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b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/__pycache__/test_unicode.cpython-312.pyc differ diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/_locales.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/_locales.py new file mode 100644 index 0000000000000000000000000000000000000000..debda9639c03c2b70312edb02ce8185de1681ffa --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/_locales.py @@ -0,0 +1,72 @@ +"""Provide class for testing in French locale + +""" +import locale +import sys + +import pytest + +__ALL__ = ['CommaDecimalPointLocale'] + + +def find_comma_decimal_point_locale(): + """See if platform has a decimal point as comma locale. + + Find a locale that uses a comma instead of a period as the + decimal point. + + Returns + ------- + old_locale: str + Locale when the function was called. + new_locale: {str, None) + First French locale found, None if none found. + + """ + if sys.platform == 'win32': + locales = ['FRENCH'] + else: + locales = ['fr_FR', 'fr_FR.UTF-8', 'fi_FI', 'fi_FI.UTF-8'] + + old_locale = locale.getlocale(locale.LC_NUMERIC) + new_locale = None + try: + for loc in locales: + try: + locale.setlocale(locale.LC_NUMERIC, loc) + new_locale = loc + break + except locale.Error: + pass + finally: + locale.setlocale(locale.LC_NUMERIC, locale=old_locale) + return old_locale, new_locale + + +class CommaDecimalPointLocale: + """Sets LC_NUMERIC to a locale with comma as decimal point. + + Classes derived from this class have setup and teardown methods that run + tests with locale.LC_NUMERIC set to a locale where commas (',') are used as + the decimal point instead of periods ('.'). On exit the locale is restored + to the initial locale. It also serves as context manager with the same + effect. If no such locale is available, the test is skipped. + + """ + (cur_locale, tst_locale) = find_comma_decimal_point_locale() + + def setup_method(self): + if self.tst_locale is None: + pytest.skip("No French locale available") + locale.setlocale(locale.LC_NUMERIC, locale=self.tst_locale) + + def teardown_method(self): + locale.setlocale(locale.LC_NUMERIC, locale=self.cur_locale) + + def __enter__(self): + if self.tst_locale is None: + pytest.skip("No French locale available") + locale.setlocale(locale.LC_NUMERIC, locale=self.tst_locale) + + def __exit__(self, type, value, traceback): + locale.setlocale(locale.LC_NUMERIC, locale=self.cur_locale) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/_natype.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/_natype.py new file mode 100644 index 0000000000000000000000000000000000000000..539dfd2b36e1090fbc564b12e442f24fe97020a2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/_natype.py @@ -0,0 +1,144 @@ +# Vendored implementation of pandas.NA, adapted from pandas/_libs/missing.pyx +# +# This is vendored to avoid adding pandas as a test dependency. + +__all__ = ["pd_NA"] + +import numbers + +import numpy as np + + +def _create_binary_propagating_op(name, is_divmod=False): + is_cmp = name.strip("_") in ["eq", "ne", "le", "lt", "ge", "gt"] + + def method(self, other): + if ( + other is pd_NA + or isinstance(other, (str, bytes, numbers.Number, np.bool)) + or (isinstance(other, np.ndarray) and not other.shape) + ): + # Need the other.shape clause to handle NumPy scalars, + # since we do a setitem on `out` below, which + # won't work for NumPy scalars. + if is_divmod: + return pd_NA, pd_NA + else: + return pd_NA + + elif isinstance(other, np.ndarray): + out = np.empty(other.shape, dtype=object) + out[:] = pd_NA + + if is_divmod: + return out, out.copy() + else: + return out + + elif is_cmp and isinstance(other, (np.datetime64, np.timedelta64)): + return pd_NA + + elif isinstance(other, np.datetime64): + if name in ["__sub__", "__rsub__"]: + return pd_NA + + elif isinstance(other, np.timedelta64): + if name in ["__sub__", "__rsub__", "__add__", "__radd__"]: + return pd_NA + + return NotImplemented + + method.__name__ = name + return method + + +def _create_unary_propagating_op(name: str): + def method(self): + return pd_NA + + method.__name__ = name + return method + + +class NAType: + def __repr__(self) -> str: + return "" + + def __format__(self, format_spec) -> str: + try: + return self.__repr__().__format__(format_spec) + except ValueError: + return self.__repr__() + + def __bool__(self): + raise TypeError("boolean value of NA is ambiguous") + + def __hash__(self): + return 2**61 - 1 + + def __reduce__(self): + return "pd_NA" + + # Binary arithmetic and comparison ops -> propagate + + __add__ = _create_binary_propagating_op("__add__") + __radd__ = _create_binary_propagating_op("__radd__") + __sub__ = _create_binary_propagating_op("__sub__") + __rsub__ = _create_binary_propagating_op("__rsub__") + __mul__ = _create_binary_propagating_op("__mul__") + __rmul__ = _create_binary_propagating_op("__rmul__") + __matmul__ = _create_binary_propagating_op("__matmul__") + __rmatmul__ = _create_binary_propagating_op("__rmatmul__") + __truediv__ = _create_binary_propagating_op("__truediv__") + __rtruediv__ = _create_binary_propagating_op("__rtruediv__") + __floordiv__ = _create_binary_propagating_op("__floordiv__") + __rfloordiv__ = _create_binary_propagating_op("__rfloordiv__") + __mod__ = _create_binary_propagating_op("__mod__") + __rmod__ = _create_binary_propagating_op("__rmod__") + __divmod__ = _create_binary_propagating_op("__divmod__", is_divmod=True) + __rdivmod__ = _create_binary_propagating_op("__rdivmod__", is_divmod=True) + # __lshift__ and __rshift__ are not implemented + + __eq__ = _create_binary_propagating_op("__eq__") + __ne__ = _create_binary_propagating_op("__ne__") + __le__ = _create_binary_propagating_op("__le__") + __lt__ = _create_binary_propagating_op("__lt__") + __gt__ = _create_binary_propagating_op("__gt__") + __ge__ = _create_binary_propagating_op("__ge__") + + # Unary ops + + __neg__ = _create_unary_propagating_op("__neg__") + __pos__ = _create_unary_propagating_op("__pos__") + __abs__ = _create_unary_propagating_op("__abs__") + __invert__ = _create_unary_propagating_op("__invert__") + + # Logical ops using Kleene logic + + def __and__(self, other): + if other is False: + return False + elif other is True or other is pd_NA: + return pd_NA + return NotImplemented + + __rand__ = __and__ + + def __or__(self, other): + if other is True: + return True + elif other is False or other is pd_NA: + return pd_NA + return NotImplemented + + __ror__ = __or__ + + def __xor__(self, other): + if other is False or other is True or other is pd_NA: + return pd_NA + return NotImplemented + + __rxor__ = __xor__ + + +pd_NA = NAType() diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test__exceptions.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test__exceptions.py new file mode 100644 index 0000000000000000000000000000000000000000..35782e7a5878c1d74207c9503aa6c81be8f07497 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test__exceptions.py @@ -0,0 +1,90 @@ +""" +Tests of the ._exceptions module. Primarily for exercising the __str__ methods. +""" + +import pickle + +import pytest + +import numpy as np +from numpy.exceptions import AxisError + +_ArrayMemoryError = np._core._exceptions._ArrayMemoryError +_UFuncNoLoopError = np._core._exceptions._UFuncNoLoopError + +class TestArrayMemoryError: + def test_pickling(self): + """ Test that _ArrayMemoryError can be pickled """ + error = _ArrayMemoryError((1023,), np.dtype(np.uint8)) + res = pickle.loads(pickle.dumps(error)) + assert res._total_size == error._total_size + + def test_str(self): + e = _ArrayMemoryError((1023,), np.dtype(np.uint8)) + str(e) # not crashing is enough + + # testing these properties is easier than testing the full string repr + def test__size_to_string(self): + """ Test e._size_to_string """ + f = _ArrayMemoryError._size_to_string + Ki = 1024 + assert f(0) == '0 bytes' + assert f(1) == '1 bytes' + assert f(1023) == '1023 bytes' + assert f(Ki) == '1.00 KiB' + assert f(Ki + 1) == '1.00 KiB' + assert f(10 * Ki) == '10.0 KiB' + assert f(int(999.4 * Ki)) == '999. KiB' + assert f(int(1023.4 * Ki)) == '1023. KiB' + assert f(int(1023.5 * Ki)) == '1.00 MiB' + assert f(Ki * Ki) == '1.00 MiB' + + # 1023.9999 Mib should round to 1 GiB + assert f(int(Ki * Ki * Ki * 0.9999)) == '1.00 GiB' + assert f(Ki * Ki * Ki * Ki * Ki * Ki) == '1.00 EiB' + # larger than sys.maxsize, adding larger prefixes isn't going to help + # anyway. + assert f(Ki * Ki * Ki * Ki * Ki * Ki * 123456) == '123456. EiB' + + def test__total_size(self): + """ Test e._total_size """ + e = _ArrayMemoryError((1,), np.dtype(np.uint8)) + assert e._total_size == 1 + + e = _ArrayMemoryError((2, 4), np.dtype((np.uint64, 16))) + assert e._total_size == 1024 + + +class TestUFuncNoLoopError: + def test_pickling(self): + """ Test that _UFuncNoLoopError can be pickled """ + assert isinstance(pickle.dumps(_UFuncNoLoopError), bytes) + + +@pytest.mark.parametrize("args", [ + (2, 1, None), + (2, 1, "test_prefix"), + ("test message",), +]) +class TestAxisError: + def test_attr(self, args): + """Validate attribute types.""" + exc = AxisError(*args) + if len(args) == 1: + assert exc.axis is None + assert exc.ndim is None + else: + axis, ndim, *_ = args + assert exc.axis == axis + assert exc.ndim == ndim + + def test_pickling(self, args): + """Test that `AxisError` can be pickled.""" + exc = AxisError(*args) + exc2 = pickle.loads(pickle.dumps(exc)) + + assert type(exc) is type(exc2) + for name in ("axis", "ndim", "args"): + attr1 = getattr(exc, name) + attr2 = getattr(exc2, name) + assert attr1 == attr2, name diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_abc.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_abc.py new file mode 100644 index 0000000000000000000000000000000000000000..aee1904f17276a420a7c5375948c0585621f78b7 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_abc.py @@ -0,0 +1,54 @@ +import numbers + +import numpy as np +from numpy._core.numerictypes import sctypes +from numpy.testing import assert_ + + +class TestABC: + def test_abstract(self): + assert_(issubclass(np.number, numbers.Number)) + + assert_(issubclass(np.inexact, numbers.Complex)) + assert_(issubclass(np.complexfloating, numbers.Complex)) + assert_(issubclass(np.floating, numbers.Real)) + + assert_(issubclass(np.integer, numbers.Integral)) + assert_(issubclass(np.signedinteger, numbers.Integral)) + assert_(issubclass(np.unsignedinteger, numbers.Integral)) + + def test_floats(self): + for t in sctypes['float']: + assert_(isinstance(t(), numbers.Real), + f"{t.__name__} is not instance of Real") + assert_(issubclass(t, numbers.Real), + f"{t.__name__} is not subclass of Real") + assert_(not isinstance(t(), numbers.Rational), + f"{t.__name__} is instance of Rational") + assert_(not issubclass(t, numbers.Rational), + f"{t.__name__} is subclass of Rational") + + def test_complex(self): + for t in sctypes['complex']: + assert_(isinstance(t(), numbers.Complex), + f"{t.__name__} is not instance of Complex") + assert_(issubclass(t, numbers.Complex), + f"{t.__name__} is not subclass of Complex") + assert_(not isinstance(t(), numbers.Real), + f"{t.__name__} is instance of Real") + assert_(not issubclass(t, numbers.Real), + f"{t.__name__} is subclass of Real") + + def test_int(self): + for t in sctypes['int']: + assert_(isinstance(t(), numbers.Integral), + f"{t.__name__} is not instance of Integral") + assert_(issubclass(t, numbers.Integral), + f"{t.__name__} is not subclass of Integral") + + def test_uint(self): + for t in sctypes['uint']: + assert_(isinstance(t(), numbers.Integral), + f"{t.__name__} is not instance of Integral") + assert_(issubclass(t, numbers.Integral), + f"{t.__name__} is not subclass of Integral") diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_api.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_api.py new file mode 100644 index 0000000000000000000000000000000000000000..216a2c75afb8418a34e928d71b057d686c61c2ba --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_api.py @@ -0,0 +1,655 @@ +import sys + +import pytest + +import numpy as np +import numpy._core.umath as ncu +from numpy._core._rational_tests import rational +from numpy.lib import stride_tricks +from numpy.testing import ( + HAS_REFCOUNT, + assert_, + assert_array_equal, + assert_equal, + assert_raises, +) + + +def test_array_array(): + tobj = type(object) + ones11 = np.ones((1, 1), np.float64) + tndarray = type(ones11) + # Test is_ndarray + assert_equal(np.array(ones11, dtype=np.float64), ones11) + if HAS_REFCOUNT: + old_refcount = sys.getrefcount(tndarray) + np.array(ones11) + assert_equal(old_refcount, sys.getrefcount(tndarray)) + + # test None + assert_equal(np.array(None, dtype=np.float64), + np.array(np.nan, dtype=np.float64)) + if HAS_REFCOUNT: + old_refcount = sys.getrefcount(tobj) + np.array(None, dtype=np.float64) + assert_equal(old_refcount, sys.getrefcount(tobj)) + + # test scalar + assert_equal(np.array(1.0, dtype=np.float64), + np.ones((), dtype=np.float64)) + if HAS_REFCOUNT: + old_refcount = sys.getrefcount(np.float64) + np.array(np.array(1.0, dtype=np.float64), dtype=np.float64) + assert_equal(old_refcount, sys.getrefcount(np.float64)) + + # test string + S2 = np.dtype((bytes, 2)) + S3 = np.dtype((bytes, 3)) + S5 = np.dtype((bytes, 5)) + assert_equal(np.array(b"1.0", dtype=np.float64), + np.ones((), dtype=np.float64)) + assert_equal(np.array(b"1.0").dtype, S3) + assert_equal(np.array(b"1.0", dtype=bytes).dtype, S3) + assert_equal(np.array(b"1.0", dtype=S2), np.array(b"1.")) + assert_equal(np.array(b"1", dtype=S5), np.ones((), dtype=S5)) + + # test string + U2 = np.dtype((str, 2)) + U3 = np.dtype((str, 3)) + U5 = np.dtype((str, 5)) + assert_equal(np.array("1.0", dtype=np.float64), + np.ones((), dtype=np.float64)) + assert_equal(np.array("1.0").dtype, U3) + assert_equal(np.array("1.0", dtype=str).dtype, U3) + assert_equal(np.array("1.0", dtype=U2), np.array("1.")) + assert_equal(np.array("1", dtype=U5), np.ones((), dtype=U5)) + + builtins = getattr(__builtins__, '__dict__', __builtins__) + assert_(hasattr(builtins, 'get')) + + # test memoryview + dat = np.array(memoryview(b'1.0'), dtype=np.float64) + assert_equal(dat, [49.0, 46.0, 48.0]) + assert_(dat.dtype.type is np.float64) + + dat = np.array(memoryview(b'1.0')) + assert_equal(dat, [49, 46, 48]) + assert_(dat.dtype.type is np.uint8) + + # test array interface + a = np.array(100.0, dtype=np.float64) + o = type("o", (object,), + {"__array_interface__": a.__array_interface__}) + assert_equal(np.array(o, dtype=np.float64), a) + + # test array_struct interface + a = np.array([(1, 4.0, 'Hello'), (2, 6.0, 'World')], + dtype=[('f0', int), ('f1', float), ('f2', str)]) + o = type("o", (object,), + {"__array_struct__": a.__array_struct__}) + # wasn't what I expected... is np.array(o) supposed to equal a ? + # instead we get an array([...], dtype=">V18") + assert_equal(bytes(np.array(o).data), bytes(a.data)) + + # test __array__ + def custom__array__(self, dtype=None, copy=None): + return np.array(100.0, dtype=dtype, copy=copy) + + o = type("o", (object,), {"__array__": custom__array__})() + assert_equal(np.array(o, dtype=np.float64), np.array(100.0, np.float64)) + + # test recursion + nested = 1.5 + for i in range(ncu.MAXDIMS): + nested = [nested] + + # no error + np.array(nested) + + # Exceeds recursion limit + assert_raises(ValueError, np.array, [nested], dtype=np.float64) + + # Try with lists... + # float32 + assert_equal(np.array([None] * 10, dtype=np.float32), + np.full((10,), np.nan, dtype=np.float32)) + assert_equal(np.array([[None]] * 10, dtype=np.float32), + np.full((10, 1), np.nan, dtype=np.float32)) + assert_equal(np.array([[None] * 10], dtype=np.float32), + np.full((1, 10), np.nan, dtype=np.float32)) + assert_equal(np.array([[None] * 10] * 10, dtype=np.float32), + np.full((10, 10), np.nan, dtype=np.float32)) + # float64 + assert_equal(np.array([None] * 10, dtype=np.float64), + np.full((10,), np.nan, dtype=np.float64)) + assert_equal(np.array([[None]] * 10, dtype=np.float64), + np.full((10, 1), np.nan, dtype=np.float64)) + assert_equal(np.array([[None] * 10], dtype=np.float64), + np.full((1, 10), np.nan, dtype=np.float64)) + assert_equal(np.array([[None] * 10] * 10, dtype=np.float64), + np.full((10, 10), np.nan, dtype=np.float64)) + + assert_equal(np.array([1.0] * 10, dtype=np.float64), + np.ones((10,), dtype=np.float64)) + assert_equal(np.array([[1.0]] * 10, dtype=np.float64), + np.ones((10, 1), dtype=np.float64)) + assert_equal(np.array([[1.0] * 10], dtype=np.float64), + np.ones((1, 10), dtype=np.float64)) + assert_equal(np.array([[1.0] * 10] * 10, dtype=np.float64), + np.ones((10, 10), dtype=np.float64)) + + # Try with tuples + assert_equal(np.array((None,) * 10, dtype=np.float64), + np.full((10,), np.nan, dtype=np.float64)) + assert_equal(np.array([(None,)] * 10, dtype=np.float64), + np.full((10, 1), np.nan, dtype=np.float64)) + assert_equal(np.array([(None,) * 10], dtype=np.float64), + np.full((1, 10), np.nan, dtype=np.float64)) + assert_equal(np.array([(None,) * 10] * 10, dtype=np.float64), + np.full((10, 10), np.nan, dtype=np.float64)) + + assert_equal(np.array((1.0,) * 10, dtype=np.float64), + np.ones((10,), dtype=np.float64)) + assert_equal(np.array([(1.0,)] * 10, dtype=np.float64), + np.ones((10, 1), dtype=np.float64)) + assert_equal(np.array([(1.0,) * 10], dtype=np.float64), + np.ones((1, 10), dtype=np.float64)) + assert_equal(np.array([(1.0,) * 10] * 10, dtype=np.float64), + np.ones((10, 10), dtype=np.float64)) + + +@pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") +def test___array___refcount(): + class MyArray: + def __init__(self, dtype): + self.val = np.array(-1, dtype=dtype) + + def __array__(self, dtype=None, copy=None): + return self.val.__array__(dtype=dtype, copy=copy) + + # test all possible scenarios: + # dtype(none | same | different) x copy(true | false | none) + dt = np.dtype(np.int32) + old_refcount = sys.getrefcount(dt) + np.array(MyArray(dt)) + assert_equal(old_refcount, sys.getrefcount(dt)) + np.array(MyArray(dt), dtype=dt) + assert_equal(old_refcount, sys.getrefcount(dt)) + np.array(MyArray(dt), copy=None) + assert_equal(old_refcount, sys.getrefcount(dt)) + np.array(MyArray(dt), dtype=dt, copy=None) + assert_equal(old_refcount, sys.getrefcount(dt)) + dt2 = np.dtype(np.int16) + old_refcount2 = sys.getrefcount(dt2) + np.array(MyArray(dt), dtype=dt2) + assert_equal(old_refcount2, sys.getrefcount(dt2)) + np.array(MyArray(dt), dtype=dt2, copy=None) + assert_equal(old_refcount2, sys.getrefcount(dt2)) + with pytest.raises(ValueError): + np.array(MyArray(dt), dtype=dt2, copy=False) + assert_equal(old_refcount2, sys.getrefcount(dt2)) + + +@pytest.mark.parametrize("array", [True, False]) +def test_array_impossible_casts(array): + # All builtin types can be forcibly cast, at least theoretically, + # but user dtypes cannot necessarily. + rt = rational(1, 2) + if array: + rt = np.array(rt) + with assert_raises(TypeError): + np.array(rt, dtype="M8") + + +def test_array_astype(): + a = np.arange(6, dtype='f4').reshape(2, 3) + # Default behavior: allows unsafe casts, keeps memory layout, + # always copies. + b = a.astype('i4') + assert_equal(a, b) + assert_equal(b.dtype, np.dtype('i4')) + assert_equal(a.strides, b.strides) + b = a.T.astype('i4') + assert_equal(a.T, b) + assert_equal(b.dtype, np.dtype('i4')) + assert_equal(a.T.strides, b.strides) + b = a.astype('f4') + assert_equal(a, b) + assert_(not (a is b)) + + # copy=False parameter skips a copy + b = a.astype('f4', copy=False) + assert_(a is b) + + # order parameter allows overriding of the memory layout, + # forcing a copy if the layout is wrong + b = a.astype('f4', order='F', copy=False) + assert_equal(a, b) + assert_(not (a is b)) + assert_(b.flags.f_contiguous) + + b = a.astype('f4', order='C', copy=False) + assert_equal(a, b) + assert_(a is b) + assert_(b.flags.c_contiguous) + + # casting parameter allows catching bad casts + b = a.astype('c8', casting='safe') + assert_equal(a, b) + assert_equal(b.dtype, np.dtype('c8')) + + assert_raises(TypeError, a.astype, 'i4', casting='safe') + + # subok=False passes through a non-subclassed array + b = a.astype('f4', subok=0, copy=False) + assert_(a is b) + + class MyNDArray(np.ndarray): + pass + + a = np.array([[0, 1, 2], [3, 4, 5]], dtype='f4').view(MyNDArray) + + # subok=True passes through a subclass + b = a.astype('f4', subok=True, copy=False) + assert_(a is b) + + # subok=True is default, and creates a subtype on a cast + b = a.astype('i4', copy=False) + assert_equal(a, b) + assert_equal(type(b), MyNDArray) + + # subok=False never returns a subclass + b = a.astype('f4', subok=False, copy=False) + assert_equal(a, b) + assert_(not (a is b)) + assert_(type(b) is not MyNDArray) + + # Make sure converting from string object to fixed length string + # does not truncate. + a = np.array([b'a' * 100], dtype='O') + b = a.astype('S') + assert_equal(a, b) + assert_equal(b.dtype, np.dtype('S100')) + a = np.array(['a' * 100], dtype='O') + b = a.astype('U') + assert_equal(a, b) + assert_equal(b.dtype, np.dtype('U100')) + + # Same test as above but for strings shorter than 64 characters + a = np.array([b'a' * 10], dtype='O') + b = a.astype('S') + assert_equal(a, b) + assert_equal(b.dtype, np.dtype('S10')) + a = np.array(['a' * 10], dtype='O') + b = a.astype('U') + assert_equal(a, b) + assert_equal(b.dtype, np.dtype('U10')) + + a = np.array(123456789012345678901234567890, dtype='O').astype('S') + assert_array_equal(a, np.array(b'1234567890' * 3, dtype='S30')) + a = np.array(123456789012345678901234567890, dtype='O').astype('U') + assert_array_equal(a, np.array('1234567890' * 3, dtype='U30')) + + a = np.array([123456789012345678901234567890], dtype='O').astype('S') + assert_array_equal(a, np.array(b'1234567890' * 3, dtype='S30')) + a = np.array([123456789012345678901234567890], dtype='O').astype('U') + assert_array_equal(a, np.array('1234567890' * 3, dtype='U30')) + + a = np.array(123456789012345678901234567890, dtype='S') + assert_array_equal(a, np.array(b'1234567890' * 3, dtype='S30')) + a = np.array(123456789012345678901234567890, dtype='U') + assert_array_equal(a, np.array('1234567890' * 3, dtype='U30')) + + a = np.array('a\u0140', dtype='U') + b = np.ndarray(buffer=a, dtype='uint32', shape=2) + assert_(b.size == 2) + + a = np.array([1000], dtype='i4') + assert_raises(TypeError, a.astype, 'S1', casting='safe') + + a = np.array(1000, dtype='i4') + assert_raises(TypeError, a.astype, 'U1', casting='safe') + + # gh-24023 + assert_raises(TypeError, a.astype) + +@pytest.mark.parametrize("dt", ["S", "U"]) +def test_array_astype_to_string_discovery_empty(dt): + # See also gh-19085 + arr = np.array([""], dtype=object) + # Note, the itemsize is the `0 -> 1` logic, which should change. + # The important part the test is rather that it does not error. + assert arr.astype(dt).dtype.itemsize == np.dtype(f"{dt}1").itemsize + + # check the same thing for `np.can_cast` (since it accepts arrays) + assert np.can_cast(arr, dt, casting="unsafe") + assert not np.can_cast(arr, dt, casting="same_kind") + # as well as for the object as a descriptor: + assert np.can_cast("O", dt, casting="unsafe") + +@pytest.mark.parametrize("dt", ["d", "f", "S13", "U32"]) +def test_array_astype_to_void(dt): + dt = np.dtype(dt) + arr = np.array([], dtype=dt) + assert arr.astype("V").dtype.itemsize == dt.itemsize + +def test_object_array_astype_to_void(): + # This is different to `test_array_astype_to_void` as object arrays + # are inspected. The default void is "V8" (8 is the length of double) + arr = np.array([], dtype="O").astype("V") + assert arr.dtype == "V8" + +@pytest.mark.parametrize("t", + np._core.sctypes['uint'] + + np._core.sctypes['int'] + + np._core.sctypes['float'] +) +def test_array_astype_warning(t): + # test ComplexWarning when casting from complex to float or int + a = np.array(10, dtype=np.complex128) + pytest.warns(np.exceptions.ComplexWarning, a.astype, t) + +@pytest.mark.parametrize(["dtype", "out_dtype"], + [(np.bytes_, np.bool), + (np.str_, np.bool), + (np.dtype("S10,S9"), np.dtype("?,?")), + # The following also checks unaligned unicode access: + (np.dtype("S7,U9"), np.dtype("?,?"))]) +def test_string_to_boolean_cast(dtype, out_dtype): + # Only the last two (empty) strings are falsy (the `\0` is stripped): + arr = np.array( + ["10", "10\0\0\0", "0\0\0", "0", "False", " ", "", "\0"], + dtype=dtype) + expected = np.array( + [True, True, True, True, True, True, False, False], + dtype=out_dtype) + assert_array_equal(arr.astype(out_dtype), expected) + # As it's similar, check that nonzero behaves the same (structs are + # nonzero if all entries are) + assert_array_equal(np.nonzero(arr), np.nonzero(expected)) + +@pytest.mark.parametrize("str_type", [str, bytes, np.str_]) +@pytest.mark.parametrize("scalar_type", + [np.complex64, np.complex128, np.clongdouble]) +def test_string_to_complex_cast(str_type, scalar_type): + value = scalar_type(b"1+3j") + assert scalar_type(value) == 1 + 3j + assert np.array([value], dtype=object).astype(scalar_type)[()] == 1 + 3j + assert np.array(value).astype(scalar_type)[()] == 1 + 3j + arr = np.zeros(1, dtype=scalar_type) + arr[0] = value + assert arr[0] == 1 + 3j + +@pytest.mark.parametrize("dtype", np.typecodes["AllFloat"]) +def test_none_to_nan_cast(dtype): + # Note that at the time of writing this test, the scalar constructors + # reject None + arr = np.zeros(1, dtype=dtype) + arr[0] = None + assert np.isnan(arr)[0] + assert np.isnan(np.array(None, dtype=dtype))[()] + assert np.isnan(np.array([None], dtype=dtype))[0] + assert np.isnan(np.array(None).astype(dtype))[()] + +def test_copyto_fromscalar(): + a = np.arange(6, dtype='f4').reshape(2, 3) + + # Simple copy + np.copyto(a, 1.5) + assert_equal(a, 1.5) + np.copyto(a.T, 2.5) + assert_equal(a, 2.5) + + # Where-masked copy + mask = np.array([[0, 1, 0], [0, 0, 1]], dtype='?') + np.copyto(a, 3.5, where=mask) + assert_equal(a, [[2.5, 3.5, 2.5], [2.5, 2.5, 3.5]]) + mask = np.array([[0, 1], [1, 1], [1, 0]], dtype='?') + np.copyto(a.T, 4.5, where=mask) + assert_equal(a, [[2.5, 4.5, 4.5], [4.5, 4.5, 3.5]]) + +def test_copyto(): + a = np.arange(6, dtype='i4').reshape(2, 3) + + # Simple copy + np.copyto(a, [[3, 1, 5], [6, 2, 1]]) + assert_equal(a, [[3, 1, 5], [6, 2, 1]]) + + # Overlapping copy should work + np.copyto(a[:, :2], a[::-1, 1::-1]) + assert_equal(a, [[2, 6, 5], [1, 3, 1]]) + + # Defaults to 'same_kind' casting + assert_raises(TypeError, np.copyto, a, 1.5) + + # Force a copy with 'unsafe' casting, truncating 1.5 to 1 + np.copyto(a, 1.5, casting='unsafe') + assert_equal(a, 1) + + # Copying with a mask + np.copyto(a, 3, where=[True, False, True]) + assert_equal(a, [[3, 1, 3], [3, 1, 3]]) + + # Casting rule still applies with a mask + assert_raises(TypeError, np.copyto, a, 3.5, where=[True, False, True]) + + # Lists of integer 0's and 1's is ok too + np.copyto(a, 4.0, casting='unsafe', where=[[0, 1, 1], [1, 0, 0]]) + assert_equal(a, [[3, 4, 4], [4, 1, 3]]) + + # Overlapping copy with mask should work + np.copyto(a[:, :2], a[::-1, 1::-1], where=[[0, 1], [1, 1]]) + assert_equal(a, [[3, 4, 4], [4, 3, 3]]) + + # 'dst' must be an array + assert_raises(TypeError, np.copyto, [1, 2, 3], [2, 3, 4]) + + +def test_copyto_cast_safety(): + with pytest.raises(TypeError): + np.copyto(np.arange(3), 3., casting="safe") + + # Can put integer and float scalars safely (and equiv): + np.copyto(np.arange(3), 3, casting="equiv") + np.copyto(np.arange(3.), 3., casting="equiv") + # And also with less precision safely: + np.copyto(np.arange(3, dtype="uint8"), 3, casting="safe") + np.copyto(np.arange(3., dtype="float32"), 3., casting="safe") + + # But not equiv: + with pytest.raises(TypeError): + np.copyto(np.arange(3, dtype="uint8"), 3, casting="equiv") + + with pytest.raises(TypeError): + np.copyto(np.arange(3., dtype="float32"), 3., casting="equiv") + + # As a special thing, object is equiv currently: + np.copyto(np.arange(3, dtype=object), 3, casting="equiv") + + # The following raises an overflow error/gives a warning but not + # type error (due to casting), though: + with pytest.raises(OverflowError): + np.copyto(np.arange(3), 2**80, casting="safe") + + with pytest.warns(RuntimeWarning): + np.copyto(np.arange(3, dtype=np.float32), 2e300, casting="safe") + + +def test_copyto_permut(): + # test explicit overflow case + pad = 500 + l = [True] * pad + [True, True, True, True] + r = np.zeros(len(l) - pad) + d = np.ones(len(l) - pad) + mask = np.array(l)[pad:] + np.copyto(r, d, where=mask[::-1]) + + # test all permutation of possible masks, 9 should be sufficient for + # current 4 byte unrolled code + power = 9 + d = np.ones(power) + for i in range(2**power): + r = np.zeros(power) + l = [(i & x) != 0 for x in range(power)] + mask = np.array(l) + np.copyto(r, d, where=mask) + assert_array_equal(r == 1, l) + assert_equal(r.sum(), sum(l)) + + r = np.zeros(power) + np.copyto(r, d, where=mask[::-1]) + assert_array_equal(r == 1, l[::-1]) + assert_equal(r.sum(), sum(l)) + + r = np.zeros(power) + np.copyto(r[::2], d[::2], where=mask[::2]) + assert_array_equal(r[::2] == 1, l[::2]) + assert_equal(r[::2].sum(), sum(l[::2])) + + r = np.zeros(power) + np.copyto(r[::2], d[::2], where=mask[::-2]) + assert_array_equal(r[::2] == 1, l[::-2]) + assert_equal(r[::2].sum(), sum(l[::-2])) + + for c in [0xFF, 0x7F, 0x02, 0x10]: + r = np.zeros(power) + mask = np.array(l) + imask = np.array(l).view(np.uint8) + imask[mask != 0] = c + np.copyto(r, d, where=mask) + assert_array_equal(r == 1, l) + assert_equal(r.sum(), sum(l)) + + r = np.zeros(power) + np.copyto(r, d, where=True) + assert_equal(r.sum(), r.size) + r = np.ones(power) + d = np.zeros(power) + np.copyto(r, d, where=False) + assert_equal(r.sum(), r.size) + +def test_copy_order(): + a = np.arange(24).reshape(2, 1, 3, 4) + b = a.copy(order='F') + c = np.arange(24).reshape(2, 1, 4, 3).swapaxes(2, 3) + + def check_copy_result(x, y, ccontig, fcontig, strides=False): + assert_(not (x is y)) + assert_equal(x, y) + assert_equal(res.flags.c_contiguous, ccontig) + assert_equal(res.flags.f_contiguous, fcontig) + + # Validate the initial state of a, b, and c + assert_(a.flags.c_contiguous) + assert_(not a.flags.f_contiguous) + assert_(not b.flags.c_contiguous) + assert_(b.flags.f_contiguous) + assert_(not c.flags.c_contiguous) + assert_(not c.flags.f_contiguous) + + # Copy with order='C' + res = a.copy(order='C') + check_copy_result(res, a, ccontig=True, fcontig=False, strides=True) + res = b.copy(order='C') + check_copy_result(res, b, ccontig=True, fcontig=False, strides=False) + res = c.copy(order='C') + check_copy_result(res, c, ccontig=True, fcontig=False, strides=False) + res = np.copy(a, order='C') + check_copy_result(res, a, ccontig=True, fcontig=False, strides=True) + res = np.copy(b, order='C') + check_copy_result(res, b, ccontig=True, fcontig=False, strides=False) + res = np.copy(c, order='C') + check_copy_result(res, c, ccontig=True, fcontig=False, strides=False) + + # Copy with order='F' + res = a.copy(order='F') + check_copy_result(res, a, ccontig=False, fcontig=True, strides=False) + res = b.copy(order='F') + check_copy_result(res, b, ccontig=False, fcontig=True, strides=True) + res = c.copy(order='F') + check_copy_result(res, c, ccontig=False, fcontig=True, strides=False) + res = np.copy(a, order='F') + check_copy_result(res, a, ccontig=False, fcontig=True, strides=False) + res = np.copy(b, order='F') + check_copy_result(res, b, ccontig=False, fcontig=True, strides=True) + res = np.copy(c, order='F') + check_copy_result(res, c, ccontig=False, fcontig=True, strides=False) + + # Copy with order='K' + res = a.copy(order='K') + check_copy_result(res, a, ccontig=True, fcontig=False, strides=True) + res = b.copy(order='K') + check_copy_result(res, b, ccontig=False, fcontig=True, strides=True) + res = c.copy(order='K') + check_copy_result(res, c, ccontig=False, fcontig=False, strides=True) + res = np.copy(a, order='K') + check_copy_result(res, a, ccontig=True, fcontig=False, strides=True) + res = np.copy(b, order='K') + check_copy_result(res, b, ccontig=False, fcontig=True, strides=True) + res = np.copy(c, order='K') + check_copy_result(res, c, ccontig=False, fcontig=False, strides=True) + +def test_contiguous_flags(): + a = np.ones((4, 4, 1))[::2, :, :] + a = stride_tricks.as_strided(a, strides=a.strides[:2] + (-123,)) + b = np.ones((2, 2, 1, 2, 2)).swapaxes(3, 4) + + def check_contig(a, ccontig, fcontig): + assert_(a.flags.c_contiguous == ccontig) + assert_(a.flags.f_contiguous == fcontig) + + # Check if new arrays are correct: + check_contig(a, False, False) + check_contig(b, False, False) + check_contig(np.empty((2, 2, 0, 2, 2)), True, True) + check_contig(np.array([[[1], [2]]], order='F'), True, True) + check_contig(np.empty((2, 2)), True, False) + check_contig(np.empty((2, 2), order='F'), False, True) + + # Check that np.array creates correct contiguous flags: + check_contig(np.array(a, copy=None), False, False) + check_contig(np.array(a, copy=None, order='C'), True, False) + check_contig(np.array(a, ndmin=4, copy=None, order='F'), False, True) + + # Check slicing update of flags and : + check_contig(a[0], True, True) + check_contig(a[None, ::4, ..., None], True, True) + check_contig(b[0, 0, ...], False, True) + check_contig(b[:, :, 0:0, :, :], True, True) + + # Test ravel and squeeze. + check_contig(a.ravel(), True, True) + check_contig(np.ones((1, 3, 1)).squeeze(), True, True) + +def test_broadcast_arrays(): + # Test user defined dtypes + dtype = 'u4,u4,u4' + a = np.array([(1, 2, 3)], dtype=dtype) + b = np.array([(1, 2, 3), (4, 5, 6), (7, 8, 9)], dtype=dtype) + result = np.broadcast_arrays(a, b) + assert_equal(result[0], np.array([(1, 2, 3), (1, 2, 3), (1, 2, 3)], dtype=dtype)) + assert_equal(result[1], np.array([(1, 2, 3), (4, 5, 6), (7, 8, 9)], dtype=dtype)) + +@pytest.mark.parametrize(["shape", "fill_value", "expected_output"], + [((2, 2), [5.0, 6.0], np.array([[5.0, 6.0], [5.0, 6.0]])), + ((3, 2), [1.0, 2.0], np.array([[1.0, 2.0], [1.0, 2.0], [1.0, 2.0]]))]) +def test_full_from_list(shape, fill_value, expected_output): + output = np.full(shape, fill_value) + assert_equal(output, expected_output) + +def test_astype_copyflag(): + # test the various copyflag options + arr = np.arange(10, dtype=np.intp) + + res_true = arr.astype(np.intp, copy=True) + assert not np.shares_memory(arr, res_true) + + res_false = arr.astype(np.intp, copy=False) + assert np.shares_memory(arr, res_false) + + res_false_float = arr.astype(np.float64, copy=False) + assert not np.shares_memory(arr, res_false_float) + + # _CopyMode enum isn't allowed + assert_raises(ValueError, arr.astype, np.float64, + copy=np._CopyMode.NEVER) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_argparse.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_argparse.py new file mode 100644 index 0000000000000000000000000000000000000000..ededced3b9fee9f8615ae49c6a8b8d38626154ae --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_argparse.py @@ -0,0 +1,90 @@ +""" +Tests for the private NumPy argument parsing functionality. +They mainly exists to ensure good test coverage without having to try the +weirder cases on actual numpy functions but test them in one place. + +The test function is defined in C to be equivalent to (errors may not always +match exactly, and could be adjusted): + + def func(arg1, /, arg2, *, arg3): + i = integer(arg1) # reproducing the 'i' parsing in Python. + return None +""" + +import threading + +import pytest + +import numpy as np +from numpy._core._multiarray_tests import ( + argparse_example_function as func, + threaded_argparse_example_function as thread_func, +) +from numpy.testing import IS_WASM + + +@pytest.mark.skipif(IS_WASM, reason="wasm doesn't have support for threads") +def test_thread_safe_argparse_cache(): + b = threading.Barrier(8) + + def call_thread_func(): + b.wait() + thread_func(arg1=3, arg2=None) + + tasks = [threading.Thread(target=call_thread_func) for _ in range(8)] + [t.start() for t in tasks] + [t.join() for t in tasks] + + +def test_invalid_integers(): + with pytest.raises(TypeError, + match="integer argument expected, got float"): + func(1.) + with pytest.raises(OverflowError): + func(2**100) + + +def test_missing_arguments(): + with pytest.raises(TypeError, + match="missing required positional argument 0"): + func() + with pytest.raises(TypeError, + match="missing required positional argument 0"): + func(arg2=1, arg3=4) + with pytest.raises(TypeError, + match=r"missing required argument \'arg2\' \(pos 1\)"): + func(1, arg3=5) + + +def test_too_many_positional(): + # the second argument is positional but can be passed as keyword. + with pytest.raises(TypeError, + match="takes from 2 to 3 positional arguments but 4 were given"): + func(1, 2, 3, 4) + + +def test_multiple_values(): + with pytest.raises(TypeError, + match=r"given by name \('arg2'\) and position \(position 1\)"): + func(1, 2, arg2=3) + + +def test_string_fallbacks(): + # We can (currently?) use numpy strings to test the "slow" fallbacks + # that should normally not be taken due to string interning. + arg2 = np.str_("arg2") + missing_arg = np.str_("missing_arg") + func(1, **{arg2: 3}) + with pytest.raises(TypeError, + match="got an unexpected keyword argument 'missing_arg'"): + func(2, **{missing_arg: 3}) + + +def test_too_many_arguments_method_forwarding(): + # Not directly related to the standard argument parsing, but we sometimes + # forward methods to Python: arr.mean() calls np._core._methods._mean() + # This adds code coverage for this `npy_forward_method`. + arr = np.arange(3) + args = range(1000) + with pytest.raises(TypeError): + arr.mean(*args) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_array_api_info.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_array_api_info.py new file mode 100644 index 0000000000000000000000000000000000000000..4842dbfa9486c1519d78980a84f9686baf104552 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_array_api_info.py @@ -0,0 +1,113 @@ +import pytest + +import numpy as np + +info = np.__array_namespace_info__() + + +def test_capabilities(): + caps = info.capabilities() + assert caps["boolean indexing"] is True + assert caps["data-dependent shapes"] is True + + # This will be added in the 2024.12 release of the array API standard. + + # assert caps["max rank"] == 64 + # np.zeros((1,)*64) + # with pytest.raises(ValueError): + # np.zeros((1,)*65) + + +def test_default_device(): + assert info.default_device() == "cpu" == np.asarray(0).device + + +def test_default_dtypes(): + dtypes = info.default_dtypes() + assert dtypes["real floating"] == np.float64 == np.asarray(0.0).dtype + assert dtypes["complex floating"] == np.complex128 == \ + np.asarray(0.0j).dtype + assert dtypes["integral"] == np.intp == np.asarray(0).dtype + assert dtypes["indexing"] == np.intp == np.argmax(np.zeros(10)).dtype + + with pytest.raises(ValueError, match="Device not understood"): + info.default_dtypes(device="gpu") + + +def test_dtypes_all(): + dtypes = info.dtypes() + assert dtypes == { + "bool": np.bool_, + "int8": np.int8, + "int16": np.int16, + "int32": np.int32, + "int64": np.int64, + "uint8": np.uint8, + "uint16": np.uint16, + "uint32": np.uint32, + "uint64": np.uint64, + "float32": np.float32, + "float64": np.float64, + "complex64": np.complex64, + "complex128": np.complex128, + } + + +dtype_categories = { + "bool": {"bool": np.bool_}, + "signed integer": { + "int8": np.int8, + "int16": np.int16, + "int32": np.int32, + "int64": np.int64, + }, + "unsigned integer": { + "uint8": np.uint8, + "uint16": np.uint16, + "uint32": np.uint32, + "uint64": np.uint64, + }, + "integral": ("signed integer", "unsigned integer"), + "real floating": {"float32": np.float32, "float64": np.float64}, + "complex floating": {"complex64": np.complex64, "complex128": + np.complex128}, + "numeric": ("integral", "real floating", "complex floating"), +} + + +@pytest.mark.parametrize("kind", dtype_categories) +def test_dtypes_kind(kind): + expected = dtype_categories[kind] + if isinstance(expected, tuple): + assert info.dtypes(kind=kind) == info.dtypes(kind=expected) + else: + assert info.dtypes(kind=kind) == expected + + +def test_dtypes_tuple(): + dtypes = info.dtypes(kind=("bool", "integral")) + assert dtypes == { + "bool": np.bool_, + "int8": np.int8, + "int16": np.int16, + "int32": np.int32, + "int64": np.int64, + "uint8": np.uint8, + "uint16": np.uint16, + "uint32": np.uint32, + "uint64": np.uint64, + } + + +def test_dtypes_invalid_kind(): + with pytest.raises(ValueError, match="unsupported kind"): + info.dtypes(kind="invalid") + + +def test_dtypes_invalid_device(): + with pytest.raises(ValueError, match="Device not understood"): + info.dtypes(device="gpu") + + +def test_devices(): + assert info.devices() == ["cpu"] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_array_coercion.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_array_coercion.py new file mode 100644 index 0000000000000000000000000000000000000000..ba28e886282f2c7b63058bb60543a88a8ca19f1b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_array_coercion.py @@ -0,0 +1,928 @@ +""" +Tests for array coercion, mainly through testing `np.array` results directly. +Note that other such tests exist, e.g., in `test_api.py` and many corner-cases +are tested (sometimes indirectly) elsewhere. +""" + +from itertools import permutations, product + +import pytest +from pytest import param + +import numpy as np +import numpy._core._multiarray_umath as ncu +from numpy._core._rational_tests import rational +from numpy.testing import IS_64BIT, IS_PYPY, assert_array_equal + + +def arraylikes(): + """ + Generator for functions converting an array into various array-likes. + If full is True (default) it includes array-likes not capable of handling + all dtypes. + """ + # base array: + def ndarray(a): + return a + + yield param(ndarray, id="ndarray") + + # subclass: + class MyArr(np.ndarray): + pass + + def subclass(a): + return a.view(MyArr) + + yield subclass + + class _SequenceLike: + # Older NumPy versions, sometimes cared whether a protocol array was + # also _SequenceLike. This shouldn't matter, but keep it for now + # for __array__ and not the others. + def __len__(self): + raise TypeError + + def __getitem__(self, _, /): + raise TypeError + + # Array-interface + class ArrayDunder(_SequenceLike): + def __init__(self, a): + self.a = a + + def __array__(self, dtype=None, copy=None): + if dtype is None: + return self.a + return self.a.astype(dtype) + + yield param(ArrayDunder, id="__array__") + + # memory-view + yield param(memoryview, id="memoryview") + + # Array-interface + class ArrayInterface: + def __init__(self, a): + self.a = a # need to hold on to keep interface valid + self.__array_interface__ = a.__array_interface__ + + yield param(ArrayInterface, id="__array_interface__") + + # Array-Struct + class ArrayStruct: + def __init__(self, a): + self.a = a # need to hold on to keep struct valid + self.__array_struct__ = a.__array_struct__ + + yield param(ArrayStruct, id="__array_struct__") + + +def scalar_instances(times=True, extended_precision=True, user_dtype=True): + # Hard-coded list of scalar instances. + # Floats: + yield param(np.sqrt(np.float16(5)), id="float16") + yield param(np.sqrt(np.float32(5)), id="float32") + yield param(np.sqrt(np.float64(5)), id="float64") + if extended_precision: + yield param(np.sqrt(np.longdouble(5)), id="longdouble") + + # Complex: + yield param(np.sqrt(np.complex64(2 + 3j)), id="complex64") + yield param(np.sqrt(np.complex128(2 + 3j)), id="complex128") + if extended_precision: + yield param(np.sqrt(np.clongdouble(2 + 3j)), id="clongdouble") + + # Bool: + # XFAIL: Bool should be added, but has some bad properties when it + # comes to strings, see also gh-9875 + # yield param(np.bool(0), id="bool") + + # Integers: + yield param(np.int8(2), id="int8") + yield param(np.int16(2), id="int16") + yield param(np.int32(2), id="int32") + yield param(np.int64(2), id="int64") + + yield param(np.uint8(2), id="uint8") + yield param(np.uint16(2), id="uint16") + yield param(np.uint32(2), id="uint32") + yield param(np.uint64(2), id="uint64") + + # Rational: + if user_dtype: + yield param(rational(1, 2), id="rational") + + # Cannot create a structured void scalar directly: + structured = np.array([(1, 3)], "i,i")[0] + assert isinstance(structured, np.void) + assert structured.dtype == np.dtype("i,i") + yield param(structured, id="structured") + + if times: + # Datetimes and timedelta + yield param(np.timedelta64(2), id="timedelta64[generic]") + yield param(np.timedelta64(23, "s"), id="timedelta64[s]") + yield param(np.timedelta64("NaT", "s"), id="timedelta64[s](NaT)") + + yield param(np.datetime64("NaT"), id="datetime64[generic](NaT)") + yield param(np.datetime64("2020-06-07 12:43", "ms"), id="datetime64[ms]") + + # Strings and unstructured void: + yield param(np.bytes_(b"1234"), id="bytes") + yield param(np.str_("2345"), id="unicode") + yield param(np.void(b"4321"), id="unstructured_void") + + +def is_parametric_dtype(dtype): + """Returns True if the dtype is a parametric legacy dtype (itemsize + is 0, or a datetime without units) + """ + if dtype.itemsize == 0: + return True + if issubclass(dtype.type, (np.datetime64, np.timedelta64)): + if dtype.name.endswith("64"): + # Generic time units + return True + return False + + +class TestStringDiscovery: + @pytest.mark.parametrize("obj", + [object(), 1.2, 10**43, None, "string"], + ids=["object", "1.2", "10**43", "None", "string"]) + def test_basic_stringlength(self, obj): + length = len(str(obj)) + expected = np.dtype(f"S{length}") + + assert np.array(obj, dtype="S").dtype == expected + assert np.array([obj], dtype="S").dtype == expected + + # A nested array is also discovered correctly + arr = np.array(obj, dtype="O") + assert np.array(arr, dtype="S").dtype == expected + # Also if we use the dtype class + assert np.array(arr, dtype=type(expected)).dtype == expected + # Check that .astype() behaves identical + assert arr.astype("S").dtype == expected + # The DType class is accepted by `.astype()` + assert arr.astype(type(np.dtype("S"))).dtype == expected + + @pytest.mark.parametrize("obj", + [object(), 1.2, 10**43, None, "string"], + ids=["object", "1.2", "10**43", "None", "string"]) + def test_nested_arrays_stringlength(self, obj): + length = len(str(obj)) + expected = np.dtype(f"S{length}") + arr = np.array(obj, dtype="O") + assert np.array([arr, arr], dtype="S").dtype == expected + + @pytest.mark.parametrize("arraylike", arraylikes()) + def test_unpack_first_level(self, arraylike): + # We unpack exactly one level of array likes + obj = np.array([None]) + obj[0] = np.array(1.2) + # the length of the included item, not of the float dtype + length = len(str(obj[0])) + expected = np.dtype(f"S{length}") + + obj = arraylike(obj) + # casting to string usually calls str(obj) + arr = np.array([obj], dtype="S") + assert arr.shape == (1, 1) + assert arr.dtype == expected + + +class TestScalarDiscovery: + def test_void_special_case(self): + # Void dtypes with structures discover tuples as elements + arr = np.array((1, 2, 3), dtype="i,i,i") + assert arr.shape == () + arr = np.array([(1, 2, 3)], dtype="i,i,i") + assert arr.shape == (1,) + + def test_char_special_case(self): + arr = np.array("string", dtype="c") + assert arr.shape == (6,) + assert arr.dtype.char == "c" + arr = np.array(["string"], dtype="c") + assert arr.shape == (1, 6) + assert arr.dtype.char == "c" + + def test_char_special_case_deep(self): + # Check that the character special case errors correctly if the + # array is too deep: + nested = ["string"] # 2 dimensions (due to string being sequence) + for i in range(ncu.MAXDIMS - 2): + nested = [nested] + + arr = np.array(nested, dtype='c') + assert arr.shape == (1,) * (ncu.MAXDIMS - 1) + (6,) + with pytest.raises(ValueError): + np.array([nested], dtype="c") + + def test_unknown_object(self): + arr = np.array(object()) + assert arr.shape == () + assert arr.dtype == np.dtype("O") + + @pytest.mark.parametrize("scalar", scalar_instances()) + def test_scalar(self, scalar): + arr = np.array(scalar) + assert arr.shape == () + assert arr.dtype == scalar.dtype + + arr = np.array([[scalar, scalar]]) + assert arr.shape == (1, 2) + assert arr.dtype == scalar.dtype + + # Additionally to string this test also runs into a corner case + # with datetime promotion (the difference is the promotion order). + @pytest.mark.filterwarnings("ignore:Promotion of numbers:FutureWarning") + def test_scalar_promotion(self): + for sc1, sc2 in product(scalar_instances(), scalar_instances()): + sc1, sc2 = sc1.values[0], sc2.values[0] + # test all combinations: + try: + arr = np.array([sc1, sc2]) + except (TypeError, ValueError): + # The promotion between two times can fail + # XFAIL (ValueError): Some object casts are currently undefined + continue + assert arr.shape == (2,) + try: + dt1, dt2 = sc1.dtype, sc2.dtype + expected_dtype = np.promote_types(dt1, dt2) + assert arr.dtype == expected_dtype + except TypeError as e: + # Will currently always go to object dtype + assert arr.dtype == np.dtype("O") + + @pytest.mark.parametrize("scalar", scalar_instances()) + def test_scalar_coercion(self, scalar): + # This tests various scalar coercion paths, mainly for the numerical + # types. It includes some paths not directly related to `np.array`. + if isinstance(scalar, np.inexact): + # Ensure we have a full-precision number if available + scalar = type(scalar)((scalar * 2)**0.5) + + # Use casting from object: + arr = np.array(scalar, dtype=object).astype(scalar.dtype) + + # Test various ways to create an array containing this scalar: + arr1 = np.array(scalar).reshape(1) + arr2 = np.array([scalar]) + arr3 = np.empty(1, dtype=scalar.dtype) + arr3[0] = scalar + arr4 = np.empty(1, dtype=scalar.dtype) + arr4[:] = [scalar] + # All of these methods should yield the same results + assert_array_equal(arr, arr1) + assert_array_equal(arr, arr2) + assert_array_equal(arr, arr3) + assert_array_equal(arr, arr4) + + @pytest.mark.xfail(IS_PYPY, reason="`int(np.complex128(3))` fails on PyPy") + @pytest.mark.filterwarnings("ignore::numpy.exceptions.ComplexWarning") + @pytest.mark.parametrize("cast_to", scalar_instances()) + def test_scalar_coercion_same_as_cast_and_assignment(self, cast_to): + """ + Test that in most cases: + * `np.array(scalar, dtype=dtype)` + * `np.empty((), dtype=dtype)[()] = scalar` + * `np.array(scalar).astype(dtype)` + should behave the same. The only exceptions are parametric dtypes + (mainly datetime/timedelta without unit) and void without fields. + """ + dtype = cast_to.dtype # use to parametrize only the target dtype + + for scalar in scalar_instances(times=False): + scalar = scalar.values[0] + + if dtype.type == np.void: + if scalar.dtype.fields is not None and dtype.fields is None: + # Here, coercion to "V6" works, but the cast fails. + # Since the types are identical, SETITEM takes care of + # this, but has different rules than the cast. + with pytest.raises(TypeError): + np.array(scalar).astype(dtype) + np.array(scalar, dtype=dtype) + np.array([scalar], dtype=dtype) + continue + + # The main test, we first try to use casting and if it succeeds + # continue below testing that things are the same, otherwise + # test that the alternative paths at least also fail. + try: + cast = np.array(scalar).astype(dtype) + except (TypeError, ValueError, RuntimeError): + # coercion should also raise (error type may change) + with pytest.raises(Exception): # noqa: B017 + np.array(scalar, dtype=dtype) + + if (isinstance(scalar, rational) and + np.issubdtype(dtype, np.signedinteger)): + return + + with pytest.raises(Exception): # noqa: B017 + np.array([scalar], dtype=dtype) + # assignment should also raise + res = np.zeros((), dtype=dtype) + with pytest.raises(Exception): # noqa: B017 + res[()] = scalar + + return + + # Non error path: + arr = np.array(scalar, dtype=dtype) + assert_array_equal(arr, cast) + # assignment behaves the same + ass = np.zeros((), dtype=dtype) + ass[()] = scalar + assert_array_equal(ass, cast) + + @pytest.mark.parametrize("pyscalar", [10, 10.32, 10.14j, 10**100]) + def test_pyscalar_subclasses(self, pyscalar): + """NumPy arrays are read/write which means that anything but invariant + behaviour is on thin ice. However, we currently are happy to discover + subclasses of Python float, int, complex the same as the base classes. + This should potentially be deprecated. + """ + class MyScalar(type(pyscalar)): + pass + + res = np.array(MyScalar(pyscalar)) + expected = np.array(pyscalar) + assert_array_equal(res, expected) + + @pytest.mark.parametrize("dtype_char", np.typecodes["All"]) + def test_default_dtype_instance(self, dtype_char): + if dtype_char in "SU": + dtype = np.dtype(dtype_char + "1") + elif dtype_char == "V": + # Legacy behaviour was to use V8. The reason was float64 being the + # default dtype and that having 8 bytes. + dtype = np.dtype("V8") + else: + dtype = np.dtype(dtype_char) + + discovered_dtype, _ = ncu._discover_array_parameters([], type(dtype)) + + assert discovered_dtype == dtype + assert discovered_dtype.itemsize == dtype.itemsize + + @pytest.mark.parametrize("dtype", np.typecodes["Integer"]) + @pytest.mark.parametrize(["scalar", "error"], + [(np.float64(np.nan), ValueError), + (np.array(-1).astype(np.ulonglong)[()], OverflowError)]) + def test_scalar_to_int_coerce_does_not_cast(self, dtype, scalar, error): + """ + Signed integers are currently different in that they do not cast other + NumPy scalar, but instead use scalar.__int__(). The hardcoded + exception to this rule is `np.array(scalar, dtype=integer)`. + """ + dtype = np.dtype(dtype) + + # This is a special case using casting logic. It warns for the NaN + # but allows the cast (giving undefined behaviour). + with np.errstate(invalid="ignore"): + coerced = np.array(scalar, dtype=dtype) + cast = np.array(scalar).astype(dtype) + assert_array_equal(coerced, cast) + + # However these fail: + with pytest.raises(error): + np.array([scalar], dtype=dtype) + with pytest.raises(error): + cast[()] = scalar + + +class TestTimeScalars: + @pytest.mark.parametrize("dtype", [np.int64, np.float32]) + @pytest.mark.parametrize("scalar", + [param(np.timedelta64("NaT", "s"), id="timedelta64[s](NaT)"), + param(np.timedelta64(123, "s"), id="timedelta64[s]"), + param(np.datetime64("NaT", "generic"), id="datetime64[generic](NaT)"), + param(np.datetime64(1, "D"), id="datetime64[D]")],) + def test_coercion_basic(self, dtype, scalar): + # Note the `[scalar]` is there because np.array(scalar) uses stricter + # `scalar.__int__()` rules for backward compatibility right now. + arr = np.array(scalar, dtype=dtype) + cast = np.array(scalar).astype(dtype) + assert_array_equal(arr, cast) + + ass = np.ones((), dtype=dtype) + if issubclass(dtype, np.integer): + with pytest.raises(TypeError): + # raises, as would np.array([scalar], dtype=dtype), this is + # conversion from times, but behaviour of integers. + ass[()] = scalar + else: + ass[()] = scalar + assert_array_equal(ass, cast) + + @pytest.mark.parametrize("dtype", [np.int64, np.float32]) + @pytest.mark.parametrize("scalar", + [param(np.timedelta64(123, "ns"), id="timedelta64[ns]"), + param(np.timedelta64(12, "generic"), id="timedelta64[generic]")]) + def test_coercion_timedelta_convert_to_number(self, dtype, scalar): + # Only "ns" and "generic" timedeltas can be converted to numbers + # so these are slightly special. + arr = np.array(scalar, dtype=dtype) + cast = np.array(scalar).astype(dtype) + ass = np.ones((), dtype=dtype) + ass[()] = scalar # raises, as would np.array([scalar], dtype=dtype) + + assert_array_equal(arr, cast) + assert_array_equal(cast, cast) + + @pytest.mark.parametrize("dtype", ["S6", "U6"]) + @pytest.mark.parametrize(["val", "unit"], + [param(123, "s", id="[s]"), param(123, "D", id="[D]")]) + def test_coercion_assignment_datetime(self, val, unit, dtype): + # String from datetime64 assignment is currently special cased to + # never use casting. This is because casting will error in this + # case, and traditionally in most cases the behaviour is maintained + # like this. (`np.array(scalar, dtype="U6")` would have failed before) + # TODO: This discrepancy _should_ be resolved, either by relaxing the + # cast, or by deprecating the first part. + scalar = np.datetime64(val, unit) + dtype = np.dtype(dtype) + cut_string = dtype.type(str(scalar)[:6]) + + arr = np.array(scalar, dtype=dtype) + assert arr[()] == cut_string + ass = np.ones((), dtype=dtype) + ass[()] = scalar + assert ass[()] == cut_string + + with pytest.raises(RuntimeError): + # However, unlike the above assignment using `str(scalar)[:6]` + # due to being handled by the string DType and not be casting + # the explicit cast fails: + np.array(scalar).astype(dtype) + + @pytest.mark.parametrize(["val", "unit"], + [param(123, "s", id="[s]"), param(123, "D", id="[D]")]) + def test_coercion_assignment_timedelta(self, val, unit): + scalar = np.timedelta64(val, unit) + + # Unlike datetime64, timedelta allows the unsafe cast: + np.array(scalar, dtype="S6") + cast = np.array(scalar).astype("S6") + ass = np.ones((), dtype="S6") + ass[()] = scalar + expected = scalar.astype("S")[:6] + assert cast[()] == expected + assert ass[()] == expected + +class TestNested: + def test_nested_simple(self): + initial = [1.2] + nested = initial + for i in range(ncu.MAXDIMS - 1): + nested = [nested] + + arr = np.array(nested, dtype="float64") + assert arr.shape == (1,) * ncu.MAXDIMS + with pytest.raises(ValueError): + np.array([nested], dtype="float64") + + with pytest.raises(ValueError, match=".*would exceed the maximum"): + np.array([nested]) # user must ask for `object` explicitly + + arr = np.array([nested], dtype=object) + assert arr.dtype == np.dtype("O") + assert arr.shape == (1,) * ncu.MAXDIMS + assert arr.item() is initial + + def test_pathological_self_containing(self): + # Test that this also works for two nested sequences + l = [] + l.append(l) + arr = np.array([l, l, l], dtype=object) + assert arr.shape == (3,) + (1,) * (ncu.MAXDIMS - 1) + + # Also check a ragged case: + arr = np.array([l, [None], l], dtype=object) + assert arr.shape == (3, 1) + + @pytest.mark.parametrize("arraylike", arraylikes()) + def test_nested_arraylikes(self, arraylike): + # We try storing an array like into an array, but the array-like + # will have too many dimensions. This means the shape discovery + # decides that the array-like must be treated as an object (a special + # case of ragged discovery). The result will be an array with one + # dimension less than the maximum dimensions, and the array being + # assigned to it (which does work for object or if `float(arraylike)` + # works). + initial = arraylike(np.ones((1, 1))) + + nested = initial + for i in range(ncu.MAXDIMS - 1): + nested = [nested] + + with pytest.raises(ValueError, match=".*would exceed the maximum"): + # It will refuse to assign the array into + np.array(nested, dtype="float64") + + # If this is object, we end up assigning a (1, 1) array into (1,) + # (due to running out of dimensions), this is currently supported but + # a special case which is not ideal. + arr = np.array(nested, dtype=object) + assert arr.shape == (1,) * ncu.MAXDIMS + assert arr.item() == np.array(initial).item() + + @pytest.mark.parametrize("arraylike", arraylikes()) + def test_uneven_depth_ragged(self, arraylike): + arr = np.arange(4).reshape((2, 2)) + arr = arraylike(arr) + + # Array is ragged in the second dimension already: + out = np.array([arr, [arr]], dtype=object) + assert out.shape == (2,) + assert out[0] is arr + assert type(out[1]) is list + + # Array is ragged in the third dimension: + with pytest.raises(ValueError): + # This is a broadcast error during assignment, because + # the array shape would be (2, 2, 2) but `arr[0, 0] = arr` fails. + np.array([arr, [arr, arr]], dtype=object) + + def test_empty_sequence(self): + arr = np.array([[], [1], [[1]]], dtype=object) + assert arr.shape == (3,) + + # The empty sequence stops further dimension discovery, so the + # result shape will be (0,) which leads to an error during: + with pytest.raises(ValueError): + np.array([[], np.empty((0, 1))], dtype=object) + + def test_array_of_different_depths(self): + # When multiple arrays (or array-likes) are included in a + # sequences and have different depth, we currently discover + # as many dimensions as they share. (see also gh-17224) + arr = np.zeros((3, 2)) + mismatch_first_dim = np.zeros((1, 2)) + mismatch_second_dim = np.zeros((3, 3)) + + dtype, shape = ncu._discover_array_parameters( + [arr, mismatch_second_dim], dtype=np.dtype("O")) + assert shape == (2, 3) + + dtype, shape = ncu._discover_array_parameters( + [arr, mismatch_first_dim], dtype=np.dtype("O")) + assert shape == (2,) + # The second case is currently supported because the arrays + # can be stored as objects: + res = np.asarray([arr, mismatch_first_dim], dtype=np.dtype("O")) + assert res[0] is arr + assert res[1] is mismatch_first_dim + + +class TestBadSequences: + # These are tests for bad objects passed into `np.array`, in general + # these have undefined behaviour. In the old code they partially worked + # when now they will fail. We could (and maybe should) create a copy + # of all sequences to be safe against bad-actors. + + def test_growing_list(self): + # List to coerce, `mylist` will append to it during coercion + obj = [] + + class mylist(list): + def __len__(self): + obj.append([1, 2]) + return super().__len__() + + obj.append(mylist([1, 2])) + + with pytest.raises(RuntimeError): + np.array(obj) + + # Note: We do not test a shrinking list. These do very evil things + # and the only way to fix them would be to copy all sequences. + # (which may be a real option in the future). + + def test_mutated_list(self): + # List to coerce, `mylist` will mutate the first element + obj = [] + + class mylist(list): + def __len__(self): + obj[0] = [2, 3] # replace with a different list. + return super().__len__() + + obj.append([2, 3]) + obj.append(mylist([1, 2])) + # Does not crash: + np.array(obj) + + def test_replace_0d_array(self): + # List to coerce, `mylist` will mutate the first element + obj = [] + + class baditem: + def __len__(self): + obj[0][0] = 2 # replace with a different list. + raise ValueError("not actually a sequence!") + + def __getitem__(self, _, /): + pass + + # Runs into a corner case in the new code, the `array(2)` is cached + # so replacing it invalidates the cache. + obj.append([np.array(2), baditem()]) + with pytest.raises(RuntimeError): + np.array(obj) + + +class TestArrayLikes: + @pytest.mark.parametrize("arraylike", arraylikes()) + def test_0d_object_special_case(self, arraylike): + arr = np.array(0.) + obj = arraylike(arr) + # A single array-like is always converted: + res = np.array(obj, dtype=object) + assert_array_equal(arr, res) + + # But a single 0-D nested array-like never: + res = np.array([obj], dtype=object) + assert res[0] is obj + + @pytest.mark.parametrize("arraylike", arraylikes()) + @pytest.mark.parametrize("arr", [np.array(0.), np.arange(4)]) + def test_object_assignment_special_case(self, arraylike, arr): + obj = arraylike(arr) + empty = np.arange(1, dtype=object) + empty[:] = [obj] + assert empty[0] is obj + + def test_0d_generic_special_case(self): + class ArraySubclass(np.ndarray): + def __float__(self): + raise TypeError("e.g. quantities raise on this") + + arr = np.array(0.) + obj = arr.view(ArraySubclass) + res = np.array(obj) + # The subclass is simply cast: + assert_array_equal(arr, res) + + # If the 0-D array-like is included, __float__ is currently + # guaranteed to be used. We may want to change that, quantities + # and masked arrays half make use of this. + with pytest.raises(TypeError): + np.array([obj]) + + # The same holds for memoryview: + obj = memoryview(arr) + res = np.array(obj) + assert_array_equal(arr, res) + with pytest.raises(ValueError): + # The error type does not matter much here. + np.array([obj]) + + def test_arraylike_classes(self): + # The classes of array-likes should generally be acceptable to be + # stored inside a numpy (object) array. This tests all of the + # special attributes (since all are checked during coercion). + arr = np.array(np.int64) + assert arr[()] is np.int64 + arr = np.array([np.int64]) + assert arr[0] is np.int64 + + # This also works for properties/unbound methods: + class ArrayLike: + @property + def __array_interface__(self): + pass + + @property + def __array_struct__(self): + pass + + def __array__(self, dtype=None, copy=None): + pass + + arr = np.array(ArrayLike) + assert arr[()] is ArrayLike + arr = np.array([ArrayLike]) + assert arr[0] is ArrayLike + + @pytest.mark.skipif(not IS_64BIT, reason="Needs 64bit platform") + @pytest.mark.thread_unsafe(reason="large slow test in parallel") + def test_too_large_array_error_paths(self): + """Test the error paths, including for memory leaks""" + arr = np.array(0, dtype="uint8") + # Guarantees that a contiguous copy won't work: + arr = np.broadcast_to(arr, 2**62) + + for i in range(5): + # repeat, to ensure caching cannot have an effect: + with pytest.raises(MemoryError): + np.array(arr) + with pytest.raises(MemoryError): + np.array([arr]) + + @pytest.mark.parametrize("attribute", + ["__array_interface__", "__array__", "__array_struct__"]) + @pytest.mark.parametrize("error", [RecursionError, MemoryError]) + def test_bad_array_like_attributes(self, attribute, error): + # RecursionError and MemoryError are considered fatal. All errors + # (except AttributeError) should probably be raised in the future, + # but shapely made use of it, so it will require a deprecation. + + class BadInterface: + def __getattr__(self, attr): + if attr == attribute: + raise error + super().__getattr__(attr) + + with pytest.raises(error): + np.array(BadInterface()) + + @pytest.mark.parametrize("error", [RecursionError, MemoryError]) + def test_bad_array_like_bad_length(self, error): + # RecursionError and MemoryError are considered "critical" in + # sequences. We could expand this more generally though. (NumPy 1.20) + class BadSequence: + def __len__(self): + raise error + + def __getitem__(self, _, /): + # must have getitem to be a Sequence + return 1 + + with pytest.raises(error): + np.array(BadSequence()) + + def test_array_interface_descr_optional(self): + # The descr should be optional regression test for gh-27249 + arr = np.ones(10, dtype="V10") + iface = arr.__array_interface__ + iface.pop("descr") + + class MyClass: + __array_interface__ = iface + + assert_array_equal(np.asarray(MyClass), arr) + + +class TestAsArray: + """Test expected behaviors of ``asarray``.""" + + def test_dtype_identity(self): + """Confirm the intended behavior for *dtype* kwarg. + + The result of ``asarray()`` should have the dtype provided through the + keyword argument, when used. This forces unique array handles to be + produced for unique np.dtype objects, but (for equivalent dtypes), the + underlying data (the base object) is shared with the original array + object. + + Ref https://github.com/numpy/numpy/issues/1468 + """ + int_array = np.array([1, 2, 3], dtype='i') + assert np.asarray(int_array) is int_array + + # The character code resolves to the singleton dtype object provided + # by the numpy package. + assert np.asarray(int_array, dtype='i') is int_array + + # Derive a dtype from n.dtype('i'), but add a metadata object to force + # the dtype to be distinct. + unequal_type = np.dtype('i', metadata={'spam': True}) + annotated_int_array = np.asarray(int_array, dtype=unequal_type) + assert annotated_int_array is not int_array + assert annotated_int_array.base is int_array + # Create an equivalent descriptor with a new and distinct dtype + # instance. + equivalent_requirement = np.dtype('i', metadata={'spam': True}) + annotated_int_array_alt = np.asarray(annotated_int_array, + dtype=equivalent_requirement) + assert unequal_type == equivalent_requirement + assert unequal_type is not equivalent_requirement + assert annotated_int_array_alt is not annotated_int_array + assert annotated_int_array_alt.dtype is equivalent_requirement + + # Check the same logic for a pair of C types whose equivalence may vary + # between computing environments. + # Find an equivalent pair. + integer_type_codes = ('i', 'l', 'q') + integer_dtypes = [np.dtype(code) for code in integer_type_codes] + typeA = None + typeB = None + for typeA, typeB in permutations(integer_dtypes, r=2): + if typeA == typeB: + assert typeA is not typeB + break + assert isinstance(typeA, np.dtype) and isinstance(typeB, np.dtype) + + # These ``asarray()`` calls may produce a new view or a copy, + # but never the same object. + long_int_array = np.asarray(int_array, dtype='l') + long_long_int_array = np.asarray(int_array, dtype='q') + assert long_int_array is not int_array + assert long_long_int_array is not int_array + assert np.asarray(long_int_array, dtype='q') is not long_int_array + array_a = np.asarray(int_array, dtype=typeA) + assert typeA == typeB + assert typeA is not typeB + assert array_a.dtype is typeA + assert array_a is not np.asarray(array_a, dtype=typeB) + assert np.asarray(array_a, dtype=typeB).dtype is typeB + assert array_a is np.asarray(array_a, dtype=typeB).base + + +class TestSpecialAttributeLookupFailure: + # An exception was raised while fetching the attribute + + class WeirdArrayLike: + @property + def __array__(self, dtype=None, copy=None): # noqa: PLR0206 + raise RuntimeError("oops!") + + class WeirdArrayInterface: + @property + def __array_interface__(self): + raise RuntimeError("oops!") + + def test_deprecated(self): + with pytest.raises(RuntimeError): + np.array(self.WeirdArrayLike()) + with pytest.raises(RuntimeError): + np.array(self.WeirdArrayInterface()) + + +def test_subarray_from_array_construction(): + # Arrays are more complex, since they "broadcast" on success: + arr = np.array([1, 2]) + + res = arr.astype("2i") + assert_array_equal(res, [[1, 1], [2, 2]]) + + res = np.array(arr, dtype="(2,)i") + + assert_array_equal(res, [[1, 1], [2, 2]]) + + res = np.array([[(1,), (2,)], arr], dtype="2i") + assert_array_equal(res, [[[1, 1], [2, 2]], [[1, 1], [2, 2]]]) + + # Also try a multi-dimensional example: + arr = np.arange(5 * 2).reshape(5, 2) + expected = np.broadcast_to(arr[:, :, np.newaxis, np.newaxis], (5, 2, 2, 2)) + + res = arr.astype("(2,2)f") + assert_array_equal(res, expected) + + res = np.array(arr, dtype="(2,2)f") + assert_array_equal(res, expected) + + +def test_empty_string(): + # Empty strings are unfortunately often converted to S1 and we need to + # make sure we are filling the S1 and not the (possibly) detected S0 + # result. This should likely just return S0 and if not maybe the decision + # to return S1 should be moved. + res = np.array([""] * 10, dtype="S") + assert_array_equal(res, np.array("\0", "S1")) + assert res.dtype == "S1" + + arr = np.array([""] * 10, dtype=object) + + res = arr.astype("S") + assert_array_equal(res, b"") + assert res.dtype == "S1" + + res = np.array(arr, dtype="S") + assert_array_equal(res, b"") + # TODO: This is arguably weird/wrong, but seems old: + assert res.dtype == f"S{np.dtype('O').itemsize}" + + res = np.array([[""] * 10, arr], dtype="S") + assert_array_equal(res, b"") + assert res.shape == (2, 10) + assert res.dtype == "S1" + + +@pytest.mark.parametrize("dtype", ["S", "U", object]) +@pytest.mark.parametrize("res_dt,hug_val", + [("float16", "1e30"), ("float32", "1e200")]) +def test_string_to_float_coercion_errors(dtype, res_dt, hug_val): + # This test primarly tests setitem + val = np.array(["3M"], dtype=dtype)[0] # use the scalar + + with pytest.raises(ValueError): + np.array(val, dtype=res_dt) + + val = np.array([hug_val], dtype=dtype)[0] # use the scalar + + with np.errstate(all="warn"): + with pytest.warns(RuntimeWarning): + np.array(val, dtype=res_dt) + + with np.errstate(all="raise"): + with pytest.raises(FloatingPointError): + np.array(val, dtype=res_dt) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_array_interface.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_array_interface.py new file mode 100644 index 0000000000000000000000000000000000000000..afb19f4e280fb2b228f6f6e5eac4a10f02412e94 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_array_interface.py @@ -0,0 +1,222 @@ +import sys +import sysconfig + +import pytest + +import numpy as np +from numpy.testing import IS_EDITABLE, IS_WASM, extbuild + + +@pytest.fixture +def get_module(tmp_path): + """ Some codes to generate data and manage temporary buffers use when + sharing with numpy via the array interface protocol. + """ + if sys.platform.startswith('cygwin'): + pytest.skip('link fails on cygwin') + if IS_WASM: + pytest.skip("Can't build module inside Wasm") + if IS_EDITABLE: + pytest.skip("Can't build module for editable install") + + prologue = ''' + #include + #define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION + #include + #include + #include + + NPY_NO_EXPORT + void delete_array_struct(PyObject *cap) { + + /* get the array interface structure */ + PyArrayInterface *inter = (PyArrayInterface*) + PyCapsule_GetPointer(cap, NULL); + + /* get the buffer by which data was shared */ + double *ptr = (double*)PyCapsule_GetContext(cap); + + /* for the purposes of the regression test set the elements + to nan */ + for (npy_intp i = 0; i < inter->shape[0]; ++i) + ptr[i] = nan(""); + + /* free the shared buffer */ + free(ptr); + + /* free the array interface structure */ + free(inter->shape); + free(inter); + + fprintf(stderr, "delete_array_struct\\ncap = %ld inter = %ld" + " ptr = %ld\\n", (long)cap, (long)inter, (long)ptr); + } + ''' + + functions = [ + ("new_array_struct", "METH_VARARGS", """ + + long long n_elem = 0; + double value = 0.0; + + if (!PyArg_ParseTuple(args, "Ld", &n_elem, &value)) { + Py_RETURN_NONE; + } + + /* allocate and initialize the data to share with numpy */ + long long n_bytes = n_elem*sizeof(double); + double *data = (double*)malloc(n_bytes); + + if (!data) { + PyErr_Format(PyExc_MemoryError, + "Failed to malloc %lld bytes", n_bytes); + + Py_RETURN_NONE; + } + + for (long long i = 0; i < n_elem; ++i) { + data[i] = value; + } + + /* calculate the shape and stride */ + int nd = 1; + + npy_intp *ss = (npy_intp*)malloc(2*nd*sizeof(npy_intp)); + npy_intp *shape = ss; + npy_intp *stride = ss + nd; + + shape[0] = n_elem; + stride[0] = sizeof(double); + + /* construct the array interface */ + PyArrayInterface *inter = (PyArrayInterface*) + malloc(sizeof(PyArrayInterface)); + + memset(inter, 0, sizeof(PyArrayInterface)); + + inter->two = 2; + inter->nd = nd; + inter->typekind = 'f'; + inter->itemsize = sizeof(double); + inter->shape = shape; + inter->strides = stride; + inter->data = data; + inter->flags = NPY_ARRAY_WRITEABLE | NPY_ARRAY_NOTSWAPPED | + NPY_ARRAY_ALIGNED | NPY_ARRAY_C_CONTIGUOUS; + + /* package into a capsule */ + PyObject *cap = PyCapsule_New(inter, NULL, delete_array_struct); + + /* save the pointer to the data */ + PyCapsule_SetContext(cap, data); + + fprintf(stderr, "new_array_struct\\ncap = %ld inter = %ld" + " ptr = %ld\\n", (long)cap, (long)inter, (long)data); + + return cap; + """) + ] + + more_init = "import_array();" + + try: + import array_interface_testing + return array_interface_testing + except ImportError: + pass + + # if it does not exist, build and load it + if sysconfig.get_platform() == "win-arm64": + pytest.skip("Meson unable to find MSVC linker on win-arm64") + return extbuild.build_and_import_extension('array_interface_testing', + functions, + prologue=prologue, + include_dirs=[np.get_include()], + build_dir=tmp_path, + more_init=more_init) + + +@pytest.mark.slow +def test_cstruct(get_module): + + class data_source: + """ + This class is for testing the timing of the PyCapsule destructor + invoked when numpy release its reference to the shared data as part of + the numpy array interface protocol. If the PyCapsule destructor is + called early the shared data is freed and invalid memory accesses will + occur. + """ + + def __init__(self, size, value): + self.size = size + self.value = value + + @property + def __array_struct__(self): + return get_module.new_array_struct(self.size, self.value) + + # write to the same stream as the C code + stderr = sys.__stderr__ + + # used to validate the shared data. + expected_value = -3.1415 + multiplier = -10000.0 + + # create some data to share with numpy via the array interface + # assign the data an expected value. + stderr.write(' ---- create an object to share data ---- \n') + buf = data_source(256, expected_value) + stderr.write(' ---- OK!\n\n') + + # share the data + stderr.write(' ---- share data via the array interface protocol ---- \n') + arr = np.array(buf, copy=False) + stderr.write(f'arr.__array_interface___ = {str(arr.__array_interface__)}\n') + stderr.write(f'arr.base = {str(arr.base)}\n') + stderr.write(' ---- OK!\n\n') + + # release the source of the shared data. this will not release the data + # that was shared with numpy, that is done in the PyCapsule destructor. + stderr.write(' ---- destroy the object that shared data ---- \n') + buf = None + stderr.write(' ---- OK!\n\n') + + # check that we got the expected data. If the PyCapsule destructor we + # defined was prematurely called then this test will fail because our + # destructor sets the elements of the array to NaN before free'ing the + # buffer. Reading the values here may also cause a SEGV + assert np.allclose(arr, expected_value) + + # read the data. If the PyCapsule destructor we defined was prematurely + # called then reading the values here may cause a SEGV and will be reported + # as invalid reads by valgrind + stderr.write(' ---- read shared data ---- \n') + stderr.write(f'arr = {str(arr)}\n') + stderr.write(' ---- OK!\n\n') + + # write to the shared buffer. If the shared data was prematurely deleted + # this will may cause a SEGV and valgrind will report invalid writes + stderr.write(' ---- modify shared data ---- \n') + arr *= multiplier + expected_value *= multiplier + stderr.write(f'arr.__array_interface___ = {str(arr.__array_interface__)}\n') + stderr.write(f'arr.base = {str(arr.base)}\n') + stderr.write(' ---- OK!\n\n') + + # read the data. If the shared data was prematurely deleted this + # will may cause a SEGV and valgrind will report invalid reads + stderr.write(' ---- read modified shared data ---- \n') + stderr.write(f'arr = {str(arr)}\n') + stderr.write(' ---- OK!\n\n') + + # check that we got the expected data. If the PyCapsule destructor we + # defined was prematurely called then this test will fail because our + # destructor sets the elements of the array to NaN before free'ing the + # buffer. Reading the values here may also cause a SEGV + assert np.allclose(arr, expected_value) + + # free the shared data, the PyCapsule destructor should run here + stderr.write(' ---- free shared data ---- \n') + arr = None + stderr.write(' ---- OK!\n\n') diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_arraymethod.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_arraymethod.py new file mode 100644 index 0000000000000000000000000000000000000000..5b3d515857182ad2ac5c1c74c3086c3e78995a5a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_arraymethod.py @@ -0,0 +1,84 @@ +""" +This file tests the generic aspects of ArrayMethod. At the time of writing +this is private API, but when added, public API may be added here. +""" + +import types +from typing import Any + +import pytest + +import numpy as np +from numpy._core._multiarray_umath import _get_castingimpl as get_castingimpl + + +class TestResolveDescriptors: + # Test mainly error paths of the resolve_descriptors function, + # note that the `casting_unittests` tests exercise this non-error paths. + + # Casting implementations are the main/only current user: + method = get_castingimpl(type(np.dtype("d")), type(np.dtype("f"))) + + @pytest.mark.parametrize("args", [ + (True,), # Not a tuple. + ((None,)), # Too few elements + ((None, None, None),), # Too many + ((None, None),), # Input dtype is None, which is invalid. + ((np.dtype("d"), True),), # Output dtype is not a dtype + ((np.dtype("f"), None),), # Input dtype does not match method + ]) + def test_invalid_arguments(self, args): + with pytest.raises(TypeError): + self.method._resolve_descriptors(*args) + + +class TestSimpleStridedCall: + # Test mainly error paths of the resolve_descriptors function, + # note that the `casting_unittests` tests exercise this non-error paths. + + # Casting implementations are the main/only current user: + method = get_castingimpl(type(np.dtype("d")), type(np.dtype("f"))) + + @pytest.mark.parametrize(["args", "error"], [ + ((True,), TypeError), # Not a tuple + (((None,),), TypeError), # Too few elements + ((None, None), TypeError), # Inputs are not arrays. + (((None, None, None),), TypeError), # Too many + (((np.arange(3), np.arange(3)),), TypeError), # Incorrect dtypes + (((np.ones(3, dtype=">d"), np.ones(3, dtype=" None: + """Test `ndarray.__class_getitem__`.""" + alias = cls[Any, Any] + assert isinstance(alias, types.GenericAlias) + assert alias.__origin__ is cls + + @pytest.mark.parametrize("arg_len", range(4)) + def test_subscript_tup(self, cls: type[np.ndarray], arg_len: int) -> None: + arg_tup = (Any,) * arg_len + if arg_len in (1, 2): + assert cls[arg_tup] + else: + match = f"Too {'few' if arg_len == 0 else 'many'} arguments" + with pytest.raises(TypeError, match=match): + cls[arg_tup] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_arrayobject.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_arrayobject.py new file mode 100644 index 0000000000000000000000000000000000000000..f4e268b377b3e5950ef13806b8d3af625e7e7e27 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_arrayobject.py @@ -0,0 +1,95 @@ +import sys + +import pytest + +import numpy as np +from numpy.testing import HAS_REFCOUNT, assert_array_equal + + +def test_matrix_transpose_raises_error_for_1d(): + msg = "matrix transpose with ndim < 2 is undefined" + arr = np.arange(48) + with pytest.raises(ValueError, match=msg): + arr.mT + + +def test_matrix_transpose_equals_transpose_2d(): + arr = np.arange(48).reshape((6, 8)) + assert_array_equal(arr.T, arr.mT) + + +ARRAY_SHAPES_TO_TEST = ( + (5, 2), + (5, 2, 3), + (5, 2, 3, 4), +) + + +@pytest.mark.parametrize("shape", ARRAY_SHAPES_TO_TEST) +def test_matrix_transpose_equals_swapaxes(shape): + num_of_axes = len(shape) + vec = np.arange(shape[-1]) + arr = np.broadcast_to(vec, shape) + tgt = np.swapaxes(arr, num_of_axes - 2, num_of_axes - 1) + mT = arr.mT + assert_array_equal(tgt, mT) + + +class MyArr(np.ndarray): + def __array_wrap__(self, arr, context=None, return_scalar=None): + return super().__array_wrap__(arr, context, return_scalar) + + +class MyArrNoWrap(np.ndarray): + pass + + +@pytest.mark.parametrize("subclass_self", [np.ndarray, MyArr, MyArrNoWrap]) +@pytest.mark.parametrize("subclass_arr", [np.ndarray, MyArr, MyArrNoWrap]) +def test_array_wrap(subclass_self, subclass_arr): + # NumPy should allow `__array_wrap__` to be called on arrays, it's logic + # is designed in a way that: + # + # * Subclasses never return scalars by default (to preserve their + # information). They can choose to if they wish. + # * NumPy returns scalars, if `return_scalar` is passed as True to allow + # manual calls to `arr.__array_wrap__` to do the right thing. + # * The type of the input should be ignored (it should be a base-class + # array, but I am not sure this is guaranteed). + + arr = np.arange(3).view(subclass_self) + + arr0d = np.array(3, dtype=np.int8).view(subclass_arr) + # With third argument True, ndarray allows "decay" to scalar. + # (I don't think NumPy would pass `None`, but it seems clear to support) + if subclass_self is np.ndarray: + assert type(arr.__array_wrap__(arr0d, None, True)) is np.int8 + else: + assert type(arr.__array_wrap__(arr0d, None, True)) is type(arr) + + # Otherwise, result should be viewed as the subclass + assert type(arr.__array_wrap__(arr0d)) is type(arr) + assert type(arr.__array_wrap__(arr0d, None, None)) is type(arr) + assert type(arr.__array_wrap__(arr0d, None, False)) is type(arr) + + # Non 0-D array can't be converted to scalar, so we ignore that + arr1d = np.array([3], dtype=np.int8).view(subclass_arr) + assert type(arr.__array_wrap__(arr1d, None, True)) is type(arr) + + +@pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") +def test_cleanup_with_refs_non_contig(): + # Regression test, leaked the dtype (but also good for rest) + dtype = np.dtype("O,i") + obj = object() + expected_ref_dtype = sys.getrefcount(dtype) + expected_ref_obj = sys.getrefcount(obj) + proto = np.full((3, 4, 5, 6, 7), np.array((obj, 2), dtype=dtype)) + # Give array a non-trivial order to exercise more cleanup paths. + arr = proto.transpose((2, 0, 3, 1, 4)).copy("K") + del proto, arr + + actual_ref_dtype = sys.getrefcount(dtype) + actual_ref_obj = sys.getrefcount(obj) + assert actual_ref_dtype == expected_ref_dtype + assert actual_ref_obj == actual_ref_dtype diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_arrayprint.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_arrayprint.py new file mode 100644 index 0000000000000000000000000000000000000000..06d1306dd408ecc4bdba589ff53e39bb3331f325 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_arrayprint.py @@ -0,0 +1,1324 @@ +import gc +import sys +import textwrap + +import pytest +from hypothesis import given +from hypothesis.extra import numpy as hynp + +import numpy as np +from numpy._core.arrayprint import _typelessdata +from numpy.testing import ( + HAS_REFCOUNT, + IS_WASM, + assert_, + assert_equal, + assert_raises, + assert_raises_regex, +) +from numpy.testing._private.utils import run_threaded + + +class TestArrayRepr: + def test_nan_inf(self): + x = np.array([np.nan, np.inf]) + assert_equal(repr(x), 'array([nan, inf])') + + def test_subclass(self): + class sub(np.ndarray): + pass + + # one dimensional + x1d = np.array([1, 2]).view(sub) + assert_equal(repr(x1d), 'sub([1, 2])') + + # two dimensional + x2d = np.array([[1, 2], [3, 4]]).view(sub) + assert_equal(repr(x2d), + 'sub([[1, 2],\n' + ' [3, 4]])') + + # two dimensional with flexible dtype + xstruct = np.ones((2, 2), dtype=[('a', ' 1) + y = sub(None) + x[()] = y + y[()] = x + assert_equal(repr(x), + 'sub(sub(sub(..., dtype=object), dtype=object), dtype=object)') + assert_equal(str(x), '...') + x[()] = 0 # resolve circular references for garbage collector + + # nested 0d-subclass-object + x = sub(None) + x[()] = sub(None) + assert_equal(repr(x), 'sub(sub(None, dtype=object), dtype=object)') + assert_equal(str(x), 'None') + + # gh-10663 + class DuckCounter(np.ndarray): + def __getitem__(self, item): + result = super().__getitem__(item) + if not isinstance(result, DuckCounter): + result = result[...].view(DuckCounter) + return result + + def to_string(self): + return {0: 'zero', 1: 'one', 2: 'two'}.get(self.item(), 'many') + + def __str__(self): + if self.shape == (): + return self.to_string() + else: + fmt = {'all': lambda x: x.to_string()} + return np.array2string(self, formatter=fmt) + + dc = np.arange(5).view(DuckCounter) + assert_equal(str(dc), "[zero one two many many]") + assert_equal(str(dc[0]), "zero") + + def test_self_containing(self): + arr0d = np.array(None) + arr0d[()] = arr0d + assert_equal(repr(arr0d), + 'array(array(..., dtype=object), dtype=object)') + arr0d[()] = 0 # resolve recursion for garbage collector + + arr1d = np.array([None, None]) + arr1d[1] = arr1d + assert_equal(repr(arr1d), + 'array([None, array(..., dtype=object)], dtype=object)') + arr1d[1] = 0 # resolve recursion for garbage collector + + first = np.array(None) + second = np.array(None) + first[()] = second + second[()] = first + assert_equal(repr(first), + 'array(array(array(..., dtype=object), dtype=object), dtype=object)') + first[()] = 0 # resolve circular references for garbage collector + + def test_containing_list(self): + # printing square brackets directly would be ambiguous + arr1d = np.array([None, None]) + arr1d[0] = [1, 2] + arr1d[1] = [3] + assert_equal(repr(arr1d), + 'array([list([1, 2]), list([3])], dtype=object)') + + def test_void_scalar_recursion(self): + # gh-9345 + repr(np.void(b'test')) # RecursionError ? + + def test_fieldless_structured(self): + # gh-10366 + no_fields = np.dtype([]) + arr_no_fields = np.empty(4, dtype=no_fields) + assert_equal(repr(arr_no_fields), 'array([(), (), (), ()], dtype=[])') + + +class TestComplexArray: + def test_str(self): + rvals = [0, 1, -1, np.inf, -np.inf, np.nan] + cvals = [complex(rp, ip) for rp in rvals for ip in rvals] + dtypes = [np.complex64, np.cdouble, np.clongdouble] + actual = [str(np.array([c], dt)) for c in cvals for dt in dtypes] + wanted = [ + '[0.+0.j]', '[0.+0.j]', '[0.+0.j]', + '[0.+1.j]', '[0.+1.j]', '[0.+1.j]', + '[0.-1.j]', '[0.-1.j]', '[0.-1.j]', + '[0.+infj]', '[0.+infj]', '[0.+infj]', + '[0.-infj]', '[0.-infj]', '[0.-infj]', + '[0.+nanj]', '[0.+nanj]', '[0.+nanj]', + '[1.+0.j]', '[1.+0.j]', '[1.+0.j]', + '[1.+1.j]', '[1.+1.j]', '[1.+1.j]', + '[1.-1.j]', '[1.-1.j]', '[1.-1.j]', + '[1.+infj]', '[1.+infj]', '[1.+infj]', + '[1.-infj]', '[1.-infj]', '[1.-infj]', + '[1.+nanj]', '[1.+nanj]', '[1.+nanj]', + '[-1.+0.j]', '[-1.+0.j]', '[-1.+0.j]', + '[-1.+1.j]', '[-1.+1.j]', '[-1.+1.j]', + '[-1.-1.j]', '[-1.-1.j]', '[-1.-1.j]', + '[-1.+infj]', '[-1.+infj]', '[-1.+infj]', + '[-1.-infj]', '[-1.-infj]', '[-1.-infj]', + '[-1.+nanj]', '[-1.+nanj]', '[-1.+nanj]', + '[inf+0.j]', '[inf+0.j]', '[inf+0.j]', + '[inf+1.j]', '[inf+1.j]', '[inf+1.j]', + '[inf-1.j]', '[inf-1.j]', '[inf-1.j]', + '[inf+infj]', '[inf+infj]', '[inf+infj]', + '[inf-infj]', '[inf-infj]', '[inf-infj]', + '[inf+nanj]', '[inf+nanj]', '[inf+nanj]', + '[-inf+0.j]', '[-inf+0.j]', '[-inf+0.j]', + '[-inf+1.j]', '[-inf+1.j]', '[-inf+1.j]', + '[-inf-1.j]', '[-inf-1.j]', '[-inf-1.j]', + '[-inf+infj]', '[-inf+infj]', '[-inf+infj]', + '[-inf-infj]', '[-inf-infj]', '[-inf-infj]', + '[-inf+nanj]', '[-inf+nanj]', '[-inf+nanj]', + '[nan+0.j]', '[nan+0.j]', '[nan+0.j]', + '[nan+1.j]', '[nan+1.j]', '[nan+1.j]', + '[nan-1.j]', '[nan-1.j]', '[nan-1.j]', + '[nan+infj]', '[nan+infj]', '[nan+infj]', + '[nan-infj]', '[nan-infj]', '[nan-infj]', + '[nan+nanj]', '[nan+nanj]', '[nan+nanj]'] + + for res, val in zip(actual, wanted): + assert_equal(res, val) + +class TestArray2String: + def test_basic(self): + """Basic test of array2string.""" + a = np.arange(3) + assert_(np.array2string(a) == '[0 1 2]') + assert_(np.array2string(a, max_line_width=4, legacy='1.13') == '[0 1\n 2]') + assert_(np.array2string(a, max_line_width=4) == '[0\n 1\n 2]') + + def test_unexpected_kwarg(self): + # ensure than an appropriate TypeError + # is raised when array2string receives + # an unexpected kwarg + + with assert_raises_regex(TypeError, 'nonsense'): + np.array2string(np.array([1, 2, 3]), + nonsense=None) + + def test_format_function(self): + """Test custom format function for each element in array.""" + def _format_function(x): + if np.abs(x) < 1: + return '.' + elif np.abs(x) < 2: + return 'o' + else: + return 'O' + + x = np.arange(3) + x_hex = "[0x0 0x1 0x2]" + x_oct = "[0o0 0o1 0o2]" + assert_(np.array2string(x, formatter={'all': _format_function}) == + "[. o O]") + assert_(np.array2string(x, formatter={'int_kind': _format_function}) == + "[. o O]") + assert_(np.array2string(x, formatter={'all': lambda x: f"{x:.4f}"}) == + "[0.0000 1.0000 2.0000]") + assert_equal(np.array2string(x, formatter={'int': hex}), + x_hex) + assert_equal(np.array2string(x, formatter={'int': oct}), + x_oct) + + x = np.arange(3.) + assert_(np.array2string(x, formatter={'float_kind': lambda x: f"{x:.2f}"}) == + "[0.00 1.00 2.00]") + assert_(np.array2string(x, formatter={'float': lambda x: f"{x:.2f}"}) == + "[0.00 1.00 2.00]") + + s = np.array(['abc', 'def']) + assert_(np.array2string(s, formatter={'numpystr': lambda s: s * 2}) == + '[abcabc defdef]') + + def test_structure_format_mixed(self): + dt = np.dtype([('name', np.str_, 16), ('grades', np.float64, (2,))]) + x = np.array([('Sarah', (8.0, 7.0)), ('John', (6.0, 7.0))], dtype=dt) + assert_equal(np.array2string(x), + "[('Sarah', [8., 7.]) ('John', [6., 7.])]") + + np.set_printoptions(legacy='1.13') + try: + # for issue #5692 + A = np.zeros(shape=10, dtype=[("A", "M8[s]")]) + A[5:].fill(np.datetime64('NaT')) + assert_equal( + np.array2string(A), + textwrap.dedent("""\ + [('1970-01-01T00:00:00',) ('1970-01-01T00:00:00',) ('1970-01-01T00:00:00',) + ('1970-01-01T00:00:00',) ('1970-01-01T00:00:00',) ('NaT',) ('NaT',) + ('NaT',) ('NaT',) ('NaT',)]""") + ) + finally: + np.set_printoptions(legacy=False) + + # same again, but with non-legacy behavior + assert_equal( + np.array2string(A), + textwrap.dedent("""\ + [('1970-01-01T00:00:00',) ('1970-01-01T00:00:00',) + ('1970-01-01T00:00:00',) ('1970-01-01T00:00:00',) + ('1970-01-01T00:00:00',) ( 'NaT',) + ( 'NaT',) ( 'NaT',) + ( 'NaT',) ( 'NaT',)]""") + ) + + # and again, with timedeltas + A = np.full(10, 123456, dtype=[("A", "m8[s]")]) + A[5:].fill(np.datetime64('NaT')) + assert_equal( + np.array2string(A), + textwrap.dedent("""\ + [(123456,) (123456,) (123456,) (123456,) (123456,) ( 'NaT',) ( 'NaT',) + ( 'NaT',) ( 'NaT',) ( 'NaT',)]""") + ) + + def test_structure_format_int(self): + # See #8160 + struct_int = np.array([([1, -1],), ([123, 1],)], + dtype=[('B', 'i4', 2)]) + assert_equal(np.array2string(struct_int), + "[([ 1, -1],) ([123, 1],)]") + struct_2dint = np.array([([[0, 1], [2, 3]],), ([[12, 0], [0, 0]],)], + dtype=[('B', 'i4', (2, 2))]) + assert_equal(np.array2string(struct_2dint), + "[([[ 0, 1], [ 2, 3]],) ([[12, 0], [ 0, 0]],)]") + + def test_structure_format_float(self): + # See #8172 + array_scalar = np.array( + (1., 2.1234567890123456789, 3.), dtype=('f8,f8,f8')) + assert_equal(np.array2string(array_scalar), "(1., 2.12345679, 3.)") + + def test_unstructured_void_repr(self): + a = np.array([27, 91, 50, 75, 7, 65, 10, 8, 27, 91, 51, 49, 109, 82, 101, 100], + dtype='u1').view('V8') + assert_equal(repr(a[0]), + r"np.void(b'\x1B\x5B\x32\x4B\x07\x41\x0A\x08')") + assert_equal(str(a[0]), r"b'\x1B\x5B\x32\x4B\x07\x41\x0A\x08'") + assert_equal(repr(a), + r"array([b'\x1B\x5B\x32\x4B\x07\x41\x0A\x08'," + "\n" + r" b'\x1B\x5B\x33\x31\x6D\x52\x65\x64'], dtype='|V8')") + + assert_equal(eval(repr(a), vars(np)), a) + assert_equal(eval(repr(a[0]), {'np': np}), a[0]) + + def test_edgeitems_kwarg(self): + # previously the global print options would be taken over the kwarg + arr = np.zeros(3, int) + assert_equal( + np.array2string(arr, edgeitems=1, threshold=0), + "[0 ... 0]" + ) + + def test_summarize_1d(self): + A = np.arange(1001) + strA = '[ 0 1 2 ... 998 999 1000]' + assert_equal(str(A), strA) + + reprA = 'array([ 0, 1, 2, ..., 998, 999, 1000])' + try: + np.set_printoptions(legacy='2.1') + assert_equal(repr(A), reprA) + finally: + np.set_printoptions(legacy=False) + + assert_equal(repr(A), reprA.replace(')', ', shape=(1001,))')) + + def test_summarize_2d(self): + A = np.arange(1002).reshape(2, 501) + strA = '[[ 0 1 2 ... 498 499 500]\n' \ + ' [ 501 502 503 ... 999 1000 1001]]' + assert_equal(str(A), strA) + + reprA = 'array([[ 0, 1, 2, ..., 498, 499, 500],\n' \ + ' [ 501, 502, 503, ..., 999, 1000, 1001]])' + try: + np.set_printoptions(legacy='2.1') + assert_equal(repr(A), reprA) + finally: + np.set_printoptions(legacy=False) + + assert_equal(repr(A), reprA.replace(')', ', shape=(2, 501))')) + + def test_summarize_2d_dtype(self): + A = np.arange(1002, dtype='i2').reshape(2, 501) + strA = '[[ 0 1 2 ... 498 499 500]\n' \ + ' [ 501 502 503 ... 999 1000 1001]]' + assert_equal(str(A), strA) + + reprA = ('array([[ 0, 1, 2, ..., 498, 499, 500],\n' + ' [ 501, 502, 503, ..., 999, 1000, 1001]],\n' + ' shape=(2, 501), dtype=int16)') + assert_equal(repr(A), reprA) + + def test_summarize_structure(self): + A = (np.arange(2002, dtype="i8", (2, 1001))]) + strB = "[([[1, 1, 1, ..., 1, 1, 1], [1, 1, 1, ..., 1, 1, 1]],)]" + assert_equal(str(B), strB) + + reprB = ( + "array([([[1, 1, 1, ..., 1, 1, 1], [1, 1, 1, ..., 1, 1, 1]],)],\n" + " dtype=[('i', '>i8', (2, 1001))])" + ) + assert_equal(repr(B), reprB) + + C = (np.arange(22, dtype=" 1: + # if the type is >1 byte, the non-native endian version + # must show endianness. + assert non_native_repr != native_repr + assert f"dtype='{non_native_dtype.byteorder}" in non_native_repr + + def test_linewidth_repr(self): + a = np.full(7, fill_value=2) + np.set_printoptions(linewidth=17) + assert_equal( + repr(a), + textwrap.dedent("""\ + array([2, 2, 2, + 2, 2, 2, + 2])""") + ) + np.set_printoptions(linewidth=17, legacy='1.13') + assert_equal( + repr(a), + textwrap.dedent("""\ + array([2, 2, 2, + 2, 2, 2, 2])""") + ) + + a = np.full(8, fill_value=2) + + np.set_printoptions(linewidth=18, legacy=False) + assert_equal( + repr(a), + textwrap.dedent("""\ + array([2, 2, 2, + 2, 2, 2, + 2, 2])""") + ) + + np.set_printoptions(linewidth=18, legacy='1.13') + assert_equal( + repr(a), + textwrap.dedent("""\ + array([2, 2, 2, 2, + 2, 2, 2, 2])""") + ) + + def test_linewidth_str(self): + a = np.full(18, fill_value=2) + np.set_printoptions(linewidth=18) + assert_equal( + str(a), + textwrap.dedent("""\ + [2 2 2 2 2 2 2 2 + 2 2 2 2 2 2 2 2 + 2 2]""") + ) + np.set_printoptions(linewidth=18, legacy='1.13') + assert_equal( + str(a), + textwrap.dedent("""\ + [2 2 2 2 2 2 2 2 2 + 2 2 2 2 2 2 2 2 2]""") + ) + + def test_edgeitems(self): + np.set_printoptions(edgeitems=1, threshold=1) + a = np.arange(27).reshape((3, 3, 3)) + assert_equal( + repr(a), + textwrap.dedent("""\ + array([[[ 0, ..., 2], + ..., + [ 6, ..., 8]], + + ..., + + [[18, ..., 20], + ..., + [24, ..., 26]]], shape=(3, 3, 3))""") + ) + + b = np.zeros((3, 3, 1, 1)) + assert_equal( + repr(b), + textwrap.dedent("""\ + array([[[[0.]], + + ..., + + [[0.]]], + + + ..., + + + [[[0.]], + + ..., + + [[0.]]]], shape=(3, 3, 1, 1))""") + ) + + # 1.13 had extra trailing spaces, and was missing newlines + try: + np.set_printoptions(legacy='1.13') + assert_equal(repr(a), ( + "array([[[ 0, ..., 2],\n" + " ..., \n" + " [ 6, ..., 8]],\n" + "\n" + " ..., \n" + " [[18, ..., 20],\n" + " ..., \n" + " [24, ..., 26]]])") + ) + assert_equal(repr(b), ( + "array([[[[ 0.]],\n" + "\n" + " ..., \n" + " [[ 0.]]],\n" + "\n" + "\n" + " ..., \n" + " [[[ 0.]],\n" + "\n" + " ..., \n" + " [[ 0.]]]])") + ) + finally: + np.set_printoptions(legacy=False) + + def test_edgeitems_structured(self): + np.set_printoptions(edgeitems=1, threshold=1) + A = np.arange(5 * 2 * 3, dtype="f4')])"), + (np.void(b'a'), r"void(b'\x61')", r"np.void(b'\x61')"), + ]) +def test_scalar_repr_special(scalar, legacy_repr, representation): + # Test NEP 51 scalar repr (and legacy option) for numeric types + assert repr(scalar) == representation + + with np.printoptions(legacy="1.25"): + assert repr(scalar) == legacy_repr + +def test_scalar_void_float_str(): + # Note that based on this currently we do not print the same as a tuple + # would, since the tuple would include the repr() inside for floats, but + # we do not do that. + scalar = np.void((1.0, 2.0), dtype=[('f0', 'f4')]) + assert str(scalar) == "(1.0, 2.0)" + +@pytest.mark.skipif(IS_WASM, reason="wasm doesn't support asyncio") +@pytest.mark.skipif(sys.version_info < (3, 11), + reason="asyncio.barrier was added in Python 3.11") +def test_printoptions_asyncio_safe(): + asyncio = pytest.importorskip("asyncio") + + b = asyncio.Barrier(2) + + async def legacy_113(): + np.set_printoptions(legacy='1.13', precision=12) + await b.wait() + po = np.get_printoptions() + assert po['legacy'] == '1.13' + assert po['precision'] == 12 + orig_linewidth = po['linewidth'] + with np.printoptions(linewidth=34, legacy='1.21'): + po = np.get_printoptions() + assert po['legacy'] == '1.21' + assert po['precision'] == 12 + assert po['linewidth'] == 34 + po = np.get_printoptions() + assert po['linewidth'] == orig_linewidth + assert po['legacy'] == '1.13' + assert po['precision'] == 12 + + async def legacy_125(): + np.set_printoptions(legacy='1.25', precision=7) + await b.wait() + po = np.get_printoptions() + assert po['legacy'] == '1.25' + assert po['precision'] == 7 + orig_linewidth = po['linewidth'] + with np.printoptions(linewidth=6, legacy='1.13'): + po = np.get_printoptions() + assert po['legacy'] == '1.13' + assert po['precision'] == 7 + assert po['linewidth'] == 6 + po = np.get_printoptions() + assert po['linewidth'] == orig_linewidth + assert po['legacy'] == '1.25' + assert po['precision'] == 7 + + async def main(): + await asyncio.gather(legacy_125(), legacy_125()) + + loop = asyncio.new_event_loop() + asyncio.run(main()) + loop.close() + +@pytest.mark.skipif(IS_WASM, reason="wasm doesn't support threads") +@pytest.mark.thread_unsafe(reason="test is already explicitly multi-threaded") +def test_multithreaded_array_printing(): + # the dragon4 implementation uses a static scratch space for performance + # reasons this test makes sure it is set up in a thread-safe manner + + run_threaded(TestPrintOptions().test_floatmode, 500) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_casting_floatingpoint_errors.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_casting_floatingpoint_errors.py new file mode 100644 index 0000000000000000000000000000000000000000..2f9c01f907c425a932fd4d3c2e47f653aa333a54 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_casting_floatingpoint_errors.py @@ -0,0 +1,154 @@ +import pytest +from pytest import param + +import numpy as np +from numpy.testing import IS_WASM + + +def values_and_dtypes(): + """ + Generate value+dtype pairs that generate floating point errors during + casts. The invalid casts to integers will generate "invalid" value + warnings, the float casts all generate "overflow". + + (The Python int/float paths don't need to get tested in all the same + situations, but it does not hurt.) + """ + # Casting to float16: + yield param(70000, "float16", id="int-to-f2") + yield param("70000", "float16", id="str-to-f2") + yield param(70000.0, "float16", id="float-to-f2") + yield param(np.longdouble(70000.), "float16", id="longdouble-to-f2") + yield param(np.float64(70000.), "float16", id="double-to-f2") + yield param(np.float32(70000.), "float16", id="float-to-f2") + # Casting to float32: + yield param(10**100, "float32", id="int-to-f4") + yield param(1e100, "float32", id="float-to-f2") + yield param(np.longdouble(1e300), "float32", id="longdouble-to-f2") + yield param(np.float64(1e300), "float32", id="double-to-f2") + # Casting to float64: + # If longdouble is double-double, its max can be rounded down to the double + # max. So we correct the double spacing (a bit weird, admittedly): + max_ld = np.finfo(np.longdouble).max + spacing = np.spacing(np.nextafter(np.finfo("f8").max, 0)) + if max_ld - spacing > np.finfo("f8").max: + yield param(np.finfo(np.longdouble).max, "float64", + id="longdouble-to-f8") + + # Cast to complex32: + yield param(2e300, "complex64", id="float-to-c8") + yield param(2e300 + 0j, "complex64", id="complex-to-c8") + yield param(2e300j, "complex64", id="complex-to-c8") + yield param(np.longdouble(2e300), "complex64", id="longdouble-to-c8") + + # Invalid float to integer casts: + with np.errstate(over="ignore"): + for to_dt in np.typecodes["AllInteger"]: + for value in [np.inf, np.nan]: + for from_dt in np.typecodes["AllFloat"]: + from_dt = np.dtype(from_dt) + from_val = from_dt.type(value) + + yield param(from_val, to_dt, id=f"{from_val}-to-{to_dt}") + + +def check_operations(dtype, value): + """ + There are many dedicated paths in NumPy which cast and should check for + floating point errors which occurred during those casts. + """ + if dtype.kind != 'i': + # These assignments use the stricter setitem logic: + def assignment(): + arr = np.empty(3, dtype=dtype) + arr[0] = value + + yield assignment + + def fill(): + arr = np.empty(3, dtype=dtype) + arr.fill(value) + + yield fill + + def copyto_scalar(): + arr = np.empty(3, dtype=dtype) + np.copyto(arr, value, casting="unsafe") + + yield copyto_scalar + + def copyto(): + arr = np.empty(3, dtype=dtype) + np.copyto(arr, np.array([value, value, value]), casting="unsafe") + + yield copyto + + def copyto_scalar_masked(): + arr = np.empty(3, dtype=dtype) + np.copyto(arr, value, casting="unsafe", + where=[True, False, True]) + + yield copyto_scalar_masked + + def copyto_masked(): + arr = np.empty(3, dtype=dtype) + np.copyto(arr, np.array([value, value, value]), casting="unsafe", + where=[True, False, True]) + + yield copyto_masked + + def direct_cast(): + np.array([value, value, value]).astype(dtype) + + yield direct_cast + + def direct_cast_nd_strided(): + arr = np.full((5, 5, 5), fill_value=value)[:, ::2, :] + arr.astype(dtype) + + yield direct_cast_nd_strided + + def boolean_array_assignment(): + arr = np.empty(3, dtype=dtype) + arr[[True, False, True]] = np.array([value, value]) + + yield boolean_array_assignment + + def integer_array_assignment(): + arr = np.empty(3, dtype=dtype) + values = np.array([value, value]) + + arr[[0, 1]] = values + + yield integer_array_assignment + + def integer_array_assignment_with_subspace(): + arr = np.empty((5, 3), dtype=dtype) + values = np.array([value, value, value]) + + arr[[0, 2]] = values + + yield integer_array_assignment_with_subspace + + def flat_assignment(): + arr = np.empty((3,), dtype=dtype) + values = np.array([value, value, value]) + arr.flat[:] = values + + yield flat_assignment + +@pytest.mark.skipif(IS_WASM, reason="no wasm fp exception support") +@pytest.mark.parametrize(["value", "dtype"], values_and_dtypes()) +@pytest.mark.filterwarnings("ignore::numpy.exceptions.ComplexWarning") +def test_floatingpoint_errors_casting(dtype, value): + dtype = np.dtype(dtype) + for operation in check_operations(dtype, value): + dtype = np.dtype(dtype) + + match = "invalid" if dtype.kind in 'iu' else "overflow" + with pytest.warns(RuntimeWarning, match=match): + operation() + + with np.errstate(all="raise"): + with pytest.raises(FloatingPointError, match=match): + operation() diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_casting_unittests.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_casting_unittests.py new file mode 100644 index 0000000000000000000000000000000000000000..5f643f8045ba93e118f47506245667ec3a491b62 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_casting_unittests.py @@ -0,0 +1,955 @@ +""" +The tests exercise the casting machinery in a more low-level manner. +The reason is mostly to test a new implementation of the casting machinery. + +Unlike most tests in NumPy, these are closer to unit-tests rather +than integration tests. +""" + +import ctypes +import enum +import random +import textwrap +import warnings + +import pytest + +import numpy as np +from numpy._core._multiarray_umath import _get_castingimpl as get_castingimpl +from numpy.lib.stride_tricks import as_strided +from numpy.testing import assert_array_equal, assert_equal + +# Simple skips object, parametric and long double (unsupported by struct) +simple_dtypes = "?bhilqBHILQefdFD" +if np.dtype("l").itemsize != np.dtype("q").itemsize: + # Remove l and L, the table was generated with 64bit linux in mind. + simple_dtypes = simple_dtypes.replace("l", "").replace("L", "") +simple_dtypes = [type(np.dtype(c)) for c in simple_dtypes] + + +def simple_dtype_instances(): + for dtype_class in simple_dtypes: + dt = dtype_class() + yield pytest.param(dt, id=str(dt)) + if dt.byteorder != "|": + dt = dt.newbyteorder() + yield pytest.param(dt, id=str(dt)) + + +def get_expected_stringlength(dtype): + """Returns the string length when casting the basic dtypes to strings. + """ + if dtype == np.bool: + return 5 + if dtype.kind in "iu": + if dtype.itemsize == 1: + length = 3 + elif dtype.itemsize == 2: + length = 5 + elif dtype.itemsize == 4: + length = 10 + elif dtype.itemsize == 8: + length = 20 + else: + raise AssertionError(f"did not find expected length for {dtype}") + + if dtype.kind == "i": + length += 1 # adds one character for the sign + + return length + + # Note: Can't do dtype comparison for longdouble on windows + if dtype.char == "g": + return 48 + elif dtype.char == "G": + return 48 * 2 + elif dtype.kind == "f": + return 32 # also for half apparently. + elif dtype.kind == "c": + return 32 * 2 + + raise AssertionError(f"did not find expected length for {dtype}") + + +class Casting(enum.IntEnum): + no = 0 + equiv = 1 + safe = 2 + same_kind = 3 + unsafe = 4 + same_value = 64 + + +same_value_dtypes = tuple(type(np.dtype(c)) for c in "?bhilqBHILQefdgFDG") + +def _get_cancast_table(): + table = textwrap.dedent(""" + X ? b h i l q B H I L Q e f d g F D G S U V O M m + ? # = = = = = = = = = = = = = = = = = = = = = . = + b . # = = = = . . . . . = = = = = = = = = = = . = + h . ~ # = = = . . . . . ~ = = = = = = = = = = . = + i . ~ ~ # = = . . . . . ~ ~ = = ~ = = = = = = . = + l . ~ ~ ~ # # . . . . . ~ ~ = = ~ = = = = = = . = + q . ~ ~ ~ # # . . . . . ~ ~ = = ~ = = = = = = . = + B . ~ = = = = # = = = = = = = = = = = = = = = . = + H . ~ ~ = = = ~ # = = = ~ = = = = = = = = = = . = + I . ~ ~ ~ = = ~ ~ # = = ~ ~ = = ~ = = = = = = . = + L . ~ ~ ~ ~ ~ ~ ~ ~ # # ~ ~ = = ~ = = = = = = . ~ + Q . ~ ~ ~ ~ ~ ~ ~ ~ # # ~ ~ = = ~ = = = = = = . ~ + e . . . . . . . . . . . # = = = = = = = = = = . . + f . . . . . . . . . . . ~ # = = = = = = = = = . . + d . . . . . . . . . . . ~ ~ # = ~ = = = = = = . . + g . . . . . . . . . . . ~ ~ ~ # ~ ~ = = = = = . . + F . . . . . . . . . . . . . . . # = = = = = = . . + D . . . . . . . . . . . . . . . ~ # = = = = = . . + G . . . . . . . . . . . . . . . ~ ~ # = = = = . . + S . . . . . . . . . . . . . . . . . . # = = = . . + U . . . . . . . . . . . . . . . . . . . # = = . . + V . . . . . . . . . . . . . . . . . . . . # = . . + O . . . . . . . . . . . . . . . . . . . . = # . . + M . . . . . . . . . . . . . . . . . . . . = = # . + m . . . . . . . . . . . . . . . . . . . . = = . # + """).strip().split("\n") + dtypes = [type(np.dtype(c)) for c in table[0][2::2]] + + convert_cast = {".": Casting.unsafe, "~": Casting.same_kind, + "=": Casting.safe, "#": Casting.equiv, + " ": -1} + + cancast = {} + for from_dt, row in zip(dtypes, table[1:]): + cancast[from_dt] = {} + for to_dt, c in zip(dtypes, row[2::2]): + cancast[from_dt][to_dt] = convert_cast[c] + # Of the types checked, numeric cast support same-value + if from_dt in same_value_dtypes and to_dt in same_value_dtypes: + cancast[from_dt][to_dt] |= Casting.same_value + + return cancast + + +CAST_TABLE = _get_cancast_table() + + +class TestChanges: + """ + These test cases exercise some behaviour changes + """ + @pytest.mark.parametrize("string", ["S", "U"]) + @pytest.mark.parametrize("floating", ["e", "f", "d", "g"]) + def test_float_to_string(self, floating, string): + assert np.can_cast(floating, string) + # 100 is long enough to hold any formatted floating + assert np.can_cast(floating, f"{string}100") + + def test_to_void(self): + # But in general, we do consider these safe: + assert np.can_cast("d", "V") + assert np.can_cast("S20", "V") + + # Do not consider it a safe cast if the void is too smaller: + assert not np.can_cast("d", "V1") + assert not np.can_cast("S20", "V1") + assert not np.can_cast("U1", "V1") + # Structured to unstructured is just like any other: + assert np.can_cast("d,i", "V", casting="same_kind") + # Unstructured void to unstructured is actually no cast at all: + assert np.can_cast("V3", "V", casting="no") + assert np.can_cast("V0", "V", casting="no") + + +class TestCasting: + size = 1500 # Best larger than NPY_LOWLEVEL_BUFFER_BLOCKSIZE * itemsize + + def get_data(self, dtype1, dtype2): + if dtype2 is None or dtype1.itemsize >= dtype2.itemsize: + length = self.size // dtype1.itemsize + else: + length = self.size // dtype2.itemsize + + # Assume that the base array is well enough aligned for all inputs. + arr1 = np.empty(length, dtype=dtype1) + assert arr1.flags.c_contiguous + assert arr1.flags.aligned + + values = [random.randrange(-128, 128) for _ in range(length)] + + for i, value in enumerate(values): + # Use item assignment to ensure this is not using casting: + if value < 0 and dtype1.kind == "u": + # Manually rollover unsigned integers (-1 -> int.max) + value = value + np.iinfo(dtype1).max + 1 + arr1[i] = value + + if dtype2 is None: + if dtype1.char == "?": + values = [bool(v) for v in values] + return arr1, values + + if dtype2.char == "?": + values = [bool(v) for v in values] + + arr2 = np.empty(length, dtype=dtype2) + assert arr2.flags.c_contiguous + assert arr2.flags.aligned + + for i, value in enumerate(values): + # Use item assignment to ensure this is not using casting: + if value < 0 and dtype2.kind == "u": + # Manually rollover unsigned integers (-1 -> int.max) + value = value + np.iinfo(dtype2).max + 1 + arr2[i] = value + + return arr1, arr2, values + + def get_data_variation(self, arr1, arr2, aligned=True, contig=True): + """ + Returns a copy of arr1 that may be non-contiguous or unaligned, and a + matching array for arr2 (although not a copy). + """ + if contig: + stride1 = arr1.dtype.itemsize + stride2 = arr2.dtype.itemsize + elif aligned: + stride1 = 2 * arr1.dtype.itemsize + stride2 = 2 * arr2.dtype.itemsize + else: + stride1 = arr1.dtype.itemsize + 1 + stride2 = arr2.dtype.itemsize + 1 + + max_size1 = len(arr1) * 3 * arr1.dtype.itemsize + 1 + max_size2 = len(arr2) * 3 * arr2.dtype.itemsize + 1 + from_bytes = np.zeros(max_size1, dtype=np.uint8) + to_bytes = np.zeros(max_size2, dtype=np.uint8) + + # Sanity check that the above is large enough: + assert stride1 * len(arr1) <= from_bytes.nbytes + assert stride2 * len(arr2) <= to_bytes.nbytes + + if aligned: + new1 = as_strided(from_bytes[:-1].view(arr1.dtype), + arr1.shape, (stride1,)) + new2 = as_strided(to_bytes[:-1].view(arr2.dtype), + arr2.shape, (stride2,)) + else: + new1 = as_strided(from_bytes[1:].view(arr1.dtype), + arr1.shape, (stride1,)) + new2 = as_strided(to_bytes[1:].view(arr2.dtype), + arr2.shape, (stride2,)) + + new1[...] = arr1 + + if not contig: + # Ensure we did not overwrite bytes that should not be written: + offset = arr1.dtype.itemsize if aligned else 0 + buf = from_bytes[offset::stride1].tobytes() + assert buf.count(b"\0") == len(buf) + + if contig: + assert new1.flags.c_contiguous + assert new2.flags.c_contiguous + else: + assert not new1.flags.c_contiguous + assert not new2.flags.c_contiguous + + if aligned: + assert new1.flags.aligned + assert new2.flags.aligned + else: + assert not new1.flags.aligned or new1.dtype.alignment == 1 + assert not new2.flags.aligned or new2.dtype.alignment == 1 + + return new1, new2 + + @pytest.mark.parametrize("from_Dt", simple_dtypes) + def test_simple_cancast(self, from_Dt): + for to_Dt in simple_dtypes: + cast = get_castingimpl(from_Dt, to_Dt) + + for from_dt in [from_Dt(), from_Dt().newbyteorder()]: + default = cast._resolve_descriptors((from_dt, None))[1][1] + assert default == to_Dt() + del default + + for to_dt in [to_Dt(), to_Dt().newbyteorder()]: + casting, (from_res, to_res), view_off = ( + cast._resolve_descriptors((from_dt, to_dt))) + assert type(from_res) == from_Dt + assert type(to_res) == to_Dt + if view_off is not None: + # If a view is acceptable, this is "no" casting + # and byte order must be matching. + assert casting == Casting.no | Casting.same_value + # The above table lists this as "equivalent", perhaps + # with "same_value" + v = CAST_TABLE[from_Dt][to_Dt] & ~Casting.same_value + assert Casting.equiv == v + # Note that to_res may not be the same as from_dt + assert from_res.isnative == to_res.isnative + else: + if from_Dt == to_Dt: + # Note that to_res may not be the same as from_dt + assert from_res.isnative != to_res.isnative + assert casting == CAST_TABLE[from_Dt][to_Dt] + + if from_Dt is to_Dt: + assert from_dt is from_res + assert to_dt is to_res + + @pytest.mark.filterwarnings("ignore::numpy.exceptions.ComplexWarning") + @pytest.mark.parametrize("from_dt", simple_dtype_instances()) + def test_simple_direct_casts(self, from_dt): + """ + This test checks numeric direct casts for dtypes supported also by the + struct module (plus complex). It tries to be test a wide range of + inputs, but skips over possibly undefined behaviour (e.g. int rollover). + Longdouble and CLongdouble are tested, but only using double precision. + + If this test creates issues, it should possibly just be simplified + or even removed (checking whether unaligned/non-contiguous casts give + the same results is useful, though). + """ + for to_dt in simple_dtype_instances(): + to_dt = to_dt.values[0] + cast = get_castingimpl(type(from_dt), type(to_dt)) + + # print("from_dt", from_dt, "to_dt", to_dt) + casting, (from_res, to_res), view_off = cast._resolve_descriptors( + (from_dt, to_dt)) + + if from_res is not from_dt or to_res is not to_dt: + # Do not test this case, it is handled in multiple steps, + # each of which should is tested individually. + return + + safe = casting <= Casting.safe + del from_res, to_res, casting + + arr1, arr2, values = self.get_data(from_dt, to_dt) + + # print("2", arr1, arr2, cast) + cast._simple_strided_call((arr1, arr2)) + # print("3") + + # Check via python list + assert arr2.tolist() == values + + # Check that the same results are achieved for strided loops + arr1_o, arr2_o = self.get_data_variation(arr1, arr2, True, False) + cast._simple_strided_call((arr1_o, arr2_o)) + + assert_array_equal(arr2_o, arr2) + assert arr2_o.tobytes() == arr2.tobytes() + + # Check if alignment makes a difference, but only if supported + # and only if the alignment can be wrong + if ((from_dt.alignment == 1 and to_dt.alignment == 1) or + not cast._supports_unaligned): + return + + arr1_o, arr2_o = self.get_data_variation(arr1, arr2, False, True) + cast._simple_strided_call((arr1_o, arr2_o)) + + assert_array_equal(arr2_o, arr2) + assert arr2_o.tobytes() == arr2.tobytes() + + arr1_o, arr2_o = self.get_data_variation(arr1, arr2, False, False) + cast._simple_strided_call((arr1_o, arr2_o)) + + assert_array_equal(arr2_o, arr2) + assert arr2_o.tobytes() == arr2.tobytes() + + del arr1_o, arr2_o, cast + + @pytest.mark.parametrize("from_Dt", simple_dtypes) + def test_numeric_to_times(self, from_Dt): + # We currently only implement contiguous loops, so only need to + # test those. + from_dt = from_Dt() + + time_dtypes = [np.dtype("M8"), np.dtype("M8[ms]"), np.dtype("M8[4D]"), + np.dtype("m8"), np.dtype("m8[ms]"), np.dtype("m8[4D]")] + for time_dt in time_dtypes: + cast = get_castingimpl(type(from_dt), type(time_dt)) + + casting, (from_res, to_res), view_off = cast._resolve_descriptors( + (from_dt, time_dt)) + + assert from_res is from_dt + assert to_res is time_dt + del from_res, to_res + + assert casting & CAST_TABLE[from_Dt][type(time_dt)] + assert view_off is None + + int64_dt = np.dtype(np.int64) + arr1, arr2, values = self.get_data(from_dt, int64_dt) + arr2 = arr2.view(time_dt) + arr2[...] = np.datetime64("NaT") + + if time_dt == np.dtype("M8"): + # This is a bit of a strange path, and could probably be removed + arr1[-1] = 0 # ensure at least one value is not NaT + + # The cast currently succeeds, but the values are invalid: + cast._simple_strided_call((arr1, arr2)) + with pytest.raises(ValueError): + str(arr2[-1]) # e.g. conversion to string fails + return + + cast._simple_strided_call((arr1, arr2)) + + assert [int(v) for v in arr2.tolist()] == values + + # Check that the same results are achieved for strided loops + arr1_o, arr2_o = self.get_data_variation(arr1, arr2, True, False) + cast._simple_strided_call((arr1_o, arr2_o)) + + assert_array_equal(arr2_o, arr2) + assert arr2_o.tobytes() == arr2.tobytes() + + @pytest.mark.parametrize( + ["from_dt", "to_dt", "expected_casting", "expected_view_off", + "nom", "denom"], + [("M8[ns]", None, Casting.no, 0, 1, 1), + (str(np.dtype("M8[ns]").newbyteorder()), None, + Casting.equiv, None, 1, 1), + ("M8", "M8[ms]", Casting.safe, 0, 1, 1), + # should be invalid cast: + ("M8[ms]", "M8", Casting.unsafe, None, 1, 1), + ("M8[5ms]", "M8[5ms]", Casting.no, 0, 1, 1), + ("M8[ns]", "M8[ms]", Casting.same_kind, None, 1, 10**6), + ("M8[ms]", "M8[ns]", Casting.safe, None, 10**6, 1), + ("M8[ms]", "M8[7ms]", Casting.same_kind, None, 1, 7), + ("M8[4D]", "M8[1M]", Casting.same_kind, None, None, + # give full values based on NumPy 1.19.x + [-2**63, 0, -1, 1314, -1315, 564442610]), + ("m8[ns]", None, Casting.no, 0, 1, 1), + (str(np.dtype("m8[ns]").newbyteorder()), None, + Casting.equiv, None, 1, 1), + ("m8", "m8[ms]", Casting.safe, 0, 1, 1), + # should be invalid cast: + ("m8[ms]", "m8", Casting.unsafe, None, 1, 1), + ("m8[5ms]", "m8[5ms]", Casting.no, 0, 1, 1), + ("m8[ns]", "m8[ms]", Casting.same_kind, None, 1, 10**6), + ("m8[ms]", "m8[ns]", Casting.safe, None, 10**6, 1), + ("m8[ms]", "m8[7ms]", Casting.same_kind, None, 1, 7), + ("m8[4D]", "m8[1M]", Casting.unsafe, None, None, + # give full values based on NumPy 1.19.x + [-2**63, 0, 0, 1314, -1315, 564442610])]) + def test_time_to_time(self, from_dt, to_dt, + expected_casting, expected_view_off, + nom, denom): + from_dt = np.dtype(from_dt) + if to_dt is not None: + to_dt = np.dtype(to_dt) + + # Test a few values for casting (results generated with NumPy 1.19) + values = np.array([-2**63, 1, 2**63 - 1, 10000, -10000, 2**32]) + values = values.astype(np.dtype("int64").newbyteorder(from_dt.byteorder)) + assert values.dtype.byteorder == from_dt.byteorder + assert np.isnat(values.view(from_dt)[0]) + + DType = type(from_dt) + cast = get_castingimpl(DType, DType) + casting, (from_res, to_res), view_off = cast._resolve_descriptors( + (from_dt, to_dt)) + assert from_res is from_dt + assert to_res is to_dt or to_dt is None + assert casting == expected_casting + assert view_off == expected_view_off + + if nom is not None: + expected_out = (values * nom // denom).view(to_res) + expected_out[0] = "NaT" + else: + expected_out = np.empty_like(values) + expected_out[...] = denom + expected_out = expected_out.view(to_dt) + + orig_arr = values.view(from_dt) + orig_out = np.empty_like(expected_out) + + if casting == Casting.unsafe and (to_dt == "m8" or to_dt == "M8"): # noqa: PLR1714 + # Casting from non-generic to generic units is an error and should + # probably be reported as an invalid cast earlier. + with pytest.raises(ValueError): + cast._simple_strided_call((orig_arr, orig_out)) + return + + for aligned in [True, True]: + for contig in [True, True]: + arr, out = self.get_data_variation( + orig_arr, orig_out, aligned, contig) + out[...] = 0 + cast._simple_strided_call((arr, out)) + assert_array_equal(out.view("int64"), expected_out.view("int64")) + + def string_with_modified_length(self, dtype, change_length): + fact = 1 if dtype.char == "S" else 4 + length = dtype.itemsize // fact + change_length + return np.dtype(f"{dtype.byteorder}{dtype.char}{length}") + + @pytest.mark.parametrize("other_DT", simple_dtypes) + @pytest.mark.parametrize("string_char", ["S", "U"]) + def test_string_cancast(self, other_DT, string_char): + fact = 1 if string_char == "S" else 4 + + string_DT = type(np.dtype(string_char)) + cast = get_castingimpl(other_DT, string_DT) + + other_dt = other_DT() + expected_length = get_expected_stringlength(other_dt) + string_dt = np.dtype(f"{string_char}{expected_length}") + + safety, (res_other_dt, res_dt), view_off = cast._resolve_descriptors( + (other_dt, None)) + assert res_dt.itemsize == expected_length * fact + assert safety == Casting.safe # we consider to string casts "safe" + assert view_off is None + assert isinstance(res_dt, string_DT) + + # These casts currently implement changing the string length, so + # check the cast-safety for too long/fixed string lengths: + for change_length in [-1, 0, 1]: + if change_length >= 0: + expected_safety = Casting.safe + else: + expected_safety = Casting.same_kind + + to_dt = self.string_with_modified_length(string_dt, change_length) + safety, (_, res_dt), view_off = cast._resolve_descriptors( + (other_dt, to_dt)) + assert res_dt is to_dt + assert safety == expected_safety + assert view_off is None + + # The opposite direction is always considered unsafe: + cast = get_castingimpl(string_DT, other_DT) + + safety, _, view_off = cast._resolve_descriptors((string_dt, other_dt)) + assert safety == Casting.unsafe + assert view_off is None + + cast = get_castingimpl(string_DT, other_DT) + safety, (_, res_dt), view_off = cast._resolve_descriptors( + (string_dt, None)) + assert safety == Casting.unsafe + assert view_off is None + assert other_dt is res_dt # returns the singleton for simple dtypes + + @pytest.mark.parametrize("string_char", ["S", "U"]) + @pytest.mark.parametrize("other_dt", simple_dtype_instances()) + def test_simple_string_casts_roundtrip(self, other_dt, string_char): + """ + Tests casts from and to string by checking the roundtripping property. + + The test also covers some string to string casts (but not all). + + If this test creates issues, it should possibly just be simplified + or even removed (checking whether unaligned/non-contiguous casts give + the same results is useful, though). + """ + string_DT = type(np.dtype(string_char)) + + cast = get_castingimpl(type(other_dt), string_DT) + cast_back = get_castingimpl(string_DT, type(other_dt)) + _, (res_other_dt, string_dt), _ = cast._resolve_descriptors( + (other_dt, None)) + + if res_other_dt is not other_dt: + # do not support non-native byteorder, skip test in that case + assert other_dt.byteorder != res_other_dt.byteorder + return + + orig_arr, values = self.get_data(other_dt, None) + str_arr = np.zeros(len(orig_arr), dtype=string_dt) + string_dt_short = self.string_with_modified_length(string_dt, -1) + str_arr_short = np.zeros(len(orig_arr), dtype=string_dt_short) + string_dt_long = self.string_with_modified_length(string_dt, 1) + str_arr_long = np.zeros(len(orig_arr), dtype=string_dt_long) + + assert not cast._supports_unaligned # if support is added, should test + assert not cast_back._supports_unaligned + + for contig in [True, False]: + other_arr, str_arr = self.get_data_variation( + orig_arr, str_arr, True, contig) + _, str_arr_short = self.get_data_variation( + orig_arr, str_arr_short.copy(), True, contig) + _, str_arr_long = self.get_data_variation( + orig_arr, str_arr_long, True, contig) + + cast._simple_strided_call((other_arr, str_arr)) + + cast._simple_strided_call((other_arr, str_arr_short)) + assert_array_equal(str_arr.astype(string_dt_short), str_arr_short) + + cast._simple_strided_call((other_arr, str_arr_long)) + assert_array_equal(str_arr, str_arr_long) + + if other_dt.kind == "b": + # Booleans do not roundtrip + continue + + other_arr[...] = 0 + cast_back._simple_strided_call((str_arr, other_arr)) + assert_array_equal(orig_arr, other_arr) + + other_arr[...] = 0 + cast_back._simple_strided_call((str_arr_long, other_arr)) + assert_array_equal(orig_arr, other_arr) + + @pytest.mark.parametrize("other_dt", ["S8", "U8"]) + @pytest.mark.parametrize("string_char", ["S", "U"]) + def test_string_to_string_cancast(self, other_dt, string_char): + other_dt = np.dtype(other_dt) + + fact = 1 if string_char == "S" else 4 + div = 1 if other_dt.char == "S" else 4 + + string_DT = type(np.dtype(string_char)) + cast = get_castingimpl(type(other_dt), string_DT) + + expected_length = other_dt.itemsize // div + string_dt = np.dtype(f"{string_char}{expected_length}") + + safety, (res_other_dt, res_dt), view_off = cast._resolve_descriptors( + (other_dt, None)) + assert res_dt.itemsize == expected_length * fact + assert isinstance(res_dt, string_DT) + + expected_view_off = None + if other_dt.char == string_char: + if other_dt.isnative: + expected_safety = Casting.no + expected_view_off = 0 + else: + expected_safety = Casting.equiv + elif string_char == "U": + expected_safety = Casting.safe + else: + expected_safety = Casting.unsafe + + assert view_off == expected_view_off + assert expected_safety == safety + + for change_length in [-1, 0, 1]: + to_dt = self.string_with_modified_length(string_dt, change_length) + safety, (_, res_dt), view_off = cast._resolve_descriptors( + (other_dt, to_dt)) + + assert res_dt is to_dt + if change_length <= 0: + assert view_off == expected_view_off + else: + assert view_off is None + if expected_safety == Casting.unsafe: + assert safety == expected_safety + elif change_length < 0: + assert safety == Casting.same_kind + elif change_length == 0: + assert safety == expected_safety + elif change_length > 0: + assert safety == Casting.safe + + @pytest.mark.parametrize("order1", [">", "<"]) + @pytest.mark.parametrize("order2", [">", "<"]) + def test_unicode_byteswapped_cast(self, order1, order2): + # Very specific tests (not using the castingimpl directly) + # that tests unicode bytedwaps including for unaligned array data. + dtype1 = np.dtype(f"{order1}U30") + dtype2 = np.dtype(f"{order2}U30") + data1 = np.empty(30 * 4 + 1, dtype=np.uint8)[1:].view(dtype1) + data2 = np.empty(30 * 4 + 1, dtype=np.uint8)[1:].view(dtype2) + if dtype1.alignment != 1: + # alignment should always be >1, but skip the check if not + assert not data1.flags.aligned + assert not data2.flags.aligned + + element = "this is a ünicode string‽" + data1[()] = element + # Test both `data1` and `data1.copy()` (which should be aligned) + for data in [data1, data1.copy()]: + data2[...] = data1 + assert data2[()] == element + assert data2.copy()[()] == element + + def test_void_to_string_special_case(self): + # Cover a small special case in void to string casting that could + # probably just as well be turned into an error (compare + # `test_object_to_parametric_internal_error` below). + assert np.array([], dtype="V5").astype("S").dtype.itemsize == 5 + assert np.array([], dtype="V5").astype("U").dtype.itemsize == 4 * 5 + + def test_object_to_parametric_internal_error(self): + # We reject casting from object to a parametric type, without + # figuring out the correct instance first. + object_dtype = type(np.dtype(object)) + other_dtype = type(np.dtype(str)) + cast = get_castingimpl(object_dtype, other_dtype) + with pytest.raises(TypeError, + match="casting from object to the parametric DType"): + cast._resolve_descriptors((np.dtype("O"), None)) + + @pytest.mark.parametrize("dtype", simple_dtype_instances()) + def test_object_and_simple_resolution(self, dtype): + # Simple test to exercise the cast when no instance is specified + object_dtype = type(np.dtype(object)) + cast = get_castingimpl(object_dtype, type(dtype)) + + safety, (_, res_dt), view_off = cast._resolve_descriptors( + (np.dtype("O"), dtype)) + assert safety == Casting.unsafe + assert view_off is None + assert res_dt is dtype + + safety, (_, res_dt), view_off = cast._resolve_descriptors( + (np.dtype("O"), None)) + assert safety == Casting.unsafe + assert view_off is None + assert res_dt == dtype.newbyteorder("=") + + @pytest.mark.parametrize("dtype", simple_dtype_instances()) + def test_simple_to_object_resolution(self, dtype): + # Simple test to exercise the cast when no instance is specified + object_dtype = type(np.dtype(object)) + cast = get_castingimpl(type(dtype), object_dtype) + + safety, (_, res_dt), view_off = cast._resolve_descriptors( + (dtype, None)) + assert safety == Casting.safe + assert view_off is None + assert res_dt is np.dtype("O") + + @pytest.mark.parametrize("casting", ["no", "unsafe"]) + def test_void_and_structured_with_subarray(self, casting): + # test case corresponding to gh-19325 + dtype = np.dtype([("foo", " casts may succeed or fail, but a NULL'ed array must + # behave the same as one filled with None's. + arr_normal = np.array([None] * 5) + arr_NULLs = np.empty_like(arr_normal) + ctypes.memset(arr_NULLs.ctypes.data, 0, arr_NULLs.nbytes) + # If the check fails (maybe it should) the test would lose its purpose: + assert arr_NULLs.tobytes() == b"\x00" * arr_NULLs.nbytes + + try: + expected = arr_normal.astype(dtype) + except TypeError: + with pytest.raises(TypeError): + arr_NULLs.astype(dtype) + else: + assert_array_equal(expected, arr_NULLs.astype(dtype)) + + @pytest.mark.parametrize("dtype", + np.typecodes["AllInteger"] + np.typecodes["AllFloat"]) + def test_nonstandard_bool_to_other(self, dtype): + # simple test for casting bool_ to numeric types, which should not + # expose the detail that NumPy bools can sometimes take values other + # than 0 and 1. See also gh-19514. + nonstandard_bools = np.array([0, 3, -7], dtype=np.int8).view(bool) + res = nonstandard_bools.astype(dtype) + expected = [0, 1, 1] + assert_array_equal(res, expected) + + @pytest.mark.parametrize("to_dtype", + np.typecodes["AllInteger"] + np.typecodes["AllFloat"]) + @pytest.mark.parametrize("from_dtype", + np.typecodes["AllInteger"] + np.typecodes["AllFloat"]) + @pytest.mark.filterwarnings("ignore::numpy.exceptions.ComplexWarning") + def test_same_value_overflow(self, from_dtype, to_dtype): + if from_dtype == to_dtype: + return + top1 = 0 + top2 = 0 + try: + top1 = np.iinfo(from_dtype).max + except ValueError: + top1 = np.finfo(from_dtype).max + try: + top2 = np.iinfo(to_dtype).max + except ValueError: + top2 = np.finfo(to_dtype).max + # No need to test if top2 > top1, since the test will also do the + # reverse dtype matching. Catch then warning if the comparison warns, + # i.e. np.int16(65535) < np.float16(6.55e4) + with warnings.catch_warnings(record=True): + warnings.simplefilter("always", RuntimeWarning) + if top2 >= top1: + # will be tested when the dtypes are reversed + return + # Happy path + arr1 = np.array([0] * 10, dtype=from_dtype) + arr2 = np.array([0] * 10, dtype=to_dtype) + arr1_astype = arr1.astype(to_dtype, casting='same_value') + assert_equal(arr1_astype, arr2, strict=True) + # Make it overflow, both aligned and unaligned + arr1[0] = top1 + aligned = np.empty(arr1.itemsize * arr1.size + 1, 'uint8') + unaligned = aligned[1:].view(arr1.dtype) + unaligned[:] = arr1 + with pytest.raises(ValueError): + # Casting float to float with overflow should raise + # RuntimeWarning (fperror) + # Casting float to int with overflow sometimes raises + # RuntimeWarning (fperror) + # Casting with overflow and 'same_value', should raise ValueError + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter("always", RuntimeWarning) + arr1.astype(to_dtype, casting='same_value') + assert len(w) < 2 + with pytest.raises(ValueError): + # again, unaligned + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter("always", RuntimeWarning) + unaligned.astype(to_dtype, casting='same_value') + assert len(w) < 2 + + @pytest.mark.parametrize("to_dtype", + np.typecodes["AllInteger"]) + @pytest.mark.parametrize("from_dtype", + np.typecodes["AllFloat"]) + @pytest.mark.filterwarnings("ignore::RuntimeWarning") + def test_same_value_float_to_int(self, from_dtype, to_dtype): + # Should not raise, since the values can round trip + arr1 = np.arange(10, dtype=from_dtype) + aligned = np.empty(arr1.itemsize * arr1.size + 1, 'uint8') + unaligned = aligned[1:].view(arr1.dtype) + unaligned[:] = arr1 + arr2 = np.arange(10, dtype=to_dtype) + assert_array_equal(arr1.astype(to_dtype, casting='same_value'), arr2) + assert_array_equal(unaligned.astype(to_dtype, casting='same_value'), arr2) + + # Should raise, since values cannot round trip. Might warn too about + # FPE errors + arr1_66 = arr1 + 0.666 + unaligned_66 = unaligned + 0.66 + with pytest.raises(ValueError): + arr1_66.astype(to_dtype, casting='same_value') + with pytest.raises(ValueError): + unaligned_66.astype(to_dtype, casting='same_value') + + @pytest.mark.parametrize("to_dtype", + np.typecodes["AllInteger"]) + @pytest.mark.parametrize("from_dtype", + np.typecodes["AllFloat"]) + @pytest.mark.filterwarnings("ignore::RuntimeWarning") + def test_same_value_float_to_int_scalar(self, from_dtype, to_dtype): + # Should not raise, since the values can round trip + s1 = np.array(10, dtype=from_dtype) + assert s1.astype(to_dtype, casting='same_value') == 10 + + # Should raise, since values cannot round trip + s1_66 = s1 + 0.666 + with pytest.raises(ValueError): + s1_66.astype(to_dtype, casting='same_value') + + @pytest.mark.parametrize("value", [np.nan, np.inf, -np.inf]) + @pytest.mark.filterwarnings("ignore::numpy.exceptions.ComplexWarning") + @pytest.mark.filterwarnings("ignore::RuntimeWarning") + def test_same_value_naninf(self, value): + # These work, but may trigger FPE warnings on macOS + np.array([value], dtype=np.half).astype(np.cdouble, casting='same_value') + np.array([value], dtype=np.half).astype(np.double, casting='same_value') + np.array([value], dtype=np.float32).astype(np.cdouble, casting='same_value') + np.array([value], dtype=np.float32).astype(np.double, casting='same_value') + np.array([value], dtype=np.float32).astype(np.half, casting='same_value') + np.array([value], dtype=np.complex64).astype(np.half, casting='same_value') + # These fail + with pytest.raises(ValueError): + np.array([value], dtype=np.half).astype(np.int64, casting='same_value') + with pytest.raises(ValueError): + np.array([value], dtype=np.complex64).astype(np.int64, casting='same_value') + with pytest.raises(ValueError): + np.array([value], dtype=np.float32).astype(np.int64, casting='same_value') + + @pytest.mark.filterwarnings("ignore::numpy.exceptions.ComplexWarning") + def test_same_value_complex(self): + arr = np.array([complex(1, 1)], dtype=np.cdouble) + # This works + arr.astype(np.complex64, casting='same_value') + # Casting with a non-zero imag part fails + with pytest.raises(ValueError): + arr.astype(np.float32, casting='same_value') + + def test_same_value_scalar(self): + i = np.array(123, dtype=np.int64) + f = np.array(123, dtype=np.float64) + assert i.astype(np.float64, casting='same_value') == f + assert f.astype(np.int64, casting='same_value') == f diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_conversion_utils.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_conversion_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..067c2973c592552f787692d674fdec1608861140 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_conversion_utils.py @@ -0,0 +1,209 @@ +""" +Tests for numpy/_core/src/multiarray/conversion_utils.c +""" +import re + +import pytest + +import numpy._core._multiarray_tests as mt +from numpy._core.multiarray import CLIP, RAISE, WRAP +from numpy.testing import assert_raises + + +class StringConverterTestCase: + allow_bytes = True + case_insensitive = True + exact_match = False + warn = True + + def _check_value_error(self, val): + pattern = fr'\(got {re.escape(repr(val))}\)' + with pytest.raises(ValueError, match=pattern) as exc: + self.conv(val) + + def _check_conv_assert_warn(self, val, expected): + if self.warn: + with assert_raises(ValueError) as exc: + assert self.conv(val) == expected + else: + assert self.conv(val) == expected + + def _check(self, val, expected): + """Takes valid non-deprecated inputs for converters, + runs converters on inputs, checks correctness of outputs, + warnings and errors""" + assert self.conv(val) == expected + + if self.allow_bytes: + assert self.conv(val.encode('ascii')) == expected + else: + with pytest.raises(TypeError): + self.conv(val.encode('ascii')) + + if len(val) != 1: + if self.exact_match: + self._check_value_error(val[:1]) + self._check_value_error(val + '\0') + else: + self._check_conv_assert_warn(val[:1], expected) + + if self.case_insensitive: + if val != val.lower(): + self._check_conv_assert_warn(val.lower(), expected) + if val != val.upper(): + self._check_conv_assert_warn(val.upper(), expected) + else: + if val != val.lower(): + self._check_value_error(val.lower()) + if val != val.upper(): + self._check_value_error(val.upper()) + + def test_wrong_type(self): + # common cases which apply to all the below + with pytest.raises(TypeError): + self.conv({}) + with pytest.raises(TypeError): + self.conv([]) + + def test_wrong_value(self): + # nonsense strings + self._check_value_error('') + self._check_value_error('\N{greek small letter pi}') + + if self.allow_bytes: + self._check_value_error(b'') + # bytes which can't be converted to strings via utf8 + self._check_value_error(b"\xFF") + if self.exact_match: + self._check_value_error("there's no way this is supported") + + +class TestByteorderConverter(StringConverterTestCase): + """ Tests of PyArray_ByteorderConverter """ + conv = mt.run_byteorder_converter + warn = False + + def test_valid(self): + for s in ['big', '>']: + self._check(s, 'NPY_BIG') + for s in ['little', '<']: + self._check(s, 'NPY_LITTLE') + for s in ['native', '=']: + self._check(s, 'NPY_NATIVE') + for s in ['ignore', '|']: + self._check(s, 'NPY_IGNORE') + for s in ['swap']: + self._check(s, 'NPY_SWAP') + + +class TestSortkindConverter(StringConverterTestCase): + """ Tests of PyArray_SortkindConverter """ + conv = mt.run_sortkind_converter + warn = False + + def test_valid(self): + self._check('quicksort', 'NPY_QUICKSORT') + self._check('heapsort', 'NPY_HEAPSORT') + self._check('mergesort', 'NPY_STABLESORT') # alias + self._check('stable', 'NPY_STABLESORT') + + +class TestSelectkindConverter(StringConverterTestCase): + """ Tests of PyArray_SelectkindConverter """ + conv = mt.run_selectkind_converter + case_insensitive = False + exact_match = True + + def test_valid(self): + self._check('introselect', 'NPY_INTROSELECT') + + +class TestSearchsideConverter(StringConverterTestCase): + """ Tests of PyArray_SearchsideConverter """ + conv = mt.run_searchside_converter + + def test_valid(self): + self._check('left', 'NPY_SEARCHLEFT') + self._check('right', 'NPY_SEARCHRIGHT') + + +class TestOrderConverter(StringConverterTestCase): + """ Tests of PyArray_OrderConverter """ + conv = mt.run_order_converter + warn = False + + def test_valid(self): + self._check('c', 'NPY_CORDER') + self._check('f', 'NPY_FORTRANORDER') + self._check('a', 'NPY_ANYORDER') + self._check('k', 'NPY_KEEPORDER') + + def test_flatten_invalid_order(self): + # invalid after gh-14596 + with pytest.raises(ValueError): + self.conv('Z') + for order in [False, True, 0, 8]: + with pytest.raises(TypeError): + self.conv(order) + + +class TestClipmodeConverter(StringConverterTestCase): + """ Tests of PyArray_ClipmodeConverter """ + conv = mt.run_clipmode_converter + + def test_valid(self): + self._check('clip', 'NPY_CLIP') + self._check('wrap', 'NPY_WRAP') + self._check('raise', 'NPY_RAISE') + + # integer values allowed here + assert self.conv(CLIP) == 'NPY_CLIP' + assert self.conv(WRAP) == 'NPY_WRAP' + assert self.conv(RAISE) == 'NPY_RAISE' + + +class TestCastingConverter(StringConverterTestCase): + """ Tests of PyArray_CastingConverter """ + conv = mt.run_casting_converter + case_insensitive = False + exact_match = True + + def test_valid(self): + self._check("no", "NPY_NO_CASTING") + self._check("equiv", "NPY_EQUIV_CASTING") + self._check("safe", "NPY_SAFE_CASTING") + self._check("unsafe", "NPY_UNSAFE_CASTING") + self._check("same_kind", "NPY_SAME_KIND_CASTING") + + def test_invalid(self): + # Currently, 'same_value' is supported only in ndarray.astype + self._check_value_error("same_value") + +class TestIntpConverter: + """ Tests of PyArray_IntpConverter """ + conv = mt.run_intp_converter + + def test_basic(self): + assert self.conv(1) == (1,) + assert self.conv((1, 2)) == (1, 2) + assert self.conv([1, 2]) == (1, 2) + assert self.conv(()) == () + + def test_none(self): + with pytest.raises(TypeError): + assert self.conv(None) == () + + def test_float(self): + with pytest.raises(TypeError): + self.conv(1.0) + with pytest.raises(TypeError): + self.conv([1, 1.0]) + + def test_too_large(self): + with pytest.raises(ValueError): + self.conv(2**64) + + def test_too_many_dims(self): + assert self.conv([1] * 64) == (1,) * 64 + with pytest.raises(ValueError): + self.conv([1] * 65) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_cpu_dispatcher.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_cpu_dispatcher.py new file mode 100644 index 0000000000000000000000000000000000000000..01fd53a3dbd09c4b0ab76eab2c9c4877dbf5340b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_cpu_dispatcher.py @@ -0,0 +1,48 @@ +from numpy._core import _umath_tests +from numpy._core._multiarray_umath import ( + __cpu_baseline__, + __cpu_dispatch__, + __cpu_features__, +) +from numpy.testing import assert_equal + + +def test_dispatcher(): + """ + Testing the utilities of the CPU dispatcher + """ + targets = ( + "X86_V2", "X86_V3", + "VSX", "VSX2", "VSX3", + "NEON", "ASIMD", "ASIMDHP", + "VX", "VXE", "LSX", "RVV" + ) + highest_sfx = "" # no suffix for the baseline + all_sfx = [] + for feature in reversed(targets): + # skip baseline features, by the default `CCompilerOpt` do not generate separated objects + # for the baseline, just one object combined all of them via 'baseline' option + # within the configuration statements. + if feature in __cpu_baseline__: + continue + # check compiler and running machine support + if feature not in __cpu_dispatch__ or not __cpu_features__[feature]: + continue + + if not highest_sfx: + highest_sfx = "_" + feature + all_sfx.append("func" + "_" + feature) + + test = _umath_tests.test_dispatch() + assert_equal(test["func"], "func" + highest_sfx) + assert_equal(test["var"], "var" + highest_sfx) + + if highest_sfx: + assert_equal(test["func_xb"], "func" + highest_sfx) + assert_equal(test["var_xb"], "var" + highest_sfx) + else: + assert_equal(test["func_xb"], "nobase") + assert_equal(test["var_xb"], "nobase") + + all_sfx.append("func") # add the baseline + assert_equal(test["all"], all_sfx) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_cpu_features.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_cpu_features.py new file mode 100644 index 0000000000000000000000000000000000000000..1a10863ea955fa5fbfa2239b0a2f34b51c79383f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_cpu_features.py @@ -0,0 +1,482 @@ +import os +import pathlib +import platform +import re +import subprocess +import sys + +import pytest + +from numpy._core._multiarray_umath import ( + __cpu_baseline__, + __cpu_dispatch__, + __cpu_features__, +) + + +def assert_features_equal(actual, desired, fname): + __tracebackhide__ = True # Hide traceback for py.test + actual, desired = str(actual), str(desired) + if actual == desired: + return + detected = str(__cpu_features__).replace("'", "") + try: + with open("/proc/cpuinfo") as fd: + cpuinfo = fd.read(2048) + except Exception as err: + cpuinfo = str(err) + + try: + import subprocess + auxv = subprocess.check_output(['/bin/true'], env={"LD_SHOW_AUXV": "1"}) + auxv = auxv.decode() + except Exception as err: + auxv = str(err) + + import textwrap + error_report = textwrap.indent( +f""" +########################################### +### Extra debugging information +########################################### +------------------------------------------- +--- NumPy Detections +------------------------------------------- +{detected} +------------------------------------------- +--- SYS / CPUINFO +------------------------------------------- +{cpuinfo}.... +------------------------------------------- +--- SYS / AUXV +------------------------------------------- +{auxv} +""", prefix='\r') + + raise AssertionError(( + "Failure Detection\n" + " NAME: '%s'\n" + " ACTUAL: %s\n" + " DESIRED: %s\n" + "%s" + ) % (fname, actual, desired, error_report)) + +def _text_to_list(txt): + out = txt.strip("][\n").replace("'", "").split(', ') + return None if out[0] == "" else out + +class AbstractTest: + features = [] + features_groups = {} + features_map = {} + features_flags = set() + + def load_flags(self): + # a hook + pass + + def test_features(self): + self.load_flags() + for gname, features in self.features_groups.items(): + test_features = [self.cpu_have(f) for f in features] + assert_features_equal(__cpu_features__.get(gname), all(test_features), gname) + + for feature_name in self.features: + cpu_have = self.cpu_have(feature_name) + npy_have = __cpu_features__.get(feature_name) + assert_features_equal(npy_have, cpu_have, feature_name) + + def cpu_have(self, feature_name): + map_names = self.features_map.get(feature_name, feature_name) + if isinstance(map_names, str): + return map_names in self.features_flags + return any(f in self.features_flags for f in map_names) + + def load_flags_cpuinfo(self, magic_key): + self.features_flags = self.get_cpuinfo_item(magic_key) + + def get_cpuinfo_item(self, magic_key): + values = set() + with open('/proc/cpuinfo') as fd: + for line in fd: + if not line.startswith(magic_key): + continue + flags_value = [s.strip() for s in line.split(':', 1)] + if len(flags_value) == 2: + values = values.union(flags_value[1].upper().split()) + return values + + def load_flags_auxv(self): + auxv = subprocess.check_output(['/bin/true'], env={"LD_SHOW_AUXV": "1"}) + for at in auxv.split(b'\n'): + if not at.startswith(b"AT_HWCAP"): + continue + hwcap_value = [s.strip() for s in at.split(b':', 1)] + if len(hwcap_value) == 2: + self.features_flags = self.features_flags.union( + hwcap_value[1].upper().decode().split() + ) + +@pytest.mark.skipif( + sys.platform == 'emscripten', + reason=( + "The subprocess module is not available on WASM platforms and" + " therefore this test class cannot be properly executed." + ), +) +@pytest.mark.thread_unsafe(reason="setup & tmp_path_factory threads-unsafe, modifies environment variables") +class TestEnvPrivation: + cwd = pathlib.Path(__file__).parent.resolve() + env = os.environ.copy() + _enable = os.environ.pop('NPY_ENABLE_CPU_FEATURES', None) + _disable = os.environ.pop('NPY_DISABLE_CPU_FEATURES', None) + SUBPROCESS_ARGS = {"cwd": cwd, "capture_output": True, "text": True, "check": True} + unavailable_feats = [ + feat for feat in __cpu_dispatch__ if not __cpu_features__[feat] + ] + UNAVAILABLE_FEAT = ( + None if len(unavailable_feats) == 0 + else unavailable_feats[0] + ) + BASELINE_FEAT = None if len(__cpu_baseline__) == 0 else __cpu_baseline__[0] + SCRIPT = """ +def main(): + from numpy._core._multiarray_umath import ( + __cpu_features__, + __cpu_dispatch__ + ) + + detected = [feat for feat in __cpu_dispatch__ if __cpu_features__[feat]] + print(detected) + +if __name__ == "__main__": + main() + """ + + @pytest.fixture(autouse=True) + def setup_class(self, tmp_path_factory): + file = tmp_path_factory.mktemp("runtime_test_script") + file /= "_runtime_detect.py" + file.write_text(self.SCRIPT) + self.file = file + + def _run(self): + return subprocess.run( + [sys.executable, self.file], + env=self.env, + **self.SUBPROCESS_ARGS, + ) + + # Helper function mimicking pytest.raises for subprocess call + def _expect_error( + self, + msg, + err_type, + no_error_msg="Failed to generate error" + ): + try: + self._run() + except subprocess.CalledProcessError as e: + assertion_message = f"Expected: {msg}\nGot: {e.stderr}" + assert re.search(msg, e.stderr), assertion_message + + assertion_message = ( + f"Expected error of type: {err_type}; see full " + f"error:\n{e.stderr}" + ) + assert re.search(err_type, e.stderr), assertion_message + else: + assert False, no_error_msg + + def setup_method(self): + """Ensure that the environment is reset""" + self.env = os.environ.copy() + + def test_runtime_feature_selection(self): + """ + Ensure that when selecting `NPY_ENABLE_CPU_FEATURES`, only the + features exactly specified are dispatched. + """ + + # Capture runtime-enabled features + out = self._run() + non_baseline_features = _text_to_list(out.stdout) + + if non_baseline_features is None: + pytest.skip( + "No dispatchable features outside of baseline detected." + ) + feature = non_baseline_features[0] + + # Capture runtime-enabled features when `NPY_ENABLE_CPU_FEATURES` is + # specified + self.env['NPY_ENABLE_CPU_FEATURES'] = feature + out = self._run() + enabled_features = _text_to_list(out.stdout) + + # Ensure that only one feature is enabled, and it is exactly the one + # specified by `NPY_ENABLE_CPU_FEATURES` + assert set(enabled_features) == {feature} + + if len(non_baseline_features) < 2: + pytest.skip("Only one non-baseline feature detected.") + # Capture runtime-enabled features when `NPY_ENABLE_CPU_FEATURES` is + # specified + self.env['NPY_ENABLE_CPU_FEATURES'] = ",".join(non_baseline_features) + out = self._run() + enabled_features = _text_to_list(out.stdout) + + # Ensure that both features are enabled, and they are exactly the ones + # specified by `NPY_ENABLE_CPU_FEATURES` + assert set(enabled_features) == set(non_baseline_features) + + @pytest.mark.parametrize("enabled, disabled", + [ + ("feature", "feature"), + ("feature", "same"), + ]) + def test_both_enable_disable_set(self, enabled, disabled): + """ + Ensure that when both environment variables are set then an + ImportError is thrown + """ + self.env['NPY_ENABLE_CPU_FEATURES'] = enabled + self.env['NPY_DISABLE_CPU_FEATURES'] = disabled + msg = "Both NPY_DISABLE_CPU_FEATURES and NPY_ENABLE_CPU_FEATURES" + err_type = "ImportError" + self._expect_error(msg, err_type) + + @pytest.mark.skipif( + not __cpu_dispatch__, + reason=( + "NPY_*_CPU_FEATURES only parsed if " + "`__cpu_dispatch__` is non-empty" + ) + ) + @pytest.mark.parametrize("action", ["ENABLE", "DISABLE"]) + def test_variable_too_long(self, action): + """ + Test that an error is thrown if the environment variables are too long + to be processed. Current limit is 1024, but this may change later. + """ + MAX_VAR_LENGTH = 1024 + # Actual length is MAX_VAR_LENGTH + 1 due to null-termination + self.env[f'NPY_{action}_CPU_FEATURES'] = "t" * MAX_VAR_LENGTH + msg = ( + f"Length of environment variable 'NPY_{action}_CPU_FEATURES' is " + f"{MAX_VAR_LENGTH + 1}, only {MAX_VAR_LENGTH} accepted" + ) + err_type = "RuntimeError" + self._expect_error(msg, err_type) + + @pytest.mark.skipif( + not __cpu_dispatch__, + reason=( + "NPY_*_CPU_FEATURES only parsed if " + "`__cpu_dispatch__` is non-empty" + ) + ) + def test_impossible_feature_disable(self): + """ + Test that a RuntimeError is thrown if an impossible feature-disabling + request is made. This includes disabling a baseline feature. + """ + + if self.BASELINE_FEAT is None: + pytest.skip("There are no unavailable features to test with") + bad_feature = self.BASELINE_FEAT + self.env['NPY_DISABLE_CPU_FEATURES'] = bad_feature + msg = ( + f"You cannot disable CPU feature '{bad_feature}', since it is " + "part of the baseline optimizations" + ) + err_type = "RuntimeError" + self._expect_error(msg, err_type) + + def test_impossible_feature_enable(self): + """ + Test that a RuntimeError is thrown if an impossible feature-enabling + request is made. This includes enabling a feature not supported by the + machine, or disabling a baseline optimization. + """ + + if self.UNAVAILABLE_FEAT is None: + pytest.skip("There are no unavailable features to test with") + bad_feature = self.UNAVAILABLE_FEAT + self.env['NPY_ENABLE_CPU_FEATURES'] = bad_feature + msg = ( + f"You cannot enable CPU features \\({bad_feature}\\), since " + "they are not supported by your machine." + ) + err_type = "RuntimeError" + self._expect_error(msg, err_type) + + # Ensure that it fails even when providing garbage in addition + feats = f"{bad_feature}, Foobar" + self.env['NPY_ENABLE_CPU_FEATURES'] = feats + msg = ( + f"You cannot enable CPU features \\({bad_feature}\\), since they " + "are not supported by your machine." + ) + self._expect_error(msg, err_type) + + if self.BASELINE_FEAT is not None: + # Ensure that only the bad feature gets reported + feats = f"{bad_feature}, {self.BASELINE_FEAT}" + self.env['NPY_ENABLE_CPU_FEATURES'] = feats + msg = ( + f"You cannot enable CPU features \\({bad_feature}\\), since " + "they are not supported by your machine." + ) + self._expect_error(msg, err_type) + + +is_linux = sys.platform.startswith('linux') +is_cygwin = sys.platform.startswith('cygwin') +machine = platform.machine() +is_x86 = re.match(r"^(amd64|x86|i386|i686)", machine, re.IGNORECASE) +@pytest.mark.skipif( + not (is_linux or is_cygwin) or not is_x86, reason="Only for Linux and x86" +) +class Test_X86_Features(AbstractTest): + features = [] + + features_groups = { + "X86_V2": [ + "SSE", "SSE2", "SSE3", "SSSE3", "SSE41", "SSE42", + "POPCNT", "LAHF", "CX16" + ], + } + features_groups["X86_V3"] = features_groups["X86_V2"] + [ + "AVX", "AVX2", "FMA3", "BMI", "BMI2", + "LZCNT", "F16C", "MOVBE" + ] + features_groups["X86_V4"] = features_groups["X86_V3"] + [ + "AVX512F", "AVX512CD", "AVX512BW", "AVX512DQ", "AVX512VL" + ] + features_groups["AVX512_ICL"] = features_groups["X86_V4"] + [ + "AVX512IFMA", "AVX512VBMI", "AVX512VNNI", + "AVX512VBMI2", "AVX512BITALG", "AVX512VPOPCNTDQ", + "VAES", "VPCLMULQDQ", "GFNI" + ] + features_groups["AVX512_SPR"] = features_groups["AVX512_ICL"] + ["AVX512FP16", "AVX512BF16"] + + features_map = { + "SSE3": "PNI", "SSE41": "SSE4_1", "SSE42": "SSE4_2", "FMA3": "FMA", + "BMI": "BMI1", "LZCNT": "ABM", "LAHF": "LAHF_LM", + "AVX512VNNI": "AVX512_VNNI", "AVX512BITALG": "AVX512_BITALG", + "AVX512VBMI2": "AVX512_VBMI2", "AVX5124FMAPS": "AVX512_4FMAPS", + "AVX5124VNNIW": "AVX512_4VNNIW", "AVX512VPOPCNTDQ": "AVX512_VPOPCNTDQ", + "AVX512FP16": "AVX512_FP16", "AVX512BF16": "AVX512_BF16" + } + + def load_flags(self): + self.load_flags_cpuinfo("flags") + + +is_power = re.match(r"^(powerpc|ppc)64", machine, re.IGNORECASE) +@pytest.mark.skipif(not is_linux or not is_power, reason="Only for Linux and Power") +class Test_POWER_Features(AbstractTest): + features = ["VSX", "VSX2", "VSX3", "VSX4"] + features_map = { + "VSX": "ARCH_2_06", + "VSX2": "ARCH_2_07", + "VSX3": "ARCH_3_00", + "VSX4": "ARCH_3_1B" + } + + def load_flags(self): + self.load_flags_auxv() + platform = self._get_platform() + + if platform: + power_match = re.search(r'power(\d+)', platform, re.IGNORECASE) + if power_match: + power_gen = int(power_match.group(1)) + if power_gen >= 7: + self.features_flags.add("ARCH_2_06") + if power_gen >= 8: + self.features_flags.add("ARCH_2_07") + if power_gen >= 9: + self.features_flags.add("ARCH_3_00") + if power_gen >= 10: + self.features_flags.add("ARCH_3_1B") + + def _get_platform(self): + """Get the AT_PLATFORM value from AUXV""" + try: + auxv = subprocess.check_output(['/bin/true'], env={"LD_SHOW_AUXV": "1"}) + for line in auxv.split(b'\n'): + if line.startswith(b'AT_PLATFORM'): + parts = line.split(b':', 1) + if len(parts) == 2: + return parts[1].strip().decode().lower() + except Exception: + pass + return None + + +is_zarch = re.match(r"^(s390x)", machine, re.IGNORECASE) +@pytest.mark.skipif(not is_linux or not is_zarch, + reason="Only for Linux and IBM Z") +class Test_ZARCH_Features(AbstractTest): + features = ["VX", "VXE", "VXE2"] + + def load_flags(self): + self.load_flags_auxv() + + +is_arm = re.match(r"^(arm|aarch64)", machine, re.IGNORECASE) +@pytest.mark.skipif(not is_linux or not is_arm, reason="Only for Linux and ARM") +class Test_ARM_Features(AbstractTest): + features = [ + "SVE", "NEON", "ASIMD", "FPHP", "ASIMDHP", "ASIMDDP", "ASIMDFHM" + ] + features_groups = { + "NEON_FP16": ["NEON", "HALF"], + "NEON_VFPV4": ["NEON", "VFPV4"], + } + + def load_flags(self): + self.load_flags_cpuinfo("Features") + arch = self.get_cpuinfo_item("CPU architecture") + # in case of mounting virtual filesystem of aarch64 kernel without linux32 + is_rootfs_v8 = ( + not re.match(r"^armv[0-9]+l$", machine) and + (int('0' + next(iter(arch))) > 7 if arch else 0) + ) + if re.match(r"^(aarch64|AARCH64)", machine) or is_rootfs_v8: + self.features_map = { + "NEON": "ASIMD", "HALF": "ASIMD", "VFPV4": "ASIMD" + } + else: + self.features_map = { + # ELF auxiliary vector and /proc/cpuinfo on Linux kernel(armv8 aarch32) + # doesn't provide information about ASIMD, so we assume that ASIMD is supported + # if the kernel reports any one of the following ARM8 features. + "ASIMD": ("AES", "SHA1", "SHA2", "PMULL", "CRC32") + } + + +is_loongarch = re.match(r"^(loongarch)", machine, re.IGNORECASE) +@pytest.mark.skipif(not is_linux or not is_loongarch, reason="Only for Linux and LoongArch") +class Test_LOONGARCH_Features(AbstractTest): + features = ["LSX"] + + def load_flags(self): + self.load_flags_cpuinfo("Features") + + +is_riscv = re.match(r"^(riscv)", machine, re.IGNORECASE) +@pytest.mark.skipif(not is_linux or not is_riscv, reason="Only for Linux and RISC-V") +class Test_RISCV_Features(AbstractTest): + features = ["RVV"] + + def load_flags(self): + self.load_flags_auxv() + if not self.features_flags: + # Let the test fail and dump if we cannot read HWCAP. + return + hwcap = int(next(iter(self.features_flags)), 16) + if hwcap & (1 << 21): # HWCAP_RISCV_V + self.features_flags.add("RVV") diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_custom_dtypes.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_custom_dtypes.py new file mode 100644 index 0000000000000000000000000000000000000000..2acb4adf4c7c02794910b21f6f00322f55c6d08f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_custom_dtypes.py @@ -0,0 +1,393 @@ +from tempfile import NamedTemporaryFile + +import pytest + +import numpy as np +from numpy._core._multiarray_umath import ( + _discover_array_parameters as discover_array_params, + _get_sfloat_dtype, +) +from numpy.testing import assert_array_equal + +SF = _get_sfloat_dtype() + + +class TestSFloat: + def _get_array(self, scaling, aligned=True): + if not aligned: + a = np.empty(3 * 8 + 1, dtype=np.uint8)[1:] + a = a.view(np.float64) + a[:] = [1., 2., 3.] + else: + a = np.array([1., 2., 3.]) + + a *= 1. / scaling # the casting code also uses the reciprocal. + return a.view(SF(scaling)) + + def test_sfloat_rescaled(self): + sf = SF(1.) + sf2 = sf.scaled_by(2.) + assert sf2.get_scaling() == 2. + sf6 = sf2.scaled_by(3.) + assert sf6.get_scaling() == 6. + + def test_class_discovery(self): + # This does not test much, since we always discover the scaling as 1. + # But most of NumPy (when writing) does not understand DType classes + dt, _ = discover_array_params([1., 2., 3.], dtype=SF) + assert dt == SF(1.) + + @pytest.mark.parametrize("scaling", [1., -1., 2.]) + def test_scaled_float_from_floats(self, scaling): + a = np.array([1., 2., 3.], dtype=SF(scaling)) + + assert a.dtype.get_scaling() == scaling + assert_array_equal(scaling * a.view(np.float64), [1., 2., 3.]) + + def test_repr(self): + # Check the repr, mainly to cover the code paths: + assert repr(SF(scaling=1.)) == "_ScaledFloatTestDType(scaling=1.0)" + + def test_dtype_str(self): + assert SF(1.).str == "_ScaledFloatTestDType(scaling=1.0)" + + def test_dtype_name(self): + assert SF(1.).name == "_ScaledFloatTestDType64" + + def test_sfloat_structured_dtype_printing(self): + dt = np.dtype([("id", int), ("value", SF(0.5))]) + # repr of structured dtypes need special handling because the + # implementation bypasses the object repr + assert "('value', '_ScaledFloatTestDType64')" in repr(dt) + + @pytest.mark.parametrize("scaling", [1., -1., 2.]) + def test_sfloat_from_float(self, scaling): + a = np.array([1., 2., 3.]).astype(dtype=SF(scaling)) + + assert a.dtype.get_scaling() == scaling + assert_array_equal(scaling * a.view(np.float64), [1., 2., 3.]) + + @pytest.mark.parametrize("aligned", [True, False]) + @pytest.mark.parametrize("scaling", [1., -1., 2.]) + def test_sfloat_getitem(self, aligned, scaling): + a = self._get_array(1., aligned) + assert a.tolist() == [1., 2., 3.] + + @pytest.mark.parametrize("aligned", [True, False]) + def test_sfloat_casts(self, aligned): + a = self._get_array(1., aligned) + + assert np.can_cast(a, SF(-1.), casting="equiv") + assert not np.can_cast(a, SF(-1.), casting="no") + na = a.astype(SF(-1.)) + assert_array_equal(-1 * na.view(np.float64), a.view(np.float64)) + + assert np.can_cast(a, SF(2.), casting="same_kind") + assert not np.can_cast(a, SF(2.), casting="safe") + a2 = a.astype(SF(2.)) + assert_array_equal(2 * a2.view(np.float64), a.view(np.float64)) + + @pytest.mark.parametrize("aligned", [True, False]) + def test_sfloat_cast_internal_errors(self, aligned): + a = self._get_array(2e300, aligned) + + with pytest.raises(TypeError, + match="error raised inside the core-loop: non-finite factor!"): + a.astype(SF(2e-300)) + + def test_sfloat_promotion(self): + assert np.result_type(SF(2.), SF(3.)) == SF(3.) + assert np.result_type(SF(3.), SF(2.)) == SF(3.) + # Float64 -> SF(1.) and then promotes normally, so both of this work: + assert np.result_type(SF(3.), np.float64) == SF(3.) + assert np.result_type(np.float64, SF(0.5)) == SF(1.) + + # Test an undefined promotion: + with pytest.raises(TypeError): + np.result_type(SF(1.), np.int64) + + def test_basic_multiply(self): + a = self._get_array(2.) + b = self._get_array(4.) + + res = a * b + # multiplies dtype scaling and content separately: + assert res.dtype.get_scaling() == 8. + expected_view = a.view(np.float64) * b.view(np.float64) + assert_array_equal(res.view(np.float64), expected_view) + + def test_possible_and_impossible_reduce(self): + # For reductions to work, the first and last operand must have the + # same dtype. For this parametric DType that is not necessarily true. + a = self._get_array(2.) + # Addition reduction works (as of writing requires to pass initial + # because setting a scaled-float from the default `0` fails). + res = np.add.reduce(a, initial=0.) + assert res == a.astype(np.float64).sum() + + # But each multiplication changes the factor, so a reduction is not + # possible (the relaxed version of the old refusal to handle any + # flexible dtype). + with pytest.raises(TypeError, + match="the resolved dtypes are not compatible"): + np.multiply.reduce(a) + + def test_basic_ufunc_at(self): + float_a = np.array([1., 2., 3.]) + b = self._get_array(2.) + + float_b = b.view(np.float64).copy() + np.multiply.at(float_b, [1, 1, 1], float_a) + np.multiply.at(b, [1, 1, 1], float_a) + + assert_array_equal(b.view(np.float64), float_b) + + def test_basic_multiply_promotion(self): + float_a = np.array([1., 2., 3.]) + b = self._get_array(2.) + + res1 = float_a * b + res2 = b * float_a + + # one factor is one, so we get the factor of b: + assert res1.dtype == res2.dtype == b.dtype + expected_view = float_a * b.view(np.float64) + assert_array_equal(res1.view(np.float64), expected_view) + assert_array_equal(res2.view(np.float64), expected_view) + + # Check that promotion works when `out` is used: + np.multiply(b, float_a, out=res2) + with pytest.raises(TypeError): + # The promoter accepts this (maybe it should not), but the SFloat + # result cannot be cast to integer: + np.multiply(b, float_a, out=np.arange(3)) + + def test_basic_addition(self): + a = self._get_array(2.) + b = self._get_array(4.) + + res = a + b + # addition uses the type promotion rules for the result: + assert res.dtype == np.result_type(a.dtype, b.dtype) + expected_view = (a.astype(res.dtype).view(np.float64) + + b.astype(res.dtype).view(np.float64)) + assert_array_equal(res.view(np.float64), expected_view) + + def test_addition_cast_safety(self): + """The addition method is special for the scaled float, because it + includes the "cast" between different factors, thus cast-safety + is influenced by the implementation. + """ + a = self._get_array(2.) + b = self._get_array(-2.) + c = self._get_array(3.) + + # sign change is "equiv": + np.add(a, b, casting="equiv") + with pytest.raises(TypeError): + np.add(a, b, casting="no") + + # Different factor is "same_kind" (default) so check that "safe" fails + with pytest.raises(TypeError): + np.add(a, c, casting="safe") + + # Check that casting the output fails also (done by the ufunc here) + with pytest.raises(TypeError): + np.add(a, a, out=c, casting="safe") + + @pytest.mark.parametrize("ufunc", + [np.logical_and, np.logical_or, np.logical_xor]) + def test_logical_ufuncs_casts_to_bool(self, ufunc): + a = self._get_array(2.) + a[0] = 0. # make sure first element is considered False. + + float_equiv = a.astype(float) + expected = ufunc(float_equiv, float_equiv) + res = ufunc(a, a) + assert_array_equal(res, expected) + + # also check that the same works for reductions: + expected = ufunc.reduce(float_equiv) + res = ufunc.reduce(a) + assert_array_equal(res, expected) + + # The output casting does not match the bool, bool -> bool loop: + with pytest.raises(TypeError): + ufunc(a, a, out=np.empty(a.shape, dtype=int), casting="equiv") + + def test_wrapped_and_wrapped_reductions(self): + a = self._get_array(2.) + float_equiv = a.astype(float) + + expected = np.hypot(float_equiv, float_equiv) + res = np.hypot(a, a) + assert res.dtype == a.dtype + res_float = res.view(np.float64) * 2 + assert_array_equal(res_float, expected) + + # Also check reduction (keepdims, due to incorrect getitem) + res = np.hypot.reduce(a, keepdims=True) + assert res.dtype == a.dtype + expected = np.hypot.reduce(float_equiv, keepdims=True) + assert res.view(np.float64) * 2 == expected + + def test_sort(self): + a = self._get_array(1.) + a = a[::-1] # reverse it + + a.sort() + assert_array_equal(a.view(np.float64), [1., 2., 3.]) + + a = self._get_array(1.) + a = a[::-1] # reverse it + + sorted_a = np.sort(a) + assert_array_equal(sorted_a.view(np.float64), [1., 2., 3.]) + # original is unchanged + assert_array_equal(a.view(np.float64), [3., 2., 1.]) + + a = self._get_array(0.5) # different factor + a = a[::2][::-1] # non-contiguous + sorted_a = np.sort(a) + assert_array_equal(sorted_a.view(np.float64), [2., 6.]) + # original is unchanged + assert_array_equal(a.view(np.float64), [6., 2.]) + + a = self._get_array(0.5, aligned=False) + a = a[::-1] # reverse it + sorted_a = np.sort(a) + assert_array_equal(sorted_a.view(np.float64), [2., 4., 6.]) + # original is unchanged + assert_array_equal(a.view(np.float64), [6., 4., 2.]) + + sorted_a = np.sort(a, stable=True) + assert_array_equal(sorted_a.view(np.float64), [2., 4., 6.]) + # original is unchanged + assert_array_equal(a.view(np.float64), [6., 4., 2.]) + + sorted_a = np.sort(a, stable=False) + assert_array_equal(sorted_a.view(np.float64), [2., 4., 6.]) + # original is unchanged + assert_array_equal(a.view(np.float64), [6., 4., 2.]) + + def test_argsort(self): + a = self._get_array(1.) + a = a[::-1] # reverse it + + indices = np.argsort(a) + assert_array_equal(indices, [2, 1, 0]) + # original is unchanged + assert_array_equal(a.view(np.float64), [3., 2., 1.]) + + a = self._get_array(0.5) + a = a[::2][::-1] # reverse it + indices = np.argsort(a) + assert_array_equal(indices, [1, 0]) + # original is unchanged + assert_array_equal(a.view(np.float64), [6., 2.]) + + a = self._get_array(0.5, aligned=False) + a = a[::-1] # reverse it + indices = np.argsort(a) + assert_array_equal(indices, [2, 1, 0]) + # original is unchanged + assert_array_equal(a.view(np.float64), [6., 4., 2.]) + + sorted_indices = np.argsort(a, stable=True) + assert_array_equal(sorted_indices, [2, 1, 0]) + # original is unchanged + assert_array_equal(a.view(np.float64), [6., 4., 2.]) + + sorted_indices = np.argsort(a, stable=False) + assert_array_equal(sorted_indices, [2, 1, 0]) + # original is unchanged + assert_array_equal(a.view(np.float64), [6., 4., 2.]) + + def test_astype_class(self): + # Very simple test that we accept `.astype()` also on the class. + # ScaledFloat always returns the default descriptor, but it does + # check the relevant code paths. + arr = np.array([1., 2., 3.], dtype=object) + + res = arr.astype(SF) # passing the class class + expected = arr.astype(SF(1.)) # above will have discovered 1. scaling + assert_array_equal(res.view(np.float64), expected.view(np.float64)) + + def test_creation_class(self): + # passing in a dtype class should return + # the default descriptor + arr1 = np.array([1., 2., 3.], dtype=SF) + assert arr1.dtype == SF(1.) + arr2 = np.array([1., 2., 3.], dtype=SF(1.)) + assert_array_equal(arr1.view(np.float64), arr2.view(np.float64)) + assert arr1.dtype == arr2.dtype + + assert np.empty(3, dtype=SF).dtype == SF(1.) + assert np.empty_like(arr1, dtype=SF).dtype == SF(1.) + assert np.zeros(3, dtype=SF).dtype == SF(1.) + assert np.zeros_like(arr1, dtype=SF).dtype == SF(1.) + + @pytest.mark.thread_unsafe( + reason="_ScaledFloatTestDType setup is thread-unsafe (gh-29850)" + ) + def test_np_save_load(self): + # this monkeypatch is needed because pickle + # uses the repr of a type to reconstruct it + np._ScaledFloatTestDType = SF + + arr = np.array([1.0, 2.0, 3.0], dtype=SF(1.0)) + + # adapted from RoundtripTest.roundtrip in np.save tests + with NamedTemporaryFile("wb", delete=False, suffix=".npz") as f: + with pytest.warns(UserWarning) as record: + np.savez(f.name, arr) + + assert len(record) == 1 + + with np.load(f.name, allow_pickle=True) as data: + larr = data["arr_0"] + assert_array_equal(arr.view(np.float64), larr.view(np.float64)) + assert larr.dtype == arr.dtype == SF(1.0) + + del np._ScaledFloatTestDType + + def test_flatiter(self): + arr = np.array([1.0, 2.0, 3.0], dtype=SF(1.0)) + + for i, val in enumerate(arr.flat): + assert arr[i] == val + + @pytest.mark.parametrize( + "index", [ + [1, 2], ..., slice(None, 2, None), + np.array([True, True, False]), np.array([0, 1]) + ], ids=["int_list", "ellipsis", "slice", "bool_array", "int_array"]) + def test_flatiter_index(self, index): + arr = np.array([1.0, 2.0, 3.0], dtype=SF(1.0)) + np.testing.assert_array_equal( + arr[index].view(np.float64), arr.flat[index].view(np.float64)) + + arr2 = arr.copy() + arr[index] = 5.0 + arr2.flat[index] = 5.0 + np.testing.assert_array_equal( + arr.view(np.float64), arr2.view(np.float64)) + +@pytest.mark.thread_unsafe( + reason="_ScaledFloatTestDType setup is thread-unsafe (gh-29850)" +) +def test_type_pickle(): + # can't actually unpickle, but we can pickle (if in namespace) + import pickle + + np._ScaledFloatTestDType = SF + + s = pickle.dumps(SF) + res = pickle.loads(s) + assert res is SF + + del np._ScaledFloatTestDType + + +def test_is_numeric(): + assert SF._is_numeric diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_cython.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_cython.py new file mode 100644 index 0000000000000000000000000000000000000000..7e2680578b3ef9ff9bcaa58cfe5b13c57565fb8c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_cython.py @@ -0,0 +1,367 @@ +import os +import subprocess +import sys +import sysconfig +from datetime import datetime + +import pytest + +import numpy as np +from numpy.testing import IS_EDITABLE, IS_WASM, assert_array_equal + +# This import is copied from random.tests.test_extending +try: + import cython + from Cython.Compiler.Version import version as cython_version +except ImportError: + cython = None +else: + from numpy._utils import _pep440 + + # Note: keep in sync with the one in pyproject.toml + required_version = "3.0.6" + if _pep440.parse(cython_version) < _pep440.Version(required_version): + # too old or wrong cython, skip the test + cython = None + +pytestmark = pytest.mark.skipif(cython is None, reason="requires cython") + + +if IS_EDITABLE: + pytest.skip( + "Editable install doesn't support tests with a compile step", + allow_module_level=True + ) + + +@pytest.fixture(scope='module') +def install_temp(tmpdir_factory): + # Based in part on test_cython from random.tests.test_extending + if IS_WASM: + pytest.skip("No subprocess") + + srcdir = os.path.join(os.path.dirname(__file__), 'examples', 'cython') + build_dir = tmpdir_factory.mktemp("cython_test") / "build" + os.makedirs(build_dir, exist_ok=True) + # Ensure we use the correct Python interpreter even when `meson` is + # installed in a different Python environment (see gh-24956) + native_file = str(build_dir / 'interpreter-native-file.ini') + with open(native_file, 'w') as f: + f.write("[binaries]\n") + f.write(f"python = '{sys.executable}'\n") + f.write(f"python3 = '{sys.executable}'") + + try: + subprocess.check_call(["meson", "--version"]) + except FileNotFoundError: + pytest.skip("No usable 'meson' found") + if sysconfig.get_platform() == "win-arm64": + pytest.skip("Meson unable to find MSVC linker on win-arm64") + if sys.platform == "win32": + subprocess.check_call(["meson", "setup", + "--buildtype=release", + "--vsenv", "--native-file", native_file, + str(srcdir)], + cwd=build_dir, + ) + else: + subprocess.check_call(["meson", "setup", + "--native-file", native_file, str(srcdir)], + cwd=build_dir + ) + try: + subprocess.check_call(["meson", "compile", "-vv"], cwd=build_dir) + except subprocess.CalledProcessError: + print("----------------") + print("meson build failed when doing") + print(f"'meson setup --native-file {native_file} {srcdir}'") + print("'meson compile -vv'") + print(f"in {build_dir}") + print("----------------") + raise + + sys.path.append(str(build_dir)) + + +def test_is_timedelta64_object(install_temp): + import checks + + assert checks.is_td64(np.timedelta64(1234)) + assert checks.is_td64(np.timedelta64(1234, "ns")) + assert checks.is_td64(np.timedelta64("NaT", "ns")) + + assert not checks.is_td64(1) + assert not checks.is_td64(None) + assert not checks.is_td64("foo") + assert not checks.is_td64(np.datetime64("now", "s")) + + +def test_is_datetime64_object(install_temp): + import checks + + assert checks.is_dt64(np.datetime64(1234, "ns")) + assert checks.is_dt64(np.datetime64("NaT", "ns")) + + assert not checks.is_dt64(1) + assert not checks.is_dt64(None) + assert not checks.is_dt64("foo") + assert not checks.is_dt64(np.timedelta64(1234)) + + +def test_get_datetime64_value(install_temp): + import checks + + dt64 = np.datetime64("2016-01-01", "ns") + + result = checks.get_dt64_value(dt64) + expected = dt64.view("i8") + + assert result == expected + + +def test_get_timedelta64_value(install_temp): + import checks + + td64 = np.timedelta64(12345, "h") + + result = checks.get_td64_value(td64) + expected = td64.view("i8") + + assert result == expected + + +def test_get_datetime64_unit(install_temp): + import checks + + dt64 = np.datetime64("2016-01-01", "ns") + result = checks.get_dt64_unit(dt64) + expected = 10 + assert result == expected + + td64 = np.timedelta64(12345, "h") + result = checks.get_dt64_unit(td64) + expected = 5 + assert result == expected + + +def test_abstract_scalars(install_temp): + import checks + + assert checks.is_integer(1) + assert checks.is_integer(np.int8(1)) + assert checks.is_integer(np.uint64(1)) + +def test_default_int(install_temp): + import checks + + assert checks.get_default_integer() is np.dtype(int) + + +def test_ravel_axis(install_temp): + import checks + + assert checks.get_ravel_axis() == np.iinfo("intc").min + + +def test_convert_datetime64_to_datetimestruct(install_temp): + # GH#21199 + import checks + + res = checks.convert_datetime64_to_datetimestruct() + + exp = { + "year": 2022, + "month": 3, + "day": 15, + "hour": 20, + "min": 1, + "sec": 55, + "us": 260292, + "ps": 0, + "as": 0, + } + + assert res == exp + + +class TestDatetimeStrings: + def test_make_iso_8601_datetime(self, install_temp): + # GH#21199 + import checks + dt = datetime(2016, 6, 2, 10, 45, 19) + # uses NPY_FR_s + result = checks.make_iso_8601_datetime(dt) + assert result == b"2016-06-02T10:45:19" + + def test_get_datetime_iso_8601_strlen(self, install_temp): + # GH#21199 + import checks + # uses NPY_FR_ns + res = checks.get_datetime_iso_8601_strlen() + assert res == 48 + + +@pytest.mark.parametrize( + "arrays", + [ + [np.random.rand(2)], + [np.random.rand(2), np.random.rand(3, 1)], + [np.random.rand(2), np.random.rand(2, 3, 2), np.random.rand(1, 3, 2)], + [np.random.rand(2, 1)] * 4 + [np.random.rand(1, 1, 1)], + ] +) +def test_multiiter_fields(install_temp, arrays): + import checks + bcast = np.broadcast(*arrays) + + assert bcast.ndim == checks.get_multiiter_number_of_dims(bcast) + assert bcast.size == checks.get_multiiter_size(bcast) + assert bcast.numiter == checks.get_multiiter_num_of_iterators(bcast) + assert bcast.shape == checks.get_multiiter_shape(bcast) + assert bcast.index == checks.get_multiiter_current_index(bcast) + assert all( + x.base is y.base + for x, y in zip(bcast.iters, checks.get_multiiter_iters(bcast)) + ) + + +def test_dtype_flags(install_temp): + import checks + dtype = np.dtype("i,O") # dtype with somewhat interesting flags + assert dtype.flags == checks.get_dtype_flags(dtype) + + +def test_conv_intp(install_temp): + import checks + + class myint: + def __int__(self): + return 3 + + # These conversion passes via `__int__`, not `__index__`: + assert checks.conv_intp(3.) == 3 + assert checks.conv_intp(myint()) == 3 + + +def test_npyiter_api(install_temp): + import checks + arr = np.random.rand(3, 2) + + it = np.nditer(arr) + assert checks.get_npyiter_size(it) == it.itersize == np.prod(arr.shape) + assert checks.get_npyiter_ndim(it) == it.ndim == 1 + assert checks.npyiter_has_index(it) == it.has_index == False + + it = np.nditer(arr, flags=["c_index"]) + assert checks.npyiter_has_index(it) == it.has_index == True + assert ( + checks.npyiter_has_delayed_bufalloc(it) + == it.has_delayed_bufalloc + == False + ) + + it = np.nditer(arr, flags=["buffered", "delay_bufalloc"]) + assert ( + checks.npyiter_has_delayed_bufalloc(it) + == it.has_delayed_bufalloc + == True + ) + + it = np.nditer(arr, flags=["multi_index"]) + assert checks.get_npyiter_size(it) == it.itersize == np.prod(arr.shape) + assert checks.npyiter_has_multi_index(it) == it.has_multi_index == True + assert checks.get_npyiter_ndim(it) == it.ndim == 2 + assert checks.test_get_multi_index_iter_next(it, arr) + + arr2 = np.random.rand(2, 1, 2) + it = np.nditer([arr, arr2]) + assert checks.get_npyiter_nop(it) == it.nop == 2 + assert checks.get_npyiter_size(it) == it.itersize == 12 + assert checks.get_npyiter_ndim(it) == it.ndim == 3 + assert all( + x is y for x, y in zip(checks.get_npyiter_operands(it), it.operands) + ) + assert all( + np.allclose(x, y) + for x, y in zip(checks.get_npyiter_itviews(it), it.itviews) + ) + + +def test_fillwithbytes(install_temp): + import checks + + arr = checks.compile_fillwithbyte() + assert_array_equal(arr, np.ones((1, 2))) + + +def test_complex(install_temp): + from checks import inc2_cfloat_struct + + arr = np.array([0, 10 + 10j], dtype="F") + inc2_cfloat_struct(arr) + assert arr[1] == (12 + 12j) + + +def test_npystring_pack(install_temp): + """Check that the cython API can write to a vstring array.""" + import checks + + arr = np.array(['a', 'b', 'c'], dtype='T') + assert checks.npystring_pack(arr) == 0 + + # checks.npystring_pack writes to the beginning of the array + assert arr[0] == "Hello world" + +def test_npystring_load(install_temp): + """Check that the cython API can load strings from a vstring array.""" + import checks + + arr = np.array(['abcd', 'b', 'c'], dtype='T') + result = checks.npystring_load(arr) + assert result == 'abcd' + + +def test_npystring_multiple_allocators(install_temp): + """Check that the cython API can acquire/release multiple vstring allocators.""" + import checks + + dt = np.dtypes.StringDType(na_object=None) + arr1 = np.array(['abcd', 'b', 'c'], dtype=dt) + arr2 = np.array(['a', 'b', 'c'], dtype=dt) + + assert checks.npystring_pack_multiple(arr1, arr2) == 0 + assert arr1[0] == "Hello world" + assert arr1[-1] is None + assert arr2[0] == "test this" + + +def test_npystring_allocators_other_dtype(install_temp): + """Check that allocators for non-StringDType arrays is NULL.""" + import checks + + arr1 = np.array([1, 2, 3], dtype='i') + arr2 = np.array([4, 5, 6], dtype='i') + + assert checks.npystring_allocators_other_types(arr1, arr2) == 0 + + +@pytest.mark.skipif(sysconfig.get_platform() == 'win-arm64', + reason='no checks module on win-arm64') +def test_npy_uintp_type_enum(install_temp): + import checks + assert checks.check_npy_uintp_type_enum() + + +@pytest.mark.skipif( + sys.version_info < (3, 14), + reason="Tests behavior that happens on Python 3.14 and newer" +) +@pytest.mark.skipif( + sysconfig.get_platform() == 'win-arm64', + reason='no checks module on win-arm64' +) +def test_resize_refcheck(install_temp): + import checks + msg = "It is possible that this is a false positive." + with pytest.raises(ValueError, match=msg): + checks.resize_refcheck_test() diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_datetime.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_datetime.py new file mode 100644 index 0000000000000000000000000000000000000000..029110c4d52d83e83b3238349c06b5b445fe9991 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_datetime.py @@ -0,0 +1,2797 @@ +import datetime +import pickle +import warnings +from zoneinfo import ZoneInfo, ZoneInfoNotFoundError + +import pytest + +import numpy +import numpy as np +from numpy.testing import ( + IS_WASM, + assert_, + assert_array_equal, + assert_equal, + assert_raises, + assert_raises_regex, +) + +try: + RecursionError +except NameError: + RecursionError = RuntimeError # python < 3.5 + +try: + ZoneInfo("US/Central") + _has_tz = True +except ZoneInfoNotFoundError: + _has_tz = False + +def _assert_equal_hash(v1, v2): + assert v1 == v2 + assert hash(v1) == hash(v2) + assert v2 in {v1} + + +class TestDateTime: + + def test_string(self): + msg = "no explicit representation of timezones available for " \ + "np.datetime64" + with pytest.warns(UserWarning, match=msg): + np.datetime64('2000-01-01T00+01') + + def test_datetime(self): + msg = "no explicit representation of timezones available for " \ + "np.datetime64" + with pytest.warns(UserWarning, match=msg): + t0 = np.datetime64('2023-06-09T12:18:40Z', 'ns') + + t0 = np.datetime64('2023-06-09T12:18:40', 'ns') + + def test_datetime_dtype_creation(self): + for unit in ['Y', 'M', 'W', 'D', + 'h', 'm', 's', 'ms', 'us', + 'μs', # alias for us + 'ns', 'ps', 'fs', 'as']: + dt1 = np.dtype(f'M8[750{unit}]') + assert_(dt1 == np.dtype(f'datetime64[750{unit}]')) + dt2 = np.dtype(f'm8[{unit}]') + assert_(dt2 == np.dtype(f'timedelta64[{unit}]')) + + # Generic units shouldn't add [] to the end + assert_equal(str(np.dtype("M8")), "datetime64") + + # Should be possible to specify the endianness + assert_equal(np.dtype("=M8"), np.dtype("M8")) + assert_equal(np.dtype("=M8[s]"), np.dtype("M8[s]")) + assert_(np.dtype(">M8") == np.dtype("M8") or + np.dtype("M8[D]") == np.dtype("M8[D]") or + np.dtype("M8") != np.dtype("m8") == np.dtype("m8") or + np.dtype("m8[D]") == np.dtype("m8[D]") or + np.dtype("m8") != np.dtype(" Scalars + assert_equal(np.datetime64(b, '[s]'), np.datetime64('NaT', '[s]')) + assert_equal(np.datetime64(b, '[ms]'), np.datetime64('NaT', '[ms]')) + assert_equal(np.datetime64(b, '[M]'), np.datetime64('NaT', '[M]')) + assert_equal(np.datetime64(b, '[Y]'), np.datetime64('NaT', '[Y]')) + assert_equal(np.datetime64(b, '[W]'), np.datetime64('NaT', '[W]')) + + # Arrays -> Scalars + assert_equal(np.datetime64(a, '[s]'), np.datetime64('NaT', '[s]')) + assert_equal(np.datetime64(a, '[ms]'), np.datetime64('NaT', '[ms]')) + assert_equal(np.datetime64(a, '[M]'), np.datetime64('NaT', '[M]')) + assert_equal(np.datetime64(a, '[Y]'), np.datetime64('NaT', '[Y]')) + assert_equal(np.datetime64(a, '[W]'), np.datetime64('NaT', '[W]')) + + # NaN -> NaT + nan = np.array([np.nan] * 8 + [0]) + fnan = nan.astype('f') + lnan = nan.astype('g') + cnan = nan.astype('D') + cfnan = nan.astype('F') + clnan = nan.astype('G') + hnan = nan.astype(np.half) + + nat = np.array([np.datetime64('NaT')] * 8 + [np.datetime64(0, 'D')]) + assert_equal(nan.astype('M8[ns]'), nat) + assert_equal(fnan.astype('M8[ns]'), nat) + assert_equal(lnan.astype('M8[ns]'), nat) + assert_equal(cnan.astype('M8[ns]'), nat) + assert_equal(cfnan.astype('M8[ns]'), nat) + assert_equal(clnan.astype('M8[ns]'), nat) + assert_equal(hnan.astype('M8[ns]'), nat) + + nat = np.array([np.timedelta64('NaT')] * 8 + [np.timedelta64(0)]) + assert_equal(nan.astype('timedelta64[ns]'), nat) + assert_equal(fnan.astype('timedelta64[ns]'), nat) + assert_equal(lnan.astype('timedelta64[ns]'), nat) + assert_equal(cnan.astype('timedelta64[ns]'), nat) + assert_equal(cfnan.astype('timedelta64[ns]'), nat) + assert_equal(clnan.astype('timedelta64[ns]'), nat) + assert_equal(hnan.astype('timedelta64[ns]'), nat) + + def test_days_creation(self): + assert_equal(np.array('1599', dtype='M8[D]').astype('i8'), + (1600 - 1970) * 365 - (1972 - 1600) / 4 + 3 - 365) + assert_equal(np.array('1600', dtype='M8[D]').astype('i8'), + (1600 - 1970) * 365 - (1972 - 1600) / 4 + 3) + assert_equal(np.array('1601', dtype='M8[D]').astype('i8'), + (1600 - 1970) * 365 - (1972 - 1600) / 4 + 3 + 366) + assert_equal(np.array('1900', dtype='M8[D]').astype('i8'), + (1900 - 1970) * 365 - (1970 - 1900) // 4) + assert_equal(np.array('1901', dtype='M8[D]').astype('i8'), + (1900 - 1970) * 365 - (1970 - 1900) // 4 + 365) + assert_equal(np.array('1967', dtype='M8[D]').astype('i8'), -3 * 365 - 1) + assert_equal(np.array('1968', dtype='M8[D]').astype('i8'), -2 * 365 - 1) + assert_equal(np.array('1969', dtype='M8[D]').astype('i8'), -1 * 365) + assert_equal(np.array('1970', dtype='M8[D]').astype('i8'), 0 * 365) + assert_equal(np.array('1971', dtype='M8[D]').astype('i8'), 1 * 365) + assert_equal(np.array('1972', dtype='M8[D]').astype('i8'), 2 * 365) + assert_equal(np.array('1973', dtype='M8[D]').astype('i8'), 3 * 365 + 1) + assert_equal(np.array('1974', dtype='M8[D]').astype('i8'), 4 * 365 + 1) + assert_equal(np.array('2000', dtype='M8[D]').astype('i8'), + (2000 - 1970) * 365 + (2000 - 1972) // 4) + assert_equal(np.array('2001', dtype='M8[D]').astype('i8'), + (2000 - 1970) * 365 + (2000 - 1972) // 4 + 366) + assert_equal(np.array('2400', dtype='M8[D]').astype('i8'), + (2400 - 1970) * 365 + (2400 - 1972) // 4 - 3) + assert_equal(np.array('2401', dtype='M8[D]').astype('i8'), + (2400 - 1970) * 365 + (2400 - 1972) // 4 - 3 + 366) + + assert_equal(np.array('1600-02-29', dtype='M8[D]').astype('i8'), + (1600 - 1970) * 365 - (1972 - 1600) // 4 + 3 + 31 + 28) + assert_equal(np.array('1600-03-01', dtype='M8[D]').astype('i8'), + (1600 - 1970) * 365 - (1972 - 1600) // 4 + 3 + 31 + 29) + assert_equal(np.array('2000-02-29', dtype='M8[D]').astype('i8'), + (2000 - 1970) * 365 + (2000 - 1972) // 4 + 31 + 28) + assert_equal(np.array('2000-03-01', dtype='M8[D]').astype('i8'), + (2000 - 1970) * 365 + (2000 - 1972) // 4 + 31 + 29) + assert_equal(np.array('2001-03-22', dtype='M8[D]').astype('i8'), + (2000 - 1970) * 365 + (2000 - 1972) // 4 + 366 + 31 + 28 + 21) + + def test_days_to_pydate(self): + assert_equal(np.array('1599', dtype='M8[D]').astype('O'), + datetime.date(1599, 1, 1)) + assert_equal(np.array('1600', dtype='M8[D]').astype('O'), + datetime.date(1600, 1, 1)) + assert_equal(np.array('1601', dtype='M8[D]').astype('O'), + datetime.date(1601, 1, 1)) + assert_equal(np.array('1900', dtype='M8[D]').astype('O'), + datetime.date(1900, 1, 1)) + assert_equal(np.array('1901', dtype='M8[D]').astype('O'), + datetime.date(1901, 1, 1)) + assert_equal(np.array('2000', dtype='M8[D]').astype('O'), + datetime.date(2000, 1, 1)) + assert_equal(np.array('2001', dtype='M8[D]').astype('O'), + datetime.date(2001, 1, 1)) + assert_equal(np.array('1600-02-29', dtype='M8[D]').astype('O'), + datetime.date(1600, 2, 29)) + assert_equal(np.array('1600-03-01', dtype='M8[D]').astype('O'), + datetime.date(1600, 3, 1)) + assert_equal(np.array('2001-03-22', dtype='M8[D]').astype('O'), + datetime.date(2001, 3, 22)) + + def test_dtype_comparison(self): + assert_(not (np.dtype('M8[us]') == np.dtype('M8[ms]'))) + assert_(np.dtype('M8[us]') != np.dtype('M8[ms]')) + assert_(np.dtype('M8[2D]') != np.dtype('M8[D]')) + assert_(np.dtype('M8[D]') != np.dtype('M8[2D]')) + + def test_pydatetime_creation(self): + a = np.array(['1960-03-12', datetime.date(1960, 3, 12)], dtype='M8[D]') + assert_equal(a[0], a[1]) + a = np.array(['1999-12-31', datetime.date(1999, 12, 31)], dtype='M8[D]') + assert_equal(a[0], a[1]) + a = np.array(['2000-01-01', datetime.date(2000, 1, 1)], dtype='M8[D]') + assert_equal(a[0], a[1]) + # Will fail if the date changes during the exact right moment + a = np.array(['today', datetime.date.today()], dtype='M8[D]') + assert_equal(a[0], a[1]) + # datetime.datetime.now() returns local time, not UTC + #a = np.array(['now', datetime.datetime.now()], dtype='M8[s]') + #assert_equal(a[0], a[1]) + + # we can give a datetime.date time units + assert_equal(np.array(datetime.date(1960, 3, 12), dtype='M8[s]'), + np.array(np.datetime64('1960-03-12T00:00:00'))) + + def test_datetime_string_conversion(self): + a = ['2011-03-16', '1920-01-01', '2013-05-19'] + str_a = np.array(a, dtype='S') + uni_a = np.array(a, dtype='U') + dt_a = np.array(a, dtype='M') + + # String to datetime + assert_equal(dt_a, str_a.astype('M')) + assert_equal(dt_a.dtype, str_a.astype('M').dtype) + dt_b = np.empty_like(dt_a) + dt_b[...] = str_a + assert_equal(dt_a, dt_b) + + # Datetime to string + assert_equal(str_a, dt_a.astype('S0')) + str_b = np.empty_like(str_a) + str_b[...] = dt_a + assert_equal(str_a, str_b) + + # Unicode to datetime + assert_equal(dt_a, uni_a.astype('M')) + assert_equal(dt_a.dtype, uni_a.astype('M').dtype) + dt_b = np.empty_like(dt_a) + dt_b[...] = uni_a + assert_equal(dt_a, dt_b) + + # Datetime to unicode + assert_equal(uni_a, dt_a.astype('U')) + uni_b = np.empty_like(uni_a) + uni_b[...] = dt_a + assert_equal(uni_a, uni_b) + + # Datetime to long string - gh-9712 + assert_equal(str_a, dt_a.astype((np.bytes_, 128))) + str_b = np.empty(str_a.shape, dtype=(np.bytes_, 128)) + str_b[...] = dt_a + assert_equal(str_a, str_b) + + @pytest.mark.parametrize("time_dtype", ["m8[D]", "M8[Y]"]) + def test_time_byteswapping(self, time_dtype): + times = np.array(["2017", "NaT"], dtype=time_dtype) + times_swapped = times.astype(times.dtype.newbyteorder()) + assert_array_equal(times, times_swapped) + + unswapped = times_swapped.view(np.dtype("int64").newbyteorder()) + assert_array_equal(unswapped, times.view(np.int64)) + + @pytest.mark.parametrize(["time1", "time2"], + [("M8[s]", "M8[D]"), ("m8[s]", "m8[ns]")]) + def test_time_byteswapped_cast(self, time1, time2): + dtype1 = np.dtype(time1) + dtype2 = np.dtype(time2) + times = np.array(["2017", "NaT"], dtype=dtype1) + expected = times.astype(dtype2) + + # Test that every byte-swapping combination also returns the same + # results (previous tests check that this comparison works fine). + res = times.astype(dtype1.newbyteorder()).astype(dtype2) + assert_array_equal(res, expected) + res = times.astype(dtype2.newbyteorder()) + assert_array_equal(res, expected) + res = times.astype(dtype1.newbyteorder()).astype(dtype2.newbyteorder()) + assert_array_equal(res, expected) + + @pytest.mark.parametrize("time_dtype", ["m8[D]", "M8[Y]"]) + @pytest.mark.parametrize("str_dtype", ["U", "S"]) + def test_datetime_conversions_byteorders(self, str_dtype, time_dtype): + times = np.array(["2017", "NaT"], dtype=time_dtype) + # Unfortunately, timedelta does not roundtrip: + from_strings = np.array(["2017", "NaT"], dtype=str_dtype) + to_strings = times.astype(str_dtype) # assume this is correct + + # Check that conversion from times to string works if src is swapped: + times_swapped = times.astype(times.dtype.newbyteorder()) + res = times_swapped.astype(str_dtype) + assert_array_equal(res, to_strings) + # And also if both are swapped: + res = times_swapped.astype(to_strings.dtype.newbyteorder()) + assert_array_equal(res, to_strings) + # only destination is swapped: + res = times.astype(to_strings.dtype.newbyteorder()) + assert_array_equal(res, to_strings) + + # Check that conversion from string to times works if src is swapped: + from_strings_swapped = from_strings.astype( + from_strings.dtype.newbyteorder()) + res = from_strings_swapped.astype(time_dtype) + assert_array_equal(res, times) + # And if both are swapped: + res = from_strings_swapped.astype(times.dtype.newbyteorder()) + assert_array_equal(res, times) + # Only destination is swapped: + res = from_strings.astype(times.dtype.newbyteorder()) + assert_array_equal(res, times) + + def test_datetime_array_str(self): + a = np.array(['2011-03-16', '1920-01-01', '2013-05-19'], dtype='M') + assert_equal(str(a), "['2011-03-16' '1920-01-01' '2013-05-19']") + + a = np.array(['2011-03-16T13:55', '1920-01-01T03:12'], dtype='M') + assert_equal(np.array2string(a, separator=', ', + formatter={'datetime': lambda x: + f"'{np.datetime_as_string(x, timezone='UTC')}'"}), + "['2011-03-16T13:55Z', '1920-01-01T03:12Z']") + + # Check that one NaT doesn't corrupt subsequent entries + a = np.array(['2010', 'NaT', '2030']).astype('M') + assert_equal(str(a), "['2010' 'NaT' '2030']") + + def test_timedelta_array_str(self): + a = np.array([-1, 0, 100], dtype='m') + assert_equal(str(a), "[ -1 0 100]") + a = np.array(['NaT', 'NaT'], dtype='m') + assert_equal(str(a), "['NaT' 'NaT']") + # Check right-alignment with NaTs + a = np.array([-1, 'NaT', 0], dtype='m') + assert_equal(str(a), "[ -1 'NaT' 0]") + a = np.array([-1, 'NaT', 1234567], dtype='m') + assert_equal(str(a), "[ -1 'NaT' 1234567]") + + # Test with other byteorder: + a = np.array([-1, 'NaT', 1234567], dtype='>m') + assert_equal(str(a), "[ -1 'NaT' 1234567]") + a = np.array([-1, 'NaT', 1234567], dtype=''\np4\nNNNI-1\nI-1\nI0\n((dp5\n(S'us'\np6\n"\ + b"I1\nI1\nI1\ntp7\ntp8\ntp9\nb." + assert_equal(pickle.loads(pkl), np.dtype('>M8[us]')) + + def test_gh_29555(self): + # check that dtype metadata round-trips when none + dt = np.dtype('>M8[us]') + assert dt.metadata is None + for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): + res = pickle.loads(pickle.dumps(dt, protocol=proto)) + assert_equal(res, dt) + assert res.metadata is None + + def test_setstate(self): + "Verify that datetime dtype __setstate__ can handle bad arguments" + dt = np.dtype('>M8[us]') + assert_raises(ValueError, dt.__setstate__, + (4, '>', None, None, None, -1, -1, 0, 1)) + assert_(dt.__reduce__()[2] == np.dtype('>M8[us]').__reduce__()[2]) + assert_raises(TypeError, dt.__setstate__, + (4, '>', None, None, None, -1, -1, 0, ({}, 'xxx'))) + assert_(dt.__reduce__()[2] == np.dtype('>M8[us]').__reduce__()[2]) + + def test_dtype_promotion(self): + # datetime datetime computes the metadata gcd + # timedelta timedelta computes the metadata gcd + for mM in ['m', 'M']: + assert_equal( + np.promote_types(np.dtype(mM + '8[2Y]'), np.dtype(mM + '8[2Y]')), + np.dtype(mM + '8[2Y]')) + assert_equal( + np.promote_types(np.dtype(mM + '8[12Y]'), np.dtype(mM + '8[15Y]')), + np.dtype(mM + '8[3Y]')) + assert_equal( + np.promote_types(np.dtype(mM + '8[62M]'), np.dtype(mM + '8[24M]')), + np.dtype(mM + '8[2M]')) + assert_equal( + np.promote_types(np.dtype(mM + '8[1W]'), np.dtype(mM + '8[2D]')), + np.dtype(mM + '8[1D]')) + assert_equal( + np.promote_types(np.dtype(mM + '8[W]'), np.dtype(mM + '8[13s]')), + np.dtype(mM + '8[s]')) + assert_equal( + np.promote_types(np.dtype(mM + '8[13W]'), np.dtype(mM + '8[49s]')), + np.dtype(mM + '8[7s]')) + # timedelta timedelta raises when there is no reasonable gcd + assert_raises(TypeError, np.promote_types, + np.dtype('m8[Y]'), np.dtype('m8[D]')) + assert_raises(TypeError, np.promote_types, + np.dtype('m8[M]'), np.dtype('m8[W]')) + # timedelta and float cannot be safely cast with each other + assert_raises(TypeError, np.promote_types, "float32", "m8") + assert_raises(TypeError, np.promote_types, "m8", "float32") + assert_raises(TypeError, np.promote_types, "uint64", "m8") + assert_raises(TypeError, np.promote_types, "m8", "uint64") + + # timedelta timedelta may overflow with big unit ranges + assert_raises(OverflowError, np.promote_types, + np.dtype('m8[W]'), np.dtype('m8[fs]')) + assert_raises(OverflowError, np.promote_types, + np.dtype('m8[s]'), np.dtype('m8[as]')) + + def test_cast_overflow(self): + # gh-4486 + def cast(): + numpy.datetime64("1971-01-01 00:00:00.000000000000000").astype("datetime64[{unit}]') + assert_equal(np.isnat(arr), res) + arr = np.array([123, -321, "NaT"], dtype=f'timedelta64[{unit}]') + assert_equal(np.isnat(arr), res) + + def test_isnat_error(self): + # Test that only datetime dtype arrays are accepted + for t in np.typecodes["All"]: + if t in np.typecodes["Datetime"]: + continue + assert_raises(TypeError, np.isnat, np.zeros(10, t)) + + def test_isfinite_scalar(self): + assert_(not np.isfinite(np.datetime64('NaT', 'ms'))) + assert_(not np.isfinite(np.datetime64('NaT', 'ns'))) + assert_(np.isfinite(np.datetime64('2038-01-19T03:14:07'))) + + assert_(not np.isfinite(np.timedelta64('NaT', "ms"))) + assert_(np.isfinite(np.timedelta64(34, "ms"))) + + @pytest.mark.parametrize('unit', ['Y', 'M', 'W', 'D', 'h', 'm', 's', 'ms', + 'us', 'ns', 'ps', 'fs', 'as']) + @pytest.mark.parametrize('dstr', ['datetime64[%s]', + 'timedelta64[%s]']) + def test_isfinite_isinf_isnan_units(self, unit, dstr): + '''check isfinite, isinf, isnan for all units of M, m dtypes + ''' + arr_val = [123, -321, "NaT"] + arr = np.array(arr_val, dtype=(dstr % unit)) + pos = np.array([True, True, False]) + neg = np.array([False, False, True]) + false = np.array([False, False, False]) + assert_equal(np.isfinite(arr), pos) + assert_equal(np.isinf(arr), false) + assert_equal(np.isnan(arr), neg) + + def test_assert_equal(self): + assert_raises(AssertionError, assert_equal, + np.datetime64('nat'), np.timedelta64('nat')) + + def test_corecursive_input(self): + # construct a co-recursive list + a, b = [], [] + a.append(b) + b.append(a) + obj_arr = np.array([None]) + obj_arr[0] = a + + # At some point this caused a stack overflow (gh-11154). Now raises + # ValueError since the nested list cannot be converted to a datetime. + assert_raises(ValueError, obj_arr.astype, 'M8') + assert_raises(ValueError, obj_arr.astype, 'm8') + + @pytest.mark.parametrize("shape", [(), (1,)]) + def test_discovery_from_object_array(self, shape): + arr = np.array("2020-10-10", dtype=object).reshape(shape) + res = np.array("2020-10-10", dtype="M8").reshape(shape) + assert res.dtype == np.dtype("M8[D]") + assert_equal(arr.astype("M8"), res) + arr[...] = np.bytes_("2020-10-10") # try a numpy string type + assert_equal(arr.astype("M8"), res) + arr = arr.astype("S") + assert_equal(arr.astype("S").astype("M8"), res) + + @pytest.mark.parametrize("time_unit", [ + "Y", "M", "W", "D", "h", "m", "s", "ms", "us", "ns", "ps", "fs", "as", + # compound units + "10D", "2M", + ]) + def test_limit_symmetry(self, time_unit): + """ + Dates should have symmetric limits around the unix epoch at +/-np.int64 + """ + epoch = np.datetime64(0, time_unit) + latest = np.datetime64(np.iinfo(np.int64).max, time_unit) + earliest = np.datetime64(-np.iinfo(np.int64).max, time_unit) + + # above should not have overflowed + assert earliest < epoch < latest + + @pytest.mark.parametrize("time_unit", [ + "Y", "M", + pytest.param("W", marks=pytest.mark.xfail(reason="gh-13197")), + "D", "h", "m", + "s", "ms", "us", "ns", "ps", "fs", "as", + pytest.param("10D", marks=pytest.mark.xfail(reason="similar to gh-13197")), + ]) + @pytest.mark.parametrize("sign", [-1, 1]) + def test_limit_str_roundtrip(self, time_unit, sign): + """ + Limits should roundtrip when converted to strings. + + This tests the conversion to and from npy_datetimestruct. + """ + # TODO: add absolute (gold standard) time span limit strings + limit = np.datetime64(np.iinfo(np.int64).max * sign, time_unit) + + # Convert to string and back. Explicit unit needed since the day and + # week reprs are not distinguishable. + limit_via_str = np.datetime64(str(limit), time_unit) + assert limit_via_str == limit + + def test_datetime_hash_nat(self): + nat1 = np.datetime64() + nat2 = np.datetime64() + assert nat1 is not nat2 + assert nat1 != nat2 + assert hash(nat1) != hash(nat2) + + @pytest.mark.parametrize('unit', ('Y', 'M', 'W', 'D', 'h', 'm', 's', 'ms', 'us')) + def test_datetime_hash_weeks(self, unit): + dt = np.datetime64(2348, 'W') # 2015-01-01 + dt2 = np.datetime64(dt, unit) + _assert_equal_hash(dt, dt2) + + dt3 = np.datetime64(int(dt2.astype(int)) + 1, unit) + assert hash(dt) != hash(dt3) # doesn't collide + + @pytest.mark.parametrize('unit', ('h', 'm', 's', 'ms', 'us')) + def test_datetime_hash_weeks_vs_pydatetime(self, unit): + dt = np.datetime64(2348, 'W') # 2015-01-01 + dt2 = np.datetime64(dt, unit) + pydt = dt2.astype(datetime.datetime) + assert isinstance(pydt, datetime.datetime) + _assert_equal_hash(pydt, dt2) + + @pytest.mark.parametrize('unit', ('Y', 'M', 'W', 'D', 'h', 'm', 's', 'ms', 'us')) + def test_datetime_hash_big_negative(self, unit): + dt = np.datetime64(-102894, 'W') # -002-01-01 + dt2 = np.datetime64(dt, unit) + _assert_equal_hash(dt, dt2) + + # can only go down to "fs" before integer overflow + @pytest.mark.parametrize('unit', ('m', 's', 'ms', 'us', 'ns', 'ps', 'fs')) + def test_datetime_hash_minutes(self, unit): + dt = np.datetime64(3, 'm') + dt2 = np.datetime64(dt, unit) + _assert_equal_hash(dt, dt2) + + @pytest.mark.parametrize('unit', ('ns', 'ps', 'fs', 'as')) + def test_datetime_hash_ns(self, unit): + dt = np.datetime64(3, 'ns') + dt2 = np.datetime64(dt, unit) + _assert_equal_hash(dt, dt2) + + dt3 = np.datetime64(int(dt2.astype(int)) + 1, unit) + assert hash(dt) != hash(dt3) # doesn't collide + + @pytest.mark.parametrize('wk', range(500000, 500010)) # 11552-09-04 + @pytest.mark.parametrize('unit', ('W', 'D', 'h', 'm', 's', 'ms', 'us')) + def test_datetime_hash_big_positive(self, wk, unit): + dt = np.datetime64(wk, 'W') + dt2 = np.datetime64(dt, unit) + _assert_equal_hash(dt, dt2) + + def test_timedelta_hash_generic(self): + assert_raises(ValueError, hash, np.timedelta64(123)) # generic + + @pytest.mark.parametrize('unit', ('Y', 'M')) + def test_timedelta_hash_year_month(self, unit): + td = np.timedelta64(45, 'Y') + td2 = np.timedelta64(td, unit) + _assert_equal_hash(td, td2) + + @pytest.mark.parametrize('unit', ('W', 'D', 'h', 'm', 's', 'ms', 'us')) + def test_timedelta_hash_weeks(self, unit): + td = np.timedelta64(10, 'W') + td2 = np.timedelta64(td, unit) + _assert_equal_hash(td, td2) + + td3 = np.timedelta64(int(td2.astype(int)) + 1, unit) + assert hash(td) != hash(td3) # doesn't collide + + @pytest.mark.parametrize('unit', ('W', 'D', 'h', 'm', 's', 'ms', 'us')) + def test_timedelta_hash_weeks_vs_pydelta(self, unit): + td = np.timedelta64(10, 'W') + td2 = np.timedelta64(td, unit) + pytd = td2.astype(datetime.timedelta) + assert isinstance(pytd, datetime.timedelta) + _assert_equal_hash(pytd, td2) + + @pytest.mark.parametrize('unit', ('ms', 'us', 'ns', 'ps', 'fs', 'as')) + def test_timedelta_hash_ms(self, unit): + td = np.timedelta64(3, 'ms') + td2 = np.timedelta64(td, unit) + _assert_equal_hash(td, td2) + + td3 = np.timedelta64(int(td2.astype(int)) + 1, unit) + assert hash(td) != hash(td3) # doesn't collide + + @pytest.mark.parametrize('wk', range(500000, 500010)) + @pytest.mark.parametrize('unit', ('W', 'D', 'h', 'm', 's', 'ms', 'us')) + def test_timedelta_hash_big_positive(self, wk, unit): + td = np.timedelta64(wk, 'W') + td2 = np.timedelta64(td, unit) + _assert_equal_hash(td, td2) + + @pytest.mark.parametrize( + "inputs, divisor, expected", + [ + ( + np.array( + [datetime.timedelta(seconds=20), datetime.timedelta(days=2)], + dtype="object", + ), + np.int64(2), + np.array( + [datetime.timedelta(seconds=10), datetime.timedelta(days=1)], + dtype="object", + ), + ), + ( + np.array( + [datetime.timedelta(seconds=20), datetime.timedelta(days=2)], + dtype="object", + ), + np.timedelta64(2, "s"), + np.array( + [10.0, 24.0 * 60.0 * 60.0], + dtype="object", + ), + ), + ( + datetime.timedelta(seconds=2), + np.array( + [datetime.timedelta(seconds=20), datetime.timedelta(days=2)], + dtype="object", + ), + np.array( + [1.0 / 10.0, 1.0 / (24.0 * 60.0 * 60.0)], + dtype="object", + ), + ), + ], + ) + def test_true_divide_object_by_timedelta( + self, + inputs: np.ndarray | type[np.generic], + divisor: np.ndarray | type[np.generic], + expected: np.ndarray, + ): + # gh-30025 + results = inputs / divisor + assert_array_equal(results, expected) + + +class TestDateTimeData: + + def test_basic(self): + a = np.array(['1980-03-23'], dtype=np.datetime64) + assert_equal(np.datetime_data(a.dtype), ('D', 1)) + + def test_bytes(self): + # byte units are converted to unicode + dt = np.datetime64('2000', (b'ms', 5)) + assert np.datetime_data(dt.dtype) == ('ms', 5) + + dt = np.datetime64('2000', b'5ms') + assert np.datetime_data(dt.dtype) == ('ms', 5) + + def test_non_ascii(self): + # μs is normalized to μ + dt = np.datetime64('2000', ('μs', 5)) + assert np.datetime_data(dt.dtype) == ('us', 5) + + dt = np.datetime64('2000', '5μs') + assert np.datetime_data(dt.dtype) == ('us', 5) + + +def test_comparisons_return_not_implemented(): + # GH#17017 + + class custom: + __array_priority__ = 10000 + + obj = custom() + + dt = np.datetime64('2000', 'ns') + td = dt - dt + + for item in [dt, td]: + assert item.__eq__(obj) is NotImplemented + assert item.__ne__(obj) is NotImplemented + assert item.__le__(obj) is NotImplemented + assert item.__lt__(obj) is NotImplemented + assert item.__ge__(obj) is NotImplemented + assert item.__gt__(obj) is NotImplemented diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_defchararray.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_defchararray.py new file mode 100644 index 0000000000000000000000000000000000000000..e98632b628293c2bf3b85427bd5d94ef2d0a08ec --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_defchararray.py @@ -0,0 +1,858 @@ +import pytest + +import numpy as np +from numpy._core.multiarray import _vec_string +from numpy.testing import ( + assert_, + assert_array_equal, + assert_equal, + assert_raises, + assert_raises_regex, +) + +kw_unicode_true = {'unicode': True} # make 2to3 work properly +kw_unicode_false = {'unicode': False} + +class TestBasic: + def test_from_object_array(self): + A = np.array([['abc', 2], + ['long ', '0123456789']], dtype='O') + B = np.char.array(A) + assert_equal(B.dtype.itemsize, 10) + assert_array_equal(B, [[b'abc', b'2'], + [b'long', b'0123456789']]) + + def test_from_object_array_unicode(self): + A = np.array([['abc', 'Sigma \u03a3'], + ['long ', '0123456789']], dtype='O') + assert_raises(ValueError, np.char.array, (A,)) + B = np.char.array(A, **kw_unicode_true) + assert_equal(B.dtype.itemsize, 10 * np.array('a', 'U').dtype.itemsize) + assert_array_equal(B, [['abc', 'Sigma \u03a3'], + ['long', '0123456789']]) + + def test_from_string_array(self): + A = np.array([[b'abc', b'foo'], + [b'long ', b'0123456789']]) + assert_equal(A.dtype.type, np.bytes_) + B = np.char.array(A) + assert_array_equal(B, A) + assert_equal(B.dtype, A.dtype) + assert_equal(B.shape, A.shape) + B[0, 0] = 'changed' + assert_(B[0, 0] != A[0, 0]) + C = np.char.asarray(A) + assert_array_equal(C, A) + assert_equal(C.dtype, A.dtype) + C[0, 0] = 'changed again' + assert_(C[0, 0] != B[0, 0]) + assert_(C[0, 0] == A[0, 0]) + + def test_from_unicode_array(self): + A = np.array([['abc', 'Sigma \u03a3'], + ['long ', '0123456789']]) + assert_equal(A.dtype.type, np.str_) + B = np.char.array(A) + assert_array_equal(B, A) + assert_equal(B.dtype, A.dtype) + assert_equal(B.shape, A.shape) + B = np.char.array(A, **kw_unicode_true) + assert_array_equal(B, A) + assert_equal(B.dtype, A.dtype) + assert_equal(B.shape, A.shape) + + def fail(): + np.char.array(A, **kw_unicode_false) + + assert_raises(UnicodeEncodeError, fail) + + def test_unicode_upconvert(self): + A = np.char.array(['abc']) + B = np.char.array(['\u03a3']) + assert_(issubclass((A + B).dtype.type, np.str_)) + + def test_from_string(self): + A = np.char.array(b'abc') + assert_equal(len(A), 1) + assert_equal(len(A[0]), 3) + assert_(issubclass(A.dtype.type, np.bytes_)) + + def test_from_unicode(self): + A = np.char.array('\u03a3') + assert_equal(len(A), 1) + assert_equal(len(A[0]), 1) + assert_equal(A.itemsize, 4) + assert_(issubclass(A.dtype.type, np.str_)) + +class TestVecString: + def test_non_existent_method(self): + + def fail(): + _vec_string('a', np.bytes_, 'bogus') + + assert_raises(AttributeError, fail) + + def test_non_string_array(self): + + def fail(): + _vec_string(1, np.bytes_, 'strip') + + assert_raises(TypeError, fail) + + def test_invalid_args_tuple(self): + + def fail(): + _vec_string(['a'], np.bytes_, 'strip', 1) + + assert_raises(TypeError, fail) + + def test_invalid_type_descr(self): + + def fail(): + _vec_string(['a'], 'BOGUS', 'strip') + + assert_raises(TypeError, fail) + + def test_invalid_function_args(self): + + def fail(): + _vec_string(['a'], np.bytes_, 'strip', (1,)) + + assert_raises(TypeError, fail) + + def test_invalid_result_type(self): + + def fail(): + _vec_string(['a'], np.int_, 'strip') + + assert_raises(TypeError, fail) + + def test_broadcast_error(self): + + def fail(): + _vec_string([['abc', 'def']], np.int_, 'find', (['a', 'd', 'j'],)) + + assert_raises(ValueError, fail) + +class TestWhitespace: + def test1(self): + A = np.array([['abc ', '123 '], + ['789 ', 'xyz ']]).view(np.char.chararray) + B = np.array([['abc', '123'], + ['789', 'xyz']]).view(np.char.chararray) + assert_(np.all(A == B)) + assert_(np.all(A >= B)) + assert_(np.all(A <= B)) + assert_(not np.any(A > B)) + assert_(not np.any(A < B)) + assert_(not np.any(A != B)) + +class TestChar: + def test_it(self): + A = np.array('abc1', dtype='c').view(np.char.chararray) + assert_equal(A.shape, (4,)) + assert_equal(A.upper()[:2].tobytes(), b'AB') + +class TestComparisons: + def A(self): + return np.array([['abc', 'abcc', '123'], + ['789', 'abc', 'xyz']]).view(np.char.chararray) + + def B(self): + return np.array([['efg', 'efg', '123 '], + ['051', 'efgg', 'tuv']]).view(np.char.chararray) + + def test_not_equal(self): + A, B = self.A(), self.B() + assert_array_equal((A != B), + [[True, True, False], [True, True, True]]) + + def test_equal(self): + A, B = self.A(), self.B() + assert_array_equal((A == B), + [[False, False, True], [False, False, False]]) + + def test_greater_equal(self): + A, B = self.A(), self.B() + assert_array_equal((A >= B), + [[False, False, True], [True, False, True]]) + + def test_less_equal(self): + A, B = self.A(), self.B() + assert_array_equal((A <= B), + [[True, True, True], [False, True, False]]) + + def test_greater(self): + A, B = self.A(), self.B() + assert_array_equal((A > B), + [[False, False, False], [True, False, True]]) + + def test_less(self): + A, B = self.A(), self.B() + assert_array_equal((A < B), + [[True, True, False], [False, True, False]]) + + def test_type(self): + A, B = self.A(), self.B() + out1 = np.char.equal(A, B) + out2 = np.char.equal('a', 'a') + assert_(isinstance(out1, np.ndarray)) + assert_(isinstance(out2, np.ndarray)) + +class TestComparisonsMixed1(TestComparisons): + """Ticket #1276""" + + def B(self): + return np.array( + [['efg', 'efg', '123 '], + ['051', 'efgg', 'tuv']], np.str_).view(np.char.chararray) + +class TestComparisonsMixed2(TestComparisons): + """Ticket #1276""" + + def A(self): + return np.array( + [['abc', 'abcc', '123'], + ['789', 'abc', 'xyz']], np.str_).view(np.char.chararray) + +class TestInformation: + def A(self): + return np.array([[' abc ', ''], + ['12345', 'MixedCase'], + ['123 \t 345 \0 ', 'UPPER']]) \ + .view(np.char.chararray) + + def B(self): + return np.array([[' \u03a3 ', ''], + ['12345', 'MixedCase'], + ['123 \t 345 \0 ', 'UPPER']]) \ + .view(np.char.chararray) + + def test_len(self): + A, B = self.A(), self.B() + assert_(issubclass(np.char.str_len(A).dtype.type, np.integer)) + assert_array_equal(np.char.str_len(A), [[5, 0], [5, 9], [12, 5]]) + assert_array_equal(np.char.str_len(B), [[3, 0], [5, 9], [12, 5]]) + + def test_count(self): + A, B = self.A(), self.B() + assert_(issubclass(A.count('').dtype.type, np.integer)) + assert_array_equal(A.count('a'), [[1, 0], [0, 1], [0, 0]]) + assert_array_equal(A.count('123'), [[0, 0], [1, 0], [1, 0]]) + # Python doesn't seem to like counting NULL characters + assert_array_equal(A.count('a', 0, 2), [[1, 0], [0, 0], [0, 0]]) + assert_array_equal(B.count('a'), [[0, 0], [0, 1], [0, 0]]) + assert_array_equal(B.count('123'), [[0, 0], [1, 0], [1, 0]]) + + def test_endswith(self): + A = self.A() + assert_(issubclass(A.endswith('').dtype.type, np.bool)) + assert_array_equal(A.endswith(' '), [[1, 0], [0, 0], [1, 0]]) + assert_array_equal(A.endswith('3', 0, 3), [[0, 0], [1, 0], [1, 0]]) + + def fail(): + A.endswith('3', 'fdjk') + + assert_raises(TypeError, fail) + + @pytest.mark.parametrize( + "dtype, encode", + [("U", str), + ("S", lambda x: x.encode('ascii')), + ]) + def test_find(self, dtype, encode): + A = self.A().astype(dtype) + assert_(issubclass(A.find(encode('a')).dtype.type, np.integer)) + assert_array_equal(A.find(encode('a')), + [[1, -1], [-1, 6], [-1, -1]]) + assert_array_equal(A.find(encode('3')), + [[-1, -1], [2, -1], [2, -1]]) + assert_array_equal(A.find(encode('a'), 0, 2), + [[1, -1], [-1, -1], [-1, -1]]) + assert_array_equal(A.find([encode('1'), encode('P')]), + [[-1, -1], [0, -1], [0, 1]]) + C = (np.array(['ABCDEFGHIJKLMNOPQRSTUVWXYZ', + '01234567890123456789012345']) + .view(np.char.chararray)).astype(dtype) + assert_array_equal(C.find(encode('M')), [12, -1]) + + def test_index(self): + A = self.A() + + def fail(): + A.index('a') + + assert_raises(ValueError, fail) + assert_(np.char.index('abcba', 'b') == 1) + assert_(issubclass(np.char.index('abcba', 'b').dtype.type, np.integer)) + + def test_isalnum(self): + A = self.A() + assert_(issubclass(A.isalnum().dtype.type, np.bool)) + assert_array_equal(A.isalnum(), [[False, False], [True, True], [False, True]]) + + def test_isalpha(self): + A = self.A() + assert_(issubclass(A.isalpha().dtype.type, np.bool)) + assert_array_equal(A.isalpha(), [[False, False], [False, True], [False, True]]) + + def test_isdigit(self): + A = self.A() + assert_(issubclass(A.isdigit().dtype.type, np.bool)) + assert_array_equal(A.isdigit(), [[False, False], [True, False], [False, False]]) + + def test_islower(self): + A = self.A() + assert_(issubclass(A.islower().dtype.type, np.bool)) + assert_array_equal(A.islower(), [[True, False], [False, False], [False, False]]) + + def test_isspace(self): + A = self.A() + assert_(issubclass(A.isspace().dtype.type, np.bool)) + assert_array_equal(A.isspace(), [[False, False], [False, False], [False, False]]) + + def test_istitle(self): + A = self.A() + assert_(issubclass(A.istitle().dtype.type, np.bool)) + assert_array_equal(A.istitle(), [[False, False], [False, False], [False, False]]) + + def test_isupper(self): + A = self.A() + assert_(issubclass(A.isupper().dtype.type, np.bool)) + assert_array_equal(A.isupper(), [[False, False], [False, False], [False, True]]) + + def test_rfind(self): + A = self.A() + assert_(issubclass(A.rfind('a').dtype.type, np.integer)) + assert_array_equal(A.rfind('a'), [[1, -1], [-1, 6], [-1, -1]]) + assert_array_equal(A.rfind('3'), [[-1, -1], [2, -1], [6, -1]]) + assert_array_equal(A.rfind('a', 0, 2), [[1, -1], [-1, -1], [-1, -1]]) + assert_array_equal(A.rfind(['1', 'P']), [[-1, -1], [0, -1], [0, 2]]) + + def test_rindex(self): + A = self.A() + + def fail(): + A.rindex('a') + + assert_raises(ValueError, fail) + assert_(np.char.rindex('abcba', 'b') == 3) + assert_(issubclass(np.char.rindex('abcba', 'b').dtype.type, np.integer)) + + def test_startswith(self): + A = self.A() + assert_(issubclass(A.startswith('').dtype.type, np.bool)) + assert_array_equal(A.startswith(' '), [[1, 0], [0, 0], [0, 0]]) + assert_array_equal(A.startswith('1', 0, 3), [[0, 0], [1, 0], [1, 0]]) + + def fail(): + A.startswith('3', 'fdjk') + + assert_raises(TypeError, fail) + +class TestMethods: + def A(self): + return np.array([[' abc ', ''], + ['12345', 'MixedCase'], + ['123 \t 345 \0 ', 'UPPER']], + dtype='S').view(np.char.chararray) + + def B(self): + return np.array([[' \u03a3 ', ''], + ['12345', 'MixedCase'], + ['123 \t 345 \0 ', 'UPPER']]) \ + .view(np.char.chararray) + + def test_capitalize(self): + A, B = self.A(), self.B() + tgt = [[b' abc ', b''], + [b'12345', b'Mixedcase'], + [b'123 \t 345 \0 ', b'Upper']] + assert_(issubclass(A.capitalize().dtype.type, np.bytes_)) + assert_array_equal(A.capitalize(), tgt) + + tgt = [[' \u03c3 ', ''], + ['12345', 'Mixedcase'], + ['123 \t 345 \0 ', 'Upper']] + assert_(issubclass(B.capitalize().dtype.type, np.str_)) + assert_array_equal(B.capitalize(), tgt) + + def test_center(self): + A = self.A() + assert_(issubclass(A.center(10).dtype.type, np.bytes_)) + C = A.center([10, 20]) + assert_array_equal(np.char.str_len(C), [[10, 20], [10, 20], [12, 20]]) + + C = A.center(20, b'#') + assert_(np.all(C.startswith(b'#'))) + assert_(np.all(C.endswith(b'#'))) + + C = np.char.center(b'FOO', [[10, 20], [15, 8]]) + tgt = [[b' FOO ', b' FOO '], + [b' FOO ', b' FOO ']] + assert_(issubclass(C.dtype.type, np.bytes_)) + assert_array_equal(C, tgt) + + def test_decode(self): + A = np.char.array([b'\\u03a3']) + assert_(A.decode('unicode-escape')[0] == '\u03a3') + + def test_encode(self): + B = self.B().encode('unicode_escape') + assert_(B[0][0] == ' \\u03a3 '.encode('latin1')) + + def test_expandtabs(self): + T = self.A().expandtabs() + assert_(T[2, 0] == b'123 345 \0') + + def test_join(self): + # NOTE: list(b'123') == [49, 50, 51] + # so that b','.join(b'123') results to an error on Py3 + A0 = self.A().decode('ascii') + + A = np.char.join([',', '#'], A0) + assert_(issubclass(A.dtype.type, np.str_)) + tgt = np.array([[' ,a,b,c, ', ''], + ['1,2,3,4,5', 'M#i#x#e#d#C#a#s#e'], + ['1,2,3, ,\t, ,3,4,5, ,\x00, ', 'U#P#P#E#R']]) + assert_array_equal(np.char.join([',', '#'], A0), tgt) + + def test_ljust(self): + A = self.A() + assert_(issubclass(A.ljust(10).dtype.type, np.bytes_)) + + C = A.ljust([10, 20]) + assert_array_equal(np.char.str_len(C), [[10, 20], [10, 20], [12, 20]]) + + C = A.ljust(20, b'#') + assert_array_equal(C.startswith(b'#'), [ + [False, True], [False, False], [False, False]]) + assert_(np.all(C.endswith(b'#'))) + + C = np.char.ljust(b'FOO', [[10, 20], [15, 8]]) + tgt = [[b'FOO ', b'FOO '], + [b'FOO ', b'FOO ']] + assert_(issubclass(C.dtype.type, np.bytes_)) + assert_array_equal(C, tgt) + + def test_lower(self): + A, B = self.A(), self.B() + tgt = [[b' abc ', b''], + [b'12345', b'mixedcase'], + [b'123 \t 345 \0 ', b'upper']] + assert_(issubclass(A.lower().dtype.type, np.bytes_)) + assert_array_equal(A.lower(), tgt) + + tgt = [[' \u03c3 ', ''], + ['12345', 'mixedcase'], + ['123 \t 345 \0 ', 'upper']] + assert_(issubclass(B.lower().dtype.type, np.str_)) + assert_array_equal(B.lower(), tgt) + + def test_lstrip(self): + A, B = self.A(), self.B() + tgt = [[b'abc ', b''], + [b'12345', b'MixedCase'], + [b'123 \t 345 \0 ', b'UPPER']] + assert_(issubclass(A.lstrip().dtype.type, np.bytes_)) + assert_array_equal(A.lstrip(), tgt) + + tgt = [[b' abc', b''], + [b'2345', b'ixedCase'], + [b'23 \t 345 \x00', b'UPPER']] + assert_array_equal(A.lstrip([b'1', b'M']), tgt) + + tgt = [['\u03a3 ', ''], + ['12345', 'MixedCase'], + ['123 \t 345 \0 ', 'UPPER']] + assert_(issubclass(B.lstrip().dtype.type, np.str_)) + assert_array_equal(B.lstrip(), tgt) + + def test_partition(self): + A = self.A() + P = A.partition([b'3', b'M']) + tgt = [[(b' abc ', b'', b''), (b'', b'', b'')], + [(b'12', b'3', b'45'), (b'', b'M', b'ixedCase')], + [(b'12', b'3', b' \t 345 \0 '), (b'UPPER', b'', b'')]] + assert_(issubclass(P.dtype.type, np.bytes_)) + assert_array_equal(P, tgt) + + def test_replace(self): + A = self.A() + R = A.replace([b'3', b'a'], + [b'##########', b'@']) + tgt = [[b' abc ', b''], + [b'12##########45', b'MixedC@se'], + [b'12########## \t ##########45 \x00 ', b'UPPER']] + assert_(issubclass(R.dtype.type, np.bytes_)) + assert_array_equal(R, tgt) + # Test special cases that should just return the input array, + # since replacements are not possible or do nothing. + S1 = A.replace(b'A very long byte string, longer than A', b'') + assert_array_equal(S1, A) + S2 = A.replace(b'', b'') + assert_array_equal(S2, A) + S3 = A.replace(b'3', b'3') + assert_array_equal(S3, A) + S4 = A.replace(b'3', b'', count=0) + assert_array_equal(S4, A) + + def test_replace_count_and_size(self): + a = np.array(['0123456789' * i for i in range(4)] + ).view(np.char.chararray) + r1 = a.replace('5', 'ABCDE') + assert r1.dtype.itemsize == (3 * 10 + 3 * 4) * 4 + assert_array_equal(r1, np.array(['01234ABCDE6789' * i + for i in range(4)])) + r2 = a.replace('5', 'ABCDE', count=1) + assert r2.dtype.itemsize == (3 * 10 + 4) * 4 + r3 = a.replace('5', 'ABCDE', count=0) + assert r3.dtype.itemsize == a.dtype.itemsize + assert_array_equal(r3, a) + # Negative values mean to replace all. + r4 = a.replace('5', 'ABCDE', count=-1) + assert r4.dtype.itemsize == (3 * 10 + 3 * 4) * 4 + assert_array_equal(r4, r1) + # We can do count on an element-by-element basis. + r5 = a.replace('5', 'ABCDE', count=[-1, -1, -1, 1]) + assert r5.dtype.itemsize == (3 * 10 + 4) * 4 + assert_array_equal(r5, np.array( + ['01234ABCDE6789' * i for i in range(3)] + + ['01234ABCDE6789' + '0123456789' * 2])) + + def test_replace_broadcasting(self): + a = np.array('0,0,0').view(np.char.chararray) + r1 = a.replace('0', '1', count=np.arange(3)) + assert r1.dtype == a.dtype + assert_array_equal(r1, np.array(['0,0,0', '1,0,0', '1,1,0'])) + r2 = a.replace('0', [['1'], ['2']], count=np.arange(1, 4)) + assert_array_equal(r2, np.array([['1,0,0', '1,1,0', '1,1,1'], + ['2,0,0', '2,2,0', '2,2,2']])) + r3 = a.replace(['0', '0,0', '0,0,0'], 'X') + assert_array_equal(r3, np.array(['X,X,X', 'X,0', 'X'])) + + def test_rjust(self): + A = self.A() + assert_(issubclass(A.rjust(10).dtype.type, np.bytes_)) + + C = A.rjust([10, 20]) + assert_array_equal(np.char.str_len(C), [[10, 20], [10, 20], [12, 20]]) + + C = A.rjust(20, b'#') + assert_(np.all(C.startswith(b'#'))) + assert_array_equal(C.endswith(b'#'), + [[False, True], [False, False], [False, False]]) + + C = np.char.rjust(b'FOO', [[10, 20], [15, 8]]) + tgt = [[b' FOO', b' FOO'], + [b' FOO', b' FOO']] + assert_(issubclass(C.dtype.type, np.bytes_)) + assert_array_equal(C, tgt) + + def test_rpartition(self): + A = self.A() + P = A.rpartition([b'3', b'M']) + tgt = [[(b'', b'', b' abc '), (b'', b'', b'')], + [(b'12', b'3', b'45'), (b'', b'M', b'ixedCase')], + [(b'123 \t ', b'3', b'45 \0 '), (b'', b'', b'UPPER')]] + assert_(issubclass(P.dtype.type, np.bytes_)) + assert_array_equal(P, tgt) + + def test_rsplit(self): + A = self.A().rsplit(b'3') + tgt = [[[b' abc '], [b'']], + [[b'12', b'45'], [b'MixedCase']], + [[b'12', b' \t ', b'45 \x00 '], [b'UPPER']]] + assert_(issubclass(A.dtype.type, np.object_)) + assert_equal(A.tolist(), tgt) + + def test_rstrip(self): + A, B = self.A(), self.B() + assert_(issubclass(A.rstrip().dtype.type, np.bytes_)) + + tgt = [[b' abc', b''], + [b'12345', b'MixedCase'], + [b'123 \t 345', b'UPPER']] + assert_array_equal(A.rstrip(), tgt) + + tgt = [[b' abc ', b''], + [b'1234', b'MixedCase'], + [b'123 \t 345 \x00', b'UPP'] + ] + assert_array_equal(A.rstrip([b'5', b'ER']), tgt) + + tgt = [[' \u03a3', ''], + ['12345', 'MixedCase'], + ['123 \t 345', 'UPPER']] + assert_(issubclass(B.rstrip().dtype.type, np.str_)) + assert_array_equal(B.rstrip(), tgt) + + def test_strip(self): + A, B = self.A(), self.B() + tgt = [[b'abc', b''], + [b'12345', b'MixedCase'], + [b'123 \t 345', b'UPPER']] + assert_(issubclass(A.strip().dtype.type, np.bytes_)) + assert_array_equal(A.strip(), tgt) + + tgt = [[b' abc ', b''], + [b'234', b'ixedCas'], + [b'23 \t 345 \x00', b'UPP']] + assert_array_equal(A.strip([b'15', b'EReM']), tgt) + + tgt = [['\u03a3', ''], + ['12345', 'MixedCase'], + ['123 \t 345', 'UPPER']] + assert_(issubclass(B.strip().dtype.type, np.str_)) + assert_array_equal(B.strip(), tgt) + + def test_split(self): + A = self.A().split(b'3') + tgt = [ + [[b' abc '], [b'']], + [[b'12', b'45'], [b'MixedCase']], + [[b'12', b' \t ', b'45 \x00 '], [b'UPPER']]] + assert_(issubclass(A.dtype.type, np.object_)) + assert_equal(A.tolist(), tgt) + + def test_splitlines(self): + A = np.char.array(['abc\nfds\nwer']).splitlines() + assert_(issubclass(A.dtype.type, np.object_)) + assert_(A.shape == (1,)) + assert_(len(A[0]) == 3) + + def test_swapcase(self): + A, B = self.A(), self.B() + tgt = [[b' ABC ', b''], + [b'12345', b'mIXEDcASE'], + [b'123 \t 345 \0 ', b'upper']] + assert_(issubclass(A.swapcase().dtype.type, np.bytes_)) + assert_array_equal(A.swapcase(), tgt) + + tgt = [[' \u03c3 ', ''], + ['12345', 'mIXEDcASE'], + ['123 \t 345 \0 ', 'upper']] + assert_(issubclass(B.swapcase().dtype.type, np.str_)) + assert_array_equal(B.swapcase(), tgt) + + def test_title(self): + A, B = self.A(), self.B() + tgt = [[b' Abc ', b''], + [b'12345', b'Mixedcase'], + [b'123 \t 345 \0 ', b'Upper']] + assert_(issubclass(A.title().dtype.type, np.bytes_)) + assert_array_equal(A.title(), tgt) + + tgt = [[' \u03a3 ', ''], + ['12345', 'Mixedcase'], + ['123 \t 345 \0 ', 'Upper']] + assert_(issubclass(B.title().dtype.type, np.str_)) + assert_array_equal(B.title(), tgt) + + def test_upper(self): + A, B = self.A(), self.B() + tgt = [[b' ABC ', b''], + [b'12345', b'MIXEDCASE'], + [b'123 \t 345 \0 ', b'UPPER']] + assert_(issubclass(A.upper().dtype.type, np.bytes_)) + assert_array_equal(A.upper(), tgt) + + tgt = [[' \u03a3 ', ''], + ['12345', 'MIXEDCASE'], + ['123 \t 345 \0 ', 'UPPER']] + assert_(issubclass(B.upper().dtype.type, np.str_)) + assert_array_equal(B.upper(), tgt) + + def test_isnumeric(self): + A, B = self.A(), self.B() + + def fail(): + A.isnumeric() + + assert_raises(TypeError, fail) + assert_(issubclass(B.isnumeric().dtype.type, np.bool)) + assert_array_equal(B.isnumeric(), [ + [False, False], [True, False], [False, False]]) + + def test_isdecimal(self): + A, B = self.A(), self.B() + + def fail(): + A.isdecimal() + + assert_raises(TypeError, fail) + assert_(issubclass(B.isdecimal().dtype.type, np.bool)) + assert_array_equal(B.isdecimal(), [ + [False, False], [True, False], [False, False]]) + +class TestOperations: + def A(self): + return np.array([['abc', '123'], + ['789', 'xyz']]).view(np.char.chararray) + + def B(self): + return np.array([['efg', '456'], + ['051', 'tuv']]).view(np.char.chararray) + + def test_argsort(self): + arr = np.array(['abc'] * 4).view(np.char.chararray) + actual = arr.argsort(stable=True) + assert_array_equal(actual, [0, 1, 2, 3]) + + def test_add(self): + A, B = self.A(), self.B() + AB = np.array([['abcefg', '123456'], + ['789051', 'xyztuv']]).view(np.char.chararray) + assert_array_equal(AB, (A + B)) + assert_(len((A + B)[0][0]) == 6) + + def test_radd(self): + A = self.A() + QA = np.array([['qabc', 'q123'], + ['q789', 'qxyz']]).view(np.char.chararray) + assert_array_equal(QA, ('q' + A)) + + def test_mul(self): + A = self.A() + for r in (2, 3, 5, 7, 197): + Ar = np.array([[A[0, 0] * r, A[0, 1] * r], + [A[1, 0] * r, A[1, 1] * r]]).view(np.char.chararray) + + assert_array_equal(Ar, (A * r)) + + for ob in [object(), 'qrs']: + with assert_raises_regex(ValueError, + 'Can only multiply by integers'): + A * ob + + def test_rmul(self): + A = self.A() + for r in (2, 3, 5, 7, 197): + Ar = np.array([[A[0, 0] * r, A[0, 1] * r], + [A[1, 0] * r, A[1, 1] * r]]).view(np.char.chararray) + assert_array_equal(Ar, (r * A)) + + for ob in [object(), 'qrs']: + with assert_raises_regex(ValueError, + 'Can only multiply by integers'): + ob * A + + def test_mod(self): + """Ticket #856""" + F = np.array([['%d', '%f'], ['%s', '%r']]).view(np.char.chararray) + C = np.array([[3, 7], [19, 1]], dtype=np.int64) + FC = np.array([['3', '7.000000'], + ['19', 'np.int64(1)']]).view(np.char.chararray) + assert_array_equal(FC, F % C) + + A = np.array([['%.3f', '%d'], ['%s', '%r']]).view(np.char.chararray) + A1 = np.array([['1.000', '1'], + ['1', repr(np.array(1)[()])]]).view(np.char.chararray) + assert_array_equal(A1, (A % 1)) + + A2 = np.array([['1.000', '2'], + ['3', repr(np.array(4)[()])]]).view(np.char.chararray) + assert_array_equal(A2, (A % [[1, 2], [3, 4]])) + + def test_rmod(self): + A = self.A() + assert_(f"{A}" == str(A)) + assert_(f"{A!r}" == repr(A)) + + for ob in [42, object()]: + with assert_raises_regex( + TypeError, "unsupported operand type.* and 'chararray'"): + ob % A + + def test_slice(self): + """Regression test for https://github.com/numpy/numpy/issues/5982""" + + arr = np.array([['abc ', 'def '], ['geh ', 'ijk ']], + dtype='S4').view(np.char.chararray) + sl1 = arr[:] + assert_array_equal(sl1, arr) + assert_(sl1.base is arr) + assert_(sl1.base.base is arr.base) + + sl2 = arr[:, :] + assert_array_equal(sl2, arr) + assert_(sl2.base is arr) + assert_(sl2.base.base is arr.base) + + assert_(arr[0, 0] == b'abc') + + @pytest.mark.parametrize('data', [['plate', ' ', 'shrimp'], + [b'retro', b' ', b'encabulator']]) + def test_getitem_length_zero_item(self, data): + # Regression test for gh-26375. + a = np.char.array(data) + # a.dtype.type() will be an empty string or bytes instance. + # The equality test will fail if a[1] has the wrong type + # or does not have length 0. + assert_equal(a[1], a.dtype.type()) + +class TestMethodsEmptyArray: + def test_encode(self): + res = np.char.encode(np.array([], dtype='U')) + assert_array_equal(res, []) + assert_(res.dtype.char == 'S') + + def test_decode(self): + res = np.char.decode(np.array([], dtype='S')) + assert_array_equal(res, []) + assert_(res.dtype.char == 'U') + + def test_decode_with_reshape(self): + res = np.char.decode(np.array([], dtype='S').reshape((1, 0, 1))) + assert_(res.shape == (1, 0, 1)) + +class TestMethodsScalarValues: + def test_mod(self): + A = np.array([[' abc ', ''], + ['12345', 'MixedCase'], + ['123 \t 345 \0 ', 'UPPER']], dtype='S') + tgt = [[b'123 abc ', b'123'], + [b'12312345', b'123MixedCase'], + [b'123123 \t 345 \0 ', b'123UPPER']] + assert_array_equal(np.char.mod(b"123%s", A), tgt) + + def test_decode(self): + bytestring = b'\x81\xc1\x81\xc1\x81\xc1' + assert_equal(np.char.decode(bytestring, encoding='cp037'), + 'aAaAaA') + + def test_encode(self): + unicode = 'aAaAaA' + assert_equal(np.char.encode(unicode, encoding='cp037'), + b'\x81\xc1\x81\xc1\x81\xc1') + + def test_expandtabs(self): + s = "\tone level of indentation\n\t\ttwo levels of indentation" + assert_equal( + np.char.expandtabs(s, tabsize=2), + " one level of indentation\n two levels of indentation" + ) + + def test_join(self): + seps = np.array(['-', '_']) + assert_array_equal(np.char.join(seps, 'hello'), + ['h-e-l-l-o', 'h_e_l_l_o']) + + def test_partition(self): + assert_equal(np.char.partition('This string', ' '), + ['This', ' ', 'string']) + + def test_rpartition(self): + assert_equal(np.char.rpartition('This string here', ' '), + ['This string', ' ', 'here']) + + def test_replace(self): + assert_equal(np.char.replace('Python is good', 'good', 'great'), + 'Python is great') + +def test_empty_indexing(): + """Regression test for ticket 1948.""" + # Check that indexing a chararray with an empty list/array returns an + # empty chararray instead of a chararray with a single empty string in it. + s = np.char.chararray((4,)) + assert_(s[[]].size == 0) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_deprecations.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_deprecations.py new file mode 100644 index 0000000000000000000000000000000000000000..7cb1fee9b890f955c5683bfb8e0609baf6d880a0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_deprecations.py @@ -0,0 +1,460 @@ +""" +Tests related to deprecation warnings. Also a convenient place +to document how deprecations should eventually be turned into errors. + +""" +import contextlib +import warnings + +import pytest + +import numpy as np +import numpy._core._struct_ufunc_tests as struct_ufunc +from numpy._core._multiarray_tests import fromstring_null_term_c_api # noqa: F401 +from numpy.testing import assert_raises + + +class _DeprecationTestCase: + # Just as warning: warnings uses re.match, so the start of this message + # must match. + message = '' + warning_cls = DeprecationWarning + + @contextlib.contextmanager + def filter_warnings(self): + with warnings.catch_warnings(record=True) as w: + # Do *not* ignore other DeprecationWarnings. Ignoring warnings + # can give very confusing results because of + # https://bugs.python.org/issue4180 and it is probably simplest to + # try to keep the tests cleanly giving only the right warning type. + # (While checking them set to "error" those are ignored anyway) + # We still have them show up, because otherwise they would be raised + warnings.filterwarnings("always", category=self.warning_cls) + warnings.filterwarnings("always", message=self.message, + category=self.warning_cls) + yield w + return + + def assert_deprecated(self, function, num=1, ignore_others=False, + function_fails=False, + exceptions=np._NoValue, + args=(), kwargs={}): + """Test if DeprecationWarnings are given and raised. + + This first checks if the function when called gives `num` + DeprecationWarnings, after that it tries to raise these + DeprecationWarnings and compares them with `exceptions`. + The exceptions can be different for cases where this code path + is simply not anticipated and the exception is replaced. + + Parameters + ---------- + function : callable + The function to test + num : int + Number of DeprecationWarnings to expect. This should normally be 1. + ignore_others : bool + Whether warnings of the wrong type should be ignored (note that + the message is not checked) + function_fails : bool + If the function would normally fail, setting this will check for + warnings inside a try/except block. + exceptions : Exception or tuple of Exceptions + Exception to expect when turning the warnings into an error. + The default checks for DeprecationWarnings. If exceptions is + empty the function is expected to run successfully. + args : tuple + Arguments for `function` + kwargs : dict + Keyword arguments for `function` + """ + __tracebackhide__ = True # Hide traceback for py.test + + if exceptions is np._NoValue: + exceptions = (self.warning_cls,) + + if function_fails: + context_manager = contextlib.suppress(Exception) + else: + context_manager = contextlib.nullcontext() + with context_manager: + with self.filter_warnings() as w_context: + function(*args, **kwargs) + + # just in case, clear the registry + num_found = 0 + for warning in w_context: + if warning.category is self.warning_cls: + num_found += 1 + elif not ignore_others: + raise AssertionError( + "expected %s but got: %s" % + (self.warning_cls.__name__, warning.category)) + if num is not None and num_found != num: + msg = f"{len(w_context)} warnings found but {num} expected." + lst = [str(w) for w in w_context] + raise AssertionError("\n".join([msg] + lst)) + + with warnings.catch_warnings(): + warnings.filterwarnings("error", message=self.message, + category=self.warning_cls) + try: + function(*args, **kwargs) + if exceptions != (): + raise AssertionError( + "No error raised during function call") + except exceptions: + if exceptions == (): + raise AssertionError( + "Error raised during function call") + + def assert_not_deprecated(self, function, args=(), kwargs={}): + """Test that warnings are not raised. + + This is just a shorthand for: + + self.assert_deprecated(function, num=0, ignore_others=True, + exceptions=tuple(), args=args, kwargs=kwargs) + """ + self.assert_deprecated(function, num=0, ignore_others=True, + exceptions=(), args=args, kwargs=kwargs) + + +class _VisibleDeprecationTestCase(_DeprecationTestCase): + warning_cls = np.exceptions.VisibleDeprecationWarning + + +class TestTestDeprecated: + def test_assert_deprecated(self): + test_case_instance = _DeprecationTestCase() + assert_raises(AssertionError, + test_case_instance.assert_deprecated, + lambda: None) + + def foo(): + warnings.warn("foo", category=DeprecationWarning, stacklevel=2) + + test_case_instance.assert_deprecated(foo) + + +class TestBincount(_DeprecationTestCase): + # 2024-07-29, 2.1.0 + @pytest.mark.parametrize('badlist', [[0.5, 1.2, 1.5], + ['0', '1', '1']]) + def test_bincount_bad_list(self, badlist): + self.assert_deprecated(lambda: np.bincount(badlist)) + + +class BuiltInRoundComplexDType(_DeprecationTestCase): + # 2020-03-31 1.19.0 + deprecated_types = [np.csingle, np.cdouble, np.clongdouble] + not_deprecated_types = [ + np.int8, np.int16, np.int32, np.int64, + np.uint8, np.uint16, np.uint32, np.uint64, + np.float16, np.float32, np.float64, + ] + + def test_deprecated(self): + for scalar_type in self.deprecated_types: + scalar = scalar_type(0) + self.assert_deprecated(round, args=(scalar,)) + self.assert_deprecated(round, args=(scalar, 0)) + self.assert_deprecated(round, args=(scalar,), kwargs={'ndigits': 0}) + + def test_not_deprecated(self): + for scalar_type in self.not_deprecated_types: + scalar = scalar_type(0) + self.assert_not_deprecated(round, args=(scalar,)) + self.assert_not_deprecated(round, args=(scalar, 0)) + self.assert_not_deprecated(round, args=(scalar,), kwargs={'ndigits': 0}) + + +class FlatteningConcatenateUnsafeCast(_DeprecationTestCase): + # NumPy 1.20, 2020-09-03 + message = "concatenate with `axis=None` will use same-kind casting" + + def test_deprecated(self): + self.assert_deprecated(np.concatenate, + args=(([0.], [1.]),), + kwargs={'axis': None, 'out': np.empty(2, dtype=np.int64)}) + + def test_not_deprecated(self): + self.assert_not_deprecated(np.concatenate, + args=(([0.], [1.]),), + kwargs={'axis': None, 'out': np.empty(2, dtype=np.int64), + 'casting': "unsafe"}) + + with assert_raises(TypeError): + # Tests should notice if the deprecation warning is given first... + np.concatenate(([0.], [1.]), out=np.empty(2, dtype=np.int64), + casting="same_kind") + + +class TestCtypesGetter(_DeprecationTestCase): + ctypes = np.array([1]).ctypes + + @pytest.mark.parametrize("name", ["data", "shape", "strides", "_as_parameter_"]) + def test_not_deprecated(self, name: str) -> None: + self.assert_not_deprecated(lambda: getattr(self.ctypes, name)) + + +class TestPyIntConversion(_DeprecationTestCase): + message = r".*stop allowing conversion of out-of-bound.*" + + @pytest.mark.parametrize("dtype", np.typecodes["AllInteger"]) + def test_deprecated_scalar(self, dtype): + dtype = np.dtype(dtype) + info = np.iinfo(dtype) + + # Cover the most common creation paths (all end up in the + # same place): + def scalar(value, dtype): + dtype.type(value) + + def assign(value, dtype): + arr = np.array([0, 0, 0], dtype=dtype) + arr[2] = value + + def create(value, dtype): + np.array([value], dtype=dtype) + + for creation_func in [scalar, assign, create]: + try: + self.assert_deprecated( + lambda: creation_func(info.min - 1, dtype)) + except OverflowError: + pass # OverflowErrors always happened also before and are OK. + + try: + self.assert_deprecated( + lambda: creation_func(info.max + 1, dtype)) + except OverflowError: + pass # OverflowErrors always happened also before and are OK. + + +@pytest.mark.parametrize("name", ["str", "bytes", "object"]) +def test_future_scalar_attributes(name): + # FutureWarning added 2022-11-17, NumPy 1.24, + assert name not in dir(np) # we may want to not add them + with pytest.warns(FutureWarning, + match=f"In the future .*{name}"): + assert not hasattr(np, name) + + # Unfortunately, they are currently still valid via `np.dtype()` + np.dtype(name) + name in np._core.sctypeDict + + +# Ignore the above future attribute warning for this test. +@pytest.mark.filterwarnings("ignore:In the future:FutureWarning") +class TestRemovedGlobals: + # Removed 2023-01-12, NumPy 1.24.0 + # Not a deprecation, but the large error was added to aid those who missed + # the previous deprecation, and should be removed similarly to one + # (or faster). + @pytest.mark.parametrize("name", + ["object", "float", "complex", "str", "int"]) + def test_attributeerror_includes_info(self, name): + msg = f".*\n`np.{name}` was a deprecated alias for the builtin" + with pytest.raises(AttributeError, match=msg): + getattr(np, name) + + +class TestDeprecatedFinfo(_DeprecationTestCase): + # Deprecated in NumPy 1.25, 2023-01-16 + def test_deprecated_none(self): + self.assert_deprecated(np.finfo, args=(None,)) + + +class TestMathAlias(_DeprecationTestCase): + def test_deprecated_np_lib_math(self): + self.assert_deprecated(lambda: np.lib.math) + + +class TestLibImports(_DeprecationTestCase): + # Deprecated in Numpy 1.26.0, 2023-09 + def test_lib_functions_deprecation_call(self): + from numpy import row_stack + from numpy._core.numerictypes import maximum_sctype + from numpy.lib._npyio_impl import recfromcsv, recfromtxt + from numpy.lib._shape_base_impl import get_array_wrap + from numpy.lib._utils_impl import safe_eval + from numpy.lib.tests.test_io import TextIO + + self.assert_deprecated(lambda: safe_eval("None")) + + data_gen = lambda: TextIO('A,B\n0,1\n2,3') + kwargs = {'delimiter': ",", 'missing_values': "N/A", 'names': True} + self.assert_deprecated(lambda: recfromcsv(data_gen())) + self.assert_deprecated(lambda: recfromtxt(data_gen(), **kwargs)) + + self.assert_deprecated(get_array_wrap) + self.assert_deprecated(lambda: maximum_sctype(int)) + + self.assert_deprecated(lambda: row_stack([[]])) + self.assert_deprecated(lambda: np.chararray) + + +class TestDeprecatedDTypeAliases(_DeprecationTestCase): + + def _check_for_warning(self, func): + with pytest.warns(DeprecationWarning, + match="alias 'a' was deprecated in NumPy 2.0") as w: + func() + assert len(w) == 1 + + def test_a_dtype_alias(self): + for dtype in ["a", "a10"]: + f = lambda: np.dtype(dtype) + self._check_for_warning(f) + self.assert_deprecated(f) + f = lambda: np.array(["hello", "world"]).astype("a10") + self._check_for_warning(f) + self.assert_deprecated(f) + + +class TestDeprecatedArrayWrap(_DeprecationTestCase): + message = "__array_wrap__.*" + + def test_deprecated(self): + class Test1: + def __array__(self, dtype=None, copy=None): + return np.arange(4) + + def __array_wrap__(self, arr, context=None): + self.called = True + return 'pass context' + + class Test2(Test1): + def __array_wrap__(self, arr): + self.called = True + return 'pass' + + test1 = Test1() + test2 = Test2() + self.assert_deprecated(lambda: np.negative(test1)) + assert test1.called + self.assert_deprecated(lambda: np.negative(test2)) + assert test2.called + +class TestDeprecatedArrayAttributeSetting(_DeprecationTestCase): + message = "Setting the .*on a NumPy array has been deprecated.*" + + def test_deprecated_strides_set(self): + x = np.eye(2) + self.assert_deprecated(setattr, args=(x, 'strides', x.strides)) + + +class TestDeprecatedDTypeParenthesizedRepeatCount(_DeprecationTestCase): + message = "Passing in a parenthesized single number" + + @pytest.mark.parametrize("string", ["(2)i,", "(3)3S,", "f,(2)f"]) + def test_parenthesized_repeat_count(self, string): + self.assert_deprecated(np.dtype, args=(string,)) + + +class TestAddNewdocUFunc(_DeprecationTestCase): + # Deprecated in Numpy 2.2, 2024-11 + @pytest.mark.thread_unsafe( + reason="modifies and checks docstring which is global state" + ) + def test_deprecated(self): + doc = struct_ufunc.add_triplet.__doc__ + # gh-26718 + # This test mutates the C-level docstring pointer for add_triplet, + # which is permanent once set. Skip when re-running tests. + if doc is not None and "new docs" in doc: + pytest.skip("Cannot retest deprecation, otherwise ValueError: " + "Cannot change docstring of ufunc with non-NULL docstring") + self.assert_deprecated( + lambda: np._core.umath._add_newdoc_ufunc( + struct_ufunc.add_triplet, "new docs" + ) + ) + + +class TestDTypeAlignBool(_VisibleDeprecationTestCase): + # Deprecated in Numpy 2.4, 2025-07 + # NOTE: As you can see, finalizing this deprecation breaks some (very) old + # pickle files. This may be fine, but needs to be done with some care since + # it breaks all of them and not just some. + # (Maybe it should be a 3.0 or only after warning more explicitly around pickles.) + message = r"dtype\(\): align should be passed as Python or NumPy boolean but got " + + def test_deprecated(self): + # in particular integers should be rejected because one may think they mean + # alignment, or pass them accidentally as a subarray shape (meaning to pass + # a tuple). + self.assert_deprecated(lambda: np.dtype("f8", align=3)) + + @pytest.mark.parametrize("align", [True, False, np.True_, np.False_]) + def test_not_deprecated(self, align): + # if the user passes a bool, it is accepted. + self.assert_not_deprecated(lambda: np.dtype("f8", align=align)) + + +class TestFlatiterIndexing0dBoolIndex(_DeprecationTestCase): + # Deprecated in Numpy 2.4, 2025-07 + message = r"Indexing flat iterators with a 0-dimensional boolean index" + + def test_0d_boolean_index_deprecated(self): + arr = np.arange(3) + # 0d boolean indices on flat iterators are deprecated + self.assert_deprecated(lambda: arr.flat[True]) + + def test_0d_boolean_assign_index_deprecated(self): + arr = np.arange(3) + + def assign_to_index(): + arr.flat[True] = 10 + + self.assert_deprecated(assign_to_index) + + +class TestFlatiterIndexingFloatIndex(_DeprecationTestCase): + # Deprecated in NumPy 2.4, 2025-07 + message = r"Invalid non-array indices for iterator objects" + + def test_float_index_deprecated(self): + arr = np.arange(3) + # float indices on flat iterators are deprecated + self.assert_deprecated(lambda: arr.flat[[1.]]) + + def test_float_assign_index_deprecated(self): + arr = np.arange(3) + + def assign_to_index(): + arr.flat[[1.]] = 10 + + self.assert_deprecated(assign_to_index) + + +@pytest.mark.thread_unsafe( + reason="warning control utilities are deprecated due to being thread-unsafe" +) +class TestWarningUtilityDeprecations(_DeprecationTestCase): + # Deprecation in NumPy 2.4, 2025-08 + message = r"NumPy warning suppression and assertion utilities are deprecated." + + def test_assert_warns_deprecated(self): + def use_assert_warns(): + with np.testing.assert_warns(RuntimeWarning): + warnings.warn("foo", RuntimeWarning, stacklevel=1) + + self.assert_deprecated(use_assert_warns) + + def test_suppress_warnings_deprecated(self): + def use_suppress_warnings(): + with np.testing.suppress_warnings() as sup: + sup.filter(RuntimeWarning, 'invalid value encountered in divide') + + self.assert_deprecated(use_suppress_warnings) + + +class TestTooManyArgsExtremum(_DeprecationTestCase): + # Deprecated in Numpy 2.4, 2025-08, gh-27639 + message = "Passing more than 2 positional arguments to np.maximum and np.minimum " + + @pytest.mark.parametrize("ufunc", [np.minimum, np.maximum]) + def test_extremem_3_args(self, ufunc): + self.assert_deprecated(ufunc, args=(np.ones(1), np.zeros(1), np.empty(1))) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_dlpack.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_dlpack.py new file mode 100644 index 0000000000000000000000000000000000000000..e8198ac1823ec52a40736df52aa14ba1745f6d90 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_dlpack.py @@ -0,0 +1,190 @@ +import sys + +import pytest + +import numpy as np +from numpy.testing import IS_PYPY, assert_array_equal + + +def new_and_old_dlpack(): + yield np.arange(5) + + class OldDLPack(np.ndarray): + # Support only the "old" version + def __dlpack__(self, stream=None): + return super().__dlpack__(stream=None) + + yield np.arange(5).view(OldDLPack) + + +class TestDLPack: + @pytest.mark.skipif(IS_PYPY, reason="PyPy can't get refcounts.") + @pytest.mark.parametrize("max_version", [(0, 0), None, (1, 0), (100, 3)]) + def test_dunder_dlpack_refcount(self, max_version): + x = np.arange(5) + y = x.__dlpack__(max_version=max_version) + startcount = sys.getrefcount(x) + del y + assert startcount - sys.getrefcount(x) == 1 + + def test_dunder_dlpack_stream(self): + x = np.arange(5) + x.__dlpack__(stream=None) + + with pytest.raises(RuntimeError): + x.__dlpack__(stream=1) + + def test_dunder_dlpack_copy(self): + # Checks the argument parsing of __dlpack__ explicitly. + # Honoring the flag is tested in the from_dlpack round-tripping test. + x = np.arange(5) + x.__dlpack__(copy=True) + x.__dlpack__(copy=None) + x.__dlpack__(copy=False) + + with pytest.raises(ValueError): + # NOTE: The copy converter should be stricter, but not just here. + x.__dlpack__(copy=np.array([1, 2, 3])) + + def test_strides_not_multiple_of_itemsize(self): + dt = np.dtype([('int', np.int32), ('char', np.int8)]) + y = np.zeros((5,), dtype=dt) + z = y['int'] + + with pytest.raises(BufferError): + np.from_dlpack(z) + + @pytest.mark.skipif(IS_PYPY, reason="PyPy can't get refcounts.") + @pytest.mark.parametrize("arr", new_and_old_dlpack()) + def test_from_dlpack_refcount(self, arr): + arr = arr.copy() + y = np.from_dlpack(arr) + startcount = sys.getrefcount(arr) + del y + assert startcount - sys.getrefcount(arr) == 1 + + @pytest.mark.parametrize("dtype", [ + np.bool, + np.int8, np.int16, np.int32, np.int64, + np.uint8, np.uint16, np.uint32, np.uint64, + np.float16, np.float32, np.float64, + np.complex64, np.complex128 + ]) + @pytest.mark.parametrize("arr", new_and_old_dlpack()) + def test_dtype_passthrough(self, arr, dtype): + x = arr.astype(dtype) + y = np.from_dlpack(x) + + assert y.dtype == x.dtype + assert_array_equal(x, y) + + def test_invalid_dtype(self): + x = np.asarray(np.datetime64('2021-05-27')) + + with pytest.raises(BufferError): + np.from_dlpack(x) + + def test_invalid_byte_swapping(self): + dt = np.dtype('=i8').newbyteorder() + x = np.arange(5, dtype=dt) + + with pytest.raises(BufferError): + np.from_dlpack(x) + + def test_non_contiguous(self): + x = np.arange(25).reshape((5, 5)) + + y1 = x[0] + assert_array_equal(y1, np.from_dlpack(y1)) + + y2 = x[:, 0] + assert_array_equal(y2, np.from_dlpack(y2)) + + y3 = x[1, :] + assert_array_equal(y3, np.from_dlpack(y3)) + + y4 = x[1] + assert_array_equal(y4, np.from_dlpack(y4)) + + y5 = np.diagonal(x).copy() + assert_array_equal(y5, np.from_dlpack(y5)) + + @pytest.mark.parametrize("ndim", range(33)) + def test_higher_dims(self, ndim): + shape = (1,) * ndim + x = np.zeros(shape, dtype=np.float64) + + assert shape == np.from_dlpack(x).shape + + def test_dlpack_device(self): + x = np.arange(5) + assert x.__dlpack_device__() == (1, 0) + y = np.from_dlpack(x) + assert y.__dlpack_device__() == (1, 0) + z = y[::2] + assert z.__dlpack_device__() == (1, 0) + + def dlpack_deleter_exception(self, max_version): + x = np.arange(5) + _ = x.__dlpack__(max_version=max_version) + raise RuntimeError + + @pytest.mark.parametrize("max_version", [None, (1, 0)]) + def test_dlpack_destructor_exception(self, max_version): + with pytest.raises(RuntimeError): + self.dlpack_deleter_exception(max_version=max_version) + + def test_readonly(self): + x = np.arange(5) + x.flags.writeable = False + # Raises without max_version + with pytest.raises(BufferError): + x.__dlpack__() + + # But works fine if we try with version + y = np.from_dlpack(x) + assert not y.flags.writeable + + def test_writeable(self): + x_new, x_old = new_and_old_dlpack() + + # new dlpacks respect writeability + y = np.from_dlpack(x_new) + assert y.flags.writeable + + # old dlpacks are not writeable for backwards compatibility + y = np.from_dlpack(x_old) + assert not y.flags.writeable + + def test_ndim0(self): + x = np.array(1.0) + y = np.from_dlpack(x) + assert_array_equal(x, y) + + def test_size1dims_arrays(self): + x = np.ndarray(dtype='f8', shape=(10, 5, 1), strides=(8, 80, 4), + buffer=np.ones(1000, dtype=np.uint8), order='F') + y = np.from_dlpack(x) + assert_array_equal(x, y) + + def test_copy(self): + x = np.arange(5) + + y = np.from_dlpack(x) + assert np.may_share_memory(x, y) + y = np.from_dlpack(x, copy=False) + assert np.may_share_memory(x, y) + y = np.from_dlpack(x, copy=True) + assert not np.may_share_memory(x, y) + + def test_device(self): + x = np.arange(5) + # requesting (1, 0), i.e. CPU device works in both calls: + x.__dlpack__(dl_device=(1, 0)) + np.from_dlpack(x, device="cpu") + np.from_dlpack(x, device=None) + + with pytest.raises(BufferError): + x.__dlpack__(dl_device=(10, 0)) + with pytest.raises(ValueError): + np.from_dlpack(x, device="gpu") diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_dtype.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_dtype.py new file mode 100644 index 0000000000000000000000000000000000000000..157d3e4c97d1105a1c8a332c0c6004c654d11e50 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_dtype.py @@ -0,0 +1,2110 @@ +import contextlib +import ctypes +import gc +import inspect +import operator +import pickle +import sys +import types +from itertools import permutations +from typing import Any + +import hypothesis +import pytest +from hypothesis.extra import numpy as hynp + +import numpy as np +import numpy.dtypes +from numpy._core._multiarray_tests import create_custom_field_dtype +from numpy._core._rational_tests import rational +from numpy.testing import ( + HAS_REFCOUNT, + IS_64BIT, + IS_PYPY, + IS_PYSTON, + IS_WASM, + assert_, + assert_array_equal, + assert_equal, + assert_raises, +) + + +def assert_dtype_equal(a, b): + assert_equal(a, b) + assert_equal(hash(a), hash(b), + "two equivalent types do not hash to the same value !") + +def assert_dtype_not_equal(a, b): + assert_(a != b) + assert_(hash(a) != hash(b), + "two different types hash to the same value !") + +class TestBuiltin: + @pytest.mark.parametrize('t', [int, float, complex, np.int32, str, object]) + def test_run(self, t): + """Only test hash runs at all.""" + dt = np.dtype(t) + hash(dt) + + @pytest.mark.parametrize('t', [int, float]) + def test_dtype(self, t): + # Make sure equivalent byte order char hash the same (e.g. < and = on + # little endian) + dt = np.dtype(t) + dt2 = dt.newbyteorder("<") + dt3 = dt.newbyteorder(">") + if dt == dt2: + assert_(dt.byteorder != dt2.byteorder, "bogus test") + assert_dtype_equal(dt, dt2) + else: + assert_(dt.byteorder != dt3.byteorder, "bogus test") + assert_dtype_equal(dt, dt3) + + def test_equivalent_dtype_hashing(self): + # Make sure equivalent dtypes with different type num hash equal + uintp = np.dtype(np.uintp) + if uintp.itemsize == 4: + left = uintp + right = np.dtype(np.uint32) + else: + left = uintp + right = np.dtype(np.ulonglong) + assert_(left == right) + assert_(hash(left) == hash(right)) + + def test_invalid_types(self): + # Make sure invalid type strings raise an error + + assert_raises(TypeError, np.dtype, 'O3') + assert_raises(TypeError, np.dtype, 'O5') + assert_raises(TypeError, np.dtype, 'O7') + assert_raises(TypeError, np.dtype, 'b3') + assert_raises(TypeError, np.dtype, 'h4') + assert_raises(TypeError, np.dtype, 'I5') + assert_raises(TypeError, np.dtype, 'e3') + assert_raises(TypeError, np.dtype, 'f5') + + if np.dtype('g').itemsize == 8 or np.dtype('g').itemsize == 16: + assert_raises(TypeError, np.dtype, 'g12') + elif np.dtype('g').itemsize == 12: + assert_raises(TypeError, np.dtype, 'g16') + + if np.dtype('l').itemsize == 8: + assert_raises(TypeError, np.dtype, 'l4') + assert_raises(TypeError, np.dtype, 'L4') + else: + assert_raises(TypeError, np.dtype, 'l8') + assert_raises(TypeError, np.dtype, 'L8') + + if np.dtype('q').itemsize == 8: + assert_raises(TypeError, np.dtype, 'q4') + assert_raises(TypeError, np.dtype, 'Q4') + else: + assert_raises(TypeError, np.dtype, 'q8') + assert_raises(TypeError, np.dtype, 'Q8') + + # Make sure negative-sized dtype raises an error + assert_raises(TypeError, np.dtype, 'S-1') + assert_raises(TypeError, np.dtype, 'U-1') + assert_raises(TypeError, np.dtype, 'V-1') + + def test_richcompare_invalid_dtype_equality(self): + # Make sure objects that cannot be converted to valid + # dtypes results in False/True when compared to valid dtypes. + # Here 7 cannot be converted to dtype. No exceptions should be raised + + assert not np.dtype(np.int32) == 7, "dtype richcompare failed for ==" + assert np.dtype(np.int32) != 7, "dtype richcompare failed for !=" + + @pytest.mark.parametrize( + 'operation', + [operator.le, operator.lt, operator.ge, operator.gt]) + def test_richcompare_invalid_dtype_comparison(self, operation): + # Make sure TypeError is raised for comparison operators + # for invalid dtypes. Here 7 is an invalid dtype. + + with pytest.raises(TypeError): + operation(np.dtype(np.int32), 7) + + @pytest.mark.parametrize("dtype", + ['Bool', 'Bytes0', 'Complex32', 'Complex64', + 'Datetime64', 'Float16', 'Float32', 'Float64', + 'Int8', 'Int16', 'Int32', 'Int64', + 'Object0', 'Str0', 'Timedelta64', + 'UInt8', 'UInt16', 'Uint32', 'UInt32', + 'Uint64', 'UInt64', 'Void0', + "Float128", "Complex128"]) + def test_numeric_style_types_are_invalid(self, dtype): + with assert_raises(TypeError): + np.dtype(dtype) + + def test_expired_dtypes_with_bad_bytesize(self): + match: str = r".*removed in NumPy 2.0.*" + with pytest.raises(TypeError, match=match): + np.dtype("int0") + with pytest.raises(TypeError, match=match): + np.dtype("uint0") + with pytest.raises(TypeError, match=match): + np.dtype("bool8") + with pytest.raises(TypeError, match=match): + np.dtype("bytes0") + with pytest.raises(TypeError, match=match): + np.dtype("str0") + with pytest.raises(TypeError, match=match): + np.dtype("object0") + with pytest.raises(TypeError, match=match): + np.dtype("void0") + + @pytest.mark.parametrize( + 'value', + ['m8', 'M8', 'datetime64', 'timedelta64', + 'i4, (2,3)f8, f4', 'S3, 3u8, (3,4)S10', + '>f', '= (3, 12), + reason="Python 3.12 has immortal refcounts, this test will no longer " + "work. See gh-23986" +) +@pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") +class TestStructuredObjectRefcounting: + """These tests cover various uses of complicated structured types which + include objects and thus require reference counting. + """ + @pytest.mark.parametrize(['dt', 'pat', 'count', 'singleton'], + iter_struct_object_dtypes()) + @pytest.mark.parametrize(["creation_func", "creation_obj"], [ + pytest.param(np.empty, None, + # None is probably used for too many things + marks=pytest.mark.skip("unreliable due to python's behaviour")), + (np.ones, 1), + (np.zeros, 0)]) + def test_structured_object_create_delete(self, dt, pat, count, singleton, + creation_func, creation_obj): + """Structured object reference counting in creation and deletion""" + # The test assumes that 0, 1, and None are singletons. + gc.collect() + before = sys.getrefcount(creation_obj) + arr = creation_func(3, dt) + + now = sys.getrefcount(creation_obj) + assert now - before == count * 3 + del arr + now = sys.getrefcount(creation_obj) + assert now == before + + @pytest.mark.parametrize(['dt', 'pat', 'count', 'singleton'], + iter_struct_object_dtypes()) + def test_structured_object_item_setting(self, dt, pat, count, singleton): + """Structured object reference counting for simple item setting""" + one = 1 + + gc.collect() + before = sys.getrefcount(singleton) + arr = np.array([pat] * 3, dt) + assert sys.getrefcount(singleton) - before == count * 3 + # Fill with `1` and check that it was replaced correctly: + before2 = sys.getrefcount(one) + arr[...] = one + after2 = sys.getrefcount(one) + assert after2 - before2 == count * 3 + del arr + gc.collect() + assert sys.getrefcount(one) == before2 + assert sys.getrefcount(singleton) == before + + @pytest.mark.parametrize(['dt', 'pat', 'count', 'singleton'], + iter_struct_object_dtypes()) + @pytest.mark.parametrize( + ['shape', 'index', 'items_changed'], + [((3,), ([0, 2],), 2), + ((3, 2), ([0, 2], slice(None)), 4), + ((3, 2), ([0, 2], [1]), 2), + ((3,), ([True, False, True]), 2)]) + def test_structured_object_indexing(self, shape, index, items_changed, + dt, pat, count, singleton): + """Structured object reference counting for advanced indexing.""" + # Use two small negative values (should be singletons, but less likely + # to run into race-conditions). This failed in some threaded envs + # When using 0 and 1. If it fails again, should remove all explicit + # checks, and rely on `pytest-leaks` reference count checker only. + val0 = -4 + val1 = -5 + + arr = np.full(shape, val0, dt) + + gc.collect() + before_val0 = sys.getrefcount(val0) + before_val1 = sys.getrefcount(val1) + # Test item getting: + part = arr[index] + after_val0 = sys.getrefcount(val0) + assert after_val0 - before_val0 == count * items_changed + del part + # Test item setting: + arr[index] = val1 + gc.collect() + after_val0 = sys.getrefcount(val0) + after_val1 = sys.getrefcount(val1) + assert before_val0 - after_val0 == count * items_changed + assert after_val1 - before_val1 == count * items_changed + + @pytest.mark.parametrize(['dt', 'pat', 'count', 'singleton'], + iter_struct_object_dtypes()) + def test_structured_object_take_and_repeat(self, dt, pat, count, singleton): + """Structured object reference counting for specialized functions. + The older functions such as take and repeat use different code paths + then item setting (when writing this). + """ + indices = [0, 1] + + arr = np.array([pat] * 3, dt) + gc.collect() + before = sys.getrefcount(singleton) + res = arr.take(indices) + after = sys.getrefcount(singleton) + assert after - before == count * 2 + new = res.repeat(10) + gc.collect() + after_repeat = sys.getrefcount(singleton) + assert after_repeat - after == count * 2 * 10 + + +class TestStructuredDtypeSparseFields: + """Tests subarray fields which contain sparse dtypes so that + not all memory is used by the dtype work. Such dtype's should + leave the underlying memory unchanged. + """ + dtype = np.dtype([('a', {'names': ['aa', 'ab'], 'formats': ['f', 'f'], + 'offsets': [0, 4]}, (2, 3))]) + sparse_dtype = np.dtype([('a', {'names': ['ab'], 'formats': ['f'], + 'offsets': [4]}, (2, 3))]) + + def test_sparse_field_assignment(self): + arr = np.zeros(3, self.dtype) + sparse_arr = arr.view(self.sparse_dtype) + + sparse_arr[...] = np.finfo(np.float32).max + # dtype is reduced when accessing the field, so shape is (3, 2, 3): + assert_array_equal(arr["a"]["aa"], np.zeros((3, 2, 3))) + + def test_sparse_field_assignment_fancy(self): + # Fancy assignment goes to the copyswap function for complex types: + arr = np.zeros(3, self.dtype) + sparse_arr = arr.view(self.sparse_dtype) + + sparse_arr[[0, 1, 2]] = np.finfo(np.float32).max + # dtype is reduced when accessing the field, so shape is (3, 2, 3): + assert_array_equal(arr["a"]["aa"], np.zeros((3, 2, 3))) + + +class TestMonsterType: + """Test deeply nested subtypes.""" + + def test1(self): + simple1 = np.dtype({'names': ['r', 'b'], 'formats': ['u1', 'u1'], + 'titles': ['Red pixel', 'Blue pixel']}) + a = np.dtype([('yo', int), ('ye', simple1), + ('yi', np.dtype((int, (3, 2))))]) + b = np.dtype([('yo', int), ('ye', simple1), + ('yi', np.dtype((int, (3, 2))))]) + assert_dtype_equal(a, b) + + c = np.dtype([('yo', int), ('ye', simple1), + ('yi', np.dtype((a, (3, 2))))]) + d = np.dtype([('yo', int), ('ye', simple1), + ('yi', np.dtype((a, (3, 2))))]) + assert_dtype_equal(c, d) + + @pytest.mark.skipif(IS_PYSTON, reason="Pyston disables recursion checking") + @pytest.mark.skipif(IS_WASM, reason="Pyodide/WASM has limited stack size") + def test_list_recursion(self): + l = [] + l.append(('f', l)) + with pytest.raises(RecursionError): + np.dtype(l) + + @pytest.mark.skipif(IS_PYSTON, reason="Pyston disables recursion checking") + @pytest.mark.skipif(IS_WASM, reason="Pyodide/WASM has limited stack size") + def test_tuple_recursion(self): + d = np.int32 + for i in range(100000): + d = (d, (1,)) + # depending on OS and Python version, this might succeed + # see gh-30370 and cpython issue #142253 + with contextlib.suppress(RecursionError): + np.dtype(d) + + @pytest.mark.skipif(IS_PYSTON, reason="Pyston disables recursion checking") + @pytest.mark.skipif(IS_WASM, reason="Pyodide/WASM has limited stack size") + def test_dict_recursion(self): + d = {"names": ['self'], "formats": [None], "offsets": [0]} + d['formats'][0] = d + with pytest.raises(RecursionError): + np.dtype(d) + + +class TestMetadata: + def test_no_metadata(self): + d = np.dtype(int) + assert_(d.metadata is None) + + def test_metadata_takes_dict(self): + d = np.dtype(int, metadata={'datum': 1}) + assert_(d.metadata == {'datum': 1}) + + def test_metadata_rejects_nondict(self): + assert_raises(TypeError, np.dtype, int, metadata='datum') + assert_raises(TypeError, np.dtype, int, metadata=1) + assert_raises(TypeError, np.dtype, int, metadata=None) + + def test_nested_metadata(self): + d = np.dtype([('a', np.dtype(int, metadata={'datum': 1}))]) + assert_(d['a'].metadata == {'datum': 1}) + + def test_base_metadata_copied(self): + d = np.dtype((np.void, np.dtype('i4,i4', metadata={'datum': 1}))) + assert_(d.metadata == {'datum': 1}) + +class TestString: + def test_complex_dtype_str(self): + dt = np.dtype([('top', [('tiles', ('>f4', (64, 64)), (1,)), + ('rtile', '>f4', (64, 36))], (3,)), + ('bottom', [('bleft', ('>f4', (8, 64)), (1,)), + ('bright', '>f4', (8, 36))])]) + assert_equal(str(dt), + "[('top', [('tiles', ('>f4', (64, 64)), (1,)), " + "('rtile', '>f4', (64, 36))], (3,)), " + "('bottom', [('bleft', ('>f4', (8, 64)), (1,)), " + "('bright', '>f4', (8, 36))])]") + + # If the sticky aligned flag is set to True, it makes the + # str() function use a dict representation with an 'aligned' flag + dt = np.dtype([('top', [('tiles', ('>f4', (64, 64)), (1,)), + ('rtile', '>f4', (64, 36))], + (3,)), + ('bottom', [('bleft', ('>f4', (8, 64)), (1,)), + ('bright', '>f4', (8, 36))])], + align=True) + assert_equal(str(dt), + "{'names': ['top', 'bottom']," + " 'formats': [([('tiles', ('>f4', (64, 64)), (1,)), " + "('rtile', '>f4', (64, 36))], (3,)), " + "[('bleft', ('>f4', (8, 64)), (1,)), " + "('bright', '>f4', (8, 36))]]," + " 'offsets': [0, 76800]," + " 'itemsize': 80000," + " 'aligned': True}") + with np.printoptions(legacy='1.21'): + assert_equal(str(dt), + "{'names':['top','bottom'], " + "'formats':[([('tiles', ('>f4', (64, 64)), (1,)), " + "('rtile', '>f4', (64, 36))], (3,))," + "[('bleft', ('>f4', (8, 64)), (1,)), " + "('bright', '>f4', (8, 36))]], " + "'offsets':[0,76800], " + "'itemsize':80000, " + "'aligned':True}") + assert_equal(np.dtype(eval(str(dt))), dt) + + dt = np.dtype({'names': ['r', 'g', 'b'], 'formats': ['u1', 'u1', 'u1'], + 'offsets': [0, 1, 2], + 'titles': ['Red pixel', 'Green pixel', 'Blue pixel']}) + assert_equal(str(dt), + "[(('Red pixel', 'r'), 'u1'), " + "(('Green pixel', 'g'), 'u1'), " + "(('Blue pixel', 'b'), 'u1')]") + + dt = np.dtype({'names': ['rgba', 'r', 'g', 'b'], + 'formats': ['f4', (64, 64)), (1,)), + ('rtile', '>f4', (64, 36))], (3,)), + ('bottom', [('bleft', ('>f4', (8, 64)), (1,)), + ('bright', '>f4', (8, 36))])]) + assert_equal(repr(dt), + "dtype([('top', [('tiles', ('>f4', (64, 64)), (1,)), " + "('rtile', '>f4', (64, 36))], (3,)), " + "('bottom', [('bleft', ('>f4', (8, 64)), (1,)), " + "('bright', '>f4', (8, 36))])])") + + dt = np.dtype({'names': ['r', 'g', 'b'], 'formats': ['u1', 'u1', 'u1'], + 'offsets': [0, 1, 2], + 'titles': ['Red pixel', 'Green pixel', 'Blue pixel']}, + align=True) + assert_equal(repr(dt), + "dtype([(('Red pixel', 'r'), 'u1'), " + "(('Green pixel', 'g'), 'u1'), " + "(('Blue pixel', 'b'), 'u1')], align=True)") + + def test_repr_structured_not_packed(self): + dt = np.dtype({'names': ['rgba', 'r', 'g', 'b'], + 'formats': ['i4") + assert np.result_type(dt).isnative + assert np.result_type(dt).num == dt.num + + # dtype with empty space: + struct_dt = np.dtype(">i4,i1,f4', (2, 1)), ('b', 'u4')]) + self.check(BigEndStruct, expected) + + def test_little_endian_structure_packed(self): + class LittleEndStruct(ctypes.LittleEndianStructure): + _fields_ = [ + ('one', ctypes.c_uint8), + ('two', ctypes.c_uint32) + ] + _pack_ = 1 + expected = np.dtype([('one', 'u1'), ('two', 'B'), + ('b', '>H') + ], align=True) + self.check(PaddedStruct, expected) + + def test_simple_endian_types(self): + self.check(ctypes.c_uint16.__ctype_le__, np.dtype('u2')) + self.check(ctypes.c_uint8.__ctype_le__, np.dtype('u1')) + self.check(ctypes.c_uint8.__ctype_be__, np.dtype('u1')) + + all_types = set(np.typecodes['All']) + all_pairs = permutations(all_types, 2) + + @pytest.mark.parametrize("pair", all_pairs) + def test_pairs(self, pair): + """ + Check that np.dtype('x,y') matches [np.dtype('x'), np.dtype('y')] + Example: np.dtype('d,I') -> dtype([('f0', ' None: + alias = np.dtype[Any] + assert isinstance(alias, types.GenericAlias) + assert alias.__origin__ is np.dtype + + @pytest.mark.parametrize("code", np.typecodes["All"]) + def test_dtype_subclass(self, code: str) -> None: + cls = type(np.dtype(code)) + alias = cls[Any] + assert isinstance(alias, types.GenericAlias) + assert alias.__origin__ is cls + + @pytest.mark.parametrize("arg_len", range(4)) + def test_subscript_tuple(self, arg_len: int) -> None: + arg_tup = (Any,) * arg_len + if arg_len == 1: + assert np.dtype[arg_tup] + else: + with pytest.raises(TypeError): + np.dtype[arg_tup] + + def test_subscript_scalar(self) -> None: + assert np.dtype[Any] + + +def test_result_type_integers_and_unitless_timedelta64(): + # Regression test for gh-20077. The following call of `result_type` + # would cause a seg. fault. + td = np.timedelta64(4) + result = np.result_type(0, td) + assert_dtype_equal(result, td.dtype) + + +def test_creating_dtype_with_dtype_class_errors(): + # Regression test for #25031, calling `np.dtype` with itself segfaulted. + with pytest.raises(TypeError, match="Cannot convert np.dtype into a"): + np.array(np.ones(10), dtype=np.dtype) + + +@pytest.mark.skipif(sys.flags.optimize == 2, reason="Python running -OO") +@pytest.mark.skipif(IS_PYPY, reason="PyPy does not modify tp_doc") +class TestDTypeSignatures: + def test_signature_dtype(self): + sig = inspect.signature(np.dtype) + + assert len(sig.parameters) == 4 + + assert "dtype" in sig.parameters + assert sig.parameters["dtype"].kind is inspect.Parameter.POSITIONAL_OR_KEYWORD + assert sig.parameters["dtype"].default is inspect.Parameter.empty + + assert "align" in sig.parameters + assert sig.parameters["align"].kind is inspect.Parameter.POSITIONAL_OR_KEYWORD + assert sig.parameters["align"].default is False + + assert "copy" in sig.parameters + assert sig.parameters["copy"].kind is inspect.Parameter.POSITIONAL_OR_KEYWORD + assert sig.parameters["copy"].default is False + + # the optional `metadata` parameter has no default, so `**kwargs` must be used + assert "kwargs" in sig.parameters + assert sig.parameters["kwargs"].kind is inspect.Parameter.VAR_KEYWORD + assert sig.parameters["kwargs"].default is inspect.Parameter.empty + + def test_signature_dtype_newbyteorder(self): + sig = inspect.signature(np.dtype.newbyteorder) + + assert len(sig.parameters) == 2 + + assert "self" in sig.parameters + assert sig.parameters["self"].kind is inspect.Parameter.POSITIONAL_ONLY + assert sig.parameters["self"].default is inspect.Parameter.empty + + assert "new_order" in sig.parameters + assert sig.parameters["new_order"].kind is inspect.Parameter.POSITIONAL_ONLY + assert sig.parameters["new_order"].default == "S" + + @pytest.mark.parametrize("typename", np.dtypes.__all__) + def test_signature_dtypes_classes(self, typename: str): + dtype_type = getattr(np.dtypes, typename) + sig = inspect.signature(dtype_type) + + match typename.lower().removesuffix("dtype"): + case "bytes" | "str": + params_expect = {"size"} + case "void": + params_expect = {"length"} + case "datetime64" | "timedelta64": + params_expect = {"unit"} + case "string": + # `na_object` cannot be used in the text signature because of its + # `np._NoValue` default, which isn't supported by `inspect.signature`, + # so `**kwargs` is used instead. + params_expect = {"coerce", "kwargs"} + case _: + params_expect = set() + + params_actual = set(sig.parameters) + assert params_actual == params_expect diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_einsum.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_einsum.py new file mode 100644 index 0000000000000000000000000000000000000000..375ef03c1dd7417dbc9710b8317d746b1fc94617 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_einsum.py @@ -0,0 +1,1351 @@ +import itertools +import warnings + +import pytest + +import numpy as np +from numpy.testing import ( + assert_, + assert_allclose, + assert_almost_equal, + assert_array_equal, + assert_equal, + assert_raises, + assert_raises_regex, +) + +# Setup for optimize einsum +chars = 'abcdefghij' +sizes = np.array([2, 3, 4, 5, 4, 3, 2, 6, 5, 4, 3]) +global_size_dict = dict(zip(chars, sizes)) + + +class TestEinsum: + @pytest.mark.parametrize("do_opt", [True, False]) + @pytest.mark.parametrize("einsum_fn", [np.einsum, np.einsum_path]) + def test_einsum_errors(self, do_opt, einsum_fn): + # Need enough arguments + assert_raises(ValueError, einsum_fn, optimize=do_opt) + assert_raises(ValueError, einsum_fn, "", optimize=do_opt) + + # subscripts must be a string + assert_raises(TypeError, einsum_fn, 0, 0, optimize=do_opt) + + # issue 4528 revealed a segfault with this call + assert_raises(TypeError, einsum_fn, *(None,) * 63, optimize=do_opt) + + # number of operands must match count in subscripts string + assert_raises(ValueError, einsum_fn, "", 0, 0, optimize=do_opt) + assert_raises(ValueError, einsum_fn, ",", 0, [0], [0], + optimize=do_opt) + assert_raises(ValueError, einsum_fn, ",", [0], optimize=do_opt) + + # can't have more subscripts than dimensions in the operand + assert_raises(ValueError, einsum_fn, "i", 0, optimize=do_opt) + assert_raises(ValueError, einsum_fn, "ij", [0, 0], optimize=do_opt) + assert_raises(ValueError, einsum_fn, "...i", 0, optimize=do_opt) + assert_raises(ValueError, einsum_fn, "i...j", [0, 0], optimize=do_opt) + assert_raises(ValueError, einsum_fn, "i...", 0, optimize=do_opt) + assert_raises(ValueError, einsum_fn, "ij...", [0, 0], optimize=do_opt) + + # invalid ellipsis + assert_raises(ValueError, einsum_fn, "i..", [0, 0], optimize=do_opt) + assert_raises(ValueError, einsum_fn, ".i...", [0, 0], optimize=do_opt) + assert_raises(ValueError, einsum_fn, "j->..j", [0, 0], optimize=do_opt) + assert_raises(ValueError, einsum_fn, "j->.j...", [0, 0], + optimize=do_opt) + + # invalid subscript character + assert_raises(ValueError, einsum_fn, "i%...", [0, 0], optimize=do_opt) + assert_raises(ValueError, einsum_fn, "...j$", [0, 0], optimize=do_opt) + assert_raises(ValueError, einsum_fn, "i->&", [0, 0], optimize=do_opt) + + # output subscripts must appear in input + assert_raises(ValueError, einsum_fn, "i->ij", [0, 0], optimize=do_opt) + + # output subscripts may only be specified once + assert_raises(ValueError, einsum_fn, "ij->jij", [[0, 0], [0, 0]], + optimize=do_opt) + + # dimensions must match when being collapsed + assert_raises(ValueError, einsum_fn, "ii", + np.arange(6).reshape(2, 3), optimize=do_opt) + assert_raises(ValueError, einsum_fn, "ii->i", + np.arange(6).reshape(2, 3), optimize=do_opt) + + with assert_raises_regex(ValueError, "'b'"): + # gh-11221 - 'c' erroneously appeared in the error message + a = np.ones((3, 3, 4, 5, 6)) + b = np.ones((3, 4, 5)) + einsum_fn('aabcb,abc', a, b) + + with pytest.raises(ValueError): + a = np.arange(3) + # einsum_path does not yet accept kwarg 'casting' + np.einsum('ij->j', [a, a], casting='same_value') + + def test_einsum_sorting_behavior(self): + # Case 1: 26 dimensions (all lowercase indices) + n1 = 26 + x1 = np.random.random((1,) * n1) + path1 = np.einsum_path(x1, range(n1))[1] # Get einsum path details + output_indices1 = path1.split("->")[-1].strip() # Extract output indices + # Assert indices are only uppercase letters and sorted correctly + assert all(c.isupper() for c in output_indices1), ( + "Output indices for n=26 should use uppercase letters only: " + f"{output_indices1}" + ) + assert_equal( + output_indices1, + ''.join(sorted(output_indices1)), + err_msg=( + "Output indices for n=26 are not lexicographically sorted: " + f"{output_indices1}" + ) + ) + + # Case 2: 27 dimensions (includes uppercase indices) + n2 = 27 + x2 = np.random.random((1,) * n2) + path2 = np.einsum_path(x2, range(n2))[1] + output_indices2 = path2.split("->")[-1].strip() + # Assert indices include both uppercase and lowercase letters + assert any(c.islower() for c in output_indices2), ( + "Output indices for n=27 should include uppercase letters: " + f"{output_indices2}" + ) + # Assert output indices are sorted uppercase before lowercase + assert_equal( + output_indices2, + ''.join(sorted(output_indices2)), + err_msg=( + "Output indices for n=27 are not lexicographically sorted: " + f"{output_indices2}" + ) + ) + + # Additional Check: Ensure dimensions correspond correctly to indices + # Generate expected mapping of dimensions to indices + expected_indices = [ + chr(i + ord('A')) if i < 26 else chr(i - 26 + ord('a')) + for i in range(n2) + ] + assert_equal( + output_indices2, + ''.join(expected_indices), + err_msg=( + "Output indices do not map to the correct dimensions. Expected: " + f"{''.join(expected_indices)}, Got: {output_indices2}" + ) + ) + + @pytest.mark.parametrize("do_opt", [True, False]) + def test_einsum_specific_errors(self, do_opt): + # out parameter must be an array + assert_raises(TypeError, np.einsum, "", 0, out='test', + optimize=do_opt) + + # order parameter must be a valid order + assert_raises(ValueError, np.einsum, "", 0, order='W', + optimize=do_opt) + + # casting parameter must be a valid casting + assert_raises(ValueError, np.einsum, "", 0, casting='blah', + optimize=do_opt) + + # dtype parameter must be a valid dtype + assert_raises(TypeError, np.einsum, "", 0, dtype='bad_data_type', + optimize=do_opt) + + # other keyword arguments are rejected + assert_raises(TypeError, np.einsum, "", 0, bad_arg=0, optimize=do_opt) + + # broadcasting to new dimensions must be enabled explicitly + assert_raises(ValueError, np.einsum, "i", np.arange(6).reshape(2, 3), + optimize=do_opt) + assert_raises(ValueError, np.einsum, "i->i", [[0, 1], [0, 1]], + out=np.arange(4).reshape(2, 2), optimize=do_opt) + + # Check order kwarg, asanyarray allows 1d to pass through + assert_raises(ValueError, np.einsum, "i->i", + np.arange(6).reshape(-1, 1), optimize=do_opt, order='d') + + def test_einsum_object_errors(self): + # Exceptions created by object arithmetic should + # successfully propagate + + class CustomException(Exception): + pass + + class DestructoBox: + + def __init__(self, value, destruct): + self._val = value + self._destruct = destruct + + def __add__(self, other): + tmp = self._val + other._val + if tmp >= self._destruct: + raise CustomException + else: + self._val = tmp + return self + + def __radd__(self, other): + if other == 0: + return self + else: + return self.__add__(other) + + def __mul__(self, other): + tmp = self._val * other._val + if tmp >= self._destruct: + raise CustomException + else: + self._val = tmp + return self + + def __rmul__(self, other): + if other == 0: + return self + else: + return self.__mul__(other) + + a = np.array([DestructoBox(i, 5) for i in range(1, 10)], + dtype='object').reshape(3, 3) + + # raised from unbuffered_loop_nop1_ndim2 + assert_raises(CustomException, np.einsum, "ij->i", a) + + # raised from unbuffered_loop_nop1_ndim3 + b = np.array([DestructoBox(i, 100) for i in range(27)], + dtype='object').reshape(3, 3, 3) + assert_raises(CustomException, np.einsum, "i...k->...", b) + + # raised from unbuffered_loop_nop2_ndim2 + b = np.array([DestructoBox(i, 55) for i in range(1, 4)], + dtype='object') + assert_raises(CustomException, np.einsum, "ij, j", a, b) + + # raised from unbuffered_loop_nop2_ndim3 + assert_raises(CustomException, np.einsum, "ij, jh", a, a) + + # raised from PyArray_EinsteinSum + assert_raises(CustomException, np.einsum, "ij->", a) + + def test_einsum_views(self): + # pass-through + for do_opt in [True, False]: + a = np.arange(6).reshape((2, 3)) + + b = np.einsum("...", a, optimize=do_opt) + assert_(b.base is a.base) + + b = np.einsum(a, [Ellipsis], optimize=do_opt) + assert_(b.base is a.base) + + b = np.einsum("ij", a, optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, a) + + b = np.einsum(a, [0, 1], optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, a) + + # output is writeable whenever input is writeable + b = np.einsum("...", a, optimize=do_opt) + assert_(b.flags['WRITEABLE']) + a.flags['WRITEABLE'] = False + b = np.einsum("...", a, optimize=do_opt) + assert_(not b.flags['WRITEABLE']) + + # transpose + a = np.arange(6).reshape((2, 3)) + + b = np.einsum("ji", a, optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, a.T) + + b = np.einsum(a, [1, 0], optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, a.T) + + # diagonal + a = np.arange(9).reshape((3, 3)) + + b = np.einsum("ii->i", a, optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [a[i, i] for i in range(3)]) + + b = np.einsum(a, [0, 0], [0], optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [a[i, i] for i in range(3)]) + + # diagonal with various ways of broadcasting an additional dimension + a = np.arange(27).reshape((3, 3, 3)) + + b = np.einsum("...ii->...i", a, optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [[x[i, i] for i in range(3)] for x in a]) + + b = np.einsum(a, [Ellipsis, 0, 0], [Ellipsis, 0], optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [[x[i, i] for i in range(3)] for x in a]) + + b = np.einsum("ii...->...i", a, optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [[x[i, i] for i in range(3)] + for x in a.transpose(2, 0, 1)]) + + b = np.einsum(a, [0, 0, Ellipsis], [Ellipsis, 0], optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [[x[i, i] for i in range(3)] + for x in a.transpose(2, 0, 1)]) + + b = np.einsum("...ii->i...", a, optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [a[:, i, i] for i in range(3)]) + + b = np.einsum(a, [Ellipsis, 0, 0], [0, Ellipsis], optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [a[:, i, i] for i in range(3)]) + + b = np.einsum("jii->ij", a, optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [a[:, i, i] for i in range(3)]) + + b = np.einsum(a, [1, 0, 0], [0, 1], optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [a[:, i, i] for i in range(3)]) + + b = np.einsum("ii...->i...", a, optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [a.transpose(2, 0, 1)[:, i, i] for i in range(3)]) + + b = np.einsum(a, [0, 0, Ellipsis], [0, Ellipsis], optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [a.transpose(2, 0, 1)[:, i, i] for i in range(3)]) + + b = np.einsum("i...i->i...", a, optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [a.transpose(1, 0, 2)[:, i, i] for i in range(3)]) + + b = np.einsum(a, [0, Ellipsis, 0], [0, Ellipsis], optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [a.transpose(1, 0, 2)[:, i, i] for i in range(3)]) + + b = np.einsum("i...i->...i", a, optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [[x[i, i] for i in range(3)] + for x in a.transpose(1, 0, 2)]) + + b = np.einsum(a, [0, Ellipsis, 0], [Ellipsis, 0], optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [[x[i, i] for i in range(3)] + for x in a.transpose(1, 0, 2)]) + + # triple diagonal + a = np.arange(27).reshape((3, 3, 3)) + + b = np.einsum("iii->i", a, optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [a[i, i, i] for i in range(3)]) + + b = np.einsum(a, [0, 0, 0], [0], optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, [a[i, i, i] for i in range(3)]) + + # swap axes + a = np.arange(24).reshape((2, 3, 4)) + + b = np.einsum("ijk->jik", a, optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, a.swapaxes(0, 1)) + + b = np.einsum(a, [0, 1, 2], [1, 0, 2], optimize=do_opt) + assert_(b.base is a.base) + assert_equal(b, a.swapaxes(0, 1)) + + def check_einsum_sums(self, dtype, do_opt=False): + dtype = np.dtype(dtype) + # Check various sums. Does many sizes to exercise unrolled loops. + + # sum(a, axis=-1) + for n in range(1, 17): + a = np.arange(n, dtype=dtype) + b = np.sum(a, axis=-1) + if hasattr(b, 'astype'): + b = b.astype(dtype) + assert_equal(np.einsum("i->", a, optimize=do_opt), b) + assert_equal(np.einsum(a, [0], [], optimize=do_opt), b) + + for n in range(1, 17): + a = np.arange(2 * 3 * n, dtype=dtype).reshape(2, 3, n) + b = np.sum(a, axis=-1) + if hasattr(b, 'astype'): + b = b.astype(dtype) + assert_equal(np.einsum("...i->...", a, optimize=do_opt), b) + assert_equal(np.einsum(a, [Ellipsis, 0], [Ellipsis], optimize=do_opt), b) + + # sum(a, axis=0) + for n in range(1, 17): + a = np.arange(2 * n, dtype=dtype).reshape(2, n) + b = np.sum(a, axis=0) + if hasattr(b, 'astype'): + b = b.astype(dtype) + assert_equal(np.einsum("i...->...", a, optimize=do_opt), b) + assert_equal(np.einsum(a, [0, Ellipsis], [Ellipsis], optimize=do_opt), b) + + for n in range(1, 17): + a = np.arange(2 * 3 * n, dtype=dtype).reshape(2, 3, n) + b = np.sum(a, axis=0) + if hasattr(b, 'astype'): + b = b.astype(dtype) + assert_equal(np.einsum("i...->...", a, optimize=do_opt), b) + assert_equal(np.einsum(a, [0, Ellipsis], [Ellipsis], optimize=do_opt), b) + + # trace(a) + for n in range(1, 17): + a = np.arange(n * n, dtype=dtype).reshape(n, n) + b = np.trace(a) + if hasattr(b, 'astype'): + b = b.astype(dtype) + assert_equal(np.einsum("ii", a, optimize=do_opt), b) + assert_equal(np.einsum(a, [0, 0], optimize=do_opt), b) + + # gh-15961: should accept numpy int64 type in subscript list + np_array = np.asarray([0, 0]) + assert_equal(np.einsum(a, np_array, optimize=do_opt), b) + assert_equal(np.einsum(a, list(np_array), optimize=do_opt), b) + + # multiply(a, b) + assert_equal(np.einsum("..., ...", 3, 4), 12) # scalar case + for n in range(1, 17): + a = np.arange(3 * n, dtype=dtype).reshape(3, n) + b = np.arange(2 * 3 * n, dtype=dtype).reshape(2, 3, n) + assert_equal(np.einsum("..., ...", a, b, optimize=do_opt), + np.multiply(a, b)) + assert_equal(np.einsum(a, [Ellipsis], b, [Ellipsis], optimize=do_opt), + np.multiply(a, b)) + + # inner(a,b) + for n in range(1, 17): + a = np.arange(2 * 3 * n, dtype=dtype).reshape(2, 3, n) + b = np.arange(n, dtype=dtype) + assert_equal(np.einsum("...i, ...i", a, b, optimize=do_opt), np.inner(a, b)) + assert_equal(np.einsum(a, [Ellipsis, 0], b, [Ellipsis, 0], optimize=do_opt), + np.inner(a, b)) + + for n in range(1, 11): + a = np.arange(n * 3 * 2, dtype=dtype).reshape(n, 3, 2) + b = np.arange(n, dtype=dtype) + assert_equal(np.einsum("i..., i...", a, b, optimize=do_opt), + np.inner(a.T, b.T).T) + assert_equal(np.einsum(a, [0, Ellipsis], b, [0, Ellipsis], optimize=do_opt), + np.inner(a.T, b.T).T) + + # outer(a,b) + for n in range(1, 17): + a = np.arange(3, dtype=dtype) + 1 + b = np.arange(n, dtype=dtype) + 1 + assert_equal(np.einsum("i,j", a, b, optimize=do_opt), + np.outer(a, b)) + assert_equal(np.einsum(a, [0], b, [1], optimize=do_opt), + np.outer(a, b)) + + # Suppress the complex warnings for the 'as f8' tests + with warnings.catch_warnings(): + warnings.simplefilter('ignore', np.exceptions.ComplexWarning) + + # matvec(a,b) / a.dot(b) where a is matrix, b is vector + for n in range(1, 17): + a = np.arange(4 * n, dtype=dtype).reshape(4, n) + b = np.arange(n, dtype=dtype) + assert_equal(np.einsum("ij, j", a, b, optimize=do_opt), + np.dot(a, b)) + assert_equal(np.einsum(a, [0, 1], b, [1], optimize=do_opt), + np.dot(a, b)) + + c = np.arange(4, dtype=dtype) + np.einsum("ij,j", a, b, out=c, + dtype='f8', casting='unsafe', optimize=do_opt) + assert_equal(c, + np.dot(a.astype('f8'), + b.astype('f8')).astype(dtype)) + c[...] = 0 + np.einsum(a, [0, 1], b, [1], out=c, + dtype='f8', casting='unsafe', optimize=do_opt) + assert_equal(c, + np.dot(a.astype('f8'), + b.astype('f8')).astype(dtype)) + + for n in range(1, 17): + a = np.arange(4 * n, dtype=dtype).reshape(4, n) + b = np.arange(n, dtype=dtype) + assert_equal(np.einsum("ji,j", a.T, b.T, optimize=do_opt), + np.dot(b.T, a.T)) + assert_equal(np.einsum(a.T, [1, 0], b.T, [1], optimize=do_opt), + np.dot(b.T, a.T)) + + c = np.arange(4, dtype=dtype) + np.einsum("ji,j", a.T, b.T, out=c, + dtype='f8', casting='unsafe', optimize=do_opt) + assert_equal(c, + np.dot(b.T.astype('f8'), + a.T.astype('f8')).astype(dtype)) + c[...] = 0 + np.einsum(a.T, [1, 0], b.T, [1], out=c, + dtype='f8', casting='unsafe', optimize=do_opt) + assert_equal(c, + np.dot(b.T.astype('f8'), + a.T.astype('f8')).astype(dtype)) + + # matmat(a,b) / a.dot(b) where a is matrix, b is matrix + for n in range(1, 17): + if n < 8 or dtype != 'f2': + a = np.arange(4 * n, dtype=dtype).reshape(4, n) + b = np.arange(n * 6, dtype=dtype).reshape(n, 6) + assert_equal(np.einsum("ij,jk", a, b, optimize=do_opt), + np.dot(a, b)) + assert_equal(np.einsum(a, [0, 1], b, [1, 2], optimize=do_opt), + np.dot(a, b)) + + for n in range(1, 17): + a = np.arange(4 * n, dtype=dtype).reshape(4, n) + b = np.arange(n * 6, dtype=dtype).reshape(n, 6) + c = np.arange(24, dtype=dtype).reshape(4, 6) + np.einsum("ij,jk", a, b, out=c, dtype='f8', casting='unsafe', + optimize=do_opt) + assert_equal(c, + np.dot(a.astype('f8'), + b.astype('f8')).astype(dtype)) + c[...] = 0 + np.einsum(a, [0, 1], b, [1, 2], out=c, + dtype='f8', casting='unsafe', optimize=do_opt) + assert_equal(c, + np.dot(a.astype('f8'), + b.astype('f8')).astype(dtype)) + + # matrix triple product (note this is not currently an efficient + # way to multiply 3 matrices) + a = np.arange(12, dtype=dtype).reshape(3, 4) + b = np.arange(20, dtype=dtype).reshape(4, 5) + c = np.arange(30, dtype=dtype).reshape(5, 6) + if dtype != 'f2': + assert_equal(np.einsum("ij,jk,kl", a, b, c, optimize=do_opt), + a.dot(b).dot(c)) + assert_equal(np.einsum(a, [0, 1], b, [1, 2], c, [2, 3], + optimize=do_opt), a.dot(b).dot(c)) + + d = np.arange(18, dtype=dtype).reshape(3, 6) + np.einsum("ij,jk,kl", a, b, c, out=d, + dtype='f8', casting='unsafe', optimize=do_opt) + tgt = a.astype('f8').dot(b.astype('f8')) + tgt = tgt.dot(c.astype('f8')).astype(dtype) + assert_equal(d, tgt) + + d[...] = 0 + np.einsum(a, [0, 1], b, [1, 2], c, [2, 3], out=d, + dtype='f8', casting='unsafe', optimize=do_opt) + tgt = a.astype('f8').dot(b.astype('f8')) + tgt = tgt.dot(c.astype('f8')).astype(dtype) + assert_equal(d, tgt) + + # tensordot(a, b) + if np.dtype(dtype) != np.dtype('f2'): + a = np.arange(60, dtype=dtype).reshape(3, 4, 5) + b = np.arange(24, dtype=dtype).reshape(4, 3, 2) + assert_equal(np.einsum("ijk, jil -> kl", a, b), + np.tensordot(a, b, axes=([1, 0], [0, 1]))) + assert_equal(np.einsum(a, [0, 1, 2], b, [1, 0, 3], [2, 3]), + np.tensordot(a, b, axes=([1, 0], [0, 1]))) + + c = np.arange(10, dtype=dtype).reshape(5, 2) + np.einsum("ijk,jil->kl", a, b, out=c, + dtype='f8', casting='unsafe', optimize=do_opt) + assert_equal(c, np.tensordot(a.astype('f8'), b.astype('f8'), + axes=([1, 0], [0, 1])).astype(dtype)) + c[...] = 0 + np.einsum(a, [0, 1, 2], b, [1, 0, 3], [2, 3], out=c, + dtype='f8', casting='unsafe', optimize=do_opt) + assert_equal(c, np.tensordot(a.astype('f8'), b.astype('f8'), + axes=([1, 0], [0, 1])).astype(dtype)) + + # logical_and(logical_and(a!=0, b!=0), c!=0) + neg_val = -2 if dtype.kind != "u" else np.iinfo(dtype).max - 1 + a = np.array([1, 3, neg_val, 0, 12, 13, 0, 1], dtype=dtype) + b = np.array([0, 3.5, 0., neg_val, 0, 1, 3, 12], dtype=dtype) + c = np.array([True, True, False, True, True, False, True, True]) + + assert_equal(np.einsum("i,i,i->i", a, b, c, + dtype='?', casting='unsafe', optimize=do_opt), + np.logical_and(np.logical_and(a != 0, b != 0), c != 0)) + assert_equal(np.einsum(a, [0], b, [0], c, [0], [0], + dtype='?', casting='unsafe'), + np.logical_and(np.logical_and(a != 0, b != 0), c != 0)) + + a = np.arange(9, dtype=dtype) + assert_equal(np.einsum(",i->", 3, a), 3 * np.sum(a)) + assert_equal(np.einsum(3, [], a, [0], []), 3 * np.sum(a)) + assert_equal(np.einsum("i,->", a, 3), 3 * np.sum(a)) + assert_equal(np.einsum(a, [0], 3, [], []), 3 * np.sum(a)) + + # Various stride0, contiguous, and SSE aligned variants + for n in range(1, 25): + a = np.arange(n, dtype=dtype) + if np.dtype(dtype).itemsize > 1: + assert_equal(np.einsum("...,...", a, a, optimize=do_opt), + np.multiply(a, a)) + assert_equal(np.einsum("i,i", a, a, optimize=do_opt), np.dot(a, a)) + assert_equal(np.einsum("i,->i", a, 2, optimize=do_opt), 2 * a) + assert_equal(np.einsum(",i->i", 2, a, optimize=do_opt), 2 * a) + assert_equal(np.einsum("i,->", a, 2, optimize=do_opt), 2 * np.sum(a)) + assert_equal(np.einsum(",i->", 2, a, optimize=do_opt), 2 * np.sum(a)) + + assert_equal(np.einsum("...,...", a[1:], a[:-1], optimize=do_opt), + np.multiply(a[1:], a[:-1])) + assert_equal(np.einsum("i,i", a[1:], a[:-1], optimize=do_opt), + np.dot(a[1:], a[:-1])) + assert_equal(np.einsum("i,->i", a[1:], 2, optimize=do_opt), 2 * a[1:]) + assert_equal(np.einsum(",i->i", 2, a[1:], optimize=do_opt), 2 * a[1:]) + assert_equal(np.einsum("i,->", a[1:], 2, optimize=do_opt), + 2 * np.sum(a[1:])) + assert_equal(np.einsum(",i->", 2, a[1:], optimize=do_opt), + 2 * np.sum(a[1:])) + + # An object array, summed as the data type + a = np.arange(9, dtype=object) + + b = np.einsum("i->", a, dtype=dtype, casting='unsafe') + assert_equal(b, np.sum(a)) + if hasattr(b, "dtype"): + # Can be a python object when dtype is object + assert_equal(b.dtype, np.dtype(dtype)) + + b = np.einsum(a, [0], [], dtype=dtype, casting='unsafe') + assert_equal(b, np.sum(a)) + if hasattr(b, "dtype"): + # Can be a python object when dtype is object + assert_equal(b.dtype, np.dtype(dtype)) + + # A case which was failing (ticket #1885) + p = np.arange(2) + 1 + q = np.arange(4).reshape(2, 2) + 3 + r = np.arange(4).reshape(2, 2) + 7 + assert_equal(np.einsum('z,mz,zm->', p, q, r), 253) + + # singleton dimensions broadcast (gh-10343) + p = np.ones((10, 2)) + q = np.ones((1, 2)) + assert_array_equal(np.einsum('ij,ij->j', p, q, optimize=True), + np.einsum('ij,ij->j', p, q, optimize=False)) + assert_array_equal(np.einsum('ij,ij->j', p, q, optimize=True), + [10.] * 2) + + # a blas-compatible contraction broadcasting case which was failing + # for optimize=True (ticket #10930) + x = np.array([2., 3.]) + y = np.array([4.]) + assert_array_equal(np.einsum("i, i", x, y, optimize=False), 20.) + assert_array_equal(np.einsum("i, i", x, y, optimize=True), 20.) + + # all-ones array was bypassing bug (ticket #10930) + p = np.ones((1, 5)) / 2 + q = np.ones((5, 5)) / 2 + for optimize in (True, False): + assert_array_equal(np.einsum("...ij,...jk->...ik", p, p, + optimize=optimize), + np.einsum("...ij,...jk->...ik", p, q, + optimize=optimize)) + assert_array_equal(np.einsum("...ij,...jk->...ik", p, q, + optimize=optimize), + np.full((1, 5), 1.25)) + + # Cases which were failing (gh-10899) + x = np.eye(2, dtype=dtype) + y = np.ones(2, dtype=dtype) + assert_array_equal(np.einsum("ji,i->", x, y, optimize=optimize), + [2.]) # contig_contig_outstride0_two + assert_array_equal(np.einsum("i,ij->", y, x, optimize=optimize), + [2.]) # stride0_contig_outstride0_two + assert_array_equal(np.einsum("ij,i->", x, y, optimize=optimize), + [2.]) # contig_stride0_outstride0_two + + def test_einsum_sums_int8(self): + self.check_einsum_sums('i1') + + def test_einsum_sums_uint8(self): + self.check_einsum_sums('u1') + + def test_einsum_sums_int16(self): + self.check_einsum_sums('i2') + + def test_einsum_sums_uint16(self): + self.check_einsum_sums('u2') + + def test_einsum_sums_int32(self): + self.check_einsum_sums('i4') + self.check_einsum_sums('i4', True) + + def test_einsum_sums_uint32(self): + self.check_einsum_sums('u4') + self.check_einsum_sums('u4', True) + + def test_einsum_sums_int64(self): + self.check_einsum_sums('i8') + + def test_einsum_sums_uint64(self): + self.check_einsum_sums('u8') + + def test_einsum_sums_float16(self): + self.check_einsum_sums('f2') + + def test_einsum_sums_float32(self): + self.check_einsum_sums('f4') + + def test_einsum_sums_float64(self): + self.check_einsum_sums('f8') + self.check_einsum_sums('f8', True) + + def test_einsum_sums_longdouble(self): + self.check_einsum_sums(np.longdouble) + + def test_einsum_sums_cfloat64(self): + self.check_einsum_sums('c8') + self.check_einsum_sums('c8', True) + + def test_einsum_sums_cfloat128(self): + self.check_einsum_sums('c16') + + def test_einsum_sums_clongdouble(self): + self.check_einsum_sums(np.clongdouble) + + def test_einsum_sums_object(self): + self.check_einsum_sums('object') + self.check_einsum_sums('object', True) + + def test_einsum_misc(self): + # This call used to crash because of a bug in + # PyArray_AssignZero + a = np.ones((1, 2)) + b = np.ones((2, 2, 1)) + assert_equal(np.einsum('ij...,j...->i...', a, b), [[[2], [2]]]) + assert_equal(np.einsum('ij...,j...->i...', a, b, optimize=True), [[[2], [2]]]) + + # Regression test for issue #10369 (test unicode inputs with Python 2) + assert_equal(np.einsum('ij...,j...->i...', a, b), [[[2], [2]]]) + assert_equal(np.einsum('...i,...i', [1, 2, 3], [2, 3, 4]), 20) + assert_equal(np.einsum('...i,...i', [1, 2, 3], [2, 3, 4], + optimize='greedy'), 20) + + # The iterator had an issue with buffering this reduction + a = np.ones((5, 12, 4, 2, 3), np.int64) + b = np.ones((5, 12, 11), np.int64) + assert_equal(np.einsum('ijklm,ijn,ijn->', a, b, b), + np.einsum('ijklm,ijn->', a, b)) + assert_equal(np.einsum('ijklm,ijn,ijn->', a, b, b, optimize=True), + np.einsum('ijklm,ijn->', a, b, optimize=True)) + + # Issue #2027, was a problem in the contiguous 3-argument + # inner loop implementation + a = np.arange(1, 3) + b = np.arange(1, 5).reshape(2, 2) + c = np.arange(1, 9).reshape(4, 2) + assert_equal(np.einsum('x,yx,zx->xzy', a, b, c), + [[[1, 3], [3, 9], [5, 15], [7, 21]], + [[8, 16], [16, 32], [24, 48], [32, 64]]]) + assert_equal(np.einsum('x,yx,zx->xzy', a, b, c, optimize=True), + [[[1, 3], [3, 9], [5, 15], [7, 21]], + [[8, 16], [16, 32], [24, 48], [32, 64]]]) + + # Ensure explicitly setting out=None does not cause an error + # see issue gh-15776 and issue gh-15256 + assert_equal(np.einsum('i,j', [1], [2], out=None), [[2]]) + + def test_object_loop(self): + + class Mult: + def __mul__(self, other): + return 42 + + objMult = np.array([Mult()]) + objNULL = np.ndarray(buffer=b'\0' * np.intp(0).itemsize, shape=1, dtype=object) + + with pytest.raises(TypeError): + np.einsum("i,j", [1], objNULL) + with pytest.raises(TypeError): + np.einsum("i,j", objNULL, [1]) + assert np.einsum("i,j", objMult, objMult) == 42 + + def test_subscript_range(self): + # Issue #7741, make sure that all letters of Latin alphabet (both uppercase & lowercase) can be used + # when creating a subscript from arrays + a = np.ones((2, 3)) + b = np.ones((3, 4)) + np.einsum(a, [0, 20], b, [20, 2], [0, 2], optimize=False) + np.einsum(a, [0, 27], b, [27, 2], [0, 2], optimize=False) + np.einsum(a, [0, 51], b, [51, 2], [0, 2], optimize=False) + assert_raises(ValueError, lambda: np.einsum(a, [0, 52], b, [52, 2], [0, 2], optimize=False)) + assert_raises(ValueError, lambda: np.einsum(a, [-1, 5], b, [5, 2], [-1, 2], optimize=False)) + + def test_einsum_broadcast(self): + # Issue #2455 change in handling ellipsis + # remove the 'middle broadcast' error + # only use the 'RIGHT' iteration in prepare_op_axes + # adds auto broadcast on left where it belongs + # broadcast on right has to be explicit + # We need to test the optimized parsing as well + + A = np.arange(2 * 3 * 4).reshape(2, 3, 4) + B = np.arange(3) + ref = np.einsum('ijk,j->ijk', A, B, optimize=False) + for opt in [True, False]: + assert_equal(np.einsum('ij...,j...->ij...', A, B, optimize=opt), ref) + assert_equal(np.einsum('ij...,...j->ij...', A, B, optimize=opt), ref) + assert_equal(np.einsum('ij...,j->ij...', A, B, optimize=opt), ref) # used to raise error + + A = np.arange(12).reshape((4, 3)) + B = np.arange(6).reshape((3, 2)) + ref = np.einsum('ik,kj->ij', A, B, optimize=False) + for opt in [True, False]: + assert_equal(np.einsum('ik...,k...->i...', A, B, optimize=opt), ref) + assert_equal(np.einsum('ik...,...kj->i...j', A, B, optimize=opt), ref) + assert_equal(np.einsum('...k,kj', A, B, optimize=opt), ref) # used to raise error + assert_equal(np.einsum('ik,k...->i...', A, B, optimize=opt), ref) # used to raise error + + dims = [2, 3, 4, 5] + a = np.arange(np.prod(dims)).reshape(dims) + v = np.arange(dims[2]) + ref = np.einsum('ijkl,k->ijl', a, v, optimize=False) + for opt in [True, False]: + assert_equal(np.einsum('ijkl,k', a, v, optimize=opt), ref) + assert_equal(np.einsum('...kl,k', a, v, optimize=opt), ref) # used to raise error + assert_equal(np.einsum('...kl,k...', a, v, optimize=opt), ref) + + J, K, M = 160, 160, 120 + A = np.arange(J * K * M).reshape(1, 1, 1, J, K, M) + B = np.arange(J * K * M * 3).reshape(J, K, M, 3) + ref = np.einsum('...lmn,...lmno->...o', A, B, optimize=False) + for opt in [True, False]: + assert_equal(np.einsum('...lmn,lmno->...o', A, B, + optimize=opt), ref) # used to raise error + + def test_einsum_fixedstridebug(self): + # Issue #4485 obscure einsum bug + # This case revealed a bug in nditer where it reported a stride + # as 'fixed' (0) when it was in fact not fixed during processing + # (0 or 4). The reason for the bug was that the check for a fixed + # stride was using the information from the 2D inner loop reuse + # to restrict the iteration dimensions it had to validate to be + # the same, but that 2D inner loop reuse logic is only triggered + # during the buffer copying step, and hence it was invalid to + # rely on those values. The fix is to check all the dimensions + # of the stride in question, which in the test case reveals that + # the stride is not fixed. + # + # NOTE: This test is triggered by the fact that the default buffersize, + # used by einsum, is 8192, and 3*2731 = 8193, is larger than that + # and results in a mismatch between the buffering and the + # striding for operand A. + A = np.arange(2 * 3).reshape(2, 3).astype(np.float32) + B = np.arange(2 * 3 * 2731).reshape(2, 3, 2731).astype(np.int16) + es = np.einsum('cl, cpx->lpx', A, B) + tp = np.tensordot(A, B, axes=(0, 0)) + assert_equal(es, tp) + # The following is the original test case from the bug report, + # made repeatable by changing random arrays to aranges. + A = np.arange(3 * 3).reshape(3, 3).astype(np.float64) + B = np.arange(3 * 3 * 64 * 64).reshape(3, 3, 64, 64).astype(np.float32) + es = np.einsum('cl, cpxy->lpxy', A, B) + tp = np.tensordot(A, B, axes=(0, 0)) + assert_equal(es, tp) + + def test_einsum_fixed_collapsingbug(self): + # Issue #5147. + # The bug only occurred when output argument of einssum was used. + x = np.random.normal(0, 1, (5, 5, 5, 5)) + y1 = np.zeros((5, 5)) + np.einsum('aabb->ab', x, out=y1) + idx = np.arange(5) + y2 = x[idx[:, None], idx[:, None], idx, idx] + assert_equal(y1, y2) + + def test_einsum_failed_on_p9_and_s390x(self): + # Issues gh-14692 and gh-12689 + # Bug with signed vs unsigned char errored on power9 and s390x Linux + tensor = np.random.random_sample((10, 10, 10, 10)) + x = np.einsum('ijij->', tensor) + y = tensor.trace(axis1=0, axis2=2).trace() + assert_allclose(x, y) + + def test_einsum_all_contig_non_contig_output(self): + # Issue gh-5907, tests that the all contiguous special case + # actually checks the contiguity of the output + x = np.ones((5, 5)) + out = np.ones(10)[::2] + correct_base = np.ones(10) + correct_base[::2] = 5 + # Always worked (inner iteration is done with 0-stride): + np.einsum('mi,mi,mi->m', x, x, x, out=out) + assert_array_equal(out.base, correct_base) + # Example 1: + out = np.ones(10)[::2] + np.einsum('im,im,im->m', x, x, x, out=out) + assert_array_equal(out.base, correct_base) + # Example 2, buffering causes x to be contiguous but + # special cases do not catch the operation before: + out = np.ones((2, 2, 2))[..., 0] + correct_base = np.ones((2, 2, 2)) + correct_base[..., 0] = 2 + x = np.ones((2, 2), np.float32) + np.einsum('ij,jk->ik', x, x, out=out) + assert_array_equal(out.base, correct_base) + + @pytest.mark.parametrize("dtype", + np.typecodes["AllFloat"] + np.typecodes["AllInteger"]) + def test_different_paths(self, dtype): + # Test originally added to cover broken float16 path: gh-20305 + # Likely most are covered elsewhere, at least partially. + dtype = np.dtype(dtype) + # Simple test, designed to exercise most specialized code paths, + # note the +0.5 for floats. This makes sure we use a float value + # where the results must be exact. + arr = (np.arange(7) + 0.5).astype(dtype) + scalar = np.array(2, dtype=dtype) + + # contig -> scalar: + res = np.einsum('i->', arr) + assert res == arr.sum() + # contig, contig -> contig: + res = np.einsum('i,i->i', arr, arr) + assert_array_equal(res, arr * arr) + # noncontig, noncontig -> contig: + res = np.einsum('i,i->i', arr.repeat(2)[::2], arr.repeat(2)[::2]) + assert_array_equal(res, arr * arr) + # contig + contig -> scalar + assert np.einsum('i,i->', arr, arr) == (arr * arr).sum() + # contig + scalar -> contig (with out) + out = np.ones(7, dtype=dtype) + res = np.einsum('i,->i', arr, dtype.type(2), out=out) + assert_array_equal(res, arr * dtype.type(2)) + # scalar + contig -> contig (with out) + res = np.einsum(',i->i', scalar, arr) + assert_array_equal(res, arr * dtype.type(2)) + # scalar + contig -> scalar + res = np.einsum(',i->', scalar, arr) + # Use einsum to compare to not have difference due to sum round-offs: + assert res == np.einsum('i->', scalar * arr) + # contig + scalar -> scalar + res = np.einsum('i,->', arr, scalar) + # Use einsum to compare to not have difference due to sum round-offs: + assert res == np.einsum('i->', scalar * arr) + # contig + contig + contig -> scalar + arr = np.array([0.5, 0.5, 0.25, 4.5, 3.], dtype=dtype) + res = np.einsum('i,i,i->', arr, arr, arr) + assert_array_equal(res, (arr * arr * arr).sum()) + # four arrays: + res = np.einsum('i,i,i,i->', arr, arr, arr, arr) + assert_array_equal(res, (arr * arr * arr * arr).sum()) + + def test_small_boolean_arrays(self): + # See gh-5946. + # Use array of True embedded in False. + a = np.zeros((16, 1, 1), dtype=np.bool)[:2] + a[...] = True + out = np.zeros((16, 1, 1), dtype=np.bool)[:2] + tgt = np.ones((2, 1, 1), dtype=np.bool) + res = np.einsum('...ij,...jk->...ik', a, a, out=out) + assert_equal(res, tgt) + + def test_out_is_res(self): + a = np.arange(9).reshape(3, 3) + res = np.einsum('...ij,...jk->...ik', a, a, out=a) + assert res is a + + def optimize_compare(self, subscripts, operands=None): + # Tests all paths of the optimization function against + # conventional einsum + if operands is None: + args = [subscripts] + terms = subscripts.split('->')[0].split(',') + for term in terms: + dims = [global_size_dict[x] for x in term] + args.append(np.random.rand(*dims)) + else: + args = [subscripts] + operands + + noopt = np.einsum(*args, optimize=False) + opt = np.einsum(*args, optimize='greedy') + assert_almost_equal(opt, noopt) + opt = np.einsum(*args, optimize='optimal') + assert_almost_equal(opt, noopt) + + def test_hadamard_like_products(self): + # Hadamard outer products + self.optimize_compare('a,ab,abc->abc') + self.optimize_compare('a,b,ab->ab') + + def test_index_transformations(self): + # Simple index transformation cases + self.optimize_compare('ea,fb,gc,hd,abcd->efgh') + self.optimize_compare('ea,fb,abcd,gc,hd->efgh') + self.optimize_compare('abcd,ea,fb,gc,hd->efgh') + + def test_complex(self): + # Long test cases + self.optimize_compare('acdf,jbje,gihb,hfac,gfac,gifabc,hfac') + self.optimize_compare('acdf,jbje,gihb,hfac,gfac,gifabc,hfac') + self.optimize_compare('cd,bdhe,aidb,hgca,gc,hgibcd,hgac') + self.optimize_compare('abhe,hidj,jgba,hiab,gab') + self.optimize_compare('bde,cdh,agdb,hica,ibd,hgicd,hiac') + self.optimize_compare('chd,bde,agbc,hiad,hgc,hgi,hiad') + self.optimize_compare('chd,bde,agbc,hiad,bdi,cgh,agdb') + self.optimize_compare('bdhe,acad,hiab,agac,hibd') + + def test_collapse(self): + # Inner products + self.optimize_compare('ab,ab,c->') + self.optimize_compare('ab,ab,c->c') + self.optimize_compare('ab,ab,cd,cd->') + self.optimize_compare('ab,ab,cd,cd->ac') + self.optimize_compare('ab,ab,cd,cd->cd') + self.optimize_compare('ab,ab,cd,cd,ef,ef->') + + def test_expand(self): + # Outer products + self.optimize_compare('ab,cd,ef->abcdef') + self.optimize_compare('ab,cd,ef->acdf') + self.optimize_compare('ab,cd,de->abcde') + self.optimize_compare('ab,cd,de->be') + self.optimize_compare('ab,bcd,cd->abcd') + self.optimize_compare('ab,bcd,cd->abd') + + def test_edge_cases(self): + # Difficult edge cases for optimization + self.optimize_compare('eb,cb,fb->cef') + self.optimize_compare('dd,fb,be,cdb->cef') + self.optimize_compare('bca,cdb,dbf,afc->') + self.optimize_compare('dcc,fce,ea,dbf->ab') + self.optimize_compare('fdf,cdd,ccd,afe->ae') + self.optimize_compare('abcd,ad') + self.optimize_compare('ed,fcd,ff,bcf->be') + self.optimize_compare('baa,dcf,af,cde->be') + self.optimize_compare('bd,db,eac->ace') + self.optimize_compare('fff,fae,bef,def->abd') + self.optimize_compare('efc,dbc,acf,fd->abe') + self.optimize_compare('ba,ac,da->bcd') + + def test_inner_product(self): + # Inner products + self.optimize_compare('ab,ab') + self.optimize_compare('ab,ba') + self.optimize_compare('abc,abc') + self.optimize_compare('abc,bac') + self.optimize_compare('abc,cba') + + def test_random_cases(self): + # Randomly built test cases + self.optimize_compare('aab,fa,df,ecc->bde') + self.optimize_compare('ecb,fef,bad,ed->ac') + self.optimize_compare('bcf,bbb,fbf,fc->') + self.optimize_compare('bb,ff,be->e') + self.optimize_compare('bcb,bb,fc,fff->') + self.optimize_compare('fbb,dfd,fc,fc->') + self.optimize_compare('afd,ba,cc,dc->bf') + self.optimize_compare('adb,bc,fa,cfc->d') + self.optimize_compare('bbd,bda,fc,db->acf') + self.optimize_compare('dba,ead,cad->bce') + self.optimize_compare('aef,fbc,dca->bde') + + def test_combined_views_mapping(self): + # gh-10792 + a = np.arange(9).reshape(1, 1, 3, 1, 3) + b = np.einsum('bbcdc->d', a) + assert_equal(b, [12]) + + def test_broadcasting_dot_cases(self): + # Ensures broadcasting cases are not mistaken for GEMM + + a = np.random.rand(1, 5, 4) + b = np.random.rand(4, 6) + c = np.random.rand(5, 6) + d = np.random.rand(10) + + self.optimize_compare('ijk,kl,jl', operands=[a, b, c]) + self.optimize_compare('ijk,kl,jl,i->i', operands=[a, b, c, d]) + + e = np.random.rand(1, 1, 5, 4) + f = np.random.rand(7, 7) + self.optimize_compare('abjk,kl,jl', operands=[e, b, c]) + self.optimize_compare('abjk,kl,jl,ab->ab', operands=[e, b, c, f]) + + # Edge case found in gh-11308 + g = np.arange(64).reshape(2, 4, 8) + self.optimize_compare('obk,ijk->ioj', operands=[g, g]) + + def test_output_order(self): + # Ensure output order is respected for optimize cases, the below + # contraction should yield a reshaped tensor view + # gh-16415 + + a = np.ones((2, 3, 5), order='F') + b = np.ones((4, 3), order='F') + + for opt in [True, False]: + tmp = np.einsum('...ft,mf->...mt', a, b, order='a', optimize=opt) + assert_(tmp.flags.f_contiguous) + + tmp = np.einsum('...ft,mf->...mt', a, b, order='f', optimize=opt) + assert_(tmp.flags.f_contiguous) + + tmp = np.einsum('...ft,mf->...mt', a, b, order='c', optimize=opt) + assert_(tmp.flags.c_contiguous) + + tmp = np.einsum('...ft,mf->...mt', a, b, order='k', optimize=opt) + assert_(tmp.flags.c_contiguous is False) + assert_(tmp.flags.f_contiguous is False) + + tmp = np.einsum('...ft,mf->...mt', a, b, optimize=opt) + assert_(tmp.flags.c_contiguous is False) + assert_(tmp.flags.f_contiguous is False) + + c = np.ones((4, 3), order='C') + for opt in [True, False]: + tmp = np.einsum('...ft,mf->...mt', a, c, order='a', optimize=opt) + assert_(tmp.flags.c_contiguous) + + d = np.ones((2, 3, 5), order='C') + for opt in [True, False]: + tmp = np.einsum('...ft,mf->...mt', d, c, order='a', optimize=opt) + assert_(tmp.flags.c_contiguous) + + def test_singleton_broadcasting(self): + eq = "ijp,ipq,ikq->ijk" + shapes = ((3, 1, 1), (3, 1, 3), (1, 3, 3)) + arrays = [np.random.rand(*shape) for shape in shapes] + self.optimize_compare(eq, operands=arrays) + + eq = "jhcabhijaci,dfijejgh->fgje" + shapes = ( + (1, 1, 1, 1, 3, 1, 1, 1, 1, 1, 1), + (3, 1, 3, 1, 1, 1, 1, 2), + ) + arrays = [np.random.rand(*shape) for shape in shapes] + self.optimize_compare(eq, operands=arrays) + + eq = "baegffahgc,hdggeff->dhg" + shapes = ((2, 1, 4, 1, 1, 1, 1, 2, 1, 1), (1, 1, 1, 1, 4, 1, 1)) + arrays = [np.random.rand(*shape) for shape in shapes] + self.optimize_compare(eq, operands=arrays) + + eq = "cehgbaifff,fhhdegih->cdghbi" + shapes = ((1, 1, 1, 1, 1, 1, 1, 1, 1, 1), (2, 1, 1, 2, 4, 1, 1, 1)) + arrays = [np.random.rand(*shape) for shape in shapes] + self.optimize_compare(eq, operands=arrays) + + eq = "gah,cdbcghefg->ef" + shapes = ((2, 3, 1), (1, 3, 1, 1, 1, 2, 1, 4, 1)) + arrays = [np.random.rand(*shape) for shape in shapes] + self.optimize_compare(eq, operands=arrays) + + eq = "cacc,bcb->" + shapes = ((1, 1, 1, 1), (1, 4, 1)) + arrays = [np.random.rand(*shape) for shape in shapes] + self.optimize_compare(eq, operands=arrays) + + +class TestEinsumPath: + def build_operands(self, string, size_dict=global_size_dict): + + # Builds views based off initial operands + operands = [string] + terms = string.split('->')[0].split(',') + for term in terms: + dims = [size_dict[x] for x in term] + operands.append(np.random.rand(*dims)) + + return operands + + def assert_path_equal(self, comp, benchmark): + # Checks if list of tuples are equivalent + ret = (len(comp) == len(benchmark)) + assert_(ret) + for pos in range(len(comp) - 1): + ret &= isinstance(comp[pos + 1], tuple) + ret &= (comp[pos + 1] == benchmark[pos + 1]) + assert_(ret) + + def test_memory_contraints(self): + # Ensure memory constraints are satisfied + + outer_test = self.build_operands('a,b,c->abc') + + path, path_str = np.einsum_path(*outer_test, optimize=('greedy', 0)) + self.assert_path_equal(path, ['einsum_path', (0, 1, 2)]) + + path, path_str = np.einsum_path(*outer_test, optimize=('optimal', 0)) + self.assert_path_equal(path, ['einsum_path', (0, 1, 2)]) + + long_test = self.build_operands('acdf,jbje,gihb,hfac') + path, path_str = np.einsum_path(*long_test, optimize=('greedy', 0)) + self.assert_path_equal(path, ['einsum_path', (0, 1, 2, 3)]) + + path, path_str = np.einsum_path(*long_test, optimize=('optimal', 0)) + self.assert_path_equal(path, ['einsum_path', (0, 1, 2, 3)]) + + def test_long_paths(self): + # Long complex cases + + # Long test 1 + long_test1 = self.build_operands('acdf,jbje,gihb,hfac,gfac,gifabc,hfac') + path, path_str = np.einsum_path(*long_test1, optimize='greedy') + self.assert_path_equal(path, ['einsum_path', + (3, 6), (3, 4), (2, 4), (2, 3), (0, 2), (0, 1)]) + + path, path_str = np.einsum_path(*long_test1, optimize='optimal') + self.assert_path_equal(path, ['einsum_path', + (3, 6), (3, 4), (2, 4), (2, 3), (0, 2), (0, 1)]) + + # Long test 2 + long_test2 = self.build_operands('chd,bde,agbc,hiad,bdi,cgh,agdb') + path, path_str = np.einsum_path(*long_test2, optimize='greedy') + self.assert_path_equal(path, ['einsum_path', + (3, 4), (0, 3), (3, 4), (1, 3), (1, 2), (0, 1)]) + + path, path_str = np.einsum_path(*long_test2, optimize='optimal') + self.assert_path_equal(path, ['einsum_path', + (0, 5), (1, 4), (3, 4), (1, 3), (1, 2), (0, 1)]) + + def test_edge_paths(self): + # Difficult edge cases + + # Edge test1 + edge_test1 = self.build_operands('eb,cb,fb->cef') + path, path_str = np.einsum_path(*edge_test1, optimize='greedy') + self.assert_path_equal(path, ['einsum_path', (0, 2), (0, 1)]) + + path, path_str = np.einsum_path(*edge_test1, optimize='optimal') + self.assert_path_equal(path, ['einsum_path', (0, 2), (0, 1)]) + + # Edge test2 + edge_test2 = self.build_operands('dd,fb,be,cdb->cef') + path, path_str = np.einsum_path(*edge_test2, optimize='greedy') + self.assert_path_equal(path, ['einsum_path', (0, 3), (0, 1), (0, 1)]) + + path, path_str = np.einsum_path(*edge_test2, optimize='optimal') + self.assert_path_equal(path, ['einsum_path', (0, 3), (0, 1), (0, 1)]) + + # Edge test3 + edge_test3 = self.build_operands('bca,cdb,dbf,afc->') + path, path_str = np.einsum_path(*edge_test3, optimize='greedy') + self.assert_path_equal(path, ['einsum_path', (1, 2), (0, 2), (0, 1)]) + + path, path_str = np.einsum_path(*edge_test3, optimize='optimal') + self.assert_path_equal(path, ['einsum_path', (1, 2), (0, 2), (0, 1)]) + + # Edge test4 + edge_test4 = self.build_operands('dcc,fce,ea,dbf->ab') + path, path_str = np.einsum_path(*edge_test4, optimize='greedy') + self.assert_path_equal(path, ['einsum_path', (1, 2), (0, 1), (0, 1)]) + + path, path_str = np.einsum_path(*edge_test4, optimize='optimal') + self.assert_path_equal(path, ['einsum_path', (1, 2), (0, 2), (0, 1)]) + + # Edge test5 + edge_test4 = self.build_operands('a,ac,ab,ad,cd,bd,bc->', + size_dict={"a": 20, "b": 20, "c": 20, "d": 20}) + path, path_str = np.einsum_path(*edge_test4, optimize='greedy') + self.assert_path_equal(path, ['einsum_path', (0, 1), (0, 1, 2, 3, 4, 5)]) + + path, path_str = np.einsum_path(*edge_test4, optimize='optimal') + self.assert_path_equal(path, ['einsum_path', (0, 1), (0, 1, 2, 3, 4, 5)]) + + def test_path_type_input(self): + # Test explicit path handling + path_test = self.build_operands('dcc,fce,ea,dbf->ab') + + path, path_str = np.einsum_path(*path_test, optimize=False) + self.assert_path_equal(path, ['einsum_path', (0, 1, 2, 3)]) + + path, path_str = np.einsum_path(*path_test, optimize=True) + self.assert_path_equal(path, ['einsum_path', (1, 2), (0, 1), (0, 1)]) + + exp_path = ['einsum_path', (0, 2), (0, 2), (0, 1)] + path, path_str = np.einsum_path(*path_test, optimize=exp_path) + self.assert_path_equal(path, exp_path) + + # Double check einsum works on the input path + noopt = np.einsum(*path_test, optimize=False) + opt = np.einsum(*path_test, optimize=exp_path) + assert_almost_equal(noopt, opt) + + def test_path_type_input_internal_trace(self): + # gh-20962 + path_test = self.build_operands('cab,cdd->ab') + exp_path = ['einsum_path', (1,), (0, 1)] + + path, path_str = np.einsum_path(*path_test, optimize=exp_path) + self.assert_path_equal(path, exp_path) + + # Double check einsum works on the input path + noopt = np.einsum(*path_test, optimize=False) + opt = np.einsum(*path_test, optimize=exp_path) + assert_almost_equal(noopt, opt) + + def test_path_type_input_invalid(self): + path_test = self.build_operands('ab,bc,cd,de->ae') + exp_path = ['einsum_path', (2, 3), (0, 1)] + assert_raises(RuntimeError, np.einsum, *path_test, optimize=exp_path) + assert_raises( + RuntimeError, np.einsum_path, *path_test, optimize=exp_path) + + path_test = self.build_operands('a,a,a->a') + exp_path = ['einsum_path', (1,), (0, 1)] + assert_raises(RuntimeError, np.einsum, *path_test, optimize=exp_path) + assert_raises( + RuntimeError, np.einsum_path, *path_test, optimize=exp_path) + + def test_spaces(self): + # gh-10794 + arr = np.array([[1]]) + for sp in itertools.product(['', ' '], repeat=4): + # no error for any spacing + np.einsum('{}...a{}->{}...a{}'.format(*sp), arr) + +def test_overlap(): + a = np.arange(9, dtype=int).reshape(3, 3) + b = np.arange(9, dtype=int).reshape(3, 3) + d = np.dot(a, b) + # sanity check + c = np.einsum('ij,jk->ik', a, b) + assert_equal(c, d) + # gh-10080, out overlaps one of the operands + c = np.einsum('ij,jk->ik', a, b, out=b) + assert_equal(c, d) + +def test_einsum_chunking_precision(): + """Most einsum operations are reductions and until NumPy 2.3 reductions + never (or almost never?) used the `GROWINNER` mechanism to increase the + inner loop size when no buffers are needed. + Because einsum reductions work roughly: + + def inner(*inputs, out): + accumulate = 0 + for vals in zip(*inputs): + accumulate += prod(vals) + out[0] += accumulate + + Calling the inner-loop more often actually improves accuracy slightly + (same effect as pairwise summation but much less). + Without adding pairwise summation to the inner-loop it seems best to just + not use GROWINNER, a quick tests suggest that is maybe 1% slowdown for + the simplest `einsum("i,i->i", x, x)` case. + + (It is not clear that we should guarantee precision to this extend.) + """ + num = 1_000_000 + value = 1. + np.finfo(np.float64).eps * 8196 + res = np.einsum("i->", np.broadcast_to(np.array(value), num)) / num + + # At with GROWINNER 11 decimals succeed (larger will be less) + assert_almost_equal(res, value, decimal=15) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_errstate.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_errstate.py new file mode 100644 index 0000000000000000000000000000000000000000..f0735a045a4dc37728f36bc374c52f63f7e57eef --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_errstate.py @@ -0,0 +1,131 @@ +import sysconfig + +import pytest + +import numpy as np +from numpy.testing import IS_WASM, assert_raises + +# The floating point emulation on ARM EABI systems lacking a hardware FPU is +# known to be buggy. This is an attempt to identify these hosts. It may not +# catch all possible cases, but it catches the known cases of gh-413 and +# gh-15562. +hosttype = sysconfig.get_config_var('HOST_GNU_TYPE') +arm_softfloat = False if hosttype is None else hosttype.endswith('gnueabi') + +class TestErrstate: + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + @pytest.mark.skipif(arm_softfloat, + reason='platform/cpu issue with FPU (gh-413,-15562)') + def test_invalid(self): + with np.errstate(all='raise', under='ignore'): + a = -np.arange(3) + # This should work + with np.errstate(invalid='ignore'): + np.sqrt(a) + # While this should fail! + with assert_raises(FloatingPointError): + np.sqrt(a) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + @pytest.mark.skipif(arm_softfloat, + reason='platform/cpu issue with FPU (gh-15562)') + def test_divide(self): + with np.errstate(all='raise', under='ignore'): + a = -np.arange(3) + # This should work + with np.errstate(divide='ignore'): + a // 0 + # While this should fail! + with assert_raises(FloatingPointError): + a // 0 + # As should this, see gh-15562 + with assert_raises(FloatingPointError): + a // a + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + @pytest.mark.skipif(arm_softfloat, + reason='platform/cpu issue with FPU (gh-15562)') + def test_errcall(self): + count = 0 + + def foo(*args): + nonlocal count + count += 1 + + olderrcall = np.geterrcall() + with np.errstate(call=foo): + assert np.geterrcall() is foo + with np.errstate(call=None): + assert np.geterrcall() is None + assert np.geterrcall() is olderrcall + assert count == 0 + + with np.errstate(call=foo, invalid="call"): + np.array(np.inf) - np.array(np.inf) + + assert count == 1 + + def test_errstate_decorator(self): + @np.errstate(all='ignore') + def foo(): + a = -np.arange(3) + a // 0 + + foo() + + def test_errstate_enter_once(self): + errstate = np.errstate(invalid="warn") + with errstate: + pass + + # The errstate context cannot be entered twice as that would not be + # thread-safe + with pytest.raises(TypeError, + match="Cannot enter `np.errstate` twice"): + with errstate: + pass + + @pytest.mark.skipif(IS_WASM, reason="wasm doesn't support asyncio") + def test_asyncio_safe(self): + # asyncio may not always work, let's assume its fine if missing + # Pyodide/wasm doesn't support it. If this test makes problems, + # it should just be skipped liberally (or run differently). + asyncio = pytest.importorskip("asyncio") + + @np.errstate(invalid="ignore") + def decorated(): + # Decorated non-async function (it is not safe to decorate an + # async one) + assert np.geterr()["invalid"] == "ignore" + + async def func1(): + decorated() + await asyncio.sleep(0.1) + decorated() + + async def func2(): + with np.errstate(invalid="raise"): + assert np.geterr()["invalid"] == "raise" + await asyncio.sleep(0.125) + assert np.geterr()["invalid"] == "raise" + + # for good sport, a third one with yet another state: + async def func3(): + with np.errstate(invalid="print"): + assert np.geterr()["invalid"] == "print" + await asyncio.sleep(0.11) + assert np.geterr()["invalid"] == "print" + + async def main(): + # simply run all three function multiple times: + await asyncio.gather( + func1(), func2(), func3(), func1(), func2(), func3(), + func1(), func2(), func3(), func1(), func2(), func3()) + + loop = asyncio.new_event_loop() + with np.errstate(invalid="warn"): + asyncio.run(main()) + assert np.geterr()["invalid"] == "warn" + + assert np.geterr()["invalid"] == "warn" # the default + loop.close() diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_extint128.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_extint128.py new file mode 100644 index 0000000000000000000000000000000000000000..6e4d74b81d3907c6dcf096730fa3f5db6e6cb80c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_extint128.py @@ -0,0 +1,217 @@ +import contextlib +import itertools +import operator + +import pytest + +import numpy as np +import numpy._core._multiarray_tests as mt +from numpy.testing import assert_equal, assert_raises + +INT64_MAX = np.iinfo(np.int64).max +INT64_MIN = np.iinfo(np.int64).min +INT64_MID = 2**32 + +# int128 is not two's complement, the sign bit is separate +INT128_MAX = 2**128 - 1 +INT128_MIN = -INT128_MAX +INT128_MID = 2**64 + +INT64_VALUES = ( + [INT64_MIN + j for j in range(20)] + + [INT64_MAX - j for j in range(20)] + + [INT64_MID + j for j in range(-20, 20)] + + [2 * INT64_MID + j for j in range(-20, 20)] + + [INT64_MID // 2 + j for j in range(-20, 20)] + + list(range(-70, 70)) +) + +INT128_VALUES = ( + [INT128_MIN + j for j in range(20)] + + [INT128_MAX - j for j in range(20)] + + [INT128_MID + j for j in range(-20, 20)] + + [2 * INT128_MID + j for j in range(-20, 20)] + + [INT128_MID // 2 + j for j in range(-20, 20)] + + list(range(-70, 70)) + + [False] # negative zero +) + +INT64_POS_VALUES = [x for x in INT64_VALUES if x > 0] + + +@contextlib.contextmanager +def exc_iter(*args): + """ + Iterate over Cartesian product of *args, and if an exception is raised, + add information of the current iterate. + """ + + value = [None] + + def iterate(): + for v in itertools.product(*args): + value[0] = v + yield v + + try: + yield iterate() + except Exception: + import traceback + msg = f"At: {repr(value[0])!r}\n{traceback.format_exc()}" + raise AssertionError(msg) + + +def test_safe_binop(): + # Test checked arithmetic routines + + ops = [ + (operator.add, 1), + (operator.sub, 2), + (operator.mul, 3) + ] + + with exc_iter(ops, INT64_VALUES, INT64_VALUES) as it: + for xop, a, b in it: + pyop, op = xop + c = pyop(a, b) + + if not (INT64_MIN <= c <= INT64_MAX): + assert_raises(OverflowError, mt.extint_safe_binop, a, b, op) + else: + d = mt.extint_safe_binop(a, b, op) + if c != d: + # assert_equal is slow + assert_equal(d, c) + + +def test_to_128(): + with exc_iter(INT64_VALUES) as it: + for a, in it: + b = mt.extint_to_128(a) + if a != b: + assert_equal(b, a) + + +def test_to_64(): + with exc_iter(INT128_VALUES) as it: + for a, in it: + if not (INT64_MIN <= a <= INT64_MAX): + assert_raises(OverflowError, mt.extint_to_64, a) + else: + b = mt.extint_to_64(a) + if a != b: + assert_equal(b, a) + + +def test_mul_64_64(): + with exc_iter(INT64_VALUES, INT64_VALUES) as it: + for a, b in it: + c = a * b + d = mt.extint_mul_64_64(a, b) + if c != d: + assert_equal(d, c) + + +def test_add_128(): + with exc_iter(INT128_VALUES, INT128_VALUES) as it: + for a, b in it: + c = a + b + if not (INT128_MIN <= c <= INT128_MAX): + assert_raises(OverflowError, mt.extint_add_128, a, b) + else: + d = mt.extint_add_128(a, b) + if c != d: + assert_equal(d, c) + + +def test_sub_128(): + with exc_iter(INT128_VALUES, INT128_VALUES) as it: + for a, b in it: + c = a - b + if not (INT128_MIN <= c <= INT128_MAX): + assert_raises(OverflowError, mt.extint_sub_128, a, b) + else: + d = mt.extint_sub_128(a, b) + if c != d: + assert_equal(d, c) + + +def test_neg_128(): + with exc_iter(INT128_VALUES) as it: + for a, in it: + b = -a + c = mt.extint_neg_128(a) + if b != c: + assert_equal(c, b) + + +def test_shl_128(): + with exc_iter(INT128_VALUES) as it: + for a, in it: + if a < 0: + b = -(((-a) << 1) & (2**128 - 1)) + else: + b = (a << 1) & (2**128 - 1) + c = mt.extint_shl_128(a) + if b != c: + assert_equal(c, b) + + +def test_shr_128(): + with exc_iter(INT128_VALUES) as it: + for a, in it: + if a < 0: + b = -((-a) >> 1) + else: + b = a >> 1 + c = mt.extint_shr_128(a) + if b != c: + assert_equal(c, b) + + +def test_gt_128(): + with exc_iter(INT128_VALUES, INT128_VALUES) as it: + for a, b in it: + c = a > b + d = mt.extint_gt_128(a, b) + if c != d: + assert_equal(d, c) + + +@pytest.mark.slow +def test_divmod_128_64(): + with exc_iter(INT128_VALUES, INT64_POS_VALUES) as it: + for a, b in it: + if a >= 0: + c, cr = divmod(a, b) + else: + c, cr = divmod(-a, b) + c = -c + cr = -cr + + d, dr = mt.extint_divmod_128_64(a, b) + + if c != d or d != dr or b * d + dr != a: + assert_equal(d, c) + assert_equal(dr, cr) + assert_equal(b * d + dr, a) + + +def test_floordiv_128_64(): + with exc_iter(INT128_VALUES, INT64_POS_VALUES) as it: + for a, b in it: + c = a // b + d = mt.extint_floordiv_128_64(a, b) + + if c != d: + assert_equal(d, c) + + +def test_ceildiv_128_64(): + with exc_iter(INT128_VALUES, INT64_POS_VALUES) as it: + for a, b in it: + c = (a + b - 1) // b + d = mt.extint_ceildiv_128_64(a, b) + + if c != d: + assert_equal(d, c) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_finfo.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_finfo.py new file mode 100644 index 0000000000000000000000000000000000000000..5703b8d6a765b575f974497e004953499496589f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_finfo.py @@ -0,0 +1,86 @@ +import pytest + +import numpy as np +from numpy import exp2, log10 +from numpy._core import numerictypes as ntypes + + +class MachArLike: + """Minimal class to simulate machine arithmetic parameters.""" + def __init__(self, dtype, machep, negep, minexp, maxexp, nmant, iexp): + self.dtype = dtype + self.machep = machep + self.negep = negep + self.minexp = minexp + self.maxexp = maxexp + self.nmant = nmant + self.iexp = iexp + self.eps = exp2(dtype(-nmant)) + self.epsneg = exp2(dtype(negep)) + self.precision = int(-log10(self.eps)) + self.resolution = dtype(10) ** (-self.precision) + + +@pytest.fixture +def float16_ma(): + """Machine arithmetic parameters for float16.""" + f16 = ntypes.float16 + return MachArLike(f16, + machep=-10, + negep=-11, + minexp=-14, + maxexp=16, + nmant=10, + iexp=5) + + +@pytest.fixture +def float32_ma(): + """Machine arithmetic parameters for float32.""" + f32 = ntypes.float32 + return MachArLike(f32, + machep=-23, + negep=-24, + minexp=-126, + maxexp=128, + nmant=23, + iexp=8) + + +@pytest.fixture +def float64_ma(): + """Machine arithmetic parameters for float64.""" + f64 = ntypes.float64 + return MachArLike(f64, + machep=-52, + negep=-53, + minexp=-1022, + maxexp=1024, + nmant=52, + iexp=11) + + +@pytest.mark.parametrize("dtype,ma_fixture", [ + (np.half, "float16_ma"), + (np.float32, "float32_ma"), + (np.float64, "float64_ma"), +]) +@pytest.mark.parametrize("prop", [ + 'machep', 'negep', 'minexp', 'maxexp', 'nmant', 'iexp', + 'eps', 'epsneg', 'precision', 'resolution' +]) +@pytest.mark.thread_unsafe( + reason="complex fixture setup is thread-unsafe (pytest-dev/pytest#13768.)" +) +def test_finfo_properties(dtype, ma_fixture, prop, request): + """Test that finfo properties match expected machine arithmetic values.""" + ma = request.getfixturevalue(ma_fixture) + finfo = np.finfo(dtype) + + actual = getattr(finfo, prop) + expected = getattr(ma, prop) + + assert actual == expected, ( + f"finfo({dtype}) property '{prop}' mismatch: " + f"expected {expected}, got {actual}" + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_function_base.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_function_base.py new file mode 100644 index 0000000000000000000000000000000000000000..c6e10397b3ff9550ffd8f727a49c3c25dd5bc20e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_function_base.py @@ -0,0 +1,504 @@ +import platform +import sys + +import pytest + +import numpy as np +from numpy import ( + arange, + array, + dtype, + errstate, + geomspace, + isnan, + linspace, + logspace, + ndarray, + nextafter, + sqrt, + stack, +) +from numpy._core import sctypes +from numpy._core.function_base import add_newdoc +from numpy.testing import ( + IS_PYPY, + assert_, + assert_allclose, + assert_array_equal, + assert_equal, + assert_raises, +) + + +def _is_armhf(): + # Check if the current platform is ARMHF (32-bit ARM architecture) + architecture = platform.architecture() + return platform.machine().startswith('arm') and architecture[0] == '32bit' + +class PhysicalQuantity(float): + def __new__(cls, value): + return float.__new__(cls, value) + + def __add__(self, x): + assert_(isinstance(x, PhysicalQuantity)) + return PhysicalQuantity(float(x) + float(self)) + __radd__ = __add__ + + def __sub__(self, x): + assert_(isinstance(x, PhysicalQuantity)) + return PhysicalQuantity(float(self) - float(x)) + + def __rsub__(self, x): + assert_(isinstance(x, PhysicalQuantity)) + return PhysicalQuantity(float(x) - float(self)) + + def __mul__(self, x): + return PhysicalQuantity(float(x) * float(self)) + __rmul__ = __mul__ + + def __truediv__(self, x): + return PhysicalQuantity(float(self) / float(x)) + + def __rtruediv__(self, x): + return PhysicalQuantity(float(x) / float(self)) + + +class PhysicalQuantity2(ndarray): + __array_priority__ = 10 + + +class TestLogspace: + + def test_basic(self): + y = logspace(0, 6) + assert_(len(y) == 50) + y = logspace(0, 6, num=100) + assert_(y[-1] == 10 ** 6) + y = logspace(0, 6, endpoint=False) + assert_(y[-1] < 10 ** 6) + y = logspace(0, 6, num=7) + assert_array_equal(y, [1, 10, 100, 1e3, 1e4, 1e5, 1e6]) + + def test_start_stop_array(self): + start = array([0., 1.]) + stop = array([6., 7.]) + t1 = logspace(start, stop, 6) + t2 = stack([logspace(_start, _stop, 6) + for _start, _stop in zip(start, stop)], axis=1) + assert_equal(t1, t2) + t3 = logspace(start, stop[0], 6) + t4 = stack([logspace(_start, stop[0], 6) + for _start in start], axis=1) + assert_equal(t3, t4) + t5 = logspace(start, stop, 6, axis=-1) + assert_equal(t5, t2.T) + + @pytest.mark.parametrize("axis", [0, 1, -1]) + def test_base_array(self, axis: int): + start = 1 + stop = 2 + num = 6 + base = array([1, 2]) + t1 = logspace(start, stop, num=num, base=base, axis=axis) + t2 = stack( + [logspace(start, stop, num=num, base=_base) for _base in base], + axis=(axis + 1) % t1.ndim, + ) + assert_equal(t1, t2) + + @pytest.mark.parametrize("axis", [0, 1, -1]) + def test_stop_base_array(self, axis: int): + start = 1 + stop = array([2, 3]) + num = 6 + base = array([1, 2]) + t1 = logspace(start, stop, num=num, base=base, axis=axis) + t2 = stack( + [logspace(start, _stop, num=num, base=_base) + for _stop, _base in zip(stop, base)], + axis=(axis + 1) % t1.ndim, + ) + assert_equal(t1, t2) + + def test_dtype(self): + y = logspace(0, 6, dtype='float32') + assert_equal(y.dtype, dtype('float32')) + y = logspace(0, 6, dtype='float64') + assert_equal(y.dtype, dtype('float64')) + y = logspace(0, 6, dtype='int32') + assert_equal(y.dtype, dtype('int32')) + + def test_physical_quantities(self): + a = PhysicalQuantity(1.0) + b = PhysicalQuantity(5.0) + assert_equal(logspace(a, b), logspace(1.0, 5.0)) + + def test_subclass(self): + a = array(1).view(PhysicalQuantity2) + b = array(7).view(PhysicalQuantity2) + ls = logspace(a, b) + assert type(ls) is PhysicalQuantity2 + assert_equal(ls, logspace(1.0, 7.0)) + ls = logspace(a, b, 1) + assert type(ls) is PhysicalQuantity2 + assert_equal(ls, logspace(1.0, 7.0, 1)) + + +class TestGeomspace: + + def test_basic(self): + y = geomspace(1, 1e6) + assert_(len(y) == 50) + y = geomspace(1, 1e6, num=100) + assert_(y[-1] == 10 ** 6) + y = geomspace(1, 1e6, endpoint=False) + assert_(y[-1] < 10 ** 6) + y = geomspace(1, 1e6, num=7) + assert_array_equal(y, [1, 10, 100, 1e3, 1e4, 1e5, 1e6]) + + y = geomspace(8, 2, num=3) + assert_allclose(y, [8, 4, 2]) + assert_array_equal(y.imag, 0) + + y = geomspace(-1, -100, num=3) + assert_array_equal(y, [-1, -10, -100]) + assert_array_equal(y.imag, 0) + + y = geomspace(-100, -1, num=3) + assert_array_equal(y, [-100, -10, -1]) + assert_array_equal(y.imag, 0) + + def test_boundaries_match_start_and_stop_exactly(self): + # make sure that the boundaries of the returned array exactly + # equal 'start' and 'stop' - this isn't obvious because + # np.exp(np.log(x)) isn't necessarily exactly equal to x + start = 0.3 + stop = 20.3 + + y = geomspace(start, stop, num=1) + assert_equal(y[0], start) + + y = geomspace(start, stop, num=1, endpoint=False) + assert_equal(y[0], start) + + y = geomspace(start, stop, num=3) + assert_equal(y[0], start) + assert_equal(y[-1], stop) + + y = geomspace(start, stop, num=3, endpoint=False) + assert_equal(y[0], start) + + def test_nan_interior(self): + with errstate(invalid='ignore'): + y = geomspace(-3, 3, num=4) + + assert_equal(y[0], -3.0) + assert_(isnan(y[1:-1]).all()) + assert_equal(y[3], 3.0) + + with errstate(invalid='ignore'): + y = geomspace(-3, 3, num=4, endpoint=False) + + assert_equal(y[0], -3.0) + assert_(isnan(y[1:]).all()) + + def test_complex(self): + # Purely imaginary + y = geomspace(1j, 16j, num=5) + assert_allclose(y, [1j, 2j, 4j, 8j, 16j]) + assert_array_equal(y.real, 0) + + y = geomspace(-4j, -324j, num=5) + assert_allclose(y, [-4j, -12j, -36j, -108j, -324j]) + assert_array_equal(y.real, 0) + + y = geomspace(1 + 1j, 1000 + 1000j, num=4) + assert_allclose(y, [1 + 1j, 10 + 10j, 100 + 100j, 1000 + 1000j]) + + y = geomspace(-1 + 1j, -1000 + 1000j, num=4) + assert_allclose(y, [-1 + 1j, -10 + 10j, -100 + 100j, -1000 + 1000j]) + + # Logarithmic spirals + y = geomspace(-1, 1, num=3, dtype=complex) + assert_allclose(y, [-1, 1j, +1]) + + y = geomspace(0 + 3j, -3 + 0j, 3) + assert_allclose(y, [0 + 3j, -3 / sqrt(2) + 3j / sqrt(2), -3 + 0j]) + y = geomspace(0 + 3j, 3 + 0j, 3) + assert_allclose(y, [0 + 3j, 3 / sqrt(2) + 3j / sqrt(2), 3 + 0j]) + y = geomspace(-3 + 0j, 0 - 3j, 3) + assert_allclose(y, [-3 + 0j, -3 / sqrt(2) - 3j / sqrt(2), 0 - 3j]) + y = geomspace(0 + 3j, -3 + 0j, 3) + assert_allclose(y, [0 + 3j, -3 / sqrt(2) + 3j / sqrt(2), -3 + 0j]) + y = geomspace(-2 - 3j, 5 + 7j, 7) + assert_allclose(y, [-2 - 3j, -0.29058977 - 4.15771027j, + 2.08885354 - 4.34146838j, 4.58345529 - 3.16355218j, + 6.41401745 - 0.55233457j, 6.75707386 + 3.11795092j, + 5 + 7j]) + + # Type promotion should prevent the -5 from becoming a NaN + y = geomspace(3j, -5, 2) + assert_allclose(y, [3j, -5]) + y = geomspace(-5, 3j, 2) + assert_allclose(y, [-5, 3j]) + + def test_complex_shortest_path(self): + # test the shortest logarithmic spiral is used, see gh-25644 + x = 1.2 + 3.4j + y = np.exp(1j * (np.pi - .1)) * x + z = np.geomspace(x, y, 5) + expected = np.array([1.2 + 3.4j, -1.47384 + 3.2905616j, + -3.33577588 + 1.36842949j, -3.36011056 - 1.30753855j, + -1.53343861 - 3.26321406j]) + np.testing.assert_array_almost_equal(z, expected) + + def test_dtype(self): + y = geomspace(1, 1e6, dtype='float32') + assert_equal(y.dtype, dtype('float32')) + y = geomspace(1, 1e6, dtype='float64') + assert_equal(y.dtype, dtype('float64')) + y = geomspace(1, 1e6, dtype='int32') + assert_equal(y.dtype, dtype('int32')) + + # Native types + y = geomspace(1, 1e6, dtype=float) + assert_equal(y.dtype, dtype('float64')) + y = geomspace(1, 1e6, dtype=complex) + assert_equal(y.dtype, dtype('complex128')) + + def test_start_stop_array_scalar(self): + lim1 = array([120, 100], dtype="int8") + lim2 = array([-120, -100], dtype="int8") + lim3 = array([1200, 1000], dtype="uint16") + t1 = geomspace(lim1[0], lim1[1], 5) + t2 = geomspace(lim2[0], lim2[1], 5) + t3 = geomspace(lim3[0], lim3[1], 5) + t4 = geomspace(120.0, 100.0, 5) + t5 = geomspace(-120.0, -100.0, 5) + t6 = geomspace(1200.0, 1000.0, 5) + + # t3 uses float32, t6 uses float64 + assert_allclose(t1, t4, rtol=1e-2) + assert_allclose(t2, t5, rtol=1e-2) + assert_allclose(t3, t6, rtol=1e-5) + + def test_start_stop_array(self): + # Try to use all special cases. + start = array([1.e0, 32., 1j, -4j, 1 + 1j, -1]) + stop = array([1.e4, 2., 16j, -324j, 10000 + 10000j, 1]) + t1 = geomspace(start, stop, 5) + t2 = stack([geomspace(_start, _stop, 5) + for _start, _stop in zip(start, stop)], axis=1) + assert_equal(t1, t2) + t3 = geomspace(start, stop[0], 5) + t4 = stack([geomspace(_start, stop[0], 5) + for _start in start], axis=1) + assert_equal(t3, t4) + t5 = geomspace(start, stop, 5, axis=-1) + assert_equal(t5, t2.T) + + def test_physical_quantities(self): + a = PhysicalQuantity(1.0) + b = PhysicalQuantity(5.0) + assert_equal(geomspace(a, b), geomspace(1.0, 5.0)) + + def test_subclass(self): + a = array(1).view(PhysicalQuantity2) + b = array(7).view(PhysicalQuantity2) + gs = geomspace(a, b) + assert type(gs) is PhysicalQuantity2 + assert_equal(gs, geomspace(1.0, 7.0)) + gs = geomspace(a, b, 1) + assert type(gs) is PhysicalQuantity2 + assert_equal(gs, geomspace(1.0, 7.0, 1)) + + def test_bounds(self): + assert_raises(ValueError, geomspace, 0, 10) + assert_raises(ValueError, geomspace, 10, 0) + assert_raises(ValueError, geomspace, 0, 0) + + +class TestLinspace: + + def test_basic(self): + y = linspace(0, 10) + assert_(len(y) == 50) + y = linspace(2, 10, num=100) + assert_(y[-1] == 10) + y = linspace(2, 10, endpoint=False) + assert_(y[-1] < 10) + assert_raises(ValueError, linspace, 0, 10, num=-1) + + def test_corner(self): + y = list(linspace(0, 1, 1)) + assert_(y == [0.0], y) + assert_raises(TypeError, linspace, 0, 1, num=2.5) + + def test_type(self): + t1 = linspace(0, 1, 0).dtype + t2 = linspace(0, 1, 1).dtype + t3 = linspace(0, 1, 2).dtype + assert_equal(t1, t2) + assert_equal(t2, t3) + + def test_dtype(self): + y = linspace(0, 6, dtype='float32') + assert_equal(y.dtype, dtype('float32')) + y = linspace(0, 6, dtype='float64') + assert_equal(y.dtype, dtype('float64')) + y = linspace(0, 6, dtype='int32') + assert_equal(y.dtype, dtype('int32')) + + def test_start_stop_array_scalar(self): + lim1 = array([-120, 100], dtype="int8") + lim2 = array([120, -100], dtype="int8") + lim3 = array([1200, 1000], dtype="uint16") + t1 = linspace(lim1[0], lim1[1], 5) + t2 = linspace(lim2[0], lim2[1], 5) + t3 = linspace(lim3[0], lim3[1], 5) + t4 = linspace(-120.0, 100.0, 5) + t5 = linspace(120.0, -100.0, 5) + t6 = linspace(1200.0, 1000.0, 5) + assert_equal(t1, t4) + assert_equal(t2, t5) + assert_equal(t3, t6) + + def test_start_stop_array(self): + start = array([-120, 120], dtype="int8") + stop = array([100, -100], dtype="int8") + t1 = linspace(start, stop, 5) + t2 = stack([linspace(_start, _stop, 5) + for _start, _stop in zip(start, stop)], axis=1) + assert_equal(t1, t2) + t3 = linspace(start, stop[0], 5) + t4 = stack([linspace(_start, stop[0], 5) + for _start in start], axis=1) + assert_equal(t3, t4) + t5 = linspace(start, stop, 5, axis=-1) + assert_equal(t5, t2.T) + + def test_complex(self): + lim1 = linspace(1 + 2j, 3 + 4j, 5) + t1 = array([1.0 + 2.j, 1.5 + 2.5j, 2.0 + 3j, 2.5 + 3.5j, 3.0 + 4j]) + lim2 = linspace(1j, 10, 5) + t2 = array([0.0 + 1.j, 2.5 + 0.75j, 5.0 + 0.5j, 7.5 + 0.25j, 10.0 + 0j]) + assert_equal(lim1, t1) + assert_equal(lim2, t2) + + def test_physical_quantities(self): + a = PhysicalQuantity(0.0) + b = PhysicalQuantity(1.0) + assert_equal(linspace(a, b), linspace(0.0, 1.0)) + + def test_subclass(self): + a = array(0).view(PhysicalQuantity2) + b = array(1).view(PhysicalQuantity2) + ls = linspace(a, b) + assert type(ls) is PhysicalQuantity2 + assert_equal(ls, linspace(0.0, 1.0)) + ls = linspace(a, b, 1) + assert type(ls) is PhysicalQuantity2 + assert_equal(ls, linspace(0.0, 1.0, 1)) + + def test_array_interface(self): + # Regression test for https://github.com/numpy/numpy/pull/6659 + # Ensure that start/stop can be objects that implement + # __array_interface__ and are convertible to numeric scalars + + class Arrayish: + """ + A generic object that supports the __array_interface__ and hence + can in principle be converted to a numeric scalar, but is not + otherwise recognized as numeric, but also happens to support + multiplication by floats. + + Data should be an object that implements the buffer interface, + and contains at least 4 bytes. + """ + + def __init__(self, data): + self._data = data + + @property + def __array_interface__(self): + return {'shape': (), 'typestr': ' 250) + assert_(len(np.lib._index_tricks_impl.mgrid.__doc__) > 300) + + @pytest.mark.skipif(sys.flags.optimize == 2, reason="Python running -OO") + def test_errors_are_ignored(self): + prev_doc = np._core.flatiter.index.__doc__ + # nothing changed, but error ignored, this should probably + # give a warning (or even error) in the future. + add_newdoc("numpy._core", "flatiter", ("index", "bad docstring")) + assert prev_doc == np._core.flatiter.index.__doc__ diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_getlimits.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_getlimits.py new file mode 100644 index 0000000000000000000000000000000000000000..4e911b89e89fa94b517ade896b285e6627c2f997 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_getlimits.py @@ -0,0 +1,171 @@ +""" Test functions for limits module. + +""" +import types +import warnings + +import pytest + +import numpy as np +from numpy import double, half, longdouble, single +from numpy._core import finfo, iinfo +from numpy.testing import assert_, assert_equal, assert_raises + +################################################## + +class TestPythonFloat: + def test_singleton(self): + ftype = finfo(float) + ftype2 = finfo(float) + assert_equal(id(ftype), id(ftype2)) + +class TestHalf: + def test_singleton(self): + ftype = finfo(half) + ftype2 = finfo(half) + assert_equal(id(ftype), id(ftype2)) + +class TestSingle: + def test_singleton(self): + ftype = finfo(single) + ftype2 = finfo(single) + assert_equal(id(ftype), id(ftype2)) + +class TestDouble: + def test_singleton(self): + ftype = finfo(double) + ftype2 = finfo(double) + assert_equal(id(ftype), id(ftype2)) + +class TestLongdouble: + def test_singleton(self): + ftype = finfo(longdouble) + ftype2 = finfo(longdouble) + assert_equal(id(ftype), id(ftype2)) + +def assert_finfo_equal(f1, f2): + # assert two finfo instances have the same attributes + for attr in ('bits', 'eps', 'epsneg', 'iexp', 'machep', + 'max', 'maxexp', 'min', 'minexp', 'negep', 'nexp', + 'nmant', 'precision', 'resolution', 'tiny', + 'smallest_normal', 'smallest_subnormal'): + assert_equal(getattr(f1, attr), getattr(f2, attr), + f'finfo instances {f1} and {f2} differ on {attr}') + +def assert_iinfo_equal(i1, i2): + # assert two iinfo instances have the same attributes + for attr in ('bits', 'min', 'max'): + assert_equal(getattr(i1, attr), getattr(i2, attr), + f'iinfo instances {i1} and {i2} differ on {attr}') + +class TestFinfo: + def test_basic(self): + dts = list(zip(['f2', 'f4', 'f8', 'c8', 'c16'], + [np.float16, np.float32, np.float64, np.complex64, + np.complex128])) + for dt1, dt2 in dts: + assert_finfo_equal(finfo(dt1), finfo(dt2)) + + assert_raises(ValueError, finfo, 'i4') + + def test_regression_gh23108(self): + # np.float32(1.0) and np.float64(1.0) have the same hash and are + # equal under the == operator + f1 = np.finfo(np.float32(1.0)) + f2 = np.finfo(np.float64(1.0)) + assert f1 != f2 + + def test_regression_gh23867(self): + class NonHashableWithDtype: + __hash__ = None + dtype = np.dtype('float32') + + x = NonHashableWithDtype() + assert np.finfo(x) == np.finfo(x.dtype) + + +class TestIinfo: + def test_basic(self): + dts = list(zip(['i1', 'i2', 'i4', 'i8', + 'u1', 'u2', 'u4', 'u8'], + [np.int8, np.int16, np.int32, np.int64, + np.uint8, np.uint16, np.uint32, np.uint64])) + for dt1, dt2 in dts: + assert_iinfo_equal(iinfo(dt1), iinfo(dt2)) + + assert_raises(ValueError, iinfo, 'f4') + + def test_unsigned_max(self): + types = np._core.sctypes['uint'] + for T in types: + with np.errstate(over="ignore"): + max_calculated = T(0) - T(1) + assert_equal(iinfo(T).max, max_calculated) + +class TestRepr: + def test_iinfo_repr(self): + expected = "iinfo(min=-32768, max=32767, dtype=int16)" + assert_equal(repr(np.iinfo(np.int16)), expected) + + def test_finfo_repr(self): + expected = "finfo(resolution=1e-06, min=-3.4028235e+38,"\ + " max=3.4028235e+38, dtype=float32)" + assert_equal(repr(np.finfo(np.float32)), expected) + + +def test_instances(): + # Test the finfo and iinfo results on numeric instances agree with + # the results on the corresponding types + + for c in [int, np.int16, np.int32, np.int64]: + class_iinfo = iinfo(c) + instance_iinfo = iinfo(c(12)) + + assert_iinfo_equal(class_iinfo, instance_iinfo) + + for c in [float, np.float16, np.float32, np.float64]: + class_finfo = finfo(c) + instance_finfo = finfo(c(1.2)) + assert_finfo_equal(class_finfo, instance_finfo) + + with pytest.raises(ValueError): + iinfo(10.) + + with pytest.raises(ValueError): + iinfo('hi') + + with pytest.raises(ValueError): + finfo(np.int64(1)) + + +def test_subnormal_warning(): + """Test that the subnormal is zero warning is not being raised.""" + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter('always') + # Test for common float types + for dtype in [np.float16, np.float32, np.float64]: + f = finfo(dtype) + _ = f.smallest_subnormal + # Also test longdouble + with np.errstate(all='ignore'): + fld = finfo(np.longdouble) + _ = fld.smallest_subnormal + # Check no warnings were raised + assert len(w) == 0 + + +def test_plausible_finfo(): + # Assert that finfo returns reasonable results for all types + for ftype in np._core.sctypes['float'] + np._core.sctypes['complex']: + info = np.finfo(ftype) + assert_(info.nmant > 1) + assert_(info.minexp < -1) + assert_(info.maxexp > 1) + + +class TestRuntimeSubscriptable: + def test_finfo_generic(self): + assert isinstance(np.finfo[np.float64], types.GenericAlias) + + def test_iinfo_generic(self): + assert isinstance(np.iinfo[np.int_], types.GenericAlias) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_half.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_half.py new file mode 100644 index 0000000000000000000000000000000000000000..3ced5b466a44a0a01a4750c771ef43df8073e102 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_half.py @@ -0,0 +1,593 @@ +import platform + +import pytest + +import numpy as np +from numpy import float16, float32, float64, uint16 +from numpy.testing import IS_WASM, assert_, assert_equal + + +def assert_raises_fpe(strmatch, callable, *args, **kwargs): + try: + callable(*args, **kwargs) + except FloatingPointError as exc: + assert_(str(exc).find(strmatch) >= 0, + f"Did not raise floating point {strmatch} error") + else: + assert_(False, + f"Did not raise floating point {strmatch} error") + +class TestHalf: + def _create_arrays_all(self): + # An array of all possible float16 values + all_f16 = np.arange(0x10000, dtype=uint16) + all_f16 = all_f16.view(float16) + + # NaN value can cause an invalid FP exception if HW is being used + with np.errstate(invalid='ignore'): + all_f32 = np.array(all_f16, dtype=float32) + all_f64 = np.array(all_f16, dtype=float64) + return all_f16, all_f32, all_f64 + + def _create_arrays_nonan(self): + # An array of all non-NaN float16 values, in sorted order + nonan_f16 = np.concatenate( + (np.arange(0xfc00, 0x7fff, -1, dtype=uint16), + np.arange(0x0000, 0x7c01, 1, dtype=uint16))) + nonan_f16 = nonan_f16.view(float16) + nonan_f32 = np.array(nonan_f16, dtype=float32) + nonan_f64 = np.array(nonan_f16, dtype=float64) + return nonan_f16, nonan_f32, nonan_f64 + + def _create_arrays_finite(self): + nonan_f16, nonan_f32, nonan_f64 = self._create_arrays_nonan() + finite_f16 = nonan_f16[1:-1] + finite_f32 = nonan_f32[1:-1] + finite_f64 = nonan_f64[1:-1] + return finite_f16, finite_f32, finite_f64 + + def test_half_conversions(self): + """Checks that all 16-bit values survive conversion + to/from 32-bit and 64-bit float""" + # Because the underlying routines preserve the NaN bits, every + # value is preserved when converting to/from other floats. + all_f16, all_f32, all_f64 = self._create_arrays_all() + nonan_f16, _, _ = self._create_arrays_nonan() + + # Convert from float32 back to float16 + with np.errstate(invalid='ignore'): + b = np.array(all_f32, dtype=float16) + # avoid testing NaNs due to differing bit patterns in Q/S NaNs + b_nn = b == b + assert_equal(all_f16[b_nn].view(dtype=uint16), + b[b_nn].view(dtype=uint16)) + + # Convert from float64 back to float16 + with np.errstate(invalid='ignore'): + b = np.array(all_f64, dtype=float16) + b_nn = b == b + assert_equal(all_f16[b_nn].view(dtype=uint16), + b[b_nn].view(dtype=uint16)) + + # Convert float16 to longdouble and back + # This doesn't necessarily preserve the extra NaN bits, + # so exclude NaNs. + a_ld = np.array(nonan_f16, dtype=np.longdouble) + b = np.array(a_ld, dtype=float16) + assert_equal(nonan_f16.view(dtype=uint16), + b.view(dtype=uint16)) + + # Check the range for which all integers can be represented + i_int = np.arange(-2048, 2049) + i_f16 = np.array(i_int, dtype=float16) + j = np.array(i_f16, dtype=int) + assert_equal(i_int, j) + + @pytest.mark.parametrize("string_dt", ["S", "U"]) + def test_half_conversion_to_string(self, string_dt): + # Currently uses S/U32 (which is sufficient for float32) + expected_dt = np.dtype(f"{string_dt}32") + assert np.promote_types(np.float16, string_dt) == expected_dt + assert np.promote_types(string_dt, np.float16) == expected_dt + + arr = np.ones(3, dtype=np.float16).astype(string_dt) + assert arr.dtype == expected_dt + + @pytest.mark.parametrize("dtype", ["S", "U", object]) + def test_to_half_cast_error(self, dtype): + arr = np.array(["3M"], dtype=dtype) + with pytest.raises(ValueError): + arr.astype(np.float16) + + arr = np.array(["23490349034"], dtype=dtype) + with np.errstate(all="warn"): + with pytest.warns(RuntimeWarning): + arr.astype(np.float16) + + with np.errstate(all="raise"): + with pytest.raises(FloatingPointError): + arr.astype(np.float16) + + @pytest.mark.parametrize("string_dt", ["S", "U"]) + def test_half_conversion_from_string(self, string_dt): + string = np.array("3.1416", dtype=string_dt) + assert string.astype(np.float16) == np.array(3.1416, dtype=np.float16) + + @pytest.mark.parametrize("offset", [None, "up", "down"]) + @pytest.mark.parametrize("shift", [None, "up", "down"]) + @pytest.mark.parametrize("float_t", [np.float32, np.float64]) + def test_half_conversion_rounding(self, float_t, shift, offset): + # Assumes that round to even is used during casting. + max_pattern = np.float16(np.finfo(np.float16).max).view(np.uint16) + + # Test all (positive) finite numbers, denormals are most interesting + # however: + f16s_patterns = np.arange(0, max_pattern + 1, dtype=np.uint16) + f16s_float = f16s_patterns.view(np.float16).astype(float_t) + + # Shift the values by half a bit up or a down (or do not shift), + if shift == "up": + f16s_float = 0.5 * (f16s_float[:-1] + f16s_float[1:])[1:] + elif shift == "down": + f16s_float = 0.5 * (f16s_float[:-1] + f16s_float[1:])[:-1] + else: + f16s_float = f16s_float[1:-1] + + # Increase the float by a minimal value: + if offset == "up": + f16s_float = np.nextafter(f16s_float, float_t(np.inf)) + elif offset == "down": + f16s_float = np.nextafter(f16s_float, float_t(-np.inf)) + + # Convert back to float16 and its bit pattern: + res_patterns = f16s_float.astype(np.float16).view(np.uint16) + + # The above calculation tries the original values, or the exact + # midpoints between the float16 values. It then further offsets them + # by as little as possible. If no offset occurs, "round to even" + # logic will be necessary, an arbitrarily small offset should cause + # normal up/down rounding always. + + # Calculate the expected pattern: + cmp_patterns = f16s_patterns[1:-1].copy() + + if shift == "down" and offset != "up": + shift_pattern = -1 + elif shift == "up" and offset != "down": + shift_pattern = 1 + else: + # There cannot be a shift, either shift is None, so all rounding + # will go back to original, or shift is reduced by offset too much. + shift_pattern = 0 + + # If rounding occurs, is it normal rounding or round to even? + if offset is None: + # Round to even occurs, modify only non-even, cast to allow + (-1) + cmp_patterns[0::2].view(np.int16)[...] += shift_pattern + else: + cmp_patterns.view(np.int16)[...] += shift_pattern + + assert_equal(res_patterns, cmp_patterns) + + @pytest.mark.parametrize(["float_t", "uint_t", "bits"], + [(np.float32, np.uint32, 23), + (np.float64, np.uint64, 52)]) + def test_half_conversion_denormal_round_even(self, float_t, uint_t, bits): + # Test specifically that all bits are considered when deciding + # whether round to even should occur (i.e. no bits are lost at the + # end. Compare also gh-12721. The most bits can get lost for the + # smallest denormal: + smallest_value = np.uint16(1).view(np.float16).astype(float_t) + assert smallest_value == 2**-24 + + # Will be rounded to zero based on round to even rule: + rounded_to_zero = smallest_value / float_t(2) + assert rounded_to_zero.astype(np.float16) == 0 + + # The significand will be all 0 for the float_t, test that we do not + # lose the lower ones of these: + for i in range(bits): + # slightly increasing the value should make it round up: + larger_pattern = rounded_to_zero.view(uint_t) | uint_t(1 << i) + larger_value = larger_pattern.view(float_t) + assert larger_value.astype(np.float16) == smallest_value + + def test_nans_infs(self): + all_f16, all_f32, _ = self._create_arrays_all() + with np.errstate(all='ignore'): + # Check some of the ufuncs + assert_equal(np.isnan(all_f16), np.isnan(all_f32)) + assert_equal(np.isinf(all_f16), np.isinf(all_f32)) + assert_equal(np.isfinite(all_f16), np.isfinite(all_f32)) + assert_equal(np.signbit(all_f16), np.signbit(all_f32)) + assert_equal(np.spacing(float16(65504)), np.inf) + + # Check comparisons of all values with NaN + nan = float16(np.nan) + + assert_(not (all_f16 == nan).any()) + assert_(not (nan == all_f16).any()) + + assert_((all_f16 != nan).all()) + assert_((nan != all_f16).all()) + + assert_(not (all_f16 < nan).any()) + assert_(not (nan < all_f16).any()) + + assert_(not (all_f16 <= nan).any()) + assert_(not (nan <= all_f16).any()) + + assert_(not (all_f16 > nan).any()) + assert_(not (nan > all_f16).any()) + + assert_(not (all_f16 >= nan).any()) + assert_(not (nan >= all_f16).any()) + + def test_half_values(self): + """Confirms a small number of known half values""" + a = np.array([1.0, -1.0, + 2.0, -2.0, + 0.0999755859375, 0.333251953125, # 1/10, 1/3 + 65504, -65504, # Maximum magnitude + 2.0**(-14), -2.0**(-14), # Minimum normal + 2.0**(-24), -2.0**(-24), # Minimum subnormal + 0, -1 / 1e1000, # Signed zeros + np.inf, -np.inf]) + b = np.array([0x3c00, 0xbc00, + 0x4000, 0xc000, + 0x2e66, 0x3555, + 0x7bff, 0xfbff, + 0x0400, 0x8400, + 0x0001, 0x8001, + 0x0000, 0x8000, + 0x7c00, 0xfc00], dtype=uint16) + b = b.view(dtype=float16) + assert_equal(a, b) + + def test_half_rounding(self): + """Checks that rounding when converting to half is correct""" + a = np.array([2.0**-25 + 2.0**-35, # Rounds to minimum subnormal + 2.0**-25, # Underflows to zero (nearest even mode) + 2.0**-26, # Underflows to zero + 1.0 + 2.0**-11 + 2.0**-16, # rounds to 1.0+2**(-10) + 1.0 + 2.0**-11, # rounds to 1.0 (nearest even mode) + 1.0 + 2.0**-12, # rounds to 1.0 + 65519, # rounds to 65504 + 65520], # rounds to inf + dtype=float64) + rounded = [2.0**-24, + 0.0, + 0.0, + 1.0 + 2.0**(-10), + 1.0, + 1.0, + 65504, + np.inf] + + # Check float64->float16 rounding + with np.errstate(over="ignore"): + b = np.array(a, dtype=float16) + assert_equal(b, rounded) + + # Check float32->float16 rounding + a = np.array(a, dtype=float32) + with np.errstate(over="ignore"): + b = np.array(a, dtype=float16) + assert_equal(b, rounded) + + def test_half_correctness(self): + """Take every finite float16, and check the casting functions with + a manual conversion.""" + finite_f16, finite_f32, finite_f64 = self._create_arrays_finite() + + # Create an array of all finite float16s + a_bits = finite_f16.view(dtype=uint16) + + # Convert to 64-bit float manually + a_sgn = (-1.0)**((a_bits & 0x8000) >> 15) + a_exp = np.array((a_bits & 0x7c00) >> 10, dtype=np.int32) - 15 + a_man = (a_bits & 0x03ff) * 2.0**(-10) + # Implicit bit of normalized floats + a_man[a_exp != -15] += 1 + # Denormalized exponent is -14 + a_exp[a_exp == -15] = -14 + + a_manual = a_sgn * a_man * 2.0**a_exp + + a32_fail = np.nonzero(finite_f32 != a_manual)[0] + if len(a32_fail) != 0: + bad_index = a32_fail[0] + assert_equal(finite_f32, a_manual, + "First non-equal is half value 0x%x -> %g != %g" % + (a_bits[bad_index], + finite_f32[bad_index], + a_manual[bad_index])) + + a64_fail = np.nonzero(finite_f64 != a_manual)[0] + if len(a64_fail) != 0: + bad_index = a64_fail[0] + assert_equal(finite_f64, a_manual, + "First non-equal is half value 0x%x -> %g != %g" % + (a_bits[bad_index], + finite_f64[bad_index], + a_manual[bad_index])) + + def test_half_ordering(self): + """Make sure comparisons are working right""" + nonan_f16, _, _ = self._create_arrays_nonan() + + # All non-NaN float16 values in reverse order + a = nonan_f16[::-1].copy() + + # 32-bit float copy + b = np.array(a, dtype=float32) + + # Should sort the same + a.sort() + b.sort() + assert_equal(a, b) + + # Comparisons should work + assert_((a[:-1] <= a[1:]).all()) + assert_(not (a[:-1] > a[1:]).any()) + assert_((a[1:] >= a[:-1]).all()) + assert_(not (a[1:] < a[:-1]).any()) + # All != except for +/-0 + assert_equal(np.nonzero(a[:-1] < a[1:])[0].size, a.size - 2) + assert_equal(np.nonzero(a[1:] > a[:-1])[0].size, a.size - 2) + + def test_half_funcs(self): + """Test the various ArrFuncs""" + + # fill + assert_equal(np.arange(10, dtype=float16), + np.arange(10, dtype=float32)) + + # fillwithscalar + a = np.zeros((5,), dtype=float16) + a.fill(1) + assert_equal(a, np.ones((5,), dtype=float16)) + + # nonzero and copyswap + a = np.array([0, 0, -1, -1 / 1e20, 0, 2.0**-24, 7.629e-6], dtype=float16) + assert_equal(a.nonzero()[0], + [2, 5, 6]) + a = a.byteswap() + a = a.view(a.dtype.newbyteorder()) + assert_equal(a.nonzero()[0], + [2, 5, 6]) + + # dot + a = np.arange(0, 10, 0.5, dtype=float16) + b = np.ones((20,), dtype=float16) + assert_equal(np.dot(a, b), + 95) + + # argmax + a = np.array([0, -np.inf, -2, 0.5, 12.55, 7.3, 2.1, 12.4], dtype=float16) + assert_equal(a.argmax(), + 4) + a = np.array([0, -np.inf, -2, np.inf, 12.55, np.nan, 2.1, 12.4], dtype=float16) + assert_equal(a.argmax(), + 5) + + # getitem + a = np.arange(10, dtype=float16) + for i in range(10): + assert_equal(a.item(i), i) + + def test_spacing_nextafter(self): + """Test np.spacing and np.nextafter""" + # All non-negative finite #'s + a = np.arange(0x7c00, dtype=uint16) + hinf = np.array((np.inf,), dtype=float16) + hnan = np.array((np.nan,), dtype=float16) + a_f16 = a.view(dtype=float16) + + assert_equal(np.spacing(a_f16[:-1]), a_f16[1:] - a_f16[:-1]) + + assert_equal(np.nextafter(a_f16[:-1], hinf), a_f16[1:]) + assert_equal(np.nextafter(a_f16[0], -hinf), -a_f16[1]) + assert_equal(np.nextafter(a_f16[1:], -hinf), a_f16[:-1]) + + assert_equal(np.nextafter(hinf, a_f16), a_f16[-1]) + assert_equal(np.nextafter(-hinf, a_f16), -a_f16[-1]) + + assert_equal(np.nextafter(hinf, hinf), hinf) + assert_equal(np.nextafter(hinf, -hinf), a_f16[-1]) + assert_equal(np.nextafter(-hinf, hinf), -a_f16[-1]) + assert_equal(np.nextafter(-hinf, -hinf), -hinf) + + assert_equal(np.nextafter(a_f16, hnan), hnan[0]) + assert_equal(np.nextafter(hnan, a_f16), hnan[0]) + + assert_equal(np.nextafter(hnan, hnan), hnan) + assert_equal(np.nextafter(hinf, hnan), hnan) + assert_equal(np.nextafter(hnan, hinf), hnan) + + # switch to negatives + a |= 0x8000 + + assert_equal(np.spacing(a_f16[0]), np.spacing(a_f16[1])) + assert_equal(np.spacing(a_f16[1:]), a_f16[:-1] - a_f16[1:]) + + assert_equal(np.nextafter(a_f16[0], hinf), -a_f16[1]) + assert_equal(np.nextafter(a_f16[1:], hinf), a_f16[:-1]) + assert_equal(np.nextafter(a_f16[:-1], -hinf), a_f16[1:]) + + assert_equal(np.nextafter(hinf, a_f16), -a_f16[-1]) + assert_equal(np.nextafter(-hinf, a_f16), a_f16[-1]) + + assert_equal(np.nextafter(a_f16, hnan), hnan[0]) + assert_equal(np.nextafter(hnan, a_f16), hnan[0]) + + def test_half_ufuncs(self): + """Test the various ufuncs""" + + a = np.array([0, 1, 2, 4, 2], dtype=float16) + b = np.array([-2, 5, 1, 4, 3], dtype=float16) + c = np.array([0, -1, -np.inf, np.nan, 6], dtype=float16) + + assert_equal(np.add(a, b), [-2, 6, 3, 8, 5]) + assert_equal(np.subtract(a, b), [2, -4, 1, 0, -1]) + assert_equal(np.multiply(a, b), [0, 5, 2, 16, 6]) + assert_equal(np.divide(a, b), [0, 0.199951171875, 2, 1, 0.66650390625]) + + assert_equal(np.equal(a, b), [False, False, False, True, False]) + assert_equal(np.not_equal(a, b), [True, True, True, False, True]) + assert_equal(np.less(a, b), [False, True, False, False, True]) + assert_equal(np.less_equal(a, b), [False, True, False, True, True]) + assert_equal(np.greater(a, b), [True, False, True, False, False]) + assert_equal(np.greater_equal(a, b), [True, False, True, True, False]) + assert_equal(np.logical_and(a, b), [False, True, True, True, True]) + assert_equal(np.logical_or(a, b), [True, True, True, True, True]) + assert_equal(np.logical_xor(a, b), [True, False, False, False, False]) + assert_equal(np.logical_not(a), [True, False, False, False, False]) + + assert_equal(np.isnan(c), [False, False, False, True, False]) + assert_equal(np.isinf(c), [False, False, True, False, False]) + assert_equal(np.isfinite(c), [True, True, False, False, True]) + assert_equal(np.signbit(b), [True, False, False, False, False]) + + assert_equal(np.copysign(b, a), [2, 5, 1, 4, 3]) + + assert_equal(np.maximum(a, b), [0, 5, 2, 4, 3]) + + x = np.maximum(b, c) + assert_(np.isnan(x[3])) + x[3] = 0 + assert_equal(x, [0, 5, 1, 0, 6]) + + assert_equal(np.minimum(a, b), [-2, 1, 1, 4, 2]) + + x = np.minimum(b, c) + assert_(np.isnan(x[3])) + x[3] = 0 + assert_equal(x, [-2, -1, -np.inf, 0, 3]) + + assert_equal(np.fmax(a, b), [0, 5, 2, 4, 3]) + assert_equal(np.fmax(b, c), [0, 5, 1, 4, 6]) + assert_equal(np.fmin(a, b), [-2, 1, 1, 4, 2]) + assert_equal(np.fmin(b, c), [-2, -1, -np.inf, 4, 3]) + + assert_equal(np.floor_divide(a, b), [0, 0, 2, 1, 0]) + assert_equal(np.remainder(a, b), [0, 1, 0, 0, 2]) + assert_equal(np.divmod(a, b), ([0, 0, 2, 1, 0], [0, 1, 0, 0, 2])) + assert_equal(np.square(b), [4, 25, 1, 16, 9]) + assert_equal(np.reciprocal(b), [-0.5, 0.199951171875, 1, 0.25, 0.333251953125]) + assert_equal(np.ones_like(b), [1, 1, 1, 1, 1]) + assert_equal(np.conjugate(b), b) + assert_equal(np.absolute(b), [2, 5, 1, 4, 3]) + assert_equal(np.negative(b), [2, -5, -1, -4, -3]) + assert_equal(np.positive(b), b) + assert_equal(np.sign(b), [-1, 1, 1, 1, 1]) + assert_equal(np.modf(b), ([0, 0, 0, 0, 0], b)) + assert_equal(np.frexp(b), ([-0.5, 0.625, 0.5, 0.5, 0.75], [2, 3, 1, 3, 2])) + assert_equal(np.ldexp(b, [0, 1, 2, 4, 2]), [-2, 10, 4, 64, 12]) + + def test_half_coercion(self): + """Test that half gets coerced properly with the other types""" + a16 = np.array((1,), dtype=float16) + a32 = np.array((1,), dtype=float32) + b16 = float16(1) + b32 = float32(1) + + assert np.power(a16, 2).dtype == float16 + assert np.power(a16, 2.0).dtype == float16 + assert np.power(a16, b16).dtype == float16 + assert np.power(a16, b32).dtype == float32 + assert np.power(a16, a16).dtype == float16 + assert np.power(a16, a32).dtype == float32 + + assert np.power(b16, 2).dtype == float16 + assert np.power(b16, 2.0).dtype == float16 + assert np.power(b16, b16).dtype, float16 + assert np.power(b16, b32).dtype, float32 + assert np.power(b16, a16).dtype, float16 + assert np.power(b16, a32).dtype, float32 + + assert np.power(a32, a16).dtype == float32 + assert np.power(a32, b16).dtype == float32 + assert np.power(b32, a16).dtype == float32 + assert np.power(b32, b16).dtype == float32 + + @pytest.mark.skipif(platform.machine() == "armv5tel", + reason="See gh-413.") + @pytest.mark.skipif(IS_WASM, + reason="fp exceptions don't work in wasm.") + def test_half_fpe(self): + with np.errstate(all='raise'): + sx16 = np.array((1e-4,), dtype=float16) + bx16 = np.array((1e4,), dtype=float16) + sy16 = float16(1e-4) + by16 = float16(1e4) + + # Underflow errors + assert_raises_fpe('underflow', lambda a, b: a * b, sx16, sx16) + assert_raises_fpe('underflow', lambda a, b: a * b, sx16, sy16) + assert_raises_fpe('underflow', lambda a, b: a * b, sy16, sx16) + assert_raises_fpe('underflow', lambda a, b: a * b, sy16, sy16) + assert_raises_fpe('underflow', lambda a, b: a / b, sx16, bx16) + assert_raises_fpe('underflow', lambda a, b: a / b, sx16, by16) + assert_raises_fpe('underflow', lambda a, b: a / b, sy16, bx16) + assert_raises_fpe('underflow', lambda a, b: a / b, sy16, by16) + assert_raises_fpe('underflow', lambda a, b: a / b, + float16(2.**-14), float16(2**11)) + assert_raises_fpe('underflow', lambda a, b: a / b, + float16(-2.**-14), float16(2**11)) + assert_raises_fpe('underflow', lambda a, b: a / b, + float16(2.**-14 + 2**-24), float16(2)) + assert_raises_fpe('underflow', lambda a, b: a / b, + float16(-2.**-14 - 2**-24), float16(2)) + assert_raises_fpe('underflow', lambda a, b: a / b, + float16(2.**-14 + 2**-23), float16(4)) + + # Overflow errors + assert_raises_fpe('overflow', lambda a, b: a * b, bx16, bx16) + assert_raises_fpe('overflow', lambda a, b: a * b, bx16, by16) + assert_raises_fpe('overflow', lambda a, b: a * b, by16, bx16) + assert_raises_fpe('overflow', lambda a, b: a * b, by16, by16) + assert_raises_fpe('overflow', lambda a, b: a / b, bx16, sx16) + assert_raises_fpe('overflow', lambda a, b: a / b, bx16, sy16) + assert_raises_fpe('overflow', lambda a, b: a / b, by16, sx16) + assert_raises_fpe('overflow', lambda a, b: a / b, by16, sy16) + assert_raises_fpe('overflow', lambda a, b: a + b, + float16(65504), float16(17)) + assert_raises_fpe('overflow', lambda a, b: a - b, + float16(-65504), float16(17)) + assert_raises_fpe('overflow', np.nextafter, float16(65504), float16(np.inf)) + assert_raises_fpe('overflow', np.nextafter, float16(-65504), float16(-np.inf)) # noqa: E501 + assert_raises_fpe('overflow', np.spacing, float16(65504)) + + # Invalid value errors + assert_raises_fpe('invalid', np.divide, float16(np.inf), float16(np.inf)) + assert_raises_fpe('invalid', np.spacing, float16(np.inf)) + assert_raises_fpe('invalid', np.spacing, float16(np.nan)) + + # These should not raise + float16(65472) + float16(32) + float16(2**-13) / float16(2) + float16(2**-14) / float16(2**10) + np.spacing(float16(-65504)) + np.nextafter(float16(65504), float16(-np.inf)) + np.nextafter(float16(-65504), float16(np.inf)) + np.nextafter(float16(np.inf), float16(0)) + np.nextafter(float16(-np.inf), float16(0)) + np.nextafter(float16(0), float16(np.nan)) + np.nextafter(float16(np.nan), float16(0)) + float16(2**-14) / float16(2**10) + float16(-2**-14) / float16(2**10) + float16(2**-14 + 2**-23) / float16(2) + float16(-2**-14 - 2**-23) / float16(2) + + def test_half_array_interface(self): + """Test that half is compatible with __array_interface__""" + class Dummy: + pass + + a = np.ones((1,), dtype=float16) + b = Dummy() + b.__array_interface__ = a.__array_interface__ + c = np.array(b) + assert_(c.dtype == float16) + assert_equal(a, c) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_hashtable.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_hashtable.py new file mode 100644 index 0000000000000000000000000000000000000000..25a7158aaf6fe04dca0f4540efa3f182d4e0b1c3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_hashtable.py @@ -0,0 +1,36 @@ +import random + +import pytest + +from numpy._core._multiarray_tests import identityhash_tester + + +@pytest.mark.parametrize("key_length", [1, 3, 6]) +@pytest.mark.parametrize("length", [1, 16, 2000]) +def test_identity_hashtable(key_length, length): + # use a 30 object pool for everything (duplicates will happen) + pool = [object() for i in range(20)] + keys_vals = [] + for i in range(length): + keys = tuple(random.choices(pool, k=key_length)) + keys_vals.append((keys, random.choice(pool))) + + dictionary = dict(keys_vals) + + # add a random item at the end: + keys_vals.append(random.choice(keys_vals)) + # the expected one could be different with duplicates: + expected = dictionary[keys_vals[-1][0]] + + res = identityhash_tester(key_length, keys_vals, replace=True) + assert res is expected + + if length == 1: + return + + # add a new item with a key that is already used and a new value, this + # should error if replace is False, see gh-26690 + new_key = (keys_vals[1][0], object()) + keys_vals[0] = new_key + with pytest.raises(RuntimeError): + identityhash_tester(key_length, keys_vals) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_indexerrors.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_indexerrors.py new file mode 100644 index 0000000000000000000000000000000000000000..70e97dd6428e859025c820b6ecef62fcecb79ba2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_indexerrors.py @@ -0,0 +1,122 @@ +import numpy as np +from numpy.testing import assert_raises, assert_raises_regex + + +class TestIndexErrors: + '''Tests to exercise indexerrors not covered by other tests.''' + + def test_arraytypes_fasttake(self): + 'take from a 0-length dimension' + x = np.empty((2, 3, 0, 4)) + assert_raises(IndexError, x.take, [0], axis=2) + assert_raises(IndexError, x.take, [1], axis=2) + assert_raises(IndexError, x.take, [0], axis=2, mode='wrap') + assert_raises(IndexError, x.take, [0], axis=2, mode='clip') + + def test_take_from_object(self): + # Check exception taking from object array + d = np.zeros(5, dtype=object) + assert_raises(IndexError, d.take, [6]) + + # Check exception taking from 0-d array + d = np.zeros((5, 0), dtype=object) + assert_raises(IndexError, d.take, [1], axis=1) + assert_raises(IndexError, d.take, [0], axis=1) + assert_raises(IndexError, d.take, [0]) + assert_raises(IndexError, d.take, [0], mode='wrap') + assert_raises(IndexError, d.take, [0], mode='clip') + + def test_multiindex_exceptions(self): + a = np.empty(5, dtype=object) + assert_raises(IndexError, a.item, 20) + a = np.empty((5, 0), dtype=object) + assert_raises(IndexError, a.item, (0, 0)) + + def test_put_exceptions(self): + a = np.zeros((5, 5)) + assert_raises(IndexError, a.put, 100, 0) + a = np.zeros((5, 5), dtype=object) + assert_raises(IndexError, a.put, 100, 0) + a = np.zeros((5, 5, 0)) + assert_raises(IndexError, a.put, 100, 0) + a = np.zeros((5, 5, 0), dtype=object) + assert_raises(IndexError, a.put, 100, 0) + + def test_iterators_exceptions(self): + "cases in iterators.c" + def assign(obj, ind, val): + obj[ind] = val + + a = np.zeros([1, 2, 3]) + assert_raises(IndexError, lambda: a[0, 5, None, 2]) + assert_raises(IndexError, lambda: a[0, 5, 0, 2]) + assert_raises(IndexError, lambda: assign(a, (0, 5, None, 2), 1)) + assert_raises(IndexError, lambda: assign(a, (0, 5, 0, 2), 1)) + + a = np.zeros([1, 0, 3]) + assert_raises(IndexError, lambda: a[0, 0, None, 2]) + assert_raises(IndexError, lambda: assign(a, (0, 0, None, 2), 1)) + + a = np.zeros([1, 2, 3]) + assert_raises(IndexError, lambda: a.flat[10]) + assert_raises(IndexError, lambda: assign(a.flat, 10, 5)) + a = np.zeros([1, 0, 3]) + assert_raises(IndexError, lambda: a.flat[10]) + assert_raises(IndexError, lambda: assign(a.flat, 10, 5)) + + a = np.zeros([1, 2, 3]) + assert_raises(IndexError, lambda: a.flat[np.array(10)]) + assert_raises(IndexError, lambda: assign(a.flat, np.array(10), 5)) + a = np.zeros([1, 0, 3]) + assert_raises(IndexError, lambda: a.flat[np.array(10)]) + assert_raises(IndexError, lambda: assign(a.flat, np.array(10), 5)) + + a = np.zeros([1, 2, 3]) + assert_raises(IndexError, lambda: a.flat[np.array([10])]) + assert_raises(IndexError, lambda: assign(a.flat, np.array([10]), 5)) + a = np.zeros([1, 0, 3]) + assert_raises(IndexError, lambda: a.flat[np.array([10])]) + assert_raises(IndexError, lambda: assign(a.flat, np.array([10]), 5)) + + def test_mapping(self): + "cases from mapping.c" + + def assign(obj, ind, val): + obj[ind] = val + + a = np.zeros((0, 10)) + assert_raises(IndexError, lambda: a[12]) + + a = np.zeros((3, 5)) + assert_raises(IndexError, lambda: a[(10, 20)]) + assert_raises(IndexError, lambda: assign(a, (10, 20), 1)) + a = np.zeros((3, 0)) + assert_raises(IndexError, lambda: a[(1, 0)]) + assert_raises(IndexError, lambda: assign(a, (1, 0), 1)) + + a = np.zeros((10,)) + assert_raises(IndexError, lambda: assign(a, 10, 1)) + a = np.zeros((0,)) + assert_raises(IndexError, lambda: assign(a, 10, 1)) + + a = np.zeros((3, 5)) + assert_raises(IndexError, lambda: a[(1, [1, 20])]) + assert_raises(IndexError, lambda: assign(a, (1, [1, 20]), 1)) + a = np.zeros((3, 0)) + assert_raises(IndexError, lambda: a[(1, [0, 1])]) + assert_raises(IndexError, lambda: assign(a, (1, [0, 1]), 1)) + + def test_mapping_error_message(self): + a = np.zeros((3, 5)) + index = (1, 2, 3, 4, 5) + assert_raises_regex( + IndexError, + "too many indices for array: " + "array is 2-dimensional, but 5 were indexed", + lambda: a[index]) + + def test_methods(self): + "cases from methods.c" + + a = np.zeros((3, 3)) + assert_raises(IndexError, lambda: a.item(100)) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_indexing.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_indexing.py new file mode 100644 index 0000000000000000000000000000000000000000..65d42d6c9370598411cd0b4f11f022de86a76e6f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_indexing.py @@ -0,0 +1,1692 @@ +import functools +import inspect +import operator +import sys +import warnings +from itertools import product + +import pytest + +import numpy as np +from numpy._core._multiarray_tests import array_indexing +from numpy.exceptions import ComplexWarning, VisibleDeprecationWarning +from numpy.testing import ( + HAS_REFCOUNT, + IS_PYPY, + assert_, + assert_array_equal, + assert_equal, + assert_raises, + assert_raises_regex, +) + + +class TestIndexing: + def test_index_no_floats(self): + a = np.array([[[5]]]) + + assert_raises(IndexError, lambda: a[0.0]) + assert_raises(IndexError, lambda: a[0, 0.0]) + assert_raises(IndexError, lambda: a[0.0, 0]) + assert_raises(IndexError, lambda: a[0.0, :]) + assert_raises(IndexError, lambda: a[:, 0.0]) + assert_raises(IndexError, lambda: a[:, 0.0, :]) + assert_raises(IndexError, lambda: a[0.0, :, :]) + assert_raises(IndexError, lambda: a[0, 0, 0.0]) + assert_raises(IndexError, lambda: a[0.0, 0, 0]) + assert_raises(IndexError, lambda: a[0, 0.0, 0]) + assert_raises(IndexError, lambda: a[-1.4]) + assert_raises(IndexError, lambda: a[0, -1.4]) + assert_raises(IndexError, lambda: a[-1.4, 0]) + assert_raises(IndexError, lambda: a[-1.4, :]) + assert_raises(IndexError, lambda: a[:, -1.4]) + assert_raises(IndexError, lambda: a[:, -1.4, :]) + assert_raises(IndexError, lambda: a[-1.4, :, :]) + assert_raises(IndexError, lambda: a[0, 0, -1.4]) + assert_raises(IndexError, lambda: a[-1.4, 0, 0]) + assert_raises(IndexError, lambda: a[0, -1.4, 0]) + assert_raises(IndexError, lambda: a[0.0:, 0.0]) + assert_raises(IndexError, lambda: a[0.0:, 0.0, :]) + + def test_slicing_no_floats(self): + a = np.array([[5]]) + + # start as float. + assert_raises(TypeError, lambda: a[0.0:]) + assert_raises(TypeError, lambda: a[0:, 0.0:2]) + assert_raises(TypeError, lambda: a[0.0::2, :0]) + assert_raises(TypeError, lambda: a[0.0:1:2, :]) + assert_raises(TypeError, lambda: a[:, 0.0:]) + # stop as float. + assert_raises(TypeError, lambda: a[:0.0]) + assert_raises(TypeError, lambda: a[:0, 1:2.0]) + assert_raises(TypeError, lambda: a[:0.0:2, :0]) + assert_raises(TypeError, lambda: a[:0.0, :]) + assert_raises(TypeError, lambda: a[:, 0:4.0:2]) + # step as float. + assert_raises(TypeError, lambda: a[::1.0]) + assert_raises(TypeError, lambda: a[0:, :2:2.0]) + assert_raises(TypeError, lambda: a[1::4.0, :0]) + assert_raises(TypeError, lambda: a[::5.0, :]) + assert_raises(TypeError, lambda: a[:, 0:4:2.0]) + # mixed. + assert_raises(TypeError, lambda: a[1.0:2:2.0]) + assert_raises(TypeError, lambda: a[1.0::2.0]) + assert_raises(TypeError, lambda: a[0:, :2.0:2.0]) + assert_raises(TypeError, lambda: a[1.0:1:4.0, :0]) + assert_raises(TypeError, lambda: a[1.0:5.0:5.0, :]) + assert_raises(TypeError, lambda: a[:, 0.4:4.0:2.0]) + # should still get the DeprecationWarning if step = 0. + assert_raises(TypeError, lambda: a[::0.0]) + + def test_index_no_array_to_index(self): + # No non-scalar arrays. + a = np.array([[[1]]]) + + assert_raises(TypeError, lambda: a[a:a:a]) + + def test_none_index(self): + # `None` index adds newaxis + a = np.array([1, 2, 3]) + assert_equal(a[None], a[np.newaxis]) + assert_equal(a[None].ndim, a.ndim + 1) + + def test_empty_tuple_index(self): + # Empty tuple index creates a view + a = np.array([1, 2, 3]) + assert_equal(a[()], a) + assert_(a[()].base is a) + a = np.array(0) + assert_(isinstance(a[()], np.int_)) + + def test_void_scalar_empty_tuple(self): + s = np.zeros((), dtype='V4') + assert_equal(s[()].dtype, s.dtype) + assert_equal(s[()], s) + assert_equal(type(s[...]), np.ndarray) + + def test_same_kind_index_casting(self): + # Indexes should be cast with same-kind and not safe, even if that + # is somewhat unsafe. So test various different code paths. + index = np.arange(5) + u_index = index.astype(np.uintp) + arr = np.arange(10) + + assert_array_equal(arr[index], arr[u_index]) + arr[u_index] = np.arange(5) + assert_array_equal(arr, np.arange(10)) + + arr = np.arange(10).reshape(5, 2) + assert_array_equal(arr[index], arr[u_index]) + + arr[u_index] = np.arange(5)[:, None] + assert_array_equal(arr, np.arange(5)[:, None].repeat(2, axis=1)) + + arr = np.arange(25).reshape(5, 5) + assert_array_equal(arr[u_index, u_index], arr[index, index]) + + def test_empty_fancy_index(self): + # Empty list index creates an empty array + # with the same dtype (but with weird shape) + a = np.array([1, 2, 3]) + assert_equal(a[[]], []) + assert_equal(a[[]].dtype, a.dtype) + + b = np.array([], dtype=np.intp) + assert_equal(a[[]], []) + assert_equal(a[[]].dtype, a.dtype) + + b = np.array([]) + assert_raises(IndexError, a.__getitem__, b) + + def test_gh_26542(self): + a = np.array([0, 1, 2]) + idx = np.array([2, 1, 0]) + a[idx] = a + expected = np.array([2, 1, 0]) + assert_equal(a, expected) + + def test_gh_26542_2d(self): + a = np.array([[0, 1, 2]]) + idx_row = np.zeros(3, dtype=int) + idx_col = np.array([2, 1, 0]) + a[idx_row, idx_col] = a + expected = np.array([[2, 1, 0]]) + assert_equal(a, expected) + + def test_gh_26542_index_overlap(self): + arr = np.arange(100) + expected_vals = np.copy(arr[:-10]) + arr[10:] = arr[:-10] + actual_vals = arr[10:] + assert_equal(actual_vals, expected_vals) + + def test_gh_26844(self): + expected = [0, 1, 3, 3, 3] + a = np.arange(5) + a[2:][a[:-2]] = 3 + assert_equal(a, expected) + + def test_gh_26844_segfault(self): + # check for absence of segfault for: + # https://github.com/numpy/numpy/pull/26958/files#r1854589178 + a = np.arange(5) + expected = [0, 1, 3, 3, 3] + a[2:][None, a[:-2]] = 3 + assert_equal(a, expected) + + def test_ellipsis_index(self): + a = np.array([[1, 2, 3], + [4, 5, 6], + [7, 8, 9]]) + assert_(a[...] is not a) + assert_equal(a[...], a) + # `a[...]` was `a` in numpy <1.9. + assert_(a[...].base is a) + + # Slicing with ellipsis can skip an + # arbitrary number of dimensions + assert_equal(a[0, ...], a[0]) + assert_equal(a[0, ...], a[0, :]) + assert_equal(a[..., 0], a[:, 0]) + + # Slicing with ellipsis always results + # in an array, not a scalar + assert_equal(a[0, ..., 1], np.array(2)) + + # Assignment with `(Ellipsis,)` on 0-d arrays + b = np.array(1) + b[(Ellipsis,)] = 2 + assert_equal(b, 2) + + def test_single_int_index(self): + # Single integer index selects one row + a = np.array([[1, 2, 3], + [4, 5, 6], + [7, 8, 9]]) + + assert_equal(a[0], [1, 2, 3]) + assert_equal(a[-1], [7, 8, 9]) + + # Index out of bounds produces IndexError + assert_raises(IndexError, a.__getitem__, 1 << 30) + # Index overflow produces IndexError + assert_raises(IndexError, a.__getitem__, 1 << 64) + + def test_single_bool_index(self): + # Single boolean index + a = np.array([[1, 2, 3], + [4, 5, 6], + [7, 8, 9]]) + + assert_equal(a[np.array(True)], a[None]) + assert_equal(a[np.array(False)], a[None][0:0]) + + def test_boolean_shape_mismatch(self): + arr = np.ones((5, 4, 3)) + + index = np.array([True]) + assert_raises(IndexError, arr.__getitem__, index) + + index = np.array([False] * 6) + assert_raises(IndexError, arr.__getitem__, index) + + index = np.zeros((4, 4), dtype=bool) + assert_raises(IndexError, arr.__getitem__, index) + + assert_raises(IndexError, arr.__getitem__, (slice(None), index)) + + def test_boolean_indexing_onedim(self): + # Indexing a 2-dimensional array with + # boolean array of length one + a = np.array([[0., 0., 0.]]) + b = np.array([True], dtype=bool) + assert_equal(a[b], a) + # boolean assignment + a[b] = 1. + assert_equal(a, [[1., 1., 1.]]) + + def test_boolean_assignment_value_mismatch(self): + # A boolean assignment should fail when the shape of the values + # cannot be broadcast to the subscription. (see also gh-3458) + a = np.arange(4) + + def f(a, v): + a[a > -1] = v + + assert_raises(ValueError, f, a, []) + assert_raises(ValueError, f, a, [1, 2, 3]) + assert_raises(ValueError, f, a[:1], [1, 2, 3]) + + def test_boolean_assignment_needs_api(self): + # See also gh-7666 + # This caused a segfault on Python 2 due to the GIL not being + # held when the iterator does not need it, but the transfer function + # does + arr = np.zeros(1000) + indx = np.zeros(1000, dtype=bool) + indx[:100] = True + arr[indx] = np.ones(100, dtype=object) + + expected = np.zeros(1000) + expected[:100] = 1 + assert_array_equal(arr, expected) + + def test_boolean_indexing_twodim(self): + # Indexing a 2-dimensional array with + # 2-dimensional boolean array + a = np.array([[1, 2, 3], + [4, 5, 6], + [7, 8, 9]]) + b = np.array([[ True, False, True], + [False, True, False], + [ True, False, True]]) + assert_equal(a[b], [1, 3, 5, 7, 9]) + assert_equal(a[b[1]], [[4, 5, 6]]) + assert_equal(a[b[0]], a[b[2]]) + + # boolean assignment + a[b] = 0 + assert_equal(a, [[0, 2, 0], + [4, 0, 6], + [0, 8, 0]]) + + def test_boolean_indexing_list(self): + # Regression test for #13715. It's a use-after-free bug which the + # test won't directly catch, but it will show up in valgrind. + a = np.array([1, 2, 3]) + b = [True, False, True] + # Two variants of the test because the first takes a fast path + assert_equal(a[b], [1, 3]) + assert_equal(a[None, b], [[1, 3]]) + + def test_reverse_strides_and_subspace_bufferinit(self): + # This tests that the strides are not reversed for simple and + # subspace fancy indexing. + a = np.ones(5) + b = np.zeros(5, dtype=np.intp)[::-1] + c = np.arange(5)[::-1] + + a[b] = c + # If the strides are not reversed, the 0 in the arange comes last. + assert_equal(a[0], 0) + + # This also tests that the subspace buffer is initialized: + a = np.ones((5, 2)) + c = np.arange(10).reshape(5, 2)[::-1] + a[b, :] = c + assert_equal(a[0], [0, 1]) + + def test_reversed_strides_result_allocation(self): + # Test a bug when calculating the output strides for a result array + # when the subspace size was 1 (and test other cases as well) + a = np.arange(10)[:, None] + i = np.arange(10)[::-1] + assert_array_equal(a[i], a[i.copy('C')]) + + a = np.arange(20).reshape(-1, 2) + + def test_uncontiguous_subspace_assignment(self): + # During development there was a bug activating a skip logic + # based on ndim instead of size. + a = np.full((3, 4, 2), -1) + b = np.full((3, 4, 2), -1) + + a[[0, 1]] = np.arange(2 * 4 * 2).reshape(2, 4, 2).T + b[[0, 1]] = np.arange(2 * 4 * 2).reshape(2, 4, 2).T.copy() + + assert_equal(a, b) + + def test_too_many_fancy_indices_special_case(self): + # Just documents behaviour, this is a small limitation. + a = np.ones((1,) * 64) # 64 is NPY_MAXDIMS + assert_raises(IndexError, a.__getitem__, (np.array([0]),) * 64) + + def test_scalar_array_bool(self): + # NumPy bools can be used as boolean index (python ones as of yet not) + a = np.array(1) + assert_equal(a[np.bool(True)], a[np.array(True)]) + assert_equal(a[np.bool(False)], a[np.array(False)]) + + # After deprecating bools as integers: + #a = np.array([0,1,2]) + #assert_equal(a[True, :], a[None, :]) + #assert_equal(a[:, True], a[:, None]) + # + #assert_(not np.may_share_memory(a, a[True, :])) + + def test_everything_returns_views(self): + # Before `...` would return a itself. + a = np.arange(5) + + assert_(a is not a[()]) + assert_(a is not a[...]) + assert_(a is not a[:]) + + def test_broaderrors_indexing(self): + a = np.zeros((5, 5)) + assert_raises(IndexError, a.__getitem__, ([0, 1], [0, 1, 2])) + assert_raises(IndexError, a.__setitem__, ([0, 1], [0, 1, 2]), 0) + + def test_trivial_fancy_out_of_bounds(self): + a = np.zeros(5) + ind = np.ones(20, dtype=np.intp) + ind[-1] = 10 + assert_raises(IndexError, a.__getitem__, ind) + assert_raises(IndexError, a.__setitem__, ind, 0) + ind = np.ones(20, dtype=np.intp) + ind[0] = 11 + assert_raises(IndexError, a.__getitem__, ind) + assert_raises(IndexError, a.__setitem__, ind, 0) + + def test_trivial_fancy_not_possible(self): + # Test that the fast path for trivial assignment is not incorrectly + # used when the index is not contiguous or 1D, see also gh-11467. + a = np.arange(6) + idx = np.arange(6, dtype=np.intp).reshape(2, 1, 3)[:, :, 0] + assert_array_equal(a[idx], idx) + + # this case must not go into the fast path, note that idx is + # a non-contiguous none 1D array here. + a[idx] = -1 + res = np.arange(6) + res[0] = -1 + res[3] = -1 + assert_array_equal(a, res) + + def test_nonbaseclass_values(self): + class SubClass(np.ndarray): + def __array_finalize__(self, old): + # Have array finalize do funny things + self.fill(99) + + a = np.zeros((5, 5)) + s = a.copy().view(type=SubClass) + s.fill(1) + + a[[0, 1, 2, 3, 4], :] = s + assert_((a == 1).all()) + + # Subspace is last, so transposing might want to finalize + a[:, [0, 1, 2, 3, 4]] = s + assert_((a == 1).all()) + + a.fill(0) + a[...] = s + assert_((a == 1).all()) + + def test_array_like_values(self): + # Similar to the above test, but use a memoryview instead + a = np.zeros((5, 5)) + s = np.arange(25, dtype=np.float64).reshape(5, 5) + + a[[0, 1, 2, 3, 4], :] = memoryview(s) + assert_array_equal(a, s) + + a[:, [0, 1, 2, 3, 4]] = memoryview(s) + assert_array_equal(a, s) + + a[...] = memoryview(s) + assert_array_equal(a, s) + + @pytest.mark.parametrize("writeable", [True, False]) + def test_subclass_writeable(self, writeable): + d = np.rec.array([('NGC1001', 11), ('NGC1002', 1.), ('NGC1003', 1.)], + dtype=[('target', 'S20'), ('V_mag', '>f4')]) + d.flags.writeable = writeable + # Advanced indexing results are always writeable: + ind = np.array([False, True, True], dtype=bool) + assert d[ind].flags.writeable + ind = np.array([0, 1]) + assert d[ind].flags.writeable + # Views should be writeable if the original array is: + assert d[...].flags.writeable == writeable + assert d[0].flags.writeable == writeable + + def test_memory_order(self): + # This is not necessary to preserve. Memory layouts for + # more complex indices are not as simple. + a = np.arange(10) + b = np.arange(10).reshape(5, 2).T + assert_(a[b].flags.f_contiguous) + + # Takes a different implementation branch: + a = a.reshape(-1, 1) + assert_(a[b, 0].flags.f_contiguous) + + def test_scalar_return_type(self): + # Full scalar indices should return scalars and object + # arrays should not call PyArray_Return on their items + class Zero: + # The most basic valid indexing + def __index__(self): + return 0 + + z = Zero() + + class ArrayLike: + # Simple array, should behave like the array + def __array__(self, dtype=None, copy=None): + return np.array(0) + + a = np.zeros(()) + assert_(isinstance(a[()], np.float64)) + a = np.zeros(1) + assert_(isinstance(a[z], np.float64)) + a = np.zeros((1, 1)) + assert_(isinstance(a[z, np.array(0)], np.float64)) + assert_(isinstance(a[z, ArrayLike()], np.float64)) + + # And object arrays do not call it too often: + b = np.array(0) + a = np.array(0, dtype=object) + a[()] = b + assert_(isinstance(a[()], np.ndarray)) + a = np.array([b, None]) + assert_(isinstance(a[z], np.ndarray)) + a = np.array([[b, None]]) + assert_(isinstance(a[z, np.array(0)], np.ndarray)) + assert_(isinstance(a[z, ArrayLike()], np.ndarray)) + + def test_small_regressions(self): + # Reference count of intp for index checks + a = np.array([0]) + if HAS_REFCOUNT: + refcount = sys.getrefcount(np.dtype(np.intp)) + # item setting always checks indices in separate function: + a[np.array([0], dtype=np.intp)] = 1 + a[np.array([0], dtype=np.uint8)] = 1 + assert_raises(IndexError, a.__setitem__, + np.array([1], dtype=np.intp), 1) + assert_raises(IndexError, a.__setitem__, + np.array([1], dtype=np.uint8), 1) + + if HAS_REFCOUNT: + assert_equal(sys.getrefcount(np.dtype(np.intp)), refcount) + + def test_unaligned(self): + v = (np.zeros(64, dtype=np.int8) + ord('a'))[1:-7] + d = v.view(np.dtype("S8")) + # unaligned source + x = (np.zeros(16, dtype=np.int8) + ord('a'))[1:-7] + x = x.view(np.dtype("S8")) + x[...] = np.array("b" * 8, dtype="S") + b = np.arange(d.size) + # trivial + assert_equal(d[b], d) + d[b] = x + # nontrivial + # unaligned index array + b = np.zeros(d.size + 1).view(np.int8)[1:-(np.intp(0).itemsize - 1)] + b = b.view(np.intp)[:d.size] + b[...] = np.arange(d.size) + assert_equal(d[b.astype(np.int16)], d) + d[b.astype(np.int16)] = x + # boolean + d[b % 2 == 0] + d[b % 2 == 0] = x[::2] + + def test_tuple_subclass(self): + arr = np.ones((5, 5)) + + # A tuple subclass should also be an nd-index + class TupleSubclass(tuple): + pass + index = ([1], [1]) + index = TupleSubclass(index) + assert_(arr[index].shape == (1,)) + # Unlike the non nd-index: + assert_(arr[index,].shape != (1,)) + + def test_broken_sequence_not_nd_index(self): + # See gh-5063: + # If we have an object which claims to be a sequence, but fails + # on item getting, this should not be converted to an nd-index (tuple) + # If this object happens to be a valid index otherwise, it should work + # This object here is very dubious and probably bad though: + class SequenceLike: + def __index__(self): + return 0 + + def __len__(self): + return 1 + + def __getitem__(self, item): + raise IndexError('Not possible') + + arr = np.arange(10) + assert_array_equal(arr[SequenceLike()], arr[SequenceLike(),]) + + # also test that field indexing does not segfault + # for a similar reason, by indexing a structured array + arr = np.zeros((1,), dtype=[('f1', 'i8'), ('f2', 'i8')]) + assert_array_equal(arr[SequenceLike()], arr[SequenceLike(),]) + + def test_indexing_array_weird_strides(self): + # See also gh-6221 + # the shapes used here come from the issue and create the correct + # size for the iterator buffering size. + x = np.ones(10) + x2 = np.ones((10, 2)) + ind = np.arange(10)[:, None, None, None] + ind = np.broadcast_to(ind, (10, 55, 4, 4)) + + # single advanced index case + assert_array_equal(x[ind], x[ind.copy()]) + # higher dimensional advanced index + zind = np.zeros(4, dtype=np.intp) + assert_array_equal(x2[ind, zind], x2[ind.copy(), zind]) + + def test_indexing_array_negative_strides(self): + # From gh-8264, + # core dumps if negative strides are used in iteration + arro = np.zeros((4, 4)) + arr = arro[::-1, ::-1] + + slices = (slice(None), [0, 1, 2, 3]) + arr[slices] = 10 + assert_array_equal(arr, 10.) + + def test_character_assignment(self): + # This is an example a function going through CopyObject which + # used to have an untested special path for scalars + # (the character special dtype case, should be deprecated probably) + arr = np.zeros((1, 5), dtype="c") + arr[0] = np.str_("asdfg") # must assign as a sequence + assert_array_equal(arr[0], np.array("asdfg", dtype="c")) + assert arr[0, 1] == b"s" # make sure not all were set to "a" for both + + @pytest.mark.parametrize("index", + [True, False, np.array([0])]) + @pytest.mark.parametrize("num", [64, 80]) + @pytest.mark.parametrize("original_ndim", [1, 64]) + def test_too_many_advanced_indices(self, index, num, original_ndim): + # These are limitations based on the number of arguments we can process. + # For `num=32` (and all boolean cases), the result is actually define; + # but the use of NpyIter (NPY_MAXARGS) limits it for technical reasons. + arr = np.ones((1,) * original_ndim) + with pytest.raises(IndexError): + arr[(index,) * num] + with pytest.raises(IndexError): + arr[(index,) * num] = 1. + + def test_nontuple_ndindex(self): + a = np.arange(25).reshape((5, 5)) + assert_equal(a[[0, 1]], np.array([a[0], a[1]])) + assert_equal(a[[0, 1], [0, 1]], np.array([0, 6])) + assert_raises(IndexError, a.__getitem__, [slice(None)]) + + +class TestFieldIndexing: + def test_scalar_return_type(self): + # Field access on an array should return an array, even if it + # is 0-d. + a = np.zeros((), [('a', 'f8')]) + assert_(isinstance(a['a'], np.ndarray)) + assert_(isinstance(a[['a']], np.ndarray)) + + +class TestBroadcastedAssignments: + def assign(self, a, ind, val): + a[ind] = val + return a + + def test_prepending_ones(self): + a = np.zeros((3, 2)) + + a[...] = np.ones((1, 3, 2)) + # Fancy with subspace with and without transpose + a[[0, 1, 2], :] = np.ones((1, 3, 2)) + a[:, [0, 1]] = np.ones((1, 3, 2)) + # Fancy without subspace (with broadcasting) + a[[[0], [1], [2]], [0, 1]] = np.ones((1, 3, 2)) + + def test_prepend_not_one(self): + assign = self.assign + s_ = np.s_ + a = np.zeros(5) + + # Too large and not only ones. + assert_raises(ValueError, assign, a, s_[...], np.ones((2, 1))) + assert_raises(ValueError, assign, a, s_[[1, 2, 3],], np.ones((2, 1))) + assert_raises(ValueError, assign, a, s_[[[1], [2]],], np.ones((2, 2, 1))) + + def test_simple_broadcasting_errors(self): + assign = self.assign + s_ = np.s_ + a = np.zeros((5, 1)) + + assert_raises(ValueError, assign, a, s_[...], np.zeros((5, 2))) + assert_raises(ValueError, assign, a, s_[...], np.zeros((5, 0))) + assert_raises(ValueError, assign, a, s_[:, [0]], np.zeros((5, 2))) + assert_raises(ValueError, assign, a, s_[:, [0]], np.zeros((5, 0))) + assert_raises(ValueError, assign, a, s_[[0], :], np.zeros((2, 1))) + + @pytest.mark.parametrize("index", [ + (..., [1, 2], slice(None)), + ([0, 1], ..., 0), + (..., [1, 2], [1, 2])]) + def test_broadcast_error_reports_correct_shape(self, index): + values = np.zeros((100, 100)) # will never broadcast below + + arr = np.zeros((3, 4, 5, 6, 7)) + # We currently report without any spaces (could be changed) + shape_str = str(arr[index].shape).replace(" ", "") + + with pytest.raises(ValueError) as e: + arr[index] = values + + assert str(e.value).endswith(shape_str) + + def test_index_is_larger(self): + # Simple case of fancy index broadcasting of the index. + a = np.zeros((5, 5)) + a[[[0], [1], [2]], [0, 1, 2]] = [2, 3, 4] + + assert_((a[:3, :3] == [2, 3, 4]).all()) + + def test_broadcast_subspace(self): + a = np.zeros((100, 100)) + v = np.arange(100)[:, None] + b = np.arange(100)[::-1] + a[b] = v + assert_((a[::-1] == v).all()) + + +class TestSubclasses: + def test_basic(self): + # Test that indexing in various ways produces SubClass instances, + # and that the base is set up correctly: the original subclass + # instance for views, and a new ndarray for advanced/boolean indexing + # where a copy was made (latter a regression test for gh-11983). + class SubClass(np.ndarray): + pass + + a = np.arange(5) + s = a.view(SubClass) + s_slice = s[:3] + assert_(type(s_slice) is SubClass) + assert_(s_slice.base is s) + assert_array_equal(s_slice, a[:3]) + + s_fancy = s[[0, 1, 2]] + assert_(type(s_fancy) is SubClass) + assert_(s_fancy.base is not s) + assert_(type(s_fancy.base) is np.ndarray) + assert_array_equal(s_fancy, a[[0, 1, 2]]) + assert_array_equal(s_fancy.base, a[[0, 1, 2]]) + + s_bool = s[s > 0] + assert_(type(s_bool) is SubClass) + assert_(s_bool.base is not s) + assert_(type(s_bool.base) is np.ndarray) + assert_array_equal(s_bool, a[a > 0]) + assert_array_equal(s_bool.base, a[a > 0]) + + def test_fancy_on_read_only(self): + # Test that fancy indexing on read-only SubClass does not make a + # read-only copy (gh-14132) + class SubClass(np.ndarray): + pass + + a = np.arange(5) + s = a.view(SubClass) + s.flags.writeable = False + s_fancy = s[[0, 1, 2]] + assert_(s_fancy.flags.writeable) + + def test_finalize_gets_full_info(self): + # Array finalize should be called on the filled array. + class SubClass(np.ndarray): + def __array_finalize__(self, old): + self.finalize_status = np.array(self) + self.old = old + + s = np.arange(10).view(SubClass) + new_s = s[:3] + assert_array_equal(new_s.finalize_status, new_s) + assert_array_equal(new_s.old, s) + + new_s = s[[0, 1, 2, 3]] + assert_array_equal(new_s.finalize_status, new_s) + assert_array_equal(new_s.old, s) + + new_s = s[s > 0] + assert_array_equal(new_s.finalize_status, new_s) + assert_array_equal(new_s.old, s) + + +class TestFancyIndexingCast: + def test_boolean_index_cast_assign(self): + # Setup the boolean index and float arrays. + shape = (8, 63) + bool_index = np.zeros(shape).astype(bool) + bool_index[0, 1] = True + zero_array = np.zeros(shape) + + # Assigning float is fine. + zero_array[bool_index] = np.array([1]) + assert_equal(zero_array[0, 1], 1) + + # Fancy indexing works, although we get a cast warning. + pytest.warns(ComplexWarning, + zero_array.__setitem__, ([0], [1]), np.array([2 + 1j])) + assert_equal(zero_array[0, 1], 2) # No complex part + + # Cast complex to float, throwing away the imaginary portion. + pytest.warns(ComplexWarning, + zero_array.__setitem__, bool_index, np.array([1j])) + assert_equal(zero_array[0, 1], 0) + + +class TestFancyIndexingEquivalence: + def test_object_assign(self): + # Check that the field and object special case using copyto is active. + # The right hand side cannot be converted to an array here. + a = np.arange(5, dtype=object) + b = a.copy() + a[:3] = [1, (1, 2), 3] + b[[0, 1, 2]] = [1, (1, 2), 3] + assert_array_equal(a, b) + + # test same for subspace fancy indexing + b = np.arange(5, dtype=object)[None, :] + b[[0], :3] = [[1, (1, 2), 3]] + assert_array_equal(a, b[0]) + + # Check that swapping of axes works. + # There was a bug that made the later assignment throw a ValueError + # do to an incorrectly transposed temporary right hand side (gh-5714) + b = b.T + b[:3, [0]] = [[1], [(1, 2)], [3]] + assert_array_equal(a, b[:, 0]) + + # Another test for the memory order of the subspace + arr = np.ones((3, 4, 5), dtype=object) + # Equivalent slicing assignment for comparison + cmp_arr = arr.copy() + cmp_arr[:1, ...] = [[[1], [2], [3], [4]]] + arr[[0], ...] = [[[1], [2], [3], [4]]] + assert_array_equal(arr, cmp_arr) + arr = arr.copy('F') + arr[[0], ...] = [[[1], [2], [3], [4]]] + assert_array_equal(arr, cmp_arr) + + def test_cast_equivalence(self): + # Yes, normal slicing uses unsafe casting. + a = np.arange(5) + b = a.copy() + + a[:3] = np.array(['2', '-3', '-1']) + b[[0, 2, 1]] = np.array(['2', '-1', '-3']) + assert_array_equal(a, b) + + # test the same for subspace fancy indexing + b = np.arange(5)[None, :] + b[[0], :3] = np.array([['2', '-3', '-1']]) + assert_array_equal(a, b[0]) + + +class TestMultiIndexingAutomated: + """ + These tests use code to mimic the C-Code indexing for selection. + + NOTE: + + * This still lacks tests for complex item setting. + * If you change behavior of indexing, you might want to modify + these tests to try more combinations. + * Behavior was written to match numpy version 1.8. (though a + first version matched 1.7.) + * Only tuple indices are supported by the mimicking code. + (and tested as of writing this) + * Error types should match most of the time as long as there + is only one error. For multiple errors, what gets raised + will usually not be the same one. They are *not* tested. + + Update 2016-11-30: It is probably not worth maintaining this test + indefinitely and it can be dropped if maintenance becomes a burden. + + """ + + def _create_array(self): + return np.arange(np.prod([3, 1, 5, 6])).reshape(3, 1, 5, 6) + + def _create_complex_indices(self): + return ['skip', Ellipsis, + 0, + # Boolean indices, up to 3-d for some special cases of eating up + # dimensions, also need to test all False + np.array([True, False, False]), + np.array([[True, False], [False, True]]), + np.array([[[False, False], [False, False]]]), + # Some slices: + slice(-5, 5, 2), + slice(1, 1, 100), + slice(4, -1, -2), + slice(None, None, -3), + # Some Fancy indexes: + np.empty((0, 1, 1), dtype=np.intp), # empty and can be broadcast + np.array([0, 1, -2]), + np.array([[2], [0], [1]]), + np.array([[0, -1], [0, 1]], dtype=np.dtype('intp').newbyteorder()), + np.array([2, -1], dtype=np.int8), + np.zeros([1] * 31, dtype=int), # trigger too large array. + np.array([0., 1.])] # invalid datatype + + def _get_multi_index(self, arr, indices): + """Mimic multi dimensional indexing. + + Parameters + ---------- + arr : ndarray + Array to be indexed. + indices : tuple of index objects + + Returns + ------- + out : ndarray + An array equivalent to the indexing operation (but always a copy). + `arr[indices]` should be identical. + no_copy : bool + Whether the indexing operation requires a copy. If this is `True`, + `np.may_share_memory(arr, arr[indices])` should be `True` (with + some exceptions for scalars and possibly 0-d arrays). + + Notes + ----- + While the function may mostly match the errors of normal indexing this + is generally not the case. + """ + in_indices = list(indices) + indices = [] + # if False, this is a fancy or boolean index + no_copy = True + # number of fancy/scalar indexes that are not consecutive + num_fancy = 0 + # number of dimensions indexed by a "fancy" index + fancy_dim = 0 + # NOTE: This is a funny twist (and probably OK to change). + # The boolean array has illegal indexes, but this is + # allowed if the broadcast fancy-indices are 0-sized. + # This variable is to catch that case. + error_unless_broadcast_to_empty = False + + # We need to handle Ellipsis and make arrays from indices, also + # check if this is fancy indexing (set no_copy). + ndim = 0 + ellipsis_pos = None # define here mostly to replace all but first. + for i, indx in enumerate(in_indices): + if indx is None: + continue + if isinstance(indx, np.ndarray) and indx.dtype == bool: + no_copy = False + if indx.ndim == 0: + raise IndexError + # boolean indices can have higher dimensions + ndim += indx.ndim + fancy_dim += indx.ndim + continue + if indx is Ellipsis: + if ellipsis_pos is None: + ellipsis_pos = i + continue # do not increment ndim counter + raise IndexError + if isinstance(indx, slice): + ndim += 1 + continue + if not isinstance(indx, np.ndarray): + # This could be open for changes in numpy. + # numpy should maybe raise an error if casting to intp + # is not safe. It rejects np.array([1., 2.]) but not + # [1., 2.] as index (same for ie. np.take). + # (Note the importance of empty lists if changing this here) + try: + indx = np.array(indx, dtype=np.intp) + except ValueError: + raise IndexError + in_indices[i] = indx + elif indx.dtype.kind not in 'bi': + raise IndexError('arrays used as indices must be of ' + 'integer (or boolean) type') + if indx.ndim != 0: + no_copy = False + ndim += 1 + fancy_dim += 1 + + if arr.ndim - ndim < 0: + # we can't take more dimensions then we have, not even for 0-d + # arrays. since a[()] makes sense, but not a[(),]. We will + # raise an error later on, unless a broadcasting error occurs + # first. + raise IndexError + + if ndim == 0 and None not in in_indices: + # Well we have no indexes or one Ellipsis. This is legal. + return arr.copy(), no_copy + + if ellipsis_pos is not None: + in_indices[ellipsis_pos:ellipsis_pos + 1] = ([slice(None, None)] * + (arr.ndim - ndim)) + + for ax, indx in enumerate(in_indices): + if isinstance(indx, slice): + # convert to an index array + indx = np.arange(*indx.indices(arr.shape[ax])) + indices.append(['s', indx]) + continue + elif indx is None: + # this is like taking a slice with one element from a new axis: + indices.append(['n', np.array([0], dtype=np.intp)]) + arr = arr.reshape(arr.shape[:ax] + (1,) + arr.shape[ax:]) + continue + if isinstance(indx, np.ndarray) and indx.dtype == bool: + if indx.shape != arr.shape[ax:ax + indx.ndim]: + raise IndexError + + try: + flat_indx = np.ravel_multi_index(np.nonzero(indx), + arr.shape[ax:ax + indx.ndim], mode='raise') + except Exception: + error_unless_broadcast_to_empty = True + # fill with 0s instead, and raise error later + flat_indx = np.array([0] * indx.sum(), dtype=np.intp) + # concatenate axis into a single one: + if indx.ndim != 0: + arr = arr.reshape(arr.shape[:ax] + + (np.prod(arr.shape[ax:ax + indx.ndim]),) + + arr.shape[ax + indx.ndim:]) + indx = flat_indx + else: + # This could be changed, a 0-d boolean index can + # make sense (even outside the 0-d indexed array case) + # Note that originally this is could be interpreted as + # integer in the full integer special case. + raise IndexError + # If the index is a singleton, the bounds check is done + # before the broadcasting. This used to be different in <1.9 + elif indx.ndim == 0 and not ( + -arr.shape[ax] <= indx < arr.shape[ax] + ): + raise IndexError + if indx.ndim == 0: + # The index is a scalar. This used to be two fold, but if + # fancy indexing was active, the check was done later, + # possibly after broadcasting it away (1.7. or earlier). + # Now it is always done. + if indx >= arr.shape[ax] or indx < - arr.shape[ax]: + raise IndexError + if (len(indices) > 0 and + indices[-1][0] == 'f' and + ax != ellipsis_pos): + # NOTE: There could still have been a 0-sized Ellipsis + # between them. Checked that with ellipsis_pos. + indices[-1].append(indx) + else: + # We have a fancy index that is not after an existing one. + # NOTE: A 0-d array triggers this as well, while one may + # expect it to not trigger it, since a scalar would not be + # considered fancy indexing. + num_fancy += 1 + indices.append(['f', indx]) + + if num_fancy > 1 and not no_copy: + # We have to flush the fancy indexes left + new_indices = indices[:] + axes = list(range(arr.ndim)) + fancy_axes = [] + new_indices.insert(0, ['f']) + ni = 0 + ai = 0 + for indx in indices: + ni += 1 + if indx[0] == 'f': + new_indices[0].extend(indx[1:]) + del new_indices[ni] + ni -= 1 + for ax in range(ai, ai + len(indx[1:])): + fancy_axes.append(ax) + axes.remove(ax) + ai += len(indx) - 1 # axis we are at + indices = new_indices + # and now we need to transpose arr: + arr = arr.transpose(*(fancy_axes + axes)) + + # We only have one 'f' index now and arr is transposed accordingly. + # Now handle newaxis by reshaping... + ax = 0 + for indx in indices: + if indx[0] == 'f': + if len(indx) == 1: + continue + # First of all, reshape arr to combine fancy axes into one: + orig_shape = arr.shape + orig_slice = orig_shape[ax:ax + len(indx[1:])] + arr = arr.reshape(arr.shape[:ax] + + (np.prod(orig_slice).astype(int),) + + arr.shape[ax + len(indx[1:]):]) + + # Check if broadcasting works + res = np.broadcast(*indx[1:]) + # unfortunately the indices might be out of bounds. So check + # that first, and use mode='wrap' then. However only if + # there are any indices... + if res.size != 0: + if error_unless_broadcast_to_empty: + raise IndexError + for _indx, _size in zip(indx[1:], orig_slice): + if _indx.size == 0: + continue + if np.any(_indx >= _size) or np.any(_indx < -_size): + raise IndexError + if len(indx[1:]) == len(orig_slice): + if np.prod(orig_slice) == 0: + # Work around for a crash or IndexError with 'wrap' + # in some 0-sized cases. + try: + mi = np.ravel_multi_index(indx[1:], orig_slice, + mode='raise') + except Exception: + # This happens with 0-sized orig_slice (sometimes?) + # here it is a ValueError, but indexing gives a: + raise IndexError('invalid index into 0-sized') + else: + mi = np.ravel_multi_index(indx[1:], orig_slice, + mode='wrap') + else: + # Maybe never happens... + raise ValueError + arr = arr.take(mi.ravel(), axis=ax) + try: + arr = arr.reshape(arr.shape[:ax] + + mi.shape + + arr.shape[ax + 1:]) + except ValueError: + # too many dimensions, probably + raise IndexError + ax += mi.ndim + continue + + # If we are here, we have a 1D array for take: + arr = arr.take(indx[1], axis=ax) + ax += 1 + + return arr, no_copy + + def _check_multi_index(self, arr, index): + """Check a multi index item getting and simple setting. + + Parameters + ---------- + arr : ndarray + Array to be indexed, must be a reshaped arange. + index : tuple of indexing objects + Index being tested. + """ + # Test item getting + try: + mimic_get, no_copy = self._get_multi_index(arr, index) + except Exception as e: + if HAS_REFCOUNT: + prev_refcount = sys.getrefcount(arr) + assert_raises(type(e), arr.__getitem__, index) + assert_raises(type(e), arr.__setitem__, index, 0) + if HAS_REFCOUNT: + assert_equal(prev_refcount, sys.getrefcount(arr)) + return + + self._compare_index_result(arr, index, mimic_get, no_copy) + + def _check_single_index(self, arr, index): + """Check a single index item getting and simple setting. + + Parameters + ---------- + arr : ndarray + Array to be indexed, must be an arange. + index : indexing object + Index being tested. Must be a single index and not a tuple + of indexing objects (see also `_check_multi_index`). + """ + try: + mimic_get, no_copy = self._get_multi_index(arr, (index,)) + except Exception as e: + if HAS_REFCOUNT: + prev_refcount = sys.getrefcount(arr) + assert_raises(type(e), arr.__getitem__, index) + assert_raises(type(e), arr.__setitem__, index, 0) + if HAS_REFCOUNT: + assert_equal(prev_refcount, sys.getrefcount(arr)) + return + + self._compare_index_result(arr, index, mimic_get, no_copy) + + def _compare_index_result(self, arr, index, mimic_get, no_copy): + """Compare mimicked result to indexing result. + """ + arr = arr.copy() + if HAS_REFCOUNT: + startcount = sys.getrefcount(arr) + indexed_arr = arr[index] + assert_array_equal(indexed_arr, mimic_get) + # Check if we got a view, unless its a 0-sized or 0-d array. + # (then its not a view, and that does not matter) + if indexed_arr.size != 0 and indexed_arr.ndim != 0: + assert_(np.may_share_memory(indexed_arr, arr) == no_copy) + # Check reference count of the original array + if HAS_REFCOUNT: + if no_copy: + # refcount increases by one: + assert_equal(sys.getrefcount(arr), startcount + 1) + else: + assert_equal(sys.getrefcount(arr), startcount) + + # Test non-broadcast setitem: + b = arr.copy() + b[index] = mimic_get + 1000 + if b.size == 0: + return # nothing to compare here... + if no_copy and indexed_arr.ndim != 0: + # change indexed_arr in-place to manipulate original: + indexed_arr += 1000 + assert_array_equal(arr, b) + return + # Use the fact that the array is originally an arange: + arr.flat[indexed_arr.ravel()] += 1000 + assert_array_equal(arr, b) + + def test_boolean(self): + a = np.array(5) + assert_equal(a[np.array(True)], 5) + a[np.array(True)] = 1 + assert_equal(a, 1) + # NOTE: This is different from normal broadcasting, as + # arr[boolean_array] works like in a multi index. Which means + # it is aligned to the left. This is probably correct for + # consistency with arr[boolean_array,] also no broadcasting + # is done at all + a = self._create_array() + self._check_multi_index( + a, (np.zeros_like(a, dtype=bool),)) + self._check_multi_index( + a, (np.zeros_like(a, dtype=bool)[..., 0],)) + self._check_multi_index( + a, (np.zeros_like(a, dtype=bool)[None, ...],)) + + def test_multidim(self): + # Automatically test combinations with complex indexes on 2nd (or 1st) + # spot and the simple ones in one other spot. + a = self._create_array() + b = np.empty((3, 0, 5, 6)) + complex_indices = self._create_complex_indices() + simple_indices = [Ellipsis, None, -1, [1], np.array([True]), 'skip'] + fill_indices = [slice(None, None), 0] + + with warnings.catch_warnings(): + # This is so that np.array(True) is not accepted in a full integer + # index, when running the file separately. + warnings.filterwarnings('error', '', DeprecationWarning) + warnings.filterwarnings('error', '', VisibleDeprecationWarning) + + def isskip(idx): + return isinstance(idx, str) and idx == "skip" + + for simple_pos in [0, 2, 3]: + tocheck = [fill_indices, complex_indices, + fill_indices, fill_indices] + tocheck[simple_pos] = simple_indices + for index in product(*tocheck): + index = tuple(i for i in index if not isskip(i)) + self._check_multi_index(a, index) + self._check_multi_index(b, index) + + # Check very simple item getting: + self._check_multi_index(a, (0, 0, 0, 0)) + self._check_multi_index(b, (0, 0, 0, 0)) + # Also check (simple cases of) too many indices: + assert_raises(IndexError, a.__getitem__, (0, 0, 0, 0, 0)) + assert_raises(IndexError, a.__setitem__, (0, 0, 0, 0, 0), 0) + assert_raises(IndexError, a.__getitem__, (0, 0, [1], 0, 0)) + assert_raises(IndexError, a.__setitem__, (0, 0, [1], 0, 0), 0) + + def test_1d(self): + a = np.arange(10) + complex_indices = self._create_complex_indices() + for index in complex_indices: + self._check_single_index(a, index) + + +class TestFloatNonIntegerArgument: + """ + These test that ``TypeError`` is raised when you try to use + non-integers as arguments to for indexing and slicing e.g. ``a[0.0:5]`` + and ``a[0.5]``, or other functions like ``array.reshape(1., -1)``. + + """ + def test_valid_indexing(self): + # These should raise no errors. + a = np.array([[[5]]]) + + a[np.array([0])] + a[[0, 0]] + a[:, [0, 0]] + a[:, 0, :] + a[:, :, :] + + def test_valid_slicing(self): + # These should raise no errors. + a = np.array([[[5]]]) + + a[::] + a[0:] + a[:2] + a[0:2] + a[::2] + a[1::2] + a[:2:2] + a[1:2:2] + + def test_non_integer_argument_errors(self): + a = np.array([[5]]) + + assert_raises(TypeError, np.reshape, a, (1., 1., -1)) + assert_raises(TypeError, np.reshape, a, (np.array(1.), -1)) + assert_raises(TypeError, np.take, a, [0], 1.) + assert_raises(TypeError, np.take, a, [0], np.float64(1.)) + + def test_non_integer_sequence_multiplication(self): + # NumPy scalar sequence multiply should not work with non-integers + def mult(a, b): + return a * b + + assert_raises(TypeError, mult, [1], np.float64(3)) + # following should be OK + mult([1], np.int_(3)) + + def test_reduce_axis_float_index(self): + d = np.zeros((3, 3, 3)) + assert_raises(TypeError, np.min, d, 0.5) + assert_raises(TypeError, np.min, d, (0.5, 1)) + assert_raises(TypeError, np.min, d, (1, 2.2)) + assert_raises(TypeError, np.min, d, (.2, 1.2)) + + +class TestBooleanIndexing: + # Using a boolean as integer argument/indexing is an error. + def test_bool_as_int_argument_errors(self): + a = np.array([[[1]]]) + + assert_raises(TypeError, np.reshape, a, (True, -1)) + assert_raises(TypeError, np.reshape, a, (np.bool(True), -1)) + # Note that operator.index(np.array(True)) does not work, a boolean + # array is thus also deprecated, but not with the same message: + assert_raises(TypeError, operator.index, np.array(True)) + assert_raises(TypeError, operator.index, np.True_) + assert_raises(TypeError, np.take, args=(a, [0], False)) + + def test_boolean_indexing_weirdness(self): + # Weird boolean indexing things + a = np.ones((2, 3, 4)) + assert a[False, True, ...].shape == (0, 2, 3, 4) + assert a[True, [0, 1], True, True, [1], [[2]]].shape == (1, 2) + assert_raises(IndexError, lambda: a[False, [0, 1], ...]) + + def test_boolean_indexing_fast_path(self): + # These used to either give the wrong error, or incorrectly give no + # error. + a = np.ones((3, 3)) + + # This used to incorrectly work (and give an array of shape (0,)) + idx1 = np.array([[False] * 9]) + assert_raises_regex(IndexError, + "boolean index did not match indexed array along axis 0; " + "size of axis is 3 but size of corresponding boolean axis is 1", + lambda: a[idx1]) + + # This used to incorrectly give a ValueError: operands could not be + # broadcast together + idx2 = np.array([[False] * 8 + [True]]) + assert_raises_regex(IndexError, + "boolean index did not match indexed array along axis 0; " + "size of axis is 3 but size of corresponding boolean axis is 1", + lambda: a[idx2]) + + # This is the same as it used to be. The above two should work like this. + idx3 = np.array([[False] * 10]) + assert_raises_regex(IndexError, + "boolean index did not match indexed array along axis 0; " + "size of axis is 3 but size of corresponding boolean axis is 1", + lambda: a[idx3]) + + # This used to give ValueError: non-broadcastable operand + a = np.ones((1, 1, 2)) + idx = np.array([[[True], [False]]]) + assert_raises_regex(IndexError, + "boolean index did not match indexed array along axis 1; " + "size of axis is 1 but size of corresponding boolean axis is 2", + lambda: a[idx]) + + +class TestArrayToIndexDeprecation: + """Creating an index from array not 0-D is an error. + + """ + def test_array_to_index_error(self): + # so no exception is expected. The raising is effectively tested above. + a = np.array([[[1]]]) + + assert_raises(TypeError, operator.index, np.array([1])) + assert_raises(TypeError, np.reshape, a, (a, -1)) + assert_raises(TypeError, np.take, a, [0], a) + + +class TestNonIntegerArrayLike: + """Tests that array_likes only valid if can safely cast to integer. + + For instance, lists give IndexError when they cannot be safely cast to + an integer. + + """ + def test_basic(self): + a = np.arange(10) + + assert_raises(IndexError, a.__getitem__, [0.5, 1.5]) + assert_raises(IndexError, a.__getitem__, (['1', '2'],)) + + # The following is valid + a.__getitem__([]) + + +class TestMultipleEllipsisError: + """An index can only have a single ellipsis. + + """ + def test_basic(self): + a = np.arange(10) + assert_raises(IndexError, lambda: a[..., ...]) + assert_raises(IndexError, a.__getitem__, ((Ellipsis,) * 2,)) + assert_raises(IndexError, a.__getitem__, ((Ellipsis,) * 3,)) + + +class TestCApiAccess: + def test_getitem(self): + subscript = functools.partial(array_indexing, 0) + + # 0-d arrays don't work: + assert_raises(IndexError, subscript, np.ones(()), 0) + # Out of bound values: + assert_raises(IndexError, subscript, np.ones(10), 11) + assert_raises(IndexError, subscript, np.ones(10), -11) + assert_raises(IndexError, subscript, np.ones((10, 10)), 11) + assert_raises(IndexError, subscript, np.ones((10, 10)), -11) + + a = np.arange(10) + assert_array_equal(a[4], subscript(a, 4)) + a = a.reshape(5, 2) + assert_array_equal(a[-4], subscript(a, -4)) + + def test_setitem(self): + assign = functools.partial(array_indexing, 1) + + # Deletion is impossible: + assert_raises(ValueError, assign, np.ones(10), 0) + # 0-d arrays don't work: + assert_raises(IndexError, assign, np.ones(()), 0, 0) + # Out of bound values: + assert_raises(IndexError, assign, np.ones(10), 11, 0) + assert_raises(IndexError, assign, np.ones(10), -11, 0) + assert_raises(IndexError, assign, np.ones((10, 10)), 11, 0) + assert_raises(IndexError, assign, np.ones((10, 10)), -11, 0) + + a = np.arange(10) + assign(a, 4, 10) + assert_(a[4] == 10) + + a = a.reshape(5, 2) + assign(a, 4, 10) + assert_array_equal(a[-1], [10, 10]) + + +class TestFlatiterIndexing: + def test_flatiter_indexing_single_integer(self): + a = np.arange(9).reshape((3, 3)) + assert_array_equal(a.flat[0], 0) + assert_array_equal(a.flat[4], 4) + assert_array_equal(a.flat[-1], 8) + + with pytest.raises(IndexError, match="index 9 is out of bounds"): + a.flat[9] + + def test_flatiter_indexing_slice(self): + a = np.arange(9).reshape((3, 3)) + assert_array_equal(a.flat[:], np.arange(9)) + assert_array_equal(a.flat[:5], np.arange(5)) + assert_array_equal(a.flat[5:10], np.arange(5, 9)) + assert_array_equal(a.flat[::2], np.arange(0, 9, 2)) + assert_array_equal(a.flat[::-1], np.arange(8, -1, -1)) + assert_array_equal(a.flat[10:5], np.array([])) + + assert_array_equal(a.flat[()], np.arange(9)) + assert_array_equal(a.flat[...], np.arange(9)) + + def test_flatiter_indexing_boolean(self): + a = np.arange(9).reshape((3, 3)) + + with pytest.warns(DeprecationWarning, match="0-dimensional boolean index"): + assert_array_equal(a.flat[True], 0) + with pytest.warns(DeprecationWarning, match="0-dimensional boolean index"): + assert_array_equal(a.flat[False], np.array([])) + + mask = np.zeros(len(a.flat), dtype=bool) + mask[::2] = True + assert_array_equal(a.flat[mask], np.arange(0, 9, 2)) + + wrong_mask = np.zeros(len(a.flat) + 1, dtype=bool) + with pytest.raises(IndexError, + match="boolean index did not match indexed flat iterator"): + a.flat[wrong_mask] + + def test_flatiter_indexing_fancy(self): + a = np.arange(9).reshape((3, 3)) + + indices = np.array([1, 3, 5]) + assert_array_equal(a.flat[indices], indices) + + assert_array_equal(a.flat[[-1, -2]], np.array([8, 7])) + + indices_2d = np.array([[1, 2], [3, 4]]) + assert_array_equal(a.flat[indices_2d], indices_2d) + + assert_array_equal(a.flat[[True, 1]], np.array([1, 1])) + + assert_array_equal(a.flat[[]], np.array([], dtype=a.dtype)) + + with pytest.raises(IndexError, + match="boolean indices for iterators are not supported"): + a.flat[[True, True]] + + a = np.arange(3) + with pytest.raises(IndexError, + match="boolean indices for iterators are not supported"): + a.flat[[True, False, True]] + assert_array_equal(a.flat[np.asarray([True, False, True])], np.array([0, 2])) + + def test_flatiter_indexing_not_supported_newaxis_mutlidimensional_float(self): + a = np.arange(9).reshape((3, 3)) + with pytest.raises(IndexError, + match=r"only integers, slices \(`:`\), " + r"ellipsis \(`\.\.\.`\) and " + r"integer or boolean arrays are valid indices"): + a.flat[None] + + with pytest.raises(IndexError, + match=r"too many indices for flat iterator: flat iterator " + r"is 1-dimensional, but 2 were indexed"): + a.flat[1, 2] + + with pytest.warns(DeprecationWarning, + match="Invalid non-array indices for iterator objects are " + "deprecated"): + assert_array_equal(a.flat[[1.0, 2.0]], np.array([1, 2])) + + def test_flatiter_assign_single_integer(self): + a = np.arange(9).reshape((3, 3)) + + a.flat[0] = 10 + assert_array_equal(a, np.array([[10, 1, 2], [3, 4, 5], [6, 7, 8]])) + + a.flat[4] = 20 + assert_array_equal(a, np.array([[10, 1, 2], [3, 20, 5], [6, 7, 8]])) + + a.flat[-1] = 30 + assert_array_equal(a, np.array([[10, 1, 2], [3, 20, 5], [6, 7, 30]])) + + with pytest.raises(IndexError, match="index 9 is out of bounds"): + a.flat[9] = 40 + + def test_flatiter_indexing_slice_assign(self): + a = np.arange(9).reshape((3, 3)) + a.flat[:] = 10 + assert_array_equal(a, np.full((3, 3), 10)) + + a = np.arange(9).reshape((3, 3)) + a.flat[:5] = 20 + assert_array_equal(a, np.array([[20, 20, 20], [20, 20, 5], [6, 7, 8]])) + + a = np.arange(9).reshape((3, 3)) + a.flat[5:10] = 30 + assert_array_equal(a, np.array([[0, 1, 2], [3, 4, 30], [30, 30, 30]])) + + a = np.arange(9).reshape((3, 3)) + a.flat[::2] = 40 + assert_array_equal(a, np.array([[40, 1, 40], [3, 40, 5], [40, 7, 40]])) + + a = np.arange(9).reshape((3, 3)) + a.flat[::-1] = 50 + assert_array_equal(a, np.full((3, 3), 50)) + + a = np.arange(9).reshape((3, 3)) + a.flat[10:5] = 60 + assert_array_equal(a, np.arange(9).reshape((3, 3))) + + a = np.arange(9).reshape((3, 3)) + with pytest.raises(IndexError, + match="Assigning to a flat iterator with a 0-D index"): + a.flat[()] = 70 + + a = np.arange(9).reshape((3, 3)) + a.flat[...] = 80 + assert_array_equal(a, np.full((3, 3), 80)) + + def test_flatiter_indexing_boolean_assign(self): + a = np.arange(9).reshape((3, 3)) + with pytest.warns(DeprecationWarning, match="0-dimensional boolean index"): + a.flat[True] = 10 + assert_array_equal(a, np.array([[10, 1, 2], [3, 4, 5], [6, 7, 8]])) + + a = np.arange(9).reshape((3, 3)) + with pytest.warns(DeprecationWarning, match="0-dimensional boolean index"): + a.flat[False] = 20 + assert_array_equal(a, np.arange(9).reshape((3, 3))) + + a = np.arange(9).reshape((3, 3)) + mask = np.zeros(len(a.flat), dtype=bool) + mask[::2] = True + a.flat[mask] = 30 + assert_array_equal(a, np.array([[30, 1, 30], [3, 30, 5], [30, 7, 30]])) + + wrong_mask = np.zeros(len(a.flat) + 1, dtype=bool) + with pytest.raises(IndexError, + match="boolean index did not match indexed flat iterator"): + a.flat[wrong_mask] = 40 + + def test_flatiter_indexing_fancy_assign(self): + a = np.arange(9).reshape((3, 3)) + indices = np.array([1, 3, 5]) + a.flat[indices] = 10 + assert_array_equal(a, np.array([[0, 10, 2], [10, 4, 10], [6, 7, 8]])) + + a.flat[[-1, -2]] = 20 + assert_array_equal(a, np.array([[0, 10, 2], [10, 4, 10], [6, 20, 20]])) + + a = np.arange(9).reshape((3, 3)) + indices_2d = np.array([[1, 2], [3, 4]]) + a.flat[indices_2d] = 30 + assert_array_equal(a, np.array([[0, 30, 30], [30, 30, 5], [6, 7, 8]])) + + a.flat[[True, 1]] = 40 + assert_array_equal(a, np.array([[0, 40, 30], [30, 30, 5], [6, 7, 8]])) + + with pytest.raises(IndexError, + match="boolean indices for iterators are not supported"): + a.flat[[True, True]] = 50 + + a = np.arange(3) + with pytest.raises(IndexError, + match="boolean indices for iterators are not supported"): + a.flat[[True, False, True]] = 20 + a.flat[np.asarray([True, False, True])] = 20 + assert_array_equal(a, np.array([20, 1, 20])) + + def test_flatiter_indexing_fancy_int16_dtype(self): + a = np.arange(9).reshape((3, 3)) + indices = np.array([1, 3, 5], dtype=np.int16) + assert_array_equal(a.flat[indices], np.array([1, 3, 5])) + + a.flat[indices] = 10 + assert_array_equal(a, np.array([[0, 10, 2], [10, 4, 10], [6, 7, 8]])) + + def test_flatiter_indexing_not_supported_newaxis_mutlid_float_assign(self): + a = np.arange(9).reshape((3, 3)) + with pytest.raises(IndexError, + match=r"only integers, slices \(`:`\), " + r"ellipsis \(`\.\.\.`\) and " + r"integer or boolean arrays are valid indices"): + a.flat[None] = 10 + + a.flat[[1, 2]] = 10 + assert_array_equal(a, np.array([[0, 10, 10], [3, 4, 5], [6, 7, 8]])) + + with pytest.warns(DeprecationWarning, + match="Invalid non-array indices for iterator objects are " + "deprecated"): + a.flat[[1.0, 2.0]] = 20 + assert_array_equal(a, np.array([[0, 20, 20], [3, 4, 5], [6, 7, 8]])) + + def test_flat_index_on_flatiter(self): + a = np.arange(9).reshape((3, 3)) + b = np.array([0, 5, 6]) + assert_equal(a.flat[b.flat], np.array([0, 5, 6])) + + def test_empty_string_flat_index_on_flatiter(self): + a = np.arange(9).reshape((3, 3)) + b = np.array([], dtype="S") + # This is arguably incorrect, and should be removed (ideally with + # deprecation). But it matches the array path and comes from not + # distinguishing `arr[np.array([]).flat]` and `arr[[]]` and the latter + # must pass. + assert_equal(a.flat[b.flat], np.array([])) + + def test_nonempty_string_flat_index_on_flatiter(self): + a = np.arange(9).reshape((3, 3)) + b = np.array(["a"], dtype="S") + with pytest.raises(IndexError, + match=r"only integers, slices \(`:`\), ellipsis \(`\.\.\.`\) " + r"and integer or boolean arrays are valid indices"): + a.flat[b.flat] + + +@pytest.mark.skipif(sys.flags.optimize == 2, reason="Python running -OO") +@pytest.mark.xfail(IS_PYPY, reason="PyPy does not modify tp_doc") +@pytest.mark.parametrize("methodname", ["__array__", "copy"]) +def test_flatiter_method_signatures(methodname: str): + method = getattr(np.flatiter, methodname) + assert callable(method) + + try: + sig = inspect.signature(method) + except ValueError as e: + pytest.fail(f"Could not get signature for np.flatiter.{methodname}: {e}") + + assert "self" in sig.parameters + assert sig.parameters["self"].kind is inspect.Parameter.POSITIONAL_ONLY diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_item_selection.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_item_selection.py new file mode 100644 index 0000000000000000000000000000000000000000..79fb82dde591aa45e6b2b140ad57534e47778c43 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_item_selection.py @@ -0,0 +1,167 @@ +import sys + +import pytest + +import numpy as np +from numpy.testing import HAS_REFCOUNT, assert_, assert_array_equal, assert_raises + + +class TestTake: + def test_simple(self): + a = [[1, 2], [3, 4]] + a_str = [[b'1', b'2'], [b'3', b'4']] + modes = ['raise', 'wrap', 'clip'] + indices = [-1, 4] + index_arrays = [np.empty(0, dtype=np.intp), + np.empty((), dtype=np.intp), + np.empty((1, 1), dtype=np.intp)] + real_indices = {'raise': {-1: 1, 4: IndexError}, + 'wrap': {-1: 1, 4: 0}, + 'clip': {-1: 0, 4: 1}} + # Currently all types but object, use the same function generation. + # So it should not be necessary to test all. However test also a non + # refcounted struct on top of object, which has a size that hits the + # default (non-specialized) path. + types = int, object, np.dtype([('', 'i2', 3)]) + for t in types: + # ta works, even if the array may be odd if buffer interface is used + ta = np.array(a if np.issubdtype(t, np.number) else a_str, dtype=t) + tresult = list(ta.T.copy()) + for index_array in index_arrays: + if index_array.size != 0: + tresult[0].shape = (2,) + index_array.shape + tresult[1].shape = (2,) + index_array.shape + for mode in modes: + for index in indices: + real_index = real_indices[mode][index] + if real_index is IndexError and index_array.size != 0: + index_array.put(0, index) + assert_raises(IndexError, ta.take, index_array, + mode=mode, axis=1) + elif index_array.size != 0: + index_array.put(0, index) + res = ta.take(index_array, mode=mode, axis=1) + assert_array_equal(res, tresult[real_index]) + else: + res = ta.take(index_array, mode=mode, axis=1) + assert_(res.shape == (2,) + index_array.shape) + + def test_refcounting(self): + objects = [object() for i in range(10)] + if HAS_REFCOUNT: + orig_rcs = [sys.getrefcount(o) for o in objects] + for mode in ('raise', 'clip', 'wrap'): + a = np.array(objects) + b = np.array([2, 2, 4, 5, 3, 5]) + a.take(b, out=a[:6], mode=mode) + del a + if HAS_REFCOUNT: + assert_(all(sys.getrefcount(o) == rc + 1 + for o, rc in zip(objects, orig_rcs))) + # not contiguous, example: + a = np.array(objects * 2)[::2] + a.take(b, out=a[:6], mode=mode) + del a + if HAS_REFCOUNT: + assert_(all(sys.getrefcount(o) == rc + 1 + for o, rc in zip(objects, orig_rcs))) + + def test_unicode_mode(self): + d = np.arange(10) + k = b'\xc3\xa4'.decode("UTF8") + assert_raises(ValueError, d.take, 5, mode=k) + + def test_empty_partition(self): + # In reference to github issue #6530 + a_original = np.array([0, 2, 4, 6, 8, 10]) + a = a_original.copy() + + # An empty partition should be a successful no-op + a.partition(np.array([], dtype=np.int16)) + + assert_array_equal(a, a_original) + + def test_empty_argpartition(self): + # In reference to github issue #6530 + a = np.array([0, 2, 4, 6, 8, 10]) + a = a.argpartition(np.array([], dtype=np.int16)) + + b = np.array([0, 1, 2, 3, 4, 5]) + assert_array_equal(a, b) + + +class TestPutMask: + @pytest.mark.parametrize("dtype", list(np.typecodes["All"]) + ["i,O"]) + def test_simple(self, dtype): + if dtype.lower() == "m": + dtype += "8[ns]" + + # putmask is weird and doesn't care about value length (even shorter) + vals = np.arange(1001).astype(dtype=dtype) + + mask = np.random.randint(2, size=1000).astype(bool) + # Use vals.dtype in case of flexible dtype (i.e. string) + arr = np.zeros(1000, dtype=vals.dtype) + zeros = arr.copy() + + np.putmask(arr, mask, vals) + assert_array_equal(arr[mask], vals[:len(mask)][mask]) + assert_array_equal(arr[~mask], zeros[~mask]) + + @pytest.mark.parametrize("dtype", list(np.typecodes["All"])[1:] + ["i,O"]) + @pytest.mark.parametrize("mode", ["raise", "wrap", "clip"]) + def test_empty(self, dtype, mode): + arr = np.zeros(1000, dtype=dtype) + arr_copy = arr.copy() + mask = np.random.randint(2, size=1000).astype(bool) + + # Allowing empty values like this is weird... + np.put(arr, mask, []) + assert_array_equal(arr, arr_copy) + + +class TestPut: + @pytest.mark.parametrize("dtype", list(np.typecodes["All"])[1:] + ["i,O"]) + @pytest.mark.parametrize("mode", ["raise", "wrap", "clip"]) + def test_simple(self, dtype, mode): + if dtype.lower() == "m": + dtype += "8[ns]" + + # put is weird and doesn't care about value length (even shorter) + vals = np.arange(1001).astype(dtype=dtype) + + # Use vals.dtype in case of flexible dtype (i.e. string) + arr = np.zeros(1000, dtype=vals.dtype) + zeros = arr.copy() + + if mode == "clip": + # Special because 0 and -1 value are "reserved" for clip test + indx = np.random.permutation(len(arr) - 2)[:-500] + 1 + + indx[-1] = 0 + indx[-2] = len(arr) - 1 + indx_put = indx.copy() + indx_put[-1] = -1389 + indx_put[-2] = 1321 + else: + # Avoid duplicates (for simplicity) and fill half only + indx = np.random.permutation(len(arr) - 3)[:-500] + indx_put = indx + if mode == "wrap": + indx_put = indx_put + len(arr) + + np.put(arr, indx_put, vals, mode=mode) + assert_array_equal(arr[indx], vals[:len(indx)]) + untouched = np.ones(len(arr), dtype=bool) + untouched[indx] = False + assert_array_equal(arr[untouched], zeros[:untouched.sum()]) + + @pytest.mark.parametrize("dtype", list(np.typecodes["All"])[1:] + ["i,O"]) + @pytest.mark.parametrize("mode", ["raise", "wrap", "clip"]) + def test_empty(self, dtype, mode): + arr = np.zeros(1000, dtype=dtype) + arr_copy = arr.copy() + + # Allowing empty values like this is weird... + np.put(arr, [1, 2, 3], []) + assert_array_equal(arr, arr_copy) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_limited_api.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_limited_api.py new file mode 100644 index 0000000000000000000000000000000000000000..984210e53af70f5b653c55b30cd32201598b9f77 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_limited_api.py @@ -0,0 +1,102 @@ +import os +import subprocess +import sys +import sysconfig + +import pytest + +from numpy.testing import IS_EDITABLE, IS_PYPY, IS_WASM, NOGIL_BUILD + +# This import is copied from random.tests.test_extending +try: + import cython + from Cython.Compiler.Version import version as cython_version +except ImportError: + cython = None +else: + from numpy._utils import _pep440 + + # Note: keep in sync with the one in pyproject.toml + required_version = "3.0.6" + if _pep440.parse(cython_version) < _pep440.Version(required_version): + # too old or wrong cython, skip the test + cython = None + +pytestmark = pytest.mark.skipif(cython is None, reason="requires cython") + + +if IS_EDITABLE: + pytest.skip( + "Editable install doesn't support tests with a compile step", + allow_module_level=True + ) + + +@pytest.fixture(scope='module') +def install_temp(tmpdir_factory): + # Based in part on test_cython from random.tests.test_extending + if IS_WASM: + pytest.skip("No subprocess") + + srcdir = os.path.join(os.path.dirname(__file__), 'examples', 'limited_api') + build_dir = tmpdir_factory.mktemp("limited_api") / "build" + os.makedirs(build_dir, exist_ok=True) + # Ensure we use the correct Python interpreter even when `meson` is + # installed in a different Python environment (see gh-24956) + native_file = str(build_dir / 'interpreter-native-file.ini') + with open(native_file, 'w') as f: + f.write("[binaries]\n") + f.write(f"python = '{sys.executable}'\n") + f.write(f"python3 = '{sys.executable}'") + + try: + subprocess.check_call(["meson", "--version"]) + except FileNotFoundError: + pytest.skip("No usable 'meson' found") + if sysconfig.get_platform() == "win-arm64": + pytest.skip("Meson unable to find MSVC linker on win-arm64") + if sys.platform == "win32": + subprocess.check_call(["meson", "setup", + "--werror", + "--buildtype=release", + "--vsenv", "--native-file", native_file, + str(srcdir)], + cwd=build_dir, + ) + else: + subprocess.check_call(["meson", "setup", "--werror", + "--native-file", native_file, str(srcdir)], + cwd=build_dir + ) + try: + subprocess.check_call( + ["meson", "compile", "-vv"], cwd=build_dir) + except subprocess.CalledProcessError as p: + print(f"{p.stdout=}") + print(f"{p.stderr=}") + raise + + sys.path.append(str(build_dir)) + + +@pytest.mark.skipif(IS_WASM, reason="Can't start subprocess") +@pytest.mark.xfail( + sysconfig.get_config_var("Py_DEBUG"), + reason=( + "Py_LIMITED_API is incompatible with Py_DEBUG, Py_TRACE_REFS, " + "and Py_REF_DEBUG" + ), +) +@pytest.mark.xfail( + NOGIL_BUILD, + reason="Py_GIL_DISABLED builds do not currently support the limited API", +) +@pytest.mark.skipif(IS_PYPY, reason="no support for limited API in PyPy") +def test_limited_api(install_temp): + """Test building a third-party C extension with the limited API + and building a cython extension with the limited API + """ + + import limited_api1 # Earliest (3.6) # noqa: F401 + import limited_api2 # cython # noqa: F401 + import limited_api_latest # Latest version (current Python) # noqa: F401 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_longdouble.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_longdouble.py new file mode 100644 index 0000000000000000000000000000000000000000..a7aa9145711a0de564220ac58ebbff7b53892dbb --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_longdouble.py @@ -0,0 +1,370 @@ +import platform +import warnings + +import pytest + +import numpy as np +from numpy._core.tests._locales import CommaDecimalPointLocale +from numpy.testing import ( + IS_MUSL, + assert_, + assert_array_equal, + assert_equal, + assert_raises, + temppath, +) + +LD_INFO = np.finfo(np.longdouble) +longdouble_longer_than_double = (LD_INFO.eps < np.finfo(np.double).eps) + + +_o = 1 + LD_INFO.eps +string_to_longdouble_inaccurate = (_o != np.longdouble(str(_o))) +del _o + + +def test_scalar_extraction(): + """Confirm that extracting a value doesn't convert to python float""" + o = 1 + LD_INFO.eps + a = np.array([o, o, o]) + assert_equal(a[1], o) + + +# Conversions string -> long double + +# 0.1 not exactly representable in base 2 floating point. +repr_precision = len(repr(np.longdouble(0.1))) +# +2 from macro block starting around line 842 in scalartypes.c.src. + + +@pytest.mark.skipif(IS_MUSL, + reason="test flaky on musllinux") +@pytest.mark.skipif(LD_INFO.precision + 2 >= repr_precision, + reason="repr precision not enough to show eps") +def test_str_roundtrip(): + # We will only see eps in repr if within printing precision. + o = 1 + LD_INFO.eps + assert_equal(np.longdouble(str(o)), o, f"str was {str(o)}") + + +@pytest.mark.skipif(string_to_longdouble_inaccurate, reason="Need strtold_l") +def test_str_roundtrip_bytes(): + o = 1 + LD_INFO.eps + assert_equal(np.longdouble(str(o).encode("ascii")), o) + + +@pytest.mark.skipif(string_to_longdouble_inaccurate, reason="Need strtold_l") +@pytest.mark.parametrize("strtype", (np.str_, np.bytes_, str, bytes)) +def test_array_and_stringlike_roundtrip(strtype): + """ + Test that string representations of long-double roundtrip both + for array casting and scalar coercion, see also gh-15608. + """ + o = 1 + LD_INFO.eps + + if strtype in (np.bytes_, bytes): + o_str = strtype(str(o).encode("ascii")) + else: + o_str = strtype(str(o)) + + # Test that `o` is correctly coerced from the string-like + assert o == np.longdouble(o_str) + + # Test that arrays also roundtrip correctly: + o_strarr = np.asarray([o] * 3, dtype=strtype) + assert (o == o_strarr.astype(np.longdouble)).all() + + # And array coercion and casting to string give the same as scalar repr: + assert (o_strarr == o_str).all() + assert (np.asarray([o] * 3).astype(strtype) == o_str).all() + + +def test_bogus_string(): + assert_raises(ValueError, np.longdouble, "spam") + assert_raises(ValueError, np.longdouble, "1.0 flub") + + +@pytest.mark.skipif(string_to_longdouble_inaccurate, reason="Need strtold_l") +def test_fromstring(): + o = 1 + LD_INFO.eps + s = (" " + str(o)) * 5 + a = np.array([o] * 5) + assert_equal(np.fromstring(s, sep=" ", dtype=np.longdouble), a, + err_msg=f"reading '{s}'") + + +def test_fromstring_complex(): + for ctype in ["complex", "cdouble"]: + # Check spacing between separator + assert_equal(np.fromstring("1, 2 , 3 ,4", sep=",", dtype=ctype), + np.array([1., 2., 3., 4.])) + # Real component not specified + assert_equal(np.fromstring("1j, -2j, 3j, 4e1j", sep=",", dtype=ctype), + np.array([1.j, -2.j, 3.j, 40.j])) + # Both components specified + assert_equal(np.fromstring("1+1j,2-2j, -3+3j, -4e1+4j", sep=",", dtype=ctype), + np.array([1. + 1.j, 2. - 2.j, - 3. + 3.j, - 40. + 4j])) + # Spaces at wrong places + with assert_raises(ValueError): + np.fromstring("1+2 j,3", dtype=ctype, sep=",") + with assert_raises(ValueError): + np.fromstring("1+ 2j,3", dtype=ctype, sep=",") + with assert_raises(ValueError): + np.fromstring("1 +2j,3", dtype=ctype, sep=",") + with assert_raises(ValueError): + np.fromstring("1+j", dtype=ctype, sep=",") + with assert_raises(ValueError): + np.fromstring("1+", dtype=ctype, sep=",") + with assert_raises(ValueError): + np.fromstring("1j+1", dtype=ctype, sep=",") + + +def test_fromstring_bogus(): + with assert_raises(ValueError): + np.fromstring("1. 2. 3. flop 4.", dtype=float, sep=" ") + + +def test_fromstring_empty(): + with assert_raises(ValueError): + np.fromstring("xxxxx", sep="x") + + +def test_fromstring_missing(): + with assert_raises(ValueError): + np.fromstring("1xx3x4x5x6", sep="x") + + +class TestFileBased: + + ldbl = 1 + LD_INFO.eps + tgt = np.array([ldbl] * 5) + out = ''.join([str(t) + '\n' for t in tgt]) + + def test_fromfile_bogus(self): + with temppath() as path: + with open(path, 'w') as f: + f.write("1. 2. 3. flop 4.\n") + + with assert_raises(ValueError): + np.fromfile(path, dtype=float, sep=" ") + + def test_fromfile_complex(self): + for ctype in ["complex", "cdouble"]: + # Check spacing between separator and only real component specified + with temppath() as path: + with open(path, 'w') as f: + f.write("1, 2 , 3 ,4\n") + + res = np.fromfile(path, dtype=ctype, sep=",") + assert_equal(res, np.array([1., 2., 3., 4.])) + + # Real component not specified + with temppath() as path: + with open(path, 'w') as f: + f.write("1j, -2j, 3j, 4e1j\n") + + res = np.fromfile(path, dtype=ctype, sep=",") + assert_equal(res, np.array([1.j, -2.j, 3.j, 40.j])) + + # Both components specified + with temppath() as path: + with open(path, 'w') as f: + f.write("1+1j,2-2j, -3+3j, -4e1+4j\n") + + res = np.fromfile(path, dtype=ctype, sep=",") + assert_equal(res, np.array([1. + 1.j, 2. - 2.j, - 3. + 3.j, - 40. + 4j])) + + # Spaces at wrong places + with temppath() as path: + with open(path, 'w') as f: + f.write("1+2 j,3\n") + + with assert_raises(ValueError): + np.fromfile(path, dtype=ctype, sep=",") + + # Spaces at wrong places + with temppath() as path: + with open(path, 'w') as f: + f.write("1+ 2j,3\n") + + with assert_raises(ValueError): + np.fromfile(path, dtype=ctype, sep=",") + + # Spaces at wrong places + with temppath() as path: + with open(path, 'w') as f: + f.write("1 +2j,3\n") + + with assert_raises(ValueError): + np.fromfile(path, dtype=ctype, sep=",") + + # Wrong sep + with temppath() as path: + with open(path, 'w') as f: + f.write("1+j\n") + + with assert_raises(ValueError): + np.fromfile(path, dtype=ctype, sep=",") + + # Wrong sep + with temppath() as path: + with open(path, 'w') as f: + f.write("1+\n") + + with assert_raises(ValueError): + np.fromfile(path, dtype=ctype, sep=",") + + # Wrong sep + with temppath() as path: + with open(path, 'w') as f: + f.write("1j+1\n") + + with assert_raises(ValueError): + np.fromfile(path, dtype=ctype, sep=",") + + @pytest.mark.skipif(string_to_longdouble_inaccurate, + reason="Need strtold_l") + def test_fromfile(self): + with temppath() as path: + with open(path, 'w') as f: + f.write(self.out) + res = np.fromfile(path, dtype=np.longdouble, sep="\n") + assert_equal(res, self.tgt) + + @pytest.mark.skipif(string_to_longdouble_inaccurate, + reason="Need strtold_l") + def test_genfromtxt(self): + with temppath() as path: + with open(path, 'w') as f: + f.write(self.out) + res = np.genfromtxt(path, dtype=np.longdouble) + assert_equal(res, self.tgt) + + @pytest.mark.skipif(string_to_longdouble_inaccurate, + reason="Need strtold_l") + def test_loadtxt(self): + with temppath() as path: + with open(path, 'w') as f: + f.write(self.out) + res = np.loadtxt(path, dtype=np.longdouble) + assert_equal(res, self.tgt) + + @pytest.mark.skipif(string_to_longdouble_inaccurate, + reason="Need strtold_l") + def test_tofile_roundtrip(self): + with temppath() as path: + self.tgt.tofile(path, sep=" ") + res = np.fromfile(path, dtype=np.longdouble, sep=" ") + assert_equal(res, self.tgt) + + +# Conversions long double -> string + + +def test_str_exact(): + o = 1 + LD_INFO.eps + assert_(str(o) != '1') + + +@pytest.mark.skipif(longdouble_longer_than_double, reason="BUG #2376") +@pytest.mark.skipif(string_to_longdouble_inaccurate, + reason="Need strtold_l") +def test_format(): + assert_(f"{1 + LD_INFO.eps:.40g}" != '1') + + +@pytest.mark.skipif(longdouble_longer_than_double, reason="BUG #2376") +@pytest.mark.skipif(string_to_longdouble_inaccurate, + reason="Need strtold_l") +def test_percent(): + o = 1 + LD_INFO.eps + assert_(f"{o:.40g}" != '1') + + +@pytest.mark.skipif(longdouble_longer_than_double, + reason="array repr problem") +@pytest.mark.skipif(string_to_longdouble_inaccurate, + reason="Need strtold_l") +def test_array_repr(): + o = 1 + LD_INFO.eps + a = np.array([o]) + b = np.array([1], dtype=np.longdouble) + if not np.all(a != b): + raise ValueError("precision loss creating arrays") + with np.printoptions(precision=LD_INFO.precision + 1): + assert_(repr(a) != repr(b)) + +# +# Locale tests: scalar types formatting should be independent of the locale +# + +class TestCommaDecimalPointLocale(CommaDecimalPointLocale): + + def test_str_roundtrip_foreign(self): + o = 1.5 + assert_equal(o, np.longdouble(str(o))) + + def test_fromstring_foreign_repr(self): + f = 1.234 + a = np.fromstring(repr(f), dtype=float, sep=" ") + assert_equal(a[0], f) + + def test_fromstring_foreign(self): + s = "1.234" + a = np.fromstring(s, dtype=np.longdouble, sep=" ") + assert_equal(a[0], np.longdouble(s)) + + def test_fromstring_foreign_sep(self): + a = np.array([1, 2, 3, 4]) + b = np.fromstring("1,2,3,4,", dtype=np.longdouble, sep=",") + assert_array_equal(a, b) + + def test_fromstring_foreign_value(self): + with assert_raises(ValueError): + np.fromstring("1,234", dtype=np.longdouble, sep=" ") + + +@pytest.mark.parametrize("int_val", [ + # cases discussed in gh-10723 + # and gh-9968 + 2 ** 1024, 0]) +def test_longdouble_from_int(int_val): + # for issue gh-9968 + str_val = str(int_val) + # we'll expect a RuntimeWarning on platforms + # with np.longdouble equivalent to np.double + # for large integer input + with warnings.catch_warnings(record=True) as w: + warnings.filterwarnings('always', '', RuntimeWarning) + # can be inf==inf on some platforms + assert np.longdouble(int_val) == np.longdouble(str_val) + # we can't directly compare the int and + # max longdouble value on all platforms + if np.allclose(np.finfo(np.longdouble).max, + np.finfo(np.double).max) and w: + assert w[0].category is RuntimeWarning + +@pytest.mark.parametrize("bool_val", [ + True, False]) +def test_longdouble_from_bool(bool_val): + assert np.longdouble(bool_val) == np.longdouble(int(bool_val)) + + +@pytest.mark.skipif( + not (IS_MUSL and platform.machine() == "x86_64"), + reason="only need to run on musllinux_x86_64" +) +def test_musllinux_x86_64_signature(): + # this test may fail if you're emulating musllinux_x86_64 on a different + # architecture, but should pass natively. + known_sigs = [b'\xcd\xcc\xcc\xcc\xcc\xcc\xcc\xcc\xfb\xbf'] + sig = (np.longdouble(-1.0) / np.longdouble(10.0)) + sig = sig.view(sig.dtype.newbyteorder('<')).tobytes()[:10] + assert sig in known_sigs + + +def test_eps_positive(): + # np.finfo('g').eps should be positive on all platforms. If this isn't true + # then something may have gone wrong with the MachArLike, e.g. if + # np._core.getlimits._discovered_machar didn't work properly + assert np.finfo(np.longdouble).eps > 0. diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_mem_overlap.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_mem_overlap.py new file mode 100644 index 0000000000000000000000000000000000000000..240ea62850ee7b90f2502215613f3d869e821ea3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_mem_overlap.py @@ -0,0 +1,933 @@ +import itertools + +import pytest + +import numpy as np +from numpy._core import _umath_tests +from numpy._core._multiarray_tests import internal_overlap, solve_diophantine +from numpy.lib.stride_tricks import as_strided +from numpy.testing import assert_, assert_array_equal, assert_equal, assert_raises + +ndims = 2 +size = 10 +shape = tuple([size] * ndims) + +MAY_SHARE_BOUNDS = 0 +MAY_SHARE_EXACT = -1 + + +def _indices_for_nelems(nelems): + """Returns slices of length nelems, from start onwards, in direction sign.""" + + if nelems == 0: + return [size // 2] # int index + + res = [] + for step in (1, 2): + for sign in (-1, 1): + start = size // 2 - nelems * step * sign // 2 + stop = start + nelems * step * sign + res.append(slice(start, stop, step * sign)) + + return res + + +def _indices_for_axis(): + """Returns (src, dst) pairs of indices.""" + + res = [] + for nelems in (0, 2, 3): + ind = _indices_for_nelems(nelems) + res.extend(itertools.product(ind, ind)) # all assignments of size "nelems" + + return res + + +def _indices(ndims): + """Returns ((axis0_src, axis0_dst), (axis1_src, axis1_dst), ... ) index pairs.""" + + ind = _indices_for_axis() + return itertools.product(ind, repeat=ndims) + + +def _check_assignment(srcidx, dstidx): + """Check assignment arr[dstidx] = arr[srcidx] works.""" + + arr = np.arange(np.prod(shape)).reshape(shape) + + cpy = arr.copy() + + cpy[dstidx] = arr[srcidx] + arr[dstidx] = arr[srcidx] + + assert_(np.all(arr == cpy), + f'assigning arr[{dstidx}] = arr[{srcidx}]') + + +def test_overlapping_assignments(): + # Test automatically generated assignments which overlap in memory. + + inds = _indices(ndims) + + for ind in inds: + srcidx = tuple(a[0] for a in ind) + dstidx = tuple(a[1] for a in ind) + + _check_assignment(srcidx, dstidx) + + +@pytest.mark.slow +def test_diophantine_fuzz(): + # Fuzz test the diophantine solver + rng = np.random.RandomState(1234) + + max_int = np.iinfo(np.intp).max + + for ndim in range(10): + feasible_count = 0 + infeasible_count = 0 + + min_count = 500 // (ndim + 1) + + while min(feasible_count, infeasible_count) < min_count: + # Ensure big and small integer problems + A_max = 1 + rng.randint(0, 11, dtype=np.intp)**6 + U_max = rng.randint(0, 11, dtype=np.intp)**6 + + A_max = min(max_int, A_max) + U_max = min(max_int - 1, U_max) + + A = tuple(int(rng.randint(1, A_max + 1, dtype=np.intp)) + for j in range(ndim)) + U = tuple(int(rng.randint(0, U_max + 2, dtype=np.intp)) + for j in range(ndim)) + + b_ub = min(max_int - 2, sum(a * ub for a, ub in zip(A, U))) + b = int(rng.randint(-1, b_ub + 2, dtype=np.intp)) + + if ndim == 0 and feasible_count < min_count: + b = 0 + + X = solve_diophantine(A, U, b) + + if X is None: + # Check the simplified decision problem agrees + X_simplified = solve_diophantine(A, U, b, simplify=1) + assert_(X_simplified is None, (A, U, b, X_simplified)) + + # Check no solution exists (provided the problem is + # small enough so that brute force checking doesn't + # take too long) + ranges = tuple(range(0, a * ub + 1, a) for a, ub in zip(A, U)) + + size = 1 + for r in ranges: + size *= len(r) + if size < 100000: + assert_(not any(sum(w) == b for w in itertools.product(*ranges))) + infeasible_count += 1 + else: + # Check the simplified decision problem agrees + X_simplified = solve_diophantine(A, U, b, simplify=1) + assert_(X_simplified is not None, (A, U, b, X_simplified)) + + # Check validity + assert_(sum(a * x for a, x in zip(A, X)) == b) + assert_(all(0 <= x <= ub for x, ub in zip(X, U))) + feasible_count += 1 + + +def test_diophantine_overflow(): + # Smoke test integer overflow detection + max_intp = np.iinfo(np.intp).max + max_int64 = np.iinfo(np.int64).max + + if max_int64 <= max_intp: + # Check that the algorithm works internally in 128-bit; + # solving this problem requires large intermediate numbers + A = (max_int64 // 2, max_int64 // 2 - 10) + U = (max_int64 // 2, max_int64 // 2 - 10) + b = 2 * (max_int64 // 2) - 10 + + assert_equal(solve_diophantine(A, U, b), (1, 1)) + + +def check_may_share_memory_exact(a, b): + got = np.may_share_memory(a, b, max_work=MAY_SHARE_EXACT) + + assert_equal(np.may_share_memory(a, b), + np.may_share_memory(a, b, max_work=MAY_SHARE_BOUNDS)) + + a.fill(0) + b.fill(0) + a.fill(1) + exact = b.any() + + err_msg = "" + if got != exact: + base_delta = a.__array_interface__['data'][0] - b.__array_interface__['data'][0] + err_msg = " " + "\n ".join([ + f"base_a - base_b = {base_delta!r}", + f"shape_a = {a.shape!r}", + f"shape_b = {b.shape!r}", + f"strides_a = {a.strides!r}", + f"strides_b = {b.strides!r}", + f"size_a = {a.size!r}", + f"size_b = {b.size!r}" + ]) + + assert_equal(got, exact, err_msg=err_msg) + + +def test_may_share_memory_manual(): + # Manual test cases for may_share_memory + + # Base arrays + xs0 = [ + np.zeros([13, 21, 23, 22], dtype=np.int8), + np.zeros([13, 21, 23 * 2, 22], dtype=np.int8)[:, :, ::2, :] + ] + + # Generate all negative stride combinations + xs = [] + for x in xs0: + for ss in itertools.product(*(([slice(None), slice(None, None, -1)],) * 4)): + xp = x[ss] + xs.append(xp) + + for x in xs: + # The default is a simple extent check + assert_(np.may_share_memory(x[:, 0, :], x[:, 1, :])) + assert_(np.may_share_memory(x[:, 0, :], x[:, 1, :], max_work=None)) + + # Exact checks + check_may_share_memory_exact(x[:, 0, :], x[:, 1, :]) + check_may_share_memory_exact(x[:, ::7], x[:, 3::3]) + + try: + xp = x.ravel() + if xp.flags.owndata: + continue + xp = xp.view(np.int16) + except ValueError: + continue + + # 0-size arrays cannot overlap + check_may_share_memory_exact(x.ravel()[6:6], + xp.reshape(13, 21, 23, 11)[:, ::7]) + + # Test itemsize is dealt with + check_may_share_memory_exact(x[:, ::7], + xp.reshape(13, 21, 23, 11)) + check_may_share_memory_exact(x[:, ::7], + xp.reshape(13, 21, 23, 11)[:, 3::3]) + check_may_share_memory_exact(x.ravel()[6:7], + xp.reshape(13, 21, 23, 11)[:, ::7]) + + # Check unit size + x = np.zeros([1], dtype=np.int8) + check_may_share_memory_exact(x, x) + check_may_share_memory_exact(x, x.copy()) + + +def iter_random_view_pairs(x, same_steps=True, equal_size=False): + rng = np.random.RandomState(1234) + + if equal_size and same_steps: + raise ValueError + + def random_slice(n, step): + start = rng.randint(0, n + 1, dtype=np.intp) + stop = rng.randint(start, n + 1, dtype=np.intp) + if rng.randint(0, 2, dtype=np.intp) == 0: + stop, start = start, stop + step *= -1 + return slice(start, stop, step) + + def random_slice_fixed_size(n, step, size): + start = rng.randint(0, n + 1 - size * step) + stop = start + (size - 1) * step + 1 + if rng.randint(0, 2) == 0: + stop, start = start - 1, stop - 1 + if stop < 0: + stop = None + step *= -1 + return slice(start, stop, step) + + # First a few regular views + yield x, x + for j in range(1, 7, 3): + yield x[j:], x[:-j] + yield x[..., j:], x[..., :-j] + + # An array with zero stride internal overlap + strides = list(x.strides) + strides[0] = 0 + xp = as_strided(x, shape=x.shape, strides=strides) + yield x, xp + yield xp, xp + + # An array with non-zero stride internal overlap + strides = list(x.strides) + if strides[0] > 1: + strides[0] = 1 + xp = as_strided(x, shape=x.shape, strides=strides) + yield x, xp + yield xp, xp + + # Then discontiguous views + while True: + steps = tuple(rng.randint(1, 11, dtype=np.intp) + if rng.randint(0, 5, dtype=np.intp) == 0 else 1 + for j in range(x.ndim)) + s1 = tuple(random_slice(p, s) for p, s in zip(x.shape, steps)) + + t1 = np.arange(x.ndim) + rng.shuffle(t1) + + if equal_size: + t2 = t1 + else: + t2 = np.arange(x.ndim) + rng.shuffle(t2) + + a = x[s1] + + if equal_size: + if a.size == 0: + continue + + steps2 = tuple(rng.randint(1, max(2, p // (1 + pa))) + if rng.randint(0, 5) == 0 else 1 + for p, s, pa in zip(x.shape, s1, a.shape)) + s2 = tuple(random_slice_fixed_size(p, s, pa) + for p, s, pa in zip(x.shape, steps2, a.shape)) + elif same_steps: + steps2 = steps + else: + steps2 = tuple(rng.randint(1, 11, dtype=np.intp) + if rng.randint(0, 5, dtype=np.intp) == 0 else 1 + for j in range(x.ndim)) + + if not equal_size: + s2 = tuple(random_slice(p, s) for p, s in zip(x.shape, steps2)) + + a = a.transpose(t1) + b = x[s2].transpose(t2) + + yield a, b + + +def check_may_share_memory_easy_fuzz(get_max_work, same_steps, min_count): + # Check that overlap problems with common strides are solved with + # little work. + x = np.zeros([17, 34, 71, 97], dtype=np.int16) + + feasible = 0 + infeasible = 0 + + pair_iter = iter_random_view_pairs(x, same_steps) + + while min(feasible, infeasible) < min_count: + a, b = next(pair_iter) + + bounds_overlap = np.may_share_memory(a, b) + may_share_answer = np.may_share_memory(a, b) + easy_answer = np.may_share_memory(a, b, max_work=get_max_work(a, b)) + exact_answer = np.may_share_memory(a, b, max_work=MAY_SHARE_EXACT) + + if easy_answer != exact_answer: + # assert_equal is slow... + assert_equal(easy_answer, exact_answer) + + if may_share_answer != bounds_overlap: + assert_equal(may_share_answer, bounds_overlap) + + if bounds_overlap: + if exact_answer: + feasible += 1 + else: + infeasible += 1 + + +@pytest.mark.slow +def test_may_share_memory_easy_fuzz(): + # Check that overlap problems with common strides are always + # solved with little work. + + check_may_share_memory_easy_fuzz(get_max_work=lambda a, b: 1, + same_steps=True, + min_count=2000) + + +@pytest.mark.slow +def test_may_share_memory_harder_fuzz(): + # Overlap problems with not necessarily common strides take more + # work. + # + # The work bound below can't be reduced much. Harder problems can + # also exist but not be detected here, as the set of problems + # comes from RNG. + + check_may_share_memory_easy_fuzz(get_max_work=lambda a, b: max(a.size, b.size) // 2, + same_steps=False, + min_count=2000) + + +def test_shares_memory_api(): + x = np.zeros([4, 5, 6], dtype=np.int8) + + assert_equal(np.shares_memory(x, x), True) + assert_equal(np.shares_memory(x, x.copy()), False) + + a = x[:, ::2, ::3] + b = x[:, ::3, ::2] + assert_equal(np.shares_memory(a, b), True) + assert_equal(np.shares_memory(a, b, max_work=None), True) + assert_raises( + np.exceptions.TooHardError, np.shares_memory, a, b, max_work=1 + ) + + +def test_may_share_memory_bad_max_work(): + x = np.zeros([1]) + assert_raises(OverflowError, np.may_share_memory, x, x, max_work=10**100) + assert_raises(OverflowError, np.shares_memory, x, x, max_work=10**100) + + +def test_internal_overlap_diophantine(): + def check(A, U, exists=None): + X = solve_diophantine(A, U, 0, require_ub_nontrivial=1) + + if exists is None: + exists = (X is not None) + + if X is not None: + sum_ax = sum(a * x for a, x in zip(A, X)) + sum_au_half = sum(a * u // 2 for a, u in zip(A, U)) + assert_(sum_ax == sum_au_half) + assert_(all(0 <= x <= u for x, u in zip(X, U))) + assert_(any(x != u // 2 for x, u in zip(X, U))) + + if exists: + assert_(X is not None, repr(X)) + else: + assert_(X is None, repr(X)) + + # Smoke tests + check((3, 2), (2 * 2, 3 * 2), exists=True) + check((3 * 2, 2), (15 * 2, (3 - 1) * 2), exists=False) + + +def test_internal_overlap_slices(): + # Slicing an array never generates internal overlap + + x = np.zeros([17, 34, 71, 97], dtype=np.int16) + + rng = np.random.RandomState(1234) + + def random_slice(n, step): + start = rng.randint(0, n + 1, dtype=np.intp) + stop = rng.randint(start, n + 1, dtype=np.intp) + if rng.randint(0, 2, dtype=np.intp) == 0: + stop, start = start, stop + step *= -1 + return slice(start, stop, step) + + cases = 0 + min_count = 5000 + + while cases < min_count: + steps = tuple(rng.randint(1, 11, dtype=np.intp) + if rng.randint(0, 5, dtype=np.intp) == 0 else 1 + for j in range(x.ndim)) + t1 = np.arange(x.ndim) + rng.shuffle(t1) + s1 = tuple(random_slice(p, s) for p, s in zip(x.shape, steps)) + a = x[s1].transpose(t1) + + assert_(not internal_overlap(a)) + cases += 1 + + +def check_internal_overlap(a, manual_expected=None): + got = internal_overlap(a) + + # Brute-force check + m = set() + ranges = tuple(range(n) for n in a.shape) + for v in itertools.product(*ranges): + offset = sum(s * w for s, w in zip(a.strides, v)) + if offset in m: + expected = True + break + else: + m.add(offset) + else: + expected = False + + # Compare + if got != expected: + assert_equal(got, expected, err_msg=repr((a.strides, a.shape))) + if manual_expected is not None and expected != manual_expected: + assert_equal(expected, manual_expected) + return got + + +def test_internal_overlap_manual(): + # Stride tricks can construct arrays with internal overlap + + # We don't care about memory bounds, the array is not + # read/write accessed + x = np.arange(1).astype(np.int8) + + # Check low-dimensional special cases + + check_internal_overlap(x, False) # 1-dim + check_internal_overlap(x.reshape([]), False) # 0-dim + + a = as_strided(x, strides=(3, 4), shape=(4, 4)) + check_internal_overlap(a, False) + + a = as_strided(x, strides=(3, 4), shape=(5, 4)) + check_internal_overlap(a, True) + + a = as_strided(x, strides=(0,), shape=(0,)) + check_internal_overlap(a, False) + + a = as_strided(x, strides=(0,), shape=(1,)) + check_internal_overlap(a, False) + + a = as_strided(x, strides=(0,), shape=(2,)) + check_internal_overlap(a, True) + + a = as_strided(x, strides=(0, -9993), shape=(87, 22)) + check_internal_overlap(a, True) + + a = as_strided(x, strides=(0, -9993), shape=(1, 22)) + check_internal_overlap(a, False) + + a = as_strided(x, strides=(0, -9993), shape=(0, 22)) + check_internal_overlap(a, False) + + +def test_internal_overlap_fuzz(): + # Fuzz check; the brute-force check is fairly slow + + x = np.arange(1).astype(np.int8) + + overlap = 0 + no_overlap = 0 + min_count = 100 + + rng = np.random.RandomState(1234) + + while min(overlap, no_overlap) < min_count: + ndim = rng.randint(1, 4, dtype=np.intp) + + strides = tuple(rng.randint(-1000, 1000, dtype=np.intp) + for j in range(ndim)) + shape = tuple(rng.randint(1, 30, dtype=np.intp) + for j in range(ndim)) + + a = as_strided(x, strides=strides, shape=shape) + result = check_internal_overlap(a) + + if result: + overlap += 1 + else: + no_overlap += 1 + + +def test_non_ndarray_inputs(): + # Regression check for gh-5604 + + class MyArray: + def __init__(self, data): + self.data = data + + @property + def __array_interface__(self): + return self.data.__array_interface__ + + class MyArray2: + def __init__(self, data): + self.data = data + + def __array__(self, dtype=None, copy=None): + return self.data + + for cls in [MyArray, MyArray2]: + x = np.arange(5) + + assert_(np.may_share_memory(cls(x[::2]), x[1::2])) + assert_(not np.shares_memory(cls(x[::2]), x[1::2])) + + assert_(np.shares_memory(cls(x[1::3]), x[::2])) + assert_(np.may_share_memory(cls(x[1::3]), x[::2])) + + +def view_element_first_byte(x): + """Construct an array viewing the first byte of each element of `x`""" + from numpy.lib._stride_tricks_impl import DummyArray + interface = dict(x.__array_interface__) + interface['typestr'] = '|b1' + interface['descr'] = [('', '|b1')] + return np.asarray(DummyArray(interface, x)) + + +def assert_copy_equivalent(operation, args, out, **kwargs): + """ + Check that operation(*args, out=out) produces results + equivalent to out[...] = operation(*args, out=out.copy()) + """ + + kwargs['out'] = out + kwargs2 = dict(kwargs) + kwargs2['out'] = out.copy() + + out_orig = out.copy() + out[...] = operation(*args, **kwargs2) + expected = out.copy() + out[...] = out_orig + + got = operation(*args, **kwargs).copy() + + if (got != expected).any(): + assert_equal(got, expected) + + +class TestUFunc: + """ + Test ufunc call memory overlap handling + """ + + def check_unary_fuzz(self, operation, get_out_axis_size, dtype=np.int16, + count=5000): + shapes = [7, 13, 8, 21, 29, 32] + + rng = np.random.RandomState(1234) + + for ndim in range(1, 6): + x = rng.randint(0, 2**16, size=shapes[:ndim]).astype(dtype) + + it = iter_random_view_pairs(x, same_steps=False, equal_size=True) + + min_count = count // (ndim + 1)**2 + + overlapping = 0 + while overlapping < min_count: + a, b = next(it) + + a_orig = a.copy() + b_orig = b.copy() + + if get_out_axis_size is None: + assert_copy_equivalent(operation, [a], out=b) + + if np.shares_memory(a, b): + overlapping += 1 + else: + for axis in itertools.chain(range(ndim), [None]): + a[...] = a_orig + b[...] = b_orig + + # Determine size for reduction axis (None if scalar) + outsize, scalarize = get_out_axis_size(a, b, axis) + if outsize == 'skip': + continue + + # Slice b to get an output array of the correct size + sl = [slice(None)] * ndim + if axis is None: + if outsize is None: + sl = [slice(0, 1)] + [0] * (ndim - 1) + else: + sl = [slice(0, outsize)] + [0] * (ndim - 1) + elif outsize is None: + k = b.shape[axis] // 2 + if ndim == 1: + sl[axis] = slice(k, k + 1) + else: + sl[axis] = k + else: + assert b.shape[axis] >= outsize + sl[axis] = slice(0, outsize) + b_out = b[tuple(sl)] + + if scalarize: + b_out = b_out.reshape([]) + + if np.shares_memory(a, b_out): + overlapping += 1 + + # Check result + assert_copy_equivalent(operation, [a], out=b_out, axis=axis) + + @pytest.mark.slow + def test_unary_ufunc_call_fuzz(self): + self.check_unary_fuzz(np.invert, None, np.int16) + + @pytest.mark.slow + def test_unary_ufunc_call_complex_fuzz(self): + # Complex typically has a smaller alignment than itemsize + self.check_unary_fuzz(np.negative, None, np.complex128, count=500) + + def test_binary_ufunc_accumulate_fuzz(self): + def get_out_axis_size(a, b, axis): + if axis is None: + if a.ndim == 1: + return a.size, False + else: + return 'skip', False # accumulate doesn't support this + else: + return a.shape[axis], False + + self.check_unary_fuzz(np.add.accumulate, get_out_axis_size, + dtype=np.int16, count=500) + + def test_binary_ufunc_reduce_fuzz(self): + def get_out_axis_size(a, b, axis): + return None, (axis is None or a.ndim == 1) + + self.check_unary_fuzz(np.add.reduce, get_out_axis_size, + dtype=np.int16, count=500) + + def test_binary_ufunc_reduceat_fuzz(self): + def get_out_axis_size(a, b, axis): + if axis is None: + if a.ndim == 1: + return a.size, False + else: + return 'skip', False # reduceat doesn't support this + else: + return a.shape[axis], False + + def do_reduceat(a, out, axis): + if axis is None: + size = len(a) + step = size // len(out) + else: + size = a.shape[axis] + step = a.shape[axis] // out.shape[axis] + idx = np.arange(0, size, step) + return np.add.reduceat(a, idx, out=out, axis=axis) + + self.check_unary_fuzz(do_reduceat, get_out_axis_size, + dtype=np.int16, count=500) + + def test_binary_ufunc_reduceat_manual(self): + def check(ufunc, a, ind, out): + c1 = ufunc.reduceat(a.copy(), ind.copy(), out=out.copy()) + c2 = ufunc.reduceat(a, ind, out=out) + assert_array_equal(c1, c2) + + # Exactly same input/output arrays + a = np.arange(10000, dtype=np.int16) + check(np.add, a, a[::-1].copy(), a) + + # Overlap with index + a = np.arange(10000, dtype=np.int16) + check(np.add, a, a[::-1], a) + + @pytest.mark.slow + def test_unary_gufunc_fuzz(self): + shapes = [7, 13, 8, 21, 29, 32] + gufunc = _umath_tests.euclidean_pdist + + rng = np.random.RandomState(1234) + + for ndim in range(2, 6): + x = rng.rand(*shapes[:ndim]) + + it = iter_random_view_pairs(x, same_steps=False, equal_size=True) + + min_count = 500 // (ndim + 1)**2 + + overlapping = 0 + while overlapping < min_count: + a, b = next(it) + + if min(a.shape[-2:]) < 2 or min(b.shape[-2:]) < 2 or a.shape[-1] < 2: + continue + + # Ensure the shapes are so that euclidean_pdist is happy + if b.shape[-1] > b.shape[-2]: + b = b[..., 0, :] + else: + b = b[..., :, 0] + + n = a.shape[-2] + p = n * (n - 1) // 2 + if p <= b.shape[-1] and p > 0: + b = b[..., :p] + else: + n = max(2, int(np.sqrt(b.shape[-1])) // 2) + p = n * (n - 1) // 2 + a = a[..., :n, :] + b = b[..., :p] + + # Call + if np.shares_memory(a, b): + overlapping += 1 + + with np.errstate(over='ignore', invalid='ignore'): + assert_copy_equivalent(gufunc, [a], out=b) + + def test_ufunc_at_manual(self): + def check(ufunc, a, ind, b=None): + a0 = a.copy() + if b is None: + ufunc.at(a0, ind.copy()) + c1 = a0.copy() + ufunc.at(a, ind) + c2 = a.copy() + else: + ufunc.at(a0, ind.copy(), b.copy()) + c1 = a0.copy() + ufunc.at(a, ind, b) + c2 = a.copy() + assert_array_equal(c1, c2) + + # Overlap with index + a = np.arange(10000, dtype=np.int16) + check(np.invert, a[::-1], a) + + # Overlap with second data array + a = np.arange(100, dtype=np.int16) + ind = np.arange(0, 100, 2, dtype=np.int16) + check(np.add, a, ind, a[25:75]) + + def test_unary_ufunc_1d_manual(self): + # Exercise ufunc fast-paths (that avoid creation of an `np.nditer`) + + def check(a, b): + a_orig = a.copy() + b_orig = b.copy() + + b0 = b.copy() + c1 = ufunc(a, out=b0) + c2 = ufunc(a, out=b) + assert_array_equal(c1, c2) + + # Trigger "fancy ufunc loop" code path + mask = view_element_first_byte(b).view(np.bool) + + a[...] = a_orig + b[...] = b_orig + c1 = ufunc(a, out=b.copy(), where=mask.copy()).copy() + + a[...] = a_orig + b[...] = b_orig + c2 = ufunc(a, out=b, where=mask.copy()).copy() + + # Also, mask overlapping with output + a[...] = a_orig + b[...] = b_orig + c3 = ufunc(a, out=b, where=mask).copy() + + assert_array_equal(c1, c2) + assert_array_equal(c1, c3) + + dtypes = [np.int8, np.int16, np.int32, np.int64, np.float32, + np.float64, np.complex64, np.complex128] + dtypes = [np.dtype(x) for x in dtypes] + + for dtype in dtypes: + if np.issubdtype(dtype, np.integer): + ufunc = np.invert + else: + ufunc = np.reciprocal + + n = 1000 + k = 10 + indices = [ + np.index_exp[:n], + np.index_exp[k:k + n], + np.index_exp[n - 1::-1], + np.index_exp[k + n - 1:k - 1:-1], + np.index_exp[:2 * n:2], + np.index_exp[k:k + 2 * n:2], + np.index_exp[2 * n - 1::-2], + np.index_exp[k + 2 * n - 1:k - 1:-2], + ] + + for xi, yi in itertools.product(indices, indices): + v = np.arange(1, 1 + n * 2 + k, dtype=dtype) + x = v[xi] + y = v[yi] + + with np.errstate(all='ignore'): + check(x, y) + + # Scalar cases + check(x[:1], y) + check(x[-1:], y) + check(x[:1].reshape([]), y) + check(x[-1:].reshape([]), y) + + def test_unary_ufunc_where_same(self): + # Check behavior at wheremask overlap + ufunc = np.invert + + def check(a, out, mask): + c1 = ufunc(a, out=out.copy(), where=mask.copy()) + c2 = ufunc(a, out=out, where=mask) + assert_array_equal(c1, c2) + + # Check behavior with same input and output arrays + x = np.arange(100).astype(np.bool) + check(x, x, x) + check(x, x.copy(), x) + check(x, x, x.copy()) + + @pytest.mark.slow + def test_binary_ufunc_1d_manual(self): + ufunc = np.add + + def check(a, b, c): + c0 = c.copy() + c1 = ufunc(a, b, out=c0) + c2 = ufunc(a, b, out=c) + assert_array_equal(c1, c2) + + for dtype in [np.int8, np.int16, np.int32, np.int64, + np.float32, np.float64, np.complex64, np.complex128]: + # Check different data dependency orders + + n = 1000 + k = 10 + + indices = [] + for p in [1, 2]: + indices.extend([ + np.index_exp[:p * n:p], + np.index_exp[k:k + p * n:p], + np.index_exp[p * n - 1::-p], + np.index_exp[k + p * n - 1:k - 1:-p], + ]) + + for x, y, z in itertools.product(indices, indices, indices): + v = np.arange(6 * n).astype(dtype) + x = v[x] + y = v[y] + z = v[z] + + check(x, y, z) + + # Scalar cases + check(x[:1], y, z) + check(x[-1:], y, z) + check(x[:1].reshape([]), y, z) + check(x[-1:].reshape([]), y, z) + check(x, y[:1], z) + check(x, y[-1:], z) + check(x, y[:1].reshape([]), z) + check(x, y[-1:].reshape([]), z) + + def test_inplace_op_simple_manual(self): + rng = np.random.RandomState(1234) + x = rng.rand(200, 200) # bigger than bufsize + + x += x.T + assert_array_equal(x - x.T, 0) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_mem_policy.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_mem_policy.py new file mode 100644 index 0000000000000000000000000000000000000000..313d3efe779ab046c3f0c4c9668f9d2cbab5c507 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_mem_policy.py @@ -0,0 +1,453 @@ +import asyncio +import gc +import os +import sys +import sysconfig +import threading + +import pytest + +import numpy as np +from numpy._core.multiarray import get_handler_name +from numpy.testing import IS_EDITABLE, IS_WASM, extbuild + + +@pytest.fixture +def get_module(tmp_path): + """ Add a memory policy that returns a false pointer 64 bytes into the + actual allocation, and fill the prefix with some text. Then check at each + memory manipulation that the prefix exists, to make sure all alloc/realloc/ + free/calloc go via the functions here. + """ + if sys.platform.startswith('cygwin'): + pytest.skip('link fails on cygwin') + if IS_WASM: + pytest.skip("Can't build module inside Wasm") + if IS_EDITABLE: + pytest.skip("Can't build module for editable install") + + functions = [ + ("get_default_policy", "METH_NOARGS", """ + Py_INCREF(PyDataMem_DefaultHandler); + return PyDataMem_DefaultHandler; + """), + ("set_secret_data_policy", "METH_NOARGS", """ + PyObject *secret_data = + PyCapsule_New(&secret_data_handler, "mem_handler", NULL); + if (secret_data == NULL) { + return NULL; + } + PyObject *old = PyDataMem_SetHandler(secret_data); + Py_DECREF(secret_data); + return old; + """), + ("set_wrong_capsule_name_data_policy", "METH_NOARGS", """ + PyObject *wrong_name_capsule = + PyCapsule_New(&secret_data_handler, "not_mem_handler", NULL); + if (wrong_name_capsule == NULL) { + return NULL; + } + PyObject *old = PyDataMem_SetHandler(wrong_name_capsule); + Py_DECREF(wrong_name_capsule); + return old; + """), + ("set_old_policy", "METH_O", """ + PyObject *old; + if (args != NULL && PyCapsule_CheckExact(args)) { + old = PyDataMem_SetHandler(args); + } + else { + old = PyDataMem_SetHandler(NULL); + } + return old; + """), + ("get_array", "METH_NOARGS", """ + char *buf = (char *)malloc(20); + npy_intp dims[1]; + dims[0] = 20; + PyArray_Descr *descr = PyArray_DescrNewFromType(NPY_UINT8); + return PyArray_NewFromDescr(&PyArray_Type, descr, 1, dims, NULL, + buf, NPY_ARRAY_WRITEABLE, NULL); + """), + ("set_own", "METH_O", """ + if (!PyArray_Check(args)) { + PyErr_SetString(PyExc_ValueError, + "need an ndarray"); + return NULL; + } + PyArray_ENABLEFLAGS((PyArrayObject*)args, NPY_ARRAY_OWNDATA); + // Maybe try this too? + // PyArray_BASE(PyArrayObject *)args) = NULL; + Py_RETURN_NONE; + """), + ("get_array_with_base", "METH_NOARGS", """ + char *buf = (char *)malloc(20); + npy_intp dims[1]; + dims[0] = 20; + PyArray_Descr *descr = PyArray_DescrNewFromType(NPY_UINT8); + PyObject *arr = PyArray_NewFromDescr(&PyArray_Type, descr, 1, dims, + NULL, buf, + NPY_ARRAY_WRITEABLE, NULL); + if (arr == NULL) return NULL; + PyObject *obj = PyCapsule_New(buf, "buf capsule", + (PyCapsule_Destructor)&warn_on_free); + if (obj == NULL) { + Py_DECREF(arr); + return NULL; + } + if (PyArray_SetBaseObject((PyArrayObject *)arr, obj) < 0) { + Py_DECREF(arr); + Py_DECREF(obj); + return NULL; + } + return arr; + + """), + ] + prologue = ''' + #define NPY_TARGET_VERSION NPY_1_22_API_VERSION + #define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION + #include + /* + * This struct allows the dynamic configuration of the allocator funcs + * of the `secret_data_allocator`. It is provided here for + * demonstration purposes, as a valid `ctx` use-case scenario. + */ + typedef struct { + void *(*malloc)(size_t); + void *(*calloc)(size_t, size_t); + void *(*realloc)(void *, size_t); + void (*free)(void *); + } SecretDataAllocatorFuncs; + + NPY_NO_EXPORT void * + shift_alloc(void *ctx, size_t sz) { + SecretDataAllocatorFuncs *funcs = (SecretDataAllocatorFuncs *)ctx; + char *real = (char *)funcs->malloc(sz + 64); + if (real == NULL) { + return NULL; + } + snprintf(real, 64, "originally allocated %ld", (unsigned long)sz); + return (void *)(real + 64); + } + NPY_NO_EXPORT void * + shift_zero(void *ctx, size_t sz, size_t cnt) { + SecretDataAllocatorFuncs *funcs = (SecretDataAllocatorFuncs *)ctx; + char *real = (char *)funcs->calloc(sz + 64, cnt); + if (real == NULL) { + return NULL; + } + snprintf(real, 64, "originally allocated %ld via zero", + (unsigned long)sz); + return (void *)(real + 64); + } + NPY_NO_EXPORT void + shift_free(void *ctx, void * p, npy_uintp sz) { + SecretDataAllocatorFuncs *funcs = (SecretDataAllocatorFuncs *)ctx; + if (p == NULL) { + return ; + } + char *real = (char *)p - 64; + if (strncmp(real, "originally allocated", 20) != 0) { + fprintf(stdout, "uh-oh, unmatched shift_free, " + "no appropriate prefix\\n"); + /* Make C runtime crash by calling free on the wrong address */ + funcs->free((char *)p + 10); + /* funcs->free(real); */ + } + else { + npy_uintp i = (npy_uintp)atoi(real +20); + if (i != sz) { + fprintf(stderr, "uh-oh, unmatched shift_free" + "(ptr, %ld) but allocated %ld\\n", sz, i); + /* This happens in some places, only print */ + funcs->free(real); + } + else { + funcs->free(real); + } + } + } + NPY_NO_EXPORT void * + shift_realloc(void *ctx, void * p, npy_uintp sz) { + SecretDataAllocatorFuncs *funcs = (SecretDataAllocatorFuncs *)ctx; + if (p != NULL) { + char *real = (char *)p - 64; + if (strncmp(real, "originally allocated", 20) != 0) { + fprintf(stdout, "uh-oh, unmatched shift_realloc\\n"); + return realloc(p, sz); + } + return (void *)((char *)funcs->realloc(real, sz + 64) + 64); + } + else { + char *real = (char *)funcs->realloc(p, sz + 64); + if (real == NULL) { + return NULL; + } + snprintf(real, 64, "originally allocated " + "%ld via realloc", (unsigned long)sz); + return (void *)(real + 64); + } + } + /* As an example, we use the standard {m|c|re}alloc/free funcs. */ + static SecretDataAllocatorFuncs secret_data_handler_ctx = { + malloc, + calloc, + realloc, + free + }; + static PyDataMem_Handler secret_data_handler = { + "secret_data_allocator", + 1, + { + &secret_data_handler_ctx, /* ctx */ + shift_alloc, /* malloc */ + shift_zero, /* calloc */ + shift_realloc, /* realloc */ + shift_free /* free */ + } + }; + void warn_on_free(void *capsule) { + PyErr_WarnEx(PyExc_UserWarning, "in warn_on_free", 1); + void * obj = PyCapsule_GetPointer(capsule, + PyCapsule_GetName(capsule)); + free(obj); + }; + ''' + more_init = "import_array();" + try: + import mem_policy + return mem_policy + except ImportError: + pass + # if it does not exist, build and load it + if sysconfig.get_platform() == "win-arm64": + pytest.skip("Meson unable to find MSVC linker on win-arm64") + return extbuild.build_and_import_extension('mem_policy', + functions, + prologue=prologue, + include_dirs=[np.get_include()], + build_dir=tmp_path, + more_init=more_init) + + +def test_set_policy(get_module): + + get_handler_name = np._core.multiarray.get_handler_name + get_handler_version = np._core.multiarray.get_handler_version + orig_policy_name = get_handler_name() + + a = np.arange(10).reshape((2, 5)) # a doesn't own its own data + assert get_handler_name(a) is None + assert get_handler_version(a) is None + assert get_handler_name(a.base) == orig_policy_name + assert get_handler_version(a.base) == 1 + + orig_policy = get_module.set_secret_data_policy() + + b = np.arange(10).reshape((2, 5)) # b doesn't own its own data + assert get_handler_name(b) is None + assert get_handler_version(b) is None + assert get_handler_name(b.base) == 'secret_data_allocator' + assert get_handler_version(b.base) == 1 + + if orig_policy_name == 'default_allocator': + get_module.set_old_policy(None) # tests PyDataMem_SetHandler(NULL) + assert get_handler_name() == 'default_allocator' + else: + get_module.set_old_policy(orig_policy) + assert get_handler_name() == orig_policy_name + + with pytest.raises(ValueError, + match="Capsule must be named 'mem_handler'"): + get_module.set_wrong_capsule_name_data_policy() + + +def test_default_policy_singleton(get_module): + get_handler_name = np._core.multiarray.get_handler_name + + # set the policy to default + orig_policy = get_module.set_old_policy(None) + + assert get_handler_name() == 'default_allocator' + + # re-set the policy to default + def_policy_1 = get_module.set_old_policy(None) + + assert get_handler_name() == 'default_allocator' + + # set the policy to original + def_policy_2 = get_module.set_old_policy(orig_policy) + + # since default policy is a singleton, + # these should be the same object + assert def_policy_1 is def_policy_2 is get_module.get_default_policy() + + +def test_policy_propagation(get_module): + # The memory policy goes hand-in-hand with flags.owndata + + class MyArr(np.ndarray): + pass + + get_handler_name = np._core.multiarray.get_handler_name + orig_policy_name = get_handler_name() + a = np.arange(10).view(MyArr).reshape((2, 5)) + assert get_handler_name(a) is None + assert a.flags.owndata is False + + assert get_handler_name(a.base) is None + assert a.base.flags.owndata is False + + assert get_handler_name(a.base.base) == orig_policy_name + assert a.base.base.flags.owndata is True + + +async def concurrent_context1(get_module, orig_policy_name, event): + if orig_policy_name == 'default_allocator': + get_module.set_secret_data_policy() + assert get_handler_name() == 'secret_data_allocator' + else: + get_module.set_old_policy(None) + assert get_handler_name() == 'default_allocator' + event.set() + + +async def concurrent_context2(get_module, orig_policy_name, event): + await event.wait() + # the policy is not affected by changes in parallel contexts + assert get_handler_name() == orig_policy_name + # change policy in the child context + if orig_policy_name == 'default_allocator': + get_module.set_secret_data_policy() + assert get_handler_name() == 'secret_data_allocator' + else: + get_module.set_old_policy(None) + assert get_handler_name() == 'default_allocator' + + +async def async_test_context_locality(get_module): + orig_policy_name = np._core.multiarray.get_handler_name() + + event = asyncio.Event() + # the child contexts inherit the parent policy + concurrent_task1 = asyncio.create_task( + concurrent_context1(get_module, orig_policy_name, event)) + concurrent_task2 = asyncio.create_task( + concurrent_context2(get_module, orig_policy_name, event)) + await concurrent_task1 + await concurrent_task2 + + # the parent context is not affected by child policy changes + assert np._core.multiarray.get_handler_name() == orig_policy_name + + +def test_context_locality(get_module): + if (sys.implementation.name == 'pypy' + and sys.pypy_version_info[:3] < (7, 3, 6)): + pytest.skip('no context-locality support in PyPy < 7.3.6') + asyncio.run(async_test_context_locality(get_module)) + + +def concurrent_thread1(get_module, event): + get_module.set_secret_data_policy() + assert np._core.multiarray.get_handler_name() == 'secret_data_allocator' + event.set() + + +def concurrent_thread2(get_module, event): + event.wait() + # the policy is not affected by changes in parallel threads + assert np._core.multiarray.get_handler_name() == 'default_allocator' + # change policy in the child thread + get_module.set_secret_data_policy() + + +def test_thread_locality(get_module): + orig_policy_name = np._core.multiarray.get_handler_name() + + event = threading.Event() + # the child threads do not inherit the parent policy + concurrent_task1 = threading.Thread(target=concurrent_thread1, + args=(get_module, event)) + concurrent_task2 = threading.Thread(target=concurrent_thread2, + args=(get_module, event)) + concurrent_task1.start() + concurrent_task2.start() + concurrent_task1.join() + concurrent_task2.join() + + # the parent thread is not affected by child policy changes + assert np._core.multiarray.get_handler_name() == orig_policy_name + + +@pytest.mark.skip(reason="too slow, see gh-23975") +def test_new_policy(get_module): + a = np.arange(10) + orig_policy_name = np._core.multiarray.get_handler_name(a) + + orig_policy = get_module.set_secret_data_policy() + + b = np.arange(10) + assert np._core.multiarray.get_handler_name(b) == 'secret_data_allocator' + + # test array manipulation. This is slow + if orig_policy_name == 'default_allocator': + # when the np._core.test tests recurse into this test, the + # policy will be set so this "if" will be false, preventing + # infinite recursion + # + # if needed, debug this by + # - running tests with -- -s (to not capture stdout/stderr + # - setting verbose=2 + # - setting extra_argv=['-vv'] here + assert np._core.test('full', verbose=1, extra_argv=[]) + # also try the ma tests, the pickling test is quite tricky + assert np.ma.test('full', verbose=1, extra_argv=[]) + + get_module.set_old_policy(orig_policy) + + c = np.arange(10) + assert np._core.multiarray.get_handler_name(c) == orig_policy_name + + +@pytest.mark.xfail(sys.implementation.name == "pypy", + reason=("bad interaction between getenv and " + "os.environ inside pytest")) +@pytest.mark.parametrize("policy", ["0", "1", None]) +@pytest.mark.thread_unsafe(reason="modifies environment variables") +def test_switch_owner(get_module, policy): + a = get_module.get_array() + assert np._core.multiarray.get_handler_name(a) is None + get_module.set_own(a) + + if policy is None: + # See what we expect to be set based on the env variable + policy = os.getenv("NUMPY_WARN_IF_NO_MEM_POLICY", "0") == "1" + oldval = None + else: + policy = policy == "1" + oldval = np._core._multiarray_umath._set_numpy_warn_if_no_mem_policy( + policy) + try: + # The policy should be NULL, so we have to assume we can call + # "free". A warning is given if the policy == "1" + if policy: + with pytest.warns(RuntimeWarning) as w: + del a + gc.collect() + else: + del a + gc.collect() + + finally: + if oldval is not None: + np._core._multiarray_umath._set_numpy_warn_if_no_mem_policy(oldval) + + +def test_owner_is_base(get_module): + a = get_module.get_array_with_base() + with pytest.warns(UserWarning, match='warn_on_free'): + del a + gc.collect() + gc.collect() diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_memmap.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_memmap.py new file mode 100644 index 0000000000000000000000000000000000000000..8e2aa0a507b1cf9cf95b8aed3b30a3c81003803f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_memmap.py @@ -0,0 +1,248 @@ +import mmap +import os +import sys +import warnings +from pathlib import Path +from tempfile import NamedTemporaryFile, TemporaryFile + +import pytest + +from numpy import ( + add, + allclose, + arange, + asarray, + average, + isscalar, + memmap, + multiply, + ndarray, + prod, + subtract, + sum, +) +from numpy.testing import ( + IS_PYPY, + assert_, + assert_array_equal, + assert_equal, + break_cycles, +) + + +@pytest.mark.thread_unsafe(reason="setup & memmap is thread-unsafe (gh-29126)") +class TestMemmap: + def setup_method(self): + self.tmpfp = NamedTemporaryFile(prefix='mmap') + self.shape = (3, 4) + self.dtype = 'float32' + self.data = arange(12, dtype=self.dtype) + self.data.resize(self.shape) + + def teardown_method(self): + self.tmpfp.close() + self.data = None + if IS_PYPY: + break_cycles() + break_cycles() + + def test_roundtrip(self): + # Write data to file + fp = memmap(self.tmpfp, dtype=self.dtype, mode='w+', + shape=self.shape) + fp[:] = self.data[:] + del fp # Test __del__ machinery, which handles cleanup + + # Read data back from file + newfp = memmap(self.tmpfp, dtype=self.dtype, mode='r', + shape=self.shape) + assert_(allclose(self.data, newfp)) + assert_array_equal(self.data, newfp) + assert_equal(newfp.flags.writeable, False) + + def test_open_with_filename(self, tmp_path): + tmpname = tmp_path / 'mmap' + fp = memmap(tmpname, dtype=self.dtype, mode='w+', + shape=self.shape) + fp[:] = self.data[:] + del fp + + def test_unnamed_file(self): + with TemporaryFile() as f: + fp = memmap(f, dtype=self.dtype, shape=self.shape) + del fp + + def test_attributes(self): + offset = 1 + mode = "w+" + fp = memmap(self.tmpfp, dtype=self.dtype, mode=mode, + shape=self.shape, offset=offset) + assert_equal(offset, fp.offset) + assert_equal(mode, fp.mode) + del fp + + def test_filename(self, tmp_path): + tmpname = tmp_path / "mmap" + fp = memmap(tmpname, dtype=self.dtype, mode='w+', + shape=self.shape) + abspath = Path(os.path.abspath(tmpname)) + fp[:] = self.data[:] + assert_equal(abspath, fp.filename) + b = fp[:1] + assert_equal(abspath, b.filename) + del b + del fp + + def test_path(self, tmp_path): + tmpname = tmp_path / "mmap" + fp = memmap(Path(tmpname), dtype=self.dtype, mode='w+', + shape=self.shape) + # os.path.realpath does not resolve symlinks on Windows + # see: https://bugs.python.org/issue9949 + # use Path.resolve, just as memmap class does internally + abspath = str(Path(tmpname).resolve()) + fp[:] = self.data[:] + assert_equal(abspath, str(fp.filename.resolve())) + b = fp[:1] + assert_equal(abspath, str(b.filename.resolve())) + del b + del fp + + def test_filename_fileobj(self): + fp = memmap(self.tmpfp, dtype=self.dtype, mode="w+", + shape=self.shape) + assert_equal(fp.filename, self.tmpfp.name) + + @pytest.mark.skipif(sys.platform == 'gnu0', + reason="Known to fail on hurd") + def test_flush(self): + fp = memmap(self.tmpfp, dtype=self.dtype, mode='w+', + shape=self.shape) + fp[:] = self.data[:] + assert_equal(fp[0], self.data[0]) + fp.flush() + + def test_del(self): + # Make sure a view does not delete the underlying mmap + fp_base = memmap(self.tmpfp, dtype=self.dtype, mode='w+', + shape=self.shape) + fp_base[0] = 5 + fp_view = fp_base[0:1] + assert_equal(fp_view[0], 5) + del fp_view + # Should still be able to access and assign values after + # deleting the view + assert_equal(fp_base[0], 5) + fp_base[0] = 6 + assert_equal(fp_base[0], 6) + + def test_arithmetic_drops_references(self): + fp = memmap(self.tmpfp, dtype=self.dtype, mode='w+', + shape=self.shape) + tmp = (fp + 10) + if isinstance(tmp, memmap): + assert_(tmp._mmap is not fp._mmap) + + def test_indexing_drops_references(self): + fp = memmap(self.tmpfp, dtype=self.dtype, mode='w+', + shape=self.shape) + tmp = fp[(1, 2), (2, 3)] + if isinstance(tmp, memmap): + assert_(tmp._mmap is not fp._mmap) + + def test_slicing_keeps_references(self): + fp = memmap(self.tmpfp, dtype=self.dtype, mode='w+', + shape=self.shape) + assert_(fp[:2, :2]._mmap is fp._mmap) + + def test_view(self): + fp = memmap(self.tmpfp, dtype=self.dtype, shape=self.shape) + new1 = fp.view() + new2 = new1.view() + assert_(new1.base is fp) + assert_(new2.base is fp) + new_array = asarray(fp) + assert_(new_array.base is fp) + + def test_ufunc_return_ndarray(self): + fp = memmap(self.tmpfp, dtype=self.dtype, shape=self.shape) + fp[:] = self.data + + with warnings.catch_warnings(): + warnings.filterwarnings( + 'ignore', "np.average currently does not preserve", FutureWarning) + for unary_op in [sum, average, prod]: + result = unary_op(fp) + assert_(isscalar(result)) + assert_(result.__class__ is self.data[0, 0].__class__) + + assert_(unary_op(fp, axis=0).__class__ is ndarray) + assert_(unary_op(fp, axis=1).__class__ is ndarray) + + for binary_op in [add, subtract, multiply]: + assert_(binary_op(fp, self.data).__class__ is ndarray) + assert_(binary_op(self.data, fp).__class__ is ndarray) + assert_(binary_op(fp, fp).__class__ is ndarray) + + fp += 1 + assert fp.__class__ is memmap + add(fp, 1, out=fp) + assert fp.__class__ is memmap + + def test_getitem(self): + fp = memmap(self.tmpfp, dtype=self.dtype, shape=self.shape) + fp[:] = self.data + + assert_(fp[1:, :-1].__class__ is memmap) + # Fancy indexing returns a copy that is not memmapped + assert_(fp[[0, 1]].__class__ is ndarray) + + def test_memmap_subclass(self): + class MemmapSubClass(memmap): + pass + + fp = MemmapSubClass(self.tmpfp, dtype=self.dtype, shape=self.shape) + fp[:] = self.data + + # We keep previous behavior for subclasses of memmap, i.e. the + # ufunc and __getitem__ output is never turned into a ndarray + assert_(sum(fp, axis=0).__class__ is MemmapSubClass) + assert_(sum(fp).__class__ is MemmapSubClass) + assert_(fp[1:, :-1].__class__ is MemmapSubClass) + assert fp[[0, 1]].__class__ is MemmapSubClass + + def test_mmap_offset_greater_than_allocation_granularity(self): + size = 5 * mmap.ALLOCATIONGRANULARITY + offset = mmap.ALLOCATIONGRANULARITY + 1 + fp = memmap(self.tmpfp, shape=size, mode='w+', offset=offset) + assert_(fp.offset == offset) + + def test_empty_array_with_offset_multiple_of_allocation_granularity(self): + self.tmpfp.write(b'a' * mmap.ALLOCATIONGRANULARITY) + size = 0 + offset = mmap.ALLOCATIONGRANULARITY + fp = memmap(self.tmpfp, shape=size, mode='w+', offset=offset) + assert_equal(fp.offset, offset) + + def test_no_shape(self): + self.tmpfp.write(b'a' * 16) + mm = memmap(self.tmpfp, dtype='float64') + assert_equal(mm.shape, (2,)) + + def test_empty_array(self): + # gh-12653 + with pytest.raises(ValueError, match='empty file'): + memmap(self.tmpfp, shape=(0, 4), mode='r') + + # gh-27723 + # empty memmap works with mode in ('w+','r+') + memmap(self.tmpfp, shape=(0, 4), mode='w+') + + # ok now the file is not empty + memmap(self.tmpfp, shape=(0, 4), mode='w+') + + def test_shape_type(self): + memmap(self.tmpfp, shape=3, mode='w+') + memmap(self.tmpfp, shape=self.shape, mode='w+') + memmap(self.tmpfp, shape=list(self.shape), mode='w+') + memmap(self.tmpfp, shape=asarray(self.shape), mode='w+') diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_multiarray.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_multiarray.py new file mode 100644 index 0000000000000000000000000000000000000000..fe3bd7770080c094cc38f005f8efa758d1b2b65e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_multiarray.py @@ -0,0 +1,11031 @@ +import builtins +import collections.abc +import ctypes +import functools +import gc +import importlib +import inspect +import io +import itertools +import mmap +import operator +import os +import pathlib +import pickle +import re +import subprocess +import sys +import tempfile +import textwrap +import warnings +import weakref +from contextlib import contextmanager + +# Need to test an object that does not fully implement math interface +from datetime import datetime, timedelta +from decimal import Decimal + +import pytest + +import numpy as np +import numpy._core._multiarray_tests as _multiarray_tests +from numpy._core._rational_tests import rational +from numpy._core.multiarray import _get_ndarray_c_version, dot +from numpy._core.tests._locales import CommaDecimalPointLocale +from numpy.exceptions import AxisError, ComplexWarning +from numpy.lib import stride_tricks +from numpy.lib.recfunctions import repack_fields +from numpy.testing import ( + BLAS_SUPPORTS_FPE, + HAS_REFCOUNT, + IS_64BIT, + IS_PYPY, + IS_PYSTON, + IS_WASM, + assert_, + assert_allclose, + assert_almost_equal, + assert_array_almost_equal, + assert_array_compare, + assert_array_equal, + assert_array_less, + assert_equal, + assert_raises, + assert_raises_regex, + break_cycles, + check_support_sve, + runstring, + temppath, +) +from numpy.testing._private.utils import _no_tracing, requires_memory + + +def assert_arg_sorted(arr, arg): + # resulting array should be sorted and arg values should be unique + assert_equal(arr[arg], np.sort(arr)) + assert_equal(np.sort(arg), np.arange(len(arg))) + + +def assert_arr_partitioned(kth, k, arr_part): + assert_equal(arr_part[k], kth) + assert_array_compare(operator.__le__, arr_part[:k], kth) + assert_array_compare(operator.__ge__, arr_part[k:], kth) + + +def _aligned_zeros(shape, dtype=float, order="C", align=None): + """ + Allocate a new ndarray with aligned memory. + + The ndarray is guaranteed *not* aligned to twice the requested alignment. + Eg, if align=4, guarantees it is not aligned to 8. If align=None uses + dtype.alignment.""" + dtype = np.dtype(dtype) + if dtype == np.dtype(object): + # Can't do this, fall back to standard allocation (which + # should always be sufficiently aligned) + if align is not None: + raise ValueError("object array alignment not supported") + return np.zeros(shape, dtype=dtype, order=order) + if align is None: + align = dtype.alignment + if not hasattr(shape, '__len__'): + shape = (shape,) + size = functools.reduce(operator.mul, shape) * dtype.itemsize + buf = np.empty(size + 2 * align + 1, np.uint8) + + ptr = buf.__array_interface__['data'][0] + offset = ptr % align + if offset != 0: + offset = align - offset + if (ptr % (2 * align)) == 0: + offset += align + + # Note: slices producing 0-size arrays do not necessarily change + # data pointer --- so we use and allocate size+1 + buf = buf[offset:offset + size + 1][:-1] + buf.fill(0) + data = np.ndarray(shape, dtype, buf, order=order) + return data + + +class TestFlags: + def test_writeable(self): + arr = np.arange(10) + mydict = locals() + arr.flags.writeable = False + assert_raises(ValueError, runstring, 'arr[0] = 3', mydict) + arr.flags.writeable = True + arr[0] = 5 + arr[0] = 0 + + def test_writeable_any_base(self): + # Ensure that any base being writeable is sufficient to change flag; + # this is especially interesting for arrays from an array interface. + arr = np.arange(10) + + class subclass(np.ndarray): + pass + + # Create subclass so base will not be collapsed, this is OK to change + view1 = arr.view(subclass) + view2 = view1[...] + arr.flags.writeable = False + view2.flags.writeable = False + view2.flags.writeable = True # Can be set to True again. + + arr = np.arange(10) + + class frominterface: + def __init__(self, arr): + self.arr = arr + self.__array_interface__ = arr.__array_interface__ + + view1 = np.asarray(frominterface) + view2 = view1[...] + view2.flags.writeable = False + view2.flags.writeable = True + + view1.flags.writeable = False + view2.flags.writeable = False + with assert_raises(ValueError): + # Must assume not writeable, since only base is not: + view2.flags.writeable = True + + def test_writeable_from_readonly(self): + # gh-9440 - make sure fromstring, from buffer on readonly buffers + # set writeable False + data = b'\x00' * 100 + vals = np.frombuffer(data, 'B') + assert_raises(ValueError, vals.setflags, write=True) + types = np.dtype([('vals', 'u1'), ('res3', 'S4')]) + values = np._core.records.fromstring(data, types) + vals = values['vals'] + assert_raises(ValueError, vals.setflags, write=True) + + def test_writeable_from_buffer(self): + data = bytearray(b'\x00' * 100) + vals = np.frombuffer(data, 'B') + assert_(vals.flags.writeable) + vals.setflags(write=False) + assert_(vals.flags.writeable is False) + vals.setflags(write=True) + assert_(vals.flags.writeable) + types = np.dtype([('vals', 'u1'), ('res3', 'S4')]) + values = np._core.records.fromstring(data, types) + vals = values['vals'] + assert_(vals.flags.writeable) + vals.setflags(write=False) + assert_(vals.flags.writeable is False) + vals.setflags(write=True) + assert_(vals.flags.writeable) + + @pytest.mark.skipif(IS_PYPY, reason="PyPy always copies") + def test_writeable_pickle(self): + import pickle + # Small arrays will be copied without setting base. + # See condition for using PyArray_SetBaseObject in + # array_setstate. + a = np.arange(1000) + for v in range(pickle.HIGHEST_PROTOCOL): + vals = pickle.loads(pickle.dumps(a, v)) + assert_(vals.flags.writeable) + assert_(isinstance(vals.base, bytes)) + + def test_writeable_from_c_data(self): + # Test that the writeable flag can be changed for an array wrapping + # low level C-data, but not owning its data. + # Also see that this is deprecated to change from python. + from numpy._core._multiarray_tests import get_c_wrapping_array + + arr_writeable = get_c_wrapping_array(True) + assert not arr_writeable.flags.owndata + assert arr_writeable.flags.writeable + view = arr_writeable[...] + + # Toggling the writeable flag works on the view: + view.flags.writeable = False + assert not view.flags.writeable + view.flags.writeable = True + assert view.flags.writeable + # Flag can be unset on the arr_writeable: + arr_writeable.flags.writeable = False + + arr_readonly = get_c_wrapping_array(False) + assert not arr_readonly.flags.owndata + assert not arr_readonly.flags.writeable + + for arr in [arr_writeable, arr_readonly]: + view = arr[...] + view.flags.writeable = False # make sure it is readonly + arr.flags.writeable = False + assert not arr.flags.writeable + + with assert_raises(ValueError): + view.flags.writeable = True + + with assert_raises(ValueError): + arr.flags.writeable = True + + def test_warnonwrite(self): + a = np.arange(10) + a.flags._warn_on_write = True + with warnings.catch_warnings(record=True) as w: + warnings.filterwarnings('always') + a[1] = 10 + a[2] = 10 + # only warn once + assert_(len(w) == 1) + + @pytest.mark.parametrize(["flag", "flag_value", "writeable"], + [("writeable", True, True), + # Delete _warn_on_write after deprecation and simplify + # the parameterization: + ("_warn_on_write", True, False), + ("writeable", False, False)]) + def test_readonly_flag_protocols(self, flag, flag_value, writeable): + a = np.arange(10) + setattr(a.flags, flag, flag_value) + + class MyArr: + __array_struct__ = a.__array_struct__ + + assert memoryview(a).readonly is not writeable + assert a.__array_interface__['data'][1] is not writeable + assert np.asarray(MyArr()).flags.writeable is writeable + + def test_otherflags(self): + arr = np.arange(10) + assert_equal(arr.flags.carray, True) + assert_equal(arr.flags['C'], True) + assert_equal(arr.flags.farray, False) + assert_equal(arr.flags.behaved, True) + assert_equal(arr.flags.fnc, False) + assert_equal(arr.flags.forc, True) + assert_equal(arr.flags.owndata, True) + assert_equal(arr.flags.writeable, True) + assert_equal(arr.flags.aligned, True) + assert_equal(arr.flags.writebackifcopy, False) + assert_equal(arr.flags['X'], False) + assert_equal(arr.flags['WRITEBACKIFCOPY'], False) + + def test_string_align(self): + a = np.zeros(4, dtype=np.dtype('|S4')) + assert_(a.flags.aligned) + # not power of two are accessed byte-wise and thus considered aligned + a = np.zeros(5, dtype=np.dtype('|S4')) + assert_(a.flags.aligned) + + def test_void_align(self): + a = np.zeros(4, dtype=np.dtype([("a", "i4"), ("b", "i4")])) + assert_(a.flags.aligned) + + @pytest.mark.parametrize("row_size", [5, 1 << 16]) + @pytest.mark.parametrize("row_count", [1, 5]) + @pytest.mark.parametrize("ndmin", [0, 1, 2]) + def test_xcontiguous_load_txt(self, row_size, row_count, ndmin): + s = io.StringIO('\n'.join(['1.0 ' * row_size] * row_count)) + a = np.loadtxt(s, ndmin=ndmin) + + assert a.flags.c_contiguous + x = [i for i in a.shape if i != 1] + assert a.flags.f_contiguous == (len(x) <= 1) + + +class TestHash: + # see #3793 + def test_int(self): + for st, ut, s in [(np.int8, np.uint8, 8), + (np.int16, np.uint16, 16), + (np.int32, np.uint32, 32), + (np.int64, np.uint64, 64)]: + for i in range(1, s): + assert_equal(hash(st(-2**i)), hash(-2**i), + err_msg="%r: -2**%d" % (st, i)) + assert_equal(hash(st(2**(i - 1))), hash(2**(i - 1)), + err_msg="%r: 2**%d" % (st, i - 1)) + assert_equal(hash(st(2**i - 1)), hash(2**i - 1), + err_msg="%r: 2**%d - 1" % (st, i)) + + i = max(i - 1, 1) + assert_equal(hash(ut(2**(i - 1))), hash(2**(i - 1)), + err_msg="%r: 2**%d" % (ut, i - 1)) + assert_equal(hash(ut(2**i - 1)), hash(2**i - 1), + err_msg="%r: 2**%d - 1" % (ut, i)) + + +class TestAttributes: + def _create_arrays(self): + one = np.arange(10) + two = np.arange(20).reshape(4, 5) + three = np.arange(60, dtype=np.float64).reshape(2, 5, 6) + return one, two, three + + def test_attributes(self): + one, two, three = self._create_arrays() + assert_equal(one.shape, (10,)) + assert_equal(two.shape, (4, 5)) + assert_equal(three.shape, (2, 5, 6)) + three.shape = (10, 3, 2) + assert_equal(three.shape, (10, 3, 2)) + three.shape = (2, 5, 6) + assert_equal(one.strides, (one.itemsize,)) + num = two.itemsize + assert_equal(two.strides, (5 * num, num)) + num = three.itemsize + assert_equal(three.strides, (30 * num, 6 * num, num)) + assert_equal(one.ndim, 1) + assert_equal(two.ndim, 2) + assert_equal(three.ndim, 3) + num = two.itemsize + assert_equal(two.size, 20) + assert_equal(two.nbytes, 20 * num) + assert_equal(two.itemsize, two.dtype.itemsize) + assert_equal(two.base, np.arange(20)) + + def test_dtypeattr(self): + one, _, three = self._create_arrays() + assert_equal(one.dtype, np.dtype(np.int_)) + assert_equal(three.dtype, np.dtype(np.float64)) + assert_equal(one.dtype.char, np.dtype(int).char) + assert one.dtype.char in "lq" + assert_equal(three.dtype.char, 'd') + assert_(three.dtype.str[0] in '<>') + assert_equal(one.dtype.str[1], 'i') + assert_equal(three.dtype.str[1], 'f') + + def test_int_subclassing(self): + # Regression test for https://github.com/numpy/numpy/pull/3526 + + numpy_int = np.int_(0) + + # int_ doesn't inherit from Python int, because it's not fixed-width + assert_(not isinstance(numpy_int, int)) + + def test_stridesattr(self): + x, _, _ = self._create_arrays() + + def make_array(size, offset, strides): + return np.ndarray(size, buffer=x, dtype=int, + offset=offset * x.itemsize, + strides=strides * x.itemsize) + + assert_equal(make_array(4, 4, -1), np.array([4, 3, 2, 1])) + assert_raises(ValueError, make_array, 4, 4, -2) + assert_raises(ValueError, make_array, 4, 2, -1) + assert_raises(ValueError, make_array, 8, 3, 1) + assert_equal(make_array(8, 3, 0), np.array([3] * 8)) + # Check behavior reported in gh-2503: + assert_raises(ValueError, make_array, (2, 3), 5, np.array([-2, -3])) + make_array(0, 0, 10) + + def test_set_stridesattr(self): + x, _, _ = self._create_arrays() + + def make_array(size, offset, strides): + try: + r = np.ndarray([size], dtype=int, buffer=x, + offset=offset * x.itemsize) + except Exception as e: + raise RuntimeError(e) + with pytest.warns(DeprecationWarning): + r.strides = strides * x.itemsize + return r + + assert_equal(make_array(4, 4, -1), np.array([4, 3, 2, 1])) + assert_equal(make_array(7, 3, 1), np.array([3, 4, 5, 6, 7, 8, 9])) + assert_raises(ValueError, make_array, 4, 4, -2) + assert_raises(ValueError, make_array, 4, 2, -1) + assert_raises(RuntimeError, make_array, 8, 3, 1) + # Check that the true extent of the array is used. + # Test relies on as_strided base not exposing a buffer. + x = stride_tricks.as_strided(np.arange(1), (10, 10), (0, 0)) + + def set_strides(arr, strides): + with pytest.warns(DeprecationWarning): + arr.strides = strides + + assert_raises(ValueError, set_strides, x, (10 * x.itemsize, x.itemsize)) + + # Test for offset calculations: + x = stride_tricks.as_strided(np.arange(10, dtype=np.int8)[-1], + shape=(10,), strides=(-1,)) + assert_raises(ValueError, set_strides, x[::-1], -1) + a = x[::-1] + with pytest.warns(DeprecationWarning): + a.strides = 1 + with pytest.warns(DeprecationWarning): + a[::2].strides = 2 + + # test 0d + arr_0d = np.array(0) + with pytest.warns(DeprecationWarning): + arr_0d.strides = () + assert_raises(TypeError, set_strides, arr_0d, None) + + def test_fill(self): + for t in "?bhilqpBHILQPfdgFDGO": + x = np.empty((3, 2, 1), t) + y = np.empty((3, 2, 1), t) + x.fill(1) + y[...] = 1 + assert_equal(x, y) + + def test_fill_max_uint64(self): + x = np.empty((3, 2, 1), dtype=np.uint64) + y = np.empty((3, 2, 1), dtype=np.uint64) + value = 2**64 - 1 + y[...] = value + x.fill(value) + assert_array_equal(x, y) + + def test_fill_struct_array(self): + # Filling from a scalar + x = np.array([(0, 0.0), (1, 1.0)], dtype='i4,f8') + x.fill(x[0]) + assert_equal(x['f1'][1], x['f1'][0]) + # Filling from a tuple that can be converted + # to a scalar + x = np.zeros(2, dtype=[('a', 'f8'), ('b', 'i4')]) + x.fill((3.5, -2)) + assert_array_equal(x['a'], [3.5, 3.5]) + assert_array_equal(x['b'], [-2, -2]) + + def test_fill_readonly(self): + # gh-22922 + a = np.zeros(11) + a.setflags(write=False) + with pytest.raises(ValueError, match=".*read-only"): + a.fill(0) + + def test_fill_subarrays(self): + # NOTE: + # This is also a regression test for a crash with PYTHONMALLOC=debug + + dtype = np.dtype("2= 3 + + arg0 = "object" if func is np.array else "a" + assert arg0 in sig.parameters + assert sig.parameters[arg0].default is inspect.Parameter.empty + assert sig.parameters[arg0].kind is inspect.Parameter.POSITIONAL_OR_KEYWORD + + assert "dtype" in sig.parameters + assert sig.parameters["dtype"].default is None + assert sig.parameters["dtype"].kind is inspect.Parameter.POSITIONAL_OR_KEYWORD + + assert "like" in sig.parameters + assert sig.parameters["like"].default is None + assert sig.parameters["like"].kind is inspect.Parameter.KEYWORD_ONLY + + +class TestAssignment: + def test_assignment_broadcasting(self): + a = np.arange(6).reshape(2, 3) + + # Broadcasting the input to the output + a[...] = np.arange(3) + assert_equal(a, [[0, 1, 2], [0, 1, 2]]) + a[...] = np.arange(2).reshape(2, 1) + assert_equal(a, [[0, 0, 0], [1, 1, 1]]) + + # For compatibility with <= 1.5, a limited version of broadcasting + # the output to the input. + # + # This behavior is inconsistent with NumPy broadcasting + # in general, because it only uses one of the two broadcasting + # rules (adding a new "1" dimension to the left of the shape), + # applied to the output instead of an input. In NumPy 2.0, this kind + # of broadcasting assignment will likely be disallowed. + a[...] = np.arange(6)[::-1].reshape(1, 2, 3) + assert_equal(a, [[5, 4, 3], [2, 1, 0]]) + # The other type of broadcasting would require a reduction operation. + + def assign(a, b): + a[...] = b + + assert_raises(ValueError, assign, a, np.arange(12).reshape(2, 2, 3)) + + def test_assignment_errors(self): + # Address issue #2276 + class C: + pass + a = np.zeros(1) + + def assign(v): + a[0] = v + + assert_raises((AttributeError, TypeError), assign, C()) + assert_raises(ValueError, assign, [1]) + + @pytest.mark.filterwarnings( + "ignore:.*set_string_function.*:DeprecationWarning" + ) + def test_unicode_assignment(self): + # gh-5049 + from numpy._core.arrayprint import set_printoptions + + @contextmanager + def inject_str(s): + """ replace ndarray.__str__ temporarily """ + set_printoptions(formatter={"all": lambda x: s}) + try: + yield + finally: + set_printoptions() + + a1d = np.array(['test']) + a0d = np.array('done') + with inject_str('bad'): + a1d[0] = a0d # previously this would invoke __str__ + assert_equal(a1d[0], 'done') + + # this would crash for the same reason + np.array([np.array('\xe5\xe4\xf6')]) + + def test_stringlike_empty_list(self): + # gh-8902 + u = np.array(['done']) + b = np.array([b'done']) + + class bad_sequence: + def __getitem__(self, _, /): pass + def __len__(self): raise RuntimeError + + assert_raises(ValueError, operator.setitem, u, 0, []) + assert_raises(ValueError, operator.setitem, b, 0, []) + + assert_raises(ValueError, operator.setitem, u, 0, bad_sequence()) + assert_raises(ValueError, operator.setitem, b, 0, bad_sequence()) + + def test_longdouble_assignment(self): + # only relevant if longdouble is larger than float + # we're looking for loss of precision + + for dtype in (np.longdouble, np.clongdouble): + # gh-8902 + tinyb = np.nextafter(np.longdouble(0), 1).astype(dtype) + tinya = np.nextafter(np.longdouble(0), -1).astype(dtype) + + # construction + tiny1d = np.array([tinya]) + assert_equal(tiny1d[0], tinya) + + # scalar = scalar + tiny1d[0] = tinyb + assert_equal(tiny1d[0], tinyb) + + # 0d = scalar + tiny1d[0, ...] = tinya + assert_equal(tiny1d[0], tinya) + + # 0d = 0d + tiny1d[0, ...] = tinyb[...] + assert_equal(tiny1d[0], tinyb) + + # scalar = 0d + tiny1d[0] = tinyb[...] + assert_equal(tiny1d[0], tinyb) + + arr = np.array([np.array(tinya)]) + assert_equal(arr[0], tinya) + + def test_cast_to_string(self): + # cast to str should do "str(scalar)", not "str(scalar.item())" + # When converting a float to a string via array assignment, we + # want to ensure that the conversion uses str(scalar) to preserve + # the expected precision. + a = np.zeros(1, dtype='S20') + a[:] = np.array(['1.12345678901234567890'], dtype='f8') + assert_equal(a[0], b"1.1234567890123457") + + +class TestDtypedescr: + def test_construction(self): + d1 = np.dtype('i4') + assert_equal(d1, np.dtype(np.int32)) + d2 = np.dtype('f8') + assert_equal(d2, np.dtype(np.float64)) + + def test_byteorders(self): + assert_(np.dtype('i4')) + assert_(np.dtype([('a', 'i4')])) + + def test_structured_non_void(self): + fields = [('a', ' ndmax validation + data = np.array([[1, 2, 3], [4, 5, 6]]) + with pytest.raises(ValueError, match="object too deep for desired array"): + np.array(data, ndmax=1, dtype=object) + + +class TestStructured: + def test_subarray_field_access(self): + a = np.zeros((3, 5), dtype=[('a', ('i4', (2, 2)))]) + a['a'] = np.arange(60).reshape(3, 5, 2, 2) + + # Since the subarray is always in C-order, a transpose + # does not swap the subarray: + assert_array_equal(a.T['a'], a['a'].transpose(1, 0, 2, 3)) + + # In Fortran order, the subarray gets appended + # like in all other cases, not prepended as a special case + b = a.copy(order='F') + assert_equal(a['a'].shape, b['a'].shape) + assert_equal(a.T['a'].shape, a.T.copy()['a'].shape) + + def test_subarray_comparison(self): + # Check that comparisons between record arrays with + # multi-dimensional field types work properly + a = np.rec.fromrecords( + [([1, 2, 3], 'a', [[1, 2], [3, 4]]), ([3, 3, 3], 'b', [[0, 0], [0, 0]])], + dtype=[('a', ('f4', 3)), ('b', object), ('c', ('i4', (2, 2)))]) + b = a.copy() + assert_equal(a == b, [True, True]) + assert_equal(a != b, [False, False]) + b[1].b = 'c' + assert_equal(a == b, [True, False]) + assert_equal(a != b, [False, True]) + for i in range(3): + b[0].a = a[0].a + b[0].a[i] = 5 + assert_equal(a == b, [False, False]) + assert_equal(a != b, [True, True]) + for i in range(2): + for j in range(2): + b = a.copy() + b[0].c[i, j] = 10 + assert_equal(a == b, [False, True]) + assert_equal(a != b, [True, False]) + + # Check that broadcasting with a subarray works, including cases that + # require promotion to work: + a = np.array([[(0,)], [(1,)]], dtype=[('a', 'f8')]) + b = np.array([(0,), (0,), (1,)], dtype=[('a', 'f8')]) + assert_equal(a == b, [[True, True, False], [False, False, True]]) + assert_equal(b == a, [[True, True, False], [False, False, True]]) + a = np.array([[(0,)], [(1,)]], dtype=[('a', 'f8', (1,))]) + b = np.array([(0,), (0,), (1,)], dtype=[('a', 'f8', (1,))]) + assert_equal(a == b, [[True, True, False], [False, False, True]]) + assert_equal(b == a, [[True, True, False], [False, False, True]]) + a = np.array([[([0, 0],)], [([1, 1],)]], dtype=[('a', 'f8', (2,))]) + b = np.array([([0, 0],), ([0, 1],), ([1, 1],)], dtype=[('a', 'f8', (2,))]) + assert_equal(a == b, [[True, False, False], [False, False, True]]) + assert_equal(b == a, [[True, False, False], [False, False, True]]) + + # Check that broadcasting Fortran-style arrays with a subarray work + a = np.array([[([0, 0],)], [([1, 1],)]], dtype=[('a', 'f8', (2,))], order='F') + b = np.array([([0, 0],), ([0, 1],), ([1, 1],)], dtype=[('a', 'f8', (2,))]) + assert_equal(a == b, [[True, False, False], [False, False, True]]) + assert_equal(b == a, [[True, False, False], [False, False, True]]) + + # Check that incompatible sub-array shapes don't result to broadcasting + x = np.zeros((1,), dtype=[('a', ('f4', (1, 2))), ('b', 'i1')]) + y = np.zeros((1,), dtype=[('a', ('f4', (2,))), ('b', 'i1')]) + # The main importance is that it does not return True: + with pytest.raises(TypeError): + x == y + + x = np.zeros((1,), dtype=[('a', ('f4', (2, 1))), ('b', 'i1')]) + y = np.zeros((1,), dtype=[('a', ('f4', (2,))), ('b', 'i1')]) + # The main importance is that it does not return True: + with pytest.raises(TypeError): + x == y + + def test_empty_structured_array_comparison(self): + # Check that comparison works on empty arrays with nontrivially + # shaped fields + a = np.zeros(0, [('a', 'i8'), ('b', 'f8')]) + assert_equal(a == b, [False, True]) + assert_equal(a != b, [True, False]) + + a = np.array([(5, 42), (10, 1)], dtype=[('a', '>f8'), ('b', 'i8')]) + assert_equal(a == b, [False, True]) + assert_equal(a != b, [True, False]) + + # Including with embedded subarray dtype (although subarray comparison + # itself may still be a bit weird and compare the raw data) + a = np.array([(5, 42), (10, 1)], dtype=[('a', '10>f8'), ('b', '5i8')]) + assert_equal(a == b, [False, True]) + assert_equal(a != b, [True, False]) + + @pytest.mark.parametrize("op", [ + operator.eq, lambda x, y: operator.eq(y, x), + operator.ne, lambda x, y: operator.ne(y, x)]) + def test_void_comparison_failures(self, op): + # In principle, one could decide to return an array of False for some + # if comparisons are impossible. But right now we return TypeError + # when "void" dtype are involved. + x = np.zeros(3, dtype=[('a', 'i1')]) + y = np.zeros(3) + # Cannot compare non-structured to structured: + with pytest.raises(TypeError): + op(x, y) + + # Added title prevents promotion, but casts are OK: + y = np.zeros(3, dtype=[(('title', 'a'), 'i1')]) + assert np.can_cast(y.dtype, x.dtype) + with pytest.raises(TypeError): + op(x, y) + + x = np.zeros(3, dtype="V7") + y = np.zeros(3, dtype="V8") + with pytest.raises(TypeError): + op(x, y) + + def test_casting(self): + # Check that casting a structured array to change its byte order + # works + a = np.array([(1,)], dtype=[('a', 'i4')], casting='unsafe')) + b = a.astype([('a', '>i4')]) + a_tmp = a.byteswap() + a_tmp = a_tmp.view(a_tmp.dtype.newbyteorder()) + assert_equal(b, a_tmp) + assert_equal(a['a'][0], b['a'][0]) + + # Check that equality comparison works on structured arrays if + # they are 'equiv'-castable + a = np.array([(5, 42), (10, 1)], dtype=[('a', '>i4'), ('b', 'f8')]) + assert_(np.can_cast(a.dtype, b.dtype, casting='equiv')) + assert_equal(a == b, [True, True]) + + # Check that 'equiv' casting can change byte order + assert_(np.can_cast(a.dtype, b.dtype, casting='equiv')) + c = a.astype(b.dtype, casting='equiv') + assert_equal(a == c, [True, True]) + + # Check that 'safe' casting can change byte order and up-cast + # fields + t = [('a', 'f8')] + assert_(np.can_cast(a.dtype, t, casting='safe')) + c = a.astype(t, casting='safe') + assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)), + [True, True]) + + # Check that 'same_kind' casting can change byte order and + # change field widths within a "kind" + t = [('a', 'f4')] + assert_(np.can_cast(a.dtype, t, casting='same_kind')) + c = a.astype(t, casting='same_kind') + assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)), + [True, True]) + + # Check that casting fails if the casting rule should fail on + # any of the fields + t = [('a', '>i8'), ('b', 'i2'), ('b', 'i8'), ('b', 'i4')] + assert_(not np.can_cast(a.dtype, t, casting=casting)) + t = [('a', '>i4'), ('b', 'i8") + ab = np.array([(1, 2)], dtype=[A, B]) + ba = np.array([(1, 2)], dtype=[B, A]) + assert_raises(TypeError, np.concatenate, ab, ba) + assert_raises(TypeError, np.result_type, ab.dtype, ba.dtype) + assert_raises(TypeError, np.promote_types, ab.dtype, ba.dtype) + + # dtypes with same field names/order but different memory offsets + # and byte-order are promotable to packed nbo. + assert_equal(np.promote_types(ab.dtype, ba[['a', 'b']].dtype), + repack_fields(ab.dtype.newbyteorder('N'))) + + # gh-13667 + # dtypes with different fieldnames but castable field types are castable + assert_equal(np.can_cast(ab.dtype, ba.dtype), True) + assert_equal(ab.astype(ba.dtype).dtype, ba.dtype) + assert_equal(np.can_cast('f8,i8', [('f0', 'f8'), ('f1', 'i8')]), True) + assert_equal(np.can_cast('f8,i8', [('f1', 'f8'), ('f0', 'i8')]), True) + assert_equal(np.can_cast('f8,i8', [('f1', 'i8'), ('f0', 'f8')]), False) + assert_equal(np.can_cast('f8,i8', [('f1', 'i8'), ('f0', 'f8')], + casting='unsafe'), True) + + ab[:] = ba # make sure assignment still works + + # tests of type-promotion of corresponding fields + dt1 = np.dtype([("", "i4")]) + dt2 = np.dtype([("", "i8")]) + assert_equal(np.promote_types(dt1, dt2), np.dtype([('f0', 'i8')])) + assert_equal(np.promote_types(dt2, dt1), np.dtype([('f0', 'i8')])) + assert_raises(TypeError, np.promote_types, dt1, np.dtype([("", "V3")])) + assert_equal(np.promote_types('i4,f8', 'i8,f4'), + np.dtype([('f0', 'i8'), ('f1', 'f8')])) + # test nested case + dt1nest = np.dtype([("", dt1)]) + dt2nest = np.dtype([("", dt2)]) + assert_equal(np.promote_types(dt1nest, dt2nest), + np.dtype([('f0', np.dtype([('f0', 'i8')]))])) + + # note that offsets are lost when promoting: + dt = np.dtype({'names': ['x'], 'formats': ['i4'], 'offsets': [8]}) + a = np.ones(3, dtype=dt) + assert_equal(np.concatenate([a, a]).dtype, np.dtype([('x', 'i4')])) + + @pytest.mark.parametrize("dtype_dict", [ + {"names": ["a", "b"], "formats": ["i4", "f"], "itemsize": 100}, + {"names": ["a", "b"], "formats": ["i4", "f"], + "offsets": [0, 12]}]) + @pytest.mark.parametrize("align", [True, False]) + def test_structured_promotion_packs(self, dtype_dict, align): + # Structured dtypes are packed when promoted (we consider the packed + # form to be "canonical"), so tere is no extra padding. + dtype = np.dtype(dtype_dict, align=align) + # Remove non "canonical" dtype options: + dtype_dict.pop("itemsize", None) + dtype_dict.pop("offsets", None) + expected = np.dtype(dtype_dict, align=align) + + res = np.promote_types(dtype, dtype) + assert res.itemsize == expected.itemsize + assert res.fields == expected.fields + + # But the "expected" one, should just be returned unchanged: + res = np.promote_types(expected, expected) + assert res is expected + + def test_structured_asarray_is_view(self): + # A scalar viewing an array preserves its view even when creating a + # new array. This test documents behaviour, it may not be the best + # desired behaviour. + arr = np.array([1], dtype="i,i") + scalar = arr[0] + assert not scalar.flags.owndata # view into the array + assert np.asarray(scalar).base is scalar + # But never when a dtype is passed in: + assert np.asarray(scalar, dtype=scalar.dtype).base is None + # A scalar which owns its data does not have this property. + # It is not easy to create one, one method is to use pickle: + scalar = pickle.loads(pickle.dumps(scalar)) + assert scalar.flags.owndata + assert np.asarray(scalar).base is None + +class TestBool: + def test_test_interning(self): + a0 = np.bool(0) + b0 = np.bool(False) + assert_(a0 is b0) + a1 = np.bool(1) + b1 = np.bool(True) + assert_(a1 is b1) + assert_(np.array([True])[0] is a1) + assert_(np.array(True)[()] is a1) + + def test_sum(self): + d = np.ones(101, dtype=bool) + assert_equal(d.sum(), d.size) + assert_equal(d[::2].sum(), d[::2].size) + assert_equal(d[::-2].sum(), d[::-2].size) + + d = np.frombuffer(b'\xff\xff' * 100, dtype=bool) + assert_equal(d.sum(), d.size) + assert_equal(d[::2].sum(), d[::2].size) + assert_equal(d[::-2].sum(), d[::-2].size) + + def check_count_nonzero(self, power, length): + powers = [2 ** i for i in range(length)] + for i in range(2**power): + l = [(i & x) != 0 for x in powers] + a = np.array(l, dtype=bool) + c = builtins.sum(l) + assert_equal(np.count_nonzero(a), c) + av = a.view(np.uint8) + av *= 3 + assert_equal(np.count_nonzero(a), c) + av *= 4 + assert_equal(np.count_nonzero(a), c) + av[av != 0] = 0xFF + assert_equal(np.count_nonzero(a), c) + + def test_count_nonzero(self): + # check all 12 bit combinations in a length 17 array + # covers most cases of the 16 byte unrolled code + self.check_count_nonzero(12, 17) + + @pytest.mark.slow + def test_count_nonzero_all(self): + # check all combinations in a length 17 array + # covers all cases of the 16 byte unrolled code + self.check_count_nonzero(17, 17) + + def test_count_nonzero_unaligned(self): + # prevent mistakes as e.g. gh-4060 + for o in range(7): + a = np.zeros((18,), dtype=bool)[o + 1:] + a[:o] = True + assert_equal(np.count_nonzero(a), builtins.sum(a.tolist())) + a = np.ones((18,), dtype=bool)[o + 1:] + a[:o] = False + assert_equal(np.count_nonzero(a), builtins.sum(a.tolist())) + + def _test_cast_from_flexible(self, dtype): + # empty string -> false + for n in range(3): + v = np.array(b'', (dtype, n)) + assert_equal(bool(v), False) + assert_equal(bool(v[()]), False) + assert_equal(v.astype(bool), False) + assert_(isinstance(v.astype(bool), np.ndarray)) + assert_(v[()].astype(bool) is np.False_) + + # anything else -> true + for n in range(1, 4): + for val in [b'a', b'0', b' ']: + v = np.array(val, (dtype, n)) + assert_equal(bool(v), True) + assert_equal(bool(v[()]), True) + assert_equal(v.astype(bool), True) + assert_(isinstance(v.astype(bool), np.ndarray)) + assert_(v[()].astype(bool) is np.True_) + + def test_cast_from_void(self): + self._test_cast_from_flexible(np.void) + + def test_cast_from_unicode(self): + self._test_cast_from_flexible(np.str_) + + def test_cast_from_bytes(self): + self._test_cast_from_flexible(np.bytes_) + + +class TestZeroSizeFlexible: + @staticmethod + def _zeros(shape, dtype=str): + dtype = np.dtype(dtype) + if dtype == np.void: + return np.zeros(shape, dtype=(dtype, 0)) + + # not constructable directly + dtype = np.dtype([('x', dtype, 0)]) + return np.zeros(shape, dtype=dtype)['x'] + + def test_create(self): + zs = self._zeros(10, bytes) + assert_equal(zs.itemsize, 0) + zs = self._zeros(10, np.void) + assert_equal(zs.itemsize, 0) + zs = self._zeros(10, str) + assert_equal(zs.itemsize, 0) + + def _test_sort_partition(self, name, kinds, **kwargs): + # Previously, these would all hang + for dt in [bytes, np.void, str]: + zs = self._zeros(10, dt) + sort_method = getattr(zs, name) + sort_func = getattr(np, name) + for kind in kinds: + sort_method(kind=kind, **kwargs) + sort_func(zs, kind=kind, **kwargs) + + def test_sort(self): + self._test_sort_partition('sort', kinds='qhs') + + def test_argsort(self): + self._test_sort_partition('argsort', kinds='qhs') + + def test_partition(self): + self._test_sort_partition('partition', kinds=['introselect'], kth=2) + + def test_argpartition(self): + self._test_sort_partition('argpartition', kinds=['introselect'], kth=2) + + def test_resize(self): + # previously an error + for dt in [bytes, np.void, str]: + zs = self._zeros(10, dt) + zs.resize(25) + zs.resize((10, 10)) + + def test_view(self): + for dt in [bytes, np.void, str]: + zs = self._zeros(10, dt) + + # viewing as itself should be allowed + assert_equal(zs.view(dt).dtype, np.dtype(dt)) + + # viewing as any non-empty type gives an empty result + assert_equal(zs.view((dt, 1)).shape, (0,)) + + def test_dumps(self): + zs = self._zeros(10, int) + assert_equal(zs, pickle.loads(zs.dumps())) + + def test_pickle(self): + for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): + for dt in [bytes, np.void, str]: + zs = self._zeros(10, dt) + p = pickle.dumps(zs, protocol=proto) + zs2 = pickle.loads(p) + + assert_equal(zs.dtype, zs2.dtype) + + def test_pickle_empty(self): + """Checking if an empty array pickled and un-pickled will not cause a + segmentation fault""" + arr = np.array([]).reshape(999999, 0) + pk_dmp = pickle.dumps(arr) + pk_load = pickle.loads(pk_dmp) + + assert pk_load.size == 0 + + @pytest.mark.skipif(pickle.HIGHEST_PROTOCOL < 5, + reason="requires pickle protocol 5") + def test_pickle_with_buffercallback(self): + array = np.arange(10) + buffers = [] + bytes_string = pickle.dumps(array, buffer_callback=buffers.append, + protocol=5) + array_from_buffer = pickle.loads(bytes_string, buffers=buffers) + # when using pickle protocol 5 with buffer callbacks, + # array_from_buffer is reconstructed from a buffer holding a view + # to the initial array's data, so modifying an element in array + # should modify it in array_from_buffer too. + array[0] = -1 + assert array_from_buffer[0] == -1, array_from_buffer[0] + + +class TestMethods: + + sort_kinds = ['quicksort', 'heapsort', 'stable'] + + def test_all_where(self): + a = np.array([[True, False, True], + [False, False, False], + [True, True, True]]) + wh_full = np.array([[True, False, True], + [False, False, False], + [True, False, True]]) + wh_lower = np.array([[False], + [False], + [True]]) + for _ax in [0, None]: + assert_equal(a.all(axis=_ax, where=wh_lower), + np.all(a[wh_lower[:, 0], :], axis=_ax)) + assert_equal(np.all(a, axis=_ax, where=wh_lower), + a[wh_lower[:, 0], :].all(axis=_ax)) + + assert_equal(a.all(where=wh_full), True) + assert_equal(np.all(a, where=wh_full), True) + assert_equal(a.all(where=False), True) + assert_equal(np.all(a, where=False), True) + + def test_any_where(self): + a = np.array([[True, False, True], + [False, False, False], + [True, True, True]]) + wh_full = np.array([[False, True, False], + [True, True, True], + [False, False, False]]) + wh_middle = np.array([[False], + [True], + [False]]) + for _ax in [0, None]: + assert_equal(a.any(axis=_ax, where=wh_middle), + np.any(a[wh_middle[:, 0], :], axis=_ax)) + assert_equal(np.any(a, axis=_ax, where=wh_middle), + a[wh_middle[:, 0], :].any(axis=_ax)) + assert_equal(a.any(where=wh_full), False) + assert_equal(np.any(a, where=wh_full), False) + assert_equal(a.any(where=False), False) + assert_equal(np.any(a, where=False), False) + + @pytest.mark.parametrize("dtype", + ["i8", "U10", "object", "datetime64[ms]"]) + def test_any_and_all_result_dtype(self, dtype): + arr = np.ones(3, dtype=dtype) + assert arr.any().dtype == np.bool + assert arr.all().dtype == np.bool + + def test_any_and_all_object_dtype(self): + # (seberg) Not sure we should even allow dtype here, but it is. + arr = np.ones(3, dtype=object) + # keepdims to prevent getting a scalar. + assert arr.any(dtype=object, keepdims=True).dtype == object + assert arr.all(dtype=object, keepdims=True).dtype == object + + def test_compress(self): + tgt = [[5, 6, 7, 8, 9]] + arr = np.arange(10).reshape(2, 5) + out = arr.compress([0, 1], axis=0) + assert_equal(out, tgt) + + tgt = [[1, 3], [6, 8]] + out = arr.compress([0, 1, 0, 1, 0], axis=1) + assert_equal(out, tgt) + + tgt = [[1], [6]] + arr = np.arange(10).reshape(2, 5) + out = arr.compress([0, 1], axis=1) + assert_equal(out, tgt) + + arr = np.arange(10).reshape(2, 5) + out = arr.compress([0, 1]) + assert_equal(out, 1) + + def test_choose(self): + x = 2 * np.ones((3,), dtype=int) + y = 3 * np.ones((3,), dtype=int) + x2 = 2 * np.ones((2, 3), dtype=int) + y2 = 3 * np.ones((2, 3), dtype=int) + ind = np.array([0, 0, 1]) + + A = ind.choose((x, y)) + assert_equal(A, [2, 2, 3]) + + A = ind.choose((x2, y2)) + assert_equal(A, [[2, 2, 3], [2, 2, 3]]) + + A = ind.choose((x, y2)) + assert_equal(A, [[2, 2, 3], [2, 2, 3]]) + + oned = np.ones(1) + # gh-12031, caused SEGFAULT + assert_raises(TypeError, oned.choose, np.void(0), [oned]) + + out = np.array(0) + ret = np.choose(np.array(1), [10, 20, 30], out=out) + assert out is ret + assert_equal(out[()], 20) + + # gh-6272 check overlap on out + x = np.arange(5) + y = np.choose([0, 0, 0], [x[:3], x[:3], x[:3]], out=x[1:4], mode='wrap') + assert_equal(y, np.array([0, 1, 2])) + + # gh_28206 check fail when out not writeable + x = np.arange(3) + out = np.zeros(3) + out.setflags(write=False) + assert_raises(ValueError, np.choose, [0, 1, 2], [x, x, x], out=out) + + def test_prod(self): + ba = [1, 2, 10, 11, 6, 5, 4] + ba2 = [[1, 2, 3, 4], [5, 6, 7, 9], [10, 3, 4, 5]] + + for ctype in [np.int16, np.uint16, np.int32, np.uint32, + np.float32, np.float64, np.complex64, np.complex128]: + a = np.array(ba, ctype) + a2 = np.array(ba2, ctype) + if ctype in ['1', 'b']: + assert_raises(ArithmeticError, a.prod) + assert_raises(ArithmeticError, a2.prod, axis=1) + else: + assert_equal(a.prod(axis=0), 26400) + assert_array_equal(a2.prod(axis=0), + np.array([50, 36, 84, 180], ctype)) + assert_array_equal(a2.prod(axis=-1), + np.array([24, 1890, 600], ctype)) + + @pytest.mark.parametrize('dtype', [None, object]) + def test_repeat(self, dtype): + m = np.array([1, 2, 3, 4, 5, 6], dtype=dtype) + m_rect = m.reshape((2, 3)) + + A = m.repeat([1, 3, 2, 1, 1, 2]) + assert_equal(A, [1, 2, 2, 2, 3, + 3, 4, 5, 6, 6]) + + A = m.repeat(2) + assert_equal(A, [1, 1, 2, 2, 3, 3, + 4, 4, 5, 5, 6, 6]) + + A = m_rect.repeat([2, 1], axis=0) + assert_equal(A, [[1, 2, 3], + [1, 2, 3], + [4, 5, 6]]) + + A = m_rect.repeat([1, 3, 2], axis=1) + assert_equal(A, [[1, 2, 2, 2, 3, 3], + [4, 5, 5, 5, 6, 6]]) + + A = m_rect.repeat(2, axis=0) + assert_equal(A, [[1, 2, 3], + [1, 2, 3], + [4, 5, 6], + [4, 5, 6]]) + + A = m_rect.repeat(2, axis=1) + assert_equal(A, [[1, 1, 2, 2, 3, 3], + [4, 4, 5, 5, 6, 6]]) + + def test_reshape(self): + arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]]) + + tgt = [[1, 2, 3, 4, 5, 6], [7, 8, 9, 10, 11, 12]] + assert_equal(arr.reshape(2, 6), tgt) + + tgt = [[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]] + assert_equal(arr.reshape(3, 4), tgt) + + tgt = [[1, 10, 8, 6], [4, 2, 11, 9], [7, 5, 3, 12]] + assert_equal(arr.reshape((3, 4), order='F'), tgt) + + tgt = [[1, 4, 7, 10], [2, 5, 8, 11], [3, 6, 9, 12]] + assert_equal(arr.T.reshape((3, 4), order='C'), tgt) + + def test_round(self): + def check_round(arr, expected, *round_args): + assert_equal(arr.round(*round_args), expected) + # With output array + out = np.zeros_like(arr) + res = arr.round(*round_args, out=out) + assert_equal(out, expected) + assert out is res + + check_round(np.array([1, 2, 3]), [1, 2, 3]) + check_round(np.array([1.2, 1.5]), [1, 2]) + check_round(np.array(1.5), 2) + check_round(np.array([12.2, 15.5]), [10, 20], -1) + check_round(np.array([12.15, 15.51]), [12.2, 15.5], 1) + # Complex rounding + check_round(np.array([4.5 + 1.5j]), [4 + 2j]) + check_round(np.array([12.5 + 15.5j]), [10 + 20j], -1) + + @pytest.mark.parametrize('dt', ['uint8', int, float, complex]) + def test_round_copies(self, dt): + a = np.arange(3, dtype=dt) + assert not np.shares_memory(a.round(), a) + assert not np.shares_memory(a.round(decimals=2), a) + + out = np.empty(3, dtype=dt) + assert not np.shares_memory(a.round(out=out), a) + + a = np.arange(12).astype(dt).reshape(3, 4).T + + assert a.flags.f_contiguous + assert np.round(a).flags.f_contiguous + + def test_squeeze(self): + a = np.array([[[1], [2], [3]]]) + assert_equal(a.squeeze(), [1, 2, 3]) + assert_equal(a.squeeze(axis=(0,)), [[1], [2], [3]]) + assert_raises(ValueError, a.squeeze, axis=(1,)) + assert_equal(a.squeeze(axis=(2,)), [[1, 2, 3]]) + + def test_transpose(self): + a = np.array([[1, 2], [3, 4]]) + assert_equal(a.transpose(), [[1, 3], [2, 4]]) + assert_raises(ValueError, lambda: a.transpose(0)) + assert_raises(ValueError, lambda: a.transpose(0, 0)) + assert_raises(ValueError, lambda: a.transpose(0, 1, 2)) + + def test_sort(self): + # test ordering for floats and complex containing nans. It is only + # necessary to check the less-than comparison, so sorts that + # only follow the insertion sort path are sufficient. We only + # test doubles and complex doubles as the logic is the same. + + # check doubles + msg = "Test real sort order with nans" + a = np.array([np.nan, 1, 0]) + b = np.sort(a) + assert_equal(b, a[::-1], msg) + # check complex + msg = "Test complex sort order with nans" + a = np.zeros(9, dtype=np.complex128) + a.real += [np.nan, np.nan, np.nan, 1, 0, 1, 1, 0, 0] + a.imag += [np.nan, 1, 0, np.nan, np.nan, 1, 0, 1, 0] + b = np.sort(a) + assert_equal(b, a[::-1], msg) + + with assert_raises_regex( + ValueError, + "`kind` and keyword parameters can't be provided at the same time" + ): + np.sort(a, kind="stable", stable=True) + + # all c scalar sorts use the same code with different types + # so it suffices to run a quick check with one type. The number + # of sorted items must be greater than ~50 to check the actual + # algorithm because quick and merge sort fall over to insertion + # sort for small arrays. + + @pytest.mark.parametrize('dtype', [np.uint8, np.uint16, np.uint32, np.uint64, + np.float16, np.float32, np.float64, + np.longdouble]) + def test_sort_unsigned(self, dtype): + a = np.arange(101, dtype=dtype) + b = a[::-1].copy() + for kind in self.sort_kinds: + msg = f"scalar sort, kind={kind}" + c = a.copy() + c.sort(kind=kind) + assert_equal(c, a, msg) + c = b.copy() + c.sort(kind=kind) + assert_equal(c, a, msg) + + @pytest.mark.parametrize('dtype', + [np.int8, np.int16, np.int32, np.int64, np.float16, + np.float32, np.float64, np.longdouble]) + def test_sort_signed(self, dtype): + a = np.arange(-50, 51, dtype=dtype) + b = a[::-1].copy() + for kind in self.sort_kinds: + msg = f"scalar sort, kind={kind}" + c = a.copy() + c.sort(kind=kind) + assert_equal(c, a, msg) + c = b.copy() + c.sort(kind=kind) + assert_equal(c, a, msg) + + @pytest.mark.parametrize('dtype', [np.float32, np.float64, np.longdouble]) + @pytest.mark.parametrize('part', ['real', 'imag']) + def test_sort_complex(self, part, dtype): + # test complex sorts. These use the same code as the scalars + # but the compare function differs. + cdtype = { + np.single: np.csingle, + np.double: np.cdouble, + np.longdouble: np.clongdouble, + }[dtype] + a = np.arange(-50, 51, dtype=dtype) + b = a[::-1].copy() + ai = (a * (1 + 1j)).astype(cdtype) + bi = (b * (1 + 1j)).astype(cdtype) + setattr(ai, part, 1) + setattr(bi, part, 1) + for kind in self.sort_kinds: + msg = f"complex sort, {part} part == 1, kind={kind}" + c = ai.copy() + c.sort(kind=kind) + assert_equal(c, ai, msg) + c = bi.copy() + c.sort(kind=kind) + assert_equal(c, ai, msg) + + def test_sort_complex_byte_swapping(self): + # test sorting of complex arrays requiring byte-swapping, gh-5441 + for endianness in '<>': + for dt in np.typecodes['Complex']: + arr = np.array([1 + 3.j, 2 + 2.j, 3 + 1.j], dtype=endianness + dt) + c = arr.copy() + c.sort() + msg = f'byte-swapped complex sort, dtype={dt}' + assert_equal(c, arr, msg) + + @pytest.mark.parametrize('dtype', [np.bytes_, np.str_]) + def test_sort_string(self, dtype): + # np.array will perform the encoding to bytes for us in the bytes test + a = np.array(['aaaaaaaa' + chr(i) for i in range(101)], dtype=dtype) + b = a[::-1].copy() + for kind in self.sort_kinds: + msg = f"kind={kind}" + c = a.copy() + c.sort(kind=kind) + assert_equal(c, a, msg) + c = b.copy() + c.sort(kind=kind) + assert_equal(c, a, msg) + + def test_sort_object(self): + # test object array sorts. + a = np.empty((101,), dtype=object) + a[:] = list(range(101)) + b = a[::-1] + for kind in ['q', 'h', 'm']: + msg = f"kind={kind}" + c = a.copy() + c.sort(kind=kind) + assert_equal(c, a, msg) + c = b.copy() + c.sort(kind=kind) + assert_equal(c, a, msg) + + @pytest.mark.parametrize("dt", [ + np.dtype([('f', float), ('i', int)]), + np.dtype([('f', float), ('i', object)])]) + @pytest.mark.parametrize("step", [1, 2]) + def test_sort_structured(self, dt, step): + # test record array sorts. + a = np.array([(i, i) for i in range(101 * step)], dtype=dt) + b = a[::-1] + for kind in ['q', 'h', 'm']: + msg = f"kind={kind}" + c = a.copy()[::step] + indx = c.argsort(kind=kind) + c.sort(kind=kind) + assert_equal(c, a[::step], msg) + assert_equal(a[::step][indx], a[::step], msg) + c = b.copy()[::step] + indx = c.argsort(kind=kind) + c.sort(kind=kind) + assert_equal(c, a[step - 1::step], msg) + assert_equal(b[::step][indx], a[step - 1::step], msg) + + @pytest.mark.parametrize('dtype', ['datetime64[D]', 'timedelta64[D]']) + def test_sort_time(self, dtype): + # test datetime64 and timedelta64 sorts. + a = np.arange(0, 101, dtype=dtype) + b = a[::-1] + for kind in ['q', 'h', 'm']: + msg = f"kind={kind}" + c = a.copy() + c.sort(kind=kind) + assert_equal(c, a, msg) + c = b.copy() + c.sort(kind=kind) + assert_equal(c, a, msg) + + def test_sort_axis(self): + # check axis handling. This should be the same for all type + # specific sorts, so we only check it for one type and one kind + a = np.array([[3, 2], [1, 0]]) + b = np.array([[1, 0], [3, 2]]) + c = np.array([[2, 3], [0, 1]]) + d = a.copy() + d.sort(axis=0) + assert_equal(d, b, "test sort with axis=0") + d = a.copy() + d.sort(axis=1) + assert_equal(d, c, "test sort with axis=1") + d = a.copy() + d.sort() + assert_equal(d, c, "test sort with default axis") + + def test_sort_size_0(self): + # check axis handling for multidimensional empty arrays + a = np.array([]).reshape((3, 2, 1, 0)) + for axis in range(-a.ndim, a.ndim): + msg = f'test empty array sort with axis={axis}' + assert_equal(np.sort(a, axis=axis), a, msg) + msg = 'test empty array sort with axis=None' + assert_equal(np.sort(a, axis=None), a.ravel(), msg) + + def test_sort_bad_ordering(self): + # test generic class with bogus ordering, + # should not segfault. + class Boom: + def __lt__(self, other): + return True + + a = np.array([Boom()] * 100, dtype=object) + for kind in self.sort_kinds: + msg = f"kind={kind}" + c = a.copy() + c.sort(kind=kind) + assert_equal(c, a, msg) + + def test_void_sort(self): + # gh-8210 - previously segfaulted + for i in range(4): + rand = np.random.randint(256, size=4000, dtype=np.uint8) + arr = rand.view('V4') + arr[::-1].sort() + + dt = np.dtype([('val', 'i4', (1,))]) + for i in range(4): + rand = np.random.randint(256, size=4000, dtype=np.uint8) + arr = rand.view(dt) + arr[::-1].sort() + + def test_sort_raises(self): + # gh-9404 + arr = np.array([0, datetime.now(), 1], dtype=object) + for kind in self.sort_kinds: + assert_raises(TypeError, arr.sort, kind=kind) + # gh-3879 + + class Raiser: + def raises_anything(*args, **kwargs): + raise TypeError("SOMETHING ERRORED") + __eq__ = __ne__ = __lt__ = __gt__ = __ge__ = __le__ = raises_anything + arr = np.array([[Raiser(), n] for n in range(10)]).reshape(-1) + np.random.shuffle(arr) + for kind in self.sort_kinds: + assert_raises(TypeError, arr.sort, kind=kind) + + def test_sort_degraded(self): + # test degraded dataset would take minutes to run with normal qsort + d = np.arange(1000000) + do = d.copy() + x = d + # create a median of 3 killer where each median is the sorted second + # last element of the quicksort partition + while x.size > 3: + mid = x.size // 2 + x[mid], x[-2] = x[-2], x[mid] + x = x[:-2] + + assert_equal(np.sort(d), do) + assert_equal(d[np.argsort(d)], do) + + def test_copy(self): + def assert_fortran(arr): + assert_(arr.flags.fortran) + assert_(arr.flags.f_contiguous) + assert_(not arr.flags.c_contiguous) + + def assert_c(arr): + assert_(not arr.flags.fortran) + assert_(not arr.flags.f_contiguous) + assert_(arr.flags.c_contiguous) + + a = np.empty((2, 2), order='F') + # Test copying a Fortran array + assert_c(a.copy()) + assert_c(a.copy('C')) + assert_fortran(a.copy('F')) + assert_fortran(a.copy('A')) + + # Now test starting with a C array. + a = np.empty((2, 2), order='C') + assert_c(a.copy()) + assert_c(a.copy('C')) + assert_fortran(a.copy('F')) + assert_c(a.copy('A')) + + @pytest.mark.parametrize("dtype", ['O', np.int32, 'i,O']) + def test__deepcopy__(self, dtype): + # Force the entry of NULLs into array + a = np.empty(4, dtype=dtype) + ctypes.memset(a.ctypes.data, 0, a.nbytes) + + # Ensure no error is raised, see gh-21833 + b = a.__deepcopy__({}) + + a[0] = 42 + with pytest.raises(AssertionError): + assert_array_equal(a, b) + + def test__deepcopy___void_scalar(self): + # see comments in gh-29643 + value = np.void('Rex', dtype=[('name', 'U10')]) + value_deepcopy = value.__deepcopy__(None) + value[0] = None + assert value_deepcopy[0] == 'Rex' + + @pytest.mark.parametrize("sctype", [np.int64, np.float32, np.float64]) + def test__deepcopy__scalar(self, sctype): + # test optimization from gh-29656 + value = sctype(1.1) + value_deepcopy = value.__deepcopy__(None) + assert value is value_deepcopy + + def test__deepcopy__catches_failure(self): + class MyObj: + def __deepcopy__(self, *args, **kwargs): + raise RuntimeError + + arr = np.array([1, MyObj(), 3], dtype='O') + with pytest.raises(RuntimeError): + arr.__deepcopy__({}) + + def test_sort_order(self): + # Test sorting an array with fields + x1 = np.array([21, 32, 14]) + x2 = np.array(['my', 'first', 'name']) + x3 = np.array([3.1, 4.5, 6.2]) + r = np.rec.fromarrays([x1, x2, x3], names='id,word,number') + + r.sort(order=['id']) + assert_equal(r.id, np.array([14, 21, 32])) + assert_equal(r.word, np.array(['name', 'my', 'first'])) + assert_equal(r.number, np.array([6.2, 3.1, 4.5])) + + r.sort(order=['word']) + assert_equal(r.id, np.array([32, 21, 14])) + assert_equal(r.word, np.array(['first', 'my', 'name'])) + assert_equal(r.number, np.array([4.5, 3.1, 6.2])) + + r.sort(order=['number']) + assert_equal(r.id, np.array([21, 32, 14])) + assert_equal(r.word, np.array(['my', 'first', 'name'])) + assert_equal(r.number, np.array([3.1, 4.5, 6.2])) + + assert_raises_regex(ValueError, 'duplicate', + lambda: r.sort(order=['id', 'id'])) + + if sys.byteorder == 'little': + strtype = '>i2' + else: + strtype = '': + for dt in np.typecodes['Complex']: + arr = np.array([1 + 3.j, 2 + 2.j, 3 + 1.j], dtype=endianness + dt) + msg = f'byte-swapped complex argsort, dtype={dt}' + assert_equal(arr.argsort(), + np.arange(len(arr), dtype=np.intp), msg) + + # test string argsorts. + s = 'aaaaaaaa' + a = np.array([s + chr(i) for i in range(101)]) + b = a[::-1].copy() + r = np.arange(101) + rr = r[::-1] + for kind in self.sort_kinds: + msg = f"string argsort, kind={kind}" + assert_equal(a.copy().argsort(kind=kind), r, msg) + assert_equal(b.copy().argsort(kind=kind), rr, msg) + + # test unicode argsorts. + s = 'aaaaaaaa' + a = np.array([s + chr(i) for i in range(101)], dtype=np.str_) + b = a[::-1] + r = np.arange(101) + rr = r[::-1] + for kind in self.sort_kinds: + msg = f"unicode argsort, kind={kind}" + assert_equal(a.copy().argsort(kind=kind), r, msg) + assert_equal(b.copy().argsort(kind=kind), rr, msg) + + # test object array argsorts. + a = np.empty((101,), dtype=object) + a[:] = list(range(101)) + b = a[::-1] + r = np.arange(101) + rr = r[::-1] + for kind in self.sort_kinds: + msg = f"object argsort, kind={kind}" + assert_equal(a.copy().argsort(kind=kind), r, msg) + assert_equal(b.copy().argsort(kind=kind), rr, msg) + + # test structured array argsorts. + dt = np.dtype([('f', float), ('i', int)]) + a = np.array([(i, i) for i in range(101)], dtype=dt) + b = a[::-1] + r = np.arange(101) + rr = r[::-1] + for kind in self.sort_kinds: + msg = f"structured array argsort, kind={kind}" + assert_equal(a.copy().argsort(kind=kind), r, msg) + assert_equal(b.copy().argsort(kind=kind), rr, msg) + + # test datetime64 argsorts. + a = np.arange(0, 101, dtype='datetime64[D]') + b = a[::-1] + r = np.arange(101) + rr = r[::-1] + for kind in ['q', 'h', 'm']: + msg = f"datetime64 argsort, kind={kind}" + assert_equal(a.copy().argsort(kind=kind), r, msg) + assert_equal(b.copy().argsort(kind=kind), rr, msg) + + # test timedelta64 argsorts. + a = np.arange(0, 101, dtype='timedelta64[D]') + b = a[::-1] + r = np.arange(101) + rr = r[::-1] + for kind in ['q', 'h', 'm']: + msg = f"timedelta64 argsort, kind={kind}" + assert_equal(a.copy().argsort(kind=kind), r, msg) + assert_equal(b.copy().argsort(kind=kind), rr, msg) + + # check axis handling. This should be the same for all type + # specific argsorts, so we only check it for one type and one kind + a = np.array([[3, 2], [1, 0]]) + b = np.array([[1, 1], [0, 0]]) + c = np.array([[1, 0], [1, 0]]) + assert_equal(a.copy().argsort(axis=0), b) + assert_equal(a.copy().argsort(axis=1), c) + assert_equal(a.copy().argsort(), c) + + # check axis handling for multidimensional empty arrays + a = np.array([]).reshape((3, 2, 1, 0)) + for axis in range(-a.ndim, a.ndim): + msg = f'test empty array argsort with axis={axis}' + assert_equal(np.argsort(a, axis=axis), + np.zeros_like(a, dtype=np.intp), msg) + msg = 'test empty array argsort with axis=None' + assert_equal(np.argsort(a, axis=None), + np.zeros_like(a.ravel(), dtype=np.intp), msg) + + # check that stable argsorts are stable + r = np.arange(100) + # scalars + a = np.zeros(100) + assert_equal(a.argsort(kind='m'), r) + # complex + a = np.zeros(100, dtype=complex) + assert_equal(a.argsort(kind='m'), r) + # string + a = np.array(['aaaaaaaaa' for i in range(100)]) + assert_equal(a.argsort(kind='m'), r) + # unicode + a = np.array(['aaaaaaaaa' for i in range(100)], dtype=np.str_) + assert_equal(a.argsort(kind='m'), r) + + with assert_raises_regex( + ValueError, + "`kind` and keyword parameters can't be provided at the same time" + ): + np.argsort(a, kind="stable", stable=True) + + def test_sort_unicode_kind(self): + d = np.arange(10) + k = b'\xc3\xa4'.decode("UTF8") + assert_raises(ValueError, d.sort, kind=k) + assert_raises(ValueError, d.argsort, kind=k) + + @pytest.mark.parametrize('a', [ + np.array([0, 1, np.nan], dtype=np.float16), + np.array([0, 1, np.nan], dtype=np.float32), + np.array([0, 1, np.nan]), + ]) + def test_searchsorted_floats(self, a): + # test for floats arrays containing nans. Explicitly test + # half, single, and double precision floats to verify that + # the NaN-handling is correct. + msg = f"Test real ({a.dtype}) searchsorted with nans, side='l'" + b = a.searchsorted(a, side='left') + assert_equal(b, np.arange(3), msg) + msg = f"Test real ({a.dtype}) searchsorted with nans, side='r'" + b = a.searchsorted(a, side='right') + assert_equal(b, np.arange(1, 4), msg) + # check keyword arguments + a.searchsorted(v=1) + x = np.array([0, 1, np.nan], dtype='float32') + y = np.searchsorted(x, x[-1]) + assert_equal(y, 2) + + def test_searchsorted_complex(self): + # test for complex arrays containing nans. + # The search sorted routines use the compare functions for the + # array type, so this checks if that is consistent with the sort + # order. + # check double complex + a = np.zeros(9, dtype=np.complex128) + a.real += [0, 0, 1, 1, 0, 1, np.nan, np.nan, np.nan] + a.imag += [0, 1, 0, 1, np.nan, np.nan, 0, 1, np.nan] + msg = "Test complex searchsorted with nans, side='l'" + b = a.searchsorted(a, side='left') + assert_equal(b, np.arange(9), msg) + msg = "Test complex searchsorted with nans, side='r'" + b = a.searchsorted(a, side='right') + assert_equal(b, np.arange(1, 10), msg) + msg = "Test searchsorted with little endian, side='l'" + a = np.array([0, 128], dtype=' p[:, i]).all(), + msg="%d: %r < %r" % (i, p[:, i], p[:, i + 1:].T)) + for row in range(p.shape[0]): + self.assert_partitioned(p[row], [i]) + self.assert_partitioned(parg[row], [i]) + + p = np.partition(d0, i, axis=0, kind=k) + parg = d0[np.argpartition(d0, i, axis=0, kind=k), + np.arange(d0.shape[1])[None, :]] + aae(p[i, :], np.array([i] * d1.shape[0], dtype=dt)) + # array_less does not seem to work right + at((p[:i, :] <= p[i, :]).all(), + msg="%d: %r <= %r" % (i, p[i, :], p[:i, :])) + at((p[i + 1:, :] > p[i, :]).all(), + msg="%d: %r < %r" % (i, p[i, :], p[:, i + 1:])) + for col in range(p.shape[1]): + self.assert_partitioned(p[:, col], [i]) + self.assert_partitioned(parg[:, col], [i]) + + # check inplace + dc = d.copy() + dc.partition(i, kind=k) + assert_equal(dc, np.partition(d, i, kind=k)) + dc = d0.copy() + dc.partition(i, axis=0, kind=k) + assert_equal(dc, np.partition(d0, i, axis=0, kind=k)) + dc = d1.copy() + dc.partition(i, axis=1, kind=k) + assert_equal(dc, np.partition(d1, i, axis=1, kind=k)) + + def assert_partitioned(self, d, kth): + prev = 0 + for k in np.sort(kth): + assert_array_compare(operator.__le__, d[prev:k], d[k], + err_msg='kth %d' % k) + assert_((d[k:] >= d[k]).all(), + msg="kth %d, %r not greater equal %r" % (k, d[k:], d[k])) + prev = k + 1 + + def test_partition_iterative(self): + d = np.arange(17) + kth = (0, 1, 2, 429, 231) + assert_raises(ValueError, d.partition, kth) + assert_raises(ValueError, d.argpartition, kth) + d = np.arange(10).reshape((2, 5)) + assert_raises(ValueError, d.partition, kth, axis=0) + assert_raises(ValueError, d.partition, kth, axis=1) + assert_raises(ValueError, np.partition, d, kth, axis=1) + assert_raises(ValueError, np.partition, d, kth, axis=None) + + d = np.array([3, 4, 2, 1]) + p = np.partition(d, (0, 3)) + self.assert_partitioned(p, (0, 3)) + self.assert_partitioned(d[np.argpartition(d, (0, 3))], (0, 3)) + + assert_array_equal(p, np.partition(d, (-3, -1))) + assert_array_equal(p, d[np.argpartition(d, (-3, -1))]) + + d = np.arange(17) + np.random.shuffle(d) + d.partition(range(d.size)) + assert_array_equal(np.arange(17), d) + np.random.shuffle(d) + assert_array_equal(np.arange(17), d[d.argpartition(range(d.size))]) + + # test unsorted kth + d = np.arange(17) + np.random.shuffle(d) + keys = np.array([1, 3, 8, -2]) + np.random.shuffle(d) + p = np.partition(d, keys) + self.assert_partitioned(p, keys) + p = d[np.argpartition(d, keys)] + self.assert_partitioned(p, keys) + np.random.shuffle(keys) + assert_array_equal(np.partition(d, keys), p) + assert_array_equal(d[np.argpartition(d, keys)], p) + + # equal kth + d = np.arange(20)[::-1] + self.assert_partitioned(np.partition(d, [5] * 4), [5]) + self.assert_partitioned(np.partition(d, [5] * 4 + [6, 13]), + [5] * 4 + [6, 13]) + self.assert_partitioned(d[np.argpartition(d, [5] * 4)], [5]) + self.assert_partitioned(d[np.argpartition(d, [5] * 4 + [6, 13])], + [5] * 4 + [6, 13]) + + d = np.arange(12) + np.random.shuffle(d) + d1 = np.tile(np.arange(12), (4, 1)) + map(np.random.shuffle, d1) + d0 = np.transpose(d1) + + kth = (1, 6, 7, -1) + p = np.partition(d1, kth, axis=1) + pa = d1[np.arange(d1.shape[0])[:, None], + d1.argpartition(kth, axis=1)] + assert_array_equal(p, pa) + for i in range(d1.shape[0]): + self.assert_partitioned(p[i, :], kth) + p = np.partition(d0, kth, axis=0) + pa = d0[np.argpartition(d0, kth, axis=0), + np.arange(d0.shape[1])[None, :]] + assert_array_equal(p, pa) + for i in range(d0.shape[1]): + self.assert_partitioned(p[:, i], kth) + + def test_partition_cdtype(self): + d = np.array([('Galahad', 1.7, 38), ('Arthur', 1.8, 41), + ('Lancelot', 1.9, 38)], + dtype=[('name', '|S10'), ('height', ' (numpy ufunc, has_in_place_version, preferred_dtype) + ops = { + 'add': (np.add, True, float), + 'sub': (np.subtract, True, float), + 'mul': (np.multiply, True, float), + 'truediv': (np.true_divide, True, float), + 'floordiv': (np.floor_divide, True, float), + 'mod': (np.remainder, True, float), + 'divmod': (np.divmod, False, float), + 'pow': (np.power, True, int), + 'lshift': (np.left_shift, True, int), + 'rshift': (np.right_shift, True, int), + 'and': (np.bitwise_and, True, int), + 'xor': (np.bitwise_xor, True, int), + 'or': (np.bitwise_or, True, int), + 'matmul': (np.matmul, True, float), + # 'ge': (np.less_equal, False), + # 'gt': (np.less, False), + # 'le': (np.greater_equal, False), + # 'lt': (np.greater, False), + # 'eq': (np.equal, False), + # 'ne': (np.not_equal, False), + } + + class Coerced(Exception): + pass + + def array_impl(self): + raise Coerced + + def op_impl(self, other): + return "forward" + + def rop_impl(self, other): + return "reverse" + + def iop_impl(self, other): + return "in-place" + + def array_ufunc_impl(self, ufunc, method, *args, **kwargs): + return ("__array_ufunc__", ufunc, method, args, kwargs) + + # Create an object with the given base, in the given module, with a + # bunch of placeholder __op__ methods, and optionally a + # __array_ufunc__ and __array_priority__. + def make_obj(base, array_priority=False, array_ufunc=False, + alleged_module="__main__"): + class_namespace = {"__array__": array_impl} + if array_priority is not False: + class_namespace["__array_priority__"] = array_priority + for op in ops: + class_namespace[f"__{op}__"] = op_impl + class_namespace[f"__r{op}__"] = rop_impl + class_namespace[f"__i{op}__"] = iop_impl + if array_ufunc is not False: + class_namespace["__array_ufunc__"] = array_ufunc + eval_namespace = {"base": base, + "class_namespace": class_namespace, + "__name__": alleged_module, + } + MyType = eval("type('MyType', (base,), class_namespace)", + eval_namespace) + if issubclass(MyType, np.ndarray): + # Use this range to avoid special case weirdnesses around + # divide-by-0, pow(x, 2), overflow due to pow(big, big), etc. + return np.arange(3, 7).reshape(2, 2).view(MyType) + else: + return MyType() + + def check(obj, binop_override_expected, ufunc_override_expected, + inplace_override_expected, check_scalar=True): + for op, (ufunc, has_inplace, dtype) in ops.items(): + err_msg = ('op: %s, ufunc: %s, has_inplace: %s, dtype: %s' + % (op, ufunc, has_inplace, dtype)) + check_objs = [np.arange(3, 7, dtype=dtype).reshape(2, 2)] + if check_scalar: + check_objs.append(check_objs[0][0]) + for arr in check_objs: + arr_method = getattr(arr, f"__{op}__") + + def first_out_arg(result): + if op == "divmod": + assert_(isinstance(result, tuple)) + return result[0] + else: + return result + + # arr __op__ obj + if binop_override_expected: + assert_equal(arr_method(obj), NotImplemented, err_msg) + elif ufunc_override_expected: + assert_equal(arr_method(obj)[0], "__array_ufunc__", + err_msg) + elif (isinstance(obj, np.ndarray) and + (type(obj).__array_ufunc__ is + np.ndarray.__array_ufunc__)): + # __array__ gets ignored + res = first_out_arg(arr_method(obj)) + assert_(res.__class__ is obj.__class__, err_msg) + else: + assert_raises((TypeError, Coerced), + arr_method, obj, err_msg=err_msg) + # obj __op__ arr + arr_rmethod = getattr(arr, f"__r{op}__") + if ufunc_override_expected: + res = arr_rmethod(obj) + assert_equal(res[0], "__array_ufunc__", + err_msg=err_msg) + assert_equal(res[1], ufunc, err_msg=err_msg) + elif (isinstance(obj, np.ndarray) and + (type(obj).__array_ufunc__ is + np.ndarray.__array_ufunc__)): + # __array__ gets ignored + res = first_out_arg(arr_rmethod(obj)) + assert_(res.__class__ is obj.__class__, err_msg) + else: + # __array_ufunc__ = "asdf" creates a TypeError + assert_raises((TypeError, Coerced), + arr_rmethod, obj, err_msg=err_msg) + + # arr __iop__ obj + # array scalars don't have in-place operators + if has_inplace and isinstance(arr, np.ndarray): + arr_imethod = getattr(arr, f"__i{op}__") + if inplace_override_expected: + assert_equal(arr_method(obj), NotImplemented, + err_msg=err_msg) + elif ufunc_override_expected: + res = arr_imethod(obj) + assert_equal(res[0], "__array_ufunc__", err_msg) + assert_equal(res[1], ufunc, err_msg) + assert_(type(res[-1]["out"]) is tuple, err_msg) + assert_(res[-1]["out"][0] is arr, err_msg) + elif (isinstance(obj, np.ndarray) and + (type(obj).__array_ufunc__ is + np.ndarray.__array_ufunc__)): + # __array__ gets ignored + assert_(arr_imethod(obj) is arr, err_msg) + else: + assert_raises((TypeError, Coerced), + arr_imethod, obj, + err_msg=err_msg) + + op_fn = getattr(operator, op, None) + if op_fn is None: + op_fn = getattr(operator, op + "_", None) + if op_fn is None: + op_fn = getattr(builtins, op) + assert_equal(op_fn(obj, arr), "forward", err_msg) + if not isinstance(obj, np.ndarray): + if binop_override_expected: + assert_equal(op_fn(arr, obj), "reverse", err_msg) + elif ufunc_override_expected: + assert_equal(op_fn(arr, obj)[0], "__array_ufunc__", + err_msg) + if ufunc_override_expected: + assert_equal(ufunc(obj, arr)[0], "__array_ufunc__", + err_msg) + + # No array priority, no array_ufunc -> nothing called + check(make_obj(object), False, False, False) + # Negative array priority, no array_ufunc -> nothing called + # (has to be very negative, because scalar priority is -1000000.0) + check(make_obj(object, array_priority=-2**30), False, False, False) + # Positive array priority, no array_ufunc -> binops and iops only + check(make_obj(object, array_priority=1), True, False, True) + # ndarray ignores array_priority for ndarray subclasses + check(make_obj(np.ndarray, array_priority=1), False, False, False, + check_scalar=False) + # Positive array_priority and array_ufunc -> array_ufunc only + check(make_obj(object, array_priority=1, + array_ufunc=array_ufunc_impl), False, True, False) + check(make_obj(np.ndarray, array_priority=1, + array_ufunc=array_ufunc_impl), False, True, False) + # array_ufunc set to None -> defer binops only + check(make_obj(object, array_ufunc=None), True, False, False) + check(make_obj(np.ndarray, array_ufunc=None), True, False, False, + check_scalar=False) + + @pytest.mark.parametrize("priority", [None, "runtime error"]) + def test_ufunc_binop_bad_array_priority(self, priority): + # Mainly checks that this does not crash. The second array has a lower + # priority than -1 ("error value"). If the __radd__ actually exists, + # bad things can happen (I think via the scalar paths). + # In principle both of these can probably just be errors in the future. + class BadPriority: + @property + def __array_priority__(self): + if priority == "runtime error": + raise RuntimeError("RuntimeError in __array_priority__!") + return priority + + def __radd__(self, other): + return "result" + + class LowPriority(np.ndarray): + __array_priority__ = -1000 + + # Priority failure uses the same as scalars (smaller -1000). So the + # LowPriority wins with 'result' for each element (inner operation). + res = np.arange(3).view(LowPriority) + BadPriority() + assert res.shape == (3,) + assert res[0] == 'result' + + @pytest.mark.parametrize("scalar", [ + np.longdouble(1), np.timedelta64(120, 'm')]) + @pytest.mark.parametrize("op", [operator.add, operator.xor]) + def test_scalar_binop_guarantees_ufunc(self, scalar, op): + # Test that __array_ufunc__ will always cause ufunc use even when + # we have to protect some other calls from recursing (see gh-26904). + class SomeClass: + def __array_ufunc__(self, ufunc, method, *inputs, **kw): + return "result" + + assert SomeClass() + scalar == "result" + assert scalar + SomeClass() == "result" + + def test_ufunc_override_normalize_signature(self): + # gh-5674 + class SomeClass: + def __array_ufunc__(self, ufunc, method, *inputs, **kw): + return kw + + a = SomeClass() + kw = np.add(a, [1]) + assert_('sig' not in kw and 'signature' not in kw) + kw = np.add(a, [1], sig='ii->i') + assert_('sig' not in kw and 'signature' in kw) + assert_equal(kw['signature'], 'ii->i') + kw = np.add(a, [1], signature='ii->i') + assert_('sig' not in kw and 'signature' in kw) + assert_equal(kw['signature'], 'ii->i') + + def test_array_ufunc_index(self): + # Check that index is set appropriately, also if only an output + # is passed on (latter is another regression tests for github bug 4753) + # This also checks implicitly that 'out' is always a tuple. + class CheckIndex: + def __array_ufunc__(self, ufunc, method, *inputs, **kw): + for i, a in enumerate(inputs): + if a is self: + return i + # calls below mean we must be in an output. + for j, a in enumerate(kw['out']): + if a is self: + return (j,) + + a = CheckIndex() + dummy = np.arange(2.) + # 1 input, 1 output + assert_equal(np.sin(a), 0) + assert_equal(np.sin(dummy, a), (0,)) + assert_equal(np.sin(dummy, out=a), (0,)) + assert_equal(np.sin(dummy, out=(a,)), (0,)) + assert_equal(np.sin(a, a), 0) + assert_equal(np.sin(a, out=a), 0) + assert_equal(np.sin(a, out=(a,)), 0) + # 1 input, 2 outputs + assert_equal(np.modf(dummy, a), (0,)) + assert_equal(np.modf(dummy, None, a), (1,)) + assert_equal(np.modf(dummy, dummy, a), (1,)) + assert_equal(np.modf(dummy, out=(a, None)), (0,)) + assert_equal(np.modf(dummy, out=(a, dummy)), (0,)) + assert_equal(np.modf(dummy, out=(None, a)), (1,)) + assert_equal(np.modf(dummy, out=(dummy, a)), (1,)) + assert_equal(np.modf(a, out=(dummy, a)), 0) + with assert_raises(TypeError): + # Out argument must be tuple, since there are multiple outputs + np.modf(dummy, out=a) + + assert_raises(ValueError, np.modf, dummy, out=(a,)) + + # 2 inputs, 1 output + assert_equal(np.add(a, dummy), 0) + assert_equal(np.add(dummy, a), 1) + assert_equal(np.add(dummy, dummy, a), (0,)) + assert_equal(np.add(dummy, a, a), 1) + assert_equal(np.add(dummy, dummy, out=a), (0,)) + assert_equal(np.add(dummy, dummy, out=(a,)), (0,)) + assert_equal(np.add(a, dummy, out=a), 0) + + def test_out_override(self): + # regression test for github bug 4753 + class OutClass(np.ndarray): + def __array_ufunc__(self, ufunc, method, *inputs, **kw): + if 'out' in kw: + tmp_kw = kw.copy() + tmp_kw.pop('out') + func = getattr(ufunc, method) + kw['out'][0][...] = func(*inputs, **tmp_kw) + + A = np.array([0]).view(OutClass) + B = np.array([5]) + C = np.array([6]) + np.multiply(C, B, A) + assert_equal(A[0], 30) + assert_(isinstance(A, OutClass)) + A[0] = 0 + np.multiply(C, B, out=A) + assert_equal(A[0], 30) + assert_(isinstance(A, OutClass)) + + def test_pow_array_object_dtype(self): + # test pow on arrays of object dtype + class SomeClass: + def __init__(self, num=None): + self.num = num + + # want to ensure a fast pow path is not taken + def __mul__(self, other): + raise AssertionError('__mul__ should not be called') + + def __truediv__(self, other): + raise AssertionError('__truediv__ should not be called') + + def __pow__(self, exp): + return SomeClass(num=self.num ** exp) + + def __eq__(self, other): + if isinstance(other, SomeClass): + return self.num == other.num + + __rpow__ = __pow__ + + def pow_for(exp, arr): + return np.array([x ** exp for x in arr]) + + obj_arr = np.array([SomeClass(1), SomeClass(2), SomeClass(3)]) + + assert_equal(obj_arr ** 0.5, pow_for(0.5, obj_arr)) + assert_equal(obj_arr ** 0, pow_for(0, obj_arr)) + assert_equal(obj_arr ** 1, pow_for(1, obj_arr)) + assert_equal(obj_arr ** -1, pow_for(-1, obj_arr)) + assert_equal(obj_arr ** 2, pow_for(2, obj_arr)) + + def test_pow_calls_square_structured_dtype(self): + # gh-29388 + dt = np.dtype([('a', 'i4'), ('b', 'i4')]) + a = np.array([(1, 2), (3, 4)], dtype=dt) + with pytest.raises(TypeError, match="ufunc 'square' not supported"): + a ** 2 + + def test_pos_array_ufunc_override(self): + class A(np.ndarray): + def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): + return getattr(ufunc, method)(*[i.view(np.ndarray) for + i in inputs], **kwargs) + tst = np.array('foo').view(A) + with assert_raises(TypeError): + +tst + + +class TestTemporaryElide: + # elision is only triggered on relatively large arrays + + def test_extension_incref_elide(self): + # test extension (e.g. cython) calling PyNumber_* slots without + # increasing the reference counts + # + # def incref_elide(a): + # d = input.copy() # refcount 1 + # return d, d + d # PyNumber_Add without increasing refcount + from numpy._core._multiarray_tests import incref_elide + d = np.ones(100000) + orig, res = incref_elide(d) + d + d + # the return original should not be changed to an inplace operation + assert_array_equal(orig, d) + assert_array_equal(res, d + d) + + def test_extension_incref_elide_stack(self): + # scanning if the refcount == 1 object is on the python stack to check + # that we are called directly from python is flawed as object may still + # be above the stack pointer and we have no access to the top of it + # + # def incref_elide_l(d): + # return l[4] + l[4] # PyNumber_Add without increasing refcount + from numpy._core._multiarray_tests import incref_elide_l + # padding with 1 makes sure the object on the stack is not overwritten + l = [1, 1, 1, 1, np.ones(100000)] + res = incref_elide_l(l) + # the return original should not be changed to an inplace operation + assert_array_equal(l[4], np.ones(100000)) + assert_array_equal(res, l[4] + l[4]) + + def test_temporary_with_cast(self): + # check that we don't elide into a temporary which would need casting + d = np.ones(200000, dtype=np.int64) + r = ((d + d) + np.array(2**222, dtype='O')) + assert_equal(r.dtype, np.dtype('O')) + + r = ((d + d) / 2) + assert_equal(r.dtype, np.dtype('f8')) + + r = np.true_divide((d + d), 2) + assert_equal(r.dtype, np.dtype('f8')) + + r = ((d + d) / 2.) + assert_equal(r.dtype, np.dtype('f8')) + + r = ((d + d) // 2) + assert_equal(r.dtype, np.dtype(np.int64)) + + # commutative elision into the astype result + f = np.ones(100000, dtype=np.float32) + assert_equal(((f + f) + f.astype(np.float64)).dtype, np.dtype('f8')) + + # no elision into lower type + d = f.astype(np.float64) + assert_equal(((f + f) + d).dtype, d.dtype) + l = np.ones(100000, dtype=np.longdouble) + assert_equal(((d + d) + l).dtype, l.dtype) + + # test unary abs with different output dtype + for dt in (np.complex64, np.complex128, np.clongdouble): + c = np.ones(100000, dtype=dt) + r = abs(c * 2.0) + assert_equal(r.dtype, np.dtype('f%d' % (c.itemsize // 2))) + + def test_elide_broadcast(self): + # test no elision on broadcast to higher dimension + # only triggers elision code path in debug mode as triggering it in + # normal mode needs 256kb large matching dimension, so a lot of memory + d = np.ones((2000, 1), dtype=int) + b = np.ones((2000), dtype=bool) + r = (1 - d) + b + assert_equal(r, 1) + assert_equal(r.shape, (2000, 2000)) + + def test_elide_scalar(self): + # check inplace op does not create ndarray from scalars + a = np.bool() + assert_(type(~(a & a)) is np.bool) + + def test_elide_scalar_readonly(self): + # The imaginary part of a real array is readonly. This needs to go + # through fast_scalar_power which is only called for powers of + # +1, -1, 0, 0.5, and 2, so use 2. Also need valid refcount for + # elision which can be gotten for the imaginary part of a real + # array. Should not error. + a = np.empty(100000, dtype=np.float64) + a.imag ** 2 + + def test_elide_readonly(self): + # don't try to elide readonly temporaries + r = np.asarray(np.broadcast_to(np.zeros(1), 100000).flat) * 0.0 + assert_equal(r, 0) + + def test_elide_updateifcopy(self): + a = np.ones(2**20)[::2] + b = a.flat.__array__() + 1 + del b + assert_equal(a, 1) + + +class TestCAPI: + def test_IsPythonScalar(self): + from numpy._core._multiarray_tests import IsPythonScalar + assert_(IsPythonScalar(b'foobar')) + assert_(IsPythonScalar(1)) + assert_(IsPythonScalar(2**80)) + assert_(IsPythonScalar(2.)) + assert_(IsPythonScalar("a")) + + @pytest.mark.parametrize("converter", + [_multiarray_tests.run_scalar_intp_converter, + _multiarray_tests.run_scalar_intp_from_sequence]) + def test_intp_sequence_converters(self, converter): + # Test simple values (-1 is special for error return paths) + assert converter(10) == (10,) + assert converter(-1) == (-1,) + # A 0-D array looks a bit like a sequence but must take the integer + # path: + assert converter(np.array(123)) == (123,) + # Test simple sequences (intp_from_sequence only supports length 1): + assert converter((10,)) == (10,) + assert converter(np.array([11])) == (11,) + + @pytest.mark.parametrize("converter", + [_multiarray_tests.run_scalar_intp_converter, + _multiarray_tests.run_scalar_intp_from_sequence]) + @pytest.mark.skipif(IS_PYPY and sys.implementation.version <= (7, 3, 8), + reason="PyPy bug in error formatting") + def test_intp_sequence_converters_errors(self, converter): + with pytest.raises(TypeError, + match="expected a sequence of integers or a single integer, "): + converter(object()) + with pytest.raises(TypeError, + match="expected a sequence of integers or a single integer, " + "got '32.0'"): + converter(32.) + with pytest.raises(TypeError, + match="'float' object cannot be interpreted as an integer"): + converter([32.]) + with pytest.raises(ValueError, + match="Maximum allowed dimension"): + # These converters currently convert overflows to a ValueError + converter(2**64) + + @pytest.mark.parametrize( + "entry_point", + [ + module + item + for item in ("sin", "strings.str_len", "fft._pocketfft_umath.ifft") + for module in ("", "numpy:") + ] + [ + "numpy.strings:str_len", + "functools:reduce", + "functools:reduce.__doc__" + ] + ) + def test_import_entry_point(self, entry_point): + modname, _, items = entry_point.rpartition(":") + if modname: + module = obj = importlib.import_module(modname) + else: + module = np + exp = functools.reduce(getattr, items.split("."), module) + got = _multiarray_tests.npy_import_entry_point(entry_point) + assert got == exp + + @pytest.mark.parametrize( + "entry_point", + ["sin.", "numpy:", "numpy:sin:__call__", "numpy.sin:__call__."] + ) + def test_import_entry_point_errors(self, entry_point): + # Don't really care about precise error. + with pytest.raises((ImportError, AttributeError)): + _multiarray_tests.npy_import_entry_point(entry_point) + + +class TestSubscripting: + def test_test_zero_rank(self): + x = np.array([1, 2, 3]) + assert_(isinstance(x[0], np.int_)) + assert_(type(x[0, ...]) is np.ndarray) + + +class TestPickling: + @pytest.mark.skipif(pickle.HIGHEST_PROTOCOL >= 5, + reason=('this tests the error messages when trying to' + 'protocol 5 although it is not available')) + def test_correct_protocol5_error_message(self): + array = np.arange(10) + + def test_record_array_with_object_dtype(self): + my_object = object() + + arr_with_object = np.array( + [(my_object, 1, 2.0)], + dtype=[('a', object), ('b', int), ('c', float)]) + arr_without_object = np.array( + [('xxx', 1, 2.0)], + dtype=[('a', str), ('b', int), ('c', float)]) + + for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): + depickled_arr_with_object = pickle.loads( + pickle.dumps(arr_with_object, protocol=proto)) + depickled_arr_without_object = pickle.loads( + pickle.dumps(arr_without_object, protocol=proto)) + + assert_equal(arr_with_object.dtype, + depickled_arr_with_object.dtype) + assert_equal(arr_without_object.dtype, + depickled_arr_without_object.dtype) + + @pytest.mark.skipif(pickle.HIGHEST_PROTOCOL < 5, + reason="requires pickle protocol 5") + def test_f_contiguous_array(self): + f_contiguous_array = np.array([[1, 2, 3], [4, 5, 6]], order='F') + buffers = [] + + # When using pickle protocol 5, Fortran-contiguous arrays can be + # serialized using out-of-band buffers + bytes_string = pickle.dumps(f_contiguous_array, protocol=5, + buffer_callback=buffers.append) + + assert len(buffers) > 0 + + depickled_f_contiguous_array = pickle.loads(bytes_string, + buffers=buffers) + + assert_equal(f_contiguous_array, depickled_f_contiguous_array) + + @pytest.mark.skipif(pickle.HIGHEST_PROTOCOL < 5, reason="requires pickle protocol 5") + @pytest.mark.parametrize('transposed_contiguous_array', + [np.random.default_rng(42).random((2, 3, 4)).transpose((1, 0, 2)), + np.random.default_rng(42).random((2, 3, 4, 5)).transpose((1, 3, 0, 2))] + + [np.random.default_rng(42).random(np.arange(2, 7)).transpose(np.random.permutation(5)) for _ in range(3)]) + def test_transposed_contiguous_array(self, transposed_contiguous_array): + buffers = [] + # When using pickle protocol 5, arrays which can be transposed to c_contiguous + # can be serialized using out-of-band buffers + bytes_string = pickle.dumps(transposed_contiguous_array, protocol=5, + buffer_callback=buffers.append) + + assert len(buffers) > 0 + + depickled_transposed_contiguous_array = pickle.loads(bytes_string, + buffers=buffers) + + assert_equal(transposed_contiguous_array, depickled_transposed_contiguous_array) + + @pytest.mark.skipif(pickle.HIGHEST_PROTOCOL < 5, reason="requires pickle protocol 5") + def test_load_legacy_pkl_protocol5(self): + # legacy byte strs are dumped in 2.2.1 + c_contiguous_dumped = b'\x80\x05\x95\x90\x00\x00\x00\x00\x00\x00\x00\x8c\x13numpy._core.numeric\x94\x8c\x0b_frombuffer\x94\x93\x94(\x96\x18\x00\x00\x00\x00\x00\x00\x00\x00\x01\x02\x03\x04\x05\x06\x07\x08\t\n\x0b\x0c\r\x0e\x0f\x10\x11\x12\x13\x14\x15\x16\x17\x94\x8c\x05numpy\x94\x8c\x05dtype\x94\x93\x94\x8c\x02u1\x94\x89\x88\x87\x94R\x94(K\x03\x8c\x01|\x94NNNJ\xff\xff\xff\xffJ\xff\xff\xff\xffK\x00t\x94bK\x03K\x04K\x02\x87\x94\x8c\x01C\x94t\x94R\x94.' # noqa: E501 + f_contiguous_dumped = b'\x80\x05\x95\x90\x00\x00\x00\x00\x00\x00\x00\x8c\x13numpy._core.numeric\x94\x8c\x0b_frombuffer\x94\x93\x94(\x96\x18\x00\x00\x00\x00\x00\x00\x00\x00\x01\x02\x03\x04\x05\x06\x07\x08\t\n\x0b\x0c\r\x0e\x0f\x10\x11\x12\x13\x14\x15\x16\x17\x94\x8c\x05numpy\x94\x8c\x05dtype\x94\x93\x94\x8c\x02u1\x94\x89\x88\x87\x94R\x94(K\x03\x8c\x01|\x94NNNJ\xff\xff\xff\xffJ\xff\xff\xff\xffK\x00t\x94bK\x03K\x04K\x02\x87\x94\x8c\x01F\x94t\x94R\x94.' # noqa: E501 + transposed_contiguous_dumped = b'\x80\x05\x95\xa5\x00\x00\x00\x00\x00\x00\x00\x8c\x16numpy._core.multiarray\x94\x8c\x0c_reconstruct\x94\x93\x94\x8c\x05numpy\x94\x8c\x07ndarray\x94\x93\x94K\x00\x85\x94C\x01b\x94\x87\x94R\x94(K\x01K\x04K\x03K\x02\x87\x94h\x03\x8c\x05dtype\x94\x93\x94\x8c\x02u1\x94\x89\x88\x87\x94R\x94(K\x03\x8c\x01|\x94NNNJ\xff\xff\xff\xffJ\xff\xff\xff\xffK\x00t\x94b\x89C\x18\x00\x01\x08\t\x10\x11\x02\x03\n\x0b\x12\x13\x04\x05\x0c\r\x14\x15\x06\x07\x0e\x0f\x16\x17\x94t\x94b.' # noqa: E501 + no_contiguous_dumped = b'\x80\x05\x95\x91\x00\x00\x00\x00\x00\x00\x00\x8c\x16numpy._core.multiarray\x94\x8c\x0c_reconstruct\x94\x93\x94\x8c\x05numpy\x94\x8c\x07ndarray\x94\x93\x94K\x00\x85\x94C\x01b\x94\x87\x94R\x94(K\x01K\x03K\x02\x86\x94h\x03\x8c\x05dtype\x94\x93\x94\x8c\x02u1\x94\x89\x88\x87\x94R\x94(K\x03\x8c\x01|\x94NNNJ\xff\xff\xff\xffJ\xff\xff\xff\xffK\x00t\x94b\x89C\x06\x00\x01\x04\x05\x08\t\x94t\x94b.' # noqa: E501 + x = np.arange(24, dtype='uint8').reshape(3, 4, 2) + assert_equal(x, pickle.loads(c_contiguous_dumped)) + x = np.arange(24, dtype='uint8').reshape(3, 4, 2, order='F') + assert_equal(x, pickle.loads(f_contiguous_dumped)) + x = np.arange(24, dtype='uint8').reshape(3, 4, 2).transpose((1, 0, 2)) + assert_equal(x, pickle.loads(transposed_contiguous_dumped)) + x = np.arange(12, dtype='uint8').reshape(3, 4)[:, :2] + assert_equal(x, pickle.loads(no_contiguous_dumped)) + + def test_non_contiguous_array(self): + non_contiguous_array = np.arange(12).reshape(3, 4)[:, :2] + assert not non_contiguous_array.flags.c_contiguous + assert not non_contiguous_array.flags.f_contiguous + + # make sure non-contiguous arrays can be pickled-depickled + # using any protocol + buffers = [] + for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): + depickled_non_contiguous_array = pickle.loads( + pickle.dumps(non_contiguous_array, protocol=proto, + buffer_callback=buffers.append if proto >= 5 else None)) + + assert_equal(len(buffers), 0) + assert_equal(non_contiguous_array, depickled_non_contiguous_array) + + @pytest.mark.thread_unsafe(reason="calls gc.collect()") + def test_roundtrip(self): + for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): + carray = np.array([[2, 9], [7, 0], [3, 8]]) + DATA = [ + carray, + np.transpose(carray), + np.array([('xxx', 1, 2.0)], dtype=[('a', (str, 3)), ('b', int), + ('c', float)]) + ] + + refs = [weakref.ref(a) for a in DATA] + for a in DATA: + assert_equal( + a, pickle.loads(pickle.dumps(a, protocol=proto)), + err_msg=f"{a!r}") + del a, DATA, carray + break_cycles() + # check for reference leaks (gh-12793) + for ref in refs: + assert ref() is None + + def _loads(self, obj): + return pickle.loads(obj, encoding='latin1') + + # version 0 pickles, using protocol=2 to pickle + # version 0 doesn't have a version field + @pytest.mark.filterwarnings( + "ignore:.*align should be passed:numpy.exceptions.VisibleDeprecationWarning") + def test_version0_int8(self): + s = b"\x80\x02cnumpy.core._internal\n_reconstruct\nq\x01cnumpy\nndarray\nq\x02K\x00\x85U\x01b\x87Rq\x03(K\x04\x85cnumpy\ndtype\nq\x04U\x02i1K\x00K\x01\x87Rq\x05(U\x01|NNJ\xff\xff\xff\xffJ\xff\xff\xff\xfftb\x89U\x04\x01\x02\x03\x04tb." + a = np.array([1, 2, 3, 4], dtype=np.int8) + p = self._loads(s) + assert_equal(a, p) + + @pytest.mark.filterwarnings( + "ignore:.*align should be passed:numpy.exceptions.VisibleDeprecationWarning") + def test_version0_float32(self): + s = b"\x80\x02cnumpy.core._internal\n_reconstruct\nq\x01cnumpy\nndarray\nq\x02K\x00\x85U\x01b\x87Rq\x03(K\x04\x85cnumpy\ndtype\nq\x04U\x02f4K\x00K\x01\x87Rq\x05(U\x01= g2, [g1[i] >= g2[i] for i in [0, 1, 2]]) + assert_array_equal(g1 < g2, [g1[i] < g2[i] for i in [0, 1, 2]]) + assert_array_equal(g1 > g2, [g1[i] > g2[i] for i in [0, 1, 2]]) + + def test_mixed(self): + g1 = np.array(["spam", "spa", "spammer", "and eggs"]) + g2 = "spam" + assert_array_equal(g1 == g2, [x == g2 for x in g1]) + assert_array_equal(g1 != g2, [x != g2 for x in g1]) + assert_array_equal(g1 < g2, [x < g2 for x in g1]) + assert_array_equal(g1 > g2, [x > g2 for x in g1]) + assert_array_equal(g1 <= g2, [x <= g2 for x in g1]) + assert_array_equal(g1 >= g2, [x >= g2 for x in g1]) + + def test_unicode(self): + g1 = np.array(["This", "is", "example"]) + g2 = np.array(["This", "was", "example"]) + assert_array_equal(g1 == g2, [g1[i] == g2[i] for i in [0, 1, 2]]) + assert_array_equal(g1 != g2, [g1[i] != g2[i] for i in [0, 1, 2]]) + assert_array_equal(g1 <= g2, [g1[i] <= g2[i] for i in [0, 1, 2]]) + assert_array_equal(g1 >= g2, [g1[i] >= g2[i] for i in [0, 1, 2]]) + assert_array_equal(g1 < g2, [g1[i] < g2[i] for i in [0, 1, 2]]) + assert_array_equal(g1 > g2, [g1[i] > g2[i] for i in [0, 1, 2]]) + +class TestArgmaxArgminCommon: + + sizes = [(), (3,), (3, 2), (2, 3), + (3, 3), (2, 3, 4), (4, 3, 2), + (1, 2, 3, 4), (2, 3, 4, 1), + (3, 4, 1, 2), (4, 1, 2, 3), + (64,), (128,), (256,)] + + @pytest.mark.parametrize("size, axis", itertools.chain(*[[(size, axis) + for axis in list(range(-len(size), len(size))) + [None]] + for size in sizes])) + @pytest.mark.parametrize('method', [np.argmax, np.argmin]) + def test_np_argmin_argmax_keepdims(self, size, axis, method): + + arr = np.random.normal(size=size) + + # contiguous arrays + if axis is None: + new_shape = [1 for _ in range(len(size))] + else: + new_shape = list(size) + new_shape[axis] = 1 + new_shape = tuple(new_shape) + + _res_orig = method(arr, axis=axis) + res_orig = _res_orig.reshape(new_shape) + res = method(arr, axis=axis, keepdims=True) + assert_equal(res, res_orig) + assert_(res.shape == new_shape) + outarray = np.empty(res.shape, dtype=res.dtype) + res1 = method(arr, axis=axis, out=outarray, + keepdims=True) + assert_(res1 is outarray) + assert_equal(res, outarray) + + if len(size) > 0: + wrong_shape = list(new_shape) + if axis is not None: + wrong_shape[axis] = 2 + else: + wrong_shape[0] = 2 + wrong_outarray = np.empty(wrong_shape, dtype=res.dtype) + with pytest.raises(ValueError): + method(arr.T, axis=axis, + out=wrong_outarray, keepdims=True) + + # non-contiguous arrays + if axis is None: + new_shape = [1 for _ in range(len(size))] + else: + new_shape = list(size)[::-1] + new_shape[axis] = 1 + new_shape = tuple(new_shape) + + _res_orig = method(arr.T, axis=axis) + res_orig = _res_orig.reshape(new_shape) + res = method(arr.T, axis=axis, keepdims=True) + assert_equal(res, res_orig) + assert_(res.shape == new_shape) + outarray = np.empty(new_shape[::-1], dtype=res.dtype) + outarray = outarray.T + res1 = method(arr.T, axis=axis, out=outarray, + keepdims=True) + assert_(res1 is outarray) + assert_equal(res, outarray) + + if len(size) > 0: + # one dimension lesser for non-zero sized + # array should raise an error + with pytest.raises(ValueError): + method(arr[0], axis=axis, + out=outarray, keepdims=True) + + if len(size) > 0: + wrong_shape = list(new_shape) + if axis is not None: + wrong_shape[axis] = 2 + else: + wrong_shape[0] = 2 + wrong_outarray = np.empty(wrong_shape, dtype=res.dtype) + with pytest.raises(ValueError): + method(arr.T, axis=axis, + out=wrong_outarray, keepdims=True) + + @pytest.mark.parametrize('method', ['max', 'min']) + def test_all(self, method): + a = np.random.normal(0, 1, (4, 5, 6, 7, 8)) + arg_method = getattr(a, 'arg' + method) + val_method = getattr(a, method) + for i in range(a.ndim): + a_maxmin = val_method(i) + aarg_maxmin = arg_method(i) + axes = list(range(a.ndim)) + axes.remove(i) + assert_(np.all(a_maxmin == aarg_maxmin.choose( + *a.transpose(i, *axes)))) + + @pytest.mark.parametrize('method', ['argmax', 'argmin']) + def test_output_shape(self, method): + # see also gh-616 + a = np.ones((10, 5)) + arg_method = getattr(a, method) + # Check some simple shape mismatches + out = np.ones(11, dtype=np.int_) + assert_raises(ValueError, arg_method, -1, out) + + out = np.ones((2, 5), dtype=np.int_) + assert_raises(ValueError, arg_method, -1, out) + + # these could be relaxed possibly (used to allow even the previous) + out = np.ones((1, 10), dtype=np.int_) + assert_raises(ValueError, arg_method, -1, out) + + out = np.ones(10, dtype=np.int_) + arg_method(-1, out=out) + assert_equal(out, arg_method(-1)) + + @pytest.mark.parametrize('ndim', [0, 1]) + @pytest.mark.parametrize('method', ['argmax', 'argmin']) + def test_ret_is_out(self, ndim, method): + a = np.ones((4,) + (256,) * ndim) + arg_method = getattr(a, method) + out = np.empty((256,) * ndim, dtype=np.intp) + ret = arg_method(axis=0, out=out) + assert ret is out + + @pytest.mark.parametrize('np_array, method, idx, val', + [(np.zeros, 'argmax', 5942, "as"), + (np.ones, 'argmin', 6001, "0")]) + def test_unicode(self, np_array, method, idx, val): + d = np_array(6031, dtype='= cmin)) + assert_(np.all(x <= cmax)) + + def _clip_type(self, type_group, array_max, + clip_min, clip_max, inplace=False, + expected_min=None, expected_max=None): + if expected_min is None: + expected_min = clip_min + if expected_max is None: + expected_max = clip_max + + for T in np._core.sctypes[type_group]: + if sys.byteorder == 'little': + byte_orders = ['=', '>'] + else: + byte_orders = ['<', '='] + + for byteorder in byte_orders: + dtype = np.dtype(T).newbyteorder(byteorder) + + x = (np.random.random(1000) * array_max).astype(dtype) + if inplace: + # The tests that call us pass clip_min and clip_max that + # might not fit in the destination dtype. They were written + # assuming the previous unsafe casting, which now must be + # passed explicitly to avoid a warning. + x.clip(clip_min, clip_max, x, casting='unsafe') + else: + x = x.clip(clip_min, clip_max) + byteorder = '=' + + if x.dtype.byteorder == '|': + byteorder = '|' + assert_equal(x.dtype.byteorder, byteorder) + self._check_range(x, expected_min, expected_max) + return x + + def test_basic(self): + for inplace in [False, True]: + self._clip_type( + 'float', 1024, -12.8, 100.2, inplace=inplace) + self._clip_type( + 'float', 1024, 0, 0, inplace=inplace) + + self._clip_type( + 'int', 1024, -120, 100, inplace=inplace) + self._clip_type( + 'int', 1024, 0, 0, inplace=inplace) + + self._clip_type( + 'uint', 1024, 0, 0, inplace=inplace) + self._clip_type( + 'uint', 1024, 10, 100, inplace=inplace) + + @pytest.mark.parametrize("inplace", [False, True]) + def test_int_out_of_range(self, inplace): + # Simple check for out-of-bound integers, also testing the in-place + # path. + x = (np.random.random(1000) * 255).astype("uint8") + out = np.empty_like(x) + res = x.clip(-1, 300, out=out if inplace else None) + assert res is out or not inplace + assert (res == x).all() + + res = x.clip(-1, 50, out=out if inplace else None) + assert res is out or not inplace + assert (res <= 50).all() + assert (res[x <= 50] == x[x <= 50]).all() + + res = x.clip(100, 1000, out=out if inplace else None) + assert res is out or not inplace + assert (res >= 100).all() + assert (res[x >= 100] == x[x >= 100]).all() + + def test_record_array(self): + rec = np.array([(-5, 2.0, 3.0), (5.0, 4.0, 3.0)], + dtype=[('x', '= 3)) + x = val.clip(min=3) + assert_(np.all(x >= 3)) + x = val.clip(max=4) + assert_(np.all(x <= 4)) + + def test_nan(self): + input_arr = np.array([-2., np.nan, 0.5, 3., 0.25, np.nan]) + result = input_arr.clip(-1, 1) + expected = np.array([-1., np.nan, 0.5, 1., 0.25, np.nan]) + assert_array_equal(result, expected) + + +class TestCompress: + def test_axis(self): + tgt = [[5, 6, 7, 8, 9]] + arr = np.arange(10).reshape(2, 5) + out = np.compress([0, 1], arr, axis=0) + assert_equal(out, tgt) + + tgt = [[1, 3], [6, 8]] + out = np.compress([0, 1, 0, 1, 0], arr, axis=1) + assert_equal(out, tgt) + + def test_truncate(self): + tgt = [[1], [6]] + arr = np.arange(10).reshape(2, 5) + out = np.compress([0, 1], arr, axis=1) + assert_equal(out, tgt) + + def test_flatten(self): + arr = np.arange(10).reshape(2, 5) + out = np.compress([0, 1], arr) + assert_equal(out, 1) + + +class TestPutmask: + def tst_basic(self, x, T, mask, val): + np.putmask(x, mask, val) + assert_equal(x[mask], np.array(val, T)) + + def test_ip_types(self): + unchecked_types = [bytes, str, np.void] + + x = np.random.random(1000) * 100 + mask = x < 40 + + for val in [-100, 0, 15]: + for types in np._core.sctypes.values(): + for T in types: + if T not in unchecked_types: + if val < 0 and np.dtype(T).kind == "u": + val = np.iinfo(T).max - 99 + self.tst_basic(x.copy().astype(T), T, mask, val) + + # Also test string of a length which uses an untypical length + dt = np.dtype("S3") + self.tst_basic(x.astype(dt), dt.type, mask, dt.type(val)[:3]) + + def test_mask_size(self): + assert_raises(ValueError, np.putmask, np.array([1, 2, 3]), [True], 5) + + @pytest.mark.parametrize('dtype', ('>i4', 'f8'), ('z', '= 2, 3) + + def test_kwargs(self): + x = np.array([0, 0]) + np.putmask(x, [0, 1], [-1, -2]) + assert_array_equal(x, [0, -2]) + + x = np.array([0, 0]) + np.putmask(x, mask=[0, 1], values=[-1, -2]) + assert_array_equal(x, [0, -2]) + + x = np.array([0, 0]) + np.putmask(x, values=[-1, -2], mask=[0, 1]) + assert_array_equal(x, [0, -2]) + + with pytest.raises(TypeError): + np.putmask(a=x, values=[-1, -2], mask=[0, 1]) + + +class TestTake: + def tst_basic(self, x): + ind = list(range(x.shape[0])) + assert_array_equal(x.take(ind, axis=0), x) + + def test_ip_types(self): + unchecked_types = [bytes, str, np.void] + + x = np.random.random(24) * 100 + x = x.reshape((2, 3, 4)) + for types in np._core.sctypes.values(): + for T in types: + if T not in unchecked_types: + self.tst_basic(x.copy().astype(T)) + + # Also test string of a length which uses an untypical length + self.tst_basic(x.astype("S3")) + + def test_raise(self): + x = np.random.random(24) * 100 + x = x.reshape((2, 3, 4)) + assert_raises(IndexError, x.take, [0, 1, 2], axis=0) + assert_raises(IndexError, x.take, [-3], axis=0) + assert_array_equal(x.take([-1], axis=0)[0], x[1]) + + def test_clip(self): + x = np.random.random(24) * 100 + x = x.reshape((2, 3, 4)) + assert_array_equal(x.take([-1], axis=0, mode='clip')[0], x[0]) + assert_array_equal(x.take([2], axis=0, mode='clip')[0], x[1]) + + def test_wrap(self): + x = np.random.random(24) * 100 + x = x.reshape((2, 3, 4)) + assert_array_equal(x.take([-1], axis=0, mode='wrap')[0], x[1]) + assert_array_equal(x.take([2], axis=0, mode='wrap')[0], x[0]) + assert_array_equal(x.take([3], axis=0, mode='wrap')[0], x[1]) + + @pytest.mark.parametrize('dtype', ('>i4', 'f8'), ('z', ' 16MB + tmp_filename = normalize_filename(tmp_path, param_filename) + d = np.zeros(4 * 1024 ** 2) + d.tofile(tmp_filename) + assert_equal(os.path.getsize(tmp_filename), d.nbytes) + assert_array_equal(d, np.fromfile(tmp_filename)) + # check offset + with open(tmp_filename, "r+b") as f: + f.seek(d.nbytes) + d.tofile(f) + assert_equal(os.path.getsize(tmp_filename), d.nbytes * 2) + # check append mode (gh-8329) + open(tmp_filename, "w").close() # delete file contents + with open(tmp_filename, "ab") as f: + d.tofile(f) + assert_array_equal(d, np.fromfile(tmp_filename)) + with open(tmp_filename, "ab") as f: + d.tofile(f) + assert_equal(os.path.getsize(tmp_filename), d.nbytes * 2) + + def test_io_open_buffered_fromfile(self, tmp_path, param_filename): + # gh-6632 + tmp_filename = normalize_filename(tmp_path, param_filename) + x = self._create_data() + x.tofile(tmp_filename) + with open(tmp_filename, 'rb', buffering=-1) as f: + y = np.fromfile(f, dtype=x.dtype) + assert_array_equal(y, x.flat) + + def test_file_position_after_fromfile(self, tmp_path, param_filename): + # gh-4118 + sizes = [io.DEFAULT_BUFFER_SIZE // 8, + io.DEFAULT_BUFFER_SIZE, + io.DEFAULT_BUFFER_SIZE * 8] + tmp_filename = normalize_filename(tmp_path, param_filename) + + for size in sizes: + with open(tmp_filename, 'wb') as f: + f.seek(size - 1) + f.write(b'\0') + + for mode in ['rb', 'r+b']: + err_msg = "%d %s" % (size, mode) + + with open(tmp_filename, mode) as f: + f.read(2) + np.fromfile(f, dtype=np.float64, count=1) + pos = f.tell() + assert_equal(pos, 10, err_msg=err_msg) + + def test_file_position_after_tofile(self, tmp_path, param_filename): + # gh-4118 + sizes = [io.DEFAULT_BUFFER_SIZE // 8, + io.DEFAULT_BUFFER_SIZE, + io.DEFAULT_BUFFER_SIZE * 8] + tmp_filename = normalize_filename(tmp_path, param_filename) + + for size in sizes: + err_msg = "%d" % (size,) + + with open(tmp_filename, 'wb') as f: + f.seek(size - 1) + f.write(b'\0') + f.seek(10) + f.write(b'12') + np.array([0], dtype=np.float64).tofile(f) + pos = f.tell() + assert_equal(pos, 10 + 2 + 8, err_msg=err_msg) + + with open(tmp_filename, 'r+b') as f: + f.read(2) + f.seek(0, 1) # seek between read&write required by ANSI C + np.array([0], dtype=np.float64).tofile(f) + pos = f.tell() + assert_equal(pos, 10, err_msg=err_msg) + + def test_load_object_array_fromfile(self, tmp_path, param_filename): + # gh-12300 + tmp_filename = normalize_filename(tmp_path, param_filename) + with open(tmp_filename, 'w') as f: + # Ensure we have a file with consistent contents + pass + + with open(tmp_filename, 'rb') as f: + assert_raises_regex(ValueError, "Cannot read into object array", + np.fromfile, f, dtype=object) + + assert_raises_regex(ValueError, "Cannot read into object array", + np.fromfile, tmp_filename, dtype=object) + + def test_fromfile_offset(self, tmp_path, param_filename): + tmp_filename = normalize_filename(tmp_path, param_filename) + x = self._create_data() + with open(tmp_filename, 'wb') as f: + x.tofile(f) + + with open(tmp_filename, 'rb') as f: + y = np.fromfile(f, dtype=x.dtype, offset=0) + assert_array_equal(y, x.flat) + + with open(tmp_filename, 'rb') as f: + count_items = len(x.flat) // 8 + offset_items = len(x.flat) // 4 + offset_bytes = x.dtype.itemsize * offset_items + y = np.fromfile( + f, dtype=x.dtype, count=count_items, offset=offset_bytes + ) + assert_array_equal( + y, x.flat[offset_items:offset_items + count_items] + ) + + # subsequent seeks should stack + offset_bytes = x.dtype.itemsize + z = np.fromfile(f, dtype=x.dtype, offset=offset_bytes) + assert_array_equal(z, x.flat[offset_items + count_items + 1:]) + + with open(tmp_filename, 'wb') as f: + x.tofile(f, sep=",") + + with open(tmp_filename, 'rb') as f: + assert_raises_regex( + TypeError, + "'offset' argument only permitted for binary files", + np.fromfile, tmp_filename, dtype=x.dtype, + sep=",", offset=1) + + @pytest.mark.skipif(IS_PYPY, reason="bug in PyPy's PyNumber_AsSsize_t") + def test_fromfile_bad_dup(self, tmp_path, param_filename, monkeypatch): + def dup_str(fd): + return 'abc' + + def dup_bigint(fd): + return 2**68 + + tmp_filename = normalize_filename(tmp_path, param_filename) + x = self._create_data() + + with open(tmp_filename, 'wb') as f: + x.tofile(f) + for dup, exc in ((dup_str, TypeError), (dup_bigint, OSError)): + monkeypatch.setattr(os, "dup", dup) + assert_raises(exc, np.fromfile, f) + + def _check_from(self, s, value, filename, **kw): + if 'sep' not in kw: + y = np.frombuffer(s, **kw) + else: + y = np.fromstring(s, **kw) + assert_array_equal(y, value) + + with open(filename, 'wb') as f: + f.write(s) + y = np.fromfile(filename, **kw) + assert_array_equal(y, value) + + @pytest.fixture(params=["period", "comma"]) + def decimal_sep_localization(self, request): + """ + Including this fixture in a test will automatically + execute it with both types of decimal separator. + + So:: + + def test_decimal(decimal_sep_localization): + pass + + is equivalent to the following two tests:: + + def test_decimal_period_separator(): + pass + + def test_decimal_comma_separator(): + with CommaDecimalPointLocale(): + pass + """ + if request.param == "period": + yield + elif request.param == "comma": + with CommaDecimalPointLocale(): + yield + else: + assert False, request.param + + def test_nan(self, tmp_path, param_filename, decimal_sep_localization): + tmp_filename = normalize_filename(tmp_path, param_filename) + self._check_from( + b"nan +nan -nan NaN nan(foo) +NaN(BAR) -NAN(q_u_u_x_)", + [np.nan, np.nan, np.nan, np.nan, np.nan, np.nan, np.nan], + tmp_filename, + sep=' ') + + def test_inf(self, tmp_path, param_filename, decimal_sep_localization): + tmp_filename = normalize_filename(tmp_path, param_filename) + self._check_from( + b"inf +inf -inf infinity -Infinity iNfInItY -inF", + [np.inf, np.inf, -np.inf, np.inf, -np.inf, np.inf, -np.inf], + tmp_filename, + sep=' ') + + def test_numbers(self, tmp_path, param_filename, decimal_sep_localization): + tmp_filename = normalize_filename(tmp_path, param_filename) + self._check_from( + b"1.234 -1.234 .3 .3e55 -123133.1231e+133", + [1.234, -1.234, .3, .3e55, -123133.1231e+133], + tmp_filename, + sep=' ') + + def test_binary(self, tmp_path, param_filename): + tmp_filename = normalize_filename(tmp_path, param_filename) + self._check_from( + b'\x00\x00\x80?\x00\x00\x00@\x00\x00@@\x00\x00\x80@', + np.array([1, 2, 3, 4]), + tmp_filename, + dtype='']) + @pytest.mark.parametrize('dtype', [float, int, complex]) + def test_basic(self, byteorder, dtype): + dt = np.dtype(dtype).newbyteorder(byteorder) + x = (np.random.random((4, 7)) * 5).astype(dt) + buf = x.tobytes() + assert_array_equal(np.frombuffer(buf, dtype=dt), x.flat) + + @pytest.mark.parametrize("obj", [np.arange(10), b"12345678"]) + def test_array_base(self, obj): + # Objects (including NumPy arrays), which do not use the + # `release_buffer` slot should be directly used as a base object. + # See also gh-21612 + new = np.frombuffer(obj) + assert new.base is obj + + def test_empty(self): + assert_array_equal(np.frombuffer(b''), np.array([])) + + @pytest.mark.skipif(IS_PYPY, + reason="PyPy's memoryview currently does not track exports. See: " + "https://foss.heptapod.net/pypy/pypy/-/issues/3724") + def test_mmap_close(self): + # The old buffer protocol was not safe for some things that the new + # one is. But `frombuffer` always used the old one for a long time. + # Checks that it is safe with the new one (using memoryviews) + with tempfile.TemporaryFile(mode='wb') as tmp: + tmp.write(b"asdf") + tmp.flush() + mm = mmap.mmap(tmp.fileno(), 0) + arr = np.frombuffer(mm, dtype=np.uint8) + with pytest.raises(BufferError): + mm.close() # cannot close while array uses the buffer + del arr + mm.close() + +class TestFlat: + def _create_arrays(self): + a = np.arange(20.0).reshape(4, 5) + a.flags.writeable = False + b = a[::2, ::2] + return a, b + + def test_contiguous(self): + testpassed = False + a, _ = self._create_arrays() + try: + a.flat[12] = 100.0 + except ValueError: + testpassed = True + assert_(testpassed) + assert_(a.flat[12] == 12.0) + + def test_discontiguous(self): + testpassed = False + _, b = self._create_arrays() + try: + b.flat[4] = 100.0 + except ValueError: + testpassed = True + assert_(testpassed) + assert_(b.flat[4] == 12.0) + + def test___array__(self): + a0 = np.arange(20.0) + a = a0.reshape(4, 5) + a0 = a0.reshape((4, 5)) + a.flags.writeable = False + b = a[::2, ::2] + b0 = a0[::2, ::2] + c = a.flat.__array__() + d = b.flat.__array__() + e = a0.flat.__array__() + f = b0.flat.__array__() + + assert_(c.flags.writeable is False) + assert_(d.flags.writeable is False) + assert_(e.flags.writeable is True) + assert_(f.flags.writeable is False) + assert_(c.flags.writebackifcopy is False) + assert_(d.flags.writebackifcopy is False) + assert_(e.flags.writebackifcopy is False) + assert_(f.flags.writebackifcopy is False) + + @pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") + def test_refcount(self): + # includes regression test for reference count error gh-13165 + a, _ = self._create_arrays() + inds = [np.intp(0), np.array([True] * a.size), np.array([0]), None] + indtype = np.dtype(np.intp) + rc_indtype = sys.getrefcount(indtype) + for ind in inds: + rc_ind = sys.getrefcount(ind) + for _ in range(100): + try: + a.flat[ind] + except IndexError: + pass + assert_(abs(sys.getrefcount(ind) - rc_ind) < 50) + assert_(abs(sys.getrefcount(indtype) - rc_indtype) < 50) + + def test_index_getset(self): + it = np.arange(10).reshape(2, 1, 5).flat + with pytest.raises(AttributeError): + it.index = 10 + + for _ in it: + pass + # Check the value of `.index` is updated correctly (see also gh-19153) + # If the type was incorrect, this would show up on big-endian machines + assert it.index == it.base.size + + def test_maxdims(self): + # The flat iterator and thus attribute is currently unfortunately + # limited to only 32 dimensions (after bumping it to 64 for 2.0) + a = np.ones((1,) * 64) + + with pytest.raises(RuntimeError, + match=".*32 dimensions but the array has 64"): + a.flat + + +class TestResize: + + @_no_tracing + def test_basic(self): + x = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]]) + if IS_PYPY: + x.resize((5, 5), refcheck=False) + else: + x.resize((5, 5)) + assert_array_equal(x.flat[:9], + np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]]).flat) + assert_array_equal(x[9:].flat, 0) + + def test_check_reference(self): + x = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]]) + y = x + assert_raises(ValueError, x.resize, (5, 1)) + + @pytest.mark.skipif(IS_WASM, reason="Cannot start subprocess") + @pytest.mark.skipif(IS_PYPY, reason="The method always raises") + def test_check_reference_module_scope(self): + code = textwrap.dedent(""" + import numpy as np + + # See gh-30991 + a = np.array([[0, 1], [2, 3]], order='C') + a.resize((2, 1)) + """) + try: + subprocess.check_output([sys.executable, "-c", code], + stderr=subprocess.STDOUT, text=True) + except subprocess.CalledProcessError as e: + assert sys.version_info >= (3, 14) + assert "ValueError" in e.stdout + assert "It is possible that this is a false positive." in e.stdout + else: + if sys.version_info >= (3, 14): + raise AssertionError("Unexpected success of resize refcheck") + + def test_check_reference_2(self): + # see gh-30265 + x = np.zeros((2, 2)) + y = x + with pytest.raises(ValueError): + x.resize((5, 5)) + + @_no_tracing + def test_int_shape(self): + x = np.eye(3) + if IS_PYPY: + x.resize(3, refcheck=False) + else: + x.resize(3) + assert_array_equal(x, np.eye(3)[0, :]) + + def test_none_shape(self): + x = np.eye(3) + x.resize(None) + assert_array_equal(x, np.eye(3)) + x.resize() + assert_array_equal(x, np.eye(3)) + + def test_0d_shape(self): + # to it multiple times to test it does not break alloc cache gh-9216 + for i in range(10): + x = np.empty((1,)) + x.resize(()) + assert_equal(x.shape, ()) + assert_equal(x.size, 1) + x = np.empty(()) + x.resize((1,)) + assert_equal(x.shape, (1,)) + assert_equal(x.size, 1) + + def test_invalid_arguments(self): + assert_raises(TypeError, np.eye(3).resize, 'hi') + assert_raises(ValueError, np.eye(3).resize, -1) + assert_raises(TypeError, np.eye(3).resize, order=1) + assert_raises(TypeError, np.eye(3).resize, refcheck='hi') + + @_no_tracing + def test_freeform_shape(self): + x = np.eye(3) + if IS_PYPY: + x.resize(3, 2, 1, refcheck=False) + else: + x.resize(3, 2, 1) + assert_(x.shape == (3, 2, 1)) + + @_no_tracing + def test_zeros_appended(self): + x = np.eye(3) + if IS_PYPY: + x.resize(2, 3, 3, refcheck=False) + else: + x.resize(2, 3, 3) + assert_array_equal(x[0], np.eye(3)) + assert_array_equal(x[1], np.zeros((3, 3))) + + @_no_tracing + def test_obj_obj(self): + # check memory is initialized on resize, gh-4857 + a = np.ones(10, dtype=[('k', object, 2)]) + if IS_PYPY: + a.resize(15, refcheck=False) + else: + a.resize(15,) + assert_equal(a.shape, (15,)) + assert_array_equal(a['k'][-5:], 0) + assert_array_equal(a['k'][:-5], 1) + + @pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") + @pytest.mark.parametrize("dtype", ["O", "O,O"]) + def test_obj_obj_shrinking(self, dtype): + # check that memory is freed when shrinking an array. + test_obj = object() + expected = sys.getrefcount(test_obj) + a = np.array([test_obj, test_obj, test_obj], dtype=dtype) + assert a.size == 3 + a.resize((2, 1)) # two elements, not three! + assert a.size == 2 + del a + # if all is well, then we reclaimed all references + assert sys.getrefcount(test_obj) == expected + + def test_empty_view(self): + # check that sizes containing a zero don't trigger a reallocate for + # already empty arrays + x = np.zeros((10, 0), int) + x_view = x[...] + x_view.resize((0, 10)) + x_view.resize((0, 100)) + + def test_check_weakref(self): + x = np.array([[1, 0, 0], [0, 1, 0], [0, 0, 1]]) + xref = weakref.ref(x) + assert_raises(ValueError, x.resize, (5, 1)) + + +class TestRecord: + def test_field_rename(self): + dt = np.dtype([('f', float), ('i', int)]) + dt.names = ['p', 'q'] + assert_equal(dt.names, ['p', 'q']) + + def test_multiple_field_name_occurrence(self): + def test_dtype_init(): + np.dtype([("A", "f8"), ("B", "f8"), ("A", "f8")]) + + # Error raised when multiple fields have the same name + assert_raises(ValueError, test_dtype_init) + + def test_bytes_fields(self): + # Bytes are not allowed in field names and not recognized in titles + # on Py3 + assert_raises(TypeError, np.dtype, [(b'a', int)]) + assert_raises(TypeError, np.dtype, [(('b', b'a'), int)]) + + dt = np.dtype([((b'a', 'b'), int)]) + assert_raises(TypeError, dt.__getitem__, b'a') + + x = np.array([(1,), (2,), (3,)], dtype=dt) + assert_raises(IndexError, x.__getitem__, b'a') + + y = x[0] + assert_raises(IndexError, y.__getitem__, b'a') + + def test_multiple_field_name_unicode(self): + def test_dtype_unicode(): + np.dtype([("\u20B9", "f8"), ("B", "f8"), ("\u20B9", "f8")]) + + # Error raised when multiple fields have the same name(unicode included) + assert_raises(ValueError, test_dtype_unicode) + + def test_fromarrays_unicode(self): + # A single name string provided to fromarrays() is allowed to be unicode + x = np._core.records.fromarrays( + [[0], [1]], names='a,b', formats='i4,i4') + assert_equal(x['a'][0], 0) + assert_equal(x['b'][0], 1) + + def test_unicode_order(self): + # Test that we can sort with order as a unicode field name + name = 'b' + x = np.array([1, 3, 2], dtype=[(name, int)]) + x.sort(order=name) + assert_equal(x['b'], np.array([1, 2, 3])) + + def test_field_names(self): + # Test unicode and 8-bit / byte strings can be used + a = np.zeros((1,), dtype=[('f1', 'i4'), + ('f2', 'i4'), + ('f3', [('sf1', 'i4')])]) + # byte string indexing fails gracefully + assert_raises(IndexError, a.__setitem__, b'f1', 1) + assert_raises(IndexError, a.__getitem__, b'f1') + assert_raises(IndexError, a['f1'].__setitem__, b'sf1', 1) + assert_raises(IndexError, a['f1'].__getitem__, b'sf1') + b = a.copy() + fn1 = 'f1' + b[fn1] = 1 + assert_equal(b[fn1], 1) + fnn = 'not at all' + assert_raises(ValueError, b.__setitem__, fnn, 1) + assert_raises(ValueError, b.__getitem__, fnn) + b[0][fn1] = 2 + assert_equal(b[fn1], 2) + # Subfield + assert_raises(ValueError, b[0].__setitem__, fnn, 1) + assert_raises(ValueError, b[0].__getitem__, fnn) + # Subfield + fn3 = 'f3' + sfn1 = 'sf1' + b[fn3][sfn1] = 1 + assert_equal(b[fn3][sfn1], 1) + assert_raises(ValueError, b[fn3].__setitem__, fnn, 1) + assert_raises(ValueError, b[fn3].__getitem__, fnn) + # multiple subfields + fn2 = 'f2' + b[fn2] = 3 + + assert_equal(b[['f1', 'f2']][0].tolist(), (2, 3)) + assert_equal(b[['f2', 'f1']][0].tolist(), (3, 2)) + assert_equal(b[['f1', 'f3']][0].tolist(), (2, (1,))) + + # non-ascii unicode field indexing is well behaved + assert_raises(ValueError, a.__setitem__, '\u03e0', 1) + assert_raises(ValueError, a.__getitem__, '\u03e0') + + def test_record_hash(self): + a = np.array([(1, 2), (1, 2)], dtype='i1,i2') + a.flags.writeable = False + b = np.array([(1, 2), (3, 4)], dtype=[('num1', 'i1'), ('num2', 'i2')]) + b.flags.writeable = False + c = np.array([(1, 2), (3, 4)], dtype='i1,i2') + c.flags.writeable = False + assert_(hash(a[0]) == hash(a[1])) + assert_(hash(a[0]) == hash(b[0])) + assert_(hash(a[0]) != hash(b[1])) + assert_(hash(c[0]) == hash(a[0]) and c[0] == a[0]) + + def test_record_no_hash(self): + a = np.array([(1, 2), (1, 2)], dtype='i1,i2') + assert_raises(TypeError, hash, a[0]) + + def test_empty_structure_creation(self): + # make sure these do not raise errors (gh-5631) + np.array([()], dtype={'names': [], 'formats': [], + 'offsets': [], 'itemsize': 12}) + np.array([(), (), (), (), ()], dtype={'names': [], 'formats': [], + 'offsets': [], 'itemsize': 12}) + + def test_multifield_indexing_view(self): + a = np.ones(3, dtype=[('a', 'i4'), ('b', 'f4'), ('c', 'u4')]) + v = a[['a', 'c']] + assert_(v.base is a) + assert_(v.dtype == np.dtype({'names': ['a', 'c'], + 'formats': ['i4', 'u4'], + 'offsets': [0, 8]})) + v[:] = (4, 5) + assert_equal(a[0].item(), (4, 1, 5)) + +class TestView: + def test_basic(self): + x = np.array([(1, 2, 3, 4), (5, 6, 7, 8)], + dtype=[('r', np.int8), ('g', np.int8), + ('b', np.int8), ('a', np.int8)]) + # We must be specific about the endianness here: + y = x.view(dtype=' 0) + assert_(issubclass(w[0].category, RuntimeWarning)) + + def test_empty(self): + A = np.zeros((0, 3)) + for f in self.funcs: + for axis in [0, None]: + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter('always') + assert_(np.isnan(f(A, axis=axis)).all()) + assert_(len(w) > 0) + assert_(issubclass(w[0].category, RuntimeWarning)) + for axis in [1]: + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter('always') + assert_equal(f(A, axis=axis), np.zeros([])) + + def test_mean_values(self): + rmat, cmat, omat = self._create_data() + for mat in [rmat, cmat, omat]: + for axis in [0, 1]: + tgt = mat.sum(axis=axis) + res = _mean(mat, axis=axis) * mat.shape[axis] + assert_almost_equal(res, tgt) + for axis in [None]: + tgt = mat.sum(axis=axis) + res = _mean(mat, axis=axis) * np.prod(mat.shape) + assert_almost_equal(res, tgt) + + def test_mean_float16(self): + # This fail if the sum inside mean is done in float16 instead + # of float32. + assert_(_mean(np.ones(100000, dtype='float16')) == 1) + + def test_mean_axis_error(self): + # Ensure that AxisError is raised instead of IndexError when axis is + # out of bounds, see gh-15817. + with assert_raises(np.exceptions.AxisError): + np.arange(10).mean(axis=2) + + def test_mean_where(self): + a = np.arange(16).reshape((4, 4)) + wh_full = np.array([[False, True, False, True], + [True, False, True, False], + [True, True, False, False], + [False, False, True, True]]) + wh_partial = np.array([[False], + [True], + [True], + [False]]) + _cases = [(1, True, [1.5, 5.5, 9.5, 13.5]), + (0, wh_full, [6., 5., 10., 9.]), + (1, wh_full, [2., 5., 8.5, 14.5]), + (0, wh_partial, [6., 7., 8., 9.])] + for _ax, _wh, _res in _cases: + assert_allclose(a.mean(axis=_ax, where=_wh), + np.array(_res)) + assert_allclose(np.mean(a, axis=_ax, where=_wh), + np.array(_res)) + + a3d = np.arange(16).reshape((2, 2, 4)) + _wh_partial = np.array([False, True, True, False]) + _res = [[1.5, 5.5], [9.5, 13.5]] + assert_allclose(a3d.mean(axis=2, where=_wh_partial), + np.array(_res)) + assert_allclose(np.mean(a3d, axis=2, where=_wh_partial), + np.array(_res)) + + with pytest.warns(RuntimeWarning) as w: + assert_allclose(a.mean(axis=1, where=wh_partial), + np.array([np.nan, 5.5, 9.5, np.nan])) + with pytest.warns(RuntimeWarning) as w: + assert_equal(a.mean(where=False), np.nan) + with pytest.warns(RuntimeWarning) as w: + assert_equal(np.mean(a, where=False), np.nan) + + def test_var_values(self): + rmat, cmat, omat = self._create_data() + for mat in [rmat, cmat, omat]: + for axis in [0, 1, None]: + msqr = _mean(mat * mat.conj(), axis=axis) + mean = _mean(mat, axis=axis) + tgt = msqr - mean * mean.conjugate() + res = _var(mat, axis=axis) + assert_almost_equal(res, tgt) + + @pytest.mark.parametrize(('complex_dtype', 'ndec'), ( + ('complex64', 6), + ('complex128', 7), + ('clongdouble', 7), + )) + def test_var_complex_values(self, complex_dtype, ndec): + _, cmat, _ = self._create_data() + # Test fast-paths for every builtin complex type + for axis in [0, 1, None]: + mat = cmat.copy().astype(complex_dtype) + msqr = _mean(mat * mat.conj(), axis=axis) + mean = _mean(mat, axis=axis) + tgt = msqr - mean * mean.conjugate() + res = _var(mat, axis=axis) + assert_almost_equal(res, tgt, decimal=ndec) + + def test_var_dimensions(self): + # _var paths for complex number introduce additions on views that + # increase dimensions. Ensure this generalizes to higher dims + _, cmat, _ = self._create_data() + mat = np.stack([cmat] * 3) + for axis in [0, 1, 2, -1, None]: + msqr = _mean(mat * mat.conj(), axis=axis) + mean = _mean(mat, axis=axis) + tgt = msqr - mean * mean.conjugate() + res = _var(mat, axis=axis) + assert_almost_equal(res, tgt) + + def test_var_complex_byteorder(self): + # Test that var fast-path does not cause failures for complex arrays + # with non-native byteorder + _, cmat, _ = self._create_data() + cmat = cmat.copy().astype('complex128') + cmat_swapped = cmat.astype(cmat.dtype.newbyteorder()) + assert_almost_equal(cmat.var(), cmat_swapped.var()) + + def test_var_axis_error(self): + # Ensure that AxisError is raised instead of IndexError when axis is + # out of bounds, see gh-15817. + with assert_raises(np.exceptions.AxisError): + np.arange(10).var(axis=2) + + def test_var_where(self): + a = np.arange(25).reshape((5, 5)) + wh_full = np.array([[False, True, False, True, True], + [True, False, True, True, False], + [True, True, False, False, True], + [False, True, True, False, True], + [True, False, True, True, False]]) + wh_partial = np.array([[False], + [True], + [True], + [False], + [True]]) + _cases = [(0, True, [50., 50., 50., 50., 50.]), + (1, True, [2., 2., 2., 2., 2.])] + for _ax, _wh, _res in _cases: + assert_allclose(a.var(axis=_ax, where=_wh), + np.array(_res)) + assert_allclose(np.var(a, axis=_ax, where=_wh), + np.array(_res)) + + a3d = np.arange(16).reshape((2, 2, 4)) + _wh_partial = np.array([False, True, True, False]) + _res = [[0.25, 0.25], [0.25, 0.25]] + assert_allclose(a3d.var(axis=2, where=_wh_partial), + np.array(_res)) + assert_allclose(np.var(a3d, axis=2, where=_wh_partial), + np.array(_res)) + + assert_allclose(np.var(a, axis=1, where=wh_full), + np.var(a[wh_full].reshape((5, 3)), axis=1)) + assert_allclose(np.var(a, axis=0, where=wh_partial), + np.var(a[wh_partial[:, 0]], axis=0)) + with pytest.warns(RuntimeWarning) as w: + assert_equal(a.var(where=False), np.nan) + with pytest.warns(RuntimeWarning) as w: + assert_equal(np.var(a, where=False), np.nan) + + def test_std_values(self): + rmat, cmat, omat = self._create_data() + for mat in [rmat, cmat, omat]: + for axis in [0, 1, None]: + tgt = np.sqrt(_var(mat, axis=axis)) + res = _std(mat, axis=axis) + assert_almost_equal(res, tgt) + + def test_std_where(self): + a = np.arange(25).reshape((5, 5))[::-1] + whf = np.array([[False, True, False, True, True], + [True, False, True, False, True], + [True, True, False, True, False], + [True, False, True, True, False], + [False, True, False, True, True]]) + whp = np.array([[False], + [False], + [True], + [True], + [False]]) + _cases = [ + (0, True, 7.07106781 * np.ones(5)), + (1, True, 1.41421356 * np.ones(5)), + (0, whf, + np.array([4.0824829, 8.16496581, 5., 7.39509973, 8.49836586])), + (0, whp, 2.5 * np.ones(5)) + ] + for _ax, _wh, _res in _cases: + assert_allclose(a.std(axis=_ax, where=_wh), _res) + assert_allclose(np.std(a, axis=_ax, where=_wh), _res) + + a3d = np.arange(16).reshape((2, 2, 4)) + _wh_partial = np.array([False, True, True, False]) + _res = [[0.5, 0.5], [0.5, 0.5]] + assert_allclose(a3d.std(axis=2, where=_wh_partial), + np.array(_res)) + assert_allclose(np.std(a3d, axis=2, where=_wh_partial), + np.array(_res)) + + assert_allclose(a.std(axis=1, where=whf), + np.std(a[whf].reshape((5, 3)), axis=1)) + assert_allclose(np.std(a, axis=1, where=whf), + (a[whf].reshape((5, 3))).std(axis=1)) + assert_allclose(a.std(axis=0, where=whp), + np.std(a[whp[:, 0]], axis=0)) + assert_allclose(np.std(a, axis=0, where=whp), + (a[whp[:, 0]]).std(axis=0)) + with pytest.warns(RuntimeWarning) as w: + assert_equal(a.std(where=False), np.nan) + with pytest.warns(RuntimeWarning) as w: + assert_equal(np.std(a, where=False), np.nan) + + def test_subclass(self): + class TestArray(np.ndarray): + def __new__(cls, data, info): + result = np.array(data) + result = result.view(cls) + result.info = info + return result + + def __array_finalize__(self, obj): + self.info = getattr(obj, "info", '') + + dat = TestArray([[1, 2, 3, 4], [5, 6, 7, 8]], 'jubba') + res = dat.mean(1) + assert_(res.info == dat.info) + res = dat.std(1) + assert_(res.info == dat.info) + res = dat.var(1) + assert_(res.info == dat.info) + + +class TestVdot: + def test_basic(self): + dt_numeric = np.typecodes['AllFloat'] + np.typecodes['AllInteger'] + dt_complex = np.typecodes['Complex'] + + # test real + a = np.eye(3) + for dt in dt_numeric + 'O': + b = a.astype(dt) + res = np.vdot(b, b) + assert_(np.isscalar(res)) + assert_equal(np.vdot(b, b), 3) + + # test complex + a = np.eye(3) * 1j + for dt in dt_complex + 'O': + b = a.astype(dt) + res = np.vdot(b, b) + assert_(np.isscalar(res)) + assert_equal(np.vdot(b, b), 3) + + # test boolean + b = np.eye(3, dtype=bool) + res = np.vdot(b, b) + assert_(np.isscalar(res)) + assert_equal(np.vdot(b, b), True) + + def test_vdot_array_order(self): + a = np.array([[1, 2], [3, 4]], order='C') + b = np.array([[1, 2], [3, 4]], order='F') + res = np.vdot(a, a) + + # integer arrays are exact + assert_equal(np.vdot(a, b), res) + assert_equal(np.vdot(b, a), res) + assert_equal(np.vdot(b, b), res) + + def test_vdot_uncontiguous(self): + for size in [2, 1000]: + # Different sizes match different branches in vdot. + a = np.zeros((size, 2, 2)) + b = np.zeros((size, 2, 2)) + a[:, 0, 0] = np.arange(size) + b[:, 0, 0] = np.arange(size) + 1 + # Make a and b uncontiguous: + a = a[..., 0] + b = b[..., 0] + + assert_equal(np.vdot(a, b), + np.vdot(a.flatten(), b.flatten())) + assert_equal(np.vdot(a, b.copy()), + np.vdot(a.flatten(), b.flatten())) + assert_equal(np.vdot(a.copy(), b), + np.vdot(a.flatten(), b.flatten())) + assert_equal(np.vdot(a.copy('F'), b), + np.vdot(a.flatten(), b.flatten())) + assert_equal(np.vdot(a, b.copy('F')), + np.vdot(a.flatten(), b.flatten())) + + +class TestDot: + N = 7 + + def _create_data(self): + rng = np.random.RandomState(128) + A = rng.random((4, 2)) + b1 = rng.random((2, 1)) + b2 = rng.random(2) + b3 = rng.random((1, 2)) + b4 = rng.random(4) + return A, b1, b2, b3, b4 + + def test_dotmatmat(self): + A, _, _, _, _ = self._create_data() + res = np.dot(A.transpose(), A) + tgt = np.array([[1.45046013, 0.86323640], + [0.86323640, 0.84934569]]) + assert_almost_equal(res, tgt, decimal=self.N) + + def test_dotmatvec(self): + A, b1, _, _, _ = self._create_data() + res = np.dot(A, b1) + tgt = np.array([[0.32114320], [0.04889721], + [0.15696029], [0.33612621]]) + assert_almost_equal(res, tgt, decimal=self.N) + + def test_dotmatvec2(self): + A, _, b2, _, _ = self._create_data() + res = np.dot(A, b2) + tgt = np.array([0.29677940, 0.04518649, 0.14468333, 0.31039293]) + assert_almost_equal(res, tgt, decimal=self.N) + + def test_dotvecmat(self): + A, _, _, _, b4 = self._create_data() + res = np.dot(b4, A) + tgt = np.array([1.23495091, 1.12222648]) + assert_almost_equal(res, tgt, decimal=self.N) + + def test_dotvecmat2(self): + A, _, _, b3, _ = self._create_data() + res = np.dot(b3, A.transpose()) + tgt = np.array([[0.58793804, 0.08957460, 0.30605758, 0.62716383]]) + assert_almost_equal(res, tgt, decimal=self.N) + + def test_dotvecmat3(self): + A, _, _, _, b4 = self._create_data() + res = np.dot(A.transpose(), b4) + tgt = np.array([1.23495091, 1.12222648]) + assert_almost_equal(res, tgt, decimal=self.N) + + def test_dotvecvecouter(self): + _, b1, _, b3, _ = self._create_data() + res = np.dot(b1, b3) + tgt = np.array([[0.20128610, 0.08400440], [0.07190947, 0.03001058]]) + assert_almost_equal(res, tgt, decimal=self.N) + + def test_dotvecvecinner(self): + _, b1, _, b3, _ = self._create_data() + res = np.dot(b3, b1) + tgt = np.array([[0.23129668]]) + assert_almost_equal(res, tgt, decimal=self.N) + + def test_dotcolumnvect1(self): + b1 = np.ones((3, 1)) + b2 = [5.3] + res = np.dot(b1, b2) + tgt = np.array([5.3, 5.3, 5.3]) + assert_almost_equal(res, tgt, decimal=self.N) + + def test_dotcolumnvect2(self): + b1 = np.ones((3, 1)).transpose() + b2 = [6.2] + res = np.dot(b2, b1) + tgt = np.array([6.2, 6.2, 6.2]) + assert_almost_equal(res, tgt, decimal=self.N) + + def test_dotvecscalar(self): + rng = np.random.RandomState(100) + b1 = rng.random((1, 1)) + b2 = rng.random((1, 4)) + res = np.dot(b1, b2) + tgt = np.array([[0.15126730, 0.23068496, 0.45905553, 0.00256425]]) + assert_almost_equal(res, tgt, decimal=self.N) + + def test_dotvecscalar2(self): + rng = np.random.RandomState(100) + b1 = rng.random((4, 1)) + b2 = rng.random((1, 1)) + res = np.dot(b1, b2) + tgt = np.array([[0.00256425], [0.00131359], [0.00200324], [0.00398638]]) + assert_almost_equal(res, tgt, decimal=self.N) + + def test_all(self): + dims = [(), (1,), (1, 1)] + dout = [(), (1,), (1, 1), (1,), (), (1,), (1, 1), (1,), (1, 1)] + for dim, (dim1, dim2) in zip(dout, itertools.product(dims, dims)): + b1 = np.zeros(dim1) + b2 = np.zeros(dim2) + res = np.dot(b1, b2) + tgt = np.zeros(dim) + assert_(res.shape == tgt.shape) + assert_almost_equal(res, tgt, decimal=self.N) + + def test_vecobject(self): + class Vec: + def __init__(self, sequence=None): + if sequence is None: + sequence = [] + self.array = np.array(sequence) + + def __add__(self, other): + out = Vec() + out.array = self.array + other.array + return out + + def __sub__(self, other): + out = Vec() + out.array = self.array - other.array + return out + + def __mul__(self, other): # with scalar + out = Vec(self.array.copy()) + out.array *= other + return out + + def __rmul__(self, other): + return self * other + + U_non_cont = np.transpose([[1., 1.], [1., 2.]]) + U_cont = np.ascontiguousarray(U_non_cont) + x = np.array([Vec([1., 0.]), Vec([0., 1.])]) + zeros = np.array([Vec([0., 0.]), Vec([0., 0.])]) + zeros_test = np.dot(U_cont, x) - np.dot(U_non_cont, x) + assert_equal(zeros[0].array, zeros_test[0].array) + assert_equal(zeros[1].array, zeros_test[1].array) + + def test_dot_2args(self): + + a = np.array([[1, 2], [3, 4]], dtype=float) + b = np.array([[1, 0], [1, 1]], dtype=float) + c = np.array([[3, 2], [7, 4]], dtype=float) + + d = dot(a, b) + assert_allclose(c, d) + + def test_dot_3args(self): + + np.random.seed(22) + f = np.random.random_sample((1024, 16)) + v = np.random.random_sample((16, 32)) + + r = np.empty((1024, 32)) + if HAS_REFCOUNT: + orig_refcount = sys.getrefcount(r) + for i in range(12): + dot(f, v, r) + if HAS_REFCOUNT: + assert_equal(sys.getrefcount(r), orig_refcount) + r2 = dot(f, v, out=None) + assert_array_equal(r2, r) + assert_(r is dot(f, v, out=r)) + + v = v[:, 0].copy() # v.shape == (16,) + r = r[:, 0].copy() # r.shape == (1024,) + r2 = dot(f, v) + assert_(r is dot(f, v, r)) + assert_array_equal(r2, r) + + def test_dot_3args_errors(self): + + np.random.seed(22) + f = np.random.random_sample((1024, 16)) + v = np.random.random_sample((16, 32)) + + r = np.empty((1024, 31)) + assert_raises(ValueError, dot, f, v, r) + + r = np.empty((1024,)) + assert_raises(ValueError, dot, f, v, r) + + r = np.empty((32,)) + assert_raises(ValueError, dot, f, v, r) + + r = np.empty((32, 1024)) + assert_raises(ValueError, dot, f, v, r) + assert_raises(ValueError, dot, f, v, r.T) + + r = np.empty((1024, 64)) + assert_raises(ValueError, dot, f, v, r[:, ::2]) + assert_raises(ValueError, dot, f, v, r[:, :32]) + + r = np.empty((1024, 32), dtype=np.float32) + assert_raises(ValueError, dot, f, v, r) + + r = np.empty((1024, 32), dtype=int) + assert_raises(ValueError, dot, f, v, r) + + def test_dot_out_result(self): + x = np.ones((), dtype=np.float16) + y = np.ones((5,), dtype=np.float16) + z = np.zeros((5,), dtype=np.float16) + res = x.dot(y, out=z) + assert np.array_equal(res, y) + assert np.array_equal(z, y) + + def test_dot_out_aliasing(self): + x = np.ones((), dtype=np.float16) + y = np.ones((5,), dtype=np.float16) + z = np.zeros((5,), dtype=np.float16) + res = x.dot(y, out=z) + z[0] = 2 + assert np.array_equal(res, z) + + def test_dot_array_order(self): + a = np.array([[1, 2], [3, 4]], order='C') + b = np.array([[1, 2], [3, 4]], order='F') + res = np.dot(a, a) + + # integer arrays are exact + assert_equal(np.dot(a, b), res) + assert_equal(np.dot(b, a), res) + assert_equal(np.dot(b, b), res) + + def test_accelerate_framework_sgemv_fix(self): + + def aligned_array(shape, align, dtype, order='C'): + d = dtype(0) + N = np.prod(shape) + tmp = np.zeros(N * d.nbytes + align, dtype=np.uint8) + address = tmp.__array_interface__["data"][0] + for offset in range(align): + if (address + offset) % align == 0: + break + tmp = tmp[offset:offset + N * d.nbytes].view(dtype=dtype) + return tmp.reshape(shape, order=order) + + def as_aligned(arr, align, dtype, order='C'): + aligned = aligned_array(arr.shape, align, dtype, order) + aligned[:] = arr[:] + return aligned + + def assert_dot_close(A, X, desired): + assert_allclose(np.dot(A, X), desired, rtol=1e-5, atol=1e-7) + + m = aligned_array(100, 15, np.float32) + s = aligned_array((100, 100), 15, np.float32) + np.dot(s, m) # this will always segfault if the bug is present + + testdata = itertools.product((15, 32), (10000,), (200, 89), ('C', 'F')) + for align, m, n, a_order in testdata: + # Calculation in double precision + A_d = np.random.rand(m, n) + X_d = np.random.rand(n) + desired = np.dot(A_d, X_d) + # Calculation with aligned single precision + A_f = as_aligned(A_d, align, np.float32, order=a_order) + X_f = as_aligned(X_d, align, np.float32) + assert_dot_close(A_f, X_f, desired) + # Strided A rows + A_d_2 = A_d[::2] + desired = np.dot(A_d_2, X_d) + A_f_2 = A_f[::2] + assert_dot_close(A_f_2, X_f, desired) + # Strided A columns, strided X vector + A_d_22 = A_d_2[:, ::2] + X_d_2 = X_d[::2] + desired = np.dot(A_d_22, X_d_2) + A_f_22 = A_f_2[:, ::2] + X_f_2 = X_f[::2] + assert_dot_close(A_f_22, X_f_2, desired) + # Check the strides are as expected + if a_order == 'F': + assert_equal(A_f_22.strides, (8, 8 * m)) + else: + assert_equal(A_f_22.strides, (8 * n, 8)) + assert_equal(X_f_2.strides, (8,)) + # Strides in A rows + cols only + X_f_2c = as_aligned(X_f_2, align, np.float32) + assert_dot_close(A_f_22, X_f_2c, desired) + # Strides just in A cols + A_d_12 = A_d[:, ::2] + desired = np.dot(A_d_12, X_d_2) + A_f_12 = A_f[:, ::2] + assert_dot_close(A_f_12, X_f_2c, desired) + # Strides in A cols and X + assert_dot_close(A_f_12, X_f_2, desired) + + @pytest.mark.slow + @pytest.mark.parametrize("dtype", [np.float64, np.complex128]) + @requires_memory(free_bytes=18e9) # complex case needs 18GiB+ + @pytest.mark.thread_unsafe(reason="crashes with low memory") + def test_huge_vectordot(self, dtype): + # Large vector multiplications are chunked with 32bit BLAS + # Test that the chunking does the right thing, see also gh-22262 + data = np.ones(2**30 + 100, dtype=dtype) + res = np.dot(data, data) + assert res == 2**30 + 100 + + def test_dtype_discovery_fails(self): + # See gh-14247, error checking was missing for failed dtype discovery + class BadObject: + def __array__(self, dtype=None, copy=None): + raise TypeError("just this tiny mint leaf") + + with pytest.raises(TypeError): + np.dot(BadObject(), BadObject()) + + with pytest.raises(TypeError): + np.dot(3.0, BadObject()) + + +class MatmulCommon: + """Common tests for '@' operator and numpy.matmul. + + """ + # Should work with these types. Will want to add + # "O" at some point + types = "?bhilqBHILQefdgFDGO" + + def test_exceptions(self): + dims = [ + ((1,), (2,)), # mismatched vector vector + ((2, 1,), (2,)), # mismatched matrix vector + ((2,), (1, 2)), # mismatched vector matrix + ((1, 2), (3, 1)), # mismatched matrix matrix + ((1,), ()), # vector scalar + ((), (1)), # scalar vector + ((1, 1), ()), # matrix scalar + ((), (1, 1)), # scalar matrix + ((2, 2, 1), (3, 1, 2)), # cannot broadcast + ] + + for dt, (dm1, dm2) in itertools.product(self.types, dims): + a = np.ones(dm1, dtype=dt) + b = np.ones(dm2, dtype=dt) + assert_raises(ValueError, self.matmul, a, b) + + def test_shapes(self): + dims = [ + ((1, 1), (2, 1, 1)), # broadcast first argument + ((2, 1, 1), (1, 1)), # broadcast second argument + ((2, 1, 1), (2, 1, 1)), # matrix stack sizes match + ] + + for dt, (dm1, dm2) in itertools.product(self.types, dims): + a = np.ones(dm1, dtype=dt) + b = np.ones(dm2, dtype=dt) + res = self.matmul(a, b) + assert_(res.shape == (2, 1, 1)) + + # vector vector returns scalars. + for dt in self.types: + a = np.ones((2,), dtype=dt) + b = np.ones((2,), dtype=dt) + c = self.matmul(a, b) + assert_(np.array(c).shape == ()) + + def test_result_types(self): + mat = np.ones((1, 1)) + vec = np.ones((1,)) + for dt in self.types: + m = mat.astype(dt) + v = vec.astype(dt) + for arg in [(m, v), (v, m), (m, m)]: + res = self.matmul(*arg) + assert_(res.dtype == dt) + + # vector vector returns scalars + if dt != "O": + res = self.matmul(v, v) + assert_(type(res) is np.dtype(dt).type) + + def test_scalar_output(self): + vec1 = np.array([2]) + vec2 = np.array([3, 4]).reshape(1, -1) + tgt = np.array([6, 8]) + for dt in self.types[1:]: + v1 = vec1.astype(dt) + v2 = vec2.astype(dt) + res = self.matmul(v1, v2) + assert_equal(res, tgt) + res = self.matmul(v2.T, v1) + assert_equal(res, tgt) + + # boolean type + vec = np.array([True, True], dtype='?').reshape(1, -1) + res = self.matmul(vec[:, 0], vec) + assert_equal(res, True) + + def test_vector_vector_values(self): + vec1 = np.array([1, 2]) + vec2 = np.array([3, 4]).reshape(-1, 1) + tgt1 = np.array([11]) + tgt2 = np.array([[3, 6], [4, 8]]) + for dt in self.types[1:]: + v1 = vec1.astype(dt) + v2 = vec2.astype(dt) + res = self.matmul(v1, v2) + assert_equal(res, tgt1) + # no broadcast, we must make v1 into a 2d ndarray + res = self.matmul(v2, v1.reshape(1, -1)) + assert_equal(res, tgt2) + + # boolean type + vec = np.array([True, True], dtype='?') + res = self.matmul(vec, vec) + assert_equal(res, True) + + def test_vector_matrix_values(self): + vec = np.array([1, 2]) + mat1 = np.array([[1, 2], [3, 4]]) + mat2 = np.stack([mat1] * 2, axis=0) + tgt1 = np.array([7, 10]) + tgt2 = np.stack([tgt1] * 2, axis=0) + for dt in self.types[1:]: + v = vec.astype(dt) + m1 = mat1.astype(dt) + m2 = mat2.astype(dt) + res = self.matmul(v, m1) + assert_equal(res, tgt1) + res = self.matmul(v, m2) + assert_equal(res, tgt2) + + # boolean type + vec = np.array([True, False]) + mat1 = np.array([[True, False], [False, True]]) + mat2 = np.stack([mat1] * 2, axis=0) + tgt1 = np.array([True, False]) + tgt2 = np.stack([tgt1] * 2, axis=0) + + res = self.matmul(vec, mat1) + assert_equal(res, tgt1) + res = self.matmul(vec, mat2) + assert_equal(res, tgt2) + + def test_matrix_vector_values(self): + vec = np.array([1, 2]) + mat1 = np.array([[1, 2], [3, 4]]) + mat2 = np.stack([mat1] * 2, axis=0) + tgt1 = np.array([5, 11]) + tgt2 = np.stack([tgt1] * 2, axis=0) + for dt in self.types[1:]: + v = vec.astype(dt) + m1 = mat1.astype(dt) + m2 = mat2.astype(dt) + res = self.matmul(m1, v) + assert_equal(res, tgt1) + res = self.matmul(m2, v) + assert_equal(res, tgt2) + + # boolean type + vec = np.array([True, False]) + mat1 = np.array([[True, False], [False, True]]) + mat2 = np.stack([mat1] * 2, axis=0) + tgt1 = np.array([True, False]) + tgt2 = np.stack([tgt1] * 2, axis=0) + + res = self.matmul(vec, mat1) + assert_equal(res, tgt1) + res = self.matmul(vec, mat2) + assert_equal(res, tgt2) + + def test_matrix_matrix_values(self): + mat1 = np.array([[1, 2], [3, 4]]) + mat2 = np.array([[1, 0], [1, 1]]) + mat12 = np.stack([mat1, mat2], axis=0) + mat21 = np.stack([mat2, mat1], axis=0) + tgt11 = np.array([[7, 10], [15, 22]]) + tgt12 = np.array([[3, 2], [7, 4]]) + tgt21 = np.array([[1, 2], [4, 6]]) + tgt12_21 = np.stack([tgt12, tgt21], axis=0) + tgt11_12 = np.stack((tgt11, tgt12), axis=0) + tgt11_21 = np.stack((tgt11, tgt21), axis=0) + for dt in self.types[1:]: + m1 = mat1.astype(dt) + m2 = mat2.astype(dt) + m12 = mat12.astype(dt) + m21 = mat21.astype(dt) + + # matrix @ matrix + res = self.matmul(m1, m2) + assert_equal(res, tgt12) + res = self.matmul(m2, m1) + assert_equal(res, tgt21) + + # stacked @ matrix + res = self.matmul(m12, m1) + assert_equal(res, tgt11_21) + + # matrix @ stacked + res = self.matmul(m1, m12) + assert_equal(res, tgt11_12) + + # stacked @ stacked + res = self.matmul(m12, m21) + assert_equal(res, tgt12_21) + + # boolean type + m1 = np.array([[1, 1], [0, 0]], dtype=np.bool) + m2 = np.array([[1, 0], [1, 1]], dtype=np.bool) + m12 = np.stack([m1, m2], axis=0) + m21 = np.stack([m2, m1], axis=0) + tgt11 = m1 + tgt12 = m1 + tgt21 = np.array([[1, 1], [1, 1]], dtype=np.bool) + tgt12_21 = np.stack([tgt12, tgt21], axis=0) + tgt11_12 = np.stack((tgt11, tgt12), axis=0) + tgt11_21 = np.stack((tgt11, tgt21), axis=0) + + # matrix @ matrix + res = self.matmul(m1, m2) + assert_equal(res, tgt12) + res = self.matmul(m2, m1) + assert_equal(res, tgt21) + + # stacked @ matrix + res = self.matmul(m12, m1) + assert_equal(res, tgt11_21) + + # matrix @ stacked + res = self.matmul(m1, m12) + assert_equal(res, tgt11_12) + + # stacked @ stacked + res = self.matmul(m12, m21) + assert_equal(res, tgt12_21) + + +class TestMatmul(MatmulCommon): + matmul = np.matmul + + def test_out_arg(self): + a = np.ones((5, 2), dtype=float) + b = np.array([[1, 3], [5, 7]], dtype=float) + tgt = np.dot(a, b) + + # test as positional argument + msg = "out positional argument" + out = np.zeros((5, 2), dtype=float) + self.matmul(a, b, out) + assert_array_equal(out, tgt, err_msg=msg) + + # test as keyword argument + msg = "out keyword argument" + out = np.zeros((5, 2), dtype=float) + self.matmul(a, b, out=out) + assert_array_equal(out, tgt, err_msg=msg) + + # test out with not allowed type cast (safe casting) + msg = "Cannot cast ufunc .* output" + out = np.zeros((5, 2), dtype=np.int32) + assert_raises_regex(TypeError, msg, self.matmul, a, b, out=out) + + # test out with type upcast to complex + out = np.zeros((5, 2), dtype=np.complex128) + c = self.matmul(a, b, out=out) + assert_(c is out) + with warnings.catch_warnings(): + warnings.simplefilter('ignore', ComplexWarning) + c = c.astype(tgt.dtype) + assert_array_equal(c, tgt) + + def test_empty_out(self): + # Check that the output cannot be broadcast, so that it cannot be + # size zero when the outer dimensions (iterator size) has size zero. + arr = np.ones((0, 1, 1)) + out = np.ones((1, 1, 1)) + assert self.matmul(arr, arr).shape == (0, 1, 1) + + with pytest.raises(ValueError, match=r"non-broadcastable"): + self.matmul(arr, arr, out=out) + + def test_out_contiguous(self): + a = np.ones((5, 2), dtype=float) + b = np.array([[1, 3], [5, 7]], dtype=float) + v = np.array([1, 3], dtype=float) + tgt = np.dot(a, b) + tgt_mv = np.dot(a, v) + + # test out non-contiguous + out = np.ones((5, 2, 2), dtype=float) + c = self.matmul(a, b, out=out[..., 0]) + assert c.base is out + assert_array_equal(c, tgt) + c = self.matmul(a, v, out=out[:, 0, 0]) + assert_array_equal(c, tgt_mv) + c = self.matmul(v, a.T, out=out[:, 0, 0]) + assert_array_equal(c, tgt_mv) + + # test out contiguous in only last dim + out = np.ones((10, 2), dtype=float) + c = self.matmul(a, b, out=out[::2, :]) + assert_array_equal(c, tgt) + + # test transposes of out, args + out = np.ones((5, 2), dtype=float) + c = self.matmul(b.T, a.T, out=out.T) + assert_array_equal(out, tgt) + + m1 = np.arange(15.).reshape(5, 3) + m2 = np.arange(21.).reshape(3, 7) + m3 = np.arange(30.).reshape(5, 6)[:, ::2] # non-contiguous + vc = np.arange(10.) + vr = np.arange(6.) + m0 = np.zeros((3, 0)) + + @pytest.mark.parametrize('args', ( + # matrix-matrix + (m1, m2), (m2.T, m1.T), (m2.T.copy(), m1.T), (m2.T, m1.T.copy()), + # matrix-matrix-transpose, contiguous and non + (m1, m1.T), (m1.T, m1), (m1, m3.T), (m3, m1.T), + (m3, m3.T), (m3.T, m3), + # matrix-matrix non-contiguous + (m3, m2), (m2.T, m3.T), (m2.T.copy(), m3.T), + # vector-matrix, matrix-vector, contiguous + (m1, vr[:3]), (vc[:5], m1), (m1.T, vc[:5]), (vr[:3], m1.T), + # vector-matrix, matrix-vector, vector non-contiguous + (m1, vr[::2]), (vc[::2], m1), (m1.T, vc[::2]), (vr[::2], m1.T), + # vector-matrix, matrix-vector, matrix non-contiguous + (m3, vr[:3]), (vc[:5], m3), (m3.T, vc[:5]), (vr[:3], m3.T), + # vector-matrix, matrix-vector, both non-contiguous + (m3, vr[::2]), (vc[::2], m3), (m3.T, vc[::2]), (vr[::2], m3.T), + # size == 0 + (m0, m0.T), (m0.T, m0), (m1, m0), (m0.T, m1.T), + )) + def test_dot_equivalent(self, args): + r1 = np.matmul(*args) + r2 = np.dot(*args) + assert_equal(r1, r2) + + r3 = np.matmul(args[0].copy(), args[1].copy()) + assert_equal(r1, r3) + + # issue 29164 with extra checks + @pytest.mark.parametrize('dtype', ( + np.float32, np.float64, np.complex64, np.complex128 + )) + def test_dot_equivalent_matrix_matrix_blastypes(self, dtype): + modes = list(itertools.product(['C', 'F'], [True, False])) + + def apply_mode(m, mode): + order, is_contiguous = mode + if is_contiguous: + return m.copy() if order == 'C' else m.T.copy().T + + retval = np.zeros( + (m.shape[0] * 2, m.shape[1] * 2), dtype=m.dtype, order=order + )[::2, ::2] + retval[...] = m + return retval + + is_complex = np.issubdtype(dtype, np.complexfloating) + m1 = self.m1.astype(dtype) + (1j if is_complex else 0) + m2 = self.m2.astype(dtype) + (1j if is_complex else 0) + dot_res = np.dot(m1, m2) + mo = np.zeros_like(dot_res) + + for mode in itertools.product(*[modes] * 3): + m1_, m2_, mo_ = [apply_mode(*x) for x in zip([m1, m2, mo], mode)] + assert_equal(np.matmul(m1_, m2_, out=mo_), dot_res) + + def test_matmul_object(self): + import fractions + + f = np.vectorize(fractions.Fraction) + + def random_ints(): + return np.random.randint(1, 1000, size=(10, 3, 3)) + M1 = f(random_ints(), random_ints()) + M2 = f(random_ints(), random_ints()) + + M3 = self.matmul(M1, M2) + + [N1, N2, N3] = [a.astype(float) for a in [M1, M2, M3]] + + assert_allclose(N3, self.matmul(N1, N2)) + + def test_matmul_object_type_scalar(self): + from fractions import Fraction as F + v = np.array([F(2, 3), F(5, 7)]) + res = self.matmul(v, v) + assert_(type(res) is F) + + def test_matmul_empty(self): + a = np.empty((3, 0), dtype=object) + b = np.empty((0, 3), dtype=object) + c = np.zeros((3, 3)) + assert_array_equal(np.matmul(a, b), c) + + def test_matmul_exception_multiply(self): + # test that matmul fails if `__mul__` is missing + class add_not_multiply: + def __add__(self, other): + return self + a = np.full((3, 3), add_not_multiply()) + with assert_raises(TypeError): + b = np.matmul(a, a) + + def test_matmul_exception_add(self): + # test that matmul fails if `__add__` is missing + class multiply_not_add: + def __mul__(self, other): + return self + a = np.full((3, 3), multiply_not_add()) + with assert_raises(TypeError): + b = np.matmul(a, a) + + def test_matmul_bool(self): + # gh-14439 + a = np.array([[1, 0], [1, 1]], dtype=bool) + assert np.max(a.view(np.uint8)) == 1 + b = np.matmul(a, a) + # matmul with boolean output should always be 0, 1 + assert np.max(b.view(np.uint8)) == 1 + + rg = np.random.default_rng(np.random.PCG64(43)) + d = rg.integers(2, size=4 * 5, dtype=np.int8) + d = d.reshape(4, 5) > 0 + out1 = np.matmul(d, d.reshape(5, 4)) + out2 = np.dot(d, d.reshape(5, 4)) + assert_equal(out1, out2) + + c = np.matmul(np.zeros((2, 0), dtype=bool), np.zeros(0, dtype=bool)) + assert not np.any(c) + + +class TestMatmulOperator(MatmulCommon): + import operator + matmul = operator.matmul + + def test_array_priority_override(self): + + class A: + __array_priority__ = 1000 + + def __matmul__(self, other): + return "A" + + def __rmatmul__(self, other): + return "A" + + a = A() + b = np.ones(2) + assert_equal(self.matmul(a, b), "A") + assert_equal(self.matmul(b, a), "A") + + def test_matmul_raises(self): + assert_raises(TypeError, self.matmul, np.int8(5), np.int8(5)) + assert_raises(TypeError, self.matmul, np.void(b'abc'), np.void(b'abc')) + assert_raises(TypeError, self.matmul, np.arange(10), np.void(b'abc')) + + +class TestMatmulInplace: + DTYPES = {} + for i in MatmulCommon.types: + for j in MatmulCommon.types: + if np.can_cast(j, i): + DTYPES[f"{i}-{j}"] = (np.dtype(i), np.dtype(j)) + + @pytest.mark.parametrize("dtype1,dtype2", DTYPES.values(), ids=DTYPES) + def test_basic(self, dtype1: np.dtype, dtype2: np.dtype) -> None: + a = np.arange(10).reshape(5, 2).astype(dtype1) + a_id = id(a) + b = np.ones((2, 2), dtype=dtype2) + + ref = a @ b + a @= b + + assert id(a) == a_id + assert a.dtype == dtype1 + assert a.shape == (5, 2) + if dtype1.kind in "fc": + np.testing.assert_allclose(a, ref) + else: + np.testing.assert_array_equal(a, ref) + + SHAPES = { + "2d_large": ((10**5, 10), (10, 10)), + "3d_large": ((10**4, 10, 10), (1, 10, 10)), + "1d": ((3,), (3,)), + "2d_1d": ((3, 3), (3,)), + "1d_2d": ((3,), (3, 3)), + "2d_broadcast": ((3, 3), (3, 1)), + "2d_broadcast_reverse": ((1, 3), (3, 3)), + "3d_broadcast1": ((3, 3, 3), (1, 3, 1)), + "3d_broadcast2": ((3, 3, 3), (1, 3, 3)), + "3d_broadcast3": ((3, 3, 3), (3, 3, 1)), + "3d_broadcast_reverse1": ((1, 3, 3), (3, 3, 3)), + "3d_broadcast_reverse2": ((3, 1, 3), (3, 3, 3)), + "3d_broadcast_reverse3": ((1, 1, 3), (3, 3, 3)), + } + + @pytest.mark.parametrize("a_shape,b_shape", SHAPES.values(), ids=SHAPES) + def test_shapes(self, a_shape: tuple[int, ...], b_shape: tuple[int, ...]): + a_size = np.prod(a_shape) + a = np.arange(a_size).reshape(a_shape).astype(np.float64) + a_id = id(a) + + b_size = np.prod(b_shape) + b = np.arange(b_size).reshape(b_shape) + + ref = a @ b + if ref.shape != a_shape: + with pytest.raises(ValueError): + a @= b + return + else: + a @= b + + assert id(a) == a_id + assert a.dtype.type == np.float64 + assert a.shape == a_shape + np.testing.assert_allclose(a, ref) + + +def test_matmul_axes(): + a = np.arange(3 * 4 * 5).reshape(3, 4, 5) + c = np.matmul(a, a, axes=[(-2, -1), (-1, -2), (1, 2)]) + assert c.shape == (3, 4, 4) + d = np.matmul(a, a, axes=[(-2, -1), (-1, -2), (0, 1)]) + assert d.shape == (4, 4, 3) + e = np.swapaxes(d, 0, 2) + assert_array_equal(e, c) + f = np.matmul(a, np.arange(3), axes=[(1, 0), (0), (0)]) + assert f.shape == (4, 5) + + +class TestInner: + + def test_inner_type_mismatch(self): + c = 1. + A = np.array((1, 1), dtype='i,i') + + assert_raises(TypeError, np.inner, c, A) + assert_raises(TypeError, np.inner, A, c) + + def test_inner_scalar_and_vector(self): + for dt in np.typecodes['AllInteger'] + np.typecodes['AllFloat'] + '?': + sca = np.array(3, dtype=dt)[()] + vec = np.array([1, 2], dtype=dt) + desired = np.array([3, 6], dtype=dt) + assert_equal(np.inner(vec, sca), desired) + assert_equal(np.inner(sca, vec), desired) + + def test_vecself(self): + # Ticket 844. + # Inner product of a vector with itself segfaults or give + # meaningless result + a = np.zeros(shape=(1, 80), dtype=np.float64) + p = np.inner(a, a) + assert_almost_equal(p, 0, decimal=14) + + def test_inner_product_with_various_contiguities(self): + # github issue 6532 + for dt in np.typecodes['AllInteger'] + np.typecodes['AllFloat'] + '?': + # check an inner product involving a matrix transpose + A = np.array([[1, 2], [3, 4]], dtype=dt) + B = np.array([[1, 3], [2, 4]], dtype=dt) + C = np.array([1, 1], dtype=dt) + desired = np.array([4, 6], dtype=dt) + assert_equal(np.inner(A.T, C), desired) + assert_equal(np.inner(C, A.T), desired) + assert_equal(np.inner(B, C), desired) + assert_equal(np.inner(C, B), desired) + # check a matrix product + desired = np.array([[7, 10], [15, 22]], dtype=dt) + assert_equal(np.inner(A, B), desired) + # check the syrk vs. gemm paths + desired = np.array([[5, 11], [11, 25]], dtype=dt) + assert_equal(np.inner(A, A), desired) + assert_equal(np.inner(A, A.copy()), desired) + # check an inner product involving an aliased and reversed view + a = np.arange(5).astype(dt) + b = a[::-1] + desired = np.array(10, dtype=dt).item() + assert_equal(np.inner(b, a), desired) + + def test_3d_tensor(self): + for dt in np.typecodes['AllInteger'] + np.typecodes['AllFloat'] + '?': + a = np.arange(24).reshape(2, 3, 4).astype(dt) + b = np.arange(24, 48).reshape(2, 3, 4).astype(dt) + desired = np.array( + [[[[ 158, 182, 206], + [ 230, 254, 278]], + + [[ 566, 654, 742], + [ 830, 918, 1006]], + + [[ 974, 1126, 1278], + [1430, 1582, 1734]]], + + [[[1382, 1598, 1814], + [2030, 2246, 2462]], + + [[1790, 2070, 2350], + [2630, 2910, 3190]], + + [[2198, 2542, 2886], + [3230, 3574, 3918]]]] + ).astype(dt) + assert_equal(np.inner(a, b), desired) + assert_equal(np.inner(b, a).transpose(2, 3, 0, 1), desired) + + +class TestChoose: + def _create_data(self): + x = 2 * np.ones((3,), dtype=int) + y = 3 * np.ones((3,), dtype=int) + x2 = 2 * np.ones((2, 3), dtype=int) + y2 = 3 * np.ones((2, 3), dtype=int) + ind = [0, 0, 1] + return x, y, x2, y2, ind + + def test_basic(self): + x, y, _, _, ind = self._create_data() + A = np.choose(ind, (x, y)) + assert_equal(A, [2, 2, 3]) + + def test_broadcast1(self): + _, _, x2, y2, ind = self._create_data() + A = np.choose(ind, (x2, y2)) + assert_equal(A, [[2, 2, 3], [2, 2, 3]]) + + def test_broadcast2(self): + x, _, _, y2, ind = self._create_data() + A = np.choose(ind, (x, y2)) + assert_equal(A, [[2, 2, 3], [2, 2, 3]]) + + @pytest.mark.parametrize("ops", + [(1000, np.array([1], dtype=np.uint8)), + (-1, np.array([1], dtype=np.uint8)), + (1., np.float32(3)), + (1., np.array([3], dtype=np.float32))],) + def test_output_dtype(self, ops): + expected_dt = np.result_type(*ops) + assert np.choose([0], ops).dtype == expected_dt + + def test_dimension_and_args_limit(self): + # Maxdims for the legacy iterator is 32, but the maximum number + # of arguments is actually larger (a itself also counts here) + a = np.ones((1,) * 32, dtype=np.intp) + res = a.choose([0, a] + [2] * 61) + with pytest.raises(ValueError, + match="Need at least 0 and at most 64 array objects"): + a.choose([0, a] + [2] * 62) + + assert_array_equal(res, a) + # Choose is unfortunately limited to 32 dims as of NumPy 2.0 + a = np.ones((1,) * 60, dtype=np.intp) + with pytest.raises(RuntimeError, + match=".*32 dimensions but the array has 60"): + a.choose([a, a]) + + +class TestRepeat: + def _create_data(self): + m = np.array([1, 2, 3, 4, 5, 6]) + m_rect = m.reshape((2, 3)) + return m, m_rect + + def test_basic(self): + m, _ = self._create_data() + A = np.repeat(m, [1, 3, 2, 1, 1, 2]) + assert_equal(A, [1, 2, 2, 2, 3, + 3, 4, 5, 6, 6]) + + def test_broadcast1(self): + m, _ = self._create_data() + A = np.repeat(m, 2) + assert_equal(A, [1, 1, 2, 2, 3, 3, + 4, 4, 5, 5, 6, 6]) + + def test_axis_spec(self): + _, m_rect = self._create_data() + A = np.repeat(m_rect, [2, 1], axis=0) + assert_equal(A, [[1, 2, 3], + [1, 2, 3], + [4, 5, 6]]) + + A = np.repeat(m_rect, [1, 3, 2], axis=1) + assert_equal(A, [[1, 2, 2, 2, 3, 3], + [4, 5, 5, 5, 6, 6]]) + + def test_broadcast2(self): + _, m_rect = self._create_data() + A = np.repeat(m_rect, 2, axis=0) + assert_equal(A, [[1, 2, 3], + [1, 2, 3], + [4, 5, 6], + [4, 5, 6]]) + + A = np.repeat(m_rect, 2, axis=1) + assert_equal(A, [[1, 1, 2, 2, 3, 3], + [4, 4, 5, 5, 6, 6]]) + + +# TODO: test for multidimensional +NEIGH_MODE = {'zero': 0, 'one': 1, 'constant': 2, 'circular': 3, 'mirror': 4} + + +@pytest.mark.parametrize('dt', [float, Decimal], ids=['float', 'object']) +class TestNeighborhoodIter: + # Simple, 2d tests + def test_simple2d(self, dt): + # Test zero and one padding for simple data type + x = np.array([[0, 1], [2, 3]], dtype=dt) + r = [np.array([[0, 0, 0], [0, 0, 1]], dtype=dt), + np.array([[0, 0, 0], [0, 1, 0]], dtype=dt), + np.array([[0, 0, 1], [0, 2, 3]], dtype=dt), + np.array([[0, 1, 0], [2, 3, 0]], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator( + x, [-1, 0, -1, 1], x[0], NEIGH_MODE['zero']) + assert_array_equal(l, r) + + r = [np.array([[1, 1, 1], [1, 0, 1]], dtype=dt), + np.array([[1, 1, 1], [0, 1, 1]], dtype=dt), + np.array([[1, 0, 1], [1, 2, 3]], dtype=dt), + np.array([[0, 1, 1], [2, 3, 1]], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator( + x, [-1, 0, -1, 1], x[0], NEIGH_MODE['one']) + assert_array_equal(l, r) + + r = [np.array([[4, 4, 4], [4, 0, 1]], dtype=dt), + np.array([[4, 4, 4], [0, 1, 4]], dtype=dt), + np.array([[4, 0, 1], [4, 2, 3]], dtype=dt), + np.array([[0, 1, 4], [2, 3, 4]], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator( + x, [-1, 0, -1, 1], 4, NEIGH_MODE['constant']) + assert_array_equal(l, r) + + # Test with start in the middle + r = [np.array([[4, 0, 1], [4, 2, 3]], dtype=dt), + np.array([[0, 1, 4], [2, 3, 4]], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator( + x, [-1, 0, -1, 1], 4, NEIGH_MODE['constant'], 2) + assert_array_equal(l, r) + + def test_mirror2d(self, dt): + x = np.array([[0, 1], [2, 3]], dtype=dt) + r = [np.array([[0, 0, 1], [0, 0, 1]], dtype=dt), + np.array([[0, 1, 1], [0, 1, 1]], dtype=dt), + np.array([[0, 0, 1], [2, 2, 3]], dtype=dt), + np.array([[0, 1, 1], [2, 3, 3]], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator( + x, [-1, 0, -1, 1], x[0], NEIGH_MODE['mirror']) + assert_array_equal(l, r) + + # Simple, 1d tests + def test_simple(self, dt): + # Test padding with constant values + x = np.linspace(1, 5, 5).astype(dt) + r = [[0, 1, 2], [1, 2, 3], [2, 3, 4], [3, 4, 5], [4, 5, 0]] + l = _multiarray_tests.test_neighborhood_iterator( + x, [-1, 1], x[0], NEIGH_MODE['zero']) + assert_array_equal(l, r) + + r = [[1, 1, 2], [1, 2, 3], [2, 3, 4], [3, 4, 5], [4, 5, 1]] + l = _multiarray_tests.test_neighborhood_iterator( + x, [-1, 1], x[0], NEIGH_MODE['one']) + assert_array_equal(l, r) + + r = [[x[4], 1, 2], [1, 2, 3], [2, 3, 4], [3, 4, 5], [4, 5, x[4]]] + l = _multiarray_tests.test_neighborhood_iterator( + x, [-1, 1], x[4], NEIGH_MODE['constant']) + assert_array_equal(l, r) + + # Test mirror modes + def test_mirror(self, dt): + x = np.linspace(1, 5, 5).astype(dt) + r = np.array([[2, 1, 1, 2, 3], [1, 1, 2, 3, 4], [1, 2, 3, 4, 5], + [2, 3, 4, 5, 5], [3, 4, 5, 5, 4]], dtype=dt) + l = _multiarray_tests.test_neighborhood_iterator( + x, [-2, 2], x[1], NEIGH_MODE['mirror']) + assert_([i.dtype == dt for i in l]) + assert_array_equal(l, r) + + # Circular mode + def test_circular(self, dt): + x = np.linspace(1, 5, 5).astype(dt) + r = np.array([[4, 5, 1, 2, 3], [5, 1, 2, 3, 4], [1, 2, 3, 4, 5], + [2, 3, 4, 5, 1], [3, 4, 5, 1, 2]], dtype=dt) + l = _multiarray_tests.test_neighborhood_iterator( + x, [-2, 2], x[0], NEIGH_MODE['circular']) + assert_array_equal(l, r) + + +# Test stacking neighborhood iterators +class TestStackedNeighborhoodIter: + # Simple, 1d test: stacking 2 constant-padded neigh iterators + def test_simple_const(self): + dt = np.float64 + # Test zero and one padding for simple data type + x = np.array([1, 2, 3], dtype=dt) + r = [np.array([0], dtype=dt), + np.array([0], dtype=dt), + np.array([1], dtype=dt), + np.array([2], dtype=dt), + np.array([3], dtype=dt), + np.array([0], dtype=dt), + np.array([0], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator_oob( + x, [-2, 4], NEIGH_MODE['zero'], [0, 0], NEIGH_MODE['zero']) + assert_array_equal(l, r) + + r = [np.array([1, 0, 1], dtype=dt), + np.array([0, 1, 2], dtype=dt), + np.array([1, 2, 3], dtype=dt), + np.array([2, 3, 0], dtype=dt), + np.array([3, 0, 1], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator_oob( + x, [-1, 3], NEIGH_MODE['zero'], [-1, 1], NEIGH_MODE['one']) + assert_array_equal(l, r) + + # 2nd simple, 1d test: stacking 2 neigh iterators, mixing const padding and + # mirror padding + def test_simple_mirror(self): + dt = np.float64 + # Stacking zero on top of mirror + x = np.array([1, 2, 3], dtype=dt) + r = [np.array([0, 1, 1], dtype=dt), + np.array([1, 1, 2], dtype=dt), + np.array([1, 2, 3], dtype=dt), + np.array([2, 3, 3], dtype=dt), + np.array([3, 3, 0], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator_oob( + x, [-1, 3], NEIGH_MODE['mirror'], [-1, 1], NEIGH_MODE['zero']) + assert_array_equal(l, r) + + # Stacking mirror on top of zero + x = np.array([1, 2, 3], dtype=dt) + r = [np.array([1, 0, 0], dtype=dt), + np.array([0, 0, 1], dtype=dt), + np.array([0, 1, 2], dtype=dt), + np.array([1, 2, 3], dtype=dt), + np.array([2, 3, 0], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator_oob( + x, [-1, 3], NEIGH_MODE['zero'], [-2, 0], NEIGH_MODE['mirror']) + assert_array_equal(l, r) + + # Stacking mirror on top of zero: 2nd + x = np.array([1, 2, 3], dtype=dt) + r = [np.array([0, 1, 2], dtype=dt), + np.array([1, 2, 3], dtype=dt), + np.array([2, 3, 0], dtype=dt), + np.array([3, 0, 0], dtype=dt), + np.array([0, 0, 3], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator_oob( + x, [-1, 3], NEIGH_MODE['zero'], [0, 2], NEIGH_MODE['mirror']) + assert_array_equal(l, r) + + # Stacking mirror on top of zero: 3rd + x = np.array([1, 2, 3], dtype=dt) + r = [np.array([1, 0, 0, 1, 2], dtype=dt), + np.array([0, 0, 1, 2, 3], dtype=dt), + np.array([0, 1, 2, 3, 0], dtype=dt), + np.array([1, 2, 3, 0, 0], dtype=dt), + np.array([2, 3, 0, 0, 3], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator_oob( + x, [-1, 3], NEIGH_MODE['zero'], [-2, 2], NEIGH_MODE['mirror']) + assert_array_equal(l, r) + + # 3rd simple, 1d test: stacking 2 neigh iterators, mixing const padding and + # circular padding + def test_simple_circular(self): + dt = np.float64 + # Stacking zero on top of mirror + x = np.array([1, 2, 3], dtype=dt) + r = [np.array([0, 3, 1], dtype=dt), + np.array([3, 1, 2], dtype=dt), + np.array([1, 2, 3], dtype=dt), + np.array([2, 3, 1], dtype=dt), + np.array([3, 1, 0], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator_oob( + x, [-1, 3], NEIGH_MODE['circular'], [-1, 1], NEIGH_MODE['zero']) + assert_array_equal(l, r) + + # Stacking mirror on top of zero + x = np.array([1, 2, 3], dtype=dt) + r = [np.array([3, 0, 0], dtype=dt), + np.array([0, 0, 1], dtype=dt), + np.array([0, 1, 2], dtype=dt), + np.array([1, 2, 3], dtype=dt), + np.array([2, 3, 0], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator_oob( + x, [-1, 3], NEIGH_MODE['zero'], [-2, 0], NEIGH_MODE['circular']) + assert_array_equal(l, r) + + # Stacking mirror on top of zero: 2nd + x = np.array([1, 2, 3], dtype=dt) + r = [np.array([0, 1, 2], dtype=dt), + np.array([1, 2, 3], dtype=dt), + np.array([2, 3, 0], dtype=dt), + np.array([3, 0, 0], dtype=dt), + np.array([0, 0, 1], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator_oob( + x, [-1, 3], NEIGH_MODE['zero'], [0, 2], NEIGH_MODE['circular']) + assert_array_equal(l, r) + + # Stacking mirror on top of zero: 3rd + x = np.array([1, 2, 3], dtype=dt) + r = [np.array([3, 0, 0, 1, 2], dtype=dt), + np.array([0, 0, 1, 2, 3], dtype=dt), + np.array([0, 1, 2, 3, 0], dtype=dt), + np.array([1, 2, 3, 0, 0], dtype=dt), + np.array([2, 3, 0, 0, 1], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator_oob( + x, [-1, 3], NEIGH_MODE['zero'], [-2, 2], NEIGH_MODE['circular']) + assert_array_equal(l, r) + + # 4th simple, 1d test: stacking 2 neigh iterators, but with lower iterator + # being strictly within the array + def test_simple_strict_within(self): + dt = np.float64 + # Stacking zero on top of zero, first neighborhood strictly inside the + # array + x = np.array([1, 2, 3], dtype=dt) + r = [np.array([1, 2, 3, 0], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator_oob( + x, [1, 1], NEIGH_MODE['zero'], [-1, 2], NEIGH_MODE['zero']) + assert_array_equal(l, r) + + # Stacking mirror on top of zero, first neighborhood strictly inside the + # array + x = np.array([1, 2, 3], dtype=dt) + r = [np.array([1, 2, 3, 3], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator_oob( + x, [1, 1], NEIGH_MODE['zero'], [-1, 2], NEIGH_MODE['mirror']) + assert_array_equal(l, r) + + # Stacking mirror on top of zero, first neighborhood strictly inside the + # array + x = np.array([1, 2, 3], dtype=dt) + r = [np.array([1, 2, 3, 1], dtype=dt)] + l = _multiarray_tests.test_neighborhood_iterator_oob( + x, [1, 1], NEIGH_MODE['zero'], [-1, 2], NEIGH_MODE['circular']) + assert_array_equal(l, r) + +class TestWarnings: + + def test_complex_warning(self): + x = np.array([1, 2]) + y = np.array([1 - 2j, 1 + 2j]) + + with warnings.catch_warnings(): + warnings.simplefilter("error", ComplexWarning) + assert_raises(ComplexWarning, x.__setitem__, slice(None), y) + assert_equal(x, [1, 2]) + + +class TestMinScalarType: + + def test_usigned_shortshort(self): + dt = np.min_scalar_type(2**8 - 1) + wanted = np.dtype('uint8') + assert_equal(wanted, dt) + + def test_usigned_short(self): + dt = np.min_scalar_type(2**16 - 1) + wanted = np.dtype('uint16') + assert_equal(wanted, dt) + + def test_usigned_int(self): + dt = np.min_scalar_type(2**32 - 1) + wanted = np.dtype('uint32') + assert_equal(wanted, dt) + + def test_usigned_longlong(self): + dt = np.min_scalar_type(2**63 - 1) + wanted = np.dtype('uint64') + assert_equal(wanted, dt) + + def test_object(self): + dt = np.min_scalar_type(2**64) + wanted = np.dtype('O') + assert_equal(wanted, dt) + + +from numpy._core._internal import _dtype_from_pep3118 + + +class TestPEP3118Dtype: + def _check(self, spec, wanted): + dt = np.dtype(wanted) + actual = _dtype_from_pep3118(spec) + assert_equal(actual, dt, + err_msg=f"spec {spec!r} != dtype {wanted!r}") + + def test_native_padding(self): + align = np.dtype('i').alignment + for j in range(8): + if j == 0: + s = 'bi' + else: + s = 'b%dxi' % j + self._check('@' + s, {'f0': ('i1', 0), + 'f1': ('i', align * (1 + j // align))}) + self._check('=' + s, {'f0': ('i1', 0), + 'f1': ('i', 1 + j)}) + + def test_native_padding_2(self): + # Native padding should work also for structs and sub-arrays + self._check('x3T{xi}', {'f0': (({'f0': ('i', 4)}, (3,)), 4)}) + self._check('^x3T{xi}', {'f0': (({'f0': ('i', 1)}, (3,)), 1)}) + + def test_trailing_padding(self): + # Trailing padding should be included, *and*, the item size + # should match the alignment if in aligned mode + align = np.dtype('i').alignment + size = np.dtype('i').itemsize + + def aligned(n): + return align * (1 + (n - 1) // align) + + base = {"formats": ['i'], "names": ['f0']} + + self._check('ix', dict(itemsize=aligned(size + 1), **base)) + self._check('ixx', dict(itemsize=aligned(size + 2), **base)) + self._check('ixxx', dict(itemsize=aligned(size + 3), **base)) + self._check('ixxxx', dict(itemsize=aligned(size + 4), **base)) + self._check('i7x', dict(itemsize=aligned(size + 7), **base)) + + self._check('^ix', dict(itemsize=size + 1, **base)) + self._check('^ixx', dict(itemsize=size + 2, **base)) + self._check('^ixxx', dict(itemsize=size + 3, **base)) + self._check('^ixxxx', dict(itemsize=size + 4, **base)) + self._check('^i7x', dict(itemsize=size + 7, **base)) + + def test_native_padding_3(self): + dt = np.dtype( + [('a', 'b'), ('b', 'i'), + ('sub', np.dtype('b,i')), ('c', 'i')], + align=True) + self._check("T{b:a:xxxi:b:T{b:f0:=i:f1:}:sub:xxxi:c:}", dt) + + dt = np.dtype( + [('a', 'b'), ('b', 'i'), ('c', 'b'), ('d', 'b'), + ('e', 'b'), ('sub', np.dtype('b,i', align=True))]) + self._check("T{b:a:=i:b:b:c:b:d:b:e:T{b:f0:xxxi:f1:}:sub:}", dt) + + def test_padding_with_array_inside_struct(self): + dt = np.dtype( + [('a', 'b'), ('b', 'i'), ('c', 'b', (3,)), + ('d', 'i')], + align=True) + self._check("T{b:a:xxxi:b:3b:c:xi:d:}", dt) + + def test_byteorder_inside_struct(self): + # The byte order after @T{=i} should be '=', not '@'. + # Check this by noting the absence of native alignment. + self._check('@T{^i}xi', {'f0': ({'f0': ('i', 0)}, 0), + 'f1': ('i', 5)}) + + def test_intra_padding(self): + # Natively aligned sub-arrays may require some internal padding + align = np.dtype('i').alignment + size = np.dtype('i').itemsize + + def aligned(n): + return (align * (1 + (n - 1) // align)) + + self._check('(3)T{ix}', ({ + "names": ['f0'], + "formats": ['i'], + "offsets": [0], + "itemsize": aligned(size + 1) + }, (3,))) + + def test_char_vs_string(self): + dt = np.dtype('c') + self._check('c', dt) + + dt = np.dtype([('f0', 'S1', (4,)), ('f1', 'S4')]) + self._check('4c4s', dt) + + def test_field_order(self): + # gh-9053 - previously, we relied on dictionary key order + self._check("(0)I:a:f:b:", [('a', 'I', (0,)), ('b', 'f')]) + self._check("(0)I:b:f:a:", [('b', 'I', (0,)), ('a', 'f')]) + + def test_unnamed_fields(self): + self._check('ii', [('f0', 'i'), ('f1', 'i')]) + self._check('ii:f0:', [('f1', 'i'), ('f0', 'i')]) + + self._check('i', 'i') + self._check('i:f0:', [('f0', 'i')]) + + +class TestNewBufferProtocol: + """ Test PEP3118 buffers """ + + def _check_roundtrip(self, obj): + obj = np.asarray(obj) + x = memoryview(obj) + y = np.asarray(x) + y2 = np.array(x) + assert_(not y.flags.owndata) + assert_(y2.flags.owndata) + + assert_equal(y.dtype, obj.dtype) + assert_equal(y.shape, obj.shape) + assert_array_equal(obj, y) + + assert_equal(y2.dtype, obj.dtype) + assert_equal(y2.shape, obj.shape) + assert_array_equal(obj, y2) + + def test_roundtrip(self): + x = np.array([1, 2, 3, 4, 5], dtype='i4') + self._check_roundtrip(x) + + x = np.array([[1, 2], [3, 4]], dtype=np.float64) + self._check_roundtrip(x) + + x = np.zeros((3, 3, 3), dtype=np.float32)[:, 0, :] + self._check_roundtrip(x) + + dt = [('a', 'b'), + ('b', 'h'), + ('c', 'i'), + ('d', 'l'), + ('dx', 'q'), + ('e', 'B'), + ('f', 'H'), + ('g', 'I'), + ('h', 'L'), + ('hx', 'Q'), + ('i', np.single), + ('j', np.double), + ('k', np.longdouble), + ('ix', np.csingle), + ('jx', np.cdouble), + ('kx', np.clongdouble), + ('l', 'S4'), + ('m', 'U4'), + ('n', 'V3'), + ('o', '?'), + ('p', np.half), + ] + x = np.array( + [(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, + b'aaaa', 'bbbb', b'xxx', True, 1.0)], + dtype=dt) + self._check_roundtrip(x) + + x = np.array(([[1, 2], [3, 4]],), dtype=[('a', (int, (2, 2)))]) + self._check_roundtrip(x) + + x = np.array([1, 2, 3], dtype='>i2') + self._check_roundtrip(x) + + x = np.array([1, 2, 3], dtype='') + x = np.zeros(4, dtype=dt) + self._check_roundtrip(x) + + def test_roundtrip_scalar(self): + # Issue #4015. + self._check_roundtrip(0) + + def test_invalid_buffer_format(self): + # datetime64 cannot be used fully in a buffer yet + # Should be fixed in the next Numpy major release + dt = np.dtype([('a', 'uint16'), ('b', 'M8[s]')]) + a = np.empty(3, dt) + assert_raises((ValueError, BufferError), memoryview, a) + assert_raises((ValueError, BufferError), memoryview, np.array((3), 'M8[D]')) + + def test_export_simple_1d(self): + x = np.array([1, 2, 3, 4, 5], dtype='i') + y = memoryview(x) + assert_equal(y.format, 'i') + assert_equal(y.shape, (5,)) + assert_equal(y.ndim, 1) + assert_equal(y.strides, (4,)) + assert_equal(y.suboffsets, ()) + assert_equal(y.itemsize, 4) + + def test_export_simple_nd(self): + x = np.array([[1, 2], [3, 4]], dtype=np.float64) + y = memoryview(x) + assert_equal(y.format, 'd') + assert_equal(y.shape, (2, 2)) + assert_equal(y.ndim, 2) + assert_equal(y.strides, (16, 8)) + assert_equal(y.suboffsets, ()) + assert_equal(y.itemsize, 8) + + def test_export_discontiguous(self): + x = np.zeros((3, 3, 3), dtype=np.float32)[:, 0, :] + y = memoryview(x) + assert_equal(y.format, 'f') + assert_equal(y.shape, (3, 3)) + assert_equal(y.ndim, 2) + assert_equal(y.strides, (36, 4)) + assert_equal(y.suboffsets, ()) + assert_equal(y.itemsize, 4) + + def test_export_record(self): + dt = [('a', 'b'), + ('b', 'h'), + ('c', 'i'), + ('d', 'l'), + ('dx', 'q'), + ('e', 'B'), + ('f', 'H'), + ('g', 'I'), + ('h', 'L'), + ('hx', 'Q'), + ('i', np.single), + ('j', np.double), + ('k', np.longdouble), + ('ix', np.csingle), + ('jx', np.cdouble), + ('kx', np.clongdouble), + ('l', 'S4'), + ('m', 'U4'), + ('n', 'V3'), + ('o', '?'), + ('p', np.half), + ] + x = np.array( + [(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, + b'aaaa', 'bbbb', b' ', True, 1.0)], + dtype=dt) + y = memoryview(x) + assert_equal(y.shape, (1,)) + assert_equal(y.ndim, 1) + assert_equal(y.suboffsets, ()) + + sz = sum(np.dtype(b).itemsize for a, b in dt) + if np.dtype('l').itemsize == 4: + assert_equal(y.format, 'T{b:a:=h:b:i:c:l:d:q:dx:B:e:@H:f:=I:g:L:h:Q:hx:f:i:d:j:^g:k:=Zf:ix:Zd:jx:^Zg:kx:4s:l:=4w:m:3x:n:?:o:@e:p:}') + else: + assert_equal(y.format, 'T{b:a:=h:b:i:c:q:d:q:dx:B:e:@H:f:=I:g:Q:h:Q:hx:f:i:d:j:^g:k:=Zf:ix:Zd:jx:^Zg:kx:4s:l:=4w:m:3x:n:?:o:@e:p:}') + assert_equal(y.strides, (sz,)) + assert_equal(y.itemsize, sz) + + def test_export_subarray(self): + x = np.array(([[1, 2], [3, 4]],), dtype=[('a', ('i', (2, 2)))]) + y = memoryview(x) + assert_equal(y.format, 'T{(2,2)i:a:}') + assert_equal(y.shape, ()) + assert_equal(y.ndim, 0) + assert_equal(y.strides, ()) + assert_equal(y.suboffsets, ()) + assert_equal(y.itemsize, 16) + + def test_export_endian(self): + x = np.array([1, 2, 3], dtype='>i') + y = memoryview(x) + if sys.byteorder == 'little': + assert_equal(y.format, '>i') + else: + assert_equal(y.format, 'i') + + x = np.array([1, 2, 3], dtype=' np.array(0, dtype=dt1), f"type {dt1} failed") + assert_(not 1 < np.array(0, dtype=dt1), f"type {dt1} failed") + + for dt2 in np.typecodes['AllInteger']: + assert_(np.array(1, dtype=dt1) > np.array(0, dtype=dt2), + f"type {dt1} and {dt2} failed") + assert_(not np.array(1, dtype=dt1) < np.array(0, dtype=dt2), + f"type {dt1} and {dt2} failed") + + # Unsigned integers + for dt1 in 'BHILQP': + assert_(-1 < np.array(1, dtype=dt1), f"type {dt1} failed") + assert_(not -1 > np.array(1, dtype=dt1), f"type {dt1} failed") + assert_(-1 != np.array(1, dtype=dt1), f"type {dt1} failed") + + # Unsigned vs signed + for dt2 in 'bhilqp': + assert_(np.array(1, dtype=dt1) > np.array(-1, dtype=dt2), + f"type {dt1} and {dt2} failed") + assert_(not np.array(1, dtype=dt1) < np.array(-1, dtype=dt2), + f"type {dt1} and {dt2} failed") + assert_(np.array(1, dtype=dt1) != np.array(-1, dtype=dt2), + f"type {dt1} and {dt2} failed") + + # Signed integers and floats + for dt1 in 'bhlqp' + np.typecodes['Float']: + assert_(1 > np.array(-1, dtype=dt1), f"type {dt1} failed") + assert_(not 1 < np.array(-1, dtype=dt1), f"type {dt1} failed") + assert_(-1 == np.array(-1, dtype=dt1), f"type {dt1} failed") + + for dt2 in 'bhlqp' + np.typecodes['Float']: + assert_(np.array(1, dtype=dt1) > np.array(-1, dtype=dt2), + f"type {dt1} and {dt2} failed") + assert_(not np.array(1, dtype=dt1) < np.array(-1, dtype=dt2), + f"type {dt1} and {dt2} failed") + assert_(np.array(-1, dtype=dt1) == np.array(-1, dtype=dt2), + f"type {dt1} and {dt2} failed") + + def test_to_bool_scalar(self): + assert_equal(bool(np.array([False])), False) + assert_equal(bool(np.array([True])), True) + assert_equal(bool(np.array([[42]])), True) + + def test_to_bool_scalar_not_convertible(self): + + class NotConvertible: + def __bool__(self): + raise NotImplementedError + + assert_raises(NotImplementedError, bool, np.array(NotConvertible())) + assert_raises(NotImplementedError, bool, np.array([NotConvertible()])) + if IS_PYSTON: + pytest.skip("Pyston disables recursion checking") + if IS_WASM: + pytest.skip("Pyodide/WASM has limited stack size") + + self_containing = np.array([None]) + self_containing[0] = self_containing + + Error = RecursionError + + assert_raises(Error, bool, self_containing) # previously stack overflow + self_containing[0] = None # resolve circular reference + + def test_to_bool_scalar_size_errors(self): + with pytest.raises(ValueError, match=".*one element is ambiguous"): + bool(np.array([1, 2])) + + with pytest.raises(ValueError, match=".*empty array is ambiguous"): + bool(np.empty((3, 0))) + + with pytest.raises(ValueError, match=".*empty array is ambiguous"): + bool(np.empty((0,))) + + def test_to_int_scalar(self): + # gh-9972 means that these aren't always the same + int_funcs = (int, lambda x: x.__int__()) + for int_func in int_funcs: + assert_equal(int_func(np.array(0)), 0) + assert_raises(TypeError, int_func, np.array([1])) + assert_raises(TypeError, int_func, np.array([[42]])) + assert_raises(TypeError, int_func, np.array([1, 2])) + + # gh-9972 + assert_equal(4, int_func(np.array('4'))) + assert_equal(5, int_func(np.bytes_(b'5'))) + assert_equal(6, int_func(np.str_('6'))) + + class NotConvertible: + def __int__(self): + raise NotImplementedError + assert_raises(NotImplementedError, + int_func, np.array(NotConvertible())) + assert_raises(TypeError, + int_func, np.array([NotConvertible()])) + + def test_to_float_scalar(self): + float_funcs = (float, lambda x: x.__float__()) + for float_func in float_funcs: + assert_equal(float_func(np.array(0)), 0.0) + assert_equal(float_func(np.array(1.0, np.float64)), 1.0) + assert_raises(TypeError, float_func, np.array([2])) + assert_raises(TypeError, float_func, np.array([3.14])) + assert_raises(TypeError, float_func, np.array([[4.0]])) + + assert_equal(5.0, float_func(np.array('5'))) + assert_equal(5.1, float_func(np.array('5.1'))) + assert_equal(6.0, float_func(np.bytes_(b'6'))) + assert_equal(6.1, float_func(np.bytes_(b'6.1'))) + assert_equal(7.0, float_func(np.str_('7'))) + assert_equal(7.1, float_func(np.str_('7.1'))) + + +class TestWhere: + def test_basic(self): + dts = [bool, np.int16, np.int32, np.int64, np.double, np.complex128, + np.longdouble, np.clongdouble] + for dt in dts: + c = np.ones(53, dtype=bool) + assert_equal(np.where( c, dt(0), dt(1)), dt(0)) + assert_equal(np.where(~c, dt(0), dt(1)), dt(1)) + assert_equal(np.where(True, dt(0), dt(1)), dt(0)) + assert_equal(np.where(False, dt(0), dt(1)), dt(1)) + d = np.ones_like(c).astype(dt) + e = np.zeros_like(d) + r = d.astype(dt) + c[7] = False + r[7] = e[7] + assert_equal(np.where(c, e, e), e) + assert_equal(np.where(c, d, e), r) + assert_equal(np.where(c, d, e[0]), r) + assert_equal(np.where(c, d[0], e), r) + assert_equal(np.where(c[::2], d[::2], e[::2]), r[::2]) + assert_equal(np.where(c[1::2], d[1::2], e[1::2]), r[1::2]) + assert_equal(np.where(c[::3], d[::3], e[::3]), r[::3]) + assert_equal(np.where(c[1::3], d[1::3], e[1::3]), r[1::3]) + assert_equal(np.where(c[::-2], d[::-2], e[::-2]), r[::-2]) + assert_equal(np.where(c[::-3], d[::-3], e[::-3]), r[::-3]) + assert_equal(np.where(c[1::-3], d[1::-3], e[1::-3]), r[1::-3]) + + @pytest.mark.skipif(IS_WASM, reason="no wasm fp exception support") + def test_exotic(self): + # object + assert_array_equal(np.where(True, None, None), np.array(None)) + # zero sized + m = np.array([], dtype=bool).reshape(0, 3) + b = np.array([], dtype=np.float64).reshape(0, 3) + assert_array_equal(np.where(m, 0, b), np.array([]).reshape(0, 3)) + + # object cast + d = np.array([-1.34, -0.16, -0.54, -0.31, -0.08, -0.95, 0.000, 0.313, + 0.547, -0.18, 0.876, 0.236, 1.969, 0.310, 0.699, 1.013, + 1.267, 0.229, -1.39, 0.487]) + nan = float('NaN') + e = np.array(['5z', '0l', nan, 'Wz', nan, nan, 'Xq', 'cs', nan, nan, + 'QN', nan, nan, 'Fd', nan, nan, 'kp', nan, '36', 'i1'], + dtype=object) + m = np.array([0, 0, 1, 0, 1, 1, 0, 0, 1, 1, + 0, 1, 1, 0, 1, 1, 0, 1, 0, 0], dtype=bool) + + r = e[:] + r[np.where(m)] = d[np.where(m)] + assert_array_equal(np.where(m, d, e), r) + + r = e[:] + r[np.where(~m)] = d[np.where(~m)] + assert_array_equal(np.where(m, e, d), r) + + assert_array_equal(np.where(m, e, e), e) + + # minimal dtype result with NaN scalar (e.g required by pandas) + d = np.array([1., 2.], dtype=np.float32) + e = float('NaN') + assert_equal(np.where(True, d, e).dtype, np.float32) + e = float('Infinity') + assert_equal(np.where(True, d, e).dtype, np.float32) + e = float('-Infinity') + assert_equal(np.where(True, d, e).dtype, np.float32) + # With NEP 50 adopted, the float will overflow here: + e = 1e150 + with pytest.warns(RuntimeWarning, match="overflow"): + res = np.where(True, d, e) + assert res.dtype == np.float32 + + def test_ndim(self): + c = [True, False] + a = np.zeros((2, 25)) + b = np.ones((2, 25)) + r = np.where(np.array(c)[:, np.newaxis], a, b) + assert_array_equal(r[0], a[0]) + assert_array_equal(r[1], b[0]) + + a = a.T + b = b.T + r = np.where(c, a, b) + assert_array_equal(r[:, 0], a[:, 0]) + assert_array_equal(r[:, 1], b[:, 0]) + + def test_dtype_mix(self): + c = np.array([False, True, False, False, False, False, True, False, + False, False, True, False]) + a = np.uint32(1) + b = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.], + dtype=np.float64) + r = np.array([5., 1., 3., 2., -1., -4., 1., -10., 10., 1., 1., 3.], + dtype=np.float64) + assert_equal(np.where(c, a, b), r) + + a = a.astype(np.float32) + b = b.astype(np.int64) + assert_equal(np.where(c, a, b), r) + + # non bool mask + c = c.astype(int) + c[c != 0] = 34242324 + assert_equal(np.where(c, a, b), r) + # invert + tmpmask = c != 0 + c[c == 0] = 41247212 + c[tmpmask] = 0 + assert_equal(np.where(c, b, a), r) + + def test_foreign(self): + c = np.array([False, True, False, False, False, False, True, False, + False, False, True, False]) + r = np.array([5., 1., 3., 2., -1., -4., 1., -10., 10., 1., 1., 3.], + dtype=np.float64) + a = np.ones(1, dtype='>i4') + b = np.array([5., 0., 3., 2., -1., -4., 0., -10., 10., 1., 0., 3.], + dtype=np.float64) + assert_equal(np.where(c, a, b), r) + + b = b.astype('>f8') + assert_equal(np.where(c, a, b), r) + + a = a.astype('i4') + assert_equal(np.where(c, a, b), r) + + def test_error(self): + c = [True, True] + a = np.ones((4, 5)) + b = np.ones((5, 5)) + assert_raises(ValueError, np.where, c, a, a) + assert_raises(ValueError, np.where, c[0], a, b) + + def test_string(self): + # gh-4778 check strings are properly filled with nulls + a = np.array("abc") + b = np.array("x" * 753) + assert_equal(np.where(True, a, b), "abc") + assert_equal(np.where(False, b, a), "abc") + + # check native datatype sized strings + a = np.array("abcd") + b = np.array("x" * 8) + assert_equal(np.where(True, a, b), "abcd") + assert_equal(np.where(False, b, a), "abcd") + + def test_empty_result(self): + # pass empty where result through an assignment which reads the data of + # empty arrays, error detectable with valgrind, see gh-8922 + x = np.zeros((1, 1)) + ibad = np.vstack(np.where(x == 99.)) + assert_array_equal(ibad, + np.atleast_2d(np.array([[], []], dtype=np.intp))) + + def test_largedim(self): + # invalid read regression gh-9304 + shape = [10, 2, 3, 4, 5, 6] + np.random.seed(2) + array = np.random.rand(*shape) + + for i in range(10): + benchmark = array.nonzero() + result = array.nonzero() + assert_array_equal(benchmark, result) + + def test_kwargs(self): + a = np.zeros(1) + with assert_raises(TypeError): + np.where(a, x=a, y=a) + + +if not IS_PYPY: + # sys.getsizeof() is not valid on PyPy + class TestSizeOf: + + def test_empty_array(self): + x = np.array([]) + assert_(sys.getsizeof(x) > 0) + + def check_array(self, dtype): + elem_size = dtype(0).itemsize + + for length in [10, 50, 100, 500]: + x = np.arange(length, dtype=dtype) + assert_(sys.getsizeof(x) > length * elem_size) + + def test_array_int32(self): + self.check_array(np.int32) + + def test_array_int64(self): + self.check_array(np.int64) + + def test_array_float32(self): + self.check_array(np.float32) + + def test_array_float64(self): + self.check_array(np.float64) + + def test_view(self): + d = np.ones(100) + assert_(sys.getsizeof(d[...]) < sys.getsizeof(d)) + + def test_reshape(self): + d = np.ones(100) + assert_(sys.getsizeof(d) < sys.getsizeof(d.reshape(100, 1, 1).copy())) + + @_no_tracing + def test_resize(self): + d = np.ones(100) + old = sys.getsizeof(d) + d.resize(50) + assert_(old > sys.getsizeof(d)) + d.resize(150) + assert_(old < sys.getsizeof(d)) + + @pytest.mark.parametrize("dtype", ["u4,f4", "u4,O"]) + def test_resize_structured(self, dtype): + a = np.array([(0, 0.0) for i in range(5)], dtype=dtype) + a.resize(1000) + assert_array_equal(a, np.zeros(1000, dtype=dtype)) + + def test_error(self): + d = np.ones(100) + assert_raises(TypeError, d.__sizeof__, "a") + + +class TestHashing: + + def test_arrays_not_hashable(self): + x = np.ones(3) + assert_raises(TypeError, hash, x) + + def test_collections_hashable(self): + x = np.array([]) + assert_(not isinstance(x, collections.abc.Hashable)) + + +class TestArrayPriority: + # This will go away when __array_priority__ is settled, meanwhile + # it serves to check unintended changes. + op = operator + binary_ops = [ + op.pow, op.add, op.sub, op.mul, op.floordiv, op.truediv, op.mod, + op.and_, op.or_, op.xor, op.lshift, op.rshift, op.mod, op.gt, + op.ge, op.lt, op.le, op.ne, op.eq + ] + + class Foo(np.ndarray): + __array_priority__ = 100. + + def __new__(cls, *args, **kwargs): + return np.array(*args, **kwargs).view(cls) + + class Bar(np.ndarray): + __array_priority__ = 101. + + def __new__(cls, *args, **kwargs): + return np.array(*args, **kwargs).view(cls) + + class Other: + __array_priority__ = 1000. + + def _all(self, other): + return self.__class__() + + __add__ = __radd__ = _all + __sub__ = __rsub__ = _all + __mul__ = __rmul__ = _all + __pow__ = __rpow__ = _all + __mod__ = __rmod__ = _all + __truediv__ = __rtruediv__ = _all + __floordiv__ = __rfloordiv__ = _all + __and__ = __rand__ = _all + __xor__ = __rxor__ = _all + __or__ = __ror__ = _all + __lshift__ = __rlshift__ = _all + __rshift__ = __rrshift__ = _all + __eq__ = _all + __ne__ = _all + __gt__ = _all + __ge__ = _all + __lt__ = _all + __le__ = _all + + def test_ndarray_subclass(self): + a = np.array([1, 2]) + b = self.Bar([1, 2]) + for f in self.binary_ops: + msg = repr(f) + assert_(isinstance(f(a, b), self.Bar), msg) + assert_(isinstance(f(b, a), self.Bar), msg) + + def test_ndarray_other(self): + a = np.array([1, 2]) + b = self.Other() + for f in self.binary_ops: + msg = repr(f) + assert_(isinstance(f(a, b), self.Other), msg) + assert_(isinstance(f(b, a), self.Other), msg) + + def test_subclass_subclass(self): + a = self.Foo([1, 2]) + b = self.Bar([1, 2]) + for f in self.binary_ops: + msg = repr(f) + assert_(isinstance(f(a, b), self.Bar), msg) + assert_(isinstance(f(b, a), self.Bar), msg) + + def test_subclass_other(self): + a = self.Foo([1, 2]) + b = self.Other() + for f in self.binary_ops: + msg = repr(f) + assert_(isinstance(f(a, b), self.Other), msg) + assert_(isinstance(f(b, a), self.Other), msg) + + +class TestBytestringArrayNonzero: + + def test_empty_bstring_array_is_falsey(self): + assert_(not np.array([''], dtype=str)) + + def test_whitespace_bstring_array_is_truthy(self): + a = np.array(['spam'], dtype=str) + a[0] = ' \0\0' + assert_(a) + + def test_all_null_bstring_array_is_falsey(self): + a = np.array(['spam'], dtype=str) + a[0] = '\0\0\0\0' + assert_(not a) + + def test_null_inside_bstring_array_is_truthy(self): + a = np.array(['spam'], dtype=str) + a[0] = ' \0 \0' + assert_(a) + + +class TestUnicodeEncoding: + """ + Tests for encoding related bugs, such as UCS2 vs UCS4, round-tripping + issues, etc + """ + def test_round_trip(self): + """ Tests that GETITEM, SETITEM, and PyArray_Scalar roundtrip """ + # gh-15363 + arr = np.zeros(shape=(), dtype="U1") + for i in range(1, sys.maxunicode + 1): + expected = chr(i) + arr[()] = expected + assert arr[()] == expected + assert arr.item() == expected + + def test_assign_scalar(self): + # gh-3258 + l = np.array(['aa', 'bb']) + l[:] = np.str_('cc') + assert_equal(l, ['cc', 'cc']) + + def test_fill_scalar(self): + # gh-7227 + l = np.array(['aa', 'bb']) + l.fill(np.str_('cc')) + assert_equal(l, ['cc', 'cc']) + + +class TestUnicodeArrayNonzero: + + def test_empty_ustring_array_is_falsey(self): + assert_(not np.array([''], dtype=np.str_)) + + def test_whitespace_ustring_array_is_truthy(self): + a = np.array(['eggs'], dtype=np.str_) + a[0] = ' \0\0' + assert_(a) + + def test_all_null_ustring_array_is_falsey(self): + a = np.array(['eggs'], dtype=np.str_) + a[0] = '\0\0\0\0' + assert_(not a) + + def test_null_inside_ustring_array_is_truthy(self): + a = np.array(['eggs'], dtype=np.str_) + a[0] = ' \0 \0' + assert_(a) + + +class TestFormat: + + def test_0d(self): + a = np.array(np.pi) + assert_equal(f'{a:0.3g}', '3.14') + assert_equal(f'{a[()]:0.3g}', '3.14') + + def test_1d_no_format(self): + a = np.array([np.pi]) + assert_equal(f'{a}', str(a)) + + def test_1d_format(self): + # until gh-5543, ensure that the behaviour matches what it used to be + a = np.array([np.pi]) + assert_raises(TypeError, '{:30}'.format, a) + + +from numpy.testing import IS_PYPY + + +class TestCTypes: + + def test_ctypes_is_available(self): + test_arr = np.array([[1, 2, 3], [4, 5, 6]]) + + assert_equal(ctypes, test_arr.ctypes._ctypes) + assert_equal(tuple(test_arr.ctypes.shape), (2, 3)) + + @pytest.mark.thread_unsafe(reason="modifies global module state") + def test_ctypes_is_not_available(self): + from numpy._core import _internal + _internal.ctypes = None + try: + test_arr = np.array([[1, 2, 3], [4, 5, 6]]) + + assert_(isinstance(test_arr.ctypes._ctypes, + _internal._missing_ctypes)) + assert_equal(tuple(test_arr.ctypes.shape), (2, 3)) + finally: + _internal.ctypes = ctypes + + def _make_readonly(x): + x.flags.writeable = False + return x + + @pytest.mark.thread_unsafe(reason="calls gc.collect()") + @pytest.mark.parametrize('arr', [ + np.array([1, 2, 3]), + np.array([['one', 'two'], ['three', 'four']]), + np.array((1, 2), dtype='i4,i4'), + np.zeros((2,), dtype=np.dtype({ + "formats": [' 2, [44, 55]) + assert_equal(a, np.array([[0, 44], [1, 55], [2, 44]])) + # hit one of the failing paths + assert_raises(ValueError, np.place, a, a > 20, []) + + def test_put_noncontiguous(self): + a = np.arange(6).reshape(2, 3).T # force non-c-contiguous + np.put(a, [0, 2], [44, 55]) + assert_equal(a, np.array([[44, 3], [55, 4], [2, 5]])) + + def test_putmask_noncontiguous(self): + a = np.arange(6).reshape(2, 3).T # force non-c-contiguous + # uses arr_putmask + np.putmask(a, a > 2, a**2) + assert_equal(a, np.array([[0, 9], [1, 16], [2, 25]])) + + def test_take_mode_raise(self): + a = np.arange(6, dtype='int') + out = np.empty(2, dtype='int') + np.take(a, [0, 2], out=out, mode='raise') + assert_equal(out, np.array([0, 2])) + + def test_choose_mod_raise(self): + a = np.array([[1, 0, 1], [0, 1, 0], [1, 0, 1]]) + out = np.empty((3, 3), dtype='int') + choices = [-10, 10] + np.choose(a, choices, out=out, mode='raise') + assert_equal(out, np.array([[ 10, -10, 10], + [-10, 10, -10], + [ 10, -10, 10]])) + + def test_flatiter__array__(self): + a = np.arange(9).reshape(3, 3) + b = a.T.flat + c = b.__array__() + # triggers the WRITEBACKIFCOPY resolution, assuming refcount semantics + del c + + def test_dot_out(self): + # if HAVE_CBLAS, will use WRITEBACKIFCOPY + a = np.arange(9, dtype=float).reshape(3, 3) + b = np.dot(a, a, out=a) + assert_equal(b, np.array([[15, 18, 21], [42, 54, 66], [69, 90, 111]])) + + def test_view_assign(self): + from numpy._core._multiarray_tests import ( + npy_create_writebackifcopy, + npy_resolve, + ) + + arr = np.arange(9).reshape(3, 3).T + arr_wb = npy_create_writebackifcopy(arr) + assert_(arr_wb.flags.writebackifcopy) + assert_(arr_wb.base is arr) + arr_wb[...] = -100 + npy_resolve(arr_wb) + # arr changes after resolve, even though we assigned to arr_wb + assert_equal(arr, -100) + # after resolve, the two arrays no longer reference each other + assert_(arr_wb.ctypes.data != 0) + assert_equal(arr_wb.base, None) + # assigning to arr_wb does not get transferred to arr + arr_wb[...] = 100 + assert_equal(arr, -100) + + @pytest.mark.leaks_references( + reason="increments self in dealloc; ignore since deprecated path.") + def test_dealloc_warning(self): + arr = np.arange(9).reshape(3, 3) + v = arr.T + with pytest.warns(RuntimeWarning): + _multiarray_tests.npy_abuse_writebackifcopy(v) + + def test_view_discard_refcount(self): + from numpy._core._multiarray_tests import ( + npy_create_writebackifcopy, + npy_discard, + ) + + arr = np.arange(9).reshape(3, 3).T + orig = arr.copy() + if HAS_REFCOUNT: + arr_cnt = sys.getrefcount(arr) + arr_wb = npy_create_writebackifcopy(arr) + assert_(arr_wb.flags.writebackifcopy) + assert_(arr_wb.base is arr) + arr_wb[...] = -100 + npy_discard(arr_wb) + # arr remains unchanged after discard + assert_equal(arr, orig) + # after discard, the two arrays no longer reference each other + assert_(arr_wb.ctypes.data != 0) + assert_equal(arr_wb.base, None) + if HAS_REFCOUNT: + assert_equal(arr_cnt, sys.getrefcount(arr)) + # assigning to arr_wb does not get transferred to arr + arr_wb[...] = 100 + assert_equal(arr, orig) + + +class TestArange: + def test_infinite(self): + assert_raises_regex( + ValueError, "size exceeded", + np.arange, 0, np.inf + ) + + def test_nan_step(self): + assert_raises_regex( + ValueError, "cannot compute length", + np.arange, 0, 1, np.nan + ) + + def test_zero_step(self): + assert_raises(ZeroDivisionError, np.arange, 0, 10, 0) + assert_raises(ZeroDivisionError, np.arange, 0.0, 10.0, 0.0) + + # empty range + assert_raises(ZeroDivisionError, np.arange, 0, 0, 0) + assert_raises(ZeroDivisionError, np.arange, 0.0, 0.0, 0.0) + + def test_require_range(self): + assert_raises(TypeError, np.arange) + assert_raises(TypeError, np.arange, step=3) + assert_raises(TypeError, np.arange, dtype='int64') + assert_raises(TypeError, np.arange, start=4) + + def test_start_stop_kwarg(self): + keyword_stop = np.arange(stop=3) + keyword_zerotostop = np.arange(0, stop=3) + keyword_start_stop = np.arange(start=3, stop=9) + + assert len(keyword_stop) == 3 + assert len(keyword_zerotostop) == 3 + assert len(keyword_start_stop) == 6 + assert_array_equal(keyword_stop, keyword_zerotostop) + + def test_arange_booleans(self): + # Arange makes some sense for booleans and works up to length 2. + # But it is weird since `arange(2, 4, dtype=bool)` works. + # Arguably, much or all of this could be deprecated/removed. + res = np.arange(False, dtype=bool) + assert_array_equal(res, np.array([], dtype="bool")) + + res = np.arange(True, dtype="bool") + assert_array_equal(res, [False]) + + res = np.arange(2, dtype="bool") + assert_array_equal(res, [False, True]) + + # This case is especially weird, but drops out without special case: + res = np.arange(6, 8, dtype="bool") + assert_array_equal(res, [True, True]) + + with pytest.raises(TypeError): + np.arange(3, dtype="bool") + + @pytest.mark.parametrize("dtype", ["S3", "U", "5i"]) + def test_rejects_bad_dtypes(self, dtype): + dtype = np.dtype(dtype) + DType_name = re.escape(str(type(dtype))) + with pytest.raises(TypeError, + match=rf"arange\(\) not supported for inputs .* {DType_name}"): + np.arange(2, dtype=dtype) + + def test_rejects_strings(self): + # Explicitly test error for strings which may call "b" - "a": + DType_name = re.escape(str(type(np.array("a").dtype))) + with pytest.raises(TypeError, + match=rf"arange\(\) not supported for inputs .* {DType_name}"): + np.arange("a", "b") + + def test_byteswapped(self): + res_be = np.arange(1, 1000, dtype=">i4") + res_le = np.arange(1, 1000, dtype="i4" + assert res_le.dtype == " arr2 + + +@pytest.mark.parametrize("op", [ + operator.eq, operator.ne, operator.le, operator.lt, operator.ge, + operator.gt]) +def test_comparisons_forwards_error(op): + class NotArray: + def __array__(self, dtype=None, copy=None): + raise TypeError("run you fools") + + with pytest.raises(TypeError, match="run you fools"): + op(np.arange(2), NotArray()) + + with pytest.raises(TypeError, match="run you fools"): + op(NotArray(), np.arange(2)) + + +def test_richcompare_scalar_boolean_singleton_return(): + # These are currently guaranteed to be the boolean numpy singletons + assert (np.array(0) == "a") is np.bool_(False) + assert (np.array(0) != "a") is np.bool_(True) + assert (np.int16(0) == "a") is np.bool_(False) + assert (np.int16(0) != "a") is np.bool_(True) + + +@pytest.mark.parametrize("op", [ + operator.eq, operator.ne, operator.le, operator.lt, operator.ge, + operator.gt]) +def test_ragged_comparison_fails(op): + # This needs to convert the internal array to True/False, which fails: + a = np.array([1, np.array([1, 2, 3])], dtype=object) + b = np.array([1, np.array([1, 2, 3])], dtype=object) + + with pytest.raises(ValueError, match="The truth value.*ambiguous"): + op(a, b) + + +@pytest.mark.parametrize( + ["fun", "npfun"], + [ + (_multiarray_tests.npy_cabs, np.absolute), + (_multiarray_tests.npy_carg, np.angle) + ] +) +@pytest.mark.parametrize("x", [1, np.inf, -np.inf, np.nan]) +@pytest.mark.parametrize("y", [1, np.inf, -np.inf, np.nan]) +@pytest.mark.parametrize("test_dtype", np.complexfloating.__subclasses__()) +def test_npymath_complex(fun, npfun, x, y, test_dtype): + # Smoketest npymath functions + z = test_dtype(complex(x, y)) + with np.errstate(invalid='ignore'): + # Fallback implementations may emit a warning for +-inf (see gh-24876): + # RuntimeWarning: invalid value encountered in absolute + got = fun(z) + expected = npfun(z) + assert_allclose(got, expected) + + +def test_npymath_real(): + # Smoketest npymath functions + from numpy._core._multiarray_tests import ( + npy_cosh, + npy_log10, + npy_sinh, + npy_tan, + npy_tanh, + ) + + funcs = {npy_log10: np.log10, + npy_cosh: np.cosh, + npy_sinh: np.sinh, + npy_tan: np.tan, + npy_tanh: np.tanh} + vals = (1, np.inf, -np.inf, np.nan) + types = (np.float32, np.float64, np.longdouble) + + with np.errstate(all='ignore'): + for fun, npfun in funcs.items(): + for x, t in itertools.product(vals, types): + z = t(x) + got = fun(z) + expected = npfun(z) + assert_allclose(got, expected) + +def test_uintalignment_and_alignment(): + # alignment code needs to satisfy these requirements: + # 1. numpy structs match C struct layout + # 2. ufuncs/casting is safe wrt to aligned access + # 3. copy code is safe wrt to "uint alidned" access + # + # Complex types are the main problem, whose alignment may not be the same + # as their "uint alignment". + # + # This test might only fail on certain platforms, where uint64 alignment is + # not equal to complex64 alignment. The second 2 tests will only fail + # for DEBUG=1. + + d1 = np.dtype('u1,c8', align=True) + d2 = np.dtype('u4,c8', align=True) + d3 = np.dtype({'names': ['a', 'b'], 'formats': ['u1', d1]}, align=True) + + assert_equal(np.zeros(1, dtype=d1)['f1'].flags['ALIGNED'], True) + assert_equal(np.zeros(1, dtype=d2)['f1'].flags['ALIGNED'], True) + assert_equal(np.zeros(1, dtype='u1,c8')['f1'].flags['ALIGNED'], False) + + # check that C struct matches numpy struct size + s = _multiarray_tests.get_struct_alignments() + for d, (alignment, size) in zip([d1, d2, d3], s): + assert_equal(d.alignment, alignment) + assert_equal(d.itemsize, size) + + # check that ufuncs don't complain in debug mode + # (this is probably OK if the aligned flag is true above) + src = np.zeros((2, 2), dtype=d1)['f1'] # 4-byte aligned, often + np.exp(src) # assert fails? + + # check that copy code doesn't complain in debug mode + dst = np.zeros((2, 2), dtype='c8') + dst[:, 1] = src[:, 1] # assert in lowlevel_strided_loops fails? + +class TestAlignment: + # adapted from scipy._lib.tests.test__util.test__aligned_zeros + # Checks that unusual memory alignments don't trip up numpy. + + def check(self, shape, dtype, order, align): + err_msg = repr((shape, dtype, order, align)) + x = _aligned_zeros(shape, dtype, order, align=align) + if align is None: + align = np.dtype(dtype).alignment + assert_equal(x.__array_interface__['data'][0] % align, 0) + if hasattr(shape, '__len__'): + assert_equal(x.shape, shape, err_msg) + else: + assert_equal(x.shape, (shape,), err_msg) + assert_equal(x.dtype, dtype) + if order == "C": + assert_(x.flags.c_contiguous, err_msg) + elif order == "F": + if x.size > 0: + assert_(x.flags.f_contiguous, err_msg) + elif order is None: + assert_(x.flags.c_contiguous, err_msg) + else: + raise ValueError + + def test_various_alignments(self): + for align in [1, 2, 3, 4, 8, 12, 16, 32, 64, None]: + for n in [0, 1, 3, 11]: + for order in ["C", "F", None]: + for dtype in list(np.typecodes["All"]) + ['i4,i4,i4']: + if dtype == 'O': + # object dtype can't be misaligned + continue + for shape in [n, (1, 2, 3, n)]: + self.check(shape, np.dtype(dtype), order, align) + + def test_strided_loop_alignments(self): + # particularly test that complex64 and float128 use right alignment + # code-paths, since these are particularly problematic. It is useful to + # turn on USE_DEBUG for this test, so lowlevel-loop asserts are run. + for align in [1, 2, 4, 8, 12, 16, None]: + xf64 = _aligned_zeros(3, np.float64) + + xc64 = _aligned_zeros(3, np.complex64, align=align) + xf128 = _aligned_zeros(3, np.longdouble, align=align) + + # test casting, both to and from misaligned + with warnings.catch_warnings(): + warnings.filterwarnings('ignore', "Casting complex values", ComplexWarning) + xc64.astype('f8') + xf64.astype(np.complex64) + test = xc64 + xf64 + + xf128.astype('f8') + xf64.astype(np.longdouble) + test = xf128 + xf64 + + test = xf128 + xc64 + + # test copy, both to and from misaligned + # contig copy + xf64[:] = xf64.copy() + xc64[:] = xc64.copy() + xf128[:] = xf128.copy() + # strided copy + xf64[::2] = xf64[::2].copy() + xc64[::2] = xc64[::2].copy() + xf128[::2] = xf128[::2].copy() + +def test_getfield(): + a = np.arange(32, dtype='uint16') + if sys.byteorder == 'little': + i = 0 + j = 1 + else: + i = 1 + j = 0 + b = a.getfield('int8', i) + assert_equal(b, a) + b = a.getfield('int8', j) + assert_equal(b, 0) + pytest.raises(ValueError, a.getfield, 'uint8', -1) + pytest.raises(ValueError, a.getfield, 'uint8', 16) + pytest.raises(ValueError, a.getfield, 'uint64', 0) + +class TestViewDtype: + """ + Verify that making a view of a non-contiguous array works as expected. + """ + def test_smaller_dtype_multiple(self): + # x is non-contiguous + x = np.arange(10, dtype=' 10: + arrs.pop(0) + elif len(arrs) <= 10: + arrs.extend([np.array([1, 2, 3]) for _ in range(1000)]) + + def replace_list_items(b): + b.wait() + rng = np.random.RandomState() + rng.seed(0x4d3d3d3) + while done < 4: + data = rng.randint(0, 1000, size=4) + arrs[data[0]] = data[1:] + + for mutation_func in (replace_list_items, contract_and_expand_list): + b = threading.Barrier(5) + try: + with concurrent.futures.ThreadPoolExecutor(max_workers=5) as tpe: + tasks = [tpe.submit(read_arrs, b) for _ in range(4)] + tasks.append(tpe.submit(mutation_func, b)) + for t in tasks: + t.result() + except RuntimeError as e: + if outcome == "success": + raise + assert "Inconsistent object during array creation?" in str(e) + msg = "replace_list_items should not raise errors" + assert mutation_func is contract_and_expand_list, msg + finally: + if len(tasks) < 5: + b.abort() + +@pytest.mark.skipif(sys.version_info < (3, 12), reason="Python >= 3.12 required") +def test_array__buffer__thread_safety(): + import inspect + arr = np.arange(1000) + flags = [inspect.BufferFlags.STRIDED, inspect.BufferFlags.READ] + + def func(b): + b.wait() + for i in range(100): + arr.__buffer__(flags[i % 2]) + + run_threaded(func, max_workers=8, pass_barrier=True) + +@pytest.mark.skipif(sys.version_info < (3, 12), reason="Python >= 3.12 required") +def test_void_dtype__buffer__thread_safety(): + import inspect + dt = np.dtype([('name', np.str_, 16), ('grades', np.float64, (2,))]) + x = np.array(('ndarray_scalar', (1.2, 3.0)), dtype=dt)[()] + assert isinstance(x, np.void) + flags = [inspect.BufferFlags.STRIDES, inspect.BufferFlags.READ] + + def func(b): + b.wait() + for i in range(100): + x.__buffer__(flags[i % 2]) + + run_threaded(func, max_workers=8, pass_barrier=True) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_nditer.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_nditer.py new file mode 100644 index 0000000000000000000000000000000000000000..d2fc69a03b5f6525a710a6191d16f7e29347006b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_nditer.py @@ -0,0 +1,3533 @@ +import inspect +import subprocess +import sys +import textwrap +import warnings + +import pytest + +import numpy as np +import numpy._core._multiarray_tests as _multiarray_tests +import numpy._core.umath as ncu +from numpy import all, arange, array, nditer +from numpy.testing import ( + HAS_REFCOUNT, + IS_64BIT, + IS_PYPY, + IS_WASM, + assert_, + assert_array_equal, + assert_equal, + assert_raises, +) +from numpy.testing._private.utils import requires_memory + + +def iter_multi_index(i): + ret = [] + while not i.finished: + ret.append(i.multi_index) + i.iternext() + return ret + +def iter_indices(i): + ret = [] + while not i.finished: + ret.append(i.index) + i.iternext() + return ret + +def iter_iterindices(i): + ret = [] + while not i.finished: + ret.append(i.iterindex) + i.iternext() + return ret + +@pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") +def test_iter_refcount(): + # Make sure the iterator doesn't leak + + # Basic + a = arange(6) + dt = np.dtype('f4').newbyteorder() + rc_a = sys.getrefcount(a) + rc_dt = sys.getrefcount(dt) + with nditer(a, [], + [['readwrite', 'updateifcopy']], + casting='unsafe', + op_dtypes=[dt]) as it: + assert_(not it.iterationneedsapi) + assert_(sys.getrefcount(a) > rc_a) + assert_(sys.getrefcount(dt) > rc_dt) + # del 'it' + it = None + assert_equal(sys.getrefcount(a), rc_a) + assert_equal(sys.getrefcount(dt), rc_dt) + + # With a copy + a = arange(6, dtype='f4') + dt = np.dtype('f4') + rc_a = sys.getrefcount(a) + rc_dt = sys.getrefcount(dt) + it = nditer(a, [], + [['readwrite']], + op_dtypes=[dt]) + rc2_a = sys.getrefcount(a) + rc2_dt = sys.getrefcount(dt) + it2 = it.copy() + assert_(sys.getrefcount(a) > rc2_a) + if sys.version_info < (3, 13): + # np.dtype('f4') is immortal after Python 3.13 + assert_(sys.getrefcount(dt) > rc2_dt) + it = None + assert_equal(sys.getrefcount(a), rc2_a) + assert_equal(sys.getrefcount(dt), rc2_dt) + it2 = None + assert_equal(sys.getrefcount(a), rc_a) + assert_equal(sys.getrefcount(dt), rc_dt) + +def test_iter_best_order(): + # The iterator should always find the iteration order + # with increasing memory addresses + + # Test the ordering for 1-D to 5-D shapes + for shape in [(5,), (3, 4), (2, 3, 4), (2, 3, 4, 3), (2, 3, 2, 2, 3)]: + a = arange(np.prod(shape)) + # Test each combination of positive and negative strides + for dirs in range(2**len(shape)): + dirs_index = [slice(None)] * len(shape) + for bit in range(len(shape)): + if ((2**bit) & dirs): + dirs_index[bit] = slice(None, None, -1) + dirs_index = tuple(dirs_index) + + aview = a.reshape(shape)[dirs_index] + # C-order + i = nditer(aview, [], [['readonly']]) + assert_equal(list(i), a) + # Fortran-order + i = nditer(aview.T, [], [['readonly']]) + assert_equal(list(i), a) + # Other order + if len(shape) > 2: + i = nditer(aview.swapaxes(0, 1), [], [['readonly']]) + assert_equal(list(i), a) + +def test_iter_c_order(): + # Test forcing C order + + # Test the ordering for 1-D to 5-D shapes + for shape in [(5,), (3, 4), (2, 3, 4), (2, 3, 4, 3), (2, 3, 2, 2, 3)]: + a = arange(np.prod(shape)) + # Test each combination of positive and negative strides + for dirs in range(2**len(shape)): + dirs_index = [slice(None)] * len(shape) + for bit in range(len(shape)): + if ((2**bit) & dirs): + dirs_index[bit] = slice(None, None, -1) + dirs_index = tuple(dirs_index) + + aview = a.reshape(shape)[dirs_index] + # C-order + i = nditer(aview, order='C') + assert_equal(list(i), aview.ravel(order='C')) + # Fortran-order + i = nditer(aview.T, order='C') + assert_equal(list(i), aview.T.ravel(order='C')) + # Other order + if len(shape) > 2: + i = nditer(aview.swapaxes(0, 1), order='C') + assert_equal(list(i), + aview.swapaxes(0, 1).ravel(order='C')) + +def test_iter_f_order(): + # Test forcing F order + + # Test the ordering for 1-D to 5-D shapes + for shape in [(5,), (3, 4), (2, 3, 4), (2, 3, 4, 3), (2, 3, 2, 2, 3)]: + a = arange(np.prod(shape)) + # Test each combination of positive and negative strides + for dirs in range(2**len(shape)): + dirs_index = [slice(None)] * len(shape) + for bit in range(len(shape)): + if ((2**bit) & dirs): + dirs_index[bit] = slice(None, None, -1) + dirs_index = tuple(dirs_index) + + aview = a.reshape(shape)[dirs_index] + # C-order + i = nditer(aview, order='F') + assert_equal(list(i), aview.ravel(order='F')) + # Fortran-order + i = nditer(aview.T, order='F') + assert_equal(list(i), aview.T.ravel(order='F')) + # Other order + if len(shape) > 2: + i = nditer(aview.swapaxes(0, 1), order='F') + assert_equal(list(i), + aview.swapaxes(0, 1).ravel(order='F')) + +def test_iter_c_or_f_order(): + # Test forcing any contiguous (C or F) order + + # Test the ordering for 1-D to 5-D shapes + for shape in [(5,), (3, 4), (2, 3, 4), (2, 3, 4, 3), (2, 3, 2, 2, 3)]: + a = arange(np.prod(shape)) + # Test each combination of positive and negative strides + for dirs in range(2**len(shape)): + dirs_index = [slice(None)] * len(shape) + for bit in range(len(shape)): + if ((2**bit) & dirs): + dirs_index[bit] = slice(None, None, -1) + dirs_index = tuple(dirs_index) + + aview = a.reshape(shape)[dirs_index] + # C-order + i = nditer(aview, order='A') + assert_equal(list(i), aview.ravel(order='A')) + # Fortran-order + i = nditer(aview.T, order='A') + assert_equal(list(i), aview.T.ravel(order='A')) + # Other order + if len(shape) > 2: + i = nditer(aview.swapaxes(0, 1), order='A') + assert_equal(list(i), + aview.swapaxes(0, 1).ravel(order='A')) + +def test_nditer_multi_index_set(): + # Test the multi_index set + a = np.arange(6).reshape(2, 3) + it = np.nditer(a, flags=['multi_index']) + + # Removes the iteration on two first elements of a[0] + it.multi_index = (0, 2,) + + assert_equal(list(it), [2, 3, 4, 5]) + +@pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") +def test_nditer_multi_index_set_refcount(): + # Test if the reference count on index variable is decreased + + index = 0 + i = np.nditer(np.array([111, 222, 333, 444]), flags=['multi_index']) + + start_count = sys.getrefcount(index) + i.multi_index = (index,) + end_count = sys.getrefcount(index) + + assert_equal(start_count, end_count) + +def test_iter_best_order_multi_index_1d(): + # The multi-indices should be correct with any reordering + + a = arange(4) + # 1D order + i = nditer(a, ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), [(0,), (1,), (2,), (3,)]) + # 1D reversed order + i = nditer(a[::-1], ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), [(3,), (2,), (1,), (0,)]) + +def test_iter_best_order_multi_index_2d(): + # The multi-indices should be correct with any reordering + + a = arange(6) + # 2D C-order + i = nditer(a.reshape(2, 3), ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), [(0, 0), (0, 1), (0, 2), (1, 0), (1, 1), (1, 2)]) + # 2D Fortran-order + i = nditer(a.reshape(2, 3).copy(order='F'), ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), [(0, 0), (1, 0), (0, 1), (1, 1), (0, 2), (1, 2)]) + # 2D reversed C-order + i = nditer(a.reshape(2, 3)[::-1], ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), [(1, 0), (1, 1), (1, 2), (0, 0), (0, 1), (0, 2)]) + i = nditer(a.reshape(2, 3)[:, ::-1], ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), [(0, 2), (0, 1), (0, 0), (1, 2), (1, 1), (1, 0)]) + i = nditer(a.reshape(2, 3)[::-1, ::-1], ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), [(1, 2), (1, 1), (1, 0), (0, 2), (0, 1), (0, 0)]) + # 2D reversed Fortran-order + i = nditer(a.reshape(2, 3).copy(order='F')[::-1], ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), [(1, 0), (0, 0), (1, 1), (0, 1), (1, 2), (0, 2)]) + i = nditer(a.reshape(2, 3).copy(order='F')[:, ::-1], + ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), [(0, 2), (1, 2), (0, 1), (1, 1), (0, 0), (1, 0)]) + i = nditer(a.reshape(2, 3).copy(order='F')[::-1, ::-1], + ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), [(1, 2), (0, 2), (1, 1), (0, 1), (1, 0), (0, 0)]) + +def test_iter_best_order_multi_index_3d(): + # The multi-indices should be correct with any reordering + + a = arange(12) + # 3D C-order + i = nditer(a.reshape(2, 3, 2), ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), + [(0, 0, 0), (0, 0, 1), (0, 1, 0), (0, 1, 1), (0, 2, 0), (0, 2, 1), + (1, 0, 0), (1, 0, 1), (1, 1, 0), (1, 1, 1), (1, 2, 0), (1, 2, 1)]) + # 3D Fortran-order + i = nditer(a.reshape(2, 3, 2).copy(order='F'), ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), + [(0, 0, 0), (1, 0, 0), (0, 1, 0), (1, 1, 0), (0, 2, 0), (1, 2, 0), + (0, 0, 1), (1, 0, 1), (0, 1, 1), (1, 1, 1), (0, 2, 1), (1, 2, 1)]) + # 3D reversed C-order + i = nditer(a.reshape(2, 3, 2)[::-1], ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), + [(1, 0, 0), (1, 0, 1), (1, 1, 0), (1, 1, 1), (1, 2, 0), (1, 2, 1), + (0, 0, 0), (0, 0, 1), (0, 1, 0), (0, 1, 1), (0, 2, 0), (0, 2, 1)]) + i = nditer(a.reshape(2, 3, 2)[:, ::-1], ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), + [(0, 2, 0), (0, 2, 1), (0, 1, 0), (0, 1, 1), (0, 0, 0), (0, 0, 1), + (1, 2, 0), (1, 2, 1), (1, 1, 0), (1, 1, 1), (1, 0, 0), (1, 0, 1)]) + i = nditer(a.reshape(2, 3, 2)[:, :, ::-1], ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), + [(0, 0, 1), (0, 0, 0), (0, 1, 1), (0, 1, 0), (0, 2, 1), (0, 2, 0), + (1, 0, 1), (1, 0, 0), (1, 1, 1), (1, 1, 0), (1, 2, 1), (1, 2, 0)]) + # 3D reversed Fortran-order + i = nditer(a.reshape(2, 3, 2).copy(order='F')[::-1], + ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), + [(1, 0, 0), (0, 0, 0), (1, 1, 0), (0, 1, 0), (1, 2, 0), (0, 2, 0), + (1, 0, 1), (0, 0, 1), (1, 1, 1), (0, 1, 1), (1, 2, 1), (0, 2, 1)]) + i = nditer(a.reshape(2, 3, 2).copy(order='F')[:, ::-1], + ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), + [(0, 2, 0), (1, 2, 0), (0, 1, 0), (1, 1, 0), (0, 0, 0), (1, 0, 0), + (0, 2, 1), (1, 2, 1), (0, 1, 1), (1, 1, 1), (0, 0, 1), (1, 0, 1)]) + i = nditer(a.reshape(2, 3, 2).copy(order='F')[:, :, ::-1], + ['multi_index'], [['readonly']]) + assert_equal(iter_multi_index(i), + [(0, 0, 1), (1, 0, 1), (0, 1, 1), (1, 1, 1), (0, 2, 1), (1, 2, 1), + (0, 0, 0), (1, 0, 0), (0, 1, 0), (1, 1, 0), (0, 2, 0), (1, 2, 0)]) + +def test_iter_best_order_c_index_1d(): + # The C index should be correct with any reordering + + a = arange(4) + # 1D order + i = nditer(a, ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), [0, 1, 2, 3]) + # 1D reversed order + i = nditer(a[::-1], ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), [3, 2, 1, 0]) + +def test_iter_best_order_c_index_2d(): + # The C index should be correct with any reordering + + a = arange(6) + # 2D C-order + i = nditer(a.reshape(2, 3), ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), [0, 1, 2, 3, 4, 5]) + # 2D Fortran-order + i = nditer(a.reshape(2, 3).copy(order='F'), + ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), [0, 3, 1, 4, 2, 5]) + # 2D reversed C-order + i = nditer(a.reshape(2, 3)[::-1], ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), [3, 4, 5, 0, 1, 2]) + i = nditer(a.reshape(2, 3)[:, ::-1], ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), [2, 1, 0, 5, 4, 3]) + i = nditer(a.reshape(2, 3)[::-1, ::-1], ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), [5, 4, 3, 2, 1, 0]) + # 2D reversed Fortran-order + i = nditer(a.reshape(2, 3).copy(order='F')[::-1], + ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), [3, 0, 4, 1, 5, 2]) + i = nditer(a.reshape(2, 3).copy(order='F')[:, ::-1], + ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), [2, 5, 1, 4, 0, 3]) + i = nditer(a.reshape(2, 3).copy(order='F')[::-1, ::-1], + ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), [5, 2, 4, 1, 3, 0]) + +def test_iter_best_order_c_index_3d(): + # The C index should be correct with any reordering + + a = arange(12) + # 3D C-order + i = nditer(a.reshape(2, 3, 2), ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), + [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]) + # 3D Fortran-order + i = nditer(a.reshape(2, 3, 2).copy(order='F'), + ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), + [0, 6, 2, 8, 4, 10, 1, 7, 3, 9, 5, 11]) + # 3D reversed C-order + i = nditer(a.reshape(2, 3, 2)[::-1], ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), + [6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5]) + i = nditer(a.reshape(2, 3, 2)[:, ::-1], ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), + [4, 5, 2, 3, 0, 1, 10, 11, 8, 9, 6, 7]) + i = nditer(a.reshape(2, 3, 2)[:, :, ::-1], ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), + [1, 0, 3, 2, 5, 4, 7, 6, 9, 8, 11, 10]) + # 3D reversed Fortran-order + i = nditer(a.reshape(2, 3, 2).copy(order='F')[::-1], + ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), + [6, 0, 8, 2, 10, 4, 7, 1, 9, 3, 11, 5]) + i = nditer(a.reshape(2, 3, 2).copy(order='F')[:, ::-1], + ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), + [4, 10, 2, 8, 0, 6, 5, 11, 3, 9, 1, 7]) + i = nditer(a.reshape(2, 3, 2).copy(order='F')[:, :, ::-1], + ['c_index'], [['readonly']]) + assert_equal(iter_indices(i), + [1, 7, 3, 9, 5, 11, 0, 6, 2, 8, 4, 10]) + +def test_iter_best_order_f_index_1d(): + # The Fortran index should be correct with any reordering + + a = arange(4) + # 1D order + i = nditer(a, ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), [0, 1, 2, 3]) + # 1D reversed order + i = nditer(a[::-1], ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), [3, 2, 1, 0]) + +def test_iter_best_order_f_index_2d(): + # The Fortran index should be correct with any reordering + + a = arange(6) + # 2D C-order + i = nditer(a.reshape(2, 3), ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), [0, 2, 4, 1, 3, 5]) + # 2D Fortran-order + i = nditer(a.reshape(2, 3).copy(order='F'), + ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), [0, 1, 2, 3, 4, 5]) + # 2D reversed C-order + i = nditer(a.reshape(2, 3)[::-1], ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), [1, 3, 5, 0, 2, 4]) + i = nditer(a.reshape(2, 3)[:, ::-1], ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), [4, 2, 0, 5, 3, 1]) + i = nditer(a.reshape(2, 3)[::-1, ::-1], ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), [5, 3, 1, 4, 2, 0]) + # 2D reversed Fortran-order + i = nditer(a.reshape(2, 3).copy(order='F')[::-1], + ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), [1, 0, 3, 2, 5, 4]) + i = nditer(a.reshape(2, 3).copy(order='F')[:, ::-1], + ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), [4, 5, 2, 3, 0, 1]) + i = nditer(a.reshape(2, 3).copy(order='F')[::-1, ::-1], + ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), [5, 4, 3, 2, 1, 0]) + +def test_iter_best_order_f_index_3d(): + # The Fortran index should be correct with any reordering + + a = arange(12) + # 3D C-order + i = nditer(a.reshape(2, 3, 2), ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), + [0, 6, 2, 8, 4, 10, 1, 7, 3, 9, 5, 11]) + # 3D Fortran-order + i = nditer(a.reshape(2, 3, 2).copy(order='F'), + ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), + [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]) + # 3D reversed C-order + i = nditer(a.reshape(2, 3, 2)[::-1], ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), + [1, 7, 3, 9, 5, 11, 0, 6, 2, 8, 4, 10]) + i = nditer(a.reshape(2, 3, 2)[:, ::-1], ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), + [4, 10, 2, 8, 0, 6, 5, 11, 3, 9, 1, 7]) + i = nditer(a.reshape(2, 3, 2)[:, :, ::-1], ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), + [6, 0, 8, 2, 10, 4, 7, 1, 9, 3, 11, 5]) + # 3D reversed Fortran-order + i = nditer(a.reshape(2, 3, 2).copy(order='F')[::-1], + ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), + [1, 0, 3, 2, 5, 4, 7, 6, 9, 8, 11, 10]) + i = nditer(a.reshape(2, 3, 2).copy(order='F')[:, ::-1], + ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), + [4, 5, 2, 3, 0, 1, 10, 11, 8, 9, 6, 7]) + i = nditer(a.reshape(2, 3, 2).copy(order='F')[:, :, ::-1], + ['f_index'], [['readonly']]) + assert_equal(iter_indices(i), + [6, 7, 8, 9, 10, 11, 0, 1, 2, 3, 4, 5]) + +def test_iter_no_inner_full_coalesce(): + # Check no_inner iterators which coalesce into a single inner loop + + for shape in [(5,), (3, 4), (2, 3, 4), (2, 3, 4, 3), (2, 3, 2, 2, 3)]: + size = np.prod(shape) + a = arange(size) + # Test each combination of forward and backwards indexing + for dirs in range(2**len(shape)): + dirs_index = [slice(None)] * len(shape) + for bit in range(len(shape)): + if ((2**bit) & dirs): + dirs_index[bit] = slice(None, None, -1) + dirs_index = tuple(dirs_index) + + aview = a.reshape(shape)[dirs_index] + # C-order + i = nditer(aview, ['external_loop'], [['readonly']]) + assert_equal(i.ndim, 1) + assert_equal(i[0].shape, (size,)) + # Fortran-order + i = nditer(aview.T, ['external_loop'], [['readonly']]) + assert_equal(i.ndim, 1) + assert_equal(i[0].shape, (size,)) + # Other order + if len(shape) > 2: + i = nditer(aview.swapaxes(0, 1), + ['external_loop'], [['readonly']]) + assert_equal(i.ndim, 1) + assert_equal(i[0].shape, (size,)) + +def test_iter_no_inner_dim_coalescing(): + # Check no_inner iterators whose dimensions may not coalesce completely + + # Skipping the last element in a dimension prevents coalescing + # with the next-bigger dimension + a = arange(24).reshape(2, 3, 4)[:, :, :-1] + i = nditer(a, ['external_loop'], [['readonly']]) + assert_equal(i.ndim, 2) + assert_equal(i[0].shape, (3,)) + a = arange(24).reshape(2, 3, 4)[:, :-1, :] + i = nditer(a, ['external_loop'], [['readonly']]) + assert_equal(i.ndim, 2) + assert_equal(i[0].shape, (8,)) + a = arange(24).reshape(2, 3, 4)[:-1, :, :] + i = nditer(a, ['external_loop'], [['readonly']]) + assert_equal(i.ndim, 1) + assert_equal(i[0].shape, (12,)) + + # Even with lots of 1-sized dimensions, should still coalesce + a = arange(24).reshape(1, 1, 2, 1, 1, 3, 1, 1, 4, 1, 1) + i = nditer(a, ['external_loop'], [['readonly']]) + assert_equal(i.ndim, 1) + assert_equal(i[0].shape, (24,)) + +def test_iter_dim_coalescing(): + # Check that the correct number of dimensions are coalesced + + # Tracking a multi-index disables coalescing + a = arange(24).reshape(2, 3, 4) + i = nditer(a, ['multi_index'], [['readonly']]) + assert_equal(i.ndim, 3) + + # A tracked index can allow coalescing if it's compatible with the array + a3d = arange(24).reshape(2, 3, 4) + i = nditer(a3d, ['c_index'], [['readonly']]) + assert_equal(i.ndim, 1) + i = nditer(a3d.swapaxes(0, 1), ['c_index'], [['readonly']]) + assert_equal(i.ndim, 3) + i = nditer(a3d.T, ['c_index'], [['readonly']]) + assert_equal(i.ndim, 3) + i = nditer(a3d.T, ['f_index'], [['readonly']]) + assert_equal(i.ndim, 1) + i = nditer(a3d.T.swapaxes(0, 1), ['f_index'], [['readonly']]) + assert_equal(i.ndim, 3) + + # When C or F order is forced, coalescing may still occur + a3d = arange(24).reshape(2, 3, 4) + i = nditer(a3d, order='C') + assert_equal(i.ndim, 1) + i = nditer(a3d.T, order='C') + assert_equal(i.ndim, 3) + i = nditer(a3d, order='F') + assert_equal(i.ndim, 3) + i = nditer(a3d.T, order='F') + assert_equal(i.ndim, 1) + i = nditer(a3d, order='A') + assert_equal(i.ndim, 1) + i = nditer(a3d.T, order='A') + assert_equal(i.ndim, 1) + +def test_iter_broadcasting(): + # Standard NumPy broadcasting rules + + # 1D with scalar + i = nditer([arange(6), np.int32(2)], ['multi_index'], [['readonly']] * 2) + assert_equal(i.itersize, 6) + assert_equal(i.shape, (6,)) + + # 2D with scalar + i = nditer([arange(6).reshape(2, 3), np.int32(2)], + ['multi_index'], [['readonly']] * 2) + assert_equal(i.itersize, 6) + assert_equal(i.shape, (2, 3)) + # 2D with 1D + i = nditer([arange(6).reshape(2, 3), arange(3)], + ['multi_index'], [['readonly']] * 2) + assert_equal(i.itersize, 6) + assert_equal(i.shape, (2, 3)) + i = nditer([arange(2).reshape(2, 1), arange(3)], + ['multi_index'], [['readonly']] * 2) + assert_equal(i.itersize, 6) + assert_equal(i.shape, (2, 3)) + # 2D with 2D + i = nditer([arange(2).reshape(2, 1), arange(3).reshape(1, 3)], + ['multi_index'], [['readonly']] * 2) + assert_equal(i.itersize, 6) + assert_equal(i.shape, (2, 3)) + + # 3D with scalar + i = nditer([np.int32(2), arange(24).reshape(4, 2, 3)], + ['multi_index'], [['readonly']] * 2) + assert_equal(i.itersize, 24) + assert_equal(i.shape, (4, 2, 3)) + # 3D with 1D + i = nditer([arange(3), arange(24).reshape(4, 2, 3)], + ['multi_index'], [['readonly']] * 2) + assert_equal(i.itersize, 24) + assert_equal(i.shape, (4, 2, 3)) + i = nditer([arange(3), arange(8).reshape(4, 2, 1)], + ['multi_index'], [['readonly']] * 2) + assert_equal(i.itersize, 24) + assert_equal(i.shape, (4, 2, 3)) + # 3D with 2D + i = nditer([arange(6).reshape(2, 3), arange(24).reshape(4, 2, 3)], + ['multi_index'], [['readonly']] * 2) + assert_equal(i.itersize, 24) + assert_equal(i.shape, (4, 2, 3)) + i = nditer([arange(2).reshape(2, 1), arange(24).reshape(4, 2, 3)], + ['multi_index'], [['readonly']] * 2) + assert_equal(i.itersize, 24) + assert_equal(i.shape, (4, 2, 3)) + i = nditer([arange(3).reshape(1, 3), arange(8).reshape(4, 2, 1)], + ['multi_index'], [['readonly']] * 2) + assert_equal(i.itersize, 24) + assert_equal(i.shape, (4, 2, 3)) + # 3D with 3D + i = nditer([arange(2).reshape(1, 2, 1), arange(3).reshape(1, 1, 3), + arange(4).reshape(4, 1, 1)], + ['multi_index'], [['readonly']] * 3) + assert_equal(i.itersize, 24) + assert_equal(i.shape, (4, 2, 3)) + i = nditer([arange(6).reshape(1, 2, 3), arange(4).reshape(4, 1, 1)], + ['multi_index'], [['readonly']] * 2) + assert_equal(i.itersize, 24) + assert_equal(i.shape, (4, 2, 3)) + i = nditer([arange(24).reshape(4, 2, 3), arange(12).reshape(4, 1, 3)], + ['multi_index'], [['readonly']] * 2) + assert_equal(i.itersize, 24) + assert_equal(i.shape, (4, 2, 3)) + +def test_iter_itershape(): + # Check that allocated outputs work with a specified shape + a = np.arange(6, dtype='i2').reshape(2, 3) + i = nditer([a, None], [], [['readonly'], ['writeonly', 'allocate']], + op_axes=[[0, 1, None], None], + itershape=(-1, -1, 4)) + assert_equal(i.operands[1].shape, (2, 3, 4)) + assert_equal(i.operands[1].strides, (24, 8, 2)) + + i = nditer([a.T, None], [], [['readonly'], ['writeonly', 'allocate']], + op_axes=[[0, 1, None], None], + itershape=(-1, -1, 4)) + assert_equal(i.operands[1].shape, (3, 2, 4)) + assert_equal(i.operands[1].strides, (8, 24, 2)) + + i = nditer([a.T, None], [], [['readonly'], ['writeonly', 'allocate']], + order='F', + op_axes=[[0, 1, None], None], + itershape=(-1, -1, 4)) + assert_equal(i.operands[1].shape, (3, 2, 4)) + assert_equal(i.operands[1].strides, (2, 6, 12)) + + # If we specify 1 in the itershape, it shouldn't allow broadcasting + # of that dimension to a bigger value + assert_raises(ValueError, nditer, [a, None], [], + [['readonly'], ['writeonly', 'allocate']], + op_axes=[[0, 1, None], None], + itershape=(-1, 1, 4)) + # Test bug that for no op_axes but itershape, they are NULLed correctly + i = np.nditer([np.ones(2), None, None], itershape=(2,)) + +def test_iter_broadcasting_errors(): + # Check that errors are thrown for bad broadcasting shapes + + # 1D with 1D + assert_raises(ValueError, nditer, [arange(2), arange(3)], + [], [['readonly']] * 2) + # 2D with 1D + assert_raises(ValueError, nditer, + [arange(6).reshape(2, 3), arange(2)], + [], [['readonly']] * 2) + # 2D with 2D + assert_raises(ValueError, nditer, + [arange(6).reshape(2, 3), arange(9).reshape(3, 3)], + [], [['readonly']] * 2) + assert_raises(ValueError, nditer, + [arange(6).reshape(2, 3), arange(4).reshape(2, 2)], + [], [['readonly']] * 2) + # 3D with 3D + assert_raises(ValueError, nditer, + [arange(36).reshape(3, 3, 4), arange(24).reshape(2, 3, 4)], + [], [['readonly']] * 2) + assert_raises(ValueError, nditer, + [arange(8).reshape(2, 4, 1), arange(24).reshape(2, 3, 4)], + [], [['readonly']] * 2) + + # Verify that the error message mentions the right shapes + try: + nditer([arange(2).reshape(1, 2, 1), + arange(3).reshape(1, 3), + arange(6).reshape(2, 3)], + [], + [['readonly'], ['readonly'], ['writeonly', 'no_broadcast']]) + raise AssertionError('Should have raised a broadcast error') + except ValueError as e: + msg = str(e) + # The message should contain the shape of the 3rd operand + assert_(msg.find('(2,3)') >= 0, + f'Message "{msg}" doesn\'t contain operand shape (2,3)') + # The message should contain the broadcast shape + assert_(msg.find('(1,2,3)') >= 0, + f'Message "{msg}" doesn\'t contain broadcast shape (1,2,3)') + + try: + nditer([arange(6).reshape(2, 3), arange(2)], + [], + [['readonly'], ['readonly']], + op_axes=[[0, 1], [0, np.newaxis]], + itershape=(4, 3)) + raise AssertionError('Should have raised a broadcast error') + except ValueError as e: + msg = str(e) + # The message should contain "shape->remappedshape" for each operand + assert_(msg.find('(2,3)->(2,3)') >= 0, + f'Message "{msg}" doesn\'t contain operand shape (2,3)->(2,3)') + assert_(msg.find('(2,)->(2,newaxis)') >= 0, + ('Message "%s" doesn\'t contain remapped operand shape' + '(2,)->(2,newaxis)') % msg) + # The message should contain the itershape parameter + assert_(msg.find('(4,3)') >= 0, + f'Message "{msg}" doesn\'t contain itershape parameter (4,3)') + + try: + nditer([np.zeros((2, 1, 1)), np.zeros((2,))], + [], + [['writeonly', 'no_broadcast'], ['readonly']]) + raise AssertionError('Should have raised a broadcast error') + except ValueError as e: + msg = str(e) + # The message should contain the shape of the bad operand + assert_(msg.find('(2,1,1)') >= 0, + f'Message "{msg}" doesn\'t contain operand shape (2,1,1)') + # The message should contain the broadcast shape + assert_(msg.find('(2,1,2)') >= 0, + f'Message "{msg}" doesn\'t contain the broadcast shape (2,1,2)') + +def test_iter_flags_errors(): + # Check that bad combinations of flags produce errors + + a = arange(6) + + # Not enough operands + assert_raises(ValueError, nditer, [], [], []) + # Bad global flag + assert_raises(ValueError, nditer, [a], ['bad flag'], [['readonly']]) + # Bad op flag + assert_raises(ValueError, nditer, [a], [], [['readonly', 'bad flag']]) + # Bad order parameter + assert_raises(ValueError, nditer, [a], [], [['readonly']], order='G') + # Bad casting parameter + assert_raises(ValueError, nditer, [a], [], [['readonly']], casting='noon') + # op_flags must match ops + assert_raises(ValueError, nditer, [a] * 3, [], [['readonly']] * 2) + # Cannot track both a C and an F index + assert_raises(ValueError, nditer, a, + ['c_index', 'f_index'], [['readonly']]) + # Inner iteration and multi-indices/indices are incompatible + assert_raises(ValueError, nditer, a, + ['external_loop', 'multi_index'], [['readonly']]) + assert_raises(ValueError, nditer, a, + ['external_loop', 'c_index'], [['readonly']]) + assert_raises(ValueError, nditer, a, + ['external_loop', 'f_index'], [['readonly']]) + # Must specify exactly one of readwrite/readonly/writeonly per operand + assert_raises(ValueError, nditer, a, [], [[]]) + assert_raises(ValueError, nditer, a, [], [['readonly', 'writeonly']]) + assert_raises(ValueError, nditer, a, [], [['readonly', 'readwrite']]) + assert_raises(ValueError, nditer, a, [], [['writeonly', 'readwrite']]) + assert_raises(ValueError, nditer, a, + [], [['readonly', 'writeonly', 'readwrite']]) + # Python scalars are always readonly + assert_raises(TypeError, nditer, 1.5, [], [['writeonly']]) + assert_raises(TypeError, nditer, 1.5, [], [['readwrite']]) + # Array scalars are always readonly + assert_raises(TypeError, nditer, np.int32(1), [], [['writeonly']]) + assert_raises(TypeError, nditer, np.int32(1), [], [['readwrite']]) + # Check readonly array + a.flags.writeable = False + assert_raises(ValueError, nditer, a, [], [['writeonly']]) + assert_raises(ValueError, nditer, a, [], [['readwrite']]) + a.flags.writeable = True + # Multi-indices available only with the multi_index flag + i = nditer(arange(6), [], [['readonly']]) + assert_raises(ValueError, lambda i: i.multi_index, i) + # Index available only with an index flag + assert_raises(ValueError, lambda i: i.index, i) + # GotoCoords and GotoIndex incompatible with buffering or no_inner + + def assign_multi_index(i): + i.multi_index = (0,) + + def assign_index(i): + i.index = 0 + + def assign_iterindex(i): + i.iterindex = 0 + + def assign_iterrange(i): + i.iterrange = (0, 1) + i = nditer(arange(6), ['external_loop']) + assert_raises(ValueError, assign_multi_index, i) + assert_raises(ValueError, assign_index, i) + assert_raises(ValueError, assign_iterindex, i) + assert_raises(ValueError, assign_iterrange, i) + i = nditer(arange(6), ['buffered']) + assert_raises(ValueError, assign_multi_index, i) + assert_raises(ValueError, assign_index, i) + assert_raises(ValueError, assign_iterrange, i) + # Can't iterate if size is zero + assert_raises(ValueError, nditer, np.array([])) + +def test_iter_slice(): + a, b, c = np.arange(3), np.arange(3), np.arange(3.) + i = nditer([a, b, c], [], ['readwrite']) + with i: + i[0:2] = (3, 3) + assert_equal(a, [3, 1, 2]) + assert_equal(b, [3, 1, 2]) + assert_equal(c, [0, 1, 2]) + i[1] = 12 + assert_equal(i[0:2], [3, 12]) + +def test_iter_assign_mapping(): + a = np.arange(24, dtype='f8').reshape(2, 3, 4).T + it = np.nditer(a, [], [['readwrite', 'updateifcopy']], + casting='same_kind', op_dtypes=[np.dtype('f4')]) + with it: + it.operands[0][...] = 3 + it.operands[0][...] = 14 + assert_equal(a, 14) + it = np.nditer(a, [], [['readwrite', 'updateifcopy']], + casting='same_kind', op_dtypes=[np.dtype('f4')]) + with it: + x = it.operands[0][-1:1] + x[...] = 14 + it.operands[0][...] = -1234 + assert_equal(a, -1234) + # check for no warnings on dealloc + x = None + it = None + +def test_iter_nbo_align_contig(): + # Check that byte order, alignment, and contig changes work + + # Byte order change by requesting a specific dtype + a = np.arange(6, dtype='f4') + au = a.byteswap() + au = au.view(au.dtype.newbyteorder()) + assert_(a.dtype.byteorder != au.dtype.byteorder) + i = nditer(au, [], [['readwrite', 'updateifcopy']], + casting='equiv', + op_dtypes=[np.dtype('f4')]) + with i: + # context manager triggers WRITEBACKIFCOPY on i at exit + assert_equal(i.dtypes[0].byteorder, a.dtype.byteorder) + assert_equal(i.operands[0].dtype.byteorder, a.dtype.byteorder) + assert_equal(i.operands[0], a) + i.operands[0][:] = 2 + assert_equal(au, [2] * 6) + del i # should not raise a warning + # Byte order change by requesting NBO + a = np.arange(6, dtype='f4') + au = a.byteswap() + au = au.view(au.dtype.newbyteorder()) + assert_(a.dtype.byteorder != au.dtype.byteorder) + with nditer(au, [], [['readwrite', 'updateifcopy', 'nbo']], + casting='equiv') as i: + # context manager triggers UPDATEIFCOPY on i at exit + assert_equal(i.dtypes[0].byteorder, a.dtype.byteorder) + assert_equal(i.operands[0].dtype.byteorder, a.dtype.byteorder) + assert_equal(i.operands[0], a) + i.operands[0][:] = 12345 + i.operands[0][:] = 2 + assert_equal(au, [2] * 6) + + # Unaligned input + a = np.zeros((6 * 4 + 1,), dtype='i1')[1:] + a = a.view('f4') + a[:] = np.arange(6, dtype='f4') + assert_(not a.flags.aligned) + # Without 'aligned', shouldn't copy + i = nditer(a, [], [['readonly']]) + assert_(not i.operands[0].flags.aligned) + assert_equal(i.operands[0], a) + # With 'aligned', should make a copy + with nditer(a, [], [['readwrite', 'updateifcopy', 'aligned']]) as i: + assert_(i.operands[0].flags.aligned) + # context manager triggers UPDATEIFCOPY on i at exit + assert_equal(i.operands[0], a) + i.operands[0][:] = 3 + assert_equal(a, [3] * 6) + + # Discontiguous input + a = arange(12) + # If it is contiguous, shouldn't copy + i = nditer(a[:6], [], [['readonly']]) + assert_(i.operands[0].flags.contiguous) + assert_equal(i.operands[0], a[:6]) + # If it isn't contiguous, should buffer + i = nditer(a[::2], ['buffered', 'external_loop'], + [['readonly', 'contig']], + buffersize=10) + assert_(i[0].flags.contiguous) + assert_equal(i[0], a[::2]) + +def test_iter_array_cast(): + # Check that arrays are cast as requested + + # No cast 'f4' -> 'f4' + a = np.arange(6, dtype='f4').reshape(2, 3) + i = nditer(a, [], [['readwrite']], op_dtypes=[np.dtype('f4')]) + with i: + assert_equal(i.operands[0], a) + assert_equal(i.operands[0].dtype, np.dtype('f4')) + + # Byte-order cast ' '>f4' + a = np.arange(6, dtype='f4')]) as i: + assert_equal(i.operands[0], a) + assert_equal(i.operands[0].dtype, np.dtype('>f4')) + + # Safe case 'f4' -> 'f8' + a = np.arange(24, dtype='f4').reshape(2, 3, 4).swapaxes(1, 2) + i = nditer(a, [], [['readonly', 'copy']], + casting='safe', + op_dtypes=[np.dtype('f8')]) + assert_equal(i.operands[0], a) + assert_equal(i.operands[0].dtype, np.dtype('f8')) + # The memory layout of the temporary should match a (a is (48,4,16)) + # except negative strides get flipped to positive strides. + assert_equal(i.operands[0].strides, (96, 8, 32)) + a = a[::-1, :, ::-1] + i = nditer(a, [], [['readonly', 'copy']], + casting='safe', + op_dtypes=[np.dtype('f8')]) + assert_equal(i.operands[0], a) + assert_equal(i.operands[0].dtype, np.dtype('f8')) + assert_equal(i.operands[0].strides, (96, 8, 32)) + + # Same-kind cast 'f8' -> 'f4' -> 'f8' + a = np.arange(24, dtype='f8').reshape(2, 3, 4).T + with nditer(a, [], + [['readwrite', 'updateifcopy']], + casting='same_kind', + op_dtypes=[np.dtype('f4')]) as i: + assert_equal(i.operands[0], a) + assert_equal(i.operands[0].dtype, np.dtype('f4')) + assert_equal(i.operands[0].strides, (4, 16, 48)) + # Check that WRITEBACKIFCOPY is activated at exit + i.operands[0][2, 1, 1] = -12.5 + assert_(a[2, 1, 1] != -12.5) + assert_equal(a[2, 1, 1], -12.5) + + a = np.arange(6, dtype='i4')[::-2] + with nditer(a, [], + [['writeonly', 'updateifcopy']], + casting='unsafe', + op_dtypes=[np.dtype('f4')]) as i: + assert_equal(i.operands[0].dtype, np.dtype('f4')) + # Even though the stride was negative in 'a', it + # becomes positive in the temporary + assert_equal(i.operands[0].strides, (4,)) + i.operands[0][:] = [1, 2, 3] + assert_equal(a, [1, 2, 3]) + +def test_iter_array_cast_errors(): + # Check that invalid casts are caught + + # Need to enable copying for casts to occur + assert_raises(TypeError, nditer, arange(2, dtype='f4'), [], + [['readonly']], op_dtypes=[np.dtype('f8')]) + # Also need to allow casting for casts to occur + assert_raises(TypeError, nditer, arange(2, dtype='f4'), [], + [['readonly', 'copy']], casting='no', + op_dtypes=[np.dtype('f8')]) + assert_raises(TypeError, nditer, arange(2, dtype='f4'), [], + [['readonly', 'copy']], casting='equiv', + op_dtypes=[np.dtype('f8')]) + assert_raises(TypeError, nditer, arange(2, dtype='f8'), [], + [['writeonly', 'updateifcopy']], + casting='no', + op_dtypes=[np.dtype('f4')]) + assert_raises(TypeError, nditer, arange(2, dtype='f8'), [], + [['writeonly', 'updateifcopy']], + casting='equiv', + op_dtypes=[np.dtype('f4')]) + # ' '>f4' should not work with casting='no' + assert_raises(TypeError, nditer, arange(2, dtype='f4')]) + # 'f4' -> 'f8' is a safe cast, but 'f8' -> 'f4' isn't + assert_raises(TypeError, nditer, arange(2, dtype='f4'), [], + [['readwrite', 'updateifcopy']], + casting='safe', + op_dtypes=[np.dtype('f8')]) + assert_raises(TypeError, nditer, arange(2, dtype='f8'), [], + [['readwrite', 'updateifcopy']], + casting='safe', + op_dtypes=[np.dtype('f4')]) + # 'f4' -> 'i4' is neither a safe nor a same-kind cast + assert_raises(TypeError, nditer, arange(2, dtype='f4'), [], + [['readonly', 'copy']], + casting='same_kind', + op_dtypes=[np.dtype('i4')]) + assert_raises(TypeError, nditer, arange(2, dtype='i4'), [], + [['writeonly', 'updateifcopy']], + casting='same_kind', + op_dtypes=[np.dtype('f4')]) + +def test_iter_scalar_cast(): + # Check that scalars are cast as requested + + # No cast 'f4' -> 'f4' + i = nditer(np.float32(2.5), [], [['readonly']], + op_dtypes=[np.dtype('f4')]) + assert_equal(i.dtypes[0], np.dtype('f4')) + assert_equal(i.value.dtype, np.dtype('f4')) + assert_equal(i.value, 2.5) + # Safe cast 'f4' -> 'f8' + i = nditer(np.float32(2.5), [], + [['readonly', 'copy']], + casting='safe', + op_dtypes=[np.dtype('f8')]) + assert_equal(i.dtypes[0], np.dtype('f8')) + assert_equal(i.value.dtype, np.dtype('f8')) + assert_equal(i.value, 2.5) + # Same-kind cast 'f8' -> 'f4' + i = nditer(np.float64(2.5), [], + [['readonly', 'copy']], + casting='same_kind', + op_dtypes=[np.dtype('f4')]) + assert_equal(i.dtypes[0], np.dtype('f4')) + assert_equal(i.value.dtype, np.dtype('f4')) + assert_equal(i.value, 2.5) + # Unsafe cast 'f8' -> 'i4' + i = nditer(np.float64(3.0), [], + [['readonly', 'copy']], + casting='unsafe', + op_dtypes=[np.dtype('i4')]) + assert_equal(i.dtypes[0], np.dtype('i4')) + assert_equal(i.value.dtype, np.dtype('i4')) + assert_equal(i.value, 3) + # Readonly scalars may be cast even without setting COPY or BUFFERED + i = nditer(3, [], [['readonly']], op_dtypes=[np.dtype('f8')]) + assert_equal(i[0].dtype, np.dtype('f8')) + assert_equal(i[0], 3.) + +def test_iter_scalar_cast_errors(): + # Check that invalid casts are caught + + # Need to allow copying/buffering for write casts of scalars to occur + assert_raises(TypeError, nditer, np.float32(2), [], + [['readwrite']], op_dtypes=[np.dtype('f8')]) + assert_raises(TypeError, nditer, 2.5, [], + [['readwrite']], op_dtypes=[np.dtype('f4')]) + # 'f8' -> 'f4' isn't a safe cast if the value would overflow + assert_raises(TypeError, nditer, np.float64(1e60), [], + [['readonly']], + casting='safe', + op_dtypes=[np.dtype('f4')]) + # 'f4' -> 'i4' is neither a safe nor a same-kind cast + assert_raises(TypeError, nditer, np.float32(2), [], + [['readonly']], + casting='same_kind', + op_dtypes=[np.dtype('i4')]) + +def test_iter_object_arrays_basic(): + # Check that object arrays work + + obj = {'a': 3, 'b': 'd'} + a = np.array([[1, 2, 3], None, obj, None], dtype='O') + if HAS_REFCOUNT: + rc = sys.getrefcount(obj) + + # Need to allow references for object arrays + assert_raises(TypeError, nditer, a) + if HAS_REFCOUNT: + assert_equal(sys.getrefcount(obj), rc) + + i = nditer(a, ['refs_ok'], ['readonly']) + vals = [x_[()] for x_ in i] + assert_equal(np.array(vals, dtype='O'), a) + vals, i, x = [None] * 3 + if HAS_REFCOUNT: + assert_equal(sys.getrefcount(obj), rc) + + i = nditer(a.reshape(2, 2).T, ['refs_ok', 'buffered'], + ['readonly'], order='C') + assert_(i.iterationneedsapi) + vals = [x_[()] for x_ in i] + assert_equal(np.array(vals, dtype='O'), a.reshape(2, 2).ravel(order='F')) + vals, i, x = [None] * 3 + if HAS_REFCOUNT: + assert_equal(sys.getrefcount(obj), rc) + + i = nditer(a.reshape(2, 2).T, ['refs_ok', 'buffered'], + ['readwrite'], order='C') + with i: + for x in i: + x[...] = None + vals, i, x = [None] * 3 + if HAS_REFCOUNT: + assert_(sys.getrefcount(obj) == rc - 1) + assert_equal(a, np.array([None] * 4, dtype='O')) + +def test_iter_object_arrays_conversions(): + # Conversions to/from objects + a = np.arange(6, dtype='O') + i = nditer(a, ['refs_ok', 'buffered'], ['readwrite'], + casting='unsafe', op_dtypes='i4') + with i: + for x in i: + x[...] += 1 + assert_equal(a, np.arange(6) + 1) + + a = np.arange(6, dtype='i4') + i = nditer(a, ['refs_ok', 'buffered'], ['readwrite'], + casting='unsafe', op_dtypes='O') + with i: + for x in i: + x[...] += 1 + assert_equal(a, np.arange(6) + 1) + + # Non-contiguous object array + a = np.zeros((6,), dtype=[('p', 'i1'), ('a', 'O')]) + a = a['a'] + a[:] = np.arange(6) + i = nditer(a, ['refs_ok', 'buffered'], ['readwrite'], + casting='unsafe', op_dtypes='i4') + with i: + for x in i: + x[...] += 1 + assert_equal(a, np.arange(6) + 1) + + # Non-contiguous value array + a = np.zeros((6,), dtype=[('p', 'i1'), ('a', 'i4')]) + a = a['a'] + a[:] = np.arange(6) + 98172488 + i = nditer(a, ['refs_ok', 'buffered'], ['readwrite'], + casting='unsafe', op_dtypes='O') + with i: + ob = i[0][()] + if HAS_REFCOUNT: + rc = sys.getrefcount(ob) + for x in i: + x[...] += 1 + if HAS_REFCOUNT: + newrc = sys.getrefcount(ob) + assert_(newrc == rc - 1) + assert_equal(a, np.arange(6) + 98172489) + +def test_iter_common_dtype(): + # Check that the iterator finds a common data type correctly + # (some checks are somewhat duplicate after adopting NEP 50) + + i = nditer([array([3], dtype='f4'), array([0], dtype='f8')], + ['common_dtype'], + [['readonly', 'copy']] * 2, + casting='safe') + assert_equal(i.dtypes[0], np.dtype('f8')) + assert_equal(i.dtypes[1], np.dtype('f8')) + i = nditer([array([3], dtype='i4'), array([0], dtype='f4')], + ['common_dtype'], + [['readonly', 'copy']] * 2, + casting='safe') + assert_equal(i.dtypes[0], np.dtype('f8')) + assert_equal(i.dtypes[1], np.dtype('f8')) + i = nditer([array([3], dtype='f4'), array(0, dtype='f8')], + ['common_dtype'], + [['readonly', 'copy']] * 2, + casting='same_kind') + assert_equal(i.dtypes[0], np.dtype('f8')) + assert_equal(i.dtypes[1], np.dtype('f8')) + i = nditer([array([3], dtype='u4'), array(0, dtype='i4')], + ['common_dtype'], + [['readonly', 'copy']] * 2, + casting='safe') + assert_equal(i.dtypes[0], np.dtype('i8')) + assert_equal(i.dtypes[1], np.dtype('i8')) + i = nditer([array([3], dtype='u4'), array(-12, dtype='i4')], + ['common_dtype'], + [['readonly', 'copy']] * 2, + casting='safe') + assert_equal(i.dtypes[0], np.dtype('i8')) + assert_equal(i.dtypes[1], np.dtype('i8')) + i = nditer([array([3], dtype='u4'), array(-12, dtype='i4'), + array([2j], dtype='c8'), array([9], dtype='f8')], + ['common_dtype'], + [['readonly', 'copy']] * 4, + casting='safe') + assert_equal(i.dtypes[0], np.dtype('c16')) + assert_equal(i.dtypes[1], np.dtype('c16')) + assert_equal(i.dtypes[2], np.dtype('c16')) + assert_equal(i.dtypes[3], np.dtype('c16')) + assert_equal(i.value, (3, -12, 2j, 9)) + + # When allocating outputs, other outputs aren't factored in + i = nditer([array([3], dtype='i4'), None, array([2j], dtype='c16')], [], + [['readonly', 'copy'], + ['writeonly', 'allocate'], + ['writeonly']], + casting='safe') + assert_equal(i.dtypes[0], np.dtype('i4')) + assert_equal(i.dtypes[1], np.dtype('i4')) + assert_equal(i.dtypes[2], np.dtype('c16')) + # But, if common data types are requested, they are + i = nditer([array([3], dtype='i4'), None, array([2j], dtype='c16')], + ['common_dtype'], + [['readonly', 'copy'], + ['writeonly', 'allocate'], + ['writeonly']], + casting='safe') + assert_equal(i.dtypes[0], np.dtype('c16')) + assert_equal(i.dtypes[1], np.dtype('c16')) + assert_equal(i.dtypes[2], np.dtype('c16')) + +def test_iter_copy_if_overlap(): + # Ensure the iterator makes copies on read/write overlap, if requested + + # Copy not needed, 1 op + for flag in ['readonly', 'writeonly', 'readwrite']: + a = arange(10) + i = nditer([a], ['copy_if_overlap'], [[flag]]) + with i: + assert_(i.operands[0] is a) + + # Copy needed, 2 ops, read-write overlap + x = arange(10) + a = x[1:] + b = x[:-1] + with nditer([a, b], ['copy_if_overlap'], [['readonly'], ['readwrite']]) as i: + assert_(not np.shares_memory(*i.operands)) + + # Copy not needed with elementwise, 2 ops, exactly same arrays + x = arange(10) + a = x + b = x + i = nditer([a, b], ['copy_if_overlap'], [['readonly', 'overlap_assume_elementwise'], + ['readwrite', 'overlap_assume_elementwise']]) + with i: + assert_(i.operands[0] is a and i.operands[1] is b) + with nditer([a, b], ['copy_if_overlap'], [['readonly'], ['readwrite']]) as i: + assert_(i.operands[0] is a and not np.shares_memory(i.operands[1], b)) + + # Copy not needed, 2 ops, no overlap + x = arange(10) + a = x[::2] + b = x[1::2] + i = nditer([a, b], ['copy_if_overlap'], [['readonly'], ['writeonly']]) + assert_(i.operands[0] is a and i.operands[1] is b) + + # Copy needed, 2 ops, read-write overlap + x = arange(4, dtype=np.int8) + a = x[3:] + b = x.view(np.int32)[:1] + with nditer([a, b], ['copy_if_overlap'], [['readonly'], ['writeonly']]) as i: + assert_(not np.shares_memory(*i.operands)) + + # Copy needed, 3 ops, read-write overlap + for flag in ['writeonly', 'readwrite']: + x = np.ones([10, 10]) + a = x + b = x.T + c = x + with nditer([a, b, c], ['copy_if_overlap'], + [['readonly'], ['readonly'], [flag]]) as i: + a2, b2, c2 = i.operands + assert_(not np.shares_memory(a2, c2)) + assert_(not np.shares_memory(b2, c2)) + + # Copy not needed, 3 ops, read-only overlap + x = np.ones([10, 10]) + a = x + b = x.T + c = x + i = nditer([a, b, c], ['copy_if_overlap'], + [['readonly'], ['readonly'], ['readonly']]) + a2, b2, c2 = i.operands + assert_(a is a2) + assert_(b is b2) + assert_(c is c2) + + # Copy not needed, 3 ops, read-only overlap + x = np.ones([10, 10]) + a = x + b = np.ones([10, 10]) + c = x.T + i = nditer([a, b, c], ['copy_if_overlap'], + [['readonly'], ['writeonly'], ['readonly']]) + a2, b2, c2 = i.operands + assert_(a is a2) + assert_(b is b2) + assert_(c is c2) + + # Copy not needed, 3 ops, write-only overlap + x = np.arange(7) + a = x[:3] + b = x[3:6] + c = x[4:7] + i = nditer([a, b, c], ['copy_if_overlap'], + [['readonly'], ['writeonly'], ['writeonly']]) + a2, b2, c2 = i.operands + assert_(a is a2) + assert_(b is b2) + assert_(c is c2) + +def test_iter_op_axes(): + # Check that custom axes work + + # Reverse the axes + a = arange(6).reshape(2, 3) + i = nditer([a, a.T], [], [['readonly']] * 2, op_axes=[[0, 1], [1, 0]]) + assert_(all([x == y for (x, y) in i])) + a = arange(24).reshape(2, 3, 4) + i = nditer([a.T, a], [], [['readonly']] * 2, op_axes=[[2, 1, 0], None]) + assert_(all([x == y for (x, y) in i])) + + # Broadcast 1D to any dimension + a = arange(1, 31).reshape(2, 3, 5) + b = arange(1, 3) + i = nditer([a, b], [], [['readonly']] * 2, op_axes=[None, [0, -1, -1]]) + assert_equal([x * y for (x, y) in i], (a * b.reshape(2, 1, 1)).ravel()) + b = arange(1, 4) + i = nditer([a, b], [], [['readonly']] * 2, op_axes=[None, [-1, 0, -1]]) + assert_equal([x * y for (x, y) in i], (a * b.reshape(1, 3, 1)).ravel()) + b = arange(1, 6) + i = nditer([a, b], [], [['readonly']] * 2, + op_axes=[None, [np.newaxis, np.newaxis, 0]]) + assert_equal([x * y for (x, y) in i], (a * b.reshape(1, 1, 5)).ravel()) + + # Inner product-style broadcasting + a = arange(24).reshape(2, 3, 4) + b = arange(40).reshape(5, 2, 4) + i = nditer([a, b], ['multi_index'], [['readonly']] * 2, + op_axes=[[0, 1, -1, -1], [-1, -1, 0, 1]]) + assert_equal(i.shape, (2, 3, 5, 2)) + + # Matrix product-style broadcasting + a = arange(12).reshape(3, 4) + b = arange(20).reshape(4, 5) + i = nditer([a, b], ['multi_index'], [['readonly']] * 2, + op_axes=[[0, -1], [-1, 1]]) + assert_equal(i.shape, (3, 5)) + +def test_iter_op_axes_errors(): + # Check that custom axes throws errors for bad inputs + + # Wrong number of items in op_axes + a = arange(6).reshape(2, 3) + assert_raises(ValueError, nditer, [a, a], [], [['readonly']] * 2, + op_axes=[[0], [1], [0]]) + # Out of bounds items in op_axes + assert_raises(ValueError, nditer, [a, a], [], [['readonly']] * 2, + op_axes=[[2, 1], [0, 1]]) + assert_raises(ValueError, nditer, [a, a], [], [['readonly']] * 2, + op_axes=[[0, 1], [2, -1]]) + # Duplicate items in op_axes + assert_raises(ValueError, nditer, [a, a], [], [['readonly']] * 2, + op_axes=[[0, 0], [0, 1]]) + assert_raises(ValueError, nditer, [a, a], [], [['readonly']] * 2, + op_axes=[[0, 1], [1, 1]]) + + # Different sized arrays in op_axes + assert_raises(ValueError, nditer, [a, a], [], [['readonly']] * 2, + op_axes=[[0, 1], [0, 1, 0]]) + + # Non-broadcastable dimensions in the result + assert_raises(ValueError, nditer, [a, a], [], [['readonly']] * 2, + op_axes=[[0, 1], [1, 0]]) + +def test_iter_copy(): + # Check that copying the iterator works correctly + a = arange(24).reshape(2, 3, 4) + + # Simple iterator + i = nditer(a) + j = i.copy() + assert_equal([x[()] for x in i], [x[()] for x in j]) + + i.iterindex = 3 + j = i.copy() + assert_equal([x[()] for x in i], [x[()] for x in j]) + + # Buffered iterator + i = nditer(a, ['buffered', 'ranged'], order='F', buffersize=3) + j = i.copy() + assert_equal([x[()] for x in i], [x[()] for x in j]) + + i.iterindex = 3 + j = i.copy() + assert_equal([x[()] for x in i], [x[()] for x in j]) + + i.iterrange = (3, 9) + j = i.copy() + assert_equal([x[()] for x in i], [x[()] for x in j]) + + i.iterrange = (2, 18) + next(i) + next(i) + j = i.copy() + assert_equal([x[()] for x in i], [x[()] for x in j]) + + # Casting iterator + with nditer(a, ['buffered'], order='F', casting='unsafe', + op_dtypes='f8', buffersize=5) as i: + j = i.copy() + assert_equal([x[()] for x in j], a.ravel(order='F')) + + a = arange(24, dtype=' unstructured (any to object), and many other + # casts, which cause this to require all steps in the casting machinery + # one level down as well as the iterator copy (which uses NpyAuxData clone) + in_dtype = np.dtype([("a", np.dtype("i,")), + ("b", np.dtype(">i,d,S17,>d,3f,O,i1"))]) + out_dtype = np.dtype([("a", np.dtype("O")), + ("b", np.dtype(">i,>i,S17,>d,>U3,3d,i1,O"))]) + arr = np.ones(1000, dtype=in_dtype) + + it = np.nditer((arr,), ["buffered", "external_loop", "refs_ok"], + op_dtypes=[out_dtype], casting="unsafe") + it_copy = it.copy() + + res1 = next(it) + del it + res2 = next(it_copy) + del it_copy + + expected = arr["a"].astype(out_dtype["a"]) + assert_array_equal(res1["a"], expected) + assert_array_equal(res2["a"], expected) + + for field in in_dtype["b"].names: + # Note that the .base avoids the subarray field + expected = arr["b"][field].astype(out_dtype["b"][field].base) + assert_array_equal(res1["b"][field], expected) + assert_array_equal(res2["b"][field], expected) + + +def test_iter_copy_casts_structured2(): + # Similar to the above, this is a fairly arcane test to cover internals + in_dtype = np.dtype([("a", np.dtype("O,O")), + ("b", np.dtype("5O,3O,(1,)O,(1,)i,(1,)O"))]) + out_dtype = np.dtype([("a", np.dtype("O")), + ("b", np.dtype("O,3i,4O,4O,4i"))]) + + arr = np.ones(1, dtype=in_dtype) + it = np.nditer((arr,), ["buffered", "external_loop", "refs_ok"], + op_dtypes=[out_dtype], casting="unsafe") + it_copy = it.copy() + + res1 = next(it) + del it + res2 = next(it_copy) + del it_copy + + # Array of two structured scalars: + for res in res1, res2: + # Cast to tuple by getitem, which may be weird and changeable?: + assert isinstance(res["a"][0], tuple) + assert res["a"][0] == (1, 1) + + for res in res1, res2: + assert_array_equal(res["b"]["f0"][0], np.ones(5, dtype=object)) + assert_array_equal(res["b"]["f1"], np.ones((1, 3), dtype="i")) + assert res["b"]["f2"].shape == (1, 4) + assert_array_equal(res["b"]["f2"][0], np.ones(4, dtype=object)) + assert_array_equal(res["b"]["f3"][0], np.ones(4, dtype=object)) + assert_array_equal(res["b"]["f3"][0], np.ones(4, dtype="i")) + + +def test_iter_allocate_output_simple(): + # Check that the iterator will properly allocate outputs + + # Simple case + a = arange(6) + i = nditer([a, None], [], [['readonly'], ['writeonly', 'allocate']], + op_dtypes=[None, np.dtype('f4')]) + assert_equal(i.operands[1].shape, a.shape) + assert_equal(i.operands[1].dtype, np.dtype('f4')) + +def test_iter_allocate_output_buffered_readwrite(): + # Allocated output with buffering + delay_bufalloc + + a = arange(6) + i = nditer([a, None], ['buffered', 'delay_bufalloc'], + [['readonly'], ['allocate', 'readwrite']]) + with i: + i.operands[1][:] = 1 + i.reset() + for x in i: + x[1][...] += x[0][...] + assert_equal(i.operands[1], a + 1) + +def test_iter_allocate_output_itorder(): + # The allocated output should match the iteration order + + # C-order input, best iteration order + a = arange(6, dtype='i4').reshape(2, 3) + i = nditer([a, None], [], [['readonly'], ['writeonly', 'allocate']], + op_dtypes=[None, np.dtype('f4')]) + assert_equal(i.operands[1].shape, a.shape) + assert_equal(i.operands[1].strides, a.strides) + assert_equal(i.operands[1].dtype, np.dtype('f4')) + # F-order input, best iteration order + a = arange(24, dtype='i4').reshape(2, 3, 4).T + i = nditer([a, None], [], [['readonly'], ['writeonly', 'allocate']], + op_dtypes=[None, np.dtype('f4')]) + assert_equal(i.operands[1].shape, a.shape) + assert_equal(i.operands[1].strides, a.strides) + assert_equal(i.operands[1].dtype, np.dtype('f4')) + # Non-contiguous input, C iteration order + a = arange(24, dtype='i4').reshape(2, 3, 4).swapaxes(0, 1) + i = nditer([a, None], [], + [['readonly'], ['writeonly', 'allocate']], + order='C', + op_dtypes=[None, np.dtype('f4')]) + assert_equal(i.operands[1].shape, a.shape) + assert_equal(i.operands[1].strides, (32, 16, 4)) + assert_equal(i.operands[1].dtype, np.dtype('f4')) + +def test_iter_allocate_output_opaxes(): + # Specifying op_axes should work + + a = arange(24, dtype='i4').reshape(2, 3, 4) + i = nditer([None, a], [], [['writeonly', 'allocate'], ['readonly']], + op_dtypes=[np.dtype('u4'), None], + op_axes=[[1, 2, 0], None]) + assert_equal(i.operands[0].shape, (4, 2, 3)) + assert_equal(i.operands[0].strides, (4, 48, 16)) + assert_equal(i.operands[0].dtype, np.dtype('u4')) + +def test_iter_allocate_output_types_promotion(): + # Check type promotion of automatic outputs (this was more interesting + # before NEP 50...) + + i = nditer([array([3], dtype='f4'), array([0], dtype='f8'), None], [], + [['readonly']] * 2 + [['writeonly', 'allocate']]) + assert_equal(i.dtypes[2], np.dtype('f8')) + i = nditer([array([3], dtype='i4'), array([0], dtype='f4'), None], [], + [['readonly']] * 2 + [['writeonly', 'allocate']]) + assert_equal(i.dtypes[2], np.dtype('f8')) + i = nditer([array([3], dtype='f4'), array(0, dtype='f8'), None], [], + [['readonly']] * 2 + [['writeonly', 'allocate']]) + assert_equal(i.dtypes[2], np.dtype('f8')) + i = nditer([array([3], dtype='u4'), array(0, dtype='i4'), None], [], + [['readonly']] * 2 + [['writeonly', 'allocate']]) + assert_equal(i.dtypes[2], np.dtype('i8')) + i = nditer([array([3], dtype='u4'), array(-12, dtype='i4'), None], [], + [['readonly']] * 2 + [['writeonly', 'allocate']]) + assert_equal(i.dtypes[2], np.dtype('i8')) + +def test_iter_allocate_output_types_byte_order(): + # Verify the rules for byte order changes + + # When there's just one input, the output type exactly matches + a = array([3], dtype='u4') + a = a.view(a.dtype.newbyteorder()) + i = nditer([a, None], [], + [['readonly'], ['writeonly', 'allocate']]) + assert_equal(i.dtypes[0], i.dtypes[1]) + # With two or more inputs, the output type is in native byte order + i = nditer([a, a, None], [], + [['readonly'], ['readonly'], ['writeonly', 'allocate']]) + assert_(i.dtypes[0] != i.dtypes[2]) + assert_equal(i.dtypes[0].newbyteorder('='), i.dtypes[2]) + +def test_iter_allocate_output_types_scalar(): + # If the inputs are all scalars, the output should be a scalar + + i = nditer([None, 1, 2.3, np.float32(12), np.complex128(3)], [], + [['writeonly', 'allocate']] + [['readonly']] * 4) + assert_equal(i.operands[0].dtype, np.dtype('complex128')) + assert_equal(i.operands[0].ndim, 0) + +def test_iter_allocate_output_subtype(): + # Make sure that the subtype with priority wins + class MyNDArray(np.ndarray): + __array_priority__ = 15 + + # subclass vs ndarray + a = np.array([[1, 2], [3, 4]]).view(MyNDArray) + b = np.arange(4).reshape(2, 2).T + i = nditer([a, b, None], [], + [['readonly'], ['readonly'], ['writeonly', 'allocate']]) + assert_equal(type(a), type(i.operands[2])) + assert_(type(b) is not type(i.operands[2])) + assert_equal(i.operands[2].shape, (2, 2)) + + # If subtypes are disabled, we should get back an ndarray. + i = nditer([a, b, None], [], + [['readonly'], ['readonly'], + ['writeonly', 'allocate', 'no_subtype']]) + assert_equal(type(b), type(i.operands[2])) + assert_(type(a) is not type(i.operands[2])) + assert_equal(i.operands[2].shape, (2, 2)) + +def test_iter_allocate_output_errors(): + # Check that the iterator will throw errors for bad output allocations + + # Need an input if no output data type is specified + a = arange(6) + assert_raises(TypeError, nditer, [a, None], [], + [['writeonly'], ['writeonly', 'allocate']]) + # Allocated output should be flagged for writing + assert_raises(ValueError, nditer, [a, None], [], + [['readonly'], ['allocate', 'readonly']]) + # Allocated output can't have buffering without delayed bufalloc + assert_raises(ValueError, nditer, [a, None], ['buffered'], + ['allocate', 'readwrite']) + # Must specify dtype if there are no inputs (cannot promote existing ones; + # maybe this should use the 'f4' here, but it does not historically.) + assert_raises(TypeError, nditer, [None, None], [], + [['writeonly', 'allocate'], + ['writeonly', 'allocate']], + op_dtypes=[None, np.dtype('f4')]) + # If using op_axes, must specify all the axes + a = arange(24, dtype='i4').reshape(2, 3, 4) + assert_raises(ValueError, nditer, [a, None], [], + [['readonly'], ['writeonly', 'allocate']], + op_dtypes=[None, np.dtype('f4')], + op_axes=[None, [0, np.newaxis, 1]]) + # If using op_axes, the axes must be within bounds + assert_raises(ValueError, nditer, [a, None], [], + [['readonly'], ['writeonly', 'allocate']], + op_dtypes=[None, np.dtype('f4')], + op_axes=[None, [0, 3, 1]]) + # If using op_axes, there can't be duplicates + assert_raises(ValueError, nditer, [a, None], [], + [['readonly'], ['writeonly', 'allocate']], + op_dtypes=[None, np.dtype('f4')], + op_axes=[None, [0, 2, 1, 0]]) + # Not all axes may be specified if a reduction. If there is a hole + # in op_axes, this is an error. + a = arange(24, dtype='i4').reshape(2, 3, 4) + assert_raises(ValueError, nditer, [a, None], ["reduce_ok"], + [['readonly'], ['readwrite', 'allocate']], + op_dtypes=[None, np.dtype('f4')], + op_axes=[None, [0, np.newaxis, 2]]) + +def test_all_allocated(): + # When no output and no shape is given, `()` is used as shape. + i = np.nditer([None], op_dtypes=["int64"]) + assert i.operands[0].shape == () + assert i.dtypes == (np.dtype("int64"),) + + i = np.nditer([None], op_dtypes=["int64"], itershape=(2, 3, 4)) + assert i.operands[0].shape == (2, 3, 4) + +def test_iter_remove_axis(): + a = arange(24).reshape(2, 3, 4) + + i = nditer(a, ['multi_index']) + i.remove_axis(1) + assert_equal(list(i), a[:, 0, :].ravel()) + + a = a[::-1, :, :] + i = nditer(a, ['multi_index']) + i.remove_axis(0) + assert_equal(list(i), a[0, :, :].ravel()) + +def test_iter_remove_multi_index_inner_loop(): + # Check that removing multi-index support works + + a = arange(24).reshape(2, 3, 4) + + i = nditer(a, ['multi_index']) + assert_equal(i.ndim, 3) + assert_equal(i.shape, (2, 3, 4)) + assert_equal(i.itviews[0].shape, (2, 3, 4)) + + # Removing the multi-index tracking causes all dimensions to coalesce + before = list(i) + i.remove_multi_index() + after = list(i) + + assert_equal(before, after) + assert_equal(i.ndim, 1) + assert_raises(ValueError, lambda i: i.shape, i) + assert_equal(i.itviews[0].shape, (24,)) + + # Removing the inner loop means there's just one iteration + i.reset() + assert_equal(i.itersize, 24) + assert_equal(i[0].shape, ()) + i.enable_external_loop() + assert_equal(i.itersize, 24) + assert_equal(i[0].shape, (24,)) + assert_equal(i.value, arange(24)) + +def test_iter_iterindex(): + # Make sure iterindex works + + buffersize = 5 + a = arange(24).reshape(4, 3, 2) + for flags in ([], ['buffered']): + i = nditer(a, flags, buffersize=buffersize) + assert_equal(iter_iterindices(i), list(range(24))) + i.iterindex = 2 + assert_equal(iter_iterindices(i), list(range(2, 24))) + + i = nditer(a, flags, order='F', buffersize=buffersize) + assert_equal(iter_iterindices(i), list(range(24))) + i.iterindex = 5 + assert_equal(iter_iterindices(i), list(range(5, 24))) + + i = nditer(a[::-1], flags, order='F', buffersize=buffersize) + assert_equal(iter_iterindices(i), list(range(24))) + i.iterindex = 9 + assert_equal(iter_iterindices(i), list(range(9, 24))) + + i = nditer(a[::-1, ::-1], flags, order='C', buffersize=buffersize) + assert_equal(iter_iterindices(i), list(range(24))) + i.iterindex = 13 + assert_equal(iter_iterindices(i), list(range(13, 24))) + + i = nditer(a[::1, ::-1], flags, buffersize=buffersize) + assert_equal(iter_iterindices(i), list(range(24))) + i.iterindex = 23 + assert_equal(iter_iterindices(i), list(range(23, 24))) + i.reset() + i.iterindex = 2 + assert_equal(iter_iterindices(i), list(range(2, 24))) + +def test_iter_iterrange(): + # Make sure getting and resetting the iterrange works + + buffersize = 5 + a = arange(24, dtype='i4').reshape(4, 3, 2) + a_fort = a.ravel(order='F') + + i = nditer(a, ['ranged'], ['readonly'], order='F', + buffersize=buffersize) + assert_equal(i.iterrange, (0, 24)) + assert_equal([x[()] for x in i], a_fort) + for r in [(0, 24), (1, 2), (3, 24), (5, 5), (0, 20), (23, 24)]: + i.iterrange = r + assert_equal(i.iterrange, r) + assert_equal([x[()] for x in i], a_fort[r[0]:r[1]]) + + i = nditer(a, ['ranged', 'buffered'], ['readonly'], order='F', + op_dtypes='f8', buffersize=buffersize) + assert_equal(i.iterrange, (0, 24)) + assert_equal([x[()] for x in i], a_fort) + for r in [(0, 24), (1, 2), (3, 24), (5, 5), (0, 20), (23, 24)]: + i.iterrange = r + assert_equal(i.iterrange, r) + assert_equal([x[()] for x in i], a_fort[r[0]:r[1]]) + + def get_array(i): + val = np.array([], dtype='f8') + for x in i: + val = np.concatenate((val, x)) + return val + + i = nditer(a, ['ranged', 'buffered', 'external_loop'], + ['readonly'], order='F', + op_dtypes='f8', buffersize=buffersize) + assert_equal(i.iterrange, (0, 24)) + assert_equal(get_array(i), a_fort) + for r in [(0, 24), (1, 2), (3, 24), (5, 5), (0, 20), (23, 24)]: + i.iterrange = r + assert_equal(i.iterrange, r) + assert_equal(get_array(i), a_fort[r[0]:r[1]]) + +def test_iter_buffering(): + # Test buffering with several buffer sizes and types + arrays = [] + # F-order swapped array + _tmp = np.arange(24, dtype='c16').reshape(2, 3, 4).T + _tmp = _tmp.view(_tmp.dtype.newbyteorder()).byteswap() + arrays.append(_tmp) + # Contiguous 1-dimensional array + arrays.append(np.arange(10, dtype='f4')) + # Unaligned array + a = np.zeros((4 * 16 + 1,), dtype='i1')[1:] + a = a.view('i4') + a[:] = np.arange(16, dtype='i4') + arrays.append(a) + # 4-D F-order array + arrays.append(np.arange(120, dtype='i4').reshape(5, 3, 2, 4).T) + for a in arrays: + for buffersize in (1, 2, 3, 5, 8, 11, 16, 1024): + vals = [] + i = nditer(a, ['buffered', 'external_loop'], + [['readonly', 'nbo', 'aligned']], + order='C', + casting='equiv', + buffersize=buffersize) + while not i.finished: + assert_(i[0].size <= buffersize) + vals.append(i[0].copy()) + i.iternext() + assert_equal(np.concatenate(vals), a.ravel(order='C')) + +def test_iter_write_buffering(): + # Test that buffering of writes is working + + # F-order swapped array + a = np.arange(24).reshape(2, 3, 4).T + a = a.view(a.dtype.newbyteorder()).byteswap() + i = nditer(a, ['buffered'], + [['readwrite', 'nbo', 'aligned']], + casting='equiv', + order='C', + buffersize=16) + x = 0 + with i: + while not i.finished: + i[0] = x + x += 1 + i.iternext() + assert_equal(a.ravel(order='C'), np.arange(24)) + +def test_iter_buffering_delayed_alloc(): + # Test that delaying buffer allocation works + + a = np.arange(6) + b = np.arange(1, dtype='f4') + i = nditer([a, b], ['buffered', 'delay_bufalloc', 'multi_index', 'reduce_ok'], + ['readwrite'], + casting='unsafe', + op_dtypes='f4') + assert_(i.has_delayed_bufalloc) + assert_raises(ValueError, lambda i: i.multi_index, i) + assert_raises(ValueError, lambda i: i[0], i) + assert_raises(ValueError, lambda i: i[0:2], i) + + def assign_iter(i): + i[0] = 0 + assert_raises(ValueError, assign_iter, i) + + i.reset() + assert_(not i.has_delayed_bufalloc) + assert_equal(i.multi_index, (0,)) + with i: + assert_equal(i[0], 0) + i[1] = 1 + assert_equal(i[0:2], [0, 1]) + assert_equal([[x[0][()], x[1][()]] for x in i], list(zip(range(6), [1] * 6))) + +def test_iter_buffered_cast_simple(): + # Test that buffering can handle a simple cast + + a = np.arange(10, dtype='f4') + i = nditer(a, ['buffered', 'external_loop'], + [['readwrite', 'nbo', 'aligned']], + casting='same_kind', + op_dtypes=[np.dtype('f8')], + buffersize=3) + with i: + for v in i: + v[...] *= 2 + + assert_equal(a, 2 * np.arange(10, dtype='f4')) + +def test_iter_buffered_cast_byteswapped(): + # Test that buffering can handle a cast which requires swap->cast->swap + + a = np.arange(10, dtype='f4') + a = a.view(a.dtype.newbyteorder()).byteswap() + i = nditer(a, ['buffered', 'external_loop'], + [['readwrite', 'nbo', 'aligned']], + casting='same_kind', + op_dtypes=[np.dtype('f8').newbyteorder()], + buffersize=3) + with i: + for v in i: + v[...] *= 2 + + assert_equal(a, 2 * np.arange(10, dtype='f4')) + + with warnings.catch_warnings(): + warnings.simplefilter('ignore', np.exceptions.ComplexWarning) + + a = np.arange(10, dtype='f8') + a = a.view(a.dtype.newbyteorder()).byteswap() + i = nditer(a, ['buffered', 'external_loop'], + [['readwrite', 'nbo', 'aligned']], + casting='unsafe', + op_dtypes=[np.dtype('c8').newbyteorder()], + buffersize=3) + with i: + for v in i: + v[...] *= 2 + + assert_equal(a, 2 * np.arange(10, dtype='f8')) + +def test_iter_buffered_cast_byteswapped_complex(): + # Test that buffering can handle a cast which requires swap->cast->copy + + a = np.arange(10, dtype='c8') + a = a.view(a.dtype.newbyteorder()).byteswap() + a += 2j + i = nditer(a, ['buffered', 'external_loop'], + [['readwrite', 'nbo', 'aligned']], + casting='same_kind', + op_dtypes=[np.dtype('c16')], + buffersize=3) + with i: + for v in i: + v[...] *= 2 + assert_equal(a, 2 * np.arange(10, dtype='c8') + 4j) + + a = np.arange(10, dtype='c8') + a += 2j + i = nditer(a, ['buffered', 'external_loop'], + [['readwrite', 'nbo', 'aligned']], + casting='same_kind', + op_dtypes=[np.dtype('c16').newbyteorder()], + buffersize=3) + with i: + for v in i: + v[...] *= 2 + assert_equal(a, 2 * np.arange(10, dtype='c8') + 4j) + + a = np.arange(10, dtype=np.clongdouble) + a = a.view(a.dtype.newbyteorder()).byteswap() + a += 2j + i = nditer(a, ['buffered', 'external_loop'], + [['readwrite', 'nbo', 'aligned']], + casting='same_kind', + op_dtypes=[np.dtype('c16')], + buffersize=3) + with i: + for v in i: + v[...] *= 2 + assert_equal(a, 2 * np.arange(10, dtype=np.clongdouble) + 4j) + + a = np.arange(10, dtype=np.longdouble) + a = a.view(a.dtype.newbyteorder()).byteswap() + i = nditer(a, ['buffered', 'external_loop'], + [['readwrite', 'nbo', 'aligned']], + casting='same_kind', + op_dtypes=[np.dtype('f4')], + buffersize=7) + with i: + for v in i: + v[...] *= 2 + assert_equal(a, 2 * np.arange(10, dtype=np.longdouble)) + +def test_iter_buffered_cast_structured_type(): + # Tests buffering of structured types + + # simple -> struct type (duplicates the value) + sdt = [('a', 'f4'), ('b', 'i8'), ('c', 'c8', (2, 3)), ('d', 'O')] + a = np.arange(3, dtype='f4') + 0.5 + i = nditer(a, ['buffered', 'refs_ok'], ['readonly'], + casting='unsafe', + op_dtypes=sdt) + vals = [np.array(x) for x in i] + assert_equal(vals[0]['a'], 0.5) + assert_equal(vals[0]['b'], 0) + assert_equal(vals[0]['c'], [[(0.5)] * 3] * 2) + assert_equal(vals[0]['d'], 0.5) + assert_equal(vals[1]['a'], 1.5) + assert_equal(vals[1]['b'], 1) + assert_equal(vals[1]['c'], [[(1.5)] * 3] * 2) + assert_equal(vals[1]['d'], 1.5) + assert_equal(vals[0].dtype, np.dtype(sdt)) + + # object -> struct type + sdt = [('a', 'f4'), ('b', 'i8'), ('c', 'c8', (2, 3)), ('d', 'O')] + a = np.zeros((3,), dtype='O') + a[0] = (0.5, 0.5, [[0.5, 0.5, 0.5], [0.5, 0.5, 0.5]], 0.5) + a[1] = (1.5, 1.5, [[1.5, 1.5, 1.5], [1.5, 1.5, 1.5]], 1.5) + a[2] = (2.5, 2.5, [[2.5, 2.5, 2.5], [2.5, 2.5, 2.5]], 2.5) + if HAS_REFCOUNT: + rc = sys.getrefcount(a[0]) + i = nditer(a, ['buffered', 'refs_ok'], ['readonly'], + casting='unsafe', + op_dtypes=sdt) + vals = [x.copy() for x in i] + assert_equal(vals[0]['a'], 0.5) + assert_equal(vals[0]['b'], 0) + assert_equal(vals[0]['c'], [[(0.5)] * 3] * 2) + assert_equal(vals[0]['d'], 0.5) + assert_equal(vals[1]['a'], 1.5) + assert_equal(vals[1]['b'], 1) + assert_equal(vals[1]['c'], [[(1.5)] * 3] * 2) + assert_equal(vals[1]['d'], 1.5) + assert_equal(vals[0].dtype, np.dtype(sdt)) + vals, i, x = [None] * 3 + if HAS_REFCOUNT: + assert_equal(sys.getrefcount(a[0]), rc) + + # single-field struct type -> simple + sdt = [('a', 'f4')] + a = np.array([(5.5,), (8,)], dtype=sdt) + i = nditer(a, ['buffered', 'refs_ok'], ['readonly'], + casting='unsafe', + op_dtypes='i4') + assert_equal([x_[()] for x_ in i], [5, 8]) + + # make sure multi-field struct type -> simple doesn't work + sdt = [('a', 'f4'), ('b', 'i8'), ('d', 'O')] + a = np.array([(5.5, 7, 'test'), (8, 10, 11)], dtype=sdt) + assert_raises(TypeError, lambda: ( + nditer(a, ['buffered', 'refs_ok'], ['readonly'], + casting='unsafe', + op_dtypes='i4'))) + + # struct type -> struct type (field-wise copy) + sdt1 = [('a', 'f4'), ('b', 'i8'), ('d', 'O')] + sdt2 = [('d', 'u2'), ('a', 'O'), ('b', 'f8')] + a = np.array([(1, 2, 3), (4, 5, 6)], dtype=sdt1) + i = nditer(a, ['buffered', 'refs_ok'], ['readonly'], + casting='unsafe', + op_dtypes=sdt2) + assert_equal(i[0].dtype, np.dtype(sdt2)) + assert_equal([np.array(x_) for x_ in i], + [np.array((1, 2, 3), dtype=sdt2), + np.array((4, 5, 6), dtype=sdt2)]) + + +def test_iter_buffered_cast_structured_type_failure_with_cleanup(): + # make sure struct type -> struct type with different + # number of fields fails + sdt1 = [('a', 'f4'), ('b', 'i8'), ('d', 'O')] + sdt2 = [('b', 'O'), ('a', 'f8')] + a = np.array([(1, 2, 3), (4, 5, 6)], dtype=sdt1) + + for intent in ["readwrite", "readonly", "writeonly"]: + # This test was initially designed to test an error at a different + # place, but will now raise earlier to to the cast not being possible: + # `assert np.can_cast(a.dtype, sdt2, casting="unsafe")` fails. + # Without a faulty DType, there is probably no reliable + # way to get the initial tested behaviour. + simple_arr = np.array([1, 2], dtype="i,i") # requires clean up + with pytest.raises(TypeError): + nditer((simple_arr, a), ['buffered', 'refs_ok'], [intent, intent], + casting='unsafe', op_dtypes=["f,f", sdt2]) + + +def test_buffered_cast_error_paths(): + with pytest.raises(ValueError): + # The input is cast into an `S3` buffer + np.nditer((np.array("a", dtype="S1"),), op_dtypes=["i"], + casting="unsafe", flags=["buffered"]) + + # The `M8[ns]` is cast into the `S3` output + it = np.nditer((np.array(1, dtype="i"),), op_dtypes=["S1"], + op_flags=["writeonly"], casting="unsafe", flags=["buffered"]) + with pytest.raises(ValueError): + with it: + buf = next(it) + buf[...] = "a" # cannot be converted to int. + +@pytest.mark.skipif(IS_WASM, reason="Cannot start subprocess") +@pytest.mark.skipif(not HAS_REFCOUNT, reason="PyPy seems to not hit this.") +def test_buffered_cast_error_paths_unraisable(): + # The following gives an unraisable error. Pytest sometimes captures that + # (depending python and/or pytest version). So with Python>=3.8 this can + # probably be cleaned out in the future to check for + # pytest.PytestUnraisableExceptionWarning: + code = textwrap.dedent(""" + import numpy as np + + it = np.nditer((np.array(1, dtype="i"),), op_dtypes=["S1"], + op_flags=["writeonly"], casting="unsafe", flags=["buffered"]) + buf = next(it) + buf[...] = "a" + del buf, it # Flushing only happens during deallocate right now. + """) + res = subprocess.check_output([sys.executable, "-c", code], + stderr=subprocess.STDOUT, text=True) + assert "ValueError" in res + + +def test_iter_buffered_cast_subarray(): + # Tests buffering of subarrays + + # one element -> many (copies it to all) + sdt1 = [('a', 'f4')] + sdt2 = [('a', 'f8', (3, 2, 2))] + a = np.zeros((6,), dtype=sdt1) + a['a'] = np.arange(6) + i = nditer(a, ['buffered', 'refs_ok'], ['readonly'], + casting='unsafe', + op_dtypes=sdt2) + assert_equal(i[0].dtype, np.dtype(sdt2)) + for x, count in zip(i, list(range(6))): + assert_(np.all(x['a'] == count)) + + # one element -> many -> back (copies it to all) + sdt1 = [('a', 'O', (1, 1))] + sdt2 = [('a', 'O', (3, 2, 2))] + a = np.zeros((6,), dtype=sdt1) + a['a'][:, 0, 0] = np.arange(6) + i = nditer(a, ['buffered', 'refs_ok'], ['readwrite'], + casting='unsafe', + op_dtypes=sdt2) + with i: + assert_equal(i[0].dtype, np.dtype(sdt2)) + count = 0 + for x in i: + assert_(np.all(x['a'] == count)) + x['a'][0] += 2 + count += 1 + assert_equal(a['a'], np.arange(6).reshape(6, 1, 1) + 2) + + # many -> one element -> back (copies just element 0) + sdt1 = [('a', 'O', (3, 2, 2))] + sdt2 = [('a', 'O', (1,))] + a = np.zeros((6,), dtype=sdt1) + a['a'][:, 0, 0, 0] = np.arange(6) + i = nditer(a, ['buffered', 'refs_ok'], ['readwrite'], + casting='unsafe', + op_dtypes=sdt2) + with i: + assert_equal(i[0].dtype, np.dtype(sdt2)) + count = 0 + for x in i: + assert_equal(x['a'], count) + x['a'] += 2 + count += 1 + assert_equal(a['a'], np.arange(6).reshape(6, 1, 1, 1) * np.ones((1, 3, 2, 2)) + 2) + + # many -> one element -> back (copies just element 0) + sdt1 = [('a', 'f8', (3, 2, 2))] + sdt2 = [('a', 'O', (1,))] + a = np.zeros((6,), dtype=sdt1) + a['a'][:, 0, 0, 0] = np.arange(6) + i = nditer(a, ['buffered', 'refs_ok'], ['readonly'], + casting='unsafe', + op_dtypes=sdt2) + assert_equal(i[0].dtype, np.dtype(sdt2)) + count = 0 + for x in i: + assert_equal(x['a'], count) + count += 1 + + # many -> one element (copies just element 0) + sdt1 = [('a', 'O', (3, 2, 2))] + sdt2 = [('a', 'f4', (1,))] + a = np.zeros((6,), dtype=sdt1) + a['a'][:, 0, 0, 0] = np.arange(6) + i = nditer(a, ['buffered', 'refs_ok'], ['readonly'], + casting='unsafe', + op_dtypes=sdt2) + assert_equal(i[0].dtype, np.dtype(sdt2)) + count = 0 + for x in i: + assert_equal(x['a'], count) + count += 1 + + # many -> matching shape (straightforward copy) + sdt1 = [('a', 'O', (3, 2, 2))] + sdt2 = [('a', 'f4', (3, 2, 2))] + a = np.zeros((6,), dtype=sdt1) + a['a'] = np.arange(6 * 3 * 2 * 2).reshape(6, 3, 2, 2) + i = nditer(a, ['buffered', 'refs_ok'], ['readonly'], + casting='unsafe', + op_dtypes=sdt2) + assert_equal(i[0].dtype, np.dtype(sdt2)) + count = 0 + for x in i: + assert_equal(x['a'], a[count]['a']) + count += 1 + + # vector -> smaller vector (truncates) + sdt1 = [('a', 'f8', (6,))] + sdt2 = [('a', 'f4', (2,))] + a = np.zeros((6,), dtype=sdt1) + a['a'] = np.arange(6 * 6).reshape(6, 6) + i = nditer(a, ['buffered', 'refs_ok'], ['readonly'], + casting='unsafe', + op_dtypes=sdt2) + assert_equal(i[0].dtype, np.dtype(sdt2)) + count = 0 + for x in i: + assert_equal(x['a'], a[count]['a'][:2]) + count += 1 + + # vector -> bigger vector (pads with zeros) + sdt1 = [('a', 'f8', (2,))] + sdt2 = [('a', 'f4', (6,))] + a = np.zeros((6,), dtype=sdt1) + a['a'] = np.arange(6 * 2).reshape(6, 2) + i = nditer(a, ['buffered', 'refs_ok'], ['readonly'], + casting='unsafe', + op_dtypes=sdt2) + assert_equal(i[0].dtype, np.dtype(sdt2)) + count = 0 + for x in i: + assert_equal(x['a'][:2], a[count]['a']) + assert_equal(x['a'][2:], [0, 0, 0, 0]) + count += 1 + + # vector -> matrix (broadcasts) + sdt1 = [('a', 'f8', (2,))] + sdt2 = [('a', 'f4', (2, 2))] + a = np.zeros((6,), dtype=sdt1) + a['a'] = np.arange(6 * 2).reshape(6, 2) + i = nditer(a, ['buffered', 'refs_ok'], ['readonly'], + casting='unsafe', + op_dtypes=sdt2) + assert_equal(i[0].dtype, np.dtype(sdt2)) + count = 0 + for x in i: + assert_equal(x['a'][0], a[count]['a']) + assert_equal(x['a'][1], a[count]['a']) + count += 1 + + # vector -> matrix (broadcasts and zero-pads) + sdt1 = [('a', 'f8', (2, 1))] + sdt2 = [('a', 'f4', (3, 2))] + a = np.zeros((6,), dtype=sdt1) + a['a'] = np.arange(6 * 2).reshape(6, 2, 1) + i = nditer(a, ['buffered', 'refs_ok'], ['readonly'], + casting='unsafe', + op_dtypes=sdt2) + assert_equal(i[0].dtype, np.dtype(sdt2)) + count = 0 + for x in i: + assert_equal(x['a'][:2, 0], a[count]['a'][:, 0]) + assert_equal(x['a'][:2, 1], a[count]['a'][:, 0]) + assert_equal(x['a'][2, :], [0, 0]) + count += 1 + + # matrix -> matrix (truncates and zero-pads) + sdt1 = [('a', 'f8', (2, 3))] + sdt2 = [('a', 'f4', (3, 2))] + a = np.zeros((6,), dtype=sdt1) + a['a'] = np.arange(6 * 2 * 3).reshape(6, 2, 3) + i = nditer(a, ['buffered', 'refs_ok'], ['readonly'], + casting='unsafe', + op_dtypes=sdt2) + assert_equal(i[0].dtype, np.dtype(sdt2)) + count = 0 + for x in i: + assert_equal(x['a'][:2, 0], a[count]['a'][:, 0]) + assert_equal(x['a'][:2, 1], a[count]['a'][:, 1]) + assert_equal(x['a'][2, :], [0, 0]) + count += 1 + +def test_iter_buffering_badwriteback(): + # Writing back from a buffer cannot combine elements + + # a needs write buffering, but had a broadcast dimension + a = np.arange(6).reshape(2, 3, 1) + b = np.arange(12).reshape(2, 3, 2) + assert_raises(ValueError, nditer, [a, b], + ['buffered', 'external_loop'], + [['readwrite'], ['writeonly']], + order='C') + + # But if a is readonly, it's fine + nditer([a, b], ['buffered', 'external_loop'], + [['readonly'], ['writeonly']], + order='C') + + # If a has just one element, it's fine too (constant 0 stride, a reduction) + a = np.arange(1).reshape(1, 1, 1) + nditer([a, b], ['buffered', 'external_loop', 'reduce_ok'], + [['readwrite'], ['writeonly']], + order='C') + + # check that it fails on other dimensions too + a = np.arange(6).reshape(1, 3, 2) + assert_raises(ValueError, nditer, [a, b], + ['buffered', 'external_loop'], + [['readwrite'], ['writeonly']], + order='C') + a = np.arange(4).reshape(2, 1, 2) + assert_raises(ValueError, nditer, [a, b], + ['buffered', 'external_loop'], + [['readwrite'], ['writeonly']], + order='C') + +def test_iter_buffering_string(): + # Safe casting disallows shrinking strings + a = np.array(['abc', 'a', 'abcd'], dtype=np.bytes_) + assert_equal(a.dtype, np.dtype('S4')) + assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'], + op_dtypes='S2') + i = nditer(a, ['buffered'], ['readonly'], op_dtypes='S6') + assert_equal(i[0], b'abc') + assert_equal(i[0].dtype, np.dtype('S6')) + + a = np.array(['abc', 'a', 'abcd'], dtype=np.str_) + assert_equal(a.dtype, np.dtype('U4')) + assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'], + op_dtypes='U2') + i = nditer(a, ['buffered'], ['readonly'], op_dtypes='U6') + assert_equal(i[0], 'abc') + assert_equal(i[0].dtype, np.dtype('U6')) + +def test_iter_buffering_growinner(): + # Test that the inner loop grows when no buffering is needed + a = np.arange(30) + i = nditer(a, ['buffered', 'growinner', 'external_loop'], + buffersize=5) + # Should end up with just one inner loop here + assert_equal(i[0].size, a.size) + + +@pytest.mark.parametrize("read_or_readwrite", ["readonly", "readwrite"]) +def test_iter_contig_flag_reduce_error(read_or_readwrite): + # Test that a non-contiguous operand is rejected without buffering. + # NOTE: This is true even for a reduction, where we return a 0-stride + # below! + with pytest.raises(TypeError, match="Iterator operand required buffering"): + it = np.nditer( + (np.zeros(()),), flags=["external_loop", "reduce_ok"], + op_flags=[(read_or_readwrite, "contig"),], itershape=(10,)) + + +@pytest.mark.parametrize("arr", [ + lambda: np.zeros(()), + lambda: np.zeros((20, 1))[::20], + lambda: np.zeros((1, 20))[:, ::20] + ]) +def test_iter_contig_flag_single_operand_strides(arr): + """ + Tests the strides with the contig flag for both broadcast and non-broadcast + operands in 3 cases where the logic is needed: + 1. When everything has a zero stride, the broadcast op needs to repeated + 2. When the reduce axis is the last axis (first to iterate). + 3. When the reduce axis is the first axis (last to iterate). + + NOTE: The semantics of the cast flag are not clearly defined when + it comes to reduction. It is unclear that there are any users. + """ + first_op = np.ones((10, 10)) + broadcast_op = arr() + red_op = arr() + # Add a first operand to ensure no axis-reordering and the result shape. + iterator = np.nditer( + (first_op, broadcast_op, red_op), + flags=["external_loop", "reduce_ok", "buffered", "delay_bufalloc"], + op_flags=[("readonly", "contig")] * 2 + [("readwrite", "contig")]) + + with iterator: + iterator.reset() + for f, b, r in iterator: + # The first operand is contigouos, we should have a view + assert np.shares_memory(f, first_op) + # Although broadcast, the second op always has a contiguous stride + assert b.strides[0] == 8 + assert not np.shares_memory(b, broadcast_op) + # The reduction has a contiguous stride or a 0 stride + if red_op.ndim == 0 or red_op.shape[-1] == 1: + assert r.strides[0] == 0 + else: + # The stride is 8, although it was not originally: + assert r.strides[0] == 8 + # If the reduce stride is 0, buffering makes no difference, but we + # do it anyway right now: + assert not np.shares_memory(r, red_op) + + +@pytest.mark.xfail(reason="The contig flag was always buggy.") +def test_iter_contig_flag_incorrect(): + # This case does the wrong thing... + iterator = np.nditer( + (np.ones((10, 10)).T, np.ones((1, 10))), + flags=["external_loop", "reduce_ok", "buffered", "delay_bufalloc"], + op_flags=[("readonly", "contig")] * 2) + + with iterator: + iterator.reset() + for a, b in iterator: + # Remove a and b from locals (pytest may want to format them) + a, b = a.strides, b.strides + assert a == 8 + assert b == 8 # should be 8 but is 0 due to axis reorder + + +@pytest.mark.slow +def test_iter_buffered_reduce_reuse(): + # large enough array for all views, including negative strides. + a = np.arange(2 * 3**5)[3**5:3**5 + 1] + flags = ['buffered', 'delay_bufalloc', 'multi_index', 'reduce_ok', 'refs_ok'] + op_flags = [('readonly',), ('readwrite', 'allocate')] + op_axes_list = [[(0, 1, 2), (0, 1, -1)], [(0, 1, 2), (0, -1, -1)]] + # wrong dtype to force buffering + op_dtypes = [float, a.dtype] + + def get_params(): + for xs in range(-3**2, 3**2 + 1): + for ys in range(xs, 3**2 + 1): + for op_axes in op_axes_list: + # last stride is reduced and because of that not + # important for this test, as it is the inner stride. + strides = (xs * a.itemsize, ys * a.itemsize, a.itemsize) + arr = np.lib.stride_tricks.as_strided(a, (3, 3, 3), strides) + + for skip in [0, 1]: + yield arr, op_axes, skip + + for arr, op_axes, skip in get_params(): + nditer2 = np.nditer([arr.copy(), None], + op_axes=op_axes, flags=flags, op_flags=op_flags, + op_dtypes=op_dtypes) + with nditer2: + nditer2.operands[-1][...] = 0 + nditer2.reset() + nditer2.iterindex = skip + + for (a2_in, b2_in) in nditer2: + b2_in += a2_in.astype(np.int_) + + comp_res = nditer2.operands[-1] + + for bufsize in range(3**3): + nditer1 = np.nditer([arr, None], + op_axes=op_axes, flags=flags, op_flags=op_flags, + buffersize=bufsize, op_dtypes=op_dtypes) + with nditer1: + nditer1.operands[-1][...] = 0 + nditer1.reset() + nditer1.iterindex = skip + + for (a1_in, b1_in) in nditer1: + b1_in += a1_in.astype(np.int_) + + res = nditer1.operands[-1] + assert_array_equal(res, comp_res) + + +def test_iter_buffered_reduce_reuse_core(): + # NumPy re-uses buffers for broadcast operands (as of writing when reading). + # Test this even if the offset is manually set at some point during + # the iteration. (not a particularly tricky path) + arr = np.empty((1, 6, 4, 1)).reshape(1, 6, 4, 1)[:, ::3, ::2, :] + arr[...] = np.arange(arr.size).reshape(arr.shape) + # First and last dimension are broadcast dimensions. + arr = np.broadcast_to(arr, (100, 2, 2, 2)) + + flags = ['buffered', 'reduce_ok', 'refs_ok', 'multi_index'] + op_flags = [('readonly',)] + + buffersize = 100 # small enough to not fit the whole array + it = np.nditer(arr, flags=flags, op_flags=op_flags, buffersize=100) + + # Iterate a bit (this will cause buffering internally) + expected = [next(it) for i in range(11)] + # Now, manually advance to inside the core (the +1) + it.iterindex = 10 * (2 * 2 * 2) + 1 + result = [next(it) for i in range(10)] + + assert expected[1:] == result + + +def test_iter_no_broadcast(): + # Test that the no_broadcast flag works + a = np.arange(24).reshape(2, 3, 4) + b = np.arange(6).reshape(2, 3, 1) + c = np.arange(12).reshape(3, 4) + + nditer([a, b, c], [], + [['readonly', 'no_broadcast'], + ['readonly'], ['readonly']]) + assert_raises(ValueError, nditer, [a, b, c], [], + [['readonly'], ['readonly', 'no_broadcast'], ['readonly']]) + assert_raises(ValueError, nditer, [a, b, c], [], + [['readonly'], ['readonly'], ['readonly', 'no_broadcast']]) + + +class TestIterNested: + + def test_basic(self): + # Test nested iteration basic usage + a = arange(12).reshape(2, 3, 2) + + i, j = np.nested_iters(a, [[0], [1, 2]]) + vals = [list(j) for _ in i] + assert_equal(vals, [[0, 1, 2, 3, 4, 5], [6, 7, 8, 9, 10, 11]]) + + i, j = np.nested_iters(a, [[0, 1], [2]]) + vals = [list(j) for _ in i] + assert_equal(vals, [[0, 1], [2, 3], [4, 5], [6, 7], [8, 9], [10, 11]]) + + i, j = np.nested_iters(a, [[0, 2], [1]]) + vals = [list(j) for _ in i] + assert_equal(vals, [[0, 2, 4], [1, 3, 5], [6, 8, 10], [7, 9, 11]]) + + def test_reorder(self): + # Test nested iteration basic usage + a = arange(12).reshape(2, 3, 2) + + # In 'K' order (default), it gets reordered + i, j = np.nested_iters(a, [[0], [2, 1]]) + vals = [list(j) for _ in i] + assert_equal(vals, [[0, 1, 2, 3, 4, 5], [6, 7, 8, 9, 10, 11]]) + + i, j = np.nested_iters(a, [[1, 0], [2]]) + vals = [list(j) for _ in i] + assert_equal(vals, [[0, 1], [2, 3], [4, 5], [6, 7], [8, 9], [10, 11]]) + + i, j = np.nested_iters(a, [[2, 0], [1]]) + vals = [list(j) for _ in i] + assert_equal(vals, [[0, 2, 4], [1, 3, 5], [6, 8, 10], [7, 9, 11]]) + + # In 'C' order, it doesn't + i, j = np.nested_iters(a, [[0], [2, 1]], order='C') + vals = [list(j) for _ in i] + assert_equal(vals, [[0, 2, 4, 1, 3, 5], [6, 8, 10, 7, 9, 11]]) + + i, j = np.nested_iters(a, [[1, 0], [2]], order='C') + vals = [list(j) for _ in i] + assert_equal(vals, [[0, 1], [6, 7], [2, 3], [8, 9], [4, 5], [10, 11]]) + + i, j = np.nested_iters(a, [[2, 0], [1]], order='C') + vals = [list(j) for _ in i] + assert_equal(vals, [[0, 2, 4], [6, 8, 10], [1, 3, 5], [7, 9, 11]]) + + def test_flip_axes(self): + # Test nested iteration with negative axes + a = arange(12).reshape(2, 3, 2)[::-1, ::-1, ::-1] + + # In 'K' order (default), the axes all get flipped + i, j = np.nested_iters(a, [[0], [1, 2]]) + vals = [list(j) for _ in i] + assert_equal(vals, [[0, 1, 2, 3, 4, 5], [6, 7, 8, 9, 10, 11]]) + + i, j = np.nested_iters(a, [[0, 1], [2]]) + vals = [list(j) for _ in i] + assert_equal(vals, [[0, 1], [2, 3], [4, 5], [6, 7], [8, 9], [10, 11]]) + + i, j = np.nested_iters(a, [[0, 2], [1]]) + vals = [list(j) for _ in i] + assert_equal(vals, [[0, 2, 4], [1, 3, 5], [6, 8, 10], [7, 9, 11]]) + + # In 'C' order, flipping axes is disabled + i, j = np.nested_iters(a, [[0], [1, 2]], order='C') + vals = [list(j) for _ in i] + assert_equal(vals, [[11, 10, 9, 8, 7, 6], [5, 4, 3, 2, 1, 0]]) + + i, j = np.nested_iters(a, [[0, 1], [2]], order='C') + vals = [list(j) for _ in i] + assert_equal(vals, [[11, 10], [9, 8], [7, 6], [5, 4], [3, 2], [1, 0]]) + + i, j = np.nested_iters(a, [[0, 2], [1]], order='C') + vals = [list(j) for _ in i] + assert_equal(vals, [[11, 9, 7], [10, 8, 6], [5, 3, 1], [4, 2, 0]]) + + def test_broadcast(self): + # Test nested iteration with broadcasting + a = arange(2).reshape(2, 1) + b = arange(3).reshape(1, 3) + + i, j = np.nested_iters([a, b], [[0], [1]]) + vals = [list(j) for _ in i] + assert_equal(vals, [[[0, 0], [0, 1], [0, 2]], [[1, 0], [1, 1], [1, 2]]]) + + i, j = np.nested_iters([a, b], [[1], [0]]) + vals = [list(j) for _ in i] + assert_equal(vals, [[[0, 0], [1, 0]], [[0, 1], [1, 1]], [[0, 2], [1, 2]]]) + + def test_dtype_copy(self): + # Test nested iteration with a copy to change dtype + + # copy + a = arange(6, dtype='i4').reshape(2, 3) + i, j = np.nested_iters(a, [[0], [1]], + op_flags=['readonly', 'copy'], + op_dtypes='f8') + assert_equal(j[0].dtype, np.dtype('f8')) + vals = [list(j) for _ in i] + assert_equal(vals, [[0, 1, 2], [3, 4, 5]]) + vals = None + + # writebackifcopy - using context manager + a = arange(6, dtype='f4').reshape(2, 3) + i, j = np.nested_iters(a, [[0], [1]], + op_flags=['readwrite', 'updateifcopy'], + casting='same_kind', + op_dtypes='f8') + with i, j: + assert_equal(j[0].dtype, np.dtype('f8')) + for x in i: + for y in j: + y[...] += 1 + assert_equal(a, [[0, 1, 2], [3, 4, 5]]) + assert_equal(a, [[1, 2, 3], [4, 5, 6]]) + + # writebackifcopy - using close() + a = arange(6, dtype='f4').reshape(2, 3) + i, j = np.nested_iters(a, [[0], [1]], + op_flags=['readwrite', 'updateifcopy'], + casting='same_kind', + op_dtypes='f8') + assert_equal(j[0].dtype, np.dtype('f8')) + for x in i: + for y in j: + y[...] += 1 + assert_equal(a, [[0, 1, 2], [3, 4, 5]]) + i.close() + j.close() + assert_equal(a, [[1, 2, 3], [4, 5, 6]]) + + def test_dtype_buffered(self): + # Test nested iteration with buffering to change dtype + + a = arange(6, dtype='f4').reshape(2, 3) + i, j = np.nested_iters(a, [[0], [1]], + flags=['buffered'], + op_flags=['readwrite'], + casting='same_kind', + op_dtypes='f8') + assert_equal(j[0].dtype, np.dtype('f8')) + for x in i: + for y in j: + y[...] += 1 + assert_equal(a, [[1, 2, 3], [4, 5, 6]]) + + def test_0d(self): + a = np.arange(12).reshape(2, 3, 2) + i, j = np.nested_iters(a, [[], [1, 0, 2]]) + vals = [list(j) for _ in i] + assert_equal(vals, [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11]]) + + i, j = np.nested_iters(a, [[1, 0, 2], []]) + vals = [list(j) for _ in i] + assert_equal(vals, [[0], [1], [2], [3], [4], [5], [6], [7], [8], [9], [10], [11]]) + + i, j, k = np.nested_iters(a, [[2, 0], [], [1]]) + vals = [] + for x in i: + for y in j: + vals.append(list(k)) + assert_equal(vals, [[0, 2, 4], [1, 3, 5], [6, 8, 10], [7, 9, 11]]) + + def test_iter_nested_iters_dtype_buffered(self): + # Test nested iteration with buffering to change dtype + + a = arange(6, dtype='f4').reshape(2, 3) + i, j = np.nested_iters(a, [[0], [1]], + flags=['buffered'], + op_flags=['readwrite'], + casting='same_kind', + op_dtypes='f8') + with i, j: + assert_equal(j[0].dtype, np.dtype('f8')) + for x in i: + for y in j: + y[...] += 1 + assert_equal(a, [[1, 2, 3], [4, 5, 6]]) + +def test_iter_reduction_error(): + + a = np.arange(6) + assert_raises(ValueError, nditer, [a, None], [], + [['readonly'], ['readwrite', 'allocate']], + op_axes=[[0], [-1]]) + + a = np.arange(6).reshape(2, 3) + assert_raises(ValueError, nditer, [a, None], ['external_loop'], + [['readonly'], ['readwrite', 'allocate']], + op_axes=[[0, 1], [-1, -1]]) + +def test_iter_reduction(): + # Test doing reductions with the iterator + + a = np.arange(6) + i = nditer([a, None], ['reduce_ok'], + [['readonly'], ['readwrite', 'allocate']], + op_axes=[[0], [-1]]) + # Need to initialize the output operand to the addition unit + with i: + i.operands[1][...] = 0 + # Do the reduction + for x, y in i: + y[...] += x + # Since no axes were specified, should have allocated a scalar + assert_equal(i.operands[1].ndim, 0) + assert_equal(i.operands[1], np.sum(a)) + + a = np.arange(6).reshape(2, 3) + i = nditer([a, None], ['reduce_ok', 'external_loop'], + [['readonly'], ['readwrite', 'allocate']], + op_axes=[[0, 1], [-1, -1]]) + # Need to initialize the output operand to the addition unit + with i: + i.operands[1][...] = 0 + # Reduction shape/strides for the output + assert_equal(i[1].shape, (6,)) + assert_equal(i[1].strides, (0,)) + # Do the reduction + for x, y in i: + # Use a for loop instead of ``y[...] += x`` + # (equivalent to ``y[...] = y[...].copy() + x``), + # because y has zero strides we use for the reduction + for j in range(len(y)): + y[j] += x[j] + # Since no axes were specified, should have allocated a scalar + assert_equal(i.operands[1].ndim, 0) + assert_equal(i.operands[1], np.sum(a)) + + # This is a tricky reduction case for the buffering double loop + # to handle + a = np.ones((2, 3, 5)) + it1 = nditer([a, None], ['reduce_ok', 'external_loop'], + [['readonly'], ['readwrite', 'allocate']], + op_axes=[None, [0, -1, 1]]) + it2 = nditer([a, None], ['reduce_ok', 'external_loop', + 'buffered', 'delay_bufalloc'], + [['readonly'], ['readwrite', 'allocate']], + op_axes=[None, [0, -1, 1]], buffersize=10) + with it1, it2: + it1.operands[1].fill(0) + it2.operands[1].fill(0) + it2.reset() + for x in it1: + x[1][...] += x[0] + for x in it2: + x[1][...] += x[0] + assert_equal(it1.operands[1], it2.operands[1]) + assert_equal(it2.operands[1].sum(), a.size) + +def test_iter_buffering_reduction(): + # Test doing buffered reductions with the iterator + + a = np.arange(6) + b = np.array(0., dtype='f8').byteswap() + b = b.view(b.dtype.newbyteorder()) + i = nditer([a, b], ['reduce_ok', 'buffered'], + [['readonly'], ['readwrite', 'nbo']], + op_axes=[[0], [-1]]) + with i: + assert_equal(i[1].dtype, np.dtype('f8')) + assert_(i[1].dtype != b.dtype) + # Do the reduction + for x, y in i: + y[...] += x + # Since no axes were specified, should have allocated a scalar + assert_equal(b, np.sum(a)) + + a = np.arange(6).reshape(2, 3) + b = np.array([0, 0], dtype='f8').byteswap() + b = b.view(b.dtype.newbyteorder()) + i = nditer([a, b], ['reduce_ok', 'external_loop', 'buffered'], + [['readonly'], ['readwrite', 'nbo']], + op_axes=[[0, 1], [0, -1]]) + # Reduction shape/strides for the output + with i: + assert_equal(i[1].shape, (3,)) + assert_equal(i[1].strides, (0,)) + # Do the reduction + for x, y in i: + # Use a for loop instead of ``y[...] += x`` + # (equivalent to ``y[...] = y[...].copy() + x``), + # because y has zero strides we use for the reduction + for j in range(len(y)): + y[j] += x[j] + assert_equal(b, np.sum(a, axis=1)) + + # Iterator inner double loop was wrong on this one + p = np.arange(2) + 1 + it = np.nditer([p, None], + ['delay_bufalloc', 'reduce_ok', 'buffered', 'external_loop'], + [['readonly'], ['readwrite', 'allocate']], + op_axes=[[-1, 0], [-1, -1]], + itershape=(2, 2)) + with it: + it.operands[1].fill(0) + it.reset() + assert_equal(it[0], [1, 2, 1, 2]) + + # Iterator inner loop should take argument contiguity into account + x = np.ones((7, 13, 8), np.int8)[4:6, 1:11:6, 1:5].transpose(1, 2, 0) + x[...] = np.arange(x.size).reshape(x.shape) + y_base = np.arange(4 * 4, dtype=np.int8).reshape(4, 4) + y_base_copy = y_base.copy() + y = y_base[::2, :, None] + + it = np.nditer([y, x], + ['buffered', 'external_loop', 'reduce_ok'], + [['readwrite'], ['readonly']]) + with it: + for a, b in it: + a.fill(2) + + assert_equal(y_base[1::2], y_base_copy[1::2]) + assert_equal(y_base[::2], 2) + +def test_iter_buffering_reduction_reuse_reduce_loops(): + # There was a bug triggering reuse of the reduce loop inappropriately, + # which caused processing to happen in unnecessarily small chunks + # and overran the buffer. + + a = np.zeros((2, 7)) + b = np.zeros((1, 7)) + it = np.nditer([a, b], flags=['reduce_ok', 'external_loop', 'buffered'], + op_flags=[['readonly'], ['readwrite']], + buffersize=5) + + with it: + bufsizes = [x.shape[0] for x, y in it] + assert_equal(bufsizes, [5, 2, 5, 2]) + assert_equal(sum(bufsizes), a.size) + +def test_iter_writemasked_badinput(): + a = np.zeros((2, 3)) + b = np.zeros((3,)) + m = np.array([[True, True, False], [False, True, False]]) + m2 = np.array([True, True, False]) + m3 = np.array([0, 1, 1], dtype='u1') + mbad1 = np.array([0, 1, 1], dtype='i1') + mbad2 = np.array([0, 1, 1], dtype='f4') + + # Need an 'arraymask' if any operand is 'writemasked' + assert_raises(ValueError, nditer, [a, m], [], + [['readwrite', 'writemasked'], ['readonly']]) + + # A 'writemasked' operand must not be readonly + assert_raises(ValueError, nditer, [a, m], [], + [['readonly', 'writemasked'], ['readonly', 'arraymask']]) + + # 'writemasked' and 'arraymask' may not be used together + assert_raises(ValueError, nditer, [a, m], [], + [['readonly'], ['readwrite', 'arraymask', 'writemasked']]) + + # 'arraymask' may only be specified once + assert_raises(ValueError, nditer, [a, m, m2], [], + [['readwrite', 'writemasked'], + ['readonly', 'arraymask'], + ['readonly', 'arraymask']]) + + # An 'arraymask' with nothing 'writemasked' also doesn't make sense + assert_raises(ValueError, nditer, [a, m], [], + [['readwrite'], ['readonly', 'arraymask']]) + + # A writemasked reduction requires a similarly smaller mask + assert_raises(ValueError, nditer, [a, b, m], ['reduce_ok'], + [['readonly'], + ['readwrite', 'writemasked'], + ['readonly', 'arraymask']]) + # But this should work with a smaller/equal mask to the reduction operand + np.nditer([a, b, m2], ['reduce_ok'], + [['readonly'], + ['readwrite', 'writemasked'], + ['readonly', 'arraymask']]) + # The arraymask itself cannot be a reduction + assert_raises(ValueError, nditer, [a, b, m2], ['reduce_ok'], + [['readonly'], + ['readwrite', 'writemasked'], + ['readwrite', 'arraymask']]) + + # A uint8 mask is ok too + np.nditer([a, m3], ['buffered'], + [['readwrite', 'writemasked'], + ['readonly', 'arraymask']], + op_dtypes=['f4', None], + casting='same_kind') + # An int8 mask isn't ok + assert_raises(TypeError, np.nditer, [a, mbad1], ['buffered'], + [['readwrite', 'writemasked'], + ['readonly', 'arraymask']], + op_dtypes=['f4', None], + casting='same_kind') + # A float32 mask isn't ok + assert_raises(TypeError, np.nditer, [a, mbad2], ['buffered'], + [['readwrite', 'writemasked'], + ['readonly', 'arraymask']], + op_dtypes=['f4', None], + casting='same_kind') + + +def _is_buffered(iterator): + try: + iterator.itviews + except ValueError: + return True + return False + +@pytest.mark.parametrize("arrs", + [np.zeros((3,), dtype='f8'), + np.zeros((9876, 3 * 5), dtype='f8')[::2, :], + np.zeros((4, 312, 124, 3), dtype='f8')[::2, :, ::2, :], + # Also test with the last dimension strided (so it does not fit if + # there is repeated access) + np.zeros((9,), dtype='f8')[::3], + np.zeros((9876, 3 * 10), dtype='f8')[::2, ::5], + np.zeros((4, 312, 124, 3), dtype='f8')[::2, :, ::2, ::-1]]) +def test_iter_writemasked(arrs): + # Note, the slicing above is to ensure that nditer cannot combine multiple + # axes into one. The repetition is just to make things a bit more + # interesting. + a = arrs.copy() + shape = a.shape + reps = shape[-1] // 3 + msk = np.empty(shape, dtype=bool) + msk[...] = [True, True, False] * reps + + # When buffering is unused, 'writemasked' effectively does nothing. + # It's up to the user of the iterator to obey the requested semantics. + it = np.nditer([a, msk], [], + [['readwrite', 'writemasked'], + ['readonly', 'arraymask']]) + with it: + for x, m in it: + x[...] = 1 + # Because we violated the semantics, all the values became 1 + assert_equal(a, np.broadcast_to([1, 1, 1] * reps, shape)) + + # Even if buffering is enabled, we still may be accessing the array + # directly. + it = np.nditer([a, msk], ['buffered'], + [['readwrite', 'writemasked'], + ['readonly', 'arraymask']]) + # @seberg: I honestly don't currently understand why a "buffered" iterator + # would end up not using a buffer for the small array here at least when + # "writemasked" is used, that seems confusing... Check by testing for + # actual memory overlap! + is_buffered = True + with it: + for x, m in it: + x[...] = 2.5 + if np.may_share_memory(x, a): + is_buffered = False + + if not is_buffered: + # Because we violated the semantics, all the values became 2.5 + assert_equal(a, np.broadcast_to([2.5, 2.5, 2.5] * reps, shape)) + else: + # For large sizes, the iterator may be buffered: + assert_equal(a, np.broadcast_to([2.5, 2.5, 1] * reps, shape)) + a[...] = 2.5 + + # If buffering will definitely happening, for instance because of + # a cast, only the items selected by the mask will be copied back from + # the buffer. + it = np.nditer([a, msk], ['buffered'], + [['readwrite', 'writemasked'], + ['readonly', 'arraymask']], + op_dtypes=['i8', None], + casting='unsafe') + with it: + for x, m in it: + x[...] = 3 + # Even though we violated the semantics, only the selected values + # were copied back + assert_equal(a, np.broadcast_to([3, 3, 2.5] * reps, shape)) + + +@pytest.mark.parametrize(["mask", "mask_axes"], [ + # Allocated operand (only broadcasts with -1) + (None, [-1, 0]), + # Reduction along the first dimension (with and without op_axes) + (np.zeros((1, 4), dtype="bool"), [0, 1]), + (np.zeros((1, 4), dtype="bool"), None), + # Test 0-D and -1 op_axes + (np.zeros(4, dtype="bool"), [-1, 0]), + (np.zeros((), dtype="bool"), [-1, -1]), + (np.zeros((), dtype="bool"), None)]) +def test_iter_writemasked_broadcast_error(mask, mask_axes): + # This assumes that a readwrite mask makes sense. This is likely not the + # case and should simply be deprecated. + arr = np.zeros((3, 4)) + itflags = ["reduce_ok"] + mask_flags = ["arraymask", "readwrite", "allocate"] + a_flags = ["writeonly", "writemasked"] + if mask_axes is None: + op_axes = None + else: + op_axes = [mask_axes, [0, 1]] + + with assert_raises(ValueError): + np.nditer((mask, arr), flags=itflags, op_flags=[mask_flags, a_flags], + op_axes=op_axes) + + +def test_iter_writemasked_decref(): + # force casting (to make it interesting) by using a structured dtype. + arr = np.arange(10000).astype(">i,O") + original = arr.copy() + mask = np.random.randint(0, 2, size=10000).astype(bool) + + it = np.nditer([arr, mask], ['buffered', "refs_ok"], + [['readwrite', 'writemasked'], + ['readonly', 'arraymask']], + op_dtypes=[" string -> longdouble` for the + # conversion. But Python may refuse `str(int)` for huge ints. + # In that case, RuntimeWarning would be correct, but conversion + # fails earlier (seems to happen on 32bit linux, possibly only debug). + if dtype in "gG": + try: + str(too_big_int) + except ValueError: + pytest.skip("`huge_int -> string -> longdouble` failed") + + # Otherwise, we overflow to infinity: + with pytest.warns(RuntimeWarning): + res = scalar_type(1) + too_big_int + assert res.dtype == dtype + assert res == np.inf + + with pytest.warns(RuntimeWarning): + # We force the dtype here, since windows may otherwise pick the + # double instead of the longdouble loop. That leads to slightly + # different results (conversion of the int fails as above). + res = np.add(np.array(1, dtype=dtype), too_big_int, dtype=dtype) + assert res.dtype == dtype + assert res == np.inf + + +@pytest.mark.parametrize("op", [operator.add, operator.pow]) +def test_weak_promotion_scalar_path(op): + # Some additional paths exercising the weak scalars. + + # Integer path: + res = op(np.uint8(3), 5) + assert res == op(3, 5) + assert res.dtype == np.uint8 or res.dtype == bool # noqa: PLR1714 + + with pytest.raises(OverflowError): + op(np.uint8(3), 1000) + + # Float path: + res = op(np.float32(3), 5.) + assert res == op(3., 5.) + assert res.dtype == np.float32 or res.dtype == bool # noqa: PLR1714 + + +def test_nep50_complex_promotion(): + with pytest.warns(RuntimeWarning, match=".*overflow"): + res = np.complex64(3) + complex(2**300) + + assert type(res) == np.complex64 + + +def test_nep50_integer_conversion_errors(): + # Implementation for error paths is mostly missing (as of writing) + with pytest.raises(OverflowError, match=".*uint8"): + np.array([1], np.uint8) + 300 + + with pytest.raises(OverflowError, match=".*uint8"): + np.uint8(1) + 300 + + # Error message depends on platform (maybe unsigned int or unsigned long) + with pytest.raises(OverflowError, + match="Python integer -1 out of bounds for uint8"): + np.uint8(1) + -1 + + +def test_nep50_with_axisconcatenator(): + # Concatenate/r_ does not promote, so this has to error: + with pytest.raises(OverflowError): + np.r_[np.arange(5, dtype=np.int8), 255] + + +@pytest.mark.parametrize("ufunc", [np.add, np.power]) +def test_nep50_huge_integers(ufunc): + # Very large integers are complicated, because they go to uint64 or + # object dtype. This tests covers a few possible paths. + with pytest.raises(OverflowError): + ufunc(np.int64(0), 2**63) # 2**63 too large for int64 + + with pytest.raises(OverflowError): + ufunc(np.uint64(0), 2**64) # 2**64 cannot be represented by uint64 + + # However, 2**63 can be represented by the uint64 (and that is used): + res = ufunc(np.uint64(1), 2**63) + + assert res.dtype == np.uint64 + assert res == ufunc(1, 2**63, dtype=object) + + # The following paths fail to warn correctly about the change: + with pytest.raises(OverflowError): + ufunc(np.int64(1), 2**63) # np.array(2**63) would go to uint + + with pytest.raises(OverflowError): + ufunc(np.int64(1), 2**100) # np.array(2**100) would go to object + + # This would go to object and thus a Python float, not a NumPy one: + res = ufunc(1.0, 2**100) + assert isinstance(res, np.float64) + + +def test_nep50_in_concat_and_choose(): + res = np.concatenate([np.float32(1), 1.], axis=None) + assert res.dtype == "float32" + + res = np.choose(1, [np.float32(1), 1.]) + assert res.dtype == "float32" + + +@pytest.mark.parametrize("expected,dtypes,optional_dtypes", [ + (np.float32, [np.float32], + [np.float16, 0.0, np.uint16, np.int16, np.int8, 0]), + (np.complex64, [np.float32, 0j], + [np.float16, 0.0, np.uint16, np.int16, np.int8, 0]), + (np.float32, [np.int16, np.uint16, np.float16], + [np.int8, np.uint8, np.float32, 0., 0]), + (np.int32, [np.int16, np.uint16], + [np.int8, np.uint8, 0, np.bool]), + ]) +@hypothesis.given(data=strategies.data()) +def test_expected_promotion(expected, dtypes, optional_dtypes, data): + # Sample randomly while ensuring "dtypes" is always present: + optional = data.draw(strategies.lists( + strategies.sampled_from(dtypes + optional_dtypes))) + all_dtypes = dtypes + optional + dtypes_sample = data.draw(strategies.permutations(all_dtypes)) + + res = np.result_type(*dtypes_sample) + assert res == expected + + +@pytest.mark.parametrize("sctype", + [np.int8, np.int16, np.int32, np.int64, + np.uint8, np.uint16, np.uint32, np.uint64]) +@pytest.mark.parametrize("other_val", + [-2 * 100, -1, 0, 9, 10, 11, 2**63, 2 * 100]) +@pytest.mark.parametrize("comp", + [operator.eq, operator.ne, operator.le, operator.lt, + operator.ge, operator.gt]) +def test_integer_comparison(sctype, other_val, comp): + # Test that comparisons with integers (especially out-of-bound) ones + # works correctly. + val_obj = 10 + val = sctype(val_obj) + # Check that the scalar behaves the same as the python int: + assert comp(10, other_val) == comp(val, other_val) + assert comp(val, other_val) == comp(10, other_val) + # Except for the result type: + assert type(comp(val, other_val)) is np.bool + + # Check that the integer array and object array behave the same: + val_obj = np.array([10, 10], dtype=object) + val = val_obj.astype(sctype) + assert_array_equal(comp(val_obj, other_val), comp(val, other_val)) + assert_array_equal(comp(other_val, val_obj), comp(other_val, val)) + + +@pytest.mark.parametrize("arr", [ + np.ones((100, 100), dtype=np.uint8)[::2], # not trivially iterable + np.ones(20000, dtype=">u4"), # cast and >buffersize + np.ones(100, dtype=">u4"), # fast path compatible with cast +]) +def test_integer_comparison_with_cast(arr): + # Similar to above, but mainly test a few cases that cover the slow path + # the test is limited to unsigned ints and -1 for simplicity. + res = arr >= -1 + assert_array_equal(res, np.ones_like(arr, dtype=bool)) + res = arr < -1 + assert_array_equal(res, np.zeros_like(arr, dtype=bool)) + + +@pytest.mark.parametrize("comp", + [np.equal, np.not_equal, np.less_equal, np.less, + np.greater_equal, np.greater]) +def test_integer_integer_comparison(comp): + # Test that the NumPy comparison ufuncs work with large Python integers + assert comp(2**200, -2**200) == comp(2**200, -2**200, dtype=object) + + +def create_with_scalar(sctype, value): + return sctype(value) + + +def create_with_array(sctype, value): + return np.array([value], dtype=sctype) + + +@pytest.mark.parametrize("sctype", + [np.int8, np.int16, np.int32, np.int64, + np.uint8, np.uint16, np.uint32, np.uint64]) +@pytest.mark.parametrize("create", [create_with_scalar, create_with_array]) +def test_oob_creation(sctype, create): + iinfo = np.iinfo(sctype) + + with pytest.raises(OverflowError): + create(sctype, iinfo.min - 1) + + with pytest.raises(OverflowError): + create(sctype, iinfo.max + 1) + + with pytest.raises(OverflowError): + create(sctype, str(iinfo.min - 1)) + + with pytest.raises(OverflowError): + create(sctype, str(iinfo.max + 1)) + + assert create(sctype, iinfo.min) == iinfo.min + assert create(sctype, iinfo.max) == iinfo.max diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_numeric.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_numeric.py new file mode 100644 index 0000000000000000000000000000000000000000..1047f4ce28d3aea8243ef32d005a71335217963b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_numeric.py @@ -0,0 +1,4301 @@ +import inspect +import itertools +import math +import platform +import sys +import warnings +from decimal import Decimal + +import pytest +from hypothesis import given, strategies as st +from hypothesis.extra import numpy as hynp + +import numpy as np +from numpy import ma +from numpy._core import sctypes +from numpy._core._rational_tests import rational +from numpy._core.numerictypes import obj2sctype +from numpy.exceptions import AxisError +from numpy.random import rand, randint, randn +from numpy.testing import ( + HAS_REFCOUNT, + IS_PYPY, + IS_WASM, + assert_, + assert_almost_equal, + assert_array_almost_equal, + assert_array_equal, + assert_array_max_ulp, + assert_equal, + assert_raises, + assert_raises_regex, +) + + +class TestResize: + def test_copies(self): + A = np.array([[1, 2], [3, 4]]) + Ar1 = np.array([[1, 2, 3, 4], [1, 2, 3, 4]]) + assert_equal(np.resize(A, (2, 4)), Ar1) + + Ar2 = np.array([[1, 2], [3, 4], [1, 2], [3, 4]]) + assert_equal(np.resize(A, (4, 2)), Ar2) + + Ar3 = np.array([[1, 2, 3], [4, 1, 2], [3, 4, 1], [2, 3, 4]]) + assert_equal(np.resize(A, (4, 3)), Ar3) + + def test_repeats(self): + A = np.array([1, 2, 3]) + Ar1 = np.array([[1, 2, 3, 1], [2, 3, 1, 2]]) + assert_equal(np.resize(A, (2, 4)), Ar1) + + Ar2 = np.array([[1, 2], [3, 1], [2, 3], [1, 2]]) + assert_equal(np.resize(A, (4, 2)), Ar2) + + Ar3 = np.array([[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]]) + assert_equal(np.resize(A, (4, 3)), Ar3) + + def test_zeroresize(self): + A = np.array([[1, 2], [3, 4]]) + Ar = np.resize(A, (0,)) + assert_array_equal(Ar, np.array([])) + assert_equal(A.dtype, Ar.dtype) + + Ar = np.resize(A, (0, 2)) + assert_equal(Ar.shape, (0, 2)) + + Ar = np.resize(A, (2, 0)) + assert_equal(Ar.shape, (2, 0)) + + def test_reshape_from_zero(self): + # See also gh-6740 + A = np.zeros(0, dtype=[('a', np.float32)]) + Ar = np.resize(A, (2, 1)) + assert_array_equal(Ar, np.zeros((2, 1), Ar.dtype)) + assert_equal(A.dtype, Ar.dtype) + + def test_negative_resize(self): + A = np.arange(0, 10, dtype=np.float32) + new_shape = (-10, -1) + with pytest.raises(ValueError, match=r"negative"): + np.resize(A, new_shape=new_shape) + + def test_unsigned_resize(self): + # ensure unsigned integer sizes don't lead to underflows + for dt_pair in [(np.int32, np.uint32), (np.int64, np.uint64)]: + arr = np.array([[23, 95], [66, 37]]) + assert_array_equal(np.resize(arr, dt_pair[0](1)), + np.resize(arr, dt_pair[1](1))) + + def test_subclass(self): + class MyArray(np.ndarray): + __array_priority__ = 1. + + my_arr = np.array([1]).view(MyArray) + assert type(np.resize(my_arr, 5)) is MyArray + assert type(np.resize(my_arr, 0)) is MyArray + + my_arr = np.array([]).view(MyArray) + assert type(np.resize(my_arr, 5)) is MyArray + + +class TestNonarrayArgs: + # check that non-array arguments to functions wrap them in arrays + def test_choose(self): + choices = [[0, 1, 2], + [3, 4, 5], + [5, 6, 7]] + tgt = [5, 1, 5] + a = [2, 0, 1] + + out = np.choose(a, choices) + assert_equal(out, tgt) + + def test_clip(self): + arr = [-1, 5, 2, 3, 10, -4, -9] + out = np.clip(arr, 2, 7) + tgt = [2, 5, 2, 3, 7, 2, 2] + assert_equal(out, tgt) + + def test_compress(self): + arr = [[0, 1, 2, 3, 4], + [5, 6, 7, 8, 9]] + tgt = [[5, 6, 7, 8, 9]] + out = np.compress([0, 1], arr, axis=0) + assert_equal(out, tgt) + + def test_count_nonzero(self): + arr = [[0, 1, 7, 0, 0], + [3, 0, 0, 2, 19]] + tgt = np.array([2, 3]) + out = np.count_nonzero(arr, axis=1) + assert_equal(out, tgt) + + def test_diagonal(self): + a = [[0, 1, 2, 3], + [4, 5, 6, 7], + [8, 9, 10, 11]] + out = np.diagonal(a) + tgt = [0, 5, 10] + + assert_equal(out, tgt) + + def test_mean(self): + A = [[1, 2, 3], [4, 5, 6]] + assert_(np.mean(A) == 3.5) + assert_(np.all(np.mean(A, 0) == np.array([2.5, 3.5, 4.5]))) + assert_(np.all(np.mean(A, 1) == np.array([2., 5.]))) + + with warnings.catch_warnings(record=True) as w: + warnings.filterwarnings('always', '', RuntimeWarning) + assert_(np.isnan(np.mean([]))) + assert_(w[0].category is RuntimeWarning) + + def test_ptp(self): + a = [3, 4, 5, 10, -3, -5, 6.0] + assert_equal(np.ptp(a, axis=0), 15.0) + + def test_prod(self): + arr = [[1, 2, 3, 4], + [5, 6, 7, 9], + [10, 3, 4, 5]] + tgt = [24, 1890, 600] + + assert_equal(np.prod(arr, axis=-1), tgt) + + def test_ravel(self): + a = [[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]] + tgt = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] + assert_equal(np.ravel(a), tgt) + + def test_repeat(self): + a = [1, 2, 3] + tgt = [1, 1, 2, 2, 3, 3] + + out = np.repeat(a, 2) + assert_equal(out, tgt) + + def test_reshape(self): + arr = [[1, 2, 3], [4, 5, 6], [7, 8, 9], [10, 11, 12]] + tgt = [[1, 2, 3, 4, 5, 6], [7, 8, 9, 10, 11, 12]] + assert_equal(np.reshape(arr, (2, 6)), tgt) + + def test_reshape_shape_arg(self): + arr = np.arange(12) + shape = (3, 4) + expected = arr.reshape(shape) + + with pytest.raises( + TypeError, + match=r"reshape\(\) missing 1 required positional " + "argument: 'shape'" + ): + np.reshape(arr) + + assert_equal(np.reshape(arr, shape), expected) + assert_equal(np.reshape(arr, shape, order="C"), expected) + assert_equal(np.reshape(arr, shape, "C"), expected) + assert_equal(np.reshape(arr, shape=shape), expected) + assert_equal(np.reshape(arr, shape=shape, order="C"), expected) + + def test_reshape_copy_arg(self): + arr = np.arange(24).reshape(2, 3, 4) + arr_f_ord = np.array(arr, order="F") + shape = (12, 2) + + assert np.shares_memory(np.reshape(arr, shape), arr) + assert np.shares_memory(np.reshape(arr, shape, order="C"), arr) + assert np.shares_memory( + np.reshape(arr_f_ord, shape, order="F"), arr_f_ord) + assert np.shares_memory(np.reshape(arr, shape, copy=None), arr) + assert np.shares_memory(np.reshape(arr, shape, copy=False), arr) + assert np.shares_memory(arr.reshape(shape, copy=False), arr) + assert not np.shares_memory(np.reshape(arr, shape, copy=True), arr) + assert not np.shares_memory( + np.reshape(arr, shape, order="C", copy=True), arr) + assert not np.shares_memory( + np.reshape(arr, shape, order="F", copy=True), arr) + assert not np.shares_memory( + np.reshape(arr, shape, order="F", copy=None), arr) + + err_msg = "Unable to avoid creating a copy while reshaping." + with pytest.raises(ValueError, match=err_msg): + np.reshape(arr, shape, order="F", copy=False) + with pytest.raises(ValueError, match=err_msg): + np.reshape(arr_f_ord, shape, order="C", copy=False) + + def test_round(self): + arr = [1.56, 72.54, 6.35, 3.25] + tgt = [1.6, 72.5, 6.4, 3.2] + assert_equal(np.around(arr, decimals=1), tgt) + s = np.float64(1.) + assert_(isinstance(s.round(), np.float64)) + assert_equal(s.round(), 1.) + + @pytest.mark.parametrize('dtype', [ + np.int8, np.int16, np.int32, np.int64, + np.uint8, np.uint16, np.uint32, np.uint64, + np.float16, np.float32, np.float64, + ]) + def test_dunder_round(self, dtype): + s = dtype(1) + assert_(isinstance(round(s), int)) + assert_(isinstance(round(s, None), int)) + assert_(isinstance(round(s, ndigits=None), int)) + assert_equal(round(s), 1) + assert_equal(round(s, None), 1) + assert_equal(round(s, ndigits=None), 1) + + @pytest.mark.parametrize('val, ndigits', [ + pytest.param(2**31 - 1, -1, + marks=pytest.mark.skip(reason="Out of range of int32") + ), + (2**31 - 1, 1 - math.ceil(math.log10(2**31 - 1))), + (2**31 - 1, -math.ceil(math.log10(2**31 - 1))) + ]) + def test_dunder_round_edgecases(self, val, ndigits): + assert_equal(round(val, ndigits), round(np.int32(val), ndigits)) + + def test_dunder_round_accuracy(self): + f = np.float64(5.1 * 10**73) + assert_(isinstance(round(f, -73), np.float64)) + assert_array_max_ulp(round(f, -73), 5.0 * 10**73) + assert_(isinstance(round(f, ndigits=-73), np.float64)) + assert_array_max_ulp(round(f, ndigits=-73), 5.0 * 10**73) + + i = np.int64(501) + assert_(isinstance(round(i, -2), np.int64)) + assert_array_max_ulp(round(i, -2), 500) + assert_(isinstance(round(i, ndigits=-2), np.int64)) + assert_array_max_ulp(round(i, ndigits=-2), 500) + + @pytest.mark.xfail(raises=AssertionError, reason="gh-15896") + def test_round_py_consistency(self): + f = 5.1 * 10**73 + assert_equal(round(np.float64(f), -73), round(f, -73)) + + def test_searchsorted(self): + arr = [-8, -5, -1, 3, 6, 10] + out = np.searchsorted(arr, 0) + assert_equal(out, 3) + + def test_size(self): + A = [[1, 2, 3], [4, 5, 6]] + assert_(np.size(A) == 6) + assert_(np.size(A, 0) == 2) + assert_(np.size(A, 1) == 3) + assert_(np.size(A, ()) == 1) + assert_(np.size(A, (0,)) == 2) + assert_(np.size(A, (1,)) == 3) + assert_(np.size(A, (0, 1)) == 6) + + def test_squeeze(self): + A = [[[1, 1, 1], [2, 2, 2], [3, 3, 3]]] + assert_equal(np.squeeze(A).shape, (3, 3)) + assert_equal(np.squeeze(np.zeros((1, 3, 1))).shape, (3,)) + assert_equal(np.squeeze(np.zeros((1, 3, 1)), axis=0).shape, (3, 1)) + assert_equal(np.squeeze(np.zeros((1, 3, 1)), axis=-1).shape, (1, 3)) + assert_equal(np.squeeze(np.zeros((1, 3, 1)), axis=2).shape, (1, 3)) + assert_equal(np.squeeze([np.zeros((3, 1))]).shape, (3,)) + assert_equal(np.squeeze([np.zeros((3, 1))], axis=0).shape, (3, 1)) + assert_equal(np.squeeze([np.zeros((3, 1))], axis=2).shape, (1, 3)) + assert_equal(np.squeeze([np.zeros((3, 1))], axis=-1).shape, (1, 3)) + + def test_std(self): + A = [[1, 2, 3], [4, 5, 6]] + assert_almost_equal(np.std(A), 1.707825127659933) + assert_almost_equal(np.std(A, 0), np.array([1.5, 1.5, 1.5])) + assert_almost_equal(np.std(A, 1), np.array([0.81649658, 0.81649658])) + + with warnings.catch_warnings(record=True) as w: + warnings.filterwarnings('always', '', RuntimeWarning) + assert_(np.isnan(np.std([]))) + assert_(w[0].category is RuntimeWarning) + + def test_swapaxes(self): + tgt = [[[0, 4], [2, 6]], [[1, 5], [3, 7]]] + a = [[[0, 1], [2, 3]], [[4, 5], [6, 7]]] + out = np.swapaxes(a, 0, 2) + assert_equal(out, tgt) + + def test_sum(self): + m = [[1, 2, 3], + [4, 5, 6], + [7, 8, 9]] + tgt = [[6], [15], [24]] + out = np.sum(m, axis=1, keepdims=True) + + assert_equal(tgt, out) + + def test_take(self): + tgt = [2, 3, 5] + indices = [1, 2, 4] + a = [1, 2, 3, 4, 5] + + out = np.take(a, indices) + assert_equal(out, tgt) + + pairs = [ + (np.int32, np.int32), (np.int32, np.int64), + (np.int64, np.int32), (np.int64, np.int64) + ] + for array_type, indices_type in pairs: + x = np.array([1, 2, 3, 4, 5], dtype=array_type) + ind = np.array([0, 2, 2, 3], dtype=indices_type) + tgt = np.array([1, 3, 3, 4], dtype=array_type) + out = np.take(x, ind) + assert_equal(out, tgt) + assert_equal(out.dtype, tgt.dtype) + + def test_trace(self): + c = [[1, 2], [3, 4], [5, 6]] + assert_equal(np.trace(c), 5) + + def test_transpose(self): + arr = [[1, 2], [3, 4], [5, 6]] + tgt = [[1, 3, 5], [2, 4, 6]] + assert_equal(np.transpose(arr, (1, 0)), tgt) + assert_equal(np.transpose(arr, (-1, -2)), tgt) + assert_equal(np.matrix_transpose(arr), tgt) + + def test_var(self): + A = [[1, 2, 3], [4, 5, 6]] + assert_almost_equal(np.var(A), 2.9166666666666665) + assert_almost_equal(np.var(A, 0), np.array([2.25, 2.25, 2.25])) + assert_almost_equal(np.var(A, 1), np.array([0.66666667, 0.66666667])) + + with warnings.catch_warnings(record=True) as w: + warnings.filterwarnings('always', '', RuntimeWarning) + assert_(np.isnan(np.var([]))) + assert_(w[0].category is RuntimeWarning) + + B = np.array([None, 0]) + B[0] = 1j + assert_almost_equal(np.var(B), 0.25) + + def test_std_with_mean_keyword(self): + # Setting the seed to make the test reproducible + rng = np.random.RandomState(1234) + A = rng.randn(10, 20, 5) + 0.5 + + mean_out = np.zeros((10, 1, 5)) + std_out = np.zeros((10, 1, 5)) + + mean = np.mean(A, + out=mean_out, + axis=1, + keepdims=True) + + # The returned object should be the object specified during calling + assert mean_out is mean + + std = np.std(A, + out=std_out, + axis=1, + keepdims=True, + mean=mean) + + # The returned object should be the object specified during calling + assert std_out is std + + # Shape of returned mean and std should be same + assert std.shape == mean.shape + assert std.shape == (10, 1, 5) + + # Output should be the same as from the individual algorithms + std_old = np.std(A, axis=1, keepdims=True) + + assert std_old.shape == mean.shape + assert_almost_equal(std, std_old) + + def test_var_with_mean_keyword(self): + # Setting the seed to make the test reproducible + rng = np.random.RandomState(1234) + A = rng.randn(10, 20, 5) + 0.5 + + mean_out = np.zeros((10, 1, 5)) + var_out = np.zeros((10, 1, 5)) + + mean = np.mean(A, + out=mean_out, + axis=1, + keepdims=True) + + # The returned object should be the object specified during calling + assert mean_out is mean + + var = np.var(A, + out=var_out, + axis=1, + keepdims=True, + mean=mean) + + # The returned object should be the object specified during calling + assert var_out is var + + # Shape of returned mean and var should be same + assert var.shape == mean.shape + assert var.shape == (10, 1, 5) + + # Output should be the same as from the individual algorithms + var_old = np.var(A, axis=1, keepdims=True) + + assert var_old.shape == mean.shape + assert_almost_equal(var, var_old) + + def test_std_with_mean_keyword_keepdims_false(self): + rng = np.random.RandomState(1234) + A = rng.randn(10, 20, 5) + 0.5 + + mean = np.mean(A, + axis=1, + keepdims=True) + + std = np.std(A, + axis=1, + keepdims=False, + mean=mean) + + # Shape of returned mean and std should be same + assert std.shape == (10, 5) + + # Output should be the same as from the individual algorithms + std_old = np.std(A, axis=1, keepdims=False) + mean_old = np.mean(A, axis=1, keepdims=False) + + assert std_old.shape == mean_old.shape + assert_equal(std, std_old) + + def test_var_with_mean_keyword_keepdims_false(self): + rng = np.random.RandomState(1234) + A = rng.randn(10, 20, 5) + 0.5 + + mean = np.mean(A, + axis=1, + keepdims=True) + + var = np.var(A, + axis=1, + keepdims=False, + mean=mean) + + # Shape of returned mean and var should be same + assert var.shape == (10, 5) + + # Output should be the same as from the individual algorithms + var_old = np.var(A, axis=1, keepdims=False) + mean_old = np.mean(A, axis=1, keepdims=False) + + assert var_old.shape == mean_old.shape + assert_equal(var, var_old) + + def test_std_with_mean_keyword_where_nontrivial(self): + rng = np.random.RandomState(1234) + A = rng.randn(10, 20, 5) + 0.5 + + where = A > 0.5 + + mean = np.mean(A, + axis=1, + keepdims=True, + where=where) + + std = np.std(A, + axis=1, + keepdims=False, + mean=mean, + where=where) + + # Shape of returned mean and std should be same + assert std.shape == (10, 5) + + # Output should be the same as from the individual algorithms + std_old = np.std(A, axis=1, where=where) + mean_old = np.mean(A, axis=1, where=where) + + assert std_old.shape == mean_old.shape + assert_equal(std, std_old) + + def test_var_with_mean_keyword_where_nontrivial(self): + rng = np.random.RandomState(1234) + A = rng.randn(10, 20, 5) + 0.5 + + where = A > 0.5 + + mean = np.mean(A, + axis=1, + keepdims=True, + where=where) + + var = np.var(A, + axis=1, + keepdims=False, + mean=mean, + where=where) + + # Shape of returned mean and var should be same + assert var.shape == (10, 5) + + # Output should be the same as from the individual algorithms + var_old = np.var(A, axis=1, where=where) + mean_old = np.mean(A, axis=1, where=where) + + assert var_old.shape == mean_old.shape + assert_equal(var, var_old) + + def test_std_with_mean_keyword_multiple_axis(self): + # Setting the seed to make the test reproducible + rng = np.random.RandomState(1234) + A = rng.randn(10, 20, 5) + 0.5 + + axis = (0, 2) + + mean = np.mean(A, + out=None, + axis=axis, + keepdims=True) + + std = np.std(A, + out=None, + axis=axis, + keepdims=False, + mean=mean) + + # Shape of returned mean and std should be same + assert std.shape == (20,) + + # Output should be the same as from the individual algorithms + std_old = np.std(A, axis=axis, keepdims=False) + + assert_almost_equal(std, std_old) + + def test_std_with_mean_keyword_axis_None(self): + # Setting the seed to make the test reproducible + rng = np.random.RandomState(1234) + A = rng.randn(10, 20, 5) + 0.5 + + axis = None + + mean = np.mean(A, + out=None, + axis=axis, + keepdims=True) + + std = np.std(A, + out=None, + axis=axis, + keepdims=False, + mean=mean) + + # Shape of returned mean and std should be same + assert std.shape == () + + # Output should be the same as from the individual algorithms + std_old = np.std(A, axis=axis, keepdims=False) + + assert_almost_equal(std, std_old) + + def test_std_with_mean_keyword_keepdims_true_masked(self): + + A = ma.array([[2., 3., 4., 5.], + [1., 2., 3., 4.]], + mask=[[True, False, True, False], + [True, False, True, False]]) + + B = ma.array([[100., 3., 104., 5.], + [101., 2., 103., 4.]], + mask=[[True, False, True, False], + [True, False, True, False]]) + + mean_out = ma.array([[0., 0., 0., 0.]], + mask=[[False, False, False, False]]) + std_out = ma.array([[0., 0., 0., 0.]], + mask=[[False, False, False, False]]) + + axis = 0 + + mean = np.mean(A, out=mean_out, + axis=axis, keepdims=True) + + std = np.std(A, out=std_out, + axis=axis, keepdims=True, + mean=mean) + + # Shape of returned mean and std should be same + assert std.shape == mean.shape + assert std.shape == (1, 4) + + # Output should be the same as from the individual algorithms + std_old = np.std(A, axis=axis, keepdims=True) + mean_old = np.mean(A, axis=axis, keepdims=True) + + assert std_old.shape == mean_old.shape + assert_almost_equal(std, std_old) + assert_almost_equal(mean, mean_old) + + assert mean_out is mean + assert std_out is std + + # masked elements should be ignored + mean_b = np.mean(B, axis=axis, keepdims=True) + std_b = np.std(B, axis=axis, keepdims=True, mean=mean_b) + assert_almost_equal(std, std_b) + assert_almost_equal(mean, mean_b) + + def test_var_with_mean_keyword_keepdims_true_masked(self): + + A = ma.array([[2., 3., 4., 5.], + [1., 2., 3., 4.]], + mask=[[True, False, True, False], + [True, False, True, False]]) + + B = ma.array([[100., 3., 104., 5.], + [101., 2., 103., 4.]], + mask=[[True, False, True, False], + [True, False, True, False]]) + + mean_out = ma.array([[0., 0., 0., 0.]], + mask=[[False, False, False, False]]) + var_out = ma.array([[0., 0., 0., 0.]], + mask=[[False, False, False, False]]) + + axis = 0 + + mean = np.mean(A, out=mean_out, + axis=axis, keepdims=True) + + var = np.var(A, out=var_out, + axis=axis, keepdims=True, + mean=mean) + + # Shape of returned mean and var should be same + assert var.shape == mean.shape + assert var.shape == (1, 4) + + # Output should be the same as from the individual algorithms + var_old = np.var(A, axis=axis, keepdims=True) + mean_old = np.mean(A, axis=axis, keepdims=True) + + assert var_old.shape == mean_old.shape + assert_almost_equal(var, var_old) + assert_almost_equal(mean, mean_old) + + assert mean_out is mean + assert var_out is var + + # masked elements should be ignored + mean_b = np.mean(B, axis=axis, keepdims=True) + var_b = np.var(B, axis=axis, keepdims=True, mean=mean_b) + assert_almost_equal(var, var_b) + assert_almost_equal(mean, mean_b) + + +class TestIsscalar: + def test_isscalar(self): + assert_(np.isscalar(3.1)) + assert_(np.isscalar(np.int16(12345))) + assert_(np.isscalar(False)) + assert_(np.isscalar('numpy')) + assert_(not np.isscalar([3.1])) + assert_(not np.isscalar(None)) + + # PEP 3141 + from fractions import Fraction + assert_(np.isscalar(Fraction(5, 17))) + from numbers import Number + assert_(np.isscalar(Number())) + + +class TestBoolScalar: + def test_logical(self): + f = np.False_ + t = np.True_ + s = "xyz" + assert_((t and s) is s) + assert_((f and s) is f) + + def test_bitwise_or(self): + f = np.False_ + t = np.True_ + assert_((t | t) is t) + assert_((f | t) is t) + assert_((t | f) is t) + assert_((f | f) is f) + + def test_bitwise_and(self): + f = np.False_ + t = np.True_ + assert_((t & t) is t) + assert_((f & t) is f) + assert_((t & f) is f) + assert_((f & f) is f) + + def test_bitwise_xor(self): + f = np.False_ + t = np.True_ + assert_((t ^ t) is f) + assert_((f ^ t) is t) + assert_((t ^ f) is t) + assert_((f ^ f) is f) + + +class TestBoolArray: + def _create_bool_arrays(self): + # offset for simd tests + t = np.array([True] * 41, dtype=bool)[1::] + f = np.array([False] * 41, dtype=bool)[1::] + o = np.array([False] * 42, dtype=bool)[2::] + nm = f.copy() + im = t.copy() + nm[3] = True + nm[-2] = True + im[3] = False + im[-2] = False + return t, f, o, nm, im + + def test_all_any(self): + t, f, _, nm, im = self._create_bool_arrays() + assert_(t.all()) + assert_(t.any()) + assert_(not f.all()) + assert_(not f.any()) + assert_(nm.any()) + assert_(im.any()) + assert_(not nm.all()) + assert_(not im.all()) + # check bad element in all positions + for i in range(256 - 7): + d = np.array([False] * 256, dtype=bool)[7::] + d[i] = True + assert_(np.any(d)) + e = np.array([True] * 256, dtype=bool)[7::] + e[i] = False + assert_(not np.all(e)) + assert_array_equal(e, ~d) + # big array test for blocked libc loops + for i in list(range(9, 6000, 507)) + [7764, 90021, -10]: + d = np.array([False] * 100043, dtype=bool) + d[i] = True + assert_(np.any(d), msg=f"{i!r}") + e = np.array([True] * 100043, dtype=bool) + e[i] = False + assert_(not np.all(e), msg=f"{i!r}") + + def test_logical_not_abs(self): + t, f, o, nm, im = self._create_bool_arrays() + assert_array_equal(~t, f) + assert_array_equal(np.abs(~t), f) + assert_array_equal(np.abs(~f), t) + assert_array_equal(np.abs(f), f) + assert_array_equal(~np.abs(f), t) + assert_array_equal(~np.abs(t), f) + assert_array_equal(np.abs(~nm), im) + np.logical_not(t, out=o) + assert_array_equal(o, f) + np.abs(t, out=o) + assert_array_equal(o, t) + + def test_logical_and_or_xor(self): + t, f, o, nm, im = self._create_bool_arrays() + assert_array_equal(t | t, t) + assert_array_equal(f | f, f) + assert_array_equal(t | f, t) + assert_array_equal(f | t, t) + np.logical_or(t, t, out=o) + assert_array_equal(o, t) + assert_array_equal(t & t, t) + assert_array_equal(f & f, f) + assert_array_equal(t & f, f) + assert_array_equal(f & t, f) + np.logical_and(t, t, out=o) + assert_array_equal(o, t) + assert_array_equal(t ^ t, f) + assert_array_equal(f ^ f, f) + assert_array_equal(t ^ f, t) + assert_array_equal(f ^ t, t) + np.logical_xor(t, t, out=o) + assert_array_equal(o, f) + + assert_array_equal(nm & t, nm) + assert_array_equal(im & f, False) + assert_array_equal(nm & True, nm) + assert_array_equal(im & False, f) + assert_array_equal(nm | t, t) + assert_array_equal(im | f, im) + assert_array_equal(nm | True, t) + assert_array_equal(im | False, im) + assert_array_equal(nm ^ t, im) + assert_array_equal(im ^ f, im) + assert_array_equal(nm ^ True, im) + assert_array_equal(im ^ False, im) + + +class TestBoolCmp: + def _create_data(self, dtype, size): + # generate data using given dtype and num for size of array + a = np.ones(size, dtype=dtype) + e = np.ones(a.size, dtype=bool) + # generate values for all permutation of 256bit simd vectors + s = 0 + r = int(size / 32) + for i in range(int(size / 8)): + a[s:s + r] = [i & 2**x for x in range(r)] + e[s:s + r] = [(i & 2**x) != 0 for x in range(r)] + s += r + n = a.copy() + n[e] = np.nan + + inf = a.copy() + inf[::3][e[::3]] = np.inf + inf[1::3][e[1::3]] = -np.inf + inf[2::3][e[2::3]] = np.nan + enonan = e.copy() + enonan[2::3] = False + + sign = a.copy() + sign[e] *= -1. + sign[1::6][e[1::6]] = -np.inf + # On RISC-V, many operations that produce NaNs, such as converting + # a -NaN from f64 to f32, return a canonical NaN. The canonical + # NaNs are always positive. See section 11.3 NaN Generation and + # Propagation of the RISC-V Unprivileged ISA for more details. + # We disable the float32 sign test on riscv64 for -np.nan as the sign + # of the NaN will be lost when it's converted to a float32. + if not (dtype == np.float32 and platform.machine() == 'riscv64'): + sign[3::6][e[3::6]] = -np.nan + sign[4::6][e[4::6]] = -0. + return a, e, n, inf, enonan, sign + + def test_float(self): + # offset for alignment test + f, ef, nf, inff, efnonan, signf = self._create_data(np.float32, 256) + for i in range(4): + assert_array_equal(f[i:] > 0, ef[i:]) + assert_array_equal(f[i:] - 1 >= 0, ef[i:]) + assert_array_equal(f[i:] == 0, ~ef[i:]) + assert_array_equal(-f[i:] < 0, ef[i:]) + assert_array_equal(-f[i:] + 1 <= 0, ef[i:]) + r = f[i:] != 0 + assert_array_equal(r, ef[i:]) + r2 = f[i:] != np.zeros_like(f[i:]) + r3 = 0 != f[i:] + assert_array_equal(r, r2) + assert_array_equal(r, r3) + # check bool == 0x1 + assert_array_equal(r.view(np.int8), r.astype(np.int8)) + assert_array_equal(r2.view(np.int8), r2.astype(np.int8)) + assert_array_equal(r3.view(np.int8), r3.astype(np.int8)) + + # isnan on amd64 takes the same code path + assert_array_equal(np.isnan(nf[i:]), ef[i:]) + assert_array_equal(np.isfinite(nf[i:]), ~ef[i:]) + assert_array_equal(np.isfinite(inff[i:]), ~ef[i:]) + assert_array_equal(np.isinf(inff[i:]), efnonan[i:]) + assert_array_equal(np.signbit(signf[i:]), ef[i:]) + + def test_double(self): + # offset for alignment test + d, ed, nd, infd, ednonan, signd = self._create_data(np.float64, 128) + for i in range(2): + assert_array_equal(d[i:] > 0, ed[i:]) + assert_array_equal(d[i:] - 1 >= 0, ed[i:]) + assert_array_equal(d[i:] == 0, ~ed[i:]) + assert_array_equal(-d[i:] < 0, ed[i:]) + assert_array_equal(-d[i:] + 1 <= 0, ed[i:]) + r = d[i:] != 0 + assert_array_equal(r, ed[i:]) + r2 = d[i:] != np.zeros_like(d[i:]) + r3 = 0 != d[i:] + assert_array_equal(r, r2) + assert_array_equal(r, r3) + # check bool == 0x1 + assert_array_equal(r.view(np.int8), r.astype(np.int8)) + assert_array_equal(r2.view(np.int8), r2.astype(np.int8)) + assert_array_equal(r3.view(np.int8), r3.astype(np.int8)) + + # isnan on amd64 takes the same code path + assert_array_equal(np.isnan(nd[i:]), ed[i:]) + assert_array_equal(np.isfinite(nd[i:]), ~ed[i:]) + assert_array_equal(np.isfinite(infd[i:]), ~ed[i:]) + assert_array_equal(np.isinf(infd[i:]), ednonan[i:]) + assert_array_equal(np.signbit(signd[i:]), ed[i:]) + + +class TestSeterr: + def test_default(self): + err = np.geterr() + assert_equal(err, + {'divide': 'warn', + 'invalid': 'warn', + 'over': 'warn', + 'under': 'ignore'} + ) + + def test_set(self): + with np.errstate(): + err = np.seterr() + old = np.seterr(divide='print') + assert_(err == old) + new = np.seterr() + assert_(new['divide'] == 'print') + np.seterr(over='raise') + assert_(np.geterr()['over'] == 'raise') + assert_(new['divide'] == 'print') + np.seterr(**old) + assert_(np.geterr() == old) + + @pytest.mark.skipif(IS_WASM, reason="no wasm fp exception support") + @pytest.mark.skipif(platform.machine() == "armv5tel", reason="See gh-413.") + def test_divide_err(self): + with np.errstate(divide='raise'): + with assert_raises(FloatingPointError): + np.array([1.]) / np.array([0.]) + + np.seterr(divide='ignore') + np.array([1.]) / np.array([0.]) + + +class TestFloatExceptions: + def assert_raises_fpe(self, fpeerr, flop, x, y): + ftype = type(x) + try: + flop(x, y) + assert_(False, + f"Type {ftype} did not raise fpe error '{fpeerr}'.") + except FloatingPointError as exc: + assert_(str(exc).find(fpeerr) >= 0, + f"Type {ftype} raised wrong fpe error '{exc}'.") + + def assert_op_raises_fpe(self, fpeerr, flop, sc1, sc2): + # Check that fpe exception is raised. + # + # Given a floating operation `flop` and two scalar values, check that + # the operation raises the floating point exception specified by + # `fpeerr`. Tests all variants with 0-d array scalars as well. + + self.assert_raises_fpe(fpeerr, flop, sc1, sc2) + self.assert_raises_fpe(fpeerr, flop, sc1[()], sc2) + self.assert_raises_fpe(fpeerr, flop, sc1, sc2[()]) + self.assert_raises_fpe(fpeerr, flop, sc1[()], sc2[()]) + + # Test for all real and complex float types + @pytest.mark.skipif(IS_WASM, reason="no wasm fp exception support") + @pytest.mark.parametrize("typecode", np.typecodes["AllFloat"]) + def test_floating_exceptions(self, typecode): + if 'bsd' in sys.platform and typecode in 'gG': + pytest.skip(reason="Fallback impl for (c)longdouble may not raise " + "FPE errors as expected on BSD OSes, " + "see gh-24876, gh-23379") + + # Test basic arithmetic function errors + with np.errstate(all='raise'): + ftype = obj2sctype(typecode) + if np.dtype(ftype).kind == 'f': + # Get some extreme values for the type + fi = np.finfo(ftype) + ft_tiny = fi.tiny + ft_max = fi.max + ft_eps = fi.eps + underflow = 'underflow' + divbyzero = 'divide by zero' + else: + # 'c', complex, corresponding real dtype + rtype = type(ftype(0).real) + fi = np.finfo(rtype) + ft_tiny = ftype(fi.tiny) + ft_max = ftype(fi.max) + ft_eps = ftype(fi.eps) + # The complex types raise different exceptions + underflow = '' + divbyzero = '' + overflow = 'overflow' + invalid = 'invalid' + + # The value of tiny for double double is NaN, so we need to + # pass the assert + if not np.isnan(ft_tiny): + self.assert_raises_fpe(underflow, + lambda a, b: a / b, ft_tiny, ft_max) + self.assert_raises_fpe(underflow, + lambda a, b: a * b, ft_tiny, ft_tiny) + self.assert_raises_fpe(overflow, + lambda a, b: a * b, ft_max, ftype(2)) + self.assert_raises_fpe(overflow, + lambda a, b: a / b, ft_max, ftype(0.5)) + self.assert_raises_fpe(overflow, + lambda a, b: a + b, ft_max, ft_max * ft_eps) + self.assert_raises_fpe(overflow, + lambda a, b: a - b, -ft_max, ft_max * ft_eps) + # On AIX, pow() with double does not raise the overflow exception, + # it returns inf. Long double is the same as double. + if sys.platform != 'aix' or typecode not in 'dDgG': + self.assert_raises_fpe(overflow, + np.power, ftype(2), ftype(2**fi.nexp)) + self.assert_raises_fpe(divbyzero, + lambda a, b: a / b, ftype(1), ftype(0)) + self.assert_raises_fpe( + invalid, lambda a, b: a / b, ftype(np.inf), ftype(np.inf) + ) + self.assert_raises_fpe(invalid, + lambda a, b: a / b, ftype(0), ftype(0)) + self.assert_raises_fpe( + invalid, lambda a, b: a - b, ftype(np.inf), ftype(np.inf) + ) + self.assert_raises_fpe( + invalid, lambda a, b: a + b, ftype(np.inf), ftype(-np.inf) + ) + self.assert_raises_fpe(invalid, + lambda a, b: a * b, ftype(0), ftype(np.inf)) + + @pytest.mark.skipif(IS_WASM, reason="no wasm fp exception support") + def test_warnings(self): + # test warning code path + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter("always") + with np.errstate(all="warn"): + np.divide(1, 0.) + assert_equal(len(w), 1) + assert_("divide by zero" in str(w[0].message)) + np.array(1e300) * np.array(1e300) + assert_equal(len(w), 2) + assert_("overflow" in str(w[-1].message)) + np.array(np.inf) - np.array(np.inf) + assert_equal(len(w), 3) + assert_("invalid value" in str(w[-1].message)) + np.array(1e-300) * np.array(1e-300) + assert_equal(len(w), 4) + assert_("underflow" in str(w[-1].message)) + + +class TestTypes: + def check_promotion_cases(self, promote_func): + # tests that the scalars get coerced correctly. + b = np.bool(0) + i8, i16, i32, i64 = np.int8(0), np.int16(0), np.int32(0), np.int64(0) + u8, u16, u32, u64 = np.uint8(0), np.uint16(0), np.uint32(0), np.uint64(0) + f32, f64, fld = np.float32(0), np.float64(0), np.longdouble(0) + c64, c128, cld = np.complex64(0), np.complex128(0), np.clongdouble(0) + + # coercion within the same kind + assert_equal(promote_func(i8, i16), np.dtype(np.int16)) + assert_equal(promote_func(i32, i8), np.dtype(np.int32)) + assert_equal(promote_func(i16, i64), np.dtype(np.int64)) + assert_equal(promote_func(u8, u32), np.dtype(np.uint32)) + assert_equal(promote_func(f32, f64), np.dtype(np.float64)) + assert_equal(promote_func(fld, f32), np.dtype(np.longdouble)) + assert_equal(promote_func(f64, fld), np.dtype(np.longdouble)) + assert_equal(promote_func(c128, c64), np.dtype(np.complex128)) + assert_equal(promote_func(cld, c128), np.dtype(np.clongdouble)) + assert_equal(promote_func(c64, fld), np.dtype(np.clongdouble)) + + # coercion between kinds + assert_equal(promote_func(b, i32), np.dtype(np.int32)) + assert_equal(promote_func(b, u8), np.dtype(np.uint8)) + assert_equal(promote_func(i8, u8), np.dtype(np.int16)) + assert_equal(promote_func(u8, i32), np.dtype(np.int32)) + assert_equal(promote_func(i64, u32), np.dtype(np.int64)) + assert_equal(promote_func(u64, i32), np.dtype(np.float64)) + assert_equal(promote_func(i32, f32), np.dtype(np.float64)) + assert_equal(promote_func(i64, f32), np.dtype(np.float64)) + assert_equal(promote_func(f32, i16), np.dtype(np.float32)) + assert_equal(promote_func(f32, u32), np.dtype(np.float64)) + assert_equal(promote_func(f32, c64), np.dtype(np.complex64)) + assert_equal(promote_func(c128, f32), np.dtype(np.complex128)) + assert_equal(promote_func(cld, f64), np.dtype(np.clongdouble)) + + # coercion between scalars and 1-D arrays + assert_equal(promote_func(np.array([b]), i8), np.dtype(np.int8)) + assert_equal(promote_func(np.array([b]), u8), np.dtype(np.uint8)) + assert_equal(promote_func(np.array([b]), i32), np.dtype(np.int32)) + assert_equal(promote_func(np.array([b]), u32), np.dtype(np.uint32)) + assert_equal(promote_func(np.array([i8]), i64), np.dtype(np.int64)) + # unsigned and signed unfortunately tend to promote to float64: + assert_equal(promote_func(u64, np.array([i32])), np.dtype(np.float64)) + assert_equal(promote_func(i64, np.array([u32])), np.dtype(np.int64)) + assert_equal(promote_func(np.array([u16]), i32), np.dtype(np.int32)) + assert_equal(promote_func(np.int32(-1), np.array([u64])), + np.dtype(np.float64)) + assert_equal(promote_func(f64, np.array([f32])), np.dtype(np.float64)) + assert_equal(promote_func(fld, np.array([f32])), + np.dtype(np.longdouble)) + assert_equal(promote_func(np.array([f64]), fld), + np.dtype(np.longdouble)) + assert_equal(promote_func(fld, np.array([c64])), + np.dtype(np.clongdouble)) + assert_equal(promote_func(c64, np.array([f64])), + np.dtype(np.complex128)) + assert_equal(promote_func(np.complex64(3j), np.array([f64])), + np.dtype(np.complex128)) + assert_equal(promote_func(np.array([f32]), c128), + np.dtype(np.complex128)) + + # coercion between scalars and 1-D arrays, where + # the scalar has greater kind than the array + assert_equal(promote_func(np.array([b]), f64), np.dtype(np.float64)) + assert_equal(promote_func(np.array([b]), i64), np.dtype(np.int64)) + assert_equal(promote_func(np.array([b]), u64), np.dtype(np.uint64)) + assert_equal(promote_func(np.array([i8]), f64), np.dtype(np.float64)) + assert_equal(promote_func(np.array([u16]), f64), np.dtype(np.float64)) + + def test_coercion(self): + def res_type(a, b): + return np.add(a, b).dtype + + self.check_promotion_cases(res_type) + + # Use-case: float/complex scalar * bool/int8 array + # shouldn't narrow the float/complex type + for a in [np.array([True, False]), np.array([-3, 12], dtype=np.int8)]: + b = 1.234 * a + assert_equal(b.dtype, np.dtype('f8'), f"array type {a.dtype}") + b = np.longdouble(1.234) * a + assert_equal(b.dtype, np.dtype(np.longdouble), + f"array type {a.dtype}") + b = np.float64(1.234) * a + assert_equal(b.dtype, np.dtype('f8'), f"array type {a.dtype}") + b = np.float32(1.234) * a + assert_equal(b.dtype, np.dtype('f4'), f"array type {a.dtype}") + b = np.float16(1.234) * a + assert_equal(b.dtype, np.dtype('f2'), f"array type {a.dtype}") + + b = 1.234j * a + assert_equal(b.dtype, np.dtype('c16'), f"array type {a.dtype}") + b = np.clongdouble(1.234j) * a + assert_equal(b.dtype, np.dtype(np.clongdouble), + f"array type {a.dtype}") + b = np.complex128(1.234j) * a + assert_equal(b.dtype, np.dtype('c16'), f"array type {a.dtype}") + b = np.complex64(1.234j) * a + assert_equal(b.dtype, np.dtype('c8'), f"array type {a.dtype}") + + # The following use-case is problematic, and to resolve its + # tricky side-effects requires more changes. + # + # Use-case: (1-t)*a, where 't' is a boolean array and 'a' is + # a float32, shouldn't promote to float64 + # + # a = np.array([1.0, 1.5], dtype=np.float32) + # t = np.array([True, False]) + # b = t*a + # assert_equal(b, [1.0, 0.0]) + # assert_equal(b.dtype, np.dtype('f4')) + # b = (1-t)*a + # assert_equal(b, [0.0, 1.5]) + # assert_equal(b.dtype, np.dtype('f4')) + # + # Probably ~t (bitwise negation) is more proper to use here, + # but this is arguably less intuitive to understand at a glance, and + # would fail if 't' is actually an integer array instead of boolean: + # + # b = (~t)*a + # assert_equal(b, [0.0, 1.5]) + # assert_equal(b.dtype, np.dtype('f4')) + + def test_result_type(self): + self.check_promotion_cases(np.result_type) + assert_(np.result_type(None) == np.dtype(None)) + + def test_promote_types_endian(self): + # promote_types should always return native-endian types + assert_equal(np.promote_types('i8', '>i8'), np.dtype('i8')) + + assert_equal(np.promote_types('>i8', '>U16'), np.dtype('U21')) + assert_equal(np.promote_types('U16', '>i8'), np.dtype('U21')) + assert_equal(np.promote_types('S5', '>U8'), np.dtype('U8')) + assert_equal(np.promote_types('U8', '>S5'), np.dtype('U8')) + assert_equal(np.promote_types('U8', '>U5'), np.dtype('U8')) + + assert_equal(np.promote_types('M8', '>M8'), np.dtype('M8')) + assert_equal(np.promote_types('m8', '>m8'), np.dtype('m8')) + + def test_can_cast_and_promote_usertypes(self): + # The rational type defines safe casting for signed integers, + # boolean. Rational itself *does* cast safely to double. + # (rational does not actually cast to all signed integers, e.g. + # int64 can be both long and longlong and it registers only the first) + valid_types = ["int8", "int16", "int32", "int64", "bool"] + invalid_types = "BHILQP" + "FDG" + "mM" + "f" + "V" + + rational_dt = np.dtype(rational) + for numpy_dtype in valid_types: + numpy_dtype = np.dtype(numpy_dtype) + assert np.can_cast(numpy_dtype, rational_dt) + assert np.promote_types(numpy_dtype, rational_dt) is rational_dt + + for numpy_dtype in invalid_types: + numpy_dtype = np.dtype(numpy_dtype) + assert not np.can_cast(numpy_dtype, rational_dt) + with pytest.raises(TypeError): + np.promote_types(numpy_dtype, rational_dt) + + double_dt = np.dtype("double") + assert np.can_cast(rational_dt, double_dt) + assert np.promote_types(double_dt, rational_dt) is double_dt + + @pytest.mark.parametrize("swap", ["", "swap"]) + @pytest.mark.parametrize("string_dtype", ["U", "S"]) + def test_promote_types_strings(self, swap, string_dtype): + if swap == "swap": + promote_types = lambda a, b: np.promote_types(b, a) + else: + promote_types = np.promote_types + + S = string_dtype + + # Promote numeric with unsized string: + assert_equal(promote_types('bool', S), np.dtype(S + '5')) + assert_equal(promote_types('b', S), np.dtype(S + '4')) + assert_equal(promote_types('u1', S), np.dtype(S + '3')) + assert_equal(promote_types('u2', S), np.dtype(S + '5')) + assert_equal(promote_types('u4', S), np.dtype(S + '10')) + assert_equal(promote_types('u8', S), np.dtype(S + '20')) + assert_equal(promote_types('i1', S), np.dtype(S + '4')) + assert_equal(promote_types('i2', S), np.dtype(S + '6')) + assert_equal(promote_types('i4', S), np.dtype(S + '11')) + assert_equal(promote_types('i8', S), np.dtype(S + '21')) + # Promote numeric with sized string: + assert_equal(promote_types('bool', S + '1'), np.dtype(S + '5')) + assert_equal(promote_types('bool', S + '30'), np.dtype(S + '30')) + assert_equal(promote_types('b', S + '1'), np.dtype(S + '4')) + assert_equal(promote_types('b', S + '30'), np.dtype(S + '30')) + assert_equal(promote_types('u1', S + '1'), np.dtype(S + '3')) + assert_equal(promote_types('u1', S + '30'), np.dtype(S + '30')) + assert_equal(promote_types('u2', S + '1'), np.dtype(S + '5')) + assert_equal(promote_types('u2', S + '30'), np.dtype(S + '30')) + assert_equal(promote_types('u4', S + '1'), np.dtype(S + '10')) + assert_equal(promote_types('u4', S + '30'), np.dtype(S + '30')) + assert_equal(promote_types('u8', S + '1'), np.dtype(S + '20')) + assert_equal(promote_types('u8', S + '30'), np.dtype(S + '30')) + # Promote with object: + assert_equal(promote_types('O', S + '30'), np.dtype('O')) + + @pytest.mark.parametrize(["dtype1", "dtype2"], + [[np.dtype("V6"), np.dtype("V10")], # mismatch shape + # Mismatching names: + [np.dtype([("name1", "i8")]), np.dtype([("name2", "i8")])], + ]) + def test_invalid_void_promotion(self, dtype1, dtype2): + with pytest.raises(TypeError): + np.promote_types(dtype1, dtype2) + + @pytest.mark.parametrize(["dtype1", "dtype2"], + [[np.dtype("V10"), np.dtype("V10")], + [np.dtype([("name1", "i8")]), + np.dtype([("name1", np.dtype("i8").newbyteorder())])], + [np.dtype("i8,i8"), np.dtype("i8,>i8")], + [np.dtype("i8,i8"), np.dtype("i4,i4")], + ]) + def test_valid_void_promotion(self, dtype1, dtype2): + assert np.promote_types(dtype1, dtype2) == dtype1 + + @pytest.mark.parametrize("dtype", + list(np.typecodes["All"]) + + ["i,i", "10i", "S3", "S100", "U3", "U100", rational]) + def test_promote_identical_types_metadata(self, dtype): + # The same type passed in twice to promote types always + # preserves metadata + metadata = {1: 1} + dtype = np.dtype(dtype, metadata=metadata) + + res = np.promote_types(dtype, dtype) + assert res.metadata == dtype.metadata + + # byte-swapping preserves and makes the dtype native: + dtype = dtype.newbyteorder() + if dtype.isnative: + # The type does not have byte swapping + return + + res = np.promote_types(dtype, dtype) + + # Metadata is (currently) generally lost on byte-swapping (except for + # unicode. + if dtype.char != "U": + assert res.metadata is None + else: + assert res.metadata == metadata + assert res.isnative + + @pytest.mark.slow + @pytest.mark.filterwarnings('ignore:Promotion of numbers:FutureWarning') + @pytest.mark.parametrize(["dtype1", "dtype2"], + itertools.product( + list(np.typecodes["All"]) + + ["i,i", "S3", "S100", "U3", "U100", rational], + repeat=2)) + def test_promote_types_metadata(self, dtype1, dtype2): + """Metadata handling in promotion does not appear formalized + right now in NumPy. This test should thus be considered to + document behaviour, rather than test the correct definition of it. + + This test is very ugly, it was useful for rewriting part of the + promotion, but probably should eventually be replaced/deleted + (i.e. when metadata handling in promotion is better defined). + """ + metadata1 = {1: 1} + metadata2 = {2: 2} + dtype1 = np.dtype(dtype1, metadata=metadata1) + dtype2 = np.dtype(dtype2, metadata=metadata2) + + try: + res = np.promote_types(dtype1, dtype2) + except TypeError: + # Promotion failed, this test only checks metadata + return + + if res.char not in "USV" or res.names is not None or res.shape != (): + # All except string dtypes (and unstructured void) lose metadata + # on promotion (unless both dtypes are identical). + # At some point structured ones did not, but were restrictive. + assert res.metadata is None + elif res == dtype1: + # If one result is the result, it is usually returned unchanged: + assert res is dtype1 + elif res == dtype2: + # dtype1 may have been cast to the same type/kind as dtype2. + # If the resulting dtype is identical we currently pick the cast + # version of dtype1, which lost the metadata: + if np.promote_types(dtype1, dtype2.kind) == dtype2: + res.metadata is None + else: + res.metadata == metadata2 + else: + assert res.metadata is None + + # Try again for byteswapped version + dtype1 = dtype1.newbyteorder() + assert dtype1.metadata == metadata1 + res_bs = np.promote_types(dtype1, dtype2) + assert res_bs == res + assert res_bs.metadata == res.metadata + + def test_can_cast(self): + assert_(np.can_cast(np.int32, np.int64)) + assert_(np.can_cast(np.float64, complex)) + assert_(not np.can_cast(complex, float)) + + assert_(np.can_cast('i8', 'f8')) + assert_(not np.can_cast('i8', 'f4')) + assert_(np.can_cast('i4', 'S11')) + + assert_(np.can_cast('i8', 'i8', 'no')) + assert_(not np.can_cast('i8', 'no')) + + assert_(np.can_cast('i8', 'equiv')) + assert_(not np.can_cast('i8', 'equiv')) + + assert_(np.can_cast('i8', 'safe')) + assert_(not np.can_cast('i4', 'safe')) + + assert_(np.can_cast('i4', 'same_kind')) + assert_(not np.can_cast('u4', 'same_kind')) + + assert_(np.can_cast('u4', 'unsafe')) + + assert_(np.can_cast('bool', 'S5')) + assert_(not np.can_cast('bool', 'S4')) + + assert_(np.can_cast('b', 'S4')) + assert_(not np.can_cast('b', 'S3')) + + assert_(np.can_cast('u1', 'S3')) + assert_(not np.can_cast('u1', 'S2')) + assert_(np.can_cast('u2', 'S5')) + assert_(not np.can_cast('u2', 'S4')) + assert_(np.can_cast('u4', 'S10')) + assert_(not np.can_cast('u4', 'S9')) + assert_(np.can_cast('u8', 'S20')) + assert_(not np.can_cast('u8', 'S19')) + + assert_(np.can_cast('i1', 'S4')) + assert_(not np.can_cast('i1', 'S3')) + assert_(np.can_cast('i2', 'S6')) + assert_(not np.can_cast('i2', 'S5')) + assert_(np.can_cast('i4', 'S11')) + assert_(not np.can_cast('i4', 'S10')) + assert_(np.can_cast('i8', 'S21')) + assert_(not np.can_cast('i8', 'S20')) + + assert_(np.can_cast('bool', 'S5')) + assert_(not np.can_cast('bool', 'S4')) + + assert_(np.can_cast('b', 'U4')) + assert_(not np.can_cast('b', 'U3')) + + assert_(np.can_cast('u1', 'U3')) + assert_(not np.can_cast('u1', 'U2')) + assert_(np.can_cast('u2', 'U5')) + assert_(not np.can_cast('u2', 'U4')) + assert_(np.can_cast('u4', 'U10')) + assert_(not np.can_cast('u4', 'U9')) + assert_(np.can_cast('u8', 'U20')) + assert_(not np.can_cast('u8', 'U19')) + + assert_(np.can_cast('i1', 'U4')) + assert_(not np.can_cast('i1', 'U3')) + assert_(np.can_cast('i2', 'U6')) + assert_(not np.can_cast('i2', 'U5')) + assert_(np.can_cast('i4', 'U11')) + assert_(not np.can_cast('i4', 'U10')) + assert_(np.can_cast('i8', 'U21')) + assert_(not np.can_cast('i8', 'U20')) + + assert_raises(TypeError, np.can_cast, 'i4', None) + assert_raises(TypeError, np.can_cast, None, 'i4') + + # Also test keyword arguments + assert_(np.can_cast(from_=np.int32, to=np.int64)) + + def test_can_cast_simple_to_structured(self): + # Non-structured can only be cast to structured in 'unsafe' mode. + assert_(not np.can_cast('i4', 'i4,i4')) + assert_(not np.can_cast('i4', 'i4,i2')) + assert_(np.can_cast('i4', 'i4,i4', casting='unsafe')) + assert_(np.can_cast('i4', 'i4,i2', casting='unsafe')) + # Even if there is just a single field which is OK. + assert_(not np.can_cast('i2', [('f1', 'i4')])) + assert_(not np.can_cast('i2', [('f1', 'i4')], casting='same_kind')) + assert_(np.can_cast('i2', [('f1', 'i4')], casting='unsafe')) + # It should be the same for recursive structured or subarrays. + assert_(not np.can_cast('i2', [('f1', 'i4,i4')])) + assert_(np.can_cast('i2', [('f1', 'i4,i4')], casting='unsafe')) + assert_(not np.can_cast('i2', [('f1', '(2,3)i4')])) + assert_(np.can_cast('i2', [('f1', '(2,3)i4')], casting='unsafe')) + + def test_can_cast_structured_to_simple(self): + # Need unsafe casting for structured to simple. + assert_(not np.can_cast([('f1', 'i4')], 'i4')) + assert_(np.can_cast([('f1', 'i4')], 'i4', casting='unsafe')) + assert_(np.can_cast([('f1', 'i4')], 'i2', casting='unsafe')) + # Since it is unclear what is being cast, multiple fields to + # single should not work even for unsafe casting. + assert_(not np.can_cast('i4,i4', 'i4', casting='unsafe')) + # But a single field inside a single field is OK. + assert_(not np.can_cast([('f1', [('x', 'i4')])], 'i4')) + assert_(np.can_cast([('f1', [('x', 'i4')])], 'i4', casting='unsafe')) + # And a subarray is fine too - it will just take the first element + # (arguably not very consistently; might also take the first field). + assert_(not np.can_cast([('f0', '(3,)i4')], 'i4')) + assert_(np.can_cast([('f0', '(3,)i4')], 'i4', casting='unsafe')) + # But a structured subarray with multiple fields should fail. + assert_(not np.can_cast([('f0', ('i4,i4'), (2,))], 'i4', + casting='unsafe')) + + def test_can_cast_values(self): + # With NumPy 2 and NEP 50, can_cast errors on Python scalars. We could + # define this as (usually safe) at some point, and already do so + # in `copyto` and ufuncs (but there an error is raised if the integer + # is out of bounds and a warning for out-of-bound floats). + # Raises even for unsafe, previously checked within range (for floats + # that was approximately whether it would overflow to inf). + with pytest.raises(TypeError): + np.can_cast(4, "int8", casting="unsafe") + + with pytest.raises(TypeError): + np.can_cast(4.0, "float64", casting="unsafe") + + with pytest.raises(TypeError): + np.can_cast(4j, "complex128", casting="unsafe") + + @pytest.mark.parametrize("dtype", + list("?bhilqBHILQefdgFDG") + [rational]) + def test_can_cast_scalars(self, dtype): + # Basic test to ensure that scalars are supported in can-cast + # (does not check behavior exhaustively). + dtype = np.dtype(dtype) + scalar = dtype.type(0) + + assert np.can_cast(scalar, "int64") == np.can_cast(dtype, "int64") + assert np.can_cast(scalar, "float32", casting="unsafe") + + +# Custom exception class to test exception propagation in fromiter +class NIterError(Exception): + pass + + +class TestFromiter: + def makegen(self): + return (x**2 for x in range(24)) + + def test_types(self): + ai32 = np.fromiter(self.makegen(), np.int32) + ai64 = np.fromiter(self.makegen(), np.int64) + af = np.fromiter(self.makegen(), float) + assert_(ai32.dtype == np.dtype(np.int32)) + assert_(ai64.dtype == np.dtype(np.int64)) + assert_(af.dtype == np.dtype(float)) + + def test_lengths(self): + expected = np.array(list(self.makegen())) + a = np.fromiter(self.makegen(), int) + a20 = np.fromiter(self.makegen(), int, 20) + assert_(len(a) == len(expected)) + assert_(len(a20) == 20) + assert_raises(ValueError, np.fromiter, + self.makegen(), int, len(expected) + 10) + + def test_values(self): + expected = np.array(list(self.makegen())) + a = np.fromiter(self.makegen(), int) + a20 = np.fromiter(self.makegen(), int, 20) + assert_(np.all(a == expected, axis=0)) + assert_(np.all(a20 == expected[:20], axis=0)) + + def load_data(self, n, eindex): + # Utility method for the issue 2592 tests. + # Raise an exception at the desired index in the iterator. + for e in range(n): + if e == eindex: + raise NIterError(f'error at index {eindex}') + yield e + + @pytest.mark.parametrize("dtype", [int, object]) + @pytest.mark.parametrize(["count", "error_index"], [(10, 5), (10, 9)]) + def test_2592(self, count, error_index, dtype): + # Test iteration exceptions are correctly raised. The data/generator + # has `count` elements but errors at `error_index` + iterable = self.load_data(count, error_index) + with pytest.raises(NIterError): + np.fromiter(iterable, dtype=dtype, count=count) + + @pytest.mark.parametrize("dtype", ["S", "S0", "V0", "U0"]) + def test_empty_not_structured(self, dtype): + # Note, "S0" could be allowed at some point, so long "S" (without + # any length) is rejected. + with pytest.raises(ValueError, match="Must specify length"): + np.fromiter([], dtype=dtype) + + @pytest.mark.parametrize(["dtype", "data"], + [("d", [1, 2, 3, 4, 5, 6, 7, 8, 9]), + ("O", [1, 2, 3, 4, 5, 6, 7, 8, 9]), + ("i,O", [(1, 2), (5, 4), (2, 3), (9, 8), (6, 7)]), + # subarray dtypes (important because their dimensions end up + # in the result arrays dimension: + ("2i", [(1, 2), (5, 4), (2, 3), (9, 8), (6, 7)]), + (np.dtype(("O", (2, 3))), + [((1, 2, 3), (3, 4, 5)), ((3, 2, 1), (5, 4, 3))])]) + @pytest.mark.parametrize("length_hint", [0, 1]) + def test_growth_and_complicated_dtypes(self, dtype, data, length_hint): + dtype = np.dtype(dtype) + + data = data * 100 # make sure we realloc a bit + + class MyIter: + # Class/example from gh-15789 + def __length_hint__(self): + # only required to be an estimate, this is legal + return length_hint # 0 or 1 + + def __iter__(self): + return iter(data) + + res = np.fromiter(MyIter(), dtype=dtype) + expected = np.array(data, dtype=dtype) + + assert_array_equal(res, expected) + + def test_empty_result(self): + class MyIter: + def __length_hint__(self): + return 10 + + def __iter__(self): + return iter([]) # actual iterator is empty. + + res = np.fromiter(MyIter(), dtype="d") + assert res.shape == (0,) + assert res.dtype == "d" + + def test_too_few_items(self): + msg = "iterator too short: Expected 10 but iterator had only 3 items." + with pytest.raises(ValueError, match=msg): + np.fromiter([1, 2, 3], count=10, dtype=int) + + def test_failed_itemsetting(self): + with pytest.raises(TypeError): + np.fromiter([1, None, 3], dtype=int) + + # The following manages to hit somewhat trickier code paths: + iterable = ((2, 3, 4) for i in range(5)) + with pytest.raises(ValueError): + np.fromiter(iterable, dtype=np.dtype((int, 2))) + + +class TestNonzero: + def test_nonzero_trivial(self): + assert_equal(np.count_nonzero(np.array([])), 0) + assert_equal(np.count_nonzero(np.array([], dtype='?')), 0) + assert_equal(np.nonzero(np.array([])), ([],)) + + assert_equal(np.count_nonzero(np.array([0])), 0) + assert_equal(np.count_nonzero(np.array([0], dtype='?')), 0) + assert_equal(np.nonzero(np.array([0])), ([],)) + + assert_equal(np.count_nonzero(np.array([1])), 1) + assert_equal(np.count_nonzero(np.array([1], dtype='?')), 1) + assert_equal(np.nonzero(np.array([1])), ([0],)) + + def test_nonzero_zerodim(self): + err_msg = "Calling nonzero on 0d arrays is not allowed" + with assert_raises_regex(ValueError, err_msg): + np.nonzero(np.array(0)) + with assert_raises_regex(ValueError, err_msg): + np.array(1).nonzero() + + def test_nonzero_onedim(self): + x = np.array([1, 0, 2, -1, 0, 0, 8]) + assert_equal(np.count_nonzero(x), 4) + assert_equal(np.count_nonzero(x), 4) + assert_equal(np.nonzero(x), ([0, 2, 3, 6],)) + + # x = np.array([(1, 2), (0, 0), (1, 1), (-1, 3), (0, 7)], + # dtype=[('a', 'i4'), ('b', 'i2')]) + x = np.array( + [(1, 2, -5, -3), (0, 0, 2, 7), (1, 1, 0, 1), (-1, 3, 1, 0), (0, 7, 0, 4)], + dtype=[('a', 'i4'), ('b', 'i2'), ('c', 'i1'), ('d', 'i8')] + ) + assert_equal(np.count_nonzero(x['a']), 3) + assert_equal(np.count_nonzero(x['b']), 4) + assert_equal(np.count_nonzero(x['c']), 3) + assert_equal(np.count_nonzero(x['d']), 4) + assert_equal(np.nonzero(x['a']), ([0, 2, 3],)) + assert_equal(np.nonzero(x['b']), ([0, 2, 3, 4],)) + + def test_nonzero_twodim(self): + x = np.array([[0, 1, 0], [2, 0, 3]]) + assert_equal(np.count_nonzero(x.astype('i1')), 3) + assert_equal(np.count_nonzero(x.astype('i2')), 3) + assert_equal(np.count_nonzero(x.astype('i4')), 3) + assert_equal(np.count_nonzero(x.astype('i8')), 3) + assert_equal(np.nonzero(x), ([0, 1, 1], [1, 0, 2])) + + x = np.eye(3) + assert_equal(np.count_nonzero(x.astype('i1')), 3) + assert_equal(np.count_nonzero(x.astype('i2')), 3) + assert_equal(np.count_nonzero(x.astype('i4')), 3) + assert_equal(np.count_nonzero(x.astype('i8')), 3) + assert_equal(np.nonzero(x), ([0, 1, 2], [0, 1, 2])) + + x = np.array([[(0, 1), (0, 0), (1, 11)], + [(1, 1), (1, 0), (0, 0)], + [(0, 0), (1, 5), (0, 1)]], dtype=[('a', 'f4'), ('b', 'u1')]) + assert_equal(np.count_nonzero(x['a']), 4) + assert_equal(np.count_nonzero(x['b']), 5) + assert_equal(np.nonzero(x['a']), ([0, 1, 1, 2], [2, 0, 1, 1])) + assert_equal(np.nonzero(x['b']), ([0, 0, 1, 2, 2], [0, 2, 0, 1, 2])) + + assert_(not x['a'].T.flags.aligned) + assert_equal(np.count_nonzero(x['a'].T), 4) + assert_equal(np.count_nonzero(x['b'].T), 5) + assert_equal(np.nonzero(x['a'].T), ([0, 1, 1, 2], [1, 1, 2, 0])) + assert_equal(np.nonzero(x['b'].T), ([0, 0, 1, 2, 2], [0, 1, 2, 0, 2])) + + def test_sparse(self): + # test special sparse condition boolean code path + for i in range(20): + c = np.zeros(200, dtype=bool) + c[i::20] = True + assert_equal(np.nonzero(c)[0], np.arange(i, 200 + i, 20)) + + c = np.zeros(400, dtype=bool) + c[10 + i:20 + i] = True + c[20 + i * 2] = True + assert_equal(np.nonzero(c)[0], + np.concatenate((np.arange(10 + i, 20 + i), [20 + i * 2]))) + + @pytest.mark.parametrize('dtype', [np.float32, np.float64]) + def test_nonzero_float_dtypes(self, dtype): + rng = np.random.default_rng(seed=10) + x = ((2**33) * rng.normal(size=100)).astype(dtype) + x[rng.choice(50, size=100)] = 0 + idxs = np.nonzero(x)[0] + assert_equal(np.array_equal(np.where(x != 0)[0], idxs), True) + + @pytest.mark.parametrize('dtype', [bool, np.int8, np.int16, np.int32, np.int64, + np.uint8, np.uint16, np.uint32, np.uint64]) + def test_nonzero_integer_dtypes(self, dtype): + rng = np.random.default_rng(seed=10) + x = rng.integers(0, 255, size=100).astype(dtype) + x[rng.choice(50, size=100)] = 0 + idxs = np.nonzero(x)[0] + assert_equal(np.array_equal(np.where(x != 0)[0], idxs), True) + + def test_return_type(self): + class C(np.ndarray): + pass + + for view in (C, np.ndarray): + for nd in range(1, 4): + shape = tuple(range(2, 2 + nd)) + x = np.arange(np.prod(shape)).reshape(shape).view(view) + for nzx in (np.nonzero(x), x.nonzero()): + for nzx_i in nzx: + assert_(type(nzx_i) is np.ndarray) + assert_(nzx_i.flags.writeable) + + def test_count_nonzero_axis(self): + # Basic check of functionality + m = np.array([[0, 1, 7, 0, 0], [3, 0, 0, 2, 19]]) + + expected = np.array([1, 1, 1, 1, 1]) + assert_equal(np.count_nonzero(m, axis=0), expected) + + expected = np.array([2, 3]) + assert_equal(np.count_nonzero(m, axis=1), expected) + + assert_raises(ValueError, np.count_nonzero, m, axis=(1, 1)) + assert_raises(TypeError, np.count_nonzero, m, axis='foo') + assert_raises(AxisError, np.count_nonzero, m, axis=3) + assert_raises(TypeError, np.count_nonzero, + m, axis=np.array([[1], [2]])) + + def test_count_nonzero_axis_all_dtypes(self): + # More thorough test that the axis argument is respected + # for all dtypes and responds correctly when presented with + # either integer or tuple arguments for axis + msg = "Mismatch for dtype: %s" + + def assert_equal_w_dt(a, b, err_msg): + assert_equal(a.dtype, b.dtype, err_msg=err_msg) + assert_equal(a, b, err_msg=err_msg) + + for dt in np.typecodes['All']: + err_msg = msg % (np.dtype(dt).name,) + + if dt != 'V': + if dt != 'M': + m = np.zeros((3, 3), dtype=dt) + n = np.ones(1, dtype=dt) + + m[0, 0] = n[0] + m[1, 0] = n[0] + + else: # np.zeros doesn't work for np.datetime64 + m = np.array(['1970-01-01'] * 9) + m = m.reshape((3, 3)) + + m[0, 0] = '1970-01-12' + m[1, 0] = '1970-01-12' + m = m.astype(dt) + + expected = np.array([2, 0, 0], dtype=np.intp) + assert_equal_w_dt(np.count_nonzero(m, axis=0), + expected, err_msg=err_msg) + + expected = np.array([1, 1, 0], dtype=np.intp) + assert_equal_w_dt(np.count_nonzero(m, axis=1), + expected, err_msg=err_msg) + + expected = np.array(2) + assert_equal(np.count_nonzero(m, axis=(0, 1)), + expected, err_msg=err_msg) + assert_equal(np.count_nonzero(m, axis=None), + expected, err_msg=err_msg) + assert_equal(np.count_nonzero(m), + expected, err_msg=err_msg) + + if dt == 'V': + # There are no 'nonzero' objects for np.void, so the testing + # setup is slightly different for this dtype + m = np.array([np.void(1)] * 6).reshape((2, 3)) + + expected = np.array([0, 0, 0], dtype=np.intp) + assert_equal_w_dt(np.count_nonzero(m, axis=0), + expected, err_msg=err_msg) + + expected = np.array([0, 0], dtype=np.intp) + assert_equal_w_dt(np.count_nonzero(m, axis=1), + expected, err_msg=err_msg) + + expected = np.array(0) + assert_equal(np.count_nonzero(m, axis=(0, 1)), + expected, err_msg=err_msg) + assert_equal(np.count_nonzero(m, axis=None), + expected, err_msg=err_msg) + assert_equal(np.count_nonzero(m), + expected, err_msg=err_msg) + + def test_count_nonzero_axis_consistent(self): + # Check that the axis behaviour for valid axes in + # non-special cases is consistent (and therefore + # correct) by checking it against an integer array + # that is then casted to the generic object dtype + from itertools import combinations, permutations + + axis = (0, 1, 2, 3) + size = (5, 5, 5, 5) + msg = "Mismatch for axis: %s" + + rng = np.random.RandomState(1234) + m = rng.randint(-100, 100, size=size) + n = m.astype(object) + + for length in range(len(axis)): + for combo in combinations(axis, length): + for perm in permutations(combo): + assert_equal( + np.count_nonzero(m, axis=perm), + np.count_nonzero(n, axis=perm), + err_msg=msg % (perm,)) + + def test_countnonzero_axis_empty(self): + a = np.array([[0, 0, 1], [1, 0, 1]]) + assert_equal(np.count_nonzero(a, axis=()), a.astype(bool)) + + def test_countnonzero_keepdims(self): + a = np.array([[0, 0, 1, 0], + [0, 3, 5, 0], + [7, 9, 2, 0]]) + assert_equal(np.count_nonzero(a, axis=0, keepdims=True), + [[1, 2, 3, 0]]) + assert_equal(np.count_nonzero(a, axis=1, keepdims=True), + [[1], [2], [3]]) + assert_equal(np.count_nonzero(a, keepdims=True), + [[6]]) + + def test_array_method(self): + # Tests that the array method + # call to nonzero works + m = np.array([[1, 0, 0], [4, 0, 6]]) + tgt = [[0, 1, 1], [0, 0, 2]] + + assert_equal(m.nonzero(), tgt) + + def test_nonzero_invalid_object(self): + # gh-9295 + a = np.array([np.array([1, 2]), 3], dtype=object) + assert_raises(ValueError, np.nonzero, a) + + class BoolErrors: + def __bool__(self): + raise ValueError("Not allowed") + + assert_raises(ValueError, np.nonzero, np.array([BoolErrors()])) + + def test_nonzero_sideeffect_safety(self): + # gh-13631 + class FalseThenTrue: + _val = False + + def __bool__(self): + try: + return self._val + finally: + self._val = True + + class TrueThenFalse: + _val = True + + def __bool__(self): + try: + return self._val + finally: + self._val = False + + # result grows on the second pass + a = np.array([True, FalseThenTrue()]) + assert_raises(RuntimeError, np.nonzero, a) + + a = np.array([[True], [FalseThenTrue()]]) + assert_raises(RuntimeError, np.nonzero, a) + + # result shrinks on the second pass + a = np.array([False, TrueThenFalse()]) + assert_raises(RuntimeError, np.nonzero, a) + + a = np.array([[False], [TrueThenFalse()]]) + assert_raises(RuntimeError, np.nonzero, a) + + def test_nonzero_sideffects_structured_void(self): + # Checks that structured void does not mutate alignment flag of + # original array. + arr = np.zeros(5, dtype="i1,i8,i8") # `ones` may short-circuit + assert arr.flags.aligned # structs are considered "aligned" + assert not arr["f2"].flags.aligned + # make sure that nonzero/count_nonzero do not flip the flag: + np.nonzero(arr) + assert arr.flags.aligned + np.count_nonzero(arr) + assert arr.flags.aligned + + def test_nonzero_exception_safe(self): + # gh-13930 + + class ThrowsAfter: + def __init__(self, iters): + self.iters_left = iters + + def __bool__(self): + if self.iters_left == 0: + raise ValueError("called `iters` times") + + self.iters_left -= 1 + return True + + """ + Test that a ValueError is raised instead of a SystemError + + If the __bool__ function is called after the error state is set, + Python (cpython) will raise a SystemError. + """ + + # assert that an exception in first pass is handled correctly + a = np.array([ThrowsAfter(5)] * 10) + assert_raises(ValueError, np.nonzero, a) + + # raise exception in second pass for 1-dimensional loop + a = np.array([ThrowsAfter(15)] * 10) + assert_raises(ValueError, np.nonzero, a) + + # raise exception in second pass for n-dimensional loop + a = np.array([[ThrowsAfter(15)]] * 10) + assert_raises(ValueError, np.nonzero, a) + + def test_nonzero_byteorder(self): + values = [0., -0., 1, float('nan'), 0, 1, + np.float16(0), np.float16(12.3)] + expected_values = [0, 0, 1, 1, 0, 1, 0, 1] + + for value, expected in zip(values, expected_values): + A = np.array([value]) + A_byteswapped = (A.view(A.dtype.newbyteorder()).byteswap()).copy() + + assert np.count_nonzero(A) == expected + assert np.count_nonzero(A_byteswapped) == expected + + def test_count_nonzero_non_aligned_array(self): + # gh-27523 + b = np.zeros(64 + 1, dtype=np.int8)[1:] + b = b.view(int) + b[:] = np.arange(b.size) + b[::2] = 0 + assert b.flags.aligned is False + assert np.count_nonzero(b) == b.size / 2 + + b = np.zeros(64 + 1, dtype=np.float16)[1:] + b = b.view(float) + b[:] = np.arange(b.size) + b[::2] = 0 + assert b.flags.aligned is False + assert np.count_nonzero(b) == b.size / 2 + + +class TestIndex: + def test_boolean(self): + a = rand(3, 5, 8) + V = rand(5, 8) + g1 = randint(0, 5, size=15) + g2 = randint(0, 8, size=15) + V[g1, g2] = -V[g1, g2] + assert_( + (np.array([a[0][V > 0], a[1][V > 0], a[2][V > 0]]) == a[:, V > 0]).all() + ) + + def test_boolean_edgecase(self): + a = np.array([], dtype='int32') + b = np.array([], dtype='bool') + c = a[b] + assert_equal(c, []) + assert_equal(c.dtype, np.dtype('int32')) + + +class TestBinaryRepr: + def test_zero(self): + assert_equal(np.binary_repr(0), '0') + + def test_positive(self): + assert_equal(np.binary_repr(10), '1010') + assert_equal(np.binary_repr(12522), + '11000011101010') + assert_equal(np.binary_repr(10736848), + '101000111101010011010000') + + def test_negative(self): + assert_equal(np.binary_repr(-1), '-1') + assert_equal(np.binary_repr(-10), '-1010') + assert_equal(np.binary_repr(-12522), + '-11000011101010') + assert_equal(np.binary_repr(-10736848), + '-101000111101010011010000') + + def test_sufficient_width(self): + assert_equal(np.binary_repr(0, width=5), '00000') + assert_equal(np.binary_repr(10, width=7), '0001010') + assert_equal(np.binary_repr(-5, width=7), '1111011') + + def test_neg_width_boundaries(self): + # see gh-8670 + + # Ensure that the example in the issue does not + # break before proceeding to a more thorough test. + assert_equal(np.binary_repr(-128, width=8), '10000000') + + for width in range(1, 11): + num = -2**(width - 1) + exp = '1' + (width - 1) * '0' + assert_equal(np.binary_repr(num, width=width), exp) + + def test_large_neg_int64(self): + # See gh-14289. + assert_equal(np.binary_repr(np.int64(-2**62), width=64), + '11' + '0' * 62) + + +class TestBaseRepr: + def test_base3(self): + assert_equal(np.base_repr(3**5, 3), '100000') + + def test_positive(self): + assert_equal(np.base_repr(12, 10), '12') + assert_equal(np.base_repr(12, 10, 4), '000012') + assert_equal(np.base_repr(12, 4), '30') + assert_equal(np.base_repr(3731624803700888, 36), '10QR0ROFCEW') + + def test_negative(self): + assert_equal(np.base_repr(-12, 10), '-12') + assert_equal(np.base_repr(-12, 10, 4), '-000012') + assert_equal(np.base_repr(-12, 4), '-30') + + def test_base_range(self): + with assert_raises(ValueError): + np.base_repr(1, 1) + with assert_raises(ValueError): + np.base_repr(1, 37) + + def test_minimal_signed_int(self): + assert_equal(np.base_repr(np.int8(-128)), '-10000000') + + +def _test_array_equal_parametrizations(): + """ + we pre-create arrays as we sometime want to pass the same instance + and sometime not. Passing the same instances may not mean the array are + equal, especially when containing None + """ + # those are 0-d arrays, it used to be a special case + # where (e0 == e0).all() would raise + e0 = np.array(0, dtype="int") + e1 = np.array(1, dtype="float") + # x,y, nan_equal, expected_result + yield (e0, e0.copy(), None, True) + yield (e0, e0.copy(), False, True) + yield (e0, e0.copy(), True, True) + + # + yield (e1, e1.copy(), None, True) + yield (e1, e1.copy(), False, True) + yield (e1, e1.copy(), True, True) + + # Non-nanable - those cannot hold nans + a12 = np.array([1, 2]) + a12b = a12.copy() + a123 = np.array([1, 2, 3]) + a13 = np.array([1, 3]) + a34 = np.array([3, 4]) + + aS1 = np.array(["a"], dtype="S1") + aS1b = aS1.copy() + aS1u4 = np.array([("a", 1)], dtype="S1,u4") + aS1u4b = aS1u4.copy() + + yield (a12, a12b, None, True) + yield (a12, a12, None, True) + yield (a12, a123, None, False) + yield (a12, a34, None, False) + yield (a12, a13, None, False) + yield (aS1, aS1b, None, True) + yield (aS1, aS1, None, True) + + # Non-float dtype - equal_nan should have no effect, + yield (a123, a123, None, True) + yield (a123, a123, False, True) + yield (a123, a123, True, True) + yield (a123, a123.copy(), None, True) + yield (a123, a123.copy(), False, True) + yield (a123, a123.copy(), True, True) + yield (a123.astype("float"), a123.astype("float"), None, True) + yield (a123.astype("float"), a123.astype("float"), False, True) + yield (a123.astype("float"), a123.astype("float"), True, True) + + # these can hold None + b1 = np.array([1, 2, np.nan]) + b2 = np.array([1, np.nan, 2]) + b3 = np.array([1, 2, np.inf]) + b4 = np.array(np.nan) + + # instances are the same + yield (b1, b1, None, False) + yield (b1, b1, False, False) + yield (b1, b1, True, True) + + # equal but not same instance + yield (b1, b1.copy(), None, False) + yield (b1, b1.copy(), False, False) + yield (b1, b1.copy(), True, True) + + # same once stripped of Nan + yield (b1, b2, None, False) + yield (b1, b2, False, False) + yield (b1, b2, True, False) + + # nan's not conflated with inf's + yield (b1, b3, None, False) + yield (b1, b3, False, False) + yield (b1, b3, True, False) + + # all Nan + yield (b4, b4, None, False) + yield (b4, b4, False, False) + yield (b4, b4, True, True) + yield (b4, b4.copy(), None, False) + yield (b4, b4.copy(), False, False) + yield (b4, b4.copy(), True, True) + + t1 = b1.astype("timedelta64") + t2 = b2.astype("timedelta64") + + # Timedeltas are particular + yield (t1, t1, None, False) + yield (t1, t1, False, False) + yield (t1, t1, True, True) + + yield (t1, t1.copy(), None, False) + yield (t1, t1.copy(), False, False) + yield (t1, t1.copy(), True, True) + + yield (t1, t2, None, False) + yield (t1, t2, False, False) + yield (t1, t2, True, False) + + # Multi-dimensional array + md1 = np.array([[0, 1], [np.nan, 1]]) + + yield (md1, md1, None, False) + yield (md1, md1, False, False) + yield (md1, md1, True, True) + yield (md1, md1.copy(), None, False) + yield (md1, md1.copy(), False, False) + yield (md1, md1.copy(), True, True) + # both complexes are nan+nan.j but the same instance + cplx1, cplx2 = [np.array([np.nan + np.nan * 1j])] * 2 + + # only real or img are nan. + cplx3, cplx4 = np.complex64(1, np.nan), np.complex64(np.nan, 1) + + # Complex values + yield (cplx1, cplx2, None, False) + yield (cplx1, cplx2, False, False) + yield (cplx1, cplx2, True, True) + + # Complex values, 1+nan, nan+1j + yield (cplx3, cplx4, None, False) + yield (cplx3, cplx4, False, False) + yield (cplx3, cplx4, True, True) + + +class TestArrayComparisons: + @pytest.mark.parametrize( + "bx,by,equal_nan,expected", _test_array_equal_parametrizations() + ) + def test_array_equal_equal_nan(self, bx, by, equal_nan, expected): + """ + This test array_equal for a few combinations: + + - are the two inputs the same object or not (same object may not + be equal if contains NaNs) + - Whether we should consider or not, NaNs, being equal. + + """ + if equal_nan is None: + res = np.array_equal(bx, by) + else: + res = np.array_equal(bx, by, equal_nan=equal_nan) + assert_(res is expected) + assert_(type(res) is bool) + + def test_array_equal_different_scalar_types(self): + # https://github.com/numpy/numpy/issues/27271 + a = np.array("foo") + b = np.array(1) + assert not np.array_equal(a, b) + assert not np.array_equiv(a, b) + + def test_none_compares_elementwise(self): + a = np.array([None, 1, None], dtype=object) + assert_equal(a == None, [True, False, True]) # noqa: E711 + assert_equal(a != None, [False, True, False]) # noqa: E711 + + a = np.ones(3) + assert_equal(a == None, [False, False, False]) # noqa: E711 + assert_equal(a != None, [True, True, True]) # noqa: E711 + + def test_array_equiv(self): + res = np.array_equiv(np.array([1, 2]), np.array([1, 2])) + assert_(res) + assert_(type(res) is bool) + res = np.array_equiv(np.array([1, 2]), np.array([1, 2, 3])) + assert_(not res) + assert_(type(res) is bool) + res = np.array_equiv(np.array([1, 2]), np.array([3, 4])) + assert_(not res) + assert_(type(res) is bool) + res = np.array_equiv(np.array([1, 2]), np.array([1, 3])) + assert_(not res) + assert_(type(res) is bool) + + res = np.array_equiv(np.array([1, 1]), np.array([1])) + assert_(res) + assert_(type(res) is bool) + res = np.array_equiv(np.array([1, 1]), np.array([[1], [1]])) + assert_(res) + assert_(type(res) is bool) + res = np.array_equiv(np.array([1, 2]), np.array([2])) + assert_(not res) + assert_(type(res) is bool) + res = np.array_equiv(np.array([1, 2]), np.array([[1], [2]])) + assert_(not res) + assert_(type(res) is bool) + res = np.array_equiv( + np.array([1, 2]), + np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]), + ) + assert_(not res) + assert_(type(res) is bool) + + @pytest.mark.parametrize("dtype", ["V0", "V3", "V10"]) + def test_compare_unstructured_voids(self, dtype): + zeros = np.zeros(3, dtype=dtype) + + assert_array_equal(zeros, zeros) + assert not (zeros != zeros).any() + + if dtype == "V0": + # Can't test != of actually different data + return + + nonzeros = np.array([b"1", b"2", b"3"], dtype=dtype) + + assert not (zeros == nonzeros).any() + assert (zeros != nonzeros).all() + + +def assert_array_strict_equal(x, y): + assert_array_equal(x, y) + # Check flags, 32 bit arches typically don't provide 16 byte alignment + if ((x.dtype.alignment <= 8 or + np.intp().dtype.itemsize != 4) and + sys.platform != 'win32'): + assert_(x.flags == y.flags) + else: + assert_(x.flags.owndata == y.flags.owndata) + assert_(x.flags.writeable == y.flags.writeable) + assert_(x.flags.c_contiguous == y.flags.c_contiguous) + assert_(x.flags.f_contiguous == y.flags.f_contiguous) + assert_(x.flags.writebackifcopy == y.flags.writebackifcopy) + # check endianness + assert_(x.dtype.isnative == y.dtype.isnative) + + +class TestClip: + nr = 5 + nc = 3 + + def fastclip(self, a, m, M, out=None, **kwargs): + return a.clip(m, M, out=out, **kwargs) + + def clip(self, a, m, M, out=None): + # use a.choose to verify fastclip result + selector = np.less(a, m) + 2 * np.greater(a, M) + return selector.choose((a, m, M), out=out) + + # Handy functions + def _generate_data(self, n, m): + return randn(n, m) + + def _generate_data_complex(self, n, m): + return randn(n, m) + 1.j * rand(n, m) + + def _generate_flt_data(self, n, m): + return (randn(n, m)).astype(np.float32) + + def _neg_byteorder(self, a): + a = np.asarray(a) + if sys.byteorder == 'little': + a = a.astype(a.dtype.newbyteorder('>')) + else: + a = a.astype(a.dtype.newbyteorder('<')) + return a + + def _generate_non_native_data(self, n, m): + data = randn(n, m) + data = self._neg_byteorder(data) + assert_(not data.dtype.isnative) + return data + + def _generate_int_data(self, n, m): + return (10 * rand(n, m)).astype(np.int64) + + def _generate_int32_data(self, n, m): + return (10 * rand(n, m)).astype(np.int32) + + # Now the real test cases + + @pytest.mark.parametrize("dtype", '?bhilqpBHILQPefdgFDGO') + def test_ones_pathological(self, dtype): + # for preservation of behavior described in + # gh-12519; amin > amax behavior may still change + # in the future + arr = np.ones(10, dtype=dtype) + expected = np.zeros(10, dtype=dtype) + actual = np.clip(arr, 1, 0) + if dtype == 'O': + assert actual.tolist() == expected.tolist() + else: + assert_equal(actual, expected) + + def test_simple_double(self): + # Test native double input with scalar min/max. + a = self._generate_data(self.nr, self.nc) + m = 0.1 + M = 0.6 + ac = self.fastclip(a, m, M) + act = self.clip(a, m, M) + assert_array_strict_equal(ac, act) + + def test_simple_int(self): + # Test native int input with scalar min/max. + a = self._generate_int_data(self.nr, self.nc) + a = a.astype(int) + m = -2 + M = 4 + ac = self.fastclip(a, m, M) + act = self.clip(a, m, M) + assert_array_strict_equal(ac, act) + + def test_array_double(self): + # Test native double input with array min/max. + a = self._generate_data(self.nr, self.nc) + m = np.zeros(a.shape) + M = m + 0.5 + ac = self.fastclip(a, m, M) + act = self.clip(a, m, M) + assert_array_strict_equal(ac, act) + + def test_simple_nonnative(self): + # Test non native double input with scalar min/max. + # Test native double input with non native double scalar min/max. + a = self._generate_non_native_data(self.nr, self.nc) + m = -0.5 + M = 0.6 + ac = self.fastclip(a, m, M) + act = self.clip(a, m, M) + assert_array_equal(ac, act) + + # Test native double input with non native double scalar min/max. + a = self._generate_data(self.nr, self.nc) + m = -0.5 + M = self._neg_byteorder(0.6) + assert_(not M.dtype.isnative) + ac = self.fastclip(a, m, M) + act = self.clip(a, m, M) + assert_array_equal(ac, act) + + def test_simple_complex(self): + # Test native complex input with native double scalar min/max. + # Test native input with complex double scalar min/max. + a = 3 * self._generate_data_complex(self.nr, self.nc) + m = -0.5 + M = 1. + ac = self.fastclip(a, m, M) + act = self.clip(a, m, M) + assert_array_strict_equal(ac, act) + + # Test native input with complex double scalar min/max. + a = 3 * self._generate_data(self.nr, self.nc) + m = -0.5 + 1.j + M = 1. + 2.j + ac = self.fastclip(a, m, M) + act = self.clip(a, m, M) + assert_array_strict_equal(ac, act) + + def test_clip_complex(self): + # Address Issue gh-5354 for clipping complex arrays + # Test native complex input without explicit min/max + # ie, either min=None or max=None + a = np.ones(10, dtype=complex) + m = a.min() + M = a.max() + am = self.fastclip(a, m, None) + aM = self.fastclip(a, None, M) + assert_array_strict_equal(am, a) + assert_array_strict_equal(aM, a) + + def test_clip_non_contig(self): + # Test clip for non contiguous native input and native scalar min/max. + a = self._generate_data(self.nr * 2, self.nc * 3) + a = a[::2, ::3] + assert_(not a.flags['F_CONTIGUOUS']) + assert_(not a.flags['C_CONTIGUOUS']) + ac = self.fastclip(a, -1.6, 1.7) + act = self.clip(a, -1.6, 1.7) + assert_array_strict_equal(ac, act) + + def test_simple_out(self): + # Test native double input with scalar min/max. + a = self._generate_data(self.nr, self.nc) + m = -0.5 + M = 0.6 + ac = np.zeros(a.shape) + act = np.zeros(a.shape) + self.fastclip(a, m, M, ac) + self.clip(a, m, M, act) + assert_array_strict_equal(ac, act) + + @pytest.mark.parametrize("casting", [None, "unsafe"]) + def test_simple_int32_inout(self, casting): + # Test native int32 input with double min/max and int32 out. + a = self._generate_int32_data(self.nr, self.nc) + m = np.float64(0) + M = np.float64(2) + ac = np.zeros(a.shape, dtype=np.int32) + act = ac.copy() + if casting is None: + with pytest.raises(TypeError): + self.fastclip(a, m, M, ac, casting=casting) + else: + # explicitly passing "unsafe" will silence warning + self.fastclip(a, m, M, ac, casting=casting) + self.clip(a, m, M, act) + assert_array_strict_equal(ac, act) + + def test_simple_int64_out(self): + # Test native int32 input with int32 scalar min/max and int64 out. + a = self._generate_int32_data(self.nr, self.nc) + m = np.int32(-1) + M = np.int32(1) + ac = np.zeros(a.shape, dtype=np.int64) + act = ac.copy() + self.fastclip(a, m, M, ac) + self.clip(a, m, M, act) + assert_array_strict_equal(ac, act) + + def test_simple_int64_inout(self): + # Test native int32 input with double array min/max and int32 out. + a = self._generate_int32_data(self.nr, self.nc) + m = np.zeros(a.shape, np.float64) + M = np.float64(1) + ac = np.zeros(a.shape, dtype=np.int32) + act = ac.copy() + self.fastclip(a, m, M, out=ac, casting="unsafe") + self.clip(a, m, M, act) + assert_array_strict_equal(ac, act) + + def test_simple_int32_out(self): + # Test native double input with scalar min/max and int out. + a = self._generate_data(self.nr, self.nc) + m = -1.0 + M = 2.0 + ac = np.zeros(a.shape, dtype=np.int32) + act = ac.copy() + self.fastclip(a, m, M, out=ac, casting="unsafe") + self.clip(a, m, M, act) + assert_array_strict_equal(ac, act) + + def test_simple_inplace_01(self): + # Test native double input with array min/max in-place. + a = self._generate_data(self.nr, self.nc) + ac = a.copy() + m = np.zeros(a.shape) + M = 1.0 + self.fastclip(a, m, M, a) + self.clip(a, m, M, ac) + assert_array_strict_equal(a, ac) + + def test_simple_inplace_02(self): + # Test native double input with scalar min/max in-place. + a = self._generate_data(self.nr, self.nc) + ac = a.copy() + m = -0.5 + M = 0.6 + self.fastclip(a, m, M, a) + self.clip(ac, m, M, ac) + assert_array_strict_equal(a, ac) + + def test_noncontig_inplace(self): + # Test non contiguous double input with double scalar min/max in-place. + a = self._generate_data(self.nr * 2, self.nc * 3) + a = a[::2, ::3] + assert_(not a.flags['F_CONTIGUOUS']) + assert_(not a.flags['C_CONTIGUOUS']) + ac = a.copy() + m = -0.5 + M = 0.6 + self.fastclip(a, m, M, a) + self.clip(ac, m, M, ac) + assert_array_equal(a, ac) + + def test_type_cast_01(self): + # Test native double input with scalar min/max. + a = self._generate_data(self.nr, self.nc) + m = -0.5 + M = 0.6 + ac = self.fastclip(a, m, M) + act = self.clip(a, m, M) + assert_array_strict_equal(ac, act) + + def test_type_cast_02(self): + # Test native int32 input with int32 scalar min/max. + a = self._generate_int_data(self.nr, self.nc) + a = a.astype(np.int32) + m = -2 + M = 4 + ac = self.fastclip(a, m, M) + act = self.clip(a, m, M) + assert_array_strict_equal(ac, act) + + def test_type_cast_03(self): + # Test native int32 input with float64 scalar min/max. + a = self._generate_int32_data(self.nr, self.nc) + m = -2 + M = 4 + ac = self.fastclip(a, np.float64(m), np.float64(M)) + act = self.clip(a, np.float64(m), np.float64(M)) + assert_array_strict_equal(ac, act) + + def test_type_cast_04(self): + # Test native int32 input with float32 scalar min/max. + a = self._generate_int32_data(self.nr, self.nc) + m = np.float32(-2) + M = np.float32(4) + act = self.fastclip(a, m, M) + ac = self.clip(a, m, M) + assert_array_strict_equal(ac, act) + + def test_type_cast_05(self): + # Test native int32 with double arrays min/max. + a = self._generate_int_data(self.nr, self.nc) + m = -0.5 + M = 1. + ac = self.fastclip(a, m * np.zeros(a.shape), M) + act = self.clip(a, m * np.zeros(a.shape), M) + assert_array_strict_equal(ac, act) + + def test_type_cast_06(self): + # Test native with NON native scalar min/max. + a = self._generate_data(self.nr, self.nc) + m = 0.5 + m_s = self._neg_byteorder(m) + M = 1. + act = self.clip(a, m_s, M) + ac = self.fastclip(a, m_s, M) + assert_array_strict_equal(ac, act) + + def test_type_cast_07(self): + # Test NON native with native array min/max. + a = self._generate_data(self.nr, self.nc) + m = -0.5 * np.ones(a.shape) + M = 1. + a_s = self._neg_byteorder(a) + assert_(not a_s.dtype.isnative) + act = a_s.clip(m, M) + ac = self.fastclip(a_s, m, M) + assert_array_strict_equal(ac, act) + + def test_type_cast_08(self): + # Test NON native with native scalar min/max. + a = self._generate_data(self.nr, self.nc) + m = -0.5 + M = 1. + a_s = self._neg_byteorder(a) + assert_(not a_s.dtype.isnative) + ac = self.fastclip(a_s, m, M) + act = a_s.clip(m, M) + assert_array_strict_equal(ac, act) + + def test_type_cast_09(self): + # Test native with NON native array min/max. + a = self._generate_data(self.nr, self.nc) + m = -0.5 * np.ones(a.shape) + M = 1. + m_s = self._neg_byteorder(m) + assert_(not m_s.dtype.isnative) + ac = self.fastclip(a, m_s, M) + act = self.clip(a, m_s, M) + assert_array_strict_equal(ac, act) + + def test_type_cast_10(self): + # Test native int32 with float min/max and float out for output argument. + a = self._generate_int_data(self.nr, self.nc) + b = np.zeros(a.shape, dtype=np.float32) + m = np.float32(-0.5) + M = np.float32(1) + act = self.clip(a, m, M, out=b) + ac = self.fastclip(a, m, M, out=b) + assert_array_strict_equal(ac, act) + + def test_type_cast_11(self): + # Test non native with native scalar, min/max, out non native + a = self._generate_non_native_data(self.nr, self.nc) + b = a.copy() + b = b.astype(b.dtype.newbyteorder('>')) + bt = b.copy() + m = -0.5 + M = 1. + self.fastclip(a, m, M, out=b) + self.clip(a, m, M, out=bt) + assert_array_strict_equal(b, bt) + + def test_type_cast_12(self): + # Test native int32 input and min/max and float out + a = self._generate_int_data(self.nr, self.nc) + b = np.zeros(a.shape, dtype=np.float32) + m = np.int32(0) + M = np.int32(1) + act = self.clip(a, m, M, out=b) + ac = self.fastclip(a, m, M, out=b) + assert_array_strict_equal(ac, act) + + def test_clip_with_out_simple(self): + # Test native double input with scalar min/max + a = self._generate_data(self.nr, self.nc) + m = -0.5 + M = 0.6 + ac = np.zeros(a.shape) + act = np.zeros(a.shape) + self.fastclip(a, m, M, ac) + self.clip(a, m, M, act) + assert_array_strict_equal(ac, act) + + def test_clip_with_out_simple2(self): + # Test native int32 input with double min/max and int32 out + a = self._generate_int32_data(self.nr, self.nc) + m = np.float64(0) + M = np.float64(2) + ac = np.zeros(a.shape, dtype=np.int32) + act = ac.copy() + self.fastclip(a, m, M, out=ac, casting="unsafe") + self.clip(a, m, M, act) + assert_array_strict_equal(ac, act) + + def test_clip_with_out_simple_int32(self): + # Test native int32 input with int32 scalar min/max and int64 out + a = self._generate_int32_data(self.nr, self.nc) + m = np.int32(-1) + M = np.int32(1) + ac = np.zeros(a.shape, dtype=np.int64) + act = ac.copy() + self.fastclip(a, m, M, ac) + self.clip(a, m, M, act) + assert_array_strict_equal(ac, act) + + def test_clip_with_out_array_int32(self): + # Test native int32 input with double array min/max and int32 out + a = self._generate_int32_data(self.nr, self.nc) + m = np.zeros(a.shape, np.float64) + M = np.float64(1) + ac = np.zeros(a.shape, dtype=np.int32) + act = ac.copy() + self.fastclip(a, m, M, out=ac, casting="unsafe") + self.clip(a, m, M, act) + assert_array_strict_equal(ac, act) + + def test_clip_with_out_array_outint32(self): + # Test native double input with scalar min/max and int out + a = self._generate_data(self.nr, self.nc) + m = -1.0 + M = 2.0 + ac = np.zeros(a.shape, dtype=np.int32) + act = ac.copy() + self.fastclip(a, m, M, out=ac, casting="unsafe") + self.clip(a, m, M, act) + assert_array_strict_equal(ac, act) + + def test_clip_with_out_transposed(self): + # Test that the out argument works when transposed + a = np.arange(16).reshape(4, 4) + out = np.empty_like(a).T + a.clip(4, 10, out=out) + expected = self.clip(a, 4, 10) + assert_array_equal(out, expected) + + def test_clip_with_out_memory_overlap(self): + # Test that the out argument works when it has memory overlap + a = np.arange(16).reshape(4, 4) + ac = a.copy() + a[:-1].clip(4, 10, out=a[1:]) + expected = self.clip(ac[:-1], 4, 10) + assert_array_equal(a[1:], expected) + + def test_clip_inplace_array(self): + # Test native double input with array min/max + a = self._generate_data(self.nr, self.nc) + ac = a.copy() + m = np.zeros(a.shape) + M = 1.0 + self.fastclip(a, m, M, a) + self.clip(a, m, M, ac) + assert_array_strict_equal(a, ac) + + def test_clip_inplace_simple(self): + # Test native double input with scalar min/max + a = self._generate_data(self.nr, self.nc) + ac = a.copy() + m = -0.5 + M = 0.6 + self.fastclip(a, m, M, a) + self.clip(a, m, M, ac) + assert_array_strict_equal(a, ac) + + def test_clip_func_takes_out(self): + # Ensure that the clip() function takes an out=argument. + a = self._generate_data(self.nr, self.nc) + ac = a.copy() + m = -0.5 + M = 0.6 + a2 = np.clip(a, m, M, out=a) + self.clip(a, m, M, ac) + assert_array_strict_equal(a2, ac) + assert_(a2 is a) + + def test_clip_nan(self): + d = np.arange(7.) + assert_equal(d.clip(min=np.nan), np.nan) + assert_equal(d.clip(max=np.nan), np.nan) + assert_equal(d.clip(min=np.nan, max=np.nan), np.nan) + assert_equal(d.clip(min=-2, max=np.nan), np.nan) + assert_equal(d.clip(min=np.nan, max=10), np.nan) + + def test_object_clip(self): + a = np.arange(10, dtype=object) + actual = np.clip(a, 1, 5) + expected = np.array([1, 1, 2, 3, 4, 5, 5, 5, 5, 5]) + assert actual.tolist() == expected.tolist() + + def test_clip_all_none(self): + arr = np.arange(10, dtype=object) + assert_equal(np.clip(arr, None, None), arr) + assert_equal(np.clip(arr), arr) + + def test_clip_invalid_casting(self): + a = np.arange(10, dtype=object) + with assert_raises_regex(ValueError, + 'casting must be one of'): + self.fastclip(a, 1, 8, casting="garbage") + + @pytest.mark.parametrize("amin, amax", [ + # two scalars + (1, 0), + # mix scalar and array + (1, np.zeros(10)), + # two arrays + (np.ones(10), np.zeros(10)), + ]) + def test_clip_value_min_max_flip(self, amin, amax): + a = np.arange(10, dtype=np.int64) + # requirement from ufunc_docstrings.py + expected = np.minimum(np.maximum(a, amin), amax) + actual = np.clip(a, amin, amax) + assert_equal(actual, expected) + + @pytest.mark.parametrize("arr, amin, amax, exp", [ + # for a bug in npy_ObjectClip, based on a + # case produced by hypothesis + (np.zeros(10, dtype=object), + 0, + -2**64 + 1, + np.full(10, -2**64 + 1, dtype=object)), + # for bugs in NPY_TIMEDELTA_MAX, based on a case + # produced by hypothesis + (np.zeros(10, dtype='m8') - 1, + 0, + 0, + np.zeros(10, dtype='m8')), + ]) + def test_clip_problem_cases(self, arr, amin, amax, exp): + actual = np.clip(arr, amin, amax) + assert_equal(actual, exp) + + @pytest.mark.parametrize("arr, amin, amax", [ + # problematic scalar nan case from hypothesis + (np.zeros(10, dtype=np.int64), + np.array(np.nan), + np.zeros(10, dtype=np.int32)), + ]) + def test_clip_scalar_nan_propagation(self, arr, amin, amax): + # enforcement of scalar nan propagation for comparisons + # called through clip() + expected = np.minimum(np.maximum(arr, amin), amax) + actual = np.clip(arr, amin, amax) + assert_equal(actual, expected) + + @pytest.mark.parametrize("arr, amin, amax", [ + (np.array([1] * 10, dtype='m8'), + np.timedelta64('NaT'), + np.zeros(10, dtype=np.int32)), + ]) + def test_NaT_propagation(self, arr, amin, amax): + expected = np.minimum(np.maximum(arr, amin), amax) + actual = np.clip(arr, amin, amax) + assert_equal(actual, expected) + + @given( + data=st.data(), + arr=hynp.arrays( + dtype=hynp.integer_dtypes() | hynp.floating_dtypes(), + shape=hynp.array_shapes() + ) + ) + def test_clip_property(self, data, arr): + """A property-based test using Hypothesis. + + This aims for maximum generality: it could in principle generate *any* + valid inputs to np.clip, and in practice generates much more varied + inputs than human testers come up with. + + Because many of the inputs have tricky dependencies - compatible dtypes + and mutually-broadcastable shapes - we use `st.data()` strategy draw + values *inside* the test function, from strategies we construct based + on previous values. An alternative would be to define a custom strategy + with `@st.composite`, but until we have duplicated code inline is fine. + + That accounts for most of the function; the actual test is just three + lines to calculate and compare actual vs expected results! + """ + numeric_dtypes = hynp.integer_dtypes() | hynp.floating_dtypes() + # Generate shapes for the bounds which can be broadcast with each other + # and with the base shape. Below, we might decide to use scalar bounds, + # but it's clearer to generate these shapes unconditionally in advance. + in_shapes, result_shape = data.draw( + hynp.mutually_broadcastable_shapes( + num_shapes=2, base_shape=arr.shape + ) + ) + # Scalar `nan` is deprecated due to the differing behaviour it shows. + s = numeric_dtypes.flatmap( + lambda x: hynp.from_dtype(x, allow_nan=False)) + amin = data.draw(s | hynp.arrays(dtype=numeric_dtypes, + shape=in_shapes[0], elements={"allow_nan": False})) + amax = data.draw(s | hynp.arrays(dtype=numeric_dtypes, + shape=in_shapes[1], elements={"allow_nan": False})) + + # Then calculate our result and expected result and check that they're + # equal! See gh-12519 and gh-19457 for discussion deciding on this + # property and the result_type argument. + result = np.clip(arr, amin, amax) + t = np.result_type(arr, amin, amax) + expected = np.minimum(amax, np.maximum(arr, amin, dtype=t), dtype=t) + assert result.dtype == t + assert_array_equal(result, expected) + + def test_clip_min_max_args(self): + arr = np.arange(5) + + assert_array_equal(np.clip(arr), arr) + assert_array_equal(np.clip(arr, min=2, max=3), np.clip(arr, 2, 3)) + assert_array_equal(np.clip(arr, min=None, max=2), + np.clip(arr, None, 2)) + + with assert_raises_regex(TypeError, "missing 1 required positional " + "argument: 'a_max'"): + np.clip(arr, 2) + with assert_raises_regex(TypeError, "missing 1 required positional " + "argument: 'a_min'"): + np.clip(arr, a_max=2) + msg = ("Passing `min` or `max` keyword argument when `a_min` and " + "`a_max` are provided is forbidden.") + with assert_raises_regex(ValueError, msg): + np.clip(arr, 2, 3, max=3) + with assert_raises_regex(ValueError, msg): + np.clip(arr, 2, 3, min=2) + + @pytest.mark.parametrize("dtype,min,max", [ + ("int32", -2**32 - 1, 2**32), + ("int32", -2**320, None), + ("int32", None, 2**300), + ("int32", -1000, 2**32), + ("int32", -2**32 - 1, 1000), + ("uint8", -1, 129), + ]) + def test_out_of_bound_pyints(self, dtype, min, max): + a = np.arange(10000).astype(dtype) + # Check min only + c = np.clip(a, min=min, max=max) + assert not np.may_share_memory(a, c) + assert c.dtype == a.dtype + if min is not None: + assert (c >= min).all() + if max is not None: + assert (c <= max).all() + + +class TestAllclose: + rtol = 1e-5 + atol = 1e-8 + + def setup_method(self): + self.olderr = np.seterr(invalid='ignore') + + def teardown_method(self): + np.seterr(**self.olderr) + + def tst_allclose(self, x, y): + assert_(np.allclose(x, y), f"{x} and {y} not close") + + def tst_not_allclose(self, x, y): + assert_(not np.allclose(x, y), f"{x} and {y} shouldn't be close") + + def test_ip_allclose(self): + # Parametric test factory. + arr = np.array([100, 1000]) + aran = np.arange(125).reshape((5, 5, 5)) + + atol = self.atol + rtol = self.rtol + + data = [([1, 0], [1, 0]), + ([atol], [0]), + ([1], [1 + rtol + atol]), + (arr, arr + arr * rtol), + (arr, arr + arr * rtol + atol * 2), + (aran, aran + aran * rtol), + (np.inf, np.inf), + (np.inf, [np.inf])] + + for (x, y) in data: + self.tst_allclose(x, y) + + def test_ip_not_allclose(self): + # Parametric test factory. + aran = np.arange(125).reshape((5, 5, 5)) + + atol = self.atol + rtol = self.rtol + + data = [([np.inf, 0], [1, np.inf]), + ([np.inf, 0], [1, 0]), + ([np.inf, np.inf], [1, np.inf]), + ([np.inf, np.inf], [1, 0]), + ([-np.inf, 0], [np.inf, 0]), + ([np.nan, 0], [np.nan, 0]), + ([atol * 2], [0]), + ([1], [1 + rtol + atol * 2]), + (aran, aran + aran * atol + atol * 2), + (np.array([np.inf, 1]), np.array([0, np.inf]))] + + for (x, y) in data: + self.tst_not_allclose(x, y) + + def test_no_parameter_modification(self): + x = np.array([np.inf, 1]) + y = np.array([0, np.inf]) + np.allclose(x, y) + assert_array_equal(x, np.array([np.inf, 1])) + assert_array_equal(y, np.array([0, np.inf])) + + def test_min_int(self): + # Could make problems because of abs(min_int) == min_int + min_int = np.iinfo(np.int_).min + a = np.array([min_int], dtype=np.int_) + assert_(np.allclose(a, a)) + + def test_equalnan(self): + x = np.array([1.0, np.nan]) + assert_(np.allclose(x, x, equal_nan=True)) + + def test_return_class_is_ndarray(self): + # Issue gh-6475 + # Check that allclose does not preserve subtypes + class Foo(np.ndarray): + def __new__(cls, *args, **kwargs): + return np.array(*args, **kwargs).view(cls) + + a = Foo([1]) + assert_(type(np.allclose(a, a)) is bool) + + +class TestIsclose: + rtol = 1e-5 + atol = 1e-8 + + def _setup(self): + atol = self.atol + rtol = self.rtol + arr = np.array([100, 1000]) + aran = np.arange(125).reshape((5, 5, 5)) + + self.all_close_tests = [ + ([1, 0], [1, 0]), + ([atol], [0]), + ([1], [1 + rtol + atol]), + (arr, arr + arr * rtol), + (arr, arr + arr * rtol + atol), + (aran, aran + aran * rtol), + (np.inf, np.inf), + (np.inf, [np.inf]), + ([np.inf, -np.inf], [np.inf, -np.inf]), + ] + self.none_close_tests = [ + ([np.inf, 0], [1, np.inf]), + ([np.inf, -np.inf], [1, 0]), + ([np.inf, np.inf], [1, -np.inf]), + ([np.inf, np.inf], [1, 0]), + ([np.nan, 0], [np.nan, -np.inf]), + ([atol * 2], [0]), + ([1], [1 + rtol + atol * 2]), + (aran, aran + rtol * 1.1 * aran + atol * 1.1), + (np.array([np.inf, 1]), np.array([0, np.inf])), + ] + self.some_close_tests = [ + ([np.inf, 0], [np.inf, atol * 2]), + ([atol, 1, 1e6 * (1 + 2 * rtol) + atol], [0, np.nan, 1e6]), + (np.arange(3), [0, 1, 2.1]), + (np.nan, [np.nan, np.nan, np.nan]), + ([0], [atol, np.inf, -np.inf, np.nan]), + (0, [atol, np.inf, -np.inf, np.nan]), + ] + self.some_close_results = [ + [True, False], + [True, False, False], + [True, True, False], + [False, False, False], + [True, False, False, False], + [True, False, False, False], + ] + + def test_ip_isclose(self): + self._setup() + tests = self.some_close_tests + results = self.some_close_results + for (x, y), result in zip(tests, results): + assert_array_equal(np.isclose(x, y), result) + + x = np.array([2.1, 2.1, 2.1, 2.1, 5, np.nan]) + y = np.array([2, 2, 2, 2, np.nan, 5]) + atol = [0.11, 0.09, 1e-8, 1e-8, 1, 1] + rtol = [1e-8, 1e-8, 0.06, 0.04, 1, 1] + expected = np.array([True, False, True, False, False, False]) + assert_array_equal(np.isclose(x, y, rtol=rtol, atol=atol), expected) + + message = "operands could not be broadcast together..." + atol = np.array([1e-8, 1e-8]) + with assert_raises(ValueError, msg=message): + np.isclose(x, y, atol=atol) + + rtol = np.array([1e-5, 1e-5]) + with assert_raises(ValueError, msg=message): + np.isclose(x, y, rtol=rtol) + + def test_nep50_isclose(self): + below_one = float(1. - np.finfo('f8').eps) + f32 = np.array(below_one, 'f4') # This is just 1 at float32 precision + assert f32 > np.array(below_one) + # NEP 50 broadcasting of python scalars + assert f32 == below_one + # Test that it works for isclose arguments too (and that those fail if + # one uses a numpy float64). + assert np.isclose(f32, below_one, atol=0, rtol=0) + assert np.isclose(f32, np.float32(0), atol=below_one) + assert np.isclose(f32, 2, atol=0, rtol=below_one / 2) + assert not np.isclose(f32, np.float64(below_one), atol=0, rtol=0) + assert not np.isclose(f32, np.float32(0), atol=np.float64(below_one)) + assert not np.isclose(f32, 2, atol=0, rtol=np.float64(below_one / 2)) + + def tst_all_isclose(self, x, y): + assert_(np.all(np.isclose(x, y)), f"{x} and {y} not close") + + def tst_none_isclose(self, x, y): + msg = "%s and %s shouldn't be close" + assert_(not np.any(np.isclose(x, y)), msg % (x, y)) + + def tst_isclose_allclose(self, x, y): + msg = "isclose.all() and allclose aren't same for %s and %s" + msg2 = "isclose and allclose aren't same for %s and %s" + if np.isscalar(x) and np.isscalar(y): + assert_(np.isclose(x, y) == np.allclose(x, y), msg=msg2 % (x, y)) + else: + assert_array_equal( + np.isclose(x, y).all(), np.allclose(x, y), msg % (x, y) + ) + + def test_ip_all_isclose(self): + self._setup() + for (x, y) in self.all_close_tests: + self.tst_all_isclose(x, y) + + x = np.array([2.3, 3.6, 4.4, np.nan]) + y = np.array([2, 3, 4, np.nan]) + atol = [0.31, 0, 0, 1] + rtol = [0, 0.21, 0.11, 1] + assert np.allclose(x, y, atol=atol, rtol=rtol, equal_nan=True) + assert not np.allclose(x, y, atol=0.1, rtol=0.1, equal_nan=True) + + # Show that gh-14330 is resolved + assert np.allclose([1, 2, float('nan')], [1, 2, float('nan')], + atol=[1, 1, 1], equal_nan=True) + + def test_ip_none_isclose(self): + self._setup() + for (x, y) in self.none_close_tests: + self.tst_none_isclose(x, y) + + def test_ip_isclose_allclose(self): + self._setup() + tests = (self.all_close_tests + self.none_close_tests + + self.some_close_tests) + for (x, y) in tests: + self.tst_isclose_allclose(x, y) + + def test_equal_nan(self): + assert_array_equal(np.isclose(np.nan, np.nan, equal_nan=True), [True]) + arr = np.array([1.0, np.nan]) + assert_array_equal(np.isclose(arr, arr, equal_nan=True), [True, True]) + + def test_masked_arrays(self): + # Make sure to test the output type when arguments are interchanged. + + x = np.ma.masked_where([True, True, False], np.arange(3)) + assert_(type(x) is type(np.isclose(2, x))) + assert_(type(x) is type(np.isclose(x, 2))) + + x = np.ma.masked_where([True, True, False], [np.nan, np.inf, np.nan]) + assert_(type(x) is type(np.isclose(np.inf, x))) + assert_(type(x) is type(np.isclose(x, np.inf))) + + x = np.ma.masked_where([True, True, False], [np.nan, np.nan, np.nan]) + y = np.isclose(np.nan, x, equal_nan=True) + assert_(type(x) is type(y)) + # Ensure that the mask isn't modified... + assert_array_equal([True, True, False], y.mask) + y = np.isclose(x, np.nan, equal_nan=True) + assert_(type(x) is type(y)) + # Ensure that the mask isn't modified... + assert_array_equal([True, True, False], y.mask) + + x = np.ma.masked_where([True, True, False], [np.nan, np.nan, np.nan]) + y = np.isclose(x, x, equal_nan=True) + assert_(type(x) is type(y)) + # Ensure that the mask isn't modified... + assert_array_equal([True, True, False], y.mask) + + def test_scalar_return(self): + assert_(np.isscalar(np.isclose(1, 1))) + + def test_no_parameter_modification(self): + x = np.array([np.inf, 1]) + y = np.array([0, np.inf]) + np.isclose(x, y) + assert_array_equal(x, np.array([np.inf, 1])) + assert_array_equal(y, np.array([0, np.inf])) + + def test_non_finite_scalar(self): + # GH7014, when two scalars are compared the output should also be a + # scalar + assert_(np.isclose(np.inf, -np.inf) is np.False_) + assert_(np.isclose(0, np.inf) is np.False_) + assert_(type(np.isclose(0, np.inf)) is np.bool) + + def test_timedelta(self): + # Allclose currently works for timedelta64 as long as `atol` is + # an integer or also a timedelta64 + a = np.array([[1, 2, 3, "NaT"]], dtype="m8[ns]") + assert np.isclose(a, a, atol=0, equal_nan=True).all() + assert np.isclose(a, a, atol=np.timedelta64(1, "ns"), equal_nan=True).all() + assert np.allclose(a, a, atol=0, equal_nan=True) + assert np.allclose(a, a, atol=np.timedelta64(1, "ns"), equal_nan=True) + + def test_tol_warnings(self): + a = np.array([1, 2, 3]) + b = np.array([np.inf, np.nan, 1]) + + for i in b: + for j in b: + # Making sure that i and j are not both numbers, + # because that won't create a warning + if (i == 1) and (j == 1): + continue + + with warnings.catch_warnings(record=True) as w: + + warnings.simplefilter("always") + c = np.isclose(a, a, atol=i, rtol=j) + assert len(w) == 1 + assert issubclass(w[-1].category, RuntimeWarning) + expected = f"One of rtol or atol is not valid, atol: {i}, rtol: {j}" + assert expected in str(w[-1].message) + + +class TestStdVar: + def _create_data(self): + A = np.array([1, -1, 1, -1]) + real_var = 1 + return A, real_var + + def test_basic(self): + A, real_var = self._create_data() + assert_almost_equal(np.var(A), real_var) + assert_almost_equal(np.std(A)**2, real_var) + + def test_scalars(self): + assert_equal(np.var(1), 0) + assert_equal(np.std(1), 0) + + def test_ddof1(self): + A, real_var = self._create_data() + assert_almost_equal(np.var(A, ddof=1), + real_var * len(A) / (len(A) - 1)) + assert_almost_equal(np.std(A, ddof=1)**2, + real_var * len(A) / (len(A) - 1)) + + def test_ddof2(self): + A, real_var = self._create_data() + assert_almost_equal(np.var(A, ddof=2), + real_var * len(A) / (len(A) - 2)) + assert_almost_equal(np.std(A, ddof=2)**2, + real_var * len(A) / (len(A) - 2)) + + def test_correction(self): + A, _ = self._create_data() + assert_almost_equal( + np.var(A, correction=1), np.var(A, ddof=1) + ) + assert_almost_equal( + np.std(A, correction=1), np.std(A, ddof=1) + ) + + err_msg = "ddof and correction can't be provided simultaneously." + + with assert_raises_regex(ValueError, err_msg): + np.var(A, ddof=1, correction=0) + + with assert_raises_regex(ValueError, err_msg): + np.std(A, ddof=1, correction=1) + + def test_out_scalar(self): + d = np.arange(10) + out = np.array(0.) + r = np.std(d, out=out) + assert_(r is out) + assert_array_equal(r, out) + r = np.var(d, out=out) + assert_(r is out) + assert_array_equal(r, out) + r = np.mean(d, out=out) + assert_(r is out) + assert_array_equal(r, out) + + +class TestStdVarComplex: + def test_basic(self): + A = np.array([1, 1.j, -1, -1.j]) + real_var = 1 + assert_almost_equal(np.var(A), real_var) + assert_almost_equal(np.std(A)**2, real_var) + + def test_scalars(self): + assert_equal(np.var(1j), 0) + assert_equal(np.std(1j), 0) + + +class TestCreationFuncs: + def check_function(self, func, fill_value=None): + dtypes_info = {np.dtype(tp) for tp in itertools.chain(*sctypes.values())} + keyfunc = lambda dtype: dtype.str + variable_sized = {tp for tp in dtypes_info if tp.str.endswith('0')} + dtypes = sorted(dtypes_info - variable_sized | + {np.dtype(tp.str.replace("0", str(i))) + for tp in variable_sized for i in range(1, 10)}, + key=keyfunc) + dtypes += [type(dt) for dt in sorted(dtypes_info, key=keyfunc)] + orders = {'C': 'c_contiguous', 'F': 'f_contiguous'} + ndims = 10 + + par = ((0, 1, 2), + range(ndims), + orders, + dtypes) + fill_kwarg = {} + if fill_value is not None: + fill_kwarg = {'fill_value': fill_value} + + for size, ndims, order, dtype in itertools.product(*par): + shape = ndims * [size] + + is_void = dtype is np.dtypes.VoidDType or ( + isinstance(dtype, np.dtype) and dtype.str.startswith('|V')) + + # do not fill void type + if fill_kwarg and is_void: + continue + + arr = func(shape, order=order, dtype=dtype, + **fill_kwarg) + + if isinstance(dtype, np.dtype): + assert_equal(arr.dtype, dtype) + elif isinstance(dtype, type(np.dtype)): + if dtype in (np.dtypes.StrDType, np.dtypes.BytesDType): + dtype_str = np.dtype(dtype.type).str.replace('0', '1') + assert_equal(arr.dtype, np.dtype(dtype_str)) + else: + assert_equal(arr.dtype, np.dtype(dtype.type)) + assert_(getattr(arr.flags, orders[order])) + + if fill_value is not None: + if arr.dtype.str.startswith('|S'): + val = str(fill_value) + else: + val = fill_value + assert_equal(arr, dtype.type(val)) + + def test_zeros(self): + self.check_function(np.zeros) + + def test_ones(self): + self.check_function(np.ones) + + def test_empty(self): + self.check_function(np.empty) + + def test_full(self): + self.check_function(np.full, 0) + self.check_function(np.full, 1) + + @pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") + def test_for_reference_leak(self): + # Make sure we have an object for reference + dim = 1 + beg = sys.getrefcount(dim) + np.zeros([dim] * 10) + assert_(sys.getrefcount(dim) == beg) + np.ones([dim] * 10) + assert_(sys.getrefcount(dim) == beg) + np.empty([dim] * 10) + assert_(sys.getrefcount(dim) == beg) + np.full([dim] * 10, 0) + assert_(sys.getrefcount(dim) == beg) + + @pytest.mark.skipif(sys.flags.optimize == 2, reason="Python running -OO") + @pytest.mark.xfail(IS_PYPY, reason="PyPy does not modify tp_doc") + @pytest.mark.parametrize("func", [np.empty, np.zeros, np.ones, np.full]) + def test_signatures(self, func): + sig = inspect.signature(func) + params = sig.parameters + + assert len(params) in {5, 6} + + assert 'shape' in params + assert params["shape"].kind is inspect.Parameter.POSITIONAL_OR_KEYWORD + assert params["shape"].default is inspect.Parameter.empty + + assert 'dtype' in params + assert params["dtype"].kind is inspect.Parameter.POSITIONAL_OR_KEYWORD + assert params["dtype"].default is None + + assert 'order' in params + assert params["order"].kind is inspect.Parameter.POSITIONAL_OR_KEYWORD + assert params["order"].default == "C" + + assert 'device' in params + assert params["device"].kind is inspect.Parameter.KEYWORD_ONLY + assert params["device"].default is None + + assert 'like' in params + assert params["like"].kind is inspect.Parameter.KEYWORD_ONLY + assert params["like"].default is None + + +class TestLikeFuncs: + '''Test ones_like, zeros_like, empty_like and full_like''' + + def compare_array_value(self, dz, value, fill_value): + if value is not None: + if fill_value: + # Conversion is close to what np.full_like uses + # but we may want to convert directly in the future + # which may result in errors (where this does not). + z = np.array(value).astype(dz.dtype) + assert_(np.all(dz == z)) + else: + assert_(np.all(dz == value)) + + def check_like_function(self, like_function, value, fill_value=False): + data = [ + # Array scalars + (np.array(3.), None), + (np.array(3), 'f8'), + # 1D arrays + (np.arange(6, dtype='f4'), None), + (np.arange(6), 'c16'), + # 2D C-layout arrays + (np.arange(6).reshape(2, 3), None), + (np.arange(6).reshape(3, 2), 'i1'), + # 2D F-layout arrays + (np.arange(6).reshape((2, 3), order='F'), None), + (np.arange(6).reshape((3, 2), order='F'), 'i1'), + # 3D C-layout arrays + (np.arange(24).reshape(2, 3, 4), None), + (np.arange(24).reshape(4, 3, 2), 'f4'), + # 3D F-layout arrays + (np.arange(24).reshape((2, 3, 4), order='F'), None), + (np.arange(24).reshape((4, 3, 2), order='F'), 'f4'), + # 3D non-C/F-layout arrays + (np.arange(24).reshape(2, 3, 4).swapaxes(0, 1), None), + (np.arange(24).reshape(4, 3, 2).swapaxes(0, 1), '?'), + ] + shapes = [(), (5,), (5, 6,), (5, 6, 7,)] + + if fill_value: + fill_kwarg = {'fill_value': value} + else: + fill_kwarg = {} + for d, dtype in data: + # default (K) order, dtype + dz = like_function(d, dtype=dtype, **fill_kwarg) + assert_equal(dz.shape, d.shape) + assert_equal(np.array(dz.strides) * d.dtype.itemsize, + np.array(d.strides) * dz.dtype.itemsize) + assert_equal(d.flags.c_contiguous, dz.flags.c_contiguous) + assert_equal(d.flags.f_contiguous, dz.flags.f_contiguous) + if dtype is None: + assert_equal(dz.dtype, d.dtype) + else: + assert_equal(dz.dtype, np.dtype(dtype)) + self.compare_array_value(dz, value, fill_value) + + # C order, default dtype + dz = like_function(d, order='C', dtype=dtype, **fill_kwarg) + assert_equal(dz.shape, d.shape) + assert_(dz.flags.c_contiguous) + if dtype is None: + assert_equal(dz.dtype, d.dtype) + else: + assert_equal(dz.dtype, np.dtype(dtype)) + self.compare_array_value(dz, value, fill_value) + + # F order, default dtype + dz = like_function(d, order='F', dtype=dtype, **fill_kwarg) + assert_equal(dz.shape, d.shape) + assert_(dz.flags.f_contiguous) + if dtype is None: + assert_equal(dz.dtype, d.dtype) + else: + assert_equal(dz.dtype, np.dtype(dtype)) + self.compare_array_value(dz, value, fill_value) + + # A order + dz = like_function(d, order='A', dtype=dtype, **fill_kwarg) + assert_equal(dz.shape, d.shape) + if d.flags.f_contiguous: + assert_(dz.flags.f_contiguous) + else: + assert_(dz.flags.c_contiguous) + if dtype is None: + assert_equal(dz.dtype, d.dtype) + else: + assert_equal(dz.dtype, np.dtype(dtype)) + self.compare_array_value(dz, value, fill_value) + + # Test the 'shape' parameter + for s in shapes: + for o in 'CFA': + sz = like_function(d, dtype=dtype, shape=s, order=o, + **fill_kwarg) + assert_equal(sz.shape, s) + if dtype is None: + assert_equal(sz.dtype, d.dtype) + else: + assert_equal(sz.dtype, np.dtype(dtype)) + if o == 'C' or (o == 'A' and d.flags.c_contiguous): + assert_(sz.flags.c_contiguous) + elif o == 'F' or (o == 'A' and d.flags.f_contiguous): + assert_(sz.flags.f_contiguous) + self.compare_array_value(sz, value, fill_value) + + if (d.ndim != len(s)): + assert_equal(np.argsort(like_function(d, dtype=dtype, + shape=s, order='K', + **fill_kwarg).strides), + np.argsort(np.empty(s, dtype=dtype, + order='C').strides)) + else: + assert_equal(np.argsort(like_function(d, dtype=dtype, + shape=s, order='K', + **fill_kwarg).strides), + np.argsort(d.strides)) + + # Test the 'subok' parameter + class MyNDArray(np.ndarray): + pass + + a = np.array([[1, 2], [3, 4]]).view(MyNDArray) + + b = like_function(a, **fill_kwarg) + assert_(type(b) is MyNDArray) + + b = like_function(a, subok=False, **fill_kwarg) + assert_(type(b) is not MyNDArray) + + # Test invalid dtype + with assert_raises(TypeError): + a = np.array(b"abc") + like_function(a, dtype="S-1", **fill_kwarg) + + def test_ones_like(self): + self.check_like_function(np.ones_like, 1) + + def test_zeros_like(self): + self.check_like_function(np.zeros_like, 0) + + def test_empty_like(self): + self.check_like_function(np.empty_like, None) + + def test_filled_like(self): + self.check_like_function(np.full_like, 0, True) + self.check_like_function(np.full_like, 1, True) + # Large integers may overflow, but using int64 is OK (casts) + # see also gh-27075 + with pytest.raises(OverflowError): + np.full_like(np.ones(3, dtype=np.int8), 1000) + self.check_like_function(np.full_like, np.int64(1000), True) + self.check_like_function(np.full_like, 123.456, True) + # Inf to integer casts cause invalid-value errors: ignore them. + with np.errstate(invalid="ignore"): + self.check_like_function(np.full_like, np.inf, True) + + @pytest.mark.parametrize('likefunc', [np.empty_like, np.full_like, + np.zeros_like, np.ones_like]) + @pytest.mark.parametrize('dtype', [str, bytes]) + def test_dtype_str_bytes(self, likefunc, dtype): + # Regression test for gh-19860 + a = np.arange(16).reshape(2, 8) + b = a[:, ::2] # Ensure b is not contiguous. + kwargs = {'fill_value': ''} if likefunc == np.full_like else {} + result = likefunc(b, dtype=dtype, **kwargs) + if dtype == str: + assert result.strides == (16, 4) + else: + # dtype is bytes + assert result.strides == (4, 1) + + +class TestCorrelate: + def _setup(self, dt): + self.x = np.array([1, 2, 3, 4, 5], dtype=dt) + self.xs = np.arange(1, 20)[::3] + self.y = np.array([-1, -2, -3], dtype=dt) + self.z1 = np.array([-3., -8., -14., -20., -26., -14., -5.], dtype=dt) + self.z1_4 = np.array([-2., -5., -8., -11., -14., -5.], dtype=dt) + self.z1r = np.array([-15., -22., -22., -16., -10., -4., -1.], dtype=dt) + self.z2 = np.array([-5., -14., -26., -20., -14., -8., -3.], dtype=dt) + self.z2r = np.array([-1., -4., -10., -16., -22., -22., -15.], dtype=dt) + self.zs = np.array([-3., -14., -30., -48., -66., -84., + -102., -54., -19.], dtype=dt) + + def test_float(self): + self._setup(float) + z = np.correlate(self.x, self.y, 'full') + assert_array_almost_equal(z, self.z1) + z = np.correlate(self.x, self.y[:-1], 'full') + assert_array_almost_equal(z, self.z1_4) + z = np.correlate(self.y, self.x, 'full') + assert_array_almost_equal(z, self.z2) + z = np.correlate(self.x[::-1], self.y, 'full') + assert_array_almost_equal(z, self.z1r) + z = np.correlate(self.y, self.x[::-1], 'full') + assert_array_almost_equal(z, self.z2r) + z = np.correlate(self.xs, self.y, 'full') + assert_array_almost_equal(z, self.zs) + + def test_object(self): + self._setup(Decimal) + z = np.correlate(self.x, self.y, 'full') + assert_array_almost_equal(z, self.z1) + z = np.correlate(self.y, self.x, 'full') + assert_array_almost_equal(z, self.z2) + + def test_no_overwrite(self): + d = np.ones(100) + k = np.ones(3) + np.correlate(d, k) + assert_array_equal(d, np.ones(100)) + assert_array_equal(k, np.ones(3)) + + def test_complex(self): + x = np.array([1, 2, 3, 4 + 1j], dtype=complex) + y = np.array([-1, -2j, 3 + 1j], dtype=complex) + r_z = np.array([3 - 1j, 6, 8 + 1j, 11 + 5j, -5 + 8j, -4 - 1j], dtype=complex) + r_z = r_z[::-1].conjugate() + z = np.correlate(y, x, mode='full') + assert_array_almost_equal(z, r_z) + + def test_zero_size(self): + with pytest.raises(ValueError): + np.correlate(np.array([]), np.ones(1000), mode='full') + with pytest.raises(ValueError): + np.correlate(np.ones(1000), np.array([]), mode='full') + + def test_mode(self): + d = np.ones(100) + k = np.ones(3) + default_mode = np.correlate(d, k, mode='valid') + with assert_raises(ValueError): + np.correlate(d, k, mode='v') + # integer mode + with assert_raises(ValueError): + np.correlate(d, k, mode=-1) + # assert_array_equal(np.correlate(d, k, mode=), default_mode) + # illegal arguments + with assert_raises(TypeError): + np.correlate(d, k, mode=None) + + +class TestConvolve: + def test_object(self): + d = [1.] * 100 + k = [1.] * 3 + assert_array_almost_equal(np.convolve(d, k)[2:-2], np.full(98, 3)) + + def test_no_overwrite(self): + d = np.ones(100) + k = np.ones(3) + np.convolve(d, k) + assert_array_equal(d, np.ones(100)) + assert_array_equal(k, np.ones(3)) + + def test_mode(self): + d = np.ones(100) + k = np.ones(3) + default_mode = np.convolve(d, k, mode='full') + with assert_raises(ValueError): + np.convolve(d, k, mode='f') + # integer mode + with assert_raises(ValueError): + np.convolve(d, k, mode=-1) + assert_array_equal(np.convolve(d, k, mode=2), default_mode) + # illegal arguments + with assert_raises(TypeError): + np.convolve(d, k, mode=None) + + def test_convolve_empty_input_error_message(self): + """ + Test that convolve raises the correct error message when inputs are empty. + Regression test for gh-30272 (variable swapping bug). + """ + with pytest.raises(ValueError, match="a cannot be empty"): + np.convolve(np.array([]), np.array([1, 2])) + + with pytest.raises(ValueError, match="v cannot be empty"): + np.convolve(np.array([1, 2]), np.array([])) + +class TestArgwhere: + + @pytest.mark.parametrize('nd', [0, 1, 2]) + def test_nd(self, nd): + # get an nd array with multiple elements in every dimension + x = np.empty((2,) * nd, bool) + + # none + x[...] = False + assert_equal(np.argwhere(x).shape, (0, nd)) + + # only one + x[...] = False + x.flat[0] = True + assert_equal(np.argwhere(x).shape, (1, nd)) + + # all but one + x[...] = True + x.flat[0] = False + assert_equal(np.argwhere(x).shape, (x.size - 1, nd)) + + # all + x[...] = True + assert_equal(np.argwhere(x).shape, (x.size, nd)) + + def test_2D(self): + x = np.arange(6).reshape((2, 3)) + assert_array_equal(np.argwhere(x > 1), + [[0, 2], + [1, 0], + [1, 1], + [1, 2]]) + + def test_list(self): + assert_equal(np.argwhere([4, 0, 2, 1, 3]), [[0], [2], [3], [4]]) + + +class TestRoll: + def test_roll1d(self): + x = np.arange(10) + xr = np.roll(x, 2) + assert_equal(xr, np.array([8, 9, 0, 1, 2, 3, 4, 5, 6, 7])) + + def test_roll2d(self): + x2 = np.reshape(np.arange(10), (2, 5)) + x2r = np.roll(x2, 1) + assert_equal(x2r, np.array([[9, 0, 1, 2, 3], [4, 5, 6, 7, 8]])) + + x2r = np.roll(x2, 1, axis=0) + assert_equal(x2r, np.array([[5, 6, 7, 8, 9], [0, 1, 2, 3, 4]])) + + x2r = np.roll(x2, 1, axis=1) + assert_equal(x2r, np.array([[4, 0, 1, 2, 3], [9, 5, 6, 7, 8]])) + + # Roll multiple axes at once. + x2r = np.roll(x2, 1, axis=(0, 1)) + assert_equal(x2r, np.array([[9, 5, 6, 7, 8], [4, 0, 1, 2, 3]])) + + x2r = np.roll(x2, (1, 0), axis=(0, 1)) + assert_equal(x2r, np.array([[5, 6, 7, 8, 9], [0, 1, 2, 3, 4]])) + + x2r = np.roll(x2, (-1, 0), axis=(0, 1)) + assert_equal(x2r, np.array([[5, 6, 7, 8, 9], [0, 1, 2, 3, 4]])) + + x2r = np.roll(x2, (0, 1), axis=(0, 1)) + assert_equal(x2r, np.array([[4, 0, 1, 2, 3], [9, 5, 6, 7, 8]])) + + x2r = np.roll(x2, (0, -1), axis=(0, 1)) + assert_equal(x2r, np.array([[1, 2, 3, 4, 0], [6, 7, 8, 9, 5]])) + + x2r = np.roll(x2, (1, 1), axis=(0, 1)) + assert_equal(x2r, np.array([[9, 5, 6, 7, 8], [4, 0, 1, 2, 3]])) + + x2r = np.roll(x2, (-1, -1), axis=(0, 1)) + assert_equal(x2r, np.array([[6, 7, 8, 9, 5], [1, 2, 3, 4, 0]])) + + # Roll the same axis multiple times. + x2r = np.roll(x2, 1, axis=(0, 0)) + assert_equal(x2r, np.array([[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]])) + + x2r = np.roll(x2, 1, axis=(1, 1)) + assert_equal(x2r, np.array([[3, 4, 0, 1, 2], [8, 9, 5, 6, 7]])) + + # Roll more than one turn in either direction. + x2r = np.roll(x2, 6, axis=1) + assert_equal(x2r, np.array([[4, 0, 1, 2, 3], [9, 5, 6, 7, 8]])) + + x2r = np.roll(x2, -4, axis=1) + assert_equal(x2r, np.array([[4, 0, 1, 2, 3], [9, 5, 6, 7, 8]])) + + def test_roll_empty(self): + x = np.array([]) + assert_equal(np.roll(x, 1), np.array([])) + + def test_roll_unsigned_shift(self): + x = np.arange(4) + shift = np.uint16(2) + assert_equal(np.roll(x, shift), np.roll(x, 2)) + + shift = np.uint64(2**63 + 2) + assert_equal(np.roll(x, shift), np.roll(x, 2)) + + def test_roll_big_int(self): + x = np.arange(4) + assert_equal(np.roll(x, 2**100), x) + + +class TestRollaxis: + + # expected shape indexed by (axis, start) for array of + # shape (1, 2, 3, 4) + tgtshape = {(0, 0): (1, 2, 3, 4), (0, 1): (1, 2, 3, 4), + (0, 2): (2, 1, 3, 4), (0, 3): (2, 3, 1, 4), + (0, 4): (2, 3, 4, 1), + (1, 0): (2, 1, 3, 4), (1, 1): (1, 2, 3, 4), + (1, 2): (1, 2, 3, 4), (1, 3): (1, 3, 2, 4), + (1, 4): (1, 3, 4, 2), + (2, 0): (3, 1, 2, 4), (2, 1): (1, 3, 2, 4), + (2, 2): (1, 2, 3, 4), (2, 3): (1, 2, 3, 4), + (2, 4): (1, 2, 4, 3), + (3, 0): (4, 1, 2, 3), (3, 1): (1, 4, 2, 3), + (3, 2): (1, 2, 4, 3), (3, 3): (1, 2, 3, 4), + (3, 4): (1, 2, 3, 4)} + + def test_exceptions(self): + a = np.arange(1 * 2 * 3 * 4).reshape(1, 2, 3, 4) + assert_raises(AxisError, np.rollaxis, a, -5, 0) + assert_raises(AxisError, np.rollaxis, a, 0, -5) + assert_raises(AxisError, np.rollaxis, a, 4, 0) + assert_raises(AxisError, np.rollaxis, a, 0, 5) + + def test_results(self): + a = np.arange(1 * 2 * 3 * 4).reshape(1, 2, 3, 4).copy() + aind = np.indices(a.shape) + assert_(a.flags['OWNDATA']) + for (i, j) in self.tgtshape: + # positive axis, positive start + res = np.rollaxis(a, axis=i, start=j) + i0, i1, i2, i3 = aind[np.array(res.shape) - 1] + assert_(np.all(res[i0, i1, i2, i3] == a)) + assert_(res.shape == self.tgtshape[(i, j)], str((i, j))) + assert_(not res.flags['OWNDATA']) + + # negative axis, positive start + ip = i + 1 + res = np.rollaxis(a, axis=-ip, start=j) + i0, i1, i2, i3 = aind[np.array(res.shape) - 1] + assert_(np.all(res[i0, i1, i2, i3] == a)) + assert_(res.shape == self.tgtshape[(4 - ip, j)]) + assert_(not res.flags['OWNDATA']) + + # positive axis, negative start + jp = j + 1 if j < 4 else j + res = np.rollaxis(a, axis=i, start=-jp) + i0, i1, i2, i3 = aind[np.array(res.shape) - 1] + assert_(np.all(res[i0, i1, i2, i3] == a)) + assert_(res.shape == self.tgtshape[(i, 4 - jp)]) + assert_(not res.flags['OWNDATA']) + + # negative axis, negative start + ip = i + 1 + jp = j + 1 if j < 4 else j + res = np.rollaxis(a, axis=-ip, start=-jp) + i0, i1, i2, i3 = aind[np.array(res.shape) - 1] + assert_(np.all(res[i0, i1, i2, i3] == a)) + assert_(res.shape == self.tgtshape[(4 - ip, 4 - jp)]) + assert_(not res.flags['OWNDATA']) + + +class TestMoveaxis: + def test_move_to_end(self): + x = np.random.randn(5, 6, 7) + for source, expected in [(0, (6, 7, 5)), + (1, (5, 7, 6)), + (2, (5, 6, 7)), + (-1, (5, 6, 7))]: + actual = np.moveaxis(x, source, -1).shape + assert_(actual, expected) + + def test_move_new_position(self): + x = np.random.randn(1, 2, 3, 4) + for source, destination, expected in [ + (0, 1, (2, 1, 3, 4)), + (1, 2, (1, 3, 2, 4)), + (1, -1, (1, 3, 4, 2)), + ]: + actual = np.moveaxis(x, source, destination).shape + assert_(actual, expected) + + def test_preserve_order(self): + x = np.zeros((1, 2, 3, 4)) + for source, destination in [ + (0, 0), + (3, -1), + (-1, 3), + ([0, -1], [0, -1]), + ([2, 0], [2, 0]), + (range(4), range(4)), + ]: + actual = np.moveaxis(x, source, destination).shape + assert_(actual, (1, 2, 3, 4)) + + def test_move_multiples(self): + x = np.zeros((0, 1, 2, 3)) + for source, destination, expected in [ + ([0, 1], [2, 3], (2, 3, 0, 1)), + ([2, 3], [0, 1], (2, 3, 0, 1)), + ([0, 1, 2], [2, 3, 0], (2, 3, 0, 1)), + ([3, 0], [1, 0], (0, 3, 1, 2)), + ([0, 3], [0, 1], (0, 3, 1, 2)), + ]: + actual = np.moveaxis(x, source, destination).shape + assert_(actual, expected) + + def test_errors(self): + x = np.random.randn(1, 2, 3) + assert_raises_regex(AxisError, 'source.*out of bounds', + np.moveaxis, x, 3, 0) + assert_raises_regex(AxisError, 'source.*out of bounds', + np.moveaxis, x, -4, 0) + assert_raises_regex(AxisError, 'destination.*out of bounds', + np.moveaxis, x, 0, 5) + assert_raises_regex(ValueError, 'repeated axis in `source`', + np.moveaxis, x, [0, 0], [0, 1]) + assert_raises_regex(ValueError, 'repeated axis in `destination`', + np.moveaxis, x, [0, 1], [1, 1]) + assert_raises_regex(ValueError, 'must have the same number', + np.moveaxis, x, 0, [0, 1]) + assert_raises_regex(ValueError, 'must have the same number', + np.moveaxis, x, [0, 1], [0]) + + def test_array_likes(self): + x = np.ma.zeros((1, 2, 3)) + result = np.moveaxis(x, 0, 0) + assert_(x.shape, result.shape) + assert_(isinstance(result, np.ma.MaskedArray)) + + x = [1, 2, 3] + result = np.moveaxis(x, 0, 0) + assert_(x, list(result)) + assert_(isinstance(result, np.ndarray)) + + +class TestCross: + @pytest.mark.filterwarnings( + "ignore:.*2-dimensional vectors.*:DeprecationWarning" + ) + def test_2x2(self): + u = [1, 2] + v = [3, 4] + z = -2 + cp = np.cross(u, v) + assert_equal(cp, z) + cp = np.cross(v, u) + assert_equal(cp, -z) + + @pytest.mark.filterwarnings( + "ignore:.*2-dimensional vectors.*:DeprecationWarning" + ) + def test_2x3(self): + u = [1, 2] + v = [3, 4, 5] + z = np.array([10, -5, -2]) + cp = np.cross(u, v) + assert_equal(cp, z) + cp = np.cross(v, u) + assert_equal(cp, -z) + + def test_3x3(self): + u = [1, 2, 3] + v = [4, 5, 6] + z = np.array([-3, 6, -3]) + cp = np.cross(u, v) + assert_equal(cp, z) + cp = np.cross(v, u) + assert_equal(cp, -z) + + @pytest.mark.filterwarnings( + "ignore:.*2-dimensional vectors.*:DeprecationWarning" + ) + def test_broadcasting(self): + # Ticket #2624 (Trac #2032) + u = np.tile([1, 2], (11, 1)) + v = np.tile([3, 4], (11, 1)) + z = -2 + assert_equal(np.cross(u, v), z) + assert_equal(np.cross(v, u), -z) + assert_equal(np.cross(u, u), 0) + + u = np.tile([1, 2], (11, 1)).T + v = np.tile([3, 4, 5], (11, 1)) + z = np.tile([10, -5, -2], (11, 1)) + assert_equal(np.cross(u, v, axisa=0), z) + assert_equal(np.cross(v, u.T), -z) + assert_equal(np.cross(v, v), 0) + + u = np.tile([1, 2, 3], (11, 1)).T + v = np.tile([3, 4], (11, 1)).T + z = np.tile([-12, 9, -2], (11, 1)) + assert_equal(np.cross(u, v, axisa=0, axisb=0), z) + assert_equal(np.cross(v.T, u.T), -z) + assert_equal(np.cross(u.T, u.T), 0) + + u = np.tile([1, 2, 3], (5, 1)) + v = np.tile([4, 5, 6], (5, 1)).T + z = np.tile([-3, 6, -3], (5, 1)) + assert_equal(np.cross(u, v, axisb=0), z) + assert_equal(np.cross(v.T, u), -z) + assert_equal(np.cross(u, u), 0) + + @pytest.mark.filterwarnings( + "ignore:.*2-dimensional vectors.*:DeprecationWarning" + ) + def test_broadcasting_shapes(self): + u = np.ones((2, 1, 3)) + v = np.ones((5, 3)) + assert_equal(np.cross(u, v).shape, (2, 5, 3)) + u = np.ones((10, 3, 5)) + v = np.ones((2, 5)) + assert_equal(np.cross(u, v, axisa=1, axisb=0).shape, (10, 5, 3)) + assert_raises(AxisError, np.cross, u, v, axisa=1, axisb=2) + assert_raises(AxisError, np.cross, u, v, axisa=3, axisb=0) + u = np.ones((10, 3, 5, 7)) + v = np.ones((5, 7, 2)) + assert_equal(np.cross(u, v, axisa=1, axisc=2).shape, (10, 5, 3, 7)) + assert_raises(AxisError, np.cross, u, v, axisa=-5, axisb=2) + assert_raises(AxisError, np.cross, u, v, axisa=1, axisb=-4) + # gh-5885 + u = np.ones((3, 4, 2)) + for axisc in range(-2, 2): + assert_equal(np.cross(u, u, axisc=axisc).shape, (3, 4)) + + def test_uint8_int32_mixed_dtypes(self): + # regression test for gh-19138 + u = np.array([[195, 8, 9]], np.uint8) + v = np.array([250, 166, 68], np.int32) + z = np.array([[950, 11010, -30370]], dtype=np.int32) + assert_equal(np.cross(v, u), z) + assert_equal(np.cross(u, v), -z) + + @pytest.mark.parametrize("a, b", [(0, [1, 2]), ([1, 2], 3)]) + def test_zero_dimension(self, a, b): + with pytest.raises(ValueError) as exc: + np.cross(a, b) + assert "At least one array has zero dimension" in str(exc.value) + + +def test_outer_out_param(): + arr1 = np.ones((5,)) + arr2 = np.ones((2,)) + arr3 = np.linspace(-2, 2, 5) + out1 = np.ndarray(shape=(5, 5)) + out2 = np.ndarray(shape=(2, 5)) + res1 = np.outer(arr1, arr3, out1) + assert_equal(res1, out1) + assert_equal(np.outer(arr2, arr3, out2), out2) + + +class TestIndices: + + def test_simple(self): + [x, y] = np.indices((4, 3)) + assert_array_equal(x, np.array([[0, 0, 0], + [1, 1, 1], + [2, 2, 2], + [3, 3, 3]])) + assert_array_equal(y, np.array([[0, 1, 2], + [0, 1, 2], + [0, 1, 2], + [0, 1, 2]])) + + def test_single_input(self): + [x] = np.indices((4,)) + assert_array_equal(x, np.array([0, 1, 2, 3])) + + [x] = np.indices((4,), sparse=True) + assert_array_equal(x, np.array([0, 1, 2, 3])) + + def test_scalar_input(self): + assert_array_equal([], np.indices(())) + assert_array_equal([], np.indices((), sparse=True)) + assert_array_equal([[]], np.indices((0,))) + assert_array_equal([[]], np.indices((0,), sparse=True)) + + def test_sparse(self): + [x, y] = np.indices((4, 3), sparse=True) + assert_array_equal(x, np.array([[0], [1], [2], [3]])) + assert_array_equal(y, np.array([[0, 1, 2]])) + + @pytest.mark.parametrize("dtype", [np.int32, np.int64, np.float32, np.float64]) + @pytest.mark.parametrize("dims", [(), (0,), (4, 3)]) + def test_return_type(self, dtype, dims): + inds = np.indices(dims, dtype=dtype) + assert_(inds.dtype == dtype) + + for arr in np.indices(dims, dtype=dtype, sparse=True): + assert_(arr.dtype == dtype) + + +class TestRequire: + flag_names = ['C', 'C_CONTIGUOUS', 'CONTIGUOUS', + 'F', 'F_CONTIGUOUS', 'FORTRAN', + 'A', 'ALIGNED', + 'W', 'WRITEABLE', + 'O', 'OWNDATA'] + + def generate_all_false(self, dtype): + arr = np.zeros((2, 2), [('junk', 'i1'), ('a', dtype)]) + arr.setflags(write=False) + a = arr['a'] + assert_(not a.flags['C']) + assert_(not a.flags['F']) + assert_(not a.flags['O']) + assert_(not a.flags['W']) + assert_(not a.flags['A']) + return a + + def set_and_check_flag(self, flag, dtype, arr): + if dtype is None: + dtype = arr.dtype + b = np.require(arr, dtype, [flag]) + assert_(b.flags[flag]) + assert_(b.dtype == dtype) + + # a further call to np.require ought to return the same array + # unless OWNDATA is specified. + c = np.require(b, None, [flag]) + if flag[0] != 'O': + assert_(c is b) + else: + assert_(c.flags[flag]) + + def test_require_each(self): + + id = ['f8', 'i4'] + fd = [None, 'f8', 'c16'] + for idtype, fdtype, flag in itertools.product(id, fd, self.flag_names): + a = self.generate_all_false(idtype) + self.set_and_check_flag(flag, fdtype, a) + + def test_unknown_requirement(self): + a = self.generate_all_false('f8') + assert_raises(KeyError, np.require, a, None, 'Q') + + def test_non_array_input(self): + a = np.require([1, 2, 3, 4], 'i4', ['C', 'A', 'O']) + assert_(a.flags['O']) + assert_(a.flags['C']) + assert_(a.flags['A']) + assert_(a.dtype == 'i4') + assert_equal(a, [1, 2, 3, 4]) + + def test_C_and_F_simul(self): + a = self.generate_all_false('f8') + assert_raises(ValueError, np.require, a, None, ['C', 'F']) + + def test_ensure_array(self): + class ArraySubclass(np.ndarray): + pass + + a = ArraySubclass((2, 2)) + b = np.require(a, None, ['E']) + assert_(type(b) is np.ndarray) + + def test_preserve_subtype(self): + class ArraySubclass(np.ndarray): + pass + + for flag in self.flag_names: + a = ArraySubclass((2, 2)) + self.set_and_check_flag(flag, None, a) + + +class TestBroadcast: + def test_broadcast_in_args(self): + # gh-5881 + arrs = [np.empty((6, 7)), np.empty((5, 6, 1)), np.empty((7,)), + np.empty((5, 1, 7))] + mits = [np.broadcast(*arrs), + np.broadcast(np.broadcast(*arrs[:0]), np.broadcast(*arrs[0:])), + np.broadcast(np.broadcast(*arrs[:1]), np.broadcast(*arrs[1:])), + np.broadcast(np.broadcast(*arrs[:2]), np.broadcast(*arrs[2:])), + np.broadcast(arrs[0], np.broadcast(*arrs[1:-1]), arrs[-1])] + for mit in mits: + assert_equal(mit.shape, (5, 6, 7)) + assert_equal(mit.ndim, 3) + assert_equal(mit.nd, 3) + assert_equal(mit.numiter, 4) + for a, ia in zip(arrs, mit.iters): + assert_(a is ia.base) + + def test_broadcast_single_arg(self): + # gh-6899 + arrs = [np.empty((5, 6, 7))] + mit = np.broadcast(*arrs) + assert_equal(mit.shape, (5, 6, 7)) + assert_equal(mit.ndim, 3) + assert_equal(mit.nd, 3) + assert_equal(mit.numiter, 1) + assert_(arrs[0] is mit.iters[0].base) + + def test_number_of_arguments(self): + arr = np.empty((5,)) + for j in range(70): + arrs = [arr] * j + if j > 64: + assert_raises(ValueError, np.broadcast, *arrs) + else: + mit = np.broadcast(*arrs) + assert_equal(mit.numiter, j) + + def test_broadcast_error_kwargs(self): + # gh-13455 + arrs = [np.empty((5, 6, 7))] + mit = np.broadcast(*arrs) + mit2 = np.broadcast(*arrs, **{}) # noqa: PIE804 + assert_equal(mit.shape, mit2.shape) + assert_equal(mit.ndim, mit2.ndim) + assert_equal(mit.nd, mit2.nd) + assert_equal(mit.numiter, mit2.numiter) + assert_(mit.iters[0].base is mit2.iters[0].base) + + assert_raises(ValueError, np.broadcast, 1, x=1) + + def test_shape_mismatch_error_message(self): + with pytest.raises(ValueError, match=r"arg 0 with shape \(1, 3\) and " + r"arg 2 with shape \(2,\)"): + np.broadcast([[1, 2, 3]], [[4], [5]], [6, 7]) + + @pytest.mark.skipif(sys.flags.optimize == 2, reason="Python running -OO") + @pytest.mark.xfail(IS_PYPY, reason="PyPy does not modify tp_doc") + def test_signatures(self): + sig_new = inspect.signature(np.broadcast) + assert len(sig_new.parameters) == 1 + assert "arrays" in sig_new.parameters + assert sig_new.parameters["arrays"].kind == inspect.Parameter.VAR_POSITIONAL + + sig_reset = inspect.signature(np.broadcast.reset) + assert len(sig_reset.parameters) == 1 + assert "self" in sig_reset.parameters + assert sig_reset.parameters["self"].kind == inspect.Parameter.POSITIONAL_ONLY + + +class TestKeepdims: + + class sub_array(np.ndarray): + def sum(self, axis=None, dtype=None, out=None): + return np.ndarray.sum(self, axis, dtype, out, keepdims=True) + + def test_raise(self): + sub_class = self.sub_array + x = np.arange(30).view(sub_class) + assert_raises(TypeError, np.sum, x, keepdims=True) + + +class TestTensordot: + + def test_rejects_duplicate_axes(self): + a = np.ones((2, 3, 3)) + b = np.ones((3, 3, 4)) + with pytest.raises(ValueError): + np.tensordot(a, b, axes=([1, 1], [0, 0])) + + def test_zero_dimension(self): + # Test resolution to issue #5663 + a = np.ndarray((3, 0)) + b = np.ndarray((0, 4)) + td = np.tensordot(a, b, (1, 0)) + assert_array_equal(td, np.dot(a, b)) + assert_array_equal(td, np.einsum('ij,jk', a, b)) + + def test_zero_dimensional(self): + # gh-12130 + arr_0d = np.array(1) + # contracting no axes is well defined + ret = np.tensordot(arr_0d, arr_0d, ([], [])) + assert_array_equal(ret, arr_0d) + + +class TestAsType: + + def test_astype(self): + data = [[1, 2], [3, 4]] + actual = np.astype( + np.array(data, dtype=np.int64), np.uint32 + ) + expected = np.array(data, dtype=np.uint32) + + assert_array_equal(actual, expected) + assert_equal(actual.dtype, expected.dtype) + + assert np.shares_memory( + actual, np.astype(actual, actual.dtype, copy=False) + ) + + actual = np.astype(np.int64(10), np.float64) + expected = np.float64(10) + assert_equal(actual, expected) + assert_equal(actual.dtype, expected.dtype) + + with pytest.raises(TypeError, match="Input should be a NumPy array"): + np.astype(data, np.float64) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_numerictypes.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_numerictypes.py new file mode 100644 index 0000000000000000000000000000000000000000..5763a964c41d2bda946f895337aab02dca029eb8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_numerictypes.py @@ -0,0 +1,650 @@ +import itertools +import sys + +import pytest + +import numpy as np +import numpy._core.numerictypes as nt +from numpy._core.numerictypes import issctype, maximum_sctype, sctype2char, sctypes +from numpy.testing import ( + IS_PYPY, + assert_, + assert_equal, + assert_raises, + assert_raises_regex, +) + +# This is the structure of the table used for plain objects: +# +# +-+-+-+ +# |x|y|z| +# +-+-+-+ + +# Structure of a plain array description: +Pdescr = [ + ('x', 'i4', (2,)), + ('y', 'f8', (2, 2)), + ('z', 'u1')] + +# A plain list of tuples with values for testing: +PbufferT = [ + # x y z + ([3, 2], [[6., 4.], [6., 4.]], 8), + ([4, 3], [[7., 5.], [7., 5.]], 9), + ] + + +# This is the structure of the table used for nested objects (DON'T PANIC!): +# +# +-+---------------------------------+-----+----------+-+-+ +# |x|Info |color|info |y|z| +# | +-----+--+----------------+----+--+ +----+-----+ | | +# | |value|y2|Info2 |name|z2| |Name|Value| | | +# | | | +----+-----+--+--+ | | | | | | | +# | | | |name|value|y3|z3| | | | | | | | +# +-+-----+--+----+-----+--+--+----+--+-----+----+-----+-+-+ +# + +# The corresponding nested array description: +Ndescr = [ + ('x', 'i4', (2,)), + ('Info', [ + ('value', 'c16'), + ('y2', 'f8'), + ('Info2', [ + ('name', 'S2'), + ('value', 'c16', (2,)), + ('y3', 'f8', (2,)), + ('z3', 'u4', (2,))]), + ('name', 'S2'), + ('z2', 'b1')]), + ('color', 'S2'), + ('info', [ + ('Name', 'U8'), + ('Value', 'c16')]), + ('y', 'f8', (2, 2)), + ('z', 'u1')] + +NbufferT = [ + # x Info color info y z + # value y2 Info2 name z2 Name Value + # name value y3 z3 + ([3, 2], (6j, 6., (b'nn', [6j, 4j], [6., 4.], [1, 2]), b'NN', True), + b'cc', ('NN', 6j), [[6., 4.], [6., 4.]], 8), + ([4, 3], (7j, 7., (b'oo', [7j, 5j], [7., 5.], [2, 1]), b'OO', False), + b'dd', ('OO', 7j), [[7., 5.], [7., 5.]], 9), + ] + + +byteorder = {'little': '<', 'big': '>'}[sys.byteorder] + +def normalize_descr(descr): + "Normalize a description adding the platform byteorder." + + out = [] + for item in descr: + dtype = item[1] + if isinstance(dtype, str): + if dtype[0] not in ['|', '<', '>']: + onebyte = dtype[1:] == "1" + if onebyte or dtype[0] in ['S', 'V', 'b']: + dtype = "|" + dtype + else: + dtype = byteorder + dtype + if len(item) > 2 and np.prod(item[2]) > 1: + nitem = (item[0], dtype, item[2]) + else: + nitem = (item[0], dtype) + out.append(nitem) + elif isinstance(dtype, list): + l = normalize_descr(dtype) + out.append((item[0], l)) + else: + raise ValueError(f"Expected a str or list and got {type(item)}") + return out + + +############################################################ +# Creation tests +############################################################ + +class CreateZeros: + """Check the creation of heterogeneous arrays zero-valued""" + + def test_zeros0D(self): + """Check creation of 0-dimensional objects""" + h = np.zeros((), dtype=self._descr) + assert_(normalize_descr(self._descr) == h.dtype.descr) + assert_(h.dtype.fields['x'][0].name[:4] == 'void') + assert_(h.dtype.fields['x'][0].char == 'V') + assert_(h.dtype.fields['x'][0].type == np.void) + # A small check that data is ok + assert_equal(h['z'], np.zeros((), dtype='u1')) + + def test_zerosSD(self): + """Check creation of single-dimensional objects""" + h = np.zeros((2,), dtype=self._descr) + assert_(normalize_descr(self._descr) == h.dtype.descr) + assert_(h.dtype['y'].name[:4] == 'void') + assert_(h.dtype['y'].char == 'V') + assert_(h.dtype['y'].type == np.void) + # A small check that data is ok + assert_equal(h['z'], np.zeros((2,), dtype='u1')) + + def test_zerosMD(self): + """Check creation of multi-dimensional objects""" + h = np.zeros((2, 3), dtype=self._descr) + assert_(normalize_descr(self._descr) == h.dtype.descr) + assert_(h.dtype['z'].name == 'uint8') + assert_(h.dtype['z'].char == 'B') + assert_(h.dtype['z'].type == np.uint8) + # A small check that data is ok + assert_equal(h['z'], np.zeros((2, 3), dtype='u1')) + + +class TestCreateZerosPlain(CreateZeros): + """Check the creation of heterogeneous arrays zero-valued (plain)""" + _descr = Pdescr + +class TestCreateZerosNested(CreateZeros): + """Check the creation of heterogeneous arrays zero-valued (nested)""" + _descr = Ndescr + + +class CreateValues: + """Check the creation of heterogeneous arrays with values""" + + def test_tuple(self): + """Check creation from tuples""" + h = np.array(self._buffer, dtype=self._descr) + assert_(normalize_descr(self._descr) == h.dtype.descr) + if self.multiple_rows: + assert_(h.shape == (2,)) + else: + assert_(h.shape == ()) + + def test_list_of_tuple(self): + """Check creation from list of tuples""" + h = np.array([self._buffer], dtype=self._descr) + assert_(normalize_descr(self._descr) == h.dtype.descr) + if self.multiple_rows: + assert_(h.shape == (1, 2)) + else: + assert_(h.shape == (1,)) + + def test_list_of_list_of_tuple(self): + """Check creation from list of list of tuples""" + h = np.array([[self._buffer]], dtype=self._descr) + assert_(normalize_descr(self._descr) == h.dtype.descr) + if self.multiple_rows: + assert_(h.shape == (1, 1, 2)) + else: + assert_(h.shape == (1, 1)) + + +class TestCreateValuesPlainSingle(CreateValues): + """Check the creation of heterogeneous arrays (plain, single row)""" + _descr = Pdescr + multiple_rows = 0 + _buffer = PbufferT[0] + +class TestCreateValuesPlainMultiple(CreateValues): + """Check the creation of heterogeneous arrays (plain, multiple rows)""" + _descr = Pdescr + multiple_rows = 1 + _buffer = PbufferT + +class TestCreateValuesNestedSingle(CreateValues): + """Check the creation of heterogeneous arrays (nested, single row)""" + _descr = Ndescr + multiple_rows = 0 + _buffer = NbufferT[0] + +class TestCreateValuesNestedMultiple(CreateValues): + """Check the creation of heterogeneous arrays (nested, multiple rows)""" + _descr = Ndescr + multiple_rows = 1 + _buffer = NbufferT + + +############################################################ +# Reading tests +############################################################ + +class ReadValuesPlain: + """Check the reading of values in heterogeneous arrays (plain)""" + + def test_access_fields(self): + h = np.array(self._buffer, dtype=self._descr) + if not self.multiple_rows: + assert_(h.shape == ()) + assert_equal(h['x'], np.array(self._buffer[0], dtype='i4')) + assert_equal(h['y'], np.array(self._buffer[1], dtype='f8')) + assert_equal(h['z'], np.array(self._buffer[2], dtype='u1')) + else: + assert_(len(h) == 2) + assert_equal(h['x'], np.array([self._buffer[0][0], + self._buffer[1][0]], dtype='i4')) + assert_equal(h['y'], np.array([self._buffer[0][1], + self._buffer[1][1]], dtype='f8')) + assert_equal(h['z'], np.array([self._buffer[0][2], + self._buffer[1][2]], dtype='u1')) + + +class TestReadValuesPlainSingle(ReadValuesPlain): + """Check the creation of heterogeneous arrays (plain, single row)""" + _descr = Pdescr + multiple_rows = 0 + _buffer = PbufferT[0] + +class TestReadValuesPlainMultiple(ReadValuesPlain): + """Check the values of heterogeneous arrays (plain, multiple rows)""" + _descr = Pdescr + multiple_rows = 1 + _buffer = PbufferT + +class ReadValuesNested: + """Check the reading of values in heterogeneous arrays (nested)""" + + def test_access_top_fields(self): + """Check reading the top fields of a nested array""" + h = np.array(self._buffer, dtype=self._descr) + if not self.multiple_rows: + assert_(h.shape == ()) + assert_equal(h['x'], np.array(self._buffer[0], dtype='i4')) + assert_equal(h['y'], np.array(self._buffer[4], dtype='f8')) + assert_equal(h['z'], np.array(self._buffer[5], dtype='u1')) + else: + assert_(len(h) == 2) + assert_equal(h['x'], np.array([self._buffer[0][0], + self._buffer[1][0]], dtype='i4')) + assert_equal(h['y'], np.array([self._buffer[0][4], + self._buffer[1][4]], dtype='f8')) + assert_equal(h['z'], np.array([self._buffer[0][5], + self._buffer[1][5]], dtype='u1')) + + def test_nested1_acessors(self): + """Check reading the nested fields of a nested array (1st level)""" + h = np.array(self._buffer, dtype=self._descr) + if not self.multiple_rows: + assert_equal(h['Info']['value'], + np.array(self._buffer[1][0], dtype='c16')) + assert_equal(h['Info']['y2'], + np.array(self._buffer[1][1], dtype='f8')) + assert_equal(h['info']['Name'], + np.array(self._buffer[3][0], dtype='U2')) + assert_equal(h['info']['Value'], + np.array(self._buffer[3][1], dtype='c16')) + else: + assert_equal(h['Info']['value'], + np.array([self._buffer[0][1][0], + self._buffer[1][1][0]], + dtype='c16')) + assert_equal(h['Info']['y2'], + np.array([self._buffer[0][1][1], + self._buffer[1][1][1]], + dtype='f8')) + assert_equal(h['info']['Name'], + np.array([self._buffer[0][3][0], + self._buffer[1][3][0]], + dtype='U2')) + assert_equal(h['info']['Value'], + np.array([self._buffer[0][3][1], + self._buffer[1][3][1]], + dtype='c16')) + + def test_nested2_acessors(self): + """Check reading the nested fields of a nested array (2nd level)""" + h = np.array(self._buffer, dtype=self._descr) + if not self.multiple_rows: + assert_equal(h['Info']['Info2']['value'], + np.array(self._buffer[1][2][1], dtype='c16')) + assert_equal(h['Info']['Info2']['z3'], + np.array(self._buffer[1][2][3], dtype='u4')) + else: + assert_equal(h['Info']['Info2']['value'], + np.array([self._buffer[0][1][2][1], + self._buffer[1][1][2][1]], + dtype='c16')) + assert_equal(h['Info']['Info2']['z3'], + np.array([self._buffer[0][1][2][3], + self._buffer[1][1][2][3]], + dtype='u4')) + + def test_nested1_descriptor(self): + """Check access nested descriptors of a nested array (1st level)""" + h = np.array(self._buffer, dtype=self._descr) + assert_(h.dtype['Info']['value'].name == 'complex128') + assert_(h.dtype['Info']['y2'].name == 'float64') + assert_(h.dtype['info']['Name'].name == 'str256') + assert_(h.dtype['info']['Value'].name == 'complex128') + + def test_nested2_descriptor(self): + """Check access nested descriptors of a nested array (2nd level)""" + h = np.array(self._buffer, dtype=self._descr) + assert_(h.dtype['Info']['Info2']['value'].name == 'void256') + assert_(h.dtype['Info']['Info2']['z3'].name == 'void64') + + +class TestReadValuesNestedSingle(ReadValuesNested): + """Check the values of heterogeneous arrays (nested, single row)""" + _descr = Ndescr + multiple_rows = False + _buffer = NbufferT[0] + +class TestReadValuesNestedMultiple(ReadValuesNested): + """Check the values of heterogeneous arrays (nested, multiple rows)""" + _descr = Ndescr + multiple_rows = True + _buffer = NbufferT + +class TestEmptyField: + def test_assign(self): + a = np.arange(10, dtype=np.float32) + a.dtype = [("int", "<0i4"), ("float", "<2f4")] + assert_(a['int'].shape == (5, 0)) + assert_(a['float'].shape == (5, 2)) + + +class TestMultipleFields: + def _bad_call(self): + ary = np.array([(1, 2, 3, 4), (5, 6, 7, 8)], dtype='i4,f4,i2,c8') + return ary['f0', 'f1'] + + def test_no_tuple(self): + assert_raises(IndexError, self._bad_call) + + def test_return(self): + ary = np.array([(1, 2, 3, 4), (5, 6, 7, 8)], dtype='i4,f4,i2,c8') + res = ary[['f0', 'f2']].tolist() + assert_(res == [(1, 3), (5, 7)]) + + +class TestIsSubDType: + # scalar types can be promoted into dtypes + wrappers = [np.dtype, lambda x: x] + + def test_both_abstract(self): + assert_(np.issubdtype(np.floating, np.inexact)) + assert_(not np.issubdtype(np.inexact, np.floating)) + + def test_same(self): + for cls in (np.float32, np.int32): + for w1, w2 in itertools.product(self.wrappers, repeat=2): + assert_(np.issubdtype(w1(cls), w2(cls))) + + def test_subclass(self): + # note we cannot promote floating to a dtype, as it would turn into a + # concrete type + for w in self.wrappers: + assert_(np.issubdtype(w(np.float32), np.floating)) + assert_(np.issubdtype(w(np.float64), np.floating)) + + def test_subclass_backwards(self): + for w in self.wrappers: + assert_(not np.issubdtype(np.floating, w(np.float32))) + assert_(not np.issubdtype(np.floating, w(np.float64))) + + def test_sibling_class(self): + for w1, w2 in itertools.product(self.wrappers, repeat=2): + assert_(not np.issubdtype(w1(np.float32), w2(np.float64))) + assert_(not np.issubdtype(w1(np.float64), w2(np.float32))) + + def test_nondtype_nonscalartype(self): + # See gh-14619 and gh-9505 which introduced the deprecation to fix + # this. These tests are directly taken from gh-9505 + assert not np.issubdtype(np.float32, 'float64') + assert not np.issubdtype(np.float32, 'f8') + assert not np.issubdtype(np.int32, str) + assert not np.issubdtype(np.int32, 'int64') + assert not np.issubdtype(np.str_, 'void') + # for the following the correct spellings are + # np.integer, np.floating, or np.complexfloating respectively: + assert not np.issubdtype(np.int8, int) # np.int8 is never np.int_ + assert not np.issubdtype(np.float32, float) + assert not np.issubdtype(np.complex64, complex) + assert not np.issubdtype(np.float32, "float") + assert not np.issubdtype(np.float64, "f") + + # Test the same for the correct first datatype and abstract one + # in the case of int, float, complex: + assert np.issubdtype(np.float64, 'float64') + assert np.issubdtype(np.float64, 'f8') + assert np.issubdtype(np.str_, str) + assert np.issubdtype(np.int64, 'int64') + assert np.issubdtype(np.void, 'void') + assert np.issubdtype(np.int8, np.integer) + assert np.issubdtype(np.float32, np.floating) + assert np.issubdtype(np.complex64, np.complexfloating) + assert np.issubdtype(np.float64, "float") + assert np.issubdtype(np.float32, "f") + + +class TestIsDType: + """ + Check correctness of `np.isdtype`. The test considers different argument + configurations: `np.isdtype(dtype, k1)` and `np.isdtype(dtype, (k1, k2))` + with concrete dtypes and dtype groups. + """ + dtype_group_dict = { + "signed integer": sctypes["int"], + "unsigned integer": sctypes["uint"], + "integral": sctypes["int"] + sctypes["uint"], + "real floating": sctypes["float"], + "complex floating": sctypes["complex"], + "numeric": ( + sctypes["int"] + sctypes["uint"] + sctypes["float"] + + sctypes["complex"] + ) + } + + @pytest.mark.parametrize( + "dtype,close_dtype", + [ + (np.int64, np.int32), (np.uint64, np.uint32), + (np.float64, np.float32), (np.complex128, np.complex64) + ] + ) + @pytest.mark.parametrize( + "dtype_group", + [ + None, "signed integer", "unsigned integer", "integral", + "real floating", "complex floating", "numeric" + ] + ) + def test_isdtype(self, dtype, close_dtype, dtype_group): + # First check if same dtypes return `true` and different ones + # give `false` (even if they're close in the dtype hierarchy!) + if dtype_group is None: + assert np.isdtype(dtype, dtype) + assert not np.isdtype(dtype, close_dtype) + assert np.isdtype(dtype, (dtype, close_dtype)) + + # Check that dtype and a dtype group that it belongs to + # return `true`, and `false` otherwise. + elif dtype in self.dtype_group_dict[dtype_group]: + assert np.isdtype(dtype, dtype_group) + assert np.isdtype(dtype, (close_dtype, dtype_group)) + else: + assert not np.isdtype(dtype, dtype_group) + + def test_isdtype_invalid_args(self): + with assert_raises_regex(TypeError, r".*must be a NumPy dtype.*"): + np.isdtype("int64", np.int64) + with assert_raises_regex(TypeError, r".*kind argument must.*"): + np.isdtype(np.int64, 1) + with assert_raises_regex(ValueError, r".*not a known kind name.*"): + np.isdtype(np.int64, "int64") + + def test_sctypes_complete(self): + # issue 26439: int32/intc were masking each other on 32-bit builds + assert np.int32 in sctypes['int'] + assert np.intc in sctypes['int'] + assert np.int64 in sctypes['int'] + assert np.uint32 in sctypes['uint'] + assert np.uintc in sctypes['uint'] + assert np.uint64 in sctypes['uint'] + +class TestSctypeDict: + def test_longdouble(self): + assert_(np._core.sctypeDict['float64'] is not np.longdouble) + assert_(np._core.sctypeDict['complex128'] is not np.clongdouble) + + def test_ulong(self): + assert np._core.sctypeDict['ulong'] is np.ulong + assert np.dtype(np.ulong) is np.dtype("ulong") + assert np.dtype(np.ulong).itemsize == np.dtype(np.long).itemsize + + +@pytest.mark.filterwarnings("ignore:.*maximum_sctype.*:DeprecationWarning") +class TestMaximumSctype: + + # note that parametrizing with sctype['int'] and similar would skip types + # with the same size (gh-11923) + + @pytest.mark.parametrize( + 't', [np.byte, np.short, np.intc, np.long, np.longlong] + ) + def test_int(self, t): + assert_equal(maximum_sctype(t), np._core.sctypes['int'][-1]) + + @pytest.mark.parametrize( + 't', [np.ubyte, np.ushort, np.uintc, np.ulong, np.ulonglong] + ) + def test_uint(self, t): + assert_equal(maximum_sctype(t), np._core.sctypes['uint'][-1]) + + @pytest.mark.parametrize('t', [np.half, np.single, np.double, np.longdouble]) + def test_float(self, t): + assert_equal(maximum_sctype(t), np._core.sctypes['float'][-1]) + + @pytest.mark.parametrize('t', [np.csingle, np.cdouble, np.clongdouble]) + def test_complex(self, t): + assert_equal(maximum_sctype(t), np._core.sctypes['complex'][-1]) + + @pytest.mark.parametrize('t', [np.bool, np.object_, np.str_, np.bytes_, + np.void]) + def test_other(self, t): + assert_equal(maximum_sctype(t), t) + + +class Test_sctype2char: + # This function is old enough that we're really just documenting the quirks + # at this point. + + def test_scalar_type(self): + assert_equal(sctype2char(np.double), 'd') + assert_equal(sctype2char(np.long), 'l') + assert_equal(sctype2char(np.int_), np.array(0).dtype.char) + assert_equal(sctype2char(np.str_), 'U') + assert_equal(sctype2char(np.bytes_), 'S') + + def test_other_type(self): + assert_equal(sctype2char(float), 'd') + assert_equal(sctype2char(list), 'O') + assert_equal(sctype2char(np.ndarray), 'O') + + def test_third_party_scalar_type(self): + from numpy._core._rational_tests import rational + assert_raises(KeyError, sctype2char, rational) + assert_raises(KeyError, sctype2char, rational(1)) + + def test_array_instance(self): + assert_equal(sctype2char(np.array([1.0, 2.0])), 'd') + + def test_abstract_type(self): + assert_raises(KeyError, sctype2char, np.floating) + + def test_non_type(self): + assert_raises(ValueError, sctype2char, 1) + +@pytest.mark.parametrize("rep, expected", [ + (np.int32, True), + (list, False), + (1.1, False), + (str, True), + (np.dtype(np.float64), True), + (np.dtype((np.int16, (3, 4))), True), + (np.dtype([('a', np.int8)]), True), + ]) +def test_issctype(rep, expected): + # ensure proper identification of scalar + # data-types by issctype() + actual = issctype(rep) + assert type(actual) is bool + assert_equal(actual, expected) + + +@pytest.mark.skipif(sys.flags.optimize > 1, + reason="no docstrings present to inspect when PYTHONOPTIMIZE/Py_OptimizeFlag > 1") +@pytest.mark.xfail(IS_PYPY, + reason="PyPy cannot modify tp_doc after PyType_Ready") +class TestDocStrings: + def test_platform_dependent_aliases(self): + if np.int64 is np.int_: + assert_('int64' in np.int_.__doc__) + elif np.int64 is np.longlong: + assert_('int64' in np.longlong.__doc__) + + +class TestScalarTypeNames: + # gh-9799 + + numeric_types = [ + np.byte, np.short, np.intc, np.long, np.longlong, + np.ubyte, np.ushort, np.uintc, np.ulong, np.ulonglong, + np.half, np.single, np.double, np.longdouble, + np.csingle, np.cdouble, np.clongdouble, + ] + + def test_names_are_unique(self): + # none of the above may be aliases for each other + assert len(set(self.numeric_types)) == len(self.numeric_types) + + # names must be unique + names = [t.__name__ for t in self.numeric_types] + assert len(set(names)) == len(names) + + @pytest.mark.parametrize('t', numeric_types) + def test_names_reflect_attributes(self, t): + """ Test that names correspond to where the type is under ``np.`` """ + assert getattr(np, t.__name__) is t + + @pytest.mark.parametrize('t', numeric_types) + def test_names_are_undersood_by_dtype(self, t): + """ Test the dtype constructor maps names back to the type """ + assert np.dtype(t.__name__).type is t + + +class TestScalarTypeOrder: + @pytest.mark.parametrize(('a', 'b'), [ + # signedinteger + (np.byte, np.short), + (np.short, np.intc), + (np.intc, np.long), + (np.long, np.longlong), + # unsignedinteger + (np.ubyte, np.ushort), + (np.ushort, np.uintc), + (np.uintc, np.ulong), + (np.ulong, np.ulonglong), + # floating + (np.half, np.single), + (np.single, np.double), + (np.double, np.longdouble), + # complexfloating + (np.csingle, np.cdouble), + (np.cdouble, np.clongdouble), + # flexible + (np.bytes_, np.str_), + (np.str_, np.void), + # bouncy castles + (np.datetime64, np.timedelta64), + ]) + def test_stable_ordering(self, a: type[np.generic], b: type[np.generic]): + assert np.ScalarType.index(a) <= np.ScalarType.index(b) + + +class TestBoolDefinition: + def test_bool_definition(self): + assert nt.bool is np.bool diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_overrides.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_overrides.py new file mode 100644 index 0000000000000000000000000000000000000000..ebcf2f0ce1121ac31f9db29a3f4c97f2bd504fea --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_overrides.py @@ -0,0 +1,800 @@ +import inspect +import os +import pickle +import sys +import tempfile +from io import StringIO +from unittest import mock + +import pytest + +import numpy as np +from numpy._core.overrides import ( + _get_implementing_args, + array_function_dispatch, + verify_matching_signatures, +) +from numpy.testing import assert_, assert_equal, assert_raises, assert_raises_regex +from numpy.testing.overrides import get_overridable_numpy_array_functions + + +def _return_not_implemented(self, *args, **kwargs): + return NotImplemented + + +# need to define this at the top level to test pickling +@array_function_dispatch(lambda array: (array,)) +def dispatched_one_arg(array): + """Docstring.""" + return 'original' + + +@array_function_dispatch(lambda array1, array2: (array1, array2)) +def dispatched_two_arg(array1, array2): + """Docstring.""" + return 'original' + + +class TestGetImplementingArgs: + + def test_ndarray(self): + array = np.array(1) + + args = _get_implementing_args([array]) + assert_equal(list(args), [array]) + + args = _get_implementing_args([array, array]) + assert_equal(list(args), [array]) + + args = _get_implementing_args([array, 1]) + assert_equal(list(args), [array]) + + args = _get_implementing_args([1, array]) + assert_equal(list(args), [array]) + + def test_ndarray_subclasses(self): + + class OverrideSub(np.ndarray): + __array_function__ = _return_not_implemented + + class NoOverrideSub(np.ndarray): + pass + + array = np.array(1).view(np.ndarray) + override_sub = np.array(1).view(OverrideSub) + no_override_sub = np.array(1).view(NoOverrideSub) + + args = _get_implementing_args([array, override_sub]) + assert_equal(list(args), [override_sub, array]) + + args = _get_implementing_args([array, no_override_sub]) + assert_equal(list(args), [no_override_sub, array]) + + args = _get_implementing_args( + [override_sub, no_override_sub]) + assert_equal(list(args), [override_sub, no_override_sub]) + + def test_ndarray_and_duck_array(self): + + class Other: + __array_function__ = _return_not_implemented + + array = np.array(1) + other = Other() + + args = _get_implementing_args([other, array]) + assert_equal(list(args), [other, array]) + + args = _get_implementing_args([array, other]) + assert_equal(list(args), [array, other]) + + def test_ndarray_subclass_and_duck_array(self): + + class OverrideSub(np.ndarray): + __array_function__ = _return_not_implemented + + class Other: + __array_function__ = _return_not_implemented + + array = np.array(1) + subarray = np.array(1).view(OverrideSub) + other = Other() + + assert_equal(_get_implementing_args([array, subarray, other]), + [subarray, array, other]) + assert_equal(_get_implementing_args([array, other, subarray]), + [subarray, array, other]) + + def test_many_duck_arrays(self): + + class A: + __array_function__ = _return_not_implemented + + class B(A): + __array_function__ = _return_not_implemented + + class C(A): + __array_function__ = _return_not_implemented + + class D: + __array_function__ = _return_not_implemented + + a = A() + b = B() + c = C() + d = D() + + assert_equal(_get_implementing_args([1]), []) + assert_equal(_get_implementing_args([a]), [a]) + assert_equal(_get_implementing_args([a, 1]), [a]) + assert_equal(_get_implementing_args([a, a, a]), [a]) + assert_equal(_get_implementing_args([a, d, a]), [a, d]) + assert_equal(_get_implementing_args([a, b]), [b, a]) + assert_equal(_get_implementing_args([b, a]), [b, a]) + assert_equal(_get_implementing_args([a, b, c]), [b, c, a]) + assert_equal(_get_implementing_args([a, c, b]), [c, b, a]) + + def test_too_many_duck_arrays(self): + namespace = {'__array_function__': _return_not_implemented} + types = [type('A' + str(i), (object,), namespace) for i in range(65)] + relevant_args = [t() for t in types] + + actual = _get_implementing_args(relevant_args[:64]) + assert_equal(actual, relevant_args[:64]) + + with assert_raises_regex(TypeError, 'distinct argument types'): + _get_implementing_args(relevant_args) + + +class TestNDArrayArrayFunction: + + def test_method(self): + + class Other: + __array_function__ = _return_not_implemented + + class NoOverrideSub(np.ndarray): + pass + + class OverrideSub(np.ndarray): + __array_function__ = _return_not_implemented + + array = np.array([1]) + other = Other() + no_override_sub = array.view(NoOverrideSub) + override_sub = array.view(OverrideSub) + + result = array.__array_function__(func=dispatched_two_arg, + types=(np.ndarray,), + args=(array, 1.), kwargs={}) + assert_equal(result, 'original') + + result = array.__array_function__(func=dispatched_two_arg, + types=(np.ndarray, Other), + args=(array, other), kwargs={}) + assert_(result is NotImplemented) + + result = array.__array_function__(func=dispatched_two_arg, + types=(np.ndarray, NoOverrideSub), + args=(array, no_override_sub), + kwargs={}) + assert_equal(result, 'original') + + result = array.__array_function__(func=dispatched_two_arg, + types=(np.ndarray, OverrideSub), + args=(array, override_sub), + kwargs={}) + assert_equal(result, 'original') + + with assert_raises_regex(TypeError, 'no implementation found'): + np.concatenate((array, other)) + + expected = np.concatenate((array, array)) + result = np.concatenate((array, no_override_sub)) + assert_equal(result, expected.view(NoOverrideSub)) + result = np.concatenate((array, override_sub)) + assert_equal(result, expected.view(OverrideSub)) + + def test_no_wrapper(self): + # Regular numpy functions have wrappers, but do not presume + # all functions do (array creation ones do not): check that + # we just call the function in that case. + array = np.array(1) + func = lambda x: x * 2 + result = array.__array_function__(func=func, types=(np.ndarray,), + args=(array,), kwargs={}) + assert_equal(result, array * 2) + + def test_wrong_arguments(self): + # Check our implementation guards against wrong arguments. + a = np.array([1, 2]) + with pytest.raises(TypeError, match="args must be a tuple"): + a.__array_function__(np.reshape, (np.ndarray,), a, (2, 1)) + with pytest.raises(TypeError, match="kwargs must be a dict"): + a.__array_function__(np.reshape, (np.ndarray,), (a,), (2, 1)) + + +class TestArrayFunctionDispatch: + + def test_pickle(self): + for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): + roundtripped = pickle.loads( + pickle.dumps(dispatched_one_arg, protocol=proto)) + assert_(roundtripped is dispatched_one_arg) + + def test_name_and_docstring(self): + assert_equal(dispatched_one_arg.__name__, 'dispatched_one_arg') + if sys.flags.optimize < 2: + assert_equal(dispatched_one_arg.__doc__, 'Docstring.') + + def test_interface(self): + + class MyArray: + def __array_function__(self, func, types, args, kwargs): + return (self, func, types, args, kwargs) + + original = MyArray() + (obj, func, types, args, kwargs) = dispatched_one_arg(original) + assert_(obj is original) + assert_(func is dispatched_one_arg) + assert_equal(set(types), {MyArray}) + # assert_equal uses the overloaded np.iscomplexobj() internally + assert_(args == (original,)) + assert_equal(kwargs, {}) + + def test_not_implemented(self): + + class MyArray: + def __array_function__(self, func, types, args, kwargs): + return NotImplemented + + array = MyArray() + with assert_raises_regex(TypeError, 'no implementation found'): + dispatched_one_arg(array) + + def test_where_dispatch(self): + + class DuckArray: + def __array_function__(self, ufunc, method, *inputs, **kwargs): + return "overridden" + + array = np.array(1) + duck_array = DuckArray() + + result = np.std(array, where=duck_array) + + assert_equal(result, "overridden") + + +class TestVerifyMatchingSignatures: + + def test_verify_matching_signatures(self): + + verify_matching_signatures(lambda x: 0, lambda x: 0) + verify_matching_signatures(lambda x=None: 0, lambda x=None: 0) + verify_matching_signatures(lambda x=1: 0, lambda x=None: 0) + + with assert_raises(RuntimeError): + verify_matching_signatures(lambda a: 0, lambda b: 0) + with assert_raises(RuntimeError): + verify_matching_signatures(lambda x: 0, lambda x=None: 0) + with assert_raises(RuntimeError): + verify_matching_signatures(lambda x=None: 0, lambda y=None: 0) + with assert_raises(RuntimeError): + verify_matching_signatures(lambda x=1: 0, lambda y=1: 0) + + def test_array_function_dispatch(self): + + with assert_raises(RuntimeError): + @array_function_dispatch(lambda x: (x,)) + def f(y): + pass + + # should not raise + @array_function_dispatch(lambda x: (x,), verify=False) + def f(y): + pass + + +def _new_duck_type_and_implements(): + """Create a duck array type and implements functions.""" + HANDLED_FUNCTIONS = {} + + class MyArray: + def __array_function__(self, func, types, args, kwargs): + if func not in HANDLED_FUNCTIONS: + return NotImplemented + if not all(issubclass(t, MyArray) for t in types): + return NotImplemented + return HANDLED_FUNCTIONS[func](*args, **kwargs) + + def implements(numpy_function): + """Register an __array_function__ implementations.""" + def decorator(func): + HANDLED_FUNCTIONS[numpy_function] = func + return func + return decorator + + return (MyArray, implements) + + +class TestArrayFunctionImplementation: + + def test_one_arg(self): + MyArray, implements = _new_duck_type_and_implements() + + @implements(dispatched_one_arg) + def _(array): + return 'myarray' + + assert_equal(dispatched_one_arg(1), 'original') + assert_equal(dispatched_one_arg(MyArray()), 'myarray') + + def test_optional_args(self): + MyArray, implements = _new_duck_type_and_implements() + + @array_function_dispatch(lambda array, option=None: (array,)) + def func_with_option(array, option='default'): + return option + + @implements(func_with_option) + def my_array_func_with_option(array, new_option='myarray'): + return new_option + + # we don't need to implement every option on __array_function__ + # implementations + assert_equal(func_with_option(1), 'default') + assert_equal(func_with_option(1, option='extra'), 'extra') + assert_equal(func_with_option(MyArray()), 'myarray') + with assert_raises(TypeError): + func_with_option(MyArray(), option='extra') + + # but new options on implementations can't be used + result = my_array_func_with_option(MyArray(), new_option='yes') + assert_equal(result, 'yes') + with assert_raises(TypeError): + func_with_option(MyArray(), new_option='no') + + def test_not_implemented(self): + MyArray, implements = _new_duck_type_and_implements() + + @array_function_dispatch(lambda array: (array,), module='my') + def func(array): + return array + + array = np.array(1) + assert_(func(array) is array) + assert_equal(func.__module__, 'my') + + with assert_raises_regex( + TypeError, "no implementation found for 'my.func'"): + func(MyArray()) + + @pytest.mark.parametrize("name", ["concatenate", "mean", "asarray"]) + def test_signature_error_message_simple(self, name): + func = getattr(np, name) + try: + # all of these functions need an argument: + func() + except TypeError as e: + exc = e + + assert exc.args[0].startswith(f"{name}()") + + def test_signature_error_message(self): + # The lambda function will be named "", but the TypeError + # should show the name as "func" + def _dispatcher(): + return () + + @array_function_dispatch(_dispatcher) + def func(): + pass + + try: + func._implementation(bad_arg=3) + except TypeError as e: + expected_exception = e + + try: + func(bad_arg=3) + raise AssertionError("must fail") + except TypeError as exc: + if exc.args[0].startswith("_dispatcher"): + # We replace the qualname currently, but it used `__name__` + # (relevant functions have the same name and qualname anyway) + pytest.skip("Python version is not using __qualname__ for " + "TypeError formatting.") + + assert exc.args == expected_exception.args + + @pytest.mark.parametrize("value", [234, "this func is not replaced"]) + def test_dispatcher_error(self, value): + # If the dispatcher raises an error, we must not attempt to mutate it + error = TypeError(value) + + def dispatcher(): + raise error + + @array_function_dispatch(dispatcher) + def func(): + return 3 + + try: + func() + raise AssertionError("must fail") + except TypeError as exc: + assert exc is error # unmodified exception + + def test_properties(self): + # Check that str and repr are sensible + func = dispatched_two_arg + assert str(func) == str(func._implementation) + repr_no_id = repr(func).split("at ")[0] + repr_no_id_impl = repr(func._implementation).split("at ")[0] + assert repr_no_id == repr_no_id_impl + + @pytest.mark.parametrize("func", [ + lambda x, y: 0, # no like argument + lambda like=None: 0, # not keyword only + lambda *, like=None, a=3: 0, # not last (not that it matters) + ]) + def test_bad_like_sig(self, func): + # We sanity check the signature, and these should fail. + with pytest.raises(RuntimeError): + array_function_dispatch()(func) + + def test_bad_like_passing(self): + # Cover internal sanity check for passing like as first positional arg + def func(*, like=None): + pass + + func_with_like = array_function_dispatch()(func) + with pytest.raises(TypeError): + func_with_like() + with pytest.raises(TypeError): + func_with_like(like=234) + + def test_too_many_args(self): + # Mainly a unit-test to increase coverage + objs = [] + for i in range(80): + class MyArr: + def __array_function__(self, *args, **kwargs): + return NotImplemented + + objs.append(MyArr()) + + def _dispatch(*args): + return args + + @array_function_dispatch(_dispatch) + def func(*args): + pass + + with pytest.raises(TypeError, match="maximum number"): + func(*objs) + + +class TestNDArrayMethods: + + def test_repr(self): + # gh-12162: should still be defined even if __array_function__ doesn't + # implement np.array_repr() + + class MyArray(np.ndarray): + def __array_function__(*args, **kwargs): + return NotImplemented + + array = np.array(1).view(MyArray) + assert_equal(repr(array), 'MyArray(1)') + assert_equal(str(array), '1') + + +class TestNumPyFunctions: + + def test_set_module(self): + assert_equal(np.sum.__module__, 'numpy') + assert_equal(np.char.equal.__module__, 'numpy.char') + assert_equal(np.fft.fft.__module__, 'numpy.fft') + assert_equal(np.linalg.solve.__module__, 'numpy.linalg') + + def test_inspect_sum(self): + signature = inspect.signature(np.sum) + assert_('axis' in signature.parameters) + + def test_override_sum(self): + MyArray, implements = _new_duck_type_and_implements() + + @implements(np.sum) + def _(array): + return 'yes' + + assert_equal(np.sum(MyArray()), 'yes') + + def test_sum_on_mock_array(self): + + # We need a proxy for mocks because __array_function__ is only looked + # up in the class dict + class ArrayProxy: + def __init__(self, value): + self.value = value + + def __array_function__(self, *args, **kwargs): + return self.value.__array_function__(*args, **kwargs) + + def __array__(self, *args, **kwargs): + return self.value.__array__(*args, **kwargs) + + proxy = ArrayProxy(mock.Mock(spec=ArrayProxy)) + proxy.value.__array_function__.return_value = 1 + result = np.sum(proxy) + assert_equal(result, 1) + proxy.value.__array_function__.assert_called_once_with( + np.sum, (ArrayProxy,), (proxy,), {}) + proxy.value.__array__.assert_not_called() + + def test_sum_forwarding_implementation(self): + + class MyArray(np.ndarray): + + def sum(self, axis, out): + return 'summed' + + def __array_function__(self, func, types, args, kwargs): + return super().__array_function__(func, types, args, kwargs) + + # note: the internal implementation of np.sum() calls the .sum() method + array = np.array(1).view(MyArray) + assert_equal(np.sum(array), 'summed') + + +class TestArrayLike: + def _create_MyArray(self): + class MyArray: + def __init__(self, function=None): + self.function = function + + def __array_function__(self, func, types, args, kwargs): + assert func is getattr(np, func.__name__) + try: + my_func = getattr(self, func.__name__) + except AttributeError: + return NotImplemented + return my_func(*args, **kwargs) + + return MyArray + + def _create_MyNoArrayFunctionArray(self): + class MyNoArrayFunctionArray: + def __init__(self, function=None): + self.function = function + + return MyNoArrayFunctionArray + + def _create_MySubclass(self): + class MySubclass(np.ndarray): + def __array_function__(self, func, types, args, kwargs): + result = super().__array_function__(func, types, args, kwargs) + return result.view(self.__class__) + + return MySubclass + + def add_method(self, name, arr_class, enable_value_error=False): + def _definition(*args, **kwargs): + # Check that `like=` isn't propagated downstream + assert 'like' not in kwargs + + if enable_value_error and 'value_error' in kwargs: + raise ValueError + + return arr_class(getattr(arr_class, name)) + setattr(arr_class, name, _definition) + + def func_args(*args, **kwargs): + return args, kwargs + + def test_array_like_not_implemented(self): + MyArray = self._create_MyArray() + self.add_method('array', MyArray) + + ref = MyArray.array() + + with assert_raises_regex(TypeError, 'no implementation found'): + array_like = np.asarray(1, like=ref) + + _array_tests = [ + ('array', *func_args((1,))), + ('asarray', *func_args((1,))), + ('asanyarray', *func_args((1,))), + ('ascontiguousarray', *func_args((2, 3))), + ('asfortranarray', *func_args((2, 3))), + ('require', *func_args((np.arange(6).reshape(2, 3),), + requirements=['A', 'F'])), + ('empty', *func_args((1,))), + ('full', *func_args((1,), 2)), + ('ones', *func_args((1,))), + ('zeros', *func_args((1,))), + ('arange', *func_args(3)), + ('frombuffer', *func_args(b'\x00' * 8, dtype=int)), + ('fromiter', *func_args(range(3), dtype=int)), + ('fromstring', *func_args('1,2', dtype=int, sep=',')), + ('loadtxt', *func_args(lambda: StringIO('0 1\n2 3'))), + ('genfromtxt', *func_args(lambda: StringIO('1,2.1'), + dtype=[('int', 'i8'), ('float', 'f8')], + delimiter=',')), + ] + + def test_nep35_functions_as_array_functions(self,): + all_array_functions = get_overridable_numpy_array_functions() + like_array_functions_subset = { + getattr(np, func_name) for func_name, *_ in self.__class__._array_tests + } + assert like_array_functions_subset.issubset(all_array_functions) + + nep35_python_functions = { + np.eye, np.fromfunction, np.full, np.genfromtxt, + np.identity, np.loadtxt, np.ones, np.require, np.tri, + } + assert nep35_python_functions.issubset(all_array_functions) + + nep35_C_functions = { + np.arange, np.array, np.asanyarray, np.asarray, + np.ascontiguousarray, np.asfortranarray, np.empty, + np.frombuffer, np.fromfile, np.fromiter, np.fromstring, + np.zeros, + } + assert nep35_C_functions.issubset(all_array_functions) + + @pytest.mark.parametrize('function, args, kwargs', _array_tests) + @pytest.mark.parametrize('numpy_ref', [True, False]) + def test_array_like(self, function, args, kwargs, numpy_ref): + MyArray = self._create_MyArray() + self.add_method('array', MyArray) + self.add_method(function, MyArray) + np_func = getattr(np, function) + my_func = getattr(MyArray, function) + + if numpy_ref is True: + ref = np.array(1) + else: + ref = MyArray.array() + + like_args = tuple(a() if callable(a) else a for a in args) + array_like = np_func(*like_args, **kwargs, like=ref) + + if numpy_ref is True: + assert type(array_like) is np.ndarray + + np_args = tuple(a() if callable(a) else a for a in args) + np_arr = np_func(*np_args, **kwargs) + + # Special-case np.empty to ensure values match + if function == "empty": + np_arr.fill(1) + array_like.fill(1) + + assert_equal(array_like, np_arr) + else: + assert type(array_like) is MyArray + assert array_like.function is my_func + + @pytest.mark.parametrize('function, args, kwargs', _array_tests) + @pytest.mark.parametrize('ref', [1, [1], "MyNoArrayFunctionArray"]) + def test_no_array_function_like(self, function, args, kwargs, ref): + MyNoArrayFunctionArray = self._create_MyNoArrayFunctionArray() + self.add_method('array', MyNoArrayFunctionArray) + self.add_method(function, MyNoArrayFunctionArray) + np_func = getattr(np, function) + + # Instantiate ref if it's the MyNoArrayFunctionArray class + if ref == "MyNoArrayFunctionArray": + ref = MyNoArrayFunctionArray.array() + + like_args = tuple(a() if callable(a) else a for a in args) + + with assert_raises_regex(TypeError, + 'The `like` argument must be an array-like that implements'): + np_func(*like_args, **kwargs, like=ref) + + @pytest.mark.parametrize('function, args, kwargs', _array_tests) + def test_subclass(self, function, args, kwargs): + MySubclass = self._create_MySubclass() + ref = np.array(1).view(MySubclass) + np_func = getattr(np, function) + like_args = tuple(a() if callable(a) else a for a in args) + array_like = np_func(*like_args, **kwargs, like=ref) + assert type(array_like) is MySubclass + if np_func is np.empty: + return + np_args = tuple(a() if callable(a) else a for a in args) + np_arr = np_func(*np_args, **kwargs) + assert_equal(array_like.view(np.ndarray), np_arr) + + @pytest.mark.parametrize('numpy_ref', [True, False]) + def test_array_like_fromfile(self, numpy_ref): + MyArray = self._create_MyArray() + self.add_method('array', MyArray) + self.add_method("fromfile", MyArray) + + if numpy_ref is True: + ref = np.array(1) + else: + ref = MyArray.array() + + data = np.random.random(5) + + with tempfile.TemporaryDirectory() as tmpdir: + fname = os.path.join(tmpdir, "testfile") + data.tofile(fname) + + array_like = np.fromfile(fname, like=ref) + if numpy_ref is True: + assert type(array_like) is np.ndarray + np_res = np.fromfile(fname, like=ref) + assert_equal(np_res, data) + assert_equal(array_like, np_res) + else: + assert type(array_like) is MyArray + assert array_like.function is MyArray.fromfile + + def test_exception_handling(self): + MyArray = self._create_MyArray() + self.add_method('array', MyArray, enable_value_error=True) + + ref = MyArray.array() + + with assert_raises(TypeError): + # Raises the error about `value_error` being invalid first + np.array(1, value_error=True, like=ref) + + @pytest.mark.parametrize('function, args, kwargs', _array_tests) + def test_like_as_none(self, function, args, kwargs): + MyArray = self._create_MyArray() + self.add_method('array', MyArray) + self.add_method(function, MyArray) + np_func = getattr(np, function) + + like_args = tuple(a() if callable(a) else a for a in args) + # required for loadtxt and genfromtxt to init w/o error. + like_args_exp = tuple(a() if callable(a) else a for a in args) + + array_like = np_func(*like_args, **kwargs, like=None) + expected = np_func(*like_args_exp, **kwargs) + # Special-case np.empty to ensure values match + if function == "empty": + array_like.fill(1) + expected.fill(1) + assert_equal(array_like, expected) + + +def test_function_like(): + # We provide a `__get__` implementation, make sure it works + assert type(np.mean) is np._core._multiarray_umath._ArrayFunctionDispatcher + + class MyClass: + def __array__(self, dtype=None, copy=None): + # valid argument to mean: + return np.arange(3) + + func1 = staticmethod(np.mean) + func2 = np.mean + func3 = classmethod(np.mean) + + m = MyClass() + assert m.func1([10]) == 10 + assert m.func2() == 1 # mean of the arange + with pytest.raises(TypeError, match="unsupported operand type"): + # Tries to operate on the class + m.func3() + + # Manual binding also works (the above may shortcut): + bound = np.mean.__get__(m, MyClass) + assert bound() == 1 + + bound = np.mean.__get__(None, MyClass) # unbound actually + assert bound([10]) == 10 + + bound = np.mean.__get__(MyClass) # classmethod + with pytest.raises(TypeError, match="unsupported operand type"): + bound() diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_print.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_print.py new file mode 100644 index 0000000000000000000000000000000000000000..95a177b57a7d6ce09fb28ea9ae82dc9f7bba510b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_print.py @@ -0,0 +1,202 @@ +import sys +from io import StringIO + +import pytest + +import numpy as np +from numpy._core.tests._locales import CommaDecimalPointLocale +from numpy.testing import IS_MUSL, assert_, assert_equal + +_REF = {np.inf: 'inf', -np.inf: '-inf', np.nan: 'nan'} + + +@pytest.mark.parametrize('tp', [np.float32, np.double, np.longdouble]) +def test_float_types(tp): + """ Check formatting. + + This is only for the str function, and only for simple types. + The precision of np.float32 and np.longdouble aren't the same as the + python float precision. + + """ + for x in [0, 1, -1, 1e20]: + assert_equal(str(tp(x)), str(float(x)), + err_msg=f'Failed str formatting for type {tp}') + + if tp(1e16).itemsize > 4: + assert_equal(str(tp(1e16)), str(float('1e16')), + err_msg=f'Failed str formatting for type {tp}') + else: + ref = '1e+16' + assert_equal(str(tp(1e16)), ref, + err_msg=f'Failed str formatting for type {tp}') + + +@pytest.mark.parametrize('tp', [np.float32, np.double, np.longdouble]) +def test_nan_inf_float(tp): + """ Check formatting of nan & inf. + + This is only for the str function, and only for simple types. + The precision of np.float32 and np.longdouble aren't the same as the + python float precision. + + """ + for x in [np.inf, -np.inf, np.nan]: + assert_equal(str(tp(x)), _REF[x], + err_msg=f'Failed str formatting for type {tp}') + + +@pytest.mark.parametrize('tp', [np.complex64, np.cdouble, np.clongdouble]) +def test_complex_types(tp): + """Check formatting of complex types. + + This is only for the str function, and only for simple types. + The precision of np.float32 and np.longdouble aren't the same as the + python float precision. + + """ + for x in [0, 1, -1, 1e20]: + assert_equal(str(tp(x)), str(complex(x)), + err_msg=f'Failed str formatting for type {tp}') + assert_equal(str(tp(x * 1j)), str(complex(x * 1j)), + err_msg=f'Failed str formatting for type {tp}') + assert_equal(str(tp(x + x * 1j)), str(complex(x + x * 1j)), + err_msg=f'Failed str formatting for type {tp}') + + if tp(1e16).itemsize > 8: + assert_equal(str(tp(1e16)), str(complex(1e16)), + err_msg=f'Failed str formatting for type {tp}') + else: + ref = '(1e+16+0j)' + assert_equal(str(tp(1e16)), ref, + err_msg=f'Failed str formatting for type {tp}') + + +@pytest.mark.parametrize('dtype', [np.complex64, np.cdouble, np.clongdouble]) +def test_complex_inf_nan(dtype): + """Check inf/nan formatting of complex types.""" + TESTS = { + complex(np.inf, 0): "(inf+0j)", + complex(0, np.inf): "infj", + complex(-np.inf, 0): "(-inf+0j)", + complex(0, -np.inf): "-infj", + complex(np.inf, 1): "(inf+1j)", + complex(1, np.inf): "(1+infj)", + complex(-np.inf, 1): "(-inf+1j)", + complex(1, -np.inf): "(1-infj)", + complex(np.nan, 0): "(nan+0j)", + complex(0, np.nan): "nanj", + complex(-np.nan, 0): "(nan+0j)", + complex(0, -np.nan): "nanj", + complex(np.nan, 1): "(nan+1j)", + complex(1, np.nan): "(1+nanj)", + complex(-np.nan, 1): "(nan+1j)", + complex(1, -np.nan): "(1+nanj)", + } + for c, s in TESTS.items(): + assert_equal(str(dtype(c)), s) + + +# print tests +def _test_redirected_print(x, tp, ref=None): + file = StringIO() + file_tp = StringIO() + stdout = sys.stdout + try: + sys.stdout = file_tp + print(tp(x)) + sys.stdout = file + if ref: + print(ref) + else: + print(x) + finally: + sys.stdout = stdout + + assert_equal(file.getvalue(), file_tp.getvalue(), + err_msg=f'print failed for type{tp}') + + +@pytest.mark.thread_unsafe(reason="sys.stdout not thread-safe") +@pytest.mark.parametrize('tp', [np.float32, np.double, np.longdouble]) +def test_float_type_print(tp): + """Check formatting when using print """ + for x in [0, 1, -1, 1e20]: + _test_redirected_print(float(x), tp) + + for x in [np.inf, -np.inf, np.nan]: + _test_redirected_print(float(x), tp, _REF[x]) + + if tp(1e16).itemsize > 4: + _test_redirected_print(1e16, tp) + else: + ref = '1e+16' + _test_redirected_print(1e16, tp, ref) + + +@pytest.mark.thread_unsafe(reason="sys.stdout not thread-safe") +@pytest.mark.parametrize('tp', [np.complex64, np.cdouble, np.clongdouble]) +def test_complex_type_print(tp): + """Check formatting when using print """ + # We do not create complex with inf/nan directly because the feature is + # missing in python < 2.6 + for x in [0, 1, -1, 1e20]: + _test_redirected_print(complex(x), tp) + + if tp(1e16).itemsize > 8: + _test_redirected_print(complex(1e16), tp) + else: + ref = '(1e+16+0j)' + _test_redirected_print(complex(1e16), tp, ref) + + _test_redirected_print(complex(np.inf, 1), tp, '(inf+1j)') + _test_redirected_print(complex(-np.inf, 1), tp, '(-inf+1j)') + _test_redirected_print(complex(-np.nan, 1), tp, '(nan+1j)') + + +def test_scalar_format(): + """Test the str.format method with NumPy scalar types""" + tests = [('{0}', True, np.bool), + ('{0}', False, np.bool), + ('{0:d}', 130, np.uint8), + ('{0:d}', 50000, np.uint16), + ('{0:d}', 3000000000, np.uint32), + ('{0:d}', 15000000000000000000, np.uint64), + ('{0:d}', -120, np.int8), + ('{0:d}', -30000, np.int16), + ('{0:d}', -2000000000, np.int32), + ('{0:d}', -7000000000000000000, np.int64), + ('{0:g}', 1.5, np.float16), + ('{0:g}', 1.5, np.float32), + ('{0:g}', 1.5, np.float64), + ('{0:g}', 1.5, np.longdouble), + ('{0:g}', 1.5 + 0.5j, np.complex64), + ('{0:g}', 1.5 + 0.5j, np.complex128), + ('{0:g}', 1.5 + 0.5j, np.clongdouble)] + + for (fmat, val, valtype) in tests: + try: + assert_equal(fmat.format(val), fmat.format(valtype(val)), + f"failed with val {val}, type {valtype}") + except ValueError as e: + assert_(False, + "format raised exception (fmt='%s', val=%s, type=%s, exc='%s')" % + (fmat, repr(val), repr(valtype), str(e))) + + +# +# Locale tests: scalar types formatting should be independent of the locale +# + +class TestCommaDecimalPointLocale(CommaDecimalPointLocale): + + def test_locale_single(self): + assert_equal(str(np.float32(1.2)), str(1.2)) + + def test_locale_double(self): + assert_equal(str(np.double(1.2)), str(1.2)) + + @pytest.mark.skipif(IS_MUSL, + reason="test flaky on musllinux") + def test_locale_longdouble(self): + assert_equal(str(np.longdouble('1.2')), str(1.2)) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_protocols.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_protocols.py new file mode 100644 index 0000000000000000000000000000000000000000..96bb600843dcf6fee4806945fbaf082cf8346203 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_protocols.py @@ -0,0 +1,46 @@ +import warnings + +import pytest + +import numpy as np + + +@pytest.mark.filterwarnings("error") +def test_getattr_warning(): + # issue gh-14735: make sure we clear only getattr errors, and let warnings + # through + class Wrapper: + def __init__(self, array): + self.array = array + + def __len__(self): + return len(self.array) + + def __getitem__(self, item): + return type(self)(self.array[item]) + + def __getattr__(self, name): + if name.startswith("__array_"): + warnings.warn("object got converted", UserWarning, stacklevel=1) + + return getattr(self.array, name) + + def __repr__(self): + return f"" + + array = Wrapper(np.arange(10)) + with pytest.raises(UserWarning, match="object got converted"): + np.asarray(array) + + +def test_array_called(): + class Wrapper: + val = '0' * 100 + + def __array__(self, dtype=None, copy=None): + return np.array([self.val], dtype=dtype, copy=copy) + + wrapped = Wrapper() + arr = np.array(wrapped, dtype=str) + assert arr.dtype == 'U100' + assert arr[0] == Wrapper.val diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_records.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_records.py new file mode 100644 index 0000000000000000000000000000000000000000..7ed6ea7687ff208e3b34025337a8f9e230da43a2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_records.py @@ -0,0 +1,544 @@ +import collections.abc +import pickle +import textwrap +from io import BytesIO +from os import path +from pathlib import Path + +import pytest + +import numpy as np +from numpy.testing import ( + assert_, + assert_array_almost_equal, + assert_array_equal, + assert_equal, + assert_raises, + temppath, +) + + +class TestFromrecords: + def test_fromrecords(self): + r = np.rec.fromrecords([[456, 'dbe', 1.2], [2, 'de', 1.3]], + names='col1,col2,col3') + assert_equal(r[0].item(), (456, 'dbe', 1.2)) + assert_equal(r['col1'].dtype.kind, 'i') + assert_equal(r['col2'].dtype.kind, 'U') + assert_equal(r['col2'].dtype.itemsize, 12) + assert_equal(r['col3'].dtype.kind, 'f') + + def test_fromrecords_0len(self): + """ Verify fromrecords works with a 0-length input """ + dtype = [('a', float), ('b', float)] + r = np.rec.fromrecords([], dtype=dtype) + assert_equal(r.shape, (0,)) + + def test_fromrecords_2d(self): + data = [ + [(1, 2), (3, 4), (5, 6)], + [(6, 5), (4, 3), (2, 1)] + ] + expected_a = [[1, 3, 5], [6, 4, 2]] + expected_b = [[2, 4, 6], [5, 3, 1]] + + # try with dtype + r1 = np.rec.fromrecords(data, dtype=[('a', int), ('b', int)]) + assert_equal(r1['a'], expected_a) + assert_equal(r1['b'], expected_b) + + # try with names + r2 = np.rec.fromrecords(data, names=['a', 'b']) + assert_equal(r2['a'], expected_a) + assert_equal(r2['b'], expected_b) + + assert_equal(r1, r2) + + def test_method_array(self): + r = np.rec.array( + b'abcdefg' * 100, formats='i2,S3,i4', shape=3, byteorder='big' + ) + assert_equal(r[1].item(), (25444, b'efg', 1633837924)) + + def test_method_array2(self): + r = np.rec.array( + [ + (1, 11, 'a'), (2, 22, 'b'), (3, 33, 'c'), (4, 44, 'd'), + (5, 55, 'ex'), (6, 66, 'f'), (7, 77, 'g') + ], + formats='u1,f4,S1' + ) + assert_equal(r[1].item(), (2, 22.0, b'b')) + + def test_recarray_slices(self): + r = np.rec.array( + [ + (1, 11, 'a'), (2, 22, 'b'), (3, 33, 'c'), (4, 44, 'd'), + (5, 55, 'ex'), (6, 66, 'f'), (7, 77, 'g') + ], + formats='u1,f4,S1' + ) + assert_equal(r[1::2][1].item(), (4, 44.0, b'd')) + + def test_recarray_fromarrays(self): + x1 = np.array([1, 2, 3, 4]) + x2 = np.array(['a', 'dd', 'xyz', '12']) + x3 = np.array([1.1, 2, 3, 4]) + r = np.rec.fromarrays([x1, x2, x3], names='a,b,c') + assert_equal(r[1].item(), (2, 'dd', 2.0)) + x1[1] = 34 + assert_equal(r.a, np.array([1, 2, 3, 4])) + + def test_recarray_fromfile(self): + data_dir = path.join(path.dirname(__file__), 'data') + filename = path.join(data_dir, 'recarray_from_file.fits') + fd = open(filename, 'rb') + fd.seek(2880 * 2) + r1 = np.rec.fromfile(fd, formats='f8,i4,S5', shape=3, byteorder='big') + fd.seek(2880 * 2) + r2 = np.rec.array(fd, formats='f8,i4,S5', shape=3, byteorder='big') + fd.seek(2880 * 2) + bytes_array = BytesIO() + bytes_array.write(fd.read()) + bytes_array.seek(0) + r3 = np.rec.fromfile( + bytes_array, formats='f8,i4,S5', shape=3, byteorder='big' + ) + fd.close() + assert_equal(r1, r2) + assert_equal(r2, r3) + + def test_recarray_from_obj(self): + count = 10 + a = np.zeros(count, dtype='O') + b = np.zeros(count, dtype='f8') + c = np.zeros(count, dtype='f8') + for i in range(len(a)): + a[i] = list(range(1, 10)) + + mine = np.rec.fromarrays([a, b, c], names='date,data1,data2') + for i in range(len(a)): + assert_(mine.date[i] == list(range(1, 10))) + assert_(mine.data1[i] == 0.0) + assert_(mine.data2[i] == 0.0) + + def test_recarray_repr(self): + a = np.array([(1, 0.1), (2, 0.2)], + dtype=[('foo', ' 2) & (a < 6)) + xb = np.where((b > 2) & (b < 6)) + ya = ((a > 2) & (a < 6)) + yb = ((b > 2) & (b < 6)) + assert_array_almost_equal(xa, ya.nonzero()) + assert_array_almost_equal(xb, yb.nonzero()) + assert_(np.all(a[ya] > 0.5)) + assert_(np.all(b[yb] > 0.5)) + + def test_endian_where(self): + # GitHub issue #369 + net = np.zeros(3, dtype='>f4') + net[1] = 0.00458849 + net[2] = 0.605202 + max_net = net.max() + test = np.where(net <= 0., max_net, net) + correct = np.array([0.60520202, 0.00458849, 0.60520202]) + assert_array_almost_equal(test, correct) + + def test_endian_recarray(self): + # Ticket #2185 + dt = np.dtype([ + ('head', '>u4'), + ('data', '>u4', 2), + ]) + buf = np.recarray(1, dtype=dt) + buf[0]['head'] = 1 + buf[0]['data'][:] = [1, 1] + + h = buf[0]['head'] + d = buf[0]['data'][0] + buf[0]['head'] = h + buf[0]['data'][0] = d + assert_(buf[0]['head'] == 1) + + def test_mem_dot(self): + # Ticket #106 + x = np.random.randn(0, 1) + y = np.random.randn(10, 1) + # Dummy array to detect bad memory access: + _z = np.ones(10) + _dummy = np.empty((0, 10)) + z = as_strided(_z, _dummy.shape, _dummy.strides) + np.dot(x, np.transpose(y), out=z) + assert_equal(_z, np.ones(10)) + # Do the same for the built-in dot: + np._core.multiarray.dot(x, np.transpose(y), out=z) + assert_equal(_z, np.ones(10)) + + def test_arange_endian(self): + # Ticket #111 + ref = np.arange(10) + x = np.arange(10, dtype=' 1 and x['two'] > 2) + + def test_method_args(self): + # Make sure methods and functions have same default axis + # keyword and arguments + funcs1 = ['argmax', 'argmin', 'sum', 'any', 'all', 'cumsum', + 'cumprod', 'prod', 'std', 'var', 'mean', + 'round', 'min', 'max', 'argsort', 'sort'] + funcs2 = ['compress', 'take', 'repeat'] + + for func in funcs1: + arr = np.random.rand(8, 7) + arr2 = arr.copy() + res1 = getattr(arr, func)() + res2 = getattr(np, func)(arr2) + if res1 is None: + res1 = arr + + if res1.dtype.kind in 'uib': + assert_((res1 == res2).all(), func) + else: + assert_(abs(res1 - res2).max() < 1e-8, func) + + for func in funcs2: + arr1 = np.random.rand(8, 7) + arr2 = np.random.rand(8, 7) + res1 = None + if func == 'compress': + arr1 = arr1.ravel() + res1 = getattr(arr2, func)(arr1) + else: + arr2 = (15 * arr2).astype(int).ravel() + if res1 is None: + res1 = getattr(arr1, func)(arr2) + res2 = getattr(np, func)(arr1, arr2) + assert_(abs(res1 - res2).max() < 1e-8, func) + + def test_mem_lexsort_strings(self): + # Ticket #298 + lst = ['abc', 'cde', 'fgh'] + np.lexsort((lst,)) + + def test_fancy_index(self): + # Ticket #302 + x = np.array([1, 2])[np.array([0])] + assert_equal(x.shape, (1,)) + + def test_recarray_copy(self): + # Ticket #312 + dt = [('x', np.int16), ('y', np.float64)] + ra = np.array([(1, 2.3)], dtype=dt) + rb = np.rec.array(ra, dtype=dt) + rb['x'] = 2. + assert_(ra['x'] != rb['x']) + + def test_rec_fromarray(self): + # Ticket #322 + x1 = np.array([[1, 2], [3, 4], [5, 6]]) + x2 = np.array(['a', 'dd', 'xyz']) + x3 = np.array([1.1, 2, 3]) + np.rec.fromarrays([x1, x2, x3], formats="(2,)i4,S3,f8") + + def test_object_array_assign(self): + x = np.empty((2, 2), object) + x.flat[2] = (1, 2, 3) + assert_equal(x.flat[2], (1, 2, 3)) + + def test_ndmin_float64(self): + # Ticket #324 + x = np.array([1, 2, 3], dtype=np.float64) + assert_equal(np.array(x, dtype=np.float32, ndmin=2).ndim, 2) + assert_equal(np.array(x, dtype=np.float64, ndmin=2).ndim, 2) + + def test_ndmin_order(self): + # Issue #465 and related checks + assert_(np.array([1, 2], order='C', ndmin=3).flags.c_contiguous) + assert_(np.array([1, 2], order='F', ndmin=3).flags.f_contiguous) + assert_(np.array(np.ones((2, 2), order='F'), ndmin=3).flags.f_contiguous) + assert_(np.array(np.ones((2, 2), order='C'), ndmin=3).flags.c_contiguous) + + def test_mem_axis_minimization(self): + # Ticket #327 + data = np.arange(5) + data = np.add.outer(data, data) + + def test_mem_float_imag(self): + # Ticket #330 + np.float64(1.0).imag + + def test_dtype_tuple(self): + # Ticket #334 + assert_(np.dtype('i4') == np.dtype(('i4', ()))) + + def test_dtype_posttuple(self): + # Ticket #335 + np.dtype([('col1', '()i4')]) + + def test_numeric_carray_compare(self): + # Ticket #341 + assert_equal(np.array(['X'], 'c'), b'X') + + def test_string_array_size(self): + # Ticket #342 + assert_raises(ValueError, + np.array, [['X'], ['X', 'X', 'X']], '|S1') + + def test_dtype_repr(self): + # Ticket #344 + dt1 = np.dtype(('uint32', 2)) + dt2 = np.dtype(('uint32', (2,))) + assert_equal(dt1.__repr__(), dt2.__repr__()) + + def test_reshape_order(self): + # Make sure reshape order works. + a = np.arange(6).reshape(2, 3, order='F') + assert_equal(a, [[0, 2, 4], [1, 3, 5]]) + a = np.array([[1, 2], [3, 4], [5, 6], [7, 8]]) + b = a[:, 1] + assert_equal(b.reshape(2, 2, order='F'), [[2, 6], [4, 8]]) + + def test_reshape_zero_strides(self): + # Issue #380, test reshaping of zero strided arrays + a = np.ones(1) + a = as_strided(a, shape=(5,), strides=(0,)) + assert_(a.reshape(5, 1).strides[0] == 0) + + def test_reshape_zero_size(self): + # GitHub Issue #2700, setting shape failed for 0-sized arrays + a = np.ones((0, 2)) + a.shape = (-1, 2) + + def test_reshape_trailing_ones_strides(self): + # GitHub issue gh-2949, bad strides for trailing ones of new shape + a = np.zeros(12, dtype=np.int32)[::2] # not contiguous + strides_c = (16, 8, 8, 8) + strides_f = (8, 24, 48, 48) + assert_equal(a.reshape(3, 2, 1, 1).strides, strides_c) + assert_equal(a.reshape(3, 2, 1, 1, order='F').strides, strides_f) + assert_equal(np.array(0, dtype=np.int32).reshape(1, 1).strides, (4, 4)) + + def test_repeat_discont(self): + # Ticket #352 + a = np.arange(12).reshape(4, 3)[:, 2] + assert_equal(a.repeat(3), [2, 2, 2, 5, 5, 5, 8, 8, 8, 11, 11, 11]) + + def test_array_index(self): + # Make sure optimization is not called in this case. + a = np.array([1, 2, 3]) + a2 = np.array([[1, 2, 3]]) + assert_equal(a[np.where(a == 3)], a2[np.where(a2 == 3)]) + + def test_object_argmax(self): + a = np.array([1, 2, 3], dtype=object) + assert_(a.argmax() == 2) + + def test_recarray_fields(self): + # Ticket #372 + dt0 = np.dtype([('f0', 'i4'), ('f1', 'i4')]) + dt1 = np.dtype([('f0', 'i8'), ('f1', 'i8')]) + for a in [np.array([(1, 2), (3, 4)], "i4,i4"), + np.rec.array([(1, 2), (3, 4)], "i4,i4"), + np.rec.array([(1, 2), (3, 4)]), + np.rec.fromarrays([(1, 2), (3, 4)], "i4,i4"), + np.rec.fromarrays([(1, 2), (3, 4)])]: + assert_(a.dtype in [dt0, dt1]) + + def test_random_shuffle(self): + # Ticket #374 + a = np.arange(5).reshape((5, 1)) + b = a.copy() + np.random.shuffle(b) + assert_equal(np.sort(b, axis=0), a) + + def test_refcount_vdot(self): + # Changeset #3443 + _assert_valid_refcount(np.vdot) + + def test_startswith(self): + ca = np.char.array(['Hi', 'There']) + assert_equal(ca.startswith('H'), [True, False]) + + def test_noncommutative_reduce_accumulate(self): + # Ticket #413 + tosubtract = np.arange(5) + todivide = np.array([2.0, 0.5, 0.25]) + assert_equal(np.subtract.reduce(tosubtract), -10) + assert_equal(np.divide.reduce(todivide), 16.0) + assert_array_equal(np.subtract.accumulate(tosubtract), + np.array([0, -1, -3, -6, -10])) + assert_array_equal(np.divide.accumulate(todivide), + np.array([2., 4., 16.])) + + def test_convolve_empty(self): + # Convolve should raise an error for empty input array. + assert_raises(ValueError, np.convolve, [], [1]) + assert_raises(ValueError, np.convolve, [1], []) + + def test_multidim_byteswap(self): + # Ticket #449 + r = np.array([(1, (0, 1, 2))], dtype="i2,3i2") + assert_array_equal(r.byteswap(), + np.array([(256, (0, 256, 512))], r.dtype)) + + def test_string_NULL(self): + # Changeset 3557 + assert_equal(np.array("a\x00\x0b\x0c\x00").item(), + 'a\x00\x0b\x0c') + + def test_junk_in_string_fields_of_recarray(self): + # Ticket #483 + r = np.array([[b'abc']], dtype=[('var1', '|S20')]) + assert_(asbytes(r['var1'][0][0]) == b'abc') + + def test_take_output(self): + # Ensure that 'take' honours output parameter. + x = np.arange(12).reshape((3, 4)) + a = np.take(x, [0, 2], axis=1) + b = np.zeros_like(a) + np.take(x, [0, 2], axis=1, out=b) + assert_array_equal(a, b) + + def test_take_object_fail(self): + # Issue gh-3001 + d = 123. + a = np.array([d, 1], dtype=object) + if HAS_REFCOUNT: + ref_d = sys.getrefcount(d) + try: + a.take([0, 100]) + except IndexError: + pass + if HAS_REFCOUNT: + assert_(ref_d == sys.getrefcount(d)) + + def test_array_str_64bit(self): + # Ticket #501 + s = np.array([1, np.nan], dtype=np.float64) + with np.errstate(all='raise'): + np.array_str(s) # Should succeed + + def test_frompyfunc_endian(self): + # Ticket #503 + from math import radians + uradians = np.frompyfunc(radians, 1, 1) + big_endian = np.array([83.4, 83.5], dtype='>f8') + little_endian = np.array([83.4, 83.5], dtype=' object + # casting succeeds + def rs(): + x = np.ones([484, 286]) + y = np.zeros([484, 286]) + x |= y + + assert_raises(TypeError, rs) + + def test_unicode_scalar(self): + # Ticket #600 + x = np.array(["DROND", "DROND1"], dtype="U6") + el = x[1] + for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): + new = pickle.loads(pickle.dumps(el, protocol=proto)) + assert_equal(new, el) + + def test_arange_non_native_dtype(self): + # Ticket #616 + for T in ('>f4', ' 0)] = v + + assert_raises(IndexError, ia, x, s, np.zeros(9, dtype=float)) + assert_raises(IndexError, ia, x, s, np.zeros(11, dtype=float)) + + # Old special case (different code path): + assert_raises(IndexError, ia, x.flat, s, np.zeros(9, dtype=float)) + assert_raises(IndexError, ia, x.flat, s, np.zeros(11, dtype=float)) + + def test_mem_scalar_indexing(self): + # Ticket #603 + x = np.array([0], dtype=float) + index = np.array(0, dtype=np.int32) + x[index] + + def test_binary_repr_0_width(self): + assert_equal(np.binary_repr(0, width=3), '000') + + def test_fromstring(self): + assert_equal(np.fromstring("12:09:09", dtype=int, sep=":"), + [12, 9, 9]) + + def test_searchsorted_variable_length(self): + x = np.array(['a', 'aa', 'b']) + y = np.array(['d', 'e']) + assert_equal(x.searchsorted(y), [3, 3]) + + def test_string_argsort_with_zeros(self): + # Check argsort for strings containing zeros. + x = np.frombuffer(b"\x00\x02\x00\x01", dtype="|S2") + assert_array_equal(x.argsort(kind='m'), np.array([1, 0])) + assert_array_equal(x.argsort(kind='q'), np.array([1, 0])) + + def test_string_sort_with_zeros(self): + # Check sort for strings containing zeros. + x = np.frombuffer(b"\x00\x02\x00\x01", dtype="|S2") + y = np.frombuffer(b"\x00\x01\x00\x02", dtype="|S2") + assert_array_equal(np.sort(x, kind="q"), y) + + def test_copy_detection_zero_dim(self): + # Ticket #658 + np.indices((0, 3, 4)).T.reshape(-1, 3) + + def test_flat_byteorder(self): + # Ticket #657 + x = np.arange(10) + assert_array_equal(x.astype('>i4'), x.astype('i4').flat[:], x.astype('i4')): + x = np.array([-1, 0, 1], dtype=dt) + assert_equal(x.flat[0].dtype, x[0].dtype) + + def test_copy_detection_corner_case(self): + # Ticket #658 + np.indices((0, 3, 4)).T.reshape(-1, 3) + + def test_object_array_refcounting(self): + # Ticket #633 + if not hasattr(sys, 'getrefcount'): + return + + # NB. this is probably CPython-specific + + cnt = sys.getrefcount + + a = object() + b = object() + c = object() + + cnt0_a = cnt(a) + cnt0_b = cnt(b) + cnt0_c = cnt(c) + + # -- 0d -> 1-d broadcast slice assignment + + arr = np.zeros(5, dtype=np.object_) + + arr[:] = a + assert_equal(cnt(a), cnt0_a + 5) + + arr[:] = b + assert_equal(cnt(a), cnt0_a) + assert_equal(cnt(b), cnt0_b + 5) + + arr[:2] = c + assert_equal(cnt(b), cnt0_b + 3) + assert_equal(cnt(c), cnt0_c + 2) + + del arr + + # -- 1-d -> 2-d broadcast slice assignment + + arr = np.zeros((5, 2), dtype=np.object_) + arr0 = np.zeros(2, dtype=np.object_) + + arr0[0] = a + assert_(cnt(a) == cnt0_a + 1) + arr0[1] = b + assert_(cnt(b) == cnt0_b + 1) + + arr[:, :] = arr0 + assert_(cnt(a) == cnt0_a + 6) + assert_(cnt(b) == cnt0_b + 6) + + arr[:, 0] = None + assert_(cnt(a) == cnt0_a + 1) + + del arr, arr0 + + # -- 2-d copying + flattening + + arr = np.zeros((5, 2), dtype=np.object_) + + arr[:, 0] = a + arr[:, 1] = b + assert_(cnt(a) == cnt0_a + 5) + assert_(cnt(b) == cnt0_b + 5) + + arr2 = arr.copy() + assert_(cnt(a) == cnt0_a + 10) + assert_(cnt(b) == cnt0_b + 10) + + arr2 = arr[:, 0].copy() + assert_(cnt(a) == cnt0_a + 10) + assert_(cnt(b) == cnt0_b + 5) + + arr2 = arr.flatten() + assert_(cnt(a) == cnt0_a + 10) + assert_(cnt(b) == cnt0_b + 10) + + del arr, arr2 + + # -- concatenate, repeat, take, choose + + arr1 = np.zeros((5, 1), dtype=np.object_) + arr2 = np.zeros((5, 1), dtype=np.object_) + + arr1[...] = a + arr2[...] = b + assert_(cnt(a) == cnt0_a + 5) + assert_(cnt(b) == cnt0_b + 5) + + tmp = np.concatenate((arr1, arr2)) + assert_(cnt(a) == cnt0_a + 5 + 5) + assert_(cnt(b) == cnt0_b + 5 + 5) + + tmp = arr1.repeat(3, axis=0) + assert_(cnt(a) == cnt0_a + 5 + 3 * 5) + + tmp = arr1.take([1, 2, 3], axis=0) + assert_(cnt(a) == cnt0_a + 5 + 3) + + x = np.array([[0], [1], [0], [1], [1]], int) + tmp = x.choose(arr1, arr2) + assert_(cnt(a) == cnt0_a + 5 + 2) + assert_(cnt(b) == cnt0_b + 5 + 3) + + def test_mem_custom_float_to_array(self): + # Ticket 702 + class MyFloat: + def __float__(self): + return 1.0 + + tmp = np.atleast_1d([MyFloat()]) + tmp.astype(float) # Should succeed + + def test_object_array_refcount_self_assign(self): + # Ticket #711 + class VictimObject: + deleted = False + + def __del__(self): + self.deleted = True + + d = VictimObject() + arr = np.zeros(5, dtype=np.object_) + arr[:] = d + del d + arr[:] = arr # refcount of 'd' might hit zero here + assert_(not arr[0].deleted) + arr[:] = arr # trying to induce a segfault by doing it again... + assert_(not arr[0].deleted) + + def test_mem_fromiter_invalid_dtype_string(self): + x = [1, 2, 3] + assert_raises(ValueError, + np.fromiter, list(x), dtype='S') + + def test_reduce_big_object_array(self): + # Ticket #713 + oldsize = np.setbufsize(10 * 16) + a = np.array([None] * 161, object) + assert_(not np.any(a)) + np.setbufsize(oldsize) + + def test_mem_0d_array_index(self): + # Ticket #714 + np.zeros(10)[np.array(0)] + + def test_nonnative_endian_fill(self): + # Non-native endian arrays were incorrectly filled with scalars + # before r5034. + if sys.byteorder == 'little': + dtype = np.dtype('>i4') + else: + dtype = np.dtype('data contains non-zero floats + x = np.array([123456789e199], dtype=np.float64) + if IS_PYPY: + x.resize((m, 0), refcheck=False) + else: + x.resize((m, 0)) + y = np.array([123456789e199], dtype=np.float64) + if IS_PYPY: + y.resize((0, n), refcheck=False) + else: + y.resize((0, n)) + + # `dot` should just return zero (m, n) matrix + z = np.dot(x, y) + assert_(np.all(z == 0)) + assert_(z.shape == (m, n)) + + def test_zeros(self): + # Regression test for #1061. + # Set a size which cannot fit into a 64 bits signed integer + sz = 2 ** 64 + with assert_raises_regex(ValueError, + 'Maximum allowed dimension exceeded'): + np.empty(sz) + + def test_huge_arange(self): + # Regression test for #1062. + # Set a size which cannot fit into a 64 bits signed integer + sz = 2 ** 64 + with assert_raises_regex(ValueError, + 'Maximum allowed size exceeded'): + np.arange(sz) + assert_(np.size == sz) + + def test_fromiter_bytes(self): + # Ticket #1058 + a = np.fromiter(list(range(10)), dtype='b') + b = np.fromiter(list(range(10)), dtype='B') + assert_(np.all(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) + assert_(np.all(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) + + def test_array_from_sequence_scalar_array(self): + # Ticket #1078: segfaults when creating an array with a sequence of + # 0d arrays. + a = np.array((np.ones(2), np.array(2)), dtype=object) + assert_equal(a.shape, (2,)) + assert_equal(a.dtype, np.dtype(object)) + assert_equal(a[0], np.ones(2)) + assert_equal(a[1], np.array(2)) + + a = np.array(((1,), np.array(1)), dtype=object) + assert_equal(a.shape, (2,)) + assert_equal(a.dtype, np.dtype(object)) + assert_equal(a[0], (1,)) + assert_equal(a[1], np.array(1)) + + def test_array_from_sequence_scalar_array2(self): + # Ticket #1081: weird array with strange input... + t = np.array([np.array([]), np.array(0, object)], dtype=object) + assert_equal(t.shape, (2,)) + assert_equal(t.dtype, np.dtype(object)) + + def test_array_too_big(self): + # Ticket #1080. + assert_raises(ValueError, np.zeros, [975] * 7, np.int8) + assert_raises(ValueError, np.zeros, [26244] * 5, np.int8) + + def test_dtype_keyerrors_(self): + # Ticket #1106. + dt = np.dtype([('f1', np.uint)]) + assert_raises(KeyError, dt.__getitem__, "f2") + assert_raises(IndexError, dt.__getitem__, 1) + assert_raises(TypeError, dt.__getitem__, 0.0) + + def test_lexsort_buffer_length(self): + # Ticket #1217, don't segfault. + a = np.ones(100, dtype=np.int8) + b = np.ones(100, dtype=np.int32) + i = np.lexsort((a[::-1], b)) + assert_equal(i, np.arange(100, dtype=int)) + + def test_object_array_to_fixed_string(self): + # Ticket #1235. + a = np.array(['abcdefgh', 'ijklmnop'], dtype=np.object_) + b = np.array(a, dtype=(np.str_, 8)) + assert_equal(a, b) + c = np.array(a, dtype=(np.str_, 5)) + assert_equal(c, np.array(['abcde', 'ijklm'])) + d = np.array(a, dtype=(np.str_, 12)) + assert_equal(a, d) + e = np.empty((2, ), dtype=(np.str_, 8)) + e[:] = a[:] + assert_equal(a, e) + + def test_unicode_to_string_cast(self): + # Ticket #1240. + a = np.array([['abc', '\u03a3'], + ['asdf', 'erw']], + dtype='U') + assert_raises(UnicodeEncodeError, np.array, a, 'S4') + + def test_unicode_to_string_cast_error(self): + # gh-15790 + a = np.array(['\x80'] * 129, dtype='U3') + assert_raises(UnicodeEncodeError, np.array, a, 'S') + b = a.reshape(3, 43)[:-1, :-1] + assert_raises(UnicodeEncodeError, np.array, b, 'S') + + def test_mixed_string_byte_array_creation(self): + a = np.array(['1234', b'123']) + assert_(a.itemsize == 16) + a = np.array([b'123', '1234']) + assert_(a.itemsize == 16) + a = np.array(['1234', b'123', '12345']) + assert_(a.itemsize == 20) + a = np.array([b'123', '1234', b'12345']) + assert_(a.itemsize == 20) + a = np.array([b'123', '1234', b'1234']) + assert_(a.itemsize == 16) + + def test_misaligned_objects_segfault(self): + # Ticket #1198 and #1267 + a1 = np.zeros((10,), dtype='O,c') + a2 = np.array(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j'], 'S10') + a1['f0'] = a2 + repr(a1) + np.argmax(a1['f0']) + a1['f0'][1] = "FOO" + a1['f0'] = "FOO" + np.array(a1['f0'], dtype='S') + np.nonzero(a1['f0']) + a1.sort() + copy.deepcopy(a1) + + def test_misaligned_scalars_segfault(self): + # Ticket #1267 + s1 = np.array(('a', 'Foo'), dtype='c,O') + s2 = np.array(('b', 'Bar'), dtype='c,O') + s1['f1'] = s2['f1'] + s1['f1'] = 'Baz' + + def test_misaligned_dot_product_objects(self): + # Ticket #1267 + # This didn't require a fix, but it's worth testing anyway, because + # it may fail if .dot stops enforcing the arrays to be BEHAVED + a = np.array([[(1, 'a'), (0, 'a')], [(0, 'a'), (1, 'a')]], dtype='O,c') + b = np.array([[(4, 'a'), (1, 'a')], [(2, 'a'), (2, 'a')]], dtype='O,c') + np.dot(a['f0'], b['f0']) + + def test_byteswap_complex_scalar(self): + # Ticket #1259 and gh-441 + for dtype in [np.dtype('<' + t) for t in np.typecodes['Complex']]: + z = np.array([2.2 - 1.1j], dtype) + x = z[0] # always native-endian + y = x.byteswap() + if x.dtype.byteorder == z.dtype.byteorder: + # little-endian machine + assert_equal(x, np.frombuffer(y.tobytes(), dtype=dtype.newbyteorder())) + else: + # big-endian machine + assert_equal(x, np.frombuffer(y.tobytes(), dtype=dtype)) + # double check real and imaginary parts: + assert_equal(x.real, y.real.byteswap()) + assert_equal(x.imag, y.imag.byteswap()) + + def test_structured_arrays_with_objects1(self): + # Ticket #1299 + stra = 'aaaa' + strb = 'bbbb' + x = np.array([[(0, stra), (1, strb)]], 'i8,O') + x[x.nonzero()] = x.ravel()[:1] + assert_(x[0, 1] == x[0, 0]) + + @pytest.mark.skipif( + sys.version_info >= (3, 12), + reason="Python 3.12 has immortal refcounts, this test no longer works." + ) + @pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") + def test_structured_arrays_with_objects2(self): + # Ticket #1299 second test + stra = 'aaaa' + strb = 'bbbb' + numb = sys.getrefcount(strb) + numa = sys.getrefcount(stra) + x = np.array([[(0, stra), (1, strb)]], 'i8,O') + x[x.nonzero()] = x.ravel()[:1] + assert_(sys.getrefcount(strb) == numb) + assert_(sys.getrefcount(stra) == numa + 2) + + def test_duplicate_title_and_name(self): + # Ticket #1254 + dtspec = [(('a', 'a'), 'i'), ('b', 'i')] + assert_raises(ValueError, np.dtype, dtspec) + + def test_signed_integer_division_overflow(self): + # Ticket #1317. + def test_type(t): + min = np.array([np.iinfo(t).min]) + min //= -1 + + with np.errstate(over="ignore"): + for t in (np.int8, np.int16, np.int32, np.int64, int): + test_type(t) + + def test_buffer_hashlib(self): + from hashlib import sha256 + + x = np.array([1, 2, 3], dtype=np.dtype('c') + + def test_log1p_compiler_shenanigans(self): + # Check if log1p is behaving on 32 bit intel systems. + assert_(np.isfinite(np.log1p(np.exp2(-53)))) + + def test_fromiter_comparison(self): + a = np.fromiter(list(range(10)), dtype='b') + b = np.fromiter(list(range(10)), dtype='B') + assert_(np.all(a == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) + assert_(np.all(b == np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))) + + def test_fromstring_crash(self): + with assert_raises(ValueError): + np.fromstring(b'aa, aa, 1.0', sep=',') + + def test_ticket_1539(self): + dtypes = [x for x in np._core.sctypeDict.values() + if (issubclass(x, np.number) + and not issubclass(x, np.timedelta64))] + a = np.array([], np.bool) # not x[0] because it is unordered + failures = [] + + for x in dtypes: + b = a.astype(x) + for y in dtypes: + c = a.astype(y) + try: + d = np.dot(b, c) + except TypeError: + failures.append((x, y)) + else: + if d != 0: + failures.append((x, y)) + if failures: + raise AssertionError(f"Failures: {failures!r}") + + def test_ticket_1538(self): + x = np.finfo(np.float32) + for name in ('eps', 'epsneg', 'max', 'min', 'resolution', 'tiny'): + assert_equal(type(getattr(x, name)), np.float32, + err_msg=name) + + def test_ticket_1434(self): + # Check that the out= argument in var and std has an effect + data = np.array(((1, 2, 3), (4, 5, 6), (7, 8, 9))) + out = np.zeros((3,)) + + ret = data.var(axis=1, out=out) + assert_(ret is out) + assert_array_equal(ret, data.var(axis=1)) + + ret = data.std(axis=1, out=out) + assert_(ret is out) + assert_array_equal(ret, data.std(axis=1)) + + def test_complex_nan_maximum(self): + cnan = complex(0, np.nan) + assert_equal(np.maximum(1, cnan), cnan) + + def test_subclass_int_tuple_assignment(self): + # ticket #1563 + class Subclass(np.ndarray): + def __new__(cls, i): + return np.ones((i,)).view(cls) + + x = Subclass(5) + x[(0,)] = 2 # shouldn't raise an exception + assert_equal(x[0], 2) + + def test_ufunc_no_unnecessary_views(self): + # ticket #1548 + class Subclass(np.ndarray): + pass + x = np.array([1, 2, 3]).view(Subclass) + y = np.add(x, x, x) + assert_equal(id(x), id(y)) + + @pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") + def test_take_refcount(self): + # ticket #939 + a = np.arange(16, dtype=float) + a.shape = (4, 4) + lut = np.ones((5 + 3, 4), float) + rgba = np.empty(shape=a.shape + (4,), dtype=lut.dtype) + c1 = sys.getrefcount(rgba) + try: + lut.take(a, axis=0, mode='clip', out=rgba) + except TypeError: + pass + c2 = sys.getrefcount(rgba) + assert_equal(c1, c2) + + def test_fromfile_tofile_seeks(self): + # tofile/fromfile used to get (#1610) the Python file handle out of sync + with tempfile.NamedTemporaryFile() as f: + f.write(np.arange(255, dtype='u1').tobytes()) + + f.seek(20) + ret = np.fromfile(f, count=4, dtype='u1') + assert_equal(ret, np.array([20, 21, 22, 23], dtype='u1')) + assert_equal(f.tell(), 24) + + f.seek(40) + np.array([1, 2, 3], dtype='u1').tofile(f) + assert_equal(f.tell(), 43) + + f.seek(40) + data = f.read(3) + assert_equal(data, b"\x01\x02\x03") + + f.seek(80) + f.read(4) + data = np.fromfile(f, dtype='u1', count=4) + assert_equal(data, np.array([84, 85, 86, 87], dtype='u1')) + + def test_complex_scalar_warning(self): + for tp in [np.csingle, np.cdouble, np.clongdouble]: + x = tp(1 + 2j) + pytest.warns(ComplexWarning, float, x) + with warnings.catch_warnings(): + warnings.simplefilter('ignore', ComplexWarning) + assert_equal(float(x), float(x.real)) + + def test_complex_scalar_complex_cast(self): + for tp in [np.csingle, np.cdouble, np.clongdouble]: + x = tp(1 + 2j) + assert_equal(complex(x), 1 + 2j) + + def test_complex_boolean_cast(self): + # Ticket #2218 + for tp in [np.csingle, np.cdouble, np.clongdouble]: + x = np.array([0, 0 + 0.5j, 0.5 + 0j], dtype=tp) + assert_equal(x.astype(bool), np.array([0, 1, 1], dtype=bool)) + assert_(np.any(x)) + assert_(np.all(x[1:])) + + def test_uint_int_conversion(self): + x = 2**64 - 1 + assert_equal(int(np.uint64(x)), x) + + def test_duplicate_field_names_assign(self): + ra = np.fromiter(((i * 3, i * 2) for i in range(10)), dtype='i8,f8') + ra.dtype.names = ('f1', 'f2') + repr(ra) # should not cause a segmentation fault + assert_raises(ValueError, setattr, ra.dtype, 'names', ('f1', 'f1')) + + def test_eq_string_and_object_array(self): + # From e-mail thread "__eq__ with str and object" (Keith Goodman) + a1 = np.array(['a', 'b'], dtype=object) + a2 = np.array(['a', 'c']) + assert_array_equal(a1 == a2, [True, False]) + assert_array_equal(a2 == a1, [True, False]) + + def test_nonzero_byteswap(self): + a = np.array([0x80000000, 0x00000080, 0], dtype=np.uint32) + a = a.view(np.float32) + assert_equal(a.nonzero()[0], [1]) + a = a.byteswap() + a = a.view(a.dtype.newbyteorder()) + assert_equal(a.nonzero()[0], [1]) # [0] if nonzero() ignores swap + + def test_empty_mul(self): + a = np.array([1.]) + a[1:1] *= 2 + assert_equal(a, [1.]) + + def test_array_side_effect(self): + # The second use of itemsize was throwing an exception because in + # ctors.c, discover_itemsize was calling PyObject_Length without + # checking the return code. This failed to get the length of the + # number 2, and the exception hung around until something checked + # PyErr_Occurred() and returned an error. + assert_equal(np.dtype('S10').itemsize, 10) + np.array([['abc', 2], ['long ', '0123456789']], dtype=np.bytes_) + assert_equal(np.dtype('S10').itemsize, 10) + + def test_any_float(self): + # all and any for floats + a = np.array([0.1, 0.9]) + assert_(np.any(a)) + assert_(np.all(a)) + + def test_large_float_sum(self): + a = np.arange(10000, dtype='f') + assert_equal(a.sum(dtype='d'), a.astype('d').sum()) + + def test_ufunc_casting_out(self): + a = np.array(1.0, dtype=np.float32) + b = np.array(1.0, dtype=np.float64) + c = np.array(1.0, dtype=np.float32) + np.add(a, b, out=c) + assert_equal(c, 2.0) + + def test_array_scalar_contiguous(self): + # Array scalars are both C and Fortran contiguous + assert_(np.array(1.0).flags.c_contiguous) + assert_(np.array(1.0).flags.f_contiguous) + assert_(np.array(np.float32(1.0)).flags.c_contiguous) + assert_(np.array(np.float32(1.0)).flags.f_contiguous) + + def test_squeeze_contiguous(self): + # Similar to GitHub issue #387 + a = np.zeros((1, 2)).squeeze() + b = np.zeros((2, 2, 2), order='F')[:, :, ::2].squeeze() + assert_(a.flags.c_contiguous) + assert_(a.flags.f_contiguous) + assert_(b.flags.f_contiguous) + + def test_squeeze_axis_handling(self): + # Issue #10779 + # Ensure proper handling of objects + # that don't support axis specification + # when squeezing + + class OldSqueeze(np.ndarray): + + def __new__(cls, + input_array): + obj = np.asarray(input_array).view(cls) + return obj + + # it is perfectly reasonable that prior + # to numpy version 1.7.0 a subclass of ndarray + # might have been created that did not expect + # squeeze to have an axis argument + # NOTE: this example is somewhat artificial; + # it is designed to simulate an old API + # expectation to guard against regression + def squeeze(self): + return super().squeeze() + + oldsqueeze = OldSqueeze(np.array([[1], [2], [3]])) + + # if no axis argument is specified the old API + # expectation should give the correct result + assert_equal(np.squeeze(oldsqueeze), + np.array([1, 2, 3])) + + # likewise, axis=None should work perfectly well + # with the old API expectation + assert_equal(np.squeeze(oldsqueeze, axis=None), + np.array([1, 2, 3])) + + # however, specification of any particular axis + # should raise a TypeError in the context of the + # old API specification, even when using a valid + # axis specification like 1 for this array + with assert_raises(TypeError): + # this would silently succeed for array + # subclasses / objects that did not support + # squeeze axis argument handling before fixing + # Issue #10779 + np.squeeze(oldsqueeze, axis=1) + + # check for the same behavior when using an invalid + # axis specification -- in this case axis=0 does not + # have size 1, but the priority should be to raise + # a TypeError for the axis argument and NOT a + # ValueError for squeezing a non-empty dimension + with assert_raises(TypeError): + np.squeeze(oldsqueeze, axis=0) + + # the new API knows how to handle the axis + # argument and will return a ValueError if + # attempting to squeeze an axis that is not + # of length 1 + with assert_raises(ValueError): + np.squeeze(np.array([[1], [2], [3]]), axis=0) + + def test_reduce_contiguous(self): + # GitHub issue #387 + a = np.add.reduce(np.zeros((2, 1, 2)), (0, 1)) + b = np.add.reduce(np.zeros((2, 1, 2)), 1) + assert_(a.flags.c_contiguous) + assert_(a.flags.f_contiguous) + assert_(b.flags.c_contiguous) + + @pytest.mark.skipif(IS_PYSTON, reason="Pyston disables recursion checking") + @pytest.mark.skipif(IS_WASM, reason="Pyodide/WASM has limited stack size") + def test_object_array_self_reference(self): + # Object arrays with references to themselves can cause problems + a = np.array(0, dtype=object) + a[()] = a + assert_raises(RecursionError, int, a) + assert_raises(RecursionError, float, a) + a[()] = None + + @pytest.mark.skipif(IS_PYSTON, reason="Pyston disables recursion checking") + @pytest.mark.skipif(IS_WASM, reason="Pyodide/WASM has limited stack size") + def test_object_array_circular_reference(self): + # Test the same for a circular reference. + a = np.array(0, dtype=object) + b = np.array(0, dtype=object) + a[()] = b + b[()] = a + assert_raises(RecursionError, int, a) + # NumPy has no tp_traverse currently, so circular references + # cannot be detected. So resolve it: + a[()] = None + + # This was causing a to become like the above + a = np.array(0, dtype=object) + a[...] += 1 + assert_equal(a, 1) + + def test_object_array_nested(self): + # but is fine with a reference to a different array + a = np.array(0, dtype=object) + b = np.array(0, dtype=object) + a[()] = b + assert_equal(int(a), int(0)) # noqa: UP018 + assert_equal(float(a), float(0)) + + def test_object_array_self_copy(self): + # An object array being copied into itself DECREF'ed before INCREF'ing + # causing segmentation faults (gh-3787) + a = np.array(object(), dtype=object) + np.copyto(a, a) + if HAS_REFCOUNT: + assert_(sys.getrefcount(a[()]) == 2) + a[()].__class__ # will segfault if object was deleted + + def test_zerosize_accumulate(self): + "Ticket #1733" + x = np.array([[42, 0]], dtype=np.uint32) + assert_equal(np.add.accumulate(x[:-1, 0]), []) + + def test_objectarray_setfield(self): + # Setfield should not overwrite Object fields with non-Object data + x = np.array([1, 2, 3], dtype=object) + assert_raises(TypeError, x.setfield, 4, np.int32, 0) + + def test_setting_rank0_string(self): + "Ticket #1736" + s1 = b"hello1" + s2 = b"hello2" + a = np.zeros((), dtype="S10") + a[()] = s1 + assert_equal(a, np.array(s1)) + a[()] = np.array(s2) + assert_equal(a, np.array(s2)) + + a = np.zeros((), dtype='f4') + a[()] = 3 + assert_equal(a, np.array(3)) + a[()] = np.array(4) + assert_equal(a, np.array(4)) + + def test_string_astype(self): + "Ticket #1748" + s1 = b'black' + s2 = b'white' + s3 = b'other' + a = np.array([[s1], [s2], [s3]]) + assert_equal(a.dtype, np.dtype('S5')) + b = a.astype(np.dtype('S0')) + assert_equal(b.dtype, np.dtype('S5')) + + def test_ticket_1756(self): + # Ticket #1756 + s = b'0123456789abcdef' + a = np.array([s] * 5) + for i in range(1, 17): + a1 = np.array(a, "|S%d" % i) + a2 = np.array([s[:i]] * 5) + assert_equal(a1, a2) + + def test_fields_strides(self): + "gh-2355" + r = np.frombuffer(b'abcdefghijklmnop' * 4 * 3, dtype='i4,(2,3)u2') + assert_equal(r[0:3:2]['f1'], r['f1'][0:3:2]) + assert_equal(r[0:3:2]['f1'][0], r[0:3:2][0]['f1']) + assert_equal(r[0:3:2]['f1'][0][()], r[0:3:2][0]['f1'][()]) + assert_equal(r[0:3:2]['f1'][0].strides, r[0:3:2][0]['f1'].strides) + + def test_alignment_update(self): + # Check that alignment flag is updated on stride setting + a = np.arange(10) + assert_(a.flags.aligned) + with pytest.warns(DeprecationWarning): + a.strides = 3 + assert_(not a.flags.aligned) + + def test_ticket_1770(self): + "Should not segfault on python 3k" + import numpy as np + try: + a = np.zeros((1,), dtype=[('f1', 'f')]) + a['f1'] = 1 + a['f2'] = 1 + except ValueError: + pass + except Exception: + raise AssertionError + + def test_ticket_1608(self): + "x.flat shouldn't modify data" + x = np.array([[1, 2], [3, 4]]).T + np.array(x.flat) + assert_equal(x, [[1, 3], [2, 4]]) + + def test_pickle_string_overwrite(self): + import re + + data = np.array([1], dtype='b') + blob = pickle.dumps(data, protocol=1) + data = pickle.loads(blob) + + # Check that loads does not clobber interned strings + s = re.sub(r"a(.)", "\x01\\1", "a_") + assert_equal(s[0], "\x01") + data[0] = 0x6a + s = re.sub(r"a(.)", "\x01\\1", "a_") + assert_equal(s[0], "\x01") + + def test_pickle_bytes_overwrite(self): + for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): + data = np.array([1], dtype='b') + data = pickle.loads(pickle.dumps(data, protocol=proto)) + data[0] = 0x7d + bytestring = "\x01 ".encode('ascii') + assert_equal(bytestring[0:1], '\x01'.encode('ascii')) + + @pytest.mark.filterwarnings( + "ignore:.*align should be passed:numpy.exceptions.VisibleDeprecationWarning") + def test_pickle_py2_array_latin1_hack(self): + # Check that unpickling hacks in Py3 that support + # encoding='latin1' work correctly. + + # Python2 output for pickle.dumps(numpy.array([129], dtype='b')) + data = b"cnumpy.core.multiarray\n_reconstruct\np0\n(cnumpy\nndarray\np1\n(I0\ntp2\nS'b'\np3\ntp4\nRp5\n(I1\n(I1\ntp6\ncnumpy\ndtype\np7\n(S'i1'\np8\nI0\nI1\ntp9\nRp10\n(I3\nS'|'\np11\nNNNI-1\nI-1\nI0\ntp12\nbI00\nS'\\x81'\np13\ntp14\nb." + # This should work: + result = pickle.loads(data, encoding='latin1') + assert_array_equal(result, np.array([129]).astype('b')) + # Should not segfault: + assert_raises(Exception, pickle.loads, data, encoding='koi8-r') + + @pytest.mark.filterwarnings( + "ignore:.*align should be passed:numpy.exceptions.VisibleDeprecationWarning") + def test_pickle_py2_scalar_latin1_hack(self): + # Check that scalar unpickling hack in Py3 that supports + # encoding='latin1' work correctly. + + # Python2 output for pickle.dumps(...) + datas = [ + # (original, python2_pickle, koi8r_validity) + (np.str_('\u6bd2'), + b"cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'U1'\np2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI4\nI4\nI0\ntp6\nbS'\\xd2k\\x00\\x00'\np7\ntp8\nRp9\n.", + 'invalid'), + + (np.float64(9e123), + b"cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'f8'\np2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI-1\nI-1\nI0\ntp6\nbS'O\\x81\\xb7Z\\xaa:\\xabY'\np7\ntp8\nRp9\n.", + 'invalid'), + + # different 8-bit code point in KOI8-R vs latin1 + (np.bytes_(b'\x9c'), + b"cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'S1'\np2\nI0\nI1\ntp3\nRp4\n(I3\nS'|'\np5\nNNNI1\nI1\nI0\ntp6\nbS'\\x9c'\np7\ntp8\nRp9\n.", + 'different'), + ] + for original, data, koi8r_validity in datas: + result = pickle.loads(data, encoding='latin1') + assert_equal(result, original) + + # Decoding under non-latin1 encoding (e.g.) KOI8-R can + # produce bad results, but should not segfault. + if koi8r_validity == 'different': + # Unicode code points happen to lie within latin1, + # but are different in koi8-r, resulting to silent + # bogus results + result = pickle.loads(data, encoding='koi8-r') + assert_(result != original) + elif koi8r_validity == 'invalid': + # Unicode code points outside latin1, so results + # to an encoding exception + assert_raises( + ValueError, pickle.loads, data, encoding='koi8-r' + ) + else: + raise ValueError(koi8r_validity) + + def test_structured_type_to_object(self): + a_rec = np.array([(0, 1), (3, 2)], dtype='i4,i8') + a_obj = np.empty((2,), dtype=object) + a_obj[0] = (0, 1) + a_obj[1] = (3, 2) + # astype records -> object + assert_equal(a_rec.astype(object), a_obj) + # '=' records -> object + b = np.empty_like(a_obj) + b[...] = a_rec + assert_equal(b, a_obj) + # '=' object -> records + b = np.empty_like(a_rec) + b[...] = a_obj + assert_equal(b, a_rec) + + def test_assign_obj_listoflists(self): + # Ticket # 1870 + # The inner list should get assigned to the object elements + a = np.zeros(4, dtype=object) + b = a.copy() + a[0] = [1] + a[1] = [2] + a[2] = [3] + a[3] = [4] + b[...] = [[1], [2], [3], [4]] + assert_equal(a, b) + # The first dimension should get broadcast + a = np.zeros((2, 2), dtype=object) + a[...] = [[1, 2]] + assert_equal(a, [[1, 2], [1, 2]]) + + @pytest.mark.slow_pypy + def test_memoryleak(self): + # Ticket #1917 - ensure that array data doesn't leak + for i in range(1000): + # 100MB times 1000 would give 100GB of memory usage if it leaks + a = np.empty((100000000,), dtype='i1') + del a + + @pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") + def test_ufunc_reduce_memoryleak(self): + a = np.arange(6) + acnt = sys.getrefcount(a) + np.add.reduce(a) + assert_equal(sys.getrefcount(a), acnt) + + def test_search_sorted_invalid_arguments(self): + # Ticket #2021, should not segfault. + x = np.arange(0, 4, dtype='datetime64[D]') + assert_raises(TypeError, x.searchsorted, 1) + + def test_string_truncation(self): + # Ticket #1990 - Data can be truncated in creation of an array from a + # mixed sequence of numeric values and strings (gh-2583) + for val in [True, 1234, 123.4, complex(1, 234)]: + for tostr, dtype in [(asunicode, "U"), (asbytes, "S")]: + b = np.array([val, tostr('xx')], dtype=dtype) + assert_equal(tostr(b[0]), tostr(val)) + b = np.array([tostr('xx'), val], dtype=dtype) + assert_equal(tostr(b[1]), tostr(val)) + + # test also with longer strings + b = np.array([val, tostr('xxxxxxxxxx')], dtype=dtype) + assert_equal(tostr(b[0]), tostr(val)) + b = np.array([tostr('xxxxxxxxxx'), val], dtype=dtype) + assert_equal(tostr(b[1]), tostr(val)) + + def test_string_truncation_ucs2(self): + # Ticket #2081. Python compiled with two byte unicode + # can lead to truncation if itemsize is not properly + # adjusted for NumPy's four byte unicode. + a = np.array(['abcd']) + assert_equal(a.dtype.itemsize, 16) + + def test_unique_stable(self): + # Ticket #2063 must always choose stable sort for argsort to + # get consistent results + v = np.array(([0] * 5 + [1] * 6 + [2] * 6) * 4) + res = np.unique(v, return_index=True) + tgt = (np.array([0, 1, 2]), np.array([0, 5, 11])) + assert_equal(res, tgt) + + def test_unicode_alloc_dealloc_match(self): + # Ticket #1578, the mismatch only showed up when running + # python-debug for python versions >= 2.7, and then as + # a core dump and error message. + a = np.array(['abc'], dtype=np.str_)[0] + del a + + def test_refcount_error_in_clip(self): + # Ticket #1588 + a = np.zeros((2,), dtype='>i2').clip(min=0) + x = a + a + # This used to segfault: + y = str(x) + # Check the final string: + assert_(y == "[0 0]") + + def test_searchsorted_wrong_dtype(self): + # Ticket #2189, it used to segfault, so we check that it raises the + # proper exception. + a = np.array([('a', 1)], dtype='S1, int') + assert_raises(TypeError, np.searchsorted, a, 1.2) + # Ticket #2066, similar problem: + dtype = np.rec.format_parser(['i4', 'i4'], [], []) + a = np.recarray((2,), dtype) + a[...] = [(1, 2), (3, 4)] + assert_raises(TypeError, np.searchsorted, a, 1) + + def test_complex64_alignment(self): + # Issue gh-2668 (trac 2076), segfault on sparc due to misalignment + dtt = np.complex64 + arr = np.arange(10, dtype=dtt) + # 2D array + arr2 = np.reshape(arr, (2, 5)) + # Fortran write followed by (C or F) read caused bus error + data_str = arr2.tobytes('F') + data_back = np.ndarray(arr2.shape, + arr2.dtype, + buffer=data_str, + order='F') + assert_array_equal(arr2, data_back) + + def test_structured_count_nonzero(self): + arr = np.array([0, 1]).astype('i4, 2i4')[:1] + count = np.count_nonzero(arr) + assert_equal(count, 0) + + def test_copymodule_preserves_f_contiguity(self): + a = np.empty((2, 2), order='F') + b = copy.copy(a) + c = copy.deepcopy(a) + assert_(b.flags.fortran) + assert_(b.flags.f_contiguous) + assert_(c.flags.fortran) + assert_(c.flags.f_contiguous) + + def test_fortran_order_buffer(self): + import numpy as np + a = np.array([['Hello', 'Foob']], dtype='U5', order='F') + arr = np.ndarray(shape=[1, 2, 5], dtype='U1', buffer=a) + arr2 = np.array([[['H', 'e', 'l', 'l', 'o'], + ['F', 'o', 'o', 'b', '']]]) + assert_array_equal(arr, arr2) + + def test_assign_from_sequence_error(self): + # Ticket #4024. + arr = np.array([1, 2, 3]) + assert_raises(ValueError, arr.__setitem__, slice(None), [9, 9]) + arr.__setitem__(slice(None), [9]) + assert_equal(arr, [9, 9, 9]) + + def test_format_on_flex_array_element(self): + # Ticket #4369. + dt = np.dtype([('date', ' 0: + # unpickling ndarray goes through _frombuffer for protocol 5 + assert b'numpy._core.numeric' in s + else: + assert b'numpy._core.multiarray' in s + + def test_object_casting_errors(self): + # gh-11993 update to ValueError (see gh-16909), since strings can in + # principle be converted to complex, but this string cannot. + arr = np.array(['AAAAA', 18465886.0, 18465886.0], dtype=object) + assert_raises(ValueError, arr.astype, 'c8') + + def test_eff1d_casting(self): + # gh-12711 + x = np.array([1, 2, 4, 7, 0], dtype=np.int16) + res = np.ediff1d(x, to_begin=-99, to_end=np.array([88, 99])) + assert_equal(res, [-99, 1, 2, 3, -7, 88, 99]) + + # The use of safe casting means, that 1<<20 is cast unsafely, an + # error may be better, but currently there is no mechanism for it. + res = np.ediff1d(x, to_begin=(1 << 20), to_end=(1 << 20)) + assert_equal(res, [0, 1, 2, 3, -7, 0]) + + def test_pickle_datetime64_array(self): + # gh-12745 (would fail with pickle5 installed) + d = np.datetime64('2015-07-04 12:59:59.50', 'ns') + arr = np.array([d]) + for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): + dumped = pickle.dumps(arr, protocol=proto) + assert_equal(pickle.loads(dumped), arr) + + def test_bad_array_interface(self): + class T: + __array_interface__ = {} + + with assert_raises(ValueError): + np.array([T()]) + + def test_2d__array__shape(self): + class T: + def __array__(self, dtype=None, copy=None): + return np.ndarray(shape=(0, 0)) + + # Make sure __array__ is used instead of Sequence methods. + def __iter__(self): + return iter([]) + + def __getitem__(self, idx): + raise AssertionError("__getitem__ was called") + + def __len__(self): + return 0 + + t = T() + # gh-13659, would raise in broadcasting [x=t for x in result] + arr = np.array([t]) + assert arr.shape == (1, 0, 0) + + @pytest.mark.skipif(sys.maxsize < 2 ** 31 + 1, reason='overflows 32-bit python') + def test_to_ctypes(self): + # gh-14214 + arr = np.zeros((2 ** 31 + 1,), 'b') + assert arr.size * arr.itemsize > 2 ** 31 + c_arr = np.ctypeslib.as_ctypes(arr) + assert_equal(c_arr._length_, arr.size) + + def test_complex_conversion_error(self): + # gh-17068 + with pytest.raises(TypeError, match=r"Unable to convert dtype.*"): + complex(np.array("now", np.datetime64)) + + def test__array_interface__descr(self): + # gh-17068 + dt = np.dtype({'names': ['a', 'b'], + 'offsets': [0, 0], + 'formats': [np.int64, np.int64]}) + descr = np.array((1, 1), dtype=dt).__array_interface__['descr'] + assert descr == [('', '|V8')] # instead of [(b'', '|V8')] + + @pytest.mark.skipif(sys.maxsize < 2 ** 31 + 1, reason='overflows 32-bit python') + @requires_memory(free_bytes=9e9) + @pytest.mark.thread_unsafe(reason="crashes with low memory") + def test_dot_big_stride(self): + # gh-17111 + # blas stride = stride//itemsize > int32 max + int32_max = np.iinfo(np.int32).max + n = int32_max + 3 + a = np.empty([n], dtype=np.float32) + b = a[::n - 1] + b[...] = 1 + assert b.strides[0] > int32_max * b.dtype.itemsize + assert np.dot(b, b) == 2.0 + + def test_frompyfunc_name(self): + # name conversion was failing for python 3 strings + # resulting in the default '?' name. Also test utf-8 + # encoding using non-ascii name. + def cassé(x): + return x + + f = np.frompyfunc(cassé, 1, 1) + assert str(f) == "" + + @pytest.mark.parametrize("operation", [ + 'add', 'subtract', 'multiply', 'floor_divide', + 'conjugate', 'fmod', 'square', 'reciprocal', + 'power', 'absolute', 'negative', 'positive', + 'greater', 'greater_equal', 'less', + 'less_equal', 'equal', 'not_equal', 'logical_and', + 'logical_not', 'logical_or', 'bitwise_and', 'bitwise_or', + 'bitwise_xor', 'invert', 'left_shift', 'right_shift', + 'gcd', 'lcm' + ] + ) + @pytest.mark.parametrize("order", [ + ('b->', 'B->'), + ('h->', 'H->'), + ('i->', 'I->'), + ('l->', 'L->'), + ('q->', 'Q->'), + ] + ) + def test_ufunc_order(self, operation, order): + # gh-18075 + # Ensure signed types before unsigned + def get_idx(string, str_lst): + for i, s in enumerate(str_lst): + if string in s: + return i + raise ValueError(f"{string} not in list") + types = getattr(np, operation).types + assert get_idx(order[0], types) < get_idx(order[1], types), ( + f"Unexpected types order of ufunc in {operation}" + f"for {order}. Possible fix: Use signed before unsigned" + "in generate_umath.py") + + def test_nonbool_logical(self): + # gh-22845 + # create two arrays with bit patterns that do not overlap. + # needs to be large enough to test both SIMD and scalar paths + size = 100 + a = np.frombuffer(b'\x01' * size, dtype=np.bool) + b = np.frombuffer(b'\x80' * size, dtype=np.bool) + expected = np.ones(size, dtype=np.bool) + assert_array_equal(np.logical_and(a, b), expected) + + @pytest.mark.skipif(IS_PYPY, reason="PyPy issue 2742") + def test_gh_23737(self): + with pytest.raises(TypeError, match="not an acceptable base type"): + class Y(np.flexible): + pass + + with pytest.raises(TypeError, match="not an acceptable base type"): + class X(np.flexible, np.ma.core.MaskedArray): + pass + + def test_load_ufunc_pickle(self): + # ufuncs are pickled with a semi-private path in + # numpy.core._multiarray_umath and must be loadable without warning + # despite np.core being deprecated. + test_data = b'\x80\x04\x95(\x00\x00\x00\x00\x00\x00\x00\x8c\x1cnumpy.core._multiarray_umath\x94\x8c\x03add\x94\x93\x94.' + result = pickle.loads(test_data, encoding='bytes') + assert result is np.add + + def test__array_namespace__(self): + arr = np.arange(2) + + xp = arr.__array_namespace__() + assert xp is np + xp = arr.__array_namespace__(api_version="2021.12") + assert xp is np + xp = arr.__array_namespace__(api_version="2022.12") + assert xp is np + xp = arr.__array_namespace__(api_version="2023.12") + assert xp is np + xp = arr.__array_namespace__(api_version="2024.12") + assert xp is np + xp = arr.__array_namespace__(api_version=None) + assert xp is np + + with pytest.raises( + ValueError, + match="Version \"2025.12\" of the Array API Standard " + "is not supported." + ): + arr.__array_namespace__(api_version="2025.12") + + with pytest.raises( + ValueError, + match="Only None and strings are allowed as the Array API version" + ): + arr.__array_namespace__(api_version=2024) + + def test_isin_refcnt_bug(self): + # gh-25295 + for _ in range(1000): + np.isclose(np.int64(2), np.int64(2), atol=1e-15, rtol=1e-300) + + def test_replace_regression(self): + # gh-25513 segfault + carr = np.char.chararray((2,), itemsize=25) + test_strings = [b' 4.52173913043478315E+00', + b' 4.95652173913043548E+00'] + carr[:] = test_strings + out = carr.replace(b"E", b"D") + expected = np.char.chararray((2,), itemsize=25) + expected[:] = [s.replace(b"E", b"D") for s in test_strings] + assert_array_equal(out, expected) + + def test_logspace_base_does_not_determine_dtype(self): + # gh-24957 and cupy/cupy/issues/7946 + start = np.array([0, 2], dtype=np.float16) + stop = np.array([2, 0], dtype=np.float16) + out = np.logspace(start, stop, num=5, axis=1, dtype=np.float32) + expected = np.array([[1., 3.1621094, 10., 31.625, 100.], + [100., 31.625, 10., 3.1621094, 1.]], + dtype=np.float32) + assert_almost_equal(out, expected) + # Check test fails if the calculation is done in float64, as happened + # before when a python float base incorrectly influenced the dtype. + out2 = np.logspace(start, stop, num=5, axis=1, dtype=np.float32, + base=np.array([10.0])) + with pytest.raises(AssertionError, match="not almost equal"): + assert_almost_equal(out2, expected) + + def test_vectorize_fixed_width_string(self): + arr = np.array(["SOme wOrd DŽ ß ᾛ ΣΣ ffi⁵Å Ç Ⅰ"]).astype(np.str_) + f = str.casefold + res = np.vectorize(f, otypes=[arr.dtype])(arr) + assert res.dtype == "U30" + + def test_repeated_square_consistency(self): + # gh-26940 + buf = np.array([-5.171866611150749e-07 + 2.5618634555957426e-07j, + 0, 0, 0, 0, 0]) + # Test buffer with regular and reverse strides + for in_vec in [buf[:3], buf[:3][::-1]]: + expected_res = np.square(in_vec) + # Output vector immediately follows input vector + # to reproduce off-by-one in nomemoverlap check. + for res in [buf[3:], buf[3:][::-1]]: + res = buf[3:] + np.square(in_vec, out=res) + assert_equal(res, expected_res) + + def test_sort_unique_crash(self): + # gh-27037 + for _ in range(4): + vals = np.linspace(0, 1, num=128) + data = np.broadcast_to(vals, (128, 128, 128)) + data = data.transpose(0, 2, 1).copy() + np.unique(data) + + def test_sort_overlap(self): + # gh-27273 + size = 100 + inp = np.linspace(0, size, num=size, dtype=np.intc) + out = np.sort(inp) + assert_equal(inp, out) + + def test_searchsorted_structured(self): + # gh-28190 + x = np.array([(0, 1.)], dtype=[('time', ' None: + cls = np.dtype(code).type + value = cls(str_value) + assert not value.is_integer() + + @pytest.mark.parametrize( + "code", np.typecodes["Float"] + np.typecodes["AllInteger"] + ) + def test_true(self, code: str) -> None: + float_array = np.arange(-5, 5).astype(code) + for value in float_array: + assert value.is_integer() + + @pytest.mark.parametrize("code", np.typecodes["Float"]) + def test_false(self, code: str) -> None: + float_array = np.arange(-5, 5).astype(code) + float_array *= 1.1 + for value in float_array: + if value == 0: + continue + assert not value.is_integer() + + +class TestClassGetItem: + @pytest.mark.parametrize("cls", [ + np.number, + np.integer, + np.inexact, + np.unsignedinteger, + np.signedinteger, + np.floating, + ]) + def test_abc(self, cls: type[np.number]) -> None: + alias = cls[Any] + assert isinstance(alias, types.GenericAlias) + assert alias.__origin__ is cls + + def test_abc_complexfloating(self) -> None: + alias = np.complexfloating[Any, Any] + assert isinstance(alias, types.GenericAlias) + assert alias.__origin__ is np.complexfloating + + @pytest.mark.parametrize("arg_len", range(4)) + def test_abc_complexfloating_subscript_tuple(self, arg_len: int) -> None: + arg_tup = (Any,) * arg_len + if arg_len in (1, 2): + assert np.complexfloating[arg_tup] + else: + match = f"Too {'few' if arg_len == 0 else 'many'} arguments" + with pytest.raises(TypeError, match=match): + np.complexfloating[arg_tup] + + @pytest.mark.parametrize("cls", [np.generic, np.flexible, np.character]) + def test_abc_non_numeric(self, cls: type[np.generic]) -> None: + with pytest.raises(TypeError): + cls[Any] + + @pytest.mark.parametrize("code", np.typecodes["All"]) + def test_concrete(self, code: str) -> None: + cls = np.dtype(code).type + if cls in {np.bool, np.datetime64}: + # these are intentionally subscriptable + assert cls[Any] + else: + with pytest.raises(TypeError): + cls[Any] + + @pytest.mark.parametrize("arg_len", range(4)) + def test_subscript_tuple(self, arg_len: int) -> None: + arg_tup = (Any,) * arg_len + if arg_len == 1: + assert np.number[arg_tup] + else: + with pytest.raises(TypeError): + np.number[arg_tup] + + def test_subscript_scalar(self) -> None: + assert np.number[Any] + + @pytest.mark.parametrize("subscript", [Literal[True], Literal[False]]) + def test_subscript_bool(self, subscript: Literal[True, False]) -> None: + assert isinstance(np.bool[subscript], types.GenericAlias) + + +class TestBitCount: + # derived in part from the cpython test "test_bit_count" + + @pytest.mark.parametrize("itype", sctypes['int'] + sctypes['uint']) + def test_small(self, itype): + for a in range(max(np.iinfo(itype).min, 0), 128): + msg = f"Smoke test for {itype}({a}).bit_count()" + assert itype(a).bit_count() == a.bit_count(), msg + + def test_bit_count(self): + for exp in [10, 17, 63]: + a = 2**exp + assert np.uint64(a).bit_count() == 1 + assert np.uint64(a - 1).bit_count() == exp + assert np.uint64(a ^ 63).bit_count() == 7 + assert np.uint64((a - 1) ^ 510).bit_count() == exp - 8 + + +class TestDevice: + """ + Test scalar.device attribute and scalar.to_device() method. + """ + scalars = [np.bool(True), np.int64(1), np.uint64(1), np.float64(1.0), + np.complex128(1 + 1j)] + + @pytest.mark.parametrize("scalar", scalars) + def test_device(self, scalar): + assert scalar.device == "cpu" + + @pytest.mark.parametrize("scalar", scalars) + def test_to_device(self, scalar): + assert scalar.to_device("cpu") is scalar + + @pytest.mark.parametrize("scalar", scalars) + def test___array_namespace__(self, scalar): + assert scalar.__array_namespace__() is np + + +@pytest.mark.parametrize("scalar", [np.bool(True), np.int8(1), np.float64(1)]) +def test_array_wrap(scalar): + # Test scalars array wrap as long as it exists. NumPy itself should + # probably not use it, so it may not be necessary to keep it around. + + arr0d = np.array(3, dtype=np.int8) + # Third argument not passed, None, or True "decays" to scalar. + # (I don't think NumPy would pass `None`, but it seems clear to support) + assert type(scalar.__array_wrap__(arr0d)) is np.int8 + assert type(scalar.__array_wrap__(arr0d, None, None)) is np.int8 + assert type(scalar.__array_wrap__(arr0d, None, True)) is np.int8 + + # Otherwise, result should be the input + assert scalar.__array_wrap__(arr0d, None, False) is arr0d + + # An old bug. A non 0-d array cannot be converted to scalar: + arr1d = np.array([3], dtype=np.int8) + assert scalar.__array_wrap__(arr1d) is arr1d + assert scalar.__array_wrap__(arr1d, None, True) is arr1d + + +@pytest.mark.skipif(sys.flags.optimize == 2, reason="Python running -OO") +@pytest.mark.skipif(IS_PYPY, reason="PyPy does not modify tp_doc") +class TestSignature: + # test that scalar types have a valid __text_signature__ or __signature__ set + @pytest.mark.parametrize( + "sctype", + [ + *sctypes["int"], + *sctypes["uint"], + *sctypes["float"], + *sctypes["complex"], + *sctypes["others"], + np.datetime64, + np.timedelta64, + ], + ) + def test_constructor_signatures(self, sctype: type[np.generic]): + try: + sig = inspect.signature(sctype) + except ValueError: + pytest.fail(f"missing signature: {sctype}") + + assert sig.parameters + + @pytest.mark.parametrize( + "sctype", + [np.integer, *sctypes["int"], *sctypes["uint"], *sctypes["float"]], + ) + def test_method_signatures_is_integer(self, sctype: type[np.integer | np.floating]): + try: + sig = inspect.signature(sctype.is_integer) + except ValueError: + pytest.fail(f"missing signature: {sctype.__name__}.is_integer") + + assert len(sig.parameters) == 1 + assert sig.parameters["self"].kind == inspect.Parameter.POSITIONAL_ONLY + + @pytest.mark.parametrize("sctype", sctypes["float"]) + def test_method_signatures_as_integer_ratio(self, sctype: type[np.floating]): + try: + sig = inspect.signature(sctype.as_integer_ratio) + except ValueError: + pytest.fail(f"missing signature: {sctype.__name__}.as_integer_ratio") + + assert len(sig.parameters) == 1 + assert sig.parameters["self"].kind == inspect.Parameter.POSITIONAL_ONLY + + @pytest.mark.parametrize( + "method_name", + [ + "__array_namespace__", "__copy__", "__deepcopy__", "all", "any", "argmax", + "argmin", "argsort", "astype", "byteswap", "choose", "clip", "compress", + "conj", "conjugate", "copy", "cumprod", "cumsum", "diagonal", "dump", + "dumps", "fill", "flatten", "getfield", "item", "max", "mean", "min", + "nonzero", "prod", "put", "ravel", "repeat", "reshape", "resize", "round", + "searchsorted", "setfield", "setflags", "sort", "squeeze", "std", "sum", + "swapaxes", "take", "to_device", "tobytes", "tofile", "tolist", "trace", + "transpose", "var", "view", + ], + ) + def test_array_scalar_method_signatures(self, method_name: str): + # methods shared by np.generic and np.ndarray should have the same signature + fn_generic = getattr(np.generic, method_name) + sig_generic = inspect.signature(fn_generic) + assert "self" in sig_generic.parameters + assert sig_generic.parameters["self"].kind is inspect.Parameter.POSITIONAL_ONLY + + fn_ndarray = getattr(np.ndarray, method_name) + sig_ndarray = inspect.signature(fn_ndarray) + assert sig_generic == sig_ndarray diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_scalarbuffer.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_scalarbuffer.py new file mode 100644 index 0000000000000000000000000000000000000000..4d2744b85e53ca1dd7cd07f118aa621eb3f7c1ce --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_scalarbuffer.py @@ -0,0 +1,153 @@ +""" +Test scalar buffer interface adheres to PEP 3118 +""" +import pytest + +import numpy as np +from numpy._core._multiarray_tests import get_buffer_info +from numpy._core._rational_tests import rational +from numpy.testing import assert_, assert_equal, assert_raises + +# PEP3118 format strings for native (standard alignment and byteorder) types +scalars_and_codes = [ + (np.bool, '?'), + (np.byte, 'b'), + (np.short, 'h'), + (np.intc, 'i'), + (np.long, 'l'), + (np.longlong, 'q'), + (np.ubyte, 'B'), + (np.ushort, 'H'), + (np.uintc, 'I'), + (np.ulong, 'L'), + (np.ulonglong, 'Q'), + (np.half, 'e'), + (np.single, 'f'), + (np.double, 'd'), + (np.longdouble, 'g'), + (np.csingle, 'Zf'), + (np.cdouble, 'Zd'), + (np.clongdouble, 'Zg'), +] +scalars_only, codes_only = zip(*scalars_and_codes) + + +class TestScalarPEP3118: + + @pytest.mark.parametrize('scalar', scalars_only, ids=codes_only) + def test_scalar_match_array(self, scalar): + x = scalar() + a = np.array([], dtype=np.dtype(scalar)) + mv_x = memoryview(x) + mv_a = memoryview(a) + assert_equal(mv_x.format, mv_a.format) + + @pytest.mark.parametrize('scalar', scalars_only, ids=codes_only) + def test_scalar_dim(self, scalar): + x = scalar() + mv_x = memoryview(x) + assert_equal(mv_x.itemsize, np.dtype(scalar).itemsize) + assert_equal(mv_x.ndim, 0) + assert_equal(mv_x.shape, ()) + assert_equal(mv_x.strides, ()) + assert_equal(mv_x.suboffsets, ()) + + @pytest.mark.parametrize('scalar, code', scalars_and_codes, ids=codes_only) + def test_scalar_code_and_properties(self, scalar, code): + x = scalar() + expected = {'strides': (), 'itemsize': x.dtype.itemsize, 'ndim': 0, + 'shape': (), 'format': code, 'readonly': True} + + mv_x = memoryview(x) + assert self._as_dict(mv_x) == expected + + @pytest.mark.parametrize('scalar', scalars_only, ids=codes_only) + def test_scalar_buffers_readonly(self, scalar): + x = scalar() + with pytest.raises(BufferError, match="scalar buffer is readonly"): + get_buffer_info(x, ["WRITABLE"]) + + def test_void_scalar_structured_data(self): + dt = np.dtype([('name', np.str_, 16), ('grades', np.float64, (2,))]) + x = np.array(('ndarray_scalar', (1.2, 3.0)), dtype=dt)[()] + assert_(isinstance(x, np.void)) + mv_x = memoryview(x) + expected_size = 16 * np.dtype((np.str_, 1)).itemsize + expected_size += 2 * np.dtype(np.float64).itemsize + assert_equal(mv_x.itemsize, expected_size) + assert_equal(mv_x.ndim, 0) + assert_equal(mv_x.shape, ()) + assert_equal(mv_x.strides, ()) + assert_equal(mv_x.suboffsets, ()) + + # check scalar format string against ndarray format string + a = np.array([('Sarah', (8.0, 7.0)), ('John', (6.0, 7.0))], dtype=dt) + assert_(isinstance(a, np.ndarray)) + mv_a = memoryview(a) + assert_equal(mv_x.itemsize, mv_a.itemsize) + assert_equal(mv_x.format, mv_a.format) + + # Check that we do not allow writeable buffer export (technically + # we could allow it sometimes here...) + with pytest.raises(BufferError, match="scalar buffer is readonly"): + get_buffer_info(x, ["WRITABLE"]) + + def _as_dict(self, m): + return {'strides': m.strides, 'shape': m.shape, 'itemsize': m.itemsize, + 'ndim': m.ndim, 'format': m.format, 'readonly': m.readonly} + + def test_datetime_memoryview(self): + # gh-11656 + # Values verified with v1.13.3, shape is not () as in test_scalar_dim + + dt1 = np.datetime64('2016-01-01') + dt2 = np.datetime64('2017-01-01') + expected = {'strides': (1,), 'itemsize': 1, 'ndim': 1, 'shape': (8,), + 'format': 'B', 'readonly': True} + v = memoryview(dt1) + assert self._as_dict(v) == expected + + v = memoryview(dt2 - dt1) + assert self._as_dict(v) == expected + + dt = np.dtype([('a', 'uint16'), ('b', 'M8[s]')]) + a = np.empty(1, dt) + # Fails to create a PEP 3118 valid buffer + assert_raises((ValueError, BufferError), memoryview, a[0]) + + # Check that we do not allow writeable buffer export + with pytest.raises(BufferError, match="scalar buffer is readonly"): + get_buffer_info(dt1, ["WRITABLE"]) + + @pytest.mark.parametrize('s', [ + pytest.param("\x32\x32", id="ascii"), + pytest.param("\uFE0F\uFE0F", id="basic multilingual"), + pytest.param("\U0001f4bb\U0001f4bb", id="non-BMP"), + ]) + def test_str_ucs4(self, s): + s = np.str_(s) # only our subclass implements the buffer protocol + + # all the same, characters always encode as ucs4 + expected = {'strides': (), 'itemsize': 8, 'ndim': 0, 'shape': (), + 'format': '2w', 'readonly': True} + + v = memoryview(s) + assert self._as_dict(v) == expected + + # integers of the paltform-appropriate endianness + code_points = np.frombuffer(v, dtype='i4') + + assert_equal(code_points, [ord(c) for c in s]) + + # Check that we do not allow writeable buffer export + with pytest.raises(BufferError, match="scalar buffer is readonly"): + get_buffer_info(s, ["WRITABLE"]) + + def test_user_scalar_fails_buffer(self): + r = rational(1) + with assert_raises(TypeError): + memoryview(r) + + # Check that we do not allow writeable buffer export + with pytest.raises(BufferError, match="scalar buffer is readonly"): + get_buffer_info(r, ["WRITABLE"]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_scalarinherit.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_scalarinherit.py new file mode 100644 index 0000000000000000000000000000000000000000..746a1574782a4709439bd047c92655dfb4d2fcb4 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_scalarinherit.py @@ -0,0 +1,105 @@ +""" Test printing of scalar types. + +""" +import pytest + +import numpy as np +from numpy.testing import assert_, assert_raises + + +class A: + pass +class B(A, np.float64): + pass + +class C(B): + pass +class D(C, B): + pass + +class B0(np.float64, A): + pass +class C0(B0): + pass + +class HasNew: + def __new__(cls, *args, **kwargs): + return cls, args, kwargs + +class B1(np.float64, HasNew): + pass + + +class TestInherit: + def test_init(self): + x = B(1.0) + assert_(str(x) == '1.0') + y = C(2.0) + assert_(str(y) == '2.0') + z = D(3.0) + assert_(str(z) == '3.0') + + def test_init2(self): + x = B0(1.0) + assert_(str(x) == '1.0') + y = C0(2.0) + assert_(str(y) == '2.0') + + def test_gh_15395(self): + # HasNew is the second base, so `np.float64` should have priority + x = B1(1.0) + assert_(str(x) == '1.0') + + # previously caused RecursionError!? + with pytest.raises(TypeError): + B1(1.0, 2.0) + + def test_int_repr(self): + # Test that integer repr works correctly for subclasses (gh-27106) + class my_int16(np.int16): + pass + + s = repr(my_int16(3)) + assert s == "my_int16(3)" + +class TestCharacter: + def test_char_radd(self): + # GH issue 9620, reached gentype_add and raise TypeError + np_s = np.bytes_('abc') + np_u = np.str_('abc') + s = b'def' + u = 'def' + assert_(np_s.__radd__(np_s) is NotImplemented) + assert_(np_s.__radd__(np_u) is NotImplemented) + assert_(np_s.__radd__(s) is NotImplemented) + assert_(np_s.__radd__(u) is NotImplemented) + assert_(np_u.__radd__(np_s) is NotImplemented) + assert_(np_u.__radd__(np_u) is NotImplemented) + assert_(np_u.__radd__(s) is NotImplemented) + assert_(np_u.__radd__(u) is NotImplemented) + assert_(s + np_s == b'defabc') + assert_(u + np_u == 'defabc') + + class MyStr(str, np.generic): + # would segfault + pass + + with assert_raises(TypeError): + # Previously worked, but gave completely wrong result + ret = s + MyStr('abc') + + class MyBytes(bytes, np.generic): + # would segfault + pass + + ret = s + MyBytes(b'abc') + assert type(ret) is type(s) + assert ret == b"defabc" + + def test_char_repeat(self): + np_s = np.bytes_('abc') + np_u = np.str_('abc') + res_s = b'abc' * 5 + res_u = 'abc' * 5 + assert_(np_s * 5 == res_s) + assert_(np_u * 5 == res_u) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_scalarmath.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_scalarmath.py new file mode 100644 index 0000000000000000000000000000000000000000..bfbc9a54cbfe5808e65787dbfa12401c8e41ee5c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_scalarmath.py @@ -0,0 +1,1168 @@ +import contextlib +import itertools +import operator +import platform +import sys +import warnings + +import pytest +from hypothesis import given, settings +from hypothesis.extra import numpy as hynp +from hypothesis.strategies import sampled_from + +import numpy as np +from numpy._core._rational_tests import rational +from numpy._utils import _pep440 +from numpy.exceptions import ComplexWarning +from numpy.testing import ( + IS_PYPY, + _gen_alignment_data, + assert_, + assert_almost_equal, + assert_array_equal, + assert_equal, + assert_raises, + check_support_sve, +) + +types = [np.bool, np.byte, np.ubyte, np.short, np.ushort, np.intc, np.uintc, + np.int_, np.uint, np.longlong, np.ulonglong, + np.single, np.double, np.longdouble, np.csingle, + np.cdouble, np.clongdouble] + +floating_types = np.floating.__subclasses__() +complex_floating_types = np.complexfloating.__subclasses__() + +objecty_things = [object(), None, np.array(None, dtype=object)] + +binary_operators_for_scalars = [ + operator.lt, operator.le, operator.eq, operator.ne, operator.ge, + operator.gt, operator.add, operator.floordiv, operator.mod, + operator.mul, operator.pow, operator.sub, operator.truediv +] +binary_operators_for_scalar_ints = binary_operators_for_scalars + [ + operator.xor, operator.or_, operator.and_ +] + + +# This compares scalarmath against ufuncs. + +class TestTypes: + def test_types(self): + for atype in types: + a = atype(1) + assert_(a == 1, f"error with {atype!r}: got {a!r}") + + def test_type_add(self): + # list of types + for k, atype in enumerate(types): + a_scalar = atype(3) + a_array = np.array([3], dtype=atype) + for l, btype in enumerate(types): + b_scalar = btype(1) + b_array = np.array([1], dtype=btype) + c_scalar = a_scalar + b_scalar + c_array = a_array + b_array + # It was comparing the type numbers, but the new ufunc + # function-finding mechanism finds the lowest function + # to which both inputs can be cast - which produces 'l' + # when you do 'q' + 'b'. The old function finding mechanism + # skipped ahead based on the first argument, but that + # does not produce properly symmetric results... + assert_equal(c_scalar.dtype, c_array.dtype, + "error with types (%d/'%c' + %d/'%c')" % + (k, np.dtype(atype).char, l, np.dtype(btype).char)) + + def test_type_create(self): + for atype in types: + a = np.array([1, 2, 3], atype) + b = atype([1, 2, 3]) + assert_equal(a, b) + + def test_leak(self): + # test leak of scalar objects + # a leak would show up in valgrind as still-reachable of ~2.6MB + for i in range(200000): + np.add(1, 1) + + +def check_ufunc_scalar_equivalence(op, arr1, arr2): + scalar1 = arr1[()] + scalar2 = arr2[()] + assert isinstance(scalar1, np.generic) + assert isinstance(scalar2, np.generic) + + if arr1.dtype.kind == "c" or arr2.dtype.kind == "c": + comp_ops = {operator.ge, operator.gt, operator.le, operator.lt} + if op in comp_ops and (np.isnan(scalar1) or np.isnan(scalar2)): + pytest.xfail("complex comp ufuncs use sort-order, scalars do not.") + if op == operator.pow and arr2.item() in [-1, 0, 0.5, 1, 2]: + # array**scalar special case can have different result dtype + # (Other powers may have issues also, but are not hit here.) + # TODO: It would be nice to resolve this issue. + pytest.skip("array**2 can have incorrect/weird result dtype") + + # ignore fpe's since they may just mismatch for integers anyway. + with warnings.catch_warnings(), np.errstate(all="ignore"): + # Comparisons DeprecationWarnings replacing errors (2022-03): + warnings.simplefilter("error", DeprecationWarning) + try: + res = op(arr1, arr2) + except Exception as e: + with pytest.raises(type(e)): + op(scalar1, scalar2) + else: + scalar_res = op(scalar1, scalar2) + assert_array_equal(scalar_res, res, strict=True) + + +@pytest.mark.slow +@settings(max_examples=10000, deadline=2000) +@given(sampled_from(binary_operators_for_scalars), + hynp.arrays(dtype=hynp.scalar_dtypes(), shape=()), + hynp.arrays(dtype=hynp.scalar_dtypes(), shape=())) +def test_array_scalar_ufunc_equivalence(op, arr1, arr2): + """ + This is a thorough test attempting to cover important promotion paths + and ensuring that arrays and scalars stay as aligned as possible. + However, if it creates troubles, it should maybe just be removed. + """ + check_ufunc_scalar_equivalence(op, arr1, arr2) + + +@pytest.mark.slow +@given(sampled_from(binary_operators_for_scalars), + hynp.scalar_dtypes(), hynp.scalar_dtypes()) +def test_array_scalar_ufunc_dtypes(op, dt1, dt2): + # Same as above, but don't worry about sampling weird values so that we + # do not have to sample as much + arr1 = np.array(2, dtype=dt1) + arr2 = np.array(3, dtype=dt2) # some power do weird things. + + check_ufunc_scalar_equivalence(op, arr1, arr2) + + +@pytest.mark.parametrize("fscalar", [np.float16, np.float32]) +def test_int_float_promotion_truediv(fscalar): + # Promotion for mixed int and float32/float16 must not go to float64 + i = np.int8(1) + f = fscalar(1) + expected = np.result_type(i, f) + assert (i / f).dtype == expected + assert (f / i).dtype == expected + # But normal int / int true division goes to float64: + assert (i / i).dtype == np.dtype("float64") + # For int16, result has to be ast least float32 (takes ufunc path): + assert (np.int16(1) / f).dtype == np.dtype("float32") + + +class TestBaseMath: + @pytest.mark.xfail(check_support_sve(), reason="gh-22982") + def test_blocked(self): + # test alignments offsets for simd instructions + # alignments for vz + 2 * (vs - 1) + 1 + for dt, sz in [(np.float32, 11), (np.float64, 7), (np.int32, 11)]: + for out, inp1, inp2, msg in _gen_alignment_data(dtype=dt, + type='binary', + max_size=sz): + exp1 = np.ones_like(inp1) + inp1[...] = np.ones_like(inp1) + inp2[...] = np.zeros_like(inp2) + assert_almost_equal(np.add(inp1, inp2), exp1, err_msg=msg) + assert_almost_equal(np.add(inp1, 2), exp1 + 2, err_msg=msg) + assert_almost_equal(np.add(1, inp2), exp1, err_msg=msg) + + np.add(inp1, inp2, out=out) + assert_almost_equal(out, exp1, err_msg=msg) + + inp2[...] += np.arange(inp2.size, dtype=dt) + 1 + assert_almost_equal(np.square(inp2), + np.multiply(inp2, inp2), err_msg=msg) + # skip true divide for ints + if dt != np.int32: + assert_almost_equal(np.reciprocal(inp2), + np.divide(1, inp2), err_msg=msg) + + inp1[...] = np.ones_like(inp1) + np.add(inp1, 2, out=out) + assert_almost_equal(out, exp1 + 2, err_msg=msg) + inp2[...] = np.ones_like(inp2) + np.add(2, inp2, out=out) + assert_almost_equal(out, exp1 + 2, err_msg=msg) + + def test_lower_align(self): + # check data that is not aligned to element size + # i.e doubles are aligned to 4 bytes on i386 + d = np.zeros(23 * 8, dtype=np.int8)[4:-4].view(np.float64) + o = np.zeros(23 * 8, dtype=np.int8)[4:-4].view(np.float64) + assert_almost_equal(d + d, d * 2) + np.add(d, d, out=o) + np.add(np.ones_like(d), d, out=o) + np.add(d, np.ones_like(d), out=o) + np.add(np.ones_like(d), d) + np.add(d, np.ones_like(d)) + + +class TestPower: + def test_small_types(self): + for t in [np.int8, np.int16, np.float16]: + a = t(3) + b = a ** 4 + assert_(b == 81, f"error with {t!r}: got {b!r}") + + def test_large_types(self): + for t in [np.int32, np.int64, np.float32, np.float64, np.longdouble]: + a = t(51) + b = a ** 4 + msg = f"error with {t!r}: got {b!r}" + if np.issubdtype(t, np.integer): + assert_(b == 6765201, msg) + else: + assert_almost_equal(b, 6765201, err_msg=msg) + + def test_integers_to_negative_integer_power(self): + # Note that the combination of uint64 with a signed integer + # has common type np.float64. The other combinations should all + # raise a ValueError for integer ** negative integer. + exp = [np.array(-1, dt)[()] for dt in 'bhilq'] + + # 1 ** -1 possible special case + base = [np.array(1, dt)[()] for dt in 'bhilqBHILQ'] + for i1, i2 in itertools.product(base, exp): + if i1.dtype != np.uint64: + assert_raises(ValueError, operator.pow, i1, i2) + else: + res = operator.pow(i1, i2) + assert_(res.dtype.type is np.float64) + assert_almost_equal(res, 1.) + + # -1 ** -1 possible special case + base = [np.array(-1, dt)[()] for dt in 'bhilq'] + for i1, i2 in itertools.product(base, exp): + if i1.dtype != np.uint64: + assert_raises(ValueError, operator.pow, i1, i2) + else: + res = operator.pow(i1, i2) + assert_(res.dtype.type is np.float64) + assert_almost_equal(res, -1.) + + # 2 ** -1 perhaps generic + base = [np.array(2, dt)[()] for dt in 'bhilqBHILQ'] + for i1, i2 in itertools.product(base, exp): + if i1.dtype != np.uint64: + assert_raises(ValueError, operator.pow, i1, i2) + else: + res = operator.pow(i1, i2) + assert_(res.dtype.type is np.float64) + assert_almost_equal(res, .5) + + def test_mixed_types(self): + typelist = [np.int8, np.int16, np.float16, + np.float32, np.float64, np.int8, + np.int16, np.int32, np.int64] + for t1 in typelist: + for t2 in typelist: + a = t1(3) + b = t2(2) + result = a**b + msg = f"error with {t1!r} and {t2!r}:got {result!r}, expected {9!r}" + if np.issubdtype(np.dtype(result), np.integer): + assert_(result == 9, msg) + else: + assert_almost_equal(result, 9, err_msg=msg) + + def test_modular_power(self): + # modular power is not implemented, so ensure it errors + a = 5 + b = 4 + c = 10 + expected = pow(a, b, c) # noqa: F841 + for t in (np.int32, np.float32, np.complex64): + # note that 3-operand power only dispatches on the first argument + assert_raises(TypeError, operator.pow, t(a), b, c) + assert_raises(TypeError, operator.pow, np.array(t(a)), b, c) + + +def floordiv_and_mod(x, y): + return (x // y, x % y) + + +def _signs(dt): + if dt in np.typecodes['UnsignedInteger']: + return (+1,) + else: + return (+1, -1) + + +class TestModulus: + + def test_modulus_basic(self): + dt = np.typecodes['AllInteger'] + np.typecodes['Float'] + for op in [floordiv_and_mod, divmod]: + for dt1, dt2 in itertools.product(dt, dt): + for sg1, sg2 in itertools.product(_signs(dt1), _signs(dt2)): + fmt = 'op: %s, dt1: %s, dt2: %s, sg1: %s, sg2: %s' + msg = fmt % (op.__name__, dt1, dt2, sg1, sg2) + a = np.array(sg1 * 71, dtype=dt1)[()] + b = np.array(sg2 * 19, dtype=dt2)[()] + div, rem = op(a, b) + assert_equal(div * b + rem, a, err_msg=msg) + if sg2 == -1: + assert_(b < rem <= 0, msg) + else: + assert_(b > rem >= 0, msg) + + def test_float_modulus_exact(self): + # test that float results are exact for small integers. This also + # holds for the same integers scaled by powers of two. + nlst = list(range(-127, 0)) + plst = list(range(1, 128)) + dividend = nlst + [0] + plst + divisor = nlst + plst + arg = list(itertools.product(dividend, divisor)) + tgt = [divmod(*t) for t in arg] + + a, b = np.array(arg, dtype=int).T + # convert exact integer results from Python to float so that + # signed zero can be used, it is checked. + tgtdiv, tgtrem = np.array(tgt, dtype=float).T + tgtdiv = np.where((tgtdiv == 0.0) & ((b < 0) ^ (a < 0)), -0.0, tgtdiv) + tgtrem = np.where((tgtrem == 0.0) & (b < 0), -0.0, tgtrem) + + for op in [floordiv_and_mod, divmod]: + for dt in np.typecodes['Float']: + msg = f'op: {op.__name__}, dtype: {dt}' + fa = a.astype(dt) + fb = b.astype(dt) + # use list comprehension so a_ and b_ are scalars + div, rem = zip(*[op(a_, b_) for a_, b_ in zip(fa, fb)]) + assert_equal(div, tgtdiv, err_msg=msg) + assert_equal(rem, tgtrem, err_msg=msg) + + def test_float_modulus_roundoff(self): + # gh-6127 + dt = np.typecodes['Float'] + for op in [floordiv_and_mod, divmod]: + for dt1, dt2 in itertools.product(dt, dt): + for sg1, sg2 in itertools.product((+1, -1), (+1, -1)): + fmt = 'op: %s, dt1: %s, dt2: %s, sg1: %s, sg2: %s' + msg = fmt % (op.__name__, dt1, dt2, sg1, sg2) + a = np.array(sg1 * 78 * 6e-8, dtype=dt1)[()] + b = np.array(sg2 * 6e-8, dtype=dt2)[()] + div, rem = op(a, b) + # Equal assertion should hold when fmod is used + assert_equal(div * b + rem, a, err_msg=msg) + if sg2 == -1: + assert_(b < rem <= 0, msg) + else: + assert_(b > rem >= 0, msg) + + def test_float_modulus_corner_cases(self): + # Check remainder magnitude. + for dt in np.typecodes['Float']: + b = np.array(1.0, dtype=dt) + a = np.nextafter(np.array(0.0, dtype=dt), -b) + rem = operator.mod(a, b) + assert_(rem <= b, f'dt: {dt}') + rem = operator.mod(-a, -b) + assert_(rem >= -b, f'dt: {dt}') + + # Check nans, inf + with warnings.catch_warnings(), np.errstate(all='ignore'): + for dt in np.typecodes['Float']: + fone = np.array(1.0, dtype=dt) + fzer = np.array(0.0, dtype=dt) + finf = np.array(np.inf, dtype=dt) + fnan = np.array(np.nan, dtype=dt) + rem = operator.mod(fone, fzer) + assert_(np.isnan(rem), f'dt: {dt}') + # MSVC 2008 returns NaN here, so disable the check. + #rem = operator.mod(fone, finf) + #assert_(rem == fone, 'dt: %s' % dt) + rem = operator.mod(fone, fnan) + assert_(np.isnan(rem), f'dt: {dt}') + rem = operator.mod(finf, fone) + assert_(np.isnan(rem), f'dt: {dt}') + for op in [floordiv_and_mod, divmod]: + div, mod = op(fone, fzer) + assert_(np.isinf(div)) and assert_(np.isnan(mod)) + + def test_inplace_floordiv_handling(self): + # issue gh-12927 + # this only applies to in-place floordiv //=, because the output type + # promotes to float which does not fit + a = np.array([1, 2], np.int64) + b = np.array([1, 2], np.uint64) + with pytest.raises(TypeError, + match=r"Cannot cast ufunc 'floor_divide' output from"): + a //= b + +class TestComparison: + def test_comparision_different_types(self): + x = np.array(1) + y = np.array('s') + eq = x == y + neq = x != y + assert eq is np.bool_(False) + assert neq is np.bool_(True) + + +class TestComplexDivision: + def test_zero_division(self): + with np.errstate(all="ignore"): + for t in [np.complex64, np.complex128]: + a = t(0.0) + b = t(1.0) + assert_(np.isinf(b / a)) + b = t(complex(np.inf, np.inf)) + assert_(np.isinf(b / a)) + b = t(complex(np.inf, np.nan)) + assert_(np.isinf(b / a)) + b = t(complex(np.nan, np.inf)) + assert_(np.isinf(b / a)) + b = t(complex(np.nan, np.nan)) + assert_(np.isnan(b / a)) + b = t(0.) + assert_(np.isnan(b / a)) + + def test_signed_zeros(self): + with np.errstate(all="ignore"): + for t in [np.complex64, np.complex128]: + # tupled (numerator, denominator, expected) + # for testing as expected == numerator/denominator + data = ( + (( 0.0, -1.0), ( 0.0, 1.0), (-1.0, -0.0)), + (( 0.0, -1.0), ( 0.0, -1.0), ( 1.0, -0.0)), + (( 0.0, -1.0), (-0.0, -1.0), ( 1.0, 0.0)), + (( 0.0, -1.0), (-0.0, 1.0), (-1.0, 0.0)), + (( 0.0, 1.0), ( 0.0, -1.0), (-1.0, 0.0)), + (( 0.0, -1.0), ( 0.0, -1.0), ( 1.0, -0.0)), + ((-0.0, -1.0), ( 0.0, -1.0), ( 1.0, -0.0)), + ((-0.0, 1.0), ( 0.0, -1.0), (-1.0, -0.0)) + ) + for cases in data: + n = cases[0] + d = cases[1] + ex = cases[2] + result = t(complex(n[0], n[1])) / t(complex(d[0], d[1])) + # check real and imag parts separately to avoid comparison + # in array context, which does not account for signed zeros + assert_equal(result.real, ex[0]) + assert_equal(result.imag, ex[1]) + + def test_branches(self): + with np.errstate(all="ignore"): + for t in [np.complex64, np.complex128]: + # tupled (numerator, denominator, expected) + # for testing as expected == numerator/denominator + data = [] + + # trigger branch: real(fabs(denom)) > imag(fabs(denom)) + # followed by else condition as neither are == 0 + data.append((( 2.0, 1.0), ( 2.0, 1.0), (1.0, 0.0))) + + # trigger branch: real(fabs(denom)) > imag(fabs(denom)) + # followed by if condition as both are == 0 + # is performed in test_zero_division(), so this is skipped + + # trigger else if branch: real(fabs(denom)) < imag(fabs(denom)) + data.append(((1.0, 2.0), (1.0, 2.0), (1.0, 0.0))) + + for cases in data: + n = cases[0] + d = cases[1] + ex = cases[2] + result = t(complex(n[0], n[1])) / t(complex(d[0], d[1])) + # check real and imag parts separately to avoid comparison + # in array context, which does not account for signed zeros + assert_equal(result.real, ex[0]) + assert_equal(result.imag, ex[1]) + + +class TestConversion: + def test_int_from_long(self): + l = [1e6, 1e12, 1e18, -1e6, -1e12, -1e18] + li = [10**6, 10**12, 10**18, -10**6, -10**12, -10**18] + for T in [None, np.float64, np.int64]: + a = np.array(l, dtype=T) + assert_equal([int(_m) for _m in a], li) + + a = np.array(l[:3], dtype=np.uint64) + assert_equal([int(_m) for _m in a], li[:3]) + + def test_iinfo_long_values(self): + for code in 'bBhH': + with pytest.raises(OverflowError): + np.array(np.iinfo(code).max + 1, dtype=code) + + for code in np.typecodes['AllInteger']: + res = np.array(np.iinfo(code).max, dtype=code) + tgt = np.iinfo(code).max + assert_(res == tgt) + + for code in np.typecodes['AllInteger']: + res = np.dtype(code).type(np.iinfo(code).max) + tgt = np.iinfo(code).max + assert_(res == tgt) + + def test_int_raise_behaviour(self): + def overflow_error_func(dtype): + dtype(np.iinfo(dtype).max + 1) + + for code in [np.int_, np.uint, np.longlong, np.ulonglong]: + assert_raises(OverflowError, overflow_error_func, code) + + def test_int_from_infinite_longdouble(self): + # gh-627 + x = np.longdouble(np.inf) + assert_raises(OverflowError, int, x) + with pytest.warns(ComplexWarning): + x = np.clongdouble(np.inf) + assert_raises(OverflowError, int, x) + + @pytest.mark.skipif(not IS_PYPY, reason="Test is PyPy only (gh-9972)") + def test_int_from_infinite_longdouble___int__(self): + x = np.longdouble(np.inf) + assert_raises(OverflowError, x.__int__) + with pytest.warns(ComplexWarning): + x = np.clongdouble(np.inf) + assert_raises(OverflowError, x.__int__) + + @pytest.mark.skipif(np.finfo(np.double) == np.finfo(np.longdouble), + reason="long double is same as double") + @pytest.mark.skipif(platform.machine().startswith("ppc"), + reason="IBM double double") + def test_int_from_huge_longdouble(self): + # Produce a longdouble that would overflow a double, + # use exponent that avoids bug in Darwin pow function. + exp = np.finfo(np.double).maxexp - 1 + huge_ld = 2 * 1234 * np.longdouble(2) ** exp + huge_i = 2 * 1234 * 2 ** exp + assert_(huge_ld != np.inf) + assert_equal(int(huge_ld), huge_i) + + def test_int_from_longdouble(self): + x = np.longdouble(1.5) + assert_equal(int(x), 1) + x = np.longdouble(-10.5) + assert_equal(int(x), -10) + + def test_numpy_scalar_relational_operators(self): + # All integer + for dt1 in np.typecodes['AllInteger']: + assert_(1 > np.array(0, dtype=dt1)[()], f"type {dt1} failed") + assert_(not 1 < np.array(0, dtype=dt1)[()], f"type {dt1} failed") + + for dt2 in np.typecodes['AllInteger']: + assert_(np.array(1, dtype=dt1)[()] > np.array(0, dtype=dt2)[()], + f"type {dt1} and {dt2} failed") + assert_(not np.array(1, dtype=dt1)[()] < np.array(0, dtype=dt2)[()], + f"type {dt1} and {dt2} failed") + + # Unsigned integers + for dt1 in 'BHILQP': + assert_(-1 < np.array(1, dtype=dt1)[()], f"type {dt1} failed") + assert_(not -1 > np.array(1, dtype=dt1)[()], f"type {dt1} failed") + assert_(-1 != np.array(1, dtype=dt1)[()], f"type {dt1} failed") + + # unsigned vs signed + for dt2 in 'bhilqp': + assert_(np.array(1, dtype=dt1)[()] > np.array(-1, dtype=dt2)[()], + f"type {dt1} and {dt2} failed") + assert_(not np.array(1, dtype=dt1)[()] < np.array(-1, dtype=dt2)[()], + f"type {dt1} and {dt2} failed") + assert_(np.array(1, dtype=dt1)[()] != np.array(-1, dtype=dt2)[()], + f"type {dt1} and {dt2} failed") + + # Signed integers and floats + for dt1 in 'bhlqp' + np.typecodes['Float']: + assert_(1 > np.array(-1, dtype=dt1)[()], f"type {dt1} failed") + assert_(not 1 < np.array(-1, dtype=dt1)[()], f"type {dt1} failed") + assert_(-1 == np.array(-1, dtype=dt1)[()], f"type {dt1} failed") + + for dt2 in 'bhlqp' + np.typecodes['Float']: + assert_(np.array(1, dtype=dt1)[()] > np.array(-1, dtype=dt2)[()], + f"type {dt1} and {dt2} failed") + assert_(not np.array(1, dtype=dt1)[()] < np.array(-1, dtype=dt2)[()], + f"type {dt1} and {dt2} failed") + assert_(np.array(-1, dtype=dt1)[()] == np.array(-1, dtype=dt2)[()], + f"type {dt1} and {dt2} failed") + + def test_scalar_comparison_to_none(self): + # Scalars should just return False and not give a warnings. + # The comparisons are flagged by pep8, ignore that. + with warnings.catch_warnings(record=True) as w: + warnings.filterwarnings('always', '', FutureWarning) + assert_(not np.float32(1) == None) # noqa: E711 + assert_(not np.str_('test') == None) # noqa: E711 + # This is dubious (see below): + assert_(not np.datetime64('NaT') == None) # noqa: E711 + + assert_(np.float32(1) != None) # noqa: E711 + assert_(np.str_('test') != None) # noqa: E711 + # This is dubious (see below): + assert_(np.datetime64('NaT') != None) # noqa: E711 + assert_(len(w) == 0) + + # For documentation purposes, this is why the datetime is dubious. + # At the time of deprecation this was no behaviour change, but + # it has to be considered when the deprecations are done. + assert_(np.equal(np.datetime64('NaT'), None)) + + +#class TestRepr: +# def test_repr(self): +# for t in types: +# val = t(1197346475.0137341) +# val_repr = repr(val) +# val2 = eval(val_repr) +# assert_equal( val, val2 ) + + +class TestRepr: + def _test_type_repr(self, t): + finfo = np.finfo(t) + last_fraction_bit_idx = finfo.nexp + finfo.nmant + last_exponent_bit_idx = finfo.nexp + storage_bytes = np.dtype(t).itemsize * 8 + # could add some more types to the list below + for which in ['small denorm', 'small norm']: + # Values from https://en.wikipedia.org/wiki/IEEE_754 + constr = np.array([0x00] * storage_bytes, dtype=np.uint8) + if which == 'small denorm': + byte = last_fraction_bit_idx // 8 + bytebit = 7 - (last_fraction_bit_idx % 8) + constr[byte] = 1 << bytebit + elif which == 'small norm': + byte = last_exponent_bit_idx // 8 + bytebit = 7 - (last_exponent_bit_idx % 8) + constr[byte] = 1 << bytebit + else: + raise ValueError('hmm') + val = constr.view(t)[0] + val_repr = repr(val) + val2 = t(eval(val_repr)) + if not (val2 == 0 and val < 1e-100): + assert_equal(val, val2) + + def test_float_repr(self): + # long double test cannot work, because eval goes through a python + # float + for t in [np.float32, np.float64]: + self._test_type_repr(t) + + +if not IS_PYPY: + # sys.getsizeof() is not valid on PyPy + class TestSizeOf: + + def test_equal_nbytes(self): + for type in types: + x = type(0) + assert_(sys.getsizeof(x) > x.nbytes) + + def test_error(self): + d = np.float32() + assert_raises(TypeError, d.__sizeof__, "a") + + +class TestMultiply: + def test_seq_repeat(self): + # Test that basic sequences get repeated when multiplied with + # numpy integers. And errors are raised when multiplied with others. + # Some of this behaviour may be controversial and could be open for + # change. + accepted_types = set(np.typecodes["AllInteger"]) + deprecated_types = {'?'} + forbidden_types = ( + set(np.typecodes["All"]) - accepted_types - deprecated_types) + forbidden_types -= {'V'} # can't default-construct void scalars + + for seq_type in (list, tuple): + seq = seq_type([1, 2, 3]) + for numpy_type in accepted_types: + i = np.dtype(numpy_type).type(2) + assert_equal(seq * i, seq * int(i)) + assert_equal(i * seq, int(i) * seq) + + for numpy_type in deprecated_types: + i = np.dtype(numpy_type).type() + with assert_raises(TypeError): + operator.mul(seq, i) + + for numpy_type in forbidden_types: + i = np.dtype(numpy_type).type() + assert_raises(TypeError, operator.mul, seq, i) + assert_raises(TypeError, operator.mul, i, seq) + + def test_no_seq_repeat_basic_array_like(self): + # Test that an array-like which does not know how to be multiplied + # does not attempt sequence repeat (raise TypeError). + # See also gh-7428. + class ArrayLike: + def __init__(self, arr): + self.arr = arr + + def __array__(self, dtype=None, copy=None): + return self.arr + + # Test for simple ArrayLike above and memoryviews (original report) + for arr_like in (ArrayLike(np.ones(3)), memoryview(np.ones(3))): + assert_array_equal(arr_like * np.float32(3.), np.full(3, 3.)) + assert_array_equal(np.float32(3.) * arr_like, np.full(3, 3.)) + assert_array_equal(arr_like * np.int_(3), np.full(3, 3)) + assert_array_equal(np.int_(3) * arr_like, np.full(3, 3)) + + +class TestNegative: + def test_exceptions(self): + a = np.ones((), dtype=np.bool)[()] + assert_raises(TypeError, operator.neg, a) + + def test_result(self): + types = np.typecodes['AllInteger'] + np.typecodes['AllFloat'] + with warnings.catch_warnings(): + warnings.simplefilter('ignore', RuntimeWarning) + for dt in types: + a = np.ones((), dtype=dt)[()] + if dt in np.typecodes['UnsignedInteger']: + st = np.dtype(dt).type + max = st(np.iinfo(dt).max) + assert_equal(operator.neg(a), max) + else: + assert_equal(operator.neg(a) + a, 0) + +class TestSubtract: + def test_exceptions(self): + a = np.ones((), dtype=np.bool)[()] + assert_raises(TypeError, operator.sub, a, a) + + def test_result(self): + types = np.typecodes['AllInteger'] + np.typecodes['AllFloat'] + with warnings.catch_warnings(): + warnings.simplefilter('ignore', RuntimeWarning) + for dt in types: + a = np.ones((), dtype=dt)[()] + assert_equal(operator.sub(a, a), 0) + + +class TestAbs: + def _test_abs_func(self, absfunc, test_dtype): + x = test_dtype(-1.5) + assert_equal(absfunc(x), 1.5) + x = test_dtype(0.0) + res = absfunc(x) + # assert_equal() checks zero signedness + assert_equal(res, 0.0) + x = test_dtype(-0.0) + res = absfunc(x) + assert_equal(res, 0.0) + + x = test_dtype(np.finfo(test_dtype).max) + assert_equal(absfunc(x), x.real) + + with warnings.catch_warnings(): + warnings.simplefilter('ignore', UserWarning) + x = test_dtype(np.finfo(test_dtype).tiny) + assert_equal(absfunc(x), x.real) + + x = test_dtype(np.finfo(test_dtype).min) + assert_equal(absfunc(x), -x.real) + + @pytest.mark.parametrize("dtype", floating_types + complex_floating_types) + def test_builtin_abs(self, dtype): + if ( + sys.platform == "cygwin" and dtype == np.clongdouble and + ( + _pep440.parse(platform.release().split("-")[0]) + < _pep440.Version("3.3.0") + ) + ): + pytest.xfail( + reason="absl is computed in double precision on cygwin < 3.3" + ) + self._test_abs_func(abs, dtype) + + @pytest.mark.parametrize("dtype", floating_types + complex_floating_types) + def test_numpy_abs(self, dtype): + if ( + sys.platform == "cygwin" and dtype == np.clongdouble and + ( + _pep440.parse(platform.release().split("-")[0]) + < _pep440.Version("3.3.0") + ) + ): + pytest.xfail( + reason="absl is computed in double precision on cygwin < 3.3" + ) + self._test_abs_func(np.abs, dtype) + +class TestBitShifts: + + @pytest.mark.parametrize('type_code', np.typecodes['AllInteger']) + @pytest.mark.parametrize('op', + [operator.rshift, operator.lshift], ids=['>>', '<<']) + def test_shift_all_bits(self, type_code, op): + """Shifts where the shift amount is the width of the type or wider """ + # gh-2449 + dt = np.dtype(type_code) + nbits = dt.itemsize * 8 + for val in [5, -5]: + for shift in [nbits, nbits + 4]: + val_scl = np.array(val).astype(dt)[()] + shift_scl = dt.type(shift) + res_scl = op(val_scl, shift_scl) + if val_scl < 0 and op is operator.rshift: + # sign bit is preserved + assert_equal(res_scl, -1) + else: + assert_equal(res_scl, 0) + + # Result on scalars should be the same as on arrays + val_arr = np.array([val_scl] * 32, dtype=dt) + shift_arr = np.array([shift] * 32, dtype=dt) + res_arr = op(val_arr, shift_arr) + assert_equal(res_arr, res_scl) + + +class TestHash: + @pytest.mark.parametrize("type_code", np.typecodes['AllInteger']) + def test_integer_hashes(self, type_code): + scalar = np.dtype(type_code).type + for i in range(128): + assert hash(i) == hash(scalar(i)) + + @pytest.mark.parametrize("type_code", np.typecodes['AllFloat']) + def test_float_and_complex_hashes(self, type_code): + scalar = np.dtype(type_code).type + for val in [np.pi, np.inf, 3, 6.]: + numpy_val = scalar(val) + # Cast back to Python, in case the NumPy scalar has less precision + if numpy_val.dtype.kind == 'c': + val = complex(numpy_val) + else: + val = float(numpy_val) + assert val == numpy_val + assert hash(val) == hash(numpy_val) + + if hash(float(np.nan)) != hash(float(np.nan)): + # If Python distinguishes different NaNs we do so too (gh-18833) + assert hash(scalar(np.nan)) != hash(scalar(np.nan)) + + @pytest.mark.parametrize("type_code", np.typecodes['Complex']) + def test_complex_hashes(self, type_code): + # Test some complex valued hashes specifically: + scalar = np.dtype(type_code).type + for val in [np.pi + 1j, np.inf - 3j, 3j, 6. + 1j]: + numpy_val = scalar(val) + assert hash(complex(numpy_val)) == hash(numpy_val) + + +@contextlib.contextmanager +def recursionlimit(n): + o = sys.getrecursionlimit() + try: + sys.setrecursionlimit(n) + yield + finally: + sys.setrecursionlimit(o) + + +@given(sampled_from(objecty_things), + sampled_from(binary_operators_for_scalar_ints), + sampled_from(types + [rational])) +@pytest.mark.thread_unsafe(reason="sets recursion limit globally") +def test_operator_object_left(o, op, type_): + try: + with recursionlimit(200): + op(o, type_(1)) + except TypeError: + pass + + +@given(sampled_from(objecty_things), + sampled_from(binary_operators_for_scalar_ints), + sampled_from(types + [rational])) +@pytest.mark.thread_unsafe(reason="sets recursion limit globally") +def test_operator_object_right(o, op, type_): + try: + with recursionlimit(200): + op(type_(1), o) + except TypeError: + pass + + +@given(sampled_from(binary_operators_for_scalars), + sampled_from(types), + sampled_from(types)) +def test_operator_scalars(op, type1, type2): + try: + op(type1(1), type2(1)) + except TypeError: + pass + + +@pytest.mark.parametrize("op", binary_operators_for_scalars) +@pytest.mark.parametrize("sctype", [np.longdouble, np.clongdouble]) +def test_longdouble_operators_with_obj(sctype, op): + # This is/used to be tricky, because NumPy generally falls back to + # using the ufunc via `np.asarray()`, this effectively might do: + # longdouble + None + # -> asarray(longdouble) + np.array(None, dtype=object) + # -> asarray(longdouble).astype(object) + np.array(None, dtype=object) + # And after getting the scalars in the inner loop: + # -> longdouble + None + # + # That would recurse infinitely. Other scalars return the python object + # on cast, so this type of things works OK. + # + # As of NumPy 2.1, this has been consolidated into the np.generic binops + # and now checks `.item()`. That also allows the below path to work now. + try: + op(sctype(3), None) + except TypeError: + pass + try: + op(None, sctype(3)) + except TypeError: + pass + + +@pytest.mark.parametrize("op", [operator.add, operator.pow, operator.sub]) +@pytest.mark.parametrize("sctype", [np.longdouble, np.clongdouble]) +def test_longdouble_with_arrlike(sctype, op): + # As of NumPy 2.1, longdouble behaves like other types and can coerce + # e.g. lists. (Not necessarily better, but consistent.) + assert_array_equal(op(sctype(3), [1, 2]), op(3, np.array([1, 2]))) + assert_array_equal(op([1, 2], sctype(3)), op(np.array([1, 2]), 3)) + + +@pytest.mark.parametrize("op", binary_operators_for_scalars) +@pytest.mark.parametrize("sctype", [np.longdouble, np.clongdouble]) +@np.errstate(all="ignore") +def test_longdouble_operators_with_large_int(sctype, op): + # (See `test_longdouble_operators_with_obj` for why longdouble is special) + # NEP 50 means that the result is clearly a (c)longdouble here: + if sctype == np.clongdouble and op in [operator.mod, operator.floordiv]: + # The above operators are not support for complex though... + with pytest.raises(TypeError): + op(sctype(3), 2**64) + with pytest.raises(TypeError): + op(sctype(3), 2**64) + else: + assert op(sctype(3), -2**64) == op(sctype(3), sctype(-2**64)) + assert op(2**64, sctype(3)) == op(sctype(2**64), sctype(3)) + + +@pytest.mark.parametrize("dtype", np.typecodes["AllInteger"]) +@pytest.mark.parametrize("operation", [ + lambda min, max: max + max, + lambda min, max: min - max, + lambda min, max: max * max], ids=["+", "-", "*"]) +def test_scalar_integer_operation_overflow(dtype, operation): + st = np.dtype(dtype).type + min = st(np.iinfo(dtype).min) + max = st(np.iinfo(dtype).max) + + with pytest.warns(RuntimeWarning, match="overflow encountered"): + operation(min, max) + + +@pytest.mark.parametrize("dtype", np.typecodes["Integer"]) +@pytest.mark.parametrize("operation", [ + lambda min, neg_1: -min, + lambda min, neg_1: abs(min), + lambda min, neg_1: min * neg_1, + pytest.param(lambda min, neg_1: min // neg_1, + marks=pytest.mark.skip(reason="broken on some platforms"))], + ids=["neg", "abs", "*", "//"]) +def test_scalar_signed_integer_overflow(dtype, operation): + # The minimum signed integer can "overflow" for some additional operations + st = np.dtype(dtype).type + min = st(np.iinfo(dtype).min) + neg_1 = st(-1) + + with pytest.warns(RuntimeWarning, match="overflow encountered"): + operation(min, neg_1) + + +@pytest.mark.parametrize("dtype", np.typecodes["UnsignedInteger"]) +def test_scalar_unsigned_integer_overflow(dtype): + val = np.dtype(dtype).type(8) + with pytest.warns(RuntimeWarning, match="overflow encountered"): + -val + + zero = np.dtype(dtype).type(0) + -zero # does not warn + +@pytest.mark.parametrize("dtype", np.typecodes["AllInteger"]) +@pytest.mark.parametrize("operation", [ + lambda val, zero: val // zero, + lambda val, zero: val % zero, ], ids=["//", "%"]) +def test_scalar_integer_operation_divbyzero(dtype, operation): + st = np.dtype(dtype).type + val = st(100) + zero = st(0) + + with pytest.warns(RuntimeWarning, match="divide by zero"): + operation(val, zero) + + +ops_with_names = [ + ("__lt__", "__gt__", operator.lt, True), + ("__le__", "__ge__", operator.le, True), + ("__eq__", "__eq__", operator.eq, True), + # Note __op__ and __rop__ may be identical here: + ("__ne__", "__ne__", operator.ne, True), + ("__gt__", "__lt__", operator.gt, True), + ("__ge__", "__le__", operator.ge, True), + ("__floordiv__", "__rfloordiv__", operator.floordiv, False), + ("__truediv__", "__rtruediv__", operator.truediv, False), + ("__add__", "__radd__", operator.add, False), + ("__mod__", "__rmod__", operator.mod, False), + ("__mul__", "__rmul__", operator.mul, False), + ("__pow__", "__rpow__", operator.pow, False), + ("__sub__", "__rsub__", operator.sub, False), +] + + +@pytest.mark.parametrize(["__op__", "__rop__", "op", "cmp"], ops_with_names) +@pytest.mark.parametrize("sctype", [np.float32, np.float64, np.longdouble]) +def test_subclass_deferral(sctype, __op__, __rop__, op, cmp): + """ + This test covers scalar subclass deferral. Note that this is exceedingly + complicated, especially since it tends to fall back to the array paths and + these additionally add the "array priority" mechanism. + + The behaviour was modified subtly in 1.22 (to make it closer to how Python + scalars work). Due to its complexity and the fact that subclassing NumPy + scalars is probably a bad idea to begin with. There is probably room + for adjustments here. + """ + class myf_simple1(sctype): + pass + + class myf_simple2(sctype): + pass + + def op_func(self, other): + return __op__ + + def rop_func(self, other): + return __rop__ + + myf_op = type("myf_op", (sctype,), {__op__: op_func, __rop__: rop_func}) + + # inheritance has to override, or this is correctly lost: + res = op(myf_simple1(1), myf_simple2(2)) + assert type(res) == sctype or type(res) == np.bool + assert op(myf_simple1(1), myf_simple2(2)) == op(1, 2) # inherited + + # Two independent subclasses do not really define an order. This could + # be attempted, but we do not since Python's `int` does neither: + assert op(myf_op(1), myf_simple1(2)) == __op__ + assert op(myf_simple1(1), myf_op(2)) == op(1, 2) # inherited + + +def test_longdouble_complex(): + # Simple test to check longdouble and complex combinations, since these + # need to go through promotion, which longdouble needs to be careful about. + x = np.longdouble(1) + assert x + 1j == 1 + 1j + assert 1j + x == 1 + 1j + + +@pytest.mark.parametrize(["__op__", "__rop__", "op", "cmp"], ops_with_names) +@pytest.mark.parametrize("subtype", [float, int, complex, np.float16]) +def test_pyscalar_subclasses(subtype, __op__, __rop__, op, cmp): + # This tests that python scalar subclasses behave like a float64 (if they + # don't override it). + # In an earlier version of NEP 50, they behaved like the Python buildins. + def op_func(self, other): + return __op__ + + def rop_func(self, other): + return __rop__ + + # Check that deferring is indicated using `__array_ufunc__`: + myt = type("myt", (subtype,), + {__op__: op_func, __rop__: rop_func, "__array_ufunc__": None}) + + # Just like normally, we should never presume we can modify the float. + assert op(myt(1), np.float64(2)) == __op__ + assert op(np.float64(1), myt(2)) == __rop__ + + if op in {operator.mod, operator.floordiv} and subtype == complex: + return # module is not support for complex. Do not test. + + if __rop__ == __op__: + return + + # When no deferring is indicated, subclasses are handled normally. + myt = type("myt", (subtype,), {__rop__: rop_func}) + behaves_like = lambda x: np.array(subtype(x))[()] + + # Check for float32, as a float subclass float64 may behave differently + res = op(myt(1), np.float16(2)) + expected = op(behaves_like(1), np.float16(2)) + assert res == expected + assert type(res) == type(expected) + res = op(np.float32(2), myt(1)) + expected = op(np.float32(2), behaves_like(1)) + assert res == expected + assert type(res) == type(expected) + + # Same check for longdouble (compare via dtype to accept float64 when + # longdouble has the identical size), which is currently not perfectly + # consistent. + res = op(myt(1), np.longdouble(2)) + expected = op(behaves_like(1), np.longdouble(2)) + assert res == expected + assert np.dtype(type(res)) == np.dtype(type(expected)) + res = op(np.float32(2), myt(1)) + expected = op(np.float32(2), behaves_like(1)) + assert res == expected + assert np.dtype(type(res)) == np.dtype(type(expected)) + + +def test_truediv_int(): + # This should work, as the result is float: + assert np.uint8(3) / 123454 == np.float64(3) / 123454 + + +@pytest.mark.slow +@pytest.mark.parametrize("op", + # TODO: Power is a bit special, but here mostly bools seem to behave oddly + [op for op in binary_operators_for_scalars if op is not operator.pow]) +@pytest.mark.parametrize("sctype", types) +@pytest.mark.parametrize("other_type", [float, int, complex]) +@pytest.mark.parametrize("rop", [True, False]) +def test_scalar_matches_array_op_with_pyscalar(op, sctype, other_type, rop): + # Check that the ufunc path matches by coercing to an array explicitly + val1 = sctype(2) + val2 = other_type(2) + + if rop: + _op = op + op = lambda x, y: _op(y, x) + + try: + res = op(val1, val2) + except TypeError: + try: + expected = op(np.asarray(val1), val2) + raise AssertionError("ufunc didn't raise.") + except TypeError: + return + else: + expected = op(np.asarray(val1), val2) + + # Note that we only check dtype equivalency, as ufuncs may pick the lower + # dtype if they are equivalent. + assert res == expected + if isinstance(val1, float) and other_type is complex and rop: + # Python complex accepts float subclasses, so we don't get a chance + # and the result may be a Python complex (thus, the `np.array()``) + assert np.array(res).dtype == expected.dtype + else: + assert res.dtype == expected.dtype diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_scalarprint.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_scalarprint.py new file mode 100644 index 0000000000000000000000000000000000000000..38ed7780f2e65183dcc856f8b6e3dad466271bc2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_scalarprint.py @@ -0,0 +1,403 @@ +""" Test printing of scalar types. + +""" +import platform + +import pytest + +import numpy as np +from numpy.testing import IS_MUSL, assert_, assert_equal, assert_raises + + +class TestRealScalars: + def test_str(self): + svals = [0.0, -0.0, 1, -1, np.inf, -np.inf, np.nan] + styps = [np.float16, np.float32, np.float64, np.longdouble] + wanted = [ + ['0.0', '0.0', '0.0', '0.0' ], # noqa: E202 + ['-0.0', '-0.0', '-0.0', '-0.0'], + ['1.0', '1.0', '1.0', '1.0' ], # noqa: E202 + ['-1.0', '-1.0', '-1.0', '-1.0'], + ['inf', 'inf', 'inf', 'inf' ], # noqa: E202 + ['-inf', '-inf', '-inf', '-inf'], + ['nan', 'nan', 'nan', 'nan' ]] # noqa: E202 + + for wants, val in zip(wanted, svals): + for want, styp in zip(wants, styps): + msg = f'for str({np.dtype(styp).name}({val!r}))' + assert_equal(str(styp(val)), want, err_msg=msg) + + def test_scalar_cutoffs(self): + # test that both the str and repr of np.float64 behaves + # like python floats in python3. + def check(v): + assert_equal(str(np.float64(v)), str(v)) + assert_equal(str(np.float64(v)), repr(v)) + assert_equal(repr(np.float64(v)), f"np.float64({v!r})") + assert_equal(repr(np.float64(v)), f"np.float64({v})") + + # check we use the same number of significant digits + check(1.12345678901234567890) + check(0.0112345678901234567890) + + # check switch from scientific output to positional and back + check(1e-5) + check(1e-4) + check(1e15) + check(1e16) + + test_cases_gh_28679 = [ + (np.half, -0.000099, "-9.9e-05"), + (np.half, 0.0001, "0.0001"), + (np.half, 999, "999.0"), + (np.half, -1000, "-1e+03"), + (np.single, 0.000099, "9.9e-05"), + (np.single, -0.000100001, "-0.000100001"), + (np.single, 999999, "999999.0"), + (np.single, -1000000, "-1e+06") + ] + + @pytest.mark.parametrize("dtype, input_val, expected_str", test_cases_gh_28679) + def test_gh_28679(self, dtype, input_val, expected_str): + # test cutoff to exponent notation for half and single + assert_equal(str(dtype(input_val)), expected_str) + + test_cases_legacy_2_2 = [ + (np.half(65504), "65500.0"), + (np.single(1.e15), "1000000000000000.0"), + (np.single(1.e16), "1e+16"), + ] + + @pytest.mark.parametrize("input_val, expected_str", test_cases_legacy_2_2) + def test_legacy_2_2_mode(self, input_val, expected_str): + # test legacy cutoff to exponent notation for half and single + with np.printoptions(legacy='2.2'): + assert_equal(str(input_val), expected_str) + + def test_dragon4(self): + # these tests are adapted from Ryan Juckett's dragon4 implementation, + # see dragon4.c for details. + + fpos32 = lambda x, **k: np.format_float_positional(np.float32(x), **k) + fsci32 = lambda x, **k: np.format_float_scientific(np.float32(x), **k) + fpos64 = lambda x, **k: np.format_float_positional(np.float64(x), **k) + fsci64 = lambda x, **k: np.format_float_scientific(np.float64(x), **k) + + preckwd = lambda prec: {'unique': False, 'precision': prec} + + assert_equal(fpos32('1.0'), "1.") + assert_equal(fsci32('1.0'), "1.e+00") + assert_equal(fpos32('10.234'), "10.234") + assert_equal(fpos32('-10.234'), "-10.234") + assert_equal(fsci32('10.234'), "1.0234e+01") + assert_equal(fsci32('-10.234'), "-1.0234e+01") + assert_equal(fpos32('1000.0'), "1000.") + assert_equal(fpos32('1.0', precision=0), "1.") + assert_equal(fsci32('1.0', precision=0), "1.e+00") + assert_equal(fpos32('10.234', precision=0), "10.") + assert_equal(fpos32('-10.234', precision=0), "-10.") + assert_equal(fsci32('10.234', precision=0), "1.e+01") + assert_equal(fsci32('-10.234', precision=0), "-1.e+01") + assert_equal(fpos32('10.234', precision=2), "10.23") + assert_equal(fsci32('-10.234', precision=2), "-1.02e+01") + assert_equal(fsci64('9.9999999999999995e-08', **preckwd(16)), + '9.9999999999999995e-08') + assert_equal(fsci64('9.8813129168249309e-324', **preckwd(16)), + '9.8813129168249309e-324') + assert_equal(fsci64('9.9999999999999694e-311', **preckwd(16)), + '9.9999999999999694e-311') + + # test rounding + # 3.1415927410 is closest float32 to np.pi + assert_equal(fpos32('3.14159265358979323846', **preckwd(10)), + "3.1415927410") + assert_equal(fsci32('3.14159265358979323846', **preckwd(10)), + "3.1415927410e+00") + assert_equal(fpos64('3.14159265358979323846', **preckwd(10)), + "3.1415926536") + assert_equal(fsci64('3.14159265358979323846', **preckwd(10)), + "3.1415926536e+00") + # 299792448 is closest float32 to 299792458 + assert_equal(fpos32('299792458.0', **preckwd(5)), "299792448.00000") + assert_equal(fsci32('299792458.0', **preckwd(5)), "2.99792e+08") + assert_equal(fpos64('299792458.0', **preckwd(5)), "299792458.00000") + assert_equal(fsci64('299792458.0', **preckwd(5)), "2.99792e+08") + + assert_equal(fpos32('3.14159265358979323846', **preckwd(25)), + "3.1415927410125732421875000") + assert_equal(fpos64('3.14159265358979323846', **preckwd(50)), + "3.14159265358979311599796346854418516159057617187500") + assert_equal(fpos64('3.14159265358979323846'), "3.141592653589793") + + # smallest numbers + assert_equal(fpos32(0.5**(126 + 23), unique=False, precision=149), + "0.00000000000000000000000000000000000000000000140129846432" + "4817070923729583289916131280261941876515771757068283889791" + "08268586060148663818836212158203125") + + assert_equal(fpos64(5e-324, unique=False, precision=1074), + "0.00000000000000000000000000000000000000000000000000000000" + "0000000000000000000000000000000000000000000000000000000000" + "0000000000000000000000000000000000000000000000000000000000" + "0000000000000000000000000000000000000000000000000000000000" + "0000000000000000000000000000000000000000000000000000000000" + "0000000000000000000000000000000000049406564584124654417656" + "8792868221372365059802614324764425585682500675507270208751" + "8652998363616359923797965646954457177309266567103559397963" + "9877479601078187812630071319031140452784581716784898210368" + "8718636056998730723050006387409153564984387312473397273169" + "6151400317153853980741262385655911710266585566867681870395" + "6031062493194527159149245532930545654440112748012970999954" + "1931989409080416563324524757147869014726780159355238611550" + "1348035264934720193790268107107491703332226844753335720832" + "4319360923828934583680601060115061698097530783422773183292" + "4790498252473077637592724787465608477820373446969953364701" + "7972677717585125660551199131504891101451037862738167250955" + "8373897335989936648099411642057026370902792427675445652290" + "87538682506419718265533447265625") + + # largest numbers + f32x = np.finfo(np.float32).max + assert_equal(fpos32(f32x, **preckwd(0)), + "340282346638528859811704183484516925440.") + assert_equal(fpos64(np.finfo(np.float64).max, **preckwd(0)), + "1797693134862315708145274237317043567980705675258449965989" + "1747680315726078002853876058955863276687817154045895351438" + "2464234321326889464182768467546703537516986049910576551282" + "0762454900903893289440758685084551339423045832369032229481" + "6580855933212334827479782620414472316873817718091929988125" + "0404026184124858368.") + # Warning: In unique mode only the integer digits necessary for + # uniqueness are computed, the rest are 0. + assert_equal(fpos32(f32x), + "340282350000000000000000000000000000000.") + + # Further tests of zero-padding vs rounding in different combinations + # of unique, fractional, precision, min_digits + # precision can only reduce digits, not add them. + # min_digits can only extend digits, not reduce them. + assert_equal(fpos32(f32x, unique=True, fractional=True, precision=0), + "340282350000000000000000000000000000000.") + assert_equal(fpos32(f32x, unique=True, fractional=True, precision=4), + "340282350000000000000000000000000000000.") + assert_equal(fpos32(f32x, unique=True, fractional=True, min_digits=0), + "340282346638528859811704183484516925440.") + assert_equal(fpos32(f32x, unique=True, fractional=True, min_digits=4), + "340282346638528859811704183484516925440.0000") + assert_equal(fpos32(f32x, unique=True, fractional=True, + min_digits=4, precision=4), + "340282346638528859811704183484516925440.0000") + assert_raises(ValueError, fpos32, f32x, unique=True, fractional=False, + precision=0) + assert_equal(fpos32(f32x, unique=True, fractional=False, precision=4), + "340300000000000000000000000000000000000.") + assert_equal(fpos32(f32x, unique=True, fractional=False, precision=20), + "340282350000000000000000000000000000000.") + assert_equal(fpos32(f32x, unique=True, fractional=False, min_digits=4), + "340282350000000000000000000000000000000.") + assert_equal(fpos32(f32x, unique=True, fractional=False, + min_digits=20), + "340282346638528859810000000000000000000.") + assert_equal(fpos32(f32x, unique=True, fractional=False, + min_digits=15), + "340282346638529000000000000000000000000.") + assert_equal(fpos32(f32x, unique=False, fractional=False, precision=4), + "340300000000000000000000000000000000000.") + # test that unique rounding is preserved when precision is supplied + # but no extra digits need to be printed (gh-18609) + a = np.float64.fromhex('-1p-97') + assert_equal(fsci64(a, unique=True), '-6.310887241768095e-30') + assert_equal(fsci64(a, unique=False, precision=15), + '-6.310887241768094e-30') + assert_equal(fsci64(a, unique=True, precision=15), + '-6.310887241768095e-30') + assert_equal(fsci64(a, unique=True, min_digits=15), + '-6.310887241768095e-30') + assert_equal(fsci64(a, unique=True, precision=15, min_digits=15), + '-6.310887241768095e-30') + # adds/remove digits in unique mode with unbiased rnding + assert_equal(fsci64(a, unique=True, precision=14), + '-6.31088724176809e-30') + assert_equal(fsci64(a, unique=True, min_digits=16), + '-6.3108872417680944e-30') + assert_equal(fsci64(a, unique=True, precision=16), + '-6.310887241768095e-30') + assert_equal(fsci64(a, unique=True, min_digits=14), + '-6.310887241768095e-30') + # test min_digits in unique mode with different rounding cases + assert_equal(fsci64('1e120', min_digits=3), '1.000e+120') + assert_equal(fsci64('1e100', min_digits=3), '1.000e+100') + + # test trailing zeros + assert_equal(fpos32('1.0', unique=False, precision=3), "1.000") + assert_equal(fpos64('1.0', unique=False, precision=3), "1.000") + assert_equal(fsci32('1.0', unique=False, precision=3), "1.000e+00") + assert_equal(fsci64('1.0', unique=False, precision=3), "1.000e+00") + assert_equal(fpos32('1.5', unique=False, precision=3), "1.500") + assert_equal(fpos64('1.5', unique=False, precision=3), "1.500") + assert_equal(fsci32('1.5', unique=False, precision=3), "1.500e+00") + assert_equal(fsci64('1.5', unique=False, precision=3), "1.500e+00") + # gh-10713 + assert_equal(fpos64('324', unique=False, precision=5, + fractional=False), "324.00") + + available_float_dtypes = [np.float16, np.float32, np.float64, np.float128]\ + if hasattr(np, 'float128') else [np.float16, np.float32, np.float64] + + @pytest.mark.parametrize("tp", available_float_dtypes) + def test_dragon4_positional_interface(self, tp): + # test is flaky for musllinux on np.float128 + if IS_MUSL and tp == np.float128: + pytest.skip("Skipping flaky test of float128 on musllinux") + + fpos = np.format_float_positional + + # test padding + assert_equal(fpos(tp('1.0'), pad_left=4, pad_right=4), " 1. ") + assert_equal(fpos(tp('-1.0'), pad_left=4, pad_right=4), " -1. ") + assert_equal(fpos(tp('-10.2'), + pad_left=4, pad_right=4), " -10.2 ") + + # test fixed (non-unique) mode + assert_equal(fpos(tp('1.0'), unique=False, precision=4), "1.0000") + + @pytest.mark.parametrize("tp", available_float_dtypes) + def test_dragon4_positional_interface_trim(self, tp): + # test is flaky for musllinux on np.float128 + if IS_MUSL and tp == np.float128: + pytest.skip("Skipping flaky test of float128 on musllinux") + + fpos = np.format_float_positional + # test trimming + # trim of 'k' or '.' only affects non-unique mode, since unique + # mode will not output trailing 0s. + assert_equal(fpos(tp('1.'), unique=False, precision=4, trim='k'), + "1.0000") + + assert_equal(fpos(tp('1.'), unique=False, precision=4, trim='.'), + "1.") + assert_equal(fpos(tp('1.2'), unique=False, precision=4, trim='.'), + "1.2" if tp != np.float16 else "1.2002") + + assert_equal(fpos(tp('1.'), unique=False, precision=4, trim='0'), + "1.0") + assert_equal(fpos(tp('1.2'), unique=False, precision=4, trim='0'), + "1.2" if tp != np.float16 else "1.2002") + assert_equal(fpos(tp('1.'), trim='0'), "1.0") + + assert_equal(fpos(tp('1.'), unique=False, precision=4, trim='-'), + "1") + assert_equal(fpos(tp('1.2'), unique=False, precision=4, trim='-'), + "1.2" if tp != np.float16 else "1.2002") + assert_equal(fpos(tp('1.'), trim='-'), "1") + assert_equal(fpos(tp('1.001'), precision=1, trim='-'), "1") + + @pytest.mark.parametrize("tp", available_float_dtypes) + @pytest.mark.parametrize("pad_val", [10**5, np.iinfo("int32").max]) + def test_dragon4_positional_interface_overflow(self, tp, pad_val): + # test is flaky for musllinux on np.float128 + if IS_MUSL and tp == np.float128: + pytest.skip("Skipping flaky test of float128 on musllinux") + + fpos = np.format_float_positional + + # gh-28068 + with pytest.raises(RuntimeError, + match="Float formatting result too large"): + fpos(tp('1.047'), unique=False, precision=pad_val) + + with pytest.raises(RuntimeError, + match="Float formatting result too large"): + fpos(tp('1.047'), precision=2, pad_left=pad_val) + + with pytest.raises(RuntimeError, + match="Float formatting result too large"): + fpos(tp('1.047'), precision=2, pad_right=pad_val) + + @pytest.mark.parametrize("tp", available_float_dtypes) + def test_dragon4_scientific_interface(self, tp): + # test is flaky for musllinux on np.float128 + if IS_MUSL and tp == np.float128: + pytest.skip("Skipping flaky test of float128 on musllinux") + + fsci = np.format_float_scientific + + # test exp_digits + assert_equal(fsci(tp('1.23e1'), exp_digits=5), "1.23e+00001") + + # test fixed (non-unique) mode + assert_equal(fsci(tp('1.0'), unique=False, precision=4), + "1.0000e+00") + + @pytest.mark.skipif(not platform.machine().startswith("ppc64"), + reason="only applies to ppc float128 values") + def test_ppc64_ibm_double_double128(self): + # check that the precision decreases once we get into the subnormal + # range. Unlike float64, this starts around 1e-292 instead of 1e-308, + # which happens when the first double is normal and the second is + # subnormal. + x = np.float128('2.123123123123123123123123123123123e-286') + got = [str(x / np.float128('2e' + str(i))) for i in range(40)] + expected = [ + "1.06156156156156156156156156156157e-286", + "1.06156156156156156156156156156158e-287", + "1.06156156156156156156156156156159e-288", + "1.0615615615615615615615615615616e-289", + "1.06156156156156156156156156156157e-290", + "1.06156156156156156156156156156156e-291", + "1.0615615615615615615615615615616e-292", + "1.0615615615615615615615615615615e-293", + "1.061561561561561561561561561562e-294", + "1.06156156156156156156156156155e-295", + "1.0615615615615615615615615616e-296", + "1.06156156156156156156156156e-297", + "1.06156156156156156156156157e-298", + "1.0615615615615615615615616e-299", + "1.06156156156156156156156e-300", + "1.06156156156156156156155e-301", + "1.0615615615615615615616e-302", + "1.061561561561561561562e-303", + "1.06156156156156156156e-304", + "1.0615615615615615618e-305", + "1.06156156156156156e-306", + "1.06156156156156157e-307", + "1.0615615615615616e-308", + "1.06156156156156e-309", + "1.06156156156157e-310", + "1.0615615615616e-311", + "1.06156156156e-312", + "1.06156156154e-313", + "1.0615615616e-314", + "1.06156156e-315", + "1.06156155e-316", + "1.061562e-317", + "1.06156e-318", + "1.06155e-319", + "1.0617e-320", + "1.06e-321", + "1.04e-322", + "1e-323", + "0.0", + "0.0"] + assert_equal(got, expected) + + # Note: we follow glibc behavior, but it (or gcc) might not be right. + # In particular we can get two values that print the same but are not + # equal: + a = np.float128('2') / np.float128('3') + b = np.float128(str(a)) + assert_equal(str(a), str(b)) + assert_(a != b) + + def float32_roundtrip(self): + # gh-9360 + x = np.float32(1024 - 2**-14) + y = np.float32(1024 - 2**-13) + assert_(repr(x) != repr(y)) + assert_equal(np.float32(repr(x)), x) + assert_equal(np.float32(repr(y)), y) + + def float64_vs_python(self): + # gh-2643, gh-6136, gh-6908 + assert_equal(repr(np.float64(0.1)), repr(0.1)) + assert_(repr(np.float64(0.20000000000000004)) != repr(0.2)) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_shape_base.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_shape_base.py new file mode 100644 index 0000000000000000000000000000000000000000..5be3d05bbf113c398ee25a98796d6b04a4759662 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_shape_base.py @@ -0,0 +1,904 @@ +import sys + +import pytest + +import numpy as np +from numpy._core import ( + arange, + array, + atleast_1d, + atleast_2d, + atleast_3d, + block, + concatenate, + hstack, + newaxis, + stack, + vstack, +) +from numpy._core.shape_base import ( + _block_concatenate, + _block_dispatcher, + _block_setup, + _block_slicing, +) +from numpy.exceptions import AxisError +from numpy.testing import ( + IS_PYPY, + assert_, + assert_array_equal, + assert_equal, + assert_raises, + assert_raises_regex, +) +from numpy.testing._private.utils import requires_memory + + +class TestAtleast1d: + def test_0D_array(self): + a = array(1) + b = array(2) + res = [atleast_1d(a), atleast_1d(b)] + desired = [array([1]), array([2])] + assert_array_equal(res, desired) + + def test_1D_array(self): + a = array([1, 2]) + b = array([2, 3]) + res = [atleast_1d(a), atleast_1d(b)] + desired = [array([1, 2]), array([2, 3])] + assert_array_equal(res, desired) + + def test_2D_array(self): + a = array([[1, 2], [1, 2]]) + b = array([[2, 3], [2, 3]]) + res = [atleast_1d(a), atleast_1d(b)] + desired = [a, b] + assert_array_equal(res, desired) + + def test_3D_array(self): + a = array([[1, 2], [1, 2]]) + b = array([[2, 3], [2, 3]]) + a = array([a, a]) + b = array([b, b]) + res = [atleast_1d(a), atleast_1d(b)] + desired = [a, b] + assert_array_equal(res, desired) + + def test_r1array(self): + """ Test to make sure equivalent Travis O's r1array function + """ + assert_(atleast_1d(3).shape == (1,)) + assert_(atleast_1d(3j).shape == (1,)) + assert_(atleast_1d(3.0).shape == (1,)) + assert_(atleast_1d([[2, 3], [4, 5]]).shape == (2, 2)) + + +class TestAtleast2d: + def test_0D_array(self): + a = array(1) + b = array(2) + res = [atleast_2d(a), atleast_2d(b)] + desired = [array([[1]]), array([[2]])] + assert_array_equal(res, desired) + + def test_1D_array(self): + a = array([1, 2]) + b = array([2, 3]) + res = [atleast_2d(a), atleast_2d(b)] + desired = [array([[1, 2]]), array([[2, 3]])] + assert_array_equal(res, desired) + + def test_2D_array(self): + a = array([[1, 2], [1, 2]]) + b = array([[2, 3], [2, 3]]) + res = [atleast_2d(a), atleast_2d(b)] + desired = [a, b] + assert_array_equal(res, desired) + + def test_3D_array(self): + a = array([[1, 2], [1, 2]]) + b = array([[2, 3], [2, 3]]) + a = array([a, a]) + b = array([b, b]) + res = [atleast_2d(a), atleast_2d(b)] + desired = [a, b] + assert_array_equal(res, desired) + + def test_r2array(self): + """ Test to make sure equivalent Travis O's r2array function + """ + assert_(atleast_2d(3).shape == (1, 1)) + assert_(atleast_2d([3j, 1]).shape == (1, 2)) + assert_(atleast_2d([[[3, 1], [4, 5]], [[3, 5], [1, 2]]]).shape == (2, 2, 2)) + + +class TestAtleast3d: + def test_0D_array(self): + a = array(1) + b = array(2) + res = [atleast_3d(a), atleast_3d(b)] + desired = [array([[[1]]]), array([[[2]]])] + assert_array_equal(res, desired) + + def test_1D_array(self): + a = array([1, 2]) + b = array([2, 3]) + res = [atleast_3d(a), atleast_3d(b)] + desired = [array([[[1], [2]]]), array([[[2], [3]]])] + assert_array_equal(res, desired) + + def test_2D_array(self): + a = array([[1, 2], [1, 2]]) + b = array([[2, 3], [2, 3]]) + res = [atleast_3d(a), atleast_3d(b)] + desired = [a[:, :, newaxis], b[:, :, newaxis]] + assert_array_equal(res, desired) + + def test_3D_array(self): + a = array([[1, 2], [1, 2]]) + b = array([[2, 3], [2, 3]]) + a = array([a, a]) + b = array([b, b]) + res = [atleast_3d(a), atleast_3d(b)] + desired = [a, b] + assert_array_equal(res, desired) + + +class TestHstack: + def test_non_iterable(self): + assert_raises(TypeError, hstack, 1) + + def test_empty_input(self): + assert_raises(ValueError, hstack, ()) + + def test_0D_array(self): + a = array(1) + b = array(2) + res = hstack([a, b]) + desired = array([1, 2]) + assert_array_equal(res, desired) + + def test_1D_array(self): + a = array([1]) + b = array([2]) + res = hstack([a, b]) + desired = array([1, 2]) + assert_array_equal(res, desired) + + def test_2D_array(self): + a = array([[1], [2]]) + b = array([[1], [2]]) + res = hstack([a, b]) + desired = array([[1, 1], [2, 2]]) + assert_array_equal(res, desired) + + def test_generator(self): + with pytest.raises(TypeError, match="arrays to stack must be"): + hstack(np.arange(3) for _ in range(2)) + with pytest.raises(TypeError, match="arrays to stack must be"): + hstack(x for x in np.ones((3, 2))) + + def test_casting_and_dtype(self): + a = np.array([1, 2, 3]) + b = np.array([2.5, 3.5, 4.5]) + res = np.hstack((a, b), casting="unsafe", dtype=np.int64) + expected_res = np.array([1, 2, 3, 2, 3, 4]) + assert_array_equal(res, expected_res) + + def test_casting_and_dtype_type_error(self): + a = np.array([1, 2, 3]) + b = np.array([2.5, 3.5, 4.5]) + with pytest.raises(TypeError): + hstack((a, b), casting="safe", dtype=np.int64) + + +class TestVstack: + def test_non_iterable(self): + assert_raises(TypeError, vstack, 1) + + def test_empty_input(self): + assert_raises(ValueError, vstack, ()) + + def test_0D_array(self): + a = array(1) + b = array(2) + res = vstack([a, b]) + desired = array([[1], [2]]) + assert_array_equal(res, desired) + + def test_1D_array(self): + a = array([1]) + b = array([2]) + res = vstack([a, b]) + desired = array([[1], [2]]) + assert_array_equal(res, desired) + + def test_2D_array(self): + a = array([[1], [2]]) + b = array([[1], [2]]) + res = vstack([a, b]) + desired = array([[1], [2], [1], [2]]) + assert_array_equal(res, desired) + + def test_2D_array2(self): + a = array([1, 2]) + b = array([1, 2]) + res = vstack([a, b]) + desired = array([[1, 2], [1, 2]]) + assert_array_equal(res, desired) + + def test_generator(self): + with pytest.raises(TypeError, match="arrays to stack must be"): + vstack(np.arange(3) for _ in range(2)) + + def test_casting_and_dtype(self): + a = np.array([1, 2, 3]) + b = np.array([2.5, 3.5, 4.5]) + res = np.vstack((a, b), casting="unsafe", dtype=np.int64) + expected_res = np.array([[1, 2, 3], [2, 3, 4]]) + assert_array_equal(res, expected_res) + + def test_casting_and_dtype_type_error(self): + a = np.array([1, 2, 3]) + b = np.array([2.5, 3.5, 4.5]) + with pytest.raises(TypeError): + vstack((a, b), casting="safe", dtype=np.int64) + + +class TestConcatenate: + def test_returns_copy(self): + a = np.eye(3) + b = np.concatenate([a]) + b[0, 0] = 2 + assert b[0, 0] != a[0, 0] + + def test_exceptions(self): + # test axis must be in bounds + for ndim in [1, 2, 3]: + a = np.ones((1,) * ndim) + np.concatenate((a, a), axis=0) # OK + assert_raises(AxisError, np.concatenate, (a, a), axis=ndim) + assert_raises(AxisError, np.concatenate, (a, a), axis=-(ndim + 1)) + + # Scalars cannot be concatenated + assert_raises(ValueError, concatenate, (0,)) + assert_raises(ValueError, concatenate, (np.array(0),)) + + # dimensionality must match + assert_raises_regex( + ValueError, + r"all the input arrays must have same number of dimensions, but " + r"the array at index 0 has 1 dimension\(s\) and the array at " + r"index 1 has 2 dimension\(s\)", + np.concatenate, (np.zeros(1), np.zeros((1, 1)))) + + # test shapes must match except for concatenation axis + a = np.ones((1, 2, 3)) + b = np.ones((2, 2, 3)) + axis = list(range(3)) + for i in range(3): + np.concatenate((a, b), axis=axis[0]) # OK + assert_raises_regex( + ValueError, + "all the input array dimensions except for the concatenation axis " + f"must match exactly, but along dimension {i}, the array at " + "index 0 has size 1 and the array at index 1 has size 2", + np.concatenate, (a, b), axis=axis[1]) + assert_raises(ValueError, np.concatenate, (a, b), axis=axis[2]) + a = np.moveaxis(a, -1, 0) + b = np.moveaxis(b, -1, 0) + axis.append(axis.pop(0)) + + # No arrays to concatenate raises ValueError + assert_raises(ValueError, concatenate, ()) + + @pytest.mark.slow + @pytest.mark.skipif( + sys.maxsize < 2**32, + reason="only problematic on 64bit platforms" + ) + @requires_memory(2 * np.iinfo(np.intc).max) + @pytest.mark.thread_unsafe(reason="crashes with low memory") + def test_huge_list_error(self): + a = np.array([1]) + max_int = np.iinfo(np.intc).max + arrs = (a,) * (max_int + 1) + msg = (fr"concatenate\(\) only supports up to {max_int} arrays" + f" but got {max_int + 1}.") + with pytest.raises(ValueError, match=msg): + np.concatenate(arrs) + + def test_concatenate_axis_None(self): + a = np.arange(4, dtype=np.float64).reshape((2, 2)) + b = list(range(3)) + c = ['x'] + r = np.concatenate((a, a), axis=None) + assert_equal(r.dtype, a.dtype) + assert_equal(r.ndim, 1) + r = np.concatenate((a, b), axis=None) + assert_equal(r.size, a.size + len(b)) + assert_equal(r.dtype, a.dtype) + r = np.concatenate((a, b, c), axis=None, dtype="U") + d = array(['0.0', '1.0', '2.0', '3.0', + '0', '1', '2', 'x']) + assert_array_equal(r, d) + + out = np.zeros(a.size + len(b)) + r = np.concatenate((a, b), axis=None) + rout = np.concatenate((a, b), axis=None, out=out) + assert_(out is rout) + assert_equal(r, rout) + + def test_large_concatenate_axis_None(self): + # When no axis is given, concatenate uses flattened versions. + # This also had a bug with many arrays (see gh-5979). + x = np.arange(1, 100) + r = np.concatenate(x, None) + assert_array_equal(x, r) + + # Once upon a time, this was the same as `axis=None` now it fails + # (with an unspecified error, as multiple things are wrong here) + with pytest.raises(ValueError): + np.concatenate(x, 100) + + def test_concatenate(self): + # Test concatenate function + # One sequence returns unmodified (but as array) + r4 = list(range(4)) + assert_array_equal(concatenate((r4,)), r4) + # Any sequence + assert_array_equal(concatenate((tuple(r4),)), r4) + assert_array_equal(concatenate((array(r4),)), r4) + # 1D default concatenation + r3 = list(range(3)) + assert_array_equal(concatenate((r4, r3)), r4 + r3) + # Mixed sequence types + assert_array_equal(concatenate((tuple(r4), r3)), r4 + r3) + assert_array_equal(concatenate((array(r4), r3)), r4 + r3) + # Explicit axis specification + assert_array_equal(concatenate((r4, r3), 0), r4 + r3) + # Including negative + assert_array_equal(concatenate((r4, r3), -1), r4 + r3) + # 2D + a23 = array([[10, 11, 12], [13, 14, 15]]) + a13 = array([[0, 1, 2]]) + res = array([[10, 11, 12], [13, 14, 15], [0, 1, 2]]) + assert_array_equal(concatenate((a23, a13)), res) + assert_array_equal(concatenate((a23, a13), 0), res) + assert_array_equal(concatenate((a23.T, a13.T), 1), res.T) + assert_array_equal(concatenate((a23.T, a13.T), -1), res.T) + # Arrays much match shape + assert_raises(ValueError, concatenate, (a23.T, a13.T), 0) + # 3D + res = arange(2 * 3 * 7).reshape((2, 3, 7)) + a0 = res[..., :4] + a1 = res[..., 4:6] + a2 = res[..., 6:] + assert_array_equal(concatenate((a0, a1, a2), 2), res) + assert_array_equal(concatenate((a0, a1, a2), -1), res) + assert_array_equal(concatenate((a0.T, a1.T, a2.T), 0), res.T) + + out = res.copy() + rout = concatenate((a0, a1, a2), 2, out=out) + assert_(out is rout) + assert_equal(res, rout) + + def test_concatenate_same_value(self): + r4 = list(range(4)) + with pytest.raises(ValueError, match="^casting must be one of"): + concatenate([r4, r4], casting="same_value") + + @pytest.mark.skipif( + IS_PYPY, + reason="PYPY handles sq_concat, nb_add differently than cpython" + ) + def test_operator_concat(self): + import operator + a = array([1, 2]) + b = array([3, 4]) + n = [1, 2] + res = array([1, 2, 3, 4]) + assert_raises(TypeError, operator.concat, a, b) + assert_raises(TypeError, operator.concat, a, n) + assert_raises(TypeError, operator.concat, n, a) + assert_raises(TypeError, operator.concat, a, 1) + assert_raises(TypeError, operator.concat, 1, a) + + def test_bad_out_shape(self): + a = array([1, 2]) + b = array([3, 4]) + + assert_raises(ValueError, concatenate, (a, b), out=np.empty(5)) + assert_raises(ValueError, concatenate, (a, b), out=np.empty((4, 1))) + assert_raises(ValueError, concatenate, (a, b), out=np.empty((1, 4))) + concatenate((a, b), out=np.empty(4)) + + @pytest.mark.parametrize("axis", [None, 0]) + @pytest.mark.parametrize("out_dtype", ["c8", "f4", "f8", ">f8", "i8", "S4"]) + @pytest.mark.parametrize("casting", + ['no', 'equiv', 'safe', 'same_kind', 'unsafe']) + def test_out_and_dtype(self, axis, out_dtype, casting): + # Compare usage of `out=out` with `dtype=out.dtype` + out = np.empty(4, dtype=out_dtype) + to_concat = (array([1.1, 2.2]), array([3.3, 4.4])) + + if not np.can_cast(to_concat[0], out_dtype, casting=casting): + with assert_raises(TypeError): + concatenate(to_concat, out=out, axis=axis, casting=casting) + with assert_raises(TypeError): + concatenate(to_concat, dtype=out.dtype, + axis=axis, casting=casting) + else: + res_out = concatenate(to_concat, out=out, + axis=axis, casting=casting) + res_dtype = concatenate(to_concat, dtype=out.dtype, + axis=axis, casting=casting) + assert res_out is out + assert_array_equal(out, res_dtype) + assert res_dtype.dtype == out_dtype + + with assert_raises(TypeError): + concatenate(to_concat, out=out, dtype=out_dtype, axis=axis) + + @pytest.mark.parametrize("axis", [None, 0]) + @pytest.mark.parametrize("string_dt", ["S", "U", "S0", "U0"]) + @pytest.mark.parametrize("arrs", + [([0.],), ([0.], [1]), ([0], ["string"], [1.])]) + def test_dtype_with_promotion(self, arrs, string_dt, axis): + # Note that U0 and S0 should be deprecated eventually and changed to + # actually give the empty string result (together with `np.array`) + res = np.concatenate(arrs, axis=axis, dtype=string_dt, casting="unsafe") + # The actual dtype should be identical to a cast (of a double array): + assert res.dtype == np.array(1.).astype(string_dt).dtype + + @pytest.mark.parametrize("axis", [None, 0]) + def test_string_dtype_does_not_inspect(self, axis): + with pytest.raises(TypeError): + np.concatenate(([None], [1]), dtype="S", axis=axis) + with pytest.raises(TypeError): + np.concatenate(([None], [1]), dtype="U", axis=axis) + + @pytest.mark.parametrize("axis", [None, 0]) + def test_subarray_error(self, axis): + with pytest.raises(TypeError, match=".*subarray dtype"): + np.concatenate(([1], [1]), dtype="(2,)i", axis=axis) + + +def test_stack(): + # non-iterable input + assert_raises(TypeError, stack, 1) + + # 0d input + for input_ in [(1, 2, 3), + [np.int32(1), np.int32(2), np.int32(3)], + [np.array(1), np.array(2), np.array(3)]]: + assert_array_equal(stack(input_), [1, 2, 3]) + # 1d input examples + a = np.array([1, 2, 3]) + b = np.array([4, 5, 6]) + r1 = array([[1, 2, 3], [4, 5, 6]]) + assert_array_equal(np.stack((a, b)), r1) + assert_array_equal(np.stack((a, b), axis=1), r1.T) + # all input types + assert_array_equal(np.stack([a, b]), r1) + assert_array_equal(np.stack(array([a, b])), r1) + # all shapes for 1d input + arrays = [np.random.randn(3) for _ in range(10)] + axes = [0, 1, -1, -2] + expected_shapes = [(10, 3), (3, 10), (3, 10), (10, 3)] + for axis, expected_shape in zip(axes, expected_shapes): + assert_equal(np.stack(arrays, axis).shape, expected_shape) + assert_raises_regex(AxisError, 'out of bounds', stack, arrays, axis=2) + assert_raises_regex(AxisError, 'out of bounds', stack, arrays, axis=-3) + # all shapes for 2d input + arrays = [np.random.randn(3, 4) for _ in range(10)] + axes = [0, 1, 2, -1, -2, -3] + expected_shapes = [(10, 3, 4), (3, 10, 4), (3, 4, 10), + (3, 4, 10), (3, 10, 4), (10, 3, 4)] + for axis, expected_shape in zip(axes, expected_shapes): + assert_equal(np.stack(arrays, axis).shape, expected_shape) + # empty arrays + assert_(stack([[], [], []]).shape == (3, 0)) + assert_(stack([[], [], []], axis=1).shape == (0, 3)) + # out + out = np.zeros_like(r1) + np.stack((a, b), out=out) + assert_array_equal(out, r1) + # edge cases + assert_raises_regex(ValueError, 'need at least one array', stack, []) + assert_raises_regex(ValueError, 'must have the same shape', + stack, [1, np.arange(3)]) + assert_raises_regex(ValueError, 'must have the same shape', + stack, [np.arange(3), 1]) + assert_raises_regex(ValueError, 'must have the same shape', + stack, [np.arange(3), 1], axis=1) + assert_raises_regex(ValueError, 'must have the same shape', + stack, [np.zeros((3, 3)), np.zeros(3)], axis=1) + assert_raises_regex(ValueError, 'must have the same shape', + stack, [np.arange(2), np.arange(3)]) + + # do not accept generators + with pytest.raises(TypeError, match="arrays to stack must be"): + stack(x for x in range(3)) + + # casting and dtype test + a = np.array([1, 2, 3]) + b = np.array([2.5, 3.5, 4.5]) + res = np.stack((a, b), axis=1, casting="unsafe", dtype=np.int64) + expected_res = np.array([[1, 2], [2, 3], [3, 4]]) + assert_array_equal(res, expected_res) + # casting and dtype with TypeError + with assert_raises(TypeError): + stack((a, b), dtype=np.int64, axis=1, casting="safe") + + +def test_unstack(): + a = np.arange(24).reshape((2, 3, 4)) + + for stacks in [np.unstack(a), + np.unstack(a, axis=0), + np.unstack(a, axis=-3)]: + assert isinstance(stacks, tuple) + assert len(stacks) == 2 + assert_array_equal(stacks[0], a[0]) + assert_array_equal(stacks[1], a[1]) + + for stacks in [np.unstack(a, axis=1), + np.unstack(a, axis=-2)]: + assert isinstance(stacks, tuple) + assert len(stacks) == 3 + assert_array_equal(stacks[0], a[:, 0]) + assert_array_equal(stacks[1], a[:, 1]) + assert_array_equal(stacks[2], a[:, 2]) + + for stacks in [np.unstack(a, axis=2), + np.unstack(a, axis=-1)]: + assert isinstance(stacks, tuple) + assert len(stacks) == 4 + assert_array_equal(stacks[0], a[:, :, 0]) + assert_array_equal(stacks[1], a[:, :, 1]) + assert_array_equal(stacks[2], a[:, :, 2]) + assert_array_equal(stacks[3], a[:, :, 3]) + + assert_raises(ValueError, np.unstack, a, axis=3) + assert_raises(ValueError, np.unstack, a, axis=-4) + assert_raises(ValueError, np.unstack, np.array(0), axis=0) + + +@pytest.mark.parametrize("axis", [0]) +@pytest.mark.parametrize("out_dtype", ["c8", "f4", "f8", ">f8", "i8"]) +@pytest.mark.parametrize("casting", + ['no', 'equiv', 'safe', 'same_kind', 'unsafe']) +def test_stack_out_and_dtype(axis, out_dtype, casting): + to_concat = (array([1, 2]), array([3, 4])) + res = array([[1, 2], [3, 4]]) + out = np.zeros_like(res) + + if not np.can_cast(to_concat[0], out_dtype, casting=casting): + with assert_raises(TypeError): + stack(to_concat, dtype=out_dtype, + axis=axis, casting=casting) + else: + res_out = stack(to_concat, out=out, + axis=axis, casting=casting) + res_dtype = stack(to_concat, dtype=out_dtype, + axis=axis, casting=casting) + assert res_out is out + assert_array_equal(out, res_dtype) + assert res_dtype.dtype == out_dtype + + with assert_raises(TypeError): + stack(to_concat, out=out, dtype=out_dtype, axis=axis) + + +class TestBlock: + @pytest.fixture(params=['block', 'force_concatenate', 'force_slicing']) + def block(self, request): + # blocking small arrays and large arrays go through different paths. + # the algorithm is triggered depending on the number of element + # copies required. + # We define a test fixture that forces most tests to go through + # both code paths. + # Ultimately, this should be removed if a single algorithm is found + # to be faster for both small and large arrays. + def _block_force_concatenate(arrays): + arrays, list_ndim, result_ndim, _ = _block_setup(arrays) + return _block_concatenate(arrays, list_ndim, result_ndim) + + def _block_force_slicing(arrays): + arrays, list_ndim, result_ndim, _ = _block_setup(arrays) + return _block_slicing(arrays, list_ndim, result_ndim) + + if request.param == 'force_concatenate': + return _block_force_concatenate + elif request.param == 'force_slicing': + return _block_force_slicing + elif request.param == 'block': + return block + else: + raise ValueError('Unknown blocking request. There is a typo in the tests.') + + def test_returns_copy(self, block): + a = np.eye(3) + b = block(a) + b[0, 0] = 2 + assert b[0, 0] != a[0, 0] + + def test_block_total_size_estimate(self, block): + _, _, _, total_size = _block_setup([1]) + assert total_size == 1 + + _, _, _, total_size = _block_setup([[1]]) + assert total_size == 1 + + _, _, _, total_size = _block_setup([[1, 1]]) + assert total_size == 2 + + _, _, _, total_size = _block_setup([[1], [1]]) + assert total_size == 2 + + _, _, _, total_size = _block_setup([[1, 2], [3, 4]]) + assert total_size == 4 + + def test_block_simple_row_wise(self, block): + a_2d = np.ones((2, 2)) + b_2d = 2 * a_2d + desired = np.array([[1, 1, 2, 2], + [1, 1, 2, 2]]) + result = block([a_2d, b_2d]) + assert_equal(desired, result) + + def test_block_simple_column_wise(self, block): + a_2d = np.ones((2, 2)) + b_2d = 2 * a_2d + expected = np.array([[1, 1], + [1, 1], + [2, 2], + [2, 2]]) + result = block([[a_2d], [b_2d]]) + assert_equal(expected, result) + + def test_block_with_1d_arrays_row_wise(self, block): + # # # 1-D vectors are treated as row arrays + a = np.array([1, 2, 3]) + b = np.array([2, 3, 4]) + expected = np.array([1, 2, 3, 2, 3, 4]) + result = block([a, b]) + assert_equal(expected, result) + + def test_block_with_1d_arrays_multiple_rows(self, block): + a = np.array([1, 2, 3]) + b = np.array([2, 3, 4]) + expected = np.array([[1, 2, 3, 2, 3, 4], + [1, 2, 3, 2, 3, 4]]) + result = block([[a, b], [a, b]]) + assert_equal(expected, result) + + def test_block_with_1d_arrays_column_wise(self, block): + # # # 1-D vectors are treated as row arrays + a_1d = np.array([1, 2, 3]) + b_1d = np.array([2, 3, 4]) + expected = np.array([[1, 2, 3], + [2, 3, 4]]) + result = block([[a_1d], [b_1d]]) + assert_equal(expected, result) + + def test_block_mixed_1d_and_2d(self, block): + a_2d = np.ones((2, 2)) + b_1d = np.array([2, 2]) + result = block([[a_2d], [b_1d]]) + expected = np.array([[1, 1], + [1, 1], + [2, 2]]) + assert_equal(expected, result) + + def test_block_complicated(self, block): + # a bit more complicated + one_2d = np.array([[1, 1, 1]]) + two_2d = np.array([[2, 2, 2]]) + three_2d = np.array([[3, 3, 3, 3, 3, 3]]) + four_1d = np.array([4, 4, 4, 4, 4, 4]) + five_0d = np.array(5) + six_1d = np.array([6, 6, 6, 6, 6]) + zero_2d = np.zeros((2, 6)) + + expected = np.array([[1, 1, 1, 2, 2, 2], + [3, 3, 3, 3, 3, 3], + [4, 4, 4, 4, 4, 4], + [5, 6, 6, 6, 6, 6], + [0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 0]]) + + result = block([[one_2d, two_2d], + [three_2d], + [four_1d], + [five_0d, six_1d], + [zero_2d]]) + assert_equal(result, expected) + + def test_nested(self, block): + one = np.array([1, 1, 1]) + two = np.array([[2, 2, 2], [2, 2, 2], [2, 2, 2]]) + three = np.array([3, 3, 3]) + four = np.array([4, 4, 4]) + five = np.array(5) + six = np.array([6, 6, 6, 6, 6]) + zero = np.zeros((2, 6)) + + result = block([ + [ + block([ + [one], + [three], + [four] + ]), + two + ], + [five, six], + [zero] + ]) + expected = np.array([[1, 1, 1, 2, 2, 2], + [3, 3, 3, 2, 2, 2], + [4, 4, 4, 2, 2, 2], + [5, 6, 6, 6, 6, 6], + [0, 0, 0, 0, 0, 0], + [0, 0, 0, 0, 0, 0]]) + + assert_equal(result, expected) + + def test_3d(self, block): + a000 = np.ones((2, 2, 2), int) * 1 + + a100 = np.ones((3, 2, 2), int) * 2 + a010 = np.ones((2, 3, 2), int) * 3 + a001 = np.ones((2, 2, 3), int) * 4 + + a011 = np.ones((2, 3, 3), int) * 5 + a101 = np.ones((3, 2, 3), int) * 6 + a110 = np.ones((3, 3, 2), int) * 7 + + a111 = np.ones((3, 3, 3), int) * 8 + + result = block([ + [ + [a000, a001], + [a010, a011], + ], + [ + [a100, a101], + [a110, a111], + ] + ]) + expected = array([[[1, 1, 4, 4, 4], + [1, 1, 4, 4, 4], + [3, 3, 5, 5, 5], + [3, 3, 5, 5, 5], + [3, 3, 5, 5, 5]], + + [[1, 1, 4, 4, 4], + [1, 1, 4, 4, 4], + [3, 3, 5, 5, 5], + [3, 3, 5, 5, 5], + [3, 3, 5, 5, 5]], + + [[2, 2, 6, 6, 6], + [2, 2, 6, 6, 6], + [7, 7, 8, 8, 8], + [7, 7, 8, 8, 8], + [7, 7, 8, 8, 8]], + + [[2, 2, 6, 6, 6], + [2, 2, 6, 6, 6], + [7, 7, 8, 8, 8], + [7, 7, 8, 8, 8], + [7, 7, 8, 8, 8]], + + [[2, 2, 6, 6, 6], + [2, 2, 6, 6, 6], + [7, 7, 8, 8, 8], + [7, 7, 8, 8, 8], + [7, 7, 8, 8, 8]]]) + + assert_array_equal(result, expected) + + def test_block_with_mismatched_shape(self, block): + a = np.array([0, 0]) + b = np.eye(2) + assert_raises(ValueError, block, [a, b]) + assert_raises(ValueError, block, [b, a]) + + to_block = [[np.ones((2, 3)), np.ones((2, 2))], + [np.ones((2, 2)), np.ones((2, 2))]] + assert_raises(ValueError, block, to_block) + + def test_no_lists(self, block): + assert_equal(block(1), np.array(1)) + assert_equal(block(np.eye(3)), np.eye(3)) + + def test_invalid_nesting(self, block): + msg = 'depths are mismatched' + assert_raises_regex(ValueError, msg, block, [1, [2]]) + assert_raises_regex(ValueError, msg, block, [1, []]) + assert_raises_regex(ValueError, msg, block, [[1], 2]) + assert_raises_regex(ValueError, msg, block, [[], 2]) + assert_raises_regex(ValueError, msg, block, [ + [[1], [2]], + [[3, 4]], + [5] # missing brackets + ]) + + def test_empty_lists(self, block): + assert_raises_regex(ValueError, 'empty', block, []) + assert_raises_regex(ValueError, 'empty', block, [[]]) + assert_raises_regex(ValueError, 'empty', block, [[1], []]) + + def test_tuple(self, block): + assert_raises_regex(TypeError, 'tuple', block, ([1, 2], [3, 4])) + assert_raises_regex(TypeError, 'tuple', block, [(1, 2), (3, 4)]) + + def test_different_ndims(self, block): + a = 1. + b = 2 * np.ones((1, 2)) + c = 3 * np.ones((1, 1, 3)) + + result = block([a, b, c]) + expected = np.array([[[1., 2., 2., 3., 3., 3.]]]) + + assert_equal(result, expected) + + def test_different_ndims_depths(self, block): + a = 1. + b = 2 * np.ones((1, 2)) + c = 3 * np.ones((1, 2, 3)) + + result = block([[a, b], [c]]) + expected = np.array([[[1., 2., 2.], + [3., 3., 3.], + [3., 3., 3.]]]) + + assert_equal(result, expected) + + def test_block_memory_order(self, block): + # 3D + arr_c = np.zeros((3,) * 3, order='C') + arr_f = np.zeros((3,) * 3, order='F') + + b_c = [[[arr_c, arr_c], + [arr_c, arr_c]], + [[arr_c, arr_c], + [arr_c, arr_c]]] + + b_f = [[[arr_f, arr_f], + [arr_f, arr_f]], + [[arr_f, arr_f], + [arr_f, arr_f]]] + + assert block(b_c).flags['C_CONTIGUOUS'] + assert block(b_f).flags['F_CONTIGUOUS'] + + arr_c = np.zeros((3, 3), order='C') + arr_f = np.zeros((3, 3), order='F') + # 2D + b_c = [[arr_c, arr_c], + [arr_c, arr_c]] + + b_f = [[arr_f, arr_f], + [arr_f, arr_f]] + + assert block(b_c).flags['C_CONTIGUOUS'] + assert block(b_f).flags['F_CONTIGUOUS'] + + +def test_block_dispatcher(): + class ArrayLike: + pass + a = ArrayLike() + b = ArrayLike() + c = ArrayLike() + assert_equal(list(_block_dispatcher(a)), [a]) + assert_equal(list(_block_dispatcher([a])), [a]) + assert_equal(list(_block_dispatcher([a, b])), [a, b]) + assert_equal(list(_block_dispatcher([[a], [b, [c]]])), [a, b, c]) + # don't recurse into non-lists + assert_equal(list(_block_dispatcher((a, b))), [(a, b)]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_simd.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_simd.py new file mode 100644 index 0000000000000000000000000000000000000000..335abc98c84e8197015c675e0c07fb2631f02e6e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_simd.py @@ -0,0 +1,1345 @@ +# NOTE: Please avoid the use of numpy.testing since NPYV intrinsics +# may be involved in their functionality. +import itertools +import math +import operator +import re + +import pytest + +from numpy._core._multiarray_umath import __cpu_baseline__ +from numpy._core._simd import clear_floatstatus, get_floatstatus, targets + + +def check_floatstatus(divbyzero=False, overflow=False, + underflow=False, invalid=False, + all=False): + #define NPY_FPE_DIVIDEBYZERO 1 + #define NPY_FPE_OVERFLOW 2 + #define NPY_FPE_UNDERFLOW 4 + #define NPY_FPE_INVALID 8 + err = get_floatstatus() + ret = (all or divbyzero) and (err & 1) != 0 + ret |= (all or overflow) and (err & 2) != 0 + ret |= (all or underflow) and (err & 4) != 0 + ret |= (all or invalid) and (err & 8) != 0 + return ret + +class _Test_Utility: + # submodule of the desired SIMD extension, e.g. targets["AVX512F"] + npyv = None + # the current data type suffix e.g. 's8' + sfx = None + # target name can be 'baseline' or one or more of CPU features + target_name = None + + def __getattr__(self, attr): + """ + To call NPV intrinsics without the attribute 'npyv' and + auto suffixing intrinsics according to class attribute 'sfx' + """ + return getattr(self.npyv, attr + "_" + self.sfx) + + def _x2(self, intrin_name): + return getattr(self.npyv, f"{intrin_name}_{self.sfx}x2") + + def _data(self, start=None, count=None, reverse=False): + """ + Create list of consecutive numbers according to number of vector's lanes. + """ + if start is None: + start = 1 + if count is None: + count = self.nlanes + rng = range(start, start + count) + if reverse: + rng = reversed(rng) + if self._is_fp(): + return [x / 1.0 for x in rng] + return list(rng) + + def _is_unsigned(self): + return self.sfx[0] == 'u' + + def _is_signed(self): + return self.sfx[0] == 's' + + def _is_fp(self): + return self.sfx[0] == 'f' + + def _scalar_size(self): + return int(self.sfx[1:]) + + def _int_clip(self, seq): + if self._is_fp(): + return seq + max_int = self._int_max() + min_int = self._int_min() + return [min(max(v, min_int), max_int) for v in seq] + + def _int_max(self): + if self._is_fp(): + return None + max_u = self._to_unsigned(self.setall(-1))[0] + if self._is_signed(): + return max_u // 2 + return max_u + + def _int_min(self): + if self._is_fp(): + return None + if self._is_unsigned(): + return 0 + return -(self._int_max() + 1) + + def _true_mask(self): + max_unsig = getattr(self.npyv, "setall_u" + self.sfx[1:])(-1) + return max_unsig[0] + + def _to_unsigned(self, vector): + if isinstance(vector, (list, tuple)): + return getattr(self.npyv, "load_u" + self.sfx[1:])(vector) + else: + sfx = vector.__name__.replace("npyv_", "") + if sfx[0] == "b": + cvt_intrin = "cvt_u{0}_b{0}" + else: + cvt_intrin = "reinterpret_u{0}_{1}" + return getattr(self.npyv, cvt_intrin.format(sfx[1:], sfx))(vector) + + def _pinfinity(self): + return float("inf") + + def _ninfinity(self): + return -float("inf") + + def _nan(self): + return float("nan") + + def _cpu_features(self): + target = self.target_name + if target == "baseline": + target = __cpu_baseline__ + else: + target = target.split('__') # multi-target separator + return ' '.join(target) + +class _SIMD_BOOL(_Test_Utility): + """ + To test all boolean vector types at once + """ + def _nlanes(self): + return getattr(self.npyv, "nlanes_u" + self.sfx[1:]) + + def _data(self, start=None, count=None, reverse=False): + true_mask = self._true_mask() + rng = range(self._nlanes()) + if reverse: + rng = reversed(rng) + return [true_mask if x % 2 else 0 for x in rng] + + def _load_b(self, data): + len_str = self.sfx[1:] + load = getattr(self.npyv, "load_u" + len_str) + cvt = getattr(self.npyv, f"cvt_b{len_str}_u{len_str}") + return cvt(load(data)) + + def test_operators_logical(self): + """ + Logical operations for boolean types. + Test intrinsics: + npyv_xor_##SFX, npyv_and_##SFX, npyv_or_##SFX, npyv_not_##SFX, + npyv_andc_b8, npvy_orc_b8, nvpy_xnor_b8 + """ + data_a = self._data() + data_b = self._data(reverse=True) + vdata_a = self._load_b(data_a) + vdata_b = self._load_b(data_b) + + data_and = [a & b for a, b in zip(data_a, data_b)] + vand = getattr(self, "and")(vdata_a, vdata_b) + assert vand == data_and + + data_or = [a | b for a, b in zip(data_a, data_b)] + vor = getattr(self, "or")(vdata_a, vdata_b) + assert vor == data_or + + data_xor = [a ^ b for a, b in zip(data_a, data_b)] + vxor = self.xor(vdata_a, vdata_b) + assert vxor == data_xor + + vnot = getattr(self, "not")(vdata_a) + assert vnot == data_b + + # among the boolean types, andc, orc and xnor only support b8 + if self.sfx not in ("b8"): + return + + data_andc = [(a & ~b) & 0xFF for a, b in zip(data_a, data_b)] + vandc = self.andc(vdata_a, vdata_b) + assert data_andc == vandc + + data_orc = [(a | ~b) & 0xFF for a, b in zip(data_a, data_b)] + vorc = self.orc(vdata_a, vdata_b) + assert data_orc == vorc + + data_xnor = [~(a ^ b) & 0xFF for a, b in zip(data_a, data_b)] + vxnor = self.xnor(vdata_a, vdata_b) + assert data_xnor == vxnor + + def test_tobits(self): + data2bits = lambda data: sum(int(x != 0) << i for i, x in enumerate(data, 0)) + for data in (self._data(), self._data(reverse=True)): + vdata = self._load_b(data) + data_bits = data2bits(data) + tobits = self.tobits(vdata) + bin_tobits = bin(tobits) + assert bin_tobits == bin(data_bits) + + def test_pack(self): + """ + Pack multiple vectors into one + Test intrinsics: + npyv_pack_b8_b16 + npyv_pack_b8_b32 + npyv_pack_b8_b64 + """ + if self.sfx not in ("b16", "b32", "b64"): + return + # create the vectors + data = self._data() + rdata = self._data(reverse=True) + vdata = self._load_b(data) + vrdata = self._load_b(rdata) + pack_simd = getattr(self.npyv, f"pack_b8_{self.sfx}") + # for scalar execution, concatenate the elements of the multiple lists + # into a single list (spack) and then iterate over the elements of + # the created list applying a mask to capture the first byte of them. + if self.sfx == "b16": + spack = [(i & 0xFF) for i in (list(rdata) + list(data))] + vpack = pack_simd(vrdata, vdata) + elif self.sfx == "b32": + spack = [(i & 0xFF) for i in (2 * list(rdata) + 2 * list(data))] + vpack = pack_simd(vrdata, vrdata, vdata, vdata) + elif self.sfx == "b64": + spack = [(i & 0xFF) for i in (4 * list(rdata) + 4 * list(data))] + vpack = pack_simd(vrdata, vrdata, vrdata, vrdata, + vdata, vdata, vdata, vdata) + assert vpack == spack + + @pytest.mark.parametrize("intrin", ["any", "all"]) + @pytest.mark.parametrize("data", ( + [-1, 0], + [0, -1], + [-1], + [0] + )) + def test_operators_crosstest(self, intrin, data): + """ + Test intrinsics: + npyv_any_##SFX + npyv_all_##SFX + """ + data_a = self._load_b(data * self._nlanes()) + func = eval(intrin) + intrin = getattr(self, intrin) + desired = func(data_a) + simd = intrin(data_a) + assert not not simd == desired + +class _SIMD_INT(_Test_Utility): + """ + To test all integer vector types at once + """ + def test_operators_shift(self): + if self.sfx in ("u8", "s8"): + return + + data_a = self._data(self._int_max() - self.nlanes) + data_b = self._data(self._int_min(), reverse=True) + vdata_a, vdata_b = self.load(data_a), self.load(data_b) + + for count in range(self._scalar_size()): + # load to cast + data_shl_a = self.load([a << count for a in data_a]) + # left shift + shl = self.shl(vdata_a, count) + assert shl == data_shl_a + # load to cast + data_shr_a = self.load([a >> count for a in data_a]) + # right shift + shr = self.shr(vdata_a, count) + assert shr == data_shr_a + + # shift by zero or max or out-range immediate constant is not + # applicable and illogical + for count in range(1, self._scalar_size()): + # load to cast + data_shl_a = self.load([a << count for a in data_a]) + # left shift by an immediate constant + shli = self.shli(vdata_a, count) + assert shli == data_shl_a + # load to cast + data_shr_a = self.load([a >> count for a in data_a]) + # right shift by an immediate constant + shri = self.shri(vdata_a, count) + assert shri == data_shr_a + + def test_arithmetic_subadd_saturated(self): + if self.sfx in ("u32", "s32", "u64", "s64"): + return + + data_a = self._data(self._int_max() - self.nlanes) + data_b = self._data(self._int_min(), reverse=True) + vdata_a, vdata_b = self.load(data_a), self.load(data_b) + + data_adds = self._int_clip([a + b for a, b in zip(data_a, data_b)]) + adds = self.adds(vdata_a, vdata_b) + assert adds == data_adds + + data_subs = self._int_clip([a - b for a, b in zip(data_a, data_b)]) + subs = self.subs(vdata_a, vdata_b) + assert subs == data_subs + + def test_math_max_min(self): + data_a = self._data() + data_b = self._data(self.nlanes) + vdata_a, vdata_b = self.load(data_a), self.load(data_b) + + data_max = [max(a, b) for a, b in zip(data_a, data_b)] + simd_max = self.max(vdata_a, vdata_b) + assert simd_max == data_max + + data_min = [min(a, b) for a, b in zip(data_a, data_b)] + simd_min = self.min(vdata_a, vdata_b) + assert simd_min == data_min + + @pytest.mark.parametrize("start", [-100, -10000, 0, 100, 10000]) + def test_reduce_max_min(self, start): + """ + Test intrinsics: + npyv_reduce_max_##sfx + npyv_reduce_min_##sfx + """ + vdata_a = self.load(self._data(start)) + assert self.reduce_max(vdata_a) == max(vdata_a) + assert self.reduce_min(vdata_a) == min(vdata_a) + + +class _SIMD_FP32(_Test_Utility): + """ + To only test single precision + """ + def test_conversions(self): + """ + Round to nearest even integer, assume CPU control register is set to rounding. + Test intrinsics: + npyv_round_s32_##SFX + """ + features = self._cpu_features() + if not self.npyv.simd_f64 and re.match(r".*(NEON|ASIMD)", features): + # very costly to emulate nearest even on Armv7 + # instead we round halves to up. e.g. 0.5 -> 1, -0.5 -> -1 + _round = lambda v: int(v + (0.5 if v >= 0 else -0.5)) + else: + _round = round + vdata_a = self.load(self._data()) + vdata_a = self.sub(vdata_a, self.setall(0.5)) + data_round = [_round(x) for x in vdata_a] + vround = self.round_s32(vdata_a) + assert vround == data_round + +class _SIMD_FP64(_Test_Utility): + """ + To only test double precision + """ + def test_conversions(self): + """ + Round to nearest even integer, assume CPU control register is set to rounding. + Test intrinsics: + npyv_round_s32_##SFX + """ + vdata_a = self.load(self._data()) + vdata_a = self.sub(vdata_a, self.setall(0.5)) + vdata_b = self.mul(vdata_a, self.setall(-1.5)) + data_round = [round(x) for x in list(vdata_a) + list(vdata_b)] + vround = self.round_s32(vdata_a, vdata_b) + assert vround == data_round + +class _SIMD_FP(_Test_Utility): + """ + To test all float vector types at once + """ + def test_arithmetic_fused(self): + vdata_a, vdata_b, vdata_c = [self.load(self._data())] * 3 + vdata_cx2 = self.add(vdata_c, vdata_c) + # multiply and add, a*b + c + data_fma = self.load([a * b + c for a, b, c in zip(vdata_a, vdata_b, vdata_c)]) + fma = self.muladd(vdata_a, vdata_b, vdata_c) + assert fma == data_fma + # multiply and subtract, a*b - c + fms = self.mulsub(vdata_a, vdata_b, vdata_c) + data_fms = self.sub(data_fma, vdata_cx2) + assert fms == data_fms + # negate multiply and add, -(a*b) + c + nfma = self.nmuladd(vdata_a, vdata_b, vdata_c) + data_nfma = self.sub(vdata_cx2, data_fma) + assert nfma == data_nfma + # negate multiply and subtract, -(a*b) - c + nfms = self.nmulsub(vdata_a, vdata_b, vdata_c) + data_nfms = self.mul(data_fma, self.setall(-1)) + assert nfms == data_nfms + # multiply, add for odd elements and subtract even elements. + # (a * b) -+ c + fmas = list(self.muladdsub(vdata_a, vdata_b, vdata_c)) + assert fmas[0::2] == list(data_fms)[0::2] + assert fmas[1::2] == list(data_fma)[1::2] + + def test_abs(self): + pinf, ninf, nan = self._pinfinity(), self._ninfinity(), self._nan() + data = self._data() + vdata = self.load(self._data()) + + abs_cases = ((-0, 0), (ninf, pinf), (pinf, pinf), (nan, nan)) + for case, desired in abs_cases: + data_abs = [desired] * self.nlanes + vabs = self.abs(self.setall(case)) + assert vabs == pytest.approx(data_abs, nan_ok=True) + + vabs = self.abs(self.mul(vdata, self.setall(-1))) + assert vabs == data + + def test_sqrt(self): + pinf, ninf, nan = self._pinfinity(), self._ninfinity(), self._nan() + data = self._data() + vdata = self.load(self._data()) + + sqrt_cases = ((-0.0, -0.0), (0.0, 0.0), (-1.0, nan), (ninf, nan), (pinf, pinf)) + for case, desired in sqrt_cases: + data_sqrt = [desired] * self.nlanes + sqrt = self.sqrt(self.setall(case)) + assert sqrt == pytest.approx(data_sqrt, nan_ok=True) + + # load to truncate precision + data_sqrt = self.load([math.sqrt(x) for x in data]) + sqrt = self.sqrt(vdata) + assert sqrt == data_sqrt + + def test_square(self): + pinf, ninf, nan = self._pinfinity(), self._ninfinity(), self._nan() + data = self._data() + vdata = self.load(self._data()) + # square + square_cases = ((nan, nan), (pinf, pinf), (ninf, pinf)) + for case, desired in square_cases: + data_square = [desired] * self.nlanes + square = self.square(self.setall(case)) + assert square == pytest.approx(data_square, nan_ok=True) + + data_square = [x * x for x in data] + square = self.square(vdata) + assert square == data_square + + @pytest.mark.parametrize("intrin, func", [("ceil", math.ceil), + ("trunc", math.trunc), ("floor", math.floor), ("rint", round)]) + def test_rounding(self, intrin, func): + """ + Test intrinsics: + npyv_rint_##SFX + npyv_ceil_##SFX + npyv_trunc_##SFX + npyv_floor##SFX + """ + intrin_name = intrin + intrin = getattr(self, intrin) + pinf, ninf, nan = self._pinfinity(), self._ninfinity(), self._nan() + # special cases + round_cases = ((nan, nan), (pinf, pinf), (ninf, ninf)) + for case, desired in round_cases: + data_round = [desired] * self.nlanes + _round = intrin(self.setall(case)) + assert _round == pytest.approx(data_round, nan_ok=True) + + for x in range(0, 2**20, 256**2): + for w in (-1.05, -1.10, -1.15, 1.05, 1.10, 1.15): + data = self.load([(x + a) * w for a in range(self.nlanes)]) + data_round = [func(x) for x in data] + _round = intrin(data) + assert _round == data_round + + # test large numbers + for i in ( + 1.1529215045988576e+18, 4.6116860183954304e+18, + 5.902958103546122e+20, 2.3611832414184488e+21 + ): + x = self.setall(i) + y = intrin(x) + data_round = [func(n) for n in x] + assert y == data_round + + # signed zero + if intrin_name == "floor": + data_szero = (-0.0,) + else: + data_szero = (-0.0, -0.25, -0.30, -0.45, -0.5) + + for w in data_szero: + _round = self._to_unsigned(intrin(self.setall(w))) + data_round = self._to_unsigned(self.setall(-0.0)) + assert _round == data_round + + @pytest.mark.parametrize("intrin", [ + "max", "maxp", "maxn", "min", "minp", "minn" + ]) + def test_max_min(self, intrin): + """ + Test intrinsics: + npyv_max_##sfx + npyv_maxp_##sfx + npyv_maxn_##sfx + npyv_min_##sfx + npyv_minp_##sfx + npyv_minn_##sfx + npyv_reduce_max_##sfx + npyv_reduce_maxp_##sfx + npyv_reduce_maxn_##sfx + npyv_reduce_min_##sfx + npyv_reduce_minp_##sfx + npyv_reduce_minn_##sfx + """ + pinf, ninf, nan = self._pinfinity(), self._ninfinity(), self._nan() + chk_nan = {"xp": 1, "np": 1, "nn": 2, "xn": 2}.get(intrin[-2:], 0) + func = eval(intrin[:3]) + reduce_intrin = getattr(self, "reduce_" + intrin) + intrin = getattr(self, intrin) + hf_nlanes = self.nlanes // 2 + + cases = ( + ([0.0, -0.0], [-0.0, 0.0]), + ([10, -10], [10, -10]), + ([pinf, 10], [10, ninf]), + ([10, pinf], [ninf, 10]), + ([10, -10], [10, -10]), + ([-10, 10], [-10, 10]) + ) + for op1, op2 in cases: + vdata_a = self.load(op1 * hf_nlanes) + vdata_b = self.load(op2 * hf_nlanes) + data = func(vdata_a, vdata_b) + simd = intrin(vdata_a, vdata_b) + assert simd == data + data = func(vdata_a) + simd = reduce_intrin(vdata_a) + assert simd == data + + if not chk_nan: + return + if chk_nan == 1: + test_nan = lambda a, b: ( + b if math.isnan(a) else a if math.isnan(b) else b + ) + else: + test_nan = lambda a, b: ( + nan if math.isnan(a) or math.isnan(b) else b + ) + cases = ( + (nan, 10), + (10, nan), + (nan, pinf), + (pinf, nan), + (nan, nan) + ) + for op1, op2 in cases: + vdata_ab = self.load([op1, op2] * hf_nlanes) + data = test_nan(op1, op2) + simd = reduce_intrin(vdata_ab) + assert simd == pytest.approx(data, nan_ok=True) + vdata_a = self.setall(op1) + vdata_b = self.setall(op2) + data = [data] * self.nlanes + simd = intrin(vdata_a, vdata_b) + assert simd == pytest.approx(data, nan_ok=True) + + def test_reciprocal(self): + pinf, ninf, nan = self._pinfinity(), self._ninfinity(), self._nan() + data = self._data() + vdata = self.load(self._data()) + + recip_cases = ((nan, nan), (pinf, 0.0), (ninf, -0.0), (0.0, pinf), (-0.0, ninf)) + for case, desired in recip_cases: + data_recip = [desired] * self.nlanes + recip = self.recip(self.setall(case)) + assert recip == pytest.approx(data_recip, nan_ok=True) + + data_recip = self.load([1 / x for x in data]) # load to truncate precision + recip = self.recip(vdata) + assert recip == data_recip + + def test_special_cases(self): + """ + Compare Not NaN. Test intrinsics: + npyv_notnan_##SFX + """ + nnan = self.notnan(self.setall(self._nan())) + assert nnan == [0] * self.nlanes + + @pytest.mark.parametrize("intrin_name", [ + "rint", "trunc", "ceil", "floor" + ]) + def test_unary_invalid_fpexception(self, intrin_name): + intrin = getattr(self, intrin_name) + for d in [float("nan"), float("inf"), -float("inf")]: + v = self.setall(d) + clear_floatstatus() + intrin(v) + assert check_floatstatus(invalid=True) is False + + @pytest.mark.parametrize('py_comp,np_comp', [ + (operator.lt, "cmplt"), + (operator.le, "cmple"), + (operator.gt, "cmpgt"), + (operator.ge, "cmpge"), + (operator.eq, "cmpeq"), + (operator.ne, "cmpneq") + ]) + def test_comparison_with_nan(self, py_comp, np_comp): + pinf, ninf, nan = self._pinfinity(), self._ninfinity(), self._nan() + mask_true = self._true_mask() + + def to_bool(vector): + return [lane == mask_true for lane in vector] + + intrin = getattr(self, np_comp) + cmp_cases = ((0, nan), (nan, 0), (nan, nan), (pinf, nan), + (ninf, nan), (-0.0, +0.0)) + for case_operand1, case_operand2 in cmp_cases: + data_a = [case_operand1] * self.nlanes + data_b = [case_operand2] * self.nlanes + vdata_a = self.setall(case_operand1) + vdata_b = self.setall(case_operand2) + vcmp = to_bool(intrin(vdata_a, vdata_b)) + data_cmp = [py_comp(a, b) for a, b in zip(data_a, data_b)] + assert vcmp == data_cmp + + @pytest.mark.parametrize("intrin", ["any", "all"]) + @pytest.mark.parametrize("data", ( + [float("nan"), 0], + [0, float("nan")], + [float("nan"), 1], + [1, float("nan")], + [float("nan"), float("nan")], + [0.0, -0.0], + [-0.0, 0.0], + [1.0, -0.0] + )) + def test_operators_crosstest(self, intrin, data): + """ + Test intrinsics: + npyv_any_##SFX + npyv_all_##SFX + """ + data_a = self.load(data * self.nlanes) + func = eval(intrin) + intrin = getattr(self, intrin) + desired = func(data_a) + simd = intrin(data_a) + assert not not simd == desired + +class _SIMD_ALL(_Test_Utility): + """ + To test all vector types at once + """ + def test_memory_load(self): + data = self._data() + # unaligned load + load_data = self.load(data) + assert load_data == data + # aligned load + loada_data = self.loada(data) + assert loada_data == data + # stream load + loads_data = self.loads(data) + assert loads_data == data + # load lower part + loadl = self.loadl(data) + loadl_half = list(loadl)[:self.nlanes // 2] + data_half = data[:self.nlanes // 2] + assert loadl_half == data_half + assert loadl != data # detect overflow + + def test_memory_store(self): + data = self._data() + vdata = self.load(data) + # unaligned store + store = [0] * self.nlanes + self.store(store, vdata) + assert store == data + # aligned store + store_a = [0] * self.nlanes + self.storea(store_a, vdata) + assert store_a == data + # stream store + store_s = [0] * self.nlanes + self.stores(store_s, vdata) + assert store_s == data + # store lower part + store_l = [0] * self.nlanes + self.storel(store_l, vdata) + assert store_l[:self.nlanes // 2] == data[:self.nlanes // 2] + assert store_l != vdata # detect overflow + # store higher part + store_h = [0] * self.nlanes + self.storeh(store_h, vdata) + assert store_h[:self.nlanes // 2] == data[self.nlanes // 2:] + assert store_h != vdata # detect overflow + + @pytest.mark.parametrize("intrin, elsizes, scale, fill", [ + ("self.load_tillz, self.load_till", (32, 64), 1, [0xffff]), + ("self.load2_tillz, self.load2_till", (32, 64), 2, [0xffff, 0x7fff]), + ]) + def test_memory_partial_load(self, intrin, elsizes, scale, fill): + if self._scalar_size() not in elsizes: + return + npyv_load_tillz, npyv_load_till = eval(intrin) + data = self._data() + lanes = list(range(1, self.nlanes + 1)) + lanes += [self.nlanes**2, self.nlanes**4] # test out of range + for n in lanes: + load_till = npyv_load_till(data, n, *fill) + load_tillz = npyv_load_tillz(data, n) + n *= scale + data_till = data[:n] + fill * ((self.nlanes - n) // scale) + assert load_till == data_till + data_tillz = data[:n] + [0] * (self.nlanes - n) + assert load_tillz == data_tillz + + @pytest.mark.parametrize("intrin, elsizes, scale", [ + ("self.store_till", (32, 64), 1), + ("self.store2_till", (32, 64), 2), + ]) + def test_memory_partial_store(self, intrin, elsizes, scale): + if self._scalar_size() not in elsizes: + return + npyv_store_till = eval(intrin) + data = self._data() + data_rev = self._data(reverse=True) + vdata = self.load(data) + lanes = list(range(1, self.nlanes + 1)) + lanes += [self.nlanes**2, self.nlanes**4] + for n in lanes: + data_till = data_rev.copy() + data_till[:n * scale] = data[:n * scale] + store_till = self._data(reverse=True) + npyv_store_till(store_till, n, vdata) + assert store_till == data_till + + @pytest.mark.parametrize("intrin, elsizes, scale", [ + ("self.loadn", (32, 64), 1), + ("self.loadn2", (32, 64), 2), + ]) + def test_memory_noncont_load(self, intrin, elsizes, scale): + if self._scalar_size() not in elsizes: + return + npyv_loadn = eval(intrin) + for stride in range(-64, 64): + if stride < 0: + data = self._data(stride, -stride * self.nlanes) + data_stride = list(itertools.chain( + *zip(*[data[-i::stride] for i in range(scale, 0, -1)]) + )) + elif stride == 0: + data = self._data() + data_stride = data[0:scale] * (self.nlanes // scale) + else: + data = self._data(count=stride * self.nlanes) + data_stride = list(itertools.chain( + *zip(*[data[i::stride] for i in range(scale)])) + ) + data_stride = self.load(data_stride) # cast unsigned + loadn = npyv_loadn(data, stride) + assert loadn == data_stride + + @pytest.mark.parametrize("intrin, elsizes, scale, fill", [ + ("self.loadn_tillz, self.loadn_till", (32, 64), 1, [0xffff]), + ("self.loadn2_tillz, self.loadn2_till", (32, 64), 2, [0xffff, 0x7fff]), + ]) + def test_memory_noncont_partial_load(self, intrin, elsizes, scale, fill): + if self._scalar_size() not in elsizes: + return + npyv_loadn_tillz, npyv_loadn_till = eval(intrin) + lanes = list(range(1, self.nlanes + 1)) + lanes += [self.nlanes**2, self.nlanes**4] + for stride in range(-64, 64): + if stride < 0: + data = self._data(stride, -stride * self.nlanes) + data_stride = list(itertools.chain( + *zip(*[data[-i::stride] for i in range(scale, 0, -1)]) + )) + elif stride == 0: + data = self._data() + data_stride = data[0:scale] * (self.nlanes // scale) + else: + data = self._data(count=stride * self.nlanes) + data_stride = list(itertools.chain( + *zip(*[data[i::stride] for i in range(scale)]) + )) + data_stride = list(self.load(data_stride)) # cast unsigned + for n in lanes: + nscale = n * scale + llanes = self.nlanes - nscale + data_stride_till = ( + data_stride[:nscale] + fill * (llanes // scale) + ) + loadn_till = npyv_loadn_till(data, stride, n, *fill) + assert loadn_till == data_stride_till + data_stride_tillz = data_stride[:nscale] + [0] * llanes + loadn_tillz = npyv_loadn_tillz(data, stride, n) + assert loadn_tillz == data_stride_tillz + + @pytest.mark.parametrize("intrin, elsizes, scale", [ + ("self.storen", (32, 64), 1), + ("self.storen2", (32, 64), 2), + ]) + def test_memory_noncont_store(self, intrin, elsizes, scale): + if self._scalar_size() not in elsizes: + return + npyv_storen = eval(intrin) + data = self._data() + vdata = self.load(data) + hlanes = self.nlanes // scale + for stride in range(1, 64): + data_storen = [0xff] * stride * self.nlanes + for s in range(0, hlanes * stride, stride): + i = (s // stride) * scale + data_storen[s:s + scale] = data[i:i + scale] + storen = [0xff] * stride * self.nlanes + storen += [0x7f] * 64 + npyv_storen(storen, stride, vdata) + assert storen[:-64] == data_storen + assert storen[-64:] == [0x7f] * 64 # detect overflow + + for stride in range(-64, 0): + data_storen = [0xff] * -stride * self.nlanes + for s in range(0, hlanes * stride, stride): + i = (s // stride) * scale + data_storen[s - scale:s or None] = data[i:i + scale] + storen = [0x7f] * 64 + storen += [0xff] * -stride * self.nlanes + npyv_storen(storen, stride, vdata) + assert storen[64:] == data_storen + assert storen[:64] == [0x7f] * 64 # detect overflow + # stride 0 + data_storen = [0x7f] * self.nlanes + storen = data_storen.copy() + data_storen[0:scale] = data[-scale:] + npyv_storen(storen, 0, vdata) + assert storen == data_storen + + @pytest.mark.parametrize("intrin, elsizes, scale", [ + ("self.storen_till", (32, 64), 1), + ("self.storen2_till", (32, 64), 2), + ]) + def test_memory_noncont_partial_store(self, intrin, elsizes, scale): + if self._scalar_size() not in elsizes: + return + npyv_storen_till = eval(intrin) + data = self._data() + vdata = self.load(data) + lanes = list(range(1, self.nlanes + 1)) + lanes += [self.nlanes**2, self.nlanes**4] + hlanes = self.nlanes // scale + for stride in range(1, 64): + for n in lanes: + data_till = [0xff] * stride * self.nlanes + tdata = data[:n * scale] + [0xff] * (self.nlanes - n * scale) + for s in range(0, hlanes * stride, stride)[:n]: + i = (s // stride) * scale + data_till[s:s + scale] = tdata[i:i + scale] + storen_till = [0xff] * stride * self.nlanes + storen_till += [0x7f] * 64 + npyv_storen_till(storen_till, stride, n, vdata) + assert storen_till[:-64] == data_till + assert storen_till[-64:] == [0x7f] * 64 # detect overflow + + for stride in range(-64, 0): + for n in lanes: + data_till = [0xff] * -stride * self.nlanes + tdata = data[:n * scale] + [0xff] * (self.nlanes - n * scale) + for s in range(0, hlanes * stride, stride)[:n]: + i = (s // stride) * scale + data_till[s - scale:s or None] = tdata[i:i + scale] + storen_till = [0x7f] * 64 + storen_till += [0xff] * -stride * self.nlanes + npyv_storen_till(storen_till, stride, n, vdata) + assert storen_till[64:] == data_till + assert storen_till[:64] == [0x7f] * 64 # detect overflow + + # stride 0 + for n in lanes: + data_till = [0x7f] * self.nlanes + storen_till = data_till.copy() + data_till[0:scale] = data[:n * scale][-scale:] + npyv_storen_till(storen_till, 0, n, vdata) + assert storen_till == data_till + + @pytest.mark.parametrize("intrin, table_size, elsize", [ + ("self.lut32", 32, 32), + ("self.lut16", 16, 64) + ]) + def test_lut(self, intrin, table_size, elsize): + """ + Test lookup table intrinsics: + npyv_lut32_##sfx + npyv_lut16_##sfx + """ + if elsize != self._scalar_size(): + return + intrin = eval(intrin) + idx_itrin = getattr(self.npyv, f"setall_u{elsize}") + table = range(table_size) + for i in table: + broadi = self.setall(i) + idx = idx_itrin(i) + lut = intrin(table, idx) + assert lut == broadi + + def test_misc(self): + broadcast_zero = self.zero() + assert broadcast_zero == [0] * self.nlanes + for i in range(1, 10): + broadcasti = self.setall(i) + assert broadcasti == [i] * self.nlanes + + data_a, data_b = self._data(), self._data(reverse=True) + vdata_a, vdata_b = self.load(data_a), self.load(data_b) + + # py level of npyv_set_* don't support ignoring the extra specified lanes or + # fill non-specified lanes with zero. + vset = self.set(*data_a) + assert vset == data_a + # py level of npyv_setf_* don't support ignoring the extra specified lanes or + # fill non-specified lanes with the specified scalar. + vsetf = self.setf(10, *data_a) + assert vsetf == data_a + + # We're testing the sanity of _simd's type-vector, + # reinterpret* intrinsics itself are tested via compiler + # during the build of _simd module + sfxes = ["u8", "s8", "u16", "s16", "u32", "s32", "u64", "s64"] + if self.npyv.simd_f64: + sfxes.append("f64") + if self.npyv.simd_f32: + sfxes.append("f32") + for sfx in sfxes: + vec_name = getattr(self, "reinterpret_" + sfx)(vdata_a).__name__ + assert vec_name == "npyv_" + sfx + + # select & mask operations + select_a = self.select(self.cmpeq(self.zero(), self.zero()), vdata_a, vdata_b) + assert select_a == data_a + select_b = self.select(self.cmpneq(self.zero(), self.zero()), vdata_a, vdata_b) + assert select_b == data_b + + # test extract elements + assert self.extract0(vdata_b) == vdata_b[0] + + # cleanup intrinsic is only used with AVX for + # zeroing registers to avoid the AVX-SSE transition penalty, + # so nothing to test here + self.npyv.cleanup() + + def test_reorder(self): + data_a, data_b = self._data(), self._data(reverse=True) + vdata_a, vdata_b = self.load(data_a), self.load(data_b) + # lower half part + data_a_lo = data_a[:self.nlanes // 2] + data_b_lo = data_b[:self.nlanes // 2] + # higher half part + data_a_hi = data_a[self.nlanes // 2:] + data_b_hi = data_b[self.nlanes // 2:] + # combine two lower parts + combinel = self.combinel(vdata_a, vdata_b) + assert combinel == data_a_lo + data_b_lo + # combine two higher parts + combineh = self.combineh(vdata_a, vdata_b) + assert combineh == data_a_hi + data_b_hi + # combine x2 + combine = self.combine(vdata_a, vdata_b) + assert combine == (data_a_lo + data_b_lo, data_a_hi + data_b_hi) + + # zip(interleave) + data_zipl = self.load([ + v for p in zip(data_a_lo, data_b_lo) for v in p + ]) + data_ziph = self.load([ + v for p in zip(data_a_hi, data_b_hi) for v in p + ]) + vzip = self.zip(vdata_a, vdata_b) + assert vzip == (data_zipl, data_ziph) + vzip = [0] * self.nlanes * 2 + self._x2("store")(vzip, (vdata_a, vdata_b)) + assert vzip == list(data_zipl) + list(data_ziph) + + # unzip(deinterleave) + unzip = self.unzip(data_zipl, data_ziph) + assert unzip == (data_a, data_b) + unzip = self._x2("load")(list(data_zipl) + list(data_ziph)) + assert unzip == (data_a, data_b) + + def test_reorder_rev64(self): + # Reverse elements of each 64-bit lane + ssize = self._scalar_size() + if ssize == 64: + return + data_rev64 = [ + y for x in range(0, self.nlanes, 64 // ssize) + for y in reversed(range(x, x + 64 // ssize)) + ] + rev64 = self.rev64(self.load(range(self.nlanes))) + assert rev64 == data_rev64 + + def test_reorder_permi128(self): + """ + Test permuting elements for each 128-bit lane. + npyv_permi128_##sfx + """ + ssize = self._scalar_size() + if ssize < 32: + return + data = self.load(self._data()) + permn = 128 // ssize + permd = permn - 1 + nlane128 = self.nlanes // permn + shfl = [0, 1] if ssize == 64 else [0, 2, 4, 6] + for i in range(permn): + indices = [(i >> shf) & permd for shf in shfl] + vperm = self.permi128(data, *indices) + data_vperm = [ + data[j + (e & -permn)] + for e, j in enumerate(indices * nlane128) + ] + assert vperm == data_vperm + + @pytest.mark.parametrize('func, intrin', [ + (operator.lt, "cmplt"), + (operator.le, "cmple"), + (operator.gt, "cmpgt"), + (operator.ge, "cmpge"), + (operator.eq, "cmpeq") + ]) + def test_operators_comparison(self, func, intrin): + if self._is_fp(): + data_a = self._data() + else: + data_a = self._data(self._int_max() - self.nlanes) + data_b = self._data(self._int_min(), reverse=True) + vdata_a, vdata_b = self.load(data_a), self.load(data_b) + intrin = getattr(self, intrin) + + mask_true = self._true_mask() + + def to_bool(vector): + return [lane == mask_true for lane in vector] + + data_cmp = [func(a, b) for a, b in zip(data_a, data_b)] + cmp = to_bool(intrin(vdata_a, vdata_b)) + assert cmp == data_cmp + + def test_operators_logical(self): + if self._is_fp(): + data_a = self._data() + else: + data_a = self._data(self._int_max() - self.nlanes) + data_b = self._data(self._int_min(), reverse=True) + vdata_a, vdata_b = self.load(data_a), self.load(data_b) + + if self._is_fp(): + data_cast_a = self._to_unsigned(vdata_a) + data_cast_b = self._to_unsigned(vdata_b) + cast, cast_data = self._to_unsigned, self._to_unsigned + else: + data_cast_a, data_cast_b = data_a, data_b + cast, cast_data = lambda a: a, self.load + + data_xor = cast_data([a ^ b for a, b in zip(data_cast_a, data_cast_b)]) + vxor = cast(self.xor(vdata_a, vdata_b)) + assert vxor == data_xor + + data_or = cast_data([a | b for a, b in zip(data_cast_a, data_cast_b)]) + vor = cast(getattr(self, "or")(vdata_a, vdata_b)) + assert vor == data_or + + data_and = cast_data([a & b for a, b in zip(data_cast_a, data_cast_b)]) + vand = cast(getattr(self, "and")(vdata_a, vdata_b)) + assert vand == data_and + + data_not = cast_data([~a for a in data_cast_a]) + vnot = cast(getattr(self, "not")(vdata_a)) + assert vnot == data_not + + if self.sfx not in ("u8"): + return + data_andc = [a & ~b for a, b in zip(data_cast_a, data_cast_b)] + vandc = cast(self.andc(vdata_a, vdata_b)) + assert vandc == data_andc + + @pytest.mark.parametrize("intrin", ["any", "all"]) + @pytest.mark.parametrize("data", ( + [1, 2, 3, 4], + [-1, -2, -3, -4], + [0, 1, 2, 3, 4], + [0x7f, 0x7fff, 0x7fffffff, 0x7fffffffffffffff], + [0, -1, -2, -3, 4], + [0], + [1], + [-1] + )) + def test_operators_crosstest(self, intrin, data): + """ + Test intrinsics: + npyv_any_##SFX + npyv_all_##SFX + """ + data_a = self.load(data * self.nlanes) + func = eval(intrin) + intrin = getattr(self, intrin) + desired = func(data_a) + simd = intrin(data_a) + assert not not simd == desired + + def test_conversion_boolean(self): + bsfx = "b" + self.sfx[1:] + to_boolean = getattr(self.npyv, f"cvt_{bsfx}_{self.sfx}") + from_boolean = getattr(self.npyv, f"cvt_{self.sfx}_{bsfx}") + + false_vb = to_boolean(self.setall(0)) + true_vb = self.cmpeq(self.setall(0), self.setall(0)) + assert false_vb != true_vb + + false_vsfx = from_boolean(false_vb) + true_vsfx = from_boolean(true_vb) + assert false_vsfx != true_vsfx + + def test_conversion_expand(self): + """ + Test expand intrinsics: + npyv_expand_u16_u8 + npyv_expand_u32_u16 + """ + if self.sfx not in ("u8", "u16"): + return + totype = self.sfx[0] + str(int(self.sfx[1:]) * 2) + expand = getattr(self.npyv, f"expand_{totype}_{self.sfx}") + # close enough from the edge to detect any deviation + data = self._data(self._int_max() - self.nlanes) + vdata = self.load(data) + edata = expand(vdata) + # lower half part + data_lo = data[:self.nlanes // 2] + # higher half part + data_hi = data[self.nlanes // 2:] + assert edata == (data_lo, data_hi) + + def test_arithmetic_subadd(self): + if self._is_fp(): + data_a = self._data() + else: + data_a = self._data(self._int_max() - self.nlanes) + data_b = self._data(self._int_min(), reverse=True) + vdata_a, vdata_b = self.load(data_a), self.load(data_b) + + # non-saturated + data_add = self.load([a + b for a, b in zip(data_a, data_b)]) # load to cast + add = self.add(vdata_a, vdata_b) + assert add == data_add + data_sub = self.load([a - b for a, b in zip(data_a, data_b)]) + sub = self.sub(vdata_a, vdata_b) + assert sub == data_sub + + def test_arithmetic_mul(self): + if self.sfx in ("u64", "s64"): + return + + if self._is_fp(): + data_a = self._data() + else: + data_a = self._data(self._int_max() - self.nlanes) + data_b = self._data(self._int_min(), reverse=True) + vdata_a, vdata_b = self.load(data_a), self.load(data_b) + + data_mul = self.load([a * b for a, b in zip(data_a, data_b)]) + mul = self.mul(vdata_a, vdata_b) + assert mul == data_mul + + def test_arithmetic_div(self): + if not self._is_fp(): + return + + data_a, data_b = self._data(), self._data(reverse=True) + vdata_a, vdata_b = self.load(data_a), self.load(data_b) + + # load to truncate f64 to precision of f32 + data_div = self.load([a / b for a, b in zip(data_a, data_b)]) + div = self.div(vdata_a, vdata_b) + assert div == data_div + + def test_arithmetic_intdiv(self): + """ + Test integer division intrinsics: + npyv_divisor_##sfx + npyv_divc_##sfx + """ + if self._is_fp(): + return + + int_min = self._int_min() + + def trunc_div(a, d): + """ + Divide towards zero works with large integers > 2^53, + and wrap around overflow similar to what C does. + """ + if d == -1 and a == int_min: + return a + sign_a, sign_d = a < 0, d < 0 + if a == 0 or sign_a == sign_d: + return a // d + return (a + sign_d - sign_a) // d + 1 + + data = [1, -int_min] # to test overflow + data += range(0, 2**8, 2**5) + data += range(0, 2**8, 2**5 - 1) + bsize = self._scalar_size() + if bsize > 8: + data += range(2**8, 2**16, 2**13) + data += range(2**8, 2**16, 2**13 - 1) + if bsize > 16: + data += range(2**16, 2**32, 2**29) + data += range(2**16, 2**32, 2**29 - 1) + if bsize > 32: + data += range(2**32, 2**64, 2**61) + data += range(2**32, 2**64, 2**61 - 1) + # negate + data += [-x for x in data] + for dividend, divisor in itertools.product(data, data): + divisor = self.setall(divisor)[0] # cast + if divisor == 0: + continue + dividend = self.load(self._data(dividend)) + data_divc = [trunc_div(a, divisor) for a in dividend] + divisor_parms = self.divisor(divisor) + divc = self.divc(dividend, divisor_parms) + assert divc == data_divc + + def test_arithmetic_reduce_sum(self): + """ + Test reduce sum intrinsics: + npyv_sum_##sfx + """ + if self.sfx not in ("u32", "u64", "f32", "f64"): + return + # reduce sum + data = self._data() + vdata = self.load(data) + + data_sum = sum(data) + vsum = self.sum(vdata) + assert vsum == data_sum + + def test_arithmetic_reduce_sumup(self): + """ + Test extend reduce sum intrinsics: + npyv_sumup_##sfx + """ + if self.sfx not in ("u8", "u16"): + return + rdata = (0, self.nlanes, self._int_min(), self._int_max() - self.nlanes) + for r in rdata: + data = self._data(r) + vdata = self.load(data) + data_sum = sum(data) + vsum = self.sumup(vdata) + assert vsum == data_sum + + def test_mask_conditional(self): + """ + Conditional addition and subtraction for all supported data types. + Test intrinsics: + npyv_ifadd_##SFX, npyv_ifsub_##SFX + """ + vdata_a = self.load(self._data()) + vdata_b = self.load(self._data(reverse=True)) + true_mask = self.cmpeq(self.zero(), self.zero()) + false_mask = self.cmpneq(self.zero(), self.zero()) + + data_sub = self.sub(vdata_b, vdata_a) + ifsub = self.ifsub(true_mask, vdata_b, vdata_a, vdata_b) + assert ifsub == data_sub + ifsub = self.ifsub(false_mask, vdata_a, vdata_b, vdata_b) + assert ifsub == vdata_b + + data_add = self.add(vdata_b, vdata_a) + ifadd = self.ifadd(true_mask, vdata_b, vdata_a, vdata_b) + assert ifadd == data_add + ifadd = self.ifadd(false_mask, vdata_a, vdata_b, vdata_b) + assert ifadd == vdata_b + + if not self._is_fp(): + return + data_div = self.div(vdata_b, vdata_a) + ifdiv = self.ifdiv(true_mask, vdata_b, vdata_a, vdata_b) + assert ifdiv == data_div + ifdivz = self.ifdivz(true_mask, vdata_b, vdata_a) + assert ifdivz == data_div + ifdiv = self.ifdiv(false_mask, vdata_a, vdata_b, vdata_b) + assert ifdiv == vdata_b + ifdivz = self.ifdivz(false_mask, vdata_a, vdata_b) + assert ifdivz == self.zero() + + +bool_sfx = ("b8", "b16", "b32", "b64") +int_sfx = ("u8", "s8", "u16", "s16", "u32", "s32", "u64", "s64") +fp_sfx = ("f32", "f64") +all_sfx = int_sfx + fp_sfx +tests_registry = { + bool_sfx: _SIMD_BOOL, + int_sfx: _SIMD_INT, + fp_sfx: _SIMD_FP, + ("f32",): _SIMD_FP32, + ("f64",): _SIMD_FP64, + all_sfx: _SIMD_ALL +} +for target_name, npyv in targets.items(): + simd_width = npyv.simd if npyv else '' + pretty_name = target_name.split('__') # multi-target separator + if len(pretty_name) > 1: + # multi-target + pretty_name = f"({' '.join(pretty_name)})" + else: + pretty_name = pretty_name[0] + + skip = "" + skip_sfx = {} + if not npyv: + skip = f"target '{pretty_name}' isn't supported by current machine" + elif not npyv.simd: + skip = f"target '{pretty_name}' isn't supported by NPYV" + else: + if not npyv.simd_f32: + skip_sfx["f32"] = f"target '{pretty_name}' "\ + "doesn't support single-precision" + if not npyv.simd_f64: + skip_sfx["f64"] = f"target '{pretty_name}' doesn't"\ + "support double-precision" + + for sfxes, cls in tests_registry.items(): + for sfx in sfxes: + skip_m = skip_sfx.get(sfx, skip) + inhr = (cls,) + attr = {"npyv": targets[target_name], "sfx": sfx, + "target_name": target_name} + type_name = f"Test{cls.__name__}_{simd_width}_{target_name}_{sfx}" + tcls = type(type_name, inhr, attr) + if skip_m: + pytest.mark.skip(reason=skip_m)(tcls) + globals()[tcls.__name__] = tcls diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_simd_module.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_simd_module.py new file mode 100644 index 0000000000000000000000000000000000000000..3de1596aa10a69d98d520921ad0d6b877652e8b5 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_simd_module.py @@ -0,0 +1,105 @@ +import pytest + +from numpy._core._simd import targets + +""" +This testing unit only for checking the sanity of common functionality, +therefore all we need is just to take one submodule that represents any +of enabled SIMD extensions to run the test on it and the second submodule +required to run only one check related to the possibility of mixing +the data types among each submodule. +""" +npyvs = [npyv_mod for npyv_mod in targets.values() if npyv_mod and npyv_mod.simd] +npyv, npyv2 = (npyvs + [None, None])[:2] + +unsigned_sfx = ["u8", "u16", "u32", "u64"] +signed_sfx = ["s8", "s16", "s32", "s64"] +fp_sfx = [] +if npyv and npyv.simd_f32: + fp_sfx.append("f32") +if npyv and npyv.simd_f64: + fp_sfx.append("f64") + +int_sfx = unsigned_sfx + signed_sfx +all_sfx = unsigned_sfx + int_sfx + +@pytest.mark.skipif(not npyv, + reason="could not find any SIMD extension with NPYV support") +class Test_SIMD_MODULE: + + @pytest.mark.parametrize('sfx', all_sfx) + def test_num_lanes(self, sfx): + nlanes = getattr(npyv, "nlanes_" + sfx) + vector = getattr(npyv, "setall_" + sfx)(1) + assert len(vector) == nlanes + + @pytest.mark.parametrize('sfx', all_sfx) + def test_type_name(self, sfx): + vector = getattr(npyv, "setall_" + sfx)(1) + assert vector.__name__ == "npyv_" + sfx + + def test_raises(self): + a, b = [npyv.setall_u32(1)] * 2 + for sfx in all_sfx: + vcb = lambda intrin: getattr(npyv, f"{intrin}_{sfx}") + pytest.raises(TypeError, vcb("add"), a) + pytest.raises(TypeError, vcb("add"), a, b, a) + pytest.raises(TypeError, vcb("setall")) + pytest.raises(TypeError, vcb("setall"), [1]) + pytest.raises(TypeError, vcb("load"), 1) + pytest.raises(ValueError, vcb("load"), [1]) + value = getattr(npyv, f"reinterpret_{sfx}_u32")(a) + pytest.raises(ValueError, vcb("store"), [1], value) + + @pytest.mark.skipif(not npyv2, reason=( + "could not find a second SIMD extension with NPYV support" + )) + def test_nomix(self): + # mix among submodules isn't allowed + a = npyv.setall_u32(1) + a2 = npyv2.setall_u32(1) + pytest.raises(TypeError, npyv.add_u32, a2, a2) + pytest.raises(TypeError, npyv2.add_u32, a, a) + + @pytest.mark.parametrize('sfx', unsigned_sfx) + def test_unsigned_overflow(self, sfx): + nlanes = getattr(npyv, "nlanes_" + sfx) + maxu = (1 << int(sfx[1:])) - 1 + maxu_72 = (1 << 72) - 1 + lane = getattr(npyv, "setall_" + sfx)(maxu_72)[0] + assert lane == maxu + lanes = getattr(npyv, "load_" + sfx)([maxu_72] * nlanes) + assert lanes == [maxu] * nlanes + lane = getattr(npyv, "setall_" + sfx)(-1)[0] + assert lane == maxu + lanes = getattr(npyv, "load_" + sfx)([-1] * nlanes) + assert lanes == [maxu] * nlanes + + @pytest.mark.parametrize('sfx', signed_sfx) + def test_signed_overflow(self, sfx): + nlanes = getattr(npyv, "nlanes_" + sfx) + maxs_72 = (1 << 71) - 1 + lane = getattr(npyv, "setall_" + sfx)(maxs_72)[0] + assert lane == -1 + lanes = getattr(npyv, "load_" + sfx)([maxs_72] * nlanes) + assert lanes == [-1] * nlanes + mins_72 = -1 << 71 + lane = getattr(npyv, "setall_" + sfx)(mins_72)[0] + assert lane == 0 + lanes = getattr(npyv, "load_" + sfx)([mins_72] * nlanes) + assert lanes == [0] * nlanes + + def test_truncate_f32(self): + if not npyv.simd_f32: + pytest.skip("F32 isn't support by the SIMD extension") + f32 = npyv.setall_f32(0.1)[0] + assert f32 != 0.1 + assert round(f32, 1) == 0.1 + + def test_compare(self): + data_range = range(npyv.nlanes_u32) + vdata = npyv.load_u32(data_range) + assert vdata == list(data_range) + assert vdata == tuple(data_range) + for i in data_range: + assert vdata[i] == data_range[i] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_stringdtype.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_stringdtype.py new file mode 100644 index 0000000000000000000000000000000000000000..492894087aa91b55ca75b3c5e33ab92bd42e54e9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_stringdtype.py @@ -0,0 +1,1855 @@ +import copy +import itertools +import os +import pickle +import string +import sys +import tempfile + +import pytest + +import numpy as np +from numpy._core.tests._natype import pd_NA +from numpy.dtypes import StringDType +from numpy.testing import IS_PYPY, assert_array_equal + + +def random_unicode_string_list(): + """Returns an array of 10 100-character strings containing random text""" + chars = list(string.ascii_letters + string.digits) + chars = np.array(chars, dtype="U1") + ret = np.random.choice(chars, size=100 * 10, replace=True) + return ret.view("U100") + + +def get_dtype(na_object, coerce=True): + """Helper to work around pd_NA boolean behavior""" + # explicit is check for pd_NA because != with pd_NA returns pd_NA + if na_object is pd_NA or na_object != "unset": + return np.dtypes.StringDType(na_object=na_object, coerce=coerce) + else: + return np.dtypes.StringDType(coerce=coerce) + + +@pytest.fixture(params=[True, False]) +def coerce(request): + """Coerce input to strings or raise an error for non-string input""" + return request.param + + +@pytest.fixture( + params=["unset", None, pd_NA, np.nan, float("nan"), "__nan__"], + ids=["unset", "None", "pandas.NA", "np.nan", "float('nan')", "string nan"], +) +def na_object(request): + """Possible values for the missing data sentinel""" + return request.param + + +@pytest.fixture() +def dtype(na_object, coerce): + """Cartesian project of missing data sentinel and string coercion options""" + return get_dtype(na_object, coerce) + +@pytest.fixture +def string_list(): + """Mix of short and long strings, some with unicode, some without""" + return ["abc", "def", "ghi" * 10, "A¢☃€ 😊" * 100, "Abc" * 1000, "DEF"] + + +@pytest.fixture(params=[True, False]) +def coerce2(request): + """Second copy of the coerce fixture for tests that need two instances""" + return request.param + + +@pytest.fixture( + params=["unset", None, pd_NA, np.nan, float("nan"), "__nan__"], + ids=["unset", "None", "pandas.NA", "np.nan", "float('nan')", "string nan"], +) +def na_object2(request): + """Second copy of the na_object fixture for tests that need two instances""" + return request.param + + +@pytest.fixture() +def dtype2(na_object2, coerce2): + """Second copy of the dtype fixture for tests that need two instances""" + # explicit is check for pd_NA because != with pd_NA returns pd_NA + if na_object2 is pd_NA or na_object2 != "unset": + return StringDType(na_object=na_object2, coerce=coerce2) + else: + return StringDType(coerce=coerce2) + + +def test_dtype_creation(): + hashes = set() + dt = StringDType() + assert not hasattr(dt, "na_object") and dt.coerce is True + hashes.add(hash(dt)) + + dt = StringDType(na_object=None) + assert dt.na_object is None and dt.coerce is True + hashes.add(hash(dt)) + + dt = StringDType(coerce=False) + assert not hasattr(dt, "na_object") and dt.coerce is False + hashes.add(hash(dt)) + + dt = StringDType(na_object=None, coerce=False) + assert dt.na_object is None and dt.coerce is False + hashes.add(hash(dt)) + + assert len(hashes) == 4 + + dt = np.dtype("T") + assert dt == StringDType() + assert dt.kind == "T" + assert dt.char == "T" + + hashes.add(hash(dt)) + assert len(hashes) == 4 + + +def test_dtype_equality(dtype): + assert dtype == dtype + for ch in "SU": + assert dtype != np.dtype(ch) + assert dtype != np.dtype(f"{ch}8") + + +def test_dtype_repr(dtype): + if not hasattr(dtype, "na_object") and dtype.coerce: + assert repr(dtype) == "StringDType()" + elif dtype.coerce: + assert repr(dtype) == f"StringDType(na_object={dtype.na_object!r})" + elif not hasattr(dtype, "na_object"): + assert repr(dtype) == "StringDType(coerce=False)" + else: + assert ( + repr(dtype) + == f"StringDType(na_object={dtype.na_object!r}, coerce=False)" + ) + + +def test_create_with_na(dtype): + if not hasattr(dtype, "na_object"): + pytest.skip("does not have an na object") + na_val = dtype.na_object + string_list = ["hello", na_val, "world"] + arr = np.array(string_list, dtype=dtype) + assert str(arr) == "[" + " ".join([repr(s) for s in string_list]) + "]" + assert arr[1] is dtype.na_object + + +@pytest.mark.parametrize("i", list(range(5))) +def test_set_replace_na(i): + # Test strings of various lengths can be set to NaN and then replaced. + s_empty = "" + s_short = "0123456789" + s_medium = "abcdefghijklmnopqrstuvwxyz" + s_long = "-=+" * 100 + strings = [s_medium, s_empty, s_short, s_medium, s_long] + a = np.array(strings, StringDType(na_object=np.nan)) + for s in [a[i], s_medium + s_short, s_short, s_empty, s_long]: + a[i] = np.nan + assert np.isnan(a[i]) + a[i] = s + assert a[i] == s + assert_array_equal(a, strings[:i] + [s] + strings[i + 1:]) + + +def test_null_roundtripping(): + data = ["hello\0world", "ABC\0DEF\0\0"] + arr = np.array(data, dtype="T") + assert data[0] == arr[0] + assert data[1] == arr[1] + + +def test_string_too_large_error(): + arr = np.array(["a", "b", "c"], dtype=StringDType()) + with pytest.raises(OverflowError): + arr * (sys.maxsize + 1) + + +@pytest.mark.parametrize( + "data", + [ + ["abc", "def", "ghi"], + ["🤣", "📵", "😰"], + ["🚜", "🙃", "😾"], + ["😹", "🚠", "🚌"], + ], +) +def test_array_creation_utf8(dtype, data): + arr = np.array(data, dtype=dtype) + assert str(arr) == "[" + " ".join(["'" + str(d) + "'" for d in data]) + "]" + assert arr.dtype == dtype + + +@pytest.mark.parametrize( + "data", + [ + [1, 2, 3], + [b"abc", b"def", b"ghi"], + [object, object, object], + ], +) +def test_scalars_string_conversion(data, dtype): + try: + str_vals = [str(d.decode('utf-8')) for d in data] + except AttributeError: + str_vals = [str(d) for d in data] + if dtype.coerce: + assert_array_equal( + np.array(data, dtype=dtype), + np.array(str_vals, dtype=dtype), + ) + else: + with pytest.raises(ValueError): + np.array(data, dtype=dtype) + + +@pytest.mark.parametrize( + ("strings"), + [ + ["this", "is", "an", "array"], + ["€", "", "😊"], + ["A¢☃€ 😊", " A☃€¢😊", "☃€😊 A¢", "😊☃A¢ €"], + ], +) +def test_self_casts(dtype, dtype2, strings): + if hasattr(dtype, "na_object"): + strings = strings + [dtype.na_object] + elif hasattr(dtype2, "na_object"): + strings = strings + [""] + arr = np.array(strings, dtype=dtype) + newarr = arr.astype(dtype2) + + if hasattr(dtype, "na_object") and not hasattr(dtype2, "na_object"): + assert newarr[-1] == str(dtype.na_object) + with pytest.raises(TypeError): + arr.astype(dtype2, casting="safe") + elif hasattr(dtype, "na_object") and hasattr(dtype2, "na_object"): + assert newarr[-1] is dtype2.na_object + arr.astype(dtype2, casting="safe") + elif hasattr(dtype2, "na_object"): + assert newarr[-1] == "" + arr.astype(dtype2, casting="safe") + else: + arr.astype(dtype2, casting="safe") + + if hasattr(dtype, "na_object") and hasattr(dtype2, "na_object"): + na1 = dtype.na_object + na2 = dtype2.na_object + if (na1 is not na2 and + # check for pd_NA first because bool(pd_NA) is an error + ((na1 is pd_NA or na2 is pd_NA) or + # the second check is a NaN check, spelled this way + # to avoid errors from math.isnan and np.isnan + (na1 != na2 and not (na1 != na1 and na2 != na2)))): + with pytest.raises(TypeError): + arr[:-1] == newarr[:-1] + return + assert_array_equal(arr[:-1], newarr[:-1]) + + +@pytest.mark.parametrize( + ("strings"), + [ + ["this", "is", "an", "array"], + ["€", "", "😊"], + ["A¢☃€ 😊", " A☃€¢😊", "☃€😊 A¢", "😊☃A¢ €"], + ], +) +class TestStringLikeCasts: + def test_unicode_casts(self, dtype, strings): + arr = np.array(strings, dtype=np.str_).astype(dtype) + expected = np.array(strings, dtype=dtype) + assert_array_equal(arr, expected) + + arr_as_U8 = expected.astype("U8") + assert_array_equal(arr_as_U8, np.array(strings, dtype="U8")) + assert_array_equal(arr_as_U8.astype(dtype), arr) + arr_as_U3 = expected.astype("U3") + assert_array_equal(arr_as_U3, np.array(strings, dtype="U3")) + assert_array_equal( + arr_as_U3.astype(dtype), + np.array([s[:3] for s in strings], dtype=dtype), + ) + + def test_void_casts(self, dtype, strings): + sarr = np.array(strings, dtype=dtype) + utf8_bytes = [s.encode("utf-8") for s in strings] + void_dtype = f"V{max(len(s) for s in utf8_bytes)}" + varr = np.array(utf8_bytes, dtype=void_dtype) + assert_array_equal(varr, sarr.astype(void_dtype)) + assert_array_equal(varr.astype(dtype), sarr) + + def test_bytes_casts(self, dtype, strings): + sarr = np.array(strings, dtype=dtype) + try: + utf8_bytes = [s.encode("ascii") for s in strings] + bytes_dtype = f"S{max(len(s) for s in utf8_bytes)}" + barr = np.array(utf8_bytes, dtype=bytes_dtype) + assert_array_equal(barr, sarr.astype(bytes_dtype)) + assert_array_equal(barr.astype(dtype), sarr) + if dtype.coerce: + barr = np.array(utf8_bytes, dtype=dtype) + assert_array_equal(barr, sarr) + barr = np.array(utf8_bytes, dtype="O") + assert_array_equal(barr.astype(dtype), sarr) + else: + with pytest.raises(ValueError): + np.array(utf8_bytes, dtype=dtype) + except UnicodeEncodeError: + with pytest.raises(UnicodeEncodeError): + sarr.astype("S20") + + +def test_additional_unicode_cast(dtype): + string_list = random_unicode_string_list() + arr = np.array(string_list, dtype=dtype) + # test that this short-circuits correctly + assert_array_equal(arr, arr.astype(arr.dtype)) + # tests the casts via the comparison promoter + assert_array_equal(arr, arr.astype(string_list.dtype)) + + +def test_insert_scalar(dtype, string_list): + """Test that inserting a scalar works.""" + arr = np.array(string_list, dtype=dtype) + scalar_instance = "what" + arr[1] = scalar_instance + assert_array_equal( + arr, + np.array(string_list[:1] + ["what"] + string_list[2:], dtype=dtype), + ) + + +comparison_operators = [ + np.equal, + np.not_equal, + np.greater, + np.greater_equal, + np.less, + np.less_equal, +] + + +@pytest.mark.parametrize("op", comparison_operators) +@pytest.mark.parametrize("o_dtype", [np.str_, object, StringDType()]) +def test_comparisons(string_list, dtype, op, o_dtype): + sarr = np.array(string_list, dtype=dtype) + oarr = np.array(string_list, dtype=o_dtype) + + # test that comparison operators work + res = op(sarr, sarr) + ores = op(oarr, oarr) + # test that promotion works as well + orres = op(sarr, oarr) + olres = op(oarr, sarr) + + assert_array_equal(res, ores) + assert_array_equal(res, orres) + assert_array_equal(res, olres) + + # test we get the correct answer for unequal length strings + sarr2 = np.array([s + "2" for s in string_list], dtype=dtype) + oarr2 = np.array([s + "2" for s in string_list], dtype=o_dtype) + + res = op(sarr, sarr2) + ores = op(oarr, oarr2) + olres = op(oarr, sarr2) + orres = op(sarr, oarr2) + + assert_array_equal(res, ores) + assert_array_equal(res, olres) + assert_array_equal(res, orres) + + res = op(sarr2, sarr) + ores = op(oarr2, oarr) + olres = op(oarr2, sarr) + orres = op(sarr2, oarr) + + assert_array_equal(res, ores) + assert_array_equal(res, olres) + assert_array_equal(res, orres) + + +def test_isnan(dtype, string_list): + if not hasattr(dtype, "na_object"): + pytest.skip("no na support") + sarr = np.array(string_list + [dtype.na_object], dtype=dtype) + is_nan = isinstance(dtype.na_object, float) and np.isnan(dtype.na_object) + bool_errors = 0 + try: + bool(dtype.na_object) + except TypeError: + bool_errors = 1 + if is_nan or bool_errors: + # isnan is only true when na_object is a NaN + assert_array_equal( + np.isnan(sarr), + np.array([0] * len(string_list) + [1], dtype=np.bool), + ) + else: + assert not np.any(np.isnan(sarr)) + + +def test_pickle(dtype, string_list): + arr = np.array(string_list, dtype=dtype) + + with tempfile.NamedTemporaryFile("wb", delete=False) as f: + pickle.dump([arr, dtype], f) + + with open(f.name, "rb") as f: + res = pickle.load(f) + + assert_array_equal(res[0], arr) + assert res[1] == dtype + + os.remove(f.name) + + +def test_stdlib_copy(dtype, string_list): + arr = np.array(string_list, dtype=dtype) + + assert_array_equal(copy.copy(arr), arr) + assert_array_equal(copy.deepcopy(arr), arr) + + +@pytest.mark.parametrize( + "strings", + [ + ["left", "right", "leftovers", "righty", "up", "down"], + [ + "left" * 10, + "right" * 10, + "leftovers" * 10, + "righty" * 10, + "up" * 10, + ], + ["🤣🤣", "🤣", "📵", "😰"], + ["🚜", "🙃", "😾"], + ["😹", "🚠", "🚌"], + ["A¢☃€ 😊", " A☃€¢😊", "☃€😊 A¢", "😊☃A¢ €"], + ], +) +def test_sort(dtype, strings): + """Test that sorting matches python's internal sorting.""" + + def test_sort(strings, arr_sorted): + arr = np.array(strings, dtype=dtype) + na_object = getattr(arr.dtype, "na_object", "") + if na_object is None and None in strings: + with pytest.raises( + ValueError, + match="Cannot compare null that is not a nan-like value", + ): + np.argsort(arr) + argsorted = None + elif na_object is pd_NA or na_object != '': + argsorted = None + else: + argsorted = np.argsort(arr) + np.random.default_rng().shuffle(arr) + if na_object is None and None in strings: + with pytest.raises( + ValueError, + match="Cannot compare null that is not a nan-like value", + ): + arr.sort() + else: + arr.sort() + assert np.array_equal(arr, arr_sorted, equal_nan=True) + if argsorted is not None: + assert np.array_equal(argsorted, np.argsort(strings)) + + # make a copy so we don't mutate the lists in the fixture + strings = strings.copy() + arr_sorted = np.array(sorted(strings), dtype=dtype) + test_sort(strings, arr_sorted) + + if not hasattr(dtype, "na_object"): + return + + # make sure NAs get sorted to the end of the array and string NAs get + # sorted like normal strings + strings.insert(0, dtype.na_object) + strings.insert(2, dtype.na_object) + # can't use append because doing that with NA converts + # the result to object dtype + if not isinstance(dtype.na_object, str): + arr_sorted = np.array( + arr_sorted.tolist() + [dtype.na_object, dtype.na_object], + dtype=dtype, + ) + else: + arr_sorted = np.array(sorted(strings), dtype=dtype) + + test_sort(strings, arr_sorted) + + +@pytest.mark.parametrize( + "strings", + [ + ["A¢☃€ 😊", " A☃€¢😊", "☃€😊 A¢", "😊☃A¢ €"], + ["A¢☃€ 😊", "", " ", " "], + ["", "a", "😸", "ááðfáíóåéë"], + ], +) +def test_nonzero(strings, na_object): + dtype = get_dtype(na_object) + arr = np.array(strings, dtype=dtype) + is_nonzero = np.array( + [i for i, item in enumerate(strings) if len(item) != 0]) + assert_array_equal(arr.nonzero()[0], is_nonzero) + + if na_object is not pd_NA and na_object == 'unset': + return + + strings_with_na = np.array(strings + [na_object], dtype=dtype) + is_nan = np.isnan(np.array([dtype.na_object], dtype=dtype))[0] + + if is_nan: + assert strings_with_na.nonzero()[0][-1] == 4 + else: + assert strings_with_na.nonzero()[0][-1] == 3 + + # check that the casting to bool and nonzero give consistent results + assert_array_equal(strings_with_na[strings_with_na.nonzero()], + strings_with_na[strings_with_na.astype(bool)]) + + +def test_where(string_list, na_object): + dtype = get_dtype(na_object) + a = np.array(string_list, dtype=dtype) + b = a[::-1] + res = np.where([True, False, True, False, True, False], a, b) + assert_array_equal(res, [a[0], b[1], a[2], b[3], a[4], b[5]]) + + +def test_fancy_indexing(string_list): + sarr = np.array(string_list, dtype="T") + assert_array_equal(sarr, sarr[np.arange(sarr.shape[0])]) + + inds = [ + [True, True], + [0, 1], + ..., + np.array([0, 1], dtype='uint8'), + ] + + lops = [ + ['a' * 25, 'b' * 25], + ['', ''], + ['hello', 'world'], + ['hello', 'world' * 25], + ] + + # see gh-27003 and gh-27053 + for ind in inds: + for lop in lops: + a = np.array(lop, dtype="T") + assert_array_equal(a[ind], a) + rop = ['d' * 25, 'e' * 25] + for b in [rop, np.array(rop, dtype="T")]: + a[ind] = b + assert_array_equal(a, b) + assert a[0] == 'd' * 25 + + # see gh-29279 + data = [ + ["AAAAAAAAAAAAAAAAA"], + ["BBBBBBBBBBBBBBBBBBBBBBBBBBBBB"], + ["CCCCCCCCCCCCCCCCC"], + ["DDDDDDDDDDDDDDDDD"], + ] + sarr = np.array(data, dtype=np.dtypes.StringDType()) + uarr = np.array(data, dtype="U30") + for ind in [[0], [1], [2], [3], [[0, 0]], [[1, 1, 3]], [[1, 1]]]: + assert_array_equal(sarr[ind], uarr[ind]) + + +def test_flatiter_indexing(): + # see gh-29659 + arr = np.array(['hello', 'world'], dtype='T') + arr.flat[:] = 9223372036854775 + assert_array_equal(arr, np.array([9223372036854775] * 2, dtype='T')) + + +def test_creation_functions(): + assert_array_equal(np.zeros(3, dtype="T"), ["", "", ""]) + assert_array_equal(np.empty(3, dtype="T"), ["", "", ""]) + + assert np.zeros(3, dtype="T")[0] == "" + assert np.empty(3, dtype="T")[0] == "" + + +def test_concatenate(string_list): + sarr = np.array(string_list, dtype="T") + sarr_cat = np.array(string_list + string_list, dtype="T") + + assert_array_equal(np.concatenate([sarr], axis=0), sarr) + + +def test_resize_method(string_list): + sarr = np.array(string_list, dtype="T") + if IS_PYPY: + sarr.resize(len(string_list) + 3, refcheck=False) + else: + sarr.resize(len(string_list) + 3) + assert_array_equal(sarr, np.array(string_list + [''] * 3, dtype="T")) + + +def test_create_with_copy_none(string_list): + arr = np.array(string_list, dtype=StringDType()) + # create another stringdtype array with an arena that has a different + # in-memory layout than the first array + arr_rev = np.array(string_list[::-1], dtype=StringDType()) + + # this should create a copy and the resulting array + # shouldn't share an allocator or arena with arr_rev, despite + # explicitly passing arr_rev.dtype + arr_copy = np.array(arr, copy=None, dtype=arr_rev.dtype) + np.testing.assert_array_equal(arr, arr_copy) + assert arr_copy.base is None + + with pytest.raises(ValueError, match="Unable to avoid copy"): + np.array(arr, copy=False, dtype=arr_rev.dtype) + + # because we're using arr's dtype instance, the view is safe + arr_view = np.array(arr, copy=None, dtype=arr.dtype) + np.testing.assert_array_equal(arr, arr) + np.testing.assert_array_equal(arr_view[::-1], arr_rev) + assert arr_view is arr + + +def test_astype_copy_false(): + orig_dt = StringDType() + arr = np.array(["hello", "world"], dtype=StringDType()) + assert not arr.astype(StringDType(coerce=False), copy=False).dtype.coerce + + assert arr.astype(orig_dt, copy=False).dtype is orig_dt + +@pytest.mark.parametrize( + "strings", + [ + ["left", "right", "leftovers", "righty", "up", "down"], + ["🤣🤣", "🤣", "📵", "😰"], + ["🚜", "🙃", "😾"], + ["😹", "🚠", "🚌"], + ["A¢☃€ 😊", " A☃€¢😊", "☃€😊 A¢", "😊☃A¢ €"], + ], +) +def test_argmax(strings): + """Test that argmax/argmin matches what python calculates.""" + arr = np.array(strings, dtype="T") + assert np.argmax(arr) == strings.index(max(strings)) + assert np.argmin(arr) == strings.index(min(strings)) + + +@pytest.mark.parametrize( + "arrfunc,expected", + [ + [np.sort, None], + [np.nonzero, (np.array([], dtype=np.int_),)], + [np.argmax, 0], + [np.argmin, 0], + ], +) +def test_arrfuncs_zeros(arrfunc, expected): + arr = np.zeros(10, dtype="T") + result = arrfunc(arr) + if expected is None: + expected = arr + assert_array_equal(result, expected, strict=True) + + +@pytest.mark.parametrize( + ("strings", "cast_answer", "any_answer", "all_answer"), + [ + [["hello", "world"], [True, True], True, True], + [["", ""], [False, False], False, False], + [["hello", ""], [True, False], True, False], + [["", "world"], [False, True], True, False], + ], +) +def test_cast_to_bool(strings, cast_answer, any_answer, all_answer): + sarr = np.array(strings, dtype="T") + assert_array_equal(sarr.astype("bool"), cast_answer) + + assert np.any(sarr) == any_answer + assert np.all(sarr) == all_answer + + +@pytest.mark.parametrize( + ("strings", "cast_answer"), + [ + [[True, True], ["True", "True"]], + [[False, False], ["False", "False"]], + [[True, False], ["True", "False"]], + [[False, True], ["False", "True"]], + ], +) +def test_cast_from_bool(strings, cast_answer): + barr = np.array(strings, dtype=bool) + assert_array_equal(barr.astype("T"), np.array(cast_answer, dtype="T")) + + +@pytest.mark.parametrize("bitsize", [8, 16, 32, 64]) +@pytest.mark.parametrize("signed", [True, False]) +def test_sized_integer_casts(bitsize, signed): + idtype = f"int{bitsize}" + if signed: + inp = [-(2**p - 1) for p in reversed(range(bitsize - 1))] + inp += [2**p - 1 for p in range(1, bitsize - 1)] + else: + idtype = "u" + idtype + inp = [2**p - 1 for p in range(bitsize)] + ainp = np.array(inp, dtype=idtype) + assert_array_equal(ainp, ainp.astype("T").astype(idtype)) + + # safe casting works + ainp.astype("T", casting="safe") + + with pytest.raises(TypeError): + ainp.astype("T").astype(idtype, casting="safe") + + oob = [str(2**bitsize), str(-(2**bitsize))] + with pytest.raises(OverflowError): + np.array(oob, dtype="T").astype(idtype) + + with pytest.raises(ValueError): + np.array(["1", np.nan, "3"], + dtype=StringDType(na_object=np.nan)).astype(idtype) + + +@pytest.mark.parametrize("typename", ["byte", "short", "int", "longlong"]) +@pytest.mark.parametrize("signed", ["", "u"]) +def test_unsized_integer_casts(typename, signed): + idtype = f"{signed}{typename}" + + inp = [1, 2, 3, 4] + ainp = np.array(inp, dtype=idtype) + assert_array_equal(ainp, ainp.astype("T").astype(idtype)) + + +@pytest.mark.parametrize( + "typename", + [ + pytest.param( + "longdouble", + marks=pytest.mark.xfail( + np.dtypes.LongDoubleDType() != np.dtypes.Float64DType(), + reason="numpy lacks an ld2a implementation", + strict=True, + ), + ), + "float64", + "float32", + "float16", + ], +) +def test_float_casts(typename): + inp = [1.1, 2.8, -3.2, 2.7e4] + ainp = np.array(inp, dtype=typename) + assert_array_equal(ainp, ainp.astype("T").astype(typename)) + + inp = [0.1] + sres = np.array(inp, dtype=typename).astype("T") + res = sres.astype(typename) + assert_array_equal(np.array(inp, dtype=typename), res) + assert sres[0] == "0.1" + + if typename == "longdouble": + # let's not worry about platform-dependent rounding of longdouble + return + + fi = np.finfo(typename) + + inp = [1e-324, fi.smallest_subnormal, -1e-324, -fi.smallest_subnormal] + eres = [0, fi.smallest_subnormal, -0, -fi.smallest_subnormal] + res = np.array(inp, dtype=typename).astype("T").astype(typename) + assert_array_equal(eres, res) + + inp = [2e308, fi.max, -2e308, fi.min] + eres = [np.inf, fi.max, -np.inf, fi.min] + res = np.array(inp, dtype=typename).astype("T").astype(typename) + assert_array_equal(eres, res) + + +def test_float_nan_cast_na_object(): + # gh-28157 + dt = np.dtypes.StringDType(na_object=np.nan) + arr1 = np.full((1,), fill_value=np.nan, dtype=dt) + arr2 = np.full_like(arr1, fill_value=np.nan) + + assert arr1.item() is np.nan + assert arr2.item() is np.nan + + inp = [1.2, 2.3, np.nan] + arr = np.array(inp).astype(dt) + assert arr[2] is np.nan + assert arr[0] == '1.2' + + +@pytest.mark.parametrize( + "typename", + [ + "csingle", + "cdouble", + pytest.param( + "clongdouble", + marks=pytest.mark.xfail( + np.dtypes.CLongDoubleDType() != np.dtypes.Complex128DType(), + reason="numpy lacks an ld2a implementation", + strict=True, + ), + ), + ], +) +def test_cfloat_casts(typename): + inp = [1.1 + 1.1j, 2.8 + 2.8j, -3.2 - 3.2j, 2.7e4 + 2.7e4j] + ainp = np.array(inp, dtype=typename) + assert_array_equal(ainp, ainp.astype("T").astype(typename)) + + inp = [0.1 + 0.1j] + sres = np.array(inp, dtype=typename).astype("T") + res = sres.astype(typename) + assert_array_equal(np.array(inp, dtype=typename), res) + assert sres[0] == "(0.1+0.1j)" + + +def test_take(string_list): + sarr = np.array(string_list, dtype="T") + res = sarr.take(np.arange(len(string_list))) + assert_array_equal(sarr, res) + + # make sure it also works for out + out = np.empty(len(string_list), dtype="T") + out[0] = "hello" + res = sarr.take(np.arange(len(string_list)), out=out) + assert res is out + assert_array_equal(sarr, res) + + +@pytest.mark.parametrize("use_out", [True, False]) +@pytest.mark.parametrize( + "ufunc_name,func", + [ + ("min", min), + ("max", max), + ], +) +def test_ufuncs_minmax(string_list, ufunc_name, func, use_out): + """Test that the min/max ufuncs match Python builtin min/max behavior.""" + arr = np.array(string_list, dtype="T") + uarr = np.array(string_list, dtype=str) + res = np.array(func(string_list), dtype="T") + assert_array_equal(getattr(arr, ufunc_name)(), res) + + ufunc = getattr(np, ufunc_name + "imum") + + if use_out: + res = ufunc(arr, arr, out=arr) + else: + res = ufunc(arr, arr) + + assert_array_equal(uarr, res) + assert_array_equal(getattr(arr, ufunc_name)(), func(string_list)) + + +def test_max_regression(): + arr = np.array(['y', 'y', 'z'], dtype="T") + assert arr.max() == 'z' + + +@pytest.mark.parametrize("use_out", [True, False]) +@pytest.mark.parametrize( + "other_strings", + [ + ["abc", "def" * 500, "ghi" * 16, "🤣" * 100, "📵", "😰"], + ["🚜", "🙃", "😾", "😹", "🚠", "🚌"], + ["🥦", "¨", "⨯", "∰ ", "⨌ ", "⎶ "], + ], +) +def test_ufunc_add(dtype, string_list, other_strings, use_out): + arr1 = np.array(string_list, dtype=dtype) + arr2 = np.array(other_strings, dtype=dtype) + result = np.array([a + b for a, b in zip(arr1, arr2)], dtype=dtype) + + if use_out: + res = np.add(arr1, arr2, out=arr1) + else: + res = np.add(arr1, arr2) + + assert_array_equal(res, result) + + if not hasattr(dtype, "na_object"): + return + + is_nan = isinstance(dtype.na_object, float) and np.isnan(dtype.na_object) + is_str = isinstance(dtype.na_object, str) + bool_errors = 0 + try: + bool(dtype.na_object) + except TypeError: + bool_errors = 1 + + arr1 = np.array([dtype.na_object] + string_list, dtype=dtype) + arr2 = np.array(other_strings + [dtype.na_object], dtype=dtype) + + if is_nan or bool_errors or is_str: + res = np.add(arr1, arr2) + assert_array_equal(res[1:-1], arr1[1:-1] + arr2[1:-1]) + if not is_str: + assert res[0] is dtype.na_object and res[-1] is dtype.na_object + else: + assert res[0] == dtype.na_object + arr2[0] + assert res[-1] == arr1[-1] + dtype.na_object + else: + with pytest.raises(ValueError): + np.add(arr1, arr2) + + +def test_ufunc_add_reduce(dtype): + values = ["a", "this is a long string", "c"] + arr = np.array(values, dtype=dtype) + out = np.empty((), dtype=dtype) + + expected = np.array("".join(values), dtype=dtype) + assert_array_equal(np.add.reduce(arr), expected) + + np.add.reduce(arr, out=out) + assert_array_equal(out, expected) + + +def test_add_promoter(string_list): + arr = np.array(string_list, dtype=StringDType()) + lresult = np.array(["hello" + s for s in string_list], dtype=StringDType()) + rresult = np.array([s + "hello" for s in string_list], dtype=StringDType()) + + for op in ["hello", np.str_("hello"), np.array(["hello"])]: + assert_array_equal(op + arr, lresult) + assert_array_equal(arr + op, rresult) + + # The promoter should be able to handle things if users pass `dtype=` + res = np.add("hello", string_list, dtype=StringDType) + assert res.dtype == StringDType() + + # The promoter should not kick in if users override the input, + # which means arr is cast, this fails because of the unknown length. + with pytest.raises(TypeError, match="cannot cast dtype"): + np.add(arr, "add", signature=("U", "U", None), casting="unsafe") + + # But it must simply reject the following: + with pytest.raises(TypeError, match=".*did not contain a loop"): + np.add(arr, "add", signature=(None, "U", None)) + + with pytest.raises(TypeError, match=".*did not contain a loop"): + np.add("a", "b", signature=("U", "U", StringDType)) + + +def test_add_no_legacy_promote_with_signature(): + # Possibly misplaced, but useful to test with string DType. We check that + # if there is clearly no loop found, a stray `dtype=` doesn't break things + # Regression test for the bad error in gh-26735 + # (If legacy promotion is gone, this can be deleted...) + with pytest.raises(TypeError, match=".*did not contain a loop"): + np.add("3", 6, dtype=StringDType) + + +def test_add_promoter_reduce(): + # Exact TypeError could change, but ensure StringDtype doesn't match + with pytest.raises(TypeError, match="the resolved dtypes are not"): + np.add.reduce(np.array(["a", "b"], dtype="U")) + + # On the other hand, using `dtype=T` in the *ufunc* should work. + np.add.reduce(np.array(["a", "b"], dtype="U"), dtype=np.dtypes.StringDType) + + +def test_multiply_reduce(): + # At the time of writing (NumPy 2.0) this is very limited (and rather + # ridiculous anyway). But it works and actually makes some sense... + # (NumPy does not allow non-scalar initial values) + repeats = np.array([2, 3, 4]) + val = "school-🚌" + res = np.multiply.reduce(repeats, initial=val, dtype=np.dtypes.StringDType) + assert res == val * np.prod(repeats) + + +def test_multiply_two_string_raises(): + arr = np.array(["hello", "world"], dtype="T") + with pytest.raises(np._core._exceptions._UFuncNoLoopError): + np.multiply(arr, arr) + + +@pytest.mark.parametrize("use_out", [True, False]) +@pytest.mark.parametrize("other", [2, [2, 1, 3, 4, 1, 3]]) +@pytest.mark.parametrize( + "other_dtype", + [ + None, + "int8", + "int16", + "int32", + "int64", + "uint8", + "uint16", + "uint32", + "uint64", + "short", + "int", + "intp", + "long", + "longlong", + "ushort", + "uint", + "uintp", + "ulong", + "ulonglong", + ], +) +def test_ufunc_multiply(dtype, string_list, other, other_dtype, use_out): + """Test the two-argument ufuncs match python builtin behavior.""" + arr = np.array(string_list, dtype=dtype) + if other_dtype is not None: + other_dtype = np.dtype(other_dtype) + try: + len(other) + result = [s * o for s, o in zip(string_list, other)] + other = np.array(other) + if other_dtype is not None: + other = other.astype(other_dtype) + except TypeError: + if other_dtype is not None: + other = other_dtype.type(other) + result = [s * other for s in string_list] + + if use_out: + arr_cache = arr.copy() + lres = np.multiply(arr, other, out=arr) + assert_array_equal(lres, result) + arr[:] = arr_cache + assert lres is arr + arr *= other + assert_array_equal(arr, result) + arr[:] = arr_cache + rres = np.multiply(other, arr, out=arr) + assert rres is arr + assert_array_equal(rres, result) + else: + lres = arr * other + assert_array_equal(lres, result) + rres = other * arr + assert_array_equal(rres, result) + + if not hasattr(dtype, "na_object"): + return + + is_nan = np.isnan(np.array([dtype.na_object], dtype=dtype))[0] + is_str = isinstance(dtype.na_object, str) + bool_errors = 0 + try: + bool(dtype.na_object) + except TypeError: + bool_errors = 1 + + arr = np.array(string_list + [dtype.na_object], dtype=dtype) + + try: + len(other) + other = np.append(other, 3) + if other_dtype is not None: + other = other.astype(other_dtype) + except TypeError: + pass + + if is_nan or bool_errors or is_str: + for res in [arr * other, other * arr]: + assert_array_equal(res[:-1], result) + if not is_str: + assert res[-1] is dtype.na_object + else: + try: + assert res[-1] == dtype.na_object * other[-1] + except (IndexError, TypeError): + assert res[-1] == dtype.na_object * other + else: + with pytest.raises(TypeError): + arr * other + with pytest.raises(TypeError): + other * arr + + +def test_findlike_promoters(): + r = "Wally" + l = "Where's Wally?" + s = np.int32(3) + e = np.int8(13) + for dtypes in [("T", "U"), ("U", "T")]: + for function, answer in [ + (np.strings.index, 8), + (np.strings.endswith, True), + ]: + assert answer == function( + np.array(l, dtype=dtypes[0]), np.array(r, dtype=dtypes[1]), s, e + ) + + +def test_strip_promoter(): + arg = ["Hello!!!!", "Hello??!!"] + strip_char = "!" + answer = ["Hello", "Hello??"] + for dtypes in [("T", "U"), ("U", "T")]: + result = np.strings.strip( + np.array(arg, dtype=dtypes[0]), + np.array(strip_char, dtype=dtypes[1]) + ) + assert_array_equal(result, answer) + assert result.dtype.char == "T" + + +def test_replace_promoter(): + arg = ["Hello, planet!", "planet, Hello!"] + old = "planet" + new = "world" + answer = ["Hello, world!", "world, Hello!"] + for dtypes in itertools.product("TU", repeat=3): + if dtypes == ("U", "U", "U"): + continue + answer_arr = np.strings.replace( + np.array(arg, dtype=dtypes[0]), + np.array(old, dtype=dtypes[1]), + np.array(new, dtype=dtypes[2]), + ) + assert_array_equal(answer_arr, answer) + assert answer_arr.dtype.char == "T" + + +def test_center_promoter(): + arg = ["Hello", "planet!"] + fillchar = "/" + for dtypes in [("T", "U"), ("U", "T")]: + answer = np.strings.center( + np.array(arg, dtype=dtypes[0]), 9, np.array(fillchar, dtype=dtypes[1]) + ) + assert_array_equal(answer, ["//Hello//", "/planet!/"]) + assert answer.dtype.char == "T" + + +DATETIME_INPUT = [ + np.datetime64("1923-04-14T12:43:12"), + np.datetime64("1994-06-21T14:43:15"), + np.datetime64("2001-10-15T04:10:32"), + np.datetime64("NaT"), + np.datetime64("1995-11-25T16:02:16"), + np.datetime64("2005-01-04T03:14:12"), + np.datetime64("2041-12-03T14:05:03"), +] + + +TIMEDELTA_INPUT = [ + np.timedelta64(12358, "s"), + np.timedelta64(23, "s"), + np.timedelta64(74, "s"), + np.timedelta64("NaT"), + np.timedelta64(23, "s"), + np.timedelta64(73, "s"), + np.timedelta64(7, "s"), +] + + +@pytest.mark.parametrize( + "input_data, input_dtype", + [ + (DATETIME_INPUT, "M8[s]"), + (TIMEDELTA_INPUT, "m8[s]") + ] +) +def test_datetime_timedelta_cast(dtype, input_data, input_dtype): + + a = np.array(input_data, dtype=input_dtype) + + has_na = hasattr(dtype, "na_object") + is_str = isinstance(getattr(dtype, "na_object", None), str) + + if not has_na or is_str: + a = np.delete(a, 3) + + sa = a.astype(dtype) + ra = sa.astype(a.dtype) + + if has_na and not is_str: + assert sa[3] is dtype.na_object + assert np.isnat(ra[3]) + + assert_array_equal(a, ra) + + if has_na and not is_str: + # don't worry about comparing how NaT is converted + sa = np.delete(sa, 3) + a = np.delete(a, 3) + + if input_dtype.startswith("M"): + assert_array_equal(sa, a.astype("U")) + else: + # The timedelta to unicode cast produces strings + # that aren't round-trippable and we don't want to + # reproduce that behavior in stringdtype + assert_array_equal(sa, a.astype("int64").astype("U")) + + +def test_nat_casts(): + s = 'nat' + all_nats = itertools.product(*zip(s.upper(), s.lower())) + all_nats = list(map(''.join, all_nats)) + NaT_dt = np.datetime64('NaT') + NaT_td = np.timedelta64('NaT') + for na_object in [np._NoValue, None, np.nan, 'nat', '']: + # numpy treats empty string and all case combinations of 'nat' as NaT + dtype = StringDType(na_object=na_object) + arr = np.array([''] + all_nats, dtype=dtype) + dt_array = arr.astype('M8[s]') + td_array = arr.astype('m8[s]') + assert_array_equal(dt_array, NaT_dt) + assert_array_equal(td_array, NaT_td) + + if na_object is np._NoValue: + output_object = 'NaT' + else: + output_object = na_object + + for arr in [dt_array, td_array]: + assert_array_equal( + arr.astype(dtype), + np.array([output_object] * arr.size, dtype=dtype)) + + +def test_nat_conversion(): + for nat in [np.datetime64("NaT", "s"), np.timedelta64("NaT", "s")]: + with pytest.raises(ValueError, match="string coercion is disabled"): + np.array(["a", nat], dtype=StringDType(coerce=False)) + + +def test_growing_strings(dtype): + # growing a string leads to a heap allocation, this tests to make sure + # we do that bookkeeping correctly for all possible starting cases + data = [ + "hello", # a short string + "abcdefghijklmnopqestuvwxyz", # a medium heap-allocated string + "hello" * 200, # a long heap-allocated string + ] + + arr = np.array(data, dtype=dtype) + uarr = np.array(data, dtype=str) + + for _ in range(5): + arr = arr + arr + uarr = uarr + uarr + + assert_array_equal(arr, uarr) + + +def test_assign_medium_strings(): + # see gh-29261 + N = 9 + src = np.array( + ( + ['0' * 256] * 3 + ['0' * 255] + ['0' * 256] + ['0' * 255] + + ['0' * 256] * 2 + ['0' * 255] + ), dtype='T') + dst = np.array( + ( + ['0' * 255] + ['0' * 256] * 2 + ['0' * 255] + ['0' * 256] + + ['0' * 255] + [''] * 5 + ), dtype='T') + + dst[1:N + 1] = src + assert_array_equal(dst[1:N + 1], src) + + +UFUNC_TEST_DATA = [ + "hello" * 10, + "Ae¢☃€ 😊" * 20, + "entry\nwith\nnewlines", + "entry\twith\ttabs", +] + + +@pytest.fixture +def string_array(dtype): + return np.array(UFUNC_TEST_DATA, dtype=dtype) + + +@pytest.fixture +def unicode_array(): + return np.array(UFUNC_TEST_DATA, dtype=np.str_) + + +NAN_PRESERVING_FUNCTIONS = [ + "capitalize", + "expandtabs", + "lower", + "lstrip", + "rstrip", + "splitlines", + "strip", + "swapcase", + "title", + "upper", +] + +BOOL_OUTPUT_FUNCTIONS = [ + "isalnum", + "isalpha", + "isdigit", + "islower", + "isspace", + "istitle", + "isupper", + "isnumeric", + "isdecimal", +] + +UNARY_FUNCTIONS = [ + "str_len", + "capitalize", + "expandtabs", + "isalnum", + "isalpha", + "isdigit", + "islower", + "isspace", + "istitle", + "isupper", + "lower", + "lstrip", + "rstrip", + "splitlines", + "strip", + "swapcase", + "title", + "upper", + "isnumeric", + "isdecimal", + "isalnum", + "islower", + "istitle", + "isupper", +] + +UNIMPLEMENTED_VEC_STRING_FUNCTIONS = [ + "capitalize", + "expandtabs", + "lower", + "splitlines", + "swapcase", + "title", + "upper", +] + +ONLY_IN_NP_CHAR = [ + "join", + "split", + "rsplit", + "splitlines" +] + + +@pytest.mark.parametrize("function_name", UNARY_FUNCTIONS) +def test_unary(string_array, unicode_array, function_name): + if function_name in ONLY_IN_NP_CHAR: + func = getattr(np.char, function_name) + else: + func = getattr(np.strings, function_name) + dtype = string_array.dtype + sres = func(string_array) + ures = func(unicode_array) + if sres.dtype == StringDType(): + ures = ures.astype(StringDType()) + assert_array_equal(sres, ures) + + if not hasattr(dtype, "na_object"): + return + + is_nan = np.isnan(np.array([dtype.na_object], dtype=dtype))[0] + is_str = isinstance(dtype.na_object, str) + na_arr = np.insert(string_array, 0, dtype.na_object) + + if function_name in UNIMPLEMENTED_VEC_STRING_FUNCTIONS: + if not is_str: + # to avoid these errors we'd need to add NA support to _vec_string + with pytest.raises((ValueError, TypeError)): + func(na_arr) + elif function_name == "splitlines": + assert func(na_arr)[0] == func(dtype.na_object)[()] + else: + assert func(na_arr)[0] == func(dtype.na_object) + return + if function_name == "str_len" and not is_str: + # str_len always errors for any non-string null, even NA ones because + # it has an integer result + with pytest.raises(ValueError): + func(na_arr) + return + if function_name in BOOL_OUTPUT_FUNCTIONS: + if is_nan: + assert func(na_arr)[0] is np.False_ + elif is_str: + assert func(na_arr)[0] == func(dtype.na_object) + else: + with pytest.raises(ValueError): + func(na_arr) + return + if not (is_nan or is_str): + with pytest.raises(ValueError): + func(na_arr) + return + res = func(na_arr) + if is_nan and function_name in NAN_PRESERVING_FUNCTIONS: + assert res[0] is dtype.na_object + elif is_str: + assert res[0] == func(dtype.na_object) + + +unicode_bug_fail = pytest.mark.xfail( + reason="unicode output width is buggy", strict=True +) + +# None means that the argument is a string array +BINARY_FUNCTIONS = [ + ("add", (None, None)), + ("multiply", (None, 2)), + ("mod", ("format: %s", None)), + ("center", (None, 25)), + ("count", (None, "A")), + ("encode", (None, "UTF-8")), + ("endswith", (None, "lo")), + ("find", (None, "A")), + ("index", (None, "e")), + ("join", ("-", None)), + ("ljust", (None, 12)), + ("lstrip", (None, "A")), + ("partition", (None, "A")), + ("replace", (None, "A", "B")), + ("rfind", (None, "A")), + ("rindex", (None, "e")), + ("rjust", (None, 12)), + ("rsplit", (None, "A")), + ("rstrip", (None, "A")), + ("rpartition", (None, "A")), + ("split", (None, "A")), + ("strip", (None, "A")), + ("startswith", (None, "A")), + ("zfill", (None, 12)), +] + +PASSES_THROUGH_NAN_NULLS = [ + "add", + "center", + "ljust", + "multiply", + "replace", + "rjust", + "strip", + "lstrip", + "rstrip", + "replace" + "zfill", +] + +NULLS_ARE_FALSEY = [ + "startswith", + "endswith", +] + +NULLS_ALWAYS_ERROR = [ + "count", + "find", + "rfind", +] + +SUPPORTS_NULLS = ( + PASSES_THROUGH_NAN_NULLS + + NULLS_ARE_FALSEY + + NULLS_ALWAYS_ERROR +) + + +def call_func(func, args, array, sanitize=True): + if args == (None, None): + return func(array, array) + if args[0] is None: + if sanitize: + san_args = tuple( + np.array(arg, dtype=array.dtype) if isinstance(arg, str) else + arg for arg in args[1:] + ) + else: + san_args = args[1:] + return func(array, *san_args) + if args[1] is None: + return func(args[0], array) + # shouldn't ever happen + assert 0 + + +@pytest.mark.parametrize("function_name, args", BINARY_FUNCTIONS) +def test_binary(string_array, unicode_array, function_name, args): + if function_name in ONLY_IN_NP_CHAR: + func = getattr(np.char, function_name) + else: + func = getattr(np.strings, function_name) + sres = call_func(func, args, string_array) + ures = call_func(func, args, unicode_array, sanitize=False) + if not isinstance(sres, tuple) and sres.dtype == StringDType(): + ures = ures.astype(StringDType()) + assert_array_equal(sres, ures) + + dtype = string_array.dtype + if function_name not in SUPPORTS_NULLS or not hasattr(dtype, "na_object"): + return + + na_arr = np.insert(string_array, 0, dtype.na_object) + is_nan = np.isnan(np.array([dtype.na_object], dtype=dtype))[0] + is_str = isinstance(dtype.na_object, str) + should_error = not (is_nan or is_str) + + if ( + (function_name in NULLS_ALWAYS_ERROR and not is_str) + or (function_name in PASSES_THROUGH_NAN_NULLS and should_error) + or (function_name in NULLS_ARE_FALSEY and should_error) + ): + with pytest.raises((ValueError, TypeError)): + call_func(func, args, na_arr) + return + + res = call_func(func, args, na_arr) + + if is_str: + assert res[0] == call_func(func, args, na_arr[:1]) + elif function_name in NULLS_ARE_FALSEY: + assert res[0] is np.False_ + elif function_name in PASSES_THROUGH_NAN_NULLS: + assert res[0] is dtype.na_object + else: + # shouldn't ever get here + assert 0 + + +@pytest.mark.parametrize("function, expected", [ + (np.strings.find, [[2, -1], [1, -1]]), + (np.strings.startswith, [[False, False], [True, False]])]) +@pytest.mark.parametrize("start, stop", [ + (1, 4), + (np.int8(1), np.int8(4)), + (np.array([1, 1], dtype='u2'), np.array([4, 4], dtype='u2'))]) +def test_non_default_start_stop(function, start, stop, expected): + a = np.array([["--🐍--", "--🦜--"], + ["-🐍---", "-🦜---"]], "T") + indx = function(a, "🐍", start, stop) + assert_array_equal(indx, expected) + + +@pytest.mark.parametrize("count", [2, np.int8(2), np.array([2, 2], 'u2')]) +def test_replace_non_default_repeat(count): + a = np.array(["🐍--", "🦜-🦜-"], "T") + result = np.strings.replace(a, "🦜-", "🦜†", count) + assert_array_equal(result, np.array(["🐍--", "🦜†🦜†"], "T")) + + +def test_strip_ljust_rjust_consistency(string_array, unicode_array): + rjs = np.char.rjust(string_array, 1000) + rju = np.char.rjust(unicode_array, 1000) + + ljs = np.char.ljust(string_array, 1000) + lju = np.char.ljust(unicode_array, 1000) + + assert_array_equal( + np.char.lstrip(rjs), + np.char.lstrip(rju).astype(StringDType()), + ) + + assert_array_equal( + np.char.rstrip(ljs), + np.char.rstrip(lju).astype(StringDType()), + ) + + assert_array_equal( + np.char.strip(ljs), + np.char.strip(lju).astype(StringDType()), + ) + + assert_array_equal( + np.char.strip(rjs), + np.char.strip(rju).astype(StringDType()), + ) + + +def test_unset_na_coercion(): + # a dtype instance with an unset na object is compatible + # with a dtype that has one set + + # this test uses the "add" and "equal" ufunc but all ufuncs that + # accept more than one string argument and produce a string should + # behave this way + # TODO: generalize to more ufuncs + inp = ["hello", "world"] + arr = np.array(inp, dtype=StringDType(na_object=None)) + for op_dtype in [None, StringDType(), StringDType(coerce=False), + StringDType(na_object=None)]: + if op_dtype is None: + op = "2" + else: + op = np.array("2", dtype=op_dtype) + res = arr + op + assert_array_equal(res, ["hello2", "world2"]) + + # dtype instances with distinct explicitly set NA objects are incompatible + for op_dtype in [StringDType(na_object=pd_NA), StringDType(na_object="")]: + op = np.array("2", dtype=op_dtype) + with pytest.raises(TypeError): + arr + op + + # comparisons only consider the na_object + for op_dtype in [None, StringDType(), StringDType(coerce=True), + StringDType(na_object=None)]: + if op_dtype is None: + op = inp + else: + op = np.array(inp, dtype=op_dtype) + assert_array_equal(arr, op) + + for op_dtype in [StringDType(na_object=pd_NA), + StringDType(na_object=np.nan)]: + op = np.array(inp, dtype=op_dtype) + with pytest.raises(TypeError): + arr == op + + +def test_repeat(string_array): + res = string_array.repeat(1000) + # Create an empty array with expanded dimension, and fill it. Then, + # reshape it to the expected result. + expected = np.empty_like(string_array, shape=string_array.shape + (1000,)) + expected[...] = string_array[:, np.newaxis] + expected = expected.reshape(-1) + + assert_array_equal(res, expected, strict=True) + + +@pytest.mark.parametrize("tile", [1, 6, (2, 5)]) +def test_accumulation(string_array, tile): + """Accumulation is odd for StringDType but tests dtypes with references. + """ + # Fill with mostly empty strings to not create absurdly big strings + arr = np.zeros_like(string_array, shape=(100,)) + arr[:len(string_array)] = string_array + arr[-len(string_array):] = string_array + + # Bloat size a bit (get above thresholds and test >1 ndim). + arr = np.tile(string_array, tile) + + res = np.add.accumulate(arr, axis=0) + res_obj = np.add.accumulate(arr.astype(object), axis=0) + assert_array_equal(res, res_obj.astype(arr.dtype), strict=True) + + if arr.ndim > 1: + res = np.add.accumulate(arr, axis=-1) + res_obj = np.add.accumulate(arr.astype(object), axis=-1) + + assert_array_equal(res, res_obj.astype(arr.dtype), strict=True) + + +class TestImplementation: + """Check that strings are stored in the arena when possible. + + This tests implementation details, so should be adjusted if + the implementation changes. + """ + + @classmethod + def setup_class(cls): + cls.MISSING = 0x80 + cls.INITIALIZED = 0x40 + cls.OUTSIDE_ARENA = 0x20 + cls.LONG = 0x10 + cls.dtype = StringDType(na_object=np.nan) + cls.sizeofstr = cls.dtype.itemsize + sp = cls.dtype.itemsize // 2 # pointer size = sizeof(size_t) + # Below, size is not strictly correct, since it really uses + # 7 (or 3) bytes, but good enough for the tests here. + cls.view_dtype = np.dtype([ + ('offset', f'u{sp}'), + ('size', f'u{sp // 2}'), + ('xsiz', f'V{sp // 2 - 1}'), + ('size_and_flags', 'u1'), + ] if sys.byteorder == 'little' else [ + ('size_and_flags', 'u1'), + ('xsiz', f'V{sp // 2 - 1}'), + ('size', f'u{sp // 2}'), + ('offset', f'u{sp}'), + ]) + cls.s_empty = "" + cls.s_short = "01234" + cls.s_medium = "abcdefghijklmnopqrstuvwxyz" + cls.s_long = "-=+" * 100 + cls.a = np.array( + [cls.s_empty, cls.s_short, cls.s_medium, cls.s_long], + cls.dtype) + + def get_view(self, a): + # Cannot view a StringDType as anything else directly, since + # it has references. So, we use a stride trick hack. + from numpy.lib._stride_tricks_impl import DummyArray + interface = dict(a.__array_interface__) + interface['descr'] = self.view_dtype.descr + interface['typestr'] = self.view_dtype.str + return np.asarray(DummyArray(interface, base=a)) + + def get_flags(self, a): + return self.get_view(a)['size_and_flags'] & 0xf0 + + def is_short(self, a): + return self.get_flags(a) == self.INITIALIZED | self.OUTSIDE_ARENA + + def is_on_heap(self, a): + return self.get_flags(a) == (self.INITIALIZED + | self.OUTSIDE_ARENA + | self.LONG) + + def is_missing(self, a): + return self.get_flags(a) & self.MISSING == self.MISSING + + def in_arena(self, a): + return (self.get_flags(a) & (self.INITIALIZED | self.OUTSIDE_ARENA) + == self.INITIALIZED) + + def test_setup(self): + is_short = self.is_short(self.a) + length = np.strings.str_len(self.a) + assert_array_equal(is_short, (length > 0) & (length <= 15)) + assert_array_equal(self.in_arena(self.a), [False, False, True, True]) + assert_array_equal(self.is_on_heap(self.a), False) + assert_array_equal(self.is_missing(self.a), False) + view = self.get_view(self.a) + sizes = np.where(is_short, view['size_and_flags'] & 0xf, + view['size']) + assert_array_equal(sizes, np.strings.str_len(self.a)) + assert_array_equal(view['xsiz'][2:], + np.void(b'\x00' * (self.sizeofstr // 4 - 1))) + # Check that the medium string uses only 1 byte for its length + # in the arena, while the long string takes 8 (or 4). + offsets = view['offset'] + assert offsets[2] == 1 + assert offsets[3] == 1 + len(self.s_medium) + self.sizeofstr // 2 + + def test_empty(self): + e = np.empty((3,), self.dtype) + assert_array_equal(self.get_flags(e), 0) + assert_array_equal(e, "") + + def test_zeros(self): + z = np.zeros((2,), self.dtype) + assert_array_equal(self.get_flags(z), 0) + assert_array_equal(z, "") + + def test_copy(self): + for c in [self.a.copy(), copy.copy(self.a), copy.deepcopy(self.a)]: + assert_array_equal(self.get_flags(c), self.get_flags(self.a)) + assert_array_equal(c, self.a) + offsets = self.get_view(c)['offset'] + assert offsets[2] == 1 + assert offsets[3] == 1 + len(self.s_medium) + self.sizeofstr // 2 + + def test_arena_use_with_setting(self): + c = np.zeros_like(self.a) + assert_array_equal(self.get_flags(c), 0) + c[:] = self.a + assert_array_equal(self.get_flags(c), self.get_flags(self.a)) + assert_array_equal(c, self.a) + + def test_arena_reuse_with_setting(self): + c = self.a.copy() + c[:] = self.a + assert_array_equal(self.get_flags(c), self.get_flags(self.a)) + assert_array_equal(c, self.a) + + def test_arena_reuse_after_missing(self): + c = self.a.copy() + c[:] = np.nan + assert np.all(self.is_missing(c)) + # Replacing with the original strings, the arena should be reused. + c[:] = self.a + assert_array_equal(self.get_flags(c), self.get_flags(self.a)) + assert_array_equal(c, self.a) + + def test_arena_reuse_after_empty(self): + c = self.a.copy() + c[:] = "" + assert_array_equal(c, "") + # Replacing with the original strings, the arena should be reused. + c[:] = self.a + assert_array_equal(self.get_flags(c), self.get_flags(self.a)) + assert_array_equal(c, self.a) + + def test_arena_reuse_for_shorter(self): + c = self.a.copy() + # A string slightly shorter than the shortest in the arena + # should be used for all strings in the arena. + c[:] = self.s_medium[:-1] + assert_array_equal(c, self.s_medium[:-1]) + # first empty string in original was never initialized, so + # filling it in now leaves it initialized inside the arena. + # second string started as a short string so it can never live + # in the arena. + in_arena = np.array([True, False, True, True]) + assert_array_equal(self.in_arena(c), in_arena) + # But when a short string is replaced, it will go on the heap. + assert_array_equal(self.is_short(c), False) + assert_array_equal(self.is_on_heap(c), ~in_arena) + # We can put the originals back, and they'll still fit, + # and short strings are back as short strings + c[:] = self.a + assert_array_equal(c, self.a) + assert_array_equal(self.in_arena(c), in_arena) + assert_array_equal(self.is_short(c), self.is_short(self.a)) + assert_array_equal(self.is_on_heap(c), False) + + def test_arena_reuse_if_possible(self): + c = self.a.copy() + # A slightly longer string will not fit in the arena for + # the medium string, but will fit for the longer one. + c[:] = self.s_medium + "±" + assert_array_equal(c, self.s_medium + "±") + in_arena_exp = np.strings.str_len(self.a) >= len(self.s_medium) + 1 + # first entry started uninitialized and empty, so filling it leaves + # it in the arena + in_arena_exp[0] = True + assert not np.all(in_arena_exp == self.in_arena(self.a)) + assert_array_equal(self.in_arena(c), in_arena_exp) + assert_array_equal(self.is_short(c), False) + assert_array_equal(self.is_on_heap(c), ~in_arena_exp) + # And once outside arena, it stays outside, since offset is lost. + # But short strings are used again. + c[:] = self.a + is_short_exp = self.is_short(self.a) + assert_array_equal(c, self.a) + assert_array_equal(self.in_arena(c), in_arena_exp) + assert_array_equal(self.is_short(c), is_short_exp) + assert_array_equal(self.is_on_heap(c), ~in_arena_exp & ~is_short_exp) + + def test_arena_no_reuse_after_short(self): + c = self.a.copy() + # If we replace a string with a short string, it cannot + # go into the arena after because the offset is lost. + c[:] = self.s_short + assert_array_equal(c, self.s_short) + assert_array_equal(self.in_arena(c), False) + c[:] = self.a + assert_array_equal(c, self.a) + assert_array_equal(self.in_arena(c), False) + assert_array_equal(self.is_on_heap(c), self.in_arena(self.a)) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_strings.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_strings.py new file mode 100644 index 0000000000000000000000000000000000000000..42e0d304c7517628c99f8977cdf83af02bcbb801 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_strings.py @@ -0,0 +1,1523 @@ +import operator +import sys + +import pytest + +import numpy as np +from numpy._core._exceptions import _UFuncNoLoopError +from numpy.testing import IS_PYPY, assert_array_equal, assert_raises +from numpy.testing._private.utils import requires_memory + +COMPARISONS = [ + (operator.eq, np.equal, "=="), + (operator.ne, np.not_equal, "!="), + (operator.lt, np.less, "<"), + (operator.le, np.less_equal, "<="), + (operator.gt, np.greater, ">"), + (operator.ge, np.greater_equal, ">="), +] + +MAX = np.iinfo(np.int64).max + +IS_PYPY_LT_7_3_16 = IS_PYPY and sys.implementation.version < (7, 3, 16) + +@pytest.mark.parametrize(["op", "ufunc", "sym"], COMPARISONS) +def test_mixed_string_comparison_ufuncs_fail(op, ufunc, sym): + arr_string = np.array(["a", "b"], dtype="S") + arr_unicode = np.array(["a", "c"], dtype="U") + + with pytest.raises(TypeError, match="did not contain a loop"): + ufunc(arr_string, arr_unicode) + + with pytest.raises(TypeError, match="did not contain a loop"): + ufunc(arr_unicode, arr_string) + +@pytest.mark.parametrize(["op", "ufunc", "sym"], COMPARISONS) +def test_mixed_string_comparisons_ufuncs_with_cast(op, ufunc, sym): + arr_string = np.array(["a", "b"], dtype="S") + arr_unicode = np.array(["a", "c"], dtype="U") + + # While there is no loop, manual casting is acceptable: + res1 = ufunc(arr_string, arr_unicode, signature="UU->?", casting="unsafe") + res2 = ufunc(arr_string, arr_unicode, signature="SS->?", casting="unsafe") + + expected = op(arr_string.astype("U"), arr_unicode) + assert_array_equal(res1, expected) + assert_array_equal(res2, expected) + + +@pytest.mark.parametrize(["op", "ufunc", "sym"], COMPARISONS) +@pytest.mark.parametrize("dtypes", [ + ("S2", "S2"), ("S2", "S10"), + ("U1"), (">U1", ">U1"), + ("U10")]) +@pytest.mark.parametrize("aligned", [True, False]) +def test_string_comparisons(op, ufunc, sym, dtypes, aligned): + # ensure native byte-order for the first view to stay within unicode range + native_dt = np.dtype(dtypes[0]).newbyteorder("=") + arr = np.arange(2**15).view(native_dt).astype(dtypes[0]) + if not aligned: + # Make `arr` unaligned: + new = np.zeros(arr.nbytes + 1, dtype=np.uint8)[1:].view(dtypes[0]) + new[...] = arr + arr = new + + arr2 = arr.astype(dtypes[1], copy=True) + np.random.shuffle(arr2) + arr[0] = arr2[0] # make sure one matches + + expected = [op(d1, d2) for d1, d2 in zip(arr.tolist(), arr2.tolist())] + assert_array_equal(op(arr, arr2), expected) + assert_array_equal(ufunc(arr, arr2), expected) + assert_array_equal( + np.char.compare_chararrays(arr, arr2, sym, False), expected + ) + + expected = [op(d2, d1) for d1, d2 in zip(arr.tolist(), arr2.tolist())] + assert_array_equal(op(arr2, arr), expected) + assert_array_equal(ufunc(arr2, arr), expected) + assert_array_equal( + np.char.compare_chararrays(arr2, arr, sym, False), expected + ) + + +@pytest.mark.parametrize(["op", "ufunc", "sym"], COMPARISONS) +@pytest.mark.parametrize("dtypes", [ + ("S2", "S2"), ("S2", "S10"), ("U10")]) +def test_string_comparisons_empty(op, ufunc, sym, dtypes): + arr = np.empty((1, 0, 1, 5), dtype=dtypes[0]) + arr2 = np.empty((100, 1, 0, 1), dtype=dtypes[1]) + + expected = np.empty(np.broadcast_shapes(arr.shape, arr2.shape), dtype=bool) + assert_array_equal(op(arr, arr2), expected) + assert_array_equal(ufunc(arr, arr2), expected) + assert_array_equal( + np.char.compare_chararrays(arr, arr2, sym, False), expected + ) + + +@pytest.mark.parametrize("str_dt", ["S", "U"]) +@pytest.mark.parametrize("float_dt", np.typecodes["AllFloat"]) +def test_float_to_string_cast(str_dt, float_dt): + float_dt = np.dtype(float_dt) + fi = np.finfo(float_dt) + arr = np.array([np.nan, np.inf, -np.inf, fi.max, fi.min], dtype=float_dt) + expected = ["nan", "inf", "-inf", str(fi.max), str(fi.min)] + if float_dt.kind == "c": + expected = [f"({r}+0j)" for r in expected] + + res = arr.astype(str_dt) + assert_array_equal(res, np.array(expected, dtype=str_dt)) + + +@pytest.mark.parametrize("str_dt", "US") +@pytest.mark.parametrize("size", [-1, np.iinfo(np.intc).max]) +def test_string_size_dtype_errors(str_dt, size): + if size > 0: + size = size // np.dtype(f"{str_dt}1").itemsize + 1 + + with pytest.raises(ValueError): + np.dtype((str_dt, size)) + with pytest.raises(TypeError): + np.dtype(f"{str_dt}{size}") + + +@pytest.mark.parametrize("str_dt", "US") +def test_string_size_dtype_large_repr(str_dt): + size = np.iinfo(np.intc).max // np.dtype(f"{str_dt}1").itemsize + size_str = str(size) + + dtype = np.dtype((str_dt, size)) + assert size_str in dtype.str + assert size_str in str(dtype) + assert size_str in repr(dtype) + + +@pytest.mark.slow +@requires_memory(2 * np.iinfo(np.intc).max) +@pytest.mark.parametrize("str_dt", "US") +@pytest.mark.thread_unsafe(reason="crashes with low memory") +def test_large_string_coercion_error(str_dt): + very_large = np.iinfo(np.intc).max // np.dtype(f"{str_dt}1").itemsize + try: + large_string = "A" * (very_large + 1) + except Exception: + # We may not be able to create this Python string on 32bit. + pytest.skip("python failed to create huge string") + + class MyStr: + def __str__(self): + return large_string + + try: + # TypeError from NumPy, or OverflowError from 32bit Python. + with pytest.raises((TypeError, OverflowError)): + np.array([large_string], dtype=str_dt) + + # Same as above, but input has to be converted to a string. + with pytest.raises((TypeError, OverflowError)): + np.array([MyStr()], dtype=str_dt) + except MemoryError: + # Catch memory errors, because `requires_memory` would do so. + raise AssertionError("Ops should raise before any large allocation.") + +@pytest.mark.slow +@requires_memory(2 * np.iinfo(np.intc).max) +@pytest.mark.parametrize("str_dt", "US") +@pytest.mark.thread_unsafe(reason="crashes with low memory") +def test_large_string_addition_error(str_dt): + very_large = np.iinfo(np.intc).max // np.dtype(f"{str_dt}1").itemsize + + a = np.array(["A" * very_large], dtype=str_dt) + b = np.array("B", dtype=str_dt) + try: + with pytest.raises(TypeError): + np.add(a, b) + with pytest.raises(TypeError): + np.add(a, a) + except MemoryError: + # Catch memory errors, because `requires_memory` would do so. + raise AssertionError("Ops should raise before any large allocation.") + + +def test_large_string_cast(): + very_large = np.iinfo(np.intc).max // 4 + # Could be nice to test very large path, but it makes too many huge + # allocations right now (need non-legacy cast loops for this). + # a = np.array([], dtype=np.dtype(("S", very_large))) + # assert a.astype("U").dtype.itemsize == very_large * 4 + + a = np.array([], dtype=np.dtype(("S", very_large + 1))) + # It is not perfect but OK if this raises a MemoryError during setup + # (this happens due clunky code and/or buffer setup.) + with pytest.raises((TypeError, MemoryError)): + a.astype("U") + + +@pytest.mark.parametrize("dt", ["S1", "U1"]) +def test_in_place_mutiply_no_overflow(dt): + # see gh-30495 + a = np.array("a", dtype=dt) + a *= 20 + assert_array_equal(a, np.array("a", dtype=dt)) + + +@pytest.mark.parametrize("dt", ["S", "U", "T"]) +class TestMethods: + + @pytest.mark.parametrize("in1,in2,out", [ + ("", "", ""), + ("abc", "abc", "abcabc"), + ("12345", "12345", "1234512345"), + ("MixedCase", "MixedCase", "MixedCaseMixedCase"), + ("12345 \0 ", "12345 \0 ", "12345 \0 12345 \0 "), + ("UPPER", "UPPER", "UPPERUPPER"), + (["abc", "def"], ["hello", "world"], ["abchello", "defworld"]), + ]) + def test_add(self, in1, in2, out, dt): + in1 = np.array(in1, dtype=dt) + in2 = np.array(in2, dtype=dt) + out = np.array(out, dtype=dt) + assert_array_equal(np.strings.add(in1, in2), out) + + @pytest.mark.parametrize("in1,in2,out", [ + ("abc", 3, "abcabcabc"), + ("abc", 0, ""), + ("abc", -1, ""), + (["abc", "def"], [1, 4], ["abc", "defdefdefdef"]), + ]) + def test_multiply(self, in1, in2, out, dt): + in1 = np.array(in1, dtype=dt) + out = np.array(out, dtype=dt) + assert_array_equal(np.strings.multiply(in1, in2), out) + + def test_multiply_raises(self, dt): + with pytest.raises(TypeError, match="unsupported type"): + np.strings.multiply(np.array("abc", dtype=dt), 3.14) + + with pytest.raises(OverflowError): + np.strings.multiply(np.array("abc", dtype=dt), sys.maxsize) + + def test_inplace_multiply(self, dt): + arr = np.array(['foo ', 'bar'], dtype=dt) + arr *= 2 + if dt != "T": + assert_array_equal(arr, np.array(['foo ', 'barb'], dtype=dt)) + else: + assert_array_equal(arr, ['foo foo ', 'barbar']) + + with pytest.raises(OverflowError): + arr *= sys.maxsize + + @pytest.mark.parametrize("i_dt", [np.int8, np.int16, np.int32, + np.int64, np.int_]) + def test_multiply_integer_dtypes(self, i_dt, dt): + a = np.array("abc", dtype=dt) + i = np.array(3, dtype=i_dt) + res = np.array("abcabcabc", dtype=dt) + assert_array_equal(np.strings.multiply(a, i), res) + + @pytest.mark.parametrize("in_,out", [ + ("", False), + ("a", True), + ("A", True), + ("\n", False), + ("abc", True), + ("aBc123", False), + ("abc\n", False), + (["abc", "aBc123"], [True, False]), + ]) + def test_isalpha(self, in_, out, dt): + in_ = np.array(in_, dtype=dt) + assert_array_equal(np.strings.isalpha(in_), out) + + @pytest.mark.parametrize("in_,out", [ + ('', False), + ('a', True), + ('A', True), + ('\n', False), + ('123abc456', True), + ('a1b3c', True), + ('aBc000 ', False), + ('abc\n', False), + ]) + def test_isalnum(self, in_, out, dt): + in_ = np.array(in_, dtype=dt) + assert_array_equal(np.strings.isalnum(in_), out) + + @pytest.mark.parametrize("in_,out", [ + ("", False), + ("a", False), + ("0", True), + ("012345", True), + ("012345a", False), + (["a", "012345"], [False, True]), + ]) + def test_isdigit(self, in_, out, dt): + in_ = np.array(in_, dtype=dt) + assert_array_equal(np.strings.isdigit(in_), out) + + @pytest.mark.parametrize("in_,out", [ + ("", False), + ("a", False), + ("1", False), + (" ", True), + ("\t", True), + ("\r", True), + ("\n", True), + (" \t\r \n", True), + (" \t\r\na", False), + (["\t1", " \t\r \n"], [False, True]) + ]) + def test_isspace(self, in_, out, dt): + in_ = np.array(in_, dtype=dt) + assert_array_equal(np.strings.isspace(in_), out) + + @pytest.mark.parametrize("in_,out", [ + ('', False), + ('a', True), + ('A', False), + ('\n', False), + ('abc', True), + ('aBc', False), + ('abc\n', True), + ]) + def test_islower(self, in_, out, dt): + in_ = np.array(in_, dtype=dt) + assert_array_equal(np.strings.islower(in_), out) + + @pytest.mark.parametrize("in_,out", [ + ('', False), + ('a', False), + ('A', True), + ('\n', False), + ('ABC', True), + ('AbC', False), + ('ABC\n', True), + ]) + def test_isupper(self, in_, out, dt): + in_ = np.array(in_, dtype=dt) + assert_array_equal(np.strings.isupper(in_), out) + + @pytest.mark.parametrize("in_,out", [ + ('', False), + ('a', False), + ('A', True), + ('\n', False), + ('A Titlecased Line', True), + ('A\nTitlecased Line', True), + ('A Titlecased, Line', True), + ('Not a capitalized String', False), + ('Not\ta Titlecase String', False), + ('Not--a Titlecase String', False), + ('NOT', False), + ]) + def test_istitle(self, in_, out, dt): + in_ = np.array(in_, dtype=dt) + assert_array_equal(np.strings.istitle(in_), out) + + @pytest.mark.parametrize("in_,out", [ + ("", 0), + ("abc", 3), + ("12345", 5), + ("MixedCase", 9), + ("12345 \x00 ", 8), + ("UPPER", 5), + (["abc", "12345 \x00 "], [3, 8]), + ]) + def test_str_len(self, in_, out, dt): + in_ = np.array(in_, dtype=dt) + assert_array_equal(np.strings.str_len(in_), out) + + @pytest.mark.parametrize("a,sub,start,end,out", [ + ("abcdefghiabc", "abc", 0, None, 0), + ("abcdefghiabc", "abc", 1, None, 9), + ("abcdefghiabc", "def", 4, None, -1), + ("abc", "", 0, None, 0), + ("abc", "", 3, None, 3), + ("abc", "", 4, None, -1), + ("rrarrrrrrrrra", "a", 0, None, 2), + ("rrarrrrrrrrra", "a", 4, None, 12), + ("rrarrrrrrrrra", "a", 4, 6, -1), + ("", "", 0, None, 0), + ("", "", 1, 1, -1), + ("", "", MAX, 0, -1), + ("", "xx", 0, None, -1), + ("", "xx", 1, 1, -1), + ("", "xx", MAX, 0, -1), + pytest.param(99 * "a" + "b", "b", 0, None, 99, + id="99*a+b-b-0-None-99"), + pytest.param(98 * "a" + "ba", "ba", 0, None, 98, + id="98*a+ba-ba-0-None-98"), + pytest.param(100 * "a", "b", 0, None, -1, + id="100*a-b-0-None--1"), + pytest.param(30000 * "a" + 100 * "b", 100 * "b", 0, None, 30000, + id="30000*a+100*b-100*b-0-None-30000"), + pytest.param(30000 * "a", 100 * "b", 0, None, -1, + id="30000*a-100*b-0-None--1"), + pytest.param(15000 * "a" + 15000 * "b", 15000 * "b", 0, None, 15000, + id="15000*a+15000*b-15000*b-0-None-15000"), + pytest.param(15000 * "a" + 15000 * "b", 15000 * "c", 0, None, -1, + id="15000*a+15000*b-15000*c-0-None--1"), + (["abcdefghiabc", "rrarrrrrrrrra"], ["def", "arr"], [0, 3], + None, [3, -1]), + ("Ae¢☃€ 😊" * 2, "😊", 0, None, 6), + ("Ae¢☃€ 😊" * 2, "😊", 7, None, 13), + pytest.param("A" * (2 ** 17), r"[\w]+\Z", 0, None, -1, + id=r"A*2**17-[\w]+\Z-0-None--1"), + ]) + def test_find(self, a, sub, start, end, out, dt): + if "😊" in a and dt == "S": + pytest.skip("Bytes dtype does not support non-ascii input") + a = np.array(a, dtype=dt) + sub = np.array(sub, dtype=dt) + assert_array_equal(np.strings.find(a, sub, start, end), out) + + @pytest.mark.parametrize("a,sub,start,end,out", [ + ("abcdefghiabc", "abc", 0, None, 9), + ("abcdefghiabc", "", 0, None, 12), + ("abcdefghiabc", "abcd", 0, None, 0), + ("abcdefghiabc", "abcz", 0, None, -1), + ("abc", "", 0, None, 3), + ("abc", "", 3, None, 3), + ("abc", "", 4, None, -1), + ("rrarrrrrrrrra", "a", 0, None, 12), + ("rrarrrrrrrrra", "a", 4, None, 12), + ("rrarrrrrrrrra", "a", 4, 6, -1), + (["abcdefghiabc", "rrarrrrrrrrra"], ["abc", "a"], [0, 0], + None, [9, 12]), + ("Ae¢☃€ 😊" * 2, "😊", 0, None, 13), + ("Ae¢☃€ 😊" * 2, "😊", 0, 7, 6), + ]) + def test_rfind(self, a, sub, start, end, out, dt): + if "😊" in a and dt == "S": + pytest.skip("Bytes dtype does not support non-ascii input") + a = np.array(a, dtype=dt) + sub = np.array(sub, dtype=dt) + assert_array_equal(np.strings.rfind(a, sub, start, end), out) + + @pytest.mark.parametrize("a,sub,start,end,out", [ + ("aaa", "a", 0, None, 3), + ("aaa", "b", 0, None, 0), + ("aaa", "a", 1, None, 2), + ("aaa", "a", 10, None, 0), + ("aaa", "a", -1, None, 1), + ("aaa", "a", -10, None, 3), + ("aaa", "a", 0, 1, 1), + ("aaa", "a", 0, 10, 3), + ("aaa", "a", 0, -1, 2), + ("aaa", "a", 0, -10, 0), + ("aaa", "", 1, None, 3), + ("aaa", "", 3, None, 1), + ("aaa", "", 10, None, 0), + ("aaa", "", -1, None, 2), + ("aaa", "", -10, None, 4), + ("aaa", "aaaa", 0, None, 0), + pytest.param(98 * "a" + "ba", "ba", 0, None, 1, + id="98*a+ba-ba-0-None-1"), + pytest.param(30000 * "a" + 100 * "b", 100 * "b", 0, None, 1, + id="30000*a+100*b-100*b-0-None-1"), + pytest.param(30000 * "a", 100 * "b", 0, None, 0, + id="30000*a-100*b-0-None-0"), + pytest.param(30000 * "a" + 100 * "ab", "ab", 0, None, 100, + id="30000*a+100*ab-ab-0-None-100"), + pytest.param(15000 * "a" + 15000 * "b", 15000 * "b", 0, None, 1, + id="15000*a+15000*b-15000*b-0-None-1"), + pytest.param(15000 * "a" + 15000 * "b", 15000 * "c", 0, None, 0, + id="15000*a+15000*b-15000*c-0-None-0"), + ("", "", 0, None, 1), + ("", "", 1, 1, 0), + ("", "", MAX, 0, 0), + ("", "xx", 0, None, 0), + ("", "xx", 1, 1, 0), + ("", "xx", MAX, 0, 0), + (["aaa", ""], ["a", ""], [0, 0], None, [3, 1]), + ("Ae¢☃€ 😊" * 100, "😊", 0, None, 100), + ]) + def test_count(self, a, sub, start, end, out, dt): + if "😊" in a and dt == "S": + pytest.skip("Bytes dtype does not support non-ascii input") + a = np.array(a, dtype=dt) + sub = np.array(sub, dtype=dt) + assert_array_equal(np.strings.count(a, sub, start, end), out) + + @pytest.mark.parametrize("a,prefix,start,end,out", [ + ("hello", "he", 0, None, True), + ("hello", "hello", 0, None, True), + ("hello", "hello world", 0, None, False), + ("hello", "", 0, None, True), + ("hello", "ello", 0, None, False), + ("hello", "ello", 1, None, True), + ("hello", "o", 4, None, True), + ("hello", "o", 5, None, False), + ("hello", "", 5, None, True), + ("hello", "lo", 6, None, False), + ("helloworld", "lowo", 3, None, True), + ("helloworld", "lowo", 3, 7, True), + ("helloworld", "lowo", 3, 6, False), + ("", "", 0, 1, True), + ("", "", 0, 0, True), + ("", "", 1, 0, False), + ("hello", "he", 0, -1, True), + ("hello", "he", -53, -1, True), + ("hello", "hello", 0, -1, False), + ("hello", "hello world", -1, -10, False), + ("hello", "ello", -5, None, False), + ("hello", "ello", -4, None, True), + ("hello", "o", -2, None, False), + ("hello", "o", -1, None, True), + ("hello", "", -3, -3, True), + ("hello", "lo", -9, None, False), + (["hello", ""], ["he", ""], [0, 0], None, [True, True]), + ]) + def test_startswith(self, a, prefix, start, end, out, dt): + a = np.array(a, dtype=dt) + prefix = np.array(prefix, dtype=dt) + assert_array_equal(np.strings.startswith(a, prefix, start, end), out) + + @pytest.mark.parametrize("a,suffix,start,end,out", [ + ("hello", "lo", 0, None, True), + ("hello", "he", 0, None, False), + ("hello", "", 0, None, True), + ("hello", "hello world", 0, None, False), + ("helloworld", "worl", 0, None, False), + ("helloworld", "worl", 3, 9, True), + ("helloworld", "world", 3, 12, True), + ("helloworld", "lowo", 1, 7, True), + ("helloworld", "lowo", 2, 7, True), + ("helloworld", "lowo", 3, 7, True), + ("helloworld", "lowo", 4, 7, False), + ("helloworld", "lowo", 3, 8, False), + ("ab", "ab", 0, 1, False), + ("ab", "ab", 0, 0, False), + ("", "", 0, 1, True), + ("", "", 0, 0, True), + ("", "", 1, 0, False), + ("hello", "lo", -2, None, True), + ("hello", "he", -2, None, False), + ("hello", "", -3, -3, True), + ("hello", "hello world", -10, -2, False), + ("helloworld", "worl", -6, None, False), + ("helloworld", "worl", -5, -1, True), + ("helloworld", "worl", -5, 9, True), + ("helloworld", "world", -7, 12, True), + ("helloworld", "lowo", -99, -3, True), + ("helloworld", "lowo", -8, -3, True), + ("helloworld", "lowo", -7, -3, True), + ("helloworld", "lowo", 3, -4, False), + ("helloworld", "lowo", -8, -2, False), + (["hello", "helloworld"], ["lo", "worl"], [0, -6], None, + [True, False]), + ]) + def test_endswith(self, a, suffix, start, end, out, dt): + a = np.array(a, dtype=dt) + suffix = np.array(suffix, dtype=dt) + assert_array_equal(np.strings.endswith(a, suffix, start, end), out) + + @pytest.mark.parametrize("a,chars,out", [ + ("", None, ""), + (" hello ", None, "hello "), + ("hello", None, "hello"), + (" \t\n\r\f\vabc \t\n\r\f\v", None, "abc \t\n\r\f\v"), + ([" hello ", "hello"], None, ["hello ", "hello"]), + ("", "", ""), + ("", "xyz", ""), + ("hello", "", "hello"), + ("xyzzyhelloxyzzy", "xyz", "helloxyzzy"), + ("hello", "xyz", "hello"), + ("xyxz", "xyxz", ""), + ("xyxzx", "x", "yxzx"), + (["xyzzyhelloxyzzy", "hello"], ["xyz", "xyz"], + ["helloxyzzy", "hello"]), + (["ba", "ac", "baa", "bba"], "b", ["a", "ac", "aa", "a"]), + ]) + def test_lstrip(self, a, chars, out, dt): + a = np.array(a, dtype=dt) + out = np.array(out, dtype=dt) + if chars is not None: + chars = np.array(chars, dtype=dt) + assert_array_equal(np.strings.lstrip(a, chars), out) + else: + assert_array_equal(np.strings.lstrip(a), out) + + @pytest.mark.parametrize("a,chars,out", [ + ("", None, ""), + (" hello ", None, " hello"), + ("hello", None, "hello"), + (" \t\n\r\f\vabc \t\n\r\f\v", None, " \t\n\r\f\vabc"), + ([" hello ", "hello"], None, [" hello", "hello"]), + ("", "", ""), + ("", "xyz", ""), + ("hello", "", "hello"), + (["hello ", "abcdefghijklmnop"], None, + ["hello", "abcdefghijklmnop"]), + ("xyzzyhelloxyzzy", "xyz", "xyzzyhello"), + ("hello", "xyz", "hello"), + ("xyxz", "xyxz", ""), + (" ", None, ""), + ("xyxzx", "x", "xyxz"), + (["xyzzyhelloxyzzy", "hello"], ["xyz", "xyz"], + ["xyzzyhello", "hello"]), + (["ab", "ac", "aab", "abb"], "b", ["a", "ac", "aa", "a"]), + ]) + def test_rstrip(self, a, chars, out, dt): + a = np.array(a, dtype=dt) + out = np.array(out, dtype=dt) + if chars is not None: + chars = np.array(chars, dtype=dt) + assert_array_equal(np.strings.rstrip(a, chars), out) + else: + assert_array_equal(np.strings.rstrip(a), out) + + @pytest.mark.parametrize("a,chars,out", [ + ("", None, ""), + (" hello ", None, "hello"), + ("hello", None, "hello"), + (" \t\n\r\f\vabc \t\n\r\f\v", None, "abc"), + ([" hello ", "hello"], None, ["hello", "hello"]), + ("", "", ""), + ("", "xyz", ""), + ("hello", "", "hello"), + ("xyzzyhelloxyzzy", "xyz", "hello"), + ("hello", "xyz", "hello"), + ("xyxz", "xyxz", ""), + ("xyxzx", "x", "yxz"), + (["xyzzyhelloxyzzy", "hello"], ["xyz", "xyz"], + ["hello", "hello"]), + (["bab", "ac", "baab", "bbabb"], "b", ["a", "ac", "aa", "a"]), + ]) + def test_strip(self, a, chars, out, dt): + a = np.array(a, dtype=dt) + if chars is not None: + chars = np.array(chars, dtype=dt) + out = np.array(out, dtype=dt) + assert_array_equal(np.strings.strip(a, chars), out) + + @pytest.mark.parametrize("buf,old,new,count,res", [ + ("", "", "", -1, ""), + ("", "", "A", -1, "A"), + ("", "A", "", -1, ""), + ("", "A", "A", -1, ""), + ("", "", "", 100, ""), + ("", "", "A", 100, "A"), + ("A", "", "", -1, "A"), + ("A", "", "*", -1, "*A*"), + ("A", "", "*1", -1, "*1A*1"), + ("A", "", "*-#", -1, "*-#A*-#"), + ("AA", "", "*-", -1, "*-A*-A*-"), + ("AA", "", "*-", -1, "*-A*-A*-"), + ("AA", "", "*-", 4, "*-A*-A*-"), + ("AA", "", "*-", 3, "*-A*-A*-"), + ("AA", "", "*-", 2, "*-A*-A"), + ("AA", "", "*-", 1, "*-AA"), + ("AA", "", "*-", 0, "AA"), + ("A", "A", "", -1, ""), + ("AAA", "A", "", -1, ""), + ("AAA", "A", "", -1, ""), + ("AAA", "A", "", 4, ""), + ("AAA", "A", "", 3, ""), + ("AAA", "A", "", 2, "A"), + ("AAA", "A", "", 1, "AA"), + ("AAA", "A", "", 0, "AAA"), + ("AAAAAAAAAA", "A", "", -1, ""), + ("ABACADA", "A", "", -1, "BCD"), + ("ABACADA", "A", "", -1, "BCD"), + ("ABACADA", "A", "", 5, "BCD"), + ("ABACADA", "A", "", 4, "BCD"), + ("ABACADA", "A", "", 3, "BCDA"), + ("ABACADA", "A", "", 2, "BCADA"), + ("ABACADA", "A", "", 1, "BACADA"), + ("ABACADA", "A", "", 0, "ABACADA"), + ("ABCAD", "A", "", -1, "BCD"), + ("ABCADAA", "A", "", -1, "BCD"), + ("BCD", "A", "", -1, "BCD"), + ("*************", "A", "", -1, "*************"), + ("^" + "A" * 1000 + "^", "A", "", 999, "^A^"), + ("the", "the", "", -1, ""), + ("theater", "the", "", -1, "ater"), + ("thethe", "the", "", -1, ""), + ("thethethethe", "the", "", -1, ""), + ("theatheatheathea", "the", "", -1, "aaaa"), + ("that", "the", "", -1, "that"), + ("thaet", "the", "", -1, "thaet"), + ("here and there", "the", "", -1, "here and re"), + ("here and there and there", "the", "", -1, "here and re and re"), + ("here and there and there", "the", "", 3, "here and re and re"), + ("here and there and there", "the", "", 2, "here and re and re"), + ("here and there and there", "the", "", 1, "here and re and there"), + ("here and there and there", "the", "", 0, "here and there and there"), + ("here and there and there", "the", "", -1, "here and re and re"), + ("abc", "the", "", -1, "abc"), + ("abcdefg", "the", "", -1, "abcdefg"), + ("bbobob", "bob", "", -1, "bob"), + ("bbobobXbbobob", "bob", "", -1, "bobXbob"), + ("aaaaaaabob", "bob", "", -1, "aaaaaaa"), + ("aaaaaaa", "bob", "", -1, "aaaaaaa"), + ("Who goes there?", "o", "o", -1, "Who goes there?"), + ("Who goes there?", "o", "O", -1, "WhO gOes there?"), + ("Who goes there?", "o", "O", -1, "WhO gOes there?"), + ("Who goes there?", "o", "O", 3, "WhO gOes there?"), + ("Who goes there?", "o", "O", 2, "WhO gOes there?"), + ("Who goes there?", "o", "O", 1, "WhO goes there?"), + ("Who goes there?", "o", "O", 0, "Who goes there?"), + ("Who goes there?", "a", "q", -1, "Who goes there?"), + ("Who goes there?", "W", "w", -1, "who goes there?"), + ("WWho goes there?WW", "W", "w", -1, "wwho goes there?ww"), + ("Who goes there?", "?", "!", -1, "Who goes there!"), + ("Who goes there??", "?", "!", -1, "Who goes there!!"), + ("Who goes there?", ".", "!", -1, "Who goes there?"), + ("This is a tissue", "is", "**", -1, "Th** ** a t**sue"), + ("This is a tissue", "is", "**", -1, "Th** ** a t**sue"), + ("This is a tissue", "is", "**", 4, "Th** ** a t**sue"), + ("This is a tissue", "is", "**", 3, "Th** ** a t**sue"), + ("This is a tissue", "is", "**", 2, "Th** ** a tissue"), + ("This is a tissue", "is", "**", 1, "Th** is a tissue"), + ("This is a tissue", "is", "**", 0, "This is a tissue"), + ("bobob", "bob", "cob", -1, "cobob"), + ("bobobXbobobob", "bob", "cob", -1, "cobobXcobocob"), + ("bobob", "bot", "bot", -1, "bobob"), + ("Reykjavik", "k", "KK", -1, "ReyKKjaviKK"), + ("Reykjavik", "k", "KK", -1, "ReyKKjaviKK"), + ("Reykjavik", "k", "KK", 2, "ReyKKjaviKK"), + ("Reykjavik", "k", "KK", 1, "ReyKKjavik"), + ("Reykjavik", "k", "KK", 0, "Reykjavik"), + ("A.B.C.", ".", "----", -1, "A----B----C----"), + ("Reykjavik", "q", "KK", -1, "Reykjavik"), + ("spam, spam, eggs and spam", "spam", "ham", -1, + "ham, ham, eggs and ham"), + ("spam, spam, eggs and spam", "spam", "ham", -1, + "ham, ham, eggs and ham"), + ("spam, spam, eggs and spam", "spam", "ham", 4, + "ham, ham, eggs and ham"), + ("spam, spam, eggs and spam", "spam", "ham", 3, + "ham, ham, eggs and ham"), + ("spam, spam, eggs and spam", "spam", "ham", 2, + "ham, ham, eggs and spam"), + ("spam, spam, eggs and spam", "spam", "ham", 1, + "ham, spam, eggs and spam"), + ("spam, spam, eggs and spam", "spam", "ham", 0, + "spam, spam, eggs and spam"), + ("bobobob", "bobob", "bob", -1, "bobob"), + ("bobobobXbobobob", "bobob", "bob", -1, "bobobXbobob"), + ("BOBOBOB", "bob", "bobby", -1, "BOBOBOB"), + ("one!two!three!", "!", "@", 1, "one@two!three!"), + ("one!two!three!", "!", "", -1, "onetwothree"), + ("one!two!three!", "!", "@", 2, "one@two@three!"), + ("one!two!three!", "!", "@", 3, "one@two@three@"), + ("one!two!three!", "!", "@", 4, "one@two@three@"), + ("one!two!three!", "!", "@", 0, "one!two!three!"), + ("one!two!three!", "!", "@", -1, "one@two@three@"), + ("one!two!three!", "x", "@", -1, "one!two!three!"), + ("one!two!three!", "x", "@", 2, "one!two!three!"), + ("abc", "", "-", -1, "-a-b-c-"), + ("abc", "", "-", 3, "-a-b-c"), + ("abc", "", "-", 0, "abc"), + ("abc", "ab", "--", 0, "abc"), + ("abc", "xy", "--", -1, "abc"), + (["abbc", "abbd"], "b", "z", [1, 2], ["azbc", "azzd"]), + ]) + def test_replace(self, buf, old, new, count, res, dt): + if "😊" in buf and dt == "S": + pytest.skip("Bytes dtype does not support non-ascii input") + buf = np.array(buf, dtype=dt) + old = np.array(old, dtype=dt) + new = np.array(new, dtype=dt) + res = np.array(res, dtype=dt) + assert_array_equal(np.strings.replace(buf, old, new, count), res) + + @pytest.mark.parametrize("buf,sub,start,end,res", [ + ("abcdefghiabc", "", 0, None, 0), + ("abcdefghiabc", "def", 0, None, 3), + ("abcdefghiabc", "abc", 0, None, 0), + ("abcdefghiabc", "abc", 1, None, 9), + ]) + def test_index(self, buf, sub, start, end, res, dt): + buf = np.array(buf, dtype=dt) + sub = np.array(sub, dtype=dt) + assert_array_equal(np.strings.index(buf, sub, start, end), res) + + @pytest.mark.parametrize("buf,sub,start,end", [ + ("abcdefghiabc", "hib", 0, None), + ("abcdefghiab", "abc", 1, None), + ("abcdefghi", "ghi", 8, None), + ("abcdefghi", "ghi", -1, None), + ("rrarrrrrrrrra", "a", 4, 6), + ]) + def test_index_raises(self, buf, sub, start, end, dt): + buf = np.array(buf, dtype=dt) + sub = np.array(sub, dtype=dt) + with pytest.raises(ValueError, match="substring not found"): + np.strings.index(buf, sub, start, end) + + @pytest.mark.parametrize("buf,sub,start,end,res", [ + ("abcdefghiabc", "", 0, None, 12), + ("abcdefghiabc", "def", 0, None, 3), + ("abcdefghiabc", "abc", 0, None, 9), + ("abcdefghiabc", "abc", 0, -1, 0), + ]) + def test_rindex(self, buf, sub, start, end, res, dt): + buf = np.array(buf, dtype=dt) + sub = np.array(sub, dtype=dt) + assert_array_equal(np.strings.rindex(buf, sub, start, end), res) + + @pytest.mark.parametrize("buf,sub,start,end", [ + ("abcdefghiabc", "hib", 0, None), + ("defghiabc", "def", 1, None), + ("defghiabc", "abc", 0, -1), + ("abcdefghi", "ghi", 0, 8), + ("abcdefghi", "ghi", 0, -1), + ("rrarrrrrrrrra", "a", 4, 6), + ]) + def test_rindex_raises(self, buf, sub, start, end, dt): + buf = np.array(buf, dtype=dt) + sub = np.array(sub, dtype=dt) + with pytest.raises(ValueError, match="substring not found"): + np.strings.rindex(buf, sub, start, end) + + @pytest.mark.parametrize("buf,tabsize,res", [ + ("abc\rab\tdef\ng\thi", 8, "abc\rab def\ng hi"), + ("abc\rab\tdef\ng\thi", 4, "abc\rab def\ng hi"), + ("abc\r\nab\tdef\ng\thi", 8, "abc\r\nab def\ng hi"), + ("abc\r\nab\tdef\ng\thi", 4, "abc\r\nab def\ng hi"), + ("abc\r\nab\r\ndef\ng\r\nhi", 4, "abc\r\nab\r\ndef\ng\r\nhi"), + (" \ta\n\tb", 1, " a\n b"), + ]) + def test_expandtabs(self, buf, tabsize, res, dt): + buf = np.array(buf, dtype=dt) + res = np.array(res, dtype=dt) + assert_array_equal(np.strings.expandtabs(buf, tabsize), res) + + def test_expandtabs_raises_overflow(self, dt): + with pytest.raises(OverflowError, match="new string is too long"): + np.strings.expandtabs(np.array("\ta\n\tb", dtype=dt), sys.maxsize) + np.strings.expandtabs(np.array("\ta\n\tb", dtype=dt), 2**61) + + def test_expandtabs_length_not_cause_segfault(self, dt): + # see gh-28829 + with pytest.raises( + _UFuncNoLoopError, + match="did not contain a loop with signature matching types", + ): + np._core.strings._expandtabs_length.reduce(np.zeros(200)) + + with pytest.raises( + _UFuncNoLoopError, + match="did not contain a loop with signature matching types", + ): + np.strings.expandtabs(np.zeros(200)) + + FILL_ERROR = "The fill character must be exactly one character long" + + def test_center_raises_multiple_character_fill(self, dt): + buf = np.array("abc", dtype=dt) + fill = np.array("**", dtype=dt) + with pytest.raises(TypeError, match=self.FILL_ERROR): + np.strings.center(buf, 10, fill) + + def test_ljust_raises_multiple_character_fill(self, dt): + buf = np.array("abc", dtype=dt) + fill = np.array("**", dtype=dt) + with pytest.raises(TypeError, match=self.FILL_ERROR): + np.strings.ljust(buf, 10, fill) + + def test_rjust_raises_multiple_character_fill(self, dt): + buf = np.array("abc", dtype=dt) + fill = np.array("**", dtype=dt) + with pytest.raises(TypeError, match=self.FILL_ERROR): + np.strings.rjust(buf, 10, fill) + + @pytest.mark.parametrize("buf,width,fillchar,res", [ + ('abc', 10, ' ', ' abc '), + ('abc', 6, ' ', ' abc '), + ('abc', 3, ' ', 'abc'), + ('abc', 2, ' ', 'abc'), + ('abc', -2, ' ', 'abc'), + ('abc', 10, '*', '***abc****'), + ]) + def test_center(self, buf, width, fillchar, res, dt): + buf = np.array(buf, dtype=dt) + fillchar = np.array(fillchar, dtype=dt) + res = np.array(res, dtype=dt) + assert_array_equal(np.strings.center(buf, width, fillchar), res) + + @pytest.mark.parametrize("buf,width,fillchar,res", [ + ('abc', 10, ' ', 'abc '), + ('abc', 6, ' ', 'abc '), + ('abc', 3, ' ', 'abc'), + ('abc', 2, ' ', 'abc'), + ('abc', -2, ' ', 'abc'), + ('abc', 10, '*', 'abc*******'), + ]) + def test_ljust(self, buf, width, fillchar, res, dt): + buf = np.array(buf, dtype=dt) + fillchar = np.array(fillchar, dtype=dt) + res = np.array(res, dtype=dt) + assert_array_equal(np.strings.ljust(buf, width, fillchar), res) + + @pytest.mark.parametrize("buf,width,fillchar,res", [ + ('abc', 10, ' ', ' abc'), + ('abc', 6, ' ', ' abc'), + ('abc', 3, ' ', 'abc'), + ('abc', 2, ' ', 'abc'), + ('abc', -2, ' ', 'abc'), + ('abc', 10, '*', '*******abc'), + ]) + def test_rjust(self, buf, width, fillchar, res, dt): + buf = np.array(buf, dtype=dt) + fillchar = np.array(fillchar, dtype=dt) + res = np.array(res, dtype=dt) + assert_array_equal(np.strings.rjust(buf, width, fillchar), res) + + @pytest.mark.parametrize("buf,width,res", [ + ('123', 2, '123'), + ('123', 3, '123'), + ('0123', 4, '0123'), + ('+123', 3, '+123'), + ('+123', 4, '+123'), + ('+123', 5, '+0123'), + ('+0123', 5, '+0123'), + ('-123', 3, '-123'), + ('-123', 4, '-123'), + ('-0123', 5, '-0123'), + ('000', 3, '000'), + ('34', 1, '34'), + ('34', -1, '34'), + ('0034', 4, '0034'), + ]) + def test_zfill(self, buf, width, res, dt): + buf = np.array(buf, dtype=dt) + res = np.array(res, dtype=dt) + assert_array_equal(np.strings.zfill(buf, width), res) + + @pytest.mark.parametrize("buf,sep,res1,res2,res3", [ + ("this is the partition method", "ti", "this is the par", + "ti", "tion method"), + ("http://www.python.org", "://", "http", "://", "www.python.org"), + ("http://www.python.org", "?", "http://www.python.org", "", ""), + ("http://www.python.org", "http://", "", "http://", "www.python.org"), + ("http://www.python.org", "org", "http://www.python.", "org", ""), + ("http://www.python.org", ["://", "?", "http://", "org"], + ["http", "http://www.python.org", "", "http://www.python."], + ["://", "", "http://", "org"], + ["www.python.org", "", "www.python.org", ""]), + ("mississippi", "ss", "mi", "ss", "issippi"), + ("mississippi", "i", "m", "i", "ssissippi"), + ("mississippi", "w", "mississippi", "", ""), + ]) + def test_partition(self, buf, sep, res1, res2, res3, dt): + buf = np.array(buf, dtype=dt) + sep = np.array(sep, dtype=dt) + res1 = np.array(res1, dtype=dt) + res2 = np.array(res2, dtype=dt) + res3 = np.array(res3, dtype=dt) + act1, act2, act3 = np.strings.partition(buf, sep) + assert_array_equal(act1, res1) + assert_array_equal(act2, res2) + assert_array_equal(act3, res3) + assert_array_equal(act1 + act2 + act3, buf) + + @pytest.mark.parametrize("buf,sep,res1,res2,res3", [ + ("this is the partition method", "ti", "this is the parti", + "ti", "on method"), + ("http://www.python.org", "://", "http", "://", "www.python.org"), + ("http://www.python.org", "?", "", "", "http://www.python.org"), + ("http://www.python.org", "http://", "", "http://", "www.python.org"), + ("http://www.python.org", "org", "http://www.python.", "org", ""), + ("http://www.python.org", ["://", "?", "http://", "org"], + ["http", "", "", "http://www.python."], + ["://", "", "http://", "org"], + ["www.python.org", "http://www.python.org", "www.python.org", ""]), + ("mississippi", "ss", "missi", "ss", "ippi"), + ("mississippi", "i", "mississipp", "i", ""), + ("mississippi", "w", "", "", "mississippi"), + ]) + def test_rpartition(self, buf, sep, res1, res2, res3, dt): + buf = np.array(buf, dtype=dt) + sep = np.array(sep, dtype=dt) + res1 = np.array(res1, dtype=dt) + res2 = np.array(res2, dtype=dt) + res3 = np.array(res3, dtype=dt) + act1, act2, act3 = np.strings.rpartition(buf, sep) + assert_array_equal(act1, res1) + assert_array_equal(act2, res2) + assert_array_equal(act3, res3) + assert_array_equal(act1 + act2 + act3, buf) + + @pytest.mark.parametrize("args", [ + (None,), + (None, None), + (None, None, -1), + (0,), + (0, None), + (0, None, -1), + (1,), + (1, None), + (1, None, -1), + (3,), + (3, None), + (5,), + (5, None), + (5, 5), + (5, 5, -1), + (6,), # test index past the end + (6, None), + (6, None, -1), + (6, 7), # test start and stop index past the end + (4, 3), # test start > stop index + (-1,), + (-1, None), + (-1, None, -1), + (-3,), + (-3, None), + ([3, 4],), + ([3, 4], None), + ([2, 4],), + ([-3, 5],), + ([-3, 5], None), + ([-3, 5], None, -1), + ([0, -5],), + ([0, -5], None), + ([0, -5], None, -1), + (1, 4), + (-3, 5), + (None, -1), + (0, [4, 2]), + ([1, 2], [-1, -2]), + (1, 5, 2), + (None, None, -1), + ([0, 6], [-1, 0], [2, -1]), + ]) + @pytest.mark.parametrize("buf", [ + ["hello", "world"], + ['hello world', 'γεια σου κόσμε', '你好世界', '👋 🌍'], + ]) + def test_slice(self, args, buf, dt): + if dt == "S" and "你好世界" in buf: + pytest.skip("Bytes dtype does not support non-ascii input") + if len(buf) == 4: + args = tuple(s * 2 if isinstance(s, list) else s for s in args) + buf = np.array(buf, dtype=dt) + act = np.strings.slice(buf, *args) + bcast_args = tuple(np.broadcast_to(arg, buf.shape) for arg in args) + res = np.array([s[slice(*arg)] + for s, arg in zip(buf, zip(*bcast_args))], + dtype=dt) + assert_array_equal(act, res) + + def test_slice_unsupported(self, dt): + with pytest.raises(TypeError, match="did not contain a loop"): + np.strings.slice(np.array([1, 2, 3]), 4) + + regexp = (r"Cannot cast ufunc '_slice' input .* " + r"from .* to dtype\('int(64|32)'\)") + with pytest.raises(TypeError, match=regexp): + np.strings.slice(np.array(['foo', 'bar'], dtype=dt), + np.array(['foo', 'bar'], dtype=dt)) + + @pytest.mark.parametrize("int_dt", [np.int8, np.int16, np.int32, + np.int64, np.uint8, np.uint16, + np.uint32, np.uint64]) + def test_slice_int_type_promotion(self, int_dt, dt): + buf = np.array(["hello", "world"], dtype=dt) + np_slice = np.strings.slice + assert_array_equal(np_slice(buf, int_dt(4)), + np.array(["hell", "worl"], dtype=dt)) + assert_array_equal(np_slice(buf, np.array([4, 4], dtype=int_dt)), + np.array(["hell", "worl"], dtype=dt)) + + assert_array_equal(np_slice(buf, int_dt(2), int_dt(4)), + np.array(["ll", "rl"], dtype=dt)) + assert_array_equal(np_slice(buf, np.array([2, 2], dtype=int_dt), + np.array([4, 4], dtype=int_dt)), + np.array(["ll", "rl"], dtype=dt)) + + assert_array_equal(np_slice(buf, int_dt(0), int_dt(4), int_dt(2)), + np.array(["hl", "wr"], dtype=dt)) + assert_array_equal(np_slice(buf, + np.array([0, 0], dtype=int_dt), + np.array([4, 4], dtype=int_dt), + np.array([2, 2], dtype=int_dt)), + np.array(["hl", "wr"], dtype=dt)) + +@pytest.mark.parametrize("dt", ["U", "T"]) +class TestMethodsWithUnicode: + @pytest.mark.parametrize("in_,out", [ + ("", False), + ("a", False), + ("0", True), + ("\u2460", False), # CIRCLED DIGIT 1 + ("\xbc", False), # VULGAR FRACTION ONE QUARTER + ("\u0660", True), # ARABIC_INDIC DIGIT ZERO + ("012345", True), + ("012345a", False), + (["0", "a"], [True, False]), + ]) + def test_isdecimal_unicode(self, in_, out, dt): + buf = np.array(in_, dtype=dt) + assert_array_equal(np.strings.isdecimal(buf), out) + + @pytest.mark.parametrize("in_,out", [ + ("", False), + ("a", False), + ("0", True), + ("\u2460", True), # CIRCLED DIGIT 1 + ("\xbc", True), # VULGAR FRACTION ONE QUARTER + ("\u0660", True), # ARABIC_INDIC DIGIT ZERO + ("012345", True), + ("012345a", False), + (["0", "a"], [True, False]), + ]) + def test_isnumeric_unicode(self, in_, out, dt): + buf = np.array(in_, dtype=dt) + assert_array_equal(np.strings.isnumeric(buf), out) + + @pytest.mark.parametrize("buf,old,new,count,res", [ + ("...\u043c......<", "<", "<", -1, "...\u043c......<"), + ("Ae¢☃€ 😊" * 2, "A", "B", -1, "Be¢☃€ 😊Be¢☃€ 😊"), + ("Ae¢☃€ 😊" * 2, "😊", "B", -1, "Ae¢☃€ BAe¢☃€ B"), + ]) + def test_replace_unicode(self, buf, old, new, count, res, dt): + buf = np.array(buf, dtype=dt) + old = np.array(old, dtype=dt) + new = np.array(new, dtype=dt) + res = np.array(res, dtype=dt) + assert_array_equal(np.strings.replace(buf, old, new, count), res) + + @pytest.mark.parametrize("in_", [ + '\U00010401', + '\U00010427', + '\U00010429', + '\U0001044E', + '\U0001D7F6', + '\U00011066', + '\U000104A0', + pytest.param('\U0001F107', marks=pytest.mark.xfail( + sys.platform == 'win32' and IS_PYPY_LT_7_3_16, + reason="PYPY bug in Py_UNICODE_ISALNUM", + strict=True)), + ]) + def test_isalnum_unicode(self, in_, dt): + in_ = np.array(in_, dtype=dt) + assert_array_equal(np.strings.isalnum(in_), True) + + @pytest.mark.parametrize("in_,out", [ + ('\u1FFc', False), + ('\u2167', False), + ('\U00010401', False), + ('\U00010427', False), + ('\U0001F40D', False), + ('\U0001F46F', False), + ('\u2177', True), + pytest.param('\U00010429', True, marks=pytest.mark.xfail( + sys.platform == 'win32' and IS_PYPY_LT_7_3_16, + reason="PYPY bug in Py_UNICODE_ISLOWER", + strict=True)), + ('\U0001044E', True), + ]) + def test_islower_unicode(self, in_, out, dt): + in_ = np.array(in_, dtype=dt) + assert_array_equal(np.strings.islower(in_), out) + + @pytest.mark.parametrize("in_,out", [ + ('\u1FFc', False), + ('\u2167', True), + ('\U00010401', True), + ('\U00010427', True), + ('\U0001F40D', False), + ('\U0001F46F', False), + ('\u2177', False), + pytest.param('\U00010429', False, marks=pytest.mark.xfail( + sys.platform == 'win32' and IS_PYPY_LT_7_3_16, + reason="PYPY bug in Py_UNICODE_ISUPPER", + strict=True)), + ('\U0001044E', False), + ]) + def test_isupper_unicode(self, in_, out, dt): + in_ = np.array(in_, dtype=dt) + assert_array_equal(np.strings.isupper(in_), out) + + @pytest.mark.parametrize("in_,out", [ + ('\u1FFc', True), + ('Greek \u1FFcitlecases ...', True), + pytest.param('\U00010401\U00010429', True, marks=pytest.mark.xfail( + sys.platform == 'win32' and IS_PYPY_LT_7_3_16, + reason="PYPY bug in Py_UNICODE_ISISTITLE", + strict=True)), + ('\U00010427\U0001044E', True), + pytest.param('\U00010429', False, marks=pytest.mark.xfail( + sys.platform == 'win32' and IS_PYPY_LT_7_3_16, + reason="PYPY bug in Py_UNICODE_ISISTITLE", + strict=True)), + ('\U0001044E', False), + ('\U0001F40D', False), + ('\U0001F46F', False), + ]) + def test_istitle_unicode(self, in_, out, dt): + in_ = np.array(in_, dtype=dt) + assert_array_equal(np.strings.istitle(in_), out) + + @pytest.mark.parametrize("buf,sub,start,end,res", [ + ("Ae¢☃€ 😊" * 2, "😊", 0, None, 6), + ("Ae¢☃€ 😊" * 2, "😊", 7, None, 13), + ]) + def test_index_unicode(self, buf, sub, start, end, res, dt): + buf = np.array(buf, dtype=dt) + sub = np.array(sub, dtype=dt) + assert_array_equal(np.strings.index(buf, sub, start, end), res) + + def test_index_raises_unicode(self, dt): + with pytest.raises(ValueError, match="substring not found"): + np.strings.index("Ae¢☃€ 😊", "😀") + + @pytest.mark.parametrize("buf,res", [ + ("Ae¢☃€ \t 😊", "Ae¢☃€ 😊"), + ("\t\U0001044E", " \U0001044E"), + ]) + def test_expandtabs(self, buf, res, dt): + buf = np.array(buf, dtype=dt) + res = np.array(res, dtype=dt) + assert_array_equal(np.strings.expandtabs(buf), res) + + @pytest.mark.parametrize("buf,width,fillchar,res", [ + ('x', 2, '\U0001044E', 'x\U0001044E'), + ('x', 3, '\U0001044E', '\U0001044Ex\U0001044E'), + ('x', 4, '\U0001044E', '\U0001044Ex\U0001044E\U0001044E'), + ]) + def test_center(self, buf, width, fillchar, res, dt): + buf = np.array(buf, dtype=dt) + fillchar = np.array(fillchar, dtype=dt) + res = np.array(res, dtype=dt) + assert_array_equal(np.strings.center(buf, width, fillchar), res) + + @pytest.mark.parametrize("buf,width,fillchar,res", [ + ('x', 2, '\U0001044E', 'x\U0001044E'), + ('x', 3, '\U0001044E', 'x\U0001044E\U0001044E'), + ('x', 4, '\U0001044E', 'x\U0001044E\U0001044E\U0001044E'), + ]) + def test_ljust(self, buf, width, fillchar, res, dt): + buf = np.array(buf, dtype=dt) + fillchar = np.array(fillchar, dtype=dt) + res = np.array(res, dtype=dt) + assert_array_equal(np.strings.ljust(buf, width, fillchar), res) + + @pytest.mark.parametrize("buf,width,fillchar,res", [ + ('x', 2, '\U0001044E', '\U0001044Ex'), + ('x', 3, '\U0001044E', '\U0001044E\U0001044Ex'), + ('x', 4, '\U0001044E', '\U0001044E\U0001044E\U0001044Ex'), + ]) + def test_rjust(self, buf, width, fillchar, res, dt): + buf = np.array(buf, dtype=dt) + fillchar = np.array(fillchar, dtype=dt) + res = np.array(res, dtype=dt) + assert_array_equal(np.strings.rjust(buf, width, fillchar), res) + + @pytest.mark.parametrize("buf,sep,res1,res2,res3", [ + ("āāāāĀĀĀĀ", "Ă", "āāāāĀĀĀĀ", "", ""), + ("āāāāĂĀĀĀĀ", "Ă", "āāāā", "Ă", "ĀĀĀĀ"), + ("āāāāĂĂĀĀĀĀ", "ĂĂ", "āāāā", "ĂĂ", "ĀĀĀĀ"), + ("𐌁𐌁𐌁𐌁𐌀𐌀𐌀𐌀", "𐌂", "𐌁𐌁𐌁𐌁𐌀𐌀𐌀𐌀", "", ""), + ("𐌁𐌁𐌁𐌁𐌂𐌀𐌀𐌀𐌀", "𐌂", "𐌁𐌁𐌁𐌁", "𐌂", "𐌀𐌀𐌀𐌀"), + ("𐌁𐌁𐌁𐌁𐌂𐌂𐌀𐌀𐌀𐌀", "𐌂𐌂", "𐌁𐌁𐌁𐌁", "𐌂𐌂", "𐌀𐌀𐌀𐌀"), + ("𐌁𐌁𐌁𐌁𐌂𐌂𐌂𐌂𐌀𐌀𐌀𐌀", "𐌂𐌂𐌂𐌂", "𐌁𐌁𐌁𐌁", "𐌂𐌂𐌂𐌂", "𐌀𐌀𐌀𐌀"), + ]) + def test_partition(self, buf, sep, res1, res2, res3, dt): + buf = np.array(buf, dtype=dt) + sep = np.array(sep, dtype=dt) + res1 = np.array(res1, dtype=dt) + res2 = np.array(res2, dtype=dt) + res3 = np.array(res3, dtype=dt) + act1, act2, act3 = np.strings.partition(buf, sep) + assert_array_equal(act1, res1) + assert_array_equal(act2, res2) + assert_array_equal(act3, res3) + assert_array_equal(act1 + act2 + act3, buf) + + @pytest.mark.parametrize("buf,sep,res1,res2,res3", [ + ("āāāāĀĀĀĀ", "Ă", "", "", "āāāāĀĀĀĀ"), + ("āāāāĂĀĀĀĀ", "Ă", "āāāā", "Ă", "ĀĀĀĀ"), + ("āāāāĂĂĀĀĀĀ", "ĂĂ", "āāāā", "ĂĂ", "ĀĀĀĀ"), + ("𐌁𐌁𐌁𐌁𐌀𐌀𐌀𐌀", "𐌂", "", "", "𐌁𐌁𐌁𐌁𐌀𐌀𐌀𐌀"), + ("𐌁𐌁𐌁𐌁𐌂𐌀𐌀𐌀𐌀", "𐌂", "𐌁𐌁𐌁𐌁", "𐌂", "𐌀𐌀𐌀𐌀"), + ("𐌁𐌁𐌁𐌁𐌂𐌂𐌀𐌀𐌀𐌀", "𐌂𐌂", "𐌁𐌁𐌁𐌁", "𐌂𐌂", "𐌀𐌀𐌀𐌀"), + ]) + def test_rpartition(self, buf, sep, res1, res2, res3, dt): + buf = np.array(buf, dtype=dt) + sep = np.array(sep, dtype=dt) + res1 = np.array(res1, dtype=dt) + res2 = np.array(res2, dtype=dt) + res3 = np.array(res3, dtype=dt) + act1, act2, act3 = np.strings.rpartition(buf, sep) + assert_array_equal(act1, res1) + assert_array_equal(act2, res2) + assert_array_equal(act3, res3) + assert_array_equal(act1 + act2 + act3, buf) + + @pytest.mark.parametrize("method", ["strip", "lstrip", "rstrip"]) + @pytest.mark.parametrize( + "source,strip", + [ + ("λμ", "μ"), + ("λμ", "λ"), + ("λ" * 5 + "μ" * 2, "μ"), + ("λ" * 5 + "μ" * 2, "λ"), + ("λ" * 5 + "A" + "μ" * 2, "μλ"), + ("λμ" * 5, "μ"), + ("λμ" * 5, "λ"), + ]) + def test_strip_functions_unicode(self, source, strip, method, dt): + src_array = np.array([source], dtype=dt) + + npy_func = getattr(np.strings, method) + py_func = getattr(str, method) + + expected = np.array([py_func(source, strip)], dtype=dt) + actual = npy_func(src_array, strip) + + assert_array_equal(actual, expected) + + @pytest.mark.parametrize("args", [ + (None,), + (0,), + (1,), + (5,), + (15,), + (22,), + (-1,), + (-3,), + ([3, 4],), + ([-5, 5],), + ([0, -8],), + (1, 12), + (-12, 15), + (None, -1), + (0, [17, 6]), + ([1, 2], [-1, -2]), + (1, 11, 2), + (None, None, -1), + ([0, 10], [-1, 0], [2, -1]), + ]) + def test_slice(self, args, dt): + buf = np.array(["Приве́т नमस्ते שָׁלוֹם", "😀😃😄😁😆😅🤣😂🙂🙃"], + dtype=dt) + act = np.strings.slice(buf, *args) + bcast_args = tuple(np.broadcast_to(arg, buf.shape) for arg in args) + res = np.array([s[slice(*arg)] + for s, arg in zip(buf, zip(*bcast_args))], + dtype=dt) + assert_array_equal(act, res) + + +class TestMixedTypeMethods: + def test_center(self): + buf = np.array("😊", dtype="U") + fill = np.array("*", dtype="S") + res = np.array("*😊*", dtype="U") + assert_array_equal(np.strings.center(buf, 3, fill), res) + + buf = np.array("s", dtype="S") + fill = np.array("*", dtype="U") + res = np.array("*s*", dtype="S") + assert_array_equal(np.strings.center(buf, 3, fill), res) + + with pytest.raises(ValueError, match="'ascii' codec can't encode"): + buf = np.array("s", dtype="S") + fill = np.array("😊", dtype="U") + np.strings.center(buf, 3, fill) + + def test_ljust(self): + buf = np.array("😊", dtype="U") + fill = np.array("*", dtype="S") + res = np.array("😊**", dtype="U") + assert_array_equal(np.strings.ljust(buf, 3, fill), res) + + buf = np.array("s", dtype="S") + fill = np.array("*", dtype="U") + res = np.array("s**", dtype="S") + assert_array_equal(np.strings.ljust(buf, 3, fill), res) + + with pytest.raises(ValueError, match="'ascii' codec can't encode"): + buf = np.array("s", dtype="S") + fill = np.array("😊", dtype="U") + np.strings.ljust(buf, 3, fill) + + def test_rjust(self): + buf = np.array("😊", dtype="U") + fill = np.array("*", dtype="S") + res = np.array("**😊", dtype="U") + assert_array_equal(np.strings.rjust(buf, 3, fill), res) + + buf = np.array("s", dtype="S") + fill = np.array("*", dtype="U") + res = np.array("**s", dtype="S") + assert_array_equal(np.strings.rjust(buf, 3, fill), res) + + with pytest.raises(ValueError, match="'ascii' codec can't encode"): + buf = np.array("s", dtype="S") + fill = np.array("😊", dtype="U") + np.strings.rjust(buf, 3, fill) + + +class TestUnicodeOnlyMethodsRaiseWithBytes: + def test_isdecimal_raises(self): + in_ = np.array(b"1") + with assert_raises(TypeError): + np.strings.isdecimal(in_) + + def test_isnumeric_bytes(self): + in_ = np.array(b"1") + with assert_raises(TypeError): + np.strings.isnumeric(in_) + + +def check_itemsize(n_elem, dt): + if dt == "T": + return np.dtype(dt).itemsize + if dt == "S": + return n_elem + if dt == "U": + return n_elem * 4 + +@pytest.mark.parametrize("dt", ["S", "U", "T"]) +class TestReplaceOnArrays: + + def test_replace_count_and_size(self, dt): + a = np.array(["0123456789" * i for i in range(4)], dtype=dt) + r1 = np.strings.replace(a, "5", "ABCDE") + assert r1.dtype.itemsize == check_itemsize(3 * 10 + 3 * 4, dt) + r1_res = np.array(["01234ABCDE6789" * i for i in range(4)], dtype=dt) + assert_array_equal(r1, r1_res) + r2 = np.strings.replace(a, "5", "ABCDE", 1) + assert r2.dtype.itemsize == check_itemsize(3 * 10 + 4, dt) + r3 = np.strings.replace(a, "5", "ABCDE", 0) + assert r3.dtype.itemsize == a.dtype.itemsize + assert_array_equal(r3, a) + # Negative values mean to replace all. + r4 = np.strings.replace(a, "5", "ABCDE", -1) + assert r4.dtype.itemsize == check_itemsize(3 * 10 + 3 * 4, dt) + assert_array_equal(r4, r1) + # We can do count on an element-by-element basis. + r5 = np.strings.replace(a, "5", "ABCDE", [-1, -1, -1, 1]) + assert r5.dtype.itemsize == check_itemsize(3 * 10 + 4, dt) + assert_array_equal(r5, np.array( + ["01234ABCDE6789" * i for i in range(3)] + + ["01234ABCDE6789" + "0123456789" * 2], dtype=dt)) + + def test_replace_broadcasting(self, dt): + a = np.array("0,0,0", dtype=dt) + r1 = np.strings.replace(a, "0", "1", np.arange(3)) + assert r1.dtype == a.dtype + assert_array_equal(r1, np.array(["0,0,0", "1,0,0", "1,1,0"], dtype=dt)) + r2 = np.strings.replace(a, "0", [["1"], ["2"]], np.arange(1, 4)) + assert_array_equal(r2, np.array([["1,0,0", "1,1,0", "1,1,1"], + ["2,0,0", "2,2,0", "2,2,2"]], + dtype=dt)) + r3 = np.strings.replace(a, ["0", "0,0", "0,0,0"], "X") + assert_array_equal(r3, np.array(["X,X,X", "X,0", "X"], dtype=dt)) + + +class TestOverride: + @classmethod + def setup_class(cls): + class Override: + + def __array_function__(self, *args, **kwargs): + return "function" + + def __array_ufunc__(self, *args, **kwargs): + return "ufunc" + + cls.override = Override() + + @pytest.mark.parametrize("func, kwargs", [ + (np.strings.center, dict(width=10)), + (np.strings.capitalize, {}), + (np.strings.decode, {}), + (np.strings.encode, {}), + (np.strings.expandtabs, {}), + (np.strings.ljust, dict(width=10)), + (np.strings.lower, {}), + (np.strings.mod, dict(values=2)), + (np.strings.multiply, dict(i=2)), + (np.strings.partition, dict(sep="foo")), + (np.strings.rjust, dict(width=10)), + (np.strings.rpartition, dict(sep="foo")), + (np.strings.swapcase, {}), + (np.strings.title, {}), + (np.strings.translate, dict(table=None)), + (np.strings.upper, {}), + (np.strings.zfill, dict(width=10)), + ]) + def test_override_function(self, func, kwargs): + assert func(self.override, **kwargs) == "function" + + @pytest.mark.parametrize("func, args, kwargs", [ + (np.strings.add, (None, ), {}), + (np.strings.lstrip, (), {}), + (np.strings.rstrip, (), {}), + (np.strings.strip, (), {}), + (np.strings.equal, (None, ), {}), + (np.strings.not_equal, (None, ), {}), + (np.strings.greater_equal, (None, ), {}), + (np.strings.less_equal, (None, ), {}), + (np.strings.greater, (None, ), {}), + (np.strings.less, (None, ), {}), + (np.strings.count, ("foo", ), {}), + (np.strings.endswith, ("foo", ), {}), + (np.strings.find, ("foo", ), {}), + (np.strings.index, ("foo", ), {}), + (np.strings.isalnum, (), {}), + (np.strings.isalpha, (), {}), + (np.strings.isdecimal, (), {}), + (np.strings.isdigit, (), {}), + (np.strings.islower, (), {}), + (np.strings.isnumeric, (), {}), + (np.strings.isspace, (), {}), + (np.strings.istitle, (), {}), + (np.strings.isupper, (), {}), + (np.strings.rfind, ("foo", ), {}), + (np.strings.rindex, ("foo", ), {}), + (np.strings.startswith, ("foo", ), {}), + (np.strings.str_len, (), {}), + ]) + def test_override_ufunc(self, func, args, kwargs): + assert func(self.override, *args, **kwargs) == "ufunc" diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_ufunc.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_ufunc.py new file mode 100644 index 0000000000000000000000000000000000000000..5c507c17ec0c61670a0fa6add67d8c7a57b8ecfd --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_ufunc.py @@ -0,0 +1,3409 @@ +import ctypes as ct +import inspect +import itertools +import pickle +import sys +import warnings + +import pytest +from pytest import param + +import numpy as np +import numpy._core._operand_flag_tests as opflag_tests +import numpy._core._rational_tests as _rational_tests +import numpy._core._umath_tests as umt +import numpy._core.umath as ncu +import numpy.linalg._umath_linalg as uml +from numpy.exceptions import AxisError +from numpy.testing import ( + HAS_REFCOUNT, + IS_PYPY, + IS_WASM, + assert_, + assert_allclose, + assert_almost_equal, + assert_array_almost_equal, + assert_array_equal, + assert_equal, + assert_no_warnings, + assert_raises, +) +from numpy.testing._private.utils import requires_memory + +UNARY_UFUNCS = [obj for obj in np._core.umath.__dict__.values() + if isinstance(obj, np.ufunc)] +UNARY_OBJECT_UFUNCS = [uf for uf in UNARY_UFUNCS if "O->O" in uf.types] + +# Remove functions that do not support `floats` +UNARY_OBJECT_UFUNCS.remove(np.bitwise_count) + + +class TestUfuncKwargs: + def test_kwarg_exact(self): + assert_raises(TypeError, np.add, 1, 2, castingx='safe') + assert_raises(TypeError, np.add, 1, 2, dtypex=int) + assert_raises(TypeError, np.add, 1, 2, extobjx=[4096]) + assert_raises(TypeError, np.add, 1, 2, outx=None) + assert_raises(TypeError, np.add, 1, 2, sigx='ii->i') + assert_raises(TypeError, np.add, 1, 2, signaturex='ii->i') + assert_raises(TypeError, np.add, 1, 2, subokx=False) + assert_raises(TypeError, np.add, 1, 2, wherex=[True]) + + def test_sig_signature(self): + assert_raises(TypeError, np.add, 1, 2, sig='ii->i', + signature='ii->i') + + def test_sig_dtype(self): + assert_raises(TypeError, np.add, 1, 2, sig='ii->i', + dtype=int) + assert_raises(TypeError, np.add, 1, 2, signature='ii->i', + dtype=int) + + def test_extobj_removed(self): + assert_raises(TypeError, np.add, 1, 2, extobj=[4096]) + + +class TestUfuncGenericLoops: + """Test generic loops. + + The loops to be tested are: + + PyUFunc_ff_f_As_dd_d + PyUFunc_ff_f + PyUFunc_dd_d + PyUFunc_gg_g + PyUFunc_FF_F_As_DD_D + PyUFunc_DD_D + PyUFunc_FF_F + PyUFunc_GG_G + PyUFunc_OO_O + PyUFunc_OO_O_method + PyUFunc_f_f_As_d_d + PyUFunc_d_d + PyUFunc_f_f + PyUFunc_g_g + PyUFunc_F_F_As_D_D + PyUFunc_F_F + PyUFunc_D_D + PyUFunc_G_G + PyUFunc_O_O + PyUFunc_O_O_method + PyUFunc_On_Om + + Where: + + f -- float + d -- double + g -- long double + F -- complex float + D -- complex double + G -- complex long double + O -- python object + + It is difficult to assure that each of these loops is entered from the + Python level as the special cased loops are a moving target and the + corresponding types are architecture dependent. We probably need to + define C level testing ufuncs to get at them. For the time being, I've + just looked at the signatures registered in the build directory to find + relevant functions. + + """ + np_dtypes = [ + (np.single, np.single), (np.single, np.double), + (np.csingle, np.csingle), (np.csingle, np.cdouble), + (np.double, np.double), (np.longdouble, np.longdouble), + (np.cdouble, np.cdouble), (np.clongdouble, np.clongdouble)] + + @pytest.mark.parametrize('input_dtype,output_dtype', np_dtypes) + def test_unary_PyUFunc(self, input_dtype, output_dtype, f=np.exp, x=0, y=1): + xs = np.full(10, input_dtype(x), dtype=output_dtype) + ys = f(xs)[::2] + assert_allclose(ys, y) + assert_equal(ys.dtype, output_dtype) + + def f2(x, y): + return x**y + + @pytest.mark.parametrize('input_dtype,output_dtype', np_dtypes) + def test_binary_PyUFunc(self, input_dtype, output_dtype, f=f2, x=0, y=1): + xs = np.full(10, input_dtype(x), dtype=output_dtype) + ys = f(xs, xs)[::2] + assert_allclose(ys, y) + assert_equal(ys.dtype, output_dtype) + + # class to use in testing object method loops + class foo: + def conjugate(self): + return np.bool(1) + + def logical_xor(self, obj): + return np.bool(1) + + def test_unary_PyUFunc_O_O(self): + x = np.ones(10, dtype=object) + assert_(np.all(np.abs(x) == 1)) + + def test_unary_PyUFunc_O_O_method_simple(self, foo=foo): + x = np.full(10, foo(), dtype=object) + assert_(np.all(np.conjugate(x) == True)) + + def test_binary_PyUFunc_OO_O(self): + x = np.ones(10, dtype=object) + assert_(np.all(np.add(x, x) == 2)) + + def test_binary_PyUFunc_OO_O_method(self, foo=foo): + x = np.full(10, foo(), dtype=object) + assert_(np.all(np.logical_xor(x, x))) + + def test_binary_PyUFunc_On_Om_method(self, foo=foo): + x = np.full((10, 2, 3), foo(), dtype=object) + assert_(np.all(np.logical_xor(x, x))) + + def test_python_complex_conjugate(self): + # The conjugate ufunc should fall back to calling the method: + arr = np.array([1 + 2j, 3 - 4j], dtype="O") + assert isinstance(arr[0], complex) + res = np.conjugate(arr) + assert res.dtype == np.dtype("O") + assert_array_equal(res, np.array([1 - 2j, 3 + 4j], dtype="O")) + + @pytest.mark.parametrize("ufunc", UNARY_OBJECT_UFUNCS) + def test_unary_PyUFunc_O_O_method_full(self, ufunc): + """Compare the result of the object loop with non-object one""" + val = np.float64(np.pi / 4) + + class MyFloat(np.float64): + def __getattr__(self, attr): + try: + return super().__getattr__(attr) + except AttributeError: + return lambda: getattr(np._core.umath, attr)(val) + + # Use 0-D arrays, to ensure the same element call + num_arr = np.array(val, dtype=np.float64) + obj_arr = np.array(MyFloat(val), dtype="O") + + with np.errstate(all="raise"): + try: + res_num = ufunc(num_arr) + except Exception as exc: + with assert_raises(type(exc)): + ufunc(obj_arr) + else: + res_obj = ufunc(obj_arr) + assert_array_almost_equal(res_num.astype("O"), res_obj) + + +def _pickleable_module_global(): + pass + + +class TestUfunc: + def test_pickle(self): + for proto in range(2, pickle.HIGHEST_PROTOCOL + 1): + assert_(pickle.loads(pickle.dumps(np.sin, + protocol=proto)) is np.sin) + + # Check that ufunc not defined in the top level numpy namespace + # such as numpy._core._rational_tests.test_add can also be pickled + res = pickle.loads(pickle.dumps(_rational_tests.test_add, + protocol=proto)) + assert_(res is _rational_tests.test_add) + + def test_pickle_withstring(self): + astring = (b"cnumpy.core\n_ufunc_reconstruct\np0\n" + b"(S'numpy._core.umath'\np1\nS'cos'\np2\ntp3\nRp4\n.") + assert_(pickle.loads(astring) is np.cos) + + @pytest.mark.skipif(IS_PYPY, reason="'is' check does not work on PyPy") + def test_pickle_name_is_qualname(self): + # This tests that a simplification of our ufunc pickle code will + # lead to allowing qualnames as names. Future ufuncs should + # possible add a specific qualname, or a hook into pickling instead + # (dask+numba may benefit). + _pickleable_module_global.ufunc = umt._pickleable_module_global_ufunc + + obj = pickle.loads(pickle.dumps(_pickleable_module_global.ufunc)) + assert obj is umt._pickleable_module_global_ufunc + + def test_reduceat_shifting_sum(self): + L = 6 + x = np.arange(L) + idx = np.array(list(zip(np.arange(L - 2), np.arange(L - 2) + 2))).ravel() + assert_array_equal(np.add.reduceat(x, idx)[::2], [1, 3, 5, 7]) + + def test_all_ufunc(self): + """Try to check presence and results of all ufuncs. + + The list of ufuncs comes from generate_umath.py and is as follows: + + ===== ==== ============= =============== ======================== + done args function types notes + ===== ==== ============= =============== ======================== + n 1 conjugate nums + O + n 1 absolute nums + O complex -> real + n 1 negative nums + O + n 1 sign nums + O -> int + n 1 invert bool + ints + O flts raise an error + n 1 degrees real + M cmplx raise an error + n 1 radians real + M cmplx raise an error + n 1 arccos flts + M + n 1 arccosh flts + M + n 1 arcsin flts + M + n 1 arcsinh flts + M + n 1 arctan flts + M + n 1 arctanh flts + M + n 1 cos flts + M + n 1 sin flts + M + n 1 tan flts + M + n 1 cosh flts + M + n 1 sinh flts + M + n 1 tanh flts + M + n 1 exp flts + M + n 1 expm1 flts + M + n 1 log flts + M + n 1 log10 flts + M + n 1 log1p flts + M + n 1 sqrt flts + M real x < 0 raises error + n 1 ceil real + M + n 1 trunc real + M + n 1 floor real + M + n 1 fabs real + M + n 1 rint flts + M + n 1 isnan flts -> bool + n 1 isinf flts -> bool + n 1 isfinite flts -> bool + n 1 signbit real -> bool + n 1 modf real -> (frac, int) + n 1 logical_not bool + nums + M -> bool + n 2 left_shift ints + O flts raise an error + n 2 right_shift ints + O flts raise an error + n 2 add bool + nums + O boolean + is || + n 2 subtract bool + nums + O boolean - is ^ + n 2 multiply bool + nums + O boolean * is & + n 2 divide nums + O + n 2 floor_divide nums + O + n 2 true_divide nums + O bBhH -> f, iIlLqQ -> d + n 2 fmod nums + M + n 2 power nums + O + n 2 greater bool + nums + O -> bool + n 2 greater_equal bool + nums + O -> bool + n 2 less bool + nums + O -> bool + n 2 less_equal bool + nums + O -> bool + n 2 equal bool + nums + O -> bool + n 2 not_equal bool + nums + O -> bool + n 2 logical_and bool + nums + M -> bool + n 2 logical_or bool + nums + M -> bool + n 2 logical_xor bool + nums + M -> bool + n 2 maximum bool + nums + O + n 2 minimum bool + nums + O + n 2 bitwise_and bool + ints + O flts raise an error + n 2 bitwise_or bool + ints + O flts raise an error + n 2 bitwise_xor bool + ints + O flts raise an error + n 2 arctan2 real + M + n 2 remainder ints + real + O + n 2 hypot real + M + ===== ==== ============= =============== ======================== + + Types other than those listed will be accepted, but they are cast to + the smallest compatible type for which the function is defined. The + casting rules are: + + bool -> int8 -> float32 + ints -> double + + """ + pass + + # from include/numpy/ufuncobject.h + size_inferred = 2 + can_ignore = 4 + + def test_signature0(self): + # the arguments to test_signature are: nin, nout, core_signature + enabled, num_dims, ixs, flags, sizes = umt.test_signature( + 2, 1, "(i),(i)->()") + assert_equal(enabled, 1) + assert_equal(num_dims, (1, 1, 0)) + assert_equal(ixs, (0, 0)) + assert_equal(flags, (self.size_inferred,)) + assert_equal(sizes, (-1,)) + + def test_signature1(self): + # empty core signature; treat as plain ufunc (with trivial core) + enabled, num_dims, ixs, flags, sizes = umt.test_signature( + 2, 1, "(),()->()") + assert_equal(enabled, 0) + assert_equal(num_dims, (0, 0, 0)) + assert_equal(ixs, ()) + assert_equal(flags, ()) + assert_equal(sizes, ()) + + def test_signature2(self): + # more complicated names for variables + enabled, num_dims, ixs, flags, sizes = umt.test_signature( + 2, 1, "(i1,i2),(J_1)->(_kAB)") + assert_equal(enabled, 1) + assert_equal(num_dims, (2, 1, 1)) + assert_equal(ixs, (0, 1, 2, 3)) + assert_equal(flags, (self.size_inferred,) * 4) + assert_equal(sizes, (-1, -1, -1, -1)) + + def test_signature3(self): + enabled, num_dims, ixs, flags, sizes = umt.test_signature( + 2, 1, "(i1, i12), (J_1)->(i12, i2)") + assert_equal(enabled, 1) + assert_equal(num_dims, (2, 1, 2)) + assert_equal(ixs, (0, 1, 2, 1, 3)) + assert_equal(flags, (self.size_inferred,) * 4) + assert_equal(sizes, (-1, -1, -1, -1)) + + def test_signature4(self): + # matrix_multiply signature from _umath_tests + enabled, num_dims, ixs, flags, sizes = umt.test_signature( + 2, 1, "(n,k),(k,m)->(n,m)") + assert_equal(enabled, 1) + assert_equal(num_dims, (2, 2, 2)) + assert_equal(ixs, (0, 1, 1, 2, 0, 2)) + assert_equal(flags, (self.size_inferred,) * 3) + assert_equal(sizes, (-1, -1, -1)) + + def test_signature5(self): + # matmul signature from _umath_tests + enabled, num_dims, ixs, flags, sizes = umt.test_signature( + 2, 1, "(n?,k),(k,m?)->(n?,m?)") + assert_equal(enabled, 1) + assert_equal(num_dims, (2, 2, 2)) + assert_equal(ixs, (0, 1, 1, 2, 0, 2)) + assert_equal(flags, (self.size_inferred | self.can_ignore, + self.size_inferred, + self.size_inferred | self.can_ignore)) + assert_equal(sizes, (-1, -1, -1)) + + def test_signature6(self): + enabled, num_dims, ixs, flags, sizes = umt.test_signature( + 1, 1, "(3)->()") + assert_equal(enabled, 1) + assert_equal(num_dims, (1, 0)) + assert_equal(ixs, (0,)) + assert_equal(flags, (0,)) + assert_equal(sizes, (3,)) + + def test_signature7(self): + enabled, num_dims, ixs, flags, sizes = umt.test_signature( + 3, 1, "(3),(03,3),(n)->(9)") + assert_equal(enabled, 1) + assert_equal(num_dims, (1, 2, 1, 1)) + assert_equal(ixs, (0, 0, 0, 1, 2)) + assert_equal(flags, (0, self.size_inferred, 0)) + assert_equal(sizes, (3, -1, 9)) + + def test_signature8(self): + enabled, num_dims, ixs, flags, sizes = umt.test_signature( + 3, 1, "(3?),(3?,3?),(n)->(9)") + assert_equal(enabled, 1) + assert_equal(num_dims, (1, 2, 1, 1)) + assert_equal(ixs, (0, 0, 0, 1, 2)) + assert_equal(flags, (self.can_ignore, self.size_inferred, 0)) + assert_equal(sizes, (3, -1, 9)) + + def test_signature9(self): + enabled, num_dims, ixs, flags, sizes = umt.test_signature( + 1, 1, "( 3) -> ( )") + assert_equal(enabled, 1) + assert_equal(num_dims, (1, 0)) + assert_equal(ixs, (0,)) + assert_equal(flags, (0,)) + assert_equal(sizes, (3,)) + + def test_signature10(self): + enabled, num_dims, ixs, flags, sizes = umt.test_signature( + 3, 1, "( 3? ) , (3? , 3?) ,(n )-> ( 9)") + assert_equal(enabled, 1) + assert_equal(num_dims, (1, 2, 1, 1)) + assert_equal(ixs, (0, 0, 0, 1, 2)) + assert_equal(flags, (self.can_ignore, self.size_inferred, 0)) + assert_equal(sizes, (3, -1, 9)) + + def test_signature_failure_extra_parenthesis(self): + with assert_raises(ValueError): + umt.test_signature(2, 1, "((i)),(i)->()") + + def test_signature_failure_mismatching_parenthesis(self): + with assert_raises(ValueError): + umt.test_signature(2, 1, "(i),)i(->()") + + def test_signature_failure_signature_missing_input_arg(self): + with assert_raises(ValueError): + umt.test_signature(2, 1, "(i),->()") + + def test_signature_failure_signature_missing_output_arg(self): + with assert_raises(ValueError): + umt.test_signature(2, 2, "(i),(i)->()") + + def test_get_signature(self): + assert_equal(np.vecdot.signature, "(n),(n)->()") + + def test_forced_sig(self): + a = 0.5 * np.arange(3, dtype='f8') + assert_equal(np.add(a, 0.5), [0.5, 1, 1.5]) + with assert_raises(TypeError): + np.add(a, 0.5, sig='i', casting='unsafe') + assert_equal(np.add(a, 0.5, sig='ii->i', casting='unsafe'), [0, 0, 1]) + with assert_raises(TypeError): + np.add(a, 0.5, sig=('i4',), casting='unsafe') + assert_equal(np.add(a, 0.5, sig=('i4', 'i4', 'i4'), + casting='unsafe'), [0, 0, 1]) + + b = np.zeros((3,), dtype='f8') + np.add(a, 0.5, out=b) + assert_equal(b, [0.5, 1, 1.5]) + b[:] = 0 + with assert_raises(TypeError): + np.add(a, 0.5, sig='i', out=b, casting='unsafe') + assert_equal(b, [0, 0, 0]) + np.add(a, 0.5, sig='ii->i', out=b, casting='unsafe') + assert_equal(b, [0, 0, 1]) + b[:] = 0 + with assert_raises(TypeError): + np.add(a, 0.5, sig=('i4',), out=b, casting='unsafe') + assert_equal(b, [0, 0, 0]) + np.add(a, 0.5, sig=('i4', 'i4', 'i4'), out=b, casting='unsafe') + assert_equal(b, [0, 0, 1]) + + def test_signature_all_None(self): + # signature all None, is an acceptable alternative (since 1.21) + # to not providing a signature. + res1 = np.add([3], [4], sig=(None, None, None)) + res2 = np.add([3], [4]) + assert_array_equal(res1, res2) + res1 = np.maximum([3], [4], sig=(None, None, None)) + res2 = np.maximum([3], [4]) + assert_array_equal(res1, res2) + + with pytest.raises(TypeError): + # special case, that would be deprecated anyway, so errors: + np.add(3, 4, signature=(None,)) + + def test_signature_dtype_type(self): + # Since that will be the normal behaviour (past NumPy 1.21) + # we do support the types already: + float_dtype = type(np.dtype(np.float64)) + np.add(3, 4, signature=(float_dtype, float_dtype, None)) + + @pytest.mark.parametrize("get_kwarg", [ + param(lambda dt: {"dtype": dt}, id="dtype"), + param(lambda dt: {"signature": (dt, None, None)}, id="signature")]) + def test_signature_dtype_instances_allowed(self, get_kwarg): + # We allow certain dtype instances when there is a clear singleton + # and the given one is equivalent; mainly for backcompat. + int64 = np.dtype("int64") + int64_2 = pickle.loads(pickle.dumps(int64)) + # Relies on pickling behavior, if assert fails just remove test... + assert int64 is not int64_2 + + assert np.add(1, 2, **get_kwarg(int64_2)).dtype == int64 + td = np.timedelta64(2, "s") + assert np.add(td, td, **get_kwarg("m8")).dtype == "m8[s]" + + msg = "The `dtype` and `signature` arguments to ufuncs" + + with pytest.raises(TypeError, match=msg): + np.add(3, 5, **get_kwarg(np.dtype("int64").newbyteorder())) + with pytest.raises(TypeError, match=msg): + np.add(3, 5, **get_kwarg(np.dtype("m8[ns]"))) + with pytest.raises(TypeError, match=msg): + np.add(3, 5, **get_kwarg("m8[ns]")) + + @pytest.mark.parametrize("casting", ["unsafe", "same_kind", "safe"]) + def test_partial_signature_mismatch(self, casting): + # If the second argument matches already, no need to specify it: + res = np.ldexp(np.float32(1.), np.int_(2), dtype="d") + assert res.dtype == "d" + res = np.ldexp(np.float32(1.), np.int_(2), signature=(None, None, "d")) + assert res.dtype == "d" + + # ldexp only has a loop for long input as second argument, overriding + # the output cannot help with that (no matter the casting) + with pytest.raises(TypeError): + np.ldexp(1., np.uint64(3), dtype="d") + with pytest.raises(TypeError): + np.ldexp(1., np.uint64(3), signature=(None, None, "d")) + + def test_partial_signature_mismatch_with_cache(self): + with pytest.raises(TypeError): + np.add(np.float16(1), np.uint64(2), sig=("e", "d", None)) + # Ensure e,d->None is in the dispatching cache (double loop) + np.add(np.float16(1), np.float64(2)) + # The error must still be raised: + with pytest.raises(TypeError): + np.add(np.float16(1), np.uint64(2), sig=("e", "d", None)) + + def test_use_output_signature_for_all_arguments(self): + # Test that providing only `dtype=` or `signature=(None, None, dtype)` + # is sufficient if falling back to a homogeneous signature works. + # In this case, the `intp, intp -> intp` loop is chosen. + res = np.power(1.5, 2.8, dtype=np.intp, casting="unsafe") + assert res == 1 # the cast happens first. + res = np.power(1.5, 2.8, signature=(None, None, np.intp), + casting="unsafe") + assert res == 1 + with pytest.raises(TypeError): + # the unsafe casting would normally cause errors though: + np.power(1.5, 2.8, dtype=np.intp) + + def test_signature_errors(self): + with pytest.raises(TypeError, + match="the signature object to ufunc must be a string or"): + np.add(3, 4, signature=123.) # neither a string nor a tuple + + with pytest.raises(ValueError): + # bad symbols that do not translate to dtypes + np.add(3, 4, signature="%^->#") + + with pytest.raises(ValueError): + np.add(3, 4, signature=b"ii-i") # incomplete and byte string + + with pytest.raises(ValueError): + np.add(3, 4, signature="ii>i") # incomplete string + + with pytest.raises(ValueError): + np.add(3, 4, signature=(None, "f8")) # bad length + + with pytest.raises(UnicodeDecodeError): + np.add(3, 4, signature=b"\xff\xff->i") + + def test_forced_dtype_times(self): + # Signatures only set the type numbers (not the actual loop dtypes) + # so using `M` in a signature/dtype should generally work: + a = np.array(['2010-01-02', '1999-03-14', '1833-03'], dtype='>M8[D]') + np.maximum(a, a, dtype="M") + np.maximum.reduce(a, dtype="M") + + arr = np.arange(10, dtype="m8[s]") + np.add(arr, arr, dtype="m") + np.maximum(arr, arr, dtype="m") + + @pytest.mark.parametrize("ufunc", [np.add, np.sqrt]) + def test_cast_safety(self, ufunc): + """Basic test for the safest casts, because ufuncs inner loops can + indicate a cast-safety as well (which is normally always "no"). + """ + def call_ufunc(arr, **kwargs): + return ufunc(*(arr,) * ufunc.nin, **kwargs) + + arr = np.array([1., 2., 3.], dtype=np.float32) + arr_bs = arr.astype(arr.dtype.newbyteorder()) + expected = call_ufunc(arr) + # Normally, a "no" cast: + res = call_ufunc(arr, casting="no") + assert_array_equal(expected, res) + # Byte-swapping is not allowed with "no" though: + with pytest.raises(TypeError): + call_ufunc(arr_bs, casting="no") + + # But is allowed with "equiv": + res = call_ufunc(arr_bs, casting="equiv") + assert_array_equal(expected, res) + + # Casting to float64 is safe, but not equiv: + with pytest.raises(TypeError): + call_ufunc(arr_bs, dtype=np.float64, casting="equiv") + + # but it is safe cast: + res = call_ufunc(arr_bs, dtype=np.float64, casting="safe") + expected = call_ufunc(arr.astype(np.float64)) # upcast + assert_array_equal(expected, res) + + @pytest.mark.parametrize("ufunc", [np.add, np.equal]) + def test_cast_safety_scalar(self, ufunc): + # We test add and equal, because equal has special scalar handling + # Note that the "equiv" casting behavior should maybe be considered + # a current implementation detail. + with pytest.raises(TypeError): + # this picks an integer loop, which is not safe + ufunc(3., 4., dtype=int, casting="safe") + + with pytest.raises(TypeError): + # We accept python float as float64 but not float32 for equiv. + ufunc(3., 4., dtype="float32", casting="equiv") + + # Special case for object and equal (note that equiv implies safe) + ufunc(3, 4, dtype=object, casting="equiv") + # Picks a double loop for both, first is equiv, second safe: + ufunc(np.array([3.]), 3., casting="equiv") + ufunc(np.array([3.]), 3, casting="safe") + ufunc(np.array([3]), 3, casting="equiv") + + def test_cast_safety_scalar_special(self): + # We allow this (and it succeeds) via object, although the equiv + # part may not be important. + np.equal(np.array([3]), 2**300, casting="equiv") + + def test_true_divide(self): + a = np.array(10) + b = np.array(20) + tgt = np.array(0.5) + + for tc in 'bhilqBHILQefdgFDG': + dt = np.dtype(tc) + aa = a.astype(dt) + bb = b.astype(dt) + + # Check result value and dtype. + for x, y in itertools.product([aa, -aa], [bb, -bb]): + + # Check with no output type specified + if tc in 'FDG': + tgt = complex(x) / complex(y) + else: + tgt = float(x) / float(y) + + res = np.true_divide(x, y) + rtol = max(np.finfo(res).resolution, 1e-15) + assert_allclose(res, tgt, rtol=rtol) + + if tc in 'bhilqBHILQ': + assert_(res.dtype.name == 'float64') + else: + assert_(res.dtype.name == dt.name) + + # Check with output type specified. This also checks for the + # incorrect casts in issue gh-3484 because the unary '-' does + # not change types, even for unsigned types, Hence casts in the + # ufunc from signed to unsigned and vice versa will lead to + # errors in the values. + for tcout in 'bhilqBHILQ': + dtout = np.dtype(tcout) + assert_raises(TypeError, np.true_divide, x, y, dtype=dtout) + + for tcout in 'efdg': + dtout = np.dtype(tcout) + if tc in 'FDG': + # Casting complex to float is not allowed + assert_raises(TypeError, np.true_divide, x, y, dtype=dtout) + else: + tgt = float(x) / float(y) + rtol = max(np.finfo(dtout).resolution, 1e-15) + # The value of tiny for double double is NaN + with warnings.catch_warnings(): + warnings.simplefilter('ignore', UserWarning) + if not np.isnan(np.finfo(dtout).tiny): + atol = max(np.finfo(dtout).tiny, 3e-308) + else: + atol = 3e-308 + # Some test values result in invalid for float16 + # and the cast to it may overflow to inf. + with np.errstate(invalid='ignore', over='ignore'): + res = np.true_divide(x, y, dtype=dtout) + if not np.isfinite(res) and tcout == 'e': + continue + assert_allclose(res, tgt, rtol=rtol, atol=atol) + assert_(res.dtype.name == dtout.name) + + for tcout in 'FDG': + dtout = np.dtype(tcout) + tgt = complex(x) / complex(y) + rtol = max(np.finfo(dtout).resolution, 1e-15) + # The value of tiny for double double is NaN + with warnings.catch_warnings(): + warnings.simplefilter('ignore', UserWarning) + if not np.isnan(np.finfo(dtout).tiny): + atol = max(np.finfo(dtout).tiny, 3e-308) + else: + atol = 3e-308 + res = np.true_divide(x, y, dtype=dtout) + if not np.isfinite(res): + continue + assert_allclose(res, tgt, rtol=rtol, atol=atol) + assert_(res.dtype.name == dtout.name) + + # Check booleans + a = np.ones((), dtype=np.bool) + res = np.true_divide(a, a) + assert_(res == 1.0) + assert_(res.dtype.name == 'float64') + res = np.true_divide(~a, a) + assert_(res == 0.0) + assert_(res.dtype.name == 'float64') + + def test_sum_stability(self): + a = np.ones(500, dtype=np.float32) + assert_almost_equal((a / 10.).sum() - a.size / 10., 0, 4) + + a = np.ones(500, dtype=np.float64) + assert_almost_equal((a / 10.).sum() - a.size / 10., 0, 13) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + def test_sum(self): + for dt in (int, np.float16, np.float32, np.float64, np.longdouble): + for v in (0, 1, 2, 7, 8, 9, 15, 16, 19, 127, + 128, 1024, 1235): + # warning if sum overflows, which it does in float16 + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter("always", RuntimeWarning) + + tgt = dt(v * (v + 1) / 2) + overflow = not np.isfinite(tgt) + assert_equal(len(w), 1 * overflow) + + d = np.arange(1, v + 1, dtype=dt) + + assert_almost_equal(np.sum(d), tgt) + assert_equal(len(w), 2 * overflow) + + assert_almost_equal(np.sum(d[::-1]), tgt) + assert_equal(len(w), 3 * overflow) + + d = np.ones(500, dtype=dt) + assert_almost_equal(np.sum(d[::2]), 250.) + assert_almost_equal(np.sum(d[1::2]), 250.) + assert_almost_equal(np.sum(d[::3]), 167.) + assert_almost_equal(np.sum(d[1::3]), 167.) + assert_almost_equal(np.sum(d[::-2]), 250.) + assert_almost_equal(np.sum(d[-1::-2]), 250.) + assert_almost_equal(np.sum(d[::-3]), 167.) + assert_almost_equal(np.sum(d[-1::-3]), 167.) + # sum with first reduction entry != 0 + d = np.ones((1,), dtype=dt) + d += d + assert_almost_equal(d, 2.) + + def test_sum_complex(self): + for dt in (np.complex64, np.complex128, np.clongdouble): + for v in (0, 1, 2, 7, 8, 9, 15, 16, 19, 127, + 128, 1024, 1235): + tgt = dt(v * (v + 1) / 2) - dt((v * (v + 1) / 2) * 1j) + d = np.empty(v, dtype=dt) + d.real = np.arange(1, v + 1) + d.imag = -np.arange(1, v + 1) + assert_almost_equal(np.sum(d), tgt) + assert_almost_equal(np.sum(d[::-1]), tgt) + + d = np.ones(500, dtype=dt) + 1j + assert_almost_equal(np.sum(d[::2]), 250. + 250j) + assert_almost_equal(np.sum(d[1::2]), 250. + 250j) + assert_almost_equal(np.sum(d[::3]), 167. + 167j) + assert_almost_equal(np.sum(d[1::3]), 167. + 167j) + assert_almost_equal(np.sum(d[::-2]), 250. + 250j) + assert_almost_equal(np.sum(d[-1::-2]), 250. + 250j) + assert_almost_equal(np.sum(d[::-3]), 167. + 167j) + assert_almost_equal(np.sum(d[-1::-3]), 167. + 167j) + # sum with first reduction entry != 0 + d = np.ones((1,), dtype=dt) + 1j + d += d + assert_almost_equal(d, 2. + 2j) + + def test_sum_initial(self): + # Integer, single axis + assert_equal(np.sum([3], initial=2), 5) + + # Floating point + assert_almost_equal(np.sum([0.2], initial=0.1), 0.3) + + # Multiple non-adjacent axes + assert_equal(np.sum(np.ones((2, 3, 5), dtype=np.int64), axis=(0, 2), initial=2), + [12, 12, 12]) + + def test_sum_where(self): + # More extensive tests done in test_reduction_with_where. + assert_equal(np.sum([[1., 2.], [3., 4.]], where=[True, False]), 4.) + assert_equal(np.sum([[1., 2.], [3., 4.]], axis=0, initial=5., + where=[True, False]), [9., 5.]) + + def test_vecdot(self): + arr1 = np.arange(6).reshape((2, 3)) + arr2 = np.arange(3).reshape((1, 3)) + + actual = np.vecdot(arr1, arr2) + expected = np.array([5, 14]) + + assert_array_equal(actual, expected) + + actual2 = np.vecdot(arr1.T, arr2.T, axis=-2) + assert_array_equal(actual2, expected) + + actual3 = np.vecdot(arr1.astype("object"), arr2) + assert_array_equal(actual3, expected.astype("object")) + + def test_matvec(self): + arr1 = np.arange(6).reshape((2, 3)) + arr2 = np.arange(3).reshape((1, 3)) + + actual = np.matvec(arr1, arr2) + expected = np.array([[5, 14]]) + + assert_array_equal(actual, expected) + + actual2 = np.matvec(arr1.T, arr2.T, axes=[(-1, -2), -2, -1]) + assert_array_equal(actual2, expected) + + actual3 = np.matvec(arr1.astype("object"), arr2) + assert_array_equal(actual3, expected.astype("object")) + + @pytest.mark.parametrize("vec", [ + np.array([[1., 2., 3.], [4., 5., 6.]]), + np.array([[1., 2j, 3.], [4., 5., 6j]]), + np.array([[1., 2., 3.], [4., 5., 6.]], dtype=object), + np.array([[1., 2j, 3.], [4., 5., 6j]], dtype=object)]) + @pytest.mark.parametrize("matrix", [ + None, + np.array([[1. + 1j, 0.5, -0.5j], + [0.25, 2j, 0.], + [4., 0., -1j]])]) + def test_vecmatvec_identity(self, matrix, vec): + """Check that (x†A)x equals x†(Ax).""" + mat = matrix if matrix is not None else np.eye(3) + matvec = np.matvec(mat, vec) # Ax + vecmat = np.vecmat(vec, mat) # x†A + if matrix is None: + assert_array_equal(matvec, vec) + assert_array_equal(vecmat.conj(), vec) + assert_array_equal(matvec, (mat @ vec[..., np.newaxis]).squeeze(-1)) + assert_array_equal(vecmat, (vec[..., np.newaxis].mT.conj() + @ mat).squeeze(-2)) + expected = np.einsum('...i,ij,...j', vec.conj(), mat, vec) + vec_matvec = (vec.conj() * matvec).sum(-1) + vecmat_vec = (vecmat * vec).sum(-1) + assert_array_equal(vec_matvec, expected) + assert_array_equal(vecmat_vec, expected) + + @pytest.mark.parametrize("ufunc, shape1, shape2, conj", [ + (np.vecdot, (3,), (3,), True), + (np.vecmat, (3,), (3, 1), True), + (np.matvec, (1, 3), (3,), False), + (np.matmul, (1, 3), (3, 1), False), + ]) + def test_vecdot_matvec_vecmat_complex(self, ufunc, shape1, shape2, conj): + arr1 = np.array([1, 2j, 3]) + arr2 = np.array([1, 2, 3]) + + actual1 = ufunc(arr1.reshape(shape1), arr2.reshape(shape2)) + expected1 = np.array(((arr1.conj() if conj else arr1) * arr2).sum(), + ndmin=min(len(shape1), len(shape2))) + assert_array_equal(actual1, expected1) + # This would fail for conj=True, since matmul omits the conjugate. + if not conj: + assert_array_equal(arr1.reshape(shape1) @ arr2.reshape(shape2), + expected1) + + actual2 = ufunc(arr2.reshape(shape1), arr1.reshape(shape2)) + expected2 = np.array(((arr2.conj() if conj else arr2) * arr1).sum(), + ndmin=min(len(shape1), len(shape2))) + assert_array_equal(actual2, expected2) + + actual3 = ufunc(arr1.reshape(shape1).astype("object"), + arr2.reshape(shape2).astype("object")) + expected3 = expected1.astype(object) + assert_array_equal(actual3, expected3) + + def test_vecdot_subclass(self): + class MySubclass(np.ndarray): + pass + + arr1 = np.arange(6).reshape((2, 3)).view(MySubclass) + arr2 = np.arange(3).reshape((1, 3)).view(MySubclass) + result = np.vecdot(arr1, arr2) + assert isinstance(result, MySubclass) + + def test_vecdot_object_no_conjugate(self): + arr = np.array(["1", "2"], dtype=object) + with pytest.raises(AttributeError, match="conjugate"): + np.vecdot(arr, arr) + + def test_vecdot_object_breaks_outer_loop_on_error(self): + arr1 = np.ones((3, 3)).astype(object) + arr2 = arr1.copy() + arr2[1, 1] = None + out = np.zeros(3).astype(object) + with pytest.raises(TypeError, match=r"\*: 'float' and 'NoneType'"): + np.vecdot(arr1, arr2, out=out) + assert out[0] == 3 + assert out[1] == out[2] == 0 + + def test_broadcast(self): + msg = "broadcast" + a = np.arange(4).reshape((2, 1, 2)) + b = np.arange(4).reshape((1, 2, 2)) + assert_array_equal(np.vecdot(a, b), np.sum(a * b, axis=-1), err_msg=msg) + msg = "extend & broadcast loop dimensions" + b = np.arange(4).reshape((2, 2)) + assert_array_equal(np.vecdot(a, b), np.sum(a * b, axis=-1), err_msg=msg) + # Broadcast in core dimensions should fail + a = np.arange(8).reshape((4, 2)) + b = np.arange(4).reshape((4, 1)) + assert_raises(ValueError, np.vecdot, a, b) + # Extend core dimensions should fail + a = np.arange(8).reshape((4, 2)) + b = np.array(7) + assert_raises(ValueError, np.vecdot, a, b) + # Broadcast should fail + a = np.arange(2).reshape((2, 1, 1)) + b = np.arange(3).reshape((3, 1, 1)) + assert_raises(ValueError, np.vecdot, a, b) + + # Writing to a broadcasted array with overlap should warn, gh-2705 + a = np.arange(2) + b = np.arange(4).reshape((2, 2)) + u, v = np.broadcast_arrays(a, b) + assert_equal(u.strides[0], 0) + x = u + v + with warnings.catch_warnings(record=True) as w: + warnings.simplefilter("always") + u += v + assert_equal(len(w), 1) + assert_(x[0, 0] != u[0, 0]) + + # Output reduction should not be allowed. + # See gh-15139 + a = np.arange(6).reshape(3, 2) + b = np.ones(2) + out = np.empty(()) + assert_raises(ValueError, np.vecdot, a, b, out) + out2 = np.empty(3) + c = np.vecdot(a, b, out2) + assert_(c is out2) + + def test_out_broadcasts(self): + # For ufuncs and gufuncs (not for reductions), we currently allow + # the output to cause broadcasting of the input arrays. + # both along dimensions with shape 1 and dimensions which do not + # exist at all in the inputs. + arr = np.arange(3).reshape(1, 3) + out = np.empty((5, 4, 3)) + np.add(arr, arr, out=out) + assert (out == np.arange(3) * 2).all() + + # The same holds for gufuncs (gh-16484) + np.vecdot(arr, arr, out=out) + # the result would be just a scalar `5`, but is broadcast fully: + assert (out == 5).all() + + @pytest.mark.parametrize(["arr", "out"], [ + ([2], np.empty(())), + ([1, 2], np.empty(1)), + (np.ones((4, 3)), np.empty((4, 1)))], + ids=["(1,)->()", "(2,)->(1,)", "(4, 3)->(4, 1)"]) + def test_out_broadcast_errors(self, arr, out): + # Output is (currently) allowed to broadcast inputs, but it cannot be + # smaller than the actual result. + with pytest.raises(ValueError, match="non-broadcastable"): + np.positive(arr, out=out) + + with pytest.raises(ValueError, match="non-broadcastable"): + np.add(np.ones(()), arr, out=out) + + def test_type_cast(self): + msg = "type cast" + a = np.arange(6, dtype='short').reshape((2, 3)) + assert_array_equal(np.vecdot(a, a), np.sum(a * a, axis=-1), + err_msg=msg) + msg = "type cast on one argument" + a = np.arange(6).reshape((2, 3)) + b = a + 0.1 + assert_array_almost_equal(np.vecdot(a, b), np.sum(a * b, axis=-1), + err_msg=msg) + + def test_endian(self): + msg = "big endian" + a = np.arange(6, dtype='>i4').reshape((2, 3)) + assert_array_equal(np.vecdot(a, a), np.sum(a * a, axis=-1), + err_msg=msg) + msg = "little endian" + a = np.arange(6, dtype='()' + a = np.arange(27.).reshape((3, 3, 3)) + b = np.arange(10., 19.).reshape((3, 1, 3)) + # basic tests on inputs (outputs tested below with matrix_multiply). + c = np.vecdot(a, b) + assert_array_equal(c, (a * b).sum(-1)) + # default + c = np.vecdot(a, b, axes=[(-1,), (-1,), ()]) + assert_array_equal(c, (a * b).sum(-1)) + # integers ok for single axis. + c = np.vecdot(a, b, axes=[-1, -1, ()]) + assert_array_equal(c, (a * b).sum(-1)) + # mix fine + c = np.vecdot(a, b, axes=[(-1,), -1, ()]) + assert_array_equal(c, (a * b).sum(-1)) + # can omit last axis. + c = np.vecdot(a, b, axes=[-1, -1]) + assert_array_equal(c, (a * b).sum(-1)) + # can pass in other types of integer (with __index__ protocol) + c = np.vecdot(a, b, axes=[np.int8(-1), np.array(-1, dtype=np.int32)]) + assert_array_equal(c, (a * b).sum(-1)) + # swap some axes + c = np.vecdot(a, b, axes=[0, 0]) + assert_array_equal(c, (a * b).sum(0)) + c = np.vecdot(a, b, axes=[0, 2]) + assert_array_equal(c, (a.transpose(1, 2, 0) * b).sum(-1)) + # Check errors for improperly constructed axes arguments. + # should have list. + assert_raises(TypeError, np.vecdot, a, b, axes=-1) + # needs enough elements + assert_raises(ValueError, np.vecdot, a, b, axes=[-1]) + # should pass in indices. + assert_raises(TypeError, np.vecdot, a, b, axes=[-1.0, -1.0]) + assert_raises(TypeError, np.vecdot, a, b, axes=[(-1.0,), -1]) + assert_raises(TypeError, np.vecdot, a, b, axes=[None, 1]) + # cannot pass an index unless there is only one dimension + # (output is wrong in this case) + assert_raises(AxisError, np.vecdot, a, b, axes=[-1, -1, -1]) + # or pass in generally the wrong number of axes + assert_raises(AxisError, np.vecdot, a, b, axes=[-1, -1, (-1,)]) + assert_raises(AxisError, np.vecdot, a, b, axes=[-1, (-2, -1), ()]) + # axes need to have same length. + assert_raises(ValueError, np.vecdot, a, b, axes=[0, 1]) + + # matrix_multiply signature: '(m,n),(n,p)->(m,p)' + mm = umt.matrix_multiply + a = np.arange(12).reshape((2, 3, 2)) + b = np.arange(8).reshape((2, 2, 2, 1)) + 1 + # Sanity check. + c = mm(a, b) + assert_array_equal(c, np.matmul(a, b)) + # Default axes. + c = mm(a, b, axes=[(-2, -1), (-2, -1), (-2, -1)]) + assert_array_equal(c, np.matmul(a, b)) + # Default with explicit axes. + c = mm(a, b, axes=[(1, 2), (2, 3), (2, 3)]) + assert_array_equal(c, np.matmul(a, b)) + # swap some axes. + c = mm(a, b, axes=[(0, -1), (1, 2), (-2, -1)]) + assert_array_equal(c, np.matmul(a.transpose(1, 0, 2), + b.transpose(0, 3, 1, 2))) + # Default with output array. + c = np.empty((2, 2, 3, 1)) + d = mm(a, b, out=c, axes=[(1, 2), (2, 3), (2, 3)]) + assert_(c is d) + assert_array_equal(c, np.matmul(a, b)) + # Transposed output array + c = np.empty((1, 2, 2, 3)) + d = mm(a, b, out=c, axes=[(-2, -1), (-2, -1), (3, 0)]) + assert_(c is d) + assert_array_equal(c, np.matmul(a, b).transpose(3, 0, 1, 2)) + # Check errors for improperly constructed axes arguments. + # wrong argument + assert_raises(TypeError, mm, a, b, axis=1) + # axes should be list + assert_raises(TypeError, mm, a, b, axes=1) + assert_raises(TypeError, mm, a, b, axes=((-2, -1), (-2, -1), (-2, -1))) + # list needs to have right length + assert_raises(ValueError, mm, a, b, axes=[]) + assert_raises(ValueError, mm, a, b, axes=[(-2, -1)]) + # list should not contain None, or lists + assert_raises(TypeError, mm, a, b, axes=[None, None, None]) + assert_raises(TypeError, + mm, a, b, axes=[[-2, -1], [-2, -1], [-2, -1]]) + assert_raises(TypeError, + mm, a, b, axes=[(-2, -1), (-2, -1), [-2, -1]]) + assert_raises(TypeError, mm, a, b, axes=[(-2, -1), (-2, -1), None]) + # single integers are AxisErrors if more are required + assert_raises(AxisError, mm, a, b, axes=[-1, -1, -1]) + assert_raises(AxisError, mm, a, b, axes=[(-2, -1), (-2, -1), -1]) + # tuples should not have duplicated values + assert_raises(ValueError, mm, a, b, axes=[(-2, -1), (-2, -1), (-2, -2)]) + # arrays should have enough axes. + z = np.zeros((2, 2)) + assert_raises(ValueError, mm, z, z[0]) + assert_raises(ValueError, mm, z, z, out=z[:, 0]) + assert_raises(ValueError, mm, z[1], z, axes=[0, 1]) + assert_raises(ValueError, mm, z, z, out=z[0], axes=[0, 1]) + # Regular ufuncs should not accept axes. + assert_raises(TypeError, np.add, 1., 1., axes=[0]) + # should be able to deal with bad unrelated kwargs. + assert_raises(TypeError, mm, z, z, axes=[0, 1], parrot=True) + + def test_axis_argument(self): + # vecdot signature: '(n),(n)->()' + a = np.arange(27.).reshape((3, 3, 3)) + b = np.arange(10., 19.).reshape((3, 1, 3)) + c = np.vecdot(a, b) + assert_array_equal(c, (a * b).sum(-1)) + c = np.vecdot(a, b, axis=-1) + assert_array_equal(c, (a * b).sum(-1)) + out = np.zeros_like(c) + d = np.vecdot(a, b, axis=-1, out=out) + assert_(d is out) + assert_array_equal(d, c) + c = np.vecdot(a, b, axis=0) + assert_array_equal(c, (a * b).sum(0)) + # Sanity checks on innerwt and cumsum. + a = np.arange(6).reshape((2, 3)) + b = np.arange(10, 16).reshape((2, 3)) + w = np.arange(20, 26).reshape((2, 3)) + assert_array_equal(umt.innerwt(a, b, w, axis=0), + np.sum(a * b * w, axis=0)) + assert_array_equal(umt.cumsum(a, axis=0), np.cumsum(a, axis=0)) + assert_array_equal(umt.cumsum(a, axis=-1), np.cumsum(a, axis=-1)) + out = np.empty_like(a) + b = umt.cumsum(a, out=out, axis=0) + assert_(out is b) + assert_array_equal(b, np.cumsum(a, axis=0)) + b = umt.cumsum(a, out=out, axis=1) + assert_(out is b) + assert_array_equal(b, np.cumsum(a, axis=-1)) + # Check errors. + # Cannot pass in both axis and axes. + assert_raises(TypeError, np.vecdot, a, b, axis=0, axes=[0, 0]) + # Not an integer. + assert_raises(TypeError, np.vecdot, a, b, axis=[0]) + # more than 1 core dimensions. + mm = umt.matrix_multiply + assert_raises(TypeError, mm, a, b, axis=1) + # Output wrong size in axis. + out = np.empty((1, 2, 3), dtype=a.dtype) + assert_raises(ValueError, umt.cumsum, a, out=out, axis=0) + # Regular ufuncs should not accept axis. + assert_raises(TypeError, np.add, 1., 1., axis=0) + + def test_keepdims_argument(self): + # vecdot signature: '(n),(n)->()' + a = np.arange(27.).reshape((3, 3, 3)) + b = np.arange(10., 19.).reshape((3, 1, 3)) + c = np.vecdot(a, b) + assert_array_equal(c, (a * b).sum(-1)) + c = np.vecdot(a, b, keepdims=False) + assert_array_equal(c, (a * b).sum(-1)) + c = np.vecdot(a, b, keepdims=True) + assert_array_equal(c, (a * b).sum(-1, keepdims=True)) + out = np.zeros_like(c) + d = np.vecdot(a, b, keepdims=True, out=out) + assert_(d is out) + assert_array_equal(d, c) + # Now combined with axis and axes. + c = np.vecdot(a, b, axis=-1, keepdims=False) + assert_array_equal(c, (a * b).sum(-1, keepdims=False)) + c = np.vecdot(a, b, axis=-1, keepdims=True) + assert_array_equal(c, (a * b).sum(-1, keepdims=True)) + c = np.vecdot(a, b, axis=0, keepdims=False) + assert_array_equal(c, (a * b).sum(0, keepdims=False)) + c = np.vecdot(a, b, axis=0, keepdims=True) + assert_array_equal(c, (a * b).sum(0, keepdims=True)) + c = np.vecdot(a, b, axes=[(-1,), (-1,), ()], keepdims=False) + assert_array_equal(c, (a * b).sum(-1)) + c = np.vecdot(a, b, axes=[(-1,), (-1,), (-1,)], keepdims=True) + assert_array_equal(c, (a * b).sum(-1, keepdims=True)) + c = np.vecdot(a, b, axes=[0, 0], keepdims=False) + assert_array_equal(c, (a * b).sum(0)) + c = np.vecdot(a, b, axes=[0, 0, 0], keepdims=True) + assert_array_equal(c, (a * b).sum(0, keepdims=True)) + c = np.vecdot(a, b, axes=[0, 2], keepdims=False) + assert_array_equal(c, (a.transpose(1, 2, 0) * b).sum(-1)) + c = np.vecdot(a, b, axes=[0, 2], keepdims=True) + assert_array_equal(c, (a.transpose(1, 2, 0) * b).sum(-1, + keepdims=True)) + c = np.vecdot(a, b, axes=[0, 2, 2], keepdims=True) + assert_array_equal(c, (a.transpose(1, 2, 0) * b).sum(-1, + keepdims=True)) + c = np.vecdot(a, b, axes=[0, 2, 0], keepdims=True) + assert_array_equal(c, (a * b.transpose(2, 0, 1)).sum(0, keepdims=True)) + # Hardly useful, but should work. + c = np.vecdot(a, b, axes=[0, 2, 1], keepdims=True) + assert_array_equal(c, (a.transpose(1, 0, 2) * b.transpose(0, 2, 1)) + .sum(1, keepdims=True)) + # Check with two core dimensions. + a = np.eye(3) * np.arange(4.)[:, np.newaxis, np.newaxis] + expected = uml.det(a) + c = uml.det(a, keepdims=False) + assert_array_equal(c, expected) + c = uml.det(a, keepdims=True) + assert_array_equal(c, expected[:, np.newaxis, np.newaxis]) + a = np.eye(3) * np.arange(4.)[:, np.newaxis, np.newaxis] + expected_s, expected_l = uml.slogdet(a) + cs, cl = uml.slogdet(a, keepdims=False) + assert_array_equal(cs, expected_s) + assert_array_equal(cl, expected_l) + cs, cl = uml.slogdet(a, keepdims=True) + assert_array_equal(cs, expected_s[:, np.newaxis, np.newaxis]) + assert_array_equal(cl, expected_l[:, np.newaxis, np.newaxis]) + # Sanity check on innerwt. + a = np.arange(6).reshape((2, 3)) + b = np.arange(10, 16).reshape((2, 3)) + w = np.arange(20, 26).reshape((2, 3)) + assert_array_equal(umt.innerwt(a, b, w, keepdims=True), + np.sum(a * b * w, axis=-1, keepdims=True)) + assert_array_equal(umt.innerwt(a, b, w, axis=0, keepdims=True), + np.sum(a * b * w, axis=0, keepdims=True)) + # Check errors. + # Not a boolean + assert_raises(TypeError, np.vecdot, a, b, keepdims='true') + # More than 1 core dimension, and core output dimensions. + mm = umt.matrix_multiply + assert_raises(TypeError, mm, a, b, keepdims=True) + assert_raises(TypeError, mm, a, b, keepdims=False) + # Regular ufuncs should not accept keepdims. + assert_raises(TypeError, np.add, 1., 1., keepdims=False) + + def test_innerwt(self): + a = np.arange(6).reshape((2, 3)) + b = np.arange(10, 16).reshape((2, 3)) + w = np.arange(20, 26).reshape((2, 3)) + assert_array_equal(umt.innerwt(a, b, w), np.sum(a * b * w, axis=-1)) + a = np.arange(100, 124).reshape((2, 3, 4)) + b = np.arange(200, 224).reshape((2, 3, 4)) + w = np.arange(300, 324).reshape((2, 3, 4)) + assert_array_equal(umt.innerwt(a, b, w), np.sum(a * b * w, axis=-1)) + + def test_innerwt_empty(self): + """Test generalized ufunc with zero-sized operands""" + a = np.array([], dtype='f8') + b = np.array([], dtype='f8') + w = np.array([], dtype='f8') + assert_array_equal(umt.innerwt(a, b, w), np.sum(a * b * w, axis=-1)) + + def test_cross1d(self): + """Test with fixed-sized signature.""" + a = np.eye(3) + assert_array_equal(umt.cross1d(a, a), np.zeros((3, 3))) + out = np.zeros((3, 3)) + result = umt.cross1d(a[0], a, out) + assert_(result is out) + assert_array_equal(result, np.vstack((np.zeros(3), a[2], -a[1]))) + assert_raises(ValueError, umt.cross1d, np.eye(4), np.eye(4)) + assert_raises(ValueError, umt.cross1d, a, np.arange(4.)) + # Wrong output core dimension. + assert_raises(ValueError, umt.cross1d, a, np.arange(3.), np.zeros((3, 4))) + # Wrong output broadcast dimension (see gh-15139). + assert_raises(ValueError, umt.cross1d, a, np.arange(3.), np.zeros(3)) + + def test_can_ignore_signature(self): + # Comparing the effects of ? in signature: + # matrix_multiply: (m,n),(n,p)->(m,p) # all must be there. + # matmul: (m?,n),(n,p?)->(m?,p?) # allow missing m, p. + mat = np.arange(12).reshape((2, 3, 2)) + single_vec = np.arange(2) + col_vec = single_vec[:, np.newaxis] + col_vec_array = np.arange(8).reshape((2, 2, 2, 1)) + 1 + # matrix @ single column vector with proper dimension + mm_col_vec = umt.matrix_multiply(mat, col_vec) + # matmul does the same thing + matmul_col_vec = umt.matmul(mat, col_vec) + assert_array_equal(matmul_col_vec, mm_col_vec) + # matrix @ vector without dimension making it a column vector. + # matrix multiply fails -> missing core dim. + assert_raises(ValueError, umt.matrix_multiply, mat, single_vec) + # matmul mimicker passes, and returns a vector. + matmul_col = umt.matmul(mat, single_vec) + assert_array_equal(matmul_col, mm_col_vec.squeeze()) + # Now with a column array: same as for column vector, + # broadcasting sensibly. + mm_col_vec = umt.matrix_multiply(mat, col_vec_array) + matmul_col_vec = umt.matmul(mat, col_vec_array) + assert_array_equal(matmul_col_vec, mm_col_vec) + # As above, but for row vector + single_vec = np.arange(3) + row_vec = single_vec[np.newaxis, :] + row_vec_array = np.arange(24).reshape((4, 2, 1, 1, 3)) + 1 + # row vector @ matrix + mm_row_vec = umt.matrix_multiply(row_vec, mat) + matmul_row_vec = umt.matmul(row_vec, mat) + assert_array_equal(matmul_row_vec, mm_row_vec) + # single row vector @ matrix + assert_raises(ValueError, umt.matrix_multiply, single_vec, mat) + matmul_row = umt.matmul(single_vec, mat) + assert_array_equal(matmul_row, mm_row_vec.squeeze()) + # row vector array @ matrix + mm_row_vec = umt.matrix_multiply(row_vec_array, mat) + matmul_row_vec = umt.matmul(row_vec_array, mat) + assert_array_equal(matmul_row_vec, mm_row_vec) + # Now for vector combinations + # row vector @ column vector + col_vec = row_vec.T + col_vec_array = row_vec_array.swapaxes(-2, -1) + mm_row_col_vec = umt.matrix_multiply(row_vec, col_vec) + matmul_row_col_vec = umt.matmul(row_vec, col_vec) + assert_array_equal(matmul_row_col_vec, mm_row_col_vec) + # single row vector @ single col vector + assert_raises(ValueError, umt.matrix_multiply, single_vec, single_vec) + matmul_row_col = umt.matmul(single_vec, single_vec) + assert_array_equal(matmul_row_col, mm_row_col_vec.squeeze()) + # row vector array @ matrix + mm_row_col_array = umt.matrix_multiply(row_vec_array, col_vec_array) + matmul_row_col_array = umt.matmul(row_vec_array, col_vec_array) + assert_array_equal(matmul_row_col_array, mm_row_col_array) + # Finally, check that things are *not* squeezed if one gives an + # output. + out = np.zeros_like(mm_row_col_array) + out = umt.matrix_multiply(row_vec_array, col_vec_array, out=out) + assert_array_equal(out, mm_row_col_array) + out[:] = 0 + out = umt.matmul(row_vec_array, col_vec_array, out=out) + assert_array_equal(out, mm_row_col_array) + # And check one cannot put missing dimensions back. + out = np.zeros_like(mm_row_col_vec) + assert_raises(ValueError, umt.matrix_multiply, single_vec, single_vec, + out) + # But fine for matmul, since it is just a broadcast. + out = umt.matmul(single_vec, single_vec, out) + assert_array_equal(out, mm_row_col_vec.squeeze()) + + def test_matrix_multiply(self): + self.compare_matrix_multiply_results(np.int64) + self.compare_matrix_multiply_results(np.double) + + def test_matrix_multiply_umath_empty(self): + res = umt.matrix_multiply(np.ones((0, 10)), np.ones((10, 0))) + assert_array_equal(res, np.zeros((0, 0))) + res = umt.matrix_multiply(np.ones((10, 0)), np.ones((0, 10))) + assert_array_equal(res, np.zeros((10, 10))) + + def compare_matrix_multiply_results(self, tp): + d1 = np.array(np.random.rand(2, 3, 4), dtype=tp) + d2 = np.array(np.random.rand(2, 3, 4), dtype=tp) + msg = f"matrix multiply on type {d1.dtype.name}" + + def permute_n(n): + if n == 1: + return ([0],) + ret = () + base = permute_n(n - 1) + for perm in base: + for i in range(n): + new = perm + [n - 1] + new[n - 1] = new[i] + new[i] = n - 1 + ret += (new,) + return ret + + def slice_n(n): + if n == 0: + return ((),) + ret = () + base = slice_n(n - 1) + for sl in base: + ret += (sl + (slice(None),),) + ret += (sl + (slice(0, 1),),) + return ret + + def broadcastable(s1, s2): + return s1 == s2 or 1 in {s1, s2} + + permute_3 = permute_n(3) + slice_3 = slice_n(3) + ((slice(None, None, -1),) * 3,) + + ref = True + for p1 in permute_3: + for p2 in permute_3: + for s1 in slice_3: + for s2 in slice_3: + a1 = d1.transpose(p1)[s1] + a2 = d2.transpose(p2)[s2] + ref = ref and a1.base is not None + ref = ref and a2.base is not None + if (a1.shape[-1] == a2.shape[-2] and + broadcastable(a1.shape[0], a2.shape[0])): + assert_array_almost_equal( + umt.matrix_multiply(a1, a2), + np.sum(a2[..., np.newaxis].swapaxes(-3, -1) * + a1[..., np.newaxis, :], axis=-1), + err_msg=msg + f' {str(a1.shape)} {str(a2.shape)}') + + assert_equal(ref, True, err_msg="reference check") + + def test_euclidean_pdist(self): + a = np.arange(12, dtype=float).reshape(4, 3) + out = np.empty((a.shape[0] * (a.shape[0] - 1) // 2,), dtype=a.dtype) + umt.euclidean_pdist(a, out) + b = np.sqrt(np.sum((a[:, None] - a)**2, axis=-1)) + b = b[~np.tri(a.shape[0], dtype=bool)] + assert_almost_equal(out, b) + # An output array is required to determine p with signature (n,d)->(p) + assert_raises(ValueError, umt.euclidean_pdist, a) + + def test_cumsum(self): + a = np.arange(10) + result = umt.cumsum(a) + assert_array_equal(result, a.cumsum()) + + def test_object_logical(self): + a = np.array([3, None, True, False, "test", ""], dtype=object) + assert_equal(np.logical_or(a, None), + np.array([x or None for x in a], dtype=object)) + assert_equal(np.logical_or(a, True), + np.array([x or True for x in a], dtype=object)) + assert_equal(np.logical_or(a, 12), + np.array([x or 12 for x in a], dtype=object)) + assert_equal(np.logical_or(a, "blah"), + np.array([x or "blah" for x in a], dtype=object)) + + assert_equal(np.logical_and(a, None), + np.array([x and None for x in a], dtype=object)) + assert_equal(np.logical_and(a, True), + np.array([x and True for x in a], dtype=object)) + assert_equal(np.logical_and(a, 12), + np.array([x and 12 for x in a], dtype=object)) + assert_equal(np.logical_and(a, "blah"), + np.array([x and "blah" for x in a], dtype=object)) + + assert_equal(np.logical_not(a), + np.array([not x for x in a], dtype=object)) + + assert_equal(np.logical_or.reduce(a), 3) + assert_equal(np.logical_and.reduce(a), None) + + def test_object_comparison(self): + class HasComparisons: + def __eq__(self, other): + return '==' + + arr0d = np.array(HasComparisons()) + assert_equal(arr0d == arr0d, True) + assert_equal(np.equal(arr0d, arr0d), True) # normal behavior is a cast + + arr1d = np.array([HasComparisons()]) + assert_equal(arr1d == arr1d, np.array([True])) + # normal behavior is a cast + assert_equal(np.equal(arr1d, arr1d), np.array([True])) + assert_equal(np.equal(arr1d, arr1d, dtype=object), np.array(['=='])) + + def test_object_array_reduction(self): + # Reductions on object arrays + a = np.array(['a', 'b', 'c'], dtype=object) + assert_equal(np.sum(a), 'abc') + assert_equal(np.max(a), 'c') + assert_equal(np.min(a), 'a') + a = np.array([True, False, True], dtype=object) + assert_equal(np.sum(a), 2) + assert_equal(np.prod(a), 0) + assert_equal(np.any(a), True) + assert_equal(np.all(a), False) + assert_equal(np.max(a), True) + assert_equal(np.min(a), False) + assert_equal(np.array([[1]], dtype=object).sum(), 1) + assert_equal(np.array([[[1, 2]]], dtype=object).sum((0, 1)), [1, 2]) + assert_equal(np.array([1], dtype=object).sum(initial=1), 2) + assert_equal(np.array([[1], [2, 3]], dtype=object) + .sum(initial=[0], where=[False, True]), [0, 2, 3]) + + def test_object_array_accumulate_inplace(self): + # Checks that in-place accumulates work, see also gh-7402 + arr = np.ones(4, dtype=object) + arr[:] = [[1] for i in range(4)] + # Twice reproduced also for tuples: + np.add.accumulate(arr, out=arr) + np.add.accumulate(arr, out=arr) + assert_array_equal(arr, + np.array([[1] * i for i in [1, 3, 6, 10]], dtype=object), + ) + + # And the same if the axis argument is used + arr = np.ones((2, 4), dtype=object) + arr[0, :] = [[2] for i in range(4)] + np.add.accumulate(arr, out=arr, axis=-1) + np.add.accumulate(arr, out=arr, axis=-1) + assert_array_equal(arr[0, :], + np.array([[2] * i for i in [1, 3, 6, 10]], dtype=object), + ) + + def test_object_array_accumulate_failure(self): + # Typical accumulation on object works as expected: + res = np.add.accumulate(np.array([1, 0, 2], dtype=object)) + assert_array_equal(res, np.array([1, 1, 3], dtype=object)) + # But errors are propagated from the inner-loop if they occur: + with pytest.raises(TypeError): + np.add.accumulate([1, None, 2]) + + def test_object_array_reduceat_inplace(self): + # Checks that in-place reduceats work, see also gh-7465 + arr = np.empty(4, dtype=object) + arr[:] = [[1] for i in range(4)] + out = np.empty(4, dtype=object) + out[:] = [[1] for i in range(4)] + np.add.reduceat(arr, np.arange(4), out=arr) + np.add.reduceat(arr, np.arange(4), out=arr) + assert_array_equal(arr, out) + + # And the same if the axis argument is used + arr = np.ones((2, 4), dtype=object) + arr[0, :] = [[2] for i in range(4)] + out = np.ones((2, 4), dtype=object) + out[0, :] = [[2] for i in range(4)] + np.add.reduceat(arr, np.arange(4), out=arr, axis=-1) + np.add.reduceat(arr, np.arange(4), out=arr, axis=-1) + assert_array_equal(arr, out) + + def test_object_array_reduceat_failure(self): + # Reduceat works as expected when no invalid operation occurs (None is + # not involved in an operation here) + res = np.add.reduceat(np.array([1, None, 2], dtype=object), [1, 2]) + assert_array_equal(res, np.array([None, 2], dtype=object)) + # But errors when None would be involved in an operation: + with pytest.raises(TypeError): + np.add.reduceat([1, None, 2], [0, 2]) + + def test_zerosize_reduction(self): + # Test with default dtype and object dtype + for a in [[], np.array([], dtype=object)]: + assert_equal(np.sum(a), 0) + assert_equal(np.prod(a), 1) + assert_equal(np.any(a), False) + assert_equal(np.all(a), True) + assert_raises(ValueError, np.max, a) + assert_raises(ValueError, np.min, a) + + def test_axis_out_of_bounds(self): + a = np.array([False, False]) + assert_raises(AxisError, a.all, axis=1) + a = np.array([False, False]) + assert_raises(AxisError, a.all, axis=-2) + + a = np.array([False, False]) + assert_raises(AxisError, a.any, axis=1) + a = np.array([False, False]) + assert_raises(AxisError, a.any, axis=-2) + + def test_scalar_reduction(self): + # The functions 'sum', 'prod', etc allow specifying axis=0 + # even for scalars + assert_equal(np.sum(3, axis=0), 3) + assert_equal(np.prod(3.5, axis=0), 3.5) + assert_equal(np.any(True, axis=0), True) + assert_equal(np.all(False, axis=0), False) + assert_equal(np.max(3, axis=0), 3) + assert_equal(np.min(2.5, axis=0), 2.5) + + # Check scalar behaviour for ufuncs without an identity + assert_equal(np.power.reduce(3), 3) + + # Make sure that scalars are coming out from this operation + assert_(type(np.prod(np.float32(2.5), axis=0)) is np.float32) + assert_(type(np.sum(np.float32(2.5), axis=0)) is np.float32) + assert_(type(np.max(np.float32(2.5), axis=0)) is np.float32) + assert_(type(np.min(np.float32(2.5), axis=0)) is np.float32) + + # check if scalars/0-d arrays get cast + assert_(type(np.any(0, axis=0)) is np.bool) + + # assert that 0-d arrays get wrapped + class MyArray(np.ndarray): + pass + a = np.array(1).view(MyArray) + assert_(type(np.any(a)) is MyArray) + + def test_casting_out_param(self): + # Test that it's possible to do casts on output + a = np.ones((200, 100), np.int64) + b = np.ones((200, 100), np.int64) + c = np.ones((200, 100), np.float64) + np.add(a, b, out=c) + assert_equal(c, 2) + + a = np.zeros(65536) + b = np.zeros(65536, dtype=np.float32) + np.subtract(a, 0, out=b) + assert_equal(b, 0) + + def test_where_param(self): + # Test that the where= ufunc parameter works with regular arrays + a = np.arange(7) + b = np.ones(7) + c = np.zeros(7) + np.add(a, b, out=c, where=(a % 2 == 1)) + assert_equal(c, [0, 2, 0, 4, 0, 6, 0]) + + a = np.arange(4).reshape(2, 2) + 2 + np.power(a, [2, 3], out=a, where=[[0, 1], [1, 0]]) + assert_equal(a, [[2, 27], [16, 5]]) + # Broadcasting the where= parameter + np.subtract(a, 2, out=a, where=[True, False]) + assert_equal(a, [[0, 27], [14, 5]]) + + def test_where_param_buffer_output(self): + # With casting on output + a = np.ones(10, np.int64) + b = np.ones(10, np.int64) + c = 1.5 * np.ones(10, np.float64) + np.add(a, b, out=c, where=[1, 0, 0, 1, 0, 0, 1, 1, 1, 0]) + assert_equal(c, [2, 1.5, 1.5, 2, 1.5, 1.5, 2, 2, 2, 1.5]) + + def test_where_param_alloc(self): + # With casting and allocated output + a = np.array([1], dtype=np.int64) + m = np.array([True], dtype=bool) + assert_equal(np.sqrt(a, where=m, out=None), [1]) + + # No casting and allocated output + a = np.array([1], dtype=np.float64) + m = np.array([True], dtype=bool) + assert_equal(np.sqrt(a, where=m, out=None), [1]) + + def test_where_with_broadcasting(self): + # See gh-17198 + a = np.random.random((5000, 4)) + b = np.random.random((5000, 1)) + + where = a > 0.3 + out = np.full_like(a, 0) + np.less(a, b, where=where, out=out) + b_where = np.broadcast_to(b, a.shape)[where] + assert_array_equal((a[where] < b_where), out[where].astype(bool)) + assert not out[~where].any() # outside mask, out remains all 0 + + def test_where_warns(self): + a = np.arange(7) + mask = a % 2 == 0 + with pytest.warns(UserWarning, match="'where' used without 'out'"): + result1 = np.add(a, a, where=mask) + # Does not warn + result2 = np.add(a, a, where=mask, out=None) + # Sanity check + assert np.all(result1[::2] == [0, 4, 8, 12]) + assert np.all(result2[::2] == [0, 4, 8, 12]) + # Also no warning for where=True + result3 = np.add(a, a, where=True) + # Sanity check + assert_array_equal(result3, a + a) + + @staticmethod + def identityless_reduce_arrs(): + yield np.empty((2, 3, 4), order='C') + yield np.empty((2, 3, 4), order='F') + # Mixed order (reduce order differs outer) + yield np.empty((2, 4, 3), order='C').swapaxes(1, 2) + # Reversed order + yield np.empty((2, 3, 4), order='C')[::-1, ::-1, ::-1] + # Not contiguous + yield np.empty((3, 5, 4), order='C').swapaxes(1, 2)[1:, 1:, 1:] + # Not contiguous and not aligned + a = np.empty((3 * 4 * 5 * 8 + 1,), dtype='i1') + a = a[1:].view(dtype='f8') + a.shape = (3, 4, 5) + a = a[1:, 1:, 1:] + yield a + + @pytest.mark.parametrize("arrs", identityless_reduce_arrs()) + @pytest.mark.parametrize("pos", [(1, 0, 0), (0, 1, 0), (0, 0, 1)]) + def test_identityless_reduction(self, arrs, pos): + # np.minimum.reduce is an identityless reduction + a = arrs.copy() + a[...] = 1 + a[pos] = 0 + + for axis in [None, (0, 1), (0, 2), (1, 2), 0, 1, 2, ()]: + if axis is None: + axes = np.array([], dtype=np.intp) + else: + axes = np.delete(np.arange(a.ndim), axis) + + expected_pos = tuple(np.array(pos)[axes]) + expected = np.ones(np.array(a.shape)[axes]) + expected[expected_pos] = 0 + + res = np.minimum.reduce(a, axis=axis) + assert_equal(res, expected, strict=True) + + res = np.full_like(res, np.nan) + np.minimum.reduce(a, axis=axis, out=res) + assert_equal(res, expected, strict=True) + + @requires_memory(6 * 1024**3) + @pytest.mark.skipif(sys.maxsize < 2**32, + reason="test array too large for 32bit platform") + @pytest.mark.thread_unsafe(reason="crashes with low memory") + def test_identityless_reduction_huge_array(self): + # Regression test for gh-20921 (copying identity incorrectly failed) + arr = np.zeros((2, 2**31), 'uint8') + arr[:, 0] = [1, 3] + arr[:, -1] = [4, 1] + res = np.maximum.reduce(arr, axis=0) + del arr + assert res[0] == 3 + assert res[-1] == 4 + + def test_reduce_identity_depends_on_loop(self): + """ + The type of the result should always depend on the selected loop, not + necessarily the output (only relevant for object arrays). + """ + # For an object loop, the default value 0 with type int is used: + assert type(np.add.reduce([], dtype=object)) is int + out = np.array(None, dtype=object) + # When the loop is float64 but `out` is object this does not happen, + # the result is float64 cast to object (which gives Python `float`). + np.add.reduce([], out=out, dtype=np.float64) + assert type(out[()]) is float + + def test_initial_reduction(self): + # np.minimum.reduce is an identityless reduction + + # For cases like np.maximum(np.abs(...), initial=0) + # More generally, a supremum over non-negative numbers. + assert_equal(np.maximum.reduce([], initial=0), 0) + + # For cases like reduction of an empty array over the reals. + assert_equal(np.minimum.reduce([], initial=np.inf), np.inf) + assert_equal(np.maximum.reduce([], initial=-np.inf), -np.inf) + + # Random tests + assert_equal(np.minimum.reduce([5], initial=4), 4) + assert_equal(np.maximum.reduce([4], initial=5), 5) + assert_equal(np.maximum.reduce([5], initial=4), 5) + assert_equal(np.minimum.reduce([4], initial=5), 4) + + # Check initial=None raises ValueError for both types of ufunc reductions + assert_raises(ValueError, np.minimum.reduce, [], initial=None) + assert_raises(ValueError, np.add.reduce, [], initial=None) + # Also in the somewhat special object case: + with pytest.raises(ValueError): + np.add.reduce([], initial=None, dtype=object) + + # Check that np._NoValue gives default behavior. + assert_equal(np.add.reduce([], initial=np._NoValue), 0) + + # Check that initial kwarg behaves as intended for dtype=object + a = np.array([10], dtype=object) + res = np.add.reduce(a, initial=5) + assert_equal(res, 15) + + def test_empty_reduction_and_identity(self): + arr = np.zeros((0, 5)) + # OK, since the reduction itself is *not* empty, the result is + assert np.true_divide.reduce(arr, axis=1).shape == (0,) + # Not OK, the reduction itself is empty and we have no identity + with pytest.raises(ValueError): + np.true_divide.reduce(arr, axis=0) + + # Test that an empty reduction fails also if the result is empty + arr = np.zeros((0, 0, 5)) + with pytest.raises(ValueError): + np.true_divide.reduce(arr, axis=1) + + # Division reduction makes sense with `initial=1` (empty or not): + res = np.true_divide.reduce(arr, axis=1, initial=1) + assert_array_equal(res, np.ones((0, 5))) + + @pytest.mark.parametrize('axis', (0, 1, None)) + @pytest.mark.parametrize('where', (np.array([False, True, True]), + np.array([[True], [False], [True]]), + np.array([[True, False, False], + [False, True, False], + [False, True, True]]))) + def test_reduction_with_where(self, axis, where): + a = np.arange(9.).reshape(3, 3) + a_copy = a.copy() + a_check = np.zeros_like(a) + np.positive(a, out=a_check, where=where) + + res = np.add.reduce(a, axis=axis, where=where) + check = a_check.sum(axis) + assert_equal(res, check) + # Check we do not overwrite elements of a internally. + assert_array_equal(a, a_copy) + + @pytest.mark.parametrize(('axis', 'where'), + ((0, np.array([True, False, True])), + (1, [True, True, False]), + (None, True))) + @pytest.mark.parametrize('initial', (-np.inf, 5.)) + def test_reduction_with_where_and_initial(self, axis, where, initial): + a = np.arange(9.).reshape(3, 3) + a_copy = a.copy() + a_check = np.full(a.shape, -np.inf) + np.positive(a, out=a_check, where=where) + + res = np.maximum.reduce(a, axis=axis, where=where, initial=initial) + check = a_check.max(axis, initial=initial) + assert_equal(res, check) + + def test_reduction_where_initial_needed(self): + a = np.arange(9.).reshape(3, 3) + m = [False, True, False] + assert_raises(ValueError, np.maximum.reduce, a, where=m) + + def test_identityless_reduction_nonreorderable(self): + a = np.array([[8.0, 2.0, 2.0], [1.0, 0.5, 0.25]]) + + res = np.divide.reduce(a, axis=0) + assert_equal(res, [8.0, 4.0, 8.0]) + + res = np.divide.reduce(a, axis=1) + assert_equal(res, [2.0, 8.0]) + + res = np.divide.reduce(a, axis=()) + assert_equal(res, a) + + assert_raises(ValueError, np.divide.reduce, a, axis=(0, 1)) + + def test_reduce_zero_axis(self): + # If we have an n x m array and do a reduction with axis=1, then we are + # doing n reductions, and each reduction takes an m-element array. For + # a reduction operation without an identity, then: + # n > 0, m > 0: fine + # n = 0, m > 0: fine, doing 0 reductions of m-element arrays + # n > 0, m = 0: can't reduce a 0-element array, ValueError + # n = 0, m = 0: can't reduce a 0-element array, ValueError (for + # consistency with the above case) + # This test doesn't actually look at return values, it just checks to + # make sure that error we get an error in exactly those cases where we + # expect one, and assumes the calculations themselves are done + # correctly. + + def ok(f, *args, **kwargs): + f(*args, **kwargs) + + def err(f, *args, **kwargs): + assert_raises(ValueError, f, *args, **kwargs) + + def t(expect, func, n, m): + expect(func, np.zeros((n, m)), axis=1) + expect(func, np.zeros((m, n)), axis=0) + expect(func, np.zeros((n // 2, n // 2, m)), axis=2) + expect(func, np.zeros((n // 2, m, n // 2)), axis=1) + expect(func, np.zeros((n, m // 2, m // 2)), axis=(1, 2)) + expect(func, np.zeros((m // 2, n, m // 2)), axis=(0, 2)) + expect(func, np.zeros((m // 3, m // 3, m // 3, + n // 2, n // 2)), + axis=(0, 1, 2)) + # Check what happens if the inner (resp. outer) dimensions are a + # mix of zero and non-zero: + expect(func, np.zeros((10, m, n)), axis=(0, 1)) + expect(func, np.zeros((10, n, m)), axis=(0, 2)) + expect(func, np.zeros((m, 10, n)), axis=0) + expect(func, np.zeros((10, m, n)), axis=1) + expect(func, np.zeros((10, n, m)), axis=2) + + # np.maximum is just an arbitrary ufunc with no reduction identity + assert_equal(np.maximum.identity, None) + t(ok, np.maximum.reduce, 30, 30) + t(ok, np.maximum.reduce, 0, 30) + t(err, np.maximum.reduce, 30, 0) + t(err, np.maximum.reduce, 0, 0) + err(np.maximum.reduce, []) + np.maximum.reduce(np.zeros((0, 0)), axis=()) + + # all of the combinations are fine for a reduction that has an + # identity + t(ok, np.add.reduce, 30, 30) + t(ok, np.add.reduce, 0, 30) + t(ok, np.add.reduce, 30, 0) + t(ok, np.add.reduce, 0, 0) + np.add.reduce([]) + np.add.reduce(np.zeros((0, 0)), axis=()) + + # OTOH, accumulate always makes sense for any combination of n and m, + # because it maps an m-element array to an m-element array. These + # tests are simpler because accumulate doesn't accept multiple axes. + for uf in (np.maximum, np.add): + uf.accumulate(np.zeros((30, 0)), axis=0) + uf.accumulate(np.zeros((0, 30)), axis=0) + uf.accumulate(np.zeros((30, 30)), axis=0) + uf.accumulate(np.zeros((0, 0)), axis=0) + + def test_safe_casting(self): + # In old versions of numpy, in-place operations used the 'unsafe' + # casting rules. In versions >= 1.10, 'same_kind' is the + # default and an exception is raised instead of a warning. + # when 'same_kind' is not satisfied. + a = np.array([1, 2, 3], dtype=int) + # Non-in-place addition is fine + assert_array_equal(assert_no_warnings(np.add, a, 1.1), + [2.1, 3.1, 4.1]) + assert_raises(TypeError, np.add, a, 1.1, out=a) + + def add_inplace(a, b): + a += b + + assert_raises(TypeError, add_inplace, a, 1.1) + # Make sure that explicitly overriding the exception is allowed: + assert_no_warnings(np.add, a, 1.1, out=a, casting="unsafe") + assert_array_equal(a, [2, 3, 4]) + + def test_ufunc_custom_out(self): + # Test ufunc with built in input types and custom output type + + a = np.array([0, 1, 2], dtype='i8') + b = np.array([0, 1, 2], dtype='i8') + c = np.empty(3, dtype=_rational_tests.rational) + + # Output must be specified so numpy knows what + # ufunc signature to look for + result = _rational_tests.test_add(a, b, c) + target = np.array([0, 2, 4], dtype=_rational_tests.rational) + assert_equal(result, target) + + # The new resolution means that we can (usually) find custom loops + # as long as they match exactly: + result = _rational_tests.test_add(a, b) + assert_equal(result, target) + + # This works even more generally, so long the default common-dtype + # promoter works out: + result = _rational_tests.test_add(a, b.astype(np.uint16), out=c) + assert_equal(result, target) + + # This scalar path used to go into legacy promotion, but doesn't now: + result = _rational_tests.test_add(a, np.uint16(2)) + target = np.array([2, 3, 4], dtype=_rational_tests.rational) + assert_equal(result, target) + + def test_operand_flags(self): + a = np.arange(16, dtype=int).reshape(4, 4) + b = np.arange(9, dtype=int).reshape(3, 3) + opflag_tests.inplace_add(a[:-1, :-1], b) + assert_equal(a, np.array([[0, 2, 4, 3], [7, 9, 11, 7], + [14, 16, 18, 11], [12, 13, 14, 15]])) + + a = np.array(0) + opflag_tests.inplace_add(a, 3) + assert_equal(a, 3) + opflag_tests.inplace_add(a, [3, 4]) + assert_equal(a, 10) + + def test_struct_ufunc(self): + import numpy._core._struct_ufunc_tests as struct_ufunc + + a = np.array([(1, 2, 3)], dtype='u8,u8,u8') + b = np.array([(1, 2, 3)], dtype='u8,u8,u8') + + result = struct_ufunc.add_triplet(a, b) + assert_equal(result, np.array([(2, 4, 6)], dtype='u8,u8,u8')) + assert_raises(RuntimeError, struct_ufunc.register_fail) + + def test_custom_ufunc(self): + a = np.array( + [_rational_tests.rational(1, 2), + _rational_tests.rational(1, 3), + _rational_tests.rational(1, 4)], + dtype=_rational_tests.rational) + b = np.array( + [_rational_tests.rational(1, 2), + _rational_tests.rational(1, 3), + _rational_tests.rational(1, 4)], + dtype=_rational_tests.rational) + + result = _rational_tests.test_add_rationals(a, b) + expected = np.array( + [_rational_tests.rational(1), + _rational_tests.rational(2, 3), + _rational_tests.rational(1, 2)], + dtype=_rational_tests.rational) + assert_equal(result, expected) + + def test_custom_ufunc_forced_sig(self): + # gh-9351 - looking for a non-first userloop would previously hang + with assert_raises(TypeError): + np.multiply(_rational_tests.rational(1), 1, + signature=(_rational_tests.rational, int, None)) + + def test_custom_array_like(self): + + class MyThing: + __array_priority__ = 1000 + + rmul_count = 0 + getitem_count = 0 + + def __init__(self, shape): + self.shape = shape + + def __len__(self): + return self.shape[0] + + def __getitem__(self, i): + MyThing.getitem_count += 1 + if not isinstance(i, tuple): + i = (i,) + if len(i) > self.ndim: + raise IndexError("boo") + + return MyThing(self.shape[len(i):]) + + def __rmul__(self, other): + MyThing.rmul_count += 1 + return self + + np.float64(5) * MyThing((3, 3)) + assert_(MyThing.rmul_count == 1, MyThing.rmul_count) + assert_(MyThing.getitem_count <= 2, MyThing.getitem_count) + + def test_array_wrap_array_priority(self): + class ArrayPriorityBase(np.ndarray): + @classmethod + def __array_wrap__(cls, array, context=None, return_scalar=False): + return cls + + class ArrayPriorityMinus0(ArrayPriorityBase): + __array_priority__ = 0 + + class ArrayPriorityMinus1000(ArrayPriorityBase): + __array_priority__ = -1000 + + class ArrayPriorityMinus1000b(ArrayPriorityBase): + __array_priority__ = -1000 + + class ArrayPriorityMinus2000(ArrayPriorityBase): + __array_priority__ = -2000 + + x = np.ones(2).view(ArrayPriorityMinus1000) + xb = np.ones(2).view(ArrayPriorityMinus1000b) + y = np.ones(2).view(ArrayPriorityMinus2000) + + assert np.add(x, y) is ArrayPriorityMinus1000 + assert np.add(y, x) is ArrayPriorityMinus1000 + assert np.add(x, xb) is ArrayPriorityMinus1000 + assert np.add(xb, x) is ArrayPriorityMinus1000b + y_minus0 = np.zeros(2).view(ArrayPriorityMinus0) + assert np.add(np.zeros(2), y_minus0) is ArrayPriorityMinus0 + assert type(np.add(xb, x, np.zeros(2))) is np.ndarray + + @pytest.mark.parametrize("a", ( + np.arange(10, dtype=int), + np.arange(10, dtype=_rational_tests.rational), + )) + def test_ufunc_at_basic(self, a): + + aa = a.copy() + np.add.at(aa, [2, 5, 2], 1) + assert_equal(aa, [0, 1, 4, 3, 4, 6, 6, 7, 8, 9]) + + with pytest.raises(ValueError): + # missing second operand + np.add.at(aa, [2, 5, 3]) + + aa = a.copy() + np.negative.at(aa, [2, 5, 3]) + assert_equal(aa, [0, 1, -2, -3, 4, -5, 6, 7, 8, 9]) + + aa = a.copy() + b = np.array([100, 100, 100]) + np.add.at(aa, [2, 5, 2], b) + assert_equal(aa, [0, 1, 202, 3, 4, 105, 6, 7, 8, 9]) + + with pytest.raises(ValueError): + # extraneous second operand + np.negative.at(a, [2, 5, 3], [1, 2, 3]) + + with pytest.raises(ValueError): + # second operand cannot be converted to an array + np.add.at(a, [2, 5, 3], [[1, 2], 1]) + + # ufuncs with indexed loops for performance in ufunc.at + indexed_ufuncs = [np.add, np.subtract, np.multiply, np.floor_divide, + np.maximum, np.minimum, np.fmax, np.fmin] + + @pytest.mark.parametrize( + "typecode", np.typecodes['AllInteger'] + np.typecodes['Float']) + @pytest.mark.parametrize("ufunc", indexed_ufuncs) + def test_ufunc_at_inner_loops(self, typecode, ufunc): + if ufunc is np.divide and typecode in np.typecodes['AllInteger']: + # Avoid divide-by-zero and inf for integer divide + a = np.ones(100, dtype=typecode) + indx = np.random.randint(100, size=30, dtype=np.intp) + vals = np.arange(1, 31, dtype=typecode) + else: + a = np.ones(1000, dtype=typecode) + indx = np.random.randint(1000, size=3000, dtype=np.intp) + vals = np.arange(3000, dtype=typecode) + atag = a.copy() + # Do the calculation twice and compare the answers + with warnings.catch_warnings(record=True) as w_at: + warnings.simplefilter('always') + ufunc.at(a, indx, vals) + with warnings.catch_warnings(record=True) as w_loop: + warnings.simplefilter('always') + for i, v in zip(indx, vals): + # Make sure all the work happens inside the ufunc + # in order to duplicate error/warning handling + ufunc(atag[i], v, out=atag[i:i + 1], casting="unsafe") + assert_equal(atag, a) + # If w_loop warned, make sure w_at warned as well + if len(w_loop) > 0: + # + assert len(w_at) > 0 + assert w_at[0].category == w_loop[0].category + assert str(w_at[0].message)[:10] == str(w_loop[0].message)[:10] + + @pytest.mark.parametrize("typecode", np.typecodes['Complex']) + @pytest.mark.parametrize("ufunc", [np.add, np.subtract, np.multiply]) + def test_ufunc_at_inner_loops_complex(self, typecode, ufunc): + a = np.ones(10, dtype=typecode) + indx = np.concatenate([np.ones(6, dtype=np.intp), + np.full(18, 4, dtype=np.intp)]) + value = a.dtype.type(1j) + ufunc.at(a, indx, value) + expected = np.ones_like(a) + if ufunc is np.multiply: + expected[1] = expected[4] = -1 + else: + expected[1] += 6 * (value if ufunc is np.add else -value) + expected[4] += 18 * (value if ufunc is np.add else -value) + + assert_array_equal(a, expected) + + def test_ufunc_at_ellipsis(self): + # Make sure the indexed loop check does not choke on iters + # with subspaces + arr = np.zeros(5) + np.add.at(arr, slice(None), np.ones(5)) + assert_array_equal(arr, np.ones(5)) + + def test_ufunc_at_negative(self): + arr = np.ones(5, dtype=np.int32) + indx = np.arange(5) + umt.indexed_negative.at(arr, indx) + # If it is [-1, -1, -1, -100, 0] then the regular strided loop was used + assert np.all(arr == [-1, -1, -1, -200, -1]) + + def test_ufunc_at_large(self): + # issue gh-23457 + indices = np.zeros(8195, dtype=np.int16) + b = np.zeros(8195, dtype=float) + b[0] = 10 + b[1] = 5 + b[8192:] = 100 + a = np.zeros(1, dtype=float) + np.add.at(a, indices, b) + assert a[0] == b.sum() + + def test_cast_index_fastpath(self): + arr = np.zeros(10) + values = np.ones(100000) + # index must be cast, which may be buffered in chunks: + index = np.zeros(len(values), dtype=np.uint8) + np.add.at(arr, index, values) + assert arr[0] == len(values) + + @pytest.mark.parametrize("value", [ + np.ones(1), np.ones(()), np.float64(1.), 1.]) + def test_ufunc_at_scalar_value_fastpath(self, value): + arr = np.zeros(1000) + # index must be cast, which may be buffered in chunks: + index = np.repeat(np.arange(1000), 2) + np.add.at(arr, index, value) + assert_array_equal(arr, np.full_like(arr, 2 * value)) + + def test_ufunc_at_multiD(self): + a = np.arange(9).reshape(3, 3) + b = np.array([[100, 100, 100], [200, 200, 200], [300, 300, 300]]) + np.add.at(a, (slice(None), [1, 2, 1]), b) + assert_equal(a, [[0, 201, 102], [3, 404, 205], [6, 607, 308]]) + + a = np.arange(27).reshape(3, 3, 3) + b = np.array([100, 200, 300]) + np.add.at(a, (slice(None), slice(None), [1, 2, 1]), b) + assert_equal(a, + [[[0, 401, 202], + [3, 404, 205], + [6, 407, 208]], + + [[9, 410, 211], + [12, 413, 214], + [15, 416, 217]], + + [[18, 419, 220], + [21, 422, 223], + [24, 425, 226]]]) + + a = np.arange(9).reshape(3, 3) + b = np.array([[100, 100, 100], [200, 200, 200], [300, 300, 300]]) + np.add.at(a, ([1, 2, 1], slice(None)), b) + assert_equal(a, [[0, 1, 2], [403, 404, 405], [206, 207, 208]]) + + a = np.arange(27).reshape(3, 3, 3) + b = np.array([100, 200, 300]) + np.add.at(a, (slice(None), [1, 2, 1], slice(None)), b) + assert_equal(a, + [[[0, 1, 2], + [203, 404, 605], + [106, 207, 308]], + + [[9, 10, 11], + [212, 413, 614], + [115, 216, 317]], + + [[18, 19, 20], + [221, 422, 623], + [124, 225, 326]]]) + + a = np.arange(9).reshape(3, 3) + b = np.array([100, 200, 300]) + np.add.at(a, (0, [1, 2, 1]), b) + assert_equal(a, [[0, 401, 202], [3, 4, 5], [6, 7, 8]]) + + a = np.arange(27).reshape(3, 3, 3) + b = np.array([100, 200, 300]) + np.add.at(a, ([1, 2, 1], 0, slice(None)), b) + assert_equal(a, + [[[0, 1, 2], + [3, 4, 5], + [6, 7, 8]], + + [[209, 410, 611], + [12, 13, 14], + [15, 16, 17]], + + [[118, 219, 320], + [21, 22, 23], + [24, 25, 26]]]) + + a = np.arange(27).reshape(3, 3, 3) + b = np.array([100, 200, 300]) + np.add.at(a, (slice(None), slice(None), slice(None)), b) + assert_equal(a, + [[[100, 201, 302], + [103, 204, 305], + [106, 207, 308]], + + [[109, 210, 311], + [112, 213, 314], + [115, 216, 317]], + + [[118, 219, 320], + [121, 222, 323], + [124, 225, 326]]]) + + def test_ufunc_at_0D(self): + a = np.array(0) + np.add.at(a, (), 1) + assert_equal(a, 1) + + assert_raises(IndexError, np.add.at, a, 0, 1) + assert_raises(IndexError, np.add.at, a, [], 1) + + def test_ufunc_at_dtypes(self): + # Test mixed dtypes + a = np.arange(10) + np.power.at(a, [1, 2, 3, 2], 3.5) + assert_equal(a, np.array([0, 1, 4414, 46, 4, 5, 6, 7, 8, 9])) + + def test_ufunc_at_boolean(self): + # Test boolean indexing and boolean ufuncs + a = np.arange(10) + index = a % 2 == 0 + np.equal.at(a, index, [0, 2, 4, 6, 8]) + assert_equal(a, [1, 1, 1, 3, 1, 5, 1, 7, 1, 9]) + + # Test unary operator + a = np.arange(10, dtype='u4') + np.invert.at(a, [2, 5, 2]) + assert_equal(a, [0, 1, 2, 3, 4, 5 ^ 0xffffffff, 6, 7, 8, 9]) + + def test_ufunc_at_advanced(self): + # Test empty subspace + orig = np.arange(4) + a = orig[:, None][:, 0:0] + np.add.at(a, [0, 1], 3) + assert_array_equal(orig, np.arange(4)) + + # Test with swapped byte order + index = np.array([1, 2, 1], np.dtype('i').newbyteorder()) + values = np.array([1, 2, 3, 4], np.dtype('f').newbyteorder()) + np.add.at(values, index, 3) + assert_array_equal(values, [1, 8, 6, 4]) + + # Test exception thrown + values = np.array(['a', 1], dtype=object) + assert_raises(TypeError, np.add.at, values, [0, 1], 1) + assert_array_equal(values, np.array(['a', 1], dtype=object)) + + # Test multiple output ufuncs raise error, gh-5665 + assert_raises(ValueError, np.modf.at, np.arange(10), [1]) + + # Test maximum + a = np.array([1, 2, 3]) + np.maximum.at(a, [0], 0) + assert_equal(a, np.array([1, 2, 3])) + + @pytest.mark.parametrize("dtype", + np.typecodes['AllInteger'] + np.typecodes['Float']) + @pytest.mark.parametrize("ufunc", + [np.add, np.subtract, np.divide, np.minimum, np.maximum]) + def test_at_negative_indexes(self, dtype, ufunc): + a = np.arange(0, 10).astype(dtype) + indxs = np.array([-1, 1, -1, 2]).astype(np.intp) + vals = np.array([1, 5, 2, 10], dtype=a.dtype) + + expected = a.copy() + for i, v in zip(indxs, vals): + expected[i] = ufunc(expected[i], v) + + ufunc.at(a, indxs, vals) + assert_array_equal(a, expected) + assert np.all(indxs == [-1, 1, -1, 2]) + + def test_at_not_none_signature(self): + # Test ufuncs with non-trivial signature raise a TypeError + a = np.ones((2, 2, 2)) + b = np.ones((1, 2, 2)) + assert_raises(TypeError, np.matmul.at, a, [0], b) + + a = np.array([[[1, 2], [3, 4]]]) + assert_raises(TypeError, np.linalg._umath_linalg.det.at, a, [0]) + + def test_at_no_loop_for_op(self): + # str dtype does not have a ufunc loop for np.add + arr = np.ones(10, dtype=str) + with pytest.raises(np._core._exceptions._UFuncNoLoopError): + np.add.at(arr, [0, 1], [0, 1]) + + def test_at_output_casting(self): + arr = np.array([-1]) + np.equal.at(arr, [0], [0]) + assert arr[0] == 0 + + def test_at_broadcast_failure(self): + arr = np.arange(5) + with pytest.raises(ValueError): + np.add.at(arr, [0, 1], [1, 2, 3]) + + def test_reduce_arguments(self): + f = np.add.reduce + d = np.ones((5, 2), dtype=int) + o = np.ones((2,), dtype=d.dtype) + r = o * 5 + assert_equal(f(d), r) + # a, axis=0, dtype=None, out=None, keepdims=False + assert_equal(f(d, axis=0), r) + assert_equal(f(d, 0), r) + assert_equal(f(d, 0, dtype=None), r) + assert_equal(f(d, 0, dtype='i'), r) + assert_equal(f(d, 0, 'i'), r) + assert_equal(f(d, 0, None), r) + assert_equal(f(d, 0, None, out=None), r) + assert_equal(f(d, 0, None, out=o), r) + assert_equal(f(d, 0, None, o), r) + assert_equal(f(d, 0, None, None), r) + assert_equal(f(d, 0, None, None, keepdims=False), r) + assert_equal(f(d, 0, None, None, True), r.reshape((1,) + r.shape)) + assert_equal(f(d, 0, None, None, False, 0), r) + assert_equal(f(d, 0, None, None, False, initial=0), r) + assert_equal(f(d, 0, None, None, False, 0, True), r) + assert_equal(f(d, 0, None, None, False, 0, where=True), r) + # multiple keywords + assert_equal(f(d, axis=0, dtype=None, out=None, keepdims=False), r) + assert_equal(f(d, 0, dtype=None, out=None, keepdims=False), r) + assert_equal(f(d, 0, None, out=None, keepdims=False), r) + assert_equal(f(d, 0, None, out=None, keepdims=False, initial=0, + where=True), r) + + # too little + assert_raises(TypeError, f) + # too much + assert_raises(TypeError, f, d, 0, None, None, False, 0, True, 1) + # invalid axis + assert_raises(TypeError, f, d, "invalid") + assert_raises(TypeError, f, d, axis="invalid") + assert_raises(TypeError, f, d, axis="invalid", dtype=None, + keepdims=True) + # invalid dtype + assert_raises(TypeError, f, d, 0, "invalid") + assert_raises(TypeError, f, d, dtype="invalid") + assert_raises(TypeError, f, d, dtype="invalid", out=None) + # invalid out + assert_raises(TypeError, f, d, 0, None, "invalid") + assert_raises(TypeError, f, d, out="invalid") + assert_raises(TypeError, f, d, out="invalid", dtype=None) + # keepdims boolean, no invalid value + # assert_raises(TypeError, f, d, 0, None, None, "invalid") + # assert_raises(TypeError, f, d, keepdims="invalid", axis=0, dtype=None) + # invalid mix + assert_raises(TypeError, f, d, 0, keepdims="invalid", dtype="invalid", + out=None) + + # invalid keyword + assert_raises(TypeError, f, d, axis=0, dtype=None, invalid=0) + assert_raises(TypeError, f, d, invalid=0) + assert_raises(TypeError, f, d, 0, keepdims=True, invalid="invalid", + out=None) + assert_raises(TypeError, f, d, axis=0, dtype=None, keepdims=True, + out=None, invalid=0) + assert_raises(TypeError, f, d, axis=0, dtype=None, + out=None, invalid=0) + + def test_structured_equal(self): + # https://github.com/numpy/numpy/issues/4855 + + class MyA(np.ndarray): + def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): + return getattr(ufunc, method)(*(input.view(np.ndarray) + for input in inputs), **kwargs) + a = np.arange(12.).reshape(4, 3) + ra = a.view(dtype=('f8,f8,f8')).squeeze() + mra = ra.view(MyA) + + target = np.array([True, False, False, False], dtype=bool) + assert_equal(np.all(target == (mra == ra[0])), True) + + def test_scalar_equal(self): + # Scalar comparisons should always work, without deprecation warnings. + # even when the ufunc fails. + a = np.array(0.) + b = np.array('a') + assert_(a != b) + assert_(b != a) + assert_(not (a == b)) + assert_(not (b == a)) + + def test_NotImplemented_not_returned(self): + # See gh-5964 and gh-2091. Some of these functions are not operator + # related and were fixed for other reasons in the past. + binary_funcs = [ + np.power, np.add, np.subtract, np.multiply, np.divide, + np.true_divide, np.floor_divide, np.bitwise_and, np.bitwise_or, + np.bitwise_xor, np.left_shift, np.right_shift, np.fmax, + np.fmin, np.fmod, np.hypot, np.logaddexp, np.logaddexp2, + np.maximum, np.minimum, np.mod, + np.greater, np.greater_equal, np.less, np.less_equal, + np.equal, np.not_equal] + + a = np.array('1') + b = 1 + c = np.array([1., 2.]) + for f in binary_funcs: + assert_raises(TypeError, f, a, b) + assert_raises(TypeError, f, c, a) + + @pytest.mark.parametrize("ufunc", + [np.logical_and, np.logical_or]) # logical_xor object loop is bad + @pytest.mark.parametrize("signature", + [(None, None, object), (object, None, None), + (None, object, None)]) + def test_logical_ufuncs_object_signatures(self, ufunc, signature): + a = np.array([True, None, False], dtype=object) + res = ufunc(a, a, signature=signature) + assert res.dtype == object + + @pytest.mark.parametrize("ufunc", + [np.logical_and, np.logical_or, np.logical_xor]) + @pytest.mark.parametrize("signature", + [(bool, None, object), (object, None, bool), + (None, object, bool)]) + def test_logical_ufuncs_mixed_object_signatures(self, ufunc, signature): + # Most mixed signatures fail (except those with bool out, e.g. `OO->?`) + a = np.array([True, None, False]) + with pytest.raises(TypeError): + ufunc(a, a, signature=signature) + + @pytest.mark.parametrize("ufunc", + [np.logical_and, np.logical_or, np.logical_xor]) + def test_logical_ufuncs_support_anything(self, ufunc): + # The logical ufuncs support even input that can't be promoted: + a = np.array(b'1', dtype="V3") + c = np.array([1., 2.]) + assert_array_equal(ufunc(a, c), ufunc([True, True], True)) + assert ufunc.reduce(a) == True + # check that the output has no effect: + out = np.zeros(2, dtype=np.int32) + expected = ufunc([True, True], True).astype(out.dtype) + assert_array_equal(ufunc(a, c, out=out), expected) + out = np.zeros((), dtype=np.int32) + assert ufunc.reduce(a, out=out) == True + # Last check, test reduction when out and a match (the complexity here + # is that the "i,i->?" may seem right, but should not match. + a = np.array([3], dtype="i") + out = np.zeros((), dtype=a.dtype) + assert ufunc.reduce(a, out=out) == 1 + + @pytest.mark.parametrize("ufunc", + [np.logical_and, np.logical_or, np.logical_xor]) + @pytest.mark.parametrize("dtype", ["S", "U"]) + @pytest.mark.parametrize("values", [["1", "hi", "0"], ["", ""]]) + def test_logical_ufuncs_supports_string(self, ufunc, dtype, values): + # note that values are either all true or all false + arr = np.array(values, dtype=dtype) + obj_arr = np.array(values, dtype=object) + res = ufunc(arr, arr) + expected = ufunc(obj_arr, obj_arr, dtype=bool) + + assert_array_equal(res, expected) + + res = ufunc.reduce(arr) + expected = ufunc.reduce(obj_arr, dtype=bool) + assert_array_equal(res, expected) + + @pytest.mark.parametrize("ufunc", + [np.logical_and, np.logical_or, np.logical_xor]) + def test_logical_ufuncs_out_cast_check(self, ufunc): + a = np.array('1') + c = np.array([1., 2.]) + out = a.copy() + with pytest.raises(TypeError): + # It would be safe, but not equiv casting: + ufunc(a, c, out=out, casting="equiv") + + def test_reducelike_byteorder_resolution(self): + # See gh-20699, byte-order changes need some extra care in the type + # resolution to make the following succeed: + arr_be = np.arange(10, dtype=">i8") + arr_le = np.arange(10, dtype="i + if 'O' in typ or '?' in typ: + continue + inp, out = typ.split('->') + args = [np.ones((3, 3), t) for t in inp] + with warnings.catch_warnings(record=True): + warnings.filterwarnings("always") + res = ufunc(*args) + if isinstance(res, tuple): + outs = tuple(out) + assert len(res) == len(outs) + for r, t in zip(res, outs): + assert r.dtype == np.dtype(t) + else: + assert res.dtype == np.dtype(out) + +@pytest.mark.parametrize('ufunc', [getattr(np, x) for x in dir(np) + if isinstance(getattr(np, x), np.ufunc)]) +def test_ufunc_noncontiguous(ufunc): + ''' + Check that contiguous and non-contiguous calls to ufuncs + have the same results for values in range(9) + ''' + for typ in ufunc.types: + # types is a list of strings like ii->i + if any(set('O?mM') & set(typ)): + # bool, object, datetime are too irregular for this simple test + continue + inp, out = typ.split('->') + args_c = [np.empty((6, 6), t) for t in inp] + # non contiguous (2, 3 step on the two dimensions) + args_n = [np.empty((12, 18), t)[::2, ::3] for t in inp] + # alignment != itemsize is possible. So create an array with such + # an odd step manually. + args_o = [] + for t in inp: + orig_dt = np.dtype(t) + off_dt = f"S{orig_dt.alignment}" # offset by alignment + dtype = np.dtype([("_", off_dt), ("t", orig_dt)], align=False) + args_o.append(np.empty((6, 6), dtype=dtype)["t"]) + for a in args_c + args_n + args_o: + a.flat = range(1, 37) + + with warnings.catch_warnings(record=True): + warnings.filterwarnings("always") + res_c = ufunc(*args_c) + res_n = ufunc(*args_n) + res_o = ufunc(*args_o) + if len(out) == 1: + res_c = (res_c,) + res_n = (res_n,) + res_o = (res_o,) + for c_ar, n_ar, o_ar in zip(res_c, res_n, res_o): + dt = c_ar.dtype + if np.issubdtype(dt, np.floating): + # for floating point results allow a small fuss in comparisons + # since different algorithms (libm vs. intrinsics) can be used + # for different input strides + res_eps = np.finfo(dt).eps + tol = 3 * res_eps + assert_allclose(res_c, res_n, atol=tol, rtol=tol) + assert_allclose(res_c, res_o, atol=tol, rtol=tol) + else: + assert_equal(c_ar, n_ar) + assert_equal(c_ar, o_ar) + + +@pytest.mark.parametrize('ufunc', [np.sign, np.equal]) +def test_ufunc_warn_with_nan(ufunc): + # issue gh-15127 + # test that calling certain ufuncs with a non-standard `nan` value does not + # emit a warning + # `b` holds a 64 bit signaling nan: the most significant bit of the + # significand is zero. + b = np.array([0x7ff0000000000001], 'i8').view('f8') + assert np.isnan(b) + if ufunc.nin == 1: + ufunc(b) + elif ufunc.nin == 2: + ufunc(b, b.copy()) + else: + raise ValueError('ufunc with more than 2 inputs') + + +@pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") +def test_ufunc_out_casterrors(): + # Tests that casting errors are correctly reported and buffers are + # cleared. + # The following array can be added to itself as an object array, but + # the result cannot be cast to an integer output: + value = 123 # relies on python cache (leak-check will still find it) + arr = np.array([value] * int(ncu.BUFSIZE * 1.5) + + ["string"] + + [value] * int(1.5 * ncu.BUFSIZE), dtype=object) + out = np.ones(len(arr), dtype=np.intp) + + count = sys.getrefcount(value) + with pytest.raises(ValueError): + # Output casting failure: + np.add(arr, arr, out=out, casting="unsafe") + + assert count == sys.getrefcount(value) + # output is unchanged after the error, this shows that the iteration + # was aborted (this is not necessarily defined behaviour) + assert out[-1] == 1 + + with pytest.raises(ValueError): + # Input casting failure: + np.add(arr, arr, out=out, dtype=np.intp, casting="unsafe") + + assert count == sys.getrefcount(value) + # output is unchanged after the error, this shows that the iteration + # was aborted (this is not necessarily defined behaviour) + assert out[-1] == 1 + + +@pytest.mark.parametrize("bad_offset", [0, int(ncu.BUFSIZE * 1.5)]) +def test_ufunc_input_casterrors(bad_offset): + value = 123 + arr = np.array([value] * bad_offset + + ["string"] + + [value] * int(1.5 * ncu.BUFSIZE), dtype=object) + with pytest.raises(ValueError): + # Force cast inputs, but the buffered cast of `arr` to intp fails: + np.add(arr, arr, dtype=np.intp, casting="unsafe") + + +@pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") +@pytest.mark.parametrize("bad_offset", [0, int(ncu.BUFSIZE * 1.5)]) +def test_ufunc_input_floatingpoint_error(bad_offset): + value = 123 + arr = np.array([value] * bad_offset + + [np.nan] + + [value] * int(1.5 * ncu.BUFSIZE)) + with np.errstate(invalid="raise"), pytest.raises(FloatingPointError): + # Force cast inputs, but the buffered cast of `arr` to intp fails: + np.add(arr, arr, dtype=np.intp, casting="unsafe") + + +@pytest.mark.skipif(sys.flags.optimize == 2, reason="Python running -OO") +@pytest.mark.xfail(IS_PYPY, reason="PyPy does not modify tp_doc") +@pytest.mark.parametrize( + "methodname", + ["__call__", "accumulate", "at", "outer", "reduce", "reduceat", "resolve_dtypes"], +) +def test_ufunc_method_signatures(methodname: str): + method = getattr(np.ufunc, methodname) + + try: + _ = inspect.signature(method) + except ValueError as e: + pytest.fail(e.args[0]) + + +def test_trivial_loop_invalid_cast(): + # This tests the fast-path "invalid cast", see gh-19904. + with pytest.raises(TypeError, + match="cast ufunc 'add' input 0"): + # the void dtype definitely cannot cast to double: + np.add(np.array(1, "i,i"), 3, signature="dd->d") + + +@pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") +@pytest.mark.parametrize("offset", + [0, ncu.BUFSIZE // 2, int(1.5 * ncu.BUFSIZE)]) +def test_reduce_casterrors(offset): + # Test reporting of casting errors in reductions, we test various + # offsets to where the casting error will occur, since these may occur + # at different places during the reduction procedure. For example + # the first item may be special. + value = 123 # relies on python cache (leak-check will still find it) + arr = np.array([value] * offset + + ["string"] + + [value] * int(1.5 * ncu.BUFSIZE), dtype=object) + out = np.array(-1, dtype=np.intp) + + count = sys.getrefcount(value) + with pytest.raises(ValueError, match="invalid literal"): + # This is an unsafe cast, but we currently always allow that. + # Note that the double loop is picked, but the cast fails. + # `initial=None` disables the use of an identity here to test failures + # while copying the first values path (not used when identity exists). + np.add.reduce(arr, dtype=np.intp, out=out, initial=None) + assert count == sys.getrefcount(value) + # If an error occurred during casting, the operation is done at most until + # the error occurs (the result of which would be `value * offset`) and -1 + # if the error happened immediately. + # This does not define behaviour, the output is invalid and thus undefined + assert out[()] < value * offset + + +@pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") +def test_reduction_no_reference_leak(): + # Test that the generic reduction does not leak references. + # gh-29358 + arr = np.array([1, 2, 3], dtype=np.int32) + count = sys.getrefcount(arr) + + np.add.reduce(arr, dtype=np.int32, initial=0) + assert count == sys.getrefcount(arr) + + np.add.accumulate(arr, dtype=np.int32) + assert count == sys.getrefcount(arr) + + np.add.reduceat(arr, [0, 1], dtype=np.int32) + assert count == sys.getrefcount(arr) + + # with `out=` the reference count is not changed + out = np.empty((), dtype=np.int32) + out_count = sys.getrefcount(out) + + np.add.reduce(arr, dtype=np.int32, out=out, initial=0) + assert count == sys.getrefcount(arr) + assert out_count == sys.getrefcount(out) + + out = np.empty(arr.shape, dtype=np.int32) + out_count = sys.getrefcount(out) + + np.add.accumulate(arr, dtype=np.int32, out=out) + assert count == sys.getrefcount(arr) + assert out_count == sys.getrefcount(out) + + out = np.empty((2,), dtype=np.int32) + out_count = sys.getrefcount(out) + + np.add.reduceat(arr, [0, 1], dtype=np.int32, out=out) + assert count == sys.getrefcount(arr) + assert out_count == sys.getrefcount(out) + + +def test_object_reduce_cleanup_on_failure(): + # Test cleanup, including of the initial value (manually provided or not) + with pytest.raises(TypeError): + np.add.reduce([1, 2, None], initial=4) + + with pytest.raises(TypeError): + np.add.reduce([1, 2, None]) + + +@pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") +@pytest.mark.parametrize("method", + [np.add.accumulate, np.add.reduce, + pytest.param(lambda x: np.add.reduceat(x, [0]), id="reduceat"), + pytest.param(lambda x: np.log.at(x, [2]), id="at")]) +def test_ufunc_methods_floaterrors(method): + # adding inf and -inf (or log(-inf) creates an invalid float and warns + arr = np.array([np.inf, 0, -np.inf]) + with np.errstate(all="warn"): + with pytest.warns(RuntimeWarning, match="invalid value"): + method(arr) + + arr = np.array([np.inf, 0, -np.inf]) + with np.errstate(all="raise"): + with pytest.raises(FloatingPointError): + method(arr) + + +def _check_neg_zero(value): + if value != 0.0: + return False + if not np.signbit(value.real): + return False + if value.dtype.kind == "c": + return np.signbit(value.imag) + return True + +@pytest.mark.parametrize("dtype", np.typecodes["AllFloat"]) +def test_addition_negative_zero(dtype): + dtype = np.dtype(dtype) + if dtype.kind == "c": + neg_zero = dtype.type(complex(-0.0, -0.0)) + else: + neg_zero = dtype.type(-0.0) + + arr = np.array(neg_zero) + arr2 = np.array(neg_zero) + + assert _check_neg_zero(arr + arr2) + # In-place ops may end up on a different path (reduce path) see gh-21211 + arr += arr2 + assert _check_neg_zero(arr) + + +@pytest.mark.parametrize("dtype", np.typecodes["AllFloat"]) +@pytest.mark.parametrize("use_initial", [True, False]) +def test_addition_reduce_negative_zero(dtype, use_initial): + dtype = np.dtype(dtype) + if dtype.kind == "c": + neg_zero = dtype.type(complex(-0.0, -0.0)) + else: + neg_zero = dtype.type(-0.0) + + kwargs = {} + if use_initial: + kwargs["initial"] = neg_zero + else: + pytest.xfail("-0. propagation in sum currently requires initial") + + # Test various length, in case SIMD paths or chunking play a role. + # 150 extends beyond the pairwise blocksize; probably not important. + for i in range(150): + arr = np.array([neg_zero] * i, dtype=dtype) + res = np.sum(arr, **kwargs) + if i > 0 or use_initial: + assert _check_neg_zero(res) + else: + # `sum([])` should probably be 0.0 and not -0.0 like `sum([-0.0])` + assert not np.signbit(res.real) + assert not np.signbit(res.imag) + + +@pytest.mark.parametrize(["dt1", "dt2"], + [("S", "U"), ("U", "S"), ("S", "d"), ("S", "V"), ("U", "l")]) +def test_addition_string_types(dt1, dt2): + arr1 = np.array([1234234], dtype=dt1) + arr2 = np.array([b"423"], dtype=dt2) + with pytest.raises(np._core._exceptions.UFuncTypeError) as exc: + np.add(arr1, arr2) + + +@pytest.mark.parametrize("order1,order2", + [(">", ">"), ("<", "<"), (">", "<"), ("<", ">")]) +def test_addition_unicode_inverse_byte_order(order1, order2): + element = 'abcd' + arr1 = np.array([element], dtype=f"{order1}U4") + arr2 = np.array([element], dtype=f"{order2}U4") + result = arr1 + arr2 + assert result == 2 * element + + +@pytest.mark.parametrize("dtype", [np.int8, np.int16, np.int32, np.int64]) +def test_find_non_long_args(dtype): + element = 'abcd' + start = dtype(0) + end = dtype(len(element)) + arr = np.array([element]) + result = np._core.umath.find(arr, "a", start, end) + assert result.dtype == np.dtype("intp") + assert result == 0 + + +def test_find_access_past_buffer(): + # This checks that no read past the string buffer occurs in + # string_fastsearch.h. The buffer class makes sure this is checked. + # To see it in action, you can remove the checks in the buffer and + # this test will produce an 'Invalid read' if run under valgrind. + arr = np.array([b'abcd', b'ebcd']) + result = np._core.umath.find(arr, b'cde', 0, np.iinfo(np.int64).max) + assert np.all(result == -1) + + +class TestLowlevelAPIAccess: + def test_resolve_dtypes_basic(self): + # Basic test for dtype resolution: + i4 = np.dtype("i4") + f4 = np.dtype("f4") + f8 = np.dtype("f8") + + r = np.add.resolve_dtypes((i4, f4, None)) + assert r == (f8, f8, f8) + + # Signature uses the same logic to parse as ufunc (less strict) + # the following is "same-kind" casting so works: + r = np.add.resolve_dtypes(( + i4, i4, None), signature=(None, None, "f4")) + assert r == (f4, f4, f4) + + # Check NEP 50 "weak" promotion also: + r = np.add.resolve_dtypes((f4, int, None)) + assert r == (f4, f4, f4) + + with pytest.raises(TypeError): + np.add.resolve_dtypes((i4, f4, None), casting="no") + + def test_resolve_dtypes_comparison(self): + i4 = np.dtype("i4") + i8 = np.dtype("i8") + b = np.dtype("?") + r = np.equal.resolve_dtypes((i4, i8, None)) + assert r == (i8, i8, b) + + def test_weird_dtypes(self): + S0 = np.dtype("S0") + # S0 is often converted by NumPy to S1, but not here: + r = np.equal.resolve_dtypes((S0, S0, None)) + assert r == (S0, S0, np.dtype(bool)) + + # Subarray dtypes are weird and may not work fully, we preserve them + # leading to a TypeError (currently no equal loop for void/structured) + dts = np.dtype("10i") + with pytest.raises(TypeError): + np.equal.resolve_dtypes((dts, dts, None)) + + def test_resolve_dtypes_reduction(self): + i2 = np.dtype("i2") + default_int_ = np.dtype(np.int_) + # Check special addition resolution: + res = np.add.resolve_dtypes((None, i2, None), reduction=True) + assert res == (default_int_, default_int_, default_int_) + + def test_resolve_dtypes_reduction_no_output(self): + i4 = np.dtype("i4") + with pytest.raises(TypeError): + # May be allowable at some point? + np.add.resolve_dtypes((i4, i4, i4), reduction=True) + + @pytest.mark.parametrize("dtypes", [ + (np.dtype("i"), np.dtype("i")), + (None, np.dtype("i"), np.dtype("f")), + (np.dtype("i"), None, np.dtype("f")), + ("i4", "i4", None)]) + def test_resolve_dtypes_errors(self, dtypes): + with pytest.raises(TypeError): + np.add.resolve_dtypes(dtypes) + + def test_resolve_dtypes_reduction_errors(self): + i2 = np.dtype("i2") + + with pytest.raises(TypeError): + np.add.resolve_dtypes((None, i2, i2)) + + with pytest.raises(TypeError): + np.add.signature((None, None, "i4")) + + @pytest.mark.skipif(not hasattr(ct, "pythonapi"), + reason="`ctypes.pythonapi` required for capsule unpacking.") + @pytest.mark.thread_unsafe(reason="modifies global object in the ctypes API") + def test_loop_access(self): + # This is a basic test for the full strided loop access + data_t = ct.c_char_p * 2 + dim_t = ct.c_ssize_t * 1 + strides_t = ct.c_ssize_t * 2 + strided_loop_t = ct.CFUNCTYPE( + ct.c_int, ct.c_void_p, data_t, dim_t, strides_t, ct.c_void_p) + + class call_info_t(ct.Structure): + _fields_ = [ + ("strided_loop", strided_loop_t), + ("context", ct.c_void_p), + ("auxdata", ct.c_void_p), + ("requires_pyapi", ct.c_byte), + ("no_floatingpoint_errors", ct.c_byte), + ] + + i4 = np.dtype("i4") + dt, call_info_obj = np.negative._resolve_dtypes_and_context((i4, i4)) + assert dt == (i4, i4) # can be used without casting + + # Fill in the rest of the information: + np.negative._get_strided_loop(call_info_obj) + + ct.pythonapi.PyCapsule_GetPointer.restype = ct.c_void_p + call_info = ct.pythonapi.PyCapsule_GetPointer( + ct.py_object(call_info_obj), + ct.c_char_p(b"numpy_1.24_ufunc_call_info")) + + call_info = ct.cast(call_info, ct.POINTER(call_info_t)).contents + + arr = np.arange(10, dtype=i4) + call_info.strided_loop( + call_info.context, + data_t(arr.ctypes.data, arr.ctypes.data), + arr.ctypes.shape, # is a C-array with 10 here + strides_t(arr.ctypes.strides[0], arr.ctypes.strides[0]), + call_info.auxdata) + + # We just directly called the negative inner-loop in-place: + assert_array_equal(arr, -np.arange(10, dtype=i4)) + + @pytest.mark.parametrize("strides", [1, (1, 2, 3), (1, "2")]) + def test__get_strided_loop_errors_bad_strides(self, strides): + i4 = np.dtype("i4") + dt, call_info = np.negative._resolve_dtypes_and_context((i4, i4)) + + with pytest.raises(TypeError, match="fixed_strides.*tuple.*or None"): + np.negative._get_strided_loop(call_info, fixed_strides=strides) + + def test__get_strided_loop_errors_bad_call_info(self): + i4 = np.dtype("i4") + dt, call_info = np.negative._resolve_dtypes_and_context((i4, i4)) + + with pytest.raises(ValueError, match="PyCapsule"): + np.negative._get_strided_loop("not the capsule!") + + with pytest.raises(TypeError, match=".*incompatible context"): + np.add._get_strided_loop(call_info) + + np.negative._get_strided_loop(call_info) + with pytest.raises(TypeError): + # cannot call it a second time: + np.negative._get_strided_loop(call_info) + + def test_long_arrays(self): + t = np.zeros((1029, 917), dtype=np.single) + t[0][0] = 1 + t[28][414] = 1 + tc = np.cos(t) + assert_equal(tc[0][0], tc[28][414]) + + +class TestUFuncInspectSignature: + PARAMS_COMMON = { + "casting": "same_kind", + "order": "K", + "dtype": None, + "subok": True, + "signature": None, + } + + PARAMS_UFUNC = { + "where": True, + } | PARAMS_COMMON + + PARAMS_GUFUNC = { + "axes": np._NoValue, + "axis": np._NoValue, + "keepdims": False, + } | PARAMS_COMMON + + @pytest.mark.parametrize("ufunc", [np.log, np.gcd, np.frexp, np.divmod, np.matvec]) + def test_dunder_signature_attr(self, ufunc: np.ufunc): + assert hasattr(ufunc, "__signature__") + assert isinstance(ufunc.__signature__, inspect.Signature) + assert inspect.signature(ufunc) == ufunc.__signature__ + + @pytest.mark.parametrize("ufunc", [np.exp, np.mod, np.frexp, np.divmod, np.vecmat]) + def test_params_common_positional(self, ufunc: np.ufunc): + sig = inspect.signature(ufunc) + + # check positional-only parameters + posonly_params = {name: param.default + for name, param in sig.parameters.items() + if param.kind is param.POSITIONAL_ONLY} + assert len(posonly_params) == ufunc.nin + assert all(default is inspect.Parameter.empty + for default in posonly_params.values()) + + # check 'out' parameter + out_param = sig.parameters.get("out") + assert out_param is not None + assert out_param.kind is inspect.Parameter.POSITIONAL_OR_KEYWORD + + @pytest.mark.parametrize("ufunc", [np.sin, np.add, np.frexp, np.divmod]) + def test_params_common_ufunc(self, ufunc: np.ufunc): + assert ufunc.signature is None # sanity check + + sig = inspect.signature(ufunc) + + # check keyword-only parameters + keyword_params = {name: param.default + for name, param in sig.parameters.items() + if param.kind is param.KEYWORD_ONLY} + assert keyword_params == self.PARAMS_UFUNC + + @pytest.mark.parametrize("gufunc", [np.matmul, np.matvec, np.vecdot, np.vecmat]) + def test_params_common_gufunc(self, gufunc: np.ufunc): + assert gufunc.signature is not None # sanity check + + sig = inspect.signature(gufunc) + + # check keyword-only parameters + keyword_params = {name: param.default + for name, param in sig.parameters.items() + if param.kind is param.KEYWORD_ONLY} + assert keyword_params == self.PARAMS_GUFUNC diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_umath.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_umath.py new file mode 100644 index 0000000000000000000000000000000000000000..ab9c594618b697faabcc52b4f61ba5520c615e6e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_umath.py @@ -0,0 +1,4975 @@ +import fnmatch +import inspect +import itertools +import operator +import platform +import sys +import warnings +from collections import namedtuple +from fractions import Fraction +from functools import reduce + +import pytest + +import numpy as np +import numpy._core.umath as ncu +from numpy._core import _umath_tests as ncu_tests, sctypes +from numpy.testing import ( + HAS_REFCOUNT, + IS_MUSL, + IS_PYPY, + IS_WASM, + _gen_alignment_data, + assert_, + assert_allclose, + assert_almost_equal, + assert_array_almost_equal, + assert_array_almost_equal_nulp, + assert_array_equal, + assert_array_max_ulp, + assert_equal, + assert_no_warnings, + assert_raises, + assert_raises_regex, +) +from numpy.testing._private.utils import _glibc_older_than + +UFUNCS = [obj for obj in np._core.umath.__dict__.values() + if isinstance(obj, np.ufunc)] + +UFUNCS_UNARY = [ + uf for uf in UFUNCS if uf.nin == 1 +] +UFUNCS_UNARY_FP = [ + uf for uf in UFUNCS_UNARY if 'f->f' in uf.types +] + +UFUNCS_BINARY = [ + uf for uf in UFUNCS if uf.nin == 2 +] +UFUNCS_BINARY_ACC = [ + uf for uf in UFUNCS_BINARY if hasattr(uf, "accumulate") and uf.nout == 1 +] + +def interesting_binop_operands(val1, val2, dtype): + """ + Helper to create "interesting" operands to cover common code paths: + * scalar inputs + * only first "values" is an array (e.g. scalar division fast-paths) + * Longer array (SIMD) placing the value of interest at different positions + * Oddly strided arrays which may not be SIMD compatible + + It does not attempt to cover unaligned access or mixed dtypes. + These are normally handled by the casting/buffering machinery. + + This is not a fixture (currently), since I believe a fixture normally + only yields once? + """ + fill_value = 1 # could be a parameter, but maybe not an optional one? + + arr1 = np.full(10003, dtype=dtype, fill_value=fill_value) + arr2 = np.full(10003, dtype=dtype, fill_value=fill_value) + + arr1[0] = val1 + arr2[0] = val2 + + extractor = lambda res: res + yield arr1[0], arr2[0], extractor, "scalars" + + extractor = lambda res: res + yield arr1[0, ...], arr2[0, ...], extractor, "scalar-arrays" + + # reset array values to fill_value: + arr1[0] = fill_value + arr2[0] = fill_value + + for pos in [0, 1, 2, 3, 4, 5, -1, -2, -3, -4]: + arr1[pos] = val1 + arr2[pos] = val2 + + extractor = lambda res: res[pos] + yield arr1, arr2, extractor, f"off-{pos}" + yield arr1, arr2[pos], extractor, f"off-{pos}-with-scalar" + + arr1[pos] = fill_value + arr2[pos] = fill_value + + for stride in [-1, 113]: + op1 = arr1[::stride] + op2 = arr2[::stride] + op1[10] = val1 + op2[10] = val2 + + extractor = lambda res: res[10] + yield op1, op2, extractor, f"stride-{stride}" + + op1[10] = fill_value + op2[10] = fill_value + + +def on_powerpc(): + """ True if we are running on a Power PC platform.""" + return platform.processor() == 'powerpc' or \ + platform.machine().startswith('ppc') + + +def bad_arcsinh(): + """The blocklisted trig functions are not accurate on aarch64/PPC for + complex256. Rather than dig through the actual problem skip the + test. This should be fixed when we can move past glibc2.17 + which is the version in manylinux2014 + """ + if platform.machine() == 'aarch64': + x = 1.78e-10 + elif on_powerpc(): + x = 2.16e-10 + else: + return False + v1 = np.arcsinh(np.float128(x)) + v2 = np.arcsinh(np.complex256(x)).real + # The eps for float128 is 1-e33, so this is way bigger + return abs((v1 / v2) - 1.0) > 1e-23 + + +class _FilterInvalids: + def setup_method(self): + self.olderr = np.seterr(invalid='ignore') + + def teardown_method(self): + np.seterr(**self.olderr) + + +class TestConstants: + def test_pi(self): + assert_allclose(ncu.pi, 3.141592653589793, 1e-15) + + def test_e(self): + assert_allclose(ncu.e, 2.718281828459045, 1e-15) + + def test_euler_gamma(self): + assert_allclose(ncu.euler_gamma, 0.5772156649015329, 1e-15) + + +class TestOut: + def test_out_subok(self): + for subok in (True, False): + a = np.array(0.5) + o = np.empty(()) + + r = np.add(a, 2, o, subok=subok) + assert_(r is o) + r = np.add(a, 2, out=o, subok=subok) + assert_(r is o) + r = np.add(a, 2, out=(o,), subok=subok) + assert_(r is o) + + d = np.array(5.7) + o1 = np.empty(()) + o2 = np.empty((), dtype=np.int32) + + r1, r2 = np.frexp(d, o1, None, subok=subok) + assert_(r1 is o1) + r1, r2 = np.frexp(d, None, o2, subok=subok) + assert_(r2 is o2) + r1, r2 = np.frexp(d, o1, o2, subok=subok) + assert_(r1 is o1) + assert_(r2 is o2) + + r1, r2 = np.frexp(d, out=(o1, None), subok=subok) + assert_(r1 is o1) + r1, r2 = np.frexp(d, out=(None, o2), subok=subok) + assert_(r2 is o2) + r1, r2 = np.frexp(d, out=(o1, o2), subok=subok) + assert_(r1 is o1) + assert_(r2 is o2) + + with assert_raises(TypeError): + # Out argument must be tuple, since there are multiple outputs. + r1, r2 = np.frexp(d, out=o1, subok=subok) + + assert_raises(TypeError, np.add, a, 2, o, o, subok=subok) + assert_raises(TypeError, np.add, a, 2, o, out=o, subok=subok) + assert_raises(TypeError, np.add, a, 2, None, out=o, subok=subok) + assert_raises(ValueError, np.add, a, 2, out=(o, o), subok=subok) + assert_raises(ValueError, np.add, a, 2, out=(), subok=subok) + assert_raises(TypeError, np.add, a, 2, [], subok=subok) + assert_raises(TypeError, np.add, a, 2, out=[], subok=subok) + assert_raises(TypeError, np.add, a, 2, out=([],), subok=subok) + o.flags.writeable = False + assert_raises(ValueError, np.add, a, 2, o, subok=subok) + assert_raises(ValueError, np.add, a, 2, out=o, subok=subok) + assert_raises(ValueError, np.add, a, 2, out=(o,), subok=subok) + + def test_out_wrap_subok(self): + class ArrayWrap(np.ndarray): + __array_priority__ = 10 + + def __new__(cls, arr): + return np.asarray(arr).view(cls).copy() + + def __array_wrap__(self, arr, context=None, return_scalar=False): + return arr.view(type(self)) + + for subok in (True, False): + a = ArrayWrap([0.5]) + + r = np.add(a, 2, subok=subok) + if subok: + assert_(isinstance(r, ArrayWrap)) + else: + assert_(type(r) == np.ndarray) + + r = np.add(a, 2, None, subok=subok) + if subok: + assert_(isinstance(r, ArrayWrap)) + else: + assert_(type(r) == np.ndarray) + + r = np.add(a, 2, out=None, subok=subok) + if subok: + assert_(isinstance(r, ArrayWrap)) + else: + assert_(type(r) == np.ndarray) + + r = np.add(a, 2, out=(None,), subok=subok) + if subok: + assert_(isinstance(r, ArrayWrap)) + else: + assert_(type(r) == np.ndarray) + + d = ArrayWrap([5.7]) + o1 = np.empty((1,)) + o2 = np.empty((1,), dtype=np.int32) + + r1, r2 = np.frexp(d, o1, subok=subok) + if subok: + assert_(isinstance(r2, ArrayWrap)) + else: + assert_(type(r2) == np.ndarray) + + r1, r2 = np.frexp(d, o1, None, subok=subok) + if subok: + assert_(isinstance(r2, ArrayWrap)) + else: + assert_(type(r2) == np.ndarray) + + r1, r2 = np.frexp(d, None, o2, subok=subok) + if subok: + assert_(isinstance(r1, ArrayWrap)) + else: + assert_(type(r1) == np.ndarray) + + r1, r2 = np.frexp(d, out=(o1, None), subok=subok) + if subok: + assert_(isinstance(r2, ArrayWrap)) + else: + assert_(type(r2) == np.ndarray) + + r1, r2 = np.frexp(d, out=(None, o2), subok=subok) + if subok: + assert_(isinstance(r1, ArrayWrap)) + else: + assert_(type(r1) == np.ndarray) + + with assert_raises(TypeError): + # Out argument must be tuple, since there are multiple outputs. + r1, r2 = np.frexp(d, out=o1, subok=subok) + + @pytest.mark.skipif(not HAS_REFCOUNT, reason="Python lacks refcounts") + def test_out_wrap_no_leak(self): + # Regression test for gh-26545 + class ArrSubclass(np.ndarray): + pass + + arr = np.arange(10).view(ArrSubclass) + orig_refcount = sys.getrefcount(arr) + arr *= 1 + assert sys.getrefcount(arr) == orig_refcount + + +class TestComparisons: + import operator + + @pytest.mark.parametrize('dtype', sctypes['uint'] + sctypes['int'] + + sctypes['float'] + [np.bool]) + @pytest.mark.parametrize('py_comp,np_comp', [ + (operator.lt, np.less), + (operator.le, np.less_equal), + (operator.gt, np.greater), + (operator.ge, np.greater_equal), + (operator.eq, np.equal), + (operator.ne, np.not_equal) + ]) + def test_comparison_functions(self, dtype, py_comp, np_comp): + # Initialize input arrays + if dtype == np.bool: + a = np.random.choice(a=[False, True], size=1000) + b = np.random.choice(a=[False, True], size=1000) + scalar = True + else: + a = np.random.randint(low=1, high=10, size=1000).astype(dtype) + b = np.random.randint(low=1, high=10, size=1000).astype(dtype) + scalar = 5 + np_scalar = np.dtype(dtype).type(scalar) + a_lst = a.tolist() + b_lst = b.tolist() + + # (Binary) Comparison (x1=array, x2=array) + comp_b = np_comp(a, b).view(np.uint8) + comp_b_list = [int(py_comp(x, y)) for x, y in zip(a_lst, b_lst)] + + # (Scalar1) Comparison (x1=scalar, x2=array) + comp_s1 = np_comp(np_scalar, b).view(np.uint8) + comp_s1_list = [int(py_comp(scalar, x)) for x in b_lst] + + # (Scalar2) Comparison (x1=array, x2=scalar) + comp_s2 = np_comp(a, np_scalar).view(np.uint8) + comp_s2_list = [int(py_comp(x, scalar)) for x in a_lst] + + # Sequence: Binary, Scalar1 and Scalar2 + assert_(comp_b.tolist() == comp_b_list, + f"Failed comparison ({py_comp.__name__})") + assert_(comp_s1.tolist() == comp_s1_list, + f"Failed comparison ({py_comp.__name__})") + assert_(comp_s2.tolist() == comp_s2_list, + f"Failed comparison ({py_comp.__name__})") + + def test_ignore_object_identity_in_equal(self): + # Check comparing identical objects whose comparison + # is not a simple boolean, e.g., arrays that are compared elementwise. + a = np.array([np.array([1, 2, 3]), None], dtype=object) + assert_raises(ValueError, np.equal, a, a) + + # Check error raised when comparing identical non-comparable objects. + class FunkyType: + def __eq__(self, other): + raise TypeError("I won't compare") + + a = np.array([FunkyType()]) + assert_raises(TypeError, np.equal, a, a) + + # Check identity doesn't override comparison mismatch. + a = np.array([np.nan], dtype=object) + assert_equal(np.equal(a, a), [False]) + + def test_ignore_object_identity_in_not_equal(self): + # Check comparing identical objects whose comparison + # is not a simple boolean, e.g., arrays that are compared elementwise. + a = np.array([np.array([1, 2, 3]), None], dtype=object) + assert_raises(ValueError, np.not_equal, a, a) + + # Check error raised when comparing identical non-comparable objects. + class FunkyType: + def __ne__(self, other): + raise TypeError("I won't compare") + + a = np.array([FunkyType()]) + assert_raises(TypeError, np.not_equal, a, a) + + # Check identity doesn't override comparison mismatch. + a = np.array([np.nan], dtype=object) + assert_equal(np.not_equal(a, a), [True]) + + def test_error_in_equal_reduce(self): + # gh-20929 + # make sure np.equal.reduce raises a TypeError if an array is passed + # without specifying the dtype + a = np.array([0, 0]) + assert_equal(np.equal.reduce(a, dtype=bool), True) + assert_raises(TypeError, np.equal.reduce, a) + + def test_object_dtype(self): + assert np.equal(1, [1], dtype=object).dtype == object + assert np.equal(1, [1], signature=(None, None, "O")).dtype == object + + def test_object_nonbool_dtype_error(self): + # bool output dtype is fine of course: + assert np.equal(1, [1], dtype=bool).dtype == bool + + # but the following are examples do not have a loop: + with pytest.raises(TypeError, match="No loop matching"): + np.equal(1, 1, dtype=np.int64) + + with pytest.raises(TypeError, match="No loop matching"): + np.equal(1, 1, sig=(None, None, "l")) + + @pytest.mark.parametrize("dtypes", ["qQ", "Qq"]) + @pytest.mark.parametrize('py_comp, np_comp', [ + (operator.lt, np.less), + (operator.le, np.less_equal), + (operator.gt, np.greater), + (operator.ge, np.greater_equal), + (operator.eq, np.equal), + (operator.ne, np.not_equal) + ]) + @pytest.mark.parametrize("vals", [(2**60, 2**60 + 1), (2**60 + 1, 2**60)]) + def test_large_integer_direct_comparison( + self, dtypes, py_comp, np_comp, vals): + # Note that float(2**60) + 1 == float(2**60). + a1 = np.array([2**60], dtype=dtypes[0]) + a2 = np.array([2**60 + 1], dtype=dtypes[1]) + expected = py_comp(2**60, 2**60 + 1) + + assert py_comp(a1, a2) == expected + assert np_comp(a1, a2) == expected + # Also check the scalars: + s1 = a1[0] + s2 = a2[0] + assert isinstance(s1, np.integer) + assert isinstance(s2, np.integer) + # The Python operator here is mainly interesting: + assert py_comp(s1, s2) == expected + assert np_comp(s1, s2) == expected + + @pytest.mark.parametrize("dtype", np.typecodes['UnsignedInteger']) + @pytest.mark.parametrize('py_comp_func, np_comp_func', [ + (operator.lt, np.less), + (operator.le, np.less_equal), + (operator.gt, np.greater), + (operator.ge, np.greater_equal), + (operator.eq, np.equal), + (operator.ne, np.not_equal) + ]) + @pytest.mark.parametrize("flip", [True, False]) + def test_unsigned_signed_direct_comparison( + self, dtype, py_comp_func, np_comp_func, flip): + if flip: + py_comp = lambda x, y: py_comp_func(y, x) + np_comp = lambda x, y: np_comp_func(y, x) + else: + py_comp = py_comp_func + np_comp = np_comp_func + + arr = np.array([np.iinfo(dtype).max], dtype=dtype) + expected = py_comp(int(arr[0]), -1) + + assert py_comp(arr, -1) == expected + assert np_comp(arr, -1) == expected + + scalar = arr[0] + assert isinstance(scalar, np.integer) + # The Python operator here is mainly interesting: + assert py_comp(scalar, -1) == expected + assert np_comp(scalar, -1) == expected + + +class TestAdd: + def test_reduce_alignment(self): + # gh-9876 + # make sure arrays with weird strides work with the optimizations in + # pairwise_sum_@TYPE@. On x86, the 'b' field will count as aligned at a + # 4 byte offset, even though its itemsize is 8. + a = np.zeros(2, dtype=[('a', np.int32), ('b', np.float64)]) + a['a'] = -1 + assert_equal(a['b'].sum(), 0) + + +class TestDivision: + def test_division_int(self): + # int division should follow Python + x = np.array([5, 10, 90, 100, -5, -10, -90, -100, -120]) + if 5 / 10 == 0.5: + assert_equal(x / 100, [0.05, 0.1, 0.9, 1, + -0.05, -0.1, -0.9, -1, -1.2]) + else: + assert_equal(x / 100, [0, 0, 0, 1, -1, -1, -1, -1, -2]) + assert_equal(x // 100, [0, 0, 0, 1, -1, -1, -1, -1, -2]) + assert_equal(x % 100, [5, 10, 90, 0, 95, 90, 10, 0, 80]) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + @pytest.mark.parametrize("dtype,ex_val", itertools.product( + sctypes['int'] + sctypes['uint'], ( + ( + # dividend + "np.array(range(fo.max-lsize, fo.max)).astype(dtype)," + # divisors + "np.arange(lsize).astype(dtype)," + # scalar divisors + "range(15)" + ), + ( + # dividend + "np.arange(fo.min, fo.min+lsize).astype(dtype)," + # divisors + "np.arange(lsize//-2, lsize//2).astype(dtype)," + # scalar divisors + "range(fo.min, fo.min + 15)" + ), ( + # dividend + "np.array(range(fo.max-lsize, fo.max)).astype(dtype)," + # divisors + "np.arange(lsize).astype(dtype)," + # scalar divisors + "[1,3,9,13,neg, fo.min+1, fo.min//2, fo.max//3, fo.max//4]" + ) + ) + )) + def test_division_int_boundary(self, dtype, ex_val): + fo = np.iinfo(dtype) + neg = -1 if fo.min < 0 else 1 + # Large enough to test SIMD loops and remainder elements + lsize = 512 + 7 + a, b, divisors = eval(ex_val) + a_lst, b_lst = a.tolist(), b.tolist() + + c_div = lambda n, d: ( + 0 if d == 0 else ( + fo.min if (n and n == fo.min and d == -1) else n // d + ) + ) + with np.errstate(divide='ignore'): + ac = a.copy() + ac //= b + div_ab = a // b + div_lst = [c_div(x, y) for x, y in zip(a_lst, b_lst)] + + msg = "Integer arrays floor division check (//)" + assert all(div_ab == div_lst), msg + msg_eq = "Integer arrays floor division check (//=)" + assert all(ac == div_lst), msg_eq + + for divisor in divisors: + ac = a.copy() + with np.errstate(divide='ignore', over='ignore'): + div_a = a // divisor + ac //= divisor + div_lst = [c_div(i, divisor) for i in a_lst] + + assert all(div_a == div_lst), msg + assert all(ac == div_lst), msg_eq + + with np.errstate(divide='raise', over='raise'): + if 0 in b: + # Verify overflow case + with pytest.raises(FloatingPointError, + match="divide by zero encountered in floor_divide"): + a // b + else: + a // b + if fo.min and fo.min in a: + with pytest.raises(FloatingPointError, + match='overflow encountered in floor_divide'): + a // -1 + elif fo.min: + a // -1 + with pytest.raises(FloatingPointError, + match="divide by zero encountered in floor_divide"): + a // 0 + with pytest.raises(FloatingPointError, + match="divide by zero encountered in floor_divide"): + ac = a.copy() + ac //= 0 + + np.array([], dtype=dtype) // 0 + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + @pytest.mark.parametrize("dtype,ex_val", itertools.product( + sctypes['int'] + sctypes['uint'], ( + "np.array([fo.max, 1, 2, 1, 1, 2, 3], dtype=dtype)", + "np.array([fo.min, 1, -2, 1, 1, 2, -3]).astype(dtype)", + "np.arange(fo.min, fo.min+(100*10), 10, dtype=dtype)", + "np.array(range(fo.max-(100*7), fo.max, 7)).astype(dtype)", + ) + )) + def test_division_int_reduce(self, dtype, ex_val): + fo = np.iinfo(dtype) + a = eval(ex_val) + lst = a.tolist() + c_div = lambda n, d: ( + 0 if d == 0 or (n and n == fo.min and d == -1) else n // d + ) + + with np.errstate(divide='ignore'): + div_a = np.floor_divide.reduce(a) + div_lst = reduce(c_div, lst) + msg = "Reduce floor integer division check" + assert div_a == div_lst, msg + + with np.errstate(divide='raise', over='raise'): + with pytest.raises(FloatingPointError, + match="divide by zero encountered in reduce"): + np.floor_divide.reduce(np.arange(-100, 100).astype(dtype)) + if fo.min: + with pytest.raises(FloatingPointError, + match='overflow encountered in reduce'): + np.floor_divide.reduce( + np.array([fo.min, 1, -1], dtype=dtype) + ) + + @pytest.mark.parametrize( + "dividend,divisor,quotient", + [(np.timedelta64(2, 'Y'), np.timedelta64(2, 'M'), 12), + (np.timedelta64(2, 'Y'), np.timedelta64(-2, 'M'), -12), + (np.timedelta64(-2, 'Y'), np.timedelta64(2, 'M'), -12), + (np.timedelta64(-2, 'Y'), np.timedelta64(-2, 'M'), 12), + (np.timedelta64(2, 'M'), np.timedelta64(-2, 'Y'), -1), + (np.timedelta64(2, 'Y'), np.timedelta64(0, 'M'), 0), + (np.timedelta64(2, 'Y'), 2, np.timedelta64(1, 'Y')), + (np.timedelta64(2, 'Y'), -2, np.timedelta64(-1, 'Y')), + (np.timedelta64(-2, 'Y'), 2, np.timedelta64(-1, 'Y')), + (np.timedelta64(-2, 'Y'), -2, np.timedelta64(1, 'Y')), + (np.timedelta64(-2, 'Y'), -2, np.timedelta64(1, 'Y')), + (np.timedelta64(-2, 'Y'), -3, np.timedelta64(0, 'Y')), + (np.timedelta64(-2, 'Y'), 0, np.timedelta64('Nat', 'Y')), + ]) + def test_division_int_timedelta(self, dividend, divisor, quotient): + # If either divisor is 0 or quotient is Nat, check for division by 0 + if divisor and (isinstance(quotient, int) or not np.isnat(quotient)): + msg = "Timedelta floor division check" + assert dividend // divisor == quotient, msg + + # Test for arrays as well + msg = "Timedelta arrays floor division check" + dividend_array = np.array([dividend] * 5) + quotient_array = np.array([quotient] * 5) + assert all(dividend_array // divisor == quotient_array), msg + else: + if IS_WASM: + pytest.skip("fp errors don't work in wasm") + with np.errstate(divide='raise', invalid='raise'): + with pytest.raises(FloatingPointError): + dividend // divisor + + def test_division_complex(self): + # check that implementation is correct + msg = "Complex division implementation check" + x = np.array([1. + 1. * 1j, 1. + .5 * 1j, 1. + 2. * 1j], dtype=np.complex128) + assert_almost_equal(x**2 / x, x, err_msg=msg) + # check overflow, underflow + msg = "Complex division overflow/underflow check" + x = np.array([1.e+110, 1.e-110], dtype=np.complex128) + y = x**2 / x + assert_almost_equal(y / x, [1, 1], err_msg=msg) + + def test_zero_division_complex(self): + with np.errstate(invalid="ignore", divide="ignore"): + x = np.array([0.0], dtype=np.complex128) + y = 1.0 / x + assert_(np.isinf(y)[0]) + y = complex(np.inf, np.nan) / x + assert_(np.isinf(y)[0]) + y = complex(np.nan, np.inf) / x + assert_(np.isinf(y)[0]) + y = complex(np.inf, np.inf) / x + assert_(np.isinf(y)[0]) + y = 0.0 / x + assert_(np.isnan(y)[0]) + + def test_floor_division_complex(self): + # check that floor division, divmod and remainder raises type errors + x = np.array([.9 + 1j, -.1 + 1j, .9 + .5 * 1j, .9 + 2. * 1j], dtype=np.complex128) + with pytest.raises(TypeError): + x // 7 + with pytest.raises(TypeError): + np.divmod(x, 7) + with pytest.raises(TypeError): + np.remainder(x, 7) + + def test_floor_division_signed_zero(self): + # Check that the sign bit is correctly set when dividing positive and + # negative zero by one. + x = np.zeros(10) + assert_equal(np.signbit(x // 1), 0) + assert_equal(np.signbit((-x) // 1), 1) + + @pytest.mark.skipif(hasattr(np.__config__, "blas_ssl2_info"), + reason="gh-22982") + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + @pytest.mark.parametrize('dtype', np.typecodes['Float']) + def test_floor_division_errors(self, dtype): + fnan = np.array(np.nan, dtype=dtype) + fone = np.array(1.0, dtype=dtype) + fzer = np.array(0.0, dtype=dtype) + finf = np.array(np.inf, dtype=dtype) + # divide by zero error check + with np.errstate(divide='raise', invalid='ignore'): + assert_raises(FloatingPointError, np.floor_divide, fone, fzer) + with np.errstate(divide='ignore', invalid='raise'): + np.floor_divide(fone, fzer) + + # The following already contain a NaN and should not warn + with np.errstate(all='raise'): + np.floor_divide(fnan, fone) + np.floor_divide(fone, fnan) + np.floor_divide(fnan, fzer) + np.floor_divide(fzer, fnan) + + @pytest.mark.parametrize('dtype', np.typecodes['Float']) + def test_floor_division_corner_cases(self, dtype): + # test corner cases like 1.0//0.0 for errors and return vals + x = np.zeros(10, dtype=dtype) + y = np.ones(10, dtype=dtype) + fnan = np.array(np.nan, dtype=dtype) + fone = np.array(1.0, dtype=dtype) + fzer = np.array(0.0, dtype=dtype) + finf = np.array(np.inf, dtype=dtype) + with warnings.catch_warnings(): + warnings.filterwarnings('ignore', "invalid value encountered in floor_divide", RuntimeWarning) + div = np.floor_divide(fnan, fone) + assert np.isnan(div), f"div: {div}" + div = np.floor_divide(fone, fnan) + assert np.isnan(div), f"div: {div}" + div = np.floor_divide(fnan, fzer) + assert np.isnan(div), f"div: {div}" + # verify 1.0//0.0 computations return inf + with np.errstate(divide='ignore'): + z = np.floor_divide(y, x) + assert_(np.isinf(z).all()) + +def floor_divide_and_remainder(x, y): + return (np.floor_divide(x, y), np.remainder(x, y)) + + +def _signs(dt): + if dt in np.typecodes['UnsignedInteger']: + return (+1,) + else: + return (+1, -1) + + +class TestRemainder: + + def test_remainder_basic(self): + dt = np.typecodes['AllInteger'] + np.typecodes['Float'] + for op in [floor_divide_and_remainder, np.divmod]: + for dt1, dt2 in itertools.product(dt, dt): + for sg1, sg2 in itertools.product(_signs(dt1), _signs(dt2)): + fmt = 'op: %s, dt1: %s, dt2: %s, sg1: %s, sg2: %s' + msg = fmt % (op.__name__, dt1, dt2, sg1, sg2) + a = np.array(sg1 * 71, dtype=dt1) + b = np.array(sg2 * 19, dtype=dt2) + div, rem = op(a, b) + assert_equal(div * b + rem, a, err_msg=msg) + if sg2 == -1: + assert_(b < rem <= 0, msg) + else: + assert_(b > rem >= 0, msg) + + def test_float_remainder_exact(self): + # test that float results are exact for small integers. This also + # holds for the same integers scaled by powers of two. + nlst = list(range(-127, 0)) + plst = list(range(1, 128)) + dividend = nlst + [0] + plst + divisor = nlst + plst + arg = list(itertools.product(dividend, divisor)) + tgt = [divmod(*t) for t in arg] + + a, b = np.array(arg, dtype=int).T + # convert exact integer results from Python to float so that + # signed zero can be used, it is checked. + tgtdiv, tgtrem = np.array(tgt, dtype=float).T + tgtdiv = np.where((tgtdiv == 0.0) & ((b < 0) ^ (a < 0)), -0.0, tgtdiv) + tgtrem = np.where((tgtrem == 0.0) & (b < 0), -0.0, tgtrem) + + for op in [floor_divide_and_remainder, np.divmod]: + for dt in np.typecodes['Float']: + msg = f'op: {op.__name__}, dtype: {dt}' + fa = a.astype(dt) + fb = b.astype(dt) + div, rem = op(fa, fb) + assert_equal(div, tgtdiv, err_msg=msg) + assert_equal(rem, tgtrem, err_msg=msg) + + def test_float_remainder_roundoff(self): + # gh-6127 + dt = np.typecodes['Float'] + for op in [floor_divide_and_remainder, np.divmod]: + for dt1, dt2 in itertools.product(dt, dt): + for sg1, sg2 in itertools.product((+1, -1), (+1, -1)): + fmt = 'op: %s, dt1: %s, dt2: %s, sg1: %s, sg2: %s' + msg = fmt % (op.__name__, dt1, dt2, sg1, sg2) + a = np.array(sg1 * 78 * 6e-8, dtype=dt1) + b = np.array(sg2 * 6e-8, dtype=dt2) + div, rem = op(a, b) + # Equal assertion should hold when fmod is used + assert_equal(div * b + rem, a, err_msg=msg) + if sg2 == -1: + assert_(b < rem <= 0, msg) + else: + assert_(b > rem >= 0, msg) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + @pytest.mark.xfail(sys.platform.startswith("darwin"), + reason="MacOS seems to not give the correct 'invalid' warning for " + "`fmod`. Hopefully, others always do.") + @pytest.mark.parametrize('dtype', np.typecodes['Float']) + def test_float_divmod_errors(self, dtype): + # Check valid errors raised for divmod and remainder + fzero = np.array(0.0, dtype=dtype) + fone = np.array(1.0, dtype=dtype) + finf = np.array(np.inf, dtype=dtype) + fnan = np.array(np.nan, dtype=dtype) + # since divmod is combination of both remainder and divide + # ops it will set both dividebyzero and invalid flags + with np.errstate(divide='raise', invalid='ignore'): + assert_raises(FloatingPointError, np.divmod, fone, fzero) + with np.errstate(divide='ignore', invalid='raise'): + assert_raises(FloatingPointError, np.divmod, fone, fzero) + with np.errstate(invalid='raise'): + assert_raises(FloatingPointError, np.divmod, fzero, fzero) + with np.errstate(invalid='raise'): + assert_raises(FloatingPointError, np.divmod, finf, finf) + with np.errstate(divide='ignore', invalid='raise'): + assert_raises(FloatingPointError, np.divmod, finf, fzero) + with np.errstate(divide='raise', invalid='ignore'): + # inf / 0 does not set any flags, only the modulo creates a NaN + np.divmod(finf, fzero) + + @pytest.mark.skipif(hasattr(np.__config__, "blas_ssl2_info"), + reason="gh-22982") + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + @pytest.mark.xfail(sys.platform.startswith("darwin"), + reason="MacOS seems to not give the correct 'invalid' warning for " + "`fmod`. Hopefully, others always do.") + @pytest.mark.parametrize('dtype', np.typecodes['Float']) + @pytest.mark.parametrize('fn', [np.fmod, np.remainder]) + def test_float_remainder_errors(self, dtype, fn): + fzero = np.array(0.0, dtype=dtype) + fone = np.array(1.0, dtype=dtype) + finf = np.array(np.inf, dtype=dtype) + fnan = np.array(np.nan, dtype=dtype) + + # The following already contain a NaN and should not warn. + with np.errstate(all='raise'): + with pytest.raises(FloatingPointError, + match="invalid value"): + fn(fone, fzero) + fn(fnan, fzero) + fn(fzero, fnan) + fn(fone, fnan) + fn(fnan, fone) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + def test_float_remainder_overflow(self): + a = np.finfo(np.float64).tiny + with np.errstate(over='ignore', invalid='ignore'): + div, mod = np.divmod(4, a) + np.isinf(div) + assert_(mod == 0) + with np.errstate(over='raise', invalid='ignore'): + assert_raises(FloatingPointError, np.divmod, 4, a) + with np.errstate(invalid='raise', over='ignore'): + assert_raises(FloatingPointError, np.divmod, 4, a) + + def test_float_divmod_corner_cases(self): + # check nan cases + for dt in np.typecodes['Float']: + fnan = np.array(np.nan, dtype=dt) + fone = np.array(1.0, dtype=dt) + fzer = np.array(0.0, dtype=dt) + finf = np.array(np.inf, dtype=dt) + with warnings.catch_warnings(): + warnings.filterwarnings('ignore', "invalid value encountered in divmod", RuntimeWarning) + warnings.filterwarnings('ignore', "divide by zero encountered in divmod", RuntimeWarning) + div, rem = np.divmod(fone, fzer) + assert np.isinf(div), f'dt: {dt}, div: {rem}' + assert np.isnan(rem), f'dt: {dt}, rem: {rem}' + div, rem = np.divmod(fzer, fzer) + assert np.isnan(rem), f'dt: {dt}, rem: {rem}' + assert_(np.isnan(div)), f'dt: {dt}, rem: {rem}' + div, rem = np.divmod(finf, finf) + assert np.isnan(div), f'dt: {dt}, rem: {rem}' + assert np.isnan(rem), f'dt: {dt}, rem: {rem}' + div, rem = np.divmod(finf, fzer) + assert np.isinf(div), f'dt: {dt}, rem: {rem}' + assert np.isnan(rem), f'dt: {dt}, rem: {rem}' + div, rem = np.divmod(fnan, fone) + assert np.isnan(rem), f"dt: {dt}, rem: {rem}" + assert np.isnan(div), f"dt: {dt}, rem: {rem}" + div, rem = np.divmod(fone, fnan) + assert np.isnan(rem), f"dt: {dt}, rem: {rem}" + assert np.isnan(div), f"dt: {dt}, rem: {rem}" + div, rem = np.divmod(fnan, fzer) + assert np.isnan(rem), f"dt: {dt}, rem: {rem}" + assert np.isnan(div), f"dt: {dt}, rem: {rem}" + + def test_float_remainder_corner_cases(self): + # Check remainder magnitude. + for dt in np.typecodes['Float']: + fone = np.array(1.0, dtype=dt) + fzer = np.array(0.0, dtype=dt) + fnan = np.array(np.nan, dtype=dt) + b = np.array(1.0, dtype=dt) + a = np.nextafter(np.array(0.0, dtype=dt), -b) + rem = np.remainder(a, b) + assert_(rem <= b, f'dt: {dt}') + rem = np.remainder(-a, -b) + assert_(rem >= -b, f'dt: {dt}') + + # Check nans, inf + with warnings.catch_warnings(): + warnings.filterwarnings('ignore', "invalid value encountered in remainder", RuntimeWarning) + warnings.filterwarnings('ignore', "invalid value encountered in fmod", RuntimeWarning) + for dt in np.typecodes['Float']: + fone = np.array(1.0, dtype=dt) + fzer = np.array(0.0, dtype=dt) + finf = np.array(np.inf, dtype=dt) + fnan = np.array(np.nan, dtype=dt) + rem = np.remainder(fone, fzer) + assert_(np.isnan(rem), f'dt: {dt}, rem: {rem}') + # MSVC 2008 returns NaN here, so disable the check. + #rem = np.remainder(fone, finf) + #assert_(rem == fone, 'dt: %s, rem: %s' % (dt, rem)) + rem = np.remainder(finf, fone) + fmod = np.fmod(finf, fone) + assert_(np.isnan(fmod), f'dt: {dt}, fmod: {fmod}') + assert_(np.isnan(rem), f'dt: {dt}, rem: {rem}') + rem = np.remainder(finf, finf) + fmod = np.fmod(finf, fone) + assert_(np.isnan(rem), f'dt: {dt}, rem: {rem}') + assert_(np.isnan(fmod), f'dt: {dt}, fmod: {fmod}') + rem = np.remainder(finf, fzer) + fmod = np.fmod(finf, fzer) + assert_(np.isnan(rem), f'dt: {dt}, rem: {rem}') + assert_(np.isnan(fmod), f'dt: {dt}, fmod: {fmod}') + rem = np.remainder(fone, fnan) + fmod = np.fmod(fone, fnan) + assert_(np.isnan(rem), f'dt: {dt}, rem: {rem}') + assert_(np.isnan(fmod), f'dt: {dt}, fmod: {fmod}') + rem = np.remainder(fnan, fzer) + fmod = np.fmod(fnan, fzer) + assert_(np.isnan(rem), f'dt: {dt}, rem: {rem}') + assert_(np.isnan(fmod), f'dt: {dt}, fmod: {rem}') + rem = np.remainder(fnan, fone) + fmod = np.fmod(fnan, fone) + assert_(np.isnan(rem), f'dt: {dt}, rem: {rem}') + assert_(np.isnan(fmod), f'dt: {dt}, fmod: {rem}') + + +class TestDivisionIntegerOverflowsAndDivideByZero: + result_type = namedtuple('result_type', + ['nocast', 'casted']) + helper_lambdas = { + 'zero': lambda dtype: 0, + 'min': lambda dtype: np.iinfo(dtype).min, + 'neg_min': lambda dtype: -np.iinfo(dtype).min, + 'min-zero': lambda dtype: (np.iinfo(dtype).min, 0), + 'neg_min-zero': lambda dtype: (-np.iinfo(dtype).min, 0), + } + overflow_results = { + np.remainder: result_type( + helper_lambdas['zero'], helper_lambdas['zero']), + np.fmod: result_type( + helper_lambdas['zero'], helper_lambdas['zero']), + operator.mod: result_type( + helper_lambdas['zero'], helper_lambdas['zero']), + operator.floordiv: result_type( + helper_lambdas['min'], helper_lambdas['neg_min']), + np.floor_divide: result_type( + helper_lambdas['min'], helper_lambdas['neg_min']), + np.divmod: result_type( + helper_lambdas['min-zero'], helper_lambdas['neg_min-zero']) + } + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + @pytest.mark.parametrize("dtype", np.typecodes["Integer"]) + def test_signed_division_overflow(self, dtype): + to_check = interesting_binop_operands(np.iinfo(dtype).min, -1, dtype) + for op1, op2, extractor, operand_identifier in to_check: + with pytest.warns(RuntimeWarning, match="overflow encountered"): + res = op1 // op2 + + assert res.dtype == op1.dtype + assert extractor(res) == np.iinfo(op1.dtype).min + + # Remainder is well defined though, and does not warn: + res = op1 % op2 + assert res.dtype == op1.dtype + assert extractor(res) == 0 + # Check fmod as well: + res = np.fmod(op1, op2) + assert extractor(res) == 0 + + # Divmod warns for the division part: + with pytest.warns(RuntimeWarning, match="overflow encountered"): + res1, res2 = np.divmod(op1, op2) + + assert res1.dtype == res2.dtype == op1.dtype + assert extractor(res1) == np.iinfo(op1.dtype).min + assert extractor(res2) == 0 + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + @pytest.mark.parametrize("dtype", np.typecodes["AllInteger"]) + def test_divide_by_zero(self, dtype): + # Note that the return value cannot be well defined here, but NumPy + # currently uses 0 consistently. This could be changed. + to_check = interesting_binop_operands(1, 0, dtype) + for op1, op2, extractor, operand_identifier in to_check: + with pytest.warns(RuntimeWarning, match="divide by zero"): + res = op1 // op2 + + assert res.dtype == op1.dtype + assert extractor(res) == 0 + + with pytest.warns(RuntimeWarning, match="divide by zero"): + res1, res2 = np.divmod(op1, op2) + + assert res1.dtype == res2.dtype == op1.dtype + assert extractor(res1) == 0 + assert extractor(res2) == 0 + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + @pytest.mark.parametrize("dividend_dtype", sctypes['int']) + @pytest.mark.parametrize("divisor_dtype", sctypes['int']) + @pytest.mark.parametrize("operation", + [np.remainder, np.fmod, np.divmod, np.floor_divide, + operator.mod, operator.floordiv]) + @np.errstate(divide='warn', over='warn') + def test_overflows(self, dividend_dtype, divisor_dtype, operation): + # SIMD tries to perform the operation on as many elements as possible + # that is a multiple of the register's size. We resort to the + # default implementation for the leftover elements. + # We try to cover all paths here. + arrays = [np.array([np.iinfo(dividend_dtype).min] * i, + dtype=dividend_dtype) for i in range(1, 129)] + divisor = np.array([-1], dtype=divisor_dtype) + # If dividend is a larger type than the divisor (`else` case), + # then, result will be a larger type than dividend and will not + # result in an overflow for `divmod` and `floor_divide`. + if np.dtype(dividend_dtype).itemsize >= np.dtype( + divisor_dtype).itemsize and operation in ( + np.divmod, np.floor_divide, operator.floordiv): + with pytest.warns( + RuntimeWarning, + match="overflow encountered in"): + result = operation( + dividend_dtype(np.iinfo(dividend_dtype).min), + divisor_dtype(-1) + ) + assert result == self.overflow_results[operation].nocast( + dividend_dtype) + + # Arrays + for a in arrays: + # In case of divmod, we need to flatten the result + # column first as we get a column vector of quotient and + # remainder and a normal flatten of the expected result. + with pytest.warns( + RuntimeWarning, + match="overflow encountered in"): + result = np.array(operation(a, divisor)).flatten('f') + expected_array = np.array( + [self.overflow_results[operation].nocast( + dividend_dtype)] * len(a)).flatten() + assert_array_equal(result, expected_array) + else: + # Scalars + result = operation( + dividend_dtype(np.iinfo(dividend_dtype).min), + divisor_dtype(-1) + ) + assert result == self.overflow_results[operation].casted( + dividend_dtype) + + # Arrays + for a in arrays: + # See above comment on flatten + result = np.array(operation(a, divisor)).flatten('f') + expected_array = np.array( + [self.overflow_results[operation].casted( + dividend_dtype)] * len(a)).flatten() + assert_array_equal(result, expected_array) + + +class TestCbrt: + def test_cbrt_scalar(self): + assert_almost_equal((np.cbrt(np.float32(-2.5)**3)), -2.5) + + def test_cbrt(self): + x = np.array([1., 2., -3., np.inf, -np.inf]) + assert_almost_equal(np.cbrt(x**3), x) + + assert_(np.isnan(np.cbrt(np.nan))) + assert_equal(np.cbrt(np.inf), np.inf) + assert_equal(np.cbrt(-np.inf), -np.inf) + + +class TestPower: + def test_power_float(self): + x = np.array([1., 2., 3.]) + assert_equal(x**0, [1., 1., 1.]) + assert_equal(x**1, x) + assert_equal(x**2, [1., 4., 9.]) + y = x.copy() + y **= 2 + assert_equal(y, [1., 4., 9.]) + assert_almost_equal(x**(-1), [1., 0.5, 1. / 3]) + assert_almost_equal(x**(0.5), [1., ncu.sqrt(2), ncu.sqrt(3)]) + + for out, inp, msg in _gen_alignment_data(dtype=np.float32, + type='unary', + max_size=11): + exp = [ncu.sqrt(i) for i in inp] + assert_almost_equal(inp**(0.5), exp, err_msg=msg) + np.sqrt(inp, out=out) + assert_equal(out, exp, err_msg=msg) + + for out, inp, msg in _gen_alignment_data(dtype=np.float64, + type='unary', + max_size=7): + exp = [ncu.sqrt(i) for i in inp] + assert_almost_equal(inp**(0.5), exp, err_msg=msg) + np.sqrt(inp, out=out) + assert_equal(out, exp, err_msg=msg) + + def test_power_complex(self): + x = np.array([1 + 2j, 2 + 3j, 3 + 4j]) + assert_equal(x**0, [1., 1., 1.]) + assert_equal(x**1, x) + assert_almost_equal(x**2, [-3 + 4j, -5 + 12j, -7 + 24j]) + assert_almost_equal(x**3, [(1 + 2j)**3, (2 + 3j)**3, (3 + 4j)**3]) + assert_almost_equal(x**4, [(1 + 2j)**4, (2 + 3j)**4, (3 + 4j)**4]) + assert_almost_equal(x**(-1), [1 / (1 + 2j), 1 / (2 + 3j), 1 / (3 + 4j)]) + assert_almost_equal(x**(-2), [1 / (1 + 2j)**2, 1 / (2 + 3j)**2, 1 / (3 + 4j)**2]) + assert_almost_equal(x**(-3), [(-11 + 2j) / 125, (-46 - 9j) / 2197, + (-117 - 44j) / 15625]) + assert_almost_equal(x**(0.5), [ncu.sqrt(1 + 2j), ncu.sqrt(2 + 3j), + ncu.sqrt(3 + 4j)]) + norm = 1. / ((x**14)[0]) + assert_almost_equal(x**14 * norm, + [i * norm for i in [-76443 + 16124j, 23161315 + 58317492j, + 5583548873 + 2465133864j]]) + + # Ticket #836 + def assert_complex_equal(x, y): + assert_array_equal(x.real, y.real) + assert_array_equal(x.imag, y.imag) + + for z in [complex(0, np.inf), complex(1, np.inf)]: + z = np.array([z], dtype=np.complex128) + with np.errstate(invalid="ignore"): + assert_complex_equal(z**1, z) + assert_complex_equal(z**2, z * z) + assert_complex_equal(z**3, z * z * z) + + def test_power_zero(self): + # ticket #1271 + zero = np.array([0j]) + one = np.array([1 + 0j]) + cnan = np.array([complex(np.nan, np.nan)]) + # FIXME cinf not tested. + #cinf = np.array([complex(np.inf, 0)]) + + def assert_complex_equal(x, y): + x, y = np.asarray(x), np.asarray(y) + assert_array_equal(x.real, y.real) + assert_array_equal(x.imag, y.imag) + + # positive powers + for p in [0.33, 0.5, 1, 1.5, 2, 3, 4, 5, 6.6]: + assert_complex_equal(np.power(zero, p), zero) + + # zero power + assert_complex_equal(np.power(zero, 0), one) + with np.errstate(invalid="ignore"): + assert_complex_equal(np.power(zero, 0 + 1j), cnan) + + # negative power + for p in [0.33, 0.5, 1, 1.5, 2, 3, 4, 5, 6.6]: + assert_complex_equal(np.power(zero, -p), cnan) + assert_complex_equal(np.power(zero, -1 + 0.2j), cnan) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + def test_zero_power_nonzero(self): + # Testing 0^{Non-zero} issue 18378 + zero = np.array([0.0 + 0.0j]) + cnan = np.array([complex(np.nan, np.nan)]) + + def assert_complex_equal(x, y): + assert_array_equal(x.real, y.real) + assert_array_equal(x.imag, y.imag) + + # Complex powers with positive real part will not generate a warning + assert_complex_equal(np.power(zero, 1 + 4j), zero) + assert_complex_equal(np.power(zero, 2 - 3j), zero) + # Testing zero values when real part is greater than zero + assert_complex_equal(np.power(zero, 1 + 1j), zero) + assert_complex_equal(np.power(zero, 1 + 0j), zero) + assert_complex_equal(np.power(zero, 1 - 1j), zero) + # Complex powers will negative real part or 0 (provided imaginary + # part is not zero) will generate a NAN and hence a RUNTIME warning + with pytest.warns(expected_warning=RuntimeWarning) as r: + assert_complex_equal(np.power(zero, -1 + 1j), cnan) + assert_complex_equal(np.power(zero, -2 - 3j), cnan) + assert_complex_equal(np.power(zero, -7 + 0j), cnan) + assert_complex_equal(np.power(zero, 0 + 1j), cnan) + assert_complex_equal(np.power(zero, 0 - 1j), cnan) + assert len(r) == 5 + + def test_fast_power(self): + x = np.array([1, 2, 3], np.int16) + res = x**2.0 + assert_((x**2.00001).dtype is res.dtype) + assert_array_equal(res, [1, 4, 9]) + # check the inplace operation on the casted copy doesn't mess with x + assert_(not np.may_share_memory(res, x)) + assert_array_equal(x, [1, 2, 3]) + + # Check that the fast path ignores 1-element not 0-d arrays + res = x ** np.array([[[2]]]) + assert_equal(res.shape, (1, 1, 3)) + + def test_integer_power(self): + a = np.array([15, 15], 'i8') + b = np.power(a, a) + assert_equal(b, [437893890380859375, 437893890380859375]) + + def test_integer_power_with_integer_zero_exponent(self): + dtypes = np.typecodes['Integer'] + for dt in dtypes: + arr = np.arange(-10, 10, dtype=dt) + assert_equal(np.power(arr, 0), np.ones_like(arr)) + + dtypes = np.typecodes['UnsignedInteger'] + for dt in dtypes: + arr = np.arange(10, dtype=dt) + assert_equal(np.power(arr, 0), np.ones_like(arr)) + + def test_integer_power_of_1(self): + dtypes = np.typecodes['AllInteger'] + for dt in dtypes: + arr = np.arange(10, dtype=dt) + assert_equal(np.power(1, arr), np.ones_like(arr)) + + def test_integer_power_of_zero(self): + dtypes = np.typecodes['AllInteger'] + for dt in dtypes: + arr = np.arange(1, 10, dtype=dt) + assert_equal(np.power(0, arr), np.zeros_like(arr)) + + def test_integer_to_negative_power(self): + dtypes = np.typecodes['Integer'] + for dt in dtypes: + a = np.array([0, 1, 2, 3], dtype=dt) + b = np.array([0, 1, 2, -3], dtype=dt) + one = np.array(1, dtype=dt) + minusone = np.array(-1, dtype=dt) + assert_raises(ValueError, np.power, a, b) + assert_raises(ValueError, np.power, a, minusone) + assert_raises(ValueError, np.power, one, b) + assert_raises(ValueError, np.power, one, minusone) + + def test_float_to_inf_power(self): + for dt in [np.float32, np.float64]: + a = np.array([1, 1, 2, 2, -2, -2, np.inf, -np.inf], dt) + b = np.array([np.inf, -np.inf, np.inf, -np.inf, + np.inf, -np.inf, np.inf, -np.inf], dt) + r = np.array([1, 1, np.inf, 0, np.inf, 0, np.inf, 0], dt) + assert_equal(np.power(a, b), r) + + def test_power_fast_paths(self): + # gh-26055 + for dt in [np.float32, np.float64]: + a = np.array([0, 1.1, 2, 12e12, -10., np.inf, -np.inf], dt) + expected = np.array([0.0, 1.21, 4., 1.44e+26, 100, np.inf, np.inf]) + result = np.power(a, 2.) + assert_array_max_ulp(result, expected.astype(dt), maxulp=1) + + a = np.array([0, 1.1, 2, 12e12], dt) + expected = np.sqrt(a).astype(dt) + result = np.power(a, 0.5) + assert_array_max_ulp(result, expected, maxulp=1) + + +class TestFloat_power: + def test_type_conversion(self): + arg_type = '?bhilBHILefdgFDG' + res_type = 'ddddddddddddgDDG' + for dtin, dtout in zip(arg_type, res_type): + msg = f"dtin: {dtin}, dtout: {dtout}" + arg = np.ones(1, dtype=dtin) + res = np.float_power(arg, arg) + assert_(res.dtype.name == np.dtype(dtout).name, msg) + + +class TestLog2: + @pytest.mark.parametrize('dt', ['f', 'd', 'g']) + def test_log2_values(self, dt): + x = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024] + y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] + xf = np.array(x, dtype=dt) + yf = np.array(y, dtype=dt) + assert_almost_equal(np.log2(xf), yf) + + @pytest.mark.parametrize("i", range(1, 65)) + def test_log2_ints(self, i): + # a good log2 implementation should provide this, + # might fail on OS with bad libm + v = np.log2(2.**i) + assert_equal(v, float(i), err_msg='at exponent %d' % i) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + def test_log2_special(self): + assert_equal(np.log2(1.), 0.) + assert_equal(np.log2(np.inf), np.inf) + assert_(np.isnan(np.log2(np.nan))) + + with warnings.catch_warnings(record=True) as w: + warnings.filterwarnings('always', '', RuntimeWarning) + assert_(np.isnan(np.log2(-1.))) + assert_(np.isnan(np.log2(-np.inf))) + assert_equal(np.log2(0.), -np.inf) + assert_(w[0].category is RuntimeWarning) + assert_(w[1].category is RuntimeWarning) + assert_(w[2].category is RuntimeWarning) + + +class TestExp2: + def test_exp2_values(self): + x = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024] + y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] + for dt in ['f', 'd', 'g']: + xf = np.array(x, dtype=dt) + yf = np.array(y, dtype=dt) + assert_almost_equal(np.exp2(yf), xf) + + +class TestLogAddExp2(_FilterInvalids): + # Need test for intermediate precisions + def test_logaddexp2_values(self): + x = [1, 2, 3, 4, 5] + y = [5, 4, 3, 2, 1] + z = [6, 6, 6, 6, 6] + for dt, dec_ in zip(['f', 'd', 'g'], [6, 15, 15]): + xf = np.log2(np.array(x, dtype=dt)) + yf = np.log2(np.array(y, dtype=dt)) + zf = np.log2(np.array(z, dtype=dt)) + assert_almost_equal(np.logaddexp2(xf, yf), zf, decimal=dec_) + + def test_logaddexp2_range(self): + x = [1000000, -1000000, 1000200, -1000200] + y = [1000200, -1000200, 1000000, -1000000] + z = [1000200, -1000000, 1000200, -1000000] + for dt in ['f', 'd', 'g']: + logxf = np.array(x, dtype=dt) + logyf = np.array(y, dtype=dt) + logzf = np.array(z, dtype=dt) + assert_almost_equal(np.logaddexp2(logxf, logyf), logzf) + + def test_inf(self): + inf = np.inf + x = [inf, -inf, inf, -inf, inf, 1, -inf, 1] # noqa: E221 + y = [inf, inf, -inf, -inf, 1, inf, 1, -inf] # noqa: E221 + z = [inf, inf, inf, -inf, inf, inf, 1, 1] + with np.errstate(invalid='raise'): + for dt in ['f', 'd', 'g']: + logxf = np.array(x, dtype=dt) + logyf = np.array(y, dtype=dt) + logzf = np.array(z, dtype=dt) + assert_equal(np.logaddexp2(logxf, logyf), logzf) + + def test_nan(self): + assert_(np.isnan(np.logaddexp2(np.nan, np.inf))) + assert_(np.isnan(np.logaddexp2(np.inf, np.nan))) + assert_(np.isnan(np.logaddexp2(np.nan, 0))) + assert_(np.isnan(np.logaddexp2(0, np.nan))) + assert_(np.isnan(np.logaddexp2(np.nan, np.nan))) + + def test_reduce(self): + assert_equal(np.logaddexp2.identity, -np.inf) + assert_equal(np.logaddexp2.reduce([]), -np.inf) + assert_equal(np.logaddexp2.reduce([-np.inf]), -np.inf) + assert_equal(np.logaddexp2.reduce([-np.inf, 0]), 0) + + +class TestLog: + def test_log_values(self): + x = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024] + y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] + for dt in ['f', 'd', 'g']: + log2_ = 0.69314718055994530943 + xf = np.array(x, dtype=dt) + yf = np.array(y, dtype=dt) * log2_ + assert_almost_equal(np.log(xf), yf) + + # test aliasing(issue #17761) + x = np.array([2, 0.937500, 3, 0.947500, 1.054697]) + xf = np.log(x) + assert_almost_equal(np.log(x, out=x), xf) + + def test_log_values_maxofdtype(self): + # test log() of max for dtype does not raise + dtypes = [np.float32, np.float64] + # This is failing at least on linux aarch64 (see gh-25460), and on most + # other non x86-64 platforms checking `longdouble` isn't too useful as + # it's an alias for float64. + if platform.machine() == 'x86_64': + dtypes += [np.longdouble] + + for dt in dtypes: + with np.errstate(all='raise'): + x = np.finfo(dt).max + np.log(x) + + def test_log_strides(self): + np.random.seed(42) + strides = np.array([-4, -3, -2, -1, 1, 2, 3, 4]) + sizes = np.arange(2, 100) + for ii in sizes: + x_f64 = np.float64(np.random.uniform(low=0.01, high=100.0, size=ii)) + x_special = x_f64.copy() + x_special[3:-1:4] = 1.0 + y_true = np.log(x_f64) + y_special = np.log(x_special) + for jj in strides: + assert_array_almost_equal_nulp(np.log(x_f64[::jj]), y_true[::jj], nulp=2) + assert_array_almost_equal_nulp(np.log(x_special[::jj]), y_special[::jj], nulp=2) + + # Reference values were computed with mpmath, with mp.dps = 200. + @pytest.mark.parametrize( + 'z, wref', + [(1 + 1e-12j, 5e-25 + 1e-12j), + (1.000000000000001 + 3e-08j, + 1.5602230246251546e-15 + 2.999999999999996e-08j), + (0.9999995000000417 + 0.0009999998333333417j, + 7.831475869017683e-18 + 0.001j), + (0.9999999999999996 + 2.999999999999999e-08j, + 5.9107901499372034e-18 + 3e-08j), + (0.99995000042 - 0.009999833j, + -7.015159763822903e-15 - 0.009999999665816696j)], + ) + def test_log_precision_float64(self, z, wref): + w = np.log(z) + assert_allclose(w, wref, rtol=1e-15) + + # Reference values were computed with mpmath, with mp.dps = 200. + @pytest.mark.parametrize( + 'z, wref', + [(np.complex64(1.0 + 3e-6j), np.complex64(4.5e-12 + 3e-06j)), + (np.complex64(1.0 - 2e-5j), np.complex64(1.9999999e-10 - 2e-5j)), + (np.complex64(0.9999999 + 1e-06j), + np.complex64(-1.192088e-07 + 1.0000001e-06j))], + ) + def test_log_precision_float32(self, z, wref): + w = np.log(z) + assert_allclose(w, wref, rtol=1e-6) + + +class TestExp: + def test_exp_values(self): + x = [1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024] + y = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10] + for dt in ['f', 'd', 'g']: + log2_ = 0.69314718055994530943 + xf = np.array(x, dtype=dt) + yf = np.array(y, dtype=dt) * log2_ + assert_almost_equal(np.exp(yf), xf) + + def test_exp_strides(self): + np.random.seed(42) + strides = np.array([-4, -3, -2, -1, 1, 2, 3, 4]) + sizes = np.arange(2, 100) + for ii in sizes: + x_f64 = np.float64(np.random.uniform(low=0.01, high=709.1, size=ii)) + y_true = np.exp(x_f64) + for jj in strides: + assert_array_almost_equal_nulp(np.exp(x_f64[::jj]), y_true[::jj], nulp=2) + +class TestSpecialFloats: + def test_exp_values(self): + with np.errstate(under='raise', over='raise'): + x = [np.nan, np.nan, np.inf, 0.] + y = [np.nan, -np.nan, np.inf, -np.inf] + for dt in ['e', 'f', 'd', 'g']: + xf = np.array(x, dtype=dt) + yf = np.array(y, dtype=dt) + assert_equal(np.exp(yf), xf) + + # See: https://github.com/numpy/numpy/issues/19192 + @pytest.mark.xfail( + _glibc_older_than("2.17"), + reason="Older glibc versions may not raise appropriate FP exceptions" + ) + def test_exp_exceptions(self): + with np.errstate(over='raise'): + assert_raises(FloatingPointError, np.exp, np.float16(11.0899)) + assert_raises(FloatingPointError, np.exp, np.float32(100.)) + assert_raises(FloatingPointError, np.exp, np.float32(1E19)) + assert_raises(FloatingPointError, np.exp, np.float64(800.)) + assert_raises(FloatingPointError, np.exp, np.float64(1E19)) + + with np.errstate(under='raise'): + assert_raises(FloatingPointError, np.exp, np.float16(-17.5)) + assert_raises(FloatingPointError, np.exp, np.float32(-1000.)) + assert_raises(FloatingPointError, np.exp, np.float32(-1E19)) + assert_raises(FloatingPointError, np.exp, np.float64(-1000.)) + assert_raises(FloatingPointError, np.exp, np.float64(-1E19)) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + def test_log_values(self): + with np.errstate(all='ignore'): + x = [np.nan, np.nan, np.inf, np.nan, -np.inf, np.nan] + y = [np.nan, -np.nan, np.inf, -np.inf, 0.0, -1.0] + y1p = [np.nan, -np.nan, np.inf, -np.inf, -1.0, -2.0] + for dt in ['e', 'f', 'd', 'g']: + xf = np.array(x, dtype=dt) + yf = np.array(y, dtype=dt) + yf1p = np.array(y1p, dtype=dt) + assert_equal(np.log(yf), xf) + assert_equal(np.log2(yf), xf) + assert_equal(np.log10(yf), xf) + assert_equal(np.log1p(yf1p), xf) + + with np.errstate(divide='raise'): + for dt in ['e', 'f', 'd']: + assert_raises(FloatingPointError, np.log, + np.array(0.0, dtype=dt)) + assert_raises(FloatingPointError, np.log2, + np.array(0.0, dtype=dt)) + assert_raises(FloatingPointError, np.log10, + np.array(0.0, dtype=dt)) + assert_raises(FloatingPointError, np.log1p, + np.array(-1.0, dtype=dt)) + + with np.errstate(invalid='raise'): + for dt in ['e', 'f', 'd']: + assert_raises(FloatingPointError, np.log, + np.array(-np.inf, dtype=dt)) + assert_raises(FloatingPointError, np.log, + np.array(-1.0, dtype=dt)) + assert_raises(FloatingPointError, np.log2, + np.array(-np.inf, dtype=dt)) + assert_raises(FloatingPointError, np.log2, + np.array(-1.0, dtype=dt)) + assert_raises(FloatingPointError, np.log10, + np.array(-np.inf, dtype=dt)) + assert_raises(FloatingPointError, np.log10, + np.array(-1.0, dtype=dt)) + assert_raises(FloatingPointError, np.log1p, + np.array(-np.inf, dtype=dt)) + assert_raises(FloatingPointError, np.log1p, + np.array(-2.0, dtype=dt)) + + # See https://github.com/numpy/numpy/issues/18005 + with assert_no_warnings(): + a = np.array(1e9, dtype='float32') + np.log(a) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + @pytest.mark.parametrize('dtype', ['e', 'f', 'd', 'g']) + def test_sincos_values(self, dtype): + with np.errstate(all='ignore'): + x = [np.nan, np.nan, np.nan, np.nan] + y = [np.nan, -np.nan, np.inf, -np.inf] + xf = np.array(x, dtype=dtype) + yf = np.array(y, dtype=dtype) + assert_equal(np.sin(yf), xf) + assert_equal(np.cos(yf), xf) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + @pytest.mark.xfail( + sys.platform.startswith("darwin"), + reason="underflow is triggered for scalar 'sin'" + ) + def test_sincos_underflow(self): + with np.errstate(under='raise'): + underflow_trigger = np.array( + float.fromhex("0x1.f37f47a03f82ap-511"), + dtype=np.float64 + ) + np.sin(underflow_trigger) + np.cos(underflow_trigger) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + @pytest.mark.parametrize('callable', [np.sin, np.cos]) + @pytest.mark.parametrize('dtype', ['e', 'f', 'd']) + @pytest.mark.parametrize('value', [np.inf, -np.inf]) + def test_sincos_errors(self, callable, dtype, value): + with np.errstate(invalid='raise'): + assert_raises(FloatingPointError, callable, + np.array([value], dtype=dtype)) + + @pytest.mark.parametrize('callable', [np.sin, np.cos]) + @pytest.mark.parametrize('dtype', ['f', 'd']) + @pytest.mark.parametrize('stride', [-1, 1, 2, 4, 5]) + def test_sincos_overlaps(self, callable, dtype, stride): + N = 100 + M = N // abs(stride) + rng = np.random.default_rng(42) + x = rng.standard_normal(N, dtype) + y = callable(x[::stride]) + callable(x[::stride], out=x[:M]) + assert_equal(x[:M], y) + + @pytest.mark.parametrize('dt', ['e', 'f', 'd', 'g']) + def test_sqrt_values(self, dt): + with np.errstate(all='ignore'): + x = [np.nan, np.nan, np.inf, np.nan, 0.] + y = [np.nan, -np.nan, np.inf, -np.inf, 0.] + xf = np.array(x, dtype=dt) + yf = np.array(y, dtype=dt) + assert_equal(np.sqrt(yf), xf) + + # with np.errstate(invalid='raise'): + # assert_raises( + # FloatingPointError, np.sqrt, np.array(-100., dtype=dt) + # ) + + def test_abs_values(self): + x = [np.nan, np.nan, np.inf, np.inf, 0., 0., 1.0, 1.0] + y = [np.nan, -np.nan, np.inf, -np.inf, 0., -0., -1.0, 1.0] + for dt in ['e', 'f', 'd', 'g']: + xf = np.array(x, dtype=dt) + yf = np.array(y, dtype=dt) + assert_equal(np.abs(yf), xf) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + def test_square_values(self): + x = [np.nan, np.nan, np.inf, np.inf] + y = [np.nan, -np.nan, np.inf, -np.inf] + with np.errstate(all='ignore'): + for dt in ['e', 'f', 'd', 'g']: + xf = np.array(x, dtype=dt) + yf = np.array(y, dtype=dt) + assert_equal(np.square(yf), xf) + + with np.errstate(over='raise'): + assert_raises(FloatingPointError, np.square, + np.array(1E3, dtype='e')) + assert_raises(FloatingPointError, np.square, + np.array(1E32, dtype='f')) + assert_raises(FloatingPointError, np.square, + np.array(1E200, dtype='d')) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + def test_reciprocal_values(self): + with np.errstate(all='ignore'): + x = [np.nan, np.nan, 0.0, -0.0, np.inf, -np.inf] + y = [np.nan, -np.nan, np.inf, -np.inf, 0., -0.] + for dt in ['e', 'f', 'd', 'g']: + xf = np.array(x, dtype=dt) + yf = np.array(y, dtype=dt) + assert_equal(np.reciprocal(yf), xf) + + with np.errstate(divide='raise'): + for dt in ['e', 'f', 'd', 'g']: + assert_raises(FloatingPointError, np.reciprocal, + np.array(-0.0, dtype=dt)) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + def test_tan(self): + with np.errstate(all='ignore'): + in_ = [np.nan, -np.nan, 0.0, -0.0, np.inf, -np.inf] + out = [np.nan, np.nan, 0.0, -0.0, np.nan, np.nan] + for dt in ['e', 'f', 'd']: + in_arr = np.array(in_, dtype=dt) + out_arr = np.array(out, dtype=dt) + assert_equal(np.tan(in_arr), out_arr) + + with np.errstate(invalid='raise'): + for dt in ['e', 'f', 'd']: + assert_raises(FloatingPointError, np.tan, + np.array(np.inf, dtype=dt)) + assert_raises(FloatingPointError, np.tan, + np.array(-np.inf, dtype=dt)) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + def test_arcsincos(self): + with np.errstate(all='ignore'): + in_ = [np.nan, -np.nan, np.inf, -np.inf] + out = [np.nan, np.nan, np.nan, np.nan] + for dt in ['e', 'f', 'd']: + in_arr = np.array(in_, dtype=dt) + out_arr = np.array(out, dtype=dt) + assert_equal(np.arcsin(in_arr), out_arr) + assert_equal(np.arccos(in_arr), out_arr) + + for callable in [np.arcsin, np.arccos]: + for value in [np.inf, -np.inf, 2.0, -2.0]: + for dt in ['e', 'f', 'd']: + with np.errstate(invalid='raise'): + assert_raises(FloatingPointError, callable, + np.array(value, dtype=dt)) + + def test_arctan(self): + with np.errstate(all='ignore'): + in_ = [np.nan, -np.nan] + out = [np.nan, np.nan] + for dt in ['e', 'f', 'd']: + in_arr = np.array(in_, dtype=dt) + out_arr = np.array(out, dtype=dt) + assert_equal(np.arctan(in_arr), out_arr) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + def test_sinh(self): + in_ = [np.nan, -np.nan, np.inf, -np.inf] + out = [np.nan, np.nan, np.inf, -np.inf] + for dt in ['e', 'f', 'd']: + in_arr = np.array(in_, dtype=dt) + out_arr = np.array(out, dtype=dt) + assert_equal(np.sinh(in_arr), out_arr) + + with np.errstate(over='raise'): + assert_raises(FloatingPointError, np.sinh, + np.array(12.0, dtype='e')) + assert_raises(FloatingPointError, np.sinh, + np.array(120.0, dtype='f')) + assert_raises(FloatingPointError, np.sinh, + np.array(1200.0, dtype='d')) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + @pytest.mark.skipif('bsd' in sys.platform, + reason="fallback implementation may not raise, see gh-2487") + def test_cosh(self): + in_ = [np.nan, -np.nan, np.inf, -np.inf] + out = [np.nan, np.nan, np.inf, np.inf] + for dt in ['e', 'f', 'd']: + in_arr = np.array(in_, dtype=dt) + out_arr = np.array(out, dtype=dt) + assert_equal(np.cosh(in_arr), out_arr) + + with np.errstate(over='raise'): + assert_raises(FloatingPointError, np.cosh, + np.array(12.0, dtype='e')) + assert_raises(FloatingPointError, np.cosh, + np.array(120.0, dtype='f')) + assert_raises(FloatingPointError, np.cosh, + np.array(1200.0, dtype='d')) + + def test_tanh(self): + in_ = [np.nan, -np.nan, np.inf, -np.inf] + out = [np.nan, np.nan, 1.0, -1.0] + for dt in ['e', 'f', 'd']: + in_arr = np.array(in_, dtype=dt) + out_arr = np.array(out, dtype=dt) + assert_array_max_ulp(np.tanh(in_arr), out_arr, 3) + + def test_arcsinh(self): + in_ = [np.nan, -np.nan, np.inf, -np.inf] + out = [np.nan, np.nan, np.inf, -np.inf] + for dt in ['e', 'f', 'd']: + in_arr = np.array(in_, dtype=dt) + out_arr = np.array(out, dtype=dt) + assert_equal(np.arcsinh(in_arr), out_arr) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + def test_arccosh(self): + with np.errstate(all='ignore'): + in_ = [np.nan, -np.nan, np.inf, -np.inf, 1.0, 0.0] + out = [np.nan, np.nan, np.inf, np.nan, 0.0, np.nan] + for dt in ['e', 'f', 'd']: + in_arr = np.array(in_, dtype=dt) + out_arr = np.array(out, dtype=dt) + assert_equal(np.arccosh(in_arr), out_arr) + + for value in [0.0, -np.inf]: + with np.errstate(invalid='raise'): + for dt in ['e', 'f', 'd']: + assert_raises(FloatingPointError, np.arccosh, + np.array(value, dtype=dt)) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + def test_arctanh(self): + with np.errstate(all='ignore'): + in_ = [np.nan, -np.nan, np.inf, -np.inf, 1.0, -1.0, 2.0] + out = [np.nan, np.nan, np.nan, np.nan, np.inf, -np.inf, np.nan] + for dt in ['e', 'f', 'd']: + in_arr = np.array(in_, dtype=dt) + out_arr = np.array(out, dtype=dt) + assert_equal(np.arctanh(in_arr), out_arr) + + for value in [1.01, np.inf, -np.inf, 1.0, -1.0]: + with np.errstate(invalid='raise', divide='raise'): + for dt in ['e', 'f', 'd']: + assert_raises(FloatingPointError, np.arctanh, + np.array(value, dtype=dt)) + + # Make sure glibc < 2.18 atanh is not used, issue 25087 + assert np.signbit(np.arctanh(-1j).real) + + # See: https://github.com/numpy/numpy/issues/20448 + @pytest.mark.xfail( + _glibc_older_than("2.17"), + reason="Older glibc versions may not raise appropriate FP exceptions" + ) + def test_exp2(self): + with np.errstate(all='ignore'): + in_ = [np.nan, -np.nan, np.inf, -np.inf] + out = [np.nan, np.nan, np.inf, 0.0] + for dt in ['e', 'f', 'd']: + in_arr = np.array(in_, dtype=dt) + out_arr = np.array(out, dtype=dt) + assert_equal(np.exp2(in_arr), out_arr) + + for value in [2000.0, -2000.0]: + with np.errstate(over='raise', under='raise'): + for dt in ['e', 'f', 'd']: + assert_raises(FloatingPointError, np.exp2, + np.array(value, dtype=dt)) + + @pytest.mark.skipif(IS_WASM, reason="fp errors don't work in wasm") + def test_expm1(self): + with np.errstate(all='ignore'): + in_ = [np.nan, -np.nan, np.inf, -np.inf] + out = [np.nan, np.nan, np.inf, -1.0] + for dt in ['e', 'f', 'd']: + in_arr = np.array(in_, dtype=dt) + out_arr = np.array(out, dtype=dt) + assert_equal(np.expm1(in_arr), out_arr) + + for value in [200.0, 2000.0]: + with np.errstate(over='raise'): + for dt in ['e', 'f']: + assert_raises(FloatingPointError, np.expm1, + np.array(value, dtype=dt)) + + # test to ensure no spurious FP exceptions are raised due to SIMD + INF_INVALID_ERR = [ + np.cos, np.sin, np.tan, np.arccos, np.arcsin, np.spacing, np.arctanh + ] + NEG_INVALID_ERR = [ + np.log, np.log2, np.log10, np.log1p, np.sqrt, np.arccosh, + np.arctanh + ] + ONE_INVALID_ERR = [ + np.arctanh, + ] + LTONE_INVALID_ERR = [ + np.arccosh, + ] + BYZERO_ERR = [ + np.log, np.log2, np.log10, np.reciprocal, np.arccosh + ] + + @pytest.mark.parametrize("ufunc", UFUNCS_UNARY_FP) + @pytest.mark.parametrize("dtype", ('e', 'f', 'd')) + @pytest.mark.parametrize("data, escape", ( + ([0.03], LTONE_INVALID_ERR), + ([0.03] * 32, LTONE_INVALID_ERR), + # neg + ([-1.0], NEG_INVALID_ERR), + ([-1.0] * 32, NEG_INVALID_ERR), + # flat + ([1.0], ONE_INVALID_ERR), + ([1.0] * 32, ONE_INVALID_ERR), + # zero + ([0.0], BYZERO_ERR), + ([0.0] * 32, BYZERO_ERR), + ([-0.0], BYZERO_ERR), + ([-0.0] * 32, BYZERO_ERR), + # nan + ([0.5, 0.5, 0.5, np.nan], LTONE_INVALID_ERR), + ([0.5, 0.5, 0.5, np.nan] * 32, LTONE_INVALID_ERR), + ([np.nan, 1.0, 1.0, 1.0], ONE_INVALID_ERR), + ([np.nan, 1.0, 1.0, 1.0] * 32, ONE_INVALID_ERR), + ([np.nan], []), + ([np.nan] * 32, []), + # inf + ([0.5, 0.5, 0.5, np.inf], INF_INVALID_ERR + LTONE_INVALID_ERR), + ([0.5, 0.5, 0.5, np.inf] * 32, INF_INVALID_ERR + LTONE_INVALID_ERR), + ([np.inf, 1.0, 1.0, 1.0], INF_INVALID_ERR), + ([np.inf, 1.0, 1.0, 1.0] * 32, INF_INVALID_ERR), + ([np.inf], INF_INVALID_ERR), + ([np.inf] * 32, INF_INVALID_ERR), + # ninf + ([0.5, 0.5, 0.5, -np.inf], + NEG_INVALID_ERR + INF_INVALID_ERR + LTONE_INVALID_ERR), + ([0.5, 0.5, 0.5, -np.inf] * 32, + NEG_INVALID_ERR + INF_INVALID_ERR + LTONE_INVALID_ERR), + ([-np.inf, 1.0, 1.0, 1.0], NEG_INVALID_ERR + INF_INVALID_ERR), + ([-np.inf, 1.0, 1.0, 1.0] * 32, NEG_INVALID_ERR + INF_INVALID_ERR), + ([-np.inf], NEG_INVALID_ERR + INF_INVALID_ERR), + ([-np.inf] * 32, NEG_INVALID_ERR + INF_INVALID_ERR), + )) + def test_unary_spurious_fpexception(self, ufunc, dtype, data, escape): + if escape and ufunc in escape: + return + # FIXME: NAN raises FP invalid exception: + # - ceil/float16 on MSVC:32-bit + # - spacing/float16 on almost all platforms + # - spacing/float32,float64 on Windows MSVC with VS2022 + if ufunc in (np.spacing, np.ceil) and dtype == 'e': + return + # Skip spacing tests with NaN on Windows MSVC (all dtypes) + import platform + if (ufunc == np.spacing and + platform.system() == 'Windows' and + any(np.isnan(d) if isinstance(d, (int, float)) else False for d in data)): + pytest.skip("spacing with NaN generates warnings on Windows/VS2022") + array = np.array(data, dtype=dtype) + with assert_no_warnings(): + ufunc(array) + + @pytest.mark.parametrize("dtype", ('e', 'f', 'd')) + def test_divide_spurious_fpexception(self, dtype): + dt = np.dtype(dtype) + dt_info = np.finfo(dt) + subnorm = dt_info.smallest_subnormal + # Verify a bug fix caused due to filling the remaining lanes of the + # partially loaded dividend SIMD vector with ones, which leads to + # raising an overflow warning when the divisor is denormal. + # see https://github.com/numpy/numpy/issues/25097 + with assert_no_warnings(): + np.zeros(128 + 1, dtype=dt) / subnorm + +class TestFPClass: + @pytest.mark.parametrize("stride", [-5, -4, -3, -2, -1, 1, + 2, 4, 5, 6, 7, 8, 9, 10]) + def test_fpclass(self, stride): + arr_f64 = np.array([np.nan, -np.nan, np.inf, -np.inf, -1.0, 1.0, -0.0, 0.0, 2.2251e-308, -2.2251e-308], dtype='d') + arr_f32 = np.array([np.nan, -np.nan, np.inf, -np.inf, -1.0, 1.0, -0.0, 0.0, 1.4013e-045, -1.4013e-045], dtype='f') + nan = np.array([True, True, False, False, False, False, False, False, False, False]) # noqa: E221 + inf = np.array([False, False, True, True, False, False, False, False, False, False]) # noqa: E221 + sign = np.array([False, True, False, True, True, False, True, False, False, True]) # noqa: E221 + finite = np.array([False, False, False, False, True, True, True, True, True, True]) # noqa: E221 + assert_equal(np.isnan(arr_f32[::stride]), nan[::stride]) + assert_equal(np.isnan(arr_f64[::stride]), nan[::stride]) + assert_equal(np.isinf(arr_f32[::stride]), inf[::stride]) + assert_equal(np.isinf(arr_f64[::stride]), inf[::stride]) + if platform.machine() == 'riscv64': + # On RISC-V, many operations that produce NaNs, such as converting + # a -NaN from f64 to f32, return a canonical NaN. The canonical + # NaNs are always positive. See section 11.3 NaN Generation and + # Propagation of the RISC-V Unprivileged ISA for more details. + # We disable the sign test on riscv64 for -np.nan as we + # cannot assume that its sign will be honoured in these tests. + arr_f64_rv = np.copy(arr_f64) + arr_f32_rv = np.copy(arr_f32) + arr_f64_rv[1] = -1.0 + arr_f32_rv[1] = -1.0 + assert_equal(np.signbit(arr_f32_rv[::stride]), sign[::stride]) + assert_equal(np.signbit(arr_f64_rv[::stride]), sign[::stride]) + else: + assert_equal(np.signbit(arr_f32[::stride]), sign[::stride]) + assert_equal(np.signbit(arr_f64[::stride]), sign[::stride]) + assert_equal(np.isfinite(arr_f32[::stride]), finite[::stride]) + assert_equal(np.isfinite(arr_f64[::stride]), finite[::stride]) + + @pytest.mark.parametrize("dtype", ['d', 'f']) + def test_fp_noncontiguous(self, dtype): + data = np.array([np.nan, -np.nan, np.inf, -np.inf, -1.0, + 1.0, -0.0, 0.0, 2.2251e-308, + -2.2251e-308], dtype=dtype) + nan = np.array([True, True, False, False, False, False, + False, False, False, False]) + inf = np.array([False, False, True, True, False, False, + False, False, False, False]) + sign = np.array([False, True, False, True, True, False, + True, False, False, True]) + finite = np.array([False, False, False, False, True, True, + True, True, True, True]) + out = np.ndarray(data.shape, dtype='bool') + ncontig_in = data[1::3] + ncontig_out = out[1::3] + contig_in = np.array(ncontig_in) + + if platform.machine() == 'riscv64': + # Disable the -np.nan signbit tests on riscv64. See comments in + # test_fpclass for more details. + data_rv = np.copy(data) + data_rv[1] = -1.0 + ncontig_sign_in = data_rv[1::3] + contig_sign_in = np.array(ncontig_sign_in) + else: + ncontig_sign_in = ncontig_in + contig_sign_in = contig_in + + assert_equal(ncontig_in.flags.c_contiguous, False) + assert_equal(ncontig_out.flags.c_contiguous, False) + assert_equal(contig_in.flags.c_contiguous, True) + assert_equal(ncontig_sign_in.flags.c_contiguous, False) + assert_equal(contig_sign_in.flags.c_contiguous, True) + # ncontig in, ncontig out + assert_equal(np.isnan(ncontig_in, out=ncontig_out), nan[1::3]) + assert_equal(np.isinf(ncontig_in, out=ncontig_out), inf[1::3]) + assert_equal(np.signbit(ncontig_sign_in, out=ncontig_out), sign[1::3]) + assert_equal(np.isfinite(ncontig_in, out=ncontig_out), finite[1::3]) + # contig in, ncontig out + assert_equal(np.isnan(contig_in, out=ncontig_out), nan[1::3]) + assert_equal(np.isinf(contig_in, out=ncontig_out), inf[1::3]) + assert_equal(np.signbit(contig_sign_in, out=ncontig_out), sign[1::3]) + assert_equal(np.isfinite(contig_in, out=ncontig_out), finite[1::3]) + # ncontig in, contig out + assert_equal(np.isnan(ncontig_in), nan[1::3]) + assert_equal(np.isinf(ncontig_in), inf[1::3]) + assert_equal(np.signbit(ncontig_sign_in), sign[1::3]) + assert_equal(np.isfinite(ncontig_in), finite[1::3]) + # contig in, contig out, nd stride + data_split = np.array(np.array_split(data, 2)) + nan_split = np.array(np.array_split(nan, 2)) + inf_split = np.array(np.array_split(inf, 2)) + sign_split = np.array(np.array_split(sign, 2)) + finite_split = np.array(np.array_split(finite, 2)) + assert_equal(np.isnan(data_split), nan_split) + assert_equal(np.isinf(data_split), inf_split) + if platform.machine() == 'riscv64': + data_split_rv = np.array(np.array_split(data_rv, 2)) + assert_equal(np.signbit(data_split_rv), sign_split) + else: + assert_equal(np.signbit(data_split), sign_split) + assert_equal(np.isfinite(data_split), finite_split) + +class TestLDExp: + @pytest.mark.parametrize("stride", [-4, -2, -1, 1, 2, 4]) + @pytest.mark.parametrize("dtype", ['f', 'd']) + def test_ldexp(self, dtype, stride): + mant = np.array([0.125, 0.25, 0.5, 1., 1., 2., 4., 8.], dtype=dtype) + exp = np.array([3, 2, 1, 0, 0, -1, -2, -3], dtype='i') + out = np.zeros(8, dtype=dtype) + assert_equal(np.ldexp(mant[::stride], exp[::stride], out=out[::stride]), np.ones(8, dtype=dtype)[::stride]) + assert_equal(out[::stride], np.ones(8, dtype=dtype)[::stride]) + +class TestFRExp: + @pytest.mark.parametrize("stride", [-4, -2, -1, 1, 2, 4]) + @pytest.mark.parametrize("dtype", ['f', 'd']) + @pytest.mark.skipif(not sys.platform.startswith('linux'), + reason="np.frexp gives different answers for NAN/INF on windows and linux") + @pytest.mark.xfail(IS_MUSL, reason="gh23049") + def test_frexp(self, dtype, stride): + arr = np.array([np.nan, np.nan, np.inf, -np.inf, 0.0, -0.0, 1.0, -1.0], dtype=dtype) + mant_true = np.array([np.nan, np.nan, np.inf, -np.inf, 0.0, -0.0, 0.5, -0.5], dtype=dtype) + exp_true = np.array([0, 0, 0, 0, 0, 0, 1, 1], dtype='i') + out_mant = np.ones(8, dtype=dtype) + out_exp = 2 * np.ones(8, dtype='i') + mant, exp = np.frexp(arr[::stride], out=(out_mant[::stride], out_exp[::stride])) + assert_equal(mant_true[::stride], mant) + assert_equal(exp_true[::stride], exp) + assert_equal(out_mant[::stride], mant_true[::stride]) + assert_equal(out_exp[::stride], exp_true[::stride]) + + +# func : [maxulperror, low, high] +avx_ufuncs = {'sqrt' : [1, 0., 100.], # noqa: E203 + 'absolute' : [0, -100., 100.], # noqa: E203 + 'reciprocal' : [1, 1., 100.], # noqa: E203 + 'square' : [1, -100., 100.], # noqa: E203 + 'rint' : [0, -100., 100.], # noqa: E203 + 'floor' : [0, -100., 100.], # noqa: E203 + 'ceil' : [0, -100., 100.], # noqa: E203 + 'trunc' : [0, -100., 100.]} # noqa: E203 + +class TestAVXUfuncs: + def test_avx_based_ufunc(self): + strides = np.array([-4, -3, -2, -1, 1, 2, 3, 4]) + np.random.seed(42) + for func, prop in avx_ufuncs.items(): + maxulperr = prop[0] + minval = prop[1] + maxval = prop[2] + # various array sizes to ensure masking in AVX is tested + for size in range(1, 32): + myfunc = getattr(np, func) + x_f32 = np.random.uniform(low=minval, high=maxval, + size=size).astype(np.float32) + x_f64 = x_f32.astype(np.float64) + x_f128 = x_f32.astype(np.longdouble) + y_true128 = myfunc(x_f128) + if maxulperr == 0: + assert_equal(myfunc(x_f32), y_true128.astype(np.float32)) + assert_equal(myfunc(x_f64), y_true128.astype(np.float64)) + else: + assert_array_max_ulp(myfunc(x_f32), + y_true128.astype(np.float32), + maxulp=maxulperr) + assert_array_max_ulp(myfunc(x_f64), + y_true128.astype(np.float64), + maxulp=maxulperr) + # various strides to test gather instruction + if size > 1: + y_true32 = myfunc(x_f32) + y_true64 = myfunc(x_f64) + for jj in strides: + assert_equal(myfunc(x_f64[::jj]), y_true64[::jj]) + assert_equal(myfunc(x_f32[::jj]), y_true32[::jj]) + +class TestAVXFloat32Transcendental: + def test_exp_float32(self): + np.random.seed(42) + x_f32 = np.float32(np.random.uniform(low=0.0, high=88.1, size=1000000)) + x_f64 = np.float64(x_f32) + assert_array_max_ulp(np.exp(x_f32), np.float32(np.exp(x_f64)), maxulp=3) + + def test_log_float32(self): + np.random.seed(42) + x_f32 = np.float32(np.random.uniform(low=0.0, high=1000, size=1000000)) + x_f64 = np.float64(x_f32) + assert_array_max_ulp(np.log(x_f32), np.float32(np.log(x_f64)), maxulp=4) + + def test_sincos_float32(self): + np.random.seed(42) + N = 1000000 + M = np.int_(N / 20) + index = np.random.randint(low=0, high=N, size=M) + x_f32 = np.float32(np.random.uniform(low=-100., high=100., size=N)) + if not _glibc_older_than("2.17"): + # test coverage for elements > 117435.992f for which glibc is used + # this is known to be problematic on old glibc, so skip it there + x_f32[index] = np.float32(10E+10 * np.random.rand(M)) + x_f64 = np.float64(x_f32) + assert_array_max_ulp(np.sin(x_f32), np.float32(np.sin(x_f64)), maxulp=2) + assert_array_max_ulp(np.cos(x_f32), np.float32(np.cos(x_f64)), maxulp=2) + # test aliasing(issue #17761) + tx_f32 = x_f32.copy() + assert_array_max_ulp(np.sin(x_f32, out=x_f32), np.float32(np.sin(x_f64)), maxulp=2) + assert_array_max_ulp(np.cos(tx_f32, out=tx_f32), np.float32(np.cos(x_f64)), maxulp=2) + + def test_strided_float32(self): + np.random.seed(42) + strides = np.array([-4, -3, -2, -1, 1, 2, 3, 4]) + sizes = np.arange(2, 100) + for ii in sizes: + x_f32 = np.float32(np.random.uniform(low=0.01, high=88.1, size=ii)) + x_f32_large = x_f32.copy() + x_f32_large[3:-1:4] = 120000.0 + exp_true = np.exp(x_f32) + log_true = np.log(x_f32) + sin_true = np.sin(x_f32_large) + cos_true = np.cos(x_f32_large) + for jj in strides: + assert_array_almost_equal_nulp(np.exp(x_f32[::jj]), exp_true[::jj], nulp=2) + assert_array_almost_equal_nulp(np.log(x_f32[::jj]), log_true[::jj], nulp=2) + assert_array_almost_equal_nulp(np.sin(x_f32_large[::jj]), sin_true[::jj], nulp=2) + assert_array_almost_equal_nulp(np.cos(x_f32_large[::jj]), cos_true[::jj], nulp=2) + +class TestLogAddExp(_FilterInvalids): + def test_logaddexp_values(self): + x = [1, 2, 3, 4, 5] + y = [5, 4, 3, 2, 1] + z = [6, 6, 6, 6, 6] + for dt, dec_ in zip(['f', 'd', 'g'], [6, 15, 15]): + xf = np.log(np.array(x, dtype=dt)) + yf = np.log(np.array(y, dtype=dt)) + zf = np.log(np.array(z, dtype=dt)) + assert_almost_equal(np.logaddexp(xf, yf), zf, decimal=dec_) + + def test_logaddexp_range(self): + x = [1000000, -1000000, 1000200, -1000200] + y = [1000200, -1000200, 1000000, -1000000] + z = [1000200, -1000000, 1000200, -1000000] + for dt in ['f', 'd', 'g']: + logxf = np.array(x, dtype=dt) + logyf = np.array(y, dtype=dt) + logzf = np.array(z, dtype=dt) + assert_almost_equal(np.logaddexp(logxf, logyf), logzf) + + def test_inf(self): + inf = np.inf + x = [inf, -inf, inf, -inf, inf, 1, -inf, 1] # noqa: E221 + y = [inf, inf, -inf, -inf, 1, inf, 1, -inf] # noqa: E221 + z = [inf, inf, inf, -inf, inf, inf, 1, 1] + with np.errstate(invalid='raise'): + for dt in ['f', 'd', 'g']: + logxf = np.array(x, dtype=dt) + logyf = np.array(y, dtype=dt) + logzf = np.array(z, dtype=dt) + assert_equal(np.logaddexp(logxf, logyf), logzf) + + def test_nan(self): + assert_(np.isnan(np.logaddexp(np.nan, np.inf))) + assert_(np.isnan(np.logaddexp(np.inf, np.nan))) + assert_(np.isnan(np.logaddexp(np.nan, 0))) + assert_(np.isnan(np.logaddexp(0, np.nan))) + assert_(np.isnan(np.logaddexp(np.nan, np.nan))) + + def test_reduce(self): + assert_equal(np.logaddexp.identity, -np.inf) + assert_equal(np.logaddexp.reduce([]), -np.inf) + + +class TestLog1p: + def test_log1p(self): + assert_almost_equal(ncu.log1p(0.2), ncu.log(1.2)) + assert_almost_equal(ncu.log1p(1e-6), ncu.log(1 + 1e-6)) + + def test_special(self): + with np.errstate(invalid="ignore", divide="ignore"): + assert_equal(ncu.log1p(np.nan), np.nan) + assert_equal(ncu.log1p(np.inf), np.inf) + assert_equal(ncu.log1p(-1.), -np.inf) + assert_equal(ncu.log1p(-2.), np.nan) + assert_equal(ncu.log1p(-np.inf), np.nan) + + +class TestExpm1: + def test_expm1(self): + assert_almost_equal(ncu.expm1(0.2), ncu.exp(0.2) - 1) + assert_almost_equal(ncu.expm1(1e-6), ncu.exp(1e-6) - 1) + + def test_special(self): + assert_equal(ncu.expm1(np.inf), np.inf) + assert_equal(ncu.expm1(0.), 0.) + assert_equal(ncu.expm1(-0.), -0.) + assert_equal(ncu.expm1(np.inf), np.inf) + assert_equal(ncu.expm1(-np.inf), -1.) + + def test_complex(self): + x = np.asarray(1e-12) + assert_allclose(x, ncu.expm1(x)) + x = x.astype(np.complex128) + assert_allclose(x, ncu.expm1(x)) + + +class TestHypot: + def test_simple(self): + assert_almost_equal(ncu.hypot(1, 1), ncu.sqrt(2)) + assert_almost_equal(ncu.hypot(0, 0), 0) + + def test_reduce(self): + assert_almost_equal(ncu.hypot.reduce([3.0, 4.0]), 5.0) + assert_almost_equal(ncu.hypot.reduce([3.0, 4.0, 0]), 5.0) + assert_almost_equal(ncu.hypot.reduce([9.0, 12.0, 20.0]), 25.0) + assert_equal(ncu.hypot.reduce([]), 0.0) + + +def assert_hypot_isnan(x, y): + with np.errstate(invalid='ignore'): + assert_(np.isnan(ncu.hypot(x, y)), + f"hypot({x}, {y}) is {ncu.hypot(x, y)}, not nan") + + +def assert_hypot_isinf(x, y): + with np.errstate(invalid='ignore'): + assert_(np.isinf(ncu.hypot(x, y)), + f"hypot({x}, {y}) is {ncu.hypot(x, y)}, not inf") + + +class TestHypotSpecialValues: + def test_nan_outputs(self): + assert_hypot_isnan(np.nan, np.nan) + assert_hypot_isnan(np.nan, 1) + + def test_nan_outputs2(self): + assert_hypot_isinf(np.nan, np.inf) + assert_hypot_isinf(np.inf, np.nan) + assert_hypot_isinf(np.inf, 0) + assert_hypot_isinf(0, np.inf) + assert_hypot_isinf(np.inf, np.inf) + assert_hypot_isinf(np.inf, 23.0) + + def test_no_fpe(self): + assert_no_warnings(ncu.hypot, np.inf, 0) + + +def assert_arctan2_isnan(x, y): + assert_(np.isnan(ncu.arctan2(x, y)), f"arctan({x}, {y}) is {ncu.arctan2(x, y)}, not nan") + + +def assert_arctan2_ispinf(x, y): + assert_((np.isinf(ncu.arctan2(x, y)) and ncu.arctan2(x, y) > 0), f"arctan({x}, {y}) is {ncu.arctan2(x, y)}, not +inf") + + +def assert_arctan2_isninf(x, y): + assert_((np.isinf(ncu.arctan2(x, y)) and ncu.arctan2(x, y) < 0), f"arctan({x}, {y}) is {ncu.arctan2(x, y)}, not -inf") + + +def assert_arctan2_ispzero(x, y): + assert_((ncu.arctan2(x, y) == 0 and not np.signbit(ncu.arctan2(x, y))), f"arctan({x}, {y}) is {ncu.arctan2(x, y)}, not +0") + + +def assert_arctan2_isnzero(x, y): + assert_((ncu.arctan2(x, y) == 0 and np.signbit(ncu.arctan2(x, y))), f"arctan({x}, {y}) is {ncu.arctan2(x, y)}, not -0") + + +class TestArctan2SpecialValues: + def test_one_one(self): + # atan2(1, 1) returns pi/4. + assert_almost_equal(ncu.arctan2(1, 1), 0.25 * np.pi) + assert_almost_equal(ncu.arctan2(-1, 1), -0.25 * np.pi) + assert_almost_equal(ncu.arctan2(1, -1), 0.75 * np.pi) + + def test_zero_nzero(self): + # atan2(+-0, -0) returns +-pi. + assert_almost_equal(ncu.arctan2(ncu.PZERO, ncu.NZERO), np.pi) + assert_almost_equal(ncu.arctan2(ncu.NZERO, ncu.NZERO), -np.pi) + + def test_zero_pzero(self): + # atan2(+-0, +0) returns +-0. + assert_arctan2_ispzero(ncu.PZERO, ncu.PZERO) + assert_arctan2_isnzero(ncu.NZERO, ncu.PZERO) + + def test_zero_negative(self): + # atan2(+-0, x) returns +-pi for x < 0. + assert_almost_equal(ncu.arctan2(ncu.PZERO, -1), np.pi) + assert_almost_equal(ncu.arctan2(ncu.NZERO, -1), -np.pi) + + def test_zero_positive(self): + # atan2(+-0, x) returns +-0 for x > 0. + assert_arctan2_ispzero(ncu.PZERO, 1) + assert_arctan2_isnzero(ncu.NZERO, 1) + + def test_positive_zero(self): + # atan2(y, +-0) returns +pi/2 for y > 0. + assert_almost_equal(ncu.arctan2(1, ncu.PZERO), 0.5 * np.pi) + assert_almost_equal(ncu.arctan2(1, ncu.NZERO), 0.5 * np.pi) + + def test_negative_zero(self): + # atan2(y, +-0) returns -pi/2 for y < 0. + assert_almost_equal(ncu.arctan2(-1, ncu.PZERO), -0.5 * np.pi) + assert_almost_equal(ncu.arctan2(-1, ncu.NZERO), -0.5 * np.pi) + + def test_any_ninf(self): + # atan2(+-y, -infinity) returns +-pi for finite y > 0. + assert_almost_equal(ncu.arctan2(1, -np.inf), np.pi) + assert_almost_equal(ncu.arctan2(-1, -np.inf), -np.pi) + + def test_any_pinf(self): + # atan2(+-y, +infinity) returns +-0 for finite y > 0. + assert_arctan2_ispzero(1, np.inf) + assert_arctan2_isnzero(-1, np.inf) + + def test_inf_any(self): + # atan2(+-infinity, x) returns +-pi/2 for finite x. + assert_almost_equal(ncu.arctan2( np.inf, 1), 0.5 * np.pi) + assert_almost_equal(ncu.arctan2(-np.inf, 1), -0.5 * np.pi) + + def test_inf_ninf(self): + # atan2(+-infinity, -infinity) returns +-3*pi/4. + assert_almost_equal(ncu.arctan2( np.inf, -np.inf), 0.75 * np.pi) + assert_almost_equal(ncu.arctan2(-np.inf, -np.inf), -0.75 * np.pi) + + def test_inf_pinf(self): + # atan2(+-infinity, +infinity) returns +-pi/4. + assert_almost_equal(ncu.arctan2( np.inf, np.inf), 0.25 * np.pi) + assert_almost_equal(ncu.arctan2(-np.inf, np.inf), -0.25 * np.pi) + + def test_nan_any(self): + # atan2(nan, x) returns nan for any x, including inf + assert_arctan2_isnan(np.nan, np.inf) + assert_arctan2_isnan(np.inf, np.nan) + assert_arctan2_isnan(np.nan, np.nan) + + +class TestLdexp: + def _check_ldexp(self, tp): + assert_almost_equal(ncu.ldexp(np.array(2., np.float32), + np.array(3, tp)), 16.) + assert_almost_equal(ncu.ldexp(np.array(2., np.float64), + np.array(3, tp)), 16.) + assert_almost_equal(ncu.ldexp(np.array(2., np.longdouble), + np.array(3, tp)), 16.) + + def test_ldexp(self): + # The default Python int type should work + assert_almost_equal(ncu.ldexp(2., 3), 16.) + # The following int types should all be accepted + self._check_ldexp(np.int8) + self._check_ldexp(np.int16) + self._check_ldexp(np.int32) + self._check_ldexp('i') + self._check_ldexp('l') + + def test_ldexp_overflow(self): + # silence warning emitted on overflow + with np.errstate(over="ignore"): + imax = np.iinfo(np.dtype('l')).max + imin = np.iinfo(np.dtype('l')).min + assert_equal(ncu.ldexp(2., imax), np.inf) + assert_equal(ncu.ldexp(2., imin), 0) + + +class TestMaximum(_FilterInvalids): + def test_reduce(self): + dflt = np.typecodes['AllFloat'] + dint = np.typecodes['AllInteger'] + seq1 = np.arange(11) + seq2 = seq1[::-1] + func = np.maximum.reduce + for dt in dint: + tmp1 = seq1.astype(dt) + tmp2 = seq2.astype(dt) + assert_equal(func(tmp1), 10) + assert_equal(func(tmp2), 10) + for dt in dflt: + tmp1 = seq1.astype(dt) + tmp2 = seq2.astype(dt) + assert_equal(func(tmp1), 10) + assert_equal(func(tmp2), 10) + tmp1[::2] = np.nan + tmp2[::2] = np.nan + assert_equal(func(tmp1), np.nan) + assert_equal(func(tmp2), np.nan) + + def test_reduce_complex(self): + assert_equal(np.maximum.reduce([1, 2j]), 1) + assert_equal(np.maximum.reduce([1 + 3j, 2j]), 1 + 3j) + + def test_float_nans(self): + nan = np.nan + arg1 = np.array([0, nan, nan]) + arg2 = np.array([nan, 0, nan]) + out = np.array([nan, nan, nan]) + assert_equal(np.maximum(arg1, arg2), out) + + def test_object_nans(self): + # Multiple checks to give this a chance to + # fail if cmp is used instead of rich compare. + # Failure cannot be guaranteed. + for i in range(1): + x = np.array(float('nan'), object) + y = 1.0 + z = np.array(float('nan'), object) + assert_(np.maximum(x, y) == 1.0) + assert_(np.maximum(z, y) == 1.0) + + def test_complex_nans(self): + nan = np.nan + for cnan in [complex(nan, 0), complex(0, nan), complex(nan, nan)]: + arg1 = np.array([0, cnan, cnan], dtype=complex) + arg2 = np.array([cnan, 0, cnan], dtype=complex) + out = np.array([nan, nan, nan], dtype=complex) + assert_equal(np.maximum(arg1, arg2), out) + + def test_object_array(self): + arg1 = np.arange(5, dtype=object) + arg2 = arg1 + 1 + assert_equal(np.maximum(arg1, arg2), arg2) + + def test_strided_array(self): + arr1 = np.array([-4.0, 1.0, 10.0, 0.0, np.nan, -np.nan, np.inf, -np.inf]) + arr2 = np.array([-2.0, -1.0, np.nan, 1.0, 0.0, np.nan, 1.0, -3.0]) # noqa: E221 + maxtrue = np.array([-2.0, 1.0, np.nan, 1.0, np.nan, np.nan, np.inf, -3.0]) + out = np.ones(8) + out_maxtrue = np.array([-2.0, 1.0, 1.0, 10.0, 1.0, 1.0, np.nan, 1.0]) + assert_equal(np.maximum(arr1, arr2), maxtrue) + assert_equal(np.maximum(arr1[::2], arr2[::2]), maxtrue[::2]) + assert_equal(np.maximum(arr1[:4:], arr2[::2]), np.array([-2.0, np.nan, 10.0, 1.0])) + assert_equal(np.maximum(arr1[::3], arr2[:3:]), np.array([-2.0, 0.0, np.nan])) + assert_equal(np.maximum(arr1[:6:2], arr2[::3], out=out[::3]), np.array([-2.0, 10., np.nan])) + assert_equal(out, out_maxtrue) + + def test_precision(self): + dtypes = [np.float16, np.float32, np.float64, np.longdouble] + + for dt in dtypes: + dtmin = np.finfo(dt).min + dtmax = np.finfo(dt).max + d1 = dt(0.1) + d1_next = np.nextafter(d1, np.inf) + + test_cases = [ + # v1 v2 expected + (dtmin, -np.inf, dtmin), + (dtmax, -np.inf, dtmax), + (d1, d1_next, d1_next), + (dtmax, np.nan, np.nan), + ] + + for v1, v2, expected in test_cases: + assert_equal(np.maximum([v1], [v2]), [expected]) + assert_equal(np.maximum.reduce([v1, v2]), expected) + + +class TestMinimum(_FilterInvalids): + def test_reduce(self): + dflt = np.typecodes['AllFloat'] + dint = np.typecodes['AllInteger'] + seq1 = np.arange(11) + seq2 = seq1[::-1] + func = np.minimum.reduce + for dt in dint: + tmp1 = seq1.astype(dt) + tmp2 = seq2.astype(dt) + assert_equal(func(tmp1), 0) + assert_equal(func(tmp2), 0) + for dt in dflt: + tmp1 = seq1.astype(dt) + tmp2 = seq2.astype(dt) + assert_equal(func(tmp1), 0) + assert_equal(func(tmp2), 0) + tmp1[::2] = np.nan + tmp2[::2] = np.nan + assert_equal(func(tmp1), np.nan) + assert_equal(func(tmp2), np.nan) + + def test_reduce_complex(self): + assert_equal(np.minimum.reduce([1, 2j]), 2j) + assert_equal(np.minimum.reduce([1 + 3j, 2j]), 2j) + + def test_float_nans(self): + nan = np.nan + arg1 = np.array([0, nan, nan]) + arg2 = np.array([nan, 0, nan]) + out = np.array([nan, nan, nan]) + assert_equal(np.minimum(arg1, arg2), out) + + def test_object_nans(self): + # Multiple checks to give this a chance to + # fail if cmp is used instead of rich compare. + # Failure cannot be guaranteed. + for i in range(1): + x = np.array(float('nan'), object) + y = 1.0 + z = np.array(float('nan'), object) + assert_(np.minimum(x, y) == 1.0) + assert_(np.minimum(z, y) == 1.0) + + def test_complex_nans(self): + nan = np.nan + for cnan in [complex(nan, 0), complex(0, nan), complex(nan, nan)]: + arg1 = np.array([0, cnan, cnan], dtype=complex) + arg2 = np.array([cnan, 0, cnan], dtype=complex) + out = np.array([nan, nan, nan], dtype=complex) + assert_equal(np.minimum(arg1, arg2), out) + + def test_object_array(self): + arg1 = np.arange(5, dtype=object) + arg2 = arg1 + 1 + assert_equal(np.minimum(arg1, arg2), arg1) + + def test_strided_array(self): + arr1 = np.array([-4.0, 1.0, 10.0, 0.0, np.nan, -np.nan, np.inf, -np.inf]) + arr2 = np.array([-2.0, -1.0, np.nan, 1.0, 0.0, np.nan, 1.0, -3.0]) + mintrue = np.array([-4.0, -1.0, np.nan, 0.0, np.nan, np.nan, 1.0, -np.inf]) + out = np.ones(8) + out_mintrue = np.array([-4.0, 1.0, 1.0, 1.0, 1.0, 1.0, np.nan, 1.0]) + assert_equal(np.minimum(arr1, arr2), mintrue) + assert_equal(np.minimum(arr1[::2], arr2[::2]), mintrue[::2]) + assert_equal(np.minimum(arr1[:4:], arr2[::2]), np.array([-4.0, np.nan, 0.0, 0.0])) + assert_equal(np.minimum(arr1[::3], arr2[:3:]), np.array([-4.0, -1.0, np.nan])) + assert_equal(np.minimum(arr1[:6:2], arr2[::3], out=out[::3]), np.array([-4.0, 1.0, np.nan])) + assert_equal(out, out_mintrue) + + def test_precision(self): + dtypes = [np.float16, np.float32, np.float64, np.longdouble] + + for dt in dtypes: + dtmin = np.finfo(dt).min + dtmax = np.finfo(dt).max + d1 = dt(0.1) + d1_next = np.nextafter(d1, np.inf) + + test_cases = [ + # v1 v2 expected + (dtmin, np.inf, dtmin), + (dtmax, np.inf, dtmax), + (d1, d1_next, d1), + (dtmin, np.nan, np.nan), + ] + + for v1, v2, expected in test_cases: + assert_equal(np.minimum([v1], [v2]), [expected]) + assert_equal(np.minimum.reduce([v1, v2]), expected) + + +class TestFmax(_FilterInvalids): + def test_reduce(self): + dflt = np.typecodes['AllFloat'] + dint = np.typecodes['AllInteger'] + seq1 = np.arange(11) + seq2 = seq1[::-1] + func = np.fmax.reduce + for dt in dint: + tmp1 = seq1.astype(dt) + tmp2 = seq2.astype(dt) + assert_equal(func(tmp1), 10) + assert_equal(func(tmp2), 10) + for dt in dflt: + tmp1 = seq1.astype(dt) + tmp2 = seq2.astype(dt) + assert_equal(func(tmp1), 10) + assert_equal(func(tmp2), 10) + tmp1[::2] = np.nan + tmp2[::2] = np.nan + assert_equal(func(tmp1), 9) + assert_equal(func(tmp2), 9) + + def test_reduce_complex(self): + assert_equal(np.fmax.reduce([1, 2j]), 1) + assert_equal(np.fmax.reduce([1 + 3j, 2j]), 1 + 3j) + + def test_float_nans(self): + nan = np.nan + arg1 = np.array([0, nan, nan]) + arg2 = np.array([nan, 0, nan]) + out = np.array([0, 0, nan]) + assert_equal(np.fmax(arg1, arg2), out) + + def test_complex_nans(self): + nan = np.nan + for cnan in [complex(nan, 0), complex(0, nan), complex(nan, nan)]: + arg1 = np.array([0, cnan, cnan], dtype=complex) + arg2 = np.array([cnan, 0, cnan], dtype=complex) + out = np.array([0, 0, nan], dtype=complex) + assert_equal(np.fmax(arg1, arg2), out) + + def test_precision(self): + dtypes = [np.float16, np.float32, np.float64, np.longdouble] + + for dt in dtypes: + dtmin = np.finfo(dt).min + dtmax = np.finfo(dt).max + d1 = dt(0.1) + d1_next = np.nextafter(d1, np.inf) + + test_cases = [ + # v1 v2 expected + (dtmin, -np.inf, dtmin), + (dtmax, -np.inf, dtmax), + (d1, d1_next, d1_next), + (dtmax, np.nan, dtmax), + ] + + for v1, v2, expected in test_cases: + assert_equal(np.fmax([v1], [v2]), [expected]) + assert_equal(np.fmax.reduce([v1, v2]), expected) + + +class TestFmin(_FilterInvalids): + def test_reduce(self): + dflt = np.typecodes['AllFloat'] + dint = np.typecodes['AllInteger'] + seq1 = np.arange(11) + seq2 = seq1[::-1] + func = np.fmin.reduce + for dt in dint: + tmp1 = seq1.astype(dt) + tmp2 = seq2.astype(dt) + assert_equal(func(tmp1), 0) + assert_equal(func(tmp2), 0) + for dt in dflt: + tmp1 = seq1.astype(dt) + tmp2 = seq2.astype(dt) + assert_equal(func(tmp1), 0) + assert_equal(func(tmp2), 0) + tmp1[::2] = np.nan + tmp2[::2] = np.nan + assert_equal(func(tmp1), 1) + assert_equal(func(tmp2), 1) + + def test_reduce_complex(self): + assert_equal(np.fmin.reduce([1, 2j]), 2j) + assert_equal(np.fmin.reduce([1 + 3j, 2j]), 2j) + + def test_float_nans(self): + nan = np.nan + arg1 = np.array([0, nan, nan]) + arg2 = np.array([nan, 0, nan]) + out = np.array([0, 0, nan]) + assert_equal(np.fmin(arg1, arg2), out) + + def test_complex_nans(self): + nan = np.nan + for cnan in [complex(nan, 0), complex(0, nan), complex(nan, nan)]: + arg1 = np.array([0, cnan, cnan], dtype=complex) + arg2 = np.array([cnan, 0, cnan], dtype=complex) + out = np.array([0, 0, nan], dtype=complex) + assert_equal(np.fmin(arg1, arg2), out) + + def test_precision(self): + dtypes = [np.float16, np.float32, np.float64, np.longdouble] + + for dt in dtypes: + dtmin = np.finfo(dt).min + dtmax = np.finfo(dt).max + d1 = dt(0.1) + d1_next = np.nextafter(d1, np.inf) + + test_cases = [ + # v1 v2 expected + (dtmin, np.inf, dtmin), + (dtmax, np.inf, dtmax), + (d1, d1_next, d1), + (dtmin, np.nan, dtmin), + ] + + for v1, v2, expected in test_cases: + assert_equal(np.fmin([v1], [v2]), [expected]) + assert_equal(np.fmin.reduce([v1, v2]), expected) + + +class TestBool: + def test_exceptions(self): + a = np.ones(1, dtype=np.bool) + assert_raises(TypeError, np.negative, a) + assert_raises(TypeError, np.positive, a) + assert_raises(TypeError, np.subtract, a, a) + + def test_truth_table_logical(self): + # 2, 3 and 4 serves as true values + input1 = [0, 0, 3, 2] + input2 = [0, 4, 0, 2] + + typecodes = (np.typecodes['AllFloat'] + + np.typecodes['AllInteger'] + + '?') # boolean + for dtype in map(np.dtype, typecodes): + arg1 = np.asarray(input1, dtype=dtype) + arg2 = np.asarray(input2, dtype=dtype) + + # OR + out = [False, True, True, True] + for func in (np.logical_or, np.maximum): + assert_equal(func(arg1, arg2).astype(bool), out) + # AND + out = [False, False, False, True] + for func in (np.logical_and, np.minimum): + assert_equal(func(arg1, arg2).astype(bool), out) + # XOR + out = [False, True, True, False] + for func in (np.logical_xor, np.not_equal): + assert_equal(func(arg1, arg2).astype(bool), out) + + def test_truth_table_bitwise(self): + arg1 = [False, False, True, True] + arg2 = [False, True, False, True] + + out = [False, True, True, True] + assert_equal(np.bitwise_or(arg1, arg2), out) + + out = [False, False, False, True] + assert_equal(np.bitwise_and(arg1, arg2), out) + + out = [False, True, True, False] + assert_equal(np.bitwise_xor(arg1, arg2), out) + + def test_reduce(self): + none = np.array([0, 0, 0, 0], bool) + some = np.array([1, 0, 1, 1], bool) + every = np.array([1, 1, 1, 1], bool) + empty = np.array([], bool) + + arrs = [none, some, every, empty] + + for arr in arrs: + assert_equal(np.logical_and.reduce(arr), all(arr)) + + for arr in arrs: + assert_equal(np.logical_or.reduce(arr), any(arr)) + + for arr in arrs: + assert_equal(np.logical_xor.reduce(arr), arr.sum() % 2 == 1) + + +class TestBitwiseUFuncs: + + _all_ints_bits = [ + np.dtype(c).itemsize * 8 for c in np.typecodes["AllInteger"]] + bitwise_types = [ + np.dtype(c) for c in '?' + np.typecodes["AllInteger"] + 'O'] + bitwise_bits = [ + 2, # boolean type + *_all_ints_bits, # All integers + max(_all_ints_bits) + 1, # Object_ type + ] + + def test_values(self): + for dt in self.bitwise_types: + zeros = np.array([0], dtype=dt) + ones = np.array([-1]).astype(dt) + msg = f"dt = '{dt.char}'" + + assert_equal(np.bitwise_not(zeros), ones, err_msg=msg) + assert_equal(np.bitwise_not(ones), zeros, err_msg=msg) + + assert_equal(np.bitwise_or(zeros, zeros), zeros, err_msg=msg) + assert_equal(np.bitwise_or(zeros, ones), ones, err_msg=msg) + assert_equal(np.bitwise_or(ones, zeros), ones, err_msg=msg) + assert_equal(np.bitwise_or(ones, ones), ones, err_msg=msg) + + assert_equal(np.bitwise_xor(zeros, zeros), zeros, err_msg=msg) + assert_equal(np.bitwise_xor(zeros, ones), ones, err_msg=msg) + assert_equal(np.bitwise_xor(ones, zeros), ones, err_msg=msg) + assert_equal(np.bitwise_xor(ones, ones), zeros, err_msg=msg) + + assert_equal(np.bitwise_and(zeros, zeros), zeros, err_msg=msg) + assert_equal(np.bitwise_and(zeros, ones), zeros, err_msg=msg) + assert_equal(np.bitwise_and(ones, zeros), zeros, err_msg=msg) + assert_equal(np.bitwise_and(ones, ones), ones, err_msg=msg) + + def test_types(self): + for dt in self.bitwise_types: + zeros = np.array([0], dtype=dt) + ones = np.array([-1]).astype(dt) + msg = f"dt = '{dt.char}'" + + assert_(np.bitwise_not(zeros).dtype == dt, msg) + assert_(np.bitwise_or(zeros, zeros).dtype == dt, msg) + assert_(np.bitwise_xor(zeros, zeros).dtype == dt, msg) + assert_(np.bitwise_and(zeros, zeros).dtype == dt, msg) + + def test_identity(self): + assert_(np.bitwise_or.identity == 0, 'bitwise_or') + assert_(np.bitwise_xor.identity == 0, 'bitwise_xor') + assert_(np.bitwise_and.identity == -1, 'bitwise_and') + + def test_reduction(self): + binary_funcs = (np.bitwise_or, np.bitwise_xor, np.bitwise_and) + + for dt in self.bitwise_types: + zeros = np.array([0], dtype=dt) + ones = np.array([-1]).astype(dt) + for f in binary_funcs: + msg = f"dt: '{dt}', f: '{f}'" + assert_equal(f.reduce(zeros), zeros, err_msg=msg) + assert_equal(f.reduce(ones), ones, err_msg=msg) + + # Test empty reduction, no object dtype + for dt in self.bitwise_types[:-1]: + # No object array types + empty = np.array([], dtype=dt) + for f in binary_funcs: + msg = f"dt: '{dt}', f: '{f}'" + tgt = np.array(f.identity).astype(dt) + res = f.reduce(empty) + assert_equal(res, tgt, err_msg=msg) + assert_(res.dtype == tgt.dtype, msg) + + # Empty object arrays use the identity. Note that the types may + # differ, the actual type used is determined by the assign_identity + # function and is not the same as the type returned by the identity + # method. + for f in binary_funcs: + msg = f"dt: '{f}'" + empty = np.array([], dtype=object) + tgt = f.identity + res = f.reduce(empty) + assert_equal(res, tgt, err_msg=msg) + + # Non-empty object arrays do not use the identity + for f in binary_funcs: + msg = f"dt: '{f}'" + btype = np.array([True], dtype=object) + assert_(type(f.reduce(btype)) is bool, msg) + + @pytest.mark.parametrize("input_dtype_obj, bitsize", + zip(bitwise_types, bitwise_bits)) + def test_bitwise_count(self, input_dtype_obj, bitsize): + input_dtype = input_dtype_obj.type + + for i in range(1, bitsize): + num = 2**i - 1 + msg = f"bitwise_count for {num}" + assert i == np.bitwise_count(input_dtype(num)), msg + if np.issubdtype( + input_dtype, np.signedinteger) or input_dtype == np.object_: + assert i == np.bitwise_count(input_dtype(-num)), msg + + a = np.array([2**i - 1 for i in range(1, bitsize)], dtype=input_dtype) + bitwise_count_a = np.bitwise_count(a) + expected = np.arange(1, bitsize, dtype=input_dtype) + + msg = f"array bitwise_count for {input_dtype}" + assert all(bitwise_count_a == expected), msg + + +class TestInt: + def test_logical_not(self): + x = np.ones(10, dtype=np.int16) + o = np.ones(10 * 2, dtype=bool) + tgt = o.copy() + tgt[::2] = False + os = o[::2] + assert_array_equal(np.logical_not(x, out=os), False) + assert_array_equal(o, tgt) + + +class TestFloatingPoint: + def test_floating_point(self): + assert_equal(ncu.FLOATING_POINT_SUPPORT, 1) + + +class TestDegrees: + def test_degrees(self): + assert_almost_equal(ncu.degrees(np.pi), 180.0) + assert_almost_equal(ncu.degrees(-0.5 * np.pi), -90.0) + + +class TestRadians: + def test_radians(self): + assert_almost_equal(ncu.radians(180.0), np.pi) + assert_almost_equal(ncu.radians(-90.0), -0.5 * np.pi) + + +class TestHeavside: + def test_heaviside(self): + x = np.array([[-30.0, -0.1, 0.0, 0.2], [7.5, np.nan, np.inf, -np.inf]]) + expectedhalf = np.array([[0.0, 0.0, 0.5, 1.0], [1.0, np.nan, 1.0, 0.0]]) + expected1 = expectedhalf.copy() + expected1[0, 2] = 1 + + h = ncu.heaviside(x, 0.5) + assert_equal(h, expectedhalf) + + h = ncu.heaviside(x, 1.0) + assert_equal(h, expected1) + + x = x.astype(np.float32) + + h = ncu.heaviside(x, np.float32(0.5)) + assert_equal(h, expectedhalf.astype(np.float32)) + + h = ncu.heaviside(x, np.float32(1.0)) + assert_equal(h, expected1.astype(np.float32)) + + +class TestSign: + def test_sign(self): + a = np.array([np.inf, -np.inf, np.nan, 0.0, 3.0, -3.0]) + out = np.zeros(a.shape) + tgt = np.array([1., -1., np.nan, 0.0, 1.0, -1.0]) + + with np.errstate(invalid='ignore'): + res = ncu.sign(a) + assert_equal(res, tgt) + res = ncu.sign(a, out) + assert_equal(res, tgt) + assert_equal(out, tgt) + + def test_sign_complex(self): + a = np.array([ + np.inf, -np.inf, complex(0, np.inf), complex(0, -np.inf), + complex(np.inf, np.inf), complex(np.inf, -np.inf), # nan + np.nan, complex(0, np.nan), complex(np.nan, np.nan), # nan + 0.0, # 0. + 3.0, -3.0, -2j, 3.0 + 4.0j, -8.0 + 6.0j + ]) + out = np.zeros(a.shape, a.dtype) + tgt = np.array([ + 1., -1., 1j, -1j, + ] + [complex(np.nan, np.nan)] * 5 + [ + 0.0, + 1.0, -1.0, -1j, 0.6 + 0.8j, -0.8 + 0.6j]) + + with np.errstate(invalid='ignore'): + res = ncu.sign(a) + assert_equal(res, tgt) + res = ncu.sign(a, out) + assert_(res is out) + assert_equal(res, tgt) + + def test_sign_dtype_object(self): + # In reference to github issue #6229 + + foo = np.array([-.1, 0, .1]) + a = np.sign(foo.astype(object)) + b = np.sign(foo) + + assert_array_equal(a, b) + + def test_sign_dtype_nan_object(self): + # In reference to github issue #6229 + def test_nan(): + foo = np.array([np.nan]) + # FIXME: a not used + a = np.sign(foo.astype(object)) + + assert_raises(TypeError, test_nan) + +class TestMinMax: + def test_minmax_blocked(self): + # simd tests on max/min, test all alignments, slow but important + # for 2 * vz + 2 * (vs - 1) + 1 (unrolled once) + for dt, sz in [(np.float32, 15), (np.float64, 7)]: + for out, inp, msg in _gen_alignment_data(dtype=dt, type='unary', + max_size=sz): + for i in range(inp.size): + inp[:] = np.arange(inp.size, dtype=dt) + inp[i] = np.nan + emsg = lambda: f'{inp!r}\n{msg}' + with warnings.catch_warnings(): + warnings.filterwarnings( + 'ignore', + "invalid value encountered in reduce", + RuntimeWarning) + assert_(np.isnan(inp.max()), msg=emsg) + assert_(np.isnan(inp.min()), msg=emsg) + + inp[i] = 1e10 + assert_equal(inp.max(), 1e10, err_msg=msg) + inp[i] = -1e10 + assert_equal(inp.min(), -1e10, err_msg=msg) + + def test_lower_align(self): + # check data that is not aligned to element size + # i.e doubles are aligned to 4 bytes on i386 + d = np.zeros(23 * 8, dtype=np.int8)[4:-4].view(np.float64) + assert_equal(d.max(), d[0]) + assert_equal(d.min(), d[0]) + + def test_reduce_reorder(self): + # gh 10370, 11029 Some compilers reorder the call to npy_getfloatstatus + # and put it before the call to an intrinsic function that causes + # invalid status to be set. Also make sure warnings are not emitted + for n in (2, 4, 8, 16, 32): + for dt in (np.float32, np.float16, np.complex64): + for r in np.diagflat(np.array([np.nan] * n, dtype=dt)): + assert_equal(np.min(r), np.nan) + + def test_minimize_no_warns(self): + a = np.minimum(np.nan, 1) + assert_equal(a, np.nan) + + +class TestAbsoluteNegative: + def test_abs_neg_blocked(self): + # simd tests on abs, test all alignments for vz + 2 * (vs - 1) + 1 + for dt, sz in [(np.float32, 11), (np.float64, 5)]: + for out, inp, msg in _gen_alignment_data(dtype=dt, type='unary', + max_size=sz): + tgt = [ncu.absolute(i) for i in inp] + np.absolute(inp, out=out) + assert_equal(out, tgt, err_msg=msg) + assert_((out >= 0).all()) + + tgt = [-1 * (i) for i in inp] + np.negative(inp, out=out) + assert_equal(out, tgt, err_msg=msg) + + for v in [np.nan, -np.inf, np.inf]: + for i in range(inp.size): + d = np.arange(inp.size, dtype=dt) + inp[:] = -d + inp[i] = v + d[i] = -v if v == -np.inf else v + assert_array_equal(np.abs(inp), d, err_msg=msg) + np.abs(inp, out=out) + assert_array_equal(out, d, err_msg=msg) + + assert_array_equal(-inp, -1 * inp, err_msg=msg) + d = -1 * inp + np.negative(inp, out=out) + assert_array_equal(out, d, err_msg=msg) + + def test_lower_align(self): + # check data that is not aligned to element size + # i.e doubles are aligned to 4 bytes on i386 + d = np.zeros(23 * 8, dtype=np.int8)[4:-4].view(np.float64) + assert_equal(np.abs(d), d) + assert_equal(np.negative(d), -d) + np.negative(d, out=d) + np.negative(np.ones_like(d), out=d) + np.abs(d, out=d) + np.abs(np.ones_like(d), out=d) + + @pytest.mark.parametrize("dtype", ['d', 'f', 'int32', 'int64']) + @pytest.mark.parametrize("big", [True, False]) + def test_noncontiguous(self, dtype, big): + data = np.array([-1.0, 1.0, -0.0, 0.0, 2.2251e-308, -2.5, 2.5, -6, + 6, -2.2251e-308, -8, 10], dtype=dtype) + expect = np.array([1.0, -1.0, 0.0, -0.0, -2.2251e-308, 2.5, -2.5, 6, + -6, 2.2251e-308, 8, -10], dtype=dtype) + if big: + data = np.repeat(data, 10) + expect = np.repeat(expect, 10) + out = np.ndarray(data.shape, dtype=dtype) + ncontig_in = data[1::2] + ncontig_out = out[1::2] + contig_in = np.array(ncontig_in) + # contig in, contig out + assert_array_equal(np.negative(contig_in), expect[1::2]) + # contig in, ncontig out + assert_array_equal(np.negative(contig_in, out=ncontig_out), + expect[1::2]) + # ncontig in, contig out + assert_array_equal(np.negative(ncontig_in), expect[1::2]) + # ncontig in, ncontig out + assert_array_equal(np.negative(ncontig_in, out=ncontig_out), + expect[1::2]) + # contig in, contig out, nd stride + data_split = np.array(np.array_split(data, 2)) + expect_split = np.array(np.array_split(expect, 2)) + assert_equal(np.negative(data_split), expect_split) + + +class TestPositive: + def test_valid(self): + valid_dtypes = [int, float, complex, object] + for dtype in valid_dtypes: + x = np.arange(5, dtype=dtype) + result = np.positive(x) + assert_equal(x, result, err_msg=str(dtype)) + + def test_invalid(self): + with assert_raises(TypeError): + np.positive(True) + with assert_raises(TypeError): + np.positive(np.datetime64('2000-01-01')) + with assert_raises(TypeError): + np.positive(np.array(['foo'], dtype=str)) + with assert_raises(TypeError): + np.positive(np.array(['bar'], dtype=object)) + + +class TestSpecialMethods: + def test_wrap(self): + + class with_wrap: + def __array__(self, dtype=None, copy=None): + return np.zeros(1) + + def __array_wrap__(self, arr, context, return_scalar): + r = with_wrap() + r.arr = arr + r.context = context + return r + + a = with_wrap() + x = ncu.minimum(a, a) + assert_equal(x.arr, np.zeros(1)) + func, args, i = x.context + assert_(func is ncu.minimum) + assert_equal(len(args), 2) + assert_equal(args[0], a) + assert_equal(args[1], a) + assert_equal(i, 0) + + def test_wrap_out(self): + # Calling convention for out should not affect how special methods are + # called + + class StoreArrayPrepareWrap(np.ndarray): + _wrap_args = None + _prepare_args = None + + def __new__(cls): + return np.zeros(()).view(cls) + + def __array_wrap__(self, obj, context, return_scalar): + self._wrap_args = context[1] + return obj + + @property + def args(self): + # We need to ensure these are fetched at the same time, before + # any other ufuncs are called by the assertions + return self._wrap_args + + def __repr__(self): + return "a" # for short test output + + def do_test(f_call, f_expected): + a = StoreArrayPrepareWrap() + + f_call(a) + + w = a.args + expected = f_expected(a) + try: + assert w == expected + except AssertionError as e: + # assert_equal produces truly useless error messages + raise AssertionError("\n".join([ + "Bad arguments passed in ufunc call", + f" expected: {expected}", + f" __array_wrap__ got: {w}" + ])) + + # method not on the out argument + do_test(lambda a: np.add(a, 0), lambda a: (a, 0)) + do_test(lambda a: np.add(a, 0, None), lambda a: (a, 0)) + do_test(lambda a: np.add(a, 0, out=None), lambda a: (a, 0)) + do_test(lambda a: np.add(a, 0, out=(None,)), lambda a: (a, 0)) + + # method on the out argument + do_test(lambda a: np.add(0, 0, a), lambda a: (0, 0, a)) + do_test(lambda a: np.add(0, 0, out=a), lambda a: (0, 0, a)) + do_test(lambda a: np.add(0, 0, out=(a,)), lambda a: (0, 0, a)) + + # Also check the where mask handling: + out = np.zeros([1], dtype=float) + do_test(lambda a: np.add(a, 0, where=False, out=None), lambda a: (a, 0)) + do_test(lambda a: np.add(0, 0, a, where=False), lambda a: (0, 0, a)) + + def test_wrap_with_iterable(self): + # test fix for bug #1026: + + class with_wrap(np.ndarray): + __array_priority__ = 10 + + def __new__(cls): + return np.asarray(1).view(cls).copy() + + def __array_wrap__(self, arr, context, return_scalar): + return arr.view(type(self)) + + a = with_wrap() + x = ncu.multiply(a, (1, 2, 3)) + assert_(isinstance(x, with_wrap)) + assert_array_equal(x, np.array((1, 2, 3))) + + def test_priority_with_scalar(self): + # test fix for bug #826: + + class A(np.ndarray): + __array_priority__ = 10 + + def __new__(cls): + return np.asarray(1.0, 'float64').view(cls).copy() + + a = A() + x = np.float64(1) * a + assert_(isinstance(x, A)) + assert_array_equal(x, np.array(1)) + + def test_priority(self): + + class A: + def __array__(self, dtype=None, copy=None): + return np.zeros(1) + + def __array_wrap__(self, arr, context, return_scalar): + r = type(self)() + r.arr = arr + r.context = context + return r + + class B(A): + __array_priority__ = 20. + + class C(A): + __array_priority__ = 40. + + x = np.zeros(1) + a = A() + b = B() + c = C() + f = ncu.minimum + assert_(type(f(x, x)) is np.ndarray) + assert_(type(f(x, a)) is A) + assert_(type(f(x, b)) is B) + assert_(type(f(x, c)) is C) + assert_(type(f(a, x)) is A) + assert_(type(f(b, x)) is B) + assert_(type(f(c, x)) is C) + + assert_(type(f(a, a)) is A) + assert_(type(f(a, b)) is B) + assert_(type(f(b, a)) is B) + assert_(type(f(b, b)) is B) + assert_(type(f(b, c)) is C) + assert_(type(f(c, b)) is C) + assert_(type(f(c, c)) is C) + + assert_(type(ncu.exp(a) is A)) + assert_(type(ncu.exp(b) is B)) + assert_(type(ncu.exp(c) is C)) + + def test_failing_wrap(self): + + class A: + def __array__(self, dtype=None, copy=None): + return np.zeros(2) + + def __array_wrap__(self, arr, context, return_scalar): + raise RuntimeError + + a = A() + assert_raises(RuntimeError, ncu.maximum, a, a) + assert_raises(RuntimeError, ncu.maximum.reduce, a) + + def test_failing_out_wrap(self): + + singleton = np.array([1.0]) + + class Ok(np.ndarray): + def __array_wrap__(self, obj, context, return_scalar): + return singleton + + class Bad(np.ndarray): + def __array_wrap__(self, obj, context, return_scalar): + raise RuntimeError + + ok = np.empty(1).view(Ok) + bad = np.empty(1).view(Bad) + # double-free (segfault) of "ok" if "bad" raises an exception + for i in range(10): + assert_raises(RuntimeError, ncu.frexp, 1, ok, bad) + + def test_none_wrap(self): + # Tests that issue #8507 is resolved. Previously, this would segfault + + class A: + def __array__(self, dtype=None, copy=None): + return np.zeros(1) + + def __array_wrap__(self, arr, context=None, return_scalar=False): + return None + + a = A() + assert_equal(ncu.maximum(a, a), None) + + def test_default_prepare(self): + + class with_wrap: + __array_priority__ = 10 + + def __array__(self, dtype=None, copy=None): + return np.zeros(1) + + def __array_wrap__(self, arr, context, return_scalar): + return arr + + a = with_wrap() + x = ncu.minimum(a, a) + assert_equal(x, np.zeros(1)) + assert_equal(type(x), np.ndarray) + + def test_array_too_many_args(self): + + class A: + def __array__(self, dtype, context, copy=None): + return np.zeros(1) + + a = A() + assert_raises_regex(TypeError, '2 required positional', np.sum, a) + + def test_ufunc_override(self): + # check override works even with instance with high priority. + class A: + def __array_ufunc__(self, func, method, *inputs, **kwargs): + return self, func, method, inputs, kwargs + + class MyNDArray(np.ndarray): + __array_priority__ = 100 + + a = A() + b = np.array([1]).view(MyNDArray) + res0 = np.multiply(a, b) + res1 = np.multiply(b, b, out=a) + + # self + assert_equal(res0[0], a) + assert_equal(res1[0], a) + assert_equal(res0[1], np.multiply) + assert_equal(res1[1], np.multiply) + assert_equal(res0[2], '__call__') + assert_equal(res1[2], '__call__') + assert_equal(res0[3], (a, b)) + assert_equal(res1[3], (b, b)) + assert_equal(res0[4], {}) + assert_equal(res1[4], {'out': (a,)}) + + def test_ufunc_override_mro(self): + + # Some multi arg functions for testing. + def tres_mul(a, b, c): + return a * b * c + + def quatro_mul(a, b, c, d): + return a * b * c * d + + # Make these into ufuncs. + three_mul_ufunc = np.frompyfunc(tres_mul, 3, 1) + four_mul_ufunc = np.frompyfunc(quatro_mul, 4, 1) + + class A: + def __array_ufunc__(self, func, method, *inputs, **kwargs): + return "A" + + class ASub(A): + def __array_ufunc__(self, func, method, *inputs, **kwargs): + return "ASub" + + class B: + def __array_ufunc__(self, func, method, *inputs, **kwargs): + return "B" + + class C: + def __init__(self): + self.count = 0 + + def __array_ufunc__(self, func, method, *inputs, **kwargs): + self.count += 1 + return NotImplemented + + class CSub(C): + def __array_ufunc__(self, func, method, *inputs, **kwargs): + self.count += 1 + return NotImplemented + + a = A() + a_sub = ASub() + b = B() + c = C() + + # Standard + res = np.multiply(a, a_sub) + assert_equal(res, "ASub") + res = np.multiply(a_sub, b) + assert_equal(res, "ASub") + + # With 1 NotImplemented + res = np.multiply(c, a) + assert_equal(res, "A") + assert_equal(c.count, 1) + # Check our counter works, so we can trust tests below. + res = np.multiply(c, a) + assert_equal(c.count, 2) + + # Both NotImplemented. + c = C() + c_sub = CSub() + assert_raises(TypeError, np.multiply, c, c_sub) + assert_equal(c.count, 1) + assert_equal(c_sub.count, 1) + c.count = c_sub.count = 0 + assert_raises(TypeError, np.multiply, c_sub, c) + assert_equal(c.count, 1) + assert_equal(c_sub.count, 1) + c.count = 0 + assert_raises(TypeError, np.multiply, c, c) + assert_equal(c.count, 1) + c.count = 0 + assert_raises(TypeError, np.multiply, 2, c) + assert_equal(c.count, 1) + + # Ternary testing. + assert_equal(three_mul_ufunc(a, 1, 2), "A") + assert_equal(three_mul_ufunc(1, a, 2), "A") + assert_equal(three_mul_ufunc(1, 2, a), "A") + + assert_equal(three_mul_ufunc(a, a, 6), "A") + assert_equal(three_mul_ufunc(a, 2, a), "A") + assert_equal(three_mul_ufunc(a, 2, b), "A") + assert_equal(three_mul_ufunc(a, 2, a_sub), "ASub") + assert_equal(three_mul_ufunc(a, a_sub, 3), "ASub") + c.count = 0 + assert_equal(three_mul_ufunc(c, a_sub, 3), "ASub") + assert_equal(c.count, 1) + c.count = 0 + assert_equal(three_mul_ufunc(1, a_sub, c), "ASub") + assert_equal(c.count, 0) + + c.count = 0 + assert_equal(three_mul_ufunc(a, b, c), "A") + assert_equal(c.count, 0) + c_sub.count = 0 + assert_equal(three_mul_ufunc(a, b, c_sub), "A") + assert_equal(c_sub.count, 0) + assert_equal(three_mul_ufunc(1, 2, b), "B") + + assert_raises(TypeError, three_mul_ufunc, 1, 2, c) + assert_raises(TypeError, three_mul_ufunc, c_sub, 2, c) + assert_raises(TypeError, three_mul_ufunc, c_sub, 2, 3) + + # Quaternary testing. + assert_equal(four_mul_ufunc(a, 1, 2, 3), "A") + assert_equal(four_mul_ufunc(1, a, 2, 3), "A") + assert_equal(four_mul_ufunc(1, 1, a, 3), "A") + assert_equal(four_mul_ufunc(1, 1, 2, a), "A") + + assert_equal(four_mul_ufunc(a, b, 2, 3), "A") + assert_equal(four_mul_ufunc(1, a, 2, b), "A") + assert_equal(four_mul_ufunc(b, 1, a, 3), "B") + assert_equal(four_mul_ufunc(a_sub, 1, 2, a), "ASub") + assert_equal(four_mul_ufunc(a, 1, 2, a_sub), "ASub") + + c = C() + c_sub = CSub() + assert_raises(TypeError, four_mul_ufunc, 1, 2, 3, c) + assert_equal(c.count, 1) + c.count = 0 + assert_raises(TypeError, four_mul_ufunc, 1, 2, c_sub, c) + assert_equal(c_sub.count, 1) + assert_equal(c.count, 1) + c2 = C() + c.count = c_sub.count = 0 + assert_raises(TypeError, four_mul_ufunc, 1, c, c_sub, c2) + assert_equal(c_sub.count, 1) + assert_equal(c.count, 1) + assert_equal(c2.count, 0) + c.count = c2.count = c_sub.count = 0 + assert_raises(TypeError, four_mul_ufunc, c2, c, c_sub, c) + assert_equal(c_sub.count, 1) + assert_equal(c.count, 0) + assert_equal(c2.count, 1) + + def test_ufunc_override_methods(self): + + class A: + def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): + return self, ufunc, method, inputs, kwargs + + # __call__ + a = A() + with assert_raises(TypeError): + np.multiply.__call__(1, a, foo='bar', answer=42) + res = np.multiply.__call__(1, a, subok='bar', where=42) + assert_equal(res[0], a) + assert_equal(res[1], np.multiply) + assert_equal(res[2], '__call__') + assert_equal(res[3], (1, a)) + assert_equal(res[4], {'subok': 'bar', 'where': 42}) + + # __call__, wrong args + assert_raises(TypeError, np.multiply, a) + assert_raises(TypeError, np.multiply, a, a, a, a) + assert_raises(TypeError, np.multiply, a, a, sig='a', signature='a') + assert_raises(TypeError, ncu_tests.inner1d, a, a, axis=0, axes=[0, 0]) + + # reduce, positional args + res = np.multiply.reduce(a, 'axis0', 'dtype0', 'out0', 'keep0') + assert_equal(res[0], a) + assert_equal(res[1], np.multiply) + assert_equal(res[2], 'reduce') + assert_equal(res[3], (a,)) + assert_equal(res[4], {'dtype': 'dtype0', + 'out': ('out0',), + 'keepdims': 'keep0', + 'axis': 'axis0'}) + + # reduce, kwargs + res = np.multiply.reduce(a, axis='axis0', dtype='dtype0', out='out0', + keepdims='keep0', initial='init0', + where='where0') + assert_equal(res[0], a) + assert_equal(res[1], np.multiply) + assert_equal(res[2], 'reduce') + assert_equal(res[3], (a,)) + assert_equal(res[4], {'dtype': 'dtype0', + 'out': ('out0',), + 'keepdims': 'keep0', + 'axis': 'axis0', + 'initial': 'init0', + 'where': 'where0'}) + # reduce, kwargs, out=None is removed + res = np.multiply.reduce(a, axis='axis0', dtype='dtype0', out=None, + keepdims='keep0', initial='init0', + where='where0') + assert_equal(res[0], a) + assert_equal(res[1], np.multiply) + assert_equal(res[2], 'reduce') + assert_equal(res[3], (a,)) + assert_equal(res[4], {'dtype': 'dtype0', + 'keepdims': 'keep0', + 'axis': 'axis0', + 'initial': 'init0', + 'where': 'where0'}) + + # reduce, output equal to None removed, but not other explicit ones, + # even if they are at their default value. + res = np.multiply.reduce(a, 0, None, None, False) + assert_equal(res[4], {'axis': 0, 'dtype': None, 'keepdims': False}) + res = np.multiply.reduce(a, out=None, axis=0, keepdims=True) + assert_equal(res[4], {'axis': 0, 'keepdims': True}) + res = np.multiply.reduce(a, None, out=(None,), dtype=None) + assert_equal(res[4], {'axis': None, 'dtype': None}) + res = np.multiply.reduce(a, 0, None, None, False, 2, True) + assert_equal(res[4], {'axis': 0, 'dtype': None, 'keepdims': False, + 'initial': 2, 'where': True}) + # np._NoValue ignored for initial + res = np.multiply.reduce(a, 0, None, None, False, + np._NoValue, True) + assert_equal(res[4], {'axis': 0, 'dtype': None, 'keepdims': False, + 'where': True}) + # None kept for initial, True for where. + res = np.multiply.reduce(a, 0, None, None, False, None, True) + assert_equal(res[4], {'axis': 0, 'dtype': None, 'keepdims': False, + 'initial': None, 'where': True}) + + # reduce, wrong args + assert_raises(ValueError, np.multiply.reduce, a, out=()) + assert_raises(ValueError, np.multiply.reduce, a, out=('out0', 'out1')) + assert_raises(TypeError, np.multiply.reduce, a, 'axis0', axis='axis0') + + # accumulate, pos args + res = np.multiply.accumulate(a, 'axis0', 'dtype0', 'out0') + assert_equal(res[0], a) + assert_equal(res[1], np.multiply) + assert_equal(res[2], 'accumulate') + assert_equal(res[3], (a,)) + assert_equal(res[4], {'dtype': 'dtype0', + 'out': ('out0',), + 'axis': 'axis0'}) + + # accumulate, kwargs + res = np.multiply.accumulate(a, axis='axis0', dtype='dtype0', + out='out0') + assert_equal(res[0], a) + assert_equal(res[1], np.multiply) + assert_equal(res[2], 'accumulate') + assert_equal(res[3], (a,)) + assert_equal(res[4], {'dtype': 'dtype0', + 'out': ('out0',), + 'axis': 'axis0'}) + + # accumulate, output equal to None removed. + res = np.multiply.accumulate(a, 0, None, None) + assert_equal(res[4], {'axis': 0, 'dtype': None}) + res = np.multiply.accumulate(a, out=None, axis=0, dtype='dtype1') + assert_equal(res[4], {'axis': 0, 'dtype': 'dtype1'}) + res = np.multiply.accumulate(a, None, out=(None,), dtype=None) + assert_equal(res[4], {'axis': None, 'dtype': None}) + + # accumulate, wrong args + assert_raises(ValueError, np.multiply.accumulate, a, out=()) + assert_raises(ValueError, np.multiply.accumulate, a, + out=('out0', 'out1')) + assert_raises(TypeError, np.multiply.accumulate, a, + 'axis0', axis='axis0') + + # reduceat, pos args + res = np.multiply.reduceat(a, [4, 2], 'axis0', 'dtype0', 'out0') + assert_equal(res[0], a) + assert_equal(res[1], np.multiply) + assert_equal(res[2], 'reduceat') + assert_equal(res[3], (a, [4, 2])) + assert_equal(res[4], {'dtype': 'dtype0', + 'out': ('out0',), + 'axis': 'axis0'}) + + # reduceat, kwargs + res = np.multiply.reduceat(a, [4, 2], axis='axis0', dtype='dtype0', + out='out0') + assert_equal(res[0], a) + assert_equal(res[1], np.multiply) + assert_equal(res[2], 'reduceat') + assert_equal(res[3], (a, [4, 2])) + assert_equal(res[4], {'dtype': 'dtype0', + 'out': ('out0',), + 'axis': 'axis0'}) + + # reduceat, output equal to None removed. + res = np.multiply.reduceat(a, [4, 2], 0, None, None) + assert_equal(res[4], {'axis': 0, 'dtype': None}) + res = np.multiply.reduceat(a, [4, 2], axis=None, out=None, dtype='dt') + assert_equal(res[4], {'axis': None, 'dtype': 'dt'}) + res = np.multiply.reduceat(a, [4, 2], None, None, out=(None,)) + assert_equal(res[4], {'axis': None, 'dtype': None}) + + # reduceat, wrong args + assert_raises(ValueError, np.multiply.reduce, a, [4, 2], out=()) + assert_raises(ValueError, np.multiply.reduce, a, [4, 2], + out=('out0', 'out1')) + assert_raises(TypeError, np.multiply.reduce, a, [4, 2], + 'axis0', axis='axis0') + + # outer + res = np.multiply.outer(a, 42) + assert_equal(res[0], a) + assert_equal(res[1], np.multiply) + assert_equal(res[2], 'outer') + assert_equal(res[3], (a, 42)) + assert_equal(res[4], {}) + + # outer, wrong args + assert_raises(TypeError, np.multiply.outer, a) + assert_raises(TypeError, np.multiply.outer, a, a, a, a) + assert_raises(TypeError, np.multiply.outer, a, a, sig='a', signature='a') + + # at + res = np.multiply.at(a, [4, 2], 'b0') + assert_equal(res[0], a) + assert_equal(res[1], np.multiply) + assert_equal(res[2], 'at') + assert_equal(res[3], (a, [4, 2], 'b0')) + + # at, wrong args + assert_raises(TypeError, np.multiply.at, a) + assert_raises(TypeError, np.multiply.at, a, a, a, a) + + def test_ufunc_override_out(self): + + class A: + def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): + return kwargs + + class B: + def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): + return kwargs + + a = A() + b = B() + res0 = np.multiply(a, b, 'out_arg') + res1 = np.multiply(a, b, out='out_arg') + res2 = np.multiply(2, b, 'out_arg') + res3 = np.multiply(3, b, out='out_arg') + res4 = np.multiply(a, 4, 'out_arg') + res5 = np.multiply(a, 5, out='out_arg') + + assert_equal(res0['out'][0], 'out_arg') + assert_equal(res1['out'][0], 'out_arg') + assert_equal(res2['out'][0], 'out_arg') + assert_equal(res3['out'][0], 'out_arg') + assert_equal(res4['out'][0], 'out_arg') + assert_equal(res5['out'][0], 'out_arg') + + # ufuncs with multiple output modf and frexp. + res6 = np.modf(a, 'out0', 'out1') + res7 = np.frexp(a, 'out0', 'out1') + assert_equal(res6['out'][0], 'out0') + assert_equal(res6['out'][1], 'out1') + assert_equal(res7['out'][0], 'out0') + assert_equal(res7['out'][1], 'out1') + + # While we're at it, check that default output is never passed on. + assert_(np.sin(a, None) == {}) + assert_(np.sin(a, out=None) == {}) + assert_(np.sin(a, out=(None,)) == {}) + assert_(np.modf(a, None) == {}) + assert_(np.modf(a, None, None) == {}) + assert_(np.modf(a, out=(None, None)) == {}) + with assert_raises(TypeError): + # Out argument must be tuple, since there are multiple outputs. + np.modf(a, out=None) + + # don't give positional and output argument, or too many arguments. + # wrong number of arguments in the tuple is an error too. + assert_raises(TypeError, np.multiply, a, b, 'one', out='two') + assert_raises(TypeError, np.multiply, a, b, 'one', 'two') + assert_raises(ValueError, np.multiply, a, b, out=('one', 'two')) + assert_raises(TypeError, np.multiply, a, out=()) + assert_raises(TypeError, np.modf, a, 'one', out=('two', 'three')) + assert_raises(TypeError, np.modf, a, 'one', 'two', 'three') + assert_raises(ValueError, np.modf, a, out=('one', 'two', 'three')) + assert_raises(ValueError, np.modf, a, out=('one',)) + + def test_ufunc_override_where(self): + + class OverriddenArrayOld(np.ndarray): + + def _unwrap(self, objs): + cls = type(self) + result = [] + for obj in objs: + if isinstance(obj, cls): + obj = np.array(obj) + elif type(obj) != np.ndarray: + return NotImplemented + result.append(obj) + return result + + def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): + + inputs = self._unwrap(inputs) + if inputs is NotImplemented: + return NotImplemented + + kwargs = kwargs.copy() + if "out" in kwargs: + kwargs["out"] = self._unwrap(kwargs["out"])[0] + if kwargs["out"] is NotImplemented: + return NotImplemented + + r = super().__array_ufunc__(ufunc, method, *inputs, **kwargs) + if r is not NotImplemented: + r = r.view(type(self)) + + return r + + class OverriddenArrayNew(OverriddenArrayOld): + def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): + + kwargs = kwargs.copy() + if "where" in kwargs: + kwargs["where"] = self._unwrap((kwargs["where"], )) + if kwargs["where"] is NotImplemented: + return NotImplemented + else: + kwargs["where"] = kwargs["where"][0] + + r = super().__array_ufunc__(ufunc, method, *inputs, **kwargs) + if r is not NotImplemented: + r = r.view(type(self)) + + return r + + ufunc = np.negative + + array = np.array([1, 2, 3]) + where = np.array([True, False, True]) + out = np.zeros(3, dtype=array.dtype) + expected = ufunc(array, where=where, out=out) + + with pytest.raises(TypeError): + ufunc( + array, + where=where.view(OverriddenArrayOld), + out=out, + ) + + result_1 = ufunc( + array, + where=where.view(OverriddenArrayNew), + out=out, + ) + assert isinstance(result_1, OverriddenArrayNew) + assert np.all(np.array(result_1) == expected, where=where) + + result_2 = ufunc( + array.view(OverriddenArrayNew), + where=where.view(OverriddenArrayNew), + out=out.view(OverriddenArrayNew), + ) + assert isinstance(result_2, OverriddenArrayNew) + assert np.all(np.array(result_2) == expected, where=where) + + def test_ufunc_override_exception(self): + + class A: + def __array_ufunc__(self, *a, **kwargs): + raise ValueError("oops") + + a = A() + assert_raises(ValueError, np.negative, 1, out=a) + assert_raises(ValueError, np.negative, a) + assert_raises(ValueError, np.divide, 1., a) + + def test_ufunc_override_not_implemented(self): + + class A: + def __array_ufunc__(self, *args, **kwargs): + return NotImplemented + + msg = ("operand type(s) all returned NotImplemented from " + "__array_ufunc__(, '__call__', <*>): 'A'") + with assert_raises_regex(TypeError, fnmatch.translate(msg)): + np.negative(A()) + + msg = ("operand type(s) all returned NotImplemented from " + "__array_ufunc__(, '__call__', <*>, , " + "out=(1,)): 'A', 'object', 'int'") + with assert_raises_regex(TypeError, fnmatch.translate(msg)): + np.add(A(), object(), out=1) + + def test_ufunc_override_disabled(self): + + class OptOut: + __array_ufunc__ = None + + opt_out = OptOut() + + # ufuncs always raise + msg = "operand 'OptOut' does not support ufuncs" + with assert_raises_regex(TypeError, msg): + np.add(opt_out, 1) + with assert_raises_regex(TypeError, msg): + np.add(1, opt_out) + with assert_raises_regex(TypeError, msg): + np.negative(opt_out) + + # opt-outs still hold even when other arguments have pathological + # __array_ufunc__ implementations + + class GreedyArray: + def __array_ufunc__(self, *args, **kwargs): + return self + + greedy = GreedyArray() + assert_(np.negative(greedy) is greedy) + with assert_raises_regex(TypeError, msg): + np.add(greedy, opt_out) + with assert_raises_regex(TypeError, msg): + np.add(greedy, 1, out=opt_out) + + def test_gufunc_override(self): + # gufunc are just ufunc instances, but follow a different path, + # so check __array_ufunc__ overrides them properly. + class A: + def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): + return self, ufunc, method, inputs, kwargs + + inner1d = ncu_tests.inner1d + a = A() + res = inner1d(a, a) + assert_equal(res[0], a) + assert_equal(res[1], inner1d) + assert_equal(res[2], '__call__') + assert_equal(res[3], (a, a)) + assert_equal(res[4], {}) + + res = inner1d(1, 1, out=a) + assert_equal(res[0], a) + assert_equal(res[1], inner1d) + assert_equal(res[2], '__call__') + assert_equal(res[3], (1, 1)) + assert_equal(res[4], {'out': (a,)}) + + # wrong number of arguments in the tuple is an error too. + assert_raises(TypeError, inner1d, a, out='two') + assert_raises(TypeError, inner1d, a, a, 'one', out='two') + assert_raises(TypeError, inner1d, a, a, 'one', 'two') + assert_raises(ValueError, inner1d, a, a, out=('one', 'two')) + assert_raises(ValueError, inner1d, a, a, out=()) + + def test_ufunc_override_with_super(self): + # NOTE: this class is used in doc/source/user/basics.subclassing.rst + # if you make any changes here, do update it there too. + class A(np.ndarray): + def __array_ufunc__(self, ufunc, method, *inputs, out=None, **kwargs): + args = [] + in_no = [] + for i, input_ in enumerate(inputs): + if isinstance(input_, A): + in_no.append(i) + args.append(input_.view(np.ndarray)) + else: + args.append(input_) + + outputs = out + out_no = [] + if outputs: + out_args = [] + for j, output in enumerate(outputs): + if isinstance(output, A): + out_no.append(j) + out_args.append(output.view(np.ndarray)) + else: + out_args.append(output) + kwargs['out'] = tuple(out_args) + else: + outputs = (None,) * ufunc.nout + + info = {} + if in_no: + info['inputs'] = in_no + if out_no: + info['outputs'] = out_no + + results = super().__array_ufunc__(ufunc, method, + *args, **kwargs) + if results is NotImplemented: + return NotImplemented + + if method == 'at': + if isinstance(inputs[0], A): + inputs[0].info = info + return + + if ufunc.nout == 1: + results = (results,) + + results = tuple((np.asarray(result).view(A) + if output is None else output) + for result, output in zip(results, outputs)) + if results and isinstance(results[0], A): + results[0].info = info + + return results[0] if len(results) == 1 else results + + class B: + def __array_ufunc__(self, ufunc, method, *inputs, **kwargs): + if any(isinstance(input_, A) for input_ in inputs): + return "A!" + else: + return NotImplemented + + d = np.arange(5.) + # 1 input, 1 output + a = np.arange(5.).view(A) + b = np.sin(a) + check = np.sin(d) + assert_(np.all(check == b)) + assert_equal(b.info, {'inputs': [0]}) + b = np.sin(d, out=(a,)) + assert_(np.all(check == b)) + assert_equal(b.info, {'outputs': [0]}) + assert_(b is a) + a = np.arange(5.).view(A) + b = np.sin(a, out=a) + assert_(np.all(check == b)) + assert_equal(b.info, {'inputs': [0], 'outputs': [0]}) + + # 1 input, 2 outputs + a = np.arange(5.).view(A) + b1, b2 = np.modf(a) + assert_equal(b1.info, {'inputs': [0]}) + b1, b2 = np.modf(d, out=(None, a)) + assert_(b2 is a) + assert_equal(b1.info, {'outputs': [1]}) + a = np.arange(5.).view(A) + b = np.arange(5.).view(A) + c1, c2 = np.modf(a, out=(a, b)) + assert_(c1 is a) + assert_(c2 is b) + assert_equal(c1.info, {'inputs': [0], 'outputs': [0, 1]}) + + # 2 input, 1 output + a = np.arange(5.).view(A) + b = np.arange(5.).view(A) + c = np.add(a, b, out=a) + assert_(c is a) + assert_equal(c.info, {'inputs': [0, 1], 'outputs': [0]}) + # some tests with a non-ndarray subclass + a = np.arange(5.) + b = B() + assert_(a.__array_ufunc__(np.add, '__call__', a, b) is NotImplemented) + assert_(b.__array_ufunc__(np.add, '__call__', a, b) is NotImplemented) + assert_raises(TypeError, np.add, a, b) + a = a.view(A) + assert_(a.__array_ufunc__(np.add, '__call__', a, b) is NotImplemented) + assert_(b.__array_ufunc__(np.add, '__call__', a, b) == "A!") + assert_(np.add(a, b) == "A!") + # regression check for gh-9102 -- tests ufunc.reduce implicitly. + d = np.array([[1, 2, 3], [1, 2, 3]]) + a = d.view(A) + c = a.any() + check = d.any() + assert_equal(c, check) + assert_(c.info, {'inputs': [0]}) + c = a.max() + check = d.max() + assert_equal(c, check) + assert_(c.info, {'inputs': [0]}) + b = np.array(0).view(A) + c = a.max(out=b) + assert_equal(c, check) + assert_(c is b) + assert_(c.info, {'inputs': [0], 'outputs': [0]}) + check = a.max(axis=0) + b = np.zeros_like(check).view(A) + c = a.max(axis=0, out=b) + assert_equal(c, check) + assert_(c is b) + assert_(c.info, {'inputs': [0], 'outputs': [0]}) + # simple explicit tests of reduce, accumulate, reduceat + check = np.add.reduce(d, axis=1) + c = np.add.reduce(a, axis=1) + assert_equal(c, check) + assert_(c.info, {'inputs': [0]}) + b = np.zeros_like(c) + c = np.add.reduce(a, 1, None, b) + assert_equal(c, check) + assert_(c is b) + assert_(c.info, {'inputs': [0], 'outputs': [0]}) + check = np.add.accumulate(d, axis=0) + c = np.add.accumulate(a, axis=0) + assert_equal(c, check) + assert_(c.info, {'inputs': [0]}) + b = np.zeros_like(c) + c = np.add.accumulate(a, 0, None, b) + assert_equal(c, check) + assert_(c is b) + assert_(c.info, {'inputs': [0], 'outputs': [0]}) + indices = [0, 2, 1] + check = np.add.reduceat(d, indices, axis=1) + c = np.add.reduceat(a, indices, axis=1) + assert_equal(c, check) + assert_(c.info, {'inputs': [0]}) + b = np.zeros_like(c) + c = np.add.reduceat(a, indices, 1, None, b) + assert_equal(c, check) + assert_(c is b) + assert_(c.info, {'inputs': [0], 'outputs': [0]}) + # and a few tests for at + d = np.array([[1, 2, 3], [1, 2, 3]]) + check = d.copy() + a = d.copy().view(A) + np.add.at(check, ([0, 1], [0, 2]), 1.) + np.add.at(a, ([0, 1], [0, 2]), 1.) + assert_equal(a, check) + assert_(a.info, {'inputs': [0]}) + b = np.array(1.).view(A) + a = d.copy().view(A) + np.add.at(a, ([0, 1], [0, 2]), b) + assert_equal(a, check) + assert_(a.info, {'inputs': [0, 2]}) + + def test_array_ufunc_direct_call(self): + # This is mainly a regression test for gh-24023 (shouldn't segfault) + a = np.array(1) + with pytest.raises(TypeError): + a.__array_ufunc__() + + # No kwargs means kwargs may be NULL on the C-level + with pytest.raises(TypeError): + a.__array_ufunc__(1, 2) + + # And the same with a valid call: + res = a.__array_ufunc__(np.add, "__call__", a, a) + assert_array_equal(res, a + a) + + @pytest.mark.thread_unsafe(reason="modifies global module") + @pytest.mark.skipif(IS_PYPY, reason="__signature__ descriptor dance fails") + def test_ufunc_docstring(self): + original_doc = np.add.__doc__ + new_doc = "new docs" + expected_dict = ( + {} if IS_PYPY else {"__module__": "numpy", "__qualname__": "add"} + ) + expected_dict["__signature__"] = inspect.signature(np.add) + + np.add.__doc__ = new_doc + assert np.add.__doc__ == new_doc + assert np.add.__dict__["__doc__"] == new_doc + + del np.add.__doc__ + assert np.add.__doc__ == original_doc + assert np.add.__dict__ == expected_dict + + np.add.__dict__["other"] = 1 + np.add.__dict__["__doc__"] = new_doc + assert np.add.__doc__ == new_doc + + del np.add.__dict__["__doc__"] + assert np.add.__doc__ == original_doc + del np.add.__dict__["other"] + assert np.add.__dict__ == expected_dict + + +class TestChoose: + def test_mixed(self): + c = np.array([True, True]) + a = np.array([True, True]) + assert_equal(np.choose(c, (a, 1)), np.array([1, 1])) + + +class TestRationalFunctions: + def test_lcm(self): + self._test_lcm_inner(np.int16) + self._test_lcm_inner(np.uint16) + + def test_lcm_object(self): + self._test_lcm_inner(np.object_) + + def test_gcd(self): + self._test_gcd_inner(np.int16) + self._test_lcm_inner(np.uint16) + + def test_gcd_object(self): + self._test_gcd_inner(np.object_) + + def _test_lcm_inner(self, dtype): + # basic use + a = np.array([12, 120], dtype=dtype) + b = np.array([20, 200], dtype=dtype) + assert_equal(np.lcm(a, b), [60, 600]) + + if not issubclass(dtype, np.unsignedinteger): + # negatives are ignored + a = np.array([12, -12, 12, -12], dtype=dtype) + b = np.array([20, 20, -20, -20], dtype=dtype) + assert_equal(np.lcm(a, b), [60] * 4) + + # reduce + a = np.array([3, 12, 20], dtype=dtype) + assert_equal(np.lcm.reduce([3, 12, 20]), 60) + + # broadcasting, and a test including 0 + a = np.arange(6).astype(dtype) + b = 20 + assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20]) + + def _test_gcd_inner(self, dtype): + # basic use + a = np.array([12, 120], dtype=dtype) + b = np.array([20, 200], dtype=dtype) + assert_equal(np.gcd(a, b), [4, 40]) + + if not issubclass(dtype, np.unsignedinteger): + # negatives are ignored + a = np.array([12, -12, 12, -12], dtype=dtype) + b = np.array([20, 20, -20, -20], dtype=dtype) + assert_equal(np.gcd(a, b), [4] * 4) + + # reduce + a = np.array([15, 25, 35], dtype=dtype) + assert_equal(np.gcd.reduce(a), 5) + + # broadcasting, and a test including 0 + a = np.arange(6).astype(dtype) + b = 20 + assert_equal(np.gcd(a, b), [20, 1, 2, 1, 4, 5]) + + def test_lcm_overflow(self): + # verify that we don't overflow when a*b does overflow + big = np.int32(np.iinfo(np.int32).max // 11) + a = 2 * big + b = 5 * big + assert_equal(np.lcm(a, b), 10 * big) + + def test_gcd_overflow(self): + for dtype in (np.int32, np.int64): + # verify that we don't overflow when taking abs(x) + # not relevant for lcm, where the result is unrepresentable anyway + a = dtype(np.iinfo(dtype).min) # negative power of two + q = -(a // 4) + assert_equal(np.gcd(a, q * 3), q) + assert_equal(np.gcd(a, -q * 3), q) + + def test_decimal(self): + from decimal import Decimal + a = np.array([1, 1, -1, -1]) * Decimal('0.20') + b = np.array([1, -1, 1, -1]) * Decimal('0.12') + + assert_equal(np.gcd(a, b), 4 * [Decimal('0.04')]) + assert_equal(np.lcm(a, b), 4 * [Decimal('0.60')]) + + def test_float(self): + # not well-defined on float due to rounding errors + assert_raises(TypeError, np.gcd, 0.3, 0.4) + assert_raises(TypeError, np.lcm, 0.3, 0.4) + + def test_huge_integers(self): + # Converting to an array first is a bit different as it means we + # have an explicit object dtype: + assert_equal(np.array(2**200), 2**200) + # Special promotion rules should ensure that this also works for + # two Python integers (even if slow). + # (We do this for comparisons, as the result is always bool and + # we also special case array comparisons with Python integers) + np.equal(2**200, 2**200) + + # But, we cannot do this when it would affect the result dtype: + with pytest.raises(OverflowError): + np.gcd(2**100, 3**100) + + # Asking for `object` explicitly is fine, though: + assert np.gcd(2**100, 3**100, dtype=object) == 1 + + # As of now, the below work, because it is using arrays (which + # will be object arrays) + a = np.array(2**100 * 3**5) + b = np.array([2**100 * 5**7, 2**50 * 3**10]) + assert_equal(np.gcd(a, b), [2**100, 2**50 * 3**5]) + assert_equal(np.lcm(a, b), [2**100 * 3**5 * 5**7, 2**100 * 3**10]) + + def test_inf_and_nan(self): + inf = np.array([np.inf], dtype=np.object_) + assert_raises(ValueError, np.gcd, inf, 1) + assert_raises(ValueError, np.gcd, 1, inf) + assert_raises(ValueError, np.gcd, np.nan, inf) + assert_raises(TypeError, np.gcd, 4, float(np.inf)) + + +class TestRoundingFunctions: + + def test_object_direct(self): + """ test direct implementation of these magic methods """ + class C: + def __floor__(self): + return 1 + + def __ceil__(self): + return 2 + + def __trunc__(self): + return 3 + + arr = np.array([C(), C()]) + assert_equal(np.floor(arr), [1, 1]) + assert_equal(np.ceil(arr), [2, 2]) + assert_equal(np.trunc(arr), [3, 3]) + + def test_object_indirect(self): + """ test implementations via __float__ """ + class C: + def __float__(self): + return -2.5 + + arr = np.array([C(), C()]) + assert_equal(np.floor(arr), [-3, -3]) + assert_equal(np.ceil(arr), [-2, -2]) + with pytest.raises(TypeError): + np.trunc(arr) # consistent with math.trunc + + def test_fraction(self): + f = Fraction(-4, 3) + assert_equal(np.floor(f), -2) + assert_equal(np.ceil(f), -1) + assert_equal(np.trunc(f), -1) + + @pytest.mark.parametrize('func', [np.floor, np.ceil, np.trunc]) + @pytest.mark.parametrize('dtype', [np.bool, np.float64, np.float32, + np.int64, np.uint32]) + def test_output_dtype(self, func, dtype): + arr = np.array([-2, 0, 4, 8]).astype(dtype) + result = func(arr) + assert_equal(arr, result) + assert result.dtype == dtype + + +class TestComplexFunctions: + funcs = [np.arcsin, np.arccos, np.arctan, np.arcsinh, np.arccosh, + np.arctanh, np.sin, np.cos, np.tan, np.exp, + np.exp2, np.log, np.sqrt, np.log10, np.log2, + np.log1p] + + def test_it(self): + for f in self.funcs: + if f is np.arccosh: + x = 1.5 + else: + x = .5 + fr = f(x) + fz = f(complex(x)) + assert_almost_equal(fz.real, fr, err_msg=f'real part {f}') + assert_almost_equal(fz.imag, 0., err_msg=f'imag part {f}') + + @pytest.mark.xfail(IS_WASM, reason="doesn't work") + def test_precisions_consistent(self): + z = 1 + 1j + for f in self.funcs: + fcf = f(np.csingle(z)) + fcd = f(np.cdouble(z)) + fcl = f(np.clongdouble(z)) + assert_almost_equal(fcf, fcd, decimal=6, err_msg=f'fch-fcd {f}') + assert_almost_equal(fcl, fcd, decimal=15, err_msg=f'fch-fcl {f}') + + @pytest.mark.xfail(IS_WASM, reason="doesn't work") + def test_branch_cuts(self): + # check branch cuts and continuity on them + _check_branch_cut(np.log, -0.5, 1j, 1, -1, True) # noqa: E221 + _check_branch_cut(np.log2, -0.5, 1j, 1, -1, True) # noqa: E221 + _check_branch_cut(np.log10, -0.5, 1j, 1, -1, True) + _check_branch_cut(np.log1p, -1.5, 1j, 1, -1, True) + _check_branch_cut(np.sqrt, -0.5, 1j, 1, -1, True) # noqa: E221 + + _check_branch_cut(np.arcsin, [ -2, 2], [1j, 1j], 1, -1, True) + _check_branch_cut(np.arccos, [ -2, 2], [1j, 1j], 1, -1, True) + _check_branch_cut(np.arctan, [0 - 2j, 2j], [1, 1], -1, 1, True) + + _check_branch_cut(np.arcsinh, [0 - 2j, 2j], [1, 1], -1, 1, True) + _check_branch_cut(np.arccosh, [ -1, 0.5], [1j, 1j], 1, -1, True) + _check_branch_cut(np.arctanh, [ -2, 2], [1j, 1j], 1, -1, True) + + # check against bogus branch cuts: assert continuity between quadrants + _check_branch_cut(np.arcsin, [0 - 2j, 2j], [ 1, 1], 1, 1) + _check_branch_cut(np.arccos, [0 - 2j, 2j], [ 1, 1], 1, 1) + _check_branch_cut(np.arctan, [ -2, 2], [1j, 1j], 1, 1) + + _check_branch_cut(np.arcsinh, [ -2, 2, 0], [1j, 1j, 1], 1, 1) + _check_branch_cut(np.arccosh, [0 - 2j, 2j, 2], [1, 1, 1j], 1, 1) + _check_branch_cut(np.arctanh, [0 - 2j, 2j, 0], [1, 1, 1j], 1, 1) + + @pytest.mark.xfail(IS_WASM, reason="doesn't work") + def test_branch_cuts_complex64(self): + # check branch cuts and continuity on them + _check_branch_cut(np.log, -0.5, 1j, 1, -1, True, np.complex64) # noqa: E221 + _check_branch_cut(np.log2, -0.5, 1j, 1, -1, True, np.complex64) # noqa: E221 + _check_branch_cut(np.log10, -0.5, 1j, 1, -1, True, np.complex64) + _check_branch_cut(np.log1p, -1.5, 1j, 1, -1, True, np.complex64) + _check_branch_cut(np.sqrt, -0.5, 1j, 1, -1, True, np.complex64) # noqa: E221 + + _check_branch_cut(np.arcsin, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64) + _check_branch_cut(np.arccos, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64) + _check_branch_cut(np.arctan, [0 - 2j, 2j], [1, 1], -1, 1, True, np.complex64) + + _check_branch_cut(np.arcsinh, [0 - 2j, 2j], [1, 1], -1, 1, True, np.complex64) + _check_branch_cut(np.arccosh, [ -1, 0.5], [1j, 1j], 1, -1, True, np.complex64) + _check_branch_cut(np.arctanh, [ -2, 2], [1j, 1j], 1, -1, True, np.complex64) + + # check against bogus branch cuts: assert continuity between quadrants + _check_branch_cut(np.arcsin, [0 - 2j, 2j], [ 1, 1], 1, 1, False, np.complex64) + _check_branch_cut(np.arccos, [0 - 2j, 2j], [ 1, 1], 1, 1, False, np.complex64) + _check_branch_cut(np.arctan, [ -2, 2], [1j, 1j], 1, 1, False, np.complex64) + + _check_branch_cut(np.arcsinh, [ -2, 2, 0], [1j, 1j, 1], 1, 1, False, np.complex64) + _check_branch_cut(np.arccosh, [0 - 2j, 2j, 2], [1, 1, 1j], 1, 1, False, np.complex64) + _check_branch_cut(np.arctanh, [0 - 2j, 2j, 0], [1, 1, 1j], 1, 1, False, np.complex64) + + def test_against_cmath(self): + import cmath + + points = [-1 - 1j, -1 + 1j, +1 - 1j, +1 + 1j] + name_map = {'arcsin': 'asin', 'arccos': 'acos', 'arctan': 'atan', + 'arcsinh': 'asinh', 'arccosh': 'acosh', 'arctanh': 'atanh'} + atol = 4 * np.finfo(complex).eps + for func in self.funcs: + fname = func.__name__.split('.')[-1] + cname = name_map.get(fname, fname) + try: + cfunc = getattr(cmath, cname) + except AttributeError: + continue + for p in points: + a = complex(func(np.complex128(p))) + b = cfunc(p) + assert_( + abs(a - b) < atol, + f"{fname} {p}: {a}; cmath: {b}" + ) + + @pytest.mark.xfail( + # manylinux2014 uses glibc2.17 + _glibc_older_than("2.18"), + reason="Older glibc versions are imprecise (maybe passes with SIMD?)" + ) + @pytest.mark.xfail(IS_WASM, reason="doesn't work") + @pytest.mark.parametrize('dtype', [ + np.complex64, np.complex128, np.clongdouble + ]) + def test_loss_of_precision(self, dtype): + """Check loss of precision in complex arc* functions""" + if dtype is np.clongdouble and platform.machine() != 'x86_64': + # Failures on musllinux, aarch64, s390x, ppc64le (see gh-17554) + pytest.skip('Only works reliably for x86-64 and recent glibc') + + # Check against known-good functions + + info = np.finfo(dtype) + real_dtype = dtype(0.).real.dtype + eps = info.eps + + def check(x, rtol): + x = x.astype(real_dtype) + + z = x.astype(dtype) + d = np.absolute(np.arcsinh(x) / np.arcsinh(z).real - 1) + assert_(np.all(d < rtol), (np.argmax(d), x[np.argmax(d)], d.max(), + 'arcsinh')) + + z = (1j * x).astype(dtype) + d = np.absolute(np.arcsinh(x) / np.arcsin(z).imag - 1) + assert_(np.all(d < rtol), (np.argmax(d), x[np.argmax(d)], d.max(), + 'arcsin')) + + z = x.astype(dtype) + d = np.absolute(np.arctanh(x) / np.arctanh(z).real - 1) + assert_(np.all(d < rtol), (np.argmax(d), x[np.argmax(d)], d.max(), + 'arctanh')) + + z = (1j * x).astype(dtype) + d = np.absolute(np.arctanh(x) / np.arctan(z).imag - 1) + assert_(np.all(d < rtol), (np.argmax(d), x[np.argmax(d)], d.max(), + 'arctan')) + + # The switchover was chosen as 1e-3; hence there can be up to + # ~eps/1e-3 of relative cancellation error before it + + x_series = np.logspace(-20, -3.001, 200) + x_basic = np.logspace(-2.999, 0, 10, endpoint=False) + + if dtype is np.clongdouble: + if bad_arcsinh(): + pytest.skip("Trig functions of np.clongdouble values known " + "to be inaccurate on aarch64 and PPC for some " + "compilation configurations.") + # It's not guaranteed that the system-provided arc functions + # are accurate down to a few epsilons. (Eg. on Linux 64-bit) + # So, give more leeway for long complex tests here: + check(x_series, 50.0 * eps) + else: + check(x_series, 2.1 * eps) + check(x_basic, 2.0 * eps / 1e-3) + + # Check a few points + + z = np.array([1e-5 * (1 + 1j)], dtype=dtype) + p = 9.999999999333333333e-6 + 1.000000000066666666e-5j + d = np.absolute(1 - np.arctanh(z) / p) + assert_(np.all(d < 1e-15)) + + p = 1.0000000000333333333e-5 + 9.999999999666666667e-6j + d = np.absolute(1 - np.arcsinh(z) / p) + assert_(np.all(d < 1e-15)) + + p = 9.999999999333333333e-6j + 1.000000000066666666e-5 + d = np.absolute(1 - np.arctan(z) / p) + assert_(np.all(d < 1e-15)) + + p = 1.0000000000333333333e-5j + 9.999999999666666667e-6 + d = np.absolute(1 - np.arcsin(z) / p) + assert_(np.all(d < 1e-15)) + + # Check continuity across switchover points + + def check(func, z0, d=1): + z0 = np.asarray(z0, dtype=dtype) + zp = z0 + abs(z0) * d * eps * 2 + zm = z0 - abs(z0) * d * eps * 2 + assert_(np.all(zp != zm), (zp, zm)) + + # NB: the cancellation error at the switchover is at least eps + good = (abs(func(zp) - func(zm)) < 2 * eps) + assert_(np.all(good), (func, z0[~good])) + + for func in (np.arcsinh, np.arcsinh, np.arcsin, np.arctanh, np.arctan): + pts = [rp + 1j * ip for rp in (-1e-3, 0, 1e-3) for ip in (-1e-3, 0, 1e-3) + if rp != 0 or ip != 0] + check(func, pts, 1) + check(func, pts, 1j) + check(func, pts, 1 + 1j) + + @np.errstate(all="ignore") + def test_promotion_corner_cases(self): + for func in self.funcs: + assert func(np.float16(1)).dtype == np.float16 + # Integer to low precision float promotion is a dubious choice: + assert func(np.uint8(1)).dtype == np.float16 + assert func(np.int16(1)).dtype == np.float32 + + +class TestAttributes: + def test_attributes(self): + add = ncu.add + assert_equal(add.__name__, 'add') + assert_(add.ntypes >= 18) # don't fail if types added + assert_('ii->i' in add.types) + assert_equal(add.nin, 2) + assert_equal(add.nout, 1) + assert_equal(add.identity, 0) + + def test_doc(self): + # don't bother checking the long list of kwargs, which are likely to + # change + assert_(ncu.add.__doc__.startswith( + "add(x1, x2, /, out=None, *, where=True")) + assert_(ncu.frexp.__doc__.startswith( + "frexp(x[, out1, out2], / [, out=(None, None)], *, where=True")) + + +class TestSubclass: + + def test_subclass_op(self): + + class simple(np.ndarray): + def __new__(subtype, shape): + self = np.ndarray.__new__(subtype, shape, dtype=object) + self.fill(0) + return self + + a = simple((3, 4)) + assert_equal(a + a, a) + + +class TestFrompyfunc: + + def test_identity(self): + def mul(a, b): + return a * b + + # with identity=value + mul_ufunc = np.frompyfunc(mul, nin=2, nout=1, identity=1) + assert_equal(mul_ufunc.reduce([2, 3, 4]), 24) + assert_equal(mul_ufunc.reduce(np.ones((2, 2)), axis=(0, 1)), 1) + assert_equal(mul_ufunc.reduce([]), 1) + + # with identity=None (reorderable) + mul_ufunc = np.frompyfunc(mul, nin=2, nout=1, identity=None) + assert_equal(mul_ufunc.reduce([2, 3, 4]), 24) + assert_equal(mul_ufunc.reduce(np.ones((2, 2)), axis=(0, 1)), 1) + assert_raises(ValueError, lambda: mul_ufunc.reduce([])) + + # with no identity (not reorderable) + mul_ufunc = np.frompyfunc(mul, nin=2, nout=1) + assert_equal(mul_ufunc.reduce([2, 3, 4]), 24) + assert_raises(ValueError, lambda: mul_ufunc.reduce(np.ones((2, 2)), axis=(0, 1))) + assert_raises(ValueError, lambda: mul_ufunc.reduce([])) + + +def _check_branch_cut(f, x0, dx, re_sign=1, im_sign=-1, sig_zero_ok=False, + dtype=complex): + """ + Check for a branch cut in a function. + + Assert that `x0` lies on a branch cut of function `f` and `f` is + continuous from the direction `dx`. + + Parameters + ---------- + f : func + Function to check + x0 : array-like + Point on branch cut + dx : array-like + Direction to check continuity in + re_sign, im_sign : {1, -1} + Change of sign of the real or imaginary part expected + sig_zero_ok : bool + Whether to check if the branch cut respects signed zero (if applicable) + dtype : dtype + Dtype to check (should be complex) + + """ + x0 = np.atleast_1d(x0).astype(dtype) + dx = np.atleast_1d(dx).astype(dtype) + + if np.dtype(dtype).char == 'F': + scale = np.finfo(dtype).eps * 1e2 + atol = np.float32(1e-2) + else: + scale = np.finfo(dtype).eps * 1e3 + atol = 1e-4 + + y0 = f(x0) + yp = f(x0 + dx * scale * np.absolute(x0) / np.absolute(dx)) + ym = f(x0 - dx * scale * np.absolute(x0) / np.absolute(dx)) + + assert_(np.all(np.absolute(y0.real - yp.real) < atol), (y0, yp)) + assert_(np.all(np.absolute(y0.imag - yp.imag) < atol), (y0, yp)) + assert_(np.all(np.absolute(y0.real - ym.real * re_sign) < atol), (y0, ym)) + assert_(np.all(np.absolute(y0.imag - ym.imag * im_sign) < atol), (y0, ym)) + + if sig_zero_ok: + # check that signed zeros also work as a displacement + jr = (x0.real == 0) & (dx.real != 0) + ji = (x0.imag == 0) & (dx.imag != 0) + if np.any(jr): + x = x0[jr] + x.real = ncu.NZERO + ym = f(x) + assert_(np.all(np.absolute(y0[jr].real - ym.real * re_sign) < atol), (y0[jr], ym)) + assert_(np.all(np.absolute(y0[jr].imag - ym.imag * im_sign) < atol), (y0[jr], ym)) + + if np.any(ji): + x = x0[ji] + x.imag = ncu.NZERO + ym = f(x) + assert_(np.all(np.absolute(y0[ji].real - ym.real * re_sign) < atol), (y0[ji], ym)) + assert_(np.all(np.absolute(y0[ji].imag - ym.imag * im_sign) < atol), (y0[ji], ym)) + +def test_copysign(): + assert_(np.copysign(1, -1) == -1) + with np.errstate(divide="ignore"): + assert_(1 / np.copysign(0, -1) < 0) + assert_(1 / np.copysign(0, 1) > 0) + assert_(np.signbit(np.copysign(np.nan, -1))) + assert_(not np.signbit(np.copysign(np.nan, 1))) + +def _test_nextafter(t): + one = t(1) + two = t(2) + zero = t(0) + eps = np.finfo(t).eps + assert_(np.nextafter(one, two) - one == eps) + assert_(np.nextafter(one, zero) - one < 0) + assert_(np.isnan(np.nextafter(np.nan, one))) + assert_(np.isnan(np.nextafter(one, np.nan))) + assert_(np.nextafter(one, one) == one) + +def test_nextafter(): + return _test_nextafter(np.float64) + + +def test_nextafterf(): + return _test_nextafter(np.float32) + + +@pytest.mark.skipif(np.finfo(np.double) == np.finfo(np.longdouble), + reason="long double is same as double") +@pytest.mark.xfail(condition=platform.machine().startswith("ppc64"), + reason="IBM double double") +def test_nextafterl(): + return _test_nextafter(np.longdouble) + + +def test_nextafter_0(): + for t, direction in itertools.product(np._core.sctypes['float'], (1, -1)): + # The value of tiny for double double is NaN, so we need to pass the + # assert + with warnings.catch_warnings(): + warnings.simplefilter('ignore', UserWarning) + if not np.isnan(np.finfo(t).tiny): + tiny = np.finfo(t).tiny + assert_( + 0. < direction * np.nextafter(t(0), t(direction)) < tiny) + assert_equal(np.nextafter(t(0), t(direction)) / t(2.1), direction * 0.0) + +def _test_spacing(t): + one = t(1) + eps = np.finfo(t).eps + nan = t(np.nan) + inf = t(np.inf) + with np.errstate(invalid='ignore'): + assert_equal(np.spacing(one), eps) + assert_(np.isnan(np.spacing(nan))) + assert_(np.isnan(np.spacing(inf))) + assert_(np.isnan(np.spacing(-inf))) + assert_(np.spacing(t(1e30)) != 0) + +def test_spacing(): + return _test_spacing(np.float64) + +def test_spacingf(): + return _test_spacing(np.float32) + + +@pytest.mark.skipif(np.finfo(np.double) == np.finfo(np.longdouble), + reason="long double is same as double") +@pytest.mark.xfail(condition=platform.machine().startswith("ppc64"), + reason="IBM double double") +def test_spacingl(): + return _test_spacing(np.longdouble) + +def test_spacing_gfortran(): + # Reference from this fortran file, built with gfortran 4.3.3 on linux + # 32bits: + # PROGRAM test_spacing + # INTEGER, PARAMETER :: SGL = SELECTED_REAL_KIND(p=6, r=37) + # INTEGER, PARAMETER :: DBL = SELECTED_REAL_KIND(p=13, r=200) + # + # WRITE(*,*) spacing(0.00001_DBL) + # WRITE(*,*) spacing(1.0_DBL) + # WRITE(*,*) spacing(1000._DBL) + # WRITE(*,*) spacing(10500._DBL) + # + # WRITE(*,*) spacing(0.00001_SGL) + # WRITE(*,*) spacing(1.0_SGL) + # WRITE(*,*) spacing(1000._SGL) + # WRITE(*,*) spacing(10500._SGL) + # END PROGRAM + ref = {np.float64: [1.69406589450860068E-021, + 2.22044604925031308E-016, + 1.13686837721616030E-013, + 1.81898940354585648E-012], + np.float32: [9.09494702E-13, + 1.19209290E-07, + 6.10351563E-05, + 9.76562500E-04]} + + for dt, dec_ in zip([np.float32, np.float64], (10, 20)): + x = np.array([1e-5, 1, 1000, 10500], dtype=dt) + assert_array_almost_equal(np.spacing(x), ref[dt], decimal=dec_) + +def test_nextafter_vs_spacing(): + # XXX: spacing does not handle long double yet + for t in [np.float32, np.float64]: + for _f in [1, 1e-5, 1000]: + f = t(_f) + f1 = t(_f + 1) + assert_(np.nextafter(f, f1) - f == np.spacing(f)) + +def test_pos_nan(): + """Check np.nan is a positive nan.""" + assert_(np.signbit(np.nan) == 0) + +def test_reduceat(): + """Test bug in reduceat when structured arrays are not copied.""" + db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)]) + a = np.empty([100], dtype=db) + a['name'] = 'Simple' + a['time'] = 10 + a['value'] = 100 + indx = [0, 7, 15, 25] + + h2 = [] + val1 = indx[0] + for val2 in indx[1:]: + h2.append(np.add.reduce(a['value'][val1:val2])) + val1 = val2 + h2.append(np.add.reduce(a['value'][val1:])) + h2 = np.array(h2) + + # test buffered -- this should work + h1 = np.add.reduceat(a['value'], indx) + assert_array_almost_equal(h1, h2) + + # This is when the error occurs. + # test no buffer + np.setbufsize(32) + h1 = np.add.reduceat(a['value'], indx) + np.setbufsize(ncu.UFUNC_BUFSIZE_DEFAULT) + assert_array_almost_equal(h1, h2) + +def test_negative_value_raises(): + with pytest.raises(ValueError, match="buffer size must be non-negative"): + np.setbufsize(-5) + + old = np.getbufsize() + try: + prev = np.setbufsize(4096) + assert prev == old + assert np.getbufsize() == 4096 + finally: + np.setbufsize(old) + +def test_reduceat_empty(): + """Reduceat should work with empty arrays""" + indices = np.array([], 'i4') + x = np.array([], 'f8') + result = np.add.reduceat(x, indices) + assert_equal(result.dtype, x.dtype) + assert_equal(result.shape, (0,)) + # Another case with a slightly different zero-sized shape + x = np.ones((5, 2)) + result = np.add.reduceat(x, [], axis=0) + assert_equal(result.dtype, x.dtype) + assert_equal(result.shape, (0, 2)) + result = np.add.reduceat(x, [], axis=1) + assert_equal(result.dtype, x.dtype) + assert_equal(result.shape, (5, 0)) + +def test_complex_nan_comparisons(): + nans = [complex(np.nan, 0), complex(0, np.nan), complex(np.nan, np.nan)] + fins = [complex(1, 0), complex(-1, 0), complex(0, 1), complex(0, -1), + complex(1, 1), complex(-1, -1), complex(0, 0)] + + with np.errstate(invalid='ignore'): + for x in nans + fins: + x = np.array([x]) + for y in nans + fins: + y = np.array([y]) + + if np.isfinite(x) and np.isfinite(y): + continue + + assert_equal(x < y, False, err_msg=f"{x!r} < {y!r}") + assert_equal(x > y, False, err_msg=f"{x!r} > {y!r}") + assert_equal(x <= y, False, err_msg=f"{x!r} <= {y!r}") + assert_equal(x >= y, False, err_msg=f"{x!r} >= {y!r}") + assert_equal(x == y, False, err_msg=f"{x!r} == {y!r}") + + +def test_rint_big_int(): + # np.rint bug for large integer values on Windows 32-bit and MKL + # https://github.com/numpy/numpy/issues/6685 + val = 4607998452777363968 + # This is exactly representable in floating point + assert_equal(val, int(float(val))) + # Rint should not change the value + assert_equal(val, np.rint(val)) + + +@pytest.mark.parametrize('ftype', [np.float32, np.float64]) +def test_memoverlap_accumulate(ftype): + # Reproduces bug https://github.com/numpy/numpy/issues/15597 + arr = np.array([0.61, 0.60, 0.77, 0.41, 0.19], dtype=ftype) + out_max = np.array([0.61, 0.61, 0.77, 0.77, 0.77], dtype=ftype) + out_min = np.array([0.61, 0.60, 0.60, 0.41, 0.19], dtype=ftype) + assert_equal(np.maximum.accumulate(arr), out_max) + assert_equal(np.minimum.accumulate(arr), out_min) + +@pytest.mark.parametrize("ufunc, dtype", [ + (ufunc, t[0]) + for ufunc in UFUNCS_BINARY_ACC + for t in ufunc.types + if t[-1] == '?' and t[0] not in 'DFGMmO' +]) +def test_memoverlap_accumulate_cmp(ufunc, dtype): + if ufunc.signature: + pytest.skip('For generic signatures only') + for size in (2, 8, 32, 64, 128, 256): + arr = np.array([0, 1, 1] * size, dtype=dtype) + acc = ufunc.accumulate(arr, dtype='?') + acc_u8 = acc.view(np.uint8) + exp = np.array(list(itertools.accumulate(arr, ufunc)), dtype=np.uint8) + assert_equal(exp, acc_u8) + +@pytest.mark.parametrize("ufunc, dtype", [ + (ufunc, t[0]) + for ufunc in UFUNCS_BINARY_ACC + for t in ufunc.types + if t[0] == t[1] and t[0] == t[-1] and t[0] not in 'DFGMmO?' +]) +def test_memoverlap_accumulate_symmetric(ufunc, dtype): + if ufunc.signature: + pytest.skip('For generic signatures only') + with np.errstate(all='ignore'): + for size in (2, 8, 32, 64, 128, 256): + arr = np.array([0, 1, 2] * size).astype(dtype) + acc = ufunc.accumulate(arr, dtype=dtype) + exp = np.array(list(itertools.accumulate(arr, ufunc)), dtype=dtype) + assert_equal(exp, acc) + +def test_signaling_nan_exceptions(): + with assert_no_warnings(): + a = np.ndarray(shape=(), dtype='float32', buffer=b'\x00\xe0\xbf\xff') + np.isnan(a) + +@pytest.mark.parametrize("arr", [ + np.arange(2), + np.matrix([0, 1]), + np.matrix([[0, 1], [2, 5]]), + ]) +def test_outer_subclass_preserve(arr): + # for gh-8661 + class foo(np.ndarray): + pass + actual = np.multiply.outer(arr.view(foo), arr.view(foo)) + assert actual.__class__.__name__ == 'foo' + +def test_outer_bad_subclass(): + class BadArr1(np.ndarray): + def __array_finalize__(self, obj): + # The outer call reshapes to 3 dims, try to do a bad reshape. + if self.ndim == 3: + self.shape = self.shape + (1,) + + class BadArr2(np.ndarray): + def __array_finalize__(self, obj): + if isinstance(obj, BadArr2): + # outer inserts 1-sized dims. In that case disturb them. + if self.shape[-1] == 1: + self.shape = self.shape[::-1] + + for cls in [BadArr1, BadArr2]: + arr = np.ones((2, 3)).view(cls) + with assert_raises(TypeError) as a: + # The first array gets reshaped (not the second one) + np.add.outer(arr, [1, 2]) + + # This actually works, since we only see the reshaping error: + arr = np.ones((2, 3)).view(cls) + assert type(np.add.outer([1, 2], arr)) is cls + +def test_outer_exceeds_maxdims(): + deep = np.ones((1,) * 33) + with assert_raises(ValueError): + np.add.outer(deep, deep) + +def test_bad_legacy_ufunc_silent_errors(): + # legacy ufuncs can't report errors and NumPy can't check if the GIL + # is released. So NumPy has to check after the GIL is released just to + # cover all bases. `np.power` uses/used to use this. + arr = np.arange(3).astype(np.float64) + + with pytest.raises(RuntimeError, match=r"How unexpected :\)!"): + ncu_tests.always_error(arr, arr) + + with pytest.raises(RuntimeError, match=r"How unexpected :\)!"): + # not contiguous means the fast-path cannot be taken + non_contig = arr.repeat(20).reshape(-1, 6)[:, ::2] + ncu_tests.always_error(non_contig, arr) + + with pytest.raises(RuntimeError, match=r"How unexpected :\)!"): + ncu_tests.always_error.outer(arr, arr) + + with pytest.raises(RuntimeError, match=r"How unexpected :\)!"): + ncu_tests.always_error.reduce(arr) + + with pytest.raises(RuntimeError, match=r"How unexpected :\)!"): + ncu_tests.always_error.reduceat(arr, [0, 1]) + + with pytest.raises(RuntimeError, match=r"How unexpected :\)!"): + ncu_tests.always_error.accumulate(arr) + + with pytest.raises(RuntimeError, match=r"How unexpected :\)!"): + ncu_tests.always_error.at(arr, [0, 1, 2], arr) + + +def test_bad_legacy_unary_ufunc_silent_errors(): + # Unary has a special scalar path right now, so test it explicitly. + with pytest.raises(RuntimeError, match=r"How unexpected :\)!"): + ncu_tests.always_error_unary(np.arange(3).astype(np.float64)) + + with pytest.raises(RuntimeError, match=r"How unexpected :\)!"): + ncu_tests.always_error_unary(1.5) + + +@pytest.mark.parametrize('x1', [np.arange(3.0), [0.0, 1.0, 2.0]]) +def test_bad_legacy_gufunc_silent_errors(x1): + # Verify that an exception raised in a gufunc loop propagates correctly. + # The signature of always_error_gufunc is '(i),()->()'. + with pytest.raises(RuntimeError, match=r"How unexpected :\)!"): + ncu_tests.always_error_gufunc(x1, 0.0) + + +class TestAddDocstring: + @pytest.mark.skipif(sys.flags.optimize == 2, reason="Python running -OO") + @pytest.mark.skipif(IS_PYPY, reason="PyPy does not modify tp_doc") + def test_add_same_docstring(self): + # test for attributes (which are C-level defined) + ncu.add_docstring(np.ndarray.flat, np.ndarray.flat.__doc__) + + # And typical functions: + def func(): + """docstring""" + return + + ncu.add_docstring(func, func.__doc__) + + @pytest.mark.skipif(sys.flags.optimize == 2, reason="Python running -OO") + def test_different_docstring_fails(self): + # test for attributes (which are C-level defined) + with assert_raises(RuntimeError): + ncu.add_docstring(np.ndarray.flat, "different docstring") + + # And typical functions: + def func(): + """docstring""" + return + + with assert_raises(RuntimeError): + ncu.add_docstring(func, "different docstring") + + +class TestAdd_newdoc_ufunc: + @pytest.mark.filterwarnings("ignore:_add_newdoc_ufunc:DeprecationWarning") + def test_ufunc_arg(self): + assert_raises(TypeError, ncu._add_newdoc_ufunc, 2, "blah") + assert_raises(ValueError, ncu._add_newdoc_ufunc, np.add, "blah") + + @pytest.mark.filterwarnings("ignore:_add_newdoc_ufunc:DeprecationWarning") + def test_string_arg(self): + assert_raises(TypeError, ncu._add_newdoc_ufunc, np.add, 3) + +class TestHypotErrorMessages: + def test_hypot_error_message_single_arg(self): + with pytest.raises(TypeError, match="hypot\\(\\) takes .* but 1 was given"): + np.hypot(5) + + def test_hypot_error_message_multiple_args(self): + with pytest.raises(TypeError, match="hypot\\(\\) takes .* but 4 were given"): + np.hypot(1, 2, 3, 4) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_umath_accuracy.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_umath_accuracy.py new file mode 100644 index 0000000000000000000000000000000000000000..3ca2f508672e90ec890df3b58082d31328efa0be --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_umath_accuracy.py @@ -0,0 +1,132 @@ +import os +import sys +from ctypes import POINTER, c_double, c_float, c_int, c_longlong, cast, pointer +from os import path + +import pytest + +import numpy as np +from numpy._core._multiarray_umath import __cpu_features__ +from numpy.testing import assert_array_max_ulp +from numpy.testing._private.utils import _glibc_older_than + +UNARY_UFUNCS = [obj for obj in np._core.umath.__dict__.values() if + isinstance(obj, np.ufunc)] +UNARY_OBJECT_UFUNCS = [uf for uf in UNARY_UFUNCS if "O->O" in uf.types] + +# Remove functions that do not support `floats` +UNARY_OBJECT_UFUNCS.remove(np.invert) +UNARY_OBJECT_UFUNCS.remove(np.bitwise_count) + +IS_AVX = __cpu_features__.get('AVX512F', False) or \ + (__cpu_features__.get('FMA3', False) and __cpu_features__.get('AVX2', False)) + +IS_AVX512FP16 = __cpu_features__.get('AVX512FP16', False) + +# only run on linux with AVX, also avoid old glibc (numpy/numpy#20448). +runtest = (sys.platform.startswith('linux') + and IS_AVX and not _glibc_older_than("2.17")) +platform_skip = pytest.mark.skipif(not runtest, + reason="avoid testing inconsistent platform " + "library implementations") + +# convert string to hex function taken from: +# https://stackoverflow.com/questions/1592158/convert-hex-to-float # +def convert(s, datatype="np.float32"): + i = int(s, 16) # convert from hex to a Python int + if (datatype == "np.float64"): + cp = pointer(c_longlong(i)) # make this into a c long long integer + fp = cast(cp, POINTER(c_double)) # cast the int pointer to a double pointer + else: + cp = pointer(c_int(i)) # make this into a c integer + fp = cast(cp, POINTER(c_float)) # cast the int pointer to a float pointer + + return fp.contents.value # dereference the pointer, get the float + + +str_to_float = np.vectorize(convert) + +class TestAccuracy: + @platform_skip + def test_validate_transcendentals(self): + with np.errstate(all='ignore'): + data_dir = path.join(path.dirname(__file__), 'data') + files = os.listdir(data_dir) + files = list(filter(lambda f: f.endswith('.csv'), files)) + for filename in files: + filepath = path.join(data_dir, filename) + with open(filepath) as fid: + file_without_comments = ( + r for r in fid if r[0] not in ('$', '#') + ) + data = np.genfromtxt(file_without_comments, + dtype=('|S39', '|S39', '|S39', int), + names=('type', 'input', 'output', 'ulperr'), + delimiter=',', + skip_header=1) + npname = path.splitext(filename)[0].split('-')[3] + npfunc = getattr(np, npname) + for datatype in np.unique(data['type']): + data_subset = data[data['type'] == datatype] + data_input_str = data_subset['input'].astype(str) + data_output_str = data_subset['output'].astype(str) + data_type_str = data_subset['type'].astype(str) + + inval = np.array(str_to_float(data_input_str, + data_type_str), + dtype=eval(datatype)) + outval = np.array(str_to_float(data_output_str, + data_type_str), + dtype=eval(datatype)) + perm = np.random.permutation(len(inval)) + inval = inval[perm] + outval = outval[perm] + maxulperr = data_subset['ulperr'].max() + assert_array_max_ulp(npfunc(inval), outval, maxulperr) + + @pytest.mark.skipif(IS_AVX512FP16, + reason="SVML FP16 have slightly higher ULP errors") + @pytest.mark.parametrize("ufunc", UNARY_OBJECT_UFUNCS) + def test_validate_fp16_transcendentals(self, ufunc): + with np.errstate(all='ignore'): + arr = np.arange(65536, dtype=np.int16) + datafp16 = np.frombuffer(arr.tobytes(), dtype=np.float16) + datafp32 = datafp16.astype(np.float32) + assert_array_max_ulp(ufunc(datafp16), ufunc(datafp32), + maxulp=1, dtype=np.float16) + + @pytest.mark.skipif(not IS_AVX512FP16, + reason="lower ULP only apply for SVML FP16") + def test_validate_svml_fp16(self): + max_ulp_err = { + "arccos": 2.54, + "arccosh": 2.09, + "arcsin": 3.06, + "arcsinh": 1.51, + "arctan": 2.61, + "arctanh": 1.88, + "cbrt": 1.57, + "cos": 1.43, + "cosh": 1.33, + "exp2": 1.33, + "exp": 1.27, + "expm1": 0.53, + "log": 1.80, + "log10": 1.27, + "log1p": 1.88, + "log2": 1.80, + "sin": 1.88, + "sinh": 2.05, + "tan": 2.26, + "tanh": 3.00, + } + + with np.errstate(all='ignore'): + arr = np.arange(65536, dtype=np.int16) + datafp16 = np.frombuffer(arr.tobytes(), dtype=np.float16) + datafp32 = datafp16.astype(np.float32) + for func in max_ulp_err: + ufunc = getattr(np, func) + ulp = np.ceil(max_ulp_err[func]) + assert_array_max_ulp(ufunc(datafp16), ufunc(datafp32), + maxulp=ulp, dtype=np.float16) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_umath_complex.py b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_umath_complex.py new file mode 100644 index 0000000000000000000000000000000000000000..7012e7e357fe11139c5b0bfd2bcdeb082348138d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/_core/tests/test_umath_complex.py @@ -0,0 +1,631 @@ +import platform +import sys + +import pytest + +import numpy as np + +# import the c-extension module directly since _arg is not exported via umath +import numpy._core._multiarray_umath as ncu +from numpy.testing import ( + assert_almost_equal, + assert_array_equal, + assert_array_max_ulp, + assert_equal, + assert_raises, +) + +# TODO: branch cuts (use Pauli code) +# TODO: conj 'symmetry' +# TODO: FPU exceptions + +# At least on Windows the results of many complex functions are not conforming +# to the C99 standard. See ticket 1574. +# Ditto for Solaris (ticket 1642) and OS X on PowerPC. +# FIXME: this will probably change when we require full C99 compatibility +with np.errstate(all='ignore'): + functions_seem_flaky = ((np.exp(complex(np.inf, 0)).imag != 0) + or (np.log(complex(ncu.NZERO, 0)).imag != np.pi)) +# TODO: replace with a check on whether platform-provided C99 funcs are used +xfail_complex_tests = (not sys.platform.startswith('linux') or functions_seem_flaky) + +# TODO This can be xfail when the generator functions are got rid of. +platform_skip = pytest.mark.skipif(xfail_complex_tests, + reason="Inadequate C99 complex support") + + +class TestCexp: + def test_simple(self): + check = check_complex_value + f = np.exp + + check(f, 1, 0, np.exp(1), 0, False) + check(f, 0, 1, np.cos(1), np.sin(1), False) + + ref = np.exp(1) * complex(np.cos(1), np.sin(1)) + check(f, 1, 1, ref.real, ref.imag, False) + + @platform_skip + def test_special_values(self): + # C99: Section G 6.3.1 + + check = check_complex_value + f = np.exp + + # cexp(+-0 + 0i) is 1 + 0i + check(f, ncu.PZERO, 0, 1, 0, False) + check(f, ncu.NZERO, 0, 1, 0, False) + + # cexp(x + infi) is nan + nani for finite x and raises 'invalid' FPU + # exception + check(f, 1, np.inf, np.nan, np.nan) + check(f, -1, np.inf, np.nan, np.nan) + check(f, 0, np.inf, np.nan, np.nan) + + # cexp(inf + 0i) is inf + 0i + check(f, np.inf, 0, np.inf, 0) + + # cexp(-inf + yi) is +0 * (cos(y) + i sin(y)) for finite y + check(f, -np.inf, 1, ncu.PZERO, ncu.PZERO) + check(f, -np.inf, 0.75 * np.pi, ncu.NZERO, ncu.PZERO) + + # cexp(inf + yi) is +inf * (cos(y) + i sin(y)) for finite y + check(f, np.inf, 1, np.inf, np.inf) + check(f, np.inf, 0.75 * np.pi, -np.inf, np.inf) + + # cexp(-inf + inf i) is +-0 +- 0i (signs unspecified) + def _check_ninf_inf(dummy): + msgform = "cexp(-inf, inf) is (%f, %f), expected (+-0, +-0)" + with np.errstate(invalid='ignore'): + z = f(np.array(complex(-np.inf, np.inf))) + if z.real != 0 or z.imag != 0: + raise AssertionError(msgform % (z.real, z.imag)) + + _check_ninf_inf(None) + + # cexp(inf + inf i) is +-inf + NaNi and raised invalid FPU ex. + def _check_inf_inf(dummy): + msgform = "cexp(inf, inf) is (%f, %f), expected (+-inf, nan)" + with np.errstate(invalid='ignore'): + z = f(np.array(complex(np.inf, np.inf))) + if not np.isinf(z.real) or not np.isnan(z.imag): + raise AssertionError(msgform % (z.real, z.imag)) + + _check_inf_inf(None) + + # cexp(-inf + nan i) is +-0 +- 0i + def _check_ninf_nan(dummy): + msgform = "cexp(-inf, nan) is (%f, %f), expected (+-0, +-0)" + with np.errstate(invalid='ignore'): + z = f(np.array(complex(-np.inf, np.nan))) + if z.real != 0 or z.imag != 0: + raise AssertionError(msgform % (z.real, z.imag)) + + _check_ninf_nan(None) + + # cexp(inf + nan i) is +-inf + nan + def _check_inf_nan(dummy): + msgform = "cexp(-inf, nan) is (%f, %f), expected (+-inf, nan)" + with np.errstate(invalid='ignore'): + z = f(np.array(complex(np.inf, np.nan))) + if not np.isinf(z.real) or not np.isnan(z.imag): + raise AssertionError(msgform % (z.real, z.imag)) + + _check_inf_nan(None) + + # cexp(nan + yi) is nan + nani for y != 0 (optional: raises invalid FPU + # ex) + check(f, np.nan, 1, np.nan, np.nan) + check(f, np.nan, -1, np.nan, np.nan) + + check(f, np.nan, np.inf, np.nan, np.nan) + check(f, np.nan, -np.inf, np.nan, np.nan) + + # cexp(nan + nani) is nan + nani + check(f, np.nan, np.nan, np.nan, np.nan) + + # TODO This can be xfail when the generator functions are got rid of. + @pytest.mark.skip(reason="cexp(nan + 0I) is wrong on most platforms") + def test_special_values2(self): + # XXX: most implementations get it wrong here (including glibc <= 2.10) + # cexp(nan + 0i) is nan + 0i + check = check_complex_value + f = np.exp + + check(f, np.nan, 0, np.nan, 0) + +class TestClog: + def test_simple(self): + x = np.array([1 + 0j, 1 + 2j]) + y_r = np.log(np.abs(x)) + 1j * np.angle(x) + y = np.log(x) + assert_almost_equal(y, y_r) + + @platform_skip + @pytest.mark.skipif(platform.machine() == "armv5tel", reason="See gh-413.") + def test_special_values(self): + xl = [] + yl = [] + + # From C99 std (Sec 6.3.2) + # XXX: check exceptions raised + # --- raise for invalid fails. + + # clog(-0 + i0) returns -inf + i pi and raises the 'divide-by-zero' + # floating-point exception. + with np.errstate(divide='raise'): + x = np.array([ncu.NZERO], dtype=complex) + y = complex(-np.inf, np.pi) + assert_raises(FloatingPointError, np.log, x) + with np.errstate(divide='ignore'): + assert_almost_equal(np.log(x), y) + + xl.append(x) + yl.append(y) + + # clog(+0 + i0) returns -inf + i0 and raises the 'divide-by-zero' + # floating-point exception. + with np.errstate(divide='raise'): + x = np.array([0], dtype=complex) + y = complex(-np.inf, 0) + assert_raises(FloatingPointError, np.log, x) + with np.errstate(divide='ignore'): + assert_almost_equal(np.log(x), y) + + xl.append(x) + yl.append(y) + + # clog(x + i inf returns +inf + i pi /2, for finite x. + x = np.array([complex(1, np.inf)], dtype=complex) + y = complex(np.inf, 0.5 * np.pi) + assert_almost_equal(np.log(x), y) + xl.append(x) + yl.append(y) + + x = np.array([complex(-1, np.inf)], dtype=complex) + assert_almost_equal(np.log(x), y) + xl.append(x) + yl.append(y) + + # clog(x + iNaN) returns NaN + iNaN and optionally raises the + # 'invalid' floating- point exception, for finite x. + with np.errstate(invalid='raise'): + x = np.array([complex(1., np.nan)], dtype=complex) + y = complex(np.nan, np.nan) + #assert_raises(FloatingPointError, np.log, x) + with np.errstate(invalid='ignore'): + assert_almost_equal(np.log(x), y) + + xl.append(x) + yl.append(y) + + with np.errstate(invalid='raise'): + x = np.array([np.inf + 1j * np.nan], dtype=complex) + #assert_raises(FloatingPointError, np.log, x) + with np.errstate(invalid='ignore'): + assert_almost_equal(np.log(x), y) + + xl.append(x) + yl.append(y) + + # clog(- inf + iy) returns +inf + ipi , for finite positive-signed y. + x = np.array([-np.inf + 1j], dtype=complex) + y = complex(np.inf, np.pi) + assert_almost_equal(np.log(x), y) + xl.append(x) + yl.append(y) + + # clog(+ inf + iy) returns +inf + i0, for finite positive-signed y. + x = np.array([np.inf + 1j], dtype=complex) + y = complex(np.inf, 0) + assert_almost_equal(np.log(x), y) + xl.append(x) + yl.append(y) + + # clog(- inf + i inf) returns +inf + i3pi /4. + x = np.array([complex(-np.inf, np.inf)], dtype=complex) + y = complex(np.inf, 0.75 * np.pi) + assert_almost_equal(np.log(x), y) + xl.append(x) + yl.append(y) + + # clog(+ inf + i inf) returns +inf + ipi /4. + x = np.array([complex(np.inf, np.inf)], dtype=complex) + y = complex(np.inf, 0.25 * np.pi) + assert_almost_equal(np.log(x), y) + xl.append(x) + yl.append(y) + + # clog(+/- inf + iNaN) returns +inf + iNaN. + x = np.array([complex(np.inf, np.nan)], dtype=complex) + y = complex(np.inf, np.nan) + assert_almost_equal(np.log(x), y) + xl.append(x) + yl.append(y) + + x = np.array([complex(-np.inf, np.nan)], dtype=complex) + assert_almost_equal(np.log(x), y) + xl.append(x) + yl.append(y) + + # clog(NaN + iy) returns NaN + iNaN and optionally raises the + # 'invalid' floating-point exception, for finite y. + x = np.array([complex(np.nan, 1)], dtype=complex) + y = complex(np.nan, np.nan) + assert_almost_equal(np.log(x), y) + xl.append(x) + yl.append(y) + + # clog(NaN + i inf) returns +inf + iNaN. + x = np.array([complex(np.nan, np.inf)], dtype=complex) + y = complex(np.inf, np.nan) + assert_almost_equal(np.log(x), y) + xl.append(x) + yl.append(y) + + # clog(NaN + iNaN) returns NaN + iNaN. + x = np.array([complex(np.nan, np.nan)], dtype=complex) + y = complex(np.nan, np.nan) + assert_almost_equal(np.log(x), y) + xl.append(x) + yl.append(y) + + # clog(conj(z)) = conj(clog(z)). + xa = np.array(xl, dtype=complex) + ya = np.array(yl, dtype=complex) + with np.errstate(divide='ignore'): + for i in range(len(xa)): + assert_almost_equal(np.log(xa[i].conj()), ya[i].conj()) + + +class TestCsqrt: + + def test_simple(self): + # sqrt(1) + check_complex_value(np.sqrt, 1, 0, 1, 0) + + # sqrt(1i) + rres = 0.5 * np.sqrt(2) + ires = rres + check_complex_value(np.sqrt, 0, 1, rres, ires, False) + + # sqrt(-1) + check_complex_value(np.sqrt, -1, 0, 0, 1) + + def test_simple_conjugate(self): + ref = np.conj(np.sqrt(complex(1, 1))) + + def f(z): + return np.sqrt(np.conj(z)) + + check_complex_value(f, 1, 1, ref.real, ref.imag, False) + + #def test_branch_cut(self): + # _check_branch_cut(f, -1, 0, 1, -1) + + @platform_skip + def test_special_values(self): + # C99: Sec G 6.4.2 + + check = check_complex_value + f = np.sqrt + + # csqrt(+-0 + 0i) is 0 + 0i + check(f, ncu.PZERO, 0, 0, 0) + check(f, ncu.NZERO, 0, 0, 0) + + # csqrt(x + infi) is inf + infi for any x (including NaN) + check(f, 1, np.inf, np.inf, np.inf) + check(f, -1, np.inf, np.inf, np.inf) + + check(f, ncu.PZERO, np.inf, np.inf, np.inf) + check(f, ncu.NZERO, np.inf, np.inf, np.inf) + check(f, np.inf, np.inf, np.inf, np.inf) + check(f, -np.inf, np.inf, np.inf, np.inf) # noqa: E221 + check(f, -np.nan, np.inf, np.inf, np.inf) # noqa: E221 + + # csqrt(x + nani) is nan + nani for any finite x + check(f, 1, np.nan, np.nan, np.nan) + check(f, -1, np.nan, np.nan, np.nan) + check(f, 0, np.nan, np.nan, np.nan) + + # csqrt(-inf + yi) is +0 + infi for any finite y > 0 + check(f, -np.inf, 1, ncu.PZERO, np.inf) + + # csqrt(inf + yi) is +inf + 0i for any finite y > 0 + check(f, np.inf, 1, np.inf, ncu.PZERO) + + # csqrt(-inf + nani) is nan +- infi (both +i infi are valid) + def _check_ninf_nan(dummy): + msgform = "csqrt(-inf, nan) is (%f, %f), expected (nan, +-inf)" + z = np.sqrt(np.array(complex(-np.inf, np.nan))) + # FIXME: ugly workaround for isinf bug. + with np.errstate(invalid='ignore'): + if not (np.isnan(z.real) and np.isinf(z.imag)): + raise AssertionError(msgform % (z.real, z.imag)) + + _check_ninf_nan(None) + + # csqrt(+inf + nani) is inf + nani + check(f, np.inf, np.nan, np.inf, np.nan) + + # csqrt(nan + yi) is nan + nani for any finite y (infinite handled in x + # + nani) + check(f, np.nan, 0, np.nan, np.nan) + check(f, np.nan, 1, np.nan, np.nan) + check(f, np.nan, np.nan, np.nan, np.nan) + + # XXX: check for conj(csqrt(z)) == csqrt(conj(z)) (need to fix branch + # cuts first) + +class TestCpow: + def setup_method(self): + self.olderr = np.seterr(invalid='ignore') + + def teardown_method(self): + np.seterr(**self.olderr) + + def test_simple(self): + x = np.array([1 + 1j, 0 + 2j, 1 + 2j, np.inf, np.nan]) + y_r = x ** 2 + y = np.power(x, 2) + assert_almost_equal(y, y_r) + + def test_scalar(self): + x = np.array([1, 1j, 2, 2.5 + .37j, np.inf, np.nan]) + y = np.array([1, 1j, -0.5 + 1.5j, -0.5 + 1.5j, 2, 3]) + lx = list(range(len(x))) + + # Hardcode the expected `builtins.complex` values, + # as complex exponentiation is broken as of bpo-44698 + p_r = [ + 1 + 0j, + 0.20787957635076193 + 0j, + 0.35812203996480685 + 0.6097119028618724j, + 0.12659112128185032 + 0.48847676699581527j, + complex(np.inf, np.nan), + complex(np.nan, np.nan), + ] + + n_r = [x[i] ** y[i] for i in lx] + for i in lx: + assert_almost_equal(n_r[i], p_r[i], err_msg='Loop %d\n' % i) + + def test_array(self): + x = np.array([1, 1j, 2, 2.5 + .37j, np.inf, np.nan]) + y = np.array([1, 1j, -0.5 + 1.5j, -0.5 + 1.5j, 2, 3]) + lx = list(range(len(x))) + + # Hardcode the expected `builtins.complex` values, + # as complex exponentiation is broken as of bpo-44698 + p_r = [ + 1 + 0j, + 0.20787957635076193 + 0j, + 0.35812203996480685 + 0.6097119028618724j, + 0.12659112128185032 + 0.48847676699581527j, + complex(np.inf, np.nan), + complex(np.nan, np.nan), + ] + + n_r = x ** y + for i in lx: + assert_almost_equal(n_r[i], p_r[i], err_msg='Loop %d\n' % i) + +class TestCabs: + def setup_method(self): + self.olderr = np.seterr(invalid='ignore') + + def teardown_method(self): + np.seterr(**self.olderr) + + def test_simple(self): + x = np.array([1 + 1j, 0 + 2j, 1 + 2j, np.inf, np.nan]) + y_r = np.array([np.sqrt(2.), 2, np.sqrt(5), np.inf, np.nan]) + y = np.abs(x) + assert_almost_equal(y, y_r) + + def test_fabs(self): + # Test that np.abs(x +- 0j) == np.abs(x) (as mandated by C99 for cabs) + x = np.array([1 + 0j], dtype=complex) + assert_array_equal(np.abs(x), np.real(x)) + + x = np.array([complex(1, ncu.NZERO)], dtype=complex) + assert_array_equal(np.abs(x), np.real(x)) + + x = np.array([complex(np.inf, ncu.NZERO)], dtype=complex) + assert_array_equal(np.abs(x), np.real(x)) + + x = np.array([complex(np.nan, ncu.NZERO)], dtype=complex) + assert_array_equal(np.abs(x), np.real(x)) + + def test_cabs_inf_nan(self): + x, y = [], [] + + # cabs(+-nan + nani) returns nan + x.append(np.nan) + y.append(np.nan) + check_real_value(np.abs, np.nan, np.nan, np.nan) + + x.append(np.nan) + y.append(-np.nan) + check_real_value(np.abs, -np.nan, np.nan, np.nan) + + # According to C99 standard, if exactly one of the real/part is inf and + # the other nan, then cabs should return inf + x.append(np.inf) + y.append(np.nan) + check_real_value(np.abs, np.inf, np.nan, np.inf) + + x.append(-np.inf) + y.append(np.nan) + check_real_value(np.abs, -np.inf, np.nan, np.inf) + + # cabs(conj(z)) == conj(cabs(z)) (= cabs(z)) + def f(a): + return np.abs(np.conj(a)) + + def g(a, b): + return np.abs(complex(a, b)) + + xa = np.array(x, dtype=complex) + assert len(xa) == len(x) == len(y) + for xi, yi in zip(x, y): + ref = g(xi, yi) + check_real_value(f, xi, yi, ref) + +class TestCarg: + def test_simple(self): + check_real_value(ncu._arg, 1, 0, 0, False) + check_real_value(ncu._arg, 0, 1, 0.5 * np.pi, False) + + check_real_value(ncu._arg, 1, 1, 0.25 * np.pi, False) + check_real_value(ncu._arg, ncu.PZERO, ncu.PZERO, ncu.PZERO) + + # TODO This can be xfail when the generator functions are got rid of. + @pytest.mark.skip( + reason="Complex arithmetic with signed zero fails on most platforms") + def test_zero(self): + # carg(-0 +- 0i) returns +- pi + check_real_value(ncu._arg, ncu.NZERO, ncu.PZERO, np.pi, False) + check_real_value(ncu._arg, ncu.NZERO, ncu.NZERO, -np.pi, False) + + # carg(+0 +- 0i) returns +- 0 + check_real_value(ncu._arg, ncu.PZERO, ncu.PZERO, ncu.PZERO) + check_real_value(ncu._arg, ncu.PZERO, ncu.NZERO, ncu.NZERO) + + # carg(x +- 0i) returns +- 0 for x > 0 + check_real_value(ncu._arg, 1, ncu.PZERO, ncu.PZERO, False) + check_real_value(ncu._arg, 1, ncu.NZERO, ncu.NZERO, False) + + # carg(x +- 0i) returns +- pi for x < 0 + check_real_value(ncu._arg, -1, ncu.PZERO, np.pi, False) + check_real_value(ncu._arg, -1, ncu.NZERO, -np.pi, False) + + # carg(+- 0 + yi) returns pi/2 for y > 0 + check_real_value(ncu._arg, ncu.PZERO, 1, 0.5 * np.pi, False) + check_real_value(ncu._arg, ncu.NZERO, 1, 0.5 * np.pi, False) + + # carg(+- 0 + yi) returns -pi/2 for y < 0 + check_real_value(ncu._arg, ncu.PZERO, -1, 0.5 * np.pi, False) + check_real_value(ncu._arg, ncu.NZERO, -1, -0.5 * np.pi, False) + + #def test_branch_cuts(self): + # _check_branch_cut(ncu._arg, -1, 1j, -1, 1) + + def test_special_values(self): + # carg(-np.inf +- yi) returns +-pi for finite y > 0 + check_real_value(ncu._arg, -np.inf, 1, np.pi, False) + check_real_value(ncu._arg, -np.inf, -1, -np.pi, False) + + # carg(np.inf +- yi) returns +-0 for finite y > 0 + check_real_value(ncu._arg, np.inf, 1, ncu.PZERO, False) + check_real_value(ncu._arg, np.inf, -1, ncu.NZERO, False) + + # carg(x +- np.infi) returns +-pi/2 for finite x + check_real_value(ncu._arg, 1, np.inf, 0.5 * np.pi, False) + check_real_value(ncu._arg, 1, -np.inf, -0.5 * np.pi, False) + + # carg(-np.inf +- np.infi) returns +-3pi/4 + check_real_value(ncu._arg, -np.inf, np.inf, 0.75 * np.pi, False) + check_real_value(ncu._arg, -np.inf, -np.inf, -0.75 * np.pi, False) + + # carg(np.inf +- np.infi) returns +-pi/4 + check_real_value(ncu._arg, np.inf, np.inf, 0.25 * np.pi, False) + check_real_value(ncu._arg, np.inf, -np.inf, -0.25 * np.pi, False) + + # carg(x + yi) returns np.nan if x or y is nan + check_real_value(ncu._arg, np.nan, 0, np.nan, False) + check_real_value(ncu._arg, 0, np.nan, np.nan, False) + + check_real_value(ncu._arg, np.nan, np.inf, np.nan, False) + check_real_value(ncu._arg, np.inf, np.nan, np.nan, False) + + +def check_real_value(f, x1, y1, x, exact=True): + z1 = np.array([complex(x1, y1)]) + if exact: + assert_equal(f(z1), x) + else: + assert_almost_equal(f(z1), x) + + +def check_complex_value(f, x1, y1, x2, y2, exact=True): + z1 = np.array([complex(x1, y1)]) + z2 = complex(x2, y2) + with np.errstate(invalid='ignore'): + if exact: + assert_equal(f(z1), z2) + else: + assert_almost_equal(f(z1), z2) + +class TestSpecialComplexAVX: + @pytest.mark.parametrize("stride", [-4, -2, -1, 1, 2, 4]) + @pytest.mark.parametrize("astype", [np.complex64, np.complex128]) + def test_array(self, stride, astype): + nan = np.nan + inf = np.inf + arr = np.array([complex(nan, nan), + complex(nan, inf), + complex(inf, nan), + complex(inf, inf), + complex(0., inf), + complex(inf, 0.), + complex(0., 0.), + complex(0., nan), + complex(nan, 0.)], dtype=astype) + abs_true = np.array([nan, inf, inf, inf, inf, inf, 0., nan, nan], + dtype=arr.real.dtype) + sq_true = np.array([complex(nan, nan), + complex(nan, nan), + complex(nan, nan), + complex(nan, inf), + complex(-inf, nan), + complex(inf, nan), + complex(0., 0.), + complex(nan, nan), + complex(nan, nan)], dtype=astype) + with np.errstate(invalid='ignore'): + assert_equal(np.abs(arr[::stride]), abs_true[::stride]) + assert_equal(np.square(arr[::stride]), sq_true[::stride]) + +class TestComplexAbsoluteAVX: + @pytest.mark.parametrize("arraysize", + [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 15, 17, 18, 19]) + @pytest.mark.parametrize("stride", [-4, -3, -2, -1, 1, 2, 3, 4]) + @pytest.mark.parametrize("astype", [np.complex64, np.complex128]) + # test to ensure masking and strides work as intended in the AVX implementation + def test_array(self, arraysize, stride, astype): + arr = np.ones(arraysize, dtype=astype) + abs_true = np.ones(arraysize, dtype=arr.real.dtype) + assert_equal(np.abs(arr[::stride]), abs_true[::stride]) + +# Testcase taken as is from https://github.com/numpy/numpy/issues/16660 +class TestComplexAbsoluteMixedDTypes: + @pytest.mark.parametrize("stride", [-4, -3, -2, -1, 1, 2, 3, 4]) + @pytest.mark.parametrize("astype", [np.complex64, np.complex128]) + @pytest.mark.parametrize("func", ['abs', 'square', 'conjugate']) + def test_array(self, stride, astype, func): + dtype = [('template_id', 'U') + uni_arr2 = str_arr.astype(' str: + if not self.build_template_path.is_file(): + raise FileNotFoundError( + errno.ENOENT, + "Meson build template" + f" {self.build_template_path.absolute()}" + " does not exist.", + ) + return self.build_template_path.read_text() + + def initialize_template(self) -> None: + self.substitutions["modulename"] = self.modulename + self.substitutions["buildtype"] = self.build_type + self.substitutions["python"] = self.python_exe + + def sources_substitution(self) -> None: + self.substitutions["source_list"] = ",\n".join( + [f"{self.indent}'''{source}'''," for source in self.sources] + ) + + def objects_substitution(self) -> None: + self.substitutions["obj_list"] = ",\n".join( + [f"{self.indent}'''{obj}'''," for obj in self.objects] + ) + + def deps_substitution(self) -> None: + self.substitutions["dep_list"] = f",\n{self.indent}".join( + [f"{self.indent}dependency('{dep}')," for dep in self.deps] + ) + + def libraries_substitution(self) -> None: + self.substitutions["lib_dir_declarations"] = "\n".join( + [ + f"lib_dir_{i} = declare_dependency(link_args : ['''-L{lib_dir}'''])" + for i, lib_dir in enumerate(self.library_dirs) + ] + ) + + self.substitutions["lib_declarations"] = "\n".join( + [ + f"{lib.replace('.', '_')} = declare_dependency(link_args : ['-l{lib}'])" + for lib in self.libraries + ] + ) + + self.substitutions["lib_list"] = f"\n{self.indent}".join( + [f"{self.indent}{lib.replace('.', '_')}," for lib in self.libraries] + ) + self.substitutions["lib_dir_list"] = f"\n{self.indent}".join( + [f"{self.indent}lib_dir_{i}," for i in range(len(self.library_dirs))] + ) + + def include_substitution(self) -> None: + self.substitutions["inc_list"] = f",\n{self.indent}".join( + [f"{self.indent}'''{inc}'''," for inc in self.include_dirs] + ) + + def fortran_args_substitution(self) -> None: + if self.fortran_args: + self.substitutions["fortran_args"] = ( + f"{self.indent}fortran_args: [{', '.join(list(self.fortran_args))}]," + ) + else: + self.substitutions["fortran_args"] = "" + + def generate_meson_build(self): + for node in self.pipeline: + node() + template = Template(self.meson_build_template()) + meson_build = template.substitute(self.substitutions) + meson_build = meson_build.replace(",,", ",") + return meson_build + + +class MesonBackend(Backend): + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + self.dependencies = self.extra_dat.get("dependencies", []) + self.meson_build_dir = "bbdir" + self.build_type = ( + "debug" if any("debug" in flag for flag in self.fc_flags) else "release" + ) + self.fc_flags = _get_flags(self.fc_flags) + + def _move_exec_to_root(self, build_dir: Path): + walk_dir = Path(build_dir) / self.meson_build_dir + path_objects = chain( + walk_dir.glob(f"{self.modulename}*.so"), + walk_dir.glob(f"{self.modulename}*.pyd"), + walk_dir.glob(f"{self.modulename}*.dll"), + ) + # Same behavior as distutils + # https://github.com/numpy/numpy/issues/24874#issuecomment-1835632293 + for path_object in path_objects: + dest_path = Path.cwd() / path_object.name + if dest_path.exists(): + dest_path.unlink() + shutil.copy2(path_object, dest_path) + os.remove(path_object) + + def write_meson_build(self, build_dir: Path) -> None: + """Writes the meson build file at specified location""" + meson_template = MesonTemplate( + self.modulename, + self.sources, + self.dependencies, + self.libraries, + self.library_dirs, + self.include_dirs, + self.extra_objects, + self.flib_flags, + self.fc_flags, + self.build_type, + sys.executable, + ) + src = meson_template.generate_meson_build() + Path(build_dir).mkdir(parents=True, exist_ok=True) + meson_build_file = Path(build_dir) / "meson.build" + meson_build_file.write_text(src) + return meson_build_file + + def _run_subprocess_command(self, command, cwd): + subprocess.run(command, cwd=cwd, check=True) + + def run_meson(self, build_dir: Path): + setup_command = ["meson", "setup", self.meson_build_dir] + self._run_subprocess_command(setup_command, build_dir) + compile_command = ["meson", "compile", "-C", self.meson_build_dir] + self._run_subprocess_command(compile_command, build_dir) + + def compile(self) -> None: + self.sources = _prepare_sources(self.modulename, self.sources, self.build_dir) + _prepare_objects(self.modulename, self.extra_objects, self.build_dir) + self.write_meson_build(self.build_dir) + self.run_meson(self.build_dir) + self._move_exec_to_root(self.build_dir) + + +def _prepare_sources(mname, sources, bdir): + extended_sources = sources.copy() + Path(bdir).mkdir(parents=True, exist_ok=True) + # Copy sources + for source in sources: + if Path(source).exists() and Path(source).is_file(): + shutil.copy(source, bdir) + generated_sources = [ + Path(f"{mname}module.c"), + Path(f"{mname}-f2pywrappers2.f90"), + Path(f"{mname}-f2pywrappers.f"), + ] + bdir = Path(bdir) + for generated_source in generated_sources: + if generated_source.exists(): + shutil.copy(generated_source, bdir / generated_source.name) + extended_sources.append(generated_source.name) + generated_source.unlink() + extended_sources = [ + Path(source).name + for source in extended_sources + if not Path(source).suffix == ".pyf" + ] + return extended_sources + +def _prepare_objects(mname, objects, bdir): + Path(bdir).mkdir(parents=True, exist_ok=True) + # Copy objects + for obj in objects: + if Path(obj).exists() and Path(obj).is_file(): + shutil.copy(obj, bdir) + +def _get_flags(fc_flags): + flag_values = [] + flag_pattern = re.compile(r"--f(77|90)flags=(.*)") + for flag in fc_flags: + match_result = flag_pattern.match(flag) + if match_result: + values = match_result.group(2).strip().split() + values = [val.strip("'\"") for val in values] + flag_values.extend(values) + # Hacky way to preserve order of flags + unique_flags = list(dict.fromkeys(flag_values)) + return unique_flags diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/_backends/_meson.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/_backends/_meson.pyi new file mode 100644 index 0000000000000000000000000000000000000000..5c85c61586fc9dee2b1fce2d6d2889e33e78ad71 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/_backends/_meson.pyi @@ -0,0 +1,62 @@ +from collections.abc import Callable +from pathlib import Path +from typing import Final, Literal as L +from typing_extensions import override + +from ._backend import Backend + +class MesonTemplate: + modulename: Final[str] + build_template_path: Final[Path] + sources: Final[list[str | Path]] + deps: Final[list[str]] + libraries: Final[list[str]] + library_dirs: Final[list[str | Path]] + include_dirs: Final[list[str | Path]] + substitutions: Final[dict[str, str]] + objects: Final[list[str | Path]] + fortran_args: Final[list[str]] + pipeline: Final[list[Callable[[], None]]] + build_type: Final[str] + python_exe: Final[str] + indent: Final[str] + + def __init__( + self, + /, + modulename: str, + sources: list[Path], + deps: list[str], + libraries: list[str], + library_dirs: list[str | Path], + include_dirs: list[str | Path], + object_files: list[str | Path], + linker_args: list[str], + fortran_args: list[str], + build_type: str, + python_exe: str, + ) -> None: ... + + # + def initialize_template(self) -> None: ... + def sources_substitution(self) -> None: ... + def objects_substitution(self) -> None: ... + def deps_substitution(self) -> None: ... + def libraries_substitution(self) -> None: ... + def include_substitution(self) -> None: ... + def fortran_args_substitution(self) -> None: ... + + # + def meson_build_template(self) -> str: ... + def generate_meson_build(self) -> str: ... + +class MesonBackend(Backend): + dependencies: list[str] + meson_build_dir: L["bdir"] + build_type: L["debug", "release"] + + def __init__(self, /, *args: object, **kwargs: object) -> None: ... + def write_meson_build(self, /, build_dir: Path) -> None: ... + def run_meson(self, /, build_dir: Path) -> None: ... + @override + def compile(self) -> None: ... diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/src/fortranobject.c b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/src/fortranobject.c new file mode 100644 index 0000000000000000000000000000000000000000..d6664d6bdfb7d013c4f3823538cd31da93a86c65 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/src/fortranobject.c @@ -0,0 +1,1436 @@ +#define FORTRANOBJECT_C +#include "fortranobject.h" + +#ifdef __cplusplus +extern "C" { +#endif + +#include +#include +#include + +/* + This file implements: FortranObject, array_from_pyobj, copy_ND_array + + Author: Pearu Peterson + $Revision: 1.52 $ + $Date: 2005/07/11 07:44:20 $ +*/ + +int +F2PyDict_SetItemString(PyObject *dict, char *name, PyObject *obj) +{ + if (obj == NULL) { + fprintf(stderr, "Error loading %s\n", name); + if (PyErr_Occurred()) { + PyErr_Print(); + PyErr_Clear(); + } + return -1; + } + return PyDict_SetItemString(dict, name, obj); +} + +/* + * Python-only fallback for thread-local callback pointers + */ +void * +F2PySwapThreadLocalCallbackPtr(char *key, void *ptr) +{ + PyObject *local_dict, *value; + void *prev; + + local_dict = PyThreadState_GetDict(); + if (local_dict == NULL) { + Py_FatalError( + "F2PySwapThreadLocalCallbackPtr: PyThreadState_GetDict " + "failed"); + } + + value = PyDict_GetItemString(local_dict, key); // noqa: borrowed-ref OK + if (value != NULL) { + prev = PyLong_AsVoidPtr(value); + if (PyErr_Occurred()) { + Py_FatalError( + "F2PySwapThreadLocalCallbackPtr: PyLong_AsVoidPtr failed"); + } + } + else { + prev = NULL; + } + + value = PyLong_FromVoidPtr((void *)ptr); + if (value == NULL) { + Py_FatalError( + "F2PySwapThreadLocalCallbackPtr: PyLong_FromVoidPtr failed"); + } + + if (PyDict_SetItemString(local_dict, key, value) != 0) { + Py_FatalError( + "F2PySwapThreadLocalCallbackPtr: PyDict_SetItemString failed"); + } + + Py_DECREF(value); + + return prev; +} + +void * +F2PyGetThreadLocalCallbackPtr(char *key) +{ + PyObject *local_dict, *value; + void *prev; + + local_dict = PyThreadState_GetDict(); + if (local_dict == NULL) { + Py_FatalError( + "F2PyGetThreadLocalCallbackPtr: PyThreadState_GetDict failed"); + } + + value = PyDict_GetItemString(local_dict, key); // noqa: borrowed-ref OK + if (value != NULL) { + prev = PyLong_AsVoidPtr(value); + if (PyErr_Occurred()) { + Py_FatalError( + "F2PyGetThreadLocalCallbackPtr: PyLong_AsVoidPtr failed"); + } + } + else { + prev = NULL; + } + + return prev; +} + +static PyArray_Descr * +get_descr_from_type_and_elsize(const int type_num, const int elsize) { + PyArray_Descr * descr = PyArray_DescrFromType(type_num); + if (type_num == NPY_STRING) { + // PyArray_DescrFromType returns descr with elsize = 0. + PyArray_DESCR_REPLACE(descr); + if (descr == NULL) { + return NULL; + } + PyDataType_SET_ELSIZE(descr, elsize); + } + return descr; +} + +/************************* FortranObject *******************************/ + +typedef PyObject *(*fortranfunc)(PyObject *, PyObject *, PyObject *, void *); + +PyObject * +PyFortranObject_New(FortranDataDef *defs, f2py_void_func init) +{ + int i; + PyFortranObject *fp = NULL; + PyObject *v = NULL; + if (init != NULL) { /* Initialize F90 module objects */ + (*(init))(); + } + fp = PyObject_New(PyFortranObject, &PyFortran_Type); + if (fp == NULL) { + return NULL; + } + if ((fp->dict = PyDict_New()) == NULL) { + Py_DECREF(fp); + return NULL; + } + fp->len = 0; + while (defs[fp->len].name != NULL) { + fp->len++; + } + if (fp->len == 0) { + goto fail; + } + fp->defs = defs; + for (i = 0; i < fp->len; i++) { + if (fp->defs[i].rank == -1) { /* Is Fortran routine */ + v = PyFortranObject_NewAsAttr(&(fp->defs[i])); + if (v == NULL) { + goto fail; + } + PyDict_SetItemString(fp->dict, fp->defs[i].name, v); + Py_XDECREF(v); + } + else if ((fp->defs[i].data) != + NULL) { /* Is Fortran variable or array (not allocatable) */ + PyArray_Descr * + descr = get_descr_from_type_and_elsize(fp->defs[i].type, + fp->defs[i].elsize); + if (descr == NULL) { + goto fail; + } + v = PyArray_NewFromDescr(&PyArray_Type, descr, fp->defs[i].rank, + fp->defs[i].dims.d, NULL, fp->defs[i].data, + NPY_ARRAY_FARRAY, NULL); + if (v == NULL) { + Py_DECREF(descr); + goto fail; + } + PyDict_SetItemString(fp->dict, fp->defs[i].name, v); + Py_XDECREF(v); + } + } + return (PyObject *)fp; +fail: + Py_XDECREF(fp); + return NULL; +} + +PyObject * +PyFortranObject_NewAsAttr(FortranDataDef *defs) +{ /* used for calling F90 module routines */ + PyFortranObject *fp = NULL; + fp = PyObject_New(PyFortranObject, &PyFortran_Type); + if (fp == NULL) + return NULL; + if ((fp->dict = PyDict_New()) == NULL) { + PyObject_Del(fp); + return NULL; + } + fp->len = 1; + fp->defs = defs; + if (defs->rank == -1) { + PyDict_SetItemString(fp->dict, "__name__", PyUnicode_FromFormat("function %s", defs->name)); + } else if (defs->rank == 0) { + PyDict_SetItemString(fp->dict, "__name__", PyUnicode_FromFormat("scalar %s", defs->name)); + } else { + PyDict_SetItemString(fp->dict, "__name__", PyUnicode_FromFormat("array %s", defs->name)); + } + return (PyObject *)fp; +} + +/* Fortran methods */ + +static void +fortran_dealloc(PyFortranObject *fp) +{ + Py_XDECREF(fp->dict); + PyObject_Del(fp); +} + +/* Returns number of bytes consumed from buf, or -1 on error. */ +static Py_ssize_t +format_def(char *buf, Py_ssize_t size, FortranDataDef def) +{ + char *p = buf; + int i; + npy_intp n; + + n = PyOS_snprintf(p, size, "array(%" NPY_INTP_FMT, def.dims.d[0]); + if (n < 0 || n >= size) { + return -1; + } + p += n; + size -= n; + + for (i = 1; i < def.rank; i++) { + n = PyOS_snprintf(p, size, ",%" NPY_INTP_FMT, def.dims.d[i]); + if (n < 0 || n >= size) { + return -1; + } + p += n; + size -= n; + } + + if (size <= 0) { + return -1; + } + + *p++ = ')'; + size--; + + if (def.data == NULL) { + static const char notalloc[] = ", not allocated"; + if ((size_t)size < sizeof(notalloc)) { + return -1; + } + memcpy(p, notalloc, sizeof(notalloc)); + p += sizeof(notalloc); + size -= sizeof(notalloc); + } + + return p - buf; +} + +static PyObject * +fortran_doc(FortranDataDef def) +{ + char *buf, *p; + PyObject *s = NULL; + Py_ssize_t n, origsize, size = 100; + + if (def.doc != NULL) { + size += strlen(def.doc); + } + origsize = size; + buf = p = (char *)PyMem_Malloc(size); + if (buf == NULL) { + return PyErr_NoMemory(); + } + + if (def.rank == -1) { + if (def.doc) { + n = strlen(def.doc); + if (n > size) { + goto fail; + } + memcpy(p, def.doc, n); + p += n; + size -= n; + } + else { + n = PyOS_snprintf(p, size, "%s - no docs available", def.name); + if (n < 0 || n >= size) { + goto fail; + } + p += n; + size -= n; + } + } + else { + PyArray_Descr *d = PyArray_DescrFromType(def.type); + n = PyOS_snprintf(p, size, "%s : '%c'-", def.name, d->type); + Py_DECREF(d); + if (n < 0 || n >= size) { + goto fail; + } + p += n; + size -= n; + + if (def.data == NULL) { + n = format_def(p, size, def); + if (n < 0) { + goto fail; + } + p += n; + size -= n; + } + else if (def.rank > 0) { + n = format_def(p, size, def); + if (n < 0) { + goto fail; + } + p += n; + size -= n; + } + else { + n = strlen("scalar"); + if (size < n) { + goto fail; + } + memcpy(p, "scalar", n); + p += n; + size -= n; + } + } + if (size <= 1) { + goto fail; + } + *p++ = '\n'; + size--; + + /* p now points one beyond the last character of the string in buf */ + s = PyUnicode_FromStringAndSize(buf, p - buf); + + PyMem_Free(buf); + return s; + +fail: + fprintf(stderr, + "fortranobject.c: fortran_doc: len(p)=%zd>%zd=size:" + " too long docstring required, increase size\n", + p - buf, origsize); + PyMem_Free(buf); + return NULL; +} + +static FortranDataDef *save_def; /* save pointer of an allocatable array */ +static void +set_data(char *d, npy_intp *f) +{ /* callback from Fortran */ + if (*f) /* In fortran f=allocated(d) */ + save_def->data = d; + else + save_def->data = NULL; + /* printf("set_data: d=%p,f=%d\n",d,*f); */ +} + +static PyObject * +fortran_getattr(PyFortranObject *fp, char *name) +{ + int i, j, k, flag; + if (fp->dict != NULL) { + // python 3.13 added PyDict_GetItemRef +#if PY_VERSION_HEX < 0x030D0000 + PyObject *v = _PyDict_GetItemStringWithError(fp->dict, name); // noqa: borrowed-ref OK + if (v == NULL && PyErr_Occurred()) { + return NULL; + } + else if (v != NULL) { + Py_INCREF(v); + return v; + } +#else + PyObject *v; + int result = PyDict_GetItemStringRef(fp->dict, name, &v); + if (result == -1) { + return NULL; + } + else if (result == 1) { + return v; + } +#endif + + } + for (i = 0, j = 1; i < fp->len && (j = strcmp(name, fp->defs[i].name)); + i++) + ; + if (j == 0) + if (fp->defs[i].rank != -1) { /* F90 allocatable array */ + if (fp->defs[i].func == NULL) + return NULL; + for (k = 0; k < fp->defs[i].rank; ++k) fp->defs[i].dims.d[k] = -1; + save_def = &fp->defs[i]; + (*(fp->defs[i].func))(&fp->defs[i].rank, fp->defs[i].dims.d, + set_data, &flag); + if (flag == 2) + k = fp->defs[i].rank + 1; + else + k = fp->defs[i].rank; + if (fp->defs[i].data != NULL) { /* array is allocated */ + PyObject *v = PyArray_New( + &PyArray_Type, k, fp->defs[i].dims.d, fp->defs[i].type, + NULL, fp->defs[i].data, 0, NPY_ARRAY_FARRAY, NULL); + if (v == NULL) + return NULL; + /* Py_INCREF(v); */ + return v; + } + else { /* array is not allocated */ + Py_RETURN_NONE; + } + } + if (strcmp(name, "__dict__") == 0) { + Py_INCREF(fp->dict); + return fp->dict; + } + if (strcmp(name, "__doc__") == 0) { + PyObject *s = PyUnicode_FromString(""), *s2, *s3; + for (i = 0; i < fp->len; i++) { + s2 = fortran_doc(fp->defs[i]); + s3 = PyUnicode_Concat(s, s2); + Py_DECREF(s2); + Py_DECREF(s); + s = s3; + } + if (PyDict_SetItemString(fp->dict, name, s)) + return NULL; + return s; + } + if ((strcmp(name, "_cpointer") == 0) && (fp->len == 1)) { + PyObject *cobj = + F2PyCapsule_FromVoidPtr((void *)(fp->defs[0].data), NULL); + if (PyDict_SetItemString(fp->dict, name, cobj)) + return NULL; + return cobj; + } + PyObject *str, *ret; + str = PyUnicode_FromString(name); + ret = PyObject_GenericGetAttr((PyObject *)fp, str); + Py_DECREF(str); + return ret; +} + +static int +fortran_setattr(PyFortranObject *fp, char *name, PyObject *v) +{ + int i, j, flag; + PyArrayObject *arr = NULL; + for (i = 0, j = 1; i < fp->len && (j = strcmp(name, fp->defs[i].name)); + i++) + ; + if (j == 0) { + if (fp->defs[i].rank == -1) { + PyErr_SetString(PyExc_AttributeError, + "over-writing fortran routine"); + return -1; + } + if (fp->defs[i].func != NULL) { /* is allocatable array */ + npy_intp dims[F2PY_MAX_DIMS]; + int k; + save_def = &fp->defs[i]; + if (v != Py_None) { /* set new value (reallocate if needed -- + see f2py generated code for more + details ) */ + for (k = 0; k < fp->defs[i].rank; k++) dims[k] = -1; + if ((arr = array_from_pyobj(fp->defs[i].type, dims, + fp->defs[i].rank, F2PY_INTENT_IN, + v)) == NULL) + return -1; + (*(fp->defs[i].func))(&fp->defs[i].rank, PyArray_DIMS(arr), + set_data, &flag); + } + else { /* deallocate */ + for (k = 0; k < fp->defs[i].rank; k++) dims[k] = 0; + (*(fp->defs[i].func))(&fp->defs[i].rank, dims, set_data, + &flag); + for (k = 0; k < fp->defs[i].rank; k++) dims[k] = -1; + } + memcpy(fp->defs[i].dims.d, dims, + fp->defs[i].rank * sizeof(npy_intp)); + } + else { /* not allocatable array */ + if ((arr = array_from_pyobj(fp->defs[i].type, fp->defs[i].dims.d, + fp->defs[i].rank, F2PY_INTENT_IN, + v)) == NULL) + return -1; + } + if (fp->defs[i].data != + NULL) { /* copy Python object to Fortran array */ + npy_intp s = PyArray_MultiplyList(fp->defs[i].dims.d, + PyArray_NDIM(arr)); + if (s == -1) + s = PyArray_MultiplyList(PyArray_DIMS(arr), PyArray_NDIM(arr)); + if (s < 0 || (memcpy(fp->defs[i].data, PyArray_DATA(arr), + s * PyArray_ITEMSIZE(arr))) == NULL) { + if ((PyObject *)arr != v) { + Py_DECREF(arr); + } + return -1; + } + if ((PyObject *)arr != v) { + Py_DECREF(arr); + } + } + else + return (fp->defs[i].func == NULL ? -1 : 0); + return 0; /* successful */ + } + if (fp->dict == NULL) { + fp->dict = PyDict_New(); + if (fp->dict == NULL) + return -1; + } + if (v == NULL) { + int rv = PyDict_DelItemString(fp->dict, name); + if (rv < 0) + PyErr_SetString(PyExc_AttributeError, + "delete non-existing fortran attribute"); + return rv; + } + else + return PyDict_SetItemString(fp->dict, name, v); +} + +static PyObject * +fortran_call(PyFortranObject *fp, PyObject *arg, PyObject *kw) +{ + int i = 0; + /* printf("fortran call + name=%s,func=%p,data=%p,%p\n",fp->defs[i].name, + fp->defs[i].func,fp->defs[i].data,&fp->defs[i].data); */ + if (fp->defs[i].rank == -1) { /* is Fortran routine */ + if (fp->defs[i].func == NULL) { + PyErr_Format(PyExc_RuntimeError, "no function to call"); + return NULL; + } + else if (fp->defs[i].data == NULL) + /* dummy routine */ + return (*((fortranfunc)(fp->defs[i].func)))((PyObject *)fp, arg, + kw, NULL); + else + return (*((fortranfunc)(fp->defs[i].func)))( + (PyObject *)fp, arg, kw, (void *)fp->defs[i].data); + } + PyErr_Format(PyExc_TypeError, "this fortran object is not callable"); + return NULL; +} + +static PyObject * +fortran_repr(PyFortranObject *fp) +{ + PyObject *name = NULL, *repr = NULL; + name = PyObject_GetAttrString((PyObject *)fp, "__name__"); + PyErr_Clear(); + if (name != NULL && PyUnicode_Check(name)) { + repr = PyUnicode_FromFormat("", name); + } + else { + repr = PyUnicode_FromString(""); + } + Py_XDECREF(name); + return repr; +} + +PyTypeObject PyFortran_Type = { + PyVarObject_HEAD_INIT(NULL, 0).tp_name = "fortran", + .tp_basicsize = sizeof(PyFortranObject), + .tp_dealloc = (destructor)fortran_dealloc, + .tp_getattr = (getattrfunc)fortran_getattr, + .tp_setattr = (setattrfunc)fortran_setattr, + .tp_repr = (reprfunc)fortran_repr, + .tp_call = (ternaryfunc)fortran_call, +}; + +/************************* f2py_report_atexit *******************************/ + +#ifdef F2PY_REPORT_ATEXIT +static int passed_time = 0; +static int passed_counter = 0; +static int passed_call_time = 0; +static struct timeb start_time; +static struct timeb stop_time; +static struct timeb start_call_time; +static struct timeb stop_call_time; +static int cb_passed_time = 0; +static int cb_passed_counter = 0; +static int cb_passed_call_time = 0; +static struct timeb cb_start_time; +static struct timeb cb_stop_time; +static struct timeb cb_start_call_time; +static struct timeb cb_stop_call_time; + +extern void +f2py_start_clock(void) +{ + ftime(&start_time); +} +extern void +f2py_start_call_clock(void) +{ + f2py_stop_clock(); + ftime(&start_call_time); +} +extern void +f2py_stop_clock(void) +{ + ftime(&stop_time); + passed_time += 1000 * (stop_time.time - start_time.time); + passed_time += stop_time.millitm - start_time.millitm; +} +extern void +f2py_stop_call_clock(void) +{ + ftime(&stop_call_time); + passed_call_time += 1000 * (stop_call_time.time - start_call_time.time); + passed_call_time += stop_call_time.millitm - start_call_time.millitm; + passed_counter += 1; + f2py_start_clock(); +} + +extern void +f2py_cb_start_clock(void) +{ + ftime(&cb_start_time); +} +extern void +f2py_cb_start_call_clock(void) +{ + f2py_cb_stop_clock(); + ftime(&cb_start_call_time); +} +extern void +f2py_cb_stop_clock(void) +{ + ftime(&cb_stop_time); + cb_passed_time += 1000 * (cb_stop_time.time - cb_start_time.time); + cb_passed_time += cb_stop_time.millitm - cb_start_time.millitm; +} +extern void +f2py_cb_stop_call_clock(void) +{ + ftime(&cb_stop_call_time); + cb_passed_call_time += + 1000 * (cb_stop_call_time.time - cb_start_call_time.time); + cb_passed_call_time += + cb_stop_call_time.millitm - cb_start_call_time.millitm; + cb_passed_counter += 1; + f2py_cb_start_clock(); +} + +static int f2py_report_on_exit_been_here = 0; +extern void +f2py_report_on_exit(int exit_flag, void *name) +{ + if (f2py_report_on_exit_been_here) { + fprintf(stderr, " %s\n", (char *)name); + return; + } + f2py_report_on_exit_been_here = 1; + fprintf(stderr, " /-----------------------\\\n"); + fprintf(stderr, " < F2PY performance report >\n"); + fprintf(stderr, " \\-----------------------/\n"); + fprintf(stderr, "Overall time spent in ...\n"); + fprintf(stderr, "(a) wrapped (Fortran/C) functions : %8d msec\n", + passed_call_time); + fprintf(stderr, "(b) f2py interface, %6d calls : %8d msec\n", + passed_counter, passed_time); + fprintf(stderr, "(c) call-back (Python) functions : %8d msec\n", + cb_passed_call_time); + fprintf(stderr, "(d) f2py call-back interface, %6d calls : %8d msec\n", + cb_passed_counter, cb_passed_time); + + fprintf(stderr, + "(e) wrapped (Fortran/C) functions (actual) : %8d msec\n\n", + passed_call_time - cb_passed_call_time - cb_passed_time); + fprintf(stderr, + "Use -DF2PY_REPORT_ATEXIT_DISABLE to disable this message.\n"); + fprintf(stderr, "Exit status: %d\n", exit_flag); + fprintf(stderr, "Modules : %s\n", (char *)name); +} +#endif + +/********************** report on array copy ****************************/ + +#ifdef F2PY_REPORT_ON_ARRAY_COPY +static void +f2py_report_on_array_copy(PyArrayObject *arr) +{ + const npy_intp arr_size = PyArray_Size((PyObject *)arr); + if (arr_size > F2PY_REPORT_ON_ARRAY_COPY) { + fprintf(stderr, + "copied an array: size=%ld, elsize=%" NPY_INTP_FMT "\n", + arr_size, (npy_intp)PyArray_ITEMSIZE(arr)); + } +} +static void +f2py_report_on_array_copy_fromany(void) +{ + fprintf(stderr, "created an array from object\n"); +} + +#define F2PY_REPORT_ON_ARRAY_COPY_FROMARR \ + f2py_report_on_array_copy((PyArrayObject *)arr) +#define F2PY_REPORT_ON_ARRAY_COPY_FROMANY f2py_report_on_array_copy_fromany() +#else +#define F2PY_REPORT_ON_ARRAY_COPY_FROMARR +#define F2PY_REPORT_ON_ARRAY_COPY_FROMANY +#endif + +/************************* array_from_obj *******************************/ + +/* + * File: array_from_pyobj.c + * + * Description: + * ------------ + * Provides array_from_pyobj function that returns a contiguous array + * object with the given dimensions and required storage order, either + * in row-major (C) or column-major (Fortran) order. The function + * array_from_pyobj is very flexible about its Python object argument + * that can be any number, list, tuple, or array. + * + * array_from_pyobj is used in f2py generated Python extension + * modules. + * + * Author: Pearu Peterson + * Created: 13-16 January 2002 + * $Id: fortranobject.c,v 1.52 2005/07/11 07:44:20 pearu Exp $ + */ + +static int check_and_fix_dimensions(const PyArrayObject* arr, + const int rank, + npy_intp *dims, + const char *errmess); + +static int +find_first_negative_dimension(const int rank, const npy_intp *dims) +{ + int i; + for (i = 0; i < rank; ++i) { + if (dims[i] < 0) { + return i; + } + } + return -1; +} + +#ifdef DEBUG_COPY_ND_ARRAY +void +dump_dims(int rank, npy_intp const *dims) +{ + int i; + printf("["); + for (i = 0; i < rank; ++i) { + printf("%3" NPY_INTP_FMT, dims[i]); + } + printf("]\n"); +} +void +dump_attrs(const PyArrayObject *obj) +{ + const PyArrayObject_fields *arr = (const PyArrayObject_fields *)obj; + int rank = PyArray_NDIM(arr); + npy_intp size = PyArray_Size((PyObject *)arr); + printf("\trank = %d, flags = %d, size = %" NPY_INTP_FMT "\n", rank, + arr->flags, size); + printf("\tstrides = "); + dump_dims(rank, arr->strides); + printf("\tdimensions = "); + dump_dims(rank, arr->dimensions); +} +#endif + +#define SWAPTYPE(a, b, t) \ + { \ + t c; \ + c = (a); \ + (a) = (b); \ + (b) = c; \ + } + +static int +swap_arrays(PyArrayObject *obj1, PyArrayObject *obj2) +{ + PyArrayObject_fields *arr1 = (PyArrayObject_fields *)obj1, + *arr2 = (PyArrayObject_fields *)obj2; + SWAPTYPE(arr1->data, arr2->data, char *); + SWAPTYPE(arr1->nd, arr2->nd, int); + SWAPTYPE(arr1->dimensions, arr2->dimensions, npy_intp *); + SWAPTYPE(arr1->strides, arr2->strides, npy_intp *); + SWAPTYPE(arr1->base, arr2->base, PyObject *); + SWAPTYPE(arr1->descr, arr2->descr, PyArray_Descr *); + SWAPTYPE(arr1->flags, arr2->flags, int); + /* SWAPTYPE(arr1->weakreflist,arr2->weakreflist,PyObject*); */ + return 0; +} + +#define ARRAY_ISCOMPATIBLE(arr,type_num) \ + ((PyArray_ISINTEGER(arr) && PyTypeNum_ISINTEGER(type_num)) || \ + (PyArray_ISFLOAT(arr) && PyTypeNum_ISFLOAT(type_num)) || \ + (PyArray_ISCOMPLEX(arr) && PyTypeNum_ISCOMPLEX(type_num)) || \ + (PyArray_ISBOOL(arr) && PyTypeNum_ISBOOL(type_num)) || \ + (PyArray_ISSTRING(arr) && PyTypeNum_ISSTRING(type_num))) + +static int +get_elsize(PyObject *obj) { + /* + get_elsize determines array itemsize from a Python object. Returns + elsize if successful, -1 otherwise. + + Supported types of the input are: numpy.ndarray, bytes, str, tuple, + list. + */ + + if (PyArray_Check(obj)) { + return PyArray_ITEMSIZE((PyArrayObject *)obj); + } else if (PyBytes_Check(obj)) { + return PyBytes_GET_SIZE(obj); + } else if (PyUnicode_Check(obj)) { + return PyUnicode_GET_LENGTH(obj); + } else if (PySequence_Check(obj)) { + PyObject* fast = PySequence_Fast(obj, "f2py:fortranobject.c:get_elsize"); // noqa: borrowed-ref OK + if (fast != NULL) { + Py_ssize_t i, n = PySequence_Fast_GET_SIZE(fast); + int sz, elsize = 0; + for (i=0; i elsize) { + elsize = sz; + } + } + Py_DECREF(fast); + return elsize; + } + } + return -1; +} + +extern PyArrayObject * +ndarray_from_pyobj(const int type_num, + const int elsize_, + npy_intp *dims, + const int rank, + const int intent, + PyObject *obj, + const char *errmess) { + /* + * Return an array with given element type and shape from a Python + * object while taking into account the usage intent of the array. + * + * - element type is defined by type_num and elsize + * - shape is defined by dims and rank + * + * ndarray_from_pyobj is used to convert Python object arguments + * to numpy ndarrays with given type and shape that data is passed + * to interfaced Fortran or C functions. + * + * errmess (if not NULL), contains a prefix of an error message + * for an exception to be triggered within this function. + * + * Negative elsize value means that elsize is to be determined + * from the Python object in runtime. + * + * Note on strings + * --------------- + * + * String type (type_num == NPY_STRING) does not have fixed + * element size and, by default, the type object sets it to + * 0. Therefore, for string types, one has to use elsize + * argument. For other types, elsize value is ignored. + * + * NumPy defines the type of a fixed-width string as + * dtype('S'). In addition, there is also dtype('c'), that + * appears as dtype('S1') (these have the same type_num value), + * but is actually different (.char attribute is either 'S' or + * 'c', respectively). + * + * In Fortran, character arrays and strings are different + * concepts. The relation between Fortran types, NumPy dtypes, + * and type_num-elsize pairs, is defined as follows: + * + * character*5 foo | dtype('S5') | elsize=5, shape=() + * character(5) foo | dtype('S1') | elsize=1, shape=(5) + * character*5 foo(n) | dtype('S5') | elsize=5, shape=(n,) + * character(5) foo(n) | dtype('S1') | elsize=1, shape=(5, n) + * character*(*) foo | dtype('S') | elsize=-1, shape=() + * + * Note about reference counting + * ----------------------------- + * + * If the caller returns the array to Python, it must be done with + * Py_BuildValue("N",arr). Otherwise, if obj!=arr then the caller + * must call Py_DECREF(arr). + * + * Note on intent(cache,out,..) + * ---------------------------- + * Don't expect correct data when returning intent(cache) array. + * + */ + char mess[F2PY_MESSAGE_BUFFER_SIZE]; + PyArrayObject *arr = NULL; + int elsize = (elsize_ < 0 ? get_elsize(obj) : elsize_); + if (elsize < 0) { + if (errmess != NULL) { + strcpy(mess, errmess); + } + sprintf(mess + strlen(mess), + " -- failed to determine element size from %s", + Py_TYPE(obj)->tp_name); + PyErr_SetString(PyExc_SystemError, mess); + return NULL; + } + PyArray_Descr * descr = get_descr_from_type_and_elsize(type_num, elsize); // new reference + if (descr == NULL) { + return NULL; + } + elsize = PyDataType_ELSIZE(descr); + if ((intent & F2PY_INTENT_HIDE) + || ((intent & F2PY_INTENT_CACHE) && (obj == Py_None)) + || ((intent & F2PY_OPTIONAL) && (obj == Py_None)) + ) { + /* intent(cache), optional, intent(hide) */ + int ineg = find_first_negative_dimension(rank, dims); + if (ineg >= 0) { + int i; + strcpy(mess, "failed to create intent(cache|hide)|optional array" + "-- must have defined dimensions but got ("); + for(i = 0; i < rank; ++i) + sprintf(mess + strlen(mess), "%" NPY_INTP_FMT ",", dims[i]); + strcat(mess, ")"); + PyErr_SetString(PyExc_ValueError, mess); + Py_DECREF(descr); + return NULL; + } + arr = (PyArrayObject *) \ + PyArray_NewFromDescr(&PyArray_Type, descr, rank, dims, + NULL, NULL, !(intent & F2PY_INTENT_C), NULL); + if (arr == NULL) { + Py_DECREF(descr); + return NULL; + } + if (PyArray_ITEMSIZE(arr) != elsize) { + strcpy(mess, "failed to create intent(cache|hide)|optional array"); + sprintf(mess+strlen(mess)," -- expected elsize=%d got %" NPY_INTP_FMT, elsize, (npy_intp)PyArray_ITEMSIZE(arr)); + PyErr_SetString(PyExc_ValueError,mess); + Py_DECREF(arr); + return NULL; + } + if (!(intent & F2PY_INTENT_CACHE)) { + PyArray_FILLWBYTE(arr, 0); + } + return arr; + } + + if (PyArray_Check(obj)) { + arr = (PyArrayObject *)obj; + if (intent & F2PY_INTENT_CACHE) { + /* intent(cache) */ + if (PyArray_ISONESEGMENT(arr) + && PyArray_ITEMSIZE(arr) >= elsize) { + if (check_and_fix_dimensions(arr, rank, dims, errmess)) { + Py_DECREF(descr); + return NULL; + } + if (intent & F2PY_INTENT_OUT) + Py_INCREF(arr); + Py_DECREF(descr); + return arr; + } + strcpy(mess, "failed to initialize intent(cache) array"); + if (!PyArray_ISONESEGMENT(arr)) + strcat(mess, " -- input must be in one segment"); + if (PyArray_ITEMSIZE(arr) < elsize) + sprintf(mess + strlen(mess), + " -- expected at least elsize=%d but got " + "%" NPY_INTP_FMT, + elsize, (npy_intp)PyArray_ITEMSIZE(arr)); + PyErr_SetString(PyExc_ValueError, mess); + Py_DECREF(descr); + return NULL; + } + + /* here we have always intent(in) or intent(inout) or intent(inplace) + */ + + if (check_and_fix_dimensions(arr, rank, dims, errmess)) { + Py_DECREF(descr); + return NULL; + } + /* + printf("intent alignment=%d\n", F2PY_GET_ALIGNMENT(intent)); + printf("alignment check=%d\n", F2PY_CHECK_ALIGNMENT(arr, intent)); + int i; + for (i=1;i<=16;i++) + printf("i=%d isaligned=%d\n", i, ARRAY_ISALIGNED(arr, i)); + */ + if ((! (intent & F2PY_INTENT_COPY)) && + PyArray_ITEMSIZE(arr) == elsize && + ARRAY_ISCOMPATIBLE(arr,type_num) && + F2PY_CHECK_ALIGNMENT(arr, intent)) { + if ((intent & F2PY_INTENT_INOUT || intent & F2PY_INTENT_INPLACE) + ? ((intent & F2PY_INTENT_C) ? PyArray_ISCARRAY(arr) : PyArray_ISFARRAY(arr)) + : ((intent & F2PY_INTENT_C) ? PyArray_ISCARRAY_RO(arr) : PyArray_ISFARRAY_RO(arr))) { + if ((intent & F2PY_INTENT_OUT)) { + Py_INCREF(arr); + } + /* Returning input array */ + Py_DECREF(descr); + return arr; + } + } + if (intent & F2PY_INTENT_INOUT) { + strcpy(mess, "failed to initialize intent(inout) array"); + /* Must use PyArray_IS*ARRAY because intent(inout) requires + * writable input */ + if ((intent & F2PY_INTENT_C) && !PyArray_ISCARRAY(arr)) + strcat(mess, " -- input not contiguous"); + if (!(intent & F2PY_INTENT_C) && !PyArray_ISFARRAY(arr)) + strcat(mess, " -- input not fortran contiguous"); + if (PyArray_ITEMSIZE(arr) != elsize) + sprintf(mess + strlen(mess), + " -- expected elsize=%d but got %" NPY_INTP_FMT, + elsize, + (npy_intp)PyArray_ITEMSIZE(arr) + ); + if (!(ARRAY_ISCOMPATIBLE(arr, type_num))) { + sprintf(mess + strlen(mess), + " -- input '%c' not compatible to '%c'", + PyArray_DESCR(arr)->type, descr->type); + } + if (!(F2PY_CHECK_ALIGNMENT(arr, intent))) + sprintf(mess + strlen(mess), " -- input not %d-aligned", + F2PY_GET_ALIGNMENT(intent)); + PyErr_SetString(PyExc_ValueError, mess); + Py_DECREF(descr); + return NULL; + } + + /* here we have always intent(in) or intent(inplace) */ + + { + PyArrayObject * retarr = (PyArrayObject *) \ + PyArray_NewFromDescr(&PyArray_Type, descr, PyArray_NDIM(arr), PyArray_DIMS(arr), + NULL, NULL, !(intent & F2PY_INTENT_C), NULL); + if (retarr==NULL) { + Py_DECREF(descr); + return NULL; + } + F2PY_REPORT_ON_ARRAY_COPY_FROMARR; + if (PyArray_CopyInto(retarr, arr)) { + Py_DECREF(retarr); + return NULL; + } + if (intent & F2PY_INTENT_INPLACE) { + if (swap_arrays(arr,retarr)) { + Py_DECREF(retarr); + return NULL; /* XXX: set exception */ + } + Py_XDECREF(retarr); + if (intent & F2PY_INTENT_OUT) + Py_INCREF(arr); + } else { + arr = retarr; + } + } + return arr; + } + + if ((intent & F2PY_INTENT_INOUT) || (intent & F2PY_INTENT_INPLACE) || + (intent & F2PY_INTENT_CACHE)) { + PyErr_Format(PyExc_TypeError, + "failed to initialize intent(inout|inplace|cache) " + "array, input '%s' object is not an array", + Py_TYPE(obj)->tp_name); + Py_DECREF(descr); + return NULL; + } + + { + F2PY_REPORT_ON_ARRAY_COPY_FROMANY; + arr = (PyArrayObject *)PyArray_FromAny( + obj, descr, 0, 0, + ((intent & F2PY_INTENT_C) ? NPY_ARRAY_CARRAY + : NPY_ARRAY_FARRAY) | + NPY_ARRAY_FORCECAST, + NULL); + // Warning: in the case of NPY_STRING, PyArray_FromAny may + // reset descr->elsize, e.g. dtype('S0') becomes dtype('S1'). + if (arr == NULL) { + Py_DECREF(descr); + return NULL; + } + if (type_num != NPY_STRING && PyArray_ITEMSIZE(arr) != elsize) { + // This is internal sanity tests: elsize has been set to + // descr->elsize in the beginning of this function. + strcpy(mess, "failed to initialize intent(in) array"); + sprintf(mess + strlen(mess), + " -- expected elsize=%d got %" NPY_INTP_FMT, elsize, + (npy_intp)PyArray_ITEMSIZE(arr)); + PyErr_SetString(PyExc_ValueError, mess); + Py_DECREF(arr); + return NULL; + } + if (check_and_fix_dimensions(arr, rank, dims, errmess)) { + Py_DECREF(arr); + return NULL; + } + return arr; + } +} + +extern PyArrayObject * +array_from_pyobj(const int type_num, + npy_intp *dims, + const int rank, + const int intent, + PyObject *obj) { + /* + Same as ndarray_from_pyobj but with elsize determined from type, + if possible. Provided for backward compatibility. + */ + PyArray_Descr* descr = PyArray_DescrFromType(type_num); + int elsize = PyDataType_ELSIZE(descr); + Py_DECREF(descr); + return ndarray_from_pyobj(type_num, elsize, dims, rank, intent, obj, NULL); +} + +/*****************************************/ +/* Helper functions for array_from_pyobj */ +/*****************************************/ + +static int +check_and_fix_dimensions(const PyArrayObject* arr, const int rank, + npy_intp *dims, const char *errmess) +{ + /* + * This function fills in blanks (that are -1's) in dims list using + * the dimensions from arr. It also checks that non-blank dims will + * match with the corresponding values in arr dimensions. + * + * Returns 0 if the function is successful. + * + * If an error condition is detected, an exception is set and 1 is + * returned. + */ + char mess[F2PY_MESSAGE_BUFFER_SIZE]; + const npy_intp arr_size = + (PyArray_NDIM(arr)) ? PyArray_Size((PyObject *)arr) : 1; +#ifdef DEBUG_COPY_ND_ARRAY + dump_attrs(arr); + printf("check_and_fix_dimensions:init: dims="); + dump_dims(rank, dims); +#endif + if (rank > PyArray_NDIM(arr)) { /* [1,2] -> [[1],[2]]; 1 -> [[1]] */ + npy_intp new_size = 1; + int free_axe = -1; + int i; + npy_intp d; + /* Fill dims where -1 or 0; check dimensions; calc new_size; */ + for (i = 0; i < PyArray_NDIM(arr); ++i) { + d = PyArray_DIM(arr, i); + if (dims[i] >= 0) { + if (d > 1 && dims[i] != d) { + PyErr_Format( + PyExc_ValueError, + "%d-th dimension must be fixed to %" NPY_INTP_FMT + " but got %" NPY_INTP_FMT "\n", + i, dims[i], d); + return 1; + } + if (!dims[i]) + dims[i] = 1; + } + else { + dims[i] = d ? d : 1; + } + new_size *= dims[i]; + } + for (i = PyArray_NDIM(arr); i < rank; ++i) + if (dims[i] > 1) { + PyErr_Format(PyExc_ValueError, + "%d-th dimension must be %" NPY_INTP_FMT + " but got 0 (not defined).\n", + i, dims[i]); + return 1; + } + else if (free_axe < 0) + free_axe = i; + else + dims[i] = 1; + if (free_axe >= 0) { + dims[free_axe] = arr_size / new_size; + new_size *= dims[free_axe]; + } + if (new_size != arr_size) { + PyErr_Format(PyExc_ValueError, + "unexpected array size: new_size=%" NPY_INTP_FMT + ", got array with arr_size=%" NPY_INTP_FMT + " (maybe too many free indices)\n", + new_size, arr_size); + return 1; + } + } + else if (rank == PyArray_NDIM(arr)) { + npy_intp new_size = 1; + int i; + npy_intp d; + for (i = 0; i < rank; ++i) { + d = PyArray_DIM(arr, i); + if (dims[i] >= 0) { + if (d > 1 && d != dims[i]) { + if (errmess != NULL) { + strcpy(mess, errmess); + } + sprintf(mess + strlen(mess), + " -- %d-th dimension must be fixed to %" + NPY_INTP_FMT " but got %" NPY_INTP_FMT, + i, dims[i], d); + PyErr_SetString(PyExc_ValueError, mess); + return 1; + } + if (!dims[i]) + dims[i] = 1; + } + else + dims[i] = d; + new_size *= dims[i]; + } + if (new_size != arr_size) { + PyErr_Format(PyExc_ValueError, + "unexpected array size: new_size=%" NPY_INTP_FMT + ", got array with arr_size=%" NPY_INTP_FMT "\n", + new_size, arr_size); + return 1; + } + } + else { /* [[1,2]] -> [[1],[2]] */ + int i, j; + npy_intp d; + int effrank; + npy_intp size; + for (i = 0, effrank = 0; i < PyArray_NDIM(arr); ++i) + if (PyArray_DIM(arr, i) > 1) + ++effrank; + if (dims[rank - 1] >= 0) + if (effrank > rank) { + PyErr_Format(PyExc_ValueError, + "too many axes: %d (effrank=%d), " + "expected rank=%d\n", + PyArray_NDIM(arr), effrank, rank); + return 1; + } + + for (i = 0, j = 0; i < rank; ++i) { + while (j < PyArray_NDIM(arr) && PyArray_DIM(arr, j) < 2) ++j; + if (j >= PyArray_NDIM(arr)) + d = 1; + else + d = PyArray_DIM(arr, j++); + if (dims[i] >= 0) { + if (d > 1 && d != dims[i]) { + if (errmess != NULL) { + strcpy(mess, errmess); + } + sprintf(mess + strlen(mess), + " -- %d-th dimension must be fixed to %" + NPY_INTP_FMT " but got %" NPY_INTP_FMT + " (real index=%d)\n", + i, dims[i], d, j-1); + PyErr_SetString(PyExc_ValueError, mess); + return 1; + } + if (!dims[i]) + dims[i] = 1; + } + else + dims[i] = d; + } + + for (i = rank; i < PyArray_NDIM(arr); + ++i) { /* [[1,2],[3,4]] -> [1,2,3,4] */ + while (j < PyArray_NDIM(arr) && PyArray_DIM(arr, j) < 2) ++j; + if (j >= PyArray_NDIM(arr)) + d = 1; + else + d = PyArray_DIM(arr, j++); + dims[rank - 1] *= d; + } + for (i = 0, size = 1; i < rank; ++i) size *= dims[i]; + if (size != arr_size) { + char msg[200]; + int len; + snprintf(msg, sizeof(msg), + "unexpected array size: size=%" NPY_INTP_FMT + ", arr_size=%" NPY_INTP_FMT + ", rank=%d, effrank=%d, arr.nd=%d, dims=[", + size, arr_size, rank, effrank, PyArray_NDIM(arr)); + for (i = 0; i < rank; ++i) { + len = strlen(msg); + snprintf(msg + len, sizeof(msg) - len, " %" NPY_INTP_FMT, + dims[i]); + } + len = strlen(msg); + snprintf(msg + len, sizeof(msg) - len, " ], arr.dims=["); + for (i = 0; i < PyArray_NDIM(arr); ++i) { + len = strlen(msg); + snprintf(msg + len, sizeof(msg) - len, " %" NPY_INTP_FMT, + PyArray_DIM(arr, i)); + } + len = strlen(msg); + snprintf(msg + len, sizeof(msg) - len, " ]\n"); + PyErr_SetString(PyExc_ValueError, msg); + return 1; + } + } +#ifdef DEBUG_COPY_ND_ARRAY + printf("check_and_fix_dimensions:end: dims="); + dump_dims(rank, dims); +#endif + return 0; +} + +/* End of file: array_from_pyobj.c */ + +/************************* copy_ND_array *******************************/ + +extern int +copy_ND_array(const PyArrayObject *arr, PyArrayObject *out) +{ + F2PY_REPORT_ON_ARRAY_COPY_FROMARR; + return PyArray_CopyInto(out, (PyArrayObject *)arr); +} + +/********************* Various utility functions ***********************/ + +extern int +f2py_describe(PyObject *obj, char *buf) { + /* + Write the description of a Python object to buf. The caller must + provide buffer with size sufficient to write the description. + + Return 1 on success. + */ + char localbuf[F2PY_MESSAGE_BUFFER_SIZE]; + if (PyBytes_Check(obj)) { + sprintf(localbuf, "%d-%s", (npy_int)PyBytes_GET_SIZE(obj), Py_TYPE(obj)->tp_name); + } else if (PyUnicode_Check(obj)) { + sprintf(localbuf, "%d-%s", (npy_int)PyUnicode_GET_LENGTH(obj), Py_TYPE(obj)->tp_name); + } else if (PyArray_CheckScalar(obj)) { + PyArrayObject* arr = (PyArrayObject*)obj; + sprintf(localbuf, "%c%" NPY_INTP_FMT "-%s-scalar", PyArray_DESCR(arr)->kind, PyArray_ITEMSIZE(arr), Py_TYPE(obj)->tp_name); + } else if (PyArray_Check(obj)) { + int i; + PyArrayObject* arr = (PyArrayObject*)obj; + strcpy(localbuf, "("); + for (i=0; ikind, PyArray_ITEMSIZE(arr), Py_TYPE(obj)->tp_name); + } else if (PySequence_Check(obj)) { + sprintf(localbuf, "%d-%s", (npy_int)PySequence_Length(obj), Py_TYPE(obj)->tp_name); + } else { + sprintf(localbuf, "%s instance", Py_TYPE(obj)->tp_name); + } + // TODO: detect the size of buf and make sure that size(buf) >= size(localbuf). + strcpy(buf, localbuf); + return 1; +} + +extern npy_intp +f2py_size_impl(PyArrayObject* var, ...) +{ + npy_intp sz = 0; + npy_intp dim; + npy_intp rank; + va_list argp; + va_start(argp, var); + dim = va_arg(argp, npy_int); + if (dim==-1) + { + sz = PyArray_SIZE(var); + } + else + { + rank = PyArray_NDIM(var); + if (dim>=1 && dim<=rank) + sz = PyArray_DIM(var, dim-1); + else + fprintf(stderr, "f2py_size: 2nd argument value=%" NPY_INTP_FMT + " fails to satisfy 1<=value<=%" NPY_INTP_FMT + ". Result will be 0.\n", dim, rank); + } + va_end(argp); + return sz; +} + +/*********************************************/ +/* Compatibility functions for Python >= 3.0 */ +/*********************************************/ + +PyObject * +F2PyCapsule_FromVoidPtr(void *ptr, void (*dtor)(PyObject *)) +{ + PyObject *ret = PyCapsule_New(ptr, NULL, dtor); + if (ret == NULL) { + PyErr_Clear(); + } + return ret; +} + +void * +F2PyCapsule_AsVoidPtr(PyObject *obj) +{ + void *ret = PyCapsule_GetPointer(obj, NULL); + if (ret == NULL) { + PyErr_Clear(); + } + return ret; +} + +int +F2PyCapsule_Check(PyObject *ptr) +{ + return PyCapsule_CheckExact(ptr); +} + +#ifdef __cplusplus +} +#endif +/************************* EOF fortranobject.c *******************************/ diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/src/fortranobject.h b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/src/fortranobject.h new file mode 100644 index 0000000000000000000000000000000000000000..4aed2f60891b9e9ea2c16373b5959b0a346e7470 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/src/fortranobject.h @@ -0,0 +1,173 @@ +#ifndef Py_FORTRANOBJECT_H +#define Py_FORTRANOBJECT_H +#ifdef __cplusplus +extern "C" { +#endif + +#include + +#ifndef NPY_NO_DEPRECATED_API +#define NPY_NO_DEPRECATED_API NPY_API_VERSION +#endif +#ifdef FORTRANOBJECT_C +#define NO_IMPORT_ARRAY +#endif +#define PY_ARRAY_UNIQUE_SYMBOL _npy_f2py_ARRAY_API +#include "numpy/arrayobject.h" +#include "numpy/npy_3kcompat.h" + +#ifdef F2PY_REPORT_ATEXIT +#include +// clang-format off +extern void f2py_start_clock(void); +extern void f2py_stop_clock(void); +extern void f2py_start_call_clock(void); +extern void f2py_stop_call_clock(void); +extern void f2py_cb_start_clock(void); +extern void f2py_cb_stop_clock(void); +extern void f2py_cb_start_call_clock(void); +extern void f2py_cb_stop_call_clock(void); +extern void f2py_report_on_exit(int, void *); +// clang-format on +#endif + +#ifdef DMALLOC +#include "dmalloc.h" +#endif + +/* Fortran object interface */ + +/* +123456789-123456789-123456789-123456789-123456789-123456789-123456789-12 + +PyFortranObject represents various Fortran objects: +Fortran (module) routines, COMMON blocks, module data. + +Author: Pearu Peterson +*/ + +#define F2PY_MAX_DIMS 40 +#define F2PY_MESSAGE_BUFFER_SIZE 300 // Increase on "stack smashing detected" + +typedef void (*f2py_set_data_func)(char *, npy_intp *); +typedef void (*f2py_void_func)(void); +typedef void (*f2py_init_func)(int *, npy_intp *, f2py_set_data_func, int *); + +/*typedef void* (*f2py_c_func)(void*,...);*/ + +typedef void *(*f2pycfunc)(void); + +typedef struct { + char *name; /* attribute (array||routine) name */ + int rank; /* array rank, 0 for scalar, max is F2PY_MAX_DIMS, + || rank=-1 for Fortran routine */ + struct { + npy_intp d[F2PY_MAX_DIMS]; + } dims; /* dimensions of the array, || not used */ + int type; /* PyArray_ || not used */ + int elsize; /* Element size || not used */ + char *data; /* pointer to array || Fortran routine */ + f2py_init_func func; /* initialization function for + allocatable arrays: + func(&rank,dims,set_ptr_func,name,len(name)) + || C/API wrapper for Fortran routine */ + char *doc; /* documentation string; only recommended + for routines. */ +} FortranDataDef; + +typedef struct { + PyObject_HEAD + int len; /* Number of attributes */ + FortranDataDef *defs; /* An array of FortranDataDef's */ + PyObject *dict; /* Fortran object attribute dictionary */ +} PyFortranObject; + +#define PyFortran_Check(op) (Py_TYPE(op) == &PyFortran_Type) +#define PyFortran_Check1(op) (0 == strcmp(Py_TYPE(op)->tp_name, "fortran")) + +extern PyTypeObject PyFortran_Type; +extern int +F2PyDict_SetItemString(PyObject *dict, char *name, PyObject *obj); +extern PyObject * +PyFortranObject_New(FortranDataDef *defs, f2py_void_func init); +extern PyObject * +PyFortranObject_NewAsAttr(FortranDataDef *defs); + +PyObject * +F2PyCapsule_FromVoidPtr(void *ptr, void (*dtor)(PyObject *)); +void * +F2PyCapsule_AsVoidPtr(PyObject *obj); +int +F2PyCapsule_Check(PyObject *ptr); + +extern void * +F2PySwapThreadLocalCallbackPtr(char *key, void *ptr); +extern void * +F2PyGetThreadLocalCallbackPtr(char *key); + +#define ISCONTIGUOUS(m) (PyArray_FLAGS(m) & NPY_ARRAY_C_CONTIGUOUS) +#define F2PY_INTENT_IN 1 +#define F2PY_INTENT_INOUT 2 +#define F2PY_INTENT_OUT 4 +#define F2PY_INTENT_HIDE 8 +#define F2PY_INTENT_CACHE 16 +#define F2PY_INTENT_COPY 32 +#define F2PY_INTENT_C 64 +#define F2PY_OPTIONAL 128 +#define F2PY_INTENT_INPLACE 256 +#define F2PY_INTENT_ALIGNED4 512 +#define F2PY_INTENT_ALIGNED8 1024 +#define F2PY_INTENT_ALIGNED16 2048 + +#define ARRAY_ISALIGNED(ARR, SIZE) ((size_t)(PyArray_DATA(ARR)) % (SIZE) == 0) +#define F2PY_ALIGN4(intent) (intent & F2PY_INTENT_ALIGNED4) +#define F2PY_ALIGN8(intent) (intent & F2PY_INTENT_ALIGNED8) +#define F2PY_ALIGN16(intent) (intent & F2PY_INTENT_ALIGNED16) + +#define F2PY_GET_ALIGNMENT(intent) \ + (F2PY_ALIGN4(intent) \ + ? 4 \ + : (F2PY_ALIGN8(intent) ? 8 : (F2PY_ALIGN16(intent) ? 16 : 1))) +#define F2PY_CHECK_ALIGNMENT(arr, intent) \ + ARRAY_ISALIGNED(arr, F2PY_GET_ALIGNMENT(intent)) +#define F2PY_ARRAY_IS_CHARACTER_COMPATIBLE(arr) ((PyArray_DESCR(arr)->type_num == NPY_STRING && PyArray_ITEMSIZE(arr) >= 1) \ + || PyArray_DESCR(arr)->type_num == NPY_UINT8) +#define F2PY_IS_UNICODE_ARRAY(arr) (PyArray_DESCR(arr)->type_num == NPY_UNICODE) + +extern PyArrayObject * +ndarray_from_pyobj(const int type_num, const int elsize_, npy_intp *dims, + const int rank, const int intent, PyObject *obj, + const char *errmess); + +extern PyArrayObject * +array_from_pyobj(const int type_num, npy_intp *dims, const int rank, + const int intent, PyObject *obj); +extern int +copy_ND_array(const PyArrayObject *in, PyArrayObject *out); + +#ifdef DEBUG_COPY_ND_ARRAY +extern void +dump_attrs(const PyArrayObject *arr); +#endif + + extern int f2py_describe(PyObject *obj, char *buf); + + /* Utility CPP macros and functions that can be used in signature file + expressions. See signature-file.rst for documentation. + */ + +#define f2py_itemsize(var) (PyArray_ITEMSIZE(capi_ ## var ## _as_array)) +#define f2py_size(var, ...) f2py_size_impl((PyArrayObject *)(capi_ ## var ## _as_array), ## __VA_ARGS__, -1) +#define f2py_rank(var) var ## _Rank +#define f2py_shape(var,dim) var ## _Dims[dim] +#define f2py_len(var) f2py_shape(var,0) +#define f2py_fshape(var,dim) f2py_shape(var,rank(var)-dim-1) +#define f2py_flen(var) f2py_fshape(var,0) +#define f2py_slen(var) capi_ ## var ## _len + + extern npy_intp f2py_size_impl(PyArrayObject* var, ...); + +#ifdef __cplusplus +} +#endif +#endif /* !Py_FORTRANOBJECT_H */ diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/__init__.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..4ed8fdd53f8c7e2651269830cedfee4173cd46d7 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/__init__.py @@ -0,0 +1,16 @@ +import pytest + +from numpy.testing import IS_EDITABLE, IS_WASM + +if IS_WASM: + pytest.skip( + "WASM/Pyodide does not use or support Fortran", + allow_module_level=True + ) + + +if IS_EDITABLE: + pytest.skip( + "Editable install doesn't support tests with a compile step", + allow_module_level=True + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/__pycache__/__init__.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..c9f035867e2b33bf589f54a6145dddbb81430e25 Binary files /dev/null and b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/__pycache__/__init__.cpython-312.pyc differ diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/__pycache__/test_abstract_interface.cpython-312.pyc 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new file mode 100644 index 0000000000000000000000000000000000000000..76d16aae2b57160228f41c00128ac0067eaf5249 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/abstract_interface/foo.f90 @@ -0,0 +1,34 @@ +module ops_module + + abstract interface + subroutine op(x, y, z) + integer, intent(in) :: x, y + integer, intent(out) :: z + end subroutine + end interface + +contains + + subroutine foo(x, y, r1, r2) + integer, intent(in) :: x, y + integer, intent(out) :: r1, r2 + procedure (op) add1, add2 + procedure (op), pointer::p + p=>add1 + call p(x, y, r1) + p=>add2 + call p(x, y, r2) + end subroutine +end module + +subroutine add1(x, y, z) + integer, intent(in) :: x, y + integer, intent(out) :: z + z = x + y +end subroutine + +subroutine add2(x, y, z) + integer, intent(in) :: x, y + integer, intent(out) :: z + z = x + 2 * y +end subroutine diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/abstract_interface/gh18403_mod.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/abstract_interface/gh18403_mod.f90 new file mode 100644 index 0000000000000000000000000000000000000000..36791e469f5aee1d5fe15b121abeb9c62a45fadf --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/abstract_interface/gh18403_mod.f90 @@ -0,0 +1,6 @@ +module test + abstract interface + subroutine foo() + end subroutine + end interface +end module test diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/array_from_pyobj/wrapmodule.c b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/array_from_pyobj/wrapmodule.c new file mode 100644 index 0000000000000000000000000000000000000000..25866f1a40ece3cf8b761f2125c948916e5e2661 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/array_from_pyobj/wrapmodule.c @@ -0,0 +1,235 @@ +/* + * This file was auto-generated with f2py (version:2_1330) and hand edited by + * Pearu for testing purposes. Do not edit this file unless you know what you + * are doing!!! + */ + +#ifdef __cplusplus +extern "C" { +#endif + +/*********************** See f2py2e/cfuncs.py: includes ***********************/ + +#define PY_SSIZE_T_CLEAN +#include +#include "fortranobject.h" +#include + +static PyObject *wrap_error; +static PyObject *wrap_module; + +/************************************ call ************************************/ +static char doc_f2py_rout_wrap_call[] = "\ +Function signature:\n\ + arr = call(type_num,dims,intent,obj)\n\ +Required arguments:\n" +" type_num : input int\n" +" dims : input int-sequence\n" +" intent : input int\n" +" obj : input python object\n" +"Return objects:\n" +" arr : array"; +static PyObject *f2py_rout_wrap_call(PyObject *capi_self, + PyObject *capi_args) { + PyObject * volatile capi_buildvalue = NULL; + int type_num = 0; + int elsize = 0; + npy_intp *dims = NULL; + PyObject *dims_capi = Py_None; + int rank = 0; + int intent = 0; + PyArrayObject *capi_arr_tmp = NULL; + PyObject *arr_capi = Py_None; + int i; + + if (!PyArg_ParseTuple(capi_args,"iiOiO|:wrap.call",\ + &type_num,&elsize,&dims_capi,&intent,&arr_capi)) + return NULL; + rank = PySequence_Length(dims_capi); + dims = malloc(rank*sizeof(npy_intp)); + for (i=0;ikind, + PyArray_DESCR(arr)->type, + PyArray_TYPE(arr), + PyArray_ITEMSIZE(arr), + PyDataType_ALIGNMENT(PyArray_DESCR(arr)), + PyArray_FLAGS(arr), + PyArray_ITEMSIZE(arr)); +} + +static PyMethodDef f2py_module_methods[] = { + + {"call",f2py_rout_wrap_call,METH_VARARGS,doc_f2py_rout_wrap_call}, + {"array_attrs",f2py_rout_wrap_attrs,METH_VARARGS,doc_f2py_rout_wrap_attrs}, + {NULL,NULL} +}; + +static struct PyModuleDef moduledef = { + PyModuleDef_HEAD_INIT, + "test_array_from_pyobj_ext", + NULL, + -1, + f2py_module_methods, + NULL, + NULL, + NULL, + NULL +}; + +PyMODINIT_FUNC PyInit_test_array_from_pyobj_ext(void) { + PyObject *m,*d, *s; + m = wrap_module = PyModule_Create(&moduledef); + Py_SET_TYPE(&PyFortran_Type, &PyType_Type); + import_array(); + if (PyErr_Occurred()) + Py_FatalError("can't initialize module wrap (failed to import numpy)"); + d = PyModule_GetDict(m); + s = PyUnicode_FromString("This module 'wrap' is auto-generated with f2py (version:2_1330).\nFunctions:\n" + " arr = call(type_num,dims,intent,obj)\n" + "."); + PyDict_SetItemString(d, "__doc__", s); + wrap_error = PyErr_NewException ("wrap.error", NULL, NULL); + Py_DECREF(s); + +#define ADDCONST(NAME, CONST) \ + s = PyLong_FromLong(CONST); \ + PyDict_SetItemString(d, NAME, s); \ + Py_DECREF(s) + + ADDCONST("F2PY_INTENT_IN", F2PY_INTENT_IN); + ADDCONST("F2PY_INTENT_INOUT", F2PY_INTENT_INOUT); + ADDCONST("F2PY_INTENT_OUT", F2PY_INTENT_OUT); + ADDCONST("F2PY_INTENT_HIDE", F2PY_INTENT_HIDE); + ADDCONST("F2PY_INTENT_CACHE", F2PY_INTENT_CACHE); + ADDCONST("F2PY_INTENT_COPY", F2PY_INTENT_COPY); + ADDCONST("F2PY_INTENT_C", F2PY_INTENT_C); + ADDCONST("F2PY_OPTIONAL", F2PY_OPTIONAL); + ADDCONST("F2PY_INTENT_INPLACE", F2PY_INTENT_INPLACE); + ADDCONST("NPY_BOOL", NPY_BOOL); + ADDCONST("NPY_BYTE", NPY_BYTE); + ADDCONST("NPY_UBYTE", NPY_UBYTE); + ADDCONST("NPY_SHORT", NPY_SHORT); + ADDCONST("NPY_USHORT", NPY_USHORT); + ADDCONST("NPY_INT", NPY_INT); + ADDCONST("NPY_UINT", NPY_UINT); + ADDCONST("NPY_INTP", NPY_INTP); + ADDCONST("NPY_UINTP", NPY_UINTP); + ADDCONST("NPY_LONG", NPY_LONG); + ADDCONST("NPY_ULONG", NPY_ULONG); + ADDCONST("NPY_LONGLONG", NPY_LONGLONG); + ADDCONST("NPY_ULONGLONG", NPY_ULONGLONG); + ADDCONST("NPY_FLOAT", NPY_FLOAT); + ADDCONST("NPY_DOUBLE", NPY_DOUBLE); + ADDCONST("NPY_LONGDOUBLE", NPY_LONGDOUBLE); + ADDCONST("NPY_CFLOAT", NPY_CFLOAT); + ADDCONST("NPY_CDOUBLE", NPY_CDOUBLE); + ADDCONST("NPY_CLONGDOUBLE", NPY_CLONGDOUBLE); + ADDCONST("NPY_OBJECT", NPY_OBJECT); + ADDCONST("NPY_STRING", NPY_STRING); + ADDCONST("NPY_UNICODE", NPY_UNICODE); + ADDCONST("NPY_VOID", NPY_VOID); + ADDCONST("NPY_NTYPES_LEGACY", NPY_NTYPES_LEGACY); + ADDCONST("NPY_NOTYPE", NPY_NOTYPE); + ADDCONST("NPY_USERDEF", NPY_USERDEF); + + ADDCONST("CONTIGUOUS", NPY_ARRAY_C_CONTIGUOUS); + ADDCONST("FORTRAN", NPY_ARRAY_F_CONTIGUOUS); + ADDCONST("OWNDATA", NPY_ARRAY_OWNDATA); + ADDCONST("FORCECAST", NPY_ARRAY_FORCECAST); + ADDCONST("ENSURECOPY", NPY_ARRAY_ENSURECOPY); + ADDCONST("ENSUREARRAY", NPY_ARRAY_ENSUREARRAY); + ADDCONST("ALIGNED", NPY_ARRAY_ALIGNED); + ADDCONST("WRITEABLE", NPY_ARRAY_WRITEABLE); + ADDCONST("WRITEBACKIFCOPY", NPY_ARRAY_WRITEBACKIFCOPY); + + ADDCONST("BEHAVED", NPY_ARRAY_BEHAVED); + ADDCONST("BEHAVED_NS", NPY_ARRAY_BEHAVED_NS); + ADDCONST("CARRAY", NPY_ARRAY_CARRAY); + ADDCONST("FARRAY", NPY_ARRAY_FARRAY); + ADDCONST("CARRAY_RO", NPY_ARRAY_CARRAY_RO); + ADDCONST("FARRAY_RO", NPY_ARRAY_FARRAY_RO); + ADDCONST("DEFAULT", NPY_ARRAY_DEFAULT); + ADDCONST("UPDATE_ALL", NPY_ARRAY_UPDATE_ALL); + +#undef ADDCONST + + if (PyErr_Occurred()) + Py_FatalError("can't initialize module wrap"); + +#ifdef F2PY_REPORT_ATEXIT + on_exit(f2py_report_on_exit,(void*)"array_from_pyobj.wrap.call"); +#endif + +#ifdef Py_GIL_DISABLED + // signal whether this module supports running with the GIL disabled + PyUnstable_Module_SetGIL(m, Py_MOD_GIL_NOT_USED); +#endif + + return m; +} +#ifdef __cplusplus +} +#endif diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/assumed_shape/.f2py_f2cmap b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/assumed_shape/.f2py_f2cmap new file mode 100644 index 0000000000000000000000000000000000000000..2665f89b52d2f17ce7b0a857bea73ec5fab2df88 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/assumed_shape/.f2py_f2cmap @@ -0,0 +1 @@ +dict(real=dict(rk="double")) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/assumed_shape/foo_free.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/assumed_shape/foo_free.f90 new file mode 100644 index 0000000000000000000000000000000000000000..b301710f5dda005e67e40cc21a5e0d62d0ec116a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/assumed_shape/foo_free.f90 @@ -0,0 +1,34 @@ + +subroutine sum(x, res) + implicit none + real, intent(in) :: x(:) + real, intent(out) :: res + + integer :: i + + !print *, "sum: size(x) = ", size(x) + + res = 0.0 + + do i = 1, size(x) + res = res + x(i) + enddo + +end subroutine sum + +function fsum(x) result (res) + implicit none + real, intent(in) :: x(:) + real :: res + + integer :: i + + !print *, "fsum: size(x) = ", size(x) + + res = 0.0 + + do i = 1, size(x) + res = res + x(i) + enddo + +end function fsum diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/assumed_shape/foo_mod.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/assumed_shape/foo_mod.f90 new file mode 100644 index 0000000000000000000000000000000000000000..cbe6317ed8f39f8a633b058a4ab64fe1797ea7b0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/assumed_shape/foo_mod.f90 @@ -0,0 +1,41 @@ + +module mod + +contains + +subroutine sum(x, res) + implicit none + real, intent(in) :: x(:) + real, intent(out) :: res + + integer :: i + + !print *, "sum: size(x) = ", size(x) + + res = 0.0 + + do i = 1, size(x) + res = res + x(i) + enddo + +end subroutine sum + +function fsum(x) result (res) + implicit none + real, intent(in) :: x(:) + real :: res + + integer :: i + + !print *, "fsum: size(x) = ", size(x) + + res = 0.0 + + do i = 1, size(x) + res = res + x(i) + enddo + +end function fsum + + +end module mod diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/assumed_shape/foo_use.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/assumed_shape/foo_use.f90 new file mode 100644 index 0000000000000000000000000000000000000000..337465ac540440fc8e8e10d23757af202e8a52a4 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/assumed_shape/foo_use.f90 @@ -0,0 +1,19 @@ +subroutine sum_with_use(x, res) + use precision + + implicit none + + real(kind=rk), intent(in) :: x(:) + real(kind=rk), intent(out) :: res + + integer :: i + + !print *, "size(x) = ", size(x) + + res = 0.0 + + do i = 1, size(x) + res = res + x(i) + enddo + + end subroutine diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/assumed_shape/precision.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/assumed_shape/precision.f90 new file mode 100644 index 0000000000000000000000000000000000000000..ed6c70cbbe7dadfd50b616a8cc1570939ef5afd8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/assumed_shape/precision.f90 @@ -0,0 +1,4 @@ +module precision + integer, parameter :: rk = selected_real_kind(8) + integer, parameter :: ik = selected_real_kind(4) +end module diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/block_docstring/foo.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/block_docstring/foo.f new file mode 100644 index 0000000000000000000000000000000000000000..c8315f12ce0f5cf3dbc4c965ad8843d0c10441cd --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/block_docstring/foo.f @@ -0,0 +1,6 @@ + SUBROUTINE FOO() + INTEGER BAR(2, 3) + + COMMON /BLOCK/ BAR + RETURN + END diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/foo.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/foo.f new file mode 100644 index 0000000000000000000000000000000000000000..ba397bb38133faa8d502807368074e6b296749b9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/foo.f @@ -0,0 +1,62 @@ + subroutine t(fun,a) + integer a +cf2py intent(out) a + external fun + call fun(a) + end + + subroutine func(a) +cf2py intent(in,out) a + integer a + a = a + 11 + end + + subroutine func0(a) +cf2py intent(out) a + integer a + a = 11 + end + + subroutine t2(a) +cf2py intent(callback) fun + integer a +cf2py intent(out) a + external fun + call fun(a) + end + + subroutine string_callback(callback, a) + external callback + double precision callback + double precision a + character*1 r +cf2py intent(out) a + r = 'r' + a = callback(r) + end + + subroutine string_callback_array(callback, cu, lencu, a) + external callback + integer callback + integer lencu + character*8 cu(lencu) + integer a +cf2py intent(out) a + + a = callback(cu, lencu) + end + + subroutine hidden_callback(a, r) + external global_f +cf2py intent(callback, hide) global_f + integer a, r, global_f +cf2py intent(out) r + r = global_f(a) + end + + subroutine hidden_callback2(a, r) + external global_f + integer a, r, global_f +cf2py intent(out) r + r = global_f(a) + end diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/gh17797.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/gh17797.f90 new file mode 100644 index 0000000000000000000000000000000000000000..49853afd766a90e521104081bf77236a252d3c70 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/gh17797.f90 @@ -0,0 +1,7 @@ +function gh17797(f, y) result(r) + external f + integer(8) :: r, f + integer(8), dimension(:) :: y + r = f(0) + r = r + sum(y) +end function gh17797 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/gh18335.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/gh18335.f90 new file mode 100644 index 0000000000000000000000000000000000000000..92b6d7540c827d20c7d2169c56f14653954d7ff9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/gh18335.f90 @@ -0,0 +1,17 @@ + ! When gh18335_workaround is defined as an extension, + ! the issue cannot be reproduced. + !subroutine gh18335_workaround(f, y) + ! implicit none + ! external f + ! integer(kind=1) :: y(1) + ! call f(y) + !end subroutine gh18335_workaround + + function gh18335(f) result (r) + implicit none + external f + integer(kind=1) :: y(1), r + y(1) = 123 + call f(y) + r = y(1) + end function gh18335 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/gh25211.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/gh25211.f new file mode 100644 index 0000000000000000000000000000000000000000..ba727a10a07ebec77845f8a67746cf5d5bb3d32a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/gh25211.f @@ -0,0 +1,10 @@ + SUBROUTINE FOO(FUN,R) + EXTERNAL FUN + INTEGER I + REAL*8 R, FUN +Cf2py intent(out) r + R = 0D0 + DO I=-5,5 + R = R + FUN(I) + ENDDO + END diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/gh25211.pyf b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/gh25211.pyf new file mode 100644 index 0000000000000000000000000000000000000000..f12011153370b022a2686222655a12245a1eb14e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/gh25211.pyf @@ -0,0 +1,18 @@ +python module __user__routines + interface + function fun(i) result (r) + integer :: i + real*8 :: r + end function fun + end interface +end python module __user__routines + +python module callback2 + interface + subroutine foo(f,r) + use __user__routines, f=>fun + external f + real*8 intent(out) :: r + end subroutine foo + end interface +end python module callback2 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/gh26681.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/gh26681.f90 new file mode 100644 index 0000000000000000000000000000000000000000..00c0ec93df059b0d1952471fae440016abbac3e5 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/callback/gh26681.f90 @@ -0,0 +1,18 @@ +module utils + implicit none + contains + subroutine my_abort(message) + implicit none + character(len=*), intent(in) :: message + !f2py callstatement PyErr_SetString(PyExc_ValueError, message);f2py_success = 0; + !f2py callprotoargument char* + write(0,*) "THIS SHOULD NOT APPEAR" + stop 1 + end subroutine my_abort + + subroutine do_something(message) + !f2py intent(callback, hide) mypy_abort + character(len=*), intent(in) :: message + call mypy_abort(message) + end subroutine do_something +end module utils diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/cli/gh_22819.pyf b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/cli/gh_22819.pyf new file mode 100644 index 0000000000000000000000000000000000000000..8eb5bb106a366ec214944c19e53d9788c0596e55 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/cli/gh_22819.pyf @@ -0,0 +1,6 @@ +python module test_22819 + interface + subroutine hello() + end subroutine hello + end interface +end python module test_22819 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/cli/hi77.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/cli/hi77.f new file mode 100644 index 0000000000000000000000000000000000000000..8b916ebe0459eb812baad694aa671011a1381f8a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/cli/hi77.f @@ -0,0 +1,3 @@ + SUBROUTINE HI + PRINT*, "HELLO WORLD" + END SUBROUTINE diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/cli/hiworld.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/cli/hiworld.f90 new file mode 100644 index 0000000000000000000000000000000000000000..981f877547a4caec513a15dea1401bbc98ce3f23 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/cli/hiworld.f90 @@ -0,0 +1,3 @@ +function hi() + print*, "Hello World" +end function diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/common/block.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/common/block.f new file mode 100644 index 0000000000000000000000000000000000000000..7ea7968fe935182bd17a697b316569546937b715 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/common/block.f @@ -0,0 +1,11 @@ + SUBROUTINE INITCB + DOUBLE PRECISION LONG + CHARACTER STRING + INTEGER OK + + COMMON /BLOCK/ LONG, STRING, OK + LONG = 1.0 + STRING = '2' + OK = 3 + RETURN + END diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/common/gh19161.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/common/gh19161.f90 new file mode 100644 index 0000000000000000000000000000000000000000..a2f40735ad66a3cb70cfc10a3938882c77ff54ea --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/common/gh19161.f90 @@ -0,0 +1,10 @@ +module typedefmod + use iso_fortran_env, only: real32 +end module typedefmod + +module data + use typedefmod, only: real32 + implicit none + real(kind=real32) :: x + common/test/x +end module data diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/accesstype.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/accesstype.f90 new file mode 100644 index 0000000000000000000000000000000000000000..e2cbd445daf57f21e2d727f42a3891ec28725175 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/accesstype.f90 @@ -0,0 +1,13 @@ +module foo + public + type, private, bind(c) :: a + integer :: i + end type a + type, bind(c) :: b_ + integer :: j + end type b_ + public :: b_ + type :: c + integer :: k + end type c +end module foo diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/common_with_division.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/common_with_division.f new file mode 100644 index 0000000000000000000000000000000000000000..4aa12cf6dcee9b4936d10f1c5d55f8d59762062a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/common_with_division.f @@ -0,0 +1,17 @@ + subroutine common_with_division + integer lmu,lb,lub,lpmin + parameter (lmu=1) + parameter (lb=20) +c crackfortran fails to parse this +c parameter (lub=(lb-1)*lmu+1) +c crackfortran can successfully parse this though + parameter (lub=lb*lmu-lmu+1) + parameter (lpmin=2) + +c crackfortran fails to parse this correctly +c common /mortmp/ ctmp((lub*(lub+1)*(lub+1))/lpmin+1) + + common /mortmp/ ctmp(lub/lpmin+1) + + return + end diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/data_common.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/data_common.f new file mode 100644 index 0000000000000000000000000000000000000000..5ffd865c837997f8aae2d8faebfd519df61d8cd2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/data_common.f @@ -0,0 +1,8 @@ + BLOCK DATA PARAM_INI + COMMON /MYCOM/ MYDATA + DATA MYDATA /0/ + END + SUBROUTINE SUB1 + COMMON /MYCOM/ MYDATA + MYDATA = MYDATA + 1 + END diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/data_multiplier.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/data_multiplier.f new file mode 100644 index 0000000000000000000000000000000000000000..19ff8a83e97b7a1fa9ef82a2f4d5241ec422cb01 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/data_multiplier.f @@ -0,0 +1,5 @@ + BLOCK DATA MYBLK + IMPLICIT DOUBLE PRECISION (A-H,O-Z) + COMMON /MYCOM/ IVAR1, IVAR2, IVAR3, IVAR4, EVAR5 + DATA IVAR1, IVAR2, IVAR3, IVAR4, EVAR5 /2*3,2*2,0.0D0/ + END diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/data_stmts.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/data_stmts.f90 new file mode 100644 index 0000000000000000000000000000000000000000..576c5e485baf209aea79f566fc09cb20138a0a25 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/data_stmts.f90 @@ -0,0 +1,20 @@ +! gh-23276 +module cmplxdat + implicit none + integer :: i, j + real :: x, y + real, dimension(2) :: z + real(kind=8) :: pi + complex(kind=8), target :: medium_ref_index + complex(kind=8), target :: ref_index_one, ref_index_two + complex(kind=8), dimension(2) :: my_array + real(kind=8), dimension(3) :: my_real_array = (/1.0d0, 2.0d0, 3.0d0/) + + data i, j / 2, 3 / + data x, y / 1.5, 2.0 / + data z / 3.5, 7.0 / + data medium_ref_index / (1.d0, 0.d0) / + data ref_index_one, ref_index_two / (13.0d0, 21.0d0), (-30.0d0, 43.0d0) / + data my_array / (1.0d0, 2.0d0), (-3.0d0, 4.0d0) / + data pi / 3.1415926535897932384626433832795028841971693993751058209749445923078164062d0 / +end module cmplxdat diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/data_with_comments.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/data_with_comments.f new file mode 100644 index 0000000000000000000000000000000000000000..4128f004e840087ab8e08a06c76995b249a561b0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/data_with_comments.f @@ -0,0 +1,8 @@ + BLOCK DATA PARAM_INI + COMMON /MYCOM/ MYTAB + INTEGER MYTAB(3) + DATA MYTAB/ + * 0, ! 1 and more commenty stuff + * 4, ! 2 + * 0 / + END diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/foo_deps.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/foo_deps.f90 new file mode 100644 index 0000000000000000000000000000000000000000..e327b25c81986b2191fc740991ca9e907b5b0fb6 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/foo_deps.f90 @@ -0,0 +1,6 @@ +module foo + type bar + character(len = 4) :: text + end type bar + type(bar), parameter :: abar = bar('abar') +end module foo diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh15035.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh15035.f new file mode 100644 index 0000000000000000000000000000000000000000..1bb2e6745952cb10067116e9ae3337c8314061ee --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh15035.f @@ -0,0 +1,16 @@ + subroutine subb(k) + real(8), intent(inout) :: k(:) + k=k+1 + endsubroutine + + subroutine subc(w,k) + real(8), intent(in) :: w(:) + real(8), intent(out) :: k(size(w)) + k=w+1 + endsubroutine + + function t0(value) + character value + character t0 + t0 = value + endfunction diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh17859.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh17859.f new file mode 100644 index 0000000000000000000000000000000000000000..995953845c5eb1b4fa2bdf70c18e0296d38e5252 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh17859.f @@ -0,0 +1,12 @@ + integer(8) function external_as_statement(fcn) + implicit none + external fcn + integer(8) :: fcn + external_as_statement = fcn(0) + end + + integer(8) function external_as_attribute(fcn) + implicit none + integer(8), external :: fcn + external_as_attribute = fcn(0) + end diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh22648.pyf b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh22648.pyf new file mode 100644 index 0000000000000000000000000000000000000000..b3454f18635fc8fe2b8ea5d15f85a9d77af9a22b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh22648.pyf @@ -0,0 +1,7 @@ +python module iri16py ! in + interface ! in :iri16py + block data ! in :iri16py:iridreg_modified.for + COMMON /fircom/ eden,tabhe,tabla,tabmo,tabza,tabfl + end block data + end interface +end python module iri16py diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh23533.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh23533.f new file mode 100644 index 0000000000000000000000000000000000000000..db522afa7d2fdd09e26f2d02a649a659d9ed7d60 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh23533.f @@ -0,0 +1,5 @@ + SUBROUTINE EXAMPLE( ) + IF( .TRUE. ) THEN + CALL DO_SOMETHING() + END IF ! ** .TRUE. ** + END diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh23598.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh23598.f90 new file mode 100644 index 0000000000000000000000000000000000000000..e0dffb5ef29e3d5ba853ff4dfeda57b2bed6a9dc --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh23598.f90 @@ -0,0 +1,4 @@ +integer function intproduct(a, b) result(res) + integer, intent(in) :: a, b + res = a*b +end function diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh23598Warn.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh23598Warn.f90 new file mode 100644 index 0000000000000000000000000000000000000000..3b44efc5ef16e9f7e1105229371ae48ecc069ee5 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh23598Warn.f90 @@ -0,0 +1,11 @@ +module test_bug + implicit none + private + public :: intproduct + +contains + integer function intproduct(a, b) result(res) + integer, intent(in) :: a, b + res = a*b + end function +end module diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh23879.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh23879.f90 new file mode 100644 index 0000000000000000000000000000000000000000..fac262d53c9d3f0f3a5ba1138594f5b694b95717 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh23879.f90 @@ -0,0 +1,20 @@ +module gh23879 + implicit none + private + public :: foo + + contains + + subroutine foo(a, b) + integer, intent(in) :: a + integer, intent(out) :: b + b = a + call bar(b) + end subroutine + + subroutine bar(x) + integer, intent(inout) :: x + x = 2*x + end subroutine + + end module gh23879 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh27697.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh27697.f90 new file mode 100644 index 0000000000000000000000000000000000000000..a5eae4e79b25cd086df4ea2aa26d39ae48a8ca88 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh27697.f90 @@ -0,0 +1,12 @@ +module utils + implicit none + contains + subroutine my_abort(message) + implicit none + character(len=*), intent(in) :: message + !f2py callstatement PyErr_SetString(PyExc_ValueError, message);f2py_success = 0; + !f2py callprotoargument char* + write(0,*) "THIS SHOULD NOT APPEAR" + stop 1 + end subroutine my_abort +end module utils diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh2848.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh2848.f90 new file mode 100644 index 0000000000000000000000000000000000000000..31ea9327a4d9134011cfc668cc88961968756d77 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/gh2848.f90 @@ -0,0 +1,13 @@ + subroutine gh2848( & + ! first 2 parameters + par1, par2,& + ! last 2 parameters + par3, par4) + + integer, intent(in) :: par1, par2 + integer, intent(out) :: par3, par4 + + par3 = par1 + par4 = par2 + + end subroutine gh2848 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/operators.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/operators.f90 new file mode 100644 index 0000000000000000000000000000000000000000..1d060a3d2bd5abd12732e6003cec53f36baeba7c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/operators.f90 @@ -0,0 +1,49 @@ +module foo + type bar + character(len = 32) :: item + end type bar + interface operator(.item.) + module procedure item_int, item_real + end interface operator(.item.) + interface operator(==) + module procedure items_are_equal + end interface operator(==) + interface assignment(=) + module procedure get_int, get_real + end interface assignment(=) +contains + function item_int(val) result(elem) + integer, intent(in) :: val + type(bar) :: elem + + write(elem%item, "(I32)") val + end function item_int + + function item_real(val) result(elem) + real, intent(in) :: val + type(bar) :: elem + + write(elem%item, "(1PE32.12)") val + end function item_real + + function items_are_equal(val1, val2) result(equal) + type(bar), intent(in) :: val1, val2 + logical :: equal + + equal = (val1%item == val2%item) + end function items_are_equal + + subroutine get_real(rval, item) + real, intent(out) :: rval + type(bar), intent(in) :: item + + read(item%item, *) rval + end subroutine get_real + + subroutine get_int(rval, item) + integer, intent(out) :: rval + type(bar), intent(in) :: item + + read(item%item, *) rval + end subroutine get_int +end module foo diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/privatemod.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/privatemod.f90 new file mode 100644 index 0000000000000000000000000000000000000000..2674c214767b33663e51ee1d32ad7a1792c92680 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/privatemod.f90 @@ -0,0 +1,11 @@ +module foo + private + integer :: a + public :: setA + integer :: b +contains + subroutine setA(v) + integer, intent(in) :: v + a = v + end subroutine setA +end module foo diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/publicmod.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/publicmod.f90 new file mode 100644 index 0000000000000000000000000000000000000000..1db76e3fe06828ba0d1b640720ec70422cde6872 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/publicmod.f90 @@ -0,0 +1,10 @@ +module foo + public + integer, private :: a + public :: setA +contains + subroutine setA(v) + integer, intent(in) :: v + a = v + end subroutine setA +end module foo diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/pubprivmod.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/pubprivmod.f90 new file mode 100644 index 0000000000000000000000000000000000000000..46bef7cb91122281ddac7d0f0474c2c01b2a5e6f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/pubprivmod.f90 @@ -0,0 +1,10 @@ +module foo + public + integer, private :: a + integer :: b +contains + subroutine setA(v) + integer, intent(in) :: v + a = v + end subroutine setA +end module foo diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/unicode_comment.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/unicode_comment.f90 new file mode 100644 index 0000000000000000000000000000000000000000..13515ce98c50e88a03004161fb135e8502005a82 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/crackfortran/unicode_comment.f90 @@ -0,0 +1,4 @@ +subroutine foo(x) + real(8), intent(in) :: x + ! Écrit à l'écran la valeur de x +end subroutine diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/f2cmap/.f2py_f2cmap b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/f2cmap/.f2py_f2cmap new file mode 100644 index 0000000000000000000000000000000000000000..a4425f8876f5b7ec9c72a11862a8cd4574d33ea8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/f2cmap/.f2py_f2cmap @@ -0,0 +1 @@ +dict(real=dict(real32='float', real64='double'), integer=dict(int64='long_long')) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/f2cmap/isoFortranEnvMap.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/f2cmap/isoFortranEnvMap.f90 new file mode 100644 index 0000000000000000000000000000000000000000..1e1dc1d4054b36d2b2d9104e8d6ab708361bfbe8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/f2cmap/isoFortranEnvMap.f90 @@ -0,0 +1,9 @@ + subroutine func1(n, x, res) + use, intrinsic :: iso_fortran_env, only: int64, real64 + implicit none + integer(int64), intent(in) :: n + real(real64), intent(in) :: x(n) + real(real64), intent(out) :: res +!f2py intent(hide) :: n + res = sum(x) + end diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/isocintrin/isoCtests.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/isocintrin/isoCtests.f90 new file mode 100644 index 0000000000000000000000000000000000000000..765f7c1ce6608a0c8588b6c20edd052e2d3e07bf --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/isocintrin/isoCtests.f90 @@ -0,0 +1,34 @@ + module coddity + use iso_c_binding, only: c_double, c_int, c_int64_t + implicit none + contains + subroutine c_add(a, b, c) bind(c, name="c_add") + real(c_double), intent(in) :: a, b + real(c_double), intent(out) :: c + c = a + b + end subroutine c_add + ! gh-9693 + function wat(x, y) result(z) bind(c) + integer(c_int), intent(in) :: x, y + integer(c_int) :: z + + z = x + 7 + end function wat + ! gh-25207 + subroutine c_add_int64(a, b, c) bind(c) + integer(c_int64_t), intent(in) :: a, b + integer(c_int64_t), intent(out) :: c + c = a + b + end subroutine c_add_int64 + ! gh-25207 + subroutine add_arr(A, B, C) + integer(c_int64_t), intent(in) :: A(3) + integer(c_int64_t), intent(in) :: B(3) + integer(c_int64_t), intent(out) :: C(3) + integer :: j + + do j = 1, 3 + C(j) = A(j)+B(j) + end do + end subroutine + end module coddity diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/kind/foo.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/kind/foo.f90 new file mode 100644 index 0000000000000000000000000000000000000000..d3d15cfb20a15004ed86e45dc91792d1c089033a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/kind/foo.f90 @@ -0,0 +1,20 @@ + + +subroutine selectedrealkind(p, r, res) + implicit none + + integer, intent(in) :: p, r + !f2py integer :: r=0 + integer, intent(out) :: res + res = selected_real_kind(p, r) + +end subroutine + +subroutine selectedintkind(p, res) + implicit none + + integer, intent(in) :: p + integer, intent(out) :: res + res = selected_int_kind(p) + +end subroutine diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/mixed/foo.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/mixed/foo.f new file mode 100644 index 0000000000000000000000000000000000000000..c34742578f8551729fdc3474d86e92c87e2868d2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/mixed/foo.f @@ -0,0 +1,5 @@ + subroutine bar11(a) +cf2py intent(out) a + integer a + a = 11 + end diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/mixed/foo_fixed.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/mixed/foo_fixed.f90 new file mode 100644 index 0000000000000000000000000000000000000000..7543a6acb7375872388cb9f2ced109db5faa17b0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/mixed/foo_fixed.f90 @@ -0,0 +1,8 @@ + module foo_fixed + contains + subroutine bar12(a) +!f2py intent(out) a + integer a + a = 12 + end subroutine bar12 + end module foo_fixed diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/mixed/foo_free.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/mixed/foo_free.f90 new file mode 100644 index 0000000000000000000000000000000000000000..c1b641f13ec2943b9dd23ba85beecda738b51825 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/mixed/foo_free.f90 @@ -0,0 +1,8 @@ +module foo_free +contains + subroutine bar13(a) + !f2py intent(out) a + integer a + a = 13 + end subroutine bar13 +end module foo_free diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/gh25337/data.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/gh25337/data.f90 new file mode 100644 index 0000000000000000000000000000000000000000..483d13ceb95c08bf38b74d8218932fc109792b09 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/gh25337/data.f90 @@ -0,0 +1,8 @@ +module data + real(8) :: shift +contains + subroutine set_shift(in_shift) + real(8), intent(in) :: in_shift + shift = in_shift + end subroutine set_shift +end module data diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/gh25337/use_data.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/gh25337/use_data.f90 new file mode 100644 index 0000000000000000000000000000000000000000..b3fae8b875d03d75199f4cf06d544edb4aab1a89 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/gh25337/use_data.f90 @@ -0,0 +1,6 @@ +subroutine shift_a(dim_a, a) + use data, only: shift + integer, intent(in) :: dim_a + real(8), intent(inout), dimension(dim_a) :: a + a = a + shift +end subroutine shift_a diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/gh26920/two_mods_with_no_public_entities.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/gh26920/two_mods_with_no_public_entities.f90 new file mode 100644 index 0000000000000000000000000000000000000000..07adce591f35756ca2fe2f3e2dd38fcaf01d2fad --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/gh26920/two_mods_with_no_public_entities.f90 @@ -0,0 +1,21 @@ + module mod2 + implicit none + private mod2_func1 + contains + + subroutine mod2_func1() + print*, "mod2_func1" + end subroutine mod2_func1 + + end module mod2 + + module mod1 + implicit none + private :: mod1_func1 + contains + + subroutine mod1_func1() + print*, "mod1_func1" + end subroutine mod1_func1 + + end module mod1 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/gh26920/two_mods_with_one_public_routine.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/gh26920/two_mods_with_one_public_routine.f90 new file mode 100644 index 0000000000000000000000000000000000000000..b7fb95b010a6657df3abeed4c71466b82dcfdab3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/gh26920/two_mods_with_one_public_routine.f90 @@ -0,0 +1,21 @@ + module mod2 + implicit none + PUBLIC :: mod2_func1 + contains + + subroutine mod2_func1() + print*, "mod2_func1" + end subroutine mod2_func1 + + end module mod2 + + module mod1 + implicit none + PUBLIC :: mod1_func1 + contains + + subroutine mod1_func1() + print*, "mod1_func1" + end subroutine mod1_func1 + + end module mod1 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/module_data_docstring.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/module_data_docstring.f90 new file mode 100644 index 0000000000000000000000000000000000000000..4505e0cbc31e50a75df94b30cd53cf923659379d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/module_data_docstring.f90 @@ -0,0 +1,12 @@ +module mod + integer :: i + integer :: x(4) + real, dimension(2,3) :: a + real, allocatable, dimension(:,:) :: b +contains + subroutine foo + integer :: k + k = 1 + a(1,2) = a(1,2)+3 + end subroutine foo +end module mod diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/use_modules.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/use_modules.f90 new file mode 100644 index 0000000000000000000000000000000000000000..aa40c86ca39d1dbcfacca9dcb2addbc6ede73140 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/modules/use_modules.f90 @@ -0,0 +1,20 @@ +module mathops + implicit none +contains + function add(a, b) result(c) + integer, intent(in) :: a, b + integer :: c + c = a + b + end function add +end module mathops + +module useops + use mathops, only: add + implicit none +contains + function sum_and_double(a, b) result(d) + integer, intent(in) :: a, b + integer :: d + d = 2 * add(a, b) + end function sum_and_double +end module useops diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/negative_bounds/issue_20853.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/negative_bounds/issue_20853.f90 new file mode 100644 index 0000000000000000000000000000000000000000..bf1fa92853316cc31f825c024855088f42577a1c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/negative_bounds/issue_20853.f90 @@ -0,0 +1,7 @@ +subroutine foo(is_, ie_, arr, tout) + implicit none + integer :: is_,ie_ + real, intent(in) :: arr(is_:ie_) + real, intent(out) :: tout(is_:ie_) + tout = arr +end diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_array.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_array.f90 new file mode 100644 index 0000000000000000000000000000000000000000..9a6bf81610d41cf5f480d6e3c25fd7ab4cf5bfff --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_array.f90 @@ -0,0 +1,45 @@ +! Check that parameter arrays are correctly intercepted. +subroutine foo_array(x, y, z) + implicit none + integer, parameter :: dp = selected_real_kind(15) + integer, parameter :: pa = 2 + integer, parameter :: intparamarray(2) = (/ 3, 5 /) + integer, dimension(pa), parameter :: pb = (/ 2, 10 /) + integer, parameter, dimension(intparamarray(1)) :: pc = (/ 2, 10, 20 /) + real(dp), parameter :: doubleparamarray(3) = (/ 3.14_dp, 4._dp, 6.44_dp /) + real(dp), intent(inout) :: x(intparamarray(1)) + real(dp), intent(inout) :: y(intparamarray(2)) + real(dp), intent(out) :: z + + x = x/pb(2) + y = y*pc(2) + z = doubleparamarray(1)*doubleparamarray(2) + doubleparamarray(3) + + return +end subroutine + +subroutine foo_array_any_index(x, y) + implicit none + integer, parameter :: dp = selected_real_kind(15) + integer, parameter, dimension(-1:1) :: myparamarray = (/ 6, 3, 1 /) + integer, parameter, dimension(2) :: nested = (/ 2, 0 /) + integer, parameter :: dim = 2 + real(dp), intent(in) :: x(myparamarray(-1)) + real(dp), intent(out) :: y(nested(1), myparamarray(nested(dim))) + + y = reshape(x, (/nested(1), myparamarray(nested(2))/)) + + return +end subroutine + +subroutine foo_array_delims(x) + implicit none + integer, parameter :: dp = selected_real_kind(15) + integer, parameter, dimension(2) :: myparamarray = (/ (6), 1 /) + integer, parameter, dimension(3) :: test = (/2, 1, (3)/) + real(dp), intent(out) :: x + + x = myparamarray(1)+test(3) + + return +end subroutine diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_both.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_both.f90 new file mode 100644 index 0000000000000000000000000000000000000000..ac90cedc525a6172a9b72f3bc76f57b79d641b6c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_both.f90 @@ -0,0 +1,57 @@ +! Check that parameters are correct intercepted. +! Constants with comma separations are commonly +! used, for instance Pi = 3._dp +subroutine foo(x) + implicit none + integer, parameter :: sp = selected_real_kind(6) + integer, parameter :: dp = selected_real_kind(15) + integer, parameter :: ii = selected_int_kind(9) + integer, parameter :: il = selected_int_kind(18) + real(dp), intent(inout) :: x + dimension x(3) + real(sp), parameter :: three_s = 3._sp + real(dp), parameter :: three_d = 3._dp + integer(ii), parameter :: three_i = 3_ii + integer(il), parameter :: three_l = 3_il + x(1) = x(1) + x(2) * three_s * three_i + x(3) * three_d * three_l + x(2) = x(2) * three_s + x(3) = x(3) * three_l + return +end subroutine + + +subroutine foo_no(x) + implicit none + integer, parameter :: sp = selected_real_kind(6) + integer, parameter :: dp = selected_real_kind(15) + integer, parameter :: ii = selected_int_kind(9) + integer, parameter :: il = selected_int_kind(18) + real(dp), intent(inout) :: x + dimension x(3) + real(sp), parameter :: three_s = 3. + real(dp), parameter :: three_d = 3. + integer(ii), parameter :: three_i = 3 + integer(il), parameter :: three_l = 3 + x(1) = x(1) + x(2) * three_s * three_i + x(3) * three_d * three_l + x(2) = x(2) * three_s + x(3) = x(3) * three_l + return +end subroutine + +subroutine foo_sum(x) + implicit none + integer, parameter :: sp = selected_real_kind(6) + integer, parameter :: dp = selected_real_kind(15) + integer, parameter :: ii = selected_int_kind(9) + integer, parameter :: il = selected_int_kind(18) + real(dp), intent(inout) :: x + dimension x(3) + real(sp), parameter :: three_s = 2._sp + 1._sp + real(dp), parameter :: three_d = 1._dp + 2._dp + integer(ii), parameter :: three_i = 2_ii + 1_ii + integer(il), parameter :: three_l = 1_il + 2_il + x(1) = x(1) + x(2) * three_s * three_i + x(3) * three_d * three_l + x(2) = x(2) * three_s + x(3) = x(3) * three_l + return +end subroutine diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_compound.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_compound.f90 new file mode 100644 index 0000000000000000000000000000000000000000..e51f5e9b2fb166a6b7d9cba57af03617024b7f2a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_compound.f90 @@ -0,0 +1,15 @@ +! Check that parameters are correct intercepted. +! Constants with comma separations are commonly +! used, for instance Pi = 3._dp +subroutine foo_compound_int(x) + implicit none + integer, parameter :: ii = selected_int_kind(9) + integer(ii), intent(inout) :: x + dimension x(3) + integer(ii), parameter :: three = 3_ii + integer(ii), parameter :: two = 2_ii + integer(ii), parameter :: six = three * 1_ii * two + + x(1) = x(1) + x(2) + x(3) * six + return +end subroutine diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_integer.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_integer.f90 new file mode 100644 index 0000000000000000000000000000000000000000..aaa83d2eb241274231130b6243ca2c970b5664e0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_integer.f90 @@ -0,0 +1,22 @@ +! Check that parameters are correct intercepted. +! Constants with comma separations are commonly +! used, for instance Pi = 3._dp +subroutine foo_int(x) + implicit none + integer, parameter :: ii = selected_int_kind(9) + integer(ii), intent(inout) :: x + dimension x(3) + integer(ii), parameter :: three = 3_ii + x(1) = x(1) + x(2) + x(3) * three + return +end subroutine + +subroutine foo_long(x) + implicit none + integer, parameter :: ii = selected_int_kind(18) + integer(ii), intent(inout) :: x + dimension x(3) + integer(ii), parameter :: three = 3_ii + x(1) = x(1) + x(2) + x(3) * three + return +end subroutine diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_non_compound.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_non_compound.f90 new file mode 100644 index 0000000000000000000000000000000000000000..62c9a5b943cb768c9270a04d1dbf36d526a4e6e8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_non_compound.f90 @@ -0,0 +1,23 @@ +! Check that parameters are correct intercepted. +! Specifically that types of constants without +! compound kind specs are correctly inferred +! adapted Gibbs iteration code from pymc +! for this test case +subroutine foo_non_compound_int(x) + implicit none + integer, parameter :: ii = selected_int_kind(9) + + integer(ii) maxiterates + parameter (maxiterates=2) + + integer(ii) maxseries + parameter (maxseries=2) + + integer(ii) wasize + parameter (wasize=maxiterates*maxseries) + integer(ii), intent(inout) :: x + dimension x(wasize) + + x(1) = x(1) + x(2) + x(3) + x(4) * wasize + return +end subroutine diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_real.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_real.f90 new file mode 100644 index 0000000000000000000000000000000000000000..02ac9dd993b39dbb69a233ed1f0d031f15f84639 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/parameter/constant_real.f90 @@ -0,0 +1,23 @@ +! Check that parameters are correct intercepted. +! Constants with comma separations are commonly +! used, for instance Pi = 3._dp +subroutine foo_single(x) + implicit none + integer, parameter :: rp = selected_real_kind(6) + real(rp), intent(inout) :: x + dimension x(3) + real(rp), parameter :: three = 3._rp + x(1) = x(1) + x(2) + x(3) * three + return +end subroutine + +subroutine foo_double(x) + implicit none + integer, parameter :: rp = selected_real_kind(15) + real(rp), intent(inout) :: x + dimension x(3) + real(rp), parameter :: three = 3._rp + x(1) = x(1) + x(2) + x(3) * three + return +end subroutine + diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/quoted_character/foo.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/quoted_character/foo.f new file mode 100644 index 0000000000000000000000000000000000000000..9dc1cfa4446d8c05c0fc0bb1c69360a687d003c3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/quoted_character/foo.f @@ -0,0 +1,14 @@ + SUBROUTINE FOO(OUT1, OUT2, OUT3, OUT4, OUT5, OUT6) + CHARACTER SINGLE, DOUBLE, SEMICOL, EXCLA, OPENPAR, CLOSEPAR + PARAMETER (SINGLE="'", DOUBLE='"', SEMICOL=';', EXCLA="!", + 1 OPENPAR="(", CLOSEPAR=")") + CHARACTER OUT1, OUT2, OUT3, OUT4, OUT5, OUT6 +Cf2py intent(out) OUT1, OUT2, OUT3, OUT4, OUT5, OUT6 + OUT1 = SINGLE + OUT2 = DOUBLE + OUT3 = SEMICOL + OUT4 = EXCLA + OUT5 = OPENPAR + OUT6 = CLOSEPAR + RETURN + END diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/AB.inc b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/AB.inc new file mode 100644 index 0000000000000000000000000000000000000000..8a02f631f43a15f17f65280d651aa46e9cdb7510 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/AB.inc @@ -0,0 +1 @@ +real(8) b, n, m diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/assignOnlyModule.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/assignOnlyModule.f90 new file mode 100644 index 0000000000000000000000000000000000000000..479ac7980c226ac19a8d97dd2e43f8833d95e66e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/assignOnlyModule.f90 @@ -0,0 +1,25 @@ + MODULE MOD_TYPES + INTEGER, PARAMETER :: SP = SELECTED_REAL_KIND(6, 37) + INTEGER, PARAMETER :: DP = SELECTED_REAL_KIND(15, 307) + END MODULE +! + MODULE F_GLOBALS + USE MOD_TYPES + IMPLICIT NONE + INTEGER, PARAMETER :: N_MAX = 16 + INTEGER, PARAMETER :: I_MAX = 18 + INTEGER, PARAMETER :: J_MAX = 72 + REAL(SP) :: XREF + END MODULE F_GLOBALS +! + SUBROUTINE DUMMY () +! + USE F_GLOBALS + USE MOD_TYPES + IMPLICIT NONE +! + REAL(SP) :: MINIMAL + MINIMAL = 0.01*XREF + RETURN +! + END SUBROUTINE DUMMY diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/datonly.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/datonly.f90 new file mode 100644 index 0000000000000000000000000000000000000000..67fc4aca82e3fd4aa9ebb4f725d1b13761dbade9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/datonly.f90 @@ -0,0 +1,17 @@ +module datonly + implicit none + integer, parameter :: max_value = 100 + real, dimension(:), allocatable :: data_array +end module datonly + +module dat + implicit none + integer, parameter :: max_= 1009 +end module dat + +subroutine simple_subroutine(ain, aout) + use dat, only: max_ + integer, intent(in) :: ain + integer, intent(out) :: aout + aout = ain + max_ +end subroutine simple_subroutine diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/f77comments.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/f77comments.f new file mode 100644 index 0000000000000000000000000000000000000000..452a01a14439b1e7a9a731a31d7f720992826698 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/f77comments.f @@ -0,0 +1,26 @@ + SUBROUTINE TESTSUB( + & INPUT1, INPUT2, !Input + & OUTPUT1, OUTPUT2) !Output + + IMPLICIT NONE + INTEGER, INTENT(IN) :: INPUT1, INPUT2 + INTEGER, INTENT(OUT) :: OUTPUT1, OUTPUT2 + + OUTPUT1 = INPUT1 + INPUT2 + OUTPUT2 = INPUT1 * INPUT2 + + RETURN + END SUBROUTINE TESTSUB + + SUBROUTINE TESTSUB2(OUTPUT) + IMPLICIT NONE + INTEGER, PARAMETER :: N = 10 ! Array dimension + REAL, INTENT(OUT) :: OUTPUT(N) + INTEGER :: I + + DO I = 1, N + OUTPUT(I) = I * 2.0 + END DO + + RETURN + END diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/f77fixedform.f95 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/f77fixedform.f95 new file mode 100644 index 0000000000000000000000000000000000000000..e47a13f7e851969f30aa38344377c5ec90708839 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/f77fixedform.f95 @@ -0,0 +1,5 @@ +C This is an invalid file, but it does compile with -ffixed-form + subroutine mwe( + & x) + real x + end subroutine mwe diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/f90continuation.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/f90continuation.f90 new file mode 100644 index 0000000000000000000000000000000000000000..879e716bbec69e94a28745ecc0d8f9c7a8ea02eb --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/f90continuation.f90 @@ -0,0 +1,9 @@ +SUBROUTINE TESTSUB(INPUT1, & ! Hello +! commenty +INPUT2, OUTPUT1, OUTPUT2) ! more comments + INTEGER, INTENT(IN) :: INPUT1, INPUT2 + INTEGER, INTENT(OUT) :: OUTPUT1, OUTPUT2 + OUTPUT1 = INPUT1 + & + INPUT2 + OUTPUT2 = INPUT1 * INPUT2 +END SUBROUTINE TESTSUB diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/incfile.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/incfile.f90 new file mode 100644 index 0000000000000000000000000000000000000000..276ef3a67352b29d37985529ad550b45f68456f0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/incfile.f90 @@ -0,0 +1,5 @@ +function add(n,m) result(b) + implicit none + include 'AB.inc' + b = n + m +end function add diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/inout.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/inout.f90 new file mode 100644 index 0000000000000000000000000000000000000000..80cdad90cec56de2226979fa0c9b0f9dfa39c7c9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/inout.f90 @@ -0,0 +1,9 @@ +! Check that intent(in out) translates as intent(inout). +! The separation seems to be a common usage. + subroutine foo(x) + implicit none + real(4), intent(in out) :: x + dimension x(3) + x(1) = x(1) + x(2) + x(3) + return + end diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/lower_f2py_fortran.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/lower_f2py_fortran.f90 new file mode 100644 index 0000000000000000000000000000000000000000..1c4b8c192b1b2783a4f5c2275731106c2a6109f2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/lower_f2py_fortran.f90 @@ -0,0 +1,5 @@ +subroutine inquire_next(IU) + IMPLICIT NONE + integer :: IU + !f2py intent(in) IU +end subroutine diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/mod_derived_types.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/mod_derived_types.f90 new file mode 100644 index 0000000000000000000000000000000000000000..7692c82cf42eff432af64f55ebf4b164a280fd2a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/regression/mod_derived_types.f90 @@ -0,0 +1,23 @@ +module mtypes + implicit none + integer, parameter :: value1 = 100 + type :: master_data + integer :: idat = 200 + end type master_data + type(master_data) :: masterdata +end module mtypes + + +subroutine no_type_subroutine(ain, aout) + use mtypes, only: value1 + integer, intent(in) :: ain + integer, intent(out) :: aout + aout = ain + value1 +end subroutine no_type_subroutine + +subroutine type_subroutine(ain, aout) + use mtypes, only: masterdata + integer, intent(in) :: ain + integer, intent(out) :: aout + aout = ain + masterdata%idat +end subroutine type_subroutine \ No newline at end of file diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_character/foo77.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_character/foo77.f new file mode 100644 index 0000000000000000000000000000000000000000..facae1016a39010cca10929837d0a95c44376e21 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_character/foo77.f @@ -0,0 +1,45 @@ + function t0(value) + character value + character t0 + t0 = value + end + function t1(value) + character*1 value + character*1 t1 + t1 = value + end + function t5(value) + character*5 value + character*5 t5 + t5 = value + end + function ts(value) + character*(*) value + character*(*) ts + ts = value + end + + subroutine s0(t0,value) + character value + character t0 +cf2py intent(out) t0 + t0 = value + end + subroutine s1(t1,value) + character*1 value + character*1 t1 +cf2py intent(out) t1 + t1 = value + end + subroutine s5(t5,value) + character*5 value + character*5 t5 +cf2py intent(out) t5 + t5 = value + end + subroutine ss(ts,value) + character*(*) value + character*10 ts +cf2py intent(out) ts + ts = value + end diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_character/foo90.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_character/foo90.f90 new file mode 100644 index 0000000000000000000000000000000000000000..36182bcf2dd71649130f5afe7ef665ac80d64af9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_character/foo90.f90 @@ -0,0 +1,48 @@ +module f90_return_char + contains + function t0(value) + character :: value + character :: t0 + t0 = value + end function t0 + function t1(value) + character(len=1) :: value + character(len=1) :: t1 + t1 = value + end function t1 + function t5(value) + character(len=5) :: value + character(len=5) :: t5 + t5 = value + end function t5 + function ts(value) + character(len=*) :: value + character(len=10) :: ts + ts = value + end function ts + + subroutine s0(t0,value) + character :: value + character :: t0 +!f2py intent(out) t0 + t0 = value + end subroutine s0 + subroutine s1(t1,value) + character(len=1) :: value + character(len=1) :: t1 +!f2py intent(out) t1 + t1 = value + end subroutine s1 + subroutine s5(t5,value) + character(len=5) :: value + character(len=5) :: t5 +!f2py intent(out) t5 + t5 = value + end subroutine s5 + subroutine ss(ts,value) + character(len=*) :: value + character(len=10) :: ts +!f2py intent(out) ts + ts = value + end subroutine ss +end module f90_return_char diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_complex/foo77.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_complex/foo77.f new file mode 100644 index 0000000000000000000000000000000000000000..37a1ec845ecacc7fbc228f1ee5f628ec73075c12 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_complex/foo77.f @@ -0,0 +1,45 @@ + function t0(value) + complex value + complex t0 + t0 = value + end + function t8(value) + complex*8 value + complex*8 t8 + t8 = value + end + function t16(value) + complex*16 value + complex*16 t16 + t16 = value + end + function td(value) + double complex value + double complex td + td = value + end + + subroutine s0(t0,value) + complex value + complex t0 +cf2py intent(out) t0 + t0 = value + end + subroutine s8(t8,value) + complex*8 value + complex*8 t8 +cf2py intent(out) t8 + t8 = value + end + subroutine s16(t16,value) + complex*16 value + complex*16 t16 +cf2py intent(out) t16 + t16 = value + end + subroutine sd(td,value) + double complex value + double complex td +cf2py intent(out) td + td = value + end diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_complex/foo90.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_complex/foo90.f90 new file mode 100644 index 0000000000000000000000000000000000000000..adc27b470538bc663416fb512a29c4b2bbe8d3dd --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_complex/foo90.f90 @@ -0,0 +1,48 @@ +module f90_return_complex + contains + function t0(value) + complex :: value + complex :: t0 + t0 = value + end function t0 + function t8(value) + complex(kind=4) :: value + complex(kind=4) :: t8 + t8 = value + end function t8 + function t16(value) + complex(kind=8) :: value + complex(kind=8) :: t16 + t16 = value + end function t16 + function td(value) + double complex :: value + double complex :: td + td = value + end function td + + subroutine s0(t0,value) + complex :: value + complex :: t0 +!f2py intent(out) t0 + t0 = value + end subroutine s0 + subroutine s8(t8,value) + complex(kind=4) :: value + complex(kind=4) :: t8 +!f2py intent(out) t8 + t8 = value + end subroutine s8 + subroutine s16(t16,value) + complex(kind=8) :: value + complex(kind=8) :: t16 +!f2py intent(out) t16 + t16 = value + end subroutine s16 + subroutine sd(td,value) + double complex :: value + double complex :: td +!f2py intent(out) td + td = value + end subroutine sd +end module f90_return_complex diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_integer/foo77.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_integer/foo77.f new file mode 100644 index 0000000000000000000000000000000000000000..1ab895b9ac340ca91c5d3a4080334bab9f033a55 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_integer/foo77.f @@ -0,0 +1,56 @@ + function t0(value) + integer value + integer t0 + t0 = value + end + function t1(value) + integer*1 value + integer*1 t1 + t1 = value + end + function t2(value) + integer*2 value + integer*2 t2 + t2 = value + end + function t4(value) + integer*4 value + integer*4 t4 + t4 = value + end + function t8(value) + integer*8 value + integer*8 t8 + t8 = value + end + + subroutine s0(t0,value) + integer value + integer t0 +cf2py intent(out) t0 + t0 = value + end + subroutine s1(t1,value) + integer*1 value + integer*1 t1 +cf2py intent(out) t1 + t1 = value + end + subroutine s2(t2,value) + integer*2 value + integer*2 t2 +cf2py intent(out) t2 + t2 = value + end + subroutine s4(t4,value) + integer*4 value + integer*4 t4 +cf2py intent(out) t4 + t4 = value + end + subroutine s8(t8,value) + integer*8 value + integer*8 t8 +cf2py intent(out) t8 + t8 = value + end diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_integer/foo90.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_integer/foo90.f90 new file mode 100644 index 0000000000000000000000000000000000000000..ba9249aa20f941dbf00f060ad5d7e8820745b0f4 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_integer/foo90.f90 @@ -0,0 +1,59 @@ +module f90_return_integer + contains + function t0(value) + integer :: value + integer :: t0 + t0 = value + end function t0 + function t1(value) + integer(kind=1) :: value + integer(kind=1) :: t1 + t1 = value + end function t1 + function t2(value) + integer(kind=2) :: value + integer(kind=2) :: t2 + t2 = value + end function t2 + function t4(value) + integer(kind=4) :: value + integer(kind=4) :: t4 + t4 = value + end function t4 + function t8(value) + integer(kind=8) :: value + integer(kind=8) :: t8 + t8 = value + end function t8 + + subroutine s0(t0,value) + integer :: value + integer :: t0 +!f2py intent(out) t0 + t0 = value + end subroutine s0 + subroutine s1(t1,value) + integer(kind=1) :: value + integer(kind=1) :: t1 +!f2py intent(out) t1 + t1 = value + end subroutine s1 + subroutine s2(t2,value) + integer(kind=2) :: value + integer(kind=2) :: t2 +!f2py intent(out) t2 + t2 = value + end subroutine s2 + subroutine s4(t4,value) + integer(kind=4) :: value + integer(kind=4) :: t4 +!f2py intent(out) t4 + t4 = value + end subroutine s4 + subroutine s8(t8,value) + integer(kind=8) :: value + integer(kind=8) :: t8 +!f2py intent(out) t8 + t8 = value + end subroutine s8 +end module f90_return_integer diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_logical/foo77.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_logical/foo77.f new file mode 100644 index 0000000000000000000000000000000000000000..ef530145fedf8b5cf3a05bdf0a46a4e22150007b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_logical/foo77.f @@ -0,0 +1,56 @@ + function t0(value) + logical value + logical t0 + t0 = value + end + function t1(value) + logical*1 value + logical*1 t1 + t1 = value + end + function t2(value) + logical*2 value + logical*2 t2 + t2 = value + end + function t4(value) + logical*4 value + logical*4 t4 + t4 = value + end +c function t8(value) +c logical*8 value +c logical*8 t8 +c t8 = value +c end + + subroutine s0(t0,value) + logical value + logical t0 +cf2py intent(out) t0 + t0 = value + end + subroutine s1(t1,value) + logical*1 value + logical*1 t1 +cf2py intent(out) t1 + t1 = value + end + subroutine s2(t2,value) + logical*2 value + logical*2 t2 +cf2py intent(out) t2 + t2 = value + end + subroutine s4(t4,value) + logical*4 value + logical*4 t4 +cf2py intent(out) t4 + t4 = value + end +c subroutine s8(t8,value) +c logical*8 value +c logical*8 t8 +cf2py intent(out) t8 +c t8 = value +c end diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_logical/foo90.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_logical/foo90.f90 new file mode 100644 index 0000000000000000000000000000000000000000..a4526468e3719140f0ed7d50a5f3a31d78d1d2de --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_logical/foo90.f90 @@ -0,0 +1,59 @@ +module f90_return_logical + contains + function t0(value) + logical :: value + logical :: t0 + t0 = value + end function t0 + function t1(value) + logical(kind=1) :: value + logical(kind=1) :: t1 + t1 = value + end function t1 + function t2(value) + logical(kind=2) :: value + logical(kind=2) :: t2 + t2 = value + end function t2 + function t4(value) + logical(kind=4) :: value + logical(kind=4) :: t4 + t4 = value + end function t4 + function t8(value) + logical(kind=8) :: value + logical(kind=8) :: t8 + t8 = value + end function t8 + + subroutine s0(t0,value) + logical :: value + logical :: t0 +!f2py intent(out) t0 + t0 = value + end subroutine s0 + subroutine s1(t1,value) + logical(kind=1) :: value + logical(kind=1) :: t1 +!f2py intent(out) t1 + t1 = value + end subroutine s1 + subroutine s2(t2,value) + logical(kind=2) :: value + logical(kind=2) :: t2 +!f2py intent(out) t2 + t2 = value + end subroutine s2 + subroutine s4(t4,value) + logical(kind=4) :: value + logical(kind=4) :: t4 +!f2py intent(out) t4 + t4 = value + end subroutine s4 + subroutine s8(t8,value) + logical(kind=8) :: value + logical(kind=8) :: t8 +!f2py intent(out) t8 + t8 = value + end subroutine s8 +end module f90_return_logical diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_real/foo77.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_real/foo77.f new file mode 100644 index 0000000000000000000000000000000000000000..bf43dbf11773d8282f3b9a7d7c4ba9da23ee6f27 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_real/foo77.f @@ -0,0 +1,45 @@ + function t0(value) + real value + real t0 + t0 = value + end + function t4(value) + real*4 value + real*4 t4 + t4 = value + end + function t8(value) + real*8 value + real*8 t8 + t8 = value + end + function td(value) + double precision value + double precision td + td = value + end + + subroutine s0(t0,value) + real value + real t0 +cf2py intent(out) t0 + t0 = value + end + subroutine s4(t4,value) + real*4 value + real*4 t4 +cf2py intent(out) t4 + t4 = value + end + subroutine s8(t8,value) + real*8 value + real*8 t8 +cf2py intent(out) t8 + t8 = value + end + subroutine sd(td,value) + double precision value + double precision td +cf2py intent(out) td + td = value + end diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_real/foo90.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_real/foo90.f90 new file mode 100644 index 0000000000000000000000000000000000000000..df9719980f2861678d5c1e4b0529a9eb0e375021 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/return_real/foo90.f90 @@ -0,0 +1,48 @@ +module f90_return_real + contains + function t0(value) + real :: value + real :: t0 + t0 = value + end function t0 + function t4(value) + real(kind=4) :: value + real(kind=4) :: t4 + t4 = value + end function t4 + function t8(value) + real(kind=8) :: value + real(kind=8) :: t8 + t8 = value + end function t8 + function td(value) + double precision :: value + double precision :: td + td = value + end function td + + subroutine s0(t0,value) + real :: value + real :: t0 +!f2py intent(out) t0 + t0 = value + end subroutine s0 + subroutine s4(t4,value) + real(kind=4) :: value + real(kind=4) :: t4 +!f2py intent(out) t4 + t4 = value + end subroutine s4 + subroutine s8(t8,value) + real(kind=8) :: value + real(kind=8) :: t8 +!f2py intent(out) t8 + t8 = value + end subroutine s8 + subroutine sd(td,value) + double precision :: value + double precision :: td +!f2py intent(out) td + td = value + end subroutine sd +end module f90_return_real diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/routines/funcfortranname.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/routines/funcfortranname.f new file mode 100644 index 0000000000000000000000000000000000000000..89be972d341966170c9f1a36af1f098e62dd4174 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/routines/funcfortranname.f @@ -0,0 +1,5 @@ + REAL*8 FUNCTION FUNCFORTRANNAME(A,B) + REAL*8 A, B + FUNCFORTRANNAME = A + B + RETURN + END FUNCTION diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/routines/funcfortranname.pyf b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/routines/funcfortranname.pyf new file mode 100644 index 0000000000000000000000000000000000000000..8730ca6a67edd4dea8df456369e5f8ef4cb5f831 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/routines/funcfortranname.pyf @@ -0,0 +1,11 @@ +python module funcfortranname ! in + interface ! in :funcfortranname + function funcfortranname_default(a,b) ! in :funcfortranname:funcfortranname.f + fortranname funcfortranname + real*8 :: a + real*8 :: b + real*8 :: funcfortranname_default + real*8, intent(out) :: funcfortranname + end function funcfortranname_default + end interface +end python module funcfortranname diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/routines/subrout.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/routines/subrout.f new file mode 100644 index 0000000000000000000000000000000000000000..1d1eeaeb5a4588141e15c19b3b8e70fef6425f1a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/routines/subrout.f @@ -0,0 +1,4 @@ + SUBROUTINE SUBROUT(A,B,C) + REAL*8 A, B, C + C = A + B + END SUBROUTINE diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/routines/subrout.pyf b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/routines/subrout.pyf new file mode 100644 index 0000000000000000000000000000000000000000..e27cbe1c7455d47ea312966c997bbcf5f690be74 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/routines/subrout.pyf @@ -0,0 +1,10 @@ +python module subrout ! in + interface ! in :subrout + subroutine subrout_default(a,b,c) ! in :subrout:subrout.f + fortranname subrout + real*8 :: a + real*8 :: b + real*8, intent(out) :: c + end subroutine subrout_default + end interface +end python module subrout diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/size/foo.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/size/foo.f90 new file mode 100644 index 0000000000000000000000000000000000000000..5b66f8c430d79a8438ad062466a97cf8c00dfb16 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/size/foo.f90 @@ -0,0 +1,44 @@ + +subroutine foo(a, n, m, b) + implicit none + + real, intent(in) :: a(n, m) + integer, intent(in) :: n, m + real, intent(out) :: b(size(a, 1)) + + integer :: i + + do i = 1, size(b) + b(i) = sum(a(i,:)) + enddo +end subroutine + +subroutine trans(x,y) + implicit none + real, intent(in), dimension(:,:) :: x + real, intent(out), dimension( size(x,2), size(x,1) ) :: y + integer :: N, M, i, j + N = size(x,1) + M = size(x,2) + DO i=1,N + do j=1,M + y(j,i) = x(i,j) + END DO + END DO +end subroutine trans + +subroutine flatten(x,y) + implicit none + real, intent(in), dimension(:,:) :: x + real, intent(out), dimension( size(x) ) :: y + integer :: N, M, i, j, k + N = size(x,1) + M = size(x,2) + k = 1 + DO i=1,N + do j=1,M + y(k) = x(i,j) + k = k + 1 + END DO + END DO +end subroutine flatten diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/char.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/char.f90 new file mode 100644 index 0000000000000000000000000000000000000000..bb7985ce50f2aa252aaca96aba6ef5d5f5d51844 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/char.f90 @@ -0,0 +1,29 @@ +MODULE char_test + +CONTAINS + +SUBROUTINE change_strings(strings, n_strs, out_strings) + IMPLICIT NONE + + ! Inputs + INTEGER, INTENT(IN) :: n_strs + CHARACTER, INTENT(IN), DIMENSION(2,n_strs) :: strings + CHARACTER, INTENT(OUT), DIMENSION(2,n_strs) :: out_strings + +!f2py INTEGER, INTENT(IN) :: n_strs +!f2py CHARACTER, INTENT(IN), DIMENSION(2,n_strs) :: strings +!f2py CHARACTER, INTENT(OUT), DIMENSION(2,n_strs) :: strings + + ! Misc. + INTEGER*4 :: j + + + DO j=1, n_strs + out_strings(1,j) = strings(1,j) + out_strings(2,j) = 'A' + END DO + +END SUBROUTINE change_strings + +END MODULE char_test + diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/fixed_string.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/fixed_string.f90 new file mode 100644 index 0000000000000000000000000000000000000000..7fd1585430fb05f84fb850ef4656d94e8a0804e9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/fixed_string.f90 @@ -0,0 +1,34 @@ +function sint(s) result(i) + implicit none + character(len=*) :: s + integer :: j, i + i = 0 + do j=len(s), 1, -1 + if (.not.((i.eq.0).and.(s(j:j).eq.' '))) then + i = i + ichar(s(j:j)) * 10 ** (j - 1) + endif + end do + return + end function sint + + function test_in_bytes4(a) result (i) + implicit none + integer :: sint + character(len=4) :: a + integer :: i + i = sint(a) + a(1:1) = 'A' + return + end function test_in_bytes4 + + function test_inout_bytes4(a) result (i) + implicit none + integer :: sint + character(len=4), intent(inout) :: a + integer :: i + if (a(1:1).ne.' ') then + a(1:1) = 'E' + endif + i = sint(a) + return + end function test_inout_bytes4 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/gh24008.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/gh24008.f new file mode 100644 index 0000000000000000000000000000000000000000..ab64cf771f68bbcecc8ac2d5d649545fc357e15b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/gh24008.f @@ -0,0 +1,8 @@ + SUBROUTINE GREET(NAME, GREETING) + CHARACTER NAME*(*), GREETING*(*) + CHARACTER*(50) MESSAGE + + MESSAGE = 'Hello, ' // NAME // ', ' // GREETING +c$$$ PRINT *, MESSAGE + + END SUBROUTINE GREET diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/gh24662.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/gh24662.f90 new file mode 100644 index 0000000000000000000000000000000000000000..ca53413cc9b48f1c8d476d329eb4b773695dd08c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/gh24662.f90 @@ -0,0 +1,7 @@ +subroutine string_inout_optional(output) + implicit none + character*(32), optional, intent(inout) :: output + if (present(output)) then + output="output string" + endif +end subroutine diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/gh25286.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/gh25286.f90 new file mode 100644 index 0000000000000000000000000000000000000000..db1c7100d2ab812de5d212c1bbd255cf2ae60be3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/gh25286.f90 @@ -0,0 +1,14 @@ +subroutine charint(trans, info) + character, intent(in) :: trans + integer, intent(out) :: info + if (trans == 'N') then + info = 1 + else if (trans == 'T') then + info = 2 + else if (trans == 'C') then + info = 3 + else + info = -1 + end if + +end subroutine charint diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/gh25286.pyf b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/gh25286.pyf new file mode 100644 index 0000000000000000000000000000000000000000..7b9609071bce3e775703b12c430f411af09e6eee --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/gh25286.pyf @@ -0,0 +1,12 @@ +python module _char_handling_test + interface + subroutine charint(trans, info) + callstatement (*f2py_func)(&trans, &info) + callprotoargument char*, int* + + character, intent(in), check(trans=='N'||trans=='T'||trans=='C') :: trans = 'N' + integer intent(out) :: info + + end subroutine charint + end interface +end python module _char_handling_test diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/gh25286_bc.pyf b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/gh25286_bc.pyf new file mode 100644 index 0000000000000000000000000000000000000000..e7b10fa9215e88e56794e9c73d0b13872cbd953c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/gh25286_bc.pyf @@ -0,0 +1,12 @@ +python module _char_handling_test + interface + subroutine charint(trans, info) + callstatement (*f2py_func)(&trans, &info) + callprotoargument char*, int* + + character, intent(in), check(*trans=='N'||*trans=='T'||*trans=='C') :: trans = 'N' + integer intent(out) :: info + + end subroutine charint + end interface +end python module _char_handling_test diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/scalar_string.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/scalar_string.f90 new file mode 100644 index 0000000000000000000000000000000000000000..f8f076172ab48ca4834d631b362f47ca374db5e4 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/scalar_string.f90 @@ -0,0 +1,9 @@ +MODULE string_test + + character(len=8) :: string + character string77 * 8 + + character(len=12), dimension(5,7) :: strarr + character strarr77(5,7) * 12 + +END MODULE string_test diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/string.f b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/string.f new file mode 100644 index 0000000000000000000000000000000000000000..5210ca4dc054de60488e45baa12b6c8bc89fc9eb --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/string/string.f @@ -0,0 +1,12 @@ +C FILE: STRING.F + SUBROUTINE FOO(A,B,C,D) + CHARACTER*5 A, B + CHARACTER*(*) C,D +Cf2py intent(in) a,c +Cf2py intent(inout) b,d + A(1:1) = 'A' + B(1:1) = 'B' + C(1:1) = 'C' + D(1:1) = 'D' + END +C END OF FILE STRING.F diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/value_attrspec/gh21665.f90 b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/value_attrspec/gh21665.f90 new file mode 100644 index 0000000000000000000000000000000000000000..7d9dc0fd4acbc081f55edfafb5dea981dcf279d5 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/src/value_attrspec/gh21665.f90 @@ -0,0 +1,9 @@ +module fortfuncs + implicit none +contains + subroutine square(x,y) + integer, intent(in), value :: x + integer, intent(out) :: y + y = x*x + end subroutine square +end module fortfuncs diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_abstract_interface.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_abstract_interface.py new file mode 100644 index 0000000000000000000000000000000000000000..21e77db3e8d3f0894c4c816454d49cb9d9572c5a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_abstract_interface.py @@ -0,0 +1,26 @@ +import pytest + +from numpy.f2py import crackfortran +from numpy.testing import IS_WASM + +from . import util + + +@pytest.mark.skipif(IS_WASM, reason="Cannot start subprocess") +@pytest.mark.slow +class TestAbstractInterface(util.F2PyTest): + sources = [util.getpath("tests", "src", "abstract_interface", "foo.f90")] + + skip = ["add1", "add2"] + + def test_abstract_interface(self): + assert self.module.ops_module.foo(3, 5) == (8, 13) + + def test_parse_abstract_interface(self): + # Test gh18403 + fpath = util.getpath("tests", "src", "abstract_interface", + "gh18403_mod.f90") + mod = crackfortran.crackfortran([str(fpath)]) + assert len(mod) == 1 + assert len(mod[0]["body"]) == 1 + assert mod[0]["body"][0]["block"] == "abstract interface" diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_array_from_pyobj.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_array_from_pyobj.py new file mode 100644 index 0000000000000000000000000000000000000000..15383e9431cc982f44c6a33f0f21f30850777727 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_array_from_pyobj.py @@ -0,0 +1,678 @@ +import copy +import platform +import sys +from pathlib import Path + +import pytest + +import numpy as np +from numpy._core._type_aliases import c_names_dict as _c_names_dict + +from . import util + +wrap = None + +# Extend core typeinfo with CHARACTER to test dtype('c') +c_names_dict = dict( + CHARACTER=np.dtype("c"), + **_c_names_dict +) + + +def get_testdir(): + testroot = Path(__file__).resolve().parent / "src" + return testroot / "array_from_pyobj" + +def setup_module(): + """ + Build the required testing extension module + + """ + global wrap + + if wrap is None: + src = [ + get_testdir() / "wrapmodule.c", + ] + wrap = util.build_meson(src, module_name="test_array_from_pyobj_ext") + + +def flags_info(arr): + flags = wrap.array_attrs(arr)[6] + return flags2names(flags) + + +def flags2names(flags): + info = [] + for flagname in [ + "CONTIGUOUS", + "FORTRAN", + "OWNDATA", + "ENSURECOPY", + "ENSUREARRAY", + "ALIGNED", + "NOTSWAPPED", + "WRITEABLE", + "WRITEBACKIFCOPY", + "UPDATEIFCOPY", + "BEHAVED", + "BEHAVED_RO", + "CARRAY", + "FARRAY", + ]: + if abs(flags) & getattr(wrap, flagname, 0): + info.append(flagname) + return info + + +class Intent: + def __init__(self, intent_list=[]): + self.intent_list = intent_list[:] + flags = 0 + for i in intent_list: + if i == "optional": + flags |= wrap.F2PY_OPTIONAL + else: + flags |= getattr(wrap, "F2PY_INTENT_" + i.upper()) + self.flags = flags + + def __getattr__(self, name): + name = name.lower() + if name == "in_": + name = "in" + return self.__class__(self.intent_list + [name]) + + def __str__(self): + return f"intent({','.join(self.intent_list)})" + + def __repr__(self): + return f"Intent({self.intent_list!r})" + + def is_intent(self, *names): + return all(name in self.intent_list for name in names) + + def is_intent_exact(self, *names): + return len(self.intent_list) == len(names) and self.is_intent(*names) + + +intent = Intent() + +_type_names = [ + "BOOL", + "BYTE", + "UBYTE", + "SHORT", + "USHORT", + "INT", + "UINT", + "LONG", + "ULONG", + "LONGLONG", + "ULONGLONG", + "FLOAT", + "DOUBLE", + "CFLOAT", + "STRING1", + "STRING5", + "CHARACTER", +] + +_cast_dict = {"BOOL": ["BOOL"]} +_cast_dict["BYTE"] = _cast_dict["BOOL"] + ["BYTE"] +_cast_dict["UBYTE"] = _cast_dict["BOOL"] + ["UBYTE"] +_cast_dict["BYTE"] = ["BYTE"] +_cast_dict["UBYTE"] = ["UBYTE"] +_cast_dict["SHORT"] = _cast_dict["BYTE"] + ["UBYTE", "SHORT"] +_cast_dict["USHORT"] = _cast_dict["UBYTE"] + ["BYTE", "USHORT"] +_cast_dict["INT"] = _cast_dict["SHORT"] + ["USHORT", "INT"] +_cast_dict["UINT"] = _cast_dict["USHORT"] + ["SHORT", "UINT"] + +_cast_dict["LONG"] = _cast_dict["INT"] + ["LONG"] +_cast_dict["ULONG"] = _cast_dict["UINT"] + ["ULONG"] + +_cast_dict["LONGLONG"] = _cast_dict["LONG"] + ["LONGLONG"] +_cast_dict["ULONGLONG"] = _cast_dict["ULONG"] + ["ULONGLONG"] + +_cast_dict["FLOAT"] = _cast_dict["SHORT"] + ["USHORT", "FLOAT"] +_cast_dict["DOUBLE"] = _cast_dict["INT"] + ["UINT", "FLOAT", "DOUBLE"] + +_cast_dict["CFLOAT"] = _cast_dict["FLOAT"] + ["CFLOAT"] + +_cast_dict['STRING1'] = ['STRING1'] +_cast_dict['STRING5'] = ['STRING5'] +_cast_dict['CHARACTER'] = ['CHARACTER'] + +# 32 bit system malloc typically does not provide the alignment required by +# 16 byte long double types this means the inout intent cannot be satisfied +# and several tests fail as the alignment flag can be randomly true or false +# when numpy gains an aligned allocator the tests could be enabled again +# +# Furthermore, on macOS ARM64 and AIX, LONGDOUBLE is an alias for DOUBLE. +if ((np.intp().dtype.itemsize != 4 or np.clongdouble().dtype.alignment <= 8) + and sys.platform not in ["win32", "aix"] + and (platform.system(), platform.processor()) != ("Darwin", "arm")): + _type_names.extend(["LONGDOUBLE", "CDOUBLE", "CLONGDOUBLE"]) + _cast_dict["LONGDOUBLE"] = _cast_dict["LONG"] + [ + "ULONG", + "FLOAT", + "DOUBLE", + "LONGDOUBLE", + ] + _cast_dict["CLONGDOUBLE"] = _cast_dict["LONGDOUBLE"] + [ + "CFLOAT", + "CDOUBLE", + "CLONGDOUBLE", + ] + _cast_dict["CDOUBLE"] = _cast_dict["DOUBLE"] + ["CFLOAT", "CDOUBLE"] + + +class Type: + _type_cache = {} + + def __new__(cls, name): + if isinstance(name, np.dtype): + dtype0 = name + name = None + for n, i in c_names_dict.items(): + if not isinstance(i, type) and dtype0.type is i.type: + name = n + break + obj = cls._type_cache.get(name.upper(), None) + if obj is not None: + return obj + obj = object.__new__(cls) + obj._init(name) + cls._type_cache[name.upper()] = obj + return obj + + def _init(self, name): + self.NAME = name.upper() + + if self.NAME == 'CHARACTER': + info = c_names_dict[self.NAME] + self.type_num = wrap.NPY_STRING + self.elsize = 1 + self.dtype = np.dtype('c') + elif self.NAME.startswith('STRING'): + info = c_names_dict[self.NAME[:6]] + self.type_num = wrap.NPY_STRING + self.elsize = int(self.NAME[6:] or 0) + self.dtype = np.dtype(f'S{self.elsize}') + else: + info = c_names_dict[self.NAME] + self.type_num = getattr(wrap, 'NPY_' + self.NAME) + self.elsize = info.itemsize + self.dtype = np.dtype(info.type) + + assert self.type_num == info.num + self.type = info.type + self.dtypechar = info.char + + def __repr__(self): + return (f"Type({self.NAME})|type_num={self.type_num}," + f" dtype={self.dtype}," + f" type={self.type}, elsize={self.elsize}," + f" dtypechar={self.dtypechar}") + + def cast_types(self): + return [self.__class__(_m) for _m in _cast_dict[self.NAME]] + + def all_types(self): + return [self.__class__(_m) for _m in _type_names] + + def smaller_types(self): + bits = c_names_dict[self.NAME].alignment + types = [] + for name in _type_names: + if c_names_dict[name].alignment < bits: + types.append(Type(name)) + return types + + def equal_types(self): + bits = c_names_dict[self.NAME].alignment + types = [] + for name in _type_names: + if name == self.NAME: + continue + if c_names_dict[name].alignment == bits: + types.append(Type(name)) + return types + + def larger_types(self): + bits = c_names_dict[self.NAME].alignment + types = [] + for name in _type_names: + if c_names_dict[name].alignment > bits: + types.append(Type(name)) + return types + + +class Array: + + def __repr__(self): + return (f'Array({self.type}, {self.dims}, {self.intent},' + f' {self.obj})|arr={self.arr}') + + def __init__(self, typ, dims, intent, obj): + self.type = typ + self.dims = dims + self.intent = intent + self.obj_copy = copy.deepcopy(obj) + self.obj = obj + + # arr.dtypechar may be different from typ.dtypechar + self.arr = wrap.call(typ.type_num, + typ.elsize, + dims, intent.flags, obj) + + assert isinstance(self.arr, np.ndarray) + + self.arr_attr = wrap.array_attrs(self.arr) + + if len(dims) > 1: + if self.intent.is_intent("c"): + assert (intent.flags & wrap.F2PY_INTENT_C) + assert not self.arr.flags["FORTRAN"] + assert self.arr.flags["CONTIGUOUS"] + assert (not self.arr_attr[6] & wrap.FORTRAN) + else: + assert (not intent.flags & wrap.F2PY_INTENT_C) + assert self.arr.flags["FORTRAN"] + assert not self.arr.flags["CONTIGUOUS"] + assert (self.arr_attr[6] & wrap.FORTRAN) + + if obj is None: + self.pyarr = None + self.pyarr_attr = None + return + + if intent.is_intent("cache"): + assert isinstance(obj, np.ndarray), repr(type(obj)) + self.pyarr = np.array(obj).reshape(*dims).copy() + else: + self.pyarr = np.array( + np.array(obj, dtype=typ.dtypechar).reshape(*dims), + order=(self.intent.is_intent("c") and "C") or "F", + ) + assert self.pyarr.dtype == typ + self.pyarr.setflags(write=self.arr.flags["WRITEABLE"]) + assert self.pyarr.flags["OWNDATA"], (obj, intent) + self.pyarr_attr = wrap.array_attrs(self.pyarr) + + if len(dims) > 1: + if self.intent.is_intent("c"): + assert not self.pyarr.flags["FORTRAN"] + assert self.pyarr.flags["CONTIGUOUS"] + assert (not self.pyarr_attr[6] & wrap.FORTRAN) + else: + assert self.pyarr.flags["FORTRAN"] + assert not self.pyarr.flags["CONTIGUOUS"] + assert (self.pyarr_attr[6] & wrap.FORTRAN) + + assert self.arr_attr[1] == self.pyarr_attr[1] # nd + assert self.arr_attr[2] == self.pyarr_attr[2] # dimensions + if self.arr_attr[1] <= 1: + assert self.arr_attr[3] == self.pyarr_attr[3], repr(( + self.arr_attr[3], + self.pyarr_attr[3], + self.arr.tobytes(), + self.pyarr.tobytes(), + )) # strides + assert self.arr_attr[5][-2:] == self.pyarr_attr[5][-2:], repr(( + self.arr_attr[5], self.pyarr_attr[5] + )) # descr + assert self.arr_attr[6] == self.pyarr_attr[6], repr(( + self.arr_attr[6], + self.pyarr_attr[6], + flags2names(0 * self.arr_attr[6] - self.pyarr_attr[6]), + flags2names(self.arr_attr[6]), + intent, + )) # flags + + if intent.is_intent("cache"): + assert self.arr_attr[5][3] >= self.type.elsize + else: + assert self.arr_attr[5][3] == self.type.elsize + assert (self.arr_equal(self.pyarr, self.arr)) + + if isinstance(self.obj, np.ndarray): + if typ.elsize == Type(obj.dtype).elsize: + if not intent.is_intent("copy") and self.arr_attr[1] <= 1: + assert self.has_shared_memory() + + def arr_equal(self, arr1, arr2): + if arr1.shape != arr2.shape: + return False + return (arr1 == arr2).all() + + def __str__(self): + return str(self.arr) + + def has_shared_memory(self): + """Check that created array shares data with input array.""" + if self.obj is self.arr: + return True + if not isinstance(self.obj, np.ndarray): + return False + obj_attr = wrap.array_attrs(self.obj) + return obj_attr[0] == self.arr_attr[0] + + +class TestIntent: + def test_in_out(self): + assert str(intent.in_.out) == "intent(in,out)" + assert intent.in_.c.is_intent("c") + assert not intent.in_.c.is_intent_exact("c") + assert intent.in_.c.is_intent_exact("c", "in") + assert intent.in_.c.is_intent_exact("in", "c") + assert not intent.in_.is_intent("c") + + +class TestSharedMemory: + + @pytest.fixture(autouse=True, scope="class", params=_type_names) + def setup_type(self, request): + request.cls.type = Type(request.param) + request.cls.array = lambda self, dims, intent, obj: Array( + Type(request.param), dims, intent, obj) + + @property + def num2seq(self): + if self.type.NAME.startswith('STRING'): + elsize = self.type.elsize + return ['1' * elsize, '2' * elsize] + return [1, 2] + + @property + def num23seq(self): + if self.type.NAME.startswith('STRING'): + elsize = self.type.elsize + return [['1' * elsize, '2' * elsize, '3' * elsize], + ['4' * elsize, '5' * elsize, '6' * elsize]] + return [[1, 2, 3], [4, 5, 6]] + + def test_in_from_2seq(self): + a = self.array([2], intent.in_, self.num2seq) + assert not a.has_shared_memory() + + def test_in_from_2casttype(self): + for t in self.type.cast_types(): + obj = np.array(self.num2seq, dtype=t.dtype) + a = self.array([len(self.num2seq)], intent.in_, obj) + if t.elsize == self.type.elsize: + assert a.has_shared_memory(), repr((self.type.dtype, t.dtype)) + else: + assert not a.has_shared_memory() + + @pytest.mark.parametrize("write", ["w", "ro"]) + @pytest.mark.parametrize("order", ["C", "F"]) + @pytest.mark.parametrize("inp", ["2seq", "23seq"]) + def test_in_nocopy(self, write, order, inp): + """Test if intent(in) array can be passed without copies""" + seq = getattr(self, "num" + inp) + obj = np.array(seq, dtype=self.type.dtype, order=order) + obj.setflags(write=(write == 'w')) + a = self.array(obj.shape, + ((order == 'C' and intent.in_.c) or intent.in_), obj) + assert a.has_shared_memory() + + def test_inout_2seq(self): + obj = np.array(self.num2seq, dtype=self.type.dtype) + a = self.array([len(self.num2seq)], intent.inout, obj) + assert a.has_shared_memory() + + try: + a = self.array([2], intent.in_.inout, self.num2seq) + except TypeError as msg: + if not str(msg).startswith( + "failed to initialize intent(inout|inplace|cache) array"): + raise + else: + raise SystemError("intent(inout) should have failed on sequence") + + def test_f_inout_23seq(self): + obj = np.array(self.num23seq, dtype=self.type.dtype, order="F") + shape = (len(self.num23seq), len(self.num23seq[0])) + a = self.array(shape, intent.in_.inout, obj) + assert a.has_shared_memory() + + obj = np.array(self.num23seq, dtype=self.type.dtype, order="C") + shape = (len(self.num23seq), len(self.num23seq[0])) + try: + a = self.array(shape, intent.in_.inout, obj) + except ValueError as msg: + if not str(msg).startswith( + "failed to initialize intent(inout) array"): + raise + else: + raise SystemError( + "intent(inout) should have failed on improper array") + + def test_c_inout_23seq(self): + obj = np.array(self.num23seq, dtype=self.type.dtype) + shape = (len(self.num23seq), len(self.num23seq[0])) + a = self.array(shape, intent.in_.c.inout, obj) + assert a.has_shared_memory() + + def test_in_copy_from_2casttype(self): + for t in self.type.cast_types(): + obj = np.array(self.num2seq, dtype=t.dtype) + a = self.array([len(self.num2seq)], intent.in_.copy, obj) + assert not a.has_shared_memory() + + def test_c_in_from_23seq(self): + a = self.array( + [len(self.num23seq), len(self.num23seq[0])], intent.in_, + self.num23seq) + assert not a.has_shared_memory() + + def test_in_from_23casttype(self): + for t in self.type.cast_types(): + obj = np.array(self.num23seq, dtype=t.dtype) + a = self.array( + [len(self.num23seq), len(self.num23seq[0])], intent.in_, obj) + assert not a.has_shared_memory() + + def test_f_in_from_23casttype(self): + for t in self.type.cast_types(): + obj = np.array(self.num23seq, dtype=t.dtype, order="F") + a = self.array( + [len(self.num23seq), len(self.num23seq[0])], intent.in_, obj) + if t.elsize == self.type.elsize: + assert a.has_shared_memory() + else: + assert not a.has_shared_memory() + + def test_c_in_from_23casttype(self): + for t in self.type.cast_types(): + obj = np.array(self.num23seq, dtype=t.dtype) + a = self.array( + [len(self.num23seq), len(self.num23seq[0])], intent.in_.c, obj) + if t.elsize == self.type.elsize: + assert a.has_shared_memory() + else: + assert not a.has_shared_memory() + + def test_f_copy_in_from_23casttype(self): + for t in self.type.cast_types(): + obj = np.array(self.num23seq, dtype=t.dtype, order="F") + a = self.array( + [len(self.num23seq), len(self.num23seq[0])], intent.in_.copy, + obj) + assert not a.has_shared_memory() + + def test_c_copy_in_from_23casttype(self): + for t in self.type.cast_types(): + obj = np.array(self.num23seq, dtype=t.dtype) + a = self.array( + [len(self.num23seq), len(self.num23seq[0])], intent.in_.c.copy, + obj) + assert not a.has_shared_memory() + + def test_in_cache_from_2casttype(self): + for t in self.type.all_types(): + if t.elsize != self.type.elsize: + continue + obj = np.array(self.num2seq, dtype=t.dtype) + shape = (len(self.num2seq), ) + a = self.array(shape, intent.in_.c.cache, obj) + assert a.has_shared_memory() + + a = self.array(shape, intent.in_.cache, obj) + assert a.has_shared_memory() + + obj = np.array(self.num2seq, dtype=t.dtype, order="F") + a = self.array(shape, intent.in_.c.cache, obj) + assert a.has_shared_memory() + + a = self.array(shape, intent.in_.cache, obj) + assert a.has_shared_memory(), repr(t.dtype) + + try: + a = self.array(shape, intent.in_.cache, obj[::-1]) + except ValueError as msg: + if not str(msg).startswith( + "failed to initialize intent(cache) array"): + raise + else: + raise SystemError( + "intent(cache) should have failed on multisegmented array") + + def test_in_cache_from_2casttype_failure(self): + for t in self.type.all_types(): + if t.NAME == 'STRING': + # string elsize is 0, so skipping the test + continue + if t.elsize >= self.type.elsize: + continue + is_int = np.issubdtype(t.dtype, np.integer) + if is_int and int(self.num2seq[0]) > np.iinfo(t.dtype).max: + # skip test if num2seq would trigger an overflow error + continue + obj = np.array(self.num2seq, dtype=t.dtype) + shape = (len(self.num2seq), ) + try: + self.array(shape, intent.in_.cache, obj) # Should succeed + except ValueError as msg: + if not str(msg).startswith( + "failed to initialize intent(cache) array"): + raise + else: + raise SystemError( + "intent(cache) should have failed on smaller array") + + def test_cache_hidden(self): + shape = (2, ) + a = self.array(shape, intent.cache.hide, None) + assert a.arr.shape == shape + + shape = (2, 3) + a = self.array(shape, intent.cache.hide, None) + assert a.arr.shape == shape + + shape = (-1, 3) + try: + a = self.array(shape, intent.cache.hide, None) + except ValueError as msg: + if not str(msg).startswith( + "failed to create intent(cache|hide)|optional array"): + raise + else: + raise SystemError( + "intent(cache) should have failed on undefined dimensions") + + def test_hidden(self): + shape = (2, ) + a = self.array(shape, intent.hide, None) + assert a.arr.shape == shape + assert a.arr_equal(a.arr, np.zeros(shape, dtype=self.type.dtype)) + + shape = (2, 3) + a = self.array(shape, intent.hide, None) + assert a.arr.shape == shape + assert a.arr_equal(a.arr, np.zeros(shape, dtype=self.type.dtype)) + assert a.arr.flags["FORTRAN"] and not a.arr.flags["CONTIGUOUS"] + + shape = (2, 3) + a = self.array(shape, intent.c.hide, None) + assert a.arr.shape == shape + assert a.arr_equal(a.arr, np.zeros(shape, dtype=self.type.dtype)) + assert not a.arr.flags["FORTRAN"] and a.arr.flags["CONTIGUOUS"] + + shape = (-1, 3) + try: + a = self.array(shape, intent.hide, None) + except ValueError as msg: + if not str(msg).startswith( + "failed to create intent(cache|hide)|optional array"): + raise + else: + raise SystemError( + "intent(hide) should have failed on undefined dimensions") + + def test_optional_none(self): + shape = (2, ) + a = self.array(shape, intent.optional, None) + assert a.arr.shape == shape + assert a.arr_equal(a.arr, np.zeros(shape, dtype=self.type.dtype)) + + shape = (2, 3) + a = self.array(shape, intent.optional, None) + assert a.arr.shape == shape + assert a.arr_equal(a.arr, np.zeros(shape, dtype=self.type.dtype)) + assert a.arr.flags["FORTRAN"] and not a.arr.flags["CONTIGUOUS"] + + shape = (2, 3) + a = self.array(shape, intent.c.optional, None) + assert a.arr.shape == shape + assert a.arr_equal(a.arr, np.zeros(shape, dtype=self.type.dtype)) + assert not a.arr.flags["FORTRAN"] and a.arr.flags["CONTIGUOUS"] + + def test_optional_from_2seq(self): + obj = self.num2seq + shape = (len(obj), ) + a = self.array(shape, intent.optional, obj) + assert a.arr.shape == shape + assert not a.has_shared_memory() + + def test_optional_from_23seq(self): + obj = self.num23seq + shape = (len(obj), len(obj[0])) + a = self.array(shape, intent.optional, obj) + assert a.arr.shape == shape + assert not a.has_shared_memory() + + a = self.array(shape, intent.optional.c, obj) + assert a.arr.shape == shape + assert not a.has_shared_memory() + + def test_inplace(self): + obj = np.array(self.num23seq, dtype=self.type.dtype) + assert not obj.flags["FORTRAN"] and obj.flags["CONTIGUOUS"] + shape = obj.shape + a = self.array(shape, intent.inplace, obj) + assert obj[1][2] == a.arr[1][2], repr((obj, a.arr)) + a.arr[1][2] = 54 + assert obj[1][2] == a.arr[1][2] == np.array(54, dtype=self.type.dtype) + assert a.arr is obj + assert obj.flags["FORTRAN"] # obj attributes are changed inplace! + assert not obj.flags["CONTIGUOUS"] + + def test_inplace_from_casttype(self): + for t in self.type.cast_types(): + if t is self.type: + continue + obj = np.array(self.num23seq, dtype=t.dtype) + assert obj.dtype.type == t.type + assert obj.dtype.type is not self.type.type + assert not obj.flags["FORTRAN"] and obj.flags["CONTIGUOUS"] + shape = obj.shape + a = self.array(shape, intent.inplace, obj) + assert obj[1][2] == a.arr[1][2], repr((obj, a.arr)) + a.arr[1][2] = 54 + assert obj[1][2] == a.arr[1][2] == np.array(54, + dtype=self.type.dtype) + assert a.arr is obj + assert obj.flags["FORTRAN"] # obj attributes changed inplace! + assert not obj.flags["CONTIGUOUS"] + assert obj.dtype.type is self.type.type # obj changed inplace! diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_assumed_shape.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_assumed_shape.py new file mode 100644 index 0000000000000000000000000000000000000000..cf75644d40ee5f656b064e51a37d11a9618a8669 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_assumed_shape.py @@ -0,0 +1,50 @@ +import os +import tempfile + +import pytest + +from . import util + + +class TestAssumedShapeSumExample(util.F2PyTest): + sources = [ + util.getpath("tests", "src", "assumed_shape", "foo_free.f90"), + util.getpath("tests", "src", "assumed_shape", "foo_use.f90"), + util.getpath("tests", "src", "assumed_shape", "precision.f90"), + util.getpath("tests", "src", "assumed_shape", "foo_mod.f90"), + util.getpath("tests", "src", "assumed_shape", ".f2py_f2cmap"), + ] + + @pytest.mark.slow + def test_all(self): + r = self.module.fsum([1, 2]) + assert r == 3 + r = self.module.sum([1, 2]) + assert r == 3 + r = self.module.sum_with_use([1, 2]) + assert r == 3 + + r = self.module.mod.sum([1, 2]) + assert r == 3 + r = self.module.mod.fsum([1, 2]) + assert r == 3 + + +class TestF2cmapOption(TestAssumedShapeSumExample): + def setup_method(self): + # Use a custom file name for .f2py_f2cmap + self.sources = list(self.sources) + f2cmap_src = self.sources.pop(-1) + + self.f2cmap_file = tempfile.NamedTemporaryFile(delete=False) + with open(f2cmap_src, "rb") as f: + self.f2cmap_file.write(f.read()) + self.f2cmap_file.close() + + self.sources.append(self.f2cmap_file.name) + self.options = ["--f2cmap", self.f2cmap_file.name] + + super().setup_method() + + def teardown_method(self): + os.unlink(self.f2cmap_file.name) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_block_docstring.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_block_docstring.py new file mode 100644 index 0000000000000000000000000000000000000000..ba255a1b473c99723abe9fd419558d29add1dd9f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_block_docstring.py @@ -0,0 +1,20 @@ +import sys + +import pytest + +from numpy.testing import IS_PYPY + +from . import util + + +@pytest.mark.slow +class TestBlockDocString(util.F2PyTest): + sources = [util.getpath("tests", "src", "block_docstring", "foo.f")] + + @pytest.mark.skipif(sys.platform == "win32", + reason="Fails with MinGW64 Gfortran (Issue #9673)") + @pytest.mark.xfail(IS_PYPY, + reason="PyPy cannot modify tp_doc after PyType_Ready") + def test_block_docstring(self): + expected = "bar : 'i'-array(2,3)\n" + assert self.module.block.__doc__ == expected diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_callback.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_callback.py new file mode 100644 index 0000000000000000000000000000000000000000..6614efb16db834d3ab06341e0ba202a8acfdd77d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_callback.py @@ -0,0 +1,263 @@ +import math +import platform +import sys +import textwrap +import threading +import time +import traceback + +import pytest + +import numpy as np +from numpy.testing import IS_PYPY + +from . import util + + +class TestF77Callback(util.F2PyTest): + sources = [util.getpath("tests", "src", "callback", "foo.f")] + + @pytest.mark.parametrize("name", ["t", "t2"]) + @pytest.mark.slow + def test_all(self, name): + self.check_function(name) + + @pytest.mark.xfail(IS_PYPY, + reason="PyPy cannot modify tp_doc after PyType_Ready") + def test_docstring(self): + expected = textwrap.dedent("""\ + a = t(fun,[fun_extra_args]) + + Wrapper for ``t``. + + Parameters + ---------- + fun : call-back function + + Other Parameters + ---------------- + fun_extra_args : input tuple, optional + Default: () + + Returns + ------- + a : int + + Notes + ----- + Call-back functions:: + + def fun(): return a + Return objects: + a : int + """) + assert self.module.t.__doc__ == expected + + def check_function(self, name): + t = getattr(self.module, name) + r = t(lambda: 4) + assert r == 4 + r = t(lambda a: 5, fun_extra_args=(6, )) + assert r == 5 + r = t(lambda a: a, fun_extra_args=(6, )) + assert r == 6 + r = t(lambda a: 5 + a, fun_extra_args=(7, )) + assert r == 12 + r = t(math.degrees, fun_extra_args=(math.pi, )) + assert r == 180 + r = t(math.degrees, fun_extra_args=(math.pi, )) + assert r == 180 + + r = t(self.module.func, fun_extra_args=(6, )) + assert r == 17 + r = t(self.module.func0) + assert r == 11 + r = t(self.module.func0._cpointer) + assert r == 11 + + class A: + def __call__(self): + return 7 + + def mth(self): + return 9 + + a = A() + r = t(a) + assert r == 7 + r = t(a.mth) + assert r == 9 + + @pytest.mark.skipif(sys.platform == 'win32', + reason='Fails with MinGW64 Gfortran (Issue #9673)') + def test_string_callback(self): + def callback(code): + if code == "r": + return 0 + else: + return 1 + + f = self.module.string_callback + r = f(callback) + assert r == 0 + + @pytest.mark.skipif(sys.platform == 'win32', + reason='Fails with MinGW64 Gfortran (Issue #9673)') + def test_string_callback_array(self): + # See gh-10027 + cu1 = np.zeros((1, ), "S8") + cu2 = np.zeros((1, 8), "c") + cu3 = np.array([""], "S8") + + def callback(cu, lencu): + if cu.shape != (lencu,): + return 1 + if cu.dtype != "S8": + return 2 + if not np.all(cu == b""): + return 3 + return 0 + + f = self.module.string_callback_array + for cu in [cu1, cu2, cu3]: + res = f(callback, cu, cu.size) + assert res == 0 + + def test_threadsafety(self): + # Segfaults if the callback handling is not threadsafe + + errors = [] + + def cb(): + # Sleep here to make it more likely for another thread + # to call their callback at the same time. + time.sleep(1e-3) + + # Check reentrancy + r = self.module.t(lambda: 123) + assert r == 123 + + return 42 + + def runner(name): + try: + for j in range(50): + r = self.module.t(cb) + assert r == 42 + self.check_function(name) + except Exception: + errors.append(traceback.format_exc()) + + threads = [ + threading.Thread(target=runner, args=(arg, )) + for arg in ("t", "t2") for n in range(20) + ] + + for t in threads: + t.start() + + for t in threads: + t.join() + + errors = "\n\n".join(errors) + if errors: + raise AssertionError(errors) + + def test_hidden_callback(self): + try: + self.module.hidden_callback(2) + except Exception as msg: + assert str(msg).startswith("Callback global_f not defined") + + try: + self.module.hidden_callback2(2) + except Exception as msg: + assert str(msg).startswith("cb: Callback global_f not defined") + + self.module.global_f = lambda x: x + 1 + r = self.module.hidden_callback(2) + assert r == 3 + + self.module.global_f = lambda x: x + 2 + r = self.module.hidden_callback(2) + assert r == 4 + + del self.module.global_f + try: + self.module.hidden_callback(2) + except Exception as msg: + assert str(msg).startswith("Callback global_f not defined") + + self.module.global_f = lambda x=0: x + 3 + r = self.module.hidden_callback(2) + assert r == 5 + + # reproducer of gh18341 + r = self.module.hidden_callback2(2) + assert r == 3 + + +class TestF77CallbackPythonTLS(TestF77Callback): + """ + Callback tests using Python thread-local storage instead of + compiler-provided + """ + + options = ["-DF2PY_USE_PYTHON_TLS"] + + +class TestF90Callback(util.F2PyTest): + sources = [util.getpath("tests", "src", "callback", "gh17797.f90")] + + @pytest.mark.slow + def test_gh17797(self): + def incr(x): + return x + 123 + + y = np.array([1, 2, 3], dtype=np.int64) + r = self.module.gh17797(incr, y) + assert r == 123 + 1 + 2 + 3 + + +class TestGH18335(util.F2PyTest): + """The reproduction of the reported issue requires specific input that + extensions may break the issue conditions, so the reproducer is + implemented as a separate test class. Do not extend this test with + other tests! + """ + sources = [util.getpath("tests", "src", "callback", "gh18335.f90")] + + @pytest.mark.slow + def test_gh18335(self): + def foo(x): + x[0] += 1 + + r = self.module.gh18335(foo) + assert r == 123 + 1 + + +class TestGH25211(util.F2PyTest): + sources = [util.getpath("tests", "src", "callback", "gh25211.f"), + util.getpath("tests", "src", "callback", "gh25211.pyf")] + module_name = "callback2" + + def test_gh25211(self): + def bar(x): + return x * x + + res = self.module.foo(bar) + assert res == 110 + + +@pytest.mark.slow +@pytest.mark.xfail(condition=(platform.system().lower() == 'darwin'), + run=False, + reason="Callback aborts cause CI failures on macOS") +class TestCBFortranCallstatement(util.F2PyTest): + sources = [util.getpath("tests", "src", "callback", "gh26681.f90")] + options = ['--lower'] + + def test_callstatement_fortran(self): + with pytest.raises(ValueError, match='helpme') as exc: + self.module.mypy_abort = self.module.utils.my_abort + self.module.utils.do_something('helpme') diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_character.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_character.py new file mode 100644 index 0000000000000000000000000000000000000000..74868a6f09f7e9bfd80bb289a4573910698f99d0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_character.py @@ -0,0 +1,641 @@ +import textwrap + +import pytest + +import numpy as np +from numpy.f2py.tests import util +from numpy.testing import assert_array_equal, assert_equal, assert_raises + + +@pytest.mark.slow +class TestCharacterString(util.F2PyTest): + # options = ['--debug-capi', '--build-dir', '/tmp/test-build-f2py'] + suffix = '.f90' + fprefix = 'test_character_string' + length_list = ['1', '3', 'star'] + + code = '' + for length in length_list: + fsuffix = length + clength = {'star': '(*)'}.get(length, length) + + code += textwrap.dedent(f""" + + subroutine {fprefix}_input_{fsuffix}(c, o, n) + character*{clength}, intent(in) :: c + integer n + !f2py integer, depend(c), intent(hide) :: n = slen(c) + integer*1, dimension(n) :: o + !f2py intent(out) o + o = transfer(c, o) + end subroutine {fprefix}_input_{fsuffix} + + subroutine {fprefix}_output_{fsuffix}(c, o, n) + character*{clength}, intent(out) :: c + integer n + integer*1, dimension(n), intent(in) :: o + !f2py integer, depend(o), intent(hide) :: n = len(o) + c = transfer(o, c) + end subroutine {fprefix}_output_{fsuffix} + + subroutine {fprefix}_array_input_{fsuffix}(c, o, m, n) + integer m, i, n + character*{clength}, intent(in), dimension(m) :: c + !f2py integer, depend(c), intent(hide) :: m = len(c) + !f2py integer, depend(c), intent(hide) :: n = f2py_itemsize(c) + integer*1, dimension(m, n), intent(out) :: o + do i=1,m + o(i, :) = transfer(c(i), o(i, :)) + end do + end subroutine {fprefix}_array_input_{fsuffix} + + subroutine {fprefix}_array_output_{fsuffix}(c, o, m, n) + character*{clength}, intent(out), dimension(m) :: c + integer n + integer*1, dimension(m, n), intent(in) :: o + !f2py character(f2py_len=n) :: c + !f2py integer, depend(o), intent(hide) :: m = len(o) + !f2py integer, depend(o), intent(hide) :: n = shape(o, 1) + do i=1,m + c(i) = transfer(o(i, :), c(i)) + end do + end subroutine {fprefix}_array_output_{fsuffix} + + subroutine {fprefix}_2d_array_input_{fsuffix}(c, o, m1, m2, n) + integer m1, m2, i, j, n + character*{clength}, intent(in), dimension(m1, m2) :: c + !f2py integer, depend(c), intent(hide) :: m1 = len(c) + !f2py integer, depend(c), intent(hide) :: m2 = shape(c, 1) + !f2py integer, depend(c), intent(hide) :: n = f2py_itemsize(c) + integer*1, dimension(m1, m2, n), intent(out) :: o + do i=1,m1 + do j=1,m2 + o(i, j, :) = transfer(c(i, j), o(i, j, :)) + end do + end do + end subroutine {fprefix}_2d_array_input_{fsuffix} + """) + + @pytest.mark.parametrize("length", length_list) + def test_input(self, length): + fsuffix = {'(*)': 'star'}.get(length, length) + f = getattr(self.module, self.fprefix + '_input_' + fsuffix) + + a = {'1': 'a', '3': 'abc', 'star': 'abcde' * 3}[length] + + assert_array_equal(f(a), np.array(list(map(ord, a)), dtype='u1')) + + @pytest.mark.parametrize("length", length_list[:-1]) + def test_output(self, length): + fsuffix = length + f = getattr(self.module, self.fprefix + '_output_' + fsuffix) + + a = {'1': 'a', '3': 'abc'}[length] + + assert_array_equal(f(np.array(list(map(ord, a)), dtype='u1')), + a.encode()) + + @pytest.mark.parametrize("length", length_list) + def test_array_input(self, length): + fsuffix = length + f = getattr(self.module, self.fprefix + '_array_input_' + fsuffix) + + a = np.array([{'1': 'a', '3': 'abc', 'star': 'abcde' * 3}[length], + {'1': 'A', '3': 'ABC', 'star': 'ABCDE' * 3}[length], + ], dtype='S') + + expected = np.array([list(s) for s in a], dtype='u1') + assert_array_equal(f(a), expected) + + @pytest.mark.parametrize("length", length_list) + def test_array_output(self, length): + fsuffix = length + f = getattr(self.module, self.fprefix + '_array_output_' + fsuffix) + + expected = np.array( + [{'1': 'a', '3': 'abc', 'star': 'abcde' * 3}[length], + {'1': 'A', '3': 'ABC', 'star': 'ABCDE' * 3}[length]], dtype='S') + + a = np.array([list(s) for s in expected], dtype='u1') + assert_array_equal(f(a), expected) + + @pytest.mark.parametrize("length", length_list) + def test_2d_array_input(self, length): + fsuffix = length + f = getattr(self.module, self.fprefix + '_2d_array_input_' + fsuffix) + + a = np.array([[{'1': 'a', '3': 'abc', 'star': 'abcde' * 3}[length], + {'1': 'A', '3': 'ABC', 'star': 'ABCDE' * 3}[length]], + [{'1': 'f', '3': 'fgh', 'star': 'fghij' * 3}[length], + {'1': 'F', '3': 'FGH', 'star': 'FGHIJ' * 3}[length]]], + dtype='S') + expected = np.array([[list(item) for item in row] for row in a], + dtype='u1', order='F') + assert_array_equal(f(a), expected) + + +class TestCharacter(util.F2PyTest): + # options = ['--debug-capi', '--build-dir', '/tmp/test-build-f2py'] + suffix = '.f90' + fprefix = 'test_character' + + code = textwrap.dedent(f""" + subroutine {fprefix}_input(c, o) + character, intent(in) :: c + integer*1 o + !f2py intent(out) o + o = transfer(c, o) + end subroutine {fprefix}_input + + subroutine {fprefix}_output(c, o) + character :: c + integer*1, intent(in) :: o + !f2py intent(out) c + c = transfer(o, c) + end subroutine {fprefix}_output + + subroutine {fprefix}_input_output(c, o) + character, intent(in) :: c + character o + !f2py intent(out) o + o = c + end subroutine {fprefix}_input_output + + subroutine {fprefix}_inout(c, n) + character :: c, n + !f2py intent(in) n + !f2py intent(inout) c + c = n + end subroutine {fprefix}_inout + + function {fprefix}_return(o) result (c) + character :: c + character, intent(in) :: o + c = transfer(o, c) + end function {fprefix}_return + + subroutine {fprefix}_array_input(c, o) + character, intent(in) :: c(3) + integer*1 o(3) + !f2py intent(out) o + integer i + do i=1,3 + o(i) = transfer(c(i), o(i)) + end do + end subroutine {fprefix}_array_input + + subroutine {fprefix}_2d_array_input(c, o) + character, intent(in) :: c(2, 3) + integer*1 o(2, 3) + !f2py intent(out) o + integer i, j + do i=1,2 + do j=1,3 + o(i, j) = transfer(c(i, j), o(i, j)) + end do + end do + end subroutine {fprefix}_2d_array_input + + subroutine {fprefix}_array_output(c, o) + character :: c(3) + integer*1, intent(in) :: o(3) + !f2py intent(out) c + do i=1,3 + c(i) = transfer(o(i), c(i)) + end do + end subroutine {fprefix}_array_output + + subroutine {fprefix}_array_inout(c, n) + character :: c(3), n(3) + !f2py intent(in) n(3) + !f2py intent(inout) c(3) + do i=1,3 + c(i) = n(i) + end do + end subroutine {fprefix}_array_inout + + subroutine {fprefix}_2d_array_inout(c, n) + character :: c(2, 3), n(2, 3) + !f2py intent(in) n(2, 3) + !f2py intent(inout) c(2. 3) + integer i, j + do i=1,2 + do j=1,3 + c(i, j) = n(i, j) + end do + end do + end subroutine {fprefix}_2d_array_inout + + function {fprefix}_array_return(o) result (c) + character, dimension(3) :: c + character, intent(in) :: o(3) + do i=1,3 + c(i) = o(i) + end do + end function {fprefix}_array_return + + function {fprefix}_optional(o) result (c) + character, intent(in) :: o + !f2py character o = "a" + character :: c + c = o + end function {fprefix}_optional + """) + + @pytest.mark.parametrize("dtype", ['c', 'S1']) + def test_input(self, dtype): + f = getattr(self.module, self.fprefix + '_input') + + assert_equal(f(np.array('a', dtype=dtype)), ord('a')) + assert_equal(f(np.array(b'a', dtype=dtype)), ord('a')) + assert_equal(f(np.array(['a'], dtype=dtype)), ord('a')) + assert_equal(f(np.array('abc', dtype=dtype)), ord('a')) + assert_equal(f(np.array([['a']], dtype=dtype)), ord('a')) + + def test_input_varia(self): + f = getattr(self.module, self.fprefix + '_input') + + assert_equal(f('a'), ord('a')) + assert_equal(f(b'a'), ord(b'a')) + assert_equal(f(''), 0) + assert_equal(f(b''), 0) + assert_equal(f(b'\0'), 0) + assert_equal(f('ab'), ord('a')) + assert_equal(f(b'ab'), ord('a')) + assert_equal(f(['a']), ord('a')) + + assert_equal(f(np.array(b'a')), ord('a')) + assert_equal(f(np.array([b'a'])), ord('a')) + a = np.array('a') + assert_equal(f(a), ord('a')) + a = np.array(['a']) + assert_equal(f(a), ord('a')) + + try: + f([]) + except IndexError as msg: + if not str(msg).endswith(' got 0-list'): + raise + else: + raise SystemError(f'{f.__name__} should have failed on empty list') + + try: + f(97) + except TypeError as msg: + if not str(msg).endswith(' got int instance'): + raise + else: + raise SystemError(f'{f.__name__} should have failed on int value') + + @pytest.mark.parametrize("dtype", ['c', 'S1', 'U1']) + def test_array_input(self, dtype): + f = getattr(self.module, self.fprefix + '_array_input') + + assert_array_equal(f(np.array(['a', 'b', 'c'], dtype=dtype)), + np.array(list(map(ord, 'abc')), dtype='i1')) + assert_array_equal(f(np.array([b'a', b'b', b'c'], dtype=dtype)), + np.array(list(map(ord, 'abc')), dtype='i1')) + + def test_array_input_varia(self): + f = getattr(self.module, self.fprefix + '_array_input') + assert_array_equal(f(['a', 'b', 'c']), + np.array(list(map(ord, 'abc')), dtype='i1')) + assert_array_equal(f([b'a', b'b', b'c']), + np.array(list(map(ord, 'abc')), dtype='i1')) + + try: + f(['a', 'b', 'c', 'd']) + except ValueError as msg: + if not str(msg).endswith( + 'th dimension must be fixed to 3 but got 4'): + raise + else: + raise SystemError( + f'{f.__name__} should have failed on wrong input') + + @pytest.mark.parametrize("dtype", ['c', 'S1', 'U1']) + def test_2d_array_input(self, dtype): + f = getattr(self.module, self.fprefix + '_2d_array_input') + + a = np.array([['a', 'b', 'c'], + ['d', 'e', 'f']], dtype=dtype, order='F') + expected = a.view(np.uint32 if dtype == 'U1' else np.uint8) + assert_array_equal(f(a), expected) + + def test_output(self): + f = getattr(self.module, self.fprefix + '_output') + + assert_equal(f(ord(b'a')), b'a') + assert_equal(f(0), b'\0') + + def test_array_output(self): + f = getattr(self.module, self.fprefix + '_array_output') + + assert_array_equal(f(list(map(ord, 'abc'))), + np.array(list('abc'), dtype='S1')) + + def test_input_output(self): + f = getattr(self.module, self.fprefix + '_input_output') + + assert_equal(f(b'a'), b'a') + assert_equal(f('a'), b'a') + assert_equal(f(''), b'\0') + + @pytest.mark.parametrize("dtype", ['c', 'S1']) + def test_inout(self, dtype): + f = getattr(self.module, self.fprefix + '_inout') + + a = np.array(list('abc'), dtype=dtype) + f(a, 'A') + assert_array_equal(a, np.array(list('Abc'), dtype=a.dtype)) + f(a[1:], 'B') + assert_array_equal(a, np.array(list('ABc'), dtype=a.dtype)) + + a = np.array(['abc'], dtype=dtype) + f(a, 'A') + assert_array_equal(a, np.array(['Abc'], dtype=a.dtype)) + + def test_inout_varia(self): + f = getattr(self.module, self.fprefix + '_inout') + a = np.array('abc', dtype='S3') + f(a, 'A') + assert_array_equal(a, np.array('Abc', dtype=a.dtype)) + + a = np.array(['abc'], dtype='S3') + f(a, 'A') + assert_array_equal(a, np.array(['Abc'], dtype=a.dtype)) + + try: + f('abc', 'A') + except ValueError as msg: + if not str(msg).endswith(' got 3-str'): + raise + else: + raise SystemError(f'{f.__name__} should have failed on str value') + + @pytest.mark.parametrize("dtype", ['c', 'S1']) + def test_array_inout(self, dtype): + f = getattr(self.module, self.fprefix + '_array_inout') + n = np.array(['A', 'B', 'C'], dtype=dtype, order='F') + + a = np.array(['a', 'b', 'c'], dtype=dtype, order='F') + f(a, n) + assert_array_equal(a, n) + + a = np.array(['a', 'b', 'c', 'd'], dtype=dtype) + f(a[1:], n) + assert_array_equal(a, np.array(['a', 'A', 'B', 'C'], dtype=dtype)) + + a = np.array([['a', 'b', 'c']], dtype=dtype, order='F') + f(a, n) + assert_array_equal(a, np.array([['A', 'B', 'C']], dtype=dtype)) + + a = np.array(['a', 'b', 'c', 'd'], dtype=dtype, order='F') + try: + f(a, n) + except ValueError as msg: + if not str(msg).endswith( + 'th dimension must be fixed to 3 but got 4'): + raise + else: + raise SystemError( + f'{f.__name__} should have failed on wrong input') + + @pytest.mark.parametrize("dtype", ['c', 'S1']) + def test_2d_array_inout(self, dtype): + f = getattr(self.module, self.fprefix + '_2d_array_inout') + n = np.array([['A', 'B', 'C'], + ['D', 'E', 'F']], + dtype=dtype, order='F') + a = np.array([['a', 'b', 'c'], + ['d', 'e', 'f']], + dtype=dtype, order='F') + f(a, n) + assert_array_equal(a, n) + + def test_return(self): + f = getattr(self.module, self.fprefix + '_return') + + assert_equal(f('a'), b'a') + + @pytest.mark.skip('fortran function returning array segfaults') + def test_array_return(self): + f = getattr(self.module, self.fprefix + '_array_return') + + a = np.array(list('abc'), dtype='S1') + assert_array_equal(f(a), a) + + def test_optional(self): + f = getattr(self.module, self.fprefix + '_optional') + + assert_equal(f(), b"a") + assert_equal(f(b'B'), b"B") + + +class TestMiscCharacter(util.F2PyTest): + # options = ['--debug-capi', '--build-dir', '/tmp/test-build-f2py'] + suffix = '.f90' + fprefix = 'test_misc_character' + + code = textwrap.dedent(f""" + subroutine {fprefix}_gh18684(x, y, m) + character(len=5), dimension(m), intent(in) :: x + character*5, dimension(m), intent(out) :: y + integer i, m + !f2py integer, intent(hide), depend(x) :: m = f2py_len(x) + do i=1,m + y(i) = x(i) + end do + end subroutine {fprefix}_gh18684 + + subroutine {fprefix}_gh6308(x, i) + integer i + !f2py check(i>=0 && i<12) i + character*5 name, x + common name(12) + name(i + 1) = x + end subroutine {fprefix}_gh6308 + + subroutine {fprefix}_gh4519(x) + character(len=*), intent(in) :: x(:) + !f2py intent(out) x + integer :: i + ! Uncomment for debug printing: + !do i=1, size(x) + ! print*, "x(",i,")=", x(i) + !end do + end subroutine {fprefix}_gh4519 + + pure function {fprefix}_gh3425(x) result (y) + character(len=*), intent(in) :: x + character(len=len(x)) :: y + integer :: i + do i = 1, len(x) + j = iachar(x(i:i)) + if (j>=iachar("a") .and. j<=iachar("z") ) then + y(i:i) = achar(j-32) + else + y(i:i) = x(i:i) + endif + end do + end function {fprefix}_gh3425 + + subroutine {fprefix}_character_bc_new(x, y, z) + character, intent(in) :: x + character, intent(out) :: y + !f2py character, depend(x) :: y = x + !f2py character, dimension((x=='a'?1:2)), depend(x), intent(out) :: z + character, dimension(*) :: z + !f2py character, optional, check(x == 'a' || x == 'b') :: x = 'a' + !f2py callstatement (*f2py_func)(&x, &y, z) + !f2py callprotoargument character*, character*, character* + if (y.eq.x) then + y = x + else + y = 'e' + endif + z(1) = 'c' + end subroutine {fprefix}_character_bc_new + + subroutine {fprefix}_character_bc_old(x, y, z) + character, intent(in) :: x + character, intent(out) :: y + !f2py character, depend(x) :: y = x[0] + !f2py character, dimension((*x=='a'?1:2)), depend(x), intent(out) :: z + character, dimension(*) :: z + !f2py character, optional, check(*x == 'a' || x[0] == 'b') :: x = 'a' + !f2py callstatement (*f2py_func)(x, y, z) + !f2py callprotoargument char*, char*, char* + if (y.eq.x) then + y = x + else + y = 'e' + endif + z(1) = 'c' + end subroutine {fprefix}_character_bc_old + """) + + @pytest.mark.slow + def test_gh18684(self): + # Test character(len=5) and character*5 usages + f = getattr(self.module, self.fprefix + '_gh18684') + x = np.array(["abcde", "fghij"], dtype='S5') + y = f(x) + + assert_array_equal(x, y) + + def test_gh6308(self): + # Test character string array in a common block + f = getattr(self.module, self.fprefix + '_gh6308') + + assert_equal(self.module._BLNK_.name.dtype, np.dtype('S5')) + assert_equal(len(self.module._BLNK_.name), 12) + f("abcde", 0) + assert_equal(self.module._BLNK_.name[0], b"abcde") + f("12345", 5) + assert_equal(self.module._BLNK_.name[5], b"12345") + + def test_gh4519(self): + # Test array of assumed length strings + f = getattr(self.module, self.fprefix + '_gh4519') + + for x, expected in [ + ('a', {'shape': (), 'dtype': np.dtype('S1')}), + ('text', {'shape': (), 'dtype': np.dtype('S4')}), + (np.array(['1', '2', '3'], dtype='S1'), + {'shape': (3,), 'dtype': np.dtype('S1')}), + (['1', '2', '34'], + {'shape': (3,), 'dtype': np.dtype('S2')}), + (['', ''], {'shape': (2,), 'dtype': np.dtype('S1')})]: + r = f(x) + for k, v in expected.items(): + assert_equal(getattr(r, k), v) + + def test_gh3425(self): + # Test returning a copy of assumed length string + f = getattr(self.module, self.fprefix + '_gh3425') + # f is equivalent to bytes.upper + + assert_equal(f('abC'), b'ABC') + assert_equal(f(''), b'') + assert_equal(f('abC12d'), b'ABC12D') + + @pytest.mark.parametrize("state", ['new', 'old']) + def test_character_bc(self, state): + f = getattr(self.module, self.fprefix + '_character_bc_' + state) + + c, a = f() + assert_equal(c, b'a') + assert_equal(len(a), 1) + + c, a = f(b'b') + assert_equal(c, b'b') + assert_equal(len(a), 2) + + assert_raises(Exception, lambda: f(b'c')) + + +class TestStringScalarArr(util.F2PyTest): + sources = [util.getpath("tests", "src", "string", "scalar_string.f90")] + + def test_char(self): + for out in (self.module.string_test.string, + self.module.string_test.string77): + expected = () + assert out.shape == expected + expected = '|S8' + assert out.dtype == expected + + def test_char_arr(self): + for out in (self.module.string_test.strarr, + self.module.string_test.strarr77): + expected = (5, 7) + assert out.shape == expected + expected = '|S12' + assert out.dtype == expected + +class TestStringAssumedLength(util.F2PyTest): + sources = [util.getpath("tests", "src", "string", "gh24008.f")] + + def test_gh24008(self): + self.module.greet("joe", "bob") + +@pytest.mark.slow +class TestStringOptionalInOut(util.F2PyTest): + sources = [util.getpath("tests", "src", "string", "gh24662.f90")] + + def test_gh24662(self): + self.module.string_inout_optional() + a = np.array('hi', dtype='S32') + self.module.string_inout_optional(a) + assert "output string" in a.tobytes().decode() + with pytest.raises(Exception): # noqa: B017 + aa = "Hi" + self.module.string_inout_optional(aa) + + +@pytest.mark.slow +class TestNewCharHandling(util.F2PyTest): + # from v1.24 onwards, gh-19388 + sources = [ + util.getpath("tests", "src", "string", "gh25286.pyf"), + util.getpath("tests", "src", "string", "gh25286.f90") + ] + module_name = "_char_handling_test" + + def test_gh25286(self): + info = self.module.charint('T') + assert info == 2 + +@pytest.mark.slow +class TestBCCharHandling(util.F2PyTest): + # SciPy style, "incorrect" bindings with a hook + sources = [ + util.getpath("tests", "src", "string", "gh25286_bc.pyf"), + util.getpath("tests", "src", "string", "gh25286.f90") + ] + module_name = "_char_handling_test" + + def test_gh25286(self): + info = self.module.charint('T') + assert info == 2 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_common.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_common.py new file mode 100644 index 0000000000000000000000000000000000000000..b9fbd84d52fbadc5949e3b577fa314caf9af8ff3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_common.py @@ -0,0 +1,23 @@ +import pytest + +import numpy as np + +from . import util + + +@pytest.mark.slow +class TestCommonBlock(util.F2PyTest): + sources = [util.getpath("tests", "src", "common", "block.f")] + + def test_common_block(self): + self.module.initcb() + assert self.module.block.long_bn == np.array(1.0, dtype=np.float64) + assert self.module.block.string_bn == np.array("2", dtype="|S1") + assert self.module.block.ok == np.array(3, dtype=np.int32) + + +class TestCommonWithUse(util.F2PyTest): + sources = [util.getpath("tests", "src", "common", "gh19161.f90")] + + def test_common_gh19161(self): + assert self.module.data.x == 0 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_crackfortran.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_crackfortran.py new file mode 100644 index 0000000000000000000000000000000000000000..c3967cfb967b6a8e7b4a4654f4c7be7a8a1bb67d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_crackfortran.py @@ -0,0 +1,421 @@ +import contextlib +import importlib +import io +import textwrap +import time + +import pytest + +import numpy as np +from numpy.f2py import crackfortran +from numpy.f2py.crackfortran import markinnerspaces, nameargspattern + +from . import util + + +class TestNoSpace(util.F2PyTest): + # issue gh-15035: add handling for endsubroutine, endfunction with no space + # between "end" and the block name + sources = [util.getpath("tests", "src", "crackfortran", "gh15035.f")] + + def test_module(self): + k = np.array([1, 2, 3], dtype=np.float64) + w = np.array([1, 2, 3], dtype=np.float64) + self.module.subb(k) + assert np.allclose(k, w + 1) + self.module.subc([w, k]) + assert np.allclose(k, w + 1) + assert self.module.t0("23") == b"2" + + +class TestPublicPrivate: + def test_defaultPrivate(self): + fpath = util.getpath("tests", "src", "crackfortran", "privatemod.f90") + mod = crackfortran.crackfortran([str(fpath)]) + assert len(mod) == 1 + mod = mod[0] + assert "private" in mod["vars"]["a"]["attrspec"] + assert "public" not in mod["vars"]["a"]["attrspec"] + assert "private" in mod["vars"]["b"]["attrspec"] + assert "public" not in mod["vars"]["b"]["attrspec"] + assert "private" not in mod["vars"]["seta"]["attrspec"] + assert "public" in mod["vars"]["seta"]["attrspec"] + + def test_defaultPublic(self, tmp_path): + fpath = util.getpath("tests", "src", "crackfortran", "publicmod.f90") + mod = crackfortran.crackfortran([str(fpath)]) + assert len(mod) == 1 + mod = mod[0] + assert "private" in mod["vars"]["a"]["attrspec"] + assert "public" not in mod["vars"]["a"]["attrspec"] + assert "private" not in mod["vars"]["seta"]["attrspec"] + assert "public" in mod["vars"]["seta"]["attrspec"] + + def test_access_type(self, tmp_path): + fpath = util.getpath("tests", "src", "crackfortran", "accesstype.f90") + mod = crackfortran.crackfortran([str(fpath)]) + assert len(mod) == 1 + tt = mod[0]['vars'] + assert set(tt['a']['attrspec']) == {'private', 'bind(c)'} + assert set(tt['b_']['attrspec']) == {'public', 'bind(c)'} + assert set(tt['c']['attrspec']) == {'public'} + + def test_nowrap_private_proceedures(self, tmp_path): + fpath = util.getpath("tests", "src", "crackfortran", "gh23879.f90") + mod = crackfortran.crackfortran([str(fpath)]) + assert len(mod) == 1 + pyf = crackfortran.crack2fortran(mod) + assert 'bar' not in pyf + +class TestModuleProcedure: + def test_moduleOperators(self, tmp_path): + fpath = util.getpath("tests", "src", "crackfortran", "operators.f90") + mod = crackfortran.crackfortran([str(fpath)]) + assert len(mod) == 1 + mod = mod[0] + assert "body" in mod and len(mod["body"]) == 9 + assert mod["body"][1]["name"] == "operator(.item.)" + assert "implementedby" in mod["body"][1] + assert mod["body"][1]["implementedby"] == \ + ["item_int", "item_real"] + assert mod["body"][2]["name"] == "operator(==)" + assert "implementedby" in mod["body"][2] + assert mod["body"][2]["implementedby"] == ["items_are_equal"] + assert mod["body"][3]["name"] == "assignment(=)" + assert "implementedby" in mod["body"][3] + assert mod["body"][3]["implementedby"] == \ + ["get_int", "get_real"] + + def test_notPublicPrivate(self, tmp_path): + fpath = util.getpath("tests", "src", "crackfortran", "pubprivmod.f90") + mod = crackfortran.crackfortran([str(fpath)]) + assert len(mod) == 1 + mod = mod[0] + assert mod['vars']['a']['attrspec'] == ['private', ] + assert mod['vars']['b']['attrspec'] == ['public', ] + assert mod['vars']['seta']['attrspec'] == ['public', ] + + +class TestExternal(util.F2PyTest): + # issue gh-17859: add external attribute support + sources = [util.getpath("tests", "src", "crackfortran", "gh17859.f")] + + def test_external_as_statement(self): + def incr(x): + return x + 123 + + r = self.module.external_as_statement(incr) + assert r == 123 + + def test_external_as_attribute(self): + def incr(x): + return x + 123 + + r = self.module.external_as_attribute(incr) + assert r == 123 + + +class TestCrackFortran(util.F2PyTest): + # gh-2848: commented lines between parameters in subroutine parameter lists + sources = [util.getpath("tests", "src", "crackfortran", "gh2848.f90"), + util.getpath("tests", "src", "crackfortran", "common_with_division.f") + ] + + def test_gh2848(self): + r = self.module.gh2848(1, 2) + assert r == (1, 2) + + def test_common_with_division(self): + assert len(self.module.mortmp.ctmp) == 11 + +class TestMarkinnerspaces: + # gh-14118: markinnerspaces does not handle multiple quotations + + def test_do_not_touch_normal_spaces(self): + test_list = ["a ", " a", "a b c", "'abcdefghij'"] + for i in test_list: + assert markinnerspaces(i) == i + + def test_one_relevant_space(self): + assert markinnerspaces("a 'b c' \\' \\'") == "a 'b@_@c' \\' \\'" + assert markinnerspaces(r'a "b c" \" \"') == r'a "b@_@c" \" \"' + + def test_ignore_inner_quotes(self): + assert markinnerspaces("a 'b c\" \" d' e") == "a 'b@_@c\"@_@\"@_@d' e" + assert markinnerspaces("a \"b c' ' d\" e") == "a \"b@_@c'@_@'@_@d\" e" + + def test_multiple_relevant_spaces(self): + assert markinnerspaces("a 'b c' 'd e'") == "a 'b@_@c' 'd@_@e'" + assert markinnerspaces(r'a "b c" "d e"') == r'a "b@_@c" "d@_@e"' + + +class TestDimSpec(util.F2PyTest): + """This test suite tests various expressions that are used as dimension + specifications. + + There exists two usage cases where analyzing dimensions + specifications are important. + + In the first case, the size of output arrays must be defined based + on the inputs to a Fortran function. Because Fortran supports + arbitrary bases for indexing, for instance, `arr(lower:upper)`, + f2py has to evaluate an expression `upper - lower + 1` where + `lower` and `upper` are arbitrary expressions of input parameters. + The evaluation is performed in C, so f2py has to translate Fortran + expressions to valid C expressions (an alternative approach is + that a developer specifies the corresponding C expressions in a + .pyf file). + + In the second case, when user provides an input array with a given + size but some hidden parameters used in dimensions specifications + need to be determined based on the input array size. This is a + harder problem because f2py has to solve the inverse problem: find + a parameter `p` such that `upper(p) - lower(p) + 1` equals to the + size of input array. In the case when this equation cannot be + solved (e.g. because the input array size is wrong), raise an + error before calling the Fortran function (that otherwise would + likely crash Python process when the size of input arrays is + wrong). f2py currently supports this case only when the equation + is linear with respect to unknown parameter. + + """ + + suffix = ".f90" + + code_template = textwrap.dedent(""" + function get_arr_size_{count}(a, n) result (length) + integer, intent(in) :: n + integer, dimension({dimspec}), intent(out) :: a + integer length + length = size(a) + end function + + subroutine get_inv_arr_size_{count}(a, n) + integer :: n + ! the value of n is computed in f2py wrapper + !f2py intent(out) n + integer, dimension({dimspec}), intent(in) :: a + if (a({first}).gt.0) then + ! print*, "a=", a + endif + end subroutine + """) + + linear_dimspecs = [ + "n", "2*n", "2:n", "n/2", "5 - n/2", "3*n:20", "n*(n+1):n*(n+5)", + "2*n, n" + ] + nonlinear_dimspecs = ["2*n:3*n*n+2*n"] + all_dimspecs = linear_dimspecs + nonlinear_dimspecs + + code = "" + for count, dimspec in enumerate(all_dimspecs): + lst = [(d.split(":")[0] if ":" in d else "1") for d in dimspec.split(',')] + code += code_template.format( + count=count, + dimspec=dimspec, + first=", ".join(lst), + ) + + @pytest.mark.parametrize("dimspec", all_dimspecs) + @pytest.mark.slow + def test_array_size(self, dimspec): + + count = self.all_dimspecs.index(dimspec) + get_arr_size = getattr(self.module, f"get_arr_size_{count}") + + for n in [1, 2, 3, 4, 5]: + sz, a = get_arr_size(n) + assert a.size == sz + + @pytest.mark.parametrize("dimspec", all_dimspecs) + def test_inv_array_size(self, dimspec): + + count = self.all_dimspecs.index(dimspec) + get_arr_size = getattr(self.module, f"get_arr_size_{count}") + get_inv_arr_size = getattr(self.module, f"get_inv_arr_size_{count}") + + for n in [1, 2, 3, 4, 5]: + sz, a = get_arr_size(n) + if dimspec in self.nonlinear_dimspecs: + # one must specify n as input, the call we'll ensure + # that a and n are compatible: + n1 = get_inv_arr_size(a, n) + else: + # in case of linear dependence, n can be determined + # from the shape of a: + n1 = get_inv_arr_size(a) + # n1 may be different from n (for instance, when `a` size + # is a function of some `n` fraction) but it must produce + # the same sized array + sz1, _ = get_arr_size(n1) + assert sz == sz1, (n, n1, sz, sz1) + + +class TestModuleDeclaration: + def test_dependencies(self, tmp_path): + fpath = util.getpath("tests", "src", "crackfortran", "foo_deps.f90") + mod = crackfortran.crackfortran([str(fpath)]) + assert len(mod) == 1 + assert mod[0]["vars"]["abar"]["="] == "bar('abar')" + + +class TestEval(util.F2PyTest): + def test_eval_scalar(self): + eval_scalar = crackfortran._eval_scalar + + assert eval_scalar('123', {}) == '123' + assert eval_scalar('12 + 3', {}) == '15' + assert eval_scalar('a + b', {"a": 1, "b": 2}) == '3' + assert eval_scalar('"123"', {}) == "'123'" + + +class TestFortranReader(util.F2PyTest): + @pytest.mark.parametrize("encoding", + ['ascii', 'utf-8', 'utf-16', 'utf-32']) + def test_input_encoding(self, tmp_path, encoding): + # gh-635 + f_path = tmp_path / f"input_with_{encoding}_encoding.f90" + with f_path.open('w', encoding=encoding) as ff: + ff.write(""" + subroutine foo() + end subroutine foo + """) + mod = crackfortran.crackfortran([str(f_path)]) + assert mod[0]['name'] == 'foo' + + +@pytest.mark.slow +class TestUnicodeComment(util.F2PyTest): + sources = [util.getpath("tests", "src", "crackfortran", "unicode_comment.f90")] + + @pytest.mark.skipif( + (importlib.util.find_spec("charset_normalizer") is None), + reason="test requires charset_normalizer which is not installed", + ) + def test_encoding_comment(self): + self.module.foo(3) + + +class TestNameArgsPatternBacktracking: + @pytest.mark.parametrize( + ['adversary'], + [ + ('@)@bind@(@',), + ('@)@bind @(@',), + ('@)@bind foo bar baz@(@',) + ] + ) + def test_nameargspattern_backtracking(self, adversary): + '''address ReDOS vulnerability: + https://github.com/numpy/numpy/issues/23338''' + trials_per_batch = 12 + batches_per_regex = 4 + start_reps, end_reps = 15, 25 + for ii in range(start_reps, end_reps): + repeated_adversary = adversary * ii + # test times in small batches. + # this gives us more chances to catch a bad regex + # while still catching it before too long if it is bad + for _ in range(batches_per_regex): + times = [] + for _ in range(trials_per_batch): + t0 = time.perf_counter() + mtch = nameargspattern.search(repeated_adversary) + times.append(time.perf_counter() - t0) + # our pattern should be much faster than 0.2s per search + # it's unlikely that a bad regex will pass even on fast CPUs + assert np.median(times) < 0.2 + assert not mtch + # if the adversary is capped with @)@, it becomes acceptable + # according to the old version of the regex. + # that should still be true. + good_version_of_adversary = repeated_adversary + '@)@' + assert nameargspattern.search(good_version_of_adversary) + +class TestFunctionReturn(util.F2PyTest): + sources = [util.getpath("tests", "src", "crackfortran", "gh23598.f90")] + + @pytest.mark.slow + def test_function_rettype(self): + # gh-23598 + assert self.module.intproduct(3, 4) == 12 + + +class TestFortranGroupCounters(util.F2PyTest): + def test_end_if_comment(self): + # gh-23533 + fpath = util.getpath("tests", "src", "crackfortran", "gh23533.f") + try: + crackfortran.crackfortran([str(fpath)]) + except Exception as exc: + assert False, f"'crackfortran.crackfortran' raised an exception {exc}" + + +class TestF77CommonBlockReader: + def test_gh22648(self, tmp_path): + fpath = util.getpath("tests", "src", "crackfortran", "gh22648.pyf") + with contextlib.redirect_stdout(io.StringIO()) as stdout_f2py: + mod = crackfortran.crackfortran([str(fpath)]) + assert "Mismatch" not in stdout_f2py.getvalue() + +class TestParamEval: + # issue gh-11612, array parameter parsing + def test_param_eval_nested(self): + v = '(/3.14, 4./)' + g_params = {"kind": crackfortran._kind_func, + "selected_int_kind": crackfortran._selected_int_kind_func, + "selected_real_kind": crackfortran._selected_real_kind_func} + params = {'dp': 8, 'intparamarray': {1: 3, 2: 5}, + 'nested': {1: 1, 2: 2, 3: 3}} + dimspec = '(2)' + ret = crackfortran.param_eval(v, g_params, params, dimspec=dimspec) + assert ret == {1: 3.14, 2: 4.0} + + def test_param_eval_nonstandard_range(self): + v = '(/ 6, 3, 1 /)' + g_params = {"kind": crackfortran._kind_func, + "selected_int_kind": crackfortran._selected_int_kind_func, + "selected_real_kind": crackfortran._selected_real_kind_func} + params = {} + dimspec = '(-1:1)' + ret = crackfortran.param_eval(v, g_params, params, dimspec=dimspec) + assert ret == {-1: 6, 0: 3, 1: 1} + + def test_param_eval_empty_range(self): + v = '6' + g_params = {"kind": crackfortran._kind_func, + "selected_int_kind": crackfortran._selected_int_kind_func, + "selected_real_kind": crackfortran._selected_real_kind_func} + params = {} + dimspec = '' + pytest.raises(ValueError, crackfortran.param_eval, v, g_params, params, + dimspec=dimspec) + + def test_param_eval_non_array_param(self): + v = '3.14_dp' + g_params = {"kind": crackfortran._kind_func, + "selected_int_kind": crackfortran._selected_int_kind_func, + "selected_real_kind": crackfortran._selected_real_kind_func} + params = {} + ret = crackfortran.param_eval(v, g_params, params, dimspec=None) + assert ret == '3.14_dp' + + def test_param_eval_too_many_dims(self): + v = 'reshape((/ (i, i=1, 250) /), (/5, 10, 5/))' + g_params = {"kind": crackfortran._kind_func, + "selected_int_kind": crackfortran._selected_int_kind_func, + "selected_real_kind": crackfortran._selected_real_kind_func} + params = {} + dimspec = '(0:4, 3:12, 5)' + pytest.raises(ValueError, crackfortran.param_eval, v, g_params, params, + dimspec=dimspec) + +@pytest.mark.slow +class TestLowerF2PYDirective(util.F2PyTest): + sources = [util.getpath("tests", "src", "crackfortran", "gh27697.f90")] + options = ['--lower'] + + def test_no_lower_fail(self): + with pytest.raises(ValueError, match='aborting directly') as exc: + self.module.utils.my_abort('aborting directly') diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_data.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_data.py new file mode 100644 index 0000000000000000000000000000000000000000..0cea5561bd6c6c44114f6c2af412b748578096b5 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_data.py @@ -0,0 +1,71 @@ +import pytest + +import numpy as np +from numpy.f2py.crackfortran import crackfortran + +from . import util + + +class TestData(util.F2PyTest): + sources = [util.getpath("tests", "src", "crackfortran", "data_stmts.f90")] + + # For gh-23276 + @pytest.mark.slow + def test_data_stmts(self): + assert self.module.cmplxdat.i == 2 + assert self.module.cmplxdat.j == 3 + assert self.module.cmplxdat.x == 1.5 + assert self.module.cmplxdat.y == 2.0 + assert self.module.cmplxdat.pi == 3.1415926535897932384626433832795028841971693993751058209749445923078164062 + assert self.module.cmplxdat.medium_ref_index == np.array(1. + 0.j) + assert np.all(self.module.cmplxdat.z == np.array([3.5, 7.0])) + assert np.all(self.module.cmplxdat.my_array == np.array([ 1. + 2.j, -3. + 4.j])) + assert np.all(self.module.cmplxdat.my_real_array == np.array([ 1., 2., 3.])) + assert np.all(self.module.cmplxdat.ref_index_one == np.array([13.0 + 21.0j])) + assert np.all(self.module.cmplxdat.ref_index_two == np.array([-30.0 + 43.0j])) + + def test_crackedlines(self): + mod = crackfortran(self.sources) + assert mod[0]['vars']['x']['='] == '1.5' + assert mod[0]['vars']['y']['='] == '2.0' + assert mod[0]['vars']['pi']['='] == '3.1415926535897932384626433832795028841971693993751058209749445923078164062d0' + assert mod[0]['vars']['my_real_array']['='] == '(/1.0d0, 2.0d0, 3.0d0/)' + assert mod[0]['vars']['ref_index_one']['='] == '(13.0d0, 21.0d0)' + assert mod[0]['vars']['ref_index_two']['='] == '(-30.0d0, 43.0d0)' + assert mod[0]['vars']['my_array']['='] == '(/(1.0d0, 2.0d0), (-3.0d0, 4.0d0)/)' + assert mod[0]['vars']['z']['='] == '(/3.5, 7.0/)' + +class TestDataF77(util.F2PyTest): + sources = [util.getpath("tests", "src", "crackfortran", "data_common.f")] + + # For gh-23276 + def test_data_stmts(self): + assert self.module.mycom.mydata == 0 + + def test_crackedlines(self): + mod = crackfortran(str(self.sources[0])) + print(mod[0]['vars']) + assert mod[0]['vars']['mydata']['='] == '0' + + +class TestDataMultiplierF77(util.F2PyTest): + sources = [util.getpath("tests", "src", "crackfortran", "data_multiplier.f")] + + # For gh-23276 + def test_data_stmts(self): + assert self.module.mycom.ivar1 == 3 + assert self.module.mycom.ivar2 == 3 + assert self.module.mycom.ivar3 == 2 + assert self.module.mycom.ivar4 == 2 + assert self.module.mycom.evar5 == 0 + + +class TestDataWithCommentsF77(util.F2PyTest): + sources = [util.getpath("tests", "src", "crackfortran", "data_with_comments.f")] + + # For gh-23276 + def test_data_stmts(self): + assert len(self.module.mycom.mytab) == 3 + assert self.module.mycom.mytab[0] == 0 + assert self.module.mycom.mytab[1] == 4 + assert self.module.mycom.mytab[2] == 0 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_docs.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_docs.py new file mode 100644 index 0000000000000000000000000000000000000000..7015af3b2627a2f8fd949001919215cda50a6c10 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_docs.py @@ -0,0 +1,66 @@ +from pathlib import Path + +import pytest + +import numpy as np +from numpy.testing import assert_array_equal, assert_equal + +from . import util + + +def get_docdir(): + parents = Path(__file__).resolve().parents + try: + # Assumes that spin is used to run tests + nproot = parents[8] + except IndexError: + docdir = None + else: + docdir = nproot / "doc" / "source" / "f2py" / "code" + if docdir and docdir.is_dir(): + return docdir + # Assumes that an editable install is used to run tests + return parents[3] / "doc" / "source" / "f2py" / "code" + + +pytestmark = pytest.mark.skipif( + not get_docdir().is_dir(), + reason=f"Could not find f2py documentation sources" + f"({get_docdir()} does not exist)", +) + +def _path(*args): + return get_docdir().joinpath(*args) + +@pytest.mark.slow +class TestDocAdvanced(util.F2PyTest): + # options = ['--debug-capi', '--build-dir', '/tmp/build-f2py'] + sources = [_path('asterisk1.f90'), _path('asterisk2.f90'), + _path('ftype.f')] + + def test_asterisk1(self): + foo = self.module.foo1 + assert_equal(foo(), b'123456789A12') + + def test_asterisk2(self): + foo = self.module.foo2 + assert_equal(foo(2), b'12') + assert_equal(foo(12), b'123456789A12') + assert_equal(foo(20), b'123456789A123456789B') + + def test_ftype(self): + ftype = self.module + ftype.foo() + assert_equal(ftype.data.a, 0) + ftype.data.a = 3 + ftype.data.x = [1, 2, 3] + assert_equal(ftype.data.a, 3) + assert_array_equal(ftype.data.x, + np.array([1, 2, 3], dtype=np.float32)) + ftype.data.x[1] = 45 + assert_array_equal(ftype.data.x, + np.array([1, 45, 3], dtype=np.float32)) + # gh-26718 Cleanup for repeated test runs + ftype.data.a = 0 + + # TODO: implement test methods for other example Fortran codes diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_f2cmap.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_f2cmap.py new file mode 100644 index 0000000000000000000000000000000000000000..a35320ccc18a470bf81d8655394d8744a3bc9a99 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_f2cmap.py @@ -0,0 +1,17 @@ +import numpy as np + +from . import util + + +class TestF2Cmap(util.F2PyTest): + sources = [ + util.getpath("tests", "src", "f2cmap", "isoFortranEnvMap.f90"), + util.getpath("tests", "src", "f2cmap", ".f2py_f2cmap") + ] + + # gh-15095 + def test_gh15095(self): + inp = np.ones(3) + out = self.module.func1(inp) + exp_out = 3 + assert out == exp_out diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_f2py2e.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_f2py2e.py new file mode 100644 index 0000000000000000000000000000000000000000..959e1527c482a7b7fc8bb3f28416633d7ece3a8f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_f2py2e.py @@ -0,0 +1,983 @@ +import platform +import re +import shlex +import subprocess +import sys +import textwrap +from collections import namedtuple +from pathlib import Path + +import pytest + +from numpy.f2py.f2py2e import main as f2pycli +from numpy.testing._private.utils import NOGIL_BUILD + +from . import util + +####################### +# F2PY Test utilities # +###################### + +# Tests for CLI commands which call meson will fail if no compilers are present, these are to be skipped + +def compiler_check_f2pycli(): + if not util.has_fortran_compiler(): + pytest.skip("CLI command needs a Fortran compiler") + else: + f2pycli() + +######################### +# CLI utils and classes # +######################### + + +PPaths = namedtuple("PPaths", "finp, f90inp, pyf, wrap77, wrap90, cmodf") + + +def get_io_paths(fname_inp, mname="untitled"): + """Takes in a temporary file for testing and returns the expected output and input paths + + Here expected output is essentially one of any of the possible generated + files. + + ..note:: + + Since this does not actually run f2py, none of these are guaranteed to + exist, and module names are typically incorrect + + Parameters + ---------- + fname_inp : str + The input filename + mname : str, optional + The name of the module, untitled by default + + Returns + ------- + genp : NamedTuple PPaths + The possible paths which are generated, not all of which exist + """ + bpath = Path(fname_inp) + return PPaths( + finp=bpath.with_suffix(".f"), + f90inp=bpath.with_suffix(".f90"), + pyf=bpath.with_suffix(".pyf"), + wrap77=bpath.with_name(f"{mname}-f2pywrappers.f"), + wrap90=bpath.with_name(f"{mname}-f2pywrappers2.f90"), + cmodf=bpath.with_name(f"{mname}module.c"), + ) + + +################ +# CLI Fixtures # +################ + + +@pytest.fixture(scope="session") +def hello_world_f90(tmpdir_factory): + """Generates a single f90 file for testing""" + fdat = util.getpath("tests", "src", "cli", "hiworld.f90").read_text() + fn = tmpdir_factory.getbasetemp() / "hello.f90" + fn.write_text(fdat, encoding="ascii") + return fn + + +@pytest.fixture(scope="session") +def gh23598_warn(tmpdir_factory): + """F90 file for testing warnings in gh23598""" + fdat = util.getpath("tests", "src", "crackfortran", "gh23598Warn.f90").read_text() + fn = tmpdir_factory.getbasetemp() / "gh23598Warn.f90" + fn.write_text(fdat, encoding="ascii") + return fn + + +@pytest.fixture(scope="session") +def gh22819_cli(tmpdir_factory): + """F90 file for testing disallowed CLI arguments in ghff819""" + fdat = util.getpath("tests", "src", "cli", "gh_22819.pyf").read_text() + fn = tmpdir_factory.getbasetemp() / "gh_22819.pyf" + fn.write_text(fdat, encoding="ascii") + return fn + + +@pytest.fixture(scope="session") +def hello_world_f77(tmpdir_factory): + """Generates a single f77 file for testing""" + fdat = util.getpath("tests", "src", "cli", "hi77.f").read_text() + fn = tmpdir_factory.getbasetemp() / "hello.f" + fn.write_text(fdat, encoding="ascii") + return fn + + +@pytest.fixture(scope="session") +def retreal_f77(tmpdir_factory): + """Generates a single f77 file for testing""" + fdat = util.getpath("tests", "src", "return_real", "foo77.f").read_text() + fn = tmpdir_factory.getbasetemp() / "foo.f" + fn.write_text(fdat, encoding="ascii") + return fn + +@pytest.fixture(scope="session") +def f2cmap_f90(tmpdir_factory): + """Generates a single f90 file for testing""" + fdat = util.getpath("tests", "src", "f2cmap", "isoFortranEnvMap.f90").read_text() + f2cmap = util.getpath("tests", "src", "f2cmap", ".f2py_f2cmap").read_text() + fn = tmpdir_factory.getbasetemp() / "f2cmap.f90" + fmap = tmpdir_factory.getbasetemp() / "mapfile" + fn.write_text(fdat, encoding="ascii") + fmap.write_text(f2cmap, encoding="ascii") + return fn + +######### +# Tests # +######### + +def test_gh22819_cli(capfd, gh22819_cli, monkeypatch): + """Check that module names are handled correctly + gh-22819 + Essentially, the -m name cannot be used to import the module, so the module + named in the .pyf needs to be used instead + + CLI :: -m and a .pyf file + """ + ipath = Path(gh22819_cli) + monkeypatch.setattr(sys, "argv", f"f2py -m blah {ipath}".split()) + with util.switchdir(ipath.parent): + f2pycli() + gen_paths = [item.name for item in ipath.parent.rglob("*") if item.is_file()] + assert "blahmodule.c" not in gen_paths # shouldn't be generated + assert "blah-f2pywrappers.f" not in gen_paths + assert "test_22819-f2pywrappers.f" in gen_paths + assert "test_22819module.c" in gen_paths + + +def test_gh22819_many_pyf(capfd, gh22819_cli, monkeypatch): + """Only one .pyf file allowed + gh-22819 + CLI :: .pyf files + """ + ipath = Path(gh22819_cli) + monkeypatch.setattr(sys, "argv", f"f2py -m blah {ipath} hello.pyf".split()) + with util.switchdir(ipath.parent): + with pytest.raises(ValueError, match="Only one .pyf file per call"): + f2pycli() + + +def test_gh23598_warn(capfd, gh23598_warn, monkeypatch): + foutl = get_io_paths(gh23598_warn, mname="test") + ipath = foutl.f90inp + monkeypatch.setattr( + sys, "argv", + f'f2py {ipath} -m test'.split()) + + with util.switchdir(ipath.parent): + f2pycli() # Generate files + wrapper = foutl.wrap90.read_text() + assert "intproductf2pywrap, intpr" not in wrapper + + +def test_gen_pyf(capfd, hello_world_f90, monkeypatch): + """Ensures that a signature file is generated via the CLI + CLI :: -h + """ + ipath = Path(hello_world_f90) + opath = Path(hello_world_f90).stem + ".pyf" + monkeypatch.setattr(sys, "argv", f'f2py -h {opath} {ipath}'.split()) + + with util.switchdir(ipath.parent): + f2pycli() # Generate wrappers + out, _ = capfd.readouterr() + assert "Saving signatures to file" in out + assert Path(f'{opath}').exists() + + +def test_gen_pyf_stdout(capfd, hello_world_f90, monkeypatch): + """Ensures that a signature file can be dumped to stdout + CLI :: -h + """ + ipath = Path(hello_world_f90) + monkeypatch.setattr(sys, "argv", f'f2py -h stdout {ipath}'.split()) + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert "Saving signatures to file" in out + assert "function hi() ! in " in out + + +def test_gen_pyf_no_overwrite(capfd, hello_world_f90, monkeypatch): + """Ensures that the CLI refuses to overwrite signature files + CLI :: -h without --overwrite-signature + """ + ipath = Path(hello_world_f90) + monkeypatch.setattr(sys, "argv", f'f2py -h faker.pyf {ipath}'.split()) + + with util.switchdir(ipath.parent): + Path("faker.pyf").write_text("Fake news", encoding="ascii") + with pytest.raises(SystemExit): + f2pycli() # Refuse to overwrite + _, err = capfd.readouterr() + assert "Use --overwrite-signature to overwrite" in err + + +@pytest.mark.skipif(sys.version_info <= (3, 12), reason="Python 3.12 required") +def test_untitled_cli(capfd, hello_world_f90, monkeypatch): + """Check that modules are named correctly + + CLI :: defaults + """ + ipath = Path(hello_world_f90) + monkeypatch.setattr(sys, "argv", f"f2py --backend meson -c {ipath}".split()) + with util.switchdir(ipath.parent): + compiler_check_f2pycli() + out, _ = capfd.readouterr() + assert "untitledmodule.c" in out + + +@pytest.mark.skipif((platform.system() != 'Linux') or (sys.version_info <= (3, 12)), reason='Compiler and 3.12 required') +def test_no_py312_distutils_fcompiler(capfd, hello_world_f90, monkeypatch): + """Check that no distutils imports are performed on 3.12 + CLI :: --fcompiler --help-link --backend distutils + """ + MNAME = "hi" + foutl = get_io_paths(hello_world_f90, mname=MNAME) + ipath = foutl.f90inp + monkeypatch.setattr( + sys, "argv", f"f2py {ipath} -c --fcompiler=gfortran -m {MNAME}".split() + ) + with util.switchdir(ipath.parent): + compiler_check_f2pycli() + out, _ = capfd.readouterr() + assert "--fcompiler cannot be used with meson" in out + monkeypatch.setattr( + sys, "argv", ["f2py", "--help-link"] + ) + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert "Use --dep for meson builds" in out + MNAME = "hi2" # Needs to be different for a new -c + monkeypatch.setattr( + sys, "argv", f"f2py {ipath} -c -m {MNAME} --backend distutils".split() + ) + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert "Cannot use distutils backend with Python>=3.12" in out + + +@pytest.mark.xfail +def test_f2py_skip(capfd, retreal_f77, monkeypatch): + """Tests that functions can be skipped + CLI :: skip: + """ + foutl = get_io_paths(retreal_f77, mname="test") + ipath = foutl.finp + toskip = "t0 t4 t8 sd s8 s4" + remaining = "td s0" + monkeypatch.setattr( + sys, "argv", + f'f2py {ipath} -m test skip: {toskip}'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + out, err = capfd.readouterr() + for skey in toskip.split(): + assert ( + f'buildmodule: Could not found the body of interfaced routine "{skey}". Skipping.' + in err) + for rkey in remaining.split(): + assert f'Constructing wrapper function "{rkey}"' in out + + +def test_f2py_only(capfd, retreal_f77, monkeypatch): + """Test that functions can be kept by only: + CLI :: only: + """ + foutl = get_io_paths(retreal_f77, mname="test") + ipath = foutl.finp + toskip = "t0 t4 t8 sd s8 s4" + tokeep = "td s0" + monkeypatch.setattr( + sys, "argv", + f'f2py {ipath} -m test only: {tokeep}'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + out, err = capfd.readouterr() + for skey in toskip.split(): + assert ( + f'buildmodule: Could not find the body of interfaced routine "{skey}". Skipping.' + in err) + for rkey in tokeep.split(): + assert f'Constructing wrapper function "{rkey}"' in out + + +def test_file_processing_switch(capfd, hello_world_f90, retreal_f77, + monkeypatch): + """Tests that it is possible to return to file processing mode + CLI :: : + BUG: numpy-gh #20520 + """ + foutl = get_io_paths(retreal_f77, mname="test") + ipath = foutl.finp + toskip = "t0 t4 t8 sd s8 s4" + ipath2 = Path(hello_world_f90) + tokeep = "td s0 hi" # hi is in ipath2 + mname = "blah" + monkeypatch.setattr( + sys, + "argv", + f'f2py {ipath} -m {mname} only: {tokeep} : {ipath2}'.split( + ), + ) + + with util.switchdir(ipath.parent): + f2pycli() + out, err = capfd.readouterr() + for skey in toskip.split(): + assert ( + f'buildmodule: Could not find the body of interfaced routine "{skey}". Skipping.' + in err) + for rkey in tokeep.split(): + assert f'Constructing wrapper function "{rkey}"' in out + + +def test_mod_gen_f77(capfd, hello_world_f90, monkeypatch): + """Checks the generation of files based on a module name + CLI :: -m + """ + MNAME = "hi" + foutl = get_io_paths(hello_world_f90, mname=MNAME) + ipath = foutl.f90inp + monkeypatch.setattr(sys, "argv", f'f2py {ipath} -m {MNAME}'.split()) + with util.switchdir(ipath.parent): + f2pycli() + + # Always generate C module + assert Path.exists(foutl.cmodf) + # File contains a function, check for F77 wrappers + assert Path.exists(foutl.wrap77) + + +def test_mod_gen_gh25263(capfd, hello_world_f77, monkeypatch): + """Check that pyf files are correctly generated with module structure + CLI :: -m -h pyf_file + BUG: numpy-gh #20520 + """ + MNAME = "hi" + foutl = get_io_paths(hello_world_f77, mname=MNAME) + ipath = foutl.finp + monkeypatch.setattr(sys, "argv", f'f2py {ipath} -m {MNAME} -h hi.pyf'.split()) + with util.switchdir(ipath.parent): + f2pycli() + with Path('hi.pyf').open() as hipyf: + pyfdat = hipyf.read() + assert "python module hi" in pyfdat + + +def test_lower_cmod(capfd, hello_world_f77, monkeypatch): + """Lowers cases by flag or when -h is present + + CLI :: --[no-]lower + """ + foutl = get_io_paths(hello_world_f77, mname="test") + ipath = foutl.finp + capshi = re.compile(r"HI\(\)") + capslo = re.compile(r"hi\(\)") + # Case I: --lower is passed + monkeypatch.setattr(sys, "argv", f'f2py {ipath} -m test --lower'.split()) + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert capslo.search(out) is not None + assert capshi.search(out) is None + # Case II: --no-lower is passed + monkeypatch.setattr(sys, "argv", + f'f2py {ipath} -m test --no-lower'.split()) + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert capslo.search(out) is None + assert capshi.search(out) is not None + + +def test_lower_sig(capfd, hello_world_f77, monkeypatch): + """Lowers cases in signature files by flag or when -h is present + + CLI :: --[no-]lower -h + """ + foutl = get_io_paths(hello_world_f77, mname="test") + ipath = foutl.finp + # Signature files + capshi = re.compile(r"Block: HI") + capslo = re.compile(r"Block: hi") + # Case I: --lower is implied by -h + # TODO: Clean up to prevent passing --overwrite-signature + monkeypatch.setattr( + sys, + "argv", + f'f2py {ipath} -h {foutl.pyf} -m test --overwrite-signature'.split(), + ) + + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert capslo.search(out) is not None + assert capshi.search(out) is None + + # Case II: --no-lower overrides -h + monkeypatch.setattr( + sys, + "argv", + f'f2py {ipath} -h {foutl.pyf} -m test --overwrite-signature --no-lower' + .split(), + ) + + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert capslo.search(out) is None + assert capshi.search(out) is not None + + +def test_build_dir(capfd, hello_world_f90, monkeypatch): + """Ensures that the build directory can be specified + + CLI :: --build-dir + """ + ipath = Path(hello_world_f90) + mname = "blah" + odir = "tttmp" + monkeypatch.setattr(sys, "argv", + f'f2py -m {mname} {ipath} --build-dir {odir}'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert f"Wrote C/API module \"{mname}\"" in out + + +def test_overwrite(capfd, hello_world_f90, monkeypatch): + """Ensures that the build directory can be specified + + CLI :: --overwrite-signature + """ + ipath = Path(hello_world_f90) + monkeypatch.setattr( + sys, "argv", + f'f2py -h faker.pyf {ipath} --overwrite-signature'.split()) + + with util.switchdir(ipath.parent): + Path("faker.pyf").write_text("Fake news", encoding="ascii") + f2pycli() + out, _ = capfd.readouterr() + assert "Saving signatures to file" in out + + +def test_latexdoc(capfd, hello_world_f90, monkeypatch): + """Ensures that TeX documentation is written out + + CLI :: --latex-doc + """ + ipath = Path(hello_world_f90) + mname = "blah" + monkeypatch.setattr(sys, "argv", + f'f2py -m {mname} {ipath} --latex-doc'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert "Documentation is saved to file" in out + with Path(f"{mname}module.tex").open() as otex: + assert "\\documentclass" in otex.read() + + +def test_nolatexdoc(capfd, hello_world_f90, monkeypatch): + """Ensures that TeX documentation is written out + + CLI :: --no-latex-doc + """ + ipath = Path(hello_world_f90) + mname = "blah" + monkeypatch.setattr(sys, "argv", + f'f2py -m {mname} {ipath} --no-latex-doc'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert "Documentation is saved to file" not in out + + +def test_shortlatex(capfd, hello_world_f90, monkeypatch): + """Ensures that truncated documentation is written out + + TODO: Test to ensure this has no effect without --latex-doc + CLI :: --latex-doc --short-latex + """ + ipath = Path(hello_world_f90) + mname = "blah" + monkeypatch.setattr( + sys, + "argv", + f'f2py -m {mname} {ipath} --latex-doc --short-latex'.split(), + ) + + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert "Documentation is saved to file" in out + with Path(f"./{mname}module.tex").open() as otex: + assert "\\documentclass" not in otex.read() + + +def test_restdoc(capfd, hello_world_f90, monkeypatch): + """Ensures that RsT documentation is written out + + CLI :: --rest-doc + """ + ipath = Path(hello_world_f90) + mname = "blah" + monkeypatch.setattr(sys, "argv", + f'f2py -m {mname} {ipath} --rest-doc'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert "ReST Documentation is saved to file" in out + with Path(f"./{mname}module.rest").open() as orst: + assert r".. -*- rest -*-" in orst.read() + + +def test_norestexdoc(capfd, hello_world_f90, monkeypatch): + """Ensures that TeX documentation is written out + + CLI :: --no-rest-doc + """ + ipath = Path(hello_world_f90) + mname = "blah" + monkeypatch.setattr(sys, "argv", + f'f2py -m {mname} {ipath} --no-rest-doc'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert "ReST Documentation is saved to file" not in out + + +def test_debugcapi(capfd, hello_world_f90, monkeypatch): + """Ensures that debugging wrappers are written + + CLI :: --debug-capi + """ + ipath = Path(hello_world_f90) + mname = "blah" + monkeypatch.setattr(sys, "argv", + f'f2py -m {mname} {ipath} --debug-capi'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + with Path(f"./{mname}module.c").open() as ocmod: + assert r"#define DEBUGCFUNCS" in ocmod.read() + + +@pytest.mark.skip(reason="Consistently fails on CI; noisy so skip not xfail.") +def test_debugcapi_bld(hello_world_f90, monkeypatch): + """Ensures that debugging wrappers work + + CLI :: --debug-capi -c + """ + ipath = Path(hello_world_f90) + mname = "blah" + monkeypatch.setattr(sys, "argv", + f'f2py -m {mname} {ipath} -c --debug-capi'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + cmd_run = shlex.split(f"{sys.executable} -c \"import blah; blah.hi()\"") + rout = subprocess.run(cmd_run, capture_output=True, encoding='UTF-8') + eout = ' Hello World\n' + eerr = textwrap.dedent("""\ +debug-capi:Python C/API function blah.hi() +debug-capi:float hi=:output,hidden,scalar +debug-capi:hi=0 +debug-capi:Fortran subroutine `f2pywraphi(&hi)' +debug-capi:hi=0 +debug-capi:Building return value. +debug-capi:Python C/API function blah.hi: successful. +debug-capi:Freeing memory. + """) + assert rout.stdout == eout + assert rout.stderr == eerr + + +def test_wrapfunc_def(capfd, hello_world_f90, monkeypatch): + """Ensures that fortran subroutine wrappers for F77 are included by default + + CLI :: --[no]-wrap-functions + """ + # Implied + ipath = Path(hello_world_f90) + mname = "blah" + monkeypatch.setattr(sys, "argv", f'f2py -m {mname} {ipath}'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert r"Fortran 77 wrappers are saved to" in out + + # Explicit + monkeypatch.setattr(sys, "argv", + f'f2py -m {mname} {ipath} --wrap-functions'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert r"Fortran 77 wrappers are saved to" in out + + +def test_nowrapfunc(capfd, hello_world_f90, monkeypatch): + """Ensures that fortran subroutine wrappers for F77 can be disabled + + CLI :: --no-wrap-functions + """ + ipath = Path(hello_world_f90) + mname = "blah" + monkeypatch.setattr(sys, "argv", + f'f2py -m {mname} {ipath} --no-wrap-functions'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert r"Fortran 77 wrappers are saved to" not in out + + +def test_inclheader(capfd, hello_world_f90, monkeypatch): + """Add to the include directories + + CLI :: -include + TODO: Document this in the help string + """ + ipath = Path(hello_world_f90) + mname = "blah" + monkeypatch.setattr( + sys, + "argv", + f'f2py -m {mname} {ipath} -include -include '. + split(), + ) + + with util.switchdir(ipath.parent): + f2pycli() + with Path(f"./{mname}module.c").open() as ocmod: + ocmr = ocmod.read() + assert "#include " in ocmr + assert "#include " in ocmr + +@pytest.mark.skipif((platform.system() != 'Linux'), reason='Compiler required') +def test_cli_obj(capfd, hello_world_f90, monkeypatch): + """Ensures that the extra object can be specified when using meson backend + """ + ipath = Path(hello_world_f90) + mname = "blah" + odir = "tttmp" + obj = "extra.o" + monkeypatch.setattr(sys, "argv", + f'f2py --backend meson --build-dir {odir} -m {mname} -c {obj} {ipath}'.split()) + + with util.switchdir(ipath.parent): + Path(obj).touch() + compiler_check_f2pycli() + with Path(f"{odir}/meson.build").open() as mesonbuild: + mbld = mesonbuild.read() + assert "objects:" in mbld + assert f"'''{obj}'''" in mbld + + +def test_inclpath(): + """Add to the include directories + + CLI :: --include-paths + """ + # TODO: populate + pass + + +def test_hlink(): + """Add to the include directories + + CLI :: --help-link + """ + # TODO: populate + pass + + +def test_f2cmap(capfd, f2cmap_f90, monkeypatch): + """Check that Fortran-to-Python KIND specs can be passed + + CLI :: --f2cmap + """ + ipath = Path(f2cmap_f90) + monkeypatch.setattr(sys, "argv", f'f2py -m blah {ipath} --f2cmap mapfile'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert "Reading f2cmap from 'mapfile' ..." in out + assert "Mapping \"real(kind=real32)\" to \"float\"" in out + assert "Mapping \"real(kind=real64)\" to \"double\"" in out + assert "Mapping \"integer(kind=int64)\" to \"long_long\"" in out + assert "Successfully applied user defined f2cmap changes" in out + + +def test_quiet(capfd, hello_world_f90, monkeypatch): + """Reduce verbosity + + CLI :: --quiet + """ + ipath = Path(hello_world_f90) + monkeypatch.setattr(sys, "argv", f'f2py -m blah {ipath} --quiet'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert len(out) == 0 + + +def test_verbose(capfd, hello_world_f90, monkeypatch): + """Increase verbosity + + CLI :: --verbose + """ + ipath = Path(hello_world_f90) + monkeypatch.setattr(sys, "argv", f'f2py -m blah {ipath} --verbose'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + out, _ = capfd.readouterr() + assert "analyzeline" in out + + +def test_version(capfd, monkeypatch): + """Ensure version + + CLI :: -v + """ + monkeypatch.setattr(sys, "argv", ["f2py", "-v"]) + # TODO: f2py2e should not call sys.exit() after printing the version + with pytest.raises(SystemExit): + f2pycli() + out, _ = capfd.readouterr() + import numpy as np + assert np.__version__ == out.strip() + + +@pytest.mark.skip(reason="Consistently fails on CI; noisy so skip not xfail.") +def test_npdistop(hello_world_f90, monkeypatch): + """ + CLI :: -c + """ + ipath = Path(hello_world_f90) + monkeypatch.setattr(sys, "argv", f'f2py -m blah {ipath} -c'.split()) + + with util.switchdir(ipath.parent): + f2pycli() + cmd_run = shlex.split(f"{sys.executable} -c \"import blah; blah.hi()\"") + rout = subprocess.run(cmd_run, capture_output=True, encoding='UTF-8') + eout = ' Hello World\n' + assert rout.stdout == eout + + +@pytest.mark.skipif((platform.system() != 'Linux') or sys.version_info <= (3, 12), + reason='Compiler and Python 3.12 or newer required') +def test_no_freethreading_compatible(hello_world_f90, monkeypatch): + """ + CLI :: --no-freethreading-compatible + """ + ipath = Path(hello_world_f90) + monkeypatch.setattr(sys, "argv", f'f2py -m blah {ipath} -c --no-freethreading-compatible'.split()) + + with util.switchdir(ipath.parent): + compiler_check_f2pycli() + cmd = f"{sys.executable} -c \"import blah; blah.hi();" + if NOGIL_BUILD: + cmd += "import sys; assert sys._is_gil_enabled() is True\"" + else: + cmd += "\"" + cmd_run = shlex.split(cmd) + rout = subprocess.run(cmd_run, capture_output=True, encoding='UTF-8') + eout = ' Hello World\n' + assert rout.stdout == eout + if NOGIL_BUILD: + assert "The global interpreter lock (GIL) has been enabled to load module 'blah'" in rout.stderr + assert rout.returncode == 0 + + +@pytest.mark.skipif((platform.system() != 'Linux') or sys.version_info <= (3, 12), + reason='Compiler and Python 3.12 or newer required') +def test_freethreading_compatible(hello_world_f90, monkeypatch): + """ + CLI :: --freethreading_compatible + """ + ipath = Path(hello_world_f90) + monkeypatch.setattr(sys, "argv", f'f2py -m blah {ipath} -c --freethreading-compatible'.split()) + + with util.switchdir(ipath.parent): + compiler_check_f2pycli() + cmd = f"{sys.executable} -c \"import blah; blah.hi();" + if NOGIL_BUILD: + cmd += "import sys; assert sys._is_gil_enabled() is False\"" + else: + cmd += "\"" + cmd_run = shlex.split(cmd) + rout = subprocess.run(cmd_run, capture_output=True, encoding='UTF-8') + eout = ' Hello World\n' + assert rout.stdout == eout + assert rout.stderr == "" + assert rout.returncode == 0 + + +# Numpy distutils flags +# TODO: These should be tested separately + +def test_npd_fcompiler(): + """ + CLI :: -c --fcompiler + """ + # TODO: populate + pass + + +def test_npd_compiler(): + """ + CLI :: -c --compiler + """ + # TODO: populate + pass + + +def test_npd_help_fcompiler(): + """ + CLI :: -c --help-fcompiler + """ + # TODO: populate + pass + + +def test_npd_f77exec(): + """ + CLI :: -c --f77exec + """ + # TODO: populate + pass + + +def test_npd_f90exec(): + """ + CLI :: -c --f90exec + """ + # TODO: populate + pass + + +def test_npd_f77flags(): + """ + CLI :: -c --f77flags + """ + # TODO: populate + pass + + +def test_npd_f90flags(): + """ + CLI :: -c --f90flags + """ + # TODO: populate + pass + + +def test_npd_opt(): + """ + CLI :: -c --opt + """ + # TODO: populate + pass + + +def test_npd_arch(): + """ + CLI :: -c --arch + """ + # TODO: populate + pass + + +def test_npd_noopt(): + """ + CLI :: -c --noopt + """ + # TODO: populate + pass + + +def test_npd_noarch(): + """ + CLI :: -c --noarch + """ + # TODO: populate + pass + + +def test_npd_debug(): + """ + CLI :: -c --debug + """ + # TODO: populate + pass + + +def test_npd_link_auto(): + """ + CLI :: -c --link- + """ + # TODO: populate + pass + + +def test_npd_lib(): + """ + CLI :: -c -L/path/to/lib/ -l + """ + # TODO: populate + pass + + +def test_npd_define(): + """ + CLI :: -D + """ + # TODO: populate + pass + + +def test_npd_undefine(): + """ + CLI :: -U + """ + # TODO: populate + pass + + +def test_npd_incl(): + """ + CLI :: -I/path/to/include/ + """ + # TODO: populate + pass + + +def test_npd_linker(): + """ + CLI :: .o .so .a + """ + # TODO: populate + pass diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_isoc.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_isoc.py new file mode 100644 index 0000000000000000000000000000000000000000..f3450f15feadd5f8509e5323ad49b847fc1d1e6a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_isoc.py @@ -0,0 +1,56 @@ +import pytest + +import numpy as np +from numpy.testing import assert_allclose + +from . import util + + +class TestISOC(util.F2PyTest): + sources = [ + util.getpath("tests", "src", "isocintrin", "isoCtests.f90"), + ] + + # gh-24553 + @pytest.mark.slow + def test_c_double(self): + out = self.module.coddity.c_add(1, 2) + exp_out = 3 + assert out == exp_out + + # gh-9693 + def test_bindc_function(self): + out = self.module.coddity.wat(1, 20) + exp_out = 8 + assert out == exp_out + + # gh-25207 + def test_bindc_kinds(self): + out = self.module.coddity.c_add_int64(1, 20) + exp_out = 21 + assert out == exp_out + + # gh-25207 + def test_bindc_add_arr(self): + a = np.array([1, 2, 3]) + b = np.array([1, 2, 3]) + out = self.module.coddity.add_arr(a, b) + exp_out = a * 2 + assert_allclose(out, exp_out) + + +def test_process_f2cmap_dict(): + from numpy.f2py.auxfuncs import process_f2cmap_dict + + f2cmap_all = {"integer": {"8": "rubbish_type"}} + new_map = {"INTEGER": {"4": "int"}} + c2py_map = {"int": "int", "rubbish_type": "long"} + + exp_map, exp_maptyp = ({"integer": {"8": "rubbish_type", "4": "int"}}, ["int"]) + + # Call the function + res_map, res_maptyp = process_f2cmap_dict(f2cmap_all, new_map, c2py_map) + + # Assert the result is as expected + assert res_map == exp_map + assert res_maptyp == exp_maptyp diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_kind.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_kind.py new file mode 100644 index 0000000000000000000000000000000000000000..c219cc8bfd090d12bcc6a582ba8289135f6f1a0b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_kind.py @@ -0,0 +1,52 @@ +import platform +import sys + +import pytest + +from numpy.f2py.crackfortran import ( + _selected_int_kind_func as selected_int_kind, + _selected_real_kind_func as selected_real_kind, +) + +from . import util + +IS_PPC_OR_AIX = platform.machine().lower().startswith("ppc") or platform.system() == 'AIX' + +class TestKind(util.F2PyTest): + sources = [util.getpath("tests", "src", "kind", "foo.f90")] + + @pytest.mark.skipif(sys.maxsize < 2 ** 31 + 1, + reason="Fails for 32 bit machines") + def test_int(self): + """Test `int` kind_func for integers up to 10**40.""" + selectedintkind = self.module.selectedintkind + + for i in range(40): + assert selectedintkind(i) == selected_int_kind( + i + ), f"selectedintkind({i}): expected {selected_int_kind(i)!r} but got {selectedintkind(i)!r}" + + def test_real(self): + """ + Test (processor-dependent) `real` kind_func for real numbers + of up to 31 digits precision (extended/quadruple). + """ + selectedrealkind = self.module.selectedrealkind + + for i in range(32): + assert selectedrealkind(i) == selected_real_kind( + i + ), f"selectedrealkind({i}): expected {selected_real_kind(i)!r} but got {selectedrealkind(i)!r}" + + @pytest.mark.xfail(IS_PPC_OR_AIX, + reason="Some PowerPC may not support full IEEE 754 precision") + def test_quad_precision(self): + """ + Test kind_func for quadruple precision [`real(16)`] of 32+ digits . + """ + selectedrealkind = self.module.selectedrealkind + + for i in range(32, 40): + assert selectedrealkind(i) == selected_real_kind( + i + ), f"selectedrealkind({i}): expected {selected_real_kind(i)!r} but got {selectedrealkind(i)!r}" diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_mixed.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_mixed.py new file mode 100644 index 0000000000000000000000000000000000000000..07f43e2bcfaa20fa4b884ca3092acfb8675f45d9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_mixed.py @@ -0,0 +1,35 @@ +import textwrap + +import pytest + +from numpy.testing import IS_PYPY + +from . import util + + +class TestMixed(util.F2PyTest): + sources = [ + util.getpath("tests", "src", "mixed", "foo.f"), + util.getpath("tests", "src", "mixed", "foo_fixed.f90"), + util.getpath("tests", "src", "mixed", "foo_free.f90"), + ] + + @pytest.mark.slow + def test_all(self): + assert self.module.bar11() == 11 + assert self.module.foo_fixed.bar12() == 12 + assert self.module.foo_free.bar13() == 13 + + @pytest.mark.xfail(IS_PYPY, + reason="PyPy cannot modify tp_doc after PyType_Ready") + def test_docstring(self): + expected = textwrap.dedent("""\ + a = bar11() + + Wrapper for ``bar11``. + + Returns + ------- + a : int + """) + assert self.module.bar11.__doc__ == expected diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_modules.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_modules.py new file mode 100644 index 0000000000000000000000000000000000000000..96d5ffc66093ddaf1a07ebda59ed6a187b1263fb --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_modules.py @@ -0,0 +1,83 @@ +import textwrap + +import pytest + +from numpy.testing import IS_PYPY + +from . import util + + +@pytest.mark.slow +class TestModuleFilterPublicEntities(util.F2PyTest): + sources = [ + util.getpath( + "tests", "src", "modules", "gh26920", + "two_mods_with_one_public_routine.f90" + ) + ] + # we filter the only public function mod2 + only = ["mod1_func1", ] + + def test_gh26920(self): + # if it compiles and can be loaded, things are fine + pass + + +@pytest.mark.slow +class TestModuleWithoutPublicEntities(util.F2PyTest): + sources = [ + util.getpath( + "tests", "src", "modules", "gh26920", + "two_mods_with_no_public_entities.f90" + ) + ] + only = ["mod1_func1", ] + + def test_gh26920(self): + # if it compiles and can be loaded, things are fine + pass + + +@pytest.mark.slow +class TestModuleDocString(util.F2PyTest): + sources = [util.getpath("tests", "src", "modules", "module_data_docstring.f90")] + + @pytest.mark.xfail(IS_PYPY, reason="PyPy cannot modify tp_doc after PyType_Ready") + def test_module_docstring(self): + assert self.module.mod.__doc__ == textwrap.dedent( + """\ + i : 'i'-scalar + x : 'i'-array(4) + a : 'f'-array(2,3) + b : 'f'-array(-1,-1), not allocated\x00 + foo()\n + Wrapper for ``foo``.\n\n""" + ) + + +@pytest.mark.slow +class TestModuleAndSubroutine(util.F2PyTest): + module_name = "example" + sources = [ + util.getpath("tests", "src", "modules", "gh25337", "data.f90"), + util.getpath("tests", "src", "modules", "gh25337", "use_data.f90"), + ] + + def test_gh25337(self): + self.module.data.set_shift(3) + assert "data" in dir(self.module) + + +@pytest.mark.slow +class TestUsedModule(util.F2PyTest): + module_name = "fmath" + sources = [ + util.getpath("tests", "src", "modules", "use_modules.f90"), + ] + + def test_gh25867(self): + compiled_mods = [x for x in dir(self.module) if "__" not in x] + assert "useops" in compiled_mods + assert self.module.useops.sum_and_double(3, 7) == 20 + assert "mathops" in compiled_mods + assert self.module.mathops.add(3, 7) == 10 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_parameter.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_parameter.py new file mode 100644 index 0000000000000000000000000000000000000000..513d021002b7d874bc8a3f64ac9fbc166c0473bd --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_parameter.py @@ -0,0 +1,129 @@ +import pytest + +import numpy as np + +from . import util + + +class TestParameters(util.F2PyTest): + # Check that intent(in out) translates as intent(inout) + sources = [ + util.getpath("tests", "src", "parameter", "constant_real.f90"), + util.getpath("tests", "src", "parameter", "constant_integer.f90"), + util.getpath("tests", "src", "parameter", "constant_both.f90"), + util.getpath("tests", "src", "parameter", "constant_compound.f90"), + util.getpath("tests", "src", "parameter", "constant_non_compound.f90"), + util.getpath("tests", "src", "parameter", "constant_array.f90"), + ] + + @pytest.mark.slow + def test_constant_real_single(self): + # non-contiguous should raise error + x = np.arange(6, dtype=np.float32)[::2] + pytest.raises(ValueError, self.module.foo_single, x) + + # check values with contiguous array + x = np.arange(3, dtype=np.float32) + self.module.foo_single(x) + assert np.allclose(x, [0 + 1 + 2 * 3, 1, 2]) + + @pytest.mark.slow + def test_constant_real_double(self): + # non-contiguous should raise error + x = np.arange(6, dtype=np.float64)[::2] + pytest.raises(ValueError, self.module.foo_double, x) + + # check values with contiguous array + x = np.arange(3, dtype=np.float64) + self.module.foo_double(x) + assert np.allclose(x, [0 + 1 + 2 * 3, 1, 2]) + + @pytest.mark.slow + def test_constant_compound_int(self): + # non-contiguous should raise error + x = np.arange(6, dtype=np.int32)[::2] + pytest.raises(ValueError, self.module.foo_compound_int, x) + + # check values with contiguous array + x = np.arange(3, dtype=np.int32) + self.module.foo_compound_int(x) + assert np.allclose(x, [0 + 1 + 2 * 6, 1, 2]) + + @pytest.mark.slow + def test_constant_non_compound_int(self): + # check values + x = np.arange(4, dtype=np.int32) + self.module.foo_non_compound_int(x) + assert np.allclose(x, [0 + 1 + 2 + 3 * 4, 1, 2, 3]) + + @pytest.mark.slow + def test_constant_integer_int(self): + # non-contiguous should raise error + x = np.arange(6, dtype=np.int32)[::2] + pytest.raises(ValueError, self.module.foo_int, x) + + # check values with contiguous array + x = np.arange(3, dtype=np.int32) + self.module.foo_int(x) + assert np.allclose(x, [0 + 1 + 2 * 3, 1, 2]) + + @pytest.mark.slow + def test_constant_integer_long(self): + # non-contiguous should raise error + x = np.arange(6, dtype=np.int64)[::2] + pytest.raises(ValueError, self.module.foo_long, x) + + # check values with contiguous array + x = np.arange(3, dtype=np.int64) + self.module.foo_long(x) + assert np.allclose(x, [0 + 1 + 2 * 3, 1, 2]) + + @pytest.mark.slow + def test_constant_both(self): + # non-contiguous should raise error + x = np.arange(6, dtype=np.float64)[::2] + pytest.raises(ValueError, self.module.foo, x) + + # check values with contiguous array + x = np.arange(3, dtype=np.float64) + self.module.foo(x) + assert np.allclose(x, [0 + 1 * 3 * 3 + 2 * 3 * 3, 1 * 3, 2 * 3]) + + @pytest.mark.slow + def test_constant_no(self): + # non-contiguous should raise error + x = np.arange(6, dtype=np.float64)[::2] + pytest.raises(ValueError, self.module.foo_no, x) + + # check values with contiguous array + x = np.arange(3, dtype=np.float64) + self.module.foo_no(x) + assert np.allclose(x, [0 + 1 * 3 * 3 + 2 * 3 * 3, 1 * 3, 2 * 3]) + + @pytest.mark.slow + def test_constant_sum(self): + # non-contiguous should raise error + x = np.arange(6, dtype=np.float64)[::2] + pytest.raises(ValueError, self.module.foo_sum, x) + + # check values with contiguous array + x = np.arange(3, dtype=np.float64) + self.module.foo_sum(x) + assert np.allclose(x, [0 + 1 * 3 * 3 + 2 * 3 * 3, 1 * 3, 2 * 3]) + + def test_constant_array(self): + x = np.arange(3, dtype=np.float64) + y = np.arange(5, dtype=np.float64) + z = self.module.foo_array(x, y) + assert np.allclose(x, [0.0, 1. / 10, 2. / 10]) + assert np.allclose(y, [0.0, 1. * 10, 2. * 10, 3. * 10, 4. * 10]) + assert np.allclose(z, 19.0) + + def test_constant_array_any_index(self): + x = np.arange(6, dtype=np.float64) + y = self.module.foo_array_any_index(x) + assert np.allclose(y, x.reshape((2, 3), order='F')) + + def test_constant_array_delims(self): + x = self.module.foo_array_delims() + assert x == 9 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_pyf_src.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_pyf_src.py new file mode 100644 index 0000000000000000000000000000000000000000..2ecb0fbeb8c816752934436fd148f3fa1452fdbe --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_pyf_src.py @@ -0,0 +1,43 @@ +# This test is ported from numpy.distutils +from numpy.f2py._src_pyf import process_str +from numpy.testing import assert_equal + +pyf_src = """ +python module foo + <_rd=real,double precision> + interface + subroutine foosub(tol) + <_rd>, intent(in,out) :: tol + end subroutine foosub + end interface +end python module foo +""" + +expected_pyf = """ +python module foo + interface + subroutine sfoosub(tol) + real, intent(in,out) :: tol + end subroutine sfoosub + subroutine dfoosub(tol) + double precision, intent(in,out) :: tol + end subroutine dfoosub + end interface +end python module foo +""" + + +def normalize_whitespace(s): + """ + Remove leading and trailing whitespace, and convert internal + stretches of whitespace to a single space. + """ + return ' '.join(s.split()) + + +def test_from_template(): + """Regression test for gh-10712.""" + pyf = process_str(pyf_src) + normalized_pyf = normalize_whitespace(pyf) + normalized_expected_pyf = normalize_whitespace(expected_pyf) + assert_equal(normalized_pyf, normalized_expected_pyf) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_quoted_character.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_quoted_character.py new file mode 100644 index 0000000000000000000000000000000000000000..3cbcb3c55b4fabe82b57a0dd5eb84da53bf1d96a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_quoted_character.py @@ -0,0 +1,18 @@ +"""See https://github.com/numpy/numpy/pull/10676. + +""" +import sys + +import pytest + +from . import util + + +class TestQuotedCharacter(util.F2PyTest): + sources = [util.getpath("tests", "src", "quoted_character", "foo.f")] + + @pytest.mark.skipif(sys.platform == "win32", + reason="Fails with MinGW64 Gfortran (Issue #9673)") + @pytest.mark.slow + def test_quoted_character(self): + assert self.module.foo() == (b"'", b'"', b";", b"!", b"(", b")") diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_regression.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_regression.py new file mode 100644 index 0000000000000000000000000000000000000000..c4636a7649147b8e55e93dab81dfb7675e8ef1f3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_regression.py @@ -0,0 +1,187 @@ +import os +import platform + +import pytest + +import numpy as np +import numpy.testing as npt + +from . import util + + +class TestIntentInOut(util.F2PyTest): + # Check that intent(in out) translates as intent(inout) + sources = [util.getpath("tests", "src", "regression", "inout.f90")] + + @pytest.mark.slow + def test_inout(self): + # non-contiguous should raise error + x = np.arange(6, dtype=np.float32)[::2] + pytest.raises(ValueError, self.module.foo, x) + + # check values with contiguous array + x = np.arange(3, dtype=np.float32) + self.module.foo(x) + assert np.allclose(x, [3, 1, 2]) + + +class TestDataOnlyMultiModule(util.F2PyTest): + # Check that modules without subroutines work + sources = [util.getpath("tests", "src", "regression", "datonly.f90")] + + @pytest.mark.slow + def test_mdat(self): + assert self.module.datonly.max_value == 100 + assert self.module.dat.max_ == 1009 + int_in = 5 + assert self.module.simple_subroutine(5) == 1014 + + +class TestModuleWithDerivedType(util.F2PyTest): + # Check that modules with derived types work + sources = [util.getpath("tests", "src", "regression", "mod_derived_types.f90")] + + @pytest.mark.slow + def test_mtypes(self): + assert self.module.no_type_subroutine(10) == 110 + assert self.module.type_subroutine(10) == 210 + + +class TestNegativeBounds(util.F2PyTest): + # Check that negative bounds work correctly + sources = [util.getpath("tests", "src", "negative_bounds", "issue_20853.f90")] + + @pytest.mark.slow + def test_negbound(self): + xvec = np.arange(12) + xlow = -6 + xhigh = 4 + + # Calculate the upper bound, + # Keeping the 1 index in mind + + def ubound(xl, xh): + return xh - xl + 1 + rval = self.module.foo(is_=xlow, ie_=xhigh, + arr=xvec[:ubound(xlow, xhigh)]) + expval = np.arange(11, dtype=np.float32) + assert np.allclose(rval, expval) + + +class TestNumpyVersionAttribute(util.F2PyTest): + # Check that th attribute __f2py_numpy_version__ is present + # in the compiled module and that has the value np.__version__. + sources = [util.getpath("tests", "src", "regression", "inout.f90")] + + @pytest.mark.slow + def test_numpy_version_attribute(self): + + # Check that self.module has an attribute named "__f2py_numpy_version__" + assert hasattr(self.module, "__f2py_numpy_version__") + + # Check that the attribute __f2py_numpy_version__ is a string + assert isinstance(self.module.__f2py_numpy_version__, str) + + # Check that __f2py_numpy_version__ has the value numpy.__version__ + assert np.__version__ == self.module.__f2py_numpy_version__ + + +def test_include_path(): + incdir = np.f2py.get_include() + fnames_in_dir = os.listdir(incdir) + for fname in ("fortranobject.c", "fortranobject.h"): + assert fname in fnames_in_dir + + +class TestIncludeFiles(util.F2PyTest): + sources = [util.getpath("tests", "src", "regression", "incfile.f90")] + options = [f"-I{util.getpath('tests', 'src', 'regression')}", + f"--include-paths {util.getpath('tests', 'src', 'regression')}"] + + @pytest.mark.slow + def test_gh25344(self): + exp = 7.0 + res = self.module.add(3.0, 4.0) + assert exp == res + +class TestF77Comments(util.F2PyTest): + # Check that comments are stripped from F77 continuation lines + sources = [util.getpath("tests", "src", "regression", "f77comments.f")] + + @pytest.mark.slow + def test_gh26148(self): + x1 = np.array(3, dtype=np.int32) + x2 = np.array(5, dtype=np.int32) + res = self.module.testsub(x1, x2) + assert res[0] == 8 + assert res[1] == 15 + + @pytest.mark.slow + def test_gh26466(self): + # Check that comments after PARAMETER directions are stripped + expected = np.arange(1, 11, dtype=np.float32) * 2 + res = self.module.testsub2() + npt.assert_allclose(expected, res) + +class TestF90Contiuation(util.F2PyTest): + # Check that comments are stripped from F90 continuation lines + sources = [util.getpath("tests", "src", "regression", "f90continuation.f90")] + + @pytest.mark.slow + def test_gh26148b(self): + x1 = np.array(3, dtype=np.int32) + x2 = np.array(5, dtype=np.int32) + res = self.module.testsub(x1, x2) + assert res[0] == 8 + assert res[1] == 15 + +class TestLowerF2PYDirectives(util.F2PyTest): + # Check variables are cased correctly + sources = [util.getpath("tests", "src", "regression", "lower_f2py_fortran.f90")] + + @pytest.mark.slow + def test_gh28014(self): + self.module.inquire_next(3) + assert True + +@pytest.mark.slow +def test_gh26623(): + # Including libraries with . should not generate an incorrect meson.build + try: + aa = util.build_module( + [util.getpath("tests", "src", "regression", "f90continuation.f90")], + ["-lfoo.bar"], + module_name="Blah", + ) + except RuntimeError as rerr: + assert "lparen got assign" not in str(rerr) + + +@pytest.mark.slow +@pytest.mark.skipif(platform.system() == "Windows", reason='Unsupported on this platform for now') +def test_gh25784(): + # Compile dubious file using passed flags + try: + aa = util.build_module( + [util.getpath("tests", "src", "regression", "f77fixedform.f95")], + options=[ + # Meson will collect and dedup these to pass to fortran_args: + "--f77flags='-ffixed-form -O2'", + "--f90flags=\"-ffixed-form -g\"", + ], + module_name="Blah", + ) + except ImportError as rerr: + assert "unknown_subroutine_" in str(rerr) + + +@pytest.mark.slow +class TestAssignmentOnlyModules(util.F2PyTest): + # Ensure that variables are exposed without functions or subroutines in a module + sources = [util.getpath("tests", "src", "regression", "assignOnlyModule.f90")] + + @pytest.mark.slow + def test_gh27167(self): + assert (self.module.f_globals.n_max == 16) + assert (self.module.f_globals.i_max == 18) + assert (self.module.f_globals.j_max == 72) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_return_character.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_return_character.py new file mode 100644 index 0000000000000000000000000000000000000000..aae3f0f91671a98259dc76a6bf95a268968b982b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_return_character.py @@ -0,0 +1,48 @@ +import platform + +import pytest + +from numpy import array + +from . import util + +IS_S390X = platform.machine() == "s390x" + + +@pytest.mark.slow +class TestReturnCharacter(util.F2PyTest): + def check_function(self, t, tname): + if tname in ["t0", "t1", "s0", "s1"]: + assert t("23") == b"2" + r = t("ab") + assert r == b"a" + r = t(array("ab")) + assert r == b"a" + r = t(array(77, "u1")) + assert r == b"M" + elif tname in ["ts", "ss"]: + assert t(23) == b"23" + assert t("123456789abcdef") == b"123456789a" + elif tname in ["t5", "s5"]: + assert t(23) == b"23" + assert t("ab") == b"ab" + assert t("123456789abcdef") == b"12345" + else: + raise NotImplementedError + + +class TestFReturnCharacter(TestReturnCharacter): + sources = [ + util.getpath("tests", "src", "return_character", "foo77.f"), + util.getpath("tests", "src", "return_character", "foo90.f90"), + ] + + @pytest.mark.xfail(IS_S390X, reason="callback returns ' '") + @pytest.mark.parametrize("name", ["t0", "t1", "t5", "s0", "s1", "s5", "ss"]) + def test_all_f77(self, name): + self.check_function(getattr(self.module, name), name) + + @pytest.mark.xfail(IS_S390X, reason="callback returns ' '") + @pytest.mark.parametrize("name", ["t0", "t1", "t5", "ts", "s0", "s1", "s5", "ss"]) + def test_all_f90(self, name): + self.check_function(getattr(self.module.f90_return_char, name), name) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_return_complex.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_return_complex.py new file mode 100644 index 0000000000000000000000000000000000000000..aa3f28e679f8d7f86a1009db90f547f6a346fe5a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_return_complex.py @@ -0,0 +1,67 @@ +import pytest + +from numpy import array + +from . import util + + +@pytest.mark.slow +class TestReturnComplex(util.F2PyTest): + def check_function(self, t, tname): + if tname in ["t0", "t8", "s0", "s8"]: + err = 1e-5 + else: + err = 0.0 + assert abs(t(234j) - 234.0j) <= err + assert abs(t(234.6) - 234.6) <= err + assert abs(t(234) - 234.0) <= err + assert abs(t(234.6 + 3j) - (234.6 + 3j)) <= err + # assert abs(t('234')-234.)<=err + # assert abs(t('234.6')-234.6)<=err + assert abs(t(-234) + 234.0) <= err + assert abs(t([234]) - 234.0) <= err + assert abs(t((234, )) - 234.0) <= err + assert abs(t(array(234)) - 234.0) <= err + assert abs(t(array(23 + 4j, "F")) - (23 + 4j)) <= err + assert abs(t(array([234])) - 234.0) <= err + assert abs(t(array([[234]])) - 234.0) <= err + assert abs(t(array([234]).astype("b")) + 22.0) <= err + assert abs(t(array([234], "h")) - 234.0) <= err + assert abs(t(array([234], "i")) - 234.0) <= err + assert abs(t(array([234], "l")) - 234.0) <= err + assert abs(t(array([234], "q")) - 234.0) <= err + assert abs(t(array([234], "f")) - 234.0) <= err + assert abs(t(array([234], "d")) - 234.0) <= err + assert abs(t(array([234 + 3j], "F")) - (234 + 3j)) <= err + assert abs(t(array([234], "D")) - 234.0) <= err + + # pytest.raises(TypeError, t, array([234], 'S1')) + pytest.raises(TypeError, t, "abc") + + pytest.raises(IndexError, t, []) + pytest.raises(IndexError, t, ()) + + pytest.raises(TypeError, t, t) + pytest.raises(TypeError, t, {}) + + try: + r = t(10**400) + assert repr(r) in ["(inf+0j)", "(Infinity+0j)"] + except OverflowError: + pass + + +class TestFReturnComplex(TestReturnComplex): + sources = [ + util.getpath("tests", "src", "return_complex", "foo77.f"), + util.getpath("tests", "src", "return_complex", "foo90.f90"), + ] + + @pytest.mark.parametrize("name", ["t0", "t8", "t16", "td", "s0", "s8", "s16", "sd"]) + def test_all_f77(self, name): + self.check_function(getattr(self.module, name), name) + + @pytest.mark.parametrize("name", ["t0", "t8", "t16", "td", "s0", "s8", "s16", "sd"]) + def test_all_f90(self, name): + self.check_function(getattr(self.module.f90_return_complex, name), + name) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_return_integer.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_return_integer.py new file mode 100644 index 0000000000000000000000000000000000000000..50309d5dadafb9d892f05aeb5a72c59a939ac3de --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_return_integer.py @@ -0,0 +1,55 @@ +import pytest + +from numpy import array + +from . import util + + +@pytest.mark.slow +class TestReturnInteger(util.F2PyTest): + def check_function(self, t, tname): + assert t(123) == 123 + assert t(123.6) == 123 + assert t("123") == 123 + assert t(-123) == -123 + assert t([123]) == 123 + assert t((123, )) == 123 + assert t(array(123)) == 123 + assert t(array(123, "b")) == 123 + assert t(array(123, "h")) == 123 + assert t(array(123, "i")) == 123 + assert t(array(123, "l")) == 123 + assert t(array(123, "B")) == 123 + assert t(array(123, "f")) == 123 + assert t(array(123, "d")) == 123 + + # pytest.raises(ValueError, t, array([123],'S3')) + pytest.raises(ValueError, t, "abc") + + pytest.raises(IndexError, t, []) + pytest.raises(IndexError, t, ()) + + pytest.raises(TypeError, t, t) + pytest.raises(TypeError, t, {}) + + if tname in ["t8", "s8"]: + pytest.raises(OverflowError, t, 100000000000000000000000) + pytest.raises(OverflowError, t, 10000000011111111111111.23) + + +class TestFReturnInteger(TestReturnInteger): + sources = [ + util.getpath("tests", "src", "return_integer", "foo77.f"), + util.getpath("tests", "src", "return_integer", "foo90.f90"), + ] + + @pytest.mark.parametrize("name", + ["t0", "t1", "t2", "t4", "t8", "s0", "s1", "s2", "s4", "s8"]) + def test_all_f77(self, name): + self.check_function(getattr(self.module, name), name) + + @pytest.mark.parametrize("name", + ["t0", "t1", "t2", "t4", "t8", "s0", "s1", "s2", "s4", "s8"]) + def test_all_f90(self, name): + self.check_function(getattr(self.module.f90_return_integer, name), + name) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_return_logical.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_return_logical.py new file mode 100644 index 0000000000000000000000000000000000000000..a4a3395723660a805dd39979bf60460aace4a45a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_return_logical.py @@ -0,0 +1,65 @@ +import pytest + +from numpy import array + +from . import util + + +class TestReturnLogical(util.F2PyTest): + def check_function(self, t): + assert t(True) == 1 + assert t(False) == 0 + assert t(0) == 0 + assert t(None) == 0 + assert t(0.0) == 0 + assert t(0j) == 0 + assert t(1j) == 1 + assert t(234) == 1 + assert t(234.6) == 1 + assert t(234.6 + 3j) == 1 + assert t("234") == 1 + assert t("aaa") == 1 + assert t("") == 0 + assert t([]) == 0 + assert t(()) == 0 + assert t({}) == 0 + assert t(t) == 1 + assert t(-234) == 1 + assert t(10**100) == 1 + assert t([234]) == 1 + assert t((234, )) == 1 + assert t(array(234)) == 1 + assert t(array([234])) == 1 + assert t(array([[234]])) == 1 + assert t(array([127], "b")) == 1 + assert t(array([234], "h")) == 1 + assert t(array([234], "i")) == 1 + assert t(array([234], "l")) == 1 + assert t(array([234], "f")) == 1 + assert t(array([234], "d")) == 1 + assert t(array([234 + 3j], "F")) == 1 + assert t(array([234], "D")) == 1 + assert t(array(0)) == 0 + assert t(array([0])) == 0 + assert t(array([[0]])) == 0 + assert t(array([0j])) == 0 + assert t(array([1])) == 1 + pytest.raises(ValueError, t, array([0, 0])) + + +class TestFReturnLogical(TestReturnLogical): + sources = [ + util.getpath("tests", "src", "return_logical", "foo77.f"), + util.getpath("tests", "src", "return_logical", "foo90.f90"), + ] + + @pytest.mark.slow + @pytest.mark.parametrize("name", ["t0", "t1", "t2", "t4", "s0", "s1", "s2", "s4"]) + def test_all_f77(self, name): + self.check_function(getattr(self.module, name)) + + @pytest.mark.slow + @pytest.mark.parametrize("name", + ["t0", "t1", "t2", "t4", "t8", "s0", "s1", "s2", "s4", "s8"]) + def test_all_f90(self, name): + self.check_function(getattr(self.module.f90_return_logical, name)) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_return_real.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_return_real.py new file mode 100644 index 0000000000000000000000000000000000000000..4339657aa013d2ebb7f214db42c0a20b307ea80d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_return_real.py @@ -0,0 +1,109 @@ +import platform + +import pytest + +from numpy import array +from numpy.testing import IS_64BIT + +from . import util + + +@pytest.mark.slow +class TestReturnReal(util.F2PyTest): + def check_function(self, t, tname): + if tname in ["t0", "t4", "s0", "s4"]: + err = 1e-5 + else: + err = 0.0 + assert abs(t(234) - 234.0) <= err + assert abs(t(234.6) - 234.6) <= err + assert abs(t("234") - 234) <= err + assert abs(t("234.6") - 234.6) <= err + assert abs(t(-234) + 234) <= err + assert abs(t([234]) - 234) <= err + assert abs(t((234, )) - 234.0) <= err + assert abs(t(array(234)) - 234.0) <= err + assert abs(t(array(234).astype("b")) + 22) <= err + assert abs(t(array(234, "h")) - 234.0) <= err + assert abs(t(array(234, "i")) - 234.0) <= err + assert abs(t(array(234, "l")) - 234.0) <= err + assert abs(t(array(234, "B")) - 234.0) <= err + assert abs(t(array(234, "f")) - 234.0) <= err + assert abs(t(array(234, "d")) - 234.0) <= err + if tname in ["t0", "t4", "s0", "s4"]: + assert t(1e200) == t(1e300) # inf + + # pytest.raises(ValueError, t, array([234], 'S1')) + pytest.raises(ValueError, t, "abc") + + pytest.raises(IndexError, t, []) + pytest.raises(IndexError, t, ()) + + pytest.raises(TypeError, t, t) + pytest.raises(TypeError, t, {}) + + try: + r = t(10**400) + assert repr(r) in ["inf", "Infinity"] + except OverflowError: + pass + + +@pytest.mark.skipif( + platform.system() == "Darwin", + reason="Prone to error when run with numpy/f2py/tests on mac os, " + "but not when run in isolation", +) +@pytest.mark.skipif( + not IS_64BIT, reason="32-bit builds are buggy" +) +class TestCReturnReal(TestReturnReal): + suffix = ".pyf" + module_name = "c_ext_return_real" + code = """ +python module c_ext_return_real +usercode \'\'\' +float t4(float value) { return value; } +void s4(float *t4, float value) { *t4 = value; } +double t8(double value) { return value; } +void s8(double *t8, double value) { *t8 = value; } +\'\'\' +interface + function t4(value) + real*4 intent(c) :: t4,value + end + function t8(value) + real*8 intent(c) :: t8,value + end + subroutine s4(t4,value) + intent(c) s4 + real*4 intent(out) :: t4 + real*4 intent(c) :: value + end + subroutine s8(t8,value) + intent(c) s8 + real*8 intent(out) :: t8 + real*8 intent(c) :: value + end +end interface +end python module c_ext_return_real + """ + + @pytest.mark.parametrize("name", ["t4", "t8", "s4", "s8"]) + def test_all(self, name): + self.check_function(getattr(self.module, name), name) + + +class TestFReturnReal(TestReturnReal): + sources = [ + util.getpath("tests", "src", "return_real", "foo77.f"), + util.getpath("tests", "src", "return_real", "foo90.f90"), + ] + + @pytest.mark.parametrize("name", ["t0", "t4", "t8", "td", "s0", "s4", "s8", "sd"]) + def test_all_f77(self, name): + self.check_function(getattr(self.module, name), name) + + @pytest.mark.parametrize("name", ["t0", "t4", "t8", "td", "s0", "s4", "s8", "sd"]) + def test_all_f90(self, name): + self.check_function(getattr(self.module.f90_return_real, name), name) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_routines.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_routines.py new file mode 100644 index 0000000000000000000000000000000000000000..01135dd692a6776ca47e52867ba56f037ef7476f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_routines.py @@ -0,0 +1,29 @@ +import pytest + +from . import util + + +@pytest.mark.slow +class TestRenamedFunc(util.F2PyTest): + sources = [ + util.getpath("tests", "src", "routines", "funcfortranname.f"), + util.getpath("tests", "src", "routines", "funcfortranname.pyf"), + ] + module_name = "funcfortranname" + + def test_gh25799(self): + assert dir(self.module) + assert self.module.funcfortranname_default(200, 12) == 212 + + +@pytest.mark.slow +class TestRenamedSubroutine(util.F2PyTest): + sources = [ + util.getpath("tests", "src", "routines", "subrout.f"), + util.getpath("tests", "src", "routines", "subrout.pyf"), + ] + module_name = "subrout" + + def test_renamed_subroutine(self): + assert dir(self.module) + assert self.module.subrout_default(200, 12) == 212 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_semicolon_split.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_semicolon_split.py new file mode 100644 index 0000000000000000000000000000000000000000..2a16b191bebaae3cc7775d2fc026f12e01aeb4d3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_semicolon_split.py @@ -0,0 +1,75 @@ +import platform + +import pytest + +from numpy.testing import IS_64BIT + +from . import util + + +@pytest.mark.skipif( + platform.system() == "Darwin", + reason="Prone to error when run with numpy/f2py/tests on mac os, " + "but not when run in isolation", +) +@pytest.mark.skipif( + not IS_64BIT, reason="32-bit builds are buggy" +) +class TestMultiline(util.F2PyTest): + suffix = ".pyf" + module_name = "multiline" + code = f""" +python module {module_name} + usercode ''' +void foo(int* x) {{ + char dummy = ';'; + *x = 42; +}} +''' + interface + subroutine foo(x) + intent(c) foo + integer intent(out) :: x + end subroutine foo + end interface +end python module {module_name} + """ + + def test_multiline(self): + assert self.module.foo() == 42 + + +@pytest.mark.skipif( + platform.system() == "Darwin", + reason="Prone to error when run with numpy/f2py/tests on mac os, " + "but not when run in isolation", +) +@pytest.mark.skipif( + not IS_64BIT, reason="32-bit builds are buggy" +) +@pytest.mark.slow +class TestCallstatement(util.F2PyTest): + suffix = ".pyf" + module_name = "callstatement" + code = f""" +python module {module_name} + usercode ''' +void foo(int* x) {{ +}} +''' + interface + subroutine foo(x) + intent(c) foo + integer intent(out) :: x + callprotoargument int* + callstatement {{ & + ; & + x = 42; & + }} + end subroutine foo + end interface +end python module {module_name} + """ + + def test_callstatement(self): + assert self.module.foo() == 42 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_size.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_size.py new file mode 100644 index 0000000000000000000000000000000000000000..ac2eaf1413efe6e99f7b519827b1032cef941d88 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_size.py @@ -0,0 +1,45 @@ +import pytest + +import numpy as np + +from . import util + + +class TestSizeSumExample(util.F2PyTest): + sources = [util.getpath("tests", "src", "size", "foo.f90")] + + @pytest.mark.slow + def test_all(self): + r = self.module.foo([[]]) + assert r == [0] + + r = self.module.foo([[1, 2]]) + assert r == [3] + + r = self.module.foo([[1, 2], [3, 4]]) + assert np.allclose(r, [3, 7]) + + r = self.module.foo([[1, 2], [3, 4], [5, 6]]) + assert np.allclose(r, [3, 7, 11]) + + @pytest.mark.slow + def test_transpose(self): + r = self.module.trans([[]]) + assert np.allclose(r.T, np.array([[]])) + + r = self.module.trans([[1, 2]]) + assert np.allclose(r, [[1.], [2.]]) + + r = self.module.trans([[1, 2, 3], [4, 5, 6]]) + assert np.allclose(r, [[1, 4], [2, 5], [3, 6]]) + + @pytest.mark.slow + def test_flatten(self): + r = self.module.flatten([[]]) + assert np.allclose(r, []) + + r = self.module.flatten([[1, 2]]) + assert np.allclose(r, [1, 2]) + + r = self.module.flatten([[1, 2, 3], [4, 5, 6]]) + assert np.allclose(r, [1, 2, 3, 4, 5, 6]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_string.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_string.py new file mode 100644 index 0000000000000000000000000000000000000000..f484ea3f11a9d2bef2fd0357feda45a0e40ff365 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_string.py @@ -0,0 +1,100 @@ +import pytest + +import numpy as np + +from . import util + + +class TestString(util.F2PyTest): + sources = [util.getpath("tests", "src", "string", "char.f90")] + + @pytest.mark.slow + def test_char(self): + strings = np.array(["ab", "cd", "ef"], dtype="c").T + inp, out = self.module.char_test.change_strings( + strings, strings.shape[1]) + assert inp == pytest.approx(strings) + expected = strings.copy() + expected[1, :] = "AAA" + assert out == pytest.approx(expected) + + +class TestDocStringArguments(util.F2PyTest): + sources = [util.getpath("tests", "src", "string", "string.f")] + + def test_example(self): + a = np.array(b"123\0\0") + b = np.array(b"123\0\0") + c = np.array(b"123") + d = np.array(b"123") + + self.module.foo(a, b, c, d) + + assert a.tobytes() == b"123\0\0" + assert b.tobytes() == b"B23\0\0" + assert c.tobytes() == b"123" + assert d.tobytes() == b"D23" + + +class TestFixedString(util.F2PyTest): + sources = [util.getpath("tests", "src", "string", "fixed_string.f90")] + + @staticmethod + def _sint(s, start=0, end=None): + """Return the content of a string buffer as integer value. + + For example: + _sint('1234') -> 4321 + _sint('123A') -> 17321 + """ + if isinstance(s, np.ndarray): + s = s.tobytes() + elif isinstance(s, str): + s = s.encode() + assert isinstance(s, bytes) + if end is None: + end = len(s) + i = 0 + for j in range(start, min(end, len(s))): + i += s[j] * 10**j + return i + + def _get_input(self, intent="in"): + if intent in ["in"]: + yield "" + yield "1" + yield "1234" + yield "12345" + yield b"" + yield b"\0" + yield b"1" + yield b"\01" + yield b"1\0" + yield b"1234" + yield b"12345" + yield np.ndarray((), np.bytes_, buffer=b"") # array(b'', dtype='|S0') + yield np.array(b"") # array(b'', dtype='|S1') + yield np.array(b"\0") + yield np.array(b"1") + yield np.array(b"1\0") + yield np.array(b"\01") + yield np.array(b"1234") + yield np.array(b"123\0") + yield np.array(b"12345") + + def test_intent_in(self): + for s in self._get_input(): + r = self.module.test_in_bytes4(s) + # also checks that s is not changed inplace + expected = self._sint(s, end=4) + assert r == expected, s + + def test_intent_inout(self): + for s in self._get_input(intent="inout"): + rest = self._sint(s, start=4) + r = self.module.test_inout_bytes4(s) + expected = self._sint(s, end=4) + assert r == expected + + # check that the rest of input string is preserved + assert rest == self._sint(s, start=4) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_symbolic.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_symbolic.py new file mode 100644 index 0000000000000000000000000000000000000000..fbf5abd9aa18c5b09d3c69ba4a0fc855c7f19810 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_symbolic.py @@ -0,0 +1,500 @@ +import pytest + +from numpy.f2py.symbolic import ( + ArithOp, + Expr, + Language, + Op, + as_apply, + as_array, + as_complex, + as_deref, + as_eq, + as_expr, + as_factors, + as_ge, + as_gt, + as_le, + as_lt, + as_ne, + as_number, + as_numer_denom, + as_ref, + as_string, + as_symbol, + as_terms, + as_ternary, + eliminate_quotes, + fromstring, + insert_quotes, + normalize, +) + +from . import util + + +class TestSymbolic(util.F2PyTest): + def test_eliminate_quotes(self): + def worker(s): + r, d = eliminate_quotes(s) + s1 = insert_quotes(r, d) + assert s1 == s + + for kind in ["", "mykind_"]: + worker(kind + '"1234" // "ABCD"') + worker(kind + '"1234" // ' + kind + '"ABCD"') + worker(kind + "\"1234\" // 'ABCD'") + worker(kind + '"1234" // ' + kind + "'ABCD'") + worker(kind + '"1\\"2\'AB\'34"') + worker("a = " + kind + "'1\\'2\"AB\"34'") + + def test_sanity(self): + x = as_symbol("x") + y = as_symbol("y") + z = as_symbol("z") + + assert x.op == Op.SYMBOL + assert repr(x) == "Expr(Op.SYMBOL, 'x')" + assert x == x + assert x != y + assert hash(x) is not None + + n = as_number(123) + m = as_number(456) + assert n.op == Op.INTEGER + assert repr(n) == "Expr(Op.INTEGER, (123, 4))" + assert n == n + assert n != m + assert hash(n) is not None + + fn = as_number(12.3) + fm = as_number(45.6) + assert fn.op == Op.REAL + assert repr(fn) == "Expr(Op.REAL, (12.3, 4))" + assert fn == fn + assert fn != fm + assert hash(fn) is not None + + c = as_complex(1, 2) + c2 = as_complex(3, 4) + assert c.op == Op.COMPLEX + assert repr(c) == ("Expr(Op.COMPLEX, (Expr(Op.INTEGER, (1, 4))," + " Expr(Op.INTEGER, (2, 4))))") + assert c == c + assert c != c2 + assert hash(c) is not None + + s = as_string("'123'") + s2 = as_string('"ABC"') + assert s.op == Op.STRING + assert repr(s) == "Expr(Op.STRING, (\"'123'\", 1))", repr(s) + assert s == s + assert s != s2 + + a = as_array((n, m)) + b = as_array((n, )) + assert a.op == Op.ARRAY + assert repr(a) == ("Expr(Op.ARRAY, (Expr(Op.INTEGER, (123, 4))," + " Expr(Op.INTEGER, (456, 4))))") + assert a == a + assert a != b + + t = as_terms(x) + u = as_terms(y) + assert t.op == Op.TERMS + assert repr(t) == "Expr(Op.TERMS, {Expr(Op.SYMBOL, 'x'): 1})" + assert t == t + assert t != u + assert hash(t) is not None + + v = as_factors(x) + w = as_factors(y) + assert v.op == Op.FACTORS + assert repr(v) == "Expr(Op.FACTORS, {Expr(Op.SYMBOL, 'x'): 1})" + assert v == v + assert w != v + assert hash(v) is not None + + t = as_ternary(x, y, z) + u = as_ternary(x, z, y) + assert t.op == Op.TERNARY + assert t == t + assert t != u + assert hash(t) is not None + + e = as_eq(x, y) + f = as_lt(x, y) + assert e.op == Op.RELATIONAL + assert e == e + assert e != f + assert hash(e) is not None + + def test_tostring_fortran(self): + x = as_symbol("x") + y = as_symbol("y") + z = as_symbol("z") + n = as_number(123) + m = as_number(456) + a = as_array((n, m)) + c = as_complex(n, m) + + assert str(x) == "x" + assert str(n) == "123" + assert str(a) == "[123, 456]" + assert str(c) == "(123, 456)" + + assert str(Expr(Op.TERMS, {x: 1})) == "x" + assert str(Expr(Op.TERMS, {x: 2})) == "2 * x" + assert str(Expr(Op.TERMS, {x: -1})) == "-x" + assert str(Expr(Op.TERMS, {x: -2})) == "-2 * x" + assert str(Expr(Op.TERMS, {x: 1, y: 1})) == "x + y" + assert str(Expr(Op.TERMS, {x: -1, y: -1})) == "-x - y" + assert str(Expr(Op.TERMS, {x: 2, y: 3})) == "2 * x + 3 * y" + assert str(Expr(Op.TERMS, {x: -2, y: 3})) == "-2 * x + 3 * y" + assert str(Expr(Op.TERMS, {x: 2, y: -3})) == "2 * x - 3 * y" + + assert str(Expr(Op.FACTORS, {x: 1})) == "x" + assert str(Expr(Op.FACTORS, {x: 2})) == "x ** 2" + assert str(Expr(Op.FACTORS, {x: -1})) == "x ** -1" + assert str(Expr(Op.FACTORS, {x: -2})) == "x ** -2" + assert str(Expr(Op.FACTORS, {x: 1, y: 1})) == "x * y" + assert str(Expr(Op.FACTORS, {x: 2, y: 3})) == "x ** 2 * y ** 3" + + v = Expr(Op.FACTORS, {x: 2, Expr(Op.TERMS, {x: 1, y: 1}): 3}) + assert str(v) == "x ** 2 * (x + y) ** 3", str(v) + v = Expr(Op.FACTORS, {x: 2, Expr(Op.FACTORS, {x: 1, y: 1}): 3}) + assert str(v) == "x ** 2 * (x * y) ** 3", str(v) + + assert str(Expr(Op.APPLY, ("f", (), {}))) == "f()" + assert str(Expr(Op.APPLY, ("f", (x, ), {}))) == "f(x)" + assert str(Expr(Op.APPLY, ("f", (x, y), {}))) == "f(x, y)" + assert str(Expr(Op.INDEXING, ("f", x))) == "f[x]" + + assert str(as_ternary(x, y, z)) == "merge(y, z, x)" + assert str(as_eq(x, y)) == "x .eq. y" + assert str(as_ne(x, y)) == "x .ne. y" + assert str(as_lt(x, y)) == "x .lt. y" + assert str(as_le(x, y)) == "x .le. y" + assert str(as_gt(x, y)) == "x .gt. y" + assert str(as_ge(x, y)) == "x .ge. y" + + def test_tostring_c(self): + language = Language.C + x = as_symbol("x") + y = as_symbol("y") + z = as_symbol("z") + n = as_number(123) + + assert Expr(Op.FACTORS, {x: 2}).tostring(language=language) == "x * x" + assert (Expr(Op.FACTORS, { + x + y: 2 + }).tostring(language=language) == "(x + y) * (x + y)") + assert Expr(Op.FACTORS, { + x: 12 + }).tostring(language=language) == "pow(x, 12)" + + assert as_apply(ArithOp.DIV, x, + y).tostring(language=language) == "x / y" + assert (as_apply(ArithOp.DIV, x, + x + y).tostring(language=language) == "x / (x + y)") + assert (as_apply(ArithOp.DIV, x - y, x + + y).tostring(language=language) == "(x - y) / (x + y)") + assert (x + (x - y) / (x + y) + + n).tostring(language=language) == "123 + x + (x - y) / (x + y)" + + assert as_ternary(x, y, z).tostring(language=language) == "(x?y:z)" + assert as_eq(x, y).tostring(language=language) == "x == y" + assert as_ne(x, y).tostring(language=language) == "x != y" + assert as_lt(x, y).tostring(language=language) == "x < y" + assert as_le(x, y).tostring(language=language) == "x <= y" + assert as_gt(x, y).tostring(language=language) == "x > y" + assert as_ge(x, y).tostring(language=language) == "x >= y" + + def test_operations(self): + x = as_symbol("x") + y = as_symbol("y") + z = as_symbol("z") + + assert x + x == Expr(Op.TERMS, {x: 2}) + assert x - x == Expr(Op.INTEGER, (0, 4)) + assert x + y == Expr(Op.TERMS, {x: 1, y: 1}) + assert x - y == Expr(Op.TERMS, {x: 1, y: -1}) + assert x * x == Expr(Op.FACTORS, {x: 2}) + assert x * y == Expr(Op.FACTORS, {x: 1, y: 1}) + + assert +x == x + assert -x == Expr(Op.TERMS, {x: -1}), repr(-x) + assert 2 * x == Expr(Op.TERMS, {x: 2}) + assert 2 + x == Expr(Op.TERMS, {x: 1, as_number(1): 2}) + assert 2 * x + 3 * y == Expr(Op.TERMS, {x: 2, y: 3}) + assert (x + y) * 2 == Expr(Op.TERMS, {x: 2, y: 2}) + + assert x**2 == Expr(Op.FACTORS, {x: 2}) + assert (x + y)**2 == Expr( + Op.TERMS, + { + Expr(Op.FACTORS, {x: 2}): 1, + Expr(Op.FACTORS, {y: 2}): 1, + Expr(Op.FACTORS, { + x: 1, + y: 1 + }): 2, + }, + ) + assert (x + y) * x == x**2 + x * y + assert (x + y)**2 == x**2 + 2 * x * y + y**2 + assert (x + y)**2 + (x - y)**2 == 2 * x**2 + 2 * y**2 + assert (x + y) * z == x * z + y * z + assert z * (x + y) == x * z + y * z + + assert (x / 2) == as_apply(ArithOp.DIV, x, as_number(2)) + assert (2 * x / 2) == x + assert (3 * x / 2) == as_apply(ArithOp.DIV, 3 * x, as_number(2)) + assert (4 * x / 2) == 2 * x + assert (5 * x / 2) == as_apply(ArithOp.DIV, 5 * x, as_number(2)) + assert (6 * x / 2) == 3 * x + assert ((3 * 5) * x / 6) == as_apply(ArithOp.DIV, 5 * x, as_number(2)) + assert (30 * x**2 * y**4 / (24 * x**3 * y**3)) == as_apply( + ArithOp.DIV, 5 * y, 4 * x) + assert ((15 * x / 6) / 5) == as_apply(ArithOp.DIV, x, + as_number(2)), (15 * x / 6) / 5 + assert (x / (5 / x)) == as_apply(ArithOp.DIV, x**2, as_number(5)) + + assert (x / 2.0) == Expr(Op.TERMS, {x: 0.5}) + + s = as_string('"ABC"') + t = as_string('"123"') + + assert s // t == Expr(Op.STRING, ('"ABC123"', 1)) + assert s // x == Expr(Op.CONCAT, (s, x)) + assert x // s == Expr(Op.CONCAT, (x, s)) + + c = as_complex(1.0, 2.0) + assert -c == as_complex(-1.0, -2.0) + assert c + c == as_expr((1 + 2j) * 2) + assert c * c == as_expr((1 + 2j)**2) + + def test_substitute(self): + x = as_symbol("x") + y = as_symbol("y") + z = as_symbol("z") + a = as_array((x, y)) + + assert x.substitute({x: y}) == y + assert (x + y).substitute({x: z}) == y + z + assert (x * y).substitute({x: z}) == y * z + assert (x**4).substitute({x: z}) == z**4 + assert (x / y).substitute({x: z}) == z / y + assert x.substitute({x: y + z}) == y + z + assert a.substitute({x: y + z}) == as_array((y + z, y)) + + assert as_ternary(x, y, + z).substitute({x: y + z}) == as_ternary(y + z, y, z) + assert as_eq(x, y).substitute({x: y + z}) == as_eq(y + z, y) + + def test_fromstring(self): + + x = as_symbol("x") + y = as_symbol("y") + z = as_symbol("z") + f = as_symbol("f") + s = as_string('"ABC"') + t = as_string('"123"') + a = as_array((x, y)) + + assert fromstring("x") == x + assert fromstring("+ x") == x + assert fromstring("- x") == -x + assert fromstring("x + y") == x + y + assert fromstring("x + 1") == x + 1 + assert fromstring("x * y") == x * y + assert fromstring("x * 2") == x * 2 + assert fromstring("x / y") == x / y + assert fromstring("x ** 2", language=Language.Python) == x**2 + assert fromstring("x ** 2 ** 3", language=Language.Python) == x**2**3 + assert fromstring("(x + y) * z") == (x + y) * z + + assert fromstring("f(x)") == f(x) + assert fromstring("f(x,y)") == f(x, y) + assert fromstring("f[x]") == f[x] + assert fromstring("f[x][y]") == f[x][y] + + assert fromstring('"ABC"') == s + assert (normalize( + fromstring('"ABC" // "123" ', + language=Language.Fortran)) == s // t) + assert fromstring('f("ABC")') == f(s) + assert fromstring('MYSTRKIND_"ABC"') == as_string('"ABC"', "MYSTRKIND") + + assert fromstring("(/x, y/)") == a, fromstring("(/x, y/)") + assert fromstring("f((/x, y/))") == f(a) + assert fromstring("(/(x+y)*z/)") == as_array(((x + y) * z, )) + + assert fromstring("123") == as_number(123) + assert fromstring("123_2") == as_number(123, 2) + assert fromstring("123_myintkind") == as_number(123, "myintkind") + + assert fromstring("123.0") == as_number(123.0, 4) + assert fromstring("123.0_4") == as_number(123.0, 4) + assert fromstring("123.0_8") == as_number(123.0, 8) + assert fromstring("123.0e0") == as_number(123.0, 4) + assert fromstring("123.0d0") == as_number(123.0, 8) + assert fromstring("123d0") == as_number(123.0, 8) + assert fromstring("123e-0") == as_number(123.0, 4) + assert fromstring("123d+0") == as_number(123.0, 8) + assert fromstring("123.0_myrealkind") == as_number(123.0, "myrealkind") + assert fromstring("3E4") == as_number(30000.0, 4) + + assert fromstring("(1, 2)") == as_complex(1, 2) + assert fromstring("(1e2, PI)") == as_complex(as_number(100.0), + as_symbol("PI")) + + assert fromstring("[1, 2]") == as_array((as_number(1), as_number(2))) + + assert fromstring("POINT(x, y=1)") == as_apply(as_symbol("POINT"), + x, + y=as_number(1)) + assert fromstring( + 'PERSON(name="John", age=50, shape=(/34, 23/))') == as_apply( + as_symbol("PERSON"), + name=as_string('"John"'), + age=as_number(50), + shape=as_array((as_number(34), as_number(23))), + ) + + assert fromstring("x?y:z") == as_ternary(x, y, z) + + assert fromstring("*x") == as_deref(x) + assert fromstring("**x") == as_deref(as_deref(x)) + assert fromstring("&x") == as_ref(x) + assert fromstring("(*x) * (*y)") == as_deref(x) * as_deref(y) + assert fromstring("(*x) * *y") == as_deref(x) * as_deref(y) + assert fromstring("*x * *y") == as_deref(x) * as_deref(y) + assert fromstring("*x**y") == as_deref(x) * as_deref(y) + + assert fromstring("x == y") == as_eq(x, y) + assert fromstring("x != y") == as_ne(x, y) + assert fromstring("x < y") == as_lt(x, y) + assert fromstring("x > y") == as_gt(x, y) + assert fromstring("x <= y") == as_le(x, y) + assert fromstring("x >= y") == as_ge(x, y) + + assert fromstring("x .eq. y", language=Language.Fortran) == as_eq(x, y) + assert fromstring("x .ne. y", language=Language.Fortran) == as_ne(x, y) + assert fromstring("x .lt. y", language=Language.Fortran) == as_lt(x, y) + assert fromstring("x .gt. y", language=Language.Fortran) == as_gt(x, y) + assert fromstring("x .le. y", language=Language.Fortran) == as_le(x, y) + assert fromstring("x .ge. y", language=Language.Fortran) == as_ge(x, y) + + def test_traverse(self): + x = as_symbol("x") + y = as_symbol("y") + z = as_symbol("z") + f = as_symbol("f") + + # Use traverse to substitute a symbol + def replace_visit(s, r=z): + if s == x: + return r + + assert x.traverse(replace_visit) == z + assert y.traverse(replace_visit) == y + assert z.traverse(replace_visit) == z + assert (f(y)).traverse(replace_visit) == f(y) + assert (f(x)).traverse(replace_visit) == f(z) + assert (f[y]).traverse(replace_visit) == f[y] + assert (f[z]).traverse(replace_visit) == f[z] + assert (x + y + z).traverse(replace_visit) == (2 * z + y) + assert (x + + f(y, x - z)).traverse(replace_visit) == (z + + f(y, as_number(0))) + assert as_eq(x, y).traverse(replace_visit) == as_eq(z, y) + + # Use traverse to collect symbols, method 1 + function_symbols = set() + symbols = set() + + def collect_symbols(s): + if s.op is Op.APPLY: + oper = s.data[0] + function_symbols.add(oper) + if oper in symbols: + symbols.remove(oper) + elif s.op is Op.SYMBOL and s not in function_symbols: + symbols.add(s) + + (x + f(y, x - z)).traverse(collect_symbols) + assert function_symbols == {f} + assert symbols == {x, y, z} + + # Use traverse to collect symbols, method 2 + def collect_symbols2(expr, symbols): + if expr.op is Op.SYMBOL: + symbols.add(expr) + + symbols = set() + (x + f(y, x - z)).traverse(collect_symbols2, symbols) + assert symbols == {x, y, z, f} + + # Use traverse to partially collect symbols + def collect_symbols3(expr, symbols): + if expr.op is Op.APPLY: + # skip traversing function calls + return expr + if expr.op is Op.SYMBOL: + symbols.add(expr) + + symbols = set() + (x + f(y, x - z)).traverse(collect_symbols3, symbols) + assert symbols == {x} + + def test_linear_solve(self): + x = as_symbol("x") + y = as_symbol("y") + z = as_symbol("z") + + assert x.linear_solve(x) == (as_number(1), as_number(0)) + assert (x + 1).linear_solve(x) == (as_number(1), as_number(1)) + assert (2 * x).linear_solve(x) == (as_number(2), as_number(0)) + assert (2 * x + 3).linear_solve(x) == (as_number(2), as_number(3)) + assert as_number(3).linear_solve(x) == (as_number(0), as_number(3)) + assert y.linear_solve(x) == (as_number(0), y) + assert (y * z).linear_solve(x) == (as_number(0), y * z) + + assert (x + y).linear_solve(x) == (as_number(1), y) + assert (z * x + y).linear_solve(x) == (z, y) + assert ((z + y) * x + y).linear_solve(x) == (z + y, y) + assert (z * y * x + y).linear_solve(x) == (z * y, y) + + pytest.raises(RuntimeError, lambda: (x * x).linear_solve(x)) + + def test_as_numer_denom(self): + x = as_symbol("x") + y = as_symbol("y") + n = as_number(123) + + assert as_numer_denom(x) == (x, as_number(1)) + assert as_numer_denom(x / n) == (x, n) + assert as_numer_denom(n / x) == (n, x) + assert as_numer_denom(x / y) == (x, y) + assert as_numer_denom(x * y) == (x * y, as_number(1)) + assert as_numer_denom(n + x / y) == (x + n * y, y) + assert as_numer_denom(n + x / (y - x / n)) == (y * n**2, y * n - x) + + def test_polynomial_atoms(self): + x = as_symbol("x") + y = as_symbol("y") + n = as_number(123) + + assert x.polynomial_atoms() == {x} + assert n.polynomial_atoms() == set() + assert (y[x]).polynomial_atoms() == {y[x]} + assert (y(x)).polynomial_atoms() == {y(x)} + assert (y(x) + x).polynomial_atoms() == {y(x), x} + assert (y(x) * x[y]).polynomial_atoms() == {y(x), x[y]} + assert (y(x)**x).polynomial_atoms() == {y(x)} + + def test_unmatched_parenthesis_gh30268(self): + #gh - 30268 + with pytest.raises(ValueError, match=r"Mismatch of \(\) parenthesis"): + Expr.parse("DATA (A, I=1, N", language=Language.Fortran) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_value_attrspec.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_value_attrspec.py new file mode 100644 index 0000000000000000000000000000000000000000..1afae08bfe0ecbba5bec31373348817cd87e9468 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/test_value_attrspec.py @@ -0,0 +1,15 @@ +import pytest + +from . import util + + +class TestValueAttr(util.F2PyTest): + sources = [util.getpath("tests", "src", "value_attrspec", "gh21665.f90")] + + # gh-21665 + @pytest.mark.slow + def test_gh21665(self): + inp = 2 + out = self.module.fortfuncs.square(inp) + exp_out = 4 + assert out == exp_out diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/util.py b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/util.py new file mode 100644 index 0000000000000000000000000000000000000000..35e5d3bd8ac07c5926477a63a8dc26f380467042 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/f2py/tests/util.py @@ -0,0 +1,442 @@ +""" +Utility functions for + +- building and importing modules on test time, using a temporary location +- detecting if compilers are present +- determining paths to tests + +""" +import atexit +import concurrent.futures +import contextlib +import glob +import os +import shutil +import subprocess +import sys +import tempfile +from importlib import import_module +from pathlib import Path + +import pytest + +import numpy +from numpy._utils import asunicode +from numpy.f2py._backends._meson import MesonBackend +from numpy.testing import IS_WASM, temppath + +# +# Check if compilers are available at all... +# + +def check_language(lang, code_snippet=None): + if sys.platform == "win32": + pytest.skip("No Fortran tests on Windows (Issue #25134)", allow_module_level=True) + tmpdir = tempfile.mkdtemp() + try: + meson_file = os.path.join(tmpdir, "meson.build") + with open(meson_file, "w") as f: + f.write("project('check_compilers')\n") + f.write(f"add_languages('{lang}')\n") + if code_snippet: + f.write(f"{lang}_compiler = meson.get_compiler('{lang}')\n") + f.write(f"{lang}_code = '''{code_snippet}'''\n") + f.write( + f"_have_{lang}_feature =" + f"{lang}_compiler.compiles({lang}_code," + f" name: '{lang} feature check')\n" + ) + try: + runmeson = subprocess.run( + ["meson", "setup", "btmp"], + check=False, + cwd=tmpdir, + capture_output=True, + ) + except subprocess.CalledProcessError: + pytest.skip("meson not present, skipping compiler dependent test", allow_module_level=True) + return runmeson.returncode == 0 + finally: + shutil.rmtree(tmpdir) + + +fortran77_code = ''' +C Example Fortran 77 code + PROGRAM HELLO + PRINT *, 'Hello, Fortran 77!' + END +''' + +fortran90_code = ''' +! Example Fortran 90 code +program hello90 + type :: greeting + character(len=20) :: text + end type greeting + + type(greeting) :: greet + greet%text = 'hello, fortran 90!' + print *, greet%text +end program hello90 +''' + +# Dummy class for caching relevant checks +class CompilerChecker: + def __init__(self): + self.compilers_checked = False + self.has_c = False + self.has_f77 = False + self.has_f90 = False + + def check_compilers(self): + if (not self.compilers_checked) and (not sys.platform == "cygwin"): + with concurrent.futures.ThreadPoolExecutor() as executor: + futures = [ + executor.submit(check_language, "c"), + executor.submit(check_language, "fortran", fortran77_code), + executor.submit(check_language, "fortran", fortran90_code) + ] + + self.has_c = futures[0].result() + self.has_f77 = futures[1].result() + self.has_f90 = futures[2].result() + + self.compilers_checked = True + + +if not IS_WASM: + checker = CompilerChecker() + checker.check_compilers() + +def has_c_compiler(): + return checker.has_c + +def has_f77_compiler(): + return checker.has_f77 + +def has_f90_compiler(): + return checker.has_f90 + +def has_fortran_compiler(): + return (checker.has_f90 and checker.has_f77) + + +# +# Maintaining a temporary module directory +# + +_module_dir = None +_module_num = 5403 + +if sys.platform == "cygwin": + NUMPY_INSTALL_ROOT = Path(__file__).parent.parent.parent + _module_list = list(NUMPY_INSTALL_ROOT.glob("**/*.dll")) + + +def _cleanup(): + global _module_dir + if _module_dir is not None: + try: + sys.path.remove(_module_dir) + except ValueError: + pass + try: + shutil.rmtree(_module_dir) + except OSError: + pass + _module_dir = None + + +def get_module_dir(): + global _module_dir + if _module_dir is None: + _module_dir = tempfile.mkdtemp() + atexit.register(_cleanup) + if _module_dir not in sys.path: + sys.path.insert(0, _module_dir) + return _module_dir + + +def get_temp_module_name(): + # Assume single-threaded, and the module dir usable only by this thread + global _module_num + get_module_dir() + name = "_test_ext_module_%d" % _module_num + _module_num += 1 + if name in sys.modules: + # this should not be possible, but check anyway + raise RuntimeError("Temporary module name already in use.") + return name + + +def _memoize(func): + memo = {} + + def wrapper(*a, **kw): + key = repr((a, kw)) + if key not in memo: + try: + memo[key] = func(*a, **kw) + except Exception as e: + memo[key] = e + raise + ret = memo[key] + if isinstance(ret, Exception): + raise ret + return ret + + wrapper.__name__ = func.__name__ + return wrapper + + +# +# Building modules +# + + +@_memoize +def build_module(source_files, options=[], skip=[], only=[], module_name=None): + """ + Compile and import a f2py module, built from the given files. + + """ + + code = f"import sys; sys.path = {sys.path!r}; import numpy.f2py; numpy.f2py.main()" + + d = get_module_dir() + # gh-27045 : Skip if no compilers are found + if not has_fortran_compiler(): + pytest.skip("No Fortran compiler available") + + # Copy files + dst_sources = [] + f2py_sources = [] + for fn in source_files: + if not os.path.isfile(fn): + raise RuntimeError(f"{fn} is not a file") + dst = os.path.join(d, os.path.basename(fn)) + shutil.copyfile(fn, dst) + dst_sources.append(dst) + + base, ext = os.path.splitext(dst) + if ext in (".f90", ".f95", ".f", ".c", ".pyf"): + f2py_sources.append(dst) + + assert f2py_sources + + # Prepare options + if module_name is None: + module_name = get_temp_module_name() + gil_options = [] + if '--freethreading-compatible' not in options and '--no-freethreading-compatible' not in options: + # default to disabling the GIL if unset in options + gil_options = ['--freethreading-compatible'] + f2py_opts = ["-c", "-m", module_name] + options + gil_options + f2py_sources + f2py_opts += ["--backend", "meson"] + if skip: + f2py_opts += ["skip:"] + skip + if only: + f2py_opts += ["only:"] + only + + # Build + cwd = os.getcwd() + try: + os.chdir(d) + cmd = [sys.executable, "-c", code] + f2py_opts + p = subprocess.Popen(cmd, + stdout=subprocess.PIPE, + stderr=subprocess.STDOUT) + out, err = p.communicate() + if p.returncode != 0: + raise RuntimeError(f"Running f2py failed: {cmd[4:]}\n{asunicode(out)}") + finally: + os.chdir(cwd) + + # Partial cleanup + for fn in dst_sources: + os.unlink(fn) + + # Rebase (Cygwin-only) + if sys.platform == "cygwin": + # If someone starts deleting modules after import, this will + # need to change to record how big each module is, rather than + # relying on rebase being able to find that from the files. + _module_list.extend( + glob.glob(os.path.join(d, f"{module_name:s}*")) + ) + subprocess.check_call( + ["/usr/bin/rebase", "--database", "--oblivious", "--verbose"] + + _module_list + ) + + # Import + return import_module(module_name) + + +@_memoize +def build_code(source_code, + options=[], + skip=[], + only=[], + suffix=None, + module_name=None): + """ + Compile and import Fortran code using f2py. + + """ + if suffix is None: + suffix = ".f" + with temppath(suffix=suffix) as path: + with open(path, "w") as f: + f.write(source_code) + return build_module([path], + options=options, + skip=skip, + only=only, + module_name=module_name) + + +# +# Building with meson +# + + +class SimplifiedMesonBackend(MesonBackend): + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + + def compile(self): + self.write_meson_build(self.build_dir) + self.run_meson(self.build_dir) + + +def build_meson(source_files, module_name=None, **kwargs): + """ + Build a module via Meson and import it. + """ + + # gh-27045 : Skip if no compilers are found + if not has_fortran_compiler(): + pytest.skip("No Fortran compiler available") + + build_dir = get_module_dir() + if module_name is None: + module_name = get_temp_module_name() + + # Initialize the MesonBackend + backend = SimplifiedMesonBackend( + modulename=module_name, + sources=source_files, + extra_objects=kwargs.get("extra_objects", []), + build_dir=build_dir, + include_dirs=kwargs.get("include_dirs", []), + library_dirs=kwargs.get("library_dirs", []), + libraries=kwargs.get("libraries", []), + define_macros=kwargs.get("define_macros", []), + undef_macros=kwargs.get("undef_macros", []), + f2py_flags=kwargs.get("f2py_flags", []), + sysinfo_flags=kwargs.get("sysinfo_flags", []), + fc_flags=kwargs.get("fc_flags", []), + flib_flags=kwargs.get("flib_flags", []), + setup_flags=kwargs.get("setup_flags", []), + remove_build_dir=kwargs.get("remove_build_dir", False), + extra_dat=kwargs.get("extra_dat", {}), + ) + + backend.compile() + + # Import the compiled module + sys.path.insert(0, f"{build_dir}/{backend.meson_build_dir}") + return import_module(module_name) + + +# +# Unittest convenience +# + + +class F2PyTest: + code = None + sources = None + options = [] + skip = [] + only = [] + suffix = ".f" + module = None + _has_c_compiler = None + _has_f77_compiler = None + _has_f90_compiler = None + + @property + def module_name(self): + cls = type(self) + return f'_{cls.__module__.rsplit(".", 1)[-1]}_{cls.__name__}_ext_module' + + @classmethod + def setup_class(cls): + if sys.platform == "win32": + pytest.skip("Fails with MinGW64 Gfortran (Issue #9673)") + F2PyTest._has_c_compiler = has_c_compiler() + F2PyTest._has_f77_compiler = has_f77_compiler() + F2PyTest._has_f90_compiler = has_f90_compiler() + F2PyTest._has_fortran_compiler = has_fortran_compiler() + + def setup_method(self): + if self.module is not None: + return + + codes = self.sources or [] + if self.code: + codes.append(self.suffix) + + needs_f77 = any(str(fn).endswith(".f") for fn in codes) + needs_f90 = any(str(fn).endswith(".f90") for fn in codes) + needs_pyf = any(str(fn).endswith(".pyf") for fn in codes) + + if needs_f77 and not self._has_f77_compiler: + pytest.skip("No Fortran 77 compiler available") + if needs_f90 and not self._has_f90_compiler: + pytest.skip("No Fortran 90 compiler available") + if needs_pyf and not self._has_fortran_compiler: + pytest.skip("No Fortran compiler available") + + # Build the module + if self.code is not None: + self.module = build_code( + self.code, + options=self.options, + skip=self.skip, + only=self.only, + suffix=self.suffix, + module_name=self.module_name, + ) + + if self.sources is not None: + self.module = build_module( + self.sources, + options=self.options, + skip=self.skip, + only=self.only, + module_name=self.module_name, + ) + + +# +# Helper functions +# + + +def getpath(*a): + # Package root + d = Path(numpy.f2py.__file__).parent.resolve() + return d.joinpath(*a) + + +@contextlib.contextmanager +def switchdir(path): + curpath = Path.cwd() + os.chdir(path) + try: + yield + finally: + os.chdir(curpath) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/linalg/tests/__pycache__/__init__.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/numpy/linalg/tests/__pycache__/__init__.cpython-312.pyc new file 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a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/arithmetic.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/arithmetic.pyi new file mode 100644 index 0000000000000000000000000000000000000000..a68df2ea53c3a8b26082e1fe7591dedbe8fd7aa7 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/arithmetic.pyi @@ -0,0 +1,126 @@ +from typing import Any + +import numpy as np +import numpy.typing as npt + +b_ = np.bool() +dt = np.datetime64(0, "D") +td = np.timedelta64(0, "D") + +AR_b: npt.NDArray[np.bool] +AR_u: npt.NDArray[np.uint32] +AR_i: npt.NDArray[np.int64] +AR_f: npt.NDArray[np.longdouble] +AR_c: npt.NDArray[np.complex128] +AR_m: npt.NDArray[np.timedelta64] +AR_M: npt.NDArray[np.datetime64] + +ANY: Any + +AR_LIKE_b: list[bool] +AR_LIKE_u: list[np.uint32] +AR_LIKE_i: list[int] +AR_LIKE_f: list[float] +AR_LIKE_c: list[complex] +AR_LIKE_m: list[np.timedelta64] +AR_LIKE_M: list[np.datetime64] + +# Array subtraction + +# NOTE: mypys `NoReturn` errors are, unfortunately, not that great +_1 = AR_b - AR_LIKE_b # type: ignore[var-annotated] +_2 = AR_LIKE_b - AR_b # type: ignore[var-annotated] +AR_i - b"" # type: ignore[operator] + +AR_f - AR_LIKE_m # type: ignore[operator] +AR_f - AR_LIKE_M # type: ignore[operator] +AR_c - AR_LIKE_m # type: ignore[operator] +AR_c - AR_LIKE_M # type: ignore[operator] + +AR_m - AR_LIKE_f # type: ignore[operator] +AR_M - AR_LIKE_f # type: ignore[operator] +AR_m - AR_LIKE_c # type: ignore[operator] +AR_M - AR_LIKE_c # type: ignore[operator] + +AR_m - AR_LIKE_M # type: ignore[operator] +AR_LIKE_m - AR_M # type: ignore[operator] + +# array floor division + +AR_M // AR_LIKE_b # type: ignore[operator] +AR_M // AR_LIKE_u # type: ignore[operator] +AR_M // AR_LIKE_i # type: ignore[operator] +AR_M // AR_LIKE_f # type: ignore[operator] +AR_M // AR_LIKE_c # type: ignore[operator] +AR_M // AR_LIKE_m # type: ignore[operator] +AR_M // AR_LIKE_M # type: ignore[operator] + +AR_b // AR_LIKE_M # type: ignore[operator] +AR_u // AR_LIKE_M # type: ignore[operator] +AR_i // AR_LIKE_M # type: ignore[operator] +AR_f // AR_LIKE_M # type: ignore[operator] +AR_c // AR_LIKE_M # type: ignore[operator] +AR_m // AR_LIKE_M # type: ignore[operator] +AR_M // AR_LIKE_M # type: ignore[operator] + +_3 = AR_m // AR_LIKE_b # type: ignore[var-annotated] +AR_m // AR_LIKE_c # type: ignore[operator] + +AR_b // AR_LIKE_m # type: ignore[operator] +AR_u // AR_LIKE_m # type: ignore[operator] +AR_i // AR_LIKE_m # type: ignore[operator] +AR_f // AR_LIKE_m # type: ignore[operator] +AR_c // AR_LIKE_m # type: ignore[operator] + +# regression tests for https://github.com/numpy/numpy/issues/28957 +AR_c // 2 # type: ignore[operator] +AR_c // AR_i # type: ignore[operator] +AR_c // AR_c # type: ignore[operator] + +# Array multiplication + +AR_b *= AR_LIKE_u # type: ignore[arg-type] +AR_b *= AR_LIKE_i # type: ignore[arg-type] +AR_b *= AR_LIKE_f # type: ignore[arg-type] +AR_b *= AR_LIKE_c # type: ignore[arg-type] +AR_b *= AR_LIKE_m # type: ignore[arg-type] + +AR_u *= AR_LIKE_f # type: ignore[arg-type] +AR_u *= AR_LIKE_c # type: ignore[arg-type] +AR_u *= AR_LIKE_m # type: ignore[arg-type] + +AR_i *= AR_LIKE_f # type: ignore[arg-type] +AR_i *= AR_LIKE_c # type: ignore[arg-type] +AR_i *= AR_LIKE_m # type: ignore[arg-type] + +AR_f *= AR_LIKE_c # type: ignore[arg-type] +AR_f *= AR_LIKE_m # type: ignore[arg-type] + +# Array power + +AR_b **= AR_LIKE_b # type: ignore[misc] +AR_b **= AR_LIKE_u # type: ignore[misc] +AR_b **= AR_LIKE_i # type: ignore[misc] +AR_b **= AR_LIKE_f # type: ignore[misc] +AR_b **= AR_LIKE_c # type: ignore[misc] + +AR_u **= AR_LIKE_f # type: ignore[arg-type] +AR_u **= AR_LIKE_c # type: ignore[arg-type] + +AR_i **= AR_LIKE_f # type: ignore[arg-type] +AR_i **= AR_LIKE_c # type: ignore[arg-type] + +AR_f **= AR_LIKE_c # type: ignore[arg-type] + +# Scalars + +b_ - b_ # type: ignore[operator] + +dt + dt # type: ignore[operator] +td - dt # type: ignore[operator] +td % 1 # type: ignore[operator] +td / dt # type: ignore[operator] +td % dt # type: ignore[operator] + +-b_ # type: ignore[operator] ++b_ # type: ignore[operator] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/array_constructors.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/array_constructors.pyi new file mode 100644 index 0000000000000000000000000000000000000000..6ed619958c1c797710e610b3521ca04ba8d04dd1 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/array_constructors.pyi @@ -0,0 +1,34 @@ +import numpy as np +import numpy.typing as npt + +a: npt.NDArray[np.float64] +generator = (i for i in range(10)) + +np.require(a, requirements=1) # type: ignore[call-overload] +np.require(a, requirements="TEST") # type: ignore[arg-type] + +np.zeros("test") # type: ignore[arg-type] +np.zeros() # type: ignore[call-overload] + +np.ones("test") # type: ignore[arg-type] +np.ones() # type: ignore[call-overload] + +np.array(0, float, True) # type: ignore[call-overload] + +np.linspace(None, "bob") # type: ignore[call-overload] +np.linspace(0, 2, num=10.0) # type: ignore[call-overload] +np.linspace(0, 2, endpoint="True") # type: ignore[call-overload] +np.linspace(0, 2, retstep=b"False") # type: ignore[call-overload] +np.linspace(0, 2, dtype=0) # type: ignore[call-overload] +np.linspace(0, 2, axis=None) # type: ignore[call-overload] + +np.logspace(None, "bob") # type: ignore[call-overload] +np.logspace(0, 2, base=None) # type: ignore[call-overload] + +np.geomspace(None, "bob") # type: ignore[call-overload] + +np.stack(generator) # type: ignore[call-overload] +np.hstack({1, 2}) # type: ignore[call-overload] +np.vstack(1) # type: ignore[call-overload] + +np.array([1], like=1) # type: ignore[call-overload] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/array_like.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/array_like.pyi new file mode 100644 index 0000000000000000000000000000000000000000..4e37354e8ebaffbeb281c5f4b13fb4ba96d55527 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/array_like.pyi @@ -0,0 +1,15 @@ +import numpy as np +from numpy._typing import ArrayLike + +class A: ... + +x1: ArrayLike = (i for i in range(10)) # type: ignore[assignment] +x2: ArrayLike = A() # type: ignore[assignment] +x3: ArrayLike = {1: "foo", 2: "bar"} # type: ignore[assignment] + +scalar = np.int64(1) +scalar.__array__(dtype=np.float64) # type: ignore[call-overload] +array = np.array([1]) +array.__array__(dtype=np.float64) # type: ignore[call-overload] + +array.setfield(np.eye(1), np.int32, (0, 1)) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/array_pad.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/array_pad.pyi new file mode 100644 index 0000000000000000000000000000000000000000..42e61c8d70d652836c6d07146cacadf00fd15536 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/array_pad.pyi @@ -0,0 +1,6 @@ +import numpy as np +import numpy.typing as npt + +AR_i8: npt.NDArray[np.int64] + +np.pad(AR_i8, 2, mode="bob") # type: ignore[call-overload] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/arrayprint.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/arrayprint.pyi new file mode 100644 index 0000000000000000000000000000000000000000..3c9dc9330a2bccfa4bae7cc83a7d159cedb1877a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/arrayprint.pyi @@ -0,0 +1,15 @@ +from collections.abc import Callable +from typing import Any + +import numpy as np +import numpy.typing as npt + +AR: npt.NDArray[np.float64] +func1: Callable[[Any], str] +func2: Callable[[np.integer], str] + +np.array2string(AR, legacy="1.14") # type: ignore[arg-type] +np.array2string(AR, sign="*") # type: ignore[arg-type] +np.array2string(AR, floatmode="default") # type: ignore[arg-type] +np.array2string(AR, formatter={"A": func1}) # type: ignore[arg-type] +np.array2string(AR, formatter={"float": func2}) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/arrayterator.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/arrayterator.pyi new file mode 100644 index 0000000000000000000000000000000000000000..8d2295a5859ffe06e84dfdcf66cb8f712f72943c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/arrayterator.pyi @@ -0,0 +1,14 @@ +import numpy as np +import numpy.typing as npt + +AR_i8: npt.NDArray[np.int64] +ar_iter = np.lib.Arrayterator(AR_i8) + +np.lib.Arrayterator(np.int64()) # type: ignore[arg-type] +ar_iter.shape = (10, 5) # type: ignore[misc] +ar_iter[None] # type: ignore[index] +ar_iter[None, 1] # type: ignore[index] +ar_iter[np.intp()] # type: ignore[index] +ar_iter[np.intp(), ...] # type: ignore[index] +ar_iter[AR_i8] # type: ignore[index] +ar_iter[AR_i8, :] # type: ignore[index] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/bitwise_ops.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/bitwise_ops.pyi new file mode 100644 index 0000000000000000000000000000000000000000..f4de2928ff54ec63bcbff72b4c0bcfde9bcfad73 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/bitwise_ops.pyi @@ -0,0 +1,17 @@ +import numpy as np + +i8 = np.int64() +i4 = np.int32() +u8 = np.uint64() +b_ = np.bool() +i = 0 + +f8 = np.float64() + +b_ >> f8 # type: ignore[operator] +i8 << f8 # type: ignore[operator] +i | f8 # type: ignore[operator] +i8 ^ f8 # type: ignore[operator] +u8 & f8 # type: ignore[operator] +~f8 # type: ignore[operator] +# TODO: Certain mixes like i4 << u8 go to float and thus should fail diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/char.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/char.pyi new file mode 100644 index 0000000000000000000000000000000000000000..3dbe5eda296e9dc85ed73d99e440c7da73600f02 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/char.pyi @@ -0,0 +1,63 @@ +import numpy as np +import numpy.typing as npt + +AR_U: npt.NDArray[np.str_] +AR_S: npt.NDArray[np.bytes_] + +np.char.equal(AR_U, AR_S) # type: ignore[arg-type] +np.char.not_equal(AR_U, AR_S) # type: ignore[arg-type] + +np.char.greater_equal(AR_U, AR_S) # type: ignore[arg-type] +np.char.less_equal(AR_U, AR_S) # type: ignore[arg-type] +np.char.greater(AR_U, AR_S) # type: ignore[arg-type] +np.char.less(AR_U, AR_S) # type: ignore[arg-type] + +np.char.encode(AR_S) # type: ignore[arg-type] +np.char.decode(AR_U) # type: ignore[arg-type] + +np.char.join(AR_U, b"_") # type: ignore[arg-type] +np.char.join(AR_S, "_") # type: ignore[arg-type] + +np.char.ljust(AR_U, 5, fillchar=b"a") # type: ignore[arg-type] +np.char.rjust(AR_U, 5, fillchar=b"a") # type: ignore[arg-type] + +np.char.lstrip(AR_U, chars=b"a") # type: ignore[arg-type] +np.char.lstrip(AR_S, chars="a") # type: ignore[arg-type] +np.char.strip(AR_U, chars=b"a") # type: ignore[arg-type] +np.char.strip(AR_S, chars="a") # type: ignore[arg-type] +np.char.rstrip(AR_U, chars=b"a") # type: ignore[arg-type] +np.char.rstrip(AR_S, chars="a") # type: ignore[arg-type] + +np.char.partition(AR_U, b"a") # type: ignore[arg-type] +np.char.partition(AR_S, "a") # type: ignore[arg-type] +np.char.rpartition(AR_U, b"a") # type: ignore[arg-type] +np.char.rpartition(AR_S, "a") # type: ignore[arg-type] + +np.char.replace(AR_U, b"_", b"-") # type: ignore[arg-type] +np.char.replace(AR_S, "_", "-") # type: ignore[arg-type] + +np.char.split(AR_U, b"_") # type: ignore[arg-type] +np.char.split(AR_S, "_") # type: ignore[arg-type] +np.char.rsplit(AR_U, b"_") # type: ignore[arg-type] +np.char.rsplit(AR_S, "_") # type: ignore[arg-type] + +np.char.count(AR_U, b"a", start=[1, 2, 3]) # type: ignore[arg-type] +np.char.count(AR_S, "a", end=9) # type: ignore[arg-type] + +np.char.endswith(AR_U, b"a", start=[1, 2, 3]) # type: ignore[arg-type] +np.char.endswith(AR_S, "a", end=9) # type: ignore[arg-type] +np.char.startswith(AR_U, b"a", start=[1, 2, 3]) # type: ignore[arg-type] +np.char.startswith(AR_S, "a", end=9) # type: ignore[arg-type] + +np.char.find(AR_U, b"a", start=[1, 2, 3]) # type: ignore[arg-type] +np.char.find(AR_S, "a", end=9) # type: ignore[arg-type] +np.char.rfind(AR_U, b"a", start=[1, 2, 3]) # type: ignore[arg-type] +np.char.rfind(AR_S, "a", end=9) # type: ignore[arg-type] + +np.char.index(AR_U, b"a", start=[1, 2, 3]) # type: ignore[arg-type] +np.char.index(AR_S, "a", end=9) # type: ignore[arg-type] +np.char.rindex(AR_U, b"a", start=[1, 2, 3]) # type: ignore[arg-type] +np.char.rindex(AR_S, "a", end=9) # type: ignore[arg-type] + +np.char.isdecimal(AR_S) # type: ignore[arg-type] +np.char.isnumeric(AR_S) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/chararray.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/chararray.pyi new file mode 100644 index 0000000000000000000000000000000000000000..589895510227e5e8a236d685bf02cc4c65a0dcee --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/chararray.pyi @@ -0,0 +1,61 @@ +from typing import Any + +import numpy as np + +AR_U: np.char.chararray[tuple[Any, ...], np.dtype[np.str_]] +AR_S: np.char.chararray[tuple[Any, ...], np.dtype[np.bytes_]] + +AR_S.encode() # type: ignore[misc] +AR_U.decode() # type: ignore[misc] + +AR_U.join(b"_") # type: ignore[arg-type] +AR_S.join("_") # type: ignore[arg-type] + +AR_U.ljust(5, fillchar=b"a") # type: ignore[arg-type] +AR_U.rjust(5, fillchar=b"a") # type: ignore[arg-type] + +AR_U.lstrip(chars=b"a") # type: ignore[arg-type] +AR_S.lstrip(chars="a") # type: ignore[arg-type] +AR_U.strip(chars=b"a") # type: ignore[arg-type] +AR_S.strip(chars="a") # type: ignore[arg-type] +AR_U.rstrip(chars=b"a") # type: ignore[arg-type] +AR_S.rstrip(chars="a") # type: ignore[arg-type] + +AR_U.partition(b"a") # type: ignore[arg-type] +AR_S.partition("a") # type: ignore[arg-type] +AR_U.rpartition(b"a") # type: ignore[arg-type] +AR_S.rpartition("a") # type: ignore[arg-type] + +AR_U.replace(b"_", b"-") # type: ignore[arg-type] +AR_S.replace("_", "-") # type: ignore[arg-type] + +AR_U.split(b"_") # type: ignore[arg-type] +AR_S.split("_") # type: ignore[arg-type] +AR_S.split(1) # type: ignore[arg-type] +AR_U.rsplit(b"_") # type: ignore[arg-type] +AR_S.rsplit("_") # type: ignore[arg-type] + +AR_U.count(b"a", start=[1, 2, 3]) # type: ignore[arg-type] +AR_S.count("a", end=9) # type: ignore[arg-type] + +AR_U.endswith(b"a", start=[1, 2, 3]) # type: ignore[arg-type] +AR_S.endswith("a", end=9) # type: ignore[arg-type] +AR_U.startswith(b"a", start=[1, 2, 3]) # type: ignore[arg-type] +AR_S.startswith("a", end=9) # type: ignore[arg-type] + +AR_U.find(b"a", start=[1, 2, 3]) # type: ignore[arg-type] +AR_S.find("a", end=9) # type: ignore[arg-type] +AR_U.rfind(b"a", start=[1, 2, 3]) # type: ignore[arg-type] +AR_S.rfind("a", end=9) # type: ignore[arg-type] + +AR_U.index(b"a", start=[1, 2, 3]) # type: ignore[arg-type] +AR_S.index("a", end=9) # type: ignore[arg-type] +AR_U.rindex(b"a", start=[1, 2, 3]) # type: ignore[arg-type] +AR_S.rindex("a", end=9) # type: ignore[arg-type] + +AR_U == AR_S # type: ignore[operator] +AR_U != AR_S # type: ignore[operator] +AR_U >= AR_S # type: ignore[operator] +AR_U <= AR_S # type: ignore[operator] +AR_U > AR_S # type: ignore[operator] +AR_U < AR_S # type: ignore[operator] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/comparisons.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/comparisons.pyi new file mode 100644 index 0000000000000000000000000000000000000000..d2965b5c1a918fc4f0170f38ff22fd6779d9e3db --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/comparisons.pyi @@ -0,0 +1,27 @@ +import numpy as np +import numpy.typing as npt + +AR_i: npt.NDArray[np.int64] +AR_f: npt.NDArray[np.float64] +AR_c: npt.NDArray[np.complex128] +AR_m: npt.NDArray[np.timedelta64] +AR_M: npt.NDArray[np.datetime64] + +AR_f > AR_m # type: ignore[operator] +AR_c > AR_m # type: ignore[operator] + +AR_m > AR_f # type: ignore[operator] +AR_m > AR_c # type: ignore[operator] + +AR_i > AR_M # type: ignore[operator] +AR_f > AR_M # type: ignore[operator] +AR_m > AR_M # type: ignore[operator] + +AR_M > AR_i # type: ignore[operator] +AR_M > AR_f # type: ignore[operator] +AR_M > AR_m # type: ignore[operator] + +AR_i > "" # type: ignore[operator] +AR_i > b"" # type: ignore[operator] +"" > AR_M # type: ignore[operator] +b"" > AR_M # type: ignore[operator] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/constants.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/constants.pyi new file mode 100644 index 0000000000000000000000000000000000000000..10717f664e0a679fdd30e232001948dac6da063d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/constants.pyi @@ -0,0 +1,3 @@ +import numpy as np + +np.little_endian = np.little_endian # type: ignore[misc] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/datasource.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/datasource.pyi new file mode 100644 index 0000000000000000000000000000000000000000..4c603cf693a15b801dd564bbcdf9ce1b1b1a2c73 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/datasource.pyi @@ -0,0 +1,16 @@ +from pathlib import Path + +import numpy as np + +path: Path +d1: np.lib.npyio.DataSource + +d1.abspath(path) # type: ignore[arg-type] +d1.abspath(b"...") # type: ignore[arg-type] + +d1.exists(path) # type: ignore[arg-type] +d1.exists(b"...") # type: ignore[arg-type] + +d1.open(path, "r") # type: ignore[arg-type] +d1.open(b"...", encoding="utf8") # type: ignore[arg-type] +d1.open(None, newline="/n") # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/dtype.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/dtype.pyi new file mode 100644 index 0000000000000000000000000000000000000000..64a7c3f775e1a14080aafda8ba3ff293232e9c47 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/dtype.pyi @@ -0,0 +1,17 @@ +import numpy as np + +class Test1: + not_dtype = np.dtype(float) + +class Test2: + dtype = float + +np.dtype(Test1()) # type: ignore[call-overload] +np.dtype(Test2()) # type: ignore[arg-type] + +np.dtype( # type: ignore[call-overload] + { + "field1": (float, 1), + "field2": (int, 3), + } +) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/einsumfunc.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/einsumfunc.pyi new file mode 100644 index 0000000000000000000000000000000000000000..982ad986297f6695126c5831ff9d6b66e1b60da8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/einsumfunc.pyi @@ -0,0 +1,12 @@ +import numpy as np +import numpy.typing as npt + +AR_i: npt.NDArray[np.int64] +AR_f: npt.NDArray[np.float64] +AR_m: npt.NDArray[np.timedelta64] +AR_U: npt.NDArray[np.str_] + +np.einsum("i,i->i", AR_i, AR_m) # type: ignore[arg-type] +np.einsum("i,i->i", AR_f, AR_f, dtype=np.int32) # type: ignore[arg-type] +np.einsum("i,i->i", AR_i, AR_i, out=AR_U) # type: ignore[type-var] +np.einsum("i,i->i", AR_i, AR_i, out=AR_U, casting="unsafe") # type: ignore[call-overload] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/flatiter.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/flatiter.pyi new file mode 100644 index 0000000000000000000000000000000000000000..2c6e912bd3185b30956af18f6ce329638165ff8c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/flatiter.pyi @@ -0,0 +1,38 @@ +from typing import Any + +import numpy as np +import numpy.typing as npt + +class _Index: + def __index__(self) -> int: ... + +class _MyArray: + def __array__(self) -> np.ndarray[tuple[int], np.dtypes.Float64DType]: ... + +_index: _Index +_my_array: _MyArray +_something: Any +_dtype: np.dtype[np.int8] + +_a_nd: np.flatiter[npt.NDArray[np.float64]] + +### + +_a_nd.base = _something # type: ignore[misc] +_a_nd.coords = _something # type: ignore[misc] +_a_nd.index = _something # type: ignore[misc] + +_a_nd.copy("C") # type: ignore[call-arg] +_a_nd.copy(order="C") # type: ignore[call-arg] + +# NOTE: Contrary to `ndarray.__getitem__` its counterpart in `flatiter` +# does not accept objects with the `__array__` or `__index__` protocols; +# boolean indexing is just plain broken (gh-17175) +_a_nd[np.True_] # type: ignore[call-overload] +_a_nd[_index] # type: ignore[call-overload] +_a_nd[_my_array] # type: ignore[call-overload] + +# `dtype` and `copy` are no-ops in `flatiter.__array__` +_a_nd.__array__(_dtype) # type: ignore[arg-type] +_a_nd.__array__(dtype=_dtype) # type: ignore[call-arg] +_a_nd.__array__(copy=True) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/fromnumeric.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/fromnumeric.pyi new file mode 100644 index 0000000000000000000000000000000000000000..92b0cb3662073011885434b8fa7279528c1cf708 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/fromnumeric.pyi @@ -0,0 +1,148 @@ +"""Tests for :mod:`numpy._core.fromnumeric`.""" + +import numpy as np +import numpy.typing as npt + +A = np.array(True, ndmin=2, dtype=bool) +A.setflags(write=False) +AR_U: npt.NDArray[np.str_] +AR_M: npt.NDArray[np.datetime64] +AR_f4: npt.NDArray[np.float32] + +a = np.bool(True) + +np.take(a, None) # type: ignore[call-overload] +np.take(a, axis=1.0) # type: ignore[call-overload] +np.take(A, out=1) # type: ignore[call-overload] +np.take(A, mode="bob") # type: ignore[call-overload] + +np.reshape(a, None) # type: ignore[call-overload] +np.reshape(A, 1, order="bob") # type: ignore[call-overload] + +np.choose(a, None) # type: ignore[call-overload] +np.choose(a, out=1.0) # type: ignore[call-overload] +np.choose(A, mode="bob") # type: ignore[call-overload] + +np.repeat(a, None) # type: ignore[call-overload] +np.repeat(A, 1, axis=1.0) # type: ignore[call-overload] + +np.swapaxes(A, None, 1) # type: ignore[call-overload] +np.swapaxes(A, 1, [0]) # type: ignore[call-overload] + +np.transpose(A, axes=1.0) # type: ignore[call-overload] + +np.partition(a, None) # type: ignore[call-overload] +np.partition(a, 0, axis="bob") # type: ignore[call-overload] +np.partition(A, 0, kind="bob") # type: ignore[call-overload] +np.partition(A, 0, order=range(5)) # type: ignore[arg-type] + +np.argpartition(a, None) # type: ignore[arg-type] +np.argpartition(a, 0, axis="bob") # type: ignore[arg-type] +np.argpartition(A, 0, kind="bob") # type: ignore[arg-type] +np.argpartition(A, 0, order=range(5)) # type: ignore[arg-type] + +np.sort(A, axis="bob") # type: ignore[call-overload] +np.sort(A, kind="bob") # type: ignore[call-overload] +np.sort(A, order=range(5)) # type: ignore[arg-type] + +np.argsort(A, axis="bob") # type: ignore[arg-type] +np.argsort(A, kind="bob") # type: ignore[arg-type] +np.argsort(A, order=range(5)) # type: ignore[arg-type] + +np.argmax(A, axis="bob") # type: ignore[call-overload] +np.argmax(A, kind="bob") # type: ignore[call-overload] +np.argmax(A, out=AR_f4) # type: ignore[type-var] + +np.argmin(A, axis="bob") # type: ignore[call-overload] +np.argmin(A, kind="bob") # type: ignore[call-overload] +np.argmin(A, out=AR_f4) # type: ignore[type-var] + +np.searchsorted(A[0], 0, side="bob") # type: ignore[call-overload] +np.searchsorted(A[0], 0, sorter=1.0) # type: ignore[call-overload] + +np.resize(A, 1.0) # type: ignore[call-overload] + +np.squeeze(A, 1.0) # type: ignore[call-overload] + +np.diagonal(A, offset=None) # type: ignore[call-overload] +np.diagonal(A, axis1="bob") # type: ignore[call-overload] +np.diagonal(A, axis2=[]) # type: ignore[call-overload] + +np.trace(A, offset=None) # type: ignore[call-overload] +np.trace(A, axis1="bob") # type: ignore[call-overload] +np.trace(A, axis2=[]) # type: ignore[call-overload] + +np.ravel(a, order="bob") # type: ignore[call-overload] + +np.nonzero(0) # type: ignore[arg-type] + +np.compress([True], A, axis=1.0) # type: ignore[call-overload] + +np.clip(a, 1, 2, out=1) # type: ignore[call-overload] + +np.sum(a, axis=1.0) # type: ignore[call-overload] +np.sum(a, keepdims=1.0) # type: ignore[call-overload] +np.sum(a, initial=[1]) # type: ignore[call-overload] + +np.all(a, axis=1.0) # type: ignore[call-overload] +np.all(a, keepdims=1.0) # type: ignore[call-overload] +np.all(a, out=1.0) # type: ignore[call-overload] + +np.any(a, axis=1.0) # type: ignore[call-overload] +np.any(a, keepdims=1.0) # type: ignore[call-overload] +np.any(a, out=1.0) # type: ignore[call-overload] + +np.cumsum(a, axis=1.0) # type: ignore[call-overload] +np.cumsum(a, dtype=1.0) # type: ignore[call-overload] +np.cumsum(a, out=1.0) # type: ignore[call-overload] + +np.ptp(a, axis=1.0) # type: ignore[call-overload] +np.ptp(a, keepdims=1.0) # type: ignore[call-overload] +np.ptp(a, out=1.0) # type: ignore[call-overload] + +np.amax(a, axis=1.0) # type: ignore[call-overload] +np.amax(a, keepdims=1.0) # type: ignore[call-overload] +np.amax(a, out=1.0) # type: ignore[call-overload] +np.amax(a, initial=[1.0]) # type: ignore[call-overload] +np.amax(a, where=[1.0]) # type: ignore[arg-type] + +np.amin(a, axis=1.0) # type: ignore[call-overload] +np.amin(a, keepdims=1.0) # type: ignore[call-overload] +np.amin(a, out=1.0) # type: ignore[call-overload] +np.amin(a, initial=[1.0]) # type: ignore[call-overload] +np.amin(a, where=[1.0]) # type: ignore[arg-type] + +np.prod(a, axis=1.0) # type: ignore[call-overload] +np.prod(a, out=False) # type: ignore[call-overload] +np.prod(a, keepdims=1.0) # type: ignore[call-overload] +np.prod(a, initial=int) # type: ignore[call-overload] +np.prod(a, where=1.0) # type: ignore[call-overload] +np.prod(AR_U) # type: ignore[arg-type] + +np.cumprod(a, axis=1.0) # type: ignore[call-overload] +np.cumprod(a, out=False) # type: ignore[call-overload] +np.cumprod(AR_U) # type: ignore[arg-type] + +np.size(a, axis=1.0) # type: ignore[arg-type] + +np.around(a, decimals=1.0) # type: ignore[call-overload] +np.around(a, out=type) # type: ignore[call-overload] +np.around(AR_U) # type: ignore[arg-type] + +np.mean(a, axis=1.0) # type: ignore[call-overload] +np.mean(a, out=False) # type: ignore[call-overload] +np.mean(a, keepdims=1.0) # type: ignore[call-overload] +np.mean(AR_U) # type: ignore[arg-type] +np.mean(AR_M) # type: ignore[arg-type] + +np.std(a, axis=1.0) # type: ignore[call-overload] +np.std(a, out=False) # type: ignore[call-overload] +np.std(a, ddof="test") # type: ignore[call-overload] +np.std(a, keepdims=1.0) # type: ignore[call-overload] +np.std(AR_U) # type: ignore[arg-type] + +np.var(a, axis=1.0) # type: ignore[call-overload] +np.var(a, out=False) # type: ignore[call-overload] +np.var(a, ddof="test") # type: ignore[call-overload] +np.var(a, keepdims=1.0) # type: ignore[call-overload] +np.var(AR_U) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/histograms.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/histograms.pyi new file mode 100644 index 0000000000000000000000000000000000000000..5f7892719eb4bf0c225e6ff6ddaf52c42de9c9c9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/histograms.pyi @@ -0,0 +1,12 @@ +import numpy as np +import numpy.typing as npt + +AR_i8: npt.NDArray[np.int64] +AR_f8: npt.NDArray[np.float64] + +np.histogram_bin_edges(AR_i8, range=(0, 1, 2)) # type: ignore[arg-type] + +np.histogram(AR_i8, range=(0, 1, 2)) # type: ignore[arg-type] + +np.histogramdd(AR_i8, range=(0, 1)) # type: ignore[arg-type] +np.histogramdd(AR_i8, range=[(0, 1, 2)]) # type: ignore[list-item] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/index_tricks.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/index_tricks.pyi new file mode 100644 index 0000000000000000000000000000000000000000..8b7b1ae2b5bfc0705bbbfbdd244c06b90d0fdd4d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/index_tricks.pyi @@ -0,0 +1,14 @@ +import numpy as np + +AR_LIKE_i: list[int] +AR_LIKE_f: list[float] + +np.ndindex([1, 2, 3]) # type: ignore[call-overload] +np.unravel_index(AR_LIKE_f, (1, 2, 3)) # type: ignore[arg-type] +np.ravel_multi_index(AR_LIKE_i, (1, 2, 3), mode="bob") # type: ignore[call-overload] +np.mgrid[1] # type: ignore[index] +np.mgrid[...] # type: ignore[index] +np.ogrid[1] # type: ignore[index] +np.ogrid[...] # type: ignore[index] +np.fill_diagonal(AR_LIKE_f, 2) # type: ignore[arg-type] +np.diag_indices(1.0) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/lib_function_base.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/lib_function_base.pyi new file mode 100644 index 0000000000000000000000000000000000000000..d7be993bf04c96555ef8dae357aacca337c3d478 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/lib_function_base.pyi @@ -0,0 +1,60 @@ +from typing import Any + +import numpy as np +import numpy.typing as npt + +AR_f8: npt.NDArray[np.float64] +AR_c16: npt.NDArray[np.complex128] +AR_m: npt.NDArray[np.timedelta64] +AR_M: npt.NDArray[np.datetime64] +AR_O: npt.NDArray[np.object_] +AR_b_list: list[npt.NDArray[np.bool]] + +def fn_none_i(a: None, /) -> npt.NDArray[Any]: ... +def fn_ar_i(a: npt.NDArray[np.float64], posarg: int, /) -> npt.NDArray[Any]: ... + +np.average(AR_m) # type: ignore[type-var] +np.select(1, [AR_f8]) # type: ignore[call-overload] +np.angle(AR_m) # type: ignore[type-var] +np.unwrap(AR_m) # type: ignore[type-var] +np.unwrap(AR_c16) # type: ignore[type-var] +np.trim_zeros(1) # type: ignore[arg-type] +np.place(1, [True], 1.5) # type: ignore[arg-type] +np.vectorize(1) # type: ignore[arg-type] +np.place(AR_f8, slice(None), 5) # type: ignore[arg-type] + +np.piecewise(AR_f8, True, [fn_ar_i], "wrong") # type: ignore[call-overload] +np.piecewise(AR_f8, AR_b_list, [fn_none_i]) # type: ignore[call-overload] +np.piecewise(AR_f8, AR_b_list, [fn_ar_i]) # type: ignore[call-overload] +np.piecewise(AR_f8, AR_b_list, [fn_ar_i], 3.14) # type: ignore[call-overload] +np.piecewise(AR_f8, AR_b_list, [fn_ar_i], 42, None) # type: ignore[call-overload] +np.piecewise(AR_f8, AR_b_list, [fn_ar_i], 42, _=None) # type: ignore[list-item] + +np.interp(AR_f8, AR_c16, AR_f8) # type: ignore[arg-type] +np.interp(AR_c16, AR_f8, AR_f8) # type: ignore[arg-type] +np.interp(AR_f8, AR_f8, AR_f8, period=AR_c16) # type: ignore[call-overload] +np.interp(AR_f8, AR_f8, AR_O) # type: ignore[arg-type] + +np.cov(AR_m) # type: ignore[type-var] +np.cov(AR_O) # type: ignore[type-var] +np.corrcoef(AR_m) # type: ignore[type-var] +np.corrcoef(AR_O) # type: ignore[type-var] +np.corrcoef(AR_f8, bias=True) # type: ignore[call-overload] +np.corrcoef(AR_f8, ddof=2) # type: ignore[call-overload] +np.blackman(1j) # type: ignore[arg-type] +np.bartlett(1j) # type: ignore[arg-type] +np.hanning(1j) # type: ignore[arg-type] +np.hamming(1j) # type: ignore[arg-type] +np.hamming(AR_c16) # type: ignore[arg-type] +np.kaiser(1j, 1) # type: ignore[arg-type] +np.sinc(AR_O) # type: ignore[type-var] +np.median(AR_M) # type: ignore[type-var] + +np.percentile(AR_f8, 50j) # type: ignore[call-overload] +np.percentile(AR_f8, 50, interpolation="bob") # type: ignore[call-overload] +np.quantile(AR_f8, 0.5j) # type: ignore[call-overload] +np.quantile(AR_f8, 0.5, interpolation="bob") # type: ignore[call-overload] +np.meshgrid(AR_f8, AR_f8, indexing="bob") # type: ignore[call-overload] +np.delete(AR_f8, AR_f8) # type: ignore[arg-type] +np.insert(AR_f8, AR_f8, 1.5) # type: ignore[arg-type] +np.digitize(AR_f8, 1j) # type: ignore[call-overload] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/lib_polynomial.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/lib_polynomial.pyi new file mode 100644 index 0000000000000000000000000000000000000000..727eb7f4b2b121f4b51c61e8df467d2ba7bb6d85 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/lib_polynomial.pyi @@ -0,0 +1,29 @@ +import numpy as np +import numpy.typing as npt + +AR_f8: npt.NDArray[np.float64] +AR_c16: npt.NDArray[np.complex128] +AR_O: npt.NDArray[np.object_] +AR_U: npt.NDArray[np.str_] + +poly_obj: np.poly1d + +np.polymul(AR_f8, AR_U) # type: ignore[arg-type] +np.polydiv(AR_f8, AR_U) # type: ignore[arg-type] + +5**poly_obj # type: ignore[operator] + +np.polyint(AR_U) # type: ignore[arg-type] +np.polyint(AR_f8, m=1j) # type: ignore[call-overload] + +np.polyder(AR_U) # type: ignore[arg-type] +np.polyder(AR_f8, m=1j) # type: ignore[call-overload] + +np.polyfit(AR_O, AR_f8, 1) # type: ignore[arg-type] +np.polyfit(AR_f8, AR_f8, 1, rcond=1j) # type: ignore[call-overload] +np.polyfit(AR_f8, AR_f8, 1, w=AR_c16) # type: ignore[arg-type] +np.polyfit(AR_f8, AR_f8, 1, cov="bob") # type: ignore[call-overload] + +np.polyval(AR_f8, AR_U) # type: ignore[arg-type] +np.polyadd(AR_f8, AR_U) # type: ignore[arg-type] +np.polysub(AR_f8, AR_U) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/lib_utils.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/lib_utils.pyi new file mode 100644 index 0000000000000000000000000000000000000000..25af32b432977e311d8612c74725340d926cf590 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/lib_utils.pyi @@ -0,0 +1,3 @@ +import numpy.lib.array_utils as array_utils + +array_utils.byte_bounds(1) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/lib_version.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/lib_version.pyi new file mode 100644 index 0000000000000000000000000000000000000000..62011a848cc15a1c2f1454a80aba21d814855a8c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/lib_version.pyi @@ -0,0 +1,6 @@ +from numpy.lib import NumpyVersion + +version: NumpyVersion + +NumpyVersion(b"1.8.0") # type: ignore[arg-type] +version >= b"1.8.0" # type: ignore[operator] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/linalg.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/linalg.pyi new file mode 100644 index 0000000000000000000000000000000000000000..78aceb235f8da5a57f6b4c52fc7b3e5e510404bc --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/linalg.pyi @@ -0,0 +1,52 @@ +import numpy as np +import numpy.typing as npt + +AR_f8: npt.NDArray[np.float64] +AR_O: npt.NDArray[np.object_] +AR_M: npt.NDArray[np.datetime64] + +np.linalg.tensorsolve(AR_O, AR_O) # type: ignore[arg-type] + +np.linalg.solve(AR_O, AR_O) # type: ignore[arg-type] + +np.linalg.tensorinv(AR_O) # type: ignore[arg-type] + +np.linalg.inv(AR_O) # type: ignore[arg-type] + +np.linalg.matrix_power(AR_M, 5) # type: ignore[arg-type] + +np.linalg.cholesky(AR_O) # type: ignore[arg-type] + +np.linalg.qr(AR_O) # type: ignore[arg-type] +np.linalg.qr(AR_f8, mode="bob") # type: ignore[call-overload] + +np.linalg.eigvals(AR_O) # type: ignore[arg-type] + +np.linalg.eigvalsh(AR_O) # type: ignore[arg-type] +np.linalg.eigvalsh(AR_O, UPLO="bob") # type: ignore[call-overload] + +np.linalg.eig(AR_O) # type: ignore[arg-type] + +np.linalg.eigh(AR_O) # type: ignore[arg-type] +np.linalg.eigh(AR_O, UPLO="bob") # type: ignore[call-overload] + +np.linalg.svd(AR_O) # type: ignore[arg-type] + +np.linalg.svdvals(AR_O) # type: ignore[arg-type] +np.linalg.svdvals(AR_M) # type: ignore[arg-type] +np.linalg.svdvals(x=AR_f8) # type: ignore[call-overload] + +np.linalg.cond(AR_O) # type: ignore[arg-type] +np.linalg.cond(AR_f8, p="bob") # type: ignore[arg-type] + +np.linalg.matrix_rank(AR_O) # type: ignore[arg-type] + +np.linalg.pinv(AR_O) # type: ignore[arg-type] + +np.linalg.slogdet(AR_O) # type: ignore[arg-type] + +np.linalg.det(AR_O) # type: ignore[arg-type] + +np.linalg.norm(AR_f8, ord="bob") # type: ignore[call-overload] + +np.linalg.multi_dot([AR_M]) # type: ignore[list-item] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ma.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ma.pyi new file mode 100644 index 0000000000000000000000000000000000000000..084ae971bdd059ce6c5f03d5eeb561f6ec5c3e84 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ma.pyi @@ -0,0 +1,155 @@ +from typing import TypeAlias, TypeVar + +import numpy as np +import numpy.typing as npt +from numpy._typing import _AnyShape + +_ScalarT = TypeVar("_ScalarT", bound=np.generic) +MaskedArray: TypeAlias = np.ma.MaskedArray[_AnyShape, np.dtype[_ScalarT]] + +MAR_1d_f8: np.ma.MaskedArray[tuple[int], np.dtype[np.float64]] +MAR_b: MaskedArray[np.bool] +MAR_c: MaskedArray[np.complex128] +MAR_td64: MaskedArray[np.timedelta64] + +AR_b: npt.NDArray[np.bool] + +MAR_1d_f8.shape = (3, 1) # type: ignore[assignment] +MAR_1d_f8.dtype = np.bool # type: ignore[assignment] + +def invalid_recordmask_setter() -> None: + # We make an inner function for this one to avoid the + # `NoReturn` causing an early exit for type checkers. + MAR_1d_f8.recordmask = [True] # type: ignore[assignment] + +np.ma.min(MAR_1d_f8, axis=1.0) # type: ignore[call-overload] +np.ma.min(MAR_1d_f8, keepdims=1.0) # type: ignore[call-overload] +np.ma.min(MAR_1d_f8, out=1.0) # type: ignore[call-overload] +np.ma.min(MAR_1d_f8, fill_value=lambda x: 27) # type: ignore[call-overload] + +MAR_1d_f8.min(axis=1.0) # type: ignore[call-overload] +MAR_1d_f8.min(keepdims=1.0) # type: ignore[call-overload] +MAR_1d_f8.min(out=1.0) # type: ignore[call-overload] +MAR_1d_f8.min(fill_value=lambda x: 27) # type: ignore[call-overload] + +np.ma.max(MAR_1d_f8, axis=1.0) # type: ignore[call-overload] +np.ma.max(MAR_1d_f8, keepdims=1.0) # type: ignore[call-overload] +np.ma.max(MAR_1d_f8, out=1.0) # type: ignore[call-overload] +np.ma.max(MAR_1d_f8, fill_value=lambda x: 27) # type: ignore[call-overload] + +MAR_1d_f8.max(axis=1.0) # type: ignore[call-overload] +MAR_1d_f8.max(keepdims=1.0) # type: ignore[call-overload] +MAR_1d_f8.max(out=1.0) # type: ignore[call-overload] +MAR_1d_f8.max(fill_value=lambda x: 27) # type: ignore[call-overload] + +np.ma.ptp(MAR_1d_f8, axis=1.0) # type: ignore[call-overload] +np.ma.ptp(MAR_1d_f8, keepdims=1.0) # type: ignore[call-overload] +np.ma.ptp(MAR_1d_f8, out=1.0) # type: ignore[call-overload] +np.ma.ptp(MAR_1d_f8, fill_value=lambda x: 27) # type: ignore[call-overload] + +MAR_1d_f8.ptp(axis=1.0) # type: ignore[call-overload] +MAR_1d_f8.ptp(keepdims=1.0) # type: ignore[call-overload] +MAR_1d_f8.ptp(out=1.0) # type: ignore[call-overload] +MAR_1d_f8.ptp(fill_value=lambda x: 27) # type: ignore[call-overload] + +MAR_1d_f8.argmin(axis=1.0) # type: ignore[call-overload] +MAR_1d_f8.argmin(keepdims=1.0) # type: ignore[call-overload] +MAR_1d_f8.argmin(out=1.0) # type: ignore[call-overload] +MAR_1d_f8.argmin(fill_value=lambda x: 27) # type: ignore[call-overload] + +np.ma.argmin(MAR_1d_f8, axis=1.0) # type: ignore[call-overload] +np.ma.argmin(MAR_1d_f8, axis=(1,)) # type: ignore[call-overload] +np.ma.argmin(MAR_1d_f8, keepdims=1.0) # type: ignore[call-overload] +np.ma.argmin(MAR_1d_f8, out=1.0) # type: ignore[call-overload] +np.ma.argmin(MAR_1d_f8, fill_value=lambda x: 27) # type: ignore[call-overload] + +MAR_1d_f8.argmax(axis=1.0) # type: ignore[call-overload] +MAR_1d_f8.argmax(keepdims=1.0) # type: ignore[call-overload] +MAR_1d_f8.argmax(out=1.0) # type: ignore[call-overload] +MAR_1d_f8.argmax(fill_value=lambda x: 27) # type: ignore[call-overload] + +np.ma.argmax(MAR_1d_f8, axis=1.0) # type: ignore[call-overload] +np.ma.argmax(MAR_1d_f8, axis=(0,)) # type: ignore[call-overload] +np.ma.argmax(MAR_1d_f8, keepdims=1.0) # type: ignore[call-overload] +np.ma.argmax(MAR_1d_f8, out=1.0) # type: ignore[call-overload] +np.ma.argmax(MAR_1d_f8, fill_value=lambda x: 27) # type: ignore[call-overload] + +MAR_1d_f8.all(axis=1.0) # type: ignore[call-overload] +MAR_1d_f8.all(keepdims=1.0) # type: ignore[call-overload] +MAR_1d_f8.all(out=1.0) # type: ignore[call-overload] + +MAR_1d_f8.any(axis=1.0) # type: ignore[call-overload] +MAR_1d_f8.any(keepdims=1.0) # type: ignore[call-overload] +MAR_1d_f8.any(out=1.0) # type: ignore[call-overload] + +MAR_1d_f8.sort(axis=(0, 1)) # type: ignore[arg-type] +MAR_1d_f8.sort(axis=None) # type: ignore[arg-type] +MAR_1d_f8.sort(kind="cabbage") # type: ignore[arg-type] +MAR_1d_f8.sort(order=lambda: "cabbage") # type: ignore[arg-type] +MAR_1d_f8.sort(endwith="cabbage") # type: ignore[arg-type] +MAR_1d_f8.sort(fill_value=lambda: "cabbage") # type: ignore[arg-type] +MAR_1d_f8.sort(stable="cabbage") # type: ignore[arg-type] +MAR_1d_f8.sort(stable=True) # type: ignore[arg-type] + +MAR_1d_f8.take(axis=1.0) # type: ignore[call-overload] +MAR_1d_f8.take(out=1) # type: ignore[call-overload] +MAR_1d_f8.take(mode="bob") # type: ignore[call-overload] + +np.ma.take(None) # type: ignore[call-overload] +np.ma.take(axis=1.0) # type: ignore[call-overload] +np.ma.take(out=1) # type: ignore[call-overload] +np.ma.take(mode="bob") # type: ignore[call-overload] + +MAR_1d_f8.partition(["cabbage"]) # type: ignore[arg-type] +MAR_1d_f8.partition(axis=(0, 1)) # type: ignore[arg-type, call-arg] +MAR_1d_f8.partition(kind="cabbage") # type: ignore[arg-type, call-arg] +MAR_1d_f8.partition(order=lambda: "cabbage") # type: ignore[arg-type, call-arg] +MAR_1d_f8.partition(AR_b) # type: ignore[arg-type] + +MAR_1d_f8.argpartition(["cabbage"]) # type: ignore[arg-type] +MAR_1d_f8.argpartition(axis=(0, 1)) # type: ignore[arg-type, call-arg] +MAR_1d_f8.argpartition(kind="cabbage") # type: ignore[arg-type, call-arg] +MAR_1d_f8.argpartition(order=lambda: "cabbage") # type: ignore[arg-type, call-arg] +MAR_1d_f8.argpartition(AR_b) # type: ignore[arg-type] + +np.ma.ndim(lambda: "lambda") # type: ignore[arg-type] + +np.ma.size(AR_b, axis="0") # type: ignore[arg-type] + +MAR_1d_f8 >= (lambda x: "mango") # type: ignore[operator] +MAR_1d_f8 > (lambda x: "mango") # type: ignore[operator] +MAR_1d_f8 <= (lambda x: "mango") # type: ignore[operator] +MAR_1d_f8 < (lambda x: "mango") # type: ignore[operator] + +MAR_1d_f8.count(axis=0.) # type: ignore[call-overload] + +np.ma.count(MAR_1d_f8, axis=0.) # type: ignore[call-overload] + +MAR_1d_f8.put(4, 999, mode="flip") # type: ignore[arg-type] + +np.ma.put(MAR_1d_f8, 4, 999, mode="flip") # type: ignore[arg-type] + +np.ma.put([1, 1, 3], 0, 999) # type: ignore[arg-type] + +np.ma.compressed(lambda: "compress me") # type: ignore[call-overload] + +np.ma.allequal(MAR_1d_f8, [1, 2, 3], fill_value=1.5) # type: ignore[arg-type] + +np.ma.allclose(MAR_1d_f8, [1, 2, 3], masked_equal=4.5) # type: ignore[arg-type] +np.ma.allclose(MAR_1d_f8, [1, 2, 3], rtol=".4") # type: ignore[arg-type] +np.ma.allclose(MAR_1d_f8, [1, 2, 3], atol=".5") # type: ignore[arg-type] + +MAR_1d_f8.__setmask__("mask") # type: ignore[arg-type] + +MAR_b *= 2 # type: ignore[arg-type] +MAR_c //= 2 # type: ignore[misc] +MAR_td64 **= 2 # type: ignore[misc] + +MAR_1d_f8.swapaxes(axis1=1, axis2=0) # type: ignore[call-arg] + +MAR_1d_f8.argsort(axis=(1, 0)) # type: ignore[arg-type] + +np.ma.MaskedArray(np.array([1, 2, 3]), keep_mask="yes") # type: ignore[call-overload] +np.ma.MaskedArray(np.array([1, 2, 3]), subok=None) # type: ignore[call-overload] +np.ma.MaskedArray(np.array([1, 2, 3]), ndim=None) # type: ignore[call-overload] +np.ma.MaskedArray(np.array([1, 2, 3]), order="Corinthian") # type: ignore[call-overload] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/memmap.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/memmap.pyi new file mode 100644 index 0000000000000000000000000000000000000000..3a4fc7df068961736ee8cf05412d5bcea5ad547a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/memmap.pyi @@ -0,0 +1,5 @@ +import numpy as np + +with open("file.txt", "r") as f: + np.memmap(f) # type: ignore[call-overload] +np.memmap("test.txt", shape=[10, 5]) # type: ignore[call-overload] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/modules.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/modules.pyi new file mode 100644 index 0000000000000000000000000000000000000000..c12a182807d395fd9d8c94882b826c23de703932 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/modules.pyi @@ -0,0 +1,17 @@ +import numpy as np + +np.testing.bob # type: ignore[attr-defined] +np.bob # type: ignore[attr-defined] + +# Stdlib modules in the namespace by accident +np.warnings # type: ignore[attr-defined] +np.sys # type: ignore[attr-defined] +np.os # type: ignore[attr-defined] +np.math # type: ignore[attr-defined] + +# Public sub-modules that are not imported to their parent module by default; +# e.g. one must first execute `import numpy.lib.recfunctions` +np.lib.recfunctions # type: ignore[attr-defined] + +np.__deprecated_attrs__ # type: ignore[attr-defined] +np.__expired_functions__ # type: ignore[attr-defined] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/multiarray.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/multiarray.pyi new file mode 100644 index 0000000000000000000000000000000000000000..51128dfbf6f785a96931cb8ee5d4df6a7574802d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/multiarray.pyi @@ -0,0 +1,52 @@ +import numpy as np +import numpy.typing as npt + +i8: np.int64 + +AR_b: npt.NDArray[np.bool] +AR_u1: npt.NDArray[np.uint8] +AR_i8: npt.NDArray[np.int64] +AR_f8: npt.NDArray[np.float64] +AR_M: npt.NDArray[np.datetime64] + +M: np.datetime64 + +AR_LIKE_f: list[float] + +def func(a: int) -> None: ... + +np.where(AR_b, 1) # type: ignore[call-overload] + +np.can_cast(AR_f8, 1) # type: ignore[arg-type] + +np.vdot(AR_M, AR_M) # type: ignore[arg-type] + +np.copyto(AR_LIKE_f, AR_f8) # type: ignore[arg-type] + +np.putmask(AR_LIKE_f, [True, True, False], 1.5) # type: ignore[arg-type] + +np.packbits(AR_f8) # type: ignore[arg-type] +np.packbits(AR_u1, bitorder=">") # type: ignore[call-overload] + +np.unpackbits(AR_i8) # type: ignore[arg-type] +np.unpackbits(AR_u1, bitorder=">") # type: ignore[call-overload] + +np.shares_memory(1, 1, max_work=i8) # type: ignore[arg-type] +np.may_share_memory(1, 1, max_work=i8) # type: ignore[arg-type] + +np.arange(stop=10) # type: ignore[call-overload] + +np.datetime_data(int) # type: ignore[arg-type] + +np.busday_offset("2012", 10) # type: ignore[call-overload] + +np.datetime_as_string("2012") # type: ignore[call-overload] + +np.char.compare_chararrays("a", b"a", "==", False) # type: ignore[call-overload] + +np.nested_iters([AR_i8, AR_i8]) # type: ignore[call-arg] +np.nested_iters([AR_i8, AR_i8], 0) # type: ignore[arg-type] +np.nested_iters([AR_i8, AR_i8], [0]) # type: ignore[list-item] +np.nested_iters([AR_i8, AR_i8], [[0], [1]], flags=["test"]) # type: ignore[list-item] +np.nested_iters([AR_i8, AR_i8], [[0], [1]], op_flags=[["test"]]) # type: ignore[list-item] +np.nested_iters([AR_i8, AR_i8], [[0], [1]], buffersize=1.0) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ndarray.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ndarray.pyi new file mode 100644 index 0000000000000000000000000000000000000000..2aeec0883e3ff1463c36d64ec233af91d83220bc --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ndarray.pyi @@ -0,0 +1,11 @@ +import numpy as np + +# Ban setting dtype since mutating the type of the array in place +# makes having ndarray be generic over dtype impossible. Generally +# users should use `ndarray.view` in this situation anyway. See +# +# https://github.com/numpy/numpy-stubs/issues/7 +# +# for more context. +float_array = np.array([1.0]) +float_array.dtype = np.bool # type: ignore[assignment, misc] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ndarray_misc.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ndarray_misc.pyi new file mode 100644 index 0000000000000000000000000000000000000000..29418930061c3753882b36457d9491ea130cd25c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ndarray_misc.pyi @@ -0,0 +1,49 @@ +""" +Tests for miscellaneous (non-magic) ``np.ndarray``/``np.generic`` methods. + +More extensive tests are performed for the methods' +function-based counterpart in `../from_numeric.py`. + +""" +from typing import Never + +import numpy as np +import numpy.typing as npt + +f8: np.float64 +AR_f8: npt.NDArray[np.float64] +AR_M: npt.NDArray[np.datetime64] +AR_b: npt.NDArray[np.bool] + +ctypes_obj = AR_f8.ctypes + +f8.argpartition(0) # type: ignore[attr-defined] +f8.partition(0) # type: ignore[attr-defined] +f8.dot(1) # type: ignore[attr-defined] + +# NOTE: The following functions retur `Never`, causing mypy to stop analysis at that +# point, which we circumvent by wrapping them in a function. + +def f8_diagonal(x: np.float64) -> Never: + return x.diagonal() # type: ignore[misc] + +def f8_nonzero(x: np.float64) -> Never: + return x.nonzero() # type: ignore[misc] + +def f8_setfield(x: np.float64) -> Never: + return x.setfield(2, np.float64) # type: ignore[misc] + +def f8_sort(x: np.float64) -> Never: + return x.sort() # type: ignore[misc] + +def f8_trace(x: np.float64) -> Never: + return x.trace() # type: ignore[misc] + +AR_M.__complex__() # type: ignore[misc] +AR_b.__index__() # type: ignore[misc] + +AR_f8[1.5] # type: ignore[call-overload] +AR_f8["field_a"] # type: ignore[call-overload] +AR_f8[["field_a", "field_b"]] # type: ignore[index] + +AR_f8.__array_finalize__(object()) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/nditer.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/nditer.pyi new file mode 100644 index 0000000000000000000000000000000000000000..fae728da454e76a5459012fd6af66345ffaa5422 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/nditer.pyi @@ -0,0 +1,8 @@ +import numpy as np + +class Test(np.nditer): ... # type: ignore[misc] + +np.nditer([0, 1], flags=["test"]) # type: ignore[list-item] +np.nditer([0, 1], op_flags=[["test"]]) # type: ignore[list-item] +np.nditer([0, 1], itershape=(1.0,)) # type: ignore[arg-type] +np.nditer([0, 1], buffersize=1.0) # type: ignore[call-overload] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/nested_sequence.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/nested_sequence.pyi new file mode 100644 index 0000000000000000000000000000000000000000..1004a36accc7958835c2bb8fa2dae9d8e0135016 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/nested_sequence.pyi @@ -0,0 +1,17 @@ +from collections.abc import Sequence + +from numpy._typing import _NestedSequence + +a: Sequence[float] +b: list[complex] +c: tuple[str, ...] +d: int +e: str + +def func(a: _NestedSequence[int]) -> None: ... + +reveal_type(func(a)) # type: ignore[arg-type, misc] +reveal_type(func(b)) # type: ignore[arg-type, misc] +reveal_type(func(c)) # type: ignore[arg-type, misc] +reveal_type(func(d)) # type: ignore[arg-type, misc] +reveal_type(func(e)) # type: ignore[arg-type, misc] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/npyio.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/npyio.pyi new file mode 100644 index 0000000000000000000000000000000000000000..e20be3a2a2470ae8d233bb5a099c0336236c9ec1 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/npyio.pyi @@ -0,0 +1,24 @@ +import pathlib +from typing import IO + +import numpy as np +import numpy.typing as npt + +str_path: str +bytes_path: bytes +pathlib_path: pathlib.Path +str_file: IO[str] +AR_i8: npt.NDArray[np.int64] + +np.load(str_file) # type: ignore[arg-type] + +np.save(bytes_path, AR_i8) # type: ignore[arg-type] +np.save(str_path, AR_i8, fix_imports=True) # type: ignore[call-arg] + +np.savez(bytes_path, AR_i8) # type: ignore[arg-type] + +np.savez_compressed(bytes_path, AR_i8) # type: ignore[arg-type] + +np.loadtxt(bytes_path) # type: ignore[arg-type] + +np.fromregex(bytes_path, ".", np.int64) # type: ignore[call-overload] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/numerictypes.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/numerictypes.pyi new file mode 100644 index 0000000000000000000000000000000000000000..a1fd47a6f479039639bf188399c8cd001f45d6c0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/numerictypes.pyi @@ -0,0 +1,5 @@ +import numpy as np + +np.isdtype(1, np.int64) # type: ignore[arg-type] + +np.issubdtype(1, np.int64) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/random.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/random.pyi new file mode 100644 index 0000000000000000000000000000000000000000..1abf4b77653c5f49fa095e0785949aef16a34ced --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/random.pyi @@ -0,0 +1,62 @@ +import numpy as np +import numpy.typing as npt + +SEED_FLOAT: float = 457.3 +SEED_ARR_FLOAT: npt.NDArray[np.float64] = np.array([1.0, 2, 3, 4]) +SEED_ARRLIKE_FLOAT: list[float] = [1.0, 2.0, 3.0, 4.0] +SEED_SEED_SEQ: np.random.SeedSequence = np.random.SeedSequence(0) +SEED_STR: str = "String seeding not allowed" + +# default rng +np.random.default_rng(SEED_FLOAT) # type: ignore[arg-type] +np.random.default_rng(SEED_ARR_FLOAT) # type: ignore[arg-type] +np.random.default_rng(SEED_ARRLIKE_FLOAT) # type: ignore[arg-type] +np.random.default_rng(SEED_STR) # type: ignore[arg-type] + +# Seed Sequence +np.random.SeedSequence(SEED_FLOAT) # type: ignore[arg-type] +np.random.SeedSequence(SEED_ARR_FLOAT) # type: ignore[arg-type] +np.random.SeedSequence(SEED_ARRLIKE_FLOAT) # type: ignore[arg-type] +np.random.SeedSequence(SEED_SEED_SEQ) # type: ignore[arg-type] +np.random.SeedSequence(SEED_STR) # type: ignore[arg-type] + +seed_seq: np.random.bit_generator.SeedSequence = np.random.SeedSequence() +seed_seq.spawn(11.5) # type: ignore[arg-type] +seed_seq.generate_state(3.14) # type: ignore[arg-type] +seed_seq.generate_state(3, np.uint8) # type: ignore[arg-type] +seed_seq.generate_state(3, "uint8") # type: ignore[arg-type] +seed_seq.generate_state(3, "u1") # type: ignore[arg-type] +seed_seq.generate_state(3, np.uint16) # type: ignore[arg-type] +seed_seq.generate_state(3, "uint16") # type: ignore[arg-type] +seed_seq.generate_state(3, "u2") # type: ignore[arg-type] +seed_seq.generate_state(3, np.int32) # type: ignore[arg-type] +seed_seq.generate_state(3, "int32") # type: ignore[arg-type] +seed_seq.generate_state(3, "i4") # type: ignore[arg-type] + +# Bit Generators +np.random.MT19937(SEED_FLOAT) # type: ignore[arg-type] +np.random.MT19937(SEED_ARR_FLOAT) # type: ignore[arg-type] +np.random.MT19937(SEED_ARRLIKE_FLOAT) # type: ignore[arg-type] +np.random.MT19937(SEED_STR) # type: ignore[arg-type] + +np.random.PCG64(SEED_FLOAT) # type: ignore[arg-type] +np.random.PCG64(SEED_ARR_FLOAT) # type: ignore[arg-type] +np.random.PCG64(SEED_ARRLIKE_FLOAT) # type: ignore[arg-type] +np.random.PCG64(SEED_STR) # type: ignore[arg-type] + +np.random.Philox(SEED_FLOAT) # type: ignore[arg-type] +np.random.Philox(SEED_ARR_FLOAT) # type: ignore[arg-type] +np.random.Philox(SEED_ARRLIKE_FLOAT) # type: ignore[arg-type] +np.random.Philox(SEED_STR) # type: ignore[arg-type] + +np.random.SFC64(SEED_FLOAT) # type: ignore[arg-type] +np.random.SFC64(SEED_ARR_FLOAT) # type: ignore[arg-type] +np.random.SFC64(SEED_ARRLIKE_FLOAT) # type: ignore[arg-type] +np.random.SFC64(SEED_STR) # type: ignore[arg-type] + +# Generator +np.random.Generator(None) # type: ignore[arg-type] +np.random.Generator(12333283902830213) # type: ignore[arg-type] +np.random.Generator("OxFEEDF00D") # type: ignore[arg-type] +np.random.Generator([123, 234]) # type: ignore[arg-type] +np.random.Generator(np.array([123, 234], dtype="u4")) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/rec.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/rec.pyi new file mode 100644 index 0000000000000000000000000000000000000000..c9d43dd2ff1fc48cfb99630d27481de929100077 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/rec.pyi @@ -0,0 +1,17 @@ +import numpy as np +import numpy.typing as npt + +AR_i8: npt.NDArray[np.int64] + +np.rec.fromarrays(1) # type: ignore[call-overload] +np.rec.fromarrays([1, 2, 3], dtype=[("f8", "f8")], formats=["f8", "f8"]) # type: ignore[call-overload] + +np.rec.fromrecords(AR_i8) # type: ignore[arg-type] +np.rec.fromrecords([(1.5,)], dtype=[("f8", "f8")], formats=["f8", "f8"]) # type: ignore[call-overload] + +np.rec.fromstring("string", dtype=[("f8", "f8")]) # type: ignore[call-overload] +np.rec.fromstring(b"bytes") # type: ignore[call-overload] +np.rec.fromstring(b"(1.5,)", dtype=[("f8", "f8")], formats=["f8", "f8"]) # type: ignore[call-overload] + +with open("test", "r") as f: + np.rec.fromfile(f, dtype=[("f8", "f8")]) # type: ignore[call-overload] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/scalars.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/scalars.pyi new file mode 100644 index 0000000000000000000000000000000000000000..018a88e652ae7c5d39119fa18fbe525b9556d373 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/scalars.pyi @@ -0,0 +1,86 @@ +import numpy as np + +f2: np.float16 +f8: np.float64 +c8: np.complex64 + +# Construction + +np.float32(3j) # type: ignore[arg-type] + +# Technically the following examples are valid NumPy code. But they +# are not considered a best practice, and people who wish to use the +# stubs should instead do +# +# np.array([1.0, 0.0, 0.0], dtype=np.float32) +# np.array([], dtype=np.complex64) +# +# See e.g. the discussion on the mailing list +# +# https://mail.python.org/pipermail/numpy-discussion/2020-April/080566.html +# +# and the issue +# +# https://github.com/numpy/numpy-stubs/issues/41 +# +# for more context. +np.float32([1.0, 0.0, 0.0]) # type: ignore[arg-type] +np.complex64([]) # type: ignore[call-overload] + +# TODO: protocols (can't check for non-existent protocols w/ __getattr__) + +np.datetime64(0) # type: ignore[call-overload] + +class A: + def __float__(self) -> float: ... + +np.int8(A()) # type: ignore[arg-type] +np.int16(A()) # type: ignore[arg-type] +np.int32(A()) # type: ignore[arg-type] +np.int64(A()) # type: ignore[arg-type] +np.uint8(A()) # type: ignore[arg-type] +np.uint16(A()) # type: ignore[arg-type] +np.uint32(A()) # type: ignore[arg-type] +np.uint64(A()) # type: ignore[arg-type] + +np.void("test") # type: ignore[call-overload] +np.void("test", dtype=None) # type: ignore[call-overload] + +np.generic(1) # type: ignore[abstract] +np.number(1) # type: ignore[abstract] +np.integer(1) # type: ignore[abstract] +np.inexact(1) # type: ignore[abstract] +np.character("test") # type: ignore[abstract] +np.flexible(b"test") # type: ignore[abstract] + +np.float64(value=0.0) # type: ignore[call-arg] +np.int64(value=0) # type: ignore[call-arg] +np.uint64(value=0) # type: ignore[call-arg] +np.complex128(value=0.0j) # type: ignore[call-overload] +np.str_(value="bob") # type: ignore[call-overload] +np.bytes_(value=b"test") # type: ignore[call-overload] +np.void(value=b"test") # type: ignore[call-overload] +np.bool(value=True) # type: ignore[call-overload] +np.datetime64(value="2019") # type: ignore[call-overload] +np.timedelta64(value=0) # type: ignore[call-overload] + +np.bytes_(b"hello", encoding="utf-8") # type: ignore[call-overload] +np.str_("hello", encoding="utf-8") # type: ignore[call-overload] + +f8.item(1) # type: ignore[call-overload] +f8.item((0, 1)) # type: ignore[arg-type] +f8.squeeze(axis=1) # type: ignore[arg-type] +f8.squeeze(axis=(0, 1)) # type: ignore[arg-type] +f8.transpose(1) # type: ignore[arg-type] + +def func(a: np.float32) -> None: ... + +func(f2) # type: ignore[arg-type] +func(f8) # type: ignore[arg-type] + +c8.__getnewargs__() # type: ignore[attr-defined] +f2.__getnewargs__() # type: ignore[attr-defined] +f2.hex() # type: ignore[attr-defined] +np.float16.fromhex("0x0.0p+0") # type: ignore[attr-defined] +f2.__trunc__() # type: ignore[attr-defined] +f2.__getformat__("float") # type: ignore[attr-defined] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/shape.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/shape.pyi new file mode 100644 index 0000000000000000000000000000000000000000..a024d7bda27367395ebf028b65a75b0b0bbfd7b6 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/shape.pyi @@ -0,0 +1,7 @@ +from typing import Any + +import numpy as np + +# test bounds of _ShapeT_co + +np.ndarray[tuple[str, str], Any] # type: ignore[type-var] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/shape_base.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/shape_base.pyi new file mode 100644 index 0000000000000000000000000000000000000000..652b24ba311e35411fd0fc11f3e79c5d90a6dac4 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/shape_base.pyi @@ -0,0 +1,8 @@ +import numpy as np + +class DTypeLike: + dtype: np.dtype[np.int_] + +dtype_like: DTypeLike + +np.expand_dims(dtype_like, (5, 10)) # type: ignore[call-overload] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/stride_tricks.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/stride_tricks.pyi new file mode 100644 index 0000000000000000000000000000000000000000..7f9a26b9692438eef717972fcc0024d2ab4dbcb9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/stride_tricks.pyi @@ -0,0 +1,9 @@ +import numpy as np +import numpy.typing as npt + +AR_f8: npt.NDArray[np.float64] + +np.lib.stride_tricks.as_strided(AR_f8, shape=8) # type: ignore[call-overload] +np.lib.stride_tricks.as_strided(AR_f8, strides=8) # type: ignore[call-overload] + +np.lib.stride_tricks.sliding_window_view(AR_f8, axis=(1,)) # type: ignore[call-overload] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/strings.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/strings.pyi new file mode 100644 index 0000000000000000000000000000000000000000..328a521ae67957086e9d490975634cda448e5497 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/strings.pyi @@ -0,0 +1,52 @@ +import numpy as np +import numpy.typing as npt + +AR_U: npt.NDArray[np.str_] +AR_S: npt.NDArray[np.bytes_] + +np.strings.equal(AR_U, AR_S) # type: ignore[arg-type] +np.strings.not_equal(AR_U, AR_S) # type: ignore[arg-type] + +np.strings.greater_equal(AR_U, AR_S) # type: ignore[arg-type] +np.strings.less_equal(AR_U, AR_S) # type: ignore[arg-type] +np.strings.greater(AR_U, AR_S) # type: ignore[arg-type] +np.strings.less(AR_U, AR_S) # type: ignore[arg-type] + +np.strings.encode(AR_S) # type: ignore[arg-type] +np.strings.decode(AR_U) # type: ignore[arg-type] + +np.strings.lstrip(AR_U, b"a") # type: ignore[arg-type] +np.strings.lstrip(AR_S, "a") # type: ignore[arg-type] +np.strings.strip(AR_U, b"a") # type: ignore[arg-type] +np.strings.strip(AR_S, "a") # type: ignore[arg-type] +np.strings.rstrip(AR_U, b"a") # type: ignore[arg-type] +np.strings.rstrip(AR_S, "a") # type: ignore[arg-type] + +np.strings.partition(AR_U, b"a") # type: ignore[arg-type] +np.strings.partition(AR_S, "a") # type: ignore[arg-type] +np.strings.rpartition(AR_U, b"a") # type: ignore[arg-type] +np.strings.rpartition(AR_S, "a") # type: ignore[arg-type] + +np.strings.count(AR_U, b"a", [1, 2, 3], [1, 2, 3]) # type: ignore[arg-type] +np.strings.count(AR_S, "a", 0, 9) # type: ignore[arg-type] + +np.strings.endswith(AR_U, b"a", [1, 2, 3], [1, 2, 3]) # type: ignore[arg-type] +np.strings.endswith(AR_S, "a", 0, 9) # type: ignore[arg-type] +np.strings.startswith(AR_U, b"a", [1, 2, 3], [1, 2, 3]) # type: ignore[arg-type] +np.strings.startswith(AR_S, "a", 0, 9) # type: ignore[arg-type] + +np.strings.find(AR_U, b"a", [1, 2, 3], [1, 2, 3]) # type: ignore[arg-type] +np.strings.find(AR_S, "a", 0, 9) # type: ignore[arg-type] +np.strings.rfind(AR_U, b"a", [1, 2, 3], [1, 2, 3]) # type: ignore[arg-type] +np.strings.rfind(AR_S, "a", 0, 9) # type: ignore[arg-type] + +np.strings.index(AR_U, b"a", start=[1, 2, 3]) # type: ignore[arg-type] +np.strings.index(AR_S, "a", end=9) # type: ignore[arg-type] +np.strings.rindex(AR_U, b"a", start=[1, 2, 3]) # type: ignore[arg-type] +np.strings.rindex(AR_S, "a", end=9) # type: ignore[arg-type] + +np.strings.isdecimal(AR_S) # type: ignore[arg-type] +np.strings.isnumeric(AR_S) # type: ignore[arg-type] + +np.strings.replace(AR_U, b"_", b"-", 10) # type: ignore[arg-type] +np.strings.replace(AR_S, "_", "-", 1) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/testing.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/testing.pyi new file mode 100644 index 0000000000000000000000000000000000000000..517062c4c95261dbde10cf52e299ffc1d0cdd8b3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/testing.pyi @@ -0,0 +1,28 @@ +import numpy as np +import numpy.typing as npt + +AR_U: npt.NDArray[np.str_] + +def func(x: object) -> bool: ... + +np.testing.assert_(True, msg=1) # type: ignore[arg-type] +np.testing.build_err_msg(1, "test") # type: ignore[arg-type] +np.testing.assert_almost_equal(AR_U, AR_U) # type: ignore[arg-type] +np.testing.assert_approx_equal([1, 2, 3], [1, 2, 3]) # type: ignore[arg-type] +np.testing.assert_array_almost_equal(AR_U, AR_U) # type: ignore[arg-type] +np.testing.assert_array_less(AR_U, AR_U) # type: ignore[arg-type] +np.testing.assert_string_equal(b"a", b"a") # type: ignore[arg-type] + +np.testing.assert_raises(expected_exception=TypeError, callable=func) # type: ignore[call-overload] +np.testing.assert_raises_regex(expected_exception=TypeError, expected_regex="T", callable=func) # type: ignore[call-overload] + +np.testing.assert_allclose(AR_U, AR_U) # type: ignore[arg-type] +np.testing.assert_array_almost_equal_nulp(AR_U, AR_U) # type: ignore[arg-type] +np.testing.assert_array_max_ulp(AR_U, AR_U) # type: ignore[arg-type] + +np.testing.assert_warns(RuntimeWarning, func) # type: ignore[call-overload] +np.testing.assert_no_warnings(func=func) # type: ignore[call-overload] +np.testing.assert_no_warnings(func) # type: ignore[call-overload] +np.testing.assert_no_warnings(func, y=None) # type: ignore[call-overload] + +np.testing.assert_no_gc_cycles(func=func) # type: ignore[call-overload] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/twodim_base.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/twodim_base.pyi new file mode 100644 index 0000000000000000000000000000000000000000..473419cecef1bd101d5e98db0fe52ddf06403f10 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/twodim_base.pyi @@ -0,0 +1,39 @@ +from typing import type_check_only + +import numpy as np +import numpy.typing as npt + +_0d_bool: np.bool +_nd_bool: npt.NDArray[np.bool] +_nd_td64: npt.NDArray[np.timedelta64] +_to_2d_bool: list[list[bool]] + +@type_check_only +def func1(ar: np.ndarray, a: int) -> npt.NDArray[np.str_]: ... +@type_check_only +def func2(ar: np.ndarray, a: float) -> float: ... + +### + +np.eye(10, M=20.0) # type: ignore[call-overload] +np.eye(10, k=2.5, dtype=int) # type: ignore[call-overload] + +np.diag(_nd_bool, k=0.5) # type: ignore[call-overload] +np.diagflat(_nd_bool, k=0.5) # type: ignore[call-overload] + +np.tri(10, M=20.0) # type: ignore[call-overload] +np.tri(10, k=2.5, dtype=int) # type: ignore[call-overload] + +np.tril(_nd_bool, k=0.5) # type: ignore[call-overload] +np.triu(_nd_bool, k=0.5) # type: ignore[call-overload] + +np.vander(_nd_td64) # type: ignore[type-var] + +np.histogram2d(_nd_td64) # type: ignore[call-overload] + +np.mask_indices(10, func1) # type: ignore[arg-type] +np.mask_indices(10, func2, 10.5) # type: ignore[arg-type] + +np.tril_indices(3.14) # type: ignore[arg-type] + +np.tril_indices_from(_to_2d_bool) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/type_check.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/type_check.pyi new file mode 100644 index 0000000000000000000000000000000000000000..8b68e996304ccda7359b1a9756865eca754aa27a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/type_check.pyi @@ -0,0 +1,12 @@ +import numpy as np + +DTYPE_i8: np.dtype[np.int64] + +np.mintypecode(DTYPE_i8) # type: ignore[arg-type] +np.iscomplexobj(DTYPE_i8) # type: ignore[arg-type] +np.isrealobj(DTYPE_i8) # type: ignore[arg-type] + +np.typename(DTYPE_i8) # type: ignore[call-overload] +np.typename("invalid") # type: ignore[call-overload] + +np.common_type(np.timedelta64()) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ufunc_config.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ufunc_config.pyi new file mode 100644 index 0000000000000000000000000000000000000000..c67b6a3acf989cda443dc1b82826cd9086202190 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ufunc_config.pyi @@ -0,0 +1,21 @@ +"""Typing tests for `numpy._core._ufunc_config`.""" + +import numpy as np + +def func1(a: str, b: int, c: float) -> None: ... +def func2(a: str, *, b: int) -> None: ... + +class Write1: + def write1(self, a: str) -> None: ... + +class Write2: + def write(self, a: str, b: str) -> None: ... + +class Write3: + def write(self, *, a: str) -> None: ... + +np.seterrcall(func1) # type: ignore[arg-type] +np.seterrcall(func2) # type: ignore[arg-type] +np.seterrcall(Write1()) # type: ignore[arg-type] +np.seterrcall(Write2()) # type: ignore[arg-type] +np.seterrcall(Write3()) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ufunclike.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ufunclike.pyi new file mode 100644 index 0000000000000000000000000000000000000000..e556e409ebbc90f1e57c096d53f656850c041b0f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ufunclike.pyi @@ -0,0 +1,21 @@ +import numpy as np +import numpy.typing as npt + +AR_c: npt.NDArray[np.complex128] +AR_m: npt.NDArray[np.timedelta64] +AR_M: npt.NDArray[np.datetime64] +AR_O: npt.NDArray[np.object_] + +np.fix(AR_c) # type: ignore[arg-type] +np.fix(AR_m) # type: ignore[arg-type] +np.fix(AR_M) # type: ignore[arg-type] + +np.isposinf(AR_c) # type: ignore[arg-type] +np.isposinf(AR_m) # type: ignore[arg-type] +np.isposinf(AR_M) # type: ignore[arg-type] +np.isposinf(AR_O) # type: ignore[arg-type] + +np.isneginf(AR_c) # type: ignore[arg-type] +np.isneginf(AR_m) # type: ignore[arg-type] +np.isneginf(AR_M) # type: ignore[arg-type] +np.isneginf(AR_O) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ufuncs.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ufuncs.pyi new file mode 100644 index 0000000000000000000000000000000000000000..1b1628d7da4431c5fc30c051a413052cbe6969ac --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/ufuncs.pyi @@ -0,0 +1,17 @@ +import numpy as np +import numpy.typing as npt + +AR_f8: npt.NDArray[np.float64] + +np.sin.nin + "foo" # type: ignore[operator] +np.sin(1, foo="bar") # type: ignore[call-overload] + +np.abs(None) # type: ignore[call-overload] + +np.add(1, 1, 1) # type: ignore[call-overload] +np.add(1, 1, axis=0) # type: ignore[call-overload] + +np.matmul(AR_f8, AR_f8, where=True) # type: ignore[call-overload] + +np.frexp(AR_f8, out=None) # type: ignore[call-overload] +np.frexp(AR_f8, out=AR_f8) # type: ignore[call-overload] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/warnings_and_errors.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/warnings_and_errors.pyi new file mode 100644 index 0000000000000000000000000000000000000000..8ba34f6dfa3ec31d2d363f88cd5a87e4b8ad69e8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/fail/warnings_and_errors.pyi @@ -0,0 +1,5 @@ +import numpy.exceptions as ex + +ex.AxisError(1.0) # type: ignore[call-overload] +ex.AxisError(1, ndim=2.0) # type: ignore[call-overload] +ex.AxisError(2, msg_prefix=404) # type: ignore[call-overload] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/misc/extended_precision.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/misc/extended_precision.pyi new file mode 100644 index 0000000000000000000000000000000000000000..7978faf4d5bd1b1fba35fc84146ee42e25c8405a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/misc/extended_precision.pyi @@ -0,0 +1,9 @@ +from typing import assert_type + +import numpy as np +from numpy._typing import _96Bit, _128Bit + +assert_type(np.float96(), np.floating[_96Bit]) +assert_type(np.float128(), np.floating[_128Bit]) +assert_type(np.complex192(), np.complexfloating[_96Bit, _96Bit]) +assert_type(np.complex256(), np.complexfloating[_128Bit, _128Bit]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/mypy.ini b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/mypy.ini new file mode 100644 index 0000000000000000000000000000000000000000..4aa465ae087bc2be5013d282a979b9a48fb9a485 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/mypy.ini @@ -0,0 +1,8 @@ +[mypy] +strict = True +enable_error_code = deprecated, ignore-without-code, truthy-bool +disallow_any_unimported = True +allow_redefinition_new = True +local_partial_types = True +show_absolute_path = True +pretty = True diff --git 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b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/arithmetic.py @@ -0,0 +1,614 @@ +from __future__ import annotations + +from typing import Any, cast + +import pytest + +import numpy as np +import numpy.typing as npt + +c16 = np.complex128(1) +f8 = np.float64(1) +i8 = np.int64(1) +u8 = np.uint64(1) + +c8 = np.complex64(1) +f4 = np.float32(1) +i4 = np.int32(1) +u4 = np.uint32(1) + +dt = np.datetime64(1, "D") +td = np.timedelta64(1, "D") + +b_ = np.bool(1) + +b = bool(1) +c = complex(1) +f = float(1) +i = 1 + + +class Object: + def __array__(self, dtype: np.typing.DTypeLike | None = None, + copy: bool | None = None) -> np.ndarray[Any, np.dtype[np.object_]]: + ret = np.empty((), dtype=object) + ret[()] = self + return ret + + def __sub__(self, value: Any) -> Object: + return self + + def __rsub__(self, value: Any) -> Object: + return self + + def __floordiv__(self, value: Any) -> Object: + return self + + def __rfloordiv__(self, value: Any) -> Object: + return self + + def __mul__(self, value: Any) -> Object: + return self + + def __rmul__(self, value: Any) -> Object: + return self + + def __pow__(self, value: Any) -> Object: + return self + + def __rpow__(self, value: Any) -> Object: + return self + + +AR_b: npt.NDArray[np.bool] = np.array([True]) +AR_u: npt.NDArray[np.uint32] = np.array([1], dtype=np.uint32) +AR_i: npt.NDArray[np.int64] = np.array([1]) +AR_integer: npt.NDArray[np.integer] = cast(npt.NDArray[np.integer], AR_i) +AR_f: npt.NDArray[np.float64] = np.array([1.0]) +AR_c: npt.NDArray[np.complex128] = np.array([1j]) +AR_m: npt.NDArray[np.timedelta64] = np.array([np.timedelta64(1, "D")]) +AR_M: npt.NDArray[np.datetime64] = np.array([np.datetime64(1, "D")]) +AR_O: npt.NDArray[np.object_] = np.array([Object()]) + +AR_LIKE_b = [True] +AR_LIKE_u = [np.uint32(1)] +AR_LIKE_i = [1] +AR_LIKE_f = [1.0] +AR_LIKE_c = [1j] +AR_LIKE_m = [np.timedelta64(1, "D")] +AR_LIKE_M = [np.datetime64(1, "D")] +AR_LIKE_O = [Object()] + +# Array subtractions + +AR_b - AR_LIKE_u +AR_b - AR_LIKE_i +AR_b - AR_LIKE_f +AR_b - AR_LIKE_c +AR_b - AR_LIKE_m +AR_b - AR_LIKE_O + +AR_LIKE_u - AR_b +AR_LIKE_i - AR_b +AR_LIKE_f - AR_b +AR_LIKE_c - AR_b +AR_LIKE_m - AR_b +AR_LIKE_M - AR_b +AR_LIKE_O - AR_b + +AR_u - AR_LIKE_b +AR_u - AR_LIKE_u +AR_u - AR_LIKE_i +AR_u - AR_LIKE_f +AR_u - AR_LIKE_c +AR_u - AR_LIKE_m +AR_u - AR_LIKE_O + +AR_LIKE_b - AR_u +AR_LIKE_u - AR_u +AR_LIKE_i - AR_u +AR_LIKE_f - AR_u +AR_LIKE_c - AR_u +AR_LIKE_m - AR_u +AR_LIKE_M - AR_u +AR_LIKE_O - AR_u + +AR_i - AR_LIKE_b +AR_i - AR_LIKE_u +AR_i - AR_LIKE_i +AR_i - AR_LIKE_f +AR_i - AR_LIKE_c +AR_i - AR_LIKE_m +AR_i - AR_LIKE_O + +AR_LIKE_b - AR_i +AR_LIKE_u - AR_i +AR_LIKE_i - AR_i +AR_LIKE_f - AR_i +AR_LIKE_c - AR_i +AR_LIKE_m - AR_i +AR_LIKE_M - AR_i +AR_LIKE_O - AR_i + +AR_f - AR_LIKE_b +AR_f - AR_LIKE_u +AR_f - AR_LIKE_i +AR_f - AR_LIKE_f +AR_f - AR_LIKE_c +AR_f - AR_LIKE_O + +AR_LIKE_b - AR_f +AR_LIKE_u - AR_f +AR_LIKE_i - AR_f +AR_LIKE_f - AR_f +AR_LIKE_c - AR_f +AR_LIKE_O - AR_f + +AR_c - AR_LIKE_b +AR_c - AR_LIKE_u +AR_c - AR_LIKE_i +AR_c - AR_LIKE_f +AR_c - AR_LIKE_c +AR_c - AR_LIKE_O + +AR_LIKE_b - AR_c +AR_LIKE_u - AR_c +AR_LIKE_i - AR_c +AR_LIKE_f - AR_c +AR_LIKE_c - AR_c +AR_LIKE_O - AR_c + +AR_m - AR_LIKE_b +AR_m - AR_LIKE_u +AR_m - AR_LIKE_i +AR_m - AR_LIKE_m + +AR_LIKE_b - AR_m +AR_LIKE_u - AR_m +AR_LIKE_i - AR_m +AR_LIKE_m - AR_m +AR_LIKE_M - AR_m + +AR_M - AR_LIKE_b +AR_M - AR_LIKE_u +AR_M - AR_LIKE_i +AR_M - AR_LIKE_m +AR_M - AR_LIKE_M + +AR_LIKE_M - AR_M + +AR_O - AR_LIKE_b +AR_O - AR_LIKE_u +AR_O - AR_LIKE_i +AR_O - AR_LIKE_f +AR_O - AR_LIKE_c +AR_O - AR_LIKE_O + +AR_LIKE_b - AR_O +AR_LIKE_u - AR_O +AR_LIKE_i - AR_O +AR_LIKE_f - AR_O +AR_LIKE_c - AR_O +AR_LIKE_O - AR_O + +AR_u += AR_b +AR_u += AR_u +AR_u += 1 # Allowed during runtime as long as the object is 0D and >=0 + +# Array floor division + +AR_b // AR_LIKE_b +AR_b // AR_LIKE_u +AR_b // AR_LIKE_i +AR_b // AR_LIKE_f +AR_b // AR_LIKE_O + +AR_LIKE_b // AR_b +AR_LIKE_u // AR_b +AR_LIKE_i // AR_b +AR_LIKE_f // AR_b +AR_LIKE_O // AR_b + +AR_u // AR_LIKE_b +AR_u // AR_LIKE_u +AR_u // AR_LIKE_i +AR_u // AR_LIKE_f +AR_u // AR_LIKE_O + +AR_LIKE_b // AR_u +AR_LIKE_u // AR_u +AR_LIKE_i // AR_u +AR_LIKE_f // AR_u +AR_LIKE_m // AR_u +AR_LIKE_O // AR_u + +AR_i // AR_LIKE_b +AR_i // AR_LIKE_u +AR_i // AR_LIKE_i +AR_i // AR_LIKE_f +AR_i // AR_LIKE_O + +AR_LIKE_b // AR_i +AR_LIKE_u // AR_i +AR_LIKE_i // AR_i +AR_LIKE_f // AR_i +AR_LIKE_m // AR_i +AR_LIKE_O // AR_i + +AR_f // AR_LIKE_b +AR_f // AR_LIKE_u +AR_f // AR_LIKE_i +AR_f // AR_LIKE_f +AR_f // AR_LIKE_O + +AR_LIKE_b // AR_f +AR_LIKE_u // AR_f +AR_LIKE_i // AR_f +AR_LIKE_f // AR_f +AR_LIKE_m // AR_f +AR_LIKE_O // AR_f + +AR_m // AR_LIKE_u +AR_m // AR_LIKE_i +AR_m // AR_LIKE_f +AR_m // AR_LIKE_m + +AR_LIKE_m // AR_m + +AR_m /= f +AR_m //= f +AR_m /= AR_f +AR_m /= AR_LIKE_f +AR_m //= AR_f +AR_m //= AR_LIKE_f + +AR_O // AR_LIKE_b +AR_O // AR_LIKE_u +AR_O // AR_LIKE_i +AR_O // AR_LIKE_f +AR_O // AR_LIKE_O + +AR_LIKE_b // AR_O +AR_LIKE_u // AR_O +AR_LIKE_i // AR_O +AR_LIKE_f // AR_O +AR_LIKE_O // AR_O + +# Inplace multiplication + +AR_b *= AR_LIKE_b + +AR_u *= AR_LIKE_b +AR_u *= AR_LIKE_u + +AR_i *= AR_LIKE_b +AR_i *= AR_LIKE_u +AR_i *= AR_LIKE_i + +AR_integer *= AR_LIKE_b +AR_integer *= AR_LIKE_u +AR_integer *= AR_LIKE_i + +AR_f *= AR_LIKE_b +AR_f *= AR_LIKE_u +AR_f *= AR_LIKE_i +AR_f *= AR_LIKE_f + +AR_c *= AR_LIKE_b +AR_c *= AR_LIKE_u +AR_c *= AR_LIKE_i +AR_c *= AR_LIKE_f +AR_c *= AR_LIKE_c + +AR_m *= AR_LIKE_b +AR_m *= AR_LIKE_u +AR_m *= AR_LIKE_i +AR_m *= AR_LIKE_f + +AR_O *= AR_LIKE_b +AR_O *= AR_LIKE_u +AR_O *= AR_LIKE_i +AR_O *= AR_LIKE_f +AR_O *= AR_LIKE_c +AR_O *= AR_LIKE_O + +# Inplace power + +AR_u **= AR_LIKE_b +AR_u **= AR_LIKE_u + +AR_i **= AR_LIKE_b +AR_i **= AR_LIKE_u +AR_i **= AR_LIKE_i + +AR_integer **= AR_LIKE_b +AR_integer **= AR_LIKE_u +AR_integer **= AR_LIKE_i + +AR_f **= AR_LIKE_b +AR_f **= AR_LIKE_u +AR_f **= AR_LIKE_i +AR_f **= AR_LIKE_f + +AR_c **= AR_LIKE_b +AR_c **= AR_LIKE_u +AR_c **= AR_LIKE_i +AR_c **= AR_LIKE_f +AR_c **= AR_LIKE_c + +AR_O **= AR_LIKE_b +AR_O **= AR_LIKE_u +AR_O **= AR_LIKE_i +AR_O **= AR_LIKE_f +AR_O **= AR_LIKE_c +AR_O **= AR_LIKE_O + +# unary ops + +-c16 +-c8 +-f8 +-f4 +-i8 +-i4 +with pytest.warns(RuntimeWarning): + -u8 + -u4 +-td +-AR_f + ++c16 ++c8 ++f8 ++f4 ++i8 ++i4 ++u8 ++u4 ++td ++AR_f + +abs(c16) +abs(c8) +abs(f8) +abs(f4) +abs(i8) +abs(i4) +abs(u8) +abs(u4) +abs(td) +abs(b_) +abs(AR_f) + +# Time structures + +dt + td +dt + i +dt + i4 +dt + i8 +dt - dt +dt - i +dt - i4 +dt - i8 + +td + td +td + i +td + i4 +td + i8 +td - td +td - i +td - i4 +td - i8 +td / f +td / f4 +td / f8 +td / td +td // td +td % td + + +# boolean + +b_ / b +b_ / b_ +b_ / i +b_ / i8 +b_ / i4 +b_ / u8 +b_ / u4 +b_ / f +b_ / f8 +b_ / f4 +b_ / c +b_ / c16 +b_ / c8 + +b / b_ +b_ / b_ +i / b_ +i8 / b_ +i4 / b_ +u8 / b_ +u4 / b_ +f / b_ +f8 / b_ +f4 / b_ +c / b_ +c16 / b_ +c8 / b_ + +# Complex + +c16 + c16 +c16 + f8 +c16 + i8 +c16 + c8 +c16 + f4 +c16 + i4 +c16 + b_ +c16 + b +c16 + c +c16 + f +c16 + i +c16 + AR_f + +c16 + c16 +f8 + c16 +i8 + c16 +c8 + c16 +f4 + c16 +i4 + c16 +b_ + c16 +b + c16 +c + c16 +f + c16 +i + c16 +AR_f + c16 + +c8 + c16 +c8 + f8 +c8 + i8 +c8 + c8 +c8 + f4 +c8 + i4 +c8 + b_ +c8 + b +c8 + c +c8 + f +c8 + i +c8 + AR_f + +c16 + c8 +f8 + c8 +i8 + c8 +c8 + c8 +f4 + c8 +i4 + c8 +b_ + c8 +b + c8 +c + c8 +f + c8 +i + c8 +AR_f + c8 + +# Float + +f8 + f8 +f8 + i8 +f8 + f4 +f8 + i4 +f8 + b_ +f8 + b +f8 + c +f8 + f +f8 + i +f8 + AR_f + +f8 + f8 +i8 + f8 +f4 + f8 +i4 + f8 +b_ + f8 +b + f8 +c + f8 +f + f8 +i + f8 +AR_f + f8 + +f4 + f8 +f4 + i8 +f4 + f4 +f4 + i4 +f4 + b_ +f4 + b +f4 + c +f4 + f +f4 + i +f4 + AR_f + +f8 + f4 +i8 + f4 +f4 + f4 +i4 + f4 +b_ + f4 +b + f4 +c + f4 +f + f4 +i + f4 +AR_f + f4 + +# Int + +i8 + i8 +i8 + u8 +i8 + i4 +i8 + u4 +i8 + b_ +i8 + b +i8 + c +i8 + f +i8 + i +i8 + AR_f + +u8 + u8 +u8 + i4 +u8 + u4 +u8 + b_ +u8 + b +u8 + c +u8 + f +u8 + i +u8 + AR_f + +i8 + i8 +u8 + i8 +i4 + i8 +u4 + i8 +b_ + i8 +b + i8 +c + i8 +f + i8 +i + i8 +AR_f + i8 + +u8 + u8 +i4 + u8 +u4 + u8 +b_ + u8 +b + u8 +c + u8 +f + u8 +i + u8 +AR_f + u8 + +i4 + i8 +i4 + i4 +i4 + i +i4 + b_ +i4 + b +i4 + AR_f + +u4 + i8 +u4 + i4 +u4 + u8 +u4 + u4 +u4 + i +u4 + b_ +u4 + b +u4 + AR_f + +i8 + i4 +i4 + i4 +i + i4 +b_ + i4 +b + i4 +AR_f + i4 + +i8 + u4 +i4 + u4 +u8 + u4 +u4 + u4 +b_ + u4 +b + u4 +i + u4 +AR_f + u4 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/array_constructors.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/array_constructors.py new file mode 100644 index 0000000000000000000000000000000000000000..d91d257cb17cf907326e066b184e6265656abdb2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/array_constructors.py @@ -0,0 +1,138 @@ +from typing import Any + +import numpy as np +import numpy.typing as npt + + +class Index: + def __index__(self) -> int: + return 0 + + +class SubClass(npt.NDArray[np.float64]): + pass + + +def func(i: int, j: int, **kwargs: Any) -> SubClass: + return B + + +i8 = np.int64(1) + +A = np.array([1]) +B = A.view(SubClass).copy() +B_stack = np.array([[1], [1]]).view(SubClass) +C = [1] + +np.ndarray(Index()) +np.ndarray([Index()]) + +np.array(1, dtype=float) +np.array(1, copy=None) +np.array(1, order='F') +np.array(1, order=None) +np.array(1, subok=True) +np.array(1, ndmin=3) +np.array(1, str, copy=True, order='C', subok=False, ndmin=2) + +np.asarray(A) +np.asarray(B) +np.asarray(C) + +np.asanyarray(A) +np.asanyarray(B) +np.asanyarray(B, dtype=int) +np.asanyarray(C) + +np.ascontiguousarray(A) +np.ascontiguousarray(B) +np.ascontiguousarray(C) + +np.asfortranarray(A) +np.asfortranarray(B) +np.asfortranarray(C) + +np.require(A) +np.require(B) +np.require(B, dtype=int) +np.require(B, requirements=None) +np.require(B, requirements="E") +np.require(B, requirements=["ENSUREARRAY"]) +np.require(B, requirements={"F", "E"}) +np.require(B, requirements=["C", "OWNDATA"]) +np.require(B, requirements="W") +np.require(B, requirements="A") +np.require(C) + +np.linspace(0, 2) +np.linspace(0.5, [0, 1, 2]) +np.linspace([0, 1, 2], 3) +np.linspace(0j, 2) +np.linspace(0, 2, num=10) +np.linspace(0, 2, endpoint=True) +np.linspace(0, 2, retstep=True) +np.linspace(0j, 2j, retstep=True) +np.linspace(0, 2, dtype=bool) +np.linspace([0, 1], [2, 3], axis=Index()) + +np.logspace(0, 2, base=2) +np.logspace(0, 2, base=2) +np.logspace(0, 2, base=[1j, 2j], num=2) + +np.geomspace(1, 2) + +np.zeros_like(A) +np.zeros_like(C) +np.zeros_like(B) +np.zeros_like(B, dtype=np.int64) + +np.ones_like(A) +np.ones_like(C) +np.ones_like(B) +np.ones_like(B, dtype=np.int64) + +np.empty_like(A) +np.empty_like(C) +np.empty_like(B) +np.empty_like(B, dtype=np.int64) + +np.full_like(A, i8) +np.full_like(C, i8) +np.full_like(B, i8) +np.full_like(B, i8, dtype=np.int64) + +np.ones(1) +np.ones([1, 1, 1]) + +np.full(1, i8) +np.full([1, 1, 1], i8) + +np.indices([1, 2, 3]) +np.indices([1, 2, 3], sparse=True) + +np.fromfunction(func, (3, 5)) + +np.identity(10) + +np.atleast_1d(C) +np.atleast_1d(A) +np.atleast_1d(C, C) +np.atleast_1d(C, A) +np.atleast_1d(A, A) + +np.atleast_2d(C) + +np.atleast_3d(C) + +np.vstack([C, C]) +np.vstack([C, A]) +np.vstack([A, A]) + +np.hstack([C, C]) + +np.stack([C, C]) +np.stack([C, C], axis=0) +np.stack([C, C], out=B_stack) + +np.block([[C, C], [C, C]]) +np.block(A) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/array_like.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/array_like.py new file mode 100644 index 0000000000000000000000000000000000000000..f922beae34ce87bfbd57cc8d0e6f5778cc4d96eb --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/array_like.py @@ -0,0 +1,43 @@ +from __future__ import annotations + +from typing import TYPE_CHECKING + +import numpy as np + +if TYPE_CHECKING: + from numpy._typing import ArrayLike, NDArray, _SupportsArray + +x1: ArrayLike = True +x2: ArrayLike = 5 +x3: ArrayLike = 1.0 +x4: ArrayLike = 1 + 1j +x5: ArrayLike = np.int8(1) +x6: ArrayLike = np.float64(1) +x7: ArrayLike = np.complex128(1) +x8: ArrayLike = np.array([1, 2, 3]) +x9: ArrayLike = [1, 2, 3] +x10: ArrayLike = (1, 2, 3) +x11: ArrayLike = "foo" +x12: ArrayLike = memoryview(b'foo') + + +class A: + def __array__(self, dtype: np.dtype | None = None) -> NDArray[np.float64]: + return np.array([1.0, 2.0, 3.0]) + + +x13: ArrayLike = A() + +scalar: _SupportsArray[np.dtype[np.int64]] = np.int64(1) +scalar.__array__() +array: _SupportsArray[np.dtype[np.int_]] = np.array(1) +array.__array__() + +a: _SupportsArray[np.dtype[np.float64]] = A() +a.__array__() +a.__array__() + +# Escape hatch for when you mean to make something like an object +# array. +object_array_scalar: object = (i for i in range(10)) +np.array(object_array_scalar) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/arrayprint.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/arrayprint.py new file mode 100644 index 0000000000000000000000000000000000000000..6c704c755570d1508424af92a0eb5aa1353666a0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/arrayprint.py @@ -0,0 +1,37 @@ +import numpy as np + +AR = np.arange(10) +AR.setflags(write=False) + +with np.printoptions(): + np.set_printoptions( + precision=1, + threshold=2, + edgeitems=3, + linewidth=4, + suppress=False, + nanstr="Bob", + infstr="Bill", + formatter={}, + sign="+", + floatmode="unique", + ) + np.get_printoptions() + str(AR) + + np.array2string( + AR, + max_line_width=5, + precision=2, + suppress_small=True, + separator=";", + prefix="test", + threshold=5, + floatmode="fixed", + suffix="?", + legacy="1.13", + ) + np.format_float_scientific(1, precision=5) + np.format_float_positional(1, trim="k") + np.array_repr(AR) + np.array_str(AR) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/arrayterator.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/arrayterator.py new file mode 100644 index 0000000000000000000000000000000000000000..a99c09a252312fde45504c58824d1c07693c15d4 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/arrayterator.py @@ -0,0 +1,28 @@ + +from __future__ import annotations + +from typing import Any + +import numpy as np + +AR_i8: np.ndarray[Any, np.dtype[np.int_]] = np.arange(10) +ar_iter = np.lib.Arrayterator(AR_i8) + +ar_iter.var +ar_iter.buf_size +ar_iter.start +ar_iter.stop +ar_iter.step +ar_iter.shape +ar_iter.flat + +ar_iter.__array__() + +for i in ar_iter: + pass + +ar_iter[0] +ar_iter[...] +ar_iter[:] +ar_iter[0, 0, 0] +ar_iter[..., 0, :] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/bitwise_ops.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/bitwise_ops.py new file mode 100644 index 0000000000000000000000000000000000000000..2d4815b0d94089fa24b7924828b826ad35d75cde --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/bitwise_ops.py @@ -0,0 +1,131 @@ +import numpy as np + +i8 = np.int64(1) +u8 = np.uint64(1) + +i4 = np.int32(1) +u4 = np.uint32(1) + +b_ = np.bool(1) + +b = bool(1) +i = 1 + +AR = np.array([0, 1, 2], dtype=np.int32) +AR.setflags(write=False) + + +i8 << i8 +i8 >> i8 +i8 | i8 +i8 ^ i8 +i8 & i8 + +i << AR +i >> AR +i | AR +i ^ AR +i & AR + +i8 << AR +i8 >> AR +i8 | AR +i8 ^ AR +i8 & AR + +i4 << i4 +i4 >> i4 +i4 | i4 +i4 ^ i4 +i4 & i4 + +i8 << i4 +i8 >> i4 +i8 | i4 +i8 ^ i4 +i8 & i4 + +i8 << i +i8 >> i +i8 | i +i8 ^ i +i8 & i + +i8 << b_ +i8 >> b_ +i8 | b_ +i8 ^ b_ +i8 & b_ + +i8 << b +i8 >> b +i8 | b +i8 ^ b +i8 & b + +u8 << u8 +u8 >> u8 +u8 | u8 +u8 ^ u8 +u8 & u8 + +u4 << u4 +u4 >> u4 +u4 | u4 +u4 ^ u4 +u4 & u4 + +u4 << i4 +u4 >> i4 +u4 | i4 +u4 ^ i4 +u4 & i4 + +u4 << i +u4 >> i +u4 | i +u4 ^ i +u4 & i + +u8 << b_ +u8 >> b_ +u8 | b_ +u8 ^ b_ +u8 & b_ + +u8 << b +u8 >> b +u8 | b +u8 ^ b +u8 & b + +b_ << b_ +b_ >> b_ +b_ | b_ +b_ ^ b_ +b_ & b_ + +b_ << AR +b_ >> AR +b_ | AR +b_ ^ AR +b_ & AR + +b_ << b +b_ >> b +b_ | b +b_ ^ b +b_ & b + +b_ << i +b_ >> i +b_ | i +b_ ^ i +b_ & i + +~i8 +~i4 +~u8 +~u4 +~b_ +~AR diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/comparisons.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/comparisons.py new file mode 100644 index 0000000000000000000000000000000000000000..b2e52762c7a8e61fbe7d6e526df4dc4ffc6676df --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/comparisons.py @@ -0,0 +1,316 @@ +from __future__ import annotations + +from typing import Any, cast + +import numpy as np + +c16 = np.complex128() +f8 = np.float64() +i8 = np.int64() +u8 = np.uint64() + +c8 = np.complex64() +f4 = np.float32() +i4 = np.int32() +u4 = np.uint32() + +dt = np.datetime64(0, "D") +td = np.timedelta64(0, "D") + +b_ = np.bool() + +b = False +c = complex() +f = 0.0 +i = 0 + +SEQ = (0, 1, 2, 3, 4) + +AR_b: np.ndarray[Any, np.dtype[np.bool]] = np.array([True]) +AR_u: np.ndarray[Any, np.dtype[np.uint32]] = np.array([1], dtype=np.uint32) +AR_i: np.ndarray[Any, np.dtype[np.int_]] = np.array([1]) +AR_f: np.ndarray[Any, np.dtype[np.float64]] = np.array([1.0]) +AR_c: np.ndarray[Any, np.dtype[np.complex128]] = np.array([1.0j]) +AR_S: np.ndarray[Any, np.dtype[np.bytes_]] = np.array([b"a"], "S") +AR_T = cast(np.ndarray[Any, np.dtypes.StringDType], np.array(["a"], "T")) +AR_U: np.ndarray[Any, np.dtype[np.str_]] = np.array(["a"], "U") +AR_m: np.ndarray[Any, np.dtype[np.timedelta64]] = np.array([np.timedelta64("1")]) +AR_M: np.ndarray[Any, np.dtype[np.datetime64]] = np.array([np.datetime64("1")]) +AR_O: np.ndarray[Any, np.dtype[np.object_]] = np.array([1], dtype=object) + +# Arrays + +AR_b > AR_b +AR_b > AR_u +AR_b > AR_i +AR_b > AR_f +AR_b > AR_c + +AR_u > AR_b +AR_u > AR_u +AR_u > AR_i +AR_u > AR_f +AR_u > AR_c + +AR_i > AR_b +AR_i > AR_u +AR_i > AR_i +AR_i > AR_f +AR_i > AR_c + +AR_f > AR_b +AR_f > AR_u +AR_f > AR_i +AR_f > AR_f +AR_f > AR_c + +AR_c > AR_b +AR_c > AR_u +AR_c > AR_i +AR_c > AR_f +AR_c > AR_c + +AR_S > AR_S +AR_S > b"" + +AR_T > AR_T +AR_T > AR_U +AR_T > "" + +AR_U > AR_U +AR_U > AR_T +AR_U > "" + +AR_m > AR_b +AR_m > AR_u +AR_m > AR_i +AR_b > AR_m +AR_u > AR_m +AR_i > AR_m + +AR_M > AR_M + +AR_O > AR_O +1 > AR_O +AR_O > 1 + +# Time structures + +dt > dt + +td > td +td > i +td > i4 +td > i8 +td > AR_i +td > SEQ + +# boolean + +b_ > b +b_ > b_ +b_ > i +b_ > i8 +b_ > i4 +b_ > u8 +b_ > u4 +b_ > f +b_ > f8 +b_ > f4 +b_ > c +b_ > c16 +b_ > c8 +b_ > AR_i +b_ > SEQ + +# Complex + +c16 > c16 +c16 > f8 +c16 > i8 +c16 > c8 +c16 > f4 +c16 > i4 +c16 > b_ +c16 > b +c16 > c +c16 > f +c16 > i +c16 > AR_i +c16 > SEQ + +c16 > c16 +f8 > c16 +i8 > c16 +c8 > c16 +f4 > c16 +i4 > c16 +b_ > c16 +b > c16 +c > c16 +f > c16 +i > c16 +AR_i > c16 +SEQ > c16 + +c8 > c16 +c8 > f8 +c8 > i8 +c8 > c8 +c8 > f4 +c8 > i4 +c8 > b_ +c8 > b +c8 > c +c8 > f +c8 > i +c8 > AR_i +c8 > SEQ + +c16 > c8 +f8 > c8 +i8 > c8 +c8 > c8 +f4 > c8 +i4 > c8 +b_ > c8 +b > c8 +c > c8 +f > c8 +i > c8 +AR_i > c8 +SEQ > c8 + +# Float + +f8 > f8 +f8 > i8 +f8 > f4 +f8 > i4 +f8 > b_ +f8 > b +f8 > c +f8 > f +f8 > i +f8 > AR_i +f8 > SEQ + +f8 > f8 +i8 > f8 +f4 > f8 +i4 > f8 +b_ > f8 +b > f8 +c > f8 +f > f8 +i > f8 +AR_i > f8 +SEQ > f8 + +f4 > f8 +f4 > i8 +f4 > f4 +f4 > i4 +f4 > b_ +f4 > b +f4 > c +f4 > f +f4 > i +f4 > AR_i +f4 > SEQ + +f8 > f4 +i8 > f4 +f4 > f4 +i4 > f4 +b_ > f4 +b > f4 +c > f4 +f > f4 +i > f4 +AR_i > f4 +SEQ > f4 + +# Int + +i8 > i8 +i8 > u8 +i8 > i4 +i8 > u4 +i8 > b_ +i8 > b +i8 > c +i8 > f +i8 > i +i8 > AR_i +i8 > SEQ + +u8 > u8 +u8 > i4 +u8 > u4 +u8 > b_ +u8 > b +u8 > c +u8 > f +u8 > i +u8 > AR_i +u8 > SEQ + +i8 > i8 +u8 > i8 +i4 > i8 +u4 > i8 +b_ > i8 +b > i8 +c > i8 +f > i8 +i > i8 +AR_i > i8 +SEQ > i8 + +u8 > u8 +i4 > u8 +u4 > u8 +b_ > u8 +b > u8 +c > u8 +f > u8 +i > u8 +AR_i > u8 +SEQ > u8 + +i4 > i8 +i4 > i4 +i4 > i +i4 > b_ +i4 > b +i4 > AR_i +i4 > SEQ + +u4 > i8 +u4 > i4 +u4 > u8 +u4 > u4 +u4 > i +u4 > b_ +u4 > b +u4 > AR_i +u4 > SEQ + +i8 > i4 +i4 > i4 +i > i4 +b_ > i4 +b > i4 +AR_i > i4 +SEQ > i4 + +i8 > u4 +i4 > u4 +u8 > u4 +u4 > u4 +b_ > u4 +b > u4 +i > u4 +AR_i > u4 +SEQ > u4 diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/dtype.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/dtype.py new file mode 100644 index 0000000000000000000000000000000000000000..9f11518276c842f2601e3f1420020f00e3b775fb --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/dtype.py @@ -0,0 +1,57 @@ +import numpy as np + +dtype_obj = np.dtype(np.str_) +void_dtype_obj = np.dtype([("f0", np.float64), ("f1", np.float32)]) + +np.dtype(dtype=np.int64) +np.dtype(int) +np.dtype("int") +np.dtype(None) + +np.dtype((int, 2)) +np.dtype((int, (1,))) + +np.dtype({"names": ["a", "b"], "formats": [int, float]}) +np.dtype({"names": ["a"], "formats": [int], "titles": [object]}) +np.dtype({"names": ["a"], "formats": [int], "titles": [object()]}) + +np.dtype([("name", np.str_, 16), ("grades", np.float64, (2,)), ("age", "int32")]) + +np.dtype( + { + "names": ["a", "b"], + "formats": [int, float], + "itemsize": 9, + "aligned": False, + "titles": ["x", "y"], + "offsets": [0, 1], + } +) + +np.dtype((np.float64, float)) + + +class Test: + dtype = np.dtype(float) + + +np.dtype(Test()) + +# Methods and attributes +dtype_obj.base +dtype_obj.subdtype +dtype_obj.newbyteorder() +dtype_obj.type +dtype_obj.name +dtype_obj.names + +dtype_obj * 0 +dtype_obj * 2 + +0 * dtype_obj +2 * dtype_obj + +void_dtype_obj["f0"] +void_dtype_obj[0] +void_dtype_obj[["f0", "f1"]] +void_dtype_obj[["f0"]] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/einsumfunc.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/einsumfunc.py new file mode 100644 index 0000000000000000000000000000000000000000..429764e67eccc7855d363da20d432fdb45e66971 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/einsumfunc.py @@ -0,0 +1,36 @@ +from __future__ import annotations + +from typing import Any + +import numpy as np + +AR_LIKE_b = [True, True, True] +AR_LIKE_u = [np.uint32(1), np.uint32(2), np.uint32(3)] +AR_LIKE_i = [1, 2, 3] +AR_LIKE_f = [1.0, 2.0, 3.0] +AR_LIKE_c = [1j, 2j, 3j] +AR_LIKE_U = ["1", "2", "3"] + +OUT_f: np.ndarray[Any, np.dtype[np.float64]] = np.empty(3, dtype=np.float64) +OUT_c: np.ndarray[Any, np.dtype[np.complex128]] = np.empty(3, dtype=np.complex128) + +np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_b) +np.einsum("i,i->i", AR_LIKE_u, AR_LIKE_u) +np.einsum("i,i->i", AR_LIKE_i, AR_LIKE_i) +np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f) +np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c) +np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_i) +np.einsum("i,i,i,i->i", AR_LIKE_b, AR_LIKE_u, AR_LIKE_i, AR_LIKE_c) + +np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f, dtype="c16") +np.einsum("i,i->i", AR_LIKE_U, AR_LIKE_U, dtype=bool, casting="unsafe") +np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f, out=OUT_c) +np.einsum("i,i->i", AR_LIKE_U, AR_LIKE_U, dtype=int, casting="unsafe", out=OUT_f) + +np.einsum_path("i,i->i", AR_LIKE_b, AR_LIKE_b) +np.einsum_path("i,i->i", AR_LIKE_u, AR_LIKE_u) +np.einsum_path("i,i->i", AR_LIKE_i, AR_LIKE_i) +np.einsum_path("i,i->i", AR_LIKE_f, AR_LIKE_f) +np.einsum_path("i,i->i", AR_LIKE_c, AR_LIKE_c) +np.einsum_path("i,i->i", AR_LIKE_b, AR_LIKE_i) +np.einsum_path("i,i,i,i->i", AR_LIKE_b, AR_LIKE_u, AR_LIKE_i, AR_LIKE_c) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/flatiter.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/flatiter.py new file mode 100644 index 0000000000000000000000000000000000000000..70de3a67917dd8e9f32f4c0dc4f38d1693d96764 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/flatiter.py @@ -0,0 +1,26 @@ +import numpy as np + +a = np.empty((2, 2)).flat + +a.base +a.copy() +a.coords +a.index +iter(a) +next(a) +a[0] +a[...] +a[:] +a.__array__() + +b = np.array([1]).flat +a[b] + +a[0] = "1" +a[:] = "2" +a[...] = "3" +a[[]] = "4" +a[[0]] = "5" +a[[[0]]] = "6" +a[[[[[0]]]]] = "7" +a[b] = "8" diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/fromnumeric.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/fromnumeric.py new file mode 100644 index 0000000000000000000000000000000000000000..7cc2bcfd8b50f235081e737c3420e1db34191637 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/fromnumeric.py @@ -0,0 +1,272 @@ +"""Tests for :mod:`numpy._core.fromnumeric`.""" + +import numpy as np + +A = np.array(True, ndmin=2, dtype=bool) +B = np.array(1.0, ndmin=2, dtype=np.float32) +A.setflags(write=False) +B.setflags(write=False) + +a = np.bool(True) +b = np.float32(1.0) +c = 1.0 +d = np.array(1.0, dtype=np.float32) # writeable + +np.take(a, 0) +np.take(b, 0) +np.take(c, 0) +np.take(A, 0) +np.take(B, 0) +np.take(A, [0]) +np.take(B, [0]) + +np.reshape(a, 1) +np.reshape(b, 1) +np.reshape(c, 1) +np.reshape(A, 1) +np.reshape(B, 1) + +np.choose(a, [True, True]) +np.choose(A, [1.0, 1.0]) + +np.repeat(a, 1) +np.repeat(b, 1) +np.repeat(c, 1) +np.repeat(A, 1) +np.repeat(B, 1) + +np.swapaxes(A, 0, 0) +np.swapaxes(B, 0, 0) + +np.transpose(a) +np.transpose(b) +np.transpose(c) +np.transpose(A) +np.transpose(B) + +np.partition(a, 0, axis=None) +np.partition(b, 0, axis=None) +np.partition(c, 0, axis=None) +np.partition(A, 0) +np.partition(B, 0) + +np.argpartition(a, 0) +np.argpartition(b, 0) +np.argpartition(c, 0) +np.argpartition(A, 0) +np.argpartition(B, 0) + +np.sort(A, 0) +np.sort(B, 0) + +np.argsort(A, 0) +np.argsort(B, 0) + +np.argmax(A) +np.argmax(B) +np.argmax(A, axis=0) +np.argmax(B, axis=0) + +np.argmin(A) +np.argmin(B) +np.argmin(A, axis=0) +np.argmin(B, axis=0) + +np.searchsorted(A[0], 0) +np.searchsorted(B[0], 0) +np.searchsorted(A[0], [0]) +np.searchsorted(B[0], [0]) + +np.resize(a, (5, 5)) +np.resize(b, (5, 5)) +np.resize(c, (5, 5)) +np.resize(A, (5, 5)) +np.resize(B, (5, 5)) + +np.squeeze(a) +np.squeeze(b) +np.squeeze(c) +np.squeeze(A) +np.squeeze(B) + +np.diagonal(A) +np.diagonal(B) + +np.trace(A) +np.trace(B) + +np.ravel(a) +np.ravel(b) +np.ravel(c) +np.ravel(A) +np.ravel(B) + +np.nonzero(A) +np.nonzero(B) + +np.shape(a) +np.shape(b) +np.shape(c) +np.shape(A) +np.shape(B) + +np.compress([True], a) +np.compress([True], b) +np.compress([True], c) +np.compress([True], A) +np.compress([True], B) + +np.clip(a, 0, 1.0) +np.clip(b, -1, 1) +np.clip(a, 0, None) +np.clip(b, None, 1) +np.clip(c, 0, 1) +np.clip(A, 0, 1) +np.clip(B, 0, 1) +np.clip(B, [0, 1], [1, 2]) + +np.sum(a) +np.sum(b) +np.sum(c) +np.sum(A) +np.sum(B) +np.sum(A, axis=0) +np.sum(B, axis=0) + +np.all(a) +np.all(b) +np.all(c) +np.all(A) +np.all(B) +np.all(A, axis=0) +np.all(B, axis=0) +np.all(A, keepdims=True) +np.all(B, keepdims=True) + +np.any(a) +np.any(b) +np.any(c) +np.any(A) +np.any(B) +np.any(A, axis=0) +np.any(B, axis=0) +np.any(A, keepdims=True) +np.any(B, keepdims=True) + +np.cumsum(a) +np.cumsum(b) +np.cumsum(c) +np.cumsum(A) +np.cumsum(B) + +np.cumulative_sum(a) +np.cumulative_sum(b) +np.cumulative_sum(c) +np.cumulative_sum(A, axis=0) +np.cumulative_sum(B, axis=0) + +np.ptp(b) +np.ptp(c) +np.ptp(B) +np.ptp(B, axis=0) +np.ptp(B, keepdims=True) + +np.amax(a) +np.amax(b) +np.amax(c) +np.amax(A) +np.amax(B) +np.amax(A, axis=0) +np.amax(B, axis=0) +np.amax(A, keepdims=True) +np.amax(B, keepdims=True) + +np.amin(a) +np.amin(b) +np.amin(c) +np.amin(A) +np.amin(B) +np.amin(A, axis=0) +np.amin(B, axis=0) +np.amin(A, keepdims=True) +np.amin(B, keepdims=True) + +np.prod(a) +np.prod(b) +np.prod(c) +np.prod(A) +np.prod(B) +np.prod(a, dtype=None) +np.prod(A, dtype=None) +np.prod(A, axis=0) +np.prod(B, axis=0) +np.prod(A, keepdims=True) +np.prod(B, keepdims=True) +np.prod(b, out=d) +np.prod(B, out=d) + +np.cumprod(a) +np.cumprod(b) +np.cumprod(c) +np.cumprod(A) +np.cumprod(B) + +np.cumulative_prod(a) +np.cumulative_prod(b) +np.cumulative_prod(c) +np.cumulative_prod(A, axis=0) +np.cumulative_prod(B, axis=0) + +np.ndim(a) +np.ndim(b) +np.ndim(c) +np.ndim(A) +np.ndim(B) + +np.size(a) +np.size(b) +np.size(c) +np.size(A) +np.size(B) + +np.around(a) +np.around(b) +np.around(c) +np.around(A) +np.around(B) + +np.mean(a) +np.mean(b) +np.mean(c) +np.mean(A) +np.mean(B) +np.mean(A, axis=0) +np.mean(B, axis=0) +np.mean(A, keepdims=True) +np.mean(B, keepdims=True) +np.mean(b, out=d) +np.mean(B, out=d) + +np.std(a) +np.std(b) +np.std(c) +np.std(A) +np.std(B) +np.std(A, axis=0) +np.std(B, axis=0) +np.std(A, keepdims=True) +np.std(B, keepdims=True) +np.std(b, out=d) +np.std(B, out=d) + +np.var(a) +np.var(b) +np.var(c) +np.var(A) +np.var(B) +np.var(A, axis=0) +np.var(B, axis=0) +np.var(A, keepdims=True) +np.var(B, keepdims=True) +np.var(b, out=d) +np.var(B, out=d) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/index_tricks.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/index_tricks.py new file mode 100644 index 0000000000000000000000000000000000000000..ea98156a8f2eacf86f0e4dff14b95588455b8d96 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/index_tricks.py @@ -0,0 +1,62 @@ +from __future__ import annotations + +from typing import Any + +import numpy as np + +AR_LIKE_b = [[True, True], [True, True]] +AR_LIKE_i = [[1, 2], [3, 4]] +AR_LIKE_f = [[1.0, 2.0], [3.0, 4.0]] +AR_LIKE_U = [["1", "2"], ["3", "4"]] + +AR_i8: np.ndarray[Any, np.dtype[np.int64]] = np.array(AR_LIKE_i, dtype=np.int64) + +np.ndenumerate(AR_i8) +np.ndenumerate(AR_LIKE_f) +np.ndenumerate(AR_LIKE_U) + +next(np.ndenumerate(AR_i8)) +next(np.ndenumerate(AR_LIKE_f)) +next(np.ndenumerate(AR_LIKE_U)) + +iter(np.ndenumerate(AR_i8)) +iter(np.ndenumerate(AR_LIKE_f)) +iter(np.ndenumerate(AR_LIKE_U)) + +iter(np.ndindex(1, 2, 3)) +next(np.ndindex(1, 2, 3)) + +np.unravel_index([22, 41, 37], (7, 6)) +np.unravel_index([31, 41, 13], (7, 6), order='F') +np.unravel_index(1621, (6, 7, 8, 9)) + +np.ravel_multi_index(AR_LIKE_i, (7, 6)) +np.ravel_multi_index(AR_LIKE_i, (7, 6), order='F') +np.ravel_multi_index(AR_LIKE_i, (4, 6), mode='clip') +np.ravel_multi_index(AR_LIKE_i, (4, 4), mode=('clip', 'wrap')) +np.ravel_multi_index((3, 1, 4, 1), (6, 7, 8, 9)) + +np.mgrid[1:1:2] +np.mgrid[1:1:2, None:10] + +np.ogrid[1:1:2] +np.ogrid[1:1:2, None:10] + +np.index_exp[0:1] +np.index_exp[0:1, None:3] +np.index_exp[0, 0:1, ..., [0, 1, 3]] + +np.s_[0:1] +np.s_[0:1, None:3] +np.s_[0, 0:1, ..., [0, 1, 3]] + +np.ix_(AR_LIKE_b[0]) +np.ix_(AR_LIKE_i[0], AR_LIKE_f[0]) +np.ix_(AR_i8[0]) + +np.fill_diagonal(AR_i8, 5) + +np.diag_indices(4) +np.diag_indices(2, 3) + +np.diag_indices_from(AR_i8) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/lib_user_array.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/lib_user_array.py new file mode 100644 index 0000000000000000000000000000000000000000..f79dc38af508b43c5d385c67072e31acca418def --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/lib_user_array.py @@ -0,0 +1,22 @@ +"""Based on the `if __name__ == "__main__"` test code in `lib/_user_array_impl.py`.""" + +from __future__ import annotations + +import numpy as np +from numpy.lib.user_array import container # type: ignore[deprecated] + +N = 10_000 +W = H = int(N**0.5) + +a: np.ndarray[tuple[int, int], np.dtype[np.int32]] +ua: container[tuple[int, int], np.dtype[np.int32]] + +a = np.arange(N, dtype=np.int32).reshape(W, H) +ua = container(a) + +ua_small: container[tuple[int, int], np.dtype[np.int32]] = ua[:3, :5] +ua_small[0, 0] = 10 + +ua_bool: container[tuple[int, int], np.dtype[np.bool]] = ua_small > 1 + +# shape: tuple[int, int] = np.shape(ua) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/lib_utils.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/lib_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..f9b3381e13d26adf44130fc62aa8bfaacfe6a658 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/lib_utils.py @@ -0,0 +1,19 @@ +from __future__ import annotations + +from io import StringIO + +import numpy as np +import numpy.lib.array_utils as array_utils + +FILE = StringIO() +AR = np.arange(10, dtype=np.float64) + + +def func(a: int) -> bool: + return True + + +array_utils.byte_bounds(AR) +array_utils.byte_bounds(np.float64()) + +np.info(1, output=FILE) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/lib_version.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/lib_version.py new file mode 100644 index 0000000000000000000000000000000000000000..f3825eca524795f4d9742873a773cd7749636e2a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/lib_version.py @@ -0,0 +1,18 @@ +from numpy.lib import NumpyVersion + +version = NumpyVersion("1.8.0") + +version.vstring +version.version +version.major +version.minor +version.bugfix +version.pre_release +version.is_devversion + +version == version +version != version +version < "1.8.0" +version <= version +version > version +version >= "1.8.0" diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/literal.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/literal.py new file mode 100644 index 0000000000000000000000000000000000000000..f1e0cb2a69d3e60d1afabeab970b156cce1dde58 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/literal.py @@ -0,0 +1,52 @@ +from __future__ import annotations + +from functools import partial +from typing import TYPE_CHECKING, Any + +import pytest + +import numpy as np + +if TYPE_CHECKING: + from collections.abc import Callable + +AR = np.array(0) +AR.setflags(write=False) + +KACF = frozenset({None, "K", "A", "C", "F"}) +ACF = frozenset({None, "A", "C", "F"}) +CF = frozenset({None, "C", "F"}) + +order_list: list[tuple[frozenset[str | None], Callable[..., Any]]] = [ + (KACF, AR.tobytes), + (KACF, partial(AR.astype, int)), + (KACF, AR.copy), + (ACF, partial(AR.reshape, 1)), + (KACF, AR.flatten), + (KACF, AR.ravel), + (KACF, partial(np.array, 1)), + # NOTE: __call__ is needed due to mypy bugs (#17620, #17631) + (KACF, partial(np.ndarray.__call__, 1)), + (CF, partial(np.zeros.__call__, 1)), + (CF, partial(np.ones.__call__, 1)), + (CF, partial(np.empty.__call__, 1)), + (CF, partial(np.full, 1, 1)), + (KACF, partial(np.zeros_like, AR)), + (KACF, partial(np.ones_like, AR)), + (KACF, partial(np.empty_like, AR)), + (KACF, partial(np.full_like, AR, 1)), + (KACF, partial(np.add.__call__, 1, 1)), # i.e. np.ufunc.__call__ + (ACF, partial(np.reshape, AR, 1)), + (KACF, partial(np.ravel, AR)), + (KACF, partial(np.asarray, 1)), + (KACF, partial(np.asanyarray, 1)), +] + +for order_set, func in order_list: + for order in order_set: + func(order=order) + + invalid_orders = KACF - order_set + for order in invalid_orders: + with pytest.raises(ValueError): + func(order=order) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ma.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ma.py new file mode 100644 index 0000000000000000000000000000000000000000..3ccea66861ebd1816dca659456ca246a3536f8d8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ma.py @@ -0,0 +1,199 @@ +import datetime as dt +from typing import Any, TypeAlias, TypeVar, cast + +import numpy as np +import numpy.typing as npt +from numpy._typing import _Shape + +_ScalarT = TypeVar("_ScalarT", bound=np.generic) +MaskedArray: TypeAlias = np.ma.MaskedArray[_Shape, np.dtype[_ScalarT]] + +# mypy: disable-error-code=no-untyped-call + +MAR_b: MaskedArray[np.bool] = np.ma.MaskedArray([True]) +MAR_u: MaskedArray[np.uint32] = np.ma.MaskedArray([1], dtype=np.uint32) +MAR_i: MaskedArray[np.int64] = np.ma.MaskedArray([1]) +MAR_f: MaskedArray[np.float64] = np.ma.MaskedArray([1.0]) +MAR_c: MaskedArray[np.complex128] = np.ma.MaskedArray([1j]) +MAR_td64: MaskedArray[np.timedelta64] = np.ma.MaskedArray([np.timedelta64(1, "D")]) +MAR_dt64: MaskedArray[np.datetime64] = np.ma.MaskedArray([np.datetime64(1, "D")]) +MAR_S: MaskedArray[np.bytes_] = np.ma.MaskedArray([b'foo'], dtype=np.bytes_) +MAR_U: MaskedArray[np.str_] = np.ma.MaskedArray(['foo'], dtype=np.str_) +MAR_T = cast(np.ma.MaskedArray[Any, np.dtypes.StringDType], + np.ma.MaskedArray(["a"], dtype="T")) +MAR_V: MaskedArray[np.void] = np.ma.MaskedArray( + [(1, 1)], + mask=[(False, False)], + dtype=[('a', int), ('b', int)] +) + +AR_b: npt.NDArray[np.bool] = np.array([True, False, True]) + +AR_LIKE_b = [True] +AR_LIKE_u = [np.uint32(1)] +AR_LIKE_i = [1] +AR_LIKE_f = [1.0] +AR_LIKE_c = [1j] +AR_LIKE_m = [np.timedelta64(1, "D")] +AR_LIKE_M = [np.datetime64(1, "D")] + +MAR_f.mask = AR_b +MAR_f.mask = np.False_ + +MAR_i.fill_value = 0 + +MAR_b.flat[MAR_i > 0] = False +MAR_i.flat[:] = 1 +MAR_f.flat[[0]] = AR_LIKE_f +MAR_c.flat[[0, 0]] = [3, 4 + 3j] +MAR_td64.flat[0] = dt.timedelta(1) +MAR_dt64.flat[0] = dt.datetime(2020, 1, 1) + +MAR_b[MAR_i > 0] = False +MAR_i[:] = 1 +MAR_f[[0]] = AR_LIKE_f +MAR_c[[0, 0]] = [3, 4 + 3j] +MAR_td64[0] = dt.timedelta(1) +MAR_dt64[0] = dt.datetime(2020, 1, 1) +MAR_V['a'] = [2] + +# Inplace addition + +MAR_b += AR_LIKE_b + +MAR_u += AR_LIKE_b +MAR_u += AR_LIKE_u + +MAR_i += AR_LIKE_b +MAR_i += 2 +MAR_i += AR_LIKE_i + +MAR_f += AR_LIKE_b +MAR_f += 2 +MAR_f += AR_LIKE_u +MAR_f += AR_LIKE_i +MAR_f += AR_LIKE_f + +MAR_c += AR_LIKE_b +MAR_c += AR_LIKE_u +MAR_c += AR_LIKE_i +MAR_c += AR_LIKE_f +MAR_c += AR_LIKE_c + +MAR_td64 += AR_LIKE_b +MAR_td64 += AR_LIKE_u +MAR_td64 += AR_LIKE_i +MAR_td64 += AR_LIKE_m +MAR_dt64 += AR_LIKE_b +MAR_dt64 += AR_LIKE_u +MAR_dt64 += AR_LIKE_i +MAR_dt64 += AR_LIKE_m + +MAR_S += b'snakes' +MAR_U += 'snakes' +MAR_T += 'snakes' + +# Inplace subtraction + +MAR_u -= AR_LIKE_b +MAR_u -= AR_LIKE_u + +MAR_i -= AR_LIKE_b +MAR_i -= AR_LIKE_i + +MAR_f -= AR_LIKE_b +MAR_f -= AR_LIKE_u +MAR_f -= AR_LIKE_i +MAR_f -= AR_LIKE_f + +MAR_c -= AR_LIKE_b +MAR_c -= AR_LIKE_u +MAR_c -= AR_LIKE_i +MAR_c -= AR_LIKE_f +MAR_c -= AR_LIKE_c + +MAR_td64 -= AR_LIKE_b +MAR_td64 -= AR_LIKE_u +MAR_td64 -= AR_LIKE_i +MAR_td64 -= AR_LIKE_m +MAR_dt64 -= AR_LIKE_b +MAR_dt64 -= AR_LIKE_u +MAR_dt64 -= AR_LIKE_i +MAR_dt64 -= AR_LIKE_m + +# Inplace floor division + +MAR_f //= AR_LIKE_b +MAR_f //= 2 +MAR_f //= AR_LIKE_u +MAR_f //= AR_LIKE_i +MAR_f //= AR_LIKE_f + +MAR_td64 //= AR_LIKE_i + +# Inplace true division + +MAR_f /= AR_LIKE_b +MAR_f /= 2 +MAR_f /= AR_LIKE_u +MAR_f /= AR_LIKE_i +MAR_f /= AR_LIKE_f + +MAR_c /= AR_LIKE_b +MAR_c /= AR_LIKE_u +MAR_c /= AR_LIKE_i +MAR_c /= AR_LIKE_f +MAR_c /= AR_LIKE_c + +MAR_td64 /= AR_LIKE_i + +# Inplace multiplication + +MAR_b *= AR_LIKE_b + +MAR_u *= AR_LIKE_b +MAR_u *= AR_LIKE_u + +MAR_i *= AR_LIKE_b +MAR_i *= 2 +MAR_i *= AR_LIKE_i + +MAR_f *= AR_LIKE_b +MAR_f *= 2 +MAR_f *= AR_LIKE_u +MAR_f *= AR_LIKE_i +MAR_f *= AR_LIKE_f + +MAR_c *= AR_LIKE_b +MAR_c *= AR_LIKE_u +MAR_c *= AR_LIKE_i +MAR_c *= AR_LIKE_f +MAR_c *= AR_LIKE_c + +MAR_td64 *= AR_LIKE_b +MAR_td64 *= AR_LIKE_u +MAR_td64 *= AR_LIKE_i +MAR_td64 *= AR_LIKE_f + +MAR_S *= 2 +MAR_U *= 2 +MAR_T *= 2 + +# Inplace power + +MAR_u **= AR_LIKE_b +MAR_u **= AR_LIKE_u + +MAR_i **= AR_LIKE_b +MAR_i **= AR_LIKE_i + +MAR_f **= AR_LIKE_b +MAR_f **= AR_LIKE_u +MAR_f **= AR_LIKE_i +MAR_f **= AR_LIKE_f + +MAR_c **= AR_LIKE_b +MAR_c **= AR_LIKE_u +MAR_c **= AR_LIKE_i +MAR_c **= AR_LIKE_f +MAR_c **= AR_LIKE_c diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/mod.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/mod.py new file mode 100644 index 0000000000000000000000000000000000000000..464326486fa296374e722e3fc77242d67f7a8dac --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/mod.py @@ -0,0 +1,149 @@ +import numpy as np + +f8 = np.float64(1) +i8 = np.int64(1) +u8 = np.uint64(1) + +f4 = np.float32(1) +i4 = np.int32(1) +u4 = np.uint32(1) + +td = np.timedelta64(1, "D") +b_ = np.bool(1) + +b = bool(1) +f = float(1) +i = 1 + +AR = np.array([1], dtype=np.bool) +AR.setflags(write=False) + +AR2 = np.array([1], dtype=np.timedelta64) +AR2.setflags(write=False) + +# Time structures + +td % td +td % AR2 +AR2 % td + +divmod(td, td) +divmod(td, AR2) +divmod(AR2, td) + +# Bool + +b_ % b +b_ % i +b_ % f +b_ % b_ +b_ % i8 +b_ % u8 +b_ % f8 +b_ % AR + +divmod(b_, b) +divmod(b_, i) +divmod(b_, f) +divmod(b_, b_) +divmod(b_, i8) +divmod(b_, u8) +divmod(b_, f8) +divmod(b_, AR) + +b % b_ +i % b_ +f % b_ +b_ % b_ +i8 % b_ +u8 % b_ +f8 % b_ +AR % b_ + +divmod(b, b_) +divmod(i, b_) +divmod(f, b_) +divmod(b_, b_) +divmod(i8, b_) +divmod(u8, b_) +divmod(f8, b_) +divmod(AR, b_) + +# int + +i8 % b +i8 % i +i8 % f +i8 % i8 +i8 % f8 +i4 % i8 +i4 % f8 +i4 % i4 +i4 % f4 +i8 % AR + +divmod(i8, b) +divmod(i8, i) +divmod(i8, f) +divmod(i8, i8) +divmod(i8, f8) +divmod(i8, i4) +divmod(i8, f4) +divmod(i4, i4) +divmod(i4, f4) +divmod(i8, AR) + +b % i8 +i % i8 +f % i8 +i8 % i8 +f8 % i8 +i8 % i4 +f8 % i4 +i4 % i4 +f4 % i4 +AR % i8 + +divmod(b, i8) +divmod(i, i8) +divmod(f, i8) +divmod(i8, i8) +divmod(f8, i8) +divmod(i4, i8) +divmod(f4, i8) +divmod(i4, i4) +divmod(f4, i4) +divmod(AR, i8) + +# float + +f8 % b +f8 % i +f8 % f +i8 % f4 +f4 % f4 +f8 % AR + +divmod(f8, b) +divmod(f8, i) +divmod(f8, f) +divmod(f8, f8) +divmod(f8, f4) +divmod(f4, f4) +divmod(f8, AR) + +b % f8 +i % f8 +f % f8 +f8 % f8 +f8 % f8 +f4 % f4 +AR % f8 + +divmod(b, f8) +divmod(i, f8) +divmod(f, f8) +divmod(f8, f8) +divmod(f4, f8) +divmod(f4, f4) +divmod(AR, f8) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/modules.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/modules.py new file mode 100644 index 0000000000000000000000000000000000000000..0c2fd4b7e7c3a2d0ed1be39928edf5b2d591e16c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/modules.py @@ -0,0 +1,45 @@ +import numpy as np +from numpy import f2py + +np.char +np.ctypeslib +np.emath +np.fft +np.lib +np.linalg +np.ma +np.matrixlib +np.polynomial +np.random +np.rec +np.strings +np.testing +np.version + +np.lib.format +np.lib.mixins +np.lib.scimath +np.lib.stride_tricks +np.lib.array_utils +np.ma.extras +np.polynomial.chebyshev +np.polynomial.hermite +np.polynomial.hermite_e +np.polynomial.laguerre +np.polynomial.legendre +np.polynomial.polynomial + +np.__path__ +np.__version__ + +np.__all__ +np.char.__all__ +np.ctypeslib.__all__ +np.emath.__all__ +np.lib.__all__ +np.ma.__all__ +np.random.__all__ +np.rec.__all__ +np.strings.__all__ +np.testing.__all__ +f2py.__all__ diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/multiarray.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/multiarray.py new file mode 100644 index 0000000000000000000000000000000000000000..3a505590b5d3818da89aecba3fdf10eecd45004d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/multiarray.py @@ -0,0 +1,77 @@ +import numpy as np +import numpy.typing as npt + +AR_f8: npt.NDArray[np.float64] = np.array([1.0]) +AR_i4 = np.array([1], dtype=np.int32) +AR_u1 = np.array([1], dtype=np.uint8) + +AR_LIKE_f = [1.5] +AR_LIKE_i = [1] + +b_f8 = np.broadcast(AR_f8) +b_i4_f8_f8 = np.broadcast(AR_i4, AR_f8, AR_f8) + +next(b_f8) +b_f8.reset() +b_f8.index +b_f8.iters +b_f8.nd +b_f8.ndim +b_f8.numiter +b_f8.shape +b_f8.size + +next(b_i4_f8_f8) +b_i4_f8_f8.reset() +b_i4_f8_f8.ndim +b_i4_f8_f8.index +b_i4_f8_f8.iters +b_i4_f8_f8.nd +b_i4_f8_f8.numiter +b_i4_f8_f8.shape +b_i4_f8_f8.size + +np.inner(AR_f8, AR_i4) + +np.where([True, True, False]) +np.where([True, True, False], 1, 0) + +np.lexsort([0, 1, 2]) + +np.can_cast(np.dtype("i8"), int) +np.can_cast(AR_f8, "f8") +np.can_cast(AR_f8, np.complex128, casting="unsafe") + +np.min_scalar_type([1]) +np.min_scalar_type(AR_f8) + +np.result_type(int, AR_i4) +np.result_type(AR_f8, AR_u1) +np.result_type(AR_f8, np.complex128) + +np.dot(AR_LIKE_f, AR_i4) +np.dot(AR_u1, 1) +np.dot(1.5j, 1) +np.dot(AR_u1, 1, out=AR_f8) + +np.vdot(AR_LIKE_f, AR_i4) +np.vdot(AR_u1, 1) +np.vdot(1.5j, 1) + +np.bincount(AR_i4) + +np.copyto(AR_f8, [1.6]) + +np.putmask(AR_f8, [True], 1.5) + +np.packbits(AR_i4) +np.packbits(AR_u1) + +np.unpackbits(AR_u1) + +np.shares_memory(1, 2) +np.shares_memory(AR_f8, AR_f8, max_work=-1) + +np.may_share_memory(1, 2) +np.may_share_memory(AR_f8, AR_f8, max_work=0) +np.may_share_memory(AR_f8, AR_f8, max_work=-1) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ndarray_conversion.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ndarray_conversion.py new file mode 100644 index 0000000000000000000000000000000000000000..a4e0bcf34bdd41bc936ee5b38ff58807e471533f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ndarray_conversion.py @@ -0,0 +1,81 @@ +import os +import tempfile + +import numpy as np + +nd = np.array([[1, 2], [3, 4]]) +scalar_array = np.array(1) + +# item +scalar_array.item() +nd.item(1) +nd.item(0, 1) +nd.item((0, 1)) + +# tobytes +nd.tobytes() +nd.tobytes("C") +nd.tobytes(None) + +# tofile +if os.name != "nt": + with tempfile.NamedTemporaryFile(suffix=".txt") as tmp: + nd.tofile(tmp.name) + nd.tofile(tmp.name, "") + nd.tofile(tmp.name, sep="") + + nd.tofile(tmp.name, "", "%s") + nd.tofile(tmp.name, format="%s") + + nd.tofile(tmp) + +# dump is pretty simple +# dumps is pretty simple + +# astype +nd.astype("float") +nd.astype(float) + +nd.astype(float, "K") +nd.astype(float, order="K") + +nd.astype(float, "K", "unsafe") +nd.astype(float, casting="unsafe") + +nd.astype(float, "K", "unsafe", True) +nd.astype(float, subok=True) + +nd.astype(float, "K", "unsafe", True, True) +nd.astype(float, copy=True) + +# byteswap +nd.byteswap() +nd.byteswap(True) + +# copy +nd.copy() +nd.copy("C") + +# view +nd.view() +nd.view(np.int64) +nd.view(dtype=np.int64) +nd.view(np.int64, np.matrix) +nd.view(type=np.matrix) + +# getfield +complex_array = np.array([[1 + 1j, 0], [0, 1 - 1j]], dtype=np.complex128) + +complex_array.getfield("float") +complex_array.getfield(float) + +complex_array.getfield("float", 8) +complex_array.getfield(float, offset=8) + +# setflags +nd.setflags() +nd.setflags(write=True) +nd.setflags(write=True, align=True) +nd.setflags(write=True, align=True, uic=False) + +# fill is pretty simple diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ndarray_misc.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ndarray_misc.py new file mode 100644 index 0000000000000000000000000000000000000000..3437338ec7d1dafafed79278cffb642cdb1c2c2f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ndarray_misc.py @@ -0,0 +1,199 @@ +""" +Tests for miscellaneous (non-magic) ``np.ndarray``/``np.generic`` methods. + +More extensive tests are performed for the methods' +function-based counterpart in `../from_numeric.py`. + +""" + +from __future__ import annotations + +import operator +from collections.abc import Hashable +from typing import Any, cast + +import numpy as np +import numpy.typing as npt + + +class SubClass(npt.NDArray[np.float64]): ... +class IntSubClass(npt.NDArray[np.intp]): ... + + +i4 = np.int32(1) +A: np.ndarray[Any, np.dtype[np.int32]] = np.array([[1]], dtype=np.int32) +B0 = np.empty((), dtype=np.int32).view(SubClass) +B1 = np.empty((1,), dtype=np.int32).view(SubClass) +B2 = np.empty((1, 1), dtype=np.int32).view(SubClass) +B_int0: IntSubClass = np.empty((), dtype=np.intp).view(IntSubClass) +C: np.ndarray[Any, np.dtype[np.int32]] = np.array([0, 1, 2], dtype=np.int32) +D = np.ones(3).view(SubClass) + +ctypes_obj = A.ctypes + +i4.all() +A.all() +A.all(axis=0) +A.all(keepdims=True) +A.all(out=B0) + +i4.any() +A.any() +A.any(axis=0) +A.any(keepdims=True) +A.any(out=B0) + +i4.argmax() +A.argmax() +A.argmax(axis=0) +A.argmax(out=B_int0) + +i4.argmin() +A.argmin() +A.argmin(axis=0) +A.argmin(out=B_int0) + +i4.argsort() +i4.argsort(stable=True) +A.argsort() +A.argsort(stable=True) + +A.sort() +A.sort(stable=True) + +i4.choose([()]) +_choices = np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]], dtype=np.int32) +C.choose(_choices) +C.choose(_choices, out=D) + +i4.clip(1) +A.clip(1) +A.clip(None, 1) +A.clip(1, out=B2) +A.clip(None, 1, out=B2) + +i4.compress([1]) +A.compress([1]) +A.compress([1], out=B1) + +i4.conj() +A.conj() +B0.conj() + +i4.conjugate() +A.conjugate() +B0.conjugate() + +i4.cumprod() +A.cumprod() +A.cumprod(out=B1) + +i4.cumsum() +A.cumsum() +A.cumsum(out=B1) + +i4.max() +A.max() +A.max(axis=0) +A.max(keepdims=True) +A.max(out=B0) + +i4.mean() +A.mean() +A.mean(axis=0) +A.mean(keepdims=True) +A.mean(out=B0) + +i4.min() +A.min() +A.min(axis=0) +A.min(keepdims=True) +A.min(out=B0) + +i4.prod() +A.prod() +A.prod(axis=0) +A.prod(keepdims=True) +A.prod(out=B0) + +i4.round() +A.round() +A.round(out=B2) + +i4.repeat(1) +A.repeat(1) +B0.repeat(1) + +i4.std() +A.std() +A.std(axis=0) +A.std(keepdims=True, mean=0.) +A.std(out=B0.astype(np.float64)) + +i4.sum() +A.sum() +A.sum(axis=0) +A.sum(keepdims=True) +A.sum(out=B0) + +i4.take(0) +A.take(0) +A.take([0]) +A.take(0, out=B0) +A.take([0], out=B1) + +i4.var() +A.var() +A.var(axis=0) +A.var(keepdims=True, mean=0.) +A.var(out=B0) + +A.argpartition([0]) + +A.diagonal() + +A.dot(1) +A.dot(1, out=B2) + +A.nonzero() + +C.searchsorted(1) + +A.trace() +A.trace(out=B0) + +void = cast(np.void, np.array(1, dtype=[("f", np.float64)]).take(0)) +void.setfield(10, np.float64) + +A.item(0) +C.item(0) + +A.ravel() +C.ravel() + +A.flatten() +C.flatten() + +A.reshape(1) +C.reshape(3) + +int(np.array(1.0, dtype=np.float64)) +int(np.array("1", dtype=np.str_)) + +float(np.array(1.0, dtype=np.float64)) +float(np.array("1", dtype=np.str_)) + +complex(np.array(1.0, dtype=np.float64)) + +operator.index(np.array(1, dtype=np.int64)) + +# this fails on numpy 2.2.1 +# https://github.com/scipy/scipy/blob/a755ee77ec47a64849abe42c349936475a6c2f24/scipy/io/arff/tests/test_arffread.py#L41-L44 +A_float = np.array([[1, 5], [2, 4], [np.nan, np.nan]]) +A_void: npt.NDArray[np.void] = np.empty(3, [("yop", float), ("yap", float)]) +A_void["yop"] = A_float[:, 0] +A_void["yap"] = A_float[:, 1] + +# regression test for https://github.com/numpy/numpy/issues/30445 +def f(x: np.generic) -> Hashable: + return x diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ndarray_shape_manipulation.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ndarray_shape_manipulation.py new file mode 100644 index 0000000000000000000000000000000000000000..0ca3dff392e12a4122740ade2ceb71b3d6e7bb08 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ndarray_shape_manipulation.py @@ -0,0 +1,47 @@ +import numpy as np + +nd1 = np.array([[1, 2], [3, 4]]) + +# reshape +nd1.reshape(4) +nd1.reshape(2, 2) +nd1.reshape((2, 2)) + +nd1.reshape((2, 2), order="C") +nd1.reshape(4, order="C") + +# resize +nd1.resize() +nd1.resize(4) +nd1.resize(2, 2) +nd1.resize((2, 2)) + +nd1.resize((2, 2), refcheck=True) +nd1.resize(4, refcheck=True) + +nd2 = np.array([[1, 2], [3, 4]]) + +# transpose +nd2.transpose() +nd2.transpose(1, 0) +nd2.transpose((1, 0)) + +# swapaxes +nd2.swapaxes(0, 1) + +# flatten +nd2.flatten() +nd2.flatten("C") + +# ravel +nd2.ravel() +nd2.ravel("C") + +# squeeze +nd2.squeeze() + +nd3 = np.array([[1, 2]]) +nd3.squeeze(0) + +nd4 = np.array([[[1, 2]]]) +nd4.squeeze((0, 1)) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/nditer.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/nditer.py new file mode 100644 index 0000000000000000000000000000000000000000..25a5b44d7aecf6486be76ae0dca0e3e8ef60699b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/nditer.py @@ -0,0 +1,4 @@ +import numpy as np + +arr = np.array([1]) +np.nditer([arr, None]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/numeric.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/numeric.py new file mode 100644 index 0000000000000000000000000000000000000000..825a6dd74f34e33f0a29f7e42b9f48abf6d2d9a7 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/numeric.py @@ -0,0 +1,90 @@ +""" +Tests for :mod:`numpy._core.numeric`. + +Does not include tests which fall under ``array_constructors``. +""" + +from typing import Any + +import numpy as np + + +class SubClass(np.ndarray[tuple[Any, ...], np.dtype[np.float64]]): ... + + +i8 = np.int64(1) + +A = np.arange(27).reshape(3, 3, 3) +B = A.tolist() +C = np.empty((27, 27)).view(SubClass) + +np.count_nonzero(i8) +np.count_nonzero(A) +np.count_nonzero(B) +np.count_nonzero(A, keepdims=True) +np.count_nonzero(A, axis=0) + +np.isfortran(i8) +np.isfortran(A) + +np.argwhere(i8) +np.argwhere(A) + +np.flatnonzero(i8) +np.flatnonzero(A) + +np.correlate(B[0][0], A.ravel(), mode="valid") +np.correlate(A.ravel(), A.ravel(), mode="same") + +np.convolve(B[0][0], A.ravel(), mode="valid") +np.convolve(A.ravel(), A.ravel(), mode="same") + +np.outer(i8, A) +np.outer(B, A) +np.outer(A, A) +np.outer(A, A, out=C) + +np.tensordot(B, A) +np.tensordot(A, A) +np.tensordot(A, A, axes=0) +np.tensordot(A, A, axes=(0, 1)) + +np.isscalar(i8) +np.isscalar(A) +np.isscalar(B) + +np.roll(A, 1) +np.roll(A, (1, 2)) +np.roll(B, 1) + +np.rollaxis(A, 0, 1) + +np.moveaxis(A, 0, 1) +np.moveaxis(A, (0, 1), (1, 2)) + +np.cross(B, A) +np.cross(A, A) + +np.indices([0, 1, 2]) +np.indices([0, 1, 2], sparse=False) +np.indices([0, 1, 2], sparse=True) + +np.binary_repr(1) + +np.base_repr(1) + +np.allclose(i8, A) +np.allclose(B, A) +np.allclose(A, A) + +np.isclose(i8, A) +np.isclose(B, A) +np.isclose(A, A) + +np.array_equal(i8, A) +np.array_equal(B, A) +np.array_equal(A, A) + +np.array_equiv(i8, A) +np.array_equiv(B, A) +np.array_equiv(A, A) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/numerictypes.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/numerictypes.py new file mode 100644 index 0000000000000000000000000000000000000000..24e1a9986d88ab320bdfab54a050ed27aec4d8b5 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/numerictypes.py @@ -0,0 +1,17 @@ +import numpy as np + +np.isdtype(np.float64, (np.int64, np.float64)) +np.isdtype(np.int64, "signed integer") + +np.issubdtype("S1", np.bytes_) +np.issubdtype(np.float64, np.float32) + +np.ScalarType +np.ScalarType[0] +np.ScalarType[3] +np.ScalarType[8] +np.ScalarType[10] + +np.typecodes["Character"] +np.typecodes["Complex"] +np.typecodes["All"] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/random.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/random.py new file mode 100644 index 0000000000000000000000000000000000000000..fd07e378e553015d0432fbec3db43f5342e5915e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/random.py @@ -0,0 +1,1498 @@ +from __future__ import annotations + +from typing import Any + +import numpy as np + +SEED_NONE = None +SEED_INT = 4579435749574957634658964293569 +SEED_ARR: np.ndarray[Any, np.dtype[np.int64]] = np.array([1, 2, 3, 4], dtype=np.int64) +SEED_ARRLIKE: list[int] = [1, 2, 3, 4] +SEED_SEED_SEQ: np.random.SeedSequence = np.random.SeedSequence(0) +SEED_MT19937: np.random.MT19937 = np.random.MT19937(0) +SEED_PCG64: np.random.PCG64 = np.random.PCG64(0) +SEED_PHILOX: np.random.Philox = np.random.Philox(0) +SEED_SFC64: np.random.SFC64 = np.random.SFC64(0) + +# default rng +np.random.default_rng() +np.random.default_rng(SEED_NONE) +np.random.default_rng(SEED_INT) +np.random.default_rng(SEED_ARR) +np.random.default_rng(SEED_ARRLIKE) +np.random.default_rng(SEED_SEED_SEQ) +np.random.default_rng(SEED_MT19937) +np.random.default_rng(SEED_PCG64) +np.random.default_rng(SEED_PHILOX) +np.random.default_rng(SEED_SFC64) + +# Seed Sequence +np.random.SeedSequence(SEED_NONE) +np.random.SeedSequence(SEED_INT) +np.random.SeedSequence(SEED_ARR) +np.random.SeedSequence(SEED_ARRLIKE) + +# Bit Generators +np.random.MT19937(SEED_NONE) +np.random.MT19937(SEED_INT) +np.random.MT19937(SEED_ARR) +np.random.MT19937(SEED_ARRLIKE) +np.random.MT19937(SEED_SEED_SEQ) + +np.random.PCG64(SEED_NONE) +np.random.PCG64(SEED_INT) +np.random.PCG64(SEED_ARR) +np.random.PCG64(SEED_ARRLIKE) +np.random.PCG64(SEED_SEED_SEQ) + +np.random.Philox(SEED_NONE) +np.random.Philox(SEED_INT) +np.random.Philox(SEED_ARR) +np.random.Philox(SEED_ARRLIKE) +np.random.Philox(SEED_SEED_SEQ) + +np.random.SFC64(SEED_NONE) +np.random.SFC64(SEED_INT) +np.random.SFC64(SEED_ARR) +np.random.SFC64(SEED_ARRLIKE) +np.random.SFC64(SEED_SEED_SEQ) + +seed_seq: np.random.bit_generator.SeedSequence = np.random.SeedSequence(SEED_NONE) +seed_seq.spawn(10) +seed_seq.generate_state(3) +seed_seq.generate_state(3, "u4") +seed_seq.generate_state(3, "uint32") +seed_seq.generate_state(3, "u8") +seed_seq.generate_state(3, "uint64") +seed_seq.generate_state(3, np.uint32) +seed_seq.generate_state(3, np.uint64) + + +def_gen: np.random.Generator = np.random.default_rng() + +D_arr_0p1: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.1]) +D_arr_0p5: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.5]) +D_arr_0p9: np.ndarray[Any, np.dtype[np.float64]] = np.array([0.9]) +D_arr_1p5: np.ndarray[Any, np.dtype[np.float64]] = np.array([1.5]) +I_arr_10: np.ndarray[Any, np.dtype[np.int_]] = np.array([10], dtype=np.int_) +I_arr_20: np.ndarray[Any, np.dtype[np.int_]] = np.array([20], dtype=np.int_) +D_arr_like_0p1: list[float] = [0.1] +D_arr_like_0p5: list[float] = [0.5] +D_arr_like_0p9: list[float] = [0.9] +D_arr_like_1p5: list[float] = [1.5] +I_arr_like_10: list[int] = [10] +I_arr_like_20: list[int] = [20] +D_2D_like: list[list[float]] = [[1, 2], [2, 3], [3, 4], [4, 5.1]] +D_2D: np.ndarray[Any, np.dtype[np.float64]] = np.array(D_2D_like) + +S_out: np.ndarray[Any, np.dtype[np.float32]] = np.empty(1, dtype=np.float32) +D_out: np.ndarray[Any, np.dtype[np.float64]] = np.empty(1) + +def_gen.standard_normal() +def_gen.standard_normal(dtype=np.float32) +def_gen.standard_normal(dtype="float32") +def_gen.standard_normal(dtype="double") +def_gen.standard_normal(dtype=np.float64) +def_gen.standard_normal(size=None) +def_gen.standard_normal(size=1) +def_gen.standard_normal(size=1, dtype=np.float32) +def_gen.standard_normal(size=1, dtype="f4") +def_gen.standard_normal(size=1, dtype="float32", out=S_out) +def_gen.standard_normal(dtype=np.float32, out=S_out) +def_gen.standard_normal(size=1, dtype=np.float64) +def_gen.standard_normal(size=1, dtype="float64") +def_gen.standard_normal(size=1, dtype="f8") +def_gen.standard_normal(out=D_out) +def_gen.standard_normal(size=1, dtype="float64") +def_gen.standard_normal(size=1, dtype="float64", out=D_out) + +def_gen.random() +def_gen.random(dtype=np.float32) +def_gen.random(dtype="float32") +def_gen.random(dtype="double") +def_gen.random(dtype=np.float64) +def_gen.random(size=None) +def_gen.random(size=1) +def_gen.random(size=1, dtype=np.float32) +def_gen.random(size=1, dtype="f4") +def_gen.random(size=1, dtype="float32", out=S_out) +def_gen.random(dtype=np.float32, out=S_out) +def_gen.random(size=1, dtype=np.float64) +def_gen.random(size=1, dtype="float64") +def_gen.random(size=1, dtype="f8") +def_gen.random(out=D_out) +def_gen.random(size=1, dtype="float64") +def_gen.random(size=1, dtype="float64", out=D_out) + +def_gen.standard_cauchy() +def_gen.standard_cauchy(size=None) +def_gen.standard_cauchy(size=1) + +def_gen.standard_exponential() +def_gen.standard_exponential(method="inv") +def_gen.standard_exponential(dtype=np.float32) +def_gen.standard_exponential(dtype="float32") +def_gen.standard_exponential(dtype="double") +def_gen.standard_exponential(dtype=np.float64) +def_gen.standard_exponential(size=None) +def_gen.standard_exponential(size=None, method="inv") +def_gen.standard_exponential(size=1, method="inv") +def_gen.standard_exponential(size=1, dtype=np.float32) +def_gen.standard_exponential(size=1, dtype="f4", method="inv") +def_gen.standard_exponential(size=1, dtype="float32", out=S_out) +def_gen.standard_exponential(dtype=np.float32, out=S_out) +def_gen.standard_exponential(size=1, dtype=np.float64, method="inv") +def_gen.standard_exponential(size=1, dtype="float64") +def_gen.standard_exponential(size=1, dtype="f8") +def_gen.standard_exponential(out=D_out) +def_gen.standard_exponential(size=1, dtype="float64") +def_gen.standard_exponential(size=1, dtype="float64", out=D_out) + +def_gen.zipf(1.5) +def_gen.zipf(1.5, size=None) +def_gen.zipf(1.5, size=1) +def_gen.zipf(D_arr_1p5) +def_gen.zipf(D_arr_1p5, size=1) +def_gen.zipf(D_arr_like_1p5) +def_gen.zipf(D_arr_like_1p5, size=1) + +def_gen.weibull(0.5) +def_gen.weibull(0.5, size=None) +def_gen.weibull(0.5, size=1) +def_gen.weibull(D_arr_0p5) +def_gen.weibull(D_arr_0p5, size=1) +def_gen.weibull(D_arr_like_0p5) +def_gen.weibull(D_arr_like_0p5, size=1) + +def_gen.standard_t(0.5) +def_gen.standard_t(0.5, size=None) +def_gen.standard_t(0.5, size=1) +def_gen.standard_t(D_arr_0p5) +def_gen.standard_t(D_arr_0p5, size=1) +def_gen.standard_t(D_arr_like_0p5) +def_gen.standard_t(D_arr_like_0p5, size=1) + +def_gen.poisson(0.5) +def_gen.poisson(0.5, size=None) +def_gen.poisson(0.5, size=1) +def_gen.poisson(D_arr_0p5) +def_gen.poisson(D_arr_0p5, size=1) +def_gen.poisson(D_arr_like_0p5) +def_gen.poisson(D_arr_like_0p5, size=1) + +def_gen.power(0.5) +def_gen.power(0.5, size=None) +def_gen.power(0.5, size=1) +def_gen.power(D_arr_0p5) +def_gen.power(D_arr_0p5, size=1) +def_gen.power(D_arr_like_0p5) +def_gen.power(D_arr_like_0p5, size=1) + +def_gen.pareto(0.5) +def_gen.pareto(0.5, size=None) +def_gen.pareto(0.5, size=1) +def_gen.pareto(D_arr_0p5) +def_gen.pareto(D_arr_0p5, size=1) +def_gen.pareto(D_arr_like_0p5) +def_gen.pareto(D_arr_like_0p5, size=1) + +def_gen.chisquare(0.5) +def_gen.chisquare(0.5, size=None) +def_gen.chisquare(0.5, size=1) +def_gen.chisquare(D_arr_0p5) +def_gen.chisquare(D_arr_0p5, size=1) +def_gen.chisquare(D_arr_like_0p5) +def_gen.chisquare(D_arr_like_0p5, size=1) + +def_gen.exponential(0.5) +def_gen.exponential(0.5, size=None) +def_gen.exponential(0.5, size=1) +def_gen.exponential(D_arr_0p5) +def_gen.exponential(D_arr_0p5, size=1) +def_gen.exponential(D_arr_like_0p5) +def_gen.exponential(D_arr_like_0p5, size=1) + +def_gen.geometric(0.5) +def_gen.geometric(0.5, size=None) +def_gen.geometric(0.5, size=1) +def_gen.geometric(D_arr_0p5) +def_gen.geometric(D_arr_0p5, size=1) +def_gen.geometric(D_arr_like_0p5) +def_gen.geometric(D_arr_like_0p5, size=1) + +def_gen.logseries(0.5) +def_gen.logseries(0.5, size=None) +def_gen.logseries(0.5, size=1) +def_gen.logseries(D_arr_0p5) +def_gen.logseries(D_arr_0p5, size=1) +def_gen.logseries(D_arr_like_0p5) +def_gen.logseries(D_arr_like_0p5, size=1) + +def_gen.rayleigh(0.5) +def_gen.rayleigh(0.5, size=None) +def_gen.rayleigh(0.5, size=1) +def_gen.rayleigh(D_arr_0p5) +def_gen.rayleigh(D_arr_0p5, size=1) +def_gen.rayleigh(D_arr_like_0p5) +def_gen.rayleigh(D_arr_like_0p5, size=1) + +def_gen.standard_gamma(0.5) +def_gen.standard_gamma(0.5, size=None) +def_gen.standard_gamma(0.5, dtype="float32") +def_gen.standard_gamma(0.5, size=None, dtype="float32") +def_gen.standard_gamma(0.5, size=1) +def_gen.standard_gamma(D_arr_0p5) +def_gen.standard_gamma(D_arr_0p5, dtype="f4") +def_gen.standard_gamma(0.5, size=1, dtype="float32", out=S_out) +def_gen.standard_gamma(D_arr_0p5, dtype=np.float32, out=S_out) +def_gen.standard_gamma(D_arr_0p5, size=1) +def_gen.standard_gamma(D_arr_like_0p5) +def_gen.standard_gamma(D_arr_like_0p5, size=1) +def_gen.standard_gamma(0.5, out=D_out) +def_gen.standard_gamma(D_arr_like_0p5, out=D_out) +def_gen.standard_gamma(D_arr_like_0p5, size=1) +def_gen.standard_gamma(D_arr_like_0p5, size=1, out=D_out, dtype=np.float64) + +def_gen.vonmises(0.5, 0.5) +def_gen.vonmises(0.5, 0.5, size=None) +def_gen.vonmises(0.5, 0.5, size=1) +def_gen.vonmises(D_arr_0p5, 0.5) +def_gen.vonmises(0.5, D_arr_0p5) +def_gen.vonmises(D_arr_0p5, 0.5, size=1) +def_gen.vonmises(0.5, D_arr_0p5, size=1) +def_gen.vonmises(D_arr_like_0p5, 0.5) +def_gen.vonmises(0.5, D_arr_like_0p5) +def_gen.vonmises(D_arr_0p5, D_arr_0p5) +def_gen.vonmises(D_arr_like_0p5, D_arr_like_0p5) +def_gen.vonmises(D_arr_0p5, D_arr_0p5, size=1) +def_gen.vonmises(D_arr_like_0p5, D_arr_like_0p5, size=1) + +def_gen.wald(0.5, 0.5) +def_gen.wald(0.5, 0.5, size=None) +def_gen.wald(0.5, 0.5, size=1) +def_gen.wald(D_arr_0p5, 0.5) +def_gen.wald(0.5, D_arr_0p5) +def_gen.wald(D_arr_0p5, 0.5, size=1) +def_gen.wald(0.5, D_arr_0p5, size=1) +def_gen.wald(D_arr_like_0p5, 0.5) +def_gen.wald(0.5, D_arr_like_0p5) +def_gen.wald(D_arr_0p5, D_arr_0p5) +def_gen.wald(D_arr_like_0p5, D_arr_like_0p5) +def_gen.wald(D_arr_0p5, D_arr_0p5, size=1) +def_gen.wald(D_arr_like_0p5, D_arr_like_0p5, size=1) + +def_gen.uniform(0.5, 0.5) +def_gen.uniform(0.5, 0.5, size=None) +def_gen.uniform(0.5, 0.5, size=1) +def_gen.uniform(D_arr_0p5, 0.5) +def_gen.uniform(0.5, D_arr_0p5) +def_gen.uniform(D_arr_0p5, 0.5, size=1) +def_gen.uniform(0.5, D_arr_0p5, size=1) +def_gen.uniform(D_arr_like_0p5, 0.5) +def_gen.uniform(0.5, D_arr_like_0p5) +def_gen.uniform(D_arr_0p5, D_arr_0p5) +def_gen.uniform(D_arr_like_0p5, D_arr_like_0p5) +def_gen.uniform(D_arr_0p5, D_arr_0p5, size=1) +def_gen.uniform(D_arr_like_0p5, D_arr_like_0p5, size=1) + +def_gen.beta(0.5, 0.5) +def_gen.beta(0.5, 0.5, size=None) +def_gen.beta(0.5, 0.5, size=1) +def_gen.beta(D_arr_0p5, 0.5) +def_gen.beta(0.5, D_arr_0p5) +def_gen.beta(D_arr_0p5, 0.5, size=1) +def_gen.beta(0.5, D_arr_0p5, size=1) +def_gen.beta(D_arr_like_0p5, 0.5) +def_gen.beta(0.5, D_arr_like_0p5) +def_gen.beta(D_arr_0p5, D_arr_0p5) +def_gen.beta(D_arr_like_0p5, D_arr_like_0p5) +def_gen.beta(D_arr_0p5, D_arr_0p5, size=1) +def_gen.beta(D_arr_like_0p5, D_arr_like_0p5, size=1) + +def_gen.f(0.5, 0.5) +def_gen.f(0.5, 0.5, size=None) +def_gen.f(0.5, 0.5, size=1) +def_gen.f(D_arr_0p5, 0.5) +def_gen.f(0.5, D_arr_0p5) +def_gen.f(D_arr_0p5, 0.5, size=1) +def_gen.f(0.5, D_arr_0p5, size=1) +def_gen.f(D_arr_like_0p5, 0.5) +def_gen.f(0.5, D_arr_like_0p5) +def_gen.f(D_arr_0p5, D_arr_0p5) +def_gen.f(D_arr_like_0p5, D_arr_like_0p5) +def_gen.f(D_arr_0p5, D_arr_0p5, size=1) +def_gen.f(D_arr_like_0p5, D_arr_like_0p5, size=1) + +def_gen.gamma(0.5, 0.5) +def_gen.gamma(0.5, 0.5, size=None) +def_gen.gamma(0.5, 0.5, size=1) +def_gen.gamma(D_arr_0p5, 0.5) +def_gen.gamma(0.5, D_arr_0p5) +def_gen.gamma(D_arr_0p5, 0.5, size=1) +def_gen.gamma(0.5, D_arr_0p5, size=1) +def_gen.gamma(D_arr_like_0p5, 0.5) +def_gen.gamma(0.5, D_arr_like_0p5) +def_gen.gamma(D_arr_0p5, D_arr_0p5) +def_gen.gamma(D_arr_like_0p5, D_arr_like_0p5) +def_gen.gamma(D_arr_0p5, D_arr_0p5, size=1) +def_gen.gamma(D_arr_like_0p5, D_arr_like_0p5, size=1) + +def_gen.gumbel(0.5, 0.5) +def_gen.gumbel(0.5, 0.5, size=None) +def_gen.gumbel(0.5, 0.5, size=1) +def_gen.gumbel(D_arr_0p5, 0.5) +def_gen.gumbel(0.5, D_arr_0p5) +def_gen.gumbel(D_arr_0p5, 0.5, size=1) +def_gen.gumbel(0.5, D_arr_0p5, size=1) +def_gen.gumbel(D_arr_like_0p5, 0.5) +def_gen.gumbel(0.5, D_arr_like_0p5) +def_gen.gumbel(D_arr_0p5, D_arr_0p5) +def_gen.gumbel(D_arr_like_0p5, D_arr_like_0p5) +def_gen.gumbel(D_arr_0p5, D_arr_0p5, size=1) +def_gen.gumbel(D_arr_like_0p5, D_arr_like_0p5, size=1) + +def_gen.laplace(0.5, 0.5) +def_gen.laplace(0.5, 0.5, size=None) +def_gen.laplace(0.5, 0.5, size=1) +def_gen.laplace(D_arr_0p5, 0.5) +def_gen.laplace(0.5, D_arr_0p5) +def_gen.laplace(D_arr_0p5, 0.5, size=1) +def_gen.laplace(0.5, D_arr_0p5, size=1) +def_gen.laplace(D_arr_like_0p5, 0.5) +def_gen.laplace(0.5, D_arr_like_0p5) +def_gen.laplace(D_arr_0p5, D_arr_0p5) +def_gen.laplace(D_arr_like_0p5, D_arr_like_0p5) +def_gen.laplace(D_arr_0p5, D_arr_0p5, size=1) +def_gen.laplace(D_arr_like_0p5, D_arr_like_0p5, size=1) + +def_gen.logistic(0.5, 0.5) +def_gen.logistic(0.5, 0.5, size=None) +def_gen.logistic(0.5, 0.5, size=1) +def_gen.logistic(D_arr_0p5, 0.5) +def_gen.logistic(0.5, D_arr_0p5) +def_gen.logistic(D_arr_0p5, 0.5, size=1) +def_gen.logistic(0.5, D_arr_0p5, size=1) +def_gen.logistic(D_arr_like_0p5, 0.5) +def_gen.logistic(0.5, D_arr_like_0p5) +def_gen.logistic(D_arr_0p5, D_arr_0p5) +def_gen.logistic(D_arr_like_0p5, D_arr_like_0p5) +def_gen.logistic(D_arr_0p5, D_arr_0p5, size=1) +def_gen.logistic(D_arr_like_0p5, D_arr_like_0p5, size=1) + +def_gen.lognormal(0.5, 0.5) +def_gen.lognormal(0.5, 0.5, size=None) +def_gen.lognormal(0.5, 0.5, size=1) +def_gen.lognormal(D_arr_0p5, 0.5) +def_gen.lognormal(0.5, D_arr_0p5) +def_gen.lognormal(D_arr_0p5, 0.5, size=1) +def_gen.lognormal(0.5, D_arr_0p5, size=1) +def_gen.lognormal(D_arr_like_0p5, 0.5) +def_gen.lognormal(0.5, D_arr_like_0p5) +def_gen.lognormal(D_arr_0p5, D_arr_0p5) +def_gen.lognormal(D_arr_like_0p5, D_arr_like_0p5) +def_gen.lognormal(D_arr_0p5, D_arr_0p5, size=1) +def_gen.lognormal(D_arr_like_0p5, D_arr_like_0p5, size=1) + +def_gen.noncentral_chisquare(0.5, 0.5) +def_gen.noncentral_chisquare(0.5, 0.5, size=None) +def_gen.noncentral_chisquare(0.5, 0.5, size=1) +def_gen.noncentral_chisquare(D_arr_0p5, 0.5) +def_gen.noncentral_chisquare(0.5, D_arr_0p5) +def_gen.noncentral_chisquare(D_arr_0p5, 0.5, size=1) +def_gen.noncentral_chisquare(0.5, D_arr_0p5, size=1) +def_gen.noncentral_chisquare(D_arr_like_0p5, 0.5) +def_gen.noncentral_chisquare(0.5, D_arr_like_0p5) +def_gen.noncentral_chisquare(D_arr_0p5, D_arr_0p5) +def_gen.noncentral_chisquare(D_arr_like_0p5, D_arr_like_0p5) +def_gen.noncentral_chisquare(D_arr_0p5, D_arr_0p5, size=1) +def_gen.noncentral_chisquare(D_arr_like_0p5, D_arr_like_0p5, size=1) + +def_gen.normal(0.5, 0.5) +def_gen.normal(0.5, 0.5, size=None) +def_gen.normal(0.5, 0.5, size=1) +def_gen.normal(D_arr_0p5, 0.5) +def_gen.normal(0.5, D_arr_0p5) +def_gen.normal(D_arr_0p5, 0.5, size=1) +def_gen.normal(0.5, D_arr_0p5, size=1) +def_gen.normal(D_arr_like_0p5, 0.5) +def_gen.normal(0.5, D_arr_like_0p5) +def_gen.normal(D_arr_0p5, D_arr_0p5) +def_gen.normal(D_arr_like_0p5, D_arr_like_0p5) +def_gen.normal(D_arr_0p5, D_arr_0p5, size=1) +def_gen.normal(D_arr_like_0p5, D_arr_like_0p5, size=1) + +def_gen.triangular(0.1, 0.5, 0.9) +def_gen.triangular(0.1, 0.5, 0.9, size=None) +def_gen.triangular(0.1, 0.5, 0.9, size=1) +def_gen.triangular(D_arr_0p1, 0.5, 0.9) +def_gen.triangular(0.1, D_arr_0p5, 0.9) +def_gen.triangular(D_arr_0p1, 0.5, D_arr_like_0p9, size=1) +def_gen.triangular(0.1, D_arr_0p5, 0.9, size=1) +def_gen.triangular(D_arr_like_0p1, 0.5, D_arr_0p9) +def_gen.triangular(0.5, D_arr_like_0p5, 0.9) +def_gen.triangular(D_arr_0p1, D_arr_0p5, 0.9) +def_gen.triangular(D_arr_like_0p1, D_arr_like_0p5, 0.9) +def_gen.triangular(D_arr_0p1, D_arr_0p5, D_arr_0p9, size=1) +def_gen.triangular(D_arr_like_0p1, D_arr_like_0p5, D_arr_like_0p9, size=1) + +def_gen.noncentral_f(0.1, 0.5, 0.9) +def_gen.noncentral_f(0.1, 0.5, 0.9, size=None) +def_gen.noncentral_f(0.1, 0.5, 0.9, size=1) +def_gen.noncentral_f(D_arr_0p1, 0.5, 0.9) +def_gen.noncentral_f(0.1, D_arr_0p5, 0.9) +def_gen.noncentral_f(D_arr_0p1, 0.5, D_arr_like_0p9, size=1) +def_gen.noncentral_f(0.1, D_arr_0p5, 0.9, size=1) +def_gen.noncentral_f(D_arr_like_0p1, 0.5, D_arr_0p9) +def_gen.noncentral_f(0.5, D_arr_like_0p5, 0.9) +def_gen.noncentral_f(D_arr_0p1, D_arr_0p5, 0.9) +def_gen.noncentral_f(D_arr_like_0p1, D_arr_like_0p5, 0.9) +def_gen.noncentral_f(D_arr_0p1, D_arr_0p5, D_arr_0p9, size=1) +def_gen.noncentral_f(D_arr_like_0p1, D_arr_like_0p5, D_arr_like_0p9, size=1) + +def_gen.binomial(10, 0.5) +def_gen.binomial(10, 0.5, size=None) +def_gen.binomial(10, 0.5, size=1) +def_gen.binomial(I_arr_10, 0.5) +def_gen.binomial(10, D_arr_0p5) +def_gen.binomial(I_arr_10, 0.5, size=1) +def_gen.binomial(10, D_arr_0p5, size=1) +def_gen.binomial(I_arr_like_10, 0.5) +def_gen.binomial(10, D_arr_like_0p5) +def_gen.binomial(I_arr_10, D_arr_0p5) +def_gen.binomial(I_arr_like_10, D_arr_like_0p5) +def_gen.binomial(I_arr_10, D_arr_0p5, size=1) +def_gen.binomial(I_arr_like_10, D_arr_like_0p5, size=1) + +def_gen.negative_binomial(10, 0.5) +def_gen.negative_binomial(10, 0.5, size=None) +def_gen.negative_binomial(10, 0.5, size=1) +def_gen.negative_binomial(I_arr_10, 0.5) +def_gen.negative_binomial(10, D_arr_0p5) +def_gen.negative_binomial(I_arr_10, 0.5, size=1) +def_gen.negative_binomial(10, D_arr_0p5, size=1) +def_gen.negative_binomial(I_arr_like_10, 0.5) +def_gen.negative_binomial(10, D_arr_like_0p5) +def_gen.negative_binomial(I_arr_10, D_arr_0p5) +def_gen.negative_binomial(I_arr_like_10, D_arr_like_0p5) +def_gen.negative_binomial(I_arr_10, D_arr_0p5, size=1) +def_gen.negative_binomial(I_arr_like_10, D_arr_like_0p5, size=1) + +def_gen.hypergeometric(20, 20, 10) +def_gen.hypergeometric(20, 20, 10, size=None) +def_gen.hypergeometric(20, 20, 10, size=1) +def_gen.hypergeometric(I_arr_20, 20, 10) +def_gen.hypergeometric(20, I_arr_20, 10) +def_gen.hypergeometric(I_arr_20, 20, I_arr_like_10, size=1) +def_gen.hypergeometric(20, I_arr_20, 10, size=1) +def_gen.hypergeometric(I_arr_like_20, 20, I_arr_10) +def_gen.hypergeometric(20, I_arr_like_20, 10) +def_gen.hypergeometric(I_arr_20, I_arr_20, 10) +def_gen.hypergeometric(I_arr_like_20, I_arr_like_20, 10) +def_gen.hypergeometric(I_arr_20, I_arr_20, I_arr_10, size=1) +def_gen.hypergeometric(I_arr_like_20, I_arr_like_20, I_arr_like_10, size=1) + +I_int64_100: np.ndarray[Any, np.dtype[np.int64]] = np.array([100], dtype=np.int64) + +def_gen.integers(0, 100) +def_gen.integers(100) +def_gen.integers([100]) +def_gen.integers(0, [100]) + +I_bool_low: np.ndarray[Any, np.dtype[np.bool]] = np.array([0], dtype=np.bool) +I_bool_low_like: list[int] = [0] +I_bool_high_open: np.ndarray[Any, np.dtype[np.bool]] = np.array([1], dtype=np.bool) +I_bool_high_closed: np.ndarray[Any, np.dtype[np.bool]] = np.array([1], dtype=np.bool) + +def_gen.integers(2, dtype=bool) +def_gen.integers(0, 2, dtype=bool) +def_gen.integers(1, dtype=bool, endpoint=True) +def_gen.integers(0, 1, dtype=bool, endpoint=True) +def_gen.integers(I_bool_low_like, 1, dtype=bool, endpoint=True) +def_gen.integers(I_bool_high_open, dtype=bool) +def_gen.integers(I_bool_low, I_bool_high_open, dtype=bool) +def_gen.integers(0, I_bool_high_open, dtype=bool) +def_gen.integers(I_bool_high_closed, dtype=bool, endpoint=True) +def_gen.integers(I_bool_low, I_bool_high_closed, dtype=bool, endpoint=True) +def_gen.integers(0, I_bool_high_closed, dtype=bool, endpoint=True) + +def_gen.integers(2, dtype=np.bool) +def_gen.integers(0, 2, dtype=np.bool) +def_gen.integers(1, dtype=np.bool, endpoint=True) +def_gen.integers(0, 1, dtype=np.bool, endpoint=True) +def_gen.integers(I_bool_low_like, 1, dtype=np.bool, endpoint=True) +def_gen.integers(I_bool_high_open, dtype=np.bool) +def_gen.integers(I_bool_low, I_bool_high_open, dtype=np.bool) +def_gen.integers(0, I_bool_high_open, dtype=np.bool) +def_gen.integers(I_bool_high_closed, dtype=np.bool, endpoint=True) +def_gen.integers(I_bool_low, I_bool_high_closed, dtype=np.bool, endpoint=True) +def_gen.integers(0, I_bool_high_closed, dtype=np.bool, endpoint=True) + +I_u1_low: np.ndarray[Any, np.dtype[np.uint8]] = np.array([0], dtype=np.uint8) +I_u1_low_like: list[int] = [0] +I_u1_high_open: np.ndarray[Any, np.dtype[np.uint8]] = np.array([255], dtype=np.uint8) +I_u1_high_closed: np.ndarray[Any, np.dtype[np.uint8]] = np.array([255], dtype=np.uint8) + +def_gen.integers(256, dtype="u1") +def_gen.integers(0, 256, dtype="u1") +def_gen.integers(255, dtype="u1", endpoint=True) +def_gen.integers(0, 255, dtype="u1", endpoint=True) +def_gen.integers(I_u1_low_like, 255, dtype="u1", endpoint=True) +def_gen.integers(I_u1_high_open, dtype="u1") +def_gen.integers(I_u1_low, I_u1_high_open, dtype="u1") +def_gen.integers(0, I_u1_high_open, dtype="u1") +def_gen.integers(I_u1_high_closed, dtype="u1", endpoint=True) +def_gen.integers(I_u1_low, I_u1_high_closed, dtype="u1", endpoint=True) +def_gen.integers(0, I_u1_high_closed, dtype="u1", endpoint=True) + +def_gen.integers(256, dtype="uint8") +def_gen.integers(0, 256, dtype="uint8") +def_gen.integers(255, dtype="uint8", endpoint=True) +def_gen.integers(0, 255, dtype="uint8", endpoint=True) +def_gen.integers(I_u1_low_like, 255, dtype="uint8", endpoint=True) +def_gen.integers(I_u1_high_open, dtype="uint8") +def_gen.integers(I_u1_low, I_u1_high_open, dtype="uint8") +def_gen.integers(0, I_u1_high_open, dtype="uint8") +def_gen.integers(I_u1_high_closed, dtype="uint8", endpoint=True) +def_gen.integers(I_u1_low, I_u1_high_closed, dtype="uint8", endpoint=True) +def_gen.integers(0, I_u1_high_closed, dtype="uint8", endpoint=True) + +def_gen.integers(256, dtype=np.uint8) +def_gen.integers(0, 256, dtype=np.uint8) +def_gen.integers(255, dtype=np.uint8, endpoint=True) +def_gen.integers(0, 255, dtype=np.uint8, endpoint=True) +def_gen.integers(I_u1_low_like, 255, dtype=np.uint8, endpoint=True) +def_gen.integers(I_u1_high_open, dtype=np.uint8) +def_gen.integers(I_u1_low, I_u1_high_open, dtype=np.uint8) +def_gen.integers(0, I_u1_high_open, dtype=np.uint8) +def_gen.integers(I_u1_high_closed, dtype=np.uint8, endpoint=True) +def_gen.integers(I_u1_low, I_u1_high_closed, dtype=np.uint8, endpoint=True) +def_gen.integers(0, I_u1_high_closed, dtype=np.uint8, endpoint=True) + +I_u2_low: np.ndarray[Any, np.dtype[np.uint16]] = np.array([0], dtype=np.uint16) +I_u2_low_like: list[int] = [0] +I_u2_high_open: np.ndarray[Any, np.dtype[np.uint16]] = np.array([65535], dtype=np.uint16) +I_u2_high_closed: np.ndarray[Any, np.dtype[np.uint16]] = np.array([65535], dtype=np.uint16) + +def_gen.integers(65536, dtype="u2") +def_gen.integers(0, 65536, dtype="u2") +def_gen.integers(65535, dtype="u2", endpoint=True) +def_gen.integers(0, 65535, dtype="u2", endpoint=True) +def_gen.integers(I_u2_low_like, 65535, dtype="u2", endpoint=True) +def_gen.integers(I_u2_high_open, dtype="u2") +def_gen.integers(I_u2_low, I_u2_high_open, dtype="u2") +def_gen.integers(0, I_u2_high_open, dtype="u2") +def_gen.integers(I_u2_high_closed, dtype="u2", endpoint=True) +def_gen.integers(I_u2_low, I_u2_high_closed, dtype="u2", endpoint=True) +def_gen.integers(0, I_u2_high_closed, dtype="u2", endpoint=True) + +def_gen.integers(65536, dtype="uint16") +def_gen.integers(0, 65536, dtype="uint16") +def_gen.integers(65535, dtype="uint16", endpoint=True) +def_gen.integers(0, 65535, dtype="uint16", endpoint=True) +def_gen.integers(I_u2_low_like, 65535, dtype="uint16", endpoint=True) +def_gen.integers(I_u2_high_open, dtype="uint16") +def_gen.integers(I_u2_low, I_u2_high_open, dtype="uint16") +def_gen.integers(0, I_u2_high_open, dtype="uint16") +def_gen.integers(I_u2_high_closed, dtype="uint16", endpoint=True) +def_gen.integers(I_u2_low, I_u2_high_closed, dtype="uint16", endpoint=True) +def_gen.integers(0, I_u2_high_closed, dtype="uint16", endpoint=True) + +def_gen.integers(65536, dtype=np.uint16) +def_gen.integers(0, 65536, dtype=np.uint16) +def_gen.integers(65535, dtype=np.uint16, endpoint=True) +def_gen.integers(0, 65535, dtype=np.uint16, endpoint=True) +def_gen.integers(I_u2_low_like, 65535, dtype=np.uint16, endpoint=True) +def_gen.integers(I_u2_high_open, dtype=np.uint16) +def_gen.integers(I_u2_low, I_u2_high_open, dtype=np.uint16) +def_gen.integers(0, I_u2_high_open, dtype=np.uint16) +def_gen.integers(I_u2_high_closed, dtype=np.uint16, endpoint=True) +def_gen.integers(I_u2_low, I_u2_high_closed, dtype=np.uint16, endpoint=True) +def_gen.integers(0, I_u2_high_closed, dtype=np.uint16, endpoint=True) + +I_u4_low: np.ndarray[Any, np.dtype[np.uint32]] = np.array([0], dtype=np.uint32) +I_u4_low_like: list[int] = [0] +I_u4_high_open: np.ndarray[Any, np.dtype[np.uint32]] = np.array([4294967295], dtype=np.uint32) +I_u4_high_closed: np.ndarray[Any, np.dtype[np.uint32]] = np.array([4294967295], dtype=np.uint32) + +def_gen.integers(4294967296, dtype="u4") +def_gen.integers(0, 4294967296, dtype="u4") +def_gen.integers(4294967295, dtype="u4", endpoint=True) +def_gen.integers(0, 4294967295, dtype="u4", endpoint=True) +def_gen.integers(I_u4_low_like, 4294967295, dtype="u4", endpoint=True) +def_gen.integers(I_u4_high_open, dtype="u4") +def_gen.integers(I_u4_low, I_u4_high_open, dtype="u4") +def_gen.integers(0, I_u4_high_open, dtype="u4") +def_gen.integers(I_u4_high_closed, dtype="u4", endpoint=True) +def_gen.integers(I_u4_low, I_u4_high_closed, dtype="u4", endpoint=True) +def_gen.integers(0, I_u4_high_closed, dtype="u4", endpoint=True) + +def_gen.integers(4294967296, dtype="uint32") +def_gen.integers(0, 4294967296, dtype="uint32") +def_gen.integers(4294967295, dtype="uint32", endpoint=True) +def_gen.integers(0, 4294967295, dtype="uint32", endpoint=True) +def_gen.integers(I_u4_low_like, 4294967295, dtype="uint32", endpoint=True) +def_gen.integers(I_u4_high_open, dtype="uint32") +def_gen.integers(I_u4_low, I_u4_high_open, dtype="uint32") +def_gen.integers(0, I_u4_high_open, dtype="uint32") +def_gen.integers(I_u4_high_closed, dtype="uint32", endpoint=True) +def_gen.integers(I_u4_low, I_u4_high_closed, dtype="uint32", endpoint=True) +def_gen.integers(0, I_u4_high_closed, dtype="uint32", endpoint=True) + +def_gen.integers(4294967296, dtype=np.uint32) +def_gen.integers(0, 4294967296, dtype=np.uint32) +def_gen.integers(4294967295, dtype=np.uint32, endpoint=True) +def_gen.integers(0, 4294967295, dtype=np.uint32, endpoint=True) +def_gen.integers(I_u4_low_like, 4294967295, dtype=np.uint32, endpoint=True) +def_gen.integers(I_u4_high_open, dtype=np.uint32) +def_gen.integers(I_u4_low, I_u4_high_open, dtype=np.uint32) +def_gen.integers(0, I_u4_high_open, dtype=np.uint32) +def_gen.integers(I_u4_high_closed, dtype=np.uint32, endpoint=True) +def_gen.integers(I_u4_low, I_u4_high_closed, dtype=np.uint32, endpoint=True) +def_gen.integers(0, I_u4_high_closed, dtype=np.uint32, endpoint=True) + +I_u8_low: np.ndarray[Any, np.dtype[np.uint64]] = np.array([0], dtype=np.uint64) +I_u8_low_like: list[int] = [0] +I_u8_high_open: np.ndarray[Any, np.dtype[np.uint64]] = np.array([18446744073709551615], dtype=np.uint64) +I_u8_high_closed: np.ndarray[Any, np.dtype[np.uint64]] = np.array([18446744073709551615], dtype=np.uint64) + +def_gen.integers(18446744073709551616, dtype="u8") +def_gen.integers(0, 18446744073709551616, dtype="u8") +def_gen.integers(18446744073709551615, dtype="u8", endpoint=True) +def_gen.integers(0, 18446744073709551615, dtype="u8", endpoint=True) +def_gen.integers(I_u8_low_like, 18446744073709551615, dtype="u8", endpoint=True) +def_gen.integers(I_u8_high_open, dtype="u8") +def_gen.integers(I_u8_low, I_u8_high_open, dtype="u8") +def_gen.integers(0, I_u8_high_open, dtype="u8") +def_gen.integers(I_u8_high_closed, dtype="u8", endpoint=True) +def_gen.integers(I_u8_low, I_u8_high_closed, dtype="u8", endpoint=True) +def_gen.integers(0, I_u8_high_closed, dtype="u8", endpoint=True) + +def_gen.integers(18446744073709551616, dtype="uint64") +def_gen.integers(0, 18446744073709551616, dtype="uint64") +def_gen.integers(18446744073709551615, dtype="uint64", endpoint=True) +def_gen.integers(0, 18446744073709551615, dtype="uint64", endpoint=True) +def_gen.integers(I_u8_low_like, 18446744073709551615, dtype="uint64", endpoint=True) +def_gen.integers(I_u8_high_open, dtype="uint64") +def_gen.integers(I_u8_low, I_u8_high_open, dtype="uint64") +def_gen.integers(0, I_u8_high_open, dtype="uint64") +def_gen.integers(I_u8_high_closed, dtype="uint64", endpoint=True) +def_gen.integers(I_u8_low, I_u8_high_closed, dtype="uint64", endpoint=True) +def_gen.integers(0, I_u8_high_closed, dtype="uint64", endpoint=True) + +def_gen.integers(18446744073709551616, dtype=np.uint64) +def_gen.integers(0, 18446744073709551616, dtype=np.uint64) +def_gen.integers(18446744073709551615, dtype=np.uint64, endpoint=True) +def_gen.integers(0, 18446744073709551615, dtype=np.uint64, endpoint=True) +def_gen.integers(I_u8_low_like, 18446744073709551615, dtype=np.uint64, endpoint=True) +def_gen.integers(I_u8_high_open, dtype=np.uint64) +def_gen.integers(I_u8_low, I_u8_high_open, dtype=np.uint64) +def_gen.integers(0, I_u8_high_open, dtype=np.uint64) +def_gen.integers(I_u8_high_closed, dtype=np.uint64, endpoint=True) +def_gen.integers(I_u8_low, I_u8_high_closed, dtype=np.uint64, endpoint=True) +def_gen.integers(0, I_u8_high_closed, dtype=np.uint64, endpoint=True) + +I_i1_low: np.ndarray[Any, np.dtype[np.int8]] = np.array([-128], dtype=np.int8) +I_i1_low_like: list[int] = [-128] +I_i1_high_open: np.ndarray[Any, np.dtype[np.int8]] = np.array([127], dtype=np.int8) +I_i1_high_closed: np.ndarray[Any, np.dtype[np.int8]] = np.array([127], dtype=np.int8) + +def_gen.integers(128, dtype="i1") +def_gen.integers(-128, 128, dtype="i1") +def_gen.integers(127, dtype="i1", endpoint=True) +def_gen.integers(-128, 127, dtype="i1", endpoint=True) +def_gen.integers(I_i1_low_like, 127, dtype="i1", endpoint=True) +def_gen.integers(I_i1_high_open, dtype="i1") +def_gen.integers(I_i1_low, I_i1_high_open, dtype="i1") +def_gen.integers(-128, I_i1_high_open, dtype="i1") +def_gen.integers(I_i1_high_closed, dtype="i1", endpoint=True) +def_gen.integers(I_i1_low, I_i1_high_closed, dtype="i1", endpoint=True) +def_gen.integers(-128, I_i1_high_closed, dtype="i1", endpoint=True) + +def_gen.integers(128, dtype="int8") +def_gen.integers(-128, 128, dtype="int8") +def_gen.integers(127, dtype="int8", endpoint=True) +def_gen.integers(-128, 127, dtype="int8", endpoint=True) +def_gen.integers(I_i1_low_like, 127, dtype="int8", endpoint=True) +def_gen.integers(I_i1_high_open, dtype="int8") +def_gen.integers(I_i1_low, I_i1_high_open, dtype="int8") +def_gen.integers(-128, I_i1_high_open, dtype="int8") +def_gen.integers(I_i1_high_closed, dtype="int8", endpoint=True) +def_gen.integers(I_i1_low, I_i1_high_closed, dtype="int8", endpoint=True) +def_gen.integers(-128, I_i1_high_closed, dtype="int8", endpoint=True) + +def_gen.integers(128, dtype=np.int8) +def_gen.integers(-128, 128, dtype=np.int8) +def_gen.integers(127, dtype=np.int8, endpoint=True) +def_gen.integers(-128, 127, dtype=np.int8, endpoint=True) +def_gen.integers(I_i1_low_like, 127, dtype=np.int8, endpoint=True) +def_gen.integers(I_i1_high_open, dtype=np.int8) +def_gen.integers(I_i1_low, I_i1_high_open, dtype=np.int8) +def_gen.integers(-128, I_i1_high_open, dtype=np.int8) +def_gen.integers(I_i1_high_closed, dtype=np.int8, endpoint=True) +def_gen.integers(I_i1_low, I_i1_high_closed, dtype=np.int8, endpoint=True) +def_gen.integers(-128, I_i1_high_closed, dtype=np.int8, endpoint=True) + +I_i2_low: np.ndarray[Any, np.dtype[np.int16]] = np.array([-32768], dtype=np.int16) +I_i2_low_like: list[int] = [-32768] +I_i2_high_open: np.ndarray[Any, np.dtype[np.int16]] = np.array([32767], dtype=np.int16) +I_i2_high_closed: np.ndarray[Any, np.dtype[np.int16]] = np.array([32767], dtype=np.int16) + +def_gen.integers(32768, dtype="i2") +def_gen.integers(-32768, 32768, dtype="i2") +def_gen.integers(32767, dtype="i2", endpoint=True) +def_gen.integers(-32768, 32767, dtype="i2", endpoint=True) +def_gen.integers(I_i2_low_like, 32767, dtype="i2", endpoint=True) +def_gen.integers(I_i2_high_open, dtype="i2") +def_gen.integers(I_i2_low, I_i2_high_open, dtype="i2") +def_gen.integers(-32768, I_i2_high_open, dtype="i2") +def_gen.integers(I_i2_high_closed, dtype="i2", endpoint=True) +def_gen.integers(I_i2_low, I_i2_high_closed, dtype="i2", endpoint=True) +def_gen.integers(-32768, I_i2_high_closed, dtype="i2", endpoint=True) + +def_gen.integers(32768, dtype="int16") +def_gen.integers(-32768, 32768, dtype="int16") +def_gen.integers(32767, dtype="int16", endpoint=True) +def_gen.integers(-32768, 32767, dtype="int16", endpoint=True) +def_gen.integers(I_i2_low_like, 32767, dtype="int16", endpoint=True) +def_gen.integers(I_i2_high_open, dtype="int16") +def_gen.integers(I_i2_low, I_i2_high_open, dtype="int16") +def_gen.integers(-32768, I_i2_high_open, dtype="int16") +def_gen.integers(I_i2_high_closed, dtype="int16", endpoint=True) +def_gen.integers(I_i2_low, I_i2_high_closed, dtype="int16", endpoint=True) +def_gen.integers(-32768, I_i2_high_closed, dtype="int16", endpoint=True) + +def_gen.integers(32768, dtype=np.int16) +def_gen.integers(-32768, 32768, dtype=np.int16) +def_gen.integers(32767, dtype=np.int16, endpoint=True) +def_gen.integers(-32768, 32767, dtype=np.int16, endpoint=True) +def_gen.integers(I_i2_low_like, 32767, dtype=np.int16, endpoint=True) +def_gen.integers(I_i2_high_open, dtype=np.int16) +def_gen.integers(I_i2_low, I_i2_high_open, dtype=np.int16) +def_gen.integers(-32768, I_i2_high_open, dtype=np.int16) +def_gen.integers(I_i2_high_closed, dtype=np.int16, endpoint=True) +def_gen.integers(I_i2_low, I_i2_high_closed, dtype=np.int16, endpoint=True) +def_gen.integers(-32768, I_i2_high_closed, dtype=np.int16, endpoint=True) + +I_i4_low: np.ndarray[Any, np.dtype[np.int32]] = np.array([-2147483648], dtype=np.int32) +I_i4_low_like: list[int] = [-2147483648] +I_i4_high_open: np.ndarray[Any, np.dtype[np.int32]] = np.array([2147483647], dtype=np.int32) +I_i4_high_closed: np.ndarray[Any, np.dtype[np.int32]] = np.array([2147483647], dtype=np.int32) + +def_gen.integers(2147483648, dtype="i4") +def_gen.integers(-2147483648, 2147483648, dtype="i4") +def_gen.integers(2147483647, dtype="i4", endpoint=True) +def_gen.integers(-2147483648, 2147483647, dtype="i4", endpoint=True) +def_gen.integers(I_i4_low_like, 2147483647, dtype="i4", endpoint=True) +def_gen.integers(I_i4_high_open, dtype="i4") +def_gen.integers(I_i4_low, I_i4_high_open, dtype="i4") +def_gen.integers(-2147483648, I_i4_high_open, dtype="i4") +def_gen.integers(I_i4_high_closed, dtype="i4", endpoint=True) +def_gen.integers(I_i4_low, I_i4_high_closed, dtype="i4", endpoint=True) +def_gen.integers(-2147483648, I_i4_high_closed, dtype="i4", endpoint=True) + +def_gen.integers(2147483648, dtype="int32") +def_gen.integers(-2147483648, 2147483648, dtype="int32") +def_gen.integers(2147483647, dtype="int32", endpoint=True) +def_gen.integers(-2147483648, 2147483647, dtype="int32", endpoint=True) +def_gen.integers(I_i4_low_like, 2147483647, dtype="int32", endpoint=True) +def_gen.integers(I_i4_high_open, dtype="int32") +def_gen.integers(I_i4_low, I_i4_high_open, dtype="int32") +def_gen.integers(-2147483648, I_i4_high_open, dtype="int32") +def_gen.integers(I_i4_high_closed, dtype="int32", endpoint=True) +def_gen.integers(I_i4_low, I_i4_high_closed, dtype="int32", endpoint=True) +def_gen.integers(-2147483648, I_i4_high_closed, dtype="int32", endpoint=True) + +def_gen.integers(2147483648, dtype=np.int32) +def_gen.integers(-2147483648, 2147483648, dtype=np.int32) +def_gen.integers(2147483647, dtype=np.int32, endpoint=True) +def_gen.integers(-2147483648, 2147483647, dtype=np.int32, endpoint=True) +def_gen.integers(I_i4_low_like, 2147483647, dtype=np.int32, endpoint=True) +def_gen.integers(I_i4_high_open, dtype=np.int32) +def_gen.integers(I_i4_low, I_i4_high_open, dtype=np.int32) +def_gen.integers(-2147483648, I_i4_high_open, dtype=np.int32) +def_gen.integers(I_i4_high_closed, dtype=np.int32, endpoint=True) +def_gen.integers(I_i4_low, I_i4_high_closed, dtype=np.int32, endpoint=True) +def_gen.integers(-2147483648, I_i4_high_closed, dtype=np.int32, endpoint=True) + +I_i8_low: np.ndarray[Any, np.dtype[np.int64]] = np.array([-9223372036854775808], dtype=np.int64) +I_i8_low_like: list[int] = [-9223372036854775808] +I_i8_high_open: np.ndarray[Any, np.dtype[np.int64]] = np.array([9223372036854775807], dtype=np.int64) +I_i8_high_closed: np.ndarray[Any, np.dtype[np.int64]] = np.array([9223372036854775807], dtype=np.int64) + +def_gen.integers(9223372036854775808, dtype="i8") +def_gen.integers(-9223372036854775808, 9223372036854775808, dtype="i8") +def_gen.integers(9223372036854775807, dtype="i8", endpoint=True) +def_gen.integers(-9223372036854775808, 9223372036854775807, dtype="i8", endpoint=True) +def_gen.integers(I_i8_low_like, 9223372036854775807, dtype="i8", endpoint=True) +def_gen.integers(I_i8_high_open, dtype="i8") +def_gen.integers(I_i8_low, I_i8_high_open, dtype="i8") +def_gen.integers(-9223372036854775808, I_i8_high_open, dtype="i8") +def_gen.integers(I_i8_high_closed, dtype="i8", endpoint=True) +def_gen.integers(I_i8_low, I_i8_high_closed, dtype="i8", endpoint=True) +def_gen.integers(-9223372036854775808, I_i8_high_closed, dtype="i8", endpoint=True) + +def_gen.integers(9223372036854775808, dtype="int64") +def_gen.integers(-9223372036854775808, 9223372036854775808, dtype="int64") +def_gen.integers(9223372036854775807, dtype="int64", endpoint=True) +def_gen.integers(-9223372036854775808, 9223372036854775807, dtype="int64", endpoint=True) +def_gen.integers(I_i8_low_like, 9223372036854775807, dtype="int64", endpoint=True) +def_gen.integers(I_i8_high_open, dtype="int64") +def_gen.integers(I_i8_low, I_i8_high_open, dtype="int64") +def_gen.integers(-9223372036854775808, I_i8_high_open, dtype="int64") +def_gen.integers(I_i8_high_closed, dtype="int64", endpoint=True) +def_gen.integers(I_i8_low, I_i8_high_closed, dtype="int64", endpoint=True) +def_gen.integers(-9223372036854775808, I_i8_high_closed, dtype="int64", endpoint=True) + +def_gen.integers(9223372036854775808, dtype=np.int64) +def_gen.integers(-9223372036854775808, 9223372036854775808, dtype=np.int64) +def_gen.integers(9223372036854775807, dtype=np.int64, endpoint=True) +def_gen.integers(-9223372036854775808, 9223372036854775807, dtype=np.int64, endpoint=True) +def_gen.integers(I_i8_low_like, 9223372036854775807, dtype=np.int64, endpoint=True) +def_gen.integers(I_i8_high_open, dtype=np.int64) +def_gen.integers(I_i8_low, I_i8_high_open, dtype=np.int64) +def_gen.integers(-9223372036854775808, I_i8_high_open, dtype=np.int64) +def_gen.integers(I_i8_high_closed, dtype=np.int64, endpoint=True) +def_gen.integers(I_i8_low, I_i8_high_closed, dtype=np.int64, endpoint=True) +def_gen.integers(-9223372036854775808, I_i8_high_closed, dtype=np.int64, endpoint=True) + + +def_gen.bit_generator + +def_gen.bytes(2) + +def_gen.choice(5) +def_gen.choice(5, 3) +def_gen.choice(5, 3, replace=True) +def_gen.choice(5, 3, p=[1 / 5] * 5) +def_gen.choice(5, 3, p=[1 / 5] * 5, replace=False) + +def_gen.choice(["pooh", "rabbit", "piglet", "Christopher"]) +def_gen.choice(["pooh", "rabbit", "piglet", "Christopher"], 3) +def_gen.choice(["pooh", "rabbit", "piglet", "Christopher"], 3, p=[1 / 4] * 4) +def_gen.choice(["pooh", "rabbit", "piglet", "Christopher"], 3, replace=True) +def_gen.choice(["pooh", "rabbit", "piglet", "Christopher"], 3, replace=False, p=np.array([1 / 8, 1 / 8, 1 / 2, 1 / 4])) + +def_gen.dirichlet([0.5, 0.5]) +def_gen.dirichlet(np.array([0.5, 0.5])) +def_gen.dirichlet(np.array([0.5, 0.5]), size=3) + +def_gen.multinomial(20, [1 / 6.0] * 6) +def_gen.multinomial(20, np.array([0.5, 0.5])) +def_gen.multinomial(20, [1 / 6.0] * 6, size=2) +def_gen.multinomial([[10], [20]], [1 / 6.0] * 6, size=(2, 2)) +def_gen.multinomial(np.array([[10], [20]]), np.array([0.5, 0.5]), size=(2, 2)) + +def_gen.multivariate_hypergeometric([3, 5, 7], 2) +def_gen.multivariate_hypergeometric(np.array([3, 5, 7]), 2) +def_gen.multivariate_hypergeometric(np.array([3, 5, 7]), 2, size=4) +def_gen.multivariate_hypergeometric(np.array([3, 5, 7]), 2, size=(4, 7)) +def_gen.multivariate_hypergeometric([3, 5, 7], 2, method="count") +def_gen.multivariate_hypergeometric(np.array([3, 5, 7]), 2, method="marginals") + +def_gen.multivariate_normal([0.0], [[1.0]]) +def_gen.multivariate_normal([0.0], np.array([[1.0]])) +def_gen.multivariate_normal(np.array([0.0]), [[1.0]]) +def_gen.multivariate_normal([0.0], np.array([[1.0]])) + +def_gen.permutation(10) +def_gen.permutation([1, 2, 3, 4]) +def_gen.permutation(np.array([1, 2, 3, 4])) +def_gen.permutation(D_2D, axis=1) +def_gen.permuted(D_2D) +def_gen.permuted(D_2D_like) +def_gen.permuted(D_2D, axis=1) +def_gen.permuted(D_2D, out=D_2D) +def_gen.permuted(D_2D_like, out=D_2D) +def_gen.permuted(D_2D_like, out=D_2D) +def_gen.permuted(D_2D, axis=1, out=D_2D) + +def_gen.shuffle(np.arange(10)) +def_gen.shuffle([1, 2, 3, 4, 5]) +def_gen.shuffle(D_2D, axis=1) + +def_gen.__str__() +def_gen.__repr__() +def_gen.__setstate__(dict(def_gen.bit_generator.state)) + +# RandomState +random_st: np.random.RandomState = np.random.RandomState() + +random_st.standard_normal() +random_st.standard_normal(size=None) +random_st.standard_normal(size=1) + +random_st.random() +random_st.random(size=None) +random_st.random(size=1) + +random_st.standard_cauchy() +random_st.standard_cauchy(size=None) +random_st.standard_cauchy(size=1) + +random_st.standard_exponential() +random_st.standard_exponential(size=None) +random_st.standard_exponential(size=1) + +random_st.zipf(1.5) +random_st.zipf(1.5, size=None) +random_st.zipf(1.5, size=1) +random_st.zipf(D_arr_1p5) +random_st.zipf(D_arr_1p5, size=1) +random_st.zipf(D_arr_like_1p5) +random_st.zipf(D_arr_like_1p5, size=1) + +random_st.weibull(0.5) +random_st.weibull(0.5, size=None) +random_st.weibull(0.5, size=1) +random_st.weibull(D_arr_0p5) +random_st.weibull(D_arr_0p5, size=1) +random_st.weibull(D_arr_like_0p5) +random_st.weibull(D_arr_like_0p5, size=1) + +random_st.standard_t(0.5) +random_st.standard_t(0.5, size=None) +random_st.standard_t(0.5, size=1) +random_st.standard_t(D_arr_0p5) +random_st.standard_t(D_arr_0p5, size=1) +random_st.standard_t(D_arr_like_0p5) +random_st.standard_t(D_arr_like_0p5, size=1) + +random_st.poisson(0.5) +random_st.poisson(0.5, size=None) +random_st.poisson(0.5, size=1) +random_st.poisson(D_arr_0p5) +random_st.poisson(D_arr_0p5, size=1) +random_st.poisson(D_arr_like_0p5) +random_st.poisson(D_arr_like_0p5, size=1) + +random_st.power(0.5) +random_st.power(0.5, size=None) +random_st.power(0.5, size=1) +random_st.power(D_arr_0p5) +random_st.power(D_arr_0p5, size=1) +random_st.power(D_arr_like_0p5) +random_st.power(D_arr_like_0p5, size=1) + +random_st.pareto(0.5) +random_st.pareto(0.5, size=None) +random_st.pareto(0.5, size=1) +random_st.pareto(D_arr_0p5) +random_st.pareto(D_arr_0p5, size=1) +random_st.pareto(D_arr_like_0p5) +random_st.pareto(D_arr_like_0p5, size=1) + +random_st.chisquare(0.5) +random_st.chisquare(0.5, size=None) +random_st.chisquare(0.5, size=1) +random_st.chisquare(D_arr_0p5) +random_st.chisquare(D_arr_0p5, size=1) +random_st.chisquare(D_arr_like_0p5) +random_st.chisquare(D_arr_like_0p5, size=1) + +random_st.exponential(0.5) +random_st.exponential(0.5, size=None) +random_st.exponential(0.5, size=1) +random_st.exponential(D_arr_0p5) +random_st.exponential(D_arr_0p5, size=1) +random_st.exponential(D_arr_like_0p5) +random_st.exponential(D_arr_like_0p5, size=1) + +random_st.geometric(0.5) +random_st.geometric(0.5, size=None) +random_st.geometric(0.5, size=1) +random_st.geometric(D_arr_0p5) +random_st.geometric(D_arr_0p5, size=1) +random_st.geometric(D_arr_like_0p5) +random_st.geometric(D_arr_like_0p5, size=1) + +random_st.logseries(0.5) +random_st.logseries(0.5, size=None) +random_st.logseries(0.5, size=1) +random_st.logseries(D_arr_0p5) +random_st.logseries(D_arr_0p5, size=1) +random_st.logseries(D_arr_like_0p5) +random_st.logseries(D_arr_like_0p5, size=1) + +random_st.rayleigh(0.5) +random_st.rayleigh(0.5, size=None) +random_st.rayleigh(0.5, size=1) +random_st.rayleigh(D_arr_0p5) +random_st.rayleigh(D_arr_0p5, size=1) +random_st.rayleigh(D_arr_like_0p5) +random_st.rayleigh(D_arr_like_0p5, size=1) + +random_st.standard_gamma(0.5) +random_st.standard_gamma(0.5, size=None) +random_st.standard_gamma(0.5, size=1) +random_st.standard_gamma(D_arr_0p5) +random_st.standard_gamma(D_arr_0p5, size=1) +random_st.standard_gamma(D_arr_like_0p5) +random_st.standard_gamma(D_arr_like_0p5, size=1) +random_st.standard_gamma(D_arr_like_0p5, size=1) + +random_st.vonmises(0.5, 0.5) +random_st.vonmises(0.5, 0.5, size=None) +random_st.vonmises(0.5, 0.5, size=1) +random_st.vonmises(D_arr_0p5, 0.5) +random_st.vonmises(0.5, D_arr_0p5) +random_st.vonmises(D_arr_0p5, 0.5, size=1) +random_st.vonmises(0.5, D_arr_0p5, size=1) +random_st.vonmises(D_arr_like_0p5, 0.5) +random_st.vonmises(0.5, D_arr_like_0p5) +random_st.vonmises(D_arr_0p5, D_arr_0p5) +random_st.vonmises(D_arr_like_0p5, D_arr_like_0p5) +random_st.vonmises(D_arr_0p5, D_arr_0p5, size=1) +random_st.vonmises(D_arr_like_0p5, D_arr_like_0p5, size=1) + +random_st.wald(0.5, 0.5) +random_st.wald(0.5, 0.5, size=None) +random_st.wald(0.5, 0.5, size=1) +random_st.wald(D_arr_0p5, 0.5) +random_st.wald(0.5, D_arr_0p5) +random_st.wald(D_arr_0p5, 0.5, size=1) +random_st.wald(0.5, D_arr_0p5, size=1) +random_st.wald(D_arr_like_0p5, 0.5) +random_st.wald(0.5, D_arr_like_0p5) +random_st.wald(D_arr_0p5, D_arr_0p5) +random_st.wald(D_arr_like_0p5, D_arr_like_0p5) +random_st.wald(D_arr_0p5, D_arr_0p5, size=1) +random_st.wald(D_arr_like_0p5, D_arr_like_0p5, size=1) + +random_st.uniform(0.5, 0.5) +random_st.uniform(0.5, 0.5, size=None) +random_st.uniform(0.5, 0.5, size=1) +random_st.uniform(D_arr_0p5, 0.5) +random_st.uniform(0.5, D_arr_0p5) +random_st.uniform(D_arr_0p5, 0.5, size=1) +random_st.uniform(0.5, D_arr_0p5, size=1) +random_st.uniform(D_arr_like_0p5, 0.5) +random_st.uniform(0.5, D_arr_like_0p5) +random_st.uniform(D_arr_0p5, D_arr_0p5) +random_st.uniform(D_arr_like_0p5, D_arr_like_0p5) +random_st.uniform(D_arr_0p5, D_arr_0p5, size=1) +random_st.uniform(D_arr_like_0p5, D_arr_like_0p5, size=1) + +random_st.beta(0.5, 0.5) +random_st.beta(0.5, 0.5, size=None) +random_st.beta(0.5, 0.5, size=1) +random_st.beta(D_arr_0p5, 0.5) +random_st.beta(0.5, D_arr_0p5) +random_st.beta(D_arr_0p5, 0.5, size=1) +random_st.beta(0.5, D_arr_0p5, size=1) +random_st.beta(D_arr_like_0p5, 0.5) +random_st.beta(0.5, D_arr_like_0p5) +random_st.beta(D_arr_0p5, D_arr_0p5) +random_st.beta(D_arr_like_0p5, D_arr_like_0p5) +random_st.beta(D_arr_0p5, D_arr_0p5, size=1) +random_st.beta(D_arr_like_0p5, D_arr_like_0p5, size=1) + +random_st.f(0.5, 0.5) +random_st.f(0.5, 0.5, size=None) +random_st.f(0.5, 0.5, size=1) +random_st.f(D_arr_0p5, 0.5) +random_st.f(0.5, D_arr_0p5) +random_st.f(D_arr_0p5, 0.5, size=1) +random_st.f(0.5, D_arr_0p5, size=1) +random_st.f(D_arr_like_0p5, 0.5) +random_st.f(0.5, D_arr_like_0p5) +random_st.f(D_arr_0p5, D_arr_0p5) +random_st.f(D_arr_like_0p5, D_arr_like_0p5) +random_st.f(D_arr_0p5, D_arr_0p5, size=1) +random_st.f(D_arr_like_0p5, D_arr_like_0p5, size=1) + +random_st.gamma(0.5, 0.5) +random_st.gamma(0.5, 0.5, size=None) +random_st.gamma(0.5, 0.5, size=1) +random_st.gamma(D_arr_0p5, 0.5) +random_st.gamma(0.5, D_arr_0p5) +random_st.gamma(D_arr_0p5, 0.5, size=1) +random_st.gamma(0.5, D_arr_0p5, size=1) +random_st.gamma(D_arr_like_0p5, 0.5) +random_st.gamma(0.5, D_arr_like_0p5) +random_st.gamma(D_arr_0p5, D_arr_0p5) +random_st.gamma(D_arr_like_0p5, D_arr_like_0p5) +random_st.gamma(D_arr_0p5, D_arr_0p5, size=1) +random_st.gamma(D_arr_like_0p5, D_arr_like_0p5, size=1) + +random_st.gumbel(0.5, 0.5) +random_st.gumbel(0.5, 0.5, size=None) +random_st.gumbel(0.5, 0.5, size=1) +random_st.gumbel(D_arr_0p5, 0.5) +random_st.gumbel(0.5, D_arr_0p5) +random_st.gumbel(D_arr_0p5, 0.5, size=1) +random_st.gumbel(0.5, D_arr_0p5, size=1) +random_st.gumbel(D_arr_like_0p5, 0.5) +random_st.gumbel(0.5, D_arr_like_0p5) +random_st.gumbel(D_arr_0p5, D_arr_0p5) +random_st.gumbel(D_arr_like_0p5, D_arr_like_0p5) +random_st.gumbel(D_arr_0p5, D_arr_0p5, size=1) +random_st.gumbel(D_arr_like_0p5, D_arr_like_0p5, size=1) + +random_st.laplace(0.5, 0.5) +random_st.laplace(0.5, 0.5, size=None) +random_st.laplace(0.5, 0.5, size=1) +random_st.laplace(D_arr_0p5, 0.5) +random_st.laplace(0.5, D_arr_0p5) +random_st.laplace(D_arr_0p5, 0.5, size=1) +random_st.laplace(0.5, D_arr_0p5, size=1) +random_st.laplace(D_arr_like_0p5, 0.5) +random_st.laplace(0.5, D_arr_like_0p5) +random_st.laplace(D_arr_0p5, D_arr_0p5) +random_st.laplace(D_arr_like_0p5, D_arr_like_0p5) +random_st.laplace(D_arr_0p5, D_arr_0p5, size=1) +random_st.laplace(D_arr_like_0p5, D_arr_like_0p5, size=1) + +random_st.logistic(0.5, 0.5) +random_st.logistic(0.5, 0.5, size=None) +random_st.logistic(0.5, 0.5, size=1) +random_st.logistic(D_arr_0p5, 0.5) +random_st.logistic(0.5, D_arr_0p5) +random_st.logistic(D_arr_0p5, 0.5, size=1) +random_st.logistic(0.5, D_arr_0p5, size=1) +random_st.logistic(D_arr_like_0p5, 0.5) +random_st.logistic(0.5, D_arr_like_0p5) +random_st.logistic(D_arr_0p5, D_arr_0p5) +random_st.logistic(D_arr_like_0p5, D_arr_like_0p5) +random_st.logistic(D_arr_0p5, D_arr_0p5, size=1) +random_st.logistic(D_arr_like_0p5, D_arr_like_0p5, size=1) + +random_st.lognormal(0.5, 0.5) +random_st.lognormal(0.5, 0.5, size=None) +random_st.lognormal(0.5, 0.5, size=1) +random_st.lognormal(D_arr_0p5, 0.5) +random_st.lognormal(0.5, D_arr_0p5) +random_st.lognormal(D_arr_0p5, 0.5, size=1) +random_st.lognormal(0.5, D_arr_0p5, size=1) +random_st.lognormal(D_arr_like_0p5, 0.5) +random_st.lognormal(0.5, D_arr_like_0p5) +random_st.lognormal(D_arr_0p5, D_arr_0p5) +random_st.lognormal(D_arr_like_0p5, D_arr_like_0p5) +random_st.lognormal(D_arr_0p5, D_arr_0p5, size=1) +random_st.lognormal(D_arr_like_0p5, D_arr_like_0p5, size=1) + +random_st.noncentral_chisquare(0.5, 0.5) +random_st.noncentral_chisquare(0.5, 0.5, size=None) +random_st.noncentral_chisquare(0.5, 0.5, size=1) +random_st.noncentral_chisquare(D_arr_0p5, 0.5) +random_st.noncentral_chisquare(0.5, D_arr_0p5) +random_st.noncentral_chisquare(D_arr_0p5, 0.5, size=1) +random_st.noncentral_chisquare(0.5, D_arr_0p5, size=1) +random_st.noncentral_chisquare(D_arr_like_0p5, 0.5) +random_st.noncentral_chisquare(0.5, D_arr_like_0p5) +random_st.noncentral_chisquare(D_arr_0p5, D_arr_0p5) +random_st.noncentral_chisquare(D_arr_like_0p5, D_arr_like_0p5) +random_st.noncentral_chisquare(D_arr_0p5, D_arr_0p5, size=1) +random_st.noncentral_chisquare(D_arr_like_0p5, D_arr_like_0p5, size=1) + +random_st.normal(0.5, 0.5) +random_st.normal(0.5, 0.5, size=None) +random_st.normal(0.5, 0.5, size=1) +random_st.normal(D_arr_0p5, 0.5) +random_st.normal(0.5, D_arr_0p5) +random_st.normal(D_arr_0p5, 0.5, size=1) +random_st.normal(0.5, D_arr_0p5, size=1) +random_st.normal(D_arr_like_0p5, 0.5) +random_st.normal(0.5, D_arr_like_0p5) +random_st.normal(D_arr_0p5, D_arr_0p5) +random_st.normal(D_arr_like_0p5, D_arr_like_0p5) +random_st.normal(D_arr_0p5, D_arr_0p5, size=1) +random_st.normal(D_arr_like_0p5, D_arr_like_0p5, size=1) + +random_st.triangular(0.1, 0.5, 0.9) +random_st.triangular(0.1, 0.5, 0.9, size=None) +random_st.triangular(0.1, 0.5, 0.9, size=1) +random_st.triangular(D_arr_0p1, 0.5, 0.9) +random_st.triangular(0.1, D_arr_0p5, 0.9) +random_st.triangular(D_arr_0p1, 0.5, D_arr_like_0p9, size=1) +random_st.triangular(0.1, D_arr_0p5, 0.9, size=1) +random_st.triangular(D_arr_like_0p1, 0.5, D_arr_0p9) +random_st.triangular(0.5, D_arr_like_0p5, 0.9) +random_st.triangular(D_arr_0p1, D_arr_0p5, 0.9) +random_st.triangular(D_arr_like_0p1, D_arr_like_0p5, 0.9) +random_st.triangular(D_arr_0p1, D_arr_0p5, D_arr_0p9, size=1) +random_st.triangular(D_arr_like_0p1, D_arr_like_0p5, D_arr_like_0p9, size=1) + +random_st.noncentral_f(0.1, 0.5, 0.9) +random_st.noncentral_f(0.1, 0.5, 0.9, size=None) +random_st.noncentral_f(0.1, 0.5, 0.9, size=1) +random_st.noncentral_f(D_arr_0p1, 0.5, 0.9) +random_st.noncentral_f(0.1, D_arr_0p5, 0.9) +random_st.noncentral_f(D_arr_0p1, 0.5, D_arr_like_0p9, size=1) +random_st.noncentral_f(0.1, D_arr_0p5, 0.9, size=1) +random_st.noncentral_f(D_arr_like_0p1, 0.5, D_arr_0p9) +random_st.noncentral_f(0.5, D_arr_like_0p5, 0.9) +random_st.noncentral_f(D_arr_0p1, D_arr_0p5, 0.9) +random_st.noncentral_f(D_arr_like_0p1, D_arr_like_0p5, 0.9) +random_st.noncentral_f(D_arr_0p1, D_arr_0p5, D_arr_0p9, size=1) +random_st.noncentral_f(D_arr_like_0p1, D_arr_like_0p5, D_arr_like_0p9, size=1) + +random_st.binomial(10, 0.5) +random_st.binomial(10, 0.5, size=None) +random_st.binomial(10, 0.5, size=1) +random_st.binomial(I_arr_10, 0.5) +random_st.binomial(10, D_arr_0p5) +random_st.binomial(I_arr_10, 0.5, size=1) +random_st.binomial(10, D_arr_0p5, size=1) +random_st.binomial(I_arr_like_10, 0.5) +random_st.binomial(10, D_arr_like_0p5) +random_st.binomial(I_arr_10, D_arr_0p5) +random_st.binomial(I_arr_like_10, D_arr_like_0p5) +random_st.binomial(I_arr_10, D_arr_0p5, size=1) +random_st.binomial(I_arr_like_10, D_arr_like_0p5, size=1) + +random_st.negative_binomial(10, 0.5) +random_st.negative_binomial(10, 0.5, size=None) +random_st.negative_binomial(10, 0.5, size=1) +random_st.negative_binomial(I_arr_10, 0.5) +random_st.negative_binomial(10, D_arr_0p5) +random_st.negative_binomial(I_arr_10, 0.5, size=1) +random_st.negative_binomial(10, D_arr_0p5, size=1) +random_st.negative_binomial(I_arr_like_10, 0.5) +random_st.negative_binomial(10, D_arr_like_0p5) +random_st.negative_binomial(I_arr_10, D_arr_0p5) +random_st.negative_binomial(I_arr_like_10, D_arr_like_0p5) +random_st.negative_binomial(I_arr_10, D_arr_0p5, size=1) +random_st.negative_binomial(I_arr_like_10, D_arr_like_0p5, size=1) + +random_st.hypergeometric(20, 20, 10) +random_st.hypergeometric(20, 20, 10, size=None) +random_st.hypergeometric(20, 20, 10, size=1) +random_st.hypergeometric(I_arr_20, 20, 10) +random_st.hypergeometric(20, I_arr_20, 10) +random_st.hypergeometric(I_arr_20, 20, I_arr_like_10, size=1) +random_st.hypergeometric(20, I_arr_20, 10, size=1) +random_st.hypergeometric(I_arr_like_20, 20, I_arr_10) +random_st.hypergeometric(20, I_arr_like_20, 10) +random_st.hypergeometric(I_arr_20, I_arr_20, 10) +random_st.hypergeometric(I_arr_like_20, I_arr_like_20, 10) +random_st.hypergeometric(I_arr_20, I_arr_20, I_arr_10, size=1) +random_st.hypergeometric(I_arr_like_20, I_arr_like_20, I_arr_like_10, size=1) + +random_st.randint(0, 100) +random_st.randint(100) +random_st.randint([100]) +random_st.randint(0, [100]) + +random_st.randint(2, dtype=bool) +random_st.randint(0, 2, dtype=bool) +random_st.randint(I_bool_high_open, dtype=bool) +random_st.randint(I_bool_low, I_bool_high_open, dtype=bool) +random_st.randint(0, I_bool_high_open, dtype=bool) + +random_st.randint(2, dtype=np.bool) +random_st.randint(0, 2, dtype=np.bool) +random_st.randint(I_bool_high_open, dtype=np.bool) +random_st.randint(I_bool_low, I_bool_high_open, dtype=np.bool) +random_st.randint(0, I_bool_high_open, dtype=np.bool) + +random_st.randint(256, dtype="u1") +random_st.randint(0, 256, dtype="u1") +random_st.randint(I_u1_high_open, dtype="u1") +random_st.randint(I_u1_low, I_u1_high_open, dtype="u1") +random_st.randint(0, I_u1_high_open, dtype="u1") + +random_st.randint(256, dtype="uint8") +random_st.randint(0, 256, dtype="uint8") +random_st.randint(I_u1_high_open, dtype="uint8") +random_st.randint(I_u1_low, I_u1_high_open, dtype="uint8") +random_st.randint(0, I_u1_high_open, dtype="uint8") + +random_st.randint(256, dtype=np.uint8) +random_st.randint(0, 256, dtype=np.uint8) +random_st.randint(I_u1_high_open, dtype=np.uint8) +random_st.randint(I_u1_low, I_u1_high_open, dtype=np.uint8) +random_st.randint(0, I_u1_high_open, dtype=np.uint8) + +random_st.randint(65536, dtype="u2") +random_st.randint(0, 65536, dtype="u2") +random_st.randint(I_u2_high_open, dtype="u2") +random_st.randint(I_u2_low, I_u2_high_open, dtype="u2") +random_st.randint(0, I_u2_high_open, dtype="u2") + +random_st.randint(65536, dtype="uint16") +random_st.randint(0, 65536, dtype="uint16") +random_st.randint(I_u2_high_open, dtype="uint16") +random_st.randint(I_u2_low, I_u2_high_open, dtype="uint16") +random_st.randint(0, I_u2_high_open, dtype="uint16") + +random_st.randint(65536, dtype=np.uint16) +random_st.randint(0, 65536, dtype=np.uint16) +random_st.randint(I_u2_high_open, dtype=np.uint16) +random_st.randint(I_u2_low, I_u2_high_open, dtype=np.uint16) +random_st.randint(0, I_u2_high_open, dtype=np.uint16) + +random_st.randint(4294967296, dtype="u4") +random_st.randint(0, 4294967296, dtype="u4") +random_st.randint(I_u4_high_open, dtype="u4") +random_st.randint(I_u4_low, I_u4_high_open, dtype="u4") +random_st.randint(0, I_u4_high_open, dtype="u4") + +random_st.randint(4294967296, dtype="uint32") +random_st.randint(0, 4294967296, dtype="uint32") +random_st.randint(I_u4_high_open, dtype="uint32") +random_st.randint(I_u4_low, I_u4_high_open, dtype="uint32") +random_st.randint(0, I_u4_high_open, dtype="uint32") + +random_st.randint(4294967296, dtype=np.uint32) +random_st.randint(0, 4294967296, dtype=np.uint32) +random_st.randint(I_u4_high_open, dtype=np.uint32) +random_st.randint(I_u4_low, I_u4_high_open, dtype=np.uint32) +random_st.randint(0, I_u4_high_open, dtype=np.uint32) + + +random_st.randint(18446744073709551616, dtype="u8") +random_st.randint(0, 18446744073709551616, dtype="u8") +random_st.randint(I_u8_high_open, dtype="u8") +random_st.randint(I_u8_low, I_u8_high_open, dtype="u8") +random_st.randint(0, I_u8_high_open, dtype="u8") + +random_st.randint(18446744073709551616, dtype="uint64") +random_st.randint(0, 18446744073709551616, dtype="uint64") +random_st.randint(I_u8_high_open, dtype="uint64") +random_st.randint(I_u8_low, I_u8_high_open, dtype="uint64") +random_st.randint(0, I_u8_high_open, dtype="uint64") + +random_st.randint(18446744073709551616, dtype=np.uint64) +random_st.randint(0, 18446744073709551616, dtype=np.uint64) +random_st.randint(I_u8_high_open, dtype=np.uint64) +random_st.randint(I_u8_low, I_u8_high_open, dtype=np.uint64) +random_st.randint(0, I_u8_high_open, dtype=np.uint64) + +random_st.randint(128, dtype="i1") +random_st.randint(-128, 128, dtype="i1") +random_st.randint(I_i1_high_open, dtype="i1") +random_st.randint(I_i1_low, I_i1_high_open, dtype="i1") +random_st.randint(-128, I_i1_high_open, dtype="i1") + +random_st.randint(128, dtype="int8") +random_st.randint(-128, 128, dtype="int8") +random_st.randint(I_i1_high_open, dtype="int8") +random_st.randint(I_i1_low, I_i1_high_open, dtype="int8") +random_st.randint(-128, I_i1_high_open, dtype="int8") + +random_st.randint(128, dtype=np.int8) +random_st.randint(-128, 128, dtype=np.int8) +random_st.randint(I_i1_high_open, dtype=np.int8) +random_st.randint(I_i1_low, I_i1_high_open, dtype=np.int8) +random_st.randint(-128, I_i1_high_open, dtype=np.int8) + +random_st.randint(32768, dtype="i2") +random_st.randint(-32768, 32768, dtype="i2") +random_st.randint(I_i2_high_open, dtype="i2") +random_st.randint(I_i2_low, I_i2_high_open, dtype="i2") +random_st.randint(-32768, I_i2_high_open, dtype="i2") +random_st.randint(32768, dtype="int16") +random_st.randint(-32768, 32768, dtype="int16") +random_st.randint(I_i2_high_open, dtype="int16") +random_st.randint(I_i2_low, I_i2_high_open, dtype="int16") +random_st.randint(-32768, I_i2_high_open, dtype="int16") +random_st.randint(32768, dtype=np.int16) +random_st.randint(-32768, 32768, dtype=np.int16) +random_st.randint(I_i2_high_open, dtype=np.int16) +random_st.randint(I_i2_low, I_i2_high_open, dtype=np.int16) +random_st.randint(-32768, I_i2_high_open, dtype=np.int16) + +random_st.randint(2147483648, dtype="i4") +random_st.randint(-2147483648, 2147483648, dtype="i4") +random_st.randint(I_i4_high_open, dtype="i4") +random_st.randint(I_i4_low, I_i4_high_open, dtype="i4") +random_st.randint(-2147483648, I_i4_high_open, dtype="i4") + +random_st.randint(2147483648, dtype="int32") +random_st.randint(-2147483648, 2147483648, dtype="int32") +random_st.randint(I_i4_high_open, dtype="int32") +random_st.randint(I_i4_low, I_i4_high_open, dtype="int32") +random_st.randint(-2147483648, I_i4_high_open, dtype="int32") + +random_st.randint(2147483648, dtype=np.int32) +random_st.randint(-2147483648, 2147483648, dtype=np.int32) +random_st.randint(I_i4_high_open, dtype=np.int32) +random_st.randint(I_i4_low, I_i4_high_open, dtype=np.int32) +random_st.randint(-2147483648, I_i4_high_open, dtype=np.int32) + +random_st.randint(9223372036854775808, dtype="i8") +random_st.randint(-9223372036854775808, 9223372036854775808, dtype="i8") +random_st.randint(I_i8_high_open, dtype="i8") +random_st.randint(I_i8_low, I_i8_high_open, dtype="i8") +random_st.randint(-9223372036854775808, I_i8_high_open, dtype="i8") + +random_st.randint(9223372036854775808, dtype="int64") +random_st.randint(-9223372036854775808, 9223372036854775808, dtype="int64") +random_st.randint(I_i8_high_open, dtype="int64") +random_st.randint(I_i8_low, I_i8_high_open, dtype="int64") +random_st.randint(-9223372036854775808, I_i8_high_open, dtype="int64") + +random_st.randint(9223372036854775808, dtype=np.int64) +random_st.randint(-9223372036854775808, 9223372036854775808, dtype=np.int64) +random_st.randint(I_i8_high_open, dtype=np.int64) +random_st.randint(I_i8_low, I_i8_high_open, dtype=np.int64) +random_st.randint(-9223372036854775808, I_i8_high_open, dtype=np.int64) + +bg: np.random.BitGenerator = random_st._bit_generator + +random_st.bytes(2) + +random_st.choice(5) +random_st.choice(5, 3) +random_st.choice(5, 3, replace=True) +random_st.choice(5, 3, p=[1 / 5] * 5) +random_st.choice(5, 3, p=[1 / 5] * 5, replace=False) + +random_st.choice(["pooh", "rabbit", "piglet", "Christopher"]) +random_st.choice(["pooh", "rabbit", "piglet", "Christopher"], 3) +random_st.choice(["pooh", "rabbit", "piglet", "Christopher"], 3, p=[1 / 4] * 4) +random_st.choice(["pooh", "rabbit", "piglet", "Christopher"], 3, replace=True) +random_st.choice(["pooh", "rabbit", "piglet", "Christopher"], 3, replace=False, p=np.array([1 / 8, 1 / 8, 1 / 2, 1 / 4])) + +random_st.dirichlet([0.5, 0.5]) +random_st.dirichlet(np.array([0.5, 0.5])) +random_st.dirichlet(np.array([0.5, 0.5]), size=3) + +random_st.multinomial(20, [1 / 6.0] * 6) +random_st.multinomial(20, np.array([0.5, 0.5])) +random_st.multinomial(20, [1 / 6.0] * 6, size=2) + +random_st.multivariate_normal([0.0], [[1.0]]) +random_st.multivariate_normal([0.0], np.array([[1.0]])) +random_st.multivariate_normal(np.array([0.0]), [[1.0]]) +random_st.multivariate_normal([0.0], np.array([[1.0]])) + +random_st.permutation(10) +random_st.permutation([1, 2, 3, 4]) +random_st.permutation(np.array([1, 2, 3, 4])) +random_st.permutation(D_2D) + +random_st.shuffle(np.arange(10)) +random_st.shuffle([1, 2, 3, 4, 5]) +random_st.shuffle(D_2D) + +np.random.RandomState(SEED_PCG64) +np.random.RandomState(0) +np.random.RandomState([0, 1, 2]) +random_st.__str__() +random_st.__repr__() +random_st_state = random_st.__getstate__() +random_st.__setstate__(random_st_state) +random_st.seed() +random_st.seed(1) +random_st.seed([0, 1]) +random_st_get_state = random_st.get_state() +random_st_get_state_legacy = random_st.get_state(legacy=True) +random_st.set_state(random_st_get_state) + +random_st.rand() +random_st.rand(1) +random_st.rand(1, 2) +random_st.randn() +random_st.randn(1) +random_st.randn(1, 2) +random_st.random_sample() +random_st.random_sample(1) +random_st.random_sample(size=(1, 2)) + +random_st.tomaxint() +random_st.tomaxint(1) +random_st.tomaxint((1,)) + +np.random.mtrand.set_bit_generator(SEED_PCG64) +np.random.mtrand.get_bit_generator() diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/recfunctions.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/recfunctions.py new file mode 100644 index 0000000000000000000000000000000000000000..586f0502b3660e13063b30d7128b3dab0558c3ba --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/recfunctions.py @@ -0,0 +1,164 @@ +"""These tests are based on the doctests from `numpy/lib/recfunctions.py`.""" + +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt +from numpy.lib import recfunctions as rfn + + +def test_recursive_fill_fields() -> None: + a: npt.NDArray[np.void] = np.array( + [(1, 10.0), (2, 20.0)], + dtype=[("A", np.int64), ("B", np.float64)], + ) + b = np.zeros((3,), dtype=a.dtype) + out = rfn.recursive_fill_fields(a, b) + assert_type(out, np.ndarray[tuple[int], np.dtype[np.void]]) + + +def test_get_names() -> None: + names: tuple[str | Any, ...] + names = rfn.get_names(np.empty((1,), dtype=[("A", int)]).dtype) + names = rfn.get_names(np.empty((1,), dtype=[("A", int), ("B", float)]).dtype) + + adtype = np.dtype([("a", int), ("b", [("b_a", int), ("b_b", int)])]) + names = rfn.get_names(adtype) + + +def test_get_names_flat() -> None: + names: tuple[str, ...] + names = rfn.get_names_flat(np.empty((1,), dtype=[("A", int)]).dtype) + names = rfn.get_names_flat(np.empty((1,), dtype=[("A", int), ("B", float)]).dtype) + + adtype = np.dtype([("a", int), ("b", [("b_a", int), ("b_b", int)])]) + names = rfn.get_names_flat(adtype) + + +def test_flatten_descr() -> None: + ndtype = np.dtype([("a", " None: + ndtype = np.dtype([ + ("A", int), + ("B", [("B_A", int), ("B_B", [("B_B_A", int), ("B_B_B", int)])]), + ]) + assert_type(rfn.get_fieldstructure(ndtype), dict[str, list[str]]) + + +def test_merge_arrays() -> None: + assert_type( + rfn.merge_arrays(( + np.ones((2,), np.int_), + np.ones((3,), np.float64), + )), + np.recarray[tuple[int], np.dtype[np.void]], + ) + + +def test_drop_fields() -> None: + ndtype = [("a", np.int64), ("b", [("b_a", np.double), ("b_b", np.int64)])] + a = np.ones((3,), dtype=ndtype) + + assert_type( + rfn.drop_fields(a, "a"), + np.ndarray[tuple[int], np.dtype[np.void]], + ) + assert_type( + rfn.drop_fields(a, "a", asrecarray=True), + np.rec.recarray[tuple[int], np.dtype[np.void]], + ) + assert_type( + rfn.rec_drop_fields(a, "a"), + np.rec.recarray[tuple[int], np.dtype[np.void]], + ) + + +def test_rename_fields() -> None: + ndtype = [("a", np.int64), ("b", [("b_a", np.double), ("b_b", np.int64)])] + a = np.ones((3,), dtype=ndtype) + + assert_type( + rfn.rename_fields(a, {"a": "A", "b_b": "B_B"}), + np.ndarray[tuple[int], np.dtype[np.void]], + ) + + +def test_repack_fields() -> None: + dt: np.dtype[np.void] = np.dtype("u1, None: + a = np.zeros(4, dtype=[("a", "i4"), ("b", "f4,u2"), ("c", "f4", 2)]) + assert_type(rfn.structured_to_unstructured(a), npt.NDArray[Any]) + + +def unstructured_to_structured() -> None: + dt: np.dtype[np.void] = np.dtype([("a", "i4"), ("b", "f4,u2"), ("c", "f4", 2)]) + a = np.arange(20, dtype=np.int32).reshape((4, 5)) + assert_type(rfn.unstructured_to_structured(a, dt), npt.NDArray[np.void]) + + +def test_apply_along_fields() -> None: + b = np.ones(4, dtype=[("x", "i4"), ("y", "f4"), ("z", "f8")]) + assert_type( + rfn.apply_along_fields(np.mean, b), + np.ndarray[tuple[int], np.dtype[np.void]], + ) + + +def test_assign_fields_by_name() -> None: + b = np.ones(4, dtype=[("x", "i4"), ("y", "f4"), ("z", "f8")]) + assert_type( + rfn.apply_along_fields(np.mean, b), + np.ndarray[tuple[int], np.dtype[np.void]], + ) + + +def test_require_fields() -> None: + a = np.ones(4, dtype=[("a", "i4"), ("b", "f8"), ("c", "u1")]) + assert_type( + rfn.require_fields(a, [("b", "f4"), ("c", "u1")]), + np.ndarray[tuple[int], np.dtype[np.void]], + ) + + +def test_stack_arrays() -> None: + x = np.zeros((2,), np.int32) + assert_type( + rfn.stack_arrays(x), + np.ndarray[tuple[int], np.dtype[np.int32]], + ) + + z = np.ones((2,), [("A", "|S3"), ("B", float)]) + zz = np.ones((2,), [("A", "|S3"), ("B", np.float64), ("C", np.float64)]) + assert_type( + rfn.stack_arrays((z, zz)), + np.ma.MaskedArray[tuple[Any, ...], np.dtype[np.void]], + ) + + +def test_find_duplicates() -> None: + ndtype = np.dtype([("a", int)]) + + a = np.ma.ones(7).view(ndtype) + assert_type( + rfn.find_duplicates(a), + np.ma.MaskedArray[tuple[int], np.dtype[np.void]], + ) + assert_type( + rfn.find_duplicates(a, ignoremask=True, return_index=True), + tuple[ + np.ma.MaskedArray[tuple[int], np.dtype[np.void]], + np.ndarray[tuple[int], np.dtype[np.int_]], + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/scalars.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/scalars.py new file mode 100644 index 0000000000000000000000000000000000000000..eeb707b255e103b481e846870b3f9a649e7d8f35 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/scalars.py @@ -0,0 +1,249 @@ +import datetime as dt + +import pytest + +import numpy as np + +b = np.bool() +b_ = np.bool_() +u8 = np.uint64() +i8 = np.int64() +f8 = np.float64() +c16 = np.complex128() +U = np.str_() +S = np.bytes_() + + +# Construction +class D: + def __index__(self) -> int: + return 0 + + +class C: + def __complex__(self) -> complex: + return 3j + + +class B: + def __int__(self) -> int: + return 4 + + +class A: + def __float__(self) -> float: + return 4.0 + + +np.complex64(3j) +np.complex64(A()) +np.complex64(C()) +np.complex128(3j) +np.complex128(C()) +np.complex128(None) +np.complex64("1.2") +np.complex128(b"2j") + +np.int8(4) +np.int16(3.4) +np.int32(4) +np.int64(-1) +np.uint8(B()) +np.uint32() +np.int32("1") +np.int64(b"2") + +np.float16(A()) +np.float32(16) +np.float64(3.0) +np.float64(None) +np.float32("1") +np.float16(b"2.5") + +np.uint64(D()) +np.float32(D()) +np.complex64(D()) + +np.bytes_(b"hello") +np.bytes_("hello", 'utf-8') +np.bytes_("hello", encoding='utf-8') +np.str_("hello") +np.str_(b"hello", 'utf-8') +np.str_(b"hello", encoding='utf-8') + +# Array-ish semantics +np.int8().real +np.int16().imag +np.int32().data +np.int64().flags + +np.uint8().itemsize * 2 +np.uint16().ndim + 1 +np.uint32().strides +np.uint64().shape + +# Time structures +np.datetime64() +np.datetime64(0, "D") +np.datetime64(0, b"D") +np.datetime64(0, ('ms', 3)) +np.datetime64("2019") +np.datetime64(b"2019") +np.datetime64("2019", "D") +np.datetime64("2019", "us") +np.datetime64("2019", "as") +np.datetime64(np.datetime64()) +np.datetime64(np.datetime64()) +np.datetime64(dt.datetime(2000, 5, 3)) +np.datetime64(dt.datetime(2000, 5, 3), "D") +np.datetime64(dt.datetime(2000, 5, 3), "us") +np.datetime64(dt.datetime(2000, 5, 3), "as") +np.datetime64(dt.date(2000, 5, 3)) +np.datetime64(dt.date(2000, 5, 3), "D") +np.datetime64(dt.date(2000, 5, 3), "us") +np.datetime64(dt.date(2000, 5, 3), "as") +np.datetime64(None) +np.datetime64(None, "D") + +np.timedelta64() +np.timedelta64(0) +np.timedelta64(0, "D") +np.timedelta64(0, ('ms', 3)) +np.timedelta64(0, b"D") +np.timedelta64("3") +np.timedelta64(b"5") +np.timedelta64(np.timedelta64(2)) +np.timedelta64(dt.timedelta(2)) +np.timedelta64(None) +np.timedelta64(None, "D") + +np.void(1) +np.void(np.int64(1)) +np.void(True) +np.void(np.bool(True)) +np.void(b"test") +np.void(np.bytes_("test")) +np.void(object(), [("a", "O"), ("b", "O")]) +np.void(object(), dtype=[("a", "O"), ("b", "O")]) + +# Protocols +i8 = np.int64() +u8 = np.uint64() +f8 = np.float64() +c16 = np.complex128() +b = np.bool() +td = np.timedelta64() +U = np.str_("1") +S = np.bytes_("1") +AR = np.array(1, dtype=np.float64) + +int(i8) +int(u8) +int(f8) +int(b) +int(td) +int(U) +int(S) +int(AR) +with pytest.warns(np.exceptions.ComplexWarning): + int(c16) + +float(i8) +float(u8) +float(f8) +float(b_) +float(td) +float(U) +float(S) +float(AR) +with pytest.warns(np.exceptions.ComplexWarning): + float(c16) + +complex(i8) +complex(u8) +complex(f8) +complex(c16) +complex(b_) +complex(td) +complex(U) +complex(AR) + + +# Misc +c16.dtype +c16.real +c16.imag +c16.real.real +c16.real.imag +c16.ndim +c16.size +c16.itemsize +c16.shape +c16.strides +c16.squeeze() +c16.byteswap() +c16.transpose() + +# Aliases +np.byte() +np.short() +np.intc() +np.intp() +np.int_() +np.longlong() + +np.ubyte() +np.ushort() +np.uintc() +np.uintp() +np.uint() +np.ulonglong() + +np.half() +np.single() +np.double() +np.longdouble() + +np.csingle() +np.cdouble() +np.clongdouble() + +b.item() +i8.item() +u8.item() +f8.item() +c16.item() +U.item() +S.item() + +b.tolist() +i8.tolist() +u8.tolist() +f8.tolist() +c16.tolist() +U.tolist() +S.tolist() + +b.ravel() +i8.ravel() +u8.ravel() +f8.ravel() +c16.ravel() +U.ravel() +S.ravel() + +b.flatten() +i8.flatten() +u8.flatten() +f8.flatten() +c16.flatten() +U.flatten() +S.flatten() + +b.reshape(1) +i8.reshape(1) +u8.reshape(1) +f8.reshape(1) +c16.reshape(1) +U.reshape(1) +S.reshape(1) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/shape.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/shape.py new file mode 100644 index 0000000000000000000000000000000000000000..e3b497bc031065fb7ec147eccc910e9ce78b043e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/shape.py @@ -0,0 +1,19 @@ +from typing import Any, NamedTuple + +import numpy as np + + +# Subtype of tuple[int, int] +class XYGrid(NamedTuple): + x_axis: int + y_axis: int + +# Test variance of _ShapeT_co +def accepts_2d(a: np.ndarray[tuple[int, int], Any]) -> None: + return None + + +accepts_2d(np.empty(XYGrid(2, 2))) +accepts_2d(np.zeros(XYGrid(2, 2), dtype=int)) +accepts_2d(np.ones(XYGrid(2, 2), dtype=int)) +accepts_2d(np.full(XYGrid(2, 2), fill_value=5, dtype=int)) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/simple.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/simple.py new file mode 100644 index 0000000000000000000000000000000000000000..003e9ee58bb18ad4df507379c3859ebf11dbce50 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/simple.py @@ -0,0 +1,170 @@ +"""Simple expression that should pass with mypy.""" +import operator +from collections.abc import Iterable + +import numpy as np +import numpy.typing as npt + +# Basic checks +array = np.array([1, 2]) + + +def ndarray_func(x: npt.NDArray[np.float64]) -> npt.NDArray[np.float64]: + return x + + +ndarray_func(np.array([1, 2], dtype=np.float64)) +array == 1 +array.dtype == float + +# Dtype construction +np.dtype(float) +np.dtype(np.float64) +np.dtype(None) +np.dtype("float64") +np.dtype(np.dtype(float)) +np.dtype(("U", 10)) +np.dtype((np.int32, (2, 2))) +# Define the arguments on the previous line to prevent bidirectional +# type inference in mypy from broadening the types. +two_tuples_dtype = [("R", "u1"), ("G", "u1"), ("B", "u1")] +np.dtype(two_tuples_dtype) + +three_tuples_dtype = [("R", "u1", 2)] +np.dtype(three_tuples_dtype) + +mixed_tuples_dtype = [("R", "u1"), ("G", np.str_, 1)] +np.dtype(mixed_tuples_dtype) + +shape_tuple_dtype = [("R", "u1", (2, 2))] +np.dtype(shape_tuple_dtype) + +shape_like_dtype = [("R", "u1", (2, 2)), ("G", np.str_, 1)] +np.dtype(shape_like_dtype) + +object_dtype = [("field1", object)] +np.dtype(object_dtype) + +np.dtype((np.int32, (np.int8, 4))) + +# Dtype comparison +np.dtype(float) == float +np.dtype(float) != np.float64 +np.dtype(float) < None +np.dtype(float) <= "float64" +np.dtype(float) > np.dtype(float) +np.dtype(float) >= np.dtype(("U", 10)) + +# Iteration and indexing +def iterable_func(x: Iterable[object]) -> Iterable[object]: + return x + + +iterable_func(array) +list(array) +iter(array) +zip(array, array) +array[1] +array[:] +array[...] +array[:] = 0 + +array_2d = np.ones((3, 3)) +array_2d[:2, :2] +array_2d[:2, :2] = 0 +array_2d[..., 0] +array_2d[..., 0] = 2 +array_2d[-1, -1] = None + +array_obj = np.zeros(1, dtype=np.object_) +array_obj[0] = slice(None) + +# Other special methods +len(array) +str(array) +array_scalar = np.array(1) +int(array_scalar) +float(array_scalar) +complex(array_scalar) +bytes(array_scalar) +operator.index(array_scalar) +bool(array_scalar) + +# comparisons +array < 1 +array <= 1 +array == 1 +array != 1 +array > 1 +array >= 1 +1 < array +1 <= array +1 == array +1 != array +1 > array +1 >= array + +# binary arithmetic +array + 1 +1 + array +array += 1 + +array - 1 +1 - array +array -= 1 + +array * 1 +1 * array +array *= 1 + +nonzero_array = np.array([1, 2]) +array / 1 +1 / nonzero_array +float_array = np.array([1.0, 2.0]) +float_array /= 1 + +array // 1 +1 // nonzero_array +array //= 1 + +array % 1 +1 % nonzero_array +array %= 1 + +divmod(array, 1) +divmod(1, nonzero_array) + +array ** 1 +1 ** array +array **= 1 + +array << 1 +1 << array +array <<= 1 + +array >> 1 +1 >> array +array >>= 1 + +array & 1 +1 & array +array &= 1 + +array ^ 1 +1 ^ array +array ^= 1 + +array | 1 +1 | array +array |= 1 + +# unary arithmetic +-array ++array +abs(array) +~array + +# Other methods +array.transpose() + +array @ array diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ufunc_config.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ufunc_config.py new file mode 100644 index 0000000000000000000000000000000000000000..778e1b57f7e3831464f0bc9ba37e4baddcdf49d8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ufunc_config.py @@ -0,0 +1,64 @@ +"""Typing tests for `numpy._core._ufunc_config`.""" + +import numpy as np + + +def func1(a: str, b: int) -> None: + return None + + +def func2(a: str, b: int, c: float = 1.0) -> None: + return None + + +def func3(a: str, b: int) -> int: + return 0 + + +class Write1: + def write(self, a: str) -> None: + return None + + +class Write2: + def write(self, a: str, b: int = 1) -> None: + return None + + +class Write3: + def write(self, a: str) -> int: + return 0 + + +_err_default = np.geterr() +_bufsize_default = np.getbufsize() +_errcall_default = np.geterrcall() + +try: + np.seterr(all=None) + np.seterr(divide="ignore") + np.seterr(over="warn") + np.seterr(under="call") + np.seterr(invalid="raise") + np.geterr() + + np.setbufsize(4096) + np.getbufsize() + + np.seterrcall(func1) + np.seterrcall(func2) + np.seterrcall(func3) + np.seterrcall(Write1()) + np.seterrcall(Write2()) + np.seterrcall(Write3()) + np.geterrcall() + + with np.errstate(call=func1, all="call"): + pass + with np.errstate(call=Write1(), divide="log", over="log"): + pass + +finally: + np.seterr(**_err_default) + np.setbufsize(_bufsize_default) + np.seterrcall(_errcall_default) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ufunclike.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ufunclike.py new file mode 100644 index 0000000000000000000000000000000000000000..7e556d10bef7badff9fcf5c36a4d229b9ef63297 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ufunclike.py @@ -0,0 +1,52 @@ +from __future__ import annotations + +from typing import Any + +import numpy as np + + +class Object: + def __ceil__(self) -> Object: + return self + + def __floor__(self) -> Object: + return self + + def __trunc__(self) -> Object: + return self + + def __ge__(self, value: object) -> bool: + return True + + def __array__(self, dtype: np.typing.DTypeLike | None = None, + copy: bool | None = None) -> np.ndarray[Any, np.dtype[np.object_]]: + ret = np.empty((), dtype=object) + ret[()] = self + return ret + + +AR_LIKE_b = [True, True, False] +AR_LIKE_u = [np.uint32(1), np.uint32(2), np.uint32(3)] +AR_LIKE_i = [1, 2, 3] +AR_LIKE_f = [1.0, 2.0, 3.0] +AR_LIKE_O = [Object(), Object(), Object()] +AR_U: np.ndarray[Any, np.dtype[np.str_]] = np.zeros(3, dtype="U5") + +np.fix(AR_LIKE_b) # type: ignore[deprecated] +np.fix(AR_LIKE_u) # type: ignore[deprecated] +np.fix(AR_LIKE_i) # type: ignore[deprecated] +np.fix(AR_LIKE_f) # type: ignore[deprecated] +np.fix(AR_LIKE_O) # type: ignore[deprecated] +np.fix(AR_LIKE_f, out=AR_U) # type: ignore[deprecated] + +np.isposinf(AR_LIKE_b) +np.isposinf(AR_LIKE_u) +np.isposinf(AR_LIKE_i) +np.isposinf(AR_LIKE_f) +np.isposinf(AR_LIKE_f, out=AR_U) + +np.isneginf(AR_LIKE_b) +np.isneginf(AR_LIKE_u) +np.isneginf(AR_LIKE_i) +np.isneginf(AR_LIKE_f) +np.isneginf(AR_LIKE_f, out=AR_U) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ufuncs.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ufuncs.py new file mode 100644 index 0000000000000000000000000000000000000000..dbc61bb0b17b594865bc909787798238c5b32bf5 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/ufuncs.py @@ -0,0 +1,16 @@ +import numpy as np + +np.sin(1) +np.sin([1, 2, 3]) +np.sin(1, out=np.empty(1)) +np.matmul(np.ones((2, 2, 2)), np.ones((2, 2, 2)), axes=[(0, 1), (0, 1), (0, 1)]) +np.sin(1, signature="D->D") +# NOTE: `np.generic` subclasses are not guaranteed to support addition; +# re-enable this we can infer the exact return type of `np.sin(...)`. +# +# np.sin(1) + np.sin(1) +np.sin.types[0] +np.sin.__name__ +np.sin.__doc__ + +np.abs(np.array([1])) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/warnings_and_errors.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/warnings_and_errors.py new file mode 100644 index 0000000000000000000000000000000000000000..c351afb084c57b2d1264a3ff020ed1e63703a623 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/pass/warnings_and_errors.py @@ -0,0 +1,6 @@ +import numpy.exceptions as ex + +ex.AxisError("test") +ex.AxisError(1, ndim=2) +ex.AxisError(1, ndim=2, msg_prefix="error") +ex.AxisError(1, ndim=2, msg_prefix=None) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/arithmetic.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/arithmetic.pyi new file mode 100644 index 0000000000000000000000000000000000000000..491bce43fdaef328baebc8d3f3e800079098e959 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/arithmetic.pyi @@ -0,0 +1,719 @@ +import datetime as dt +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt +from numpy._typing import _64Bit, _128Bit + +b: bool +c: complex +f: float +i: int + +c16: np.complex128 +c8: np.complex64 + +# Can't directly import `np.float128` as it is not available on all platforms +f16: np.floating[_128Bit] +f8: np.float64 +f4: np.float32 + +i8: np.int64 +i4: np.int32 + +u8: np.uint64 +u4: np.uint32 + +b_: np.bool + +M8: np.datetime64 +M8_none: np.datetime64[None] +M8_date: np.datetime64[dt.date] +M8_time: np.datetime64[dt.datetime] +M8_int: np.datetime64[int] +date: dt.date +time: dt.datetime + +m8: np.timedelta64 +m8_none: np.timedelta64[None] +m8_int: np.timedelta64[int] +m8_delta: np.timedelta64[dt.timedelta] +delta: dt.timedelta + +AR_b: npt.NDArray[np.bool] +AR_u: npt.NDArray[np.uint32] +AR_i: npt.NDArray[np.int64] +AR_f: npt.NDArray[np.float64] +AR_c: npt.NDArray[np.complex128] +AR_m: npt.NDArray[np.timedelta64] +AR_M: npt.NDArray[np.datetime64] +AR_O: npt.NDArray[np.object_] +AR_S: npt.NDArray[np.bytes_] +AR_U: npt.NDArray[np.str_] +AR_T: np.ndarray[tuple[Any, ...], np.dtypes.StringDType] +AR_floating: npt.NDArray[np.floating] +AR_number: npt.NDArray[np.number] +AR_Any: npt.NDArray[Any] + +AR_LIKE_b: list[bool] +AR_LIKE_u: list[np.uint32] +AR_LIKE_i: list[int] +AR_LIKE_f: list[float] +AR_LIKE_c: list[complex] +AR_LIKE_m: list[np.timedelta64] +AR_LIKE_M: list[np.datetime64] +AR_LIKE_O: list[np.object_] + +# Array subtraction + +assert_type(AR_number - AR_number, npt.NDArray[np.number]) + +assert_type(AR_b - AR_LIKE_u, npt.NDArray[np.uint32]) +assert_type(AR_b - AR_LIKE_i, npt.NDArray[np.signedinteger]) +assert_type(AR_b - AR_LIKE_f, npt.NDArray[np.floating]) +assert_type(AR_b - AR_LIKE_c, npt.NDArray[np.complexfloating]) +assert_type(AR_b - AR_LIKE_m, npt.NDArray[np.timedelta64]) +assert_type(AR_b - AR_LIKE_O, Any) + +assert_type(AR_LIKE_u - AR_b, npt.NDArray[np.uint32]) +assert_type(AR_LIKE_i - AR_b, npt.NDArray[np.signedinteger]) +assert_type(AR_LIKE_f - AR_b, npt.NDArray[np.floating]) +assert_type(AR_LIKE_c - AR_b, npt.NDArray[np.complexfloating]) +assert_type(AR_LIKE_m - AR_b, npt.NDArray[np.timedelta64]) +assert_type(AR_LIKE_M - AR_b, npt.NDArray[np.datetime64]) +assert_type(AR_LIKE_O - AR_b, Any) + +assert_type(AR_u - AR_LIKE_b, npt.NDArray[np.uint32]) +assert_type(AR_u - AR_LIKE_u, npt.NDArray[np.unsignedinteger]) +assert_type(AR_u - AR_LIKE_i, npt.NDArray[np.signedinteger]) +assert_type(AR_u - AR_LIKE_f, npt.NDArray[np.floating]) +assert_type(AR_u - AR_LIKE_c, npt.NDArray[np.complexfloating]) +assert_type(AR_u - AR_LIKE_m, npt.NDArray[np.timedelta64]) +assert_type(AR_u - AR_LIKE_O, Any) + +assert_type(AR_LIKE_b - AR_u, npt.NDArray[np.uint32]) +assert_type(AR_LIKE_u - AR_u, npt.NDArray[np.unsignedinteger]) +assert_type(AR_LIKE_i - AR_u, npt.NDArray[np.signedinteger]) +assert_type(AR_LIKE_f - AR_u, npt.NDArray[np.floating]) +assert_type(AR_LIKE_c - AR_u, npt.NDArray[np.complexfloating]) +assert_type(AR_LIKE_m - AR_u, npt.NDArray[np.timedelta64]) +assert_type(AR_LIKE_M - AR_u, npt.NDArray[np.datetime64]) +assert_type(AR_LIKE_O - AR_u, Any) + +assert_type(AR_i - AR_LIKE_b, npt.NDArray[np.int64]) +assert_type(AR_i - AR_LIKE_u, npt.NDArray[np.signedinteger]) +assert_type(AR_i - AR_LIKE_i, npt.NDArray[np.signedinteger]) +assert_type(AR_i - AR_LIKE_f, npt.NDArray[np.floating]) +assert_type(AR_i - AR_LIKE_c, npt.NDArray[np.complexfloating]) +assert_type(AR_i - AR_LIKE_m, npt.NDArray[np.timedelta64]) +assert_type(AR_i - AR_LIKE_O, Any) + +assert_type(AR_LIKE_b - AR_i, npt.NDArray[np.int64]) +assert_type(AR_LIKE_u - AR_i, npt.NDArray[np.signedinteger]) +assert_type(AR_LIKE_i - AR_i, npt.NDArray[np.signedinteger]) +assert_type(AR_LIKE_f - AR_i, npt.NDArray[np.floating]) +assert_type(AR_LIKE_c - AR_i, npt.NDArray[np.complexfloating]) +assert_type(AR_LIKE_m - AR_i, npt.NDArray[np.timedelta64]) +assert_type(AR_LIKE_M - AR_i, npt.NDArray[np.datetime64]) +assert_type(AR_LIKE_O - AR_i, Any) + +assert_type(AR_f - AR_LIKE_b, npt.NDArray[np.float64]) +assert_type(AR_f - AR_LIKE_u, npt.NDArray[np.float64]) +assert_type(AR_f - AR_LIKE_i, npt.NDArray[np.float64]) +assert_type(AR_f - AR_LIKE_f, npt.NDArray[np.float64]) +assert_type(AR_f - AR_LIKE_c, npt.NDArray[np.complexfloating]) +assert_type(AR_f - AR_LIKE_O, Any) + +assert_type(AR_LIKE_b - AR_f, npt.NDArray[np.float64]) +assert_type(AR_LIKE_u - AR_f, npt.NDArray[np.float64]) +assert_type(AR_LIKE_i - AR_f, npt.NDArray[np.float64]) +assert_type(AR_LIKE_f - AR_f, npt.NDArray[np.float64]) +assert_type(AR_LIKE_c - AR_f, npt.NDArray[np.complexfloating]) +assert_type(AR_LIKE_O - AR_f, Any) + +assert_type(AR_c - AR_LIKE_b, npt.NDArray[np.complex128]) +assert_type(AR_c - AR_LIKE_u, npt.NDArray[np.complex128]) +assert_type(AR_c - AR_LIKE_i, npt.NDArray[np.complex128]) +assert_type(AR_c - AR_LIKE_f, npt.NDArray[np.complex128]) +assert_type(AR_c - AR_LIKE_c, npt.NDArray[np.complex128]) +assert_type(AR_c - AR_LIKE_O, Any) + +assert_type(AR_LIKE_b - AR_c, npt.NDArray[np.complex128]) +assert_type(AR_LIKE_u - AR_c, npt.NDArray[np.complex128]) +assert_type(AR_LIKE_i - AR_c, npt.NDArray[np.complex128]) +assert_type(AR_LIKE_f - AR_c, npt.NDArray[np.complex128]) +assert_type(AR_LIKE_c - AR_c, npt.NDArray[np.complex128]) +assert_type(AR_LIKE_O - AR_c, Any) + +assert_type(AR_m - AR_LIKE_b, npt.NDArray[np.timedelta64]) +assert_type(AR_m - AR_LIKE_u, npt.NDArray[np.timedelta64]) +assert_type(AR_m - AR_LIKE_i, npt.NDArray[np.timedelta64]) +assert_type(AR_m - AR_LIKE_m, npt.NDArray[np.timedelta64]) +assert_type(AR_m - AR_LIKE_O, Any) + +assert_type(AR_LIKE_b - AR_m, npt.NDArray[np.timedelta64]) +assert_type(AR_LIKE_u - AR_m, npt.NDArray[np.timedelta64]) +assert_type(AR_LIKE_i - AR_m, npt.NDArray[np.timedelta64]) +assert_type(AR_LIKE_m - AR_m, npt.NDArray[np.timedelta64]) +assert_type(AR_LIKE_M - AR_m, npt.NDArray[np.datetime64]) +assert_type(AR_LIKE_O - AR_m, Any) + +assert_type(AR_M - AR_LIKE_b, npt.NDArray[np.datetime64]) +assert_type(AR_M - AR_LIKE_u, npt.NDArray[np.datetime64]) +assert_type(AR_M - AR_LIKE_i, npt.NDArray[np.datetime64]) +assert_type(AR_M - AR_LIKE_m, npt.NDArray[np.datetime64]) +assert_type(AR_M - AR_LIKE_M, npt.NDArray[np.timedelta64]) +assert_type(AR_M - AR_LIKE_O, Any) + +assert_type(AR_LIKE_M - AR_M, npt.NDArray[np.timedelta64]) +assert_type(AR_LIKE_O - AR_M, Any) + +assert_type(AR_O - AR_LIKE_b, Any) +assert_type(AR_O - AR_LIKE_u, Any) +assert_type(AR_O - AR_LIKE_i, Any) +assert_type(AR_O - AR_LIKE_f, Any) +assert_type(AR_O - AR_LIKE_c, Any) +assert_type(AR_O - AR_LIKE_m, Any) +assert_type(AR_O - AR_LIKE_M, Any) +assert_type(AR_O - AR_LIKE_O, Any) + +assert_type(AR_LIKE_b - AR_O, Any) +assert_type(AR_LIKE_u - AR_O, Any) +assert_type(AR_LIKE_i - AR_O, Any) +assert_type(AR_LIKE_f - AR_O, Any) +assert_type(AR_LIKE_c - AR_O, Any) +assert_type(AR_LIKE_m - AR_O, Any) +assert_type(AR_LIKE_M - AR_O, Any) +assert_type(AR_LIKE_O - AR_O, Any) + +# Array "true" division + +assert_type(AR_f / b, npt.NDArray[np.float64]) +assert_type(AR_f / i, npt.NDArray[np.float64]) +assert_type(AR_f / f, npt.NDArray[np.float64]) + +assert_type(b / AR_f, npt.NDArray[np.float64]) +assert_type(i / AR_f, npt.NDArray[np.float64]) +assert_type(f / AR_f, npt.NDArray[np.float64]) + +assert_type(AR_b / AR_LIKE_b, npt.NDArray[np.float64]) +assert_type(AR_b / AR_LIKE_u, npt.NDArray[np.float64]) +assert_type(AR_b / AR_LIKE_i, npt.NDArray[np.float64]) +assert_type(AR_b / AR_LIKE_f, npt.NDArray[np.float64]) +assert_type(AR_b / AR_LIKE_O, Any) + +assert_type(AR_LIKE_b / AR_b, npt.NDArray[np.float64]) +assert_type(AR_LIKE_u / AR_b, npt.NDArray[np.float64]) +assert_type(AR_LIKE_i / AR_b, npt.NDArray[np.float64]) +assert_type(AR_LIKE_f / AR_b, npt.NDArray[np.float64]) +assert_type(AR_LIKE_O / AR_b, Any) + +assert_type(AR_u / AR_LIKE_b, npt.NDArray[np.float64]) +assert_type(AR_u / AR_LIKE_u, npt.NDArray[np.float64]) +assert_type(AR_u / AR_LIKE_i, npt.NDArray[np.float64]) +assert_type(AR_u / AR_LIKE_f, npt.NDArray[np.float64]) +assert_type(AR_u / AR_LIKE_O, Any) + +assert_type(AR_LIKE_b / AR_u, npt.NDArray[np.float64]) +assert_type(AR_LIKE_u / AR_u, npt.NDArray[np.float64]) +assert_type(AR_LIKE_i / AR_u, npt.NDArray[np.float64]) +assert_type(AR_LIKE_f / AR_u, npt.NDArray[np.float64]) +assert_type(AR_LIKE_m / AR_u, npt.NDArray[np.timedelta64]) +assert_type(AR_LIKE_O / AR_u, Any) + +assert_type(AR_i / AR_LIKE_b, npt.NDArray[np.float64]) +assert_type(AR_i / AR_LIKE_u, npt.NDArray[np.float64]) +assert_type(AR_i / AR_LIKE_i, npt.NDArray[np.float64]) +assert_type(AR_i / AR_LIKE_f, npt.NDArray[np.float64]) +assert_type(AR_i / AR_LIKE_O, Any) + +assert_type(AR_LIKE_b / AR_i, npt.NDArray[np.float64]) +assert_type(AR_LIKE_u / AR_i, npt.NDArray[np.float64]) +assert_type(AR_LIKE_i / AR_i, npt.NDArray[np.float64]) +assert_type(AR_LIKE_f / AR_i, npt.NDArray[np.float64]) +assert_type(AR_LIKE_m / AR_i, npt.NDArray[np.timedelta64]) +assert_type(AR_LIKE_O / AR_i, Any) + +assert_type(AR_f / AR_LIKE_b, npt.NDArray[np.float64]) +assert_type(AR_f / AR_LIKE_u, npt.NDArray[np.float64]) +assert_type(AR_f / AR_LIKE_i, npt.NDArray[np.float64]) +assert_type(AR_f / AR_LIKE_f, npt.NDArray[np.float64]) +assert_type(AR_f / AR_LIKE_O, Any) + +assert_type(AR_LIKE_b / AR_f, npt.NDArray[np.float64]) +assert_type(AR_LIKE_u / AR_f, npt.NDArray[np.float64]) +assert_type(AR_LIKE_i / AR_f, npt.NDArray[np.float64]) +assert_type(AR_LIKE_f / AR_f, npt.NDArray[np.float64]) +assert_type(AR_LIKE_m / AR_f, npt.NDArray[np.timedelta64]) +assert_type(AR_LIKE_O / AR_f, Any) + +assert_type(AR_m / AR_LIKE_u, npt.NDArray[np.timedelta64]) +assert_type(AR_m / AR_LIKE_i, npt.NDArray[np.timedelta64]) +assert_type(AR_m / AR_LIKE_f, npt.NDArray[np.timedelta64]) +assert_type(AR_m / AR_LIKE_m, npt.NDArray[np.float64]) +assert_type(AR_m / AR_LIKE_O, Any) + +assert_type(AR_LIKE_m / AR_m, npt.NDArray[np.float64]) +assert_type(AR_LIKE_O / AR_m, Any) + +assert_type(AR_O / AR_LIKE_b, Any) +assert_type(AR_O / AR_LIKE_u, Any) +assert_type(AR_O / AR_LIKE_i, Any) +assert_type(AR_O / AR_LIKE_f, Any) +assert_type(AR_O / AR_LIKE_m, Any) +assert_type(AR_O / AR_LIKE_M, Any) +assert_type(AR_O / AR_LIKE_O, Any) + +assert_type(AR_LIKE_b / AR_O, Any) +assert_type(AR_LIKE_u / AR_O, Any) +assert_type(AR_LIKE_i / AR_O, Any) +assert_type(AR_LIKE_f / AR_O, Any) +assert_type(AR_LIKE_m / AR_O, Any) +assert_type(AR_LIKE_M / AR_O, Any) +assert_type(AR_LIKE_O / AR_O, Any) + +# Array floor division + +assert_type(AR_b // AR_LIKE_b, npt.NDArray[np.int8]) +assert_type(AR_b // AR_LIKE_u, npt.NDArray[np.uint32]) +assert_type(AR_b // AR_LIKE_i, npt.NDArray[np.signedinteger]) +assert_type(AR_b // AR_LIKE_f, npt.NDArray[np.floating]) +assert_type(AR_b // AR_LIKE_O, Any) + +assert_type(AR_LIKE_b // AR_b, npt.NDArray[np.int8]) +assert_type(AR_LIKE_u // AR_b, npt.NDArray[np.uint32]) +assert_type(AR_LIKE_i // AR_b, npt.NDArray[np.signedinteger]) +assert_type(AR_LIKE_f // AR_b, npt.NDArray[np.floating]) +assert_type(AR_LIKE_O // AR_b, Any) + +assert_type(AR_u // AR_LIKE_b, npt.NDArray[np.uint32]) +assert_type(AR_u // AR_LIKE_u, npt.NDArray[np.unsignedinteger]) +assert_type(AR_u // AR_LIKE_i, npt.NDArray[np.signedinteger]) +assert_type(AR_u // AR_LIKE_f, npt.NDArray[np.floating]) +assert_type(AR_u // AR_LIKE_O, Any) + +assert_type(AR_LIKE_b // AR_u, npt.NDArray[np.uint32]) +assert_type(AR_LIKE_u // AR_u, npt.NDArray[np.unsignedinteger]) +assert_type(AR_LIKE_i // AR_u, npt.NDArray[np.signedinteger]) +assert_type(AR_LIKE_f // AR_u, npt.NDArray[np.floating]) +assert_type(AR_LIKE_m // AR_u, npt.NDArray[np.timedelta64]) +assert_type(AR_LIKE_O // AR_u, Any) + +assert_type(AR_i // AR_LIKE_b, npt.NDArray[np.int64]) +assert_type(AR_i // AR_LIKE_u, npt.NDArray[np.signedinteger]) +assert_type(AR_i // AR_LIKE_i, npt.NDArray[np.signedinteger]) +assert_type(AR_i // AR_LIKE_f, npt.NDArray[np.floating]) +assert_type(AR_i // AR_LIKE_O, Any) + +assert_type(AR_LIKE_b // AR_i, npt.NDArray[np.int64]) +assert_type(AR_LIKE_u // AR_i, npt.NDArray[np.signedinteger]) +assert_type(AR_LIKE_i // AR_i, npt.NDArray[np.signedinteger]) +assert_type(AR_LIKE_f // AR_i, npt.NDArray[np.floating]) +assert_type(AR_LIKE_m // AR_i, npt.NDArray[np.timedelta64]) +assert_type(AR_LIKE_O // AR_i, Any) + +assert_type(AR_f // AR_LIKE_b, npt.NDArray[np.float64]) +assert_type(AR_f // AR_LIKE_u, npt.NDArray[np.float64]) +assert_type(AR_f // AR_LIKE_i, npt.NDArray[np.float64]) +assert_type(AR_f // AR_LIKE_f, npt.NDArray[np.float64]) +assert_type(AR_f // AR_LIKE_O, Any) + +assert_type(AR_LIKE_b // AR_f, npt.NDArray[np.float64]) +assert_type(AR_LIKE_u // AR_f, npt.NDArray[np.float64]) +assert_type(AR_LIKE_i // AR_f, npt.NDArray[np.float64]) +assert_type(AR_LIKE_f // AR_f, npt.NDArray[np.float64]) +assert_type(AR_LIKE_m // AR_f, npt.NDArray[np.timedelta64]) +assert_type(AR_LIKE_O // AR_f, Any) + +assert_type(AR_m // AR_LIKE_u, npt.NDArray[np.timedelta64]) +assert_type(AR_m // AR_LIKE_i, npt.NDArray[np.timedelta64]) +assert_type(AR_m // AR_LIKE_f, npt.NDArray[np.timedelta64]) +assert_type(AR_m // AR_LIKE_m, npt.NDArray[np.int64]) +assert_type(AR_m // AR_LIKE_O, Any) + +assert_type(AR_LIKE_m // AR_m, npt.NDArray[np.int64]) +assert_type(AR_LIKE_O // AR_m, Any) + +assert_type(AR_O // AR_LIKE_b, Any) +assert_type(AR_O // AR_LIKE_u, Any) +assert_type(AR_O // AR_LIKE_i, Any) +assert_type(AR_O // AR_LIKE_f, Any) +assert_type(AR_O // AR_LIKE_m, Any) +assert_type(AR_O // AR_LIKE_M, Any) +assert_type(AR_O // AR_LIKE_O, Any) + +assert_type(AR_LIKE_b // AR_O, Any) +assert_type(AR_LIKE_u // AR_O, Any) +assert_type(AR_LIKE_i // AR_O, Any) +assert_type(AR_LIKE_f // AR_O, Any) +assert_type(AR_LIKE_m // AR_O, Any) +assert_type(AR_LIKE_M // AR_O, Any) +assert_type(AR_LIKE_O // AR_O, Any) + +# unary ops + +assert_type(-f16, np.floating[_128Bit]) +assert_type(-c16, np.complex128) +assert_type(-c8, np.complex64) +assert_type(-f8, np.float64) +assert_type(-f4, np.float32) +assert_type(-i8, np.int64) +assert_type(-i4, np.int32) +assert_type(-u8, np.uint64) +assert_type(-u4, np.uint32) +assert_type(-m8, np.timedelta64) +assert_type(-m8_none, np.timedelta64[None]) +assert_type(-m8_int, np.timedelta64[int]) +assert_type(-m8_delta, np.timedelta64[dt.timedelta]) +assert_type(-AR_f, npt.NDArray[np.float64]) + +assert_type(+f16, np.floating[_128Bit]) +assert_type(+c16, np.complex128) +assert_type(+c8, np.complex64) +assert_type(+f8, np.float64) +assert_type(+f4, np.float32) +assert_type(+i8, np.int64) +assert_type(+i4, np.int32) +assert_type(+u8, np.uint64) +assert_type(+u4, np.uint32) +assert_type(+m8_none, np.timedelta64[None]) +assert_type(+m8_int, np.timedelta64[int]) +assert_type(+m8_delta, np.timedelta64[dt.timedelta]) +assert_type(+AR_f, npt.NDArray[np.float64]) + +assert_type(abs(f16), np.floating[_128Bit]) +assert_type(abs(c16), np.float64) +assert_type(abs(c8), np.float32) +assert_type(abs(f8), np.float64) +assert_type(abs(f4), np.float32) +assert_type(abs(i8), np.int64) +assert_type(abs(i4), np.int32) +assert_type(abs(u8), np.uint64) +assert_type(abs(u4), np.uint32) +assert_type(abs(m8), np.timedelta64) +assert_type(abs(m8_none), np.timedelta64[None]) +assert_type(abs(m8_int), np.timedelta64[int]) +assert_type(abs(m8_delta), np.timedelta64[dt.timedelta]) +assert_type(abs(b_), np.bool) +assert_type(abs(AR_O), npt.NDArray[np.object_]) + +# Time structures + +assert_type(M8 + m8, np.datetime64) +assert_type(M8 + i, np.datetime64) +assert_type(M8 + i8, np.datetime64) +assert_type(M8 - M8, np.timedelta64) +assert_type(M8 - i, np.datetime64) +assert_type(M8 - i8, np.datetime64) + +assert_type(M8_none + m8, np.datetime64[None]) +assert_type(M8_none + i, np.datetime64[None]) +assert_type(M8_none + i8, np.datetime64[None]) +assert_type(M8_none - M8, np.timedelta64[None]) +assert_type(M8_none - m8, np.datetime64[None]) +assert_type(M8_none - i, np.datetime64[None]) +assert_type(M8_none - i8, np.datetime64[None]) + +assert_type(m8 + m8, np.timedelta64) +assert_type(m8 + i, np.timedelta64) +assert_type(m8 + i8, np.timedelta64) +assert_type(m8 - m8, np.timedelta64) +assert_type(m8 - i, np.timedelta64) +assert_type(m8 - i8, np.timedelta64) +assert_type(m8 * f, np.timedelta64) +assert_type(m8 * f4, np.timedelta64) +assert_type(m8 * np.True_, np.timedelta64) +assert_type(m8 / f, np.timedelta64) +assert_type(m8 / f4, np.timedelta64) +assert_type(m8 / m8, np.float64) +assert_type(m8 // m8, np.int64) +assert_type(m8 % m8, np.timedelta64) +assert_type(divmod(m8, m8), tuple[np.int64, np.timedelta64]) + +assert_type(m8_none + m8, np.timedelta64[None]) +assert_type(m8_none + i, np.timedelta64[None]) +assert_type(m8_none + i8, np.timedelta64[None]) +assert_type(m8_none - i, np.timedelta64[None]) +assert_type(m8_none - i8, np.timedelta64[None]) + +assert_type(m8_int + i, np.timedelta64[int]) +assert_type(m8_int + m8_delta, np.timedelta64[int]) +assert_type(m8_int + m8, np.timedelta64[int | None]) +assert_type(m8_int - i, np.timedelta64[int]) +assert_type(m8_int - m8_delta, np.timedelta64[int]) +assert_type(m8_int - m8, np.timedelta64[int | None]) + +assert_type(m8_delta + date, dt.date) +assert_type(m8_delta + time, dt.datetime) +assert_type(m8_delta + delta, dt.timedelta) +assert_type(m8_delta - delta, dt.timedelta) +assert_type(m8_delta / delta, float) +assert_type(m8_delta // delta, int) +assert_type(m8_delta % delta, dt.timedelta) +assert_type(divmod(m8_delta, delta), tuple[int, dt.timedelta]) + +# boolean + +assert_type(b_ / b, np.float64) +assert_type(b_ / b_, np.float64) +assert_type(b_ / i, np.float64) +assert_type(b_ / i8, np.float64) +assert_type(b_ / i4, np.float64) +assert_type(b_ / u8, np.float64) +assert_type(b_ / u4, np.float64) +assert_type(b_ / f, np.float64) +assert_type(b_ / f16, np.floating[_128Bit]) +assert_type(b_ / f8, np.float64) +assert_type(b_ / f4, np.float32) +assert_type(b_ / c, np.complex128) +assert_type(b_ / c16, np.complex128) +assert_type(b_ / c8, np.complex64) + +assert_type(b / b_, np.float64) +assert_type(b_ / b_, np.float64) +assert_type(i / b_, np.float64) +assert_type(i8 / b_, np.float64) +assert_type(i4 / b_, np.float64) +assert_type(u8 / b_, np.float64) +assert_type(u4 / b_, np.float64) +assert_type(f / b_, np.float64) +assert_type(f16 / b_, np.floating[_128Bit]) +assert_type(f8 / b_, np.float64) +assert_type(f4 / b_, np.float32) +assert_type(c / b_, np.complex128) +assert_type(c16 / b_, np.complex128) +assert_type(c8 / b_, np.complex64) + +# Complex + +assert_type(c16 + f16, np.complexfloating) +assert_type(c16 + c16, np.complex128) +assert_type(c16 + f8, np.complex128) +assert_type(c16 + i8, np.complex128) +assert_type(c16 + c8, np.complex128) +assert_type(c16 + f4, np.complex128) +assert_type(c16 + i4, np.complex128) +assert_type(c16 + b_, np.complex128) +assert_type(c16 + b, np.complex128) +assert_type(c16 + c, np.complex128) +assert_type(c16 + f, np.complex128) +assert_type(c16 + AR_f, npt.NDArray[np.complex128]) + +assert_type(f16 + c16, np.complexfloating) +assert_type(c16 + c16, np.complex128) +assert_type(f8 + c16, np.complex128) +assert_type(i8 + c16, np.complex128) +assert_type(c8 + c16, np.complex128 | np.complex64) +assert_type(f4 + c16, np.complexfloating) +assert_type(i4 + c16, np.complex128) +assert_type(b_ + c16, np.complex128) +assert_type(b + c16, np.complex128) +assert_type(c + c16, np.complex128) +assert_type(f + c16, np.complex128) +assert_type(AR_f + c16, npt.NDArray[np.complex128]) + +assert_type(c8 + f16, np.complex64 | np.complexfloating[_128Bit, _128Bit]) +assert_type(c8 + c16, np.complex64 | np.complex128) +assert_type(c8 + f8, np.complex64 | np.complex128) +assert_type(c8 + i8, np.complex64 | np.complexfloating[_64Bit, _64Bit]) +assert_type(c8 + c8, np.complex64) +assert_type(c8 + f4, np.complex64) +assert_type(c8 + i4, np.complex64) +assert_type(c8 + b_, np.complex64) +assert_type(c8 + b, np.complex64) +assert_type(c8 + c, np.complex64 | np.complex128) +assert_type(c8 + f, np.complex64 | np.complex128) +assert_type(c8 + AR_f, npt.NDArray[np.complexfloating]) + +assert_type(f16 + c8, np.complexfloating[_128Bit, _128Bit] | np.complex64) +assert_type(c16 + c8, np.complex128) +assert_type(f8 + c8, np.complexfloating[_64Bit, _64Bit]) +assert_type(i8 + c8, np.complexfloating[_64Bit, _64Bit] | np.complex64) +assert_type(c8 + c8, np.complex64) +assert_type(f4 + c8, np.complex64) +assert_type(i4 + c8, np.complex64) +assert_type(b_ + c8, np.complex64) +assert_type(b + c8, np.complex64) +assert_type(c + c8, np.complex64 | np.complex128) +assert_type(f + c8, np.complex64 | np.complex128) +assert_type(AR_f + c8, npt.NDArray[np.complexfloating]) + +# Float + +assert_type(f8 + f16, np.floating) +assert_type(f8 + f8, np.float64) +assert_type(f8 + i8, np.float64) +assert_type(f8 + f4, np.float64) +assert_type(f8 + i4, np.float64) +assert_type(f8 + b_, np.float64) +assert_type(f8 + b, np.float64) +assert_type(f8 + c, np.float64 | np.complex128) +assert_type(f8 + f, np.float64) +assert_type(f8 + AR_f, npt.NDArray[np.float64]) + +assert_type(f16 + f8, np.floating) +assert_type(f8 + f8, np.float64) +assert_type(i8 + f8, np.float64) +assert_type(f4 + f8, np.floating) +assert_type(i4 + f8, np.float64) +assert_type(b_ + f8, np.float64) +assert_type(b + f8, np.float64) +assert_type(c + f8, np.complex128 | np.float64) +assert_type(f + f8, np.float64) +assert_type(AR_f + f8, npt.NDArray[np.float64]) + +assert_type(f4 + f16, np.floating) +assert_type(f4 + f8, np.floating) +assert_type(f4 + i8, np.floating) +assert_type(f4 + f4, np.float32) +assert_type(f4 + i4, np.floating) +assert_type(f4 + b_, np.float32) +assert_type(f4 + b, np.float32) +assert_type(f4 + c, np.complexfloating) +assert_type(f4 + f, np.float32) +assert_type(f4 + AR_f, npt.NDArray[np.float64]) + +assert_type(f16 + f4, np.floating) +assert_type(f8 + f4, np.float64) +assert_type(i8 + f4, np.floating) +assert_type(f4 + f4, np.float32) +assert_type(i4 + f4, np.floating) +assert_type(b_ + f4, np.float32) +assert_type(b + f4, np.float32) +assert_type(c + f4, np.complexfloating) +assert_type(f + f4, np.float32) +assert_type(AR_f + f4, npt.NDArray[np.float64]) + +# Int + +assert_type(i8 + i8, np.int64) +assert_type(i8 + u8, Any) +assert_type(i8 + i4, np.signedinteger) +assert_type(i8 + u4, Any) +assert_type(i8 + b_, np.int64) +assert_type(i8 + b, np.int64) +assert_type(i8 + c, np.complex128) +assert_type(i8 + f, np.float64) +assert_type(i8 + AR_f, npt.NDArray[np.float64]) + +assert_type(u8 + u8, np.uint64) +assert_type(u8 + i4, Any) +assert_type(u8 + u4, np.unsignedinteger) +assert_type(u8 + b_, np.uint64) +assert_type(u8 + b, np.uint64) +assert_type(u8 + c, np.complex128) +assert_type(u8 + f, np.float64) +assert_type(u8 + AR_f, npt.NDArray[np.float64]) + +assert_type(i8 + i8, np.int64) +assert_type(u8 + i8, Any) +assert_type(i4 + i8, np.signedinteger) +assert_type(u4 + i8, Any) +assert_type(b_ + i8, np.int64) +assert_type(b + i8, np.int64) +assert_type(c + i8, np.complex128) +assert_type(f + i8, np.float64) +assert_type(AR_f + i8, npt.NDArray[np.float64]) + +assert_type(u8 + u8, np.uint64) +assert_type(i4 + u8, Any) +assert_type(u4 + u8, np.unsignedinteger) +assert_type(b_ + u8, np.uint64) +assert_type(b + u8, np.uint64) +assert_type(c + u8, np.complex128) +assert_type(f + u8, np.float64) +assert_type(AR_f + u8, npt.NDArray[np.float64]) + +assert_type(i4 + i8, np.signedinteger) +assert_type(i4 + i4, np.int32) +assert_type(i4 + b_, np.int32) +assert_type(i4 + b, np.int32) +assert_type(i4 + AR_f, npt.NDArray[np.float64]) + +assert_type(u4 + i8, Any) +assert_type(u4 + i4, Any) +assert_type(u4 + u8, np.unsignedinteger) +assert_type(u4 + u4, np.uint32) +assert_type(u4 + b_, np.uint32) +assert_type(u4 + b, np.uint32) +assert_type(u4 + AR_f, npt.NDArray[np.float64]) + +assert_type(i8 + i4, np.signedinteger) +assert_type(i4 + i4, np.int32) +assert_type(b_ + i4, np.int32) +assert_type(b + i4, np.int32) +assert_type(AR_f + i4, npt.NDArray[np.float64]) + +assert_type(i8 + u4, Any) +assert_type(i4 + u4, Any) +assert_type(u8 + u4, np.unsignedinteger) +assert_type(u4 + u4, np.uint32) +assert_type(b_ + u4, np.uint32) +assert_type(b + u4, np.uint32) +assert_type(AR_f + u4, npt.NDArray[np.float64]) + +# Any + +assert_type(AR_Any + 2, npt.NDArray[Any]) + +# regression tests for https://github.com/numpy/numpy/issues/28805 + +assert_type(AR_floating + f, npt.NDArray[np.floating]) +assert_type(AR_floating - f, npt.NDArray[np.floating]) +assert_type(AR_floating * f, npt.NDArray[np.floating]) +assert_type(AR_floating ** f, npt.NDArray[np.floating]) +assert_type(AR_floating / f, npt.NDArray[np.floating]) +assert_type(AR_floating // f, npt.NDArray[np.floating]) +assert_type(AR_floating % f, npt.NDArray[np.floating]) +assert_type(divmod(AR_floating, f), tuple[npt.NDArray[np.floating], npt.NDArray[np.floating]]) + +assert_type(f + AR_floating, npt.NDArray[np.floating]) +assert_type(f - AR_floating, npt.NDArray[np.floating]) +assert_type(f * AR_floating, npt.NDArray[np.floating]) +assert_type(f ** AR_floating, npt.NDArray[np.floating]) +assert_type(f / AR_floating, npt.NDArray[np.floating]) +assert_type(f // AR_floating, npt.NDArray[np.floating]) +assert_type(f % AR_floating, npt.NDArray[np.floating]) +assert_type(divmod(f, AR_floating), tuple[npt.NDArray[np.floating], npt.NDArray[np.floating]]) + +# character-like + +assert_type(AR_S + b"", npt.NDArray[np.bytes_]) +assert_type(AR_S + [b""], npt.NDArray[np.bytes_]) +assert_type([b""] + AR_S, npt.NDArray[np.bytes_]) +assert_type(AR_S + AR_S, npt.NDArray[np.bytes_]) + +assert_type(AR_U + "", npt.NDArray[np.str_]) +assert_type(AR_U + [""], npt.NDArray[np.str_]) +assert_type("" + AR_U, npt.NDArray[np.str_]) +assert_type([""] + AR_U, npt.NDArray[np.str_]) +assert_type(AR_U + AR_U, npt.NDArray[np.str_]) + +assert_type(AR_T + "", np.ndarray[tuple[Any, ...], np.dtypes.StringDType]) +assert_type(AR_T + [""], np.ndarray[tuple[Any, ...], np.dtypes.StringDType]) +assert_type("" + AR_T, np.ndarray[tuple[Any, ...], np.dtypes.StringDType]) +assert_type([""] + AR_T, np.ndarray[tuple[Any, ...], np.dtypes.StringDType]) +assert_type(AR_T + AR_T, np.ndarray[tuple[Any, ...], np.dtypes.StringDType]) +assert_type(AR_T + AR_U, np.ndarray[tuple[Any, ...], np.dtypes.StringDType]) +assert_type(AR_U + AR_T, np.ndarray[tuple[Any, ...], np.dtypes.StringDType]) + +assert_type(AR_S * i, np.ndarray[tuple[Any, ...], np.dtype[np.bytes_]]) +assert_type(AR_S * AR_LIKE_i, np.ndarray[tuple[Any, ...], np.dtype[np.bytes_]]) +assert_type(AR_S * AR_i, np.ndarray[tuple[Any, ...], np.dtype[np.bytes_]]) +assert_type(i * AR_S, np.ndarray[tuple[Any, ...], np.dtype[np.bytes_]]) +# mypy incorrectly infers `AR_LIKE_i * AR_S` as `list[int]` +assert_type(AR_i * AR_S, np.ndarray[tuple[Any, ...], np.dtype[np.bytes_]]) + +assert_type(AR_U * i, np.ndarray[tuple[Any, ...], np.dtype[np.str_]]) +assert_type(AR_U * AR_LIKE_i, np.ndarray[tuple[Any, ...], np.dtype[np.str_]]) +assert_type(AR_U * AR_i, np.ndarray[tuple[Any, ...], np.dtype[np.str_]]) +assert_type(i * AR_U, np.ndarray[tuple[Any, ...], np.dtype[np.str_]]) +# mypy incorrectly infers `AR_LIKE_i * AR_U` as `list[int]` +assert_type(AR_i * AR_U, np.ndarray[tuple[Any, ...], np.dtype[np.str_]]) + +assert_type(AR_T * i, np.ndarray[tuple[Any, ...], np.dtypes.StringDType]) +assert_type(AR_T * AR_LIKE_i, np.ndarray[tuple[Any, ...], np.dtypes.StringDType]) +assert_type(AR_T * AR_i, np.ndarray[tuple[Any, ...], np.dtypes.StringDType]) +assert_type(i * AR_T, np.ndarray[tuple[Any, ...], np.dtypes.StringDType]) +# mypy incorrectly infers `AR_LIKE_i * AR_T` as `list[int]` +assert_type(AR_i * AR_T, np.ndarray[tuple[Any, ...], np.dtypes.StringDType]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/array_api_info.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/array_api_info.pyi new file mode 100644 index 0000000000000000000000000000000000000000..765f9eff516856657f4aaa8aebf22a4c2851a599 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/array_api_info.pyi @@ -0,0 +1,70 @@ +from typing import Literal, Never, assert_type + +import numpy as np + +info = np.__array_namespace_info__() + +assert_type(info.__module__, Literal["numpy"]) + +assert_type(info.default_device(), Literal["cpu"]) +assert_type(info.devices()[0], Literal["cpu"]) +assert_type(info.devices()[-1], Literal["cpu"]) + +assert_type(info.capabilities()["boolean indexing"], Literal[True]) +assert_type(info.capabilities()["data-dependent shapes"], Literal[True]) + +assert_type(info.default_dtypes()["real floating"], np.dtype[np.float64]) +assert_type(info.default_dtypes()["complex floating"], np.dtype[np.complex128]) +assert_type(info.default_dtypes()["integral"], np.dtype[np.int_]) +assert_type(info.default_dtypes()["indexing"], np.dtype[np.intp]) + +assert_type(info.dtypes()["bool"], np.dtype[np.bool]) +assert_type(info.dtypes()["int8"], np.dtype[np.int8]) +assert_type(info.dtypes()["uint8"], np.dtype[np.uint8]) +assert_type(info.dtypes()["float32"], np.dtype[np.float32]) +assert_type(info.dtypes()["complex64"], np.dtype[np.complex64]) + +assert_type(info.dtypes(kind="bool")["bool"], np.dtype[np.bool]) +assert_type(info.dtypes(kind="signed integer")["int64"], np.dtype[np.int64]) +assert_type(info.dtypes(kind="unsigned integer")["uint64"], np.dtype[np.uint64]) +assert_type(info.dtypes(kind="integral")["int32"], np.dtype[np.int32]) +assert_type(info.dtypes(kind="integral")["uint32"], np.dtype[np.uint32]) +assert_type(info.dtypes(kind="real floating")["float64"], np.dtype[np.float64]) +assert_type(info.dtypes(kind="complex floating")["complex128"], np.dtype[np.complex128]) +assert_type(info.dtypes(kind="numeric")["int16"], np.dtype[np.int16]) +assert_type(info.dtypes(kind="numeric")["uint16"], np.dtype[np.uint16]) +assert_type(info.dtypes(kind="numeric")["float64"], np.dtype[np.float64]) +assert_type(info.dtypes(kind="numeric")["complex128"], np.dtype[np.complex128]) + +assert_type(info.dtypes(kind=()), dict[Never, Never]) + +assert_type(info.dtypes(kind=("bool",))["bool"], np.dtype[np.bool]) +assert_type(info.dtypes(kind=("signed integer",))["int64"], np.dtype[np.int64]) +assert_type(info.dtypes(kind=("integral",))["uint32"], np.dtype[np.uint32]) +assert_type(info.dtypes(kind=("complex floating",))["complex128"], np.dtype[np.complex128]) +assert_type(info.dtypes(kind=("numeric",))["float64"], np.dtype[np.float64]) + +assert_type( + info.dtypes(kind=("signed integer", "unsigned integer"))["int8"], + np.dtype[np.int8], +) +assert_type( + info.dtypes(kind=("signed integer", "unsigned integer"))["uint8"], + np.dtype[np.uint8], +) +assert_type( + info.dtypes(kind=("integral", "real floating", "complex floating"))["int16"], + np.dtype[np.int16], +) +assert_type( + info.dtypes(kind=("integral", "real floating", "complex floating"))["uint16"], + np.dtype[np.uint16], +) +assert_type( + info.dtypes(kind=("integral", "real floating", "complex floating"))["float32"], + np.dtype[np.float32], +) +assert_type( + info.dtypes(kind=("integral", "real floating", "complex floating"))["complex64"], + np.dtype[np.complex64], +) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/array_constructors.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/array_constructors.pyi new file mode 100644 index 0000000000000000000000000000000000000000..bfdbe8727bb855793e44448526c70879b7344eff --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/array_constructors.pyi @@ -0,0 +1,279 @@ +import sys +from collections import deque +from pathlib import Path +from typing import Any, Generic, TypeVar, assert_type + +import numpy as np +import numpy.typing as npt + +_ScalarT_co = TypeVar("_ScalarT_co", bound=np.generic, covariant=True) + +class SubClass(npt.NDArray[_ScalarT_co]): ... + +class IntoSubClass(Generic[_ScalarT_co]): + def __array__(self) -> SubClass[_ScalarT_co]: ... + +i8: np.int64 + +A: npt.NDArray[np.float64] +B: SubClass[np.float64] +C: list[int] +D: SubClass[np.float64 | np.int64] +E: IntoSubClass[np.float64 | np.int64] + +mixed_shape: tuple[int, np.int64] + +def func(i: int, j: int, **kwargs: Any) -> SubClass[np.float64]: ... + +assert_type(np.empty_like(A), npt.NDArray[np.float64]) +assert_type(np.empty_like(B), SubClass[np.float64]) +assert_type(np.empty_like([1, 1.0]), npt.NDArray[Any]) +assert_type(np.empty_like(A, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(np.empty_like(A, dtype="c16"), npt.NDArray[Any]) + +assert_type(np.array(A), npt.NDArray[np.float64]) +assert_type(np.array(B), npt.NDArray[np.float64]) +assert_type(np.array([1, 1.0]), npt.NDArray[Any]) +assert_type(np.array(deque([1, 2, 3])), npt.NDArray[Any]) +assert_type(np.array(A, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(np.array(A, dtype="c16"), npt.NDArray[Any]) +assert_type(np.array(A, like=A), npt.NDArray[np.float64]) +assert_type(np.array(A, subok=True), npt.NDArray[np.float64]) +assert_type(np.array(B, subok=True), SubClass[np.float64]) +assert_type(np.array(B, subok=True, ndmin=0), SubClass[np.float64]) +assert_type(np.array(B, subok=True, ndmin=1), SubClass[np.float64]) +assert_type(np.array(D), npt.NDArray[np.float64 | np.int64]) +assert_type(np.array(E, subok=True), SubClass[np.float64 | np.int64]) +# https://github.com/numpy/numpy/issues/29245 +assert_type(np.array([], dtype=np.bool), npt.NDArray[np.bool]) + +assert_type(np.zeros([1, 5, 6]), npt.NDArray[np.float64]) +assert_type(np.zeros([1, 5, 6], dtype=np.int64), npt.NDArray[np.int64]) +assert_type(np.zeros([1, 5, 6], dtype="c16"), npt.NDArray[Any]) +assert_type(np.zeros(mixed_shape), npt.NDArray[np.float64]) + +assert_type(np.empty([1, 5, 6]), npt.NDArray[np.float64]) +assert_type(np.empty([1, 5, 6], dtype=np.int64), npt.NDArray[np.int64]) +assert_type(np.empty([1, 5, 6], dtype="c16"), npt.NDArray[Any]) +assert_type(np.empty(mixed_shape), npt.NDArray[np.float64]) + +assert_type(np.concatenate(A), npt.NDArray[np.float64]) +assert_type(np.concatenate([A, A]), npt.NDArray[Any]) # pyright correctly infers this as NDArray[float64] +assert_type(np.concatenate([[1], A]), npt.NDArray[Any]) +assert_type(np.concatenate([[1], [1]]), npt.NDArray[Any]) +assert_type(np.concatenate((A, A)), npt.NDArray[np.float64]) +assert_type(np.concatenate(([1], [1])), npt.NDArray[Any]) +assert_type(np.concatenate([1, 1.0]), npt.NDArray[Any]) +assert_type(np.concatenate(A, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(np.concatenate(A, dtype="c16"), npt.NDArray[Any]) +assert_type(np.concatenate([1, 1.0], out=A), npt.NDArray[np.float64]) + +assert_type(np.asarray(A), npt.NDArray[np.float64]) +assert_type(np.asarray(B), npt.NDArray[np.float64]) +assert_type(np.asarray([1, 1.0]), npt.NDArray[Any]) +assert_type(np.asarray(A, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(np.asarray(A, dtype="c16"), npt.NDArray[Any]) + +assert_type(np.asanyarray(A), npt.NDArray[np.float64]) +assert_type(np.asanyarray(B), SubClass[np.float64]) +assert_type(np.asanyarray([1, 1.0]), npt.NDArray[Any]) +assert_type(np.asanyarray(A, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(np.asanyarray(A, dtype="c16"), npt.NDArray[Any]) + +assert_type(np.ascontiguousarray(A), npt.NDArray[np.float64]) +assert_type(np.ascontiguousarray(B), npt.NDArray[np.float64]) +assert_type(np.ascontiguousarray([1, 1.0]), npt.NDArray[Any]) +assert_type(np.ascontiguousarray(A, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(np.ascontiguousarray(A, dtype="c16"), npt.NDArray[Any]) + +assert_type(np.asfortranarray(A), npt.NDArray[np.float64]) +assert_type(np.asfortranarray(B), npt.NDArray[np.float64]) +assert_type(np.asfortranarray([1, 1.0]), npt.NDArray[Any]) +assert_type(np.asfortranarray(A, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(np.asfortranarray(A, dtype="c16"), npt.NDArray[Any]) + +assert_type(np.fromstring("1 1 1", sep=" "), npt.NDArray[np.float64]) +assert_type(np.fromstring(b"1 1 1", sep=" "), npt.NDArray[np.float64]) +assert_type(np.fromstring("1 1 1", dtype=np.int64, sep=" "), npt.NDArray[np.int64]) +assert_type(np.fromstring(b"1 1 1", dtype=np.int64, sep=" "), npt.NDArray[np.int64]) +assert_type(np.fromstring("1 1 1", dtype="c16", sep=" "), npt.NDArray[Any]) +assert_type(np.fromstring(b"1 1 1", dtype="c16", sep=" "), npt.NDArray[Any]) + +assert_type(np.fromfile("test.txt", sep=" "), npt.NDArray[np.float64]) +assert_type(np.fromfile("test.txt", dtype=np.int64, sep=" "), npt.NDArray[np.int64]) +assert_type(np.fromfile("test.txt", dtype="c16", sep=" "), npt.NDArray[Any]) +with open("test.txt") as f: + assert_type(np.fromfile(f, sep=" "), npt.NDArray[np.float64]) + assert_type(np.fromfile(b"test.txt", sep=" "), npt.NDArray[np.float64]) + assert_type(np.fromfile(Path("test.txt"), sep=" "), npt.NDArray[np.float64]) + +assert_type(np.fromiter("12345", np.float64), npt.NDArray[np.float64]) +assert_type(np.fromiter("12345", float), npt.NDArray[Any]) + +assert_type(np.frombuffer(A), npt.NDArray[np.float64]) +assert_type(np.frombuffer(A, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(np.frombuffer(A, dtype="c16"), npt.NDArray[Any]) + +_x_bool: bool +_x_int: int +_x_float: float +_x_timedelta: np.timedelta64 +_x_datetime: np.datetime64 + +assert_type(np.arange(False, True), np.ndarray[tuple[int], np.dtype[np.int_]]) +assert_type(np.arange(10), np.ndarray[tuple[int], np.dtype[np.int_]]) +assert_type(np.arange(0, 10, step=2), np.ndarray[tuple[int], np.dtype[np.int_]]) +assert_type(np.arange(10.0), np.ndarray[tuple[int], np.dtype[np.float64 | Any]]) +assert_type(np.arange(0, stop=10.0), np.ndarray[tuple[int], np.dtype[np.float64 | Any]]) +assert_type(np.arange(_x_timedelta), np.ndarray[tuple[int], np.dtype[np.timedelta64[Any]]]) +assert_type(np.arange(0, _x_timedelta), np.ndarray[tuple[int], np.dtype[np.timedelta64[Any]]]) +assert_type(np.arange(_x_datetime, _x_datetime), np.ndarray[tuple[int], np.dtype[np.datetime64[Any]]]) +assert_type(np.arange(10, dtype=np.float64), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.arange(0, 10, step=2, dtype=np.int16), np.ndarray[tuple[int], np.dtype[np.int16]]) +assert_type(np.arange(10, dtype=int), np.ndarray[tuple[int], np.dtype[np.int_]]) +assert_type(np.arange(0, 10, dtype="f8"), np.ndarray[tuple[int], np.dtype]) +# https://github.com/numpy/numpy/issues/30628 +assert_type(np.arange("2025-12-20", "2025-12-23", dtype="datetime64[D]"), np.ndarray[tuple[int], np.dtype[np.datetime64[Any]]]) + +assert_type(np.require(A), npt.NDArray[np.float64]) +assert_type(np.require(B), SubClass[np.float64]) +assert_type(np.require(B, requirements=None), SubClass[np.float64]) +assert_type(np.require(B, dtype=int), npt.NDArray[Any]) +assert_type(np.require(B, requirements="E"), npt.NDArray[Any]) +assert_type(np.require(B, requirements=["ENSUREARRAY"]), npt.NDArray[Any]) +assert_type(np.require(B, requirements={"F", "E"}), npt.NDArray[Any]) +assert_type(np.require(B, requirements=["C", "OWNDATA"]), SubClass[np.float64]) +assert_type(np.require(B, requirements="W"), SubClass[np.float64]) +assert_type(np.require(B, requirements="A"), SubClass[np.float64]) +assert_type(np.require(C), npt.NDArray[Any]) + +assert_type(np.linspace(0, 10), npt.NDArray[np.float64]) +assert_type(np.linspace(0, 10j), npt.NDArray[np.complexfloating]) +assert_type(np.linspace(0, 10, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(np.linspace(0, 10, dtype=int), npt.NDArray[Any]) +assert_type(np.linspace(0, 10, retstep=True), tuple[npt.NDArray[np.float64], np.float64]) +assert_type(np.linspace(0j, 10, retstep=True), tuple[npt.NDArray[np.complexfloating], np.complexfloating]) +assert_type(np.linspace(0, 10, retstep=True, dtype=np.int64), tuple[npt.NDArray[np.int64], np.int64]) +assert_type(np.linspace(0j, 10, retstep=True, dtype=int), tuple[npt.NDArray[Any], Any]) + +assert_type(np.logspace(0, 10), npt.NDArray[np.float64]) +assert_type(np.logspace(0, 10j), npt.NDArray[np.complexfloating]) +assert_type(np.logspace(0, 10, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(np.logspace(0, 10, dtype=int), npt.NDArray[Any]) + +assert_type(np.geomspace(0, 10), npt.NDArray[np.float64]) +assert_type(np.geomspace(0, 10j), npt.NDArray[np.complexfloating]) +assert_type(np.geomspace(0, 10, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(np.geomspace(0, 10, dtype=int), npt.NDArray[Any]) + +assert_type(np.zeros_like(A), npt.NDArray[np.float64]) +assert_type(np.zeros_like(C), npt.NDArray[Any]) +assert_type(np.zeros_like(A, dtype=float), npt.NDArray[Any]) +assert_type(np.zeros_like(B), SubClass[np.float64]) +assert_type(np.zeros_like(B, dtype=np.int64), npt.NDArray[np.int64]) + +assert_type(np.ones_like(A), npt.NDArray[np.float64]) +assert_type(np.ones_like(C), npt.NDArray[Any]) +assert_type(np.ones_like(A, dtype=float), npt.NDArray[Any]) +assert_type(np.ones_like(B), SubClass[np.float64]) +assert_type(np.ones_like(B, dtype=np.int64), npt.NDArray[np.int64]) + +assert_type(np.full_like(A, i8), npt.NDArray[np.float64]) +assert_type(np.full_like(C, i8), npt.NDArray[Any]) +assert_type(np.full_like(A, i8, dtype=int), npt.NDArray[Any]) +assert_type(np.full_like(B, i8), SubClass[np.float64]) +assert_type(np.full_like(B, i8, dtype=np.int64), npt.NDArray[np.int64]) + +_size: int +_shape_0d: tuple[()] +_shape_1d: tuple[int] +_shape_2d: tuple[int, int] +_shape_nd: tuple[int, ...] +_shape_like: list[int] + +assert_type(np.ones(_shape_0d), np.ndarray[tuple[()], np.dtype[np.float64]]) +assert_type(np.ones(_size), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.ones(_shape_2d), np.ndarray[tuple[int, int], np.dtype[np.float64]]) +assert_type(np.ones(_shape_nd), np.ndarray[tuple[int, ...], np.dtype[np.float64]]) +assert_type(np.ones(_shape_1d, dtype=np.int64), np.ndarray[tuple[int], np.dtype[np.int64]]) +assert_type(np.ones(_shape_like), npt.NDArray[np.float64]) +assert_type( + np.ones(_shape_like, dtype=np.dtypes.Int64DType()), + np.ndarray[tuple[Any, ...], np.dtypes.Int64DType], +) +assert_type(np.ones(_shape_like, dtype=int), npt.NDArray[Any]) +assert_type(np.ones(mixed_shape), npt.NDArray[np.float64]) + +assert_type(np.full(_size, i8), np.ndarray[tuple[int], np.dtype[np.int64]]) +assert_type(np.full(_shape_2d, i8), np.ndarray[tuple[int, int], np.dtype[np.int64]]) +assert_type(np.full(_shape_like, i8), npt.NDArray[np.int64]) +assert_type(np.full(_shape_like, 42), npt.NDArray[Any]) +assert_type(np.full(_size, i8, dtype=np.float64), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.full(_size, i8, dtype=float), np.ndarray[tuple[int], np.dtype]) +assert_type(np.full(_shape_like, 42, dtype=float), npt.NDArray[Any]) +assert_type(np.full(_shape_0d, i8, dtype=object), np.ndarray[tuple[()], np.dtype]) + +assert_type(np.indices([1, 2, 3]), npt.NDArray[np.int_]) +assert_type(np.indices([1, 2, 3], sparse=True), tuple[npt.NDArray[np.int_], ...]) + +assert_type(np.fromfunction(func, (3, 5)), SubClass[np.float64]) + +assert_type(np.identity(3), np.ndarray[tuple[int, int], np.dtype[np.float64]]) +assert_type(np.identity(3, dtype=np.int8), np.ndarray[tuple[int, int], np.dtype[np.int8]]) +assert_type(np.identity(3, dtype=bool), np.ndarray[tuple[int, int], np.dtype[np.bool]]) +assert_type(np.identity(3, dtype="bool"), np.ndarray[tuple[int, int], np.dtype[np.bool]]) +assert_type(np.identity(3, dtype="b1"), np.ndarray[tuple[int, int], np.dtype[np.bool]]) +assert_type(np.identity(3, dtype="?"), np.ndarray[tuple[int, int], np.dtype[np.bool]]) +assert_type(np.identity(3, dtype=int), np.ndarray[tuple[int, int], np.dtype[np.int_ | Any]]) +assert_type(np.identity(3, dtype="int"), np.ndarray[tuple[int, int], np.dtype[np.int_ | Any]]) +assert_type(np.identity(3, dtype="n"), np.ndarray[tuple[int, int], np.dtype[np.int_ | Any]]) +assert_type(np.identity(3, dtype=float), np.ndarray[tuple[int, int], np.dtype[np.float64 | Any]]) +assert_type(np.identity(3, dtype="float"), np.ndarray[tuple[int, int], np.dtype[np.float64 | Any]]) +assert_type(np.identity(3, dtype="f8"), np.ndarray[tuple[int, int], np.dtype[np.float64 | Any]]) +assert_type(np.identity(3, dtype="d"), np.ndarray[tuple[int, int], np.dtype[np.float64 | Any]]) +assert_type(np.identity(3, dtype=complex), np.ndarray[tuple[int, int], np.dtype[np.complex128 | Any]]) +assert_type(np.identity(3, dtype="complex"), np.ndarray[tuple[int, int], np.dtype[np.complex128 | Any]]) +assert_type(np.identity(3, dtype="c16"), np.ndarray[tuple[int, int], np.dtype[np.complex128 | Any]]) +assert_type(np.identity(3, dtype="D"), np.ndarray[tuple[int, int], np.dtype[np.complex128 | Any]]) + +assert_type(np.atleast_1d(A), npt.NDArray[np.float64]) +assert_type(np.atleast_1d(C), npt.NDArray[Any]) +assert_type(np.atleast_1d(A, A), tuple[npt.NDArray[np.float64], npt.NDArray[np.float64]]) +assert_type(np.atleast_1d(A, C), tuple[npt.NDArray[Any], npt.NDArray[Any]]) +assert_type(np.atleast_1d(C, C), tuple[npt.NDArray[Any], npt.NDArray[Any]]) +assert_type(np.atleast_1d(A, A, A), tuple[npt.NDArray[np.float64], ...]) +assert_type(np.atleast_1d(C, C, C), tuple[npt.NDArray[Any], ...]) + +assert_type(np.atleast_2d(A), npt.NDArray[np.float64]) +assert_type(np.atleast_2d(A, A), tuple[npt.NDArray[np.float64], npt.NDArray[np.float64]]) +assert_type(np.atleast_2d(A, A, A), tuple[npt.NDArray[np.float64], ...]) + +assert_type(np.atleast_3d(A), npt.NDArray[np.float64]) +assert_type(np.atleast_3d(A, A), tuple[npt.NDArray[np.float64], npt.NDArray[np.float64]]) +assert_type(np.atleast_3d(A, A, A), tuple[npt.NDArray[np.float64], ...]) + +assert_type(np.vstack([A, A]), npt.NDArray[np.float64]) +assert_type(np.vstack([A, A], dtype=np.float32), npt.NDArray[np.float32]) +assert_type(np.vstack([A, C]), npt.NDArray[Any]) +assert_type(np.vstack([C, C]), npt.NDArray[Any]) + +assert_type(np.hstack([A, A]), npt.NDArray[np.float64]) +assert_type(np.hstack([A, A], dtype=np.float32), npt.NDArray[np.float32]) + +assert_type(np.stack([A, A]), npt.NDArray[np.float64]) +assert_type(np.stack([A, A], dtype=np.float32), npt.NDArray[np.float32]) +assert_type(np.stack([A, C]), npt.NDArray[Any]) +assert_type(np.stack([C, C]), npt.NDArray[Any]) +assert_type(np.stack([A, A], axis=0), npt.NDArray[np.float64]) +assert_type(np.stack([A, A], out=B), SubClass[np.float64]) + +assert_type(np.block([[A, A], [A, A]]), npt.NDArray[Any]) # pyright correctly infers this as NDArray[float64] +assert_type(np.block(C), npt.NDArray[Any]) + +if sys.version_info >= (3, 12): + from collections.abc import Buffer + + def create_array(obj: npt.ArrayLike) -> npt.NDArray[Any]: ... + + buffer: Buffer + assert_type(create_array(buffer), npt.NDArray[Any]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/arraypad.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/arraypad.pyi new file mode 100644 index 0000000000000000000000000000000000000000..3d53d913a7705868fe36219cf75d787285c935e5 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/arraypad.pyi @@ -0,0 +1,27 @@ +from collections.abc import Mapping +from typing import Any, SupportsIndex, assert_type + +import numpy as np +import numpy.typing as npt + +def mode_func( + ar: npt.NDArray[np.number], + width: tuple[int, int], + iaxis: SupportsIndex, + kwargs: Mapping[str, Any], +) -> None: ... + +AR_i8: npt.NDArray[np.int64] +AR_f8: npt.NDArray[np.float64] +AR_LIKE: list[int] + +assert_type(np.pad(AR_i8, (2, 3), "constant"), npt.NDArray[np.int64]) +assert_type(np.pad(AR_LIKE, (2, 3), "constant"), npt.NDArray[Any]) + +assert_type(np.pad(AR_f8, (2, 3), mode_func), npt.NDArray[np.float64]) +assert_type(np.pad(AR_f8, (2, 3), mode_func, a=1, b=2), npt.NDArray[np.float64]) + +assert_type(np.pad(AR_i8, {-1: (2, 3)}), npt.NDArray[np.int64]) +assert_type(np.pad(AR_i8, {-2: 4}), npt.NDArray[np.int64]) +pad_width: dict[int, int | tuple[int, int]] = {-1: (2, 3), -2: 4} +assert_type(np.pad(AR_i8, pad_width), npt.NDArray[np.int64]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/arrayprint.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/arrayprint.pyi new file mode 100644 index 0000000000000000000000000000000000000000..17e175edc2b7796578b34eca3eaba9f1656f2e02 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/arrayprint.pyi @@ -0,0 +1,25 @@ +import contextlib +from collections.abc import Callable +from typing import assert_type + +import numpy as np +import numpy.typing as npt +from numpy._core.arrayprint import _FormatOptions + +AR: npt.NDArray[np.int64] +func_float: Callable[[np.floating], str] +func_int: Callable[[np.integer], str] + +assert_type(np.get_printoptions(), _FormatOptions) +assert_type( + np.array2string(AR, formatter={"float_kind": func_float, "int_kind": func_int}), + str, +) +assert_type(np.format_float_scientific(1.0), str) +assert_type(np.format_float_positional(1), str) +assert_type(np.array_repr(AR), str) +assert_type(np.array_str(AR), str) + +assert_type(np.printoptions(), contextlib._GeneratorContextManager[_FormatOptions]) +with np.printoptions() as dct: + assert_type(dct, _FormatOptions) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/arraysetops.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/arraysetops.pyi new file mode 100644 index 0000000000000000000000000000000000000000..7e5ca5c5717baeb13a12af2cb8cfa42469c34fb7 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/arraysetops.pyi @@ -0,0 +1,74 @@ +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt +from numpy.lib._arraysetops_impl import ( + UniqueAllResult, + UniqueCountsResult, + UniqueInverseResult, +) + +AR_b: npt.NDArray[np.bool] +AR_i8: npt.NDArray[np.int64] +AR_f8: npt.NDArray[np.float64] +AR_M: npt.NDArray[np.datetime64] +AR_O: npt.NDArray[np.object_] + +AR_LIKE_f8: list[float] + +assert_type(np.ediff1d(AR_b), npt.NDArray[np.int8]) +assert_type(np.ediff1d(AR_i8, to_end=[1, 2, 3]), npt.NDArray[np.int64]) +assert_type(np.ediff1d(AR_M), npt.NDArray[np.timedelta64]) +assert_type(np.ediff1d(AR_O), npt.NDArray[np.object_]) +assert_type(np.ediff1d(AR_LIKE_f8, to_begin=[1, 1.5]), npt.NDArray[Any]) + +assert_type(np.intersect1d(AR_i8, AR_i8), npt.NDArray[np.int64]) +assert_type(np.intersect1d(AR_M, AR_M, assume_unique=True), npt.NDArray[np.datetime64]) +assert_type(np.intersect1d(AR_f8, AR_i8), npt.NDArray[Any]) +assert_type( + np.intersect1d(AR_f8, AR_f8, return_indices=True), + tuple[npt.NDArray[np.float64], npt.NDArray[np.intp], npt.NDArray[np.intp]], +) + +assert_type(np.setxor1d(AR_i8, AR_i8), npt.NDArray[np.int64]) +assert_type(np.setxor1d(AR_M, AR_M, assume_unique=True), npt.NDArray[np.datetime64]) +assert_type(np.setxor1d(AR_f8, AR_i8), npt.NDArray[Any]) + +assert_type(np.isin(AR_i8, AR_i8), npt.NDArray[np.bool]) +assert_type(np.isin(AR_M, AR_M, assume_unique=True), npt.NDArray[np.bool]) +assert_type(np.isin(AR_f8, AR_i8), npt.NDArray[np.bool]) +assert_type(np.isin(AR_f8, AR_LIKE_f8, invert=True), npt.NDArray[np.bool]) + +assert_type(np.union1d(AR_i8, AR_i8), npt.NDArray[np.int64]) +assert_type(np.union1d(AR_M, AR_M), npt.NDArray[np.datetime64]) +assert_type(np.union1d(AR_f8, AR_i8), npt.NDArray[Any]) + +assert_type(np.setdiff1d(AR_i8, AR_i8), npt.NDArray[np.int64]) +assert_type(np.setdiff1d(AR_M, AR_M, assume_unique=True), npt.NDArray[np.datetime64]) +assert_type(np.setdiff1d(AR_f8, AR_i8), npt.NDArray[Any]) + +assert_type(np.unique(AR_f8), npt.NDArray[np.float64]) +assert_type(np.unique(AR_LIKE_f8, axis=0), npt.NDArray[Any]) +assert_type(np.unique(AR_f8, return_index=True), tuple[npt.NDArray[np.float64], npt.NDArray[np.intp]]) +assert_type(np.unique(AR_LIKE_f8, return_index=True), tuple[npt.NDArray[Any], npt.NDArray[np.intp]]) +assert_type(np.unique(AR_f8, return_inverse=True), tuple[npt.NDArray[np.float64], npt.NDArray[np.intp]]) +assert_type(np.unique(AR_LIKE_f8, return_inverse=True), tuple[npt.NDArray[Any], npt.NDArray[np.intp]]) +assert_type(np.unique(AR_f8, return_counts=True), tuple[npt.NDArray[np.float64], npt.NDArray[np.intp]]) +assert_type(np.unique(AR_LIKE_f8, return_counts=True), tuple[npt.NDArray[Any], npt.NDArray[np.intp]]) +assert_type(np.unique(AR_f8, return_index=True, return_inverse=True), tuple[npt.NDArray[np.float64], npt.NDArray[np.intp], npt.NDArray[np.intp]]) +assert_type(np.unique(AR_LIKE_f8, return_index=True, return_inverse=True), tuple[npt.NDArray[Any], npt.NDArray[np.intp], npt.NDArray[np.intp]]) +assert_type(np.unique(AR_f8, return_index=True, return_counts=True), tuple[npt.NDArray[np.float64], npt.NDArray[np.intp], npt.NDArray[np.intp]]) +assert_type(np.unique(AR_LIKE_f8, return_index=True, return_counts=True), tuple[npt.NDArray[Any], npt.NDArray[np.intp], npt.NDArray[np.intp]]) +assert_type(np.unique(AR_f8, return_inverse=True, return_counts=True), tuple[npt.NDArray[np.float64], npt.NDArray[np.intp], npt.NDArray[np.intp]]) +assert_type(np.unique(AR_LIKE_f8, return_inverse=True, return_counts=True), tuple[npt.NDArray[Any], npt.NDArray[np.intp], npt.NDArray[np.intp]]) +assert_type(np.unique(AR_f8, return_index=True, return_inverse=True, return_counts=True), tuple[npt.NDArray[np.float64], npt.NDArray[np.intp], npt.NDArray[np.intp], npt.NDArray[np.intp]]) +assert_type(np.unique(AR_LIKE_f8, return_index=True, return_inverse=True, return_counts=True), tuple[npt.NDArray[Any], npt.NDArray[np.intp], npt.NDArray[np.intp], npt.NDArray[np.intp]]) + +assert_type(np.unique_all(AR_f8), UniqueAllResult[np.float64]) +assert_type(np.unique_all(AR_LIKE_f8), UniqueAllResult[Any]) +assert_type(np.unique_counts(AR_f8), UniqueCountsResult[np.float64]) +assert_type(np.unique_counts(AR_LIKE_f8), UniqueCountsResult[Any]) +assert_type(np.unique_inverse(AR_f8), UniqueInverseResult[np.float64]) +assert_type(np.unique_inverse(AR_LIKE_f8), UniqueInverseResult[Any]) +assert_type(np.unique_values(AR_f8), npt.NDArray[np.float64]) +assert_type(np.unique_values(AR_LIKE_f8), npt.NDArray[Any]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/arrayterator.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/arrayterator.pyi new file mode 100644 index 0000000000000000000000000000000000000000..85eeff4add0873053ae76f9b0c24bc7c8cbf58c0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/arrayterator.pyi @@ -0,0 +1,27 @@ +from collections.abc import Generator +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt + +AR_i8: npt.NDArray[np.int64] +ar_iter = np.lib.Arrayterator(AR_i8) + +assert_type(ar_iter.var, npt.NDArray[np.int64]) +assert_type(ar_iter.buf_size, int | None) +assert_type(ar_iter.start, list[int]) +assert_type(ar_iter.stop, list[int]) +assert_type(ar_iter.step, list[int]) +assert_type(ar_iter.shape, tuple[Any, ...]) +assert_type(ar_iter.flat, Generator[np.int64]) + +assert_type(ar_iter.__array__(), npt.NDArray[np.int64]) + +for i in ar_iter: + assert_type(i, npt.NDArray[np.int64]) + +assert_type(ar_iter[0], np.lib.Arrayterator[tuple[Any, ...], np.dtype[np.int64]]) +assert_type(ar_iter[...], np.lib.Arrayterator[tuple[Any, ...], np.dtype[np.int64]]) +assert_type(ar_iter[:], np.lib.Arrayterator[tuple[Any, ...], np.dtype[np.int64]]) +assert_type(ar_iter[0, 0, 0], np.lib.Arrayterator[tuple[Any, ...], np.dtype[np.int64]]) +assert_type(ar_iter[..., 0, :], np.lib.Arrayterator[tuple[Any, ...], np.dtype[np.int64]]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/bitwise_ops.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/bitwise_ops.pyi new file mode 100644 index 0000000000000000000000000000000000000000..49986bd5d12c590e92d134efa66307dbcdf9c56a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/bitwise_ops.pyi @@ -0,0 +1,166 @@ +from typing import Literal as L, TypeAlias, assert_type + +import numpy as np +import numpy.typing as npt + +FalseType: TypeAlias = L[False] +TrueType: TypeAlias = L[True] + +i4: np.int32 +i8: np.int64 + +u4: np.uint32 +u8: np.uint64 + +b_: np.bool[bool] +b0_: np.bool[FalseType] +b1_: np.bool[TrueType] + +b: bool +b0: FalseType +b1: TrueType + +i: int + +AR: npt.NDArray[np.int32] + +assert_type(i8 << i8, np.int64) +assert_type(i8 >> i8, np.int64) +assert_type(i8 | i8, np.int64) +assert_type(i8 ^ i8, np.int64) +assert_type(i8 & i8, np.int64) + +assert_type(i8 << AR, npt.NDArray[np.signedinteger]) +assert_type(i8 >> AR, npt.NDArray[np.signedinteger]) +assert_type(i8 | AR, npt.NDArray[np.signedinteger]) +assert_type(i8 ^ AR, npt.NDArray[np.signedinteger]) +assert_type(i8 & AR, npt.NDArray[np.signedinteger]) + +assert_type(i4 << i4, np.int32) +assert_type(i4 >> i4, np.int32) +assert_type(i4 | i4, np.int32) +assert_type(i4 ^ i4, np.int32) +assert_type(i4 & i4, np.int32) + +assert_type(i8 << i4, np.signedinteger) +assert_type(i8 >> i4, np.signedinteger) +assert_type(i8 | i4, np.signedinteger) +assert_type(i8 ^ i4, np.signedinteger) +assert_type(i8 & i4, np.signedinteger) + +assert_type(i8 << b_, np.int64) +assert_type(i8 >> b_, np.int64) +assert_type(i8 | b_, np.int64) +assert_type(i8 ^ b_, np.int64) +assert_type(i8 & b_, np.int64) + +assert_type(i8 << b, np.int64) +assert_type(i8 >> b, np.int64) +assert_type(i8 | b, np.int64) +assert_type(i8 ^ b, np.int64) +assert_type(i8 & b, np.int64) + +assert_type(u8 << u8, np.uint64) +assert_type(u8 >> u8, np.uint64) +assert_type(u8 | u8, np.uint64) +assert_type(u8 ^ u8, np.uint64) +assert_type(u8 & u8, np.uint64) + +assert_type(u8 << AR, npt.NDArray[np.signedinteger]) +assert_type(u8 >> AR, npt.NDArray[np.signedinteger]) +assert_type(u8 | AR, npt.NDArray[np.signedinteger]) +assert_type(u8 ^ AR, npt.NDArray[np.signedinteger]) +assert_type(u8 & AR, npt.NDArray[np.signedinteger]) + +assert_type(u4 << u4, np.uint32) +assert_type(u4 >> u4, np.uint32) +assert_type(u4 | u4, np.uint32) +assert_type(u4 ^ u4, np.uint32) +assert_type(u4 & u4, np.uint32) + +assert_type(u4 << i4, np.signedinteger) +assert_type(u4 >> i4, np.signedinteger) +assert_type(u4 | i4, np.signedinteger) +assert_type(u4 ^ i4, np.signedinteger) +assert_type(u4 & i4, np.signedinteger) + +assert_type(u4 << i, np.uint32) +assert_type(u4 >> i, np.uint32) +assert_type(u4 | i, np.uint32) +assert_type(u4 ^ i, np.uint32) +assert_type(u4 & i, np.uint32) + +assert_type(u8 << b_, np.uint64) +assert_type(u8 >> b_, np.uint64) +assert_type(u8 | b_, np.uint64) +assert_type(u8 ^ b_, np.uint64) +assert_type(u8 & b_, np.uint64) + +assert_type(u8 << b, np.uint64) +assert_type(u8 >> b, np.uint64) +assert_type(u8 | b, np.uint64) +assert_type(u8 ^ b, np.uint64) +assert_type(u8 & b, np.uint64) + +assert_type(b_ << b_, np.int8) +assert_type(b_ >> b_, np.int8) +assert_type(b_ | b_, np.bool) +assert_type(b_ ^ b_, np.bool) +assert_type(b_ & b_, np.bool) + +assert_type(b_ << AR, npt.NDArray[np.signedinteger]) +assert_type(b_ >> AR, npt.NDArray[np.signedinteger]) +assert_type(b_ | AR, npt.NDArray[np.signedinteger]) +assert_type(b_ ^ AR, npt.NDArray[np.signedinteger]) +assert_type(b_ & AR, npt.NDArray[np.signedinteger]) + +assert_type(b_ << b, np.int8) +assert_type(b_ >> b, np.int8) +assert_type(b_ | b, np.bool) +assert_type(b_ ^ b, np.bool) +assert_type(b_ & b, np.bool) + +assert_type(b_ << i, np.int_) +assert_type(b_ >> i, np.int_) +assert_type(b_ | i, np.bool | np.int_) +assert_type(b_ ^ i, np.bool | np.int_) +assert_type(b_ & i, np.bool | np.int_) + +assert_type(~i8, np.int64) +assert_type(~i4, np.int32) +assert_type(~u8, np.uint64) +assert_type(~u4, np.uint32) +assert_type(~b_, np.bool) +assert_type(~b0_, np.bool[TrueType]) +assert_type(~b1_, np.bool[FalseType]) +assert_type(~AR, npt.NDArray[np.int32]) + +assert_type(b_ | b0_, np.bool) +assert_type(b0_ | b_, np.bool) +assert_type(b_ | b1_, np.bool[TrueType]) +assert_type(b1_ | b_, np.bool[TrueType]) + +assert_type(b_ ^ b0_, np.bool) +assert_type(b0_ ^ b_, np.bool) +assert_type(b_ ^ b1_, np.bool) +assert_type(b1_ ^ b_, np.bool) + +assert_type(b_ & b0_, np.bool[FalseType]) +assert_type(b0_ & b_, np.bool[FalseType]) +assert_type(b_ & b1_, np.bool) +assert_type(b1_ & b_, np.bool) + +assert_type(b0_ | b0_, np.bool[FalseType]) +assert_type(b0_ | b1_, np.bool[TrueType]) +assert_type(b1_ | b0_, np.bool[TrueType]) +assert_type(b1_ | b1_, np.bool[TrueType]) + +assert_type(b0_ ^ b0_, np.bool[FalseType]) +assert_type(b0_ ^ b1_, np.bool[TrueType]) +assert_type(b1_ ^ b0_, np.bool[TrueType]) +assert_type(b1_ ^ b1_, np.bool[FalseType]) + +assert_type(b0_ & b0_, np.bool[FalseType]) +assert_type(b0_ & b1_, np.bool[FalseType]) +assert_type(b1_ & b0_, np.bool[FalseType]) +assert_type(b1_ & b1_, np.bool[TrueType]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/char.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/char.pyi new file mode 100644 index 0000000000000000000000000000000000000000..2fba2feae3851c06bd5ea57f7547159e18fc1a86 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/char.pyi @@ -0,0 +1,225 @@ +from typing import TypeAlias, assert_type + +import numpy as np +import numpy._typing as np_t +import numpy.typing as npt + +AR_T_alias: TypeAlias = np.ndarray[np_t._AnyShape, np.dtypes.StringDType] +AR_TU_alias: TypeAlias = AR_T_alias | npt.NDArray[np.str_] + +AR_U: npt.NDArray[np.str_] +AR_S: npt.NDArray[np.bytes_] +AR_T: AR_T_alias + +assert_type(np.char.equal(AR_U, AR_U), npt.NDArray[np.bool]) +assert_type(np.char.equal(AR_S, AR_S), npt.NDArray[np.bool]) +assert_type(np.char.equal(AR_T, AR_T), npt.NDArray[np.bool]) + +assert_type(np.char.not_equal(AR_U, AR_U), npt.NDArray[np.bool]) +assert_type(np.char.not_equal(AR_S, AR_S), npt.NDArray[np.bool]) +assert_type(np.char.not_equal(AR_T, AR_T), npt.NDArray[np.bool]) + +assert_type(np.char.greater_equal(AR_U, AR_U), npt.NDArray[np.bool]) +assert_type(np.char.greater_equal(AR_S, AR_S), npt.NDArray[np.bool]) +assert_type(np.char.greater_equal(AR_T, AR_T), npt.NDArray[np.bool]) + +assert_type(np.char.less_equal(AR_U, AR_U), npt.NDArray[np.bool]) +assert_type(np.char.less_equal(AR_S, AR_S), npt.NDArray[np.bool]) +assert_type(np.char.less_equal(AR_T, AR_T), npt.NDArray[np.bool]) + +assert_type(np.char.greater(AR_U, AR_U), npt.NDArray[np.bool]) +assert_type(np.char.greater(AR_S, AR_S), npt.NDArray[np.bool]) +assert_type(np.char.greater(AR_T, AR_T), npt.NDArray[np.bool]) + +assert_type(np.char.less(AR_U, AR_U), npt.NDArray[np.bool]) +assert_type(np.char.less(AR_S, AR_S), npt.NDArray[np.bool]) +assert_type(np.char.less(AR_T, AR_T), npt.NDArray[np.bool]) + +assert_type(np.char.multiply(AR_U, 5), npt.NDArray[np.str_]) +assert_type(np.char.multiply(AR_S, [5, 4, 3]), npt.NDArray[np.bytes_]) +assert_type(np.char.multiply(AR_T, 5), AR_T_alias) + +assert_type(np.char.mod(AR_U, "test"), npt.NDArray[np.str_]) +assert_type(np.char.mod(AR_S, "test"), npt.NDArray[np.bytes_]) +assert_type(np.char.mod(AR_T, "test"), AR_T_alias) + +assert_type(np.char.capitalize(AR_U), npt.NDArray[np.str_]) +assert_type(np.char.capitalize(AR_S), npt.NDArray[np.bytes_]) +assert_type(np.char.capitalize(AR_T), AR_T_alias) + +assert_type(np.char.center(AR_U, 5), npt.NDArray[np.str_]) +assert_type(np.char.center(AR_S, [2, 3, 4], b"a"), npt.NDArray[np.bytes_]) +assert_type(np.char.center(AR_T, 5), AR_T_alias) + +assert_type(np.char.encode(AR_U), npt.NDArray[np.bytes_]) +assert_type(np.char.encode(AR_T), npt.NDArray[np.bytes_]) +assert_type(np.char.decode(AR_S), npt.NDArray[np.str_]) + +assert_type(np.char.expandtabs(AR_U), npt.NDArray[np.str_]) +assert_type(np.char.expandtabs(AR_S, tabsize=4), npt.NDArray[np.bytes_]) +assert_type(np.char.expandtabs(AR_T), AR_T_alias) + +assert_type(np.char.join(AR_U, "_"), npt.NDArray[np.str_]) +assert_type(np.char.join(AR_S, [b"_", b""]), npt.NDArray[np.bytes_]) +assert_type(np.char.join(AR_T, "_"), AR_TU_alias) + +assert_type(np.char.ljust(AR_U, 5), npt.NDArray[np.str_]) +assert_type(np.char.ljust(AR_S, [4, 3, 1], fillchar=[b"a", b"b", b"c"]), npt.NDArray[np.bytes_]) +assert_type(np.char.ljust(AR_S, [4, 3, 1], fillchar="a"), npt.NDArray[np.bytes_]) +assert_type(np.char.ljust(AR_T, 5), AR_T_alias) +assert_type(np.char.ljust(AR_T, [4, 2, 1], fillchar=["a", "b", "c"]), AR_TU_alias) + +assert_type(np.char.rjust(AR_U, 5), npt.NDArray[np.str_]) +assert_type(np.char.rjust(AR_S, [4, 3, 1], fillchar=[b"a", b"b", b"c"]), npt.NDArray[np.bytes_]) +assert_type(np.char.rjust(AR_T, 5), AR_T_alias) +assert_type(np.char.rjust(AR_T, [4, 2, 1], fillchar=["a", "b", "c"]), AR_TU_alias) + +assert_type(np.char.lstrip(AR_U), npt.NDArray[np.str_]) +assert_type(np.char.lstrip(AR_S, b"_"), npt.NDArray[np.bytes_]) +assert_type(np.char.lstrip(AR_T), AR_T_alias) +assert_type(np.char.lstrip(AR_T, "_"), AR_TU_alias) + +assert_type(np.char.rstrip(AR_U), npt.NDArray[np.str_]) +assert_type(np.char.rstrip(AR_S, b"_"), npt.NDArray[np.bytes_]) +assert_type(np.char.rstrip(AR_T), AR_T_alias) +assert_type(np.char.rstrip(AR_T, "_"), AR_TU_alias) + +assert_type(np.char.strip(AR_U), npt.NDArray[np.str_]) +assert_type(np.char.strip(AR_S, b"_"), npt.NDArray[np.bytes_]) +assert_type(np.char.strip(AR_T), AR_T_alias) +assert_type(np.char.strip(AR_T, "_"), AR_TU_alias) + +assert_type(np.char.count(AR_U, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(np.char.count(AR_S, [b"a", b"b", b"c"], end=9), npt.NDArray[np.int_]) +assert_type(np.char.count(AR_T, AR_T, start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(np.char.count(AR_T, ["a", "b", "c"], end=9), npt.NDArray[np.int_]) + +assert_type(np.char.partition(AR_U, "\n"), npt.NDArray[np.str_]) +assert_type(np.char.partition(AR_S, [b"a", b"b", b"c"]), npt.NDArray[np.bytes_]) +assert_type(np.char.partition(AR_T, "\n"), AR_TU_alias) + +assert_type(np.char.rpartition(AR_U, "\n"), npt.NDArray[np.str_]) +assert_type(np.char.rpartition(AR_S, [b"a", b"b", b"c"]), npt.NDArray[np.bytes_]) +assert_type(np.char.rpartition(AR_T, "\n"), AR_TU_alias) + +assert_type(np.char.replace(AR_U, "_", "-"), npt.NDArray[np.str_]) +assert_type(np.char.replace(AR_S, [b"_", b""], [b"a", b"b"]), npt.NDArray[np.bytes_]) +assert_type(np.char.replace(AR_T, "_", "_"), AR_TU_alias) + +assert_type(np.char.split(AR_U, "_"), npt.NDArray[np.object_]) +assert_type(np.char.split(AR_S, maxsplit=[1, 2, 3]), npt.NDArray[np.object_]) +assert_type(np.char.split(AR_T, "_"), npt.NDArray[np.object_]) + +assert_type(np.char.rsplit(AR_U, "_"), npt.NDArray[np.object_]) +assert_type(np.char.rsplit(AR_S, maxsplit=[1, 2, 3]), npt.NDArray[np.object_]) +assert_type(np.char.rsplit(AR_T, "_"), npt.NDArray[np.object_]) + +assert_type(np.char.splitlines(AR_U), npt.NDArray[np.object_]) +assert_type(np.char.splitlines(AR_S, keepends=[True, True, False]), npt.NDArray[np.object_]) +assert_type(np.char.splitlines(AR_T), npt.NDArray[np.object_]) + +assert_type(np.char.lower(AR_U), npt.NDArray[np.str_]) +assert_type(np.char.lower(AR_S), npt.NDArray[np.bytes_]) +assert_type(np.char.lower(AR_T), AR_T_alias) + +assert_type(np.char.upper(AR_U), npt.NDArray[np.str_]) +assert_type(np.char.upper(AR_S), npt.NDArray[np.bytes_]) +assert_type(np.char.upper(AR_T), AR_T_alias) + +assert_type(np.char.swapcase(AR_U), npt.NDArray[np.str_]) +assert_type(np.char.swapcase(AR_S), npt.NDArray[np.bytes_]) +assert_type(np.char.swapcase(AR_T), AR_T_alias) + +assert_type(np.char.title(AR_U), npt.NDArray[np.str_]) +assert_type(np.char.title(AR_S), npt.NDArray[np.bytes_]) +assert_type(np.char.title(AR_T), AR_T_alias) + +assert_type(np.char.zfill(AR_U, 5), npt.NDArray[np.str_]) +assert_type(np.char.zfill(AR_S, [2, 3, 4]), npt.NDArray[np.bytes_]) +assert_type(np.char.zfill(AR_T, 5), AR_T_alias) + +assert_type(np.char.endswith(AR_U, "a", start=[1, 2, 3]), npt.NDArray[np.bool]) +assert_type(np.char.endswith(AR_S, [b"a", b"b", b"c"], end=9), npt.NDArray[np.bool]) +assert_type(np.char.endswith(AR_T, "a", start=[1, 2, 3]), npt.NDArray[np.bool]) + +assert_type(np.char.startswith(AR_U, "a", start=[1, 2, 3]), npt.NDArray[np.bool]) +assert_type(np.char.startswith(AR_S, [b"a", b"b", b"c"], end=9), npt.NDArray[np.bool]) +assert_type(np.char.startswith(AR_T, "a", start=[1, 2, 3]), npt.NDArray[np.bool]) + +assert_type(np.char.find(AR_U, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(np.char.find(AR_S, [b"a", b"b", b"c"], end=9), npt.NDArray[np.int_]) +assert_type(np.char.find(AR_T, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) + +assert_type(np.char.rfind(AR_U, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(np.char.rfind(AR_S, [b"a", b"b", b"c"], end=9), npt.NDArray[np.int_]) +assert_type(np.char.rfind(AR_T, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) + +assert_type(np.char.index(AR_U, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(np.char.index(AR_S, [b"a", b"b", b"c"], end=9), npt.NDArray[np.int_]) +assert_type(np.char.index(AR_T, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) + +assert_type(np.char.rindex(AR_U, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(np.char.rindex(AR_S, [b"a", b"b", b"c"], end=9), npt.NDArray[np.int_]) +assert_type(np.char.rindex(AR_T, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) + +assert_type(np.char.isalpha(AR_U), npt.NDArray[np.bool]) +assert_type(np.char.isalpha(AR_S), npt.NDArray[np.bool]) +assert_type(np.char.isalpha(AR_T), npt.NDArray[np.bool]) + +assert_type(np.char.isalnum(AR_U), npt.NDArray[np.bool]) +assert_type(np.char.isalnum(AR_S), npt.NDArray[np.bool]) +assert_type(np.char.isalnum(AR_T), npt.NDArray[np.bool]) + +assert_type(np.char.isdecimal(AR_U), npt.NDArray[np.bool]) +assert_type(np.char.isdecimal(AR_T), npt.NDArray[np.bool]) + +assert_type(np.char.isdigit(AR_U), npt.NDArray[np.bool]) +assert_type(np.char.isdigit(AR_S), npt.NDArray[np.bool]) +assert_type(np.char.isdigit(AR_T), npt.NDArray[np.bool]) + +assert_type(np.char.islower(AR_U), npt.NDArray[np.bool]) +assert_type(np.char.islower(AR_S), npt.NDArray[np.bool]) +assert_type(np.char.islower(AR_T), npt.NDArray[np.bool]) + +assert_type(np.char.isnumeric(AR_U), npt.NDArray[np.bool]) +assert_type(np.char.isnumeric(AR_T), npt.NDArray[np.bool]) + +assert_type(np.char.isspace(AR_U), npt.NDArray[np.bool]) +assert_type(np.char.isspace(AR_S), npt.NDArray[np.bool]) +assert_type(np.char.isspace(AR_T), npt.NDArray[np.bool]) + +assert_type(np.char.istitle(AR_U), npt.NDArray[np.bool]) +assert_type(np.char.istitle(AR_S), npt.NDArray[np.bool]) +assert_type(np.char.istitle(AR_T), npt.NDArray[np.bool]) + +assert_type(np.char.isupper(AR_U), npt.NDArray[np.bool]) +assert_type(np.char.isupper(AR_S), npt.NDArray[np.bool]) +assert_type(np.char.isupper(AR_T), npt.NDArray[np.bool]) + +assert_type(np.char.str_len(AR_U), npt.NDArray[np.int_]) +assert_type(np.char.str_len(AR_S), npt.NDArray[np.int_]) +assert_type(np.char.str_len(AR_T), npt.NDArray[np.int_]) + +assert_type(np.char.translate(AR_U, ""), npt.NDArray[np.str_]) +assert_type(np.char.translate(AR_S, ""), npt.NDArray[np.bytes_]) +assert_type(np.char.translate(AR_T, ""), AR_T_alias) + +assert_type(np.char.array(AR_U), np.char.chararray[np_t._AnyShape, np.dtype[np.str_]]) +assert_type(np.char.array(AR_S, order="K"), np.char.chararray[np_t._AnyShape, np.dtype[np.bytes_]]) +assert_type(np.char.array("bob", copy=True), np.char.chararray[np_t._AnyShape, np.dtype[np.str_]]) +assert_type(np.char.array(b"bob", itemsize=5), np.char.chararray[np_t._AnyShape, np.dtype[np.bytes_]]) +assert_type(np.char.array(1, unicode=False), np.char.chararray[np_t._AnyShape, np.dtype[np.bytes_]]) +assert_type(np.char.array(1, unicode=True), np.char.chararray[np_t._AnyShape, np.dtype[np.str_]]) +assert_type(np.char.array(1), np.char.chararray[np_t._AnyShape, np.dtype[np.str_]] | np.char.chararray[np_t._AnyShape, np.dtype[np.bytes_]]) +assert_type(np.char.array(AR_U, unicode=False), np.char.chararray[np_t._AnyShape, np.dtype[np.bytes_]]) +assert_type(np.char.array(AR_S, unicode=True), np.char.chararray[np_t._AnyShape, np.dtype[np.str_]]) + +assert_type(np.char.asarray(AR_U), np.char.chararray[np_t._AnyShape, np.dtype[np.str_]]) +assert_type(np.char.asarray(AR_S, order="K"), np.char.chararray[np_t._AnyShape, np.dtype[np.bytes_]]) +assert_type(np.char.asarray("bob"), np.char.chararray[np_t._AnyShape, np.dtype[np.str_]]) +assert_type(np.char.asarray(b"bob", itemsize=5), np.char.chararray[np_t._AnyShape, np.dtype[np.bytes_]]) +assert_type(np.char.asarray(1, unicode=False), np.char.chararray[np_t._AnyShape, np.dtype[np.bytes_]]) +assert_type(np.char.asarray(1, unicode=True), np.char.chararray[np_t._AnyShape, np.dtype[np.str_]]) +assert_type(np.char.asarray(1), np.char.chararray[np_t._AnyShape, np.dtype[np.str_]] | np.char.chararray[np_t._AnyShape, np.dtype[np.bytes_]]) +assert_type(np.char.asarray(AR_U, unicode=False), np.char.chararray[np_t._AnyShape, np.dtype[np.bytes_]]) +assert_type(np.char.asarray(AR_S, unicode=True), np.char.chararray[np_t._AnyShape, np.dtype[np.str_]]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/chararray.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/chararray.pyi new file mode 100644 index 0000000000000000000000000000000000000000..5c3dc85038db9d2b190db3e4c423d698eeece3ed --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/chararray.pyi @@ -0,0 +1,138 @@ +from typing import Any, TypeAlias, assert_type + +import numpy as np +import numpy.typing as npt + +_BytesCharArray: TypeAlias = np.char.chararray[tuple[Any, ...], np.dtype[np.bytes_]] +_StrCharArray: TypeAlias = np.char.chararray[tuple[Any, ...], np.dtype[np.str_]] + +AR_U: _StrCharArray +AR_S: _BytesCharArray + +assert_type(AR_U == AR_U, npt.NDArray[np.bool]) +assert_type(AR_S == AR_S, npt.NDArray[np.bool]) + +assert_type(AR_U != AR_U, npt.NDArray[np.bool]) +assert_type(AR_S != AR_S, npt.NDArray[np.bool]) + +assert_type(AR_U >= AR_U, npt.NDArray[np.bool]) +assert_type(AR_S >= AR_S, npt.NDArray[np.bool]) + +assert_type(AR_U <= AR_U, npt.NDArray[np.bool]) +assert_type(AR_S <= AR_S, npt.NDArray[np.bool]) + +assert_type(AR_U > AR_U, npt.NDArray[np.bool]) +assert_type(AR_S > AR_S, npt.NDArray[np.bool]) + +assert_type(AR_U < AR_U, npt.NDArray[np.bool]) +assert_type(AR_S < AR_S, npt.NDArray[np.bool]) + +assert_type(AR_U * 5, _StrCharArray) +assert_type(AR_S * [5], _BytesCharArray) + +assert_type(AR_U % "test", _StrCharArray) +assert_type(AR_S % b"test", _BytesCharArray) + +assert_type(AR_U.capitalize(), _StrCharArray) +assert_type(AR_S.capitalize(), _BytesCharArray) + +assert_type(AR_U.center(5), _StrCharArray) +assert_type(AR_S.center([2, 3, 4], b"a"), _BytesCharArray) + +assert_type(AR_U.encode(), _BytesCharArray) +assert_type(AR_S.decode(), _StrCharArray) + +assert_type(AR_U.expandtabs(), _StrCharArray) +assert_type(AR_S.expandtabs(tabsize=4), _BytesCharArray) + +assert_type(AR_U.join("_"), _StrCharArray) +assert_type(AR_S.join([b"_", b""]), _BytesCharArray) + +assert_type(AR_U.ljust(5), _StrCharArray) +assert_type(AR_S.ljust([4, 3, 1], fillchar=[b"a", b"b", b"c"]), _BytesCharArray) +assert_type(AR_S.ljust([4, 3, 1], fillchar="a"), _BytesCharArray) +assert_type(AR_U.rjust(5), _StrCharArray) +assert_type(AR_S.rjust([4, 3, 1], fillchar=[b"a", b"b", b"c"]), _BytesCharArray) + +assert_type(AR_U.lstrip(), _StrCharArray) +assert_type(AR_S.lstrip(chars=b"_"), _BytesCharArray) +assert_type(AR_U.rstrip(), _StrCharArray) +assert_type(AR_S.rstrip(chars=b"_"), _BytesCharArray) +assert_type(AR_U.strip(), _StrCharArray) +assert_type(AR_S.strip(chars=b"_"), _BytesCharArray) + +assert_type(AR_U.partition("\n"), _StrCharArray) +assert_type(AR_S.partition([b"a", b"b", b"c"]), _BytesCharArray) +assert_type(AR_U.rpartition("\n"), _StrCharArray) +assert_type(AR_S.rpartition([b"a", b"b", b"c"]), _BytesCharArray) + +assert_type(AR_U.replace("_", "-"), _StrCharArray) +assert_type(AR_S.replace([b"_", b""], [b"a", b"b"]), _BytesCharArray) + +assert_type(AR_U.split("_"), npt.NDArray[np.object_]) +assert_type(AR_S.split(maxsplit=[1, 2, 3]), npt.NDArray[np.object_]) +assert_type(AR_U.rsplit("_"), npt.NDArray[np.object_]) +assert_type(AR_S.rsplit(maxsplit=[1, 2, 3]), npt.NDArray[np.object_]) + +assert_type(AR_U.splitlines(), npt.NDArray[np.object_]) +assert_type(AR_S.splitlines(keepends=[True, True, False]), npt.NDArray[np.object_]) + +assert_type(AR_U.swapcase(), _StrCharArray) +assert_type(AR_S.swapcase(), _BytesCharArray) + +assert_type(AR_U.title(), _StrCharArray) +assert_type(AR_S.title(), _BytesCharArray) + +assert_type(AR_U.upper(), _StrCharArray) +assert_type(AR_S.upper(), _BytesCharArray) + +assert_type(AR_U.zfill(5), _StrCharArray) +assert_type(AR_S.zfill([2, 3, 4]), _BytesCharArray) + +assert_type(AR_U.count("a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(AR_S.count([b"a", b"b", b"c"], end=9), npt.NDArray[np.int_]) + +assert_type(AR_U.endswith("a", start=[1, 2, 3]), npt.NDArray[np.bool]) +assert_type(AR_S.endswith([b"a", b"b", b"c"], end=9), npt.NDArray[np.bool]) +assert_type(AR_U.startswith("a", start=[1, 2, 3]), npt.NDArray[np.bool]) +assert_type(AR_S.startswith([b"a", b"b", b"c"], end=9), npt.NDArray[np.bool]) + +assert_type(AR_U.find("a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(AR_S.find([b"a", b"b", b"c"], end=9), npt.NDArray[np.int_]) +assert_type(AR_U.rfind("a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(AR_S.rfind([b"a", b"b", b"c"], end=9), npt.NDArray[np.int_]) + +assert_type(AR_U.index("a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(AR_S.index([b"a", b"b", b"c"], end=9), npt.NDArray[np.int_]) +assert_type(AR_U.rindex("a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(AR_S.rindex([b"a", b"b", b"c"], end=9), npt.NDArray[np.int_]) + +assert_type(AR_U.isalpha(), npt.NDArray[np.bool]) +assert_type(AR_S.isalpha(), npt.NDArray[np.bool]) + +assert_type(AR_U.isalnum(), npt.NDArray[np.bool]) +assert_type(AR_S.isalnum(), npt.NDArray[np.bool]) + +assert_type(AR_U.isdecimal(), npt.NDArray[np.bool]) +assert_type(AR_S.isdecimal(), npt.NDArray[np.bool]) + +assert_type(AR_U.isdigit(), npt.NDArray[np.bool]) +assert_type(AR_S.isdigit(), npt.NDArray[np.bool]) + +assert_type(AR_U.islower(), npt.NDArray[np.bool]) +assert_type(AR_S.islower(), npt.NDArray[np.bool]) + +assert_type(AR_U.isnumeric(), npt.NDArray[np.bool]) +assert_type(AR_S.isnumeric(), npt.NDArray[np.bool]) + +assert_type(AR_U.isspace(), npt.NDArray[np.bool]) +assert_type(AR_S.isspace(), npt.NDArray[np.bool]) + +assert_type(AR_U.istitle(), npt.NDArray[np.bool]) +assert_type(AR_S.istitle(), npt.NDArray[np.bool]) + +assert_type(AR_U.isupper(), npt.NDArray[np.bool]) +assert_type(AR_S.isupper(), npt.NDArray[np.bool]) + +assert_type(AR_U.__array_finalize__(object()), None) +assert_type(AR_S.__array_finalize__(object()), None) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/comparisons.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/comparisons.pyi new file mode 100644 index 0000000000000000000000000000000000000000..6df5a3d94314629213c5c28fa77ae62a310872dd --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/comparisons.pyi @@ -0,0 +1,264 @@ +import decimal +import fractions +from typing import assert_type + +import numpy as np +import numpy.typing as npt + +c16 = np.complex128() +f8 = np.float64() +i8 = np.int64() +u8 = np.uint64() + +c8 = np.complex64() +f4 = np.float32() +i4 = np.int32() +u4 = np.uint32() + +dt = np.datetime64(0, "D") +td = np.timedelta64(0, "D") + +b_ = np.bool() + +b = False +c = complex() +f = 0.0 +i = 0 + +AR = np.array([0], dtype=np.int64) +AR.setflags(write=False) + +SEQ = (0, 1, 2, 3, 4) + +# object-like comparisons + +assert_type(i8 > fractions.Fraction(1, 5), np.bool) +assert_type(i8 > [fractions.Fraction(1, 5)], npt.NDArray[np.bool]) +assert_type(i8 > decimal.Decimal("1.5"), np.bool) +assert_type(i8 > [decimal.Decimal("1.5")], npt.NDArray[np.bool]) + +# Time structures + +assert_type(dt > dt, np.bool) + +assert_type(td > td, np.bool) +assert_type(td > i, np.bool) +assert_type(td > i4, np.bool) +assert_type(td > i8, np.bool) + +assert_type(td > AR, npt.NDArray[np.bool]) +assert_type(td > SEQ, npt.NDArray[np.bool]) +assert_type(AR > SEQ, npt.NDArray[np.bool]) +assert_type(AR > td, npt.NDArray[np.bool]) +assert_type(SEQ > td, npt.NDArray[np.bool]) +assert_type(SEQ > AR, npt.NDArray[np.bool]) + +# boolean + +assert_type(b_ > b, np.bool) +assert_type(b_ > b_, np.bool) +assert_type(b_ > i, np.bool) +assert_type(b_ > i8, np.bool) +assert_type(b_ > i4, np.bool) +assert_type(b_ > u8, np.bool) +assert_type(b_ > u4, np.bool) +assert_type(b_ > f, np.bool) +assert_type(b_ > f8, np.bool) +assert_type(b_ > f4, np.bool) +assert_type(b_ > c, np.bool) +assert_type(b_ > c16, np.bool) +assert_type(b_ > c8, np.bool) +assert_type(b_ > AR, npt.NDArray[np.bool]) +assert_type(b_ > SEQ, npt.NDArray[np.bool]) + +# Complex + +assert_type(c16 > c16, np.bool) +assert_type(c16 > f8, np.bool) +assert_type(c16 > i8, np.bool) +assert_type(c16 > c8, np.bool) +assert_type(c16 > f4, np.bool) +assert_type(c16 > i4, np.bool) +assert_type(c16 > b_, np.bool) +assert_type(c16 > b, np.bool) +assert_type(c16 > c, np.bool) +assert_type(c16 > f, np.bool) +assert_type(c16 > i, np.bool) +assert_type(c16 > AR, npt.NDArray[np.bool]) +assert_type(c16 > SEQ, npt.NDArray[np.bool]) + +assert_type(c16 > c16, np.bool) +assert_type(f8 > c16, np.bool) +assert_type(i8 > c16, np.bool) +assert_type(c8 > c16, np.bool) +assert_type(f4 > c16, np.bool) +assert_type(i4 > c16, np.bool) +assert_type(b_ > c16, np.bool) +assert_type(b > c16, np.bool) +assert_type(c > c16, np.bool) +assert_type(f > c16, np.bool) +assert_type(i > c16, np.bool) +assert_type(AR > c16, npt.NDArray[np.bool]) +assert_type(SEQ > c16, npt.NDArray[np.bool]) + +assert_type(c8 > c16, np.bool) +assert_type(c8 > f8, np.bool) +assert_type(c8 > i8, np.bool) +assert_type(c8 > c8, np.bool) +assert_type(c8 > f4, np.bool) +assert_type(c8 > i4, np.bool) +assert_type(c8 > b_, np.bool) +assert_type(c8 > b, np.bool) +assert_type(c8 > c, np.bool) +assert_type(c8 > f, np.bool) +assert_type(c8 > i, np.bool) +assert_type(c8 > AR, npt.NDArray[np.bool]) +assert_type(c8 > SEQ, npt.NDArray[np.bool]) + +assert_type(c16 > c8, np.bool) +assert_type(f8 > c8, np.bool) +assert_type(i8 > c8, np.bool) +assert_type(c8 > c8, np.bool) +assert_type(f4 > c8, np.bool) +assert_type(i4 > c8, np.bool) +assert_type(b_ > c8, np.bool) +assert_type(b > c8, np.bool) +assert_type(c > c8, np.bool) +assert_type(f > c8, np.bool) +assert_type(i > c8, np.bool) +assert_type(AR > c8, npt.NDArray[np.bool]) +assert_type(SEQ > c8, npt.NDArray[np.bool]) + +# Float + +assert_type(f8 > f8, np.bool) +assert_type(f8 > i8, np.bool) +assert_type(f8 > f4, np.bool) +assert_type(f8 > i4, np.bool) +assert_type(f8 > b_, np.bool) +assert_type(f8 > b, np.bool) +assert_type(f8 > c, np.bool) +assert_type(f8 > f, np.bool) +assert_type(f8 > i, np.bool) +assert_type(f8 > AR, npt.NDArray[np.bool]) +assert_type(f8 > SEQ, npt.NDArray[np.bool]) + +assert_type(f8 > f8, np.bool) +assert_type(i8 > f8, np.bool) +assert_type(f4 > f8, np.bool) +assert_type(i4 > f8, np.bool) +assert_type(b_ > f8, np.bool) +assert_type(b > f8, np.bool) +assert_type(c > f8, np.bool) +assert_type(f > f8, np.bool) +assert_type(i > f8, np.bool) +assert_type(AR > f8, npt.NDArray[np.bool]) +assert_type(SEQ > f8, npt.NDArray[np.bool]) + +assert_type(f4 > f8, np.bool) +assert_type(f4 > i8, np.bool) +assert_type(f4 > f4, np.bool) +assert_type(f4 > i4, np.bool) +assert_type(f4 > b_, np.bool) +assert_type(f4 > b, np.bool) +assert_type(f4 > c, np.bool) +assert_type(f4 > f, np.bool) +assert_type(f4 > i, np.bool) +assert_type(f4 > AR, npt.NDArray[np.bool]) +assert_type(f4 > SEQ, npt.NDArray[np.bool]) + +assert_type(f8 > f4, np.bool) +assert_type(i8 > f4, np.bool) +assert_type(f4 > f4, np.bool) +assert_type(i4 > f4, np.bool) +assert_type(b_ > f4, np.bool) +assert_type(b > f4, np.bool) +assert_type(c > f4, np.bool) +assert_type(f > f4, np.bool) +assert_type(i > f4, np.bool) +assert_type(AR > f4, npt.NDArray[np.bool]) +assert_type(SEQ > f4, npt.NDArray[np.bool]) + +# Int + +assert_type(i8 > i8, np.bool) +assert_type(i8 > u8, np.bool) +assert_type(i8 > i4, np.bool) +assert_type(i8 > u4, np.bool) +assert_type(i8 > b_, np.bool) +assert_type(i8 > b, np.bool) +assert_type(i8 > c, np.bool) +assert_type(i8 > f, np.bool) +assert_type(i8 > i, np.bool) +assert_type(i8 > AR, npt.NDArray[np.bool]) +assert_type(i8 > SEQ, npt.NDArray[np.bool]) + +assert_type(u8 > u8, np.bool) +assert_type(u8 > i4, np.bool) +assert_type(u8 > u4, np.bool) +assert_type(u8 > b_, np.bool) +assert_type(u8 > b, np.bool) +assert_type(u8 > c, np.bool) +assert_type(u8 > f, np.bool) +assert_type(u8 > i, np.bool) +assert_type(u8 > AR, npt.NDArray[np.bool]) +assert_type(u8 > SEQ, npt.NDArray[np.bool]) + +assert_type(i8 > i8, np.bool) +assert_type(u8 > i8, np.bool) +assert_type(i4 > i8, np.bool) +assert_type(u4 > i8, np.bool) +assert_type(b_ > i8, np.bool) +assert_type(b > i8, np.bool) +assert_type(c > i8, np.bool) +assert_type(f > i8, np.bool) +assert_type(i > i8, np.bool) +assert_type(AR > i8, npt.NDArray[np.bool]) +assert_type(SEQ > i8, npt.NDArray[np.bool]) + +assert_type(u8 > u8, np.bool) +assert_type(i4 > u8, np.bool) +assert_type(u4 > u8, np.bool) +assert_type(b_ > u8, np.bool) +assert_type(b > u8, np.bool) +assert_type(c > u8, np.bool) +assert_type(f > u8, np.bool) +assert_type(i > u8, np.bool) +assert_type(AR > u8, npt.NDArray[np.bool]) +assert_type(SEQ > u8, npt.NDArray[np.bool]) + +assert_type(i4 > i8, np.bool) +assert_type(i4 > i4, np.bool) +assert_type(i4 > i, np.bool) +assert_type(i4 > b_, np.bool) +assert_type(i4 > b, np.bool) +assert_type(i4 > AR, npt.NDArray[np.bool]) +assert_type(i4 > SEQ, npt.NDArray[np.bool]) + +assert_type(u4 > i8, np.bool) +assert_type(u4 > i4, np.bool) +assert_type(u4 > u8, np.bool) +assert_type(u4 > u4, np.bool) +assert_type(u4 > i, np.bool) +assert_type(u4 > b_, np.bool) +assert_type(u4 > b, np.bool) +assert_type(u4 > AR, npt.NDArray[np.bool]) +assert_type(u4 > SEQ, npt.NDArray[np.bool]) + +assert_type(i8 > i4, np.bool) +assert_type(i4 > i4, np.bool) +assert_type(i > i4, np.bool) +assert_type(b_ > i4, np.bool) +assert_type(b > i4, np.bool) +assert_type(AR > i4, npt.NDArray[np.bool]) +assert_type(SEQ > i4, npt.NDArray[np.bool]) + +assert_type(i8 > u4, np.bool) +assert_type(i4 > u4, np.bool) +assert_type(u8 > u4, np.bool) +assert_type(u4 > u4, np.bool) +assert_type(b_ > u4, np.bool) +assert_type(b > u4, np.bool) +assert_type(i > u4, np.bool) +assert_type(AR > u4, npt.NDArray[np.bool]) +assert_type(SEQ > u4, npt.NDArray[np.bool]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/constants.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/constants.pyi new file mode 100644 index 0000000000000000000000000000000000000000..d4474f46ce7e19571125dc45669692a1c501a5b9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/constants.pyi @@ -0,0 +1,14 @@ +from typing import Literal, assert_type + +import numpy as np + +assert_type(np.e, float) +assert_type(np.euler_gamma, float) +assert_type(np.inf, float) +assert_type(np.nan, float) +assert_type(np.pi, float) + +assert_type(np.little_endian, bool) + +assert_type(np.True_, np.bool[Literal[True]]) +assert_type(np.False_, np.bool[Literal[False]]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ctypeslib.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ctypeslib.pyi new file mode 100644 index 0000000000000000000000000000000000000000..0564d725cf62f2419460b0f7cdabfd890947438e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ctypeslib.pyi @@ -0,0 +1,81 @@ +import ctypes as ct +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt +from numpy import ctypeslib + +AR_bool: npt.NDArray[np.bool] +AR_ubyte: npt.NDArray[np.ubyte] +AR_ushort: npt.NDArray[np.ushort] +AR_uintc: npt.NDArray[np.uintc] +AR_ulong: npt.NDArray[np.ulong] +AR_ulonglong: npt.NDArray[np.ulonglong] +AR_byte: npt.NDArray[np.byte] +AR_short: npt.NDArray[np.short] +AR_intc: npt.NDArray[np.intc] +AR_long: npt.NDArray[np.long] +AR_longlong: npt.NDArray[np.longlong] +AR_single: npt.NDArray[np.single] +AR_double: npt.NDArray[np.double] +AR_longdouble: npt.NDArray[np.longdouble] +AR_void: npt.NDArray[np.void] + +pointer: ct._Pointer[Any] + +assert_type(np.ctypeslib.c_intp(), ctypeslib.c_intp) + +assert_type(np.ctypeslib.ndpointer(), type[ctypeslib._ndptr[None]]) +assert_type(np.ctypeslib.ndpointer(dtype=np.float64), type[ctypeslib._ndptr[np.dtype[np.float64]]]) +assert_type(np.ctypeslib.ndpointer(dtype=float), type[ctypeslib._ndptr[np.dtype]]) +assert_type(np.ctypeslib.ndpointer(shape=(10, 3)), type[ctypeslib._ndptr[None]]) +assert_type(np.ctypeslib.ndpointer(np.int64, shape=(10, 3)), type[ctypeslib._concrete_ndptr[np.dtype[np.int64]]]) +assert_type(np.ctypeslib.ndpointer(int, shape=(1,)), type[np.ctypeslib._concrete_ndptr[np.dtype]]) + +assert_type(np.ctypeslib.as_ctypes_type(np.bool), type[ct.c_bool]) +assert_type(np.ctypeslib.as_ctypes_type(np.ubyte), type[ct.c_ubyte]) +assert_type(np.ctypeslib.as_ctypes_type(np.ushort), type[ct.c_ushort]) +assert_type(np.ctypeslib.as_ctypes_type(np.uintc), type[ct.c_uint]) +assert_type(np.ctypeslib.as_ctypes_type(np.byte), type[ct.c_byte]) +assert_type(np.ctypeslib.as_ctypes_type(np.short), type[ct.c_short]) +assert_type(np.ctypeslib.as_ctypes_type(np.intc), type[ct.c_int]) +assert_type(np.ctypeslib.as_ctypes_type(np.single), type[ct.c_float]) +assert_type(np.ctypeslib.as_ctypes_type(np.double), type[ct.c_double]) +assert_type(np.ctypeslib.as_ctypes_type(ct.c_double), type[ct.c_double]) +assert_type(np.ctypeslib.as_ctypes_type("q"), type[ct.c_longlong]) +assert_type(np.ctypeslib.as_ctypes_type([("i8", np.int64), ("f8", np.float64)]), type[Any]) +assert_type(np.ctypeslib.as_ctypes_type("i8"), type[Any]) +assert_type(np.ctypeslib.as_ctypes_type("f8"), type[Any]) + +assert_type(np.ctypeslib.as_ctypes(AR_bool.take(0)), ct.c_bool) +assert_type(np.ctypeslib.as_ctypes(AR_ubyte.take(0)), ct.c_ubyte) +assert_type(np.ctypeslib.as_ctypes(AR_ushort.take(0)), ct.c_ushort) +assert_type(np.ctypeslib.as_ctypes(AR_uintc.take(0)), ct.c_uint) + +assert_type(np.ctypeslib.as_ctypes(AR_byte.take(0)), ct.c_byte) +assert_type(np.ctypeslib.as_ctypes(AR_short.take(0)), ct.c_short) +assert_type(np.ctypeslib.as_ctypes(AR_intc.take(0)), ct.c_int) +assert_type(np.ctypeslib.as_ctypes(AR_single.take(0)), ct.c_float) +assert_type(np.ctypeslib.as_ctypes(AR_double.take(0)), ct.c_double) +assert_type(np.ctypeslib.as_ctypes(AR_void.take(0)), Any) +assert_type(np.ctypeslib.as_ctypes(AR_bool), ct.Array[ct.c_bool]) +assert_type(np.ctypeslib.as_ctypes(AR_ubyte), ct.Array[ct.c_ubyte]) +assert_type(np.ctypeslib.as_ctypes(AR_ushort), ct.Array[ct.c_ushort]) +assert_type(np.ctypeslib.as_ctypes(AR_uintc), ct.Array[ct.c_uint]) +assert_type(np.ctypeslib.as_ctypes(AR_byte), ct.Array[ct.c_byte]) +assert_type(np.ctypeslib.as_ctypes(AR_short), ct.Array[ct.c_short]) +assert_type(np.ctypeslib.as_ctypes(AR_intc), ct.Array[ct.c_int]) +assert_type(np.ctypeslib.as_ctypes(AR_single), ct.Array[ct.c_float]) +assert_type(np.ctypeslib.as_ctypes(AR_double), ct.Array[ct.c_double]) +assert_type(np.ctypeslib.as_ctypes(AR_void), ct.Array[Any]) + +assert_type(np.ctypeslib.as_array(AR_ubyte), npt.NDArray[np.ubyte]) +assert_type(np.ctypeslib.as_array(1), npt.NDArray[Any]) +assert_type(np.ctypeslib.as_array(pointer), npt.NDArray[Any]) + +assert_type(np.ctypeslib.as_ctypes_type(np.long), type[ct.c_long]) +assert_type(np.ctypeslib.as_ctypes_type(np.ulong), type[ct.c_ulong]) +assert_type(np.ctypeslib.as_ctypes(AR_ulong), ct.Array[ct.c_ulong]) +assert_type(np.ctypeslib.as_ctypes(AR_long), ct.Array[ct.c_long]) +assert_type(np.ctypeslib.as_ctypes(AR_long.take(0)), ct.c_long) +assert_type(np.ctypeslib.as_ctypes(AR_ulong.take(0)), ct.c_ulong) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/datasource.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/datasource.pyi new file mode 100644 index 0000000000000000000000000000000000000000..9f017911a1ff89dd1f80c059fb13976bc60cd12b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/datasource.pyi @@ -0,0 +1,23 @@ +from pathlib import Path +from typing import IO, Any, assert_type + +import numpy as np + +path1: Path +path2: str + +d1 = np.lib.npyio.DataSource(path1) +d2 = np.lib.npyio.DataSource(path2) +d3 = np.lib.npyio.DataSource(None) + +assert_type(d1.abspath("..."), str) +assert_type(d2.abspath("..."), str) +assert_type(d3.abspath("..."), str) + +assert_type(d1.exists("..."), bool) +assert_type(d2.exists("..."), bool) +assert_type(d3.exists("..."), bool) + +assert_type(d1.open("...", "r"), IO[Any]) +assert_type(d2.open("...", encoding="utf8"), IO[Any]) +assert_type(d3.open("...", newline="/n"), IO[Any]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/dtype.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/dtype.pyi new file mode 100644 index 0000000000000000000000000000000000000000..7f670b3be51c6507b5cba4469f7e96c878cea571 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/dtype.pyi @@ -0,0 +1,132 @@ +import ctypes as ct +import datetime as dt +from decimal import Decimal +from fractions import Fraction +from typing import Any, Literal, LiteralString, TypeAlias, assert_type + +import numpy as np +from numpy.dtypes import StringDType + +# a combination of likely `object` dtype-like candidates (no `_co`) +_PyObjectLike: TypeAlias = Decimal | Fraction | dt.datetime | dt.timedelta + +dtype_U: np.dtype[np.str_] +dtype_V: np.dtype[np.void] +dtype_i8: np.dtype[np.int64] + +py_object: type[_PyObjectLike] +py_character: type[str | bytes] + +ct_floating: type[ct.c_float | ct.c_double | ct.c_longdouble] +ct_number: type[ct.c_uint8 | ct.c_float] +ct_generic: type[ct.c_bool | ct.c_char] + +cs_integer: Literal["u1", "V", "S"] +cs_generic: Literal["H", "U", "h", "|M8[Y]", "?"] + +dt_inexact: np.dtype[np.inexact] +dt_string: StringDType + +assert_type(np.dtype(np.float64), np.dtype[np.float64]) +assert_type(np.dtype(np.float64, metadata={"test": "test"}), np.dtype[np.float64]) +assert_type(np.dtype(np.int64), np.dtype[np.int64]) + +# String aliases +assert_type(np.dtype("float64"), np.dtype[np.float64]) +assert_type(np.dtype("float32"), np.dtype[np.float32]) +assert_type(np.dtype("int64"), np.dtype[np.int64]) +assert_type(np.dtype("int32"), np.dtype[np.int32]) +assert_type(np.dtype("bool"), np.dtype[np.bool]) +assert_type(np.dtype("bytes"), np.dtype[np.bytes_]) +assert_type(np.dtype("str"), np.dtype[np.str_]) + +# Python types +assert_type(np.dtype(bool), np.dtype[np.bool]) +assert_type(np.dtype(int), np.dtype[np.int_ | np.bool]) +assert_type(np.dtype(float), np.dtype[np.float64 | np.int_ | np.bool]) +assert_type(np.dtype(complex), np.dtype[np.complex128 | np.float64 | np.int_ | np.bool]) +assert_type(np.dtype(py_object), np.dtype[np.object_]) +assert_type(np.dtype(str), np.dtype[np.str_]) +assert_type(np.dtype(bytes), np.dtype[np.bytes_]) +assert_type(np.dtype(memoryview), np.dtype[np.void]) +assert_type(np.dtype(py_character), np.dtype[np.character]) + +# object types +assert_type(np.dtype(list), np.dtype[np.object_]) +assert_type(np.dtype(dt.datetime), np.dtype[np.object_]) +assert_type(np.dtype(dt.timedelta), np.dtype[np.object_]) +assert_type(np.dtype(Decimal), np.dtype[np.object_]) +assert_type(np.dtype(Fraction), np.dtype[np.object_]) + +# char-codes +assert_type(np.dtype("?"), np.dtype[np.bool]) +assert_type(np.dtype("|b1"), np.dtype[np.bool]) +assert_type(np.dtype("u1"), np.dtype[np.uint8]) +assert_type(np.dtype("l"), np.dtype[np.long]) +assert_type(np.dtype("longlong"), np.dtype[np.longlong]) +assert_type(np.dtype(">g"), np.dtype[np.longdouble]) +assert_type(np.dtype(cs_integer), np.dtype[np.integer]) + +# ctypes +assert_type(np.dtype(ct.c_double), np.dtype[np.float64]) # see numpy/numpy#29155 +assert_type(np.dtype(ct.c_longlong), np.dtype[np.longlong]) +assert_type(np.dtype(ct.c_uint32), np.dtype[np.uint32]) +assert_type(np.dtype(ct.c_bool), np.dtype[np.bool]) +assert_type(np.dtype(ct.c_char), np.dtype[np.bytes_]) +assert_type(np.dtype(ct.py_object), np.dtype[np.object_]) + +# Special case for None +assert_type(np.dtype(None), np.dtype[np.float64]) + +# dtypes of dtypes +assert_type(np.dtype(np.dtype(np.float64)), np.dtype[np.float64]) +assert_type(np.dtype(dt_inexact), np.dtype[np.inexact]) + +# Parameterized dtypes +assert_type(np.dtype("S8"), np.dtype) + +# Void +assert_type(np.dtype(("U", 10)), np.dtype[np.void]) +assert_type(np.dtype({"formats": (int, "u8"), "names": ("n", "B")}), np.dtype[np.void]) + +# StringDType +assert_type(np.dtype(dt_string), StringDType) +assert_type(np.dtype("T"), StringDType) +assert_type(np.dtype("=T"), StringDType) +assert_type(np.dtype("|T"), StringDType) + +# Methods and attributes +assert_type(dtype_U.base, np.dtype) +assert_type(dtype_U.subdtype, tuple[np.dtype, tuple[Any, ...]] | None) +assert_type(dtype_U.newbyteorder(), np.dtype[np.str_]) +assert_type(dtype_U.type, type[np.str_]) +assert_type(dtype_U.name, LiteralString) +assert_type(dtype_U.names, tuple[str, ...] | None) + +assert_type(dtype_U * 0, np.dtype[np.str_]) +assert_type(dtype_U * 1, np.dtype[np.str_]) +assert_type(dtype_U * 2, np.dtype[np.str_]) + +assert_type(dtype_i8 * 0, np.dtype[np.void]) +assert_type(dtype_i8 * 1, np.dtype[np.int64]) +assert_type(dtype_i8 * 2, np.dtype[np.void]) + +assert_type(0 * dtype_U, np.dtype[np.str_]) +assert_type(1 * dtype_U, np.dtype[np.str_]) +assert_type(2 * dtype_U, np.dtype[np.str_]) + +assert_type(0 * dtype_i8, np.dtype) +assert_type(1 * dtype_i8, np.dtype) +assert_type(2 * dtype_i8, np.dtype) + +assert_type(dtype_V["f0"], np.dtype) +assert_type(dtype_V[0], np.dtype) +assert_type(dtype_V[["f0", "f1"]], np.dtype[np.void]) +assert_type(dtype_V[["f0"]], np.dtype[np.void]) + +class _D: + __numpy_dtype__: np.dtype[np.int8] + +assert_type(np.dtype(_D()), np.dtype[np.int8]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/einsumfunc.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/einsumfunc.pyi new file mode 100644 index 0000000000000000000000000000000000000000..cc58f006e249bb5fd520fa45bbe1f1690e4c203d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/einsumfunc.pyi @@ -0,0 +1,39 @@ +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt + +AR_LIKE_b: list[bool] +AR_LIKE_u: list[np.uint32] +AR_LIKE_i: list[int] +AR_LIKE_f: list[float] +AR_LIKE_c: list[complex] +AR_LIKE_U: list[str] +AR_o: npt.NDArray[np.object_] + +OUT_f: npt.NDArray[np.float64] + +assert_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_b), Any) +assert_type(np.einsum("i,i->i", AR_o, AR_o), Any) +assert_type(np.einsum("i,i->i", AR_LIKE_u, AR_LIKE_u), Any) +assert_type(np.einsum("i,i->i", AR_LIKE_i, AR_LIKE_i), Any) +assert_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f), Any) +assert_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c), Any) +assert_type(np.einsum("i,i->i", AR_LIKE_b, AR_LIKE_i), Any) +assert_type(np.einsum("i,i,i,i->i", AR_LIKE_b, AR_LIKE_u, AR_LIKE_i, AR_LIKE_c), Any) + +assert_type(np.einsum("i,i->i", AR_LIKE_c, AR_LIKE_c, out=OUT_f), npt.NDArray[np.float64]) +assert_type(np.einsum("i,i->i", AR_LIKE_U, AR_LIKE_U, dtype=bool, casting="unsafe", out=OUT_f), npt.NDArray[np.float64]) +assert_type(np.einsum("i,i->i", AR_LIKE_f, AR_LIKE_f, dtype="c16"), Any) +assert_type(np.einsum("i,i->i", AR_LIKE_U, AR_LIKE_U, dtype=bool, casting="unsafe"), Any) + +assert_type(np.einsum_path("i,i->i", AR_LIKE_b, AR_LIKE_b), tuple[list[Any], str]) +assert_type(np.einsum_path("i,i->i", AR_LIKE_u, AR_LIKE_u), tuple[list[Any], str]) +assert_type(np.einsum_path("i,i->i", AR_LIKE_i, AR_LIKE_i), tuple[list[Any], str]) +assert_type(np.einsum_path("i,i->i", AR_LIKE_f, AR_LIKE_f), tuple[list[Any], str]) +assert_type(np.einsum_path("i,i->i", AR_LIKE_c, AR_LIKE_c), tuple[list[Any], str]) +assert_type(np.einsum_path("i,i->i", AR_LIKE_b, AR_LIKE_i), tuple[list[Any], str]) +assert_type(np.einsum_path("i,i,i,i->i", AR_LIKE_b, AR_LIKE_u, AR_LIKE_i, AR_LIKE_c), tuple[list[Any], str]) + +assert_type(np.einsum([[1, 1], [1, 1]], AR_LIKE_i, AR_LIKE_i), Any) +assert_type(np.einsum_path([[1, 1], [1, 1]], AR_LIKE_i, AR_LIKE_i), tuple[list[Any], str]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/emath.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/emath.pyi new file mode 100644 index 0000000000000000000000000000000000000000..1d7bff893e73445dec3f34e5078ebe19a7d893ed --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/emath.pyi @@ -0,0 +1,54 @@ +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt + +AR_f8: npt.NDArray[np.float64] +AR_c16: npt.NDArray[np.complex128] +f8: np.float64 +c16: np.complex128 + +assert_type(np.emath.sqrt(f8), Any) +assert_type(np.emath.sqrt(AR_f8), npt.NDArray[Any]) +assert_type(np.emath.sqrt(c16), np.complexfloating) +assert_type(np.emath.sqrt(AR_c16), npt.NDArray[np.complexfloating]) + +assert_type(np.emath.log(f8), Any) +assert_type(np.emath.log(AR_f8), npt.NDArray[Any]) +assert_type(np.emath.log(c16), np.complexfloating) +assert_type(np.emath.log(AR_c16), npt.NDArray[np.complexfloating]) + +assert_type(np.emath.log10(f8), Any) +assert_type(np.emath.log10(AR_f8), npt.NDArray[Any]) +assert_type(np.emath.log10(c16), np.complexfloating) +assert_type(np.emath.log10(AR_c16), npt.NDArray[np.complexfloating]) + +assert_type(np.emath.log2(f8), Any) +assert_type(np.emath.log2(AR_f8), npt.NDArray[Any]) +assert_type(np.emath.log2(c16), np.complexfloating) +assert_type(np.emath.log2(AR_c16), npt.NDArray[np.complexfloating]) + +assert_type(np.emath.logn(f8, 2), Any) +assert_type(np.emath.logn(AR_f8, 4), npt.NDArray[Any]) +assert_type(np.emath.logn(f8, 1j), np.complexfloating) +assert_type(np.emath.logn(AR_c16, 1.5), npt.NDArray[np.complexfloating]) + +assert_type(np.emath.power(f8, 2), Any) +assert_type(np.emath.power(AR_f8, 4), npt.NDArray[Any]) +assert_type(np.emath.power(f8, 2j), np.complexfloating) +assert_type(np.emath.power(AR_c16, 1.5), npt.NDArray[np.complexfloating]) + +assert_type(np.emath.arccos(f8), Any) +assert_type(np.emath.arccos(AR_f8), npt.NDArray[Any]) +assert_type(np.emath.arccos(c16), np.complexfloating) +assert_type(np.emath.arccos(AR_c16), npt.NDArray[np.complexfloating]) + +assert_type(np.emath.arcsin(f8), Any) +assert_type(np.emath.arcsin(AR_f8), npt.NDArray[Any]) +assert_type(np.emath.arcsin(c16), np.complexfloating) +assert_type(np.emath.arcsin(AR_c16), npt.NDArray[np.complexfloating]) + +assert_type(np.emath.arctanh(f8), Any) +assert_type(np.emath.arctanh(AR_f8), npt.NDArray[Any]) +assert_type(np.emath.arctanh(c16), np.complexfloating) +assert_type(np.emath.arctanh(AR_c16), npt.NDArray[np.complexfloating]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/fft.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/fft.pyi new file mode 100644 index 0000000000000000000000000000000000000000..dacd2b89777c1453088f2fedee82996bfb1e66ca --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/fft.pyi @@ -0,0 +1,37 @@ +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt + +AR_f8: npt.NDArray[np.float64] +AR_c16: npt.NDArray[np.complex128] +AR_LIKE_f8: list[float] + +assert_type(np.fft.fftshift(AR_f8), npt.NDArray[np.float64]) +assert_type(np.fft.fftshift(AR_LIKE_f8, axes=0), npt.NDArray[Any]) + +assert_type(np.fft.ifftshift(AR_f8), npt.NDArray[np.float64]) +assert_type(np.fft.ifftshift(AR_LIKE_f8, axes=0), npt.NDArray[Any]) + +assert_type(np.fft.fftfreq(5, AR_f8), npt.NDArray[np.floating]) +assert_type(np.fft.fftfreq(np.int64(), AR_c16), npt.NDArray[np.complexfloating]) + +assert_type(np.fft.fftfreq(5, AR_f8), npt.NDArray[np.floating]) +assert_type(np.fft.fftfreq(np.int64(), AR_c16), npt.NDArray[np.complexfloating]) + +assert_type(np.fft.fft(AR_f8), npt.NDArray[np.complex128]) +assert_type(np.fft.ifft(AR_f8, axis=1), npt.NDArray[np.complex128]) +assert_type(np.fft.rfft(AR_f8, n=None), npt.NDArray[np.complex128]) +assert_type(np.fft.irfft(AR_f8, norm="ortho"), npt.NDArray[np.float64]) +assert_type(np.fft.hfft(AR_f8, n=2), npt.NDArray[np.float64]) +assert_type(np.fft.ihfft(AR_f8), npt.NDArray[np.complex128]) + +assert_type(np.fft.fftn(AR_f8), npt.NDArray[np.complex128]) +assert_type(np.fft.ifftn(AR_f8), npt.NDArray[np.complex128]) +assert_type(np.fft.rfftn(AR_f8), npt.NDArray[np.complex128]) +assert_type(np.fft.irfftn(AR_f8), npt.NDArray[np.float64]) + +assert_type(np.fft.rfft2(AR_f8), npt.NDArray[np.complex128]) +assert_type(np.fft.ifft2(AR_f8), npt.NDArray[np.complex128]) +assert_type(np.fft.fft2(AR_f8), npt.NDArray[np.complex128]) +assert_type(np.fft.irfft2(AR_f8), npt.NDArray[np.float64]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/flatiter.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/flatiter.pyi new file mode 100644 index 0000000000000000000000000000000000000000..98d61a6d342825dc67755dae40f8407e6f96aa1c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/flatiter.pyi @@ -0,0 +1,86 @@ +from typing import Any, TypeAlias, assert_type + +import numpy as np + +_ArrayND: TypeAlias = np.ndarray[tuple[Any, ...], np.dtypes.StrDType] +_Array1D: TypeAlias = np.ndarray[tuple[int], np.dtypes.BytesDType] +_Array2D: TypeAlias = np.ndarray[tuple[int, int], np.dtypes.Int8DType] + +_a_nd: np.flatiter[_ArrayND] +_a_1d: np.flatiter[_Array1D] +_a_2d: np.flatiter[_Array2D] + +### + +# .base +assert_type(_a_nd.base, _ArrayND) +assert_type(_a_1d.base, _Array1D) +assert_type(_a_2d.base, _Array2D) + +# .coords +assert_type(_a_nd.coords, tuple[Any, ...]) +assert_type(_a_1d.coords, tuple[int]) +assert_type(_a_2d.coords, tuple[int, int]) + +# .index +assert_type(_a_nd.index, int) +assert_type(_a_1d.index, int) +assert_type(_a_2d.index, int) + +# .__len__() +assert_type(len(_a_nd), int) +assert_type(len(_a_1d), int) +assert_type(len(_a_2d), int) + +# .__iter__() +assert_type(iter(_a_nd), np.flatiter[_ArrayND]) +assert_type(iter(_a_1d), np.flatiter[_Array1D]) +assert_type(iter(_a_2d), np.flatiter[_Array2D]) + +# .__next__() +assert_type(next(_a_nd), np.str_) +assert_type(next(_a_1d), np.bytes_) +assert_type(next(_a_2d), np.int8) + +# .__getitem__(()) +assert_type(_a_nd[()], _ArrayND) +assert_type(_a_1d[()], _Array1D) +assert_type(_a_2d[()], _Array2D) +# .__getitem__(int) +assert_type(_a_nd[0], np.str_) +assert_type(_a_1d[0], np.bytes_) +assert_type(_a_2d[0], np.int8) +# .__getitem__(slice) +assert_type(_a_nd[::], np.ndarray[tuple[int], np.dtypes.StrDType]) +assert_type(_a_1d[::], np.ndarray[tuple[int], np.dtypes.BytesDType]) +assert_type(_a_2d[::], np.ndarray[tuple[int], np.dtypes.Int8DType]) +# .__getitem__(EllipsisType) +assert_type(_a_nd[...], np.ndarray[tuple[int], np.dtypes.StrDType]) +assert_type(_a_1d[...], np.ndarray[tuple[int], np.dtypes.BytesDType]) +assert_type(_a_2d[...], np.ndarray[tuple[int], np.dtypes.Int8DType]) +# .__getitem__(list[!]) +assert_type(_a_nd[[]], np.ndarray[tuple[int], np.dtypes.StrDType]) +assert_type(_a_1d[[]], np.ndarray[tuple[int], np.dtypes.BytesDType]) +assert_type(_a_2d[[]], np.ndarray[tuple[int], np.dtypes.Int8DType]) +# .__getitem__(list[int]) +assert_type(_a_nd[[0]], np.ndarray[tuple[int], np.dtypes.StrDType]) +assert_type(_a_1d[[0]], np.ndarray[tuple[int], np.dtypes.BytesDType]) +assert_type(_a_2d[[0]], np.ndarray[tuple[int], np.dtypes.Int8DType]) +# .__getitem__(list[list[int]]) +assert_type(_a_nd[[[0]]], np.ndarray[tuple[int, int], np.dtypes.StrDType]) +assert_type(_a_1d[[[0]]], np.ndarray[tuple[int, int], np.dtypes.BytesDType]) +assert_type(_a_2d[[[0]]], np.ndarray[tuple[int, int], np.dtypes.Int8DType]) +# .__getitem__(list[list[list[list[int]]]]) +assert_type(_a_nd[[[[[0]]]]], np.ndarray[tuple[Any, ...], np.dtypes.StrDType]) +assert_type(_a_1d[[[[[0]]]]], np.ndarray[tuple[Any, ...], np.dtypes.BytesDType]) +assert_type(_a_2d[[[[[0]]]]], np.ndarray[tuple[Any, ...], np.dtypes.Int8DType]) + +# __array__() +assert_type(_a_nd.__array__(), np.ndarray[tuple[int], np.dtypes.StrDType]) +assert_type(_a_1d.__array__(), np.ndarray[tuple[int], np.dtypes.BytesDType]) +assert_type(_a_2d.__array__(), np.ndarray[tuple[int], np.dtypes.Int8DType]) + +# .copy() +assert_type(_a_nd.copy(), np.ndarray[tuple[int], np.dtypes.StrDType]) +assert_type(_a_1d.copy(), np.ndarray[tuple[int], np.dtypes.BytesDType]) +assert_type(_a_2d.copy(), np.ndarray[tuple[int], np.dtypes.Int8DType]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/fromnumeric.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/fromnumeric.pyi new file mode 100644 index 0000000000000000000000000000000000000000..58ea2c5f8732c5e9deab89e9c0a757d166957469 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/fromnumeric.pyi @@ -0,0 +1,347 @@ +"""Tests for :mod:`_core.fromnumeric`.""" + +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt + +class NDArraySubclass(npt.NDArray[np.complex128]): ... + +AR_b: npt.NDArray[np.bool] +AR_f4: npt.NDArray[np.float32] +AR_c16: npt.NDArray[np.complex128] +AR_u8: npt.NDArray[np.uint64] +AR_i8: npt.NDArray[np.int64] +AR_O: npt.NDArray[np.object_] +AR_subclass: NDArraySubclass +AR_m: npt.NDArray[np.timedelta64] +AR_0d: np.ndarray[tuple[()]] +AR_1d: np.ndarray[tuple[int]] +AR_nd: np.ndarray + +b: np.bool +f4: np.float32 +i8: np.int64 +f: float + +# integer‑dtype subclass for argmin/argmax +class NDArrayIntSubclass(npt.NDArray[np.intp]): ... +AR_sub_i: NDArrayIntSubclass + +assert_type(np.take(b, 0), np.bool) +assert_type(np.take(f4, 0), np.float32) +assert_type(np.take(f, 0), Any) +assert_type(np.take(AR_b, 0), np.bool) +assert_type(np.take(AR_f4, 0), np.float32) +assert_type(np.take(AR_b, [0]), npt.NDArray[np.bool]) +assert_type(np.take(AR_f4, [0]), npt.NDArray[np.float32]) +assert_type(np.take([1], [0]), npt.NDArray[Any]) +assert_type(np.take(AR_f4, [0], out=AR_subclass), NDArraySubclass) + +assert_type(np.reshape(b, 1), np.ndarray[tuple[int], np.dtype[np.bool]]) +assert_type(np.reshape(f4, 1), np.ndarray[tuple[int], np.dtype[np.float32]]) +assert_type(np.reshape(f, 1), np.ndarray[tuple[int], np.dtype]) +assert_type(np.reshape(AR_b, 1), np.ndarray[tuple[int], np.dtype[np.bool]]) +assert_type(np.reshape(AR_f4, 1), np.ndarray[tuple[int], np.dtype[np.float32]]) + +assert_type(np.choose(1, [True, True]), Any) +assert_type(np.choose([1], [True, True]), npt.NDArray[Any]) +assert_type(np.choose([1], AR_b), npt.NDArray[np.bool]) +assert_type(np.choose([1], AR_b, out=AR_f4), npt.NDArray[np.float32]) + +assert_type(np.repeat(b, 1), np.ndarray[tuple[int], np.dtype[np.bool]]) +assert_type(np.repeat(b, 1, axis=0), npt.NDArray[np.bool]) +assert_type(np.repeat(f4, 1), np.ndarray[tuple[int], np.dtype[np.float32]]) +assert_type(np.repeat(f, 1), np.ndarray[tuple[int], np.dtype[Any]]) +assert_type(np.repeat(AR_b, 1), np.ndarray[tuple[int], np.dtype[np.bool]]) +assert_type(np.repeat(AR_f4, 1), np.ndarray[tuple[int], np.dtype[np.float32]]) +assert_type(np.repeat(AR_f4, 1, axis=0), npt.NDArray[np.float32]) + +# TODO: array_bdd tests for np.put() + +assert_type(np.swapaxes([[0, 1]], 0, 0), npt.NDArray[Any]) +assert_type(np.swapaxes(AR_b, 0, 0), npt.NDArray[np.bool]) +assert_type(np.swapaxes(AR_f4, 0, 0), npt.NDArray[np.float32]) + +assert_type(np.transpose(b), npt.NDArray[np.bool]) +assert_type(np.transpose(f4), npt.NDArray[np.float32]) +assert_type(np.transpose(f), npt.NDArray[Any]) +assert_type(np.transpose(AR_b), npt.NDArray[np.bool]) +assert_type(np.transpose(AR_f4), npt.NDArray[np.float32]) + +assert_type(np.partition(b, 0, axis=None), npt.NDArray[np.bool]) +assert_type(np.partition(f4, 0, axis=None), npt.NDArray[np.float32]) +assert_type(np.partition(f, 0, axis=None), npt.NDArray[Any]) +assert_type(np.partition(AR_b, 0), npt.NDArray[np.bool]) +assert_type(np.partition(AR_f4, 0), npt.NDArray[np.float32]) + +assert_type(np.argpartition(b, 0), npt.NDArray[np.intp]) +assert_type(np.argpartition(f4, 0), npt.NDArray[np.intp]) +assert_type(np.argpartition(f, 0), npt.NDArray[np.intp]) +assert_type(np.argpartition(AR_b, 0), npt.NDArray[np.intp]) +assert_type(np.argpartition(AR_f4, 0), npt.NDArray[np.intp]) + +assert_type(np.sort([2, 1], 0), npt.NDArray[Any]) +assert_type(np.sort(AR_b, 0), npt.NDArray[np.bool]) +assert_type(np.sort(AR_f4, 0), npt.NDArray[np.float32]) + +assert_type(np.argsort(AR_b, 0), npt.NDArray[np.intp]) +assert_type(np.argsort(AR_f4, 0), npt.NDArray[np.intp]) + +assert_type(np.argmax(AR_b), np.intp) +assert_type(np.argmax(AR_f4), np.intp) +assert_type(np.argmax(AR_b, axis=0), Any) +assert_type(np.argmax(AR_f4, axis=0), Any) +assert_type(np.argmax(AR_f4, out=AR_sub_i), NDArrayIntSubclass) + +assert_type(np.argmin(AR_b), np.intp) +assert_type(np.argmin(AR_f4), np.intp) +assert_type(np.argmin(AR_b, axis=0), Any) +assert_type(np.argmin(AR_f4, axis=0), Any) +assert_type(np.argmin(AR_f4, out=AR_sub_i), NDArrayIntSubclass) + +assert_type(np.searchsorted(AR_b[0], 0), np.intp) +assert_type(np.searchsorted(AR_f4[0], 0), np.intp) +assert_type(np.searchsorted(AR_b[0], [0]), npt.NDArray[np.intp]) +assert_type(np.searchsorted(AR_f4[0], [0]), npt.NDArray[np.intp]) + +assert_type(np.resize(b, (5, 5)), np.ndarray[tuple[int, int], np.dtype[np.bool]]) +assert_type(np.resize(f4, (5, 5)), np.ndarray[tuple[int, int], np.dtype[np.float32]]) +assert_type(np.resize(f, (5, 5)), np.ndarray[tuple[int, int], np.dtype]) +assert_type(np.resize(AR_b, (5, 5)), np.ndarray[tuple[int, int], np.dtype[np.bool]]) +assert_type(np.resize(AR_f4, (5, 5)), np.ndarray[tuple[int, int], np.dtype[np.float32]]) + +assert_type(np.squeeze(b), np.bool) +assert_type(np.squeeze(f4), np.float32) +assert_type(np.squeeze(f), npt.NDArray[Any]) +assert_type(np.squeeze(AR_b), npt.NDArray[np.bool]) +assert_type(np.squeeze(AR_f4), npt.NDArray[np.float32]) + +assert_type(np.diagonal(AR_b), npt.NDArray[np.bool]) +assert_type(np.diagonal(AR_f4), npt.NDArray[np.float32]) + +assert_type(np.trace(AR_b), Any) +assert_type(np.trace(AR_f4), Any) +assert_type(np.trace(AR_f4, out=AR_subclass), NDArraySubclass) +assert_type(np.trace(AR_f4, out=AR_subclass, dtype=None), NDArraySubclass) + +assert_type(np.ravel(b), np.ndarray[tuple[int], np.dtype[np.bool]]) +assert_type(np.ravel(f4), np.ndarray[tuple[int], np.dtype[np.float32]]) +assert_type(np.ravel(f), np.ndarray[tuple[int], np.dtype[np.float64 | Any]]) +assert_type(np.ravel(AR_b), np.ndarray[tuple[int], np.dtype[np.bool]]) +assert_type(np.ravel(AR_f4), np.ndarray[tuple[int], np.dtype[np.float32]]) + +assert_type(np.nonzero(AR_b), tuple[np.ndarray[tuple[int], np.dtype[np.intp]], ...]) +assert_type(np.nonzero(AR_f4), tuple[np.ndarray[tuple[int], np.dtype[np.intp]], ...]) +assert_type(np.nonzero(AR_1d), tuple[np.ndarray[tuple[int], np.dtype[np.intp]], ...]) +assert_type(np.nonzero(AR_nd), tuple[np.ndarray[tuple[int], np.dtype[np.intp]], ...]) + +assert_type(np.shape(b), tuple[()]) +assert_type(np.shape(f), tuple[()]) +assert_type(np.shape([1]), tuple[int]) +assert_type(np.shape([[2]]), tuple[int, int]) +assert_type(np.shape([[[3]]]), tuple[Any, ...]) +assert_type(np.shape(AR_b), tuple[Any, ...]) +assert_type(np.shape(AR_nd), tuple[Any, ...]) +# these fail on mypy, but it works as expected with pyright/pylance +# assert_type(np.shape(AR_0d), tuple[()]) +# assert_type(np.shape(AR_1d), tuple[int]) +# assert_type(np.shape(AR_2d), tuple[int, int]) + +assert_type(np.compress([True], b), npt.NDArray[np.bool]) +assert_type(np.compress([True], f4), npt.NDArray[np.float32]) +assert_type(np.compress([True], f), npt.NDArray[Any]) +assert_type(np.compress([True], AR_b), npt.NDArray[np.bool]) +assert_type(np.compress([True], AR_f4), npt.NDArray[np.float32]) + +assert_type(np.clip(b, 0, 1.0), np.bool) +assert_type(np.clip(f4, -1, 1), np.float32) +assert_type(np.clip(f, 0, 1), Any) +assert_type(np.clip(AR_b, 0, 1), npt.NDArray[np.bool]) +assert_type(np.clip(AR_f4, 0, 1), npt.NDArray[np.float32]) +assert_type(np.clip([0], 0, 1), npt.NDArray[Any]) +assert_type(np.clip(AR_b, 0, 1, out=AR_subclass), NDArraySubclass) + +assert_type(np.sum(b), np.bool) +assert_type(np.sum(f4), np.float32) +assert_type(np.sum(f), Any) +assert_type(np.sum(AR_b), np.bool) +assert_type(np.sum(AR_f4), np.float32) +assert_type(np.sum(AR_b, axis=0), Any) +assert_type(np.sum(AR_f4, axis=0), Any) +assert_type(np.sum(AR_f4, out=AR_subclass), NDArraySubclass) +assert_type(np.sum(AR_f4, dtype=np.float64), np.float64) +assert_type(np.sum(AR_f4, None, np.float64), np.float64) +assert_type(np.sum(AR_f4, dtype=np.float64, keepdims=False), np.float64) +assert_type(np.sum(AR_f4, None, np.float64, keepdims=False), np.float64) +assert_type(np.sum(AR_f4, dtype=np.float64, keepdims=True), np.float64 | npt.NDArray[np.float64]) +assert_type(np.sum(AR_f4, None, np.float64, keepdims=True), np.float64 | npt.NDArray[np.float64]) + +assert_type(np.all(b), np.bool) +assert_type(np.all(f4), np.bool) +assert_type(np.all(f), np.bool) +assert_type(np.all(AR_b), np.bool) +assert_type(np.all(AR_f4), np.bool) +assert_type(np.all(AR_b, axis=0), Any) +assert_type(np.all(AR_f4, axis=0), Any) +assert_type(np.all(AR_b, keepdims=True), Any) +assert_type(np.all(AR_f4, keepdims=True), Any) +assert_type(np.all(AR_f4, out=AR_subclass), NDArraySubclass) + +assert_type(np.any(b), np.bool) +assert_type(np.any(f4), np.bool) +assert_type(np.any(f), np.bool) +assert_type(np.any(AR_b), np.bool) +assert_type(np.any(AR_f4), np.bool) +assert_type(np.any(AR_b, axis=0), Any) +assert_type(np.any(AR_f4, axis=0), Any) +assert_type(np.any(AR_b, keepdims=True), Any) +assert_type(np.any(AR_f4, keepdims=True), Any) +assert_type(np.any(AR_f4, out=AR_subclass), NDArraySubclass) + +assert_type(np.cumsum(b), npt.NDArray[np.bool]) +assert_type(np.cumsum(f4), npt.NDArray[np.float32]) +assert_type(np.cumsum(f), npt.NDArray[Any]) +assert_type(np.cumsum(AR_b), npt.NDArray[np.bool]) +assert_type(np.cumsum(AR_f4), npt.NDArray[np.float32]) +assert_type(np.cumsum(f, dtype=float), npt.NDArray[Any]) +assert_type(np.cumsum(f, dtype=np.float64), npt.NDArray[np.float64]) +assert_type(np.cumsum(AR_f4, out=AR_subclass), NDArraySubclass) + +assert_type(np.cumulative_sum(b), npt.NDArray[np.bool]) +assert_type(np.cumulative_sum(f4), npt.NDArray[np.float32]) +assert_type(np.cumulative_sum(f), npt.NDArray[Any]) +assert_type(np.cumulative_sum(AR_b), npt.NDArray[np.bool]) +assert_type(np.cumulative_sum(AR_f4), npt.NDArray[np.float32]) +assert_type(np.cumulative_sum(f, dtype=float), npt.NDArray[Any]) +assert_type(np.cumulative_sum(f, dtype=np.float64), npt.NDArray[np.float64]) +assert_type(np.cumulative_sum(AR_f4, out=AR_subclass), NDArraySubclass) + +assert_type(np.ptp(b), np.bool) +assert_type(np.ptp(f4), np.float32) +assert_type(np.ptp(f), Any) +assert_type(np.ptp(AR_b), np.bool) +assert_type(np.ptp(AR_f4), np.float32) +assert_type(np.ptp(AR_b, axis=0), Any) +assert_type(np.ptp(AR_f4, axis=0), Any) +assert_type(np.ptp(AR_b, keepdims=True), Any) +assert_type(np.ptp(AR_f4, keepdims=True), Any) +assert_type(np.ptp(AR_f4, out=AR_subclass), NDArraySubclass) + +assert_type(np.amax(b), np.bool) +assert_type(np.amax(f4), np.float32) +assert_type(np.amax(f), Any) +assert_type(np.amax(AR_b), np.bool) +assert_type(np.amax(AR_f4), np.float32) +assert_type(np.amax(AR_b, axis=0), Any) +assert_type(np.amax(AR_f4, axis=0), Any) +assert_type(np.amax(AR_b, keepdims=True), Any) +assert_type(np.amax(AR_f4, keepdims=True), Any) +assert_type(np.amax(AR_f4, out=AR_subclass), NDArraySubclass) + +assert_type(np.amin(b), np.bool) +assert_type(np.amin(f4), np.float32) +assert_type(np.amin(f), Any) +assert_type(np.amin(AR_b), np.bool) +assert_type(np.amin(AR_f4), np.float32) +assert_type(np.amin(AR_b, axis=0), Any) +assert_type(np.amin(AR_f4, axis=0), Any) +assert_type(np.amin(AR_b, keepdims=True), Any) +assert_type(np.amin(AR_f4, keepdims=True), Any) +assert_type(np.amin(AR_f4, out=AR_subclass), NDArraySubclass) + +assert_type(np.prod(AR_b), np.int_) +assert_type(np.prod(AR_u8), np.uint64) +assert_type(np.prod(AR_i8), np.int64) +assert_type(np.prod(AR_f4), np.floating) +assert_type(np.prod(AR_c16), np.complexfloating) +assert_type(np.prod(AR_O), Any) +assert_type(np.prod(AR_f4, axis=0), Any) +assert_type(np.prod(AR_f4, keepdims=True), Any) +assert_type(np.prod(AR_f4, dtype=np.float64), np.float64) +assert_type(np.prod(AR_f4, dtype=float), Any) +assert_type(np.prod(AR_f4, out=AR_subclass), NDArraySubclass) + +assert_type(np.cumprod(AR_b), npt.NDArray[np.int_]) +assert_type(np.cumprod(AR_u8), npt.NDArray[np.uint64]) +assert_type(np.cumprod(AR_i8), npt.NDArray[np.int64]) +assert_type(np.cumprod(AR_f4), npt.NDArray[np.floating]) +assert_type(np.cumprod(AR_c16), npt.NDArray[np.complexfloating]) +assert_type(np.cumprod(AR_O), npt.NDArray[np.object_]) +assert_type(np.cumprod(AR_f4, axis=0), npt.NDArray[np.floating]) +assert_type(np.cumprod(AR_f4, dtype=np.float64), npt.NDArray[np.float64]) +assert_type(np.cumprod(AR_f4, dtype=float), npt.NDArray[Any]) +assert_type(np.cumprod(AR_f4, out=AR_subclass), NDArraySubclass) + +assert_type(np.cumulative_prod(AR_b), npt.NDArray[np.int_]) +assert_type(np.cumulative_prod(AR_u8), npt.NDArray[np.uint64]) +assert_type(np.cumulative_prod(AR_i8), npt.NDArray[np.int64]) +assert_type(np.cumulative_prod(AR_f4), npt.NDArray[np.floating]) +assert_type(np.cumulative_prod(AR_c16), npt.NDArray[np.complexfloating]) +assert_type(np.cumulative_prod(AR_O), npt.NDArray[np.object_]) +assert_type(np.cumulative_prod(AR_f4, axis=0), npt.NDArray[np.floating]) +assert_type(np.cumulative_prod(AR_f4, dtype=np.float64), npt.NDArray[np.float64]) +assert_type(np.cumulative_prod(AR_f4, dtype=float), npt.NDArray[Any]) +assert_type(np.cumulative_prod(AR_f4, out=AR_subclass), NDArraySubclass) + +assert_type(np.ndim(b), int) +assert_type(np.ndim(f4), int) +assert_type(np.ndim(f), int) +assert_type(np.ndim(AR_b), int) +assert_type(np.ndim(AR_f4), int) + +assert_type(np.size(b), int) +assert_type(np.size(f4), int) +assert_type(np.size(f), int) +assert_type(np.size(AR_b), int) +assert_type(np.size(AR_f4), int) + +assert_type(np.around(b), np.float16) +assert_type(np.around(f), Any) +assert_type(np.around(i8), np.int64) +assert_type(np.around(f4), np.float32) +assert_type(np.around(AR_b), npt.NDArray[np.float16]) +assert_type(np.around(AR_i8), npt.NDArray[np.int64]) +assert_type(np.around(AR_f4), npt.NDArray[np.float32]) +assert_type(np.around([1.5]), npt.NDArray[Any]) +assert_type(np.around(AR_f4, out=AR_subclass), NDArraySubclass) + +assert_type(np.mean(AR_b), np.floating) +assert_type(np.mean(AR_i8), np.floating) +assert_type(np.mean(AR_f4), np.floating) +assert_type(np.mean(AR_m), np.timedelta64) +assert_type(np.mean(AR_c16), np.complexfloating) +assert_type(np.mean(AR_O), Any) +assert_type(np.mean(AR_f4, axis=0), Any) +assert_type(np.mean(AR_f4, keepdims=True), Any) +assert_type(np.mean(AR_f4, dtype=float), Any) +assert_type(np.mean(AR_f4, dtype=np.float64), np.float64) +assert_type(np.mean(AR_f4, out=AR_subclass), NDArraySubclass) +assert_type(np.mean(AR_f4, dtype=np.float64), np.float64) +assert_type(np.mean(AR_f4, None, np.float64), np.float64) +assert_type(np.mean(AR_f4, dtype=np.float64, keepdims=False), np.float64) +assert_type(np.mean(AR_f4, None, np.float64, keepdims=False), np.float64) +assert_type(np.mean(AR_f4, dtype=np.float64, keepdims=True), np.float64 | npt.NDArray[np.float64]) +assert_type(np.mean(AR_f4, None, np.float64, keepdims=True), np.float64 | npt.NDArray[np.float64]) + +assert_type(np.std(AR_b), np.floating) +assert_type(np.std(AR_i8), np.floating) +assert_type(np.std(AR_f4), np.floating) +assert_type(np.std(AR_c16), np.floating) +assert_type(np.std(AR_O), Any) +assert_type(np.std(AR_f4, axis=0), Any) +assert_type(np.std(AR_f4, keepdims=True), Any) +assert_type(np.std(AR_f4, dtype=float), Any) +assert_type(np.std(AR_f4, dtype=np.float64), np.float64) +assert_type(np.std(AR_f4, out=AR_subclass), NDArraySubclass) + +assert_type(np.var(AR_b), np.floating) +assert_type(np.var(AR_i8), np.floating) +assert_type(np.var(AR_f4), np.floating) +assert_type(np.var(AR_c16), np.floating) +assert_type(np.var(AR_O), Any) +assert_type(np.var(AR_f4, axis=0), Any) +assert_type(np.var(AR_f4, keepdims=True), Any) +assert_type(np.var(AR_f4, dtype=float), Any) +assert_type(np.var(AR_f4, dtype=np.float64), np.float64) +assert_type(np.var(AR_f4, out=AR_subclass), NDArraySubclass) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/getlimits.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/getlimits.pyi new file mode 100644 index 0000000000000000000000000000000000000000..cc964d75305500669476231af2b9c974107a673c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/getlimits.pyi @@ -0,0 +1,53 @@ +from typing import assert_type + +import numpy as np + +f: float +f8: np.float64 +c8: np.complex64 +c16: np.complex128 + +i: int +i8: np.int64 +u4: np.uint32 + +finfo_f8: np.finfo[np.float64] +iinfo_i8: np.iinfo[np.int64] + +assert_type(np.finfo(f), np.finfo[np.float64]) +assert_type(np.finfo(f8), np.finfo[np.float64]) +assert_type(np.finfo(c8), np.finfo[np.float32]) +assert_type(np.finfo(c16), np.finfo[np.float64]) +assert_type(np.finfo("f2"), np.finfo[np.float16]) + +assert_type(finfo_f8.dtype, np.dtype[np.float64]) +assert_type(finfo_f8.bits, int) +assert_type(finfo_f8.eps, np.float64) +assert_type(finfo_f8.epsneg, np.float64) +assert_type(finfo_f8.iexp, int) +assert_type(finfo_f8.machep, int) +assert_type(finfo_f8.max, np.float64) +assert_type(finfo_f8.maxexp, int) +assert_type(finfo_f8.min, np.float64) +assert_type(finfo_f8.minexp, int) +assert_type(finfo_f8.negep, int) +assert_type(finfo_f8.nexp, int) +assert_type(finfo_f8.nmant, int) +assert_type(finfo_f8.precision, int) +assert_type(finfo_f8.resolution, np.float64) +assert_type(finfo_f8.tiny, np.float64) +assert_type(finfo_f8.smallest_normal, np.float64) +assert_type(finfo_f8.smallest_subnormal, np.float64) + +assert_type(np.iinfo(i), np.iinfo[np.int_]) +assert_type(np.iinfo(i8), np.iinfo[np.int64]) +assert_type(np.iinfo(u4), np.iinfo[np.uint32]) +assert_type(np.iinfo("i2"), np.iinfo[np.int16]) +assert_type(np.iinfo("u2"), np.iinfo[np.uint16]) + +assert_type(iinfo_i8.dtype, np.dtype[np.int64]) +assert_type(iinfo_i8.kind, str) +assert_type(iinfo_i8.bits, int) +assert_type(iinfo_i8.key, str) +assert_type(iinfo_i8.min, int) +assert_type(iinfo_i8.max, int) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/histograms.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/histograms.pyi new file mode 100644 index 0000000000000000000000000000000000000000..c1c63d59cb8805237e1d4907f2e90ef6f6ee4cfd --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/histograms.pyi @@ -0,0 +1,25 @@ +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt + +AR_i8: npt.NDArray[np.int64] +AR_f8: npt.NDArray[np.float64] + +assert_type(np.histogram_bin_edges(AR_i8, bins="auto"), npt.NDArray[Any]) +assert_type(np.histogram_bin_edges(AR_i8, bins="rice", range=(0, 3)), npt.NDArray[Any]) +assert_type(np.histogram_bin_edges(AR_i8, bins="scott", weights=AR_f8), npt.NDArray[Any]) + +assert_type(np.histogram(AR_i8, bins="auto"), tuple[npt.NDArray[Any], npt.NDArray[Any]]) +assert_type(np.histogram(AR_i8, bins="rice", range=(0, 3)), tuple[npt.NDArray[Any], npt.NDArray[Any]]) +assert_type(np.histogram(AR_i8, bins="scott", weights=AR_f8), tuple[npt.NDArray[Any], npt.NDArray[Any]]) +assert_type(np.histogram(AR_f8, bins=1, density=True), tuple[npt.NDArray[Any], npt.NDArray[Any]]) + +assert_type(np.histogramdd(AR_i8, bins=[1]), + tuple[npt.NDArray[Any], tuple[npt.NDArray[Any], ...]]) +assert_type(np.histogramdd(AR_i8, range=[(0, 3)]), + tuple[npt.NDArray[Any], tuple[npt.NDArray[Any], ...]]) +assert_type(np.histogramdd(AR_i8, weights=AR_f8), + tuple[npt.NDArray[Any], tuple[npt.NDArray[Any], ...]]) +assert_type(np.histogramdd(AR_f8, density=True), + tuple[npt.NDArray[Any], tuple[npt.NDArray[Any], ...]]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/index_tricks.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/index_tricks.pyi new file mode 100644 index 0000000000000000000000000000000000000000..f6067c3bed6bfd0adecab400a1028f40af479b24 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/index_tricks.pyi @@ -0,0 +1,70 @@ +from types import EllipsisType +from typing import Any, Literal, assert_type + +import numpy as np +import numpy.typing as npt + +AR_LIKE_b: list[bool] +AR_LIKE_i: list[int] +AR_LIKE_f: list[float] +AR_LIKE_U: list[str] +AR_LIKE_O: list[object] + +AR_i8: npt.NDArray[np.int64] +AR_O: npt.NDArray[np.object_] + +assert_type(np.ndenumerate(AR_i8), np.ndenumerate[np.int64]) +assert_type(np.ndenumerate(AR_LIKE_f), np.ndenumerate[np.float64]) +assert_type(np.ndenumerate(AR_LIKE_U), np.ndenumerate[np.str_]) +assert_type(np.ndenumerate(AR_LIKE_O), np.ndenumerate[Any]) + +assert_type(next(np.ndenumerate(AR_i8)), tuple[tuple[Any, ...], np.int64]) +assert_type(next(np.ndenumerate(AR_LIKE_f)), tuple[tuple[Any, ...], np.float64]) +assert_type(next(np.ndenumerate(AR_LIKE_U)), tuple[tuple[Any, ...], np.str_]) +assert_type(next(np.ndenumerate(AR_LIKE_O)), tuple[tuple[Any, ...], Any]) + +assert_type(iter(np.ndenumerate(AR_i8)), np.ndenumerate[np.int64]) +assert_type(iter(np.ndenumerate(AR_LIKE_f)), np.ndenumerate[np.float64]) +assert_type(iter(np.ndenumerate(AR_LIKE_U)), np.ndenumerate[np.str_]) +assert_type(iter(np.ndenumerate(AR_LIKE_O)), np.ndenumerate[Any]) + +assert_type(np.ndindex(1, 2, 3), np.ndindex) +assert_type(np.ndindex((1, 2, 3)), np.ndindex) +assert_type(iter(np.ndindex(1, 2, 3)), np.ndindex) +assert_type(next(np.ndindex(1, 2, 3)), tuple[Any, ...]) + +assert_type(np.unravel_index([22, 41, 37], (7, 6)), tuple[npt.NDArray[np.intp], ...]) +assert_type(np.unravel_index([31, 41, 13], (7, 6), order="F"), tuple[npt.NDArray[np.intp], ...]) +assert_type(np.unravel_index(1621, (6, 7, 8, 9)), tuple[np.intp, ...]) + +assert_type(np.ravel_multi_index([[1]], (7, 6)), npt.NDArray[np.intp]) +assert_type(np.ravel_multi_index(AR_LIKE_i, (7, 6)), np.intp) +assert_type(np.ravel_multi_index(AR_LIKE_i, (7, 6), order="F"), np.intp) +assert_type(np.ravel_multi_index(AR_LIKE_i, (4, 6), mode="clip"), np.intp) +assert_type(np.ravel_multi_index(AR_LIKE_i, (4, 4), mode=("clip", "wrap")), np.intp) +assert_type(np.ravel_multi_index((3, 1, 4, 1), (6, 7, 8, 9)), np.intp) + +assert_type(np.mgrid[1:1:2], npt.NDArray[Any]) +assert_type(np.mgrid[1:1:2, None:10], npt.NDArray[Any]) + +assert_type(np.ogrid[1:1:2], tuple[npt.NDArray[Any], ...]) +assert_type(np.ogrid[1:1:2, None:10], tuple[npt.NDArray[Any], ...]) + +assert_type(np.index_exp[0:1], tuple[slice[int, int, None]]) +assert_type(np.index_exp[0:1, None:3], tuple[slice[int, int, None], slice[None, int, None]]) +assert_type(np.index_exp[0, 0:1, ..., [0, 1, 3]], tuple[Literal[0], slice[int, int, None], EllipsisType, list[int]]) + +assert_type(np.s_[0:1], slice[int, int, None]) +assert_type(np.s_[0:1, None:3], tuple[slice[int, int, None], slice[None, int, None]]) +assert_type(np.s_[0, 0:1, ..., [0, 1, 3]], tuple[Literal[0], slice[int, int, None], EllipsisType, list[int]]) + +assert_type(np.ix_(AR_LIKE_b), tuple[npt.NDArray[np.bool], ...]) +assert_type(np.ix_(AR_LIKE_i, AR_LIKE_f), tuple[npt.NDArray[np.float64], ...]) +assert_type(np.ix_(AR_i8), tuple[npt.NDArray[np.int64], ...]) + +assert_type(np.fill_diagonal(AR_i8, 5), None) + +assert_type(np.diag_indices(4), tuple[npt.NDArray[np.int_], ...]) +assert_type(np.diag_indices(2, 3), tuple[npt.NDArray[np.int_], ...]) + +assert_type(np.diag_indices_from(AR_i8), tuple[npt.NDArray[np.int_], ...]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/lib_function_base.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/lib_function_base.pyi new file mode 100644 index 0000000000000000000000000000000000000000..345635d06327608f636a0821c57a321a20d53fd4 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/lib_function_base.pyi @@ -0,0 +1,409 @@ +from collections.abc import Callable +from fractions import Fraction +from typing import Any, LiteralString, assert_type, type_check_only + +import numpy as np +import numpy.typing as npt + +f8: np.float64 +AR_LIKE_b: list[bool] +AR_LIKE_i8: list[int] +AR_LIKE_f8: list[float] +AR_LIKE_c16: list[complex] +AR_LIKE_O: list[Fraction] + +AR_u1: npt.NDArray[np.uint8] +AR_i8: npt.NDArray[np.int64] +AR_f2: npt.NDArray[np.float16] +AR_f4: npt.NDArray[np.float32] +AR_f8: npt.NDArray[np.float64] +AR_f10: npt.NDArray[np.longdouble] +AR_c8: npt.NDArray[np.complex64] +AR_c16: npt.NDArray[np.complex128] +AR_c20: npt.NDArray[np.clongdouble] +AR_m: npt.NDArray[np.timedelta64] +AR_M: npt.NDArray[np.datetime64] +AR_O: npt.NDArray[np.object_] +AR_b: npt.NDArray[np.bool] +AR_U: npt.NDArray[np.str_] +CHAR_AR_U: np.char.chararray[tuple[Any, ...], np.dtype[np.str_]] + +AR_f8_1d: np.ndarray[tuple[int], np.dtype[np.float64]] +AR_f8_2d: np.ndarray[tuple[int, int], np.dtype[np.float64]] +AR_f8_3d: np.ndarray[tuple[int, int, int], np.dtype[np.float64]] +AR_c16_1d: np.ndarray[tuple[int], np.dtype[np.complex128]] + +AR_b_list: list[npt.NDArray[np.bool]] + +@type_check_only +def func(a: np.ndarray, posarg: bool = ..., /, arg: int = ..., *, kwarg: str = ...) -> np.ndarray: ... +@type_check_only +def func_f8(a: npt.NDArray[np.float64]) -> npt.NDArray[np.float64]: ... + +### + +# vectorize +vectorized_func: np.vectorize +assert_type(vectorized_func.pyfunc, Callable[..., Any]) +assert_type(vectorized_func.cache, bool) +assert_type(vectorized_func.signature, LiteralString | None) +assert_type(vectorized_func.otypes, LiteralString | None) +assert_type(vectorized_func.excluded, set[int | str]) +assert_type(vectorized_func.__doc__, str | None) +assert_type(vectorized_func([1]), Any) +assert_type(np.vectorize(int), np.vectorize) +assert_type( + np.vectorize(int, otypes="i", doc="doc", excluded=(), cache=True, signature=None), + np.vectorize, +) + +# rot90 +assert_type(np.rot90(AR_f8_1d), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.rot90(AR_f8, k=2), npt.NDArray[np.float64]) +assert_type(np.rot90(AR_LIKE_f8, axes=(0, 1)), np.ndarray) + +# flip +assert_type(np.flip(AR_f8_1d), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.flip(AR_f8, axis=(0, 1)), npt.NDArray[np.float64]) +assert_type(np.flip(AR_LIKE_f8, axis=0), np.ndarray) + +# iterable +assert_type(np.iterable(1), bool) +assert_type(np.iterable([1]), bool) + +# average +assert_type(np.average(AR_f8_2d), np.float64) +assert_type(np.average(AR_f8_2d, axis=1), npt.NDArray[np.float64]) +assert_type(np.average(AR_f8_2d, keepdims=True), np.ndarray[tuple[int, int], np.dtype[np.float64]]) +assert_type(np.average(AR_f8), np.float64) +assert_type(np.average(AR_f8, axis=1), npt.NDArray[np.float64]) +assert_type(np.average(AR_f8, keepdims=True), npt.NDArray[np.float64]) +assert_type(np.average(AR_f8, returned=True), tuple[np.float64, np.float64]) +assert_type(np.average(AR_f8, axis=1, returned=True), tuple[npt.NDArray[np.float64], npt.NDArray[np.float64]]) +assert_type(np.average(AR_f8, keepdims=True, returned=True), tuple[npt.NDArray[np.float64], npt.NDArray[np.float64]]) +assert_type(np.average(AR_LIKE_f8), np.float64) +assert_type(np.average(AR_LIKE_f8, weights=AR_f8), np.float64) +assert_type(np.average(AR_LIKE_f8, axis=1), npt.NDArray[np.float64]) +assert_type(np.average(AR_LIKE_f8, keepdims=True), npt.NDArray[np.float64]) +assert_type(np.average(AR_LIKE_f8, returned=True), tuple[np.float64, np.float64]) +assert_type(np.average(AR_LIKE_f8, axis=1, returned=True), tuple[npt.NDArray[np.float64], npt.NDArray[np.float64]]) +assert_type(np.average(AR_LIKE_f8, keepdims=True, returned=True), tuple[npt.NDArray[np.float64], npt.NDArray[np.float64]]) +assert_type(np.average(AR_O), Any) +assert_type(np.average(AR_O, axis=1), np.ndarray) +assert_type(np.average(AR_O, keepdims=True), np.ndarray) +assert_type(np.average(AR_O, returned=True), tuple[Any, Any]) +assert_type(np.average(AR_O, axis=1, returned=True), tuple[np.ndarray, np.ndarray]) +assert_type(np.average(AR_O, keepdims=True, returned=True), tuple[np.ndarray, np.ndarray]) + +# asarray_chkfinite +assert_type(np.asarray_chkfinite(AR_f8_1d), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.asarray_chkfinite(AR_f8), npt.NDArray[np.float64]) +assert_type(np.asarray_chkfinite(AR_LIKE_f8), np.ndarray) +assert_type(np.asarray_chkfinite(AR_f8, dtype=np.float64), npt.NDArray[np.float64]) +assert_type(np.asarray_chkfinite(AR_f8, dtype=float), np.ndarray) + +# piecewise +assert_type(np.piecewise(AR_f8_1d, AR_b, [func]), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.piecewise(AR_f8, AR_b, [func]), npt.NDArray[np.float64]) +assert_type(np.piecewise(AR_f8, AR_b, [func_f8]), npt.NDArray[np.float64]) +assert_type(np.piecewise(AR_f8, AR_b_list, [func]), npt.NDArray[np.float64]) +assert_type(np.piecewise(AR_f8, AR_b_list, [func_f8]), npt.NDArray[np.float64]) +assert_type(np.piecewise(AR_f8, AR_b_list, [func], True, -1, kwarg=""), npt.NDArray[np.float64]) +assert_type(np.piecewise(AR_f8, AR_b_list, [func], True, arg=-1, kwarg=""), npt.NDArray[np.float64]) +assert_type(np.piecewise(AR_LIKE_f8, AR_b_list, [func]), np.ndarray) +assert_type(np.piecewise(AR_LIKE_f8, AR_b_list, [func_f8]), npt.NDArray[np.float64]) + +# extract +assert_type(np.extract(AR_i8, AR_f8), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.extract(AR_i8, AR_LIKE_b), np.ndarray[tuple[int], np.dtype[np.bool]]) +assert_type(np.extract(AR_i8, AR_LIKE_i8), np.ndarray[tuple[int], np.dtype[np.int_]]) +assert_type(np.extract(AR_i8, AR_LIKE_f8), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.extract(AR_i8, AR_LIKE_c16), np.ndarray[tuple[int], np.dtype[np.complex128]]) + +# select +assert_type(np.select([AR_b], [AR_f8_1d]), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.select([AR_b], [AR_f8]), npt.NDArray[np.float64]) + +# places +assert_type(np.place(AR_f8, mask=AR_i8, vals=5.0), None) + +# copy +assert_type(np.copy(AR_LIKE_f8), np.ndarray) +assert_type(np.copy(AR_U), npt.NDArray[np.str_]) +assert_type(np.copy(CHAR_AR_U, "K", subok=True), np.char.chararray[tuple[Any, ...], np.dtype[np.str_]]) +assert_type(np.copy(CHAR_AR_U, subok=True), np.char.chararray[tuple[Any, ...], np.dtype[np.str_]]) +# pyright correctly infers `NDArray[str_]` here +assert_type(np.copy(CHAR_AR_U), np.ndarray[Any, Any]) # pyright: ignore[reportAssertTypeFailure] + +# gradient +assert_type(np.gradient(AR_f8_1d, 1), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type( + np.gradient(AR_f8_2d, [1, 2], [2, 3.5, 4]), + tuple[ + np.ndarray[tuple[int, int], np.dtype[np.float64]], + np.ndarray[tuple[int, int], np.dtype[np.float64]], + ], +) +assert_type( + np.gradient(AR_f8_3d), + tuple[ + np.ndarray[tuple[int, int, int], np.dtype[np.float64]], + np.ndarray[tuple[int, int, int], np.dtype[np.float64]], + np.ndarray[tuple[int, int, int], np.dtype[np.float64]], + ], +) +assert_type(np.gradient(AR_f8), np.ndarray[tuple[int], np.dtype[np.float64]] | Any) +assert_type(np.gradient(AR_LIKE_f8, edge_order=2), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.gradient(AR_LIKE_c16, axis=0), np.ndarray[tuple[int], np.dtype[np.complex128]]) + +# diff +assert_type(np.diff("git", n=0), str) +assert_type(np.diff(AR_f8), npt.NDArray[np.float64]) +assert_type(np.diff(AR_f8_1d, axis=0), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.diff(AR_f8_2d, axis=0), np.ndarray[tuple[int, int], np.dtype[np.float64]]) +assert_type(np.diff(AR_LIKE_f8, prepend=1.5), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.diff(AR_c16), npt.NDArray[np.complex128]) +assert_type(np.diff(AR_c16_1d), np.ndarray[tuple[int], np.dtype[np.complex128]]) +assert_type(np.diff(AR_LIKE_c16), np.ndarray[tuple[int], np.dtype[np.complex128]]) + +# interp +assert_type(np.interp(1, [1], AR_f8), np.float64) +assert_type(np.interp(1, [1], [1]), np.float64) +assert_type(np.interp(1, [1], AR_c16), np.complex128) +assert_type(np.interp(1, [1], [1j]), np.complex128) +assert_type(np.interp([1], [1], AR_f8), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.interp([1], [1], [1]), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.interp([1], [1], AR_c16), np.ndarray[tuple[int], np.dtype[np.complex128]]) +assert_type(np.interp([1], [1], [1j]), np.ndarray[tuple[int], np.dtype[np.complex128]]) + +# angle +assert_type(np.angle(1), np.float64) +assert_type(np.angle(1, deg=True), np.float64) +assert_type(np.angle(1j), np.float64) +assert_type(np.angle(f8), np.float64) +assert_type(np.angle(AR_b), npt.NDArray[np.float64]) +assert_type(np.angle(AR_u1), npt.NDArray[np.float64]) +assert_type(np.angle(AR_i8), npt.NDArray[np.float64]) +assert_type(np.angle(AR_f2), npt.NDArray[np.float16]) +assert_type(np.angle(AR_f4), npt.NDArray[np.float32]) +assert_type(np.angle(AR_c8), npt.NDArray[np.float32]) +assert_type(np.angle(AR_f8), npt.NDArray[np.float64]) +assert_type(np.angle(AR_c16), npt.NDArray[np.float64]) +assert_type(np.angle(AR_f10), npt.NDArray[np.longdouble]) +assert_type(np.angle(AR_c20), npt.NDArray[np.longdouble]) +assert_type(np.angle(AR_f8_1d), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.angle(AR_c16_1d), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.angle(AR_LIKE_b), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.angle(AR_LIKE_i8), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.angle(AR_LIKE_f8), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.angle(AR_LIKE_c16), np.ndarray[tuple[int], np.dtype[np.float64]]) + +# unwrap +assert_type(np.unwrap(AR_f2), npt.NDArray[np.float16]) +assert_type(np.unwrap(AR_f8), npt.NDArray[np.float64]) +assert_type(np.unwrap(AR_f10), npt.NDArray[np.longdouble]) +assert_type(np.unwrap(AR_O), npt.NDArray[np.object_]) +assert_type(np.unwrap(AR_f8_1d), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.unwrap(AR_f8_2d), np.ndarray[tuple[int, int], np.dtype[np.float64]]) +assert_type(np.unwrap(AR_f8_3d), np.ndarray[tuple[int, int, int], np.dtype[np.float64]]) +assert_type(np.unwrap(AR_LIKE_b), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.unwrap(AR_LIKE_i8), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.unwrap(AR_LIKE_f8), np.ndarray[tuple[int], np.dtype[np.float64]]) + +# sort_complex +assert_type(np.sort_complex(AR_u1), npt.NDArray[np.complex64]) +assert_type(np.sort_complex(AR_f8), npt.NDArray[np.complex128]) +assert_type(np.sort_complex(AR_f10), npt.NDArray[np.clongdouble]) +assert_type(np.sort_complex(AR_f8_1d), np.ndarray[tuple[int], np.dtype[np.complex128]]) +assert_type(np.sort_complex(AR_c16_1d), np.ndarray[tuple[int], np.dtype[np.complex128]]) + +# trim_zeros +assert_type(np.trim_zeros(AR_f8), npt.NDArray[np.float64]) +assert_type(np.trim_zeros(AR_LIKE_f8), list[float]) + +# cov +assert_type(np.cov(AR_f8_1d), np.ndarray[tuple[()], np.dtype[np.float64]]) +assert_type(np.cov(AR_f8_2d), npt.NDArray[np.float64]) +assert_type(np.cov(AR_f8), npt.NDArray[np.float64]) +assert_type(np.cov(AR_f8, AR_f8), np.ndarray[tuple[int, int], np.dtype[np.float64]]) +assert_type(np.cov(AR_c16, AR_c16), np.ndarray[tuple[int, int], np.dtype[np.complex128]]) +assert_type(np.cov(AR_LIKE_f8), np.ndarray[tuple[()], np.dtype[np.float64]]) +assert_type(np.cov(AR_LIKE_f8, AR_LIKE_f8), np.ndarray[tuple[int, int], np.dtype[np.float64]]) +assert_type(np.cov(AR_LIKE_f8, dtype=np.float16), np.ndarray[tuple[()], np.dtype[np.float16]]) +assert_type(np.cov(AR_LIKE_f8, AR_LIKE_f8, dtype=np.float32), np.ndarray[tuple[int, int], np.dtype[np.float32]]) +assert_type(np.cov(AR_f8, AR_f8, dtype=float), np.ndarray[tuple[int, int]]) +assert_type(np.cov(AR_LIKE_f8, dtype=float), np.ndarray[tuple[()]]) +assert_type(np.cov(AR_LIKE_f8, AR_LIKE_f8, dtype=float), np.ndarray[tuple[int, int]]) + +# corrcoef +assert_type(np.corrcoef(AR_f8_1d), np.float64) +assert_type(np.corrcoef(AR_f8_2d), np.ndarray[tuple[int, int], np.dtype[np.float64]] | np.float64) +assert_type(np.corrcoef(AR_f8), np.ndarray[tuple[int, int], np.dtype[np.float64]] | np.float64) +assert_type(np.corrcoef(AR_f8, AR_f8), np.ndarray[tuple[int, int], np.dtype[np.float64]]) +assert_type(np.corrcoef(AR_c16, AR_c16), np.ndarray[tuple[int, int], np.dtype[np.complex128]]) +assert_type(np.corrcoef(AR_LIKE_f8), np.float64) +assert_type(np.corrcoef(AR_LIKE_f8, AR_LIKE_f8), np.ndarray[tuple[int, int], np.dtype[np.float64]]) +assert_type(np.corrcoef(AR_LIKE_f8, dtype=np.float16), np.float16) +assert_type(np.corrcoef(AR_LIKE_f8, AR_LIKE_f8, dtype=np.float32), np.ndarray[tuple[int, int], np.dtype[np.float32]]) +assert_type(np.corrcoef(AR_f8, AR_f8, dtype=float), np.ndarray[tuple[int, int]]) +assert_type(np.corrcoef(AR_LIKE_f8, dtype=float), Any) +assert_type(np.corrcoef(AR_LIKE_f8, AR_LIKE_f8, dtype=float), np.ndarray[tuple[int, int]]) + +# window functions +assert_type(np.blackman(5), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.bartlett(6), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.hanning(4.5), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.hamming(0), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.kaiser(4, 5.9), np.ndarray[tuple[int], np.dtype[np.float64]]) + +# i0 (bessel function) +assert_type(np.i0(AR_i8), npt.NDArray[np.float64]) + +# sinc (cardinal sine function) +assert_type(np.sinc(1.0), np.float64) +assert_type(np.sinc(1j), np.complex128 | Any) +assert_type(np.sinc(AR_f8), npt.NDArray[np.float64]) +assert_type(np.sinc(AR_c16), npt.NDArray[np.complex128]) +assert_type(np.sinc(AR_LIKE_f8), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.sinc(AR_LIKE_c16), np.ndarray[tuple[int], np.dtype[np.complex128]]) + +# median +assert_type(np.median(AR_f8, keepdims=False), np.float64) +assert_type(np.median(AR_c16, overwrite_input=True), np.complex128) +assert_type(np.median(AR_m), np.timedelta64) +assert_type(np.median(AR_O), Any) +assert_type(np.median(AR_f8, keepdims=True), npt.NDArray[np.float64]) +assert_type(np.median(AR_f8, axis=0), npt.NDArray[np.float64]) +assert_type(np.median(AR_c16, keepdims=True), npt.NDArray[np.complex128]) +assert_type(np.median(AR_c16, axis=0), npt.NDArray[np.complex128]) +assert_type(np.median(AR_LIKE_f8, keepdims=True), npt.NDArray[np.float64]) +assert_type(np.median(AR_LIKE_c16, keepdims=True), npt.NDArray[np.complex128]) +assert_type(np.median(AR_LIKE_f8, out=AR_c16), npt.NDArray[np.complex128]) + +# percentile +assert_type(np.percentile(AR_f8, 50), np.float64) +assert_type(np.percentile(AR_f8, 50, axis=1), npt.NDArray[np.float64]) +assert_type(np.percentile(AR_f8, 50, axis=(1, 0)), npt.NDArray[np.float64]) +assert_type(np.percentile(AR_f8, 50, keepdims=True), npt.NDArray[np.float64]) +assert_type(np.percentile(AR_f8, 50, axis=0, keepdims=True), npt.NDArray[np.float64]) +assert_type(np.percentile(AR_c16, 50), np.complex128) +assert_type(np.percentile(AR_m, 50), np.timedelta64) +assert_type(np.percentile(AR_M, 50, overwrite_input=True), np.datetime64) +assert_type(np.percentile(AR_O, 50), Any) +assert_type(np.percentile(AR_f8, [50]), npt.NDArray[np.float64]) +assert_type(np.percentile(AR_f8, [50], axis=1), npt.NDArray[np.float64]) +assert_type(np.percentile(AR_f8, [50], keepdims=True), npt.NDArray[np.float64]) +assert_type(np.percentile(AR_c16, [50]), npt.NDArray[np.complex128]) +assert_type(np.percentile(AR_m, [50]), npt.NDArray[np.timedelta64]) +assert_type(np.percentile(AR_M, [50], method="nearest"), npt.NDArray[np.datetime64]) +assert_type(np.percentile(AR_O, [50]), npt.NDArray[np.object_]) +assert_type(np.percentile(AR_f8, [50], keepdims=True), npt.NDArray[np.float64]) +assert_type(np.percentile(AR_f8, [50], out=AR_c16), npt.NDArray[np.complex128]) + +# quantile +assert_type(np.quantile(AR_f8, 0.50), np.float64) +assert_type(np.quantile(AR_f8, 0.50, axis=1), npt.NDArray[np.float64]) +assert_type(np.quantile(AR_f8, 0.50, axis=(1, 0)), npt.NDArray[np.float64]) +assert_type(np.quantile(AR_f8, 0.50, keepdims=True), npt.NDArray[np.float64]) +assert_type(np.quantile(AR_f8, 0.50, axis=0, keepdims=True), npt.NDArray[np.float64]) +assert_type(np.quantile(AR_c16, 0.50), np.complex128) +assert_type(np.quantile(AR_m, 0.50), np.timedelta64) +assert_type(np.quantile(AR_M, 0.50, overwrite_input=True), np.datetime64) +assert_type(np.quantile(AR_O, 0.50), Any) +assert_type(np.quantile(AR_f8, [0.50]), npt.NDArray[np.float64]) +assert_type(np.quantile(AR_f8, [0.50], axis=1), npt.NDArray[np.float64]) +assert_type(np.quantile(AR_f8, [0.50], keepdims=True), npt.NDArray[np.float64]) +assert_type(np.quantile(AR_c16, [0.50]), npt.NDArray[np.complex128]) +assert_type(np.quantile(AR_m, [0.50]), npt.NDArray[np.timedelta64]) +assert_type(np.quantile(AR_M, [0.50], method="nearest"), npt.NDArray[np.datetime64]) +assert_type(np.quantile(AR_O, [0.50]), npt.NDArray[np.object_]) +assert_type(np.quantile(AR_f8, [0.50], keepdims=True), npt.NDArray[np.float64]) +assert_type(np.quantile(AR_f8, [0.50], out=AR_c16), npt.NDArray[np.complex128]) + +# trapezoid +assert_type(np.trapezoid(AR_LIKE_f8), np.float64) +assert_type(np.trapezoid(AR_LIKE_f8, AR_LIKE_f8), np.float64) +assert_type(np.trapezoid(AR_LIKE_c16), np.complex128) +assert_type(np.trapezoid(AR_LIKE_c16, AR_LIKE_f8), np.complex128) +assert_type(np.trapezoid(AR_LIKE_f8, AR_LIKE_c16), np.complex128) +assert_type(np.trapezoid(AR_LIKE_O), float) +assert_type(np.trapezoid(AR_LIKE_O, AR_LIKE_f8), float) +assert_type(np.trapezoid(AR_f8), np.float64 | npt.NDArray[np.float64]) +assert_type(np.trapezoid(AR_f8, AR_f8), np.float64 | npt.NDArray[np.float64]) +assert_type(np.trapezoid(AR_c16), np.complex128 | npt.NDArray[np.complex128]) +assert_type(np.trapezoid(AR_c16, AR_c16), np.complex128 | npt.NDArray[np.complex128]) +assert_type(np.trapezoid(AR_m), np.timedelta64 | npt.NDArray[np.timedelta64]) +assert_type(np.trapezoid(AR_O), npt.NDArray[np.object_] | Any) +assert_type(np.trapezoid(AR_O, AR_LIKE_f8), npt.NDArray[np.object_] | Any) + +# meshgrid +assert_type(np.meshgrid(), tuple[()]) +assert_type( + np.meshgrid(AR_f8), + tuple[ + np.ndarray[tuple[int], np.dtype[np.float64]], + ], +) +assert_type( + np.meshgrid(AR_c16, indexing="ij"), + tuple[ + np.ndarray[tuple[int], np.dtype[np.complex128]], + ], +) +assert_type( + np.meshgrid(AR_i8, AR_f8, copy=False), + tuple[ + np.ndarray[tuple[int, int], np.dtype[np.int64]], + np.ndarray[tuple[int, int], np.dtype[np.float64]], + ], +) +assert_type( + np.meshgrid(AR_LIKE_f8, AR_f8), + tuple[ + np.ndarray[tuple[int, int]], + np.ndarray[tuple[int, int], np.dtype[np.float64]], + ], +) +assert_type( + np.meshgrid(AR_f8, AR_LIKE_f8), + tuple[ + np.ndarray[tuple[int, int], np.dtype[np.float64]], + np.ndarray[tuple[int, int]], + ], +) +assert_type( + np.meshgrid(AR_LIKE_f8, AR_LIKE_f8), + tuple[ + np.ndarray[tuple[int, int]], + np.ndarray[tuple[int, int]], + ], +) +assert_type( + np.meshgrid(AR_f8, AR_i8, AR_c16), + tuple[ + np.ndarray[tuple[int, int, int], np.dtype[np.float64]], + np.ndarray[tuple[int, int, int], np.dtype[np.int64]], + np.ndarray[tuple[int, int, int], np.dtype[np.complex128]], + ], +) +assert_type(np.meshgrid(AR_f8, AR_f8, AR_f8, AR_f8), tuple[npt.NDArray[np.float64], ...]) +assert_type(np.meshgrid(AR_f8, AR_f8, AR_f8, AR_LIKE_f8), tuple[np.ndarray, ...]) +assert_type(np.meshgrid(*AR_LIKE_f8), tuple[np.ndarray, ...]) + +# delete +assert_type(np.delete(AR_f8, np.s_[:5]), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.delete(AR_LIKE_f8, [0, 4, 9], axis=0), np.ndarray) + +# insert +assert_type(np.insert(AR_f8, np.s_[:5], 5), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.insert(AR_LIKE_f8, [0, 4, 9], [0.5, 9.2, 7], axis=0), np.ndarray) + +# append +assert_type(np.append(f8, f8), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.append(AR_f8, AR_f8), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.append(AR_LIKE_f8, AR_LIKE_c16, axis=0), np.ndarray) +assert_type(np.append(AR_f8, AR_LIKE_f8, axis=0), np.ndarray) + +# digitize +assert_type(np.digitize(4.5, [1]), np.intp) +assert_type(np.digitize(AR_f8, [1, 2, 3]), npt.NDArray[np.intp]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/lib_polynomial.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/lib_polynomial.pyi new file mode 100644 index 0000000000000000000000000000000000000000..b7cbadefc610c7a3ebf7a6aeecac1ee7647e973b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/lib_polynomial.pyi @@ -0,0 +1,147 @@ +from collections.abc import Iterator +from typing import Any, NoReturn, assert_type + +import numpy as np +import numpy.typing as npt + +AR_b: npt.NDArray[np.bool] +AR_u4: npt.NDArray[np.uint32] +AR_i8: npt.NDArray[np.int64] +AR_f8: npt.NDArray[np.float64] +AR_c16: npt.NDArray[np.complex128] +AR_O: npt.NDArray[np.object_] + +poly_obj: np.poly1d + +assert_type(poly_obj.variable, str) +assert_type(poly_obj.order, int) +assert_type(poly_obj.o, int) +assert_type(poly_obj.roots, npt.NDArray[Any]) +assert_type(poly_obj.r, npt.NDArray[Any]) +assert_type(poly_obj.coeffs, npt.NDArray[Any]) +assert_type(poly_obj.c, npt.NDArray[Any]) +assert_type(poly_obj.coef, npt.NDArray[Any]) +assert_type(poly_obj.coefficients, npt.NDArray[Any]) +assert_type(poly_obj.__hash__, None) + +assert_type(poly_obj(1), Any) +assert_type(poly_obj([1]), npt.NDArray[Any]) +assert_type(poly_obj(poly_obj), np.poly1d) + +assert_type(len(poly_obj), int) +assert_type(-poly_obj, np.poly1d) +assert_type(+poly_obj, np.poly1d) + +assert_type(poly_obj * 5, np.poly1d) +assert_type(5 * poly_obj, np.poly1d) +assert_type(poly_obj + 5, np.poly1d) +assert_type(5 + poly_obj, np.poly1d) +assert_type(poly_obj - 5, np.poly1d) +assert_type(5 - poly_obj, np.poly1d) +assert_type(poly_obj**1, np.poly1d) +assert_type(poly_obj**1.0, np.poly1d) +assert_type(poly_obj / 5, np.poly1d) +assert_type(5 / poly_obj, np.poly1d) + +assert_type(poly_obj[0], Any) +poly_obj[0] = 5 +assert_type(iter(poly_obj), Iterator[Any]) +assert_type(poly_obj.deriv(), np.poly1d) +assert_type(poly_obj.integ(), np.poly1d) + +assert_type(np.poly(poly_obj), npt.NDArray[np.floating]) +assert_type(np.poly(AR_f8), npt.NDArray[np.floating]) +assert_type(np.poly(AR_c16), npt.NDArray[np.floating]) + +assert_type(np.polyint(poly_obj), np.poly1d) +assert_type(np.polyint(AR_f8), npt.NDArray[np.floating]) +assert_type(np.polyint(AR_f8, k=AR_c16), npt.NDArray[np.complexfloating]) +assert_type(np.polyint(AR_O, m=2), npt.NDArray[np.object_]) + +assert_type(np.polyder(poly_obj), np.poly1d) +assert_type(np.polyder(AR_f8), npt.NDArray[np.floating]) +assert_type(np.polyder(AR_c16), npt.NDArray[np.complexfloating]) +assert_type(np.polyder(AR_O, m=2), npt.NDArray[np.object_]) + +assert_type(np.polyfit(AR_f8, AR_f8, 2), npt.NDArray[np.float64]) +assert_type( + np.polyfit(AR_f8, AR_i8, 1, full=True), + tuple[ + npt.NDArray[np.float64], + npt.NDArray[np.float64], + npt.NDArray[np.int32], + npt.NDArray[np.float64], + npt.NDArray[np.float64], + ], +) +assert_type( + np.polyfit(AR_u4, AR_f8, 1.0, cov="unscaled"), + tuple[ + npt.NDArray[np.float64], + npt.NDArray[np.float64], + ], +) +assert_type(np.polyfit(AR_c16, AR_f8, 2), npt.NDArray[np.complex128]) +assert_type( + np.polyfit(AR_f8, AR_c16, 1, full=True), + tuple[ + npt.NDArray[np.complex128], + npt.NDArray[np.float64], + npt.NDArray[np.int32], + npt.NDArray[np.float64], + npt.NDArray[np.float64], + ], +) +assert_type( + np.polyfit(AR_u4, AR_c16, 1.0, cov=True), + tuple[ + npt.NDArray[np.complex128], + npt.NDArray[np.complex128], + ], +) + +assert_type(np.polyval(AR_b, AR_b), npt.NDArray[np.int64]) +assert_type(np.polyval(AR_u4, AR_b), npt.NDArray[np.unsignedinteger]) +assert_type(np.polyval(AR_i8, AR_i8), npt.NDArray[np.signedinteger]) +assert_type(np.polyval(AR_f8, AR_i8), npt.NDArray[np.floating]) +assert_type(np.polyval(AR_i8, AR_c16), npt.NDArray[np.complexfloating]) +assert_type(np.polyval(AR_O, AR_O), npt.NDArray[np.object_]) + +assert_type(np.polyadd(poly_obj, AR_i8), np.poly1d) +assert_type(np.polyadd(AR_f8, poly_obj), np.poly1d) +assert_type(np.polyadd(AR_b, AR_b), npt.NDArray[np.bool]) +assert_type(np.polyadd(AR_u4, AR_b), npt.NDArray[np.unsignedinteger]) +assert_type(np.polyadd(AR_i8, AR_i8), npt.NDArray[np.signedinteger]) +assert_type(np.polyadd(AR_f8, AR_i8), npt.NDArray[np.floating]) +assert_type(np.polyadd(AR_i8, AR_c16), npt.NDArray[np.complexfloating]) +assert_type(np.polyadd(AR_O, AR_O), npt.NDArray[np.object_]) + +assert_type(np.polysub(poly_obj, AR_i8), np.poly1d) +assert_type(np.polysub(AR_f8, poly_obj), np.poly1d) + +def test_invalid_polysub() -> None: + assert_type(np.polysub(AR_b, AR_b), NoReturn) + +assert_type(np.polysub(AR_u4, AR_b), npt.NDArray[np.unsignedinteger]) +assert_type(np.polysub(AR_i8, AR_i8), npt.NDArray[np.signedinteger]) +assert_type(np.polysub(AR_f8, AR_i8), npt.NDArray[np.floating]) +assert_type(np.polysub(AR_i8, AR_c16), npt.NDArray[np.complexfloating]) +assert_type(np.polysub(AR_O, AR_O), npt.NDArray[np.object_]) + +assert_type(np.polymul(poly_obj, AR_i8), np.poly1d) +assert_type(np.polymul(AR_f8, poly_obj), np.poly1d) +assert_type(np.polymul(AR_b, AR_b), npt.NDArray[np.bool]) +assert_type(np.polymul(AR_u4, AR_b), npt.NDArray[np.unsignedinteger]) +assert_type(np.polymul(AR_i8, AR_i8), npt.NDArray[np.signedinteger]) +assert_type(np.polymul(AR_f8, AR_i8), npt.NDArray[np.floating]) +assert_type(np.polymul(AR_i8, AR_c16), npt.NDArray[np.complexfloating]) +assert_type(np.polymul(AR_O, AR_O), npt.NDArray[np.object_]) + +assert_type(np.polydiv(poly_obj, AR_i8), tuple[np.poly1d, np.poly1d]) +assert_type(np.polydiv(AR_f8, poly_obj), tuple[np.poly1d, np.poly1d]) +assert_type(np.polydiv(AR_b, AR_b), tuple[npt.NDArray[np.floating], npt.NDArray[np.floating]]) +assert_type(np.polydiv(AR_u4, AR_b), tuple[npt.NDArray[np.floating], npt.NDArray[np.floating]]) +assert_type(np.polydiv(AR_i8, AR_i8), tuple[npt.NDArray[np.floating], npt.NDArray[np.floating]]) +assert_type(np.polydiv(AR_f8, AR_i8), tuple[npt.NDArray[np.floating], npt.NDArray[np.floating]]) +assert_type(np.polydiv(AR_i8, AR_c16), tuple[npt.NDArray[np.complexfloating], npt.NDArray[np.complexfloating]]) +assert_type(np.polydiv(AR_O, AR_O), tuple[npt.NDArray[Any], npt.NDArray[Any]]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/lib_utils.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/lib_utils.pyi new file mode 100644 index 0000000000000000000000000000000000000000..c9470e00a3590c00594d87856a232575bc9ff63e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/lib_utils.pyi @@ -0,0 +1,17 @@ +from io import StringIO +from typing import assert_type + +import numpy as np +import numpy.lib.array_utils as array_utils +import numpy.typing as npt + +AR: npt.NDArray[np.float64] +AR_DICT: dict[str, npt.NDArray[np.float64]] +FILE: StringIO + +def func(a: int) -> bool: ... + +assert_type(array_utils.byte_bounds(AR), tuple[int, int]) +assert_type(array_utils.byte_bounds(np.float64()), tuple[int, int]) + +assert_type(np.info(1, output=FILE), None) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/lib_version.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/lib_version.pyi new file mode 100644 index 0000000000000000000000000000000000000000..03735375ae3e8945c5f9d8f1cab7c90be60f8cf6 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/lib_version.pyi @@ -0,0 +1,20 @@ +from typing import assert_type + +from numpy.lib import NumpyVersion + +version = NumpyVersion("1.8.0") + +assert_type(version.vstring, str) +assert_type(version.version, str) +assert_type(version.major, int) +assert_type(version.minor, int) +assert_type(version.bugfix, int) +assert_type(version.pre_release, str) +assert_type(version.is_devversion, bool) + +assert_type(version == version, bool) +assert_type(version != version, bool) +assert_type(version < "1.8.0", bool) +assert_type(version <= version, bool) +assert_type(version > version, bool) +assert_type(version >= "1.8.0", bool) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/linalg.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/linalg.pyi new file mode 100644 index 0000000000000000000000000000000000000000..60056516def0e06f168ee5f6c165160bc6c38be6 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/linalg.pyi @@ -0,0 +1,154 @@ +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt +from numpy.linalg._linalg import ( + EighResult, + EigResult, + QRResult, + SlogdetResult, + SVDResult, +) + +float_list_2d: list[list[float]] +AR_i8: npt.NDArray[np.int64] +AR_f4: npt.NDArray[np.float32] +AR_f8: npt.NDArray[np.float64] +AR_c8: npt.NDArray[np.complex64] +AR_c16: npt.NDArray[np.complex128] +AR_O: npt.NDArray[np.object_] +AR_m: npt.NDArray[np.timedelta64] +AR_S: npt.NDArray[np.str_] +AR_b: npt.NDArray[np.bool] + +assert_type(np.linalg.tensorsolve(AR_i8, AR_i8), npt.NDArray[np.float64]) +assert_type(np.linalg.tensorsolve(AR_i8, AR_f8), npt.NDArray[np.floating]) +assert_type(np.linalg.tensorsolve(AR_c16, AR_f8), npt.NDArray[np.complexfloating]) + +assert_type(np.linalg.solve(AR_i8, AR_i8), npt.NDArray[np.float64]) +assert_type(np.linalg.solve(AR_i8, AR_f8), npt.NDArray[np.floating]) +assert_type(np.linalg.solve(AR_c16, AR_f8), npt.NDArray[np.complexfloating]) + +assert_type(np.linalg.tensorinv(AR_i8), npt.NDArray[np.float64]) +assert_type(np.linalg.tensorinv(AR_f8), npt.NDArray[np.floating]) +assert_type(np.linalg.tensorinv(AR_c16), npt.NDArray[np.complexfloating]) + +assert_type(np.linalg.inv(AR_i8), npt.NDArray[np.float64]) +assert_type(np.linalg.inv(AR_f8), npt.NDArray[np.floating]) +assert_type(np.linalg.inv(AR_c16), npt.NDArray[np.complexfloating]) + +assert_type(np.linalg.matrix_power(AR_i8, -1), npt.NDArray[Any]) +assert_type(np.linalg.matrix_power(AR_f8, 0), npt.NDArray[Any]) +assert_type(np.linalg.matrix_power(AR_c16, 1), npt.NDArray[Any]) +assert_type(np.linalg.matrix_power(AR_O, 2), npt.NDArray[Any]) + +assert_type(np.linalg.cholesky(AR_i8), npt.NDArray[np.float64]) +assert_type(np.linalg.cholesky(AR_f8), npt.NDArray[np.floating]) +assert_type(np.linalg.cholesky(AR_c16), npt.NDArray[np.complexfloating]) + +assert_type(np.linalg.outer(AR_i8, AR_i8), npt.NDArray[np.int64]) +assert_type(np.linalg.outer(AR_f8, AR_f8), npt.NDArray[np.float64]) +assert_type(np.linalg.outer(AR_c16, AR_c16), npt.NDArray[np.complex128]) +assert_type(np.linalg.outer(AR_b, AR_b), npt.NDArray[np.bool]) +assert_type(np.linalg.outer(AR_O, AR_O), npt.NDArray[np.object_]) +assert_type(np.linalg.outer(AR_i8, AR_m), npt.NDArray[np.timedelta64]) + +assert_type(np.linalg.qr(AR_i8), QRResult) +assert_type(np.linalg.qr(AR_f8), QRResult) +assert_type(np.linalg.qr(AR_c16), QRResult) + +assert_type(np.linalg.eigvals(AR_i8), npt.NDArray[np.float64] | npt.NDArray[np.complex128]) +assert_type(np.linalg.eigvals(AR_f8), npt.NDArray[np.floating] | npt.NDArray[np.complexfloating]) +assert_type(np.linalg.eigvals(AR_c16), npt.NDArray[np.complexfloating]) + +assert_type(np.linalg.eigvalsh(AR_i8), npt.NDArray[np.float64]) +assert_type(np.linalg.eigvalsh(AR_f8), npt.NDArray[np.floating]) +assert_type(np.linalg.eigvalsh(AR_c16), npt.NDArray[np.floating]) + +assert_type(np.linalg.eig(AR_i8), EigResult) +assert_type(np.linalg.eig(AR_f8), EigResult) +assert_type(np.linalg.eig(AR_c16), EigResult) + +assert_type(np.linalg.eigh(AR_i8), EighResult) +assert_type(np.linalg.eigh(AR_f8), EighResult) +assert_type(np.linalg.eigh(AR_c16), EighResult) + +assert_type(np.linalg.svd(AR_i8), SVDResult) +assert_type(np.linalg.svd(AR_f8), SVDResult) +assert_type(np.linalg.svd(AR_c16), SVDResult) +assert_type(np.linalg.svd(AR_i8, compute_uv=False), npt.NDArray[np.float64]) +assert_type(np.linalg.svd(AR_i8, True, False), npt.NDArray[np.float64]) +assert_type(np.linalg.svd(AR_f8, compute_uv=False), npt.NDArray[np.floating]) +assert_type(np.linalg.svd(AR_c16, compute_uv=False), npt.NDArray[np.floating]) +assert_type(np.linalg.svd(AR_c16, True, False), npt.NDArray[np.floating]) + +assert_type(np.linalg.svdvals(AR_b), npt.NDArray[np.float64]) +assert_type(np.linalg.svdvals(AR_i8), npt.NDArray[np.float64]) +assert_type(np.linalg.svdvals(AR_f4), npt.NDArray[np.float32]) +assert_type(np.linalg.svdvals(AR_c8), npt.NDArray[np.float32]) +assert_type(np.linalg.svdvals(AR_f8), npt.NDArray[np.float64]) +assert_type(np.linalg.svdvals(AR_c16), npt.NDArray[np.float64]) +assert_type(np.linalg.svdvals([[1, 2], [3, 4]]), npt.NDArray[np.float64]) +assert_type(np.linalg.svdvals([[1.0, 2.0], [3.0, 4.0]]), npt.NDArray[np.float64]) +assert_type(np.linalg.svdvals([[1j, 2j], [3j, 4j]]), npt.NDArray[np.float64]) + +assert_type(np.linalg.cond(AR_i8), Any) +assert_type(np.linalg.cond(AR_f8), Any) +assert_type(np.linalg.cond(AR_c16), Any) + +assert_type(np.linalg.matrix_rank(AR_i8), Any) +assert_type(np.linalg.matrix_rank(AR_f8), Any) +assert_type(np.linalg.matrix_rank(AR_c16), Any) + +assert_type(np.linalg.pinv(AR_i8), npt.NDArray[np.float64]) +assert_type(np.linalg.pinv(AR_f8), npt.NDArray[np.floating]) +assert_type(np.linalg.pinv(AR_c16), npt.NDArray[np.complexfloating]) + +assert_type(np.linalg.slogdet(AR_i8), SlogdetResult) +assert_type(np.linalg.slogdet(AR_f8), SlogdetResult) +assert_type(np.linalg.slogdet(AR_c16), SlogdetResult) + +assert_type(np.linalg.det(AR_i8), Any) +assert_type(np.linalg.det(AR_f8), Any) +assert_type(np.linalg.det(AR_c16), Any) + +assert_type(np.linalg.lstsq(AR_i8, AR_i8), tuple[npt.NDArray[np.float64], npt.NDArray[np.float64], np.int32, npt.NDArray[np.float64]]) +assert_type(np.linalg.lstsq(AR_i8, AR_f8), tuple[npt.NDArray[np.floating], npt.NDArray[np.floating], np.int32, npt.NDArray[np.floating]]) +assert_type(np.linalg.lstsq(AR_f8, AR_c16), tuple[npt.NDArray[np.complexfloating], npt.NDArray[np.floating], np.int32, npt.NDArray[np.floating]]) + +assert_type(np.linalg.norm(AR_i8), np.floating) +assert_type(np.linalg.norm(AR_f8), np.floating) +assert_type(np.linalg.norm(AR_c16), np.floating) +assert_type(np.linalg.norm(AR_S), np.floating) +assert_type(np.linalg.norm(AR_f8, axis=0), Any) + +assert_type(np.linalg.matrix_norm(AR_i8), np.floating) +assert_type(np.linalg.matrix_norm(AR_f8), np.floating) +assert_type(np.linalg.matrix_norm(AR_c16), np.floating) +assert_type(np.linalg.matrix_norm(AR_S), np.floating) + +assert_type(np.linalg.vector_norm(AR_i8), np.floating) +assert_type(np.linalg.vector_norm(AR_f8), np.floating) +assert_type(np.linalg.vector_norm(AR_c16), np.floating) +assert_type(np.linalg.vector_norm(AR_S), np.floating) + +assert_type(np.linalg.tensordot(AR_b, AR_b), npt.NDArray[np.bool]) +assert_type(np.linalg.tensordot(AR_i8, AR_i8), npt.NDArray[np.int64]) +assert_type(np.linalg.tensordot(AR_f8, AR_f8), npt.NDArray[np.float64]) +assert_type(np.linalg.tensordot(AR_c16, AR_c16), npt.NDArray[np.complex128]) +assert_type(np.linalg.tensordot(AR_m, AR_m), npt.NDArray[np.timedelta64]) +assert_type(np.linalg.tensordot(AR_O, AR_O), npt.NDArray[np.object_]) + +assert_type(np.linalg.multi_dot([AR_i8, AR_i8]), Any) +assert_type(np.linalg.multi_dot([AR_i8, AR_f8]), Any) +assert_type(np.linalg.multi_dot([AR_f8, AR_c16]), Any) +assert_type(np.linalg.multi_dot([AR_O, AR_O]), Any) +assert_type(np.linalg.multi_dot([AR_m, AR_m]), Any) + +assert_type(np.linalg.cross(AR_i8, AR_i8), npt.NDArray[np.signedinteger]) +assert_type(np.linalg.cross(AR_f8, AR_f8), npt.NDArray[np.floating]) +assert_type(np.linalg.cross(AR_c16, AR_c16), npt.NDArray[np.complexfloating]) + +assert_type(np.linalg.matmul(AR_i8, AR_i8), npt.NDArray[np.int64]) +assert_type(np.linalg.matmul(AR_f8, AR_f8), npt.NDArray[np.float64]) +assert_type(np.linalg.matmul(AR_c16, AR_c16), npt.NDArray[np.complex128]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ma.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ma.pyi new file mode 100644 index 0000000000000000000000000000000000000000..8eef32ddd59375fd2ae1dd7044c0ecd950227f69 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ma.pyi @@ -0,0 +1,1098 @@ +from typing import Any, Generic, Literal, NoReturn, TypeAlias, TypeVar, assert_type + +import numpy as np +from numpy import dtype, generic +from numpy._typing import NDArray, _AnyShape + +_ScalarT = TypeVar("_ScalarT", bound=generic) +_ScalarT_co = TypeVar("_ScalarT_co", bound=generic, covariant=True) + +MaskedArray: TypeAlias = np.ma.MaskedArray[_AnyShape, dtype[_ScalarT]] +_NoMaskType: TypeAlias = np.bool[Literal[False]] +_Array1D: TypeAlias = np.ndarray[tuple[int], np.dtype[_ScalarT]] + +class MaskedArraySubclass(MaskedArray[_ScalarT_co]): ... + +class IntoMaskedArraySubClass(Generic[_ScalarT_co]): + def __array__(self) -> MaskedArraySubclass[_ScalarT_co]: ... + +MaskedArraySubclassC: TypeAlias = MaskedArraySubclass[np.complex128] + +AR_b: NDArray[np.bool] +AR_f4: NDArray[np.float32] +AR_i8: NDArray[np.int64] +AR_u4: NDArray[np.uint32] +AR_dt64: NDArray[np.datetime64] +AR_td64: NDArray[np.timedelta64] +AR_o: NDArray[np.timedelta64] + +AR_LIKE_b: list[bool] +AR_LIKE_u: list[np.uint32] +AR_LIKE_i: list[int] +AR_LIKE_f: list[float] +AR_LIKE_c: list[complex] +AR_LIKE_td64: list[np.timedelta64] +AR_LIKE_dt64: list[np.datetime64] +AR_LIKE_o: list[np.object_] +AR_number: NDArray[np.number] + +MAR_c8: MaskedArray[np.complex64] +MAR_c16: MaskedArray[np.complex128] +MAR_b: MaskedArray[np.bool] +MAR_f4: MaskedArray[np.float32] +MAR_f8: MaskedArray[np.float64] +MAR_i8: MaskedArray[np.int64] +MAR_u4: MaskedArray[np.uint32] +MAR_dt64: MaskedArray[np.datetime64] +MAR_td64: MaskedArray[np.timedelta64] +MAR_o: MaskedArray[np.object_] +MAR_s: MaskedArray[np.str_] +MAR_byte: MaskedArray[np.bytes_] +MAR_V: MaskedArray[np.void] +MAR_floating: MaskedArray[np.floating] +MAR_number: MaskedArray[np.number] + +MAR_subclass: MaskedArraySubclassC +MAR_into_subclass: IntoMaskedArraySubClass[np.float32] + +MAR_1d: np.ma.MaskedArray[tuple[int], np.dtype] +MAR_2d_f4: np.ma.MaskedArray[tuple[int, int], np.dtype[np.float32]] +MAR_2d_V: np.ma.MaskedArray[tuple[int, int], np.dtype[np.void]] + +b: np.bool +f4: np.float32 +f: float +i: int + +assert_type(MAR_1d.shape, tuple[int]) + +assert_type(MAR_f4.dtype, np.dtype[np.float32]) + +assert_type(int(MAR_i8), int) +assert_type(float(MAR_f4), float) + +assert_type(np.ma.min(MAR_b), np.bool) +assert_type(np.ma.min(MAR_f4), np.float32) +assert_type(np.ma.min(MAR_b, axis=0), Any) +assert_type(np.ma.min(MAR_f4, axis=0), Any) +assert_type(np.ma.min(MAR_b, keepdims=True), Any) +assert_type(np.ma.min(MAR_f4, keepdims=True), Any) +assert_type(np.ma.min(MAR_f4, out=MAR_subclass), MaskedArraySubclassC) +assert_type(np.ma.min(MAR_f4, 0, MAR_subclass), MaskedArraySubclassC) +assert_type(np.ma.min(MAR_f4, None, MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_b.min(), np.bool) +assert_type(MAR_f4.min(), np.float32) +assert_type(MAR_b.min(axis=0), Any) +assert_type(MAR_f4.min(axis=0), Any) +assert_type(MAR_b.min(keepdims=True), Any) +assert_type(MAR_f4.min(keepdims=True), Any) +assert_type(MAR_f4.min(out=MAR_subclass), MaskedArraySubclassC) +assert_type(MAR_f4.min(0, MAR_subclass), MaskedArraySubclassC) +assert_type(MAR_f4.min(None, MAR_subclass), MaskedArraySubclassC) + +assert_type(np.ma.max(MAR_b), np.bool) +assert_type(np.ma.max(MAR_f4), np.float32) +assert_type(np.ma.max(MAR_b, axis=0), Any) +assert_type(np.ma.max(MAR_f4, axis=0), Any) +assert_type(np.ma.max(MAR_b, keepdims=True), Any) +assert_type(np.ma.max(MAR_f4, keepdims=True), Any) +assert_type(np.ma.max(MAR_f4, out=MAR_subclass), MaskedArraySubclassC) +assert_type(np.ma.max(MAR_f4, 0, MAR_subclass), MaskedArraySubclassC) +assert_type(np.ma.max(MAR_f4, None, MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_b.max(), np.bool) +assert_type(MAR_f4.max(), np.float32) +assert_type(MAR_b.max(axis=0), Any) +assert_type(MAR_f4.max(axis=0), Any) +assert_type(MAR_b.max(keepdims=True), Any) +assert_type(MAR_f4.max(keepdims=True), Any) +assert_type(MAR_f4.max(out=MAR_subclass), MaskedArraySubclassC) +assert_type(MAR_f4.max(0, MAR_subclass), MaskedArraySubclassC) +assert_type(MAR_f4.max(None, MAR_subclass), MaskedArraySubclassC) + +assert_type(np.ma.ptp(MAR_b), np.bool) +assert_type(np.ma.ptp(MAR_f4), np.float32) +assert_type(np.ma.ptp(MAR_b, axis=0), Any) +assert_type(np.ma.ptp(MAR_f4, axis=0), Any) +assert_type(np.ma.ptp(MAR_b, keepdims=True), Any) +assert_type(np.ma.ptp(MAR_f4, keepdims=True), Any) +assert_type(np.ma.ptp(MAR_f4, out=MAR_subclass), MaskedArraySubclassC) +assert_type(np.ma.ptp(MAR_f4, 0, MAR_subclass), MaskedArraySubclassC) +assert_type(np.ma.ptp(MAR_f4, None, MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_b.ptp(), np.bool) +assert_type(MAR_f4.ptp(), np.float32) +assert_type(MAR_b.ptp(axis=0), Any) +assert_type(MAR_f4.ptp(axis=0), Any) +assert_type(MAR_b.ptp(keepdims=True), Any) +assert_type(MAR_f4.ptp(keepdims=True), Any) +assert_type(MAR_f4.ptp(out=MAR_subclass), MaskedArraySubclassC) +assert_type(MAR_f4.ptp(0, MAR_subclass), MaskedArraySubclassC) +assert_type(MAR_f4.ptp(None, MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_b.argmin(), np.intp) +assert_type(MAR_f4.argmin(), np.intp) +assert_type(MAR_f4.argmax(fill_value=6.28318, keepdims=False), np.intp) +assert_type(MAR_b.argmin(axis=0), Any) +assert_type(MAR_f4.argmin(axis=0), Any) +assert_type(MAR_b.argmin(keepdims=True), Any) +assert_type(MAR_f4.argmin(out=MAR_subclass), MaskedArraySubclassC) +assert_type(MAR_f4.argmin(None, None, out=MAR_subclass), MaskedArraySubclassC) + +assert_type(np.ma.argmin(MAR_b), np.intp) +assert_type(np.ma.argmin(MAR_f4), np.intp) +assert_type(np.ma.argmin(MAR_f4, fill_value=6.28318, keepdims=False), np.intp) +assert_type(np.ma.argmin(MAR_b, axis=0), Any) +assert_type(np.ma.argmin(MAR_f4, axis=0), Any) +assert_type(np.ma.argmin(MAR_b, keepdims=True), Any) +assert_type(np.ma.argmin(MAR_f4, out=MAR_subclass), MaskedArraySubclassC) +assert_type(np.ma.argmin(MAR_f4, None, None, out=MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_b.argmax(), np.intp) +assert_type(MAR_f4.argmax(), np.intp) +assert_type(MAR_f4.argmax(fill_value=6.28318, keepdims=False), np.intp) +assert_type(MAR_b.argmax(axis=0), Any) +assert_type(MAR_f4.argmax(axis=0), Any) +assert_type(MAR_b.argmax(keepdims=True), Any) +assert_type(MAR_f4.argmax(out=MAR_subclass), MaskedArraySubclassC) +assert_type(MAR_f4.argmax(None, None, out=MAR_subclass), MaskedArraySubclassC) + +assert_type(np.ma.argmax(MAR_b), np.intp) +assert_type(np.ma.argmax(MAR_f4), np.intp) +assert_type(np.ma.argmax(MAR_f4, fill_value=6.28318, keepdims=False), np.intp) +assert_type(np.ma.argmax(MAR_b, axis=0), Any) +assert_type(np.ma.argmax(MAR_f4, axis=0), Any) +assert_type(np.ma.argmax(MAR_b, keepdims=True), Any) +assert_type(np.ma.argmax(MAR_f4, out=MAR_subclass), MaskedArraySubclassC) +assert_type(np.ma.argmax(MAR_f4, None, None, out=MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_b.all(), np.bool) +assert_type(MAR_f4.all(), np.bool) +assert_type(MAR_f4.all(keepdims=False), np.bool) +assert_type(MAR_b.all(axis=0), np.bool | MaskedArray[np.bool]) +assert_type(MAR_b.all(axis=0, keepdims=True), MaskedArray[np.bool]) +assert_type(MAR_b.all(0, None, True), MaskedArray[np.bool]) +assert_type(MAR_f4.all(axis=0), np.bool | MaskedArray[np.bool]) +assert_type(MAR_b.all(keepdims=True), MaskedArray[np.bool]) +assert_type(MAR_f4.all(out=MAR_subclass), MaskedArraySubclassC) +assert_type(MAR_f4.all(None, out=MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_b.any(), np.bool) +assert_type(MAR_f4.any(), np.bool) +assert_type(MAR_f4.any(keepdims=False), np.bool) +assert_type(MAR_b.any(axis=0), np.bool | MaskedArray[np.bool]) +assert_type(MAR_b.any(axis=0, keepdims=True), MaskedArray[np.bool]) +assert_type(MAR_b.any(0, None, True), MaskedArray[np.bool]) +assert_type(MAR_f4.any(axis=0), np.bool | MaskedArray[np.bool]) +assert_type(MAR_b.any(keepdims=True), MaskedArray[np.bool]) +assert_type(MAR_f4.any(out=MAR_subclass), MaskedArraySubclassC) +assert_type(MAR_f4.any(None, out=MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_f4.sort(), None) +assert_type(MAR_f4.sort(axis=0, kind="quicksort", order="K", endwith=False, fill_value=42., stable=False), None) + +assert_type(np.ma.sort(MAR_f4), MaskedArray[np.float32]) +assert_type(np.ma.sort(MAR_subclass), MaskedArraySubclassC) +assert_type(np.ma.sort([[0, 1], [2, 3]]), NDArray[Any]) +assert_type(np.ma.sort(AR_f4), NDArray[np.float32]) + +assert_type(MAR_f8.take(0), np.float64) +assert_type(MAR_1d.take(0), Any) +assert_type(MAR_f8.take([0]), MaskedArray[np.float64]) +assert_type(MAR_f8.take(0, out=MAR_subclass), MaskedArraySubclassC) +assert_type(MAR_f8.take([0], out=MAR_subclass), MaskedArraySubclassC) + +assert_type(np.ma.take(f, 0), Any) +assert_type(np.ma.take(f4, 0), np.float32) +assert_type(np.ma.take(MAR_f8, 0), np.float64) +assert_type(np.ma.take(AR_f4, 0), np.float32) +assert_type(np.ma.take(MAR_1d, 0), Any) +assert_type(np.ma.take(MAR_f8, [0]), MaskedArray[np.float64]) +assert_type(np.ma.take(AR_f4, [0]), MaskedArray[np.float32]) +assert_type(np.ma.take(MAR_f8, 0, out=MAR_subclass), MaskedArraySubclassC) +assert_type(np.ma.take(MAR_f8, [0], out=MAR_subclass), MaskedArraySubclassC) +assert_type(np.ma.take([1], [0]), MaskedArray[Any]) +assert_type(np.ma.take(np.eye(2), 1, axis=0), MaskedArray[np.float64]) + +assert_type(MAR_f4.partition(1), None) +assert_type(MAR_V.partition(1, axis=0, kind="introselect", order="K"), None) + +assert_type(MAR_f4.argpartition(1), MaskedArray[np.intp]) +assert_type(MAR_1d.argpartition(1, axis=0, kind="introselect", order="K"), MaskedArray[np.intp]) + +assert_type(np.ma.ndim(f4), int) +assert_type(np.ma.ndim(MAR_b), int) +assert_type(np.ma.ndim(AR_f4), int) + +assert_type(np.ma.size(b), int) +assert_type(np.ma.size(MAR_f4, axis=0), int) +assert_type(np.ma.size(AR_f4), int) + +assert_type(np.ma.is_masked(MAR_f4), bool) + +assert_type(MAR_f4.ids(), tuple[int, int]) + +assert_type(MAR_f4.iscontiguous(), bool) + +assert_type(MAR_f4 >= 3, MaskedArray[np.bool]) +assert_type(MAR_i8 >= AR_td64, MaskedArray[np.bool]) +assert_type(MAR_b >= AR_td64, MaskedArray[np.bool]) +assert_type(MAR_td64 >= AR_td64, MaskedArray[np.bool]) +assert_type(MAR_dt64 >= AR_dt64, MaskedArray[np.bool]) +assert_type(MAR_o >= AR_o, MaskedArray[np.bool]) +assert_type(MAR_1d >= 0, MaskedArray[np.bool]) +assert_type(MAR_s >= MAR_s, MaskedArray[np.bool]) +assert_type(MAR_byte >= MAR_byte, MaskedArray[np.bool]) + +assert_type(MAR_f4 > 3, MaskedArray[np.bool]) +assert_type(MAR_i8 > AR_td64, MaskedArray[np.bool]) +assert_type(MAR_b > AR_td64, MaskedArray[np.bool]) +assert_type(MAR_td64 > AR_td64, MaskedArray[np.bool]) +assert_type(MAR_dt64 > AR_dt64, MaskedArray[np.bool]) +assert_type(MAR_o > AR_o, MaskedArray[np.bool]) +assert_type(MAR_1d > 0, MaskedArray[np.bool]) +assert_type(MAR_s > MAR_s, MaskedArray[np.bool]) +assert_type(MAR_byte > MAR_byte, MaskedArray[np.bool]) + +assert_type(MAR_f4 <= 3, MaskedArray[np.bool]) +assert_type(MAR_i8 <= AR_td64, MaskedArray[np.bool]) +assert_type(MAR_b <= AR_td64, MaskedArray[np.bool]) +assert_type(MAR_td64 <= AR_td64, MaskedArray[np.bool]) +assert_type(MAR_dt64 <= AR_dt64, MaskedArray[np.bool]) +assert_type(MAR_o <= AR_o, MaskedArray[np.bool]) +assert_type(MAR_1d <= 0, MaskedArray[np.bool]) +assert_type(MAR_s <= MAR_s, MaskedArray[np.bool]) +assert_type(MAR_byte <= MAR_byte, MaskedArray[np.bool]) + +assert_type(MAR_f4 < 3, MaskedArray[np.bool]) +assert_type(MAR_i8 < AR_td64, MaskedArray[np.bool]) +assert_type(MAR_b < AR_td64, MaskedArray[np.bool]) +assert_type(MAR_td64 < AR_td64, MaskedArray[np.bool]) +assert_type(MAR_dt64 < AR_dt64, MaskedArray[np.bool]) +assert_type(MAR_o < AR_o, MaskedArray[np.bool]) +assert_type(MAR_1d < 0, MaskedArray[np.bool]) +assert_type(MAR_s < MAR_s, MaskedArray[np.bool]) +assert_type(MAR_byte < MAR_byte, MaskedArray[np.bool]) + +assert_type(MAR_f4 <= 3, MaskedArray[np.bool]) +assert_type(MAR_i8 <= AR_td64, MaskedArray[np.bool]) +assert_type(MAR_b <= AR_td64, MaskedArray[np.bool]) +assert_type(MAR_td64 <= AR_td64, MaskedArray[np.bool]) +assert_type(MAR_dt64 <= AR_dt64, MaskedArray[np.bool]) +assert_type(MAR_o <= AR_o, MaskedArray[np.bool]) +assert_type(MAR_1d <= 0, MaskedArray[np.bool]) +assert_type(MAR_s <= MAR_s, MaskedArray[np.bool]) +assert_type(MAR_byte <= MAR_byte, MaskedArray[np.bool]) + +assert_type(MAR_byte.count(), int) +assert_type(MAR_f4.count(axis=None), int) +assert_type(MAR_f4.count(axis=0), NDArray[np.int_]) +assert_type(MAR_b.count(axis=(0, 1)), NDArray[np.int_]) +assert_type(MAR_o.count(keepdims=True), NDArray[np.int_]) +assert_type(MAR_o.count(axis=None, keepdims=True), NDArray[np.int_]) +assert_type(MAR_o.count(None, True), NDArray[np.int_]) + +assert_type(np.ma.count(MAR_byte), int) +assert_type(np.ma.count(MAR_byte, axis=None), int) +assert_type(np.ma.count(MAR_f4, axis=0), NDArray[np.int_]) +assert_type(np.ma.count(MAR_b, axis=(0, 1)), NDArray[np.int_]) +assert_type(np.ma.count(MAR_o, keepdims=True), NDArray[np.int_]) +assert_type(np.ma.count(MAR_o, axis=None, keepdims=True), NDArray[np.int_]) +assert_type(np.ma.count(MAR_o, None, True), NDArray[np.int_]) + +assert_type(MAR_f4.compressed(), np.ndarray[tuple[int], np.dtype[np.float32]]) + +assert_type(MAR_f4.compress([True, False]), np.ma.MaskedArray[tuple[int], np.dtype[np.float32]]) +assert_type(MAR_f4.compress([True, False], axis=0), MaskedArray[np.float32]) +assert_type(MAR_f4.compress([True, False], axis=0, out=MAR_subclass), MaskedArraySubclassC) +assert_type(MAR_f4.compress([True, False], 0, MAR_subclass), MaskedArraySubclassC) + +assert_type(np.ma.compressed(MAR_i8), np.ndarray[tuple[int], np.dtype[np.int64]]) +assert_type(np.ma.compressed([[1, 2, 3]]), np.ndarray[tuple[int], np.dtype]) + +assert_type(MAR_f4.put([0, 4, 8], [10, 20, 30]), None) +assert_type(MAR_f4.put(4, 999), None) +assert_type(MAR_f4.put(4, 999, mode="clip"), None) + +assert_type(MAR_c8.__array_wrap__(AR_b), MaskedArray[np.bool]) + +assert_type(np.ma.put(MAR_f4, [0, 4, 8], [10, 20, 30]), None) +assert_type(np.ma.put(MAR_f4, 4, 999), None) +assert_type(np.ma.put(MAR_f4, 4, 999, mode="clip"), None) + +assert_type(np.ma.putmask(MAR_f4, [True, False], [0, 1]), None) +assert_type(np.ma.putmask(MAR_f4, np.False_, [0, 1]), None) + +assert_type(MAR_f4.filled(float("nan")), NDArray[np.float32]) +assert_type(MAR_i8.filled(), NDArray[np.int64]) +assert_type(MAR_1d.filled(), np.ndarray[tuple[int], np.dtype]) + +assert_type(np.ma.filled(MAR_f4, float("nan")), NDArray[np.float32]) +assert_type(np.ma.filled([[1, 2, 3]]), NDArray[Any]) +# PyRight detects this one correctly, but mypy doesn't. +# https://github.com/numpy/numpy/pull/28742#discussion_r2048968375 +assert_type(np.ma.filled(MAR_1d), np.ndarray[tuple[int], np.dtype]) # type: ignore[assert-type] + +assert_type(MAR_b.repeat(3), np.ma.MaskedArray[tuple[int], np.dtype[np.bool]]) +assert_type(MAR_2d_f4.repeat(MAR_i8), np.ma.MaskedArray[tuple[int], np.dtype[np.float32]]) +assert_type(MAR_2d_f4.repeat(MAR_i8, axis=None), np.ma.MaskedArray[tuple[int], np.dtype[np.float32]]) +assert_type(MAR_2d_f4.repeat(MAR_i8, axis=0), MaskedArray[np.float32]) + +assert_type(np.ma.allequal(AR_f4, MAR_f4), bool) +assert_type(np.ma.allequal(AR_f4, MAR_f4, fill_value=False), bool) + +assert_type(np.ma.allclose(AR_f4, MAR_f4), bool) +assert_type(np.ma.allclose(AR_f4, MAR_f4, masked_equal=False), bool) +assert_type(np.ma.allclose(AR_f4, MAR_f4, rtol=.4, atol=.3), bool) + +assert_type(MAR_2d_f4.ravel(), np.ma.MaskedArray[tuple[int], np.dtype[np.float32]]) +assert_type(MAR_1d.ravel(order="A"), np.ma.MaskedArray[tuple[int], np.dtype[Any]]) + +assert_type(np.ma.getmask(MAR_f4), NDArray[np.bool] | _NoMaskType) +# PyRight detects this one correctly, but mypy doesn't: +# `Revealed type is "Union[numpy.ndarray[Any, Any], numpy.bool[Any]]"` +assert_type(np.ma.getmask(MAR_1d), np.ndarray[tuple[int], np.dtype[np.bool]] | np.bool) # type: ignore[assert-type] +assert_type(np.ma.getmask(MAR_2d_f4), np.ndarray[tuple[int, int], np.dtype[np.bool]] | _NoMaskType) +assert_type(np.ma.getmask([1, 2]), NDArray[np.bool] | _NoMaskType) +assert_type(np.ma.getmask(np.int64(1)), _NoMaskType) + +assert_type(np.ma.is_mask(MAR_1d), bool) +assert_type(np.ma.is_mask(AR_b), bool) + +def func(x: object) -> None: + if np.ma.is_mask(x): + assert_type(x, NDArray[np.bool]) + else: + assert_type(x, object) + +assert_type(MAR_2d_f4.mT, np.ma.MaskedArray[tuple[int, int], np.dtype[np.float32]]) + +assert_type(MAR_c16.real, MaskedArray[np.float64]) +assert_type(MAR_c16.imag, MaskedArray[np.float64]) + +assert_type(MAR_2d_f4.baseclass, type[NDArray[Any]]) + +assert_type(MAR_b.swapaxes(0, 1), MaskedArray[np.bool]) +assert_type(MAR_2d_f4.swapaxes(1, 0), np.ma.MaskedArray[tuple[int, int], np.dtype[np.float32]]) + +assert_type(MAR_2d_f4[AR_i8], MaskedArray[np.float32]) +assert_type(MAR_2d_f4[[1, 2, 3]], MaskedArray[np.float32]) +assert_type(MAR_2d_f4[1:], MaskedArray[np.float32]) +assert_type(MAR_2d_f4[:], MaskedArray[np.float32]) +assert_type(MAR_2d_f4[0, 0], Any) +assert_type(MAR_2d_f4[:, np.newaxis], MaskedArray[np.float32]) +assert_type(MAR_2d_f4[..., -1], MaskedArray[np.float32]) +assert_type(MAR_2d_V["field_0"], np.ma.MaskedArray[tuple[int, int], np.dtype]) +assert_type(MAR_2d_V[["field_0", "field_1"]], np.ma.MaskedArray[tuple[int, int], np.dtype[np.void]]) + +assert_type(np.ma.nomask, np.bool[Literal[False]]) +assert_type(np.ma.MaskType, type[np.bool]) + +assert_type(MAR_1d.__setmask__([True, False]), None) +assert_type(MAR_1d.__setmask__(np.False_), None) + +assert_type(MAR_2d_f4.harden_mask(), np.ma.MaskedArray[tuple[int, int], np.dtype[np.float32]]) +assert_type(MAR_i8.harden_mask(), MaskedArray[np.int64]) +assert_type(MAR_2d_f4.soften_mask(), np.ma.MaskedArray[tuple[int, int], np.dtype[np.float32]]) +assert_type(MAR_i8.soften_mask(), MaskedArray[np.int64]) +assert_type(MAR_f4.unshare_mask(), MaskedArray[np.float32]) +assert_type(MAR_b.shrink_mask(), MaskedArray[np.bool_]) + +assert_type(MAR_i8.hardmask, bool) +assert_type(MAR_i8.sharedmask, bool) + +assert_type(MAR_i8.recordmask, np.ma.MaskType | NDArray[np.ma.MaskType]) +assert_type(MAR_2d_f4.recordmask, np.ma.MaskType | np.ndarray[tuple[int, int], np.dtype[np.ma.MaskType]]) + +assert_type(MAR_2d_f4.anom(), np.ma.MaskedArray[tuple[int, int], np.dtype[np.float32]]) +assert_type(MAR_2d_f4.anom(axis=0, dtype=np.float16), np.ma.MaskedArray[tuple[int, int], np.dtype]) +assert_type(MAR_2d_f4.anom(0, np.float16), np.ma.MaskedArray[tuple[int, int], np.dtype]) +assert_type(MAR_2d_f4.anom(0, "float16"), np.ma.MaskedArray[tuple[int, int], np.dtype]) + +assert_type(MAR_i8.fill_value, np.int64) + +assert_type(MAR_b.transpose(), MaskedArray[np.bool]) +assert_type(MAR_2d_f4.transpose(), np.ma.MaskedArray[tuple[int, int], np.dtype[np.float32]]) +assert_type(MAR_2d_f4.transpose(1, 0), np.ma.MaskedArray[tuple[int, int], np.dtype[np.float32]]) +assert_type(MAR_2d_f4.transpose((1, 0)), np.ma.MaskedArray[tuple[int, int], np.dtype[np.float32]]) +assert_type(MAR_b.T, MaskedArray[np.bool]) +assert_type(MAR_2d_f4.T, np.ma.MaskedArray[tuple[int, int], np.dtype[np.float32]]) + +assert_type(MAR_2d_f4.dot(1), MaskedArray[Any]) +assert_type(MAR_2d_f4.dot([1]), MaskedArray[Any]) +assert_type(MAR_2d_f4.dot(1, out=MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_2d_f4.nonzero(), tuple[_Array1D[np.intp], ...]) +assert_type(MAR_2d_f4.nonzero()[0], _Array1D[np.intp]) + +assert_type(MAR_f8.trace(), Any) +assert_type(MAR_f8.trace(out=MAR_subclass), MaskedArraySubclassC) +assert_type(MAR_f8.trace(out=MAR_subclass, dtype=None), MaskedArraySubclassC) + +assert_type(MAR_f8.round(), MaskedArray[np.float64]) +assert_type(MAR_f8.round(out=MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_i8.reshape(None), MaskedArray[np.int64]) +assert_type(MAR_f8.reshape(-1), np.ma.MaskedArray[tuple[int], np.dtype[np.float64]]) +assert_type(MAR_c8.reshape(2, 3, 4, 5), np.ma.MaskedArray[tuple[int, int, int, int], np.dtype[np.complex64]]) +assert_type(MAR_td64.reshape(()), np.ma.MaskedArray[tuple[()], np.dtype[np.timedelta64]]) +assert_type(MAR_s.reshape([]), np.ma.MaskedArray[tuple[()], np.dtype[np.str_]]) +assert_type(MAR_V.reshape((480, 720, 4)), np.ma.MaskedArray[tuple[int, int, int], np.dtype[np.void]]) + +assert_type(MAR_f8.cumprod(), MaskedArray[Any]) +assert_type(MAR_f8.cumprod(out=MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_f8.cumsum(), MaskedArray[Any]) +assert_type(MAR_f8.cumsum(out=MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_f8.view(), MaskedArray[np.float64]) +assert_type(MAR_f8.view(dtype=np.float32), MaskedArray[np.float32]) +assert_type(MAR_f8.view(dtype=np.dtype(np.float32)), MaskedArray[np.float32]) +assert_type(MAR_f8.view(dtype=np.float32, fill_value=0), MaskedArray[np.float32]) +assert_type(MAR_f8.view(type=np.ndarray), np.ndarray[Any, Any]) +assert_type(MAR_f8.view(None, np.ndarray), np.ndarray[Any, Any]) +assert_type(MAR_f8.view(dtype=np.ndarray), np.ndarray[Any, Any]) +assert_type(MAR_f8.view(dtype="float32"), MaskedArray[Any]) +assert_type(MAR_f8.view(dtype="float32", type=np.ndarray), np.ndarray[Any, Any]) +assert_type(MAR_2d_f4.view(dtype=np.float16), np.ma.MaskedArray[tuple[int, int], np.dtype[np.float16]]) +assert_type(MAR_2d_f4.view(dtype=np.dtype(np.float16)), np.ma.MaskedArray[tuple[int, int], np.dtype[np.float16]]) + +assert_type(MAR_f8.__deepcopy__(), MaskedArray[np.float64]) + +assert_type(MAR_f8.argsort(), MaskedArray[np.intp]) +assert_type(MAR_f8.argsort(axis=0, kind="heap", order=("x", "y")), MaskedArray[np.intp]) +assert_type(MAR_f8.argsort(endwith=True, fill_value=1.5, stable=False), MaskedArray[np.intp]) + +assert_type(MAR_2d_f4.flat, np.ma.core.MaskedIterator[tuple[int, int], np.dtype[np.float32]]) +assert_type(MAR_2d_f4.flat.ma, np.ma.MaskedArray[tuple[int, int], np.dtype[np.float32]]) +assert_type(MAR_2d_f4.flat[AR_i8], MaskedArray[np.float32]) +assert_type(MAR_2d_f4.flat[[1, 2, 3]], MaskedArray[np.float32]) +assert_type(MAR_2d_f4.flat[1:], MaskedArray[np.float32]) +assert_type(MAR_2d_f4.flat[:], MaskedArray[np.float32]) +assert_type(MAR_2d_f4.flat[0, 0], Any) +assert_type(MAR_2d_f4.flat[:, np.newaxis], MaskedArray[np.float32]) +assert_type(MAR_2d_f4.flat[..., -1], MaskedArray[np.float32]) + +def invalid_resize() -> None: + assert_type(MAR_f8.resize((1, 1)), NoReturn) # type: ignore[arg-type] + +assert_type(np.ma.MaskedArray(AR_f4), MaskedArray[np.float32]) +assert_type(np.ma.MaskedArray(np.array([1, 2, 3]), [True, True, False], np.float16), MaskedArray[np.float16]) +assert_type(np.ma.MaskedArray(np.array([1, 2, 3]), dtype=np.float16), MaskedArray[np.float16]) +assert_type(np.ma.MaskedArray(np.array([1, 2, 3]), copy=True), MaskedArray[Any]) +# TODO: This one could be made more precise, the return type could be `MaskedArraySubclassC` +assert_type(np.ma.MaskedArray(MAR_subclass), MaskedArray[np.complex128]) +# TODO: This one could be made more precise, the return type could be `MaskedArraySubclass[np.float32]` +assert_type(np.ma.MaskedArray(MAR_into_subclass), MaskedArray[np.float32]) + +# Masked Array addition + +assert_type(MAR_b + AR_LIKE_u, MaskedArray[np.uint32]) +assert_type(MAR_b + AR_LIKE_i, MaskedArray[np.signedinteger]) +assert_type(MAR_b + AR_LIKE_f, MaskedArray[np.floating]) +assert_type(MAR_b + AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_b + AR_LIKE_td64, MaskedArray[np.timedelta64]) +assert_type(MAR_b + AR_LIKE_o, Any) + +assert_type(AR_LIKE_u + MAR_b, MaskedArray[np.uint32]) +assert_type(AR_LIKE_i + MAR_b, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_f + MAR_b, MaskedArray[np.floating]) +assert_type(AR_LIKE_c + MAR_b, MaskedArray[np.complexfloating]) +assert_type(AR_LIKE_td64 + MAR_b, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_dt64 + MAR_b, MaskedArray[np.datetime64]) +assert_type(AR_LIKE_o + MAR_b, Any) + +assert_type(MAR_u4 + AR_LIKE_b, MaskedArray[np.uint32]) +assert_type(MAR_u4 + AR_LIKE_u, MaskedArray[np.unsignedinteger]) +assert_type(MAR_u4 + AR_LIKE_i, MaskedArray[np.signedinteger]) +assert_type(MAR_u4 + AR_LIKE_f, MaskedArray[np.floating]) +assert_type(MAR_u4 + AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_u4 + AR_LIKE_td64, MaskedArray[np.timedelta64]) +assert_type(MAR_u4 + AR_LIKE_o, Any) + +assert_type(AR_LIKE_b + MAR_u4, MaskedArray[np.uint32]) +assert_type(AR_LIKE_u + MAR_u4, MaskedArray[np.unsignedinteger]) +assert_type(AR_LIKE_i + MAR_u4, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_f + MAR_u4, MaskedArray[np.floating]) +assert_type(AR_LIKE_c + MAR_u4, MaskedArray[np.complexfloating]) +assert_type(AR_LIKE_td64 + MAR_u4, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_dt64 + MAR_u4, MaskedArray[np.datetime64]) +assert_type(AR_LIKE_o + MAR_u4, Any) + +assert_type(MAR_i8 + AR_LIKE_b, MaskedArray[np.int64]) +assert_type(MAR_i8 + AR_LIKE_u, MaskedArray[np.signedinteger]) +assert_type(MAR_i8 + AR_LIKE_i, MaskedArray[np.signedinteger]) +assert_type(MAR_i8 + AR_LIKE_f, MaskedArray[np.floating]) +assert_type(MAR_i8 + AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_i8 + AR_LIKE_td64, MaskedArray[np.timedelta64]) +assert_type(MAR_i8 + AR_LIKE_o, Any) + +assert_type(AR_LIKE_b + MAR_i8, MaskedArray[np.int64]) +assert_type(AR_LIKE_u + MAR_i8, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_i + MAR_i8, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_f + MAR_i8, MaskedArray[np.floating]) +assert_type(AR_LIKE_c + MAR_i8, MaskedArray[np.complexfloating]) +assert_type(AR_LIKE_td64 + MAR_i8, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_dt64 + MAR_i8, MaskedArray[np.datetime64]) +assert_type(AR_LIKE_o + MAR_i8, Any) + +assert_type(MAR_f8 + AR_LIKE_b, MaskedArray[np.float64]) +assert_type(MAR_f8 + AR_LIKE_u, MaskedArray[np.float64]) +assert_type(MAR_f8 + AR_LIKE_i, MaskedArray[np.float64]) +assert_type(MAR_f8 + AR_LIKE_f, MaskedArray[np.float64]) +assert_type(MAR_f8 + AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_f8 + AR_LIKE_o, Any) + +assert_type(AR_LIKE_b + MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_u + MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_i + MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_f + MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_c + MAR_f8, MaskedArray[np.complexfloating]) +assert_type(AR_LIKE_o + MAR_f8, Any) + +assert_type(MAR_c16 + AR_LIKE_b, MaskedArray[np.complex128]) +assert_type(MAR_c16 + AR_LIKE_u, MaskedArray[np.complex128]) +assert_type(MAR_c16 + AR_LIKE_i, MaskedArray[np.complex128]) +assert_type(MAR_c16 + AR_LIKE_f, MaskedArray[np.complex128]) +assert_type(MAR_c16 + AR_LIKE_c, MaskedArray[np.complex128]) +assert_type(MAR_c16 + AR_LIKE_o, Any) + +assert_type(AR_LIKE_b + MAR_c16, MaskedArray[np.complex128]) +assert_type(AR_LIKE_u + MAR_c16, MaskedArray[np.complex128]) +assert_type(AR_LIKE_i + MAR_c16, MaskedArray[np.complex128]) +assert_type(AR_LIKE_f + MAR_c16, MaskedArray[np.complex128]) +assert_type(AR_LIKE_c + MAR_c16, MaskedArray[np.complex128]) +assert_type(AR_LIKE_o + MAR_c16, Any) + +assert_type(MAR_td64 + AR_LIKE_b, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 + AR_LIKE_u, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 + AR_LIKE_i, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 + AR_LIKE_td64, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 + AR_LIKE_o, Any) + +assert_type(AR_LIKE_b + MAR_td64, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_u + MAR_td64, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_i + MAR_td64, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_td64 + MAR_td64, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_dt64 + MAR_td64, MaskedArray[np.datetime64]) +assert_type(AR_LIKE_o + MAR_td64, Any) + +assert_type(MAR_dt64 + AR_LIKE_b, MaskedArray[np.datetime64]) +assert_type(MAR_dt64 + AR_LIKE_u, MaskedArray[np.datetime64]) +assert_type(MAR_dt64 + AR_LIKE_i, MaskedArray[np.datetime64]) +assert_type(MAR_dt64 + AR_LIKE_td64, MaskedArray[np.datetime64]) +assert_type(MAR_dt64 + AR_LIKE_o, Any) + +assert_type(AR_LIKE_o + MAR_dt64, Any) + +assert_type(MAR_o + AR_LIKE_b, Any) +assert_type(MAR_o + AR_LIKE_u, Any) +assert_type(MAR_o + AR_LIKE_i, Any) +assert_type(MAR_o + AR_LIKE_f, Any) +assert_type(MAR_o + AR_LIKE_c, Any) +assert_type(MAR_o + AR_LIKE_td64, Any) +assert_type(MAR_o + AR_LIKE_dt64, Any) +assert_type(MAR_o + AR_LIKE_o, Any) + +assert_type(AR_LIKE_b + MAR_o, Any) +assert_type(AR_LIKE_u + MAR_o, Any) +assert_type(AR_LIKE_i + MAR_o, Any) +assert_type(AR_LIKE_f + MAR_o, Any) +assert_type(AR_LIKE_c + MAR_o, Any) +assert_type(AR_LIKE_td64 + MAR_o, Any) +assert_type(AR_LIKE_dt64 + MAR_o, Any) +assert_type(AR_LIKE_o + MAR_o, Any) + +# Masked Array subtraction +# Keep in sync with numpy/typing/tests/data/reveal/arithmetic.pyi + +assert_type(MAR_number - AR_number, MaskedArray[np.number]) + +assert_type(MAR_b - AR_LIKE_u, MaskedArray[np.uint32]) +assert_type(MAR_b - AR_LIKE_i, MaskedArray[np.signedinteger]) +assert_type(MAR_b - AR_LIKE_f, MaskedArray[np.floating]) +assert_type(MAR_b - AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_b - AR_LIKE_td64, MaskedArray[np.timedelta64]) +assert_type(MAR_b - AR_LIKE_o, Any) + +assert_type(AR_LIKE_u - MAR_b, MaskedArray[np.uint32]) +assert_type(AR_LIKE_i - MAR_b, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_f - MAR_b, MaskedArray[np.floating]) +assert_type(AR_LIKE_c - MAR_b, MaskedArray[np.complexfloating]) +assert_type(AR_LIKE_td64 - MAR_b, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_dt64 - MAR_b, MaskedArray[np.datetime64]) +assert_type(AR_LIKE_o - MAR_b, Any) + +assert_type(MAR_u4 - AR_LIKE_b, MaskedArray[np.uint32]) +assert_type(MAR_u4 - AR_LIKE_u, MaskedArray[np.unsignedinteger]) +assert_type(MAR_u4 - AR_LIKE_i, MaskedArray[np.signedinteger]) +assert_type(MAR_u4 - AR_LIKE_f, MaskedArray[np.floating]) +assert_type(MAR_u4 - AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_u4 - AR_LIKE_td64, MaskedArray[np.timedelta64]) +assert_type(MAR_u4 - AR_LIKE_o, Any) + +assert_type(AR_LIKE_b - MAR_u4, MaskedArray[np.uint32]) +assert_type(AR_LIKE_u - MAR_u4, MaskedArray[np.unsignedinteger]) +assert_type(AR_LIKE_i - MAR_u4, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_f - MAR_u4, MaskedArray[np.floating]) +assert_type(AR_LIKE_c - MAR_u4, MaskedArray[np.complexfloating]) +assert_type(AR_LIKE_td64 - MAR_u4, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_dt64 - MAR_u4, MaskedArray[np.datetime64]) +assert_type(AR_LIKE_o - MAR_u4, Any) + +assert_type(MAR_i8 - AR_LIKE_b, MaskedArray[np.int64]) +assert_type(MAR_i8 - AR_LIKE_u, MaskedArray[np.signedinteger]) +assert_type(MAR_i8 - AR_LIKE_i, MaskedArray[np.signedinteger]) +assert_type(MAR_i8 - AR_LIKE_f, MaskedArray[np.floating]) +assert_type(MAR_i8 - AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_i8 - AR_LIKE_td64, MaskedArray[np.timedelta64]) +assert_type(MAR_i8 - AR_LIKE_o, Any) + +assert_type(AR_LIKE_b - MAR_i8, MaskedArray[np.int64]) +assert_type(AR_LIKE_u - MAR_i8, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_i - MAR_i8, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_f - MAR_i8, MaskedArray[np.floating]) +assert_type(AR_LIKE_c - MAR_i8, MaskedArray[np.complexfloating]) +assert_type(AR_LIKE_td64 - MAR_i8, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_dt64 - MAR_i8, MaskedArray[np.datetime64]) +assert_type(AR_LIKE_o - MAR_i8, Any) + +assert_type(MAR_f8 - AR_LIKE_b, MaskedArray[np.float64]) +assert_type(MAR_f8 - AR_LIKE_u, MaskedArray[np.float64]) +assert_type(MAR_f8 - AR_LIKE_i, MaskedArray[np.float64]) +assert_type(MAR_f8 - AR_LIKE_f, MaskedArray[np.float64]) +assert_type(MAR_f8 - AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_f8 - AR_LIKE_o, Any) + +assert_type(AR_LIKE_b - MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_u - MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_i - MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_f - MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_c - MAR_f8, MaskedArray[np.complexfloating]) +assert_type(AR_LIKE_o - MAR_f8, Any) + +assert_type(MAR_c16 - AR_LIKE_b, MaskedArray[np.complex128]) +assert_type(MAR_c16 - AR_LIKE_u, MaskedArray[np.complex128]) +assert_type(MAR_c16 - AR_LIKE_i, MaskedArray[np.complex128]) +assert_type(MAR_c16 - AR_LIKE_f, MaskedArray[np.complex128]) +assert_type(MAR_c16 - AR_LIKE_c, MaskedArray[np.complex128]) +assert_type(MAR_c16 - AR_LIKE_o, Any) + +assert_type(AR_LIKE_b - MAR_c16, MaskedArray[np.complex128]) +assert_type(AR_LIKE_u - MAR_c16, MaskedArray[np.complex128]) +assert_type(AR_LIKE_i - MAR_c16, MaskedArray[np.complex128]) +assert_type(AR_LIKE_f - MAR_c16, MaskedArray[np.complex128]) +assert_type(AR_LIKE_c - MAR_c16, MaskedArray[np.complex128]) +assert_type(AR_LIKE_o - MAR_c16, Any) + +assert_type(MAR_td64 - AR_LIKE_b, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 - AR_LIKE_u, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 - AR_LIKE_i, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 - AR_LIKE_td64, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 - AR_LIKE_o, Any) + +assert_type(AR_LIKE_b - MAR_td64, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_u - MAR_td64, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_i - MAR_td64, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_td64 - MAR_td64, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_dt64 - MAR_td64, MaskedArray[np.datetime64]) +assert_type(AR_LIKE_o - MAR_td64, Any) + +assert_type(MAR_dt64 - AR_LIKE_b, MaskedArray[np.datetime64]) +assert_type(MAR_dt64 - AR_LIKE_u, MaskedArray[np.datetime64]) +assert_type(MAR_dt64 - AR_LIKE_i, MaskedArray[np.datetime64]) +assert_type(MAR_dt64 - AR_LIKE_td64, MaskedArray[np.datetime64]) +assert_type(MAR_dt64 - AR_LIKE_dt64, MaskedArray[np.timedelta64]) +assert_type(MAR_dt64 - AR_LIKE_o, Any) + +assert_type(AR_LIKE_dt64 - MAR_dt64, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_o - MAR_dt64, Any) + +assert_type(MAR_o - AR_LIKE_b, Any) +assert_type(MAR_o - AR_LIKE_u, Any) +assert_type(MAR_o - AR_LIKE_i, Any) +assert_type(MAR_o - AR_LIKE_f, Any) +assert_type(MAR_o - AR_LIKE_c, Any) +assert_type(MAR_o - AR_LIKE_td64, Any) +assert_type(MAR_o - AR_LIKE_dt64, Any) +assert_type(MAR_o - AR_LIKE_o, Any) + +assert_type(AR_LIKE_b - MAR_o, Any) +assert_type(AR_LIKE_u - MAR_o, Any) +assert_type(AR_LIKE_i - MAR_o, Any) +assert_type(AR_LIKE_f - MAR_o, Any) +assert_type(AR_LIKE_c - MAR_o, Any) +assert_type(AR_LIKE_td64 - MAR_o, Any) +assert_type(AR_LIKE_dt64 - MAR_o, Any) +assert_type(AR_LIKE_o - MAR_o, Any) + +# Masked Array multiplication + +assert_type(MAR_b * AR_LIKE_u, MaskedArray[np.uint32]) +assert_type(MAR_b * AR_LIKE_i, MaskedArray[np.signedinteger]) +assert_type(MAR_b * AR_LIKE_f, MaskedArray[np.floating]) +assert_type(MAR_b * AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_b * AR_LIKE_td64, MaskedArray[np.timedelta64]) +assert_type(MAR_b * AR_LIKE_o, Any) + +# Ignore due to https://github.com/python/mypy/issues/19341 +assert_type(AR_LIKE_u * MAR_b, MaskedArray[np.uint32]) # type: ignore[assert-type] +assert_type(AR_LIKE_i * MAR_b, MaskedArray[np.signedinteger]) # type: ignore[assert-type] +assert_type(AR_LIKE_f * MAR_b, MaskedArray[np.floating]) # type: ignore[assert-type] +assert_type(AR_LIKE_c * MAR_b, MaskedArray[np.complexfloating]) # type: ignore[assert-type] +assert_type(AR_LIKE_td64 * MAR_b, MaskedArray[np.timedelta64]) # type: ignore[assert-type] +assert_type(AR_LIKE_o * MAR_b, Any) # type: ignore[assert-type] + +assert_type(MAR_u4 * AR_LIKE_b, MaskedArray[np.uint32]) +assert_type(MAR_u4 * AR_LIKE_u, MaskedArray[np.unsignedinteger]) +assert_type(MAR_u4 * AR_LIKE_i, MaskedArray[np.signedinteger]) +assert_type(MAR_u4 * AR_LIKE_f, MaskedArray[np.floating]) +assert_type(MAR_u4 * AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_u4 * AR_LIKE_td64, MaskedArray[np.timedelta64]) +assert_type(MAR_u4 * AR_LIKE_o, Any) + +assert_type(MAR_i8 * AR_LIKE_b, MaskedArray[np.int64]) +assert_type(MAR_i8 * AR_LIKE_u, MaskedArray[np.signedinteger]) +assert_type(MAR_i8 * AR_LIKE_i, MaskedArray[np.signedinteger]) +assert_type(MAR_i8 * AR_LIKE_f, MaskedArray[np.floating]) +assert_type(MAR_i8 * AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_i8 * AR_LIKE_td64, MaskedArray[np.timedelta64]) +assert_type(MAR_i8 * AR_LIKE_o, Any) + +assert_type(MAR_f8 * AR_LIKE_b, MaskedArray[np.float64]) +assert_type(MAR_f8 * AR_LIKE_u, MaskedArray[np.float64]) +assert_type(MAR_f8 * AR_LIKE_i, MaskedArray[np.float64]) +assert_type(MAR_f8 * AR_LIKE_f, MaskedArray[np.float64]) +assert_type(MAR_f8 * AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_f8 * AR_LIKE_o, Any) + +# Ignore due to https://github.com/python/mypy/issues/19341 +assert_type(AR_LIKE_b * MAR_f8, MaskedArray[np.float64]) # type: ignore[assert-type] +assert_type(AR_LIKE_u * MAR_f8, MaskedArray[np.float64]) # type: ignore[assert-type] +assert_type(AR_LIKE_i * MAR_f8, MaskedArray[np.float64]) # type: ignore[assert-type] +assert_type(AR_LIKE_f * MAR_f8, MaskedArray[np.float64]) # type: ignore[assert-type] +assert_type(AR_LIKE_c * MAR_f8, MaskedArray[np.complexfloating]) # type: ignore[assert-type] +assert_type(AR_LIKE_o * MAR_f8, Any) # type: ignore[assert-type] + +assert_type(MAR_c16 * AR_LIKE_b, MaskedArray[np.complex128]) +assert_type(MAR_c16 * AR_LIKE_u, MaskedArray[np.complex128]) +assert_type(MAR_c16 * AR_LIKE_i, MaskedArray[np.complex128]) +assert_type(MAR_c16 * AR_LIKE_f, MaskedArray[np.complex128]) +assert_type(MAR_c16 * AR_LIKE_c, MaskedArray[np.complex128]) +assert_type(MAR_c16 * AR_LIKE_o, Any) + +# Ignore due to https://github.com/python/mypy/issues/19341 +assert_type(AR_LIKE_b * MAR_c16, MaskedArray[np.complex128]) # type: ignore[assert-type] +assert_type(AR_LIKE_u * MAR_c16, MaskedArray[np.complex128]) # type: ignore[assert-type] +assert_type(AR_LIKE_i * MAR_c16, MaskedArray[np.complex128]) # type: ignore[assert-type] +assert_type(AR_LIKE_f * MAR_c16, MaskedArray[np.complex128]) # type: ignore[assert-type] +assert_type(AR_LIKE_c * MAR_c16, MaskedArray[np.complex128]) # type: ignore[assert-type] +assert_type(AR_LIKE_o * MAR_c16, Any) # type: ignore[assert-type] + +assert_type(MAR_td64 * AR_LIKE_b, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 * AR_LIKE_u, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 * AR_LIKE_i, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 * AR_LIKE_o, Any) + +# Ignore due to https://github.com/python/mypy/issues/19341 +assert_type(AR_LIKE_b * MAR_td64, MaskedArray[np.timedelta64]) # type: ignore[assert-type] +assert_type(AR_LIKE_u * MAR_td64, MaskedArray[np.timedelta64]) # type: ignore[assert-type] +assert_type(AR_LIKE_i * MAR_td64, MaskedArray[np.timedelta64]) # type: ignore[assert-type] +assert_type(AR_LIKE_td64 * MAR_td64, MaskedArray[np.timedelta64]) # type: ignore[assert-type] +assert_type(AR_LIKE_dt64 * MAR_td64, MaskedArray[np.datetime64]) # type: ignore[assert-type] +assert_type(AR_LIKE_o * MAR_td64, Any) # type: ignore[assert-type] + +assert_type(AR_LIKE_o * MAR_dt64, Any) # type: ignore[assert-type] + +assert_type(MAR_o * AR_LIKE_b, Any) +assert_type(MAR_o * AR_LIKE_u, Any) +assert_type(MAR_o * AR_LIKE_i, Any) +assert_type(MAR_o * AR_LIKE_f, Any) +assert_type(MAR_o * AR_LIKE_c, Any) +assert_type(MAR_o * AR_LIKE_td64, Any) +assert_type(MAR_o * AR_LIKE_dt64, Any) +assert_type(MAR_o * AR_LIKE_o, Any) + +# Ignore due to https://github.com/python/mypy/issues/19341 +assert_type(AR_LIKE_b * MAR_o, Any) # type: ignore[assert-type] +assert_type(AR_LIKE_u * MAR_o, Any) # type: ignore[assert-type] +assert_type(AR_LIKE_i * MAR_o, Any) # type: ignore[assert-type] +assert_type(AR_LIKE_f * MAR_o, Any) # type: ignore[assert-type] +assert_type(AR_LIKE_c * MAR_o, Any) # type: ignore[assert-type] +assert_type(AR_LIKE_td64 * MAR_o, Any) # type: ignore[assert-type] +assert_type(AR_LIKE_dt64 * MAR_o, Any) # type: ignore[assert-type] +assert_type(AR_LIKE_o * MAR_o, Any) # type: ignore[assert-type] + +assert_type(MAR_f8.sum(), Any) +assert_type(MAR_f8.sum(axis=0), Any) +assert_type(MAR_f8.sum(keepdims=True), Any) +assert_type(MAR_f8.sum(out=MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_f8.std(), Any) +assert_type(MAR_f8.std(axis=0), Any) +assert_type(MAR_f8.std(keepdims=True, mean=0.), Any) +assert_type(MAR_f8.std(out=MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_f8.var(), Any) +assert_type(MAR_f8.var(axis=0), Any) +assert_type(MAR_f8.var(keepdims=True, mean=0.), Any) +assert_type(MAR_f8.var(out=MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_f8.mean(), Any) +assert_type(MAR_f8.mean(axis=0), Any) +assert_type(MAR_f8.mean(keepdims=True), Any) +assert_type(MAR_f8.mean(out=MAR_subclass), MaskedArraySubclassC) + +assert_type(MAR_f8.prod(), Any) +assert_type(MAR_f8.prod(axis=0), Any) +assert_type(MAR_f8.prod(keepdims=True), Any) +assert_type(MAR_f8.prod(out=MAR_subclass), MaskedArraySubclassC) + +# MaskedArray "true" division + +assert_type(MAR_f8 / b, MaskedArray[np.float64]) +assert_type(MAR_f8 / i, MaskedArray[np.float64]) +assert_type(MAR_f8 / f, MaskedArray[np.float64]) + +assert_type(b / MAR_f8, MaskedArray[np.float64]) +assert_type(i / MAR_f8, MaskedArray[np.float64]) +assert_type(f / MAR_f8, MaskedArray[np.float64]) + +assert_type(MAR_b / AR_LIKE_b, MaskedArray[np.float64]) +assert_type(MAR_b / AR_LIKE_u, MaskedArray[np.float64]) +assert_type(MAR_b / AR_LIKE_i, MaskedArray[np.float64]) +assert_type(MAR_b / AR_LIKE_f, MaskedArray[np.float64]) +assert_type(MAR_b / AR_LIKE_o, Any) + +assert_type(AR_LIKE_b / MAR_b, MaskedArray[np.float64]) +assert_type(AR_LIKE_u / MAR_b, MaskedArray[np.float64]) +assert_type(AR_LIKE_i / MAR_b, MaskedArray[np.float64]) +assert_type(AR_LIKE_f / MAR_b, MaskedArray[np.float64]) +assert_type(AR_LIKE_o / MAR_b, Any) + +assert_type(MAR_u4 / AR_LIKE_b, MaskedArray[np.float64]) +assert_type(MAR_u4 / AR_LIKE_u, MaskedArray[np.float64]) +assert_type(MAR_u4 / AR_LIKE_i, MaskedArray[np.float64]) +assert_type(MAR_u4 / AR_LIKE_f, MaskedArray[np.float64]) +assert_type(MAR_u4 / AR_LIKE_o, Any) + +assert_type(AR_LIKE_b / MAR_u4, MaskedArray[np.float64]) +assert_type(AR_LIKE_u / MAR_u4, MaskedArray[np.float64]) +assert_type(AR_LIKE_i / MAR_u4, MaskedArray[np.float64]) +assert_type(AR_LIKE_f / MAR_u4, MaskedArray[np.float64]) +assert_type(AR_LIKE_td64 / MAR_u4, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_o / MAR_u4, Any) + +assert_type(MAR_i8 / AR_LIKE_b, MaskedArray[np.float64]) +assert_type(MAR_i8 / AR_LIKE_u, MaskedArray[np.float64]) +assert_type(MAR_i8 / AR_LIKE_i, MaskedArray[np.float64]) +assert_type(MAR_i8 / AR_LIKE_f, MaskedArray[np.float64]) +assert_type(MAR_i8 / AR_LIKE_o, Any) + +assert_type(AR_LIKE_b / MAR_i8, MaskedArray[np.float64]) +assert_type(AR_LIKE_u / MAR_i8, MaskedArray[np.float64]) +assert_type(AR_LIKE_i / MAR_i8, MaskedArray[np.float64]) +assert_type(AR_LIKE_f / MAR_i8, MaskedArray[np.float64]) +assert_type(AR_LIKE_td64 / MAR_i8, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_o / MAR_i8, Any) + +assert_type(MAR_f8 / AR_LIKE_b, MaskedArray[np.float64]) +assert_type(MAR_f8 / AR_LIKE_u, MaskedArray[np.float64]) +assert_type(MAR_f8 / AR_LIKE_i, MaskedArray[np.float64]) +assert_type(MAR_f8 / AR_LIKE_f, MaskedArray[np.float64]) +assert_type(MAR_f8 / AR_LIKE_o, Any) + +assert_type(AR_LIKE_b / MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_u / MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_i / MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_f / MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_td64 / MAR_f8, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_o / MAR_f8, Any) + +assert_type(MAR_td64 / AR_LIKE_u, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 / AR_LIKE_i, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 / AR_LIKE_f, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 / AR_LIKE_td64, MaskedArray[np.float64]) +assert_type(MAR_td64 / AR_LIKE_o, Any) + +assert_type(AR_LIKE_td64 / MAR_td64, MaskedArray[np.float64]) +assert_type(AR_LIKE_o / MAR_td64, Any) + +assert_type(MAR_o / AR_LIKE_b, Any) +assert_type(MAR_o / AR_LIKE_u, Any) +assert_type(MAR_o / AR_LIKE_i, Any) +assert_type(MAR_o / AR_LIKE_f, Any) +assert_type(MAR_o / AR_LIKE_td64, Any) +assert_type(MAR_o / AR_LIKE_dt64, Any) +assert_type(MAR_o / AR_LIKE_o, Any) + +assert_type(AR_LIKE_b / MAR_o, Any) +assert_type(AR_LIKE_u / MAR_o, Any) +assert_type(AR_LIKE_i / MAR_o, Any) +assert_type(AR_LIKE_f / MAR_o, Any) +assert_type(AR_LIKE_td64 / MAR_o, Any) +assert_type(AR_LIKE_dt64 / MAR_o, Any) +assert_type(AR_LIKE_o / MAR_o, Any) + +# MaskedArray floor division + +assert_type(MAR_b // AR_LIKE_b, MaskedArray[np.int8]) +assert_type(MAR_b // AR_LIKE_u, MaskedArray[np.uint32]) +assert_type(MAR_b // AR_LIKE_i, MaskedArray[np.signedinteger]) +assert_type(MAR_b // AR_LIKE_f, MaskedArray[np.floating]) +assert_type(MAR_b // AR_LIKE_o, Any) + +assert_type(AR_LIKE_b // MAR_b, MaskedArray[np.int8]) +assert_type(AR_LIKE_u // MAR_b, MaskedArray[np.uint32]) +assert_type(AR_LIKE_i // MAR_b, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_f // MAR_b, MaskedArray[np.floating]) +assert_type(AR_LIKE_o // MAR_b, Any) + +assert_type(MAR_u4 // AR_LIKE_b, MaskedArray[np.uint32]) +assert_type(MAR_u4 // AR_LIKE_u, MaskedArray[np.unsignedinteger]) +assert_type(MAR_u4 // AR_LIKE_i, MaskedArray[np.signedinteger]) +assert_type(MAR_u4 // AR_LIKE_f, MaskedArray[np.floating]) +assert_type(MAR_u4 // AR_LIKE_o, Any) + +assert_type(AR_LIKE_b // MAR_u4, MaskedArray[np.uint32]) +assert_type(AR_LIKE_u // MAR_u4, MaskedArray[np.unsignedinteger]) +assert_type(AR_LIKE_i // MAR_u4, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_f // MAR_u4, MaskedArray[np.floating]) +assert_type(AR_LIKE_td64 // MAR_u4, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_o // MAR_u4, Any) + +assert_type(MAR_i8 // AR_LIKE_b, MaskedArray[np.int64]) +assert_type(MAR_i8 // AR_LIKE_u, MaskedArray[np.signedinteger]) +assert_type(MAR_i8 // AR_LIKE_i, MaskedArray[np.signedinteger]) +assert_type(MAR_i8 // AR_LIKE_f, MaskedArray[np.floating]) +assert_type(MAR_i8 // AR_LIKE_o, Any) + +assert_type(AR_LIKE_b // MAR_i8, MaskedArray[np.int64]) +assert_type(AR_LIKE_u // MAR_i8, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_i // MAR_i8, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_f // MAR_i8, MaskedArray[np.floating]) +assert_type(AR_LIKE_td64 // MAR_i8, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_o // MAR_i8, Any) + +assert_type(MAR_f8 // AR_LIKE_b, MaskedArray[np.float64]) +assert_type(MAR_f8 // AR_LIKE_u, MaskedArray[np.float64]) +assert_type(MAR_f8 // AR_LIKE_i, MaskedArray[np.float64]) +assert_type(MAR_f8 // AR_LIKE_f, MaskedArray[np.float64]) +assert_type(MAR_f8 // AR_LIKE_o, Any) + +assert_type(AR_LIKE_b // MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_u // MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_i // MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_f // MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_td64 // MAR_f8, MaskedArray[np.timedelta64]) +assert_type(AR_LIKE_o // MAR_f8, Any) + +assert_type(MAR_td64 // AR_LIKE_u, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 // AR_LIKE_i, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 // AR_LIKE_f, MaskedArray[np.timedelta64]) +assert_type(MAR_td64 // AR_LIKE_td64, MaskedArray[np.int64]) +assert_type(MAR_td64 // AR_LIKE_o, Any) + +assert_type(AR_LIKE_td64 // MAR_td64, MaskedArray[np.int64]) +assert_type(AR_LIKE_o // MAR_td64, Any) + +assert_type(MAR_o // AR_LIKE_b, Any) +assert_type(MAR_o // AR_LIKE_u, Any) +assert_type(MAR_o // AR_LIKE_i, Any) +assert_type(MAR_o // AR_LIKE_f, Any) +assert_type(MAR_o // AR_LIKE_td64, Any) +assert_type(MAR_o // AR_LIKE_dt64, Any) +assert_type(MAR_o // AR_LIKE_o, Any) + +assert_type(AR_LIKE_b // MAR_o, Any) +assert_type(AR_LIKE_u // MAR_o, Any) +assert_type(AR_LIKE_i // MAR_o, Any) +assert_type(AR_LIKE_f // MAR_o, Any) +assert_type(AR_LIKE_td64 // MAR_o, Any) +assert_type(AR_LIKE_dt64 // MAR_o, Any) +assert_type(AR_LIKE_o // MAR_o, Any) + +# Masked Array power + +assert_type(MAR_b ** AR_LIKE_u, MaskedArray[np.uint32]) +assert_type(MAR_b ** AR_LIKE_i, MaskedArray[np.signedinteger]) +assert_type(MAR_b ** AR_LIKE_f, MaskedArray[np.floating]) +assert_type(MAR_b ** AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_b ** AR_LIKE_o, Any) + +assert_type(AR_LIKE_u ** MAR_b, MaskedArray[np.uint32]) +assert_type(AR_LIKE_i ** MAR_b, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_f ** MAR_b, MaskedArray[np.floating]) +assert_type(AR_LIKE_c ** MAR_b, MaskedArray[np.complexfloating]) +assert_type(AR_LIKE_o ** MAR_b, Any) + +assert_type(MAR_u4 ** AR_LIKE_b, MaskedArray[np.uint32]) +assert_type(MAR_u4 ** AR_LIKE_u, MaskedArray[np.unsignedinteger]) +assert_type(MAR_u4 ** AR_LIKE_i, MaskedArray[np.signedinteger]) +assert_type(MAR_u4 ** AR_LIKE_f, MaskedArray[np.floating]) +assert_type(MAR_u4 ** AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_u4 ** AR_LIKE_o, Any) + +assert_type(AR_LIKE_b ** MAR_u4, MaskedArray[np.uint32]) +assert_type(AR_LIKE_u ** MAR_u4, MaskedArray[np.unsignedinteger]) +assert_type(AR_LIKE_i ** MAR_u4, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_f ** MAR_u4, MaskedArray[np.floating]) +assert_type(AR_LIKE_c ** MAR_u4, MaskedArray[np.complexfloating]) +assert_type(AR_LIKE_o ** MAR_u4, Any) + +assert_type(MAR_i8 ** AR_LIKE_b, MaskedArray[np.int64]) +assert_type(MAR_i8 ** AR_LIKE_u, MaskedArray[np.signedinteger]) +assert_type(MAR_i8 ** AR_LIKE_i, MaskedArray[np.signedinteger]) +assert_type(MAR_i8 ** AR_LIKE_f, MaskedArray[np.floating]) +assert_type(MAR_i8 ** AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_i8 ** AR_LIKE_o, Any) +assert_type(MAR_i8 ** AR_LIKE_b, MaskedArray[np.int64]) + +assert_type(AR_LIKE_u ** MAR_i8, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_i ** MAR_i8, MaskedArray[np.signedinteger]) +assert_type(AR_LIKE_f ** MAR_i8, MaskedArray[np.floating]) +assert_type(AR_LIKE_c ** MAR_i8, MaskedArray[np.complexfloating]) +assert_type(AR_LIKE_o ** MAR_i8, Any) + +assert_type(MAR_f8 ** AR_LIKE_b, MaskedArray[np.float64]) +assert_type(MAR_f8 ** AR_LIKE_u, MaskedArray[np.float64]) +assert_type(MAR_f8 ** AR_LIKE_i, MaskedArray[np.float64]) +assert_type(MAR_f8 ** AR_LIKE_f, MaskedArray[np.float64]) +assert_type(MAR_f8 ** AR_LIKE_c, MaskedArray[np.complexfloating]) +assert_type(MAR_f8 ** AR_LIKE_o, Any) + +assert_type(AR_LIKE_b ** MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_u ** MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_i ** MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_f ** MAR_f8, MaskedArray[np.float64]) +assert_type(AR_LIKE_c ** MAR_f8, MaskedArray[np.complexfloating]) +assert_type(AR_LIKE_o ** MAR_f8, Any) + +assert_type(MAR_c16 ** AR_LIKE_b, MaskedArray[np.complex128]) +assert_type(MAR_c16 ** AR_LIKE_u, MaskedArray[np.complex128]) +assert_type(MAR_c16 ** AR_LIKE_i, MaskedArray[np.complex128]) +assert_type(MAR_c16 ** AR_LIKE_f, MaskedArray[np.complex128]) +assert_type(MAR_c16 ** AR_LIKE_c, MaskedArray[np.complex128]) +assert_type(MAR_c16 ** AR_LIKE_o, Any) + +assert_type(AR_LIKE_b ** MAR_c16, MaskedArray[np.complex128]) +assert_type(AR_LIKE_u ** MAR_c16, MaskedArray[np.complex128]) +assert_type(AR_LIKE_i ** MAR_c16, MaskedArray[np.complex128]) +assert_type(AR_LIKE_f ** MAR_c16, MaskedArray[np.complex128]) +assert_type(AR_LIKE_c ** MAR_c16, MaskedArray[np.complex128]) +assert_type(AR_LIKE_o ** MAR_c16, Any) + +assert_type(MAR_o ** AR_LIKE_b, Any) +assert_type(MAR_o ** AR_LIKE_u, Any) +assert_type(MAR_o ** AR_LIKE_i, Any) +assert_type(MAR_o ** AR_LIKE_f, Any) +assert_type(MAR_o ** AR_LIKE_c, Any) +assert_type(MAR_o ** AR_LIKE_o, Any) + +assert_type(AR_LIKE_b ** MAR_o, Any) +assert_type(AR_LIKE_u ** MAR_o, Any) +assert_type(AR_LIKE_i ** MAR_o, Any) +assert_type(AR_LIKE_f ** MAR_o, Any) +assert_type(AR_LIKE_c ** MAR_o, Any) +assert_type(AR_LIKE_o ** MAR_o, Any) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/matrix.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/matrix.pyi new file mode 100644 index 0000000000000000000000000000000000000000..3a32b3d394f0da125da06a96327c23f60f5dc504 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/matrix.pyi @@ -0,0 +1,73 @@ +from typing import Any, TypeAlias, assert_type + +import numpy as np +import numpy.typing as npt + +_Shape2D: TypeAlias = tuple[int, int] + +mat: np.matrix[_Shape2D, np.dtype[np.int64]] +ar_f8: npt.NDArray[np.float64] +ar_ip: npt.NDArray[np.intp] + +assert_type(mat * 5, np.matrix) +assert_type(5 * mat, np.matrix) +mat *= 5 + +assert_type(mat**5, np.matrix) +mat **= 5 + +assert_type(mat.sum(), Any) +assert_type(mat.mean(), Any) +assert_type(mat.std(), Any) +assert_type(mat.var(), Any) +assert_type(mat.prod(), Any) +assert_type(mat.any(), np.bool) +assert_type(mat.all(), np.bool) +assert_type(mat.max(), np.int64) +assert_type(mat.min(), np.int64) +assert_type(mat.argmax(), np.intp) +assert_type(mat.argmin(), np.intp) +assert_type(mat.ptp(), np.int64) + +assert_type(mat.sum(axis=0), np.matrix) +assert_type(mat.mean(axis=0), np.matrix) +assert_type(mat.std(axis=0), np.matrix) +assert_type(mat.var(axis=0), np.matrix) +assert_type(mat.prod(axis=0), np.matrix) +assert_type(mat.any(axis=0), np.matrix[_Shape2D, np.dtype[np.bool]]) +assert_type(mat.all(axis=0), np.matrix[_Shape2D, np.dtype[np.bool]]) +assert_type(mat.max(axis=0), np.matrix[_Shape2D, np.dtype[np.int64]]) +assert_type(mat.min(axis=0), np.matrix[_Shape2D, np.dtype[np.int64]]) +assert_type(mat.argmax(axis=0), np.matrix[_Shape2D, np.dtype[np.intp]]) +assert_type(mat.argmin(axis=0), np.matrix[_Shape2D, np.dtype[np.intp]]) +assert_type(mat.ptp(axis=0), np.matrix[_Shape2D, np.dtype[np.int64]]) + +assert_type(mat.sum(out=ar_f8), npt.NDArray[np.float64]) +assert_type(mat.mean(out=ar_f8), npt.NDArray[np.float64]) +assert_type(mat.std(out=ar_f8), npt.NDArray[np.float64]) +assert_type(mat.var(out=ar_f8), npt.NDArray[np.float64]) +assert_type(mat.prod(out=ar_f8), npt.NDArray[np.float64]) +assert_type(mat.any(out=ar_f8), npt.NDArray[np.float64]) +assert_type(mat.all(out=ar_f8), npt.NDArray[np.float64]) +assert_type(mat.max(out=ar_f8), npt.NDArray[np.float64]) +assert_type(mat.min(out=ar_f8), npt.NDArray[np.float64]) +assert_type(mat.argmax(out=ar_ip), npt.NDArray[np.intp]) +assert_type(mat.argmin(out=ar_ip), npt.NDArray[np.intp]) +assert_type(mat.ptp(out=ar_f8), npt.NDArray[np.float64]) + +assert_type(mat.T, np.matrix[_Shape2D, np.dtype[np.int64]]) +assert_type(mat.I, np.matrix) +assert_type(mat.A, np.ndarray[_Shape2D, np.dtype[np.int64]]) +assert_type(mat.A1, npt.NDArray[np.int64]) +assert_type(mat.H, np.matrix[_Shape2D, np.dtype[np.int64]]) +assert_type(mat.getT(), np.matrix[_Shape2D, np.dtype[np.int64]]) +assert_type(mat.getI(), np.matrix) +assert_type(mat.getA(), np.ndarray[_Shape2D, np.dtype[np.int64]]) +assert_type(mat.getA1(), npt.NDArray[np.int64]) +assert_type(mat.getH(), np.matrix[_Shape2D, np.dtype[np.int64]]) + +assert_type(np.bmat(ar_f8), np.matrix) +assert_type(np.bmat([[0, 1, 2]]), np.matrix) +assert_type(np.bmat("mat"), np.matrix) + +assert_type(np.asmatrix(ar_f8, dtype=np.int64), np.matrix) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/memmap.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/memmap.pyi new file mode 100644 index 0000000000000000000000000000000000000000..f3e20ed2d5e7df74e3e2fa66d743430fece8cb62 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/memmap.pyi @@ -0,0 +1,19 @@ +from typing import Any, assert_type + +import numpy as np + +memmap_obj: np.memmap[Any, np.dtype[np.str_]] + +assert_type(np.memmap.__array_priority__, float) +assert_type(memmap_obj.__array_priority__, float) +assert_type(memmap_obj.filename, str | None) +assert_type(memmap_obj.offset, int) +assert_type(memmap_obj.mode, str) +assert_type(memmap_obj.flush(), None) + +assert_type(np.memmap("file.txt", offset=5), np.memmap[Any, np.dtype[np.uint8]]) +assert_type(np.memmap(b"file.txt", dtype=np.float64, shape=(10, 3)), np.memmap[Any, np.dtype[np.float64]]) +with open("file.txt", "rb") as f: + assert_type(np.memmap(f, dtype=float, order="K"), np.memmap[Any, np.dtype]) + +assert_type(memmap_obj.__array_finalize__(object()), None) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/mod.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/mod.pyi new file mode 100644 index 0000000000000000000000000000000000000000..ef07dc0c8c8aab9a6615f04a5903cf07be667548 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/mod.pyi @@ -0,0 +1,178 @@ +import datetime as dt +from typing import Literal as L, assert_type + +import numpy as np +import numpy.typing as npt + +f8: np.float64 +i8: np.int64 +u8: np.uint64 + +f4: np.float32 +i4: np.int32 +u4: np.uint32 + +m: np.timedelta64 +m_nat: np.timedelta64[None] +m_int0: np.timedelta64[L[0]] +m_int: np.timedelta64[int] +m_td: np.timedelta64[dt.timedelta] + +b_: np.bool + +b: bool +i: int +f: float + +AR_b: npt.NDArray[np.bool] +AR_m: npt.NDArray[np.timedelta64] + +# Time structures + +assert_type(m % m, np.timedelta64) +assert_type(m % m_nat, np.timedelta64[None]) +assert_type(m % m_int0, np.timedelta64[None]) +assert_type(m % m_int, np.timedelta64[int | None]) +assert_type(m_nat % m, np.timedelta64[None]) +assert_type(m_int % m_nat, np.timedelta64[None]) +assert_type(m_int % m_int0, np.timedelta64[None]) +assert_type(m_int % m_int, np.timedelta64[int | None]) +assert_type(m_int % m_td, np.timedelta64[int | None]) +assert_type(m_td % m_nat, np.timedelta64[None]) +assert_type(m_td % m_int0, np.timedelta64[None]) +assert_type(m_td % m_int, np.timedelta64[int | None]) +assert_type(m_td % m_td, np.timedelta64[dt.timedelta | None]) + +assert_type(AR_m % m, npt.NDArray[np.timedelta64]) +assert_type(m % AR_m, npt.NDArray[np.timedelta64]) + +assert_type(divmod(m, m), tuple[np.int64, np.timedelta64]) +assert_type(divmod(m, m_nat), tuple[np.int64, np.timedelta64[None]]) +assert_type(divmod(m, m_int0), tuple[np.int64, np.timedelta64[None]]) +# workarounds for https://github.com/microsoft/pyright/issues/9663 +assert_type(m.__divmod__(m_int), tuple[np.int64, np.timedelta64[int | None]]) +assert_type(divmod(m_nat, m), tuple[np.int64, np.timedelta64[None]]) +assert_type(divmod(m_int, m_nat), tuple[np.int64, np.timedelta64[None]]) +assert_type(divmod(m_int, m_int0), tuple[np.int64, np.timedelta64[None]]) +assert_type(divmod(m_int, m_int), tuple[np.int64, np.timedelta64[int | None]]) +assert_type(divmod(m_int, m_td), tuple[np.int64, np.timedelta64[int | None]]) +assert_type(divmod(m_td, m_nat), tuple[np.int64, np.timedelta64[None]]) +assert_type(divmod(m_td, m_int0), tuple[np.int64, np.timedelta64[None]]) +assert_type(divmod(m_td, m_int), tuple[np.int64, np.timedelta64[int | None]]) +assert_type(divmod(m_td, m_td), tuple[np.int64, np.timedelta64[dt.timedelta | None]]) + +assert_type(divmod(AR_m, m), tuple[npt.NDArray[np.int64], npt.NDArray[np.timedelta64]]) +assert_type(divmod(m, AR_m), tuple[npt.NDArray[np.int64], npt.NDArray[np.timedelta64]]) + +# Bool + +assert_type(b_ % b, np.int8) +assert_type(b_ % i, np.int_) +assert_type(b_ % f, np.float64) +assert_type(b_ % b_, np.int8) +assert_type(b_ % i8, np.int64) +assert_type(b_ % u8, np.uint64) +assert_type(b_ % f8, np.float64) +assert_type(b_ % AR_b, npt.NDArray[np.int8]) + +assert_type(divmod(b_, b), tuple[np.int8, np.int8]) +assert_type(divmod(b_, b_), tuple[np.int8, np.int8]) +# workarounds for https://github.com/microsoft/pyright/issues/9663 +assert_type(b_.__divmod__(i), tuple[np.int_, np.int_]) +assert_type(b_.__divmod__(f), tuple[np.float64, np.float64]) +assert_type(b_.__divmod__(i8), tuple[np.int64, np.int64]) +assert_type(b_.__divmod__(u8), tuple[np.uint64, np.uint64]) +assert_type(divmod(b_, f8), tuple[np.float64, np.float64]) +assert_type(divmod(b_, AR_b), tuple[npt.NDArray[np.int8], npt.NDArray[np.int8]]) + +assert_type(b % b_, np.int8) +assert_type(i % b_, np.int_) +assert_type(f % b_, np.float64) +assert_type(b_ % b_, np.int8) +assert_type(i8 % b_, np.int64) +assert_type(u8 % b_, np.uint64) +assert_type(f8 % b_, np.float64) +assert_type(AR_b % b_, npt.NDArray[np.int8]) + +assert_type(divmod(b, b_), tuple[np.int8, np.int8]) +assert_type(divmod(i, b_), tuple[np.int_, np.int_]) +assert_type(divmod(f, b_), tuple[np.float64, np.float64]) +assert_type(divmod(b_, b_), tuple[np.int8, np.int8]) +assert_type(divmod(i8, b_), tuple[np.int64, np.int64]) +assert_type(divmod(u8, b_), tuple[np.uint64, np.uint64]) +assert_type(divmod(f8, b_), tuple[np.float64, np.float64]) +assert_type(divmod(AR_b, b_), tuple[npt.NDArray[np.int8], npt.NDArray[np.int8]]) + +# int + +assert_type(i8 % b, np.int64) +assert_type(i8 % i8, np.int64) +assert_type(i8 % f, np.float64) +assert_type(i8 % f8, np.float64) +assert_type(i4 % i8, np.signedinteger) +assert_type(i4 % f8, np.float64) +assert_type(i4 % i4, np.int32) +assert_type(i4 % f4, np.floating) +assert_type(i8 % AR_b, npt.NDArray[np.int64]) + +assert_type(divmod(i8, b), tuple[np.int64, np.int64]) +assert_type(divmod(i8, i4), tuple[np.signedinteger, np.signedinteger]) +assert_type(divmod(i8, i8), tuple[np.int64, np.int64]) +# workarounds for https://github.com/microsoft/pyright/issues/9663 +assert_type(i8.__divmod__(f), tuple[np.float64, np.float64]) +assert_type(i8.__divmod__(f8), tuple[np.float64, np.float64]) +assert_type(divmod(i8, f4), tuple[np.floating, np.floating]) +assert_type(divmod(i4, i4), tuple[np.int32, np.int32]) +assert_type(divmod(i4, f4), tuple[np.floating, np.floating]) +assert_type(divmod(i8, AR_b), tuple[npt.NDArray[np.int64], npt.NDArray[np.int64]]) + +assert_type(b % i8, np.int64) +assert_type(f % i8, np.float64) +assert_type(i8 % i8, np.int64) +assert_type(f8 % i8, np.float64) +assert_type(i8 % i4, np.signedinteger) +assert_type(f8 % i4, np.float64) +assert_type(i4 % i4, np.int32) +assert_type(f4 % i4, np.floating) +assert_type(AR_b % i8, npt.NDArray[np.int64]) + +assert_type(divmod(b, i8), tuple[np.int64, np.int64]) +assert_type(divmod(f, i8), tuple[np.float64, np.float64]) +assert_type(divmod(i8, i8), tuple[np.int64, np.int64]) +assert_type(divmod(f8, i8), tuple[np.float64, np.float64]) +assert_type(divmod(i4, i8), tuple[np.signedinteger, np.signedinteger]) +assert_type(divmod(i4, i4), tuple[np.int32, np.int32]) +# workarounds for https://github.com/microsoft/pyright/issues/9663 +assert_type(f4.__divmod__(i8), tuple[np.floating, np.floating]) +assert_type(f4.__divmod__(i4), tuple[np.floating, np.floating]) +assert_type(AR_b.__divmod__(i8), tuple[npt.NDArray[np.int64], npt.NDArray[np.int64]]) + +# float + +assert_type(f8 % b, np.float64) +assert_type(f8 % f, np.float64) +assert_type(i8 % f4, np.floating) +assert_type(f4 % f4, np.float32) +assert_type(f8 % AR_b, npt.NDArray[np.float64]) + +assert_type(divmod(f8, b), tuple[np.float64, np.float64]) +assert_type(divmod(f8, f), tuple[np.float64, np.float64]) +assert_type(divmod(f8, f8), tuple[np.float64, np.float64]) +assert_type(divmod(f8, f4), tuple[np.float64, np.float64]) +assert_type(divmod(f4, f4), tuple[np.float32, np.float32]) +assert_type(divmod(f8, AR_b), tuple[npt.NDArray[np.float64], npt.NDArray[np.float64]]) + +assert_type(b % f8, np.float64) +assert_type(f % f8, np.float64) # pyright: ignore[reportAssertTypeFailure] # pyright incorrectly infers `builtins.float` +assert_type(f8 % f8, np.float64) +assert_type(f8 % f8, np.float64) +assert_type(f4 % f4, np.float32) +assert_type(AR_b % f8, npt.NDArray[np.float64]) + +assert_type(divmod(b, f8), tuple[np.float64, np.float64]) +assert_type(divmod(f8, f8), tuple[np.float64, np.float64]) +assert_type(divmod(f4, f4), tuple[np.float32, np.float32]) +# workarounds for https://github.com/microsoft/pyright/issues/9663 +assert_type(f8.__rdivmod__(f), tuple[np.float64, np.float64]) +assert_type(f8.__rdivmod__(f4), tuple[np.float64, np.float64]) +assert_type(AR_b.__divmod__(f8), tuple[npt.NDArray[np.float64], npt.NDArray[np.float64]]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/modules.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/modules.pyi new file mode 100644 index 0000000000000000000000000000000000000000..628fb500bfda11752336fa52fea5b81c259501ae --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/modules.pyi @@ -0,0 +1,51 @@ +import types +from typing import assert_type + +import numpy as np +from numpy import f2py + +assert_type(np, types.ModuleType) + +assert_type(np.char, types.ModuleType) +assert_type(np.ctypeslib, types.ModuleType) +assert_type(np.emath, types.ModuleType) +assert_type(np.fft, types.ModuleType) +assert_type(np.lib, types.ModuleType) +assert_type(np.linalg, types.ModuleType) +assert_type(np.ma, types.ModuleType) +assert_type(np.matrixlib, types.ModuleType) +assert_type(np.polynomial, types.ModuleType) +assert_type(np.random, types.ModuleType) +assert_type(np.rec, types.ModuleType) +assert_type(np.testing, types.ModuleType) +assert_type(np.version, types.ModuleType) +assert_type(np.exceptions, types.ModuleType) +assert_type(np.dtypes, types.ModuleType) + +assert_type(np.lib.format, types.ModuleType) +assert_type(np.lib.mixins, types.ModuleType) +assert_type(np.lib.scimath, types.ModuleType) +assert_type(np.lib.stride_tricks, types.ModuleType) +assert_type(np.ma.extras, types.ModuleType) +assert_type(np.polynomial.chebyshev, types.ModuleType) +assert_type(np.polynomial.hermite, types.ModuleType) +assert_type(np.polynomial.hermite_e, types.ModuleType) +assert_type(np.polynomial.laguerre, types.ModuleType) +assert_type(np.polynomial.legendre, types.ModuleType) +assert_type(np.polynomial.polynomial, types.ModuleType) + +assert_type(np.__path__, list[str]) +assert_type(np.__version__, str) +assert_type(np.test, np._pytesttester.PytestTester) +assert_type(np.test.module_name, str) + +assert_type(np.__all__, list[str]) +assert_type(np.char.__all__, list[str]) +assert_type(np.ctypeslib.__all__, list[str]) +assert_type(np.emath.__all__, list[str]) +assert_type(np.lib.__all__, list[str]) +assert_type(np.ma.__all__, list[str]) +assert_type(np.random.__all__, list[str]) +assert_type(np.rec.__all__, list[str]) +assert_type(np.testing.__all__, list[str]) +assert_type(f2py.__all__, list[str]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/multiarray.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/multiarray.pyi new file mode 100644 index 0000000000000000000000000000000000000000..424f60df27e7ce49d894415add02579f89dc69f9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/multiarray.pyi @@ -0,0 +1,197 @@ +import datetime as dt +from typing import Any, Literal, TypeVar, assert_type + +import numpy as np +import numpy.typing as npt + +_ScalarT_co = TypeVar("_ScalarT_co", bound=np.generic, covariant=True) + +class SubClass(npt.NDArray[_ScalarT_co]): ... + +subclass: SubClass[np.float64] + +AR_f8: npt.NDArray[np.float64] +AR_i8: npt.NDArray[np.int64] +AR_u1: npt.NDArray[np.uint8] +AR_m: npt.NDArray[np.timedelta64] +AR_M: npt.NDArray[np.datetime64] + +AR_LIKE_f: list[float] +AR_LIKE_i: list[int] + +m: np.timedelta64 +M: np.datetime64 + +b_f8 = np.broadcast(AR_f8) +b_i8_f8_f8 = np.broadcast(AR_i8, AR_f8, AR_f8) + +nditer_obj: np.nditer + +date_scalar: dt.date +date_seq: list[dt.date] +timedelta_seq: list[dt.timedelta] + +n1: Literal[1] +n2: Literal[2] +n3: Literal[3] + +f8: np.float64 + +def func11(a: int) -> bool: ... +def func21(a: int, b: int) -> int: ... +def func12(a: int) -> tuple[complex, bool]: ... + +assert_type(next(b_f8), tuple[Any, ...]) +assert_type(b_f8.reset(), None) +assert_type(b_f8.index, int) +assert_type(b_f8.iters, tuple[np.flatiter[Any], ...]) +assert_type(b_f8.nd, int) +assert_type(b_f8.ndim, int) +assert_type(b_f8.numiter, int) +assert_type(b_f8.shape, tuple[Any, ...]) +assert_type(b_f8.size, int) + +assert_type(next(b_i8_f8_f8), tuple[Any, ...]) +assert_type(b_i8_f8_f8.reset(), None) +assert_type(b_i8_f8_f8.index, int) +assert_type(b_i8_f8_f8.iters, tuple[np.flatiter[Any], ...]) +assert_type(b_i8_f8_f8.nd, int) +assert_type(b_i8_f8_f8.ndim, int) +assert_type(b_i8_f8_f8.numiter, int) +assert_type(b_i8_f8_f8.shape, tuple[Any, ...]) +assert_type(b_i8_f8_f8.size, int) + +assert_type(np.inner(AR_f8, AR_i8), Any) + +assert_type(np.where([True, True, False]), tuple[npt.NDArray[np.intp], ...]) +assert_type(np.where([True, True, False], 1, 0), npt.NDArray[Any]) + +assert_type(np.lexsort([0, 1, 2]), npt.NDArray[np.intp]) + +assert_type(np.can_cast(np.dtype("i8"), int), bool) +assert_type(np.can_cast(AR_f8, "f8"), bool) +assert_type(np.can_cast(AR_f8, np.complex128, casting="unsafe"), bool) + +assert_type(np.min_scalar_type([1]), np.dtype) +assert_type(np.min_scalar_type(AR_f8), np.dtype) + +assert_type(np.result_type(int, [1]), np.dtype) +assert_type(np.result_type(AR_f8, AR_u1), np.dtype) +assert_type(np.result_type(AR_f8, np.complex128), np.dtype) + +assert_type(np.dot(AR_LIKE_f, AR_i8), Any) +assert_type(np.dot(AR_u1, 1), Any) +assert_type(np.dot(1.5j, 1), Any) +assert_type(np.dot(AR_u1, 1, out=AR_f8), npt.NDArray[np.float64]) + +assert_type(np.vdot(AR_LIKE_f, AR_i8), np.floating) +assert_type(np.vdot(AR_u1, 1), np.signedinteger) +assert_type(np.vdot(1.5j, 1), np.complexfloating) + +assert_type(np.bincount(AR_i8), npt.NDArray[np.intp]) + +assert_type(np.copyto(AR_f8, [1., 1.5, 1.6]), None) + +assert_type(np.putmask(AR_f8, [True, True, False], 1.5), None) + +assert_type(np.packbits(AR_i8), np.ndarray[tuple[int], np.dtype[np.uint8]]) +assert_type(np.packbits(AR_u1), np.ndarray[tuple[int], np.dtype[np.uint8]]) +assert_type(np.packbits(AR_i8, axis=1), npt.NDArray[np.uint8]) +assert_type(np.packbits(AR_u1, axis=1), npt.NDArray[np.uint8]) + +assert_type(np.unpackbits(AR_u1), np.ndarray[tuple[int], np.dtype[np.uint8]]) +assert_type(np.unpackbits(AR_u1, axis=1), npt.NDArray[np.uint8]) + +assert_type(np.shares_memory(1, 2), bool) +assert_type(np.shares_memory(AR_f8, AR_f8, max_work=-1), bool) + +assert_type(np.may_share_memory(1, 2), bool) +assert_type(np.may_share_memory(AR_f8, AR_f8, max_work=0), bool) + +assert_type(np.promote_types(np.int32, np.int64), np.dtype) +assert_type(np.promote_types("f4", float), np.dtype) + +assert_type(np.frompyfunc(func11, n1, n1).nin, Literal[1]) +assert_type(np.frompyfunc(func11, n1, n1).nout, Literal[1]) +assert_type(np.frompyfunc(func11, n1, n1).nargs, Literal[2]) +assert_type(np.frompyfunc(func11, n1, n1).ntypes, Literal[1]) +assert_type(np.frompyfunc(func11, n1, n1).identity, None) +assert_type(np.frompyfunc(func11, n1, n1).signature, None) +assert_type(np.frompyfunc(func11, n1, n1)(f8), bool) +assert_type(np.frompyfunc(func11, n1, n1)(AR_f8), bool | npt.NDArray[np.object_]) +assert_type(np.frompyfunc(func11, n1, n1).at(AR_f8, AR_i8), None) + +assert_type(np.frompyfunc(func21, n2, n1).nin, Literal[2]) +assert_type(np.frompyfunc(func21, n2, n1).nout, Literal[1]) +assert_type(np.frompyfunc(func21, n2, n1).nargs, Literal[3]) +assert_type(np.frompyfunc(func21, n2, n1).ntypes, Literal[1]) +assert_type(np.frompyfunc(func21, n2, n1).identity, None) +assert_type(np.frompyfunc(func21, n2, n1).signature, None) +assert_type(np.frompyfunc(func21, n2, n1)(f8, f8), int) +assert_type(np.frompyfunc(func21, n2, n1)(AR_f8, f8), int | npt.NDArray[np.object_]) +assert_type(np.frompyfunc(func21, n2, n1)(f8, AR_f8), int | npt.NDArray[np.object_]) +assert_type(np.frompyfunc(func21, n2, n1).reduce(AR_f8, axis=0), int | npt.NDArray[np.object_]) +assert_type(np.frompyfunc(func21, n2, n1).accumulate(AR_f8), npt.NDArray[np.object_]) +assert_type(np.frompyfunc(func21, n2, n1).reduceat(AR_f8, AR_i8), npt.NDArray[np.object_]) +assert_type(np.frompyfunc(func21, n2, n1).outer(f8, f8), int) +assert_type(np.frompyfunc(func21, n2, n1).outer(AR_f8, f8), int | npt.NDArray[np.object_]) + +assert_type(np.frompyfunc(func21, n2, n1, identity=0).nin, Literal[2]) +assert_type(np.frompyfunc(func21, n2, n1, identity=0).nout, Literal[1]) +assert_type(np.frompyfunc(func21, n2, n1, identity=0).nargs, Literal[3]) +assert_type(np.frompyfunc(func21, n2, n1, identity=0).ntypes, Literal[1]) +assert_type(np.frompyfunc(func21, n2, n1, identity=0).identity, int) +assert_type(np.frompyfunc(func21, n2, n1, identity=0).signature, None) + +assert_type(np.frompyfunc(func12, n1, n2).nin, Literal[1]) +assert_type(np.frompyfunc(func12, n1, n2).nout, Literal[2]) +assert_type(np.frompyfunc(func12, n1, n2).nargs, int) +assert_type(np.frompyfunc(func12, n1, n2).ntypes, Literal[1]) +assert_type(np.frompyfunc(func12, n1, n2).identity, None) +assert_type(np.frompyfunc(func12, n1, n2).signature, None) +assert_type( + np.frompyfunc(func12, n2, n2)(f8, f8), + tuple[complex, complex, *tuple[complex, ...]], +) +assert_type( + np.frompyfunc(func12, n2, n2)(AR_f8, f8), + tuple[ + complex | npt.NDArray[np.object_], + complex | npt.NDArray[np.object_], + *tuple[complex | npt.NDArray[np.object_], ...], + ], +) + +assert_type(np.datetime_data("m8[D]"), tuple[str, int]) +assert_type(np.datetime_data(np.datetime64), tuple[str, int]) +assert_type(np.datetime_data(np.dtype(np.timedelta64)), tuple[str, int]) + +assert_type(np.busday_count("2011-01", "2011-02"), np.int_) +assert_type(np.busday_count(["2011-01"], "2011-02"), npt.NDArray[np.int_]) +assert_type(np.busday_count(["2011-01"], date_scalar), npt.NDArray[np.int_]) + +assert_type(np.busday_offset(M, m), np.datetime64) +assert_type(np.busday_offset(date_scalar, m), np.datetime64) +assert_type(np.busday_offset(M, 5), np.datetime64) +assert_type(np.busday_offset(AR_M, m), npt.NDArray[np.datetime64]) +assert_type(np.busday_offset(M, timedelta_seq), npt.NDArray[np.datetime64]) +assert_type(np.busday_offset("2011-01", "2011-02", roll="forward"), np.datetime64) +assert_type(np.busday_offset(["2011-01"], "2011-02", roll="forward"), npt.NDArray[np.datetime64]) + +assert_type(np.is_busday("2012"), np.bool) +assert_type(np.is_busday(date_scalar), np.bool) +assert_type(np.is_busday(["2012"]), npt.NDArray[np.bool]) + +assert_type(np.datetime_as_string(M), np.str_) +assert_type(np.datetime_as_string(AR_M), npt.NDArray[np.str_]) + +assert_type(np.busdaycalendar(holidays=date_seq), np.busdaycalendar) +assert_type(np.busdaycalendar(holidays=[M]), np.busdaycalendar) + +assert_type(np.char.compare_chararrays("a", "b", "!=", rstrip=False), npt.NDArray[np.bool]) +assert_type(np.char.compare_chararrays(b"a", b"a", "==", True), npt.NDArray[np.bool]) + +assert_type(np.nested_iters([AR_i8, AR_i8], [[0], [1]], flags=["c_index"]), tuple[np.nditer, ...]) +assert_type(np.nested_iters([AR_i8, AR_i8], [[0], [1]], op_flags=[["readonly", "readonly"]]), tuple[np.nditer, ...]) +assert_type(np.nested_iters([AR_i8, AR_i8], [[0], [1]], op_dtypes=np.int_), tuple[np.nditer, ...]) +assert_type(np.nested_iters([AR_i8, AR_i8], [[0], [1]], order="C", casting="no"), tuple[np.nditer, ...]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/nbit_base_example.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/nbit_base_example.pyi new file mode 100644 index 0000000000000000000000000000000000000000..66470b95bf156dcc36af597d01adab6fcc26a45b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/nbit_base_example.pyi @@ -0,0 +1,20 @@ +from typing import TypeVar, assert_type + +import numpy as np +import numpy.typing as npt +from numpy._typing import _32Bit, _64Bit + +T1 = TypeVar("T1", bound=npt.NBitBase) # type: ignore[deprecated] # pyright: ignore[reportDeprecated] +T2 = TypeVar("T2", bound=npt.NBitBase) # type: ignore[deprecated] # pyright: ignore[reportDeprecated] + +def add(a: np.floating[T1], b: np.integer[T2]) -> np.floating[T1 | T2]: ... + +i8: np.int64 +i4: np.int32 +f8: np.float64 +f4: np.float32 + +assert_type(add(f8, i8), np.floating[_64Bit]) +assert_type(add(f4, i8), np.floating[_32Bit | _64Bit]) +assert_type(add(f8, i4), np.floating[_32Bit | _64Bit]) +assert_type(add(f4, i4), np.floating[_32Bit]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ndarray_assignability.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ndarray_assignability.pyi new file mode 100644 index 0000000000000000000000000000000000000000..feaccf28f57830e2f258bc82a9ccd53c04d5db57 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ndarray_assignability.pyi @@ -0,0 +1,82 @@ +from typing import Any, Protocol, TypeAlias, TypeVar, assert_type + +import numpy as np +from numpy._typing import _64Bit + +_T = TypeVar("_T") +_T_co = TypeVar("_T_co", covariant=True) + +class CanAbs(Protocol[_T_co]): + def __abs__(self, /) -> _T_co: ... + +class CanInvert(Protocol[_T_co]): + def __invert__(self, /) -> _T_co: ... + +class CanNeg(Protocol[_T_co]): + def __neg__(self, /) -> _T_co: ... + +class CanPos(Protocol[_T_co]): + def __pos__(self, /) -> _T_co: ... + +def do_abs(x: CanAbs[_T]) -> _T: ... +def do_invert(x: CanInvert[_T]) -> _T: ... +def do_neg(x: CanNeg[_T]) -> _T: ... +def do_pos(x: CanPos[_T]) -> _T: ... + +_Bool_1d: TypeAlias = np.ndarray[tuple[int], np.dtype[np.bool]] +_UInt8_1d: TypeAlias = np.ndarray[tuple[int], np.dtype[np.uint8]] +_Int16_1d: TypeAlias = np.ndarray[tuple[int], np.dtype[np.int16]] +_LongLong_1d: TypeAlias = np.ndarray[tuple[int], np.dtype[np.longlong]] +_Float32_1d: TypeAlias = np.ndarray[tuple[int], np.dtype[np.float32]] +_Float64_1d: TypeAlias = np.ndarray[tuple[int], np.dtype[np.float64]] +_LongDouble_1d: TypeAlias = np.ndarray[tuple[int], np.dtype[np.longdouble]] +_Complex64_1d: TypeAlias = np.ndarray[tuple[int], np.dtype[np.complex64]] +_Complex128_1d: TypeAlias = np.ndarray[tuple[int], np.dtype[np.complex128]] +_CLongDouble_1d: TypeAlias = np.ndarray[tuple[int], np.dtype[np.clongdouble]] +_Void_1d: TypeAlias = np.ndarray[tuple[int], np.dtype[np.void]] + +b1_1d: _Bool_1d +u1_1d: _UInt8_1d +i2_1d: _Int16_1d +q_1d: _LongLong_1d +f4_1d: _Float32_1d +f8_1d: _Float64_1d +g_1d: _LongDouble_1d +c8_1d: _Complex64_1d +c16_1d: _Complex128_1d +G_1d: _CLongDouble_1d +V_1d: _Void_1d + +assert_type(do_abs(b1_1d), _Bool_1d) +assert_type(do_abs(u1_1d), _UInt8_1d) +assert_type(do_abs(i2_1d), _Int16_1d) +assert_type(do_abs(q_1d), _LongLong_1d) +assert_type(do_abs(f4_1d), _Float32_1d) +assert_type(do_abs(f8_1d), _Float64_1d) +assert_type(do_abs(g_1d), _LongDouble_1d) + +assert_type(do_abs(c8_1d), _Float32_1d) +# NOTE: Unfortunately it's not possible to have this return a `float64` sctype, see +# https://github.com/python/mypy/issues/14070 +assert_type(do_abs(c16_1d), np.ndarray[tuple[int], np.dtype[np.floating[_64Bit]]]) +assert_type(do_abs(G_1d), _LongDouble_1d) + +assert_type(do_invert(b1_1d), _Bool_1d) +assert_type(do_invert(u1_1d), _UInt8_1d) +assert_type(do_invert(i2_1d), _Int16_1d) +assert_type(do_invert(q_1d), _LongLong_1d) + +assert_type(do_neg(u1_1d), _UInt8_1d) +assert_type(do_neg(i2_1d), _Int16_1d) +assert_type(do_neg(q_1d), _LongLong_1d) +assert_type(do_neg(f4_1d), _Float32_1d) +assert_type(do_neg(c16_1d), _Complex128_1d) + +assert_type(do_pos(u1_1d), _UInt8_1d) +assert_type(do_pos(i2_1d), _Int16_1d) +assert_type(do_pos(q_1d), _LongLong_1d) +assert_type(do_pos(f4_1d), _Float32_1d) +assert_type(do_pos(c16_1d), _Complex128_1d) + +# this shape is effectively equivalent to `tuple[int, *tuple[Any, ...]]`, i.e. ndim >= 1 +assert_type(V_1d["field"], np.ndarray[tuple[int] | tuple[Any, ...]]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ndarray_conversion.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ndarray_conversion.pyi new file mode 100644 index 0000000000000000000000000000000000000000..2af616440c5e7b35ab4697b520fb879c0aebfde9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ndarray_conversion.pyi @@ -0,0 +1,83 @@ +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt + +b1_0d: np.ndarray[tuple[()], np.dtype[np.bool]] +u2_1d: np.ndarray[tuple[int], np.dtype[np.uint16]] +i4_2d: np.ndarray[tuple[int, int], np.dtype[np.int32]] +f8_3d: np.ndarray[tuple[int, int, int], np.dtype[np.float64]] +cG_4d: np.ndarray[tuple[int, int, int, int], np.dtype[np.clongdouble]] +i0_nd: npt.NDArray[np.int_] +uncertain_dtype: np.int32 | np.float64 | np.str_ + +# item +assert_type(i0_nd.item(), int) +assert_type(i0_nd.item(1), int) +assert_type(i0_nd.item(0, 1), int) +assert_type(i0_nd.item((0, 1)), int) + +assert_type(b1_0d.item(()), bool) +assert_type(u2_1d.item((0,)), int) +assert_type(i4_2d.item(-1, 2), int) +assert_type(f8_3d.item(2, 1, -1), float) +assert_type(cG_4d.item(-0xEd_fed_Deb_a_dead_bee), complex) # c'mon Ed, we talked about this... + +# tolist +assert_type(b1_0d.tolist(), bool) +assert_type(u2_1d.tolist(), list[int]) +assert_type(i4_2d.tolist(), list[list[int]]) +assert_type(f8_3d.tolist(), list[list[list[float]]]) +assert_type(cG_4d.tolist(), Any) +assert_type(i0_nd.tolist(), Any) + +# regression tests for numpy/numpy#27944 +any_dtype: np.ndarray[Any, Any] +any_sctype: np.ndarray[Any, Any] +assert_type(any_dtype.tolist(), Any) +assert_type(any_sctype.tolist(), Any) + +# tobytes is pretty simple +# tofile does not return a value +# dump does not return a value +# dumps is pretty simple + +# astype +assert_type(i0_nd.astype("float"), npt.NDArray[Any]) +assert_type(i0_nd.astype(float), npt.NDArray[Any]) +assert_type(i0_nd.astype(np.float64), npt.NDArray[np.float64]) +assert_type(i0_nd.astype(np.float64, "K"), npt.NDArray[np.float64]) +assert_type(i0_nd.astype(np.float64, "K", "unsafe"), npt.NDArray[np.float64]) +assert_type(i0_nd.astype(np.float64, "K", "unsafe", True), npt.NDArray[np.float64]) +assert_type(i0_nd.astype(np.float64, "K", "unsafe", True, True), npt.NDArray[np.float64]) + +assert_type(np.astype(i0_nd, np.float64), npt.NDArray[np.float64]) + +assert_type(i4_2d.astype(np.uint16), np.ndarray[tuple[int, int], np.dtype[np.uint16]]) +assert_type(np.astype(i4_2d, np.uint16), np.ndarray[tuple[int, int], np.dtype[np.uint16]]) +assert_type(f8_3d.astype(np.int16), np.ndarray[tuple[int, int, int], np.dtype[np.int16]]) +assert_type(np.astype(f8_3d, np.int16), np.ndarray[tuple[int, int, int], np.dtype[np.int16]]) +assert_type(i4_2d.astype(uncertain_dtype), np.ndarray[tuple[int, int], np.dtype[np.generic]]) +assert_type(np.astype(i4_2d, uncertain_dtype), np.ndarray[tuple[int, int], np.dtype]) + +# byteswap +assert_type(i0_nd.byteswap(), npt.NDArray[np.int_]) +assert_type(i0_nd.byteswap(True), npt.NDArray[np.int_]) + +# copy +assert_type(i0_nd.copy(), npt.NDArray[np.int_]) +assert_type(i0_nd.copy("C"), npt.NDArray[np.int_]) + +assert_type(i0_nd.view(), npt.NDArray[np.int_]) +assert_type(i0_nd.view(np.float64), npt.NDArray[np.float64]) +assert_type(i0_nd.view(float), npt.NDArray[Any]) +assert_type(i0_nd.view(np.float64, np.matrix), np.matrix) + +# getfield +assert_type(i0_nd.getfield("float"), npt.NDArray[Any]) +assert_type(i0_nd.getfield(float), npt.NDArray[Any]) +assert_type(i0_nd.getfield(np.float64), npt.NDArray[np.float64]) +assert_type(i0_nd.getfield(np.float64, 8), npt.NDArray[np.float64]) + +# setflags does not return a value +# fill does not return a value diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ndarray_misc.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ndarray_misc.pyi new file mode 100644 index 0000000000000000000000000000000000000000..2972a58c328f311a2b7dc5d9a9c90737b9f6c04f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ndarray_misc.pyi @@ -0,0 +1,246 @@ +""" +Tests for miscellaneous (non-magic) ``np.ndarray``/``np.generic`` methods. + +More extensive tests are performed for the methods' +function-based counterpart in `../from_numeric.py`. + +""" + +import ctypes as ct +import operator +from collections.abc import Iterator +from types import ModuleType +from typing import Any, Literal, assert_type +from typing_extensions import CapsuleType + +import numpy as np +import numpy.typing as npt + +class SubClass(npt.NDArray[np.object_]): ... + +f8: np.float64 +i8: np.int64 +B: SubClass +AR_f8: npt.NDArray[np.float64] +AR_i8: npt.NDArray[np.int64] +AR_u1: npt.NDArray[np.uint8] +AR_c8: npt.NDArray[np.complex64] +AR_m: npt.NDArray[np.timedelta64] +AR_U: npt.NDArray[np.str_] +AR_V: npt.NDArray[np.void] + +AR_f8_1d: np.ndarray[tuple[int], np.dtype[np.float64]] +AR_f8_2d: np.ndarray[tuple[int, int], np.dtype[np.float64]] +AR_f8_3d: np.ndarray[tuple[int, int, int], np.dtype[np.float64]] + +ctypes_obj = AR_f8.ctypes + +assert_type(AR_f8.__dlpack__(), CapsuleType) +assert_type(AR_f8.__dlpack_device__(), tuple[Literal[1], Literal[0]]) + +assert_type(ctypes_obj.data, int) +assert_type(ctypes_obj.shape, ct.Array[np.ctypeslib.c_intp]) +assert_type(ctypes_obj.strides, ct.Array[np.ctypeslib.c_intp]) +assert_type(ctypes_obj._as_parameter_, ct.c_void_p) + +assert_type(ctypes_obj.data_as(ct.c_void_p), ct.c_void_p) +assert_type(ctypes_obj.shape_as(ct.c_longlong), ct.Array[ct.c_longlong]) +assert_type(ctypes_obj.strides_as(ct.c_ubyte), ct.Array[ct.c_ubyte]) + +assert_type(f8.all(), np.bool) +assert_type(AR_f8.all(), np.bool) +assert_type(AR_f8.all(axis=0), np.bool | npt.NDArray[np.bool]) +assert_type(AR_f8.all(keepdims=True), np.bool | npt.NDArray[np.bool]) +assert_type(AR_f8.all(out=B), SubClass) + +assert_type(f8.any(), np.bool) +assert_type(AR_f8.any(), np.bool) +assert_type(AR_f8.any(axis=0), np.bool | npt.NDArray[np.bool]) +assert_type(AR_f8.any(keepdims=True), np.bool | npt.NDArray[np.bool]) +assert_type(AR_f8.any(out=B), SubClass) + +assert_type(f8.argmax(), np.intp) +assert_type(AR_f8.argmax(), np.intp) +assert_type(AR_f8.argmax(axis=0), Any) +assert_type(AR_f8.argmax(out=AR_i8), npt.NDArray[np.intp]) + +assert_type(f8.argmin(), np.intp) +assert_type(AR_f8.argmin(), np.intp) +assert_type(AR_f8.argmin(axis=0), Any) +assert_type(AR_f8.argmin(out=AR_i8), npt.NDArray[np.intp]) + +assert_type(f8.argsort(), npt.NDArray[np.intp]) +assert_type(AR_f8.argsort(), npt.NDArray[np.intp]) + +assert_type(f8.astype(np.int64).choose([()]), npt.NDArray[Any]) +assert_type(AR_f8.choose([0]), npt.NDArray[Any]) +assert_type(AR_f8.choose([0], out=B), SubClass) + +assert_type(f8.clip(1), npt.NDArray[Any]) +assert_type(AR_f8.clip(1), npt.NDArray[Any]) +assert_type(AR_f8.clip(None, 1), npt.NDArray[Any]) +assert_type(AR_f8.clip(1, out=B), SubClass) +assert_type(AR_f8.clip(None, 1, out=B), SubClass) + +assert_type(f8.compress([0]), npt.NDArray[Any]) +assert_type(AR_f8.compress([0]), npt.NDArray[Any]) +assert_type(AR_f8.compress([0], out=B), SubClass) + +assert_type(f8.conj(), np.float64) +assert_type(AR_f8.conj(), npt.NDArray[np.float64]) +assert_type(B.conj(), SubClass) + +assert_type(f8.conjugate(), np.float64) +assert_type(AR_f8.conjugate(), npt.NDArray[np.float64]) +assert_type(B.conjugate(), SubClass) + +assert_type(f8.cumprod(), npt.NDArray[Any]) +assert_type(AR_f8.cumprod(), npt.NDArray[Any]) +assert_type(AR_f8.cumprod(out=B), SubClass) + +assert_type(f8.cumsum(), npt.NDArray[Any]) +assert_type(AR_f8.cumsum(), npt.NDArray[Any]) +assert_type(AR_f8.cumsum(out=B), SubClass) + +assert_type(f8.max(), Any) +assert_type(AR_f8.max(), Any) +assert_type(AR_f8.max(axis=0), Any) +assert_type(AR_f8.max(keepdims=True), Any) +assert_type(AR_f8.max(out=B), SubClass) + +assert_type(f8.mean(), Any) +assert_type(AR_f8.mean(), Any) +assert_type(AR_f8.mean(axis=0), Any) +assert_type(AR_f8.mean(keepdims=True), Any) +assert_type(AR_f8.mean(out=B), SubClass) + +assert_type(f8.min(), Any) +assert_type(AR_f8.min(), Any) +assert_type(AR_f8.min(axis=0), Any) +assert_type(AR_f8.min(keepdims=True), Any) +assert_type(AR_f8.min(out=B), SubClass) + +assert_type(f8.prod(), Any) +assert_type(AR_f8.prod(), Any) +assert_type(AR_f8.prod(axis=0), Any) +assert_type(AR_f8.prod(keepdims=True), Any) +assert_type(AR_f8.prod(out=B), SubClass) + +assert_type(f8.round(), np.float64) +assert_type(AR_f8.round(), npt.NDArray[np.float64]) +assert_type(AR_f8.round(out=B), SubClass) + +assert_type(f8.repeat(1), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(f8.repeat(1, axis=0), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(AR_f8.repeat(1), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(AR_f8.repeat(1, axis=0), npt.NDArray[np.float64]) +assert_type(B.repeat(1), np.ndarray[tuple[int], np.dtype[np.object_]]) +assert_type(B.repeat(1, axis=0), npt.NDArray[np.object_]) + +assert_type(f8.std(), Any) +assert_type(AR_f8.std(), Any) +assert_type(AR_f8.std(axis=0), Any) +assert_type(AR_f8.std(keepdims=True), Any) +assert_type(AR_f8.std(out=B), SubClass) + +assert_type(f8.sum(), Any) +assert_type(AR_f8.sum(), Any) +assert_type(AR_f8.sum(axis=0), Any) +assert_type(AR_f8.sum(keepdims=True), Any) +assert_type(AR_f8.sum(out=B), SubClass) + +assert_type(f8.take(0), np.float64) +assert_type(AR_f8.take(0), np.float64) +assert_type(AR_f8.take([0]), npt.NDArray[np.float64]) +assert_type(AR_f8.take(0, out=B), SubClass) +assert_type(AR_f8.take([0], out=B), SubClass) + +assert_type(f8.var(), Any) +assert_type(AR_f8.var(), Any) +assert_type(AR_f8.var(axis=0), Any) +assert_type(AR_f8.var(keepdims=True), Any) +assert_type(AR_f8.var(out=B), SubClass) + +assert_type(AR_f8.argpartition([0]), npt.NDArray[np.intp]) + +assert_type(AR_f8.diagonal(), npt.NDArray[np.float64]) + +assert_type(AR_f8.dot(1), npt.NDArray[Any]) +assert_type(AR_f8.dot([1]), Any) +assert_type(AR_f8.dot(1, out=B), SubClass) + +assert_type(AR_f8.nonzero(), tuple[np.ndarray[tuple[int], np.dtype[np.intp]], ...]) + +assert_type(AR_f8.searchsorted(1), np.intp) +assert_type(AR_f8.searchsorted([1]), npt.NDArray[np.intp]) + +assert_type(AR_f8.trace(), Any) +assert_type(AR_f8.trace(out=B), SubClass) + +assert_type(AR_f8.item(), float) +assert_type(AR_U.item(), str) + +assert_type(AR_f8.ravel(), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(AR_U.ravel(), np.ndarray[tuple[int], np.dtype[np.str_]]) + +assert_type(AR_f8.flatten(), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(AR_U.flatten(), np.ndarray[tuple[int], np.dtype[np.str_]]) + +assert_type(AR_i8.reshape(None), npt.NDArray[np.int64]) +assert_type(AR_f8.reshape(-1), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(AR_c8.reshape(2, 3, 4, 5), np.ndarray[tuple[int, int, int, int], np.dtype[np.complex64]]) +assert_type(AR_m.reshape(()), np.ndarray[tuple[()], np.dtype[np.timedelta64]]) +assert_type(AR_U.reshape([]), np.ndarray[tuple[()], np.dtype[np.str_]]) +assert_type(AR_V.reshape((480, 720, 4)), np.ndarray[tuple[int, int, int], np.dtype[np.void]]) + +assert_type(int(AR_f8), int) +assert_type(int(AR_U), int) + +assert_type(float(AR_f8), float) +assert_type(float(AR_U), float) + +assert_type(complex(AR_f8), complex) + +assert_type(operator.index(AR_i8), int) + +assert_type(AR_f8.__array_wrap__(B), npt.NDArray[np.object_]) + +assert_type(AR_V[0], Any) +assert_type(AR_V[0, 0], Any) +assert_type(AR_V[AR_i8], npt.NDArray[np.void]) +assert_type(AR_V[AR_i8, AR_i8], npt.NDArray[np.void]) +assert_type(AR_V[AR_i8, None], npt.NDArray[np.void]) +assert_type(AR_V[0, ...], npt.NDArray[np.void]) +assert_type(AR_V[[0]], npt.NDArray[np.void]) +assert_type(AR_V[[0], [0]], npt.NDArray[np.void]) +assert_type(AR_V[:], npt.NDArray[np.void]) +assert_type(AR_V["a"], npt.NDArray[Any]) +assert_type(AR_V[["a", "b"]], npt.NDArray[np.void]) + +assert_type(AR_f8.dump("test_file"), None) +assert_type(AR_f8.dump(b"test_file"), None) +with open("test_file", "wb") as f: + assert_type(AR_f8.dump(f), None) + +assert_type(AR_f8.__array_finalize__(None), None) +assert_type(AR_f8.__array_finalize__(B), None) +assert_type(AR_f8.__array_finalize__(AR_f8), None) + +assert_type(f8.device, Literal["cpu"]) +assert_type(AR_f8.device, Literal["cpu"]) + +assert_type(f8.to_device("cpu"), np.float64) +assert_type(i8.to_device("cpu"), np.int64) +assert_type(AR_f8.to_device("cpu"), npt.NDArray[np.float64]) +assert_type(AR_i8.to_device("cpu"), npt.NDArray[np.int64]) +assert_type(AR_u1.to_device("cpu"), npt.NDArray[np.uint8]) +assert_type(AR_c8.to_device("cpu"), npt.NDArray[np.complex64]) +assert_type(AR_m.to_device("cpu"), npt.NDArray[np.timedelta64]) + +assert_type(f8.__array_namespace__(), ModuleType) +assert_type(AR_f8.__array_namespace__(), ModuleType) + +assert_type(iter(AR_f8), Iterator[Any]) # any-D +assert_type(iter(AR_f8_1d), Iterator[np.float64]) # 1-D +assert_type(iter(AR_f8_2d), Iterator[npt.NDArray[np.float64]]) # 2-D +assert_type(iter(AR_f8_3d), Iterator[npt.NDArray[np.float64]]) # 3-D diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ndarray_shape_manipulation.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ndarray_shape_manipulation.pyi new file mode 100644 index 0000000000000000000000000000000000000000..0ce599a4031049b366a66b30537c503b612588fe --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ndarray_shape_manipulation.pyi @@ -0,0 +1,47 @@ +from typing import TypeAlias, assert_type + +import numpy as np +import numpy.typing as npt + +_ArrayND: TypeAlias = npt.NDArray[np.int64] +_Array2D: TypeAlias = np.ndarray[tuple[int, int], np.dtype[np.int8]] +_Array3D: TypeAlias = np.ndarray[tuple[int, int, int], np.dtype[np.bool]] + +_nd: _ArrayND +_2d: _Array2D +_3d: _Array3D + +# reshape +assert_type(_nd.reshape(None), npt.NDArray[np.int64]) +assert_type(_nd.reshape(4), np.ndarray[tuple[int], np.dtype[np.int64]]) +assert_type(_nd.reshape((4,)), np.ndarray[tuple[int], np.dtype[np.int64]]) +assert_type(_nd.reshape(2, 2), np.ndarray[tuple[int, int], np.dtype[np.int64]]) +assert_type(_nd.reshape((2, 2)), np.ndarray[tuple[int, int], np.dtype[np.int64]]) + +assert_type(_nd.reshape((2, 2), order="C"), np.ndarray[tuple[int, int], np.dtype[np.int64]]) +assert_type(_nd.reshape(4, order="C"), np.ndarray[tuple[int], np.dtype[np.int64]]) + +# resize does not return a value + +# transpose +assert_type(_nd.transpose(), npt.NDArray[np.int64]) +assert_type(_nd.transpose(1, 0), npt.NDArray[np.int64]) +assert_type(_nd.transpose((1, 0)), npt.NDArray[np.int64]) + +# swapaxes +assert_type(_nd.swapaxes(0, 1), _ArrayND) +assert_type(_2d.swapaxes(0, 1), _Array2D) +assert_type(_3d.swapaxes(0, 1), _Array3D) + +# flatten +assert_type(_nd.flatten(), np.ndarray[tuple[int], np.dtype[np.int64]]) +assert_type(_nd.flatten("C"), np.ndarray[tuple[int], np.dtype[np.int64]]) + +# ravel +assert_type(_nd.ravel(), np.ndarray[tuple[int], np.dtype[np.int64]]) +assert_type(_nd.ravel("C"), np.ndarray[tuple[int], np.dtype[np.int64]]) + +# squeeze +assert_type(_nd.squeeze(), npt.NDArray[np.int64]) +assert_type(_nd.squeeze(0), npt.NDArray[np.int64]) +assert_type(_nd.squeeze((0, 2)), npt.NDArray[np.int64]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/nditer.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/nditer.pyi new file mode 100644 index 0000000000000000000000000000000000000000..8965f3c03e6de46740c7b1aa8978f1730a0ac799 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/nditer.pyi @@ -0,0 +1,49 @@ +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt + +nditer_obj: np.nditer + +assert_type(np.nditer([0, 1], flags=["c_index"]), np.nditer) +assert_type(np.nditer([0, 1], op_flags=[["readonly", "readonly"]]), np.nditer) +assert_type(np.nditer([0, 1], op_dtypes=np.int_), np.nditer) +assert_type(np.nditer([0, 1], order="C", casting="no"), np.nditer) + +assert_type(nditer_obj.dtypes, tuple[np.dtype, ...]) +assert_type(nditer_obj.finished, bool) +assert_type(nditer_obj.has_delayed_bufalloc, bool) +assert_type(nditer_obj.has_index, bool) +assert_type(nditer_obj.has_multi_index, bool) +assert_type(nditer_obj.index, int) +assert_type(nditer_obj.iterationneedsapi, bool) +assert_type(nditer_obj.iterindex, int) +assert_type(nditer_obj.iterrange, tuple[int, ...]) +assert_type(nditer_obj.itersize, int) +assert_type(nditer_obj.itviews, tuple[npt.NDArray[Any], ...]) +assert_type(nditer_obj.multi_index, tuple[int, ...]) +assert_type(nditer_obj.ndim, int) +assert_type(nditer_obj.nop, int) +assert_type(nditer_obj.operands, tuple[npt.NDArray[Any], ...]) +assert_type(nditer_obj.shape, tuple[int, ...]) +assert_type(nditer_obj.value, tuple[npt.NDArray[Any], ...]) + +assert_type(nditer_obj.close(), None) +assert_type(nditer_obj.copy(), np.nditer) +assert_type(nditer_obj.debug_print(), None) +assert_type(nditer_obj.enable_external_loop(), None) +assert_type(nditer_obj.iternext(), bool) +assert_type(nditer_obj.remove_axis(0), None) +assert_type(nditer_obj.remove_multi_index(), None) +assert_type(nditer_obj.reset(), None) + +assert_type(len(nditer_obj), int) +assert_type(iter(nditer_obj), np.nditer) +assert_type(next(nditer_obj), tuple[npt.NDArray[Any], ...]) +assert_type(nditer_obj.__copy__(), np.nditer) +with nditer_obj as f: + assert_type(f, np.nditer) +assert_type(nditer_obj[0], npt.NDArray[Any]) +assert_type(nditer_obj[:], tuple[npt.NDArray[Any], ...]) +nditer_obj[0] = 0 +nditer_obj[:] = [0, 1] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/nested_sequence.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/nested_sequence.pyi new file mode 100644 index 0000000000000000000000000000000000000000..b4f98b79c3339fa856a09cd639961b5bb8156fd3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/nested_sequence.pyi @@ -0,0 +1,25 @@ +from collections.abc import Sequence +from typing import Any, assert_type + +from numpy._typing import _NestedSequence + +a: Sequence[int] +b: Sequence[Sequence[int]] +c: Sequence[Sequence[Sequence[int]]] +d: Sequence[Sequence[Sequence[Sequence[int]]]] +e: Sequence[bool] +f: tuple[int, ...] +g: list[int] +h: Sequence[Any] + +def func(a: _NestedSequence[int]) -> None: ... + +assert_type(func(a), None) +assert_type(func(b), None) +assert_type(func(c), None) +assert_type(func(d), None) +assert_type(func(e), None) +assert_type(func(f), None) +assert_type(func(g), None) +assert_type(func(h), None) +assert_type(func(range(15)), None) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/npyio.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/npyio.pyi new file mode 100644 index 0000000000000000000000000000000000000000..e3eaa45a5fa1a4cf0366f674e7a1629fac9b9dd8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/npyio.pyi @@ -0,0 +1,83 @@ +import pathlib +import re +import zipfile +from collections.abc import Mapping +from typing import IO, Any, assert_type + +import numpy as np +import numpy.typing as npt +from numpy.lib._npyio_impl import BagObj + +str_path: str +pathlib_path: pathlib.Path +str_file: IO[str] +bytes_file: IO[bytes] + +npz_file: np.lib.npyio.NpzFile + +AR_i8: npt.NDArray[np.int64] +AR_LIKE_f8: list[float] + +class BytesWriter: + def write(self, data: bytes) -> None: ... + +class BytesReader: + def read(self, n: int = ...) -> bytes: ... + def seek(self, offset: int, whence: int = ...) -> int: ... + +bytes_writer: BytesWriter +bytes_reader: BytesReader + +assert_type(npz_file.zip, zipfile.ZipFile | None) +assert_type(npz_file.fid, IO[str] | None) +assert_type(npz_file.files, list[str]) +assert_type(npz_file.allow_pickle, bool) +assert_type(npz_file.pickle_kwargs, Mapping[str, Any] | None) +assert_type(npz_file.f, BagObj[np.lib.npyio.NpzFile]) +assert_type(npz_file["test"], npt.NDArray[Any]) +assert_type(len(npz_file), int) +with npz_file as f: + assert_type(f, np.lib.npyio.NpzFile) + +assert_type(np.load(bytes_file), Any) +assert_type(np.load(pathlib_path, allow_pickle=True), Any) +assert_type(np.load(str_path, encoding="bytes"), Any) +assert_type(np.load(bytes_reader), Any) + +assert_type(np.save(bytes_file, AR_LIKE_f8), None) +assert_type(np.save(pathlib_path, AR_i8, allow_pickle=True), None) +assert_type(np.save(str_path, AR_LIKE_f8), None) +assert_type(np.save(bytes_writer, AR_LIKE_f8), None) + +assert_type(np.savez(bytes_file, AR_LIKE_f8), None) +assert_type(np.savez(pathlib_path, ar1=AR_i8, ar2=AR_i8), None) +assert_type(np.savez(str_path, AR_LIKE_f8, ar1=AR_i8), None) +assert_type(np.savez(bytes_writer, AR_LIKE_f8, ar1=AR_i8), None) + +assert_type(np.savez_compressed(bytes_file, AR_LIKE_f8), None) +assert_type(np.savez_compressed(pathlib_path, ar1=AR_i8, ar2=AR_i8), None) +assert_type(np.savez_compressed(str_path, AR_LIKE_f8, ar1=AR_i8), None) +assert_type(np.savez_compressed(bytes_writer, AR_LIKE_f8, ar1=AR_i8), None) + +assert_type(np.loadtxt(bytes_file), npt.NDArray[np.float64]) +assert_type(np.loadtxt(pathlib_path, dtype=np.str_), npt.NDArray[np.str_]) +assert_type(np.loadtxt(str_path, dtype=str, skiprows=2), npt.NDArray[Any]) +assert_type(np.loadtxt(str_file, comments="test"), npt.NDArray[np.float64]) +assert_type(np.loadtxt(str_file, comments=None), npt.NDArray[np.float64]) +assert_type(np.loadtxt(str_path, delimiter="\n"), npt.NDArray[np.float64]) +assert_type(np.loadtxt(str_path, ndmin=2), npt.NDArray[np.float64]) +assert_type(np.loadtxt(["1", "2", "3"]), npt.NDArray[np.float64]) + +assert_type(np.fromregex(bytes_file, "test", np.float64), npt.NDArray[np.float64]) +assert_type(np.fromregex(str_file, b"test", dtype=float), npt.NDArray[Any]) +assert_type(np.fromregex(str_path, re.compile("test"), dtype=np.str_, encoding="utf8"), npt.NDArray[np.str_]) +assert_type(np.fromregex(pathlib_path, "test", np.float64), npt.NDArray[np.float64]) +assert_type(np.fromregex(bytes_reader, "test", np.float64), npt.NDArray[np.float64]) + +assert_type(np.genfromtxt(bytes_file), npt.NDArray[Any]) +assert_type(np.genfromtxt(pathlib_path, dtype=np.str_), npt.NDArray[np.str_]) +assert_type(np.genfromtxt(str_path, dtype=str, skip_header=2), npt.NDArray[Any]) +assert_type(np.genfromtxt(str_file, comments="test"), npt.NDArray[Any]) +assert_type(np.genfromtxt(str_path, delimiter="\n"), npt.NDArray[Any]) +assert_type(np.genfromtxt(str_path, ndmin=2), npt.NDArray[Any]) +assert_type(np.genfromtxt(["1", "2", "3"], ndmin=2), npt.NDArray[Any]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/numeric.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/numeric.pyi new file mode 100644 index 0000000000000000000000000000000000000000..24f97d2d078436f0b99420714e8aef11b1297da3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/numeric.pyi @@ -0,0 +1,170 @@ +""" +Tests for :mod:`_core.numeric`. + +Does not include tests which fall under ``array_constructors``. + +""" + +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt + +class SubClass(npt.NDArray[np.int64]): ... + +i8: np.int64 + +AR_b: npt.NDArray[np.bool] +AR_u8: npt.NDArray[np.uint64] +AR_i8: npt.NDArray[np.int64] +AR_f8: npt.NDArray[np.float64] +AR_c16: npt.NDArray[np.complex128] +AR_m: npt.NDArray[np.timedelta64] +AR_O: npt.NDArray[np.object_] + +_sub_nd_i8: SubClass + +_to_1d_bool: list[bool] +_to_1d_int: list[int] +_to_1d_float: list[float] +_to_1d_complex: list[complex] + +### + +assert_type(np.count_nonzero(i8), np.intp) +assert_type(np.count_nonzero(AR_i8), np.intp) +assert_type(np.count_nonzero(_to_1d_int), np.intp) +assert_type(np.count_nonzero(AR_i8, keepdims=True), npt.NDArray[np.intp]) +assert_type(np.count_nonzero(AR_i8, axis=0), Any) + +assert_type(np.isfortran(i8), bool) +assert_type(np.isfortran(AR_i8), bool) + +assert_type(np.argwhere(i8), np.ndarray[tuple[int, int], np.dtype[np.intp]]) +assert_type(np.argwhere(AR_i8), np.ndarray[tuple[int, int], np.dtype[np.intp]]) + +assert_type(np.flatnonzero(i8), np.ndarray[tuple[int], np.dtype[np.intp]]) +assert_type(np.flatnonzero(AR_i8), np.ndarray[tuple[int], np.dtype[np.intp]]) + +# correlate +assert_type(np.correlate(AR_i8, AR_i8), np.ndarray[tuple[int], np.dtype[np.int64]]) +assert_type(np.correlate(AR_b, AR_b), np.ndarray[tuple[int], np.dtype[np.bool]]) +assert_type(np.correlate(AR_u8, AR_u8), np.ndarray[tuple[int], np.dtype[np.uint64]]) +assert_type(np.correlate(AR_i8, AR_i8), np.ndarray[tuple[int], np.dtype[np.int64]]) +assert_type(np.correlate(AR_f8, AR_f8), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.correlate(AR_f8, AR_i8), np.ndarray[tuple[int], np.dtype[np.float64 | Any]]) +assert_type(np.correlate(AR_c16, AR_c16), np.ndarray[tuple[int], np.dtype[np.complex128]]) +assert_type(np.correlate(AR_c16, AR_f8), np.ndarray[tuple[int], np.dtype[np.complex128 | Any]]) +assert_type(np.correlate(AR_m, AR_m), np.ndarray[tuple[int], np.dtype[np.timedelta64]]) +assert_type(np.correlate(AR_i8, AR_m), np.ndarray[tuple[int], np.dtype[np.timedelta64 | Any]]) +assert_type(np.correlate(AR_O, AR_O), np.ndarray[tuple[int], np.dtype[np.object_]]) +assert_type(np.correlate(_to_1d_bool, _to_1d_bool), np.ndarray[tuple[int], np.dtype[np.bool]]) +assert_type(np.correlate(_to_1d_int, _to_1d_int), np.ndarray[tuple[int], np.dtype[np.int_ | Any]]) +assert_type(np.correlate(_to_1d_float, _to_1d_float), np.ndarray[tuple[int], np.dtype[np.float64 | Any]]) +assert_type(np.correlate(_to_1d_complex, _to_1d_complex), np.ndarray[tuple[int], np.dtype[np.complex128 | Any]]) + +# convolve (same as correlate) +assert_type(np.convolve(AR_i8, AR_i8), np.ndarray[tuple[int], np.dtype[np.int64]]) +assert_type(np.convolve(AR_b, AR_b), np.ndarray[tuple[int], np.dtype[np.bool]]) +assert_type(np.convolve(AR_u8, AR_u8), np.ndarray[tuple[int], np.dtype[np.uint64]]) +assert_type(np.convolve(AR_i8, AR_i8), np.ndarray[tuple[int], np.dtype[np.int64]]) +assert_type(np.convolve(AR_f8, AR_f8), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(np.convolve(AR_f8, AR_i8), np.ndarray[tuple[int], np.dtype[np.float64 | Any]]) +assert_type(np.convolve(AR_c16, AR_c16), np.ndarray[tuple[int], np.dtype[np.complex128]]) +assert_type(np.convolve(AR_c16, AR_f8), np.ndarray[tuple[int], np.dtype[np.complex128 | Any]]) +assert_type(np.convolve(AR_m, AR_m), np.ndarray[tuple[int], np.dtype[np.timedelta64]]) +assert_type(np.convolve(AR_i8, AR_m), np.ndarray[tuple[int], np.dtype[np.timedelta64 | Any]]) +assert_type(np.convolve(AR_O, AR_O), np.ndarray[tuple[int], np.dtype[np.object_]]) +assert_type(np.convolve(_to_1d_bool, _to_1d_bool), np.ndarray[tuple[int], np.dtype[np.bool]]) +assert_type(np.convolve(_to_1d_int, _to_1d_int), np.ndarray[tuple[int], np.dtype[np.int_ | Any]]) +assert_type(np.convolve(_to_1d_float, _to_1d_float), np.ndarray[tuple[int], np.dtype[np.float64 | Any]]) +assert_type(np.convolve(_to_1d_complex, _to_1d_complex), np.ndarray[tuple[int], np.dtype[np.complex128 | Any]]) + +# outer (very similar to above, but 2D output) +assert_type(np.outer(AR_i8, AR_i8), np.ndarray[tuple[int, int], np.dtype[np.int64]]) +assert_type(np.outer(AR_b, AR_b), np.ndarray[tuple[int, int], np.dtype[np.bool]]) +assert_type(np.outer(AR_u8, AR_u8), np.ndarray[tuple[int, int], np.dtype[np.uint64]]) +assert_type(np.outer(AR_i8, AR_i8), np.ndarray[tuple[int, int], np.dtype[np.int64]]) +assert_type(np.outer(AR_f8, AR_f8), np.ndarray[tuple[int, int], np.dtype[np.float64]]) +assert_type(np.outer(AR_f8, AR_i8), np.ndarray[tuple[int, int], np.dtype[np.float64 | Any]]) +assert_type(np.outer(AR_c16, AR_c16), np.ndarray[tuple[int, int], np.dtype[np.complex128]]) +assert_type(np.outer(AR_c16, AR_f8), np.ndarray[tuple[int, int], np.dtype[np.complex128 | Any]]) +assert_type(np.outer(AR_m, AR_m), np.ndarray[tuple[int, int], np.dtype[np.timedelta64]]) +assert_type(np.outer(AR_i8, AR_m), np.ndarray[tuple[int, int], np.dtype[np.timedelta64 | Any]]) +assert_type(np.outer(AR_O, AR_O), np.ndarray[tuple[int, int], np.dtype[np.object_]]) +assert_type(np.outer(AR_i8, AR_i8, out=_sub_nd_i8), SubClass) +assert_type(np.outer(_to_1d_bool, _to_1d_bool), np.ndarray[tuple[int, int], np.dtype[np.bool]]) +assert_type(np.outer(_to_1d_int, _to_1d_int), np.ndarray[tuple[int, int], np.dtype[np.int_ | Any]]) +assert_type(np.outer(_to_1d_float, _to_1d_float), np.ndarray[tuple[int, int], np.dtype[np.float64 | Any]]) +assert_type(np.outer(_to_1d_complex, _to_1d_complex), np.ndarray[tuple[int, int], np.dtype[np.complex128 | Any]]) + +# tensordot +assert_type(np.tensordot(AR_i8, AR_i8), npt.NDArray[np.int64]) +assert_type(np.tensordot(AR_b, AR_b), npt.NDArray[np.bool]) +assert_type(np.tensordot(AR_u8, AR_u8), npt.NDArray[np.uint64]) +assert_type(np.tensordot(AR_i8, AR_i8), npt.NDArray[np.int64]) +assert_type(np.tensordot(AR_f8, AR_f8), npt.NDArray[np.float64]) +assert_type(np.tensordot(AR_f8, AR_i8), npt.NDArray[np.float64 | Any]) +assert_type(np.tensordot(AR_c16, AR_c16), npt.NDArray[np.complex128]) +assert_type(np.tensordot(AR_c16, AR_f8), npt.NDArray[np.complex128 | Any]) +assert_type(np.tensordot(AR_m, AR_m), npt.NDArray[np.timedelta64]) +assert_type(np.tensordot(AR_O, AR_O), npt.NDArray[np.object_]) +assert_type(np.tensordot(_to_1d_bool, _to_1d_bool), npt.NDArray[np.bool]) +assert_type(np.tensordot(_to_1d_int, _to_1d_int), npt.NDArray[np.int_ | Any]) +assert_type(np.tensordot(_to_1d_float, _to_1d_float), npt.NDArray[np.float64 | Any]) +assert_type(np.tensordot(_to_1d_complex, _to_1d_complex), npt.NDArray[np.complex128 | Any]) + +# cross +assert_type(np.cross(AR_i8, AR_i8), npt.NDArray[np.int64]) +assert_type(np.cross(AR_u8, AR_u8), npt.NDArray[np.uint64]) +assert_type(np.cross(AR_i8, AR_i8), npt.NDArray[np.int64]) +assert_type(np.cross(AR_f8, AR_f8), npt.NDArray[np.float64]) +assert_type(np.cross(AR_f8, AR_i8), npt.NDArray[np.float64 | Any]) +assert_type(np.cross(AR_c16, AR_c16), npt.NDArray[np.complex128]) +assert_type(np.cross(AR_c16, AR_f8), npt.NDArray[np.complex128 | Any]) +assert_type(np.cross(AR_m, AR_m), npt.NDArray[np.timedelta64]) +assert_type(np.cross(AR_O, AR_O), npt.NDArray[np.object_]) +assert_type(np.cross(_to_1d_int, _to_1d_int), npt.NDArray[np.int_ | Any]) +assert_type(np.cross(_to_1d_float, _to_1d_float), npt.NDArray[np.float64 | Any]) +assert_type(np.cross(_to_1d_complex, _to_1d_complex), npt.NDArray[np.complex128 | Any]) + +assert_type(np.isscalar(i8), bool) +assert_type(np.isscalar(AR_i8), bool) +assert_type(np.isscalar(_to_1d_int), bool) + +assert_type(np.roll(AR_i8, 1), npt.NDArray[np.int64]) +assert_type(np.roll(AR_i8, (1, 2)), npt.NDArray[np.int64]) +assert_type(np.roll(_to_1d_int, 1), npt.NDArray[Any]) + +assert_type(np.rollaxis(AR_i8, 0, 1), npt.NDArray[np.int64]) + +assert_type(np.moveaxis(AR_i8, 0, 1), npt.NDArray[np.int64]) +assert_type(np.moveaxis(AR_i8, (0, 1), (1, 2)), npt.NDArray[np.int64]) + +assert_type(np.indices([0, 1, 2]), npt.NDArray[np.int_]) +assert_type(np.indices([0, 1, 2], sparse=True), tuple[npt.NDArray[np.int_], ...]) +assert_type(np.indices([0, 1, 2], dtype=np.float64), npt.NDArray[np.float64]) +assert_type(np.indices([0, 1, 2], sparse=True, dtype=np.float64), tuple[npt.NDArray[np.float64], ...]) +assert_type(np.indices([0, 1, 2], dtype=float), npt.NDArray[Any]) +assert_type(np.indices([0, 1, 2], sparse=True, dtype=float), tuple[npt.NDArray[Any], ...]) + +assert_type(np.binary_repr(1), str) + +assert_type(np.base_repr(1), str) + +assert_type(np.allclose(i8, AR_i8), bool) +assert_type(np.allclose(_to_1d_int, AR_i8), bool) +assert_type(np.allclose(AR_i8, AR_i8), bool) + +assert_type(np.isclose(i8, i8), np.bool) +assert_type(np.isclose(i8, AR_i8), npt.NDArray[np.bool]) +assert_type(np.isclose(_to_1d_int, _to_1d_int), np.ndarray[tuple[int], np.dtype[np.bool]]) +assert_type(np.isclose(AR_i8, AR_i8), npt.NDArray[np.bool]) + +assert_type(np.array_equal(i8, AR_i8), bool) +assert_type(np.array_equal(_to_1d_int, AR_i8), bool) +assert_type(np.array_equal(AR_i8, AR_i8), bool) + +assert_type(np.array_equiv(i8, AR_i8), bool) +assert_type(np.array_equiv(_to_1d_int, AR_i8), bool) +assert_type(np.array_equiv(AR_i8, AR_i8), bool) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/numerictypes.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/numerictypes.pyi new file mode 100644 index 0000000000000000000000000000000000000000..75d108ce5a0ffb3fdbd6cf4c4712909298ad5780 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/numerictypes.pyi @@ -0,0 +1,16 @@ +from typing import Literal, assert_type + +import numpy as np + +assert_type(np.ScalarType[0], type[int]) +assert_type(np.ScalarType[3], type[bool]) +assert_type(np.ScalarType[8], type[np.complex64]) +assert_type(np.ScalarType[9], type[np.complex128]) +assert_type(np.ScalarType[-1], type[np.void]) +assert_type(np.bool_(object()), np.bool) + +assert_type(np.typecodes["Character"], Literal["c"]) +assert_type(np.typecodes["Complex"], Literal["FDG"]) +assert_type(np.typecodes["All"], Literal["?bhilqnpBHILQNPefdgFDGSUVOMm"]) + +assert_type(np.sctypeDict["uint8"], type[np.generic]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/polynomial_polybase.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/polynomial_polybase.pyi new file mode 100644 index 0000000000000000000000000000000000000000..4c4899ad6308722b14ac67d1585c2b77b58755f6 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/polynomial_polybase.pyi @@ -0,0 +1,217 @@ +from collections.abc import Sequence +from decimal import Decimal +from typing import Any, Literal as L, TypeAlias, TypeVar, assert_type + +import numpy as np +import numpy.polynomial as npp +import numpy.typing as npt + +_Ar_x: TypeAlias = npt.NDArray[np.inexact | np.object_] +_Ar_f: TypeAlias = npt.NDArray[np.floating] +_Ar_c: TypeAlias = npt.NDArray[np.complexfloating] +_Ar_O: TypeAlias = npt.NDArray[np.object_] + +_Ar_x_n: TypeAlias = np.ndarray[tuple[int], np.dtype[np.inexact | np.object_]] +_Ar_f_n: TypeAlias = np.ndarray[tuple[int], np.dtype[np.floating]] +_Ar_c_n: TypeAlias = np.ndarray[tuple[int], np.dtype[np.complexfloating]] +_Ar_O_n: TypeAlias = np.ndarray[tuple[int], np.dtype[np.object_]] + +_Ar_x_2: TypeAlias = np.ndarray[tuple[L[2]], np.dtype[np.float64 | Any]] +_Ar_f_2: TypeAlias = np.ndarray[tuple[L[2]], np.dtype[np.floating]] +_Ar_c_2: TypeAlias = np.ndarray[tuple[L[2]], np.dtype[np.complexfloating]] +_Ar_O_2: TypeAlias = np.ndarray[tuple[L[2]], np.dtype[np.object_]] + +_ScalarT = TypeVar("_ScalarT", bound=np.generic) +_Ar_1d: TypeAlias = np.ndarray[tuple[int], np.dtype[_ScalarT]] + +_BasisName: TypeAlias = L["X"] + +SC_i: np.int_ +SC_i_co: int | np.int_ +SC_f: np.float64 +SC_f_co: float | np.float64 | np.int_ +SC_c: np.complex128 +SC_c_co: complex | np.complex128 +SC_O: Decimal + +AR_i: npt.NDArray[np.int_] +AR_f: npt.NDArray[np.float64] +AR_f_co: npt.NDArray[np.float64] | npt.NDArray[np.int_] +AR_c: npt.NDArray[np.complex128] +AR_c_co: npt.NDArray[np.complex128] | npt.NDArray[np.float64] | npt.NDArray[np.int_] +AR_O: npt.NDArray[np.object_] +AR_O_co: npt.NDArray[np.object_ | np.number] + +SQ_i: Sequence[int] +SQ_f: Sequence[float] +SQ_c: Sequence[complex] +SQ_O: Sequence[Decimal] + +PS_poly: npp.Polynomial +PS_cheb: npp.Chebyshev +PS_herm: npp.Hermite +PS_herme: npp.HermiteE +PS_lag: npp.Laguerre +PS_leg: npp.Legendre +PS_all: ( + npp.Polynomial + | npp.Chebyshev + | npp.Hermite + | npp.HermiteE + | npp.Laguerre + | npp.Legendre +) + +# static- and classmethods + +assert_type(type(PS_poly).basis_name, None) +assert_type(type(PS_cheb).basis_name, L["T"]) +assert_type(type(PS_herm).basis_name, L["H"]) +assert_type(type(PS_herme).basis_name, L["He"]) +assert_type(type(PS_lag).basis_name, L["L"]) +assert_type(type(PS_leg).basis_name, L["P"]) + +assert_type(type(PS_all).__hash__, None) +assert_type(type(PS_all).__array_ufunc__, None) +assert_type(type(PS_all).maxpower, L[100]) + +assert_type(type(PS_poly).fromroots(SC_i), npp.Polynomial) +assert_type(type(PS_poly).fromroots(SQ_i), npp.Polynomial) +assert_type(type(PS_poly).fromroots(AR_i), npp.Polynomial) +assert_type(type(PS_cheb).fromroots(SC_f), npp.Chebyshev) +assert_type(type(PS_cheb).fromroots(SQ_f), npp.Chebyshev) +assert_type(type(PS_cheb).fromroots(AR_f_co), npp.Chebyshev) +assert_type(type(PS_herm).fromroots(SC_c), npp.Hermite) +assert_type(type(PS_herm).fromroots(SQ_c), npp.Hermite) +assert_type(type(PS_herm).fromroots(AR_c_co), npp.Hermite) +assert_type(type(PS_leg).fromroots(SC_O), npp.Legendre) +assert_type(type(PS_leg).fromroots(SQ_O), npp.Legendre) +assert_type(type(PS_leg).fromroots(AR_O_co), npp.Legendre) + +assert_type(type(PS_poly).identity(), npp.Polynomial) +assert_type(type(PS_cheb).identity(symbol="z"), npp.Chebyshev) + +assert_type(type(PS_lag).basis(SC_i), npp.Laguerre) +assert_type(type(PS_leg).basis(32, symbol="u"), npp.Legendre) + +assert_type(type(PS_herm).cast(PS_poly), npp.Hermite) +assert_type(type(PS_herme).cast(PS_leg), npp.HermiteE) + +# attributes / properties + +assert_type(PS_all.coef, _Ar_x_n) +assert_type(PS_all.domain, _Ar_x_2) +assert_type(PS_all.window, _Ar_x_2) +assert_type(PS_all.symbol, str) + +# instance methods + +assert_type(PS_all.has_samecoef(PS_all), bool) +assert_type(PS_all.has_samedomain(PS_all), bool) +assert_type(PS_all.has_samewindow(PS_all), bool) +assert_type(PS_all.has_sametype(PS_all), bool) +assert_type(PS_poly.has_sametype(PS_poly), bool) +assert_type(PS_poly.has_sametype(PS_leg), bool) +assert_type(PS_poly.has_sametype(NotADirectoryError), bool) + +assert_type(PS_poly.copy(), npp.Polynomial) +assert_type(PS_cheb.copy(), npp.Chebyshev) +assert_type(PS_herm.copy(), npp.Hermite) +assert_type(PS_herme.copy(), npp.HermiteE) +assert_type(PS_lag.copy(), npp.Laguerre) +assert_type(PS_leg.copy(), npp.Legendre) + +assert_type(PS_leg.cutdeg(3), npp.Legendre) +assert_type(PS_leg.trim(), npp.Legendre) +assert_type(PS_leg.trim(tol=SC_f_co), npp.Legendre) +assert_type(PS_leg.truncate(SC_i_co), npp.Legendre) + +assert_type(PS_all.convert(None, npp.Chebyshev), npp.Chebyshev) +assert_type(PS_all.convert((0, 1), npp.Laguerre), npp.Laguerre) +assert_type(PS_all.convert([0, 1], npp.Hermite, [-1, 1]), npp.Hermite) + +assert_type(PS_all.degree(), int) +assert_type(PS_all.mapparms(), tuple[Any, Any]) + +assert_type(PS_poly.integ(), npp.Polynomial) +assert_type(PS_herme.integ(SC_i_co), npp.HermiteE) +assert_type(PS_lag.integ(SC_i_co, SC_f_co), npp.Laguerre) +assert_type(PS_poly.deriv(), npp.Polynomial) +assert_type(PS_herm.deriv(SC_i_co), npp.Hermite) + +assert_type(PS_poly.roots(), _Ar_x_n) + +assert_type( + PS_poly.linspace(), + tuple[_Ar_1d[np.float64 | np.complex128], _Ar_1d[np.float64 | np.complex128]], +) + +assert_type( + PS_poly.linspace(9), + tuple[_Ar_1d[np.float64 | np.complex128], _Ar_1d[np.float64 | np.complex128]], +) + +assert_type(PS_cheb.fit(AR_c_co, AR_c_co, SC_i_co), npp.Chebyshev) +assert_type(PS_leg.fit(AR_c_co, AR_c_co, AR_i), npp.Legendre) +assert_type(PS_herm.fit(AR_c_co, AR_c_co, SQ_i), npp.Hermite) +assert_type(PS_poly.fit(AR_c_co, SQ_c, SQ_i), npp.Polynomial) +assert_type(PS_lag.fit(SQ_c, SQ_c, SQ_i, full=False), npp.Laguerre) +assert_type( + PS_herme.fit(SQ_c, AR_c_co, SC_i_co, full=True), + tuple[npp.HermiteE, Sequence[np.inexact | np.int32]], +) + +# custom operations + +assert_type(PS_all.__hash__, None) +assert_type(PS_all.__array_ufunc__, None) + +assert_type(str(PS_all), str) +assert_type(repr(PS_all), str) +assert_type(format(PS_all), str) + +assert_type(len(PS_all), int) +assert_type(next(iter(PS_all)), np.float64 | Any) + +assert_type(PS_all(SC_f_co), np.float64 | Any) +assert_type(PS_all(SC_c_co), np.complex128 | Any) +assert_type(PS_all(Decimal()), np.float64 | Any) +assert_type(PS_poly(SQ_f), npt.NDArray[np.float64 | Any]) +assert_type(PS_poly(SQ_c), npt.NDArray[np.complex128 | Any]) +assert_type(PS_poly(SQ_O), npt.NDArray[np.object_]) +assert_type(PS_poly(AR_f), npt.NDArray[np.float64 | Any]) +assert_type(PS_poly(AR_c), npt.NDArray[np.complex128 | Any]) +assert_type(PS_poly(AR_O), npt.NDArray[np.object_]) +assert_type(PS_all(PS_poly), npp.Polynomial) + +assert_type(PS_poly == PS_poly, bool) +assert_type(PS_poly != PS_poly, bool) + +assert_type(-PS_poly, npp.Polynomial) +assert_type(+PS_poly, npp.Polynomial) + +assert_type(PS_poly + 5, npp.Polynomial) +assert_type(PS_poly - 5, npp.Polynomial) +assert_type(PS_poly * 5, npp.Polynomial) +assert_type(PS_poly / 5, npp.Polynomial) +assert_type(PS_poly // 5, npp.Polynomial) +assert_type(PS_poly % 5, npp.Polynomial) + +assert_type(PS_poly + PS_leg, npp.Polynomial) +assert_type(PS_poly - PS_leg, npp.Polynomial) +assert_type(PS_poly * PS_leg, npp.Polynomial) +assert_type(PS_poly / PS_leg, npp.Polynomial) +assert_type(PS_poly // PS_leg, npp.Polynomial) +assert_type(PS_poly % PS_leg, npp.Polynomial) + +assert_type(5 + PS_poly, npp.Polynomial) +assert_type(5 - PS_poly, npp.Polynomial) +assert_type(5 * PS_poly, npp.Polynomial) +assert_type(5 / PS_poly, npp.Polynomial) +assert_type(5 // PS_poly, npp.Polynomial) +assert_type(5 % PS_poly, npp.Polynomial) +assert_type(divmod(PS_poly, 5), tuple[npp.Polynomial, npp.Polynomial]) +assert_type(divmod(5, PS_poly), tuple[npp.Polynomial, npp.Polynomial]) + +assert_type(PS_poly**1, npp.Polynomial) +assert_type(PS_poly**1.0, npp.Polynomial) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/polynomial_polyutils.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/polynomial_polyutils.pyi new file mode 100644 index 0000000000000000000000000000000000000000..07d6c9d1af65805fbf0a9cebfb77e552fdb02ead --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/polynomial_polyutils.pyi @@ -0,0 +1,218 @@ +from collections.abc import Sequence +from decimal import Decimal +from fractions import Fraction +from typing import Literal as L, TypeAlias, assert_type + +import numpy as np +import numpy.polynomial.polyutils as pu +import numpy.typing as npt +from numpy.polynomial._polytypes import _Tuple2 + +_ArrFloat1D: TypeAlias = np.ndarray[tuple[int], np.dtype[np.floating]] +_ArrComplex1D: TypeAlias = np.ndarray[tuple[int], np.dtype[np.complexfloating]] +_ArrObject1D: TypeAlias = np.ndarray[tuple[int], np.dtype[np.object_]] + +_ArrFloat1D_2: TypeAlias = np.ndarray[tuple[L[2]], np.dtype[np.float64]] +_ArrComplex1D_2: TypeAlias = np.ndarray[tuple[L[2]], np.dtype[np.complex128]] +_ArrObject1D_2: TypeAlias = np.ndarray[tuple[L[2]], np.dtype[np.object_]] + +num_int: int +num_float: float +num_complex: complex +# will result in an `object_` dtype +num_object: Decimal | Fraction + +sct_int: np.int_ +sct_float: np.float64 +sct_complex: np.complex128 +sct_object: np.object_ # doesn't exist at runtime + +arr_int: npt.NDArray[np.int_] +arr_float: npt.NDArray[np.float64] +arr_complex: npt.NDArray[np.complex128] +arr_object: npt.NDArray[np.object_] + +seq_num_int: Sequence[int] +seq_num_float: Sequence[float] +seq_num_complex: Sequence[complex] +seq_num_object: Sequence[Decimal | Fraction] + +seq_sct_int: Sequence[np.int_] +seq_sct_float: Sequence[np.float64] +seq_sct_complex: Sequence[np.complex128] +seq_sct_object: Sequence[np.object_] + +seq_arr_int: Sequence[npt.NDArray[np.int_]] +seq_arr_float: Sequence[npt.NDArray[np.float64]] +seq_arr_complex: Sequence[npt.NDArray[np.complex128]] +seq_arr_object: Sequence[npt.NDArray[np.object_]] + +seq_seq_num_int: Sequence[Sequence[int]] +seq_seq_num_float: Sequence[Sequence[float]] +seq_seq_num_complex: Sequence[Sequence[complex]] +seq_seq_num_object: Sequence[Sequence[Decimal | Fraction]] + +seq_seq_sct_int: Sequence[Sequence[np.int_]] +seq_seq_sct_float: Sequence[Sequence[np.float64]] +seq_seq_sct_complex: Sequence[Sequence[np.complex128]] +seq_seq_sct_object: Sequence[Sequence[np.object_]] # doesn't exist at runtime + +# as_series + +assert_type(pu.as_series(arr_int), list[_ArrFloat1D]) +assert_type(pu.as_series(arr_float), list[_ArrFloat1D]) +assert_type(pu.as_series(arr_complex), list[_ArrComplex1D]) +assert_type(pu.as_series(arr_object), list[_ArrObject1D]) + +assert_type(pu.as_series(seq_num_int), list[_ArrFloat1D]) +assert_type(pu.as_series(seq_num_float), list[_ArrFloat1D]) +assert_type(pu.as_series(seq_num_complex), list[_ArrComplex1D]) +assert_type(pu.as_series(seq_num_object), list[_ArrObject1D]) + +assert_type(pu.as_series(seq_sct_int), list[_ArrFloat1D]) +assert_type(pu.as_series(seq_sct_float), list[_ArrFloat1D]) +assert_type(pu.as_series(seq_sct_complex), list[_ArrComplex1D]) +assert_type(pu.as_series(seq_sct_object), list[_ArrObject1D]) + +assert_type(pu.as_series(seq_arr_int), list[_ArrFloat1D]) +assert_type(pu.as_series(seq_arr_float), list[_ArrFloat1D]) +assert_type(pu.as_series(seq_arr_complex), list[_ArrComplex1D]) +assert_type(pu.as_series(seq_arr_object), list[_ArrObject1D]) + +assert_type(pu.as_series(seq_seq_num_int), list[_ArrFloat1D]) +assert_type(pu.as_series(seq_seq_num_float), list[_ArrFloat1D]) +assert_type(pu.as_series(seq_seq_num_complex), list[_ArrComplex1D]) +assert_type(pu.as_series(seq_seq_num_object), list[_ArrObject1D]) + +assert_type(pu.as_series(seq_seq_sct_int), list[_ArrFloat1D]) +assert_type(pu.as_series(seq_seq_sct_float), list[_ArrFloat1D]) +assert_type(pu.as_series(seq_seq_sct_complex), list[_ArrComplex1D]) +assert_type(pu.as_series(seq_seq_sct_object), list[_ArrObject1D]) + +# trimcoef + +assert_type(pu.trimcoef(num_int), _ArrFloat1D) +assert_type(pu.trimcoef(num_float), _ArrFloat1D) +assert_type(pu.trimcoef(num_complex), _ArrComplex1D) +assert_type(pu.trimcoef(num_object), _ArrObject1D) +assert_type(pu.trimcoef(num_object), _ArrObject1D) + +assert_type(pu.trimcoef(sct_int), _ArrFloat1D) +assert_type(pu.trimcoef(sct_float), _ArrFloat1D) +assert_type(pu.trimcoef(sct_complex), _ArrComplex1D) +assert_type(pu.trimcoef(sct_object), _ArrObject1D) + +assert_type(pu.trimcoef(arr_int), _ArrFloat1D) +assert_type(pu.trimcoef(arr_float), _ArrFloat1D) +assert_type(pu.trimcoef(arr_complex), _ArrComplex1D) +assert_type(pu.trimcoef(arr_object), _ArrObject1D) + +assert_type(pu.trimcoef(seq_num_int), _ArrFloat1D) +assert_type(pu.trimcoef(seq_num_float), _ArrFloat1D) +assert_type(pu.trimcoef(seq_num_complex), _ArrComplex1D) +assert_type(pu.trimcoef(seq_num_object), _ArrObject1D) + +assert_type(pu.trimcoef(seq_sct_int), _ArrFloat1D) +assert_type(pu.trimcoef(seq_sct_float), _ArrFloat1D) +assert_type(pu.trimcoef(seq_sct_complex), _ArrComplex1D) +assert_type(pu.trimcoef(seq_sct_object), _ArrObject1D) + +# getdomain + +assert_type(pu.getdomain(num_int), _ArrFloat1D_2) +assert_type(pu.getdomain(num_float), _ArrFloat1D_2) +assert_type(pu.getdomain(num_complex), _ArrComplex1D_2) +assert_type(pu.getdomain(num_object), _ArrObject1D_2) +assert_type(pu.getdomain(num_object), _ArrObject1D_2) + +assert_type(pu.getdomain(sct_int), _ArrFloat1D_2) +assert_type(pu.getdomain(sct_float), _ArrFloat1D_2) +assert_type(pu.getdomain(sct_complex), _ArrComplex1D_2) +assert_type(pu.getdomain(sct_object), _ArrObject1D_2) + +assert_type(pu.getdomain(arr_int), _ArrFloat1D_2) +assert_type(pu.getdomain(arr_float), _ArrFloat1D_2) +assert_type(pu.getdomain(arr_complex), _ArrComplex1D_2) +assert_type(pu.getdomain(arr_object), _ArrObject1D_2) + +assert_type(pu.getdomain(seq_num_int), _ArrFloat1D_2) +assert_type(pu.getdomain(seq_num_float), _ArrFloat1D_2) +assert_type(pu.getdomain(seq_num_complex), _ArrComplex1D_2) +assert_type(pu.getdomain(seq_num_object), _ArrObject1D_2) + +assert_type(pu.getdomain(seq_sct_int), _ArrFloat1D_2) +assert_type(pu.getdomain(seq_sct_float), _ArrFloat1D_2) +assert_type(pu.getdomain(seq_sct_complex), _ArrComplex1D_2) +assert_type(pu.getdomain(seq_sct_object), _ArrObject1D_2) + +# mapparms + +assert_type(pu.mapparms(seq_num_int, seq_num_int), _Tuple2[float]) +assert_type(pu.mapparms(seq_num_int, seq_num_float), _Tuple2[float]) +assert_type(pu.mapparms(seq_num_float, seq_num_float), _Tuple2[float]) +assert_type(pu.mapparms(seq_num_float, seq_num_complex), _Tuple2[complex]) +assert_type(pu.mapparms(seq_num_complex, seq_num_complex), _Tuple2[complex]) +assert_type(pu.mapparms(seq_num_complex, seq_num_object), _Tuple2[object]) +assert_type(pu.mapparms(seq_num_object, seq_num_object), _Tuple2[object]) + +assert_type(pu.mapparms(seq_sct_int, seq_sct_int), _Tuple2[np.floating]) +assert_type(pu.mapparms(seq_sct_int, seq_sct_float), _Tuple2[np.floating]) +assert_type(pu.mapparms(seq_sct_float, seq_sct_float), _Tuple2[float]) +assert_type(pu.mapparms(seq_sct_float, seq_sct_complex), _Tuple2[complex]) +assert_type(pu.mapparms(seq_sct_complex, seq_sct_complex), _Tuple2[complex]) +assert_type(pu.mapparms(seq_sct_complex, seq_sct_object), _Tuple2[object]) +assert_type(pu.mapparms(seq_sct_object, seq_sct_object), _Tuple2[object]) + +assert_type(pu.mapparms(arr_int, arr_int), _Tuple2[np.floating]) +assert_type(pu.mapparms(arr_int, arr_float), _Tuple2[np.floating]) +assert_type(pu.mapparms(arr_float, arr_float), _Tuple2[np.floating]) +assert_type(pu.mapparms(arr_float, arr_complex), _Tuple2[np.complexfloating]) +assert_type(pu.mapparms(arr_complex, arr_complex), _Tuple2[np.complexfloating]) +assert_type(pu.mapparms(arr_complex, arr_object), _Tuple2[object]) +assert_type(pu.mapparms(arr_object, arr_object), _Tuple2[object]) + +# mapdomain + +assert_type(pu.mapdomain(num_int, seq_num_int, seq_num_int), np.floating) +assert_type(pu.mapdomain(num_int, seq_num_int, seq_num_float), np.floating) +assert_type(pu.mapdomain(num_int, seq_num_float, seq_num_float), np.floating) +assert_type(pu.mapdomain(num_float, seq_num_float, seq_num_float), np.floating) +assert_type(pu.mapdomain(num_float, seq_num_float, seq_num_complex), np.complexfloating) +assert_type(pu.mapdomain(num_float, seq_num_complex, seq_num_complex), np.complexfloating) +assert_type(pu.mapdomain(num_complex, seq_num_complex, seq_num_complex), np.complexfloating) +assert_type(pu.mapdomain(num_complex, seq_num_complex, seq_num_object), object) +assert_type(pu.mapdomain(num_complex, seq_num_object, seq_num_object), object) +assert_type(pu.mapdomain(num_object, seq_num_object, seq_num_object), object) + +assert_type(pu.mapdomain(seq_num_int, seq_num_int, seq_num_int), _ArrFloat1D) +assert_type(pu.mapdomain(seq_num_int, seq_num_int, seq_num_float), _ArrFloat1D) +assert_type(pu.mapdomain(seq_num_int, seq_num_float, seq_num_float), _ArrFloat1D) +assert_type(pu.mapdomain(seq_num_float, seq_num_float, seq_num_float), _ArrFloat1D) +assert_type(pu.mapdomain(seq_num_float, seq_num_float, seq_num_complex), _ArrComplex1D) +assert_type(pu.mapdomain(seq_num_float, seq_num_complex, seq_num_complex), _ArrComplex1D) +assert_type(pu.mapdomain(seq_num_complex, seq_num_complex, seq_num_complex), _ArrComplex1D) +assert_type(pu.mapdomain(seq_num_complex, seq_num_complex, seq_num_object), _ArrObject1D) +assert_type(pu.mapdomain(seq_num_complex, seq_num_object, seq_num_object), _ArrObject1D) +assert_type(pu.mapdomain(seq_num_object, seq_num_object, seq_num_object), _ArrObject1D) + +assert_type(pu.mapdomain(seq_sct_int, seq_sct_int, seq_sct_int), _ArrFloat1D) +assert_type(pu.mapdomain(seq_sct_int, seq_sct_int, seq_sct_float), _ArrFloat1D) +assert_type(pu.mapdomain(seq_sct_int, seq_sct_float, seq_sct_float), _ArrFloat1D) +assert_type(pu.mapdomain(seq_sct_float, seq_sct_float, seq_sct_float), _ArrFloat1D) +assert_type(pu.mapdomain(seq_sct_float, seq_sct_float, seq_sct_complex), _ArrComplex1D) +assert_type(pu.mapdomain(seq_sct_float, seq_sct_complex, seq_sct_complex), _ArrComplex1D) +assert_type(pu.mapdomain(seq_sct_complex, seq_sct_complex, seq_sct_complex), _ArrComplex1D) +assert_type(pu.mapdomain(seq_sct_complex, seq_sct_complex, seq_sct_object), _ArrObject1D) +assert_type(pu.mapdomain(seq_sct_complex, seq_sct_object, seq_sct_object), _ArrObject1D) +assert_type(pu.mapdomain(seq_sct_object, seq_sct_object, seq_sct_object), _ArrObject1D) + +assert_type(pu.mapdomain(arr_int, arr_int, arr_int), _ArrFloat1D) +assert_type(pu.mapdomain(arr_int, arr_int, arr_float), _ArrFloat1D) +assert_type(pu.mapdomain(arr_int, arr_float, arr_float), _ArrFloat1D) +assert_type(pu.mapdomain(arr_float, arr_float, arr_float), _ArrFloat1D) +assert_type(pu.mapdomain(arr_float, arr_float, arr_complex), _ArrComplex1D) +assert_type(pu.mapdomain(arr_float, arr_complex, arr_complex), _ArrComplex1D) +assert_type(pu.mapdomain(arr_complex, arr_complex, arr_complex), _ArrComplex1D) +assert_type(pu.mapdomain(arr_complex, arr_complex, arr_object), _ArrObject1D) +assert_type(pu.mapdomain(arr_complex, arr_object, arr_object), _ArrObject1D) +assert_type(pu.mapdomain(arr_object, arr_object, arr_object), _ArrObject1D) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/polynomial_series.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/polynomial_series.pyi new file mode 100644 index 0000000000000000000000000000000000000000..3188ad9a123909449fb9f007035f243d8eba8b86 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/polynomial_series.pyi @@ -0,0 +1,138 @@ +from collections.abc import Sequence +from typing import Any, TypeAlias, assert_type + +import numpy as np +import numpy.polynomial as npp +import numpy.typing as npt + +_ArrFloat1D: TypeAlias = np.ndarray[tuple[int], np.dtype[np.floating]] +_ArrFloat1D64: TypeAlias = np.ndarray[tuple[int], np.dtype[np.float64]] +_ArrComplex1D: TypeAlias = np.ndarray[tuple[int], np.dtype[np.complexfloating]] +_ArrComplex1D128: TypeAlias = np.ndarray[tuple[int], np.dtype[np.complex128]] +_ArrObject1D: TypeAlias = np.ndarray[tuple[int], np.dtype[np.object_]] + +AR_b: npt.NDArray[np.bool] +AR_u4: npt.NDArray[np.uint32] +AR_i8: npt.NDArray[np.int64] +AR_f8: npt.NDArray[np.float64] +AR_c16: npt.NDArray[np.complex128] +AR_O: npt.NDArray[np.object_] + +PS_poly: npp.Polynomial +PS_cheb: npp.Chebyshev + +assert_type(npp.polynomial.polyroots(AR_f8), _ArrFloat1D64) +assert_type(npp.polynomial.polyroots(AR_c16), _ArrComplex1D128) +assert_type(npp.polynomial.polyroots(AR_O), _ArrObject1D) + +assert_type(npp.polynomial.polyfromroots(AR_f8), _ArrFloat1D) +assert_type(npp.polynomial.polyfromroots(AR_c16), _ArrComplex1D) +assert_type(npp.polynomial.polyfromroots(AR_O), _ArrObject1D) + +# assert_type(npp.polynomial.polyadd(AR_b, AR_b), NoReturn) +assert_type(npp.polynomial.polyadd(AR_u4, AR_b), _ArrFloat1D) +assert_type(npp.polynomial.polyadd(AR_i8, AR_i8), _ArrFloat1D) +assert_type(npp.polynomial.polyadd(AR_f8, AR_i8), _ArrFloat1D) +assert_type(npp.polynomial.polyadd(AR_i8, AR_c16), _ArrComplex1D) +assert_type(npp.polynomial.polyadd(AR_O, AR_O), _ArrObject1D) + +assert_type(npp.polynomial.polymulx(AR_u4), _ArrFloat1D) +assert_type(npp.polynomial.polymulx(AR_i8), _ArrFloat1D) +assert_type(npp.polynomial.polymulx(AR_f8), _ArrFloat1D) +assert_type(npp.polynomial.polymulx(AR_c16), _ArrComplex1D) +assert_type(npp.polynomial.polymulx(AR_O), _ArrObject1D) + +assert_type(npp.polynomial.polypow(AR_u4, 2), _ArrFloat1D) +assert_type(npp.polynomial.polypow(AR_i8, 2), _ArrFloat1D) +assert_type(npp.polynomial.polypow(AR_f8, 2), _ArrFloat1D) +assert_type(npp.polynomial.polypow(AR_c16, 2), _ArrComplex1D) +assert_type(npp.polynomial.polypow(AR_O, 2), _ArrObject1D) + +# assert_type(npp.polynomial.polyder(PS_poly), npt.NDArray[np.object_]) +assert_type(npp.polynomial.polyder(AR_f8), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyder(AR_c16), npt.NDArray[np.complexfloating]) +assert_type(npp.polynomial.polyder(AR_O, m=2), npt.NDArray[np.object_]) + +# assert_type(npp.polynomial.polyint(PS_poly), npt.NDArray[np.object_]) +assert_type(npp.polynomial.polyint(AR_f8), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyint(AR_f8, k=AR_c16), npt.NDArray[np.complexfloating]) +assert_type(npp.polynomial.polyint(AR_O, m=2), npt.NDArray[np.object_]) + +assert_type(npp.polynomial.polyval(AR_b, AR_b), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyval(AR_u4, AR_b), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyval(AR_i8, AR_i8), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyval(AR_f8, AR_i8), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyval(AR_i8, AR_c16), npt.NDArray[np.complexfloating]) +assert_type(npp.polynomial.polyval(AR_O, AR_O), npt.NDArray[np.object_]) + +assert_type(npp.polynomial.polyval2d(AR_b, AR_b, AR_b), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyval2d(AR_u4, AR_u4, AR_b), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyval2d(AR_i8, AR_i8, AR_i8), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyval2d(AR_f8, AR_f8, AR_i8), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyval2d(AR_i8, AR_i8, AR_c16), npt.NDArray[np.complexfloating]) +assert_type(npp.polynomial.polyval2d(AR_O, AR_O, AR_O), npt.NDArray[np.object_]) + +assert_type(npp.polynomial.polyval3d(AR_b, AR_b, AR_b, AR_b), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyval3d(AR_u4, AR_u4, AR_u4, AR_b), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyval3d(AR_i8, AR_i8, AR_i8, AR_i8), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyval3d(AR_f8, AR_f8, AR_f8, AR_i8), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyval3d(AR_i8, AR_i8, AR_i8, AR_c16), npt.NDArray[np.complexfloating]) +assert_type(npp.polynomial.polyval3d(AR_O, AR_O, AR_O, AR_O), npt.NDArray[np.object_]) + +assert_type(npp.polynomial.polyvalfromroots(AR_b, AR_b), npt.NDArray[np.float64 | Any]) +assert_type(npp.polynomial.polyvalfromroots(AR_u4, AR_b), npt.NDArray[np.float64 | Any]) +assert_type(npp.polynomial.polyvalfromroots(AR_i8, AR_i8), npt.NDArray[np.float64 | Any]) +assert_type(npp.polynomial.polyvalfromroots(AR_f8, AR_i8), npt.NDArray[np.float64 | Any]) +assert_type(npp.polynomial.polyvalfromroots(AR_i8, AR_c16), npt.NDArray[np.complex128 | Any]) +assert_type(npp.polynomial.polyvalfromroots(AR_O, AR_O), npt.NDArray[np.object_ | Any]) + +assert_type(npp.polynomial.polyvander(AR_f8, 3), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyvander(AR_c16, 3), npt.NDArray[np.complexfloating]) +assert_type(npp.polynomial.polyvander(AR_O, 3), npt.NDArray[np.object_]) + +assert_type(npp.polynomial.polyvander2d(AR_f8, AR_f8, [4, 2]), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyvander2d(AR_c16, AR_c16, [4, 2]), npt.NDArray[np.complexfloating]) +assert_type(npp.polynomial.polyvander2d(AR_O, AR_O, [4, 2]), npt.NDArray[np.object_]) + +assert_type(npp.polynomial.polyvander3d(AR_f8, AR_f8, AR_f8, [4, 3, 2]), npt.NDArray[np.floating]) +assert_type(npp.polynomial.polyvander3d(AR_c16, AR_c16, AR_c16, [4, 3, 2]), npt.NDArray[np.complexfloating]) +assert_type(npp.polynomial.polyvander3d(AR_O, AR_O, AR_O, [4, 3, 2]), npt.NDArray[np.object_]) + +assert_type( + npp.polynomial.polyfit(AR_f8, AR_f8, 2), + npt.NDArray[np.floating], +) +assert_type( + npp.polynomial.polyfit(AR_f8, AR_i8, 1, full=True), + tuple[npt.NDArray[np.floating], Sequence[np.inexact | np.int32]], +) +assert_type( + npp.polynomial.polyfit(AR_c16, AR_f8, 2), + npt.NDArray[np.complexfloating], +) +assert_type( + npp.polynomial.polyfit(AR_f8, AR_c16, 1, full=True)[0], + npt.NDArray[np.complexfloating], +) + +assert_type(npp.chebyshev.chebgauss(2), tuple[_ArrFloat1D64, _ArrFloat1D64]) + +assert_type(npp.chebyshev.chebweight(AR_f8), npt.NDArray[np.float64]) +assert_type(npp.chebyshev.chebweight(AR_c16), npt.NDArray[np.complex128]) +assert_type(npp.chebyshev.chebweight(AR_O), npt.NDArray[np.object_]) + +assert_type(npp.chebyshev.poly2cheb(AR_f8), _ArrFloat1D) +assert_type(npp.chebyshev.poly2cheb(AR_c16), _ArrComplex1D) +assert_type(npp.chebyshev.poly2cheb(AR_O), _ArrObject1D) + +assert_type(npp.chebyshev.cheb2poly(AR_f8), _ArrFloat1D) +assert_type(npp.chebyshev.cheb2poly(AR_c16), _ArrComplex1D) +assert_type(npp.chebyshev.cheb2poly(AR_O), _ArrObject1D) + +assert_type(npp.chebyshev.chebpts1(6), _ArrFloat1D64) +assert_type(npp.chebyshev.chebpts2(6), _ArrFloat1D64) + +assert_type( + npp.chebyshev.chebinterpolate(np.tanh, 3), + npt.NDArray[np.float64 | np.complex128 | np.object_], +) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/random.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/random.pyi new file mode 100644 index 0000000000000000000000000000000000000000..e188eb02893f06faf35b1b5265c83dc24f1d84c9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/random.pyi @@ -0,0 +1,1546 @@ +import threading +from collections.abc import Sequence +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt +from numpy.random._generator import Generator +from numpy.random._mt19937 import MT19937 +from numpy.random._pcg64 import PCG64 +from numpy.random._philox import Philox +from numpy.random._sfc64 import SFC64 +from numpy.random.bit_generator import SeedlessSeedSequence, SeedSequence + +def_rng = np.random.default_rng() +seed_seq = np.random.SeedSequence() +mt19937 = np.random.MT19937() +pcg64 = np.random.PCG64() +sfc64 = np.random.SFC64() +philox = np.random.Philox() +seedless_seq = SeedlessSeedSequence() + +assert_type(def_rng, Generator) +assert_type(mt19937, MT19937) +assert_type(pcg64, PCG64) +assert_type(sfc64, SFC64) +assert_type(philox, Philox) +assert_type(seed_seq, SeedSequence) +assert_type(seedless_seq, SeedlessSeedSequence) + +mt19937_jumped = mt19937.jumped() +mt19937_jumped3 = mt19937.jumped(3) +mt19937_raw = mt19937.random_raw() +mt19937_raw_arr = mt19937.random_raw(5) + +assert_type(mt19937_jumped, MT19937) +assert_type(mt19937_jumped3, MT19937) +assert_type(mt19937_raw, int) +assert_type(mt19937_raw_arr, npt.NDArray[np.uint64]) +assert_type(mt19937.lock, threading.Lock) + +pcg64_jumped = pcg64.jumped() +pcg64_jumped3 = pcg64.jumped(3) +pcg64_adv = pcg64.advance(3) +pcg64_raw = pcg64.random_raw() +pcg64_raw_arr = pcg64.random_raw(5) + +assert_type(pcg64_jumped, PCG64) +assert_type(pcg64_jumped3, PCG64) +assert_type(pcg64_adv, PCG64) +assert_type(pcg64_raw, int) +assert_type(pcg64_raw_arr, npt.NDArray[np.uint64]) +assert_type(pcg64.lock, threading.Lock) + +philox_jumped = philox.jumped() +philox_jumped3 = philox.jumped(3) +philox_adv = philox.advance(3) +philox_raw = philox.random_raw() +philox_raw_arr = philox.random_raw(5) + +assert_type(philox_jumped, Philox) +assert_type(philox_jumped3, Philox) +assert_type(philox_adv, Philox) +assert_type(philox_raw, int) +assert_type(philox_raw_arr, npt.NDArray[np.uint64]) +assert_type(philox.lock, threading.Lock) + +sfc64_raw = sfc64.random_raw() +sfc64_raw_arr = sfc64.random_raw(5) + +assert_type(sfc64_raw, int) +assert_type(sfc64_raw_arr, npt.NDArray[np.uint64]) +assert_type(sfc64.lock, threading.Lock) + +assert_type(seed_seq.pool, npt.NDArray[np.uint32]) +assert_type(seed_seq.entropy, int | Sequence[int] | None) +assert_type(seed_seq.spawn(1), list[np.random.SeedSequence]) +assert_type(seed_seq.generate_state(8, "uint32"), npt.NDArray[np.uint32 | np.uint64]) +assert_type(seed_seq.generate_state(8, "uint64"), npt.NDArray[np.uint32 | np.uint64]) + +def_gen: np.random.Generator = np.random.default_rng() + +D_arr_0p1: npt.NDArray[np.float64] = np.array([0.1]) +D_arr_0p5: npt.NDArray[np.float64] = np.array([0.5]) +D_arr_0p9: npt.NDArray[np.float64] = np.array([0.9]) +D_arr_1p5: npt.NDArray[np.float64] = np.array([1.5]) +I_arr_10: npt.NDArray[np.int_] = np.array([10], dtype=np.int_) +I_arr_20: npt.NDArray[np.int_] = np.array([20], dtype=np.int_) +D_arr_like_0p1: list[float] = [0.1] +D_arr_like_0p5: list[float] = [0.5] +D_arr_like_0p9: list[float] = [0.9] +D_arr_like_1p5: list[float] = [1.5] +I_arr_like_10: list[int] = [10] +I_arr_like_20: list[int] = [20] +D_2D_like: list[list[float]] = [[1, 2], [2, 3], [3, 4], [4, 5.1]] +D_2D: npt.NDArray[np.float64] = np.array(D_2D_like) +S_out: npt.NDArray[np.float32] = np.empty(1, dtype=np.float32) +D_out: npt.NDArray[np.float64] = np.empty(1) + +assert_type(def_gen.standard_normal(), float) +assert_type(def_gen.standard_normal(dtype=np.float32), float) +assert_type(def_gen.standard_normal(dtype="float32"), float) +assert_type(def_gen.standard_normal(dtype="double"), float) +assert_type(def_gen.standard_normal(dtype=np.float64), float) +assert_type(def_gen.standard_normal(size=None), float) +assert_type(def_gen.standard_normal(size=1), npt.NDArray[np.float64]) +assert_type(def_gen.standard_normal(size=1, dtype=np.float32), npt.NDArray[np.float32]) +assert_type(def_gen.standard_normal(size=1, dtype="f4"), npt.NDArray[np.float32]) +assert_type(def_gen.standard_normal(size=1, dtype="float32", out=S_out), npt.NDArray[np.float32]) +assert_type(def_gen.standard_normal(dtype=np.float32, out=S_out), npt.NDArray[np.float32]) +assert_type(def_gen.standard_normal(size=1, dtype=np.float64), npt.NDArray[np.float64]) +assert_type(def_gen.standard_normal(size=1, dtype="float64"), npt.NDArray[np.float64]) +assert_type(def_gen.standard_normal(size=1, dtype="f8"), npt.NDArray[np.float64]) +assert_type(def_gen.standard_normal(out=D_out), npt.NDArray[np.float64]) +assert_type(def_gen.standard_normal(size=1, dtype="float64"), npt.NDArray[np.float64]) +assert_type(def_gen.standard_normal(size=1, dtype="float64", out=D_out), npt.NDArray[np.float64]) + +assert_type(def_gen.random(), float) +assert_type(def_gen.random(dtype=np.float32), float) +assert_type(def_gen.random(dtype="float32"), float) +assert_type(def_gen.random(dtype="double"), float) +assert_type(def_gen.random(dtype=np.float64), float) +assert_type(def_gen.random(size=None), float) +assert_type(def_gen.random(size=1), npt.NDArray[np.float64]) +assert_type(def_gen.random(size=1, dtype=np.float32), npt.NDArray[np.float32]) +assert_type(def_gen.random(size=1, dtype="f4"), npt.NDArray[np.float32]) +assert_type(def_gen.random(size=1, dtype="float32", out=S_out), npt.NDArray[np.float32]) +assert_type(def_gen.random(dtype=np.float32, out=S_out), npt.NDArray[np.float32]) +assert_type(def_gen.random(size=1, dtype=np.float64), npt.NDArray[np.float64]) +assert_type(def_gen.random(size=1, dtype="float64"), npt.NDArray[np.float64]) +assert_type(def_gen.random(size=1, dtype="f8"), npt.NDArray[np.float64]) +assert_type(def_gen.random(out=D_out), npt.NDArray[np.float64]) +assert_type(def_gen.random(size=1, dtype="float64"), npt.NDArray[np.float64]) +assert_type(def_gen.random(size=1, dtype="float64", out=D_out), npt.NDArray[np.float64]) + +assert_type(def_gen.standard_cauchy(), float) +assert_type(def_gen.standard_cauchy(size=None), float) +assert_type(def_gen.standard_cauchy(size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.standard_exponential(), float) +assert_type(def_gen.standard_exponential(method="inv"), float) +assert_type(def_gen.standard_exponential(dtype=np.float32), float) +assert_type(def_gen.standard_exponential(dtype="float32"), float) +assert_type(def_gen.standard_exponential(dtype="double"), float) +assert_type(def_gen.standard_exponential(dtype=np.float64), float) +assert_type(def_gen.standard_exponential(size=None), float) +assert_type(def_gen.standard_exponential(size=None, method="inv"), float) +assert_type(def_gen.standard_exponential(size=1, method="inv"), npt.NDArray[np.float64]) +assert_type(def_gen.standard_exponential(size=1, dtype=np.float32), npt.NDArray[np.float32]) +assert_type(def_gen.standard_exponential(size=1, dtype="f4", method="inv"), npt.NDArray[np.float32]) +assert_type(def_gen.standard_exponential(size=1, dtype="float32", out=S_out), npt.NDArray[np.float32]) +assert_type(def_gen.standard_exponential(dtype=np.float32, out=S_out), npt.NDArray[np.float32]) +assert_type(def_gen.standard_exponential(size=1, dtype=np.float64, method="inv"), npt.NDArray[np.float64]) +assert_type(def_gen.standard_exponential(size=1, dtype="float64"), npt.NDArray[np.float64]) +assert_type(def_gen.standard_exponential(size=1, dtype="f8"), npt.NDArray[np.float64]) +assert_type(def_gen.standard_exponential(out=D_out), npt.NDArray[np.float64]) +assert_type(def_gen.standard_exponential(size=1, dtype="float64"), npt.NDArray[np.float64]) +assert_type(def_gen.standard_exponential(size=1, dtype="float64", out=D_out), npt.NDArray[np.float64]) + +assert_type(def_gen.zipf(1.5), int) +assert_type(def_gen.zipf(1.5, size=None), int) +assert_type(def_gen.zipf(1.5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.zipf(D_arr_1p5), npt.NDArray[np.int64]) +assert_type(def_gen.zipf(D_arr_1p5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.zipf(D_arr_like_1p5), npt.NDArray[np.int64]) +assert_type(def_gen.zipf(D_arr_like_1p5, size=1), npt.NDArray[np.int64]) + +assert_type(def_gen.weibull(0.5), float) +assert_type(def_gen.weibull(0.5, size=None), float) +assert_type(def_gen.weibull(0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.weibull(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.weibull(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.weibull(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.weibull(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.standard_t(0.5), float) +assert_type(def_gen.standard_t(0.5, size=None), float) +assert_type(def_gen.standard_t(0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.standard_t(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.standard_t(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.standard_t(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.standard_t(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.poisson(0.5), int) +assert_type(def_gen.poisson(0.5, size=None), int) +assert_type(def_gen.poisson(0.5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.poisson(D_arr_0p5), npt.NDArray[np.int64]) +assert_type(def_gen.poisson(D_arr_0p5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.poisson(D_arr_like_0p5), npt.NDArray[np.int64]) +assert_type(def_gen.poisson(D_arr_like_0p5, size=1), npt.NDArray[np.int64]) + +assert_type(def_gen.power(0.5), float) +assert_type(def_gen.power(0.5, size=None), float) +assert_type(def_gen.power(0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.power(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.power(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.power(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.power(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.pareto(0.5), float) +assert_type(def_gen.pareto(0.5, size=None), float) +assert_type(def_gen.pareto(0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.pareto(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.pareto(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.pareto(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.pareto(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.chisquare(0.5), float) +assert_type(def_gen.chisquare(0.5, size=None), float) +assert_type(def_gen.chisquare(0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.chisquare(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.chisquare(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.chisquare(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.chisquare(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.exponential(0.5), float) +assert_type(def_gen.exponential(0.5, size=None), float) +assert_type(def_gen.exponential(0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.exponential(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.exponential(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.exponential(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.exponential(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.geometric(0.5), int) +assert_type(def_gen.geometric(0.5, size=None), int) +assert_type(def_gen.geometric(0.5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.geometric(D_arr_0p5), npt.NDArray[np.int64]) +assert_type(def_gen.geometric(D_arr_0p5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.geometric(D_arr_like_0p5), npt.NDArray[np.int64]) +assert_type(def_gen.geometric(D_arr_like_0p5, size=1), npt.NDArray[np.int64]) + +assert_type(def_gen.logseries(0.5), int) +assert_type(def_gen.logseries(0.5, size=None), int) +assert_type(def_gen.logseries(0.5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.logseries(D_arr_0p5), npt.NDArray[np.int64]) +assert_type(def_gen.logseries(D_arr_0p5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.logseries(D_arr_like_0p5), npt.NDArray[np.int64]) +assert_type(def_gen.logseries(D_arr_like_0p5, size=1), npt.NDArray[np.int64]) + +assert_type(def_gen.rayleigh(0.5), float) +assert_type(def_gen.rayleigh(0.5, size=None), float) +assert_type(def_gen.rayleigh(0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.rayleigh(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.rayleigh(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.rayleigh(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.rayleigh(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.standard_gamma(0.5), float) +assert_type(def_gen.standard_gamma(0.5, size=None), float) +assert_type(def_gen.standard_gamma(0.5, dtype="float32"), float) +assert_type(def_gen.standard_gamma(0.5, size=None, dtype="float32"), float) +assert_type(def_gen.standard_gamma(0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.standard_gamma(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.standard_gamma(D_arr_0p5, dtype="f4"), npt.NDArray[np.float32]) +assert_type(def_gen.standard_gamma(0.5, size=1, dtype="float32", out=S_out), npt.NDArray[np.float32]) +assert_type(def_gen.standard_gamma(D_arr_0p5, dtype=np.float32, out=S_out), npt.NDArray[np.float32]) +assert_type(def_gen.standard_gamma(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.standard_gamma(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.standard_gamma(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.standard_gamma(0.5, out=D_out), npt.NDArray[np.float64]) +assert_type(def_gen.standard_gamma(D_arr_like_0p5, out=D_out), npt.NDArray[np.float64]) +assert_type(def_gen.standard_gamma(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.standard_gamma(D_arr_like_0p5, size=1, out=D_out, dtype=np.float64), npt.NDArray[np.float64]) + +assert_type(def_gen.vonmises(0.5, 0.5), float) +assert_type(def_gen.vonmises(0.5, 0.5, size=None), float) +assert_type(def_gen.vonmises(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.vonmises(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.vonmises(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.vonmises(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.vonmises(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.vonmises(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.vonmises(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.vonmises(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.vonmises(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.vonmises(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.vonmises(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.wald(0.5, 0.5), float) +assert_type(def_gen.wald(0.5, 0.5, size=None), float) +assert_type(def_gen.wald(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.wald(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.wald(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.wald(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.wald(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.wald(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.wald(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.wald(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.wald(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.wald(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.wald(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.uniform(0.5, 0.5), float) +assert_type(def_gen.uniform(0.5, 0.5, size=None), float) +assert_type(def_gen.uniform(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.uniform(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.uniform(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.uniform(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.uniform(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.uniform(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.uniform(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.uniform(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.uniform(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.uniform(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.uniform(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.beta(0.5, 0.5), float) +assert_type(def_gen.beta(0.5, 0.5, size=None), float) +assert_type(def_gen.beta(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.beta(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.beta(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.beta(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.beta(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.beta(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.beta(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.beta(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.beta(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.beta(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.beta(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.f(0.5, 0.5), float) +assert_type(def_gen.f(0.5, 0.5, size=None), float) +assert_type(def_gen.f(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.f(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.f(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.f(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.f(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.f(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.f(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.f(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.f(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.f(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.f(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.gamma(0.5, 0.5), float) +assert_type(def_gen.gamma(0.5, 0.5, size=None), float) +assert_type(def_gen.gamma(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.gamma(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.gamma(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.gamma(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.gamma(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.gamma(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.gamma(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.gamma(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.gamma(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.gamma(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.gamma(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.gumbel(0.5, 0.5), float) +assert_type(def_gen.gumbel(0.5, 0.5, size=None), float) +assert_type(def_gen.gumbel(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.gumbel(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.gumbel(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.gumbel(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.gumbel(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.gumbel(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.gumbel(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.gumbel(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.gumbel(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.gumbel(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.gumbel(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.laplace(0.5, 0.5), float) +assert_type(def_gen.laplace(0.5, 0.5, size=None), float) +assert_type(def_gen.laplace(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.laplace(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.laplace(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.laplace(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.laplace(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.laplace(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.laplace(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.laplace(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.laplace(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.laplace(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.laplace(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.logistic(0.5, 0.5), float) +assert_type(def_gen.logistic(0.5, 0.5, size=None), float) +assert_type(def_gen.logistic(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.logistic(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.logistic(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.logistic(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.logistic(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.logistic(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.logistic(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.logistic(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.logistic(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.logistic(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.logistic(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.lognormal(0.5, 0.5), float) +assert_type(def_gen.lognormal(0.5, 0.5, size=None), float) +assert_type(def_gen.lognormal(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.lognormal(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.lognormal(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.lognormal(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.lognormal(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.lognormal(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.lognormal(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.lognormal(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.lognormal(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.lognormal(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.lognormal(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.noncentral_chisquare(0.5, 0.5), float) +assert_type(def_gen.noncentral_chisquare(0.5, 0.5, size=None), float) +assert_type(def_gen.noncentral_chisquare(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_chisquare(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_chisquare(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_chisquare(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_chisquare(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_chisquare(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_chisquare(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_chisquare(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_chisquare(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_chisquare(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_chisquare(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.normal(0.5, 0.5), float) +assert_type(def_gen.normal(0.5, 0.5, size=None), float) +assert_type(def_gen.normal(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.normal(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.normal(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.normal(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.normal(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.normal(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(def_gen.normal(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.normal(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.normal(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(def_gen.normal(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.normal(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.triangular(0.1, 0.5, 0.9), float) +assert_type(def_gen.triangular(0.1, 0.5, 0.9, size=None), float) +assert_type(def_gen.triangular(0.1, 0.5, 0.9, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.triangular(D_arr_0p1, 0.5, 0.9), npt.NDArray[np.float64]) +assert_type(def_gen.triangular(0.1, D_arr_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(def_gen.triangular(D_arr_0p1, 0.5, D_arr_like_0p9, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.triangular(0.1, D_arr_0p5, 0.9, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.triangular(D_arr_like_0p1, 0.5, D_arr_0p9), npt.NDArray[np.float64]) +assert_type(def_gen.triangular(0.5, D_arr_like_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(def_gen.triangular(D_arr_0p1, D_arr_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(def_gen.triangular(D_arr_like_0p1, D_arr_like_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(def_gen.triangular(D_arr_0p1, D_arr_0p5, D_arr_0p9, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.triangular(D_arr_like_0p1, D_arr_like_0p5, D_arr_like_0p9, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.noncentral_f(0.1, 0.5, 0.9), float) +assert_type(def_gen.noncentral_f(0.1, 0.5, 0.9, size=None), float) +assert_type(def_gen.noncentral_f(0.1, 0.5, 0.9, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_f(D_arr_0p1, 0.5, 0.9), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_f(0.1, D_arr_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_f(D_arr_0p1, 0.5, D_arr_like_0p9, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_f(0.1, D_arr_0p5, 0.9, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_f(D_arr_like_0p1, 0.5, D_arr_0p9), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_f(0.5, D_arr_like_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_f(D_arr_0p1, D_arr_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_f(D_arr_like_0p1, D_arr_like_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_f(D_arr_0p1, D_arr_0p5, D_arr_0p9, size=1), npt.NDArray[np.float64]) +assert_type(def_gen.noncentral_f(D_arr_like_0p1, D_arr_like_0p5, D_arr_like_0p9, size=1), npt.NDArray[np.float64]) + +assert_type(def_gen.binomial(10, 0.5), int) +assert_type(def_gen.binomial(10, 0.5, size=None), int) +assert_type(def_gen.binomial(10, 0.5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.binomial(I_arr_10, 0.5), npt.NDArray[np.int64]) +assert_type(def_gen.binomial(10, D_arr_0p5), npt.NDArray[np.int64]) +assert_type(def_gen.binomial(I_arr_10, 0.5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.binomial(10, D_arr_0p5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.binomial(I_arr_like_10, 0.5), npt.NDArray[np.int64]) +assert_type(def_gen.binomial(10, D_arr_like_0p5), npt.NDArray[np.int64]) +assert_type(def_gen.binomial(I_arr_10, D_arr_0p5), npt.NDArray[np.int64]) +assert_type(def_gen.binomial(I_arr_like_10, D_arr_like_0p5), npt.NDArray[np.int64]) +assert_type(def_gen.binomial(I_arr_10, D_arr_0p5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.binomial(I_arr_like_10, D_arr_like_0p5, size=1), npt.NDArray[np.int64]) + +assert_type(def_gen.negative_binomial(10, 0.5), int) +assert_type(def_gen.negative_binomial(10, 0.5, size=None), int) +assert_type(def_gen.negative_binomial(10, 0.5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.negative_binomial(I_arr_10, 0.5), npt.NDArray[np.int64]) +assert_type(def_gen.negative_binomial(10, D_arr_0p5), npt.NDArray[np.int64]) +assert_type(def_gen.negative_binomial(I_arr_10, 0.5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.negative_binomial(10, D_arr_0p5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.negative_binomial(I_arr_like_10, 0.5), npt.NDArray[np.int64]) +assert_type(def_gen.negative_binomial(10, D_arr_like_0p5), npt.NDArray[np.int64]) +assert_type(def_gen.negative_binomial(I_arr_10, D_arr_0p5), npt.NDArray[np.int64]) +assert_type(def_gen.negative_binomial(I_arr_like_10, D_arr_like_0p5), npt.NDArray[np.int64]) +assert_type(def_gen.negative_binomial(I_arr_10, D_arr_0p5, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.negative_binomial(I_arr_like_10, D_arr_like_0p5, size=1), npt.NDArray[np.int64]) + +assert_type(def_gen.hypergeometric(20, 20, 10), int) +assert_type(def_gen.hypergeometric(20, 20, 10, size=None), int) +assert_type(def_gen.hypergeometric(20, 20, 10, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.hypergeometric(I_arr_20, 20, 10), npt.NDArray[np.int64]) +assert_type(def_gen.hypergeometric(20, I_arr_20, 10), npt.NDArray[np.int64]) +assert_type(def_gen.hypergeometric(I_arr_20, 20, I_arr_like_10, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.hypergeometric(20, I_arr_20, 10, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.hypergeometric(I_arr_like_20, 20, I_arr_10), npt.NDArray[np.int64]) +assert_type(def_gen.hypergeometric(20, I_arr_like_20, 10), npt.NDArray[np.int64]) +assert_type(def_gen.hypergeometric(I_arr_20, I_arr_20, 10), npt.NDArray[np.int64]) +assert_type(def_gen.hypergeometric(I_arr_like_20, I_arr_like_20, 10), npt.NDArray[np.int64]) +assert_type(def_gen.hypergeometric(I_arr_20, I_arr_20, I_arr_10, size=1), npt.NDArray[np.int64]) +assert_type(def_gen.hypergeometric(I_arr_like_20, I_arr_like_20, I_arr_like_10, size=1), npt.NDArray[np.int64]) + +I_int64_100: npt.NDArray[np.int64] = np.array([100], dtype=np.int64) + +assert_type(def_gen.integers(0, 100), np.int64) +assert_type(def_gen.integers(100), np.int64) +assert_type(def_gen.integers([100]), npt.NDArray[np.int64]) +assert_type(def_gen.integers(0, [100]), npt.NDArray[np.int64]) + +I_bool_low: npt.NDArray[np.bool] = np.array([0], dtype=np.bool) +I_bool_low_like: list[int] = [0] +I_bool_high_open: npt.NDArray[np.bool] = np.array([1], dtype=np.bool) +I_bool_high_closed: npt.NDArray[np.bool] = np.array([1], dtype=np.bool) + +assert_type(def_gen.integers(2, dtype=bool), bool) +assert_type(def_gen.integers(0, 2, dtype=bool), bool) +assert_type(def_gen.integers(1, dtype=bool, endpoint=True), bool) +assert_type(def_gen.integers(0, 1, dtype=bool, endpoint=True), bool) +assert_type(def_gen.integers(I_bool_low_like, 1, dtype=bool, endpoint=True), npt.NDArray[np.bool]) +assert_type(def_gen.integers(I_bool_high_open, dtype=bool), npt.NDArray[np.bool]) +assert_type(def_gen.integers(I_bool_low, I_bool_high_open, dtype=bool), npt.NDArray[np.bool]) +assert_type(def_gen.integers(0, I_bool_high_open, dtype=bool), npt.NDArray[np.bool]) +assert_type(def_gen.integers(I_bool_high_closed, dtype=bool, endpoint=True), npt.NDArray[np.bool]) +assert_type(def_gen.integers(I_bool_low, I_bool_high_closed, dtype=bool, endpoint=True), npt.NDArray[np.bool]) +assert_type(def_gen.integers(0, I_bool_high_closed, dtype=bool, endpoint=True), npt.NDArray[np.bool]) + +assert_type(def_gen.integers(2, dtype=np.bool), np.bool) +assert_type(def_gen.integers(0, 2, dtype=np.bool), np.bool) +assert_type(def_gen.integers(1, dtype=np.bool, endpoint=True), np.bool) +assert_type(def_gen.integers(0, 1, dtype=np.bool, endpoint=True), np.bool) +assert_type(def_gen.integers(I_bool_low_like, 1, dtype=np.bool, endpoint=True), npt.NDArray[np.bool]) +assert_type(def_gen.integers(I_bool_high_open, dtype=np.bool), npt.NDArray[np.bool]) +assert_type(def_gen.integers(I_bool_low, I_bool_high_open, dtype=np.bool), npt.NDArray[np.bool]) +assert_type(def_gen.integers(0, I_bool_high_open, dtype=np.bool), npt.NDArray[np.bool]) +assert_type(def_gen.integers(I_bool_high_closed, dtype=np.bool, endpoint=True), npt.NDArray[np.bool]) +assert_type(def_gen.integers(I_bool_low, I_bool_high_closed, dtype=np.bool, endpoint=True), npt.NDArray[np.bool]) +assert_type(def_gen.integers(0, I_bool_high_closed, dtype=np.bool, endpoint=True), npt.NDArray[np.bool]) + +I_u1_low: npt.NDArray[np.uint8] = np.array([0], dtype=np.uint8) +I_u1_low_like: list[int] = [0] +I_u1_high_open: npt.NDArray[np.uint8] = np.array([255], dtype=np.uint8) +I_u1_high_closed: npt.NDArray[np.uint8] = np.array([255], dtype=np.uint8) + +assert_type(def_gen.integers(256, dtype="u1"), np.uint8) +assert_type(def_gen.integers(0, 256, dtype="u1"), np.uint8) +assert_type(def_gen.integers(255, dtype="u1", endpoint=True), np.uint8) +assert_type(def_gen.integers(0, 255, dtype="u1", endpoint=True), np.uint8) +assert_type(def_gen.integers(I_u1_low_like, 255, dtype="u1", endpoint=True), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(I_u1_high_open, dtype="u1"), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(I_u1_low, I_u1_high_open, dtype="u1"), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(0, I_u1_high_open, dtype="u1"), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(I_u1_high_closed, dtype="u1", endpoint=True), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(I_u1_low, I_u1_high_closed, dtype="u1", endpoint=True), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(0, I_u1_high_closed, dtype="u1", endpoint=True), npt.NDArray[np.uint8]) + +assert_type(def_gen.integers(256, dtype="uint8"), np.uint8) +assert_type(def_gen.integers(0, 256, dtype="uint8"), np.uint8) +assert_type(def_gen.integers(255, dtype="uint8", endpoint=True), np.uint8) +assert_type(def_gen.integers(0, 255, dtype="uint8", endpoint=True), np.uint8) +assert_type(def_gen.integers(I_u1_low_like, 255, dtype="uint8", endpoint=True), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(I_u1_high_open, dtype="uint8"), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(I_u1_low, I_u1_high_open, dtype="uint8"), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(0, I_u1_high_open, dtype="uint8"), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(I_u1_high_closed, dtype="uint8", endpoint=True), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(I_u1_low, I_u1_high_closed, dtype="uint8", endpoint=True), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(0, I_u1_high_closed, dtype="uint8", endpoint=True), npt.NDArray[np.uint8]) + +assert_type(def_gen.integers(256, dtype=np.uint8), np.uint8) +assert_type(def_gen.integers(0, 256, dtype=np.uint8), np.uint8) +assert_type(def_gen.integers(255, dtype=np.uint8, endpoint=True), np.uint8) +assert_type(def_gen.integers(0, 255, dtype=np.uint8, endpoint=True), np.uint8) +assert_type(def_gen.integers(I_u1_low_like, 255, dtype=np.uint8, endpoint=True), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(I_u1_high_open, dtype=np.uint8), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(I_u1_low, I_u1_high_open, dtype=np.uint8), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(0, I_u1_high_open, dtype=np.uint8), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(I_u1_high_closed, dtype=np.uint8, endpoint=True), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(I_u1_low, I_u1_high_closed, dtype=np.uint8, endpoint=True), npt.NDArray[np.uint8]) +assert_type(def_gen.integers(0, I_u1_high_closed, dtype=np.uint8, endpoint=True), npt.NDArray[np.uint8]) + +I_u2_low: npt.NDArray[np.uint16] = np.array([0], dtype=np.uint16) +I_u2_low_like: list[int] = [0] +I_u2_high_open: npt.NDArray[np.uint16] = np.array([65535], dtype=np.uint16) +I_u2_high_closed: npt.NDArray[np.uint16] = np.array([65535], dtype=np.uint16) + +assert_type(def_gen.integers(65536, dtype="u2"), np.uint16) +assert_type(def_gen.integers(0, 65536, dtype="u2"), np.uint16) +assert_type(def_gen.integers(65535, dtype="u2", endpoint=True), np.uint16) +assert_type(def_gen.integers(0, 65535, dtype="u2", endpoint=True), np.uint16) +assert_type(def_gen.integers(I_u2_low_like, 65535, dtype="u2", endpoint=True), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(I_u2_high_open, dtype="u2"), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(I_u2_low, I_u2_high_open, dtype="u2"), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(0, I_u2_high_open, dtype="u2"), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(I_u2_high_closed, dtype="u2", endpoint=True), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(I_u2_low, I_u2_high_closed, dtype="u2", endpoint=True), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(0, I_u2_high_closed, dtype="u2", endpoint=True), npt.NDArray[np.uint16]) + +assert_type(def_gen.integers(65536, dtype="uint16"), np.uint16) +assert_type(def_gen.integers(0, 65536, dtype="uint16"), np.uint16) +assert_type(def_gen.integers(65535, dtype="uint16", endpoint=True), np.uint16) +assert_type(def_gen.integers(0, 65535, dtype="uint16", endpoint=True), np.uint16) +assert_type(def_gen.integers(I_u2_low_like, 65535, dtype="uint16", endpoint=True), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(I_u2_high_open, dtype="uint16"), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(I_u2_low, I_u2_high_open, dtype="uint16"), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(0, I_u2_high_open, dtype="uint16"), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(I_u2_high_closed, dtype="uint16", endpoint=True), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(I_u2_low, I_u2_high_closed, dtype="uint16", endpoint=True), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(0, I_u2_high_closed, dtype="uint16", endpoint=True), npt.NDArray[np.uint16]) + +assert_type(def_gen.integers(65536, dtype=np.uint16), np.uint16) +assert_type(def_gen.integers(0, 65536, dtype=np.uint16), np.uint16) +assert_type(def_gen.integers(65535, dtype=np.uint16, endpoint=True), np.uint16) +assert_type(def_gen.integers(0, 65535, dtype=np.uint16, endpoint=True), np.uint16) +assert_type(def_gen.integers(I_u2_low_like, 65535, dtype=np.uint16, endpoint=True), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(I_u2_high_open, dtype=np.uint16), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(I_u2_low, I_u2_high_open, dtype=np.uint16), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(0, I_u2_high_open, dtype=np.uint16), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(I_u2_high_closed, dtype=np.uint16, endpoint=True), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(I_u2_low, I_u2_high_closed, dtype=np.uint16, endpoint=True), npt.NDArray[np.uint16]) +assert_type(def_gen.integers(0, I_u2_high_closed, dtype=np.uint16, endpoint=True), npt.NDArray[np.uint16]) + +I_u4_low: npt.NDArray[np.uint32] = np.array([0], dtype=np.uint32) +I_u4_low_like: list[int] = [0] +I_u4_high_open: npt.NDArray[np.uint32] = np.array([4294967295], dtype=np.uint32) +I_u4_high_closed: npt.NDArray[np.uint32] = np.array([4294967295], dtype=np.uint32) + +assert_type(def_gen.integers(4294967296, dtype=np.int_), np.int_) +assert_type(def_gen.integers(0, 4294967296, dtype=np.int_), np.int_) +assert_type(def_gen.integers(4294967295, dtype=np.int_, endpoint=True), np.int_) +assert_type(def_gen.integers(0, 4294967295, dtype=np.int_, endpoint=True), np.int_) +assert_type(def_gen.integers(I_u4_low_like, 4294967295, dtype=np.int_, endpoint=True), npt.NDArray[np.int_]) +assert_type(def_gen.integers(I_u4_high_open, dtype=np.int_), npt.NDArray[np.int_]) +assert_type(def_gen.integers(I_u4_low, I_u4_high_open, dtype=np.int_), npt.NDArray[np.int_]) +assert_type(def_gen.integers(0, I_u4_high_open, dtype=np.int_), npt.NDArray[np.int_]) +assert_type(def_gen.integers(I_u4_high_closed, dtype=np.int_, endpoint=True), npt.NDArray[np.int_]) +assert_type(def_gen.integers(I_u4_low, I_u4_high_closed, dtype=np.int_, endpoint=True), npt.NDArray[np.int_]) +assert_type(def_gen.integers(0, I_u4_high_closed, dtype=np.int_, endpoint=True), npt.NDArray[np.int_]) + +assert_type(def_gen.integers(4294967296, dtype="u4"), np.uint32) +assert_type(def_gen.integers(0, 4294967296, dtype="u4"), np.uint32) +assert_type(def_gen.integers(4294967295, dtype="u4", endpoint=True), np.uint32) +assert_type(def_gen.integers(0, 4294967295, dtype="u4", endpoint=True), np.uint32) +assert_type(def_gen.integers(I_u4_low_like, 4294967295, dtype="u4", endpoint=True), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(I_u4_high_open, dtype="u4"), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(I_u4_low, I_u4_high_open, dtype="u4"), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(0, I_u4_high_open, dtype="u4"), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(I_u4_high_closed, dtype="u4", endpoint=True), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(I_u4_low, I_u4_high_closed, dtype="u4", endpoint=True), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(0, I_u4_high_closed, dtype="u4", endpoint=True), npt.NDArray[np.uint32]) + +assert_type(def_gen.integers(4294967296, dtype="uint32"), np.uint32) +assert_type(def_gen.integers(0, 4294967296, dtype="uint32"), np.uint32) +assert_type(def_gen.integers(4294967295, dtype="uint32", endpoint=True), np.uint32) +assert_type(def_gen.integers(0, 4294967295, dtype="uint32", endpoint=True), np.uint32) +assert_type(def_gen.integers(I_u4_low_like, 4294967295, dtype="uint32", endpoint=True), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(I_u4_high_open, dtype="uint32"), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(I_u4_low, I_u4_high_open, dtype="uint32"), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(0, I_u4_high_open, dtype="uint32"), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(I_u4_high_closed, dtype="uint32", endpoint=True), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(I_u4_low, I_u4_high_closed, dtype="uint32", endpoint=True), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(0, I_u4_high_closed, dtype="uint32", endpoint=True), npt.NDArray[np.uint32]) + +assert_type(def_gen.integers(4294967296, dtype=np.uint32), np.uint32) +assert_type(def_gen.integers(0, 4294967296, dtype=np.uint32), np.uint32) +assert_type(def_gen.integers(4294967295, dtype=np.uint32, endpoint=True), np.uint32) +assert_type(def_gen.integers(0, 4294967295, dtype=np.uint32, endpoint=True), np.uint32) +assert_type(def_gen.integers(I_u4_low_like, 4294967295, dtype=np.uint32, endpoint=True), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(I_u4_high_open, dtype=np.uint32), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(I_u4_low, I_u4_high_open, dtype=np.uint32), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(0, I_u4_high_open, dtype=np.uint32), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(I_u4_high_closed, dtype=np.uint32, endpoint=True), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(I_u4_low, I_u4_high_closed, dtype=np.uint32, endpoint=True), npt.NDArray[np.uint32]) +assert_type(def_gen.integers(0, I_u4_high_closed, dtype=np.uint32, endpoint=True), npt.NDArray[np.uint32]) + +assert_type(def_gen.integers(4294967296, dtype=np.uint), np.uint) +assert_type(def_gen.integers(0, 4294967296, dtype=np.uint), np.uint) +assert_type(def_gen.integers(4294967295, dtype=np.uint, endpoint=True), np.uint) +assert_type(def_gen.integers(0, 4294967295, dtype=np.uint, endpoint=True), np.uint) +assert_type(def_gen.integers(I_u4_low_like, 4294967295, dtype=np.uint, endpoint=True), npt.NDArray[np.uint]) +assert_type(def_gen.integers(I_u4_high_open, dtype=np.uint), npt.NDArray[np.uint]) +assert_type(def_gen.integers(I_u4_low, I_u4_high_open, dtype=np.uint), npt.NDArray[np.uint]) +assert_type(def_gen.integers(0, I_u4_high_open, dtype=np.uint), npt.NDArray[np.uint]) +assert_type(def_gen.integers(I_u4_high_closed, dtype=np.uint, endpoint=True), npt.NDArray[np.uint]) +assert_type(def_gen.integers(I_u4_low, I_u4_high_closed, dtype=np.uint, endpoint=True), npt.NDArray[np.uint]) +assert_type(def_gen.integers(0, I_u4_high_closed, dtype=np.uint, endpoint=True), npt.NDArray[np.uint]) + +I_u8_low: npt.NDArray[np.uint64] = np.array([0], dtype=np.uint64) +I_u8_low_like: list[int] = [0] +I_u8_high_open: npt.NDArray[np.uint64] = np.array([18446744073709551615], dtype=np.uint64) +I_u8_high_closed: npt.NDArray[np.uint64] = np.array([18446744073709551615], dtype=np.uint64) + +assert_type(def_gen.integers(18446744073709551616, dtype="u8"), np.uint64) +assert_type(def_gen.integers(0, 18446744073709551616, dtype="u8"), np.uint64) +assert_type(def_gen.integers(18446744073709551615, dtype="u8", endpoint=True), np.uint64) +assert_type(def_gen.integers(0, 18446744073709551615, dtype="u8", endpoint=True), np.uint64) +assert_type(def_gen.integers(I_u8_low_like, 18446744073709551615, dtype="u8", endpoint=True), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(I_u8_high_open, dtype="u8"), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(I_u8_low, I_u8_high_open, dtype="u8"), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(0, I_u8_high_open, dtype="u8"), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(I_u8_high_closed, dtype="u8", endpoint=True), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(I_u8_low, I_u8_high_closed, dtype="u8", endpoint=True), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(0, I_u8_high_closed, dtype="u8", endpoint=True), npt.NDArray[np.uint64]) + +assert_type(def_gen.integers(18446744073709551616, dtype="uint64"), np.uint64) +assert_type(def_gen.integers(0, 18446744073709551616, dtype="uint64"), np.uint64) +assert_type(def_gen.integers(18446744073709551615, dtype="uint64", endpoint=True), np.uint64) +assert_type(def_gen.integers(0, 18446744073709551615, dtype="uint64", endpoint=True), np.uint64) +assert_type(def_gen.integers(I_u8_low_like, 18446744073709551615, dtype="uint64", endpoint=True), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(I_u8_high_open, dtype="uint64"), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(I_u8_low, I_u8_high_open, dtype="uint64"), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(0, I_u8_high_open, dtype="uint64"), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(I_u8_high_closed, dtype="uint64", endpoint=True), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(I_u8_low, I_u8_high_closed, dtype="uint64", endpoint=True), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(0, I_u8_high_closed, dtype="uint64", endpoint=True), npt.NDArray[np.uint64]) + +assert_type(def_gen.integers(18446744073709551616, dtype=np.uint64), np.uint64) +assert_type(def_gen.integers(0, 18446744073709551616, dtype=np.uint64), np.uint64) +assert_type(def_gen.integers(18446744073709551615, dtype=np.uint64, endpoint=True), np.uint64) +assert_type(def_gen.integers(0, 18446744073709551615, dtype=np.uint64, endpoint=True), np.uint64) +assert_type(def_gen.integers(I_u8_low_like, 18446744073709551615, dtype=np.uint64, endpoint=True), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(I_u8_high_open, dtype=np.uint64), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(I_u8_low, I_u8_high_open, dtype=np.uint64), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(0, I_u8_high_open, dtype=np.uint64), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(I_u8_high_closed, dtype=np.uint64, endpoint=True), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(I_u8_low, I_u8_high_closed, dtype=np.uint64, endpoint=True), npt.NDArray[np.uint64]) +assert_type(def_gen.integers(0, I_u8_high_closed, dtype=np.uint64, endpoint=True), npt.NDArray[np.uint64]) + +I_i1_low: npt.NDArray[np.int8] = np.array([-128], dtype=np.int8) +I_i1_low_like: list[int] = [-128] +I_i1_high_open: npt.NDArray[np.int8] = np.array([127], dtype=np.int8) +I_i1_high_closed: npt.NDArray[np.int8] = np.array([127], dtype=np.int8) + +assert_type(def_gen.integers(128, dtype="i1"), np.int8) +assert_type(def_gen.integers(-128, 128, dtype="i1"), np.int8) +assert_type(def_gen.integers(127, dtype="i1", endpoint=True), np.int8) +assert_type(def_gen.integers(-128, 127, dtype="i1", endpoint=True), np.int8) +assert_type(def_gen.integers(I_i1_low_like, 127, dtype="i1", endpoint=True), npt.NDArray[np.int8]) +assert_type(def_gen.integers(I_i1_high_open, dtype="i1"), npt.NDArray[np.int8]) +assert_type(def_gen.integers(I_i1_low, I_i1_high_open, dtype="i1"), npt.NDArray[np.int8]) +assert_type(def_gen.integers(-128, I_i1_high_open, dtype="i1"), npt.NDArray[np.int8]) +assert_type(def_gen.integers(I_i1_high_closed, dtype="i1", endpoint=True), npt.NDArray[np.int8]) +assert_type(def_gen.integers(I_i1_low, I_i1_high_closed, dtype="i1", endpoint=True), npt.NDArray[np.int8]) +assert_type(def_gen.integers(-128, I_i1_high_closed, dtype="i1", endpoint=True), npt.NDArray[np.int8]) + +assert_type(def_gen.integers(128, dtype="int8"), np.int8) +assert_type(def_gen.integers(-128, 128, dtype="int8"), np.int8) +assert_type(def_gen.integers(127, dtype="int8", endpoint=True), np.int8) +assert_type(def_gen.integers(-128, 127, dtype="int8", endpoint=True), np.int8) +assert_type(def_gen.integers(I_i1_low_like, 127, dtype="int8", endpoint=True), npt.NDArray[np.int8]) +assert_type(def_gen.integers(I_i1_high_open, dtype="int8"), npt.NDArray[np.int8]) +assert_type(def_gen.integers(I_i1_low, I_i1_high_open, dtype="int8"), npt.NDArray[np.int8]) +assert_type(def_gen.integers(-128, I_i1_high_open, dtype="int8"), npt.NDArray[np.int8]) +assert_type(def_gen.integers(I_i1_high_closed, dtype="int8", endpoint=True), npt.NDArray[np.int8]) +assert_type(def_gen.integers(I_i1_low, I_i1_high_closed, dtype="int8", endpoint=True), npt.NDArray[np.int8]) +assert_type(def_gen.integers(-128, I_i1_high_closed, dtype="int8", endpoint=True), npt.NDArray[np.int8]) + +assert_type(def_gen.integers(128, dtype=np.int8), np.int8) +assert_type(def_gen.integers(-128, 128, dtype=np.int8), np.int8) +assert_type(def_gen.integers(127, dtype=np.int8, endpoint=True), np.int8) +assert_type(def_gen.integers(-128, 127, dtype=np.int8, endpoint=True), np.int8) +assert_type(def_gen.integers(I_i1_low_like, 127, dtype=np.int8, endpoint=True), npt.NDArray[np.int8]) +assert_type(def_gen.integers(I_i1_high_open, dtype=np.int8), npt.NDArray[np.int8]) +assert_type(def_gen.integers(I_i1_low, I_i1_high_open, dtype=np.int8), npt.NDArray[np.int8]) +assert_type(def_gen.integers(-128, I_i1_high_open, dtype=np.int8), npt.NDArray[np.int8]) +assert_type(def_gen.integers(I_i1_high_closed, dtype=np.int8, endpoint=True), npt.NDArray[np.int8]) +assert_type(def_gen.integers(I_i1_low, I_i1_high_closed, dtype=np.int8, endpoint=True), npt.NDArray[np.int8]) +assert_type(def_gen.integers(-128, I_i1_high_closed, dtype=np.int8, endpoint=True), npt.NDArray[np.int8]) + +I_i2_low: npt.NDArray[np.int16] = np.array([-32768], dtype=np.int16) +I_i2_low_like: list[int] = [-32768] +I_i2_high_open: npt.NDArray[np.int16] = np.array([32767], dtype=np.int16) +I_i2_high_closed: npt.NDArray[np.int16] = np.array([32767], dtype=np.int16) + +assert_type(def_gen.integers(32768, dtype="i2"), np.int16) +assert_type(def_gen.integers(-32768, 32768, dtype="i2"), np.int16) +assert_type(def_gen.integers(32767, dtype="i2", endpoint=True), np.int16) +assert_type(def_gen.integers(-32768, 32767, dtype="i2", endpoint=True), np.int16) +assert_type(def_gen.integers(I_i2_low_like, 32767, dtype="i2", endpoint=True), npt.NDArray[np.int16]) +assert_type(def_gen.integers(I_i2_high_open, dtype="i2"), npt.NDArray[np.int16]) +assert_type(def_gen.integers(I_i2_low, I_i2_high_open, dtype="i2"), npt.NDArray[np.int16]) +assert_type(def_gen.integers(-32768, I_i2_high_open, dtype="i2"), npt.NDArray[np.int16]) +assert_type(def_gen.integers(I_i2_high_closed, dtype="i2", endpoint=True), npt.NDArray[np.int16]) +assert_type(def_gen.integers(I_i2_low, I_i2_high_closed, dtype="i2", endpoint=True), npt.NDArray[np.int16]) +assert_type(def_gen.integers(-32768, I_i2_high_closed, dtype="i2", endpoint=True), npt.NDArray[np.int16]) + +assert_type(def_gen.integers(32768, dtype="int16"), np.int16) +assert_type(def_gen.integers(-32768, 32768, dtype="int16"), np.int16) +assert_type(def_gen.integers(32767, dtype="int16", endpoint=True), np.int16) +assert_type(def_gen.integers(-32768, 32767, dtype="int16", endpoint=True), np.int16) +assert_type(def_gen.integers(I_i2_low_like, 32767, dtype="int16", endpoint=True), npt.NDArray[np.int16]) +assert_type(def_gen.integers(I_i2_high_open, dtype="int16"), npt.NDArray[np.int16]) +assert_type(def_gen.integers(I_i2_low, I_i2_high_open, dtype="int16"), npt.NDArray[np.int16]) +assert_type(def_gen.integers(-32768, I_i2_high_open, dtype="int16"), npt.NDArray[np.int16]) +assert_type(def_gen.integers(I_i2_high_closed, dtype="int16", endpoint=True), npt.NDArray[np.int16]) +assert_type(def_gen.integers(I_i2_low, I_i2_high_closed, dtype="int16", endpoint=True), npt.NDArray[np.int16]) +assert_type(def_gen.integers(-32768, I_i2_high_closed, dtype="int16", endpoint=True), npt.NDArray[np.int16]) + +assert_type(def_gen.integers(32768, dtype=np.int16), np.int16) +assert_type(def_gen.integers(-32768, 32768, dtype=np.int16), np.int16) +assert_type(def_gen.integers(32767, dtype=np.int16, endpoint=True), np.int16) +assert_type(def_gen.integers(-32768, 32767, dtype=np.int16, endpoint=True), np.int16) +assert_type(def_gen.integers(I_i2_low_like, 32767, dtype=np.int16, endpoint=True), npt.NDArray[np.int16]) +assert_type(def_gen.integers(I_i2_high_open, dtype=np.int16), npt.NDArray[np.int16]) +assert_type(def_gen.integers(I_i2_low, I_i2_high_open, dtype=np.int16), npt.NDArray[np.int16]) +assert_type(def_gen.integers(-32768, I_i2_high_open, dtype=np.int16), npt.NDArray[np.int16]) +assert_type(def_gen.integers(I_i2_high_closed, dtype=np.int16, endpoint=True), npt.NDArray[np.int16]) +assert_type(def_gen.integers(I_i2_low, I_i2_high_closed, dtype=np.int16, endpoint=True), npt.NDArray[np.int16]) +assert_type(def_gen.integers(-32768, I_i2_high_closed, dtype=np.int16, endpoint=True), npt.NDArray[np.int16]) + +I_i4_low: npt.NDArray[np.int32] = np.array([-2147483648], dtype=np.int32) +I_i4_low_like: list[int] = [-2147483648] +I_i4_high_open: npt.NDArray[np.int32] = np.array([2147483647], dtype=np.int32) +I_i4_high_closed: npt.NDArray[np.int32] = np.array([2147483647], dtype=np.int32) + +assert_type(def_gen.integers(2147483648, dtype="i4"), np.int32) +assert_type(def_gen.integers(-2147483648, 2147483648, dtype="i4"), np.int32) +assert_type(def_gen.integers(2147483647, dtype="i4", endpoint=True), np.int32) +assert_type(def_gen.integers(-2147483648, 2147483647, dtype="i4", endpoint=True), np.int32) +assert_type(def_gen.integers(I_i4_low_like, 2147483647, dtype="i4", endpoint=True), npt.NDArray[np.int32]) +assert_type(def_gen.integers(I_i4_high_open, dtype="i4"), npt.NDArray[np.int32]) +assert_type(def_gen.integers(I_i4_low, I_i4_high_open, dtype="i4"), npt.NDArray[np.int32]) +assert_type(def_gen.integers(-2147483648, I_i4_high_open, dtype="i4"), npt.NDArray[np.int32]) +assert_type(def_gen.integers(I_i4_high_closed, dtype="i4", endpoint=True), npt.NDArray[np.int32]) +assert_type(def_gen.integers(I_i4_low, I_i4_high_closed, dtype="i4", endpoint=True), npt.NDArray[np.int32]) +assert_type(def_gen.integers(-2147483648, I_i4_high_closed, dtype="i4", endpoint=True), npt.NDArray[np.int32]) + +assert_type(def_gen.integers(2147483648, dtype="int32"), np.int32) +assert_type(def_gen.integers(-2147483648, 2147483648, dtype="int32"), np.int32) +assert_type(def_gen.integers(2147483647, dtype="int32", endpoint=True), np.int32) +assert_type(def_gen.integers(-2147483648, 2147483647, dtype="int32", endpoint=True), np.int32) +assert_type(def_gen.integers(I_i4_low_like, 2147483647, dtype="int32", endpoint=True), npt.NDArray[np.int32]) +assert_type(def_gen.integers(I_i4_high_open, dtype="int32"), npt.NDArray[np.int32]) +assert_type(def_gen.integers(I_i4_low, I_i4_high_open, dtype="int32"), npt.NDArray[np.int32]) +assert_type(def_gen.integers(-2147483648, I_i4_high_open, dtype="int32"), npt.NDArray[np.int32]) +assert_type(def_gen.integers(I_i4_high_closed, dtype="int32", endpoint=True), npt.NDArray[np.int32]) +assert_type(def_gen.integers(I_i4_low, I_i4_high_closed, dtype="int32", endpoint=True), npt.NDArray[np.int32]) +assert_type(def_gen.integers(-2147483648, I_i4_high_closed, dtype="int32", endpoint=True), npt.NDArray[np.int32]) + +assert_type(def_gen.integers(2147483648, dtype=np.int32), np.int32) +assert_type(def_gen.integers(-2147483648, 2147483648, dtype=np.int32), np.int32) +assert_type(def_gen.integers(2147483647, dtype=np.int32, endpoint=True), np.int32) +assert_type(def_gen.integers(-2147483648, 2147483647, dtype=np.int32, endpoint=True), np.int32) +assert_type(def_gen.integers(I_i4_low_like, 2147483647, dtype=np.int32, endpoint=True), npt.NDArray[np.int32]) +assert_type(def_gen.integers(I_i4_high_open, dtype=np.int32), npt.NDArray[np.int32]) +assert_type(def_gen.integers(I_i4_low, I_i4_high_open, dtype=np.int32), npt.NDArray[np.int32]) +assert_type(def_gen.integers(-2147483648, I_i4_high_open, dtype=np.int32), npt.NDArray[np.int32]) +assert_type(def_gen.integers(I_i4_high_closed, dtype=np.int32, endpoint=True), npt.NDArray[np.int32]) +assert_type(def_gen.integers(I_i4_low, I_i4_high_closed, dtype=np.int32, endpoint=True), npt.NDArray[np.int32]) +assert_type(def_gen.integers(-2147483648, I_i4_high_closed, dtype=np.int32, endpoint=True), npt.NDArray[np.int32]) + +I_i8_low: npt.NDArray[np.int64] = np.array([-9223372036854775808], dtype=np.int64) +I_i8_low_like: list[int] = [-9223372036854775808] +I_i8_high_open: npt.NDArray[np.int64] = np.array([9223372036854775807], dtype=np.int64) +I_i8_high_closed: npt.NDArray[np.int64] = np.array([9223372036854775807], dtype=np.int64) + +assert_type(def_gen.integers(9223372036854775808, dtype="i8"), np.int64) +assert_type(def_gen.integers(-9223372036854775808, 9223372036854775808, dtype="i8"), np.int64) +assert_type(def_gen.integers(9223372036854775807, dtype="i8", endpoint=True), np.int64) +assert_type(def_gen.integers(-9223372036854775808, 9223372036854775807, dtype="i8", endpoint=True), np.int64) +assert_type(def_gen.integers(I_i8_low_like, 9223372036854775807, dtype="i8", endpoint=True), npt.NDArray[np.int64]) +assert_type(def_gen.integers(I_i8_high_open, dtype="i8"), npt.NDArray[np.int64]) +assert_type(def_gen.integers(I_i8_low, I_i8_high_open, dtype="i8"), npt.NDArray[np.int64]) +assert_type(def_gen.integers(-9223372036854775808, I_i8_high_open, dtype="i8"), npt.NDArray[np.int64]) +assert_type(def_gen.integers(I_i8_high_closed, dtype="i8", endpoint=True), npt.NDArray[np.int64]) +assert_type(def_gen.integers(I_i8_low, I_i8_high_closed, dtype="i8", endpoint=True), npt.NDArray[np.int64]) +assert_type(def_gen.integers(-9223372036854775808, I_i8_high_closed, dtype="i8", endpoint=True), npt.NDArray[np.int64]) + +assert_type(def_gen.integers(9223372036854775808, dtype="int64"), np.int64) +assert_type(def_gen.integers(-9223372036854775808, 9223372036854775808, dtype="int64"), np.int64) +assert_type(def_gen.integers(9223372036854775807, dtype="int64", endpoint=True), np.int64) +assert_type(def_gen.integers(-9223372036854775808, 9223372036854775807, dtype="int64", endpoint=True), np.int64) +assert_type(def_gen.integers(I_i8_low_like, 9223372036854775807, dtype="int64", endpoint=True), npt.NDArray[np.int64]) +assert_type(def_gen.integers(I_i8_high_open, dtype="int64"), npt.NDArray[np.int64]) +assert_type(def_gen.integers(I_i8_low, I_i8_high_open, dtype="int64"), npt.NDArray[np.int64]) +assert_type(def_gen.integers(-9223372036854775808, I_i8_high_open, dtype="int64"), npt.NDArray[np.int64]) +assert_type(def_gen.integers(I_i8_high_closed, dtype="int64", endpoint=True), npt.NDArray[np.int64]) +assert_type(def_gen.integers(I_i8_low, I_i8_high_closed, dtype="int64", endpoint=True), npt.NDArray[np.int64]) +assert_type(def_gen.integers(-9223372036854775808, I_i8_high_closed, dtype="int64", endpoint=True), npt.NDArray[np.int64]) + +assert_type(def_gen.integers(9223372036854775808, dtype=np.int64), np.int64) +assert_type(def_gen.integers(-9223372036854775808, 9223372036854775808, dtype=np.int64), np.int64) +assert_type(def_gen.integers(9223372036854775807, dtype=np.int64, endpoint=True), np.int64) +assert_type(def_gen.integers(-9223372036854775808, 9223372036854775807, dtype=np.int64, endpoint=True), np.int64) +assert_type(def_gen.integers(I_i8_low_like, 9223372036854775807, dtype=np.int64, endpoint=True), npt.NDArray[np.int64]) +assert_type(def_gen.integers(I_i8_high_open, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(def_gen.integers(I_i8_low, I_i8_high_open, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(def_gen.integers(-9223372036854775808, I_i8_high_open, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(def_gen.integers(I_i8_high_closed, dtype=np.int64, endpoint=True), npt.NDArray[np.int64]) +assert_type(def_gen.integers(I_i8_low, I_i8_high_closed, dtype=np.int64, endpoint=True), npt.NDArray[np.int64]) +assert_type(def_gen.integers(-9223372036854775808, I_i8_high_closed, dtype=np.int64, endpoint=True), npt.NDArray[np.int64]) + +assert_type(def_gen.bit_generator, np.random.BitGenerator) + +assert_type(def_gen.bytes(2), bytes) + +assert_type(def_gen.choice(5), int) +assert_type(def_gen.choice(5, 3), npt.NDArray[np.int64]) +assert_type(def_gen.choice(5, 3, replace=True), npt.NDArray[np.int64]) +assert_type(def_gen.choice(5, 3, p=[1 / 5] * 5), npt.NDArray[np.int64]) +assert_type(def_gen.choice(5, 3, p=[1 / 5] * 5, replace=False), npt.NDArray[np.int64]) + +assert_type(def_gen.choice(["pooh", "rabbit", "piglet", "Christopher"]), Any) +assert_type(def_gen.choice(["pooh", "rabbit", "piglet", "Christopher"], 3), npt.NDArray[Any]) +assert_type(def_gen.choice(["pooh", "rabbit", "piglet", "Christopher"], 3, p=[1 / 4] * 4), npt.NDArray[Any]) +assert_type(def_gen.choice(["pooh", "rabbit", "piglet", "Christopher"], 3, replace=True), npt.NDArray[Any]) +assert_type(def_gen.choice(["pooh", "rabbit", "piglet", "Christopher"], 3, replace=False, p=np.array([1 / 8, 1 / 8, 1 / 2, 1 / 4])), npt.NDArray[Any]) + +assert_type(def_gen.dirichlet([0.5, 0.5]), npt.NDArray[np.float64]) +assert_type(def_gen.dirichlet(np.array([0.5, 0.5])), npt.NDArray[np.float64]) +assert_type(def_gen.dirichlet(np.array([0.5, 0.5]), size=3), npt.NDArray[np.float64]) + +assert_type(def_gen.multinomial(20, [1 / 6.0] * 6), npt.NDArray[np.int64]) +assert_type(def_gen.multinomial(20, np.array([0.5, 0.5])), npt.NDArray[np.int64]) +assert_type(def_gen.multinomial(20, [1 / 6.0] * 6, size=2), npt.NDArray[np.int64]) +assert_type(def_gen.multinomial([[10], [20]], [1 / 6.0] * 6, size=(2, 2)), npt.NDArray[np.int64]) +assert_type(def_gen.multinomial(np.array([[10], [20]]), np.array([0.5, 0.5]), size=(2, 2)), npt.NDArray[np.int64]) + +assert_type(def_gen.multivariate_hypergeometric([3, 5, 7], 2), npt.NDArray[np.int64]) +assert_type(def_gen.multivariate_hypergeometric(np.array([3, 5, 7]), 2), npt.NDArray[np.int64]) +assert_type(def_gen.multivariate_hypergeometric(np.array([3, 5, 7]), 2, size=4), npt.NDArray[np.int64]) +assert_type(def_gen.multivariate_hypergeometric(np.array([3, 5, 7]), 2, size=(4, 7)), npt.NDArray[np.int64]) +assert_type(def_gen.multivariate_hypergeometric([3, 5, 7], 2, method="count"), npt.NDArray[np.int64]) +assert_type(def_gen.multivariate_hypergeometric(np.array([3, 5, 7]), 2, method="marginals"), npt.NDArray[np.int64]) + +assert_type(def_gen.multivariate_normal([0.0], [[1.0]]), npt.NDArray[np.float64]) +assert_type(def_gen.multivariate_normal([0.0], np.array([[1.0]])), npt.NDArray[np.float64]) +assert_type(def_gen.multivariate_normal(np.array([0.0]), [[1.0]]), npt.NDArray[np.float64]) +assert_type(def_gen.multivariate_normal([0.0], np.array([[1.0]])), npt.NDArray[np.float64]) + +assert_type(def_gen.permutation(10), npt.NDArray[np.int64]) +assert_type(def_gen.permutation([1, 2, 3, 4]), npt.NDArray[Any]) +assert_type(def_gen.permutation(np.array([1, 2, 3, 4])), npt.NDArray[Any]) +assert_type(def_gen.permutation(D_2D, axis=1), npt.NDArray[Any]) +assert_type(def_gen.permuted(D_2D), npt.NDArray[Any]) +assert_type(def_gen.permuted(D_2D_like), npt.NDArray[Any]) +assert_type(def_gen.permuted(D_2D, axis=1), npt.NDArray[Any]) +assert_type(def_gen.permuted(D_2D, out=D_2D), npt.NDArray[Any]) +assert_type(def_gen.permuted(D_2D_like, out=D_2D), npt.NDArray[Any]) +assert_type(def_gen.permuted(D_2D_like, out=D_2D), npt.NDArray[Any]) +assert_type(def_gen.permuted(D_2D, axis=1, out=D_2D), npt.NDArray[Any]) + +assert_type(def_gen.shuffle(np.arange(10)), None) +assert_type(def_gen.shuffle([1, 2, 3, 4, 5]), None) +assert_type(def_gen.shuffle(D_2D, axis=1), None) + +assert_type(np.random.Generator(pcg64), np.random.Generator) +assert_type(def_gen.__str__(), str) +assert_type(def_gen.__repr__(), str) +assert_type(def_gen.__setstate__(dict(def_gen.bit_generator.state)), None) + +# RandomState +random_st: np.random.RandomState = np.random.RandomState() + +assert_type(random_st.standard_normal(), float) +assert_type(random_st.standard_normal(size=None), float) +assert_type(random_st.standard_normal(size=1), npt.NDArray[np.float64]) + +assert_type(random_st.random(), float) +assert_type(random_st.random(size=None), float) +assert_type(random_st.random(size=1), npt.NDArray[np.float64]) + +assert_type(random_st.standard_cauchy(), float) +assert_type(random_st.standard_cauchy(size=None), float) +assert_type(random_st.standard_cauchy(size=1), npt.NDArray[np.float64]) + +assert_type(random_st.standard_exponential(), float) +assert_type(random_st.standard_exponential(size=None), float) +assert_type(random_st.standard_exponential(size=1), npt.NDArray[np.float64]) + +assert_type(random_st.zipf(1.5), int) +assert_type(random_st.zipf(1.5, size=None), int) +assert_type(random_st.zipf(1.5, size=1), npt.NDArray[np.long]) +assert_type(random_st.zipf(D_arr_1p5), npt.NDArray[np.long]) +assert_type(random_st.zipf(D_arr_1p5, size=1), npt.NDArray[np.long]) +assert_type(random_st.zipf(D_arr_like_1p5), npt.NDArray[np.long]) +assert_type(random_st.zipf(D_arr_like_1p5, size=1), npt.NDArray[np.long]) + +assert_type(random_st.weibull(0.5), float) +assert_type(random_st.weibull(0.5, size=None), float) +assert_type(random_st.weibull(0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.weibull(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.weibull(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.weibull(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.weibull(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.standard_t(0.5), float) +assert_type(random_st.standard_t(0.5, size=None), float) +assert_type(random_st.standard_t(0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.standard_t(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.standard_t(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.standard_t(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.standard_t(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.poisson(0.5), int) +assert_type(random_st.poisson(0.5, size=None), int) +assert_type(random_st.poisson(0.5, size=1), npt.NDArray[np.long]) +assert_type(random_st.poisson(D_arr_0p5), npt.NDArray[np.long]) +assert_type(random_st.poisson(D_arr_0p5, size=1), npt.NDArray[np.long]) +assert_type(random_st.poisson(D_arr_like_0p5), npt.NDArray[np.long]) +assert_type(random_st.poisson(D_arr_like_0p5, size=1), npt.NDArray[np.long]) + +assert_type(random_st.power(0.5), float) +assert_type(random_st.power(0.5, size=None), float) +assert_type(random_st.power(0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.power(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.power(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.power(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.power(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.pareto(0.5), float) +assert_type(random_st.pareto(0.5, size=None), float) +assert_type(random_st.pareto(0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.pareto(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.pareto(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.pareto(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.pareto(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.chisquare(0.5), float) +assert_type(random_st.chisquare(0.5, size=None), float) +assert_type(random_st.chisquare(0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.chisquare(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.chisquare(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.chisquare(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.chisquare(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.exponential(0.5), float) +assert_type(random_st.exponential(0.5, size=None), float) +assert_type(random_st.exponential(0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.exponential(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.exponential(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.exponential(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.exponential(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.geometric(0.5), int) +assert_type(random_st.geometric(0.5, size=None), int) +assert_type(random_st.geometric(0.5, size=1), npt.NDArray[np.long]) +assert_type(random_st.geometric(D_arr_0p5), npt.NDArray[np.long]) +assert_type(random_st.geometric(D_arr_0p5, size=1), npt.NDArray[np.long]) +assert_type(random_st.geometric(D_arr_like_0p5), npt.NDArray[np.long]) +assert_type(random_st.geometric(D_arr_like_0p5, size=1), npt.NDArray[np.long]) + +assert_type(random_st.logseries(0.5), int) +assert_type(random_st.logseries(0.5, size=None), int) +assert_type(random_st.logseries(0.5, size=1), npt.NDArray[np.long]) +assert_type(random_st.logseries(D_arr_0p5), npt.NDArray[np.long]) +assert_type(random_st.logseries(D_arr_0p5, size=1), npt.NDArray[np.long]) +assert_type(random_st.logseries(D_arr_like_0p5), npt.NDArray[np.long]) +assert_type(random_st.logseries(D_arr_like_0p5, size=1), npt.NDArray[np.long]) + +assert_type(random_st.rayleigh(0.5), float) +assert_type(random_st.rayleigh(0.5, size=None), float) +assert_type(random_st.rayleigh(0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.rayleigh(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.rayleigh(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.rayleigh(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.rayleigh(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.standard_gamma(0.5), float) +assert_type(random_st.standard_gamma(0.5, size=None), float) +assert_type(random_st.standard_gamma(0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.standard_gamma(D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.standard_gamma(D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.standard_gamma(D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.standard_gamma(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.standard_gamma(D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.vonmises(0.5, 0.5), float) +assert_type(random_st.vonmises(0.5, 0.5, size=None), float) +assert_type(random_st.vonmises(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.vonmises(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.vonmises(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.vonmises(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.vonmises(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.vonmises(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.vonmises(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.vonmises(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.vonmises(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.vonmises(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.vonmises(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.wald(0.5, 0.5), float) +assert_type(random_st.wald(0.5, 0.5, size=None), float) +assert_type(random_st.wald(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.wald(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.wald(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.wald(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.wald(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.wald(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.wald(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.wald(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.wald(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.wald(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.wald(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.uniform(0.5, 0.5), float) +assert_type(random_st.uniform(0.5, 0.5, size=None), float) +assert_type(random_st.uniform(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.uniform(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.uniform(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.uniform(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.uniform(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.uniform(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.uniform(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.uniform(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.uniform(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.uniform(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.uniform(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.beta(0.5, 0.5), float) +assert_type(random_st.beta(0.5, 0.5, size=None), float) +assert_type(random_st.beta(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.beta(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.beta(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.beta(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.beta(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.beta(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.beta(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.beta(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.beta(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.beta(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.beta(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.f(0.5, 0.5), float) +assert_type(random_st.f(0.5, 0.5, size=None), float) +assert_type(random_st.f(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.f(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.f(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.f(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.f(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.f(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.f(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.f(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.f(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.f(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.f(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.gamma(0.5, 0.5), float) +assert_type(random_st.gamma(0.5, 0.5, size=None), float) +assert_type(random_st.gamma(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.gamma(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.gamma(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.gamma(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.gamma(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.gamma(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.gamma(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.gamma(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.gamma(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.gamma(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.gamma(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.gumbel(0.5, 0.5), float) +assert_type(random_st.gumbel(0.5, 0.5, size=None), float) +assert_type(random_st.gumbel(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.gumbel(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.gumbel(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.gumbel(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.gumbel(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.gumbel(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.gumbel(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.gumbel(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.gumbel(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.gumbel(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.gumbel(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.laplace(0.5, 0.5), float) +assert_type(random_st.laplace(0.5, 0.5, size=None), float) +assert_type(random_st.laplace(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.laplace(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.laplace(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.laplace(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.laplace(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.laplace(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.laplace(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.laplace(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.laplace(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.laplace(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.laplace(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.logistic(0.5, 0.5), float) +assert_type(random_st.logistic(0.5, 0.5, size=None), float) +assert_type(random_st.logistic(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.logistic(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.logistic(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.logistic(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.logistic(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.logistic(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.logistic(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.logistic(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.logistic(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.logistic(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.logistic(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.lognormal(0.5, 0.5), float) +assert_type(random_st.lognormal(0.5, 0.5, size=None), float) +assert_type(random_st.lognormal(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.lognormal(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.lognormal(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.lognormal(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.lognormal(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.lognormal(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.lognormal(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.lognormal(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.lognormal(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.lognormal(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.lognormal(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.noncentral_chisquare(0.5, 0.5), float) +assert_type(random_st.noncentral_chisquare(0.5, 0.5, size=None), float) +assert_type(random_st.noncentral_chisquare(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_chisquare(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_chisquare(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_chisquare(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_chisquare(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_chisquare(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_chisquare(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_chisquare(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_chisquare(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_chisquare(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_chisquare(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.normal(0.5, 0.5), float) +assert_type(random_st.normal(0.5, 0.5, size=None), float) +assert_type(random_st.normal(0.5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.normal(D_arr_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.normal(0.5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.normal(D_arr_0p5, 0.5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.normal(0.5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.normal(D_arr_like_0p5, 0.5), npt.NDArray[np.float64]) +assert_type(random_st.normal(0.5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.normal(D_arr_0p5, D_arr_0p5), npt.NDArray[np.float64]) +assert_type(random_st.normal(D_arr_like_0p5, D_arr_like_0p5), npt.NDArray[np.float64]) +assert_type(random_st.normal(D_arr_0p5, D_arr_0p5, size=1), npt.NDArray[np.float64]) +assert_type(random_st.normal(D_arr_like_0p5, D_arr_like_0p5, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.triangular(0.1, 0.5, 0.9), float) +assert_type(random_st.triangular(0.1, 0.5, 0.9, size=None), float) +assert_type(random_st.triangular(0.1, 0.5, 0.9, size=1), npt.NDArray[np.float64]) +assert_type(random_st.triangular(D_arr_0p1, 0.5, 0.9), npt.NDArray[np.float64]) +assert_type(random_st.triangular(0.1, D_arr_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(random_st.triangular(D_arr_0p1, 0.5, D_arr_like_0p9, size=1), npt.NDArray[np.float64]) +assert_type(random_st.triangular(0.1, D_arr_0p5, 0.9, size=1), npt.NDArray[np.float64]) +assert_type(random_st.triangular(D_arr_like_0p1, 0.5, D_arr_0p9), npt.NDArray[np.float64]) +assert_type(random_st.triangular(0.5, D_arr_like_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(random_st.triangular(D_arr_0p1, D_arr_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(random_st.triangular(D_arr_like_0p1, D_arr_like_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(random_st.triangular(D_arr_0p1, D_arr_0p5, D_arr_0p9, size=1), npt.NDArray[np.float64]) +assert_type(random_st.triangular(D_arr_like_0p1, D_arr_like_0p5, D_arr_like_0p9, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.noncentral_f(0.1, 0.5, 0.9), float) +assert_type(random_st.noncentral_f(0.1, 0.5, 0.9, size=None), float) +assert_type(random_st.noncentral_f(0.1, 0.5, 0.9, size=1), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_f(D_arr_0p1, 0.5, 0.9), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_f(0.1, D_arr_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_f(D_arr_0p1, 0.5, D_arr_like_0p9, size=1), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_f(0.1, D_arr_0p5, 0.9, size=1), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_f(D_arr_like_0p1, 0.5, D_arr_0p9), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_f(0.5, D_arr_like_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_f(D_arr_0p1, D_arr_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_f(D_arr_like_0p1, D_arr_like_0p5, 0.9), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_f(D_arr_0p1, D_arr_0p5, D_arr_0p9, size=1), npt.NDArray[np.float64]) +assert_type(random_st.noncentral_f(D_arr_like_0p1, D_arr_like_0p5, D_arr_like_0p9, size=1), npt.NDArray[np.float64]) + +assert_type(random_st.binomial(10, 0.5), int) +assert_type(random_st.binomial(10, 0.5, size=None), int) +assert_type(random_st.binomial(10, 0.5, size=1), npt.NDArray[np.long]) +assert_type(random_st.binomial(I_arr_10, 0.5), npt.NDArray[np.long]) +assert_type(random_st.binomial(10, D_arr_0p5), npt.NDArray[np.long]) +assert_type(random_st.binomial(I_arr_10, 0.5, size=1), npt.NDArray[np.long]) +assert_type(random_st.binomial(10, D_arr_0p5, size=1), npt.NDArray[np.long]) +assert_type(random_st.binomial(I_arr_like_10, 0.5), npt.NDArray[np.long]) +assert_type(random_st.binomial(10, D_arr_like_0p5), npt.NDArray[np.long]) +assert_type(random_st.binomial(I_arr_10, D_arr_0p5), npt.NDArray[np.long]) +assert_type(random_st.binomial(I_arr_like_10, D_arr_like_0p5), npt.NDArray[np.long]) +assert_type(random_st.binomial(I_arr_10, D_arr_0p5, size=1), npt.NDArray[np.long]) +assert_type(random_st.binomial(I_arr_like_10, D_arr_like_0p5, size=1), npt.NDArray[np.long]) + +assert_type(random_st.negative_binomial(10, 0.5), int) +assert_type(random_st.negative_binomial(10, 0.5, size=None), int) +assert_type(random_st.negative_binomial(10, 0.5, size=1), npt.NDArray[np.long]) +assert_type(random_st.negative_binomial(I_arr_10, 0.5), npt.NDArray[np.long]) +assert_type(random_st.negative_binomial(10, D_arr_0p5), npt.NDArray[np.long]) +assert_type(random_st.negative_binomial(I_arr_10, 0.5, size=1), npt.NDArray[np.long]) +assert_type(random_st.negative_binomial(10, D_arr_0p5, size=1), npt.NDArray[np.long]) +assert_type(random_st.negative_binomial(I_arr_like_10, 0.5), npt.NDArray[np.long]) +assert_type(random_st.negative_binomial(10, D_arr_like_0p5), npt.NDArray[np.long]) +assert_type(random_st.negative_binomial(I_arr_10, D_arr_0p5), npt.NDArray[np.long]) +assert_type(random_st.negative_binomial(I_arr_like_10, D_arr_like_0p5), npt.NDArray[np.long]) +assert_type(random_st.negative_binomial(I_arr_10, D_arr_0p5, size=1), npt.NDArray[np.long]) +assert_type(random_st.negative_binomial(I_arr_like_10, D_arr_like_0p5, size=1), npt.NDArray[np.long]) + +assert_type(random_st.hypergeometric(20, 20, 10), int) +assert_type(random_st.hypergeometric(20, 20, 10, size=None), int) +assert_type(random_st.hypergeometric(20, 20, 10, size=1), npt.NDArray[np.long]) +assert_type(random_st.hypergeometric(I_arr_20, 20, 10), npt.NDArray[np.long]) +assert_type(random_st.hypergeometric(20, I_arr_20, 10), npt.NDArray[np.long]) +assert_type(random_st.hypergeometric(I_arr_20, 20, I_arr_like_10, size=1), npt.NDArray[np.long]) +assert_type(random_st.hypergeometric(20, I_arr_20, 10, size=1), npt.NDArray[np.long]) +assert_type(random_st.hypergeometric(I_arr_like_20, 20, I_arr_10), npt.NDArray[np.long]) +assert_type(random_st.hypergeometric(20, I_arr_like_20, 10), npt.NDArray[np.long]) +assert_type(random_st.hypergeometric(I_arr_20, I_arr_20, 10), npt.NDArray[np.long]) +assert_type(random_st.hypergeometric(I_arr_like_20, I_arr_like_20, 10), npt.NDArray[np.long]) +assert_type(random_st.hypergeometric(I_arr_20, I_arr_20, I_arr_10, size=1), npt.NDArray[np.long]) +assert_type(random_st.hypergeometric(I_arr_like_20, I_arr_like_20, I_arr_like_10, size=1), npt.NDArray[np.long]) + +assert_type(random_st.randint(0, 100), int) +assert_type(random_st.randint(100), int) +assert_type(random_st.randint([100]), npt.NDArray[np.long]) +assert_type(random_st.randint(0, [100]), npt.NDArray[np.long]) + +assert_type(random_st.randint(2, dtype=bool), bool) +assert_type(random_st.randint(0, 2, dtype=bool), bool) +assert_type(random_st.randint(I_bool_high_open, dtype=bool), npt.NDArray[np.bool]) +assert_type(random_st.randint(I_bool_low, I_bool_high_open, dtype=bool), npt.NDArray[np.bool]) +assert_type(random_st.randint(0, I_bool_high_open, dtype=bool), npt.NDArray[np.bool]) + +assert_type(random_st.randint(2, dtype=np.bool), np.bool) +assert_type(random_st.randint(0, 2, dtype=np.bool), np.bool) +assert_type(random_st.randint(I_bool_high_open, dtype=np.bool), npt.NDArray[np.bool]) +assert_type(random_st.randint(I_bool_low, I_bool_high_open, dtype=np.bool), npt.NDArray[np.bool]) +assert_type(random_st.randint(0, I_bool_high_open, dtype=np.bool), npt.NDArray[np.bool]) + +assert_type(random_st.randint(256, dtype="u1"), np.uint8) +assert_type(random_st.randint(0, 256, dtype="u1"), np.uint8) +assert_type(random_st.randint(I_u1_high_open, dtype="u1"), npt.NDArray[np.uint8]) +assert_type(random_st.randint(I_u1_low, I_u1_high_open, dtype="u1"), npt.NDArray[np.uint8]) +assert_type(random_st.randint(0, I_u1_high_open, dtype="u1"), npt.NDArray[np.uint8]) + +assert_type(random_st.randint(256, dtype="uint8"), np.uint8) +assert_type(random_st.randint(0, 256, dtype="uint8"), np.uint8) +assert_type(random_st.randint(I_u1_high_open, dtype="uint8"), npt.NDArray[np.uint8]) +assert_type(random_st.randint(I_u1_low, I_u1_high_open, dtype="uint8"), npt.NDArray[np.uint8]) +assert_type(random_st.randint(0, I_u1_high_open, dtype="uint8"), npt.NDArray[np.uint8]) + +assert_type(random_st.randint(256, dtype=np.uint8), np.uint8) +assert_type(random_st.randint(0, 256, dtype=np.uint8), np.uint8) +assert_type(random_st.randint(I_u1_high_open, dtype=np.uint8), npt.NDArray[np.uint8]) +assert_type(random_st.randint(I_u1_low, I_u1_high_open, dtype=np.uint8), npt.NDArray[np.uint8]) +assert_type(random_st.randint(0, I_u1_high_open, dtype=np.uint8), npt.NDArray[np.uint8]) + +assert_type(random_st.randint(65536, dtype="u2"), np.uint16) +assert_type(random_st.randint(0, 65536, dtype="u2"), np.uint16) +assert_type(random_st.randint(I_u2_high_open, dtype="u2"), npt.NDArray[np.uint16]) +assert_type(random_st.randint(I_u2_low, I_u2_high_open, dtype="u2"), npt.NDArray[np.uint16]) +assert_type(random_st.randint(0, I_u2_high_open, dtype="u2"), npt.NDArray[np.uint16]) + +assert_type(random_st.randint(65536, dtype="uint16"), np.uint16) +assert_type(random_st.randint(0, 65536, dtype="uint16"), np.uint16) +assert_type(random_st.randint(I_u2_high_open, dtype="uint16"), npt.NDArray[np.uint16]) +assert_type(random_st.randint(I_u2_low, I_u2_high_open, dtype="uint16"), npt.NDArray[np.uint16]) +assert_type(random_st.randint(0, I_u2_high_open, dtype="uint16"), npt.NDArray[np.uint16]) + +assert_type(random_st.randint(65536, dtype=np.uint16), np.uint16) +assert_type(random_st.randint(0, 65536, dtype=np.uint16), np.uint16) +assert_type(random_st.randint(I_u2_high_open, dtype=np.uint16), npt.NDArray[np.uint16]) +assert_type(random_st.randint(I_u2_low, I_u2_high_open, dtype=np.uint16), npt.NDArray[np.uint16]) +assert_type(random_st.randint(0, I_u2_high_open, dtype=np.uint16), npt.NDArray[np.uint16]) + +assert_type(random_st.randint(4294967296, dtype="u4"), np.uint32) +assert_type(random_st.randint(0, 4294967296, dtype="u4"), np.uint32) +assert_type(random_st.randint(I_u4_high_open, dtype="u4"), npt.NDArray[np.uint32]) +assert_type(random_st.randint(I_u4_low, I_u4_high_open, dtype="u4"), npt.NDArray[np.uint32]) +assert_type(random_st.randint(0, I_u4_high_open, dtype="u4"), npt.NDArray[np.uint32]) + +assert_type(random_st.randint(4294967296, dtype="uint32"), np.uint32) +assert_type(random_st.randint(0, 4294967296, dtype="uint32"), np.uint32) +assert_type(random_st.randint(I_u4_high_open, dtype="uint32"), npt.NDArray[np.uint32]) +assert_type(random_st.randint(I_u4_low, I_u4_high_open, dtype="uint32"), npt.NDArray[np.uint32]) +assert_type(random_st.randint(0, I_u4_high_open, dtype="uint32"), npt.NDArray[np.uint32]) + +assert_type(random_st.randint(4294967296, dtype=np.uint32), np.uint32) +assert_type(random_st.randint(0, 4294967296, dtype=np.uint32), np.uint32) +assert_type(random_st.randint(I_u4_high_open, dtype=np.uint32), npt.NDArray[np.uint32]) +assert_type(random_st.randint(I_u4_low, I_u4_high_open, dtype=np.uint32), npt.NDArray[np.uint32]) +assert_type(random_st.randint(0, I_u4_high_open, dtype=np.uint32), npt.NDArray[np.uint32]) + +assert_type(random_st.randint(4294967296, dtype=np.uint), np.uint) +assert_type(random_st.randint(0, 4294967296, dtype=np.uint), np.uint) +assert_type(random_st.randint(I_u4_high_open, dtype=np.uint), npt.NDArray[np.uint]) +assert_type(random_st.randint(I_u4_low, I_u4_high_open, dtype=np.uint), npt.NDArray[np.uint]) +assert_type(random_st.randint(0, I_u4_high_open, dtype=np.uint), npt.NDArray[np.uint]) + +assert_type(random_st.randint(18446744073709551616, dtype="u8"), np.uint64) +assert_type(random_st.randint(0, 18446744073709551616, dtype="u8"), np.uint64) +assert_type(random_st.randint(I_u8_high_open, dtype="u8"), npt.NDArray[np.uint64]) +assert_type(random_st.randint(I_u8_low, I_u8_high_open, dtype="u8"), npt.NDArray[np.uint64]) +assert_type(random_st.randint(0, I_u8_high_open, dtype="u8"), npt.NDArray[np.uint64]) + +assert_type(random_st.randint(18446744073709551616, dtype="uint64"), np.uint64) +assert_type(random_st.randint(0, 18446744073709551616, dtype="uint64"), np.uint64) +assert_type(random_st.randint(I_u8_high_open, dtype="uint64"), npt.NDArray[np.uint64]) +assert_type(random_st.randint(I_u8_low, I_u8_high_open, dtype="uint64"), npt.NDArray[np.uint64]) +assert_type(random_st.randint(0, I_u8_high_open, dtype="uint64"), npt.NDArray[np.uint64]) + +assert_type(random_st.randint(18446744073709551616, dtype=np.uint64), np.uint64) +assert_type(random_st.randint(0, 18446744073709551616, dtype=np.uint64), np.uint64) +assert_type(random_st.randint(I_u8_high_open, dtype=np.uint64), npt.NDArray[np.uint64]) +assert_type(random_st.randint(I_u8_low, I_u8_high_open, dtype=np.uint64), npt.NDArray[np.uint64]) +assert_type(random_st.randint(0, I_u8_high_open, dtype=np.uint64), npt.NDArray[np.uint64]) + +assert_type(random_st.randint(128, dtype="i1"), np.int8) +assert_type(random_st.randint(-128, 128, dtype="i1"), np.int8) +assert_type(random_st.randint(I_i1_high_open, dtype="i1"), npt.NDArray[np.int8]) +assert_type(random_st.randint(I_i1_low, I_i1_high_open, dtype="i1"), npt.NDArray[np.int8]) +assert_type(random_st.randint(-128, I_i1_high_open, dtype="i1"), npt.NDArray[np.int8]) + +assert_type(random_st.randint(128, dtype="int8"), np.int8) +assert_type(random_st.randint(-128, 128, dtype="int8"), np.int8) +assert_type(random_st.randint(I_i1_high_open, dtype="int8"), npt.NDArray[np.int8]) +assert_type(random_st.randint(I_i1_low, I_i1_high_open, dtype="int8"), npt.NDArray[np.int8]) +assert_type(random_st.randint(-128, I_i1_high_open, dtype="int8"), npt.NDArray[np.int8]) + +assert_type(random_st.randint(128, dtype=np.int8), np.int8) +assert_type(random_st.randint(-128, 128, dtype=np.int8), np.int8) +assert_type(random_st.randint(I_i1_high_open, dtype=np.int8), npt.NDArray[np.int8]) +assert_type(random_st.randint(I_i1_low, I_i1_high_open, dtype=np.int8), npt.NDArray[np.int8]) +assert_type(random_st.randint(-128, I_i1_high_open, dtype=np.int8), npt.NDArray[np.int8]) + +assert_type(random_st.randint(32768, dtype="i2"), np.int16) +assert_type(random_st.randint(-32768, 32768, dtype="i2"), np.int16) +assert_type(random_st.randint(I_i2_high_open, dtype="i2"), npt.NDArray[np.int16]) +assert_type(random_st.randint(I_i2_low, I_i2_high_open, dtype="i2"), npt.NDArray[np.int16]) +assert_type(random_st.randint(-32768, I_i2_high_open, dtype="i2"), npt.NDArray[np.int16]) + +assert_type(random_st.randint(32768, dtype="int16"), np.int16) +assert_type(random_st.randint(-32768, 32768, dtype="int16"), np.int16) +assert_type(random_st.randint(I_i2_high_open, dtype="int16"), npt.NDArray[np.int16]) +assert_type(random_st.randint(I_i2_low, I_i2_high_open, dtype="int16"), npt.NDArray[np.int16]) +assert_type(random_st.randint(-32768, I_i2_high_open, dtype="int16"), npt.NDArray[np.int16]) + +assert_type(random_st.randint(32768, dtype=np.int16), np.int16) +assert_type(random_st.randint(-32768, 32768, dtype=np.int16), np.int16) +assert_type(random_st.randint(I_i2_high_open, dtype=np.int16), npt.NDArray[np.int16]) +assert_type(random_st.randint(I_i2_low, I_i2_high_open, dtype=np.int16), npt.NDArray[np.int16]) +assert_type(random_st.randint(-32768, I_i2_high_open, dtype=np.int16), npt.NDArray[np.int16]) + +assert_type(random_st.randint(2147483648, dtype="i4"), np.int32) +assert_type(random_st.randint(-2147483648, 2147483648, dtype="i4"), np.int32) +assert_type(random_st.randint(I_i4_high_open, dtype="i4"), npt.NDArray[np.int32]) +assert_type(random_st.randint(I_i4_low, I_i4_high_open, dtype="i4"), npt.NDArray[np.int32]) +assert_type(random_st.randint(-2147483648, I_i4_high_open, dtype="i4"), npt.NDArray[np.int32]) + +assert_type(random_st.randint(2147483648, dtype="int32"), np.int32) +assert_type(random_st.randint(-2147483648, 2147483648, dtype="int32"), np.int32) +assert_type(random_st.randint(I_i4_high_open, dtype="int32"), npt.NDArray[np.int32]) +assert_type(random_st.randint(I_i4_low, I_i4_high_open, dtype="int32"), npt.NDArray[np.int32]) +assert_type(random_st.randint(-2147483648, I_i4_high_open, dtype="int32"), npt.NDArray[np.int32]) + +assert_type(random_st.randint(2147483648, dtype=np.int32), np.int32) +assert_type(random_st.randint(-2147483648, 2147483648, dtype=np.int32), np.int32) +assert_type(random_st.randint(I_i4_high_open, dtype=np.int32), npt.NDArray[np.int32]) +assert_type(random_st.randint(I_i4_low, I_i4_high_open, dtype=np.int32), npt.NDArray[np.int32]) +assert_type(random_st.randint(-2147483648, I_i4_high_open, dtype=np.int32), npt.NDArray[np.int32]) + +assert_type(random_st.randint(2147483648, dtype=np.int_), np.int_) +assert_type(random_st.randint(-2147483648, 2147483648, dtype=np.int_), np.int_) +assert_type(random_st.randint(I_i4_high_open, dtype=np.int_), npt.NDArray[np.int_]) +assert_type(random_st.randint(I_i4_low, I_i4_high_open, dtype=np.int_), npt.NDArray[np.int_]) +assert_type(random_st.randint(-2147483648, I_i4_high_open, dtype=np.int_), npt.NDArray[np.int_]) + +assert_type(random_st.randint(9223372036854775808, dtype="i8"), np.int64) +assert_type(random_st.randint(-9223372036854775808, 9223372036854775808, dtype="i8"), np.int64) +assert_type(random_st.randint(I_i8_high_open, dtype="i8"), npt.NDArray[np.int64]) +assert_type(random_st.randint(I_i8_low, I_i8_high_open, dtype="i8"), npt.NDArray[np.int64]) +assert_type(random_st.randint(-9223372036854775808, I_i8_high_open, dtype="i8"), npt.NDArray[np.int64]) + +assert_type(random_st.randint(9223372036854775808, dtype="int64"), np.int64) +assert_type(random_st.randint(-9223372036854775808, 9223372036854775808, dtype="int64"), np.int64) +assert_type(random_st.randint(I_i8_high_open, dtype="int64"), npt.NDArray[np.int64]) +assert_type(random_st.randint(I_i8_low, I_i8_high_open, dtype="int64"), npt.NDArray[np.int64]) +assert_type(random_st.randint(-9223372036854775808, I_i8_high_open, dtype="int64"), npt.NDArray[np.int64]) + +assert_type(random_st.randint(9223372036854775808, dtype=np.int64), np.int64) +assert_type(random_st.randint(-9223372036854775808, 9223372036854775808, dtype=np.int64), np.int64) +assert_type(random_st.randint(I_i8_high_open, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(random_st.randint(I_i8_low, I_i8_high_open, dtype=np.int64), npt.NDArray[np.int64]) +assert_type(random_st.randint(-9223372036854775808, I_i8_high_open, dtype=np.int64), npt.NDArray[np.int64]) + +assert_type(random_st._bit_generator, np.random.BitGenerator) + +assert_type(random_st.bytes(2), bytes) + +assert_type(random_st.choice(5), int) +assert_type(random_st.choice(5, 3), npt.NDArray[np.long]) +assert_type(random_st.choice(5, 3, replace=True), npt.NDArray[np.long]) +assert_type(random_st.choice(5, 3, p=[1 / 5] * 5), npt.NDArray[np.long]) +assert_type(random_st.choice(5, 3, p=[1 / 5] * 5, replace=False), npt.NDArray[np.long]) + +assert_type(random_st.choice(["pooh", "rabbit", "piglet", "Christopher"]), Any) +assert_type(random_st.choice(["pooh", "rabbit", "piglet", "Christopher"], 3), npt.NDArray[Any]) +assert_type(random_st.choice(["pooh", "rabbit", "piglet", "Christopher"], 3, p=[1 / 4] * 4), npt.NDArray[Any]) +assert_type(random_st.choice(["pooh", "rabbit", "piglet", "Christopher"], 3, replace=True), npt.NDArray[Any]) +assert_type(random_st.choice(["pooh", "rabbit", "piglet", "Christopher"], 3, replace=False, p=np.array([1 / 8, 1 / 8, 1 / 2, 1 / 4])), npt.NDArray[Any]) + +assert_type(random_st.dirichlet([0.5, 0.5]), npt.NDArray[np.float64]) +assert_type(random_st.dirichlet(np.array([0.5, 0.5])), npt.NDArray[np.float64]) +assert_type(random_st.dirichlet(np.array([0.5, 0.5]), size=3), npt.NDArray[np.float64]) + +assert_type(random_st.multinomial(20, [1 / 6.0] * 6), npt.NDArray[np.long]) +assert_type(random_st.multinomial(20, np.array([0.5, 0.5])), npt.NDArray[np.long]) +assert_type(random_st.multinomial(20, [1 / 6.0] * 6, size=2), npt.NDArray[np.long]) + +assert_type(random_st.multivariate_normal([0.0], [[1.0]]), npt.NDArray[np.float64]) +assert_type(random_st.multivariate_normal([0.0], np.array([[1.0]])), npt.NDArray[np.float64]) +assert_type(random_st.multivariate_normal(np.array([0.0]), [[1.0]]), npt.NDArray[np.float64]) +assert_type(random_st.multivariate_normal([0.0], np.array([[1.0]])), npt.NDArray[np.float64]) + +assert_type(random_st.permutation(10), npt.NDArray[np.long]) +assert_type(random_st.permutation([1, 2, 3, 4]), npt.NDArray[Any]) +assert_type(random_st.permutation(np.array([1, 2, 3, 4])), npt.NDArray[Any]) +assert_type(random_st.permutation(D_2D), npt.NDArray[Any]) + +assert_type(random_st.shuffle(np.arange(10)), None) +assert_type(random_st.shuffle([1, 2, 3, 4, 5]), None) +assert_type(random_st.shuffle(D_2D), None) + +assert_type(np.random.RandomState(pcg64), np.random.RandomState) +assert_type(np.random.RandomState(0), np.random.RandomState) +assert_type(np.random.RandomState([0, 1, 2]), np.random.RandomState) +assert_type(random_st.__str__(), str) +assert_type(random_st.__repr__(), str) +random_st_state = random_st.__getstate__() +assert_type(random_st_state, dict[str, Any]) +assert_type(random_st.__setstate__(random_st_state), None) +assert_type(random_st.seed(), None) +assert_type(random_st.seed(1), None) +assert_type(random_st.seed([0, 1]), None) +random_st_get_state = random_st.get_state() +assert_type(random_st_state, dict[str, Any]) +random_st_get_state_legacy = random_st.get_state(legacy=True) +assert_type(random_st_get_state_legacy, dict[str, Any] | tuple[str, npt.NDArray[np.uint32], int, int, float]) +assert_type(random_st.set_state(random_st_get_state), None) + +assert_type(random_st.rand(), float) +assert_type(random_st.rand(1), npt.NDArray[np.float64]) +assert_type(random_st.rand(1, 2), npt.NDArray[np.float64]) +assert_type(random_st.randn(), float) +assert_type(random_st.randn(1), npt.NDArray[np.float64]) +assert_type(random_st.randn(1, 2), npt.NDArray[np.float64]) +assert_type(random_st.random_sample(), float) +assert_type(random_st.random_sample(1), npt.NDArray[np.float64]) +assert_type(random_st.random_sample(size=(1, 2)), npt.NDArray[np.float64]) + +assert_type(random_st.tomaxint(), int) +assert_type(random_st.tomaxint(1), npt.NDArray[np.int64]) +assert_type(random_st.tomaxint((1,)), npt.NDArray[np.int64]) + +assert_type(np.random.mtrand.set_bit_generator(pcg64), None) +assert_type(np.random.mtrand.get_bit_generator(), np.random.BitGenerator) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/rec.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/rec.pyi new file mode 100644 index 0000000000000000000000000000000000000000..aacf217e42072cacc9a245d7d7faef8cb340f2c2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/rec.pyi @@ -0,0 +1,171 @@ +import io +from typing import Any, TypeAlias, assert_type + +import numpy as np +import numpy.typing as npt + +_RecArray: TypeAlias = np.recarray[tuple[Any, ...], np.dtype[np.record]] + +AR_i8: npt.NDArray[np.int64] +REC_AR_V: _RecArray +AR_LIST: list[npt.NDArray[np.int64]] + +record: np.record +file_obj: io.BufferedIOBase + +assert_type(np.rec.format_parser( + formats=[np.float64, np.int64, np.bool], + names=["f8", "i8", "?"], + titles=None, + aligned=True, +), np.rec.format_parser) +assert_type(np.rec.format_parser.dtype, np.dtype[np.void]) + +assert_type(record.field_a, Any) +assert_type(record.field_b, Any) +assert_type(record["field_a"], Any) +assert_type(record["field_b"], Any) +assert_type(record.pprint(), str) +record.field_c = 5 + +assert_type(REC_AR_V.field(0), Any) +assert_type(REC_AR_V.field("field_a"), Any) +assert_type(REC_AR_V.field(0, AR_i8), None) +assert_type(REC_AR_V.field("field_a", AR_i8), None) +assert_type(REC_AR_V["field_a"], npt.NDArray[Any]) +assert_type(REC_AR_V.field_a, Any) +assert_type(REC_AR_V.__array_finalize__(object()), None) + +assert_type( + np.recarray( + shape=(10, 5), + formats=[np.float64, np.int64, np.bool], + order="K", + byteorder="|", + ), + _RecArray, +) + +assert_type( + np.recarray( + shape=(10, 5), + dtype=[("f8", np.float64), ("i8", np.int64)], + strides=(5, 5), + ), + np.recarray, +) + +assert_type(np.rec.fromarrays(AR_LIST), np.recarray) +assert_type( + np.rec.fromarrays(AR_LIST, dtype=np.int64), + np.recarray, +) +assert_type( + np.rec.fromarrays( + AR_LIST, + formats=[np.int64, np.float64], + names=["i8", "f8"] + ), + _RecArray, +) + +assert_type( + np.rec.fromrecords((1, 1.5)), + _RecArray +) + +assert_type( + np.rec.fromrecords( + [(1, 1.5)], + dtype=[("i8", np.int64), ("f8", np.float64)], + ), + _RecArray, +) + +assert_type( + np.rec.fromrecords( + REC_AR_V, + formats=[np.int64, np.float64], + names=["i8", "f8"] + ), + _RecArray, +) + +assert_type( + np.rec.fromstring( + b"(1, 1.5)", + dtype=[("i8", np.int64), ("f8", np.float64)], + ), + _RecArray, +) + +assert_type( + np.rec.fromstring( + REC_AR_V, + formats=[np.int64, np.float64], + names=["i8", "f8"] + ), + _RecArray, +) + +assert_type( + np.rec.fromfile( + "test_file.txt", + dtype=[("i8", np.int64), ("f8", np.float64)], + ), + np.recarray, +) + +assert_type( + np.rec.fromfile( + file_obj, + formats=[np.int64, np.float64], + names=["i8", "f8"] + ), + _RecArray, +) + +assert_type(np.rec.array(AR_i8), np.recarray[tuple[Any, ...], np.dtype[np.int64]]) + +assert_type( + np.rec.array([(1, 1.5)], dtype=[("i8", np.int64), ("f8", np.float64)]), + np.recarray, +) + +assert_type( + np.rec.array( + [(1, 1.5)], + formats=[np.int64, np.float64], + names=["i8", "f8"] + ), + _RecArray, +) + +assert_type( + np.rec.array( + None, + dtype=np.float64, + shape=(10, 3), + ), + np.recarray, +) + +assert_type( + np.rec.array( + None, + formats=[np.int64, np.float64], + names=["i8", "f8"], + shape=(10, 3), + ), + _RecArray, +) + +assert_type( + np.rec.array(file_obj, dtype=np.float64), + np.recarray, +) + +assert_type( + np.rec.array(file_obj, formats=[np.int64, np.float64], names=["i8", "f8"]), + _RecArray, +) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/scalars.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/scalars.pyi new file mode 100644 index 0000000000000000000000000000000000000000..67444e33dfc389e164092afee1423ac29a16ed44 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/scalars.pyi @@ -0,0 +1,191 @@ +from typing import Any, Literal, TypeAlias, assert_type + +import numpy as np + +_1: TypeAlias = Literal[1] + +b: np.bool +u8: np.uint64 +i8: np.int64 +f8: np.float64 +c8: np.complex64 +c16: np.complex128 +m: np.timedelta64 +U: np.str_ +S: np.bytes_ +V: np.void +O: np.object_ # cannot exists at runtime + +array_nd: np.ndarray[Any, Any] +array_0d: np.ndarray[tuple[()], Any] +array_2d_2x2: np.ndarray[tuple[Literal[2], Literal[2]], Any] + +assert_type(c8.real, np.float32) +assert_type(c8.imag, np.float32) + +assert_type(c8.real.real, np.float32) +assert_type(c8.real.imag, np.float32) + +assert_type(c8.itemsize, int) +assert_type(c8.shape, tuple[()]) +assert_type(c8.strides, tuple[()]) + +assert_type(c8.ndim, Literal[0]) +assert_type(c8.size, Literal[1]) + +assert_type(c8.squeeze(), np.complex64) +assert_type(c8.byteswap(), np.complex64) +assert_type(c8.transpose(), np.complex64) + +assert_type(c8.dtype, np.dtype[np.complex64]) + +assert_type(c8.real, np.float32) +assert_type(c16.imag, np.float64) + +assert_type(np.str_("foo"), np.str_) + +assert_type(V[0], Any) +assert_type(V["field1"], Any) +assert_type(V[["field1", "field2"]], np.void) +V[0] = 5 + +# Aliases +assert_type(np.bool_(), np.bool[Literal[False]]) +assert_type(np.byte(), np.byte) +assert_type(np.short(), np.short) +assert_type(np.intc(), np.intc) +assert_type(np.intp(), np.intp) +assert_type(np.int_(), np.int_) +assert_type(np.long(), np.long) +assert_type(np.longlong(), np.longlong) + +assert_type(np.ubyte(), np.ubyte) +assert_type(np.ushort(), np.ushort) +assert_type(np.uintc(), np.uintc) +assert_type(np.uintp(), np.uintp) +assert_type(np.uint(), np.uint) +assert_type(np.ulong(), np.ulong) +assert_type(np.ulonglong(), np.ulonglong) + +assert_type(np.half(), np.half) +assert_type(np.single(), np.single) +assert_type(np.double(), np.double) +assert_type(np.longdouble(), np.longdouble) + +assert_type(np.csingle(), np.csingle) +assert_type(np.cdouble(), np.cdouble) +assert_type(np.clongdouble(), np.clongdouble) + +assert_type(b.item(), bool) +assert_type(i8.item(), int) +assert_type(u8.item(), int) +assert_type(f8.item(), float) +assert_type(c16.item(), complex) +assert_type(U.item(), str) +assert_type(S.item(), bytes) + +assert_type(b.tolist(), bool) +assert_type(i8.tolist(), int) +assert_type(u8.tolist(), int) +assert_type(f8.tolist(), float) +assert_type(c16.tolist(), complex) +assert_type(U.tolist(), str) +assert_type(S.tolist(), bytes) + +assert_type(b.ravel(), np.ndarray[tuple[int], np.dtype[np.bool]]) +assert_type(i8.ravel(), np.ndarray[tuple[int], np.dtype[np.int64]]) +assert_type(u8.ravel(), np.ndarray[tuple[int], np.dtype[np.uint64]]) +assert_type(f8.ravel(), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(c16.ravel(), np.ndarray[tuple[int], np.dtype[np.complex128]]) +assert_type(U.ravel(), np.ndarray[tuple[int], np.dtype[np.str_]]) +assert_type(S.ravel(), np.ndarray[tuple[int], np.dtype[np.bytes_]]) + +assert_type(b.flatten(), np.ndarray[tuple[int], np.dtype[np.bool]]) +assert_type(i8.flatten(), np.ndarray[tuple[int], np.dtype[np.int64]]) +assert_type(u8.flatten(), np.ndarray[tuple[int], np.dtype[np.uint64]]) +assert_type(f8.flatten(), np.ndarray[tuple[int], np.dtype[np.float64]]) +assert_type(c16.flatten(), np.ndarray[tuple[int], np.dtype[np.complex128]]) +assert_type(U.flatten(), np.ndarray[tuple[int], np.dtype[np.str_]]) +assert_type(S.flatten(), np.ndarray[tuple[int], np.dtype[np.bytes_]]) + +assert_type(b.reshape(()), np.bool) +assert_type(i8.reshape([]), np.int64) +assert_type(b.reshape(1), np.ndarray[tuple[_1], np.dtype[np.bool]]) +assert_type(i8.reshape(-1), np.ndarray[tuple[_1], np.dtype[np.int64]]) +assert_type(u8.reshape(1, 1), np.ndarray[tuple[_1, _1], np.dtype[np.uint64]]) +assert_type(f8.reshape(1, -1), np.ndarray[tuple[_1, _1], np.dtype[np.float64]]) +assert_type(c16.reshape(1, 1, 1), np.ndarray[tuple[_1, _1, _1], np.dtype[np.complex128]]) +assert_type(U.reshape(1, 1, 1, 1), np.ndarray[tuple[_1, _1, _1, _1], np.dtype[np.str_]]) +assert_type( + S.reshape(1, 1, 1, 1, 1), + np.ndarray[ + # len(shape) >= 5 + tuple[_1, _1, _1, _1, _1, *tuple[_1, ...]], + np.dtype[np.bytes_], + ], +) + +assert_type(i8.astype(float), Any) +assert_type(i8.astype(np.float64), np.float64) + +assert_type(i8.view(), np.int64) +assert_type(i8.view(np.float64), np.float64) +assert_type(i8.view(float), Any) +assert_type(i8.view(np.float64, np.ndarray), np.float64) + +assert_type(i8.getfield(float), Any) +assert_type(i8.getfield(np.float64), np.float64) +assert_type(i8.getfield(np.float64, 8), np.float64) + +assert_type(f8.as_integer_ratio(), tuple[int, int]) +assert_type(f8.is_integer(), bool) +assert_type(f8.__trunc__(), int) +assert_type(f8.__getformat__("float"), str) +assert_type(f8.hex(), str) +assert_type(np.float64.fromhex("0x0.0p+0"), np.float64) + +assert_type(f8.__getnewargs__(), tuple[float]) +assert_type(c16.__getnewargs__(), tuple[float, float]) + +assert_type(i8.numerator, np.int64) +assert_type(i8.denominator, Literal[1]) +assert_type(u8.numerator, np.uint64) +assert_type(u8.denominator, Literal[1]) +assert_type(m.numerator, np.timedelta64) +assert_type(m.denominator, Literal[1]) + +assert_type(round(i8), int) +assert_type(round(i8, 3), np.int64) +assert_type(round(u8), int) +assert_type(round(u8, 3), np.uint64) +assert_type(round(f8), int) +assert_type(round(f8, 3), np.float64) + +assert_type(f8.__ceil__(), int) +assert_type(f8.__floor__(), int) + +assert_type(i8.is_integer(), Literal[True]) + +assert_type(O.real, np.object_) +assert_type(O.imag, np.object_) +assert_type(int(O), int) +assert_type(float(O), float) +assert_type(complex(O), complex) + +# These fail fail because of a mypy __new__ bug: +# https://github.com/python/mypy/issues/15182 +# According to the typing spec, the following statements are valid, see +# https://typing.readthedocs.io/en/latest/spec/constructors.html#new-method + +# assert_type(np.object_(), None) +# assert_type(np.object_(None), None) +# assert_type(np.object_(array_nd), np.ndarray[Any, np.dtype[np.object_]]) +# assert_type(np.object_([]), npt.NDArray[np.object_]) +# assert_type(np.object_(()), npt.NDArray[np.object_]) +# assert_type(np.object_(range(4)), npt.NDArray[np.object_]) +# assert_type(np.object_(+42), int) +# assert_type(np.object_(1 / 137), float) +# assert_type(np.object_('Developers! ' * (1 << 6)), str) +# assert_type(np.object_(object()), object) +# assert_type(np.object_({False, True, NotADirectoryError}), set[Any]) +# assert_type(np.object_({'spam': 'food', 'ham': 'food'}), dict[str, str]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/shape.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/shape.pyi new file mode 100644 index 0000000000000000000000000000000000000000..2406a39f9682b66623bd9879afdfcfe311c5f869 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/shape.pyi @@ -0,0 +1,13 @@ +from typing import Any, NamedTuple, assert_type + +import numpy as np + +# Subtype of tuple[int, int] +class XYGrid(NamedTuple): + x_axis: int + y_axis: int + +arr: np.ndarray[XYGrid, Any] + +# Test shape property matches shape typevar +assert_type(arr.shape, XYGrid) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/shape_base.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/shape_base.pyi new file mode 100644 index 0000000000000000000000000000000000000000..e409a53bcef95ad549769011cf0a7d28ea78320e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/shape_base.pyi @@ -0,0 +1,52 @@ +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt + +i8: np.int64 +f8: np.float64 + +AR_b: npt.NDArray[np.bool] +AR_i8: npt.NDArray[np.int64] +AR_f8: npt.NDArray[np.float64] + +AR_LIKE_f8: list[float] + +assert_type(np.take_along_axis(AR_f8, AR_i8, axis=1), npt.NDArray[np.float64]) +assert_type(np.take_along_axis(f8, AR_i8, axis=None), npt.NDArray[np.float64]) + +assert_type(np.put_along_axis(AR_f8, AR_i8, "1.0", axis=1), None) + +assert_type(np.expand_dims(AR_i8, 2), npt.NDArray[np.int64]) +assert_type(np.expand_dims(AR_LIKE_f8, 2), npt.NDArray[Any]) + +assert_type(np.column_stack([AR_i8]), npt.NDArray[np.int64]) +assert_type(np.column_stack([AR_LIKE_f8]), npt.NDArray[Any]) + +assert_type(np.dstack([AR_i8]), npt.NDArray[np.int64]) +assert_type(np.dstack([AR_LIKE_f8]), npt.NDArray[Any]) + +assert_type(np.array_split(AR_i8, [3, 5, 6, 10]), list[npt.NDArray[np.int64]]) +assert_type(np.array_split(AR_LIKE_f8, [3, 5, 6, 10]), list[npt.NDArray[Any]]) + +assert_type(np.split(AR_i8, [3, 5, 6, 10]), list[npt.NDArray[np.int64]]) +assert_type(np.split(AR_LIKE_f8, [3, 5, 6, 10]), list[npt.NDArray[Any]]) + +assert_type(np.hsplit(AR_i8, [3, 5, 6, 10]), list[npt.NDArray[np.int64]]) +assert_type(np.hsplit(AR_LIKE_f8, [3, 5, 6, 10]), list[npt.NDArray[Any]]) + +assert_type(np.vsplit(AR_i8, [3, 5, 6, 10]), list[npt.NDArray[np.int64]]) +assert_type(np.vsplit(AR_LIKE_f8, [3, 5, 6, 10]), list[npt.NDArray[Any]]) + +assert_type(np.dsplit(AR_i8, [3, 5, 6, 10]), list[npt.NDArray[np.int64]]) +assert_type(np.dsplit(AR_LIKE_f8, [3, 5, 6, 10]), list[npt.NDArray[Any]]) + +assert_type(np.kron(AR_b, AR_b), npt.NDArray[np.bool]) +assert_type(np.kron(AR_b, AR_i8), npt.NDArray[np.signedinteger]) +assert_type(np.kron(AR_f8, AR_f8), npt.NDArray[np.floating]) + +assert_type(np.tile(AR_i8, 5), npt.NDArray[np.int64]) +assert_type(np.tile(AR_LIKE_f8, [2, 2]), npt.NDArray[Any]) + +assert_type(np.unstack(AR_i8, axis=0), tuple[npt.NDArray[np.int64], ...]) +assert_type(np.unstack(AR_LIKE_f8, axis=0), tuple[npt.NDArray[Any], ...]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/stride_tricks.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/stride_tricks.pyi new file mode 100644 index 0000000000000000000000000000000000000000..8fde9b8ae30dd6dd25b1d4f6f68c1321e6f3c0a0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/stride_tricks.pyi @@ -0,0 +1,27 @@ +from typing import Any, assert_type + +import numpy as np +import numpy.typing as npt + +AR_f8: npt.NDArray[np.float64] +AR_LIKE_f: list[float] +interface_dict: dict[str, Any] + +assert_type(np.lib.stride_tricks.as_strided(AR_f8), npt.NDArray[np.float64]) +assert_type(np.lib.stride_tricks.as_strided(AR_LIKE_f), npt.NDArray[Any]) +assert_type(np.lib.stride_tricks.as_strided(AR_f8, strides=(1, 5)), npt.NDArray[np.float64]) +assert_type(np.lib.stride_tricks.as_strided(AR_f8, shape=[9, 20]), npt.NDArray[np.float64]) + +assert_type(np.lib.stride_tricks.sliding_window_view(AR_f8, 5), npt.NDArray[np.float64]) +assert_type(np.lib.stride_tricks.sliding_window_view(AR_LIKE_f, (1, 5)), npt.NDArray[Any]) +assert_type(np.lib.stride_tricks.sliding_window_view(AR_f8, [9], axis=1), npt.NDArray[np.float64]) + +assert_type(np.broadcast_to(AR_f8, 5), npt.NDArray[np.float64]) +assert_type(np.broadcast_to(AR_LIKE_f, (1, 5)), npt.NDArray[Any]) +assert_type(np.broadcast_to(AR_f8, [4, 6], subok=True), npt.NDArray[np.float64]) + +assert_type(np.broadcast_shapes((1, 2), [3, 1], (3, 2)), tuple[Any, ...]) +assert_type(np.broadcast_shapes((6, 7), (5, 6, 1), 7, (5, 1, 7)), tuple[Any, ...]) + +assert_type(np.broadcast_arrays(AR_f8, AR_f8), tuple[npt.NDArray[Any], ...]) +assert_type(np.broadcast_arrays(AR_f8, AR_LIKE_f), tuple[npt.NDArray[Any], ...]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/strings.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/strings.pyi new file mode 100644 index 0000000000000000000000000000000000000000..18bd252d5ff90f34878ba34fd150bf17093cdc61 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/strings.pyi @@ -0,0 +1,196 @@ +from typing import TypeAlias, assert_type + +import numpy as np +import numpy._typing as np_t +import numpy.typing as npt + +AR_T_alias: TypeAlias = np.ndarray[np_t._AnyShape, np.dtypes.StringDType] +AR_TU_alias: TypeAlias = AR_T_alias | npt.NDArray[np.str_] + +AR_U: npt.NDArray[np.str_] +AR_S: npt.NDArray[np.bytes_] +AR_T: AR_T_alias + +assert_type(np.strings.equal(AR_U, AR_U), npt.NDArray[np.bool]) +assert_type(np.strings.equal(AR_S, AR_S), npt.NDArray[np.bool]) +assert_type(np.strings.equal(AR_T, AR_T), npt.NDArray[np.bool]) + +assert_type(np.strings.not_equal(AR_U, AR_U), npt.NDArray[np.bool]) +assert_type(np.strings.not_equal(AR_S, AR_S), npt.NDArray[np.bool]) +assert_type(np.strings.not_equal(AR_T, AR_T), npt.NDArray[np.bool]) + +assert_type(np.strings.greater_equal(AR_U, AR_U), npt.NDArray[np.bool]) +assert_type(np.strings.greater_equal(AR_S, AR_S), npt.NDArray[np.bool]) +assert_type(np.strings.greater_equal(AR_T, AR_T), npt.NDArray[np.bool]) + +assert_type(np.strings.less_equal(AR_U, AR_U), npt.NDArray[np.bool]) +assert_type(np.strings.less_equal(AR_S, AR_S), npt.NDArray[np.bool]) +assert_type(np.strings.less_equal(AR_T, AR_T), npt.NDArray[np.bool]) + +assert_type(np.strings.greater(AR_U, AR_U), npt.NDArray[np.bool]) +assert_type(np.strings.greater(AR_S, AR_S), npt.NDArray[np.bool]) +assert_type(np.strings.greater(AR_T, AR_T), npt.NDArray[np.bool]) + +assert_type(np.strings.less(AR_U, AR_U), npt.NDArray[np.bool]) +assert_type(np.strings.less(AR_S, AR_S), npt.NDArray[np.bool]) +assert_type(np.strings.less(AR_T, AR_T), npt.NDArray[np.bool]) + +assert_type(np.strings.add(AR_U, AR_U), npt.NDArray[np.str_]) +assert_type(np.strings.add(AR_S, AR_S), npt.NDArray[np.bytes_]) +assert_type(np.strings.add(AR_T, AR_T), AR_T_alias) + +assert_type(np.strings.multiply(AR_U, 5), npt.NDArray[np.str_]) +assert_type(np.strings.multiply(AR_S, [5, 4, 3]), npt.NDArray[np.bytes_]) +assert_type(np.strings.multiply(AR_T, 5), AR_T_alias) + +assert_type(np.strings.mod(AR_U, "test"), npt.NDArray[np.str_]) +assert_type(np.strings.mod(AR_S, "test"), npt.NDArray[np.bytes_]) +assert_type(np.strings.mod(AR_T, "test"), AR_T_alias) + +assert_type(np.strings.capitalize(AR_U), npt.NDArray[np.str_]) +assert_type(np.strings.capitalize(AR_S), npt.NDArray[np.bytes_]) +assert_type(np.strings.capitalize(AR_T), AR_T_alias) + +assert_type(np.strings.center(AR_U, 5), npt.NDArray[np.str_]) +assert_type(np.strings.center(AR_S, [2, 3, 4], b"a"), npt.NDArray[np.bytes_]) +assert_type(np.strings.center(AR_T, 5), AR_T_alias) + +assert_type(np.strings.encode(AR_U), npt.NDArray[np.bytes_]) +assert_type(np.strings.encode(AR_T), npt.NDArray[np.bytes_]) +assert_type(np.strings.decode(AR_S), npt.NDArray[np.str_]) + +assert_type(np.strings.expandtabs(AR_U), npt.NDArray[np.str_]) +assert_type(np.strings.expandtabs(AR_S, tabsize=4), npt.NDArray[np.bytes_]) +assert_type(np.strings.expandtabs(AR_T), AR_T_alias) + +assert_type(np.strings.ljust(AR_U, 5), npt.NDArray[np.str_]) +assert_type(np.strings.ljust(AR_S, [4, 3, 1], fillchar=[b"a", b"b", b"c"]), npt.NDArray[np.bytes_]) +assert_type(np.strings.ljust(AR_T, 5), AR_T_alias) +assert_type(np.strings.ljust(AR_T, [4, 2, 1], fillchar=["a", "b", "c"]), AR_T_alias) + +assert_type(np.strings.rjust(AR_U, 5), npt.NDArray[np.str_]) +assert_type(np.strings.rjust(AR_S, [4, 3, 1], fillchar=[b"a", b"b", b"c"]), npt.NDArray[np.bytes_]) +assert_type(np.strings.rjust(AR_T, 5), AR_T_alias) +assert_type(np.strings.rjust(AR_T, [4, 2, 1], fillchar=["a", "b", "c"]), AR_T_alias) + +assert_type(np.strings.lstrip(AR_U), npt.NDArray[np.str_]) +assert_type(np.strings.lstrip(AR_S, b"_"), npt.NDArray[np.bytes_]) +assert_type(np.strings.lstrip(AR_T), AR_T_alias) +assert_type(np.strings.lstrip(AR_T, "_"), AR_T_alias) + +assert_type(np.strings.rstrip(AR_U), npt.NDArray[np.str_]) +assert_type(np.strings.rstrip(AR_S, b"_"), npt.NDArray[np.bytes_]) +assert_type(np.strings.rstrip(AR_T), AR_T_alias) +assert_type(np.strings.rstrip(AR_T, "_"), AR_T_alias) + +assert_type(np.strings.strip(AR_U), npt.NDArray[np.str_]) +assert_type(np.strings.strip(AR_S, b"_"), npt.NDArray[np.bytes_]) +assert_type(np.strings.strip(AR_T), AR_T_alias) +assert_type(np.strings.strip(AR_T, "_"), AR_T_alias) + +assert_type(np.strings.count(AR_U, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(np.strings.count(AR_S, [b"a", b"b", b"c"], end=9), npt.NDArray[np.int_]) +assert_type(np.strings.count(AR_T, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(np.strings.count(AR_T, ["a", "b", "c"], end=9), npt.NDArray[np.int_]) + +assert_type(np.strings.partition(AR_U, "\n"), npt.NDArray[np.str_]) +assert_type(np.strings.partition(AR_S, [b"a", b"b", b"c"]), npt.NDArray[np.bytes_]) +assert_type(np.strings.partition(AR_T, "\n"), AR_TU_alias) + +assert_type(np.strings.rpartition(AR_U, "\n"), npt.NDArray[np.str_]) +assert_type(np.strings.rpartition(AR_S, [b"a", b"b", b"c"]), npt.NDArray[np.bytes_]) +assert_type(np.strings.rpartition(AR_T, "\n"), AR_TU_alias) + +assert_type(np.strings.replace(AR_U, "_", "-"), npt.NDArray[np.str_]) +assert_type(np.strings.replace(AR_S, [b"_", b""], [b"a", b"b"]), npt.NDArray[np.bytes_]) +assert_type(np.strings.replace(AR_T, "_", "_"), AR_TU_alias) + +assert_type(np.strings.lower(AR_U), npt.NDArray[np.str_]) +assert_type(np.strings.lower(AR_S), npt.NDArray[np.bytes_]) +assert_type(np.strings.lower(AR_T), AR_T_alias) + +assert_type(np.strings.upper(AR_U), npt.NDArray[np.str_]) +assert_type(np.strings.upper(AR_S), npt.NDArray[np.bytes_]) +assert_type(np.strings.upper(AR_T), AR_T_alias) + +assert_type(np.strings.swapcase(AR_U), npt.NDArray[np.str_]) +assert_type(np.strings.swapcase(AR_S), npt.NDArray[np.bytes_]) +assert_type(np.strings.swapcase(AR_T), AR_T_alias) + +assert_type(np.strings.title(AR_U), npt.NDArray[np.str_]) +assert_type(np.strings.title(AR_S), npt.NDArray[np.bytes_]) +assert_type(np.strings.title(AR_T), AR_T_alias) + +assert_type(np.strings.zfill(AR_U, 5), npt.NDArray[np.str_]) +assert_type(np.strings.zfill(AR_S, [2, 3, 4]), npt.NDArray[np.bytes_]) +assert_type(np.strings.zfill(AR_T, 5), AR_T_alias) + +assert_type(np.strings.endswith(AR_U, "a", start=[1, 2, 3]), npt.NDArray[np.bool]) +assert_type(np.strings.endswith(AR_S, [b"a", b"b", b"c"], end=9), npt.NDArray[np.bool]) +assert_type(np.strings.endswith(AR_T, "a", start=[1, 2, 3]), npt.NDArray[np.bool]) + +assert_type(np.strings.startswith(AR_U, "a", start=[1, 2, 3]), npt.NDArray[np.bool]) +assert_type(np.strings.startswith(AR_S, [b"a", b"b", b"c"], end=9), npt.NDArray[np.bool]) +assert_type(np.strings.startswith(AR_T, "a", start=[1, 2, 3]), npt.NDArray[np.bool]) + +assert_type(np.strings.find(AR_U, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(np.strings.find(AR_S, [b"a", b"b", b"c"], end=9), npt.NDArray[np.int_]) +assert_type(np.strings.find(AR_T, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) + +assert_type(np.strings.rfind(AR_U, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(np.strings.rfind(AR_S, [b"a", b"b", b"c"], end=9), npt.NDArray[np.int_]) +assert_type(np.strings.rfind(AR_T, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) + +assert_type(np.strings.index(AR_U, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(np.strings.index(AR_S, [b"a", b"b", b"c"], end=9), npt.NDArray[np.int_]) +assert_type(np.strings.index(AR_T, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) + +assert_type(np.strings.rindex(AR_U, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) +assert_type(np.strings.rindex(AR_S, [b"a", b"b", b"c"], end=9), npt.NDArray[np.int_]) +assert_type(np.strings.rindex(AR_T, "a", start=[1, 2, 3]), npt.NDArray[np.int_]) + +assert_type(np.strings.isalpha(AR_U), npt.NDArray[np.bool]) +assert_type(np.strings.isalpha(AR_S), npt.NDArray[np.bool]) +assert_type(np.strings.isalpha(AR_T), npt.NDArray[np.bool]) + +assert_type(np.strings.isalnum(AR_U), npt.NDArray[np.bool]) +assert_type(np.strings.isalnum(AR_S), npt.NDArray[np.bool]) +assert_type(np.strings.isalnum(AR_T), npt.NDArray[np.bool]) + +assert_type(np.strings.isdecimal(AR_U), npt.NDArray[np.bool]) +assert_type(np.strings.isdecimal(AR_T), npt.NDArray[np.bool]) + +assert_type(np.strings.isdigit(AR_U), npt.NDArray[np.bool]) +assert_type(np.strings.isdigit(AR_S), npt.NDArray[np.bool]) +assert_type(np.strings.isdigit(AR_T), npt.NDArray[np.bool]) + +assert_type(np.strings.islower(AR_U), npt.NDArray[np.bool]) +assert_type(np.strings.islower(AR_S), npt.NDArray[np.bool]) +assert_type(np.strings.islower(AR_T), npt.NDArray[np.bool]) + +assert_type(np.strings.isnumeric(AR_U), npt.NDArray[np.bool]) +assert_type(np.strings.isnumeric(AR_T), npt.NDArray[np.bool]) + +assert_type(np.strings.isspace(AR_U), npt.NDArray[np.bool]) +assert_type(np.strings.isspace(AR_S), npt.NDArray[np.bool]) +assert_type(np.strings.isspace(AR_T), npt.NDArray[np.bool]) + +assert_type(np.strings.istitle(AR_U), npt.NDArray[np.bool]) +assert_type(np.strings.istitle(AR_S), npt.NDArray[np.bool]) +assert_type(np.strings.istitle(AR_T), npt.NDArray[np.bool]) + +assert_type(np.strings.isupper(AR_U), npt.NDArray[np.bool]) +assert_type(np.strings.isupper(AR_S), npt.NDArray[np.bool]) +assert_type(np.strings.isupper(AR_T), npt.NDArray[np.bool]) + +assert_type(np.strings.str_len(AR_U), npt.NDArray[np.int_]) +assert_type(np.strings.str_len(AR_S), npt.NDArray[np.int_]) +assert_type(np.strings.str_len(AR_T), npt.NDArray[np.int_]) + +assert_type(np.strings.translate(AR_U, ""), npt.NDArray[np.str_]) +assert_type(np.strings.translate(AR_S, ""), npt.NDArray[np.bytes_]) +assert_type(np.strings.translate(AR_T, ""), AR_T_alias) + +assert_type(np.strings.slice(AR_U, 1, 5, 2), npt.NDArray[np.str_]) +assert_type(np.strings.slice(AR_S, 1, 5, 2), npt.NDArray[np.bytes_]) +assert_type(np.strings.slice(AR_T, 1, 5, 2), AR_T_alias) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/testing.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/testing.pyi new file mode 100644 index 0000000000000000000000000000000000000000..34fbc5feeb41b930293170c8ba78734a37a9eb07 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/testing.pyi @@ -0,0 +1,198 @@ +import contextlib +import re +import sys +import types +import unittest +import warnings +from collections.abc import Callable +from pathlib import Path +from typing import Any, TypeVar, assert_type + +import numpy as np +import numpy.typing as npt + +AR_f8: npt.NDArray[np.float64] +AR_i8: npt.NDArray[np.int64] + +bool_obj: bool +suppress_obj: np.testing.suppress_warnings # type: ignore[deprecated] # pyright: ignore[reportDeprecated] +FT = TypeVar("FT", bound=Callable[..., Any]) + +def func() -> int: ... + +def func2( + x: npt.NDArray[np.number], + y: npt.NDArray[np.number], +) -> npt.NDArray[np.bool]: ... + +assert_type(np.testing.KnownFailureException(), np.testing.KnownFailureException) +assert_type(np.testing.IgnoreException(), np.testing.IgnoreException) + +assert_type( + np.testing.clear_and_catch_warnings(modules=[np.testing]), + np.testing.clear_and_catch_warnings[None], +) +assert_type( + np.testing.clear_and_catch_warnings(True), + np.testing.clear_and_catch_warnings[list[warnings.WarningMessage]], +) +assert_type( + np.testing.clear_and_catch_warnings(False), + np.testing.clear_and_catch_warnings[None], +) +assert_type( + np.testing.clear_and_catch_warnings(bool_obj), + np.testing.clear_and_catch_warnings, +) +assert_type( + np.testing.clear_and_catch_warnings.class_modules, + tuple[types.ModuleType, ...], +) +assert_type( + np.testing.clear_and_catch_warnings.modules, + set[types.ModuleType], +) + +with np.testing.clear_and_catch_warnings(True) as c1: + assert_type(c1, list[warnings.WarningMessage]) +with np.testing.clear_and_catch_warnings() as c2: + assert_type(c2, None) + +assert_type(np.testing.suppress_warnings("once"), np.testing.suppress_warnings) # type: ignore[deprecated] # pyright: ignore[reportDeprecated] +assert_type(np.testing.suppress_warnings()(func), Callable[[], int]) # type: ignore[deprecated] # pyright: ignore[reportDeprecated] +assert_type(suppress_obj.filter(RuntimeWarning), None) +assert_type(suppress_obj.record(RuntimeWarning), list[warnings.WarningMessage]) +with suppress_obj as c3: + assert_type(c3, np.testing.suppress_warnings) # type: ignore[deprecated] # pyright: ignore[reportDeprecated] + +assert_type(np.testing.verbose, int) +assert_type(np.testing.IS_PYPY, bool) +assert_type(np.testing.HAS_REFCOUNT, bool) +assert_type(np.testing.HAS_LAPACK64, bool) + +assert_type(np.testing.assert_(1, msg="test"), None) +assert_type(np.testing.assert_(2, msg=lambda: "test"), None) + +if sys.platform == "win32" or sys.platform == "cygwin": + assert_type(np.testing.memusage(), int) +elif sys.platform == "linux": + assert_type(np.testing.memusage(), int | None) + +assert_type(np.testing.jiffies(), int) + +assert_type(np.testing.build_err_msg([0, 1, 2], "test"), str) +assert_type(np.testing.build_err_msg(range(2), "test", header="header"), str) +assert_type(np.testing.build_err_msg(np.arange(9).reshape(3, 3), "test", verbose=False), str) +assert_type(np.testing.build_err_msg("abc", "test", names=["x", "y"]), str) +assert_type(np.testing.build_err_msg([1.0, 2.0], "test", precision=5), str) + +assert_type(np.testing.assert_equal({1}, {1}), None) +assert_type(np.testing.assert_equal([1, 2, 3], [1, 2, 3], err_msg="fail"), None) +assert_type(np.testing.assert_equal(1, 1.0, verbose=True), None) + +assert_type(np.testing.print_assert_equal("Test XYZ of func xyz", [0, 1], [0, 1]), None) + +assert_type(np.testing.assert_almost_equal(1.0, 1.1), None) +assert_type(np.testing.assert_almost_equal([1, 2, 3], [1, 2, 3], err_msg="fail"), None) +assert_type(np.testing.assert_almost_equal(1, 1.0, verbose=True), None) +assert_type(np.testing.assert_almost_equal(1, 1.0001, decimal=2), None) + +assert_type(np.testing.assert_approx_equal(1.0, 1.1), None) +assert_type(np.testing.assert_approx_equal("1", "2", err_msg="fail"), None) +assert_type(np.testing.assert_approx_equal(1, 1.0, verbose=True), None) +assert_type(np.testing.assert_approx_equal(1, 1.0001, significant=2), None) + +assert_type(np.testing.assert_array_compare(func2, AR_i8, AR_f8, err_msg="test"), None) +assert_type(np.testing.assert_array_compare(func2, AR_i8, AR_f8, verbose=True), None) +assert_type(np.testing.assert_array_compare(func2, AR_i8, AR_f8, header="header"), None) +assert_type(np.testing.assert_array_compare(func2, AR_i8, AR_f8, precision=np.int64()), None) +assert_type(np.testing.assert_array_compare(func2, AR_i8, AR_f8, equal_nan=False), None) +assert_type(np.testing.assert_array_compare(func2, AR_i8, AR_f8, equal_inf=True), None) + +assert_type(np.testing.assert_array_equal(AR_i8, AR_f8), None) +assert_type(np.testing.assert_array_equal(AR_i8, AR_f8, err_msg="test"), None) +assert_type(np.testing.assert_array_equal(AR_i8, AR_f8, verbose=True), None) + +assert_type(np.testing.assert_array_almost_equal(AR_i8, AR_f8), None) +assert_type(np.testing.assert_array_almost_equal(AR_i8, AR_f8, err_msg="test"), None) +assert_type(np.testing.assert_array_almost_equal(AR_i8, AR_f8, verbose=True), None) +assert_type(np.testing.assert_array_almost_equal(AR_i8, AR_f8, decimal=1), None) + +assert_type(np.testing.assert_array_less(AR_i8, AR_f8), None) +assert_type(np.testing.assert_array_less(AR_i8, AR_f8, err_msg="test"), None) +assert_type(np.testing.assert_array_less(AR_i8, AR_f8, verbose=True), None) + +assert_type(np.testing.runstring("1 + 1", {}), Any) +assert_type(np.testing.runstring("int64() + 1", {"int64": np.int64}), Any) + +assert_type(np.testing.assert_string_equal("1", "1"), None) + +assert_type(np.testing.rundocs(), None) +assert_type(np.testing.rundocs("test.py"), None) +assert_type(np.testing.rundocs(Path("test.py"), raise_on_error=True), None) + +def func3(a: int) -> bool: ... + +assert_type( + np.testing.assert_raises(RuntimeWarning), + unittest.case._AssertRaisesContext[RuntimeWarning], +) +assert_type(np.testing.assert_raises(RuntimeWarning, func3, 5), None) + +assert_type( + np.testing.assert_raises_regex(RuntimeWarning, r"test"), + unittest.case._AssertRaisesContext[RuntimeWarning], +) +assert_type(np.testing.assert_raises_regex(RuntimeWarning, b"test", func3, 5), None) +assert_type(np.testing.assert_raises_regex(RuntimeWarning, re.compile(b"test"), func3, 5), None) + +class Test: ... + +def decorate(a: FT) -> FT: + return a + +assert_type(np.testing.decorate_methods(Test, decorate), None) +assert_type(np.testing.decorate_methods(Test, decorate, None), None) +assert_type(np.testing.decorate_methods(Test, decorate, "test"), None) +assert_type(np.testing.decorate_methods(Test, decorate, b"test"), None) +assert_type(np.testing.decorate_methods(Test, decorate, re.compile("test")), None) + +assert_type(np.testing.measure("for i in range(1000): np.sqrt(i**2)"), float) +assert_type(np.testing.measure(b"for i in range(1000): np.sqrt(i**2)", times=5), float) + +assert_type(np.testing.assert_allclose(AR_i8, AR_f8), None) +assert_type(np.testing.assert_allclose(AR_i8, AR_f8, rtol=0.005), None) +assert_type(np.testing.assert_allclose(AR_i8, AR_f8, atol=1), None) +assert_type(np.testing.assert_allclose(AR_i8, AR_f8, equal_nan=True), None) +assert_type(np.testing.assert_allclose(AR_i8, AR_f8, err_msg="err"), None) +assert_type(np.testing.assert_allclose(AR_i8, AR_f8, verbose=False), None) + +assert_type(np.testing.assert_array_almost_equal_nulp(AR_i8, AR_f8, nulp=2), None) + +assert_type(np.testing.assert_array_max_ulp(AR_i8, AR_f8, maxulp=2), npt.NDArray[Any]) +assert_type(np.testing.assert_array_max_ulp(AR_i8, AR_f8, dtype=np.float32), npt.NDArray[Any]) + +assert_type(np.testing.assert_warns(RuntimeWarning), contextlib._GeneratorContextManager[None]) # type: ignore[deprecated] # pyright: ignore[reportDeprecated] +assert_type(np.testing.assert_warns(RuntimeWarning, func3, 5), bool) # type: ignore[deprecated] # pyright: ignore[reportDeprecated] + +def func4(a: int, b: str) -> bool: ... + +assert_type(np.testing.assert_no_warnings(), contextlib._GeneratorContextManager[None]) +assert_type(np.testing.assert_no_warnings(func3, 5), bool) +assert_type(np.testing.assert_no_warnings(func4, a=1, b="test"), bool) +assert_type(np.testing.assert_no_warnings(func4, 1, "test"), bool) + +assert_type(np.testing.tempdir("test_dir"), contextlib._GeneratorContextManager[str]) +assert_type(np.testing.tempdir(prefix=b"test"), contextlib._GeneratorContextManager[bytes]) +assert_type(np.testing.tempdir("test_dir", dir=Path("here")), contextlib._GeneratorContextManager[str]) + +assert_type(np.testing.temppath("test_dir", text=True), contextlib._GeneratorContextManager[str]) +assert_type(np.testing.temppath(prefix=b"test"), contextlib._GeneratorContextManager[bytes]) +assert_type(np.testing.temppath("test_dir", dir=Path("here")), contextlib._GeneratorContextManager[str]) + +assert_type(np.testing.assert_no_gc_cycles(), contextlib._GeneratorContextManager[None]) +assert_type(np.testing.assert_no_gc_cycles(func3, 5), None) + +assert_type(np.testing.break_cycles(), None) + +assert_type(np.testing.TestCase(), unittest.case.TestCase) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/twodim_base.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/twodim_base.pyi new file mode 100644 index 0000000000000000000000000000000000000000..1fd17e36279bb87bf39fb26e3b3148945893f425 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/twodim_base.pyi @@ -0,0 +1,225 @@ +from typing import Any, TypeAlias, TypeVar, assert_type, type_check_only + +import numpy as np +import numpy.typing as npt + +_ScalarT = TypeVar("_ScalarT", bound=np.generic) + +_1D: TypeAlias = tuple[int] +_2D: TypeAlias = tuple[int, int] +_ND: TypeAlias = tuple[Any, ...] + +_Indices2D: TypeAlias = tuple[ + np.ndarray[_1D, np.dtype[np.intp]], + np.ndarray[_1D, np.dtype[np.intp]], +] + +### + +_nd_bool: np.ndarray[_ND, np.dtype[np.bool]] +_1d_bool: np.ndarray[_1D, np.dtype[np.bool]] +_2d_bool: np.ndarray[_2D, np.dtype[np.bool]] +_nd_u64: np.ndarray[_ND, np.dtype[np.uint64]] +_nd_i64: np.ndarray[_ND, np.dtype[np.int64]] +_nd_f64: np.ndarray[_ND, np.dtype[np.float64]] +_nd_c128: np.ndarray[_ND, np.dtype[np.complex128]] +_nd_obj: np.ndarray[_ND, np.dtype[np.object_]] + +_to_nd_bool: list[bool] | list[list[bool]] +_to_1d_bool: list[bool] +_to_2d_bool: list[list[bool]] + +_to_1d_f64: list[float] +_to_1d_c128: list[complex] + +@type_check_only +def func1(ar: npt.NDArray[_ScalarT], a: int) -> npt.NDArray[_ScalarT]: ... +@type_check_only +def func2(ar: npt.NDArray[np.number], a: str) -> npt.NDArray[np.float64]: ... + +@type_check_only +class _Cube: + shape = 3, 4 + ndim = 2 + +### + +# fliplr +assert_type(np.fliplr(_nd_bool), np.ndarray[_ND, np.dtype[np.bool]]) +assert_type(np.fliplr(_1d_bool), np.ndarray[_1D, np.dtype[np.bool]]) +assert_type(np.fliplr(_2d_bool), np.ndarray[_2D, np.dtype[np.bool]]) +assert_type(np.fliplr(_to_nd_bool), np.ndarray) +assert_type(np.fliplr(_to_1d_bool), np.ndarray) +assert_type(np.fliplr(_to_2d_bool), np.ndarray) + +# flipud +assert_type(np.flipud(_nd_bool), np.ndarray[_ND, np.dtype[np.bool]]) +assert_type(np.flipud(_1d_bool), np.ndarray[_1D, np.dtype[np.bool]]) +assert_type(np.flipud(_2d_bool), np.ndarray[_2D, np.dtype[np.bool]]) +assert_type(np.flipud(_to_nd_bool), np.ndarray) +assert_type(np.flipud(_to_1d_bool), np.ndarray) +assert_type(np.flipud(_to_2d_bool), np.ndarray) + +# eye +assert_type(np.eye(10), np.ndarray[_2D, np.dtype[np.float64]]) +assert_type(np.eye(10, M=20, dtype=np.int64), np.ndarray[_2D, np.dtype[np.int64]]) +assert_type(np.eye(10, k=2, dtype=int), np.ndarray[_2D]) + +# diag +assert_type(np.diag(_nd_bool), np.ndarray[_ND, np.dtype[np.bool]]) +assert_type(np.diag(_1d_bool), np.ndarray[_2D, np.dtype[np.bool]]) +assert_type(np.diag(_2d_bool), np.ndarray[_1D, np.dtype[np.bool]]) +assert_type(np.diag(_to_nd_bool, k=0), np.ndarray) +assert_type(np.diag(_to_1d_bool, k=0), np.ndarray[_2D]) +assert_type(np.diag(_to_2d_bool, k=0), np.ndarray[_1D]) + +# diagflat +assert_type(np.diagflat(_nd_bool), np.ndarray[_2D, np.dtype[np.bool]]) +assert_type(np.diagflat(_1d_bool), np.ndarray[_2D, np.dtype[np.bool]]) +assert_type(np.diagflat(_2d_bool), np.ndarray[_2D, np.dtype[np.bool]]) +assert_type(np.diagflat(_to_nd_bool, k=0), np.ndarray[_2D]) +assert_type(np.diagflat(_to_1d_bool, k=0), np.ndarray[_2D]) +assert_type(np.diagflat(_to_2d_bool, k=0), np.ndarray[_2D]) + +# tri +assert_type(np.tri(10), np.ndarray[_2D, np.dtype[np.float64]]) +assert_type(np.tri(10, M=20, dtype=np.int64), np.ndarray[_2D, np.dtype[np.int64]]) +assert_type(np.tri(10, k=2, dtype=int), np.ndarray[_2D]) + +# tril +assert_type(np.tril(_nd_bool), np.ndarray[_ND, np.dtype[np.bool]]) +assert_type(np.tril(_to_nd_bool, k=0), np.ndarray) +assert_type(np.tril(_to_1d_bool, k=0), np.ndarray) +assert_type(np.tril(_to_2d_bool, k=0), np.ndarray) + +# triu +assert_type(np.triu(_nd_bool), np.ndarray[_ND, np.dtype[np.bool]]) +assert_type(np.triu(_to_nd_bool, k=0), np.ndarray) +assert_type(np.triu(_to_1d_bool, k=0), np.ndarray) +assert_type(np.triu(_to_2d_bool, k=0), np.ndarray) + +# vander +assert_type(np.vander(_nd_bool), np.ndarray[_2D, np.dtype[np.int_]]) +assert_type(np.vander(_nd_u64), np.ndarray[_2D, np.dtype[np.uint64]]) +assert_type(np.vander(_nd_i64, N=2), np.ndarray[_2D, np.dtype[np.int64]]) +assert_type(np.vander(_nd_f64, increasing=True), np.ndarray[_2D, np.dtype[np.float64]]) +assert_type(np.vander(_nd_c128), np.ndarray[_2D, np.dtype[np.complex128]]) +assert_type(np.vander(_nd_obj), np.ndarray[_2D, np.dtype[np.object_]]) + +# histogram2d +assert_type( + np.histogram2d(_to_1d_f64, _to_1d_f64), + tuple[ + np.ndarray[_2D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.float64]], + ], +) +assert_type( + np.histogram2d(_to_1d_c128, _to_1d_c128), + tuple[ + np.ndarray[_2D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.complex128 | Any]], + np.ndarray[_1D, np.dtype[np.complex128 | Any]], + ], +) +assert_type( + np.histogram2d(_nd_i64, _nd_bool), + tuple[ + np.ndarray[_2D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.float64]], + ], +) +assert_type( + np.histogram2d(_nd_f64, _nd_i64), + tuple[ + np.ndarray[_2D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.float64]], + ], +) +assert_type( + np.histogram2d(_nd_i64, _nd_f64), + tuple[ + np.ndarray[_2D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.float64]], + ], +) +assert_type( + np.histogram2d(_nd_f64, _nd_c128, weights=_to_1d_bool), + tuple[ + np.ndarray[_2D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.complex128]], + np.ndarray[_1D, np.dtype[np.complex128]], + ], +) +assert_type( + np.histogram2d(_nd_f64, _nd_c128, bins=8), + tuple[ + np.ndarray[_2D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.complex128]], + np.ndarray[_1D, np.dtype[np.complex128]], + ], +) +assert_type( + np.histogram2d(_nd_c128, _nd_f64, bins=(8, 5)), + tuple[ + np.ndarray[_2D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.complex128]], + np.ndarray[_1D, np.dtype[np.complex128]], + ], +) +assert_type( + np.histogram2d(_nd_c128, _nd_i64, bins=_nd_u64), + tuple[ + np.ndarray[_2D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.uint64]], + np.ndarray[_1D, np.dtype[np.uint64]], + ], +) +assert_type( + np.histogram2d(_nd_c128, _nd_c128, bins=(_nd_u64, _nd_u64)), + tuple[ + np.ndarray[_2D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.uint64]], + np.ndarray[_1D, np.dtype[np.uint64]], + ], +) +assert_type( + np.histogram2d(_nd_c128, _nd_c128, bins=(_nd_bool, 8)), + tuple[ + np.ndarray[_2D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.complex128 | np.bool]], + np.ndarray[_1D, np.dtype[np.complex128 | np.bool]], + ], +) +assert_type( + np.histogram2d(_nd_c128, _nd_c128, bins=(_to_1d_f64, 8)), + tuple[ + np.ndarray[_2D, np.dtype[np.float64]], + np.ndarray[_1D, np.dtype[np.complex128 | Any]], + np.ndarray[_1D, np.dtype[np.complex128 | Any]], + ], +) + +# mask_indices +assert_type(np.mask_indices(10, func1), _Indices2D) +assert_type(np.mask_indices(8, func2, "0"), _Indices2D) + +# tril_indices +assert_type(np.tril_indices(3), _Indices2D) +assert_type(np.tril_indices(3, 1), _Indices2D) +assert_type(np.tril_indices(3, 1, 2), _Indices2D) +# tril_indices +assert_type(np.triu_indices(3), _Indices2D) +assert_type(np.triu_indices(3, 1), _Indices2D) +assert_type(np.triu_indices(3, 1, 2), _Indices2D) + +# tril_indices_from +assert_type(np.tril_indices_from(_2d_bool), _Indices2D) +assert_type(np.tril_indices_from(_Cube()), _Indices2D) +# triu_indices_from +assert_type(np.triu_indices_from(_2d_bool), _Indices2D) +assert_type(np.triu_indices_from(_Cube()), _Indices2D) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/type_check.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/type_check.pyi new file mode 100644 index 0000000000000000000000000000000000000000..df95da78ffb7a4669b88310739bb710d7d41f6ae --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/type_check.pyi @@ -0,0 +1,67 @@ +from typing import Any, Literal, assert_type + +import numpy as np +import numpy.typing as npt + +f8: np.float64 +f: float + +# NOTE: Avoid importing the platform specific `np.float128` type +AR_i8: npt.NDArray[np.int64] +AR_i4: npt.NDArray[np.int32] +AR_f2: npt.NDArray[np.float16] +AR_f8: npt.NDArray[np.float64] +AR_f16: npt.NDArray[np.longdouble] +AR_c8: npt.NDArray[np.complex64] +AR_c16: npt.NDArray[np.complex128] + +AR_LIKE_f: list[float] + +class ComplexObj: + real: slice + imag: slice + +assert_type(np.mintypecode(["f8"], typeset="qfQF"), str) + +assert_type(np.real(ComplexObj()), slice) +assert_type(np.real(AR_f8), npt.NDArray[np.float64]) +assert_type(np.real(AR_c16), npt.NDArray[np.float64]) +assert_type(np.real(AR_LIKE_f), npt.NDArray[Any]) + +assert_type(np.imag(ComplexObj()), slice) +assert_type(np.imag(AR_f8), npt.NDArray[np.float64]) +assert_type(np.imag(AR_c16), npt.NDArray[np.float64]) +assert_type(np.imag(AR_LIKE_f), npt.NDArray[Any]) + +assert_type(np.iscomplex(f8), np.bool) +assert_type(np.iscomplex(AR_f8), npt.NDArray[np.bool]) +assert_type(np.iscomplex(AR_LIKE_f), npt.NDArray[np.bool]) + +assert_type(np.isreal(f8), np.bool) +assert_type(np.isreal(AR_f8), npt.NDArray[np.bool]) +assert_type(np.isreal(AR_LIKE_f), npt.NDArray[np.bool]) + +assert_type(np.iscomplexobj(f8), bool) +assert_type(np.isrealobj(f8), bool) + +assert_type(np.nan_to_num(f8), np.float64) +assert_type(np.nan_to_num(f, copy=True), Any) +assert_type(np.nan_to_num(AR_f8, nan=1.5), npt.NDArray[np.float64]) +assert_type(np.nan_to_num(AR_LIKE_f, posinf=9999), npt.NDArray[Any]) + +assert_type(np.real_if_close(AR_f8), npt.NDArray[np.float64]) +assert_type(np.real_if_close(AR_c16), npt.NDArray[np.float64 | np.complex128]) +assert_type(np.real_if_close(AR_c8), npt.NDArray[np.float32 | np.complex64]) +assert_type(np.real_if_close(AR_LIKE_f), npt.NDArray[Any]) + +assert_type(np.typename("h"), Literal["short"]) +assert_type(np.typename("B"), Literal["unsigned char"]) +assert_type(np.typename("V"), Literal["void"]) +assert_type(np.typename("S1"), Literal["character"]) + +assert_type(np.common_type(AR_i4), type[np.float64]) +assert_type(np.common_type(AR_f2), type[np.float16]) +assert_type(np.common_type(AR_f2, AR_i4), type[np.float64]) +assert_type(np.common_type(AR_f16, AR_i4), type[np.longdouble]) +assert_type(np.common_type(AR_c8, AR_f2), type[np.complex64]) +assert_type(np.common_type(AR_f2, AR_c8, AR_i4), type[np.complexfloating]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ufunc_config.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ufunc_config.pyi new file mode 100644 index 0000000000000000000000000000000000000000..77c27eb3b4cabcc70e823ceff2aad7f437c87e9c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ufunc_config.pyi @@ -0,0 +1,29 @@ +"""Typing tests for `_core._ufunc_config`.""" + +from _typeshed import SupportsWrite +from collections.abc import Callable +from typing import Any, assert_type + +import numpy as np + +def func(a: str, b: int) -> None: ... + +class Write: + def write(self, value: str) -> None: ... + +assert_type(np.seterr(all=None), np._core._ufunc_config._ErrDict) +assert_type(np.seterr(divide="ignore"), np._core._ufunc_config._ErrDict) +assert_type(np.seterr(over="warn"), np._core._ufunc_config._ErrDict) +assert_type(np.seterr(under="call"), np._core._ufunc_config._ErrDict) +assert_type(np.seterr(invalid="raise"), np._core._ufunc_config._ErrDict) +assert_type(np.geterr(), np._core._ufunc_config._ErrDict) + +assert_type(np.setbufsize(4096), int) +assert_type(np.getbufsize(), int) + +assert_type(np.seterrcall(func), Callable[[str, int], Any] | SupportsWrite[str] | None) +assert_type(np.seterrcall(Write()), Callable[[str, int], Any] | SupportsWrite[str] | None) +assert_type(np.geterrcall(), Callable[[str, int], Any] | SupportsWrite[str] | None) + +assert_type(np.errstate(call=func, all="call"), np.errstate) +assert_type(np.errstate(call=Write(), divide="log", over="log"), np.errstate) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ufunclike.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ufunclike.pyi new file mode 100644 index 0000000000000000000000000000000000000000..c679b82d28367964f5cc15683fd3e388ced08ce1 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ufunclike.pyi @@ -0,0 +1,31 @@ +from typing import assert_type + +import numpy as np +import numpy.typing as npt + +AR_LIKE_b: list[bool] +AR_LIKE_u: list[np.uint32] +AR_LIKE_i: list[int] +AR_LIKE_f: list[float] +AR_LIKE_O: list[np.object_] + +AR_U: npt.NDArray[np.str_] + +assert_type(np.fix(AR_LIKE_b), npt.NDArray[np.floating]) # type: ignore[deprecated] +assert_type(np.fix(AR_LIKE_u), npt.NDArray[np.floating]) # type: ignore[deprecated] +assert_type(np.fix(AR_LIKE_i), npt.NDArray[np.floating]) # type: ignore[deprecated] +assert_type(np.fix(AR_LIKE_f), npt.NDArray[np.floating]) # type: ignore[deprecated] +assert_type(np.fix(AR_LIKE_O), npt.NDArray[np.object_]) # type: ignore[deprecated] +assert_type(np.fix(AR_LIKE_f, out=AR_U), npt.NDArray[np.str_]) # type: ignore[deprecated] + +assert_type(np.isposinf(AR_LIKE_b), npt.NDArray[np.bool]) +assert_type(np.isposinf(AR_LIKE_u), npt.NDArray[np.bool]) +assert_type(np.isposinf(AR_LIKE_i), npt.NDArray[np.bool]) +assert_type(np.isposinf(AR_LIKE_f), npt.NDArray[np.bool]) +assert_type(np.isposinf(AR_LIKE_f, out=AR_U), npt.NDArray[np.str_]) + +assert_type(np.isneginf(AR_LIKE_b), npt.NDArray[np.bool]) +assert_type(np.isneginf(AR_LIKE_u), npt.NDArray[np.bool]) +assert_type(np.isneginf(AR_LIKE_i), npt.NDArray[np.bool]) +assert_type(np.isneginf(AR_LIKE_f), npt.NDArray[np.bool]) +assert_type(np.isneginf(AR_LIKE_f, out=AR_U), npt.NDArray[np.str_]) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ufuncs.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ufuncs.pyi new file mode 100644 index 0000000000000000000000000000000000000000..eda92f2117c6d64e4f0718f3270f70e103496ea9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/ufuncs.pyi @@ -0,0 +1,142 @@ +from typing import Any, Literal, NoReturn, assert_type + +import numpy as np +import numpy.typing as npt + +i8: np.int64 +f8: np.float64 +AR_f8: npt.NDArray[np.float64] +AR_i8: npt.NDArray[np.int64] + +assert_type(np.absolute.__doc__, str) +assert_type(np.absolute.types, list[str]) + +assert_type(np.absolute.__name__, Literal["absolute"]) +assert_type(np.absolute.__qualname__, Literal["absolute"]) +assert_type(np.absolute.ntypes, Literal[20]) +assert_type(np.absolute.identity, None) +assert_type(np.absolute.nin, Literal[1]) +assert_type(np.absolute.nin, Literal[1]) +assert_type(np.absolute.nout, Literal[1]) +assert_type(np.absolute.nargs, Literal[2]) +assert_type(np.absolute.signature, None) +assert_type(np.absolute(f8), Any) +assert_type(np.absolute(AR_f8), npt.NDArray[Any]) +assert_type(np.absolute.at(AR_f8, AR_i8), None) + +assert_type(np.add.__name__, Literal["add"]) +assert_type(np.add.__qualname__, Literal["add"]) +assert_type(np.add.ntypes, Literal[22]) +assert_type(np.add.identity, Literal[0]) +assert_type(np.add.nin, Literal[2]) +assert_type(np.add.nout, Literal[1]) +assert_type(np.add.nargs, Literal[3]) +assert_type(np.add.signature, None) +assert_type(np.add(f8, f8), Any) +assert_type(np.add(AR_f8, f8), npt.NDArray[Any]) +assert_type(np.add.at(AR_f8, AR_i8, f8), None) +assert_type(np.add.reduce(AR_f8, axis=0), Any) +assert_type(np.add.accumulate(AR_f8), npt.NDArray[Any]) +assert_type(np.add.reduceat(AR_f8, AR_i8), npt.NDArray[Any]) +assert_type(np.add.outer(f8, f8), Any) +assert_type(np.add.outer(AR_f8, f8), npt.NDArray[Any]) + +assert_type(np.frexp.__name__, Literal["frexp"]) +assert_type(np.frexp.__qualname__, Literal["frexp"]) +assert_type(np.frexp.ntypes, Literal[4]) +assert_type(np.frexp.identity, None) +assert_type(np.frexp.nin, Literal[1]) +assert_type(np.frexp.nout, Literal[2]) +assert_type(np.frexp.nargs, Literal[3]) +assert_type(np.frexp.signature, None) +assert_type(np.frexp(f8), tuple[Any, Any]) +assert_type(np.frexp(AR_f8), tuple[npt.NDArray[Any], npt.NDArray[Any]]) + +assert_type(np.divmod.__name__, Literal["divmod"]) +assert_type(np.divmod.__qualname__, Literal["divmod"]) +assert_type(np.divmod.ntypes, Literal[15]) +assert_type(np.divmod.identity, None) +assert_type(np.divmod.nin, Literal[2]) +assert_type(np.divmod.nout, Literal[2]) +assert_type(np.divmod.nargs, Literal[4]) +assert_type(np.divmod.signature, None) +assert_type(np.divmod(f8, f8), tuple[Any, Any]) +assert_type(np.divmod(AR_f8, f8), tuple[npt.NDArray[Any], npt.NDArray[Any]]) + +assert_type(np.matmul.__name__, Literal["matmul"]) +assert_type(np.matmul.__qualname__, Literal["matmul"]) +assert_type(np.matmul.ntypes, Literal[19]) +assert_type(np.matmul.identity, None) +assert_type(np.matmul.nin, Literal[2]) +assert_type(np.matmul.nout, Literal[1]) +assert_type(np.matmul.nargs, Literal[3]) +assert_type(np.matmul.signature, Literal["(n?,k),(k,m?)->(n?,m?)"]) +assert_type(np.matmul.identity, None) +assert_type(np.matmul(AR_f8, AR_f8), Any) +assert_type(np.matmul(AR_f8, AR_f8, axes=[(0, 1), (0, 1), (0, 1)]), Any) + +assert_type(np.vecdot.__name__, Literal["vecdot"]) +assert_type(np.vecdot.__qualname__, Literal["vecdot"]) +assert_type(np.vecdot.ntypes, Literal[19]) +assert_type(np.vecdot.identity, None) +assert_type(np.vecdot.nin, Literal[2]) +assert_type(np.vecdot.nout, Literal[1]) +assert_type(np.vecdot.nargs, Literal[3]) +assert_type(np.vecdot.signature, Literal["(n),(n)->()"]) +assert_type(np.vecdot.identity, None) +assert_type(np.vecdot(AR_f8, AR_f8), Any) + +assert_type(np.bitwise_count.__name__, Literal["bitwise_count"]) +assert_type(np.bitwise_count.__qualname__, Literal["bitwise_count"]) +assert_type(np.bitwise_count.ntypes, Literal[11]) +assert_type(np.bitwise_count.identity, None) +assert_type(np.bitwise_count.nin, Literal[1]) +assert_type(np.bitwise_count.nout, Literal[1]) +assert_type(np.bitwise_count.nargs, Literal[2]) +assert_type(np.bitwise_count.signature, None) +assert_type(np.bitwise_count.identity, None) +assert_type(np.bitwise_count(i8), Any) +assert_type(np.bitwise_count(AR_i8), npt.NDArray[Any]) + +def test_absolute_outer_invalid() -> None: + assert_type(np.absolute.outer(AR_f8, AR_f8), NoReturn) # type: ignore[arg-type] +def test_frexp_outer_invalid() -> None: + assert_type(np.frexp.outer(AR_f8, AR_f8), NoReturn) # type: ignore[arg-type] +def test_divmod_outer_invalid() -> None: + assert_type(np.divmod.outer(AR_f8, AR_f8), NoReturn) # type: ignore[arg-type] +def test_matmul_outer_invalid() -> None: + assert_type(np.matmul.outer(AR_f8, AR_f8), NoReturn) # type: ignore[arg-type] + +def test_absolute_reduceat_invalid() -> None: + assert_type(np.absolute.reduceat(AR_f8, AR_i8), NoReturn) # type: ignore[arg-type] +def test_frexp_reduceat_invalid() -> None: + assert_type(np.frexp.reduceat(AR_f8, AR_i8), NoReturn) # type: ignore[arg-type] +def test_divmod_reduceat_invalid() -> None: + assert_type(np.divmod.reduceat(AR_f8, AR_i8), NoReturn) # type: ignore[arg-type] +def test_matmul_reduceat_invalid() -> None: + assert_type(np.matmul.reduceat(AR_f8, AR_i8), NoReturn) # type: ignore[arg-type] + +def test_absolute_reduce_invalid() -> None: + assert_type(np.absolute.reduce(AR_f8), NoReturn) # type: ignore[arg-type] +def test_frexp_reduce_invalid() -> None: + assert_type(np.frexp.reduce(AR_f8), NoReturn) # type: ignore[arg-type] +def test_divmod_reduce_invalid() -> None: + assert_type(np.divmod.reduce(AR_f8), NoReturn) # type: ignore[arg-type] +def test_matmul_reduce_invalid() -> None: + assert_type(np.matmul.reduce(AR_f8), NoReturn) # type: ignore[arg-type] + +def test_absolute_accumulate_invalid() -> None: + assert_type(np.absolute.accumulate(AR_f8), NoReturn) # type: ignore[arg-type] +def test_frexp_accumulate_invalid() -> None: + assert_type(np.frexp.accumulate(AR_f8), NoReturn) # type: ignore[arg-type] +def test_divmod_accumulate_invalid() -> None: + assert_type(np.divmod.accumulate(AR_f8), NoReturn) # type: ignore[arg-type] +def test_matmul_accumulate_invalid() -> None: + assert_type(np.matmul.accumulate(AR_f8), NoReturn) # type: ignore[arg-type] + +def test_frexp_at_invalid() -> None: + assert_type(np.frexp.at(AR_f8, i8), NoReturn) # type: ignore[arg-type] +def test_divmod_at_invalid() -> None: + assert_type(np.divmod.at(AR_f8, i8, AR_f8), NoReturn) # type: ignore[arg-type] +def test_matmul_at_invalid() -> None: + assert_type(np.matmul.at(AR_f8, i8, AR_f8), NoReturn) # type: ignore[arg-type] diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/warnings_and_errors.pyi b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/warnings_and_errors.pyi new file mode 100644 index 0000000000000000000000000000000000000000..f756a8e45d46629d499612c5452932811dc95084 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/data/reveal/warnings_and_errors.pyi @@ -0,0 +1,11 @@ +from typing import assert_type + +import numpy.exceptions as ex + +assert_type(ex.ModuleDeprecationWarning(), ex.ModuleDeprecationWarning) +assert_type(ex.VisibleDeprecationWarning(), ex.VisibleDeprecationWarning) +assert_type(ex.ComplexWarning(), ex.ComplexWarning) +assert_type(ex.RankWarning(), ex.RankWarning) +assert_type(ex.TooHardError(), ex.TooHardError) +assert_type(ex.AxisError("test"), ex.AxisError) +assert_type(ex.AxisError(5, 1), ex.AxisError) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/test_isfile.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/test_isfile.py new file mode 100644 index 0000000000000000000000000000000000000000..0e3157a1e54df6962c25b0b7a72a387b333156bb --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/test_isfile.py @@ -0,0 +1,38 @@ +import os +import sys +from pathlib import Path + +import pytest + +import numpy as np +from numpy.testing import assert_ + +ROOT = Path(np.__file__).parents[0] +FILES = [ + ROOT / "py.typed", + ROOT / "__init__.pyi", + ROOT / "ctypeslib" / "__init__.pyi", + ROOT / "_core" / "__init__.pyi", + ROOT / "f2py" / "__init__.pyi", + ROOT / "fft" / "__init__.pyi", + ROOT / "lib" / "__init__.pyi", + ROOT / "linalg" / "__init__.pyi", + ROOT / "ma" / "__init__.pyi", + ROOT / "matrixlib" / "__init__.pyi", + ROOT / "polynomial" / "__init__.pyi", + ROOT / "random" / "__init__.pyi", + ROOT / "testing" / "__init__.pyi", +] +if sys.version_info < (3, 12): + FILES += [ROOT / "distutils" / "__init__.pyi"] + + +@pytest.mark.thread_unsafe( + reason="os.path has a thread-safety bug (python/cpython#140054). " + "Expected to only be a problem in 3.14.0" +) +class TestIsFile: + def test_isfile(self): + """Test if all ``.pyi`` files are properly installed.""" + for file in FILES: + assert_(os.path.isfile(file)) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/test_runtime.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/test_runtime.py new file mode 100644 index 0000000000000000000000000000000000000000..462fe4eabdc024655807eb42394f0e244213500e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/test_runtime.py @@ -0,0 +1,110 @@ +"""Test the runtime usage of `numpy.typing`.""" + +from typing import ( + Any, + NamedTuple, + Union, # pyright: ignore[reportDeprecated] + get_args, + get_origin, + get_type_hints, +) + +import pytest + +import numpy as np +import numpy._typing as _npt +import numpy.typing as npt + + +class TypeTup(NamedTuple): + typ: type + args: tuple[type, ...] + origin: type | None + + +def _flatten_type_alias(t: Any) -> Any: + # "flattens" a TypeAliasType to its underlying type alias + return getattr(t, "__value__", t) + + +NDArrayTup = TypeTup(npt.NDArray, npt.NDArray.__args__, np.ndarray) + +TYPES = { + "ArrayLike": TypeTup( + _flatten_type_alias(npt.ArrayLike), + _flatten_type_alias(npt.ArrayLike).__args__, + Union, + ), + "DTypeLike": TypeTup( + _flatten_type_alias(npt.DTypeLike), + _flatten_type_alias(npt.DTypeLike).__args__, + Union, + ), + "NBitBase": TypeTup(npt.NBitBase, (), None), # type: ignore[deprecated] # pyright: ignore[reportDeprecated] + "NDArray": NDArrayTup, +} + + +@pytest.mark.parametrize("name,tup", TYPES.items(), ids=TYPES.keys()) +def test_get_args(name: type, tup: TypeTup) -> None: + """Test `typing.get_args`.""" + typ, ref = tup.typ, tup.args + out = get_args(typ) + assert out == ref + + +@pytest.mark.parametrize("name,tup", TYPES.items(), ids=TYPES.keys()) +def test_get_origin(name: type, tup: TypeTup) -> None: + """Test `typing.get_origin`.""" + typ, ref = tup.typ, tup.origin + out = get_origin(typ) + assert out == ref + + +@pytest.mark.parametrize("name,tup", TYPES.items(), ids=TYPES.keys()) +def test_get_type_hints(name: type, tup: TypeTup) -> None: + """Test `typing.get_type_hints`.""" + typ = tup.typ + + def func(a: typ) -> None: pass + + out = get_type_hints(func) + ref = {"a": typ, "return": type(None)} + assert out == ref + + +@pytest.mark.parametrize("name,tup", TYPES.items(), ids=TYPES.keys()) +def test_get_type_hints_str(name: type, tup: TypeTup) -> None: + """Test `typing.get_type_hints` with string-representation of types.""" + typ_str, typ = f"npt.{name}", tup.typ + + def func(a: typ_str) -> None: pass + + out = get_type_hints(func) + ref = {"a": getattr(npt, str(name)), "return": type(None)} + assert out == ref + + +def test_keys() -> None: + """Test that ``TYPES.keys()`` and ``numpy.typing.__all__`` are synced.""" + keys = TYPES.keys() + ref = set(npt.__all__) + assert keys == ref + + +PROTOCOLS: dict[str, tuple[type[Any], object]] = { + "_SupportsArray": (_npt._SupportsArray, np.arange(10)), + "_SupportsArrayFunc": (_npt._SupportsArrayFunc, np.arange(10)), + "_NestedSequence": (_npt._NestedSequence, [1]), +} + + +@pytest.mark.parametrize("cls,obj", PROTOCOLS.values(), ids=PROTOCOLS.keys()) +class TestRuntimeProtocol: + def test_isinstance(self, cls: type[Any], obj: object) -> None: + assert isinstance(obj, cls) + assert not isinstance(None, cls) + + def test_issubclass(self, cls: type[Any], obj: object) -> None: + assert issubclass(type(obj), cls) + assert not issubclass(type(None), cls) diff --git a/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/test_typing.py b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/test_typing.py new file mode 100644 index 0000000000000000000000000000000000000000..ca4cf37fec3b6e151b2396af6f1532cdf1dd49c7 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/numpy/typing/tests/test_typing.py @@ -0,0 +1,205 @@ +import importlib.util +import os +import re +import shutil +import textwrap +from collections import defaultdict +from typing import TYPE_CHECKING + +import pytest + +# Only trigger a full `mypy` run if this environment variable is set +# Note that these tests tend to take over a minute even on a macOS M1 CPU, +# and more than that in CI. +RUN_MYPY = "NPY_RUN_MYPY_IN_TESTSUITE" in os.environ +if RUN_MYPY and RUN_MYPY not in ('0', '', 'false'): + RUN_MYPY = True + +# Skips all functions in this file +pytestmark = pytest.mark.skipif( + not RUN_MYPY, + reason="`NPY_RUN_MYPY_IN_TESTSUITE` not set" +) + + +try: + from mypy import api +except ImportError: + NO_MYPY = True +else: + NO_MYPY = False + +if TYPE_CHECKING: + from collections.abc import Iterator + + # We need this as annotation, but it's located in a private namespace. + # As a compromise, do *not* import it during runtime + from _pytest.mark.structures import ParameterSet + +DATA_DIR = os.path.join(os.path.dirname(__file__), "data") +PASS_DIR = os.path.join(DATA_DIR, "pass") +FAIL_DIR = os.path.join(DATA_DIR, "fail") +REVEAL_DIR = os.path.join(DATA_DIR, "reveal") +MISC_DIR = os.path.join(DATA_DIR, "misc") +MYPY_INI = os.path.join(DATA_DIR, "mypy.ini") +CACHE_DIR = os.path.join(DATA_DIR, ".mypy_cache") + +#: A dictionary with file names as keys and lists of the mypy stdout as values. +#: To-be populated by `run_mypy`. +OUTPUT_MYPY: defaultdict[str, list[str]] = defaultdict(list) + + +def _key_func(key: str) -> str: + """Split at the first occurrence of the ``:`` character. + + Windows drive-letters (*e.g.* ``C:``) are ignored herein. + """ + drive, tail = os.path.splitdrive(key) + return os.path.join(drive, tail.split(":", 1)[0]) + + +def _strip_filename(msg: str) -> tuple[int, str]: + """Strip the filename and line number from a mypy message.""" + _, tail = os.path.splitdrive(msg) + _, lineno, msg = tail.split(":", 2) + return int(lineno), msg.strip() + + +def strip_func(match: re.Match[str]) -> str: + """`re.sub` helper function for stripping module names.""" + return match.groups()[1] + + +@pytest.fixture(scope="module", autouse=True) +def run_mypy() -> None: + """Clears the cache and run mypy before running any of the typing tests. + + The mypy results are cached in `OUTPUT_MYPY` for further use. + + The cache refresh can be skipped using + + NUMPY_TYPING_TEST_CLEAR_CACHE=0 pytest numpy/typing/tests + """ + if ( + os.path.isdir(CACHE_DIR) + and bool(os.environ.get("NUMPY_TYPING_TEST_CLEAR_CACHE", True)) # noqa: PLW1508 + ): + shutil.rmtree(CACHE_DIR) + + split_pattern = re.compile(r"(\s+)?\^(\~+)?") + for directory in (PASS_DIR, REVEAL_DIR, FAIL_DIR, MISC_DIR): + # Run mypy + stdout, stderr, exit_code = api.run([ + "--config-file", + MYPY_INI, + "--cache-dir", + CACHE_DIR, + directory, + ]) + if stderr: + pytest.fail(f"Unexpected mypy standard error\n\n{stderr}", False) + elif exit_code not in {0, 1}: + pytest.fail(f"Unexpected mypy exit code: {exit_code}\n\n{stdout}", False) + + str_concat = "" + filename: str | None = None + for i in stdout.split("\n"): + if "note:" in i: + continue + if filename is None: + filename = _key_func(i) + + str_concat += f"{i}\n" + if split_pattern.match(i) is not None: + OUTPUT_MYPY[filename].append(str_concat) + str_concat = "" + filename = None + + +def get_test_cases(*directories: str) -> "Iterator[ParameterSet]": + for directory in directories: + for root, _, files in os.walk(directory): + for fname in files: + short_fname, ext = os.path.splitext(fname) + if ext not in (".pyi", ".py"): + continue + + fullpath = os.path.join(root, fname) + yield pytest.param(fullpath, id=short_fname) + + +_FAIL_INDENT = " " * 4 +_FAIL_SEP = "\n" + "_" * 79 + "\n\n" + +_FAIL_MSG_REVEAL = """{}:{} - reveal mismatch: + +{}""" + + +@pytest.mark.slow +@pytest.mark.skipif(NO_MYPY, reason="Mypy is not installed") +@pytest.mark.parametrize("path", get_test_cases(PASS_DIR, FAIL_DIR)) +def test_pass(path) -> None: + # Alias `OUTPUT_MYPY` so that it appears in the local namespace + output_mypy = OUTPUT_MYPY + + if path not in output_mypy: + return + + relpath = os.path.relpath(path) + + # collect any reported errors, and clean up the output + messages = [] + for message in output_mypy[path]: + lineno, content = _strip_filename(message) + content = content.removeprefix("error:").lstrip() + messages.append(f"{relpath}:{lineno} - {content}") + + if messages: + pytest.fail("\n".join(messages), pytrace=False) + + +@pytest.mark.slow +@pytest.mark.skipif(NO_MYPY, reason="Mypy is not installed") +@pytest.mark.parametrize("path", get_test_cases(REVEAL_DIR)) +def test_reveal(path: str) -> None: + """Validate that mypy correctly infers the return-types of + the expressions in `path`. + """ + __tracebackhide__ = True + + output_mypy = OUTPUT_MYPY + if path not in output_mypy: + return + + relpath = os.path.relpath(path) + + # collect any reported errors, and clean up the output + failures = [] + for error_line in output_mypy[path]: + lineno, error_msg = 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b/.venv_haddock/lib/python3.12/site-packages/plotly/colors/__init__.py @@ -0,0 +1,51 @@ +# ruff: noqa: F405 + +"""For a list of colors available in `plotly.colors`, please see + +* the `tutorial on discrete color sequences `_ +* the `list of built-in continuous color scales `_ +* the `tutorial on continuous colors `_ + +Color scales and sequences are available within the following namespaces + +* cyclical +* diverging +* qualitative +* sequential +""" + +from _plotly_utils.colors import * # noqa: F403 + +__all__ = [ + "named_colorscales", + "cyclical", + "diverging", + "sequential", + "qualitative", + "colorbrewer", + "carto", + "cmocean", + "color_parser", + "colorscale_to_colors", + "colorscale_to_scale", + "convert_colors_to_same_type", + "convert_colorscale_to_rgb", + "convert_dict_colors_to_same_type", + "convert_to_RGB_255", + "find_intermediate_color", + "hex_to_rgb", + "label_rgb", + "make_colorscale", + "n_colors", + "sample_colorscale", + "unconvert_from_RGB_255", + "unlabel_rgb", + "validate_colors", + "validate_colors_dict", + "validate_colorscale", + "validate_scale_values", + "plotlyjs", + "DEFAULT_PLOTLY_COLORS", + "PLOTLY_SCALES", + "get_colorscale", +] diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/colors/__pycache__/__init__.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/plotly/colors/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..3efc0a4aa8de30e137350077916322add7eba3c4 Binary files /dev/null and b/.venv_haddock/lib/python3.12/site-packages/plotly/colors/__pycache__/__init__.cpython-312.pyc differ diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/data/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/data/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..3bba38974b93cda0e29f16a78e1a7af4888d59bc --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/data/__init__.py @@ -0,0 +1,430 @@ +""" +Built-in datasets for demonstration, educational and test purposes. +""" + +import os +from importlib import import_module + +import narwhals.stable.v1 as nw + +AVAILABLE_BACKENDS = {"pandas", "polars", "pyarrow", "modin", "cudf"} +BACKENDS_WITH_INDEX_SUPPORT = {"pandas", "modin", "cudf"} + + +def gapminder( + datetimes=False, + centroids=False, + year=None, + pretty_names=False, + return_type="pandas", +): + """ + Each row represents a country on a given year. + + https://www.gapminder.org/data/ + + Parameters + ---------- + datetimes: bool + Whether or not 'year' column will converted to datetime type + + centroids: bool + If True, ['centroid_lat', 'centroid_lon'] columns are added + + year: int | None + If provided, the dataset will be filtered for that year + + pretty_names: bool + If True, prettifies the column names + + return_type: {'pandas', 'polars', 'pyarrow', 'modin', 'cudf'} + Type of the resulting dataframe + + Returns + ------- + Dataframe of `return_type` type + Dataframe with 1704 rows and the following columns: + `['country', 'continent', 'year', 'lifeExp', 'pop', 'gdpPercap', + 'iso_alpha', 'iso_num']`. + + If `datetimes` is True, the 'year' column will be a datetime column + If `centroids` is True, two new columns are added: ['centroid_lat', 'centroid_lon'] + If `year` is an integer, the dataset will be filtered for that year + """ + df = nw.from_native( + _get_dataset("gapminder", return_type=return_type), eager_only=True + ) + if year: + df = df.filter(nw.col("year") == year) + if datetimes: + df = df.with_columns( + # Concatenate the year value with the literal "-01-01" so that it can be + # casted to datetime from "%Y-%m-%d" format + nw.concat_str( + [nw.col("year").cast(nw.String()), nw.lit("-01-01")] + ).str.to_datetime(format="%Y-%m-%d") + ) + if not centroids: + df = df.drop("centroid_lat", "centroid_lon") + if pretty_names: + df = df.rename( + dict( + country="Country", + continent="Continent", + year="Year", + lifeExp="Life Expectancy", + gdpPercap="GDP per Capita", + pop="Population", + iso_alpha="ISO Alpha Country Code", + iso_num="ISO Numeric Country Code", + centroid_lat="Centroid Latitude", + centroid_lon="Centroid Longitude", + ) + ) + return df.to_native() + + +def tips(pretty_names=False, return_type="pandas"): + """ + Each row represents a restaurant bill. + + https://vincentarelbundock.github.io/Rdatasets/doc/reshape2/tips.html + + Parameters + ---------- + pretty_names: bool + If True, prettifies the column names + + return_type: {'pandas', 'polars', 'pyarrow', 'modin', 'cudf'} + Type of the resulting dataframe + + Returns + ------- + Dataframe of `return_type` type + Dataframe with 244 rows and the following columns: + `['total_bill', 'tip', 'sex', 'smoker', 'day', 'time', 'size']`. + """ + + df = nw.from_native(_get_dataset("tips", return_type=return_type), eager_only=True) + if pretty_names: + df = df.rename( + dict( + total_bill="Total Bill", + tip="Tip", + sex="Payer Gender", + smoker="Smokers at Table", + day="Day of Week", + time="Meal", + size="Party Size", + ) + ) + return df.to_native() + + +def iris(return_type="pandas"): + """ + Each row represents a flower. + + https://en.wikipedia.org/wiki/Iris_flower_data_set + + Parameters + ---------- + return_type: {'pandas', 'polars', 'pyarrow', 'modin', 'cudf'} + Type of the resulting dataframe + + Returns + ------- + Dataframe of `return_type` type + Dataframe with 150 rows and the following columns: + `['sepal_length', 'sepal_width', 'petal_length', 'petal_width', 'species', 'species_id']`. + """ + return _get_dataset("iris", return_type=return_type) + + +def wind(return_type="pandas"): + """ + Each row represents a level of wind intensity in a cardinal direction, and its frequency. + + Parameters + ---------- + return_type: {'pandas', 'polars', 'pyarrow', 'modin', 'cudf'} + Type of the resulting dataframe + + Returns + ------- + Dataframe of `return_type` type + Dataframe with 128 rows and the following columns: + `['direction', 'strength', 'frequency']`. + """ + return _get_dataset("wind", return_type=return_type) + + +def election(return_type="pandas"): + """ + Each row represents voting results for an electoral district in the 2013 Montreal + mayoral election. + + Parameters + ---------- + return_type: {'pandas', 'polars', 'pyarrow', 'modin', 'cudf'} + Type of the resulting dataframe + + Returns + ------- + Dataframe of `return_type` type + Dataframe with 58 rows and the following columns: + `['district', 'Coderre', 'Bergeron', 'Joly', 'total', 'winner', 'result', 'district_id']`. + """ + return _get_dataset("election", return_type=return_type) + + +def election_geojson(): + """ + Each feature represents an electoral district in the 2013 Montreal mayoral election. + + Returns + ------- + A GeoJSON-formatted `dict` with 58 polygon or multi-polygon features whose `id` + is an electoral district numerical ID and whose `district` property is the ID and + district name. + """ + import gzip + import json + import os + + path = os.path.join( + os.path.dirname(os.path.dirname(__file__)), + "package_data", + "datasets", + "election.geojson.gz", + ) + with gzip.GzipFile(path, "r") as f: + result = json.loads(f.read().decode("utf-8")) + return result + + +def carshare(return_type="pandas"): + """ + Each row represents the availability of car-sharing services near the centroid of a zone + in Montreal over a month-long period. + + Parameters + ---------- + return_type: {'pandas', 'polars', 'pyarrow', 'modin', 'cudf'} + Type of the resulting dataframe + + Returns + ------- + Dataframe of `return_type` type + Dataframe` with 249 rows and the following columns: + `['centroid_lat', 'centroid_lon', 'car_hours', 'peak_hour']`. + """ + return _get_dataset("carshare", return_type=return_type) + + +def stocks(indexed=False, datetimes=False, return_type="pandas"): + """ + Each row in this wide dataset represents closing prices from 6 tech stocks in 2018/2019. + + Parameters + ---------- + indexed: bool + Whether or not the 'date' column is used as the index and the column index + is named 'company'. Applicable only if `return_type='pandas'` + + datetimes: bool + Whether or not the 'date' column will be of datetime type + + return_type: {'pandas', 'polars', 'pyarrow', 'modin', 'cudf'} + Type of the resulting dataframe + + Returns + ------- + Dataframe of `return_type` type + Dataframe with 100 rows and the following columns: + `['date', 'GOOG', 'AAPL', 'AMZN', 'FB', 'NFLX', 'MSFT']`. + If `indexed` is True, the 'date' column is used as the index and the column index + is named 'company' + If `datetimes` is True, the 'date' column will be a datetime column + """ + if indexed and return_type not in BACKENDS_WITH_INDEX_SUPPORT: + msg = f"Backend '{return_type}' does not support setting index" + raise NotImplementedError(msg) + + df = nw.from_native( + _get_dataset("stocks", return_type=return_type), eager_only=True + ).with_columns(nw.col("date").cast(nw.String())) + + if datetimes: + df = df.with_columns(nw.col("date").str.to_datetime()) + + if indexed: # then it must be pandas + df = df.to_native().set_index("date") + df.columns.name = "company" + return df + + return df.to_native() + + +def experiment(indexed=False, return_type="pandas"): + """ + Each row in this wide dataset represents the results of 100 simulated participants + on three hypothetical experiments, along with their gender and control/treatment group. + + Parameters + ---------- + indexed: bool + If True, then the index is named "participant". + Applicable only if `return_type='pandas'` + + return_type: {'pandas', 'polars', 'pyarrow', 'modin', 'cudf'} + Type of the resulting dataframe + + Returns + ------- + Dataframe of `return_type` type + Dataframe with 100 rows and the following columns: + `['experiment_1', 'experiment_2', 'experiment_3', 'gender', 'group']`. + If `indexed` is True, the data frame index is named "participant" + """ + + if indexed and return_type not in BACKENDS_WITH_INDEX_SUPPORT: + msg = f"Backend '{return_type}' does not support setting index" + raise NotImplementedError(msg) + + df = nw.from_native( + _get_dataset("experiment", return_type=return_type), eager_only=True + ) + if indexed: # then it must be pandas + df = df.to_native() + df.index.name = "participant" + return df + return df.to_native() + + +def medals_wide(indexed=False, return_type="pandas"): + """ + This dataset represents the medal table for Olympic Short Track Speed Skating for the + top three nations as of 2020. + + Parameters + ---------- + indexed: bool + Whether or not the 'nation' column is used as the index and the column index + is named 'medal'. Applicable only if `return_type='pandas'` + + return_type: {'pandas', 'polars', 'pyarrow', 'modin', 'cudf'} + Type of the resulting dataframe + + Returns + ------- + Dataframe of `return_type` type + Dataframe with 3 rows and the following columns: + `['nation', 'gold', 'silver', 'bronze']`. + If `indexed` is True, the 'nation' column is used as the index and the column index + is named 'medal' + """ + + if indexed and return_type not in BACKENDS_WITH_INDEX_SUPPORT: + msg = f"Backend '{return_type}' does not support setting index" + raise NotImplementedError(msg) + + df = nw.from_native( + _get_dataset("medals", return_type=return_type), eager_only=True + ) + if indexed: # then it must be pandas + df = df.to_native().set_index("nation") + df.columns.name = "medal" + return df + return df.to_native() + + +def medals_long(indexed=False, return_type="pandas"): + """ + This dataset represents the medal table for Olympic Short Track Speed Skating for the + top three nations as of 2020. + + Parameters + ---------- + indexed: bool + Whether or not the 'nation' column is used as the index. + Applicable only if `return_type='pandas'` + + return_type: {'pandas', 'polars', 'pyarrow', 'modin', 'cudf'} + Type of the resulting dataframe + + Returns + ------- + Dataframe of `return_type` type + Dataframe with 9 rows and the following columns: `['nation', 'medal', 'count']`. + If `indexed` is True, the 'nation' column is used as the index. + """ + + if indexed and return_type not in BACKENDS_WITH_INDEX_SUPPORT: + msg = f"Backend '{return_type}' does not support setting index" + raise NotImplementedError(msg) + + df = nw.from_native( + _get_dataset("medals", return_type=return_type), eager_only=True + ).unpivot( + index=["nation"], + value_name="count", + variable_name="medal", + ) + if indexed: + df = nw.maybe_set_index(df, "nation") + return df.to_native() + + +def _get_dataset(d, return_type): + """ + Loads the dataset using the specified backend. + + Notice that the available backends are 'pandas', 'polars', 'pyarrow' and they all have + a `read_csv` function (pyarrow has it via pyarrow.csv). Therefore we can dynamically + load the library using `importlib.import_module` and then call + `backend.read_csv(filepath)`. + + Parameters + ---------- + d: str + Name of the dataset to load. + + return_type: {'pandas', 'polars', 'pyarrow', 'modin', 'cudf'} + Type of the resulting dataframe + + Returns + ------- + Dataframe of `return_type` type + """ + filepath = os.path.join( + os.path.dirname(os.path.dirname(__file__)), + "package_data", + "datasets", + d + ".csv.gz", + ) + + if return_type not in AVAILABLE_BACKENDS: + msg = ( + f"Unsupported return_type. Found {return_type}, expected one " + f"of {AVAILABLE_BACKENDS}" + ) + raise NotImplementedError(msg) + + try: + if return_type == "pyarrow": + module_to_load = "pyarrow.csv" + elif return_type == "modin": + module_to_load = "modin.pandas" + else: + module_to_load = return_type + backend = import_module(module_to_load) + except ModuleNotFoundError: + msg = f"return_type={return_type}, but {return_type} is not installed" + raise ModuleNotFoundError(msg) + + try: + return backend.read_csv(filepath) + except Exception as e: + msg = f"Unable to read '{d}' dataset due to: {e}" + raise Exception(msg).with_traceback(e.__traceback__) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/data/__pycache__/__init__.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/plotly/data/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..cabca91171d67162d284dbd0a6817c2464fa19e9 Binary files /dev/null and b/.venv_haddock/lib/python3.12/site-packages/plotly/data/__pycache__/__init__.cpython-312.pyc differ diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/express/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/express/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..62a9bca08a27c8d465b176c77bfb264500e49e3b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/express/__init__.py @@ -0,0 +1,132 @@ +# ruff: noqa: E402 + +""" +`plotly.express` is a terse, consistent, high-level wrapper around `plotly.graph_objects` +for rapid data exploration and figure generation. Learn more at https://plotly.com/python/plotly-express/ +""" + +from plotly import optional_imports + +np = optional_imports.get_module("numpy") +if np is None: + raise ImportError( + """\ +Plotly Express requires numpy to be installed. You can install numpy using pip with: + +$ pip install numpy + +Or install Plotly Express and its dependencies directly with: + +$ pip install "plotly[express]" + +You can also use Plotly Graph Objects to create a large number of charts without installing +numpy. See examples here: https://plotly.com/python/graph-objects/ +""" + ) + +from ._imshow import imshow +from ._chart_types import ( # noqa: F401 + scatter, + scatter_3d, + scatter_polar, + scatter_ternary, + scatter_map, + scatter_mapbox, + scatter_geo, + line, + line_3d, + line_polar, + line_ternary, + line_map, + line_mapbox, + line_geo, + area, + bar, + timeline, + bar_polar, + violin, + box, + strip, + histogram, + ecdf, + scatter_matrix, + parallel_coordinates, + parallel_categories, + choropleth, + density_contour, + density_heatmap, + pie, + sunburst, + treemap, + icicle, + funnel, + funnel_area, + choropleth_map, + choropleth_mapbox, + density_map, + density_mapbox, +) + + +from ._core import ( # noqa: F401 + set_mapbox_access_token, + defaults, + get_trendline_results, + NO_COLOR, +) + +from ._special_inputs import IdentityMap, Constant, Range # noqa: F401 + +from . import data, colors, trendline_functions # noqa: F401 + +__all__ = [ + "scatter", + "scatter_3d", + "scatter_polar", + "scatter_ternary", + "scatter_map", + "scatter_mapbox", + "scatter_geo", + "scatter_matrix", + "density_contour", + "density_heatmap", + "density_map", + "density_mapbox", + "line", + "line_3d", + "line_polar", + "line_ternary", + "line_map", + "line_mapbox", + "line_geo", + "parallel_coordinates", + "parallel_categories", + "area", + "bar", + "timeline", + "bar_polar", + "violin", + "box", + "strip", + "histogram", + "ecdf", + "choropleth", + "choropleth_map", + "choropleth_mapbox", + "pie", + "sunburst", + "treemap", + "icicle", + "funnel", + "funnel_area", + "imshow", + "data", + "colors", + "trendline_functions", + "set_mapbox_access_token", + "get_trendline_results", + "IdentityMap", + "Constant", + "Range", + "NO_COLOR", +] diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/express/__pycache__/__init__.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/plotly/express/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 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import make_figure +from ._doc import make_docstring +import plotly.graph_objs as go + +_wide_mode_xy_append = [ + "Either `x` or `y` can optionally be a list of column references or array_likes, ", + "in which case the data will be treated as if it were 'wide' rather than 'long'.", +] +_cartesian_append_dict = dict(x=_wide_mode_xy_append, y=_wide_mode_xy_append) + + +def scatter( + data_frame=None, + x=None, + y=None, + color=None, + symbol=None, + size=None, + hover_name=None, + hover_data=None, + custom_data=None, + text=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + error_x=None, + error_x_minus=None, + error_y=None, + error_y_minus=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + orientation=None, + color_discrete_sequence=None, + color_discrete_map=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + symbol_sequence=None, + symbol_map=None, + opacity=None, + size_max=None, + marginal_x=None, + marginal_y=None, + trendline=None, + trendline_options=None, + trendline_color_override=None, + trendline_scope="trace", + log_x=False, + log_y=False, + range_x=None, + range_y=None, + render_mode="auto", + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a scatter plot, each row of `data_frame` is represented by a symbol + mark in 2D space. + """ + return make_figure(args=locals(), constructor=go.Scatter) + + +scatter.__doc__ = make_docstring(scatter, append_dict=_cartesian_append_dict) + + +def density_contour( + data_frame=None, + x=None, + y=None, + z=None, + color=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + hover_name=None, + hover_data=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + orientation=None, + color_discrete_sequence=None, + color_discrete_map=None, + marginal_x=None, + marginal_y=None, + trendline=None, + trendline_options=None, + trendline_color_override=None, + trendline_scope="trace", + log_x=False, + log_y=False, + range_x=None, + range_y=None, + histfunc=None, + histnorm=None, + nbinsx=None, + nbinsy=None, + text_auto=False, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a density contour plot, rows of `data_frame` are grouped together + into contour marks to visualize the 2D distribution of an aggregate + function `histfunc` (e.g. the count or sum) of the value `z`. + """ + return make_figure( + args=locals(), + constructor=go.Histogram2dContour, + trace_patch=dict( + contours=dict(coloring="none"), + histfunc=histfunc, + histnorm=histnorm, + nbinsx=nbinsx, + nbinsy=nbinsy, + xbingroup="x", + ybingroup="y", + ), + ) + + +density_contour.__doc__ = make_docstring( + density_contour, + append_dict=dict( + x=_wide_mode_xy_append, + y=_wide_mode_xy_append, + z=[ + "For `density_heatmap` and `density_contour` these values are used as the inputs to `histfunc`.", + ], + histfunc=["The arguments to this function are the values of `z`."], + ), +) + + +def density_heatmap( + data_frame=None, + x=None, + y=None, + z=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + hover_name=None, + hover_data=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + orientation=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + marginal_x=None, + marginal_y=None, + opacity=None, + log_x=False, + log_y=False, + range_x=None, + range_y=None, + histfunc=None, + histnorm=None, + nbinsx=None, + nbinsy=None, + text_auto=False, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a density heatmap, rows of `data_frame` are grouped together into + colored rectangular tiles to visualize the 2D distribution of an + aggregate function `histfunc` (e.g. the count or sum) of the value `z`. + """ + return make_figure( + args=locals(), + constructor=go.Histogram2d, + trace_patch=dict( + histfunc=histfunc, + histnorm=histnorm, + nbinsx=nbinsx, + nbinsy=nbinsy, + xbingroup="x", + ybingroup="y", + ), + ) + + +density_heatmap.__doc__ = make_docstring( + density_heatmap, + append_dict=dict( + x=_wide_mode_xy_append, + y=_wide_mode_xy_append, + z=[ + "For `density_heatmap` and `density_contour` these values are used as the inputs to `histfunc`.", + ], + histfunc=[ + "The arguments to this function are the values of `z`.", + ], + ), +) + + +def line( + data_frame=None, + x=None, + y=None, + line_group=None, + color=None, + line_dash=None, + symbol=None, + hover_name=None, + hover_data=None, + custom_data=None, + text=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + error_x=None, + error_x_minus=None, + error_y=None, + error_y_minus=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + orientation=None, + color_discrete_sequence=None, + color_discrete_map=None, + line_dash_sequence=None, + line_dash_map=None, + symbol_sequence=None, + symbol_map=None, + markers=False, + log_x=False, + log_y=False, + range_x=None, + range_y=None, + line_shape=None, + render_mode="auto", + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a 2D line plot, each row of `data_frame` is represented as a vertex of + a polyline mark in 2D space. + """ + return make_figure(args=locals(), constructor=go.Scatter) + + +line.__doc__ = make_docstring(line, append_dict=_cartesian_append_dict) + + +def area( + data_frame=None, + x=None, + y=None, + line_group=None, + color=None, + pattern_shape=None, + symbol=None, + hover_name=None, + hover_data=None, + custom_data=None, + text=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + pattern_shape_sequence=None, + pattern_shape_map=None, + symbol_sequence=None, + symbol_map=None, + markers=False, + orientation=None, + groupnorm=None, + log_x=False, + log_y=False, + range_x=None, + range_y=None, + line_shape=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a stacked area plot, each row of `data_frame` is represented as + a vertex of a polyline mark in 2D space. The area between + successive polylines is filled. + """ + return make_figure( + args=locals(), + constructor=go.Scatter, + trace_patch=dict(stackgroup=1, mode="lines", groupnorm=groupnorm), + ) + + +area.__doc__ = make_docstring(area, append_dict=_cartesian_append_dict) + + +def bar( + data_frame=None, + x=None, + y=None, + color=None, + pattern_shape=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + hover_name=None, + hover_data=None, + custom_data=None, + text=None, + base=None, + error_x=None, + error_x_minus=None, + error_y=None, + error_y_minus=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + color_continuous_scale=None, + pattern_shape_sequence=None, + pattern_shape_map=None, + range_color=None, + color_continuous_midpoint=None, + opacity=None, + orientation=None, + barmode="relative", + log_x=False, + log_y=False, + range_x=None, + range_y=None, + text_auto=False, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a bar plot, each row of `data_frame` is represented as a rectangular + mark. + """ + return make_figure( + args=locals(), + constructor=go.Bar, + trace_patch=dict(textposition="auto"), + layout_patch=dict(barmode=barmode), + ) + + +bar.__doc__ = make_docstring(bar, append_dict=_cartesian_append_dict) + + +def timeline( + data_frame=None, + x_start=None, + x_end=None, + y=None, + color=None, + pattern_shape=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + hover_name=None, + hover_data=None, + custom_data=None, + text=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + pattern_shape_sequence=None, + pattern_shape_map=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + opacity=None, + range_x=None, + range_y=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a timeline plot, each row of `data_frame` is represented as a rectangular + mark on an x axis of type `date`, spanning from `x_start` to `x_end`. + """ + return make_figure( + args=locals(), + constructor="timeline", + trace_patch=dict(textposition="auto", orientation="h"), + layout_patch=dict(barmode="overlay"), + ) + + +timeline.__doc__ = make_docstring(timeline) + + +def histogram( + data_frame=None, + x=None, + y=None, + color=None, + pattern_shape=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + hover_name=None, + hover_data=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + pattern_shape_sequence=None, + pattern_shape_map=None, + marginal=None, + opacity=None, + orientation=None, + barmode="relative", + barnorm=None, + histnorm=None, + log_x=False, + log_y=False, + range_x=None, + range_y=None, + histfunc=None, + cumulative=None, + nbins=None, + text_auto=False, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a histogram, rows of `data_frame` are grouped together into a + rectangular mark to visualize the 1D distribution of an aggregate + function `histfunc` (e.g. the count or sum) of the value `y` (or `x` if + `orientation` is `'h'`). + """ + return make_figure( + args=locals(), + constructor=go.Histogram, + trace_patch=dict( + histnorm=histnorm, + histfunc=histfunc, + cumulative=dict(enabled=cumulative), + ), + layout_patch=dict(barmode=barmode, barnorm=barnorm), + ) + + +histogram.__doc__ = make_docstring( + histogram, + append_dict=dict( + x=["If `orientation` is `'h'`, these values are used as inputs to `histfunc`."] + + _wide_mode_xy_append, + y=["If `orientation` is `'v'`, these values are used as inputs to `histfunc`."] + + _wide_mode_xy_append, + histfunc=[ + "The arguments to this function are the values of `y` (`x`) if `orientation` is `'v'` (`'h'`).", + ], + ), +) + + +def ecdf( + data_frame=None, + x=None, + y=None, + color=None, + text=None, + line_dash=None, + symbol=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + hover_name=None, + hover_data=None, + animation_frame=None, + animation_group=None, + markers=False, + lines=True, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + line_dash_sequence=None, + line_dash_map=None, + symbol_sequence=None, + symbol_map=None, + marginal=None, + opacity=None, + orientation=None, + ecdfnorm="probability", + ecdfmode="standard", + render_mode="auto", + log_x=False, + log_y=False, + range_x=None, + range_y=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a Empirical Cumulative Distribution Function (ECDF) plot, rows of `data_frame` + are sorted by the value `x` (or `y` if `orientation` is `'h'`) and their cumulative + count (or the cumulative sum of `y` if supplied and `orientation` is `h`) is drawn + as a line. + """ + return make_figure(args=locals(), constructor=go.Scatter) + + +ecdf.__doc__ = make_docstring( + ecdf, + append_dict=dict( + x=[ + "If `orientation` is `'h'`, the cumulative sum of this argument is plotted rather than the cumulative count." + ] + + _wide_mode_xy_append, + y=[ + "If `orientation` is `'v'`, the cumulative sum of this argument is plotted rather than the cumulative count." + ] + + _wide_mode_xy_append, + ), +) + + +def violin( + data_frame=None, + x=None, + y=None, + color=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + hover_name=None, + hover_data=None, + custom_data=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + orientation=None, + violinmode=None, + log_x=False, + log_y=False, + range_x=None, + range_y=None, + points=None, + box=False, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a violin plot, rows of `data_frame` are grouped together into a + curved mark to visualize their distribution. + """ + return make_figure( + args=locals(), + constructor=go.Violin, + trace_patch=dict( + points=points, + box=dict(visible=box), + scalegroup=True, + x0=" ", + y0=" ", + ), + layout_patch=dict(violinmode=violinmode), + ) + + +violin.__doc__ = make_docstring(violin, append_dict=_cartesian_append_dict) + + +def box( + data_frame=None, + x=None, + y=None, + color=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + hover_name=None, + hover_data=None, + custom_data=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + orientation=None, + boxmode=None, + log_x=False, + log_y=False, + range_x=None, + range_y=None, + points=None, + notched=False, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a box plot, rows of `data_frame` are grouped together into a + box-and-whisker mark to visualize their distribution. + + Each box spans from quartile 1 (Q1) to quartile 3 (Q3). The second + quartile (Q2) is marked by a line inside the box. By default, the + whiskers correspond to the box' edges +/- 1.5 times the interquartile + range (IQR: Q3-Q1), see "points" for other options. + """ + return make_figure( + args=locals(), + constructor=go.Box, + trace_patch=dict(boxpoints=points, notched=notched, x0=" ", y0=" "), + layout_patch=dict(boxmode=boxmode), + ) + + +box.__doc__ = make_docstring(box, append_dict=_cartesian_append_dict) + + +def strip( + data_frame=None, + x=None, + y=None, + color=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + hover_name=None, + hover_data=None, + custom_data=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + orientation=None, + stripmode=None, + log_x=False, + log_y=False, + range_x=None, + range_y=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a strip plot each row of `data_frame` is represented as a jittered + mark within categories. + """ + return make_figure( + args=locals(), + constructor=go.Box, + trace_patch=dict( + boxpoints="all", + pointpos=0, + hoveron="points", + fillcolor="rgba(255,255,255,0)", + line={"color": "rgba(255,255,255,0)"}, + x0=" ", + y0=" ", + ), + layout_patch=dict(boxmode=stripmode), + ) + + +strip.__doc__ = make_docstring(strip, append_dict=_cartesian_append_dict) + + +def scatter_3d( + data_frame=None, + x=None, + y=None, + z=None, + color=None, + symbol=None, + size=None, + text=None, + hover_name=None, + hover_data=None, + custom_data=None, + error_x=None, + error_x_minus=None, + error_y=None, + error_y_minus=None, + error_z=None, + error_z_minus=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + size_max=None, + color_discrete_sequence=None, + color_discrete_map=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + symbol_sequence=None, + symbol_map=None, + opacity=None, + log_x=False, + log_y=False, + log_z=False, + range_x=None, + range_y=None, + range_z=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a 3D scatter plot, each row of `data_frame` is represented by a + symbol mark in 3D space. + """ + return make_figure(args=locals(), constructor=go.Scatter3d) + + +scatter_3d.__doc__ = make_docstring(scatter_3d) + + +def line_3d( + data_frame=None, + x=None, + y=None, + z=None, + color=None, + line_dash=None, + text=None, + line_group=None, + symbol=None, + hover_name=None, + hover_data=None, + custom_data=None, + error_x=None, + error_x_minus=None, + error_y=None, + error_y_minus=None, + error_z=None, + error_z_minus=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + line_dash_sequence=None, + line_dash_map=None, + symbol_sequence=None, + symbol_map=None, + markers=False, + log_x=False, + log_y=False, + log_z=False, + range_x=None, + range_y=None, + range_z=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a 3D line plot, each row of `data_frame` is represented as a vertex of + a polyline mark in 3D space. + """ + return make_figure(args=locals(), constructor=go.Scatter3d) + + +line_3d.__doc__ = make_docstring(line_3d) + + +def scatter_ternary( + data_frame=None, + a=None, + b=None, + c=None, + color=None, + symbol=None, + size=None, + text=None, + hover_name=None, + hover_data=None, + custom_data=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + symbol_sequence=None, + symbol_map=None, + opacity=None, + size_max=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a ternary scatter plot, each row of `data_frame` is represented by a + symbol mark in ternary coordinates. + """ + return make_figure(args=locals(), constructor=go.Scatterternary) + + +scatter_ternary.__doc__ = make_docstring(scatter_ternary) + + +def line_ternary( + data_frame=None, + a=None, + b=None, + c=None, + color=None, + line_dash=None, + line_group=None, + symbol=None, + hover_name=None, + hover_data=None, + custom_data=None, + text=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + line_dash_sequence=None, + line_dash_map=None, + symbol_sequence=None, + symbol_map=None, + markers=False, + line_shape=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a ternary line plot, each row of `data_frame` is represented as + a vertex of a polyline mark in ternary coordinates. + """ + return make_figure(args=locals(), constructor=go.Scatterternary) + + +line_ternary.__doc__ = make_docstring(line_ternary) + + +def scatter_polar( + data_frame=None, + r=None, + theta=None, + color=None, + symbol=None, + size=None, + hover_name=None, + hover_data=None, + custom_data=None, + text=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + symbol_sequence=None, + symbol_map=None, + opacity=None, + direction="clockwise", + start_angle=90, + size_max=None, + range_r=None, + range_theta=None, + log_r=False, + render_mode="auto", + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a polar scatter plot, each row of `data_frame` is represented by a + symbol mark in polar coordinates. + """ + return make_figure(args=locals(), constructor=go.Scatterpolar) + + +scatter_polar.__doc__ = make_docstring(scatter_polar) + + +def line_polar( + data_frame=None, + r=None, + theta=None, + color=None, + line_dash=None, + hover_name=None, + hover_data=None, + custom_data=None, + line_group=None, + text=None, + symbol=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + line_dash_sequence=None, + line_dash_map=None, + symbol_sequence=None, + symbol_map=None, + markers=False, + direction="clockwise", + start_angle=90, + line_close=False, + line_shape=None, + render_mode="auto", + range_r=None, + range_theta=None, + log_r=False, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a polar line plot, each row of `data_frame` is represented as a + vertex of a polyline mark in polar coordinates. + """ + return make_figure(args=locals(), constructor=go.Scatterpolar) + + +line_polar.__doc__ = make_docstring(line_polar) + + +def bar_polar( + data_frame=None, + r=None, + theta=None, + color=None, + pattern_shape=None, + hover_name=None, + hover_data=None, + custom_data=None, + base=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + color_continuous_scale=None, + pattern_shape_sequence=None, + pattern_shape_map=None, + range_color=None, + color_continuous_midpoint=None, + barnorm=None, + barmode="relative", + direction="clockwise", + start_angle=90, + range_r=None, + range_theta=None, + log_r=False, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a polar bar plot, each row of `data_frame` is represented as a wedge + mark in polar coordinates. + """ + return make_figure( + args=locals(), + constructor=go.Barpolar, + layout_patch=dict(barnorm=barnorm, barmode=barmode), + ) + + +bar_polar.__doc__ = make_docstring(bar_polar) + + +def choropleth( + data_frame=None, + lat=None, + lon=None, + locations=None, + locationmode=None, + geojson=None, + featureidkey=None, + color=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + hover_name=None, + hover_data=None, + custom_data=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + projection=None, + scope=None, + center=None, + fitbounds=None, + basemap_visible=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a choropleth map, each row of `data_frame` is represented by a + colored region mark on a map. + """ + + if locationmode == "country names": + warn( + "The library used by the *country names* `locationmode` option is changing in an upcoming version. " + "Country names in existing plots may not work in the new version. " + "To ensure consistent behavior, consider setting `locationmode` to *ISO-3*.", + DeprecationWarning, + stacklevel=2, + ) + + return make_figure( + args=locals(), + constructor=go.Choropleth, + trace_patch=dict(locationmode=locationmode), + ) + + +choropleth.__doc__ = make_docstring(choropleth) + + +def scatter_geo( + data_frame=None, + lat=None, + lon=None, + locations=None, + locationmode=None, + geojson=None, + featureidkey=None, + color=None, + text=None, + symbol=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + hover_name=None, + hover_data=None, + custom_data=None, + size=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + symbol_sequence=None, + symbol_map=None, + opacity=None, + size_max=None, + projection=None, + scope=None, + center=None, + fitbounds=None, + basemap_visible=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a geographic scatter plot, each row of `data_frame` is represented + by a symbol mark on a map. + """ + + if locationmode == "country names": + warn( + "The library used by the *country names* `locationmode` option is changing in an upcoming version. " + "Country names in existing plots may not work in the new version. " + "To ensure consistent behavior, consider setting `locationmode` to *ISO-3*.", + DeprecationWarning, + stacklevel=2, + ) + + return make_figure( + args=locals(), + constructor=go.Scattergeo, + trace_patch=dict(locationmode=locationmode), + ) + + +scatter_geo.__doc__ = make_docstring(scatter_geo) + + +def line_geo( + data_frame=None, + lat=None, + lon=None, + locations=None, + locationmode=None, + geojson=None, + featureidkey=None, + color=None, + line_dash=None, + text=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + hover_name=None, + hover_data=None, + custom_data=None, + line_group=None, + symbol=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + line_dash_sequence=None, + line_dash_map=None, + symbol_sequence=None, + symbol_map=None, + markers=False, + projection=None, + scope=None, + center=None, + fitbounds=None, + basemap_visible=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a geographic line plot, each row of `data_frame` is represented as + a vertex of a polyline mark on a map. + """ + return make_figure( + args=locals(), + constructor=go.Scattergeo, + trace_patch=dict(locationmode=locationmode), + ) + + +line_geo.__doc__ = make_docstring(line_geo) + + +def scatter_map( + data_frame=None, + lat=None, + lon=None, + color=None, + text=None, + hover_name=None, + hover_data=None, + custom_data=None, + size=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + opacity=None, + size_max=None, + zoom=8, + center=None, + map_style=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a scatter map, each row of `data_frame` is represented by a + symbol mark on the map. + """ + return make_figure(args=locals(), constructor=go.Scattermap) + + +scatter_map.__doc__ = make_docstring(scatter_map) + + +def choropleth_map( + data_frame=None, + geojson=None, + featureidkey=None, + locations=None, + color=None, + hover_name=None, + hover_data=None, + custom_data=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + opacity=None, + zoom=8, + center=None, + map_style=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a choropleth map, each row of `data_frame` is represented by a + colored region on the map. + """ + return make_figure(args=locals(), constructor=go.Choroplethmap) + + +choropleth_map.__doc__ = make_docstring(choropleth_map) + + +def density_map( + data_frame=None, + lat=None, + lon=None, + z=None, + hover_name=None, + hover_data=None, + custom_data=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + opacity=None, + zoom=8, + center=None, + map_style=None, + radius=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a density map, each row of `data_frame` contributes to the intensity of + the color of the region around the corresponding point on the map. + """ + return make_figure( + args=locals(), constructor=go.Densitymap, trace_patch=dict(radius=radius) + ) + + +density_map.__doc__ = make_docstring(density_map) + + +def line_map( + data_frame=None, + lat=None, + lon=None, + color=None, + text=None, + hover_name=None, + hover_data=None, + custom_data=None, + line_group=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + zoom=8, + center=None, + map_style=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a line map, each row of `data_frame` is represented as + a vertex of a polyline mark on the map. + """ + return make_figure(args=locals(), constructor=go.Scattermap) + + +line_map.__doc__ = make_docstring(line_map) + + +def scatter_mapbox( + data_frame=None, + lat=None, + lon=None, + color=None, + text=None, + hover_name=None, + hover_data=None, + custom_data=None, + size=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + opacity=None, + size_max=None, + zoom=8, + center=None, + mapbox_style=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + *scatter_mapbox* is deprecated! Use *scatter_map* instead. + Learn more at: https://plotly.com/python/mapbox-to-maplibre/ + In a Mapbox scatter plot, each row of `data_frame` is represented by a + symbol mark on a Mapbox map. + """ + warn( + "*scatter_mapbox* is deprecated!" + + " Use *scatter_map* instead." + + " Learn more at: https://plotly.com/python/mapbox-to-maplibre/", + stacklevel=2, + category=DeprecationWarning, + ) + return make_figure(args=locals(), constructor=go.Scattermapbox) + + +scatter_mapbox.__doc__ = make_docstring(scatter_mapbox) + + +def choropleth_mapbox( + data_frame=None, + geojson=None, + featureidkey=None, + locations=None, + color=None, + hover_name=None, + hover_data=None, + custom_data=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + opacity=None, + zoom=8, + center=None, + mapbox_style=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + *choropleth_mapbox* is deprecated! Use *choropleth_map* instead. + Learn more at: https://plotly.com/python/mapbox-to-maplibre/ + In a Mapbox choropleth map, each row of `data_frame` is represented by a + colored region on a Mapbox map. + """ + warn( + "*choropleth_mapbox* is deprecated!" + + " Use *choropleth_map* instead." + + " Learn more at: https://plotly.com/python/mapbox-to-maplibre/", + stacklevel=2, + category=DeprecationWarning, + ) + return make_figure(args=locals(), constructor=go.Choroplethmapbox) + + +choropleth_mapbox.__doc__ = make_docstring(choropleth_mapbox) + + +def density_mapbox( + data_frame=None, + lat=None, + lon=None, + z=None, + hover_name=None, + hover_data=None, + custom_data=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + opacity=None, + zoom=8, + center=None, + mapbox_style=None, + radius=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + *density_mapbox* is deprecated! Use *density_map* instead. + Learn more at: https://plotly.com/python/mapbox-to-maplibre/ + In a Mapbox density map, each row of `data_frame` contributes to the intensity of + the color of the region around the corresponding point on the map + """ + warn( + "*density_mapbox* is deprecated!" + + " Use *density_map* instead." + + " Learn more at: https://plotly.com/python/mapbox-to-maplibre/", + stacklevel=2, + category=DeprecationWarning, + ) + return make_figure( + args=locals(), constructor=go.Densitymapbox, trace_patch=dict(radius=radius) + ) + + +density_mapbox.__doc__ = make_docstring(density_mapbox) + + +def line_mapbox( + data_frame=None, + lat=None, + lon=None, + color=None, + text=None, + hover_name=None, + hover_data=None, + custom_data=None, + line_group=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + zoom=8, + center=None, + mapbox_style=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + *line_mapbox* is deprecated! Use *line_map* instead. + Learn more at: https://plotly.com/python/mapbox-to-maplibre/ + In a Mapbox line plot, each row of `data_frame` is represented as + a vertex of a polyline mark on a Mapbox map. + """ + warn( + "*line_mapbox* is deprecated!" + + " Use *line_map* instead." + + " Learn more at: https://plotly.com/python/mapbox-to-maplibre/", + stacklevel=2, + category=DeprecationWarning, + ) + return make_figure(args=locals(), constructor=go.Scattermapbox) + + +line_mapbox.__doc__ = make_docstring(line_mapbox) + + +def scatter_matrix( + data_frame=None, + dimensions=None, + color=None, + symbol=None, + size=None, + hover_name=None, + hover_data=None, + custom_data=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + symbol_sequence=None, + symbol_map=None, + opacity=None, + size_max=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a scatter plot matrix (or SPLOM), each row of `data_frame` is + represented by a multiple symbol marks, one in each cell of a grid of + 2D scatter plots, which plot each pair of `dimensions` against each + other. + """ + return make_figure( + args=locals(), constructor=go.Splom, layout_patch=dict(dragmode="select") + ) + + +scatter_matrix.__doc__ = make_docstring(scatter_matrix) + + +def parallel_coordinates( + data_frame=None, + dimensions=None, + color=None, + labels=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a parallel coordinates plot, each row of `data_frame` is represented + by a polyline mark which traverses a set of parallel axes, one for each + of the `dimensions`. + """ + return make_figure(args=locals(), constructor=go.Parcoords) + + +parallel_coordinates.__doc__ = make_docstring(parallel_coordinates) + + +def parallel_categories( + data_frame=None, + dimensions=None, + color=None, + labels=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, + dimensions_max_cardinality=50, +) -> go.Figure: + """ + In a parallel categories (or parallel sets) plot, each row of + `data_frame` is grouped with other rows that share the same values of + `dimensions` and then plotted as a polyline mark through a set of + parallel axes, one for each of the `dimensions`. + """ + return make_figure(args=locals(), constructor=go.Parcats) + + +parallel_categories.__doc__ = make_docstring(parallel_categories) + + +def pie( + data_frame=None, + names=None, + values=None, + color=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + color_discrete_sequence=None, + color_discrete_map=None, + hover_name=None, + hover_data=None, + custom_data=None, + category_orders=None, + labels=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, + opacity=None, + hole=None, +) -> go.Figure: + """ + In a pie plot, each row of `data_frame` is represented as a sector of a + pie. + """ + if color_discrete_sequence is not None: + layout_patch = {"piecolorway": color_discrete_sequence} + else: + layout_patch = {} + return make_figure( + args=locals(), + constructor=go.Pie, + trace_patch=dict(showlegend=(names is not None), hole=hole), + layout_patch=layout_patch, + ) + + +pie.__doc__ = make_docstring( + pie, + override_dict=dict( + hole=[ + "float", + "Sets the fraction of the radius to cut out of the pie." + "Use this to make a donut chart.", + ], + ), +) + + +def sunburst( + data_frame=None, + names=None, + values=None, + parents=None, + path=None, + ids=None, + color=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + color_discrete_sequence=None, + color_discrete_map=None, + hover_name=None, + hover_data=None, + custom_data=None, + labels=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, + branchvalues=None, + maxdepth=None, +) -> go.Figure: + """ + A sunburst plot represents hierarchial data as sectors laid out over + several levels of concentric rings. + """ + if color_discrete_sequence is not None: + layout_patch = {"sunburstcolorway": color_discrete_sequence} + else: + layout_patch = {} + if path is not None and (ids is not None or parents is not None): + raise ValueError( + "Either `path` should be provided, or `ids` and `parents`." + "These parameters are mutually exclusive and cannot be passed together." + ) + if path is not None and branchvalues is None: + branchvalues = "total" + return make_figure( + args=locals(), + constructor=go.Sunburst, + trace_patch=dict(branchvalues=branchvalues, maxdepth=maxdepth), + layout_patch=layout_patch, + ) + + +sunburst.__doc__ = make_docstring(sunburst) + + +def treemap( + data_frame=None, + names=None, + values=None, + parents=None, + ids=None, + path=None, + color=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + color_discrete_sequence=None, + color_discrete_map=None, + hover_name=None, + hover_data=None, + custom_data=None, + labels=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, + branchvalues=None, + maxdepth=None, +) -> go.Figure: + """ + A treemap plot represents hierarchial data as nested rectangular + sectors. + """ + if color_discrete_sequence is not None: + layout_patch = {"treemapcolorway": color_discrete_sequence} + else: + layout_patch = {} + if path is not None and (ids is not None or parents is not None): + raise ValueError( + "Either `path` should be provided, or `ids` and `parents`." + "These parameters are mutually exclusive and cannot be passed together." + ) + if path is not None and branchvalues is None: + branchvalues = "total" + return make_figure( + args=locals(), + constructor=go.Treemap, + trace_patch=dict(branchvalues=branchvalues, maxdepth=maxdepth), + layout_patch=layout_patch, + ) + + +treemap.__doc__ = make_docstring(treemap) + + +def icicle( + data_frame=None, + names=None, + values=None, + parents=None, + path=None, + ids=None, + color=None, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + color_discrete_sequence=None, + color_discrete_map=None, + hover_name=None, + hover_data=None, + custom_data=None, + labels=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, + branchvalues=None, + maxdepth=None, +) -> go.Figure: + """ + An icicle plot represents hierarchial data with adjoined rectangular + sectors that all cascade from root down to leaf in one direction. + """ + if color_discrete_sequence is not None: + layout_patch = {"iciclecolorway": color_discrete_sequence} + else: + layout_patch = {} + if path is not None and (ids is not None or parents is not None): + raise ValueError( + "Either `path` should be provided, or `ids` and `parents`." + "These parameters are mutually exclusive and cannot be passed together." + ) + if path is not None and branchvalues is None: + branchvalues = "total" + return make_figure( + args=locals(), + constructor=go.Icicle, + trace_patch=dict(branchvalues=branchvalues, maxdepth=maxdepth), + layout_patch=layout_patch, + ) + + +icicle.__doc__ = make_docstring(icicle) + + +def funnel( + data_frame=None, + x=None, + y=None, + color=None, + facet_row=None, + facet_col=None, + facet_col_wrap=0, + facet_row_spacing=None, + facet_col_spacing=None, + hover_name=None, + hover_data=None, + custom_data=None, + text=None, + animation_frame=None, + animation_group=None, + category_orders=None, + labels=None, + color_discrete_sequence=None, + color_discrete_map=None, + opacity=None, + orientation=None, + log_x=False, + log_y=False, + range_x=None, + range_y=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, +) -> go.Figure: + """ + In a funnel plot, each row of `data_frame` is represented as a + rectangular sector of a funnel. + """ + return make_figure(args=locals(), constructor=go.Funnel) + + +funnel.__doc__ = make_docstring(funnel, append_dict=_cartesian_append_dict) + + +def funnel_area( + data_frame=None, + names=None, + values=None, + color=None, + color_discrete_sequence=None, + color_discrete_map=None, + hover_name=None, + hover_data=None, + custom_data=None, + labels=None, + title=None, + subtitle=None, + template=None, + width=None, + height=None, + opacity=None, +) -> go.Figure: + """ + In a funnel area plot, each row of `data_frame` is represented as a + trapezoidal sector of a funnel. + """ + if color_discrete_sequence is not None: + layout_patch = {"funnelareacolorway": color_discrete_sequence} + else: + layout_patch = {} + return make_figure( + args=locals(), + constructor=go.Funnelarea, + trace_patch=dict(showlegend=(names is not None)), + layout_patch=layout_patch, + ) + + +funnel_area.__doc__ = make_docstring(funnel_area) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/express/_core.py b/.venv_haddock/lib/python3.12/site-packages/plotly/express/_core.py new file mode 100644 index 0000000000000000000000000000000000000000..9fbf526cdebfaea9a499ab5e8b31051a27546223 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/express/_core.py @@ -0,0 +1,2925 @@ +import plotly.graph_objs as go +import plotly.io as pio +from collections import namedtuple, OrderedDict +from ._special_inputs import IdentityMap, Constant, Range +from .trendline_functions import ols, lowess, rolling, expanding, ewm + +from _plotly_utils.basevalidators import ColorscaleValidator +from plotly.colors import qualitative, sequential +import math + +from plotly._subplots import ( + make_subplots, + _set_trace_grid_reference, + _subplot_type_for_trace_type, +) + +import narwhals.stable.v1 as nw + +# The reason to use narwhals.stable.v1 is to have a stable and perfectly +# backwards-compatible API, hence the confidence to not pin the Narwhals version exactly, +# allowing for multiple major libraries to have Narwhals as a dependency without +# forbidding users to install them all together due to dependency conflicts. + +NO_COLOR = "px_no_color_constant" + + +trendline_functions = dict( + lowess=lowess, rolling=rolling, ewm=ewm, expanding=expanding, ols=ols +) + +# Declare all supported attributes, across all plot types +direct_attrables = ( + ["base", "x", "y", "z", "a", "b", "c", "r", "theta", "size", "x_start", "x_end"] + + ["hover_name", "text", "names", "values", "parents", "wide_cross"] + + ["ids", "error_x", "error_x_minus", "error_y", "error_y_minus", "error_z"] + + ["error_z_minus", "lat", "lon", "locations", "animation_group"] +) +array_attrables = ["dimensions", "custom_data", "hover_data", "path", "wide_variable"] +group_attrables = ["animation_frame", "facet_row", "facet_col", "line_group"] +renameable_group_attrables = [ + "color", # renamed to marker.color or line.color in infer_config + "symbol", # renamed to marker.symbol in infer_config + "line_dash", # renamed to line.dash in infer_config + "pattern_shape", # renamed to marker.pattern.shape in infer_config +] +all_attrables = ( + direct_attrables + array_attrables + group_attrables + renameable_group_attrables +) + +cartesians = [go.Scatter, go.Scattergl, go.Bar, go.Funnel, go.Box, go.Violin] +cartesians += [go.Histogram, go.Histogram2d, go.Histogram2dContour] + + +class PxDefaults(object): + __slots__ = [ + "template", + "width", + "height", + "color_discrete_sequence", + "color_discrete_map", + "color_continuous_scale", + "symbol_sequence", + "symbol_map", + "line_dash_sequence", + "line_dash_map", + "pattern_shape_sequence", + "pattern_shape_map", + "size_max", + "category_orders", + "labels", + ] + + def __init__(self): + self.reset() + + def reset(self): + self.template = None + self.width = None + self.height = None + self.color_discrete_sequence = None + self.color_discrete_map = {} + self.color_continuous_scale = None + self.symbol_sequence = None + self.symbol_map = {} + self.line_dash_sequence = None + self.line_dash_map = {} + self.pattern_shape_sequence = None + self.pattern_shape_map = {} + self.size_max = 20 + self.category_orders = {} + self.labels = {} + + +defaults = PxDefaults() +del PxDefaults + + +MAPBOX_TOKEN = None + + +def set_mapbox_access_token(token): + """ + Arguments: + token: A Mapbox token to be used in `plotly.express.scatter_mapbox` and \ + `plotly.express.line_mapbox` figures. See \ + https://docs.mapbox.com/help/how-mapbox-works/access-tokens/ for more details + """ + global MAPBOX_TOKEN + MAPBOX_TOKEN = token + + +def get_trendline_results(fig): + """ + Extracts fit statistics for trendlines (when applied to figures generated with + the `trendline` argument set to `"ols"`). + + Arguments: + fig: the output of a `plotly.express` charting call + Returns: + A `pandas.DataFrame` with a column "px_fit_results" containing the `statsmodels` + results objects, along with columns identifying the subset of the data the + trendline was fit on. + """ + return fig._px_trendlines + + +Mapping = namedtuple( + "Mapping", + [ + "show_in_trace_name", + "grouper", + "val_map", + "sequence", + "updater", + "variable", + "facet", + ], +) +TraceSpec = namedtuple("TraceSpec", ["constructor", "attrs", "trace_patch", "marginal"]) + + +def get_label(args, column): + try: + return args["labels"][column] + except Exception: + return column + + +def invert_label(args, column): + """Invert mapping. + Find key corresponding to value column in dict args["labels"]. + Returns `column` if the value does not exist. + """ + reversed_labels = {value: key for (key, value) in args["labels"].items()} + try: + return reversed_labels[column] + except Exception: + return column + + +def _is_continuous(df: nw.DataFrame, col_name: str) -> bool: + if nw.dependencies.is_pandas_like_dataframe(df_native := df.to_native()): + # fastpath for pandas: Narwhals' Series.dtype has a bit of overhead, as it + # tries to distinguish between true "object" columns, and "string" columns + # disguised as "object". But here, we deal with neither. + return df_native[col_name].dtype.kind in "ifc" + return df.get_column(col_name).dtype.is_numeric() + + +def _to_unix_epoch_seconds(s: nw.Series) -> nw.Series: + dtype = s.dtype + if dtype == nw.Date: + return s.dt.timestamp("ms") / 1_000 + if dtype == nw.Datetime: + if dtype.time_unit in ("s", "ms"): + return s.dt.timestamp("ms") / 1_000 + elif dtype.time_unit == "us": + return s.dt.timestamp("us") / 1_000_000 + elif dtype.time_unit == "ns": + return s.dt.timestamp("ns") / 1_000_000_000 + else: + msg = "Unexpected dtype, please report a bug" + raise ValueError(msg) + else: + msg = f"Expected Date or Datetime, got {dtype}" + raise TypeError(msg) + + +def _generate_temporary_column_name(n_bytes, columns) -> str: + """Wraps of Narwhals generate_temporary_column_name to generate a token + which is guaranteed to not be in columns, nor in [col + token for col in columns] + """ + counter = 0 + while True: + # This is guaranteed to not be in columns by Narwhals + token = nw.generate_temporary_column_name(n_bytes, columns=columns) + + # Now check that it is not in the [col + token for col in columns] list + if token not in {f"{c}{token}" for c in columns}: + return token + + counter += 1 + if counter > 100: + msg = ( + "Internal Error: Plotly was not able to generate a column name with " + f"{n_bytes=} and not in {columns}.\n" + "Please report this to " + "https://github.com/plotly/plotly.py/issues/new and we will try to " + "replicate and fix it." + ) + raise AssertionError(msg) + + +def get_decorated_label(args, column, role): + original_label = label = get_label(args, column) + if "histfunc" in args and ( + (role == "z") + or (role == "x" and "orientation" in args and args["orientation"] == "h") + or (role == "y" and "orientation" in args and args["orientation"] == "v") + ): + histfunc = args["histfunc"] or "count" + if histfunc != "count": + label = "%s of %s" % (histfunc, label) + else: + label = "count" + + if "histnorm" in args and args["histnorm"] is not None: + if label == "count": + label = args["histnorm"] + else: + histnorm = args["histnorm"] + if histfunc == "sum": + if histnorm == "probability": + label = "%s of %s" % ("fraction", label) + elif histnorm == "percent": + label = "%s of %s" % (histnorm, label) + else: + label = "%s weighted by %s" % (histnorm, original_label) + elif histnorm == "probability": + label = "%s of sum of %s" % ("fraction", label) + elif histnorm == "percent": + label = "%s of sum of %s" % ("percent", label) + else: + label = "%s of %s" % (histnorm, label) + + if "barnorm" in args and args["barnorm"] is not None: + label = "%s (normalized as %s)" % (label, args["barnorm"]) + + return label + + +def make_mapping(args, variable): + if variable == "line_group" or variable == "animation_frame": + return Mapping( + show_in_trace_name=False, + grouper=args[variable], + val_map={}, + sequence=[""], + variable=variable, + updater=(lambda trace, v: v), + facet=None, + ) + if variable == "facet_row" or variable == "facet_col": + letter = "x" if variable == "facet_col" else "y" + return Mapping( + show_in_trace_name=False, + variable=letter, + grouper=args[variable], + val_map={}, + sequence=[i for i in range(1, 1000)], + updater=(lambda trace, v: v), + facet="row" if variable == "facet_row" else "col", + ) + (parent, variable, *other_variables) = variable.split(".") + vprefix = variable + arg_name = variable + if variable == "color": + vprefix = "color_discrete" + if variable == "dash": + arg_name = "line_dash" + vprefix = "line_dash" + if variable in ["pattern", "shape"]: + arg_name = "pattern_shape" + vprefix = "pattern_shape" + if args[vprefix + "_map"] == "identity": + val_map = IdentityMap() + else: + val_map = args[vprefix + "_map"].copy() + return Mapping( + show_in_trace_name=True, + variable=variable, + grouper=args[arg_name], + val_map=val_map, + sequence=args[vprefix + "_sequence"], + updater=lambda trace, v: trace.update( + {parent: {".".join([variable] + other_variables): v}} + ), + facet=None, + ) + + +def make_trace_kwargs(args, trace_spec, trace_data, mapping_labels, sizeref): + """Populates a dict with arguments to update trace + + Parameters + ---------- + args : dict + args to be used for the trace + trace_spec : NamedTuple + which kind of trace to be used (has constructor, marginal etc. + attributes) + trace_data : pandas DataFrame + data + mapping_labels : dict + to be used for hovertemplate + sizeref : float + marker sizeref + + Returns + ------- + trace_patch : dict + dict to be used to update trace + fit_results : dict + fit information to be used for trendlines + """ + trace_data: nw.DataFrame + df: nw.DataFrame = args["data_frame"] + + if "line_close" in args and args["line_close"]: + trace_data = nw.concat([trace_data, trace_data.head(1)], how="vertical") + + trace_patch = trace_spec.trace_patch.copy() or {} + fit_results = None + hover_header = "" + for attr_name in trace_spec.attrs: + attr_value = args[attr_name] + attr_label = get_decorated_label(args, attr_value, attr_name) + if attr_name == "dimensions": + dims = [ + (name, trace_data.get_column(name)) + for name in trace_data.columns + if ((not attr_value) or (name in attr_value)) + and (trace_spec.constructor != go.Parcoords or _is_continuous(df, name)) + and ( + trace_spec.constructor != go.Parcats + or (attr_value is not None and name in attr_value) + or nw.to_py_scalar(df.get_column(name).n_unique()) + <= args["dimensions_max_cardinality"] + ) + ] + trace_patch["dimensions"] = [ + dict(label=get_label(args, name), values=column) + for (name, column) in dims + ] + if trace_spec.constructor == go.Splom: + for d in trace_patch["dimensions"]: + d["axis"] = dict(matches=True) + mapping_labels["%{xaxis.title.text}"] = "%{x}" + mapping_labels["%{yaxis.title.text}"] = "%{y}" + + elif attr_value is not None: + if attr_name == "size": + if "marker" not in trace_patch: + trace_patch["marker"] = dict() + trace_patch["marker"]["size"] = trace_data.get_column(attr_value) + trace_patch["marker"]["sizemode"] = "area" + trace_patch["marker"]["sizeref"] = sizeref + mapping_labels[attr_label] = "%{marker.size}" + elif attr_name == "marginal_x": + if trace_spec.constructor == go.Histogram: + mapping_labels["count"] = "%{y}" + elif attr_name == "marginal_y": + if trace_spec.constructor == go.Histogram: + mapping_labels["count"] = "%{x}" + elif attr_name == "trendline": + if ( + args["x"] + and args["y"] + and len( + trace_data.select(nw.col(args["x"], args["y"])).drop_nulls() + ) + > 1 + ): + # sorting is bad but trace_specs with "trendline" have no other attrs + sorted_trace_data = trace_data.sort(by=args["x"], nulls_last=True) + y = sorted_trace_data.get_column(args["y"]) + x = sorted_trace_data.get_column(args["x"]) + + if x.dtype == nw.Datetime or x.dtype == nw.Date: + # convert to unix epoch seconds + x = _to_unix_epoch_seconds(x) + elif not x.dtype.is_numeric(): + try: + x = x.cast(nw.Float64()) + except ValueError: + raise ValueError( + "Could not convert value of 'x' ('%s') into a numeric type. " + "If 'x' contains stringified dates, please convert to a datetime column." + % args["x"] + ) + + if not y.dtype.is_numeric(): + try: + y = y.cast(nw.Float64()) + except ValueError: + raise ValueError( + "Could not convert value of 'y' into a numeric type." + ) + + # preserve original values of "x" in case they're dates + # otherwise numpy/pandas can mess with the timezones + # NB this means trendline functions must output one-to-one with the input series + # i.e. we can't do resampling, because then the X values might not line up! + non_missing = ~(x.is_null() | y.is_null()) + trace_patch["x"] = sorted_trace_data.filter(non_missing).get_column( + args["x"] + ) + if ( + trace_patch["x"].dtype == nw.Datetime + and trace_patch["x"].dtype.time_zone is not None + ): + # Remove time zone so that local time is displayed + trace_patch["x"] = ( + trace_patch["x"].dt.replace_time_zone(None).to_numpy() + ) + else: + trace_patch["x"] = trace_patch["x"].to_numpy() + + trendline_function = trendline_functions[attr_value] + y_out, hover_header, fit_results = trendline_function( + args["trendline_options"], + sorted_trace_data.get_column(args["x"]), # narwhals series + x.to_numpy(), # numpy array + y.to_numpy(), # numpy array + args["x"], + args["y"], + non_missing.to_numpy(), # numpy array + ) + assert len(y_out) == len(trace_patch["x"]), ( + "missing-data-handling failure in trendline code" + ) + trace_patch["y"] = y_out + mapping_labels[get_label(args, args["x"])] = "%{x}" + mapping_labels[get_label(args, args["y"])] = "%{y} (trend)" + elif attr_name.startswith("error"): + error_xy = attr_name[:7] + arr = "arrayminus" if attr_name.endswith("minus") else "array" + if error_xy not in trace_patch: + trace_patch[error_xy] = {} + trace_patch[error_xy][arr] = trace_data.get_column(attr_value) + elif attr_name == "custom_data": + if len(attr_value) > 0: + # here we store a data frame in customdata, and it's serialized + # as a list of row lists, which is what we want + trace_patch["customdata"] = trace_data.select(nw.col(attr_value)) + elif attr_name == "hover_name": + if trace_spec.constructor not in [ + go.Histogram, + go.Histogram2d, + go.Histogram2dContour, + ]: + trace_patch["hovertext"] = trace_data.get_column(attr_value) + if hover_header == "": + hover_header = "%{hovertext}

" + elif attr_name == "hover_data": + if trace_spec.constructor not in [ + go.Histogram, + go.Histogram2d, + go.Histogram2dContour, + ]: + hover_is_dict = isinstance(attr_value, dict) + customdata_cols = args.get("custom_data") or [] + for col in attr_value: + if hover_is_dict and not attr_value[col]: + continue + if col in [ + args.get("x"), + args.get("y"), + args.get("z"), + args.get("base"), + ]: + continue + try: + position = args["custom_data"].index(col) + except (ValueError, AttributeError, KeyError): + position = len(customdata_cols) + customdata_cols.append(col) + attr_label_col = get_decorated_label(args, col, None) + mapping_labels[attr_label_col] = "%%{customdata[%d]}" % ( + position + ) + + if len(customdata_cols) > 0: + # here we store a data frame in customdata, and it's serialized + # as a list of row lists, which is what we want + + # dict.fromkeys(customdata_cols) allows to deduplicate column + # names, yet maintaining the original order. + trace_patch["customdata"] = trace_data.select( + *[nw.col(c) for c in dict.fromkeys(customdata_cols)] + ) + elif attr_name == "color": + if trace_spec.constructor in [ + go.Choropleth, + go.Choroplethmap, + go.Choroplethmapbox, + ]: + trace_patch["z"] = trace_data.get_column(attr_value) + trace_patch["coloraxis"] = "coloraxis1" + mapping_labels[attr_label] = "%{z}" + elif trace_spec.constructor in [ + go.Sunburst, + go.Treemap, + go.Icicle, + go.Pie, + go.Funnelarea, + ]: + if "marker" not in trace_patch: + trace_patch["marker"] = dict() + + if args.get("color_is_continuous"): + trace_patch["marker"]["colors"] = trace_data.get_column( + attr_value + ) + trace_patch["marker"]["coloraxis"] = "coloraxis1" + mapping_labels[attr_label] = "%{color}" + else: + trace_patch["marker"]["colors"] = [] + if args["color_discrete_map"] is not None: + mapping = args["color_discrete_map"].copy() + else: + mapping = {} + for cat in trace_data.get_column(attr_value).to_list(): + # although trace_data.get_column(attr_value) is a Narwhals + # Series, which is an iterable, explicitly calling a to_list() + # makes sure that the elements we loop over are python objects + # in all cases, since depending on the backend this may not be + # the case (e.g. PyArrow) + if mapping.get(cat) is None: + mapping[cat] = args["color_discrete_sequence"][ + len(mapping) % len(args["color_discrete_sequence"]) + ] + trace_patch["marker"]["colors"].append(mapping[cat]) + else: + colorable = "marker" + if trace_spec.constructor in [go.Parcats, go.Parcoords]: + colorable = "line" + if colorable not in trace_patch: + trace_patch[colorable] = dict() + trace_patch[colorable]["color"] = trace_data.get_column(attr_value) + trace_patch[colorable]["coloraxis"] = "coloraxis1" + mapping_labels[attr_label] = "%%{%s.color}" % colorable + elif attr_name == "animation_group": + trace_patch["ids"] = trace_data.get_column(attr_value) + elif attr_name == "locations": + trace_patch[attr_name] = trace_data.get_column(attr_value) + mapping_labels[attr_label] = "%{location}" + elif attr_name == "values": + trace_patch[attr_name] = trace_data.get_column(attr_value) + _label = "value" if attr_label == "values" else attr_label + mapping_labels[_label] = "%{value}" + elif attr_name == "parents": + trace_patch[attr_name] = trace_data.get_column(attr_value) + _label = "parent" if attr_label == "parents" else attr_label + mapping_labels[_label] = "%{parent}" + elif attr_name == "ids": + trace_patch[attr_name] = trace_data.get_column(attr_value) + _label = "id" if attr_label == "ids" else attr_label + mapping_labels[_label] = "%{id}" + elif attr_name == "names": + if trace_spec.constructor in [ + go.Sunburst, + go.Treemap, + go.Icicle, + go.Pie, + go.Funnelarea, + ]: + trace_patch["labels"] = trace_data.get_column(attr_value) + _label = "label" if attr_label == "names" else attr_label + mapping_labels[_label] = "%{label}" + else: + trace_patch[attr_name] = trace_data.get_column(attr_value) + else: + trace_patch[attr_name] = trace_data.get_column(attr_value) + mapping_labels[attr_label] = "%%{%s}" % attr_name + elif (trace_spec.constructor == go.Histogram and attr_name in ["x", "y"]) or ( + trace_spec.constructor in [go.Histogram2d, go.Histogram2dContour] + and attr_name == "z" + ): + # ensure that stuff like "count" gets into the hoverlabel + mapping_labels[attr_label] = "%%{%s}" % attr_name + if trace_spec.constructor not in [go.Parcoords, go.Parcats]: + # Modify mapping_labels according to hover_data keys + # if hover_data is a dict + mapping_labels_copy = OrderedDict(mapping_labels) + if args["hover_data"] and isinstance(args["hover_data"], dict): + for k, v in mapping_labels.items(): + # We need to invert the mapping here + k_args = invert_label(args, k) + if k_args in args["hover_data"]: + formatter = args["hover_data"][k_args][0] + if formatter: + if isinstance(formatter, str): + mapping_labels_copy[k] = v.replace("}", "%s}" % formatter) + else: + _ = mapping_labels_copy.pop(k) + hover_lines = [k + "=" + v for k, v in mapping_labels_copy.items()] + trace_patch["hovertemplate"] = hover_header + "
".join(hover_lines) + trace_patch["hovertemplate"] += "" + return trace_patch, fit_results + + +def configure_axes(args, constructor, fig, orders): + configurators = { + go.Scatter3d: configure_3d_axes, + go.Scatterternary: configure_ternary_axes, + go.Scatterpolar: configure_polar_axes, + go.Scatterpolargl: configure_polar_axes, + go.Barpolar: configure_polar_axes, + go.Scattermap: configure_map, + go.Choroplethmap: configure_map, + go.Densitymap: configure_map, + go.Scattermapbox: configure_mapbox, + go.Choroplethmapbox: configure_mapbox, + go.Densitymapbox: configure_mapbox, + go.Scattergeo: configure_geo, + go.Choropleth: configure_geo, + } + for c in cartesians: + configurators[c] = configure_cartesian_axes + if constructor in configurators: + configurators[constructor](args, fig, orders) + + +def set_cartesian_axis_opts(args, axis, letter, orders): + log_key = "log_" + letter + range_key = "range_" + letter + if log_key in args and args[log_key]: + axis["type"] = "log" + if range_key in args and args[range_key]: + axis["range"] = [math.log(r, 10) for r in args[range_key]] + elif range_key in args and args[range_key]: + axis["range"] = args[range_key] + + if args[letter] in orders: + axis["categoryorder"] = "array" + axis["categoryarray"] = ( + orders[args[letter]] + if isinstance(axis, go.layout.XAxis) + else list(reversed(orders[args[letter]])) # top down for Y axis + ) + + +def configure_cartesian_marginal_axes(args, fig, orders): + nrows = len(fig._grid_ref) + ncols = len(fig._grid_ref[0]) + + # Set y-axis titles and axis options in the left-most column + for yaxis in fig.select_yaxes(col=1): + set_cartesian_axis_opts(args, yaxis, "y", orders) + + # Set x-axis titles and axis options in the bottom-most row + for xaxis in fig.select_xaxes(row=1): + set_cartesian_axis_opts(args, xaxis, "x", orders) + + # Configure axis ticks on marginal subplots + if args["marginal_x"]: + fig.update_yaxes( + showticklabels=False, showline=False, ticks="", range=None, row=nrows + ) + if args["template"].layout.yaxis.showgrid is None: + fig.update_yaxes(showgrid=args["marginal_x"] == "histogram", row=nrows) + if args["template"].layout.xaxis.showgrid is None: + fig.update_xaxes(showgrid=True, row=nrows) + + if args["marginal_y"]: + fig.update_xaxes( + showticklabels=False, showline=False, ticks="", range=None, col=ncols + ) + if args["template"].layout.xaxis.showgrid is None: + fig.update_xaxes(showgrid=args["marginal_y"] == "histogram", col=ncols) + if args["template"].layout.yaxis.showgrid is None: + fig.update_yaxes(showgrid=True, col=ncols) + + # Add axis titles to non-marginal subplots + y_title = get_decorated_label(args, args["y"], "y") + if args["marginal_x"]: + fig.update_yaxes(title_text=y_title, row=1, col=1) + else: + for row in range(1, nrows + 1): + fig.update_yaxes(title_text=y_title, row=row, col=1) + + x_title = get_decorated_label(args, args["x"], "x") + if args["marginal_y"]: + fig.update_xaxes(title_text=x_title, row=1, col=1) + else: + for col in range(1, ncols + 1): + fig.update_xaxes(title_text=x_title, row=1, col=col) + + # Configure axis type across all x-axes + if "log_x" in args and args["log_x"]: + fig.update_xaxes(type="log") + + # Configure axis type across all y-axes + if "log_y" in args and args["log_y"]: + fig.update_yaxes(type="log") + + # Configure matching and axis type for marginal y-axes + matches_y = "y" + str(ncols + 1) + if args["marginal_x"]: + for row in range(2, nrows + 1, 2): + fig.update_yaxes(matches=matches_y, type=None, row=row) + + if args["marginal_y"]: + for col in range(2, ncols + 1, 2): + fig.update_xaxes(matches="x2", type=None, col=col) + + +def configure_cartesian_axes(args, fig, orders): + if ("marginal_x" in args and args["marginal_x"]) or ( + "marginal_y" in args and args["marginal_y"] + ): + configure_cartesian_marginal_axes(args, fig, orders) + return + + # Set y-axis titles and axis options in the left-most column + y_title = get_decorated_label(args, args["y"], "y") + for yaxis in fig.select_yaxes(col=1): + yaxis.update(title_text=y_title) + set_cartesian_axis_opts(args, yaxis, "y", orders) + + # Set x-axis titles and axis options in the bottom-most row + x_title = get_decorated_label(args, args["x"], "x") + for xaxis in fig.select_xaxes(row=1): + if "is_timeline" not in args: + xaxis.update(title_text=x_title) + set_cartesian_axis_opts(args, xaxis, "x", orders) + + # Configure axis type across all x-axes + if "log_x" in args and args["log_x"]: + fig.update_xaxes(type="log") + + # Configure axis type across all y-axes + if "log_y" in args and args["log_y"]: + fig.update_yaxes(type="log") + + if "is_timeline" in args: + fig.update_xaxes(type="date") + + if "ecdfmode" in args: + if args["orientation"] == "v": + fig.update_yaxes(rangemode="tozero") + else: + fig.update_xaxes(rangemode="tozero") + + +def configure_ternary_axes(args, fig, orders): + fig.update_ternaries( + aaxis=dict(title_text=get_label(args, args["a"])), + baxis=dict(title_text=get_label(args, args["b"])), + caxis=dict(title_text=get_label(args, args["c"])), + ) + + +def configure_polar_axes(args, fig, orders): + patch = dict( + angularaxis=dict(direction=args["direction"], rotation=args["start_angle"]), + radialaxis=dict(), + ) + + for var, axis in [("r", "radialaxis"), ("theta", "angularaxis")]: + if args[var] in orders: + patch[axis]["categoryorder"] = "array" + patch[axis]["categoryarray"] = orders[args[var]] + + radialaxis = patch["radialaxis"] + if args["log_r"]: + radialaxis["type"] = "log" + if args["range_r"]: + radialaxis["range"] = [math.log(x, 10) for x in args["range_r"]] + else: + if args["range_r"]: + radialaxis["range"] = args["range_r"] + + if args["range_theta"]: + patch["sector"] = args["range_theta"] + fig.update_polars(patch) + + +def configure_3d_axes(args, fig, orders): + patch = dict( + xaxis=dict(title_text=get_label(args, args["x"])), + yaxis=dict(title_text=get_label(args, args["y"])), + zaxis=dict(title_text=get_label(args, args["z"])), + ) + + for letter in ["x", "y", "z"]: + axis = patch[letter + "axis"] + if args["log_" + letter]: + axis["type"] = "log" + if args["range_" + letter]: + axis["range"] = [math.log(x, 10) for x in args["range_" + letter]] + else: + if args["range_" + letter]: + axis["range"] = args["range_" + letter] + if args[letter] in orders: + axis["categoryorder"] = "array" + axis["categoryarray"] = orders[args[letter]] + fig.update_scenes(patch) + + +def configure_mapbox(args, fig, orders): + center = args["center"] + if not center and "lat" in args and "lon" in args: + center = dict( + lat=args["data_frame"][args["lat"]].mean(), + lon=args["data_frame"][args["lon"]].mean(), + ) + fig.update_mapboxes( + accesstoken=MAPBOX_TOKEN, + center=center, + zoom=args["zoom"], + style=args["mapbox_style"], + ) + + +def configure_map(args, fig, orders): + center = args["center"] + if not center and "lat" in args and "lon" in args: + center = dict( + lat=args["data_frame"][args["lat"]].mean(), + lon=args["data_frame"][args["lon"]].mean(), + ) + fig.update_maps( + center=center, + zoom=args["zoom"], + style=args["map_style"], + ) + + +def configure_geo(args, fig, orders): + fig.update_geos( + center=args["center"], + scope=args["scope"], + fitbounds=args["fitbounds"], + visible=args["basemap_visible"], + projection=dict(type=args["projection"]), + ) + + +def configure_animation_controls(args, constructor, fig): + def frame_args(duration): + return { + "frame": {"duration": duration, "redraw": constructor != go.Scatter}, + "mode": "immediate", + "fromcurrent": True, + "transition": {"duration": duration, "easing": "linear"}, + } + + if "animation_frame" in args and args["animation_frame"] and len(fig.frames) > 1: + fig.layout.updatemenus = [ + { + "buttons": [ + { + "args": [None, frame_args(500)], + "label": "▶", + "method": "animate", + }, + { + "args": [[None], frame_args(0)], + "label": "◼", + "method": "animate", + }, + ], + "direction": "left", + "pad": {"r": 10, "t": 70}, + "showactive": False, + "type": "buttons", + "x": 0.1, + "xanchor": "right", + "y": 0, + "yanchor": "top", + } + ] + fig.layout.sliders = [ + { + "active": 0, + "yanchor": "top", + "xanchor": "left", + "currentvalue": { + "prefix": get_label(args, args["animation_frame"]) + "=" + }, + "pad": {"b": 10, "t": 60}, + "len": 0.9, + "x": 0.1, + "y": 0, + "steps": [ + { + "args": [[f.name], frame_args(0)], + "label": f.name, + "method": "animate", + } + for f in fig.frames + ], + } + ] + + +def make_trace_spec(args, constructor, attrs, trace_patch): + if constructor in [go.Scatter, go.Scatterpolar]: + if "render_mode" in args and ( + args["render_mode"] == "webgl" + or ( + args["render_mode"] == "auto" + and len(args["data_frame"]) > 1000 + and args.get("line_shape") != "spline" + and args["animation_frame"] is None + ) + ): + if constructor == go.Scatter: + constructor = go.Scattergl + if "orientation" in trace_patch: + del trace_patch["orientation"] + else: + constructor = go.Scatterpolargl + # Create base trace specification + result = [TraceSpec(constructor, attrs, trace_patch, None)] + + # Add marginal trace specifications + for letter in ["x", "y"]: + if "marginal_" + letter in args and args["marginal_" + letter]: + trace_spec = None + axis_map = dict( + xaxis="x1" if letter == "x" else "x2", + yaxis="y1" if letter == "y" else "y2", + ) + if args["marginal_" + letter] == "histogram": + trace_spec = TraceSpec( + constructor=go.Histogram, + attrs=[letter, "marginal_" + letter], + trace_patch=dict(opacity=0.5, bingroup=letter, **axis_map), + marginal=letter, + ) + elif args["marginal_" + letter] == "violin": + trace_spec = TraceSpec( + constructor=go.Violin, + attrs=[letter, "hover_name", "hover_data"], + trace_patch=dict(scalegroup=letter), + marginal=letter, + ) + elif args["marginal_" + letter] == "box": + trace_spec = TraceSpec( + constructor=go.Box, + attrs=[letter, "hover_name", "hover_data"], + trace_patch=dict(notched=True), + marginal=letter, + ) + elif args["marginal_" + letter] == "rug": + symbols = {"x": "line-ns-open", "y": "line-ew-open"} + trace_spec = TraceSpec( + constructor=go.Box, + attrs=[letter, "hover_name", "hover_data"], + trace_patch=dict( + fillcolor="rgba(255,255,255,0)", + line={"color": "rgba(255,255,255,0)"}, + boxpoints="all", + jitter=0, + hoveron="points", + marker={"symbol": symbols[letter]}, + ), + marginal=letter, + ) + if "color" in attrs or "color" not in args: + if "marker" not in trace_spec.trace_patch: + trace_spec.trace_patch["marker"] = dict() + first_default_color = args["color_continuous_scale"][0] + trace_spec.trace_patch["marker"]["color"] = first_default_color + result.append(trace_spec) + + # Add trendline trace specifications + if args.get("trendline") and args.get("trendline_scope", "trace") == "trace": + result.append(make_trendline_spec(args, constructor)) + return result + + +def make_trendline_spec(args, constructor): + trace_spec = TraceSpec( + constructor=( + go.Scattergl + if constructor == go.Scattergl # could be contour + else go.Scatter + ), + attrs=["trendline"], + trace_patch=dict(mode="lines"), + marginal=None, + ) + if args["trendline_color_override"]: + trace_spec.trace_patch["line"] = dict(color=args["trendline_color_override"]) + return trace_spec + + +def one_group(x): + return "" + + +def apply_default_cascade(args, constructor): + # first we apply px.defaults to unspecified args + + for param in defaults.__slots__: + if param in args and args[param] is None: + args[param] = getattr(defaults, param) + + # load the default template if set, otherwise "plotly" + if args["template"] is None: + if pio.templates.default is not None: + args["template"] = pio.templates.default + else: + args["template"] = "plotly" + + try: + # retrieve the actual template if we were given a name + args["template"] = pio.templates[args["template"]] + except Exception: + # otherwise try to build a real template + args["template"] = go.layout.Template(args["template"]) + + # if colors not set explicitly or in px.defaults, defer to a template + # if the template doesn't have one, we set some final fallback defaults + if "color_continuous_scale" in args: + if ( + args["color_continuous_scale"] is None + and args["template"].layout.colorscale.sequential + ): + args["color_continuous_scale"] = [ + x[1] for x in args["template"].layout.colorscale.sequential + ] + if args["color_continuous_scale"] is None: + args["color_continuous_scale"] = sequential.Viridis + + # if color_discrete_sequence not set explicitly or in px.defaults, + # see if we can defer to template. Try trace-specific colors first, + # then layout.colorway, then set reasonable defaults + if "color_discrete_sequence" in args: + if args["color_discrete_sequence"] is None and constructor is not None: + if constructor == "timeline": + trace_type = "bar" + else: + trace_type = constructor().type + if trace_data_list := getattr(args["template"].data, trace_type, None): + trace_specific_colors = [ + trace_data.marker.color + for trace_data in trace_data_list + if hasattr(trace_data, "marker") + and hasattr(trace_data.marker, "color") + ] + # If template contains at least one color for this trace type, assign to color_discrete_sequence + if any(trace_specific_colors): + args["color_discrete_sequence"] = trace_specific_colors + # fallback to layout.colorway if trace-specific colors not available + if args["color_discrete_sequence"] is None and args["template"].layout.colorway: + args["color_discrete_sequence"] = args["template"].layout.colorway + # final fallback to default qualitative palette + if args["color_discrete_sequence"] is None: + args["color_discrete_sequence"] = qualitative.D3 + + # if symbol_sequence/line_dash_sequence not set explicitly or in px.defaults, + # see if we can defer to template. If not, set reasonable defaults + if "symbol_sequence" in args: + if args["symbol_sequence"] is None and args["template"].data.scatter: + args["symbol_sequence"] = [ + scatter.marker.symbol for scatter in args["template"].data.scatter + ] + if not args["symbol_sequence"] or not any(args["symbol_sequence"]): + args["symbol_sequence"] = ["circle", "diamond", "square", "x", "cross"] + + if "line_dash_sequence" in args: + if args["line_dash_sequence"] is None and args["template"].data.scatter: + args["line_dash_sequence"] = [ + scatter.line.dash for scatter in args["template"].data.scatter + ] + if not args["line_dash_sequence"] or not any(args["line_dash_sequence"]): + args["line_dash_sequence"] = [ + "solid", + "dot", + "dash", + "longdash", + "dashdot", + "longdashdot", + ] + + if "pattern_shape_sequence" in args: + if args["pattern_shape_sequence"] is None and args["template"].data.bar: + args["pattern_shape_sequence"] = [ + bar.marker.pattern.shape for bar in args["template"].data.bar + ] + if not args["pattern_shape_sequence"] or not any( + args["pattern_shape_sequence"] + ): + args["pattern_shape_sequence"] = ["", "/", "\\", "x", "+", "."] + + +def _check_name_not_reserved(field_name, reserved_names): + if field_name not in reserved_names: + return field_name + else: + raise NameError( + "A name conflict was encountered for argument '%s'. " + "A column or index with name '%s' is ambiguous." % (field_name, field_name) + ) + + +def _get_reserved_col_names(args): + """ + This function builds a list of columns of the data_frame argument used + as arguments, either as str/int arguments or given as columns + (pandas series type). + """ + df: nw.DataFrame = args["data_frame"] + reserved_names = set() + for field in args: + if field not in all_attrables: + continue + names = args[field] if field in array_attrables else [args[field]] + if names is None: + continue + for arg in names: + if arg is None: + continue + elif isinstance(arg, str): # no need to add ints since kw arg are not ints + reserved_names.add(arg) + elif nw.dependencies.is_into_series(arg): + arg_series = nw.from_native(arg, series_only=True) + arg_name = arg_series.name + if arg_name and arg_name in df.columns: + in_df = (arg_series == df.get_column(arg_name)).all() + if in_df: + reserved_names.add(arg_name) + elif arg is nw.maybe_get_index(df) and arg.name is not None: + reserved_names.add(arg.name) + + return reserved_names + + +def _is_col_list(columns, arg, is_pd_like, native_namespace): + """Returns True if arg looks like it's a list of columns or references to columns + in df_input, and False otherwise (in which case it's assumed to be a single column + or reference to a column). + """ + if arg is None or isinstance(arg, str) or isinstance(arg, int): + return False + if is_pd_like and isinstance(arg, native_namespace.MultiIndex): + return False # just to keep existing behaviour for now + try: + iter(arg) + except TypeError: + return False # not iterable + for c in arg: + if isinstance(c, str) or isinstance(c, int): + if columns is None or c not in columns: + return False + else: + try: + iter(c) + except TypeError: + return False # not iterable + return True + + +def _isinstance_listlike(x): + """Returns True if x is an iterable which can be transformed into a pandas Series, + False for the other types of possible values of a `hover_data` dict. + A tuple of length 2 is a special case corresponding to a (format, data) tuple. + """ + if ( + isinstance(x, str) + or (isinstance(x, tuple) and len(x) == 2) + or isinstance(x, bool) + or x is None + ): + return False + else: + return True + + +def _escape_col_name(columns, col_name, extra): + if columns is None: + return col_name + while col_name in columns or col_name in extra: + col_name = "_" + col_name + return col_name + + +def to_named_series(x, name=None, native_namespace=None): + """Assuming x is list-like or even an existing Series, returns a new Series named `name`.""" + # With `pass_through=True`, the original object will be returned if unable to convert + # to a Narwhals Series. + x = nw.from_native(x, series_only=True, pass_through=True) + if isinstance(x, nw.Series): + return x.rename(name) + elif native_namespace is not None: + return nw.new_series(name=name, values=x, native_namespace=native_namespace) + else: + try: + import pandas as pd + + return nw.new_series(name=name, values=x, native_namespace=pd) + except ImportError: + msg = "Pandas installation is required if no dataframe is provided." + raise NotImplementedError(msg) + + +def process_args_into_dataframe( + args, wide_mode, var_name, value_name, is_pd_like, native_namespace +): + """ + After this function runs, the `all_attrables` keys of `args` all contain only + references to columns of `df_output`. This function handles the extraction of data + from `args["attrable"]` and column-name-generation as appropriate, and adds the + data to `df_output` and then replaces `args["attrable"]` with the appropriate + reference. + """ + + df_input: nw.DataFrame | None = args["data_frame"] + df_provided = df_input is not None + + # we use a dict instead of a dataframe directly so that it doesn't cause + # PerformanceWarning by pandas by repeatedly setting the columns. + # a dict is used instead of a list as the columns needs to be overwritten. + df_output = {} + constants = {} + ranges = [] + wide_id_vars = set() + reserved_names = _get_reserved_col_names(args) if df_provided else set() + + # Case of functions with a "dimensions" kw: scatter_matrix, parcats, parcoords + if "dimensions" in args and args["dimensions"] is None: + if not df_provided: + raise ValueError( + "No data were provided. Please provide data either with the `data_frame` or with the `dimensions` argument." + ) + else: + df_output = {col: df_input.get_column(col) for col in df_input.columns} + + # hover_data is a dict + hover_data_is_dict = ( + "hover_data" in args + and args["hover_data"] + and isinstance(args["hover_data"], dict) + ) + # If dict, convert all values of hover_data to tuples to simplify processing + if hover_data_is_dict: + for k in args["hover_data"]: + if _isinstance_listlike(args["hover_data"][k]): + args["hover_data"][k] = (True, args["hover_data"][k]) + if not isinstance(args["hover_data"][k], tuple): + args["hover_data"][k] = (args["hover_data"][k], None) + if df_provided and args["hover_data"][k][1] is not None and k in df_input: + raise ValueError( + "Ambiguous input: values for '%s' appear both in hover_data and data_frame" + % k + ) + # Loop over possible arguments + for field_name in all_attrables: + # Massaging variables + argument_list = ( + [args.get(field_name)] + if field_name not in array_attrables + else args.get(field_name) + ) + + # argument not specified, continue + # The original also tested `or argument_list is [None]` but + # that clause is always False, so it has been removed. The + # alternative fix would have been to test that `argument_list` + # is of length 1 and its sole element is `None`, but that + # feels pedantic. All tests pass with the change below; let's + # see if the world decides we were wrong. + if argument_list is None: + continue + + # Argument name: field_name if the argument is not a list + # Else we give names like ["hover_data_0, hover_data_1"] etc. + field_list = ( + [field_name] + if field_name not in array_attrables + else [field_name + "_" + str(i) for i in range(len(argument_list))] + ) + # argument_list and field_list ready, iterate over them + # Core of the loop starts here + for i, (argument, field) in enumerate(zip(argument_list, field_list)): + length = len(df_output[next(iter(df_output))]) if len(df_output) else 0 + if argument is None: + continue + col_name = None + # Case of multiindex + if is_pd_like and isinstance(argument, native_namespace.MultiIndex): + raise TypeError( + f"Argument '{field}' is a {native_namespace.__name__} MultiIndex. " + f"{native_namespace.__name__} MultiIndex is not supported by plotly " + "express at the moment." + ) + # ----------------- argument is a special value ---------------------- + if isinstance(argument, (Constant, Range)): + col_name = _check_name_not_reserved( + str(argument.label) if argument.label is not None else field, + reserved_names, + ) + if isinstance(argument, Constant): + constants[col_name] = argument.value + else: + ranges.append(col_name) + # ----------------- argument is likely a col name ---------------------- + elif isinstance(argument, str) or not hasattr(argument, "__len__"): + if ( + field_name == "hover_data" + and hover_data_is_dict + and args["hover_data"][str(argument)][1] is not None + ): + # hover_data has onboard data + # previously-checked to have no name-conflict with data_frame + col_name = str(argument) + real_argument = args["hover_data"][col_name][1] + + if length and (real_length := len(real_argument)) != length: + raise ValueError( + "All arguments should have the same length. " + "The length of hover_data key `%s` is %d, whereas the " + "length of previously-processed arguments %s is %d" + % ( + argument, + real_length, + str(list(df_output.keys())), + length, + ) + ) + df_output[col_name] = to_named_series( + real_argument, col_name, native_namespace + ) + elif not df_provided: + raise ValueError( + "String or int arguments are only possible when a " + "DataFrame or an array is provided in the `data_frame` " + "argument. No DataFrame was provided, but argument " + "'%s' is of type str or int." % field + ) + # Check validity of column name + elif argument not in df_input.columns: + if wide_mode and argument in (value_name, var_name): + continue + else: + err_msg = ( + "Value of '%s' is not the name of a column in 'data_frame'. " + "Expected one of %s but received: %s" + % (field, str(list(df_input.columns)), argument) + ) + if argument == "index": + err_msg += "\n To use the index, pass it in directly as `df.index`." + raise ValueError(err_msg) + elif length and (actual_len := len(df_input)) != length: + raise ValueError( + "All arguments should have the same length. " + "The length of column argument `df[%s]` is %d, whereas the " + "length of previously-processed arguments %s is %d" + % ( + field, + actual_len, + str(list(df_output.keys())), + length, + ) + ) + else: + col_name = str(argument) + df_output[col_name] = to_named_series( + df_input.get_column(argument), col_name + ) + # ----------------- argument is likely a column / array / list.... ------- + else: + if df_provided and hasattr(argument, "name"): + if is_pd_like and argument is nw.maybe_get_index(df_input): + if argument.name is None or argument.name in df_input.columns: + col_name = "index" + else: + col_name = argument.name + col_name = _escape_col_name( + df_input.columns, col_name, [var_name, value_name] + ) + else: + if ( + argument.name is not None + and argument.name in df_input.columns + and ( + to_named_series( + argument, argument.name, native_namespace + ) + == df_input.get_column(argument.name) + ).all() + ): + col_name = argument.name + if col_name is None: # numpy array, list... + col_name = _check_name_not_reserved(field, reserved_names) + + if length and (len_arg := len(argument)) != length: + raise ValueError( + "All arguments should have the same length. " + "The length of argument `%s` is %d, whereas the " + "length of previously-processed arguments %s is %d" + % (field, len_arg, str(list(df_output.keys())), length) + ) + + df_output[str(col_name)] = to_named_series( + x=argument, + name=str(col_name), + native_namespace=native_namespace, + ) + + # Finally, update argument with column name now that column exists + assert col_name is not None, ( + "Data-frame processing failure, likely due to a internal bug. " + "Please report this to " + "https://github.com/plotly/plotly.py/issues/new and we will try to " + "replicate and fix it." + ) + if field_name not in array_attrables: + args[field_name] = str(col_name) + elif isinstance(args[field_name], dict): + pass + else: + args[field_name][i] = str(col_name) + if field_name != "wide_variable": + wide_id_vars.add(str(col_name)) + + length = len(df_output[next(iter(df_output))]) if len(df_output) else 0 + + if native_namespace is None: + try: + import pandas as pd + + native_namespace = pd + except ImportError: + msg = "Pandas installation is required if no dataframe is provided." + raise NotImplementedError(msg) + + if ranges: + import numpy as np + + range_series = nw.new_series( + name="__placeholder__", + values=np.arange(length), + native_namespace=native_namespace, + ) + df_output.update( + {col_name: range_series.alias(col_name) for col_name in ranges} + ) + + df_output.update( + { + # constant is single value. repeat by len to avoid creating NaN on concatenating + col_name: nw.new_series( + name=col_name, + values=[constants[col_name]] * length, + native_namespace=native_namespace, + ) + for col_name in constants + } + ) + + if df_output: + df_output = nw.from_dict(df_output) + else: + try: + import pandas as pd + except ImportError: + msg = "Pandas installation is required." + raise NotImplementedError(msg) + df_output = nw.from_native(pd.DataFrame({}), eager_only=True) + return df_output, wide_id_vars + + +def build_dataframe(args, constructor): + """ + Constructs a dataframe and modifies `args` in-place. + + The argument values in `args` can be either strings corresponding to + existing columns of a dataframe, or data arrays (lists, numpy arrays, + pandas columns, series). + + Parameters + ---------- + args : OrderedDict + arguments passed to the px function and subsequently modified + constructor : graph_object trace class + the trace type selected for this figure + """ + + # make copies of all the fields via dict() and list() + for field in args: + if field in array_attrables and args[field] is not None: + if isinstance(args[field], dict): + args[field] = dict(args[field]) + elif field in ["custom_data", "hover_data"] and isinstance( + args[field], str + ): + args[field] = [args[field]] + else: + args[field] = list(args[field]) + + # Cast data_frame argument to DataFrame (it could be a numpy array, dict etc.) + df_provided = args["data_frame"] is not None + + # Flag that indicates if the resulting data_frame after parsing is pandas-like + # (in terms of resulting Narwhals DataFrame). + # True if pandas, modin.pandas or cudf DataFrame/Series instance, or converted from + # PySpark to pandas. + is_pd_like = False + + # Flag that indicates if data_frame needs to be converted to PyArrow. + # True if Ibis, DuckDB, Vaex, or implements __dataframe__ + needs_interchanging = False + + # If data_frame is provided, we parse it into a narwhals DataFrame, while accounting + # for compatibility with pandas specific paths (e.g. Index/MultiIndex case). + if df_provided: + # data_frame is pandas-like DataFrame (pandas, modin.pandas, cudf) + if nw.dependencies.is_pandas_like_dataframe(args["data_frame"]): + columns = args["data_frame"].columns # This can be multi index + args["data_frame"] = nw.from_native(args["data_frame"], eager_only=True) + is_pd_like = True + + # data_frame is pandas-like Series (pandas, modin.pandas, cudf) + elif nw.dependencies.is_pandas_like_series(args["data_frame"]): + args["data_frame"] = nw.from_native( + args["data_frame"], series_only=True + ).to_frame() + columns = args["data_frame"].columns + is_pd_like = True + + # data_frame is any other DataFrame object natively supported via Narwhals. + # With `pass_through=True`, the original object will be returned if unable to convert + # to a Narwhals DataFrame, making this condition False. + elif isinstance( + data_frame := nw.from_native( + args["data_frame"], eager_or_interchange_only=True, pass_through=True + ), + nw.DataFrame, + ): + args["data_frame"] = data_frame + needs_interchanging = nw.get_level(data_frame) == "interchange" + columns = args["data_frame"].columns + + # data_frame is any other Series object natively supported via Narwhals. + # With `pass_through=True`, the original object will be returned if unable to convert + # to a Narwhals Series, making this condition False. + elif isinstance( + series := nw.from_native( + args["data_frame"], series_only=True, pass_through=True + ), + nw.Series, + ): + args["data_frame"] = series.to_frame() + columns = args["data_frame"].columns + + # data_frame is PySpark: it does not support interchange protocol and it is not + # integrated in Narwhals. We use its native method to convert it to pandas. + elif hasattr(args["data_frame"], "toPandas"): + args["data_frame"] = nw.from_native( + args["data_frame"].toPandas(), eager_only=True + ) + columns = args["data_frame"].columns + is_pd_like = True + + # data_frame is some other object type (e.g. dict, list, ...) + # We try to import pandas, and then try to instantiate a pandas dataframe from + # this such object + else: + try: + import pandas as pd + + try: + args["data_frame"] = nw.from_native( + pd.DataFrame(args["data_frame"]) + ) + columns = args["data_frame"].columns + is_pd_like = True + except Exception: + msg = ( + f"Unable to convert data_frame of type {type(args['data_frame'])} " + "to pandas DataFrame. Please provide a supported dataframe type " + "or a type that can be passed to pd.DataFrame." + ) + + raise NotImplementedError(msg) + except ImportError: + msg = ( + f"Attempting to convert data_frame of type {type(args['data_frame'])} " + "to pandas DataFrame, but Pandas is not installed. " + "Convert it to supported dataframe type or install pandas." + ) + raise NotImplementedError(msg) + + # data_frame is not provided + else: + columns = None + + df_input: nw.DataFrame | None = args["data_frame"] + index = ( + nw.maybe_get_index(df_input) + if df_provided and not needs_interchanging + else None + ) + native_namespace = ( + nw.get_native_namespace(df_input) + if df_provided and not needs_interchanging + else None + ) + + # now we handle special cases like wide-mode or x-xor-y specification + # by rearranging args to tee things up for process_args_into_dataframe to work + no_x = args.get("x") is None + no_y = args.get("y") is None + wide_x = ( + False + if no_x + else _is_col_list(columns, args["x"], is_pd_like, native_namespace) + ) + wide_y = ( + False + if no_y + else _is_col_list(columns, args["y"], is_pd_like, native_namespace) + ) + + wide_mode = False + var_name = None # will likely be "variable" in wide_mode + wide_cross_name = None # will likely be "index" in wide_mode + value_name = None # will likely be "value" in wide_mode + hist2d_types = [go.Histogram2d, go.Histogram2dContour] + hist1d_orientation = constructor == go.Histogram or "ecdfmode" in args + if constructor in cartesians: + if wide_x and wide_y: + raise ValueError( + "Cannot accept list of column references or list of columns for both `x` and `y`." + ) + if df_provided and no_x and no_y: + wide_mode = True + if is_pd_like and isinstance(columns, native_namespace.MultiIndex): + raise TypeError( + f"Data frame columns is a {native_namespace.__name__} MultiIndex. " + f"{native_namespace.__name__} MultiIndex is not supported by plotly " + "express at the moment." + ) + args["wide_variable"] = list(columns) + if is_pd_like and isinstance(columns, native_namespace.Index): + var_name = columns.name + else: + var_name = None + if var_name in [None, "value", "index"] or var_name in columns: + var_name = "variable" + if constructor == go.Funnel: + wide_orientation = args.get("orientation") or "h" + else: + wide_orientation = args.get("orientation") or "v" + args["orientation"] = wide_orientation + args["wide_cross"] = None + elif wide_x != wide_y: + wide_mode = True + args["wide_variable"] = args["y"] if wide_y else args["x"] + if df_provided and is_pd_like and args["wide_variable"] is columns: + var_name = columns.name + if is_pd_like and isinstance(args["wide_variable"], native_namespace.Index): + args["wide_variable"] = list(args["wide_variable"]) + if var_name in [None, "value", "index"] or ( + df_provided and var_name in columns + ): + var_name = "variable" + if hist1d_orientation: + wide_orientation = "v" if wide_x else "h" + else: + wide_orientation = "v" if wide_y else "h" + args["y" if wide_y else "x"] = None + args["wide_cross"] = None + if not no_x and not no_y: + wide_cross_name = "__x__" if wide_y else "__y__" + + if wide_mode: + value_name = _escape_col_name(columns, "value", []) + var_name = _escape_col_name(columns, var_name, []) + + # If the data_frame has interchange-only support levelin Narwhals, then we need to + # convert it to a full support level backend. + # Hence we convert requires Interchange to PyArrow. + if needs_interchanging: + if wide_mode: + args["data_frame"] = nw.from_native( + args["data_frame"].to_arrow(), eager_only=True + ) + else: + # Save precious resources by only interchanging columns that are + # actually going to be plotted. This is tricky to do in the general case, + # because Plotly allows calls like `px.line(df, x='x', y=['y1', df['y1']])`, + # but interchange-only objects (e.g. DuckDB) don't typically have a concept + # of self-standing Series. It's more important to perform project pushdown + # here seeing as we're materialising to an (eager) PyArrow table. + necessary_columns = { + i for i in args.values() if isinstance(i, str) and i in columns + } + for field in args: + if args[field] is not None and field in array_attrables: + necessary_columns.update(i for i in args[field] if i in columns) + columns = list(necessary_columns) + args["data_frame"] = nw.from_native( + args["data_frame"].select(columns).to_arrow(), eager_only=True + ) + import pyarrow as pa + + native_namespace = pa + missing_bar_dim = None + if ( + constructor in [go.Scatter, go.Bar, go.Funnel] + hist2d_types + and not hist1d_orientation + ): + if not wide_mode and (no_x != no_y): + for ax in ["x", "y"]: + if args.get(ax) is None: + args[ax] = ( + index + if index is not None + else Range( + label=_escape_col_name(columns, ax, [var_name, value_name]) + ) + ) + if constructor == go.Bar: + missing_bar_dim = ax + else: + if args["orientation"] is None: + args["orientation"] = "v" if ax == "x" else "h" + if wide_mode and wide_cross_name is None: + if no_x != no_y and args["orientation"] is None: + args["orientation"] = "v" if no_x else "h" + if df_provided and is_pd_like and index is not None: + if isinstance(index, native_namespace.MultiIndex): + raise TypeError( + f"Data frame index is a {native_namespace.__name__} MultiIndex. " + f"{native_namespace.__name__} MultiIndex is not supported by " + "plotly express at the moment." + ) + args["wide_cross"] = index + else: + args["wide_cross"] = Range( + label=_escape_col_name(columns, "index", [var_name, value_name]) + ) + + no_color = False + if isinstance(args.get("color"), str) and args["color"] == NO_COLOR: + no_color = True + args["color"] = None + # now that things have been prepped, we do the systematic rewriting of `args` + + df_output, wide_id_vars = process_args_into_dataframe( + args, + wide_mode, + var_name, + value_name, + is_pd_like, + native_namespace, + ) + df_output: nw.DataFrame + # now that `df_output` exists and `args` contains only references, we complete + # the special-case and wide-mode handling by further rewriting args and/or mutating + # df_output + + count_name = _escape_col_name(df_output.columns, "count", [var_name, value_name]) + if not wide_mode and missing_bar_dim and constructor == go.Bar: + # now that we've populated df_output, we check to see if the non-missing + # dimension is categorical: if so, then setting the missing dimension to a + # constant 1 is a less-insane thing to do than setting it to the index by + # default and we let the normal auto-orientation-code do its thing later + other_dim = "x" if missing_bar_dim == "y" else "y" + if not _is_continuous(df_output, args[other_dim]): + args[missing_bar_dim] = count_name + df_output = df_output.with_columns(nw.lit(1).alias(count_name)) + else: + # on the other hand, if the non-missing dimension is continuous, then we + # can use this information to override the normal auto-orientation code + if args["orientation"] is None: + args["orientation"] = "v" if missing_bar_dim == "x" else "h" + + if constructor in hist2d_types: + del args["orientation"] + + if wide_mode: + # at this point, `df_output` is semi-long/semi-wide, but we know which columns + # are which, so we melt it and reassign `args` to refer to the newly-tidy + # columns, keeping track of various names and manglings set up above + wide_value_vars = [c for c in args["wide_variable"] if c not in wide_id_vars] + del args["wide_variable"] + if wide_cross_name == "__x__": + wide_cross_name = args["x"] + elif wide_cross_name == "__y__": + wide_cross_name = args["y"] + else: + wide_cross_name = args["wide_cross"] + del args["wide_cross"] + dtype = None + for v in wide_value_vars: + v_dtype = df_output.get_column(v).dtype + v_dtype = "number" if v_dtype.is_numeric() else str(v_dtype) + if dtype is None: + dtype = v_dtype + elif dtype != v_dtype: + raise ValueError( + "Plotly Express cannot process wide-form data with columns of different type." + ) + df_output = df_output.unpivot( + index=wide_id_vars, + on=wide_value_vars, + variable_name=var_name, + value_name=value_name, + ) + assert len(df_output.columns) == len(set(df_output.columns)), ( + "Wide-mode name-inference failure, likely due to a internal bug. " + "Please report this to " + "https://github.com/plotly/plotly.py/issues/new and we will try to " + "replicate and fix it." + ) + df_output = df_output.with_columns(nw.col(var_name).cast(nw.String)) + orient_v = wide_orientation == "v" + + if hist1d_orientation: + args["x" if orient_v else "y"] = value_name + args["y" if orient_v else "x"] = wide_cross_name + args["color"] = args["color"] or var_name + elif constructor in [go.Scatter, go.Funnel] + hist2d_types: + args["x" if orient_v else "y"] = wide_cross_name + args["y" if orient_v else "x"] = value_name + if constructor != go.Histogram2d: + args["color"] = args["color"] or var_name + if "line_group" in args: + args["line_group"] = args["line_group"] or var_name + elif constructor == go.Bar: + if _is_continuous(df_output, value_name): + args["x" if orient_v else "y"] = wide_cross_name + args["y" if orient_v else "x"] = value_name + args["color"] = args["color"] or var_name + else: + args["x" if orient_v else "y"] = value_name + args["y" if orient_v else "x"] = count_name + df_output = df_output.with_columns(nw.lit(1).alias(count_name)) + args["color"] = args["color"] or var_name + elif constructor in [go.Violin, go.Box]: + args["x" if orient_v else "y"] = wide_cross_name or var_name + args["y" if orient_v else "x"] = value_name + + if hist1d_orientation and constructor == go.Scatter: + if args["x"] is not None and args["y"] is not None: + args["histfunc"] = "sum" + elif args["x"] is None: + args["histfunc"] = None + args["orientation"] = "h" + args["x"] = count_name + df_output = df_output.with_columns(nw.lit(1).alias(count_name)) + else: + args["histfunc"] = None + args["orientation"] = "v" + args["y"] = count_name + df_output = df_output.with_columns(nw.lit(1).alias(count_name)) + + if no_color: + args["color"] = None + args["data_frame"] = df_output + return args + + +def _check_dataframe_all_leaves(df: nw.DataFrame) -> None: + cols = df.columns + df_sorted = df.sort(by=cols, descending=False, nulls_last=True) + null_mask = df_sorted.select(nw.all().is_null()) + df_sorted = df_sorted.select(nw.all().cast(nw.String())) + null_indices_mask = null_mask.select( + null_mask=nw.any_horizontal(nw.all()) + ).get_column("null_mask") + + null_mask_filtered = null_mask.filter(null_indices_mask) + if not null_mask_filtered.is_empty(): + for col_idx in range(1, null_mask_filtered.shape[1]): + # For each row, if a True value is encountered, then check that + # all values in subsequent columns are also True + null_entries_with_non_null_children = ( + ~null_mask_filtered[:, col_idx] & null_mask_filtered[:, col_idx - 1] + ) + if nw.to_py_scalar(null_entries_with_non_null_children.any()): + row_idx = null_entries_with_non_null_children.to_list().index(True) + raise ValueError( + "None entries cannot have not-None children", + df_sorted.row(row_idx), + ) + + fill_series = nw.new_series( + name="fill_value", + values=[""] * len(df_sorted), + dtype=nw.String(), + native_namespace=nw.get_native_namespace(df_sorted), + ) + df_sorted = df_sorted.with_columns( + **{ + c: df_sorted.get_column(c).zip_with(~null_mask.get_column(c), fill_series) + for c in cols + } + ) + + # Conversion to list is due to python native vs pyarrow scalars + row_strings = ( + df_sorted.select( + row_strings=nw.concat_str(cols, separator="", ignore_nulls=False) + ) + .get_column("row_strings") + .to_list() + ) + + null_indices = set(null_indices_mask.arg_true().to_list()) + for i, (current_row, next_row) in enumerate( + zip(row_strings[:-1], row_strings[1:]), start=1 + ): + if (next_row in current_row) and (i in null_indices): + raise ValueError( + "Non-leaves rows are not permitted in the dataframe \n", + df_sorted.row(i), + "is not a leaf.", + ) + + +def process_dataframe_hierarchy(args): + """ + Build dataframe for sunburst, treemap, or icicle when the path argument is provided. + """ + df: nw.DataFrame = args["data_frame"] + path = args["path"][::-1] + _check_dataframe_all_leaves(df[path[::-1]]) + discrete_color = not _is_continuous(df, args["color"]) if args["color"] else False + + df = df.lazy() + + new_path = [col_name + "_path_copy" for col_name in path] + df = df.with_columns( + nw.col(col_name).alias(new_col_name) + for new_col_name, col_name in zip(new_path, path) + ) + path = new_path + # ------------ Define aggregation functions -------------------------------- + agg_f = {} + if args["values"]: + try: + df = df.with_columns(nw.col(args["values"]).cast(nw.Float64())) + + except Exception: # pandas, Polars and pyarrow exception types are different + raise ValueError( + "Column `%s` of `df` could not be converted to a numerical data type." + % args["values"] + ) + + if args["color"] and args["color"] == args["values"]: + new_value_col_name = args["values"] + "_sum" + df = df.with_columns(nw.col(args["values"]).alias(new_value_col_name)) + args["values"] = new_value_col_name + count_colname = args["values"] + else: + # we need a count column for the first groupby and the weighted mean of color + # trick to be sure the col name is unused: take the sum of existing names + columns = df.collect_schema().names() + count_colname = ( + "count" if "count" not in columns else "".join([str(el) for el in columns]) + ) + # we can modify df because it's a copy of the px argument + df = df.with_columns(nw.lit(1).alias(count_colname)) + args["values"] = count_colname + + # Since count_colname is always in agg_f, it can be used later to normalize color + # in the continuous case after some gymnastic + agg_f[count_colname] = nw.sum(count_colname) + + discrete_aggs = [] + continuous_aggs = [] + + n_unique_token = _generate_temporary_column_name( + n_bytes=16, columns=df.collect_schema().names() + ) + + # In theory, for discrete columns aggregation, we should have a way to do + # `.agg(nw.col(x).unique())` in group_by and successively unpack/parse it as: + # ``` + # (nw.when(nw.col(x).list.len()==1) + # .then(nw.col(x).list.first()) + # .otherwise(nw.lit("(?)")) + # ) + # ``` + # which replicates the original pandas only codebase: + # ``` + # def discrete_agg(x): + # uniques = x.unique() + # return uniques[0] if len(uniques) == 1 else "(?)" + # + # df.groupby(path[i:]).agg(...) + # ``` + # However this is not possible, therefore the following workaround is provided. + # We make two aggregations for the same column: + # - take the max value + # - take the number of unique values + # Finally, after the group by statement, it is unpacked via: + # ``` + # (nw.when(nw.col(col_n_unique) == 1) + # .then(nw.col(col_max_value)) # which is the unique value + # .otherwise(nw.lit("(?)")) + # ) + # ``` + + if args["color"]: + if discrete_color: + discrete_aggs.append(args["color"]) + agg_f[args["color"]] = nw.col(args["color"]).max() + agg_f[f"{args['color']}{n_unique_token}"] = ( + nw.col(args["color"]) + .n_unique() + .alias(f"{args['color']}{n_unique_token}") + ) + else: + # This first needs to be multiplied by `count_colname` + continuous_aggs.append(args["color"]) + + agg_f[args["color"]] = nw.sum(args["color"]) + + # Other columns (for color, hover_data, custom_data etc.) + cols = list(set(df.collect_schema().names()).difference(path)) + df = df.with_columns(nw.col(c).cast(nw.String()) for c in cols if c not in agg_f) + + for col in cols: # for hover_data, custom_data etc. + if col not in agg_f: + # Similar trick as above + discrete_aggs.append(col) + agg_f[col] = nw.col(col).max() + agg_f[f"{col}{n_unique_token}"] = ( + nw.col(col).n_unique().alias(f"{col}{n_unique_token}") + ) + # Avoid collisions with reserved names - columns in the path have been copied already + cols = list(set(cols) - set(["labels", "parent", "id"])) + # ---------------------------------------------------------------------------- + all_trees = [] + + if args["color"] and not discrete_color: + df = df.with_columns( + (nw.col(args["color"]) * nw.col(count_colname)).alias(args["color"]) + ) + + def post_agg(dframe: nw.LazyFrame, continuous_aggs, discrete_aggs) -> nw.LazyFrame: + """ + - continuous_aggs is either [] or [args["color"]] + - discrete_aggs is either [args["color"], ] or [] + """ + return dframe.with_columns( + *[nw.col(col) / nw.col(count_colname) for col in continuous_aggs], + *[ + ( + nw.when(nw.col(f"{col}{n_unique_token}") == 1) + .then(nw.col(col)) + .otherwise(nw.lit("(?)")) + .alias(col) + ) + for col in discrete_aggs + ], + ).drop([f"{col}{n_unique_token}" for col in discrete_aggs]) + + for i, level in enumerate(path): + dfg = ( + df.group_by(path[i:], drop_null_keys=True) + .agg(**agg_f) + .pipe(post_agg, continuous_aggs, discrete_aggs) + ) + + # Path label massaging + df_tree = dfg.with_columns( + *cols, + labels=nw.col(level).cast(nw.String()), + parent=nw.lit(""), + id=nw.col(level).cast(nw.String()), + ) + if i < len(path) - 1: + _concat_str_token = _generate_temporary_column_name( + n_bytes=16, columns=[*cols, "labels", "parent", "id"] + ) + df_tree = ( + df_tree.with_columns( + nw.concat_str( + [ + nw.col(path[j]).cast(nw.String()) + for j in range(len(path) - 1, i, -1) + ], + separator="/", + ).alias(_concat_str_token) + ) + .with_columns( + parent=nw.concat_str( + [nw.col(_concat_str_token), nw.col("parent")], separator="/" + ), + id=nw.concat_str( + [nw.col(_concat_str_token), nw.col("id")], separator="/" + ), + ) + .drop(_concat_str_token) + ) + + # strip "/" if at the end of the string, equivalent to `.str.rstrip` + df_tree = df_tree.with_columns( + parent=nw.col("parent").str.replace("/?$", "").str.replace("^/?", "") + ) + + all_trees.append(df_tree.select(*["labels", "parent", "id", *cols])) + + df_all_trees = nw.maybe_reset_index(nw.concat(all_trees, how="vertical").collect()) + + # we want to make sure than (?) is the first color of the sequence + if args["color"] and discrete_color: + sort_col_name = "sort_color_if_discrete_color" + while sort_col_name in df_all_trees.columns: + sort_col_name += "0" + df_all_trees = df_all_trees.with_columns( + nw.col(args["color"]).cast(nw.String()).alias(sort_col_name) + ).sort(by=sort_col_name, nulls_last=True) + + # Now modify arguments + args["data_frame"] = df_all_trees + args["path"] = None + args["ids"] = "id" + args["names"] = "labels" + args["parents"] = "parent" + if args["color"]: + if not args["hover_data"]: + args["hover_data"] = [args["color"]] + elif isinstance(args["hover_data"], dict): + if not args["hover_data"].get(args["color"]): + args["hover_data"][args["color"]] = (True, None) + else: + args["hover_data"].append(args["color"]) + return args + + +def process_dataframe_timeline(args): + """ + Massage input for bar traces for px.timeline() + """ + args["is_timeline"] = True + if args["x_start"] is None or args["x_end"] is None: + raise ValueError("Both x_start and x_end are required") + + df: nw.DataFrame = args["data_frame"] + schema = df.schema + to_convert_to_datetime = [ + col + for col in [args["x_start"], args["x_end"]] + if schema[col] != nw.Datetime and schema[col] != nw.Date + ] + + if to_convert_to_datetime: + try: + df = df.with_columns(nw.col(to_convert_to_datetime).str.to_datetime()) + except Exception as exc: + raise TypeError( + "Both x_start and x_end must refer to data convertible to datetimes." + ) from exc + + # note that we are not adding any columns to the data frame here, so no risk of overwrite + args["data_frame"] = df.with_columns( + (nw.col(args["x_end"]) - nw.col(args["x_start"])) + .dt.total_milliseconds() + .alias(args["x_end"]) + ) + args["x"] = args["x_end"] + args["base"] = args["x_start"] + del args["x_start"], args["x_end"] + return args + + +def process_dataframe_pie(args, trace_patch): + import numpy as np + + names = args.get("names") + if names is None: + return args, trace_patch + order_in = args["category_orders"].get(names, {}).copy() + if not order_in: + return args, trace_patch + df: nw.DataFrame = args["data_frame"] + trace_patch["sort"] = False + trace_patch["direction"] = "clockwise" + uniques = df.get_column(names).unique(maintain_order=True).to_list() + order = [x for x in OrderedDict.fromkeys(list(order_in) + uniques) if x in uniques] + + # Sort args['data_frame'] by column `names` according to order `order`. + token = nw.generate_temporary_column_name(8, df.columns) + args["data_frame"] = ( + df.with_columns( + nw.col(names) + .replace_strict(order, np.arange(len(order)), return_dtype=nw.UInt32) + .alias(token) + ) + .sort(token) + .drop(token) + ) + return args, trace_patch + + +def infer_config(args, constructor, trace_patch, layout_patch): + attrs = [k for k in direct_attrables + array_attrables if k in args] + grouped_attrs = [] + df: nw.DataFrame = args["data_frame"] + + # Compute sizeref + sizeref = 0 + if "size" in args and args["size"]: + sizeref = ( + nw.to_py_scalar(df.get_column(args["size"]).max()) / args["size_max"] ** 2 + ) + + # Compute color attributes and grouping attributes + if "color" in args: + if "color_continuous_scale" in args: + if "color_discrete_sequence" not in args: + attrs.append("color") + else: + if args["color"] and _is_continuous(df, args["color"]): + attrs.append("color") + args["color_is_continuous"] = True + elif constructor in [go.Sunburst, go.Treemap, go.Icicle]: + attrs.append("color") + args["color_is_continuous"] = False + else: + grouped_attrs.append("marker.color") + elif "line_group" in args or constructor == go.Histogram2dContour: + grouped_attrs.append("line.color") + elif constructor in [go.Pie, go.Funnelarea]: + attrs.append("color") + if args["color"]: + if args["hover_data"] is None: + args["hover_data"] = [] + args["hover_data"].append(args["color"]) + else: + grouped_attrs.append("marker.color") + + show_colorbar = bool( + "color" in attrs + and args["color"] + and constructor not in [go.Pie, go.Funnelarea] + and ( + constructor not in [go.Treemap, go.Sunburst, go.Icicle] + or args.get("color_is_continuous") + ) + ) + else: + show_colorbar = False + + if "line_dash" in args: + grouped_attrs.append("line.dash") + + if "symbol" in args: + grouped_attrs.append("marker.symbol") + + if "pattern_shape" in args: + if constructor in [go.Scatter]: + grouped_attrs.append("fillpattern.shape") + else: + grouped_attrs.append("marker.pattern.shape") + + if "orientation" in args: + has_x = args["x"] is not None + has_y = args["y"] is not None + if args["orientation"] is None: + if constructor in [go.Histogram, go.Scatter]: + if has_y and not has_x: + args["orientation"] = "h" + elif constructor in [go.Violin, go.Box, go.Bar, go.Funnel]: + if has_x and not has_y: + args["orientation"] = "h" + + if args["orientation"] is None and has_x and has_y: + x_is_continuous = _is_continuous(df, args["x"]) + y_is_continuous = _is_continuous(df, args["y"]) + if x_is_continuous and not y_is_continuous: + args["orientation"] = "h" + if y_is_continuous and not x_is_continuous: + args["orientation"] = "v" + + if args["orientation"] is None: + args["orientation"] = "v" + + if constructor == go.Histogram: + if has_x and has_y and args["histfunc"] is None: + args["histfunc"] = trace_patch["histfunc"] = "sum" + + orientation = args["orientation"] + nbins = args["nbins"] + trace_patch["nbinsx"] = nbins if orientation == "v" else None + trace_patch["nbinsy"] = None if orientation == "v" else nbins + trace_patch["bingroup"] = "x" if orientation == "v" else "y" + trace_patch["orientation"] = args["orientation"] + + if constructor in [go.Violin, go.Box]: + mode = "boxmode" if constructor == go.Box else "violinmode" + if layout_patch[mode] is None and args["color"] is not None: + if args["y"] == args["color"] and args["orientation"] == "h": + layout_patch[mode] = "overlay" + elif args["x"] == args["color"] and args["orientation"] == "v": + layout_patch[mode] = "overlay" + if layout_patch[mode] is None: + layout_patch[mode] = "group" + + if ( + constructor == go.Histogram2d + and args["z"] is not None + and args["histfunc"] is None + ): + args["histfunc"] = trace_patch["histfunc"] = "sum" + + if args.get("text_auto", False) is not False: + if constructor in [go.Histogram2d, go.Histogram2dContour]: + letter = "z" + elif constructor == go.Bar: + letter = "y" if args["orientation"] == "v" else "x" + else: + letter = "value" + if args["text_auto"] is True: + trace_patch["texttemplate"] = "%{" + letter + "}" + else: + trace_patch["texttemplate"] = "%{" + letter + ":" + args["text_auto"] + "}" + + if constructor in [go.Histogram2d, go.Densitymap, go.Densitymapbox]: + show_colorbar = True + trace_patch["coloraxis"] = "coloraxis1" + + if "opacity" in args: + if args["opacity"] is None: + if "barmode" in args and args["barmode"] == "overlay": + trace_patch["marker"] = dict(opacity=0.5) + elif constructor in [ + go.Densitymap, + go.Densitymapbox, + go.Pie, + go.Funnel, + go.Funnelarea, + ]: + trace_patch["opacity"] = args["opacity"] + else: + trace_patch["marker"] = dict(opacity=args["opacity"]) + if ( + "line_group" in args or "line_dash" in args + ): # px.line, px.line_*, px.area, px.ecdf + modes = set() + if args.get("lines", True): + modes.add("lines") + if args.get("text") or args.get("symbol") or args.get("markers"): + modes.add("markers") + if args.get("text"): + modes.add("text") + if len(modes) == 0: + modes.add("lines") + trace_patch["mode"] = "+".join(sorted(modes)) + elif constructor != go.Splom and ( + "symbol" in args or constructor in [go.Scattermap, go.Scattermapbox] + ): + trace_patch["mode"] = "markers" + ("+text" if args["text"] else "") + + if "line_shape" in args: + trace_patch["line"] = dict(shape=args["line_shape"]) + elif "ecdfmode" in args: + trace_patch["line"] = dict( + shape="vh" if args["ecdfmode"] == "reversed" else "hv" + ) + + if "geojson" in args: + trace_patch["featureidkey"] = args["featureidkey"] + trace_patch["geojson"] = ( + args["geojson"] + if not hasattr(args["geojson"], "__geo_interface__") # for geopandas + else args["geojson"].__geo_interface__ + ) + + # Compute marginal attribute: copy to appropriate marginal_* + if "marginal" in args: + position = "marginal_x" if args["orientation"] == "v" else "marginal_y" + other_position = "marginal_x" if args["orientation"] == "h" else "marginal_y" + args[position] = args["marginal"] + args[other_position] = None + + # Ignore facet rows and columns when data frame is empty so as to prevent nrows/ncols equaling 0 + if df.is_empty(): + args["facet_row"] = args["facet_col"] = None + + # If both marginals and faceting are specified, faceting wins + if args.get("facet_col") is not None and args.get("marginal_y") is not None: + args["marginal_y"] = None + + if args.get("facet_row") is not None and args.get("marginal_x") is not None: + args["marginal_x"] = None + + # facet_col_wrap only works if no marginals or row faceting is used + if ( + args.get("marginal_x") is not None + or args.get("marginal_y") is not None + or args.get("facet_row") is not None + ): + args["facet_col_wrap"] = 0 + + if "trendline" in args and args["trendline"] is not None: + if args["trendline"] not in trendline_functions: + raise ValueError( + "Value '%s' for `trendline` must be one of %s" + % (args["trendline"], trendline_functions.keys()) + ) + + if "trendline_options" in args and args["trendline_options"] is None: + args["trendline_options"] = dict() + + if "ecdfnorm" in args: + if args.get("ecdfnorm", None) not in [None, "percent", "probability"]: + raise ValueError( + "`ecdfnorm` must be one of None, 'percent' or 'probability'. " + + "'%s' was provided." % args["ecdfnorm"] + ) + args["histnorm"] = args["ecdfnorm"] + + # Compute applicable grouping attributes + grouped_attrs.extend([k for k in group_attrables if k in args]) + + # Create grouped mappings + grouped_mappings = [make_mapping(args, a) for a in grouped_attrs] + + # Create trace specs + trace_specs = make_trace_spec(args, constructor, attrs, trace_patch) + return trace_specs, grouped_mappings, sizeref, show_colorbar + + +def get_groups_and_orders(args, grouper): + """ + `orders` is the user-supplied ordering with the remaining data-frame-supplied + ordering appended if the column is used for grouping. It includes anything the user + gave, for any variable, including values not present in the dataset. It's a dict + where the keys are e.g. "x" or "color" + + `groups` is the dicts of groups, ordered by the order above. Its keys are + tuples like [("value1", ""), ("value2", "")] where each tuple contains the name + of a single dimension-group + """ + orders = {} if "category_orders" not in args else args["category_orders"].copy() + df: nw.DataFrame = args["data_frame"] + # figure out orders and what the single group name would be if there were one + single_group_name = [] + unique_cache = dict() + + for i, col in enumerate(grouper): + if col == one_group: + single_group_name.append("") + else: + if col not in unique_cache: + unique_cache[col] = ( + df.get_column(col).unique(maintain_order=True).to_list() + ) + uniques = unique_cache[col] + if len(uniques) == 1: + single_group_name.append(uniques[0]) + if col not in orders: + orders[col] = uniques + else: + orders[col] = list(OrderedDict.fromkeys(list(orders[col]) + uniques)) + + if len(single_group_name) == len(grouper): + # we have a single group, so we can skip all group-by operations! + groups = {tuple(single_group_name): df} + else: + required_grouper = [group for group in orders if group in grouper] + grouped = dict(df.group_by(required_grouper, drop_null_keys=True).__iter__()) + + sorted_group_names = sorted( + grouped.keys(), + key=lambda values: [ + orders[group].index(value) if value in orders[group] else -1 + for group, value in zip(required_grouper, values) + ], + ) + + # calculate the full group_names by inserting "" in the tuple index for one_group groups + full_sorted_group_names = [ + tuple( + [ + ( + "" + if col == one_group + else sub_group_names[required_grouper.index(col)] + ) + for col in grouper + ] + ) + for sub_group_names in sorted_group_names + ] + + groups = { + sf: grouped[s] for sf, s in zip(full_sorted_group_names, sorted_group_names) + } + return groups, orders + + +def make_figure(args, constructor, trace_patch=None, layout_patch=None): + trace_patch = trace_patch or {} + layout_patch = layout_patch or {} + apply_default_cascade(args, constructor=constructor) + + args = build_dataframe(args, constructor) + if constructor in [go.Treemap, go.Sunburst, go.Icicle] and args["path"] is not None: + args = process_dataframe_hierarchy(args) + if constructor in [go.Pie]: + args, trace_patch = process_dataframe_pie(args, trace_patch) + if constructor == "timeline": + constructor = go.Bar + args = process_dataframe_timeline(args) + + # If we have marginal histograms, set barmode to "overlay" + if "histogram" in [args.get("marginal_x"), args.get("marginal_y")]: + layout_patch["barmode"] = "overlay" + + trace_specs, grouped_mappings, sizeref, show_colorbar = infer_config( + args, constructor, trace_patch, layout_patch + ) + grouper = [x.grouper or one_group for x in grouped_mappings] or [one_group] + groups, orders = get_groups_and_orders(args, grouper) + + col_labels = [] + row_labels = [] + nrows = ncols = 1 + for m in grouped_mappings: + if m.grouper not in orders: + m.val_map[""] = m.sequence[0] + else: + sorted_values = orders[m.grouper] + if m.facet == "col": + prefix = get_label(args, args["facet_col"]) + "=" + col_labels = [prefix + str(s) for s in sorted_values] + ncols = len(col_labels) + if m.facet == "row": + prefix = get_label(args, args["facet_row"]) + "=" + row_labels = [prefix + str(s) for s in sorted_values] + nrows = len(row_labels) + for val in sorted_values: + if val not in m.val_map: # always False if it's an IdentityMap + m.val_map[val] = m.sequence[len(m.val_map) % len(m.sequence)] + + subplot_type = _subplot_type_for_trace_type(constructor().type) + + trace_names_by_frame = {} + frames = OrderedDict() + trendline_rows = [] + trace_name_labels = None + facet_col_wrap = args.get("facet_col_wrap", 0) + for group_name, group in groups.items(): + mapping_labels = OrderedDict() + trace_name_labels = OrderedDict() + frame_name = "" + for col, val, m in zip(grouper, group_name, grouped_mappings): + if col != one_group: + key = get_label(args, col) + if not isinstance(m.val_map, IdentityMap): + mapping_labels[key] = str(val) + if m.show_in_trace_name: + trace_name_labels[key] = str(val) + if m.variable == "animation_frame": + frame_name = val + trace_name = ", ".join(trace_name_labels.values()) + if frame_name not in trace_names_by_frame: + trace_names_by_frame[frame_name] = set() + trace_names = trace_names_by_frame[frame_name] + + for trace_spec in trace_specs: + # Create the trace + trace = trace_spec.constructor(name=trace_name) + if trace_spec.constructor not in [ + go.Parcats, + go.Parcoords, + go.Choropleth, + go.Choroplethmap, + go.Choroplethmapbox, + go.Densitymap, + go.Densitymapbox, + go.Histogram2d, + go.Sunburst, + go.Treemap, + go.Icicle, + ]: + trace.update( + legendgroup=trace_name, + showlegend=(trace_name != "" and trace_name not in trace_names), + ) + + # Set 'offsetgroup' only in group barmode (or if no barmode is set) + barmode = layout_patch.get("barmode") + if trace_spec.constructor in [go.Bar, go.Box, go.Violin, go.Histogram] and ( + barmode == "group" or barmode is None + ): + trace.update(alignmentgroup=True, offsetgroup=trace_name) + trace_names.add(trace_name) + + # Init subplot row/col + trace._subplot_row = 1 + trace._subplot_col = 1 + + for i, m in enumerate(grouped_mappings): + val = group_name[i] + try: + m.updater(trace, m.val_map[val]) # covers most cases + except ValueError: + # this catches some odd cases like marginals + if ( + trace_spec != trace_specs[0] + and ( + trace_spec.constructor in [go.Violin, go.Box] + and m.variable in ["symbol", "pattern", "dash"] + ) + or ( + trace_spec.constructor in [go.Histogram] + and m.variable in ["symbol", "dash"] + ) + ): + pass + elif ( + trace_spec != trace_specs[0] + and trace_spec.constructor in [go.Histogram] + and m.variable == "color" + ): + trace.update(marker=dict(color=m.val_map[val])) + elif ( + trace_spec.constructor + in [go.Choropleth, go.Choroplethmap, go.Choroplethmapbox] + and m.variable == "color" + ): + trace.update( + z=[1] * len(group), + colorscale=[m.val_map[val]] * 2, + showscale=False, + showlegend=True, + ) + else: + raise + + # Find row for trace, handling facet_row and marginal_x + if m.facet == "row": + row = m.val_map[val] + else: + if ( + args.get("marginal_x") is not None # there is a marginal + and trace_spec.marginal != "x" # and we're not it + ): + row = 2 + else: + row = 1 + + # Find col for trace, handling facet_col and marginal_y + if m.facet == "col": + col = m.val_map[val] + if facet_col_wrap: # assumes no facet_row, no marginals + row = 1 + ((col - 1) // facet_col_wrap) + col = 1 + ((col - 1) % facet_col_wrap) + else: + if trace_spec.marginal == "y": + col = 2 + else: + col = 1 + + if row > 1: + trace._subplot_row = row + + if col > 1: + trace._subplot_col = col + if ( + trace_specs[0].constructor == go.Histogram2dContour + and trace_spec.constructor == go.Box + and trace.line.color + ): + trace.update(marker=dict(color=trace.line.color)) + + if "ecdfmode" in args: + base = args["x"] if args["orientation"] == "v" else args["y"] + var = args["x"] if args["orientation"] == "h" else args["y"] + ascending = args.get("ecdfmode", "standard") != "reversed" + group = group.sort(by=base, descending=not ascending, nulls_last=True) + group_sum = group.get_column( + var + ).sum() # compute here before next line mutates + group = group.with_columns(nw.col(var).cum_sum().alias(var)) + if not ascending: + group = group.sort(by=base, descending=False, nulls_last=True) + + if args.get("ecdfmode", "standard") == "complementary": + group = group.with_columns((group_sum - nw.col(var)).alias(var)) + + if args["ecdfnorm"] == "probability": + group = group.with_columns(nw.col(var) / group_sum) + elif args["ecdfnorm"] == "percent": + group = group.with_columns((nw.col(var) / group_sum) * 100.0) + + patch, fit_results = make_trace_kwargs( + args, trace_spec, group, mapping_labels.copy(), sizeref + ) + trace.update(patch) + if fit_results is not None: + trendline_rows.append(mapping_labels.copy()) + trendline_rows[-1]["px_fit_results"] = fit_results + if frame_name not in frames: + frames[frame_name] = dict(data=[], name=frame_name) + frames[frame_name]["data"].append(trace) + frame_list = [f for f in frames.values()] + if len(frame_list) > 1: + frame_list = sorted( + frame_list, key=lambda f: orders[args["animation_frame"]].index(f["name"]) + ) + + if show_colorbar: + colorvar = ( + "z" + if constructor in [go.Histogram2d, go.Densitymap, go.Densitymapbox] + else "color" + ) + range_color = args["range_color"] or [None, None] + + colorscale_validator = ColorscaleValidator("colorscale", "make_figure") + layout_patch["coloraxis1"] = dict( + colorscale=colorscale_validator.validate_coerce( + args["color_continuous_scale"] + ), + cmid=args["color_continuous_midpoint"], + cmin=range_color[0], + cmax=range_color[1], + colorbar=dict( + title_text=get_decorated_label(args, args[colorvar], colorvar) + ), + ) + for v in ["height", "width"]: + if args[v]: + layout_patch[v] = args[v] + layout_patch["legend"] = dict(tracegroupgap=0) + if trace_name_labels: + layout_patch["legend"]["title_text"] = ", ".join(trace_name_labels) + if args["title"]: + layout_patch["title_text"] = args["title"] + elif args["template"].layout.margin.t is None: + layout_patch["margin"] = {"t": 60} + if args["subtitle"]: + layout_patch["title_subtitle_text"] = args["subtitle"] + if ( + "size" in args + and args["size"] + and args["template"].layout.legend.itemsizing is None + ): + layout_patch["legend"]["itemsizing"] = "constant" + + if facet_col_wrap: + nrows = math.ceil(ncols / facet_col_wrap) + ncols = min(ncols, facet_col_wrap) + + if args.get("marginal_x") is not None: + nrows += 1 + + if args.get("marginal_y") is not None: + ncols += 1 + + fig = init_figure( + args, subplot_type, frame_list, nrows, ncols, col_labels, row_labels + ) + + # Position traces in subplots + for frame in frame_list: + for trace in frame["data"]: + if isinstance(trace, go.Splom): + # Special case that is not compatible with make_subplots + continue + + _set_trace_grid_reference( + trace, + fig.layout, + fig._grid_ref, + nrows - trace._subplot_row + 1, + trace._subplot_col, + ) + + # Add traces, layout and frames to figure + fig.add_traces(frame_list[0]["data"] if len(frame_list) > 0 else []) + fig.update_layout(layout_patch) + if "template" in args and args["template"] is not None: + fig.update_layout(template=args["template"], overwrite=True) + for f in frame_list: + f["name"] = str(f["name"]) + fig.frames = frame_list if len(frames) > 1 else [] + + if args.get("trendline") and args.get("trendline_scope", "trace") == "overall": + trendline_spec = make_trendline_spec(args, constructor) + trendline_trace = trendline_spec.constructor( + name="Overall Trendline", legendgroup="Overall Trendline", showlegend=False + ) + if "line" not in trendline_spec.trace_patch: # no color override + for m in grouped_mappings: + if m.variable == "color": + next_color = m.sequence[len(m.val_map) % len(m.sequence)] + trendline_spec.trace_patch["line"] = dict(color=next_color) + patch, fit_results = make_trace_kwargs( + args, trendline_spec, args["data_frame"], {}, sizeref + ) + trendline_trace.update(patch) + fig.add_trace( + trendline_trace, row="all", col="all", exclude_empty_subplots=True + ) + fig.update_traces(selector=-1, showlegend=True) + if fit_results is not None: + trendline_rows.append(dict(px_fit_results=fit_results)) + + if trendline_rows: + try: + import pandas as pd + + fig._px_trendlines = pd.DataFrame(trendline_rows) + except ImportError: + msg = "Trendlines require pandas to be installed." + raise NotImplementedError(msg) + else: + fig._px_trendlines = [] + + configure_axes(args, constructor, fig, orders) + configure_animation_controls(args, constructor, fig) + return fig + + +def init_figure(args, subplot_type, frame_list, nrows, ncols, col_labels, row_labels): + # Build subplot specs + specs = [[dict(type=subplot_type or "domain")] * ncols for _ in range(nrows)] + + # Default row/column widths uniform + column_widths = [1.0] * ncols + row_heights = [1.0] * nrows + facet_col_wrap = args.get("facet_col_wrap", 0) + + # Build column_widths/row_heights + if subplot_type == "xy": + if args.get("marginal_x") is not None: + if args["marginal_x"] == "histogram" or ("color" in args and args["color"]): + main_size = 0.74 + else: + main_size = 0.84 + + row_heights = [main_size] * (nrows - 1) + [1 - main_size] + vertical_spacing = 0.01 + elif facet_col_wrap: + vertical_spacing = args.get("facet_row_spacing") or 0.07 + else: + vertical_spacing = args.get("facet_row_spacing") or 0.03 + + if args.get("marginal_y") is not None: + if args["marginal_y"] == "histogram" or ("color" in args and args["color"]): + main_size = 0.74 + else: + main_size = 0.84 + + column_widths = [main_size] * (ncols - 1) + [1 - main_size] + horizontal_spacing = 0.005 + else: + horizontal_spacing = args.get("facet_col_spacing") or 0.02 + else: + # Other subplot types: + # 'scene', 'geo', 'polar', 'ternary', 'mapbox', 'domain', None + # + # We can customize subplot spacing per type once we enable faceting + # for all plot types + if facet_col_wrap: + vertical_spacing = args.get("facet_row_spacing") or 0.07 + else: + vertical_spacing = args.get("facet_row_spacing") or 0.03 + horizontal_spacing = args.get("facet_col_spacing") or 0.02 + + if facet_col_wrap: + subplot_labels = [None] * nrows * ncols + while len(col_labels) < nrows * ncols: + col_labels.append(None) + for i in range(nrows): + for j in range(ncols): + subplot_labels[i * ncols + j] = col_labels[(nrows - 1 - i) * ncols + j] + + def _spacing_error_translator(e, direction, facet_arg): + """ + Translates the spacing errors thrown by the underlying make_subplots + routine into one that describes an argument adjustable through px. + """ + if ("%s spacing" % (direction,)) in e.args[0]: + e.args = ( + e.args[0] + + """ +Use the {facet_arg} argument to adjust this spacing.""".format(facet_arg=facet_arg), + ) + raise e + + # Create figure with subplots + try: + fig = make_subplots( + rows=nrows, + cols=ncols, + specs=specs, + shared_xaxes="all", + shared_yaxes="all", + row_titles=[] if facet_col_wrap else list(reversed(row_labels)), + column_titles=[] if facet_col_wrap else col_labels, + subplot_titles=subplot_labels if facet_col_wrap else [], + horizontal_spacing=horizontal_spacing, + vertical_spacing=vertical_spacing, + row_heights=row_heights, + column_widths=column_widths, + start_cell="bottom-left", + ) + except ValueError as e: + _spacing_error_translator(e, "Horizontal", "facet_col_spacing") + _spacing_error_translator(e, "Vertical", "facet_row_spacing") + raise + + # Remove explicit font size of row/col titles so template can take over + for annot in fig.layout.annotations: + annot.update(font=None) + + return fig diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/express/_doc.py b/.venv_haddock/lib/python3.12/site-packages/plotly/express/_doc.py new file mode 100644 index 0000000000000000000000000000000000000000..59faac4c0b3b7c0520a51de972b28cd83911ad58 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/express/_doc.py @@ -0,0 +1,640 @@ +import inspect +from textwrap import TextWrapper + +try: + getfullargspec = inspect.getfullargspec +except AttributeError: # python 2 + getfullargspec = inspect.getargspec + + +colref_type = "str or int or Series or array-like" +colref_desc = "Either a name of a column in `data_frame`, or a pandas Series or array_like object." +colref_list_type = "list of str or int, or Series or array-like" +colref_list_desc = ( + "Either names of columns in `data_frame`, or pandas Series, or array_like objects" +) + +docs = dict( + data_frame=[ + "DataFrame or array-like or dict", + "This argument needs to be passed for column names (and not keyword names) to be used.", + "Array-like and dict are transformed internally to a pandas DataFrame.", + "Optional: if missing, a DataFrame gets constructed under the hood using the other arguments.", + ], + x=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to position marks along the x axis in cartesian coordinates.", + ], + y=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to position marks along the y axis in cartesian coordinates.", + ], + z=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to position marks along the z axis in cartesian coordinates.", + ], + x_start=[ + colref_type, + colref_desc, + "(required)", + "Values from this column or array_like are used to position marks along the x axis in cartesian coordinates.", + ], + x_end=[ + colref_type, + colref_desc, + "(required)", + "Values from this column or array_like are used to position marks along the x axis in cartesian coordinates.", + ], + a=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to position marks along the a axis in ternary coordinates.", + ], + b=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to position marks along the b axis in ternary coordinates.", + ], + c=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to position marks along the c axis in ternary coordinates.", + ], + r=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to position marks along the radial axis in polar coordinates.", + ], + theta=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to position marks along the angular axis in polar coordinates.", + ], + values=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to set values associated to sectors.", + ], + parents=[ + colref_type, + colref_desc, + "Values from this column or array_like are used as parents in sunburst and treemap charts.", + ], + ids=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to set ids of sectors", + ], + path=[ + colref_list_type, + colref_list_desc, + "List of columns names or columns of a rectangular dataframe defining the hierarchy of sectors, from root to leaves.", + "An error is raised if path AND ids or parents is passed", + ], + lat=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to position marks according to latitude on a map.", + ], + lon=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to position marks according to longitude on a map.", + ], + locations=[ + colref_type, + colref_desc, + "Values from this column or array_like are to be interpreted according to `locationmode` and mapped to longitude/latitude.", + ], + base=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to position the base of the bar.", + ], + dimensions=[ + colref_list_type, + colref_list_desc, + "Values from these columns are used for multidimensional visualization.", + ], + dimensions_max_cardinality=[ + "int (default 50)", + "When `dimensions` is `None` and `data_frame` is provided, " + "columns with more than this number of unique values are excluded from the output.", + "Not used when `dimensions` is passed.", + ], + error_x=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to size x-axis error bars.", + "If `error_x_minus` is `None`, error bars will be symmetrical, otherwise `error_x` is used for the positive direction only.", + ], + error_x_minus=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to size x-axis error bars in the negative direction.", + "Ignored if `error_x` is `None`.", + ], + error_y=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to size y-axis error bars.", + "If `error_y_minus` is `None`, error bars will be symmetrical, otherwise `error_y` is used for the positive direction only.", + ], + error_y_minus=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to size y-axis error bars in the negative direction.", + "Ignored if `error_y` is `None`.", + ], + error_z=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to size z-axis error bars.", + "If `error_z_minus` is `None`, error bars will be symmetrical, otherwise `error_z` is used for the positive direction only.", + ], + error_z_minus=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to size z-axis error bars in the negative direction.", + "Ignored if `error_z` is `None`.", + ], + color=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to assign color to marks.", + ], + opacity=["float", "Value between 0 and 1. Sets the opacity for markers."], + line_dash=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to assign dash-patterns to lines.", + ], + line_group=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to group rows of `data_frame` into lines.", + ], + symbol=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to assign symbols to marks.", + ], + pattern_shape=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to assign pattern shapes to marks.", + ], + size=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to assign mark sizes.", + ], + radius=["int (default is 30)", "Sets the radius of influence of each point."], + hover_name=[ + colref_type, + colref_desc, + "Values from this column or array_like appear in bold in the hover tooltip.", + ], + hover_data=[ + "str, or list of str or int, or Series or array-like, or dict", + "Either a name or list of names of columns in `data_frame`, or pandas Series,", + "or array_like objects", + "or a dict with column names as keys, with values True (for default formatting)", + "False (in order to remove this column from hover information),", + "or a formatting string, for example ':.3f' or '|%a'", + "or list-like data to appear in the hover tooltip", + "or tuples with a bool or formatting string as first element,", + "and list-like data to appear in hover as second element", + "Values from these columns appear as extra data in the hover tooltip.", + ], + custom_data=[ + "str, or list of str or int, or Series or array-like", + "Either name or list of names of columns in `data_frame`, or pandas Series, or array_like objects", + "Values from these columns are extra data, to be used in widgets or Dash callbacks for example. This data is not user-visible but is included in events emitted by the figure (lasso selection etc.)", + ], + text=[ + colref_type, + colref_desc, + "Values from this column or array_like appear in the figure as text labels.", + ], + names=[ + colref_type, + colref_desc, + "Values from this column or array_like are used as labels for sectors.", + ], + locationmode=[ + "str", + "One of 'ISO-3', 'USA-states', or 'country names'", + "Determines the set of locations used to match entries in `locations` to regions on the map.", + ], + facet_row=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to assign marks to facetted subplots in the vertical direction.", + ], + facet_col=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to assign marks to facetted subplots in the horizontal direction.", + ], + facet_col_wrap=[ + "int", + "Maximum number of facet columns.", + "Wraps the column variable at this width, so that the column facets span multiple rows.", + "Ignored if 0, and forced to 0 if `facet_row` or a `marginal` is set.", + ], + facet_row_spacing=[ + "float between 0 and 1", + "Spacing between facet rows, in paper units. Default is 0.03 or 0.07 when facet_col_wrap is used.", + ], + facet_col_spacing=[ + "float between 0 and 1", + "Spacing between facet columns, in paper units Default is 0.02.", + ], + animation_frame=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to assign marks to animation frames.", + ], + animation_group=[ + colref_type, + colref_desc, + "Values from this column or array_like are used to provide object-constancy across animation frames: rows with matching `animation_group`s will be treated as if they describe the same object in each frame.", + ], + symbol_sequence=[ + "list of str", + "Strings should define valid plotly.js symbols.", + "When `symbol` is set, values in that column are assigned symbols by cycling through `symbol_sequence` in the order described in `category_orders`, unless the value of `symbol` is a key in `symbol_map`.", + ], + symbol_map=[ + "dict with str keys and str values (default `{}`)", + "String values should define plotly.js symbols", + "Used to override `symbol_sequence` to assign a specific symbols to marks corresponding with specific values.", + "Keys in `symbol_map` should be values in the column denoted by `symbol`.", + "Alternatively, if the values of `symbol` are valid symbol names, the string `'identity'` may be passed to cause them to be used directly.", + ], + line_dash_map=[ + "dict with str keys and str values (default `{}`)", + "Strings values define plotly.js dash-patterns.", + "Used to override `line_dash_sequences` to assign a specific dash-patterns to lines corresponding with specific values.", + "Keys in `line_dash_map` should be values in the column denoted by `line_dash`.", + "Alternatively, if the values of `line_dash` are valid line-dash names, the string `'identity'` may be passed to cause them to be used directly.", + ], + line_dash_sequence=[ + "list of str", + "Strings should define valid plotly.js dash-patterns.", + "When `line_dash` is set, values in that column are assigned dash-patterns by cycling through `line_dash_sequence` in the order described in `category_orders`, unless the value of `line_dash` is a key in `line_dash_map`.", + ], + pattern_shape_map=[ + "dict with str keys and str values (default `{}`)", + "Strings values define plotly.js patterns-shapes.", + "Used to override `pattern_shape_sequences` to assign a specific patterns-shapes to lines corresponding with specific values.", + "Keys in `pattern_shape_map` should be values in the column denoted by `pattern_shape`.", + "Alternatively, if the values of `pattern_shape` are valid patterns-shapes names, the string `'identity'` may be passed to cause them to be used directly.", + ], + pattern_shape_sequence=[ + "list of str", + "Strings should define valid plotly.js patterns-shapes.", + "When `pattern_shape` is set, values in that column are assigned patterns-shapes by cycling through `pattern_shape_sequence` in the order described in `category_orders`, unless the value of `pattern_shape` is a key in `pattern_shape_map`.", + ], + color_discrete_sequence=[ + "list of str", + "Strings should define valid CSS-colors.", + "When `color` is set and the values in the corresponding column are not numeric, values in that column are assigned colors by cycling through `color_discrete_sequence` in the order described in `category_orders`, unless the value of `color` is a key in `color_discrete_map`.", + "Various useful color sequences are available in the `plotly.express.colors` submodules, specifically `plotly.express.colors.qualitative`.", + ], + color_discrete_map=[ + "dict with str keys and str values (default `{}`)", + "String values should define valid CSS-colors", + "Used to override `color_discrete_sequence` to assign a specific colors to marks corresponding with specific values.", + "Keys in `color_discrete_map` should be values in the column denoted by `color`.", + "Alternatively, if the values of `color` are valid colors, the string `'identity'` may be passed to cause them to be used directly.", + ], + color_continuous_scale=[ + "list of str", + "Strings should define valid CSS-colors", + "This list is used to build a continuous color scale when the column denoted by `color` contains numeric data.", + "Various useful color scales are available in the `plotly.express.colors` submodules, specifically `plotly.express.colors.sequential`, `plotly.express.colors.diverging` and `plotly.express.colors.cyclical`.", + ], + color_continuous_midpoint=[ + "number (default `None`)", + "If set, computes the bounds of the continuous color scale to have the desired midpoint.", + "Setting this value is recommended when using `plotly.express.colors.diverging` color scales as the inputs to `color_continuous_scale`.", + ], + size_max=["int (default `20`)", "Set the maximum mark size when using `size`."], + markers=["boolean (default `False`)", "If `True`, markers are shown on lines."], + lines=[ + "boolean (default `True`)", + "If `False`, lines are not drawn (forced to `True` if `markers` is `False`).", + ], + log_x=[ + "boolean (default `False`)", + "If `True`, the x-axis is log-scaled in cartesian coordinates.", + ], + log_y=[ + "boolean (default `False`)", + "If `True`, the y-axis is log-scaled in cartesian coordinates.", + ], + log_z=[ + "boolean (default `False`)", + "If `True`, the z-axis is log-scaled in cartesian coordinates.", + ], + log_r=[ + "boolean (default `False`)", + "If `True`, the radial axis is log-scaled in polar coordinates.", + ], + range_x=[ + "list of two numbers", + "If provided, overrides auto-scaling on the x-axis in cartesian coordinates.", + ], + range_y=[ + "list of two numbers", + "If provided, overrides auto-scaling on the y-axis in cartesian coordinates.", + ], + range_z=[ + "list of two numbers", + "If provided, overrides auto-scaling on the z-axis in cartesian coordinates.", + ], + range_color=[ + "list of two numbers", + "If provided, overrides auto-scaling on the continuous color scale.", + ], + range_r=[ + "list of two numbers", + "If provided, overrides auto-scaling on the radial axis in polar coordinates.", + ], + range_theta=[ + "list of two numbers", + "If provided, overrides auto-scaling on the angular axis in polar coordinates.", + ], + title=["str", "The figure title."], + subtitle=["str", "The figure subtitle."], + template=[ + "str or dict or plotly.graph_objects.layout.Template instance", + "The figure template name (must be a key in plotly.io.templates) or definition.", + ], + width=["int (default `None`)", "The figure width in pixels."], + height=["int (default `None`)", "The figure height in pixels."], + labels=[ + "dict with str keys and str values (default `{}`)", + "By default, column names are used in the figure for axis titles, legend entries and hovers.", + "This parameter allows this to be overridden.", + "The keys of this dict should correspond to column names, and the values should correspond to the desired label to be displayed.", + ], + category_orders=[ + "dict with str keys and list of str values (default `{}`)", + "By default, in Python 3.6+, the order of categorical values in axes, legends and facets depends on the order in which these values are first encountered in `data_frame` (and no order is guaranteed by default in Python below 3.6).", + "This parameter is used to force a specific ordering of values per column.", + "The keys of this dict should correspond to column names, and the values should be lists of strings corresponding to the specific display order desired.", + ], + marginal=[ + "str", + "One of `'rug'`, `'box'`, `'violin'`, or `'histogram'`.", + "If set, a subplot is drawn alongside the main plot, visualizing the distribution.", + ], + marginal_x=[ + "str", + "One of `'rug'`, `'box'`, `'violin'`, or `'histogram'`.", + "If set, a horizontal subplot is drawn above the main plot, visualizing the x-distribution.", + ], + marginal_y=[ + "str", + "One of `'rug'`, `'box'`, `'violin'`, or `'histogram'`.", + "If set, a vertical subplot is drawn to the right of the main plot, visualizing the y-distribution.", + ], + trendline=[ + "str", + "One of `'ols'`, `'lowess'`, `'rolling'`, `'expanding'` or `'ewm'`.", + "If `'ols'`, an Ordinary Least Squares regression line will be drawn for each discrete-color/symbol group.", + "If `'lowess`', a Locally Weighted Scatterplot Smoothing line will be drawn for each discrete-color/symbol group.", + "If `'rolling`', a Rolling (e.g. rolling average, rolling median) line will be drawn for each discrete-color/symbol group.", + "If `'expanding`', an Expanding (e.g. expanding average, expanding sum) line will be drawn for each discrete-color/symbol group.", + "If `'ewm`', an Exponentially Weighted Moment (e.g. exponentially-weighted moving average) line will be drawn for each discrete-color/symbol group.", + "See the docstrings for the functions in `plotly.express.trendline_functions` for more details on these functions and how", + "to configure them with the `trendline_options` argument.", + ], + trendline_options=[ + "dict", + "Options passed as the first argument to the function from `plotly.express.trendline_functions` ", + "named in the `trendline` argument.", + ], + trendline_color_override=[ + "str", + "Valid CSS color.", + "If provided, and if `trendline` is set, all trendlines will be drawn in this color rather than in the same color as the traces from which they draw their inputs.", + ], + trendline_scope=[ + "str (one of `'trace'` or `'overall'`, default `'trace'`)", + "If `'trace'`, then one trendline is drawn per trace (i.e. per color, symbol, facet, animation frame etc) and if `'overall'` then one trendline is computed for the entire dataset, and replicated across all facets.", + ], + render_mode=[ + "str", + "One of `'auto'`, `'svg'` or `'webgl'`, default `'auto'`", + "Controls the browser API used to draw marks.", + "`'svg'` is appropriate for figures of less than 1000 data points, and will allow for fully-vectorized output.", + "`'webgl'` is likely necessary for acceptable performance above 1000 points but rasterizes part of the output. ", + "`'auto'` uses heuristics to choose the mode.", + ], + direction=[ + "str", + "One of '`counterclockwise'` or `'clockwise'`. Default is `'clockwise'`", + "Sets the direction in which increasing values of the angular axis are drawn.", + ], + start_angle=[ + "int (default `90`)", + "Sets start angle for the angular axis, with 0 being due east and 90 being due north.", + ], + histfunc=[ + "str (default `'count'` if no arguments are provided, else `'sum'`)", + "One of `'count'`, `'sum'`, `'avg'`, `'min'`, or `'max'`.", + "Function used to aggregate values for summarization (note: can be normalized with `histnorm`).", + ], + histnorm=[ + "str (default `None`)", + "One of `'percent'`, `'probability'`, `'density'`, or `'probability density'`", + "If `None`, the output of `histfunc` is used as is.", + "If `'probability'`, the output of `histfunc` for a given bin is divided by the sum of the output of `histfunc` for all bins.", + "If `'percent'`, the output of `histfunc` for a given bin is divided by the sum of the output of `histfunc` for all bins and multiplied by 100.", + "If `'density'`, the output of `histfunc` for a given bin is divided by the size of the bin.", + "If `'probability density'`, the output of `histfunc` for a given bin is normalized such that it corresponds to the probability that a random event whose distribution is described by the output of `histfunc` will fall into that bin.", + ], + barnorm=[ + "str (default `None`)", + "One of `'fraction'` or `'percent'`.", + "If `'fraction'`, the value of each bar is divided by the sum of all values at that location coordinate.", + "`'percent'` is the same but multiplied by 100 to show percentages.", + "`None` will stack up all values at each location coordinate.", + ], + groupnorm=[ + "str (default `None`)", + "One of `'fraction'` or `'percent'`.", + "If `'fraction'`, the value of each point is divided by the sum of all values at that location coordinate.", + "`'percent'` is the same but multiplied by 100 to show percentages.", + "`None` will stack up all values at each location coordinate.", + ], + barmode=[ + "str (default `'relative'`)", + "One of `'group'`, `'overlay'` or `'relative'`", + "In `'relative'` mode, bars are stacked above zero for positive values and below zero for negative values.", + "In `'overlay'` mode, bars are drawn on top of one another.", + "In `'group'` mode, bars are placed beside each other.", + ], + boxmode=[ + "str (default `'group'`)", + "One of `'group'` or `'overlay'`", + "In `'overlay'` mode, boxes are on drawn top of one another.", + "In `'group'` mode, boxes are placed beside each other.", + ], + violinmode=[ + "str (default `'group'`)", + "One of `'group'` or `'overlay'`", + "In `'overlay'` mode, violins are on drawn top of one another.", + "In `'group'` mode, violins are placed beside each other.", + ], + stripmode=[ + "str (default `'group'`)", + "One of `'group'` or `'overlay'`", + "In `'overlay'` mode, strips are on drawn top of one another.", + "In `'group'` mode, strips are placed beside each other.", + ], + zoom=["int (default `8`)", "Between 0 and 20.", "Sets map zoom level."], + orientation=[ + "str, one of `'h'` for horizontal or `'v'` for vertical. ", + "(default `'v'` if `x` and `y` are provided and both continuous or both categorical, ", + "otherwise `'v'`(`'h'`) if `x`(`y`) is categorical and `y`(`x`) is continuous, ", + "otherwise `'v'`(`'h'`) if only `x`(`y`) is provided) ", + ], + line_close=[ + "boolean (default `False`)", + "If `True`, an extra line segment is drawn between the first and last point.", + ], + line_shape=[ + "str (default `'linear'`)", + "One of `'linear'`, `'spline'`, `'hv'`, `'vh'`, `'hvh'`, or `'vhv'`", + ], + fitbounds=["str (default `False`).", "One of `False`, `locations` or `geojson`."], + basemap_visible=["bool", "Force the basemap visibility."], + scope=[ + "str (default `'world'`).", + "One of `'world'`, `'usa'`, `'europe'`, `'asia'`, `'africa'`, `'north america'`, or `'south america'`" + "Default is `'world'` unless `projection` is set to `'albers usa'`, which forces `'usa'`.", + ], + projection=[ + "str ", + "One of `'equirectangular'`, `'mercator'`, `'orthographic'`, `'natural earth'`, `'kavrayskiy7'`, `'miller'`, `'robinson'`, `'eckert4'`, `'azimuthal equal area'`, `'azimuthal equidistant'`, `'conic equal area'`, `'conic conformal'`, `'conic equidistant'`, `'gnomonic'`, `'stereographic'`, `'mollweide'`, `'hammer'`, `'transverse mercator'`, `'albers usa'`, `'winkel tripel'`, `'aitoff'`, or `'sinusoidal'`" + "Default depends on `scope`.", + ], + center=[ + "dict", + "Dict keys are `'lat'` and `'lon'`", + "Sets the center point of the map.", + ], + map_style=[ + "str (default `'basic'`)", + "Identifier of base map style.", + "Allowed values are `'basic'`, `'carto-darkmatter'`, `'carto-darkmatter-nolabels'`, `'carto-positron'`, `'carto-positron-nolabels'`, `'carto-voyager'`, `'carto-voyager-nolabels'`, `'dark'`, `'light'`, `'open-street-map'`, `'outdoors'`, `'satellite'`, `'satellite-streets'`, `'streets'`, `'white-bg'`.", + ], + mapbox_style=[ + "str (default `'basic'`, needs Mapbox API token)", + "Identifier of base map style, some of which require a Mapbox or Stadia Maps API token to be set using `plotly.express.set_mapbox_access_token()`.", + "Allowed values which do not require a token are `'open-street-map'`, `'white-bg'`, `'carto-positron'`, `'carto-darkmatter'`.", + "Allowed values which require a Mapbox API token are `'basic'`, `'streets'`, `'outdoors'`, `'light'`, `'dark'`, `'satellite'`, `'satellite-streets'`.", + "Allowed values which require a Stadia Maps API token are `'stamen-terrain'`, `'stamen-toner'`, `'stamen-watercolor'`.", + ], + points=[ + "str or boolean (default `'outliers'`)", + "One of `'outliers'`, `'suspectedoutliers'`, `'all'`, or `False`.", + "If `'outliers'`, only the sample points lying outside the whiskers are shown.", + "If `'suspectedoutliers'`, all outlier points are shown and those less than 4*Q1-3*Q3 or greater than 4*Q3-3*Q1 are highlighted with the marker's `'outliercolor'`.", + "If `'outliers'`, only the sample points lying outside the whiskers are shown.", + "If `'all'`, all sample points are shown.", + "If `False`, no sample points are shown and the whiskers extend to the full range of the sample.", + ], + box=["boolean (default `False`)", "If `True`, boxes are drawn inside the violins."], + notched=["boolean (default `False`)", "If `True`, boxes are drawn with notches."], + geojson=[ + "GeoJSON-formatted dict", + "Must contain a Polygon feature collection, with IDs, which are references from `locations`.", + ], + featureidkey=[ + "str (default: `'id'`)", + "Path to field in GeoJSON feature object with which to match the values passed in to `locations`." + "The most common alternative to the default is of the form `'properties.`.", + ], + cumulative=[ + "boolean (default `False`)", + "If `True`, histogram values are cumulative.", + ], + nbins=["int", "Positive integer.", "Sets the number of bins."], + nbinsx=["int", "Positive integer.", "Sets the number of bins along the x axis."], + nbinsy=["int", "Positive integer.", "Sets the number of bins along the y axis."], + branchvalues=[ + "str", + "'total' or 'remainder'", + "Determines how the items in `values` are summed. When" + "set to 'total', items in `values` are taken to be value" + "of all its descendants. When set to 'remainder', items" + "in `values` corresponding to the root and the branches" + ":sectors are taken to be the extra part not part of the" + "sum of the values at their leaves.", + ], + maxdepth=[ + "int", + "Positive integer", + "Sets the number of rendered sectors from any given `level`. Set `maxdepth` to -1 to render all the" + "levels in the hierarchy.", + ], + ecdfnorm=[ + "string or `None` (default `'probability'`)", + "One of `'probability'` or `'percent'`", + "If `None`, values will be raw counts or sums.", + "If `'probability', values will be probabilities normalized from 0 to 1.", + "If `'percent', values will be percentages normalized from 0 to 100.", + ], + ecdfmode=[ + "string (default `'standard'`)", + "One of `'standard'`, `'complementary'` or `'reversed'`", + "If `'standard'`, the ECDF is plotted such that values represent data at or below the point.", + "If `'complementary'`, the CCDF is plotted such that values represent data above the point.", + "If `'reversed'`, a variant of the CCDF is plotted such that values represent data at or above the point.", + ], + text_auto=[ + "bool or string (default `False`)", + "If `True` or a string, the x or y or z values will be displayed as text, depending on the orientation", + "A string like `'.2f'` will be interpreted as a `texttemplate` numeric formatting directive.", + ], +) + + +def make_docstring(fn, override_dict=None, append_dict=None): + override_dict = {} if override_dict is None else override_dict + append_dict = {} if append_dict is None else append_dict + tw = TextWrapper( + width=75, + initial_indent=" ", + subsequent_indent=" ", + break_on_hyphens=False, + ) + result = (fn.__doc__ or "") + "\nParameters\n----------\n" + for param in getfullargspec(fn)[0]: + if override_dict.get(param): + param_doc = list(override_dict[param]) + else: + param_doc = list(docs[param]) + if append_dict.get(param): + param_doc += append_dict[param] + param_desc_list = param_doc[1:] + param_desc = ( + tw.fill(" ".join(param_desc_list or "")) + if param in docs or param in override_dict + else "(documentation missing from map)" + ) + + param_type = param_doc[0] + result += "%s: %s\n%s\n" % (param, param_type, param_desc) + result += "\nReturns\n-------\n" + result += " plotly.graph_objects.Figure" + return result diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/express/_imshow.py b/.venv_haddock/lib/python3.12/site-packages/plotly/express/_imshow.py new file mode 100644 index 0000000000000000000000000000000000000000..7a3dd8a6df9f3311e7a4d1426efc5bef1bd20785 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/express/_imshow.py @@ -0,0 +1,605 @@ +import plotly.graph_objs as go +from _plotly_utils.basevalidators import ColorscaleValidator +from ._core import apply_default_cascade, init_figure, configure_animation_controls +from .imshow_utils import rescale_intensity, _integer_ranges, _integer_types +import narwhals.stable.v1 as nw +import numpy as np +import itertools +from plotly.utils import image_array_to_data_uri + +try: + import xarray + + xarray_imported = True +except ImportError: + xarray_imported = False + +_float_types = [] + + +def _vectorize_zvalue(z, mode="max"): + alpha = 255 if mode == "max" else 0 + if z is None: + return z + elif np.isscalar(z): + return [z] * 3 + [alpha] + elif len(z) == 1: + return list(z) * 3 + [alpha] + elif len(z) == 3: + return list(z) + [alpha] + elif len(z) == 4: + return z + else: + raise ValueError( + "zmax can be a scalar, or an iterable of length 1, 3 or 4. " + "A value of %s was passed for zmax." % str(z) + ) + + +def _infer_zmax_from_type(img): + dt = img.dtype.type + rtol = 1.05 + if dt in _integer_types: + return _integer_ranges[dt][1] + else: + im_max = img[np.isfinite(img)].max() + if im_max <= 1 * rtol: + return 1 + elif im_max <= 255 * rtol: + return 255 + elif im_max <= 65535 * rtol: + return 65535 + else: + return 2**32 + + +def imshow( + img, + zmin=None, + zmax=None, + origin=None, + labels={}, + x=None, + y=None, + animation_frame=None, + facet_col=None, + facet_col_wrap=None, + facet_col_spacing=None, + facet_row_spacing=None, + color_continuous_scale=None, + color_continuous_midpoint=None, + range_color=None, + title=None, + template=None, + width=None, + height=None, + aspect=None, + contrast_rescaling=None, + binary_string=None, + binary_backend="auto", + binary_compression_level=4, + binary_format="png", + text_auto=False, +) -> go.Figure: + """ + Display an image, i.e. data on a 2D regular raster. + + Parameters + ---------- + + img: array-like image, or xarray + The image data. Supported array shapes are + + - (M, N): an image with scalar data. The data is visualized + using a colormap. + - (M, N, 3): an image with RGB values. + - (M, N, 4): an image with RGBA values, i.e. including transparency. + + zmin, zmax : scalar or iterable, optional + zmin and zmax define the scalar range that the colormap covers. By default, + zmin and zmax correspond to the min and max values of the datatype for integer + datatypes (ie [0-255] for uint8 images, [0, 65535] for uint16 images, etc.). For + a multichannel image of floats, the max of the image is computed and zmax is the + smallest power of 256 (1, 255, 65535) greater than this max value, + with a 5% tolerance. For a single-channel image, the max of the image is used. + Overridden by range_color. + + origin : str, 'upper' or 'lower' (default 'upper') + position of the [0, 0] pixel of the image array, in the upper left or lower left + corner. The convention 'upper' is typically used for matrices and images. + + labels : dict with str keys and str values (default `{}`) + Sets names used in the figure for axis titles (keys ``x`` and ``y``), + colorbar title and hoverlabel (key ``color``). The values should correspond + to the desired label to be displayed. If ``img`` is an xarray, dimension + names are used for axis titles, and long name for the colorbar title + (unless overridden in ``labels``). Possible keys are: x, y, and color. + + x, y: list-like, optional + x and y are used to label the axes of single-channel heatmap visualizations and + their lengths must match the lengths of the second and first dimensions of the + img argument. They are auto-populated if the input is an xarray. + + animation_frame: int or str, optional (default None) + axis number along which the image array is sliced to create an animation plot. + If `img` is an xarray, `animation_frame` can be the name of one the dimensions. + + facet_col: int or str, optional (default None) + axis number along which the image array is sliced to create a facetted plot. + If `img` is an xarray, `facet_col` can be the name of one the dimensions. + + facet_col_wrap: int + Maximum number of facet columns. Wraps the column variable at this width, + so that the column facets span multiple rows. + Ignored if `facet_col` is None. + + facet_col_spacing: float between 0 and 1 + Spacing between facet columns, in paper units. Default is 0.02. + + facet_row_spacing: float between 0 and 1 + Spacing between facet rows created when ``facet_col_wrap`` is used, in + paper units. Default is 0.0.7. + + color_continuous_scale : str or list of str + colormap used to map scalar data to colors (for a 2D image). This parameter is + not used for RGB or RGBA images. If a string is provided, it should be the name + of a known color scale, and if a list is provided, it should be a list of CSS- + compatible colors. + + color_continuous_midpoint : number + If set, computes the bounds of the continuous color scale to have the desired + midpoint. Overridden by range_color or zmin and zmax. + + range_color : list of two numbers + If provided, overrides auto-scaling on the continuous color scale, including + overriding `color_continuous_midpoint`. Also overrides zmin and zmax. Used only + for single-channel images. + + title : str + The figure title. + + template : str or dict or plotly.graph_objects.layout.Template instance + The figure template name or definition. + + width : number + The figure width in pixels. + + height: number + The figure height in pixels. + + aspect: 'equal', 'auto', or None + - 'equal': Ensures an aspect ratio of 1 or pixels (square pixels) + - 'auto': The axes is kept fixed and the aspect ratio of pixels is + adjusted so that the data fit in the axes. In general, this will + result in non-square pixels. + - if None, 'equal' is used for numpy arrays and 'auto' for xarrays + (which have typically heterogeneous coordinates) + + contrast_rescaling: 'minmax', 'infer', or None + how to determine data values corresponding to the bounds of the color + range, when zmin or zmax are not passed. If `minmax`, the min and max + values of the image are used. If `infer`, a heuristic based on the image + data type is used. + + binary_string: bool, default None + if True, the image data are first rescaled and encoded as uint8 and + then passed to plotly.js as a b64 PNG string. If False, data are passed + unchanged as a numerical array. Setting to True may lead to performance + gains, at the cost of a loss of precision depending on the original data + type. If None, use_binary_string is set to True for multichannel (eg) RGB + arrays, and to False for single-channel (2D) arrays. 2D arrays are + represented as grayscale and with no colorbar if use_binary_string is + True. + + binary_backend: str, 'auto' (default), 'pil' or 'pypng' + Third-party package for the transformation of numpy arrays to + png b64 strings. If 'auto', Pillow is used if installed, otherwise + pypng. + + binary_compression_level: int, between 0 and 9 (default 4) + png compression level to be passed to the backend when transforming an + array to a png b64 string. Increasing `binary_compression` decreases the + size of the png string, but the compression step takes more time. For most + images it is not worth using levels greater than 5, but it's possible to + test `len(fig.data[0].source)` and to time the execution of `imshow` to + tune the level of compression. 0 means no compression (not recommended). + + binary_format: str, 'png' (default) or 'jpg' + compression format used to generate b64 string. 'png' is recommended + since it uses lossless compression, but 'jpg' (lossy) compression can + result if smaller binary strings for natural images. + + text_auto: bool or str (default `False`) + If `True` or a string, single-channel `img` values will be displayed as text. + A string like `'.2f'` will be interpreted as a `texttemplate` numeric formatting directive. + + Returns + ------- + fig : graph_objects.Figure containing the displayed image + + See also + -------- + + plotly.graph_objects.Image : image trace + plotly.graph_objects.Heatmap : heatmap trace + + Notes + ----- + + In order to update and customize the returned figure, use + `go.Figure.update_traces` or `go.Figure.update_layout`. + + If an xarray is passed, dimensions names and coordinates are used for + axes labels and ticks. + """ + args = locals() + apply_default_cascade(args, constructor=None) + labels = labels.copy() + nslices_facet = 1 + if facet_col is not None: + if isinstance(facet_col, str): + facet_col = img.dims.index(facet_col) + nslices_facet = img.shape[facet_col] + facet_slices = range(nslices_facet) + ncols = int(facet_col_wrap) if facet_col_wrap is not None else nslices_facet + nrows = ( + nslices_facet // ncols + 1 + if nslices_facet % ncols + else nslices_facet // ncols + ) + else: + nrows = 1 + ncols = 1 + if animation_frame is not None: + if isinstance(animation_frame, str): + animation_frame = img.dims.index(animation_frame) + nslices_animation = img.shape[animation_frame] + animation_slices = range(nslices_animation) + slice_dimensions = (facet_col is not None) + ( + animation_frame is not None + ) # 0, 1, or 2 + facet_label = None + animation_label = None + img_is_xarray = False + # ----- Define x and y, set labels if img is an xarray ------------------- + if xarray_imported and isinstance(img, xarray.DataArray): + dims = list(img.dims) + img_is_xarray = True + pop_indexes = [] + if facet_col is not None: + facet_slices = img.coords[img.dims[facet_col]].values + pop_indexes.append(facet_col) + facet_label = img.dims[facet_col] + if animation_frame is not None: + animation_slices = img.coords[img.dims[animation_frame]].values + pop_indexes.append(animation_frame) + animation_label = img.dims[animation_frame] + # Remove indices in sorted order. + for index in sorted(pop_indexes, reverse=True): + _ = dims.pop(index) + y_label, x_label = dims[0], dims[1] + # np.datetime64 is not handled correctly by go.Heatmap + for ax in [x_label, y_label]: + if np.issubdtype(img.coords[ax].dtype, np.datetime64): + img.coords[ax] = img.coords[ax].astype(str) + if x is None: + x = img.coords[x_label].values + if y is None: + y = img.coords[y_label].values + if aspect is None: + aspect = "auto" + if labels.get("x", None) is None: + labels["x"] = x_label + if labels.get("y", None) is None: + labels["y"] = y_label + if labels.get("animation_frame", None) is None: + labels["animation_frame"] = animation_label + if labels.get("facet_col", None) is None: + labels["facet_col"] = facet_label + if labels.get("color", None) is None: + labels["color"] = xarray.plot.utils.label_from_attrs(img) + labels["color"] = labels["color"].replace("\n", "
") + else: + if hasattr(img, "columns") and hasattr(img.columns, "__len__"): + if x is None: + x = img.columns + if labels.get("x", None) is None and hasattr(img.columns, "name"): + labels["x"] = img.columns.name or "" + if hasattr(img, "index") and hasattr(img.index, "__len__"): + if y is None: + y = img.index + if labels.get("y", None) is None and hasattr(img.index, "name"): + labels["y"] = img.index.name or "" + + if labels.get("x", None) is None: + labels["x"] = "" + if labels.get("y", None) is None: + labels["y"] = "" + if labels.get("color", None) is None: + labels["color"] = "" + if aspect is None: + aspect = "equal" + + # --- Set the value of binary_string (forbidden for pandas) + img = nw.from_native(img, pass_through=True) + if isinstance(img, nw.DataFrame): + if binary_string: + raise ValueError("Binary strings cannot be used with pandas arrays") + is_dataframe = True + else: + is_dataframe = False + + # --------------- Starting from here img is always a numpy array -------- + img = np.asanyarray(img) + # Reshape array so that animation dimension comes first, then facets, then images + if facet_col is not None: + img = np.moveaxis(img, facet_col, 0) + if animation_frame is not None and animation_frame < facet_col: + animation_frame += 1 + facet_col = True + if animation_frame is not None: + img = np.moveaxis(img, animation_frame, 0) + animation_frame = True + args["animation_frame"] = ( + "animation_frame" + if labels.get("animation_frame") is None + else labels["animation_frame"] + ) + iterables = () + if animation_frame is not None: + iterables += (range(nslices_animation),) + if facet_col is not None: + iterables += (range(nslices_facet),) + + # Default behaviour of binary_string: True for RGB images, False for 2D + if binary_string is None: + binary_string = img.ndim >= (3 + slice_dimensions) and not is_dataframe + + # Cast bools to uint8 (also one byte) + if img.dtype == bool: + img = 255 * img.astype(np.uint8) + + if range_color is not None: + zmin = range_color[0] + zmax = range_color[1] + + # -------- Contrast rescaling: either minmax or infer ------------------ + if contrast_rescaling is None: + contrast_rescaling = "minmax" if img.ndim == (2 + slice_dimensions) else "infer" + + # We try to set zmin and zmax only if necessary, because traces have good defaults + if contrast_rescaling == "minmax": + # When using binary_string and minmax we need to set zmin and zmax to rescale the image + if (zmin is not None or binary_string) and zmax is None: + zmax = img.max() + if (zmax is not None or binary_string) and zmin is None: + zmin = img.min() + else: + # For uint8 data and infer we let zmin and zmax to be None if passed as None + if zmax is None and img.dtype != np.uint8: + zmax = _infer_zmax_from_type(img) + if zmin is None and zmax is not None: + zmin = 0 + + # For 2d data, use Heatmap trace, unless binary_string is True + if img.ndim == 2 + slice_dimensions and not binary_string: + y_index = slice_dimensions + if y is not None and img.shape[y_index] != len(y): + raise ValueError( + "The length of the y vector must match the length of the first " + + "dimension of the img matrix." + ) + x_index = slice_dimensions + 1 + if x is not None and img.shape[x_index] != len(x): + raise ValueError( + "The length of the x vector must match the length of the second " + + "dimension of the img matrix." + ) + + texttemplate = None + if text_auto is True: + texttemplate = "%{z}" + elif text_auto is not False: + texttemplate = "%{z:" + text_auto + "}" + + traces = [ + go.Heatmap( + x=x, + y=y, + z=img[index_tup], + coloraxis="coloraxis1", + name=str(i), + texttemplate=texttemplate, + ) + for i, index_tup in enumerate(itertools.product(*iterables)) + ] + autorange = True if origin == "lower" else "reversed" + layout = dict(yaxis=dict(autorange=autorange)) + if aspect == "equal": + layout["xaxis"] = dict(scaleanchor="y", constrain="domain") + layout["yaxis"]["constrain"] = "domain" + colorscale_validator = ColorscaleValidator("colorscale", "imshow") + layout["coloraxis1"] = dict( + colorscale=colorscale_validator.validate_coerce( + args["color_continuous_scale"] + ), + cmid=color_continuous_midpoint, + cmin=zmin, + cmax=zmax, + ) + if labels["color"]: + layout["coloraxis1"]["colorbar"] = dict(title_text=labels["color"]) + + # For 2D+RGB data, use Image trace + elif ( + img.ndim >= 3 + and (img.shape[-1] in [3, 4] or slice_dimensions and binary_string) + ) or (img.ndim == 2 and binary_string): + rescale_image = True # to check whether image has been modified + if zmin is not None and zmax is not None: + zmin, zmax = ( + _vectorize_zvalue(zmin, mode="min"), + _vectorize_zvalue(zmax, mode="max"), + ) + x0, y0, dx, dy = (None,) * 4 + error_msg_xarray = ( + "Non-numerical coordinates were passed with xarray `img`, but " + "the Image trace cannot handle it. Please use `binary_string=False` " + "for 2D data or pass instead the numpy array `img.values` to `px.imshow`." + ) + if x is not None: + x = np.asanyarray(x) + if np.issubdtype(x.dtype, np.number): + x0 = x[0] + dx = x[1] - x[0] + else: + error_msg = ( + error_msg_xarray + if img_is_xarray + else ( + "Only numerical values are accepted for the `x` parameter " + "when an Image trace is used." + ) + ) + raise ValueError(error_msg) + if y is not None: + y = np.asanyarray(y) + if np.issubdtype(y.dtype, np.number): + y0 = y[0] + dy = y[1] - y[0] + else: + error_msg = ( + error_msg_xarray + if img_is_xarray + else ( + "Only numerical values are accepted for the `y` parameter " + "when an Image trace is used." + ) + ) + raise ValueError(error_msg) + if binary_string: + if zmin is None and zmax is None: # no rescaling, faster + img_rescaled = img + rescale_image = False + elif img.ndim == 2 + slice_dimensions: # single-channel image + img_rescaled = rescale_intensity( + img, in_range=(zmin[0], zmax[0]), out_range=np.uint8 + ) + else: + img_rescaled = np.stack( + [ + rescale_intensity( + img[..., ch], + in_range=(zmin[ch], zmax[ch]), + out_range=np.uint8, + ) + for ch in range(img.shape[-1]) + ], + axis=-1, + ) + img_str = [ + image_array_to_data_uri( + img_rescaled[index_tup], + backend=binary_backend, + compression=binary_compression_level, + ext=binary_format, + ) + for index_tup in itertools.product(*iterables) + ] + + traces = [ + go.Image(source=img_str_slice, name=str(i), x0=x0, y0=y0, dx=dx, dy=dy) + for i, img_str_slice in enumerate(img_str) + ] + else: + colormodel = "rgb" if img.shape[-1] == 3 else "rgba256" + traces = [ + go.Image( + z=img[index_tup], + zmin=zmin, + zmax=zmax, + colormodel=colormodel, + x0=x0, + y0=y0, + dx=dx, + dy=dy, + ) + for index_tup in itertools.product(*iterables) + ] + layout = {} + if origin == "lower" or (dy is not None and dy < 0): + layout["yaxis"] = dict(autorange=True) + if dx is not None and dx < 0: + layout["xaxis"] = dict(autorange="reversed") + else: + raise ValueError( + "px.imshow only accepts 2D single-channel, RGB or RGBA images. " + "An image of shape %s was provided. " + "Alternatively, 3- or 4-D single or multichannel datasets can be " + "visualized using the `facet_col` or/and `animation_frame` arguments." + % str(img.shape) + ) + + # Now build figure + col_labels = [] + if facet_col is not None: + slice_label = ( + "facet_col" if labels.get("facet_col") is None else labels["facet_col"] + ) + col_labels = [f"{slice_label}={i}" for i in facet_slices] + fig = init_figure(args, "xy", [], nrows, ncols, col_labels, []) + for attr_name in ["height", "width"]: + if args[attr_name]: + layout[attr_name] = args[attr_name] + if args["title"]: + layout["title_text"] = args["title"] + elif args["template"].layout.margin.t is None: + layout["margin"] = {"t": 60} + + frame_list = [] + for index, trace in enumerate(traces): + if (facet_col and index < nrows * ncols) or index == 0: + fig.add_trace(trace, row=nrows - index // ncols, col=index % ncols + 1) + if animation_frame is not None: + for i, index in zip(range(nslices_animation), animation_slices): + frame_list.append( + dict( + data=traces[nslices_facet * i : nslices_facet * (i + 1)], + layout=layout, + name=str(index), + ) + ) + if animation_frame: + fig.frames = frame_list + fig.update_layout(layout) + # Hover name, z or color + if binary_string and rescale_image and not np.all(img == img_rescaled): + # we rescaled the image, hence z is not displayed in hover since it does + # not correspond to img values + hovertemplate = "%s: %%{x}
%s: %%{y}" % ( + labels["x"] or "x", + labels["y"] or "y", + ) + else: + if trace["type"] == "heatmap": + hover_name = "%{z}" + elif img.ndim == 2: + hover_name = "%{z[0]}" + elif img.ndim == 3 and img.shape[-1] == 3: + hover_name = "[%{z[0]}, %{z[1]}, %{z[2]}]" + else: + hover_name = "%{z}" + hovertemplate = "%s: %%{x}
%s: %%{y}
%s: %s" % ( + labels["x"] or "x", + labels["y"] or "y", + labels["color"] or "color", + hover_name, + ) + fig.update_traces(hovertemplate=hovertemplate) + if labels["x"]: + fig.update_xaxes(title_text=labels["x"], row=1) + if labels["y"]: + fig.update_yaxes(title_text=labels["y"], col=1) + configure_animation_controls(args, go.Image, fig) + fig.update_layout(template=args["template"], overwrite=True) + return fig diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/express/_special_inputs.py b/.venv_haddock/lib/python3.12/site-packages/plotly/express/_special_inputs.py new file mode 100644 index 0000000000000000000000000000000000000000..c1b3d4d102f8c1081fe5cfa94e510d84782fcac1 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/express/_special_inputs.py @@ -0,0 +1,40 @@ +class IdentityMap(object): + """ + `dict`-like object which acts as if the value for any key is the key itself. Objects + of this class can be passed in to arguments like `color_discrete_map` to + use the provided data values as colors, rather than mapping them to colors cycled + from `color_discrete_sequence`. This works for any `_map` argument to Plotly Express + functions, such as `line_dash_map` and `symbol_map`. + """ + + def __getitem__(self, key): + return key + + def __contains__(self, key): + return True + + def copy(self): + return self + + +class Constant(object): + """ + Objects of this class can be passed to Plotly Express functions that expect column + identifiers or list-like objects to indicate that this attribute should take on a + constant value. An optional label can be provided. + """ + + def __init__(self, value, label=None): + self.value = value + self.label = label + + +class Range(object): + """ + Objects of this class can be passed to Plotly Express functions that expect column + identifiers or list-like objects to indicate that this attribute should be mapped + onto integers starting at 0. An optional label can be provided. + """ + + def __init__(self, label=None): + self.label = label diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/express/colors/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/express/colors/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..62cd3cac2de6810afb2c7361bfdb87b4ae497998 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/express/colors/__init__.py @@ -0,0 +1,52 @@ +# ruff: noqa: F405 +"""For a list of colors available in `plotly.express.colors`, please see + +* the `tutorial on discrete color sequences `_ +* the `list of built-in continuous color scales `_ +* the `tutorial on continuous colors `_ + +Color scales are available within the following namespaces + +* cyclical +* diverging +* qualitative +* sequential +""" + +from plotly.colors import * # noqa: F403 + + +__all__ = [ + "named_colorscales", + "cyclical", + "diverging", + "sequential", + "qualitative", + "colorbrewer", + "colorbrewer", + "carto", + "cmocean", + "color_parser", + "colorscale_to_colors", + "colorscale_to_scale", + "convert_colors_to_same_type", + "convert_colorscale_to_rgb", + "convert_dict_colors_to_same_type", + "convert_to_RGB_255", + "find_intermediate_color", + "hex_to_rgb", + "label_rgb", + "make_colorscale", + "n_colors", + "unconvert_from_RGB_255", + "unlabel_rgb", + "validate_colors", + "validate_colors_dict", + "validate_colorscale", + "validate_scale_values", + "plotlyjs", + "DEFAULT_PLOTLY_COLORS", + "PLOTLY_SCALES", + "get_colorscale", + "sample_colorscale", +] diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/express/colors/__pycache__/__init__.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/plotly/express/colors/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..5dfd49f14c9368f6696e1814791a1b74a29837e7 Binary files /dev/null and b/.venv_haddock/lib/python3.12/site-packages/plotly/express/colors/__pycache__/__init__.cpython-312.pyc differ diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/express/data/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/express/data/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..5096f3339a4ca3ff93bcffe43198489555d84cf0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/express/data/__init__.py @@ -0,0 +1,18 @@ +# ruff: noqa: F405 +"""Built-in datasets for demonstration, educational and test purposes.""" + +from plotly.data import * # noqa: F403 + +__all__ = [ + "carshare", + "election", + "election_geojson", + "experiment", + "gapminder", + "iris", + "medals_wide", + "medals_long", + "stocks", + "tips", + "wind", +] diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/express/data/__pycache__/__init__.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/plotly/express/data/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..ab7c4e9568670e4495265c1ed0540a20757c5199 Binary files /dev/null and b/.venv_haddock/lib/python3.12/site-packages/plotly/express/data/__pycache__/__init__.cpython-312.pyc differ diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/express/imshow_utils.py b/.venv_haddock/lib/python3.12/site-packages/plotly/express/imshow_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..7f110ede4d062be9b8d9133022bd67f3fe1a4118 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/express/imshow_utils.py @@ -0,0 +1,247 @@ +"""Vendored code from scikit-image in order to limit the number of dependencies +Extracted from scikit-image/skimage/exposure/exposure.py +""" + +import numpy as np + +from warnings import warn + +_integer_types = ( + np.byte, + np.ubyte, # 8 bits + np.short, + np.ushort, # 16 bits + np.intc, + np.uintc, # 16 or 32 or 64 bits + np.int_, + np.uint, # 32 or 64 bits + np.longlong, + np.ulonglong, +) # 64 bits +_integer_ranges = {t: (np.iinfo(t).min, np.iinfo(t).max) for t in _integer_types} +dtype_range = { + np.bool_: (False, True), + np.float16: (-1, 1), + np.float32: (-1, 1), + np.float64: (-1, 1), +} +dtype_range.update(_integer_ranges) + + +DTYPE_RANGE = dtype_range.copy() +DTYPE_RANGE.update((d.__name__, limits) for d, limits in dtype_range.items()) +DTYPE_RANGE.update( + { + "uint10": (0, 2**10 - 1), + "uint12": (0, 2**12 - 1), + "uint14": (0, 2**14 - 1), + "bool": dtype_range[np.bool_], + "float": dtype_range[np.float64], + } +) + + +def intensity_range(image, range_values="image", clip_negative=False): + """Return image intensity range (min, max) based on desired value type. + + Parameters + ---------- + image : array + Input image. + range_values : str or 2-tuple, optional + The image intensity range is configured by this parameter. + The possible values for this parameter are enumerated below. + + 'image' + Return image min/max as the range. + 'dtype' + Return min/max of the image's dtype as the range. + dtype-name + Return intensity range based on desired `dtype`. Must be valid key + in `DTYPE_RANGE`. Note: `image` is ignored for this range type. + 2-tuple + Return `range_values` as min/max intensities. Note that there's no + reason to use this function if you just want to specify the + intensity range explicitly. This option is included for functions + that use `intensity_range` to support all desired range types. + + clip_negative : bool, optional + If True, clip the negative range (i.e. return 0 for min intensity) + even if the image dtype allows negative values. + """ + if range_values == "dtype": + range_values = image.dtype.type + + if range_values == "image": + i_min = np.min(image) + i_max = np.max(image) + elif range_values in DTYPE_RANGE: + i_min, i_max = DTYPE_RANGE[range_values] + if clip_negative: + i_min = 0 + else: + i_min, i_max = range_values + return i_min, i_max + + +def _output_dtype(dtype_or_range): + """Determine the output dtype for rescale_intensity. + + The dtype is determined according to the following rules: + - if ``dtype_or_range`` is a dtype, that is the output dtype. + - if ``dtype_or_range`` is a dtype string, that is the dtype used, unless + it is not a NumPy data type (e.g. 'uint12' for 12-bit unsigned integers), + in which case the data type that can contain it will be used + (e.g. uint16 in this case). + - if ``dtype_or_range`` is a pair of values, the output data type will be + float. + + Parameters + ---------- + dtype_or_range : type, string, or 2-tuple of int/float + The desired range for the output, expressed as either a NumPy dtype or + as a (min, max) pair of numbers. + + Returns + ------- + out_dtype : type + The data type appropriate for the desired output. + """ + if type(dtype_or_range) in [list, tuple, np.ndarray]: + # pair of values: always return float. + return np.float_ + if isinstance(dtype_or_range, type): + # already a type: return it + return dtype_or_range + if dtype_or_range in DTYPE_RANGE: + # string key in DTYPE_RANGE dictionary + try: + # if it's a canonical numpy dtype, convert + return np.dtype(dtype_or_range).type + except TypeError: # uint10, uint12, uint14 + # otherwise, return uint16 + return np.uint16 + else: + raise ValueError( + "Incorrect value for out_range, should be a valid image data " + "type or a pair of values, got %s." % str(dtype_or_range) + ) + + +def rescale_intensity(image, in_range="image", out_range="dtype"): + """Return image after stretching or shrinking its intensity levels. + + The desired intensity range of the input and output, `in_range` and + `out_range` respectively, are used to stretch or shrink the intensity range + of the input image. See examples below. + + Parameters + ---------- + image : array + Image array. + in_range, out_range : str or 2-tuple, optional + Min and max intensity values of input and output image. + The possible values for this parameter are enumerated below. + + 'image' + Use image min/max as the intensity range. + 'dtype' + Use min/max of the image's dtype as the intensity range. + dtype-name + Use intensity range based on desired `dtype`. Must be valid key + in `DTYPE_RANGE`. + 2-tuple + Use `range_values` as explicit min/max intensities. + + Returns + ------- + out : array + Image array after rescaling its intensity. This image is the same dtype + as the input image. + + Notes + ----- + .. versionchanged:: 0.17 + The dtype of the output array has changed to match the output dtype, or + float if the output range is specified by a pair of floats. + + See Also + -------- + equalize_hist + + Examples + -------- + By default, the min/max intensities of the input image are stretched to + the limits allowed by the image's dtype, since `in_range` defaults to + 'image' and `out_range` defaults to 'dtype': + + >>> image = np.array([51, 102, 153], dtype=np.uint8) + >>> rescale_intensity(image) + array([ 0, 127, 255], dtype=uint8) + + It's easy to accidentally convert an image dtype from uint8 to float: + + >>> 1.0 * image + array([ 51., 102., 153.]) + + Use `rescale_intensity` to rescale to the proper range for float dtypes: + + >>> image_float = 1.0 * image + >>> rescale_intensity(image_float) + array([0. , 0.5, 1. ]) + + To maintain the low contrast of the original, use the `in_range` parameter: + + >>> rescale_intensity(image_float, in_range=(0, 255)) + array([0.2, 0.4, 0.6]) + + If the min/max value of `in_range` is more/less than the min/max image + intensity, then the intensity levels are clipped: + + >>> rescale_intensity(image_float, in_range=(0, 102)) + array([0.5, 1. , 1. ]) + + If you have an image with signed integers but want to rescale the image to + just the positive range, use the `out_range` parameter. In that case, the + output dtype will be float: + + >>> image = np.array([-10, 0, 10], dtype=np.int8) + >>> rescale_intensity(image, out_range=(0, 127)) + array([ 0. , 63.5, 127. ]) + + To get the desired range with a specific dtype, use ``.astype()``: + + >>> rescale_intensity(image, out_range=(0, 127)).astype(np.int8) + array([ 0, 63, 127], dtype=int8) + + If the input image is constant, the output will be clipped directly to the + output range: + >>> image = np.array([130, 130, 130], dtype=np.int32) + >>> rescale_intensity(image, out_range=(0, 127)).astype(np.int32) + array([127, 127, 127], dtype=int32) + """ + if out_range in ["dtype", "image"]: + out_dtype = _output_dtype(image.dtype.type) + else: + out_dtype = _output_dtype(out_range) + + imin, imax = map(float, intensity_range(image, in_range)) + omin, omax = map( + float, intensity_range(image, out_range, clip_negative=(imin >= 0)) + ) + + if np.any(np.isnan([imin, imax, omin, omax])): + warn( + "One or more intensity levels are NaN. Rescaling will broadcast " + "NaN to the full image. Provide intensity levels yourself to " + "avoid this. E.g. with np.nanmin(image), np.nanmax(image).", + stacklevel=2, + ) + + image = np.clip(image, imin, imax) + + if imin != imax: + image = (image - imin) / (imax - imin) + return np.asarray(image * (omax - omin) + omin, dtype=out_dtype) + else: + return np.clip(image, omin, omax).astype(out_dtype) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/express/trendline_functions/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/express/trendline_functions/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..18ff219979a1b9af1f51cf9b5a4dca9192d7fda3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/express/trendline_functions/__init__.py @@ -0,0 +1,170 @@ +""" +The `trendline_functions` module contains functions which are called by Plotly Express +when the `trendline` argument is used. Valid values for `trendline` are the names of the +functions in this module, and the value of the `trendline_options` argument to PX +functions is passed in as the first argument to these functions when called. + +Note that the functions in this module are not meant to be called directly, and are +exposed as part of the public API for documentation purposes. +""" + +__all__ = ["ols", "lowess", "rolling", "ewm", "expanding"] + + +def ols(trendline_options, x_raw, x, y, x_label, y_label, non_missing): + """Ordinary Least Squares (OLS) trendline function + + Requires `statsmodels` to be installed. + + This trendline function causes fit results to be stored within the figure, + accessible via the `plotly.express.get_trendline_results` function. The fit results + are the output of the `statsmodels.api.OLS` function. + + Valid keys for the `trendline_options` dict are: + + - `add_constant` (`bool`, default `True`): if `False`, the trendline passes through + the origin but if `True` a y-intercept is fitted. + + - `log_x` and `log_y` (`bool`, default `False`): if `True` the OLS is computed with + respect to the base 10 logarithm of the input. Note that this means no zeros can + be present in the input. + """ + import numpy as np + + valid_options = ["add_constant", "log_x", "log_y"] + for k in trendline_options.keys(): + if k not in valid_options: + raise ValueError( + "OLS trendline_options keys must be one of [%s] but got '%s'" + % (", ".join(valid_options), k) + ) + + import statsmodels.api as sm + + add_constant = trendline_options.get("add_constant", True) + log_x = trendline_options.get("log_x", False) + log_y = trendline_options.get("log_y", False) + + if log_y: + if np.any(y <= 0): + raise ValueError( + "Can't do OLS trendline with `log_y=True` when `y` contains non-positive values." + ) + y = np.log10(y) + y_label = "log10(%s)" % y_label + if log_x: + if np.any(x <= 0): + raise ValueError( + "Can't do OLS trendline with `log_x=True` when `x` contains non-positive values." + ) + x = np.log10(x) + x_label = "log10(%s)" % x_label + if add_constant: + x = sm.add_constant(x) + fit_results = sm.OLS(y, x, missing="drop").fit() + y_out = fit_results.predict() + if log_y: + y_out = np.power(10, y_out) + hover_header = "OLS trendline
" + if len(fit_results.params) == 2: + hover_header += "%s = %g * %s + %g
" % ( + y_label, + fit_results.params[1], + x_label, + fit_results.params[0], + ) + elif not add_constant: + hover_header += "%s = %g * %s
" % (y_label, fit_results.params[0], x_label) + else: + hover_header += "%s = %g
" % (y_label, fit_results.params[0]) + hover_header += "R2=%f

" % fit_results.rsquared + return y_out, hover_header, fit_results + + +def lowess(trendline_options, x_raw, x, y, x_label, y_label, non_missing): + """LOcally WEighted Scatterplot Smoothing (LOWESS) trendline function + + Requires `statsmodels` to be installed. + + Valid keys for the `trendline_options` dict are: + + - `frac` (`float`, default `0.6666666`): the `frac` parameter from the + `statsmodels.api.nonparametric.lowess` function + """ + + valid_options = ["frac"] + for k in trendline_options.keys(): + if k not in valid_options: + raise ValueError( + "LOWESS trendline_options keys must be one of [%s] but got '%s'" + % (", ".join(valid_options), k) + ) + + import statsmodels.api as sm + + frac = trendline_options.get("frac", 0.6666666) + y_out = sm.nonparametric.lowess(y, x, missing="drop", frac=frac)[:, 1] + hover_header = "LOWESS trendline

" + return y_out, hover_header, None + + +def _pandas(mode, trendline_options, x_raw, y, non_missing): + import numpy as np + + try: + import pandas as pd + except ImportError: + msg = "Trendline requires pandas to be installed" + raise ImportError(msg) + + modes = dict(rolling="Rolling", ewm="Exponentially Weighted", expanding="Expanding") + trendline_options = trendline_options.copy() + function_name = trendline_options.pop("function", "mean") + function_args = trendline_options.pop("function_args", dict()) + + series = pd.Series(np.copy(y), index=x_raw.to_pandas()) + + # TODO: Narwhals Series/DataFrame do not support rolling, ewm nor expanding, therefore + # it fallbacks to pandas Series independently of the original type. + # Plotly issue: https://github.com/plotly/plotly.py/issues/4834 + # Narwhals issue: https://github.com/narwhals-dev/narwhals/issues/1254 + agg = getattr(series, mode) # e.g. series.rolling + agg_obj = agg(**trendline_options) # e.g. series.rolling(**opts) + function = getattr(agg_obj, function_name) # e.g. series.rolling(**opts).mean + y_out = function(**function_args) # e.g. series.rolling(**opts).mean(**opts) + y_out = y_out[non_missing] + hover_header = "%s %s trendline

" % (modes[mode], function_name) + return y_out, hover_header, None + + +def rolling(trendline_options, x_raw, x, y, x_label, y_label, non_missing): + """Rolling trendline function + + The value of the `function` key of the `trendline_options` dict is the function to + use (defaults to `mean`) and the value of the `function_args` key are taken to be + its arguments as a dict. The remainder of the `trendline_options` dict is passed as + keyword arguments into the `pandas.Series.rolling` function. + """ + return _pandas("rolling", trendline_options, x_raw, y, non_missing) + + +def expanding(trendline_options, x_raw, x, y, x_label, y_label, non_missing): + """Expanding trendline function + + The value of the `function` key of the `trendline_options` dict is the function to + use (defaults to `mean`) and the value of the `function_args` key are taken to be + its arguments as a dict. The remainder of the `trendline_options` dict is passed as + keyword arguments into the `pandas.Series.expanding` function. + """ + return _pandas("expanding", trendline_options, x_raw, y, non_missing) + + +def ewm(trendline_options, x_raw, x, y, x_label, y_label, non_missing): + """Exponentially Weighted Moment (EWM) trendline function + + The value of the `function` key of the `trendline_options` dict is the function to + use (defaults to `mean`) and the value of the `function_args` key are taken to be + its arguments as a dict. The remainder of the `trendline_options` dict is passed as + keyword arguments into the `pandas.Series.ewm` function. + """ + return _pandas("ewm", trendline_options, x_raw, y, non_missing) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/express/trendline_functions/__pycache__/__init__.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/plotly/express/trendline_functions/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..cb5d3ce1589f6401100d24fca0f4f052d3b8b490 Binary files /dev/null and b/.venv_haddock/lib/python3.12/site-packages/plotly/express/trendline_functions/__pycache__/__init__.cpython-312.pyc differ diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_2d_density.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_2d_density.py new file mode 100644 index 0000000000000000000000000000000000000000..3094d0bcad0decc0432cb852e714bf8c3d4be1bc --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_2d_density.py @@ -0,0 +1,155 @@ +from numbers import Number + +import plotly.exceptions + +import plotly.colors as clrs +from plotly.graph_objs import graph_objs + + +def make_linear_colorscale(colors): + """ + Makes a list of colors into a colorscale-acceptable form + + For documentation regarding to the form of the output, see + https://plot.ly/python/reference/#mesh3d-colorscale + """ + scale = 1.0 / (len(colors) - 1) + return [[i * scale, color] for i, color in enumerate(colors)] + + +def create_2d_density( + x, + y, + colorscale="Earth", + ncontours=20, + hist_color=(0, 0, 0.5), + point_color=(0, 0, 0.5), + point_size=2, + title="2D Density Plot", + height=600, + width=600, +): + """ + **deprecated**, use instead + :func:`plotly.express.density_heatmap`. + + :param (list|array) x: x-axis data for plot generation + :param (list|array) y: y-axis data for plot generation + :param (str|tuple|list) colorscale: either a plotly scale name, an rgb + or hex color, a color tuple or a list or tuple of colors. An rgb + color is of the form 'rgb(x, y, z)' where x, y, z belong to the + interval [0, 255] and a color tuple is a tuple of the form + (a, b, c) where a, b and c belong to [0, 1]. If colormap is a + list, it must contain the valid color types aforementioned as its + members. + :param (int) ncontours: the number of 2D contours to draw on the plot + :param (str) hist_color: the color of the plotted histograms + :param (str) point_color: the color of the scatter points + :param (str) point_size: the color of the scatter points + :param (str) title: set the title for the plot + :param (float) height: the height of the chart + :param (float) width: the width of the chart + + Examples + -------- + + Example 1: Simple 2D Density Plot + + >>> from plotly.figure_factory import create_2d_density + >>> import numpy as np + + >>> # Make data points + >>> t = np.linspace(-1,1.2,2000) + >>> x = (t**3)+(0.3*np.random.randn(2000)) + >>> y = (t**6)+(0.3*np.random.randn(2000)) + + >>> # Create a figure + >>> fig = create_2d_density(x, y) + + >>> # Plot the data + >>> fig.show() + + Example 2: Using Parameters + + >>> from plotly.figure_factory import create_2d_density + + >>> import numpy as np + + >>> # Make data points + >>> t = np.linspace(-1,1.2,2000) + >>> x = (t**3)+(0.3*np.random.randn(2000)) + >>> y = (t**6)+(0.3*np.random.randn(2000)) + + >>> # Create custom colorscale + >>> colorscale = ['#7A4579', '#D56073', 'rgb(236,158,105)', + ... (1, 1, 0.2), (0.98,0.98,0.98)] + + >>> # Create a figure + >>> fig = create_2d_density(x, y, colorscale=colorscale, + ... hist_color='rgb(255, 237, 222)', point_size=3) + + >>> # Plot the data + >>> fig.show() + """ + + # validate x and y are filled with numbers only + for array in [x, y]: + if not all(isinstance(element, Number) for element in array): + raise plotly.exceptions.PlotlyError( + "All elements of your 'x' and 'y' lists must be numbers." + ) + + # validate x and y are the same length + if len(x) != len(y): + raise plotly.exceptions.PlotlyError( + "Both lists 'x' and 'y' must be the same length." + ) + + colorscale = clrs.validate_colors(colorscale, "rgb") + colorscale = make_linear_colorscale(colorscale) + + # validate hist_color and point_color + hist_color = clrs.validate_colors(hist_color, "rgb") + point_color = clrs.validate_colors(point_color, "rgb") + + trace1 = graph_objs.Scatter( + x=x, + y=y, + mode="markers", + name="points", + marker=dict(color=point_color[0], size=point_size, opacity=0.4), + ) + trace2 = graph_objs.Histogram2dContour( + x=x, + y=y, + name="density", + ncontours=ncontours, + colorscale=colorscale, + reversescale=True, + showscale=False, + ) + trace3 = graph_objs.Histogram( + x=x, name="x density", marker=dict(color=hist_color[0]), yaxis="y2" + ) + trace4 = graph_objs.Histogram( + y=y, name="y density", marker=dict(color=hist_color[0]), xaxis="x2" + ) + data = [trace1, trace2, trace3, trace4] + + layout = graph_objs.Layout( + showlegend=False, + autosize=False, + title=title, + height=height, + width=width, + xaxis=dict(domain=[0, 0.85], showgrid=False, zeroline=False), + yaxis=dict(domain=[0, 0.85], showgrid=False, zeroline=False), + margin=dict(t=50), + hovermode="closest", + bargap=0, + xaxis2=dict(domain=[0.85, 1], showgrid=False, zeroline=False), + yaxis2=dict(domain=[0.85, 1], showgrid=False, zeroline=False), + ) + + fig = graph_objs.Figure(data=data, layout=layout) + return fig diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..c0ded37ca28afa3fa198817d0594b72d77c89b2b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/__init__.py @@ -0,0 +1,76 @@ +# ruff: noqa: E402 + +from plotly import optional_imports + +# Require that numpy exists for figure_factory +np = optional_imports.get_module("numpy") +if np is None: + raise ImportError( + """\ +The figure factory module requires the numpy package""" + ) + + +from plotly.figure_factory._2d_density import create_2d_density +from plotly.figure_factory._annotated_heatmap import create_annotated_heatmap +from plotly.figure_factory._bullet import create_bullet +from plotly.figure_factory._candlestick import create_candlestick +from plotly.figure_factory._dendrogram import create_dendrogram +from plotly.figure_factory._distplot import create_distplot +from plotly.figure_factory._facet_grid import create_facet_grid +from plotly.figure_factory._gantt import create_gantt +from plotly.figure_factory._ohlc import create_ohlc +from plotly.figure_factory._quiver import create_quiver +from plotly.figure_factory._scatterplot import create_scatterplotmatrix +from plotly.figure_factory._streamline import create_streamline +from plotly.figure_factory._table import create_table +from plotly.figure_factory._trisurf import create_trisurf +from plotly.figure_factory._violin import create_violin + +if optional_imports.get_module("pandas") is not None: + from plotly.figure_factory._county_choropleth import create_choropleth + from plotly.figure_factory._hexbin_map import ( + create_hexbin_map, + create_hexbin_mapbox, + ) +else: + + def create_choropleth(*args, **kwargs): + raise ImportError("Please install pandas to use `create_choropleth`") + + def create_hexbin_map(*args, **kwargs): + raise ImportError("Please install pandas to use `create_hexbin_map`") + + def create_hexbin_mapbox(*args, **kwargs): + raise ImportError("Please install pandas to use `create_hexbin_mapbox`") + + +if optional_imports.get_module("skimage") is not None: + from plotly.figure_factory._ternary_contour import create_ternary_contour +else: + + def create_ternary_contour(*args, **kwargs): + raise ImportError("Please install scikit-image to use `create_ternary_contour`") + + +__all__ = [ + "create_2d_density", + "create_annotated_heatmap", + "create_bullet", + "create_candlestick", + "create_choropleth", + "create_dendrogram", + "create_distplot", + "create_facet_grid", + "create_gantt", + "create_hexbin_map", + "create_hexbin_mapbox", + "create_ohlc", + "create_quiver", + "create_scatterplotmatrix", + "create_streamline", + "create_table", + "create_ternary_contour", + "create_trisurf", + "create_violin", +] diff --git 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a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_annotated_heatmap.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_annotated_heatmap.py new file mode 100644 index 0000000000000000000000000000000000000000..5da24ae5bc35f8b87b16872e0421ecd77c93a5f0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_annotated_heatmap.py @@ -0,0 +1,307 @@ +import plotly.colors as clrs +from plotly import exceptions, optional_imports +from plotly.figure_factory import utils +from plotly.graph_objs import graph_objs +from plotly.validator_cache import ValidatorCache + +# Optional imports, may be None for users that only use our core functionality. +np = optional_imports.get_module("numpy") + + +def validate_annotated_heatmap(z, x, y, annotation_text): + """ + Annotated-heatmap-specific validations + + Check that if a text matrix is supplied, it has the same + dimensions as the z matrix. + + See FigureFactory.create_annotated_heatmap() for params + + :raises: (PlotlyError) If z and text matrices do not have the same + dimensions. + """ + if annotation_text is not None and isinstance(annotation_text, list): + utils.validate_equal_length(z, annotation_text) + for lst in range(len(z)): + if len(z[lst]) != len(annotation_text[lst]): + raise exceptions.PlotlyError( + "z and text should have the same dimensions" + ) + + if x: + if len(x) != len(z[0]): + raise exceptions.PlotlyError( + "oops, the x list that you " + "provided does not match the " + "width of your z matrix " + ) + + if y: + if len(y) != len(z): + raise exceptions.PlotlyError( + "oops, the y list that you " + "provided does not match the " + "length of your z matrix " + ) + + +def create_annotated_heatmap( + z, + x=None, + y=None, + annotation_text=None, + colorscale="Plasma", + font_colors=None, + showscale=False, + reversescale=False, + **kwargs, +): + """ + **deprecated**, use instead + :func:`plotly.express.imshow`. + + Function that creates annotated heatmaps + + This function adds annotations to each cell of the heatmap. + + :param (list[list]|ndarray) z: z matrix to create heatmap. + :param (list) x: x axis labels. + :param (list) y: y axis labels. + :param (list[list]|ndarray) annotation_text: Text strings for + annotations. Should have the same dimensions as the z matrix. If no + text is added, the values of the z matrix are annotated. Default = + z matrix values. + :param (list|str) colorscale: heatmap colorscale. + :param (list) font_colors: List of two color strings: [min_text_color, + max_text_color] where min_text_color is applied to annotations for + heatmap values < (max_value - min_value)/2. If font_colors is not + defined, the colors are defined logically as black or white + depending on the heatmap's colorscale. + :param (bool) showscale: Display colorscale. Default = False + :param (bool) reversescale: Reverse colorscale. Default = False + :param kwargs: kwargs passed through plotly.graph_objs.Heatmap. + These kwargs describe other attributes about the annotated Heatmap + trace such as the colorscale. For more information on valid kwargs + call help(plotly.graph_objs.Heatmap) + + Example 1: Simple annotated heatmap with default configuration + + >>> import plotly.figure_factory as ff + + >>> z = [[0.300000, 0.00000, 0.65, 0.300000], + ... [1, 0.100005, 0.45, 0.4300], + ... [0.300000, 0.00000, 0.65, 0.300000], + ... [1, 0.100005, 0.45, 0.00000]] + + >>> fig = ff.create_annotated_heatmap(z) + >>> fig.show() + """ + + # Avoiding mutables in the call signature + font_colors = font_colors if font_colors is not None else [] + validate_annotated_heatmap(z, x, y, annotation_text) + + # validate colorscale + colorscale_validator = ValidatorCache.get_validator("heatmap", "colorscale") + colorscale = colorscale_validator.validate_coerce(colorscale) + + annotations = _AnnotatedHeatmap( + z, x, y, annotation_text, colorscale, font_colors, reversescale, **kwargs + ).make_annotations() + + if x or y: + trace = dict( + type="heatmap", + z=z, + x=x, + y=y, + colorscale=colorscale, + showscale=showscale, + reversescale=reversescale, + **kwargs, + ) + layout = dict( + annotations=annotations, + xaxis=dict(ticks="", dtick=1, side="top", gridcolor="rgb(0, 0, 0)"), + yaxis=dict(ticks="", dtick=1, ticksuffix=" "), + ) + else: + trace = dict( + type="heatmap", + z=z, + colorscale=colorscale, + showscale=showscale, + reversescale=reversescale, + **kwargs, + ) + layout = dict( + annotations=annotations, + xaxis=dict( + ticks="", side="top", gridcolor="rgb(0, 0, 0)", showticklabels=False + ), + yaxis=dict(ticks="", ticksuffix=" ", showticklabels=False), + ) + + data = [trace] + + return graph_objs.Figure(data=data, layout=layout) + + +def to_rgb_color_list(color_str, default): + color_str = color_str.strip() + if color_str.startswith("rgb"): + return [int(v) for v in color_str.strip("rgba()").split(",")] + elif color_str.startswith("#"): + return clrs.hex_to_rgb(color_str) + else: + return default + + +def should_use_black_text(background_color): + return ( + background_color[0] * 0.299 + + background_color[1] * 0.587 + + background_color[2] * 0.114 + ) > 186 + + +class _AnnotatedHeatmap(object): + """ + Refer to TraceFactory.create_annotated_heatmap() for docstring + """ + + def __init__( + self, z, x, y, annotation_text, colorscale, font_colors, reversescale, **kwargs + ): + self.z = z + if x: + self.x = x + else: + self.x = range(len(z[0])) + if y: + self.y = y + else: + self.y = range(len(z)) + if annotation_text is not None: + self.annotation_text = annotation_text + else: + self.annotation_text = self.z + self.colorscale = colorscale + self.reversescale = reversescale + self.font_colors = font_colors + + if np and isinstance(self.z, np.ndarray): + self.zmin = np.amin(self.z) + self.zmax = np.amax(self.z) + else: + self.zmin = min([v for row in self.z for v in row]) + self.zmax = max([v for row in self.z for v in row]) + + if kwargs.get("zmin", None) is not None: + self.zmin = kwargs["zmin"] + if kwargs.get("zmax", None) is not None: + self.zmax = kwargs["zmax"] + + self.zmid = (self.zmax + self.zmin) / 2 + + if kwargs.get("zmid", None) is not None: + self.zmid = kwargs["zmid"] + + def get_text_color(self): + """ + Get font color for annotations. + + The annotated heatmap can feature two text colors: min_text_color and + max_text_color. The min_text_color is applied to annotations for + heatmap values < (max_value - min_value)/2. The user can define these + two colors. Otherwise the colors are defined logically as black or + white depending on the heatmap's colorscale. + + :rtype (string, string) min_text_color, max_text_color: text + color for annotations for heatmap values < + (max_value - min_value)/2 and text color for annotations for + heatmap values >= (max_value - min_value)/2 + """ + # Plotly colorscales ranging from a lighter shade to a darker shade + colorscales = [ + "Greys", + "Greens", + "Blues", + "YIGnBu", + "YIOrRd", + "RdBu", + "Picnic", + "Jet", + "Hot", + "Blackbody", + "Earth", + "Electric", + "Viridis", + "Cividis", + ] + # Plotly colorscales ranging from a darker shade to a lighter shade + colorscales_reverse = ["Reds"] + + white = "#FFFFFF" + black = "#000000" + if self.font_colors: + min_text_color = self.font_colors[0] + max_text_color = self.font_colors[-1] + elif self.colorscale in colorscales and self.reversescale: + min_text_color = black + max_text_color = white + elif self.colorscale in colorscales: + min_text_color = white + max_text_color = black + elif self.colorscale in colorscales_reverse and self.reversescale: + min_text_color = white + max_text_color = black + elif self.colorscale in colorscales_reverse: + min_text_color = black + max_text_color = white + elif isinstance(self.colorscale, list): + min_col = to_rgb_color_list(self.colorscale[0][1], [255, 255, 255]) + max_col = to_rgb_color_list(self.colorscale[-1][1], [255, 255, 255]) + + # swap min/max colors if reverse scale + if self.reversescale: + min_col, max_col = max_col, min_col + + if should_use_black_text(min_col): + min_text_color = black + else: + min_text_color = white + + if should_use_black_text(max_col): + max_text_color = black + else: + max_text_color = white + else: + min_text_color = black + max_text_color = black + return min_text_color, max_text_color + + def make_annotations(self): + """ + Get annotations for each cell of the heatmap with graph_objs.Annotation + + :rtype (list[dict]) annotations: list of annotations for each cell of + the heatmap + """ + min_text_color, max_text_color = _AnnotatedHeatmap.get_text_color(self) + annotations = [] + for n, row in enumerate(self.z): + for m, val in enumerate(row): + font_color = min_text_color if val < self.zmid else max_text_color + annotations.append( + graph_objs.layout.Annotation( + text=str(self.annotation_text[n][m]), + x=self.x[m], + y=self.y[n], + xref="x1", + yref="y1", + font=dict(color=font_color), + showarrow=False, + ) + ) + return annotations diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_bullet.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_bullet.py new file mode 100644 index 0000000000000000000000000000000000000000..ce51e9360c8dd98054ab9c7fc631a8eec1a449d4 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_bullet.py @@ -0,0 +1,366 @@ +import math + +from plotly import exceptions, optional_imports +import plotly.colors as clrs +from plotly.figure_factory import utils + +import plotly +import plotly.graph_objs as go + +pd = optional_imports.get_module("pandas") + + +def _bullet( + df, + markers, + measures, + ranges, + subtitles, + titles, + orientation, + range_colors, + measure_colors, + horizontal_spacing, + vertical_spacing, + scatter_options, + layout_options, +): + num_of_lanes = len(df) + num_of_rows = num_of_lanes if orientation == "h" else 1 + num_of_cols = 1 if orientation == "h" else num_of_lanes + if not horizontal_spacing: + horizontal_spacing = 1.0 / num_of_lanes + if not vertical_spacing: + vertical_spacing = 1.0 / num_of_lanes + fig = plotly.subplots.make_subplots( + num_of_rows, + num_of_cols, + print_grid=False, + horizontal_spacing=horizontal_spacing, + vertical_spacing=vertical_spacing, + ) + + # layout + fig["layout"].update( + dict(shapes=[]), + title="Bullet Chart", + height=600, + width=1000, + showlegend=False, + barmode="stack", + annotations=[], + margin=dict(l=120 if orientation == "h" else 80), + ) + + # update layout + fig["layout"].update(layout_options) + + if orientation == "h": + width_axis = "yaxis" + length_axis = "xaxis" + else: + width_axis = "xaxis" + length_axis = "yaxis" + + for key in fig["layout"]: + if "xaxis" in key or "yaxis" in key: + fig["layout"][key]["showgrid"] = False + fig["layout"][key]["zeroline"] = False + if length_axis in key: + fig["layout"][key]["tickwidth"] = 1 + if width_axis in key: + fig["layout"][key]["showticklabels"] = False + fig["layout"][key]["range"] = [0, 1] + + # narrow domain if 1 bar + if num_of_lanes <= 1: + fig["layout"][width_axis + "1"]["domain"] = [0.4, 0.6] + + if not range_colors: + range_colors = ["rgb(200, 200, 200)", "rgb(245, 245, 245)"] + if not measure_colors: + measure_colors = ["rgb(31, 119, 180)", "rgb(176, 196, 221)"] + + for row in range(num_of_lanes): + # ranges bars + for idx in range(len(df.iloc[row]["ranges"])): + inter_colors = clrs.n_colors( + range_colors[0], range_colors[1], len(df.iloc[row]["ranges"]), "rgb" + ) + x = ( + [sorted(df.iloc[row]["ranges"])[-1 - idx]] + if orientation == "h" + else [0] + ) + y = ( + [0] + if orientation == "h" + else [sorted(df.iloc[row]["ranges"])[-1 - idx]] + ) + bar = go.Bar( + x=x, + y=y, + marker=dict(color=inter_colors[-1 - idx]), + name="ranges", + hoverinfo="x" if orientation == "h" else "y", + orientation=orientation, + width=2, + base=0, + xaxis="x{}".format(row + 1), + yaxis="y{}".format(row + 1), + ) + fig.add_trace(bar) + + # measures bars + for idx in range(len(df.iloc[row]["measures"])): + inter_colors = clrs.n_colors( + measure_colors[0], + measure_colors[1], + len(df.iloc[row]["measures"]), + "rgb", + ) + x = ( + [sorted(df.iloc[row]["measures"])[-1 - idx]] + if orientation == "h" + else [0.5] + ) + y = ( + [0.5] + if orientation == "h" + else [sorted(df.iloc[row]["measures"])[-1 - idx]] + ) + bar = go.Bar( + x=x, + y=y, + marker=dict(color=inter_colors[-1 - idx]), + name="measures", + hoverinfo="x" if orientation == "h" else "y", + orientation=orientation, + width=0.4, + base=0, + xaxis="x{}".format(row + 1), + yaxis="y{}".format(row + 1), + ) + fig.add_trace(bar) + + # markers + x = df.iloc[row]["markers"] if orientation == "h" else [0.5] + y = [0.5] if orientation == "h" else df.iloc[row]["markers"] + markers = go.Scatter( + x=x, + y=y, + name="markers", + hoverinfo="x" if orientation == "h" else "y", + xaxis="x{}".format(row + 1), + yaxis="y{}".format(row + 1), + **scatter_options, + ) + + fig.add_trace(markers) + + # titles and subtitles + title = df.iloc[row]["titles"] + if "subtitles" in df: + subtitle = "
{}".format(df.iloc[row]["subtitles"]) + else: + subtitle = "" + label = "{}".format(title) + subtitle + annot = utils.annotation_dict_for_label( + label, + (num_of_lanes - row if orientation == "h" else row + 1), + num_of_lanes, + vertical_spacing if orientation == "h" else horizontal_spacing, + "row" if orientation == "h" else "col", + True if orientation == "h" else False, + False, + ) + fig["layout"]["annotations"] += (annot,) + + return fig + + +def create_bullet( + data, + markers=None, + measures=None, + ranges=None, + subtitles=None, + titles=None, + orientation="h", + range_colors=("rgb(200, 200, 200)", "rgb(245, 245, 245)"), + measure_colors=("rgb(31, 119, 180)", "rgb(176, 196, 221)"), + horizontal_spacing=None, + vertical_spacing=None, + scatter_options={}, + **layout_options, +): + """ + **deprecated**, use instead the plotly.graph_objects trace + :class:`plotly.graph_objects.Indicator`. + + :param (pd.DataFrame | list | tuple) data: either a list/tuple of + dictionaries or a pandas DataFrame. + :param (str) markers: the column name or dictionary key for the markers in + each subplot. + :param (str) measures: the column name or dictionary key for the measure + bars in each subplot. This bar usually represents the quantitative + measure of performance, usually a list of two values [a, b] and are + the blue bars in the foreground of each subplot by default. + :param (str) ranges: the column name or dictionary key for the qualitative + ranges of performance, usually a 3-item list [bad, okay, good]. They + correspond to the grey bars in the background of each chart. + :param (str) subtitles: the column name or dictionary key for the subtitle + of each subplot chart. The subplots are displayed right underneath + each title. + :param (str) titles: the column name or dictionary key for the main label + of each subplot chart. + :param (bool) orientation: if 'h', the bars are placed horizontally as + rows. If 'v' the bars are placed vertically in the chart. + :param (list) range_colors: a tuple of two colors between which all + the rectangles for the range are drawn. These rectangles are meant to + be qualitative indicators against which the marker and measure bars + are compared. + Default=('rgb(200, 200, 200)', 'rgb(245, 245, 245)') + :param (list) measure_colors: a tuple of two colors which is used to color + the thin quantitative bars in the bullet chart. + Default=('rgb(31, 119, 180)', 'rgb(176, 196, 221)') + :param (float) horizontal_spacing: see the 'horizontal_spacing' param in + plotly.tools.make_subplots. Ranges between 0 and 1. + :param (float) vertical_spacing: see the 'vertical_spacing' param in + plotly.tools.make_subplots. Ranges between 0 and 1. + :param (dict) scatter_options: describes attributes for the scatter trace + in each subplot such as name and marker size. Call + help(plotly.graph_objs.Scatter) for more information on valid params. + :param layout_options: describes attributes for the layout of the figure + such as title, height and width. Call help(plotly.graph_objs.Layout) + for more information on valid params. + + Example 1: Use a Dictionary + + >>> import plotly.figure_factory as ff + + >>> data = [ + ... {"label": "revenue", "sublabel": "us$, in thousands", + ... "range": [150, 225, 300], "performance": [220,270], "point": [250]}, + ... {"label": "Profit", "sublabel": "%", "range": [20, 25, 30], + ... "performance": [21, 23], "point": [26]}, + ... {"label": "Order Size", "sublabel":"US$, average","range": [350, 500, 600], + ... "performance": [100,320],"point": [550]}, + ... {"label": "New Customers", "sublabel": "count", "range": [1400, 2000, 2500], + ... "performance": [1000, 1650],"point": [2100]}, + ... {"label": "Satisfaction", "sublabel": "out of 5","range": [3.5, 4.25, 5], + ... "performance": [3.2, 4.7], "point": [4.4]} + ... ] + + >>> fig = ff.create_bullet( + ... data, titles='label', subtitles='sublabel', markers='point', + ... measures='performance', ranges='range', orientation='h', + ... title='my simple bullet chart' + ... ) + >>> fig.show() + + Example 2: Use a DataFrame with Custom Colors + + >>> import plotly.figure_factory as ff + >>> import pandas as pd + >>> data = pd.read_json('https://cdn.rawgit.com/plotly/datasets/master/BulletData.json') + + >>> fig = ff.create_bullet( + ... data, titles='title', markers='markers', measures='measures', + ... orientation='v', measure_colors=['rgb(14, 52, 75)', 'rgb(31, 141, 127)'], + ... scatter_options={'marker': {'symbol': 'circle'}}, width=700) + >>> fig.show() + """ + # validate df + if not pd: + raise ImportError("'pandas' must be installed for this figure factory.") + + if utils.is_sequence(data): + if not all(isinstance(item, dict) for item in data): + raise exceptions.PlotlyError( + "Every entry of the data argument list, tuple, etc must " + "be a dictionary." + ) + + elif not isinstance(data, pd.DataFrame): + raise exceptions.PlotlyError( + "You must input a pandas DataFrame, or a list of dictionaries." + ) + + # make DataFrame from data with correct column headers + col_names = ["titles", "subtitle", "markers", "measures", "ranges"] + if utils.is_sequence(data): + df = pd.DataFrame( + [ + [d[titles] for d in data] if titles else [""] * len(data), + [d[subtitles] for d in data] if subtitles else [""] * len(data), + [d[markers] for d in data] if markers else [[]] * len(data), + [d[measures] for d in data] if measures else [[]] * len(data), + [d[ranges] for d in data] if ranges else [[]] * len(data), + ], + index=col_names, + ) + elif isinstance(data, pd.DataFrame): + df = pd.DataFrame( + [ + data[titles].tolist() if titles else [""] * len(data), + data[subtitles].tolist() if subtitles else [""] * len(data), + data[markers].tolist() if markers else [[]] * len(data), + data[measures].tolist() if measures else [[]] * len(data), + data[ranges].tolist() if ranges else [[]] * len(data), + ], + index=col_names, + ) + df = pd.DataFrame.transpose(df) + + # make sure ranges, measures, 'markers' are not NAN or NONE + for needed_key in ["ranges", "measures", "markers"]: + for idx, r in enumerate(df[needed_key]): + try: + r_is_nan = math.isnan(r) + if r_is_nan or r is None: + df[needed_key][idx] = [] + except TypeError: + pass + + # validate custom colors + for colors_list in [range_colors, measure_colors]: + if colors_list: + if len(colors_list) != 2: + raise exceptions.PlotlyError( + "Both 'range_colors' or 'measure_colors' must be a list " + "of two valid colors." + ) + clrs.validate_colors(colors_list) + colors_list = clrs.convert_colors_to_same_type(colors_list, "rgb")[0] + + # default scatter options + default_scatter = { + "marker": {"size": 12, "symbol": "diamond-tall", "color": "rgb(0, 0, 0)"} + } + + if scatter_options == {}: + scatter_options.update(default_scatter) + else: + # add default options to scatter_options if they are not present + for k in default_scatter["marker"]: + if k not in scatter_options["marker"]: + scatter_options["marker"][k] = default_scatter["marker"][k] + + fig = _bullet( + df, + markers, + measures, + ranges, + subtitles, + titles, + orientation, + range_colors, + measure_colors, + horizontal_spacing, + vertical_spacing, + scatter_options, + layout_options, + ) + + return fig diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_candlestick.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_candlestick.py new file mode 100644 index 0000000000000000000000000000000000000000..572ccfe142f669b3a58cb0fc4afa457daea74b85 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_candlestick.py @@ -0,0 +1,277 @@ +from plotly.figure_factory import utils +from plotly.figure_factory._ohlc import ( + _DEFAULT_INCREASING_COLOR, + _DEFAULT_DECREASING_COLOR, + validate_ohlc, +) +from plotly.graph_objs import graph_objs + + +def make_increasing_candle(open, high, low, close, dates, **kwargs): + """ + Makes boxplot trace for increasing candlesticks + + _make_increasing_candle() and _make_decreasing_candle separate the + increasing traces from the decreasing traces so kwargs (such as + color) can be passed separately to increasing or decreasing traces + when direction is set to 'increasing' or 'decreasing' in + FigureFactory.create_candlestick() + + :param (list) open: opening values + :param (list) high: high values + :param (list) low: low values + :param (list) close: closing values + :param (list) dates: list of datetime objects. Default: None + :param kwargs: kwargs to be passed to increasing trace via + plotly.graph_objs.Scatter. + + :rtype (list) candle_incr_data: list of the box trace for + increasing candlesticks. + """ + increase_x, increase_y = _Candlestick( + open, high, low, close, dates, **kwargs + ).get_candle_increase() + + if "line" in kwargs: + kwargs.setdefault("fillcolor", kwargs["line"]["color"]) + else: + kwargs.setdefault("fillcolor", _DEFAULT_INCREASING_COLOR) + if "name" in kwargs: + kwargs.setdefault("showlegend", True) + else: + kwargs.setdefault("showlegend", False) + kwargs.setdefault("name", "Increasing") + kwargs.setdefault("line", dict(color=_DEFAULT_INCREASING_COLOR)) + + candle_incr_data = dict( + type="box", + x=increase_x, + y=increase_y, + whiskerwidth=0, + boxpoints=False, + **kwargs, + ) + + return [candle_incr_data] + + +def make_decreasing_candle(open, high, low, close, dates, **kwargs): + """ + Makes boxplot trace for decreasing candlesticks + + :param (list) open: opening values + :param (list) high: high values + :param (list) low: low values + :param (list) close: closing values + :param (list) dates: list of datetime objects. Default: None + :param kwargs: kwargs to be passed to decreasing trace via + plotly.graph_objs.Scatter. + + :rtype (list) candle_decr_data: list of the box trace for + decreasing candlesticks. + """ + + decrease_x, decrease_y = _Candlestick( + open, high, low, close, dates, **kwargs + ).get_candle_decrease() + + if "line" in kwargs: + kwargs.setdefault("fillcolor", kwargs["line"]["color"]) + else: + kwargs.setdefault("fillcolor", _DEFAULT_DECREASING_COLOR) + kwargs.setdefault("showlegend", False) + kwargs.setdefault("line", dict(color=_DEFAULT_DECREASING_COLOR)) + kwargs.setdefault("name", "Decreasing") + + candle_decr_data = dict( + type="box", + x=decrease_x, + y=decrease_y, + whiskerwidth=0, + boxpoints=False, + **kwargs, + ) + + return [candle_decr_data] + + +def create_candlestick(open, high, low, close, dates=None, direction="both", **kwargs): + """ + **deprecated**, use instead the plotly.graph_objects trace + :class:`plotly.graph_objects.Candlestick` + + :param (list) open: opening values + :param (list) high: high values + :param (list) low: low values + :param (list) close: closing values + :param (list) dates: list of datetime objects. Default: None + :param (string) direction: direction can be 'increasing', 'decreasing', + or 'both'. When the direction is 'increasing', the returned figure + consists of all candlesticks where the close value is greater than + the corresponding open value, and when the direction is + 'decreasing', the returned figure consists of all candlesticks + where the close value is less than or equal to the corresponding + open value. When the direction is 'both', both increasing and + decreasing candlesticks are returned. Default: 'both' + :param kwargs: kwargs passed through plotly.graph_objs.Scatter. + These kwargs describe other attributes about the ohlc Scatter trace + such as the color or the legend name. For more information on valid + kwargs call help(plotly.graph_objs.Scatter) + + :rtype (dict): returns a representation of candlestick chart figure. + + Example 1: Simple candlestick chart from a Pandas DataFrame + + >>> from plotly.figure_factory import create_candlestick + >>> from datetime import datetime + >>> import pandas as pd + + >>> df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv') + >>> fig = create_candlestick(df['AAPL.Open'], df['AAPL.High'], df['AAPL.Low'], df['AAPL.Close'], + ... dates=df.index) + >>> fig.show() + + Example 2: Customize the candlestick colors + + >>> from plotly.figure_factory import create_candlestick + >>> from plotly.graph_objs import Line, Marker + >>> from datetime import datetime + + >>> import pandas as pd + >>> df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv') + + >>> # Make increasing candlesticks and customize their color and name + >>> fig_increasing = create_candlestick(df['AAPL.Open'], df['AAPL.High'], df['AAPL.Low'], df['AAPL.Close'], + ... dates=df.index, + ... direction='increasing', name='AAPL', + ... marker=Marker(color='rgb(150, 200, 250)'), + ... line=Line(color='rgb(150, 200, 250)')) + + >>> # Make decreasing candlesticks and customize their color and name + >>> fig_decreasing = create_candlestick(df['AAPL.Open'], df['AAPL.High'], df['AAPL.Low'], df['AAPL.Close'], + ... dates=df.index, + ... direction='decreasing', + ... marker=Marker(color='rgb(128, 128, 128)'), + ... line=Line(color='rgb(128, 128, 128)')) + + >>> # Initialize the figure + >>> fig = fig_increasing + + >>> # Add decreasing data with .extend() + >>> fig.add_trace(fig_decreasing['data']) # doctest: +SKIP + >>> fig.show() + + Example 3: Candlestick chart with datetime objects + + >>> from plotly.figure_factory import create_candlestick + + >>> from datetime import datetime + + >>> # Add data + >>> open_data = [33.0, 33.3, 33.5, 33.0, 34.1] + >>> high_data = [33.1, 33.3, 33.6, 33.2, 34.8] + >>> low_data = [32.7, 32.7, 32.8, 32.6, 32.8] + >>> close_data = [33.0, 32.9, 33.3, 33.1, 33.1] + >>> dates = [datetime(year=2013, month=10, day=10), + ... datetime(year=2013, month=11, day=10), + ... datetime(year=2013, month=12, day=10), + ... datetime(year=2014, month=1, day=10), + ... datetime(year=2014, month=2, day=10)] + + >>> # Create ohlc + >>> fig = create_candlestick(open_data, high_data, + ... low_data, close_data, dates=dates) + >>> fig.show() + """ + if dates is not None: + utils.validate_equal_length(open, high, low, close, dates) + else: + utils.validate_equal_length(open, high, low, close) + validate_ohlc(open, high, low, close, direction, **kwargs) + + if direction == "increasing": + candle_incr_data = make_increasing_candle( + open, high, low, close, dates, **kwargs + ) + data = candle_incr_data + elif direction == "decreasing": + candle_decr_data = make_decreasing_candle( + open, high, low, close, dates, **kwargs + ) + data = candle_decr_data + else: + candle_incr_data = make_increasing_candle( + open, high, low, close, dates, **kwargs + ) + candle_decr_data = make_decreasing_candle( + open, high, low, close, dates, **kwargs + ) + data = candle_incr_data + candle_decr_data + + layout = graph_objs.Layout() + return graph_objs.Figure(data=data, layout=layout) + + +class _Candlestick(object): + """ + Refer to FigureFactory.create_candlestick() for docstring. + """ + + def __init__(self, open, high, low, close, dates, **kwargs): + self.open = open + self.high = high + self.low = low + self.close = close + if dates is not None: + self.x = dates + else: + self.x = [x for x in range(len(self.open))] + self.get_candle_increase() + + def get_candle_increase(self): + """ + Separate increasing data from decreasing data. + + The data is increasing when close value > open value + and decreasing when the close value <= open value. + """ + increase_y = [] + increase_x = [] + for index in range(len(self.open)): + if self.close[index] > self.open[index]: + increase_y.append(self.low[index]) + increase_y.append(self.open[index]) + increase_y.append(self.close[index]) + increase_y.append(self.close[index]) + increase_y.append(self.close[index]) + increase_y.append(self.high[index]) + increase_x.append(self.x[index]) + + increase_x = [[x, x, x, x, x, x] for x in increase_x] + increase_x = utils.flatten(increase_x) + + return increase_x, increase_y + + def get_candle_decrease(self): + """ + Separate increasing data from decreasing data. + + The data is increasing when close value > open value + and decreasing when the close value <= open value. + """ + decrease_y = [] + decrease_x = [] + for index in range(len(self.open)): + if self.close[index] <= self.open[index]: + decrease_y.append(self.low[index]) + decrease_y.append(self.open[index]) + decrease_y.append(self.close[index]) + decrease_y.append(self.close[index]) + decrease_y.append(self.close[index]) + decrease_y.append(self.high[index]) + decrease_x.append(self.x[index]) + + decrease_x = [[x, x, x, x, x, x] for x in decrease_x] + decrease_x = utils.flatten(decrease_x) + + return decrease_x, decrease_y diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_county_choropleth.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_county_choropleth.py new file mode 100644 index 0000000000000000000000000000000000000000..7b397e7c531b7237c543ad9f6f1781aa1e0d1ddd --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_county_choropleth.py @@ -0,0 +1,1013 @@ +import io +import numpy as np +import os +import pandas as pd +import warnings + +from math import log, floor +from numbers import Number + +from plotly import optional_imports +import plotly.colors as clrs +from plotly.figure_factory import utils +from plotly.exceptions import PlotlyError +import plotly.graph_objs as go + +pd.options.mode.chained_assignment = None + +shapely = optional_imports.get_module("shapely") +shapefile = optional_imports.get_module("shapefile") +gp = optional_imports.get_module("geopandas") +_plotly_geo = optional_imports.get_module("_plotly_geo") + + +def _create_us_counties_df(st_to_state_name_dict, state_to_st_dict): + # URLS + abs_dir_path = os.path.realpath(_plotly_geo.__file__) + + abs_plotly_geo_path = os.path.dirname(abs_dir_path) + + abs_package_data_dir_path = os.path.join(abs_plotly_geo_path, "package_data") + + shape_pre2010 = "gz_2010_us_050_00_500k.shp" + shape_pre2010 = os.path.join(abs_package_data_dir_path, shape_pre2010) + + df_shape_pre2010 = gp.read_file(shape_pre2010) + df_shape_pre2010["FIPS"] = df_shape_pre2010["STATE"] + df_shape_pre2010["COUNTY"] + df_shape_pre2010["FIPS"] = pd.to_numeric(df_shape_pre2010["FIPS"]) + + states_path = "cb_2016_us_state_500k.shp" + states_path = os.path.join(abs_package_data_dir_path, states_path) + + df_state = gp.read_file(states_path) + df_state = df_state[["STATEFP", "NAME", "geometry"]] + df_state = df_state.rename(columns={"NAME": "STATE_NAME"}) + + filenames = [ + "cb_2016_us_county_500k.dbf", + "cb_2016_us_county_500k.shp", + "cb_2016_us_county_500k.shx", + ] + + for j in range(len(filenames)): + filenames[j] = os.path.join(abs_package_data_dir_path, filenames[j]) + + dbf = io.open(filenames[0], "rb") + shp = io.open(filenames[1], "rb") + shx = io.open(filenames[2], "rb") + + r = shapefile.Reader(shp=shp, shx=shx, dbf=dbf) + + attributes, geometry = [], [] + field_names = [field[0] for field in r.fields[1:]] + for row in r.shapeRecords(): + geometry.append(shapely.geometry.shape(row.shape.__geo_interface__)) + attributes.append(dict(zip(field_names, row.record))) + + gdf = gp.GeoDataFrame(data=attributes, geometry=geometry) + + gdf["FIPS"] = gdf["STATEFP"] + gdf["COUNTYFP"] + gdf["FIPS"] = pd.to_numeric(gdf["FIPS"]) + + # add missing counties + f = 46113 + singlerow = pd.DataFrame( + [ + [ + st_to_state_name_dict["SD"], + "SD", + df_shape_pre2010[df_shape_pre2010["FIPS"] == f]["geometry"].iloc[0], + df_shape_pre2010[df_shape_pre2010["FIPS"] == f]["FIPS"].iloc[0], + "46", + "Shannon", + ] + ], + columns=["State", "ST", "geometry", "FIPS", "STATEFP", "NAME"], + index=[max(gdf.index) + 1], + ) + gdf = pd.concat([gdf, singlerow], sort=True) + + f = 51515 + singlerow = pd.DataFrame( + [ + [ + st_to_state_name_dict["VA"], + "VA", + df_shape_pre2010[df_shape_pre2010["FIPS"] == f]["geometry"].iloc[0], + df_shape_pre2010[df_shape_pre2010["FIPS"] == f]["FIPS"].iloc[0], + "51", + "Bedford City", + ] + ], + columns=["State", "ST", "geometry", "FIPS", "STATEFP", "NAME"], + index=[max(gdf.index) + 1], + ) + gdf = pd.concat([gdf, singlerow], sort=True) + + f = 2270 + singlerow = pd.DataFrame( + [ + [ + st_to_state_name_dict["AK"], + "AK", + df_shape_pre2010[df_shape_pre2010["FIPS"] == f]["geometry"].iloc[0], + df_shape_pre2010[df_shape_pre2010["FIPS"] == f]["FIPS"].iloc[0], + "02", + "Wade Hampton", + ] + ], + columns=["State", "ST", "geometry", "FIPS", "STATEFP", "NAME"], + index=[max(gdf.index) + 1], + ) + gdf = pd.concat([gdf, singlerow], sort=True) + + row_2198 = gdf[gdf["FIPS"] == 2198] + row_2198.index = [max(gdf.index) + 1] + row_2198.loc[row_2198.index[0], "FIPS"] = 2201 + row_2198.loc[row_2198.index[0], "STATEFP"] = "02" + gdf = pd.concat([gdf, row_2198], sort=True) + + row_2105 = gdf[gdf["FIPS"] == 2105] + row_2105.index = [max(gdf.index) + 1] + row_2105.loc[row_2105.index[0], "FIPS"] = 2232 + row_2105.loc[row_2105.index[0], "STATEFP"] = "02" + gdf = pd.concat([gdf, row_2105], sort=True) + gdf = gdf.rename(columns={"NAME": "COUNTY_NAME"}) + + gdf_reduced = gdf[["FIPS", "STATEFP", "COUNTY_NAME", "geometry"]] + gdf_statefp = gdf_reduced.merge(df_state[["STATEFP", "STATE_NAME"]], on="STATEFP") + + ST = [] + for n in gdf_statefp["STATE_NAME"]: + ST.append(state_to_st_dict[n]) + + gdf_statefp["ST"] = ST + return gdf_statefp, df_state + + +st_to_state_name_dict = { + "AK": "Alaska", + "AL": "Alabama", + "AR": "Arkansas", + "AZ": "Arizona", + "CA": "California", + "CO": "Colorado", + "CT": "Connecticut", + "DC": "District of Columbia", + "DE": "Delaware", + "FL": "Florida", + "GA": "Georgia", + "HI": "Hawaii", + "IA": "Iowa", + "ID": "Idaho", + "IL": "Illinois", + "IN": "Indiana", + "KS": "Kansas", + "KY": "Kentucky", + "LA": "Louisiana", + "MA": "Massachusetts", + "MD": "Maryland", + "ME": "Maine", + "MI": "Michigan", + "MN": "Minnesota", + "MO": "Missouri", + "MS": "Mississippi", + "MT": "Montana", + "NC": "North Carolina", + "ND": "North Dakota", + "NE": "Nebraska", + "NH": "New Hampshire", + "NJ": "New Jersey", + "NM": "New Mexico", + "NV": "Nevada", + "NY": "New York", + "OH": "Ohio", + "OK": "Oklahoma", + "OR": "Oregon", + "PA": "Pennsylvania", + "RI": "Rhode Island", + "SC": "South Carolina", + "SD": "South Dakota", + "TN": "Tennessee", + "TX": "Texas", + "UT": "Utah", + "VA": "Virginia", + "VT": "Vermont", + "WA": "Washington", + "WI": "Wisconsin", + "WV": "West Virginia", + "WY": "Wyoming", +} + +state_to_st_dict = { + "Alabama": "AL", + "Alaska": "AK", + "American Samoa": "AS", + "Arizona": "AZ", + "Arkansas": "AR", + "California": "CA", + "Colorado": "CO", + "Commonwealth of the Northern Mariana Islands": "MP", + "Connecticut": "CT", + "Delaware": "DE", + "District of Columbia": "DC", + "Florida": "FL", + "Georgia": "GA", + "Guam": "GU", + "Hawaii": "HI", + "Idaho": "ID", + "Illinois": "IL", + "Indiana": "IN", + "Iowa": "IA", + "Kansas": "KS", + "Kentucky": "KY", + "Louisiana": "LA", + "Maine": "ME", + "Maryland": "MD", + "Massachusetts": "MA", + "Michigan": "MI", + "Minnesota": "MN", + "Mississippi": "MS", + "Missouri": "MO", + "Montana": "MT", + "Nebraska": "NE", + "Nevada": "NV", + "New Hampshire": "NH", + "New Jersey": "NJ", + "New Mexico": "NM", + "New York": "NY", + "North Carolina": "NC", + "North Dakota": "ND", + "Ohio": "OH", + "Oklahoma": "OK", + "Oregon": "OR", + "Pennsylvania": "PA", + "Puerto Rico": "", + "Rhode Island": "RI", + "South Carolina": "SC", + "South Dakota": "SD", + "Tennessee": "TN", + "Texas": "TX", + "United States Virgin Islands": "VI", + "Utah": "UT", + "Vermont": "VT", + "Virginia": "VA", + "Washington": "WA", + "West Virginia": "WV", + "Wisconsin": "WI", + "Wyoming": "WY", +} + +USA_XRANGE = [-125.0, -65.0] +USA_YRANGE = [25.0, 49.0] + + +def _human_format(number): + units = ["", "K", "M", "G", "T", "P"] + k = 1000.0 + magnitude = int(floor(log(number, k))) + return "%.2f%s" % (number / k**magnitude, units[magnitude]) + + +def _intervals_as_labels(array_of_intervals, round_legend_values, exponent_format): + """ + Transform an number interval to a clean string for legend + + Example: [-inf, 30] to '< 30' + """ + infs = [float("-inf"), float("inf")] + string_intervals = [] + for interval in array_of_intervals: + # round to 2nd decimal place + if round_legend_values: + rnd_interval = [ + (int(interval[i]) if interval[i] not in infs else interval[i]) + for i in range(2) + ] + else: + rnd_interval = [round(interval[0], 2), round(interval[1], 2)] + + num0 = rnd_interval[0] + num1 = rnd_interval[1] + if exponent_format: + if num0 not in infs: + num0 = _human_format(num0) + if num1 not in infs: + num1 = _human_format(num1) + else: + if num0 not in infs: + num0 = "{:,}".format(num0) + if num1 not in infs: + num1 = "{:,}".format(num1) + + if num0 == float("-inf"): + as_str = "< {}".format(num1) + elif num1 == float("inf"): + as_str = "> {}".format(num0) + else: + as_str = "{} - {}".format(num0, num1) + string_intervals.append(as_str) + return string_intervals + + +def _calculations( + df, + fips, + values, + index, + f, + simplify_county, + level, + x_centroids, + y_centroids, + centroid_text, + x_traces, + y_traces, + fips_polygon_map, +): + # 0-pad FIPS code to ensure exactly 5 digits + padded_f = str(f).zfill(5) + if fips_polygon_map[f].type == "Polygon": + x = fips_polygon_map[f].simplify(simplify_county).exterior.xy[0].tolist() + y = fips_polygon_map[f].simplify(simplify_county).exterior.xy[1].tolist() + + x_c, y_c = fips_polygon_map[f].centroid.xy + county_name_str = str(df[df["FIPS"] == f]["COUNTY_NAME"].iloc[0]) + state_name_str = str(df[df["FIPS"] == f]["STATE_NAME"].iloc[0]) + + t_c = ( + "County: " + + county_name_str + + "
" + + "State: " + + state_name_str + + "
" + + "FIPS: " + + padded_f + + "
Value: " + + str(values[index]) + ) + + x_centroids.append(x_c[0]) + y_centroids.append(y_c[0]) + centroid_text.append(t_c) + + x_traces[level] = x_traces[level] + x + [np.nan] + y_traces[level] = y_traces[level] + y + [np.nan] + elif fips_polygon_map[f].type == "MultiPolygon": + x = [ + poly.simplify(simplify_county).exterior.xy[0].tolist() + for poly in fips_polygon_map[f].geoms + ] + y = [ + poly.simplify(simplify_county).exterior.xy[1].tolist() + for poly in fips_polygon_map[f].geoms + ] + + x_c = [poly.centroid.xy[0].tolist() for poly in fips_polygon_map[f].geoms] + y_c = [poly.centroid.xy[1].tolist() for poly in fips_polygon_map[f].geoms] + + county_name_str = str(df[df["FIPS"] == f]["COUNTY_NAME"].iloc[0]) + state_name_str = str(df[df["FIPS"] == f]["STATE_NAME"].iloc[0]) + text = ( + "County: " + + county_name_str + + "
" + + "State: " + + state_name_str + + "
" + + "FIPS: " + + padded_f + + "
Value: " + + str(values[index]) + ) + t_c = [text for poly in fips_polygon_map[f].geoms] + x_centroids = x_c + x_centroids + y_centroids = y_c + y_centroids + centroid_text = t_c + centroid_text + for x_y_idx in range(len(x)): + x_traces[level] = x_traces[level] + x[x_y_idx] + [np.nan] + y_traces[level] = y_traces[level] + y[x_y_idx] + [np.nan] + + return x_traces, y_traces, x_centroids, y_centroids, centroid_text + + +def create_choropleth( + fips, + values, + scope=["usa"], + binning_endpoints=None, + colorscale=None, + order=None, + simplify_county=0.02, + simplify_state=0.02, + asp=None, + show_hover=True, + show_state_data=True, + state_outline=None, + county_outline=None, + centroid_marker=None, + round_legend_values=False, + exponent_format=False, + legend_title="", + **layout_options, +): + """ + **deprecated**, use instead + :func:`plotly.express.choropleth` with custom GeoJSON. + + This function also requires `shapely`, `geopandas` and `plotly-geo` to be installed. + + Returns figure for county choropleth. Uses data from package_data. + + :param (list) fips: list of FIPS values which correspond to the con + catination of state and county ids. An example is '01001'. + :param (list) values: list of numbers/strings which correspond to the + fips list. These are the values that will determine how the counties + are colored. + :param (list) scope: list of states and/or states abbreviations. Fits + all states in the camera tightly. Selecting ['usa'] is the equivalent + of appending all 50 states into your scope list. Selecting only 'usa' + does not include 'Alaska', 'Puerto Rico', 'American Samoa', + 'Commonwealth of the Northern Mariana Islands', 'Guam', + 'United States Virgin Islands'. These must be added manually to the + list. + Default = ['usa'] + :param (list) binning_endpoints: ascending numbers which implicitly define + real number intervals which are used as bins. The colorscale used must + have the same number of colors as the number of bins and this will + result in a categorical colormap. + :param (list) colorscale: a list of colors with length equal to the + number of categories of colors. The length must match either all + unique numbers in the 'values' list or if endpoints is being used, the + number of categories created by the endpoints.\n + For example, if binning_endpoints = [4, 6, 8], then there are 4 bins: + [-inf, 4), [4, 6), [6, 8), [8, inf) + :param (list) order: a list of the unique categories (numbers/bins) in any + desired order. This is helpful if you want to order string values to + a chosen colorscale. + :param (float) simplify_county: determines the simplification factor + for the counties. The larger the number, the fewer vertices and edges + each polygon has. See + http://toblerity.org/shapely/manual.html#object.simplify for more + information. + Default = 0.02 + :param (float) simplify_state: simplifies the state outline polygon. + See http://toblerity.org/shapely/manual.html#object.simplify for more + information. + Default = 0.02 + :param (float) asp: the width-to-height aspect ratio for the camera. + Default = 2.5 + :param (bool) show_hover: show county hover and centroid info + :param (bool) show_state_data: reveals state boundary lines + :param (dict) state_outline: dict of attributes of the state outline + including width and color. See + https://plot.ly/python/reference/#scatter-marker-line for all valid + params + :param (dict) county_outline: dict of attributes of the county outline + including width and color. See + https://plot.ly/python/reference/#scatter-marker-line for all valid + params + :param (dict) centroid_marker: dict of attributes of the centroid marker. + The centroid markers are invisible by default and appear visible on + selection. See https://plot.ly/python/reference/#scatter-marker for + all valid params + :param (bool) round_legend_values: automatically round the numbers that + appear in the legend to the nearest integer. + Default = False + :param (bool) exponent_format: if set to True, puts numbers in the K, M, + B number format. For example 4000.0 becomes 4.0K + Default = False + :param (str) legend_title: title that appears above the legend + :param **layout_options: a **kwargs argument for all layout parameters + + + Example 1: Florida:: + + import plotly.plotly as py + import plotly.figure_factory as ff + + import numpy as np + import pandas as pd + + df_sample = pd.read_csv( + 'https://raw.githubusercontent.com/plotly/datasets/master/minoritymajority.csv' + ) + df_sample_r = df_sample[df_sample['STNAME'] == 'Florida'] + + values = df_sample_r['TOT_POP'].tolist() + fips = df_sample_r['FIPS'].tolist() + + binning_endpoints = list(np.mgrid[min(values):max(values):4j]) + colorscale = ["#030512","#1d1d3b","#323268","#3d4b94","#3e6ab0", + "#4989bc","#60a7c7","#85c5d3","#b7e0e4","#eafcfd"] + fig = ff.create_choropleth( + fips=fips, values=values, scope=['Florida'], show_state_data=True, + colorscale=colorscale, binning_endpoints=binning_endpoints, + round_legend_values=True, plot_bgcolor='rgb(229,229,229)', + paper_bgcolor='rgb(229,229,229)', legend_title='Florida Population', + county_outline={'color': 'rgb(255,255,255)', 'width': 0.5}, + exponent_format=True, + ) + + Example 2: New England:: + + import plotly.figure_factory as ff + + import pandas as pd + + NE_states = ['Connecticut', 'Maine', 'Massachusetts', + 'New Hampshire', 'Rhode Island'] + df_sample = pd.read_csv( + 'https://raw.githubusercontent.com/plotly/datasets/master/minoritymajority.csv' + ) + df_sample_r = df_sample[df_sample['STNAME'].isin(NE_states)] + colorscale = ['rgb(68.0, 1.0, 84.0)', + 'rgb(66.0, 64.0, 134.0)', + 'rgb(38.0, 130.0, 142.0)', + 'rgb(63.0, 188.0, 115.0)', + 'rgb(216.0, 226.0, 25.0)'] + + values = df_sample_r['TOT_POP'].tolist() + fips = df_sample_r['FIPS'].tolist() + fig = ff.create_choropleth( + fips=fips, values=values, scope=NE_states, show_state_data=True + ) + fig.show() + + Example 3: California and Surrounding States:: + + import plotly.figure_factory as ff + + import pandas as pd + + df_sample = pd.read_csv( + 'https://raw.githubusercontent.com/plotly/datasets/master/minoritymajority.csv' + ) + df_sample_r = df_sample[df_sample['STNAME'] == 'California'] + + values = df_sample_r['TOT_POP'].tolist() + fips = df_sample_r['FIPS'].tolist() + + colorscale = [ + 'rgb(193, 193, 193)', + 'rgb(239,239,239)', + 'rgb(195, 196, 222)', + 'rgb(144,148,194)', + 'rgb(101,104,168)', + 'rgb(65, 53, 132)' + ] + + fig = ff.create_choropleth( + fips=fips, values=values, colorscale=colorscale, + scope=['CA', 'AZ', 'Nevada', 'Oregon', ' Idaho'], + binning_endpoints=[14348, 63983, 134827, 426762, 2081313], + county_outline={'color': 'rgb(255,255,255)', 'width': 0.5}, + legend_title='California Counties', + title='California and Nearby States' + ) + fig.show() + + Example 4: USA:: + + import plotly.figure_factory as ff + + import numpy as np + import pandas as pd + + df_sample = pd.read_csv( + 'https://raw.githubusercontent.com/plotly/datasets/master/laucnty16.csv' + ) + df_sample['State FIPS Code'] = df_sample['State FIPS Code'].apply( + lambda x: str(x).zfill(2) + ) + df_sample['County FIPS Code'] = df_sample['County FIPS Code'].apply( + lambda x: str(x).zfill(3) + ) + df_sample['FIPS'] = ( + df_sample['State FIPS Code'] + df_sample['County FIPS Code'] + ) + + binning_endpoints = list(np.linspace(1, 12, len(colorscale) - 1)) + colorscale = ["#f7fbff", "#ebf3fb", "#deebf7", "#d2e3f3", "#c6dbef", + "#b3d2e9", "#9ecae1", "#85bcdb", "#6baed6", "#57a0ce", + "#4292c6", "#3082be", "#2171b5", "#1361a9", "#08519c", + "#0b4083","#08306b"] + fips = df_sample['FIPS'] + values = df_sample['Unemployment Rate (%)'] + fig = ff.create_choropleth( + fips=fips, values=values, scope=['usa'], + binning_endpoints=binning_endpoints, colorscale=colorscale, + show_hover=True, centroid_marker={'opacity': 0}, + asp=2.9, title='USA by Unemployment %', + legend_title='Unemployment %' + ) + fig.show() + """ + # ensure optional modules imported + if not _plotly_geo: + raise ValueError( + """ +The create_choropleth figure factory requires the plotly-geo package. +Install using pip with: + +$ pip install plotly-geo + +Or, install using conda with + +$ conda install -c plotly plotly-geo +""" + ) + + if not gp or not shapefile or not shapely: + raise ImportError( + "geopandas, pyshp and shapely must be installed for this figure " + "factory.\n\nRun the following commands to install the correct " + "versions of the following modules:\n\n" + "```\n" + "$ pip install geopandas==0.3.0\n" + "$ pip install pyshp==1.2.10\n" + "$ pip install shapely==1.6.3\n" + "```\n" + "If you are using Windows, follow this post to properly " + "install geopandas and dependencies:" + "http://geoffboeing.com/2014/09/using-geopandas-windows/\n\n" + "If you are using Anaconda, do not use PIP to install the " + "packages above. Instead use conda to install them:\n\n" + "```\n" + "$ conda install plotly\n" + "$ conda install geopandas\n" + "```" + ) + + df, df_state = _create_us_counties_df(st_to_state_name_dict, state_to_st_dict) + + fips_polygon_map = dict(zip(df["FIPS"].tolist(), df["geometry"].tolist())) + + if not state_outline: + state_outline = {"color": "rgb(240, 240, 240)", "width": 1} + if not county_outline: + county_outline = {"color": "rgb(0, 0, 0)", "width": 0} + if not centroid_marker: + centroid_marker = {"size": 3, "color": "white", "opacity": 1} + + # ensure centroid markers appear on selection + if "opacity" not in centroid_marker: + centroid_marker.update({"opacity": 1}) + + if len(fips) != len(values): + raise PlotlyError("fips and values must be the same length") + + # make fips, values into lists + if isinstance(fips, pd.core.series.Series): + fips = fips.tolist() + if isinstance(values, pd.core.series.Series): + values = values.tolist() + + # make fips numeric + fips = map(lambda x: int(x), fips) + + if binning_endpoints: + intervals = utils.endpts_to_intervals(binning_endpoints) + LEVELS = _intervals_as_labels(intervals, round_legend_values, exponent_format) + else: + if not order: + LEVELS = sorted(list(set(values))) + else: + # check if order is permutation + # of unique color col values + same_sets = sorted(list(set(values))) == set(order) + no_duplicates = not any(order.count(x) > 1 for x in order) + if same_sets and no_duplicates: + LEVELS = order + else: + raise PlotlyError( + "if you are using a custom order of unique values from " + "your color column, you must: have all the unique values " + "in your order and have no duplicate items" + ) + + if not colorscale: + colorscale = [] + viridis_colors = clrs.colorscale_to_colors(clrs.PLOTLY_SCALES["Viridis"]) + viridis_colors = clrs.color_parser(viridis_colors, clrs.hex_to_rgb) + viridis_colors = clrs.color_parser(viridis_colors, clrs.label_rgb) + viri_len = len(viridis_colors) + 1 + viri_intervals = utils.endpts_to_intervals(list(np.linspace(0, 1, viri_len)))[ + 1:-1 + ] + + for L in np.linspace(0, 1, len(LEVELS)): + for idx, inter in enumerate(viri_intervals): + if L == 0: + break + elif inter[0] < L <= inter[1]: + break + + intermed = (L - viri_intervals[idx][0]) / ( + viri_intervals[idx][1] - viri_intervals[idx][0] + ) + + float_color = clrs.find_intermediate_color( + viridis_colors[idx], viridis_colors[idx], intermed, colortype="rgb" + ) + + # make R,G,B into int values + float_color = clrs.unlabel_rgb(float_color) + float_color = clrs.unconvert_from_RGB_255(float_color) + int_rgb = clrs.convert_to_RGB_255(float_color) + int_rgb = clrs.label_rgb(int_rgb) + + colorscale.append(int_rgb) + + if len(colorscale) < len(LEVELS): + raise PlotlyError( + "You have {} LEVELS. Your number of colors in 'colorscale' must " + "be at least the number of LEVELS: {}. If you are " + "using 'binning_endpoints' then 'colorscale' must have at " + "least len(binning_endpoints) + 2 colors".format( + len(LEVELS), min(LEVELS, LEVELS[:20]) + ) + ) + + color_lookup = dict(zip(LEVELS, colorscale)) + x_traces = dict(zip(LEVELS, [[] for i in range(len(LEVELS))])) + y_traces = dict(zip(LEVELS, [[] for i in range(len(LEVELS))])) + + # scope + if isinstance(scope, str): + raise PlotlyError("'scope' must be a list/tuple/sequence") + + scope_names = [] + extra_states = [ + "Alaska", + "Commonwealth of the Northern Mariana Islands", + "Puerto Rico", + "Guam", + "United States Virgin Islands", + "American Samoa", + ] + for state in scope: + if state.lower() == "usa": + scope_names = df["STATE_NAME"].unique() + scope_names = list(scope_names) + for ex_st in extra_states: + try: + scope_names.remove(ex_st) + except ValueError: + pass + else: + if state in st_to_state_name_dict.keys(): + state = st_to_state_name_dict[state] + scope_names.append(state) + df_state = df_state[df_state["STATE_NAME"].isin(scope_names)] + + plot_data = [] + x_centroids = [] + y_centroids = [] + centroid_text = [] + fips_not_in_shapefile = [] + if not binning_endpoints: + for index, f in enumerate(fips): + level = values[index] + try: + fips_polygon_map[f].type + + ( + x_traces, + y_traces, + x_centroids, + y_centroids, + centroid_text, + ) = _calculations( + df, + fips, + values, + index, + f, + simplify_county, + level, + x_centroids, + y_centroids, + centroid_text, + x_traces, + y_traces, + fips_polygon_map, + ) + except KeyError: + fips_not_in_shapefile.append(f) + + else: + for index, f in enumerate(fips): + for j, inter in enumerate(intervals): + if inter[0] < values[index] <= inter[1]: + break + level = LEVELS[j] + + try: + fips_polygon_map[f].type + + ( + x_traces, + y_traces, + x_centroids, + y_centroids, + centroid_text, + ) = _calculations( + df, + fips, + values, + index, + f, + simplify_county, + level, + x_centroids, + y_centroids, + centroid_text, + x_traces, + y_traces, + fips_polygon_map, + ) + except KeyError: + fips_not_in_shapefile.append(f) + + if len(fips_not_in_shapefile) > 0: + msg = ( + "Unrecognized FIPS Values\n\nWhoops! It looks like you are " + "trying to pass at least one FIPS value that is not in " + "our shapefile of FIPS and data for the counties. Your " + "choropleth will still show up but these counties cannot " + "be shown.\nUnrecognized FIPS are: {}".format(fips_not_in_shapefile) + ) + warnings.warn(msg) + + x_states = [] + y_states = [] + for index, row in df_state.iterrows(): + if df_state["geometry"][index].type == "Polygon": + x = row.geometry.simplify(simplify_state).exterior.xy[0].tolist() + y = row.geometry.simplify(simplify_state).exterior.xy[1].tolist() + x_states = x_states + x + y_states = y_states + y + elif df_state["geometry"][index].type == "MultiPolygon": + x = [ + poly.simplify(simplify_state).exterior.xy[0].tolist() + for poly in df_state["geometry"][index].geoms + ] + y = [ + poly.simplify(simplify_state).exterior.xy[1].tolist() + for poly in df_state["geometry"][index].geoms + ] + for segment in range(len(x)): + x_states = x_states + x[segment] + y_states = y_states + y[segment] + x_states.append(np.nan) + y_states.append(np.nan) + x_states.append(np.nan) + y_states.append(np.nan) + + for lev in LEVELS: + county_data = dict( + type="scatter", + mode="lines", + x=x_traces[lev], + y=y_traces[lev], + line=county_outline, + fill="toself", + fillcolor=color_lookup[lev], + name=lev, + hoverinfo="none", + ) + plot_data.append(county_data) + + if show_hover: + hover_points = dict( + type="scatter", + showlegend=False, + legendgroup="centroids", + x=x_centroids, + y=y_centroids, + text=centroid_text, + name="US Counties", + mode="markers", + marker={"color": "white", "opacity": 0}, + hoverinfo="text", + ) + centroids_on_select = dict( + selected=dict(marker=centroid_marker), + unselected=dict(marker=dict(opacity=0)), + ) + hover_points.update(centroids_on_select) + plot_data.append(hover_points) + + if show_state_data: + state_data = dict( + type="scatter", + legendgroup="States", + line=state_outline, + x=x_states, + y=y_states, + hoverinfo="text", + showlegend=False, + mode="lines", + ) + plot_data.append(state_data) + + DEFAULT_LAYOUT = dict( + hovermode="closest", + xaxis=dict( + autorange=False, + range=USA_XRANGE, + showgrid=False, + zeroline=False, + fixedrange=True, + showticklabels=False, + ), + yaxis=dict( + autorange=False, + range=USA_YRANGE, + showgrid=False, + zeroline=False, + fixedrange=True, + showticklabels=False, + ), + margin=dict(t=40, b=20, r=20, l=20), + width=900, + height=450, + dragmode="select", + legend=dict(traceorder="reversed", xanchor="right", yanchor="top", x=1, y=1), + annotations=[], + ) + fig = dict(data=plot_data, layout=DEFAULT_LAYOUT) + fig["layout"].update(layout_options) + fig["layout"]["annotations"].append( + dict( + x=1, + y=1.05, + xref="paper", + yref="paper", + xanchor="right", + showarrow=False, + text="" + legend_title + "", + ) + ) + + if len(scope) == 1 and scope[0].lower() == "usa": + xaxis_range_low = -125.0 + xaxis_range_high = -55.0 + yaxis_range_low = 25.0 + yaxis_range_high = 49.0 + else: + xaxis_range_low = float("inf") + xaxis_range_high = float("-inf") + yaxis_range_low = float("inf") + yaxis_range_high = float("-inf") + for trace in fig["data"]: + if all(isinstance(n, Number) for n in trace["x"]): + calc_x_min = min(trace["x"] or [float("inf")]) + calc_x_max = max(trace["x"] or [float("-inf")]) + if calc_x_min < xaxis_range_low: + xaxis_range_low = calc_x_min + if calc_x_max > xaxis_range_high: + xaxis_range_high = calc_x_max + if all(isinstance(n, Number) for n in trace["y"]): + calc_y_min = min(trace["y"] or [float("inf")]) + calc_y_max = max(trace["y"] or [float("-inf")]) + if calc_y_min < yaxis_range_low: + yaxis_range_low = calc_y_min + if calc_y_max > yaxis_range_high: + yaxis_range_high = calc_y_max + + # camera zoom + fig["layout"]["xaxis"]["range"] = [xaxis_range_low, xaxis_range_high] + fig["layout"]["yaxis"]["range"] = [yaxis_range_low, yaxis_range_high] + + # aspect ratio + if asp is None: + usa_x_range = USA_XRANGE[1] - USA_XRANGE[0] + usa_y_range = USA_YRANGE[1] - USA_YRANGE[0] + asp = usa_x_range / usa_y_range + + # based on your figure + width = float( + fig["layout"]["xaxis"]["range"][1] - fig["layout"]["xaxis"]["range"][0] + ) + height = float( + fig["layout"]["yaxis"]["range"][1] - fig["layout"]["yaxis"]["range"][0] + ) + + center = ( + sum(fig["layout"]["xaxis"]["range"]) / 2.0, + sum(fig["layout"]["yaxis"]["range"]) / 2.0, + ) + + if height / width > (1 / asp): + new_width = asp * height + fig["layout"]["xaxis"]["range"][0] = center[0] - new_width * 0.5 + fig["layout"]["xaxis"]["range"][1] = center[0] + new_width * 0.5 + else: + new_height = (1 / asp) * width + fig["layout"]["yaxis"]["range"][0] = center[1] - new_height * 0.5 + fig["layout"]["yaxis"]["range"][1] = center[1] + new_height * 0.5 + + return go.Figure(fig) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_dendrogram.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_dendrogram.py new file mode 100644 index 0000000000000000000000000000000000000000..fd6d5050b865ebbbd88bd9c6aeebac24e3994ce2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_dendrogram.py @@ -0,0 +1,395 @@ +from collections import OrderedDict + +from plotly import exceptions, optional_imports +from plotly.graph_objs import graph_objs + +# Optional imports, may be None for users that only use our core functionality. +np = optional_imports.get_module("numpy") +scp = optional_imports.get_module("scipy") +sch = optional_imports.get_module("scipy.cluster.hierarchy") +scs = optional_imports.get_module("scipy.spatial") + + +def create_dendrogram( + X, + orientation="bottom", + labels=None, + colorscale=None, + distfun=None, + linkagefun=lambda x: sch.linkage(x, "complete"), + hovertext=None, + color_threshold=None, +): + """ + Function that returns a dendrogram Plotly figure object. This is a thin + wrapper around scipy.cluster.hierarchy.dendrogram. + + See also https://dash.plot.ly/dash-bio/clustergram. + + :param (ndarray) X: Matrix of observations as array of arrays + :param (str) orientation: 'top', 'right', 'bottom', or 'left' + :param (list) labels: List of axis category labels(observation labels) + :param (list) colorscale: Optional colorscale for the dendrogram tree. + Requires 8 colors to be specified, the 7th of + which is ignored. With scipy>=1.5.0, the 2nd, 3rd + and 6th are used twice as often as the others. + Given a shorter list, the missing values are + replaced with defaults and with a longer list the + extra values are ignored. + :param (function) distfun: Function to compute the pairwise distance from + the observations + :param (function) linkagefun: Function to compute the linkage matrix from + the pairwise distances + :param (list[list]) hovertext: List of hovertext for constituent traces of dendrogram + clusters + :param (double) color_threshold: Value at which the separation of clusters will be made + + Example 1: Simple bottom oriented dendrogram + + >>> from plotly.figure_factory import create_dendrogram + + >>> import numpy as np + + >>> X = np.random.rand(10,10) + >>> fig = create_dendrogram(X) + >>> fig.show() + + Example 2: Dendrogram to put on the left of the heatmap + + >>> from plotly.figure_factory import create_dendrogram + + >>> import numpy as np + + >>> X = np.random.rand(5,5) + >>> names = ['Jack', 'Oxana', 'John', 'Chelsea', 'Mark'] + >>> dendro = create_dendrogram(X, orientation='right', labels=names) + >>> dendro.update_layout({'width':700, 'height':500}) # doctest: +SKIP + >>> dendro.show() + + Example 3: Dendrogram with Pandas + + >>> from plotly.figure_factory import create_dendrogram + + >>> import numpy as np + >>> import pandas as pd + + >>> Index= ['A','B','C','D','E','F','G','H','I','J'] + >>> df = pd.DataFrame(abs(np.random.randn(10, 10)), index=Index) + >>> fig = create_dendrogram(df, labels=Index) + >>> fig.show() + """ + if not scp or not scs or not sch: + raise ImportError( + "FigureFactory.create_dendrogram requires scipy, \ + scipy.spatial and scipy.hierarchy" + ) + + s = X.shape + if len(s) != 2: + exceptions.PlotlyError("X should be 2-dimensional array.") + + if distfun is None: + distfun = scs.distance.pdist + + dendrogram = _Dendrogram( + X, + orientation, + labels, + colorscale, + distfun=distfun, + linkagefun=linkagefun, + hovertext=hovertext, + color_threshold=color_threshold, + ) + + return graph_objs.Figure(data=dendrogram.data, layout=dendrogram.layout) + + +class _Dendrogram(object): + """Refer to FigureFactory.create_dendrogram() for docstring.""" + + def __init__( + self, + X, + orientation="bottom", + labels=None, + colorscale=None, + width=np.inf, + height=np.inf, + xaxis="xaxis", + yaxis="yaxis", + distfun=None, + linkagefun=lambda x: sch.linkage(x, "complete"), + hovertext=None, + color_threshold=None, + ): + self.orientation = orientation + self.labels = labels + self.xaxis = xaxis + self.yaxis = yaxis + self.data = [] + self.leaves = [] + self.sign = {self.xaxis: 1, self.yaxis: 1} + self.layout = {self.xaxis: {}, self.yaxis: {}} + + if self.orientation in ["left", "bottom"]: + self.sign[self.xaxis] = 1 + else: + self.sign[self.xaxis] = -1 + + if self.orientation in ["right", "bottom"]: + self.sign[self.yaxis] = 1 + else: + self.sign[self.yaxis] = -1 + + if distfun is None: + distfun = scs.distance.pdist + + (dd_traces, xvals, yvals, ordered_labels, leaves) = self.get_dendrogram_traces( + X, colorscale, distfun, linkagefun, hovertext, color_threshold + ) + + self.labels = ordered_labels + self.leaves = leaves + yvals_flat = yvals.flatten() + xvals_flat = xvals.flatten() + + self.zero_vals = [] + + for i in range(len(yvals_flat)): + if yvals_flat[i] == 0.0 and xvals_flat[i] not in self.zero_vals: + self.zero_vals.append(xvals_flat[i]) + + if len(self.zero_vals) > len(yvals) + 1: + # If the length of zero_vals is larger than the length of yvals, + # it means that there are wrong vals because of the identicial samples. + # Three and more identicial samples will make the yvals of spliting + # center into 0 and it will accidentally take it as leaves. + l_border = int(min(self.zero_vals)) + r_border = int(max(self.zero_vals)) + correct_leaves_pos = range( + l_border, r_border + 1, int((r_border - l_border) / len(yvals)) + ) + # Regenerating the leaves pos from the self.zero_vals with equally intervals. + self.zero_vals = [v for v in correct_leaves_pos] + + self.zero_vals.sort() + self.layout = self.set_figure_layout(width, height) + self.data = dd_traces + + def get_color_dict(self, colorscale): + """ + Returns colorscale used for dendrogram tree clusters. + + :param (list) colorscale: Colors to use for the plot in rgb format. + :rtype (dict): A dict of default colors mapped to the user colorscale. + + """ + + # These are the color codes returned for dendrograms + # We're replacing them with nicer colors + # This list is the colors that can be used by dendrogram, which were + # determined as the combination of the default above_threshold_color and + # the default color palette (see scipy/cluster/hierarchy.py) + d = { + "r": "red", + "g": "green", + "b": "blue", + "c": "cyan", + "m": "magenta", + "y": "yellow", + "k": "black", + # TODO: 'w' doesn't seem to be in the default color + # palette in scipy/cluster/hierarchy.py + "w": "white", + } + default_colors = OrderedDict(sorted(d.items(), key=lambda t: t[0])) + + if colorscale is None: + rgb_colorscale = [ + "rgb(0,116,217)", # blue + "rgb(35,205,205)", # cyan + "rgb(61,153,112)", # green + "rgb(40,35,35)", # black + "rgb(133,20,75)", # magenta + "rgb(255,65,54)", # red + "rgb(255,255,255)", # white + "rgb(255,220,0)", # yellow + ] + else: + rgb_colorscale = colorscale + + for i in range(len(default_colors.keys())): + k = list(default_colors.keys())[i] # PY3 won't index keys + if i < len(rgb_colorscale): + default_colors[k] = rgb_colorscale[i] + + # add support for cyclic format colors as introduced in scipy===1.5.0 + # before this, the colors were named 'r', 'b', 'y' etc., now they are + # named 'C0', 'C1', etc. To keep the colors consistent regardless of the + # scipy version, we try as much as possible to map the new colors to the + # old colors + # this mapping was found by inpecting scipy/cluster/hierarchy.py (see + # comment above). + new_old_color_map = [ + ("C0", "b"), + ("C1", "g"), + ("C2", "r"), + ("C3", "c"), + ("C4", "m"), + ("C5", "y"), + ("C6", "k"), + ("C7", "g"), + ("C8", "r"), + ("C9", "c"), + ] + for nc, oc in new_old_color_map: + try: + default_colors[nc] = default_colors[oc] + except KeyError: + # it could happen that the old color isn't found (if a custom + # colorscale was specified), in this case we set it to an + # arbitrary default. + default_colors[nc] = "rgb(0,116,217)" + + return default_colors + + def set_axis_layout(self, axis_key): + """ + Sets and returns default axis object for dendrogram figure. + + :param (str) axis_key: E.g., 'xaxis', 'xaxis1', 'yaxis', yaxis1', etc. + :rtype (dict): An axis_key dictionary with set parameters. + + """ + axis_defaults = { + "type": "linear", + "ticks": "outside", + "mirror": "allticks", + "rangemode": "tozero", + "showticklabels": True, + "zeroline": False, + "showgrid": False, + "showline": True, + } + + if len(self.labels) != 0: + axis_key_labels = self.xaxis + if self.orientation in ["left", "right"]: + axis_key_labels = self.yaxis + if axis_key_labels not in self.layout: + self.layout[axis_key_labels] = {} + self.layout[axis_key_labels]["tickvals"] = [ + zv * self.sign[axis_key] for zv in self.zero_vals + ] + self.layout[axis_key_labels]["ticktext"] = self.labels + self.layout[axis_key_labels]["tickmode"] = "array" + + self.layout[axis_key].update(axis_defaults) + + return self.layout[axis_key] + + def set_figure_layout(self, width, height): + """ + Sets and returns default layout object for dendrogram figure. + + """ + self.layout.update( + { + "showlegend": False, + "autosize": False, + "hovermode": "closest", + "width": width, + "height": height, + } + ) + + self.set_axis_layout(self.xaxis) + self.set_axis_layout(self.yaxis) + + return self.layout + + def get_dendrogram_traces( + self, X, colorscale, distfun, linkagefun, hovertext, color_threshold + ): + """ + Calculates all the elements needed for plotting a dendrogram. + + :param (ndarray) X: Matrix of observations as array of arrays + :param (list) colorscale: Color scale for dendrogram tree clusters + :param (function) distfun: Function to compute the pairwise distance + from the observations + :param (function) linkagefun: Function to compute the linkage matrix + from the pairwise distances + :param (list) hovertext: List of hovertext for constituent traces of dendrogram + :rtype (tuple): Contains all the traces in the following order: + (a) trace_list: List of Plotly trace objects for dendrogram tree + (b) icoord: All X points of the dendrogram tree as array of arrays + with length 4 + (c) dcoord: All Y points of the dendrogram tree as array of arrays + with length 4 + (d) ordered_labels: leaf labels in the order they are going to + appear on the plot + (e) P['leaves']: left-to-right traversal of the leaves + + """ + d = distfun(X) + Z = linkagefun(d) + P = sch.dendrogram( + Z, + orientation=self.orientation, + labels=self.labels, + no_plot=True, + color_threshold=color_threshold, + ) + + icoord = np.array(P["icoord"]) + dcoord = np.array(P["dcoord"]) + ordered_labels = np.array(P["ivl"]) + color_list = np.array(P["color_list"]) + colors = self.get_color_dict(colorscale) + + trace_list = [] + + for i in range(len(icoord)): + # xs and ys are arrays of 4 points that make up the '∩' shapes + # of the dendrogram tree + if self.orientation in ["top", "bottom"]: + xs = icoord[i] + else: + xs = dcoord[i] + + if self.orientation in ["top", "bottom"]: + ys = dcoord[i] + else: + ys = icoord[i] + color_key = color_list[i] + hovertext_label = None + if hovertext: + hovertext_label = hovertext[i] + trace = dict( + type="scatter", + x=np.multiply(self.sign[self.xaxis], xs), + y=np.multiply(self.sign[self.yaxis], ys), + mode="lines", + marker=dict(color=colors[color_key]), + text=hovertext_label, + hoverinfo="text", + ) + + try: + x_index = int(self.xaxis[-1]) + except ValueError: + x_index = "" + + try: + y_index = int(self.yaxis[-1]) + except ValueError: + y_index = "" + + trace["xaxis"] = f"x{x_index}" + trace["yaxis"] = f"y{y_index}" + + trace_list.append(trace) + + return trace_list, icoord, dcoord, ordered_labels, P["leaves"] diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_distplot.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_distplot.py new file mode 100644 index 0000000000000000000000000000000000000000..73f660964560e0f7d66dfd6ba6cced9ad9e62286 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_distplot.py @@ -0,0 +1,441 @@ +from plotly import exceptions, optional_imports +from plotly.figure_factory import utils +from plotly.graph_objs import graph_objs + +# Optional imports, may be None for users that only use our core functionality. +np = optional_imports.get_module("numpy") +pd = optional_imports.get_module("pandas") +scipy = optional_imports.get_module("scipy") +scipy_stats = optional_imports.get_module("scipy.stats") + + +DEFAULT_HISTNORM = "probability density" +ALTERNATIVE_HISTNORM = "probability" + + +def validate_distplot(hist_data, curve_type): + """ + Distplot-specific validations + + :raises: (PlotlyError) If hist_data is not a list of lists + :raises: (PlotlyError) If curve_type is not valid (i.e. not 'kde' or + 'normal'). + """ + hist_data_types = (list,) + if np: + hist_data_types += (np.ndarray,) + if pd: + hist_data_types += (pd.core.series.Series,) + + if not isinstance(hist_data[0], hist_data_types): + raise exceptions.PlotlyError( + "Oops, this function was written " + "to handle multiple datasets, if " + "you want to plot just one, make " + "sure your hist_data variable is " + "still a list of lists, i.e. x = " + "[1, 2, 3] -> x = [[1, 2, 3]]" + ) + + curve_opts = ("kde", "normal") + if curve_type not in curve_opts: + raise exceptions.PlotlyError("curve_type must be defined as 'kde' or 'normal'") + + if not scipy: + raise ImportError("FigureFactory.create_distplot requires scipy") + + +def create_distplot( + hist_data, + group_labels, + bin_size=1.0, + curve_type="kde", + colors=None, + rug_text=None, + histnorm=DEFAULT_HISTNORM, + show_hist=True, + show_curve=True, + show_rug=True, +): + """ + Function that creates a distplot similar to seaborn.distplot; + **this function is deprecated**, use instead :mod:`plotly.express` + functions, for example + + >>> import plotly.express as px + >>> tips = px.data.tips() + >>> fig = px.histogram(tips, x="total_bill", y="tip", color="sex", marginal="rug", + ... hover_data=tips.columns) + >>> fig.show() + + + The distplot can be composed of all or any combination of the following + 3 components: (1) histogram, (2) curve: (a) kernel density estimation + or (b) normal curve, and (3) rug plot. Additionally, multiple distplots + (from multiple datasets) can be created in the same plot. + + :param (list[list]) hist_data: Use list of lists to plot multiple data + sets on the same plot. + :param (list[str]) group_labels: Names for each data set. + :param (list[float]|float) bin_size: Size of histogram bins. + Default = 1. + :param (str) curve_type: 'kde' or 'normal'. Default = 'kde' + :param (str) histnorm: 'probability density' or 'probability' + Default = 'probability density' + :param (bool) show_hist: Add histogram to distplot? Default = True + :param (bool) show_curve: Add curve to distplot? Default = True + :param (bool) show_rug: Add rug to distplot? Default = True + :param (list[str]) colors: Colors for traces. + :param (list[list]) rug_text: Hovertext values for rug_plot, + :return (dict): Representation of a distplot figure. + + Example 1: Simple distplot of 1 data set + + >>> from plotly.figure_factory import create_distplot + + >>> hist_data = [[1.1, 1.1, 2.5, 3.0, 3.5, + ... 3.5, 4.1, 4.4, 4.5, 4.5, + ... 5.0, 5.0, 5.2, 5.5, 5.5, + ... 5.5, 5.5, 5.5, 6.1, 7.0]] + >>> group_labels = ['distplot example'] + >>> fig = create_distplot(hist_data, group_labels) + >>> fig.show() + + + Example 2: Two data sets and added rug text + + >>> from plotly.figure_factory import create_distplot + >>> # Add histogram data + >>> hist1_x = [0.8, 1.2, 0.2, 0.6, 1.6, + ... -0.9, -0.07, 1.95, 0.9, -0.2, + ... -0.5, 0.3, 0.4, -0.37, 0.6] + >>> hist2_x = [0.8, 1.5, 1.5, 0.6, 0.59, + ... 1.0, 0.8, 1.7, 0.5, 0.8, + ... -0.3, 1.2, 0.56, 0.3, 2.2] + + >>> # Group data together + >>> hist_data = [hist1_x, hist2_x] + + >>> group_labels = ['2012', '2013'] + + >>> # Add text + >>> rug_text_1 = ['a1', 'b1', 'c1', 'd1', 'e1', + ... 'f1', 'g1', 'h1', 'i1', 'j1', + ... 'k1', 'l1', 'm1', 'n1', 'o1'] + + >>> rug_text_2 = ['a2', 'b2', 'c2', 'd2', 'e2', + ... 'f2', 'g2', 'h2', 'i2', 'j2', + ... 'k2', 'l2', 'm2', 'n2', 'o2'] + + >>> # Group text together + >>> rug_text_all = [rug_text_1, rug_text_2] + + >>> # Create distplot + >>> fig = create_distplot( + ... hist_data, group_labels, rug_text=rug_text_all, bin_size=.2) + + >>> # Add title + >>> fig.update_layout(title='Dist Plot') # doctest: +SKIP + >>> fig.show() + + + Example 3: Plot with normal curve and hide rug plot + + >>> from plotly.figure_factory import create_distplot + >>> import numpy as np + + >>> x1 = np.random.randn(190) + >>> x2 = np.random.randn(200)+1 + >>> x3 = np.random.randn(200)-1 + >>> x4 = np.random.randn(210)+2 + + >>> hist_data = [x1, x2, x3, x4] + >>> group_labels = ['2012', '2013', '2014', '2015'] + + >>> fig = create_distplot( + ... hist_data, group_labels, curve_type='normal', + ... show_rug=False, bin_size=.4) + + + Example 4: Distplot with Pandas + + >>> from plotly.figure_factory import create_distplot + >>> import numpy as np + >>> import pandas as pd + + >>> df = pd.DataFrame({'2012': np.random.randn(200), + ... '2013': np.random.randn(200)+1}) + >>> fig = create_distplot([df[c] for c in df.columns], df.columns) + >>> fig.show() + """ + if colors is None: + colors = [] + if rug_text is None: + rug_text = [] + + validate_distplot(hist_data, curve_type) + utils.validate_equal_length(hist_data, group_labels) + + if isinstance(bin_size, (float, int)): + bin_size = [bin_size] * len(hist_data) + + data = [] + if show_hist: + hist = _Distplot( + hist_data, + histnorm, + group_labels, + bin_size, + curve_type, + colors, + rug_text, + show_hist, + show_curve, + ).make_hist() + + data.append(hist) + + if show_curve: + if curve_type == "normal": + curve = _Distplot( + hist_data, + histnorm, + group_labels, + bin_size, + curve_type, + colors, + rug_text, + show_hist, + show_curve, + ).make_normal() + else: + curve = _Distplot( + hist_data, + histnorm, + group_labels, + bin_size, + curve_type, + colors, + rug_text, + show_hist, + show_curve, + ).make_kde() + + data.append(curve) + + if show_rug: + rug = _Distplot( + hist_data, + histnorm, + group_labels, + bin_size, + curve_type, + colors, + rug_text, + show_hist, + show_curve, + ).make_rug() + + data.append(rug) + layout = graph_objs.Layout( + barmode="overlay", + hovermode="closest", + legend=dict(traceorder="reversed"), + xaxis1=dict(domain=[0.0, 1.0], anchor="y2", zeroline=False), + yaxis1=dict(domain=[0.35, 1], anchor="free", position=0.0), + yaxis2=dict(domain=[0, 0.25], anchor="x1", dtick=1, showticklabels=False), + ) + else: + layout = graph_objs.Layout( + barmode="overlay", + hovermode="closest", + legend=dict(traceorder="reversed"), + xaxis1=dict(domain=[0.0, 1.0], anchor="y2", zeroline=False), + yaxis1=dict(domain=[0.0, 1], anchor="free", position=0.0), + ) + + data = sum(data, []) + return graph_objs.Figure(data=data, layout=layout) + + +class _Distplot(object): + """ + Refer to TraceFactory.create_distplot() for docstring + """ + + def __init__( + self, + hist_data, + histnorm, + group_labels, + bin_size, + curve_type, + colors, + rug_text, + show_hist, + show_curve, + ): + self.hist_data = hist_data + self.histnorm = histnorm + self.group_labels = group_labels + self.bin_size = bin_size + self.show_hist = show_hist + self.show_curve = show_curve + self.trace_number = len(hist_data) + if rug_text: + self.rug_text = rug_text + else: + self.rug_text = [None] * self.trace_number + + self.start = [] + self.end = [] + if colors: + self.colors = colors + else: + self.colors = [ + "rgb(31, 119, 180)", + "rgb(255, 127, 14)", + "rgb(44, 160, 44)", + "rgb(214, 39, 40)", + "rgb(148, 103, 189)", + "rgb(140, 86, 75)", + "rgb(227, 119, 194)", + "rgb(127, 127, 127)", + "rgb(188, 189, 34)", + "rgb(23, 190, 207)", + ] + self.curve_x = [None] * self.trace_number + self.curve_y = [None] * self.trace_number + + for trace in self.hist_data: + self.start.append(min(trace) * 1.0) + self.end.append(max(trace) * 1.0) + + def make_hist(self): + """ + Makes the histogram(s) for FigureFactory.create_distplot(). + + :rtype (list) hist: list of histogram representations + """ + hist = [None] * self.trace_number + + for index in range(self.trace_number): + hist[index] = dict( + type="histogram", + x=self.hist_data[index], + xaxis="x1", + yaxis="y1", + histnorm=self.histnorm, + name=self.group_labels[index], + legendgroup=self.group_labels[index], + marker=dict(color=self.colors[index % len(self.colors)]), + autobinx=False, + xbins=dict( + start=self.start[index], + end=self.end[index], + size=self.bin_size[index], + ), + opacity=0.7, + ) + return hist + + def make_kde(self): + """ + Makes the kernel density estimation(s) for create_distplot(). + + This is called when curve_type = 'kde' in create_distplot(). + + :rtype (list) curve: list of kde representations + """ + curve = [None] * self.trace_number + for index in range(self.trace_number): + self.curve_x[index] = [ + self.start[index] + x * (self.end[index] - self.start[index]) / 500 + for x in range(500) + ] + self.curve_y[index] = scipy_stats.gaussian_kde(self.hist_data[index])( + self.curve_x[index] + ) + + if self.histnorm == ALTERNATIVE_HISTNORM: + self.curve_y[index] *= self.bin_size[index] + + for index in range(self.trace_number): + curve[index] = dict( + type="scatter", + x=self.curve_x[index], + y=self.curve_y[index], + xaxis="x1", + yaxis="y1", + mode="lines", + name=self.group_labels[index], + legendgroup=self.group_labels[index], + showlegend=False if self.show_hist else True, + marker=dict(color=self.colors[index % len(self.colors)]), + ) + return curve + + def make_normal(self): + """ + Makes the normal curve(s) for create_distplot(). + + This is called when curve_type = 'normal' in create_distplot(). + + :rtype (list) curve: list of normal curve representations + """ + curve = [None] * self.trace_number + mean = [None] * self.trace_number + sd = [None] * self.trace_number + + for index in range(self.trace_number): + mean[index], sd[index] = scipy_stats.norm.fit(self.hist_data[index]) + self.curve_x[index] = [ + self.start[index] + x * (self.end[index] - self.start[index]) / 500 + for x in range(500) + ] + self.curve_y[index] = scipy_stats.norm.pdf( + self.curve_x[index], loc=mean[index], scale=sd[index] + ) + + if self.histnorm == ALTERNATIVE_HISTNORM: + self.curve_y[index] *= self.bin_size[index] + + for index in range(self.trace_number): + curve[index] = dict( + type="scatter", + x=self.curve_x[index], + y=self.curve_y[index], + xaxis="x1", + yaxis="y1", + mode="lines", + name=self.group_labels[index], + legendgroup=self.group_labels[index], + showlegend=False if self.show_hist else True, + marker=dict(color=self.colors[index % len(self.colors)]), + ) + return curve + + def make_rug(self): + """ + Makes the rug plot(s) for create_distplot(). + + :rtype (list) rug: list of rug plot representations + """ + rug = [None] * self.trace_number + for index in range(self.trace_number): + rug[index] = dict( + type="scatter", + x=self.hist_data[index], + y=([self.group_labels[index]] * len(self.hist_data[index])), + xaxis="x1", + yaxis="y2", + mode="markers", + name=self.group_labels[index], + legendgroup=self.group_labels[index], + showlegend=(False if self.show_hist or self.show_curve else True), + text=self.rug_text[index], + marker=dict( + color=self.colors[index % len(self.colors)], symbol="line-ns-open" + ), + ) + return rug diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_facet_grid.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_facet_grid.py new file mode 100644 index 0000000000000000000000000000000000000000..06dc71d2ac34cb2461618da5222e9ade4acc9c41 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_facet_grid.py @@ -0,0 +1,1195 @@ +from plotly import exceptions, optional_imports +import plotly.colors as clrs +from plotly.figure_factory import utils +from plotly.subplots import make_subplots + +import math +from numbers import Number + +pd = optional_imports.get_module("pandas") + +TICK_COLOR = "#969696" +AXIS_TITLE_COLOR = "#0f0f0f" +AXIS_TITLE_SIZE = 12 +GRID_COLOR = "#ffffff" +LEGEND_COLOR = "#efefef" +PLOT_BGCOLOR = "#ededed" +ANNOT_RECT_COLOR = "#d0d0d0" +LEGEND_BORDER_WIDTH = 1 +LEGEND_ANNOT_X = 1.05 +LEGEND_ANNOT_Y = 0.5 +MAX_TICKS_PER_AXIS = 5 +THRES_FOR_FLIPPED_FACET_TITLES = 10 +GRID_WIDTH = 1 + +VALID_TRACE_TYPES = ["scatter", "scattergl", "histogram", "bar", "box"] + +CUSTOM_LABEL_ERROR = ( + "If you are using a dictionary for custom labels for the facet row/col, " + "make sure each key in that column of the dataframe is in your facet " + "labels. The keys you need are {}" +) + + +def _is_flipped(num): + if num >= THRES_FOR_FLIPPED_FACET_TITLES: + flipped = True + else: + flipped = False + return flipped + + +def _return_label(original_label, facet_labels, facet_var): + if isinstance(facet_labels, dict): + label = facet_labels[original_label] + elif isinstance(facet_labels, str): + label = "{}: {}".format(facet_var, original_label) + else: + label = original_label + return label + + +def _legend_annotation(color_name): + legend_title = dict( + textangle=0, + xanchor="left", + yanchor="middle", + x=LEGEND_ANNOT_X, + y=1.03, + showarrow=False, + xref="paper", + yref="paper", + text="factor({})".format(color_name), + font=dict(size=13, color="#000000"), + ) + return legend_title + + +def _annotation_dict( + text, lane, num_of_lanes, SUBPLOT_SPACING, row_col="col", flipped=True +): + temp = (1 - (num_of_lanes - 1) * SUBPLOT_SPACING) / (num_of_lanes) + if not flipped: + xanchor = "center" + yanchor = "middle" + if row_col == "col": + x = (lane - 1) * (temp + SUBPLOT_SPACING) + 0.5 * temp + y = 1.03 + textangle = 0 + elif row_col == "row": + y = (lane - 1) * (temp + SUBPLOT_SPACING) + 0.5 * temp + x = 1.03 + textangle = 90 + else: + if row_col == "col": + xanchor = "center" + yanchor = "bottom" + x = (lane - 1) * (temp + SUBPLOT_SPACING) + 0.5 * temp + y = 1.0 + textangle = 270 + elif row_col == "row": + xanchor = "left" + yanchor = "middle" + y = (lane - 1) * (temp + SUBPLOT_SPACING) + 0.5 * temp + x = 1.0 + textangle = 0 + + annotation_dict = dict( + textangle=textangle, + xanchor=xanchor, + yanchor=yanchor, + x=x, + y=y, + showarrow=False, + xref="paper", + yref="paper", + text=str(text), + font=dict(size=13, color=AXIS_TITLE_COLOR), + ) + return annotation_dict + + +def _axis_title_annotation(text, x_or_y_axis): + if x_or_y_axis == "x": + x_pos = 0.5 + y_pos = -0.1 + textangle = 0 + elif x_or_y_axis == "y": + x_pos = -0.1 + y_pos = 0.5 + textangle = 270 + + if not text: + text = "" + + annot = { + "font": {"color": "#000000", "size": AXIS_TITLE_SIZE}, + "showarrow": False, + "text": text, + "textangle": textangle, + "x": x_pos, + "xanchor": "center", + "xref": "paper", + "y": y_pos, + "yanchor": "middle", + "yref": "paper", + } + return annot + + +def _add_shapes_to_fig(fig, annot_rect_color, flipped_rows=False, flipped_cols=False): + shapes_list = [] + for key in fig["layout"].to_plotly_json().keys(): + if "axis" in key and fig["layout"][key]["domain"] != [0.0, 1.0]: + shape = { + "fillcolor": annot_rect_color, + "layer": "below", + "line": {"color": annot_rect_color, "width": 1}, + "type": "rect", + "xref": "paper", + "yref": "paper", + } + + if "xaxis" in key: + shape["x0"] = fig["layout"][key]["domain"][0] + shape["x1"] = fig["layout"][key]["domain"][1] + shape["y0"] = 1.005 + shape["y1"] = 1.05 + + if flipped_cols: + shape["y1"] += 0.5 + shapes_list.append(shape) + + elif "yaxis" in key: + shape["x0"] = 1.005 + shape["x1"] = 1.05 + shape["y0"] = fig["layout"][key]["domain"][0] + shape["y1"] = fig["layout"][key]["domain"][1] + + if flipped_rows: + shape["x1"] += 1 + shapes_list.append(shape) + + fig["layout"]["shapes"] = shapes_list + + +def _make_trace_for_scatter(trace, trace_type, color, **kwargs_marker): + if trace_type in ["scatter", "scattergl"]: + trace["mode"] = "markers" + trace["marker"] = dict(color=color, **kwargs_marker) + return trace + + +def _facet_grid_color_categorical( + df, + x, + y, + facet_row, + facet_col, + color_name, + colormap, + num_of_rows, + num_of_cols, + facet_row_labels, + facet_col_labels, + trace_type, + flipped_rows, + flipped_cols, + show_boxes, + SUBPLOT_SPACING, + marker_color, + kwargs_trace, + kwargs_marker, +): + fig = make_subplots( + rows=num_of_rows, + cols=num_of_cols, + shared_xaxes=True, + shared_yaxes=True, + horizontal_spacing=SUBPLOT_SPACING, + vertical_spacing=SUBPLOT_SPACING, + print_grid=False, + ) + + annotations = [] + if not facet_row and not facet_col: + color_groups = list(df.groupby(color_name)) + for group in color_groups: + trace = dict( + type=trace_type, + name=group[0], + marker=dict(color=colormap[group[0]]), + **kwargs_trace, + ) + if x: + trace["x"] = group[1][x] + if y: + trace["y"] = group[1][y] + trace = _make_trace_for_scatter( + trace, trace_type, colormap[group[0]], **kwargs_marker + ) + + fig.append_trace(trace, 1, 1) + + elif (facet_row and not facet_col) or (not facet_row and facet_col): + groups_by_facet = list(df.groupby(facet_row if facet_row else facet_col)) + for j, group in enumerate(groups_by_facet): + for color_val in df[color_name].unique(): + data_by_color = group[1][group[1][color_name] == color_val] + trace = dict( + type=trace_type, + name=color_val, + marker=dict(color=colormap[color_val]), + **kwargs_trace, + ) + if x: + trace["x"] = data_by_color[x] + if y: + trace["y"] = data_by_color[y] + trace = _make_trace_for_scatter( + trace, trace_type, colormap[color_val], **kwargs_marker + ) + + fig.append_trace( + trace, j + 1 if facet_row else 1, 1 if facet_row else j + 1 + ) + + label = _return_label( + group[0], + facet_row_labels if facet_row else facet_col_labels, + facet_row if facet_row else facet_col, + ) + + annotations.append( + _annotation_dict( + label, + num_of_rows - j if facet_row else j + 1, + num_of_rows if facet_row else num_of_cols, + SUBPLOT_SPACING, + "row" if facet_row else "col", + flipped_rows, + ) + ) + + elif facet_row and facet_col: + groups_by_facets = list(df.groupby([facet_row, facet_col])) + tuple_to_facet_group = {item[0]: item[1] for item in groups_by_facets} + + row_values = df[facet_row].unique() + col_values = df[facet_col].unique() + color_vals = df[color_name].unique() + for row_count, x_val in enumerate(row_values): + for col_count, y_val in enumerate(col_values): + try: + group = tuple_to_facet_group[(x_val, y_val)] + except KeyError: + group = pd.DataFrame( + [[None, None, None]], columns=[x, y, color_name] + ) + + for color_val in color_vals: + if group.values.tolist() != [[None, None, None]]: + group_filtered = group[group[color_name] == color_val] + + trace = dict( + type=trace_type, + name=color_val, + marker=dict(color=colormap[color_val]), + **kwargs_trace, + ) + new_x = group_filtered[x] + new_y = group_filtered[y] + else: + trace = dict( + type=trace_type, + name=color_val, + marker=dict(color=colormap[color_val]), + showlegend=False, + **kwargs_trace, + ) + new_x = group[x] + new_y = group[y] + + if x: + trace["x"] = new_x + if y: + trace["y"] = new_y + trace = _make_trace_for_scatter( + trace, trace_type, colormap[color_val], **kwargs_marker + ) + + fig.append_trace(trace, row_count + 1, col_count + 1) + if row_count == 0: + label = _return_label( + col_values[col_count], facet_col_labels, facet_col + ) + annotations.append( + _annotation_dict( + label, + col_count + 1, + num_of_cols, + SUBPLOT_SPACING, + row_col="col", + flipped=flipped_cols, + ) + ) + label = _return_label(row_values[row_count], facet_row_labels, facet_row) + annotations.append( + _annotation_dict( + label, + num_of_rows - row_count, + num_of_rows, + SUBPLOT_SPACING, + row_col="row", + flipped=flipped_rows, + ) + ) + + return fig, annotations + + +def _facet_grid_color_numerical( + df, + x, + y, + facet_row, + facet_col, + color_name, + colormap, + num_of_rows, + num_of_cols, + facet_row_labels, + facet_col_labels, + trace_type, + flipped_rows, + flipped_cols, + show_boxes, + SUBPLOT_SPACING, + marker_color, + kwargs_trace, + kwargs_marker, +): + fig = make_subplots( + rows=num_of_rows, + cols=num_of_cols, + shared_xaxes=True, + shared_yaxes=True, + horizontal_spacing=SUBPLOT_SPACING, + vertical_spacing=SUBPLOT_SPACING, + print_grid=False, + ) + + annotations = [] + if not facet_row and not facet_col: + trace = dict( + type=trace_type, + marker=dict(color=df[color_name], colorscale=colormap, showscale=True), + **kwargs_trace, + ) + if x: + trace["x"] = df[x] + if y: + trace["y"] = df[y] + trace = _make_trace_for_scatter( + trace, trace_type, df[color_name], **kwargs_marker + ) + + fig.append_trace(trace, 1, 1) + + if (facet_row and not facet_col) or (not facet_row and facet_col): + groups_by_facet = list(df.groupby(facet_row if facet_row else facet_col)) + for j, group in enumerate(groups_by_facet): + trace = dict( + type=trace_type, + marker=dict( + color=df[color_name], + colorscale=colormap, + showscale=True, + colorbar=dict(x=1.15), + ), + **kwargs_trace, + ) + if x: + trace["x"] = group[1][x] + if y: + trace["y"] = group[1][y] + trace = _make_trace_for_scatter( + trace, trace_type, df[color_name], **kwargs_marker + ) + + fig.append_trace( + trace, j + 1 if facet_row else 1, 1 if facet_row else j + 1 + ) + + labels = facet_row_labels if facet_row else facet_col_labels + label = _return_label( + group[0], labels, facet_row if facet_row else facet_col + ) + + annotations.append( + _annotation_dict( + label, + num_of_rows - j if facet_row else j + 1, + num_of_rows if facet_row else num_of_cols, + SUBPLOT_SPACING, + "row" if facet_row else "col", + flipped=flipped_rows, + ) + ) + + elif facet_row and facet_col: + groups_by_facets = list(df.groupby([facet_row, facet_col])) + tuple_to_facet_group = {item[0]: item[1] for item in groups_by_facets} + + row_values = df[facet_row].unique() + col_values = df[facet_col].unique() + for row_count, x_val in enumerate(row_values): + for col_count, y_val in enumerate(col_values): + try: + group = tuple_to_facet_group[(x_val, y_val)] + except KeyError: + group = pd.DataFrame( + [[None, None, None]], columns=[x, y, color_name] + ) + + if group.values.tolist() != [[None, None, None]]: + trace = dict( + type=trace_type, + marker=dict( + color=df[color_name], + colorscale=colormap, + showscale=(row_count == 0), + colorbar=dict(x=1.15), + ), + **kwargs_trace, + ) + + else: + trace = dict(type=trace_type, showlegend=False, **kwargs_trace) + + if x: + trace["x"] = group[x] + if y: + trace["y"] = group[y] + trace = _make_trace_for_scatter( + trace, trace_type, df[color_name], **kwargs_marker + ) + + fig.append_trace(trace, row_count + 1, col_count + 1) + if row_count == 0: + label = _return_label( + col_values[col_count], facet_col_labels, facet_col + ) + annotations.append( + _annotation_dict( + label, + col_count + 1, + num_of_cols, + SUBPLOT_SPACING, + row_col="col", + flipped=flipped_cols, + ) + ) + label = _return_label(row_values[row_count], facet_row_labels, facet_row) + annotations.append( + _annotation_dict( + row_values[row_count], + num_of_rows - row_count, + num_of_rows, + SUBPLOT_SPACING, + row_col="row", + flipped=flipped_rows, + ) + ) + + return fig, annotations + + +def _facet_grid( + df, + x, + y, + facet_row, + facet_col, + num_of_rows, + num_of_cols, + facet_row_labels, + facet_col_labels, + trace_type, + flipped_rows, + flipped_cols, + show_boxes, + SUBPLOT_SPACING, + marker_color, + kwargs_trace, + kwargs_marker, +): + fig = make_subplots( + rows=num_of_rows, + cols=num_of_cols, + shared_xaxes=True, + shared_yaxes=True, + horizontal_spacing=SUBPLOT_SPACING, + vertical_spacing=SUBPLOT_SPACING, + print_grid=False, + ) + annotations = [] + if not facet_row and not facet_col: + trace = dict( + type=trace_type, + marker=dict(color=marker_color, line=kwargs_marker["line"]), + **kwargs_trace, + ) + + if x: + trace["x"] = df[x] + if y: + trace["y"] = df[y] + trace = _make_trace_for_scatter( + trace, trace_type, marker_color, **kwargs_marker + ) + + fig.append_trace(trace, 1, 1) + + elif (facet_row and not facet_col) or (not facet_row and facet_col): + groups_by_facet = list(df.groupby(facet_row if facet_row else facet_col)) + for j, group in enumerate(groups_by_facet): + trace = dict( + type=trace_type, + marker=dict(color=marker_color, line=kwargs_marker["line"]), + **kwargs_trace, + ) + + if x: + trace["x"] = group[1][x] + if y: + trace["y"] = group[1][y] + trace = _make_trace_for_scatter( + trace, trace_type, marker_color, **kwargs_marker + ) + + fig.append_trace( + trace, j + 1 if facet_row else 1, 1 if facet_row else j + 1 + ) + + label = _return_label( + group[0], + facet_row_labels if facet_row else facet_col_labels, + facet_row if facet_row else facet_col, + ) + + annotations.append( + _annotation_dict( + label, + num_of_rows - j if facet_row else j + 1, + num_of_rows if facet_row else num_of_cols, + SUBPLOT_SPACING, + "row" if facet_row else "col", + flipped_rows, + ) + ) + + elif facet_row and facet_col: + groups_by_facets = list(df.groupby([facet_row, facet_col])) + tuple_to_facet_group = {item[0]: item[1] for item in groups_by_facets} + + row_values = df[facet_row].unique() + col_values = df[facet_col].unique() + for row_count, x_val in enumerate(row_values): + for col_count, y_val in enumerate(col_values): + try: + group = tuple_to_facet_group[(x_val, y_val)] + except KeyError: + group = pd.DataFrame([[None, None]], columns=[x, y]) + trace = dict( + type=trace_type, + marker=dict(color=marker_color, line=kwargs_marker["line"]), + **kwargs_trace, + ) + if x: + trace["x"] = group[x] + if y: + trace["y"] = group[y] + trace = _make_trace_for_scatter( + trace, trace_type, marker_color, **kwargs_marker + ) + + fig.append_trace(trace, row_count + 1, col_count + 1) + if row_count == 0: + label = _return_label( + col_values[col_count], facet_col_labels, facet_col + ) + annotations.append( + _annotation_dict( + label, + col_count + 1, + num_of_cols, + SUBPLOT_SPACING, + row_col="col", + flipped=flipped_cols, + ) + ) + + label = _return_label(row_values[row_count], facet_row_labels, facet_row) + annotations.append( + _annotation_dict( + label, + num_of_rows - row_count, + num_of_rows, + SUBPLOT_SPACING, + row_col="row", + flipped=flipped_rows, + ) + ) + + return fig, annotations + + +def create_facet_grid( + df, + x=None, + y=None, + facet_row=None, + facet_col=None, + color_name=None, + colormap=None, + color_is_cat=False, + facet_row_labels=None, + facet_col_labels=None, + height=None, + width=None, + trace_type="scatter", + scales="fixed", + dtick_x=None, + dtick_y=None, + show_boxes=True, + ggplot2=False, + binsize=1, + **kwargs, +): + """ + Returns figure for facet grid; **this function is deprecated**, since + plotly.express functions should be used instead, for example + + >>> import plotly.express as px + >>> tips = px.data.tips() + >>> fig = px.scatter(tips, + ... x='total_bill', + ... y='tip', + ... facet_row='sex', + ... facet_col='smoker', + ... color='size') + + + :param (pd.DataFrame) df: the dataframe of columns for the facet grid. + :param (str) x: the name of the dataframe column for the x axis data. + :param (str) y: the name of the dataframe column for the y axis data. + :param (str) facet_row: the name of the dataframe column that is used to + facet the grid into row panels. + :param (str) facet_col: the name of the dataframe column that is used to + facet the grid into column panels. + :param (str) color_name: the name of your dataframe column that will + function as the colormap variable. + :param (str|list|dict) colormap: the param that determines how the + color_name column colors the data. If the dataframe contains numeric + data, then a dictionary of colors will group the data categorically + while a Plotly Colorscale name or a custom colorscale will treat it + numerically. To learn more about colors and types of colormap, run + `help(plotly.colors)`. + :param (bool) color_is_cat: determines whether a numerical column for the + colormap will be treated as categorical (True) or sequential (False). + Default = False. + :param (str|dict) facet_row_labels: set to either 'name' or a dictionary + of all the unique values in the faceting row mapped to some text to + show up in the label annotations. If None, labeling works like usual. + :param (str|dict) facet_col_labels: set to either 'name' or a dictionary + of all the values in the faceting row mapped to some text to show up + in the label annotations. If None, labeling works like usual. + :param (int) height: the height of the facet grid figure. + :param (int) width: the width of the facet grid figure. + :param (str) trace_type: decides the type of plot to appear in the + facet grid. The options are 'scatter', 'scattergl', 'histogram', + 'bar', and 'box'. + Default = 'scatter'. + :param (str) scales: determines if axes have fixed ranges or not. Valid + settings are 'fixed' (all axes fixed), 'free_x' (x axis free only), + 'free_y' (y axis free only) or 'free' (both axes free). + :param (float) dtick_x: determines the distance between each tick on the + x-axis. Default is None which means dtick_x is set automatically. + :param (float) dtick_y: determines the distance between each tick on the + y-axis. Default is None which means dtick_y is set automatically. + :param (bool) show_boxes: draws grey boxes behind the facet titles. + :param (bool) ggplot2: draws the facet grid in the style of `ggplot2`. See + http://ggplot2.tidyverse.org/reference/facet_grid.html for reference. + Default = False + :param (int) binsize: groups all data into bins of a given length. + :param (dict) kwargs: a dictionary of scatterplot arguments. + + Examples 1: One Way Faceting + + >>> import plotly.figure_factory as ff + >>> import pandas as pd + >>> mpg = pd.read_table('https://raw.githubusercontent.com/plotly/datasets/master/mpg_2017.txt') + + >>> fig = ff.create_facet_grid( + ... mpg, + ... x='displ', + ... y='cty', + ... facet_col='cyl', + ... ) + >>> fig.show() + + Example 2: Two Way Faceting + + >>> import plotly.figure_factory as ff + + >>> import pandas as pd + + >>> mpg = pd.read_table('https://raw.githubusercontent.com/plotly/datasets/master/mpg_2017.txt') + + >>> fig = ff.create_facet_grid( + ... mpg, + ... x='displ', + ... y='cty', + ... facet_row='drv', + ... facet_col='cyl', + ... ) + >>> fig.show() + + Example 3: Categorical Coloring + + >>> import plotly.figure_factory as ff + >>> import pandas as pd + >>> mtcars = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/mtcars.csv') + >>> mtcars.cyl = mtcars.cyl.astype(str) + >>> fig = ff.create_facet_grid( + ... mtcars, + ... x='mpg', + ... y='wt', + ... facet_col='cyl', + ... color_name='cyl', + ... color_is_cat=True, + ... ) + >>> fig.show() + + + """ + if not pd: + raise ImportError("'pandas' must be installed for this figure_factory.") + + if not isinstance(df, pd.DataFrame): + raise exceptions.PlotlyError("You must input a pandas DataFrame.") + + # make sure all columns are of homogenous datatype + utils.validate_dataframe(df) + + if trace_type in ["scatter", "scattergl"]: + if not x or not y: + raise exceptions.PlotlyError( + "You need to input 'x' and 'y' if you are you are using a " + "trace_type of 'scatter' or 'scattergl'." + ) + + for key in [x, y, facet_row, facet_col, color_name]: + if key is not None: + try: + df[key] + except KeyError: + raise exceptions.PlotlyError( + "x, y, facet_row, facet_col and color_name must be keys " + "in your dataframe." + ) + # autoscale histogram bars + if trace_type not in ["scatter", "scattergl"]: + scales = "free" + + # validate scales + if scales not in ["fixed", "free_x", "free_y", "free"]: + raise exceptions.PlotlyError( + "'scales' must be set to 'fixed', 'free_x', 'free_y' and 'free'." + ) + + if trace_type not in VALID_TRACE_TYPES: + raise exceptions.PlotlyError( + "'trace_type' must be in {}".format(VALID_TRACE_TYPES) + ) + + if trace_type == "histogram": + SUBPLOT_SPACING = 0.06 + else: + SUBPLOT_SPACING = 0.015 + + # seperate kwargs for marker and else + if "marker" in kwargs: + kwargs_marker = kwargs["marker"] + else: + kwargs_marker = {} + marker_color = kwargs_marker.pop("color", None) + kwargs.pop("marker", None) + kwargs_trace = kwargs + + if "size" not in kwargs_marker: + if ggplot2: + kwargs_marker["size"] = 5 + else: + kwargs_marker["size"] = 8 + + if "opacity" not in kwargs_marker: + if not ggplot2: + kwargs_trace["opacity"] = 0.6 + + if "line" not in kwargs_marker: + if not ggplot2: + kwargs_marker["line"] = {"color": "darkgrey", "width": 1} + else: + kwargs_marker["line"] = {} + + # default marker size + if not ggplot2: + if not marker_color: + marker_color = "rgb(31, 119, 180)" + else: + marker_color = "rgb(0, 0, 0)" + + num_of_rows = 1 + num_of_cols = 1 + flipped_rows = False + flipped_cols = False + if facet_row: + num_of_rows = len(df[facet_row].unique()) + flipped_rows = _is_flipped(num_of_rows) + if isinstance(facet_row_labels, dict): + for key in df[facet_row].unique(): + if key not in facet_row_labels.keys(): + unique_keys = df[facet_row].unique().tolist() + raise exceptions.PlotlyError(CUSTOM_LABEL_ERROR.format(unique_keys)) + if facet_col: + num_of_cols = len(df[facet_col].unique()) + flipped_cols = _is_flipped(num_of_cols) + if isinstance(facet_col_labels, dict): + for key in df[facet_col].unique(): + if key not in facet_col_labels.keys(): + unique_keys = df[facet_col].unique().tolist() + raise exceptions.PlotlyError(CUSTOM_LABEL_ERROR.format(unique_keys)) + show_legend = False + if color_name: + if isinstance(df[color_name].iloc[0], str) or color_is_cat: + show_legend = True + if isinstance(colormap, dict): + clrs.validate_colors_dict(colormap, "rgb") + + for val in df[color_name].unique(): + if val not in colormap.keys(): + raise exceptions.PlotlyError( + "If using 'colormap' as a dictionary, make sure " + "all the values of the colormap column are in " + "the keys of your dictionary." + ) + else: + # use default plotly colors for dictionary + default_colors = clrs.DEFAULT_PLOTLY_COLORS + colormap = {} + j = 0 + for val in df[color_name].unique(): + if j >= len(default_colors): + j = 0 + colormap[val] = default_colors[j] + j += 1 + fig, annotations = _facet_grid_color_categorical( + df, + x, + y, + facet_row, + facet_col, + color_name, + colormap, + num_of_rows, + num_of_cols, + facet_row_labels, + facet_col_labels, + trace_type, + flipped_rows, + flipped_cols, + show_boxes, + SUBPLOT_SPACING, + marker_color, + kwargs_trace, + kwargs_marker, + ) + + elif isinstance(df[color_name].iloc[0], Number): + if isinstance(colormap, dict): + show_legend = True + clrs.validate_colors_dict(colormap, "rgb") + + for val in df[color_name].unique(): + if val not in colormap.keys(): + raise exceptions.PlotlyError( + "If using 'colormap' as a dictionary, make sure " + "all the values of the colormap column are in " + "the keys of your dictionary." + ) + fig, annotations = _facet_grid_color_categorical( + df, + x, + y, + facet_row, + facet_col, + color_name, + colormap, + num_of_rows, + num_of_cols, + facet_row_labels, + facet_col_labels, + trace_type, + flipped_rows, + flipped_cols, + show_boxes, + SUBPLOT_SPACING, + marker_color, + kwargs_trace, + kwargs_marker, + ) + + elif isinstance(colormap, list): + colorscale_list = colormap + clrs.validate_colorscale(colorscale_list) + + fig, annotations = _facet_grid_color_numerical( + df, + x, + y, + facet_row, + facet_col, + color_name, + colorscale_list, + num_of_rows, + num_of_cols, + facet_row_labels, + facet_col_labels, + trace_type, + flipped_rows, + flipped_cols, + show_boxes, + SUBPLOT_SPACING, + marker_color, + kwargs_trace, + kwargs_marker, + ) + elif isinstance(colormap, str): + if colormap in clrs.PLOTLY_SCALES.keys(): + colorscale_list = clrs.PLOTLY_SCALES[colormap] + else: + raise exceptions.PlotlyError( + "If 'colormap' is a string, it must be the name " + "of a Plotly Colorscale. The available colorscale " + "names are {}".format(clrs.PLOTLY_SCALES.keys()) + ) + fig, annotations = _facet_grid_color_numerical( + df, + x, + y, + facet_row, + facet_col, + color_name, + colorscale_list, + num_of_rows, + num_of_cols, + facet_row_labels, + facet_col_labels, + trace_type, + flipped_rows, + flipped_cols, + show_boxes, + SUBPLOT_SPACING, + marker_color, + kwargs_trace, + kwargs_marker, + ) + else: + colorscale_list = clrs.PLOTLY_SCALES["Reds"] + fig, annotations = _facet_grid_color_numerical( + df, + x, + y, + facet_row, + facet_col, + color_name, + colorscale_list, + num_of_rows, + num_of_cols, + facet_row_labels, + facet_col_labels, + trace_type, + flipped_rows, + flipped_cols, + show_boxes, + SUBPLOT_SPACING, + marker_color, + kwargs_trace, + kwargs_marker, + ) + + else: + fig, annotations = _facet_grid( + df, + x, + y, + facet_row, + facet_col, + num_of_rows, + num_of_cols, + facet_row_labels, + facet_col_labels, + trace_type, + flipped_rows, + flipped_cols, + show_boxes, + SUBPLOT_SPACING, + marker_color, + kwargs_trace, + kwargs_marker, + ) + + if not height: + height = max(600, 100 * num_of_rows) + if not width: + width = max(600, 100 * num_of_cols) + + fig["layout"].update( + height=height, width=width, title="", paper_bgcolor="rgb(251, 251, 251)" + ) + if ggplot2: + fig["layout"].update( + plot_bgcolor=PLOT_BGCOLOR, + paper_bgcolor="rgb(255, 255, 255)", + hovermode="closest", + ) + + # axis titles + x_title_annot = _axis_title_annotation(x, "x") + y_title_annot = _axis_title_annotation(y, "y") + + # annotations + annotations.append(x_title_annot) + annotations.append(y_title_annot) + + # legend + fig["layout"]["showlegend"] = show_legend + fig["layout"]["legend"]["bgcolor"] = LEGEND_COLOR + fig["layout"]["legend"]["borderwidth"] = LEGEND_BORDER_WIDTH + fig["layout"]["legend"]["x"] = 1.05 + fig["layout"]["legend"]["y"] = 1 + fig["layout"]["legend"]["yanchor"] = "top" + + if show_legend: + fig["layout"]["showlegend"] = show_legend + if ggplot2: + if color_name: + legend_annot = _legend_annotation(color_name) + annotations.append(legend_annot) + fig["layout"]["margin"]["r"] = 150 + + # assign annotations to figure + fig["layout"]["annotations"] = annotations + + # add shaded boxes behind axis titles + if show_boxes and ggplot2: + _add_shapes_to_fig(fig, ANNOT_RECT_COLOR, flipped_rows, flipped_cols) + + # all xaxis and yaxis labels + axis_labels = {"x": [], "y": []} + for key in fig["layout"]: + if "xaxis" in key: + axis_labels["x"].append(key) + elif "yaxis" in key: + axis_labels["y"].append(key) + + string_number_in_data = False + for var in [v for v in [x, y] if v]: + if isinstance(df[var].tolist()[0], str): + for item in df[var]: + try: + int(item) + string_number_in_data = True + except ValueError: + pass + + if string_number_in_data: + for x_y in axis_labels.keys(): + for axis_name in axis_labels[x_y]: + fig["layout"][axis_name]["type"] = "category" + + if scales == "fixed": + fixed_axes = ["x", "y"] + elif scales == "free_x": + fixed_axes = ["y"] + elif scales == "free_y": + fixed_axes = ["x"] + elif scales == "free": + fixed_axes = [] + + # fixed ranges + for x_y in fixed_axes: + min_ranges = [] + max_ranges = [] + for trace in fig["data"]: + if trace[x_y] is not None and len(trace[x_y]) > 0: + min_ranges.append(min(trace[x_y])) + max_ranges.append(max(trace[x_y])) + while None in min_ranges: + min_ranges.remove(None) + while None in max_ranges: + max_ranges.remove(None) + + min_range = min(min_ranges) + max_range = max(max_ranges) + + range_are_numbers = isinstance(min_range, Number) and isinstance( + max_range, Number + ) + + if range_are_numbers: + min_range = math.floor(min_range) + max_range = math.ceil(max_range) + + # extend widen frame by 5% on each side + min_range -= 0.05 * (max_range - min_range) + max_range += 0.05 * (max_range - min_range) + + if x_y == "x": + if dtick_x: + dtick = dtick_x + else: + dtick = math.floor((max_range - min_range) / MAX_TICKS_PER_AXIS) + elif x_y == "y": + if dtick_y: + dtick = dtick_y + else: + dtick = math.floor((max_range - min_range) / MAX_TICKS_PER_AXIS) + else: + dtick = 1 + + for axis_title in axis_labels[x_y]: + fig["layout"][axis_title]["dtick"] = dtick + fig["layout"][axis_title]["ticklen"] = 0 + fig["layout"][axis_title]["zeroline"] = False + if ggplot2: + fig["layout"][axis_title]["tickwidth"] = 1 + fig["layout"][axis_title]["ticklen"] = 4 + fig["layout"][axis_title]["gridwidth"] = GRID_WIDTH + + fig["layout"][axis_title]["gridcolor"] = GRID_COLOR + fig["layout"][axis_title]["gridwidth"] = 2 + fig["layout"][axis_title]["tickfont"] = { + "color": TICK_COLOR, + "size": 10, + } + + # insert ranges into fig + if x_y in fixed_axes: + for key in fig["layout"]: + if "{}axis".format(x_y) in key and range_are_numbers: + fig["layout"][key]["range"] = [min_range, max_range] + + return fig diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_gantt.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_gantt.py new file mode 100644 index 0000000000000000000000000000000000000000..006754a0ff14f35d68da18ff214278e2dd23e22b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_gantt.py @@ -0,0 +1,1035 @@ +from numbers import Number + +import copy + +from plotly import exceptions, optional_imports +import plotly.colors as clrs +from plotly.figure_factory import utils +import plotly.graph_objects as go + +pd = optional_imports.get_module("pandas") + +REQUIRED_GANTT_KEYS = ["Task", "Start", "Finish"] + + +def _get_corner_points(x0, y0, x1, y1): + """ + Returns the corner points of a scatter rectangle + + :param x0: x-start + :param y0: y-lower + :param x1: x-end + :param y1: y-upper + :return: ([x], [y]), tuple of lists containing the x and y values + """ + + return ([x0, x1, x1, x0], [y0, y0, y1, y1]) + + +def validate_gantt(df): + """ + Validates the inputted dataframe or list + """ + if pd and isinstance(df, pd.core.frame.DataFrame): + # validate that df has all the required keys + for key in REQUIRED_GANTT_KEYS: + if key not in df: + raise exceptions.PlotlyError( + "The columns in your dataframe must include the " + "following keys: {0}".format(", ".join(REQUIRED_GANTT_KEYS)) + ) + + columns = {key: df[key].values for key in df} + num_of_rows = len(df.index) + chart = [] + # Using only keys present in the DataFrame columns + keys = list(df.columns) + for index in range(num_of_rows): + task_dict = {key: columns[key][index] for key in keys} + chart.append(task_dict) + + return chart + + # validate if df is a list + if not isinstance(df, list): + raise exceptions.PlotlyError( + "You must input either a dataframe or a list of dictionaries." + ) + + # validate if df is empty + if len(df) <= 0: + raise exceptions.PlotlyError( + "Your list is empty. It must contain at least one dictionary." + ) + if not isinstance(df[0], dict): + raise exceptions.PlotlyError("Your list must only include dictionaries.") + return df + + +def gantt( + chart, + colors, + title, + bar_width, + showgrid_x, + showgrid_y, + height, + width, + tasks=None, + task_names=None, + data=None, + group_tasks=False, + show_hover_fill=True, + show_colorbar=True, +): + """ + Refer to create_gantt() for docstring + """ + if tasks is None: + tasks = [] + if task_names is None: + task_names = [] + if data is None: + data = [] + + for index in range(len(chart)): + task = dict( + x0=chart[index]["Start"], + x1=chart[index]["Finish"], + name=chart[index]["Task"], + ) + if "Description" in chart[index]: + task["description"] = chart[index]["Description"] + tasks.append(task) + + # create a scatter trace for every task group + scatter_data_dict = dict() + marker_data_dict = dict() + + if show_hover_fill: + hoverinfo = "name" + else: + hoverinfo = "skip" + + scatter_data_template = { + "x": [], + "y": [], + "mode": "none", + "fill": "toself", + "hoverinfo": hoverinfo, + } + + marker_data_template = { + "x": [], + "y": [], + "mode": "markers", + "text": [], + "marker": dict(color="", size=1, opacity=0), + "name": "", + "showlegend": False, + } + + # create the list of task names + for index in range(len(tasks)): + tn = tasks[index]["name"] + # Is added to task_names if group_tasks is set to False, + # or if the option is used (True) it only adds them if the + # name is not already in the list + if not group_tasks or tn not in task_names: + task_names.append(tn) + # Guarantees that for grouped tasks the tasks that are inserted first + # are shown at the top + if group_tasks: + task_names.reverse() + + color_index = 0 + for index in range(len(tasks)): + tn = tasks[index]["name"] + del tasks[index]["name"] + + # If group_tasks is True, all tasks with the same name belong + # to the same row. + groupID = index + if group_tasks: + groupID = task_names.index(tn) + tasks[index]["y0"] = groupID - bar_width + tasks[index]["y1"] = groupID + bar_width + + # check if colors need to be looped + if color_index >= len(colors): + color_index = 0 + tasks[index]["fillcolor"] = colors[color_index] + color_id = tasks[index]["fillcolor"] + + if color_id not in scatter_data_dict: + scatter_data_dict[color_id] = copy.deepcopy(scatter_data_template) + + scatter_data_dict[color_id]["fillcolor"] = color_id + scatter_data_dict[color_id]["name"] = str(tn) + scatter_data_dict[color_id]["legendgroup"] = color_id + + # if there are already values append the gap + if len(scatter_data_dict[color_id]["x"]) > 0: + # a gap on the scatterplot separates the rectangles from each other + scatter_data_dict[color_id]["x"].append( + scatter_data_dict[color_id]["x"][-1] + ) + scatter_data_dict[color_id]["y"].append(None) + + xs, ys = _get_corner_points( + tasks[index]["x0"], + tasks[index]["y0"], + tasks[index]["x1"], + tasks[index]["y1"], + ) + + scatter_data_dict[color_id]["x"] += xs + scatter_data_dict[color_id]["y"] += ys + + # append dummy markers for showing start and end of interval + if color_id not in marker_data_dict: + marker_data_dict[color_id] = copy.deepcopy(marker_data_template) + marker_data_dict[color_id]["marker"]["color"] = color_id + marker_data_dict[color_id]["legendgroup"] = color_id + + marker_data_dict[color_id]["x"].append(tasks[index]["x0"]) + marker_data_dict[color_id]["x"].append(tasks[index]["x1"]) + marker_data_dict[color_id]["y"].append(groupID) + marker_data_dict[color_id]["y"].append(groupID) + + if "description" in tasks[index]: + marker_data_dict[color_id]["text"].append(tasks[index]["description"]) + marker_data_dict[color_id]["text"].append(tasks[index]["description"]) + del tasks[index]["description"] + else: + marker_data_dict[color_id]["text"].append(None) + marker_data_dict[color_id]["text"].append(None) + + color_index += 1 + + showlegend = show_colorbar + + layout = dict( + title=title, + showlegend=showlegend, + height=height, + width=width, + shapes=[], + hovermode="closest", + yaxis=dict( + showgrid=showgrid_y, + ticktext=task_names, + tickvals=list(range(len(task_names))), + range=[-1, len(task_names) + 1], + autorange=False, + zeroline=False, + ), + xaxis=dict( + showgrid=showgrid_x, + zeroline=False, + rangeselector=dict( + buttons=list( + [ + dict(count=7, label="1w", step="day", stepmode="backward"), + dict(count=1, label="1m", step="month", stepmode="backward"), + dict(count=6, label="6m", step="month", stepmode="backward"), + dict(count=1, label="YTD", step="year", stepmode="todate"), + dict(count=1, label="1y", step="year", stepmode="backward"), + dict(step="all"), + ] + ) + ), + type="date", + ), + ) + + data = [scatter_data_dict[k] for k in sorted(scatter_data_dict)] + data += [marker_data_dict[k] for k in sorted(marker_data_dict)] + + # fig = dict( + # data=data, layout=layout + # ) + fig = go.Figure(data=data, layout=layout) + return fig + + +def gantt_colorscale( + chart, + colors, + title, + index_col, + show_colorbar, + bar_width, + showgrid_x, + showgrid_y, + height, + width, + tasks=None, + task_names=None, + data=None, + group_tasks=False, + show_hover_fill=True, +): + """ + Refer to FigureFactory.create_gantt() for docstring + """ + if tasks is None: + tasks = [] + if task_names is None: + task_names = [] + if data is None: + data = [] + showlegend = False + + for index in range(len(chart)): + task = dict( + x0=chart[index]["Start"], + x1=chart[index]["Finish"], + name=chart[index]["Task"], + ) + if "Description" in chart[index]: + task["description"] = chart[index]["Description"] + tasks.append(task) + + # create a scatter trace for every task group + scatter_data_dict = dict() + # create scatter traces for the start- and endpoints + marker_data_dict = dict() + + if show_hover_fill: + hoverinfo = "name" + else: + hoverinfo = "skip" + + scatter_data_template = { + "x": [], + "y": [], + "mode": "none", + "fill": "toself", + "showlegend": False, + "hoverinfo": hoverinfo, + "legendgroup": "", + } + + marker_data_template = { + "x": [], + "y": [], + "mode": "markers", + "text": [], + "marker": dict(color="", size=1, opacity=0), + "name": "", + "showlegend": False, + "legendgroup": "", + } + + index_vals = [] + for row in range(len(tasks)): + if chart[row][index_col] not in index_vals: + index_vals.append(chart[row][index_col]) + + index_vals.sort() + + # compute the color for task based on indexing column + if isinstance(chart[0][index_col], Number): + # check that colors has at least 2 colors + if len(colors) < 2: + raise exceptions.PlotlyError( + "You must use at least 2 colors in 'colors' if you " + "are using a colorscale. However only the first two " + "colors given will be used for the lower and upper " + "bounds on the colormap." + ) + + # create the list of task names + for index in range(len(tasks)): + tn = tasks[index]["name"] + # Is added to task_names if group_tasks is set to False, + # or if the option is used (True) it only adds them if the + # name is not already in the list + if not group_tasks or tn not in task_names: + task_names.append(tn) + # Guarantees that for grouped tasks the tasks that are inserted + # first are shown at the top + if group_tasks: + task_names.reverse() + + for index in range(len(tasks)): + tn = tasks[index]["name"] + del tasks[index]["name"] + + # If group_tasks is True, all tasks with the same name belong + # to the same row. + groupID = index + if group_tasks: + groupID = task_names.index(tn) + tasks[index]["y0"] = groupID - bar_width + tasks[index]["y1"] = groupID + bar_width + + # unlabel color + colors = clrs.color_parser(colors, clrs.unlabel_rgb) + lowcolor = colors[0] + highcolor = colors[1] + + intermed = (chart[index][index_col]) / 100.0 + intermed_color = clrs.find_intermediate_color(lowcolor, highcolor, intermed) + intermed_color = clrs.color_parser(intermed_color, clrs.label_rgb) + tasks[index]["fillcolor"] = intermed_color + color_id = tasks[index]["fillcolor"] + + if color_id not in scatter_data_dict: + scatter_data_dict[color_id] = copy.deepcopy(scatter_data_template) + + scatter_data_dict[color_id]["fillcolor"] = color_id + scatter_data_dict[color_id]["name"] = str(chart[index][index_col]) + scatter_data_dict[color_id]["legendgroup"] = color_id + + # relabel colors with 'rgb' + colors = clrs.color_parser(colors, clrs.label_rgb) + + # if there are already values append the gap + if len(scatter_data_dict[color_id]["x"]) > 0: + # a gap on the scatterplot separates the rectangles from each other + scatter_data_dict[color_id]["x"].append( + scatter_data_dict[color_id]["x"][-1] + ) + scatter_data_dict[color_id]["y"].append(None) + + xs, ys = _get_corner_points( + tasks[index]["x0"], + tasks[index]["y0"], + tasks[index]["x1"], + tasks[index]["y1"], + ) + + scatter_data_dict[color_id]["x"] += xs + scatter_data_dict[color_id]["y"] += ys + + # append dummy markers for showing start and end of interval + if color_id not in marker_data_dict: + marker_data_dict[color_id] = copy.deepcopy(marker_data_template) + marker_data_dict[color_id]["marker"]["color"] = color_id + marker_data_dict[color_id]["legendgroup"] = color_id + + marker_data_dict[color_id]["x"].append(tasks[index]["x0"]) + marker_data_dict[color_id]["x"].append(tasks[index]["x1"]) + marker_data_dict[color_id]["y"].append(groupID) + marker_data_dict[color_id]["y"].append(groupID) + + if "description" in tasks[index]: + marker_data_dict[color_id]["text"].append(tasks[index]["description"]) + marker_data_dict[color_id]["text"].append(tasks[index]["description"]) + del tasks[index]["description"] + else: + marker_data_dict[color_id]["text"].append(None) + marker_data_dict[color_id]["text"].append(None) + + # add colorbar to one of the traces randomly just for display + if show_colorbar is True: + k = list(marker_data_dict.keys())[0] + marker_data_dict[k]["marker"].update( + dict( + colorscale=[[0, colors[0]], [1, colors[1]]], + showscale=True, + cmax=100, + cmin=0, + ) + ) + + if isinstance(chart[0][index_col], str): + index_vals = [] + for row in range(len(tasks)): + if chart[row][index_col] not in index_vals: + index_vals.append(chart[row][index_col]) + + index_vals.sort() + + if len(colors) < len(index_vals): + raise exceptions.PlotlyError( + "Error. The number of colors in 'colors' must be no less " + "than the number of unique index values in your group " + "column." + ) + + # make a dictionary assignment to each index value + index_vals_dict = {} + # define color index + c_index = 0 + for key in index_vals: + if c_index > len(colors) - 1: + c_index = 0 + index_vals_dict[key] = colors[c_index] + c_index += 1 + + # create the list of task names + for index in range(len(tasks)): + tn = tasks[index]["name"] + # Is added to task_names if group_tasks is set to False, + # or if the option is used (True) it only adds them if the + # name is not already in the list + if not group_tasks or tn not in task_names: + task_names.append(tn) + # Guarantees that for grouped tasks the tasks that are inserted + # first are shown at the top + if group_tasks: + task_names.reverse() + + for index in range(len(tasks)): + tn = tasks[index]["name"] + del tasks[index]["name"] + + # If group_tasks is True, all tasks with the same name belong + # to the same row. + groupID = index + if group_tasks: + groupID = task_names.index(tn) + tasks[index]["y0"] = groupID - bar_width + tasks[index]["y1"] = groupID + bar_width + + tasks[index]["fillcolor"] = index_vals_dict[chart[index][index_col]] + color_id = tasks[index]["fillcolor"] + + if color_id not in scatter_data_dict: + scatter_data_dict[color_id] = copy.deepcopy(scatter_data_template) + + scatter_data_dict[color_id]["fillcolor"] = color_id + scatter_data_dict[color_id]["legendgroup"] = color_id + scatter_data_dict[color_id]["name"] = str(chart[index][index_col]) + + # relabel colors with 'rgb' + colors = clrs.color_parser(colors, clrs.label_rgb) + + # if there are already values append the gap + if len(scatter_data_dict[color_id]["x"]) > 0: + # a gap on the scatterplot separates the rectangles from each other + scatter_data_dict[color_id]["x"].append( + scatter_data_dict[color_id]["x"][-1] + ) + scatter_data_dict[color_id]["y"].append(None) + + xs, ys = _get_corner_points( + tasks[index]["x0"], + tasks[index]["y0"], + tasks[index]["x1"], + tasks[index]["y1"], + ) + + scatter_data_dict[color_id]["x"] += xs + scatter_data_dict[color_id]["y"] += ys + + # append dummy markers for showing start and end of interval + if color_id not in marker_data_dict: + marker_data_dict[color_id] = copy.deepcopy(marker_data_template) + marker_data_dict[color_id]["marker"]["color"] = color_id + marker_data_dict[color_id]["legendgroup"] = color_id + + marker_data_dict[color_id]["x"].append(tasks[index]["x0"]) + marker_data_dict[color_id]["x"].append(tasks[index]["x1"]) + marker_data_dict[color_id]["y"].append(groupID) + marker_data_dict[color_id]["y"].append(groupID) + + if "description" in tasks[index]: + marker_data_dict[color_id]["text"].append(tasks[index]["description"]) + marker_data_dict[color_id]["text"].append(tasks[index]["description"]) + del tasks[index]["description"] + else: + marker_data_dict[color_id]["text"].append(None) + marker_data_dict[color_id]["text"].append(None) + + if show_colorbar is True: + showlegend = True + for k in scatter_data_dict: + scatter_data_dict[k]["showlegend"] = showlegend + # add colorbar to one of the traces randomly just for display + # if show_colorbar is True: + # k = list(marker_data_dict.keys())[0] + # marker_data_dict[k]["marker"].update( + # dict( + # colorscale=[[0, colors[0]], [1, colors[1]]], + # showscale=True, + # cmax=100, + # cmin=0, + # ) + # ) + + layout = dict( + title=title, + showlegend=showlegend, + height=height, + width=width, + shapes=[], + hovermode="closest", + yaxis=dict( + showgrid=showgrid_y, + ticktext=task_names, + tickvals=list(range(len(task_names))), + range=[-1, len(task_names) + 1], + autorange=False, + zeroline=False, + ), + xaxis=dict( + showgrid=showgrid_x, + zeroline=False, + rangeselector=dict( + buttons=list( + [ + dict(count=7, label="1w", step="day", stepmode="backward"), + dict(count=1, label="1m", step="month", stepmode="backward"), + dict(count=6, label="6m", step="month", stepmode="backward"), + dict(count=1, label="YTD", step="year", stepmode="todate"), + dict(count=1, label="1y", step="year", stepmode="backward"), + dict(step="all"), + ] + ) + ), + type="date", + ), + ) + + data = [scatter_data_dict[k] for k in sorted(scatter_data_dict)] + data += [marker_data_dict[k] for k in sorted(marker_data_dict)] + + # fig = dict( + # data=data, layout=layout + # ) + fig = go.Figure(data=data, layout=layout) + return fig + + +def gantt_dict( + chart, + colors, + title, + index_col, + show_colorbar, + bar_width, + showgrid_x, + showgrid_y, + height, + width, + tasks=None, + task_names=None, + data=None, + group_tasks=False, + show_hover_fill=True, +): + """ + Refer to FigureFactory.create_gantt() for docstring + """ + + if tasks is None: + tasks = [] + if task_names is None: + task_names = [] + if data is None: + data = [] + showlegend = False + + for index in range(len(chart)): + task = dict( + x0=chart[index]["Start"], + x1=chart[index]["Finish"], + name=chart[index]["Task"], + ) + if "Description" in chart[index]: + task["description"] = chart[index]["Description"] + tasks.append(task) + + # create a scatter trace for every task group + scatter_data_dict = dict() + # create scatter traces for the start- and endpoints + marker_data_dict = dict() + + if show_hover_fill: + hoverinfo = "name" + else: + hoverinfo = "skip" + + scatter_data_template = { + "x": [], + "y": [], + "mode": "none", + "fill": "toself", + "hoverinfo": hoverinfo, + "legendgroup": "", + } + + marker_data_template = { + "x": [], + "y": [], + "mode": "markers", + "text": [], + "marker": dict(color="", size=1, opacity=0), + "name": "", + "showlegend": False, + } + + index_vals = [] + for row in range(len(tasks)): + if chart[row][index_col] not in index_vals: + index_vals.append(chart[row][index_col]) + + index_vals.sort() + + # verify each value in index column appears in colors dictionary + for key in index_vals: + if key not in colors: + raise exceptions.PlotlyError( + "If you are using colors as a dictionary, all of its " + "keys must be all the values in the index column." + ) + + # create the list of task names + for index in range(len(tasks)): + tn = tasks[index]["name"] + # Is added to task_names if group_tasks is set to False, + # or if the option is used (True) it only adds them if the + # name is not already in the list + if not group_tasks or tn not in task_names: + task_names.append(tn) + # Guarantees that for grouped tasks the tasks that are inserted first + # are shown at the top + if group_tasks: + task_names.reverse() + + for index in range(len(tasks)): + tn = tasks[index]["name"] + del tasks[index]["name"] + + # If group_tasks is True, all tasks with the same name belong + # to the same row. + groupID = index + if group_tasks: + groupID = task_names.index(tn) + tasks[index]["y0"] = groupID - bar_width + tasks[index]["y1"] = groupID + bar_width + + tasks[index]["fillcolor"] = colors[chart[index][index_col]] + color_id = tasks[index]["fillcolor"] + + if color_id not in scatter_data_dict: + scatter_data_dict[color_id] = copy.deepcopy(scatter_data_template) + + scatter_data_dict[color_id]["legendgroup"] = color_id + scatter_data_dict[color_id]["fillcolor"] = color_id + + # if there are already values append the gap + if len(scatter_data_dict[color_id]["x"]) > 0: + # a gap on the scatterplot separates the rectangles from each other + scatter_data_dict[color_id]["x"].append( + scatter_data_dict[color_id]["x"][-1] + ) + scatter_data_dict[color_id]["y"].append(None) + + xs, ys = _get_corner_points( + tasks[index]["x0"], + tasks[index]["y0"], + tasks[index]["x1"], + tasks[index]["y1"], + ) + + scatter_data_dict[color_id]["x"] += xs + scatter_data_dict[color_id]["y"] += ys + + # append dummy markers for showing start and end of interval + if color_id not in marker_data_dict: + marker_data_dict[color_id] = copy.deepcopy(marker_data_template) + marker_data_dict[color_id]["marker"]["color"] = color_id + marker_data_dict[color_id]["legendgroup"] = color_id + + marker_data_dict[color_id]["x"].append(tasks[index]["x0"]) + marker_data_dict[color_id]["x"].append(tasks[index]["x1"]) + marker_data_dict[color_id]["y"].append(groupID) + marker_data_dict[color_id]["y"].append(groupID) + + if "description" in tasks[index]: + marker_data_dict[color_id]["text"].append(tasks[index]["description"]) + marker_data_dict[color_id]["text"].append(tasks[index]["description"]) + del tasks[index]["description"] + else: + marker_data_dict[color_id]["text"].append(None) + marker_data_dict[color_id]["text"].append(None) + + if show_colorbar is True: + showlegend = True + + for index_value in index_vals: + scatter_data_dict[colors[index_value]]["name"] = str(index_value) + + layout = dict( + title=title, + showlegend=showlegend, + height=height, + width=width, + shapes=[], + hovermode="closest", + yaxis=dict( + showgrid=showgrid_y, + ticktext=task_names, + tickvals=list(range(len(task_names))), + range=[-1, len(task_names) + 1], + autorange=False, + zeroline=False, + ), + xaxis=dict( + showgrid=showgrid_x, + zeroline=False, + rangeselector=dict( + buttons=list( + [ + dict(count=7, label="1w", step="day", stepmode="backward"), + dict(count=1, label="1m", step="month", stepmode="backward"), + dict(count=6, label="6m", step="month", stepmode="backward"), + dict(count=1, label="YTD", step="year", stepmode="todate"), + dict(count=1, label="1y", step="year", stepmode="backward"), + dict(step="all"), + ] + ) + ), + type="date", + ), + ) + + data = [scatter_data_dict[k] for k in sorted(scatter_data_dict)] + data += [marker_data_dict[k] for k in sorted(marker_data_dict)] + + # fig = dict( + # data=data, layout=layout + # ) + fig = go.Figure(data=data, layout=layout) + return fig + + +def create_gantt( + df, + colors=None, + index_col=None, + show_colorbar=False, + reverse_colors=False, + title="Gantt Chart", + bar_width=0.2, + showgrid_x=False, + showgrid_y=False, + height=600, + width=None, + tasks=None, + task_names=None, + data=None, + group_tasks=False, + show_hover_fill=True, +): + """ + **deprecated**, use instead + :func:`plotly.express.timeline`. + + Returns figure for a gantt chart + + :param (array|list) df: input data for gantt chart. Must be either a + a dataframe or a list. If dataframe, the columns must include + 'Task', 'Start' and 'Finish'. Other columns can be included and + used for indexing. If a list, its elements must be dictionaries + with the same required column headers: 'Task', 'Start' and + 'Finish'. + :param (str|list|dict|tuple) colors: either a plotly scale name, an + rgb or hex color, a color tuple or a list of colors. An rgb color + is of the form 'rgb(x, y, z)' where x, y, z belong to the interval + [0, 255] and a color tuple is a tuple of the form (a, b, c) where + a, b and c belong to [0, 1]. If colors is a list, it must + contain the valid color types aforementioned as its members. + If a dictionary, all values of the indexing column must be keys in + colors. + :param (str|float) index_col: the column header (if df is a data + frame) that will function as the indexing column. If df is a list, + index_col must be one of the keys in all the items of df. + :param (bool) show_colorbar: determines if colorbar will be visible. + Only applies if values in the index column are numeric. + :param (bool) show_hover_fill: enables/disables the hovertext for the + filled area of the chart. + :param (bool) reverse_colors: reverses the order of selected colors + :param (str) title: the title of the chart + :param (float) bar_width: the width of the horizontal bars in the plot + :param (bool) showgrid_x: show/hide the x-axis grid + :param (bool) showgrid_y: show/hide the y-axis grid + :param (float) height: the height of the chart + :param (float) width: the width of the chart + + Example 1: Simple Gantt Chart + + >>> from plotly.figure_factory import create_gantt + + >>> # Make data for chart + >>> df = [dict(Task="Job A", Start='2009-01-01', Finish='2009-02-30'), + ... dict(Task="Job B", Start='2009-03-05', Finish='2009-04-15'), + ... dict(Task="Job C", Start='2009-02-20', Finish='2009-05-30')] + + >>> # Create a figure + >>> fig = create_gantt(df) + >>> fig.show() + + + Example 2: Index by Column with Numerical Entries + + >>> from plotly.figure_factory import create_gantt + + >>> # Make data for chart + >>> df = [dict(Task="Job A", Start='2009-01-01', + ... Finish='2009-02-30', Complete=10), + ... dict(Task="Job B", Start='2009-03-05', + ... Finish='2009-04-15', Complete=60), + ... dict(Task="Job C", Start='2009-02-20', + ... Finish='2009-05-30', Complete=95)] + + >>> # Create a figure with Plotly colorscale + >>> fig = create_gantt(df, colors='Blues', index_col='Complete', + ... show_colorbar=True, bar_width=0.5, + ... showgrid_x=True, showgrid_y=True) + >>> fig.show() + + + Example 3: Index by Column with String Entries + + >>> from plotly.figure_factory import create_gantt + + >>> # Make data for chart + >>> df = [dict(Task="Job A", Start='2009-01-01', + ... Finish='2009-02-30', Resource='Apple'), + ... dict(Task="Job B", Start='2009-03-05', + ... Finish='2009-04-15', Resource='Grape'), + ... dict(Task="Job C", Start='2009-02-20', + ... Finish='2009-05-30', Resource='Banana')] + + >>> # Create a figure with Plotly colorscale + >>> fig = create_gantt(df, colors=['rgb(200, 50, 25)', (1, 0, 1), '#6c4774'], + ... index_col='Resource', reverse_colors=True, + ... show_colorbar=True) + >>> fig.show() + + + Example 4: Use a dictionary for colors + + >>> from plotly.figure_factory import create_gantt + >>> # Make data for chart + >>> df = [dict(Task="Job A", Start='2009-01-01', + ... Finish='2009-02-30', Resource='Apple'), + ... dict(Task="Job B", Start='2009-03-05', + ... Finish='2009-04-15', Resource='Grape'), + ... dict(Task="Job C", Start='2009-02-20', + ... Finish='2009-05-30', Resource='Banana')] + + >>> # Make a dictionary of colors + >>> colors = {'Apple': 'rgb(255, 0, 0)', + ... 'Grape': 'rgb(170, 14, 200)', + ... 'Banana': (1, 1, 0.2)} + + >>> # Create a figure with Plotly colorscale + >>> fig = create_gantt(df, colors=colors, index_col='Resource', + ... show_colorbar=True) + + >>> fig.show() + + Example 5: Use a pandas dataframe + + >>> from plotly.figure_factory import create_gantt + >>> import pandas as pd + + >>> # Make data as a dataframe + >>> df = pd.DataFrame([['Run', '2010-01-01', '2011-02-02', 10], + ... ['Fast', '2011-01-01', '2012-06-05', 55], + ... ['Eat', '2012-01-05', '2013-07-05', 94]], + ... columns=['Task', 'Start', 'Finish', 'Complete']) + + >>> # Create a figure with Plotly colorscale + >>> fig = create_gantt(df, colors='Blues', index_col='Complete', + ... show_colorbar=True, bar_width=0.5, + ... showgrid_x=True, showgrid_y=True) + >>> fig.show() + """ + # validate gantt input data + chart = validate_gantt(df) + + if index_col: + if index_col not in chart[0]: + raise exceptions.PlotlyError( + "In order to use an indexing column and assign colors to " + "the values of the index, you must choose an actual " + "column name in the dataframe or key if a list of " + "dictionaries is being used." + ) + + # validate gantt index column + index_list = [] + for dictionary in chart: + index_list.append(dictionary[index_col]) + utils.validate_index(index_list) + + # Validate colors + if isinstance(colors, dict): + colors = clrs.validate_colors_dict(colors, "rgb") + else: + colors = clrs.validate_colors(colors, "rgb") + + if reverse_colors is True: + colors.reverse() + + if not index_col: + if isinstance(colors, dict): + raise exceptions.PlotlyError( + "Error. You have set colors to a dictionary but have not " + "picked an index. An index is required if you are " + "assigning colors to particular values in a dictionary." + ) + fig = gantt( + chart, + colors, + title, + bar_width, + showgrid_x, + showgrid_y, + height, + width, + tasks=None, + task_names=None, + data=None, + group_tasks=group_tasks, + show_hover_fill=show_hover_fill, + show_colorbar=show_colorbar, + ) + return fig + else: + if not isinstance(colors, dict): + fig = gantt_colorscale( + chart, + colors, + title, + index_col, + show_colorbar, + bar_width, + showgrid_x, + showgrid_y, + height, + width, + tasks=None, + task_names=None, + data=None, + group_tasks=group_tasks, + show_hover_fill=show_hover_fill, + ) + return fig + else: + fig = gantt_dict( + chart, + colors, + title, + index_col, + show_colorbar, + bar_width, + showgrid_x, + showgrid_y, + height, + width, + tasks=None, + task_names=None, + data=None, + group_tasks=group_tasks, + show_hover_fill=show_hover_fill, + ) + return fig diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_hexbin_map.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_hexbin_map.py new file mode 100644 index 0000000000000000000000000000000000000000..792cae5e2388f66d7587c98395a90a2e252f622f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_hexbin_map.py @@ -0,0 +1,546 @@ +from plotly.express._core import build_dataframe +from plotly.express._doc import make_docstring +from plotly.express._chart_types import choropleth_map, scatter_map +import narwhals.stable.v1 as nw +import numpy as np +import warnings + + +def _project_latlon_to_wgs84(lat, lon): + """ + Projects lat and lon to WGS84, used to get regular hexagons on a mapbox map + """ + x = lon * np.pi / 180 + y = np.arctanh(np.sin(lat * np.pi / 180)) + return x, y + + +def _project_wgs84_to_latlon(x, y): + """ + Projects WGS84 to lat and lon, used to get regular hexagons on a mapbox map + """ + lon = x * 180 / np.pi + lat = (2 * np.arctan(np.exp(y)) - np.pi / 2) * 180 / np.pi + return lat, lon + + +def _getBoundsZoomLevel(lon_min, lon_max, lat_min, lat_max, mapDim): + """ + Get the mapbox zoom level given bounds and a figure dimension + Source: https://stackoverflow.com/questions/6048975/google-maps-v3-how-to-calculate-the-zoom-level-for-a-given-bounds + """ + + scale = ( + 2 # adjustment to reflect MapBox base tiles are 512x512 vs. Google's 256x256 + ) + WORLD_DIM = {"height": 256 * scale, "width": 256 * scale} + ZOOM_MAX = 18 + + def latRad(lat): + sin = np.sin(lat * np.pi / 180) + radX2 = np.log((1 + sin) / (1 - sin)) / 2 + return max(min(radX2, np.pi), -np.pi) / 2 + + def zoom(mapPx, worldPx, fraction): + return 0.95 * np.log(mapPx / worldPx / fraction) / np.log(2) + + latFraction = (latRad(lat_max) - latRad(lat_min)) / np.pi + + lngDiff = lon_max - lon_min + lngFraction = ((lngDiff + 360) if lngDiff < 0 else lngDiff) / 360 + + latZoom = zoom(mapDim["height"], WORLD_DIM["height"], latFraction) + lngZoom = zoom(mapDim["width"], WORLD_DIM["width"], lngFraction) + + return min(latZoom, lngZoom, ZOOM_MAX) + + +def _compute_hexbin(x, y, x_range, y_range, color, nx, agg_func, min_count): + """ + Computes the aggregation at hexagonal bin level. + Also defines the coordinates of the hexagons for plotting. + The binning is inspired by matplotlib's implementation. + + Parameters + ---------- + x : np.ndarray + Array of x values (shape N) + y : np.ndarray + Array of y values (shape N) + x_range : np.ndarray + Min and max x (shape 2) + y_range : np.ndarray + Min and max y (shape 2) + color : np.ndarray + Metric to aggregate at hexagon level (shape N) + nx : int + Number of hexagons horizontally + agg_func : function + Numpy compatible aggregator, this function must take a one-dimensional + np.ndarray as input and output a scalar + min_count : int + Minimum number of points in the hexagon for the hexagon to be displayed + + Returns + ------- + np.ndarray + X coordinates of each hexagon (shape M x 6) + np.ndarray + Y coordinates of each hexagon (shape M x 6) + np.ndarray + Centers of the hexagons (shape M x 2) + np.ndarray + Aggregated value in each hexagon (shape M) + + """ + xmin = x_range.min() + xmax = x_range.max() + ymin = y_range.min() + ymax = y_range.max() + + # In the x-direction, the hexagons exactly cover the region from + # xmin to xmax. Need some padding to avoid roundoff errors. + padding = 1.0e-9 * (xmax - xmin) + xmin -= padding + xmax += padding + + Dx = xmax - xmin + Dy = ymax - ymin + if Dx == 0 and Dy > 0: + dx = Dy / nx + elif Dx == 0 and Dy == 0: + dx, _ = _project_latlon_to_wgs84(1, 1) + else: + dx = Dx / nx + dy = dx * np.sqrt(3) + ny = np.ceil(Dy / dy).astype(int) + + # Center the hexagons vertically since we only want regular hexagons + ymin -= (ymin + dy * ny - ymax) / 2 + + x = (x - xmin) / dx + y = (y - ymin) / dy + ix1 = np.round(x).astype(int) + iy1 = np.round(y).astype(int) + ix2 = np.floor(x).astype(int) + iy2 = np.floor(y).astype(int) + + nx1 = nx + 1 + ny1 = ny + 1 + nx2 = nx + ny2 = ny + n = nx1 * ny1 + nx2 * ny2 + + d1 = (x - ix1) ** 2 + 3.0 * (y - iy1) ** 2 + d2 = (x - ix2 - 0.5) ** 2 + 3.0 * (y - iy2 - 0.5) ** 2 + bdist = d1 < d2 + + if color is None: + lattice1 = np.zeros((nx1, ny1)) + lattice2 = np.zeros((nx2, ny2)) + c1 = (0 <= ix1) & (ix1 < nx1) & (0 <= iy1) & (iy1 < ny1) & bdist + c2 = (0 <= ix2) & (ix2 < nx2) & (0 <= iy2) & (iy2 < ny2) & ~bdist + np.add.at(lattice1, (ix1[c1], iy1[c1]), 1) + np.add.at(lattice2, (ix2[c2], iy2[c2]), 1) + if min_count is not None: + lattice1[lattice1 < min_count] = np.nan + lattice2[lattice2 < min_count] = np.nan + accum = np.concatenate([lattice1.ravel(), lattice2.ravel()]) + good_idxs = ~np.isnan(accum) + else: + if min_count is None: + min_count = 1 + + # create accumulation arrays + lattice1 = np.empty((nx1, ny1), dtype=object) + for i in range(nx1): + for j in range(ny1): + lattice1[i, j] = [] + lattice2 = np.empty((nx2, ny2), dtype=object) + for i in range(nx2): + for j in range(ny2): + lattice2[i, j] = [] + + for i in range(len(x)): + if bdist[i]: + if 0 <= ix1[i] < nx1 and 0 <= iy1[i] < ny1: + lattice1[ix1[i], iy1[i]].append(color[i]) + else: + if 0 <= ix2[i] < nx2 and 0 <= iy2[i] < ny2: + lattice2[ix2[i], iy2[i]].append(color[i]) + + for i in range(nx1): + for j in range(ny1): + vals = lattice1[i, j] + if len(vals) >= min_count: + lattice1[i, j] = agg_func(vals) + else: + lattice1[i, j] = np.nan + for i in range(nx2): + for j in range(ny2): + vals = lattice2[i, j] + if len(vals) >= min_count: + lattice2[i, j] = agg_func(vals) + else: + lattice2[i, j] = np.nan + + accum = np.hstack( + (lattice1.astype(float).ravel(), lattice2.astype(float).ravel()) + ) + good_idxs = ~np.isnan(accum) + + agreggated_value = accum[good_idxs] + + centers = np.zeros((n, 2), float) + centers[: nx1 * ny1, 0] = np.repeat(np.arange(nx1), ny1) + centers[: nx1 * ny1, 1] = np.tile(np.arange(ny1), nx1) + centers[nx1 * ny1 :, 0] = np.repeat(np.arange(nx2) + 0.5, ny2) + centers[nx1 * ny1 :, 1] = np.tile(np.arange(ny2), nx2) + 0.5 + centers[:, 0] *= dx + centers[:, 1] *= dy + centers[:, 0] += xmin + centers[:, 1] += ymin + centers = centers[good_idxs] + + # Define normalised regular hexagon coordinates + hx = [0, 0.5, 0.5, 0, -0.5, -0.5] + hy = [ + -0.5 / np.cos(np.pi / 6), + -0.5 * np.tan(np.pi / 6), + 0.5 * np.tan(np.pi / 6), + 0.5 / np.cos(np.pi / 6), + 0.5 * np.tan(np.pi / 6), + -0.5 * np.tan(np.pi / 6), + ] + + # Number of hexagons needed + m = len(centers) + + # Coordinates for all hexagonal patches + hxs = np.array([hx] * m) * dx + np.vstack(centers[:, 0]) + hys = np.array([hy] * m) * dy / np.sqrt(3) + np.vstack(centers[:, 1]) + + return hxs, hys, centers, agreggated_value + + +def _compute_wgs84_hexbin( + lat=None, + lon=None, + lat_range=None, + lon_range=None, + color=None, + nx=None, + agg_func=None, + min_count=None, + native_namespace=None, +): + """ + Computes the lat-lon aggregation at hexagonal bin level. + Latitude and longitude need to be projected to WGS84 before aggregating + in order to display regular hexagons on the map. + + Parameters + ---------- + lat : np.ndarray + Array of latitudes (shape N) + lon : np.ndarray + Array of longitudes (shape N) + lat_range : np.ndarray + Min and max latitudes (shape 2) + lon_range : np.ndarray + Min and max longitudes (shape 2) + color : np.ndarray + Metric to aggregate at hexagon level (shape N) + nx : int + Number of hexagons horizontally + agg_func : function + Numpy compatible aggregator, this function must take a one-dimensional + np.ndarray as input and output a scalar + min_count : int + Minimum number of points in the hexagon for the hexagon to be displayed + + Returns + ------- + np.ndarray + Lat coordinates of each hexagon (shape M x 6) + np.ndarray + Lon coordinates of each hexagon (shape M x 6) + nw.Series + Unique id for each hexagon, to be used in the geojson data (shape M) + np.ndarray + Aggregated value in each hexagon (shape M) + + """ + # Project to WGS 84 + x, y = _project_latlon_to_wgs84(lat, lon) + + if lat_range is None: + lat_range = np.array([lat.min(), lat.max()]) + if lon_range is None: + lon_range = np.array([lon.min(), lon.max()]) + + x_range, y_range = _project_latlon_to_wgs84(lat_range, lon_range) + + hxs, hys, centers, agreggated_value = _compute_hexbin( + x, y, x_range, y_range, color, nx, agg_func, min_count + ) + + # Convert back to lat-lon + hexagons_lats, hexagons_lons = _project_wgs84_to_latlon(hxs, hys) + + # Create unique feature id based on hexagon center + centers = centers.astype(str) + hexagons_ids = ( + nw.from_dict( + {"x1": centers[:, 0], "x2": centers[:, 1]}, + native_namespace=native_namespace, + ) + .select(hexagons_ids=nw.concat_str([nw.col("x1"), nw.col("x2")], separator=",")) + .get_column("hexagons_ids") + ) + + return hexagons_lats, hexagons_lons, hexagons_ids, agreggated_value + + +def _hexagons_to_geojson(hexagons_lats, hexagons_lons, ids=None): + """ + Creates a geojson of hexagonal features based on the outputs of + _compute_wgs84_hexbin + """ + features = [] + if ids is None: + ids = np.arange(len(hexagons_lats)) + for lat, lon, idx in zip(hexagons_lats, hexagons_lons, ids): + points = np.array([lon, lat]).T.tolist() + points.append(points[0]) + features.append( + dict( + type="Feature", + id=idx, + geometry=dict(type="Polygon", coordinates=[points]), + ) + ) + return dict(type="FeatureCollection", features=features) + + +def create_hexbin_map( + data_frame=None, + lat=None, + lon=None, + color=None, + nx_hexagon=5, + agg_func=None, + animation_frame=None, + color_discrete_sequence=None, + color_discrete_map={}, + labels={}, + color_continuous_scale=None, + range_color=None, + color_continuous_midpoint=None, + opacity=None, + zoom=None, + center=None, + map_style=None, + title=None, + template=None, + width=None, + height=None, + min_count=None, + show_original_data=False, + original_data_marker=None, +): + """ + Returns a figure aggregating scattered points into connected hexagons + """ + args = build_dataframe(args=locals(), constructor=None) + native_namespace = nw.get_native_namespace(args["data_frame"]) + if agg_func is None: + agg_func = np.mean + + lat_range = ( + args["data_frame"] + .select( + nw.min(args["lat"]).name.suffix("_min"), + nw.max(args["lat"]).name.suffix("_max"), + ) + .to_numpy() + .squeeze() + ) + + lon_range = ( + args["data_frame"] + .select( + nw.min(args["lon"]).name.suffix("_min"), + nw.max(args["lon"]).name.suffix("_max"), + ) + .to_numpy() + .squeeze() + ) + + hexagons_lats, hexagons_lons, hexagons_ids, count = _compute_wgs84_hexbin( + lat=args["data_frame"].get_column(args["lat"]).to_numpy(), + lon=args["data_frame"].get_column(args["lon"]).to_numpy(), + lat_range=lat_range, + lon_range=lon_range, + color=None, + nx=nx_hexagon, + agg_func=agg_func, + min_count=min_count, + native_namespace=native_namespace, + ) + + geojson = _hexagons_to_geojson(hexagons_lats, hexagons_lons, hexagons_ids) + + if zoom is None: + if height is None and width is None: + mapDim = dict(height=450, width=450) + elif height is None and width is not None: + mapDim = dict(height=450, width=width) + elif height is not None and width is None: + mapDim = dict(height=height, width=height) + else: + mapDim = dict(height=height, width=width) + zoom = _getBoundsZoomLevel( + lon_range[0], lon_range[1], lat_range[0], lat_range[1], mapDim + ) + + if center is None: + center = dict(lat=lat_range.mean(), lon=lon_range.mean()) + + if args["animation_frame"] is not None: + groups = dict( + args["data_frame"] + .group_by(args["animation_frame"], drop_null_keys=True) + .__iter__() + ) + else: + groups = {(0,): args["data_frame"]} + + agg_data_frame_list = [] + for key, df in groups.items(): + _, _, hexagons_ids, aggregated_value = _compute_wgs84_hexbin( + lat=df.get_column(args["lat"]).to_numpy(), + lon=df.get_column(args["lon"]).to_numpy(), + lat_range=lat_range, + lon_range=lon_range, + color=df.get_column(args["color"]).to_numpy() if args["color"] else None, + nx=nx_hexagon, + agg_func=agg_func, + min_count=min_count, + native_namespace=native_namespace, + ) + agg_data_frame_list.append( + nw.from_dict( + { + "frame": [key[0]] * len(hexagons_ids), + "locations": hexagons_ids, + "color": aggregated_value, + }, + native_namespace=native_namespace, + ) + ) + + agg_data_frame = nw.concat(agg_data_frame_list, how="vertical").with_columns( + color=nw.col("color").cast(nw.Int64) + ) + + if range_color is None: + range_color = [ + agg_data_frame["color"].min(), + agg_data_frame["color"].max(), + ] + + fig = choropleth_map( + data_frame=agg_data_frame.to_native(), + geojson=geojson, + locations="locations", + color="color", + hover_data={"color": True, "locations": False, "frame": False}, + animation_frame=("frame" if args["animation_frame"] is not None else None), + color_discrete_sequence=color_discrete_sequence, + color_discrete_map=color_discrete_map, + labels=labels, + color_continuous_scale=color_continuous_scale, + range_color=range_color, + color_continuous_midpoint=color_continuous_midpoint, + opacity=opacity, + zoom=zoom, + center=center, + map_style=map_style, + title=title, + template=template, + width=width, + height=height, + ) + + if show_original_data: + original_fig = scatter_map( + data_frame=( + args["data_frame"].sort( + by=args["animation_frame"], + descending=False, + nulls_last=True, + ) + if args["animation_frame"] is not None + else args["data_frame"] + ).to_native(), + lat=args["lat"], + lon=args["lon"], + animation_frame=args["animation_frame"], + ) + original_fig.data[0].hoverinfo = "skip" + original_fig.data[0].hovertemplate = None + original_fig.data[0].marker = original_data_marker + + fig.add_trace(original_fig.data[0]) + + if args["animation_frame"] is not None: + for i in range(len(original_fig.frames)): + original_fig.frames[i].data[0].hoverinfo = "skip" + original_fig.frames[i].data[0].hovertemplate = None + original_fig.frames[i].data[0].marker = original_data_marker + + fig.frames[i].data = [ + fig.frames[i].data[0], + original_fig.frames[i].data[0], + ] + + return fig + + +create_hexbin_map.__doc__ = make_docstring( + create_hexbin_map, + override_dict=dict( + nx_hexagon=["int", "Number of hexagons (horizontally) to be created"], + agg_func=[ + "function", + "Numpy array aggregator, it must take as input a 1D array", + "and output a scalar value.", + ], + min_count=[ + "int", + "Minimum number of points in a hexagon for it to be displayed.", + "If None and color is not set, display all hexagons.", + "If None and color is set, only display hexagons that contain points.", + ], + show_original_data=[ + "bool", + "Whether to show the original data on top of the hexbin aggregation.", + ], + original_data_marker=["dict", "Scattermap marker options."], + ), +) + + +def create_hexbin_mapbox(*args, **kwargs): + warnings.warn( + "create_hexbin_mapbox() is deprecated and will be removed in the next major version. " + + "Please use create_hexbin_map() instead. " + + "Learn more at: https://plotly.com/python/mapbox-to-maplibre/", + stacklevel=2, + category=DeprecationWarning, + ) + if "mapbox_style" in kwargs: + kwargs["map_style"] = kwargs.pop("mapbox_style") + + return create_hexbin_map(*args, **kwargs) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_ohlc.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_ohlc.py new file mode 100644 index 0000000000000000000000000000000000000000..a0b1b4838bed44ee324199c824929e977ae8c77b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_ohlc.py @@ -0,0 +1,295 @@ +from plotly import exceptions +from plotly.graph_objs import graph_objs +from plotly.figure_factory import utils + + +# Default colours for finance charts +_DEFAULT_INCREASING_COLOR = "#3D9970" # http://clrs.cc +_DEFAULT_DECREASING_COLOR = "#FF4136" + + +def validate_ohlc(open, high, low, close, direction, **kwargs): + """ + ohlc and candlestick specific validations + + Specifically, this checks that the high value is the greatest value and + the low value is the lowest value in each unit. + + See FigureFactory.create_ohlc() or FigureFactory.create_candlestick() + for params + + :raises: (PlotlyError) If the high value is not the greatest value in + each unit. + :raises: (PlotlyError) If the low value is not the lowest value in each + unit. + :raises: (PlotlyError) If direction is not 'increasing' or 'decreasing' + """ + for lst in [open, low, close]: + for index in range(len(high)): + if high[index] < lst[index]: + raise exceptions.PlotlyError( + "Oops! Looks like some of " + "your high values are less " + "the corresponding open, " + "low, or close values. " + "Double check that your data " + "is entered in O-H-L-C order" + ) + + for lst in [open, high, close]: + for index in range(len(low)): + if low[index] > lst[index]: + raise exceptions.PlotlyError( + "Oops! Looks like some of " + "your low values are greater " + "than the corresponding high" + ", open, or close values. " + "Double check that your data " + "is entered in O-H-L-C order" + ) + + direction_opts = ("increasing", "decreasing", "both") + if direction not in direction_opts: + raise exceptions.PlotlyError( + "direction must be defined as 'increasing', 'decreasing', or 'both'" + ) + + +def make_increasing_ohlc(open, high, low, close, dates, **kwargs): + """ + Makes increasing ohlc sticks + + _make_increasing_ohlc() and _make_decreasing_ohlc separate the + increasing trace from the decreasing trace so kwargs (such as + color) can be passed separately to increasing or decreasing traces + when direction is set to 'increasing' or 'decreasing' in + FigureFactory.create_candlestick() + + :param (list) open: opening values + :param (list) high: high values + :param (list) low: low values + :param (list) close: closing values + :param (list) dates: list of datetime objects. Default: None + :param kwargs: kwargs to be passed to increasing trace via + plotly.graph_objs.Scatter. + + :rtype (trace) ohlc_incr_data: Scatter trace of all increasing ohlc + sticks. + """ + (flat_increase_x, flat_increase_y, text_increase) = _OHLC( + open, high, low, close, dates + ).get_increase() + + if "name" in kwargs: + showlegend = True + else: + kwargs.setdefault("name", "Increasing") + showlegend = False + + kwargs.setdefault("line", dict(color=_DEFAULT_INCREASING_COLOR, width=1)) + kwargs.setdefault("text", text_increase) + + ohlc_incr = dict( + type="scatter", + x=flat_increase_x, + y=flat_increase_y, + mode="lines", + showlegend=showlegend, + **kwargs, + ) + return ohlc_incr + + +def make_decreasing_ohlc(open, high, low, close, dates, **kwargs): + """ + Makes decreasing ohlc sticks + + :param (list) open: opening values + :param (list) high: high values + :param (list) low: low values + :param (list) close: closing values + :param (list) dates: list of datetime objects. Default: None + :param kwargs: kwargs to be passed to increasing trace via + plotly.graph_objs.Scatter. + + :rtype (trace) ohlc_decr_data: Scatter trace of all decreasing ohlc + sticks. + """ + (flat_decrease_x, flat_decrease_y, text_decrease) = _OHLC( + open, high, low, close, dates + ).get_decrease() + + kwargs.setdefault("line", dict(color=_DEFAULT_DECREASING_COLOR, width=1)) + kwargs.setdefault("text", text_decrease) + kwargs.setdefault("showlegend", False) + kwargs.setdefault("name", "Decreasing") + + ohlc_decr = dict( + type="scatter", x=flat_decrease_x, y=flat_decrease_y, mode="lines", **kwargs + ) + return ohlc_decr + + +def create_ohlc(open, high, low, close, dates=None, direction="both", **kwargs): + """ + **deprecated**, use instead the plotly.graph_objects trace + :class:`plotly.graph_objects.Ohlc` + + :param (list) open: opening values + :param (list) high: high values + :param (list) low: low values + :param (list) close: closing + :param (list) dates: list of datetime objects. Default: None + :param (string) direction: direction can be 'increasing', 'decreasing', + or 'both'. When the direction is 'increasing', the returned figure + consists of all units where the close value is greater than the + corresponding open value, and when the direction is 'decreasing', + the returned figure consists of all units where the close value is + less than or equal to the corresponding open value. When the + direction is 'both', both increasing and decreasing units are + returned. Default: 'both' + :param kwargs: kwargs passed through plotly.graph_objs.Scatter. + These kwargs describe other attributes about the ohlc Scatter trace + such as the color or the legend name. For more information on valid + kwargs call help(plotly.graph_objs.Scatter) + + :rtype (dict): returns a representation of an ohlc chart figure. + + Example 1: Simple OHLC chart from a Pandas DataFrame + + >>> from plotly.figure_factory import create_ohlc + >>> from datetime import datetime + + >>> import pandas as pd + >>> df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/finance-charts-apple.csv') + >>> fig = create_ohlc(df['AAPL.Open'], df['AAPL.High'], df['AAPL.Low'], df['AAPL.Close'], dates=df.index) + >>> fig.show() + """ + if dates is not None: + utils.validate_equal_length(open, high, low, close, dates) + else: + utils.validate_equal_length(open, high, low, close) + validate_ohlc(open, high, low, close, direction, **kwargs) + + if direction == "increasing": + ohlc_incr = make_increasing_ohlc(open, high, low, close, dates, **kwargs) + data = [ohlc_incr] + elif direction == "decreasing": + ohlc_decr = make_decreasing_ohlc(open, high, low, close, dates, **kwargs) + data = [ohlc_decr] + else: + ohlc_incr = make_increasing_ohlc(open, high, low, close, dates, **kwargs) + ohlc_decr = make_decreasing_ohlc(open, high, low, close, dates, **kwargs) + data = [ohlc_incr, ohlc_decr] + + layout = graph_objs.Layout(xaxis=dict(zeroline=False), hovermode="closest") + + return graph_objs.Figure(data=data, layout=layout) + + +class _OHLC(object): + """ + Refer to FigureFactory.create_ohlc_increase() for docstring. + """ + + def __init__(self, open, high, low, close, dates, **kwargs): + self.open = open + self.high = high + self.low = low + self.close = close + self.empty = [None] * len(open) + self.dates = dates + + self.all_x = [] + self.all_y = [] + self.increase_x = [] + self.increase_y = [] + self.decrease_x = [] + self.decrease_y = [] + self.get_all_xy() + self.separate_increase_decrease() + + def get_all_xy(self): + """ + Zip data to create OHLC shape + + OHLC shape: low to high vertical bar with + horizontal branches for open and close values. + If dates were added, the smallest date difference is calculated and + multiplied by .2 to get the length of the open and close branches. + If no date data was provided, the x-axis is a list of integers and the + length of the open and close branches is .2. + """ + self.all_y = list( + zip( + self.open, + self.open, + self.high, + self.low, + self.close, + self.close, + self.empty, + ) + ) + if self.dates is not None: + date_dif = [] + for i in range(len(self.dates) - 1): + date_dif.append(self.dates[i + 1] - self.dates[i]) + date_dif_min = (min(date_dif)) / 5 + self.all_x = [ + [x - date_dif_min, x, x, x, x, x + date_dif_min, None] + for x in self.dates + ] + else: + self.all_x = [ + [x - 0.2, x, x, x, x, x + 0.2, None] for x in range(len(self.open)) + ] + + def separate_increase_decrease(self): + """ + Separate data into two groups: increase and decrease + + (1) Increase, where close > open and + (2) Decrease, where close <= open + """ + for index in range(len(self.open)): + if self.close[index] is None: + pass + elif self.close[index] > self.open[index]: + self.increase_x.append(self.all_x[index]) + self.increase_y.append(self.all_y[index]) + else: + self.decrease_x.append(self.all_x[index]) + self.decrease_y.append(self.all_y[index]) + + def get_increase(self): + """ + Flatten increase data and get increase text + + :rtype (list, list, list): flat_increase_x: x-values for the increasing + trace, flat_increase_y: y=values for the increasing trace and + text_increase: hovertext for the increasing trace + """ + flat_increase_x = utils.flatten(self.increase_x) + flat_increase_y = utils.flatten(self.increase_y) + text_increase = ("Open", "Open", "High", "Low", "Close", "Close", "") * ( + len(self.increase_x) + ) + + return flat_increase_x, flat_increase_y, text_increase + + def get_decrease(self): + """ + Flatten decrease data and get decrease text + + :rtype (list, list, list): flat_decrease_x: x-values for the decreasing + trace, flat_decrease_y: y=values for the decreasing trace and + text_decrease: hovertext for the decreasing trace + """ + flat_decrease_x = utils.flatten(self.decrease_x) + flat_decrease_y = utils.flatten(self.decrease_y) + text_decrease = ("Open", "Open", "High", "Low", "Close", "Close", "") * ( + len(self.decrease_x) + ) + + return flat_decrease_x, flat_decrease_y, text_decrease diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_quiver.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_quiver.py new file mode 100644 index 0000000000000000000000000000000000000000..fa182222881bb363f0622f4fe3c890709da19325 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_quiver.py @@ -0,0 +1,265 @@ +import math + +from plotly import exceptions +from plotly.graph_objs import graph_objs +from plotly.figure_factory import utils + + +def create_quiver( + x, y, u, v, scale=0.1, arrow_scale=0.3, angle=math.pi / 9, scaleratio=None, **kwargs +): + """ + Returns data for a quiver plot. + + :param (list|ndarray) x: x coordinates of the arrow locations + :param (list|ndarray) y: y coordinates of the arrow locations + :param (list|ndarray) u: x components of the arrow vectors + :param (list|ndarray) v: y components of the arrow vectors + :param (float in [0,1]) scale: scales size of the arrows(ideally to + avoid overlap). Default = .1 + :param (float in [0,1]) arrow_scale: value multiplied to length of barb + to get length of arrowhead. Default = .3 + :param (angle in radians) angle: angle of arrowhead. Default = pi/9 + :param (positive float) scaleratio: the ratio between the scale of the y-axis + and the scale of the x-axis (scale_y / scale_x). Default = None, the + scale ratio is not fixed. + :param kwargs: kwargs passed through plotly.graph_objs.Scatter + for more information on valid kwargs call + help(plotly.graph_objs.Scatter) + + :rtype (dict): returns a representation of quiver figure. + + Example 1: Trivial Quiver + + >>> from plotly.figure_factory import create_quiver + >>> import math + + >>> # 1 Arrow from (0,0) to (1,1) + >>> fig = create_quiver(x=[0], y=[0], u=[1], v=[1], scale=1) + >>> fig.show() + + + Example 2: Quiver plot using meshgrid + + >>> from plotly.figure_factory import create_quiver + + >>> import numpy as np + >>> import math + + >>> # Add data + >>> x,y = np.meshgrid(np.arange(0, 2, .2), np.arange(0, 2, .2)) + >>> u = np.cos(x)*y + >>> v = np.sin(x)*y + + >>> #Create quiver + >>> fig = create_quiver(x, y, u, v) + >>> fig.show() + + + Example 3: Styling the quiver plot + + >>> from plotly.figure_factory import create_quiver + >>> import numpy as np + >>> import math + + >>> # Add data + >>> x, y = np.meshgrid(np.arange(-np.pi, math.pi, .5), + ... np.arange(-math.pi, math.pi, .5)) + >>> u = np.cos(x)*y + >>> v = np.sin(x)*y + + >>> # Create quiver + >>> fig = create_quiver(x, y, u, v, scale=.2, arrow_scale=.3, angle=math.pi/6, + ... name='Wind Velocity', line=dict(width=1)) + + >>> # Add title to layout + >>> fig.update_layout(title='Quiver Plot') # doctest: +SKIP + >>> fig.show() + + + Example 4: Forcing a fix scale ratio to maintain the arrow length + + >>> from plotly.figure_factory import create_quiver + >>> import numpy as np + + >>> # Add data + >>> x,y = np.meshgrid(np.arange(0.5, 3.5, .5), np.arange(0.5, 4.5, .5)) + >>> u = x + >>> v = y + >>> angle = np.arctan(v / u) + >>> norm = 0.25 + >>> u = norm * np.cos(angle) + >>> v = norm * np.sin(angle) + + >>> # Create quiver with a fix scale ratio + >>> fig = create_quiver(x, y, u, v, scale = 1, scaleratio = 0.5) + >>> fig.show() + """ + utils.validate_equal_length(x, y, u, v) + utils.validate_positive_scalars(arrow_scale=arrow_scale, scale=scale) + + if scaleratio is None: + quiver_obj = _Quiver(x, y, u, v, scale, arrow_scale, angle) + else: + quiver_obj = _Quiver(x, y, u, v, scale, arrow_scale, angle, scaleratio) + + barb_x, barb_y = quiver_obj.get_barbs() + arrow_x, arrow_y = quiver_obj.get_quiver_arrows() + + quiver_plot = graph_objs.Scatter( + x=barb_x + arrow_x, y=barb_y + arrow_y, mode="lines", **kwargs + ) + + data = [quiver_plot] + + if scaleratio is None: + layout = graph_objs.Layout(hovermode="closest") + else: + layout = graph_objs.Layout( + hovermode="closest", yaxis=dict(scaleratio=scaleratio, scaleanchor="x") + ) + + return graph_objs.Figure(data=data, layout=layout) + + +class _Quiver(object): + """ + Refer to FigureFactory.create_quiver() for docstring + """ + + def __init__(self, x, y, u, v, scale, arrow_scale, angle, scaleratio=1, **kwargs): + try: + x = utils.flatten(x) + except exceptions.PlotlyError: + pass + + try: + y = utils.flatten(y) + except exceptions.PlotlyError: + pass + + try: + u = utils.flatten(u) + except exceptions.PlotlyError: + pass + + try: + v = utils.flatten(v) + except exceptions.PlotlyError: + pass + + self.x = x + self.y = y + self.u = u + self.v = v + self.scale = scale + self.scaleratio = scaleratio + self.arrow_scale = arrow_scale + self.angle = angle + self.end_x = [] + self.end_y = [] + self.scale_uv() + barb_x, barb_y = self.get_barbs() + arrow_x, arrow_y = self.get_quiver_arrows() + + def scale_uv(self): + """ + Scales u and v to avoid overlap of the arrows. + + u and v are added to x and y to get the + endpoints of the arrows so a smaller scale value will + result in less overlap of arrows. + """ + self.u = [i * self.scale * self.scaleratio for i in self.u] + self.v = [i * self.scale for i in self.v] + + def get_barbs(self): + """ + Creates x and y startpoint and endpoint pairs + + After finding the endpoint of each barb this zips startpoint and + endpoint pairs to create 2 lists: x_values for barbs and y values + for barbs + + :rtype: (list, list) barb_x, barb_y: list of startpoint and endpoint + x_value pairs separated by a None to create the barb of the arrow, + and list of startpoint and endpoint y_value pairs separated by a + None to create the barb of the arrow. + """ + self.end_x = [i + j for i, j in zip(self.x, self.u)] + self.end_y = [i + j for i, j in zip(self.y, self.v)] + empty = [None] * len(self.x) + barb_x = utils.flatten(zip(self.x, self.end_x, empty)) + barb_y = utils.flatten(zip(self.y, self.end_y, empty)) + return barb_x, barb_y + + def get_quiver_arrows(self): + """ + Creates lists of x and y values to plot the arrows + + Gets length of each barb then calculates the length of each side of + the arrow. Gets angle of barb and applies angle to each side of the + arrowhead. Next uses arrow_scale to scale the length of arrowhead and + creates x and y values for arrowhead point1 and point2. Finally x and y + values for point1, endpoint and point2s for each arrowhead are + separated by a None and zipped to create lists of x and y values for + the arrows. + + :rtype: (list, list) arrow_x, arrow_y: list of point1, endpoint, point2 + x_values separated by a None to create the arrowhead and list of + point1, endpoint, point2 y_values separated by a None to create + the barb of the arrow. + """ + dif_x = [i - j for i, j in zip(self.end_x, self.x)] + dif_y = [i - j for i, j in zip(self.end_y, self.y)] + + # Get barb lengths(default arrow length = 30% barb length) + barb_len = [None] * len(self.x) + for index in range(len(barb_len)): + barb_len[index] = math.hypot(dif_x[index] / self.scaleratio, dif_y[index]) + + # Make arrow lengths + arrow_len = [None] * len(self.x) + arrow_len = [i * self.arrow_scale for i in barb_len] + + # Get barb angles + barb_ang = [None] * len(self.x) + for index in range(len(barb_ang)): + barb_ang[index] = math.atan2(dif_y[index], dif_x[index] / self.scaleratio) + + # Set angles to create arrow + ang1 = [i + self.angle for i in barb_ang] + ang2 = [i - self.angle for i in barb_ang] + + cos_ang1 = [None] * len(ang1) + for index in range(len(ang1)): + cos_ang1[index] = math.cos(ang1[index]) + seg1_x = [i * j for i, j in zip(arrow_len, cos_ang1)] + + sin_ang1 = [None] * len(ang1) + for index in range(len(ang1)): + sin_ang1[index] = math.sin(ang1[index]) + seg1_y = [i * j for i, j in zip(arrow_len, sin_ang1)] + + cos_ang2 = [None] * len(ang2) + for index in range(len(ang2)): + cos_ang2[index] = math.cos(ang2[index]) + seg2_x = [i * j for i, j in zip(arrow_len, cos_ang2)] + + sin_ang2 = [None] * len(ang2) + for index in range(len(ang2)): + sin_ang2[index] = math.sin(ang2[index]) + seg2_y = [i * j for i, j in zip(arrow_len, sin_ang2)] + + # Set coordinates to create arrow + for index in range(len(self.end_x)): + point1_x = [i - j * self.scaleratio for i, j in zip(self.end_x, seg1_x)] + point1_y = [i - j for i, j in zip(self.end_y, seg1_y)] + point2_x = [i - j * self.scaleratio for i, j in zip(self.end_x, seg2_x)] + point2_y = [i - j for i, j in zip(self.end_y, seg2_y)] + + # Combine lists to create arrow + empty = [None] * len(self.end_x) + arrow_x = utils.flatten(zip(point1_x, self.end_x, point2_x, empty)) + arrow_y = utils.flatten(zip(point1_y, self.end_y, point2_y, empty)) + return arrow_x, arrow_y diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_scatterplot.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_scatterplot.py new file mode 100644 index 0000000000000000000000000000000000000000..758952726150a37ecb194809a9c33415dd22697d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_scatterplot.py @@ -0,0 +1,1135 @@ +from plotly import exceptions, optional_imports +import plotly.colors as clrs +from plotly.figure_factory import utils +from plotly.graph_objs import graph_objs +from plotly.subplots import make_subplots + +pd = optional_imports.get_module("pandas") + +DIAG_CHOICES = ["scatter", "histogram", "box"] +VALID_COLORMAP_TYPES = ["cat", "seq"] + + +def endpts_to_intervals(endpts): + """ + Returns a list of intervals for categorical colormaps + + Accepts a list or tuple of sequentially increasing numbers and returns + a list representation of the mathematical intervals with these numbers + as endpoints. For example, [1, 6] returns [[-inf, 1], [1, 6], [6, inf]] + + :raises: (PlotlyError) If input is not a list or tuple + :raises: (PlotlyError) If the input contains a string + :raises: (PlotlyError) If any number does not increase after the + previous one in the sequence + """ + length = len(endpts) + # Check if endpts is a list or tuple + if not (isinstance(endpts, (tuple)) or isinstance(endpts, (list))): + raise exceptions.PlotlyError( + "The intervals_endpts argument must " + "be a list or tuple of a sequence " + "of increasing numbers." + ) + # Check if endpts contains only numbers + for item in endpts: + if isinstance(item, str): + raise exceptions.PlotlyError( + "The intervals_endpts argument " + "must be a list or tuple of a " + "sequence of increasing " + "numbers." + ) + # Check if numbers in endpts are increasing + for k in range(length - 1): + if endpts[k] >= endpts[k + 1]: + raise exceptions.PlotlyError( + "The intervals_endpts argument " + "must be a list or tuple of a " + "sequence of increasing " + "numbers." + ) + else: + intervals = [] + # add -inf to intervals + intervals.append([float("-inf"), endpts[0]]) + for k in range(length - 1): + interval = [] + interval.append(endpts[k]) + interval.append(endpts[k + 1]) + intervals.append(interval) + # add +inf to intervals + intervals.append([endpts[length - 1], float("inf")]) + return intervals + + +def hide_tick_labels_from_box_subplots(fig): + """ + Hides tick labels for box plots in scatterplotmatrix subplots. + """ + boxplot_xaxes = [] + for trace in fig["data"]: + if trace["type"] == "box": + # stores the xaxes which correspond to boxplot subplots + # since we use xaxis1, xaxis2, etc, in plotly.py + boxplot_xaxes.append("xaxis{}".format(trace["xaxis"][1:])) + for xaxis in boxplot_xaxes: + fig["layout"][xaxis]["showticklabels"] = False + + +def validate_scatterplotmatrix(df, index, diag, colormap_type, **kwargs): + """ + Validates basic inputs for FigureFactory.create_scatterplotmatrix() + + :raises: (PlotlyError) If pandas is not imported + :raises: (PlotlyError) If pandas dataframe is not inputted + :raises: (PlotlyError) If pandas dataframe has <= 1 columns + :raises: (PlotlyError) If diagonal plot choice (diag) is not one of + the viable options + :raises: (PlotlyError) If colormap_type is not a valid choice + :raises: (PlotlyError) If kwargs contains 'size', 'color' or + 'colorscale' + """ + if not pd: + raise ImportError( + "FigureFactory.scatterplotmatrix requires a pandas DataFrame." + ) + + # Check if pandas dataframe + if not isinstance(df, pd.core.frame.DataFrame): + raise exceptions.PlotlyError( + "Dataframe not inputed. Please " + "use a pandas dataframe to pro" + "duce a scatterplot matrix." + ) + + # Check if dataframe is 1 column or less + if len(df.columns) <= 1: + raise exceptions.PlotlyError( + "Dataframe has only one column. To " + "use the scatterplot matrix, use at " + "least 2 columns." + ) + + # Check that diag parameter is a valid selection + if diag not in DIAG_CHOICES: + raise exceptions.PlotlyError( + "Make sure diag is set to one of {}".format(DIAG_CHOICES) + ) + + # Check that colormap_types is a valid selection + if colormap_type not in VALID_COLORMAP_TYPES: + raise exceptions.PlotlyError( + "Must choose a valid colormap type. " + "Either 'cat' or 'seq' for a cate" + "gorical and sequential colormap " + "respectively." + ) + + # Check for not 'size' or 'color' in 'marker' of **kwargs + if "marker" in kwargs: + FORBIDDEN_PARAMS = ["size", "color", "colorscale"] + if any(param in kwargs["marker"] for param in FORBIDDEN_PARAMS): + raise exceptions.PlotlyError( + "Your kwargs dictionary cannot " + "include the 'size', 'color' or " + "'colorscale' key words inside " + "the marker dict since 'size' is " + "already an argument of the " + "scatterplot matrix function and " + "both 'color' and 'colorscale " + "are set internally." + ) + + +def scatterplot(dataframe, headers, diag, size, height, width, title, **kwargs): + """ + Refer to FigureFactory.create_scatterplotmatrix() for docstring + + Returns fig for scatterplotmatrix without index + + """ + dim = len(dataframe) + fig = make_subplots(rows=dim, cols=dim, print_grid=False) + trace_list = [] + # Insert traces into trace_list + for listy in dataframe: + for listx in dataframe: + if (listx == listy) and (diag == "histogram"): + trace = graph_objs.Histogram(x=listx, showlegend=False) + elif (listx == listy) and (diag == "box"): + trace = graph_objs.Box(y=listx, name=None, showlegend=False) + else: + if "marker" in kwargs: + kwargs["marker"]["size"] = size + trace = graph_objs.Scatter( + x=listx, y=listy, mode="markers", showlegend=False, **kwargs + ) + trace_list.append(trace) + else: + trace = graph_objs.Scatter( + x=listx, + y=listy, + mode="markers", + marker=dict(size=size), + showlegend=False, + **kwargs, + ) + trace_list.append(trace) + + trace_index = 0 + indices = range(1, dim + 1) + for y_index in indices: + for x_index in indices: + fig.append_trace(trace_list[trace_index], y_index, x_index) + trace_index += 1 + + # Insert headers into the figure + for j in range(dim): + xaxis_key = "xaxis{}".format((dim * dim) - dim + 1 + j) + fig["layout"][xaxis_key].update(title=headers[j]) + for j in range(dim): + yaxis_key = "yaxis{}".format(1 + (dim * j)) + fig["layout"][yaxis_key].update(title=headers[j]) + + fig["layout"].update(height=height, width=width, title=title, showlegend=True) + + hide_tick_labels_from_box_subplots(fig) + + return fig + + +def scatterplot_dict( + dataframe, + headers, + diag, + size, + height, + width, + title, + index, + index_vals, + endpts, + colormap, + colormap_type, + **kwargs, +): + """ + Refer to FigureFactory.create_scatterplotmatrix() for docstring + + Returns fig for scatterplotmatrix with both index and colormap picked. + Used if colormap is a dictionary with index values as keys pointing to + colors. Forces colormap_type to behave categorically because it would + not make sense colors are assigned to each index value and thus + implies that a categorical approach should be taken + + """ + + theme = colormap + dim = len(dataframe) + fig = make_subplots(rows=dim, cols=dim, print_grid=False) + trace_list = [] + legend_param = 0 + # Work over all permutations of list pairs + for listy in dataframe: + for listx in dataframe: + # create a dictionary for index_vals + unique_index_vals = {} + for name in index_vals: + if name not in unique_index_vals: + unique_index_vals[name] = [] + + # Fill all the rest of the names into the dictionary + for name in sorted(unique_index_vals.keys()): + new_listx = [] + new_listy = [] + for j in range(len(index_vals)): + if index_vals[j] == name: + new_listx.append(listx[j]) + new_listy.append(listy[j]) + # Generate trace with VISIBLE icon + if legend_param == 1: + if (listx == listy) and (diag == "histogram"): + trace = graph_objs.Histogram( + x=new_listx, marker=dict(color=theme[name]), showlegend=True + ) + elif (listx == listy) and (diag == "box"): + trace = graph_objs.Box( + y=new_listx, + name=None, + marker=dict(color=theme[name]), + showlegend=True, + ) + else: + if "marker" in kwargs: + kwargs["marker"]["size"] = size + kwargs["marker"]["color"] = theme[name] + trace = graph_objs.Scatter( + x=new_listx, + y=new_listy, + mode="markers", + name=name, + showlegend=True, + **kwargs, + ) + else: + trace = graph_objs.Scatter( + x=new_listx, + y=new_listy, + mode="markers", + name=name, + marker=dict(size=size, color=theme[name]), + showlegend=True, + **kwargs, + ) + # Generate trace with INVISIBLE icon + else: + if (listx == listy) and (diag == "histogram"): + trace = graph_objs.Histogram( + x=new_listx, + marker=dict(color=theme[name]), + showlegend=False, + ) + elif (listx == listy) and (diag == "box"): + trace = graph_objs.Box( + y=new_listx, + name=None, + marker=dict(color=theme[name]), + showlegend=False, + ) + else: + if "marker" in kwargs: + kwargs["marker"]["size"] = size + kwargs["marker"]["color"] = theme[name] + trace = graph_objs.Scatter( + x=new_listx, + y=new_listy, + mode="markers", + name=name, + showlegend=False, + **kwargs, + ) + else: + trace = graph_objs.Scatter( + x=new_listx, + y=new_listy, + mode="markers", + name=name, + marker=dict(size=size, color=theme[name]), + showlegend=False, + **kwargs, + ) + # Push the trace into dictionary + unique_index_vals[name] = trace + trace_list.append(unique_index_vals) + legend_param += 1 + + trace_index = 0 + indices = range(1, dim + 1) + for y_index in indices: + for x_index in indices: + for name in sorted(trace_list[trace_index].keys()): + fig.append_trace(trace_list[trace_index][name], y_index, x_index) + trace_index += 1 + + # Insert headers into the figure + for j in range(dim): + xaxis_key = "xaxis{}".format((dim * dim) - dim + 1 + j) + fig["layout"][xaxis_key].update(title=headers[j]) + + for j in range(dim): + yaxis_key = "yaxis{}".format(1 + (dim * j)) + fig["layout"][yaxis_key].update(title=headers[j]) + + hide_tick_labels_from_box_subplots(fig) + + if diag == "histogram": + fig["layout"].update( + height=height, width=width, title=title, showlegend=True, barmode="stack" + ) + return fig + + else: + fig["layout"].update(height=height, width=width, title=title, showlegend=True) + return fig + + +def scatterplot_theme( + dataframe, + headers, + diag, + size, + height, + width, + title, + index, + index_vals, + endpts, + colormap, + colormap_type, + **kwargs, +): + """ + Refer to FigureFactory.create_scatterplotmatrix() for docstring + + Returns fig for scatterplotmatrix with both index and colormap picked + + """ + + # Check if index is made of string values + if isinstance(index_vals[0], str): + unique_index_vals = [] + for name in index_vals: + if name not in unique_index_vals: + unique_index_vals.append(name) + n_colors_len = len(unique_index_vals) + + # Convert colormap to list of n RGB tuples + if colormap_type == "seq": + foo = clrs.color_parser(colormap, clrs.unlabel_rgb) + foo = clrs.n_colors(foo[0], foo[1], n_colors_len) + theme = clrs.color_parser(foo, clrs.label_rgb) + + if colormap_type == "cat": + # leave list of colors the same way + theme = colormap + + dim = len(dataframe) + fig = make_subplots(rows=dim, cols=dim, print_grid=False) + trace_list = [] + legend_param = 0 + # Work over all permutations of list pairs + for listy in dataframe: + for listx in dataframe: + # create a dictionary for index_vals + unique_index_vals = {} + for name in index_vals: + if name not in unique_index_vals: + unique_index_vals[name] = [] + + c_indx = 0 # color index + # Fill all the rest of the names into the dictionary + for name in sorted(unique_index_vals.keys()): + new_listx = [] + new_listy = [] + for j in range(len(index_vals)): + if index_vals[j] == name: + new_listx.append(listx[j]) + new_listy.append(listy[j]) + # Generate trace with VISIBLE icon + if legend_param == 1: + if (listx == listy) and (diag == "histogram"): + trace = graph_objs.Histogram( + x=new_listx, + marker=dict(color=theme[c_indx]), + showlegend=True, + ) + elif (listx == listy) and (diag == "box"): + trace = graph_objs.Box( + y=new_listx, + name=None, + marker=dict(color=theme[c_indx]), + showlegend=True, + ) + else: + if "marker" in kwargs: + kwargs["marker"]["size"] = size + kwargs["marker"]["color"] = theme[c_indx] + trace = graph_objs.Scatter( + x=new_listx, + y=new_listy, + mode="markers", + name=name, + showlegend=True, + **kwargs, + ) + else: + trace = graph_objs.Scatter( + x=new_listx, + y=new_listy, + mode="markers", + name=name, + marker=dict(size=size, color=theme[c_indx]), + showlegend=True, + **kwargs, + ) + # Generate trace with INVISIBLE icon + else: + if (listx == listy) and (diag == "histogram"): + trace = graph_objs.Histogram( + x=new_listx, + marker=dict(color=theme[c_indx]), + showlegend=False, + ) + elif (listx == listy) and (diag == "box"): + trace = graph_objs.Box( + y=new_listx, + name=None, + marker=dict(color=theme[c_indx]), + showlegend=False, + ) + else: + if "marker" in kwargs: + kwargs["marker"]["size"] = size + kwargs["marker"]["color"] = theme[c_indx] + trace = graph_objs.Scatter( + x=new_listx, + y=new_listy, + mode="markers", + name=name, + showlegend=False, + **kwargs, + ) + else: + trace = graph_objs.Scatter( + x=new_listx, + y=new_listy, + mode="markers", + name=name, + marker=dict(size=size, color=theme[c_indx]), + showlegend=False, + **kwargs, + ) + # Push the trace into dictionary + unique_index_vals[name] = trace + if c_indx >= (len(theme) - 1): + c_indx = -1 + c_indx += 1 + trace_list.append(unique_index_vals) + legend_param += 1 + + trace_index = 0 + indices = range(1, dim + 1) + for y_index in indices: + for x_index in indices: + for name in sorted(trace_list[trace_index].keys()): + fig.append_trace(trace_list[trace_index][name], y_index, x_index) + trace_index += 1 + + # Insert headers into the figure + for j in range(dim): + xaxis_key = "xaxis{}".format((dim * dim) - dim + 1 + j) + fig["layout"][xaxis_key].update(title=headers[j]) + + for j in range(dim): + yaxis_key = "yaxis{}".format(1 + (dim * j)) + fig["layout"][yaxis_key].update(title=headers[j]) + + hide_tick_labels_from_box_subplots(fig) + + if diag == "histogram": + fig["layout"].update( + height=height, + width=width, + title=title, + showlegend=True, + barmode="stack", + ) + return fig + + elif diag == "box": + fig["layout"].update( + height=height, width=width, title=title, showlegend=True + ) + return fig + + else: + fig["layout"].update( + height=height, width=width, title=title, showlegend=True + ) + return fig + + else: + if endpts: + intervals = utils.endpts_to_intervals(endpts) + + # Convert colormap to list of n RGB tuples + if colormap_type == "seq": + foo = clrs.color_parser(colormap, clrs.unlabel_rgb) + foo = clrs.n_colors(foo[0], foo[1], len(intervals)) + theme = clrs.color_parser(foo, clrs.label_rgb) + + if colormap_type == "cat": + # leave list of colors the same way + theme = colormap + + dim = len(dataframe) + fig = make_subplots(rows=dim, cols=dim, print_grid=False) + trace_list = [] + legend_param = 0 + # Work over all permutations of list pairs + for listy in dataframe: + for listx in dataframe: + interval_labels = {} + for interval in intervals: + interval_labels[str(interval)] = [] + + c_indx = 0 # color index + # Fill all the rest of the names into the dictionary + for interval in intervals: + new_listx = [] + new_listy = [] + for j in range(len(index_vals)): + if interval[0] < index_vals[j] <= interval[1]: + new_listx.append(listx[j]) + new_listy.append(listy[j]) + # Generate trace with VISIBLE icon + if legend_param == 1: + if (listx == listy) and (diag == "histogram"): + trace = graph_objs.Histogram( + x=new_listx, + marker=dict(color=theme[c_indx]), + showlegend=True, + ) + elif (listx == listy) and (diag == "box"): + trace = graph_objs.Box( + y=new_listx, + name=None, + marker=dict(color=theme[c_indx]), + showlegend=True, + ) + else: + if "marker" in kwargs: + kwargs["marker"]["size"] = size + (kwargs["marker"]["color"]) = theme[c_indx] + trace = graph_objs.Scatter( + x=new_listx, + y=new_listy, + mode="markers", + name=str(interval), + showlegend=True, + **kwargs, + ) + else: + trace = graph_objs.Scatter( + x=new_listx, + y=new_listy, + mode="markers", + name=str(interval), + marker=dict(size=size, color=theme[c_indx]), + showlegend=True, + **kwargs, + ) + # Generate trace with INVISIBLE icon + else: + if (listx == listy) and (diag == "histogram"): + trace = graph_objs.Histogram( + x=new_listx, + marker=dict(color=theme[c_indx]), + showlegend=False, + ) + elif (listx == listy) and (diag == "box"): + trace = graph_objs.Box( + y=new_listx, + name=None, + marker=dict(color=theme[c_indx]), + showlegend=False, + ) + else: + if "marker" in kwargs: + kwargs["marker"]["size"] = size + (kwargs["marker"]["color"]) = theme[c_indx] + trace = graph_objs.Scatter( + x=new_listx, + y=new_listy, + mode="markers", + name=str(interval), + showlegend=False, + **kwargs, + ) + else: + trace = graph_objs.Scatter( + x=new_listx, + y=new_listy, + mode="markers", + name=str(interval), + marker=dict(size=size, color=theme[c_indx]), + showlegend=False, + **kwargs, + ) + # Push the trace into dictionary + interval_labels[str(interval)] = trace + if c_indx >= (len(theme) - 1): + c_indx = -1 + c_indx += 1 + trace_list.append(interval_labels) + legend_param += 1 + + trace_index = 0 + indices = range(1, dim + 1) + for y_index in indices: + for x_index in indices: + for interval in intervals: + fig.append_trace( + trace_list[trace_index][str(interval)], y_index, x_index + ) + trace_index += 1 + + # Insert headers into the figure + for j in range(dim): + xaxis_key = "xaxis{}".format((dim * dim) - dim + 1 + j) + fig["layout"][xaxis_key].update(title=headers[j]) + for j in range(dim): + yaxis_key = "yaxis{}".format(1 + (dim * j)) + fig["layout"][yaxis_key].update(title=headers[j]) + + hide_tick_labels_from_box_subplots(fig) + + if diag == "histogram": + fig["layout"].update( + height=height, + width=width, + title=title, + showlegend=True, + barmode="stack", + ) + return fig + + elif diag == "box": + fig["layout"].update( + height=height, width=width, title=title, showlegend=True + ) + return fig + + else: + fig["layout"].update( + height=height, width=width, title=title, showlegend=True + ) + return fig + + else: + theme = colormap + + # add a copy of rgb color to theme if it contains one color + if len(theme) <= 1: + theme.append(theme[0]) + + color = [] + for incr in range(len(theme)): + color.append([1.0 / (len(theme) - 1) * incr, theme[incr]]) + + dim = len(dataframe) + fig = make_subplots(rows=dim, cols=dim, print_grid=False) + trace_list = [] + legend_param = 0 + # Run through all permutations of list pairs + for listy in dataframe: + for listx in dataframe: + # Generate trace with VISIBLE icon + if legend_param == 1: + if (listx == listy) and (diag == "histogram"): + trace = graph_objs.Histogram( + x=listx, marker=dict(color=theme[0]), showlegend=False + ) + elif (listx == listy) and (diag == "box"): + trace = graph_objs.Box( + y=listx, marker=dict(color=theme[0]), showlegend=False + ) + else: + if "marker" in kwargs: + kwargs["marker"]["size"] = size + kwargs["marker"]["color"] = index_vals + kwargs["marker"]["colorscale"] = color + kwargs["marker"]["showscale"] = True + trace = graph_objs.Scatter( + x=listx, + y=listy, + mode="markers", + showlegend=False, + **kwargs, + ) + else: + trace = graph_objs.Scatter( + x=listx, + y=listy, + mode="markers", + marker=dict( + size=size, + color=index_vals, + colorscale=color, + showscale=True, + ), + showlegend=False, + **kwargs, + ) + # Generate trace with INVISIBLE icon + else: + if (listx == listy) and (diag == "histogram"): + trace = graph_objs.Histogram( + x=listx, marker=dict(color=theme[0]), showlegend=False + ) + elif (listx == listy) and (diag == "box"): + trace = graph_objs.Box( + y=listx, marker=dict(color=theme[0]), showlegend=False + ) + else: + if "marker" in kwargs: + kwargs["marker"]["size"] = size + kwargs["marker"]["color"] = index_vals + kwargs["marker"]["colorscale"] = color + kwargs["marker"]["showscale"] = False + trace = graph_objs.Scatter( + x=listx, + y=listy, + mode="markers", + showlegend=False, + **kwargs, + ) + else: + trace = graph_objs.Scatter( + x=listx, + y=listy, + mode="markers", + marker=dict( + size=size, + color=index_vals, + colorscale=color, + showscale=False, + ), + showlegend=False, + **kwargs, + ) + # Push the trace into list + trace_list.append(trace) + legend_param += 1 + + trace_index = 0 + indices = range(1, dim + 1) + for y_index in indices: + for x_index in indices: + fig.append_trace(trace_list[trace_index], y_index, x_index) + trace_index += 1 + + # Insert headers into the figure + for j in range(dim): + xaxis_key = "xaxis{}".format((dim * dim) - dim + 1 + j) + fig["layout"][xaxis_key].update(title=headers[j]) + for j in range(dim): + yaxis_key = "yaxis{}".format(1 + (dim * j)) + fig["layout"][yaxis_key].update(title=headers[j]) + + hide_tick_labels_from_box_subplots(fig) + + if diag == "histogram": + fig["layout"].update( + height=height, + width=width, + title=title, + showlegend=True, + barmode="stack", + ) + return fig + + elif diag == "box": + fig["layout"].update( + height=height, width=width, title=title, showlegend=True + ) + return fig + + else: + fig["layout"].update( + height=height, width=width, title=title, showlegend=True + ) + return fig + + +def create_scatterplotmatrix( + df, + index=None, + endpts=None, + diag="scatter", + height=500, + width=500, + size=6, + title="Scatterplot Matrix", + colormap=None, + colormap_type="cat", + dataframe=None, + headers=None, + index_vals=None, + **kwargs, +): + """ + Returns data for a scatterplot matrix; + **deprecated**, + use instead the plotly.graph_objects trace + :class:`plotly.graph_objects.Splom`. + + :param (array) df: array of the data with column headers + :param (str) index: name of the index column in data array + :param (list|tuple) endpts: takes an increasing sequece of numbers + that defines intervals on the real line. They are used to group + the entries in an index of numbers into their corresponding + interval and therefore can be treated as categorical data + :param (str) diag: sets the chart type for the main diagonal plots. + The options are 'scatter', 'histogram' and 'box'. + :param (int|float) height: sets the height of the chart + :param (int|float) width: sets the width of the chart + :param (float) size: sets the marker size (in px) + :param (str) title: the title label of the scatterplot matrix + :param (str|tuple|list|dict) colormap: either a plotly scale name, + an rgb or hex color, a color tuple, a list of colors or a + dictionary. An rgb color is of the form 'rgb(x, y, z)' where + x, y and z belong to the interval [0, 255] and a color tuple is a + tuple of the form (a, b, c) where a, b and c belong to [0, 1]. + If colormap is a list, it must contain valid color types as its + members. + If colormap is a dictionary, all the string entries in + the index column must be a key in colormap. In this case, the + colormap_type is forced to 'cat' or categorical + :param (str) colormap_type: determines how colormap is interpreted. + Valid choices are 'seq' (sequential) and 'cat' (categorical). If + 'seq' is selected, only the first two colors in colormap will be + considered (when colormap is a list) and the index values will be + linearly interpolated between those two colors. This option is + forced if all index values are numeric. + If 'cat' is selected, a color from colormap will be assigned to + each category from index, including the intervals if endpts is + being used + :param (dict) **kwargs: a dictionary of scatterplot arguments + The only forbidden parameters are 'size', 'color' and + 'colorscale' in 'marker' + + Example 1: Vanilla Scatterplot Matrix + + >>> from plotly.graph_objs import graph_objs + >>> from plotly.figure_factory import create_scatterplotmatrix + + >>> import numpy as np + >>> import pandas as pd + + >>> # Create dataframe + >>> df = pd.DataFrame(np.random.randn(10, 2), + ... columns=['Column 1', 'Column 2']) + + >>> # Create scatterplot matrix + >>> fig = create_scatterplotmatrix(df) + >>> fig.show() + + + Example 2: Indexing a Column + + >>> from plotly.graph_objs import graph_objs + >>> from plotly.figure_factory import create_scatterplotmatrix + + >>> import numpy as np + >>> import pandas as pd + + >>> # Create dataframe with index + >>> df = pd.DataFrame(np.random.randn(10, 2), + ... columns=['A', 'B']) + + >>> # Add another column of strings to the dataframe + >>> df['Fruit'] = pd.Series(['apple', 'apple', 'grape', 'apple', 'apple', + ... 'grape', 'pear', 'pear', 'apple', 'pear']) + + >>> # Create scatterplot matrix + >>> fig = create_scatterplotmatrix(df, index='Fruit', size=10) + >>> fig.show() + + + Example 3: Styling the Diagonal Subplots + + >>> from plotly.graph_objs import graph_objs + >>> from plotly.figure_factory import create_scatterplotmatrix + + >>> import numpy as np + >>> import pandas as pd + + >>> # Create dataframe with index + >>> df = pd.DataFrame(np.random.randn(10, 4), + ... columns=['A', 'B', 'C', 'D']) + + >>> # Add another column of strings to the dataframe + >>> df['Fruit'] = pd.Series(['apple', 'apple', 'grape', 'apple', 'apple', + ... 'grape', 'pear', 'pear', 'apple', 'pear']) + + >>> # Create scatterplot matrix + >>> fig = create_scatterplotmatrix(df, diag='box', index='Fruit', height=1000, + ... width=1000) + >>> fig.show() + + + Example 4: Use a Theme to Style the Subplots + + >>> from plotly.graph_objs import graph_objs + >>> from plotly.figure_factory import create_scatterplotmatrix + + >>> import numpy as np + >>> import pandas as pd + + >>> # Create dataframe with random data + >>> df = pd.DataFrame(np.random.randn(100, 3), + ... columns=['A', 'B', 'C']) + + >>> # Create scatterplot matrix using a built-in + >>> # Plotly palette scale and indexing column 'A' + >>> fig = create_scatterplotmatrix(df, diag='histogram', index='A', + ... colormap='Blues', height=800, width=800) + >>> fig.show() + + + Example 5: Example 4 with Interval Factoring + + >>> from plotly.graph_objs import graph_objs + >>> from plotly.figure_factory import create_scatterplotmatrix + + >>> import numpy as np + >>> import pandas as pd + + >>> # Create dataframe with random data + >>> df = pd.DataFrame(np.random.randn(100, 3), + ... columns=['A', 'B', 'C']) + + >>> # Create scatterplot matrix using a list of 2 rgb tuples + >>> # and endpoints at -1, 0 and 1 + >>> fig = create_scatterplotmatrix(df, diag='histogram', index='A', + ... colormap=['rgb(140, 255, 50)', + ... 'rgb(170, 60, 115)', '#6c4774', + ... (0.5, 0.1, 0.8)], + ... endpts=[-1, 0, 1], height=800, width=800) + >>> fig.show() + + + Example 6: Using the colormap as a Dictionary + + >>> from plotly.graph_objs import graph_objs + >>> from plotly.figure_factory import create_scatterplotmatrix + + >>> import numpy as np + >>> import pandas as pd + >>> import random + + >>> # Create dataframe with random data + >>> df = pd.DataFrame(np.random.randn(100, 3), + ... columns=['Column A', + ... 'Column B', + ... 'Column C']) + + >>> # Add new color column to dataframe + >>> new_column = [] + >>> strange_colors = ['turquoise', 'limegreen', 'goldenrod'] + + >>> for j in range(100): + ... new_column.append(random.choice(strange_colors)) + >>> df['Colors'] = pd.Series(new_column, index=df.index) + + >>> # Create scatterplot matrix using a dictionary of hex color values + >>> # which correspond to actual color names in 'Colors' column + >>> fig = create_scatterplotmatrix( + ... df, diag='box', index='Colors', + ... colormap= dict( + ... turquoise = '#00F5FF', + ... limegreen = '#32CD32', + ... goldenrod = '#DAA520' + ... ), + ... colormap_type='cat', + ... height=800, width=800 + ... ) + >>> fig.show() + """ + # TODO: protected until #282 + if dataframe is None: + dataframe = [] + if headers is None: + headers = [] + if index_vals is None: + index_vals = [] + + validate_scatterplotmatrix(df, index, diag, colormap_type, **kwargs) + + # Validate colormap + if isinstance(colormap, dict): + colormap = clrs.validate_colors_dict(colormap, "rgb") + elif isinstance(colormap, str) and "rgb" not in colormap and "#" not in colormap: + if colormap not in clrs.PLOTLY_SCALES.keys(): + raise exceptions.PlotlyError( + "If 'colormap' is a string, it must be the name " + "of a Plotly Colorscale. The available colorscale " + "names are {}".format(clrs.PLOTLY_SCALES.keys()) + ) + else: + # TODO change below to allow the correct Plotly colorscale + colormap = clrs.colorscale_to_colors(clrs.PLOTLY_SCALES[colormap]) + # keep only first and last item - fix later + colormap = [colormap[0]] + [colormap[-1]] + colormap = clrs.validate_colors(colormap, "rgb") + else: + colormap = clrs.validate_colors(colormap, "rgb") + + if not index: + for name in df: + headers.append(name) + for name in headers: + dataframe.append(df[name].values.tolist()) + # Check for same data-type in df columns + utils.validate_dataframe(dataframe) + figure = scatterplot( + dataframe, headers, diag, size, height, width, title, **kwargs + ) + return figure + else: + # Validate index selection + if index not in df: + raise exceptions.PlotlyError( + "Make sure you set the index " + "input variable to one of the " + "column names of your " + "dataframe." + ) + index_vals = df[index].values.tolist() + for name in df: + if name != index: + headers.append(name) + for name in headers: + dataframe.append(df[name].values.tolist()) + + # check for same data-type in each df column + utils.validate_dataframe(dataframe) + utils.validate_index(index_vals) + + # check if all colormap keys are in the index + # if colormap is a dictionary + if isinstance(colormap, dict): + for key in colormap: + if not all(index in colormap for index in index_vals): + raise exceptions.PlotlyError( + "If colormap is a " + "dictionary, all the " + "names in the index " + "must be keys." + ) + figure = scatterplot_dict( + dataframe, + headers, + diag, + size, + height, + width, + title, + index, + index_vals, + endpts, + colormap, + colormap_type, + **kwargs, + ) + return figure + + else: + figure = scatterplot_theme( + dataframe, + headers, + diag, + size, + height, + width, + title, + index, + index_vals, + endpts, + colormap, + colormap_type, + **kwargs, + ) + return figure diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_streamline.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_streamline.py new file mode 100644 index 0000000000000000000000000000000000000000..55b74c3e7b7fd886e2d77b7b28aa77cb0c8fca49 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_streamline.py @@ -0,0 +1,406 @@ +import math + +from plotly import exceptions, optional_imports +from plotly.figure_factory import utils +from plotly.graph_objs import graph_objs + +np = optional_imports.get_module("numpy") + + +def validate_streamline(x, y): + """ + Streamline-specific validations + + Specifically, this checks that x and y are both evenly spaced, + and that the package numpy is available. + + See FigureFactory.create_streamline() for params + + :raises: (ImportError) If numpy is not available. + :raises: (PlotlyError) If x is not evenly spaced. + :raises: (PlotlyError) If y is not evenly spaced. + """ + if np is False: + raise ImportError("FigureFactory.create_streamline requires numpy") + for index in range(len(x) - 1): + if ((x[index + 1] - x[index]) - (x[1] - x[0])) > 0.0001: + raise exceptions.PlotlyError( + "x must be a 1 dimensional, evenly spaced array" + ) + for index in range(len(y) - 1): + if ((y[index + 1] - y[index]) - (y[1] - y[0])) > 0.0001: + raise exceptions.PlotlyError( + "y must be a 1 dimensional, evenly spaced array" + ) + + +def create_streamline( + x, y, u, v, density=1, angle=math.pi / 9, arrow_scale=0.09, **kwargs +): + """ + Returns data for a streamline plot. + + :param (list|ndarray) x: 1 dimensional, evenly spaced list or array + :param (list|ndarray) y: 1 dimensional, evenly spaced list or array + :param (ndarray) u: 2 dimensional array + :param (ndarray) v: 2 dimensional array + :param (float|int) density: controls the density of streamlines in + plot. This is multiplied by 30 to scale similiarly to other + available streamline functions such as matplotlib. + Default = 1 + :param (angle in radians) angle: angle of arrowhead. Default = pi/9 + :param (float in [0,1]) arrow_scale: value to scale length of arrowhead + Default = .09 + :param kwargs: kwargs passed through plotly.graph_objs.Scatter + for more information on valid kwargs call + help(plotly.graph_objs.Scatter) + + :rtype (dict): returns a representation of streamline figure. + + Example 1: Plot simple streamline and increase arrow size + + >>> from plotly.figure_factory import create_streamline + >>> import plotly.graph_objects as go + >>> import numpy as np + >>> import math + + >>> # Add data + >>> x = np.linspace(-3, 3, 100) + >>> y = np.linspace(-3, 3, 100) + >>> Y, X = np.meshgrid(x, y) + >>> u = -1 - X**2 + Y + >>> v = 1 + X - Y**2 + >>> u = u.T # Transpose + >>> v = v.T # Transpose + + >>> # Create streamline + >>> fig = create_streamline(x, y, u, v, arrow_scale=.1) + >>> fig.show() + + Example 2: from nbviewer.ipython.org/github/barbagroup/AeroPython + + >>> from plotly.figure_factory import create_streamline + >>> import numpy as np + >>> import math + + >>> # Add data + >>> N = 50 + >>> x_start, x_end = -2.0, 2.0 + >>> y_start, y_end = -1.0, 1.0 + >>> x = np.linspace(x_start, x_end, N) + >>> y = np.linspace(y_start, y_end, N) + >>> X, Y = np.meshgrid(x, y) + >>> ss = 5.0 + >>> x_s, y_s = -1.0, 0.0 + + >>> # Compute the velocity field on the mesh grid + >>> u_s = ss/(2*np.pi) * (X-x_s)/((X-x_s)**2 + (Y-y_s)**2) + >>> v_s = ss/(2*np.pi) * (Y-y_s)/((X-x_s)**2 + (Y-y_s)**2) + + >>> # Create streamline + >>> fig = create_streamline(x, y, u_s, v_s, density=2, name='streamline') + + >>> # Add source point + >>> point = go.Scatter(x=[x_s], y=[y_s], mode='markers', + ... marker_size=14, name='source point') + + >>> fig.add_trace(point) # doctest: +SKIP + >>> fig.show() + """ + utils.validate_equal_length(x, y) + utils.validate_equal_length(u, v) + validate_streamline(x, y) + utils.validate_positive_scalars(density=density, arrow_scale=arrow_scale) + + streamline_x, streamline_y = _Streamline( + x, y, u, v, density, angle, arrow_scale + ).sum_streamlines() + arrow_x, arrow_y = _Streamline( + x, y, u, v, density, angle, arrow_scale + ).get_streamline_arrows() + + streamline = graph_objs.Scatter( + x=streamline_x + arrow_x, y=streamline_y + arrow_y, mode="lines", **kwargs + ) + + data = [streamline] + layout = graph_objs.Layout(hovermode="closest") + + return graph_objs.Figure(data=data, layout=layout) + + +class _Streamline(object): + """ + Refer to FigureFactory.create_streamline() for docstring + """ + + def __init__(self, x, y, u, v, density, angle, arrow_scale, **kwargs): + self.x = np.array(x) + self.y = np.array(y) + self.u = np.array(u) + self.v = np.array(v) + self.angle = angle + self.arrow_scale = arrow_scale + self.density = int(30 * density) # Scale similarly to other functions + self.delta_x = self.x[1] - self.x[0] + self.delta_y = self.y[1] - self.y[0] + self.val_x = self.x + self.val_y = self.y + + # Set up spacing + self.blank = np.zeros((self.density, self.density)) + self.spacing_x = len(self.x) / float(self.density - 1) + self.spacing_y = len(self.y) / float(self.density - 1) + self.trajectories = [] + + # Rescale speed onto axes-coordinates + self.u = self.u / (self.x[-1] - self.x[0]) + self.v = self.v / (self.y[-1] - self.y[0]) + self.speed = np.sqrt(self.u**2 + self.v**2) + + # Rescale u and v for integrations. + self.u *= len(self.x) + self.v *= len(self.y) + self.st_x = [] + self.st_y = [] + self.get_streamlines() + streamline_x, streamline_y = self.sum_streamlines() + arrows_x, arrows_y = self.get_streamline_arrows() + + def blank_pos(self, xi, yi): + """ + Set up positions for trajectories to be used with rk4 function. + """ + return (int((xi / self.spacing_x) + 0.5), int((yi / self.spacing_y) + 0.5)) + + def value_at(self, a, xi, yi): + """ + Set up for RK4 function, based on Bokeh's streamline code + """ + if isinstance(xi, np.ndarray): + self.x = xi.astype(int) + self.y = yi.astype(int) + else: + self.val_x = int(xi) + self.val_y = int(yi) + a00 = a[self.val_y, self.val_x] + a01 = a[self.val_y, self.val_x + 1] + a10 = a[self.val_y + 1, self.val_x] + a11 = a[self.val_y + 1, self.val_x + 1] + xt = xi - self.val_x + yt = yi - self.val_y + a0 = a00 * (1 - xt) + a01 * xt + a1 = a10 * (1 - xt) + a11 * xt + return a0 * (1 - yt) + a1 * yt + + def rk4_integrate(self, x0, y0): + """ + RK4 forward and back trajectories from the initial conditions. + + Adapted from Bokeh's streamline -uses Runge-Kutta method to fill + x and y trajectories then checks length of traj (s in units of axes) + """ + + def f(xi, yi): + dt_ds = 1.0 / self.value_at(self.speed, xi, yi) + ui = self.value_at(self.u, xi, yi) + vi = self.value_at(self.v, xi, yi) + return ui * dt_ds, vi * dt_ds + + def g(xi, yi): + dt_ds = 1.0 / self.value_at(self.speed, xi, yi) + ui = self.value_at(self.u, xi, yi) + vi = self.value_at(self.v, xi, yi) + return -ui * dt_ds, -vi * dt_ds + + def check(xi, yi): + return (0 <= xi < len(self.x) - 1) and (0 <= yi < len(self.y) - 1) + + xb_changes = [] + yb_changes = [] + + def rk4(x0, y0, f): + ds = 0.01 + stotal = 0 + xi = x0 + yi = y0 + xb, yb = self.blank_pos(xi, yi) + xf_traj = [] + yf_traj = [] + while check(xi, yi): + xf_traj.append(xi) + yf_traj.append(yi) + try: + k1x, k1y = f(xi, yi) + k2x, k2y = f(xi + 0.5 * ds * k1x, yi + 0.5 * ds * k1y) + k3x, k3y = f(xi + 0.5 * ds * k2x, yi + 0.5 * ds * k2y) + k4x, k4y = f(xi + ds * k3x, yi + ds * k3y) + except IndexError: + break + xi += ds * (k1x + 2 * k2x + 2 * k3x + k4x) / 6.0 + yi += ds * (k1y + 2 * k2y + 2 * k3y + k4y) / 6.0 + if not check(xi, yi): + break + stotal += ds + new_xb, new_yb = self.blank_pos(xi, yi) + if new_xb != xb or new_yb != yb: + if self.blank[new_yb, new_xb] == 0: + self.blank[new_yb, new_xb] = 1 + xb_changes.append(new_xb) + yb_changes.append(new_yb) + xb = new_xb + yb = new_yb + else: + break + if stotal > 2: + break + return stotal, xf_traj, yf_traj + + sf, xf_traj, yf_traj = rk4(x0, y0, f) + sb, xb_traj, yb_traj = rk4(x0, y0, g) + stotal = sf + sb + x_traj = xb_traj[::-1] + xf_traj[1:] + y_traj = yb_traj[::-1] + yf_traj[1:] + + if len(x_traj) < 1: + return None + if stotal > 0.2: + initxb, inityb = self.blank_pos(x0, y0) + self.blank[inityb, initxb] = 1 + return x_traj, y_traj + else: + for xb, yb in zip(xb_changes, yb_changes): + self.blank[yb, xb] = 0 + return None + + def traj(self, xb, yb): + """ + Integrate trajectories + + :param (int) xb: results of passing xi through self.blank_pos + :param (int) xy: results of passing yi through self.blank_pos + + Calculate each trajectory based on rk4 integrate method. + """ + + if xb < 0 or xb >= self.density or yb < 0 or yb >= self.density: + return + if self.blank[yb, xb] == 0: + t = self.rk4_integrate(xb * self.spacing_x, yb * self.spacing_y) + if t is not None: + self.trajectories.append(t) + + def get_streamlines(self): + """ + Get streamlines by building trajectory set. + """ + for indent in range(self.density // 2): + for xi in range(self.density - 2 * indent): + self.traj(xi + indent, indent) + self.traj(xi + indent, self.density - 1 - indent) + self.traj(indent, xi + indent) + self.traj(self.density - 1 - indent, xi + indent) + + self.st_x = [ + np.array(t[0]) * self.delta_x + self.x[0] for t in self.trajectories + ] + self.st_y = [ + np.array(t[1]) * self.delta_y + self.y[0] for t in self.trajectories + ] + + for index in range(len(self.st_x)): + self.st_x[index] = self.st_x[index].tolist() + self.st_x[index].append(np.nan) + + for index in range(len(self.st_y)): + self.st_y[index] = self.st_y[index].tolist() + self.st_y[index].append(np.nan) + + def get_streamline_arrows(self): + """ + Makes an arrow for each streamline. + + Gets angle of streamline at 1/3 mark and creates arrow coordinates + based off of user defined angle and arrow_scale. + + :param (array) st_x: x-values for all streamlines + :param (array) st_y: y-values for all streamlines + :param (angle in radians) angle: angle of arrowhead. Default = pi/9 + :param (float in [0,1]) arrow_scale: value to scale length of arrowhead + Default = .09 + :rtype (list, list) arrows_x: x-values to create arrowhead and + arrows_y: y-values to create arrowhead + """ + arrow_end_x = np.empty((len(self.st_x))) + arrow_end_y = np.empty((len(self.st_y))) + arrow_start_x = np.empty((len(self.st_x))) + arrow_start_y = np.empty((len(self.st_y))) + for index in range(len(self.st_x)): + arrow_end_x[index] = self.st_x[index][int(len(self.st_x[index]) / 3)] + arrow_start_x[index] = self.st_x[index][ + (int(len(self.st_x[index]) / 3)) - 1 + ] + arrow_end_y[index] = self.st_y[index][int(len(self.st_y[index]) / 3)] + arrow_start_y[index] = self.st_y[index][ + (int(len(self.st_y[index]) / 3)) - 1 + ] + + dif_x = arrow_end_x - arrow_start_x + dif_y = arrow_end_y - arrow_start_y + + orig_err = np.geterr() + np.seterr(divide="ignore", invalid="ignore") + streamline_ang = np.arctan(dif_y / dif_x) + np.seterr(**orig_err) + + ang1 = streamline_ang + (self.angle) + ang2 = streamline_ang - (self.angle) + + seg1_x = np.cos(ang1) * self.arrow_scale + seg1_y = np.sin(ang1) * self.arrow_scale + seg2_x = np.cos(ang2) * self.arrow_scale + seg2_y = np.sin(ang2) * self.arrow_scale + + point1_x = np.empty((len(dif_x))) + point1_y = np.empty((len(dif_y))) + point2_x = np.empty((len(dif_x))) + point2_y = np.empty((len(dif_y))) + + for index in range(len(dif_x)): + if dif_x[index] >= 0: + point1_x[index] = arrow_end_x[index] - seg1_x[index] + point1_y[index] = arrow_end_y[index] - seg1_y[index] + point2_x[index] = arrow_end_x[index] - seg2_x[index] + point2_y[index] = arrow_end_y[index] - seg2_y[index] + else: + point1_x[index] = arrow_end_x[index] + seg1_x[index] + point1_y[index] = arrow_end_y[index] + seg1_y[index] + point2_x[index] = arrow_end_x[index] + seg2_x[index] + point2_y[index] = arrow_end_y[index] + seg2_y[index] + + space = np.empty((len(point1_x))) + space[:] = np.nan + + # Combine arrays into array + arrows_x = np.array([point1_x, arrow_end_x, point2_x, space]) + arrows_x = arrows_x.flatten("F") + arrows_x = arrows_x.tolist() + + # Combine arrays into array + arrows_y = np.array([point1_y, arrow_end_y, point2_y, space]) + arrows_y = arrows_y.flatten("F") + arrows_y = arrows_y.tolist() + + return arrows_x, arrows_y + + def sum_streamlines(self): + """ + Makes all streamlines readable as a single trace. + + :rtype (list, list): streamline_x: all x values for each streamline + combined into single list and streamline_y: all y values for each + streamline combined into single list + """ + streamline_x = sum(self.st_x, []) + streamline_y = sum(self.st_y, []) + return streamline_x, streamline_y diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_table.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_table.py new file mode 100644 index 0000000000000000000000000000000000000000..bda731f601e5e17e8861ffdaab41ee6a5cfd1b40 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_table.py @@ -0,0 +1,280 @@ +from plotly import exceptions, optional_imports +from plotly.graph_objs import graph_objs + +pd = optional_imports.get_module("pandas") + + +def validate_table(table_text, font_colors): + """ + Table-specific validations + + Check that font_colors is supplied correctly (1, 3, or len(text) + colors). + + :raises: (PlotlyError) If font_colors is supplied incorretly. + + See FigureFactory.create_table() for params + """ + font_colors_len_options = [1, 3, len(table_text)] + if len(font_colors) not in font_colors_len_options: + raise exceptions.PlotlyError( + "Oops, font_colors should be a list of length 1, 3 or len(text)" + ) + + +def create_table( + table_text, + colorscale=None, + font_colors=None, + index=False, + index_title="", + annotation_offset=0.45, + height_constant=30, + hoverinfo="none", + **kwargs, +): + """ + Function that creates data tables. + + See also the plotly.graph_objects trace + :class:`plotly.graph_objects.Table` + + :param (pandas.Dataframe | list[list]) text: data for table. + :param (str|list[list]) colorscale: Colorscale for table where the + color at value 0 is the header color, .5 is the first table color + and 1 is the second table color. (Set .5 and 1 to avoid the striped + table effect). Default=[[0, '#66b2ff'], [.5, '#d9d9d9'], + [1, '#ffffff']] + :param (list) font_colors: Color for fonts in table. Can be a single + color, three colors, or a color for each row in the table. + Default=['#000000'] (black text for the entire table) + :param (int) height_constant: Constant multiplied by # of rows to + create table height. Default=30. + :param (bool) index: Create (header-colored) index column index from + Pandas dataframe or list[0] for each list in text. Default=False. + :param (string) index_title: Title for index column. Default=''. + :param kwargs: kwargs passed through plotly.graph_objs.Heatmap. + These kwargs describe other attributes about the annotated Heatmap + trace such as the colorscale. For more information on valid kwargs + call help(plotly.graph_objs.Heatmap) + + Example 1: Simple Plotly Table + + >>> from plotly.figure_factory import create_table + + >>> text = [['Country', 'Year', 'Population'], + ... ['US', 2000, 282200000], + ... ['Canada', 2000, 27790000], + ... ['US', 2010, 309000000], + ... ['Canada', 2010, 34000000]] + + >>> table = create_table(text) + >>> table.show() + + Example 2: Table with Custom Coloring + + >>> from plotly.figure_factory import create_table + >>> text = [['Country', 'Year', 'Population'], + ... ['US', 2000, 282200000], + ... ['Canada', 2000, 27790000], + ... ['US', 2010, 309000000], + ... ['Canada', 2010, 34000000]] + >>> table = create_table(text, + ... colorscale=[[0, '#000000'], + ... [.5, '#80beff'], + ... [1, '#cce5ff']], + ... font_colors=['#ffffff', '#000000', + ... '#000000']) + >>> table.show() + + Example 3: Simple Plotly Table with Pandas + + >>> from plotly.figure_factory import create_table + >>> import pandas as pd + >>> df = pd.read_csv('http://www.stat.ubc.ca/~jenny/notOcto/STAT545A/examples/gapminder/data/gapminderDataFiveYear.txt', sep='\t') + >>> df_p = df[0:25] + >>> table_simple = create_table(df_p) + >>> table_simple.show() + + """ + + # Avoiding mutables in the call signature + colorscale = ( + colorscale + if colorscale is not None + else [[0, "#00083e"], [0.5, "#ededee"], [1, "#ffffff"]] + ) + font_colors = ( + font_colors if font_colors is not None else ["#ffffff", "#000000", "#000000"] + ) + + validate_table(table_text, font_colors) + table_matrix = _Table( + table_text, + colorscale, + font_colors, + index, + index_title, + annotation_offset, + **kwargs, + ).get_table_matrix() + annotations = _Table( + table_text, + colorscale, + font_colors, + index, + index_title, + annotation_offset, + **kwargs, + ).make_table_annotations() + + trace = dict( + type="heatmap", + z=table_matrix, + opacity=0.75, + colorscale=colorscale, + showscale=False, + hoverinfo=hoverinfo, + **kwargs, + ) + + data = [trace] + layout = dict( + annotations=annotations, + height=len(table_matrix) * height_constant + 50, + margin=dict(t=0, b=0, r=0, l=0), + yaxis=dict( + autorange="reversed", + zeroline=False, + gridwidth=2, + ticks="", + dtick=1, + tick0=0.5, + showticklabels=False, + ), + xaxis=dict( + zeroline=False, + gridwidth=2, + ticks="", + dtick=1, + tick0=-0.5, + showticklabels=False, + ), + ) + return graph_objs.Figure(data=data, layout=layout) + + +class _Table(object): + """ + Refer to TraceFactory.create_table() for docstring + """ + + def __init__( + self, + table_text, + colorscale, + font_colors, + index, + index_title, + annotation_offset, + **kwargs, + ): + if pd and isinstance(table_text, pd.DataFrame): + headers = table_text.columns.tolist() + table_text_index = table_text.index.tolist() + table_text = table_text.values.tolist() + table_text.insert(0, headers) + if index: + table_text_index.insert(0, index_title) + for i in range(len(table_text)): + table_text[i].insert(0, table_text_index[i]) + self.table_text = table_text + self.colorscale = colorscale + self.font_colors = font_colors + self.index = index + self.annotation_offset = annotation_offset + self.x = range(len(table_text[0])) + self.y = range(len(table_text)) + + def get_table_matrix(self): + """ + Create z matrix to make heatmap with striped table coloring + + :rtype (list[list]) table_matrix: z matrix to make heatmap with striped + table coloring. + """ + header = [0] * len(self.table_text[0]) + odd_row = [0.5] * len(self.table_text[0]) + even_row = [1] * len(self.table_text[0]) + table_matrix = [None] * len(self.table_text) + table_matrix[0] = header + for i in range(1, len(self.table_text), 2): + table_matrix[i] = odd_row + for i in range(2, len(self.table_text), 2): + table_matrix[i] = even_row + if self.index: + for array in table_matrix: + array[0] = 0 + return table_matrix + + def get_table_font_color(self): + """ + Fill font-color array. + + Table text color can vary by row so this extends a single color or + creates an array to set a header color and two alternating colors to + create the striped table pattern. + + :rtype (list[list]) all_font_colors: list of font colors for each row + in table. + """ + if len(self.font_colors) == 1: + all_font_colors = self.font_colors * len(self.table_text) + elif len(self.font_colors) == 3: + all_font_colors = list(range(len(self.table_text))) + all_font_colors[0] = self.font_colors[0] + for i in range(1, len(self.table_text), 2): + all_font_colors[i] = self.font_colors[1] + for i in range(2, len(self.table_text), 2): + all_font_colors[i] = self.font_colors[2] + elif len(self.font_colors) == len(self.table_text): + all_font_colors = self.font_colors + else: + all_font_colors = ["#000000"] * len(self.table_text) + return all_font_colors + + def make_table_annotations(self): + """ + Generate annotations to fill in table text + + :rtype (list) annotations: list of annotations for each cell of the + table. + """ + all_font_colors = _Table.get_table_font_color(self) + annotations = [] + for n, row in enumerate(self.table_text): + for m, val in enumerate(row): + # Bold text in header and index + format_text = ( + "" + str(val) + "" + if n == 0 or self.index and m < 1 + else str(val) + ) + # Match font color of index to font color of header + font_color = ( + self.font_colors[0] if self.index and m == 0 else all_font_colors[n] + ) + annotations.append( + graph_objs.layout.Annotation( + text=format_text, + x=self.x[m] - self.annotation_offset, + y=self.y[n], + xref="x1", + yref="y1", + align="left", + xanchor="left", + font=dict(color=font_color), + showarrow=False, + ) + ) + return annotations diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_ternary_contour.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_ternary_contour.py new file mode 100644 index 0000000000000000000000000000000000000000..b49463dc752859aaf76f8e7f6ac9d75679893fd0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_ternary_contour.py @@ -0,0 +1,692 @@ +import plotly.colors as clrs +from plotly.graph_objs import graph_objs as go +from plotly import exceptions +from plotly import optional_imports + +from skimage import measure + +np = optional_imports.get_module("numpy") +scipy_interp = optional_imports.get_module("scipy.interpolate") + +# -------------------------- Layout ------------------------------ + + +def _ternary_layout( + title="Ternary contour plot", width=550, height=525, pole_labels=["a", "b", "c"] +): + """ + Layout of ternary contour plot, to be passed to ``go.FigureWidget`` + object. + + Parameters + ========== + title : str or None + Title of ternary plot + width : int + Figure width. + height : int + Figure height. + pole_labels : str, default ['a', 'b', 'c'] + Names of the three poles of the triangle. + """ + return dict( + title=title, + width=width, + height=height, + ternary=dict( + sum=1, + aaxis=dict( + title=dict(text=pole_labels[0]), min=0.01, linewidth=2, ticks="outside" + ), + baxis=dict( + title=dict(text=pole_labels[1]), min=0.01, linewidth=2, ticks="outside" + ), + caxis=dict( + title=dict(text=pole_labels[2]), min=0.01, linewidth=2, ticks="outside" + ), + ), + showlegend=False, + ) + + +# ------------- Transformations of coordinates ------------------- + + +def _replace_zero_coords(ternary_data, delta=0.0005): + """ + Replaces zero ternary coordinates with delta and normalize the new + triplets (a, b, c). + + Parameters + ---------- + + ternary_data : ndarray of shape (N, 3) + + delta : float + Small float to regularize logarithm. + + Notes + ----- + Implements a method + by J. A. Martin-Fernandez, C. Barcelo-Vidal, V. Pawlowsky-Glahn, + Dealing with zeros and missing values in compositional data sets + using nonparametric imputation, Mathematical Geology 35 (2003), + pp 253-278. + """ + zero_mask = ternary_data == 0 + is_any_coord_zero = np.any(zero_mask, axis=0) + + unity_complement = 1 - delta * is_any_coord_zero + if np.any(unity_complement) < 0: + raise ValueError( + "The provided value of delta led to negative" + "ternary coords.Set a smaller delta" + ) + ternary_data = np.where(zero_mask, delta, unity_complement * ternary_data) + return ternary_data + + +def _ilr_transform(barycentric): + """ + Perform Isometric Log-Ratio on barycentric (compositional) data. + + Parameters + ---------- + barycentric: ndarray of shape (3, N) + Barycentric coordinates. + + References + ---------- + "An algebraic method to compute isometric logratio transformation and + back transformation of compositional data", Jarauta-Bragulat, E., + Buenestado, P.; Hervada-Sala, C., in Proc. of the Annual Conf. of the + Intl Assoc for Math Geology, 2003, pp 31-30. + """ + barycentric = np.asarray(barycentric) + x_0 = np.log(barycentric[0] / barycentric[1]) / np.sqrt(2) + x_1 = ( + 1.0 / np.sqrt(6) * np.log(barycentric[0] * barycentric[1] / barycentric[2] ** 2) + ) + ilr_tdata = np.stack((x_0, x_1)) + return ilr_tdata + + +def _ilr_inverse(x): + """ + Perform inverse Isometric Log-Ratio (ILR) transform to retrieve + barycentric (compositional) data. + + Parameters + ---------- + x : array of shape (2, N) + Coordinates in ILR space. + + References + ---------- + "An algebraic method to compute isometric logratio transformation and + back transformation of compositional data", Jarauta-Bragulat, E., + Buenestado, P.; Hervada-Sala, C., in Proc. of the Annual Conf. of the + Intl Assoc for Math Geology, 2003, pp 31-30. + """ + x = np.array(x) + matrix = np.array([[0.5, 1, 1.0], [-0.5, 1, 1.0], [0.0, 0.0, 1.0]]) + s = np.sqrt(2) / 2 + t = np.sqrt(3 / 2) + Sk = np.einsum("ik, kj -> ij", np.array([[s, t], [-s, t]]), x) + Z = -np.log(1 + np.exp(Sk).sum(axis=0)) + log_barycentric = np.einsum( + "ik, kj -> ij", matrix, np.stack((2 * s * x[0], t * x[1], Z)) + ) + iilr_tdata = np.exp(log_barycentric) + return iilr_tdata + + +def _transform_barycentric_cartesian(): + """ + Returns the transformation matrix from barycentric to Cartesian + coordinates and conversely. + """ + # reference triangle + tri_verts = np.array([[0.5, np.sqrt(3) / 2], [0, 0], [1, 0]]) + M = np.array([tri_verts[:, 0], tri_verts[:, 1], np.ones(3)]) + return M, np.linalg.inv(M) + + +def _prepare_barycentric_coord(b_coords): + """ + Check ternary coordinates and return the right barycentric coordinates. + """ + if not isinstance(b_coords, (list, np.ndarray)): + raise ValueError( + "Data should be either an array of shape (n,m)," + "or a list of n m-lists, m=2 or 3" + ) + b_coords = np.asarray(b_coords) + if b_coords.shape[0] not in (2, 3): + raise ValueError( + "A point should have 2 (a, b) or 3 (a, b, c)barycentric coordinates" + ) + if ( + (len(b_coords) == 3) + and not np.allclose(b_coords.sum(axis=0), 1, rtol=0.01) + and not np.allclose(b_coords.sum(axis=0), 100, rtol=0.01) + ): + msg = "The sum of coordinates should be 1 or 100 for all data points" + raise ValueError(msg) + + if len(b_coords) == 2: + A, B = b_coords + C = 1 - (A + B) + else: + A, B, C = b_coords / b_coords.sum(axis=0) + if np.any(np.stack((A, B, C)) < 0): + raise ValueError("Barycentric coordinates should be positive.") + return np.stack((A, B, C)) + + +def _compute_grid(coordinates, values, interp_mode="ilr"): + """ + Transform data points with Cartesian or ILR mapping, then Compute + interpolation on a regular grid. + + Parameters + ========== + + coordinates : array-like + Barycentric coordinates of data points. + values : 1-d array-like + Data points, field to be represented as contours. + interp_mode : 'ilr' (default) or 'cartesian' + Defines how data are interpolated to compute contours. + """ + if interp_mode == "cartesian": + M, invM = _transform_barycentric_cartesian() + coord_points = np.einsum("ik, kj -> ij", M, coordinates) + elif interp_mode == "ilr": + coordinates = _replace_zero_coords(coordinates) + coord_points = _ilr_transform(coordinates) + else: + raise ValueError("interp_mode should be cartesian or ilr") + xx, yy = coord_points[:2] + x_min, x_max = xx.min(), xx.max() + y_min, y_max = yy.min(), yy.max() + n_interp = max(200, int(np.sqrt(len(values)))) + gr_x = np.linspace(x_min, x_max, n_interp) + gr_y = np.linspace(y_min, y_max, n_interp) + grid_x, grid_y = np.meshgrid(gr_x, gr_y) + # We use cubic interpolation, except outside of the convex hull + # of data points where we use nearest neighbor values. + grid_z = scipy_interp.griddata( + coord_points[:2].T, values, (grid_x, grid_y), method="cubic" + ) + return grid_z, gr_x, gr_y + + +# ----------------------- Contour traces ---------------------- + + +def _polygon_area(x, y): + return 0.5 * np.abs(np.dot(x, np.roll(y, 1)) - np.dot(y, np.roll(x, 1))) + + +def _colors(ncontours, colormap=None): + """ + Return a list of ``ncontours`` colors from the ``colormap`` colorscale. + """ + if colormap in clrs.PLOTLY_SCALES.keys(): + cmap = clrs.PLOTLY_SCALES[colormap] + else: + raise exceptions.PlotlyError( + "Colorscale must be a valid Plotly Colorscale." + "The available colorscale names are {}".format(clrs.PLOTLY_SCALES.keys()) + ) + values = np.linspace(0, 1, ncontours) + vals_cmap = np.array([pair[0] for pair in cmap]) + cols = np.array([pair[1] for pair in cmap]) + inds = np.searchsorted(vals_cmap, values) + if "#" in cols[0]: # for Viridis + cols = [clrs.label_rgb(clrs.hex_to_rgb(col)) for col in cols] + + colors = [cols[0]] + for ind, val in zip(inds[1:], values[1:]): + val1, val2 = vals_cmap[ind - 1], vals_cmap[ind] + interm = (val - val1) / (val2 - val1) + col = clrs.find_intermediate_color( + cols[ind - 1], cols[ind], interm, colortype="rgb" + ) + colors.append(col) + return colors + + +def _is_invalid_contour(x, y): + """ + Utility function for _contour_trace + + Contours with an area of the order as 1 pixel are considered spurious. + """ + too_small = np.all(np.abs(x - x[0]) < 2) and np.all(np.abs(y - y[0]) < 2) + return too_small + + +def _extract_contours(im, values, colors): + """ + Utility function for _contour_trace. + + In ``im`` only one part of the domain has valid values (corresponding + to a subdomain where barycentric coordinates are well defined). When + computing contours, we need to assign values outside of this domain. + We can choose a value either smaller than all the values inside the + valid domain, or larger. This value must be chose with caution so that + no spurious contours are added. For example, if the boundary of the valid + domain has large values and the outer value is set to a small one, all + intermediate contours will be added at the boundary. + + Therefore, we compute the two sets of contours (with an outer value + smaller of larger than all values in the valid domain), and choose + the value resulting in a smaller total number of contours. There might + be a faster way to do this, but it works... + """ + mask_nan = np.isnan(im) + im_min, im_max = ( + im[np.logical_not(mask_nan)].min(), + im[np.logical_not(mask_nan)].max(), + ) + zz_min = np.copy(im) + zz_min[mask_nan] = 2 * im_min + zz_max = np.copy(im) + zz_max[mask_nan] = 2 * im_max + all_contours1, all_values1, all_areas1, all_colors1 = [], [], [], [] + all_contours2, all_values2, all_areas2, all_colors2 = [], [], [], [] + for i, val in enumerate(values): + contour_level1 = measure.find_contours(zz_min, val) + contour_level2 = measure.find_contours(zz_max, val) + all_contours1.extend(contour_level1) + all_contours2.extend(contour_level2) + all_values1.extend([val] * len(contour_level1)) + all_values2.extend([val] * len(contour_level2)) + all_areas1.extend( + [_polygon_area(contour.T[1], contour.T[0]) for contour in contour_level1] + ) + all_areas2.extend( + [_polygon_area(contour.T[1], contour.T[0]) for contour in contour_level2] + ) + all_colors1.extend([colors[i]] * len(contour_level1)) + all_colors2.extend([colors[i]] * len(contour_level2)) + if len(all_contours1) <= len(all_contours2): + return all_contours1, all_values1, all_areas1, all_colors1 + else: + return all_contours2, all_values2, all_areas2, all_colors2 + + +def _add_outer_contour( + all_contours, + all_values, + all_areas, + all_colors, + values, + val_outer, + v_min, + v_max, + colors, + color_min, + color_max, +): + """ + Utility function for _contour_trace + + Adds the background color to fill gaps outside of computed contours. + + To compute the background color, the color of the contour with largest + area (``val_outer``) is used. As background color, we choose the next + color value in the direction of the extrema of the colormap. + + Then we add information for the outer contour for the different lists + provided as arguments. + + A discrete colormap with all used colors is also returned (to be used + by colorscale trace). + """ + # The exact value of outer contour is not used when defining the trace + outer_contour = 20 * np.array([[0, 0, 1], [0, 1, 0.5]]).T + all_contours = [outer_contour] + all_contours + delta_values = np.diff(values)[0] + values = np.concatenate( + ([values[0] - delta_values], values, [values[-1] + delta_values]) + ) + colors = np.concatenate(([color_min], colors, [color_max])) + index = np.nonzero(values == val_outer)[0][0] + if index < len(values) / 2: + index -= 1 + else: + index += 1 + all_colors = [colors[index]] + all_colors + all_values = [values[index]] + all_values + all_areas = [0] + all_areas + used_colors = [color for color in colors if color in all_colors] + # Define discrete colorscale + color_number = len(used_colors) + scale = np.linspace(0, 1, color_number + 1) + discrete_cm = [] + for i, color in enumerate(used_colors): + discrete_cm.append([scale[i], used_colors[i]]) + discrete_cm.append([scale[i + 1], used_colors[i]]) + discrete_cm.append([scale[color_number], used_colors[color_number - 1]]) + + return all_contours, all_values, all_areas, all_colors, discrete_cm + + +def _contour_trace( + x, + y, + z, + ncontours=None, + colorscale="Electric", + linecolor="rgb(150,150,150)", + interp_mode="ilr", + coloring=None, + v_min=0, + v_max=1, +): + """ + Contour trace in Cartesian coordinates. + + Parameters + ========== + + x, y : array-like + Cartesian coordinates + z : array-like + Field to be represented as contours. + ncontours : int or None + Number of contours to display (determined automatically if None). + colorscale : None or str (Plotly colormap) + colorscale of the contours. + linecolor : rgb color + Color used for lines. If ``colorscale`` is not None, line colors are + determined from ``colorscale`` instead. + interp_mode : 'ilr' (default) or 'cartesian' + Defines how data are interpolated to compute contours. If 'irl', + ILR (Isometric Log-Ratio) of compositional data is performed. If + 'cartesian', contours are determined in Cartesian space. + coloring : None or 'lines' + How to display contour. Filled contours if None, lines if ``lines``. + vmin, vmax : float + Bounds of interval of values used for the colorspace + + Notes + ===== + """ + # Prepare colors + # We do not take extrema, for example for one single contour + # the color will be the middle point of the colormap + colors = _colors(ncontours + 2, colorscale) + # Values used for contours, extrema are not used + # For example for a binary array [0, 1], the value of + # the contour for ncontours=1 is 0.5. + values = np.linspace(v_min, v_max, ncontours + 2) + color_min, color_max = colors[0], colors[-1] + colors = colors[1:-1] + values = values[1:-1] + + # Color of line contours + if linecolor is None: + linecolor = "rgb(150, 150, 150)" + else: + colors = [linecolor] * ncontours + + # Retrieve all contours + all_contours, all_values, all_areas, all_colors = _extract_contours( + z, values, colors + ) + + # Now sort contours by decreasing area + order = np.argsort(all_areas)[::-1] + + # Add outer contour + all_contours, all_values, all_areas, all_colors, discrete_cm = _add_outer_contour( + all_contours, + all_values, + all_areas, + all_colors, + values, + all_values[order[0]], + v_min, + v_max, + colors, + color_min, + color_max, + ) + order = np.concatenate(([0], order + 1)) + + # Compute traces, in the order of decreasing area + traces = [] + M, invM = _transform_barycentric_cartesian() + dx = (x.max() - x.min()) / x.size + dy = (y.max() - y.min()) / y.size + for index in order: + y_contour, x_contour = all_contours[index].T + val = all_values[index] + if interp_mode == "cartesian": + bar_coords = np.dot( + invM, + np.stack((dx * x_contour, dy * y_contour, np.ones(x_contour.shape))), + ) + elif interp_mode == "ilr": + bar_coords = _ilr_inverse( + np.stack((dx * x_contour + x.min(), dy * y_contour + y.min())) + ) + if index == 0: # outer triangle + a = np.array([1, 0, 0]) + b = np.array([0, 1, 0]) + c = np.array([0, 0, 1]) + else: + a, b, c = bar_coords + if _is_invalid_contour(x_contour, y_contour): + continue + + _col = all_colors[index] if coloring == "lines" else linecolor + trace = dict( + type="scatterternary", + a=a, + b=b, + c=c, + mode="lines", + line=dict(color=_col, shape="spline", width=1), + fill="toself", + fillcolor=all_colors[index], + showlegend=True, + hoverinfo="skip", + name="%.3f" % val, + ) + if coloring == "lines": + trace["fill"] = None + traces.append(trace) + + return traces, discrete_cm + + +# -------------------- Figure Factory for ternary contour ------------- + + +def create_ternary_contour( + coordinates, + values, + pole_labels=["a", "b", "c"], + width=500, + height=500, + ncontours=None, + showscale=False, + coloring=None, + colorscale="Bluered", + linecolor=None, + title=None, + interp_mode="ilr", + showmarkers=False, +): + """ + Ternary contour plot. + + Parameters + ---------- + + coordinates : list or ndarray + Barycentric coordinates of shape (2, N) or (3, N) where N is the + number of data points. The sum of the 3 coordinates is expected + to be 1 for all data points. + values : array-like + Data points of field to be represented as contours. + pole_labels : str, default ['a', 'b', 'c'] + Names of the three poles of the triangle. + width : int + Figure width. + height : int + Figure height. + ncontours : int or None + Number of contours to display (determined automatically if None). + showscale : bool, default False + If True, a colorbar showing the color scale is displayed. + coloring : None or 'lines' + How to display contour. Filled contours if None, lines if ``lines``. + colorscale : None or str (Plotly colormap) + colorscale of the contours. + linecolor : None or rgb color + Color used for lines. ``colorscale`` has to be set to None, otherwise + line colors are determined from ``colorscale``. + title : str or None + Title of ternary plot + interp_mode : 'ilr' (default) or 'cartesian' + Defines how data are interpolated to compute contours. If 'irl', + ILR (Isometric Log-Ratio) of compositional data is performed. If + 'cartesian', contours are determined in Cartesian space. + showmarkers : bool, default False + If True, markers corresponding to input compositional points are + superimposed on contours, using the same colorscale. + + Examples + ======== + + Example 1: ternary contour plot with filled contours + + >>> import plotly.figure_factory as ff + >>> import numpy as np + >>> # Define coordinates + >>> a, b = np.mgrid[0:1:20j, 0:1:20j] + >>> mask = a + b <= 1 + >>> a = a[mask].ravel() + >>> b = b[mask].ravel() + >>> c = 1 - a - b + >>> # Values to be displayed as contours + >>> z = a * b * c + >>> fig = ff.create_ternary_contour(np.stack((a, b, c)), z) + >>> fig.show() + + It is also possible to give only two barycentric coordinates for each + point, since the sum of the three coordinates is one: + + >>> fig = ff.create_ternary_contour(np.stack((a, b)), z) + + + Example 2: ternary contour plot with line contours + + >>> fig = ff.create_ternary_contour(np.stack((a, b, c)), z, coloring='lines') + + Example 3: customize number of contours + + >>> fig = ff.create_ternary_contour(np.stack((a, b, c)), z, ncontours=8) + + Example 4: superimpose contour plot and original data as markers + + >>> fig = ff.create_ternary_contour(np.stack((a, b, c)), z, coloring='lines', + ... showmarkers=True) + + Example 5: customize title and pole labels + + >>> fig = ff.create_ternary_contour(np.stack((a, b, c)), z, + ... title='Ternary plot', + ... pole_labels=['clay', 'quartz', 'fledspar']) + """ + if scipy_interp is None: + raise ImportError( + """\ + The create_ternary_contour figure factory requires the scipy package""" + ) + sk_measure = optional_imports.get_module("skimage") + if sk_measure is None: + raise ImportError( + """\ + The create_ternary_contour figure factory requires the scikit-image + package""" + ) + if colorscale is None: + showscale = False + if ncontours is None: + ncontours = 5 + coordinates = _prepare_barycentric_coord(coordinates) + v_min, v_max = values.min(), values.max() + grid_z, gr_x, gr_y = _compute_grid(coordinates, values, interp_mode=interp_mode) + + layout = _ternary_layout( + pole_labels=pole_labels, width=width, height=height, title=title + ) + + contour_trace, discrete_cm = _contour_trace( + gr_x, + gr_y, + grid_z, + ncontours=ncontours, + colorscale=colorscale, + linecolor=linecolor, + interp_mode=interp_mode, + coloring=coloring, + v_min=v_min, + v_max=v_max, + ) + + fig = go.Figure(data=contour_trace, layout=layout) + + opacity = 1 if showmarkers else 0 + a, b, c = coordinates + hovertemplate = ( + pole_labels[0] + + ": %{a:.3f}
" + + pole_labels[1] + + ": %{b:.3f}
" + + pole_labels[2] + + ": %{c:.3f}
" + "z: %{marker.color:.3f}" + ) + + fig.add_scatterternary( + a=a, + b=b, + c=c, + mode="markers", + marker={ + "color": values, + "colorscale": colorscale, + "line": {"color": "rgb(120, 120, 120)", "width": int(coloring != "lines")}, + }, + opacity=opacity, + hovertemplate=hovertemplate, + ) + if showscale: + if not showmarkers: + colorscale = discrete_cm + colorbar = dict( + { + "type": "scatterternary", + "a": [None], + "b": [None], + "c": [None], + "marker": { + "cmin": values.min(), + "cmax": values.max(), + "colorscale": colorscale, + "showscale": True, + }, + "mode": "markers", + } + ) + fig.add_trace(colorbar) + + return fig diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_trisurf.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_trisurf.py new file mode 100644 index 0000000000000000000000000000000000000000..f935292efb7e15613ef297cc95fd2854f59c3125 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_trisurf.py @@ -0,0 +1,509 @@ +from plotly import exceptions, optional_imports +import plotly.colors as clrs +from plotly.graph_objs import graph_objs + +np = optional_imports.get_module("numpy") + + +def map_face2color(face, colormap, scale, vmin, vmax): + """ + Normalize facecolor values by vmin/vmax and return rgb-color strings + + This function takes a tuple color along with a colormap and a minimum + (vmin) and maximum (vmax) range of possible mean distances for the + given parametrized surface. It returns an rgb color based on the mean + distance between vmin and vmax + + """ + if vmin >= vmax: + raise exceptions.PlotlyError( + "Incorrect relation between vmin " + "and vmax. The vmin value cannot be " + "bigger than or equal to the value " + "of vmax." + ) + if len(colormap) == 1: + # color each triangle face with the same color in colormap + face_color = colormap[0] + face_color = clrs.convert_to_RGB_255(face_color) + face_color = clrs.label_rgb(face_color) + return face_color + if face == vmax: + # pick last color in colormap + face_color = colormap[-1] + face_color = clrs.convert_to_RGB_255(face_color) + face_color = clrs.label_rgb(face_color) + return face_color + else: + if scale is None: + # find the normalized distance t of a triangle face between + # vmin and vmax where the distance is between 0 and 1 + t = (face - vmin) / float((vmax - vmin)) + low_color_index = int(t / (1.0 / (len(colormap) - 1))) + + face_color = clrs.find_intermediate_color( + colormap[low_color_index], + colormap[low_color_index + 1], + t * (len(colormap) - 1) - low_color_index, + ) + + face_color = clrs.convert_to_RGB_255(face_color) + face_color = clrs.label_rgb(face_color) + else: + # find the face color for a non-linearly interpolated scale + t = (face - vmin) / float((vmax - vmin)) + + low_color_index = 0 + for k in range(len(scale) - 1): + if scale[k] <= t < scale[k + 1]: + break + low_color_index += 1 + + low_scale_val = scale[low_color_index] + high_scale_val = scale[low_color_index + 1] + + face_color = clrs.find_intermediate_color( + colormap[low_color_index], + colormap[low_color_index + 1], + (t - low_scale_val) / (high_scale_val - low_scale_val), + ) + + face_color = clrs.convert_to_RGB_255(face_color) + face_color = clrs.label_rgb(face_color) + return face_color + + +def trisurf( + x, + y, + z, + simplices, + show_colorbar, + edges_color, + scale, + colormap=None, + color_func=None, + plot_edges=False, + x_edge=None, + y_edge=None, + z_edge=None, + facecolor=None, +): + """ + Refer to FigureFactory.create_trisurf() for docstring + """ + # numpy import check + if not np: + raise ImportError("FigureFactory._trisurf() requires numpy imported.") + points3D = np.vstack((x, y, z)).T + simplices = np.atleast_2d(simplices) + + # vertices of the surface triangles + tri_vertices = points3D[simplices] + + # Define colors for the triangle faces + if color_func is None: + # mean values of z-coordinates of triangle vertices + mean_dists = tri_vertices[:, :, 2].mean(-1) + elif isinstance(color_func, (list, np.ndarray)): + # Pre-computed list / array of values to map onto color + if len(color_func) != len(simplices): + raise ValueError( + "If color_func is a list/array, it must " + "be the same length as simplices." + ) + + # convert all colors in color_func to rgb + for index in range(len(color_func)): + if isinstance(color_func[index], str): + if "#" in color_func[index]: + foo = clrs.hex_to_rgb(color_func[index]) + color_func[index] = clrs.label_rgb(foo) + + if isinstance(color_func[index], tuple): + foo = clrs.convert_to_RGB_255(color_func[index]) + color_func[index] = clrs.label_rgb(foo) + + mean_dists = np.asarray(color_func) + else: + # apply user inputted function to calculate + # custom coloring for triangle vertices + mean_dists = [] + for triangle in tri_vertices: + dists = [] + for vertex in triangle: + dist = color_func(vertex[0], vertex[1], vertex[2]) + dists.append(dist) + mean_dists.append(np.mean(dists)) + mean_dists = np.asarray(mean_dists) + + # Check if facecolors are already strings and can be skipped + if isinstance(mean_dists[0], str): + facecolor = mean_dists + else: + min_mean_dists = np.min(mean_dists) + max_mean_dists = np.max(mean_dists) + + if facecolor is None: + facecolor = [] + for index in range(len(mean_dists)): + color = map_face2color( + mean_dists[index], colormap, scale, min_mean_dists, max_mean_dists + ) + facecolor.append(color) + + # Make sure facecolor is a list so output is consistent across Pythons + facecolor = np.asarray(facecolor) + ii, jj, kk = simplices.T + + triangles = graph_objs.Mesh3d( + x=x, y=y, z=z, facecolor=facecolor, i=ii, j=jj, k=kk, name="" + ) + + mean_dists_are_numbers = not isinstance(mean_dists[0], str) + + if mean_dists_are_numbers and show_colorbar is True: + # make a colorscale from the colors + colorscale = clrs.make_colorscale(colormap, scale) + colorscale = clrs.convert_colorscale_to_rgb(colorscale) + + colorbar = graph_objs.Scatter3d( + x=x[:1], + y=y[:1], + z=z[:1], + mode="markers", + marker=dict( + size=0.1, + color=[min_mean_dists, max_mean_dists], + colorscale=colorscale, + showscale=True, + ), + hoverinfo="none", + showlegend=False, + ) + + # the triangle sides are not plotted + if plot_edges is False: + if mean_dists_are_numbers and show_colorbar is True: + return [triangles, colorbar] + else: + return [triangles] + + # define the lists x_edge, y_edge and z_edge, of x, y, resp z + # coordinates of edge end points for each triangle + # None separates data corresponding to two consecutive triangles + is_none = [ii is None for ii in [x_edge, y_edge, z_edge]] + if any(is_none): + if not all(is_none): + raise ValueError( + "If any (x_edge, y_edge, z_edge) is None, all must be None" + ) + else: + x_edge = [] + y_edge = [] + z_edge = [] + + # Pull indices we care about, then add a None column to separate tris + ixs_triangles = [0, 1, 2, 0] + pull_edges = tri_vertices[:, ixs_triangles, :] + x_edge_pull = np.hstack( + [pull_edges[:, :, 0], np.tile(None, [pull_edges.shape[0], 1])] + ) + y_edge_pull = np.hstack( + [pull_edges[:, :, 1], np.tile(None, [pull_edges.shape[0], 1])] + ) + z_edge_pull = np.hstack( + [pull_edges[:, :, 2], np.tile(None, [pull_edges.shape[0], 1])] + ) + + # Now unravel the edges into a 1-d vector for plotting + x_edge = np.hstack([x_edge, x_edge_pull.reshape([1, -1])[0]]) + y_edge = np.hstack([y_edge, y_edge_pull.reshape([1, -1])[0]]) + z_edge = np.hstack([z_edge, z_edge_pull.reshape([1, -1])[0]]) + + if not (len(x_edge) == len(y_edge) == len(z_edge)): + raise exceptions.PlotlyError( + "The lengths of x_edge, y_edge and z_edge are not the same." + ) + + # define the lines for plotting + lines = graph_objs.Scatter3d( + x=x_edge, + y=y_edge, + z=z_edge, + mode="lines", + line=graph_objs.scatter3d.Line(color=edges_color, width=1.5), + showlegend=False, + ) + + if mean_dists_are_numbers and show_colorbar is True: + return [triangles, lines, colorbar] + else: + return [triangles, lines] + + +def create_trisurf( + x, + y, + z, + simplices, + colormap=None, + show_colorbar=True, + scale=None, + color_func=None, + title="Trisurf Plot", + plot_edges=True, + showbackground=True, + backgroundcolor="rgb(230, 230, 230)", + gridcolor="rgb(255, 255, 255)", + zerolinecolor="rgb(255, 255, 255)", + edges_color="rgb(50, 50, 50)", + height=800, + width=800, + aspectratio=None, +): + """ + Returns figure for a triangulated surface plot + + :param (array) x: data values of x in a 1D array + :param (array) y: data values of y in a 1D array + :param (array) z: data values of z in a 1D array + :param (array) simplices: an array of shape (ntri, 3) where ntri is + the number of triangles in the triangularization. Each row of the + array contains the indicies of the verticies of each triangle + :param (str|tuple|list) colormap: either a plotly scale name, an rgb + or hex color, a color tuple or a list of colors. An rgb color is + of the form 'rgb(x, y, z)' where x, y, z belong to the interval + [0, 255] and a color tuple is a tuple of the form (a, b, c) where + a, b and c belong to [0, 1]. If colormap is a list, it must + contain the valid color types aforementioned as its members + :param (bool) show_colorbar: determines if colorbar is visible + :param (list|array) scale: sets the scale values to be used if a non- + linearly interpolated colormap is desired. If left as None, a + linear interpolation between the colors will be excecuted + :param (function|list) color_func: The parameter that determines the + coloring of the surface. Takes either a function with 3 arguments + x, y, z or a list/array of color values the same length as + simplices. If None, coloring will only depend on the z axis + :param (str) title: title of the plot + :param (bool) plot_edges: determines if the triangles on the trisurf + are visible + :param (bool) showbackground: makes background in plot visible + :param (str) backgroundcolor: color of background. Takes a string of + the form 'rgb(x,y,z)' x,y,z are between 0 and 255 inclusive + :param (str) gridcolor: color of the gridlines besides the axes. Takes + a string of the form 'rgb(x,y,z)' x,y,z are between 0 and 255 + inclusive + :param (str) zerolinecolor: color of the axes. Takes a string of the + form 'rgb(x,y,z)' x,y,z are between 0 and 255 inclusive + :param (str) edges_color: color of the edges, if plot_edges is True + :param (int|float) height: the height of the plot (in pixels) + :param (int|float) width: the width of the plot (in pixels) + :param (dict) aspectratio: a dictionary of the aspect ratio values for + the x, y and z axes. 'x', 'y' and 'z' take (int|float) values + + Example 1: Sphere + + >>> # Necessary Imports for Trisurf + >>> import numpy as np + >>> from scipy.spatial import Delaunay + + >>> from plotly.figure_factory import create_trisurf + >>> from plotly.graph_objs import graph_objs + + >>> # Make data for plot + >>> u = np.linspace(0, 2*np.pi, 20) + >>> v = np.linspace(0, np.pi, 20) + >>> u,v = np.meshgrid(u,v) + >>> u = u.flatten() + >>> v = v.flatten() + + >>> x = np.sin(v)*np.cos(u) + >>> y = np.sin(v)*np.sin(u) + >>> z = np.cos(v) + + >>> points2D = np.vstack([u,v]).T + >>> tri = Delaunay(points2D) + >>> simplices = tri.simplices + + >>> # Create a figure + >>> fig1 = create_trisurf(x=x, y=y, z=z, colormap="Rainbow", + ... simplices=simplices) + + Example 2: Torus + + >>> # Necessary Imports for Trisurf + >>> import numpy as np + >>> from scipy.spatial import Delaunay + + >>> from plotly.figure_factory import create_trisurf + >>> from plotly.graph_objs import graph_objs + + >>> # Make data for plot + >>> u = np.linspace(0, 2*np.pi, 20) + >>> v = np.linspace(0, 2*np.pi, 20) + >>> u,v = np.meshgrid(u,v) + >>> u = u.flatten() + >>> v = v.flatten() + + >>> x = (3 + (np.cos(v)))*np.cos(u) + >>> y = (3 + (np.cos(v)))*np.sin(u) + >>> z = np.sin(v) + + >>> points2D = np.vstack([u,v]).T + >>> tri = Delaunay(points2D) + >>> simplices = tri.simplices + + >>> # Create a figure + >>> fig1 = create_trisurf(x=x, y=y, z=z, colormap="Viridis", + ... simplices=simplices) + + Example 3: Mobius Band + + >>> # Necessary Imports for Trisurf + >>> import numpy as np + >>> from scipy.spatial import Delaunay + + >>> from plotly.figure_factory import create_trisurf + >>> from plotly.graph_objs import graph_objs + + >>> # Make data for plot + >>> u = np.linspace(0, 2*np.pi, 24) + >>> v = np.linspace(-1, 1, 8) + >>> u,v = np.meshgrid(u,v) + >>> u = u.flatten() + >>> v = v.flatten() + + >>> tp = 1 + 0.5*v*np.cos(u/2.) + >>> x = tp*np.cos(u) + >>> y = tp*np.sin(u) + >>> z = 0.5*v*np.sin(u/2.) + + >>> points2D = np.vstack([u,v]).T + >>> tri = Delaunay(points2D) + >>> simplices = tri.simplices + + >>> # Create a figure + >>> fig1 = create_trisurf(x=x, y=y, z=z, colormap=[(0.2, 0.4, 0.6), (1, 1, 1)], + ... simplices=simplices) + + Example 4: Using a Custom Colormap Function with Light Cone + + >>> # Necessary Imports for Trisurf + >>> import numpy as np + >>> from scipy.spatial import Delaunay + + >>> from plotly.figure_factory import create_trisurf + >>> from plotly.graph_objs import graph_objs + + >>> # Make data for plot + >>> u=np.linspace(-np.pi, np.pi, 30) + >>> v=np.linspace(-np.pi, np.pi, 30) + >>> u,v=np.meshgrid(u,v) + >>> u=u.flatten() + >>> v=v.flatten() + + >>> x = u + >>> y = u*np.cos(v) + >>> z = u*np.sin(v) + + >>> points2D = np.vstack([u,v]).T + >>> tri = Delaunay(points2D) + >>> simplices = tri.simplices + + >>> # Define distance function + >>> def dist_origin(x, y, z): + ... return np.sqrt((1.0 * x)**2 + (1.0 * y)**2 + (1.0 * z)**2) + + >>> # Create a figure + >>> fig1 = create_trisurf(x=x, y=y, z=z, + ... colormap=['#FFFFFF', '#E4FFFE', + ... '#A4F6F9', '#FF99FE', + ... '#BA52ED'], + ... scale=[0, 0.6, 0.71, 0.89, 1], + ... simplices=simplices, + ... color_func=dist_origin) + + Example 5: Enter color_func as a list of colors + + >>> # Necessary Imports for Trisurf + >>> import numpy as np + >>> from scipy.spatial import Delaunay + >>> import random + + >>> from plotly.figure_factory import create_trisurf + >>> from plotly.graph_objs import graph_objs + + >>> # Make data for plot + >>> u=np.linspace(-np.pi, np.pi, 30) + >>> v=np.linspace(-np.pi, np.pi, 30) + >>> u,v=np.meshgrid(u,v) + >>> u=u.flatten() + >>> v=v.flatten() + + >>> x = u + >>> y = u*np.cos(v) + >>> z = u*np.sin(v) + + >>> points2D = np.vstack([u,v]).T + >>> tri = Delaunay(points2D) + >>> simplices = tri.simplices + + + >>> colors = [] + >>> color_choices = ['rgb(0, 0, 0)', '#6c4774', '#d6c7dd'] + + >>> for index in range(len(simplices)): + ... colors.append(random.choice(color_choices)) + + >>> fig = create_trisurf( + ... x, y, z, simplices, + ... color_func=colors, + ... show_colorbar=True, + ... edges_color='rgb(2, 85, 180)', + ... title=' Modern Art' + ... ) + """ + if aspectratio is None: + aspectratio = {"x": 1, "y": 1, "z": 1} + + # Validate colormap + clrs.validate_colors(colormap) + colormap, scale = clrs.convert_colors_to_same_type( + colormap, colortype="tuple", return_default_colors=True, scale=scale + ) + + data1 = trisurf( + x, + y, + z, + simplices, + show_colorbar=show_colorbar, + color_func=color_func, + colormap=colormap, + scale=scale, + edges_color=edges_color, + plot_edges=plot_edges, + ) + + axis = dict( + showbackground=showbackground, + backgroundcolor=backgroundcolor, + gridcolor=gridcolor, + zerolinecolor=zerolinecolor, + ) + layout = graph_objs.Layout( + title=title, + width=width, + height=height, + scene=graph_objs.layout.Scene( + xaxis=graph_objs.layout.scene.XAxis(**axis), + yaxis=graph_objs.layout.scene.YAxis(**axis), + zaxis=graph_objs.layout.scene.ZAxis(**axis), + aspectratio=dict( + x=aspectratio["x"], y=aspectratio["y"], z=aspectratio["z"] + ), + ), + ) + + return graph_objs.Figure(data=data1, layout=layout) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_violin.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_violin.py new file mode 100644 index 0000000000000000000000000000000000000000..55924e69238349e5fbd032c12c428a8d881367f5 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/_violin.py @@ -0,0 +1,704 @@ +from numbers import Number + +from plotly import exceptions, optional_imports +import plotly.colors as clrs +from plotly.graph_objs import graph_objs +from plotly.subplots import make_subplots + +pd = optional_imports.get_module("pandas") +np = optional_imports.get_module("numpy") +scipy_stats = optional_imports.get_module("scipy.stats") + + +def calc_stats(data): + """ + Calculate statistics for use in violin plot. + """ + x = np.asarray(data, float) + vals_min = np.min(x) + vals_max = np.max(x) + q2 = np.percentile(x, 50, interpolation="linear") + q1 = np.percentile(x, 25, interpolation="lower") + q3 = np.percentile(x, 75, interpolation="higher") + iqr = q3 - q1 + whisker_dist = 1.5 * iqr + + # in order to prevent drawing whiskers outside the interval + # of data one defines the whisker positions as: + d1 = np.min(x[x >= (q1 - whisker_dist)]) + d2 = np.max(x[x <= (q3 + whisker_dist)]) + return { + "min": vals_min, + "max": vals_max, + "q1": q1, + "q2": q2, + "q3": q3, + "d1": d1, + "d2": d2, + } + + +def make_half_violin(x, y, fillcolor="#1f77b4", linecolor="rgb(0, 0, 0)"): + """ + Produces a sideways probability distribution fig violin plot. + """ + text = [ + "(pdf(y), y)=(" + "{:0.2f}".format(x[i]) + ", " + "{:0.2f}".format(y[i]) + ")" + for i in range(len(x)) + ] + + return graph_objs.Scatter( + x=x, + y=y, + mode="lines", + name="", + text=text, + fill="tonextx", + fillcolor=fillcolor, + line=graph_objs.scatter.Line(width=0.5, color=linecolor, shape="spline"), + hoverinfo="text", + opacity=0.5, + ) + + +def make_violin_rugplot(vals, pdf_max, distance, color="#1f77b4"): + """ + Returns a rugplot fig for a violin plot. + """ + return graph_objs.Scatter( + y=vals, + x=[-pdf_max - distance] * len(vals), + marker=graph_objs.scatter.Marker(color=color, symbol="line-ew-open"), + mode="markers", + name="", + showlegend=False, + hoverinfo="y", + ) + + +def make_non_outlier_interval(d1, d2): + """ + Returns the scatterplot fig of most of a violin plot. + """ + return graph_objs.Scatter( + x=[0, 0], + y=[d1, d2], + name="", + mode="lines", + line=graph_objs.scatter.Line(width=1.5, color="rgb(0,0,0)"), + ) + + +def make_quartiles(q1, q3): + """ + Makes the upper and lower quartiles for a violin plot. + """ + return graph_objs.Scatter( + x=[0, 0], + y=[q1, q3], + text=[ + "lower-quartile: " + "{:0.2f}".format(q1), + "upper-quartile: " + "{:0.2f}".format(q3), + ], + mode="lines", + line=graph_objs.scatter.Line(width=4, color="rgb(0,0,0)"), + hoverinfo="text", + ) + + +def make_median(q2): + """ + Formats the 'median' hovertext for a violin plot. + """ + return graph_objs.Scatter( + x=[0], + y=[q2], + text=["median: " + "{:0.2f}".format(q2)], + mode="markers", + marker=dict(symbol="square", color="rgb(255,255,255)"), + hoverinfo="text", + ) + + +def make_XAxis(xaxis_title, xaxis_range): + """ + Makes the x-axis for a violin plot. + """ + xaxis = graph_objs.layout.XAxis( + title=xaxis_title, + range=xaxis_range, + showgrid=False, + zeroline=False, + showline=False, + mirror=False, + ticks="", + showticklabels=False, + ) + return xaxis + + +def make_YAxis(yaxis_title): + """ + Makes the y-axis for a violin plot. + """ + yaxis = graph_objs.layout.YAxis( + title=yaxis_title, + showticklabels=True, + autorange=True, + ticklen=4, + showline=True, + zeroline=False, + showgrid=False, + mirror=False, + ) + return yaxis + + +def violinplot(vals, fillcolor="#1f77b4", rugplot=True): + """ + Refer to FigureFactory.create_violin() for docstring. + """ + vals = np.asarray(vals, float) + # summary statistics + vals_min = calc_stats(vals)["min"] + vals_max = calc_stats(vals)["max"] + q1 = calc_stats(vals)["q1"] + q2 = calc_stats(vals)["q2"] + q3 = calc_stats(vals)["q3"] + d1 = calc_stats(vals)["d1"] + d2 = calc_stats(vals)["d2"] + + # kernel density estimation of pdf + pdf = scipy_stats.gaussian_kde(vals) + # grid over the data interval + xx = np.linspace(vals_min, vals_max, 100) + # evaluate the pdf at the grid xx + yy = pdf(xx) + max_pdf = np.max(yy) + # distance from the violin plot to rugplot + distance = (2.0 * max_pdf) / 10 if rugplot else 0 + # range for x values in the plot + plot_xrange = [-max_pdf - distance - 0.1, max_pdf + 0.1] + plot_data = [ + make_half_violin(-yy, xx, fillcolor=fillcolor), + make_half_violin(yy, xx, fillcolor=fillcolor), + make_non_outlier_interval(d1, d2), + make_quartiles(q1, q3), + make_median(q2), + ] + if rugplot: + plot_data.append( + make_violin_rugplot(vals, max_pdf, distance=distance, color=fillcolor) + ) + return plot_data, plot_xrange + + +def violin_no_colorscale( + data, + data_header, + group_header, + colors, + use_colorscale, + group_stats, + rugplot, + sort, + height, + width, + title, +): + """ + Refer to FigureFactory.create_violin() for docstring. + + Returns fig for violin plot without colorscale. + + """ + + # collect all group names + group_name = [] + for name in data[group_header]: + if name not in group_name: + group_name.append(name) + if sort: + group_name.sort() + + gb = data.groupby([group_header]) + L = len(group_name) + + fig = make_subplots( + rows=1, cols=L, shared_yaxes=True, horizontal_spacing=0.025, print_grid=False + ) + color_index = 0 + for k, gr in enumerate(group_name): + vals = np.asarray(gb.get_group(gr)[data_header], float) + if color_index >= len(colors): + color_index = 0 + plot_data, plot_xrange = violinplot( + vals, fillcolor=colors[color_index], rugplot=rugplot + ) + for item in plot_data: + fig.append_trace(item, 1, k + 1) + color_index += 1 + + # add violin plot labels + fig["layout"].update( + {"xaxis{}".format(k + 1): make_XAxis(group_name[k], plot_xrange)} + ) + + # set the sharey axis style + fig["layout"].update({"yaxis{}".format(1): make_YAxis("")}) + fig["layout"].update( + title=title, + showlegend=False, + hovermode="closest", + autosize=False, + height=height, + width=width, + ) + + return fig + + +def violin_colorscale( + data, + data_header, + group_header, + colors, + use_colorscale, + group_stats, + rugplot, + sort, + height, + width, + title, +): + """ + Refer to FigureFactory.create_violin() for docstring. + + Returns fig for violin plot with colorscale. + + """ + + # collect all group names + group_name = [] + for name in data[group_header]: + if name not in group_name: + group_name.append(name) + if sort: + group_name.sort() + + # make sure all group names are keys in group_stats + for group in group_name: + if group not in group_stats: + raise exceptions.PlotlyError( + "All values/groups in the index " + "column must be represented " + "as a key in group_stats." + ) + + gb = data.groupby([group_header]) + L = len(group_name) + + fig = make_subplots( + rows=1, cols=L, shared_yaxes=True, horizontal_spacing=0.025, print_grid=False + ) + + # prepare low and high color for colorscale + lowcolor = clrs.color_parser(colors[0], clrs.unlabel_rgb) + highcolor = clrs.color_parser(colors[1], clrs.unlabel_rgb) + + # find min and max values in group_stats + group_stats_values = [] + for key in group_stats: + group_stats_values.append(group_stats[key]) + + max_value = max(group_stats_values) + min_value = min(group_stats_values) + + for k, gr in enumerate(group_name): + vals = np.asarray(gb.get_group(gr)[data_header], float) + + # find intermediate color from colorscale + intermed = (group_stats[gr] - min_value) / (max_value - min_value) + intermed_color = clrs.find_intermediate_color(lowcolor, highcolor, intermed) + + plot_data, plot_xrange = violinplot( + vals, fillcolor="rgb{}".format(intermed_color), rugplot=rugplot + ) + for item in plot_data: + fig.append_trace(item, 1, k + 1) + fig["layout"].update( + {"xaxis{}".format(k + 1): make_XAxis(group_name[k], plot_xrange)} + ) + # add colorbar to plot + trace_dummy = graph_objs.Scatter( + x=[0], + y=[0], + mode="markers", + marker=dict( + size=2, + cmin=min_value, + cmax=max_value, + colorscale=[[0, colors[0]], [1, colors[1]]], + showscale=True, + ), + showlegend=False, + ) + fig.append_trace(trace_dummy, 1, L) + + # set the sharey axis style + fig["layout"].update({"yaxis{}".format(1): make_YAxis("")}) + fig["layout"].update( + title=title, + showlegend=False, + hovermode="closest", + autosize=False, + height=height, + width=width, + ) + + return fig + + +def violin_dict( + data, + data_header, + group_header, + colors, + use_colorscale, + group_stats, + rugplot, + sort, + height, + width, + title, +): + """ + Refer to FigureFactory.create_violin() for docstring. + + Returns fig for violin plot without colorscale. + + """ + + # collect all group names + group_name = [] + for name in data[group_header]: + if name not in group_name: + group_name.append(name) + + if sort: + group_name.sort() + + # check if all group names appear in colors dict + for group in group_name: + if group not in colors: + raise exceptions.PlotlyError( + "If colors is a dictionary, all " + "the group names must appear as " + "keys in colors." + ) + + gb = data.groupby([group_header]) + L = len(group_name) + + fig = make_subplots( + rows=1, cols=L, shared_yaxes=True, horizontal_spacing=0.025, print_grid=False + ) + + for k, gr in enumerate(group_name): + vals = np.asarray(gb.get_group(gr)[data_header], float) + plot_data, plot_xrange = violinplot(vals, fillcolor=colors[gr], rugplot=rugplot) + for item in plot_data: + fig.append_trace(item, 1, k + 1) + + # add violin plot labels + fig["layout"].update( + {"xaxis{}".format(k + 1): make_XAxis(group_name[k], plot_xrange)} + ) + + # set the sharey axis style + fig["layout"].update({"yaxis{}".format(1): make_YAxis("")}) + fig["layout"].update( + title=title, + showlegend=False, + hovermode="closest", + autosize=False, + height=height, + width=width, + ) + + return fig + + +def create_violin( + data, + data_header=None, + group_header=None, + colors=None, + use_colorscale=False, + group_stats=None, + rugplot=True, + sort=False, + height=450, + width=600, + title="Violin and Rug Plot", +): + """ + **deprecated**, use instead the plotly.graph_objects trace + :class:`plotly.graph_objects.Violin`. + + :param (list|array) data: accepts either a list of numerical values, + a list of dictionaries all with identical keys and at least one + column of numeric values, or a pandas dataframe with at least one + column of numbers. + :param (str) data_header: the header of the data column to be used + from an inputted pandas dataframe. Not applicable if 'data' is + a list of numeric values. + :param (str) group_header: applicable if grouping data by a variable. + 'group_header' must be set to the name of the grouping variable. + :param (str|tuple|list|dict) colors: either a plotly scale name, + an rgb or hex color, a color tuple, a list of colors or a + dictionary. An rgb color is of the form 'rgb(x, y, z)' where + x, y and z belong to the interval [0, 255] and a color tuple is a + tuple of the form (a, b, c) where a, b and c belong to [0, 1]. + If colors is a list, it must contain valid color types as its + members. + :param (bool) use_colorscale: only applicable if grouping by another + variable. Will implement a colorscale based on the first 2 colors + of param colors. This means colors must be a list with at least 2 + colors in it (Plotly colorscales are accepted since they map to a + list of two rgb colors). Default = False + :param (dict) group_stats: a dictionary where each key is a unique + value from the group_header column in data. Each value must be a + number and will be used to color the violin plots if a colorscale + is being used. + :param (bool) rugplot: determines if a rugplot is draw on violin plot. + Default = True + :param (bool) sort: determines if violins are sorted + alphabetically (True) or by input order (False). Default = False + :param (float) height: the height of the violin plot. + :param (float) width: the width of the violin plot. + :param (str) title: the title of the violin plot. + + Example 1: Single Violin Plot + + >>> from plotly.figure_factory import create_violin + >>> import plotly.graph_objs as graph_objects + + >>> import numpy as np + >>> from scipy import stats + + >>> # create list of random values + >>> data_list = np.random.randn(100) + + >>> # create violin fig + >>> fig = create_violin(data_list, colors='#604d9e') + + >>> # plot + >>> fig.show() + + Example 2: Multiple Violin Plots with Qualitative Coloring + + >>> from plotly.figure_factory import create_violin + >>> import plotly.graph_objs as graph_objects + + >>> import numpy as np + >>> import pandas as pd + >>> from scipy import stats + + >>> # create dataframe + >>> np.random.seed(619517) + >>> Nr=250 + >>> y = np.random.randn(Nr) + >>> gr = np.random.choice(list("ABCDE"), Nr) + >>> norm_params=[(0, 1.2), (0.7, 1), (-0.5, 1.4), (0.3, 1), (0.8, 0.9)] + + >>> for i, letter in enumerate("ABCDE"): + ... y[gr == letter] *=norm_params[i][1]+ norm_params[i][0] + >>> df = pd.DataFrame(dict(Score=y, Group=gr)) + + >>> # create violin fig + >>> fig = create_violin(df, data_header='Score', group_header='Group', + ... sort=True, height=600, width=1000) + + >>> # plot + >>> fig.show() + + Example 3: Violin Plots with Colorscale + + >>> from plotly.figure_factory import create_violin + >>> import plotly.graph_objs as graph_objects + + >>> import numpy as np + >>> import pandas as pd + >>> from scipy import stats + + >>> # create dataframe + >>> np.random.seed(619517) + >>> Nr=250 + >>> y = np.random.randn(Nr) + >>> gr = np.random.choice(list("ABCDE"), Nr) + >>> norm_params=[(0, 1.2), (0.7, 1), (-0.5, 1.4), (0.3, 1), (0.8, 0.9)] + + >>> for i, letter in enumerate("ABCDE"): + ... y[gr == letter] *=norm_params[i][1]+ norm_params[i][0] + >>> df = pd.DataFrame(dict(Score=y, Group=gr)) + + >>> # define header params + >>> data_header = 'Score' + >>> group_header = 'Group' + + >>> # make groupby object with pandas + >>> group_stats = {} + >>> groupby_data = df.groupby([group_header]) + + >>> for group in "ABCDE": + ... data_from_group = groupby_data.get_group(group)[data_header] + ... # take a stat of the grouped data + ... stat = np.median(data_from_group) + ... # add to dictionary + ... group_stats[group] = stat + + >>> # create violin fig + >>> fig = create_violin(df, data_header='Score', group_header='Group', + ... height=600, width=1000, use_colorscale=True, + ... group_stats=group_stats) + + >>> # plot + >>> fig.show() + """ + + # Validate colors + if isinstance(colors, dict): + valid_colors = clrs.validate_colors_dict(colors, "rgb") + else: + valid_colors = clrs.validate_colors(colors, "rgb") + + # validate data and choose plot type + if group_header is None: + if isinstance(data, list): + if len(data) <= 0: + raise exceptions.PlotlyError( + "If data is a list, it must be " + "nonempty and contain either " + "numbers or dictionaries." + ) + + if not all(isinstance(element, Number) for element in data): + raise exceptions.PlotlyError( + "If data is a list, it must contain only numbers." + ) + + if pd and isinstance(data, pd.core.frame.DataFrame): + if data_header is None: + raise exceptions.PlotlyError( + "data_header must be the " + "column name with the " + "desired numeric data for " + "the violin plot." + ) + + data = data[data_header].values.tolist() + + # call the plotting functions + plot_data, plot_xrange = violinplot( + data, fillcolor=valid_colors[0], rugplot=rugplot + ) + + layout = graph_objs.Layout( + title=title, + autosize=False, + font=graph_objs.layout.Font(size=11), + height=height, + showlegend=False, + width=width, + xaxis=make_XAxis("", plot_xrange), + yaxis=make_YAxis(""), + hovermode="closest", + ) + layout["yaxis"].update(dict(showline=False, showticklabels=False, ticks="")) + + fig = graph_objs.Figure(data=plot_data, layout=layout) + + return fig + + else: + if not isinstance(data, pd.core.frame.DataFrame): + raise exceptions.PlotlyError( + "Error. You must use a pandas " + "DataFrame if you are using a " + "group header." + ) + + if data_header is None: + raise exceptions.PlotlyError( + "data_header must be the column " + "name with the desired numeric " + "data for the violin plot." + ) + + if use_colorscale is False: + if isinstance(valid_colors, dict): + # validate colors dict choice below + fig = violin_dict( + data, + data_header, + group_header, + valid_colors, + use_colorscale, + group_stats, + rugplot, + sort, + height, + width, + title, + ) + return fig + else: + fig = violin_no_colorscale( + data, + data_header, + group_header, + valid_colors, + use_colorscale, + group_stats, + rugplot, + sort, + height, + width, + title, + ) + return fig + else: + if isinstance(valid_colors, dict): + raise exceptions.PlotlyError( + "The colors param cannot be " + "a dictionary if you are " + "using a colorscale." + ) + + if len(valid_colors) < 2: + raise exceptions.PlotlyError( + "colors must be a list with " + "at least 2 colors. A " + "Plotly scale is allowed." + ) + + if not isinstance(group_stats, dict): + raise exceptions.PlotlyError( + "Your group_stats param must be a dictionary." + ) + + fig = violin_colorscale( + data, + data_header, + group_header, + valid_colors, + use_colorscale, + group_stats, + rugplot, + sort, + height, + width, + title, + ) + return fig diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/utils.py b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..e20a319af13cc31e14063bac021eb2103d24d34b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/figure_factory/utils.py @@ -0,0 +1,249 @@ +from collections.abc import Sequence + +from plotly import exceptions + + +def is_sequence(obj): + return isinstance(obj, Sequence) and not isinstance(obj, str) + + +def validate_index(index_vals): + """ + Validates if a list contains all numbers or all strings + + :raises: (PlotlyError) If there are any two items in the list whose + types differ + """ + from numbers import Number + + if isinstance(index_vals[0], Number): + if not all(isinstance(item, Number) for item in index_vals): + raise exceptions.PlotlyError( + "Error in indexing column. " + "Make sure all entries of each " + "column are all numbers or " + "all strings." + ) + + elif isinstance(index_vals[0], str): + if not all(isinstance(item, str) for item in index_vals): + raise exceptions.PlotlyError( + "Error in indexing column. " + "Make sure all entries of each " + "column are all numbers or " + "all strings." + ) + + +def validate_dataframe(array): + """ + Validates all strings or numbers in each dataframe column + + :raises: (PlotlyError) If there are any two items in any list whose + types differ + """ + from numbers import Number + + for vector in array: + if isinstance(vector[0], Number): + if not all(isinstance(item, Number) for item in vector): + raise exceptions.PlotlyError( + "Error in dataframe. " + "Make sure all entries of " + "each column are either " + "numbers or strings." + ) + elif isinstance(vector[0], str): + if not all(isinstance(item, str) for item in vector): + raise exceptions.PlotlyError( + "Error in dataframe. " + "Make sure all entries of " + "each column are either " + "numbers or strings." + ) + + +def validate_equal_length(*args): + """ + Validates that data lists or ndarrays are the same length. + + :raises: (PlotlyError) If any data lists are not the same length. + """ + length = len(args[0]) + if any(len(lst) != length for lst in args): + raise exceptions.PlotlyError( + "Oops! Your data lists or ndarrays should be the same length." + ) + + +def validate_positive_scalars(**kwargs): + """ + Validates that all values given in key/val pairs are positive. + + Accepts kwargs to improve Exception messages. + + :raises: (PlotlyError) If any value is < 0 or raises. + """ + for key, val in kwargs.items(): + try: + if val <= 0: + raise ValueError("{} must be > 0, got {}".format(key, val)) + except TypeError: + raise exceptions.PlotlyError("{} must be a number, got {}".format(key, val)) + + +def flatten(array): + """ + Uses list comprehension to flatten array + + :param (array): An iterable to flatten + :raises (PlotlyError): If iterable is not nested. + :rtype (list): The flattened list. + """ + try: + return [item for sublist in array for item in sublist] + except TypeError: + raise exceptions.PlotlyError( + "Your data array could not be " + "flattened! Make sure your data is " + "entered as lists or ndarrays!" + ) + + +def endpts_to_intervals(endpts): + """ + Returns a list of intervals for categorical colormaps + + Accepts a list or tuple of sequentially increasing numbers and returns + a list representation of the mathematical intervals with these numbers + as endpoints. For example, [1, 6] returns [[-inf, 1], [1, 6], [6, inf]] + + :raises: (PlotlyError) If input is not a list or tuple + :raises: (PlotlyError) If the input contains a string + :raises: (PlotlyError) If any number does not increase after the + previous one in the sequence + """ + length = len(endpts) + # Check if endpts is a list or tuple + if not (isinstance(endpts, (tuple)) or isinstance(endpts, (list))): + raise exceptions.PlotlyError( + "The intervals_endpts argument must " + "be a list or tuple of a sequence " + "of increasing numbers." + ) + # Check if endpts contains only numbers + for item in endpts: + if isinstance(item, str): + raise exceptions.PlotlyError( + "The intervals_endpts argument " + "must be a list or tuple of a " + "sequence of increasing " + "numbers." + ) + # Check if numbers in endpts are increasing + for k in range(length - 1): + if endpts[k] >= endpts[k + 1]: + raise exceptions.PlotlyError( + "The intervals_endpts argument " + "must be a list or tuple of a " + "sequence of increasing " + "numbers." + ) + else: + intervals = [] + # add -inf to intervals + intervals.append([float("-inf"), endpts[0]]) + for k in range(length - 1): + interval = [] + interval.append(endpts[k]) + interval.append(endpts[k + 1]) + intervals.append(interval) + # add +inf to intervals + intervals.append([endpts[length - 1], float("inf")]) + return intervals + + +def annotation_dict_for_label( + text, + lane, + num_of_lanes, + subplot_spacing, + row_col="col", + flipped=True, + right_side=True, + text_color="#0f0f0f", +): + """ + Returns annotation dict for label of n labels of a 1xn or nx1 subplot. + + :param (str) text: the text for a label. + :param (int) lane: the label number for text. From 1 to n inclusive. + :param (int) num_of_lanes: the number 'n' of rows or columns in subplot. + :param (float) subplot_spacing: the value for the horizontal_spacing and + vertical_spacing params in your plotly.tools.make_subplots() call. + :param (str) row_col: choose whether labels are placed along rows or + columns. + :param (bool) flipped: flips text by 90 degrees. Text is printed + horizontally if set to True and row_col='row', or if False and + row_col='col'. + :param (bool) right_side: only applicable if row_col is set to 'row'. + :param (str) text_color: color of the text. + """ + temp = (1 - (num_of_lanes - 1) * subplot_spacing) / (num_of_lanes) + if not flipped: + xanchor = "center" + yanchor = "middle" + if row_col == "col": + x = (lane - 1) * (temp + subplot_spacing) + 0.5 * temp + y = 1.03 + textangle = 0 + elif row_col == "row": + y = (lane - 1) * (temp + subplot_spacing) + 0.5 * temp + x = 1.03 + textangle = 90 + else: + if row_col == "col": + xanchor = "center" + yanchor = "bottom" + x = (lane - 1) * (temp + subplot_spacing) + 0.5 * temp + y = 1.0 + textangle = 270 + elif row_col == "row": + yanchor = "middle" + y = (lane - 1) * (temp + subplot_spacing) + 0.5 * temp + if right_side: + x = 1.0 + xanchor = "left" + else: + x = -0.01 + xanchor = "right" + textangle = 0 + + annotation_dict = dict( + textangle=textangle, + xanchor=xanchor, + yanchor=yanchor, + x=x, + y=y, + showarrow=False, + xref="paper", + yref="paper", + text=text, + font=dict(size=13, color=text_color), + ) + return annotation_dict + + +def list_of_options(iterable, conj="and", period=True): + """ + Returns an English listing of objects seperated by commas ',' + + For example, ['foo', 'bar', 'baz'] becomes 'foo, bar and baz' + if the conjunction 'and' is selected. + """ + if len(iterable) < 2: + raise exceptions.PlotlyError( + "Your list or tuple must contain at least 2 items." + ) + template = (len(iterable) - 2) * "{}, " + "{} " + conj + " {}" + period * "." + return template.format(*iterable) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objects/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objects/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..ab87744d0d7c7dfbb2b4bd5be23fdd616928d600 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objects/__init__.py @@ -0,0 +1,306 @@ +# ruff: noqa: F401 +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ..graph_objs import Waterfall + from ..graph_objs import Volume + from ..graph_objs import Violin + from ..graph_objs import Treemap + from ..graph_objs import Table + from ..graph_objs import Surface + from ..graph_objs import Sunburst + from ..graph_objs import Streamtube + from ..graph_objs import Splom + from ..graph_objs import Scatterternary + from ..graph_objs import Scattersmith + from ..graph_objs import Scatterpolargl + from ..graph_objs import Scatterpolar + from ..graph_objs import Scattermapbox + from ..graph_objs import Scattermap + from ..graph_objs import Scattergl + from ..graph_objs import Scattergeo + from ..graph_objs import Scattercarpet + from ..graph_objs import Scatter3d + from ..graph_objs import Scatter + from ..graph_objs import Sankey + from ..graph_objs import Pie + from ..graph_objs import Parcoords + from ..graph_objs import Parcats + from ..graph_objs import Ohlc + from ..graph_objs import Mesh3d + from ..graph_objs import Isosurface + from ..graph_objs import Indicator + from ..graph_objs import Image + from ..graph_objs import Icicle + from ..graph_objs import Histogram2dContour + from ..graph_objs import Histogram2d + from ..graph_objs import Histogram + from ..graph_objs import Heatmap + from ..graph_objs import Funnelarea + from ..graph_objs import Funnel + from ..graph_objs import Densitymapbox + from ..graph_objs import Densitymap + from ..graph_objs import Contourcarpet + from ..graph_objs import Contour + from ..graph_objs import Cone + from ..graph_objs import Choroplethmapbox + from ..graph_objs import Choroplethmap + from ..graph_objs import Choropleth + from ..graph_objs import Carpet + from ..graph_objs import Candlestick + from ..graph_objs import Box + from ..graph_objs import Barpolar + from ..graph_objs import Bar + from ..graph_objs import Layout + from ..graph_objs import Frame + from ..graph_objs import Figure + from ..graph_objs import Data + from ..graph_objs import Annotations + from ..graph_objs import Frames + from ..graph_objs import AngularAxis + from ..graph_objs import Annotation + from ..graph_objs import ColorBar + from ..graph_objs import Contours + from ..graph_objs import ErrorX + from ..graph_objs import ErrorY + from ..graph_objs import ErrorZ + from ..graph_objs import Font + from ..graph_objs import Legend + from ..graph_objs import Line + from ..graph_objs import Margin + from ..graph_objs import Marker + from ..graph_objs import RadialAxis + from ..graph_objs import Scene + from ..graph_objs import Stream + from ..graph_objs import XAxis + from ..graph_objs import YAxis + from ..graph_objs import ZAxis + from ..graph_objs import XBins + from ..graph_objs import YBins + from ..graph_objs import Trace + from ..graph_objs import Histogram2dcontour + from ..graph_objs import waterfall + from ..graph_objs import volume + from ..graph_objs import violin + from ..graph_objs import treemap + from ..graph_objs import table + from ..graph_objs import surface + from ..graph_objs import sunburst + from ..graph_objs import streamtube + from ..graph_objs import splom + from ..graph_objs import scatterternary + from ..graph_objs import scattersmith + from ..graph_objs import scatterpolargl + from ..graph_objs import scatterpolar + from ..graph_objs import scattermapbox + from ..graph_objs import scattermap + from ..graph_objs import scattergl + from ..graph_objs import scattergeo + from ..graph_objs import scattercarpet + from ..graph_objs import scatter3d + from ..graph_objs import scatter + from ..graph_objs import sankey + from ..graph_objs import pie + from ..graph_objs import parcoords + from ..graph_objs import parcats + from ..graph_objs import ohlc + from ..graph_objs import mesh3d + from ..graph_objs import isosurface + from ..graph_objs import indicator + from ..graph_objs import image + from ..graph_objs import icicle + from ..graph_objs import histogram2dcontour + from ..graph_objs import histogram2d + from ..graph_objs import histogram + from ..graph_objs import heatmap + from ..graph_objs import funnelarea + from ..graph_objs import funnel + from ..graph_objs import densitymapbox + from ..graph_objs import densitymap + from ..graph_objs import contourcarpet + from ..graph_objs import contour + from ..graph_objs import cone + from ..graph_objs import choroplethmapbox + from ..graph_objs import choroplethmap + from ..graph_objs import choropleth + from ..graph_objs import carpet + from ..graph_objs import candlestick + from ..graph_objs import box + from ..graph_objs import barpolar + from ..graph_objs import bar + from ..graph_objs import layout +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [ + "..graph_objs.waterfall", + "..graph_objs.volume", + "..graph_objs.violin", + "..graph_objs.treemap", + "..graph_objs.table", + "..graph_objs.surface", + "..graph_objs.sunburst", + "..graph_objs.streamtube", + "..graph_objs.splom", + "..graph_objs.scatterternary", + "..graph_objs.scattersmith", + "..graph_objs.scatterpolargl", + "..graph_objs.scatterpolar", + "..graph_objs.scattermapbox", + "..graph_objs.scattermap", + "..graph_objs.scattergl", + "..graph_objs.scattergeo", + "..graph_objs.scattercarpet", + "..graph_objs.scatter3d", + "..graph_objs.scatter", + "..graph_objs.sankey", + "..graph_objs.pie", + "..graph_objs.parcoords", + "..graph_objs.parcats", + "..graph_objs.ohlc", + "..graph_objs.mesh3d", + "..graph_objs.isosurface", + "..graph_objs.indicator", + "..graph_objs.image", + "..graph_objs.icicle", + "..graph_objs.histogram2dcontour", + "..graph_objs.histogram2d", + "..graph_objs.histogram", + "..graph_objs.heatmap", + "..graph_objs.funnelarea", + "..graph_objs.funnel", + "..graph_objs.densitymapbox", + "..graph_objs.densitymap", + "..graph_objs.contourcarpet", + "..graph_objs.contour", + "..graph_objs.cone", + "..graph_objs.choroplethmapbox", + "..graph_objs.choroplethmap", + "..graph_objs.choropleth", + "..graph_objs.carpet", + "..graph_objs.candlestick", + "..graph_objs.box", + "..graph_objs.barpolar", + "..graph_objs.bar", + "..graph_objs.layout", + ], + [ + "..graph_objs.Waterfall", + "..graph_objs.Volume", + "..graph_objs.Violin", + "..graph_objs.Treemap", + "..graph_objs.Table", + "..graph_objs.Surface", + "..graph_objs.Sunburst", + "..graph_objs.Streamtube", + "..graph_objs.Splom", + "..graph_objs.Scatterternary", + "..graph_objs.Scattersmith", + "..graph_objs.Scatterpolargl", + "..graph_objs.Scatterpolar", + "..graph_objs.Scattermapbox", + "..graph_objs.Scattermap", + "..graph_objs.Scattergl", + "..graph_objs.Scattergeo", + "..graph_objs.Scattercarpet", + "..graph_objs.Scatter3d", + "..graph_objs.Scatter", + "..graph_objs.Sankey", + "..graph_objs.Pie", + "..graph_objs.Parcoords", + "..graph_objs.Parcats", + "..graph_objs.Ohlc", + "..graph_objs.Mesh3d", + "..graph_objs.Isosurface", + "..graph_objs.Indicator", + "..graph_objs.Image", + "..graph_objs.Icicle", + "..graph_objs.Histogram2dContour", + "..graph_objs.Histogram2d", + "..graph_objs.Histogram", + "..graph_objs.Heatmap", + "..graph_objs.Funnelarea", + "..graph_objs.Funnel", + "..graph_objs.Densitymapbox", + "..graph_objs.Densitymap", + "..graph_objs.Contourcarpet", + "..graph_objs.Contour", + "..graph_objs.Cone", + "..graph_objs.Choroplethmapbox", + "..graph_objs.Choroplethmap", + "..graph_objs.Choropleth", + "..graph_objs.Carpet", + "..graph_objs.Candlestick", + "..graph_objs.Box", + "..graph_objs.Barpolar", + "..graph_objs.Bar", + "..graph_objs.Layout", + "..graph_objs.Frame", + "..graph_objs.Figure", + "..graph_objs.Data", + "..graph_objs.Annotations", + "..graph_objs.Frames", + "..graph_objs.AngularAxis", + "..graph_objs.Annotation", + "..graph_objs.ColorBar", + "..graph_objs.Contours", + "..graph_objs.ErrorX", + "..graph_objs.ErrorY", + "..graph_objs.ErrorZ", + "..graph_objs.Font", + "..graph_objs.Legend", + "..graph_objs.Line", + "..graph_objs.Margin", + "..graph_objs.Marker", + "..graph_objs.RadialAxis", + "..graph_objs.Scene", + "..graph_objs.Stream", + "..graph_objs.XAxis", + "..graph_objs.YAxis", + "..graph_objs.ZAxis", + "..graph_objs.XBins", + "..graph_objs.YBins", + "..graph_objs.Trace", + "..graph_objs.Histogram2dcontour", + ], + ) + + +if sys.version_info < (3, 7) or TYPE_CHECKING: + try: + import ipywidgets as _ipywidgets + from packaging.version import Version as _Version + + if _Version(_ipywidgets.__version__) >= _Version("7.0.0"): + from ..graph_objs._figurewidget import FigureWidget + else: + raise ImportError() + except Exception: + from ..missing_anywidget import FigureWidget +else: + __all__.append("FigureWidget") + orig_getattr = __getattr__ + + def __getattr__(import_name): + if import_name == "FigureWidget": + try: + import ipywidgets + from packaging.version import Version + + if Version(ipywidgets.__version__) >= Version("7.0.0"): + from ..graph_objs._figurewidget import FigureWidget + + return FigureWidget + else: + raise ImportError() + except Exception: + from ..missing_anywidget import FigureWidget + + return FigureWidget + else: + raise ImportError() + + return orig_getattr(import_name) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objects/__pycache__/__init__.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objects/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..11b129f68482fb2dcf9022d1c9e95e9e09315439 Binary files /dev/null and b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objects/__pycache__/__init__.cpython-312.pyc differ diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..57a7317fd57bb65740e026a53e9e49e67155ea15 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/__init__.py @@ -0,0 +1,305 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._bar import Bar + from ._barpolar import Barpolar + from ._box import Box + from ._candlestick import Candlestick + from ._carpet import Carpet + from ._choropleth import Choropleth + from ._choroplethmap import Choroplethmap + from ._choroplethmapbox import Choroplethmapbox + from ._cone import Cone + from ._contour import Contour + from ._contourcarpet import Contourcarpet + from ._densitymap import Densitymap + from ._densitymapbox import Densitymapbox + from ._deprecations import AngularAxis + from ._deprecations import Annotation + from ._deprecations import Annotations + from ._deprecations import ColorBar + from ._deprecations import Contours + from ._deprecations import Data + from ._deprecations import ErrorX + from ._deprecations import ErrorY + from ._deprecations import ErrorZ + from ._deprecations import Font + from ._deprecations import Frames + from ._deprecations import Histogram2dcontour + from ._deprecations import Legend + from ._deprecations import Line + from ._deprecations import Margin + from ._deprecations import Marker + from ._deprecations import RadialAxis + from ._deprecations import Scene + from ._deprecations import Stream + from ._deprecations import Trace + from ._deprecations import XAxis + from ._deprecations import XBins + from ._deprecations import YAxis + from ._deprecations import YBins + from ._deprecations import ZAxis + from ._figure import Figure + from ._frame import Frame + from ._funnel import Funnel + from ._funnelarea import Funnelarea + from ._heatmap import Heatmap + from ._histogram import Histogram + from ._histogram2d import Histogram2d + from ._histogram2dcontour import Histogram2dContour + from ._icicle import Icicle + from ._image import Image + from ._indicator import Indicator + from ._isosurface import Isosurface + from ._layout import Layout + from ._mesh3d import Mesh3d + from ._ohlc import Ohlc + from ._parcats import Parcats + from ._parcoords import Parcoords + from ._pie import Pie + from ._sankey import Sankey + from ._scatter import Scatter + from ._scatter3d import Scatter3d + from ._scattercarpet import Scattercarpet + from ._scattergeo import Scattergeo + from ._scattergl import Scattergl + from ._scattermap import Scattermap + from ._scattermapbox import Scattermapbox + from ._scatterpolar import Scatterpolar + from ._scatterpolargl import Scatterpolargl + from ._scattersmith import Scattersmith + from ._scatterternary import Scatterternary + from ._splom import Splom + from ._streamtube import Streamtube + from ._sunburst import Sunburst + from ._surface import Surface + from ._table import Table + from ._treemap import Treemap + from ._violin import Violin + from ._volume import Volume + from ._waterfall import Waterfall + from . import bar + from . import barpolar + from . import box + from . import candlestick + from . import carpet + from . import choropleth + from . import choroplethmap + from . import choroplethmapbox + from . import cone + from . import contour + from . import contourcarpet + from . import densitymap + from . import densitymapbox + from . import funnel + from . import funnelarea + from . import heatmap + from . import histogram + from . import histogram2d + from . import histogram2dcontour + from . import icicle + from . import image + from . import indicator + from . import isosurface + from . import layout + from . import mesh3d + from . import ohlc + from . import parcats + from . import parcoords + from . import pie + from . import sankey + from . import scatter + from . import scatter3d + from . import scattercarpet + from . import scattergeo + from . import scattergl + from . import scattermap + from . import scattermapbox + from . import scatterpolar + from . import scatterpolargl + from . import scattersmith + from . import scatterternary + from . import splom + from . import streamtube + from . import sunburst + from . import surface + from . import table + from . import treemap + from . import violin + from . import volume + from . import waterfall +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [ + ".bar", + ".barpolar", + ".box", + ".candlestick", + ".carpet", + ".choropleth", + ".choroplethmap", + ".choroplethmapbox", + ".cone", + ".contour", + ".contourcarpet", + ".densitymap", + ".densitymapbox", + ".funnel", + ".funnelarea", + ".heatmap", + ".histogram", + ".histogram2d", + ".histogram2dcontour", + ".icicle", + ".image", + ".indicator", + ".isosurface", + ".layout", + ".mesh3d", + ".ohlc", + ".parcats", + ".parcoords", + ".pie", + ".sankey", + ".scatter", + ".scatter3d", + ".scattercarpet", + ".scattergeo", + ".scattergl", + ".scattermap", + ".scattermapbox", + ".scatterpolar", + ".scatterpolargl", + ".scattersmith", + ".scatterternary", + ".splom", + ".streamtube", + ".sunburst", + ".surface", + ".table", + ".treemap", + ".violin", + ".volume", + ".waterfall", + ], + [ + "._bar.Bar", + "._barpolar.Barpolar", + "._box.Box", + "._candlestick.Candlestick", + "._carpet.Carpet", + "._choropleth.Choropleth", + "._choroplethmap.Choroplethmap", + "._choroplethmapbox.Choroplethmapbox", + "._cone.Cone", + "._contour.Contour", + "._contourcarpet.Contourcarpet", + "._densitymap.Densitymap", + "._densitymapbox.Densitymapbox", + "._deprecations.AngularAxis", + "._deprecations.Annotation", + "._deprecations.Annotations", + "._deprecations.ColorBar", + "._deprecations.Contours", + "._deprecations.Data", + "._deprecations.ErrorX", + "._deprecations.ErrorY", + "._deprecations.ErrorZ", + "._deprecations.Font", + "._deprecations.Frames", + "._deprecations.Histogram2dcontour", + "._deprecations.Legend", + "._deprecations.Line", + "._deprecations.Margin", + "._deprecations.Marker", + "._deprecations.RadialAxis", + "._deprecations.Scene", + "._deprecations.Stream", + "._deprecations.Trace", + "._deprecations.XAxis", + "._deprecations.XBins", + "._deprecations.YAxis", + "._deprecations.YBins", + "._deprecations.ZAxis", + "._figure.Figure", + "._frame.Frame", + "._funnel.Funnel", + "._funnelarea.Funnelarea", + "._heatmap.Heatmap", + "._histogram.Histogram", + "._histogram2d.Histogram2d", + "._histogram2dcontour.Histogram2dContour", + "._icicle.Icicle", + "._image.Image", + "._indicator.Indicator", + "._isosurface.Isosurface", + "._layout.Layout", + "._mesh3d.Mesh3d", + "._ohlc.Ohlc", + "._parcats.Parcats", + "._parcoords.Parcoords", + "._pie.Pie", + "._sankey.Sankey", + "._scatter.Scatter", + "._scatter3d.Scatter3d", + "._scattercarpet.Scattercarpet", + "._scattergeo.Scattergeo", + "._scattergl.Scattergl", + "._scattermap.Scattermap", + "._scattermapbox.Scattermapbox", + "._scatterpolar.Scatterpolar", + "._scatterpolargl.Scatterpolargl", + "._scattersmith.Scattersmith", + "._scatterternary.Scatterternary", + "._splom.Splom", + "._streamtube.Streamtube", + "._sunburst.Sunburst", + "._surface.Surface", + "._table.Table", + "._treemap.Treemap", + "._violin.Violin", + "._volume.Volume", + "._waterfall.Waterfall", + ], + ) + + +if sys.version_info < (3, 7) or TYPE_CHECKING: + try: + import ipywidgets as _ipywidgets + from packaging.version import Version as _Version + + if _Version(_ipywidgets.__version__) >= _Version("7.0.0"): + from ..graph_objs._figurewidget import FigureWidget + else: + raise ImportError() + except Exception: + from ..missing_anywidget import FigureWidget +else: + __all__.append("FigureWidget") + orig_getattr = __getattr__ + + def __getattr__(import_name): + if import_name == "FigureWidget": + try: + import ipywidgets + from packaging.version import Version + + if Version(ipywidgets.__version__) >= Version("7.0.0"): + from ..graph_objs._figurewidget import FigureWidget + + return FigureWidget + else: + raise ImportError() + except Exception: + from ..missing_anywidget import FigureWidget + + return FigureWidget + else: + raise ImportError() + + return orig_getattr(import_name) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_bar.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_bar.py new file mode 100644 index 0000000000000000000000000000000000000000..e2cd24617f7094b2904272c1328d99b1ce70f390 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_bar.py @@ -0,0 +1,2690 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Bar(_BaseTraceType): + _parent_path_str = "" + _path_str = "bar" + _valid_props = { + "alignmentgroup", + "base", + "basesrc", + "cliponaxis", + "constraintext", + "customdata", + "customdatasrc", + "dx", + "dy", + "error_x", + "error_y", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "insidetextanchor", + "insidetextfont", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "marker", + "meta", + "metasrc", + "name", + "offset", + "offsetgroup", + "offsetsrc", + "opacity", + "orientation", + "outsidetextfont", + "selected", + "selectedpoints", + "showlegend", + "stream", + "text", + "textangle", + "textfont", + "textposition", + "textpositionsrc", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "type", + "uid", + "uirevision", + "unselected", + "visible", + "width", + "widthsrc", + "x", + "x0", + "xaxis", + "xcalendar", + "xhoverformat", + "xperiod", + "xperiod0", + "xperiodalignment", + "xsrc", + "y", + "y0", + "yaxis", + "ycalendar", + "yhoverformat", + "yperiod", + "yperiod0", + "yperiodalignment", + "ysrc", + "zorder", + } + + @property + def alignmentgroup(self): + """ + Set several traces linked to the same position axis or matching + axes to the same alignmentgroup. This controls whether bars + compute their positional range dependently or independently. + + The 'alignmentgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["alignmentgroup"] + + @alignmentgroup.setter + def alignmentgroup(self, val): + self["alignmentgroup"] = val + + @property + def base(self): + """ + Sets where the bar base is drawn (in position axis units). In + "stack" or "relative" barmode, traces that set "base" will be + excluded and drawn in "overlay" mode instead. + + The 'base' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["base"] + + @base.setter + def base(self, val): + self["base"] = val + + @property + def basesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `base`. + + The 'basesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["basesrc"] + + @basesrc.setter + def basesrc(self, val): + self["basesrc"] = val + + @property + def cliponaxis(self): + """ + Determines whether the text nodes are clipped about the subplot + axes. To show the text nodes above axis lines and tick labels, + make sure to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + + The 'cliponaxis' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cliponaxis"] + + @cliponaxis.setter + def cliponaxis(self, val): + self["cliponaxis"] = val + + @property + def constraintext(self): + """ + Constrain the size of text inside or outside a bar to be no + larger than the bar itself. + + The 'constraintext' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['inside', 'outside', 'both', 'none'] + + Returns + ------- + Any + """ + return self["constraintext"] + + @constraintext.setter + def constraintext(self, val): + self["constraintext"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def dx(self): + """ + Sets the x coordinate step. See `x0` for more info. + + The 'dx' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dx"] + + @dx.setter + def dx(self, val): + self["dx"] = val + + @property + def dy(self): + """ + Sets the y coordinate step. See `y0` for more info. + + The 'dy' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dy"] + + @dy.setter + def dy(self, val): + self["dy"] = val + + @property + def error_x(self): + """ + The 'error_x' property is an instance of ErrorX + that may be specified as: + - An instance of :class:`plotly.graph_objs.bar.ErrorX` + - A dict of string/value properties that will be passed + to the ErrorX constructor + + Returns + ------- + plotly.graph_objs.bar.ErrorX + """ + return self["error_x"] + + @error_x.setter + def error_x(self, val): + self["error_x"] = val + + @property + def error_y(self): + """ + The 'error_y' property is an instance of ErrorY + that may be specified as: + - An instance of :class:`plotly.graph_objs.bar.ErrorY` + - A dict of string/value properties that will be passed + to the ErrorY constructor + + Returns + ------- + plotly.graph_objs.bar.ErrorY + """ + return self["error_y"] + + @error_y.setter + def error_y(self, val): + self["error_y"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.bar.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.bar.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables `value` + and `label`. Anything contained in tag `` is displayed + in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each (x,y) pair. If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (x,y) coordinates. To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def insidetextanchor(self): + """ + Determines if texts are kept at center or start/end points in + `textposition` "inside" mode. + + The 'insidetextanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['end', 'middle', 'start'] + + Returns + ------- + Any + """ + return self["insidetextanchor"] + + @insidetextanchor.setter + def insidetextanchor(self, val): + self["insidetextanchor"] = val + + @property + def insidetextfont(self): + """ + Sets the font used for `text` lying inside the bar. + + The 'insidetextfont' property is an instance of Insidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.bar.Insidetextfont` + - A dict of string/value properties that will be passed + to the Insidetextfont constructor + + Returns + ------- + plotly.graph_objs.bar.Insidetextfont + """ + return self["insidetextfont"] + + @insidetextfont.setter + def insidetextfont(self, val): + self["insidetextfont"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.bar.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.bar.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.bar.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.bar.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def offset(self): + """ + Shifts the position where the bar is drawn (in position axis + units). In "group" barmode, traces that set "offset" will be + excluded and drawn in "overlay" mode instead. + + The 'offset' property is a number and may be specified as: + - An int or float + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["offset"] + + @offset.setter + def offset(self, val): + self["offset"] = val + + @property + def offsetgroup(self): + """ + Set several traces linked to the same position axis or matching + axes to the same offsetgroup where bars of the same position + coordinate will line up. + + The 'offsetgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["offsetgroup"] + + @offsetgroup.setter + def offsetgroup(self, val): + self["offsetgroup"] = val + + @property + def offsetsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `offset`. + + The 'offsetsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["offsetsrc"] + + @offsetsrc.setter + def offsetsrc(self, val): + self["offsetsrc"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def orientation(self): + """ + Sets the orientation of the bars. With "v" ("h"), the value of + the each bar spans along the vertical (horizontal). + + The 'orientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['v', 'h'] + + Returns + ------- + Any + """ + return self["orientation"] + + @orientation.setter + def orientation(self, val): + self["orientation"] = val + + @property + def outsidetextfont(self): + """ + Sets the font used for `text` lying outside the bar. + + The 'outsidetextfont' property is an instance of Outsidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.bar.Outsidetextfont` + - A dict of string/value properties that will be passed + to the Outsidetextfont constructor + + Returns + ------- + plotly.graph_objs.bar.Outsidetextfont + """ + return self["outsidetextfont"] + + @outsidetextfont.setter + def outsidetextfont(self, val): + self["outsidetextfont"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.bar.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.bar.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.bar.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.bar.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets text elements associated with each (x,y) pair. If a single + string, the same string appears over all the data points. If an + array of string, the items are mapped in order to the this + trace's (x,y) coordinates. If trace `hoverinfo` contains a + "text" flag and "hovertext" is not set, these elements will be + seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textangle(self): + """ + Sets the angle of the tick labels with respect to the bar. For + example, a `tickangle` of -90 draws the tick labels vertically. + With "auto" the texts may automatically be rotated to fit with + the maximum size in bars. + + The 'textangle' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["textangle"] + + @textangle.setter + def textangle(self, val): + self["textangle"] = val + + @property + def textfont(self): + """ + Sets the font used for `text`. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.bar.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.bar.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textposition(self): + """ + Specifies the location of the `text`. "inside" positions `text` + inside, next to the bar end (rotated and scaled if needed). + "outside" positions `text` outside, next to the bar end (scaled + if needed), unless there is another bar stacked on this one, + then the text gets pushed inside. "auto" tries to position + `text` inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If "none", no + text appears. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['inside', 'outside', 'auto', 'none'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textpositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `textposition`. + + The 'textpositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textpositionsrc"] + + @textpositionsrc.setter + def textpositionsrc(self, val): + self["textpositionsrc"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `value` and `label`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.bar.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.bar.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def width(self): + """ + Sets the bar width (in position axis units). + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def widthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `width`. + + The 'widthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["widthsrc"] + + @widthsrc.setter + def widthsrc(self, val): + self["widthsrc"] = val + + @property + def x(self): + """ + Sets the x coordinates. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def x0(self): + """ + Alternate to `x`. Builds a linear space of x coordinates. Use + with `dx` where `x0` is the starting coordinate and `dx` the + step. + + The 'x0' property accepts values of any type + + Returns + ------- + Any + """ + return self["x0"] + + @x0.setter + def x0(self, val): + self["x0"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def xcalendar(self): + """ + Sets the calendar system to use with `x` date data. + + The 'xcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["xcalendar"] + + @xcalendar.setter + def xcalendar(self, val): + self["xcalendar"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the x axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'xperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod"] + + @xperiod.setter + def xperiod(self, val): + self["xperiod"] = val + + @property + def xperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the x0 + axis. When `x0period` is round number of weeks, the `x0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'xperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod0"] + + @xperiod0.setter + def xperiod0(self, val): + self["xperiod0"] = val + + @property + def xperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + + The 'xperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["xperiodalignment"] + + @xperiodalignment.setter + def xperiodalignment(self, val): + self["xperiodalignment"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the y coordinates. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def y0(self): + """ + Alternate to `y`. Builds a linear space of y coordinates. Use + with `dy` where `y0` is the starting coordinate and `dy` the + step. + + The 'y0' property accepts values of any type + + Returns + ------- + Any + """ + return self["y0"] + + @y0.setter + def y0(self, val): + self["y0"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def ycalendar(self): + """ + Sets the calendar system to use with `y` date data. + + The 'ycalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["ycalendar"] + + @ycalendar.setter + def ycalendar(self, val): + self["ycalendar"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def yperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the y axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'yperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod"] + + @yperiod.setter + def yperiod(self, val): + self["yperiod"] = val + + @property + def yperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the y0 + axis. When `y0period` is round number of weeks, the `y0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'yperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod0"] + + @yperiod0.setter + def yperiod0(self, val): + self["yperiod0"] = val + + @property + def yperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + + The 'yperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["yperiodalignment"] + + @yperiodalignment.setter + def yperiodalignment(self, val): + self["yperiodalignment"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def zorder(self): + """ + Sets the layer on which this trace is displayed, relative to + other SVG traces on the same subplot. SVG traces with higher + `zorder` appear in front of those with lower `zorder`. + + The 'zorder' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["zorder"] + + @zorder.setter + def zorder(self, val): + self["zorder"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + base + Sets where the bar base is drawn (in position axis + units). In "stack" or "relative" barmode, traces that + set "base" will be excluded and drawn in "overlay" mode + instead. + basesrc + Sets the source reference on Chart Studio Cloud for + `base`. + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + error_x + :class:`plotly.graph_objects.bar.ErrorX` instance or + dict with compatible properties + error_y + :class:`plotly.graph_objects.bar.ErrorY` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.bar.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `value` and `label`. Anything contained in + tag `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.bar.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.bar.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the position where the bar is drawn (in position + axis units). In "group" barmode, traces that set + "offset" will be excluded and drawn in "overlay" mode + instead. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + offsetsrc + Sets the source reference on Chart Studio Cloud for + `offset`. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the bars. With "v" ("h"), the + value of the each bar spans along the vertical + (horizontal). + outsidetextfont + Sets the font used for `text` lying outside the bar. + selected + :class:`plotly.graph_objects.bar.Selected` instance or + dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.bar.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the font used for `text`. + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `value` and `label`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.bar.Unselected` instance + or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar width (in position axis units). + widthsrc + Sets the source reference on Chart Studio Cloud for + `width`. + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + """ + + def __init__( + self, + arg=None, + alignmentgroup=None, + base=None, + basesrc=None, + cliponaxis=None, + constraintext=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + error_x=None, + error_y=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextanchor=None, + insidetextfont=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + offset=None, + offsetgroup=None, + offsetsrc=None, + opacity=None, + orientation=None, + outsidetextfont=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textangle=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + width=None, + widthsrc=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + zorder=None, + **kwargs, + ): + """ + Construct a new Bar object + + The data visualized by the span of the bars is set in `y` if + `orientation` is set to "v" (the default) and the labels are + set in `x`. By setting `orientation` to "h", the roles are + interchanged. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Bar` + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + base + Sets where the bar base is drawn (in position axis + units). In "stack" or "relative" barmode, traces that + set "base" will be excluded and drawn in "overlay" mode + instead. + basesrc + Sets the source reference on Chart Studio Cloud for + `base`. + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + error_x + :class:`plotly.graph_objects.bar.ErrorX` instance or + dict with compatible properties + error_y + :class:`plotly.graph_objects.bar.ErrorY` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.bar.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `value` and `label`. Anything contained in + tag `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.bar.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.bar.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the position where the bar is drawn (in position + axis units). In "group" barmode, traces that set + "offset" will be excluded and drawn in "overlay" mode + instead. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + offsetsrc + Sets the source reference on Chart Studio Cloud for + `offset`. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the bars. With "v" ("h"), the + value of the each bar spans along the vertical + (horizontal). + outsidetextfont + Sets the font used for `text` lying outside the bar. + selected + :class:`plotly.graph_objects.bar.Selected` instance or + dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.bar.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the font used for `text`. + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `value` and `label`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.bar.Unselected` instance + or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar width (in position axis units). + widthsrc + Sets the source reference on Chart Studio Cloud for + `width`. + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + + Returns + ------- + Bar + """ + super().__init__("bar") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Bar +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Bar`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("alignmentgroup", arg, alignmentgroup) + self._set_property("base", arg, base) + self._set_property("basesrc", arg, basesrc) + self._set_property("cliponaxis", arg, cliponaxis) + self._set_property("constraintext", arg, constraintext) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("dx", arg, dx) + self._set_property("dy", arg, dy) + self._set_property("error_x", arg, error_x) + self._set_property("error_y", arg, error_y) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("insidetextanchor", arg, insidetextanchor) + self._set_property("insidetextfont", arg, insidetextfont) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("offset", arg, offset) + self._set_property("offsetgroup", arg, offsetgroup) + self._set_property("offsetsrc", arg, offsetsrc) + self._set_property("opacity", arg, opacity) + self._set_property("orientation", arg, orientation) + self._set_property("outsidetextfont", arg, outsidetextfont) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textangle", arg, textangle) + self._set_property("textfont", arg, textfont) + self._set_property("textposition", arg, textposition) + self._set_property("textpositionsrc", arg, textpositionsrc) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + self._set_property("width", arg, width) + self._set_property("widthsrc", arg, widthsrc) + self._set_property("x", arg, x) + self._set_property("x0", arg, x0) + self._set_property("xaxis", arg, xaxis) + self._set_property("xcalendar", arg, xcalendar) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xperiod", arg, xperiod) + self._set_property("xperiod0", arg, xperiod0) + self._set_property("xperiodalignment", arg, xperiodalignment) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("y0", arg, y0) + self._set_property("yaxis", arg, yaxis) + self._set_property("ycalendar", arg, ycalendar) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("yperiod", arg, yperiod) + self._set_property("yperiod0", arg, yperiod0) + self._set_property("yperiodalignment", arg, yperiodalignment) + self._set_property("ysrc", arg, ysrc) + self._set_property("zorder", arg, zorder) + + self._props["type"] = "bar" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_barpolar.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_barpolar.py new file mode 100644 index 0000000000000000000000000000000000000000..9f414c9adc829bff98694b1182c625c504c6a919 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_barpolar.py @@ -0,0 +1,1655 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Barpolar(_BaseTraceType): + _parent_path_str = "" + _path_str = "barpolar" + _valid_props = { + "base", + "basesrc", + "customdata", + "customdatasrc", + "dr", + "dtheta", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "marker", + "meta", + "metasrc", + "name", + "offset", + "offsetsrc", + "opacity", + "r", + "r0", + "rsrc", + "selected", + "selectedpoints", + "showlegend", + "stream", + "subplot", + "text", + "textsrc", + "theta", + "theta0", + "thetasrc", + "thetaunit", + "type", + "uid", + "uirevision", + "unselected", + "visible", + "width", + "widthsrc", + } + + @property + def base(self): + """ + Sets where the bar base is drawn (in radial axis units). In + "stack" barmode, traces that set "base" will be excluded and + drawn in "overlay" mode instead. + + The 'base' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["base"] + + @base.setter + def base(self, val): + self["base"] = val + + @property + def basesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `base`. + + The 'basesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["basesrc"] + + @basesrc.setter + def basesrc(self, val): + self["basesrc"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def dr(self): + """ + Sets the r coordinate step. + + The 'dr' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dr"] + + @dr.setter + def dr(self, val): + self["dr"] = val + + @property + def dtheta(self): + """ + Sets the theta coordinate step. By default, the `dtheta` step + equals the subplot's period divided by the length of the `r` + coordinates. + + The 'dtheta' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dtheta"] + + @dtheta.setter + def dtheta(self, val): + self["dtheta"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['r', 'theta', 'text', 'name'] joined with '+' characters + (e.g. 'r+theta') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.barpolar.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.barpolar.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.barpolar.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.barpolar.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.barpolar.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.barpolar.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def offset(self): + """ + Shifts the angular position where the bar is drawn (in + "thetatunit" units). + + The 'offset' property is a number and may be specified as: + - An int or float + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["offset"] + + @offset.setter + def offset(self, val): + self["offset"] = val + + @property + def offsetsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `offset`. + + The 'offsetsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["offsetsrc"] + + @offsetsrc.setter + def offsetsrc(self, val): + self["offsetsrc"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def r(self): + """ + Sets the radial coordinates + + The 'r' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["r"] + + @r.setter + def r(self, val): + self["r"] = val + + @property + def r0(self): + """ + Alternate to `r`. Builds a linear space of r coordinates. Use + with `dr` where `r0` is the starting coordinate and `dr` the + step. + + The 'r0' property accepts values of any type + + Returns + ------- + Any + """ + return self["r0"] + + @r0.setter + def r0(self, val): + self["r0"] = val + + @property + def rsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `r`. + + The 'rsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["rsrc"] + + @rsrc.setter + def rsrc(self, val): + self["rsrc"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.barpolar.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.barpolar.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.barpolar.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.barpolar.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def subplot(self): + """ + Sets a reference between this trace's data coordinates and a + polar subplot. If "polar" (the default value), the data refer + to `layout.polar`. If "polar2", the data refer to + `layout.polar2`, and so on. + + The 'subplot' property is an identifier of a particular + subplot, of type 'polar', that may be specified as: + - the string 'polar' optionally followed by an integer >= 1 + (e.g. 'polar', 'polar1', 'polar2', 'polar3', etc.) + + Returns + ------- + str + """ + return self["subplot"] + + @subplot.setter + def subplot(self, val): + self["subplot"] = val + + @property + def text(self): + """ + Sets hover text elements associated with each bar. If a single + string, the same string appears over all bars. If an array of + string, the items are mapped in order to the this trace's + coordinates. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def theta(self): + """ + Sets the angular coordinates + + The 'theta' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["theta"] + + @theta.setter + def theta(self, val): + self["theta"] = val + + @property + def theta0(self): + """ + Alternate to `theta`. Builds a linear space of theta + coordinates. Use with `dtheta` where `theta0` is the starting + coordinate and `dtheta` the step. + + The 'theta0' property accepts values of any type + + Returns + ------- + Any + """ + return self["theta0"] + + @theta0.setter + def theta0(self, val): + self["theta0"] = val + + @property + def thetasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `theta`. + + The 'thetasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["thetasrc"] + + @thetasrc.setter + def thetasrc(self, val): + self["thetasrc"] = val + + @property + def thetaunit(self): + """ + Sets the unit of input "theta" values. Has an effect only when + on "linear" angular axes. + + The 'thetaunit' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['radians', 'degrees', 'gradians'] + + Returns + ------- + Any + """ + return self["thetaunit"] + + @thetaunit.setter + def thetaunit(self, val): + self["thetaunit"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.barpolar.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.barpolar.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def width(self): + """ + Sets the bar angular width (in "thetaunit" units). + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def widthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `width`. + + The 'widthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["widthsrc"] + + @widthsrc.setter + def widthsrc(self, val): + self["widthsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + base + Sets where the bar base is drawn (in radial axis + units). In "stack" barmode, traces that set "base" will + be excluded and drawn in "overlay" mode instead. + basesrc + Sets the source reference on Chart Studio Cloud for + `base`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dr + Sets the r coordinate step. + dtheta + Sets the theta coordinate step. By default, the + `dtheta` step equals the subplot's period divided by + the length of the `r` coordinates. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.barpolar.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.barpolar.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.barpolar.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the angular position where the bar is drawn (in + "thetatunit" units). + offsetsrc + Sets the source reference on Chart Studio Cloud for + `offset`. + opacity + Sets the opacity of the trace. + r + Sets the radial coordinates + r0 + Alternate to `r`. Builds a linear space of r + coordinates. Use with `dr` where `r0` is the starting + coordinate and `dr` the step. + rsrc + Sets the source reference on Chart Studio Cloud for + `r`. + selected + :class:`plotly.graph_objects.barpolar.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.barpolar.Stream` instance + or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a polar subplot. If "polar" (the default value), + the data refer to `layout.polar`. If "polar2", the data + refer to `layout.polar2`, and so on. + text + Sets hover text elements associated with each bar. If a + single string, the same string appears over all bars. + If an array of string, the items are mapped in order to + the this trace's coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + theta + Sets the angular coordinates + theta0 + Alternate to `theta`. Builds a linear space of theta + coordinates. Use with `dtheta` where `theta0` is the + starting coordinate and `dtheta` the step. + thetasrc + Sets the source reference on Chart Studio Cloud for + `theta`. + thetaunit + Sets the unit of input "theta" values. Has an effect + only when on "linear" angular axes. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.barpolar.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar angular width (in "thetaunit" units). + widthsrc + Sets the source reference on Chart Studio Cloud for + `width`. + """ + + def __init__( + self, + arg=None, + base=None, + basesrc=None, + customdata=None, + customdatasrc=None, + dr=None, + dtheta=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + offset=None, + offsetsrc=None, + opacity=None, + r=None, + r0=None, + rsrc=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textsrc=None, + theta=None, + theta0=None, + thetasrc=None, + thetaunit=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + width=None, + widthsrc=None, + **kwargs, + ): + """ + Construct a new Barpolar object + + The data visualized by the radial span of the bars is set in + `r` + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Barpolar` + base + Sets where the bar base is drawn (in radial axis + units). In "stack" barmode, traces that set "base" will + be excluded and drawn in "overlay" mode instead. + basesrc + Sets the source reference on Chart Studio Cloud for + `base`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dr + Sets the r coordinate step. + dtheta + Sets the theta coordinate step. By default, the + `dtheta` step equals the subplot's period divided by + the length of the `r` coordinates. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.barpolar.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.barpolar.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.barpolar.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the angular position where the bar is drawn (in + "thetatunit" units). + offsetsrc + Sets the source reference on Chart Studio Cloud for + `offset`. + opacity + Sets the opacity of the trace. + r + Sets the radial coordinates + r0 + Alternate to `r`. Builds a linear space of r + coordinates. Use with `dr` where `r0` is the starting + coordinate and `dr` the step. + rsrc + Sets the source reference on Chart Studio Cloud for + `r`. + selected + :class:`plotly.graph_objects.barpolar.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.barpolar.Stream` instance + or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a polar subplot. If "polar" (the default value), + the data refer to `layout.polar`. If "polar2", the data + refer to `layout.polar2`, and so on. + text + Sets hover text elements associated with each bar. If a + single string, the same string appears over all bars. + If an array of string, the items are mapped in order to + the this trace's coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + theta + Sets the angular coordinates + theta0 + Alternate to `theta`. Builds a linear space of theta + coordinates. Use with `dtheta` where `theta0` is the + starting coordinate and `dtheta` the step. + thetasrc + Sets the source reference on Chart Studio Cloud for + `theta`. + thetaunit + Sets the unit of input "theta" values. Has an effect + only when on "linear" angular axes. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.barpolar.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar angular width (in "thetaunit" units). + widthsrc + Sets the source reference on Chart Studio Cloud for + `width`. + + Returns + ------- + Barpolar + """ + super().__init__("barpolar") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Barpolar +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Barpolar`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("base", arg, base) + self._set_property("basesrc", arg, basesrc) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("dr", arg, dr) + self._set_property("dtheta", arg, dtheta) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("offset", arg, offset) + self._set_property("offsetsrc", arg, offsetsrc) + self._set_property("opacity", arg, opacity) + self._set_property("r", arg, r) + self._set_property("r0", arg, r0) + self._set_property("rsrc", arg, rsrc) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("subplot", arg, subplot) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("theta", arg, theta) + self._set_property("theta0", arg, theta0) + self._set_property("thetasrc", arg, thetasrc) + self._set_property("thetaunit", arg, thetaunit) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + self._set_property("width", arg, width) + self._set_property("widthsrc", arg, widthsrc) + + self._props["type"] = "barpolar" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_box.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_box.py new file mode 100644 index 0000000000000000000000000000000000000000..0309be1a4056499e0fbbc0279493e15923838590 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_box.py @@ -0,0 +1,3099 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Box(_BaseTraceType): + _parent_path_str = "" + _path_str = "box" + _valid_props = { + "alignmentgroup", + "boxmean", + "boxpoints", + "customdata", + "customdatasrc", + "dx", + "dy", + "fillcolor", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hoveron", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "jitter", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "lowerfence", + "lowerfencesrc", + "marker", + "mean", + "meansrc", + "median", + "mediansrc", + "meta", + "metasrc", + "name", + "notched", + "notchspan", + "notchspansrc", + "notchwidth", + "offsetgroup", + "opacity", + "orientation", + "pointpos", + "q1", + "q1src", + "q3", + "q3src", + "quartilemethod", + "sd", + "sdmultiple", + "sdsrc", + "selected", + "selectedpoints", + "showlegend", + "showwhiskers", + "sizemode", + "stream", + "text", + "textsrc", + "type", + "uid", + "uirevision", + "unselected", + "upperfence", + "upperfencesrc", + "visible", + "whiskerwidth", + "width", + "x", + "x0", + "xaxis", + "xcalendar", + "xhoverformat", + "xperiod", + "xperiod0", + "xperiodalignment", + "xsrc", + "y", + "y0", + "yaxis", + "ycalendar", + "yhoverformat", + "yperiod", + "yperiod0", + "yperiodalignment", + "ysrc", + "zorder", + } + + @property + def alignmentgroup(self): + """ + Set several traces linked to the same position axis or matching + axes to the same alignmentgroup. This controls whether bars + compute their positional range dependently or independently. + + The 'alignmentgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["alignmentgroup"] + + @alignmentgroup.setter + def alignmentgroup(self, val): + self["alignmentgroup"] = val + + @property + def boxmean(self): + """ + If True, the mean of the box(es)' underlying distribution is + drawn as a dashed line inside the box(es). If "sd" the standard + deviation is also drawn. Defaults to True when `mean` is set. + Defaults to "sd" when `sd` is set Otherwise defaults to False. + + The 'boxmean' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, 'sd', False] + + Returns + ------- + Any + """ + return self["boxmean"] + + @boxmean.setter + def boxmean(self, val): + self["boxmean"] = val + + @property + def boxpoints(self): + """ + If "outliers", only the sample points lying outside the + whiskers are shown If "suspectedoutliers", the outlier points + are shown and points either less than 4*Q1-3*Q3 or greater than + 4*Q3-3*Q1 are highlighted (see `outliercolor`) If "all", all + sample points are shown If False, only the box(es) are shown + with no sample points Defaults to "suspectedoutliers" when + `marker.outliercolor` or `marker.line.outliercolor` is set. + Defaults to "all" under the q1/median/q3 signature. Otherwise + defaults to "outliers". + + The 'boxpoints' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'outliers', 'suspectedoutliers', False] + + Returns + ------- + Any + """ + return self["boxpoints"] + + @boxpoints.setter + def boxpoints(self, val): + self["boxpoints"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def dx(self): + """ + Sets the x coordinate step for multi-box traces set using + q1/median/q3. + + The 'dx' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dx"] + + @dx.setter + def dx(self, val): + self["dx"] = val + + @property + def dy(self): + """ + Sets the y coordinate step for multi-box traces set using + q1/median/q3. + + The 'dy' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dy"] + + @dy.setter + def dy(self, val): + self["dy"] = val + + @property + def fillcolor(self): + """ + Sets the fill color. Defaults to a half-transparent variant of + the line color, marker color, or marker line color, whichever + is available. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.box.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.box.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hoveron(self): + """ + Do the hover effects highlight individual boxes or sample + points or both? + + The 'hoveron' property is a flaglist and may be specified + as a string containing: + - Any combination of ['boxes', 'points'] joined with '+' characters + (e.g. 'boxes+points') + + Returns + ------- + Any + """ + return self["hoveron"] + + @hoveron.setter + def hoveron(self, val): + self["hoveron"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def jitter(self): + """ + Sets the amount of jitter in the sample points drawn. If 0, the + sample points align along the distribution axis. If 1, the + sample points are drawn in a random jitter of width equal to + the width of the box(es). + + The 'jitter' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["jitter"] + + @jitter.setter + def jitter(self, val): + self["jitter"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.box.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.box.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.box.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.box.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def lowerfence(self): + """ + Sets the lower fence values. There should be as many items as + the number of boxes desired. This attribute has effect only + under the q1/median/q3 signature. If `lowerfence` is not + provided but a sample (in `y` or `x`) is set, we compute the + lower as the last sample point below 1.5 times the IQR. + + The 'lowerfence' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["lowerfence"] + + @lowerfence.setter + def lowerfence(self, val): + self["lowerfence"] = val + + @property + def lowerfencesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `lowerfence`. + + The 'lowerfencesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["lowerfencesrc"] + + @lowerfencesrc.setter + def lowerfencesrc(self, val): + self["lowerfencesrc"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.box.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.box.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def mean(self): + """ + Sets the mean values. There should be as many items as the + number of boxes desired. This attribute has effect only under + the q1/median/q3 signature. If `mean` is not provided but a + sample (in `y` or `x`) is set, we compute the mean for each box + using the sample values. + + The 'mean' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["mean"] + + @mean.setter + def mean(self, val): + self["mean"] = val + + @property + def meansrc(self): + """ + Sets the source reference on Chart Studio Cloud for `mean`. + + The 'meansrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["meansrc"] + + @meansrc.setter + def meansrc(self, val): + self["meansrc"] = val + + @property + def median(self): + """ + Sets the median values. There should be as many items as the + number of boxes desired. + + The 'median' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["median"] + + @median.setter + def median(self, val): + self["median"] = val + + @property + def mediansrc(self): + """ + Sets the source reference on Chart Studio Cloud for `median`. + + The 'mediansrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["mediansrc"] + + @mediansrc.setter + def mediansrc(self, val): + self["mediansrc"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. For box traces, the name will also be used for + the position coordinate, if `x` and `x0` (`y` and `y0` if + horizontal) are missing and the position axis is categorical + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def notched(self): + """ + Determines whether or not notches are drawn. Notches displays a + confidence interval around the median. We compute the + confidence interval as median +/- 1.57 * IQR / sqrt(N), where + IQR is the interquartile range and N is the sample size. If two + boxes' notches do not overlap there is 95% confidence their + medians differ. See + https://sites.google.com/site/davidsstatistics/home/notched- + box-plots for more info. Defaults to False unless `notchwidth` + or `notchspan` is set. + + The 'notched' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["notched"] + + @notched.setter + def notched(self, val): + self["notched"] = val + + @property + def notchspan(self): + """ + Sets the notch span from the boxes' `median` values. There + should be as many items as the number of boxes desired. This + attribute has effect only under the q1/median/q3 signature. If + `notchspan` is not provided but a sample (in `y` or `x`) is + set, we compute it as 1.57 * IQR / sqrt(N), where N is the + sample size. + + The 'notchspan' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["notchspan"] + + @notchspan.setter + def notchspan(self, val): + self["notchspan"] = val + + @property + def notchspansrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `notchspan`. + + The 'notchspansrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["notchspansrc"] + + @notchspansrc.setter + def notchspansrc(self, val): + self["notchspansrc"] = val + + @property + def notchwidth(self): + """ + Sets the width of the notches relative to the box width. For + example, with 0, the notches are as wide as the box(es). + + The 'notchwidth' property is a number and may be specified as: + - An int or float in the interval [0, 0.5] + + Returns + ------- + int|float + """ + return self["notchwidth"] + + @notchwidth.setter + def notchwidth(self, val): + self["notchwidth"] = val + + @property + def offsetgroup(self): + """ + Set several traces linked to the same position axis or matching + axes to the same offsetgroup where bars of the same position + coordinate will line up. + + The 'offsetgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["offsetgroup"] + + @offsetgroup.setter + def offsetgroup(self, val): + self["offsetgroup"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def orientation(self): + """ + Sets the orientation of the box(es). If "v" ("h"), the + distribution is visualized along the vertical (horizontal). + + The 'orientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['v', 'h'] + + Returns + ------- + Any + """ + return self["orientation"] + + @orientation.setter + def orientation(self, val): + self["orientation"] = val + + @property + def pointpos(self): + """ + Sets the position of the sample points in relation to the + box(es). If 0, the sample points are places over the center of + the box(es). Positive (negative) values correspond to positions + to the right (left) for vertical boxes and above (below) for + horizontal boxes + + The 'pointpos' property is a number and may be specified as: + - An int or float in the interval [-2, 2] + + Returns + ------- + int|float + """ + return self["pointpos"] + + @pointpos.setter + def pointpos(self, val): + self["pointpos"] = val + + @property + def q1(self): + """ + Sets the Quartile 1 values. There should be as many items as + the number of boxes desired. + + The 'q1' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["q1"] + + @q1.setter + def q1(self, val): + self["q1"] = val + + @property + def q1src(self): + """ + Sets the source reference on Chart Studio Cloud for `q1`. + + The 'q1src' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["q1src"] + + @q1src.setter + def q1src(self, val): + self["q1src"] = val + + @property + def q3(self): + """ + Sets the Quartile 3 values. There should be as many items as + the number of boxes desired. + + The 'q3' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["q3"] + + @q3.setter + def q3(self, val): + self["q3"] = val + + @property + def q3src(self): + """ + Sets the source reference on Chart Studio Cloud for `q3`. + + The 'q3src' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["q3src"] + + @q3src.setter + def q3src(self, val): + self["q3src"] = val + + @property + def quartilemethod(self): + """ + Sets the method used to compute the sample's Q1 and Q3 + quartiles. The "linear" method uses the 25th percentile for Q1 + and 75th percentile for Q3 as computed using method #10 (listed + on http://jse.amstat.org/v14n3/langford.html). The "exclusive" + method uses the median to divide the ordered dataset into two + halves if the sample is odd, it does not include the median in + either half - Q1 is then the median of the lower half and Q3 + the median of the upper half. The "inclusive" method also uses + the median to divide the ordered dataset into two halves but if + the sample is odd, it includes the median in both halves - Q1 + is then the median of the lower half and Q3 the median of the + upper half. + + The 'quartilemethod' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['linear', 'exclusive', 'inclusive'] + + Returns + ------- + Any + """ + return self["quartilemethod"] + + @quartilemethod.setter + def quartilemethod(self, val): + self["quartilemethod"] = val + + @property + def sd(self): + """ + Sets the standard deviation values. There should be as many + items as the number of boxes desired. This attribute has effect + only under the q1/median/q3 signature. If `sd` is not provided + but a sample (in `y` or `x`) is set, we compute the standard + deviation for each box using the sample values. + + The 'sd' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["sd"] + + @sd.setter + def sd(self, val): + self["sd"] = val + + @property + def sdmultiple(self): + """ + Scales the box size when sizemode=sd Allowing boxes to be drawn + across any stddev range For example 1-stddev, 3-stddev, + 5-stddev + + The 'sdmultiple' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["sdmultiple"] + + @sdmultiple.setter + def sdmultiple(self, val): + self["sdmultiple"] = val + + @property + def sdsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `sd`. + + The 'sdsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["sdsrc"] + + @sdsrc.setter + def sdsrc(self, val): + self["sdsrc"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.box.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.box.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showwhiskers(self): + """ + Determines whether or not whiskers are visible. Defaults to + true for `sizemode` "quartiles", false for "sd". + + The 'showwhiskers' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showwhiskers"] + + @showwhiskers.setter + def showwhiskers(self, val): + self["showwhiskers"] = val + + @property + def sizemode(self): + """ + Sets the upper and lower bound for the boxes quartiles means + box is drawn between Q1 and Q3 SD means the box is drawn + between Mean +- Standard Deviation Argument sdmultiple (default + 1) to scale the box size So it could be drawn 1-stddev, + 3-stddev etc + + The 'sizemode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['quartiles', 'sd'] + + Returns + ------- + Any + """ + return self["sizemode"] + + @sizemode.setter + def sizemode(self, val): + self["sizemode"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.box.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.box.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets the text elements associated with each sample value. If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (x,y) coordinates. To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.box.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.box.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def upperfence(self): + """ + Sets the upper fence values. There should be as many items as + the number of boxes desired. This attribute has effect only + under the q1/median/q3 signature. If `upperfence` is not + provided but a sample (in `y` or `x`) is set, we compute the + upper as the last sample point above 1.5 times the IQR. + + The 'upperfence' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["upperfence"] + + @upperfence.setter + def upperfence(self, val): + self["upperfence"] = val + + @property + def upperfencesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `upperfence`. + + The 'upperfencesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["upperfencesrc"] + + @upperfencesrc.setter + def upperfencesrc(self, val): + self["upperfencesrc"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def whiskerwidth(self): + """ + Sets the width of the whiskers relative to the box width. For + example, with 1, the whiskers are as wide as the box(es). + + The 'whiskerwidth' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["whiskerwidth"] + + @whiskerwidth.setter + def whiskerwidth(self, val): + self["whiskerwidth"] = val + + @property + def width(self): + """ + Sets the width of the box in data coordinate If 0 (default + value) the width is automatically selected based on the + positions of other box traces in the same subplot. + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def x(self): + """ + Sets the x sample data or coordinates. See overview for more + info. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def x0(self): + """ + Sets the x coordinate for single-box traces or the starting + coordinate for multi-box traces set using q1/median/q3. See + overview for more info. + + The 'x0' property accepts values of any type + + Returns + ------- + Any + """ + return self["x0"] + + @x0.setter + def x0(self, val): + self["x0"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def xcalendar(self): + """ + Sets the calendar system to use with `x` date data. + + The 'xcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["xcalendar"] + + @xcalendar.setter + def xcalendar(self, val): + self["xcalendar"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the x axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'xperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod"] + + @xperiod.setter + def xperiod(self, val): + self["xperiod"] = val + + @property + def xperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the x0 + axis. When `x0period` is round number of weeks, the `x0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'xperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod0"] + + @xperiod0.setter + def xperiod0(self, val): + self["xperiod0"] = val + + @property + def xperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + + The 'xperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["xperiodalignment"] + + @xperiodalignment.setter + def xperiodalignment(self, val): + self["xperiodalignment"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the y sample data or coordinates. See overview for more + info. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def y0(self): + """ + Sets the y coordinate for single-box traces or the starting + coordinate for multi-box traces set using q1/median/q3. See + overview for more info. + + The 'y0' property accepts values of any type + + Returns + ------- + Any + """ + return self["y0"] + + @y0.setter + def y0(self, val): + self["y0"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def ycalendar(self): + """ + Sets the calendar system to use with `y` date data. + + The 'ycalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["ycalendar"] + + @ycalendar.setter + def ycalendar(self, val): + self["ycalendar"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def yperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the y axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'yperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod"] + + @yperiod.setter + def yperiod(self, val): + self["yperiod"] = val + + @property + def yperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the y0 + axis. When `y0period` is round number of weeks, the `y0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'yperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod0"] + + @yperiod0.setter + def yperiod0(self, val): + self["yperiod0"] = val + + @property + def yperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + + The 'yperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["yperiodalignment"] + + @yperiodalignment.setter + def yperiodalignment(self, val): + self["yperiodalignment"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def zorder(self): + """ + Sets the layer on which this trace is displayed, relative to + other SVG traces on the same subplot. SVG traces with higher + `zorder` appear in front of those with lower `zorder`. + + The 'zorder' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["zorder"] + + @zorder.setter + def zorder(self, val): + self["zorder"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + boxmean + If True, the mean of the box(es)' underlying + distribution is drawn as a dashed line inside the + box(es). If "sd" the standard deviation is also drawn. + Defaults to True when `mean` is set. Defaults to "sd" + when `sd` is set Otherwise defaults to False. + boxpoints + If "outliers", only the sample points lying outside the + whiskers are shown If "suspectedoutliers", the outlier + points are shown and points either less than 4*Q1-3*Q3 + or greater than 4*Q3-3*Q1 are highlighted (see + `outliercolor`) If "all", all sample points are shown + If False, only the box(es) are shown with no sample + points Defaults to "suspectedoutliers" when + `marker.outliercolor` or `marker.line.outliercolor` is + set. Defaults to "all" under the q1/median/q3 + signature. Otherwise defaults to "outliers". + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step for multi-box traces set + using q1/median/q3. + dy + Sets the y coordinate step for multi-box traces set + using q1/median/q3. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.box.Hoverlabel` instance + or dict with compatible properties + hoveron + Do the hover effects highlight individual boxes or + sample points or both? + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + jitter + Sets the amount of jitter in the sample points drawn. + If 0, the sample points align along the distribution + axis. If 1, the sample points are drawn in a random + jitter of width equal to the width of the box(es). + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.box.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.box.Line` instance or dict + with compatible properties + lowerfence + Sets the lower fence values. There should be as many + items as the number of boxes desired. This attribute + has effect only under the q1/median/q3 signature. If + `lowerfence` is not provided but a sample (in `y` or + `x`) is set, we compute the lower as the last sample + point below 1.5 times the IQR. + lowerfencesrc + Sets the source reference on Chart Studio Cloud for + `lowerfence`. + marker + :class:`plotly.graph_objects.box.Marker` instance or + dict with compatible properties + mean + Sets the mean values. There should be as many items as + the number of boxes desired. This attribute has effect + only under the q1/median/q3 signature. If `mean` is not + provided but a sample (in `y` or `x`) is set, we + compute the mean for each box using the sample values. + meansrc + Sets the source reference on Chart Studio Cloud for + `mean`. + median + Sets the median values. There should be as many items + as the number of boxes desired. + mediansrc + Sets the source reference on Chart Studio Cloud for + `median`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. For box traces, the name will + also be used for the position coordinate, if `x` and + `x0` (`y` and `y0` if horizontal) are missing and the + position axis is categorical + notched + Determines whether or not notches are drawn. Notches + displays a confidence interval around the median. We + compute the confidence interval as median +/- 1.57 * + IQR / sqrt(N), where IQR is the interquartile range and + N is the sample size. If two boxes' notches do not + overlap there is 95% confidence their medians differ. + See https://sites.google.com/site/davidsstatistics/home + /notched-box-plots for more info. Defaults to False + unless `notchwidth` or `notchspan` is set. + notchspan + Sets the notch span from the boxes' `median` values. + There should be as many items as the number of boxes + desired. This attribute has effect only under the + q1/median/q3 signature. If `notchspan` is not provided + but a sample (in `y` or `x`) is set, we compute it as + 1.57 * IQR / sqrt(N), where N is the sample size. + notchspansrc + Sets the source reference on Chart Studio Cloud for + `notchspan`. + notchwidth + Sets the width of the notches relative to the box + width. For example, with 0, the notches are as wide as + the box(es). + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the box(es). If "v" ("h"), the + distribution is visualized along the vertical + (horizontal). + pointpos + Sets the position of the sample points in relation to + the box(es). If 0, the sample points are places over + the center of the box(es). Positive (negative) values + correspond to positions to the right (left) for + vertical boxes and above (below) for horizontal boxes + q1 + Sets the Quartile 1 values. There should be as many + items as the number of boxes desired. + q1src + Sets the source reference on Chart Studio Cloud for + `q1`. + q3 + Sets the Quartile 3 values. There should be as many + items as the number of boxes desired. + q3src + Sets the source reference on Chart Studio Cloud for + `q3`. + quartilemethod + Sets the method used to compute the sample's Q1 and Q3 + quartiles. The "linear" method uses the 25th percentile + for Q1 and 75th percentile for Q3 as computed using + method #10 (listed on + http://jse.amstat.org/v14n3/langford.html). The + "exclusive" method uses the median to divide the + ordered dataset into two halves if the sample is odd, + it does not include the median in either half - Q1 is + then the median of the lower half and Q3 the median of + the upper half. The "inclusive" method also uses the + median to divide the ordered dataset into two halves + but if the sample is odd, it includes the median in + both halves - Q1 is then the median of the lower half + and Q3 the median of the upper half. + sd + Sets the standard deviation values. There should be as + many items as the number of boxes desired. This + attribute has effect only under the q1/median/q3 + signature. If `sd` is not provided but a sample (in `y` + or `x`) is set, we compute the standard deviation for + each box using the sample values. + sdmultiple + Scales the box size when sizemode=sd Allowing boxes to + be drawn across any stddev range For example 1-stddev, + 3-stddev, 5-stddev + sdsrc + Sets the source reference on Chart Studio Cloud for + `sd`. + selected + :class:`plotly.graph_objects.box.Selected` instance or + dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showwhiskers + Determines whether or not whiskers are visible. + Defaults to true for `sizemode` "quartiles", false for + "sd". + sizemode + Sets the upper and lower bound for the boxes quartiles + means box is drawn between Q1 and Q3 SD means the box + is drawn between Mean +- Standard Deviation Argument + sdmultiple (default 1) to scale the box size So it + could be drawn 1-stddev, 3-stddev etc + stream + :class:`plotly.graph_objects.box.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with each sample + value. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.box.Unselected` instance + or dict with compatible properties + upperfence + Sets the upper fence values. There should be as many + items as the number of boxes desired. This attribute + has effect only under the q1/median/q3 signature. If + `upperfence` is not provided but a sample (in `y` or + `x`) is set, we compute the upper as the last sample + point above 1.5 times the IQR. + upperfencesrc + Sets the source reference on Chart Studio Cloud for + `upperfence`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + whiskerwidth + Sets the width of the whiskers relative to the box + width. For example, with 1, the whiskers are as wide as + the box(es). + width + Sets the width of the box in data coordinate If 0 + (default value) the width is automatically selected + based on the positions of other box traces in the same + subplot. + x + Sets the x sample data or coordinates. See overview for + more info. + x0 + Sets the x coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y sample data or coordinates. See overview for + more info. + y0 + Sets the y coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + """ + + def __init__( + self, + arg=None, + alignmentgroup=None, + boxmean=None, + boxpoints=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + jitter=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + lowerfence=None, + lowerfencesrc=None, + marker=None, + mean=None, + meansrc=None, + median=None, + mediansrc=None, + meta=None, + metasrc=None, + name=None, + notched=None, + notchspan=None, + notchspansrc=None, + notchwidth=None, + offsetgroup=None, + opacity=None, + orientation=None, + pointpos=None, + q1=None, + q1src=None, + q3=None, + q3src=None, + quartilemethod=None, + sd=None, + sdmultiple=None, + sdsrc=None, + selected=None, + selectedpoints=None, + showlegend=None, + showwhiskers=None, + sizemode=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + upperfence=None, + upperfencesrc=None, + visible=None, + whiskerwidth=None, + width=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + zorder=None, + **kwargs, + ): + """ + Construct a new Box object + + Each box spans from quartile 1 (Q1) to quartile 3 (Q3). The + second quartile (Q2, i.e. the median) is marked by a line + inside the box. The fences grow outward from the boxes' edges, + by default they span +/- 1.5 times the interquartile range + (IQR: Q3-Q1), The sample mean and standard deviation as well as + notches and the sample, outlier and suspected outliers points + can be optionally added to the box plot. The values and + positions corresponding to each boxes can be input using two + signatures. The first signature expects users to supply the + sample values in the `y` data array for vertical boxes (`x` for + horizontal boxes). By supplying an `x` (`y`) array, one box per + distinct `x` (`y`) value is drawn If no `x` (`y`) list is + provided, a single box is drawn. In this case, the box is + positioned with the trace `name` or with `x0` (`y0`) if + provided. The second signature expects users to supply the + boxes corresponding Q1, median and Q3 statistics in the `q1`, + `median` and `q3` data arrays respectively. Other box features + relying on statistics namely `lowerfence`, `upperfence`, + `notchspan` can be set directly by the users. To have plotly + compute them or to show sample points besides the boxes, users + can set the `y` data array for vertical boxes (`x` for + horizontal boxes) to a 2D array with the outer length + corresponding to the number of boxes in the traces and the + inner length corresponding the sample size. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Box` + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + boxmean + If True, the mean of the box(es)' underlying + distribution is drawn as a dashed line inside the + box(es). If "sd" the standard deviation is also drawn. + Defaults to True when `mean` is set. Defaults to "sd" + when `sd` is set Otherwise defaults to False. + boxpoints + If "outliers", only the sample points lying outside the + whiskers are shown If "suspectedoutliers", the outlier + points are shown and points either less than 4*Q1-3*Q3 + or greater than 4*Q3-3*Q1 are highlighted (see + `outliercolor`) If "all", all sample points are shown + If False, only the box(es) are shown with no sample + points Defaults to "suspectedoutliers" when + `marker.outliercolor` or `marker.line.outliercolor` is + set. Defaults to "all" under the q1/median/q3 + signature. Otherwise defaults to "outliers". + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step for multi-box traces set + using q1/median/q3. + dy + Sets the y coordinate step for multi-box traces set + using q1/median/q3. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.box.Hoverlabel` instance + or dict with compatible properties + hoveron + Do the hover effects highlight individual boxes or + sample points or both? + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + jitter + Sets the amount of jitter in the sample points drawn. + If 0, the sample points align along the distribution + axis. If 1, the sample points are drawn in a random + jitter of width equal to the width of the box(es). + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.box.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.box.Line` instance or dict + with compatible properties + lowerfence + Sets the lower fence values. There should be as many + items as the number of boxes desired. This attribute + has effect only under the q1/median/q3 signature. If + `lowerfence` is not provided but a sample (in `y` or + `x`) is set, we compute the lower as the last sample + point below 1.5 times the IQR. + lowerfencesrc + Sets the source reference on Chart Studio Cloud for + `lowerfence`. + marker + :class:`plotly.graph_objects.box.Marker` instance or + dict with compatible properties + mean + Sets the mean values. There should be as many items as + the number of boxes desired. This attribute has effect + only under the q1/median/q3 signature. If `mean` is not + provided but a sample (in `y` or `x`) is set, we + compute the mean for each box using the sample values. + meansrc + Sets the source reference on Chart Studio Cloud for + `mean`. + median + Sets the median values. There should be as many items + as the number of boxes desired. + mediansrc + Sets the source reference on Chart Studio Cloud for + `median`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. For box traces, the name will + also be used for the position coordinate, if `x` and + `x0` (`y` and `y0` if horizontal) are missing and the + position axis is categorical + notched + Determines whether or not notches are drawn. Notches + displays a confidence interval around the median. We + compute the confidence interval as median +/- 1.57 * + IQR / sqrt(N), where IQR is the interquartile range and + N is the sample size. If two boxes' notches do not + overlap there is 95% confidence their medians differ. + See https://sites.google.com/site/davidsstatistics/home + /notched-box-plots for more info. Defaults to False + unless `notchwidth` or `notchspan` is set. + notchspan + Sets the notch span from the boxes' `median` values. + There should be as many items as the number of boxes + desired. This attribute has effect only under the + q1/median/q3 signature. If `notchspan` is not provided + but a sample (in `y` or `x`) is set, we compute it as + 1.57 * IQR / sqrt(N), where N is the sample size. + notchspansrc + Sets the source reference on Chart Studio Cloud for + `notchspan`. + notchwidth + Sets the width of the notches relative to the box + width. For example, with 0, the notches are as wide as + the box(es). + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the box(es). If "v" ("h"), the + distribution is visualized along the vertical + (horizontal). + pointpos + Sets the position of the sample points in relation to + the box(es). If 0, the sample points are places over + the center of the box(es). Positive (negative) values + correspond to positions to the right (left) for + vertical boxes and above (below) for horizontal boxes + q1 + Sets the Quartile 1 values. There should be as many + items as the number of boxes desired. + q1src + Sets the source reference on Chart Studio Cloud for + `q1`. + q3 + Sets the Quartile 3 values. There should be as many + items as the number of boxes desired. + q3src + Sets the source reference on Chart Studio Cloud for + `q3`. + quartilemethod + Sets the method used to compute the sample's Q1 and Q3 + quartiles. The "linear" method uses the 25th percentile + for Q1 and 75th percentile for Q3 as computed using + method #10 (listed on + http://jse.amstat.org/v14n3/langford.html). The + "exclusive" method uses the median to divide the + ordered dataset into two halves if the sample is odd, + it does not include the median in either half - Q1 is + then the median of the lower half and Q3 the median of + the upper half. The "inclusive" method also uses the + median to divide the ordered dataset into two halves + but if the sample is odd, it includes the median in + both halves - Q1 is then the median of the lower half + and Q3 the median of the upper half. + sd + Sets the standard deviation values. There should be as + many items as the number of boxes desired. This + attribute has effect only under the q1/median/q3 + signature. If `sd` is not provided but a sample (in `y` + or `x`) is set, we compute the standard deviation for + each box using the sample values. + sdmultiple + Scales the box size when sizemode=sd Allowing boxes to + be drawn across any stddev range For example 1-stddev, + 3-stddev, 5-stddev + sdsrc + Sets the source reference on Chart Studio Cloud for + `sd`. + selected + :class:`plotly.graph_objects.box.Selected` instance or + dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showwhiskers + Determines whether or not whiskers are visible. + Defaults to true for `sizemode` "quartiles", false for + "sd". + sizemode + Sets the upper and lower bound for the boxes quartiles + means box is drawn between Q1 and Q3 SD means the box + is drawn between Mean +- Standard Deviation Argument + sdmultiple (default 1) to scale the box size So it + could be drawn 1-stddev, 3-stddev etc + stream + :class:`plotly.graph_objects.box.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with each sample + value. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.box.Unselected` instance + or dict with compatible properties + upperfence + Sets the upper fence values. There should be as many + items as the number of boxes desired. This attribute + has effect only under the q1/median/q3 signature. If + `upperfence` is not provided but a sample (in `y` or + `x`) is set, we compute the upper as the last sample + point above 1.5 times the IQR. + upperfencesrc + Sets the source reference on Chart Studio Cloud for + `upperfence`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + whiskerwidth + Sets the width of the whiskers relative to the box + width. For example, with 1, the whiskers are as wide as + the box(es). + width + Sets the width of the box in data coordinate If 0 + (default value) the width is automatically selected + based on the positions of other box traces in the same + subplot. + x + Sets the x sample data or coordinates. See overview for + more info. + x0 + Sets the x coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y sample data or coordinates. See overview for + more info. + y0 + Sets the y coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + + Returns + ------- + Box + """ + super().__init__("box") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Box +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Box`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("alignmentgroup", arg, alignmentgroup) + self._set_property("boxmean", arg, boxmean) + self._set_property("boxpoints", arg, boxpoints) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("dx", arg, dx) + self._set_property("dy", arg, dy) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hoveron", arg, hoveron) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("jitter", arg, jitter) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("lowerfence", arg, lowerfence) + self._set_property("lowerfencesrc", arg, lowerfencesrc) + self._set_property("marker", arg, marker) + self._set_property("mean", arg, mean) + self._set_property("meansrc", arg, meansrc) + self._set_property("median", arg, median) + self._set_property("mediansrc", arg, mediansrc) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("notched", arg, notched) + self._set_property("notchspan", arg, notchspan) + self._set_property("notchspansrc", arg, notchspansrc) + self._set_property("notchwidth", arg, notchwidth) + self._set_property("offsetgroup", arg, offsetgroup) + self._set_property("opacity", arg, opacity) + self._set_property("orientation", arg, orientation) + self._set_property("pointpos", arg, pointpos) + self._set_property("q1", arg, q1) + self._set_property("q1src", arg, q1src) + self._set_property("q3", arg, q3) + self._set_property("q3src", arg, q3src) + self._set_property("quartilemethod", arg, quartilemethod) + self._set_property("sd", arg, sd) + self._set_property("sdmultiple", arg, sdmultiple) + self._set_property("sdsrc", arg, sdsrc) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("showwhiskers", arg, showwhiskers) + self._set_property("sizemode", arg, sizemode) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("upperfence", arg, upperfence) + self._set_property("upperfencesrc", arg, upperfencesrc) + self._set_property("visible", arg, visible) + self._set_property("whiskerwidth", arg, whiskerwidth) + self._set_property("width", arg, width) + self._set_property("x", arg, x) + self._set_property("x0", arg, x0) + self._set_property("xaxis", arg, xaxis) + self._set_property("xcalendar", arg, xcalendar) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xperiod", arg, xperiod) + self._set_property("xperiod0", arg, xperiod0) + self._set_property("xperiodalignment", arg, xperiodalignment) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("y0", arg, y0) + self._set_property("yaxis", arg, yaxis) + self._set_property("ycalendar", arg, ycalendar) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("yperiod", arg, yperiod) + self._set_property("yperiod0", arg, yperiod0) + self._set_property("yperiodalignment", arg, yperiodalignment) + self._set_property("ysrc", arg, ysrc) + self._set_property("zorder", arg, zorder) + + self._props["type"] = "box" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_candlestick.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_candlestick.py new file mode 100644 index 0000000000000000000000000000000000000000..67131d8fa0b707b4ccad6f7e5a6bee76b842747d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_candlestick.py @@ -0,0 +1,1860 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Candlestick(_BaseTraceType): + _parent_path_str = "" + _path_str = "candlestick" + _valid_props = { + "close", + "closesrc", + "customdata", + "customdatasrc", + "decreasing", + "high", + "highsrc", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "increasing", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "low", + "lowsrc", + "meta", + "metasrc", + "name", + "opacity", + "open", + "opensrc", + "selectedpoints", + "showlegend", + "stream", + "text", + "textsrc", + "type", + "uid", + "uirevision", + "visible", + "whiskerwidth", + "x", + "xaxis", + "xcalendar", + "xhoverformat", + "xperiod", + "xperiod0", + "xperiodalignment", + "xsrc", + "yaxis", + "yhoverformat", + "zorder", + } + + @property + def close(self): + """ + Sets the close values. + + The 'close' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["close"] + + @close.setter + def close(self, val): + self["close"] = val + + @property + def closesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `close`. + + The 'closesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["closesrc"] + + @closesrc.setter + def closesrc(self, val): + self["closesrc"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def decreasing(self): + """ + The 'decreasing' property is an instance of Decreasing + that may be specified as: + - An instance of :class:`plotly.graph_objs.candlestick.Decreasing` + - A dict of string/value properties that will be passed + to the Decreasing constructor + + Returns + ------- + plotly.graph_objs.candlestick.Decreasing + """ + return self["decreasing"] + + @decreasing.setter + def decreasing(self, val): + self["decreasing"] = val + + @property + def high(self): + """ + Sets the high values. + + The 'high' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["high"] + + @high.setter + def high(self, val): + self["high"] = val + + @property + def highsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `high`. + + The 'highsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["highsrc"] + + @highsrc.setter + def highsrc(self, val): + self["highsrc"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.candlestick.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.candlestick.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables `open`, + `high`, `low` and `close`. Anything contained in tag `` + is displayed in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def increasing(self): + """ + The 'increasing' property is an instance of Increasing + that may be specified as: + - An instance of :class:`plotly.graph_objs.candlestick.Increasing` + - A dict of string/value properties that will be passed + to the Increasing constructor + + Returns + ------- + plotly.graph_objs.candlestick.Increasing + """ + return self["increasing"] + + @increasing.setter + def increasing(self, val): + self["increasing"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.candlestick.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.candlestick.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.candlestick.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.candlestick.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def low(self): + """ + Sets the low values. + + The 'low' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["low"] + + @low.setter + def low(self, val): + self["low"] = val + + @property + def lowsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `low`. + + The 'lowsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["lowsrc"] + + @lowsrc.setter + def lowsrc(self, val): + self["lowsrc"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def open(self): + """ + Sets the open values. + + The 'open' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["open"] + + @open.setter + def open(self, val): + self["open"] = val + + @property + def opensrc(self): + """ + Sets the source reference on Chart Studio Cloud for `open`. + + The 'opensrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["opensrc"] + + @opensrc.setter + def opensrc(self, val): + self["opensrc"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.candlestick.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.candlestick.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets hover text elements associated with each sample point. If + a single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + this trace's sample points. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def whiskerwidth(self): + """ + Sets the width of the whiskers relative to the box width. For + example, with 1, the whiskers are as wide as the box(es). + + The 'whiskerwidth' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["whiskerwidth"] + + @whiskerwidth.setter + def whiskerwidth(self, val): + self["whiskerwidth"] = val + + @property + def x(self): + """ + Sets the x coordinates. If absent, linear coordinate will be + generated. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def xcalendar(self): + """ + Sets the calendar system to use with `x` date data. + + The 'xcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["xcalendar"] + + @xcalendar.setter + def xcalendar(self, val): + self["xcalendar"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the x axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'xperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod"] + + @xperiod.setter + def xperiod(self, val): + self["xperiod"] = val + + @property + def xperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the x0 + axis. When `x0period` is round number of weeks, the `x0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'xperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod0"] + + @xperiod0.setter + def xperiod0(self, val): + self["xperiod0"] = val + + @property + def xperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + + The 'xperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["xperiodalignment"] + + @xperiodalignment.setter + def xperiodalignment(self, val): + self["xperiodalignment"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def zorder(self): + """ + Sets the layer on which this trace is displayed, relative to + other SVG traces on the same subplot. SVG traces with higher + `zorder` appear in front of those with lower `zorder`. + + The 'zorder' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["zorder"] + + @zorder.setter + def zorder(self, val): + self["zorder"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + close + Sets the close values. + closesrc + Sets the source reference on Chart Studio Cloud for + `close`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + decreasing + :class:`plotly.graph_objects.candlestick.Decreasing` + instance or dict with compatible properties + high + Sets the high values. + highsrc + Sets the source reference on Chart Studio Cloud for + `high`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.candlestick.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `open`, `high`, `low` and `close`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + increasing + :class:`plotly.graph_objects.candlestick.Increasing` + instance or dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.candlestick.Legendgrouptit + le` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.candlestick.Line` instance + or dict with compatible properties + low + Sets the low values. + lowsrc + Sets the source reference on Chart Studio Cloud for + `low`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + open + Sets the open values. + opensrc + Sets the source reference on Chart Studio Cloud for + `open`. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.candlestick.Stream` + instance or dict with compatible properties + text + Sets hover text elements associated with each sample + point. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to this trace's sample points. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + whiskerwidth + Sets the width of the whiskers relative to the box + width. For example, with 1, the whiskers are as wide as + the box(es). + x + Sets the x coordinates. If absent, linear coordinate + will be generated. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + """ + + def __init__( + self, + arg=None, + close=None, + closesrc=None, + customdata=None, + customdatasrc=None, + decreasing=None, + high=None, + highsrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + increasing=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + low=None, + lowsrc=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + open=None, + opensrc=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + visible=None, + whiskerwidth=None, + x=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + yaxis=None, + yhoverformat=None, + zorder=None, + **kwargs, + ): + """ + Construct a new Candlestick object + + The candlestick is a style of financial chart describing open, + high, low and close for a given `x` coordinate (most likely + time). The boxes represent the spread between the `open` and + `close` values and the lines represent the spread between the + `low` and `high` values Sample points where the close value is + higher (lower) then the open value are called increasing + (decreasing). By default, increasing candles are drawn in green + whereas decreasing are drawn in red. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Candlestick` + close + Sets the close values. + closesrc + Sets the source reference on Chart Studio Cloud for + `close`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + decreasing + :class:`plotly.graph_objects.candlestick.Decreasing` + instance or dict with compatible properties + high + Sets the high values. + highsrc + Sets the source reference on Chart Studio Cloud for + `high`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.candlestick.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `open`, `high`, `low` and `close`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + increasing + :class:`plotly.graph_objects.candlestick.Increasing` + instance or dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.candlestick.Legendgrouptit + le` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.candlestick.Line` instance + or dict with compatible properties + low + Sets the low values. + lowsrc + Sets the source reference on Chart Studio Cloud for + `low`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + open + Sets the open values. + opensrc + Sets the source reference on Chart Studio Cloud for + `open`. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.candlestick.Stream` + instance or dict with compatible properties + text + Sets hover text elements associated with each sample + point. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to this trace's sample points. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + whiskerwidth + Sets the width of the whiskers relative to the box + width. For example, with 1, the whiskers are as wide as + the box(es). + x + Sets the x coordinates. If absent, linear coordinate + will be generated. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + + Returns + ------- + Candlestick + """ + super().__init__("candlestick") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Candlestick +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Candlestick`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("close", arg, close) + self._set_property("closesrc", arg, closesrc) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("decreasing", arg, decreasing) + self._set_property("high", arg, high) + self._set_property("highsrc", arg, highsrc) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("increasing", arg, increasing) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("low", arg, low) + self._set_property("lowsrc", arg, lowsrc) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("open", arg, open) + self._set_property("opensrc", arg, opensrc) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._set_property("whiskerwidth", arg, whiskerwidth) + self._set_property("x", arg, x) + self._set_property("xaxis", arg, xaxis) + self._set_property("xcalendar", arg, xcalendar) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xperiod", arg, xperiod) + self._set_property("xperiod0", arg, xperiod0) + self._set_property("xperiodalignment", arg, xperiodalignment) + self._set_property("xsrc", arg, xsrc) + self._set_property("yaxis", arg, yaxis) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("zorder", arg, zorder) + + self._props["type"] = "candlestick" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_carpet.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_carpet.py new file mode 100644 index 0000000000000000000000000000000000000000..26e6a7a75f4f392b5f031bad0cb1d5702e806ac2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_carpet.py @@ -0,0 +1,1257 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Carpet(_BaseTraceType): + _parent_path_str = "" + _path_str = "carpet" + _valid_props = { + "a", + "a0", + "aaxis", + "asrc", + "b", + "b0", + "baxis", + "bsrc", + "carpet", + "cheaterslope", + "color", + "customdata", + "customdatasrc", + "da", + "db", + "font", + "ids", + "idssrc", + "legend", + "legendgrouptitle", + "legendrank", + "legendwidth", + "meta", + "metasrc", + "name", + "opacity", + "stream", + "type", + "uid", + "uirevision", + "visible", + "x", + "xaxis", + "xsrc", + "y", + "yaxis", + "ysrc", + "zorder", + } + + @property + def a(self): + """ + An array containing values of the first parameter value + + The 'a' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["a"] + + @a.setter + def a(self, val): + self["a"] = val + + @property + def a0(self): + """ + Alternate to `a`. Builds a linear space of a coordinates. Use + with `da` where `a0` is the starting coordinate and `da` the + step. + + The 'a0' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["a0"] + + @a0.setter + def a0(self, val): + self["a0"] = val + + @property + def aaxis(self): + """ + The 'aaxis' property is an instance of Aaxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.carpet.Aaxis` + - A dict of string/value properties that will be passed + to the Aaxis constructor + + Returns + ------- + plotly.graph_objs.carpet.Aaxis + """ + return self["aaxis"] + + @aaxis.setter + def aaxis(self, val): + self["aaxis"] = val + + @property + def asrc(self): + """ + Sets the source reference on Chart Studio Cloud for `a`. + + The 'asrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["asrc"] + + @asrc.setter + def asrc(self, val): + self["asrc"] = val + + @property + def b(self): + """ + A two dimensional array of y coordinates at each carpet point. + + The 'b' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["b"] + + @b.setter + def b(self, val): + self["b"] = val + + @property + def b0(self): + """ + Alternate to `b`. Builds a linear space of a coordinates. Use + with `db` where `b0` is the starting coordinate and `db` the + step. + + The 'b0' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["b0"] + + @b0.setter + def b0(self, val): + self["b0"] = val + + @property + def baxis(self): + """ + The 'baxis' property is an instance of Baxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.carpet.Baxis` + - A dict of string/value properties that will be passed + to the Baxis constructor + + Returns + ------- + plotly.graph_objs.carpet.Baxis + """ + return self["baxis"] + + @baxis.setter + def baxis(self, val): + self["baxis"] = val + + @property + def bsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `b`. + + The 'bsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bsrc"] + + @bsrc.setter + def bsrc(self, val): + self["bsrc"] = val + + @property + def carpet(self): + """ + An identifier for this carpet, so that `scattercarpet` and + `contourcarpet` traces can specify a carpet plot on which they + lie + + The 'carpet' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["carpet"] + + @carpet.setter + def carpet(self, val): + self["carpet"] = val + + @property + def cheaterslope(self): + """ + The shift applied to each successive row of data in creating a + cheater plot. Only used if `x` is been omitted. + + The 'cheaterslope' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cheaterslope"] + + @cheaterslope.setter + def cheaterslope(self, val): + self["cheaterslope"] = val + + @property + def color(self): + """ + Sets default for all colors associated with this axis all at + once: line, font, tick, and grid colors. Grid color is + lightened by blending this with the plot background Individual + pieces can override this. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def da(self): + """ + Sets the a coordinate step. See `a0` for more info. + + The 'da' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["da"] + + @da.setter + def da(self, val): + self["da"] = val + + @property + def db(self): + """ + Sets the b coordinate step. See `b0` for more info. + + The 'db' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["db"] + + @db.setter + def db(self, val): + self["db"] = val + + @property + def font(self): + """ + The default font used for axis & tick labels on this carpet + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.carpet.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.carpet.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.carpet.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.carpet.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.carpet.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.carpet.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + A two dimensional array of x coordinates at each carpet point. + If omitted, the plot is a cheater plot and the xaxis is hidden + by default. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + A two dimensional array of y coordinates at each carpet point. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def zorder(self): + """ + Sets the layer on which this trace is displayed, relative to + other SVG traces on the same subplot. SVG traces with higher + `zorder` appear in front of those with lower `zorder`. + + The 'zorder' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["zorder"] + + @zorder.setter + def zorder(self, val): + self["zorder"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + a + An array containing values of the first parameter value + a0 + Alternate to `a`. Builds a linear space of a + coordinates. Use with `da` where `a0` is the starting + coordinate and `da` the step. + aaxis + :class:`plotly.graph_objects.carpet.Aaxis` instance or + dict with compatible properties + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + b + A two dimensional array of y coordinates at each carpet + point. + b0 + Alternate to `b`. Builds a linear space of a + coordinates. Use with `db` where `b0` is the starting + coordinate and `db` the step. + baxis + :class:`plotly.graph_objects.carpet.Baxis` instance or + dict with compatible properties + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + carpet + An identifier for this carpet, so that `scattercarpet` + and `contourcarpet` traces can specify a carpet plot on + which they lie + cheaterslope + The shift applied to each successive row of data in + creating a cheater plot. Only used if `x` is been + omitted. + color + Sets default for all colors associated with this axis + all at once: line, font, tick, and grid colors. Grid + color is lightened by blending this with the plot + background Individual pieces can override this. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + da + Sets the a coordinate step. See `a0` for more info. + db + Sets the b coordinate step. See `b0` for more info. + font + The default font used for axis & tick labels on this + carpet + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.carpet.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + stream + :class:`plotly.graph_objects.carpet.Stream` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + A two dimensional array of x coordinates at each carpet + point. If omitted, the plot is a cheater plot and the + xaxis is hidden by default. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + A two dimensional array of y coordinates at each carpet + point. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + """ + + def __init__( + self, + arg=None, + a=None, + a0=None, + aaxis=None, + asrc=None, + b=None, + b0=None, + baxis=None, + bsrc=None, + carpet=None, + cheaterslope=None, + color=None, + customdata=None, + customdatasrc=None, + da=None, + db=None, + font=None, + ids=None, + idssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + stream=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xaxis=None, + xsrc=None, + y=None, + yaxis=None, + ysrc=None, + zorder=None, + **kwargs, + ): + """ + Construct a new Carpet object + + The data describing carpet axis layout is set in `y` and + (optionally) also `x`. If only `y` is present, `x` the plot is + interpreted as a cheater plot and is filled in using the `y` + values. `x` and `y` may either be 2D arrays matching with each + dimension matching that of `a` and `b`, or they may be 1D + arrays with total length equal to that of `a` and `b`. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Carpet` + a + An array containing values of the first parameter value + a0 + Alternate to `a`. Builds a linear space of a + coordinates. Use with `da` where `a0` is the starting + coordinate and `da` the step. + aaxis + :class:`plotly.graph_objects.carpet.Aaxis` instance or + dict with compatible properties + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + b + A two dimensional array of y coordinates at each carpet + point. + b0 + Alternate to `b`. Builds a linear space of a + coordinates. Use with `db` where `b0` is the starting + coordinate and `db` the step. + baxis + :class:`plotly.graph_objects.carpet.Baxis` instance or + dict with compatible properties + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + carpet + An identifier for this carpet, so that `scattercarpet` + and `contourcarpet` traces can specify a carpet plot on + which they lie + cheaterslope + The shift applied to each successive row of data in + creating a cheater plot. Only used if `x` is been + omitted. + color + Sets default for all colors associated with this axis + all at once: line, font, tick, and grid colors. Grid + color is lightened by blending this with the plot + background Individual pieces can override this. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + da + Sets the a coordinate step. See `a0` for more info. + db + Sets the b coordinate step. See `b0` for more info. + font + The default font used for axis & tick labels on this + carpet + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.carpet.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + stream + :class:`plotly.graph_objects.carpet.Stream` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + A two dimensional array of x coordinates at each carpet + point. If omitted, the plot is a cheater plot and the + xaxis is hidden by default. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + A two dimensional array of y coordinates at each carpet + point. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + + Returns + ------- + Carpet + """ + super().__init__("carpet") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Carpet +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Carpet`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("a", arg, a) + self._set_property("a0", arg, a0) + self._set_property("aaxis", arg, aaxis) + self._set_property("asrc", arg, asrc) + self._set_property("b", arg, b) + self._set_property("b0", arg, b0) + self._set_property("baxis", arg, baxis) + self._set_property("bsrc", arg, bsrc) + self._set_property("carpet", arg, carpet) + self._set_property("cheaterslope", arg, cheaterslope) + self._set_property("color", arg, color) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("da", arg, da) + self._set_property("db", arg, db) + self._set_property("font", arg, font) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("stream", arg, stream) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("xaxis", arg, xaxis) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("yaxis", arg, yaxis) + self._set_property("ysrc", arg, ysrc) + self._set_property("zorder", arg, zorder) + + self._props["type"] = "carpet" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_choropleth.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_choropleth.py new file mode 100644 index 0000000000000000000000000000000000000000..d4be517e4d36329b21879e8f9f7b551119afa5ea --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_choropleth.py @@ -0,0 +1,1823 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy +import warnings + + +class Choropleth(_BaseTraceType): + _parent_path_str = "" + _path_str = "choropleth" + _valid_props = { + "autocolorscale", + "coloraxis", + "colorbar", + "colorscale", + "customdata", + "customdatasrc", + "featureidkey", + "geo", + "geojson", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "locationmode", + "locations", + "locationssrc", + "marker", + "meta", + "metasrc", + "name", + "reversescale", + "selected", + "selectedpoints", + "showlegend", + "showscale", + "stream", + "text", + "textsrc", + "type", + "uid", + "uirevision", + "unselected", + "visible", + "z", + "zauto", + "zmax", + "zmid", + "zmin", + "zsrc", + } + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.choropleth.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.choropleth.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def featureidkey(self): + """ + Sets the key in GeoJSON features which is used as id to match + the items included in the `locations` array. Only has an effect + when `geojson` is set. Support nested property, for example + "properties.name". + + The 'featureidkey' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["featureidkey"] + + @featureidkey.setter + def featureidkey(self, val): + self["featureidkey"] = val + + @property + def geo(self): + """ + Sets a reference between this trace's geospatial coordinates + and a geographic map. If "geo" (the default value), the + geospatial coordinates refer to `layout.geo`. If "geo2", the + geospatial coordinates refer to `layout.geo2`, and so on. + + The 'geo' property is an identifier of a particular + subplot, of type 'geo', that may be specified as: + - the string 'geo' optionally followed by an integer >= 1 + (e.g. 'geo', 'geo1', 'geo2', 'geo3', etc.) + + Returns + ------- + str + """ + return self["geo"] + + @geo.setter + def geo(self, val): + self["geo"] = val + + @property + def geojson(self): + """ + Sets optional GeoJSON data associated with this trace. If not + given, the features on the base map are used. It can be set as + a valid GeoJSON object or as a URL string. Note that we only + accept GeoJSONs of type "FeatureCollection" or "Feature" with + geometries of type "Polygon" or "MultiPolygon". + + The 'geojson' property accepts values of any type + + Returns + ------- + Any + """ + return self["geojson"] + + @geojson.setter + def geojson(self, val): + self["geojson"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['location', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'location+z') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.choropleth.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.choropleth.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.choropleth.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.choropleth.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def locationmode(self): + """ + The library used by the *country names* `locationmode` option + is changing in an upcoming version. Country names in existing + plots may not work in the new version. Determines the set of + locations used to match entries in `locations` to regions on + the map. Values "ISO-3", "USA-states", *country names* + correspond to features on the base map and value "geojson-id" + corresponds to features from a custom GeoJSON linked to the + `geojson` attribute. + + The 'locationmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['ISO-3', 'USA-states', 'country names', 'geojson-id'] + + Returns + ------- + Any + """ + return self["locationmode"] + + @locationmode.setter + def locationmode(self, val): + self["locationmode"] = val + + @property + def locations(self): + """ + Sets the coordinates via location IDs or names. See + `locationmode` for more info. + + The 'locations' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["locations"] + + @locations.setter + def locations(self, val): + self["locations"] = val + + @property + def locationssrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `locations`. + + The 'locationssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["locationssrc"] + + @locationssrc.setter + def locationssrc(self, val): + self["locationssrc"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.choropleth.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.choropleth.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `zmin` will + correspond to the last color in the array and `zmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.choropleth.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.choropleth.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.choropleth.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.choropleth.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets the text elements associated with each location. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.choropleth.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.choropleth.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def z(self): + """ + Sets the color values. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `z`) or the bounds set in + `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` + are set by the user. + + The 'zauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["zauto"] + + @zauto.setter + def zauto(self, val): + self["zauto"] = val + + @property + def zmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as in `z` and if set, `zmin` must be set as well. + + The 'zmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmax"] + + @zmax.setter + def zmax(self, val): + self["zmax"] = val + + @property + def zmid(self): + """ + Sets the mid-point of the color domain by scaling `zmin` and/or + `zmax` to be equidistant to this point. Value should have the + same units as in `z`. Has no effect when `zauto` is `false`. + + The 'zmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmid"] + + @zmid.setter + def zmid(self, val): + self["zmid"] = val + + @property + def zmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as in `z` and if set, `zmax` must be set as well. + + The 'zmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmin"] + + @zmin.setter + def zmin(self, val): + self["zmin"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.choropleth.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. Only + has an effect when `geojson` is set. Support nested + property, for example "properties.name". + geo + Sets a reference between this trace's geospatial + coordinates and a geographic map. If "geo" (the default + value), the geospatial coordinates refer to + `layout.geo`. If "geo2", the geospatial coordinates + refer to `layout.geo2`, and so on. + geojson + Sets optional GeoJSON data associated with this trace. + If not given, the features on the base map are used. It + can be set as a valid GeoJSON object or as a URL + string. Note that we only accept GeoJSONs of type + "FeatureCollection" or "Feature" with geometries of + type "Polygon" or "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.choropleth.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.choropleth.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + locationmode + The library used by the *country names* `locationmode` + option is changing in an upcoming version. Country + names in existing plots may not work in the new + version. Determines the set of locations used to match + entries in `locations` to regions on the map. Values + "ISO-3", "USA-states", *country names* correspond to + features on the base map and value "geojson-id" + corresponds to features from a custom GeoJSON linked to + the `geojson` attribute. + locations + Sets the coordinates via location IDs or names. See + `locationmode` for more info. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + marker + :class:`plotly.graph_objects.choropleth.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + selected + :class:`plotly.graph_objects.choropleth.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.choropleth.Stream` + instance or dict with compatible properties + text + Sets the text elements associated with each location. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.choropleth.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the color values. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + autocolorscale=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + featureidkey=None, + geo=None, + geojson=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + locationmode=None, + locations=None, + locationssrc=None, + marker=None, + meta=None, + metasrc=None, + name=None, + reversescale=None, + selected=None, + selectedpoints=None, + showlegend=None, + showscale=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Choropleth object + + The data that describes the choropleth value-to-color mapping + is set in `z`. The geographic locations corresponding to each + value in `z` are set in `locations`. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Choropleth` + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.choropleth.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. Only + has an effect when `geojson` is set. Support nested + property, for example "properties.name". + geo + Sets a reference between this trace's geospatial + coordinates and a geographic map. If "geo" (the default + value), the geospatial coordinates refer to + `layout.geo`. If "geo2", the geospatial coordinates + refer to `layout.geo2`, and so on. + geojson + Sets optional GeoJSON data associated with this trace. + If not given, the features on the base map are used. It + can be set as a valid GeoJSON object or as a URL + string. Note that we only accept GeoJSONs of type + "FeatureCollection" or "Feature" with geometries of + type "Polygon" or "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.choropleth.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.choropleth.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + locationmode + The library used by the *country names* `locationmode` + option is changing in an upcoming version. Country + names in existing plots may not work in the new + version. Determines the set of locations used to match + entries in `locations` to regions on the map. Values + "ISO-3", "USA-states", *country names* correspond to + features on the base map and value "geojson-id" + corresponds to features from a custom GeoJSON linked to + the `geojson` attribute. + locations + Sets the coordinates via location IDs or names. See + `locationmode` for more info. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + marker + :class:`plotly.graph_objects.choropleth.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + selected + :class:`plotly.graph_objects.choropleth.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.choropleth.Stream` + instance or dict with compatible properties + text + Sets the text elements associated with each location. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.choropleth.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the color values. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Choropleth + """ + super().__init__("choropleth") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Choropleth +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Choropleth`""") + + if locationmode == "country names" and kwargs.get("_validate"): + warnings.warn( + "The library used by the *country names* `locationmode` option is changing in an upcoming version. " + "Country names in existing plots may not work in the new version. " + "To ensure consistent behavior, consider setting `locationmode` to *ISO-3*.", + DeprecationWarning, + stacklevel=5, + ) + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("featureidkey", arg, featureidkey) + self._set_property("geo", arg, geo) + self._set_property("geojson", arg, geojson) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("locationmode", arg, locationmode) + self._set_property("locations", arg, locations) + self._set_property("locationssrc", arg, locationssrc) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("reversescale", arg, reversescale) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + self._set_property("z", arg, z) + self._set_property("zauto", arg, zauto) + self._set_property("zmax", arg, zmax) + self._set_property("zmid", arg, zmid) + self._set_property("zmin", arg, zmin) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "choropleth" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_choroplethmap.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_choroplethmap.py new file mode 100644 index 0000000000000000000000000000000000000000..eb548811ab49a719b7adf33e28302e3f9a22ee75 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_choroplethmap.py @@ -0,0 +1,1796 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Choroplethmap(_BaseTraceType): + _parent_path_str = "" + _path_str = "choroplethmap" + _valid_props = { + "autocolorscale", + "below", + "coloraxis", + "colorbar", + "colorscale", + "customdata", + "customdatasrc", + "featureidkey", + "geojson", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "locations", + "locationssrc", + "marker", + "meta", + "metasrc", + "name", + "reversescale", + "selected", + "selectedpoints", + "showlegend", + "showscale", + "stream", + "subplot", + "text", + "textsrc", + "type", + "uid", + "uirevision", + "unselected", + "visible", + "z", + "zauto", + "zmax", + "zmid", + "zmin", + "zsrc", + } + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def below(self): + """ + Determines if the choropleth polygons will be inserted before + the layer with the specified ID. By default, choroplethmap + traces are placed above the water layers. If set to '', the + layer will be inserted above every existing layer. + + The 'below' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["below"] + + @below.setter + def below(self, val): + self["below"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmap.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.choroplethmap.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def featureidkey(self): + """ + Sets the key in GeoJSON features which is used as id to match + the items included in the `locations` array. Support nested + property, for example "properties.name". + + The 'featureidkey' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["featureidkey"] + + @featureidkey.setter + def featureidkey(self, val): + self["featureidkey"] = val + + @property + def geojson(self): + """ + Sets the GeoJSON data associated with this trace. It can be set + as a valid GeoJSON object or as a URL string. Note that we only + accept GeoJSONs of type "FeatureCollection" or "Feature" with + geometries of type "Polygon" or "MultiPolygon". + + The 'geojson' property accepts values of any type + + Returns + ------- + Any + """ + return self["geojson"] + + @geojson.setter + def geojson(self, val): + self["geojson"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['location', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'location+z') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmap.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.choroplethmap.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variable + `properties` Anything contained in tag `` is displayed + in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmap.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.choroplethmap.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def locations(self): + """ + Sets which features found in "geojson" to plot using their + feature `id` field. + + The 'locations' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["locations"] + + @locations.setter + def locations(self, val): + self["locations"] = val + + @property + def locationssrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `locations`. + + The 'locationssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["locationssrc"] + + @locationssrc.setter + def locationssrc(self, val): + self["locationssrc"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmap.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.choroplethmap.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `zmin` will + correspond to the last color in the array and `zmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmap.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.choroplethmap.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmap.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.choroplethmap.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def subplot(self): + """ + Sets a reference between this trace's data coordinates and a + map subplot. If "map" (the default value), the data refer to + `layout.map`. If "map2", the data refer to `layout.map2`, and + so on. + + The 'subplot' property is an identifier of a particular + subplot, of type 'map', that may be specified as: + - the string 'map' optionally followed by an integer >= 1 + (e.g. 'map', 'map1', 'map2', 'map3', etc.) + + Returns + ------- + str + """ + return self["subplot"] + + @subplot.setter + def subplot(self, val): + self["subplot"] = val + + @property + def text(self): + """ + Sets the text elements associated with each location. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmap.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.choroplethmap.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def z(self): + """ + Sets the color values. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `z`) or the bounds set in + `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` + are set by the user. + + The 'zauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["zauto"] + + @zauto.setter + def zauto(self, val): + self["zauto"] = val + + @property + def zmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as in `z` and if set, `zmin` must be set as well. + + The 'zmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmax"] + + @zmax.setter + def zmax(self, val): + self["zmax"] = val + + @property + def zmid(self): + """ + Sets the mid-point of the color domain by scaling `zmin` and/or + `zmax` to be equidistant to this point. Value should have the + same units as in `z`. Has no effect when `zauto` is `false`. + + The 'zmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmid"] + + @zmid.setter + def zmid(self, val): + self["zmid"] = val + + @property + def zmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as in `z` and if set, `zmax` must be set as well. + + The 'zmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmin"] + + @zmin.setter + def zmin(self, val): + self["zmin"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the choropleth polygons will be inserted + before the layer with the specified ID. By default, + choroplethmap traces are placed above the water layers. + If set to '', the layer will be inserted above every + existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.choroplethmap.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. + Support nested property, for example "properties.name". + geojson + Sets the GeoJSON data associated with this trace. It + can be set as a valid GeoJSON object or as a URL + string. Note that we only accept GeoJSONs of type + "FeatureCollection" or "Feature" with geometries of + type "Polygon" or "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.choroplethmap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `properties` Anything contained in tag + `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.choroplethmap.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + locations + Sets which features found in "geojson" to plot using + their feature `id` field. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + marker + :class:`plotly.graph_objects.choroplethmap.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + selected + :class:`plotly.graph_objects.choroplethmap.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.choroplethmap.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a map subplot. If "map" (the default value), the + data refer to `layout.map`. If "map2", the data refer + to `layout.map2`, and so on. + text + Sets the text elements associated with each location. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.choroplethmap.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the color values. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + autocolorscale=None, + below=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + featureidkey=None, + geojson=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + locations=None, + locationssrc=None, + marker=None, + meta=None, + metasrc=None, + name=None, + reversescale=None, + selected=None, + selectedpoints=None, + showlegend=None, + showscale=None, + stream=None, + subplot=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Choroplethmap object + + GeoJSON features to be filled are set in `geojson` The data + that describes the choropleth value-to-color mapping is set in + `locations` and `z`. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Choroplethmap` + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the choropleth polygons will be inserted + before the layer with the specified ID. By default, + choroplethmap traces are placed above the water layers. + If set to '', the layer will be inserted above every + existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.choroplethmap.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. + Support nested property, for example "properties.name". + geojson + Sets the GeoJSON data associated with this trace. It + can be set as a valid GeoJSON object or as a URL + string. Note that we only accept GeoJSONs of type + "FeatureCollection" or "Feature" with geometries of + type "Polygon" or "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.choroplethmap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `properties` Anything contained in tag + `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.choroplethmap.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + locations + Sets which features found in "geojson" to plot using + their feature `id` field. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + marker + :class:`plotly.graph_objects.choroplethmap.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + selected + :class:`plotly.graph_objects.choroplethmap.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.choroplethmap.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a map subplot. If "map" (the default value), the + data refer to `layout.map`. If "map2", the data refer + to `layout.map2`, and so on. + text + Sets the text elements associated with each location. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.choroplethmap.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the color values. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Choroplethmap + """ + super().__init__("choroplethmap") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Choroplethmap +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Choroplethmap`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("below", arg, below) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("featureidkey", arg, featureidkey) + self._set_property("geojson", arg, geojson) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("locations", arg, locations) + self._set_property("locationssrc", arg, locationssrc) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("reversescale", arg, reversescale) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("stream", arg, stream) + self._set_property("subplot", arg, subplot) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + self._set_property("z", arg, z) + self._set_property("zauto", arg, zauto) + self._set_property("zmax", arg, zmax) + self._set_property("zmid", arg, zmid) + self._set_property("zmin", arg, zmin) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "choroplethmap" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_choroplethmapbox.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_choroplethmapbox.py new file mode 100644 index 0000000000000000000000000000000000000000..b89f6f022cd4bbbfabbe2cc0078d305934eba54e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_choroplethmapbox.py @@ -0,0 +1,1824 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy +import warnings + + +class Choroplethmapbox(_BaseTraceType): + _parent_path_str = "" + _path_str = "choroplethmapbox" + _valid_props = { + "autocolorscale", + "below", + "coloraxis", + "colorbar", + "colorscale", + "customdata", + "customdatasrc", + "featureidkey", + "geojson", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "locations", + "locationssrc", + "marker", + "meta", + "metasrc", + "name", + "reversescale", + "selected", + "selectedpoints", + "showlegend", + "showscale", + "stream", + "subplot", + "text", + "textsrc", + "type", + "uid", + "uirevision", + "unselected", + "visible", + "z", + "zauto", + "zmax", + "zmid", + "zmin", + "zsrc", + } + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def below(self): + """ + Determines if the choropleth polygons will be inserted before + the layer with the specified ID. By default, choroplethmapbox + traces are placed above the water layers. If set to '', the + layer will be inserted above every existing layer. + + The 'below' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["below"] + + @below.setter + def below(self, val): + self["below"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmapbox.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.choroplethmapbox.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def featureidkey(self): + """ + Sets the key in GeoJSON features which is used as id to match + the items included in the `locations` array. Support nested + property, for example "properties.name". + + The 'featureidkey' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["featureidkey"] + + @featureidkey.setter + def featureidkey(self, val): + self["featureidkey"] = val + + @property + def geojson(self): + """ + Sets the GeoJSON data associated with this trace. It can be set + as a valid GeoJSON object or as a URL string. Note that we only + accept GeoJSONs of type "FeatureCollection" or "Feature" with + geometries of type "Polygon" or "MultiPolygon". + + The 'geojson' property accepts values of any type + + Returns + ------- + Any + """ + return self["geojson"] + + @geojson.setter + def geojson(self, val): + self["geojson"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['location', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'location+z') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmapbox.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.choroplethmapbox.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variable + `properties` Anything contained in tag `` is displayed + in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmapbox.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.choroplethmapbox.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def locations(self): + """ + Sets which features found in "geojson" to plot using their + feature `id` field. + + The 'locations' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["locations"] + + @locations.setter + def locations(self, val): + self["locations"] = val + + @property + def locationssrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `locations`. + + The 'locationssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["locationssrc"] + + @locationssrc.setter + def locationssrc(self, val): + self["locationssrc"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmapbox.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.choroplethmapbox.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `zmin` will + correspond to the last color in the array and `zmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmapbox.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.choroplethmapbox.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmapbox.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.choroplethmapbox.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def subplot(self): + """ + mapbox subplots and traces are deprecated! Please consider + switching to `map` subplots and traces. Learn more at: + https://plotly.com/python/maplibre-migration/ as well as + https://plotly.com/javascript/maplibre-migration/ Sets a + reference between this trace's data coordinates and a mapbox + subplot. If "mapbox" (the default value), the data refer to + `layout.mapbox`. If "mapbox2", the data refer to + `layout.mapbox2`, and so on. + + The 'subplot' property is an identifier of a particular + subplot, of type 'mapbox', that may be specified as: + - the string 'mapbox' optionally followed by an integer >= 1 + (e.g. 'mapbox', 'mapbox1', 'mapbox2', 'mapbox3', etc.) + + Returns + ------- + str + """ + return self["subplot"] + + @subplot.setter + def subplot(self, val): + self["subplot"] = val + + @property + def text(self): + """ + Sets the text elements associated with each location. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmapbox.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.choroplethmapbox.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def z(self): + """ + Sets the color values. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `z`) or the bounds set in + `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` + are set by the user. + + The 'zauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["zauto"] + + @zauto.setter + def zauto(self, val): + self["zauto"] = val + + @property + def zmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as in `z` and if set, `zmin` must be set as well. + + The 'zmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmax"] + + @zmax.setter + def zmax(self, val): + self["zmax"] = val + + @property + def zmid(self): + """ + Sets the mid-point of the color domain by scaling `zmin` and/or + `zmax` to be equidistant to this point. Value should have the + same units as in `z`. Has no effect when `zauto` is `false`. + + The 'zmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmid"] + + @zmid.setter + def zmid(self, val): + self["zmid"] = val + + @property + def zmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as in `z` and if set, `zmax` must be set as well. + + The 'zmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmin"] + + @zmin.setter + def zmin(self, val): + self["zmin"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the choropleth polygons will be inserted + before the layer with the specified ID. By default, + choroplethmapbox traces are placed above the water + layers. If set to '', the layer will be inserted above + every existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.choroplethmapbox.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. + Support nested property, for example "properties.name". + geojson + Sets the GeoJSON data associated with this trace. It + can be set as a valid GeoJSON object or as a URL + string. Note that we only accept GeoJSONs of type + "FeatureCollection" or "Feature" with geometries of + type "Polygon" or "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.choroplethmapbox.Hoverlabe + l` instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `properties` Anything contained in tag + `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.choroplethmapbox.Legendgro + uptitle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + locations + Sets which features found in "geojson" to plot using + their feature `id` field. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + marker + :class:`plotly.graph_objects.choroplethmapbox.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + selected + :class:`plotly.graph_objects.choroplethmapbox.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.choroplethmapbox.Stream` + instance or dict with compatible properties + subplot + mapbox subplots and traces are deprecated! Please + consider switching to `map` subplots and traces. Learn + more at: https://plotly.com/python/maplibre-migration/ + as well as https://plotly.com/javascript/maplibre- + migration/ Sets a reference between this trace's data + coordinates and a mapbox subplot. If "mapbox" (the + default value), the data refer to `layout.mapbox`. If + "mapbox2", the data refer to `layout.mapbox2`, and so + on. + text + Sets the text elements associated with each location. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.choroplethmapbox.Unselecte + d` instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the color values. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + autocolorscale=None, + below=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + featureidkey=None, + geojson=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + locations=None, + locationssrc=None, + marker=None, + meta=None, + metasrc=None, + name=None, + reversescale=None, + selected=None, + selectedpoints=None, + showlegend=None, + showscale=None, + stream=None, + subplot=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Choroplethmapbox object + + "choroplethmapbox" trace is deprecated! Please consider + switching to the "choroplethmap" trace type and `map` subplots. + Learn more at: https://plotly.com/python/maplibre-migration/ as + well as https://plotly.com/javascript/maplibre-migration/ + GeoJSON features to be filled are set in `geojson` The data + that describes the choropleth value-to-color mapping is set in + `locations` and `z`. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.Choroplethmapbox` + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the choropleth polygons will be inserted + before the layer with the specified ID. By default, + choroplethmapbox traces are placed above the water + layers. If set to '', the layer will be inserted above + every existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.choroplethmapbox.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. + Support nested property, for example "properties.name". + geojson + Sets the GeoJSON data associated with this trace. It + can be set as a valid GeoJSON object or as a URL + string. Note that we only accept GeoJSONs of type + "FeatureCollection" or "Feature" with geometries of + type "Polygon" or "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.choroplethmapbox.Hoverlabe + l` instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `properties` Anything contained in tag + `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.choroplethmapbox.Legendgro + uptitle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + locations + Sets which features found in "geojson" to plot using + their feature `id` field. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + marker + :class:`plotly.graph_objects.choroplethmapbox.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + selected + :class:`plotly.graph_objects.choroplethmapbox.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.choroplethmapbox.Stream` + instance or dict with compatible properties + subplot + mapbox subplots and traces are deprecated! Please + consider switching to `map` subplots and traces. Learn + more at: https://plotly.com/python/maplibre-migration/ + as well as https://plotly.com/javascript/maplibre- + migration/ Sets a reference between this trace's data + coordinates and a mapbox subplot. If "mapbox" (the + default value), the data refer to `layout.mapbox`. If + "mapbox2", the data refer to `layout.mapbox2`, and so + on. + text + Sets the text elements associated with each location. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.choroplethmapbox.Unselecte + d` instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the color values. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Choroplethmapbox + """ + super().__init__("choroplethmapbox") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Choroplethmapbox +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Choroplethmapbox`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("below", arg, below) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("featureidkey", arg, featureidkey) + self._set_property("geojson", arg, geojson) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("locations", arg, locations) + self._set_property("locationssrc", arg, locationssrc) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("reversescale", arg, reversescale) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("stream", arg, stream) + self._set_property("subplot", arg, subplot) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + self._set_property("z", arg, z) + self._set_property("zauto", arg, zauto) + self._set_property("zmax", arg, zmax) + self._set_property("zmid", arg, zmid) + self._set_property("zmin", arg, zmin) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "choroplethmapbox" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False + + warnings.warn( + "*choroplethmapbox* is deprecated!" + + " Use *choroplethmap* instead." + + " Learn more at: https://plotly.com/python/mapbox-to-maplibre/", + stacklevel=2, + category=DeprecationWarning, + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_cone.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_cone.py new file mode 100644 index 0000000000000000000000000000000000000000..29de7ce02f997c8c8b81bad2626e3f1c34375a26 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_cone.py @@ -0,0 +1,2309 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Cone(_BaseTraceType): + _parent_path_str = "" + _path_str = "cone" + _valid_props = { + "anchor", + "autocolorscale", + "cauto", + "cmax", + "cmid", + "cmin", + "coloraxis", + "colorbar", + "colorscale", + "customdata", + "customdatasrc", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "lighting", + "lightposition", + "meta", + "metasrc", + "name", + "opacity", + "reversescale", + "scene", + "showlegend", + "showscale", + "sizemode", + "sizeref", + "stream", + "text", + "textsrc", + "type", + "u", + "uhoverformat", + "uid", + "uirevision", + "usrc", + "v", + "vhoverformat", + "visible", + "vsrc", + "w", + "whoverformat", + "wsrc", + "x", + "xhoverformat", + "xsrc", + "y", + "yhoverformat", + "ysrc", + "z", + "zhoverformat", + "zsrc", + } + + @property + def anchor(self): + """ + Sets the cones' anchor with respect to their x/y/z positions. + Note that "cm" denote the cone's center of mass which + corresponds to 1/4 from the tail to tip. + + The 'anchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['tip', 'tail', 'cm', 'center'] + + Returns + ------- + Any + """ + return self["anchor"] + + @anchor.setter + def anchor(self, val): + self["anchor"] = val + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def cauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here u/v/w norm) or the bounds set + in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` + are set by the user. + + The 'cauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cauto"] + + @cauto.setter + def cauto(self, val): + self["cauto"] = val + + @property + def cmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as u/v/w norm and if set, `cmin` must be set as + well. + + The 'cmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmax"] + + @cmax.setter + def cmax(self, val): + self["cmax"] = val + + @property + def cmid(self): + """ + Sets the mid-point of the color domain by scaling `cmin` and/or + `cmax` to be equidistant to this point. Value should have the + same units as u/v/w norm. Has no effect when `cauto` is + `false`. + + The 'cmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmid"] + + @cmid.setter + def cmid(self, val): + self["cmid"] = val + + @property + def cmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as u/v/w norm and if set, `cmax` must be set as + well. + + The 'cmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmin"] + + @cmin.setter + def cmin(self, val): + self["cmin"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.cone.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.cone.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'u', 'v', 'w', 'norm', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.cone.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.cone.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variable `norm` + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.cone.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.cone.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def lighting(self): + """ + The 'lighting' property is an instance of Lighting + that may be specified as: + - An instance of :class:`plotly.graph_objs.cone.Lighting` + - A dict of string/value properties that will be passed + to the Lighting constructor + + Returns + ------- + plotly.graph_objs.cone.Lighting + """ + return self["lighting"] + + @lighting.setter + def lighting(self, val): + self["lighting"] = val + + @property + def lightposition(self): + """ + The 'lightposition' property is an instance of Lightposition + that may be specified as: + - An instance of :class:`plotly.graph_objs.cone.Lightposition` + - A dict of string/value properties that will be passed + to the Lightposition constructor + + Returns + ------- + plotly.graph_objs.cone.Lightposition + """ + return self["lightposition"] + + @lightposition.setter + def lightposition(self, val): + self["lightposition"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the surface. Please note that in the case + of using high `opacity` values for example a value greater than + or equal to 0.5 on two surfaces (and 0.25 with four surfaces), + an overlay of multiple transparent surfaces may not perfectly + be sorted in depth by the webgl API. This behavior may be + improved in the near future and is subject to change. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `cmin` will + correspond to the last color in the array and `cmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def scene(self): + """ + Sets a reference between this trace's 3D coordinate system and + a 3D scene. If "scene" (the default value), the (x,y,z) + coordinates refer to `layout.scene`. If "scene2", the (x,y,z) + coordinates refer to `layout.scene2`, and so on. + + The 'scene' property is an identifier of a particular + subplot, of type 'scene', that may be specified as: + - the string 'scene' optionally followed by an integer >= 1 + (e.g. 'scene', 'scene1', 'scene2', 'scene3', etc.) + + Returns + ------- + str + """ + return self["scene"] + + @scene.setter + def scene(self, val): + self["scene"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def sizemode(self): + """ + Determines whether `sizeref` is set as a "scaled" (i.e + unitless) scalar (normalized by the max u/v/w norm in the + vector field) or as "absolute" value (in the same units as the + vector field). To display sizes in actual vector length use + "raw". + + The 'sizemode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['scaled', 'absolute', 'raw'] + + Returns + ------- + Any + """ + return self["sizemode"] + + @sizemode.setter + def sizemode(self, val): + self["sizemode"] = val + + @property + def sizeref(self): + """ + Adjusts the cone size scaling. The size of the cones is + determined by their u/v/w norm multiplied a factor and + `sizeref`. This factor (computed internally) corresponds to the + minimum "time" to travel across two successive x/y/z positions + at the average velocity of those two successive positions. All + cones in a given trace use the same factor. With `sizemode` set + to "raw", its default value is 1. With `sizemode` set to + "scaled", `sizeref` is unitless, its default value is 0.5. With + `sizemode` set to "absolute", `sizeref` has the same units as + the u/v/w vector field, its the default value is half the + sample's maximum vector norm. + + The 'sizeref' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["sizeref"] + + @sizeref.setter + def sizeref(self, val): + self["sizeref"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.cone.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.cone.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets the text elements associated with the cones. If trace + `hoverinfo` contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def u(self): + """ + Sets the x components of the vector field. + + The 'u' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["u"] + + @u.setter + def u(self, val): + self["u"] = val + + @property + def uhoverformat(self): + """ + Sets the hover text formatting rulefor `u` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format.By + default the values are formatted using generic number format. + + The 'uhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uhoverformat"] + + @uhoverformat.setter + def uhoverformat(self, val): + self["uhoverformat"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def usrc(self): + """ + Sets the source reference on Chart Studio Cloud for `u`. + + The 'usrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["usrc"] + + @usrc.setter + def usrc(self, val): + self["usrc"] = val + + @property + def v(self): + """ + Sets the y components of the vector field. + + The 'v' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["v"] + + @v.setter + def v(self, val): + self["v"] = val + + @property + def vhoverformat(self): + """ + Sets the hover text formatting rulefor `v` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format.By + default the values are formatted using generic number format. + + The 'vhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["vhoverformat"] + + @vhoverformat.setter + def vhoverformat(self, val): + self["vhoverformat"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def vsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `v`. + + The 'vsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["vsrc"] + + @vsrc.setter + def vsrc(self, val): + self["vsrc"] = val + + @property + def w(self): + """ + Sets the z components of the vector field. + + The 'w' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["w"] + + @w.setter + def w(self, val): + self["w"] = val + + @property + def whoverformat(self): + """ + Sets the hover text formatting rulefor `w` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format.By + default the values are formatted using generic number format. + + The 'whoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["whoverformat"] + + @whoverformat.setter + def whoverformat(self, val): + self["whoverformat"] = val + + @property + def wsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `w`. + + The 'wsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["wsrc"] + + @wsrc.setter + def wsrc(self, val): + self["wsrc"] = val + + @property + def x(self): + """ + Sets the x coordinates of the vector field and of the displayed + cones. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the y coordinates of the vector field and of the displayed + cones. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def z(self): + """ + Sets the z coordinates of the vector field and of the displayed + cones. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zhoverformat(self): + """ + Sets the hover text formatting rulefor `z` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `zaxis.hoverformat`. + + The 'zhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["zhoverformat"] + + @zhoverformat.setter + def zhoverformat(self, val): + self["zhoverformat"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + anchor + Sets the cones' anchor with respect to their x/y/z + positions. Note that "cm" denote the cone's center of + mass which corresponds to 1/4 from the tail to tip. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here u/v/w norm) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmin` + must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as u/v/w norm. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmax` + must be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.cone.ColorBar` instance or + dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.cone.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `norm` Anything contained in tag `` + is displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.cone.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.cone.Lighting` instance or + dict with compatible properties + lightposition + :class:`plotly.graph_objects.cone.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + sizemode + Determines whether `sizeref` is set as a "scaled" (i.e + unitless) scalar (normalized by the max u/v/w norm in + the vector field) or as "absolute" value (in the same + units as the vector field). To display sizes in actual + vector length use "raw". + sizeref + Adjusts the cone size scaling. The size of the cones is + determined by their u/v/w norm multiplied a factor and + `sizeref`. This factor (computed internally) + corresponds to the minimum "time" to travel across two + successive x/y/z positions at the average velocity of + those two successive positions. All cones in a given + trace use the same factor. With `sizemode` set to + "raw", its default value is 1. With `sizemode` set to + "scaled", `sizeref` is unitless, its default value is + 0.5. With `sizemode` set to "absolute", `sizeref` has + the same units as the u/v/w vector field, its the + default value is half the sample's maximum vector norm. + stream + :class:`plotly.graph_objects.cone.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with the cones. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + u + Sets the x components of the vector field. + uhoverformat + Sets the hover text formatting rulefor `u` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + usrc + Sets the source reference on Chart Studio Cloud for + `u`. + v + Sets the y components of the vector field. + vhoverformat + Sets the hover text formatting rulefor `v` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + vsrc + Sets the source reference on Chart Studio Cloud for + `v`. + w + Sets the z components of the vector field. + whoverformat + Sets the hover text formatting rulefor `w` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + wsrc + Sets the source reference on Chart Studio Cloud for + `w`. + x + Sets the x coordinates of the vector field and of the + displayed cones. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates of the vector field and of the + displayed cones. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates of the vector field and of the + displayed cones. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + anchor=None, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + sizemode=None, + sizeref=None, + stream=None, + text=None, + textsrc=None, + u=None, + uhoverformat=None, + uid=None, + uirevision=None, + usrc=None, + v=None, + vhoverformat=None, + visible=None, + vsrc=None, + w=None, + whoverformat=None, + wsrc=None, + x=None, + xhoverformat=None, + xsrc=None, + y=None, + yhoverformat=None, + ysrc=None, + z=None, + zhoverformat=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Cone object + + Use cone traces to visualize vector fields. Specify a vector + field using 6 1D arrays, 3 position arrays `x`, `y` and `z` and + 3 vector component arrays `u`, `v`, `w`. The cones are drawn + exactly at the positions given by `x`, `y` and `z`. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Cone` + anchor + Sets the cones' anchor with respect to their x/y/z + positions. Note that "cm" denote the cone's center of + mass which corresponds to 1/4 from the tail to tip. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here u/v/w norm) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmin` + must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as u/v/w norm. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmax` + must be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.cone.ColorBar` instance or + dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.cone.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `norm` Anything contained in tag `` + is displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.cone.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.cone.Lighting` instance or + dict with compatible properties + lightposition + :class:`plotly.graph_objects.cone.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + sizemode + Determines whether `sizeref` is set as a "scaled" (i.e + unitless) scalar (normalized by the max u/v/w norm in + the vector field) or as "absolute" value (in the same + units as the vector field). To display sizes in actual + vector length use "raw". + sizeref + Adjusts the cone size scaling. The size of the cones is + determined by their u/v/w norm multiplied a factor and + `sizeref`. This factor (computed internally) + corresponds to the minimum "time" to travel across two + successive x/y/z positions at the average velocity of + those two successive positions. All cones in a given + trace use the same factor. With `sizemode` set to + "raw", its default value is 1. With `sizemode` set to + "scaled", `sizeref` is unitless, its default value is + 0.5. With `sizemode` set to "absolute", `sizeref` has + the same units as the u/v/w vector field, its the + default value is half the sample's maximum vector norm. + stream + :class:`plotly.graph_objects.cone.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with the cones. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + u + Sets the x components of the vector field. + uhoverformat + Sets the hover text formatting rulefor `u` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + usrc + Sets the source reference on Chart Studio Cloud for + `u`. + v + Sets the y components of the vector field. + vhoverformat + Sets the hover text formatting rulefor `v` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + vsrc + Sets the source reference on Chart Studio Cloud for + `v`. + w + Sets the z components of the vector field. + whoverformat + Sets the hover text formatting rulefor `w` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + wsrc + Sets the source reference on Chart Studio Cloud for + `w`. + x + Sets the x coordinates of the vector field and of the + displayed cones. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates of the vector field and of the + displayed cones. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates of the vector field and of the + displayed cones. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Cone + """ + super().__init__("cone") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Cone +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Cone`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("anchor", arg, anchor) + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("cauto", arg, cauto) + self._set_property("cmax", arg, cmax) + self._set_property("cmid", arg, cmid) + self._set_property("cmin", arg, cmin) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("lighting", arg, lighting) + self._set_property("lightposition", arg, lightposition) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("reversescale", arg, reversescale) + self._set_property("scene", arg, scene) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("sizemode", arg, sizemode) + self._set_property("sizeref", arg, sizeref) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("u", arg, u) + self._set_property("uhoverformat", arg, uhoverformat) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("usrc", arg, usrc) + self._set_property("v", arg, v) + self._set_property("vhoverformat", arg, vhoverformat) + self._set_property("visible", arg, visible) + self._set_property("vsrc", arg, vsrc) + self._set_property("w", arg, w) + self._set_property("whoverformat", arg, whoverformat) + self._set_property("wsrc", arg, wsrc) + self._set_property("x", arg, x) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("ysrc", arg, ysrc) + self._set_property("z", arg, z) + self._set_property("zhoverformat", arg, zhoverformat) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "cone" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_contour.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_contour.py new file mode 100644 index 0000000000000000000000000000000000000000..c2c9f0dcc00fa63a3c939ad87a327c00a342429c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_contour.py @@ -0,0 +1,2711 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Contour(_BaseTraceType): + _parent_path_str = "" + _path_str = "contour" + _valid_props = { + "autocolorscale", + "autocontour", + "coloraxis", + "colorbar", + "colorscale", + "connectgaps", + "contours", + "customdata", + "customdatasrc", + "dx", + "dy", + "fillcolor", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hoverongaps", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "meta", + "metasrc", + "name", + "ncontours", + "opacity", + "reversescale", + "showlegend", + "showscale", + "stream", + "text", + "textfont", + "textsrc", + "texttemplate", + "texttemplatefallback", + "transpose", + "type", + "uid", + "uirevision", + "visible", + "x", + "x0", + "xaxis", + "xcalendar", + "xhoverformat", + "xperiod", + "xperiod0", + "xperiodalignment", + "xsrc", + "xtype", + "y", + "y0", + "yaxis", + "ycalendar", + "yhoverformat", + "yperiod", + "yperiod0", + "yperiodalignment", + "ysrc", + "ytype", + "z", + "zauto", + "zhoverformat", + "zmax", + "zmid", + "zmin", + "zorder", + "zsrc", + } + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def autocontour(self): + """ + Determines whether or not the contour level attributes are + picked by an algorithm. If True, the number of contour levels + can be set in `ncontours`. If False, set the contour level + attributes in `contours`. + + The 'autocontour' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocontour"] + + @autocontour.setter + def autocontour(self, val): + self["autocontour"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.contour.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.contour.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def connectgaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the `z` data are filled in. It is defaulted to true if `z` + is a one dimensional array otherwise it is defaulted to false. + + The 'connectgaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["connectgaps"] + + @connectgaps.setter + def connectgaps(self, val): + self["connectgaps"] = val + + @property + def contours(self): + """ + The 'contours' property is an instance of Contours + that may be specified as: + - An instance of :class:`plotly.graph_objs.contour.Contours` + - A dict of string/value properties that will be passed + to the Contours constructor + + Returns + ------- + plotly.graph_objs.contour.Contours + """ + return self["contours"] + + @contours.setter + def contours(self, val): + self["contours"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def dx(self): + """ + Sets the x coordinate step. See `x0` for more info. + + The 'dx' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dx"] + + @dx.setter + def dx(self, val): + self["dx"] = val + + @property + def dy(self): + """ + Sets the y coordinate step. See `y0` for more info. + + The 'dy' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dy"] + + @dy.setter + def dy(self, val): + self["dy"] = val + + @property + def fillcolor(self): + """ + Sets the fill color if `contours.type` is "constraint". + Defaults to a half-transparent variant of the line color, + marker color, or marker line color, whichever is available. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A number that will be interpreted as a color + according to contour.colorscale + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.contour.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.contour.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hoverongaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the `z` data have hover labels associated with them. + + The 'hoverongaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["hoverongaps"] + + @hoverongaps.setter + def hoverongaps(self, val): + self["hoverongaps"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.contour.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.contour.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.contour.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.contour.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def ncontours(self): + """ + Sets the maximum number of contour levels. The actual number of + contours will be chosen automatically to be less than or equal + to the value of `ncontours`. Has an effect only if + `autocontour` is True or if `contours.size` is missing. + + The 'ncontours' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 9223372036854775807] + + Returns + ------- + int + """ + return self["ncontours"] + + @ncontours.setter + def ncontours(self, val): + self["ncontours"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `zmin` will + correspond to the last color in the array and `zmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.contour.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.contour.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets the text elements associated with each z value. + + The 'text' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + For this trace it only has an effect if `coloring` is set to + "heatmap". Sets the text font. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.contour.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.contour.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + For this trace it only has an effect if `coloring` is set to + "heatmap". Template string used for rendering the information + text that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, for + example "y: %{y}". Numbers are formatted using d3-format's + syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `x`, `y`, `z` and `text`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def transpose(self): + """ + Transposes the z data. + + The 'transpose' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["transpose"] + + @transpose.setter + def transpose(self, val): + self["transpose"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the x coordinates. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def x0(self): + """ + Alternate to `x`. Builds a linear space of x coordinates. Use + with `dx` where `x0` is the starting coordinate and `dx` the + step. + + The 'x0' property accepts values of any type + + Returns + ------- + Any + """ + return self["x0"] + + @x0.setter + def x0(self, val): + self["x0"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def xcalendar(self): + """ + Sets the calendar system to use with `x` date data. + + The 'xcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["xcalendar"] + + @xcalendar.setter + def xcalendar(self, val): + self["xcalendar"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the x axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'xperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod"] + + @xperiod.setter + def xperiod(self, val): + self["xperiod"] = val + + @property + def xperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the x0 + axis. When `x0period` is round number of weeks, the `x0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'xperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod0"] + + @xperiod0.setter + def xperiod0(self, val): + self["xperiod0"] = val + + @property + def xperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + + The 'xperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["xperiodalignment"] + + @xperiodalignment.setter + def xperiodalignment(self, val): + self["xperiodalignment"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def xtype(self): + """ + If "array", the heatmap's x coordinates are given by "x" (the + default behavior when `x` is provided). If "scaled", the + heatmap's x coordinates are given by "x0" and "dx" (the default + behavior when `x` is not provided). + + The 'xtype' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['array', 'scaled'] + + Returns + ------- + Any + """ + return self["xtype"] + + @xtype.setter + def xtype(self, val): + self["xtype"] = val + + @property + def y(self): + """ + Sets the y coordinates. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def y0(self): + """ + Alternate to `y`. Builds a linear space of y coordinates. Use + with `dy` where `y0` is the starting coordinate and `dy` the + step. + + The 'y0' property accepts values of any type + + Returns + ------- + Any + """ + return self["y0"] + + @y0.setter + def y0(self, val): + self["y0"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def ycalendar(self): + """ + Sets the calendar system to use with `y` date data. + + The 'ycalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["ycalendar"] + + @ycalendar.setter + def ycalendar(self, val): + self["ycalendar"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def yperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the y axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'yperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod"] + + @yperiod.setter + def yperiod(self, val): + self["yperiod"] = val + + @property + def yperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the y0 + axis. When `y0period` is round number of weeks, the `y0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'yperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod0"] + + @yperiod0.setter + def yperiod0(self, val): + self["yperiod0"] = val + + @property + def yperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + + The 'yperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["yperiodalignment"] + + @yperiodalignment.setter + def yperiodalignment(self, val): + self["yperiodalignment"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def ytype(self): + """ + If "array", the heatmap's y coordinates are given by "y" (the + default behavior when `y` is provided) If "scaled", the + heatmap's y coordinates are given by "y0" and "dy" (the default + behavior when `y` is not provided) + + The 'ytype' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['array', 'scaled'] + + Returns + ------- + Any + """ + return self["ytype"] + + @ytype.setter + def ytype(self, val): + self["ytype"] = val + + @property + def z(self): + """ + Sets the z data. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `z`) or the bounds set in + `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` + are set by the user. + + The 'zauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["zauto"] + + @zauto.setter + def zauto(self, val): + self["zauto"] = val + + @property + def zhoverformat(self): + """ + Sets the hover text formatting rulefor `z` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format.By + default the values are formatted using generic number format. + + The 'zhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["zhoverformat"] + + @zhoverformat.setter + def zhoverformat(self, val): + self["zhoverformat"] = val + + @property + def zmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as in `z` and if set, `zmin` must be set as well. + + The 'zmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmax"] + + @zmax.setter + def zmax(self, val): + self["zmax"] = val + + @property + def zmid(self): + """ + Sets the mid-point of the color domain by scaling `zmin` and/or + `zmax` to be equidistant to this point. Value should have the + same units as in `z`. Has no effect when `zauto` is `false`. + + The 'zmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmid"] + + @zmid.setter + def zmid(self, val): + self["zmid"] = val + + @property + def zmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as in `z` and if set, `zmax` must be set as well. + + The 'zmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmin"] + + @zmin.setter + def zmin(self, val): + self["zmin"] = val + + @property + def zorder(self): + """ + Sets the layer on which this trace is displayed, relative to + other SVG traces on the same subplot. SVG traces with higher + `zorder` appear in front of those with lower `zorder`. + + The 'zorder' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["zorder"] + + @zorder.setter + def zorder(self, val): + self["zorder"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + autocontour + Determines whether or not the contour level attributes + are picked by an algorithm. If True, the number of + contour levels can be set in `ncontours`. If False, set + the contour level attributes in `contours`. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.contour.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data are filled in. It is defaulted + to true if `z` is a one dimensional array otherwise it + is defaulted to false. + contours + :class:`plotly.graph_objects.contour.Contours` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + fillcolor + Sets the fill color if `contours.type` is "constraint". + Defaults to a half-transparent variant of the line + color, marker color, or marker line color, whichever is + available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.contour.Hoverlabel` + instance or dict with compatible properties + hoverongaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data have hover labels associated + with them. + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.contour.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.contour.Line` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + ncontours + Sets the maximum number of contour levels. The actual + number of contours will be chosen automatically to be + less than or equal to the value of `ncontours`. Has an + effect only if `autocontour` is True or if + `contours.size` is missing. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.contour.Stream` instance + or dict with compatible properties + text + Sets the text elements associated with each z value. + textfont + For this trace it only has an effect if `coloring` is + set to "heatmap". Sets the text font. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + For this trace it only has an effect if `coloring` is + set to "heatmap". Template string used for rendering + the information text that appears on points. Note that + this will override `textinfo`. Variables are inserted + using %{variable}, for example "y: %{y}". Numbers are + formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `x`, `y`, `z` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + transpose + Transposes the z data. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + xtype + If "array", the heatmap's x coordinates are given by + "x" (the default behavior when `x` is provided). If + "scaled", the heatmap's x coordinates are given by "x0" + and "dx" (the default behavior when `x` is not + provided). + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + ytype + If "array", the heatmap's y coordinates are given by + "y" (the default behavior when `y` is provided) If + "scaled", the heatmap's y coordinates are given by "y0" + and "dy" (the default behavior when `y` is not + provided) + z + Sets the z data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + autocolorscale=None, + autocontour=None, + coloraxis=None, + colorbar=None, + colorscale=None, + connectgaps=None, + contours=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoverongaps=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + meta=None, + metasrc=None, + name=None, + ncontours=None, + opacity=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + text=None, + textfont=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + transpose=None, + uid=None, + uirevision=None, + visible=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + xtype=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + ytype=None, + z=None, + zauto=None, + zhoverformat=None, + zmax=None, + zmid=None, + zmin=None, + zorder=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Contour object + + The data from which contour lines are computed is set in `z`. + Data in `z` must be a 2D list of numbers. Say that `z` has N + rows and M columns, then by default, these N rows correspond to + N y coordinates (set in `y` or auto-generated) and the M + columns correspond to M x coordinates (set in `x` or auto- + generated). By setting `transpose` to True, the above behavior + is flipped. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Contour` + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + autocontour + Determines whether or not the contour level attributes + are picked by an algorithm. If True, the number of + contour levels can be set in `ncontours`. If False, set + the contour level attributes in `contours`. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.contour.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data are filled in. It is defaulted + to true if `z` is a one dimensional array otherwise it + is defaulted to false. + contours + :class:`plotly.graph_objects.contour.Contours` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + fillcolor + Sets the fill color if `contours.type` is "constraint". + Defaults to a half-transparent variant of the line + color, marker color, or marker line color, whichever is + available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.contour.Hoverlabel` + instance or dict with compatible properties + hoverongaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data have hover labels associated + with them. + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.contour.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.contour.Line` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + ncontours + Sets the maximum number of contour levels. The actual + number of contours will be chosen automatically to be + less than or equal to the value of `ncontours`. Has an + effect only if `autocontour` is True or if + `contours.size` is missing. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.contour.Stream` instance + or dict with compatible properties + text + Sets the text elements associated with each z value. + textfont + For this trace it only has an effect if `coloring` is + set to "heatmap". Sets the text font. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + For this trace it only has an effect if `coloring` is + set to "heatmap". Template string used for rendering + the information text that appears on points. Note that + this will override `textinfo`. Variables are inserted + using %{variable}, for example "y: %{y}". Numbers are + formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `x`, `y`, `z` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + transpose + Transposes the z data. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + xtype + If "array", the heatmap's x coordinates are given by + "x" (the default behavior when `x` is provided). If + "scaled", the heatmap's x coordinates are given by "x0" + and "dx" (the default behavior when `x` is not + provided). + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + ytype + If "array", the heatmap's y coordinates are given by + "y" (the default behavior when `y` is provided) If + "scaled", the heatmap's y coordinates are given by "y0" + and "dy" (the default behavior when `y` is not + provided) + z + Sets the z data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Contour + """ + super().__init__("contour") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Contour +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Contour`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("autocontour", arg, autocontour) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("connectgaps", arg, connectgaps) + self._set_property("contours", arg, contours) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("dx", arg, dx) + self._set_property("dy", arg, dy) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hoverongaps", arg, hoverongaps) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("ncontours", arg, ncontours) + self._set_property("opacity", arg, opacity) + self._set_property("reversescale", arg, reversescale) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("transpose", arg, transpose) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("x0", arg, x0) + self._set_property("xaxis", arg, xaxis) + self._set_property("xcalendar", arg, xcalendar) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xperiod", arg, xperiod) + self._set_property("xperiod0", arg, xperiod0) + self._set_property("xperiodalignment", arg, xperiodalignment) + self._set_property("xsrc", arg, xsrc) + self._set_property("xtype", arg, xtype) + self._set_property("y", arg, y) + self._set_property("y0", arg, y0) + self._set_property("yaxis", arg, yaxis) + self._set_property("ycalendar", arg, ycalendar) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("yperiod", arg, yperiod) + self._set_property("yperiod0", arg, yperiod0) + self._set_property("yperiodalignment", arg, yperiodalignment) + self._set_property("ysrc", arg, ysrc) + self._set_property("ytype", arg, ytype) + self._set_property("z", arg, z) + self._set_property("zauto", arg, zauto) + self._set_property("zhoverformat", arg, zhoverformat) + self._set_property("zmax", arg, zmax) + self._set_property("zmid", arg, zmid) + self._set_property("zmin", arg, zmin) + self._set_property("zorder", arg, zorder) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "contour" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_contourcarpet.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_contourcarpet.py new file mode 100644 index 0000000000000000000000000000000000000000..837b6d9a72c9de05e6dba3699f56ed09c1b24294 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_contourcarpet.py @@ -0,0 +1,1837 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Contourcarpet(_BaseTraceType): + _parent_path_str = "" + _path_str = "contourcarpet" + _valid_props = { + "a", + "a0", + "asrc", + "atype", + "autocolorscale", + "autocontour", + "b", + "b0", + "bsrc", + "btype", + "carpet", + "coloraxis", + "colorbar", + "colorscale", + "contours", + "customdata", + "customdatasrc", + "da", + "db", + "fillcolor", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "meta", + "metasrc", + "name", + "ncontours", + "opacity", + "reversescale", + "showlegend", + "showscale", + "stream", + "text", + "textsrc", + "transpose", + "type", + "uid", + "uirevision", + "visible", + "xaxis", + "yaxis", + "z", + "zauto", + "zmax", + "zmid", + "zmin", + "zorder", + "zsrc", + } + + @property + def a(self): + """ + Sets the x coordinates. + + The 'a' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["a"] + + @a.setter + def a(self, val): + self["a"] = val + + @property + def a0(self): + """ + Alternate to `x`. Builds a linear space of x coordinates. Use + with `dx` where `x0` is the starting coordinate and `dx` the + step. + + The 'a0' property accepts values of any type + + Returns + ------- + Any + """ + return self["a0"] + + @a0.setter + def a0(self, val): + self["a0"] = val + + @property + def asrc(self): + """ + Sets the source reference on Chart Studio Cloud for `a`. + + The 'asrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["asrc"] + + @asrc.setter + def asrc(self, val): + self["asrc"] = val + + @property + def atype(self): + """ + If "array", the heatmap's x coordinates are given by "x" (the + default behavior when `x` is provided). If "scaled", the + heatmap's x coordinates are given by "x0" and "dx" (the default + behavior when `x` is not provided). + + The 'atype' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['array', 'scaled'] + + Returns + ------- + Any + """ + return self["atype"] + + @atype.setter + def atype(self, val): + self["atype"] = val + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def autocontour(self): + """ + Determines whether or not the contour level attributes are + picked by an algorithm. If True, the number of contour levels + can be set in `ncontours`. If False, set the contour level + attributes in `contours`. + + The 'autocontour' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocontour"] + + @autocontour.setter + def autocontour(self, val): + self["autocontour"] = val + + @property + def b(self): + """ + Sets the y coordinates. + + The 'b' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["b"] + + @b.setter + def b(self, val): + self["b"] = val + + @property + def b0(self): + """ + Alternate to `y`. Builds a linear space of y coordinates. Use + with `dy` where `y0` is the starting coordinate and `dy` the + step. + + The 'b0' property accepts values of any type + + Returns + ------- + Any + """ + return self["b0"] + + @b0.setter + def b0(self, val): + self["b0"] = val + + @property + def bsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `b`. + + The 'bsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bsrc"] + + @bsrc.setter + def bsrc(self, val): + self["bsrc"] = val + + @property + def btype(self): + """ + If "array", the heatmap's y coordinates are given by "y" (the + default behavior when `y` is provided) If "scaled", the + heatmap's y coordinates are given by "y0" and "dy" (the default + behavior when `y` is not provided) + + The 'btype' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['array', 'scaled'] + + Returns + ------- + Any + """ + return self["btype"] + + @btype.setter + def btype(self, val): + self["btype"] = val + + @property + def carpet(self): + """ + The `carpet` of the carpet axes on which this contour trace + lies + + The 'carpet' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["carpet"] + + @carpet.setter + def carpet(self, val): + self["carpet"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.contourcarpet.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.contourcarpet.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def contours(self): + """ + The 'contours' property is an instance of Contours + that may be specified as: + - An instance of :class:`plotly.graph_objs.contourcarpet.Contours` + - A dict of string/value properties that will be passed + to the Contours constructor + + Returns + ------- + plotly.graph_objs.contourcarpet.Contours + """ + return self["contours"] + + @contours.setter + def contours(self, val): + self["contours"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def da(self): + """ + Sets the x coordinate step. See `x0` for more info. + + The 'da' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["da"] + + @da.setter + def da(self, val): + self["da"] = val + + @property + def db(self): + """ + Sets the y coordinate step. See `y0` for more info. + + The 'db' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["db"] + + @db.setter + def db(self, val): + self["db"] = val + + @property + def fillcolor(self): + """ + Sets the fill color if `contours.type` is "constraint". + Defaults to a half-transparent variant of the line color, + marker color, or marker line color, whichever is available. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A number that will be interpreted as a color + according to contourcarpet.colorscale + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.contourcarpet.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.contourcarpet.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.contourcarpet.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.contourcarpet.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def ncontours(self): + """ + Sets the maximum number of contour levels. The actual number of + contours will be chosen automatically to be less than or equal + to the value of `ncontours`. Has an effect only if + `autocontour` is True or if `contours.size` is missing. + + The 'ncontours' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 9223372036854775807] + + Returns + ------- + int + """ + return self["ncontours"] + + @ncontours.setter + def ncontours(self, val): + self["ncontours"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `zmin` will + correspond to the last color in the array and `zmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.contourcarpet.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.contourcarpet.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets the text elements associated with each z value. + + The 'text' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def transpose(self): + """ + Transposes the z data. + + The 'transpose' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["transpose"] + + @transpose.setter + def transpose(self, val): + self["transpose"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def z(self): + """ + Sets the z data. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `z`) or the bounds set in + `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` + are set by the user. + + The 'zauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["zauto"] + + @zauto.setter + def zauto(self, val): + self["zauto"] = val + + @property + def zmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as in `z` and if set, `zmin` must be set as well. + + The 'zmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmax"] + + @zmax.setter + def zmax(self, val): + self["zmax"] = val + + @property + def zmid(self): + """ + Sets the mid-point of the color domain by scaling `zmin` and/or + `zmax` to be equidistant to this point. Value should have the + same units as in `z`. Has no effect when `zauto` is `false`. + + The 'zmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmid"] + + @zmid.setter + def zmid(self, val): + self["zmid"] = val + + @property + def zmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as in `z` and if set, `zmax` must be set as well. + + The 'zmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmin"] + + @zmin.setter + def zmin(self, val): + self["zmin"] = val + + @property + def zorder(self): + """ + Sets the layer on which this trace is displayed, relative to + other SVG traces on the same subplot. SVG traces with higher + `zorder` appear in front of those with lower `zorder`. + + The 'zorder' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["zorder"] + + @zorder.setter + def zorder(self, val): + self["zorder"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + a + Sets the x coordinates. + a0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + atype + If "array", the heatmap's x coordinates are given by + "x" (the default behavior when `x` is provided). If + "scaled", the heatmap's x coordinates are given by "x0" + and "dx" (the default behavior when `x` is not + provided). + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + autocontour + Determines whether or not the contour level attributes + are picked by an algorithm. If True, the number of + contour levels can be set in `ncontours`. If False, set + the contour level attributes in `contours`. + b + Sets the y coordinates. + b0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + btype + If "array", the heatmap's y coordinates are given by + "y" (the default behavior when `y` is provided) If + "scaled", the heatmap's y coordinates are given by "y0" + and "dy" (the default behavior when `y` is not + provided) + carpet + The `carpet` of the carpet axes on which this contour + trace lies + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.contourcarpet.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contours + :class:`plotly.graph_objects.contourcarpet.Contours` + instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + da + Sets the x coordinate step. See `x0` for more info. + db + Sets the y coordinate step. See `y0` for more info. + fillcolor + Sets the fill color if `contours.type` is "constraint". + Defaults to a half-transparent variant of the line + color, marker color, or marker line color, whichever is + available. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.contourcarpet.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.contourcarpet.Line` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + ncontours + Sets the maximum number of contour levels. The actual + number of contours will be chosen automatically to be + less than or equal to the value of `ncontours`. Has an + effect only if `autocontour` is True or if + `contours.size` is missing. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.contourcarpet.Stream` + instance or dict with compatible properties + text + Sets the text elements associated with each z value. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + transpose + Transposes the z data. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + z + Sets the z data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + a=None, + a0=None, + asrc=None, + atype=None, + autocolorscale=None, + autocontour=None, + b=None, + b0=None, + bsrc=None, + btype=None, + carpet=None, + coloraxis=None, + colorbar=None, + colorscale=None, + contours=None, + customdata=None, + customdatasrc=None, + da=None, + db=None, + fillcolor=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + meta=None, + metasrc=None, + name=None, + ncontours=None, + opacity=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + text=None, + textsrc=None, + transpose=None, + uid=None, + uirevision=None, + visible=None, + xaxis=None, + yaxis=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zorder=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Contourcarpet object + + Plots contours on either the first carpet axis or the carpet + axis with a matching `carpet` attribute. Data `z` is + interpreted as matching that of the corresponding carpet axis. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Contourcarpet` + a + Sets the x coordinates. + a0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + atype + If "array", the heatmap's x coordinates are given by + "x" (the default behavior when `x` is provided). If + "scaled", the heatmap's x coordinates are given by "x0" + and "dx" (the default behavior when `x` is not + provided). + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + autocontour + Determines whether or not the contour level attributes + are picked by an algorithm. If True, the number of + contour levels can be set in `ncontours`. If False, set + the contour level attributes in `contours`. + b + Sets the y coordinates. + b0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + btype + If "array", the heatmap's y coordinates are given by + "y" (the default behavior when `y` is provided) If + "scaled", the heatmap's y coordinates are given by "y0" + and "dy" (the default behavior when `y` is not + provided) + carpet + The `carpet` of the carpet axes on which this contour + trace lies + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.contourcarpet.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contours + :class:`plotly.graph_objects.contourcarpet.Contours` + instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + da + Sets the x coordinate step. See `x0` for more info. + db + Sets the y coordinate step. See `y0` for more info. + fillcolor + Sets the fill color if `contours.type` is "constraint". + Defaults to a half-transparent variant of the line + color, marker color, or marker line color, whichever is + available. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.contourcarpet.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.contourcarpet.Line` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + ncontours + Sets the maximum number of contour levels. The actual + number of contours will be chosen automatically to be + less than or equal to the value of `ncontours`. Has an + effect only if `autocontour` is True or if + `contours.size` is missing. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.contourcarpet.Stream` + instance or dict with compatible properties + text + Sets the text elements associated with each z value. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + transpose + Transposes the z data. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + z + Sets the z data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Contourcarpet + """ + super().__init__("contourcarpet") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Contourcarpet +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Contourcarpet`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("a", arg, a) + self._set_property("a0", arg, a0) + self._set_property("asrc", arg, asrc) + self._set_property("atype", arg, atype) + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("autocontour", arg, autocontour) + self._set_property("b", arg, b) + self._set_property("b0", arg, b0) + self._set_property("bsrc", arg, bsrc) + self._set_property("btype", arg, btype) + self._set_property("carpet", arg, carpet) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("contours", arg, contours) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("da", arg, da) + self._set_property("db", arg, db) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("ncontours", arg, ncontours) + self._set_property("opacity", arg, opacity) + self._set_property("reversescale", arg, reversescale) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("transpose", arg, transpose) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._set_property("xaxis", arg, xaxis) + self._set_property("yaxis", arg, yaxis) + self._set_property("z", arg, z) + self._set_property("zauto", arg, zauto) + self._set_property("zmax", arg, zmax) + self._set_property("zmid", arg, zmid) + self._set_property("zmin", arg, zmin) + self._set_property("zorder", arg, zorder) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "contourcarpet" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_densitymap.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_densitymap.py new file mode 100644 index 0000000000000000000000000000000000000000..c659825168c63c95c0b121a6f006e6d66351510f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_densitymap.py @@ -0,0 +1,1771 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Densitymap(_BaseTraceType): + _parent_path_str = "" + _path_str = "densitymap" + _valid_props = { + "autocolorscale", + "below", + "coloraxis", + "colorbar", + "colorscale", + "customdata", + "customdatasrc", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "lat", + "latsrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "lon", + "lonsrc", + "meta", + "metasrc", + "name", + "opacity", + "radius", + "radiussrc", + "reversescale", + "showlegend", + "showscale", + "stream", + "subplot", + "text", + "textsrc", + "type", + "uid", + "uirevision", + "visible", + "z", + "zauto", + "zmax", + "zmid", + "zmin", + "zsrc", + } + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def below(self): + """ + Determines if the densitymap trace will be inserted before the + layer with the specified ID. By default, densitymap traces are + placed below the first layer of type symbol If set to '', the + layer will be inserted above every existing layer. + + The 'below' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["below"] + + @below.setter + def below(self, val): + self["below"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.densitymap.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.densitymap.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lon', 'lat', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'lon+lat') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.densitymap.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.densitymap.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each (lon,lat) pair If + a single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (lon,lat) coordinates. To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def lat(self): + """ + Sets the latitude coordinates (in degrees North). + + The 'lat' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["lat"] + + @lat.setter + def lat(self, val): + self["lat"] = val + + @property + def latsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `lat`. + + The 'latsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["latsrc"] + + @latsrc.setter + def latsrc(self, val): + self["latsrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.densitymap.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.densitymap.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def lon(self): + """ + Sets the longitude coordinates (in degrees East). + + The 'lon' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["lon"] + + @lon.setter + def lon(self, val): + self["lon"] = val + + @property + def lonsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `lon`. + + The 'lonsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["lonsrc"] + + @lonsrc.setter + def lonsrc(self, val): + self["lonsrc"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def radius(self): + """ + Sets the radius of influence of one `lon` / `lat` point in + pixels. Increasing the value makes the densitymap trace + smoother, but less detailed. + + The 'radius' property is a number and may be specified as: + - An int or float in the interval [1, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["radius"] + + @radius.setter + def radius(self, val): + self["radius"] = val + + @property + def radiussrc(self): + """ + Sets the source reference on Chart Studio Cloud for `radius`. + + The 'radiussrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["radiussrc"] + + @radiussrc.setter + def radiussrc(self, val): + self["radiussrc"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `zmin` will + correspond to the last color in the array and `zmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.densitymap.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.densitymap.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def subplot(self): + """ + Sets a reference between this trace's data coordinates and a + map subplot. If "map" (the default value), the data refer to + `layout.map`. If "map2", the data refer to `layout.map2`, and + so on. + + The 'subplot' property is an identifier of a particular + subplot, of type 'map', that may be specified as: + - the string 'map' optionally followed by an integer >= 1 + (e.g. 'map', 'map1', 'map2', 'map3', etc.) + + Returns + ------- + str + """ + return self["subplot"] + + @subplot.setter + def subplot(self, val): + self["subplot"] = val + + @property + def text(self): + """ + Sets text elements associated with each (lon,lat) pair If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (lon,lat) coordinates. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, these + elements will be seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def z(self): + """ + Sets the points' weight. For example, a value of 10 would be + equivalent to having 10 points of weight 1 in the same spot + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `z`) or the bounds set in + `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` + are set by the user. + + The 'zauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["zauto"] + + @zauto.setter + def zauto(self, val): + self["zauto"] = val + + @property + def zmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as in `z` and if set, `zmin` must be set as well. + + The 'zmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmax"] + + @zmax.setter + def zmax(self, val): + self["zmax"] = val + + @property + def zmid(self): + """ + Sets the mid-point of the color domain by scaling `zmin` and/or + `zmax` to be equidistant to this point. Value should have the + same units as in `z`. Has no effect when `zauto` is `false`. + + The 'zmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmid"] + + @zmid.setter + def zmid(self, val): + self["zmid"] = val + + @property + def zmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as in `z` and if set, `zmax` must be set as well. + + The 'zmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmin"] + + @zmin.setter + def zmin(self, val): + self["zmin"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the densitymap trace will be inserted + before the layer with the specified ID. By default, + densitymap traces are placed below the first layer of + type symbol If set to '', the layer will be inserted + above every existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.densitymap.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.densitymap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.densitymap.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + radius + Sets the radius of influence of one `lon` / `lat` point + in pixels. Increasing the value makes the densitymap + trace smoother, but less detailed. + radiussrc + Sets the source reference on Chart Studio Cloud for + `radius`. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.densitymap.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a map subplot. If "map" (the default value), the + data refer to `layout.map`. If "map2", the data refer + to `layout.map2`, and so on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the points' weight. For example, a value of 10 + would be equivalent to having 10 points of weight 1 in + the same spot + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + autocolorscale=None, + below=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + lat=None, + latsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lon=None, + lonsrc=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + radius=None, + radiussrc=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + subplot=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + visible=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Densitymap object + + Draws a bivariate kernel density estimation with a Gaussian + kernel from `lon` and `lat` coordinates and optional `z` values + using a colorscale. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Densitymap` + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the densitymap trace will be inserted + before the layer with the specified ID. By default, + densitymap traces are placed below the first layer of + type symbol If set to '', the layer will be inserted + above every existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.densitymap.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.densitymap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.densitymap.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + radius + Sets the radius of influence of one `lon` / `lat` point + in pixels. Increasing the value makes the densitymap + trace smoother, but less detailed. + radiussrc + Sets the source reference on Chart Studio Cloud for + `radius`. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.densitymap.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a map subplot. If "map" (the default value), the + data refer to `layout.map`. If "map2", the data refer + to `layout.map2`, and so on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the points' weight. For example, a value of 10 + would be equivalent to having 10 points of weight 1 in + the same spot + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Densitymap + """ + super().__init__("densitymap") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Densitymap +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Densitymap`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("below", arg, below) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("lat", arg, lat) + self._set_property("latsrc", arg, latsrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("lon", arg, lon) + self._set_property("lonsrc", arg, lonsrc) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("radius", arg, radius) + self._set_property("radiussrc", arg, radiussrc) + self._set_property("reversescale", arg, reversescale) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("stream", arg, stream) + self._set_property("subplot", arg, subplot) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._set_property("z", arg, z) + self._set_property("zauto", arg, zauto) + self._set_property("zmax", arg, zmax) + self._set_property("zmid", arg, zmid) + self._set_property("zmin", arg, zmin) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "densitymap" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_densitymapbox.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_densitymapbox.py new file mode 100644 index 0000000000000000000000000000000000000000..b3fb169b53a19ed465899cf9a6b06ca986e495a4 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_densitymapbox.py @@ -0,0 +1,1798 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy +import warnings + + +class Densitymapbox(_BaseTraceType): + _parent_path_str = "" + _path_str = "densitymapbox" + _valid_props = { + "autocolorscale", + "below", + "coloraxis", + "colorbar", + "colorscale", + "customdata", + "customdatasrc", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "lat", + "latsrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "lon", + "lonsrc", + "meta", + "metasrc", + "name", + "opacity", + "radius", + "radiussrc", + "reversescale", + "showlegend", + "showscale", + "stream", + "subplot", + "text", + "textsrc", + "type", + "uid", + "uirevision", + "visible", + "z", + "zauto", + "zmax", + "zmid", + "zmin", + "zsrc", + } + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def below(self): + """ + Determines if the densitymapbox trace will be inserted before + the layer with the specified ID. By default, densitymapbox + traces are placed below the first layer of type symbol If set + to '', the layer will be inserted above every existing layer. + + The 'below' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["below"] + + @below.setter + def below(self, val): + self["below"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.densitymapbox.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.densitymapbox.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lon', 'lat', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'lon+lat') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.densitymapbox.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.densitymapbox.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each (lon,lat) pair If + a single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (lon,lat) coordinates. To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def lat(self): + """ + Sets the latitude coordinates (in degrees North). + + The 'lat' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["lat"] + + @lat.setter + def lat(self, val): + self["lat"] = val + + @property + def latsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `lat`. + + The 'latsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["latsrc"] + + @latsrc.setter + def latsrc(self, val): + self["latsrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.densitymapbox.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.densitymapbox.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def lon(self): + """ + Sets the longitude coordinates (in degrees East). + + The 'lon' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["lon"] + + @lon.setter + def lon(self, val): + self["lon"] = val + + @property + def lonsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `lon`. + + The 'lonsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["lonsrc"] + + @lonsrc.setter + def lonsrc(self, val): + self["lonsrc"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def radius(self): + """ + Sets the radius of influence of one `lon` / `lat` point in + pixels. Increasing the value makes the densitymapbox trace + smoother, but less detailed. + + The 'radius' property is a number and may be specified as: + - An int or float in the interval [1, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["radius"] + + @radius.setter + def radius(self, val): + self["radius"] = val + + @property + def radiussrc(self): + """ + Sets the source reference on Chart Studio Cloud for `radius`. + + The 'radiussrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["radiussrc"] + + @radiussrc.setter + def radiussrc(self, val): + self["radiussrc"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `zmin` will + correspond to the last color in the array and `zmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.densitymapbox.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.densitymapbox.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def subplot(self): + """ + mapbox subplots and traces are deprecated! Please consider + switching to `map` subplots and traces. Learn more at: + https://plotly.com/python/maplibre-migration/ as well as + https://plotly.com/javascript/maplibre-migration/ Sets a + reference between this trace's data coordinates and a mapbox + subplot. If "mapbox" (the default value), the data refer to + `layout.mapbox`. If "mapbox2", the data refer to + `layout.mapbox2`, and so on. + + The 'subplot' property is an identifier of a particular + subplot, of type 'mapbox', that may be specified as: + - the string 'mapbox' optionally followed by an integer >= 1 + (e.g. 'mapbox', 'mapbox1', 'mapbox2', 'mapbox3', etc.) + + Returns + ------- + str + """ + return self["subplot"] + + @subplot.setter + def subplot(self, val): + self["subplot"] = val + + @property + def text(self): + """ + Sets text elements associated with each (lon,lat) pair If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (lon,lat) coordinates. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, these + elements will be seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def z(self): + """ + Sets the points' weight. For example, a value of 10 would be + equivalent to having 10 points of weight 1 in the same spot + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `z`) or the bounds set in + `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` + are set by the user. + + The 'zauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["zauto"] + + @zauto.setter + def zauto(self, val): + self["zauto"] = val + + @property + def zmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as in `z` and if set, `zmin` must be set as well. + + The 'zmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmax"] + + @zmax.setter + def zmax(self, val): + self["zmax"] = val + + @property + def zmid(self): + """ + Sets the mid-point of the color domain by scaling `zmin` and/or + `zmax` to be equidistant to this point. Value should have the + same units as in `z`. Has no effect when `zauto` is `false`. + + The 'zmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmid"] + + @zmid.setter + def zmid(self, val): + self["zmid"] = val + + @property + def zmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as in `z` and if set, `zmax` must be set as well. + + The 'zmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmin"] + + @zmin.setter + def zmin(self, val): + self["zmin"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the densitymapbox trace will be inserted + before the layer with the specified ID. By default, + densitymapbox traces are placed below the first layer + of type symbol If set to '', the layer will be inserted + above every existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.densitymapbox.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.densitymapbox.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.densitymapbox.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + radius + Sets the radius of influence of one `lon` / `lat` point + in pixels. Increasing the value makes the densitymapbox + trace smoother, but less detailed. + radiussrc + Sets the source reference on Chart Studio Cloud for + `radius`. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.densitymapbox.Stream` + instance or dict with compatible properties + subplot + mapbox subplots and traces are deprecated! Please + consider switching to `map` subplots and traces. Learn + more at: https://plotly.com/python/maplibre-migration/ + as well as https://plotly.com/javascript/maplibre- + migration/ Sets a reference between this trace's data + coordinates and a mapbox subplot. If "mapbox" (the + default value), the data refer to `layout.mapbox`. If + "mapbox2", the data refer to `layout.mapbox2`, and so + on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the points' weight. For example, a value of 10 + would be equivalent to having 10 points of weight 1 in + the same spot + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + autocolorscale=None, + below=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + lat=None, + latsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lon=None, + lonsrc=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + radius=None, + radiussrc=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + subplot=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + visible=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Densitymapbox object + + "densitymapbox" trace is deprecated! Please consider switching + to the "densitymap" trace type and `map` subplots. Learn more + at: https://plotly.com/python/maplibre-migration/ as well as + https://plotly.com/javascript/maplibre-migration/ Draws a + bivariate kernel density estimation with a Gaussian kernel from + `lon` and `lat` coordinates and optional `z` values using a + colorscale. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Densitymapbox` + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the densitymapbox trace will be inserted + before the layer with the specified ID. By default, + densitymapbox traces are placed below the first layer + of type symbol If set to '', the layer will be inserted + above every existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.densitymapbox.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.densitymapbox.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.densitymapbox.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + radius + Sets the radius of influence of one `lon` / `lat` point + in pixels. Increasing the value makes the densitymapbox + trace smoother, but less detailed. + radiussrc + Sets the source reference on Chart Studio Cloud for + `radius`. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.densitymapbox.Stream` + instance or dict with compatible properties + subplot + mapbox subplots and traces are deprecated! Please + consider switching to `map` subplots and traces. Learn + more at: https://plotly.com/python/maplibre-migration/ + as well as https://plotly.com/javascript/maplibre- + migration/ Sets a reference between this trace's data + coordinates and a mapbox subplot. If "mapbox" (the + default value), the data refer to `layout.mapbox`. If + "mapbox2", the data refer to `layout.mapbox2`, and so + on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the points' weight. For example, a value of 10 + would be equivalent to having 10 points of weight 1 in + the same spot + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Densitymapbox + """ + super().__init__("densitymapbox") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Densitymapbox +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Densitymapbox`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("below", arg, below) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("lat", arg, lat) + self._set_property("latsrc", arg, latsrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("lon", arg, lon) + self._set_property("lonsrc", arg, lonsrc) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("radius", arg, radius) + self._set_property("radiussrc", arg, radiussrc) + self._set_property("reversescale", arg, reversescale) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("stream", arg, stream) + self._set_property("subplot", arg, subplot) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._set_property("z", arg, z) + self._set_property("zauto", arg, zauto) + self._set_property("zmax", arg, zmax) + self._set_property("zmid", arg, zmid) + self._set_property("zmin", arg, zmin) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "densitymapbox" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False + + warnings.warn( + "*densitymapbox* is deprecated!" + + " Use *densitymap* instead." + + " Learn more at: https://plotly.com/python/mapbox-to-maplibre/", + stacklevel=2, + category=DeprecationWarning, + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_deprecations.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_deprecations.py new file mode 100644 index 0000000000000000000000000000000000000000..aa08325deb37cde1aa49fe84978f43fb3ae3489a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_deprecations.py @@ -0,0 +1,723 @@ +import warnings + +warnings.filterwarnings( + "default", r"plotly\.graph_objs\.\w+ is deprecated", DeprecationWarning +) + + +class Data(list): + """ + plotly.graph_objs.Data is deprecated. + Please replace it with a list or tuple of instances of the following types + - plotly.graph_objs.Scatter + - plotly.graph_objs.Bar + - plotly.graph_objs.Area + - plotly.graph_objs.Histogram + - etc. + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.Data is deprecated. + Please replace it with a list or tuple of instances of the following types + - plotly.graph_objs.Scatter + - plotly.graph_objs.Bar + - plotly.graph_objs.Area + - plotly.graph_objs.Histogram + - etc. + + """ + warnings.warn( + """plotly.graph_objs.Data is deprecated. +Please replace it with a list or tuple of instances of the following types + - plotly.graph_objs.Scatter + - plotly.graph_objs.Bar + - plotly.graph_objs.Area + - plotly.graph_objs.Histogram + - etc. +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class Annotations(list): + """ + plotly.graph_objs.Annotations is deprecated. + Please replace it with a list or tuple of instances of the following types + - plotly.graph_objs.layout.Annotation + - plotly.graph_objs.layout.scene.Annotation + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.Annotations is deprecated. + Please replace it with a list or tuple of instances of the following types + - plotly.graph_objs.layout.Annotation + - plotly.graph_objs.layout.scene.Annotation + + """ + warnings.warn( + """plotly.graph_objs.Annotations is deprecated. +Please replace it with a list or tuple of instances of the following types + - plotly.graph_objs.layout.Annotation + - plotly.graph_objs.layout.scene.Annotation +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class Frames(list): + """ + plotly.graph_objs.Frames is deprecated. + Please replace it with a list or tuple of instances of the following types + - plotly.graph_objs.Frame + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.Frames is deprecated. + Please replace it with a list or tuple of instances of the following types + - plotly.graph_objs.Frame + + """ + warnings.warn( + """plotly.graph_objs.Frames is deprecated. +Please replace it with a list or tuple of instances of the following types + - plotly.graph_objs.Frame +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class AngularAxis(dict): + """ + plotly.graph_objs.AngularAxis is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.AngularAxis + - plotly.graph_objs.layout.polar.AngularAxis + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.AngularAxis is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.AngularAxis + - plotly.graph_objs.layout.polar.AngularAxis + + """ + warnings.warn( + """plotly.graph_objs.AngularAxis is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.layout.AngularAxis + - plotly.graph_objs.layout.polar.AngularAxis +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class Annotation(dict): + """ + plotly.graph_objs.Annotation is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.Annotation + - plotly.graph_objs.layout.scene.Annotation + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.Annotation is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.Annotation + - plotly.graph_objs.layout.scene.Annotation + + """ + warnings.warn( + """plotly.graph_objs.Annotation is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.layout.Annotation + - plotly.graph_objs.layout.scene.Annotation +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class ColorBar(dict): + """ + plotly.graph_objs.ColorBar is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.marker.ColorBar + - plotly.graph_objs.surface.ColorBar + - etc. + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.ColorBar is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.marker.ColorBar + - plotly.graph_objs.surface.ColorBar + - etc. + + """ + warnings.warn( + """plotly.graph_objs.ColorBar is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.marker.ColorBar + - plotly.graph_objs.surface.ColorBar + - etc. +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class Contours(dict): + """ + plotly.graph_objs.Contours is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.contour.Contours + - plotly.graph_objs.surface.Contours + - etc. + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.Contours is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.contour.Contours + - plotly.graph_objs.surface.Contours + - etc. + + """ + warnings.warn( + """plotly.graph_objs.Contours is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.contour.Contours + - plotly.graph_objs.surface.Contours + - etc. +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class ErrorX(dict): + """ + plotly.graph_objs.ErrorX is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.ErrorX + - plotly.graph_objs.histogram.ErrorX + - etc. + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.ErrorX is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.ErrorX + - plotly.graph_objs.histogram.ErrorX + - etc. + + """ + warnings.warn( + """plotly.graph_objs.ErrorX is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.ErrorX + - plotly.graph_objs.histogram.ErrorX + - etc. +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class ErrorY(dict): + """ + plotly.graph_objs.ErrorY is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.ErrorY + - plotly.graph_objs.histogram.ErrorY + - etc. + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.ErrorY is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.ErrorY + - plotly.graph_objs.histogram.ErrorY + - etc. + + """ + warnings.warn( + """plotly.graph_objs.ErrorY is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.ErrorY + - plotly.graph_objs.histogram.ErrorY + - etc. +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class ErrorZ(dict): + """ + plotly.graph_objs.ErrorZ is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.scatter3d.ErrorZ + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.ErrorZ is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.scatter3d.ErrorZ + + """ + warnings.warn( + """plotly.graph_objs.ErrorZ is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.scatter3d.ErrorZ +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class Font(dict): + """ + plotly.graph_objs.Font is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.Font + - plotly.graph_objs.layout.hoverlabel.Font + - etc. + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.Font is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.Font + - plotly.graph_objs.layout.hoverlabel.Font + - etc. + + """ + warnings.warn( + """plotly.graph_objs.Font is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.layout.Font + - plotly.graph_objs.layout.hoverlabel.Font + - etc. +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class Legend(dict): + """ + plotly.graph_objs.Legend is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.Legend + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.Legend is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.Legend + + """ + warnings.warn( + """plotly.graph_objs.Legend is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.layout.Legend +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class Line(dict): + """ + plotly.graph_objs.Line is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.Line + - plotly.graph_objs.layout.shape.Line + - etc. + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.Line is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.Line + - plotly.graph_objs.layout.shape.Line + - etc. + + """ + warnings.warn( + """plotly.graph_objs.Line is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.Line + - plotly.graph_objs.layout.shape.Line + - etc. +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class Margin(dict): + """ + plotly.graph_objs.Margin is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.Margin + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.Margin is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.Margin + + """ + warnings.warn( + """plotly.graph_objs.Margin is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.layout.Margin +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class Marker(dict): + """ + plotly.graph_objs.Marker is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.Marker + - plotly.graph_objs.histogram.selected.Marker + - etc. + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.Marker is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.Marker + - plotly.graph_objs.histogram.selected.Marker + - etc. + + """ + warnings.warn( + """plotly.graph_objs.Marker is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.Marker + - plotly.graph_objs.histogram.selected.Marker + - etc. +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class RadialAxis(dict): + """ + plotly.graph_objs.RadialAxis is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.RadialAxis + - plotly.graph_objs.layout.polar.RadialAxis + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.RadialAxis is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.RadialAxis + - plotly.graph_objs.layout.polar.RadialAxis + + """ + warnings.warn( + """plotly.graph_objs.RadialAxis is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.layout.RadialAxis + - plotly.graph_objs.layout.polar.RadialAxis +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class Scene(dict): + """ + plotly.graph_objs.Scene is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.Scene + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.Scene is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.Scene + + """ + warnings.warn( + """plotly.graph_objs.Scene is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.layout.Scene +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class Stream(dict): + """ + plotly.graph_objs.Stream is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.Stream + - plotly.graph_objs.area.Stream + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.Stream is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.Stream + - plotly.graph_objs.area.Stream + + """ + warnings.warn( + """plotly.graph_objs.Stream is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.scatter.Stream + - plotly.graph_objs.area.Stream +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class XAxis(dict): + """ + plotly.graph_objs.XAxis is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.XAxis + - plotly.graph_objs.layout.scene.XAxis + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.XAxis is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.XAxis + - plotly.graph_objs.layout.scene.XAxis + + """ + warnings.warn( + """plotly.graph_objs.XAxis is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.layout.XAxis + - plotly.graph_objs.layout.scene.XAxis +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class YAxis(dict): + """ + plotly.graph_objs.YAxis is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.YAxis + - plotly.graph_objs.layout.scene.YAxis + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.YAxis is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.YAxis + - plotly.graph_objs.layout.scene.YAxis + + """ + warnings.warn( + """plotly.graph_objs.YAxis is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.layout.YAxis + - plotly.graph_objs.layout.scene.YAxis +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class ZAxis(dict): + """ + plotly.graph_objs.ZAxis is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.scene.ZAxis + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.ZAxis is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.layout.scene.ZAxis + + """ + warnings.warn( + """plotly.graph_objs.ZAxis is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.layout.scene.ZAxis +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class XBins(dict): + """ + plotly.graph_objs.XBins is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.histogram.XBins + - plotly.graph_objs.histogram2d.XBins + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.XBins is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.histogram.XBins + - plotly.graph_objs.histogram2d.XBins + + """ + warnings.warn( + """plotly.graph_objs.XBins is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.histogram.XBins + - plotly.graph_objs.histogram2d.XBins +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class YBins(dict): + """ + plotly.graph_objs.YBins is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.histogram.YBins + - plotly.graph_objs.histogram2d.YBins + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.YBins is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.histogram.YBins + - plotly.graph_objs.histogram2d.YBins + + """ + warnings.warn( + """plotly.graph_objs.YBins is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.histogram.YBins + - plotly.graph_objs.histogram2d.YBins +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class Trace(dict): + """ + plotly.graph_objs.Trace is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.Scatter + - plotly.graph_objs.Bar + - plotly.graph_objs.Area + - plotly.graph_objs.Histogram + - etc. + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.Trace is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.Scatter + - plotly.graph_objs.Bar + - plotly.graph_objs.Area + - plotly.graph_objs.Histogram + - etc. + + """ + warnings.warn( + """plotly.graph_objs.Trace is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.Scatter + - plotly.graph_objs.Bar + - plotly.graph_objs.Area + - plotly.graph_objs.Histogram + - etc. +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) + + +class Histogram2dcontour(dict): + """ + plotly.graph_objs.Histogram2dcontour is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.Histogram2dContour + + """ + + def __init__(self, *args, **kwargs): + """ + plotly.graph_objs.Histogram2dcontour is deprecated. + Please replace it with one of the following more specific types + - plotly.graph_objs.Histogram2dContour + + """ + warnings.warn( + """plotly.graph_objs.Histogram2dcontour is deprecated. +Please replace it with one of the following more specific types + - plotly.graph_objs.Histogram2dContour +""", + DeprecationWarning, + ) + super().__init__(*args, **kwargs) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_figure.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_figure.py new file mode 100644 index 0000000000000000000000000000000000000000..c950ed8fc42ea61a98bc851f0ec4dd14b78717cc --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_figure.py @@ -0,0 +1,25367 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseFigure + + +class Figure(BaseFigure): + def __init__( + self, data=None, layout=None, frames=None, skip_invalid=False, **kwargs + ): + """ + Create a new :class:Figure instance + + Parameters + ---------- + data + The 'data' property is a tuple of trace instances + that may be specified as: + - A list or tuple of trace instances + (e.g. [Scatter(...), Bar(...)]) + - A single trace instance + (e.g. Scatter(...), Bar(...), etc.) + - A list or tuple of dicts of string/value properties where: + - The 'type' property specifies the trace type + One of: ['bar', 'barpolar', 'box', 'candlestick', + 'carpet', 'choropleth', 'choroplethmap', + 'choroplethmapbox', 'cone', 'contour', + 'contourcarpet', 'densitymap', + 'densitymapbox', 'funnel', 'funnelarea', + 'heatmap', 'histogram', 'histogram2d', + 'histogram2dcontour', 'icicle', 'image', + 'indicator', 'isosurface', 'mesh3d', 'ohlc', + 'parcats', 'parcoords', 'pie', 'sankey', + 'scatter', 'scatter3d', 'scattercarpet', + 'scattergeo', 'scattergl', 'scattermap', + 'scattermapbox', 'scatterpolar', + 'scatterpolargl', 'scattersmith', + 'scatterternary', 'splom', 'streamtube', + 'sunburst', 'surface', 'table', 'treemap', + 'violin', 'volume', 'waterfall'] + + - All remaining properties are passed to the constructor of + the specified trace type + + (e.g. [{'type': 'scatter', ...}, {'type': 'bar, ...}]) + + layout + The 'layout' property is an instance of Layout + that may be specified as: + - An instance of :class:`plotly.graph_objs.Layout` + - A dict of string/value properties that will be passed + to the Layout constructor + + frames + The 'frames' property is a tuple of instances of + Frame that may be specified as: + - A list or tuple of instances of plotly.graph_objs.Frame + - A list or tuple of dicts of string/value properties that + will be passed to the Frame constructor + + skip_invalid: bool + If True, invalid properties in the figure specification will be + skipped silently. If False (default) invalid properties in the + figure specification will result in a ValueError + + Raises + ------ + ValueError + if a property in the specification of data, layout, or frames + is invalid AND skip_invalid is False + """ + super().__init__(data, layout, frames, skip_invalid, **kwargs) + + def update(self, dict1=None, overwrite=False, **kwargs) -> "Figure": + """ + + Update the properties of the figure with a dict and/or with + keyword arguments. + + This recursively updates the structure of the figure + object with the values in the input dict / keyword arguments. + + Parameters + ---------- + dict1 : dict + Dictionary of properties to be updated + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + kwargs : + Keyword/value pair of properties to be updated + + Examples + -------- + >>> import plotly.graph_objs as go + >>> fig = go.Figure(data=[{'y': [1, 2, 3]}]) + >>> fig.update(data=[{'y': [4, 5, 6]}]) # doctest: +ELLIPSIS + Figure(...) + >>> fig.to_plotly_json() # doctest: +SKIP + {'data': [{'type': 'scatter', + 'uid': 'e86a7c7a-346a-11e8-8aa8-a0999b0c017b', + 'y': array([4, 5, 6], dtype=int32)}], + 'layout': {}} + + >>> fig = go.Figure(layout={'xaxis': + ... {'color': 'green', + ... 'range': [0, 1]}}) + >>> fig.update({'layout': {'xaxis': {'color': 'pink'}}}) # doctest: +ELLIPSIS + Figure(...) + >>> fig.to_plotly_json() # doctest: +SKIP + {'data': [], + 'layout': {'xaxis': + {'color': 'pink', + 'range': [0, 1]}}} + + Returns + ------- + BaseFigure + Updated figure + + """ + return super().update(dict1, overwrite, **kwargs) + + def update_traces( + self, + patch=None, + selector=None, + row=None, + col=None, + secondary_y=None, + overwrite=False, + **kwargs, + ) -> "Figure": + """ + + Perform a property update operation on all traces that satisfy the + specified selection criteria + + Parameters + ---------- + patch: dict or None (default None) + Dictionary of property updates to be applied to all traces that + satisfy the selection criteria. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all traces are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each trace and those for which the function returned True + will be in the selection. If an int N, the Nth trace matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of traces to select. + To select traces by row and column, the Figure must have been + created using plotly.subplots.make_subplots. If None + (the default), all traces are selected. + secondary_y: boolean or None (default None) + * If True, only select traces associated with the secondary + y-axis of the subplot. + * If False, only select traces associated with the primary + y-axis of the subplot. + * If None (the default), do not filter traces based on secondary + y-axis. + + To select traces by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + **kwargs + Additional property updates to apply to each selected trace. If + a property is specified in both patch and in **kwargs then the + one in **kwargs takes precedence. + + Returns + ------- + self + Returns the Figure object that the method was called on + + """ + return super().update_traces( + patch, selector, row, col, secondary_y, overwrite, **kwargs + ) + + def update_layout(self, dict1=None, overwrite=False, **kwargs) -> "Figure": + """ + + Update the properties of the figure's layout with a dict and/or with + keyword arguments. + + This recursively updates the structure of the original + layout with the values in the input dict / keyword arguments. + + Parameters + ---------- + dict1 : dict + Dictionary of properties to be updated + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + kwargs : + Keyword/value pair of properties to be updated + + Returns + ------- + BaseFigure + The Figure object that the update_layout method was called on + + """ + return super().update_layout(dict1, overwrite, **kwargs) + + def for_each_trace( + self, fn, selector=None, row=None, col=None, secondary_y=None + ) -> "Figure": + """ + + Apply a function to all traces that satisfy the specified selection + criteria + + Parameters + ---------- + fn: + Function that inputs a single trace object. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all traces are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each trace and those for which the function returned True + will be in the selection. If an int N, the Nth trace matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of traces to select. + To select traces by row and column, the Figure must have been + created using plotly.subplots.make_subplots. If None + (the default), all traces are selected. + secondary_y: boolean or None (default None) + * If True, only select traces associated with the secondary + y-axis of the subplot. + * If False, only select traces associated with the primary + y-axis of the subplot. + * If None (the default), do not filter traces based on secondary + y-axis. + + To select traces by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + self + Returns the Figure object that the method was called on + + """ + return super().for_each_trace(fn, selector, row, col, secondary_y) + + def add_trace( + self, trace, row=None, col=None, secondary_y=None, exclude_empty_subplots=False + ) -> "Figure": + """ + + Add a trace to the figure + + Parameters + ---------- + trace : BaseTraceType or dict + Either: + - An instances of a trace classe from the plotly.graph_objs + package (e.g plotly.graph_objs.Scatter, plotly.graph_objs.Bar) + - or a dicts where: + + - The 'type' property specifies the trace type (e.g. + 'scatter', 'bar', 'area', etc.). If the dict has no 'type' + property then 'scatter' is assumed. + - All remaining properties are passed to the constructor + of the specified trace type. + + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`. + If 'all', addresses all rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`. + If 'all', addresses all columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + * The trace argument is a 2D cartesian trace + (scatter, bar, etc.) + exclude_empty_subplots: boolean + If True, the trace will not be added to subplots that don't already + have traces. + Returns + ------- + BaseFigure + The Figure that add_trace was called on + + Examples + -------- + + >>> from plotly import subplots + >>> import plotly.graph_objs as go + + Add two Scatter traces to a figure + + >>> fig = go.Figure() + >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2])) # doctest: +ELLIPSIS + Figure(...) + >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2])) # doctest: +ELLIPSIS + Figure(...) + + + Add two Scatter traces to vertically stacked subplots + + >>> fig = subplots.make_subplots(rows=2) + >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2]), row=1, col=1) # doctest: +ELLIPSIS + Figure(...) + >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2]), row=2, col=1) # doctest: +ELLIPSIS + Figure(...) + + """ + return super().add_trace(trace, row, col, secondary_y, exclude_empty_subplots) + + def add_traces( + self, + data, + rows=None, + cols=None, + secondary_ys=None, + exclude_empty_subplots=False, + ) -> "Figure": + """ + + Add traces to the figure + + Parameters + ---------- + data : list[BaseTraceType or dict] + A list of trace specifications to be added. + Trace specifications may be either: + + - Instances of trace classes from the plotly.graph_objs + package (e.g plotly.graph_objs.Scatter, plotly.graph_objs.Bar) + - Dicts where: + + - The 'type' property specifies the trace type (e.g. + 'scatter', 'bar', 'area', etc.). If the dict has no 'type' + property then 'scatter' is assumed. + - All remaining properties are passed to the constructor + of the specified trace type. + + rows : None, list[int], or int (default None) + List of subplot row indexes (starting from 1) for the traces to be + added. Only valid if figure was created using + `plotly.tools.make_subplots` + If a single integer is passed, all traces will be added to row number + + cols : None or list[int] (default None) + List of subplot column indexes (starting from 1) for the traces + to be added. Only valid if figure was created using + `plotly.tools.make_subplots` + If a single integer is passed, all traces will be added to column number + + + secondary_ys: None or list[boolean] (default None) + List of secondary_y booleans for traces to be added. See the + docstring for `add_trace` for more info. + + exclude_empty_subplots: boolean + If True, the trace will not be added to subplots that don't already + have traces. + + Returns + ------- + BaseFigure + The Figure that add_traces was called on + + Examples + -------- + + >>> from plotly import subplots + >>> import plotly.graph_objs as go + + Add two Scatter traces to a figure + + >>> fig = go.Figure() + >>> fig.add_traces([go.Scatter(x=[1,2,3], y=[2,1,2]), + ... go.Scatter(x=[1,2,3], y=[2,1,2])]) # doctest: +ELLIPSIS + Figure(...) + + Add two Scatter traces to vertically stacked subplots + + >>> fig = subplots.make_subplots(rows=2) + >>> fig.add_traces([go.Scatter(x=[1,2,3], y=[2,1,2]), + ... go.Scatter(x=[1,2,3], y=[2,1,2])], + ... rows=[1, 2], cols=[1, 1]) # doctest: +ELLIPSIS + Figure(...) + + """ + return super().add_traces( + data, rows, cols, secondary_ys, exclude_empty_subplots + ) + + def add_vline( + self, + x, + row="all", + col="all", + exclude_empty_subplots=True, + annotation=None, + **kwargs, + ) -> "Figure": + """ + + Add a vertical line to a plot or subplot that extends infinitely in the + y-dimension. + + Parameters + ---------- + x: float or int + A number representing the x coordinate of the vertical line. + exclude_empty_subplots: Boolean + If True (default) do not place the shape on subplots that have no data + plotted on them. + row: None, int or 'all' + Subplot row for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + col: None, int or 'all' + Subplot column for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + annotation: dict or plotly.graph_objects.layout.Annotation. If dict(), + it is interpreted as describing an annotation. The annotation is + placed relative to the shape based on annotation_position (see + below) unless its x or y value has been specified for the annotation + passed here. xref and yref are always the same as for the added + shape and cannot be overridden. + annotation_position: a string containing optionally ["top", "bottom"] + and ["left", "right"] specifying where the text should be anchored + to on the line. Example positions are "bottom left", "right top", + "right", "bottom". If an annotation is added but annotation_position is + not specified, this defaults to "top right". + annotation_*: any parameters to go.layout.Annotation can be passed as + keywords by prefixing them with "annotation_". For example, to specify the + annotation text "example" you can pass annotation_text="example" as a + keyword argument. + **kwargs: + Any named function parameters that can be passed to 'add_shape', + except for x0, x1, y0, y1 or type. + """ + return super().add_vline( + x, row, col, exclude_empty_subplots, annotation, **kwargs + ) + + def add_hline( + self, + y, + row="all", + col="all", + exclude_empty_subplots=True, + annotation=None, + **kwargs, + ) -> "Figure": + """ + + Add a horizontal line to a plot or subplot that extends infinitely in the + x-dimension. + + Parameters + ---------- + y: float or int + A number representing the y coordinate of the horizontal line. + exclude_empty_subplots: Boolean + If True (default) do not place the shape on subplots that have no data + plotted on them. + row: None, int or 'all' + Subplot row for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + col: None, int or 'all' + Subplot column for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + annotation: dict or plotly.graph_objects.layout.Annotation. If dict(), + it is interpreted as describing an annotation. The annotation is + placed relative to the shape based on annotation_position (see + below) unless its x or y value has been specified for the annotation + passed here. xref and yref are always the same as for the added + shape and cannot be overridden. + annotation_position: a string containing optionally ["top", "bottom"] + and ["left", "right"] specifying where the text should be anchored + to on the line. Example positions are "bottom left", "right top", + "right", "bottom". If an annotation is added but annotation_position is + not specified, this defaults to "top right". + annotation_*: any parameters to go.layout.Annotation can be passed as + keywords by prefixing them with "annotation_". For example, to specify the + annotation text "example" you can pass annotation_text="example" as a + keyword argument. + **kwargs: + Any named function parameters that can be passed to 'add_shape', + except for x0, x1, y0, y1 or type. + """ + return super().add_hline( + y, row, col, exclude_empty_subplots, annotation, **kwargs + ) + + def add_vrect( + self, + x0, + x1, + row="all", + col="all", + exclude_empty_subplots=True, + annotation=None, + **kwargs, + ) -> "Figure": + """ + + Add a rectangle to a plot or subplot that extends infinitely in the + y-dimension. + + Parameters + ---------- + x0: float or int + A number representing the x coordinate of one side of the rectangle. + x1: float or int + A number representing the x coordinate of the other side of the rectangle. + exclude_empty_subplots: Boolean + If True (default) do not place the shape on subplots that have no data + plotted on them. + row: None, int or 'all' + Subplot row for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + col: None, int or 'all' + Subplot column for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + annotation: dict or plotly.graph_objects.layout.Annotation. If dict(), + it is interpreted as describing an annotation. The annotation is + placed relative to the shape based on annotation_position (see + below) unless its x or y value has been specified for the annotation + passed here. xref and yref are always the same as for the added + shape and cannot be overridden. + annotation_position: a string containing optionally ["inside", "outside"], ["top", "bottom"] + and ["left", "right"] specifying where the text should be anchored + to on the rectangle. Example positions are "outside top left", "inside + bottom", "right", "inside left", "inside" ("outside" is not supported). If + an annotation is added but annotation_position is not specified this + defaults to "inside top right". + annotation_*: any parameters to go.layout.Annotation can be passed as + keywords by prefixing them with "annotation_". For example, to specify the + annotation text "example" you can pass annotation_text="example" as a + keyword argument. + **kwargs: + Any named function parameters that can be passed to 'add_shape', + except for x0, x1, y0, y1 or type. + """ + return super().add_vrect( + x0, x1, row, col, exclude_empty_subplots, annotation, **kwargs + ) + + def add_hrect( + self, + y0, + y1, + row="all", + col="all", + exclude_empty_subplots=True, + annotation=None, + **kwargs, + ) -> "Figure": + """ + + Add a rectangle to a plot or subplot that extends infinitely in the + x-dimension. + + Parameters + ---------- + y0: float or int + A number representing the y coordinate of one side of the rectangle. + y1: float or int + A number representing the y coordinate of the other side of the rectangle. + exclude_empty_subplots: Boolean + If True (default) do not place the shape on subplots that have no data + plotted on them. + row: None, int or 'all' + Subplot row for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + col: None, int or 'all' + Subplot column for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + annotation: dict or plotly.graph_objects.layout.Annotation. If dict(), + it is interpreted as describing an annotation. The annotation is + placed relative to the shape based on annotation_position (see + below) unless its x or y value has been specified for the annotation + passed here. xref and yref are always the same as for the added + shape and cannot be overridden. + annotation_position: a string containing optionally ["inside", "outside"], ["top", "bottom"] + and ["left", "right"] specifying where the text should be anchored + to on the rectangle. Example positions are "outside top left", "inside + bottom", "right", "inside left", "inside" ("outside" is not supported). If + an annotation is added but annotation_position is not specified this + defaults to "inside top right". + annotation_*: any parameters to go.layout.Annotation can be passed as + keywords by prefixing them with "annotation_". For example, to specify the + annotation text "example" you can pass annotation_text="example" as a + keyword argument. + **kwargs: + Any named function parameters that can be passed to 'add_shape', + except for x0, x1, y0, y1 or type. + """ + return super().add_hrect( + y0, y1, row, col, exclude_empty_subplots, annotation, **kwargs + ) + + def set_subplots(self, rows=None, cols=None, **make_subplots_args) -> "Figure": + """ + + Add subplots to this figure. If the figure already contains subplots, + then this throws an error. Accepts any keyword arguments that + plotly.subplots.make_subplots accepts. + + """ + return super().set_subplots(rows, cols, **make_subplots_args) + + def add_bar( + self, + alignmentgroup=None, + base=None, + basesrc=None, + cliponaxis=None, + constraintext=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + error_x=None, + error_y=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextanchor=None, + insidetextfont=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + offset=None, + offsetgroup=None, + offsetsrc=None, + opacity=None, + orientation=None, + outsidetextfont=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textangle=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + width=None, + widthsrc=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Bar trace + + The data visualized by the span of the bars is set in `y` if + `orientation` is set to "v" (the default) and the labels are + set in `x`. By setting `orientation` to "h", the roles are + interchanged. + + Parameters + ---------- + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + base + Sets where the bar base is drawn (in position axis + units). In "stack" or "relative" barmode, traces that + set "base" will be excluded and drawn in "overlay" mode + instead. + basesrc + Sets the source reference on Chart Studio Cloud for + `base`. + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + error_x + :class:`plotly.graph_objects.bar.ErrorX` instance or + dict with compatible properties + error_y + :class:`plotly.graph_objects.bar.ErrorY` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.bar.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `value` and `label`. Anything contained in + tag `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.bar.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.bar.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the position where the bar is drawn (in position + axis units). In "group" barmode, traces that set + "offset" will be excluded and drawn in "overlay" mode + instead. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + offsetsrc + Sets the source reference on Chart Studio Cloud for + `offset`. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the bars. With "v" ("h"), the + value of the each bar spans along the vertical + (horizontal). + outsidetextfont + Sets the font used for `text` lying outside the bar. + selected + :class:`plotly.graph_objects.bar.Selected` instance or + dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.bar.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the font used for `text`. + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `value` and `label`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.bar.Unselected` instance + or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar width (in position axis units). + widthsrc + Sets the source reference on Chart Studio Cloud for + `width`. + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Bar + + new_trace = Bar( + alignmentgroup=alignmentgroup, + base=base, + basesrc=basesrc, + cliponaxis=cliponaxis, + constraintext=constraintext, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + error_x=error_x, + error_y=error_y, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextanchor=insidetextanchor, + insidetextfont=insidetextfont, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + offset=offset, + offsetgroup=offsetgroup, + offsetsrc=offsetsrc, + opacity=opacity, + orientation=orientation, + outsidetextfont=outsidetextfont, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textangle=textangle, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + width=width, + widthsrc=widthsrc, + x=x, + x0=x0, + xaxis=xaxis, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + y=y, + y0=y0, + yaxis=yaxis, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_barpolar( + self, + base=None, + basesrc=None, + customdata=None, + customdatasrc=None, + dr=None, + dtheta=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + offset=None, + offsetsrc=None, + opacity=None, + r=None, + r0=None, + rsrc=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textsrc=None, + theta=None, + theta0=None, + thetasrc=None, + thetaunit=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + width=None, + widthsrc=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Barpolar trace + + The data visualized by the radial span of the bars is set in + `r` + + Parameters + ---------- + base + Sets where the bar base is drawn (in radial axis + units). In "stack" barmode, traces that set "base" will + be excluded and drawn in "overlay" mode instead. + basesrc + Sets the source reference on Chart Studio Cloud for + `base`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dr + Sets the r coordinate step. + dtheta + Sets the theta coordinate step. By default, the + `dtheta` step equals the subplot's period divided by + the length of the `r` coordinates. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.barpolar.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.barpolar.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.barpolar.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the angular position where the bar is drawn (in + "thetatunit" units). + offsetsrc + Sets the source reference on Chart Studio Cloud for + `offset`. + opacity + Sets the opacity of the trace. + r + Sets the radial coordinates + r0 + Alternate to `r`. Builds a linear space of r + coordinates. Use with `dr` where `r0` is the starting + coordinate and `dr` the step. + rsrc + Sets the source reference on Chart Studio Cloud for + `r`. + selected + :class:`plotly.graph_objects.barpolar.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.barpolar.Stream` instance + or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a polar subplot. If "polar" (the default value), + the data refer to `layout.polar`. If "polar2", the data + refer to `layout.polar2`, and so on. + text + Sets hover text elements associated with each bar. If a + single string, the same string appears over all bars. + If an array of string, the items are mapped in order to + the this trace's coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + theta + Sets the angular coordinates + theta0 + Alternate to `theta`. Builds a linear space of theta + coordinates. Use with `dtheta` where `theta0` is the + starting coordinate and `dtheta` the step. + thetasrc + Sets the source reference on Chart Studio Cloud for + `theta`. + thetaunit + Sets the unit of input "theta" values. Has an effect + only when on "linear" angular axes. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.barpolar.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar angular width (in "thetaunit" units). + widthsrc + Sets the source reference on Chart Studio Cloud for + `width`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Barpolar + + new_trace = Barpolar( + base=base, + basesrc=basesrc, + customdata=customdata, + customdatasrc=customdatasrc, + dr=dr, + dtheta=dtheta, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + offset=offset, + offsetsrc=offsetsrc, + opacity=opacity, + r=r, + r0=r0, + rsrc=rsrc, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + subplot=subplot, + text=text, + textsrc=textsrc, + theta=theta, + theta0=theta0, + thetasrc=thetasrc, + thetaunit=thetaunit, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + width=width, + widthsrc=widthsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_box( + self, + alignmentgroup=None, + boxmean=None, + boxpoints=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + jitter=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + lowerfence=None, + lowerfencesrc=None, + marker=None, + mean=None, + meansrc=None, + median=None, + mediansrc=None, + meta=None, + metasrc=None, + name=None, + notched=None, + notchspan=None, + notchspansrc=None, + notchwidth=None, + offsetgroup=None, + opacity=None, + orientation=None, + pointpos=None, + q1=None, + q1src=None, + q3=None, + q3src=None, + quartilemethod=None, + sd=None, + sdmultiple=None, + sdsrc=None, + selected=None, + selectedpoints=None, + showlegend=None, + showwhiskers=None, + sizemode=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + upperfence=None, + upperfencesrc=None, + visible=None, + whiskerwidth=None, + width=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Box trace + + Each box spans from quartile 1 (Q1) to quartile 3 (Q3). The + second quartile (Q2, i.e. the median) is marked by a line + inside the box. The fences grow outward from the boxes' edges, + by default they span +/- 1.5 times the interquartile range + (IQR: Q3-Q1), The sample mean and standard deviation as well as + notches and the sample, outlier and suspected outliers points + can be optionally added to the box plot. The values and + positions corresponding to each boxes can be input using two + signatures. The first signature expects users to supply the + sample values in the `y` data array for vertical boxes (`x` for + horizontal boxes). By supplying an `x` (`y`) array, one box per + distinct `x` (`y`) value is drawn If no `x` (`y`) list is + provided, a single box is drawn. In this case, the box is + positioned with the trace `name` or with `x0` (`y0`) if + provided. The second signature expects users to supply the + boxes corresponding Q1, median and Q3 statistics in the `q1`, + `median` and `q3` data arrays respectively. Other box features + relying on statistics namely `lowerfence`, `upperfence`, + `notchspan` can be set directly by the users. To have plotly + compute them or to show sample points besides the boxes, users + can set the `y` data array for vertical boxes (`x` for + horizontal boxes) to a 2D array with the outer length + corresponding to the number of boxes in the traces and the + inner length corresponding the sample size. + + Parameters + ---------- + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + boxmean + If True, the mean of the box(es)' underlying + distribution is drawn as a dashed line inside the + box(es). If "sd" the standard deviation is also drawn. + Defaults to True when `mean` is set. Defaults to "sd" + when `sd` is set Otherwise defaults to False. + boxpoints + If "outliers", only the sample points lying outside the + whiskers are shown If "suspectedoutliers", the outlier + points are shown and points either less than 4*Q1-3*Q3 + or greater than 4*Q3-3*Q1 are highlighted (see + `outliercolor`) If "all", all sample points are shown + If False, only the box(es) are shown with no sample + points Defaults to "suspectedoutliers" when + `marker.outliercolor` or `marker.line.outliercolor` is + set. Defaults to "all" under the q1/median/q3 + signature. Otherwise defaults to "outliers". + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step for multi-box traces set + using q1/median/q3. + dy + Sets the y coordinate step for multi-box traces set + using q1/median/q3. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.box.Hoverlabel` instance + or dict with compatible properties + hoveron + Do the hover effects highlight individual boxes or + sample points or both? + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + jitter + Sets the amount of jitter in the sample points drawn. + If 0, the sample points align along the distribution + axis. If 1, the sample points are drawn in a random + jitter of width equal to the width of the box(es). + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.box.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.box.Line` instance or dict + with compatible properties + lowerfence + Sets the lower fence values. There should be as many + items as the number of boxes desired. This attribute + has effect only under the q1/median/q3 signature. If + `lowerfence` is not provided but a sample (in `y` or + `x`) is set, we compute the lower as the last sample + point below 1.5 times the IQR. + lowerfencesrc + Sets the source reference on Chart Studio Cloud for + `lowerfence`. + marker + :class:`plotly.graph_objects.box.Marker` instance or + dict with compatible properties + mean + Sets the mean values. There should be as many items as + the number of boxes desired. This attribute has effect + only under the q1/median/q3 signature. If `mean` is not + provided but a sample (in `y` or `x`) is set, we + compute the mean for each box using the sample values. + meansrc + Sets the source reference on Chart Studio Cloud for + `mean`. + median + Sets the median values. There should be as many items + as the number of boxes desired. + mediansrc + Sets the source reference on Chart Studio Cloud for + `median`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. For box traces, the name will + also be used for the position coordinate, if `x` and + `x0` (`y` and `y0` if horizontal) are missing and the + position axis is categorical + notched + Determines whether or not notches are drawn. Notches + displays a confidence interval around the median. We + compute the confidence interval as median +/- 1.57 * + IQR / sqrt(N), where IQR is the interquartile range and + N is the sample size. If two boxes' notches do not + overlap there is 95% confidence their medians differ. + See https://sites.google.com/site/davidsstatistics/home + /notched-box-plots for more info. Defaults to False + unless `notchwidth` or `notchspan` is set. + notchspan + Sets the notch span from the boxes' `median` values. + There should be as many items as the number of boxes + desired. This attribute has effect only under the + q1/median/q3 signature. If `notchspan` is not provided + but a sample (in `y` or `x`) is set, we compute it as + 1.57 * IQR / sqrt(N), where N is the sample size. + notchspansrc + Sets the source reference on Chart Studio Cloud for + `notchspan`. + notchwidth + Sets the width of the notches relative to the box + width. For example, with 0, the notches are as wide as + the box(es). + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the box(es). If "v" ("h"), the + distribution is visualized along the vertical + (horizontal). + pointpos + Sets the position of the sample points in relation to + the box(es). If 0, the sample points are places over + the center of the box(es). Positive (negative) values + correspond to positions to the right (left) for + vertical boxes and above (below) for horizontal boxes + q1 + Sets the Quartile 1 values. There should be as many + items as the number of boxes desired. + q1src + Sets the source reference on Chart Studio Cloud for + `q1`. + q3 + Sets the Quartile 3 values. There should be as many + items as the number of boxes desired. + q3src + Sets the source reference on Chart Studio Cloud for + `q3`. + quartilemethod + Sets the method used to compute the sample's Q1 and Q3 + quartiles. The "linear" method uses the 25th percentile + for Q1 and 75th percentile for Q3 as computed using + method #10 (listed on + http://jse.amstat.org/v14n3/langford.html). The + "exclusive" method uses the median to divide the + ordered dataset into two halves if the sample is odd, + it does not include the median in either half - Q1 is + then the median of the lower half and Q3 the median of + the upper half. The "inclusive" method also uses the + median to divide the ordered dataset into two halves + but if the sample is odd, it includes the median in + both halves - Q1 is then the median of the lower half + and Q3 the median of the upper half. + sd + Sets the standard deviation values. There should be as + many items as the number of boxes desired. This + attribute has effect only under the q1/median/q3 + signature. If `sd` is not provided but a sample (in `y` + or `x`) is set, we compute the standard deviation for + each box using the sample values. + sdmultiple + Scales the box size when sizemode=sd Allowing boxes to + be drawn across any stddev range For example 1-stddev, + 3-stddev, 5-stddev + sdsrc + Sets the source reference on Chart Studio Cloud for + `sd`. + selected + :class:`plotly.graph_objects.box.Selected` instance or + dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showwhiskers + Determines whether or not whiskers are visible. + Defaults to true for `sizemode` "quartiles", false for + "sd". + sizemode + Sets the upper and lower bound for the boxes quartiles + means box is drawn between Q1 and Q3 SD means the box + is drawn between Mean +- Standard Deviation Argument + sdmultiple (default 1) to scale the box size So it + could be drawn 1-stddev, 3-stddev etc + stream + :class:`plotly.graph_objects.box.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with each sample + value. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.box.Unselected` instance + or dict with compatible properties + upperfence + Sets the upper fence values. There should be as many + items as the number of boxes desired. This attribute + has effect only under the q1/median/q3 signature. If + `upperfence` is not provided but a sample (in `y` or + `x`) is set, we compute the upper as the last sample + point above 1.5 times the IQR. + upperfencesrc + Sets the source reference on Chart Studio Cloud for + `upperfence`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + whiskerwidth + Sets the width of the whiskers relative to the box + width. For example, with 1, the whiskers are as wide as + the box(es). + width + Sets the width of the box in data coordinate If 0 + (default value) the width is automatically selected + based on the positions of other box traces in the same + subplot. + x + Sets the x sample data or coordinates. See overview for + more info. + x0 + Sets the x coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y sample data or coordinates. See overview for + more info. + y0 + Sets the y coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Box + + new_trace = Box( + alignmentgroup=alignmentgroup, + boxmean=boxmean, + boxpoints=boxpoints, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + jitter=jitter, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + lowerfence=lowerfence, + lowerfencesrc=lowerfencesrc, + marker=marker, + mean=mean, + meansrc=meansrc, + median=median, + mediansrc=mediansrc, + meta=meta, + metasrc=metasrc, + name=name, + notched=notched, + notchspan=notchspan, + notchspansrc=notchspansrc, + notchwidth=notchwidth, + offsetgroup=offsetgroup, + opacity=opacity, + orientation=orientation, + pointpos=pointpos, + q1=q1, + q1src=q1src, + q3=q3, + q3src=q3src, + quartilemethod=quartilemethod, + sd=sd, + sdmultiple=sdmultiple, + sdsrc=sdsrc, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + showwhiskers=showwhiskers, + sizemode=sizemode, + stream=stream, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + upperfence=upperfence, + upperfencesrc=upperfencesrc, + visible=visible, + whiskerwidth=whiskerwidth, + width=width, + x=x, + x0=x0, + xaxis=xaxis, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + y=y, + y0=y0, + yaxis=yaxis, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_candlestick( + self, + close=None, + closesrc=None, + customdata=None, + customdatasrc=None, + decreasing=None, + high=None, + highsrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + increasing=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + low=None, + lowsrc=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + open=None, + opensrc=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + visible=None, + whiskerwidth=None, + x=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + yaxis=None, + yhoverformat=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Candlestick trace + + The candlestick is a style of financial chart describing open, + high, low and close for a given `x` coordinate (most likely + time). The boxes represent the spread between the `open` and + `close` values and the lines represent the spread between the + `low` and `high` values Sample points where the close value is + higher (lower) then the open value are called increasing + (decreasing). By default, increasing candles are drawn in green + whereas decreasing are drawn in red. + + Parameters + ---------- + close + Sets the close values. + closesrc + Sets the source reference on Chart Studio Cloud for + `close`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + decreasing + :class:`plotly.graph_objects.candlestick.Decreasing` + instance or dict with compatible properties + high + Sets the high values. + highsrc + Sets the source reference on Chart Studio Cloud for + `high`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.candlestick.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `open`, `high`, `low` and `close`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + increasing + :class:`plotly.graph_objects.candlestick.Increasing` + instance or dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.candlestick.Legendgrouptit + le` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.candlestick.Line` instance + or dict with compatible properties + low + Sets the low values. + lowsrc + Sets the source reference on Chart Studio Cloud for + `low`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + open + Sets the open values. + opensrc + Sets the source reference on Chart Studio Cloud for + `open`. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.candlestick.Stream` + instance or dict with compatible properties + text + Sets hover text elements associated with each sample + point. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to this trace's sample points. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + whiskerwidth + Sets the width of the whiskers relative to the box + width. For example, with 1, the whiskers are as wide as + the box(es). + x + Sets the x coordinates. If absent, linear coordinate + will be generated. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Candlestick + + new_trace = Candlestick( + close=close, + closesrc=closesrc, + customdata=customdata, + customdatasrc=customdatasrc, + decreasing=decreasing, + high=high, + highsrc=highsrc, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + increasing=increasing, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + low=low, + lowsrc=lowsrc, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + open=open, + opensrc=opensrc, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + visible=visible, + whiskerwidth=whiskerwidth, + x=x, + xaxis=xaxis, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + yaxis=yaxis, + yhoverformat=yhoverformat, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_carpet( + self, + a=None, + a0=None, + aaxis=None, + asrc=None, + b=None, + b0=None, + baxis=None, + bsrc=None, + carpet=None, + cheaterslope=None, + color=None, + customdata=None, + customdatasrc=None, + da=None, + db=None, + font=None, + ids=None, + idssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + stream=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xaxis=None, + xsrc=None, + y=None, + yaxis=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Carpet trace + + The data describing carpet axis layout is set in `y` and + (optionally) also `x`. If only `y` is present, `x` the plot is + interpreted as a cheater plot and is filled in using the `y` + values. `x` and `y` may either be 2D arrays matching with each + dimension matching that of `a` and `b`, or they may be 1D + arrays with total length equal to that of `a` and `b`. + + Parameters + ---------- + a + An array containing values of the first parameter value + a0 + Alternate to `a`. Builds a linear space of a + coordinates. Use with `da` where `a0` is the starting + coordinate and `da` the step. + aaxis + :class:`plotly.graph_objects.carpet.Aaxis` instance or + dict with compatible properties + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + b + A two dimensional array of y coordinates at each carpet + point. + b0 + Alternate to `b`. Builds a linear space of a + coordinates. Use with `db` where `b0` is the starting + coordinate and `db` the step. + baxis + :class:`plotly.graph_objects.carpet.Baxis` instance or + dict with compatible properties + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + carpet + An identifier for this carpet, so that `scattercarpet` + and `contourcarpet` traces can specify a carpet plot on + which they lie + cheaterslope + The shift applied to each successive row of data in + creating a cheater plot. Only used if `x` is been + omitted. + color + Sets default for all colors associated with this axis + all at once: line, font, tick, and grid colors. Grid + color is lightened by blending this with the plot + background Individual pieces can override this. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + da + Sets the a coordinate step. See `a0` for more info. + db + Sets the b coordinate step. See `b0` for more info. + font + The default font used for axis & tick labels on this + carpet + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.carpet.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + stream + :class:`plotly.graph_objects.carpet.Stream` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + A two dimensional array of x coordinates at each carpet + point. If omitted, the plot is a cheater plot and the + xaxis is hidden by default. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + A two dimensional array of y coordinates at each carpet + point. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Carpet + + new_trace = Carpet( + a=a, + a0=a0, + aaxis=aaxis, + asrc=asrc, + b=b, + b0=b0, + baxis=baxis, + bsrc=bsrc, + carpet=carpet, + cheaterslope=cheaterslope, + color=color, + customdata=customdata, + customdatasrc=customdatasrc, + da=da, + db=db, + font=font, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + stream=stream, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + xaxis=xaxis, + xsrc=xsrc, + y=y, + yaxis=yaxis, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_choropleth( + self, + autocolorscale=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + featureidkey=None, + geo=None, + geojson=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + locationmode=None, + locations=None, + locationssrc=None, + marker=None, + meta=None, + metasrc=None, + name=None, + reversescale=None, + selected=None, + selectedpoints=None, + showlegend=None, + showscale=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Choropleth trace + + The data that describes the choropleth value-to-color mapping + is set in `z`. The geographic locations corresponding to each + value in `z` are set in `locations`. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.choropleth.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. Only + has an effect when `geojson` is set. Support nested + property, for example "properties.name". + geo + Sets a reference between this trace's geospatial + coordinates and a geographic map. If "geo" (the default + value), the geospatial coordinates refer to + `layout.geo`. If "geo2", the geospatial coordinates + refer to `layout.geo2`, and so on. + geojson + Sets optional GeoJSON data associated with this trace. + If not given, the features on the base map are used. It + can be set as a valid GeoJSON object or as a URL + string. Note that we only accept GeoJSONs of type + "FeatureCollection" or "Feature" with geometries of + type "Polygon" or "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.choropleth.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.choropleth.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + locationmode + The library used by the *country names* `locationmode` + option is changing in an upcoming version. Country + names in existing plots may not work in the new + version. Determines the set of locations used to match + entries in `locations` to regions on the map. Values + "ISO-3", "USA-states", *country names* correspond to + features on the base map and value "geojson-id" + corresponds to features from a custom GeoJSON linked to + the `geojson` attribute. + locations + Sets the coordinates via location IDs or names. See + `locationmode` for more info. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + marker + :class:`plotly.graph_objects.choropleth.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + selected + :class:`plotly.graph_objects.choropleth.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.choropleth.Stream` + instance or dict with compatible properties + text + Sets the text elements associated with each location. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.choropleth.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the color values. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Choropleth + + new_trace = Choropleth( + autocolorscale=autocolorscale, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + featureidkey=featureidkey, + geo=geo, + geojson=geojson, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + locationmode=locationmode, + locations=locations, + locationssrc=locationssrc, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + reversescale=reversescale, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + showscale=showscale, + stream=stream, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + z=z, + zauto=zauto, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_choroplethmap( + self, + autocolorscale=None, + below=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + featureidkey=None, + geojson=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + locations=None, + locationssrc=None, + marker=None, + meta=None, + metasrc=None, + name=None, + reversescale=None, + selected=None, + selectedpoints=None, + showlegend=None, + showscale=None, + stream=None, + subplot=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Choroplethmap trace + + GeoJSON features to be filled are set in `geojson` The data + that describes the choropleth value-to-color mapping is set in + `locations` and `z`. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the choropleth polygons will be inserted + before the layer with the specified ID. By default, + choroplethmap traces are placed above the water layers. + If set to '', the layer will be inserted above every + existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.choroplethmap.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. + Support nested property, for example "properties.name". + geojson + Sets the GeoJSON data associated with this trace. It + can be set as a valid GeoJSON object or as a URL + string. Note that we only accept GeoJSONs of type + "FeatureCollection" or "Feature" with geometries of + type "Polygon" or "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.choroplethmap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `properties` Anything contained in tag + `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.choroplethmap.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + locations + Sets which features found in "geojson" to plot using + their feature `id` field. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + marker + :class:`plotly.graph_objects.choroplethmap.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + selected + :class:`plotly.graph_objects.choroplethmap.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.choroplethmap.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a map subplot. If "map" (the default value), the + data refer to `layout.map`. If "map2", the data refer + to `layout.map2`, and so on. + text + Sets the text elements associated with each location. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.choroplethmap.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the color values. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Choroplethmap + + new_trace = Choroplethmap( + autocolorscale=autocolorscale, + below=below, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + featureidkey=featureidkey, + geojson=geojson, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + locations=locations, + locationssrc=locationssrc, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + reversescale=reversescale, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + showscale=showscale, + stream=stream, + subplot=subplot, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + z=z, + zauto=zauto, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_choroplethmapbox( + self, + autocolorscale=None, + below=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + featureidkey=None, + geojson=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + locations=None, + locationssrc=None, + marker=None, + meta=None, + metasrc=None, + name=None, + reversescale=None, + selected=None, + selectedpoints=None, + showlegend=None, + showscale=None, + stream=None, + subplot=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Choroplethmapbox trace + + "choroplethmapbox" trace is deprecated! Please consider + switching to the "choroplethmap" trace type and `map` subplots. + Learn more at: https://plotly.com/python/maplibre-migration/ as + well as https://plotly.com/javascript/maplibre-migration/ + GeoJSON features to be filled are set in `geojson` The data + that describes the choropleth value-to-color mapping is set in + `locations` and `z`. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the choropleth polygons will be inserted + before the layer with the specified ID. By default, + choroplethmapbox traces are placed above the water + layers. If set to '', the layer will be inserted above + every existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.choroplethmapbox.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. + Support nested property, for example "properties.name". + geojson + Sets the GeoJSON data associated with this trace. It + can be set as a valid GeoJSON object or as a URL + string. Note that we only accept GeoJSONs of type + "FeatureCollection" or "Feature" with geometries of + type "Polygon" or "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.choroplethmapbox.Hoverlabe + l` instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `properties` Anything contained in tag + `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.choroplethmapbox.Legendgro + uptitle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + locations + Sets which features found in "geojson" to plot using + their feature `id` field. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + marker + :class:`plotly.graph_objects.choroplethmapbox.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + selected + :class:`plotly.graph_objects.choroplethmapbox.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.choroplethmapbox.Stream` + instance or dict with compatible properties + subplot + mapbox subplots and traces are deprecated! Please + consider switching to `map` subplots and traces. Learn + more at: https://plotly.com/python/maplibre-migration/ + as well as https://plotly.com/javascript/maplibre- + migration/ Sets a reference between this trace's data + coordinates and a mapbox subplot. If "mapbox" (the + default value), the data refer to `layout.mapbox`. If + "mapbox2", the data refer to `layout.mapbox2`, and so + on. + text + Sets the text elements associated with each location. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.choroplethmapbox.Unselecte + d` instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the color values. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Choroplethmapbox + + new_trace = Choroplethmapbox( + autocolorscale=autocolorscale, + below=below, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + featureidkey=featureidkey, + geojson=geojson, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + locations=locations, + locationssrc=locationssrc, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + reversescale=reversescale, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + showscale=showscale, + stream=stream, + subplot=subplot, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + z=z, + zauto=zauto, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_cone( + self, + anchor=None, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + sizemode=None, + sizeref=None, + stream=None, + text=None, + textsrc=None, + u=None, + uhoverformat=None, + uid=None, + uirevision=None, + usrc=None, + v=None, + vhoverformat=None, + visible=None, + vsrc=None, + w=None, + whoverformat=None, + wsrc=None, + x=None, + xhoverformat=None, + xsrc=None, + y=None, + yhoverformat=None, + ysrc=None, + z=None, + zhoverformat=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Cone trace + + Use cone traces to visualize vector fields. Specify a vector + field using 6 1D arrays, 3 position arrays `x`, `y` and `z` and + 3 vector component arrays `u`, `v`, `w`. The cones are drawn + exactly at the positions given by `x`, `y` and `z`. + + Parameters + ---------- + anchor + Sets the cones' anchor with respect to their x/y/z + positions. Note that "cm" denote the cone's center of + mass which corresponds to 1/4 from the tail to tip. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here u/v/w norm) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmin` + must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as u/v/w norm. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmax` + must be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.cone.ColorBar` instance or + dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.cone.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `norm` Anything contained in tag `` + is displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.cone.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.cone.Lighting` instance or + dict with compatible properties + lightposition + :class:`plotly.graph_objects.cone.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + sizemode + Determines whether `sizeref` is set as a "scaled" (i.e + unitless) scalar (normalized by the max u/v/w norm in + the vector field) or as "absolute" value (in the same + units as the vector field). To display sizes in actual + vector length use "raw". + sizeref + Adjusts the cone size scaling. The size of the cones is + determined by their u/v/w norm multiplied a factor and + `sizeref`. This factor (computed internally) + corresponds to the minimum "time" to travel across two + successive x/y/z positions at the average velocity of + those two successive positions. All cones in a given + trace use the same factor. With `sizemode` set to + "raw", its default value is 1. With `sizemode` set to + "scaled", `sizeref` is unitless, its default value is + 0.5. With `sizemode` set to "absolute", `sizeref` has + the same units as the u/v/w vector field, its the + default value is half the sample's maximum vector norm. + stream + :class:`plotly.graph_objects.cone.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with the cones. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + u + Sets the x components of the vector field. + uhoverformat + Sets the hover text formatting rulefor `u` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + usrc + Sets the source reference on Chart Studio Cloud for + `u`. + v + Sets the y components of the vector field. + vhoverformat + Sets the hover text formatting rulefor `v` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + vsrc + Sets the source reference on Chart Studio Cloud for + `v`. + w + Sets the z components of the vector field. + whoverformat + Sets the hover text formatting rulefor `w` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + wsrc + Sets the source reference on Chart Studio Cloud for + `w`. + x + Sets the x coordinates of the vector field and of the + displayed cones. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates of the vector field and of the + displayed cones. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates of the vector field and of the + displayed cones. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Cone + + new_trace = Cone( + anchor=anchor, + autocolorscale=autocolorscale, + cauto=cauto, + cmax=cmax, + cmid=cmid, + cmin=cmin, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lighting=lighting, + lightposition=lightposition, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + reversescale=reversescale, + scene=scene, + showlegend=showlegend, + showscale=showscale, + sizemode=sizemode, + sizeref=sizeref, + stream=stream, + text=text, + textsrc=textsrc, + u=u, + uhoverformat=uhoverformat, + uid=uid, + uirevision=uirevision, + usrc=usrc, + v=v, + vhoverformat=vhoverformat, + visible=visible, + vsrc=vsrc, + w=w, + whoverformat=whoverformat, + wsrc=wsrc, + x=x, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zhoverformat=zhoverformat, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_contour( + self, + autocolorscale=None, + autocontour=None, + coloraxis=None, + colorbar=None, + colorscale=None, + connectgaps=None, + contours=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoverongaps=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + meta=None, + metasrc=None, + name=None, + ncontours=None, + opacity=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + text=None, + textfont=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + transpose=None, + uid=None, + uirevision=None, + visible=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + xtype=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + ytype=None, + z=None, + zauto=None, + zhoverformat=None, + zmax=None, + zmid=None, + zmin=None, + zorder=None, + zsrc=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Contour trace + + The data from which contour lines are computed is set in `z`. + Data in `z` must be a 2D list of numbers. Say that `z` has N + rows and M columns, then by default, these N rows correspond to + N y coordinates (set in `y` or auto-generated) and the M + columns correspond to M x coordinates (set in `x` or auto- + generated). By setting `transpose` to True, the above behavior + is flipped. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + autocontour + Determines whether or not the contour level attributes + are picked by an algorithm. If True, the number of + contour levels can be set in `ncontours`. If False, set + the contour level attributes in `contours`. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.contour.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data are filled in. It is defaulted + to true if `z` is a one dimensional array otherwise it + is defaulted to false. + contours + :class:`plotly.graph_objects.contour.Contours` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + fillcolor + Sets the fill color if `contours.type` is "constraint". + Defaults to a half-transparent variant of the line + color, marker color, or marker line color, whichever is + available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.contour.Hoverlabel` + instance or dict with compatible properties + hoverongaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data have hover labels associated + with them. + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.contour.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.contour.Line` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + ncontours + Sets the maximum number of contour levels. The actual + number of contours will be chosen automatically to be + less than or equal to the value of `ncontours`. Has an + effect only if `autocontour` is True or if + `contours.size` is missing. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.contour.Stream` instance + or dict with compatible properties + text + Sets the text elements associated with each z value. + textfont + For this trace it only has an effect if `coloring` is + set to "heatmap". Sets the text font. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + For this trace it only has an effect if `coloring` is + set to "heatmap". Template string used for rendering + the information text that appears on points. Note that + this will override `textinfo`. Variables are inserted + using %{variable}, for example "y: %{y}". Numbers are + formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `x`, `y`, `z` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + transpose + Transposes the z data. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + xtype + If "array", the heatmap's x coordinates are given by + "x" (the default behavior when `x` is provided). If + "scaled", the heatmap's x coordinates are given by "x0" + and "dx" (the default behavior when `x` is not + provided). + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + ytype + If "array", the heatmap's y coordinates are given by + "y" (the default behavior when `y` is provided) If + "scaled", the heatmap's y coordinates are given by "y0" + and "dy" (the default behavior when `y` is not + provided) + z + Sets the z data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Contour + + new_trace = Contour( + autocolorscale=autocolorscale, + autocontour=autocontour, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + connectgaps=connectgaps, + contours=contours, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoverongaps=hoverongaps, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + meta=meta, + metasrc=metasrc, + name=name, + ncontours=ncontours, + opacity=opacity, + reversescale=reversescale, + showlegend=showlegend, + showscale=showscale, + stream=stream, + text=text, + textfont=textfont, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + transpose=transpose, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + x0=x0, + xaxis=xaxis, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + xtype=xtype, + y=y, + y0=y0, + yaxis=yaxis, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + ytype=ytype, + z=z, + zauto=zauto, + zhoverformat=zhoverformat, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zorder=zorder, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_contourcarpet( + self, + a=None, + a0=None, + asrc=None, + atype=None, + autocolorscale=None, + autocontour=None, + b=None, + b0=None, + bsrc=None, + btype=None, + carpet=None, + coloraxis=None, + colorbar=None, + colorscale=None, + contours=None, + customdata=None, + customdatasrc=None, + da=None, + db=None, + fillcolor=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + meta=None, + metasrc=None, + name=None, + ncontours=None, + opacity=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + text=None, + textsrc=None, + transpose=None, + uid=None, + uirevision=None, + visible=None, + xaxis=None, + yaxis=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zorder=None, + zsrc=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Contourcarpet trace + + Plots contours on either the first carpet axis or the carpet + axis with a matching `carpet` attribute. Data `z` is + interpreted as matching that of the corresponding carpet axis. + + Parameters + ---------- + a + Sets the x coordinates. + a0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + atype + If "array", the heatmap's x coordinates are given by + "x" (the default behavior when `x` is provided). If + "scaled", the heatmap's x coordinates are given by "x0" + and "dx" (the default behavior when `x` is not + provided). + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + autocontour + Determines whether or not the contour level attributes + are picked by an algorithm. If True, the number of + contour levels can be set in `ncontours`. If False, set + the contour level attributes in `contours`. + b + Sets the y coordinates. + b0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + btype + If "array", the heatmap's y coordinates are given by + "y" (the default behavior when `y` is provided) If + "scaled", the heatmap's y coordinates are given by "y0" + and "dy" (the default behavior when `y` is not + provided) + carpet + The `carpet` of the carpet axes on which this contour + trace lies + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.contourcarpet.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contours + :class:`plotly.graph_objects.contourcarpet.Contours` + instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + da + Sets the x coordinate step. See `x0` for more info. + db + Sets the y coordinate step. See `y0` for more info. + fillcolor + Sets the fill color if `contours.type` is "constraint". + Defaults to a half-transparent variant of the line + color, marker color, or marker line color, whichever is + available. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.contourcarpet.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.contourcarpet.Line` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + ncontours + Sets the maximum number of contour levels. The actual + number of contours will be chosen automatically to be + less than or equal to the value of `ncontours`. Has an + effect only if `autocontour` is True or if + `contours.size` is missing. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.contourcarpet.Stream` + instance or dict with compatible properties + text + Sets the text elements associated with each z value. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + transpose + Transposes the z data. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + z + Sets the z data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Contourcarpet + + new_trace = Contourcarpet( + a=a, + a0=a0, + asrc=asrc, + atype=atype, + autocolorscale=autocolorscale, + autocontour=autocontour, + b=b, + b0=b0, + bsrc=bsrc, + btype=btype, + carpet=carpet, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + contours=contours, + customdata=customdata, + customdatasrc=customdatasrc, + da=da, + db=db, + fillcolor=fillcolor, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + meta=meta, + metasrc=metasrc, + name=name, + ncontours=ncontours, + opacity=opacity, + reversescale=reversescale, + showlegend=showlegend, + showscale=showscale, + stream=stream, + text=text, + textsrc=textsrc, + transpose=transpose, + uid=uid, + uirevision=uirevision, + visible=visible, + xaxis=xaxis, + yaxis=yaxis, + z=z, + zauto=zauto, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zorder=zorder, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_densitymap( + self, + autocolorscale=None, + below=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + lat=None, + latsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lon=None, + lonsrc=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + radius=None, + radiussrc=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + subplot=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + visible=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Densitymap trace + + Draws a bivariate kernel density estimation with a Gaussian + kernel from `lon` and `lat` coordinates and optional `z` values + using a colorscale. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the densitymap trace will be inserted + before the layer with the specified ID. By default, + densitymap traces are placed below the first layer of + type symbol If set to '', the layer will be inserted + above every existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.densitymap.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.densitymap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.densitymap.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + radius + Sets the radius of influence of one `lon` / `lat` point + in pixels. Increasing the value makes the densitymap + trace smoother, but less detailed. + radiussrc + Sets the source reference on Chart Studio Cloud for + `radius`. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.densitymap.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a map subplot. If "map" (the default value), the + data refer to `layout.map`. If "map2", the data refer + to `layout.map2`, and so on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the points' weight. For example, a value of 10 + would be equivalent to having 10 points of weight 1 in + the same spot + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Densitymap + + new_trace = Densitymap( + autocolorscale=autocolorscale, + below=below, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + lat=lat, + latsrc=latsrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lon=lon, + lonsrc=lonsrc, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + radius=radius, + radiussrc=radiussrc, + reversescale=reversescale, + showlegend=showlegend, + showscale=showscale, + stream=stream, + subplot=subplot, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + visible=visible, + z=z, + zauto=zauto, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_densitymapbox( + self, + autocolorscale=None, + below=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + lat=None, + latsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lon=None, + lonsrc=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + radius=None, + radiussrc=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + subplot=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + visible=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Densitymapbox trace + + "densitymapbox" trace is deprecated! Please consider switching + to the "densitymap" trace type and `map` subplots. Learn more + at: https://plotly.com/python/maplibre-migration/ as well as + https://plotly.com/javascript/maplibre-migration/ Draws a + bivariate kernel density estimation with a Gaussian kernel from + `lon` and `lat` coordinates and optional `z` values using a + colorscale. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the densitymapbox trace will be inserted + before the layer with the specified ID. By default, + densitymapbox traces are placed below the first layer + of type symbol If set to '', the layer will be inserted + above every existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.densitymapbox.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.densitymapbox.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.densitymapbox.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + radius + Sets the radius of influence of one `lon` / `lat` point + in pixels. Increasing the value makes the densitymapbox + trace smoother, but less detailed. + radiussrc + Sets the source reference on Chart Studio Cloud for + `radius`. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.densitymapbox.Stream` + instance or dict with compatible properties + subplot + mapbox subplots and traces are deprecated! Please + consider switching to `map` subplots and traces. Learn + more at: https://plotly.com/python/maplibre-migration/ + as well as https://plotly.com/javascript/maplibre- + migration/ Sets a reference between this trace's data + coordinates and a mapbox subplot. If "mapbox" (the + default value), the data refer to `layout.mapbox`. If + "mapbox2", the data refer to `layout.mapbox2`, and so + on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the points' weight. For example, a value of 10 + would be equivalent to having 10 points of weight 1 in + the same spot + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Densitymapbox + + new_trace = Densitymapbox( + autocolorscale=autocolorscale, + below=below, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + lat=lat, + latsrc=latsrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lon=lon, + lonsrc=lonsrc, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + radius=radius, + radiussrc=radiussrc, + reversescale=reversescale, + showlegend=showlegend, + showscale=showscale, + stream=stream, + subplot=subplot, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + visible=visible, + z=z, + zauto=zauto, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_funnel( + self, + alignmentgroup=None, + cliponaxis=None, + connector=None, + constraintext=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextanchor=None, + insidetextfont=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + offset=None, + offsetgroup=None, + opacity=None, + orientation=None, + outsidetextfont=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textangle=None, + textfont=None, + textinfo=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + visible=None, + width=None, + x=None, + x0=None, + xaxis=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Funnel trace + + Visualize stages in a process using length-encoded bars. This + trace can be used to show data in either a part-to-whole + representation wherein each item appears in a single stage, or + in a "drop-off" representation wherein each item appears in + each stage it traversed. See also the "funnelarea" trace type + for a different approach to visualizing funnel data. + + Parameters + ---------- + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + connector + :class:`plotly.graph_objects.funnel.Connector` instance + or dict with compatible properties + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.funnel.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `percentInitial`, `percentPrevious` and + `percentTotal`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.funnel.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.funnel.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the position where the bar is drawn (in position + axis units). In "group" barmode, traces that set + "offset" will be excluded and drawn in "overlay" mode + instead. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the funnels. With "v" ("h"), + the value of the each bar spans along the vertical + (horizontal). By default funnels are tend to be + oriented horizontally; unless only "y" array is + presented or orientation is set to "v". Also regarding + graphs including only 'horizontal' funnels, "autorange" + on the "y-axis" are set to "reversed". + outsidetextfont + Sets the font used for `text` lying outside the bar. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.funnel.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the font used for `text`. + textinfo + Determines which trace information appear on the graph. + In the case of having multiple funnels, percentages & + totals are computed separately (per trace). + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `percentInitial`, `percentPrevious`, + `percentTotal`, `label` and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar width (in position axis units). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Funnel + + new_trace = Funnel( + alignmentgroup=alignmentgroup, + cliponaxis=cliponaxis, + connector=connector, + constraintext=constraintext, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextanchor=insidetextanchor, + insidetextfont=insidetextfont, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + offset=offset, + offsetgroup=offsetgroup, + opacity=opacity, + orientation=orientation, + outsidetextfont=outsidetextfont, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textangle=textangle, + textfont=textfont, + textinfo=textinfo, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + visible=visible, + width=width, + x=x, + x0=x0, + xaxis=xaxis, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + y=y, + y0=y0, + yaxis=yaxis, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_funnelarea( + self, + aspectratio=None, + baseratio=None, + customdata=None, + customdatasrc=None, + dlabel=None, + domain=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextfont=None, + label0=None, + labels=None, + labelssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + scalegroup=None, + showlegend=None, + stream=None, + text=None, + textfont=None, + textinfo=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + title=None, + uid=None, + uirevision=None, + values=None, + valuessrc=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Funnelarea trace + + Visualize stages in a process using area-encoded trapezoids. + This trace can be used to show data in a part-to-whole + representation similar to a "pie" trace, wherein each item + appears in a single stage. See also the "funnel" trace type for + a different approach to visualizing funnel data. + + Parameters + ---------- + aspectratio + Sets the ratio between height and width + baseratio + Sets the ratio between bottom length and maximum top + length. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dlabel + Sets the label step. See `label0` for more info. + domain + :class:`plotly.graph_objects.funnelarea.Domain` + instance or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.funnelarea.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `text` and + `percent`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + label0 + Alternate to `labels`. Builds a numeric set of labels. + Use with `dlabel` where `label0` is the starting label + and `dlabel` the step. + labels + Sets the sector labels. If `labels` entries are + duplicated, we sum associated `values` or simply count + occurrences if `values` is not provided. For other + array attributes (including color) we use the first + non-empty entry among all occurrences of the label. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.funnelarea.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.funnelarea.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + scalegroup + If there are multiple funnelareas that should be sized + according to their totals, link them by providing a + non-empty group id here shared by every trace in the + same group. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.funnelarea.Stream` + instance or dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Specifies the location of the `textinfo`. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `text` and + `percent`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + title + :class:`plotly.graph_objects.funnelarea.Title` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values of the sectors. If omitted, we count + occurrences of each label. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Funnelarea + + new_trace = Funnelarea( + aspectratio=aspectratio, + baseratio=baseratio, + customdata=customdata, + customdatasrc=customdatasrc, + dlabel=dlabel, + domain=domain, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextfont=insidetextfont, + label0=label0, + labels=labels, + labelssrc=labelssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + scalegroup=scalegroup, + showlegend=showlegend, + stream=stream, + text=text, + textfont=textfont, + textinfo=textinfo, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + title=title, + uid=uid, + uirevision=uirevision, + values=values, + valuessrc=valuessrc, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_heatmap( + self, + autocolorscale=None, + coloraxis=None, + colorbar=None, + colorscale=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoverongaps=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + text=None, + textfont=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + transpose=None, + uid=None, + uirevision=None, + visible=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xgap=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + xtype=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + ygap=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + ytype=None, + z=None, + zauto=None, + zhoverformat=None, + zmax=None, + zmid=None, + zmin=None, + zorder=None, + zsmooth=None, + zsrc=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Heatmap trace + + The data that describes the heatmap value-to-color mapping is + set in `z`. Data in `z` can either be a 2D list of values + (ragged or not) or a 1D array of values. In the case where `z` + is a 2D list, say that `z` has N rows and M columns. Then, by + default, the resulting heatmap will have N partitions along the + y axis and M partitions along the x axis. In other words, the + i-th row/ j-th column cell in `z` is mapped to the i-th + partition of the y axis (starting from the bottom of the plot) + and the j-th partition of the x-axis (starting from the left of + the plot). This behavior can be flipped by using `transpose`. + Moreover, `x` (`y`) can be provided with M or M+1 (N or N+1) + elements. If M (N), then the coordinates correspond to the + center of the heatmap cells and the cells have equal width. If + M+1 (N+1), then the coordinates correspond to the edges of the + heatmap cells. In the case where `z` is a 1D list, the x and y + coordinates must be provided in `x` and `y` respectively to + form data triplets. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.heatmap.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data are filled in. It is defaulted + to true if `z` is a one dimensional array and `zsmooth` + is not false; otherwise it is defaulted to false. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.heatmap.Hoverlabel` + instance or dict with compatible properties + hoverongaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data have hover labels associated + with them. + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.heatmap.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.heatmap.Stream` instance + or dict with compatible properties + text + Sets the text elements associated with each z value. + textfont + Sets the text font. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `x`, `y`, `z` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + transpose + Transposes the z data. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xgap + Sets the horizontal gap (in pixels) between bricks. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + xtype + If "array", the heatmap's x coordinates are given by + "x" (the default behavior when `x` is provided). If + "scaled", the heatmap's x coordinates are given by "x0" + and "dx" (the default behavior when `x` is not + provided). + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + ygap + Sets the vertical gap (in pixels) between bricks. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + ytype + If "array", the heatmap's y coordinates are given by + "y" (the default behavior when `y` is provided) If + "scaled", the heatmap's y coordinates are given by "y0" + and "dy" (the default behavior when `y` is not + provided) + z + Sets the z data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsmooth + Picks a smoothing algorithm use to smooth `z` data. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Heatmap + + new_trace = Heatmap( + autocolorscale=autocolorscale, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoverongaps=hoverongaps, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + reversescale=reversescale, + showlegend=showlegend, + showscale=showscale, + stream=stream, + text=text, + textfont=textfont, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + transpose=transpose, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + x0=x0, + xaxis=xaxis, + xcalendar=xcalendar, + xgap=xgap, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + xtype=xtype, + y=y, + y0=y0, + yaxis=yaxis, + ycalendar=ycalendar, + ygap=ygap, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + ytype=ytype, + z=z, + zauto=zauto, + zhoverformat=zhoverformat, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zorder=zorder, + zsmooth=zsmooth, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_histogram( + self, + alignmentgroup=None, + autobinx=None, + autobiny=None, + bingroup=None, + cliponaxis=None, + constraintext=None, + cumulative=None, + customdata=None, + customdatasrc=None, + error_x=None, + error_y=None, + histfunc=None, + histnorm=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextanchor=None, + insidetextfont=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + nbinsx=None, + nbinsy=None, + offsetgroup=None, + opacity=None, + orientation=None, + outsidetextfont=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textangle=None, + textfont=None, + textposition=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + x=None, + xaxis=None, + xbins=None, + xcalendar=None, + xhoverformat=None, + xsrc=None, + y=None, + yaxis=None, + ybins=None, + ycalendar=None, + yhoverformat=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Histogram trace + + The sample data from which statistics are computed is set in + `x` for vertically spanning histograms and in `y` for + horizontally spanning histograms. Binning options are set + `xbins` and `ybins` respectively if no aggregation data is + provided. + + Parameters + ---------- + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + autobinx + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobinx` is not needed. + However, we accept `autobinx: true` or `false` and will + update `xbins` accordingly before deleting `autobinx` + from the trace. + autobiny + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobiny` is not needed. + However, we accept `autobiny: true` or `false` and will + update `ybins` accordingly before deleting `autobiny` + from the trace. + bingroup + Set a group of histogram traces which will have + compatible bin settings. Note that traces on the same + subplot and with the same "orientation" under `barmode` + "stack", "relative" and "group" are forced into the + same bingroup, Using `bingroup`, traces under `barmode` + "overlay" and on different axes (of the same axis type) + can have compatible bin settings. Note that histogram + and histogram2d* trace can share the same `bingroup` + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + cumulative + :class:`plotly.graph_objects.histogram.Cumulative` + instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + error_x + :class:`plotly.graph_objects.histogram.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.histogram.ErrorY` instance + or dict with compatible properties + histfunc + Specifies the binning function used for this histogram + trace. If "count", the histogram values are computed by + counting the number of values lying inside each bin. If + "sum", "avg", "min", "max", the histogram values are + computed using the sum, the average, the minimum or the + maximum of the values lying inside each bin + respectively. + histnorm + Specifies the type of normalization used for this + histogram trace. If "", the span of each bar + corresponds to the number of occurrences (i.e. the + number of data points lying inside the bins). If + "percent" / "probability", the span of each bar + corresponds to the percentage / fraction of occurrences + with respect to the total number of sample points + (here, the sum of all bin HEIGHTS equals 100% / 1). If + "density", the span of each bar corresponds to the + number of occurrences in a bin divided by the size of + the bin interval (here, the sum of all bin AREAS equals + the total number of sample points). If *probability + density*, the area of each bar corresponds to the + probability that an event will fall into the + corresponding bin (here, the sum of all bin AREAS + equals 1). + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.histogram.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `binNumber` Anything contained in tag + `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.histogram.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.histogram.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + nbinsx + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `xbins.size` is provided. + nbinsy + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `ybins.size` is provided. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the bars. With "v" ("h"), the + value of the each bar spans along the vertical + (horizontal). + outsidetextfont + Sets the font used for `text` lying outside the bar. + selected + :class:`plotly.graph_objects.histogram.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.histogram.Stream` instance + or dict with compatible properties + text + Sets hover text elements associated with each bar. If a + single string, the same string appears over all bars. + If an array of string, the items are mapped in order to + the this trace's coordinates. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the text font. + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label` and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.histogram.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the sample data to be binned on the x axis. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xbins + :class:`plotly.graph_objects.histogram.XBins` instance + or dict with compatible properties + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the sample data to be binned on the y axis. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ybins + :class:`plotly.graph_objects.histogram.YBins` instance + or dict with compatible properties + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Histogram + + new_trace = Histogram( + alignmentgroup=alignmentgroup, + autobinx=autobinx, + autobiny=autobiny, + bingroup=bingroup, + cliponaxis=cliponaxis, + constraintext=constraintext, + cumulative=cumulative, + customdata=customdata, + customdatasrc=customdatasrc, + error_x=error_x, + error_y=error_y, + histfunc=histfunc, + histnorm=histnorm, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextanchor=insidetextanchor, + insidetextfont=insidetextfont, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + nbinsx=nbinsx, + nbinsy=nbinsy, + offsetgroup=offsetgroup, + opacity=opacity, + orientation=orientation, + outsidetextfont=outsidetextfont, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textangle=textangle, + textfont=textfont, + textposition=textposition, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + x=x, + xaxis=xaxis, + xbins=xbins, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + yaxis=yaxis, + ybins=ybins, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_histogram2d( + self, + autobinx=None, + autobiny=None, + autocolorscale=None, + bingroup=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + histfunc=None, + histnorm=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + nbinsx=None, + nbinsy=None, + opacity=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + textfont=None, + texttemplate=None, + texttemplatefallback=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xaxis=None, + xbingroup=None, + xbins=None, + xcalendar=None, + xgap=None, + xhoverformat=None, + xsrc=None, + y=None, + yaxis=None, + ybingroup=None, + ybins=None, + ycalendar=None, + ygap=None, + yhoverformat=None, + ysrc=None, + z=None, + zauto=None, + zhoverformat=None, + zmax=None, + zmid=None, + zmin=None, + zsmooth=None, + zsrc=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Histogram2d trace + + The sample data from which statistics are computed is set in + `x` and `y` (where `x` and `y` represent marginal + distributions, binning is set in `xbins` and `ybins` in this + case) or `z` (where `z` represent the 2D distribution and + binning set, binning is set by `x` and `y` in this case). The + resulting distribution is visualized as a heatmap. + + Parameters + ---------- + autobinx + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobinx` is not needed. + However, we accept `autobinx: true` or `false` and will + update `xbins` accordingly before deleting `autobinx` + from the trace. + autobiny + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobiny` is not needed. + However, we accept `autobiny: true` or `false` and will + update `ybins` accordingly before deleting `autobiny` + from the trace. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + bingroup + Set the `xbingroup` and `ybingroup` default prefix For + example, setting a `bingroup` of 1 on two histogram2d + traces will make them their x-bins and y-bins match + separately. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.histogram2d.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + histfunc + Specifies the binning function used for this histogram + trace. If "count", the histogram values are computed by + counting the number of values lying inside each bin. If + "sum", "avg", "min", "max", the histogram values are + computed using the sum, the average, the minimum or the + maximum of the values lying inside each bin + respectively. + histnorm + Specifies the type of normalization used for this + histogram trace. If "", the span of each bar + corresponds to the number of occurrences (i.e. the + number of data points lying inside the bins). If + "percent" / "probability", the span of each bar + corresponds to the percentage / fraction of occurrences + with respect to the total number of sample points + (here, the sum of all bin HEIGHTS equals 100% / 1). If + "density", the span of each bar corresponds to the + number of occurrences in a bin divided by the size of + the bin interval (here, the sum of all bin AREAS equals + the total number of sample points). If *probability + density*, the area of each bar corresponds to the + probability that an event will fall into the + corresponding bin (here, the sum of all bin AREAS + equals 1). + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.histogram2d.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `z` Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.histogram2d.Legendgrouptit + le` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.histogram2d.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + nbinsx + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `xbins.size` is provided. + nbinsy + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `ybins.size` is provided. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.histogram2d.Stream` + instance or dict with compatible properties + textfont + Sets the text font. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `z` + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the sample data to be binned on the x axis. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xbingroup + Set a group of histogram traces which will have + compatible x-bin settings. Using `xbingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible x-bin settings. + Note that the same `xbingroup` value can be used to set + (1D) histogram `bingroup` + xbins + :class:`plotly.graph_objects.histogram2d.XBins` + instance or dict with compatible properties + xcalendar + Sets the calendar system to use with `x` date data. + xgap + Sets the horizontal gap (in pixels) between bricks. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the sample data to be binned on the y axis. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ybingroup + Set a group of histogram traces which will have + compatible y-bin settings. Using `ybingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible y-bin settings. + Note that the same `ybingroup` value can be used to set + (1D) histogram `bingroup` + ybins + :class:`plotly.graph_objects.histogram2d.YBins` + instance or dict with compatible properties + ycalendar + Sets the calendar system to use with `y` date data. + ygap + Sets the vertical gap (in pixels) between bricks. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the aggregation data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsmooth + Picks a smoothing algorithm use to smooth `z` data. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Histogram2d + + new_trace = Histogram2d( + autobinx=autobinx, + autobiny=autobiny, + autocolorscale=autocolorscale, + bingroup=bingroup, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + histfunc=histfunc, + histnorm=histnorm, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + nbinsx=nbinsx, + nbinsy=nbinsy, + opacity=opacity, + reversescale=reversescale, + showlegend=showlegend, + showscale=showscale, + stream=stream, + textfont=textfont, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + xaxis=xaxis, + xbingroup=xbingroup, + xbins=xbins, + xcalendar=xcalendar, + xgap=xgap, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + yaxis=yaxis, + ybingroup=ybingroup, + ybins=ybins, + ycalendar=ycalendar, + ygap=ygap, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zauto=zauto, + zhoverformat=zhoverformat, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zsmooth=zsmooth, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_histogram2dcontour( + self, + autobinx=None, + autobiny=None, + autocolorscale=None, + autocontour=None, + bingroup=None, + coloraxis=None, + colorbar=None, + colorscale=None, + contours=None, + customdata=None, + customdatasrc=None, + histfunc=None, + histnorm=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + name=None, + nbinsx=None, + nbinsy=None, + ncontours=None, + opacity=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + textfont=None, + texttemplate=None, + texttemplatefallback=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xaxis=None, + xbingroup=None, + xbins=None, + xcalendar=None, + xhoverformat=None, + xsrc=None, + y=None, + yaxis=None, + ybingroup=None, + ybins=None, + ycalendar=None, + yhoverformat=None, + ysrc=None, + z=None, + zauto=None, + zhoverformat=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Histogram2dContour trace + + The sample data from which statistics are computed is set in + `x` and `y` (where `x` and `y` represent marginal + distributions, binning is set in `xbins` and `ybins` in this + case) or `z` (where `z` represent the 2D distribution and + binning set, binning is set by `x` and `y` in this case). The + resulting distribution is visualized as a contour plot. + + Parameters + ---------- + autobinx + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobinx` is not needed. + However, we accept `autobinx: true` or `false` and will + update `xbins` accordingly before deleting `autobinx` + from the trace. + autobiny + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobiny` is not needed. + However, we accept `autobiny: true` or `false` and will + update `ybins` accordingly before deleting `autobiny` + from the trace. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + autocontour + Determines whether or not the contour level attributes + are picked by an algorithm. If True, the number of + contour levels can be set in `ncontours`. If False, set + the contour level attributes in `contours`. + bingroup + Set the `xbingroup` and `ybingroup` default prefix For + example, setting a `bingroup` of 1 on two histogram2d + traces will make them their x-bins and y-bins match + separately. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.histogram2dcontour.ColorBa + r` instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contours + :class:`plotly.graph_objects.histogram2dcontour.Contour + s` instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + histfunc + Specifies the binning function used for this histogram + trace. If "count", the histogram values are computed by + counting the number of values lying inside each bin. If + "sum", "avg", "min", "max", the histogram values are + computed using the sum, the average, the minimum or the + maximum of the values lying inside each bin + respectively. + histnorm + Specifies the type of normalization used for this + histogram trace. If "", the span of each bar + corresponds to the number of occurrences (i.e. the + number of data points lying inside the bins). If + "percent" / "probability", the span of each bar + corresponds to the percentage / fraction of occurrences + with respect to the total number of sample points + (here, the sum of all bin HEIGHTS equals 100% / 1). If + "density", the span of each bar corresponds to the + number of occurrences in a bin divided by the size of + the bin interval (here, the sum of all bin AREAS equals + the total number of sample points). If *probability + density*, the area of each bar corresponds to the + probability that an event will fall into the + corresponding bin (here, the sum of all bin AREAS + equals 1). + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.histogram2dcontour.Hoverla + bel` instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `z` Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.histogram2dcontour.Legendg + rouptitle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.histogram2dcontour.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.histogram2dcontour.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + nbinsx + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `xbins.size` is provided. + nbinsy + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `ybins.size` is provided. + ncontours + Sets the maximum number of contour levels. The actual + number of contours will be chosen automatically to be + less than or equal to the value of `ncontours`. Has an + effect only if `autocontour` is True or if + `contours.size` is missing. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.histogram2dcontour.Stream` + instance or dict with compatible properties + textfont + For this trace it only has an effect if `coloring` is + set to "heatmap". Sets the text font. + texttemplate + For this trace it only has an effect if `coloring` is + set to "heatmap". Template string used for rendering + the information text that appears on points. Note that + this will override `textinfo`. Variables are inserted + using %{variable}, for example "y: %{y}". Numbers are + formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `x`, `y`, `z` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the sample data to be binned on the x axis. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xbingroup + Set a group of histogram traces which will have + compatible x-bin settings. Using `xbingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible x-bin settings. + Note that the same `xbingroup` value can be used to set + (1D) histogram `bingroup` + xbins + :class:`plotly.graph_objects.histogram2dcontour.XBins` + instance or dict with compatible properties + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the sample data to be binned on the y axis. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ybingroup + Set a group of histogram traces which will have + compatible y-bin settings. Using `ybingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible y-bin settings. + Note that the same `ybingroup` value can be used to set + (1D) histogram `bingroup` + ybins + :class:`plotly.graph_objects.histogram2dcontour.YBins` + instance or dict with compatible properties + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the aggregation data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Histogram2dContour + + new_trace = Histogram2dContour( + autobinx=autobinx, + autobiny=autobiny, + autocolorscale=autocolorscale, + autocontour=autocontour, + bingroup=bingroup, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + contours=contours, + customdata=customdata, + customdatasrc=customdatasrc, + histfunc=histfunc, + histnorm=histnorm, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + nbinsx=nbinsx, + nbinsy=nbinsy, + ncontours=ncontours, + opacity=opacity, + reversescale=reversescale, + showlegend=showlegend, + showscale=showscale, + stream=stream, + textfont=textfont, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + xaxis=xaxis, + xbingroup=xbingroup, + xbins=xbins, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + yaxis=yaxis, + ybingroup=ybingroup, + ybins=ybins, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zauto=zauto, + zhoverformat=zhoverformat, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_icicle( + self, + branchvalues=None, + count=None, + customdata=None, + customdatasrc=None, + domain=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextfont=None, + labels=None, + labelssrc=None, + leaf=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + level=None, + marker=None, + maxdepth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + outsidetextfont=None, + parents=None, + parentssrc=None, + pathbar=None, + root=None, + sort=None, + stream=None, + text=None, + textfont=None, + textinfo=None, + textposition=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + tiling=None, + uid=None, + uirevision=None, + values=None, + valuessrc=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Icicle trace + + Visualize hierarchal data from leaves (and/or outer branches) + towards root with rectangles. The icicle sectors are determined + by the entries in "labels" or "ids" and in "parents". + + Parameters + ---------- + branchvalues + Determines how the items in `values` are summed. When + set to "total", items in `values` are taken to be value + of all its descendants. When set to "remainder", items + in `values` corresponding to the root and the branches + sectors are taken to be the extra part not part of the + sum of the values at their leaves. + count + Determines default for `values` when it is not + provided, by inferring a 1 for each of the "leaves" + and/or "branches", otherwise 0. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.icicle.Domain` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.icicle.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry` and `percentParent`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + labels + Sets the labels of each of the sectors. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + leaf + :class:`plotly.graph_objects.icicle.Leaf` instance or + dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.icicle.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + level + Sets the level from which this trace hierarchy is + rendered. Set `level` to `''` to start from the root + node in the hierarchy. Must be an "id" if `ids` is + filled in, otherwise plotly attempts to find a matching + item in `labels`. + marker + :class:`plotly.graph_objects.icicle.Marker` instance or + dict with compatible properties + maxdepth + Sets the number of rendered sectors from any given + `level`. Set `maxdepth` to "-1" to render all the + levels in the hierarchy. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. This option refers to the root of the hierarchy + presented on top left corner of a treemap graph. Please + note that if a hierarchy has multiple root nodes, this + option won't have any effect and `insidetextfont` would + be used. + parents + Sets the parent sectors for each of the sectors. Empty + string items '' are understood to reference the root + node in the hierarchy. If `ids` is filled, `parents` + items are understood to be "ids" themselves. When `ids` + is not set, plotly attempts to find matching items in + `labels`, but beware they must be unique. + parentssrc + Sets the source reference on Chart Studio Cloud for + `parents`. + pathbar + :class:`plotly.graph_objects.icicle.Pathbar` instance + or dict with compatible properties + root + :class:`plotly.graph_objects.icicle.Root` instance or + dict with compatible properties + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.icicle.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Sets the positions of the `text` elements. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry`, `percentParent`, `label` + and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + tiling + :class:`plotly.graph_objects.icicle.Tiling` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values associated with each of the sectors. + Use with `branchvalues` to determine how the values are + summed. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Icicle + + new_trace = Icicle( + branchvalues=branchvalues, + count=count, + customdata=customdata, + customdatasrc=customdatasrc, + domain=domain, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextfont=insidetextfont, + labels=labels, + labelssrc=labelssrc, + leaf=leaf, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + level=level, + marker=marker, + maxdepth=maxdepth, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + outsidetextfont=outsidetextfont, + parents=parents, + parentssrc=parentssrc, + pathbar=pathbar, + root=root, + sort=sort, + stream=stream, + text=text, + textfont=textfont, + textinfo=textinfo, + textposition=textposition, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + tiling=tiling, + uid=uid, + uirevision=uirevision, + values=values, + valuessrc=valuessrc, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_image( + self, + colormodel=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + source=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + visible=None, + x0=None, + xaxis=None, + y0=None, + yaxis=None, + z=None, + zmax=None, + zmin=None, + zorder=None, + zsmooth=None, + zsrc=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Image trace + + Display an image, i.e. data on a 2D regular raster. By default, + when an image is displayed in a subplot, its y axis will be + reversed (ie. `autorange: 'reversed'`), constrained to the + domain (ie. `constrain: 'domain'`) and it will have the same + scale as its x axis (ie. `scaleanchor: 'x,`) in order for + pixels to be rendered as squares. + + Parameters + ---------- + colormodel + Color model used to map the numerical color components + described in `z` into colors. If `source` is specified, + this attribute will be set to `rgba256` otherwise it + defaults to `rgb`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Set the pixel's horizontal size. + dy + Set the pixel's vertical size + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.image.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `z`, `color` and `colormodel`. Anything + contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.image.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + source + Specifies the data URI of the image to be visualized. + The URI consists of "data:image/[][;base64\\]," + stream + :class:`plotly.graph_objects.image.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with each z value. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x0 + Set the image's x position. The left edge of the image + (or the right edge if the x axis is reversed or dx is + negative) will be found at xmin=x0-dx/2 + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + y0 + Set the image's y position. The top edge of the image + (or the bottom edge if the y axis is NOT reversed or if + dy is negative) will be found at ymin=y0-dy/2. By + default when an image trace is included, the y axis + will be reversed so that the image is right-side-up, + but you can disable this by setting + yaxis.autorange=true or by providing an explicit y axis + range. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + z + A 2-dimensional array in which each element is an array + of 3 or 4 numbers representing a color. + zmax + Array defining the higher bound for each color + component. Note that the default value will depend on + the colormodel. For the `rgb` colormodel, it is [255, + 255, 255]. For the `rgba` colormodel, it is [255, 255, + 255, 1]. For the `rgba256` colormodel, it is [255, 255, + 255, 255]. For the `hsl` colormodel, it is [360, 100, + 100]. For the `hsla` colormodel, it is [360, 100, 100, + 1]. + zmin + Array defining the lower bound for each color + component. Note that the default value will depend on + the colormodel. For the `rgb` colormodel, it is [0, 0, + 0]. For the `rgba` colormodel, it is [0, 0, 0, 0]. For + the `rgba256` colormodel, it is [0, 0, 0, 0]. For the + `hsl` colormodel, it is [0, 0, 0]. For the `hsla` + colormodel, it is [0, 0, 0, 0]. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsmooth + Picks a smoothing algorithm used to smooth `z` data. + This only applies for image traces that use the + `source` attribute. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Image + + new_trace = Image( + colormodel=colormodel, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + source=source, + stream=stream, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + visible=visible, + x0=x0, + xaxis=xaxis, + y0=y0, + yaxis=yaxis, + z=z, + zmax=zmax, + zmin=zmin, + zorder=zorder, + zsmooth=zsmooth, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_indicator( + self, + align=None, + customdata=None, + customdatasrc=None, + delta=None, + domain=None, + gauge=None, + ids=None, + idssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + meta=None, + metasrc=None, + mode=None, + name=None, + number=None, + stream=None, + title=None, + uid=None, + uirevision=None, + value=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Indicator trace + + An indicator is used to visualize a single `value` along with + some contextual information such as `steps` or a `threshold`, + using a combination of three visual elements: a number, a + delta, and/or a gauge. Deltas are taken with respect to a + `reference`. Gauges can be either angular or bullet (aka + linear) gauges. + + Parameters + ---------- + align + Sets the horizontal alignment of the `text` within the + box. Note that this attribute has no effect if an + angular gauge is displayed: in this case, it is always + centered + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + delta + :class:`plotly.graph_objects.indicator.Delta` instance + or dict with compatible properties + domain + :class:`plotly.graph_objects.indicator.Domain` instance + or dict with compatible properties + gauge + The gauge of the Indicator plot. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.indicator.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines how the value is displayed on the graph. + `number` displays the value numerically in text. + `delta` displays the difference to a reference value in + text. Finally, `gauge` displays the value graphically + on an axis. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + number + :class:`plotly.graph_objects.indicator.Number` instance + or dict with compatible properties + stream + :class:`plotly.graph_objects.indicator.Stream` instance + or dict with compatible properties + title + :class:`plotly.graph_objects.indicator.Title` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + value + Sets the number to be displayed. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Indicator + + new_trace = Indicator( + align=align, + customdata=customdata, + customdatasrc=customdatasrc, + delta=delta, + domain=domain, + gauge=gauge, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + number=number, + stream=stream, + title=title, + uid=uid, + uirevision=uirevision, + value=value, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_isosurface( + self, + autocolorscale=None, + caps=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + coloraxis=None, + colorbar=None, + colorscale=None, + contour=None, + customdata=None, + customdatasrc=None, + flatshading=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + isomax=None, + isomin=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + slices=None, + spaceframe=None, + stream=None, + surface=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + value=None, + valuehoverformat=None, + valuesrc=None, + visible=None, + x=None, + xhoverformat=None, + xsrc=None, + y=None, + yhoverformat=None, + ysrc=None, + z=None, + zhoverformat=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Isosurface trace + + Draws isosurfaces between iso-min and iso-max values with + coordinates given by four 1-dimensional arrays containing the + `value`, `x`, `y` and `z` of every vertex of a uniform or non- + uniform 3-D grid. Horizontal or vertical slices, caps as well + as spaceframe between iso-min and iso-max values could also be + drawn using this trace. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + caps + :class:`plotly.graph_objects.isosurface.Caps` instance + or dict with compatible properties + cauto + Determines whether or not the color domain is computed + with respect to the input data (here `value`) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as `value` and if set, `cmin` must + be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as `value`. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as `value` and if set, `cmax` must + be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.isosurface.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contour + :class:`plotly.graph_objects.isosurface.Contour` + instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + flatshading + Determines whether or not normal smoothing is applied + to the meshes, creating meshes with an angular, low- + poly look via flat reflections. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.isosurface.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + isomax + Sets the maximum boundary for iso-surface plot. + isomin + Sets the minimum boundary for iso-surface plot. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.isosurface.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.isosurface.Lighting` + instance or dict with compatible properties + lightposition + :class:`plotly.graph_objects.isosurface.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + slices + :class:`plotly.graph_objects.isosurface.Slices` + instance or dict with compatible properties + spaceframe + :class:`plotly.graph_objects.isosurface.Spaceframe` + instance or dict with compatible properties + stream + :class:`plotly.graph_objects.isosurface.Stream` + instance or dict with compatible properties + surface + :class:`plotly.graph_objects.isosurface.Surface` + instance or dict with compatible properties + text + Sets the text elements associated with the vertices. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + value + Sets the 4th dimension (value) of the vertices. + valuehoverformat + Sets the hover text formatting rulefor `value` using + d3 formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + valuesrc + Sets the source reference on Chart Studio Cloud for + `value`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the X coordinates of the vertices on X axis. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the Y coordinates of the vertices on Y axis. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the Z coordinates of the vertices on Z axis. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Isosurface + + new_trace = Isosurface( + autocolorscale=autocolorscale, + caps=caps, + cauto=cauto, + cmax=cmax, + cmid=cmid, + cmin=cmin, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + contour=contour, + customdata=customdata, + customdatasrc=customdatasrc, + flatshading=flatshading, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + isomax=isomax, + isomin=isomin, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lighting=lighting, + lightposition=lightposition, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + reversescale=reversescale, + scene=scene, + showlegend=showlegend, + showscale=showscale, + slices=slices, + spaceframe=spaceframe, + stream=stream, + surface=surface, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + value=value, + valuehoverformat=valuehoverformat, + valuesrc=valuesrc, + visible=visible, + x=x, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zhoverformat=zhoverformat, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_mesh3d( + self, + alphahull=None, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + color=None, + coloraxis=None, + colorbar=None, + colorscale=None, + contour=None, + customdata=None, + customdatasrc=None, + delaunayaxis=None, + facecolor=None, + facecolorsrc=None, + flatshading=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + i=None, + ids=None, + idssrc=None, + intensity=None, + intensitymode=None, + intensitysrc=None, + isrc=None, + j=None, + jsrc=None, + k=None, + ksrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + vertexcolor=None, + vertexcolorsrc=None, + visible=None, + x=None, + xcalendar=None, + xhoverformat=None, + xsrc=None, + y=None, + ycalendar=None, + yhoverformat=None, + ysrc=None, + z=None, + zcalendar=None, + zhoverformat=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Mesh3d trace + + Draws sets of triangles with coordinates given by three + 1-dimensional arrays in `x`, `y`, `z` and (1) a sets of `i`, + `j`, `k` indices (2) Delaunay triangulation or (3) the Alpha- + shape algorithm or (4) the Convex-hull algorithm + + Parameters + ---------- + alphahull + Determines how the mesh surface triangles are derived + from the set of vertices (points) represented by the + `x`, `y` and `z` arrays, if the `i`, `j`, `k` arrays + are not supplied. For general use of `mesh3d` it is + preferred that `i`, `j`, `k` are supplied. If "-1", + Delaunay triangulation is used, which is mainly + suitable if the mesh is a single, more or less layer + surface that is perpendicular to `delaunayaxis`. In + case the `delaunayaxis` intersects the mesh surface at + more than one point it will result triangles that are + very long in the dimension of `delaunayaxis`. If ">0", + the alpha-shape algorithm is used. In this case, the + positive `alphahull` value signals the use of the + alpha-shape algorithm, _and_ its value acts as the + parameter for the mesh fitting. If 0, the convex-hull + algorithm is used. It is suitable for convex bodies or + if the intention is to enclose the `x`, `y` and `z` + point set into a convex hull. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here `intensity`) or + the bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as `intensity` and if set, `cmin` + must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as `intensity`. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as `intensity` and if set, `cmax` + must be set as well. + color + Sets the color of the whole mesh + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.mesh3d.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contour + :class:`plotly.graph_objects.mesh3d.Contour` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + delaunayaxis + Sets the Delaunay axis, which is the axis that is + perpendicular to the surface of the Delaunay + triangulation. It has an effect if `i`, `j`, `k` are + not provided and `alphahull` is set to indicate + Delaunay triangulation. + facecolor + Sets the color of each face Overrides "color" and + "vertexcolor". + facecolorsrc + Sets the source reference on Chart Studio Cloud for + `facecolor`. + flatshading + Determines whether or not normal smoothing is applied + to the meshes, creating meshes with an angular, low- + poly look via flat reflections. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.mesh3d.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + i + A vector of vertex indices, i.e. integer values between + 0 and the length of the vertex vectors, representing + the "first" vertex of a triangle. For example, `{i[m], + j[m], k[m]}` together represent face m (triangle m) in + the mesh, where `i[m] = n` points to the triplet + `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, + each element in `i` represents a point in space, which + is the first vertex of a triangle. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + intensity + Sets the intensity values for vertices or cells as + defined by `intensitymode`. It can be used for plotting + fields on meshes. + intensitymode + Determines the source of `intensity` values. + intensitysrc + Sets the source reference on Chart Studio Cloud for + `intensity`. + isrc + Sets the source reference on Chart Studio Cloud for + `i`. + j + A vector of vertex indices, i.e. integer values between + 0 and the length of the vertex vectors, representing + the "second" vertex of a triangle. For example, `{i[m], + j[m], k[m]}` together represent face m (triangle m) in + the mesh, where `j[m] = n` points to the triplet + `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, + each element in `j` represents a point in space, which + is the second vertex of a triangle. + jsrc + Sets the source reference on Chart Studio Cloud for + `j`. + k + A vector of vertex indices, i.e. integer values between + 0 and the length of the vertex vectors, representing + the "third" vertex of a triangle. For example, `{i[m], + j[m], k[m]}` together represent face m (triangle m) in + the mesh, where `k[m] = n` points to the triplet + `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, + each element in `k` represents a point in space, which + is the third vertex of a triangle. + ksrc + Sets the source reference on Chart Studio Cloud for + `k`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.mesh3d.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.mesh3d.Lighting` instance + or dict with compatible properties + lightposition + :class:`plotly.graph_objects.mesh3d.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.mesh3d.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with the vertices. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + vertexcolor + Sets the color of each vertex Overrides "color". While + Red, green and blue colors are in the range of 0 and + 255; in the case of having vertex color data in RGBA + format, the alpha color should be normalized to be + between 0 and 1. + vertexcolorsrc + Sets the source reference on Chart Studio Cloud for + `vertexcolor`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the X coordinates of the vertices. The nth element + of vectors `x`, `y` and `z` jointly represent the X, Y + and Z coordinates of the nth vertex. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the Y coordinates of the vertices. The nth element + of vectors `x`, `y` and `z` jointly represent the X, Y + and Z coordinates of the nth vertex. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the Z coordinates of the vertices. The nth element + of vectors `x`, `y` and `z` jointly represent the X, Y + and Z coordinates of the nth vertex. + zcalendar + Sets the calendar system to use with `z` date data. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Mesh3d + + new_trace = Mesh3d( + alphahull=alphahull, + autocolorscale=autocolorscale, + cauto=cauto, + cmax=cmax, + cmid=cmid, + cmin=cmin, + color=color, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + contour=contour, + customdata=customdata, + customdatasrc=customdatasrc, + delaunayaxis=delaunayaxis, + facecolor=facecolor, + facecolorsrc=facecolorsrc, + flatshading=flatshading, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + i=i, + ids=ids, + idssrc=idssrc, + intensity=intensity, + intensitymode=intensitymode, + intensitysrc=intensitysrc, + isrc=isrc, + j=j, + jsrc=jsrc, + k=k, + ksrc=ksrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lighting=lighting, + lightposition=lightposition, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + reversescale=reversescale, + scene=scene, + showlegend=showlegend, + showscale=showscale, + stream=stream, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + vertexcolor=vertexcolor, + vertexcolorsrc=vertexcolorsrc, + visible=visible, + x=x, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zcalendar=zcalendar, + zhoverformat=zhoverformat, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_ohlc( + self, + close=None, + closesrc=None, + customdata=None, + customdatasrc=None, + decreasing=None, + high=None, + highsrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + increasing=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + low=None, + lowsrc=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + open=None, + opensrc=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textsrc=None, + tickwidth=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + yaxis=None, + yhoverformat=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Ohlc trace + + The ohlc (short for Open-High-Low-Close) is a style of + financial chart describing open, high, low and close for a + given `x` coordinate (most likely time). The tip of the lines + represent the `low` and `high` values and the horizontal + segments represent the `open` and `close` values. Sample points + where the close value is higher (lower) then the open value are + called increasing (decreasing). By default, increasing items + are drawn in green whereas decreasing are drawn in red. + + Parameters + ---------- + close + Sets the close values. + closesrc + Sets the source reference on Chart Studio Cloud for + `close`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + decreasing + :class:`plotly.graph_objects.ohlc.Decreasing` instance + or dict with compatible properties + high + Sets the high values. + highsrc + Sets the source reference on Chart Studio Cloud for + `high`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.ohlc.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `open`, `high`, `low` and `close`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + increasing + :class:`plotly.graph_objects.ohlc.Increasing` instance + or dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.ohlc.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.ohlc.Line` instance or + dict with compatible properties + low + Sets the low values. + lowsrc + Sets the source reference on Chart Studio Cloud for + `low`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + open + Sets the open values. + opensrc + Sets the source reference on Chart Studio Cloud for + `open`. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.ohlc.Stream` instance or + dict with compatible properties + text + Sets hover text elements associated with each sample + point. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to this trace's sample points. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + tickwidth + Sets the width of the open/close tick marks relative to + the "x" minimal interval. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. If absent, linear coordinate + will be generated. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Ohlc + + new_trace = Ohlc( + close=close, + closesrc=closesrc, + customdata=customdata, + customdatasrc=customdatasrc, + decreasing=decreasing, + high=high, + highsrc=highsrc, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + increasing=increasing, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + low=low, + lowsrc=lowsrc, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + open=open, + opensrc=opensrc, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textsrc=textsrc, + tickwidth=tickwidth, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + xaxis=xaxis, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + yaxis=yaxis, + yhoverformat=yhoverformat, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_parcats( + self, + arrangement=None, + bundlecolors=None, + counts=None, + countssrc=None, + dimensions=None, + dimensiondefaults=None, + domain=None, + hoverinfo=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + labelfont=None, + legendgrouptitle=None, + legendwidth=None, + line=None, + meta=None, + metasrc=None, + name=None, + sortpaths=None, + stream=None, + tickfont=None, + uid=None, + uirevision=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Parcats trace + + Parallel categories diagram for multidimensional categorical + data. + + Parameters + ---------- + arrangement + Sets the drag interaction mode for categories and + dimensions. If `perpendicular`, the categories can only + move along a line perpendicular to the paths. If + `freeform`, the categories can freely move on the + plane. If `fixed`, the categories and dimensions are + stationary. + bundlecolors + Sort paths so that like colors are bundled together + within each category. + counts + The number of observations represented by each state. + Defaults to 1 so that each state represents one + observation + countssrc + Sets the source reference on Chart Studio Cloud for + `counts`. + dimensions + The dimensions (variables) of the parallel categories + diagram. + dimensiondefaults + When used in a template (as + layout.template.data.parcats.dimensiondefaults), sets + the default property values to use for elements of + parcats.dimensions + domain + :class:`plotly.graph_objects.parcats.Domain` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoveron + Sets the hover interaction mode for the parcats + diagram. If `category`, hover interaction take place + per category. If `color`, hover interactions take place + per color per category. If `dimension`, hover + interactions take place across all categories per + dimension. + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `count`, `probability`, `category`, + `categorycount`, `colorcount` and `bandcolorcount`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + labelfont + Sets the font for the `dimension` labels. + legendgrouptitle + :class:`plotly.graph_objects.parcats.Legendgrouptitle` + instance or dict with compatible properties + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.parcats.Line` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + sortpaths + Sets the path sorting algorithm. If `forward`, sort + paths based on dimension categories from left to right. + If `backward`, sort paths based on dimensions + categories from right to left. + stream + :class:`plotly.graph_objects.parcats.Stream` instance + or dict with compatible properties + tickfont + Sets the font for the `category` labels. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Parcats + + new_trace = Parcats( + arrangement=arrangement, + bundlecolors=bundlecolors, + counts=counts, + countssrc=countssrc, + dimensions=dimensions, + dimensiondefaults=dimensiondefaults, + domain=domain, + hoverinfo=hoverinfo, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + labelfont=labelfont, + legendgrouptitle=legendgrouptitle, + legendwidth=legendwidth, + line=line, + meta=meta, + metasrc=metasrc, + name=name, + sortpaths=sortpaths, + stream=stream, + tickfont=tickfont, + uid=uid, + uirevision=uirevision, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_parcoords( + self, + customdata=None, + customdatasrc=None, + dimensions=None, + dimensiondefaults=None, + domain=None, + ids=None, + idssrc=None, + labelangle=None, + labelfont=None, + labelside=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + meta=None, + metasrc=None, + name=None, + rangefont=None, + stream=None, + tickfont=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Parcoords trace + + Parallel coordinates for multidimensional exploratory data + analysis. The samples are specified in `dimensions`. The colors + are set in `line.color`. + + Parameters + ---------- + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dimensions + The dimensions (variables) of the parallel coordinates + chart. 2..60 dimensions are supported. + dimensiondefaults + When used in a template (as + layout.template.data.parcoords.dimensiondefaults), sets + the default property values to use for elements of + parcoords.dimensions + domain + :class:`plotly.graph_objects.parcoords.Domain` instance + or dict with compatible properties + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + labelangle + Sets the angle of the labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + labels vertically. Tilted labels with "labelangle" may + be positioned better inside margins when + `labelposition` is set to "bottom". + labelfont + Sets the font for the `dimension` labels. + labelside + Specifies the location of the `label`. "top" positions + labels above, next to the title "bottom" positions + labels below the graph Tilted labels with "labelangle" + may be positioned better inside margins when + `labelposition` is set to "bottom". + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.parcoords.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.parcoords.Line` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + rangefont + Sets the font for the `dimension` range values. + stream + :class:`plotly.graph_objects.parcoords.Stream` instance + or dict with compatible properties + tickfont + Sets the font for the `dimension` tick values. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.parcoords.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Parcoords + + new_trace = Parcoords( + customdata=customdata, + customdatasrc=customdatasrc, + dimensions=dimensions, + dimensiondefaults=dimensiondefaults, + domain=domain, + ids=ids, + idssrc=idssrc, + labelangle=labelangle, + labelfont=labelfont, + labelside=labelside, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + meta=meta, + metasrc=metasrc, + name=name, + rangefont=rangefont, + stream=stream, + tickfont=tickfont, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_pie( + self, + automargin=None, + customdata=None, + customdatasrc=None, + direction=None, + dlabel=None, + domain=None, + hole=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextfont=None, + insidetextorientation=None, + label0=None, + labels=None, + labelssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendsrc=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + outsidetextfont=None, + pull=None, + pullsrc=None, + rotation=None, + scalegroup=None, + showlegend=None, + showlegendsrc=None, + sort=None, + stream=None, + text=None, + textfont=None, + textinfo=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + title=None, + uid=None, + uirevision=None, + values=None, + valuessrc=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Pie trace + + A data visualized by the sectors of the pie is set in `values`. + The sector labels are set in `labels`. The sector colors are + set in `marker.colors` + + Parameters + ---------- + automargin + Determines whether outside text labels can push the + margins. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + direction + Specifies the direction at which succeeding sectors + follow one another. + dlabel + Sets the label step. See `label0` for more info. + domain + :class:`plotly.graph_objects.pie.Domain` instance or + dict with compatible properties + hole + Sets the fraction of the radius to cut out of the pie. + Use this to make a donut chart. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.pie.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `percent` and + `text`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + insidetextorientation + Controls the orientation of the text inside chart + sectors. When set to "auto", text may be oriented in + any direction in order to be as big as possible in the + middle of a sector. The "horizontal" option orients + text to be parallel with the bottom of the chart, and + may make text smaller in order to achieve that goal. + The "radial" option orients text along the radius of + the sector. The "tangential" option orients text + perpendicular to the radius of the sector. + label0 + Alternate to `labels`. Builds a numeric set of labels. + Use with `dlabel` where `label0` is the starting label + and `dlabel` the step. + labels + Sets the sector labels. If `labels` entries are + duplicated, we sum associated `values` or simply count + occurrences if `values` is not provided. For other + array attributes (including color) we use the first + non-empty entry among all occurrences of the label. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + legend + Sets the reference to a legend to show the pie slices + in. Can be an array if `values` is set. In that case, + each entry specifies the legend reference for one + slice. References to these legends are "legend", + "legend2", "legend3", etc. Settings for these legends + are set in the layout, under `layout.legend`, + `layout.legend2`, etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.pie.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendsrc + Sets the source reference on Chart Studio Cloud for + `legend`. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.pie.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. + pull + Sets the fraction of larger radius to pull the sectors + out from the center. This can be a constant to pull all + slices apart from each other equally or an array to + highlight one or more slices. + pullsrc + Sets the source reference on Chart Studio Cloud for + `pull`. + rotation + Instead of the first slice starting at 12 o'clock, + rotate to some other angle. + scalegroup + If there are multiple pie charts that should be sized + according to their totals, link them by providing a + non-empty group id here shared by every trace in the + same group. + showlegend + Determines whether or not items corresponding to the + pie slices are shown in the legend. Can be an array if + `values` is set. In that case, each entry specifies + appearance in the legend for one slice. + showlegendsrc + Sets the source reference on Chart Studio Cloud for + `showlegend`. + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.pie.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Specifies the location of the `textinfo`. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `percent` and + `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + title + :class:`plotly.graph_objects.pie.Title` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values of the sectors. If omitted, we count + occurrences of each label. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Pie + + new_trace = Pie( + automargin=automargin, + customdata=customdata, + customdatasrc=customdatasrc, + direction=direction, + dlabel=dlabel, + domain=domain, + hole=hole, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextfont=insidetextfont, + insidetextorientation=insidetextorientation, + label0=label0, + labels=labels, + labelssrc=labelssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendsrc=legendsrc, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + outsidetextfont=outsidetextfont, + pull=pull, + pullsrc=pullsrc, + rotation=rotation, + scalegroup=scalegroup, + showlegend=showlegend, + showlegendsrc=showlegendsrc, + sort=sort, + stream=stream, + text=text, + textfont=textfont, + textinfo=textinfo, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + title=title, + uid=uid, + uirevision=uirevision, + values=values, + valuessrc=valuessrc, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_sankey( + self, + arrangement=None, + customdata=None, + customdatasrc=None, + domain=None, + hoverinfo=None, + hoverlabel=None, + ids=None, + idssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + link=None, + meta=None, + metasrc=None, + name=None, + node=None, + orientation=None, + selectedpoints=None, + stream=None, + textfont=None, + uid=None, + uirevision=None, + valueformat=None, + valuesuffix=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Sankey trace + + Sankey plots for network flow data analysis. The nodes are + specified in `nodes` and the links between sources and targets + in `links`. The colors are set in `nodes[i].color` and + `links[i].color`, otherwise defaults are used. + + Parameters + ---------- + arrangement + If value is `snap` (the default), the node arrangement + is assisted by automatic snapping of elements to + preserve space between nodes specified via `nodepad`. + If value is `perpendicular`, the nodes can only move + along a line perpendicular to the flow. If value is + `freeform`, the nodes can freely move on the plane. If + value is `fixed`, the nodes are stationary. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.sankey.Domain` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. Note that this attribute is + superseded by `node.hoverinfo` and `node.hoverinfo` for + nodes and links respectively. + hoverlabel + :class:`plotly.graph_objects.sankey.Hoverlabel` + instance or dict with compatible properties + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.sankey.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + link + The links of the Sankey plot. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + node + The nodes of the Sankey plot. + orientation + Sets the orientation of the Sankey diagram. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + stream + :class:`plotly.graph_objects.sankey.Stream` instance or + dict with compatible properties + textfont + Sets the font for node labels + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + valueformat + Sets the value formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + valuesuffix + Adds a unit to follow the value in the hover tooltip. + Add a space if a separation is necessary from the + value. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Sankey + + new_trace = Sankey( + arrangement=arrangement, + customdata=customdata, + customdatasrc=customdatasrc, + domain=domain, + hoverinfo=hoverinfo, + hoverlabel=hoverlabel, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + link=link, + meta=meta, + metasrc=metasrc, + name=name, + node=node, + orientation=orientation, + selectedpoints=selectedpoints, + stream=stream, + textfont=textfont, + uid=uid, + uirevision=uirevision, + valueformat=valueformat, + valuesuffix=valuesuffix, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scatter( + self, + alignmentgroup=None, + cliponaxis=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + error_x=None, + error_y=None, + fill=None, + fillcolor=None, + fillgradient=None, + fillpattern=None, + groupnorm=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + offsetgroup=None, + opacity=None, + orientation=None, + selected=None, + selectedpoints=None, + showlegend=None, + stackgaps=None, + stackgroup=None, + stream=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Scatter trace + + The scatter trace type encompasses line charts, scatter charts, + text charts, and bubble charts. The data visualized as scatter + point or lines is set in `x` and `y`. Text (appearing either on + the chart or on hover only) is via `text`. Bubble charts are + achieved by setting `marker.size` and/or `marker.color` to + numerical arrays. + + Parameters + ---------- + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + error_x + :class:`plotly.graph_objects.scatter.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.scatter.ErrorY` instance + or dict with compatible properties + fill + Sets the area to fill with a solid color. Defaults to + "none" unless this trace is stacked, then it gets + "tonexty" ("tonextx") if `orientation` is "v" ("h") Use + with `fillcolor` if not "none". "tozerox" and "tozeroy" + fill to x=0 and y=0 respectively. "tonextx" and + "tonexty" fill between the endpoints of this trace and + the endpoints of the trace before it, connecting those + endpoints with straight lines (to make a stacked area + graph); if there is no trace before it, they behave + like "tozerox" and "tozeroy". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. Traces in a `stackgroup` will only fill to (or + be filled to) other traces in the same group. With + multiple `stackgroup`s or some traces stacked and some + not, if fill-linked traces are not already consecutive, + the later ones will be pushed down in the drawing + order. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. If fillgradient is + specified, fillcolor is ignored except for setting the + background color of the hover label, if any. + fillgradient + Sets a fill gradient. If not specified, the fillcolor + is used instead. + fillpattern + Sets the pattern within the marker. + groupnorm + Only relevant when `stackgroup` is used, and only the + first `groupnorm` found in the `stackgroup` will be + used - including if `visible` is "legendonly" but not + if it is `false`. Sets the normalization for the sum of + this `stackgroup`. With "fraction", the value of each + trace at each location is divided by the sum of all + trace values at that location. "percent" is the same + but multiplied by 100 to show percentages. If there are + multiple subplots, or multiple `stackgroup`s on one + subplot, each will be normalized within its own set. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatter.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatter.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatter.Line` instance or + dict with compatible properties + marker + :class:`plotly.graph_objects.scatter.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Only relevant in the following cases: 1. when + `scattermode` is set to "group". 2. when `stackgroup` + is used, and only the first `orientation` found in the + `stackgroup` will be used - including if `visible` is + "legendonly" but not if it is `false`. Sets the + stacking direction. With "v" ("h"), the y (x) values of + subsequent traces are added. Also affects the default + value of `fill`. + selected + :class:`plotly.graph_objects.scatter.Selected` instance + or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stackgaps + Only relevant when `stackgroup` is used, and only the + first `stackgaps` found in the `stackgroup` will be + used - including if `visible` is "legendonly" but not + if it is `false`. Determines how we handle locations at + which other traces in this group have data but this one + does not. With *infer zero* we insert a zero at these + locations. With "interpolate" we linearly interpolate + between existing values, and extrapolate a constant + beyond the existing values. + stackgroup + Set several scatter traces (on the same subplot) to the + same stackgroup in order to add their y values (or + their x values if `orientation` is "h"). If blank or + omitted this trace will not be stacked. Stacking also + turns `fill` on by default, using "tonexty" ("tonextx") + if `orientation` is "h" ("v") and sets the default + `mode` to "lines" irrespective of point count. You can + only stack on a numeric (linear or log) axis. Traces in + a `stackgroup` will only fill to (or be filled to) + other traces in the same group. With multiple + `stackgroup`s or some traces stacked and some not, if + fill-linked traces are not already consecutive, the + later ones will be pushed down in the drawing order. + stream + :class:`plotly.graph_objects.scatter.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatter.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Scatter + + new_trace = Scatter( + alignmentgroup=alignmentgroup, + cliponaxis=cliponaxis, + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + error_x=error_x, + error_y=error_y, + fill=fill, + fillcolor=fillcolor, + fillgradient=fillgradient, + fillpattern=fillpattern, + groupnorm=groupnorm, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + offsetgroup=offsetgroup, + opacity=opacity, + orientation=orientation, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stackgaps=stackgaps, + stackgroup=stackgroup, + stream=stream, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + x=x, + x0=x0, + xaxis=xaxis, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + y=y, + y0=y0, + yaxis=yaxis, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_scatter3d( + self, + connectgaps=None, + customdata=None, + customdatasrc=None, + error_x=None, + error_y=None, + error_z=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + projection=None, + scene=None, + showlegend=None, + stream=None, + surfaceaxis=None, + surfacecolor=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xcalendar=None, + xhoverformat=None, + xsrc=None, + y=None, + ycalendar=None, + yhoverformat=None, + ysrc=None, + z=None, + zcalendar=None, + zhoverformat=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Scatter3d trace + + The data visualized as scatter point or lines in 3D dimension + is set in `x`, `y`, `z`. Text (appearing either on the chart or + on hover only) is via `text`. Bubble charts are achieved by + setting `marker.size` and/or `marker.color` Projections are + achieved via `projection`. Surface fills are achieved via + `surfaceaxis`. + + Parameters + ---------- + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + error_x + :class:`plotly.graph_objects.scatter3d.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.scatter3d.ErrorY` instance + or dict with compatible properties + error_z + :class:`plotly.graph_objects.scatter3d.ErrorZ` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatter3d.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets text elements associated with each (x,y,z) + triplet. If a single string, the same string appears + over all the data points. If an array of string, the + items are mapped in order to the this trace's (x,y,z) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatter3d.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatter3d.Line` instance + or dict with compatible properties + marker + :class:`plotly.graph_objects.scatter3d.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + projection + :class:`plotly.graph_objects.scatter3d.Projection` + instance or dict with compatible properties + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatter3d.Stream` instance + or dict with compatible properties + surfaceaxis + If "-1", the scatter points are not fill with a surface + If 0, 1, 2, the scatter points are filled with a + Delaunay surface about the x, y, z respectively. + surfacecolor + Sets the surface fill color. + text + Sets text elements associated with each (x,y,z) + triplet. If a single string, the same string appears + over all the data points. If an array of string, the + items are mapped in order to the this trace's (x,y,z) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates. + zcalendar + Sets the calendar system to use with `z` date data. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Scatter3d + + new_trace = Scatter3d( + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + error_x=error_x, + error_y=error_y, + error_z=error_z, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + projection=projection, + scene=scene, + showlegend=showlegend, + stream=stream, + surfaceaxis=surfaceaxis, + surfacecolor=surfacecolor, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zcalendar=zcalendar, + zhoverformat=zhoverformat, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scattercarpet( + self, + a=None, + asrc=None, + b=None, + bsrc=None, + carpet=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + xaxis=None, + yaxis=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Scattercarpet trace + + Plots a scatter trace on either the first carpet axis or the + carpet axis with a matching `carpet` attribute. + + Parameters + ---------- + a + Sets the a-axis coordinates. + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + b + Sets the b-axis coordinates. + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + carpet + An identifier for this carpet, so that `scattercarpet` + and `contourcarpet` traces can specify a carpet plot on + which they lie + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scatterternary has a subset + of the options available to scatter. "toself" connects + the endpoints of the trace (or each segment of the + trace if it has gaps) into a closed shape. "tonext" + fills the space between two traces if one completely + encloses the other (eg consecutive contour lines), and + behaves like "toself" if there is no trace before it. + "tonext" should not be used if one trace does not + enclose the other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattercarpet.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (a,b) + point. If a single string, the same string appears over + all the data points. If an array of strings, the items + are mapped in order to the the data points in (a,b). To + be seen, trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattercarpet.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattercarpet.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scattercarpet.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattercarpet.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattercarpet.Stream` + instance or dict with compatible properties + text + Sets text elements associated with each (a,b) point. If + a single string, the same string appears over all the + data points. If an array of strings, the items are + mapped in order to the the data points in (a,b). If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `a`, `b` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattercarpet.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Scattercarpet + + new_trace = Scattercarpet( + a=a, + asrc=asrc, + b=b, + bsrc=bsrc, + carpet=carpet, + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + xaxis=xaxis, + yaxis=yaxis, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_scattergeo( + self, + connectgaps=None, + customdata=None, + customdatasrc=None, + featureidkey=None, + fill=None, + fillcolor=None, + geo=None, + geojson=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + lat=None, + latsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + locationmode=None, + locations=None, + locationssrc=None, + lon=None, + lonsrc=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Scattergeo trace + + The data visualized as scatter point or lines on a geographic + map is provided either by longitude/latitude pairs in `lon` and + `lat` respectively or by geographic location IDs or names in + `locations`. + + Parameters + ---------- + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. Only + has an effect when `geojson` is set. Support nested + property, for example "properties.name". + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + geo + Sets a reference between this trace's geospatial + coordinates and a geographic map. If "geo" (the default + value), the geospatial coordinates refer to + `layout.geo`. If "geo2", the geospatial coordinates + refer to `layout.geo2`, and so on. + geojson + Sets optional GeoJSON data associated with this trace. + If not given, the features on the base map are used + when `locations` is set. It can be set as a valid + GeoJSON object or as a URL string. Note that we only + accept GeoJSONs of type "FeatureCollection" or + "Feature" with geometries of type "Polygon" or + "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattergeo.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair or item in `locations`. If a single string, the + same string appears over all the data points. If an + array of string, the items are mapped in order to the + this trace's (lon,lat) or `locations` coordinates. To + be seen, trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattergeo.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattergeo.Line` instance + or dict with compatible properties + locationmode + The library used by the *country names* `locationmode` + option is changing in an upcoming version. Country + names in existing plots may not work in the new + version. Determines the set of locations used to match + entries in `locations` to regions on the map. Values + "ISO-3", "USA-states", *country names* correspond to + features on the base map and value "geojson-id" + corresponds to features from a custom GeoJSON linked to + the `geojson` attribute. + locations + Sets the coordinates via location IDs or names. + Coordinates correspond to the centroid of each location + given. See `locationmode` for more info. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + marker + :class:`plotly.graph_objects.scattergeo.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattergeo.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattergeo.Stream` + instance or dict with compatible properties + text + Sets text elements associated with each (lon,lat) pair + or item in `locations`. If a single string, the same + string appears over all the data points. If an array of + string, the items are mapped in order to the this + trace's (lon,lat) or `locations` coordinates. If trace + `hoverinfo` contains a "text" flag and "hovertext" is + not set, these elements will be seen in the hover + labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `lat`, `lon`, `location` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattergeo.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Scattergeo + + new_trace = Scattergeo( + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + featureidkey=featureidkey, + fill=fill, + fillcolor=fillcolor, + geo=geo, + geojson=geojson, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + lat=lat, + latsrc=latsrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + locationmode=locationmode, + locations=locations, + locationssrc=locationssrc, + lon=lon, + lonsrc=lonsrc, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scattergl( + self, + connectgaps=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + error_x=None, + error_y=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Scattergl trace + + The data visualized as scatter point or lines is set in `x` and + `y` using the WebGL plotting engine. Bubble charts are achieved + by setting `marker.size` and/or `marker.color` to a numerical + arrays. + + Parameters + ---------- + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + error_x + :class:`plotly.graph_objects.scattergl.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.scattergl.ErrorY` instance + or dict with compatible properties + fill + Sets the area to fill with a solid color. Defaults to + "none" unless this trace is stacked, then it gets + "tonexty" ("tonextx") if `orientation` is "v" ("h") Use + with `fillcolor` if not "none". "tozerox" and "tozeroy" + fill to x=0 and y=0 respectively. "tonextx" and + "tonexty" fill between the endpoints of this trace and + the endpoints of the trace before it, connecting those + endpoints with straight lines (to make a stacked area + graph); if there is no trace before it, they behave + like "tozerox" and "tozeroy". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. Traces in a `stackgroup` will only fill to (or + be filled to) other traces in the same group. With + multiple `stackgroup`s or some traces stacked and some + not, if fill-linked traces are not already consecutive, + the later ones will be pushed down in the drawing + order. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattergl.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattergl.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattergl.Line` instance + or dict with compatible properties + marker + :class:`plotly.graph_objects.scattergl.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattergl.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattergl.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattergl.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Scattergl + + new_trace = Scattergl( + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + error_x=error_x, + error_y=error_y, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + x=x, + x0=x0, + xaxis=xaxis, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + y=y, + y0=y0, + yaxis=yaxis, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_scattermap( + self, + below=None, + cluster=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + lat=None, + latsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + lon=None, + lonsrc=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textfont=None, + textposition=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Scattermap trace + + The data visualized as scatter point, lines or marker symbols + on a MapLibre GL geographic map is provided by + longitude/latitude pairs in `lon` and `lat`. + + Parameters + ---------- + below + Determines if this scattermap trace's layers are to be + inserted before the layer with the specified ID. By + default, scattermap layers are inserted above all the + base layers. To place the scattermap layers above every + other layer, set `below` to "''". + cluster + :class:`plotly.graph_objects.scattermap.Cluster` + instance or dict with compatible properties + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattermap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattermap.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattermap.Line` instance + or dict with compatible properties + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + marker + :class:`plotly.graph_objects.scattermap.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattermap.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattermap.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a map subplot. If "map" (the default value), the + data refer to `layout.map`. If "map2", the data refer + to `layout.map2`, and so on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textfont + Sets the icon text font (color=map.layer.paint.text- + color, size=map.layer.layout.text-size). Has an effect + only when `type` is set to "symbol". + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `lat`, `lon` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattermap.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Scattermap + + new_trace = Scattermap( + below=below, + cluster=cluster, + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + lat=lat, + latsrc=latsrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + lon=lon, + lonsrc=lonsrc, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + subplot=subplot, + text=text, + textfont=textfont, + textposition=textposition, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scattermapbox( + self, + below=None, + cluster=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + lat=None, + latsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + lon=None, + lonsrc=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textfont=None, + textposition=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Scattermapbox trace + + "scattermapbox" trace is deprecated! Please consider switching + to the "scattermap" trace type and `map` subplots. Learn more + at: https://plotly.com/python/maplibre-migration/ as well as + https://plotly.com/javascript/maplibre-migration/ The data + visualized as scatter point, lines or marker symbols on a + Mapbox GL geographic map is provided by longitude/latitude + pairs in `lon` and `lat`. + + Parameters + ---------- + below + Determines if this scattermapbox trace's layers are to + be inserted before the layer with the specified ID. By + default, scattermapbox layers are inserted above all + the base layers. To place the scattermapbox layers + above every other layer, set `below` to "''". + cluster + :class:`plotly.graph_objects.scattermapbox.Cluster` + instance or dict with compatible properties + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattermapbox.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattermapbox.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattermapbox.Line` + instance or dict with compatible properties + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + marker + :class:`plotly.graph_objects.scattermapbox.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattermapbox.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattermapbox.Stream` + instance or dict with compatible properties + subplot + mapbox subplots and traces are deprecated! Please + consider switching to `map` subplots and traces. Learn + more at: https://plotly.com/python/maplibre-migration/ + as well as https://plotly.com/javascript/maplibre- + migration/ Sets a reference between this trace's data + coordinates and a mapbox subplot. If "mapbox" (the + default value), the data refer to `layout.mapbox`. If + "mapbox2", the data refer to `layout.mapbox2`, and so + on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textfont + Sets the icon text font (color=mapbox.layer.paint.text- + color, size=mapbox.layer.layout.text-size). Has an + effect only when `type` is set to "symbol". + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `lat`, `lon` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattermapbox.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Scattermapbox + + new_trace = Scattermapbox( + below=below, + cluster=cluster, + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + lat=lat, + latsrc=latsrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + lon=lon, + lonsrc=lonsrc, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + subplot=subplot, + text=text, + textfont=textfont, + textposition=textposition, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scatterpolar( + self, + cliponaxis=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + dr=None, + dtheta=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + r=None, + r0=None, + rsrc=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + theta=None, + theta0=None, + thetasrc=None, + thetaunit=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Scatterpolar trace + + The scatterpolar trace type encompasses line charts, scatter + charts, text charts, and bubble charts in polar coordinates. + The data visualized as scatter point or lines is set in `r` + (radial) and `theta` (angular) coordinates Text (appearing + either on the chart or on hover only) is via `text`. Bubble + charts are achieved by setting `marker.size` and/or + `marker.color` to numerical arrays. + + Parameters + ---------- + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dr + Sets the r coordinate step. + dtheta + Sets the theta coordinate step. By default, the + `dtheta` step equals the subplot's period divided by + the length of the `r` coordinates. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scatterpolar has a subset of + the options available to scatter. "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatterpolar.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatterpolar.Legendgroupti + tle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatterpolar.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scatterpolar.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + r + Sets the radial coordinates + r0 + Alternate to `r`. Builds a linear space of r + coordinates. Use with `dr` where `r0` is the starting + coordinate and `dr` the step. + rsrc + Sets the source reference on Chart Studio Cloud for + `r`. + selected + :class:`plotly.graph_objects.scatterpolar.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatterpolar.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a polar subplot. If "polar" (the default value), + the data refer to `layout.polar`. If "polar2", the data + refer to `layout.polar2`, and so on. + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `r`, `theta` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + theta + Sets the angular coordinates + theta0 + Alternate to `theta`. Builds a linear space of theta + coordinates. Use with `dtheta` where `theta0` is the + starting coordinate and `dtheta` the step. + thetasrc + Sets the source reference on Chart Studio Cloud for + `theta`. + thetaunit + Sets the unit of input "theta" values. Has an effect + only when on "linear" angular axes. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatterpolar.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Scatterpolar + + new_trace = Scatterpolar( + cliponaxis=cliponaxis, + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + dr=dr, + dtheta=dtheta, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + r=r, + r0=r0, + rsrc=rsrc, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + subplot=subplot, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + theta=theta, + theta0=theta0, + thetasrc=thetasrc, + thetaunit=thetaunit, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scatterpolargl( + self, + connectgaps=None, + customdata=None, + customdatasrc=None, + dr=None, + dtheta=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + r=None, + r0=None, + rsrc=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + theta=None, + theta0=None, + thetasrc=None, + thetaunit=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Scatterpolargl trace + + The scatterpolargl trace type encompasses line charts, scatter + charts, and bubble charts in polar coordinates using the WebGL + plotting engine. The data visualized as scatter point or lines + is set in `r` (radial) and `theta` (angular) coordinates Bubble + charts are achieved by setting `marker.size` and/or + `marker.color` to numerical arrays. + + Parameters + ---------- + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dr + Sets the r coordinate step. + dtheta + Sets the theta coordinate step. By default, the + `dtheta` step equals the subplot's period divided by + the length of the `r` coordinates. + fill + Sets the area to fill with a solid color. Defaults to + "none" unless this trace is stacked, then it gets + "tonexty" ("tonextx") if `orientation` is "v" ("h") Use + with `fillcolor` if not "none". "tozerox" and "tozeroy" + fill to x=0 and y=0 respectively. "tonextx" and + "tonexty" fill between the endpoints of this trace and + the endpoints of the trace before it, connecting those + endpoints with straight lines (to make a stacked area + graph); if there is no trace before it, they behave + like "tozerox" and "tozeroy". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. Traces in a `stackgroup` will only fill to (or + be filled to) other traces in the same group. With + multiple `stackgroup`s or some traces stacked and some + not, if fill-linked traces are not already consecutive, + the later ones will be pushed down in the drawing + order. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatterpolargl.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatterpolargl.Legendgroup + title` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatterpolargl.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scatterpolargl.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + r + Sets the radial coordinates + r0 + Alternate to `r`. Builds a linear space of r + coordinates. Use with `dr` where `r0` is the starting + coordinate and `dr` the step. + rsrc + Sets the source reference on Chart Studio Cloud for + `r`. + selected + :class:`plotly.graph_objects.scatterpolargl.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatterpolargl.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a polar subplot. If "polar" (the default value), + the data refer to `layout.polar`. If "polar2", the data + refer to `layout.polar2`, and so on. + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `r`, `theta` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + theta + Sets the angular coordinates + theta0 + Alternate to `theta`. Builds a linear space of theta + coordinates. Use with `dtheta` where `theta0` is the + starting coordinate and `dtheta` the step. + thetasrc + Sets the source reference on Chart Studio Cloud for + `theta`. + thetaunit + Sets the unit of input "theta" values. Has an effect + only when on "linear" angular axes. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatterpolargl.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Scatterpolargl + + new_trace = Scatterpolargl( + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + dr=dr, + dtheta=dtheta, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + r=r, + r0=r0, + rsrc=rsrc, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + subplot=subplot, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + theta=theta, + theta0=theta0, + thetasrc=thetasrc, + thetaunit=thetaunit, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scattersmith( + self, + cliponaxis=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + imag=None, + imagsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + real=None, + realsrc=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Scattersmith trace + + The scattersmith trace type encompasses line charts, scatter + charts, text charts, and bubble charts in smith coordinates. + The data visualized as scatter point or lines is set in `real` + and `imag` (imaginary) coordinates Text (appearing either on + the chart or on hover only) is via `text`. Bubble charts are + achieved by setting `marker.size` and/or `marker.color` to + numerical arrays. + + Parameters + ---------- + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scattersmith has a subset of + the options available to scatter. "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattersmith.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + imag + Sets the imaginary component of the data, in units of + normalized impedance such that real=1, imag=0 is the + center of the chart. + imagsrc + Sets the source reference on Chart Studio Cloud for + `imag`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattersmith.Legendgroupti + tle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattersmith.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scattersmith.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + real + Sets the real component of the data, in units of + normalized impedance such that real=1, imag=0 is the + center of the chart. + realsrc + Sets the source reference on Chart Studio Cloud for + `real`. + selected + :class:`plotly.graph_objects.scattersmith.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattersmith.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a smith subplot. If "smith" (the default value), + the data refer to `layout.smith`. If "smith2", the data + refer to `layout.smith2`, and so on. + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `real`, `imag` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattersmith.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Scattersmith + + new_trace = Scattersmith( + cliponaxis=cliponaxis, + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + imag=imag, + imagsrc=imagsrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + real=real, + realsrc=realsrc, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + subplot=subplot, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scatterternary( + self, + a=None, + asrc=None, + b=None, + bsrc=None, + c=None, + cliponaxis=None, + connectgaps=None, + csrc=None, + customdata=None, + customdatasrc=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + sum=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Scatterternary trace + + Provides similar functionality to the "scatter" type but on a + ternary phase diagram. The data is provided by at least two + arrays out of `a`, `b`, `c` triplets. + + Parameters + ---------- + a + Sets the quantity of component `a` in each data point. + If `a`, `b`, and `c` are all provided, they need not be + normalized, only the relative values matter. If only + two arrays are provided they must be normalized to + match `ternary.sum`. + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + b + Sets the quantity of component `a` in each data point. + If `a`, `b`, and `c` are all provided, they need not be + normalized, only the relative values matter. If only + two arrays are provided they must be normalized to + match `ternary.sum`. + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + c + Sets the quantity of component `a` in each data point. + If `a`, `b`, and `c` are all provided, they need not be + normalized, only the relative values matter. If only + two arrays are provided they must be normalized to + match `ternary.sum`. + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + csrc + Sets the source reference on Chart Studio Cloud for + `c`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scatterternary has a subset + of the options available to scatter. "toself" connects + the endpoints of the trace (or each segment of the + trace if it has gaps) into a closed shape. "tonext" + fills the space between two traces if one completely + encloses the other (eg consecutive contour lines), and + behaves like "toself" if there is no trace before it. + "tonext" should not be used if one trace does not + enclose the other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatterternary.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (a,b,c) + point. If a single string, the same string appears over + all the data points. If an array of strings, the items + are mapped in order to the the data points in (a,b,c). + To be seen, trace `hoverinfo` must contain a "text" + flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatterternary.Legendgroup + title` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatterternary.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scatterternary.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scatterternary.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatterternary.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a ternary subplot. If "ternary" (the default + value), the data refer to `layout.ternary`. If + "ternary2", the data refer to `layout.ternary2`, and so + on. + sum + The number each triplet should sum to, if only two of + `a`, `b`, and `c` are provided. This overrides + `ternary.sum` to normalize this specific trace, but + does not affect the values displayed on the axes. 0 (or + missing) means to use ternary.sum + text + Sets text elements associated with each (a,b,c) point. + If a single string, the same string appears over all + the data points. If an array of strings, the items are + mapped in order to the the data points in (a,b,c). If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `a`, `b`, `c` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatterternary.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Scatterternary + + new_trace = Scatterternary( + a=a, + asrc=asrc, + b=b, + bsrc=bsrc, + c=c, + cliponaxis=cliponaxis, + connectgaps=connectgaps, + csrc=csrc, + customdata=customdata, + customdatasrc=customdatasrc, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + subplot=subplot, + sum=sum, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_splom( + self, + customdata=None, + customdatasrc=None, + diagonal=None, + dimensions=None, + dimensiondefaults=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + showlowerhalf=None, + showupperhalf=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + xaxes=None, + xhoverformat=None, + yaxes=None, + yhoverformat=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Splom trace + + Splom traces generate scatter plot matrix visualizations. Each + splom `dimensions` items correspond to a generated axis. Values + for each of those dimensions are set in `dimensions[i].values`. + Splom traces support all `scattergl` marker style attributes. + Specify `layout.grid` attributes and/or layout x-axis and + y-axis attributes for more control over the axis positioning + and style. + + Parameters + ---------- + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + diagonal + :class:`plotly.graph_objects.splom.Diagonal` instance + or dict with compatible properties + dimensions + A tuple of + :class:`plotly.graph_objects.splom.Dimension` instances + or dicts with compatible properties + dimensiondefaults + When used in a template (as + layout.template.data.splom.dimensiondefaults), sets the + default property values to use for elements of + splom.dimensions + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.splom.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.splom.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.splom.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.splom.Selected` instance + or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showlowerhalf + Determines whether or not subplots on the lower half + from the diagonal are displayed. + showupperhalf + Determines whether or not subplots on the upper half + from the diagonal are displayed. + stream + :class:`plotly.graph_objects.splom.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each (x,y) pair to + appear on hover. If a single string, the same string + appears over all the data points. If an array of + string, the items are mapped in order to the this + trace's (x,y) coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.splom.Unselected` instance + or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + xaxes + Sets the list of x axes corresponding to dimensions of + this splom trace. By default, a splom will match the + first N xaxes where N is the number of input + dimensions. Note that, in case where `diagonal.visible` + is false and `showupperhalf` or `showlowerhalf` is + false, this splom trace will generate one less x-axis + and one less y-axis. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + yaxes + Sets the list of y axes corresponding to dimensions of + this splom trace. By default, a splom will match the + first N yaxes where N is the number of input + dimensions. Note that, in case where `diagonal.visible` + is false and `showupperhalf` or `showlowerhalf` is + false, this splom trace will generate one less x-axis + and one less y-axis. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Splom + + new_trace = Splom( + customdata=customdata, + customdatasrc=customdatasrc, + diagonal=diagonal, + dimensions=dimensions, + dimensiondefaults=dimensiondefaults, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + showlowerhalf=showlowerhalf, + showupperhalf=showupperhalf, + stream=stream, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + xaxes=xaxes, + xhoverformat=xhoverformat, + yaxes=yaxes, + yhoverformat=yhoverformat, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_streamtube( + self, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + maxdisplayed=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + sizeref=None, + starts=None, + stream=None, + text=None, + u=None, + uhoverformat=None, + uid=None, + uirevision=None, + usrc=None, + v=None, + vhoverformat=None, + visible=None, + vsrc=None, + w=None, + whoverformat=None, + wsrc=None, + x=None, + xhoverformat=None, + xsrc=None, + y=None, + yhoverformat=None, + ysrc=None, + z=None, + zhoverformat=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Streamtube trace + + Use a streamtube trace to visualize flow in a vector field. + Specify a vector field using 6 1D arrays of equal length, 3 + position arrays `x`, `y` and `z` and 3 vector component arrays + `u`, `v`, and `w`. By default, the tubes' starting positions + will be cut from the vector field's x-z plane at its minimum y + value. To specify your own starting position, use attributes + `starts.x`, `starts.y` and `starts.z`. The color is encoded by + the norm of (u, v, w), and the local radius by the divergence + of (u, v, w). + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here u/v/w norm) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmin` + must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as u/v/w norm. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmax` + must be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.streamtube.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.streamtube.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `tubex`, `tubey`, `tubez`, `tubeu`, + `tubev`, `tubew`, `norm` and `divergence`. Anything + contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.streamtube.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.streamtube.Lighting` + instance or dict with compatible properties + lightposition + :class:`plotly.graph_objects.streamtube.Lightposition` + instance or dict with compatible properties + maxdisplayed + The maximum number of displayed segments in a + streamtube. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + sizeref + The scaling factor for the streamtubes. The default is + 1, which avoids two max divergence tubes from touching + at adjacent starting positions. + starts + :class:`plotly.graph_objects.streamtube.Starts` + instance or dict with compatible properties + stream + :class:`plotly.graph_objects.streamtube.Stream` + instance or dict with compatible properties + text + Sets a text element associated with this trace. If + trace `hoverinfo` contains a "text" flag, this text + element will be seen in all hover labels. Note that + streamtube traces do not support array `text` values. + u + Sets the x components of the vector field. + uhoverformat + Sets the hover text formatting rulefor `u` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + usrc + Sets the source reference on Chart Studio Cloud for + `u`. + v + Sets the y components of the vector field. + vhoverformat + Sets the hover text formatting rulefor `v` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + vsrc + Sets the source reference on Chart Studio Cloud for + `v`. + w + Sets the z components of the vector field. + whoverformat + Sets the hover text formatting rulefor `w` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + wsrc + Sets the source reference on Chart Studio Cloud for + `w`. + x + Sets the x coordinates of the vector field. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates of the vector field. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates of the vector field. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Streamtube + + new_trace = Streamtube( + autocolorscale=autocolorscale, + cauto=cauto, + cmax=cmax, + cmid=cmid, + cmin=cmin, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lighting=lighting, + lightposition=lightposition, + maxdisplayed=maxdisplayed, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + reversescale=reversescale, + scene=scene, + showlegend=showlegend, + showscale=showscale, + sizeref=sizeref, + starts=starts, + stream=stream, + text=text, + u=u, + uhoverformat=uhoverformat, + uid=uid, + uirevision=uirevision, + usrc=usrc, + v=v, + vhoverformat=vhoverformat, + visible=visible, + vsrc=vsrc, + w=w, + whoverformat=whoverformat, + wsrc=wsrc, + x=x, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zhoverformat=zhoverformat, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_sunburst( + self, + branchvalues=None, + count=None, + customdata=None, + customdatasrc=None, + domain=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextfont=None, + insidetextorientation=None, + labels=None, + labelssrc=None, + leaf=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + level=None, + marker=None, + maxdepth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + outsidetextfont=None, + parents=None, + parentssrc=None, + root=None, + rotation=None, + sort=None, + stream=None, + text=None, + textfont=None, + textinfo=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + values=None, + valuessrc=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Sunburst trace + + Visualize hierarchal data spanning outward radially from root + to leaves. The sunburst sectors are determined by the entries + in "labels" or "ids" and in "parents". + + Parameters + ---------- + branchvalues + Determines how the items in `values` are summed. When + set to "total", items in `values` are taken to be value + of all its descendants. When set to "remainder", items + in `values` corresponding to the root and the branches + sectors are taken to be the extra part not part of the + sum of the values at their leaves. + count + Determines default for `values` when it is not + provided, by inferring a 1 for each of the "leaves" + and/or "branches", otherwise 0. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.sunburst.Domain` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.sunburst.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry` and `percentParent`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + insidetextorientation + Controls the orientation of the text inside chart + sectors. When set to "auto", text may be oriented in + any direction in order to be as big as possible in the + middle of a sector. The "horizontal" option orients + text to be parallel with the bottom of the chart, and + may make text smaller in order to achieve that goal. + The "radial" option orients text along the radius of + the sector. The "tangential" option orients text + perpendicular to the radius of the sector. + labels + Sets the labels of each of the sectors. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + leaf + :class:`plotly.graph_objects.sunburst.Leaf` instance or + dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.sunburst.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + level + Sets the level from which this trace hierarchy is + rendered. Set `level` to `''` to start from the root + node in the hierarchy. Must be an "id" if `ids` is + filled in, otherwise plotly attempts to find a matching + item in `labels`. + marker + :class:`plotly.graph_objects.sunburst.Marker` instance + or dict with compatible properties + maxdepth + Sets the number of rendered sectors from any given + `level`. Set `maxdepth` to "-1" to render all the + levels in the hierarchy. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. This option refers to the root of the hierarchy + presented at the center of a sunburst graph. Please + note that if a hierarchy has multiple root nodes, this + option won't have any effect and `insidetextfont` would + be used. + parents + Sets the parent sectors for each of the sectors. Empty + string items '' are understood to reference the root + node in the hierarchy. If `ids` is filled, `parents` + items are understood to be "ids" themselves. When `ids` + is not set, plotly attempts to find matching items in + `labels`, but beware they must be unique. + parentssrc + Sets the source reference on Chart Studio Cloud for + `parents`. + root + :class:`plotly.graph_objects.sunburst.Root` instance or + dict with compatible properties + rotation + Rotates the whole diagram counterclockwise by some + angle. By default the first slice starts at 3 o'clock. + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.sunburst.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry`, `percentParent`, `label` + and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values associated with each of the sectors. + Use with `branchvalues` to determine how the values are + summed. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Sunburst + + new_trace = Sunburst( + branchvalues=branchvalues, + count=count, + customdata=customdata, + customdatasrc=customdatasrc, + domain=domain, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextfont=insidetextfont, + insidetextorientation=insidetextorientation, + labels=labels, + labelssrc=labelssrc, + leaf=leaf, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + level=level, + marker=marker, + maxdepth=maxdepth, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + outsidetextfont=outsidetextfont, + parents=parents, + parentssrc=parentssrc, + root=root, + rotation=rotation, + sort=sort, + stream=stream, + text=text, + textfont=textfont, + textinfo=textinfo, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + values=values, + valuessrc=valuessrc, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_surface( + self, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + coloraxis=None, + colorbar=None, + colorscale=None, + connectgaps=None, + contours=None, + customdata=None, + customdatasrc=None, + hidesurface=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + opacityscale=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + stream=None, + surfacecolor=None, + surfacecolorsrc=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xcalendar=None, + xhoverformat=None, + xsrc=None, + y=None, + ycalendar=None, + yhoverformat=None, + ysrc=None, + z=None, + zcalendar=None, + zhoverformat=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Surface trace + + The data the describes the coordinates of the surface is set in + `z`. Data in `z` should be a 2D list. Coordinates in `x` and + `y` can either be 1D lists or 2D lists (e.g. to graph + parametric surfaces). If not provided in `x` and `y`, the x and + y coordinates are assumed to be linear starting at 0 with a + unit step. The color scale corresponds to the `z` values by + default. For custom color scales, use `surfacecolor` which + should be a 2D list, where its bounds can be controlled using + `cmin` and `cmax`. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here z or surfacecolor) + or the bounds set in `cmin` and `cmax` Defaults to + `false` when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as z or surfacecolor and if set, + `cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as z or surfacecolor. + Has no effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as z or surfacecolor and if set, + `cmax` must be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.surface.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data are filled in. + contours + :class:`plotly.graph_objects.surface.Contours` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hidesurface + Determines whether or not a surface is drawn. For + example, set `hidesurface` to False `contours.x.show` + to True and `contours.y.show` to True to draw a wire + frame plot. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.surface.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.surface.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.surface.Lighting` instance + or dict with compatible properties + lightposition + :class:`plotly.graph_objects.surface.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + opacityscale + Sets the opacityscale. The opacityscale must be an + array containing arrays mapping a normalized value to + an opacity value. At minimum, a mapping for the lowest + (0) and highest (1) values are required. For example, + `[[0, 1], [0.5, 0.2], [1, 1]]` means that higher/lower + values would have higher opacity values and those in + the middle would be more transparent Alternatively, + `opacityscale` may be a palette name string of the + following list: 'min', 'max', 'extremes' and 'uniform'. + The default is 'uniform'. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.surface.Stream` instance + or dict with compatible properties + surfacecolor + Sets the surface color values, used for setting a color + scale independent of `z`. + surfacecolorsrc + Sets the source reference on Chart Studio Cloud for + `surfacecolor`. + text + Sets the text elements associated with each z value. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates. + zcalendar + Sets the calendar system to use with `z` date data. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Surface + + new_trace = Surface( + autocolorscale=autocolorscale, + cauto=cauto, + cmax=cmax, + cmid=cmid, + cmin=cmin, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + connectgaps=connectgaps, + contours=contours, + customdata=customdata, + customdatasrc=customdatasrc, + hidesurface=hidesurface, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lighting=lighting, + lightposition=lightposition, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + opacityscale=opacityscale, + reversescale=reversescale, + scene=scene, + showlegend=showlegend, + showscale=showscale, + stream=stream, + surfacecolor=surfacecolor, + surfacecolorsrc=surfacecolorsrc, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zcalendar=zcalendar, + zhoverformat=zhoverformat, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_table( + self, + cells=None, + columnorder=None, + columnordersrc=None, + columnwidth=None, + columnwidthsrc=None, + customdata=None, + customdatasrc=None, + domain=None, + header=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + ids=None, + idssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + meta=None, + metasrc=None, + name=None, + stream=None, + uid=None, + uirevision=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Table trace + + Table view for detailed data viewing. The data are arranged in + a grid of rows and columns. Most styling can be specified for + columns, rows or individual cells. Table is using a column- + major order, ie. the grid is represented as a vector of column + vectors. + + Parameters + ---------- + cells + :class:`plotly.graph_objects.table.Cells` instance or + dict with compatible properties + columnorder + Specifies the rendered order of the data columns; for + example, a value `2` at position `0` means that column + index `0` in the data will be rendered as the third + column, as columns have an index base of zero. + columnordersrc + Sets the source reference on Chart Studio Cloud for + `columnorder`. + columnwidth + The width of columns expressed as a ratio. Columns fill + the available width in proportion of their specified + column widths. + columnwidthsrc + Sets the source reference on Chart Studio Cloud for + `columnwidth`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.table.Domain` instance or + dict with compatible properties + header + :class:`plotly.graph_objects.table.Header` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.table.Hoverlabel` instance + or dict with compatible properties + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.table.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + stream + :class:`plotly.graph_objects.table.Stream` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Table + + new_trace = Table( + cells=cells, + columnorder=columnorder, + columnordersrc=columnordersrc, + columnwidth=columnwidth, + columnwidthsrc=columnwidthsrc, + customdata=customdata, + customdatasrc=customdatasrc, + domain=domain, + header=header, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + meta=meta, + metasrc=metasrc, + name=name, + stream=stream, + uid=uid, + uirevision=uirevision, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_treemap( + self, + branchvalues=None, + count=None, + customdata=None, + customdatasrc=None, + domain=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextfont=None, + labels=None, + labelssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + level=None, + marker=None, + maxdepth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + outsidetextfont=None, + parents=None, + parentssrc=None, + pathbar=None, + root=None, + sort=None, + stream=None, + text=None, + textfont=None, + textinfo=None, + textposition=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + tiling=None, + uid=None, + uirevision=None, + values=None, + valuessrc=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Treemap trace + + Visualize hierarchal data from leaves (and/or outer branches) + towards root with rectangles. The treemap sectors are + determined by the entries in "labels" or "ids" and in + "parents". + + Parameters + ---------- + branchvalues + Determines how the items in `values` are summed. When + set to "total", items in `values` are taken to be value + of all its descendants. When set to "remainder", items + in `values` corresponding to the root and the branches + sectors are taken to be the extra part not part of the + sum of the values at their leaves. + count + Determines default for `values` when it is not + provided, by inferring a 1 for each of the "leaves" + and/or "branches", otherwise 0. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.treemap.Domain` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.treemap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry` and `percentParent`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + labels + Sets the labels of each of the sectors. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.treemap.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + level + Sets the level from which this trace hierarchy is + rendered. Set `level` to `''` to start from the root + node in the hierarchy. Must be an "id" if `ids` is + filled in, otherwise plotly attempts to find a matching + item in `labels`. + marker + :class:`plotly.graph_objects.treemap.Marker` instance + or dict with compatible properties + maxdepth + Sets the number of rendered sectors from any given + `level`. Set `maxdepth` to "-1" to render all the + levels in the hierarchy. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. This option refers to the root of the hierarchy + presented on top left corner of a treemap graph. Please + note that if a hierarchy has multiple root nodes, this + option won't have any effect and `insidetextfont` would + be used. + parents + Sets the parent sectors for each of the sectors. Empty + string items '' are understood to reference the root + node in the hierarchy. If `ids` is filled, `parents` + items are understood to be "ids" themselves. When `ids` + is not set, plotly attempts to find matching items in + `labels`, but beware they must be unique. + parentssrc + Sets the source reference on Chart Studio Cloud for + `parents`. + pathbar + :class:`plotly.graph_objects.treemap.Pathbar` instance + or dict with compatible properties + root + :class:`plotly.graph_objects.treemap.Root` instance or + dict with compatible properties + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.treemap.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Sets the positions of the `text` elements. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry`, `percentParent`, `label` + and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + tiling + :class:`plotly.graph_objects.treemap.Tiling` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values associated with each of the sectors. + Use with `branchvalues` to determine how the values are + summed. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Treemap + + new_trace = Treemap( + branchvalues=branchvalues, + count=count, + customdata=customdata, + customdatasrc=customdatasrc, + domain=domain, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextfont=insidetextfont, + labels=labels, + labelssrc=labelssrc, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + level=level, + marker=marker, + maxdepth=maxdepth, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + outsidetextfont=outsidetextfont, + parents=parents, + parentssrc=parentssrc, + pathbar=pathbar, + root=root, + sort=sort, + stream=stream, + text=text, + textfont=textfont, + textinfo=textinfo, + textposition=textposition, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + tiling=tiling, + uid=uid, + uirevision=uirevision, + values=values, + valuessrc=valuessrc, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_violin( + self, + alignmentgroup=None, + bandwidth=None, + box=None, + customdata=None, + customdatasrc=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + jitter=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meanline=None, + meta=None, + metasrc=None, + name=None, + offsetgroup=None, + opacity=None, + orientation=None, + pointpos=None, + points=None, + quartilemethod=None, + scalegroup=None, + scalemode=None, + selected=None, + selectedpoints=None, + showlegend=None, + side=None, + span=None, + spanmode=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + width=None, + x=None, + x0=None, + xaxis=None, + xhoverformat=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + yhoverformat=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Violin trace + + In vertical (horizontal) violin plots, statistics are computed + using `y` (`x`) values. By supplying an `x` (`y`) array, one + violin per distinct x (y) value is drawn If no `x` (`y`) list + is provided, a single violin is drawn. That violin position is + then positioned with with `name` or with `x0` (`y0`) if + provided. + + Parameters + ---------- + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + bandwidth + Sets the bandwidth used to compute the kernel density + estimate. By default, the bandwidth is determined by + Silverman's rule of thumb. + box + :class:`plotly.graph_objects.violin.Box` instance or + dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.violin.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual violins or + sample points or the kernel density estimate or any + combination of them? + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + jitter + Sets the amount of jitter in the sample points drawn. + If 0, the sample points align along the distribution + axis. If 1, the sample points are drawn in a random + jitter of width equal to the width of the violins. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.violin.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.violin.Line` instance or + dict with compatible properties + marker + :class:`plotly.graph_objects.violin.Marker` instance or + dict with compatible properties + meanline + :class:`plotly.graph_objects.violin.Meanline` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. For violin traces, the name + will also be used for the position coordinate, if `x` + and `x0` (`y` and `y0` if horizontal) are missing and + the position axis is categorical. Note that the trace + name is also used as a default value for attribute + `scalegroup` (please see its description for details). + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the violin(s). If "v" ("h"), + the distribution is visualized along the vertical + (horizontal). + pointpos + Sets the position of the sample points in relation to + the violins. If 0, the sample points are places over + the center of the violins. Positive (negative) values + correspond to positions to the right (left) for + vertical violins and above (below) for horizontal + violins. + points + If "outliers", only the sample points lying outside the + whiskers are shown If "suspectedoutliers", the outlier + points are shown and points either less than 4*Q1-3*Q3 + or greater than 4*Q3-3*Q1 are highlighted (see + `outliercolor`) If "all", all sample points are shown + If False, only the violins are shown with no sample + points. Defaults to "suspectedoutliers" when + `marker.outliercolor` or `marker.line.outliercolor` is + set, otherwise defaults to "outliers". + quartilemethod + Sets the method used to compute the sample's Q1 and Q3 + quartiles. The "linear" method uses the 25th percentile + for Q1 and 75th percentile for Q3 as computed using + method #10 (listed on + http://jse.amstat.org/v14n3/langford.html). The + "exclusive" method uses the median to divide the + ordered dataset into two halves if the sample is odd, + it does not include the median in either half - Q1 is + then the median of the lower half and Q3 the median of + the upper half. The "inclusive" method also uses the + median to divide the ordered dataset into two halves + but if the sample is odd, it includes the median in + both halves - Q1 is then the median of the lower half + and Q3 the median of the upper half. + scalegroup + If there are multiple violins that should be sized + according to to some metric (see `scalemode`), link + them by providing a non-empty group id here shared by + every trace in the same group. If a violin's `width` is + undefined, `scalegroup` will default to the trace's + name. In this case, violins with the same names will be + linked together + scalemode + Sets the metric by which the width of each violin is + determined. "width" means each violin has the same + (max) width "count" means the violins are scaled by the + number of sample points making up each violin. + selected + :class:`plotly.graph_objects.violin.Selected` instance + or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + side + Determines on which side of the position value the + density function making up one half of a violin is + plotted. Useful when comparing two violin traces under + "overlay" mode, where one trace has `side` set to + "positive" and the other to "negative". + span + Sets the span in data space for which the density + function will be computed. Has an effect only when + `spanmode` is set to "manual". + spanmode + Sets the method by which the span in data space where + the density function will be computed. "soft" means the + span goes from the sample's minimum value minus two + bandwidths to the sample's maximum value plus two + bandwidths. "hard" means the span goes from the + sample's minimum to its maximum value. For custom span + settings, use mode "manual" and fill in the `span` + attribute. + stream + :class:`plotly.graph_objects.violin.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with each sample + value. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.violin.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the width of the violin in data coordinates. If 0 + (default value) the width is automatically selected + based on the positions of other violin traces in the + same subplot. + x + Sets the x sample data or coordinates. See overview for + more info. + x0 + Sets the x coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y sample data or coordinates. See overview for + more info. + y0 + Sets the y coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Violin + + new_trace = Violin( + alignmentgroup=alignmentgroup, + bandwidth=bandwidth, + box=box, + customdata=customdata, + customdatasrc=customdatasrc, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + jitter=jitter, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meanline=meanline, + meta=meta, + metasrc=metasrc, + name=name, + offsetgroup=offsetgroup, + opacity=opacity, + orientation=orientation, + pointpos=pointpos, + points=points, + quartilemethod=quartilemethod, + scalegroup=scalegroup, + scalemode=scalemode, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + side=side, + span=span, + spanmode=spanmode, + stream=stream, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + width=width, + x=x, + x0=x0, + xaxis=xaxis, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + y0=y0, + yaxis=yaxis, + yhoverformat=yhoverformat, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_volume( + self, + autocolorscale=None, + caps=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + coloraxis=None, + colorbar=None, + colorscale=None, + contour=None, + customdata=None, + customdatasrc=None, + flatshading=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + isomax=None, + isomin=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + opacityscale=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + slices=None, + spaceframe=None, + stream=None, + surface=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + value=None, + valuehoverformat=None, + valuesrc=None, + visible=None, + x=None, + xhoverformat=None, + xsrc=None, + y=None, + yhoverformat=None, + ysrc=None, + z=None, + zhoverformat=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "Figure": + """ + Add a new Volume trace + + Draws volume trace between iso-min and iso-max values with + coordinates given by four 1-dimensional arrays containing the + `value`, `x`, `y` and `z` of every vertex of a uniform or non- + uniform 3-D grid. Horizontal or vertical slices, caps as well + as spaceframe between iso-min and iso-max values could also be + drawn using this trace. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + caps + :class:`plotly.graph_objects.volume.Caps` instance or + dict with compatible properties + cauto + Determines whether or not the color domain is computed + with respect to the input data (here `value`) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as `value` and if set, `cmin` must + be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as `value`. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as `value` and if set, `cmax` must + be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.volume.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contour + :class:`plotly.graph_objects.volume.Contour` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + flatshading + Determines whether or not normal smoothing is applied + to the meshes, creating meshes with an angular, low- + poly look via flat reflections. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.volume.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + isomax + Sets the maximum boundary for iso-surface plot. + isomin + Sets the minimum boundary for iso-surface plot. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.volume.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.volume.Lighting` instance + or dict with compatible properties + lightposition + :class:`plotly.graph_objects.volume.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + opacityscale + Sets the opacityscale. The opacityscale must be an + array containing arrays mapping a normalized value to + an opacity value. At minimum, a mapping for the lowest + (0) and highest (1) values are required. For example, + `[[0, 1], [0.5, 0.2], [1, 1]]` means that higher/lower + values would have higher opacity values and those in + the middle would be more transparent Alternatively, + `opacityscale` may be a palette name string of the + following list: 'min', 'max', 'extremes' and 'uniform'. + The default is 'uniform'. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + slices + :class:`plotly.graph_objects.volume.Slices` instance or + dict with compatible properties + spaceframe + :class:`plotly.graph_objects.volume.Spaceframe` + instance or dict with compatible properties + stream + :class:`plotly.graph_objects.volume.Stream` instance or + dict with compatible properties + surface + :class:`plotly.graph_objects.volume.Surface` instance + or dict with compatible properties + text + Sets the text elements associated with the vertices. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + value + Sets the 4th dimension (value) of the vertices. + valuehoverformat + Sets the hover text formatting rulefor `value` using + d3 formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + valuesrc + Sets the source reference on Chart Studio Cloud for + `value`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the X coordinates of the vertices on X axis. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the Y coordinates of the vertices on Y axis. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the Z coordinates of the vertices on Z axis. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + Figure + """ + from plotly.graph_objs import Volume + + new_trace = Volume( + autocolorscale=autocolorscale, + caps=caps, + cauto=cauto, + cmax=cmax, + cmid=cmid, + cmin=cmin, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + contour=contour, + customdata=customdata, + customdatasrc=customdatasrc, + flatshading=flatshading, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + isomax=isomax, + isomin=isomin, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lighting=lighting, + lightposition=lightposition, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + opacityscale=opacityscale, + reversescale=reversescale, + scene=scene, + showlegend=showlegend, + showscale=showscale, + slices=slices, + spaceframe=spaceframe, + stream=stream, + surface=surface, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + value=value, + valuehoverformat=valuehoverformat, + valuesrc=valuesrc, + visible=visible, + x=x, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zhoverformat=zhoverformat, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_waterfall( + self, + alignmentgroup=None, + base=None, + cliponaxis=None, + connector=None, + constraintext=None, + customdata=None, + customdatasrc=None, + decreasing=None, + dx=None, + dy=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + increasing=None, + insidetextanchor=None, + insidetextfont=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + measure=None, + measuresrc=None, + meta=None, + metasrc=None, + name=None, + offset=None, + offsetgroup=None, + offsetsrc=None, + opacity=None, + orientation=None, + outsidetextfont=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textangle=None, + textfont=None, + textinfo=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + totals=None, + uid=None, + uirevision=None, + visible=None, + width=None, + widthsrc=None, + x=None, + x0=None, + xaxis=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Add a new Waterfall trace + + Draws waterfall trace which is useful graph to displays the + contribution of various elements (either positive or negative) + in a bar chart. The data visualized by the span of the bars is + set in `y` if `orientation` is set to "v" (the default) and the + labels are set in `x`. By setting `orientation` to "h", the + roles are interchanged. + + Parameters + ---------- + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + base + Sets where the bar base is drawn (in position axis + units). + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + connector + :class:`plotly.graph_objects.waterfall.Connector` + instance or dict with compatible properties + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + decreasing + :class:`plotly.graph_objects.waterfall.Decreasing` + instance or dict with compatible properties + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.waterfall.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `initial`, `delta` and `final`. Anything + contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + increasing + :class:`plotly.graph_objects.waterfall.Increasing` + instance or dict with compatible properties + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.waterfall.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + measure + An array containing types of values. By default the + values are considered as 'relative'. However; it is + possible to use 'total' to compute the sums. Also + 'absolute' could be applied to reset the computed total + or to declare an initial value where needed. + measuresrc + Sets the source reference on Chart Studio Cloud for + `measure`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the position where the bar is drawn (in position + axis units). In "group" barmode, traces that set + "offset" will be excluded and drawn in "overlay" mode + instead. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + offsetsrc + Sets the source reference on Chart Studio Cloud for + `offset`. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the bars. With "v" ("h"), the + value of the each bar spans along the vertical + (horizontal). + outsidetextfont + Sets the font used for `text` lying outside the bar. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.waterfall.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the font used for `text`. + textinfo + Determines which trace information appear on the graph. + In the case of having multiple waterfalls, totals are + computed separately (per trace). + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `initial`, `delta`, `final` and `label`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + totals + :class:`plotly.graph_objects.waterfall.Totals` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar width (in position axis units). + widthsrc + Sets the source reference on Chart Studio Cloud for + `width`. + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + Figure + """ + from plotly.graph_objs import Waterfall + + new_trace = Waterfall( + alignmentgroup=alignmentgroup, + base=base, + cliponaxis=cliponaxis, + connector=connector, + constraintext=constraintext, + customdata=customdata, + customdatasrc=customdatasrc, + decreasing=decreasing, + dx=dx, + dy=dy, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + increasing=increasing, + insidetextanchor=insidetextanchor, + insidetextfont=insidetextfont, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + measure=measure, + measuresrc=measuresrc, + meta=meta, + metasrc=metasrc, + name=name, + offset=offset, + offsetgroup=offsetgroup, + offsetsrc=offsetsrc, + opacity=opacity, + orientation=orientation, + outsidetextfont=outsidetextfont, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textangle=textangle, + textfont=textfont, + textinfo=textinfo, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + totals=totals, + uid=uid, + uirevision=uirevision, + visible=visible, + width=width, + widthsrc=widthsrc, + x=x, + x0=x0, + xaxis=xaxis, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + y=y, + y0=y0, + yaxis=yaxis, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def select_coloraxes(self, selector=None, row=None, col=None): + """ + Select coloraxis subplot objects from a particular subplot cell + and/or coloraxis subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + coloraxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all coloraxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + coloraxis and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of coloraxis objects to select. + To select coloraxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all coloraxis objects are selected. + Returns + ------- + generator + Generator that iterates through all of the coloraxis + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("coloraxis", selector, row, col) + + def for_each_coloraxis(self, fn, selector=None, row=None, col=None) -> "Figure": + """ + Apply a function to all coloraxis objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single coloraxis object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + coloraxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all coloraxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + coloraxis and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of coloraxis objects to select. + To select coloraxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all coloraxis objects are selected. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_coloraxes(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_coloraxes( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "Figure": + """ + Perform a property update operation on all coloraxis objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + coloraxis objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + coloraxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all coloraxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + coloraxis and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of coloraxis objects to select. + To select coloraxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all coloraxis objects are selected. + **kwargs + Additional property updates to apply to each selected + coloraxis object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_coloraxes(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_geos(self, selector=None, row=None, col=None): + """ + Select geo subplot objects from a particular subplot cell + and/or geo subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + geo objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all geo objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + geo and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of geo objects to select. + To select geo objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all geo objects are selected. + Returns + ------- + generator + Generator that iterates through all of the geo + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("geo", selector, row, col) + + def for_each_geo(self, fn, selector=None, row=None, col=None) -> "Figure": + """ + Apply a function to all geo objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single geo object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + geo objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all geo objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + geo and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of geo objects to select. + To select geo objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all geo objects are selected. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_geos(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_geos( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "Figure": + """ + Perform a property update operation on all geo objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + geo objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + geo objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all geo objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + geo and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of geo objects to select. + To select geo objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all geo objects are selected. + **kwargs + Additional property updates to apply to each selected + geo object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_geos(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_legends(self, selector=None, row=None, col=None): + """ + Select legend subplot objects from a particular subplot cell + and/or legend subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + legend objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all legend objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + legend and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of legend objects to select. + To select legend objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all legend objects are selected. + Returns + ------- + generator + Generator that iterates through all of the legend + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("legend", selector, row, col) + + def for_each_legend(self, fn, selector=None, row=None, col=None) -> "Figure": + """ + Apply a function to all legend objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single legend object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + legend objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all legend objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + legend and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of legend objects to select. + To select legend objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all legend objects are selected. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_legends(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_legends( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "Figure": + """ + Perform a property update operation on all legend objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + legend objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + legend objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all legend objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + legend and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of legend objects to select. + To select legend objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all legend objects are selected. + **kwargs + Additional property updates to apply to each selected + legend object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_legends(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_maps(self, selector=None, row=None, col=None): + """ + Select map subplot objects from a particular subplot cell + and/or map subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + map objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all map objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + map and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of map objects to select. + To select map objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all map objects are selected. + Returns + ------- + generator + Generator that iterates through all of the map + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("map", selector, row, col) + + def for_each_map(self, fn, selector=None, row=None, col=None) -> "Figure": + """ + Apply a function to all map objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single map object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + map objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all map objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + map and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of map objects to select. + To select map objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all map objects are selected. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_maps(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_maps( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "Figure": + """ + Perform a property update operation on all map objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + map objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + map objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all map objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + map and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of map objects to select. + To select map objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all map objects are selected. + **kwargs + Additional property updates to apply to each selected + map object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_maps(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_mapboxes(self, selector=None, row=None, col=None): + """ + Select mapbox subplot objects from a particular subplot cell + and/or mapbox subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + mapbox objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all mapbox objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + mapbox and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of mapbox objects to select. + To select mapbox objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all mapbox objects are selected. + Returns + ------- + generator + Generator that iterates through all of the mapbox + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("mapbox", selector, row, col) + + def for_each_mapbox(self, fn, selector=None, row=None, col=None) -> "Figure": + """ + Apply a function to all mapbox objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single mapbox object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + mapbox objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all mapbox objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + mapbox and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of mapbox objects to select. + To select mapbox objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all mapbox objects are selected. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_mapboxes(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_mapboxes( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "Figure": + """ + Perform a property update operation on all mapbox objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + mapbox objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + mapbox objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all mapbox objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + mapbox and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of mapbox objects to select. + To select mapbox objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all mapbox objects are selected. + **kwargs + Additional property updates to apply to each selected + mapbox object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_mapboxes(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_polars(self, selector=None, row=None, col=None): + """ + Select polar subplot objects from a particular subplot cell + and/or polar subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + polar objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all polar objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + polar and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of polar objects to select. + To select polar objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all polar objects are selected. + Returns + ------- + generator + Generator that iterates through all of the polar + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("polar", selector, row, col) + + def for_each_polar(self, fn, selector=None, row=None, col=None) -> "Figure": + """ + Apply a function to all polar objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single polar object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + polar objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all polar objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + polar and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of polar objects to select. + To select polar objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all polar objects are selected. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_polars(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_polars( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "Figure": + """ + Perform a property update operation on all polar objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + polar objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + polar objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all polar objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + polar and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of polar objects to select. + To select polar objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all polar objects are selected. + **kwargs + Additional property updates to apply to each selected + polar object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_polars(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_scenes(self, selector=None, row=None, col=None): + """ + Select scene subplot objects from a particular subplot cell + and/or scene subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + scene objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all scene objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + scene and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of scene objects to select. + To select scene objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all scene objects are selected. + Returns + ------- + generator + Generator that iterates through all of the scene + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("scene", selector, row, col) + + def for_each_scene(self, fn, selector=None, row=None, col=None) -> "Figure": + """ + Apply a function to all scene objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single scene object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + scene objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all scene objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + scene and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of scene objects to select. + To select scene objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all scene objects are selected. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_scenes(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_scenes( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "Figure": + """ + Perform a property update operation on all scene objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + scene objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + scene objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all scene objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + scene and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of scene objects to select. + To select scene objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all scene objects are selected. + **kwargs + Additional property updates to apply to each selected + scene object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_scenes(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_smiths(self, selector=None, row=None, col=None): + """ + Select smith subplot objects from a particular subplot cell + and/or smith subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + smith objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all smith objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + smith and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of smith objects to select. + To select smith objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all smith objects are selected. + Returns + ------- + generator + Generator that iterates through all of the smith + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("smith", selector, row, col) + + def for_each_smith(self, fn, selector=None, row=None, col=None) -> "Figure": + """ + Apply a function to all smith objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single smith object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + smith objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all smith objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + smith and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of smith objects to select. + To select smith objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all smith objects are selected. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_smiths(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_smiths( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "Figure": + """ + Perform a property update operation on all smith objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + smith objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + smith objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all smith objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + smith and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of smith objects to select. + To select smith objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all smith objects are selected. + **kwargs + Additional property updates to apply to each selected + smith object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_smiths(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_ternaries(self, selector=None, row=None, col=None): + """ + Select ternary subplot objects from a particular subplot cell + and/or ternary subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + ternary objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all ternary objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + ternary and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of ternary objects to select. + To select ternary objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all ternary objects are selected. + Returns + ------- + generator + Generator that iterates through all of the ternary + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("ternary", selector, row, col) + + def for_each_ternary(self, fn, selector=None, row=None, col=None) -> "Figure": + """ + Apply a function to all ternary objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single ternary object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + ternary objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all ternary objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + ternary and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of ternary objects to select. + To select ternary objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all ternary objects are selected. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_ternaries(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_ternaries( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "Figure": + """ + Perform a property update operation on all ternary objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + ternary objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + ternary objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all ternary objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + ternary and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of ternary objects to select. + To select ternary objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all ternary objects are selected. + **kwargs + Additional property updates to apply to each selected + ternary object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_ternaries(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_xaxes(self, selector=None, row=None, col=None): + """ + Select xaxis subplot objects from a particular subplot cell + and/or xaxis subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + xaxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all xaxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + xaxis and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of xaxis objects to select. + To select xaxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all xaxis objects are selected. + Returns + ------- + generator + Generator that iterates through all of the xaxis + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("xaxis", selector, row, col) + + def for_each_xaxis(self, fn, selector=None, row=None, col=None) -> "Figure": + """ + Apply a function to all xaxis objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single xaxis object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + xaxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all xaxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + xaxis and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of xaxis objects to select. + To select xaxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all xaxis objects are selected. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_xaxes(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_xaxes( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "Figure": + """ + Perform a property update operation on all xaxis objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + xaxis objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + xaxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all xaxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + xaxis and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of xaxis objects to select. + To select xaxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all xaxis objects are selected. + **kwargs + Additional property updates to apply to each selected + xaxis object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_xaxes(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_yaxes(self, selector=None, row=None, col=None, secondary_y=None): + """ + Select yaxis subplot objects from a particular subplot cell + and/or yaxis subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + yaxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all yaxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + yaxis and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of yaxis objects to select. + To select yaxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all yaxis objects are selected. + secondary_y: boolean or None (default None) + * If True, only select yaxis objects associated with the secondary + y-axis of the subplot. + * If False, only select yaxis objects associated with the primary + y-axis of the subplot. + * If None (the default), do not filter yaxis objects based on + a secondary y-axis condition. + + To select yaxis objects by secondary y-axis, the Figure must + have been created using plotly.subplots.make_subplots. See + the docstring for the specs argument to make_subplots for more + info on creating subplots with secondary y-axes. + Returns + ------- + generator + Generator that iterates through all of the yaxis + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix( + "yaxis", selector, row, col, secondary_y=secondary_y + ) + + def for_each_yaxis( + self, fn, selector=None, row=None, col=None, secondary_y=None + ) -> "Figure": + """ + Apply a function to all yaxis objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single yaxis object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + yaxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all yaxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + yaxis and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of yaxis objects to select. + To select yaxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all yaxis objects are selected. + secondary_y: boolean or None (default None) + * If True, only select yaxis objects associated with the secondary + y-axis of the subplot. + * If False, only select yaxis objects associated with the primary + y-axis of the subplot. + * If None (the default), do not filter yaxis objects based on + a secondary y-axis condition. + + To select yaxis objects by secondary y-axis, the Figure must + have been created using plotly.subplots.make_subplots. See + the docstring for the specs argument to make_subplots for more + info on creating subplots with secondary y-axes. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_yaxes( + selector=selector, row=row, col=col, secondary_y=secondary_y + ): + fn(obj) + + return self + + def update_yaxes( + self, + patch=None, + selector=None, + overwrite=False, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "Figure": + """ + Perform a property update operation on all yaxis objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + yaxis objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + yaxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all yaxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + yaxis and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of yaxis objects to select. + To select yaxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all yaxis objects are selected. + secondary_y: boolean or None (default None) + * If True, only select yaxis objects associated with the secondary + y-axis of the subplot. + * If False, only select yaxis objects associated with the primary + y-axis of the subplot. + * If None (the default), do not filter yaxis objects based on + a secondary y-axis condition. + + To select yaxis objects by secondary y-axis, the Figure must + have been created using plotly.subplots.make_subplots. See + the docstring for the specs argument to make_subplots for more + info on creating subplots with secondary y-axes. + **kwargs + Additional property updates to apply to each selected + yaxis object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self.select_yaxes( + selector=selector, row=row, col=col, secondary_y=secondary_y + ): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_annotations(self, selector=None, row=None, col=None, secondary_y=None): + """ + Select annotations from a particular subplot cell and/or annotations + that satisfy custom selection criteria. + + Parameters + ---------- + selector: dict, function, int, str, or None (default None) + Dict to use as selection criteria. + Annotations will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all annotations are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each annotation and those for which the function returned True + will be in the selection. If an int N, the Nth annotation matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of annotations to select. + To select annotations by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + annotation that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all annotations are selected. + secondary_y: boolean or None (default None) + * If True, only select annotations associated with the secondary + y-axis of the subplot. + * If False, only select annotations associated with the primary + y-axis of the subplot. + * If None (the default), do not filter annotations based on secondary + y-axis. + + To select annotations by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + generator + Generator that iterates through all of the annotations that satisfy + all of the specified selection criteria + """ + return self._select_annotations_like( + "annotations", selector=selector, row=row, col=col, secondary_y=secondary_y + ) + + def for_each_annotation( + self, fn, selector=None, row=None, col=None, secondary_y=None + ): + """ + Apply a function to all annotations that satisfy the specified selection + criteria + + Parameters + ---------- + fn: + Function that inputs a single annotation object. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all annotations are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each annotation and those for which the function returned True + will be in the selection. If an int N, the Nth annotation matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of annotations to select. + To select annotations by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + annotations that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all annotations are selected. + secondary_y: boolean or None (default None) + * If True, only select annotations associated with the secondary + y-axis of the subplot. + * If False, only select annotations associated with the primary + y-axis of the subplot. + * If None (the default), do not filter annotations based on secondary + y-axis. + + To select annotations by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self._select_annotations_like( + prop="annotations", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + fn(obj) + + return self + + def update_annotations( + self, patch=None, selector=None, row=None, col=None, secondary_y=None, **kwargs + ) -> "Figure": + """ + Perform a property update operation on all annotations that satisfy the + specified selection criteria + + Parameters + ---------- + patch: dict or None (default None) + Dictionary of property updates to be applied to all annotations that + satisfy the selection criteria. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all annotations are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each annotation and those for which the function returned True + will be in the selection. If an int N, the Nth annotation matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of annotations to select. + To select annotations by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + annotation that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all annotations are selected. + secondary_y: boolean or None (default None) + * If True, only select annotations associated with the secondary + y-axis of the subplot. + * If False, only select annotations associated with the primary + y-axis of the subplot. + * If None (the default), do not filter annotations based on secondary + y-axis. + + To select annotations by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + **kwargs + Additional property updates to apply to each selected annotation. If + a property is specified in both patch and in **kwargs then the + one in **kwargs takes precedence. + + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self._select_annotations_like( + prop="annotations", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + obj.update(patch, **kwargs) + + return self + + def add_annotation( + self, + arg=None, + align=None, + arrowcolor=None, + arrowhead=None, + arrowside=None, + arrowsize=None, + arrowwidth=None, + ax=None, + axref=None, + ay=None, + ayref=None, + bgcolor=None, + bordercolor=None, + borderpad=None, + borderwidth=None, + captureevents=None, + clicktoshow=None, + font=None, + height=None, + hoverlabel=None, + hovertext=None, + name=None, + opacity=None, + showarrow=None, + standoff=None, + startarrowhead=None, + startarrowsize=None, + startstandoff=None, + templateitemname=None, + text=None, + textangle=None, + valign=None, + visible=None, + width=None, + x=None, + xanchor=None, + xclick=None, + xref=None, + xshift=None, + y=None, + yanchor=None, + yclick=None, + yref=None, + yshift=None, + row=None, + col=None, + secondary_y=None, + exclude_empty_subplots=None, + **kwargs, + ) -> "Figure": + """ + Create and add a new annotation to the figure's layout + + Parameters + ---------- + arg + instance of Annotation or dict with compatible + properties + align + Sets the horizontal alignment of the `text` within the + box. Has an effect only if `text` spans two or more + lines (i.e. `text` contains one or more
HTML tags) + or if an explicit width is set to override the text + width. + arrowcolor + Sets the color of the annotation arrow. + arrowhead + Sets the end annotation arrow head style. + arrowside + Sets the annotation arrow head position. + arrowsize + Sets the size of the end annotation arrow head, + relative to `arrowwidth`. A value of 1 (default) gives + a head about 3x as wide as the line. + arrowwidth + Sets the width (in px) of annotation arrow line. + ax + Sets the x component of the arrow tail about the arrow + head. If `axref` is `pixel`, a positive (negative) + component corresponds to an arrow pointing from right + to left (left to right). If `axref` is not `pixel` and + is exactly the same as `xref`, this is an absolute + value on that axis, like `x`, specified in the same + coordinates as `xref`. + axref + Indicates in what coordinates the tail of the + annotation (ax,ay) is specified. If set to a x axis id + (e.g. "x" or "x2"), the `x` position refers to a x + coordinate. If set to "paper", the `x` position refers + to the distance from the left of the plotting area in + normalized coordinates where 0 (1) corresponds to the + left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. In order for absolute + positioning of the arrow to work, "axref" must be + exactly the same as "xref", otherwise "axref" will + revert to "pixel" (explained next). For relative + positioning, "axref" can be set to "pixel", in which + case the "ax" value is specified in pixels relative to + "x". Absolute positioning is useful for trendline + annotations which should continue to indicate the + correct trend when zoomed. Relative positioning is + useful for specifying the text offset for an annotated + point. + ay + Sets the y component of the arrow tail about the arrow + head. If `ayref` is `pixel`, a positive (negative) + component corresponds to an arrow pointing from bottom + to top (top to bottom). If `ayref` is not `pixel` and + is exactly the same as `yref`, this is an absolute + value on that axis, like `y`, specified in the same + coordinates as `yref`. + ayref + Indicates in what coordinates the tail of the + annotation (ax,ay) is specified. If set to a y axis id + (e.g. "y" or "y2"), the `y` position refers to a y + coordinate. If set to "paper", the `y` position refers + to the distance from the bottom of the plotting area in + normalized coordinates where 0 (1) corresponds to the + bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. In order for absolute + positioning of the arrow to work, "ayref" must be + exactly the same as "yref", otherwise "ayref" will + revert to "pixel" (explained next). For relative + positioning, "ayref" can be set to "pixel", in which + case the "ay" value is specified in pixels relative to + "y". Absolute positioning is useful for trendline + annotations which should continue to indicate the + correct trend when zoomed. Relative positioning is + useful for specifying the text offset for an annotated + point. + bgcolor + Sets the background color of the annotation. + bordercolor + Sets the color of the border enclosing the annotation + `text`. + borderpad + Sets the padding (in px) between the `text` and the + enclosing border. + borderwidth + Sets the width (in px) of the border enclosing the + annotation `text`. + captureevents + Determines whether the annotation text box captures + mouse move and click events, or allows those events to + pass through to data points in the plot that may be + behind the annotation. By default `captureevents` is + False unless `hovertext` is provided. If you use the + event `plotly_clickannotation` without `hovertext` you + must explicitly enable `captureevents`. + clicktoshow + Makes this annotation respond to clicks on the plot. If + you click a data point that exactly matches the `x` and + `y` values of this annotation, and it is hidden + (visible: false), it will appear. In "onoff" mode, you + must click the same point again to make it disappear, + so if you click multiple points, you can show multiple + annotations. In "onout" mode, a click anywhere else in + the plot (on another data point or not) will hide this + annotation. If you need to show/hide this annotation in + response to different `x` or `y` values, you can set + `xclick` and/or `yclick`. This is useful for example to + label the side of a bar. To label markers though, + `standoff` is preferred over `xclick` and `yclick`. + font + Sets the annotation text font. + height + Sets an explicit height for the text box. null + (default) lets the text set the box height. Taller text + will be clipped. + hoverlabel + :class:`plotly.graph_objects.layout.annotation.Hoverlab + el` instance or dict with compatible properties + hovertext + Sets text to appear when hovering over this annotation. + If omitted or blank, no hover label will appear. + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the annotation (text + arrow). + showarrow + Determines whether or not the annotation is drawn with + an arrow. If True, `text` is placed near the arrow's + tail. If False, `text` lines up with the `x` and `y` + provided. + standoff + Sets a distance, in pixels, to move the end arrowhead + away from the position it is pointing at, for example + to point at the edge of a marker independent of zoom. + Note that this shortens the arrow from the `ax` / `ay` + vector, in contrast to `xshift` / `yshift` which moves + everything by this amount. + startarrowhead + Sets the start annotation arrow head style. + startarrowsize + Sets the size of the start annotation arrow head, + relative to `arrowwidth`. A value of 1 (default) gives + a head about 3x as wide as the line. + startstandoff + Sets a distance, in pixels, to move the start arrowhead + away from the position it is pointing at, for example + to point at the edge of a marker independent of zoom. + Note that this shortens the arrow from the `ax` / `ay` + vector, in contrast to `xshift` / `yshift` which moves + everything by this amount. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + text + Sets the text associated with this annotation. Plotly + uses a subset of HTML tags to do things like newline + (`
`), bold (``), italics (``), + hyperlinks (``). Tags ``, + ``, ``, ``, ``, and `` are also + supported. + textangle + Sets the angle at which the `text` is drawn with + respect to the horizontal. + valign + Sets the vertical alignment of the `text` within the + box. Has an effect only if an explicit height is set to + override the text height. + visible + Determines whether or not this annotation is visible. + width + Sets an explicit width for the text box. null (default) + lets the text set the box width. Wider text will be + clipped. There is no automatic wrapping; use
to + start a new line. + x + Sets the annotation's x position. If the axis `type` is + "log", then you must take the log of your desired + range. If the axis `type` is "date", it should be date + strings, like date data, though Date objects and unix + milliseconds will be accepted and converted to strings. + If the axis `type` is "category", it should be numbers, + using the scale where each category is assigned a + serial number from zero in the order it appears. + xanchor + Sets the text box's horizontal position anchor This + anchor binds the `x` position to the "left", "center" + or "right" of the annotation. For example, if `x` is + set to 1, `xref` to "paper" and `xanchor` to "right" + then the right-most portion of the annotation lines up + with the right-most edge of the plotting area. If + "auto", the anchor is equivalent to "center" for data- + referenced annotations or if there is an arrow, whereas + for paper-referenced with no arrow, the anchor picked + corresponds to the closest side. + xclick + Toggle this annotation when clicking a data point whose + `x` value is `xclick` rather than the annotation's `x` + value. + xref + Sets the annotation's x coordinate axis. If set to a x + axis id (e.g. "x" or "x2"), the `x` position refers to + a x coordinate. If set to "paper", the `x` position + refers to the distance from the left of the plotting + area in normalized coordinates where 0 (1) corresponds + to the left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + xshift + Shifts the position of the whole annotation and arrow + to the right (positive) or left (negative) by this many + pixels. + y + Sets the annotation's y position. If the axis `type` is + "log", then you must take the log of your desired + range. If the axis `type` is "date", it should be date + strings, like date data, though Date objects and unix + milliseconds will be accepted and converted to strings. + If the axis `type` is "category", it should be numbers, + using the scale where each category is assigned a + serial number from zero in the order it appears. + yanchor + Sets the text box's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the annotation. For example, if `y` is set + to 1, `yref` to "paper" and `yanchor` to "top" then the + top-most portion of the annotation lines up with the + top-most edge of the plotting area. If "auto", the + anchor is equivalent to "middle" for data-referenced + annotations or if there is an arrow, whereas for paper- + referenced with no arrow, the anchor picked corresponds + to the closest side. + yclick + Toggle this annotation when clicking a data point whose + `y` value is `yclick` rather than the annotation's `y` + value. + yref + Sets the annotation's y coordinate axis. If set to a y + axis id (e.g. "y" or "y2"), the `y` position refers to + a y coordinate. If set to "paper", the `y` position + refers to the distance from the bottom of the plotting + area in normalized coordinates where 0 (1) corresponds + to the bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + yshift + Shifts the position of the whole annotation and arrow + up (positive) or down (negative) by this many pixels. + row + Subplot row for annotation. If 'all', addresses all + rows in the specified column(s). + col + Subplot column for annotation. If 'all', addresses all + columns in the specified row(s). + secondary_y + Whether to add annotation to secondary y-axis + exclude_empty_subplots + If True, annotation will not be added to subplots + without traces. + + Returns + ------- + Figure + """ + from plotly.graph_objs import layout as _layout + + new_obj = _layout.Annotation( + arg, + align=align, + arrowcolor=arrowcolor, + arrowhead=arrowhead, + arrowside=arrowside, + arrowsize=arrowsize, + arrowwidth=arrowwidth, + ax=ax, + axref=axref, + ay=ay, + ayref=ayref, + bgcolor=bgcolor, + bordercolor=bordercolor, + borderpad=borderpad, + borderwidth=borderwidth, + captureevents=captureevents, + clicktoshow=clicktoshow, + font=font, + height=height, + hoverlabel=hoverlabel, + hovertext=hovertext, + name=name, + opacity=opacity, + showarrow=showarrow, + standoff=standoff, + startarrowhead=startarrowhead, + startarrowsize=startarrowsize, + startstandoff=startstandoff, + templateitemname=templateitemname, + text=text, + textangle=textangle, + valign=valign, + visible=visible, + width=width, + x=x, + xanchor=xanchor, + xclick=xclick, + xref=xref, + xshift=xshift, + y=y, + yanchor=yanchor, + yclick=yclick, + yref=yref, + yshift=yshift, + **kwargs, + ) + return self._add_annotation_like( + "annotation", + "annotations", + new_obj, + row=row, + col=col, + secondary_y=secondary_y, + exclude_empty_subplots=exclude_empty_subplots, + ) + + def select_layout_images(self, selector=None, row=None, col=None, secondary_y=None): + """ + Select images from a particular subplot cell and/or images + that satisfy custom selection criteria. + + Parameters + ---------- + selector: dict, function, int, str, or None (default None) + Dict to use as selection criteria. + Annotations will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all images are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each image and those for which the function returned True + will be in the selection. If an int N, the Nth image matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of images to select. + To select images by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + image that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all images are selected. + secondary_y: boolean or None (default None) + * If True, only select images associated with the secondary + y-axis of the subplot. + * If False, only select images associated with the primary + y-axis of the subplot. + * If None (the default), do not filter images based on secondary + y-axis. + + To select images by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + generator + Generator that iterates through all of the images that satisfy + all of the specified selection criteria + """ + return self._select_annotations_like( + "images", selector=selector, row=row, col=col, secondary_y=secondary_y + ) + + def for_each_layout_image( + self, fn, selector=None, row=None, col=None, secondary_y=None + ): + """ + Apply a function to all images that satisfy the specified selection + criteria + + Parameters + ---------- + fn: + Function that inputs a single image object. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all images are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each image and those for which the function returned True + will be in the selection. If an int N, the Nth image matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of images to select. + To select images by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + images that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all images are selected. + secondary_y: boolean or None (default None) + * If True, only select images associated with the secondary + y-axis of the subplot. + * If False, only select images associated with the primary + y-axis of the subplot. + * If None (the default), do not filter images based on secondary + y-axis. + + To select images by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self._select_annotations_like( + prop="images", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + fn(obj) + + return self + + def update_layout_images( + self, patch=None, selector=None, row=None, col=None, secondary_y=None, **kwargs + ) -> "Figure": + """ + Perform a property update operation on all images that satisfy the + specified selection criteria + + Parameters + ---------- + patch: dict or None (default None) + Dictionary of property updates to be applied to all images that + satisfy the selection criteria. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all images are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each image and those for which the function returned True + will be in the selection. If an int N, the Nth image matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of images to select. + To select images by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + image that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all images are selected. + secondary_y: boolean or None (default None) + * If True, only select images associated with the secondary + y-axis of the subplot. + * If False, only select images associated with the primary + y-axis of the subplot. + * If None (the default), do not filter images based on secondary + y-axis. + + To select images by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + **kwargs + Additional property updates to apply to each selected image. If + a property is specified in both patch and in **kwargs then the + one in **kwargs takes precedence. + + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self._select_annotations_like( + prop="images", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + obj.update(patch, **kwargs) + + return self + + def add_layout_image( + self, + arg=None, + layer=None, + name=None, + opacity=None, + sizex=None, + sizey=None, + sizing=None, + source=None, + templateitemname=None, + visible=None, + x=None, + xanchor=None, + xref=None, + y=None, + yanchor=None, + yref=None, + row=None, + col=None, + secondary_y=None, + exclude_empty_subplots=None, + **kwargs, + ) -> "Figure": + """ + Create and add a new image to the figure's layout + + Parameters + ---------- + arg + instance of Image or dict with compatible properties + layer + Specifies whether images are drawn below or above + traces. When `xref` and `yref` are both set to `paper`, + image is drawn below the entire plot area. + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the image. + sizex + Sets the image container size horizontally. The image + will be sized based on the `position` value. When + `xref` is set to `paper`, units are sized relative to + the plot width. When `xref` ends with ` domain`, units + are sized relative to the axis width. + sizey + Sets the image container size vertically. The image + will be sized based on the `position` value. When + `yref` is set to `paper`, units are sized relative to + the plot height. When `yref` ends with ` domain`, units + are sized relative to the axis height. + sizing + Specifies which dimension of the image to constrain. + source + Specifies the URL of the image to be used. The URL must + be accessible from the domain where the plot code is + run, and can be either relative or absolute. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + visible + Determines whether or not this image is visible. + x + Sets the image's x position. When `xref` is set to + `paper`, units are sized relative to the plot height. + See `xref` for more info + xanchor + Sets the anchor for the x position + xref + Sets the images's x coordinate axis. If set to a x axis + id (e.g. "x" or "x2"), the `x` position refers to a x + coordinate. If set to "paper", the `x` position refers + to the distance from the left of the plotting area in + normalized coordinates where 0 (1) corresponds to the + left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + y + Sets the image's y position. When `yref` is set to + `paper`, units are sized relative to the plot height. + See `yref` for more info + yanchor + Sets the anchor for the y position. + yref + Sets the images's y coordinate axis. If set to a y axis + id (e.g. "y" or "y2"), the `y` position refers to a y + coordinate. If set to "paper", the `y` position refers + to the distance from the bottom of the plotting area in + normalized coordinates where 0 (1) corresponds to the + bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + row + Subplot row for image. If 'all', addresses all rows in + the specified column(s). + col + Subplot column for image. If 'all', addresses all + columns in the specified row(s). + secondary_y + Whether to add image to secondary y-axis + exclude_empty_subplots + If True, image will not be added to subplots without + traces. + + Returns + ------- + Figure + """ + from plotly.graph_objs import layout as _layout + + new_obj = _layout.Image( + arg, + layer=layer, + name=name, + opacity=opacity, + sizex=sizex, + sizey=sizey, + sizing=sizing, + source=source, + templateitemname=templateitemname, + visible=visible, + x=x, + xanchor=xanchor, + xref=xref, + y=y, + yanchor=yanchor, + yref=yref, + **kwargs, + ) + return self._add_annotation_like( + "image", + "images", + new_obj, + row=row, + col=col, + secondary_y=secondary_y, + exclude_empty_subplots=exclude_empty_subplots, + ) + + def select_selections(self, selector=None, row=None, col=None, secondary_y=None): + """ + Select selections from a particular subplot cell and/or selections + that satisfy custom selection criteria. + + Parameters + ---------- + selector: dict, function, int, str, or None (default None) + Dict to use as selection criteria. + Annotations will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all selections are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each selection and those for which the function returned True + will be in the selection. If an int N, the Nth selection matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of selections to select. + To select selections by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + selection that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all selections are selected. + secondary_y: boolean or None (default None) + * If True, only select selections associated with the secondary + y-axis of the subplot. + * If False, only select selections associated with the primary + y-axis of the subplot. + * If None (the default), do not filter selections based on secondary + y-axis. + + To select selections by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + generator + Generator that iterates through all of the selections that satisfy + all of the specified selection criteria + """ + return self._select_annotations_like( + "selections", selector=selector, row=row, col=col, secondary_y=secondary_y + ) + + def for_each_selection( + self, fn, selector=None, row=None, col=None, secondary_y=None + ): + """ + Apply a function to all selections that satisfy the specified selection + criteria + + Parameters + ---------- + fn: + Function that inputs a single selection object. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all selections are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each selection and those for which the function returned True + will be in the selection. If an int N, the Nth selection matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of selections to select. + To select selections by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + selections that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all selections are selected. + secondary_y: boolean or None (default None) + * If True, only select selections associated with the secondary + y-axis of the subplot. + * If False, only select selections associated with the primary + y-axis of the subplot. + * If None (the default), do not filter selections based on secondary + y-axis. + + To select selections by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self._select_annotations_like( + prop="selections", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + fn(obj) + + return self + + def update_selections( + self, patch=None, selector=None, row=None, col=None, secondary_y=None, **kwargs + ) -> "Figure": + """ + Perform a property update operation on all selections that satisfy the + specified selection criteria + + Parameters + ---------- + patch: dict or None (default None) + Dictionary of property updates to be applied to all selections that + satisfy the selection criteria. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all selections are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each selection and those for which the function returned True + will be in the selection. If an int N, the Nth selection matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of selections to select. + To select selections by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + selection that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all selections are selected. + secondary_y: boolean or None (default None) + * If True, only select selections associated with the secondary + y-axis of the subplot. + * If False, only select selections associated with the primary + y-axis of the subplot. + * If None (the default), do not filter selections based on secondary + y-axis. + + To select selections by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + **kwargs + Additional property updates to apply to each selected selection. If + a property is specified in both patch and in **kwargs then the + one in **kwargs takes precedence. + + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self._select_annotations_like( + prop="selections", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + obj.update(patch, **kwargs) + + return self + + def add_selection( + self, + arg=None, + line=None, + name=None, + opacity=None, + path=None, + templateitemname=None, + type=None, + x0=None, + x1=None, + xref=None, + y0=None, + y1=None, + yref=None, + row=None, + col=None, + secondary_y=None, + exclude_empty_subplots=None, + **kwargs, + ) -> "Figure": + """ + Create and add a new selection to the figure's layout + + Parameters + ---------- + arg + instance of Selection or dict with compatible + properties + line + :class:`plotly.graph_objects.layout.selection.Line` + instance or dict with compatible properties + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the selection. + path + For `type` "path" - a valid SVG path similar to + `shapes.path` in data coordinates. Allowed segments + are: M, L and Z. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + type + Specifies the selection type to be drawn. If "rect", a + rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), + (`x1`,`y1`) and (`x0`,`y1`). If "path", draw a custom + SVG path using `path`. + x0 + Sets the selection's starting x position. + x1 + Sets the selection's end x position. + xref + Sets the selection's x coordinate axis. If set to a x + axis id (e.g. "x" or "x2"), the `x` position refers to + a x coordinate. If set to "paper", the `x` position + refers to the distance from the left of the plotting + area in normalized coordinates where 0 (1) corresponds + to the left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + y0 + Sets the selection's starting y position. + y1 + Sets the selection's end y position. + yref + Sets the selection's x coordinate axis. If set to a y + axis id (e.g. "y" or "y2"), the `y` position refers to + a y coordinate. If set to "paper", the `y` position + refers to the distance from the bottom of the plotting + area in normalized coordinates where 0 (1) corresponds + to the bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + row + Subplot row for selection. If 'all', addresses all rows + in the specified column(s). + col + Subplot column for selection. If 'all', addresses all + columns in the specified row(s). + secondary_y + Whether to add selection to secondary y-axis + exclude_empty_subplots + If True, selection will not be added to subplots + without traces. + + Returns + ------- + Figure + """ + from plotly.graph_objs import layout as _layout + + new_obj = _layout.Selection( + arg, + line=line, + name=name, + opacity=opacity, + path=path, + templateitemname=templateitemname, + type=type, + x0=x0, + x1=x1, + xref=xref, + y0=y0, + y1=y1, + yref=yref, + **kwargs, + ) + return self._add_annotation_like( + "selection", + "selections", + new_obj, + row=row, + col=col, + secondary_y=secondary_y, + exclude_empty_subplots=exclude_empty_subplots, + ) + + def select_shapes(self, selector=None, row=None, col=None, secondary_y=None): + """ + Select shapes from a particular subplot cell and/or shapes + that satisfy custom selection criteria. + + Parameters + ---------- + selector: dict, function, int, str, or None (default None) + Dict to use as selection criteria. + Annotations will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all shapes are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each shape and those for which the function returned True + will be in the selection. If an int N, the Nth shape matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of shapes to select. + To select shapes by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + shape that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all shapes are selected. + secondary_y: boolean or None (default None) + * If True, only select shapes associated with the secondary + y-axis of the subplot. + * If False, only select shapes associated with the primary + y-axis of the subplot. + * If None (the default), do not filter shapes based on secondary + y-axis. + + To select shapes by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + generator + Generator that iterates through all of the shapes that satisfy + all of the specified selection criteria + """ + return self._select_annotations_like( + "shapes", selector=selector, row=row, col=col, secondary_y=secondary_y + ) + + def for_each_shape(self, fn, selector=None, row=None, col=None, secondary_y=None): + """ + Apply a function to all shapes that satisfy the specified selection + criteria + + Parameters + ---------- + fn: + Function that inputs a single shape object. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all shapes are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each shape and those for which the function returned True + will be in the selection. If an int N, the Nth shape matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of shapes to select. + To select shapes by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + shapes that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all shapes are selected. + secondary_y: boolean or None (default None) + * If True, only select shapes associated with the secondary + y-axis of the subplot. + * If False, only select shapes associated with the primary + y-axis of the subplot. + * If None (the default), do not filter shapes based on secondary + y-axis. + + To select shapes by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self._select_annotations_like( + prop="shapes", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + fn(obj) + + return self + + def update_shapes( + self, patch=None, selector=None, row=None, col=None, secondary_y=None, **kwargs + ) -> "Figure": + """ + Perform a property update operation on all shapes that satisfy the + specified selection criteria + + Parameters + ---------- + patch: dict or None (default None) + Dictionary of property updates to be applied to all shapes that + satisfy the selection criteria. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all shapes are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each shape and those for which the function returned True + will be in the selection. If an int N, the Nth shape matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of shapes to select. + To select shapes by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + shape that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all shapes are selected. + secondary_y: boolean or None (default None) + * If True, only select shapes associated with the secondary + y-axis of the subplot. + * If False, only select shapes associated with the primary + y-axis of the subplot. + * If None (the default), do not filter shapes based on secondary + y-axis. + + To select shapes by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + **kwargs + Additional property updates to apply to each selected shape. If + a property is specified in both patch and in **kwargs then the + one in **kwargs takes precedence. + + Returns + ------- + self + Returns the Figure object that the method was called on + """ + for obj in self._select_annotations_like( + prop="shapes", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + obj.update(patch, **kwargs) + + return self + + def add_shape( + self, + arg=None, + editable=None, + fillcolor=None, + fillrule=None, + label=None, + layer=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + name=None, + opacity=None, + path=None, + showlegend=None, + templateitemname=None, + type=None, + visible=None, + x0=None, + x0shift=None, + x1=None, + x1shift=None, + xanchor=None, + xref=None, + xsizemode=None, + y0=None, + y0shift=None, + y1=None, + y1shift=None, + yanchor=None, + yref=None, + ysizemode=None, + row=None, + col=None, + secondary_y=None, + exclude_empty_subplots=None, + **kwargs, + ) -> "Figure": + """ + Create and add a new shape to the figure's layout + + Parameters + ---------- + arg + instance of Shape or dict with compatible properties + editable + Determines whether the shape could be activated for + edit or not. Has no effect when the older editable + shapes mode is enabled via `config.editable` or + `config.edits.shapePosition`. + fillcolor + Sets the color filling the shape's interior. Only + applies to closed shapes. + fillrule + Determines which regions of complex paths constitute + the interior. For more info please visit + https://developer.mozilla.org/en- + US/docs/Web/SVG/Attribute/fill-rule + label + :class:`plotly.graph_objects.layout.shape.Label` + instance or dict with compatible properties + layer + Specifies whether shapes are drawn below gridlines + ("below"), between gridlines and traces ("between") or + above traces ("above"). + legend + Sets the reference to a legend to show this shape in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this shape. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.layout.shape.Legendgroupti + tle` instance or dict with compatible properties + legendrank + Sets the legend rank for this shape. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this shape. + line + :class:`plotly.graph_objects.layout.shape.Line` + instance or dict with compatible properties + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the shape. + path + For `type` "path" - a valid SVG path with the pixel + values replaced by data values in + `xsizemode`/`ysizemode` being "scaled" and taken + unmodified as pixels relative to `xanchor` and + `yanchor` in case of "pixel" size mode. There are a few + restrictions / quirks only absolute instructions, not + relative. So the allowed segments are: M, L, H, V, Q, + C, T, S, and Z arcs (A) are not allowed because radius + rx and ry are relative. In the future we could consider + supporting relative commands, but we would have to + decide on how to handle date and log axes. Note that + even as is, Q and C Bezier paths that are smooth on + linear axes may not be smooth on log, and vice versa. + no chained "polybezier" commands - specify the segment + type for each one. On category axes, values are numbers + scaled to the serial numbers of categories because + using the categories themselves there would be no way + to describe fractional positions On data axes: because + space and T are both normal components of path strings, + we can't use either to separate date from time parts. + Therefore we'll use underscore for this purpose: + 2015-02-21_13:45:56.789 + showlegend + Determines whether or not this shape is shown in the + legend. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + type + Specifies the shape type to be drawn. If "line", a line + is drawn from (`x0`,`y0`) to (`x1`,`y1`) with respect + to the axes' sizing mode. If "circle", a circle is + drawn from ((`x0`+`x1`)/2, (`y0`+`y1`)/2)) with radius + (|(`x0`+`x1`)/2 - `x0`|, |(`y0`+`y1`)/2 -`y0`)|) with + respect to the axes' sizing mode. If "rect", a + rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), + (`x1`,`y1`), (`x0`,`y1`), (`x0`,`y0`) with respect to + the axes' sizing mode. If "path", draw a custom SVG + path using `path`. with respect to the axes' sizing + mode. + visible + Determines whether or not this shape is visible. If + "legendonly", the shape is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x0 + Sets the shape's starting x position. See `type` and + `xsizemode` for more info. + x0shift + Shifts `x0` away from the center of the category when + `xref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + x1 + Sets the shape's end x position. See `type` and + `xsizemode` for more info. + x1shift + Shifts `x1` away from the center of the category when + `xref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + xanchor + Only relevant in conjunction with `xsizemode` set to + "pixel". Specifies the anchor point on the x axis to + which `x0`, `x1` and x coordinates within `path` are + relative to. E.g. useful to attach a pixel sized shape + to a certain data value. No effect when `xsizemode` not + set to "pixel". + xref + Sets the shape's x coordinate axis. If set to a x axis + id (e.g. "x" or "x2"), the `x` position refers to a x + coordinate. If set to "paper", the `x` position refers + to the distance from the left of the plotting area in + normalized coordinates where 0 (1) corresponds to the + left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + xsizemode + Sets the shapes's sizing mode along the x axis. If set + to "scaled", `x0`, `x1` and x coordinates within `path` + refer to data values on the x axis or a fraction of the + plot area's width (`xref` set to "paper"). If set to + "pixel", `xanchor` specifies the x position in terms of + data or plot fraction but `x0`, `x1` and x coordinates + within `path` are pixels relative to `xanchor`. This + way, the shape can have a fixed width while maintaining + a position relative to data or plot fraction. + y0 + Sets the shape's starting y position. See `type` and + `ysizemode` for more info. + y0shift + Shifts `y0` away from the center of the category when + `yref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + y1 + Sets the shape's end y position. See `type` and + `ysizemode` for more info. + y1shift + Shifts `y1` away from the center of the category when + `yref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + yanchor + Only relevant in conjunction with `ysizemode` set to + "pixel". Specifies the anchor point on the y axis to + which `y0`, `y1` and y coordinates within `path` are + relative to. E.g. useful to attach a pixel sized shape + to a certain data value. No effect when `ysizemode` not + set to "pixel". + yref + Sets the shape's y coordinate axis. If set to a y axis + id (e.g. "y" or "y2"), the `y` position refers to a y + coordinate. If set to "paper", the `y` position refers + to the distance from the bottom of the plotting area in + normalized coordinates where 0 (1) corresponds to the + bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + ysizemode + Sets the shapes's sizing mode along the y axis. If set + to "scaled", `y0`, `y1` and y coordinates within `path` + refer to data values on the y axis or a fraction of the + plot area's height (`yref` set to "paper"). If set to + "pixel", `yanchor` specifies the y position in terms of + data or plot fraction but `y0`, `y1` and y coordinates + within `path` are pixels relative to `yanchor`. This + way, the shape can have a fixed height while + maintaining a position relative to data or plot + fraction. + row + Subplot row for shape. If 'all', addresses all rows in + the specified column(s). + col + Subplot column for shape. If 'all', addresses all + columns in the specified row(s). + secondary_y + Whether to add shape to secondary y-axis + exclude_empty_subplots + If True, shape will not be added to subplots without + traces. + + Returns + ------- + Figure + """ + from plotly.graph_objs import layout as _layout + + new_obj = _layout.Shape( + arg, + editable=editable, + fillcolor=fillcolor, + fillrule=fillrule, + label=label, + layer=layer, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + name=name, + opacity=opacity, + path=path, + showlegend=showlegend, + templateitemname=templateitemname, + type=type, + visible=visible, + x0=x0, + x0shift=x0shift, + x1=x1, + x1shift=x1shift, + xanchor=xanchor, + xref=xref, + xsizemode=xsizemode, + y0=y0, + y0shift=y0shift, + y1=y1, + y1shift=y1shift, + yanchor=yanchor, + yref=yref, + ysizemode=ysizemode, + **kwargs, + ) + return self._add_annotation_like( + "shape", + "shapes", + new_obj, + row=row, + col=col, + secondary_y=secondary_y, + exclude_empty_subplots=exclude_empty_subplots, + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_figurewidget.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_figurewidget.py new file mode 100644 index 0000000000000000000000000000000000000000..758a4dfc6845075a52d81480b577d0bdbb41b973 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_figurewidget.py @@ -0,0 +1,25371 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basewidget import BaseFigureWidget + + +class FigureWidget(BaseFigureWidget): + def __init__( + self, data=None, layout=None, frames=None, skip_invalid=False, **kwargs + ): + """ + Create a new :class:FigureWidget instance + + Parameters + ---------- + data + The 'data' property is a tuple of trace instances + that may be specified as: + - A list or tuple of trace instances + (e.g. [Scatter(...), Bar(...)]) + - A single trace instance + (e.g. Scatter(...), Bar(...), etc.) + - A list or tuple of dicts of string/value properties where: + - The 'type' property specifies the trace type + One of: ['bar', 'barpolar', 'box', 'candlestick', + 'carpet', 'choropleth', 'choroplethmap', + 'choroplethmapbox', 'cone', 'contour', + 'contourcarpet', 'densitymap', + 'densitymapbox', 'funnel', 'funnelarea', + 'heatmap', 'histogram', 'histogram2d', + 'histogram2dcontour', 'icicle', 'image', + 'indicator', 'isosurface', 'mesh3d', 'ohlc', + 'parcats', 'parcoords', 'pie', 'sankey', + 'scatter', 'scatter3d', 'scattercarpet', + 'scattergeo', 'scattergl', 'scattermap', + 'scattermapbox', 'scatterpolar', + 'scatterpolargl', 'scattersmith', + 'scatterternary', 'splom', 'streamtube', + 'sunburst', 'surface', 'table', 'treemap', + 'violin', 'volume', 'waterfall'] + + - All remaining properties are passed to the constructor of + the specified trace type + + (e.g. [{'type': 'scatter', ...}, {'type': 'bar, ...}]) + + layout + The 'layout' property is an instance of Layout + that may be specified as: + - An instance of :class:`plotly.graph_objs.Layout` + - A dict of string/value properties that will be passed + to the Layout constructor + + frames + The 'frames' property is a tuple of instances of + Frame that may be specified as: + - A list or tuple of instances of plotly.graph_objs.Frame + - A list or tuple of dicts of string/value properties that + will be passed to the Frame constructor + + skip_invalid: bool + If True, invalid properties in the figure specification will be + skipped silently. If False (default) invalid properties in the + figure specification will result in a ValueError + + Raises + ------ + ValueError + if a property in the specification of data, layout, or frames + is invalid AND skip_invalid is False + """ + super().__init__(data, layout, frames, skip_invalid, **kwargs) + + def update(self, dict1=None, overwrite=False, **kwargs) -> "FigureWidget": + """ + + Update the properties of the figure with a dict and/or with + keyword arguments. + + This recursively updates the structure of the figure + object with the values in the input dict / keyword arguments. + + Parameters + ---------- + dict1 : dict + Dictionary of properties to be updated + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + kwargs : + Keyword/value pair of properties to be updated + + Examples + -------- + >>> import plotly.graph_objs as go + >>> fig = go.Figure(data=[{'y': [1, 2, 3]}]) + >>> fig.update(data=[{'y': [4, 5, 6]}]) # doctest: +ELLIPSIS + Figure(...) + >>> fig.to_plotly_json() # doctest: +SKIP + {'data': [{'type': 'scatter', + 'uid': 'e86a7c7a-346a-11e8-8aa8-a0999b0c017b', + 'y': array([4, 5, 6], dtype=int32)}], + 'layout': {}} + + >>> fig = go.Figure(layout={'xaxis': + ... {'color': 'green', + ... 'range': [0, 1]}}) + >>> fig.update({'layout': {'xaxis': {'color': 'pink'}}}) # doctest: +ELLIPSIS + Figure(...) + >>> fig.to_plotly_json() # doctest: +SKIP + {'data': [], + 'layout': {'xaxis': + {'color': 'pink', + 'range': [0, 1]}}} + + Returns + ------- + BaseFigure + Updated figure + + """ + return super().update(dict1, overwrite, **kwargs) + + def update_traces( + self, + patch=None, + selector=None, + row=None, + col=None, + secondary_y=None, + overwrite=False, + **kwargs, + ) -> "FigureWidget": + """ + + Perform a property update operation on all traces that satisfy the + specified selection criteria + + Parameters + ---------- + patch: dict or None (default None) + Dictionary of property updates to be applied to all traces that + satisfy the selection criteria. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all traces are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each trace and those for which the function returned True + will be in the selection. If an int N, the Nth trace matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of traces to select. + To select traces by row and column, the Figure must have been + created using plotly.subplots.make_subplots. If None + (the default), all traces are selected. + secondary_y: boolean or None (default None) + * If True, only select traces associated with the secondary + y-axis of the subplot. + * If False, only select traces associated with the primary + y-axis of the subplot. + * If None (the default), do not filter traces based on secondary + y-axis. + + To select traces by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + **kwargs + Additional property updates to apply to each selected trace. If + a property is specified in both patch and in **kwargs then the + one in **kwargs takes precedence. + + Returns + ------- + self + Returns the Figure object that the method was called on + + """ + return super().update_traces( + patch, selector, row, col, secondary_y, overwrite, **kwargs + ) + + def update_layout(self, dict1=None, overwrite=False, **kwargs) -> "FigureWidget": + """ + + Update the properties of the figure's layout with a dict and/or with + keyword arguments. + + This recursively updates the structure of the original + layout with the values in the input dict / keyword arguments. + + Parameters + ---------- + dict1 : dict + Dictionary of properties to be updated + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + kwargs : + Keyword/value pair of properties to be updated + + Returns + ------- + BaseFigure + The Figure object that the update_layout method was called on + + """ + return super().update_layout(dict1, overwrite, **kwargs) + + def for_each_trace( + self, fn, selector=None, row=None, col=None, secondary_y=None + ) -> "FigureWidget": + """ + + Apply a function to all traces that satisfy the specified selection + criteria + + Parameters + ---------- + fn: + Function that inputs a single trace object. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all traces are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each trace and those for which the function returned True + will be in the selection. If an int N, the Nth trace matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of traces to select. + To select traces by row and column, the Figure must have been + created using plotly.subplots.make_subplots. If None + (the default), all traces are selected. + secondary_y: boolean or None (default None) + * If True, only select traces associated with the secondary + y-axis of the subplot. + * If False, only select traces associated with the primary + y-axis of the subplot. + * If None (the default), do not filter traces based on secondary + y-axis. + + To select traces by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + self + Returns the Figure object that the method was called on + + """ + return super().for_each_trace(fn, selector, row, col, secondary_y) + + def add_trace( + self, trace, row=None, col=None, secondary_y=None, exclude_empty_subplots=False + ) -> "FigureWidget": + """ + + Add a trace to the figure + + Parameters + ---------- + trace : BaseTraceType or dict + Either: + - An instances of a trace classe from the plotly.graph_objs + package (e.g plotly.graph_objs.Scatter, plotly.graph_objs.Bar) + - or a dicts where: + + - The 'type' property specifies the trace type (e.g. + 'scatter', 'bar', 'area', etc.). If the dict has no 'type' + property then 'scatter' is assumed. + - All remaining properties are passed to the constructor + of the specified trace type. + + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`. + If 'all', addresses all rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`. + If 'all', addresses all columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + * The trace argument is a 2D cartesian trace + (scatter, bar, etc.) + exclude_empty_subplots: boolean + If True, the trace will not be added to subplots that don't already + have traces. + Returns + ------- + BaseFigure + The Figure that add_trace was called on + + Examples + -------- + + >>> from plotly import subplots + >>> import plotly.graph_objs as go + + Add two Scatter traces to a figure + + >>> fig = go.Figure() + >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2])) # doctest: +ELLIPSIS + Figure(...) + >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2])) # doctest: +ELLIPSIS + Figure(...) + + + Add two Scatter traces to vertically stacked subplots + + >>> fig = subplots.make_subplots(rows=2) + >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2]), row=1, col=1) # doctest: +ELLIPSIS + Figure(...) + >>> fig.add_trace(go.Scatter(x=[1,2,3], y=[2,1,2]), row=2, col=1) # doctest: +ELLIPSIS + Figure(...) + + """ + return super().add_trace(trace, row, col, secondary_y, exclude_empty_subplots) + + def add_traces( + self, + data, + rows=None, + cols=None, + secondary_ys=None, + exclude_empty_subplots=False, + ) -> "FigureWidget": + """ + + Add traces to the figure + + Parameters + ---------- + data : list[BaseTraceType or dict] + A list of trace specifications to be added. + Trace specifications may be either: + + - Instances of trace classes from the plotly.graph_objs + package (e.g plotly.graph_objs.Scatter, plotly.graph_objs.Bar) + - Dicts where: + + - The 'type' property specifies the trace type (e.g. + 'scatter', 'bar', 'area', etc.). If the dict has no 'type' + property then 'scatter' is assumed. + - All remaining properties are passed to the constructor + of the specified trace type. + + rows : None, list[int], or int (default None) + List of subplot row indexes (starting from 1) for the traces to be + added. Only valid if figure was created using + `plotly.tools.make_subplots` + If a single integer is passed, all traces will be added to row number + + cols : None or list[int] (default None) + List of subplot column indexes (starting from 1) for the traces + to be added. Only valid if figure was created using + `plotly.tools.make_subplots` + If a single integer is passed, all traces will be added to column number + + + secondary_ys: None or list[boolean] (default None) + List of secondary_y booleans for traces to be added. See the + docstring for `add_trace` for more info. + + exclude_empty_subplots: boolean + If True, the trace will not be added to subplots that don't already + have traces. + + Returns + ------- + BaseFigure + The Figure that add_traces was called on + + Examples + -------- + + >>> from plotly import subplots + >>> import plotly.graph_objs as go + + Add two Scatter traces to a figure + + >>> fig = go.Figure() + >>> fig.add_traces([go.Scatter(x=[1,2,3], y=[2,1,2]), + ... go.Scatter(x=[1,2,3], y=[2,1,2])]) # doctest: +ELLIPSIS + Figure(...) + + Add two Scatter traces to vertically stacked subplots + + >>> fig = subplots.make_subplots(rows=2) + >>> fig.add_traces([go.Scatter(x=[1,2,3], y=[2,1,2]), + ... go.Scatter(x=[1,2,3], y=[2,1,2])], + ... rows=[1, 2], cols=[1, 1]) # doctest: +ELLIPSIS + Figure(...) + + """ + return super().add_traces( + data, rows, cols, secondary_ys, exclude_empty_subplots + ) + + def add_vline( + self, + x, + row="all", + col="all", + exclude_empty_subplots=True, + annotation=None, + **kwargs, + ) -> "FigureWidget": + """ + + Add a vertical line to a plot or subplot that extends infinitely in the + y-dimension. + + Parameters + ---------- + x: float or int + A number representing the x coordinate of the vertical line. + exclude_empty_subplots: Boolean + If True (default) do not place the shape on subplots that have no data + plotted on them. + row: None, int or 'all' + Subplot row for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + col: None, int or 'all' + Subplot column for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + annotation: dict or plotly.graph_objects.layout.Annotation. If dict(), + it is interpreted as describing an annotation. The annotation is + placed relative to the shape based on annotation_position (see + below) unless its x or y value has been specified for the annotation + passed here. xref and yref are always the same as for the added + shape and cannot be overridden. + annotation_position: a string containing optionally ["top", "bottom"] + and ["left", "right"] specifying where the text should be anchored + to on the line. Example positions are "bottom left", "right top", + "right", "bottom". If an annotation is added but annotation_position is + not specified, this defaults to "top right". + annotation_*: any parameters to go.layout.Annotation can be passed as + keywords by prefixing them with "annotation_". For example, to specify the + annotation text "example" you can pass annotation_text="example" as a + keyword argument. + **kwargs: + Any named function parameters that can be passed to 'add_shape', + except for x0, x1, y0, y1 or type. + """ + return super().add_vline( + x, row, col, exclude_empty_subplots, annotation, **kwargs + ) + + def add_hline( + self, + y, + row="all", + col="all", + exclude_empty_subplots=True, + annotation=None, + **kwargs, + ) -> "FigureWidget": + """ + + Add a horizontal line to a plot or subplot that extends infinitely in the + x-dimension. + + Parameters + ---------- + y: float or int + A number representing the y coordinate of the horizontal line. + exclude_empty_subplots: Boolean + If True (default) do not place the shape on subplots that have no data + plotted on them. + row: None, int or 'all' + Subplot row for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + col: None, int or 'all' + Subplot column for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + annotation: dict or plotly.graph_objects.layout.Annotation. If dict(), + it is interpreted as describing an annotation. The annotation is + placed relative to the shape based on annotation_position (see + below) unless its x or y value has been specified for the annotation + passed here. xref and yref are always the same as for the added + shape and cannot be overridden. + annotation_position: a string containing optionally ["top", "bottom"] + and ["left", "right"] specifying where the text should be anchored + to on the line. Example positions are "bottom left", "right top", + "right", "bottom". If an annotation is added but annotation_position is + not specified, this defaults to "top right". + annotation_*: any parameters to go.layout.Annotation can be passed as + keywords by prefixing them with "annotation_". For example, to specify the + annotation text "example" you can pass annotation_text="example" as a + keyword argument. + **kwargs: + Any named function parameters that can be passed to 'add_shape', + except for x0, x1, y0, y1 or type. + """ + return super().add_hline( + y, row, col, exclude_empty_subplots, annotation, **kwargs + ) + + def add_vrect( + self, + x0, + x1, + row="all", + col="all", + exclude_empty_subplots=True, + annotation=None, + **kwargs, + ) -> "FigureWidget": + """ + + Add a rectangle to a plot or subplot that extends infinitely in the + y-dimension. + + Parameters + ---------- + x0: float or int + A number representing the x coordinate of one side of the rectangle. + x1: float or int + A number representing the x coordinate of the other side of the rectangle. + exclude_empty_subplots: Boolean + If True (default) do not place the shape on subplots that have no data + plotted on them. + row: None, int or 'all' + Subplot row for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + col: None, int or 'all' + Subplot column for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + annotation: dict or plotly.graph_objects.layout.Annotation. If dict(), + it is interpreted as describing an annotation. The annotation is + placed relative to the shape based on annotation_position (see + below) unless its x or y value has been specified for the annotation + passed here. xref and yref are always the same as for the added + shape and cannot be overridden. + annotation_position: a string containing optionally ["inside", "outside"], ["top", "bottom"] + and ["left", "right"] specifying where the text should be anchored + to on the rectangle. Example positions are "outside top left", "inside + bottom", "right", "inside left", "inside" ("outside" is not supported). If + an annotation is added but annotation_position is not specified this + defaults to "inside top right". + annotation_*: any parameters to go.layout.Annotation can be passed as + keywords by prefixing them with "annotation_". For example, to specify the + annotation text "example" you can pass annotation_text="example" as a + keyword argument. + **kwargs: + Any named function parameters that can be passed to 'add_shape', + except for x0, x1, y0, y1 or type. + """ + return super().add_vrect( + x0, x1, row, col, exclude_empty_subplots, annotation, **kwargs + ) + + def add_hrect( + self, + y0, + y1, + row="all", + col="all", + exclude_empty_subplots=True, + annotation=None, + **kwargs, + ) -> "FigureWidget": + """ + + Add a rectangle to a plot or subplot that extends infinitely in the + x-dimension. + + Parameters + ---------- + y0: float or int + A number representing the y coordinate of one side of the rectangle. + y1: float or int + A number representing the y coordinate of the other side of the rectangle. + exclude_empty_subplots: Boolean + If True (default) do not place the shape on subplots that have no data + plotted on them. + row: None, int or 'all' + Subplot row for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + col: None, int or 'all' + Subplot column for shape indexed starting at 1. If 'all', addresses all rows in + the specified column(s). If both row and col are None, addresses the + first subplot if subplots exist, or the only plot. By default is "all". + annotation: dict or plotly.graph_objects.layout.Annotation. If dict(), + it is interpreted as describing an annotation. The annotation is + placed relative to the shape based on annotation_position (see + below) unless its x or y value has been specified for the annotation + passed here. xref and yref are always the same as for the added + shape and cannot be overridden. + annotation_position: a string containing optionally ["inside", "outside"], ["top", "bottom"] + and ["left", "right"] specifying where the text should be anchored + to on the rectangle. Example positions are "outside top left", "inside + bottom", "right", "inside left", "inside" ("outside" is not supported). If + an annotation is added but annotation_position is not specified this + defaults to "inside top right". + annotation_*: any parameters to go.layout.Annotation can be passed as + keywords by prefixing them with "annotation_". For example, to specify the + annotation text "example" you can pass annotation_text="example" as a + keyword argument. + **kwargs: + Any named function parameters that can be passed to 'add_shape', + except for x0, x1, y0, y1 or type. + """ + return super().add_hrect( + y0, y1, row, col, exclude_empty_subplots, annotation, **kwargs + ) + + def set_subplots( + self, rows=None, cols=None, **make_subplots_args + ) -> "FigureWidget": + """ + + Add subplots to this figure. If the figure already contains subplots, + then this throws an error. Accepts any keyword arguments that + plotly.subplots.make_subplots accepts. + + """ + return super().set_subplots(rows, cols, **make_subplots_args) + + def add_bar( + self, + alignmentgroup=None, + base=None, + basesrc=None, + cliponaxis=None, + constraintext=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + error_x=None, + error_y=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextanchor=None, + insidetextfont=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + offset=None, + offsetgroup=None, + offsetsrc=None, + opacity=None, + orientation=None, + outsidetextfont=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textangle=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + width=None, + widthsrc=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Bar trace + + The data visualized by the span of the bars is set in `y` if + `orientation` is set to "v" (the default) and the labels are + set in `x`. By setting `orientation` to "h", the roles are + interchanged. + + Parameters + ---------- + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + base + Sets where the bar base is drawn (in position axis + units). In "stack" or "relative" barmode, traces that + set "base" will be excluded and drawn in "overlay" mode + instead. + basesrc + Sets the source reference on Chart Studio Cloud for + `base`. + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + error_x + :class:`plotly.graph_objects.bar.ErrorX` instance or + dict with compatible properties + error_y + :class:`plotly.graph_objects.bar.ErrorY` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.bar.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `value` and `label`. Anything contained in + tag `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.bar.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.bar.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the position where the bar is drawn (in position + axis units). In "group" barmode, traces that set + "offset" will be excluded and drawn in "overlay" mode + instead. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + offsetsrc + Sets the source reference on Chart Studio Cloud for + `offset`. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the bars. With "v" ("h"), the + value of the each bar spans along the vertical + (horizontal). + outsidetextfont + Sets the font used for `text` lying outside the bar. + selected + :class:`plotly.graph_objects.bar.Selected` instance or + dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.bar.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the font used for `text`. + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `value` and `label`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.bar.Unselected` instance + or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar width (in position axis units). + widthsrc + Sets the source reference on Chart Studio Cloud for + `width`. + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Bar + + new_trace = Bar( + alignmentgroup=alignmentgroup, + base=base, + basesrc=basesrc, + cliponaxis=cliponaxis, + constraintext=constraintext, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + error_x=error_x, + error_y=error_y, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextanchor=insidetextanchor, + insidetextfont=insidetextfont, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + offset=offset, + offsetgroup=offsetgroup, + offsetsrc=offsetsrc, + opacity=opacity, + orientation=orientation, + outsidetextfont=outsidetextfont, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textangle=textangle, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + width=width, + widthsrc=widthsrc, + x=x, + x0=x0, + xaxis=xaxis, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + y=y, + y0=y0, + yaxis=yaxis, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_barpolar( + self, + base=None, + basesrc=None, + customdata=None, + customdatasrc=None, + dr=None, + dtheta=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + offset=None, + offsetsrc=None, + opacity=None, + r=None, + r0=None, + rsrc=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textsrc=None, + theta=None, + theta0=None, + thetasrc=None, + thetaunit=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + width=None, + widthsrc=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Barpolar trace + + The data visualized by the radial span of the bars is set in + `r` + + Parameters + ---------- + base + Sets where the bar base is drawn (in radial axis + units). In "stack" barmode, traces that set "base" will + be excluded and drawn in "overlay" mode instead. + basesrc + Sets the source reference on Chart Studio Cloud for + `base`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dr + Sets the r coordinate step. + dtheta + Sets the theta coordinate step. By default, the + `dtheta` step equals the subplot's period divided by + the length of the `r` coordinates. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.barpolar.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.barpolar.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.barpolar.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the angular position where the bar is drawn (in + "thetatunit" units). + offsetsrc + Sets the source reference on Chart Studio Cloud for + `offset`. + opacity + Sets the opacity of the trace. + r + Sets the radial coordinates + r0 + Alternate to `r`. Builds a linear space of r + coordinates. Use with `dr` where `r0` is the starting + coordinate and `dr` the step. + rsrc + Sets the source reference on Chart Studio Cloud for + `r`. + selected + :class:`plotly.graph_objects.barpolar.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.barpolar.Stream` instance + or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a polar subplot. If "polar" (the default value), + the data refer to `layout.polar`. If "polar2", the data + refer to `layout.polar2`, and so on. + text + Sets hover text elements associated with each bar. If a + single string, the same string appears over all bars. + If an array of string, the items are mapped in order to + the this trace's coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + theta + Sets the angular coordinates + theta0 + Alternate to `theta`. Builds a linear space of theta + coordinates. Use with `dtheta` where `theta0` is the + starting coordinate and `dtheta` the step. + thetasrc + Sets the source reference on Chart Studio Cloud for + `theta`. + thetaunit + Sets the unit of input "theta" values. Has an effect + only when on "linear" angular axes. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.barpolar.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar angular width (in "thetaunit" units). + widthsrc + Sets the source reference on Chart Studio Cloud for + `width`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Barpolar + + new_trace = Barpolar( + base=base, + basesrc=basesrc, + customdata=customdata, + customdatasrc=customdatasrc, + dr=dr, + dtheta=dtheta, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + offset=offset, + offsetsrc=offsetsrc, + opacity=opacity, + r=r, + r0=r0, + rsrc=rsrc, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + subplot=subplot, + text=text, + textsrc=textsrc, + theta=theta, + theta0=theta0, + thetasrc=thetasrc, + thetaunit=thetaunit, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + width=width, + widthsrc=widthsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_box( + self, + alignmentgroup=None, + boxmean=None, + boxpoints=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + jitter=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + lowerfence=None, + lowerfencesrc=None, + marker=None, + mean=None, + meansrc=None, + median=None, + mediansrc=None, + meta=None, + metasrc=None, + name=None, + notched=None, + notchspan=None, + notchspansrc=None, + notchwidth=None, + offsetgroup=None, + opacity=None, + orientation=None, + pointpos=None, + q1=None, + q1src=None, + q3=None, + q3src=None, + quartilemethod=None, + sd=None, + sdmultiple=None, + sdsrc=None, + selected=None, + selectedpoints=None, + showlegend=None, + showwhiskers=None, + sizemode=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + upperfence=None, + upperfencesrc=None, + visible=None, + whiskerwidth=None, + width=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Box trace + + Each box spans from quartile 1 (Q1) to quartile 3 (Q3). The + second quartile (Q2, i.e. the median) is marked by a line + inside the box. The fences grow outward from the boxes' edges, + by default they span +/- 1.5 times the interquartile range + (IQR: Q3-Q1), The sample mean and standard deviation as well as + notches and the sample, outlier and suspected outliers points + can be optionally added to the box plot. The values and + positions corresponding to each boxes can be input using two + signatures. The first signature expects users to supply the + sample values in the `y` data array for vertical boxes (`x` for + horizontal boxes). By supplying an `x` (`y`) array, one box per + distinct `x` (`y`) value is drawn If no `x` (`y`) list is + provided, a single box is drawn. In this case, the box is + positioned with the trace `name` or with `x0` (`y0`) if + provided. The second signature expects users to supply the + boxes corresponding Q1, median and Q3 statistics in the `q1`, + `median` and `q3` data arrays respectively. Other box features + relying on statistics namely `lowerfence`, `upperfence`, + `notchspan` can be set directly by the users. To have plotly + compute them or to show sample points besides the boxes, users + can set the `y` data array for vertical boxes (`x` for + horizontal boxes) to a 2D array with the outer length + corresponding to the number of boxes in the traces and the + inner length corresponding the sample size. + + Parameters + ---------- + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + boxmean + If True, the mean of the box(es)' underlying + distribution is drawn as a dashed line inside the + box(es). If "sd" the standard deviation is also drawn. + Defaults to True when `mean` is set. Defaults to "sd" + when `sd` is set Otherwise defaults to False. + boxpoints + If "outliers", only the sample points lying outside the + whiskers are shown If "suspectedoutliers", the outlier + points are shown and points either less than 4*Q1-3*Q3 + or greater than 4*Q3-3*Q1 are highlighted (see + `outliercolor`) If "all", all sample points are shown + If False, only the box(es) are shown with no sample + points Defaults to "suspectedoutliers" when + `marker.outliercolor` or `marker.line.outliercolor` is + set. Defaults to "all" under the q1/median/q3 + signature. Otherwise defaults to "outliers". + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step for multi-box traces set + using q1/median/q3. + dy + Sets the y coordinate step for multi-box traces set + using q1/median/q3. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.box.Hoverlabel` instance + or dict with compatible properties + hoveron + Do the hover effects highlight individual boxes or + sample points or both? + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + jitter + Sets the amount of jitter in the sample points drawn. + If 0, the sample points align along the distribution + axis. If 1, the sample points are drawn in a random + jitter of width equal to the width of the box(es). + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.box.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.box.Line` instance or dict + with compatible properties + lowerfence + Sets the lower fence values. There should be as many + items as the number of boxes desired. This attribute + has effect only under the q1/median/q3 signature. If + `lowerfence` is not provided but a sample (in `y` or + `x`) is set, we compute the lower as the last sample + point below 1.5 times the IQR. + lowerfencesrc + Sets the source reference on Chart Studio Cloud for + `lowerfence`. + marker + :class:`plotly.graph_objects.box.Marker` instance or + dict with compatible properties + mean + Sets the mean values. There should be as many items as + the number of boxes desired. This attribute has effect + only under the q1/median/q3 signature. If `mean` is not + provided but a sample (in `y` or `x`) is set, we + compute the mean for each box using the sample values. + meansrc + Sets the source reference on Chart Studio Cloud for + `mean`. + median + Sets the median values. There should be as many items + as the number of boxes desired. + mediansrc + Sets the source reference on Chart Studio Cloud for + `median`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. For box traces, the name will + also be used for the position coordinate, if `x` and + `x0` (`y` and `y0` if horizontal) are missing and the + position axis is categorical + notched + Determines whether or not notches are drawn. Notches + displays a confidence interval around the median. We + compute the confidence interval as median +/- 1.57 * + IQR / sqrt(N), where IQR is the interquartile range and + N is the sample size. If two boxes' notches do not + overlap there is 95% confidence their medians differ. + See https://sites.google.com/site/davidsstatistics/home + /notched-box-plots for more info. Defaults to False + unless `notchwidth` or `notchspan` is set. + notchspan + Sets the notch span from the boxes' `median` values. + There should be as many items as the number of boxes + desired. This attribute has effect only under the + q1/median/q3 signature. If `notchspan` is not provided + but a sample (in `y` or `x`) is set, we compute it as + 1.57 * IQR / sqrt(N), where N is the sample size. + notchspansrc + Sets the source reference on Chart Studio Cloud for + `notchspan`. + notchwidth + Sets the width of the notches relative to the box + width. For example, with 0, the notches are as wide as + the box(es). + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the box(es). If "v" ("h"), the + distribution is visualized along the vertical + (horizontal). + pointpos + Sets the position of the sample points in relation to + the box(es). If 0, the sample points are places over + the center of the box(es). Positive (negative) values + correspond to positions to the right (left) for + vertical boxes and above (below) for horizontal boxes + q1 + Sets the Quartile 1 values. There should be as many + items as the number of boxes desired. + q1src + Sets the source reference on Chart Studio Cloud for + `q1`. + q3 + Sets the Quartile 3 values. There should be as many + items as the number of boxes desired. + q3src + Sets the source reference on Chart Studio Cloud for + `q3`. + quartilemethod + Sets the method used to compute the sample's Q1 and Q3 + quartiles. The "linear" method uses the 25th percentile + for Q1 and 75th percentile for Q3 as computed using + method #10 (listed on + http://jse.amstat.org/v14n3/langford.html). The + "exclusive" method uses the median to divide the + ordered dataset into two halves if the sample is odd, + it does not include the median in either half - Q1 is + then the median of the lower half and Q3 the median of + the upper half. The "inclusive" method also uses the + median to divide the ordered dataset into two halves + but if the sample is odd, it includes the median in + both halves - Q1 is then the median of the lower half + and Q3 the median of the upper half. + sd + Sets the standard deviation values. There should be as + many items as the number of boxes desired. This + attribute has effect only under the q1/median/q3 + signature. If `sd` is not provided but a sample (in `y` + or `x`) is set, we compute the standard deviation for + each box using the sample values. + sdmultiple + Scales the box size when sizemode=sd Allowing boxes to + be drawn across any stddev range For example 1-stddev, + 3-stddev, 5-stddev + sdsrc + Sets the source reference on Chart Studio Cloud for + `sd`. + selected + :class:`plotly.graph_objects.box.Selected` instance or + dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showwhiskers + Determines whether or not whiskers are visible. + Defaults to true for `sizemode` "quartiles", false for + "sd". + sizemode + Sets the upper and lower bound for the boxes quartiles + means box is drawn between Q1 and Q3 SD means the box + is drawn between Mean +- Standard Deviation Argument + sdmultiple (default 1) to scale the box size So it + could be drawn 1-stddev, 3-stddev etc + stream + :class:`plotly.graph_objects.box.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with each sample + value. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.box.Unselected` instance + or dict with compatible properties + upperfence + Sets the upper fence values. There should be as many + items as the number of boxes desired. This attribute + has effect only under the q1/median/q3 signature. If + `upperfence` is not provided but a sample (in `y` or + `x`) is set, we compute the upper as the last sample + point above 1.5 times the IQR. + upperfencesrc + Sets the source reference on Chart Studio Cloud for + `upperfence`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + whiskerwidth + Sets the width of the whiskers relative to the box + width. For example, with 1, the whiskers are as wide as + the box(es). + width + Sets the width of the box in data coordinate If 0 + (default value) the width is automatically selected + based on the positions of other box traces in the same + subplot. + x + Sets the x sample data or coordinates. See overview for + more info. + x0 + Sets the x coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y sample data or coordinates. See overview for + more info. + y0 + Sets the y coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Box + + new_trace = Box( + alignmentgroup=alignmentgroup, + boxmean=boxmean, + boxpoints=boxpoints, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + jitter=jitter, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + lowerfence=lowerfence, + lowerfencesrc=lowerfencesrc, + marker=marker, + mean=mean, + meansrc=meansrc, + median=median, + mediansrc=mediansrc, + meta=meta, + metasrc=metasrc, + name=name, + notched=notched, + notchspan=notchspan, + notchspansrc=notchspansrc, + notchwidth=notchwidth, + offsetgroup=offsetgroup, + opacity=opacity, + orientation=orientation, + pointpos=pointpos, + q1=q1, + q1src=q1src, + q3=q3, + q3src=q3src, + quartilemethod=quartilemethod, + sd=sd, + sdmultiple=sdmultiple, + sdsrc=sdsrc, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + showwhiskers=showwhiskers, + sizemode=sizemode, + stream=stream, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + upperfence=upperfence, + upperfencesrc=upperfencesrc, + visible=visible, + whiskerwidth=whiskerwidth, + width=width, + x=x, + x0=x0, + xaxis=xaxis, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + y=y, + y0=y0, + yaxis=yaxis, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_candlestick( + self, + close=None, + closesrc=None, + customdata=None, + customdatasrc=None, + decreasing=None, + high=None, + highsrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + increasing=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + low=None, + lowsrc=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + open=None, + opensrc=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + visible=None, + whiskerwidth=None, + x=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + yaxis=None, + yhoverformat=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Candlestick trace + + The candlestick is a style of financial chart describing open, + high, low and close for a given `x` coordinate (most likely + time). The boxes represent the spread between the `open` and + `close` values and the lines represent the spread between the + `low` and `high` values Sample points where the close value is + higher (lower) then the open value are called increasing + (decreasing). By default, increasing candles are drawn in green + whereas decreasing are drawn in red. + + Parameters + ---------- + close + Sets the close values. + closesrc + Sets the source reference on Chart Studio Cloud for + `close`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + decreasing + :class:`plotly.graph_objects.candlestick.Decreasing` + instance or dict with compatible properties + high + Sets the high values. + highsrc + Sets the source reference on Chart Studio Cloud for + `high`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.candlestick.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `open`, `high`, `low` and `close`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + increasing + :class:`plotly.graph_objects.candlestick.Increasing` + instance or dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.candlestick.Legendgrouptit + le` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.candlestick.Line` instance + or dict with compatible properties + low + Sets the low values. + lowsrc + Sets the source reference on Chart Studio Cloud for + `low`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + open + Sets the open values. + opensrc + Sets the source reference on Chart Studio Cloud for + `open`. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.candlestick.Stream` + instance or dict with compatible properties + text + Sets hover text elements associated with each sample + point. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to this trace's sample points. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + whiskerwidth + Sets the width of the whiskers relative to the box + width. For example, with 1, the whiskers are as wide as + the box(es). + x + Sets the x coordinates. If absent, linear coordinate + will be generated. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Candlestick + + new_trace = Candlestick( + close=close, + closesrc=closesrc, + customdata=customdata, + customdatasrc=customdatasrc, + decreasing=decreasing, + high=high, + highsrc=highsrc, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + increasing=increasing, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + low=low, + lowsrc=lowsrc, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + open=open, + opensrc=opensrc, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + visible=visible, + whiskerwidth=whiskerwidth, + x=x, + xaxis=xaxis, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + yaxis=yaxis, + yhoverformat=yhoverformat, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_carpet( + self, + a=None, + a0=None, + aaxis=None, + asrc=None, + b=None, + b0=None, + baxis=None, + bsrc=None, + carpet=None, + cheaterslope=None, + color=None, + customdata=None, + customdatasrc=None, + da=None, + db=None, + font=None, + ids=None, + idssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + stream=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xaxis=None, + xsrc=None, + y=None, + yaxis=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Carpet trace + + The data describing carpet axis layout is set in `y` and + (optionally) also `x`. If only `y` is present, `x` the plot is + interpreted as a cheater plot and is filled in using the `y` + values. `x` and `y` may either be 2D arrays matching with each + dimension matching that of `a` and `b`, or they may be 1D + arrays with total length equal to that of `a` and `b`. + + Parameters + ---------- + a + An array containing values of the first parameter value + a0 + Alternate to `a`. Builds a linear space of a + coordinates. Use with `da` where `a0` is the starting + coordinate and `da` the step. + aaxis + :class:`plotly.graph_objects.carpet.Aaxis` instance or + dict with compatible properties + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + b + A two dimensional array of y coordinates at each carpet + point. + b0 + Alternate to `b`. Builds a linear space of a + coordinates. Use with `db` where `b0` is the starting + coordinate and `db` the step. + baxis + :class:`plotly.graph_objects.carpet.Baxis` instance or + dict with compatible properties + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + carpet + An identifier for this carpet, so that `scattercarpet` + and `contourcarpet` traces can specify a carpet plot on + which they lie + cheaterslope + The shift applied to each successive row of data in + creating a cheater plot. Only used if `x` is been + omitted. + color + Sets default for all colors associated with this axis + all at once: line, font, tick, and grid colors. Grid + color is lightened by blending this with the plot + background Individual pieces can override this. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + da + Sets the a coordinate step. See `a0` for more info. + db + Sets the b coordinate step. See `b0` for more info. + font + The default font used for axis & tick labels on this + carpet + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.carpet.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + stream + :class:`plotly.graph_objects.carpet.Stream` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + A two dimensional array of x coordinates at each carpet + point. If omitted, the plot is a cheater plot and the + xaxis is hidden by default. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + A two dimensional array of y coordinates at each carpet + point. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Carpet + + new_trace = Carpet( + a=a, + a0=a0, + aaxis=aaxis, + asrc=asrc, + b=b, + b0=b0, + baxis=baxis, + bsrc=bsrc, + carpet=carpet, + cheaterslope=cheaterslope, + color=color, + customdata=customdata, + customdatasrc=customdatasrc, + da=da, + db=db, + font=font, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + stream=stream, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + xaxis=xaxis, + xsrc=xsrc, + y=y, + yaxis=yaxis, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_choropleth( + self, + autocolorscale=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + featureidkey=None, + geo=None, + geojson=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + locationmode=None, + locations=None, + locationssrc=None, + marker=None, + meta=None, + metasrc=None, + name=None, + reversescale=None, + selected=None, + selectedpoints=None, + showlegend=None, + showscale=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Choropleth trace + + The data that describes the choropleth value-to-color mapping + is set in `z`. The geographic locations corresponding to each + value in `z` are set in `locations`. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.choropleth.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. Only + has an effect when `geojson` is set. Support nested + property, for example "properties.name". + geo + Sets a reference between this trace's geospatial + coordinates and a geographic map. If "geo" (the default + value), the geospatial coordinates refer to + `layout.geo`. If "geo2", the geospatial coordinates + refer to `layout.geo2`, and so on. + geojson + Sets optional GeoJSON data associated with this trace. + If not given, the features on the base map are used. It + can be set as a valid GeoJSON object or as a URL + string. Note that we only accept GeoJSONs of type + "FeatureCollection" or "Feature" with geometries of + type "Polygon" or "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.choropleth.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.choropleth.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + locationmode + The library used by the *country names* `locationmode` + option is changing in an upcoming version. Country + names in existing plots may not work in the new + version. Determines the set of locations used to match + entries in `locations` to regions on the map. Values + "ISO-3", "USA-states", *country names* correspond to + features on the base map and value "geojson-id" + corresponds to features from a custom GeoJSON linked to + the `geojson` attribute. + locations + Sets the coordinates via location IDs or names. See + `locationmode` for more info. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + marker + :class:`plotly.graph_objects.choropleth.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + selected + :class:`plotly.graph_objects.choropleth.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.choropleth.Stream` + instance or dict with compatible properties + text + Sets the text elements associated with each location. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.choropleth.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the color values. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Choropleth + + new_trace = Choropleth( + autocolorscale=autocolorscale, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + featureidkey=featureidkey, + geo=geo, + geojson=geojson, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + locationmode=locationmode, + locations=locations, + locationssrc=locationssrc, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + reversescale=reversescale, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + showscale=showscale, + stream=stream, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + z=z, + zauto=zauto, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_choroplethmap( + self, + autocolorscale=None, + below=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + featureidkey=None, + geojson=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + locations=None, + locationssrc=None, + marker=None, + meta=None, + metasrc=None, + name=None, + reversescale=None, + selected=None, + selectedpoints=None, + showlegend=None, + showscale=None, + stream=None, + subplot=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Choroplethmap trace + + GeoJSON features to be filled are set in `geojson` The data + that describes the choropleth value-to-color mapping is set in + `locations` and `z`. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the choropleth polygons will be inserted + before the layer with the specified ID. By default, + choroplethmap traces are placed above the water layers. + If set to '', the layer will be inserted above every + existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.choroplethmap.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. + Support nested property, for example "properties.name". + geojson + Sets the GeoJSON data associated with this trace. It + can be set as a valid GeoJSON object or as a URL + string. Note that we only accept GeoJSONs of type + "FeatureCollection" or "Feature" with geometries of + type "Polygon" or "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.choroplethmap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `properties` Anything contained in tag + `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.choroplethmap.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + locations + Sets which features found in "geojson" to plot using + their feature `id` field. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + marker + :class:`plotly.graph_objects.choroplethmap.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + selected + :class:`plotly.graph_objects.choroplethmap.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.choroplethmap.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a map subplot. If "map" (the default value), the + data refer to `layout.map`. If "map2", the data refer + to `layout.map2`, and so on. + text + Sets the text elements associated with each location. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.choroplethmap.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the color values. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Choroplethmap + + new_trace = Choroplethmap( + autocolorscale=autocolorscale, + below=below, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + featureidkey=featureidkey, + geojson=geojson, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + locations=locations, + locationssrc=locationssrc, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + reversescale=reversescale, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + showscale=showscale, + stream=stream, + subplot=subplot, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + z=z, + zauto=zauto, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_choroplethmapbox( + self, + autocolorscale=None, + below=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + featureidkey=None, + geojson=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + locations=None, + locationssrc=None, + marker=None, + meta=None, + metasrc=None, + name=None, + reversescale=None, + selected=None, + selectedpoints=None, + showlegend=None, + showscale=None, + stream=None, + subplot=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Choroplethmapbox trace + + "choroplethmapbox" trace is deprecated! Please consider + switching to the "choroplethmap" trace type and `map` subplots. + Learn more at: https://plotly.com/python/maplibre-migration/ as + well as https://plotly.com/javascript/maplibre-migration/ + GeoJSON features to be filled are set in `geojson` The data + that describes the choropleth value-to-color mapping is set in + `locations` and `z`. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the choropleth polygons will be inserted + before the layer with the specified ID. By default, + choroplethmapbox traces are placed above the water + layers. If set to '', the layer will be inserted above + every existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.choroplethmapbox.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. + Support nested property, for example "properties.name". + geojson + Sets the GeoJSON data associated with this trace. It + can be set as a valid GeoJSON object or as a URL + string. Note that we only accept GeoJSONs of type + "FeatureCollection" or "Feature" with geometries of + type "Polygon" or "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.choroplethmapbox.Hoverlabe + l` instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `properties` Anything contained in tag + `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.choroplethmapbox.Legendgro + uptitle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + locations + Sets which features found in "geojson" to plot using + their feature `id` field. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + marker + :class:`plotly.graph_objects.choroplethmapbox.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + selected + :class:`plotly.graph_objects.choroplethmapbox.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.choroplethmapbox.Stream` + instance or dict with compatible properties + subplot + mapbox subplots and traces are deprecated! Please + consider switching to `map` subplots and traces. Learn + more at: https://plotly.com/python/maplibre-migration/ + as well as https://plotly.com/javascript/maplibre- + migration/ Sets a reference between this trace's data + coordinates and a mapbox subplot. If "mapbox" (the + default value), the data refer to `layout.mapbox`. If + "mapbox2", the data refer to `layout.mapbox2`, and so + on. + text + Sets the text elements associated with each location. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.choroplethmapbox.Unselecte + d` instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the color values. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Choroplethmapbox + + new_trace = Choroplethmapbox( + autocolorscale=autocolorscale, + below=below, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + featureidkey=featureidkey, + geojson=geojson, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + locations=locations, + locationssrc=locationssrc, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + reversescale=reversescale, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + showscale=showscale, + stream=stream, + subplot=subplot, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + z=z, + zauto=zauto, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_cone( + self, + anchor=None, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + sizemode=None, + sizeref=None, + stream=None, + text=None, + textsrc=None, + u=None, + uhoverformat=None, + uid=None, + uirevision=None, + usrc=None, + v=None, + vhoverformat=None, + visible=None, + vsrc=None, + w=None, + whoverformat=None, + wsrc=None, + x=None, + xhoverformat=None, + xsrc=None, + y=None, + yhoverformat=None, + ysrc=None, + z=None, + zhoverformat=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Cone trace + + Use cone traces to visualize vector fields. Specify a vector + field using 6 1D arrays, 3 position arrays `x`, `y` and `z` and + 3 vector component arrays `u`, `v`, `w`. The cones are drawn + exactly at the positions given by `x`, `y` and `z`. + + Parameters + ---------- + anchor + Sets the cones' anchor with respect to their x/y/z + positions. Note that "cm" denote the cone's center of + mass which corresponds to 1/4 from the tail to tip. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here u/v/w norm) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmin` + must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as u/v/w norm. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmax` + must be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.cone.ColorBar` instance or + dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.cone.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `norm` Anything contained in tag `` + is displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.cone.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.cone.Lighting` instance or + dict with compatible properties + lightposition + :class:`plotly.graph_objects.cone.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + sizemode + Determines whether `sizeref` is set as a "scaled" (i.e + unitless) scalar (normalized by the max u/v/w norm in + the vector field) or as "absolute" value (in the same + units as the vector field). To display sizes in actual + vector length use "raw". + sizeref + Adjusts the cone size scaling. The size of the cones is + determined by their u/v/w norm multiplied a factor and + `sizeref`. This factor (computed internally) + corresponds to the minimum "time" to travel across two + successive x/y/z positions at the average velocity of + those two successive positions. All cones in a given + trace use the same factor. With `sizemode` set to + "raw", its default value is 1. With `sizemode` set to + "scaled", `sizeref` is unitless, its default value is + 0.5. With `sizemode` set to "absolute", `sizeref` has + the same units as the u/v/w vector field, its the + default value is half the sample's maximum vector norm. + stream + :class:`plotly.graph_objects.cone.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with the cones. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + u + Sets the x components of the vector field. + uhoverformat + Sets the hover text formatting rulefor `u` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + usrc + Sets the source reference on Chart Studio Cloud for + `u`. + v + Sets the y components of the vector field. + vhoverformat + Sets the hover text formatting rulefor `v` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + vsrc + Sets the source reference on Chart Studio Cloud for + `v`. + w + Sets the z components of the vector field. + whoverformat + Sets the hover text formatting rulefor `w` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + wsrc + Sets the source reference on Chart Studio Cloud for + `w`. + x + Sets the x coordinates of the vector field and of the + displayed cones. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates of the vector field and of the + displayed cones. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates of the vector field and of the + displayed cones. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Cone + + new_trace = Cone( + anchor=anchor, + autocolorscale=autocolorscale, + cauto=cauto, + cmax=cmax, + cmid=cmid, + cmin=cmin, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lighting=lighting, + lightposition=lightposition, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + reversescale=reversescale, + scene=scene, + showlegend=showlegend, + showscale=showscale, + sizemode=sizemode, + sizeref=sizeref, + stream=stream, + text=text, + textsrc=textsrc, + u=u, + uhoverformat=uhoverformat, + uid=uid, + uirevision=uirevision, + usrc=usrc, + v=v, + vhoverformat=vhoverformat, + visible=visible, + vsrc=vsrc, + w=w, + whoverformat=whoverformat, + wsrc=wsrc, + x=x, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zhoverformat=zhoverformat, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_contour( + self, + autocolorscale=None, + autocontour=None, + coloraxis=None, + colorbar=None, + colorscale=None, + connectgaps=None, + contours=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoverongaps=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + meta=None, + metasrc=None, + name=None, + ncontours=None, + opacity=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + text=None, + textfont=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + transpose=None, + uid=None, + uirevision=None, + visible=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + xtype=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + ytype=None, + z=None, + zauto=None, + zhoverformat=None, + zmax=None, + zmid=None, + zmin=None, + zorder=None, + zsrc=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Contour trace + + The data from which contour lines are computed is set in `z`. + Data in `z` must be a 2D list of numbers. Say that `z` has N + rows and M columns, then by default, these N rows correspond to + N y coordinates (set in `y` or auto-generated) and the M + columns correspond to M x coordinates (set in `x` or auto- + generated). By setting `transpose` to True, the above behavior + is flipped. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + autocontour + Determines whether or not the contour level attributes + are picked by an algorithm. If True, the number of + contour levels can be set in `ncontours`. If False, set + the contour level attributes in `contours`. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.contour.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data are filled in. It is defaulted + to true if `z` is a one dimensional array otherwise it + is defaulted to false. + contours + :class:`plotly.graph_objects.contour.Contours` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + fillcolor + Sets the fill color if `contours.type` is "constraint". + Defaults to a half-transparent variant of the line + color, marker color, or marker line color, whichever is + available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.contour.Hoverlabel` + instance or dict with compatible properties + hoverongaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data have hover labels associated + with them. + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.contour.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.contour.Line` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + ncontours + Sets the maximum number of contour levels. The actual + number of contours will be chosen automatically to be + less than or equal to the value of `ncontours`. Has an + effect only if `autocontour` is True or if + `contours.size` is missing. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.contour.Stream` instance + or dict with compatible properties + text + Sets the text elements associated with each z value. + textfont + For this trace it only has an effect if `coloring` is + set to "heatmap". Sets the text font. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + For this trace it only has an effect if `coloring` is + set to "heatmap". Template string used for rendering + the information text that appears on points. Note that + this will override `textinfo`. Variables are inserted + using %{variable}, for example "y: %{y}". Numbers are + formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `x`, `y`, `z` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + transpose + Transposes the z data. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + xtype + If "array", the heatmap's x coordinates are given by + "x" (the default behavior when `x` is provided). If + "scaled", the heatmap's x coordinates are given by "x0" + and "dx" (the default behavior when `x` is not + provided). + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + ytype + If "array", the heatmap's y coordinates are given by + "y" (the default behavior when `y` is provided) If + "scaled", the heatmap's y coordinates are given by "y0" + and "dy" (the default behavior when `y` is not + provided) + z + Sets the z data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Contour + + new_trace = Contour( + autocolorscale=autocolorscale, + autocontour=autocontour, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + connectgaps=connectgaps, + contours=contours, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoverongaps=hoverongaps, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + meta=meta, + metasrc=metasrc, + name=name, + ncontours=ncontours, + opacity=opacity, + reversescale=reversescale, + showlegend=showlegend, + showscale=showscale, + stream=stream, + text=text, + textfont=textfont, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + transpose=transpose, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + x0=x0, + xaxis=xaxis, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + xtype=xtype, + y=y, + y0=y0, + yaxis=yaxis, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + ytype=ytype, + z=z, + zauto=zauto, + zhoverformat=zhoverformat, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zorder=zorder, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_contourcarpet( + self, + a=None, + a0=None, + asrc=None, + atype=None, + autocolorscale=None, + autocontour=None, + b=None, + b0=None, + bsrc=None, + btype=None, + carpet=None, + coloraxis=None, + colorbar=None, + colorscale=None, + contours=None, + customdata=None, + customdatasrc=None, + da=None, + db=None, + fillcolor=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + meta=None, + metasrc=None, + name=None, + ncontours=None, + opacity=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + text=None, + textsrc=None, + transpose=None, + uid=None, + uirevision=None, + visible=None, + xaxis=None, + yaxis=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zorder=None, + zsrc=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Contourcarpet trace + + Plots contours on either the first carpet axis or the carpet + axis with a matching `carpet` attribute. Data `z` is + interpreted as matching that of the corresponding carpet axis. + + Parameters + ---------- + a + Sets the x coordinates. + a0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + atype + If "array", the heatmap's x coordinates are given by + "x" (the default behavior when `x` is provided). If + "scaled", the heatmap's x coordinates are given by "x0" + and "dx" (the default behavior when `x` is not + provided). + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + autocontour + Determines whether or not the contour level attributes + are picked by an algorithm. If True, the number of + contour levels can be set in `ncontours`. If False, set + the contour level attributes in `contours`. + b + Sets the y coordinates. + b0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + btype + If "array", the heatmap's y coordinates are given by + "y" (the default behavior when `y` is provided) If + "scaled", the heatmap's y coordinates are given by "y0" + and "dy" (the default behavior when `y` is not + provided) + carpet + The `carpet` of the carpet axes on which this contour + trace lies + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.contourcarpet.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contours + :class:`plotly.graph_objects.contourcarpet.Contours` + instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + da + Sets the x coordinate step. See `x0` for more info. + db + Sets the y coordinate step. See `y0` for more info. + fillcolor + Sets the fill color if `contours.type` is "constraint". + Defaults to a half-transparent variant of the line + color, marker color, or marker line color, whichever is + available. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.contourcarpet.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.contourcarpet.Line` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + ncontours + Sets the maximum number of contour levels. The actual + number of contours will be chosen automatically to be + less than or equal to the value of `ncontours`. Has an + effect only if `autocontour` is True or if + `contours.size` is missing. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.contourcarpet.Stream` + instance or dict with compatible properties + text + Sets the text elements associated with each z value. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + transpose + Transposes the z data. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + z + Sets the z data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Contourcarpet + + new_trace = Contourcarpet( + a=a, + a0=a0, + asrc=asrc, + atype=atype, + autocolorscale=autocolorscale, + autocontour=autocontour, + b=b, + b0=b0, + bsrc=bsrc, + btype=btype, + carpet=carpet, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + contours=contours, + customdata=customdata, + customdatasrc=customdatasrc, + da=da, + db=db, + fillcolor=fillcolor, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + meta=meta, + metasrc=metasrc, + name=name, + ncontours=ncontours, + opacity=opacity, + reversescale=reversescale, + showlegend=showlegend, + showscale=showscale, + stream=stream, + text=text, + textsrc=textsrc, + transpose=transpose, + uid=uid, + uirevision=uirevision, + visible=visible, + xaxis=xaxis, + yaxis=yaxis, + z=z, + zauto=zauto, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zorder=zorder, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_densitymap( + self, + autocolorscale=None, + below=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + lat=None, + latsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lon=None, + lonsrc=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + radius=None, + radiussrc=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + subplot=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + visible=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Densitymap trace + + Draws a bivariate kernel density estimation with a Gaussian + kernel from `lon` and `lat` coordinates and optional `z` values + using a colorscale. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the densitymap trace will be inserted + before the layer with the specified ID. By default, + densitymap traces are placed below the first layer of + type symbol If set to '', the layer will be inserted + above every existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.densitymap.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.densitymap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.densitymap.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + radius + Sets the radius of influence of one `lon` / `lat` point + in pixels. Increasing the value makes the densitymap + trace smoother, but less detailed. + radiussrc + Sets the source reference on Chart Studio Cloud for + `radius`. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.densitymap.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a map subplot. If "map" (the default value), the + data refer to `layout.map`. If "map2", the data refer + to `layout.map2`, and so on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the points' weight. For example, a value of 10 + would be equivalent to having 10 points of weight 1 in + the same spot + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Densitymap + + new_trace = Densitymap( + autocolorscale=autocolorscale, + below=below, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + lat=lat, + latsrc=latsrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lon=lon, + lonsrc=lonsrc, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + radius=radius, + radiussrc=radiussrc, + reversescale=reversescale, + showlegend=showlegend, + showscale=showscale, + stream=stream, + subplot=subplot, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + visible=visible, + z=z, + zauto=zauto, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_densitymapbox( + self, + autocolorscale=None, + below=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + lat=None, + latsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lon=None, + lonsrc=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + radius=None, + radiussrc=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + subplot=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + visible=None, + z=None, + zauto=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Densitymapbox trace + + "densitymapbox" trace is deprecated! Please consider switching + to the "densitymap" trace type and `map` subplots. Learn more + at: https://plotly.com/python/maplibre-migration/ as well as + https://plotly.com/javascript/maplibre-migration/ Draws a + bivariate kernel density estimation with a Gaussian kernel from + `lon` and `lat` coordinates and optional `z` values using a + colorscale. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + below + Determines if the densitymapbox trace will be inserted + before the layer with the specified ID. By default, + densitymapbox traces are placed below the first layer + of type symbol If set to '', the layer will be inserted + above every existing layer. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.densitymapbox.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.densitymapbox.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.densitymapbox.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + radius + Sets the radius of influence of one `lon` / `lat` point + in pixels. Increasing the value makes the densitymapbox + trace smoother, but less detailed. + radiussrc + Sets the source reference on Chart Studio Cloud for + `radius`. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.densitymapbox.Stream` + instance or dict with compatible properties + subplot + mapbox subplots and traces are deprecated! Please + consider switching to `map` subplots and traces. Learn + more at: https://plotly.com/python/maplibre-migration/ + as well as https://plotly.com/javascript/maplibre- + migration/ Sets a reference between this trace's data + coordinates and a mapbox subplot. If "mapbox" (the + default value), the data refer to `layout.mapbox`. If + "mapbox2", the data refer to `layout.mapbox2`, and so + on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + z + Sets the points' weight. For example, a value of 10 + would be equivalent to having 10 points of weight 1 in + the same spot + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Densitymapbox + + new_trace = Densitymapbox( + autocolorscale=autocolorscale, + below=below, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + lat=lat, + latsrc=latsrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lon=lon, + lonsrc=lonsrc, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + radius=radius, + radiussrc=radiussrc, + reversescale=reversescale, + showlegend=showlegend, + showscale=showscale, + stream=stream, + subplot=subplot, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + visible=visible, + z=z, + zauto=zauto, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_funnel( + self, + alignmentgroup=None, + cliponaxis=None, + connector=None, + constraintext=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextanchor=None, + insidetextfont=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + offset=None, + offsetgroup=None, + opacity=None, + orientation=None, + outsidetextfont=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textangle=None, + textfont=None, + textinfo=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + visible=None, + width=None, + x=None, + x0=None, + xaxis=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Funnel trace + + Visualize stages in a process using length-encoded bars. This + trace can be used to show data in either a part-to-whole + representation wherein each item appears in a single stage, or + in a "drop-off" representation wherein each item appears in + each stage it traversed. See also the "funnelarea" trace type + for a different approach to visualizing funnel data. + + Parameters + ---------- + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + connector + :class:`plotly.graph_objects.funnel.Connector` instance + or dict with compatible properties + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.funnel.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `percentInitial`, `percentPrevious` and + `percentTotal`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.funnel.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.funnel.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the position where the bar is drawn (in position + axis units). In "group" barmode, traces that set + "offset" will be excluded and drawn in "overlay" mode + instead. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the funnels. With "v" ("h"), + the value of the each bar spans along the vertical + (horizontal). By default funnels are tend to be + oriented horizontally; unless only "y" array is + presented or orientation is set to "v". Also regarding + graphs including only 'horizontal' funnels, "autorange" + on the "y-axis" are set to "reversed". + outsidetextfont + Sets the font used for `text` lying outside the bar. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.funnel.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the font used for `text`. + textinfo + Determines which trace information appear on the graph. + In the case of having multiple funnels, percentages & + totals are computed separately (per trace). + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `percentInitial`, `percentPrevious`, + `percentTotal`, `label` and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar width (in position axis units). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Funnel + + new_trace = Funnel( + alignmentgroup=alignmentgroup, + cliponaxis=cliponaxis, + connector=connector, + constraintext=constraintext, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextanchor=insidetextanchor, + insidetextfont=insidetextfont, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + offset=offset, + offsetgroup=offsetgroup, + opacity=opacity, + orientation=orientation, + outsidetextfont=outsidetextfont, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textangle=textangle, + textfont=textfont, + textinfo=textinfo, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + visible=visible, + width=width, + x=x, + x0=x0, + xaxis=xaxis, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + y=y, + y0=y0, + yaxis=yaxis, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_funnelarea( + self, + aspectratio=None, + baseratio=None, + customdata=None, + customdatasrc=None, + dlabel=None, + domain=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextfont=None, + label0=None, + labels=None, + labelssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + scalegroup=None, + showlegend=None, + stream=None, + text=None, + textfont=None, + textinfo=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + title=None, + uid=None, + uirevision=None, + values=None, + valuessrc=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Funnelarea trace + + Visualize stages in a process using area-encoded trapezoids. + This trace can be used to show data in a part-to-whole + representation similar to a "pie" trace, wherein each item + appears in a single stage. See also the "funnel" trace type for + a different approach to visualizing funnel data. + + Parameters + ---------- + aspectratio + Sets the ratio between height and width + baseratio + Sets the ratio between bottom length and maximum top + length. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dlabel + Sets the label step. See `label0` for more info. + domain + :class:`plotly.graph_objects.funnelarea.Domain` + instance or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.funnelarea.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `text` and + `percent`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + label0 + Alternate to `labels`. Builds a numeric set of labels. + Use with `dlabel` where `label0` is the starting label + and `dlabel` the step. + labels + Sets the sector labels. If `labels` entries are + duplicated, we sum associated `values` or simply count + occurrences if `values` is not provided. For other + array attributes (including color) we use the first + non-empty entry among all occurrences of the label. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.funnelarea.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.funnelarea.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + scalegroup + If there are multiple funnelareas that should be sized + according to their totals, link them by providing a + non-empty group id here shared by every trace in the + same group. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.funnelarea.Stream` + instance or dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Specifies the location of the `textinfo`. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `text` and + `percent`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + title + :class:`plotly.graph_objects.funnelarea.Title` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values of the sectors. If omitted, we count + occurrences of each label. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Funnelarea + + new_trace = Funnelarea( + aspectratio=aspectratio, + baseratio=baseratio, + customdata=customdata, + customdatasrc=customdatasrc, + dlabel=dlabel, + domain=domain, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextfont=insidetextfont, + label0=label0, + labels=labels, + labelssrc=labelssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + scalegroup=scalegroup, + showlegend=showlegend, + stream=stream, + text=text, + textfont=textfont, + textinfo=textinfo, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + title=title, + uid=uid, + uirevision=uirevision, + values=values, + valuessrc=valuessrc, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_heatmap( + self, + autocolorscale=None, + coloraxis=None, + colorbar=None, + colorscale=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoverongaps=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + text=None, + textfont=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + transpose=None, + uid=None, + uirevision=None, + visible=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xgap=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + xtype=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + ygap=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + ytype=None, + z=None, + zauto=None, + zhoverformat=None, + zmax=None, + zmid=None, + zmin=None, + zorder=None, + zsmooth=None, + zsrc=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Heatmap trace + + The data that describes the heatmap value-to-color mapping is + set in `z`. Data in `z` can either be a 2D list of values + (ragged or not) or a 1D array of values. In the case where `z` + is a 2D list, say that `z` has N rows and M columns. Then, by + default, the resulting heatmap will have N partitions along the + y axis and M partitions along the x axis. In other words, the + i-th row/ j-th column cell in `z` is mapped to the i-th + partition of the y axis (starting from the bottom of the plot) + and the j-th partition of the x-axis (starting from the left of + the plot). This behavior can be flipped by using `transpose`. + Moreover, `x` (`y`) can be provided with M or M+1 (N or N+1) + elements. If M (N), then the coordinates correspond to the + center of the heatmap cells and the cells have equal width. If + M+1 (N+1), then the coordinates correspond to the edges of the + heatmap cells. In the case where `z` is a 1D list, the x and y + coordinates must be provided in `x` and `y` respectively to + form data triplets. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.heatmap.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data are filled in. It is defaulted + to true if `z` is a one dimensional array and `zsmooth` + is not false; otherwise it is defaulted to false. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.heatmap.Hoverlabel` + instance or dict with compatible properties + hoverongaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data have hover labels associated + with them. + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.heatmap.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.heatmap.Stream` instance + or dict with compatible properties + text + Sets the text elements associated with each z value. + textfont + Sets the text font. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `x`, `y`, `z` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + transpose + Transposes the z data. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xgap + Sets the horizontal gap (in pixels) between bricks. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + xtype + If "array", the heatmap's x coordinates are given by + "x" (the default behavior when `x` is provided). If + "scaled", the heatmap's x coordinates are given by "x0" + and "dx" (the default behavior when `x` is not + provided). + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + ygap + Sets the vertical gap (in pixels) between bricks. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + ytype + If "array", the heatmap's y coordinates are given by + "y" (the default behavior when `y` is provided) If + "scaled", the heatmap's y coordinates are given by "y0" + and "dy" (the default behavior when `y` is not + provided) + z + Sets the z data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsmooth + Picks a smoothing algorithm use to smooth `z` data. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Heatmap + + new_trace = Heatmap( + autocolorscale=autocolorscale, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoverongaps=hoverongaps, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + reversescale=reversescale, + showlegend=showlegend, + showscale=showscale, + stream=stream, + text=text, + textfont=textfont, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + transpose=transpose, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + x0=x0, + xaxis=xaxis, + xcalendar=xcalendar, + xgap=xgap, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + xtype=xtype, + y=y, + y0=y0, + yaxis=yaxis, + ycalendar=ycalendar, + ygap=ygap, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + ytype=ytype, + z=z, + zauto=zauto, + zhoverformat=zhoverformat, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zorder=zorder, + zsmooth=zsmooth, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_histogram( + self, + alignmentgroup=None, + autobinx=None, + autobiny=None, + bingroup=None, + cliponaxis=None, + constraintext=None, + cumulative=None, + customdata=None, + customdatasrc=None, + error_x=None, + error_y=None, + histfunc=None, + histnorm=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextanchor=None, + insidetextfont=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + nbinsx=None, + nbinsy=None, + offsetgroup=None, + opacity=None, + orientation=None, + outsidetextfont=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textangle=None, + textfont=None, + textposition=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + x=None, + xaxis=None, + xbins=None, + xcalendar=None, + xhoverformat=None, + xsrc=None, + y=None, + yaxis=None, + ybins=None, + ycalendar=None, + yhoverformat=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Histogram trace + + The sample data from which statistics are computed is set in + `x` for vertically spanning histograms and in `y` for + horizontally spanning histograms. Binning options are set + `xbins` and `ybins` respectively if no aggregation data is + provided. + + Parameters + ---------- + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + autobinx + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobinx` is not needed. + However, we accept `autobinx: true` or `false` and will + update `xbins` accordingly before deleting `autobinx` + from the trace. + autobiny + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobiny` is not needed. + However, we accept `autobiny: true` or `false` and will + update `ybins` accordingly before deleting `autobiny` + from the trace. + bingroup + Set a group of histogram traces which will have + compatible bin settings. Note that traces on the same + subplot and with the same "orientation" under `barmode` + "stack", "relative" and "group" are forced into the + same bingroup, Using `bingroup`, traces under `barmode` + "overlay" and on different axes (of the same axis type) + can have compatible bin settings. Note that histogram + and histogram2d* trace can share the same `bingroup` + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + cumulative + :class:`plotly.graph_objects.histogram.Cumulative` + instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + error_x + :class:`plotly.graph_objects.histogram.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.histogram.ErrorY` instance + or dict with compatible properties + histfunc + Specifies the binning function used for this histogram + trace. If "count", the histogram values are computed by + counting the number of values lying inside each bin. If + "sum", "avg", "min", "max", the histogram values are + computed using the sum, the average, the minimum or the + maximum of the values lying inside each bin + respectively. + histnorm + Specifies the type of normalization used for this + histogram trace. If "", the span of each bar + corresponds to the number of occurrences (i.e. the + number of data points lying inside the bins). If + "percent" / "probability", the span of each bar + corresponds to the percentage / fraction of occurrences + with respect to the total number of sample points + (here, the sum of all bin HEIGHTS equals 100% / 1). If + "density", the span of each bar corresponds to the + number of occurrences in a bin divided by the size of + the bin interval (here, the sum of all bin AREAS equals + the total number of sample points). If *probability + density*, the area of each bar corresponds to the + probability that an event will fall into the + corresponding bin (here, the sum of all bin AREAS + equals 1). + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.histogram.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `binNumber` Anything contained in tag + `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.histogram.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.histogram.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + nbinsx + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `xbins.size` is provided. + nbinsy + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `ybins.size` is provided. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the bars. With "v" ("h"), the + value of the each bar spans along the vertical + (horizontal). + outsidetextfont + Sets the font used for `text` lying outside the bar. + selected + :class:`plotly.graph_objects.histogram.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.histogram.Stream` instance + or dict with compatible properties + text + Sets hover text elements associated with each bar. If a + single string, the same string appears over all bars. + If an array of string, the items are mapped in order to + the this trace's coordinates. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the text font. + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label` and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.histogram.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the sample data to be binned on the x axis. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xbins + :class:`plotly.graph_objects.histogram.XBins` instance + or dict with compatible properties + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the sample data to be binned on the y axis. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ybins + :class:`plotly.graph_objects.histogram.YBins` instance + or dict with compatible properties + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Histogram + + new_trace = Histogram( + alignmentgroup=alignmentgroup, + autobinx=autobinx, + autobiny=autobiny, + bingroup=bingroup, + cliponaxis=cliponaxis, + constraintext=constraintext, + cumulative=cumulative, + customdata=customdata, + customdatasrc=customdatasrc, + error_x=error_x, + error_y=error_y, + histfunc=histfunc, + histnorm=histnorm, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextanchor=insidetextanchor, + insidetextfont=insidetextfont, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + nbinsx=nbinsx, + nbinsy=nbinsy, + offsetgroup=offsetgroup, + opacity=opacity, + orientation=orientation, + outsidetextfont=outsidetextfont, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textangle=textangle, + textfont=textfont, + textposition=textposition, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + x=x, + xaxis=xaxis, + xbins=xbins, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + yaxis=yaxis, + ybins=ybins, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_histogram2d( + self, + autobinx=None, + autobiny=None, + autocolorscale=None, + bingroup=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + histfunc=None, + histnorm=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + nbinsx=None, + nbinsy=None, + opacity=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + textfont=None, + texttemplate=None, + texttemplatefallback=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xaxis=None, + xbingroup=None, + xbins=None, + xcalendar=None, + xgap=None, + xhoverformat=None, + xsrc=None, + y=None, + yaxis=None, + ybingroup=None, + ybins=None, + ycalendar=None, + ygap=None, + yhoverformat=None, + ysrc=None, + z=None, + zauto=None, + zhoverformat=None, + zmax=None, + zmid=None, + zmin=None, + zsmooth=None, + zsrc=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Histogram2d trace + + The sample data from which statistics are computed is set in + `x` and `y` (where `x` and `y` represent marginal + distributions, binning is set in `xbins` and `ybins` in this + case) or `z` (where `z` represent the 2D distribution and + binning set, binning is set by `x` and `y` in this case). The + resulting distribution is visualized as a heatmap. + + Parameters + ---------- + autobinx + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobinx` is not needed. + However, we accept `autobinx: true` or `false` and will + update `xbins` accordingly before deleting `autobinx` + from the trace. + autobiny + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobiny` is not needed. + However, we accept `autobiny: true` or `false` and will + update `ybins` accordingly before deleting `autobiny` + from the trace. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + bingroup + Set the `xbingroup` and `ybingroup` default prefix For + example, setting a `bingroup` of 1 on two histogram2d + traces will make them their x-bins and y-bins match + separately. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.histogram2d.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + histfunc + Specifies the binning function used for this histogram + trace. If "count", the histogram values are computed by + counting the number of values lying inside each bin. If + "sum", "avg", "min", "max", the histogram values are + computed using the sum, the average, the minimum or the + maximum of the values lying inside each bin + respectively. + histnorm + Specifies the type of normalization used for this + histogram trace. If "", the span of each bar + corresponds to the number of occurrences (i.e. the + number of data points lying inside the bins). If + "percent" / "probability", the span of each bar + corresponds to the percentage / fraction of occurrences + with respect to the total number of sample points + (here, the sum of all bin HEIGHTS equals 100% / 1). If + "density", the span of each bar corresponds to the + number of occurrences in a bin divided by the size of + the bin interval (here, the sum of all bin AREAS equals + the total number of sample points). If *probability + density*, the area of each bar corresponds to the + probability that an event will fall into the + corresponding bin (here, the sum of all bin AREAS + equals 1). + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.histogram2d.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `z` Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.histogram2d.Legendgrouptit + le` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.histogram2d.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + nbinsx + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `xbins.size` is provided. + nbinsy + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `ybins.size` is provided. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.histogram2d.Stream` + instance or dict with compatible properties + textfont + Sets the text font. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `z` + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the sample data to be binned on the x axis. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xbingroup + Set a group of histogram traces which will have + compatible x-bin settings. Using `xbingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible x-bin settings. + Note that the same `xbingroup` value can be used to set + (1D) histogram `bingroup` + xbins + :class:`plotly.graph_objects.histogram2d.XBins` + instance or dict with compatible properties + xcalendar + Sets the calendar system to use with `x` date data. + xgap + Sets the horizontal gap (in pixels) between bricks. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the sample data to be binned on the y axis. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ybingroup + Set a group of histogram traces which will have + compatible y-bin settings. Using `ybingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible y-bin settings. + Note that the same `ybingroup` value can be used to set + (1D) histogram `bingroup` + ybins + :class:`plotly.graph_objects.histogram2d.YBins` + instance or dict with compatible properties + ycalendar + Sets the calendar system to use with `y` date data. + ygap + Sets the vertical gap (in pixels) between bricks. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the aggregation data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsmooth + Picks a smoothing algorithm use to smooth `z` data. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Histogram2d + + new_trace = Histogram2d( + autobinx=autobinx, + autobiny=autobiny, + autocolorscale=autocolorscale, + bingroup=bingroup, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + histfunc=histfunc, + histnorm=histnorm, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + nbinsx=nbinsx, + nbinsy=nbinsy, + opacity=opacity, + reversescale=reversescale, + showlegend=showlegend, + showscale=showscale, + stream=stream, + textfont=textfont, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + xaxis=xaxis, + xbingroup=xbingroup, + xbins=xbins, + xcalendar=xcalendar, + xgap=xgap, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + yaxis=yaxis, + ybingroup=ybingroup, + ybins=ybins, + ycalendar=ycalendar, + ygap=ygap, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zauto=zauto, + zhoverformat=zhoverformat, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zsmooth=zsmooth, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_histogram2dcontour( + self, + autobinx=None, + autobiny=None, + autocolorscale=None, + autocontour=None, + bingroup=None, + coloraxis=None, + colorbar=None, + colorscale=None, + contours=None, + customdata=None, + customdatasrc=None, + histfunc=None, + histnorm=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + name=None, + nbinsx=None, + nbinsy=None, + ncontours=None, + opacity=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + textfont=None, + texttemplate=None, + texttemplatefallback=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xaxis=None, + xbingroup=None, + xbins=None, + xcalendar=None, + xhoverformat=None, + xsrc=None, + y=None, + yaxis=None, + ybingroup=None, + ybins=None, + ycalendar=None, + yhoverformat=None, + ysrc=None, + z=None, + zauto=None, + zhoverformat=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Histogram2dContour trace + + The sample data from which statistics are computed is set in + `x` and `y` (where `x` and `y` represent marginal + distributions, binning is set in `xbins` and `ybins` in this + case) or `z` (where `z` represent the 2D distribution and + binning set, binning is set by `x` and `y` in this case). The + resulting distribution is visualized as a contour plot. + + Parameters + ---------- + autobinx + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobinx` is not needed. + However, we accept `autobinx: true` or `false` and will + update `xbins` accordingly before deleting `autobinx` + from the trace. + autobiny + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobiny` is not needed. + However, we accept `autobiny: true` or `false` and will + update `ybins` accordingly before deleting `autobiny` + from the trace. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + autocontour + Determines whether or not the contour level attributes + are picked by an algorithm. If True, the number of + contour levels can be set in `ncontours`. If False, set + the contour level attributes in `contours`. + bingroup + Set the `xbingroup` and `ybingroup` default prefix For + example, setting a `bingroup` of 1 on two histogram2d + traces will make them their x-bins and y-bins match + separately. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.histogram2dcontour.ColorBa + r` instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contours + :class:`plotly.graph_objects.histogram2dcontour.Contour + s` instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + histfunc + Specifies the binning function used for this histogram + trace. If "count", the histogram values are computed by + counting the number of values lying inside each bin. If + "sum", "avg", "min", "max", the histogram values are + computed using the sum, the average, the minimum or the + maximum of the values lying inside each bin + respectively. + histnorm + Specifies the type of normalization used for this + histogram trace. If "", the span of each bar + corresponds to the number of occurrences (i.e. the + number of data points lying inside the bins). If + "percent" / "probability", the span of each bar + corresponds to the percentage / fraction of occurrences + with respect to the total number of sample points + (here, the sum of all bin HEIGHTS equals 100% / 1). If + "density", the span of each bar corresponds to the + number of occurrences in a bin divided by the size of + the bin interval (here, the sum of all bin AREAS equals + the total number of sample points). If *probability + density*, the area of each bar corresponds to the + probability that an event will fall into the + corresponding bin (here, the sum of all bin AREAS + equals 1). + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.histogram2dcontour.Hoverla + bel` instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `z` Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.histogram2dcontour.Legendg + rouptitle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.histogram2dcontour.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.histogram2dcontour.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + nbinsx + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `xbins.size` is provided. + nbinsy + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `ybins.size` is provided. + ncontours + Sets the maximum number of contour levels. The actual + number of contours will be chosen automatically to be + less than or equal to the value of `ncontours`. Has an + effect only if `autocontour` is True or if + `contours.size` is missing. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.histogram2dcontour.Stream` + instance or dict with compatible properties + textfont + For this trace it only has an effect if `coloring` is + set to "heatmap". Sets the text font. + texttemplate + For this trace it only has an effect if `coloring` is + set to "heatmap". Template string used for rendering + the information text that appears on points. Note that + this will override `textinfo`. Variables are inserted + using %{variable}, for example "y: %{y}". Numbers are + formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `x`, `y`, `z` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the sample data to be binned on the x axis. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xbingroup + Set a group of histogram traces which will have + compatible x-bin settings. Using `xbingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible x-bin settings. + Note that the same `xbingroup` value can be used to set + (1D) histogram `bingroup` + xbins + :class:`plotly.graph_objects.histogram2dcontour.XBins` + instance or dict with compatible properties + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the sample data to be binned on the y axis. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ybingroup + Set a group of histogram traces which will have + compatible y-bin settings. Using `ybingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible y-bin settings. + Note that the same `ybingroup` value can be used to set + (1D) histogram `bingroup` + ybins + :class:`plotly.graph_objects.histogram2dcontour.YBins` + instance or dict with compatible properties + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the aggregation data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Histogram2dContour + + new_trace = Histogram2dContour( + autobinx=autobinx, + autobiny=autobiny, + autocolorscale=autocolorscale, + autocontour=autocontour, + bingroup=bingroup, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + contours=contours, + customdata=customdata, + customdatasrc=customdatasrc, + histfunc=histfunc, + histnorm=histnorm, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + nbinsx=nbinsx, + nbinsy=nbinsy, + ncontours=ncontours, + opacity=opacity, + reversescale=reversescale, + showlegend=showlegend, + showscale=showscale, + stream=stream, + textfont=textfont, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + xaxis=xaxis, + xbingroup=xbingroup, + xbins=xbins, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + yaxis=yaxis, + ybingroup=ybingroup, + ybins=ybins, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zauto=zauto, + zhoverformat=zhoverformat, + zmax=zmax, + zmid=zmid, + zmin=zmin, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_icicle( + self, + branchvalues=None, + count=None, + customdata=None, + customdatasrc=None, + domain=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextfont=None, + labels=None, + labelssrc=None, + leaf=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + level=None, + marker=None, + maxdepth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + outsidetextfont=None, + parents=None, + parentssrc=None, + pathbar=None, + root=None, + sort=None, + stream=None, + text=None, + textfont=None, + textinfo=None, + textposition=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + tiling=None, + uid=None, + uirevision=None, + values=None, + valuessrc=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Icicle trace + + Visualize hierarchal data from leaves (and/or outer branches) + towards root with rectangles. The icicle sectors are determined + by the entries in "labels" or "ids" and in "parents". + + Parameters + ---------- + branchvalues + Determines how the items in `values` are summed. When + set to "total", items in `values` are taken to be value + of all its descendants. When set to "remainder", items + in `values` corresponding to the root and the branches + sectors are taken to be the extra part not part of the + sum of the values at their leaves. + count + Determines default for `values` when it is not + provided, by inferring a 1 for each of the "leaves" + and/or "branches", otherwise 0. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.icicle.Domain` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.icicle.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry` and `percentParent`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + labels + Sets the labels of each of the sectors. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + leaf + :class:`plotly.graph_objects.icicle.Leaf` instance or + dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.icicle.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + level + Sets the level from which this trace hierarchy is + rendered. Set `level` to `''` to start from the root + node in the hierarchy. Must be an "id" if `ids` is + filled in, otherwise plotly attempts to find a matching + item in `labels`. + marker + :class:`plotly.graph_objects.icicle.Marker` instance or + dict with compatible properties + maxdepth + Sets the number of rendered sectors from any given + `level`. Set `maxdepth` to "-1" to render all the + levels in the hierarchy. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. This option refers to the root of the hierarchy + presented on top left corner of a treemap graph. Please + note that if a hierarchy has multiple root nodes, this + option won't have any effect and `insidetextfont` would + be used. + parents + Sets the parent sectors for each of the sectors. Empty + string items '' are understood to reference the root + node in the hierarchy. If `ids` is filled, `parents` + items are understood to be "ids" themselves. When `ids` + is not set, plotly attempts to find matching items in + `labels`, but beware they must be unique. + parentssrc + Sets the source reference on Chart Studio Cloud for + `parents`. + pathbar + :class:`plotly.graph_objects.icicle.Pathbar` instance + or dict with compatible properties + root + :class:`plotly.graph_objects.icicle.Root` instance or + dict with compatible properties + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.icicle.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Sets the positions of the `text` elements. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry`, `percentParent`, `label` + and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + tiling + :class:`plotly.graph_objects.icicle.Tiling` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values associated with each of the sectors. + Use with `branchvalues` to determine how the values are + summed. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Icicle + + new_trace = Icicle( + branchvalues=branchvalues, + count=count, + customdata=customdata, + customdatasrc=customdatasrc, + domain=domain, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextfont=insidetextfont, + labels=labels, + labelssrc=labelssrc, + leaf=leaf, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + level=level, + marker=marker, + maxdepth=maxdepth, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + outsidetextfont=outsidetextfont, + parents=parents, + parentssrc=parentssrc, + pathbar=pathbar, + root=root, + sort=sort, + stream=stream, + text=text, + textfont=textfont, + textinfo=textinfo, + textposition=textposition, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + tiling=tiling, + uid=uid, + uirevision=uirevision, + values=values, + valuessrc=valuessrc, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_image( + self, + colormodel=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + source=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + visible=None, + x0=None, + xaxis=None, + y0=None, + yaxis=None, + z=None, + zmax=None, + zmin=None, + zorder=None, + zsmooth=None, + zsrc=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Image trace + + Display an image, i.e. data on a 2D regular raster. By default, + when an image is displayed in a subplot, its y axis will be + reversed (ie. `autorange: 'reversed'`), constrained to the + domain (ie. `constrain: 'domain'`) and it will have the same + scale as its x axis (ie. `scaleanchor: 'x,`) in order for + pixels to be rendered as squares. + + Parameters + ---------- + colormodel + Color model used to map the numerical color components + described in `z` into colors. If `source` is specified, + this attribute will be set to `rgba256` otherwise it + defaults to `rgb`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Set the pixel's horizontal size. + dy + Set the pixel's vertical size + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.image.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `z`, `color` and `colormodel`. Anything + contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.image.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + source + Specifies the data URI of the image to be visualized. + The URI consists of "data:image/[][;base64\\]," + stream + :class:`plotly.graph_objects.image.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with each z value. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x0 + Set the image's x position. The left edge of the image + (or the right edge if the x axis is reversed or dx is + negative) will be found at xmin=x0-dx/2 + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + y0 + Set the image's y position. The top edge of the image + (or the bottom edge if the y axis is NOT reversed or if + dy is negative) will be found at ymin=y0-dy/2. By + default when an image trace is included, the y axis + will be reversed so that the image is right-side-up, + but you can disable this by setting + yaxis.autorange=true or by providing an explicit y axis + range. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + z + A 2-dimensional array in which each element is an array + of 3 or 4 numbers representing a color. + zmax + Array defining the higher bound for each color + component. Note that the default value will depend on + the colormodel. For the `rgb` colormodel, it is [255, + 255, 255]. For the `rgba` colormodel, it is [255, 255, + 255, 1]. For the `rgba256` colormodel, it is [255, 255, + 255, 255]. For the `hsl` colormodel, it is [360, 100, + 100]. For the `hsla` colormodel, it is [360, 100, 100, + 1]. + zmin + Array defining the lower bound for each color + component. Note that the default value will depend on + the colormodel. For the `rgb` colormodel, it is [0, 0, + 0]. For the `rgba` colormodel, it is [0, 0, 0, 0]. For + the `rgba256` colormodel, it is [0, 0, 0, 0]. For the + `hsl` colormodel, it is [0, 0, 0]. For the `hsla` + colormodel, it is [0, 0, 0, 0]. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsmooth + Picks a smoothing algorithm used to smooth `z` data. + This only applies for image traces that use the + `source` attribute. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Image + + new_trace = Image( + colormodel=colormodel, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + source=source, + stream=stream, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + visible=visible, + x0=x0, + xaxis=xaxis, + y0=y0, + yaxis=yaxis, + z=z, + zmax=zmax, + zmin=zmin, + zorder=zorder, + zsmooth=zsmooth, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_indicator( + self, + align=None, + customdata=None, + customdatasrc=None, + delta=None, + domain=None, + gauge=None, + ids=None, + idssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + meta=None, + metasrc=None, + mode=None, + name=None, + number=None, + stream=None, + title=None, + uid=None, + uirevision=None, + value=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Indicator trace + + An indicator is used to visualize a single `value` along with + some contextual information such as `steps` or a `threshold`, + using a combination of three visual elements: a number, a + delta, and/or a gauge. Deltas are taken with respect to a + `reference`. Gauges can be either angular or bullet (aka + linear) gauges. + + Parameters + ---------- + align + Sets the horizontal alignment of the `text` within the + box. Note that this attribute has no effect if an + angular gauge is displayed: in this case, it is always + centered + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + delta + :class:`plotly.graph_objects.indicator.Delta` instance + or dict with compatible properties + domain + :class:`plotly.graph_objects.indicator.Domain` instance + or dict with compatible properties + gauge + The gauge of the Indicator plot. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.indicator.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines how the value is displayed on the graph. + `number` displays the value numerically in text. + `delta` displays the difference to a reference value in + text. Finally, `gauge` displays the value graphically + on an axis. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + number + :class:`plotly.graph_objects.indicator.Number` instance + or dict with compatible properties + stream + :class:`plotly.graph_objects.indicator.Stream` instance + or dict with compatible properties + title + :class:`plotly.graph_objects.indicator.Title` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + value + Sets the number to be displayed. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Indicator + + new_trace = Indicator( + align=align, + customdata=customdata, + customdatasrc=customdatasrc, + delta=delta, + domain=domain, + gauge=gauge, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + number=number, + stream=stream, + title=title, + uid=uid, + uirevision=uirevision, + value=value, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_isosurface( + self, + autocolorscale=None, + caps=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + coloraxis=None, + colorbar=None, + colorscale=None, + contour=None, + customdata=None, + customdatasrc=None, + flatshading=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + isomax=None, + isomin=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + slices=None, + spaceframe=None, + stream=None, + surface=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + value=None, + valuehoverformat=None, + valuesrc=None, + visible=None, + x=None, + xhoverformat=None, + xsrc=None, + y=None, + yhoverformat=None, + ysrc=None, + z=None, + zhoverformat=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Isosurface trace + + Draws isosurfaces between iso-min and iso-max values with + coordinates given by four 1-dimensional arrays containing the + `value`, `x`, `y` and `z` of every vertex of a uniform or non- + uniform 3-D grid. Horizontal or vertical slices, caps as well + as spaceframe between iso-min and iso-max values could also be + drawn using this trace. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + caps + :class:`plotly.graph_objects.isosurface.Caps` instance + or dict with compatible properties + cauto + Determines whether or not the color domain is computed + with respect to the input data (here `value`) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as `value` and if set, `cmin` must + be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as `value`. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as `value` and if set, `cmax` must + be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.isosurface.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contour + :class:`plotly.graph_objects.isosurface.Contour` + instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + flatshading + Determines whether or not normal smoothing is applied + to the meshes, creating meshes with an angular, low- + poly look via flat reflections. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.isosurface.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + isomax + Sets the maximum boundary for iso-surface plot. + isomin + Sets the minimum boundary for iso-surface plot. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.isosurface.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.isosurface.Lighting` + instance or dict with compatible properties + lightposition + :class:`plotly.graph_objects.isosurface.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + slices + :class:`plotly.graph_objects.isosurface.Slices` + instance or dict with compatible properties + spaceframe + :class:`plotly.graph_objects.isosurface.Spaceframe` + instance or dict with compatible properties + stream + :class:`plotly.graph_objects.isosurface.Stream` + instance or dict with compatible properties + surface + :class:`plotly.graph_objects.isosurface.Surface` + instance or dict with compatible properties + text + Sets the text elements associated with the vertices. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + value + Sets the 4th dimension (value) of the vertices. + valuehoverformat + Sets the hover text formatting rulefor `value` using + d3 formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + valuesrc + Sets the source reference on Chart Studio Cloud for + `value`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the X coordinates of the vertices on X axis. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the Y coordinates of the vertices on Y axis. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the Z coordinates of the vertices on Z axis. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Isosurface + + new_trace = Isosurface( + autocolorscale=autocolorscale, + caps=caps, + cauto=cauto, + cmax=cmax, + cmid=cmid, + cmin=cmin, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + contour=contour, + customdata=customdata, + customdatasrc=customdatasrc, + flatshading=flatshading, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + isomax=isomax, + isomin=isomin, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lighting=lighting, + lightposition=lightposition, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + reversescale=reversescale, + scene=scene, + showlegend=showlegend, + showscale=showscale, + slices=slices, + spaceframe=spaceframe, + stream=stream, + surface=surface, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + value=value, + valuehoverformat=valuehoverformat, + valuesrc=valuesrc, + visible=visible, + x=x, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zhoverformat=zhoverformat, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_mesh3d( + self, + alphahull=None, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + color=None, + coloraxis=None, + colorbar=None, + colorscale=None, + contour=None, + customdata=None, + customdatasrc=None, + delaunayaxis=None, + facecolor=None, + facecolorsrc=None, + flatshading=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + i=None, + ids=None, + idssrc=None, + intensity=None, + intensitymode=None, + intensitysrc=None, + isrc=None, + j=None, + jsrc=None, + k=None, + ksrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + vertexcolor=None, + vertexcolorsrc=None, + visible=None, + x=None, + xcalendar=None, + xhoverformat=None, + xsrc=None, + y=None, + ycalendar=None, + yhoverformat=None, + ysrc=None, + z=None, + zcalendar=None, + zhoverformat=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Mesh3d trace + + Draws sets of triangles with coordinates given by three + 1-dimensional arrays in `x`, `y`, `z` and (1) a sets of `i`, + `j`, `k` indices (2) Delaunay triangulation or (3) the Alpha- + shape algorithm or (4) the Convex-hull algorithm + + Parameters + ---------- + alphahull + Determines how the mesh surface triangles are derived + from the set of vertices (points) represented by the + `x`, `y` and `z` arrays, if the `i`, `j`, `k` arrays + are not supplied. For general use of `mesh3d` it is + preferred that `i`, `j`, `k` are supplied. If "-1", + Delaunay triangulation is used, which is mainly + suitable if the mesh is a single, more or less layer + surface that is perpendicular to `delaunayaxis`. In + case the `delaunayaxis` intersects the mesh surface at + more than one point it will result triangles that are + very long in the dimension of `delaunayaxis`. If ">0", + the alpha-shape algorithm is used. In this case, the + positive `alphahull` value signals the use of the + alpha-shape algorithm, _and_ its value acts as the + parameter for the mesh fitting. If 0, the convex-hull + algorithm is used. It is suitable for convex bodies or + if the intention is to enclose the `x`, `y` and `z` + point set into a convex hull. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here `intensity`) or + the bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as `intensity` and if set, `cmin` + must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as `intensity`. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as `intensity` and if set, `cmax` + must be set as well. + color + Sets the color of the whole mesh + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.mesh3d.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contour + :class:`plotly.graph_objects.mesh3d.Contour` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + delaunayaxis + Sets the Delaunay axis, which is the axis that is + perpendicular to the surface of the Delaunay + triangulation. It has an effect if `i`, `j`, `k` are + not provided and `alphahull` is set to indicate + Delaunay triangulation. + facecolor + Sets the color of each face Overrides "color" and + "vertexcolor". + facecolorsrc + Sets the source reference on Chart Studio Cloud for + `facecolor`. + flatshading + Determines whether or not normal smoothing is applied + to the meshes, creating meshes with an angular, low- + poly look via flat reflections. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.mesh3d.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + i + A vector of vertex indices, i.e. integer values between + 0 and the length of the vertex vectors, representing + the "first" vertex of a triangle. For example, `{i[m], + j[m], k[m]}` together represent face m (triangle m) in + the mesh, where `i[m] = n` points to the triplet + `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, + each element in `i` represents a point in space, which + is the first vertex of a triangle. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + intensity + Sets the intensity values for vertices or cells as + defined by `intensitymode`. It can be used for plotting + fields on meshes. + intensitymode + Determines the source of `intensity` values. + intensitysrc + Sets the source reference on Chart Studio Cloud for + `intensity`. + isrc + Sets the source reference on Chart Studio Cloud for + `i`. + j + A vector of vertex indices, i.e. integer values between + 0 and the length of the vertex vectors, representing + the "second" vertex of a triangle. For example, `{i[m], + j[m], k[m]}` together represent face m (triangle m) in + the mesh, where `j[m] = n` points to the triplet + `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, + each element in `j` represents a point in space, which + is the second vertex of a triangle. + jsrc + Sets the source reference on Chart Studio Cloud for + `j`. + k + A vector of vertex indices, i.e. integer values between + 0 and the length of the vertex vectors, representing + the "third" vertex of a triangle. For example, `{i[m], + j[m], k[m]}` together represent face m (triangle m) in + the mesh, where `k[m] = n` points to the triplet + `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, + each element in `k` represents a point in space, which + is the third vertex of a triangle. + ksrc + Sets the source reference on Chart Studio Cloud for + `k`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.mesh3d.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.mesh3d.Lighting` instance + or dict with compatible properties + lightposition + :class:`plotly.graph_objects.mesh3d.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.mesh3d.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with the vertices. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + vertexcolor + Sets the color of each vertex Overrides "color". While + Red, green and blue colors are in the range of 0 and + 255; in the case of having vertex color data in RGBA + format, the alpha color should be normalized to be + between 0 and 1. + vertexcolorsrc + Sets the source reference on Chart Studio Cloud for + `vertexcolor`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the X coordinates of the vertices. The nth element + of vectors `x`, `y` and `z` jointly represent the X, Y + and Z coordinates of the nth vertex. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the Y coordinates of the vertices. The nth element + of vectors `x`, `y` and `z` jointly represent the X, Y + and Z coordinates of the nth vertex. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the Z coordinates of the vertices. The nth element + of vectors `x`, `y` and `z` jointly represent the X, Y + and Z coordinates of the nth vertex. + zcalendar + Sets the calendar system to use with `z` date data. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Mesh3d + + new_trace = Mesh3d( + alphahull=alphahull, + autocolorscale=autocolorscale, + cauto=cauto, + cmax=cmax, + cmid=cmid, + cmin=cmin, + color=color, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + contour=contour, + customdata=customdata, + customdatasrc=customdatasrc, + delaunayaxis=delaunayaxis, + facecolor=facecolor, + facecolorsrc=facecolorsrc, + flatshading=flatshading, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + i=i, + ids=ids, + idssrc=idssrc, + intensity=intensity, + intensitymode=intensitymode, + intensitysrc=intensitysrc, + isrc=isrc, + j=j, + jsrc=jsrc, + k=k, + ksrc=ksrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lighting=lighting, + lightposition=lightposition, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + reversescale=reversescale, + scene=scene, + showlegend=showlegend, + showscale=showscale, + stream=stream, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + vertexcolor=vertexcolor, + vertexcolorsrc=vertexcolorsrc, + visible=visible, + x=x, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zcalendar=zcalendar, + zhoverformat=zhoverformat, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_ohlc( + self, + close=None, + closesrc=None, + customdata=None, + customdatasrc=None, + decreasing=None, + high=None, + highsrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + increasing=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + low=None, + lowsrc=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + open=None, + opensrc=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textsrc=None, + tickwidth=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + yaxis=None, + yhoverformat=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Ohlc trace + + The ohlc (short for Open-High-Low-Close) is a style of + financial chart describing open, high, low and close for a + given `x` coordinate (most likely time). The tip of the lines + represent the `low` and `high` values and the horizontal + segments represent the `open` and `close` values. Sample points + where the close value is higher (lower) then the open value are + called increasing (decreasing). By default, increasing items + are drawn in green whereas decreasing are drawn in red. + + Parameters + ---------- + close + Sets the close values. + closesrc + Sets the source reference on Chart Studio Cloud for + `close`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + decreasing + :class:`plotly.graph_objects.ohlc.Decreasing` instance + or dict with compatible properties + high + Sets the high values. + highsrc + Sets the source reference on Chart Studio Cloud for + `high`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.ohlc.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `open`, `high`, `low` and `close`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + increasing + :class:`plotly.graph_objects.ohlc.Increasing` instance + or dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.ohlc.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.ohlc.Line` instance or + dict with compatible properties + low + Sets the low values. + lowsrc + Sets the source reference on Chart Studio Cloud for + `low`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + open + Sets the open values. + opensrc + Sets the source reference on Chart Studio Cloud for + `open`. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.ohlc.Stream` instance or + dict with compatible properties + text + Sets hover text elements associated with each sample + point. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to this trace's sample points. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + tickwidth + Sets the width of the open/close tick marks relative to + the "x" minimal interval. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. If absent, linear coordinate + will be generated. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Ohlc + + new_trace = Ohlc( + close=close, + closesrc=closesrc, + customdata=customdata, + customdatasrc=customdatasrc, + decreasing=decreasing, + high=high, + highsrc=highsrc, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + increasing=increasing, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + low=low, + lowsrc=lowsrc, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + open=open, + opensrc=opensrc, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textsrc=textsrc, + tickwidth=tickwidth, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + xaxis=xaxis, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + yaxis=yaxis, + yhoverformat=yhoverformat, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_parcats( + self, + arrangement=None, + bundlecolors=None, + counts=None, + countssrc=None, + dimensions=None, + dimensiondefaults=None, + domain=None, + hoverinfo=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + labelfont=None, + legendgrouptitle=None, + legendwidth=None, + line=None, + meta=None, + metasrc=None, + name=None, + sortpaths=None, + stream=None, + tickfont=None, + uid=None, + uirevision=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Parcats trace + + Parallel categories diagram for multidimensional categorical + data. + + Parameters + ---------- + arrangement + Sets the drag interaction mode for categories and + dimensions. If `perpendicular`, the categories can only + move along a line perpendicular to the paths. If + `freeform`, the categories can freely move on the + plane. If `fixed`, the categories and dimensions are + stationary. + bundlecolors + Sort paths so that like colors are bundled together + within each category. + counts + The number of observations represented by each state. + Defaults to 1 so that each state represents one + observation + countssrc + Sets the source reference on Chart Studio Cloud for + `counts`. + dimensions + The dimensions (variables) of the parallel categories + diagram. + dimensiondefaults + When used in a template (as + layout.template.data.parcats.dimensiondefaults), sets + the default property values to use for elements of + parcats.dimensions + domain + :class:`plotly.graph_objects.parcats.Domain` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoveron + Sets the hover interaction mode for the parcats + diagram. If `category`, hover interaction take place + per category. If `color`, hover interactions take place + per color per category. If `dimension`, hover + interactions take place across all categories per + dimension. + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `count`, `probability`, `category`, + `categorycount`, `colorcount` and `bandcolorcount`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + labelfont + Sets the font for the `dimension` labels. + legendgrouptitle + :class:`plotly.graph_objects.parcats.Legendgrouptitle` + instance or dict with compatible properties + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.parcats.Line` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + sortpaths + Sets the path sorting algorithm. If `forward`, sort + paths based on dimension categories from left to right. + If `backward`, sort paths based on dimensions + categories from right to left. + stream + :class:`plotly.graph_objects.parcats.Stream` instance + or dict with compatible properties + tickfont + Sets the font for the `category` labels. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Parcats + + new_trace = Parcats( + arrangement=arrangement, + bundlecolors=bundlecolors, + counts=counts, + countssrc=countssrc, + dimensions=dimensions, + dimensiondefaults=dimensiondefaults, + domain=domain, + hoverinfo=hoverinfo, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + labelfont=labelfont, + legendgrouptitle=legendgrouptitle, + legendwidth=legendwidth, + line=line, + meta=meta, + metasrc=metasrc, + name=name, + sortpaths=sortpaths, + stream=stream, + tickfont=tickfont, + uid=uid, + uirevision=uirevision, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_parcoords( + self, + customdata=None, + customdatasrc=None, + dimensions=None, + dimensiondefaults=None, + domain=None, + ids=None, + idssrc=None, + labelangle=None, + labelfont=None, + labelside=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + meta=None, + metasrc=None, + name=None, + rangefont=None, + stream=None, + tickfont=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Parcoords trace + + Parallel coordinates for multidimensional exploratory data + analysis. The samples are specified in `dimensions`. The colors + are set in `line.color`. + + Parameters + ---------- + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dimensions + The dimensions (variables) of the parallel coordinates + chart. 2..60 dimensions are supported. + dimensiondefaults + When used in a template (as + layout.template.data.parcoords.dimensiondefaults), sets + the default property values to use for elements of + parcoords.dimensions + domain + :class:`plotly.graph_objects.parcoords.Domain` instance + or dict with compatible properties + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + labelangle + Sets the angle of the labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + labels vertically. Tilted labels with "labelangle" may + be positioned better inside margins when + `labelposition` is set to "bottom". + labelfont + Sets the font for the `dimension` labels. + labelside + Specifies the location of the `label`. "top" positions + labels above, next to the title "bottom" positions + labels below the graph Tilted labels with "labelangle" + may be positioned better inside margins when + `labelposition` is set to "bottom". + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.parcoords.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.parcoords.Line` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + rangefont + Sets the font for the `dimension` range values. + stream + :class:`plotly.graph_objects.parcoords.Stream` instance + or dict with compatible properties + tickfont + Sets the font for the `dimension` tick values. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.parcoords.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Parcoords + + new_trace = Parcoords( + customdata=customdata, + customdatasrc=customdatasrc, + dimensions=dimensions, + dimensiondefaults=dimensiondefaults, + domain=domain, + ids=ids, + idssrc=idssrc, + labelangle=labelangle, + labelfont=labelfont, + labelside=labelside, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + meta=meta, + metasrc=metasrc, + name=name, + rangefont=rangefont, + stream=stream, + tickfont=tickfont, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_pie( + self, + automargin=None, + customdata=None, + customdatasrc=None, + direction=None, + dlabel=None, + domain=None, + hole=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextfont=None, + insidetextorientation=None, + label0=None, + labels=None, + labelssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendsrc=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + outsidetextfont=None, + pull=None, + pullsrc=None, + rotation=None, + scalegroup=None, + showlegend=None, + showlegendsrc=None, + sort=None, + stream=None, + text=None, + textfont=None, + textinfo=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + title=None, + uid=None, + uirevision=None, + values=None, + valuessrc=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Pie trace + + A data visualized by the sectors of the pie is set in `values`. + The sector labels are set in `labels`. The sector colors are + set in `marker.colors` + + Parameters + ---------- + automargin + Determines whether outside text labels can push the + margins. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + direction + Specifies the direction at which succeeding sectors + follow one another. + dlabel + Sets the label step. See `label0` for more info. + domain + :class:`plotly.graph_objects.pie.Domain` instance or + dict with compatible properties + hole + Sets the fraction of the radius to cut out of the pie. + Use this to make a donut chart. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.pie.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `percent` and + `text`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + insidetextorientation + Controls the orientation of the text inside chart + sectors. When set to "auto", text may be oriented in + any direction in order to be as big as possible in the + middle of a sector. The "horizontal" option orients + text to be parallel with the bottom of the chart, and + may make text smaller in order to achieve that goal. + The "radial" option orients text along the radius of + the sector. The "tangential" option orients text + perpendicular to the radius of the sector. + label0 + Alternate to `labels`. Builds a numeric set of labels. + Use with `dlabel` where `label0` is the starting label + and `dlabel` the step. + labels + Sets the sector labels. If `labels` entries are + duplicated, we sum associated `values` or simply count + occurrences if `values` is not provided. For other + array attributes (including color) we use the first + non-empty entry among all occurrences of the label. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + legend + Sets the reference to a legend to show the pie slices + in. Can be an array if `values` is set. In that case, + each entry specifies the legend reference for one + slice. References to these legends are "legend", + "legend2", "legend3", etc. Settings for these legends + are set in the layout, under `layout.legend`, + `layout.legend2`, etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.pie.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendsrc + Sets the source reference on Chart Studio Cloud for + `legend`. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.pie.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. + pull + Sets the fraction of larger radius to pull the sectors + out from the center. This can be a constant to pull all + slices apart from each other equally or an array to + highlight one or more slices. + pullsrc + Sets the source reference on Chart Studio Cloud for + `pull`. + rotation + Instead of the first slice starting at 12 o'clock, + rotate to some other angle. + scalegroup + If there are multiple pie charts that should be sized + according to their totals, link them by providing a + non-empty group id here shared by every trace in the + same group. + showlegend + Determines whether or not items corresponding to the + pie slices are shown in the legend. Can be an array if + `values` is set. In that case, each entry specifies + appearance in the legend for one slice. + showlegendsrc + Sets the source reference on Chart Studio Cloud for + `showlegend`. + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.pie.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Specifies the location of the `textinfo`. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `percent` and + `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + title + :class:`plotly.graph_objects.pie.Title` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values of the sectors. If omitted, we count + occurrences of each label. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Pie + + new_trace = Pie( + automargin=automargin, + customdata=customdata, + customdatasrc=customdatasrc, + direction=direction, + dlabel=dlabel, + domain=domain, + hole=hole, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextfont=insidetextfont, + insidetextorientation=insidetextorientation, + label0=label0, + labels=labels, + labelssrc=labelssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendsrc=legendsrc, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + outsidetextfont=outsidetextfont, + pull=pull, + pullsrc=pullsrc, + rotation=rotation, + scalegroup=scalegroup, + showlegend=showlegend, + showlegendsrc=showlegendsrc, + sort=sort, + stream=stream, + text=text, + textfont=textfont, + textinfo=textinfo, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + title=title, + uid=uid, + uirevision=uirevision, + values=values, + valuessrc=valuessrc, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_sankey( + self, + arrangement=None, + customdata=None, + customdatasrc=None, + domain=None, + hoverinfo=None, + hoverlabel=None, + ids=None, + idssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + link=None, + meta=None, + metasrc=None, + name=None, + node=None, + orientation=None, + selectedpoints=None, + stream=None, + textfont=None, + uid=None, + uirevision=None, + valueformat=None, + valuesuffix=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Sankey trace + + Sankey plots for network flow data analysis. The nodes are + specified in `nodes` and the links between sources and targets + in `links`. The colors are set in `nodes[i].color` and + `links[i].color`, otherwise defaults are used. + + Parameters + ---------- + arrangement + If value is `snap` (the default), the node arrangement + is assisted by automatic snapping of elements to + preserve space between nodes specified via `nodepad`. + If value is `perpendicular`, the nodes can only move + along a line perpendicular to the flow. If value is + `freeform`, the nodes can freely move on the plane. If + value is `fixed`, the nodes are stationary. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.sankey.Domain` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. Note that this attribute is + superseded by `node.hoverinfo` and `node.hoverinfo` for + nodes and links respectively. + hoverlabel + :class:`plotly.graph_objects.sankey.Hoverlabel` + instance or dict with compatible properties + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.sankey.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + link + The links of the Sankey plot. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + node + The nodes of the Sankey plot. + orientation + Sets the orientation of the Sankey diagram. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + stream + :class:`plotly.graph_objects.sankey.Stream` instance or + dict with compatible properties + textfont + Sets the font for node labels + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + valueformat + Sets the value formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + valuesuffix + Adds a unit to follow the value in the hover tooltip. + Add a space if a separation is necessary from the + value. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Sankey + + new_trace = Sankey( + arrangement=arrangement, + customdata=customdata, + customdatasrc=customdatasrc, + domain=domain, + hoverinfo=hoverinfo, + hoverlabel=hoverlabel, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + link=link, + meta=meta, + metasrc=metasrc, + name=name, + node=node, + orientation=orientation, + selectedpoints=selectedpoints, + stream=stream, + textfont=textfont, + uid=uid, + uirevision=uirevision, + valueformat=valueformat, + valuesuffix=valuesuffix, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scatter( + self, + alignmentgroup=None, + cliponaxis=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + error_x=None, + error_y=None, + fill=None, + fillcolor=None, + fillgradient=None, + fillpattern=None, + groupnorm=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + offsetgroup=None, + opacity=None, + orientation=None, + selected=None, + selectedpoints=None, + showlegend=None, + stackgaps=None, + stackgroup=None, + stream=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Scatter trace + + The scatter trace type encompasses line charts, scatter charts, + text charts, and bubble charts. The data visualized as scatter + point or lines is set in `x` and `y`. Text (appearing either on + the chart or on hover only) is via `text`. Bubble charts are + achieved by setting `marker.size` and/or `marker.color` to + numerical arrays. + + Parameters + ---------- + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + error_x + :class:`plotly.graph_objects.scatter.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.scatter.ErrorY` instance + or dict with compatible properties + fill + Sets the area to fill with a solid color. Defaults to + "none" unless this trace is stacked, then it gets + "tonexty" ("tonextx") if `orientation` is "v" ("h") Use + with `fillcolor` if not "none". "tozerox" and "tozeroy" + fill to x=0 and y=0 respectively. "tonextx" and + "tonexty" fill between the endpoints of this trace and + the endpoints of the trace before it, connecting those + endpoints with straight lines (to make a stacked area + graph); if there is no trace before it, they behave + like "tozerox" and "tozeroy". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. Traces in a `stackgroup` will only fill to (or + be filled to) other traces in the same group. With + multiple `stackgroup`s or some traces stacked and some + not, if fill-linked traces are not already consecutive, + the later ones will be pushed down in the drawing + order. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. If fillgradient is + specified, fillcolor is ignored except for setting the + background color of the hover label, if any. + fillgradient + Sets a fill gradient. If not specified, the fillcolor + is used instead. + fillpattern + Sets the pattern within the marker. + groupnorm + Only relevant when `stackgroup` is used, and only the + first `groupnorm` found in the `stackgroup` will be + used - including if `visible` is "legendonly" but not + if it is `false`. Sets the normalization for the sum of + this `stackgroup`. With "fraction", the value of each + trace at each location is divided by the sum of all + trace values at that location. "percent" is the same + but multiplied by 100 to show percentages. If there are + multiple subplots, or multiple `stackgroup`s on one + subplot, each will be normalized within its own set. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatter.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatter.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatter.Line` instance or + dict with compatible properties + marker + :class:`plotly.graph_objects.scatter.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Only relevant in the following cases: 1. when + `scattermode` is set to "group". 2. when `stackgroup` + is used, and only the first `orientation` found in the + `stackgroup` will be used - including if `visible` is + "legendonly" but not if it is `false`. Sets the + stacking direction. With "v" ("h"), the y (x) values of + subsequent traces are added. Also affects the default + value of `fill`. + selected + :class:`plotly.graph_objects.scatter.Selected` instance + or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stackgaps + Only relevant when `stackgroup` is used, and only the + first `stackgaps` found in the `stackgroup` will be + used - including if `visible` is "legendonly" but not + if it is `false`. Determines how we handle locations at + which other traces in this group have data but this one + does not. With *infer zero* we insert a zero at these + locations. With "interpolate" we linearly interpolate + between existing values, and extrapolate a constant + beyond the existing values. + stackgroup + Set several scatter traces (on the same subplot) to the + same stackgroup in order to add their y values (or + their x values if `orientation` is "h"). If blank or + omitted this trace will not be stacked. Stacking also + turns `fill` on by default, using "tonexty" ("tonextx") + if `orientation` is "h" ("v") and sets the default + `mode` to "lines" irrespective of point count. You can + only stack on a numeric (linear or log) axis. Traces in + a `stackgroup` will only fill to (or be filled to) + other traces in the same group. With multiple + `stackgroup`s or some traces stacked and some not, if + fill-linked traces are not already consecutive, the + later ones will be pushed down in the drawing order. + stream + :class:`plotly.graph_objects.scatter.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatter.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Scatter + + new_trace = Scatter( + alignmentgroup=alignmentgroup, + cliponaxis=cliponaxis, + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + error_x=error_x, + error_y=error_y, + fill=fill, + fillcolor=fillcolor, + fillgradient=fillgradient, + fillpattern=fillpattern, + groupnorm=groupnorm, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + offsetgroup=offsetgroup, + opacity=opacity, + orientation=orientation, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stackgaps=stackgaps, + stackgroup=stackgroup, + stream=stream, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + x=x, + x0=x0, + xaxis=xaxis, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + y=y, + y0=y0, + yaxis=yaxis, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_scatter3d( + self, + connectgaps=None, + customdata=None, + customdatasrc=None, + error_x=None, + error_y=None, + error_z=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + projection=None, + scene=None, + showlegend=None, + stream=None, + surfaceaxis=None, + surfacecolor=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xcalendar=None, + xhoverformat=None, + xsrc=None, + y=None, + ycalendar=None, + yhoverformat=None, + ysrc=None, + z=None, + zcalendar=None, + zhoverformat=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Scatter3d trace + + The data visualized as scatter point or lines in 3D dimension + is set in `x`, `y`, `z`. Text (appearing either on the chart or + on hover only) is via `text`. Bubble charts are achieved by + setting `marker.size` and/or `marker.color` Projections are + achieved via `projection`. Surface fills are achieved via + `surfaceaxis`. + + Parameters + ---------- + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + error_x + :class:`plotly.graph_objects.scatter3d.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.scatter3d.ErrorY` instance + or dict with compatible properties + error_z + :class:`plotly.graph_objects.scatter3d.ErrorZ` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatter3d.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets text elements associated with each (x,y,z) + triplet. If a single string, the same string appears + over all the data points. If an array of string, the + items are mapped in order to the this trace's (x,y,z) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatter3d.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatter3d.Line` instance + or dict with compatible properties + marker + :class:`plotly.graph_objects.scatter3d.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + projection + :class:`plotly.graph_objects.scatter3d.Projection` + instance or dict with compatible properties + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatter3d.Stream` instance + or dict with compatible properties + surfaceaxis + If "-1", the scatter points are not fill with a surface + If 0, 1, 2, the scatter points are filled with a + Delaunay surface about the x, y, z respectively. + surfacecolor + Sets the surface fill color. + text + Sets text elements associated with each (x,y,z) + triplet. If a single string, the same string appears + over all the data points. If an array of string, the + items are mapped in order to the this trace's (x,y,z) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates. + zcalendar + Sets the calendar system to use with `z` date data. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Scatter3d + + new_trace = Scatter3d( + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + error_x=error_x, + error_y=error_y, + error_z=error_z, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + projection=projection, + scene=scene, + showlegend=showlegend, + stream=stream, + surfaceaxis=surfaceaxis, + surfacecolor=surfacecolor, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zcalendar=zcalendar, + zhoverformat=zhoverformat, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scattercarpet( + self, + a=None, + asrc=None, + b=None, + bsrc=None, + carpet=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + xaxis=None, + yaxis=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Scattercarpet trace + + Plots a scatter trace on either the first carpet axis or the + carpet axis with a matching `carpet` attribute. + + Parameters + ---------- + a + Sets the a-axis coordinates. + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + b + Sets the b-axis coordinates. + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + carpet + An identifier for this carpet, so that `scattercarpet` + and `contourcarpet` traces can specify a carpet plot on + which they lie + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scatterternary has a subset + of the options available to scatter. "toself" connects + the endpoints of the trace (or each segment of the + trace if it has gaps) into a closed shape. "tonext" + fills the space between two traces if one completely + encloses the other (eg consecutive contour lines), and + behaves like "toself" if there is no trace before it. + "tonext" should not be used if one trace does not + enclose the other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattercarpet.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (a,b) + point. If a single string, the same string appears over + all the data points. If an array of strings, the items + are mapped in order to the the data points in (a,b). To + be seen, trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattercarpet.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattercarpet.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scattercarpet.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattercarpet.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattercarpet.Stream` + instance or dict with compatible properties + text + Sets text elements associated with each (a,b) point. If + a single string, the same string appears over all the + data points. If an array of strings, the items are + mapped in order to the the data points in (a,b). If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `a`, `b` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattercarpet.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Scattercarpet + + new_trace = Scattercarpet( + a=a, + asrc=asrc, + b=b, + bsrc=bsrc, + carpet=carpet, + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + xaxis=xaxis, + yaxis=yaxis, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_scattergeo( + self, + connectgaps=None, + customdata=None, + customdatasrc=None, + featureidkey=None, + fill=None, + fillcolor=None, + geo=None, + geojson=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + lat=None, + latsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + locationmode=None, + locations=None, + locationssrc=None, + lon=None, + lonsrc=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Scattergeo trace + + The data visualized as scatter point or lines on a geographic + map is provided either by longitude/latitude pairs in `lon` and + `lat` respectively or by geographic location IDs or names in + `locations`. + + Parameters + ---------- + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. Only + has an effect when `geojson` is set. Support nested + property, for example "properties.name". + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + geo + Sets a reference between this trace's geospatial + coordinates and a geographic map. If "geo" (the default + value), the geospatial coordinates refer to + `layout.geo`. If "geo2", the geospatial coordinates + refer to `layout.geo2`, and so on. + geojson + Sets optional GeoJSON data associated with this trace. + If not given, the features on the base map are used + when `locations` is set. It can be set as a valid + GeoJSON object or as a URL string. Note that we only + accept GeoJSONs of type "FeatureCollection" or + "Feature" with geometries of type "Polygon" or + "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattergeo.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair or item in `locations`. If a single string, the + same string appears over all the data points. If an + array of string, the items are mapped in order to the + this trace's (lon,lat) or `locations` coordinates. To + be seen, trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattergeo.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattergeo.Line` instance + or dict with compatible properties + locationmode + The library used by the *country names* `locationmode` + option is changing in an upcoming version. Country + names in existing plots may not work in the new + version. Determines the set of locations used to match + entries in `locations` to regions on the map. Values + "ISO-3", "USA-states", *country names* correspond to + features on the base map and value "geojson-id" + corresponds to features from a custom GeoJSON linked to + the `geojson` attribute. + locations + Sets the coordinates via location IDs or names. + Coordinates correspond to the centroid of each location + given. See `locationmode` for more info. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + marker + :class:`plotly.graph_objects.scattergeo.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattergeo.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattergeo.Stream` + instance or dict with compatible properties + text + Sets text elements associated with each (lon,lat) pair + or item in `locations`. If a single string, the same + string appears over all the data points. If an array of + string, the items are mapped in order to the this + trace's (lon,lat) or `locations` coordinates. If trace + `hoverinfo` contains a "text" flag and "hovertext" is + not set, these elements will be seen in the hover + labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `lat`, `lon`, `location` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattergeo.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Scattergeo + + new_trace = Scattergeo( + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + featureidkey=featureidkey, + fill=fill, + fillcolor=fillcolor, + geo=geo, + geojson=geojson, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + lat=lat, + latsrc=latsrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + locationmode=locationmode, + locations=locations, + locationssrc=locationssrc, + lon=lon, + lonsrc=lonsrc, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scattergl( + self, + connectgaps=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + error_x=None, + error_y=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Scattergl trace + + The data visualized as scatter point or lines is set in `x` and + `y` using the WebGL plotting engine. Bubble charts are achieved + by setting `marker.size` and/or `marker.color` to a numerical + arrays. + + Parameters + ---------- + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + error_x + :class:`plotly.graph_objects.scattergl.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.scattergl.ErrorY` instance + or dict with compatible properties + fill + Sets the area to fill with a solid color. Defaults to + "none" unless this trace is stacked, then it gets + "tonexty" ("tonextx") if `orientation` is "v" ("h") Use + with `fillcolor` if not "none". "tozerox" and "tozeroy" + fill to x=0 and y=0 respectively. "tonextx" and + "tonexty" fill between the endpoints of this trace and + the endpoints of the trace before it, connecting those + endpoints with straight lines (to make a stacked area + graph); if there is no trace before it, they behave + like "tozerox" and "tozeroy". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. Traces in a `stackgroup` will only fill to (or + be filled to) other traces in the same group. With + multiple `stackgroup`s or some traces stacked and some + not, if fill-linked traces are not already consecutive, + the later ones will be pushed down in the drawing + order. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattergl.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattergl.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattergl.Line` instance + or dict with compatible properties + marker + :class:`plotly.graph_objects.scattergl.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattergl.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattergl.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattergl.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Scattergl + + new_trace = Scattergl( + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + dx=dx, + dy=dy, + error_x=error_x, + error_y=error_y, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + x=x, + x0=x0, + xaxis=xaxis, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + y=y, + y0=y0, + yaxis=yaxis, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_scattermap( + self, + below=None, + cluster=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + lat=None, + latsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + lon=None, + lonsrc=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textfont=None, + textposition=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Scattermap trace + + The data visualized as scatter point, lines or marker symbols + on a MapLibre GL geographic map is provided by + longitude/latitude pairs in `lon` and `lat`. + + Parameters + ---------- + below + Determines if this scattermap trace's layers are to be + inserted before the layer with the specified ID. By + default, scattermap layers are inserted above all the + base layers. To place the scattermap layers above every + other layer, set `below` to "''". + cluster + :class:`plotly.graph_objects.scattermap.Cluster` + instance or dict with compatible properties + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattermap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattermap.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattermap.Line` instance + or dict with compatible properties + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + marker + :class:`plotly.graph_objects.scattermap.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattermap.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattermap.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a map subplot. If "map" (the default value), the + data refer to `layout.map`. If "map2", the data refer + to `layout.map2`, and so on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textfont + Sets the icon text font (color=map.layer.paint.text- + color, size=map.layer.layout.text-size). Has an effect + only when `type` is set to "symbol". + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `lat`, `lon` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattermap.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Scattermap + + new_trace = Scattermap( + below=below, + cluster=cluster, + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + lat=lat, + latsrc=latsrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + lon=lon, + lonsrc=lonsrc, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + subplot=subplot, + text=text, + textfont=textfont, + textposition=textposition, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scattermapbox( + self, + below=None, + cluster=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + lat=None, + latsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + lon=None, + lonsrc=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textfont=None, + textposition=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Scattermapbox trace + + "scattermapbox" trace is deprecated! Please consider switching + to the "scattermap" trace type and `map` subplots. Learn more + at: https://plotly.com/python/maplibre-migration/ as well as + https://plotly.com/javascript/maplibre-migration/ The data + visualized as scatter point, lines or marker symbols on a + Mapbox GL geographic map is provided by longitude/latitude + pairs in `lon` and `lat`. + + Parameters + ---------- + below + Determines if this scattermapbox trace's layers are to + be inserted before the layer with the specified ID. By + default, scattermapbox layers are inserted above all + the base layers. To place the scattermapbox layers + above every other layer, set `below` to "''". + cluster + :class:`plotly.graph_objects.scattermapbox.Cluster` + instance or dict with compatible properties + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattermapbox.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattermapbox.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattermapbox.Line` + instance or dict with compatible properties + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + marker + :class:`plotly.graph_objects.scattermapbox.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattermapbox.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattermapbox.Stream` + instance or dict with compatible properties + subplot + mapbox subplots and traces are deprecated! Please + consider switching to `map` subplots and traces. Learn + more at: https://plotly.com/python/maplibre-migration/ + as well as https://plotly.com/javascript/maplibre- + migration/ Sets a reference between this trace's data + coordinates and a mapbox subplot. If "mapbox" (the + default value), the data refer to `layout.mapbox`. If + "mapbox2", the data refer to `layout.mapbox2`, and so + on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textfont + Sets the icon text font (color=mapbox.layer.paint.text- + color, size=mapbox.layer.layout.text-size). Has an + effect only when `type` is set to "symbol". + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `lat`, `lon` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattermapbox.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Scattermapbox + + new_trace = Scattermapbox( + below=below, + cluster=cluster, + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + lat=lat, + latsrc=latsrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + lon=lon, + lonsrc=lonsrc, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + subplot=subplot, + text=text, + textfont=textfont, + textposition=textposition, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scatterpolar( + self, + cliponaxis=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + dr=None, + dtheta=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + r=None, + r0=None, + rsrc=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + theta=None, + theta0=None, + thetasrc=None, + thetaunit=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Scatterpolar trace + + The scatterpolar trace type encompasses line charts, scatter + charts, text charts, and bubble charts in polar coordinates. + The data visualized as scatter point or lines is set in `r` + (radial) and `theta` (angular) coordinates Text (appearing + either on the chart or on hover only) is via `text`. Bubble + charts are achieved by setting `marker.size` and/or + `marker.color` to numerical arrays. + + Parameters + ---------- + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dr + Sets the r coordinate step. + dtheta + Sets the theta coordinate step. By default, the + `dtheta` step equals the subplot's period divided by + the length of the `r` coordinates. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scatterpolar has a subset of + the options available to scatter. "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatterpolar.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatterpolar.Legendgroupti + tle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatterpolar.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scatterpolar.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + r + Sets the radial coordinates + r0 + Alternate to `r`. Builds a linear space of r + coordinates. Use with `dr` where `r0` is the starting + coordinate and `dr` the step. + rsrc + Sets the source reference on Chart Studio Cloud for + `r`. + selected + :class:`plotly.graph_objects.scatterpolar.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatterpolar.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a polar subplot. If "polar" (the default value), + the data refer to `layout.polar`. If "polar2", the data + refer to `layout.polar2`, and so on. + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `r`, `theta` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + theta + Sets the angular coordinates + theta0 + Alternate to `theta`. Builds a linear space of theta + coordinates. Use with `dtheta` where `theta0` is the + starting coordinate and `dtheta` the step. + thetasrc + Sets the source reference on Chart Studio Cloud for + `theta`. + thetaunit + Sets the unit of input "theta" values. Has an effect + only when on "linear" angular axes. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatterpolar.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Scatterpolar + + new_trace = Scatterpolar( + cliponaxis=cliponaxis, + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + dr=dr, + dtheta=dtheta, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + r=r, + r0=r0, + rsrc=rsrc, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + subplot=subplot, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + theta=theta, + theta0=theta0, + thetasrc=thetasrc, + thetaunit=thetaunit, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scatterpolargl( + self, + connectgaps=None, + customdata=None, + customdatasrc=None, + dr=None, + dtheta=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + r=None, + r0=None, + rsrc=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + theta=None, + theta0=None, + thetasrc=None, + thetaunit=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Scatterpolargl trace + + The scatterpolargl trace type encompasses line charts, scatter + charts, and bubble charts in polar coordinates using the WebGL + plotting engine. The data visualized as scatter point or lines + is set in `r` (radial) and `theta` (angular) coordinates Bubble + charts are achieved by setting `marker.size` and/or + `marker.color` to numerical arrays. + + Parameters + ---------- + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dr + Sets the r coordinate step. + dtheta + Sets the theta coordinate step. By default, the + `dtheta` step equals the subplot's period divided by + the length of the `r` coordinates. + fill + Sets the area to fill with a solid color. Defaults to + "none" unless this trace is stacked, then it gets + "tonexty" ("tonextx") if `orientation` is "v" ("h") Use + with `fillcolor` if not "none". "tozerox" and "tozeroy" + fill to x=0 and y=0 respectively. "tonextx" and + "tonexty" fill between the endpoints of this trace and + the endpoints of the trace before it, connecting those + endpoints with straight lines (to make a stacked area + graph); if there is no trace before it, they behave + like "tozerox" and "tozeroy". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. Traces in a `stackgroup` will only fill to (or + be filled to) other traces in the same group. With + multiple `stackgroup`s or some traces stacked and some + not, if fill-linked traces are not already consecutive, + the later ones will be pushed down in the drawing + order. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatterpolargl.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatterpolargl.Legendgroup + title` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatterpolargl.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scatterpolargl.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + r + Sets the radial coordinates + r0 + Alternate to `r`. Builds a linear space of r + coordinates. Use with `dr` where `r0` is the starting + coordinate and `dr` the step. + rsrc + Sets the source reference on Chart Studio Cloud for + `r`. + selected + :class:`plotly.graph_objects.scatterpolargl.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatterpolargl.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a polar subplot. If "polar" (the default value), + the data refer to `layout.polar`. If "polar2", the data + refer to `layout.polar2`, and so on. + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `r`, `theta` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + theta + Sets the angular coordinates + theta0 + Alternate to `theta`. Builds a linear space of theta + coordinates. Use with `dtheta` where `theta0` is the + starting coordinate and `dtheta` the step. + thetasrc + Sets the source reference on Chart Studio Cloud for + `theta`. + thetaunit + Sets the unit of input "theta" values. Has an effect + only when on "linear" angular axes. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatterpolargl.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Scatterpolargl + + new_trace = Scatterpolargl( + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + dr=dr, + dtheta=dtheta, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + r=r, + r0=r0, + rsrc=rsrc, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + subplot=subplot, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + theta=theta, + theta0=theta0, + thetasrc=thetasrc, + thetaunit=thetaunit, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scattersmith( + self, + cliponaxis=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + imag=None, + imagsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + real=None, + realsrc=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Scattersmith trace + + The scattersmith trace type encompasses line charts, scatter + charts, text charts, and bubble charts in smith coordinates. + The data visualized as scatter point or lines is set in `real` + and `imag` (imaginary) coordinates Text (appearing either on + the chart or on hover only) is via `text`. Bubble charts are + achieved by setting `marker.size` and/or `marker.color` to + numerical arrays. + + Parameters + ---------- + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scattersmith has a subset of + the options available to scatter. "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattersmith.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + imag + Sets the imaginary component of the data, in units of + normalized impedance such that real=1, imag=0 is the + center of the chart. + imagsrc + Sets the source reference on Chart Studio Cloud for + `imag`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattersmith.Legendgroupti + tle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattersmith.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scattersmith.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + real + Sets the real component of the data, in units of + normalized impedance such that real=1, imag=0 is the + center of the chart. + realsrc + Sets the source reference on Chart Studio Cloud for + `real`. + selected + :class:`plotly.graph_objects.scattersmith.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattersmith.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a smith subplot. If "smith" (the default value), + the data refer to `layout.smith`. If "smith2", the data + refer to `layout.smith2`, and so on. + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `real`, `imag` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattersmith.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Scattersmith + + new_trace = Scattersmith( + cliponaxis=cliponaxis, + connectgaps=connectgaps, + customdata=customdata, + customdatasrc=customdatasrc, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + imag=imag, + imagsrc=imagsrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + real=real, + realsrc=realsrc, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + subplot=subplot, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_scatterternary( + self, + a=None, + asrc=None, + b=None, + bsrc=None, + c=None, + cliponaxis=None, + connectgaps=None, + csrc=None, + customdata=None, + customdatasrc=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + sum=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Scatterternary trace + + Provides similar functionality to the "scatter" type but on a + ternary phase diagram. The data is provided by at least two + arrays out of `a`, `b`, `c` triplets. + + Parameters + ---------- + a + Sets the quantity of component `a` in each data point. + If `a`, `b`, and `c` are all provided, they need not be + normalized, only the relative values matter. If only + two arrays are provided they must be normalized to + match `ternary.sum`. + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + b + Sets the quantity of component `a` in each data point. + If `a`, `b`, and `c` are all provided, they need not be + normalized, only the relative values matter. If only + two arrays are provided they must be normalized to + match `ternary.sum`. + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + c + Sets the quantity of component `a` in each data point. + If `a`, `b`, and `c` are all provided, they need not be + normalized, only the relative values matter. If only + two arrays are provided they must be normalized to + match `ternary.sum`. + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + csrc + Sets the source reference on Chart Studio Cloud for + `c`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scatterternary has a subset + of the options available to scatter. "toself" connects + the endpoints of the trace (or each segment of the + trace if it has gaps) into a closed shape. "tonext" + fills the space between two traces if one completely + encloses the other (eg consecutive contour lines), and + behaves like "toself" if there is no trace before it. + "tonext" should not be used if one trace does not + enclose the other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatterternary.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (a,b,c) + point. If a single string, the same string appears over + all the data points. If an array of strings, the items + are mapped in order to the the data points in (a,b,c). + To be seen, trace `hoverinfo` must contain a "text" + flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatterternary.Legendgroup + title` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatterternary.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scatterternary.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scatterternary.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatterternary.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a ternary subplot. If "ternary" (the default + value), the data refer to `layout.ternary`. If + "ternary2", the data refer to `layout.ternary2`, and so + on. + sum + The number each triplet should sum to, if only two of + `a`, `b`, and `c` are provided. This overrides + `ternary.sum` to normalize this specific trace, but + does not affect the values displayed on the axes. 0 (or + missing) means to use ternary.sum + text + Sets text elements associated with each (a,b,c) point. + If a single string, the same string appears over all + the data points. If an array of strings, the items are + mapped in order to the the data points in (a,b,c). If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `a`, `b`, `c` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatterternary.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Scatterternary + + new_trace = Scatterternary( + a=a, + asrc=asrc, + b=b, + bsrc=bsrc, + c=c, + cliponaxis=cliponaxis, + connectgaps=connectgaps, + csrc=csrc, + customdata=customdata, + customdatasrc=customdatasrc, + fill=fill, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meta=meta, + metasrc=metasrc, + mode=mode, + name=name, + opacity=opacity, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + subplot=subplot, + sum=sum, + text=text, + textfont=textfont, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_splom( + self, + customdata=None, + customdatasrc=None, + diagonal=None, + dimensions=None, + dimensiondefaults=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + showlowerhalf=None, + showupperhalf=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + xaxes=None, + xhoverformat=None, + yaxes=None, + yhoverformat=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Splom trace + + Splom traces generate scatter plot matrix visualizations. Each + splom `dimensions` items correspond to a generated axis. Values + for each of those dimensions are set in `dimensions[i].values`. + Splom traces support all `scattergl` marker style attributes. + Specify `layout.grid` attributes and/or layout x-axis and + y-axis attributes for more control over the axis positioning + and style. + + Parameters + ---------- + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + diagonal + :class:`plotly.graph_objects.splom.Diagonal` instance + or dict with compatible properties + dimensions + A tuple of + :class:`plotly.graph_objects.splom.Dimension` instances + or dicts with compatible properties + dimensiondefaults + When used in a template (as + layout.template.data.splom.dimensiondefaults), sets the + default property values to use for elements of + splom.dimensions + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.splom.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.splom.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.splom.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.splom.Selected` instance + or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showlowerhalf + Determines whether or not subplots on the lower half + from the diagonal are displayed. + showupperhalf + Determines whether or not subplots on the upper half + from the diagonal are displayed. + stream + :class:`plotly.graph_objects.splom.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each (x,y) pair to + appear on hover. If a single string, the same string + appears over all the data points. If an array of + string, the items are mapped in order to the this + trace's (x,y) coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.splom.Unselected` instance + or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + xaxes + Sets the list of x axes corresponding to dimensions of + this splom trace. By default, a splom will match the + first N xaxes where N is the number of input + dimensions. Note that, in case where `diagonal.visible` + is false and `showupperhalf` or `showlowerhalf` is + false, this splom trace will generate one less x-axis + and one less y-axis. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + yaxes + Sets the list of y axes corresponding to dimensions of + this splom trace. By default, a splom will match the + first N yaxes where N is the number of input + dimensions. Note that, in case where `diagonal.visible` + is false and `showupperhalf` or `showlowerhalf` is + false, this splom trace will generate one less x-axis + and one less y-axis. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Splom + + new_trace = Splom( + customdata=customdata, + customdatasrc=customdatasrc, + diagonal=diagonal, + dimensions=dimensions, + dimensiondefaults=dimensiondefaults, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + marker=marker, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + showlowerhalf=showlowerhalf, + showupperhalf=showupperhalf, + stream=stream, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + xaxes=xaxes, + xhoverformat=xhoverformat, + yaxes=yaxes, + yhoverformat=yhoverformat, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_streamtube( + self, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + maxdisplayed=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + sizeref=None, + starts=None, + stream=None, + text=None, + u=None, + uhoverformat=None, + uid=None, + uirevision=None, + usrc=None, + v=None, + vhoverformat=None, + visible=None, + vsrc=None, + w=None, + whoverformat=None, + wsrc=None, + x=None, + xhoverformat=None, + xsrc=None, + y=None, + yhoverformat=None, + ysrc=None, + z=None, + zhoverformat=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Streamtube trace + + Use a streamtube trace to visualize flow in a vector field. + Specify a vector field using 6 1D arrays of equal length, 3 + position arrays `x`, `y` and `z` and 3 vector component arrays + `u`, `v`, and `w`. By default, the tubes' starting positions + will be cut from the vector field's x-z plane at its minimum y + value. To specify your own starting position, use attributes + `starts.x`, `starts.y` and `starts.z`. The color is encoded by + the norm of (u, v, w), and the local radius by the divergence + of (u, v, w). + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here u/v/w norm) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmin` + must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as u/v/w norm. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmax` + must be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.streamtube.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.streamtube.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `tubex`, `tubey`, `tubez`, `tubeu`, + `tubev`, `tubew`, `norm` and `divergence`. Anything + contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.streamtube.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.streamtube.Lighting` + instance or dict with compatible properties + lightposition + :class:`plotly.graph_objects.streamtube.Lightposition` + instance or dict with compatible properties + maxdisplayed + The maximum number of displayed segments in a + streamtube. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + sizeref + The scaling factor for the streamtubes. The default is + 1, which avoids two max divergence tubes from touching + at adjacent starting positions. + starts + :class:`plotly.graph_objects.streamtube.Starts` + instance or dict with compatible properties + stream + :class:`plotly.graph_objects.streamtube.Stream` + instance or dict with compatible properties + text + Sets a text element associated with this trace. If + trace `hoverinfo` contains a "text" flag, this text + element will be seen in all hover labels. Note that + streamtube traces do not support array `text` values. + u + Sets the x components of the vector field. + uhoverformat + Sets the hover text formatting rulefor `u` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + usrc + Sets the source reference on Chart Studio Cloud for + `u`. + v + Sets the y components of the vector field. + vhoverformat + Sets the hover text formatting rulefor `v` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + vsrc + Sets the source reference on Chart Studio Cloud for + `v`. + w + Sets the z components of the vector field. + whoverformat + Sets the hover text formatting rulefor `w` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + wsrc + Sets the source reference on Chart Studio Cloud for + `w`. + x + Sets the x coordinates of the vector field. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates of the vector field. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates of the vector field. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Streamtube + + new_trace = Streamtube( + autocolorscale=autocolorscale, + cauto=cauto, + cmax=cmax, + cmid=cmid, + cmin=cmin, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + customdata=customdata, + customdatasrc=customdatasrc, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lighting=lighting, + lightposition=lightposition, + maxdisplayed=maxdisplayed, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + reversescale=reversescale, + scene=scene, + showlegend=showlegend, + showscale=showscale, + sizeref=sizeref, + starts=starts, + stream=stream, + text=text, + u=u, + uhoverformat=uhoverformat, + uid=uid, + uirevision=uirevision, + usrc=usrc, + v=v, + vhoverformat=vhoverformat, + visible=visible, + vsrc=vsrc, + w=w, + whoverformat=whoverformat, + wsrc=wsrc, + x=x, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zhoverformat=zhoverformat, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_sunburst( + self, + branchvalues=None, + count=None, + customdata=None, + customdatasrc=None, + domain=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextfont=None, + insidetextorientation=None, + labels=None, + labelssrc=None, + leaf=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + level=None, + marker=None, + maxdepth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + outsidetextfont=None, + parents=None, + parentssrc=None, + root=None, + rotation=None, + sort=None, + stream=None, + text=None, + textfont=None, + textinfo=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + values=None, + valuessrc=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Sunburst trace + + Visualize hierarchal data spanning outward radially from root + to leaves. The sunburst sectors are determined by the entries + in "labels" or "ids" and in "parents". + + Parameters + ---------- + branchvalues + Determines how the items in `values` are summed. When + set to "total", items in `values` are taken to be value + of all its descendants. When set to "remainder", items + in `values` corresponding to the root and the branches + sectors are taken to be the extra part not part of the + sum of the values at their leaves. + count + Determines default for `values` when it is not + provided, by inferring a 1 for each of the "leaves" + and/or "branches", otherwise 0. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.sunburst.Domain` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.sunburst.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry` and `percentParent`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + insidetextorientation + Controls the orientation of the text inside chart + sectors. When set to "auto", text may be oriented in + any direction in order to be as big as possible in the + middle of a sector. The "horizontal" option orients + text to be parallel with the bottom of the chart, and + may make text smaller in order to achieve that goal. + The "radial" option orients text along the radius of + the sector. The "tangential" option orients text + perpendicular to the radius of the sector. + labels + Sets the labels of each of the sectors. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + leaf + :class:`plotly.graph_objects.sunburst.Leaf` instance or + dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.sunburst.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + level + Sets the level from which this trace hierarchy is + rendered. Set `level` to `''` to start from the root + node in the hierarchy. Must be an "id" if `ids` is + filled in, otherwise plotly attempts to find a matching + item in `labels`. + marker + :class:`plotly.graph_objects.sunburst.Marker` instance + or dict with compatible properties + maxdepth + Sets the number of rendered sectors from any given + `level`. Set `maxdepth` to "-1" to render all the + levels in the hierarchy. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. This option refers to the root of the hierarchy + presented at the center of a sunburst graph. Please + note that if a hierarchy has multiple root nodes, this + option won't have any effect and `insidetextfont` would + be used. + parents + Sets the parent sectors for each of the sectors. Empty + string items '' are understood to reference the root + node in the hierarchy. If `ids` is filled, `parents` + items are understood to be "ids" themselves. When `ids` + is not set, plotly attempts to find matching items in + `labels`, but beware they must be unique. + parentssrc + Sets the source reference on Chart Studio Cloud for + `parents`. + root + :class:`plotly.graph_objects.sunburst.Root` instance or + dict with compatible properties + rotation + Rotates the whole diagram counterclockwise by some + angle. By default the first slice starts at 3 o'clock. + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.sunburst.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry`, `percentParent`, `label` + and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values associated with each of the sectors. + Use with `branchvalues` to determine how the values are + summed. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Sunburst + + new_trace = Sunburst( + branchvalues=branchvalues, + count=count, + customdata=customdata, + customdatasrc=customdatasrc, + domain=domain, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextfont=insidetextfont, + insidetextorientation=insidetextorientation, + labels=labels, + labelssrc=labelssrc, + leaf=leaf, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + level=level, + marker=marker, + maxdepth=maxdepth, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + outsidetextfont=outsidetextfont, + parents=parents, + parentssrc=parentssrc, + root=root, + rotation=rotation, + sort=sort, + stream=stream, + text=text, + textfont=textfont, + textinfo=textinfo, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + uid=uid, + uirevision=uirevision, + values=values, + valuessrc=valuessrc, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_surface( + self, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + coloraxis=None, + colorbar=None, + colorscale=None, + connectgaps=None, + contours=None, + customdata=None, + customdatasrc=None, + hidesurface=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + opacityscale=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + stream=None, + surfacecolor=None, + surfacecolorsrc=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xcalendar=None, + xhoverformat=None, + xsrc=None, + y=None, + ycalendar=None, + yhoverformat=None, + ysrc=None, + z=None, + zcalendar=None, + zhoverformat=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Surface trace + + The data the describes the coordinates of the surface is set in + `z`. Data in `z` should be a 2D list. Coordinates in `x` and + `y` can either be 1D lists or 2D lists (e.g. to graph + parametric surfaces). If not provided in `x` and `y`, the x and + y coordinates are assumed to be linear starting at 0 with a + unit step. The color scale corresponds to the `z` values by + default. For custom color scales, use `surfacecolor` which + should be a 2D list, where its bounds can be controlled using + `cmin` and `cmax`. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here z or surfacecolor) + or the bounds set in `cmin` and `cmax` Defaults to + `false` when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as z or surfacecolor and if set, + `cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as z or surfacecolor. + Has no effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as z or surfacecolor and if set, + `cmax` must be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.surface.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data are filled in. + contours + :class:`plotly.graph_objects.surface.Contours` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hidesurface + Determines whether or not a surface is drawn. For + example, set `hidesurface` to False `contours.x.show` + to True and `contours.y.show` to True to draw a wire + frame plot. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.surface.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.surface.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.surface.Lighting` instance + or dict with compatible properties + lightposition + :class:`plotly.graph_objects.surface.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + opacityscale + Sets the opacityscale. The opacityscale must be an + array containing arrays mapping a normalized value to + an opacity value. At minimum, a mapping for the lowest + (0) and highest (1) values are required. For example, + `[[0, 1], [0.5, 0.2], [1, 1]]` means that higher/lower + values would have higher opacity values and those in + the middle would be more transparent Alternatively, + `opacityscale` may be a palette name string of the + following list: 'min', 'max', 'extremes' and 'uniform'. + The default is 'uniform'. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.surface.Stream` instance + or dict with compatible properties + surfacecolor + Sets the surface color values, used for setting a color + scale independent of `z`. + surfacecolorsrc + Sets the source reference on Chart Studio Cloud for + `surfacecolor`. + text + Sets the text elements associated with each z value. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates. + zcalendar + Sets the calendar system to use with `z` date data. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Surface + + new_trace = Surface( + autocolorscale=autocolorscale, + cauto=cauto, + cmax=cmax, + cmid=cmid, + cmin=cmin, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + connectgaps=connectgaps, + contours=contours, + customdata=customdata, + customdatasrc=customdatasrc, + hidesurface=hidesurface, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lighting=lighting, + lightposition=lightposition, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + opacityscale=opacityscale, + reversescale=reversescale, + scene=scene, + showlegend=showlegend, + showscale=showscale, + stream=stream, + surfacecolor=surfacecolor, + surfacecolorsrc=surfacecolorsrc, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + visible=visible, + x=x, + xcalendar=xcalendar, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + ycalendar=ycalendar, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zcalendar=zcalendar, + zhoverformat=zhoverformat, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_table( + self, + cells=None, + columnorder=None, + columnordersrc=None, + columnwidth=None, + columnwidthsrc=None, + customdata=None, + customdatasrc=None, + domain=None, + header=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + ids=None, + idssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + meta=None, + metasrc=None, + name=None, + stream=None, + uid=None, + uirevision=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Table trace + + Table view for detailed data viewing. The data are arranged in + a grid of rows and columns. Most styling can be specified for + columns, rows or individual cells. Table is using a column- + major order, ie. the grid is represented as a vector of column + vectors. + + Parameters + ---------- + cells + :class:`plotly.graph_objects.table.Cells` instance or + dict with compatible properties + columnorder + Specifies the rendered order of the data columns; for + example, a value `2` at position `0` means that column + index `0` in the data will be rendered as the third + column, as columns have an index base of zero. + columnordersrc + Sets the source reference on Chart Studio Cloud for + `columnorder`. + columnwidth + The width of columns expressed as a ratio. Columns fill + the available width in proportion of their specified + column widths. + columnwidthsrc + Sets the source reference on Chart Studio Cloud for + `columnwidth`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.table.Domain` instance or + dict with compatible properties + header + :class:`plotly.graph_objects.table.Header` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.table.Hoverlabel` instance + or dict with compatible properties + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.table.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + stream + :class:`plotly.graph_objects.table.Stream` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Table + + new_trace = Table( + cells=cells, + columnorder=columnorder, + columnordersrc=columnordersrc, + columnwidth=columnwidth, + columnwidthsrc=columnwidthsrc, + customdata=customdata, + customdatasrc=customdatasrc, + domain=domain, + header=header, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + ids=ids, + idssrc=idssrc, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + meta=meta, + metasrc=metasrc, + name=name, + stream=stream, + uid=uid, + uirevision=uirevision, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_treemap( + self, + branchvalues=None, + count=None, + customdata=None, + customdatasrc=None, + domain=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextfont=None, + labels=None, + labelssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + level=None, + marker=None, + maxdepth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + outsidetextfont=None, + parents=None, + parentssrc=None, + pathbar=None, + root=None, + sort=None, + stream=None, + text=None, + textfont=None, + textinfo=None, + textposition=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + tiling=None, + uid=None, + uirevision=None, + values=None, + valuessrc=None, + visible=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Treemap trace + + Visualize hierarchal data from leaves (and/or outer branches) + towards root with rectangles. The treemap sectors are + determined by the entries in "labels" or "ids" and in + "parents". + + Parameters + ---------- + branchvalues + Determines how the items in `values` are summed. When + set to "total", items in `values` are taken to be value + of all its descendants. When set to "remainder", items + in `values` corresponding to the root and the branches + sectors are taken to be the extra part not part of the + sum of the values at their leaves. + count + Determines default for `values` when it is not + provided, by inferring a 1 for each of the "leaves" + and/or "branches", otherwise 0. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.treemap.Domain` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.treemap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry` and `percentParent`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + labels + Sets the labels of each of the sectors. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.treemap.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + level + Sets the level from which this trace hierarchy is + rendered. Set `level` to `''` to start from the root + node in the hierarchy. Must be an "id" if `ids` is + filled in, otherwise plotly attempts to find a matching + item in `labels`. + marker + :class:`plotly.graph_objects.treemap.Marker` instance + or dict with compatible properties + maxdepth + Sets the number of rendered sectors from any given + `level`. Set `maxdepth` to "-1" to render all the + levels in the hierarchy. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. This option refers to the root of the hierarchy + presented on top left corner of a treemap graph. Please + note that if a hierarchy has multiple root nodes, this + option won't have any effect and `insidetextfont` would + be used. + parents + Sets the parent sectors for each of the sectors. Empty + string items '' are understood to reference the root + node in the hierarchy. If `ids` is filled, `parents` + items are understood to be "ids" themselves. When `ids` + is not set, plotly attempts to find matching items in + `labels`, but beware they must be unique. + parentssrc + Sets the source reference on Chart Studio Cloud for + `parents`. + pathbar + :class:`plotly.graph_objects.treemap.Pathbar` instance + or dict with compatible properties + root + :class:`plotly.graph_objects.treemap.Root` instance or + dict with compatible properties + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.treemap.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Sets the positions of the `text` elements. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry`, `percentParent`, `label` + and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + tiling + :class:`plotly.graph_objects.treemap.Tiling` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values associated with each of the sectors. + Use with `branchvalues` to determine how the values are + summed. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Treemap + + new_trace = Treemap( + branchvalues=branchvalues, + count=count, + customdata=customdata, + customdatasrc=customdatasrc, + domain=domain, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + insidetextfont=insidetextfont, + labels=labels, + labelssrc=labelssrc, + legend=legend, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + level=level, + marker=marker, + maxdepth=maxdepth, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + outsidetextfont=outsidetextfont, + parents=parents, + parentssrc=parentssrc, + pathbar=pathbar, + root=root, + sort=sort, + stream=stream, + text=text, + textfont=textfont, + textinfo=textinfo, + textposition=textposition, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + tiling=tiling, + uid=uid, + uirevision=uirevision, + values=values, + valuessrc=valuessrc, + visible=visible, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_violin( + self, + alignmentgroup=None, + bandwidth=None, + box=None, + customdata=None, + customdatasrc=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + jitter=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meanline=None, + meta=None, + metasrc=None, + name=None, + offsetgroup=None, + opacity=None, + orientation=None, + pointpos=None, + points=None, + quartilemethod=None, + scalegroup=None, + scalemode=None, + selected=None, + selectedpoints=None, + showlegend=None, + side=None, + span=None, + spanmode=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + width=None, + x=None, + x0=None, + xaxis=None, + xhoverformat=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + yhoverformat=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Violin trace + + In vertical (horizontal) violin plots, statistics are computed + using `y` (`x`) values. By supplying an `x` (`y`) array, one + violin per distinct x (y) value is drawn If no `x` (`y`) list + is provided, a single violin is drawn. That violin position is + then positioned with with `name` or with `x0` (`y0`) if + provided. + + Parameters + ---------- + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + bandwidth + Sets the bandwidth used to compute the kernel density + estimate. By default, the bandwidth is determined by + Silverman's rule of thumb. + box + :class:`plotly.graph_objects.violin.Box` instance or + dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.violin.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual violins or + sample points or the kernel density estimate or any + combination of them? + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + jitter + Sets the amount of jitter in the sample points drawn. + If 0, the sample points align along the distribution + axis. If 1, the sample points are drawn in a random + jitter of width equal to the width of the violins. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.violin.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.violin.Line` instance or + dict with compatible properties + marker + :class:`plotly.graph_objects.violin.Marker` instance or + dict with compatible properties + meanline + :class:`plotly.graph_objects.violin.Meanline` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. For violin traces, the name + will also be used for the position coordinate, if `x` + and `x0` (`y` and `y0` if horizontal) are missing and + the position axis is categorical. Note that the trace + name is also used as a default value for attribute + `scalegroup` (please see its description for details). + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the violin(s). If "v" ("h"), + the distribution is visualized along the vertical + (horizontal). + pointpos + Sets the position of the sample points in relation to + the violins. If 0, the sample points are places over + the center of the violins. Positive (negative) values + correspond to positions to the right (left) for + vertical violins and above (below) for horizontal + violins. + points + If "outliers", only the sample points lying outside the + whiskers are shown If "suspectedoutliers", the outlier + points are shown and points either less than 4*Q1-3*Q3 + or greater than 4*Q3-3*Q1 are highlighted (see + `outliercolor`) If "all", all sample points are shown + If False, only the violins are shown with no sample + points. Defaults to "suspectedoutliers" when + `marker.outliercolor` or `marker.line.outliercolor` is + set, otherwise defaults to "outliers". + quartilemethod + Sets the method used to compute the sample's Q1 and Q3 + quartiles. The "linear" method uses the 25th percentile + for Q1 and 75th percentile for Q3 as computed using + method #10 (listed on + http://jse.amstat.org/v14n3/langford.html). The + "exclusive" method uses the median to divide the + ordered dataset into two halves if the sample is odd, + it does not include the median in either half - Q1 is + then the median of the lower half and Q3 the median of + the upper half. The "inclusive" method also uses the + median to divide the ordered dataset into two halves + but if the sample is odd, it includes the median in + both halves - Q1 is then the median of the lower half + and Q3 the median of the upper half. + scalegroup + If there are multiple violins that should be sized + according to to some metric (see `scalemode`), link + them by providing a non-empty group id here shared by + every trace in the same group. If a violin's `width` is + undefined, `scalegroup` will default to the trace's + name. In this case, violins with the same names will be + linked together + scalemode + Sets the metric by which the width of each violin is + determined. "width" means each violin has the same + (max) width "count" means the violins are scaled by the + number of sample points making up each violin. + selected + :class:`plotly.graph_objects.violin.Selected` instance + or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + side + Determines on which side of the position value the + density function making up one half of a violin is + plotted. Useful when comparing two violin traces under + "overlay" mode, where one trace has `side` set to + "positive" and the other to "negative". + span + Sets the span in data space for which the density + function will be computed. Has an effect only when + `spanmode` is set to "manual". + spanmode + Sets the method by which the span in data space where + the density function will be computed. "soft" means the + span goes from the sample's minimum value minus two + bandwidths to the sample's maximum value plus two + bandwidths. "hard" means the span goes from the + sample's minimum to its maximum value. For custom span + settings, use mode "manual" and fill in the `span` + attribute. + stream + :class:`plotly.graph_objects.violin.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with each sample + value. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.violin.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the width of the violin in data coordinates. If 0 + (default value) the width is automatically selected + based on the positions of other violin traces in the + same subplot. + x + Sets the x sample data or coordinates. See overview for + more info. + x0 + Sets the x coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y sample data or coordinates. See overview for + more info. + y0 + Sets the y coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Violin + + new_trace = Violin( + alignmentgroup=alignmentgroup, + bandwidth=bandwidth, + box=box, + customdata=customdata, + customdatasrc=customdatasrc, + fillcolor=fillcolor, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hoveron=hoveron, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + jitter=jitter, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + marker=marker, + meanline=meanline, + meta=meta, + metasrc=metasrc, + name=name, + offsetgroup=offsetgroup, + opacity=opacity, + orientation=orientation, + pointpos=pointpos, + points=points, + quartilemethod=quartilemethod, + scalegroup=scalegroup, + scalemode=scalemode, + selected=selected, + selectedpoints=selectedpoints, + showlegend=showlegend, + side=side, + span=span, + spanmode=spanmode, + stream=stream, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + unselected=unselected, + visible=visible, + width=width, + x=x, + x0=x0, + xaxis=xaxis, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + y0=y0, + yaxis=yaxis, + yhoverformat=yhoverformat, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def add_volume( + self, + autocolorscale=None, + caps=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + coloraxis=None, + colorbar=None, + colorscale=None, + contour=None, + customdata=None, + customdatasrc=None, + flatshading=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + isomax=None, + isomin=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + opacityscale=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + slices=None, + spaceframe=None, + stream=None, + surface=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + value=None, + valuehoverformat=None, + valuesrc=None, + visible=None, + x=None, + xhoverformat=None, + xsrc=None, + y=None, + yhoverformat=None, + ysrc=None, + z=None, + zhoverformat=None, + zsrc=None, + row=None, + col=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Volume trace + + Draws volume trace between iso-min and iso-max values with + coordinates given by four 1-dimensional arrays containing the + `value`, `x`, `y` and `z` of every vertex of a uniform or non- + uniform 3-D grid. Horizontal or vertical slices, caps as well + as spaceframe between iso-min and iso-max values could also be + drawn using this trace. + + Parameters + ---------- + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + caps + :class:`plotly.graph_objects.volume.Caps` instance or + dict with compatible properties + cauto + Determines whether or not the color domain is computed + with respect to the input data (here `value`) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as `value` and if set, `cmin` must + be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as `value`. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as `value` and if set, `cmax` must + be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.volume.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contour + :class:`plotly.graph_objects.volume.Contour` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + flatshading + Determines whether or not normal smoothing is applied + to the meshes, creating meshes with an angular, low- + poly look via flat reflections. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.volume.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + isomax + Sets the maximum boundary for iso-surface plot. + isomin + Sets the minimum boundary for iso-surface plot. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.volume.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.volume.Lighting` instance + or dict with compatible properties + lightposition + :class:`plotly.graph_objects.volume.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + opacityscale + Sets the opacityscale. The opacityscale must be an + array containing arrays mapping a normalized value to + an opacity value. At minimum, a mapping for the lowest + (0) and highest (1) values are required. For example, + `[[0, 1], [0.5, 0.2], [1, 1]]` means that higher/lower + values would have higher opacity values and those in + the middle would be more transparent Alternatively, + `opacityscale` may be a palette name string of the + following list: 'min', 'max', 'extremes' and 'uniform'. + The default is 'uniform'. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + slices + :class:`plotly.graph_objects.volume.Slices` instance or + dict with compatible properties + spaceframe + :class:`plotly.graph_objects.volume.Spaceframe` + instance or dict with compatible properties + stream + :class:`plotly.graph_objects.volume.Stream` instance or + dict with compatible properties + surface + :class:`plotly.graph_objects.volume.Surface` instance + or dict with compatible properties + text + Sets the text elements associated with the vertices. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + value + Sets the 4th dimension (value) of the vertices. + valuehoverformat + Sets the hover text formatting rulefor `value` using + d3 formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + valuesrc + Sets the source reference on Chart Studio Cloud for + `value`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the X coordinates of the vertices on X axis. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the Y coordinates of the vertices on Y axis. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the Z coordinates of the vertices on Z axis. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Volume + + new_trace = Volume( + autocolorscale=autocolorscale, + caps=caps, + cauto=cauto, + cmax=cmax, + cmid=cmid, + cmin=cmin, + coloraxis=coloraxis, + colorbar=colorbar, + colorscale=colorscale, + contour=contour, + customdata=customdata, + customdatasrc=customdatasrc, + flatshading=flatshading, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + isomax=isomax, + isomin=isomin, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + lighting=lighting, + lightposition=lightposition, + meta=meta, + metasrc=metasrc, + name=name, + opacity=opacity, + opacityscale=opacityscale, + reversescale=reversescale, + scene=scene, + showlegend=showlegend, + showscale=showscale, + slices=slices, + spaceframe=spaceframe, + stream=stream, + surface=surface, + text=text, + textsrc=textsrc, + uid=uid, + uirevision=uirevision, + value=value, + valuehoverformat=valuehoverformat, + valuesrc=valuesrc, + visible=visible, + x=x, + xhoverformat=xhoverformat, + xsrc=xsrc, + y=y, + yhoverformat=yhoverformat, + ysrc=ysrc, + z=z, + zhoverformat=zhoverformat, + zsrc=zsrc, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col) + + def add_waterfall( + self, + alignmentgroup=None, + base=None, + cliponaxis=None, + connector=None, + constraintext=None, + customdata=None, + customdatasrc=None, + decreasing=None, + dx=None, + dy=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + increasing=None, + insidetextanchor=None, + insidetextfont=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + measure=None, + measuresrc=None, + meta=None, + metasrc=None, + name=None, + offset=None, + offsetgroup=None, + offsetsrc=None, + opacity=None, + orientation=None, + outsidetextfont=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textangle=None, + textfont=None, + textinfo=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + totals=None, + uid=None, + uirevision=None, + visible=None, + width=None, + widthsrc=None, + x=None, + x0=None, + xaxis=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + zorder=None, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Add a new Waterfall trace + + Draws waterfall trace which is useful graph to displays the + contribution of various elements (either positive or negative) + in a bar chart. The data visualized by the span of the bars is + set in `y` if `orientation` is set to "v" (the default) and the + labels are set in `x`. By setting `orientation` to "h", the + roles are interchanged. + + Parameters + ---------- + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + base + Sets where the bar base is drawn (in position axis + units). + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + connector + :class:`plotly.graph_objects.waterfall.Connector` + instance or dict with compatible properties + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + decreasing + :class:`plotly.graph_objects.waterfall.Decreasing` + instance or dict with compatible properties + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.waterfall.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `initial`, `delta` and `final`. Anything + contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + increasing + :class:`plotly.graph_objects.waterfall.Increasing` + instance or dict with compatible properties + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.waterfall.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + measure + An array containing types of values. By default the + values are considered as 'relative'. However; it is + possible to use 'total' to compute the sums. Also + 'absolute' could be applied to reset the computed total + or to declare an initial value where needed. + measuresrc + Sets the source reference on Chart Studio Cloud for + `measure`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the position where the bar is drawn (in position + axis units). In "group" barmode, traces that set + "offset" will be excluded and drawn in "overlay" mode + instead. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + offsetsrc + Sets the source reference on Chart Studio Cloud for + `offset`. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the bars. With "v" ("h"), the + value of the each bar spans along the vertical + (horizontal). + outsidetextfont + Sets the font used for `text` lying outside the bar. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.waterfall.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the font used for `text`. + textinfo + Determines which trace information appear on the graph. + In the case of having multiple waterfalls, totals are + computed separately (per trace). + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `initial`, `delta`, `final` and `label`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + totals + :class:`plotly.graph_objects.waterfall.Totals` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar width (in position axis units). + widthsrc + Sets the source reference on Chart Studio Cloud for + `width`. + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + row : 'all', int or None (default) + Subplot row index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + rows in the specified column(s). + col : 'all', int or None (default) + Subplot col index (starting from 1) for the trace to be + added. Only valid if figure was created using + `plotly.tools.make_subplots`.If 'all', addresses all + columns in the specified row(s). + secondary_y: boolean or None (default None) + If True, associate this trace with the secondary y-axis of the + subplot at the specified row and col. Only valid if all of the + following conditions are satisfied: + * The figure was created using `plotly.subplots.make_subplots`. + * The row and col arguments are not None + * The subplot at the specified row and col has type xy + (which is the default) and secondary_y True. These + properties are specified in the specs argument to + make_subplots. See the make_subplots docstring for more info. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import Waterfall + + new_trace = Waterfall( + alignmentgroup=alignmentgroup, + base=base, + cliponaxis=cliponaxis, + connector=connector, + constraintext=constraintext, + customdata=customdata, + customdatasrc=customdatasrc, + decreasing=decreasing, + dx=dx, + dy=dy, + hoverinfo=hoverinfo, + hoverinfosrc=hoverinfosrc, + hoverlabel=hoverlabel, + hovertemplate=hovertemplate, + hovertemplatefallback=hovertemplatefallback, + hovertemplatesrc=hovertemplatesrc, + hovertext=hovertext, + hovertextsrc=hovertextsrc, + ids=ids, + idssrc=idssrc, + increasing=increasing, + insidetextanchor=insidetextanchor, + insidetextfont=insidetextfont, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + measure=measure, + measuresrc=measuresrc, + meta=meta, + metasrc=metasrc, + name=name, + offset=offset, + offsetgroup=offsetgroup, + offsetsrc=offsetsrc, + opacity=opacity, + orientation=orientation, + outsidetextfont=outsidetextfont, + selectedpoints=selectedpoints, + showlegend=showlegend, + stream=stream, + text=text, + textangle=textangle, + textfont=textfont, + textinfo=textinfo, + textposition=textposition, + textpositionsrc=textpositionsrc, + textsrc=textsrc, + texttemplate=texttemplate, + texttemplatefallback=texttemplatefallback, + texttemplatesrc=texttemplatesrc, + totals=totals, + uid=uid, + uirevision=uirevision, + visible=visible, + width=width, + widthsrc=widthsrc, + x=x, + x0=x0, + xaxis=xaxis, + xhoverformat=xhoverformat, + xperiod=xperiod, + xperiod0=xperiod0, + xperiodalignment=xperiodalignment, + xsrc=xsrc, + y=y, + y0=y0, + yaxis=yaxis, + yhoverformat=yhoverformat, + yperiod=yperiod, + yperiod0=yperiod0, + yperiodalignment=yperiodalignment, + ysrc=ysrc, + zorder=zorder, + **kwargs, + ) + return self.add_trace(new_trace, row=row, col=col, secondary_y=secondary_y) + + def select_coloraxes(self, selector=None, row=None, col=None): + """ + Select coloraxis subplot objects from a particular subplot cell + and/or coloraxis subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + coloraxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all coloraxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + coloraxis and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of coloraxis objects to select. + To select coloraxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all coloraxis objects are selected. + Returns + ------- + generator + Generator that iterates through all of the coloraxis + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("coloraxis", selector, row, col) + + def for_each_coloraxis( + self, fn, selector=None, row=None, col=None + ) -> "FigureWidget": + """ + Apply a function to all coloraxis objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single coloraxis object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + coloraxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all coloraxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + coloraxis and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of coloraxis objects to select. + To select coloraxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all coloraxis objects are selected. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_coloraxes(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_coloraxes( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "FigureWidget": + """ + Perform a property update operation on all coloraxis objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + coloraxis objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + coloraxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all coloraxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + coloraxis and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of coloraxis objects to select. + To select coloraxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all coloraxis objects are selected. + **kwargs + Additional property updates to apply to each selected + coloraxis object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_coloraxes(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_geos(self, selector=None, row=None, col=None): + """ + Select geo subplot objects from a particular subplot cell + and/or geo subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + geo objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all geo objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + geo and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of geo objects to select. + To select geo objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all geo objects are selected. + Returns + ------- + generator + Generator that iterates through all of the geo + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("geo", selector, row, col) + + def for_each_geo(self, fn, selector=None, row=None, col=None) -> "FigureWidget": + """ + Apply a function to all geo objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single geo object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + geo objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all geo objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + geo and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of geo objects to select. + To select geo objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all geo objects are selected. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_geos(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_geos( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "FigureWidget": + """ + Perform a property update operation on all geo objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + geo objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + geo objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all geo objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + geo and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of geo objects to select. + To select geo objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all geo objects are selected. + **kwargs + Additional property updates to apply to each selected + geo object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_geos(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_legends(self, selector=None, row=None, col=None): + """ + Select legend subplot objects from a particular subplot cell + and/or legend subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + legend objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all legend objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + legend and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of legend objects to select. + To select legend objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all legend objects are selected. + Returns + ------- + generator + Generator that iterates through all of the legend + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("legend", selector, row, col) + + def for_each_legend(self, fn, selector=None, row=None, col=None) -> "FigureWidget": + """ + Apply a function to all legend objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single legend object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + legend objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all legend objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + legend and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of legend objects to select. + To select legend objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all legend objects are selected. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_legends(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_legends( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "FigureWidget": + """ + Perform a property update operation on all legend objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + legend objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + legend objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all legend objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + legend and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of legend objects to select. + To select legend objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all legend objects are selected. + **kwargs + Additional property updates to apply to each selected + legend object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_legends(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_maps(self, selector=None, row=None, col=None): + """ + Select map subplot objects from a particular subplot cell + and/or map subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + map objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all map objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + map and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of map objects to select. + To select map objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all map objects are selected. + Returns + ------- + generator + Generator that iterates through all of the map + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("map", selector, row, col) + + def for_each_map(self, fn, selector=None, row=None, col=None) -> "FigureWidget": + """ + Apply a function to all map objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single map object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + map objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all map objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + map and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of map objects to select. + To select map objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all map objects are selected. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_maps(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_maps( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "FigureWidget": + """ + Perform a property update operation on all map objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + map objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + map objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all map objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + map and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of map objects to select. + To select map objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all map objects are selected. + **kwargs + Additional property updates to apply to each selected + map object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_maps(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_mapboxes(self, selector=None, row=None, col=None): + """ + Select mapbox subplot objects from a particular subplot cell + and/or mapbox subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + mapbox objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all mapbox objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + mapbox and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of mapbox objects to select. + To select mapbox objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all mapbox objects are selected. + Returns + ------- + generator + Generator that iterates through all of the mapbox + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("mapbox", selector, row, col) + + def for_each_mapbox(self, fn, selector=None, row=None, col=None) -> "FigureWidget": + """ + Apply a function to all mapbox objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single mapbox object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + mapbox objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all mapbox objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + mapbox and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of mapbox objects to select. + To select mapbox objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all mapbox objects are selected. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_mapboxes(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_mapboxes( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "FigureWidget": + """ + Perform a property update operation on all mapbox objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + mapbox objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + mapbox objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all mapbox objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + mapbox and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of mapbox objects to select. + To select mapbox objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all mapbox objects are selected. + **kwargs + Additional property updates to apply to each selected + mapbox object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_mapboxes(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_polars(self, selector=None, row=None, col=None): + """ + Select polar subplot objects from a particular subplot cell + and/or polar subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + polar objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all polar objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + polar and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of polar objects to select. + To select polar objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all polar objects are selected. + Returns + ------- + generator + Generator that iterates through all of the polar + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("polar", selector, row, col) + + def for_each_polar(self, fn, selector=None, row=None, col=None) -> "FigureWidget": + """ + Apply a function to all polar objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single polar object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + polar objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all polar objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + polar and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of polar objects to select. + To select polar objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all polar objects are selected. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_polars(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_polars( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "FigureWidget": + """ + Perform a property update operation on all polar objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + polar objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + polar objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all polar objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + polar and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of polar objects to select. + To select polar objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all polar objects are selected. + **kwargs + Additional property updates to apply to each selected + polar object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_polars(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_scenes(self, selector=None, row=None, col=None): + """ + Select scene subplot objects from a particular subplot cell + and/or scene subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + scene objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all scene objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + scene and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of scene objects to select. + To select scene objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all scene objects are selected. + Returns + ------- + generator + Generator that iterates through all of the scene + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("scene", selector, row, col) + + def for_each_scene(self, fn, selector=None, row=None, col=None) -> "FigureWidget": + """ + Apply a function to all scene objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single scene object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + scene objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all scene objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + scene and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of scene objects to select. + To select scene objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all scene objects are selected. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_scenes(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_scenes( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "FigureWidget": + """ + Perform a property update operation on all scene objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + scene objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + scene objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all scene objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + scene and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of scene objects to select. + To select scene objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all scene objects are selected. + **kwargs + Additional property updates to apply to each selected + scene object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_scenes(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_smiths(self, selector=None, row=None, col=None): + """ + Select smith subplot objects from a particular subplot cell + and/or smith subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + smith objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all smith objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + smith and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of smith objects to select. + To select smith objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all smith objects are selected. + Returns + ------- + generator + Generator that iterates through all of the smith + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("smith", selector, row, col) + + def for_each_smith(self, fn, selector=None, row=None, col=None) -> "FigureWidget": + """ + Apply a function to all smith objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single smith object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + smith objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all smith objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + smith and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of smith objects to select. + To select smith objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all smith objects are selected. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_smiths(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_smiths( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "FigureWidget": + """ + Perform a property update operation on all smith objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + smith objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + smith objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all smith objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + smith and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of smith objects to select. + To select smith objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all smith objects are selected. + **kwargs + Additional property updates to apply to each selected + smith object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_smiths(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_ternaries(self, selector=None, row=None, col=None): + """ + Select ternary subplot objects from a particular subplot cell + and/or ternary subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + ternary objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all ternary objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + ternary and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of ternary objects to select. + To select ternary objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all ternary objects are selected. + Returns + ------- + generator + Generator that iterates through all of the ternary + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("ternary", selector, row, col) + + def for_each_ternary(self, fn, selector=None, row=None, col=None) -> "FigureWidget": + """ + Apply a function to all ternary objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single ternary object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + ternary objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all ternary objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + ternary and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of ternary objects to select. + To select ternary objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all ternary objects are selected. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_ternaries(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_ternaries( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "FigureWidget": + """ + Perform a property update operation on all ternary objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + ternary objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + ternary objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all ternary objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + ternary and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of ternary objects to select. + To select ternary objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all ternary objects are selected. + **kwargs + Additional property updates to apply to each selected + ternary object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_ternaries(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_xaxes(self, selector=None, row=None, col=None): + """ + Select xaxis subplot objects from a particular subplot cell + and/or xaxis subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + xaxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all xaxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + xaxis and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of xaxis objects to select. + To select xaxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all xaxis objects are selected. + Returns + ------- + generator + Generator that iterates through all of the xaxis + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix("xaxis", selector, row, col) + + def for_each_xaxis(self, fn, selector=None, row=None, col=None) -> "FigureWidget": + """ + Apply a function to all xaxis objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single xaxis object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + xaxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all xaxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + xaxis and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of xaxis objects to select. + To select xaxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all xaxis objects are selected. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_xaxes(selector=selector, row=row, col=col): + fn(obj) + + return self + + def update_xaxes( + self, patch=None, selector=None, overwrite=False, row=None, col=None, **kwargs + ) -> "FigureWidget": + """ + Perform a property update operation on all xaxis objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + xaxis objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + xaxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all xaxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + xaxis and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of xaxis objects to select. + To select xaxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all xaxis objects are selected. + **kwargs + Additional property updates to apply to each selected + xaxis object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_xaxes(selector=selector, row=row, col=col): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_yaxes(self, selector=None, row=None, col=None, secondary_y=None): + """ + Select yaxis subplot objects from a particular subplot cell + and/or yaxis subplot objects that satisfy custom selection + criteria. + + Parameters + ---------- + selector: dict, function, or None (default None) + Dict to use as selection criteria. + yaxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all yaxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + yaxis and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of yaxis objects to select. + To select yaxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all yaxis objects are selected. + secondary_y: boolean or None (default None) + * If True, only select yaxis objects associated with the secondary + y-axis of the subplot. + * If False, only select yaxis objects associated with the primary + y-axis of the subplot. + * If None (the default), do not filter yaxis objects based on + a secondary y-axis condition. + + To select yaxis objects by secondary y-axis, the Figure must + have been created using plotly.subplots.make_subplots. See + the docstring for the specs argument to make_subplots for more + info on creating subplots with secondary y-axes. + Returns + ------- + generator + Generator that iterates through all of the yaxis + objects that satisfy all of the specified selection criteria + """ + + return self._select_layout_subplots_by_prefix( + "yaxis", selector, row, col, secondary_y=secondary_y + ) + + def for_each_yaxis( + self, fn, selector=None, row=None, col=None, secondary_y=None + ) -> "FigureWidget": + """ + Apply a function to all yaxis objects that satisfy the + specified selection criteria + + Parameters + ---------- + fn: + Function that inputs a single yaxis object. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + yaxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all yaxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + yaxis and those for which the function returned True will + be in the selection. + row, col: int or None (default None) + Subplot row and column index of yaxis objects to select. + To select yaxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all yaxis objects are selected. + secondary_y: boolean or None (default None) + * If True, only select yaxis objects associated with the secondary + y-axis of the subplot. + * If False, only select yaxis objects associated with the primary + y-axis of the subplot. + * If None (the default), do not filter yaxis objects based on + a secondary y-axis condition. + + To select yaxis objects by secondary y-axis, the Figure must + have been created using plotly.subplots.make_subplots. See + the docstring for the specs argument to make_subplots for more + info on creating subplots with secondary y-axes. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_yaxes( + selector=selector, row=row, col=col, secondary_y=secondary_y + ): + fn(obj) + + return self + + def update_yaxes( + self, + patch=None, + selector=None, + overwrite=False, + row=None, + col=None, + secondary_y=None, + **kwargs, + ) -> "FigureWidget": + """ + Perform a property update operation on all yaxis objects + that satisfy the specified selection criteria + + Parameters + ---------- + patch: dict + Dictionary of property updates to be applied to all + yaxis objects that satisfy the selection criteria. + selector: dict, function, or None (default None) + Dict to use as selection criteria. + yaxis objects will be selected if they contain + properties corresponding to all of the dictionary's keys, with + values that exactly match the supplied values. If None + (the default), all yaxis objects are selected. If a + function, it must be a function accepting a single argument and + returning a boolean. The function will be called on each + yaxis and those for which the function returned True will + be in the selection. + overwrite: bool + If True, overwrite existing properties. If False, apply updates + to existing properties recursively, preserving existing + properties that are not specified in the update operation. + row, col: int or None (default None) + Subplot row and column index of yaxis objects to select. + To select yaxis objects by row and column, the Figure + must have been created using plotly.subplots.make_subplots. + If None (the default), all yaxis objects are selected. + secondary_y: boolean or None (default None) + * If True, only select yaxis objects associated with the secondary + y-axis of the subplot. + * If False, only select yaxis objects associated with the primary + y-axis of the subplot. + * If None (the default), do not filter yaxis objects based on + a secondary y-axis condition. + + To select yaxis objects by secondary y-axis, the Figure must + have been created using plotly.subplots.make_subplots. See + the docstring for the specs argument to make_subplots for more + info on creating subplots with secondary y-axes. + **kwargs + Additional property updates to apply to each selected + yaxis object. If a property is specified in + both patch and in **kwargs then the one in **kwargs + takes precedence. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self.select_yaxes( + selector=selector, row=row, col=col, secondary_y=secondary_y + ): + obj.update(patch, overwrite=overwrite, **kwargs) + + return self + + def select_annotations(self, selector=None, row=None, col=None, secondary_y=None): + """ + Select annotations from a particular subplot cell and/or annotations + that satisfy custom selection criteria. + + Parameters + ---------- + selector: dict, function, int, str, or None (default None) + Dict to use as selection criteria. + Annotations will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all annotations are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each annotation and those for which the function returned True + will be in the selection. If an int N, the Nth annotation matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of annotations to select. + To select annotations by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + annotation that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all annotations are selected. + secondary_y: boolean or None (default None) + * If True, only select annotations associated with the secondary + y-axis of the subplot. + * If False, only select annotations associated with the primary + y-axis of the subplot. + * If None (the default), do not filter annotations based on secondary + y-axis. + + To select annotations by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + generator + Generator that iterates through all of the annotations that satisfy + all of the specified selection criteria + """ + return self._select_annotations_like( + "annotations", selector=selector, row=row, col=col, secondary_y=secondary_y + ) + + def for_each_annotation( + self, fn, selector=None, row=None, col=None, secondary_y=None + ): + """ + Apply a function to all annotations that satisfy the specified selection + criteria + + Parameters + ---------- + fn: + Function that inputs a single annotation object. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all annotations are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each annotation and those for which the function returned True + will be in the selection. If an int N, the Nth annotation matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of annotations to select. + To select annotations by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + annotations that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all annotations are selected. + secondary_y: boolean or None (default None) + * If True, only select annotations associated with the secondary + y-axis of the subplot. + * If False, only select annotations associated with the primary + y-axis of the subplot. + * If None (the default), do not filter annotations based on secondary + y-axis. + + To select annotations by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self._select_annotations_like( + prop="annotations", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + fn(obj) + + return self + + def update_annotations( + self, patch=None, selector=None, row=None, col=None, secondary_y=None, **kwargs + ) -> "FigureWidget": + """ + Perform a property update operation on all annotations that satisfy the + specified selection criteria + + Parameters + ---------- + patch: dict or None (default None) + Dictionary of property updates to be applied to all annotations that + satisfy the selection criteria. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all annotations are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each annotation and those for which the function returned True + will be in the selection. If an int N, the Nth annotation matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of annotations to select. + To select annotations by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + annotation that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all annotations are selected. + secondary_y: boolean or None (default None) + * If True, only select annotations associated with the secondary + y-axis of the subplot. + * If False, only select annotations associated with the primary + y-axis of the subplot. + * If None (the default), do not filter annotations based on secondary + y-axis. + + To select annotations by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + **kwargs + Additional property updates to apply to each selected annotation. If + a property is specified in both patch and in **kwargs then the + one in **kwargs takes precedence. + + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self._select_annotations_like( + prop="annotations", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + obj.update(patch, **kwargs) + + return self + + def add_annotation( + self, + arg=None, + align=None, + arrowcolor=None, + arrowhead=None, + arrowside=None, + arrowsize=None, + arrowwidth=None, + ax=None, + axref=None, + ay=None, + ayref=None, + bgcolor=None, + bordercolor=None, + borderpad=None, + borderwidth=None, + captureevents=None, + clicktoshow=None, + font=None, + height=None, + hoverlabel=None, + hovertext=None, + name=None, + opacity=None, + showarrow=None, + standoff=None, + startarrowhead=None, + startarrowsize=None, + startstandoff=None, + templateitemname=None, + text=None, + textangle=None, + valign=None, + visible=None, + width=None, + x=None, + xanchor=None, + xclick=None, + xref=None, + xshift=None, + y=None, + yanchor=None, + yclick=None, + yref=None, + yshift=None, + row=None, + col=None, + secondary_y=None, + exclude_empty_subplots=None, + **kwargs, + ) -> "FigureWidget": + """ + Create and add a new annotation to the figure's layout + + Parameters + ---------- + arg + instance of Annotation or dict with compatible + properties + align + Sets the horizontal alignment of the `text` within the + box. Has an effect only if `text` spans two or more + lines (i.e. `text` contains one or more
HTML tags) + or if an explicit width is set to override the text + width. + arrowcolor + Sets the color of the annotation arrow. + arrowhead + Sets the end annotation arrow head style. + arrowside + Sets the annotation arrow head position. + arrowsize + Sets the size of the end annotation arrow head, + relative to `arrowwidth`. A value of 1 (default) gives + a head about 3x as wide as the line. + arrowwidth + Sets the width (in px) of annotation arrow line. + ax + Sets the x component of the arrow tail about the arrow + head. If `axref` is `pixel`, a positive (negative) + component corresponds to an arrow pointing from right + to left (left to right). If `axref` is not `pixel` and + is exactly the same as `xref`, this is an absolute + value on that axis, like `x`, specified in the same + coordinates as `xref`. + axref + Indicates in what coordinates the tail of the + annotation (ax,ay) is specified. If set to a x axis id + (e.g. "x" or "x2"), the `x` position refers to a x + coordinate. If set to "paper", the `x` position refers + to the distance from the left of the plotting area in + normalized coordinates where 0 (1) corresponds to the + left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. In order for absolute + positioning of the arrow to work, "axref" must be + exactly the same as "xref", otherwise "axref" will + revert to "pixel" (explained next). For relative + positioning, "axref" can be set to "pixel", in which + case the "ax" value is specified in pixels relative to + "x". Absolute positioning is useful for trendline + annotations which should continue to indicate the + correct trend when zoomed. Relative positioning is + useful for specifying the text offset for an annotated + point. + ay + Sets the y component of the arrow tail about the arrow + head. If `ayref` is `pixel`, a positive (negative) + component corresponds to an arrow pointing from bottom + to top (top to bottom). If `ayref` is not `pixel` and + is exactly the same as `yref`, this is an absolute + value on that axis, like `y`, specified in the same + coordinates as `yref`. + ayref + Indicates in what coordinates the tail of the + annotation (ax,ay) is specified. If set to a y axis id + (e.g. "y" or "y2"), the `y` position refers to a y + coordinate. If set to "paper", the `y` position refers + to the distance from the bottom of the plotting area in + normalized coordinates where 0 (1) corresponds to the + bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. In order for absolute + positioning of the arrow to work, "ayref" must be + exactly the same as "yref", otherwise "ayref" will + revert to "pixel" (explained next). For relative + positioning, "ayref" can be set to "pixel", in which + case the "ay" value is specified in pixels relative to + "y". Absolute positioning is useful for trendline + annotations which should continue to indicate the + correct trend when zoomed. Relative positioning is + useful for specifying the text offset for an annotated + point. + bgcolor + Sets the background color of the annotation. + bordercolor + Sets the color of the border enclosing the annotation + `text`. + borderpad + Sets the padding (in px) between the `text` and the + enclosing border. + borderwidth + Sets the width (in px) of the border enclosing the + annotation `text`. + captureevents + Determines whether the annotation text box captures + mouse move and click events, or allows those events to + pass through to data points in the plot that may be + behind the annotation. By default `captureevents` is + False unless `hovertext` is provided. If you use the + event `plotly_clickannotation` without `hovertext` you + must explicitly enable `captureevents`. + clicktoshow + Makes this annotation respond to clicks on the plot. If + you click a data point that exactly matches the `x` and + `y` values of this annotation, and it is hidden + (visible: false), it will appear. In "onoff" mode, you + must click the same point again to make it disappear, + so if you click multiple points, you can show multiple + annotations. In "onout" mode, a click anywhere else in + the plot (on another data point or not) will hide this + annotation. If you need to show/hide this annotation in + response to different `x` or `y` values, you can set + `xclick` and/or `yclick`. This is useful for example to + label the side of a bar. To label markers though, + `standoff` is preferred over `xclick` and `yclick`. + font + Sets the annotation text font. + height + Sets an explicit height for the text box. null + (default) lets the text set the box height. Taller text + will be clipped. + hoverlabel + :class:`plotly.graph_objects.layout.annotation.Hoverlab + el` instance or dict with compatible properties + hovertext + Sets text to appear when hovering over this annotation. + If omitted or blank, no hover label will appear. + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the annotation (text + arrow). + showarrow + Determines whether or not the annotation is drawn with + an arrow. If True, `text` is placed near the arrow's + tail. If False, `text` lines up with the `x` and `y` + provided. + standoff + Sets a distance, in pixels, to move the end arrowhead + away from the position it is pointing at, for example + to point at the edge of a marker independent of zoom. + Note that this shortens the arrow from the `ax` / `ay` + vector, in contrast to `xshift` / `yshift` which moves + everything by this amount. + startarrowhead + Sets the start annotation arrow head style. + startarrowsize + Sets the size of the start annotation arrow head, + relative to `arrowwidth`. A value of 1 (default) gives + a head about 3x as wide as the line. + startstandoff + Sets a distance, in pixels, to move the start arrowhead + away from the position it is pointing at, for example + to point at the edge of a marker independent of zoom. + Note that this shortens the arrow from the `ax` / `ay` + vector, in contrast to `xshift` / `yshift` which moves + everything by this amount. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + text + Sets the text associated with this annotation. Plotly + uses a subset of HTML tags to do things like newline + (`
`), bold (``), italics (``), + hyperlinks (``). Tags ``, + ``, ``, ``, ``, and `` are also + supported. + textangle + Sets the angle at which the `text` is drawn with + respect to the horizontal. + valign + Sets the vertical alignment of the `text` within the + box. Has an effect only if an explicit height is set to + override the text height. + visible + Determines whether or not this annotation is visible. + width + Sets an explicit width for the text box. null (default) + lets the text set the box width. Wider text will be + clipped. There is no automatic wrapping; use
to + start a new line. + x + Sets the annotation's x position. If the axis `type` is + "log", then you must take the log of your desired + range. If the axis `type` is "date", it should be date + strings, like date data, though Date objects and unix + milliseconds will be accepted and converted to strings. + If the axis `type` is "category", it should be numbers, + using the scale where each category is assigned a + serial number from zero in the order it appears. + xanchor + Sets the text box's horizontal position anchor This + anchor binds the `x` position to the "left", "center" + or "right" of the annotation. For example, if `x` is + set to 1, `xref` to "paper" and `xanchor` to "right" + then the right-most portion of the annotation lines up + with the right-most edge of the plotting area. If + "auto", the anchor is equivalent to "center" for data- + referenced annotations or if there is an arrow, whereas + for paper-referenced with no arrow, the anchor picked + corresponds to the closest side. + xclick + Toggle this annotation when clicking a data point whose + `x` value is `xclick` rather than the annotation's `x` + value. + xref + Sets the annotation's x coordinate axis. If set to a x + axis id (e.g. "x" or "x2"), the `x` position refers to + a x coordinate. If set to "paper", the `x` position + refers to the distance from the left of the plotting + area in normalized coordinates where 0 (1) corresponds + to the left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + xshift + Shifts the position of the whole annotation and arrow + to the right (positive) or left (negative) by this many + pixels. + y + Sets the annotation's y position. If the axis `type` is + "log", then you must take the log of your desired + range. If the axis `type` is "date", it should be date + strings, like date data, though Date objects and unix + milliseconds will be accepted and converted to strings. + If the axis `type` is "category", it should be numbers, + using the scale where each category is assigned a + serial number from zero in the order it appears. + yanchor + Sets the text box's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the annotation. For example, if `y` is set + to 1, `yref` to "paper" and `yanchor` to "top" then the + top-most portion of the annotation lines up with the + top-most edge of the plotting area. If "auto", the + anchor is equivalent to "middle" for data-referenced + annotations or if there is an arrow, whereas for paper- + referenced with no arrow, the anchor picked corresponds + to the closest side. + yclick + Toggle this annotation when clicking a data point whose + `y` value is `yclick` rather than the annotation's `y` + value. + yref + Sets the annotation's y coordinate axis. If set to a y + axis id (e.g. "y" or "y2"), the `y` position refers to + a y coordinate. If set to "paper", the `y` position + refers to the distance from the bottom of the plotting + area in normalized coordinates where 0 (1) corresponds + to the bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + yshift + Shifts the position of the whole annotation and arrow + up (positive) or down (negative) by this many pixels. + row + Subplot row for annotation. If 'all', addresses all + rows in the specified column(s). + col + Subplot column for annotation. If 'all', addresses all + columns in the specified row(s). + secondary_y + Whether to add annotation to secondary y-axis + exclude_empty_subplots + If True, annotation will not be added to subplots + without traces. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import layout as _layout + + new_obj = _layout.Annotation( + arg, + align=align, + arrowcolor=arrowcolor, + arrowhead=arrowhead, + arrowside=arrowside, + arrowsize=arrowsize, + arrowwidth=arrowwidth, + ax=ax, + axref=axref, + ay=ay, + ayref=ayref, + bgcolor=bgcolor, + bordercolor=bordercolor, + borderpad=borderpad, + borderwidth=borderwidth, + captureevents=captureevents, + clicktoshow=clicktoshow, + font=font, + height=height, + hoverlabel=hoverlabel, + hovertext=hovertext, + name=name, + opacity=opacity, + showarrow=showarrow, + standoff=standoff, + startarrowhead=startarrowhead, + startarrowsize=startarrowsize, + startstandoff=startstandoff, + templateitemname=templateitemname, + text=text, + textangle=textangle, + valign=valign, + visible=visible, + width=width, + x=x, + xanchor=xanchor, + xclick=xclick, + xref=xref, + xshift=xshift, + y=y, + yanchor=yanchor, + yclick=yclick, + yref=yref, + yshift=yshift, + **kwargs, + ) + return self._add_annotation_like( + "annotation", + "annotations", + new_obj, + row=row, + col=col, + secondary_y=secondary_y, + exclude_empty_subplots=exclude_empty_subplots, + ) + + def select_layout_images(self, selector=None, row=None, col=None, secondary_y=None): + """ + Select images from a particular subplot cell and/or images + that satisfy custom selection criteria. + + Parameters + ---------- + selector: dict, function, int, str, or None (default None) + Dict to use as selection criteria. + Annotations will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all images are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each image and those for which the function returned True + will be in the selection. If an int N, the Nth image matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of images to select. + To select images by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + image that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all images are selected. + secondary_y: boolean or None (default None) + * If True, only select images associated with the secondary + y-axis of the subplot. + * If False, only select images associated with the primary + y-axis of the subplot. + * If None (the default), do not filter images based on secondary + y-axis. + + To select images by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + generator + Generator that iterates through all of the images that satisfy + all of the specified selection criteria + """ + return self._select_annotations_like( + "images", selector=selector, row=row, col=col, secondary_y=secondary_y + ) + + def for_each_layout_image( + self, fn, selector=None, row=None, col=None, secondary_y=None + ): + """ + Apply a function to all images that satisfy the specified selection + criteria + + Parameters + ---------- + fn: + Function that inputs a single image object. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all images are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each image and those for which the function returned True + will be in the selection. If an int N, the Nth image matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of images to select. + To select images by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + images that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all images are selected. + secondary_y: boolean or None (default None) + * If True, only select images associated with the secondary + y-axis of the subplot. + * If False, only select images associated with the primary + y-axis of the subplot. + * If None (the default), do not filter images based on secondary + y-axis. + + To select images by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self._select_annotations_like( + prop="images", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + fn(obj) + + return self + + def update_layout_images( + self, patch=None, selector=None, row=None, col=None, secondary_y=None, **kwargs + ) -> "FigureWidget": + """ + Perform a property update operation on all images that satisfy the + specified selection criteria + + Parameters + ---------- + patch: dict or None (default None) + Dictionary of property updates to be applied to all images that + satisfy the selection criteria. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all images are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each image and those for which the function returned True + will be in the selection. If an int N, the Nth image matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of images to select. + To select images by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + image that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all images are selected. + secondary_y: boolean or None (default None) + * If True, only select images associated with the secondary + y-axis of the subplot. + * If False, only select images associated with the primary + y-axis of the subplot. + * If None (the default), do not filter images based on secondary + y-axis. + + To select images by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + **kwargs + Additional property updates to apply to each selected image. If + a property is specified in both patch and in **kwargs then the + one in **kwargs takes precedence. + + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self._select_annotations_like( + prop="images", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + obj.update(patch, **kwargs) + + return self + + def add_layout_image( + self, + arg=None, + layer=None, + name=None, + opacity=None, + sizex=None, + sizey=None, + sizing=None, + source=None, + templateitemname=None, + visible=None, + x=None, + xanchor=None, + xref=None, + y=None, + yanchor=None, + yref=None, + row=None, + col=None, + secondary_y=None, + exclude_empty_subplots=None, + **kwargs, + ) -> "FigureWidget": + """ + Create and add a new image to the figure's layout + + Parameters + ---------- + arg + instance of Image or dict with compatible properties + layer + Specifies whether images are drawn below or above + traces. When `xref` and `yref` are both set to `paper`, + image is drawn below the entire plot area. + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the image. + sizex + Sets the image container size horizontally. The image + will be sized based on the `position` value. When + `xref` is set to `paper`, units are sized relative to + the plot width. When `xref` ends with ` domain`, units + are sized relative to the axis width. + sizey + Sets the image container size vertically. The image + will be sized based on the `position` value. When + `yref` is set to `paper`, units are sized relative to + the plot height. When `yref` ends with ` domain`, units + are sized relative to the axis height. + sizing + Specifies which dimension of the image to constrain. + source + Specifies the URL of the image to be used. The URL must + be accessible from the domain where the plot code is + run, and can be either relative or absolute. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + visible + Determines whether or not this image is visible. + x + Sets the image's x position. When `xref` is set to + `paper`, units are sized relative to the plot height. + See `xref` for more info + xanchor + Sets the anchor for the x position + xref + Sets the images's x coordinate axis. If set to a x axis + id (e.g. "x" or "x2"), the `x` position refers to a x + coordinate. If set to "paper", the `x` position refers + to the distance from the left of the plotting area in + normalized coordinates where 0 (1) corresponds to the + left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + y + Sets the image's y position. When `yref` is set to + `paper`, units are sized relative to the plot height. + See `yref` for more info + yanchor + Sets the anchor for the y position. + yref + Sets the images's y coordinate axis. If set to a y axis + id (e.g. "y" or "y2"), the `y` position refers to a y + coordinate. If set to "paper", the `y` position refers + to the distance from the bottom of the plotting area in + normalized coordinates where 0 (1) corresponds to the + bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + row + Subplot row for image. If 'all', addresses all rows in + the specified column(s). + col + Subplot column for image. If 'all', addresses all + columns in the specified row(s). + secondary_y + Whether to add image to secondary y-axis + exclude_empty_subplots + If True, image will not be added to subplots without + traces. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import layout as _layout + + new_obj = _layout.Image( + arg, + layer=layer, + name=name, + opacity=opacity, + sizex=sizex, + sizey=sizey, + sizing=sizing, + source=source, + templateitemname=templateitemname, + visible=visible, + x=x, + xanchor=xanchor, + xref=xref, + y=y, + yanchor=yanchor, + yref=yref, + **kwargs, + ) + return self._add_annotation_like( + "image", + "images", + new_obj, + row=row, + col=col, + secondary_y=secondary_y, + exclude_empty_subplots=exclude_empty_subplots, + ) + + def select_selections(self, selector=None, row=None, col=None, secondary_y=None): + """ + Select selections from a particular subplot cell and/or selections + that satisfy custom selection criteria. + + Parameters + ---------- + selector: dict, function, int, str, or None (default None) + Dict to use as selection criteria. + Annotations will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all selections are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each selection and those for which the function returned True + will be in the selection. If an int N, the Nth selection matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of selections to select. + To select selections by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + selection that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all selections are selected. + secondary_y: boolean or None (default None) + * If True, only select selections associated with the secondary + y-axis of the subplot. + * If False, only select selections associated with the primary + y-axis of the subplot. + * If None (the default), do not filter selections based on secondary + y-axis. + + To select selections by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + generator + Generator that iterates through all of the selections that satisfy + all of the specified selection criteria + """ + return self._select_annotations_like( + "selections", selector=selector, row=row, col=col, secondary_y=secondary_y + ) + + def for_each_selection( + self, fn, selector=None, row=None, col=None, secondary_y=None + ): + """ + Apply a function to all selections that satisfy the specified selection + criteria + + Parameters + ---------- + fn: + Function that inputs a single selection object. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all selections are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each selection and those for which the function returned True + will be in the selection. If an int N, the Nth selection matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of selections to select. + To select selections by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + selections that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all selections are selected. + secondary_y: boolean or None (default None) + * If True, only select selections associated with the secondary + y-axis of the subplot. + * If False, only select selections associated with the primary + y-axis of the subplot. + * If None (the default), do not filter selections based on secondary + y-axis. + + To select selections by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self._select_annotations_like( + prop="selections", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + fn(obj) + + return self + + def update_selections( + self, patch=None, selector=None, row=None, col=None, secondary_y=None, **kwargs + ) -> "FigureWidget": + """ + Perform a property update operation on all selections that satisfy the + specified selection criteria + + Parameters + ---------- + patch: dict or None (default None) + Dictionary of property updates to be applied to all selections that + satisfy the selection criteria. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all selections are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each selection and those for which the function returned True + will be in the selection. If an int N, the Nth selection matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of selections to select. + To select selections by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + selection that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all selections are selected. + secondary_y: boolean or None (default None) + * If True, only select selections associated with the secondary + y-axis of the subplot. + * If False, only select selections associated with the primary + y-axis of the subplot. + * If None (the default), do not filter selections based on secondary + y-axis. + + To select selections by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + **kwargs + Additional property updates to apply to each selected selection. If + a property is specified in both patch and in **kwargs then the + one in **kwargs takes precedence. + + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self._select_annotations_like( + prop="selections", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + obj.update(patch, **kwargs) + + return self + + def add_selection( + self, + arg=None, + line=None, + name=None, + opacity=None, + path=None, + templateitemname=None, + type=None, + x0=None, + x1=None, + xref=None, + y0=None, + y1=None, + yref=None, + row=None, + col=None, + secondary_y=None, + exclude_empty_subplots=None, + **kwargs, + ) -> "FigureWidget": + """ + Create and add a new selection to the figure's layout + + Parameters + ---------- + arg + instance of Selection or dict with compatible + properties + line + :class:`plotly.graph_objects.layout.selection.Line` + instance or dict with compatible properties + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the selection. + path + For `type` "path" - a valid SVG path similar to + `shapes.path` in data coordinates. Allowed segments + are: M, L and Z. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + type + Specifies the selection type to be drawn. If "rect", a + rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), + (`x1`,`y1`) and (`x0`,`y1`). If "path", draw a custom + SVG path using `path`. + x0 + Sets the selection's starting x position. + x1 + Sets the selection's end x position. + xref + Sets the selection's x coordinate axis. If set to a x + axis id (e.g. "x" or "x2"), the `x` position refers to + a x coordinate. If set to "paper", the `x` position + refers to the distance from the left of the plotting + area in normalized coordinates where 0 (1) corresponds + to the left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + y0 + Sets the selection's starting y position. + y1 + Sets the selection's end y position. + yref + Sets the selection's x coordinate axis. If set to a y + axis id (e.g. "y" or "y2"), the `y` position refers to + a y coordinate. If set to "paper", the `y` position + refers to the distance from the bottom of the plotting + area in normalized coordinates where 0 (1) corresponds + to the bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + row + Subplot row for selection. If 'all', addresses all rows + in the specified column(s). + col + Subplot column for selection. If 'all', addresses all + columns in the specified row(s). + secondary_y + Whether to add selection to secondary y-axis + exclude_empty_subplots + If True, selection will not be added to subplots + without traces. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import layout as _layout + + new_obj = _layout.Selection( + arg, + line=line, + name=name, + opacity=opacity, + path=path, + templateitemname=templateitemname, + type=type, + x0=x0, + x1=x1, + xref=xref, + y0=y0, + y1=y1, + yref=yref, + **kwargs, + ) + return self._add_annotation_like( + "selection", + "selections", + new_obj, + row=row, + col=col, + secondary_y=secondary_y, + exclude_empty_subplots=exclude_empty_subplots, + ) + + def select_shapes(self, selector=None, row=None, col=None, secondary_y=None): + """ + Select shapes from a particular subplot cell and/or shapes + that satisfy custom selection criteria. + + Parameters + ---------- + selector: dict, function, int, str, or None (default None) + Dict to use as selection criteria. + Annotations will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all shapes are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each shape and those for which the function returned True + will be in the selection. If an int N, the Nth shape matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of shapes to select. + To select shapes by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + shape that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all shapes are selected. + secondary_y: boolean or None (default None) + * If True, only select shapes associated with the secondary + y-axis of the subplot. + * If False, only select shapes associated with the primary + y-axis of the subplot. + * If None (the default), do not filter shapes based on secondary + y-axis. + + To select shapes by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + generator + Generator that iterates through all of the shapes that satisfy + all of the specified selection criteria + """ + return self._select_annotations_like( + "shapes", selector=selector, row=row, col=col, secondary_y=secondary_y + ) + + def for_each_shape(self, fn, selector=None, row=None, col=None, secondary_y=None): + """ + Apply a function to all shapes that satisfy the specified selection + criteria + + Parameters + ---------- + fn: + Function that inputs a single shape object. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all shapes are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each shape and those for which the function returned True + will be in the selection. If an int N, the Nth shape matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of shapes to select. + To select shapes by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + shapes that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all shapes are selected. + secondary_y: boolean or None (default None) + * If True, only select shapes associated with the secondary + y-axis of the subplot. + * If False, only select shapes associated with the primary + y-axis of the subplot. + * If None (the default), do not filter shapes based on secondary + y-axis. + + To select shapes by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self._select_annotations_like( + prop="shapes", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + fn(obj) + + return self + + def update_shapes( + self, patch=None, selector=None, row=None, col=None, secondary_y=None, **kwargs + ) -> "FigureWidget": + """ + Perform a property update operation on all shapes that satisfy the + specified selection criteria + + Parameters + ---------- + patch: dict or None (default None) + Dictionary of property updates to be applied to all shapes that + satisfy the selection criteria. + selector: dict, function, int, str or None (default None) + Dict to use as selection criteria. + Traces will be selected if they contain properties corresponding + to all of the dictionary's keys, with values that exactly match + the supplied values. If None (the default), all shapes are + selected. If a function, it must be a function accepting a single + argument and returning a boolean. The function will be called on + each shape and those for which the function returned True + will be in the selection. If an int N, the Nth shape matching row + and col will be selected (N can be negative). If a string S, the selector + is equivalent to dict(type=S). + row, col: int or None (default None) + Subplot row and column index of shapes to select. + To select shapes by row and column, the Figure must have been + created using plotly.subplots.make_subplots. To select only those + shape that are in paper coordinates, set row and col to the + string 'paper'. If None (the default), all shapes are selected. + secondary_y: boolean or None (default None) + * If True, only select shapes associated with the secondary + y-axis of the subplot. + * If False, only select shapes associated with the primary + y-axis of the subplot. + * If None (the default), do not filter shapes based on secondary + y-axis. + + To select shapes by secondary y-axis, the Figure must have been + created using plotly.subplots.make_subplots. See the docstring + for the specs argument to make_subplots for more info on + creating subplots with secondary y-axes. + **kwargs + Additional property updates to apply to each selected shape. If + a property is specified in both patch and in **kwargs then the + one in **kwargs takes precedence. + + Returns + ------- + self + Returns the FigureWidget object that the method was called on + """ + for obj in self._select_annotations_like( + prop="shapes", + selector=selector, + row=row, + col=col, + secondary_y=secondary_y, + ): + obj.update(patch, **kwargs) + + return self + + def add_shape( + self, + arg=None, + editable=None, + fillcolor=None, + fillrule=None, + label=None, + layer=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + name=None, + opacity=None, + path=None, + showlegend=None, + templateitemname=None, + type=None, + visible=None, + x0=None, + x0shift=None, + x1=None, + x1shift=None, + xanchor=None, + xref=None, + xsizemode=None, + y0=None, + y0shift=None, + y1=None, + y1shift=None, + yanchor=None, + yref=None, + ysizemode=None, + row=None, + col=None, + secondary_y=None, + exclude_empty_subplots=None, + **kwargs, + ) -> "FigureWidget": + """ + Create and add a new shape to the figure's layout + + Parameters + ---------- + arg + instance of Shape or dict with compatible properties + editable + Determines whether the shape could be activated for + edit or not. Has no effect when the older editable + shapes mode is enabled via `config.editable` or + `config.edits.shapePosition`. + fillcolor + Sets the color filling the shape's interior. Only + applies to closed shapes. + fillrule + Determines which regions of complex paths constitute + the interior. For more info please visit + https://developer.mozilla.org/en- + US/docs/Web/SVG/Attribute/fill-rule + label + :class:`plotly.graph_objects.layout.shape.Label` + instance or dict with compatible properties + layer + Specifies whether shapes are drawn below gridlines + ("below"), between gridlines and traces ("between") or + above traces ("above"). + legend + Sets the reference to a legend to show this shape in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this shape. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.layout.shape.Legendgroupti + tle` instance or dict with compatible properties + legendrank + Sets the legend rank for this shape. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this shape. + line + :class:`plotly.graph_objects.layout.shape.Line` + instance or dict with compatible properties + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the shape. + path + For `type` "path" - a valid SVG path with the pixel + values replaced by data values in + `xsizemode`/`ysizemode` being "scaled" and taken + unmodified as pixels relative to `xanchor` and + `yanchor` in case of "pixel" size mode. There are a few + restrictions / quirks only absolute instructions, not + relative. So the allowed segments are: M, L, H, V, Q, + C, T, S, and Z arcs (A) are not allowed because radius + rx and ry are relative. In the future we could consider + supporting relative commands, but we would have to + decide on how to handle date and log axes. Note that + even as is, Q and C Bezier paths that are smooth on + linear axes may not be smooth on log, and vice versa. + no chained "polybezier" commands - specify the segment + type for each one. On category axes, values are numbers + scaled to the serial numbers of categories because + using the categories themselves there would be no way + to describe fractional positions On data axes: because + space and T are both normal components of path strings, + we can't use either to separate date from time parts. + Therefore we'll use underscore for this purpose: + 2015-02-21_13:45:56.789 + showlegend + Determines whether or not this shape is shown in the + legend. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + type + Specifies the shape type to be drawn. If "line", a line + is drawn from (`x0`,`y0`) to (`x1`,`y1`) with respect + to the axes' sizing mode. If "circle", a circle is + drawn from ((`x0`+`x1`)/2, (`y0`+`y1`)/2)) with radius + (|(`x0`+`x1`)/2 - `x0`|, |(`y0`+`y1`)/2 -`y0`)|) with + respect to the axes' sizing mode. If "rect", a + rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), + (`x1`,`y1`), (`x0`,`y1`), (`x0`,`y0`) with respect to + the axes' sizing mode. If "path", draw a custom SVG + path using `path`. with respect to the axes' sizing + mode. + visible + Determines whether or not this shape is visible. If + "legendonly", the shape is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x0 + Sets the shape's starting x position. See `type` and + `xsizemode` for more info. + x0shift + Shifts `x0` away from the center of the category when + `xref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + x1 + Sets the shape's end x position. See `type` and + `xsizemode` for more info. + x1shift + Shifts `x1` away from the center of the category when + `xref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + xanchor + Only relevant in conjunction with `xsizemode` set to + "pixel". Specifies the anchor point on the x axis to + which `x0`, `x1` and x coordinates within `path` are + relative to. E.g. useful to attach a pixel sized shape + to a certain data value. No effect when `xsizemode` not + set to "pixel". + xref + Sets the shape's x coordinate axis. If set to a x axis + id (e.g. "x" or "x2"), the `x` position refers to a x + coordinate. If set to "paper", the `x` position refers + to the distance from the left of the plotting area in + normalized coordinates where 0 (1) corresponds to the + left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + xsizemode + Sets the shapes's sizing mode along the x axis. If set + to "scaled", `x0`, `x1` and x coordinates within `path` + refer to data values on the x axis or a fraction of the + plot area's width (`xref` set to "paper"). If set to + "pixel", `xanchor` specifies the x position in terms of + data or plot fraction but `x0`, `x1` and x coordinates + within `path` are pixels relative to `xanchor`. This + way, the shape can have a fixed width while maintaining + a position relative to data or plot fraction. + y0 + Sets the shape's starting y position. See `type` and + `ysizemode` for more info. + y0shift + Shifts `y0` away from the center of the category when + `yref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + y1 + Sets the shape's end y position. See `type` and + `ysizemode` for more info. + y1shift + Shifts `y1` away from the center of the category when + `yref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + yanchor + Only relevant in conjunction with `ysizemode` set to + "pixel". Specifies the anchor point on the y axis to + which `y0`, `y1` and y coordinates within `path` are + relative to. E.g. useful to attach a pixel sized shape + to a certain data value. No effect when `ysizemode` not + set to "pixel". + yref + Sets the shape's y coordinate axis. If set to a y axis + id (e.g. "y" or "y2"), the `y` position refers to a y + coordinate. If set to "paper", the `y` position refers + to the distance from the bottom of the plotting area in + normalized coordinates where 0 (1) corresponds to the + bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + ysizemode + Sets the shapes's sizing mode along the y axis. If set + to "scaled", `y0`, `y1` and y coordinates within `path` + refer to data values on the y axis or a fraction of the + plot area's height (`yref` set to "paper"). If set to + "pixel", `yanchor` specifies the y position in terms of + data or plot fraction but `y0`, `y1` and y coordinates + within `path` are pixels relative to `yanchor`. This + way, the shape can have a fixed height while + maintaining a position relative to data or plot + fraction. + row + Subplot row for shape. If 'all', addresses all rows in + the specified column(s). + col + Subplot column for shape. If 'all', addresses all + columns in the specified row(s). + secondary_y + Whether to add shape to secondary y-axis + exclude_empty_subplots + If True, shape will not be added to subplots without + traces. + + Returns + ------- + FigureWidget + """ + from plotly.graph_objs import layout as _layout + + new_obj = _layout.Shape( + arg, + editable=editable, + fillcolor=fillcolor, + fillrule=fillrule, + label=label, + layer=layer, + legend=legend, + legendgroup=legendgroup, + legendgrouptitle=legendgrouptitle, + legendrank=legendrank, + legendwidth=legendwidth, + line=line, + name=name, + opacity=opacity, + path=path, + showlegend=showlegend, + templateitemname=templateitemname, + type=type, + visible=visible, + x0=x0, + x0shift=x0shift, + x1=x1, + x1shift=x1shift, + xanchor=xanchor, + xref=xref, + xsizemode=xsizemode, + y0=y0, + y0shift=y0shift, + y1=y1, + y1shift=y1shift, + yanchor=yanchor, + yref=yref, + ysizemode=ysizemode, + **kwargs, + ) + return self._add_annotation_like( + "shape", + "shapes", + new_obj, + row=row, + col=col, + secondary_y=secondary_y, + exclude_empty_subplots=exclude_empty_subplots, + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_frame.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_frame.py new file mode 100644 index 0000000000000000000000000000000000000000..703e8d244af7c68a2d33139e5bd72a1d136cd5b0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_frame.py @@ -0,0 +1,220 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseFrameHierarchyType as _BaseFrameHierarchyType +import copy as _copy + + +class Frame(_BaseFrameHierarchyType): + _parent_path_str = "" + _path_str = "frame" + _valid_props = {"baseframe", "data", "group", "layout", "name", "traces"} + + @property + def baseframe(self): + """ + The name of the frame into which this frame's properties are + merged before applying. This is used to unify properties and + avoid needing to specify the same values for the same + properties in multiple frames. + + The 'baseframe' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["baseframe"] + + @baseframe.setter + def baseframe(self, val): + self["baseframe"] = val + + @property + def data(self): + """ + A list of traces this frame modifies. The format is identical + to the normal trace definition. + + Returns + ------- + Any + """ + return self["data"] + + @data.setter + def data(self, val): + self["data"] = val + + @property + def group(self): + """ + An identifier that specifies the group to which the frame + belongs, used by animate to select a subset of frames. + + The 'group' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["group"] + + @group.setter + def group(self, val): + self["group"] = val + + @property + def layout(self): + """ + Layout properties which this frame modifies. The format is + identical to the normal layout definition. + + Returns + ------- + Any + """ + return self["layout"] + + @layout.setter + def layout(self, val): + self["layout"] = val + + @property + def name(self): + """ + A label by which to identify the frame + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def traces(self): + """ + A list of trace indices that identify the respective traces in + the data attribute + + The 'traces' property accepts values of any type + + Returns + ------- + Any + """ + return self["traces"] + + @traces.setter + def traces(self, val): + self["traces"] = val + + @property + def _prop_descriptions(self): + return """\ + baseframe + The name of the frame into which this frame's + properties are merged before applying. This is used to + unify properties and avoid needing to specify the same + values for the same properties in multiple frames. + data + A list of traces this frame modifies. The format is + identical to the normal trace definition. + group + An identifier that specifies the group to which the + frame belongs, used by animate to select a subset of + frames. + layout + Layout properties which this frame modifies. The format + is identical to the normal layout definition. + name + A label by which to identify the frame + traces + A list of trace indices that identify the respective + traces in the data attribute + """ + + def __init__( + self, + arg=None, + baseframe=None, + data=None, + group=None, + layout=None, + name=None, + traces=None, + **kwargs, + ): + """ + Construct a new Frame object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Frame` + baseframe + The name of the frame into which this frame's + properties are merged before applying. This is used to + unify properties and avoid needing to specify the same + values for the same properties in multiple frames. + data + A list of traces this frame modifies. The format is + identical to the normal trace definition. + group + An identifier that specifies the group to which the + frame belongs, used by animate to select a subset of + frames. + layout + Layout properties which this frame modifies. The format + is identical to the normal layout definition. + name + A label by which to identify the frame + traces + A list of trace indices that identify the respective + traces in the data attribute + + Returns + ------- + Frame + """ + super().__init__("frames") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Frame +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Frame`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("baseframe", arg, baseframe) + self._set_property("data", arg, data) + self._set_property("group", arg, group) + self._set_property("layout", arg, layout) + self._set_property("name", arg, name) + self._set_property("traces", arg, traces) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_funnel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_funnel.py new file mode 100644 index 0000000000000000000000000000000000000000..244c2861bbdc23b9eda8501655e33997bba44386 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_funnel.py @@ -0,0 +1,2487 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Funnel(_BaseTraceType): + _parent_path_str = "" + _path_str = "funnel" + _valid_props = { + "alignmentgroup", + "cliponaxis", + "connector", + "constraintext", + "customdata", + "customdatasrc", + "dx", + "dy", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "insidetextanchor", + "insidetextfont", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "marker", + "meta", + "metasrc", + "name", + "offset", + "offsetgroup", + "opacity", + "orientation", + "outsidetextfont", + "selectedpoints", + "showlegend", + "stream", + "text", + "textangle", + "textfont", + "textinfo", + "textposition", + "textpositionsrc", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "type", + "uid", + "uirevision", + "visible", + "width", + "x", + "x0", + "xaxis", + "xhoverformat", + "xperiod", + "xperiod0", + "xperiodalignment", + "xsrc", + "y", + "y0", + "yaxis", + "yhoverformat", + "yperiod", + "yperiod0", + "yperiodalignment", + "ysrc", + "zorder", + } + + @property + def alignmentgroup(self): + """ + Set several traces linked to the same position axis or matching + axes to the same alignmentgroup. This controls whether bars + compute their positional range dependently or independently. + + The 'alignmentgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["alignmentgroup"] + + @alignmentgroup.setter + def alignmentgroup(self, val): + self["alignmentgroup"] = val + + @property + def cliponaxis(self): + """ + Determines whether the text nodes are clipped about the subplot + axes. To show the text nodes above axis lines and tick labels, + make sure to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + + The 'cliponaxis' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cliponaxis"] + + @cliponaxis.setter + def cliponaxis(self, val): + self["cliponaxis"] = val + + @property + def connector(self): + """ + The 'connector' property is an instance of Connector + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnel.Connector` + - A dict of string/value properties that will be passed + to the Connector constructor + + Returns + ------- + plotly.graph_objs.funnel.Connector + """ + return self["connector"] + + @connector.setter + def connector(self, val): + self["connector"] = val + + @property + def constraintext(self): + """ + Constrain the size of text inside or outside a bar to be no + larger than the bar itself. + + The 'constraintext' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['inside', 'outside', 'both', 'none'] + + Returns + ------- + Any + """ + return self["constraintext"] + + @constraintext.setter + def constraintext(self, val): + self["constraintext"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def dx(self): + """ + Sets the x coordinate step. See `x0` for more info. + + The 'dx' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dx"] + + @dx.setter + def dx(self, val): + self["dx"] = val + + @property + def dy(self): + """ + Sets the y coordinate step. See `y0` for more info. + + The 'dy' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dy"] + + @dy.setter + def dy(self, val): + self["dy"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['name', 'x', 'y', 'text', 'percent initial', 'percent previous', 'percent total'] joined with '+' characters + (e.g. 'name+x') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnel.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.funnel.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables + `percentInitial`, `percentPrevious` and `percentTotal`. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each (x,y) pair. If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (x,y) coordinates. To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def insidetextanchor(self): + """ + Determines if texts are kept at center or start/end points in + `textposition` "inside" mode. + + The 'insidetextanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['end', 'middle', 'start'] + + Returns + ------- + Any + """ + return self["insidetextanchor"] + + @insidetextanchor.setter + def insidetextanchor(self, val): + self["insidetextanchor"] = val + + @property + def insidetextfont(self): + """ + Sets the font used for `text` lying inside the bar. + + The 'insidetextfont' property is an instance of Insidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnel.Insidetextfont` + - A dict of string/value properties that will be passed + to the Insidetextfont constructor + + Returns + ------- + plotly.graph_objs.funnel.Insidetextfont + """ + return self["insidetextfont"] + + @insidetextfont.setter + def insidetextfont(self, val): + self["insidetextfont"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnel.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.funnel.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnel.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.funnel.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def offset(self): + """ + Shifts the position where the bar is drawn (in position axis + units). In "group" barmode, traces that set "offset" will be + excluded and drawn in "overlay" mode instead. + + The 'offset' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["offset"] + + @offset.setter + def offset(self, val): + self["offset"] = val + + @property + def offsetgroup(self): + """ + Set several traces linked to the same position axis or matching + axes to the same offsetgroup where bars of the same position + coordinate will line up. + + The 'offsetgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["offsetgroup"] + + @offsetgroup.setter + def offsetgroup(self, val): + self["offsetgroup"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def orientation(self): + """ + Sets the orientation of the funnels. With "v" ("h"), the value + of the each bar spans along the vertical (horizontal). By + default funnels are tend to be oriented horizontally; unless + only "y" array is presented or orientation is set to "v". Also + regarding graphs including only 'horizontal' funnels, + "autorange" on the "y-axis" are set to "reversed". + + The 'orientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['v', 'h'] + + Returns + ------- + Any + """ + return self["orientation"] + + @orientation.setter + def orientation(self, val): + self["orientation"] = val + + @property + def outsidetextfont(self): + """ + Sets the font used for `text` lying outside the bar. + + The 'outsidetextfont' property is an instance of Outsidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnel.Outsidetextfont` + - A dict of string/value properties that will be passed + to the Outsidetextfont constructor + + Returns + ------- + plotly.graph_objs.funnel.Outsidetextfont + """ + return self["outsidetextfont"] + + @outsidetextfont.setter + def outsidetextfont(self, val): + self["outsidetextfont"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnel.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.funnel.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets text elements associated with each (x,y) pair. If a single + string, the same string appears over all the data points. If an + array of string, the items are mapped in order to the this + trace's (x,y) coordinates. If trace `hoverinfo` contains a + "text" flag and "hovertext" is not set, these elements will be + seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textangle(self): + """ + Sets the angle of the tick labels with respect to the bar. For + example, a `tickangle` of -90 draws the tick labels vertically. + With "auto" the texts may automatically be rotated to fit with + the maximum size in bars. + + The 'textangle' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["textangle"] + + @textangle.setter + def textangle(self, val): + self["textangle"] = val + + @property + def textfont(self): + """ + Sets the font used for `text`. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnel.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.funnel.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textinfo(self): + """ + Determines which trace information appear on the graph. In the + case of having multiple funnels, percentages & totals are + computed separately (per trace). + + The 'textinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['label', 'text', 'percent initial', 'percent previous', 'percent total', 'value'] joined with '+' characters + (e.g. 'label+text') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["textinfo"] + + @textinfo.setter + def textinfo(self, val): + self["textinfo"] = val + + @property + def textposition(self): + """ + Specifies the location of the `text`. "inside" positions `text` + inside, next to the bar end (rotated and scaled if needed). + "outside" positions `text` outside, next to the bar end (scaled + if needed), unless there is another bar stacked on this one, + then the text gets pushed inside. "auto" tries to position + `text` inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If "none", no + text appears. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['inside', 'outside', 'auto', 'none'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textpositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `textposition`. + + The 'textpositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textpositionsrc"] + + @textpositionsrc.setter + def textpositionsrc(self, val): + self["textpositionsrc"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `percentInitial`, `percentPrevious`, `percentTotal`, `label` + and `value`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def width(self): + """ + Sets the bar width (in position axis units). + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def x(self): + """ + Sets the x coordinates. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def x0(self): + """ + Alternate to `x`. Builds a linear space of x coordinates. Use + with `dx` where `x0` is the starting coordinate and `dx` the + step. + + The 'x0' property accepts values of any type + + Returns + ------- + Any + """ + return self["x0"] + + @x0.setter + def x0(self, val): + self["x0"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the x axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'xperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod"] + + @xperiod.setter + def xperiod(self, val): + self["xperiod"] = val + + @property + def xperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the x0 + axis. When `x0period` is round number of weeks, the `x0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'xperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod0"] + + @xperiod0.setter + def xperiod0(self, val): + self["xperiod0"] = val + + @property + def xperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + + The 'xperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["xperiodalignment"] + + @xperiodalignment.setter + def xperiodalignment(self, val): + self["xperiodalignment"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the y coordinates. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def y0(self): + """ + Alternate to `y`. Builds a linear space of y coordinates. Use + with `dy` where `y0` is the starting coordinate and `dy` the + step. + + The 'y0' property accepts values of any type + + Returns + ------- + Any + """ + return self["y0"] + + @y0.setter + def y0(self, val): + self["y0"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def yperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the y axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'yperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod"] + + @yperiod.setter + def yperiod(self, val): + self["yperiod"] = val + + @property + def yperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the y0 + axis. When `y0period` is round number of weeks, the `y0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'yperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod0"] + + @yperiod0.setter + def yperiod0(self, val): + self["yperiod0"] = val + + @property + def yperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + + The 'yperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["yperiodalignment"] + + @yperiodalignment.setter + def yperiodalignment(self, val): + self["yperiodalignment"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def zorder(self): + """ + Sets the layer on which this trace is displayed, relative to + other SVG traces on the same subplot. SVG traces with higher + `zorder` appear in front of those with lower `zorder`. + + The 'zorder' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["zorder"] + + @zorder.setter + def zorder(self, val): + self["zorder"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + connector + :class:`plotly.graph_objects.funnel.Connector` instance + or dict with compatible properties + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.funnel.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `percentInitial`, `percentPrevious` and + `percentTotal`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.funnel.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.funnel.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the position where the bar is drawn (in position + axis units). In "group" barmode, traces that set + "offset" will be excluded and drawn in "overlay" mode + instead. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the funnels. With "v" ("h"), + the value of the each bar spans along the vertical + (horizontal). By default funnels are tend to be + oriented horizontally; unless only "y" array is + presented or orientation is set to "v". Also regarding + graphs including only 'horizontal' funnels, "autorange" + on the "y-axis" are set to "reversed". + outsidetextfont + Sets the font used for `text` lying outside the bar. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.funnel.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the font used for `text`. + textinfo + Determines which trace information appear on the graph. + In the case of having multiple funnels, percentages & + totals are computed separately (per trace). + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `percentInitial`, `percentPrevious`, + `percentTotal`, `label` and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar width (in position axis units). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + """ + + def __init__( + self, + arg=None, + alignmentgroup=None, + cliponaxis=None, + connector=None, + constraintext=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextanchor=None, + insidetextfont=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + offset=None, + offsetgroup=None, + opacity=None, + orientation=None, + outsidetextfont=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textangle=None, + textfont=None, + textinfo=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + visible=None, + width=None, + x=None, + x0=None, + xaxis=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + zorder=None, + **kwargs, + ): + """ + Construct a new Funnel object + + Visualize stages in a process using length-encoded bars. This + trace can be used to show data in either a part-to-whole + representation wherein each item appears in a single stage, or + in a "drop-off" representation wherein each item appears in + each stage it traversed. See also the "funnelarea" trace type + for a different approach to visualizing funnel data. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Funnel` + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + connector + :class:`plotly.graph_objects.funnel.Connector` instance + or dict with compatible properties + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.funnel.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `percentInitial`, `percentPrevious` and + `percentTotal`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.funnel.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.funnel.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the position where the bar is drawn (in position + axis units). In "group" barmode, traces that set + "offset" will be excluded and drawn in "overlay" mode + instead. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the funnels. With "v" ("h"), + the value of the each bar spans along the vertical + (horizontal). By default funnels are tend to be + oriented horizontally; unless only "y" array is + presented or orientation is set to "v". Also regarding + graphs including only 'horizontal' funnels, "autorange" + on the "y-axis" are set to "reversed". + outsidetextfont + Sets the font used for `text` lying outside the bar. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.funnel.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the font used for `text`. + textinfo + Determines which trace information appear on the graph. + In the case of having multiple funnels, percentages & + totals are computed separately (per trace). + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `percentInitial`, `percentPrevious`, + `percentTotal`, `label` and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar width (in position axis units). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + + Returns + ------- + Funnel + """ + super().__init__("funnel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Funnel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Funnel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("alignmentgroup", arg, alignmentgroup) + self._set_property("cliponaxis", arg, cliponaxis) + self._set_property("connector", arg, connector) + self._set_property("constraintext", arg, constraintext) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("dx", arg, dx) + self._set_property("dy", arg, dy) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("insidetextanchor", arg, insidetextanchor) + self._set_property("insidetextfont", arg, insidetextfont) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("offset", arg, offset) + self._set_property("offsetgroup", arg, offsetgroup) + self._set_property("opacity", arg, opacity) + self._set_property("orientation", arg, orientation) + self._set_property("outsidetextfont", arg, outsidetextfont) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textangle", arg, textangle) + self._set_property("textfont", arg, textfont) + self._set_property("textinfo", arg, textinfo) + self._set_property("textposition", arg, textposition) + self._set_property("textpositionsrc", arg, textpositionsrc) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._set_property("width", arg, width) + self._set_property("x", arg, x) + self._set_property("x0", arg, x0) + self._set_property("xaxis", arg, xaxis) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xperiod", arg, xperiod) + self._set_property("xperiod0", arg, xperiod0) + self._set_property("xperiodalignment", arg, xperiodalignment) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("y0", arg, y0) + self._set_property("yaxis", arg, yaxis) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("yperiod", arg, yperiod) + self._set_property("yperiod0", arg, yperiod0) + self._set_property("yperiodalignment", arg, yperiodalignment) + self._set_property("ysrc", arg, ysrc) + self._set_property("zorder", arg, zorder) + + self._props["type"] = "funnel" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_funnelarea.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_funnelarea.py new file mode 100644 index 0000000000000000000000000000000000000000..a3db350eb990cb1477ada69a47587e85e93d6382 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_funnelarea.py @@ -0,0 +1,1734 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Funnelarea(_BaseTraceType): + _parent_path_str = "" + _path_str = "funnelarea" + _valid_props = { + "aspectratio", + "baseratio", + "customdata", + "customdatasrc", + "dlabel", + "domain", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "insidetextfont", + "label0", + "labels", + "labelssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "marker", + "meta", + "metasrc", + "name", + "opacity", + "scalegroup", + "showlegend", + "stream", + "text", + "textfont", + "textinfo", + "textposition", + "textpositionsrc", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "title", + "type", + "uid", + "uirevision", + "values", + "valuessrc", + "visible", + } + + @property + def aspectratio(self): + """ + Sets the ratio between height and width + + The 'aspectratio' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["aspectratio"] + + @aspectratio.setter + def aspectratio(self, val): + self["aspectratio"] = val + + @property + def baseratio(self): + """ + Sets the ratio between bottom length and maximum top length. + + The 'baseratio' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["baseratio"] + + @baseratio.setter + def baseratio(self, val): + self["baseratio"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def dlabel(self): + """ + Sets the label step. See `label0` for more info. + + The 'dlabel' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dlabel"] + + @dlabel.setter + def dlabel(self, val): + self["dlabel"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnelarea.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.funnelarea.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['label', 'text', 'value', 'percent', 'name'] joined with '+' characters + (e.g. 'label+text') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnelarea.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.funnelarea.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables `label`, + `color`, `value`, `text` and `percent`. Anything contained in + tag `` is displayed in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each sector. If a + single string, the same string appears for all data points. If + an array of string, the items are mapped in order of this + trace's sectors. To be seen, trace `hoverinfo` must contain a + "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def insidetextfont(self): + """ + Sets the font used for `textinfo` lying inside the sector. + + The 'insidetextfont' property is an instance of Insidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnelarea.Insidetextfont` + - A dict of string/value properties that will be passed + to the Insidetextfont constructor + + Returns + ------- + plotly.graph_objs.funnelarea.Insidetextfont + """ + return self["insidetextfont"] + + @insidetextfont.setter + def insidetextfont(self, val): + self["insidetextfont"] = val + + @property + def label0(self): + """ + Alternate to `labels`. Builds a numeric set of labels. Use with + `dlabel` where `label0` is the starting label and `dlabel` the + step. + + The 'label0' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["label0"] + + @label0.setter + def label0(self, val): + self["label0"] = val + + @property + def labels(self): + """ + Sets the sector labels. If `labels` entries are duplicated, we + sum associated `values` or simply count occurrences if `values` + is not provided. For other array attributes (including color) + we use the first non-empty entry among all occurrences of the + label. + + The 'labels' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["labels"] + + @labels.setter + def labels(self, val): + self["labels"] = val + + @property + def labelssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `labels`. + + The 'labelssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["labelssrc"] + + @labelssrc.setter + def labelssrc(self, val): + self["labelssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnelarea.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.funnelarea.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnelarea.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.funnelarea.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def scalegroup(self): + """ + If there are multiple funnelareas that should be sized + according to their totals, link them by providing a non-empty + group id here shared by every trace in the same group. + + The 'scalegroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["scalegroup"] + + @scalegroup.setter + def scalegroup(self, val): + self["scalegroup"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnelarea.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.funnelarea.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets text elements associated with each sector. If trace + `textinfo` contains a "text" flag, these elements will be seen + on the chart. If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in the + hover labels. + + The 'text' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the font used for `textinfo`. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnelarea.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.funnelarea.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textinfo(self): + """ + Determines which trace information appear on the graph. + + The 'textinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['label', 'text', 'value', 'percent'] joined with '+' characters + (e.g. 'label+text') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["textinfo"] + + @textinfo.setter + def textinfo(self, val): + self["textinfo"] = val + + @property + def textposition(self): + """ + Specifies the location of the `textinfo`. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['inside', 'none'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textpositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `textposition`. + + The 'textpositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textpositionsrc"] + + @textpositionsrc.setter + def textpositionsrc(self, val): + self["textpositionsrc"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `label`, `color`, `value`, `text` and `percent`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def title(self): + """ + The 'title' property is an instance of Title + that may be specified as: + - An instance of :class:`plotly.graph_objs.funnelarea.Title` + - A dict of string/value properties that will be passed + to the Title constructor + + Returns + ------- + plotly.graph_objs.funnelarea.Title + """ + return self["title"] + + @title.setter + def title(self, val): + self["title"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def values(self): + """ + Sets the values of the sectors. If omitted, we count + occurrences of each label. + + The 'values' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["values"] + + @values.setter + def values(self, val): + self["values"] = val + + @property + def valuessrc(self): + """ + Sets the source reference on Chart Studio Cloud for `values`. + + The 'valuessrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["valuessrc"] + + @valuessrc.setter + def valuessrc(self, val): + self["valuessrc"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + aspectratio + Sets the ratio between height and width + baseratio + Sets the ratio between bottom length and maximum top + length. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dlabel + Sets the label step. See `label0` for more info. + domain + :class:`plotly.graph_objects.funnelarea.Domain` + instance or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.funnelarea.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `text` and + `percent`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + label0 + Alternate to `labels`. Builds a numeric set of labels. + Use with `dlabel` where `label0` is the starting label + and `dlabel` the step. + labels + Sets the sector labels. If `labels` entries are + duplicated, we sum associated `values` or simply count + occurrences if `values` is not provided. For other + array attributes (including color) we use the first + non-empty entry among all occurrences of the label. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.funnelarea.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.funnelarea.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + scalegroup + If there are multiple funnelareas that should be sized + according to their totals, link them by providing a + non-empty group id here shared by every trace in the + same group. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.funnelarea.Stream` + instance or dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Specifies the location of the `textinfo`. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `text` and + `percent`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + title + :class:`plotly.graph_objects.funnelarea.Title` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values of the sectors. If omitted, we count + occurrences of each label. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + aspectratio=None, + baseratio=None, + customdata=None, + customdatasrc=None, + dlabel=None, + domain=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextfont=None, + label0=None, + labels=None, + labelssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + scalegroup=None, + showlegend=None, + stream=None, + text=None, + textfont=None, + textinfo=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + title=None, + uid=None, + uirevision=None, + values=None, + valuessrc=None, + visible=None, + **kwargs, + ): + """ + Construct a new Funnelarea object + + Visualize stages in a process using area-encoded trapezoids. + This trace can be used to show data in a part-to-whole + representation similar to a "pie" trace, wherein each item + appears in a single stage. See also the "funnel" trace type for + a different approach to visualizing funnel data. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Funnelarea` + aspectratio + Sets the ratio between height and width + baseratio + Sets the ratio between bottom length and maximum top + length. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dlabel + Sets the label step. See `label0` for more info. + domain + :class:`plotly.graph_objects.funnelarea.Domain` + instance or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.funnelarea.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `text` and + `percent`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + label0 + Alternate to `labels`. Builds a numeric set of labels. + Use with `dlabel` where `label0` is the starting label + and `dlabel` the step. + labels + Sets the sector labels. If `labels` entries are + duplicated, we sum associated `values` or simply count + occurrences if `values` is not provided. For other + array attributes (including color) we use the first + non-empty entry among all occurrences of the label. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.funnelarea.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.funnelarea.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + scalegroup + If there are multiple funnelareas that should be sized + according to their totals, link them by providing a + non-empty group id here shared by every trace in the + same group. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.funnelarea.Stream` + instance or dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Specifies the location of the `textinfo`. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `text` and + `percent`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + title + :class:`plotly.graph_objects.funnelarea.Title` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values of the sectors. If omitted, we count + occurrences of each label. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Funnelarea + """ + super().__init__("funnelarea") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Funnelarea +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Funnelarea`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("aspectratio", arg, aspectratio) + self._set_property("baseratio", arg, baseratio) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("dlabel", arg, dlabel) + self._set_property("domain", arg, domain) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("insidetextfont", arg, insidetextfont) + self._set_property("label0", arg, label0) + self._set_property("labels", arg, labels) + self._set_property("labelssrc", arg, labelssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("scalegroup", arg, scalegroup) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textinfo", arg, textinfo) + self._set_property("textposition", arg, textposition) + self._set_property("textpositionsrc", arg, textpositionsrc) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("title", arg, title) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("values", arg, values) + self._set_property("valuessrc", arg, valuessrc) + self._set_property("visible", arg, visible) + + self._props["type"] = "funnelarea" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_heatmap.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_heatmap.py new file mode 100644 index 0000000000000000000000000000000000000000..69d10f2a18acb0a7f68b17bc8a8af4b8a53e0956 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_heatmap.py @@ -0,0 +1,2626 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Heatmap(_BaseTraceType): + _parent_path_str = "" + _path_str = "heatmap" + _valid_props = { + "autocolorscale", + "coloraxis", + "colorbar", + "colorscale", + "connectgaps", + "customdata", + "customdatasrc", + "dx", + "dy", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hoverongaps", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "meta", + "metasrc", + "name", + "opacity", + "reversescale", + "showlegend", + "showscale", + "stream", + "text", + "textfont", + "textsrc", + "texttemplate", + "texttemplatefallback", + "transpose", + "type", + "uid", + "uirevision", + "visible", + "x", + "x0", + "xaxis", + "xcalendar", + "xgap", + "xhoverformat", + "xperiod", + "xperiod0", + "xperiodalignment", + "xsrc", + "xtype", + "y", + "y0", + "yaxis", + "ycalendar", + "ygap", + "yhoverformat", + "yperiod", + "yperiod0", + "yperiodalignment", + "ysrc", + "ytype", + "z", + "zauto", + "zhoverformat", + "zmax", + "zmid", + "zmin", + "zorder", + "zsmooth", + "zsrc", + } + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.heatmap.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.heatmap.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def connectgaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the `z` data are filled in. It is defaulted to true if `z` + is a one dimensional array and `zsmooth` is not false; + otherwise it is defaulted to false. + + The 'connectgaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["connectgaps"] + + @connectgaps.setter + def connectgaps(self, val): + self["connectgaps"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def dx(self): + """ + Sets the x coordinate step. See `x0` for more info. + + The 'dx' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dx"] + + @dx.setter + def dx(self, val): + self["dx"] = val + + @property + def dy(self): + """ + Sets the y coordinate step. See `y0` for more info. + + The 'dy' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dy"] + + @dy.setter + def dy(self, val): + self["dy"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.heatmap.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.heatmap.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hoverongaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the `z` data have hover labels associated with them. + + The 'hoverongaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["hoverongaps"] + + @hoverongaps.setter + def hoverongaps(self, val): + self["hoverongaps"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.heatmap.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.heatmap.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `zmin` will + correspond to the last color in the array and `zmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.heatmap.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.heatmap.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets the text elements associated with each z value. + + The 'text' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the text font. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.heatmap.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.heatmap.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `x`, `y`, `z` and `text`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def transpose(self): + """ + Transposes the z data. + + The 'transpose' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["transpose"] + + @transpose.setter + def transpose(self, val): + self["transpose"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the x coordinates. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def x0(self): + """ + Alternate to `x`. Builds a linear space of x coordinates. Use + with `dx` where `x0` is the starting coordinate and `dx` the + step. + + The 'x0' property accepts values of any type + + Returns + ------- + Any + """ + return self["x0"] + + @x0.setter + def x0(self, val): + self["x0"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def xcalendar(self): + """ + Sets the calendar system to use with `x` date data. + + The 'xcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["xcalendar"] + + @xcalendar.setter + def xcalendar(self, val): + self["xcalendar"] = val + + @property + def xgap(self): + """ + Sets the horizontal gap (in pixels) between bricks. + + The 'xgap' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["xgap"] + + @xgap.setter + def xgap(self, val): + self["xgap"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the x axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'xperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod"] + + @xperiod.setter + def xperiod(self, val): + self["xperiod"] = val + + @property + def xperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the x0 + axis. When `x0period` is round number of weeks, the `x0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'xperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod0"] + + @xperiod0.setter + def xperiod0(self, val): + self["xperiod0"] = val + + @property + def xperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + + The 'xperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["xperiodalignment"] + + @xperiodalignment.setter + def xperiodalignment(self, val): + self["xperiodalignment"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def xtype(self): + """ + If "array", the heatmap's x coordinates are given by "x" (the + default behavior when `x` is provided). If "scaled", the + heatmap's x coordinates are given by "x0" and "dx" (the default + behavior when `x` is not provided). + + The 'xtype' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['array', 'scaled'] + + Returns + ------- + Any + """ + return self["xtype"] + + @xtype.setter + def xtype(self, val): + self["xtype"] = val + + @property + def y(self): + """ + Sets the y coordinates. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def y0(self): + """ + Alternate to `y`. Builds a linear space of y coordinates. Use + with `dy` where `y0` is the starting coordinate and `dy` the + step. + + The 'y0' property accepts values of any type + + Returns + ------- + Any + """ + return self["y0"] + + @y0.setter + def y0(self, val): + self["y0"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def ycalendar(self): + """ + Sets the calendar system to use with `y` date data. + + The 'ycalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["ycalendar"] + + @ycalendar.setter + def ycalendar(self, val): + self["ycalendar"] = val + + @property + def ygap(self): + """ + Sets the vertical gap (in pixels) between bricks. + + The 'ygap' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["ygap"] + + @ygap.setter + def ygap(self, val): + self["ygap"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def yperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the y axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'yperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod"] + + @yperiod.setter + def yperiod(self, val): + self["yperiod"] = val + + @property + def yperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the y0 + axis. When `y0period` is round number of weeks, the `y0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'yperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod0"] + + @yperiod0.setter + def yperiod0(self, val): + self["yperiod0"] = val + + @property + def yperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + + The 'yperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["yperiodalignment"] + + @yperiodalignment.setter + def yperiodalignment(self, val): + self["yperiodalignment"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def ytype(self): + """ + If "array", the heatmap's y coordinates are given by "y" (the + default behavior when `y` is provided) If "scaled", the + heatmap's y coordinates are given by "y0" and "dy" (the default + behavior when `y` is not provided) + + The 'ytype' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['array', 'scaled'] + + Returns + ------- + Any + """ + return self["ytype"] + + @ytype.setter + def ytype(self, val): + self["ytype"] = val + + @property + def z(self): + """ + Sets the z data. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `z`) or the bounds set in + `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` + are set by the user. + + The 'zauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["zauto"] + + @zauto.setter + def zauto(self, val): + self["zauto"] = val + + @property + def zhoverformat(self): + """ + Sets the hover text formatting rulefor `z` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format.By + default the values are formatted using generic number format. + + The 'zhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["zhoverformat"] + + @zhoverformat.setter + def zhoverformat(self, val): + self["zhoverformat"] = val + + @property + def zmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as in `z` and if set, `zmin` must be set as well. + + The 'zmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmax"] + + @zmax.setter + def zmax(self, val): + self["zmax"] = val + + @property + def zmid(self): + """ + Sets the mid-point of the color domain by scaling `zmin` and/or + `zmax` to be equidistant to this point. Value should have the + same units as in `z`. Has no effect when `zauto` is `false`. + + The 'zmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmid"] + + @zmid.setter + def zmid(self, val): + self["zmid"] = val + + @property + def zmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as in `z` and if set, `zmax` must be set as well. + + The 'zmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmin"] + + @zmin.setter + def zmin(self, val): + self["zmin"] = val + + @property + def zorder(self): + """ + Sets the layer on which this trace is displayed, relative to + other SVG traces on the same subplot. SVG traces with higher + `zorder` appear in front of those with lower `zorder`. + + The 'zorder' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["zorder"] + + @zorder.setter + def zorder(self, val): + self["zorder"] = val + + @property + def zsmooth(self): + """ + Picks a smoothing algorithm use to smooth `z` data. + + The 'zsmooth' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fast', 'best', False] + + Returns + ------- + Any + """ + return self["zsmooth"] + + @zsmooth.setter + def zsmooth(self, val): + self["zsmooth"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.heatmap.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data are filled in. It is defaulted + to true if `z` is a one dimensional array and `zsmooth` + is not false; otherwise it is defaulted to false. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.heatmap.Hoverlabel` + instance or dict with compatible properties + hoverongaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data have hover labels associated + with them. + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.heatmap.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.heatmap.Stream` instance + or dict with compatible properties + text + Sets the text elements associated with each z value. + textfont + Sets the text font. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `x`, `y`, `z` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + transpose + Transposes the z data. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xgap + Sets the horizontal gap (in pixels) between bricks. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + xtype + If "array", the heatmap's x coordinates are given by + "x" (the default behavior when `x` is provided). If + "scaled", the heatmap's x coordinates are given by "x0" + and "dx" (the default behavior when `x` is not + provided). + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + ygap + Sets the vertical gap (in pixels) between bricks. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + ytype + If "array", the heatmap's y coordinates are given by + "y" (the default behavior when `y` is provided) If + "scaled", the heatmap's y coordinates are given by "y0" + and "dy" (the default behavior when `y` is not + provided) + z + Sets the z data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsmooth + Picks a smoothing algorithm use to smooth `z` data. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + autocolorscale=None, + coloraxis=None, + colorbar=None, + colorscale=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoverongaps=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + text=None, + textfont=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + transpose=None, + uid=None, + uirevision=None, + visible=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xgap=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + xtype=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + ygap=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + ytype=None, + z=None, + zauto=None, + zhoverformat=None, + zmax=None, + zmid=None, + zmin=None, + zorder=None, + zsmooth=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Heatmap object + + The data that describes the heatmap value-to-color mapping is + set in `z`. Data in `z` can either be a 2D list of values + (ragged or not) or a 1D array of values. In the case where `z` + is a 2D list, say that `z` has N rows and M columns. Then, by + default, the resulting heatmap will have N partitions along the + y axis and M partitions along the x axis. In other words, the + i-th row/ j-th column cell in `z` is mapped to the i-th + partition of the y axis (starting from the bottom of the plot) + and the j-th partition of the x-axis (starting from the left of + the plot). This behavior can be flipped by using `transpose`. + Moreover, `x` (`y`) can be provided with M or M+1 (N or N+1) + elements. If M (N), then the coordinates correspond to the + center of the heatmap cells and the cells have equal width. If + M+1 (N+1), then the coordinates correspond to the edges of the + heatmap cells. In the case where `z` is a 1D list, the x and y + coordinates must be provided in `x` and `y` respectively to + form data triplets. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Heatmap` + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.heatmap.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data are filled in. It is defaulted + to true if `z` is a one dimensional array and `zsmooth` + is not false; otherwise it is defaulted to false. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.heatmap.Hoverlabel` + instance or dict with compatible properties + hoverongaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data have hover labels associated + with them. + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.heatmap.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.heatmap.Stream` instance + or dict with compatible properties + text + Sets the text elements associated with each z value. + textfont + Sets the text font. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `x`, `y`, `z` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + transpose + Transposes the z data. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xgap + Sets the horizontal gap (in pixels) between bricks. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + xtype + If "array", the heatmap's x coordinates are given by + "x" (the default behavior when `x` is provided). If + "scaled", the heatmap's x coordinates are given by "x0" + and "dx" (the default behavior when `x` is not + provided). + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + ygap + Sets the vertical gap (in pixels) between bricks. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + ytype + If "array", the heatmap's y coordinates are given by + "y" (the default behavior when `y` is provided) If + "scaled", the heatmap's y coordinates are given by "y0" + and "dy" (the default behavior when `y` is not + provided) + z + Sets the z data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsmooth + Picks a smoothing algorithm use to smooth `z` data. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Heatmap + """ + super().__init__("heatmap") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Heatmap +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Heatmap`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("connectgaps", arg, connectgaps) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("dx", arg, dx) + self._set_property("dy", arg, dy) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hoverongaps", arg, hoverongaps) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("reversescale", arg, reversescale) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("transpose", arg, transpose) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("x0", arg, x0) + self._set_property("xaxis", arg, xaxis) + self._set_property("xcalendar", arg, xcalendar) + self._set_property("xgap", arg, xgap) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xperiod", arg, xperiod) + self._set_property("xperiod0", arg, xperiod0) + self._set_property("xperiodalignment", arg, xperiodalignment) + self._set_property("xsrc", arg, xsrc) + self._set_property("xtype", arg, xtype) + self._set_property("y", arg, y) + self._set_property("y0", arg, y0) + self._set_property("yaxis", arg, yaxis) + self._set_property("ycalendar", arg, ycalendar) + self._set_property("ygap", arg, ygap) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("yperiod", arg, yperiod) + self._set_property("yperiod0", arg, yperiod0) + self._set_property("yperiodalignment", arg, yperiodalignment) + self._set_property("ysrc", arg, ysrc) + self._set_property("ytype", arg, ytype) + self._set_property("z", arg, z) + self._set_property("zauto", arg, zauto) + self._set_property("zhoverformat", arg, zhoverformat) + self._set_property("zmax", arg, zmax) + self._set_property("zmid", arg, zmid) + self._set_property("zmin", arg, zmin) + self._set_property("zorder", arg, zorder) + self._set_property("zsmooth", arg, zsmooth) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "heatmap" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_histogram.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_histogram.py new file mode 100644 index 0000000000000000000000000000000000000000..f642f05be87036c2bfd27b71072524c8358977f3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_histogram.py @@ -0,0 +1,2512 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Histogram(_BaseTraceType): + _parent_path_str = "" + _path_str = "histogram" + _valid_props = { + "alignmentgroup", + "autobinx", + "autobiny", + "bingroup", + "cliponaxis", + "constraintext", + "cumulative", + "customdata", + "customdatasrc", + "error_x", + "error_y", + "histfunc", + "histnorm", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "insidetextanchor", + "insidetextfont", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "marker", + "meta", + "metasrc", + "name", + "nbinsx", + "nbinsy", + "offsetgroup", + "opacity", + "orientation", + "outsidetextfont", + "selected", + "selectedpoints", + "showlegend", + "stream", + "text", + "textangle", + "textfont", + "textposition", + "textsrc", + "texttemplate", + "texttemplatefallback", + "type", + "uid", + "uirevision", + "unselected", + "visible", + "x", + "xaxis", + "xbins", + "xcalendar", + "xhoverformat", + "xsrc", + "y", + "yaxis", + "ybins", + "ycalendar", + "yhoverformat", + "ysrc", + "zorder", + } + + @property + def alignmentgroup(self): + """ + Set several traces linked to the same position axis or matching + axes to the same alignmentgroup. This controls whether bars + compute their positional range dependently or independently. + + The 'alignmentgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["alignmentgroup"] + + @alignmentgroup.setter + def alignmentgroup(self, val): + self["alignmentgroup"] = val + + @property + def autobinx(self): + """ + Obsolete: since v1.42 each bin attribute is auto-determined + separately and `autobinx` is not needed. However, we accept + `autobinx: true` or `false` and will update `xbins` accordingly + before deleting `autobinx` from the trace. + + The 'autobinx' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autobinx"] + + @autobinx.setter + def autobinx(self, val): + self["autobinx"] = val + + @property + def autobiny(self): + """ + Obsolete: since v1.42 each bin attribute is auto-determined + separately and `autobiny` is not needed. However, we accept + `autobiny: true` or `false` and will update `ybins` accordingly + before deleting `autobiny` from the trace. + + The 'autobiny' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autobiny"] + + @autobiny.setter + def autobiny(self, val): + self["autobiny"] = val + + @property + def bingroup(self): + """ + Set a group of histogram traces which will have compatible bin + settings. Note that traces on the same subplot and with the + same "orientation" under `barmode` "stack", "relative" and + "group" are forced into the same bingroup, Using `bingroup`, + traces under `barmode` "overlay" and on different axes (of the + same axis type) can have compatible bin settings. Note that + histogram and histogram2d* trace can share the same `bingroup` + + The 'bingroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["bingroup"] + + @bingroup.setter + def bingroup(self, val): + self["bingroup"] = val + + @property + def cliponaxis(self): + """ + Determines whether the text nodes are clipped about the subplot + axes. To show the text nodes above axis lines and tick labels, + make sure to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + + The 'cliponaxis' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cliponaxis"] + + @cliponaxis.setter + def cliponaxis(self, val): + self["cliponaxis"] = val + + @property + def constraintext(self): + """ + Constrain the size of text inside or outside a bar to be no + larger than the bar itself. + + The 'constraintext' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['inside', 'outside', 'both', 'none'] + + Returns + ------- + Any + """ + return self["constraintext"] + + @constraintext.setter + def constraintext(self, val): + self["constraintext"] = val + + @property + def cumulative(self): + """ + The 'cumulative' property is an instance of Cumulative + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram.Cumulative` + - A dict of string/value properties that will be passed + to the Cumulative constructor + + Returns + ------- + plotly.graph_objs.histogram.Cumulative + """ + return self["cumulative"] + + @cumulative.setter + def cumulative(self, val): + self["cumulative"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def error_x(self): + """ + The 'error_x' property is an instance of ErrorX + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram.ErrorX` + - A dict of string/value properties that will be passed + to the ErrorX constructor + + Returns + ------- + plotly.graph_objs.histogram.ErrorX + """ + return self["error_x"] + + @error_x.setter + def error_x(self, val): + self["error_x"] = val + + @property + def error_y(self): + """ + The 'error_y' property is an instance of ErrorY + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram.ErrorY` + - A dict of string/value properties that will be passed + to the ErrorY constructor + + Returns + ------- + plotly.graph_objs.histogram.ErrorY + """ + return self["error_y"] + + @error_y.setter + def error_y(self, val): + self["error_y"] = val + + @property + def histfunc(self): + """ + Specifies the binning function used for this histogram trace. + If "count", the histogram values are computed by counting the + number of values lying inside each bin. If "sum", "avg", "min", + "max", the histogram values are computed using the sum, the + average, the minimum or the maximum of the values lying inside + each bin respectively. + + The 'histfunc' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['count', 'sum', 'avg', 'min', 'max'] + + Returns + ------- + Any + """ + return self["histfunc"] + + @histfunc.setter + def histfunc(self, val): + self["histfunc"] = val + + @property + def histnorm(self): + """ + Specifies the type of normalization used for this histogram + trace. If "", the span of each bar corresponds to the number of + occurrences (i.e. the number of data points lying inside the + bins). If "percent" / "probability", the span of each bar + corresponds to the percentage / fraction of occurrences with + respect to the total number of sample points (here, the sum of + all bin HEIGHTS equals 100% / 1). If "density", the span of + each bar corresponds to the number of occurrences in a bin + divided by the size of the bin interval (here, the sum of all + bin AREAS equals the total number of sample points). If + *probability density*, the area of each bar corresponds to the + probability that an event will fall into the corresponding bin + (here, the sum of all bin AREAS equals 1). + + The 'histnorm' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['', 'percent', 'probability', 'density', 'probability + density'] + + Returns + ------- + Any + """ + return self["histnorm"] + + @histnorm.setter + def histnorm(self, val): + self["histnorm"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.histogram.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variable `binNumber` + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def insidetextanchor(self): + """ + Determines if texts are kept at center or start/end points in + `textposition` "inside" mode. + + The 'insidetextanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['end', 'middle', 'start'] + + Returns + ------- + Any + """ + return self["insidetextanchor"] + + @insidetextanchor.setter + def insidetextanchor(self, val): + self["insidetextanchor"] = val + + @property + def insidetextfont(self): + """ + Sets the font used for `text` lying inside the bar. + + The 'insidetextfont' property is an instance of Insidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram.Insidetextfont` + - A dict of string/value properties that will be passed + to the Insidetextfont constructor + + Returns + ------- + plotly.graph_objs.histogram.Insidetextfont + """ + return self["insidetextfont"] + + @insidetextfont.setter + def insidetextfont(self, val): + self["insidetextfont"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.histogram.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.histogram.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def nbinsx(self): + """ + Specifies the maximum number of desired bins. This value will + be used in an algorithm that will decide the optimal bin size + such that the histogram best visualizes the distribution of the + data. Ignored if `xbins.size` is provided. + + The 'nbinsx' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["nbinsx"] + + @nbinsx.setter + def nbinsx(self, val): + self["nbinsx"] = val + + @property + def nbinsy(self): + """ + Specifies the maximum number of desired bins. This value will + be used in an algorithm that will decide the optimal bin size + such that the histogram best visualizes the distribution of the + data. Ignored if `ybins.size` is provided. + + The 'nbinsy' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["nbinsy"] + + @nbinsy.setter + def nbinsy(self, val): + self["nbinsy"] = val + + @property + def offsetgroup(self): + """ + Set several traces linked to the same position axis or matching + axes to the same offsetgroup where bars of the same position + coordinate will line up. + + The 'offsetgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["offsetgroup"] + + @offsetgroup.setter + def offsetgroup(self, val): + self["offsetgroup"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def orientation(self): + """ + Sets the orientation of the bars. With "v" ("h"), the value of + the each bar spans along the vertical (horizontal). + + The 'orientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['v', 'h'] + + Returns + ------- + Any + """ + return self["orientation"] + + @orientation.setter + def orientation(self, val): + self["orientation"] = val + + @property + def outsidetextfont(self): + """ + Sets the font used for `text` lying outside the bar. + + The 'outsidetextfont' property is an instance of Outsidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram.Outsidetextfont` + - A dict of string/value properties that will be passed + to the Outsidetextfont constructor + + Returns + ------- + plotly.graph_objs.histogram.Outsidetextfont + """ + return self["outsidetextfont"] + + @outsidetextfont.setter + def outsidetextfont(self, val): + self["outsidetextfont"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.histogram.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.histogram.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets hover text elements associated with each bar. If a single + string, the same string appears over all bars. If an array of + string, the items are mapped in order to the this trace's + coordinates. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textangle(self): + """ + Sets the angle of the tick labels with respect to the bar. For + example, a `tickangle` of -90 draws the tick labels vertically. + With "auto" the texts may automatically be rotated to fit with + the maximum size in bars. + + The 'textangle' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["textangle"] + + @textangle.setter + def textangle(self, val): + self["textangle"] = val + + @property + def textfont(self): + """ + Sets the text font. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.histogram.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textposition(self): + """ + Specifies the location of the `text`. "inside" positions `text` + inside, next to the bar end (rotated and scaled if needed). + "outside" positions `text` outside, next to the bar end (scaled + if needed), unless there is another bar stacked on this one, + then the text gets pushed inside. "auto" tries to position + `text` inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If "none", no + text appears. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['inside', 'outside', 'auto', 'none'] + + Returns + ------- + Any + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `label` and `value`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.histogram.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the sample data to be binned on the x axis. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def xbins(self): + """ + The 'xbins' property is an instance of XBins + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram.XBins` + - A dict of string/value properties that will be passed + to the XBins constructor + + Returns + ------- + plotly.graph_objs.histogram.XBins + """ + return self["xbins"] + + @xbins.setter + def xbins(self, val): + self["xbins"] = val + + @property + def xcalendar(self): + """ + Sets the calendar system to use with `x` date data. + + The 'xcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["xcalendar"] + + @xcalendar.setter + def xcalendar(self, val): + self["xcalendar"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the sample data to be binned on the y axis. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def ybins(self): + """ + The 'ybins' property is an instance of YBins + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram.YBins` + - A dict of string/value properties that will be passed + to the YBins constructor + + Returns + ------- + plotly.graph_objs.histogram.YBins + """ + return self["ybins"] + + @ybins.setter + def ybins(self, val): + self["ybins"] = val + + @property + def ycalendar(self): + """ + Sets the calendar system to use with `y` date data. + + The 'ycalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["ycalendar"] + + @ycalendar.setter + def ycalendar(self, val): + self["ycalendar"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def zorder(self): + """ + Sets the layer on which this trace is displayed, relative to + other SVG traces on the same subplot. SVG traces with higher + `zorder` appear in front of those with lower `zorder`. + + The 'zorder' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["zorder"] + + @zorder.setter + def zorder(self, val): + self["zorder"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + autobinx + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobinx` is not needed. + However, we accept `autobinx: true` or `false` and will + update `xbins` accordingly before deleting `autobinx` + from the trace. + autobiny + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobiny` is not needed. + However, we accept `autobiny: true` or `false` and will + update `ybins` accordingly before deleting `autobiny` + from the trace. + bingroup + Set a group of histogram traces which will have + compatible bin settings. Note that traces on the same + subplot and with the same "orientation" under `barmode` + "stack", "relative" and "group" are forced into the + same bingroup, Using `bingroup`, traces under `barmode` + "overlay" and on different axes (of the same axis type) + can have compatible bin settings. Note that histogram + and histogram2d* trace can share the same `bingroup` + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + cumulative + :class:`plotly.graph_objects.histogram.Cumulative` + instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + error_x + :class:`plotly.graph_objects.histogram.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.histogram.ErrorY` instance + or dict with compatible properties + histfunc + Specifies the binning function used for this histogram + trace. If "count", the histogram values are computed by + counting the number of values lying inside each bin. If + "sum", "avg", "min", "max", the histogram values are + computed using the sum, the average, the minimum or the + maximum of the values lying inside each bin + respectively. + histnorm + Specifies the type of normalization used for this + histogram trace. If "", the span of each bar + corresponds to the number of occurrences (i.e. the + number of data points lying inside the bins). If + "percent" / "probability", the span of each bar + corresponds to the percentage / fraction of occurrences + with respect to the total number of sample points + (here, the sum of all bin HEIGHTS equals 100% / 1). If + "density", the span of each bar corresponds to the + number of occurrences in a bin divided by the size of + the bin interval (here, the sum of all bin AREAS equals + the total number of sample points). If *probability + density*, the area of each bar corresponds to the + probability that an event will fall into the + corresponding bin (here, the sum of all bin AREAS + equals 1). + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.histogram.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `binNumber` Anything contained in tag + `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.histogram.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.histogram.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + nbinsx + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `xbins.size` is provided. + nbinsy + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `ybins.size` is provided. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the bars. With "v" ("h"), the + value of the each bar spans along the vertical + (horizontal). + outsidetextfont + Sets the font used for `text` lying outside the bar. + selected + :class:`plotly.graph_objects.histogram.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.histogram.Stream` instance + or dict with compatible properties + text + Sets hover text elements associated with each bar. If a + single string, the same string appears over all bars. + If an array of string, the items are mapped in order to + the this trace's coordinates. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the text font. + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label` and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.histogram.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the sample data to be binned on the x axis. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xbins + :class:`plotly.graph_objects.histogram.XBins` instance + or dict with compatible properties + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the sample data to be binned on the y axis. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ybins + :class:`plotly.graph_objects.histogram.YBins` instance + or dict with compatible properties + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + """ + + def __init__( + self, + arg=None, + alignmentgroup=None, + autobinx=None, + autobiny=None, + bingroup=None, + cliponaxis=None, + constraintext=None, + cumulative=None, + customdata=None, + customdatasrc=None, + error_x=None, + error_y=None, + histfunc=None, + histnorm=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextanchor=None, + insidetextfont=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + nbinsx=None, + nbinsy=None, + offsetgroup=None, + opacity=None, + orientation=None, + outsidetextfont=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textangle=None, + textfont=None, + textposition=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + x=None, + xaxis=None, + xbins=None, + xcalendar=None, + xhoverformat=None, + xsrc=None, + y=None, + yaxis=None, + ybins=None, + ycalendar=None, + yhoverformat=None, + ysrc=None, + zorder=None, + **kwargs, + ): + """ + Construct a new Histogram object + + The sample data from which statistics are computed is set in + `x` for vertically spanning histograms and in `y` for + horizontally spanning histograms. Binning options are set + `xbins` and `ybins` respectively if no aggregation data is + provided. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Histogram` + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + autobinx + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobinx` is not needed. + However, we accept `autobinx: true` or `false` and will + update `xbins` accordingly before deleting `autobinx` + from the trace. + autobiny + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobiny` is not needed. + However, we accept `autobiny: true` or `false` and will + update `ybins` accordingly before deleting `autobiny` + from the trace. + bingroup + Set a group of histogram traces which will have + compatible bin settings. Note that traces on the same + subplot and with the same "orientation" under `barmode` + "stack", "relative" and "group" are forced into the + same bingroup, Using `bingroup`, traces under `barmode` + "overlay" and on different axes (of the same axis type) + can have compatible bin settings. Note that histogram + and histogram2d* trace can share the same `bingroup` + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + cumulative + :class:`plotly.graph_objects.histogram.Cumulative` + instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + error_x + :class:`plotly.graph_objects.histogram.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.histogram.ErrorY` instance + or dict with compatible properties + histfunc + Specifies the binning function used for this histogram + trace. If "count", the histogram values are computed by + counting the number of values lying inside each bin. If + "sum", "avg", "min", "max", the histogram values are + computed using the sum, the average, the minimum or the + maximum of the values lying inside each bin + respectively. + histnorm + Specifies the type of normalization used for this + histogram trace. If "", the span of each bar + corresponds to the number of occurrences (i.e. the + number of data points lying inside the bins). If + "percent" / "probability", the span of each bar + corresponds to the percentage / fraction of occurrences + with respect to the total number of sample points + (here, the sum of all bin HEIGHTS equals 100% / 1). If + "density", the span of each bar corresponds to the + number of occurrences in a bin divided by the size of + the bin interval (here, the sum of all bin AREAS equals + the total number of sample points). If *probability + density*, the area of each bar corresponds to the + probability that an event will fall into the + corresponding bin (here, the sum of all bin AREAS + equals 1). + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.histogram.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `binNumber` Anything contained in tag + `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.histogram.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.histogram.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + nbinsx + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `xbins.size` is provided. + nbinsy + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `ybins.size` is provided. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the bars. With "v" ("h"), the + value of the each bar spans along the vertical + (horizontal). + outsidetextfont + Sets the font used for `text` lying outside the bar. + selected + :class:`plotly.graph_objects.histogram.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.histogram.Stream` instance + or dict with compatible properties + text + Sets hover text elements associated with each bar. If a + single string, the same string appears over all bars. + If an array of string, the items are mapped in order to + the this trace's coordinates. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the text font. + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label` and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.histogram.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the sample data to be binned on the x axis. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xbins + :class:`plotly.graph_objects.histogram.XBins` instance + or dict with compatible properties + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the sample data to be binned on the y axis. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ybins + :class:`plotly.graph_objects.histogram.YBins` instance + or dict with compatible properties + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + + Returns + ------- + Histogram + """ + super().__init__("histogram") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Histogram +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Histogram`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("alignmentgroup", arg, alignmentgroup) + self._set_property("autobinx", arg, autobinx) + self._set_property("autobiny", arg, autobiny) + self._set_property("bingroup", arg, bingroup) + self._set_property("cliponaxis", arg, cliponaxis) + self._set_property("constraintext", arg, constraintext) + self._set_property("cumulative", arg, cumulative) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("error_x", arg, error_x) + self._set_property("error_y", arg, error_y) + self._set_property("histfunc", arg, histfunc) + self._set_property("histnorm", arg, histnorm) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("insidetextanchor", arg, insidetextanchor) + self._set_property("insidetextfont", arg, insidetextfont) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("nbinsx", arg, nbinsx) + self._set_property("nbinsy", arg, nbinsy) + self._set_property("offsetgroup", arg, offsetgroup) + self._set_property("opacity", arg, opacity) + self._set_property("orientation", arg, orientation) + self._set_property("outsidetextfont", arg, outsidetextfont) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textangle", arg, textangle) + self._set_property("textfont", arg, textfont) + self._set_property("textposition", arg, textposition) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("xaxis", arg, xaxis) + self._set_property("xbins", arg, xbins) + self._set_property("xcalendar", arg, xcalendar) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("yaxis", arg, yaxis) + self._set_property("ybins", arg, ybins) + self._set_property("ycalendar", arg, ycalendar) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("ysrc", arg, ysrc) + self._set_property("zorder", arg, zorder) + + self._props["type"] = "histogram" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_histogram2d.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_histogram2d.py new file mode 100644 index 0000000000000000000000000000000000000000..67a70a6db6a2b308ff059753965ab326a6182a7c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_histogram2d.py @@ -0,0 +1,2459 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Histogram2d(_BaseTraceType): + _parent_path_str = "" + _path_str = "histogram2d" + _valid_props = { + "autobinx", + "autobiny", + "autocolorscale", + "bingroup", + "coloraxis", + "colorbar", + "colorscale", + "customdata", + "customdatasrc", + "histfunc", + "histnorm", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "marker", + "meta", + "metasrc", + "name", + "nbinsx", + "nbinsy", + "opacity", + "reversescale", + "showlegend", + "showscale", + "stream", + "textfont", + "texttemplate", + "texttemplatefallback", + "type", + "uid", + "uirevision", + "visible", + "x", + "xaxis", + "xbingroup", + "xbins", + "xcalendar", + "xgap", + "xhoverformat", + "xsrc", + "y", + "yaxis", + "ybingroup", + "ybins", + "ycalendar", + "ygap", + "yhoverformat", + "ysrc", + "z", + "zauto", + "zhoverformat", + "zmax", + "zmid", + "zmin", + "zsmooth", + "zsrc", + } + + @property + def autobinx(self): + """ + Obsolete: since v1.42 each bin attribute is auto-determined + separately and `autobinx` is not needed. However, we accept + `autobinx: true` or `false` and will update `xbins` accordingly + before deleting `autobinx` from the trace. + + The 'autobinx' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autobinx"] + + @autobinx.setter + def autobinx(self, val): + self["autobinx"] = val + + @property + def autobiny(self): + """ + Obsolete: since v1.42 each bin attribute is auto-determined + separately and `autobiny` is not needed. However, we accept + `autobiny: true` or `false` and will update `ybins` accordingly + before deleting `autobiny` from the trace. + + The 'autobiny' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autobiny"] + + @autobiny.setter + def autobiny(self, val): + self["autobiny"] = val + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def bingroup(self): + """ + Set the `xbingroup` and `ybingroup` default prefix For example, + setting a `bingroup` of 1 on two histogram2d traces will make + them their x-bins and y-bins match separately. + + The 'bingroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["bingroup"] + + @bingroup.setter + def bingroup(self, val): + self["bingroup"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2d.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.histogram2d.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def histfunc(self): + """ + Specifies the binning function used for this histogram trace. + If "count", the histogram values are computed by counting the + number of values lying inside each bin. If "sum", "avg", "min", + "max", the histogram values are computed using the sum, the + average, the minimum or the maximum of the values lying inside + each bin respectively. + + The 'histfunc' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['count', 'sum', 'avg', 'min', 'max'] + + Returns + ------- + Any + """ + return self["histfunc"] + + @histfunc.setter + def histfunc(self, val): + self["histfunc"] = val + + @property + def histnorm(self): + """ + Specifies the type of normalization used for this histogram + trace. If "", the span of each bar corresponds to the number of + occurrences (i.e. the number of data points lying inside the + bins). If "percent" / "probability", the span of each bar + corresponds to the percentage / fraction of occurrences with + respect to the total number of sample points (here, the sum of + all bin HEIGHTS equals 100% / 1). If "density", the span of + each bar corresponds to the number of occurrences in a bin + divided by the size of the bin interval (here, the sum of all + bin AREAS equals the total number of sample points). If + *probability density*, the area of each bar corresponds to the + probability that an event will fall into the corresponding bin + (here, the sum of all bin AREAS equals 1). + + The 'histnorm' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['', 'percent', 'probability', 'density', 'probability + density'] + + Returns + ------- + Any + """ + return self["histnorm"] + + @histnorm.setter + def histnorm(self, val): + self["histnorm"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2d.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.histogram2d.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variable `z` + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2d.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.histogram2d.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2d.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.histogram2d.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def nbinsx(self): + """ + Specifies the maximum number of desired bins. This value will + be used in an algorithm that will decide the optimal bin size + such that the histogram best visualizes the distribution of the + data. Ignored if `xbins.size` is provided. + + The 'nbinsx' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["nbinsx"] + + @nbinsx.setter + def nbinsx(self, val): + self["nbinsx"] = val + + @property + def nbinsy(self): + """ + Specifies the maximum number of desired bins. This value will + be used in an algorithm that will decide the optimal bin size + such that the histogram best visualizes the distribution of the + data. Ignored if `ybins.size` is provided. + + The 'nbinsy' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["nbinsy"] + + @nbinsy.setter + def nbinsy(self, val): + self["nbinsy"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `zmin` will + correspond to the last color in the array and `zmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2d.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.histogram2d.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def textfont(self): + """ + Sets the text font. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2d.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.histogram2d.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variable + `z` + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the sample data to be binned on the x axis. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def xbingroup(self): + """ + Set a group of histogram traces which will have compatible + x-bin settings. Using `xbingroup`, histogram2d and + histogram2dcontour traces (on axes of the same axis type) can + have compatible x-bin settings. Note that the same `xbingroup` + value can be used to set (1D) histogram `bingroup` + + The 'xbingroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xbingroup"] + + @xbingroup.setter + def xbingroup(self, val): + self["xbingroup"] = val + + @property + def xbins(self): + """ + The 'xbins' property is an instance of XBins + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2d.XBins` + - A dict of string/value properties that will be passed + to the XBins constructor + + Returns + ------- + plotly.graph_objs.histogram2d.XBins + """ + return self["xbins"] + + @xbins.setter + def xbins(self, val): + self["xbins"] = val + + @property + def xcalendar(self): + """ + Sets the calendar system to use with `x` date data. + + The 'xcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["xcalendar"] + + @xcalendar.setter + def xcalendar(self, val): + self["xcalendar"] = val + + @property + def xgap(self): + """ + Sets the horizontal gap (in pixels) between bricks. + + The 'xgap' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["xgap"] + + @xgap.setter + def xgap(self, val): + self["xgap"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the sample data to be binned on the y axis. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def ybingroup(self): + """ + Set a group of histogram traces which will have compatible + y-bin settings. Using `ybingroup`, histogram2d and + histogram2dcontour traces (on axes of the same axis type) can + have compatible y-bin settings. Note that the same `ybingroup` + value can be used to set (1D) histogram `bingroup` + + The 'ybingroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["ybingroup"] + + @ybingroup.setter + def ybingroup(self, val): + self["ybingroup"] = val + + @property + def ybins(self): + """ + The 'ybins' property is an instance of YBins + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2d.YBins` + - A dict of string/value properties that will be passed + to the YBins constructor + + Returns + ------- + plotly.graph_objs.histogram2d.YBins + """ + return self["ybins"] + + @ybins.setter + def ybins(self, val): + self["ybins"] = val + + @property + def ycalendar(self): + """ + Sets the calendar system to use with `y` date data. + + The 'ycalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["ycalendar"] + + @ycalendar.setter + def ycalendar(self, val): + self["ycalendar"] = val + + @property + def ygap(self): + """ + Sets the vertical gap (in pixels) between bricks. + + The 'ygap' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["ygap"] + + @ygap.setter + def ygap(self, val): + self["ygap"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def z(self): + """ + Sets the aggregation data. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `z`) or the bounds set in + `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` + are set by the user. + + The 'zauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["zauto"] + + @zauto.setter + def zauto(self, val): + self["zauto"] = val + + @property + def zhoverformat(self): + """ + Sets the hover text formatting rulefor `z` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format.By + default the values are formatted using generic number format. + + The 'zhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["zhoverformat"] + + @zhoverformat.setter + def zhoverformat(self, val): + self["zhoverformat"] = val + + @property + def zmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as in `z` and if set, `zmin` must be set as well. + + The 'zmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmax"] + + @zmax.setter + def zmax(self, val): + self["zmax"] = val + + @property + def zmid(self): + """ + Sets the mid-point of the color domain by scaling `zmin` and/or + `zmax` to be equidistant to this point. Value should have the + same units as in `z`. Has no effect when `zauto` is `false`. + + The 'zmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmid"] + + @zmid.setter + def zmid(self, val): + self["zmid"] = val + + @property + def zmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as in `z` and if set, `zmax` must be set as well. + + The 'zmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmin"] + + @zmin.setter + def zmin(self, val): + self["zmin"] = val + + @property + def zsmooth(self): + """ + Picks a smoothing algorithm use to smooth `z` data. + + The 'zsmooth' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fast', 'best', False] + + Returns + ------- + Any + """ + return self["zsmooth"] + + @zsmooth.setter + def zsmooth(self, val): + self["zsmooth"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + autobinx + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobinx` is not needed. + However, we accept `autobinx: true` or `false` and will + update `xbins` accordingly before deleting `autobinx` + from the trace. + autobiny + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobiny` is not needed. + However, we accept `autobiny: true` or `false` and will + update `ybins` accordingly before deleting `autobiny` + from the trace. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + bingroup + Set the `xbingroup` and `ybingroup` default prefix For + example, setting a `bingroup` of 1 on two histogram2d + traces will make them their x-bins and y-bins match + separately. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.histogram2d.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + histfunc + Specifies the binning function used for this histogram + trace. If "count", the histogram values are computed by + counting the number of values lying inside each bin. If + "sum", "avg", "min", "max", the histogram values are + computed using the sum, the average, the minimum or the + maximum of the values lying inside each bin + respectively. + histnorm + Specifies the type of normalization used for this + histogram trace. If "", the span of each bar + corresponds to the number of occurrences (i.e. the + number of data points lying inside the bins). If + "percent" / "probability", the span of each bar + corresponds to the percentage / fraction of occurrences + with respect to the total number of sample points + (here, the sum of all bin HEIGHTS equals 100% / 1). If + "density", the span of each bar corresponds to the + number of occurrences in a bin divided by the size of + the bin interval (here, the sum of all bin AREAS equals + the total number of sample points). If *probability + density*, the area of each bar corresponds to the + probability that an event will fall into the + corresponding bin (here, the sum of all bin AREAS + equals 1). + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.histogram2d.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `z` Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.histogram2d.Legendgrouptit + le` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.histogram2d.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + nbinsx + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `xbins.size` is provided. + nbinsy + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `ybins.size` is provided. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.histogram2d.Stream` + instance or dict with compatible properties + textfont + Sets the text font. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `z` + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the sample data to be binned on the x axis. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xbingroup + Set a group of histogram traces which will have + compatible x-bin settings. Using `xbingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible x-bin settings. + Note that the same `xbingroup` value can be used to set + (1D) histogram `bingroup` + xbins + :class:`plotly.graph_objects.histogram2d.XBins` + instance or dict with compatible properties + xcalendar + Sets the calendar system to use with `x` date data. + xgap + Sets the horizontal gap (in pixels) between bricks. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the sample data to be binned on the y axis. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ybingroup + Set a group of histogram traces which will have + compatible y-bin settings. Using `ybingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible y-bin settings. + Note that the same `ybingroup` value can be used to set + (1D) histogram `bingroup` + ybins + :class:`plotly.graph_objects.histogram2d.YBins` + instance or dict with compatible properties + ycalendar + Sets the calendar system to use with `y` date data. + ygap + Sets the vertical gap (in pixels) between bricks. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the aggregation data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsmooth + Picks a smoothing algorithm use to smooth `z` data. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + autobinx=None, + autobiny=None, + autocolorscale=None, + bingroup=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + histfunc=None, + histnorm=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + nbinsx=None, + nbinsy=None, + opacity=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + textfont=None, + texttemplate=None, + texttemplatefallback=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xaxis=None, + xbingroup=None, + xbins=None, + xcalendar=None, + xgap=None, + xhoverformat=None, + xsrc=None, + y=None, + yaxis=None, + ybingroup=None, + ybins=None, + ycalendar=None, + ygap=None, + yhoverformat=None, + ysrc=None, + z=None, + zauto=None, + zhoverformat=None, + zmax=None, + zmid=None, + zmin=None, + zsmooth=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Histogram2d object + + The sample data from which statistics are computed is set in + `x` and `y` (where `x` and `y` represent marginal + distributions, binning is set in `xbins` and `ybins` in this + case) or `z` (where `z` represent the 2D distribution and + binning set, binning is set by `x` and `y` in this case). The + resulting distribution is visualized as a heatmap. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Histogram2d` + autobinx + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobinx` is not needed. + However, we accept `autobinx: true` or `false` and will + update `xbins` accordingly before deleting `autobinx` + from the trace. + autobiny + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobiny` is not needed. + However, we accept `autobiny: true` or `false` and will + update `ybins` accordingly before deleting `autobiny` + from the trace. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + bingroup + Set the `xbingroup` and `ybingroup` default prefix For + example, setting a `bingroup` of 1 on two histogram2d + traces will make them their x-bins and y-bins match + separately. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.histogram2d.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + histfunc + Specifies the binning function used for this histogram + trace. If "count", the histogram values are computed by + counting the number of values lying inside each bin. If + "sum", "avg", "min", "max", the histogram values are + computed using the sum, the average, the minimum or the + maximum of the values lying inside each bin + respectively. + histnorm + Specifies the type of normalization used for this + histogram trace. If "", the span of each bar + corresponds to the number of occurrences (i.e. the + number of data points lying inside the bins). If + "percent" / "probability", the span of each bar + corresponds to the percentage / fraction of occurrences + with respect to the total number of sample points + (here, the sum of all bin HEIGHTS equals 100% / 1). If + "density", the span of each bar corresponds to the + number of occurrences in a bin divided by the size of + the bin interval (here, the sum of all bin AREAS equals + the total number of sample points). If *probability + density*, the area of each bar corresponds to the + probability that an event will fall into the + corresponding bin (here, the sum of all bin AREAS + equals 1). + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.histogram2d.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `z` Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.histogram2d.Legendgrouptit + le` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.histogram2d.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + nbinsx + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `xbins.size` is provided. + nbinsy + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `ybins.size` is provided. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.histogram2d.Stream` + instance or dict with compatible properties + textfont + Sets the text font. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `z` + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the sample data to be binned on the x axis. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xbingroup + Set a group of histogram traces which will have + compatible x-bin settings. Using `xbingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible x-bin settings. + Note that the same `xbingroup` value can be used to set + (1D) histogram `bingroup` + xbins + :class:`plotly.graph_objects.histogram2d.XBins` + instance or dict with compatible properties + xcalendar + Sets the calendar system to use with `x` date data. + xgap + Sets the horizontal gap (in pixels) between bricks. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the sample data to be binned on the y axis. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ybingroup + Set a group of histogram traces which will have + compatible y-bin settings. Using `ybingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible y-bin settings. + Note that the same `ybingroup` value can be used to set + (1D) histogram `bingroup` + ybins + :class:`plotly.graph_objects.histogram2d.YBins` + instance or dict with compatible properties + ycalendar + Sets the calendar system to use with `y` date data. + ygap + Sets the vertical gap (in pixels) between bricks. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the aggregation data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsmooth + Picks a smoothing algorithm use to smooth `z` data. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Histogram2d + """ + super().__init__("histogram2d") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Histogram2d +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Histogram2d`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autobinx", arg, autobinx) + self._set_property("autobiny", arg, autobiny) + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("bingroup", arg, bingroup) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("histfunc", arg, histfunc) + self._set_property("histnorm", arg, histnorm) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("nbinsx", arg, nbinsx) + self._set_property("nbinsy", arg, nbinsy) + self._set_property("opacity", arg, opacity) + self._set_property("reversescale", arg, reversescale) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("stream", arg, stream) + self._set_property("textfont", arg, textfont) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("xaxis", arg, xaxis) + self._set_property("xbingroup", arg, xbingroup) + self._set_property("xbins", arg, xbins) + self._set_property("xcalendar", arg, xcalendar) + self._set_property("xgap", arg, xgap) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("yaxis", arg, yaxis) + self._set_property("ybingroup", arg, ybingroup) + self._set_property("ybins", arg, ybins) + self._set_property("ycalendar", arg, ycalendar) + self._set_property("ygap", arg, ygap) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("ysrc", arg, ysrc) + self._set_property("z", arg, z) + self._set_property("zauto", arg, zauto) + self._set_property("zhoverformat", arg, zhoverformat) + self._set_property("zmax", arg, zmax) + self._set_property("zmid", arg, zmid) + self._set_property("zmin", arg, zmin) + self._set_property("zsmooth", arg, zsmooth) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "histogram2d" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_histogram2dcontour.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_histogram2dcontour.py new file mode 100644 index 0000000000000000000000000000000000000000..c36c7078033f8f2288ede095b0b53f50b484790b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_histogram2dcontour.py @@ -0,0 +1,2517 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Histogram2dContour(_BaseTraceType): + _parent_path_str = "" + _path_str = "histogram2dcontour" + _valid_props = { + "autobinx", + "autobiny", + "autocolorscale", + "autocontour", + "bingroup", + "coloraxis", + "colorbar", + "colorscale", + "contours", + "customdata", + "customdatasrc", + "histfunc", + "histnorm", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "marker", + "meta", + "metasrc", + "name", + "nbinsx", + "nbinsy", + "ncontours", + "opacity", + "reversescale", + "showlegend", + "showscale", + "stream", + "textfont", + "texttemplate", + "texttemplatefallback", + "type", + "uid", + "uirevision", + "visible", + "x", + "xaxis", + "xbingroup", + "xbins", + "xcalendar", + "xhoverformat", + "xsrc", + "y", + "yaxis", + "ybingroup", + "ybins", + "ycalendar", + "yhoverformat", + "ysrc", + "z", + "zauto", + "zhoverformat", + "zmax", + "zmid", + "zmin", + "zsrc", + } + + @property + def autobinx(self): + """ + Obsolete: since v1.42 each bin attribute is auto-determined + separately and `autobinx` is not needed. However, we accept + `autobinx: true` or `false` and will update `xbins` accordingly + before deleting `autobinx` from the trace. + + The 'autobinx' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autobinx"] + + @autobinx.setter + def autobinx(self, val): + self["autobinx"] = val + + @property + def autobiny(self): + """ + Obsolete: since v1.42 each bin attribute is auto-determined + separately and `autobiny` is not needed. However, we accept + `autobiny: true` or `false` and will update `ybins` accordingly + before deleting `autobiny` from the trace. + + The 'autobiny' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autobiny"] + + @autobiny.setter + def autobiny(self, val): + self["autobiny"] = val + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def autocontour(self): + """ + Determines whether or not the contour level attributes are + picked by an algorithm. If True, the number of contour levels + can be set in `ncontours`. If False, set the contour level + attributes in `contours`. + + The 'autocontour' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocontour"] + + @autocontour.setter + def autocontour(self, val): + self["autocontour"] = val + + @property + def bingroup(self): + """ + Set the `xbingroup` and `ybingroup` default prefix For example, + setting a `bingroup` of 1 on two histogram2d traces will make + them their x-bins and y-bins match separately. + + The 'bingroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["bingroup"] + + @bingroup.setter + def bingroup(self, val): + self["bingroup"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def contours(self): + """ + The 'contours' property is an instance of Contours + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.Contours` + - A dict of string/value properties that will be passed + to the Contours constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.Contours + """ + return self["contours"] + + @contours.setter + def contours(self, val): + self["contours"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def histfunc(self): + """ + Specifies the binning function used for this histogram trace. + If "count", the histogram values are computed by counting the + number of values lying inside each bin. If "sum", "avg", "min", + "max", the histogram values are computed using the sum, the + average, the minimum or the maximum of the values lying inside + each bin respectively. + + The 'histfunc' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['count', 'sum', 'avg', 'min', 'max'] + + Returns + ------- + Any + """ + return self["histfunc"] + + @histfunc.setter + def histfunc(self, val): + self["histfunc"] = val + + @property + def histnorm(self): + """ + Specifies the type of normalization used for this histogram + trace. If "", the span of each bar corresponds to the number of + occurrences (i.e. the number of data points lying inside the + bins). If "percent" / "probability", the span of each bar + corresponds to the percentage / fraction of occurrences with + respect to the total number of sample points (here, the sum of + all bin HEIGHTS equals 100% / 1). If "density", the span of + each bar corresponds to the number of occurrences in a bin + divided by the size of the bin interval (here, the sum of all + bin AREAS equals the total number of sample points). If + *probability density*, the area of each bar corresponds to the + probability that an event will fall into the corresponding bin + (here, the sum of all bin AREAS equals 1). + + The 'histnorm' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['', 'percent', 'probability', 'density', 'probability + density'] + + Returns + ------- + Any + """ + return self["histnorm"] + + @histnorm.setter + def histnorm(self, val): + self["histnorm"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variable `z` + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def nbinsx(self): + """ + Specifies the maximum number of desired bins. This value will + be used in an algorithm that will decide the optimal bin size + such that the histogram best visualizes the distribution of the + data. Ignored if `xbins.size` is provided. + + The 'nbinsx' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["nbinsx"] + + @nbinsx.setter + def nbinsx(self, val): + self["nbinsx"] = val + + @property + def nbinsy(self): + """ + Specifies the maximum number of desired bins. This value will + be used in an algorithm that will decide the optimal bin size + such that the histogram best visualizes the distribution of the + data. Ignored if `ybins.size` is provided. + + The 'nbinsy' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["nbinsy"] + + @nbinsy.setter + def nbinsy(self, val): + self["nbinsy"] = val + + @property + def ncontours(self): + """ + Sets the maximum number of contour levels. The actual number of + contours will be chosen automatically to be less than or equal + to the value of `ncontours`. Has an effect only if + `autocontour` is True or if `contours.size` is missing. + + The 'ncontours' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 9223372036854775807] + + Returns + ------- + int + """ + return self["ncontours"] + + @ncontours.setter + def ncontours(self, val): + self["ncontours"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `zmin` will + correspond to the last color in the array and `zmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def textfont(self): + """ + For this trace it only has an effect if `coloring` is set to + "heatmap". Sets the text font. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def texttemplate(self): + """ + For this trace it only has an effect if `coloring` is set to + "heatmap". Template string used for rendering the information + text that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, for + example "y: %{y}". Numbers are formatted using d3-format's + syntax %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `x`, `y`, `z` and `text`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the sample data to be binned on the x axis. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def xbingroup(self): + """ + Set a group of histogram traces which will have compatible + x-bin settings. Using `xbingroup`, histogram2d and + histogram2dcontour traces (on axes of the same axis type) can + have compatible x-bin settings. Note that the same `xbingroup` + value can be used to set (1D) histogram `bingroup` + + The 'xbingroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xbingroup"] + + @xbingroup.setter + def xbingroup(self, val): + self["xbingroup"] = val + + @property + def xbins(self): + """ + The 'xbins' property is an instance of XBins + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.XBins` + - A dict of string/value properties that will be passed + to the XBins constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.XBins + """ + return self["xbins"] + + @xbins.setter + def xbins(self, val): + self["xbins"] = val + + @property + def xcalendar(self): + """ + Sets the calendar system to use with `x` date data. + + The 'xcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["xcalendar"] + + @xcalendar.setter + def xcalendar(self, val): + self["xcalendar"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the sample data to be binned on the y axis. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def ybingroup(self): + """ + Set a group of histogram traces which will have compatible + y-bin settings. Using `ybingroup`, histogram2d and + histogram2dcontour traces (on axes of the same axis type) can + have compatible y-bin settings. Note that the same `ybingroup` + value can be used to set (1D) histogram `bingroup` + + The 'ybingroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["ybingroup"] + + @ybingroup.setter + def ybingroup(self, val): + self["ybingroup"] = val + + @property + def ybins(self): + """ + The 'ybins' property is an instance of YBins + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.YBins` + - A dict of string/value properties that will be passed + to the YBins constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.YBins + """ + return self["ybins"] + + @ybins.setter + def ybins(self, val): + self["ybins"] = val + + @property + def ycalendar(self): + """ + Sets the calendar system to use with `y` date data. + + The 'ycalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["ycalendar"] + + @ycalendar.setter + def ycalendar(self, val): + self["ycalendar"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def z(self): + """ + Sets the aggregation data. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `z`) or the bounds set in + `zmin` and `zmax` Defaults to `false` when `zmin` and `zmax` + are set by the user. + + The 'zauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["zauto"] + + @zauto.setter + def zauto(self, val): + self["zauto"] = val + + @property + def zhoverformat(self): + """ + Sets the hover text formatting rulefor `z` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format.By + default the values are formatted using generic number format. + + The 'zhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["zhoverformat"] + + @zhoverformat.setter + def zhoverformat(self, val): + self["zhoverformat"] = val + + @property + def zmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as in `z` and if set, `zmin` must be set as well. + + The 'zmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmax"] + + @zmax.setter + def zmax(self, val): + self["zmax"] = val + + @property + def zmid(self): + """ + Sets the mid-point of the color domain by scaling `zmin` and/or + `zmax` to be equidistant to this point. Value should have the + same units as in `z`. Has no effect when `zauto` is `false`. + + The 'zmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmid"] + + @zmid.setter + def zmid(self, val): + self["zmid"] = val + + @property + def zmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as in `z` and if set, `zmax` must be set as well. + + The 'zmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zmin"] + + @zmin.setter + def zmin(self, val): + self["zmin"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + autobinx + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobinx` is not needed. + However, we accept `autobinx: true` or `false` and will + update `xbins` accordingly before deleting `autobinx` + from the trace. + autobiny + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobiny` is not needed. + However, we accept `autobiny: true` or `false` and will + update `ybins` accordingly before deleting `autobiny` + from the trace. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + autocontour + Determines whether or not the contour level attributes + are picked by an algorithm. If True, the number of + contour levels can be set in `ncontours`. If False, set + the contour level attributes in `contours`. + bingroup + Set the `xbingroup` and `ybingroup` default prefix For + example, setting a `bingroup` of 1 on two histogram2d + traces will make them their x-bins and y-bins match + separately. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.histogram2dcontour.ColorBa + r` instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contours + :class:`plotly.graph_objects.histogram2dcontour.Contour + s` instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + histfunc + Specifies the binning function used for this histogram + trace. If "count", the histogram values are computed by + counting the number of values lying inside each bin. If + "sum", "avg", "min", "max", the histogram values are + computed using the sum, the average, the minimum or the + maximum of the values lying inside each bin + respectively. + histnorm + Specifies the type of normalization used for this + histogram trace. If "", the span of each bar + corresponds to the number of occurrences (i.e. the + number of data points lying inside the bins). If + "percent" / "probability", the span of each bar + corresponds to the percentage / fraction of occurrences + with respect to the total number of sample points + (here, the sum of all bin HEIGHTS equals 100% / 1). If + "density", the span of each bar corresponds to the + number of occurrences in a bin divided by the size of + the bin interval (here, the sum of all bin AREAS equals + the total number of sample points). If *probability + density*, the area of each bar corresponds to the + probability that an event will fall into the + corresponding bin (here, the sum of all bin AREAS + equals 1). + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.histogram2dcontour.Hoverla + bel` instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `z` Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.histogram2dcontour.Legendg + rouptitle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.histogram2dcontour.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.histogram2dcontour.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + nbinsx + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `xbins.size` is provided. + nbinsy + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `ybins.size` is provided. + ncontours + Sets the maximum number of contour levels. The actual + number of contours will be chosen automatically to be + less than or equal to the value of `ncontours`. Has an + effect only if `autocontour` is True or if + `contours.size` is missing. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.histogram2dcontour.Stream` + instance or dict with compatible properties + textfont + For this trace it only has an effect if `coloring` is + set to "heatmap". Sets the text font. + texttemplate + For this trace it only has an effect if `coloring` is + set to "heatmap". Template string used for rendering + the information text that appears on points. Note that + this will override `textinfo`. Variables are inserted + using %{variable}, for example "y: %{y}". Numbers are + formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `x`, `y`, `z` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the sample data to be binned on the x axis. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xbingroup + Set a group of histogram traces which will have + compatible x-bin settings. Using `xbingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible x-bin settings. + Note that the same `xbingroup` value can be used to set + (1D) histogram `bingroup` + xbins + :class:`plotly.graph_objects.histogram2dcontour.XBins` + instance or dict with compatible properties + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the sample data to be binned on the y axis. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ybingroup + Set a group of histogram traces which will have + compatible y-bin settings. Using `ybingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible y-bin settings. + Note that the same `ybingroup` value can be used to set + (1D) histogram `bingroup` + ybins + :class:`plotly.graph_objects.histogram2dcontour.YBins` + instance or dict with compatible properties + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the aggregation data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + autobinx=None, + autobiny=None, + autocolorscale=None, + autocontour=None, + bingroup=None, + coloraxis=None, + colorbar=None, + colorscale=None, + contours=None, + customdata=None, + customdatasrc=None, + histfunc=None, + histnorm=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + name=None, + nbinsx=None, + nbinsy=None, + ncontours=None, + opacity=None, + reversescale=None, + showlegend=None, + showscale=None, + stream=None, + textfont=None, + texttemplate=None, + texttemplatefallback=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xaxis=None, + xbingroup=None, + xbins=None, + xcalendar=None, + xhoverformat=None, + xsrc=None, + y=None, + yaxis=None, + ybingroup=None, + ybins=None, + ycalendar=None, + yhoverformat=None, + ysrc=None, + z=None, + zauto=None, + zhoverformat=None, + zmax=None, + zmid=None, + zmin=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Histogram2dContour object + + The sample data from which statistics are computed is set in + `x` and `y` (where `x` and `y` represent marginal + distributions, binning is set in `xbins` and `ybins` in this + case) or `z` (where `z` represent the 2D distribution and + binning set, binning is set by `x` and `y` in this case). The + resulting distribution is visualized as a contour plot. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.Histogram2dContour` + autobinx + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobinx` is not needed. + However, we accept `autobinx: true` or `false` and will + update `xbins` accordingly before deleting `autobinx` + from the trace. + autobiny + Obsolete: since v1.42 each bin attribute is auto- + determined separately and `autobiny` is not needed. + However, we accept `autobiny: true` or `false` and will + update `ybins` accordingly before deleting `autobiny` + from the trace. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + autocontour + Determines whether or not the contour level attributes + are picked by an algorithm. If True, the number of + contour levels can be set in `ncontours`. If False, set + the contour level attributes in `contours`. + bingroup + Set the `xbingroup` and `ybingroup` default prefix For + example, setting a `bingroup` of 1 on two histogram2d + traces will make them their x-bins and y-bins match + separately. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.histogram2dcontour.ColorBa + r` instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `zmin` and `zmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contours + :class:`plotly.graph_objects.histogram2dcontour.Contour + s` instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + histfunc + Specifies the binning function used for this histogram + trace. If "count", the histogram values are computed by + counting the number of values lying inside each bin. If + "sum", "avg", "min", "max", the histogram values are + computed using the sum, the average, the minimum or the + maximum of the values lying inside each bin + respectively. + histnorm + Specifies the type of normalization used for this + histogram trace. If "", the span of each bar + corresponds to the number of occurrences (i.e. the + number of data points lying inside the bins). If + "percent" / "probability", the span of each bar + corresponds to the percentage / fraction of occurrences + with respect to the total number of sample points + (here, the sum of all bin HEIGHTS equals 100% / 1). If + "density", the span of each bar corresponds to the + number of occurrences in a bin divided by the size of + the bin interval (here, the sum of all bin AREAS equals + the total number of sample points). If *probability + density*, the area of each bar corresponds to the + probability that an event will fall into the + corresponding bin (here, the sum of all bin AREAS + equals 1). + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.histogram2dcontour.Hoverla + bel` instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variable `z` Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.histogram2dcontour.Legendg + rouptitle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.histogram2dcontour.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.histogram2dcontour.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + nbinsx + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `xbins.size` is provided. + nbinsy + Specifies the maximum number of desired bins. This + value will be used in an algorithm that will decide the + optimal bin size such that the histogram best + visualizes the distribution of the data. Ignored if + `ybins.size` is provided. + ncontours + Sets the maximum number of contour levels. The actual + number of contours will be chosen automatically to be + less than or equal to the value of `ncontours`. Has an + effect only if `autocontour` is True or if + `contours.size` is missing. + opacity + Sets the opacity of the trace. + reversescale + Reverses the color mapping if true. If true, `zmin` + will correspond to the last color in the array and + `zmax` will correspond to the first color. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.histogram2dcontour.Stream` + instance or dict with compatible properties + textfont + For this trace it only has an effect if `coloring` is + set to "heatmap". Sets the text font. + texttemplate + For this trace it only has an effect if `coloring` is + set to "heatmap". Template string used for rendering + the information text that appears on points. Note that + this will override `textinfo`. Variables are inserted + using %{variable}, for example "y: %{y}". Numbers are + formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `x`, `y`, `z` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the sample data to be binned on the x axis. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xbingroup + Set a group of histogram traces which will have + compatible x-bin settings. Using `xbingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible x-bin settings. + Note that the same `xbingroup` value can be used to set + (1D) histogram `bingroup` + xbins + :class:`plotly.graph_objects.histogram2dcontour.XBins` + instance or dict with compatible properties + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the sample data to be binned on the y axis. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ybingroup + Set a group of histogram traces which will have + compatible y-bin settings. Using `ybingroup`, + histogram2d and histogram2dcontour traces (on axes of + the same axis type) can have compatible y-bin settings. + Note that the same `ybingroup` value can be used to set + (1D) histogram `bingroup` + ybins + :class:`plotly.graph_objects.histogram2dcontour.YBins` + instance or dict with compatible properties + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the aggregation data. + zauto + Determines whether or not the color domain is computed + with respect to the input data (here in `z`) or the + bounds set in `zmin` and `zmax` Defaults to `false` + when `zmin` and `zmax` are set by the user. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + zmax + Sets the upper bound of the color domain. Value should + have the same units as in `z` and if set, `zmin` must + be set as well. + zmid + Sets the mid-point of the color domain by scaling + `zmin` and/or `zmax` to be equidistant to this point. + Value should have the same units as in `z`. Has no + effect when `zauto` is `false`. + zmin + Sets the lower bound of the color domain. Value should + have the same units as in `z` and if set, `zmax` must + be set as well. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Histogram2dContour + """ + super().__init__("histogram2dcontour") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Histogram2dContour +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Histogram2dContour`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autobinx", arg, autobinx) + self._set_property("autobiny", arg, autobiny) + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("autocontour", arg, autocontour) + self._set_property("bingroup", arg, bingroup) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("contours", arg, contours) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("histfunc", arg, histfunc) + self._set_property("histnorm", arg, histnorm) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("nbinsx", arg, nbinsx) + self._set_property("nbinsy", arg, nbinsy) + self._set_property("ncontours", arg, ncontours) + self._set_property("opacity", arg, opacity) + self._set_property("reversescale", arg, reversescale) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("stream", arg, stream) + self._set_property("textfont", arg, textfont) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("xaxis", arg, xaxis) + self._set_property("xbingroup", arg, xbingroup) + self._set_property("xbins", arg, xbins) + self._set_property("xcalendar", arg, xcalendar) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("yaxis", arg, yaxis) + self._set_property("ybingroup", arg, ybingroup) + self._set_property("ybins", arg, ybins) + self._set_property("ycalendar", arg, ycalendar) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("ysrc", arg, ysrc) + self._set_property("z", arg, z) + self._set_property("zauto", arg, zauto) + self._set_property("zhoverformat", arg, zhoverformat) + self._set_property("zmax", arg, zmax) + self._set_property("zmid", arg, zmid) + self._set_property("zmin", arg, zmin) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "histogram2dcontour" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_icicle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_icicle.py new file mode 100644 index 0000000000000000000000000000000000000000..c1909cbe7e073b692e8fb5d4cc2c9f7c5cba3be1 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_icicle.py @@ -0,0 +1,1859 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Icicle(_BaseTraceType): + _parent_path_str = "" + _path_str = "icicle" + _valid_props = { + "branchvalues", + "count", + "customdata", + "customdatasrc", + "domain", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "insidetextfont", + "labels", + "labelssrc", + "leaf", + "legend", + "legendgrouptitle", + "legendrank", + "legendwidth", + "level", + "marker", + "maxdepth", + "meta", + "metasrc", + "name", + "opacity", + "outsidetextfont", + "parents", + "parentssrc", + "pathbar", + "root", + "sort", + "stream", + "text", + "textfont", + "textinfo", + "textposition", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "tiling", + "type", + "uid", + "uirevision", + "values", + "valuessrc", + "visible", + } + + @property + def branchvalues(self): + """ + Determines how the items in `values` are summed. When set to + "total", items in `values` are taken to be value of all its + descendants. When set to "remainder", items in `values` + corresponding to the root and the branches sectors are taken to + be the extra part not part of the sum of the values at their + leaves. + + The 'branchvalues' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['remainder', 'total'] + + Returns + ------- + Any + """ + return self["branchvalues"] + + @branchvalues.setter + def branchvalues(self, val): + self["branchvalues"] = val + + @property + def count(self): + """ + Determines default for `values` when it is not provided, by + inferring a 1 for each of the "leaves" and/or "branches", + otherwise 0. + + The 'count' property is a flaglist and may be specified + as a string containing: + - Any combination of ['branches', 'leaves'] joined with '+' characters + (e.g. 'branches+leaves') + + Returns + ------- + Any + """ + return self["count"] + + @count.setter + def count(self, val): + self["count"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.icicle.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.icicle.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['label', 'text', 'value', 'name', 'current path', 'percent root', 'percent entry', 'percent parent'] joined with '+' characters + (e.g. 'label+text') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.icicle.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.icicle.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables + `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry` + and `percentParent`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each sector. If a + single string, the same string appears for all data points. If + an array of string, the items are mapped in order of this + trace's sectors. To be seen, trace `hoverinfo` must contain a + "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def insidetextfont(self): + """ + Sets the font used for `textinfo` lying inside the sector. + + The 'insidetextfont' property is an instance of Insidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.icicle.Insidetextfont` + - A dict of string/value properties that will be passed + to the Insidetextfont constructor + + Returns + ------- + plotly.graph_objs.icicle.Insidetextfont + """ + return self["insidetextfont"] + + @insidetextfont.setter + def insidetextfont(self, val): + self["insidetextfont"] = val + + @property + def labels(self): + """ + Sets the labels of each of the sectors. + + The 'labels' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["labels"] + + @labels.setter + def labels(self, val): + self["labels"] = val + + @property + def labelssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `labels`. + + The 'labelssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["labelssrc"] + + @labelssrc.setter + def labelssrc(self, val): + self["labelssrc"] = val + + @property + def leaf(self): + """ + The 'leaf' property is an instance of Leaf + that may be specified as: + - An instance of :class:`plotly.graph_objs.icicle.Leaf` + - A dict of string/value properties that will be passed + to the Leaf constructor + + Returns + ------- + plotly.graph_objs.icicle.Leaf + """ + return self["leaf"] + + @leaf.setter + def leaf(self, val): + self["leaf"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.icicle.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.icicle.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def level(self): + """ + Sets the level from which this trace hierarchy is rendered. Set + `level` to `''` to start from the root node in the hierarchy. + Must be an "id" if `ids` is filled in, otherwise plotly + attempts to find a matching item in `labels`. + + The 'level' property accepts values of any type + + Returns + ------- + Any + """ + return self["level"] + + @level.setter + def level(self, val): + self["level"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.icicle.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.icicle.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def maxdepth(self): + """ + Sets the number of rendered sectors from any given `level`. Set + `maxdepth` to "-1" to render all the levels in the hierarchy. + + The 'maxdepth' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["maxdepth"] + + @maxdepth.setter + def maxdepth(self, val): + self["maxdepth"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def outsidetextfont(self): + """ + Sets the font used for `textinfo` lying outside the sector. + This option refers to the root of the hierarchy presented on + top left corner of a treemap graph. Please note that if a + hierarchy has multiple root nodes, this option won't have any + effect and `insidetextfont` would be used. + + The 'outsidetextfont' property is an instance of Outsidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.icicle.Outsidetextfont` + - A dict of string/value properties that will be passed + to the Outsidetextfont constructor + + Returns + ------- + plotly.graph_objs.icicle.Outsidetextfont + """ + return self["outsidetextfont"] + + @outsidetextfont.setter + def outsidetextfont(self, val): + self["outsidetextfont"] = val + + @property + def parents(self): + """ + Sets the parent sectors for each of the sectors. Empty string + items '' are understood to reference the root node in the + hierarchy. If `ids` is filled, `parents` items are understood + to be "ids" themselves. When `ids` is not set, plotly attempts + to find matching items in `labels`, but beware they must be + unique. + + The 'parents' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["parents"] + + @parents.setter + def parents(self, val): + self["parents"] = val + + @property + def parentssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `parents`. + + The 'parentssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["parentssrc"] + + @parentssrc.setter + def parentssrc(self, val): + self["parentssrc"] = val + + @property + def pathbar(self): + """ + The 'pathbar' property is an instance of Pathbar + that may be specified as: + - An instance of :class:`plotly.graph_objs.icicle.Pathbar` + - A dict of string/value properties that will be passed + to the Pathbar constructor + + Returns + ------- + plotly.graph_objs.icicle.Pathbar + """ + return self["pathbar"] + + @pathbar.setter + def pathbar(self, val): + self["pathbar"] = val + + @property + def root(self): + """ + The 'root' property is an instance of Root + that may be specified as: + - An instance of :class:`plotly.graph_objs.icicle.Root` + - A dict of string/value properties that will be passed + to the Root constructor + + Returns + ------- + plotly.graph_objs.icicle.Root + """ + return self["root"] + + @root.setter + def root(self, val): + self["root"] = val + + @property + def sort(self): + """ + Determines whether or not the sectors are reordered from + largest to smallest. + + The 'sort' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["sort"] + + @sort.setter + def sort(self, val): + self["sort"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.icicle.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.icicle.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets text elements associated with each sector. If trace + `textinfo` contains a "text" flag, these elements will be seen + on the chart. If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in the + hover labels. + + The 'text' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the font used for `textinfo`. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.icicle.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.icicle.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textinfo(self): + """ + Determines which trace information appear on the graph. + + The 'textinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['label', 'text', 'value', 'current path', 'percent root', 'percent entry', 'percent parent'] joined with '+' characters + (e.g. 'label+text') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["textinfo"] + + @textinfo.setter + def textinfo(self, val): + self["textinfo"] = val + + @property + def textposition(self): + """ + Sets the positions of the `text` elements. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top left', 'top center', 'top right', 'middle left', + 'middle center', 'middle right', 'bottom left', 'bottom + center', 'bottom right'] + + Returns + ------- + Any + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry`, + `percentParent`, `label` and `value`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def tiling(self): + """ + The 'tiling' property is an instance of Tiling + that may be specified as: + - An instance of :class:`plotly.graph_objs.icicle.Tiling` + - A dict of string/value properties that will be passed + to the Tiling constructor + + Returns + ------- + plotly.graph_objs.icicle.Tiling + """ + return self["tiling"] + + @tiling.setter + def tiling(self, val): + self["tiling"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def values(self): + """ + Sets the values associated with each of the sectors. Use with + `branchvalues` to determine how the values are summed. + + The 'values' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["values"] + + @values.setter + def values(self, val): + self["values"] = val + + @property + def valuessrc(self): + """ + Sets the source reference on Chart Studio Cloud for `values`. + + The 'valuessrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["valuessrc"] + + @valuessrc.setter + def valuessrc(self, val): + self["valuessrc"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + branchvalues + Determines how the items in `values` are summed. When + set to "total", items in `values` are taken to be value + of all its descendants. When set to "remainder", items + in `values` corresponding to the root and the branches + sectors are taken to be the extra part not part of the + sum of the values at their leaves. + count + Determines default for `values` when it is not + provided, by inferring a 1 for each of the "leaves" + and/or "branches", otherwise 0. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.icicle.Domain` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.icicle.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry` and `percentParent`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + labels + Sets the labels of each of the sectors. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + leaf + :class:`plotly.graph_objects.icicle.Leaf` instance or + dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.icicle.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + level + Sets the level from which this trace hierarchy is + rendered. Set `level` to `''` to start from the root + node in the hierarchy. Must be an "id" if `ids` is + filled in, otherwise plotly attempts to find a matching + item in `labels`. + marker + :class:`plotly.graph_objects.icicle.Marker` instance or + dict with compatible properties + maxdepth + Sets the number of rendered sectors from any given + `level`. Set `maxdepth` to "-1" to render all the + levels in the hierarchy. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. This option refers to the root of the hierarchy + presented on top left corner of a treemap graph. Please + note that if a hierarchy has multiple root nodes, this + option won't have any effect and `insidetextfont` would + be used. + parents + Sets the parent sectors for each of the sectors. Empty + string items '' are understood to reference the root + node in the hierarchy. If `ids` is filled, `parents` + items are understood to be "ids" themselves. When `ids` + is not set, plotly attempts to find matching items in + `labels`, but beware they must be unique. + parentssrc + Sets the source reference on Chart Studio Cloud for + `parents`. + pathbar + :class:`plotly.graph_objects.icicle.Pathbar` instance + or dict with compatible properties + root + :class:`plotly.graph_objects.icicle.Root` instance or + dict with compatible properties + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.icicle.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Sets the positions of the `text` elements. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry`, `percentParent`, `label` + and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + tiling + :class:`plotly.graph_objects.icicle.Tiling` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values associated with each of the sectors. + Use with `branchvalues` to determine how the values are + summed. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + branchvalues=None, + count=None, + customdata=None, + customdatasrc=None, + domain=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextfont=None, + labels=None, + labelssrc=None, + leaf=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + level=None, + marker=None, + maxdepth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + outsidetextfont=None, + parents=None, + parentssrc=None, + pathbar=None, + root=None, + sort=None, + stream=None, + text=None, + textfont=None, + textinfo=None, + textposition=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + tiling=None, + uid=None, + uirevision=None, + values=None, + valuessrc=None, + visible=None, + **kwargs, + ): + """ + Construct a new Icicle object + + Visualize hierarchal data from leaves (and/or outer branches) + towards root with rectangles. The icicle sectors are determined + by the entries in "labels" or "ids" and in "parents". + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Icicle` + branchvalues + Determines how the items in `values` are summed. When + set to "total", items in `values` are taken to be value + of all its descendants. When set to "remainder", items + in `values` corresponding to the root and the branches + sectors are taken to be the extra part not part of the + sum of the values at their leaves. + count + Determines default for `values` when it is not + provided, by inferring a 1 for each of the "leaves" + and/or "branches", otherwise 0. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.icicle.Domain` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.icicle.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry` and `percentParent`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + labels + Sets the labels of each of the sectors. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + leaf + :class:`plotly.graph_objects.icicle.Leaf` instance or + dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.icicle.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + level + Sets the level from which this trace hierarchy is + rendered. Set `level` to `''` to start from the root + node in the hierarchy. Must be an "id" if `ids` is + filled in, otherwise plotly attempts to find a matching + item in `labels`. + marker + :class:`plotly.graph_objects.icicle.Marker` instance or + dict with compatible properties + maxdepth + Sets the number of rendered sectors from any given + `level`. Set `maxdepth` to "-1" to render all the + levels in the hierarchy. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. This option refers to the root of the hierarchy + presented on top left corner of a treemap graph. Please + note that if a hierarchy has multiple root nodes, this + option won't have any effect and `insidetextfont` would + be used. + parents + Sets the parent sectors for each of the sectors. Empty + string items '' are understood to reference the root + node in the hierarchy. If `ids` is filled, `parents` + items are understood to be "ids" themselves. When `ids` + is not set, plotly attempts to find matching items in + `labels`, but beware they must be unique. + parentssrc + Sets the source reference on Chart Studio Cloud for + `parents`. + pathbar + :class:`plotly.graph_objects.icicle.Pathbar` instance + or dict with compatible properties + root + :class:`plotly.graph_objects.icicle.Root` instance or + dict with compatible properties + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.icicle.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Sets the positions of the `text` elements. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry`, `percentParent`, `label` + and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + tiling + :class:`plotly.graph_objects.icicle.Tiling` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values associated with each of the sectors. + Use with `branchvalues` to determine how the values are + summed. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Icicle + """ + super().__init__("icicle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Icicle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Icicle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("branchvalues", arg, branchvalues) + self._set_property("count", arg, count) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("domain", arg, domain) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("insidetextfont", arg, insidetextfont) + self._set_property("labels", arg, labels) + self._set_property("labelssrc", arg, labelssrc) + self._set_property("leaf", arg, leaf) + self._set_property("legend", arg, legend) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("level", arg, level) + self._set_property("marker", arg, marker) + self._set_property("maxdepth", arg, maxdepth) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("outsidetextfont", arg, outsidetextfont) + self._set_property("parents", arg, parents) + self._set_property("parentssrc", arg, parentssrc) + self._set_property("pathbar", arg, pathbar) + self._set_property("root", arg, root) + self._set_property("sort", arg, sort) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textinfo", arg, textinfo) + self._set_property("textposition", arg, textposition) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("tiling", arg, tiling) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("values", arg, values) + self._set_property("valuessrc", arg, valuessrc) + self._set_property("visible", arg, visible) + + self._props["type"] = "icicle" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_image.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_image.py new file mode 100644 index 0000000000000000000000000000000000000000..e1ebdbe36fe262e65765066bd2e9ac7e07fc9142 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_image.py @@ -0,0 +1,1503 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Image(_BaseTraceType): + _parent_path_str = "" + _path_str = "image" + _valid_props = { + "colormodel", + "customdata", + "customdatasrc", + "dx", + "dy", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgrouptitle", + "legendrank", + "legendwidth", + "meta", + "metasrc", + "name", + "opacity", + "source", + "stream", + "text", + "textsrc", + "type", + "uid", + "uirevision", + "visible", + "x0", + "xaxis", + "y0", + "yaxis", + "z", + "zmax", + "zmin", + "zorder", + "zsmooth", + "zsrc", + } + + @property + def colormodel(self): + """ + Color model used to map the numerical color components + described in `z` into colors. If `source` is specified, this + attribute will be set to `rgba256` otherwise it defaults to + `rgb`. + + The 'colormodel' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['rgb', 'rgba', 'rgba256', 'hsl', 'hsla'] + + Returns + ------- + Any + """ + return self["colormodel"] + + @colormodel.setter + def colormodel(self, val): + self["colormodel"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def dx(self): + """ + Set the pixel's horizontal size. + + The 'dx' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dx"] + + @dx.setter + def dx(self, val): + self["dx"] = val + + @property + def dy(self): + """ + Set the pixel's vertical size + + The 'dy' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dy"] + + @dy.setter + def dy(self, val): + self["dy"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'color', 'name', 'text'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.image.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.image.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables `z`, + `color` and `colormodel`. Anything contained in tag `` + is displayed in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.image.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.image.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def source(self): + """ + Specifies the data URI of the image to be visualized. The URI + consists of "data:image/[][;base64\\]," + + The 'source' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["source"] + + @source.setter + def source(self, val): + self["source"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.image.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.image.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets the text elements associated with each z value. + + The 'text' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x0(self): + """ + Set the image's x position. The left edge of the image (or the + right edge if the x axis is reversed or dx is negative) will be + found at xmin=x0-dx/2 + + The 'x0' property accepts values of any type + + Returns + ------- + Any + """ + return self["x0"] + + @x0.setter + def x0(self, val): + self["x0"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def y0(self): + """ + Set the image's y position. The top edge of the image (or the + bottom edge if the y axis is NOT reversed or if dy is negative) + will be found at ymin=y0-dy/2. By default when an image trace + is included, the y axis will be reversed so that the image is + right-side-up, but you can disable this by setting + yaxis.autorange=true or by providing an explicit y axis range. + + The 'y0' property accepts values of any type + + Returns + ------- + Any + """ + return self["y0"] + + @y0.setter + def y0(self, val): + self["y0"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def z(self): + """ + A 2-dimensional array in which each element is an array of 3 or + 4 numbers representing a color. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zmax(self): + """ + Array defining the higher bound for each color component. Note + that the default value will depend on the colormodel. For the + `rgb` colormodel, it is [255, 255, 255]. For the `rgba` + colormodel, it is [255, 255, 255, 1]. For the `rgba256` + colormodel, it is [255, 255, 255, 255]. For the `hsl` + colormodel, it is [360, 100, 100]. For the `hsla` colormodel, + it is [360, 100, 100, 1]. + + The 'zmax' property is an info array that may be specified as: + + * a list or tuple of 4 elements where: + (0) The 'zmax[0]' property is a number and may be specified as: + - An int or float + (1) The 'zmax[1]' property is a number and may be specified as: + - An int or float + (2) The 'zmax[2]' property is a number and may be specified as: + - An int or float + (3) The 'zmax[3]' property is a number and may be specified as: + - An int or float + + Returns + ------- + list + """ + return self["zmax"] + + @zmax.setter + def zmax(self, val): + self["zmax"] = val + + @property + def zmin(self): + """ + Array defining the lower bound for each color component. Note + that the default value will depend on the colormodel. For the + `rgb` colormodel, it is [0, 0, 0]. For the `rgba` colormodel, + it is [0, 0, 0, 0]. For the `rgba256` colormodel, it is [0, 0, + 0, 0]. For the `hsl` colormodel, it is [0, 0, 0]. For the + `hsla` colormodel, it is [0, 0, 0, 0]. + + The 'zmin' property is an info array that may be specified as: + + * a list or tuple of 4 elements where: + (0) The 'zmin[0]' property is a number and may be specified as: + - An int or float + (1) The 'zmin[1]' property is a number and may be specified as: + - An int or float + (2) The 'zmin[2]' property is a number and may be specified as: + - An int or float + (3) The 'zmin[3]' property is a number and may be specified as: + - An int or float + + Returns + ------- + list + """ + return self["zmin"] + + @zmin.setter + def zmin(self, val): + self["zmin"] = val + + @property + def zorder(self): + """ + Sets the layer on which this trace is displayed, relative to + other SVG traces on the same subplot. SVG traces with higher + `zorder` appear in front of those with lower `zorder`. + + The 'zorder' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["zorder"] + + @zorder.setter + def zorder(self, val): + self["zorder"] = val + + @property + def zsmooth(self): + """ + Picks a smoothing algorithm used to smooth `z` data. This only + applies for image traces that use the `source` attribute. + + The 'zsmooth' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fast', False] + + Returns + ------- + Any + """ + return self["zsmooth"] + + @zsmooth.setter + def zsmooth(self, val): + self["zsmooth"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + colormodel + Color model used to map the numerical color components + described in `z` into colors. If `source` is specified, + this attribute will be set to `rgba256` otherwise it + defaults to `rgb`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Set the pixel's horizontal size. + dy + Set the pixel's vertical size + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.image.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `z`, `color` and `colormodel`. Anything + contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.image.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + source + Specifies the data URI of the image to be visualized. + The URI consists of "data:image/[][;base64\\]," + stream + :class:`plotly.graph_objects.image.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with each z value. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x0 + Set the image's x position. The left edge of the image + (or the right edge if the x axis is reversed or dx is + negative) will be found at xmin=x0-dx/2 + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + y0 + Set the image's y position. The top edge of the image + (or the bottom edge if the y axis is NOT reversed or if + dy is negative) will be found at ymin=y0-dy/2. By + default when an image trace is included, the y axis + will be reversed so that the image is right-side-up, + but you can disable this by setting + yaxis.autorange=true or by providing an explicit y axis + range. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + z + A 2-dimensional array in which each element is an array + of 3 or 4 numbers representing a color. + zmax + Array defining the higher bound for each color + component. Note that the default value will depend on + the colormodel. For the `rgb` colormodel, it is [255, + 255, 255]. For the `rgba` colormodel, it is [255, 255, + 255, 1]. For the `rgba256` colormodel, it is [255, 255, + 255, 255]. For the `hsl` colormodel, it is [360, 100, + 100]. For the `hsla` colormodel, it is [360, 100, 100, + 1]. + zmin + Array defining the lower bound for each color + component. Note that the default value will depend on + the colormodel. For the `rgb` colormodel, it is [0, 0, + 0]. For the `rgba` colormodel, it is [0, 0, 0, 0]. For + the `rgba256` colormodel, it is [0, 0, 0, 0]. For the + `hsl` colormodel, it is [0, 0, 0]. For the `hsla` + colormodel, it is [0, 0, 0, 0]. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsmooth + Picks a smoothing algorithm used to smooth `z` data. + This only applies for image traces that use the + `source` attribute. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + colormodel=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + source=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + visible=None, + x0=None, + xaxis=None, + y0=None, + yaxis=None, + z=None, + zmax=None, + zmin=None, + zorder=None, + zsmooth=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Image object + + Display an image, i.e. data on a 2D regular raster. By default, + when an image is displayed in a subplot, its y axis will be + reversed (ie. `autorange: 'reversed'`), constrained to the + domain (ie. `constrain: 'domain'`) and it will have the same + scale as its x axis (ie. `scaleanchor: 'x,`) in order for + pixels to be rendered as squares. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Image` + colormodel + Color model used to map the numerical color components + described in `z` into colors. If `source` is specified, + this attribute will be set to `rgba256` otherwise it + defaults to `rgb`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Set the pixel's horizontal size. + dy + Set the pixel's vertical size + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.image.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `z`, `color` and `colormodel`. Anything + contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.image.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + source + Specifies the data URI of the image to be visualized. + The URI consists of "data:image/[][;base64\\]," + stream + :class:`plotly.graph_objects.image.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with each z value. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x0 + Set the image's x position. The left edge of the image + (or the right edge if the x axis is reversed or dx is + negative) will be found at xmin=x0-dx/2 + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + y0 + Set the image's y position. The top edge of the image + (or the bottom edge if the y axis is NOT reversed or if + dy is negative) will be found at ymin=y0-dy/2. By + default when an image trace is included, the y axis + will be reversed so that the image is right-side-up, + but you can disable this by setting + yaxis.autorange=true or by providing an explicit y axis + range. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + z + A 2-dimensional array in which each element is an array + of 3 or 4 numbers representing a color. + zmax + Array defining the higher bound for each color + component. Note that the default value will depend on + the colormodel. For the `rgb` colormodel, it is [255, + 255, 255]. For the `rgba` colormodel, it is [255, 255, + 255, 1]. For the `rgba256` colormodel, it is [255, 255, + 255, 255]. For the `hsl` colormodel, it is [360, 100, + 100]. For the `hsla` colormodel, it is [360, 100, 100, + 1]. + zmin + Array defining the lower bound for each color + component. Note that the default value will depend on + the colormodel. For the `rgb` colormodel, it is [0, 0, + 0]. For the `rgba` colormodel, it is [0, 0, 0, 0]. For + the `rgba256` colormodel, it is [0, 0, 0, 0]. For the + `hsl` colormodel, it is [0, 0, 0]. For the `hsla` + colormodel, it is [0, 0, 0, 0]. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + zsmooth + Picks a smoothing algorithm used to smooth `z` data. + This only applies for image traces that use the + `source` attribute. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Image + """ + super().__init__("image") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Image +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Image`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("colormodel", arg, colormodel) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("dx", arg, dx) + self._set_property("dy", arg, dy) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("source", arg, source) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._set_property("x0", arg, x0) + self._set_property("xaxis", arg, xaxis) + self._set_property("y0", arg, y0) + self._set_property("yaxis", arg, yaxis) + self._set_property("z", arg, z) + self._set_property("zmax", arg, zmax) + self._set_property("zmin", arg, zmin) + self._set_property("zorder", arg, zorder) + self._set_property("zsmooth", arg, zsmooth) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "image" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_indicator.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_indicator.py new file mode 100644 index 0000000000000000000000000000000000000000..e54f53442e7b21bd894d66164c31bb3a9ae9880f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_indicator.py @@ -0,0 +1,848 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Indicator(_BaseTraceType): + _parent_path_str = "" + _path_str = "indicator" + _valid_props = { + "align", + "customdata", + "customdatasrc", + "delta", + "domain", + "gauge", + "ids", + "idssrc", + "legend", + "legendgrouptitle", + "legendrank", + "legendwidth", + "meta", + "metasrc", + "mode", + "name", + "number", + "stream", + "title", + "type", + "uid", + "uirevision", + "value", + "visible", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the `text` within the box. + Note that this attribute has no effect if an angular gauge is + displayed: in this case, it is always centered + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'center', 'right'] + + Returns + ------- + Any + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def delta(self): + """ + The 'delta' property is an instance of Delta + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.Delta` + - A dict of string/value properties that will be passed + to the Delta constructor + + Returns + ------- + plotly.graph_objs.indicator.Delta + """ + return self["delta"] + + @delta.setter + def delta(self, val): + self["delta"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.indicator.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def gauge(self): + """ + The gauge of the Indicator plot. + + The 'gauge' property is an instance of Gauge + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.Gauge` + - A dict of string/value properties that will be passed + to the Gauge constructor + + Returns + ------- + plotly.graph_objs.indicator.Gauge + """ + return self["gauge"] + + @gauge.setter + def gauge(self, val): + self["gauge"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.indicator.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def mode(self): + """ + Determines how the value is displayed on the graph. `number` + displays the value numerically in text. `delta` displays the + difference to a reference value in text. Finally, `gauge` + displays the value graphically on an axis. + + The 'mode' property is a flaglist and may be specified + as a string containing: + - Any combination of ['number', 'delta', 'gauge'] joined with '+' characters + (e.g. 'number+delta') + + Returns + ------- + Any + """ + return self["mode"] + + @mode.setter + def mode(self, val): + self["mode"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def number(self): + """ + The 'number' property is an instance of Number + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.Number` + - A dict of string/value properties that will be passed + to the Number constructor + + Returns + ------- + plotly.graph_objs.indicator.Number + """ + return self["number"] + + @number.setter + def number(self, val): + self["number"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.indicator.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def title(self): + """ + The 'title' property is an instance of Title + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.Title` + - A dict of string/value properties that will be passed + to the Title constructor + + Returns + ------- + plotly.graph_objs.indicator.Title + """ + return self["title"] + + @title.setter + def title(self, val): + self["title"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def value(self): + """ + Sets the number to be displayed. + + The 'value' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["value"] + + @value.setter + def value(self, val): + self["value"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the `text` within the + box. Note that this attribute has no effect if an + angular gauge is displayed: in this case, it is always + centered + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + delta + :class:`plotly.graph_objects.indicator.Delta` instance + or dict with compatible properties + domain + :class:`plotly.graph_objects.indicator.Domain` instance + or dict with compatible properties + gauge + The gauge of the Indicator plot. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.indicator.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines how the value is displayed on the graph. + `number` displays the value numerically in text. + `delta` displays the difference to a reference value in + text. Finally, `gauge` displays the value graphically + on an axis. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + number + :class:`plotly.graph_objects.indicator.Number` instance + or dict with compatible properties + stream + :class:`plotly.graph_objects.indicator.Stream` instance + or dict with compatible properties + title + :class:`plotly.graph_objects.indicator.Title` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + value + Sets the number to be displayed. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + align=None, + customdata=None, + customdatasrc=None, + delta=None, + domain=None, + gauge=None, + ids=None, + idssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + meta=None, + metasrc=None, + mode=None, + name=None, + number=None, + stream=None, + title=None, + uid=None, + uirevision=None, + value=None, + visible=None, + **kwargs, + ): + """ + Construct a new Indicator object + + An indicator is used to visualize a single `value` along with + some contextual information such as `steps` or a `threshold`, + using a combination of three visual elements: a number, a + delta, and/or a gauge. Deltas are taken with respect to a + `reference`. Gauges can be either angular or bullet (aka + linear) gauges. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Indicator` + align + Sets the horizontal alignment of the `text` within the + box. Note that this attribute has no effect if an + angular gauge is displayed: in this case, it is always + centered + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + delta + :class:`plotly.graph_objects.indicator.Delta` instance + or dict with compatible properties + domain + :class:`plotly.graph_objects.indicator.Domain` instance + or dict with compatible properties + gauge + The gauge of the Indicator plot. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.indicator.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines how the value is displayed on the graph. + `number` displays the value numerically in text. + `delta` displays the difference to a reference value in + text. Finally, `gauge` displays the value graphically + on an axis. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + number + :class:`plotly.graph_objects.indicator.Number` instance + or dict with compatible properties + stream + :class:`plotly.graph_objects.indicator.Stream` instance + or dict with compatible properties + title + :class:`plotly.graph_objects.indicator.Title` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + value + Sets the number to be displayed. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Indicator + """ + super().__init__("indicator") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Indicator +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Indicator`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("delta", arg, delta) + self._set_property("domain", arg, domain) + self._set_property("gauge", arg, gauge) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("mode", arg, mode) + self._set_property("name", arg, name) + self._set_property("number", arg, number) + self._set_property("stream", arg, stream) + self._set_property("title", arg, title) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("value", arg, value) + self._set_property("visible", arg, visible) + + self._props["type"] = "indicator" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_isosurface.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_isosurface.py new file mode 100644 index 0000000000000000000000000000000000000000..f68216dcfbd61aef34b272ecdc9deb2cb17d20ce --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_isosurface.py @@ -0,0 +1,2210 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Isosurface(_BaseTraceType): + _parent_path_str = "" + _path_str = "isosurface" + _valid_props = { + "autocolorscale", + "caps", + "cauto", + "cmax", + "cmid", + "cmin", + "coloraxis", + "colorbar", + "colorscale", + "contour", + "customdata", + "customdatasrc", + "flatshading", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "isomax", + "isomin", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "lighting", + "lightposition", + "meta", + "metasrc", + "name", + "opacity", + "reversescale", + "scene", + "showlegend", + "showscale", + "slices", + "spaceframe", + "stream", + "surface", + "text", + "textsrc", + "type", + "uid", + "uirevision", + "value", + "valuehoverformat", + "valuesrc", + "visible", + "x", + "xhoverformat", + "xsrc", + "y", + "yhoverformat", + "ysrc", + "z", + "zhoverformat", + "zsrc", + } + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def caps(self): + """ + The 'caps' property is an instance of Caps + that may be specified as: + - An instance of :class:`plotly.graph_objs.isosurface.Caps` + - A dict of string/value properties that will be passed + to the Caps constructor + + Returns + ------- + plotly.graph_objs.isosurface.Caps + """ + return self["caps"] + + @caps.setter + def caps(self, val): + self["caps"] = val + + @property + def cauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here `value`) or the bounds set in + `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` + are set by the user. + + The 'cauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cauto"] + + @cauto.setter + def cauto(self, val): + self["cauto"] = val + + @property + def cmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as `value` and if set, `cmin` must be set as well. + + The 'cmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmax"] + + @cmax.setter + def cmax(self, val): + self["cmax"] = val + + @property + def cmid(self): + """ + Sets the mid-point of the color domain by scaling `cmin` and/or + `cmax` to be equidistant to this point. Value should have the + same units as `value`. Has no effect when `cauto` is `false`. + + The 'cmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmid"] + + @cmid.setter + def cmid(self, val): + self["cmid"] = val + + @property + def cmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as `value` and if set, `cmax` must be set as well. + + The 'cmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmin"] + + @cmin.setter + def cmin(self, val): + self["cmin"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.isosurface.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.isosurface.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def contour(self): + """ + The 'contour' property is an instance of Contour + that may be specified as: + - An instance of :class:`plotly.graph_objs.isosurface.Contour` + - A dict of string/value properties that will be passed + to the Contour constructor + + Returns + ------- + plotly.graph_objs.isosurface.Contour + """ + return self["contour"] + + @contour.setter + def contour(self, val): + self["contour"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def flatshading(self): + """ + Determines whether or not normal smoothing is applied to the + meshes, creating meshes with an angular, low-poly look via flat + reflections. + + The 'flatshading' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["flatshading"] + + @flatshading.setter + def flatshading(self, val): + self["flatshading"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.isosurface.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.isosurface.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def isomax(self): + """ + Sets the maximum boundary for iso-surface plot. + + The 'isomax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["isomax"] + + @isomax.setter + def isomax(self, val): + self["isomax"] = val + + @property + def isomin(self): + """ + Sets the minimum boundary for iso-surface plot. + + The 'isomin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["isomin"] + + @isomin.setter + def isomin(self, val): + self["isomin"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.isosurface.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.isosurface.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def lighting(self): + """ + The 'lighting' property is an instance of Lighting + that may be specified as: + - An instance of :class:`plotly.graph_objs.isosurface.Lighting` + - A dict of string/value properties that will be passed + to the Lighting constructor + + Returns + ------- + plotly.graph_objs.isosurface.Lighting + """ + return self["lighting"] + + @lighting.setter + def lighting(self, val): + self["lighting"] = val + + @property + def lightposition(self): + """ + The 'lightposition' property is an instance of Lightposition + that may be specified as: + - An instance of :class:`plotly.graph_objs.isosurface.Lightposition` + - A dict of string/value properties that will be passed + to the Lightposition constructor + + Returns + ------- + plotly.graph_objs.isosurface.Lightposition + """ + return self["lightposition"] + + @lightposition.setter + def lightposition(self, val): + self["lightposition"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the surface. Please note that in the case + of using high `opacity` values for example a value greater than + or equal to 0.5 on two surfaces (and 0.25 with four surfaces), + an overlay of multiple transparent surfaces may not perfectly + be sorted in depth by the webgl API. This behavior may be + improved in the near future and is subject to change. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `cmin` will + correspond to the last color in the array and `cmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def scene(self): + """ + Sets a reference between this trace's 3D coordinate system and + a 3D scene. If "scene" (the default value), the (x,y,z) + coordinates refer to `layout.scene`. If "scene2", the (x,y,z) + coordinates refer to `layout.scene2`, and so on. + + The 'scene' property is an identifier of a particular + subplot, of type 'scene', that may be specified as: + - the string 'scene' optionally followed by an integer >= 1 + (e.g. 'scene', 'scene1', 'scene2', 'scene3', etc.) + + Returns + ------- + str + """ + return self["scene"] + + @scene.setter + def scene(self, val): + self["scene"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def slices(self): + """ + The 'slices' property is an instance of Slices + that may be specified as: + - An instance of :class:`plotly.graph_objs.isosurface.Slices` + - A dict of string/value properties that will be passed + to the Slices constructor + + Returns + ------- + plotly.graph_objs.isosurface.Slices + """ + return self["slices"] + + @slices.setter + def slices(self, val): + self["slices"] = val + + @property + def spaceframe(self): + """ + The 'spaceframe' property is an instance of Spaceframe + that may be specified as: + - An instance of :class:`plotly.graph_objs.isosurface.Spaceframe` + - A dict of string/value properties that will be passed + to the Spaceframe constructor + + Returns + ------- + plotly.graph_objs.isosurface.Spaceframe + """ + return self["spaceframe"] + + @spaceframe.setter + def spaceframe(self, val): + self["spaceframe"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.isosurface.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.isosurface.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def surface(self): + """ + The 'surface' property is an instance of Surface + that may be specified as: + - An instance of :class:`plotly.graph_objs.isosurface.Surface` + - A dict of string/value properties that will be passed + to the Surface constructor + + Returns + ------- + plotly.graph_objs.isosurface.Surface + """ + return self["surface"] + + @surface.setter + def surface(self, val): + self["surface"] = val + + @property + def text(self): + """ + Sets the text elements associated with the vertices. If trace + `hoverinfo` contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def value(self): + """ + Sets the 4th dimension (value) of the vertices. + + The 'value' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["value"] + + @value.setter + def value(self, val): + self["value"] = val + + @property + def valuehoverformat(self): + """ + Sets the hover text formatting rulefor `value` using d3 + formatting mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format.By + default the values are formatted using generic number format. + + The 'valuehoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["valuehoverformat"] + + @valuehoverformat.setter + def valuehoverformat(self, val): + self["valuehoverformat"] = val + + @property + def valuesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `value`. + + The 'valuesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["valuesrc"] + + @valuesrc.setter + def valuesrc(self, val): + self["valuesrc"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the X coordinates of the vertices on X axis. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the Y coordinates of the vertices on Y axis. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def z(self): + """ + Sets the Z coordinates of the vertices on Z axis. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zhoverformat(self): + """ + Sets the hover text formatting rulefor `z` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `zaxis.hoverformat`. + + The 'zhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["zhoverformat"] + + @zhoverformat.setter + def zhoverformat(self, val): + self["zhoverformat"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + caps + :class:`plotly.graph_objects.isosurface.Caps` instance + or dict with compatible properties + cauto + Determines whether or not the color domain is computed + with respect to the input data (here `value`) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as `value` and if set, `cmin` must + be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as `value`. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as `value` and if set, `cmax` must + be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.isosurface.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contour + :class:`plotly.graph_objects.isosurface.Contour` + instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + flatshading + Determines whether or not normal smoothing is applied + to the meshes, creating meshes with an angular, low- + poly look via flat reflections. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.isosurface.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + isomax + Sets the maximum boundary for iso-surface plot. + isomin + Sets the minimum boundary for iso-surface plot. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.isosurface.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.isosurface.Lighting` + instance or dict with compatible properties + lightposition + :class:`plotly.graph_objects.isosurface.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + slices + :class:`plotly.graph_objects.isosurface.Slices` + instance or dict with compatible properties + spaceframe + :class:`plotly.graph_objects.isosurface.Spaceframe` + instance or dict with compatible properties + stream + :class:`plotly.graph_objects.isosurface.Stream` + instance or dict with compatible properties + surface + :class:`plotly.graph_objects.isosurface.Surface` + instance or dict with compatible properties + text + Sets the text elements associated with the vertices. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + value + Sets the 4th dimension (value) of the vertices. + valuehoverformat + Sets the hover text formatting rulefor `value` using + d3 formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + valuesrc + Sets the source reference on Chart Studio Cloud for + `value`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the X coordinates of the vertices on X axis. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the Y coordinates of the vertices on Y axis. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the Z coordinates of the vertices on Z axis. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + autocolorscale=None, + caps=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + coloraxis=None, + colorbar=None, + colorscale=None, + contour=None, + customdata=None, + customdatasrc=None, + flatshading=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + isomax=None, + isomin=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + slices=None, + spaceframe=None, + stream=None, + surface=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + value=None, + valuehoverformat=None, + valuesrc=None, + visible=None, + x=None, + xhoverformat=None, + xsrc=None, + y=None, + yhoverformat=None, + ysrc=None, + z=None, + zhoverformat=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Isosurface object + + Draws isosurfaces between iso-min and iso-max values with + coordinates given by four 1-dimensional arrays containing the + `value`, `x`, `y` and `z` of every vertex of a uniform or non- + uniform 3-D grid. Horizontal or vertical slices, caps as well + as spaceframe between iso-min and iso-max values could also be + drawn using this trace. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Isosurface` + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + caps + :class:`plotly.graph_objects.isosurface.Caps` instance + or dict with compatible properties + cauto + Determines whether or not the color domain is computed + with respect to the input data (here `value`) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as `value` and if set, `cmin` must + be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as `value`. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as `value` and if set, `cmax` must + be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.isosurface.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contour + :class:`plotly.graph_objects.isosurface.Contour` + instance or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + flatshading + Determines whether or not normal smoothing is applied + to the meshes, creating meshes with an angular, low- + poly look via flat reflections. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.isosurface.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + isomax + Sets the maximum boundary for iso-surface plot. + isomin + Sets the minimum boundary for iso-surface plot. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.isosurface.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.isosurface.Lighting` + instance or dict with compatible properties + lightposition + :class:`plotly.graph_objects.isosurface.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + slices + :class:`plotly.graph_objects.isosurface.Slices` + instance or dict with compatible properties + spaceframe + :class:`plotly.graph_objects.isosurface.Spaceframe` + instance or dict with compatible properties + stream + :class:`plotly.graph_objects.isosurface.Stream` + instance or dict with compatible properties + surface + :class:`plotly.graph_objects.isosurface.Surface` + instance or dict with compatible properties + text + Sets the text elements associated with the vertices. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + value + Sets the 4th dimension (value) of the vertices. + valuehoverformat + Sets the hover text formatting rulefor `value` using + d3 formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + valuesrc + Sets the source reference on Chart Studio Cloud for + `value`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the X coordinates of the vertices on X axis. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the Y coordinates of the vertices on Y axis. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the Z coordinates of the vertices on Z axis. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Isosurface + """ + super().__init__("isosurface") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Isosurface +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Isosurface`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("caps", arg, caps) + self._set_property("cauto", arg, cauto) + self._set_property("cmax", arg, cmax) + self._set_property("cmid", arg, cmid) + self._set_property("cmin", arg, cmin) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("contour", arg, contour) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("flatshading", arg, flatshading) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("isomax", arg, isomax) + self._set_property("isomin", arg, isomin) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("lighting", arg, lighting) + self._set_property("lightposition", arg, lightposition) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("reversescale", arg, reversescale) + self._set_property("scene", arg, scene) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("slices", arg, slices) + self._set_property("spaceframe", arg, spaceframe) + self._set_property("stream", arg, stream) + self._set_property("surface", arg, surface) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("value", arg, value) + self._set_property("valuehoverformat", arg, valuehoverformat) + self._set_property("valuesrc", arg, valuesrc) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("ysrc", arg, ysrc) + self._set_property("z", arg, z) + self._set_property("zhoverformat", arg, zhoverformat) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "isosurface" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_layout.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_layout.py new file mode 100644 index 0000000000000000000000000000000000000000..5917d7d574cc672350dff2f9f25619cf294d7c08 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_layout.py @@ -0,0 +1,3507 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutType as _BaseLayoutType +import copy as _copy + + +class Layout(_BaseLayoutType): + _subplotid_prop_names = [ + "coloraxis", + "geo", + "legend", + "map", + "mapbox", + "polar", + "scene", + "smith", + "ternary", + "xaxis", + "yaxis", + ] + + import re + + _subplotid_prop_re = re.compile("^(" + "|".join(_subplotid_prop_names) + r")(\d+)$") + + @property + def _subplotid_validators(self): + """ + dict of validator classes for each subplot type + + Returns + ------- + dict + """ + from plotly.validator_cache import ValidatorCache + + return { + "coloraxis": ValidatorCache.get_validator("layout", "coloraxis"), + "geo": ValidatorCache.get_validator("layout", "geo"), + "legend": ValidatorCache.get_validator("layout", "legend"), + "map": ValidatorCache.get_validator("layout", "map"), + "mapbox": ValidatorCache.get_validator("layout", "mapbox"), + "polar": ValidatorCache.get_validator("layout", "polar"), + "scene": ValidatorCache.get_validator("layout", "scene"), + "smith": ValidatorCache.get_validator("layout", "smith"), + "ternary": ValidatorCache.get_validator("layout", "ternary"), + "xaxis": ValidatorCache.get_validator("layout", "xaxis"), + "yaxis": ValidatorCache.get_validator("layout", "yaxis"), + } + + def _subplot_re_match(self, prop): + return self._subplotid_prop_re.match(prop) + + _parent_path_str = "" + _path_str = "layout" + _valid_props = { + "activeselection", + "activeshape", + "annotationdefaults", + "annotations", + "autosize", + "autotypenumbers", + "barcornerradius", + "bargap", + "bargroupgap", + "barmode", + "barnorm", + "boxgap", + "boxgroupgap", + "boxmode", + "calendar", + "clickmode", + "coloraxis", + "colorscale", + "colorway", + "computed", + "datarevision", + "dragmode", + "editrevision", + "extendfunnelareacolors", + "extendiciclecolors", + "extendpiecolors", + "extendsunburstcolors", + "extendtreemapcolors", + "font", + "funnelareacolorway", + "funnelgap", + "funnelgroupgap", + "funnelmode", + "geo", + "grid", + "height", + "hiddenlabels", + "hiddenlabelssrc", + "hidesources", + "hoverdistance", + "hoverlabel", + "hovermode", + "hoversubplots", + "iciclecolorway", + "imagedefaults", + "images", + "legend", + "map", + "mapbox", + "margin", + "meta", + "metasrc", + "minreducedheight", + "minreducedwidth", + "modebar", + "newselection", + "newshape", + "paper_bgcolor", + "piecolorway", + "plot_bgcolor", + "polar", + "scattergap", + "scattermode", + "scene", + "selectdirection", + "selectiondefaults", + "selectionrevision", + "selections", + "separators", + "shapedefaults", + "shapes", + "showlegend", + "sliderdefaults", + "sliders", + "smith", + "spikedistance", + "sunburstcolorway", + "template", + "ternary", + "title", + "transition", + "treemapcolorway", + "uirevision", + "uniformtext", + "updatemenudefaults", + "updatemenus", + "violingap", + "violingroupgap", + "violinmode", + "waterfallgap", + "waterfallgroupgap", + "waterfallmode", + "width", + "xaxis", + "yaxis", + } + + @property + def activeselection(self): + """ + The 'activeselection' property is an instance of Activeselection + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Activeselection` + - A dict of string/value properties that will be passed + to the Activeselection constructor + + Returns + ------- + plotly.graph_objs.layout.Activeselection + """ + return self["activeselection"] + + @activeselection.setter + def activeselection(self, val): + self["activeselection"] = val + + @property + def activeshape(self): + """ + The 'activeshape' property is an instance of Activeshape + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Activeshape` + - A dict of string/value properties that will be passed + to the Activeshape constructor + + Returns + ------- + plotly.graph_objs.layout.Activeshape + """ + return self["activeshape"] + + @activeshape.setter + def activeshape(self, val): + self["activeshape"] = val + + @property + def annotations(self): + """ + The 'annotations' property is a tuple of instances of + Annotation that may be specified as: + - A list or tuple of instances of plotly.graph_objs.layout.Annotation + - A list or tuple of dicts of string/value properties that + will be passed to the Annotation constructor + + Returns + ------- + tuple[plotly.graph_objs.layout.Annotation] + """ + return self["annotations"] + + @annotations.setter + def annotations(self, val): + self["annotations"] = val + + @property + def annotationdefaults(self): + """ + When used in a template (as + layout.template.layout.annotationdefaults), sets the default + property values to use for elements of layout.annotations + + The 'annotationdefaults' property is an instance of Annotation + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Annotation` + - A dict of string/value properties that will be passed + to the Annotation constructor + + Returns + ------- + plotly.graph_objs.layout.Annotation + """ + return self["annotationdefaults"] + + @annotationdefaults.setter + def annotationdefaults(self, val): + self["annotationdefaults"] = val + + @property + def autosize(self): + """ + Determines whether or not a layout width or height that has + been left undefined by the user is initialized on each + relayout. Note that, regardless of this attribute, an undefined + layout width or height is always initialized on the first call + to plot. + + The 'autosize' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autosize"] + + @autosize.setter + def autosize(self, val): + self["autosize"] = val + + @property + def autotypenumbers(self): + """ + Using "strict" a numeric string in trace data is not converted + to a number. Using *convert types* a numeric string in trace + data may be treated as a number during automatic axis `type` + detection. This is the default value; however it could be + overridden for individual axes. + + The 'autotypenumbers' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['convert types', 'strict'] + + Returns + ------- + Any + """ + return self["autotypenumbers"] + + @autotypenumbers.setter + def autotypenumbers(self, val): + self["autotypenumbers"] = val + + @property + def barcornerradius(self): + """ + Sets the rounding of bar corners. May be an integer number of + pixels, or a percentage of bar width (as a string ending in %). + + The 'barcornerradius' property accepts values of any type + + Returns + ------- + Any + """ + return self["barcornerradius"] + + @barcornerradius.setter + def barcornerradius(self, val): + self["barcornerradius"] = val + + @property + def bargap(self): + """ + Sets the gap (in plot fraction) between bars of adjacent + location coordinates. + + The 'bargap' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["bargap"] + + @bargap.setter + def bargap(self, val): + self["bargap"] = val + + @property + def bargroupgap(self): + """ + Sets the gap (in plot fraction) between bars of the same + location coordinate. + + The 'bargroupgap' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["bargroupgap"] + + @bargroupgap.setter + def bargroupgap(self, val): + self["bargroupgap"] = val + + @property + def barmode(self): + """ + Determines how bars at the same location coordinate are + displayed on the graph. With "stack", the bars are stacked on + top of one another With "relative", the bars are stacked on top + of one another, with negative values below the axis, positive + values above With "group", the bars are plotted next to one + another centered around the shared location. With "overlay", + the bars are plotted over one another, you might need to reduce + "opacity" to see multiple bars. + + The 'barmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['stack', 'group', 'overlay', 'relative'] + + Returns + ------- + Any + """ + return self["barmode"] + + @barmode.setter + def barmode(self, val): + self["barmode"] = val + + @property + def barnorm(self): + """ + Sets the normalization for bar traces on the graph. With + "fraction", the value of each bar is divided by the sum of all + values at that location coordinate. "percent" is the same but + multiplied by 100 to show percentages. + + The 'barnorm' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['', 'fraction', 'percent'] + + Returns + ------- + Any + """ + return self["barnorm"] + + @barnorm.setter + def barnorm(self, val): + self["barnorm"] = val + + @property + def boxgap(self): + """ + Sets the gap (in plot fraction) between boxes of adjacent + location coordinates. Has no effect on traces that have "width" + set. + + The 'boxgap' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["boxgap"] + + @boxgap.setter + def boxgap(self, val): + self["boxgap"] = val + + @property + def boxgroupgap(self): + """ + Sets the gap (in plot fraction) between boxes of the same + location coordinate. Has no effect on traces that have "width" + set. + + The 'boxgroupgap' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["boxgroupgap"] + + @boxgroupgap.setter + def boxgroupgap(self, val): + self["boxgroupgap"] = val + + @property + def boxmode(self): + """ + Determines how boxes at the same location coordinate are + displayed on the graph. If "group", the boxes are plotted next + to one another centered around the shared location. If + "overlay", the boxes are plotted over one another, you might + need to set "opacity" to see them multiple boxes. Has no effect + on traces that have "width" set. + + The 'boxmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['group', 'overlay'] + + Returns + ------- + Any + """ + return self["boxmode"] + + @boxmode.setter + def boxmode(self, val): + self["boxmode"] = val + + @property + def calendar(self): + """ + Sets the default calendar system to use for interpreting and + displaying dates throughout the plot. + + The 'calendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["calendar"] + + @calendar.setter + def calendar(self, val): + self["calendar"] = val + + @property + def clickmode(self): + """ + Determines the mode of single click interactions. "event" is + the default value and emits the `plotly_click` event. In + addition this mode emits the `plotly_selected` event in drag + modes "lasso" and "select", but with no event data attached + (kept for compatibility reasons). The "select" flag enables + selecting single data points via click. This mode also supports + persistent selections, meaning that pressing Shift while + clicking, adds to / subtracts from an existing selection. + "select" with `hovermode`: "x" can be confusing, consider + explicitly setting `hovermode`: "closest" when using this + feature. Selection events are sent accordingly as long as + "event" flag is set as well. When the "event" flag is missing, + `plotly_click` and `plotly_selected` events are not fired. + + The 'clickmode' property is a flaglist and may be specified + as a string containing: + - Any combination of ['event', 'select'] joined with '+' characters + (e.g. 'event+select') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["clickmode"] + + @clickmode.setter + def clickmode(self, val): + self["clickmode"] = val + + @property + def coloraxis(self): + """ + The 'coloraxis' property is an instance of Coloraxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Coloraxis` + - A dict of string/value properties that will be passed + to the Coloraxis constructor + + Returns + ------- + plotly.graph_objs.layout.Coloraxis + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorscale(self): + """ + The 'colorscale' property is an instance of Colorscale + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Colorscale` + - A dict of string/value properties that will be passed + to the Colorscale constructor + + Returns + ------- + plotly.graph_objs.layout.Colorscale + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def colorway(self): + """ + Sets the default trace colors. + + The 'colorway' property is a colorlist that may be specified + as a tuple, list, one-dimensional numpy array, or pandas Series of valid + color strings + + Returns + ------- + list + """ + return self["colorway"] + + @colorway.setter + def colorway(self, val): + self["colorway"] = val + + @property + def computed(self): + """ + Placeholder for exporting automargin-impacting values namely + `margin.t`, `margin.b`, `margin.l` and `margin.r` in "full- + json" mode. + + The 'computed' property accepts values of any type + + Returns + ------- + Any + """ + return self["computed"] + + @computed.setter + def computed(self, val): + self["computed"] = val + + @property + def datarevision(self): + """ + If provided, a changed value tells `Plotly.react` that one or + more data arrays has changed. This way you can modify arrays + in-place rather than making a complete new copy for an + incremental change. If NOT provided, `Plotly.react` assumes + that data arrays are being treated as immutable, thus any data + array with a different identity from its predecessor contains + new data. + + The 'datarevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["datarevision"] + + @datarevision.setter + def datarevision(self, val): + self["datarevision"] = val + + @property + def dragmode(self): + """ + Determines the mode of drag interactions. "select" and "lasso" + apply only to scatter traces with markers or text. "orbit" and + "turntable" apply only to 3D scenes. + + The 'dragmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['zoom', 'pan', 'select', 'lasso', 'drawclosedpath', + 'drawopenpath', 'drawline', 'drawrect', 'drawcircle', + 'orbit', 'turntable', False] + + Returns + ------- + Any + """ + return self["dragmode"] + + @dragmode.setter + def dragmode(self, val): + self["dragmode"] = val + + @property + def editrevision(self): + """ + Controls persistence of user-driven changes in `editable: true` + configuration, other than trace names and axis titles. Defaults + to `layout.uirevision`. + + The 'editrevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["editrevision"] + + @editrevision.setter + def editrevision(self, val): + self["editrevision"] = val + + @property + def extendfunnelareacolors(self): + """ + If `true`, the funnelarea slice colors (whether given by + `funnelareacolorway` or inherited from `colorway`) will be + extended to three times its original length by first repeating + every color 20% lighter then each color 20% darker. This is + intended to reduce the likelihood of reusing the same color + when you have many slices, but you can set `false` to disable. + Colors provided in the trace, using `marker.colors`, are never + extended. + + The 'extendfunnelareacolors' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["extendfunnelareacolors"] + + @extendfunnelareacolors.setter + def extendfunnelareacolors(self, val): + self["extendfunnelareacolors"] = val + + @property + def extendiciclecolors(self): + """ + If `true`, the icicle slice colors (whether given by + `iciclecolorway` or inherited from `colorway`) will be extended + to three times its original length by first repeating every + color 20% lighter then each color 20% darker. This is intended + to reduce the likelihood of reusing the same color when you + have many slices, but you can set `false` to disable. Colors + provided in the trace, using `marker.colors`, are never + extended. + + The 'extendiciclecolors' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["extendiciclecolors"] + + @extendiciclecolors.setter + def extendiciclecolors(self, val): + self["extendiciclecolors"] = val + + @property + def extendpiecolors(self): + """ + If `true`, the pie slice colors (whether given by `piecolorway` + or inherited from `colorway`) will be extended to three times + its original length by first repeating every color 20% lighter + then each color 20% darker. This is intended to reduce the + likelihood of reusing the same color when you have many slices, + but you can set `false` to disable. Colors provided in the + trace, using `marker.colors`, are never extended. + + The 'extendpiecolors' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["extendpiecolors"] + + @extendpiecolors.setter + def extendpiecolors(self, val): + self["extendpiecolors"] = val + + @property + def extendsunburstcolors(self): + """ + If `true`, the sunburst slice colors (whether given by + `sunburstcolorway` or inherited from `colorway`) will be + extended to three times its original length by first repeating + every color 20% lighter then each color 20% darker. This is + intended to reduce the likelihood of reusing the same color + when you have many slices, but you can set `false` to disable. + Colors provided in the trace, using `marker.colors`, are never + extended. + + The 'extendsunburstcolors' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["extendsunburstcolors"] + + @extendsunburstcolors.setter + def extendsunburstcolors(self, val): + self["extendsunburstcolors"] = val + + @property + def extendtreemapcolors(self): + """ + If `true`, the treemap slice colors (whether given by + `treemapcolorway` or inherited from `colorway`) will be + extended to three times its original length by first repeating + every color 20% lighter then each color 20% darker. This is + intended to reduce the likelihood of reusing the same color + when you have many slices, but you can set `false` to disable. + Colors provided in the trace, using `marker.colors`, are never + extended. + + The 'extendtreemapcolors' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["extendtreemapcolors"] + + @extendtreemapcolors.setter + def extendtreemapcolors(self, val): + self["extendtreemapcolors"] = val + + @property + def font(self): + """ + Sets the global font. Note that fonts used in traces and other + layout components inherit from the global font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.layout.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def funnelareacolorway(self): + """ + Sets the default funnelarea slice colors. Defaults to the main + `colorway` used for trace colors. If you specify a new list + here it can still be extended with lighter and darker colors, + see `extendfunnelareacolors`. + + The 'funnelareacolorway' property is a colorlist that may be specified + as a tuple, list, one-dimensional numpy array, or pandas Series of valid + color strings + + Returns + ------- + list + """ + return self["funnelareacolorway"] + + @funnelareacolorway.setter + def funnelareacolorway(self, val): + self["funnelareacolorway"] = val + + @property + def funnelgap(self): + """ + Sets the gap (in plot fraction) between bars of adjacent + location coordinates. + + The 'funnelgap' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["funnelgap"] + + @funnelgap.setter + def funnelgap(self, val): + self["funnelgap"] = val + + @property + def funnelgroupgap(self): + """ + Sets the gap (in plot fraction) between bars of the same + location coordinate. + + The 'funnelgroupgap' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["funnelgroupgap"] + + @funnelgroupgap.setter + def funnelgroupgap(self, val): + self["funnelgroupgap"] = val + + @property + def funnelmode(self): + """ + Determines how bars at the same location coordinate are + displayed on the graph. With "stack", the bars are stacked on + top of one another With "group", the bars are plotted next to + one another centered around the shared location. With + "overlay", the bars are plotted over one another, you might + need to reduce "opacity" to see multiple bars. + + The 'funnelmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['stack', 'group', 'overlay'] + + Returns + ------- + Any + """ + return self["funnelmode"] + + @funnelmode.setter + def funnelmode(self, val): + self["funnelmode"] = val + + @property + def geo(self): + """ + The 'geo' property is an instance of Geo + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Geo` + - A dict of string/value properties that will be passed + to the Geo constructor + + Returns + ------- + plotly.graph_objs.layout.Geo + """ + return self["geo"] + + @geo.setter + def geo(self, val): + self["geo"] = val + + @property + def grid(self): + """ + The 'grid' property is an instance of Grid + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Grid` + - A dict of string/value properties that will be passed + to the Grid constructor + + Returns + ------- + plotly.graph_objs.layout.Grid + """ + return self["grid"] + + @grid.setter + def grid(self, val): + self["grid"] = val + + @property + def height(self): + """ + Sets the plot's height (in px). + + The 'height' property is a number and may be specified as: + - An int or float in the interval [10, inf] + + Returns + ------- + int|float + """ + return self["height"] + + @height.setter + def height(self, val): + self["height"] = val + + @property + def hiddenlabels(self): + """ + hiddenlabels is the funnelarea & pie chart analog of + visible:'legendonly' but it can contain many labels, and can + simultaneously hide slices from several pies/funnelarea charts + + The 'hiddenlabels' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["hiddenlabels"] + + @hiddenlabels.setter + def hiddenlabels(self, val): + self["hiddenlabels"] = val + + @property + def hiddenlabelssrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hiddenlabels`. + + The 'hiddenlabelssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hiddenlabelssrc"] + + @hiddenlabelssrc.setter + def hiddenlabelssrc(self, val): + self["hiddenlabelssrc"] = val + + @property + def hidesources(self): + """ + Determines whether or not a text link citing the data source is + placed at the bottom-right cored of the figure. Has only an + effect only on graphs that have been generated via forked + graphs from the Chart Studio Cloud (at https://chart- + studio.plotly.com or on-premise). + + The 'hidesources' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["hidesources"] + + @hidesources.setter + def hidesources(self, val): + self["hidesources"] = val + + @property + def hoverdistance(self): + """ + Sets the default distance (in pixels) to look for data to add + hover labels (-1 means no cutoff, 0 means no looking for data). + This is only a real distance for hovering on point-like + objects, like scatter points. For area-like objects (bars, + scatter fills, etc) hovering is on inside the area and off + outside, but these objects will not supersede hover on point- + like objects in case of conflict. + + The 'hoverdistance' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + + Returns + ------- + int + """ + return self["hoverdistance"] + + @hoverdistance.setter + def hoverdistance(self, val): + self["hoverdistance"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.layout.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovermode(self): + """ + Determines the mode of hover interactions. If "closest", a + single hoverlabel will appear for the "closest" point within + the `hoverdistance`. If "x" (or "y"), multiple hoverlabels will + appear for multiple points at the "closest" x- (or y-) + coordinate within the `hoverdistance`, with the caveat that no + more than one hoverlabel will appear per trace. If *x unified* + (or *y unified*), a single hoverlabel will appear multiple + points at the closest x- (or y-) coordinate within the + `hoverdistance` with the caveat that no more than one + hoverlabel will appear per trace. In this mode, spikelines are + enabled by default perpendicular to the specified axis. If + false, hover interactions are disabled. + + The 'hovermode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['x', 'y', 'closest', False, 'x unified', 'y unified'] + + Returns + ------- + Any + """ + return self["hovermode"] + + @hovermode.setter + def hovermode(self, val): + self["hovermode"] = val + + @property + def hoversubplots(self): + """ + Determines expansion of hover effects to other subplots If + "single" just the axis pair of the primary point is included + without overlaying subplots. If "overlaying" all subplots using + the main axis and occupying the same space are included. If + "axis", also include stacked subplots using the same axis when + `hovermode` is set to "x", *x unified*, "y" or *y unified*. + + The 'hoversubplots' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['single', 'overlaying', 'axis'] + + Returns + ------- + Any + """ + return self["hoversubplots"] + + @hoversubplots.setter + def hoversubplots(self, val): + self["hoversubplots"] = val + + @property + def iciclecolorway(self): + """ + Sets the default icicle slice colors. Defaults to the main + `colorway` used for trace colors. If you specify a new list + here it can still be extended with lighter and darker colors, + see `extendiciclecolors`. + + The 'iciclecolorway' property is a colorlist that may be specified + as a tuple, list, one-dimensional numpy array, or pandas Series of valid + color strings + + Returns + ------- + list + """ + return self["iciclecolorway"] + + @iciclecolorway.setter + def iciclecolorway(self, val): + self["iciclecolorway"] = val + + @property + def images(self): + """ + The 'images' property is a tuple of instances of + Image that may be specified as: + - A list or tuple of instances of plotly.graph_objs.layout.Image + - A list or tuple of dicts of string/value properties that + will be passed to the Image constructor + + Returns + ------- + tuple[plotly.graph_objs.layout.Image] + """ + return self["images"] + + @images.setter + def images(self, val): + self["images"] = val + + @property + def imagedefaults(self): + """ + When used in a template (as + layout.template.layout.imagedefaults), sets the default + property values to use for elements of layout.images + + The 'imagedefaults' property is an instance of Image + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Image` + - A dict of string/value properties that will be passed + to the Image constructor + + Returns + ------- + plotly.graph_objs.layout.Image + """ + return self["imagedefaults"] + + @imagedefaults.setter + def imagedefaults(self, val): + self["imagedefaults"] = val + + @property + def legend(self): + """ + The 'legend' property is an instance of Legend + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Legend` + - A dict of string/value properties that will be passed + to the Legend constructor + + Returns + ------- + plotly.graph_objs.layout.Legend + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def map(self): + """ + The 'map' property is an instance of Map + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Map` + - A dict of string/value properties that will be passed + to the Map constructor + + Returns + ------- + plotly.graph_objs.layout.Map + """ + return self["map"] + + @map.setter + def map(self, val): + self["map"] = val + + @property + def mapbox(self): + """ + The 'mapbox' property is an instance of Mapbox + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Mapbox` + - A dict of string/value properties that will be passed + to the Mapbox constructor + + Returns + ------- + plotly.graph_objs.layout.Mapbox + """ + return self["mapbox"] + + @mapbox.setter + def mapbox(self, val): + self["mapbox"] = val + + @property + def margin(self): + """ + The 'margin' property is an instance of Margin + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Margin` + - A dict of string/value properties that will be passed + to the Margin constructor + + Returns + ------- + plotly.graph_objs.layout.Margin + """ + return self["margin"] + + @margin.setter + def margin(self, val): + self["margin"] = val + + @property + def meta(self): + """ + Assigns extra meta information that can be used in various + `text` attributes. Attributes such as the graph, axis and + colorbar `title.text`, annotation `text` `trace.name` in legend + items, `rangeselector`, `updatemenus` and `sliders` `label` + text all support `meta`. One can access `meta` fields using + template strings: `%{meta[i]}` where `i` is the index of the + `meta` item in question. `meta` can also be an object for + example `{key: value}` which can be accessed %{meta[key]}. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def minreducedheight(self): + """ + Minimum height of the plot with margin.automargin applied (in + px) + + The 'minreducedheight' property is a number and may be specified as: + - An int or float in the interval [2, inf] + + Returns + ------- + int|float + """ + return self["minreducedheight"] + + @minreducedheight.setter + def minreducedheight(self, val): + self["minreducedheight"] = val + + @property + def minreducedwidth(self): + """ + Minimum width of the plot with margin.automargin applied (in + px) + + The 'minreducedwidth' property is a number and may be specified as: + - An int or float in the interval [2, inf] + + Returns + ------- + int|float + """ + return self["minreducedwidth"] + + @minreducedwidth.setter + def minreducedwidth(self, val): + self["minreducedwidth"] = val + + @property + def modebar(self): + """ + The 'modebar' property is an instance of Modebar + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Modebar` + - A dict of string/value properties that will be passed + to the Modebar constructor + + Returns + ------- + plotly.graph_objs.layout.Modebar + """ + return self["modebar"] + + @modebar.setter + def modebar(self, val): + self["modebar"] = val + + @property + def newselection(self): + """ + The 'newselection' property is an instance of Newselection + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Newselection` + - A dict of string/value properties that will be passed + to the Newselection constructor + + Returns + ------- + plotly.graph_objs.layout.Newselection + """ + return self["newselection"] + + @newselection.setter + def newselection(self, val): + self["newselection"] = val + + @property + def newshape(self): + """ + The 'newshape' property is an instance of Newshape + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Newshape` + - A dict of string/value properties that will be passed + to the Newshape constructor + + Returns + ------- + plotly.graph_objs.layout.Newshape + """ + return self["newshape"] + + @newshape.setter + def newshape(self, val): + self["newshape"] = val + + @property + def paper_bgcolor(self): + """ + Sets the background color of the paper where the graph is + drawn. + + The 'paper_bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["paper_bgcolor"] + + @paper_bgcolor.setter + def paper_bgcolor(self, val): + self["paper_bgcolor"] = val + + @property + def piecolorway(self): + """ + Sets the default pie slice colors. Defaults to the main + `colorway` used for trace colors. If you specify a new list + here it can still be extended with lighter and darker colors, + see `extendpiecolors`. + + The 'piecolorway' property is a colorlist that may be specified + as a tuple, list, one-dimensional numpy array, or pandas Series of valid + color strings + + Returns + ------- + list + """ + return self["piecolorway"] + + @piecolorway.setter + def piecolorway(self, val): + self["piecolorway"] = val + + @property + def plot_bgcolor(self): + """ + Sets the background color of the plotting area in-between x and + y axes. + + The 'plot_bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["plot_bgcolor"] + + @plot_bgcolor.setter + def plot_bgcolor(self, val): + self["plot_bgcolor"] = val + + @property + def polar(self): + """ + The 'polar' property is an instance of Polar + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Polar` + - A dict of string/value properties that will be passed + to the Polar constructor + + Returns + ------- + plotly.graph_objs.layout.Polar + """ + return self["polar"] + + @polar.setter + def polar(self, val): + self["polar"] = val + + @property + def scattergap(self): + """ + Sets the gap (in plot fraction) between scatter points of + adjacent location coordinates. Defaults to `bargap`. + + The 'scattergap' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["scattergap"] + + @scattergap.setter + def scattergap(self, val): + self["scattergap"] = val + + @property + def scattermode(self): + """ + Determines how scatter points at the same location coordinate + are displayed on the graph. With "group", the scatter points + are plotted next to one another centered around the shared + location. With "overlay", the scatter points are plotted over + one another, you might need to reduce "opacity" to see multiple + scatter points. + + The 'scattermode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['group', 'overlay'] + + Returns + ------- + Any + """ + return self["scattermode"] + + @scattermode.setter + def scattermode(self, val): + self["scattermode"] = val + + @property + def scene(self): + """ + The 'scene' property is an instance of Scene + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Scene` + - A dict of string/value properties that will be passed + to the Scene constructor + + Returns + ------- + plotly.graph_objs.layout.Scene + """ + return self["scene"] + + @scene.setter + def scene(self, val): + self["scene"] = val + + @property + def selectdirection(self): + """ + When `dragmode` is set to "select", this limits the selection + of the drag to horizontal, vertical or diagonal. "h" only + allows horizontal selection, "v" only vertical, "d" only + diagonal and "any" sets no limit. + + The 'selectdirection' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['h', 'v', 'd', 'any'] + + Returns + ------- + Any + """ + return self["selectdirection"] + + @selectdirection.setter + def selectdirection(self, val): + self["selectdirection"] = val + + @property + def selectionrevision(self): + """ + Controls persistence of user-driven changes in selected points + from all traces. + + The 'selectionrevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectionrevision"] + + @selectionrevision.setter + def selectionrevision(self, val): + self["selectionrevision"] = val + + @property + def selections(self): + """ + The 'selections' property is a tuple of instances of + Selection that may be specified as: + - A list or tuple of instances of plotly.graph_objs.layout.Selection + - A list or tuple of dicts of string/value properties that + will be passed to the Selection constructor + + Returns + ------- + tuple[plotly.graph_objs.layout.Selection] + """ + return self["selections"] + + @selections.setter + def selections(self, val): + self["selections"] = val + + @property + def selectiondefaults(self): + """ + When used in a template (as + layout.template.layout.selectiondefaults), sets the default + property values to use for elements of layout.selections + + The 'selectiondefaults' property is an instance of Selection + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Selection` + - A dict of string/value properties that will be passed + to the Selection constructor + + Returns + ------- + plotly.graph_objs.layout.Selection + """ + return self["selectiondefaults"] + + @selectiondefaults.setter + def selectiondefaults(self, val): + self["selectiondefaults"] = val + + @property + def separators(self): + """ + Sets the decimal and thousand separators. For example, *. * + puts a '.' before decimals and a space between thousands. In + English locales, dflt is ".," but other locales may alter this + default. + + The 'separators' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["separators"] + + @separators.setter + def separators(self, val): + self["separators"] = val + + @property + def shapes(self): + """ + The 'shapes' property is a tuple of instances of + Shape that may be specified as: + - A list or tuple of instances of plotly.graph_objs.layout.Shape + - A list or tuple of dicts of string/value properties that + will be passed to the Shape constructor + + Returns + ------- + tuple[plotly.graph_objs.layout.Shape] + """ + return self["shapes"] + + @shapes.setter + def shapes(self, val): + self["shapes"] = val + + @property + def shapedefaults(self): + """ + When used in a template (as + layout.template.layout.shapedefaults), sets the default + property values to use for elements of layout.shapes + + The 'shapedefaults' property is an instance of Shape + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Shape` + - A dict of string/value properties that will be passed + to the Shape constructor + + Returns + ------- + plotly.graph_objs.layout.Shape + """ + return self["shapedefaults"] + + @shapedefaults.setter + def shapedefaults(self, val): + self["shapedefaults"] = val + + @property + def showlegend(self): + """ + Determines whether or not a legend is drawn. Default is `true` + if there is a trace to show and any of these: a) Two or more + traces would by default be shown in the legend. b) One pie + trace is shown in the legend. c) One trace is explicitly given + with `showlegend: true`. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def sliders(self): + """ + The 'sliders' property is a tuple of instances of + Slider that may be specified as: + - A list or tuple of instances of plotly.graph_objs.layout.Slider + - A list or tuple of dicts of string/value properties that + will be passed to the Slider constructor + + Returns + ------- + tuple[plotly.graph_objs.layout.Slider] + """ + return self["sliders"] + + @sliders.setter + def sliders(self, val): + self["sliders"] = val + + @property + def sliderdefaults(self): + """ + When used in a template (as + layout.template.layout.sliderdefaults), sets the default + property values to use for elements of layout.sliders + + The 'sliderdefaults' property is an instance of Slider + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Slider` + - A dict of string/value properties that will be passed + to the Slider constructor + + Returns + ------- + plotly.graph_objs.layout.Slider + """ + return self["sliderdefaults"] + + @sliderdefaults.setter + def sliderdefaults(self, val): + self["sliderdefaults"] = val + + @property + def smith(self): + """ + The 'smith' property is an instance of Smith + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Smith` + - A dict of string/value properties that will be passed + to the Smith constructor + + Returns + ------- + plotly.graph_objs.layout.Smith + """ + return self["smith"] + + @smith.setter + def smith(self, val): + self["smith"] = val + + @property + def spikedistance(self): + """ + Sets the default distance (in pixels) to look for data to draw + spikelines to (-1 means no cutoff, 0 means no looking for + data). As with hoverdistance, distance does not apply to area- + like objects. In addition, some objects can be hovered on but + will not generate spikelines, such as scatter fills. + + The 'spikedistance' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + + Returns + ------- + int + """ + return self["spikedistance"] + + @spikedistance.setter + def spikedistance(self, val): + self["spikedistance"] = val + + @property + def sunburstcolorway(self): + """ + Sets the default sunburst slice colors. Defaults to the main + `colorway` used for trace colors. If you specify a new list + here it can still be extended with lighter and darker colors, + see `extendsunburstcolors`. + + The 'sunburstcolorway' property is a colorlist that may be specified + as a tuple, list, one-dimensional numpy array, or pandas Series of valid + color strings + + Returns + ------- + list + """ + return self["sunburstcolorway"] + + @sunburstcolorway.setter + def sunburstcolorway(self, val): + self["sunburstcolorway"] = val + + @property + def template(self): + """ + Default attributes to be applied to the plot. This should be a + dict with format: `{'layout': layoutTemplate, 'data': + {trace_type: [traceTemplate, ...], ...}}` where + `layoutTemplate` is a dict matching the structure of + `figure.layout` and `traceTemplate` is a dict matching the + structure of the trace with type `trace_type` (e.g. 'scatter'). + Alternatively, this may be specified as an instance of + plotly.graph_objs.layout.Template. Trace templates are applied + cyclically to traces of each type. Container arrays (eg + `annotations`) have special handling: An object ending in + `defaults` (eg `annotationdefaults`) is applied to each array + item. But if an item has a `templateitemname` key we look in + the template array for an item with matching `name` and apply + that instead. If no matching `name` is found we mark the item + invisible. Any named template item not referenced is appended + to the end of the array, so this can be used to add a watermark + annotation or a logo image, for example. To omit one of these + items on the plot, make an item with matching + `templateitemname` and `visible: false`. + + The 'template' property is an instance of Template + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Template` + - A dict of string/value properties that will be passed + to the Template constructor + - The name of a registered template where current registered templates + are stored in the plotly.io.templates configuration object. The names + of all registered templates can be retrieved with: + >>> import plotly.io as pio + >>> list(pio.templates) # doctest: +ELLIPSIS + ['ggplot2', 'seaborn', 'simple_white', 'plotly', 'plotly_white', ...] + + - A string containing multiple registered template names, joined on '+' + characters (e.g. 'template1+template2'). In this case the resulting + template is computed by merging together the collection of registered + templates + + Returns + ------- + plotly.graph_objs.layout.Template + """ + return self["template"] + + @template.setter + def template(self, val): + self["template"] = val + + @property + def ternary(self): + """ + The 'ternary' property is an instance of Ternary + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Ternary` + - A dict of string/value properties that will be passed + to the Ternary constructor + + Returns + ------- + plotly.graph_objs.layout.Ternary + """ + return self["ternary"] + + @ternary.setter + def ternary(self, val): + self["ternary"] = val + + @property + def title(self): + """ + The 'title' property is an instance of Title + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Title` + - A dict of string/value properties that will be passed + to the Title constructor + + Returns + ------- + plotly.graph_objs.layout.Title + """ + return self["title"] + + @title.setter + def title(self, val): + self["title"] = val + + @property + def transition(self): + """ + Sets transition options used during Plotly.react updates. + + The 'transition' property is an instance of Transition + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Transition` + - A dict of string/value properties that will be passed + to the Transition constructor + + Returns + ------- + plotly.graph_objs.layout.Transition + """ + return self["transition"] + + @transition.setter + def transition(self, val): + self["transition"] = val + + @property + def treemapcolorway(self): + """ + Sets the default treemap slice colors. Defaults to the main + `colorway` used for trace colors. If you specify a new list + here it can still be extended with lighter and darker colors, + see `extendtreemapcolors`. + + The 'treemapcolorway' property is a colorlist that may be specified + as a tuple, list, one-dimensional numpy array, or pandas Series of valid + color strings + + Returns + ------- + list + """ + return self["treemapcolorway"] + + @treemapcolorway.setter + def treemapcolorway(self, val): + self["treemapcolorway"] = val + + @property + def uirevision(self): + """ + Used to allow user interactions with the plot to persist after + `Plotly.react` calls that are unaware of these interactions. If + `uirevision` is omitted, or if it is given and it changed from + the previous `Plotly.react` call, the exact new figure is used. + If `uirevision` is truthy and did NOT change, any attribute + that has been affected by user interactions and did not receive + a different value in the new figure will keep the interaction + value. `layout.uirevision` attribute serves as the default for + `uirevision` attributes in various sub-containers. For finer + control you can set these sub-attributes directly. For example, + if your app separately controls the data on the x and y axes + you might set `xaxis.uirevision=*time*` and + `yaxis.uirevision=*cost*`. Then if only the y data is changed, + you can update `yaxis.uirevision=*quantity*` and the y axis + range will reset but the x axis range will retain any user- + driven zoom. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def uniformtext(self): + """ + The 'uniformtext' property is an instance of Uniformtext + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Uniformtext` + - A dict of string/value properties that will be passed + to the Uniformtext constructor + + Returns + ------- + plotly.graph_objs.layout.Uniformtext + """ + return self["uniformtext"] + + @uniformtext.setter + def uniformtext(self, val): + self["uniformtext"] = val + + @property + def updatemenus(self): + """ + The 'updatemenus' property is a tuple of instances of + Updatemenu that may be specified as: + - A list or tuple of instances of plotly.graph_objs.layout.Updatemenu + - A list or tuple of dicts of string/value properties that + will be passed to the Updatemenu constructor + + Returns + ------- + tuple[plotly.graph_objs.layout.Updatemenu] + """ + return self["updatemenus"] + + @updatemenus.setter + def updatemenus(self, val): + self["updatemenus"] = val + + @property + def updatemenudefaults(self): + """ + When used in a template (as + layout.template.layout.updatemenudefaults), sets the default + property values to use for elements of layout.updatemenus + + The 'updatemenudefaults' property is an instance of Updatemenu + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.Updatemenu` + - A dict of string/value properties that will be passed + to the Updatemenu constructor + + Returns + ------- + plotly.graph_objs.layout.Updatemenu + """ + return self["updatemenudefaults"] + + @updatemenudefaults.setter + def updatemenudefaults(self, val): + self["updatemenudefaults"] = val + + @property + def violingap(self): + """ + Sets the gap (in plot fraction) between violins of adjacent + location coordinates. Has no effect on traces that have "width" + set. + + The 'violingap' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["violingap"] + + @violingap.setter + def violingap(self, val): + self["violingap"] = val + + @property + def violingroupgap(self): + """ + Sets the gap (in plot fraction) between violins of the same + location coordinate. Has no effect on traces that have "width" + set. + + The 'violingroupgap' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["violingroupgap"] + + @violingroupgap.setter + def violingroupgap(self, val): + self["violingroupgap"] = val + + @property + def violinmode(self): + """ + Determines how violins at the same location coordinate are + displayed on the graph. If "group", the violins are plotted + next to one another centered around the shared location. If + "overlay", the violins are plotted over one another, you might + need to set "opacity" to see them multiple violins. Has no + effect on traces that have "width" set. + + The 'violinmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['group', 'overlay'] + + Returns + ------- + Any + """ + return self["violinmode"] + + @violinmode.setter + def violinmode(self, val): + self["violinmode"] = val + + @property + def waterfallgap(self): + """ + Sets the gap (in plot fraction) between bars of adjacent + location coordinates. + + The 'waterfallgap' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["waterfallgap"] + + @waterfallgap.setter + def waterfallgap(self, val): + self["waterfallgap"] = val + + @property + def waterfallgroupgap(self): + """ + Sets the gap (in plot fraction) between bars of the same + location coordinate. + + The 'waterfallgroupgap' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["waterfallgroupgap"] + + @waterfallgroupgap.setter + def waterfallgroupgap(self, val): + self["waterfallgroupgap"] = val + + @property + def waterfallmode(self): + """ + Determines how bars at the same location coordinate are + displayed on the graph. With "group", the bars are plotted next + to one another centered around the shared location. With + "overlay", the bars are plotted over one another, you might + need to reduce "opacity" to see multiple bars. + + The 'waterfallmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['group', 'overlay'] + + Returns + ------- + Any + """ + return self["waterfallmode"] + + @waterfallmode.setter + def waterfallmode(self, val): + self["waterfallmode"] = val + + @property + def width(self): + """ + Sets the plot's width (in px). + + The 'width' property is a number and may be specified as: + - An int or float in the interval [10, inf] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def xaxis(self): + """ + The 'xaxis' property is an instance of XAxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.XAxis` + - A dict of string/value properties that will be passed + to the XAxis constructor + + Returns + ------- + plotly.graph_objs.layout.XAxis + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def yaxis(self): + """ + The 'yaxis' property is an instance of YAxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.YAxis` + - A dict of string/value properties that will be passed + to the YAxis constructor + + Returns + ------- + plotly.graph_objs.layout.YAxis + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def _prop_descriptions(self): + return """\ + activeselection + :class:`plotly.graph_objects.layout.Activeselection` + instance or dict with compatible properties + activeshape + :class:`plotly.graph_objects.layout.Activeshape` + instance or dict with compatible properties + annotations + A tuple of + :class:`plotly.graph_objects.layout.Annotation` + instances or dicts with compatible properties + annotationdefaults + When used in a template (as + layout.template.layout.annotationdefaults), sets the + default property values to use for elements of + layout.annotations + autosize + Determines whether or not a layout width or height that + has been left undefined by the user is initialized on + each relayout. Note that, regardless of this attribute, + an undefined layout width or height is always + initialized on the first call to plot. + autotypenumbers + Using "strict" a numeric string in trace data is not + converted to a number. Using *convert types* a numeric + string in trace data may be treated as a number during + automatic axis `type` detection. This is the default + value; however it could be overridden for individual + axes. + barcornerradius + Sets the rounding of bar corners. May be an integer + number of pixels, or a percentage of bar width (as a + string ending in %). + bargap + Sets the gap (in plot fraction) between bars of + adjacent location coordinates. + bargroupgap + Sets the gap (in plot fraction) between bars of the + same location coordinate. + barmode + Determines how bars at the same location coordinate are + displayed on the graph. With "stack", the bars are + stacked on top of one another With "relative", the bars + are stacked on top of one another, with negative values + below the axis, positive values above With "group", the + bars are plotted next to one another centered around + the shared location. With "overlay", the bars are + plotted over one another, you might need to reduce + "opacity" to see multiple bars. + barnorm + Sets the normalization for bar traces on the graph. + With "fraction", the value of each bar is divided by + the sum of all values at that location coordinate. + "percent" is the same but multiplied by 100 to show + percentages. + boxgap + Sets the gap (in plot fraction) between boxes of + adjacent location coordinates. Has no effect on traces + that have "width" set. + boxgroupgap + Sets the gap (in plot fraction) between boxes of the + same location coordinate. Has no effect on traces that + have "width" set. + boxmode + Determines how boxes at the same location coordinate + are displayed on the graph. If "group", the boxes are + plotted next to one another centered around the shared + location. If "overlay", the boxes are plotted over one + another, you might need to set "opacity" to see them + multiple boxes. Has no effect on traces that have + "width" set. + calendar + Sets the default calendar system to use for + interpreting and displaying dates throughout the plot. + clickmode + Determines the mode of single click interactions. + "event" is the default value and emits the + `plotly_click` event. In addition this mode emits the + `plotly_selected` event in drag modes "lasso" and + "select", but with no event data attached (kept for + compatibility reasons). The "select" flag enables + selecting single data points via click. This mode also + supports persistent selections, meaning that pressing + Shift while clicking, adds to / subtracts from an + existing selection. "select" with `hovermode`: "x" can + be confusing, consider explicitly setting `hovermode`: + "closest" when using this feature. Selection events are + sent accordingly as long as "event" flag is set as + well. When the "event" flag is missing, `plotly_click` + and `plotly_selected` events are not fired. + coloraxis + :class:`plotly.graph_objects.layout.Coloraxis` instance + or dict with compatible properties + colorscale + :class:`plotly.graph_objects.layout.Colorscale` + instance or dict with compatible properties + colorway + Sets the default trace colors. + computed + Placeholder for exporting automargin-impacting values + namely `margin.t`, `margin.b`, `margin.l` and + `margin.r` in "full-json" mode. + datarevision + If provided, a changed value tells `Plotly.react` that + one or more data arrays has changed. This way you can + modify arrays in-place rather than making a complete + new copy for an incremental change. If NOT provided, + `Plotly.react` assumes that data arrays are being + treated as immutable, thus any data array with a + different identity from its predecessor contains new + data. + dragmode + Determines the mode of drag interactions. "select" and + "lasso" apply only to scatter traces with markers or + text. "orbit" and "turntable" apply only to 3D scenes. + editrevision + Controls persistence of user-driven changes in + `editable: true` configuration, other than trace names + and axis titles. Defaults to `layout.uirevision`. + extendfunnelareacolors + If `true`, the funnelarea slice colors (whether given + by `funnelareacolorway` or inherited from `colorway`) + will be extended to three times its original length by + first repeating every color 20% lighter then each color + 20% darker. This is intended to reduce the likelihood + of reusing the same color when you have many slices, + but you can set `false` to disable. Colors provided in + the trace, using `marker.colors`, are never extended. + extendiciclecolors + If `true`, the icicle slice colors (whether given by + `iciclecolorway` or inherited from `colorway`) will be + extended to three times its original length by first + repeating every color 20% lighter then each color 20% + darker. This is intended to reduce the likelihood of + reusing the same color when you have many slices, but + you can set `false` to disable. Colors provided in the + trace, using `marker.colors`, are never extended. + extendpiecolors + If `true`, the pie slice colors (whether given by + `piecolorway` or inherited from `colorway`) will be + extended to three times its original length by first + repeating every color 20% lighter then each color 20% + darker. This is intended to reduce the likelihood of + reusing the same color when you have many slices, but + you can set `false` to disable. Colors provided in the + trace, using `marker.colors`, are never extended. + extendsunburstcolors + If `true`, the sunburst slice colors (whether given by + `sunburstcolorway` or inherited from `colorway`) will + be extended to three times its original length by first + repeating every color 20% lighter then each color 20% + darker. This is intended to reduce the likelihood of + reusing the same color when you have many slices, but + you can set `false` to disable. Colors provided in the + trace, using `marker.colors`, are never extended. + extendtreemapcolors + If `true`, the treemap slice colors (whether given by + `treemapcolorway` or inherited from `colorway`) will be + extended to three times its original length by first + repeating every color 20% lighter then each color 20% + darker. This is intended to reduce the likelihood of + reusing the same color when you have many slices, but + you can set `false` to disable. Colors provided in the + trace, using `marker.colors`, are never extended. + font + Sets the global font. Note that fonts used in traces + and other layout components inherit from the global + font. + funnelareacolorway + Sets the default funnelarea slice colors. Defaults to + the main `colorway` used for trace colors. If you + specify a new list here it can still be extended with + lighter and darker colors, see + `extendfunnelareacolors`. + funnelgap + Sets the gap (in plot fraction) between bars of + adjacent location coordinates. + funnelgroupgap + Sets the gap (in plot fraction) between bars of the + same location coordinate. + funnelmode + Determines how bars at the same location coordinate are + displayed on the graph. With "stack", the bars are + stacked on top of one another With "group", the bars + are plotted next to one another centered around the + shared location. With "overlay", the bars are plotted + over one another, you might need to reduce "opacity" to + see multiple bars. + geo + :class:`plotly.graph_objects.layout.Geo` instance or + dict with compatible properties + grid + :class:`plotly.graph_objects.layout.Grid` instance or + dict with compatible properties + height + Sets the plot's height (in px). + hiddenlabels + hiddenlabels is the funnelarea & pie chart analog of + visible:'legendonly' but it can contain many labels, + and can simultaneously hide slices from several + pies/funnelarea charts + hiddenlabelssrc + Sets the source reference on Chart Studio Cloud for + `hiddenlabels`. + hidesources + Determines whether or not a text link citing the data + source is placed at the bottom-right cored of the + figure. Has only an effect only on graphs that have + been generated via forked graphs from the Chart Studio + Cloud (at https://chart-studio.plotly.com or on- + premise). + hoverdistance + Sets the default distance (in pixels) to look for data + to add hover labels (-1 means no cutoff, 0 means no + looking for data). This is only a real distance for + hovering on point-like objects, like scatter points. + For area-like objects (bars, scatter fills, etc) + hovering is on inside the area and off outside, but + these objects will not supersede hover on point-like + objects in case of conflict. + hoverlabel + :class:`plotly.graph_objects.layout.Hoverlabel` + instance or dict with compatible properties + hovermode + Determines the mode of hover interactions. If + "closest", a single hoverlabel will appear for the + "closest" point within the `hoverdistance`. If "x" (or + "y"), multiple hoverlabels will appear for multiple + points at the "closest" x- (or y-) coordinate within + the `hoverdistance`, with the caveat that no more than + one hoverlabel will appear per trace. If *x unified* + (or *y unified*), a single hoverlabel will appear + multiple points at the closest x- (or y-) coordinate + within the `hoverdistance` with the caveat that no more + than one hoverlabel will appear per trace. In this + mode, spikelines are enabled by default perpendicular + to the specified axis. If false, hover interactions are + disabled. + hoversubplots + Determines expansion of hover effects to other subplots + If "single" just the axis pair of the primary point is + included without overlaying subplots. If "overlaying" + all subplots using the main axis and occupying the same + space are included. If "axis", also include stacked + subplots using the same axis when `hovermode` is set to + "x", *x unified*, "y" or *y unified*. + iciclecolorway + Sets the default icicle slice colors. Defaults to the + main `colorway` used for trace colors. If you specify a + new list here it can still be extended with lighter and + darker colors, see `extendiciclecolors`. + images + A tuple of :class:`plotly.graph_objects.layout.Image` + instances or dicts with compatible properties + imagedefaults + When used in a template (as + layout.template.layout.imagedefaults), sets the default + property values to use for elements of layout.images + legend + :class:`plotly.graph_objects.layout.Legend` instance or + dict with compatible properties + map + :class:`plotly.graph_objects.layout.Map` instance or + dict with compatible properties + mapbox + :class:`plotly.graph_objects.layout.Mapbox` instance or + dict with compatible properties + margin + :class:`plotly.graph_objects.layout.Margin` instance or + dict with compatible properties + meta + Assigns extra meta information that can be used in + various `text` attributes. Attributes such as the + graph, axis and colorbar `title.text`, annotation + `text` `trace.name` in legend items, `rangeselector`, + `updatemenus` and `sliders` `label` text all support + `meta`. One can access `meta` fields using template + strings: `%{meta[i]}` where `i` is the index of the + `meta` item in question. `meta` can also be an object + for example `{key: value}` which can be accessed + %{meta[key]}. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + minreducedheight + Minimum height of the plot with margin.automargin + applied (in px) + minreducedwidth + Minimum width of the plot with margin.automargin + applied (in px) + modebar + :class:`plotly.graph_objects.layout.Modebar` instance + or dict with compatible properties + newselection + :class:`plotly.graph_objects.layout.Newselection` + instance or dict with compatible properties + newshape + :class:`plotly.graph_objects.layout.Newshape` instance + or dict with compatible properties + paper_bgcolor + Sets the background color of the paper where the graph + is drawn. + piecolorway + Sets the default pie slice colors. Defaults to the main + `colorway` used for trace colors. If you specify a new + list here it can still be extended with lighter and + darker colors, see `extendpiecolors`. + plot_bgcolor + Sets the background color of the plotting area in- + between x and y axes. + polar + :class:`plotly.graph_objects.layout.Polar` instance or + dict with compatible properties + scattergap + Sets the gap (in plot fraction) between scatter points + of adjacent location coordinates. Defaults to `bargap`. + scattermode + Determines how scatter points at the same location + coordinate are displayed on the graph. With "group", + the scatter points are plotted next to one another + centered around the shared location. With "overlay", + the scatter points are plotted over one another, you + might need to reduce "opacity" to see multiple scatter + points. + scene + :class:`plotly.graph_objects.layout.Scene` instance or + dict with compatible properties + selectdirection + When `dragmode` is set to "select", this limits the + selection of the drag to horizontal, vertical or + diagonal. "h" only allows horizontal selection, "v" + only vertical, "d" only diagonal and "any" sets no + limit. + selectionrevision + Controls persistence of user-driven changes in selected + points from all traces. + selections + A tuple of + :class:`plotly.graph_objects.layout.Selection` + instances or dicts with compatible properties + selectiondefaults + When used in a template (as + layout.template.layout.selectiondefaults), sets the + default property values to use for elements of + layout.selections + separators + Sets the decimal and thousand separators. For example, + *. * puts a '.' before decimals and a space between + thousands. In English locales, dflt is ".," but other + locales may alter this default. + shapes + A tuple of :class:`plotly.graph_objects.layout.Shape` + instances or dicts with compatible properties + shapedefaults + When used in a template (as + layout.template.layout.shapedefaults), sets the default + property values to use for elements of layout.shapes + showlegend + Determines whether or not a legend is drawn. Default is + `true` if there is a trace to show and any of these: a) + Two or more traces would by default be shown in the + legend. b) One pie trace is shown in the legend. c) One + trace is explicitly given with `showlegend: true`. + sliders + A tuple of :class:`plotly.graph_objects.layout.Slider` + instances or dicts with compatible properties + sliderdefaults + When used in a template (as + layout.template.layout.sliderdefaults), sets the + default property values to use for elements of + layout.sliders + smith + :class:`plotly.graph_objects.layout.Smith` instance or + dict with compatible properties + spikedistance + Sets the default distance (in pixels) to look for data + to draw spikelines to (-1 means no cutoff, 0 means no + looking for data). As with hoverdistance, distance does + not apply to area-like objects. In addition, some + objects can be hovered on but will not generate + spikelines, such as scatter fills. + sunburstcolorway + Sets the default sunburst slice colors. Defaults to the + main `colorway` used for trace colors. If you specify a + new list here it can still be extended with lighter and + darker colors, see `extendsunburstcolors`. + template + Default attributes to be applied to the plot. This + should be a dict with format: `{'layout': + layoutTemplate, 'data': {trace_type: [traceTemplate, + ...], ...}}` where `layoutTemplate` is a dict matching + the structure of `figure.layout` and `traceTemplate` is + a dict matching the structure of the trace with type + `trace_type` (e.g. 'scatter'). Alternatively, this may + be specified as an instance of + plotly.graph_objs.layout.Template. Trace templates are + applied cyclically to traces of each type. Container + arrays (eg `annotations`) have special handling: An + object ending in `defaults` (eg `annotationdefaults`) + is applied to each array item. But if an item has a + `templateitemname` key we look in the template array + for an item with matching `name` and apply that + instead. If no matching `name` is found we mark the + item invisible. Any named template item not referenced + is appended to the end of the array, so this can be + used to add a watermark annotation or a logo image, for + example. To omit one of these items on the plot, make + an item with matching `templateitemname` and `visible: + false`. + ternary + :class:`plotly.graph_objects.layout.Ternary` instance + or dict with compatible properties + title + :class:`plotly.graph_objects.layout.Title` instance or + dict with compatible properties + transition + Sets transition options used during Plotly.react + updates. + treemapcolorway + Sets the default treemap slice colors. Defaults to the + main `colorway` used for trace colors. If you specify a + new list here it can still be extended with lighter and + darker colors, see `extendtreemapcolors`. + uirevision + Used to allow user interactions with the plot to + persist after `Plotly.react` calls that are unaware of + these interactions. If `uirevision` is omitted, or if + it is given and it changed from the previous + `Plotly.react` call, the exact new figure is used. If + `uirevision` is truthy and did NOT change, any + attribute that has been affected by user interactions + and did not receive a different value in the new figure + will keep the interaction value. `layout.uirevision` + attribute serves as the default for `uirevision` + attributes in various sub-containers. For finer control + you can set these sub-attributes directly. For example, + if your app separately controls the data on the x and y + axes you might set `xaxis.uirevision=*time*` and + `yaxis.uirevision=*cost*`. Then if only the y data is + changed, you can update `yaxis.uirevision=*quantity*` + and the y axis range will reset but the x axis range + will retain any user-driven zoom. + uniformtext + :class:`plotly.graph_objects.layout.Uniformtext` + instance or dict with compatible properties + updatemenus + A tuple of + :class:`plotly.graph_objects.layout.Updatemenu` + instances or dicts with compatible properties + updatemenudefaults + When used in a template (as + layout.template.layout.updatemenudefaults), sets the + default property values to use for elements of + layout.updatemenus + violingap + Sets the gap (in plot fraction) between violins of + adjacent location coordinates. Has no effect on traces + that have "width" set. + violingroupgap + Sets the gap (in plot fraction) between violins of the + same location coordinate. Has no effect on traces that + have "width" set. + violinmode + Determines how violins at the same location coordinate + are displayed on the graph. If "group", the violins are + plotted next to one another centered around the shared + location. If "overlay", the violins are plotted over + one another, you might need to set "opacity" to see + them multiple violins. Has no effect on traces that + have "width" set. + waterfallgap + Sets the gap (in plot fraction) between bars of + adjacent location coordinates. + waterfallgroupgap + Sets the gap (in plot fraction) between bars of the + same location coordinate. + waterfallmode + Determines how bars at the same location coordinate are + displayed on the graph. With "group", the bars are + plotted next to one another centered around the shared + location. With "overlay", the bars are plotted over one + another, you might need to reduce "opacity" to see + multiple bars. + width + Sets the plot's width (in px). + xaxis + :class:`plotly.graph_objects.layout.XAxis` instance or + dict with compatible properties + yaxis + :class:`plotly.graph_objects.layout.YAxis` instance or + dict with compatible properties + """ + + def __init__( + self, + arg=None, + activeselection=None, + activeshape=None, + annotations=None, + annotationdefaults=None, + autosize=None, + autotypenumbers=None, + barcornerradius=None, + bargap=None, + bargroupgap=None, + barmode=None, + barnorm=None, + boxgap=None, + boxgroupgap=None, + boxmode=None, + calendar=None, + clickmode=None, + coloraxis=None, + colorscale=None, + colorway=None, + computed=None, + datarevision=None, + dragmode=None, + editrevision=None, + extendfunnelareacolors=None, + extendiciclecolors=None, + extendpiecolors=None, + extendsunburstcolors=None, + extendtreemapcolors=None, + font=None, + funnelareacolorway=None, + funnelgap=None, + funnelgroupgap=None, + funnelmode=None, + geo=None, + grid=None, + height=None, + hiddenlabels=None, + hiddenlabelssrc=None, + hidesources=None, + hoverdistance=None, + hoverlabel=None, + hovermode=None, + hoversubplots=None, + iciclecolorway=None, + images=None, + imagedefaults=None, + legend=None, + map=None, + mapbox=None, + margin=None, + meta=None, + metasrc=None, + minreducedheight=None, + minreducedwidth=None, + modebar=None, + newselection=None, + newshape=None, + paper_bgcolor=None, + piecolorway=None, + plot_bgcolor=None, + polar=None, + scattergap=None, + scattermode=None, + scene=None, + selectdirection=None, + selectionrevision=None, + selections=None, + selectiondefaults=None, + separators=None, + shapes=None, + shapedefaults=None, + showlegend=None, + sliders=None, + sliderdefaults=None, + smith=None, + spikedistance=None, + sunburstcolorway=None, + template=None, + ternary=None, + title=None, + transition=None, + treemapcolorway=None, + uirevision=None, + uniformtext=None, + updatemenus=None, + updatemenudefaults=None, + violingap=None, + violingroupgap=None, + violinmode=None, + waterfallgap=None, + waterfallgroupgap=None, + waterfallmode=None, + width=None, + xaxis=None, + yaxis=None, + **kwargs, + ): + """ + Construct a new Layout object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Layout` + activeselection + :class:`plotly.graph_objects.layout.Activeselection` + instance or dict with compatible properties + activeshape + :class:`plotly.graph_objects.layout.Activeshape` + instance or dict with compatible properties + annotations + A tuple of + :class:`plotly.graph_objects.layout.Annotation` + instances or dicts with compatible properties + annotationdefaults + When used in a template (as + layout.template.layout.annotationdefaults), sets the + default property values to use for elements of + layout.annotations + autosize + Determines whether or not a layout width or height that + has been left undefined by the user is initialized on + each relayout. Note that, regardless of this attribute, + an undefined layout width or height is always + initialized on the first call to plot. + autotypenumbers + Using "strict" a numeric string in trace data is not + converted to a number. Using *convert types* a numeric + string in trace data may be treated as a number during + automatic axis `type` detection. This is the default + value; however it could be overridden for individual + axes. + barcornerradius + Sets the rounding of bar corners. May be an integer + number of pixels, or a percentage of bar width (as a + string ending in %). + bargap + Sets the gap (in plot fraction) between bars of + adjacent location coordinates. + bargroupgap + Sets the gap (in plot fraction) between bars of the + same location coordinate. + barmode + Determines how bars at the same location coordinate are + displayed on the graph. With "stack", the bars are + stacked on top of one another With "relative", the bars + are stacked on top of one another, with negative values + below the axis, positive values above With "group", the + bars are plotted next to one another centered around + the shared location. With "overlay", the bars are + plotted over one another, you might need to reduce + "opacity" to see multiple bars. + barnorm + Sets the normalization for bar traces on the graph. + With "fraction", the value of each bar is divided by + the sum of all values at that location coordinate. + "percent" is the same but multiplied by 100 to show + percentages. + boxgap + Sets the gap (in plot fraction) between boxes of + adjacent location coordinates. Has no effect on traces + that have "width" set. + boxgroupgap + Sets the gap (in plot fraction) between boxes of the + same location coordinate. Has no effect on traces that + have "width" set. + boxmode + Determines how boxes at the same location coordinate + are displayed on the graph. If "group", the boxes are + plotted next to one another centered around the shared + location. If "overlay", the boxes are plotted over one + another, you might need to set "opacity" to see them + multiple boxes. Has no effect on traces that have + "width" set. + calendar + Sets the default calendar system to use for + interpreting and displaying dates throughout the plot. + clickmode + Determines the mode of single click interactions. + "event" is the default value and emits the + `plotly_click` event. In addition this mode emits the + `plotly_selected` event in drag modes "lasso" and + "select", but with no event data attached (kept for + compatibility reasons). The "select" flag enables + selecting single data points via click. This mode also + supports persistent selections, meaning that pressing + Shift while clicking, adds to / subtracts from an + existing selection. "select" with `hovermode`: "x" can + be confusing, consider explicitly setting `hovermode`: + "closest" when using this feature. Selection events are + sent accordingly as long as "event" flag is set as + well. When the "event" flag is missing, `plotly_click` + and `plotly_selected` events are not fired. + coloraxis + :class:`plotly.graph_objects.layout.Coloraxis` instance + or dict with compatible properties + colorscale + :class:`plotly.graph_objects.layout.Colorscale` + instance or dict with compatible properties + colorway + Sets the default trace colors. + computed + Placeholder for exporting automargin-impacting values + namely `margin.t`, `margin.b`, `margin.l` and + `margin.r` in "full-json" mode. + datarevision + If provided, a changed value tells `Plotly.react` that + one or more data arrays has changed. This way you can + modify arrays in-place rather than making a complete + new copy for an incremental change. If NOT provided, + `Plotly.react` assumes that data arrays are being + treated as immutable, thus any data array with a + different identity from its predecessor contains new + data. + dragmode + Determines the mode of drag interactions. "select" and + "lasso" apply only to scatter traces with markers or + text. "orbit" and "turntable" apply only to 3D scenes. + editrevision + Controls persistence of user-driven changes in + `editable: true` configuration, other than trace names + and axis titles. Defaults to `layout.uirevision`. + extendfunnelareacolors + If `true`, the funnelarea slice colors (whether given + by `funnelareacolorway` or inherited from `colorway`) + will be extended to three times its original length by + first repeating every color 20% lighter then each color + 20% darker. This is intended to reduce the likelihood + of reusing the same color when you have many slices, + but you can set `false` to disable. Colors provided in + the trace, using `marker.colors`, are never extended. + extendiciclecolors + If `true`, the icicle slice colors (whether given by + `iciclecolorway` or inherited from `colorway`) will be + extended to three times its original length by first + repeating every color 20% lighter then each color 20% + darker. This is intended to reduce the likelihood of + reusing the same color when you have many slices, but + you can set `false` to disable. Colors provided in the + trace, using `marker.colors`, are never extended. + extendpiecolors + If `true`, the pie slice colors (whether given by + `piecolorway` or inherited from `colorway`) will be + extended to three times its original length by first + repeating every color 20% lighter then each color 20% + darker. This is intended to reduce the likelihood of + reusing the same color when you have many slices, but + you can set `false` to disable. Colors provided in the + trace, using `marker.colors`, are never extended. + extendsunburstcolors + If `true`, the sunburst slice colors (whether given by + `sunburstcolorway` or inherited from `colorway`) will + be extended to three times its original length by first + repeating every color 20% lighter then each color 20% + darker. This is intended to reduce the likelihood of + reusing the same color when you have many slices, but + you can set `false` to disable. Colors provided in the + trace, using `marker.colors`, are never extended. + extendtreemapcolors + If `true`, the treemap slice colors (whether given by + `treemapcolorway` or inherited from `colorway`) will be + extended to three times its original length by first + repeating every color 20% lighter then each color 20% + darker. This is intended to reduce the likelihood of + reusing the same color when you have many slices, but + you can set `false` to disable. Colors provided in the + trace, using `marker.colors`, are never extended. + font + Sets the global font. Note that fonts used in traces + and other layout components inherit from the global + font. + funnelareacolorway + Sets the default funnelarea slice colors. Defaults to + the main `colorway` used for trace colors. If you + specify a new list here it can still be extended with + lighter and darker colors, see + `extendfunnelareacolors`. + funnelgap + Sets the gap (in plot fraction) between bars of + adjacent location coordinates. + funnelgroupgap + Sets the gap (in plot fraction) between bars of the + same location coordinate. + funnelmode + Determines how bars at the same location coordinate are + displayed on the graph. With "stack", the bars are + stacked on top of one another With "group", the bars + are plotted next to one another centered around the + shared location. With "overlay", the bars are plotted + over one another, you might need to reduce "opacity" to + see multiple bars. + geo + :class:`plotly.graph_objects.layout.Geo` instance or + dict with compatible properties + grid + :class:`plotly.graph_objects.layout.Grid` instance or + dict with compatible properties + height + Sets the plot's height (in px). + hiddenlabels + hiddenlabels is the funnelarea & pie chart analog of + visible:'legendonly' but it can contain many labels, + and can simultaneously hide slices from several + pies/funnelarea charts + hiddenlabelssrc + Sets the source reference on Chart Studio Cloud for + `hiddenlabels`. + hidesources + Determines whether or not a text link citing the data + source is placed at the bottom-right cored of the + figure. Has only an effect only on graphs that have + been generated via forked graphs from the Chart Studio + Cloud (at https://chart-studio.plotly.com or on- + premise). + hoverdistance + Sets the default distance (in pixels) to look for data + to add hover labels (-1 means no cutoff, 0 means no + looking for data). This is only a real distance for + hovering on point-like objects, like scatter points. + For area-like objects (bars, scatter fills, etc) + hovering is on inside the area and off outside, but + these objects will not supersede hover on point-like + objects in case of conflict. + hoverlabel + :class:`plotly.graph_objects.layout.Hoverlabel` + instance or dict with compatible properties + hovermode + Determines the mode of hover interactions. If + "closest", a single hoverlabel will appear for the + "closest" point within the `hoverdistance`. If "x" (or + "y"), multiple hoverlabels will appear for multiple + points at the "closest" x- (or y-) coordinate within + the `hoverdistance`, with the caveat that no more than + one hoverlabel will appear per trace. If *x unified* + (or *y unified*), a single hoverlabel will appear + multiple points at the closest x- (or y-) coordinate + within the `hoverdistance` with the caveat that no more + than one hoverlabel will appear per trace. In this + mode, spikelines are enabled by default perpendicular + to the specified axis. If false, hover interactions are + disabled. + hoversubplots + Determines expansion of hover effects to other subplots + If "single" just the axis pair of the primary point is + included without overlaying subplots. If "overlaying" + all subplots using the main axis and occupying the same + space are included. If "axis", also include stacked + subplots using the same axis when `hovermode` is set to + "x", *x unified*, "y" or *y unified*. + iciclecolorway + Sets the default icicle slice colors. Defaults to the + main `colorway` used for trace colors. If you specify a + new list here it can still be extended with lighter and + darker colors, see `extendiciclecolors`. + images + A tuple of :class:`plotly.graph_objects.layout.Image` + instances or dicts with compatible properties + imagedefaults + When used in a template (as + layout.template.layout.imagedefaults), sets the default + property values to use for elements of layout.images + legend + :class:`plotly.graph_objects.layout.Legend` instance or + dict with compatible properties + map + :class:`plotly.graph_objects.layout.Map` instance or + dict with compatible properties + mapbox + :class:`plotly.graph_objects.layout.Mapbox` instance or + dict with compatible properties + margin + :class:`plotly.graph_objects.layout.Margin` instance or + dict with compatible properties + meta + Assigns extra meta information that can be used in + various `text` attributes. Attributes such as the + graph, axis and colorbar `title.text`, annotation + `text` `trace.name` in legend items, `rangeselector`, + `updatemenus` and `sliders` `label` text all support + `meta`. One can access `meta` fields using template + strings: `%{meta[i]}` where `i` is the index of the + `meta` item in question. `meta` can also be an object + for example `{key: value}` which can be accessed + %{meta[key]}. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + minreducedheight + Minimum height of the plot with margin.automargin + applied (in px) + minreducedwidth + Minimum width of the plot with margin.automargin + applied (in px) + modebar + :class:`plotly.graph_objects.layout.Modebar` instance + or dict with compatible properties + newselection + :class:`plotly.graph_objects.layout.Newselection` + instance or dict with compatible properties + newshape + :class:`plotly.graph_objects.layout.Newshape` instance + or dict with compatible properties + paper_bgcolor + Sets the background color of the paper where the graph + is drawn. + piecolorway + Sets the default pie slice colors. Defaults to the main + `colorway` used for trace colors. If you specify a new + list here it can still be extended with lighter and + darker colors, see `extendpiecolors`. + plot_bgcolor + Sets the background color of the plotting area in- + between x and y axes. + polar + :class:`plotly.graph_objects.layout.Polar` instance or + dict with compatible properties + scattergap + Sets the gap (in plot fraction) between scatter points + of adjacent location coordinates. Defaults to `bargap`. + scattermode + Determines how scatter points at the same location + coordinate are displayed on the graph. With "group", + the scatter points are plotted next to one another + centered around the shared location. With "overlay", + the scatter points are plotted over one another, you + might need to reduce "opacity" to see multiple scatter + points. + scene + :class:`plotly.graph_objects.layout.Scene` instance or + dict with compatible properties + selectdirection + When `dragmode` is set to "select", this limits the + selection of the drag to horizontal, vertical or + diagonal. "h" only allows horizontal selection, "v" + only vertical, "d" only diagonal and "any" sets no + limit. + selectionrevision + Controls persistence of user-driven changes in selected + points from all traces. + selections + A tuple of + :class:`plotly.graph_objects.layout.Selection` + instances or dicts with compatible properties + selectiondefaults + When used in a template (as + layout.template.layout.selectiondefaults), sets the + default property values to use for elements of + layout.selections + separators + Sets the decimal and thousand separators. For example, + *. * puts a '.' before decimals and a space between + thousands. In English locales, dflt is ".," but other + locales may alter this default. + shapes + A tuple of :class:`plotly.graph_objects.layout.Shape` + instances or dicts with compatible properties + shapedefaults + When used in a template (as + layout.template.layout.shapedefaults), sets the default + property values to use for elements of layout.shapes + showlegend + Determines whether or not a legend is drawn. Default is + `true` if there is a trace to show and any of these: a) + Two or more traces would by default be shown in the + legend. b) One pie trace is shown in the legend. c) One + trace is explicitly given with `showlegend: true`. + sliders + A tuple of :class:`plotly.graph_objects.layout.Slider` + instances or dicts with compatible properties + sliderdefaults + When used in a template (as + layout.template.layout.sliderdefaults), sets the + default property values to use for elements of + layout.sliders + smith + :class:`plotly.graph_objects.layout.Smith` instance or + dict with compatible properties + spikedistance + Sets the default distance (in pixels) to look for data + to draw spikelines to (-1 means no cutoff, 0 means no + looking for data). As with hoverdistance, distance does + not apply to area-like objects. In addition, some + objects can be hovered on but will not generate + spikelines, such as scatter fills. + sunburstcolorway + Sets the default sunburst slice colors. Defaults to the + main `colorway` used for trace colors. If you specify a + new list here it can still be extended with lighter and + darker colors, see `extendsunburstcolors`. + template + Default attributes to be applied to the plot. This + should be a dict with format: `{'layout': + layoutTemplate, 'data': {trace_type: [traceTemplate, + ...], ...}}` where `layoutTemplate` is a dict matching + the structure of `figure.layout` and `traceTemplate` is + a dict matching the structure of the trace with type + `trace_type` (e.g. 'scatter'). Alternatively, this may + be specified as an instance of + plotly.graph_objs.layout.Template. Trace templates are + applied cyclically to traces of each type. Container + arrays (eg `annotations`) have special handling: An + object ending in `defaults` (eg `annotationdefaults`) + is applied to each array item. But if an item has a + `templateitemname` key we look in the template array + for an item with matching `name` and apply that + instead. If no matching `name` is found we mark the + item invisible. Any named template item not referenced + is appended to the end of the array, so this can be + used to add a watermark annotation or a logo image, for + example. To omit one of these items on the plot, make + an item with matching `templateitemname` and `visible: + false`. + ternary + :class:`plotly.graph_objects.layout.Ternary` instance + or dict with compatible properties + title + :class:`plotly.graph_objects.layout.Title` instance or + dict with compatible properties + transition + Sets transition options used during Plotly.react + updates. + treemapcolorway + Sets the default treemap slice colors. Defaults to the + main `colorway` used for trace colors. If you specify a + new list here it can still be extended with lighter and + darker colors, see `extendtreemapcolors`. + uirevision + Used to allow user interactions with the plot to + persist after `Plotly.react` calls that are unaware of + these interactions. If `uirevision` is omitted, or if + it is given and it changed from the previous + `Plotly.react` call, the exact new figure is used. If + `uirevision` is truthy and did NOT change, any + attribute that has been affected by user interactions + and did not receive a different value in the new figure + will keep the interaction value. `layout.uirevision` + attribute serves as the default for `uirevision` + attributes in various sub-containers. For finer control + you can set these sub-attributes directly. For example, + if your app separately controls the data on the x and y + axes you might set `xaxis.uirevision=*time*` and + `yaxis.uirevision=*cost*`. Then if only the y data is + changed, you can update `yaxis.uirevision=*quantity*` + and the y axis range will reset but the x axis range + will retain any user-driven zoom. + uniformtext + :class:`plotly.graph_objects.layout.Uniformtext` + instance or dict with compatible properties + updatemenus + A tuple of + :class:`plotly.graph_objects.layout.Updatemenu` + instances or dicts with compatible properties + updatemenudefaults + When used in a template (as + layout.template.layout.updatemenudefaults), sets the + default property values to use for elements of + layout.updatemenus + violingap + Sets the gap (in plot fraction) between violins of + adjacent location coordinates. Has no effect on traces + that have "width" set. + violingroupgap + Sets the gap (in plot fraction) between violins of the + same location coordinate. Has no effect on traces that + have "width" set. + violinmode + Determines how violins at the same location coordinate + are displayed on the graph. If "group", the violins are + plotted next to one another centered around the shared + location. If "overlay", the violins are plotted over + one another, you might need to set "opacity" to see + them multiple violins. Has no effect on traces that + have "width" set. + waterfallgap + Sets the gap (in plot fraction) between bars of + adjacent location coordinates. + waterfallgroupgap + Sets the gap (in plot fraction) between bars of the + same location coordinate. + waterfallmode + Determines how bars at the same location coordinate are + displayed on the graph. With "group", the bars are + plotted next to one another centered around the shared + location. With "overlay", the bars are plotted over one + another, you might need to reduce "opacity" to see + multiple bars. + width + Sets the plot's width (in px). + xaxis + :class:`plotly.graph_objects.layout.XAxis` instance or + dict with compatible properties + yaxis + :class:`plotly.graph_objects.layout.YAxis` instance or + dict with compatible properties + + Returns + ------- + Layout + """ + super().__init__("layout") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + self._valid_props = { + "activeselection", + "activeshape", + "annotationdefaults", + "annotations", + "autosize", + "autotypenumbers", + "barcornerradius", + "bargap", + "bargroupgap", + "barmode", + "barnorm", + "boxgap", + "boxgroupgap", + "boxmode", + "calendar", + "clickmode", + "coloraxis", + "colorscale", + "colorway", + "computed", + "datarevision", + "dragmode", + "editrevision", + "extendfunnelareacolors", + "extendiciclecolors", + "extendpiecolors", + "extendsunburstcolors", + "extendtreemapcolors", + "font", + "funnelareacolorway", + "funnelgap", + "funnelgroupgap", + "funnelmode", + "geo", + "grid", + "height", + "hiddenlabels", + "hiddenlabelssrc", + "hidesources", + "hoverdistance", + "hoverlabel", + "hovermode", + "hoversubplots", + "iciclecolorway", + "imagedefaults", + "images", + "legend", + "map", + "mapbox", + "margin", + "meta", + "metasrc", + "minreducedheight", + "minreducedwidth", + "modebar", + "newselection", + "newshape", + "paper_bgcolor", + "piecolorway", + "plot_bgcolor", + "polar", + "scattergap", + "scattermode", + "scene", + "selectdirection", + "selectiondefaults", + "selectionrevision", + "selections", + "separators", + "shapedefaults", + "shapes", + "showlegend", + "sliderdefaults", + "sliders", + "smith", + "spikedistance", + "sunburstcolorway", + "template", + "ternary", + "title", + "transition", + "treemapcolorway", + "uirevision", + "uniformtext", + "updatemenudefaults", + "updatemenus", + "violingap", + "violingroupgap", + "violinmode", + "waterfallgap", + "waterfallgroupgap", + "waterfallmode", + "width", + "xaxis", + "yaxis", + } + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Layout +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Layout`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("activeselection", arg, activeselection) + self._set_property("activeshape", arg, activeshape) + self._set_property("annotations", arg, annotations) + self._set_property("annotationdefaults", arg, annotationdefaults) + self._set_property("autosize", arg, autosize) + self._set_property("autotypenumbers", arg, autotypenumbers) + self._set_property("barcornerradius", arg, barcornerradius) + self._set_property("bargap", arg, bargap) + self._set_property("bargroupgap", arg, bargroupgap) + self._set_property("barmode", arg, barmode) + self._set_property("barnorm", arg, barnorm) + self._set_property("boxgap", arg, boxgap) + self._set_property("boxgroupgap", arg, boxgroupgap) + self._set_property("boxmode", arg, boxmode) + self._set_property("calendar", arg, calendar) + self._set_property("clickmode", arg, clickmode) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorscale", arg, colorscale) + self._set_property("colorway", arg, colorway) + self._set_property("computed", arg, computed) + self._set_property("datarevision", arg, datarevision) + self._set_property("dragmode", arg, dragmode) + self._set_property("editrevision", arg, editrevision) + self._set_property("extendfunnelareacolors", arg, extendfunnelareacolors) + self._set_property("extendiciclecolors", arg, extendiciclecolors) + self._set_property("extendpiecolors", arg, extendpiecolors) + self._set_property("extendsunburstcolors", arg, extendsunburstcolors) + self._set_property("extendtreemapcolors", arg, extendtreemapcolors) + self._set_property("font", arg, font) + self._set_property("funnelareacolorway", arg, funnelareacolorway) + self._set_property("funnelgap", arg, funnelgap) + self._set_property("funnelgroupgap", arg, funnelgroupgap) + self._set_property("funnelmode", arg, funnelmode) + self._set_property("geo", arg, geo) + self._set_property("grid", arg, grid) + self._set_property("height", arg, height) + self._set_property("hiddenlabels", arg, hiddenlabels) + self._set_property("hiddenlabelssrc", arg, hiddenlabelssrc) + self._set_property("hidesources", arg, hidesources) + self._set_property("hoverdistance", arg, hoverdistance) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovermode", arg, hovermode) + self._set_property("hoversubplots", arg, hoversubplots) + self._set_property("iciclecolorway", arg, iciclecolorway) + self._set_property("images", arg, images) + self._set_property("imagedefaults", arg, imagedefaults) + self._set_property("legend", arg, legend) + self._set_property("map", arg, map) + self._set_property("mapbox", arg, mapbox) + self._set_property("margin", arg, margin) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("minreducedheight", arg, minreducedheight) + self._set_property("minreducedwidth", arg, minreducedwidth) + self._set_property("modebar", arg, modebar) + self._set_property("newselection", arg, newselection) + self._set_property("newshape", arg, newshape) + self._set_property("paper_bgcolor", arg, paper_bgcolor) + self._set_property("piecolorway", arg, piecolorway) + self._set_property("plot_bgcolor", arg, plot_bgcolor) + self._set_property("polar", arg, polar) + self._set_property("scattergap", arg, scattergap) + self._set_property("scattermode", arg, scattermode) + self._set_property("scene", arg, scene) + self._set_property("selectdirection", arg, selectdirection) + self._set_property("selectionrevision", arg, selectionrevision) + self._set_property("selections", arg, selections) + self._set_property("selectiondefaults", arg, selectiondefaults) + self._set_property("separators", arg, separators) + self._set_property("shapes", arg, shapes) + self._set_property("shapedefaults", arg, shapedefaults) + self._set_property("showlegend", arg, showlegend) + self._set_property("sliders", arg, sliders) + self._set_property("sliderdefaults", arg, sliderdefaults) + self._set_property("smith", arg, smith) + self._set_property("spikedistance", arg, spikedistance) + self._set_property("sunburstcolorway", arg, sunburstcolorway) + self._set_property("template", arg, template) + self._set_property("ternary", arg, ternary) + self._set_property("title", arg, title) + self._set_property("transition", arg, transition) + self._set_property("treemapcolorway", arg, treemapcolorway) + self._set_property("uirevision", arg, uirevision) + self._set_property("uniformtext", arg, uniformtext) + self._set_property("updatemenus", arg, updatemenus) + self._set_property("updatemenudefaults", arg, updatemenudefaults) + self._set_property("violingap", arg, violingap) + self._set_property("violingroupgap", arg, violingroupgap) + self._set_property("violinmode", arg, violinmode) + self._set_property("waterfallgap", arg, waterfallgap) + self._set_property("waterfallgroupgap", arg, waterfallgroupgap) + self._set_property("waterfallmode", arg, waterfallmode) + self._set_property("width", arg, width) + self._set_property("xaxis", arg, xaxis) + self._set_property("yaxis", arg, yaxis) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_mesh3d.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_mesh3d.py new file mode 100644 index 0000000000000000000000000000000000000000..231b7300a8563c856afa36b2777ded5d63a43e60 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_mesh3d.py @@ -0,0 +1,2626 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Mesh3d(_BaseTraceType): + _parent_path_str = "" + _path_str = "mesh3d" + _valid_props = { + "alphahull", + "autocolorscale", + "cauto", + "cmax", + "cmid", + "cmin", + "color", + "coloraxis", + "colorbar", + "colorscale", + "contour", + "customdata", + "customdatasrc", + "delaunayaxis", + "facecolor", + "facecolorsrc", + "flatshading", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "i", + "ids", + "idssrc", + "intensity", + "intensitymode", + "intensitysrc", + "isrc", + "j", + "jsrc", + "k", + "ksrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "lighting", + "lightposition", + "meta", + "metasrc", + "name", + "opacity", + "reversescale", + "scene", + "showlegend", + "showscale", + "stream", + "text", + "textsrc", + "type", + "uid", + "uirevision", + "vertexcolor", + "vertexcolorsrc", + "visible", + "x", + "xcalendar", + "xhoverformat", + "xsrc", + "y", + "ycalendar", + "yhoverformat", + "ysrc", + "z", + "zcalendar", + "zhoverformat", + "zsrc", + } + + @property + def alphahull(self): + """ + Determines how the mesh surface triangles are derived from the + set of vertices (points) represented by the `x`, `y` and `z` + arrays, if the `i`, `j`, `k` arrays are not supplied. For + general use of `mesh3d` it is preferred that `i`, `j`, `k` are + supplied. If "-1", Delaunay triangulation is used, which is + mainly suitable if the mesh is a single, more or less layer + surface that is perpendicular to `delaunayaxis`. In case the + `delaunayaxis` intersects the mesh surface at more than one + point it will result triangles that are very long in the + dimension of `delaunayaxis`. If ">0", the alpha-shape algorithm + is used. In this case, the positive `alphahull` value signals + the use of the alpha-shape algorithm, _and_ its value acts as + the parameter for the mesh fitting. If 0, the convex-hull + algorithm is used. It is suitable for convex bodies or if the + intention is to enclose the `x`, `y` and `z` point set into a + convex hull. + + The 'alphahull' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["alphahull"] + + @alphahull.setter + def alphahull(self, val): + self["alphahull"] = val + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def cauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here `intensity`) or the bounds set + in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` + are set by the user. + + The 'cauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cauto"] + + @cauto.setter + def cauto(self, val): + self["cauto"] = val + + @property + def cmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as `intensity` and if set, `cmin` must be set as + well. + + The 'cmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmax"] + + @cmax.setter + def cmax(self, val): + self["cmax"] = val + + @property + def cmid(self): + """ + Sets the mid-point of the color domain by scaling `cmin` and/or + `cmax` to be equidistant to this point. Value should have the + same units as `intensity`. Has no effect when `cauto` is + `false`. + + The 'cmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmid"] + + @cmid.setter + def cmid(self, val): + self["cmid"] = val + + @property + def cmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as `intensity` and if set, `cmax` must be set as + well. + + The 'cmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmin"] + + @cmin.setter + def cmin(self, val): + self["cmin"] = val + + @property + def color(self): + """ + Sets the color of the whole mesh + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A number that will be interpreted as a color + according to mesh3d.colorscale + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.mesh3d.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.mesh3d.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def contour(self): + """ + The 'contour' property is an instance of Contour + that may be specified as: + - An instance of :class:`plotly.graph_objs.mesh3d.Contour` + - A dict of string/value properties that will be passed + to the Contour constructor + + Returns + ------- + plotly.graph_objs.mesh3d.Contour + """ + return self["contour"] + + @contour.setter + def contour(self, val): + self["contour"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def delaunayaxis(self): + """ + Sets the Delaunay axis, which is the axis that is perpendicular + to the surface of the Delaunay triangulation. It has an effect + if `i`, `j`, `k` are not provided and `alphahull` is set to + indicate Delaunay triangulation. + + The 'delaunayaxis' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['x', 'y', 'z'] + + Returns + ------- + Any + """ + return self["delaunayaxis"] + + @delaunayaxis.setter + def delaunayaxis(self, val): + self["delaunayaxis"] = val + + @property + def facecolor(self): + """ + Sets the color of each face Overrides "color" and + "vertexcolor". + + The 'facecolor' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["facecolor"] + + @facecolor.setter + def facecolor(self, val): + self["facecolor"] = val + + @property + def facecolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `facecolor`. + + The 'facecolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["facecolorsrc"] + + @facecolorsrc.setter + def facecolorsrc(self, val): + self["facecolorsrc"] = val + + @property + def flatshading(self): + """ + Determines whether or not normal smoothing is applied to the + meshes, creating meshes with an angular, low-poly look via flat + reflections. + + The 'flatshading' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["flatshading"] + + @flatshading.setter + def flatshading(self, val): + self["flatshading"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.mesh3d.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.mesh3d.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def i(self): + """ + A vector of vertex indices, i.e. integer values between 0 and + the length of the vertex vectors, representing the "first" + vertex of a triangle. For example, `{i[m], j[m], k[m]}` + together represent face m (triangle m) in the mesh, where `i[m] + = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex + arrays. Therefore, each element in `i` represents a point in + space, which is the first vertex of a triangle. + + The 'i' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["i"] + + @i.setter + def i(self, val): + self["i"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def intensity(self): + """ + Sets the intensity values for vertices or cells as defined by + `intensitymode`. It can be used for plotting fields on meshes. + + The 'intensity' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["intensity"] + + @intensity.setter + def intensity(self, val): + self["intensity"] = val + + @property + def intensitymode(self): + """ + Determines the source of `intensity` values. + + The 'intensitymode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['vertex', 'cell'] + + Returns + ------- + Any + """ + return self["intensitymode"] + + @intensitymode.setter + def intensitymode(self, val): + self["intensitymode"] = val + + @property + def intensitysrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `intensity`. + + The 'intensitysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["intensitysrc"] + + @intensitysrc.setter + def intensitysrc(self, val): + self["intensitysrc"] = val + + @property + def isrc(self): + """ + Sets the source reference on Chart Studio Cloud for `i`. + + The 'isrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["isrc"] + + @isrc.setter + def isrc(self, val): + self["isrc"] = val + + @property + def j(self): + """ + A vector of vertex indices, i.e. integer values between 0 and + the length of the vertex vectors, representing the "second" + vertex of a triangle. For example, `{i[m], j[m], k[m]}` + together represent face m (triangle m) in the mesh, where `j[m] + = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex + arrays. Therefore, each element in `j` represents a point in + space, which is the second vertex of a triangle. + + The 'j' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["j"] + + @j.setter + def j(self, val): + self["j"] = val + + @property + def jsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `j`. + + The 'jsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["jsrc"] + + @jsrc.setter + def jsrc(self, val): + self["jsrc"] = val + + @property + def k(self): + """ + A vector of vertex indices, i.e. integer values between 0 and + the length of the vertex vectors, representing the "third" + vertex of a triangle. For example, `{i[m], j[m], k[m]}` + together represent face m (triangle m) in the mesh, where `k[m] + = n` points to the triplet `{x[n], y[n], z[n]}` in the vertex + arrays. Therefore, each element in `k` represents a point in + space, which is the third vertex of a triangle. + + The 'k' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["k"] + + @k.setter + def k(self, val): + self["k"] = val + + @property + def ksrc(self): + """ + Sets the source reference on Chart Studio Cloud for `k`. + + The 'ksrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ksrc"] + + @ksrc.setter + def ksrc(self, val): + self["ksrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.mesh3d.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.mesh3d.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def lighting(self): + """ + The 'lighting' property is an instance of Lighting + that may be specified as: + - An instance of :class:`plotly.graph_objs.mesh3d.Lighting` + - A dict of string/value properties that will be passed + to the Lighting constructor + + Returns + ------- + plotly.graph_objs.mesh3d.Lighting + """ + return self["lighting"] + + @lighting.setter + def lighting(self, val): + self["lighting"] = val + + @property + def lightposition(self): + """ + The 'lightposition' property is an instance of Lightposition + that may be specified as: + - An instance of :class:`plotly.graph_objs.mesh3d.Lightposition` + - A dict of string/value properties that will be passed + to the Lightposition constructor + + Returns + ------- + plotly.graph_objs.mesh3d.Lightposition + """ + return self["lightposition"] + + @lightposition.setter + def lightposition(self, val): + self["lightposition"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the surface. Please note that in the case + of using high `opacity` values for example a value greater than + or equal to 0.5 on two surfaces (and 0.25 with four surfaces), + an overlay of multiple transparent surfaces may not perfectly + be sorted in depth by the webgl API. This behavior may be + improved in the near future and is subject to change. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `cmin` will + correspond to the last color in the array and `cmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def scene(self): + """ + Sets a reference between this trace's 3D coordinate system and + a 3D scene. If "scene" (the default value), the (x,y,z) + coordinates refer to `layout.scene`. If "scene2", the (x,y,z) + coordinates refer to `layout.scene2`, and so on. + + The 'scene' property is an identifier of a particular + subplot, of type 'scene', that may be specified as: + - the string 'scene' optionally followed by an integer >= 1 + (e.g. 'scene', 'scene1', 'scene2', 'scene3', etc.) + + Returns + ------- + str + """ + return self["scene"] + + @scene.setter + def scene(self, val): + self["scene"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.mesh3d.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.mesh3d.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets the text elements associated with the vertices. If trace + `hoverinfo` contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def vertexcolor(self): + """ + Sets the color of each vertex Overrides "color". While Red, + green and blue colors are in the range of 0 and 255; in the + case of having vertex color data in RGBA format, the alpha + color should be normalized to be between 0 and 1. + + The 'vertexcolor' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["vertexcolor"] + + @vertexcolor.setter + def vertexcolor(self, val): + self["vertexcolor"] = val + + @property + def vertexcolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `vertexcolor`. + + The 'vertexcolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["vertexcolorsrc"] + + @vertexcolorsrc.setter + def vertexcolorsrc(self, val): + self["vertexcolorsrc"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the X coordinates of the vertices. The nth element of + vectors `x`, `y` and `z` jointly represent the X, Y and Z + coordinates of the nth vertex. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xcalendar(self): + """ + Sets the calendar system to use with `x` date data. + + The 'xcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["xcalendar"] + + @xcalendar.setter + def xcalendar(self, val): + self["xcalendar"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the Y coordinates of the vertices. The nth element of + vectors `x`, `y` and `z` jointly represent the X, Y and Z + coordinates of the nth vertex. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def ycalendar(self): + """ + Sets the calendar system to use with `y` date data. + + The 'ycalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["ycalendar"] + + @ycalendar.setter + def ycalendar(self, val): + self["ycalendar"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def z(self): + """ + Sets the Z coordinates of the vertices. The nth element of + vectors `x`, `y` and `z` jointly represent the X, Y and Z + coordinates of the nth vertex. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zcalendar(self): + """ + Sets the calendar system to use with `z` date data. + + The 'zcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["zcalendar"] + + @zcalendar.setter + def zcalendar(self, val): + self["zcalendar"] = val + + @property + def zhoverformat(self): + """ + Sets the hover text formatting rulefor `z` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `zaxis.hoverformat`. + + The 'zhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["zhoverformat"] + + @zhoverformat.setter + def zhoverformat(self, val): + self["zhoverformat"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + alphahull + Determines how the mesh surface triangles are derived + from the set of vertices (points) represented by the + `x`, `y` and `z` arrays, if the `i`, `j`, `k` arrays + are not supplied. For general use of `mesh3d` it is + preferred that `i`, `j`, `k` are supplied. If "-1", + Delaunay triangulation is used, which is mainly + suitable if the mesh is a single, more or less layer + surface that is perpendicular to `delaunayaxis`. In + case the `delaunayaxis` intersects the mesh surface at + more than one point it will result triangles that are + very long in the dimension of `delaunayaxis`. If ">0", + the alpha-shape algorithm is used. In this case, the + positive `alphahull` value signals the use of the + alpha-shape algorithm, _and_ its value acts as the + parameter for the mesh fitting. If 0, the convex-hull + algorithm is used. It is suitable for convex bodies or + if the intention is to enclose the `x`, `y` and `z` + point set into a convex hull. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here `intensity`) or + the bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as `intensity` and if set, `cmin` + must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as `intensity`. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as `intensity` and if set, `cmax` + must be set as well. + color + Sets the color of the whole mesh + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.mesh3d.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contour + :class:`plotly.graph_objects.mesh3d.Contour` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + delaunayaxis + Sets the Delaunay axis, which is the axis that is + perpendicular to the surface of the Delaunay + triangulation. It has an effect if `i`, `j`, `k` are + not provided and `alphahull` is set to indicate + Delaunay triangulation. + facecolor + Sets the color of each face Overrides "color" and + "vertexcolor". + facecolorsrc + Sets the source reference on Chart Studio Cloud for + `facecolor`. + flatshading + Determines whether or not normal smoothing is applied + to the meshes, creating meshes with an angular, low- + poly look via flat reflections. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.mesh3d.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + i + A vector of vertex indices, i.e. integer values between + 0 and the length of the vertex vectors, representing + the "first" vertex of a triangle. For example, `{i[m], + j[m], k[m]}` together represent face m (triangle m) in + the mesh, where `i[m] = n` points to the triplet + `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, + each element in `i` represents a point in space, which + is the first vertex of a triangle. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + intensity + Sets the intensity values for vertices or cells as + defined by `intensitymode`. It can be used for plotting + fields on meshes. + intensitymode + Determines the source of `intensity` values. + intensitysrc + Sets the source reference on Chart Studio Cloud for + `intensity`. + isrc + Sets the source reference on Chart Studio Cloud for + `i`. + j + A vector of vertex indices, i.e. integer values between + 0 and the length of the vertex vectors, representing + the "second" vertex of a triangle. For example, `{i[m], + j[m], k[m]}` together represent face m (triangle m) in + the mesh, where `j[m] = n` points to the triplet + `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, + each element in `j` represents a point in space, which + is the second vertex of a triangle. + jsrc + Sets the source reference on Chart Studio Cloud for + `j`. + k + A vector of vertex indices, i.e. integer values between + 0 and the length of the vertex vectors, representing + the "third" vertex of a triangle. For example, `{i[m], + j[m], k[m]}` together represent face m (triangle m) in + the mesh, where `k[m] = n` points to the triplet + `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, + each element in `k` represents a point in space, which + is the third vertex of a triangle. + ksrc + Sets the source reference on Chart Studio Cloud for + `k`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.mesh3d.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.mesh3d.Lighting` instance + or dict with compatible properties + lightposition + :class:`plotly.graph_objects.mesh3d.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.mesh3d.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with the vertices. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + vertexcolor + Sets the color of each vertex Overrides "color". While + Red, green and blue colors are in the range of 0 and + 255; in the case of having vertex color data in RGBA + format, the alpha color should be normalized to be + between 0 and 1. + vertexcolorsrc + Sets the source reference on Chart Studio Cloud for + `vertexcolor`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the X coordinates of the vertices. The nth element + of vectors `x`, `y` and `z` jointly represent the X, Y + and Z coordinates of the nth vertex. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the Y coordinates of the vertices. The nth element + of vectors `x`, `y` and `z` jointly represent the X, Y + and Z coordinates of the nth vertex. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the Z coordinates of the vertices. The nth element + of vectors `x`, `y` and `z` jointly represent the X, Y + and Z coordinates of the nth vertex. + zcalendar + Sets the calendar system to use with `z` date data. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + alphahull=None, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + color=None, + coloraxis=None, + colorbar=None, + colorscale=None, + contour=None, + customdata=None, + customdatasrc=None, + delaunayaxis=None, + facecolor=None, + facecolorsrc=None, + flatshading=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + i=None, + ids=None, + idssrc=None, + intensity=None, + intensitymode=None, + intensitysrc=None, + isrc=None, + j=None, + jsrc=None, + k=None, + ksrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + vertexcolor=None, + vertexcolorsrc=None, + visible=None, + x=None, + xcalendar=None, + xhoverformat=None, + xsrc=None, + y=None, + ycalendar=None, + yhoverformat=None, + ysrc=None, + z=None, + zcalendar=None, + zhoverformat=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Mesh3d object + + Draws sets of triangles with coordinates given by three + 1-dimensional arrays in `x`, `y`, `z` and (1) a sets of `i`, + `j`, `k` indices (2) Delaunay triangulation or (3) the Alpha- + shape algorithm or (4) the Convex-hull algorithm + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Mesh3d` + alphahull + Determines how the mesh surface triangles are derived + from the set of vertices (points) represented by the + `x`, `y` and `z` arrays, if the `i`, `j`, `k` arrays + are not supplied. For general use of `mesh3d` it is + preferred that `i`, `j`, `k` are supplied. If "-1", + Delaunay triangulation is used, which is mainly + suitable if the mesh is a single, more or less layer + surface that is perpendicular to `delaunayaxis`. In + case the `delaunayaxis` intersects the mesh surface at + more than one point it will result triangles that are + very long in the dimension of `delaunayaxis`. If ">0", + the alpha-shape algorithm is used. In this case, the + positive `alphahull` value signals the use of the + alpha-shape algorithm, _and_ its value acts as the + parameter for the mesh fitting. If 0, the convex-hull + algorithm is used. It is suitable for convex bodies or + if the intention is to enclose the `x`, `y` and `z` + point set into a convex hull. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here `intensity`) or + the bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as `intensity` and if set, `cmin` + must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as `intensity`. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as `intensity` and if set, `cmax` + must be set as well. + color + Sets the color of the whole mesh + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.mesh3d.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contour + :class:`plotly.graph_objects.mesh3d.Contour` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + delaunayaxis + Sets the Delaunay axis, which is the axis that is + perpendicular to the surface of the Delaunay + triangulation. It has an effect if `i`, `j`, `k` are + not provided and `alphahull` is set to indicate + Delaunay triangulation. + facecolor + Sets the color of each face Overrides "color" and + "vertexcolor". + facecolorsrc + Sets the source reference on Chart Studio Cloud for + `facecolor`. + flatshading + Determines whether or not normal smoothing is applied + to the meshes, creating meshes with an angular, low- + poly look via flat reflections. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.mesh3d.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + i + A vector of vertex indices, i.e. integer values between + 0 and the length of the vertex vectors, representing + the "first" vertex of a triangle. For example, `{i[m], + j[m], k[m]}` together represent face m (triangle m) in + the mesh, where `i[m] = n` points to the triplet + `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, + each element in `i` represents a point in space, which + is the first vertex of a triangle. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + intensity + Sets the intensity values for vertices or cells as + defined by `intensitymode`. It can be used for plotting + fields on meshes. + intensitymode + Determines the source of `intensity` values. + intensitysrc + Sets the source reference on Chart Studio Cloud for + `intensity`. + isrc + Sets the source reference on Chart Studio Cloud for + `i`. + j + A vector of vertex indices, i.e. integer values between + 0 and the length of the vertex vectors, representing + the "second" vertex of a triangle. For example, `{i[m], + j[m], k[m]}` together represent face m (triangle m) in + the mesh, where `j[m] = n` points to the triplet + `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, + each element in `j` represents a point in space, which + is the second vertex of a triangle. + jsrc + Sets the source reference on Chart Studio Cloud for + `j`. + k + A vector of vertex indices, i.e. integer values between + 0 and the length of the vertex vectors, representing + the "third" vertex of a triangle. For example, `{i[m], + j[m], k[m]}` together represent face m (triangle m) in + the mesh, where `k[m] = n` points to the triplet + `{x[n], y[n], z[n]}` in the vertex arrays. Therefore, + each element in `k` represents a point in space, which + is the third vertex of a triangle. + ksrc + Sets the source reference on Chart Studio Cloud for + `k`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.mesh3d.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.mesh3d.Lighting` instance + or dict with compatible properties + lightposition + :class:`plotly.graph_objects.mesh3d.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.mesh3d.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with the vertices. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + vertexcolor + Sets the color of each vertex Overrides "color". While + Red, green and blue colors are in the range of 0 and + 255; in the case of having vertex color data in RGBA + format, the alpha color should be normalized to be + between 0 and 1. + vertexcolorsrc + Sets the source reference on Chart Studio Cloud for + `vertexcolor`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the X coordinates of the vertices. The nth element + of vectors `x`, `y` and `z` jointly represent the X, Y + and Z coordinates of the nth vertex. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the Y coordinates of the vertices. The nth element + of vectors `x`, `y` and `z` jointly represent the X, Y + and Z coordinates of the nth vertex. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the Z coordinates of the vertices. The nth element + of vectors `x`, `y` and `z` jointly represent the X, Y + and Z coordinates of the nth vertex. + zcalendar + Sets the calendar system to use with `z` date data. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Mesh3d + """ + super().__init__("mesh3d") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Mesh3d +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Mesh3d`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("alphahull", arg, alphahull) + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("cauto", arg, cauto) + self._set_property("cmax", arg, cmax) + self._set_property("cmid", arg, cmid) + self._set_property("cmin", arg, cmin) + self._set_property("color", arg, color) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("contour", arg, contour) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("delaunayaxis", arg, delaunayaxis) + self._set_property("facecolor", arg, facecolor) + self._set_property("facecolorsrc", arg, facecolorsrc) + self._set_property("flatshading", arg, flatshading) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("i", arg, i) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("intensity", arg, intensity) + self._set_property("intensitymode", arg, intensitymode) + self._set_property("intensitysrc", arg, intensitysrc) + self._set_property("isrc", arg, isrc) + self._set_property("j", arg, j) + self._set_property("jsrc", arg, jsrc) + self._set_property("k", arg, k) + self._set_property("ksrc", arg, ksrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("lighting", arg, lighting) + self._set_property("lightposition", arg, lightposition) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("reversescale", arg, reversescale) + self._set_property("scene", arg, scene) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("vertexcolor", arg, vertexcolor) + self._set_property("vertexcolorsrc", arg, vertexcolorsrc) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("xcalendar", arg, xcalendar) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("ycalendar", arg, ycalendar) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("ysrc", arg, ysrc) + self._set_property("z", arg, z) + self._set_property("zcalendar", arg, zcalendar) + self._set_property("zhoverformat", arg, zhoverformat) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "mesh3d" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_ohlc.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_ohlc.py new file mode 100644 index 0000000000000000000000000000000000000000..d8376e8aae6405ce227b980d2d219fb1cac697a3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_ohlc.py @@ -0,0 +1,1858 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Ohlc(_BaseTraceType): + _parent_path_str = "" + _path_str = "ohlc" + _valid_props = { + "close", + "closesrc", + "customdata", + "customdatasrc", + "decreasing", + "high", + "highsrc", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "increasing", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "low", + "lowsrc", + "meta", + "metasrc", + "name", + "opacity", + "open", + "opensrc", + "selectedpoints", + "showlegend", + "stream", + "text", + "textsrc", + "tickwidth", + "type", + "uid", + "uirevision", + "visible", + "x", + "xaxis", + "xcalendar", + "xhoverformat", + "xperiod", + "xperiod0", + "xperiodalignment", + "xsrc", + "yaxis", + "yhoverformat", + "zorder", + } + + @property + def close(self): + """ + Sets the close values. + + The 'close' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["close"] + + @close.setter + def close(self, val): + self["close"] = val + + @property + def closesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `close`. + + The 'closesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["closesrc"] + + @closesrc.setter + def closesrc(self, val): + self["closesrc"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def decreasing(self): + """ + The 'decreasing' property is an instance of Decreasing + that may be specified as: + - An instance of :class:`plotly.graph_objs.ohlc.Decreasing` + - A dict of string/value properties that will be passed + to the Decreasing constructor + + Returns + ------- + plotly.graph_objs.ohlc.Decreasing + """ + return self["decreasing"] + + @decreasing.setter + def decreasing(self, val): + self["decreasing"] = val + + @property + def high(self): + """ + Sets the high values. + + The 'high' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["high"] + + @high.setter + def high(self, val): + self["high"] = val + + @property + def highsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `high`. + + The 'highsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["highsrc"] + + @highsrc.setter + def highsrc(self, val): + self["highsrc"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.ohlc.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.ohlc.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables `open`, + `high`, `low` and `close`. Anything contained in tag `` + is displayed in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def increasing(self): + """ + The 'increasing' property is an instance of Increasing + that may be specified as: + - An instance of :class:`plotly.graph_objs.ohlc.Increasing` + - A dict of string/value properties that will be passed + to the Increasing constructor + + Returns + ------- + plotly.graph_objs.ohlc.Increasing + """ + return self["increasing"] + + @increasing.setter + def increasing(self, val): + self["increasing"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.ohlc.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.ohlc.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.ohlc.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.ohlc.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def low(self): + """ + Sets the low values. + + The 'low' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["low"] + + @low.setter + def low(self, val): + self["low"] = val + + @property + def lowsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `low`. + + The 'lowsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["lowsrc"] + + @lowsrc.setter + def lowsrc(self, val): + self["lowsrc"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def open(self): + """ + Sets the open values. + + The 'open' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["open"] + + @open.setter + def open(self, val): + self["open"] = val + + @property + def opensrc(self): + """ + Sets the source reference on Chart Studio Cloud for `open`. + + The 'opensrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["opensrc"] + + @opensrc.setter + def opensrc(self, val): + self["opensrc"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.ohlc.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.ohlc.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets hover text elements associated with each sample point. If + a single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + this trace's sample points. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def tickwidth(self): + """ + Sets the width of the open/close tick marks relative to the "x" + minimal interval. + + The 'tickwidth' property is a number and may be specified as: + - An int or float in the interval [0, 0.5] + + Returns + ------- + int|float + """ + return self["tickwidth"] + + @tickwidth.setter + def tickwidth(self, val): + self["tickwidth"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the x coordinates. If absent, linear coordinate will be + generated. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def xcalendar(self): + """ + Sets the calendar system to use with `x` date data. + + The 'xcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["xcalendar"] + + @xcalendar.setter + def xcalendar(self, val): + self["xcalendar"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the x axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'xperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod"] + + @xperiod.setter + def xperiod(self, val): + self["xperiod"] = val + + @property + def xperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the x0 + axis. When `x0period` is round number of weeks, the `x0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'xperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod0"] + + @xperiod0.setter + def xperiod0(self, val): + self["xperiod0"] = val + + @property + def xperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + + The 'xperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["xperiodalignment"] + + @xperiodalignment.setter + def xperiodalignment(self, val): + self["xperiodalignment"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def zorder(self): + """ + Sets the layer on which this trace is displayed, relative to + other SVG traces on the same subplot. SVG traces with higher + `zorder` appear in front of those with lower `zorder`. + + The 'zorder' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["zorder"] + + @zorder.setter + def zorder(self, val): + self["zorder"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + close + Sets the close values. + closesrc + Sets the source reference on Chart Studio Cloud for + `close`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + decreasing + :class:`plotly.graph_objects.ohlc.Decreasing` instance + or dict with compatible properties + high + Sets the high values. + highsrc + Sets the source reference on Chart Studio Cloud for + `high`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.ohlc.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `open`, `high`, `low` and `close`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + increasing + :class:`plotly.graph_objects.ohlc.Increasing` instance + or dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.ohlc.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.ohlc.Line` instance or + dict with compatible properties + low + Sets the low values. + lowsrc + Sets the source reference on Chart Studio Cloud for + `low`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + open + Sets the open values. + opensrc + Sets the source reference on Chart Studio Cloud for + `open`. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.ohlc.Stream` instance or + dict with compatible properties + text + Sets hover text elements associated with each sample + point. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to this trace's sample points. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + tickwidth + Sets the width of the open/close tick marks relative to + the "x" minimal interval. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. If absent, linear coordinate + will be generated. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + """ + + def __init__( + self, + arg=None, + close=None, + closesrc=None, + customdata=None, + customdatasrc=None, + decreasing=None, + high=None, + highsrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + increasing=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + low=None, + lowsrc=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + open=None, + opensrc=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textsrc=None, + tickwidth=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + yaxis=None, + yhoverformat=None, + zorder=None, + **kwargs, + ): + """ + Construct a new Ohlc object + + The ohlc (short for Open-High-Low-Close) is a style of + financial chart describing open, high, low and close for a + given `x` coordinate (most likely time). The tip of the lines + represent the `low` and `high` values and the horizontal + segments represent the `open` and `close` values. Sample points + where the close value is higher (lower) then the open value are + called increasing (decreasing). By default, increasing items + are drawn in green whereas decreasing are drawn in red. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Ohlc` + close + Sets the close values. + closesrc + Sets the source reference on Chart Studio Cloud for + `close`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + decreasing + :class:`plotly.graph_objects.ohlc.Decreasing` instance + or dict with compatible properties + high + Sets the high values. + highsrc + Sets the source reference on Chart Studio Cloud for + `high`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.ohlc.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `open`, `high`, `low` and `close`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + increasing + :class:`plotly.graph_objects.ohlc.Increasing` instance + or dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.ohlc.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.ohlc.Line` instance or + dict with compatible properties + low + Sets the low values. + lowsrc + Sets the source reference on Chart Studio Cloud for + `low`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + open + Sets the open values. + opensrc + Sets the source reference on Chart Studio Cloud for + `open`. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.ohlc.Stream` instance or + dict with compatible properties + text + Sets hover text elements associated with each sample + point. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to this trace's sample points. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + tickwidth + Sets the width of the open/close tick marks relative to + the "x" minimal interval. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. If absent, linear coordinate + will be generated. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + + Returns + ------- + Ohlc + """ + super().__init__("ohlc") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Ohlc +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Ohlc`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("close", arg, close) + self._set_property("closesrc", arg, closesrc) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("decreasing", arg, decreasing) + self._set_property("high", arg, high) + self._set_property("highsrc", arg, highsrc) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("increasing", arg, increasing) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("low", arg, low) + self._set_property("lowsrc", arg, lowsrc) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("open", arg, open) + self._set_property("opensrc", arg, opensrc) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("tickwidth", arg, tickwidth) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("xaxis", arg, xaxis) + self._set_property("xcalendar", arg, xcalendar) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xperiod", arg, xperiod) + self._set_property("xperiod0", arg, xperiod0) + self._set_property("xperiodalignment", arg, xperiodalignment) + self._set_property("xsrc", arg, xsrc) + self._set_property("yaxis", arg, yaxis) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("zorder", arg, zorder) + + self._props["type"] = "ohlc" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_parcats.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_parcats.py new file mode 100644 index 0000000000000000000000000000000000000000..2c444dd54ebc7b72e8ece941d03c8efb21682633 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_parcats.py @@ -0,0 +1,971 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Parcats(_BaseTraceType): + _parent_path_str = "" + _path_str = "parcats" + _valid_props = { + "arrangement", + "bundlecolors", + "counts", + "countssrc", + "dimensiondefaults", + "dimensions", + "domain", + "hoverinfo", + "hoveron", + "hovertemplate", + "hovertemplatefallback", + "labelfont", + "legendgrouptitle", + "legendwidth", + "line", + "meta", + "metasrc", + "name", + "sortpaths", + "stream", + "tickfont", + "type", + "uid", + "uirevision", + "visible", + } + + @property + def arrangement(self): + """ + Sets the drag interaction mode for categories and dimensions. + If `perpendicular`, the categories can only move along a line + perpendicular to the paths. If `freeform`, the categories can + freely move on the plane. If `fixed`, the categories and + dimensions are stationary. + + The 'arrangement' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['perpendicular', 'freeform', 'fixed'] + + Returns + ------- + Any + """ + return self["arrangement"] + + @arrangement.setter + def arrangement(self, val): + self["arrangement"] = val + + @property + def bundlecolors(self): + """ + Sort paths so that like colors are bundled together within each + category. + + The 'bundlecolors' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["bundlecolors"] + + @bundlecolors.setter + def bundlecolors(self, val): + self["bundlecolors"] = val + + @property + def counts(self): + """ + The number of observations represented by each state. Defaults + to 1 so that each state represents one observation + + The 'counts' property is a number and may be specified as: + - An int or float in the interval [0, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["counts"] + + @counts.setter + def counts(self, val): + self["counts"] = val + + @property + def countssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `counts`. + + The 'countssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["countssrc"] + + @countssrc.setter + def countssrc(self, val): + self["countssrc"] = val + + @property + def dimensions(self): + """ + The dimensions (variables) of the parallel categories diagram. + + The 'dimensions' property is a tuple of instances of + Dimension that may be specified as: + - A list or tuple of instances of plotly.graph_objs.parcats.Dimension + - A list or tuple of dicts of string/value properties that + will be passed to the Dimension constructor + + Returns + ------- + tuple[plotly.graph_objs.parcats.Dimension] + """ + return self["dimensions"] + + @dimensions.setter + def dimensions(self, val): + self["dimensions"] = val + + @property + def dimensiondefaults(self): + """ + When used in a template (as + layout.template.data.parcats.dimensiondefaults), sets the + default property values to use for elements of + parcats.dimensions + + The 'dimensiondefaults' property is an instance of Dimension + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcats.Dimension` + - A dict of string/value properties that will be passed + to the Dimension constructor + + Returns + ------- + plotly.graph_objs.parcats.Dimension + """ + return self["dimensiondefaults"] + + @dimensiondefaults.setter + def dimensiondefaults(self, val): + self["dimensiondefaults"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcats.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.parcats.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['count', 'probability'] joined with '+' characters + (e.g. 'count+probability') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + + Returns + ------- + Any + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoveron(self): + """ + Sets the hover interaction mode for the parcats diagram. If + `category`, hover interaction take place per category. If + `color`, hover interactions take place per color per category. + If `dimension`, hover interactions take place across all + categories per dimension. + + The 'hoveron' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['category', 'color', 'dimension'] + + Returns + ------- + Any + """ + return self["hoveron"] + + @hoveron.setter + def hoveron(self, val): + self["hoveron"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables `count`, + `probability`, `category`, `categorycount`, `colorcount` and + `bandcolorcount`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def labelfont(self): + """ + Sets the font for the `dimension` labels. + + The 'labelfont' property is an instance of Labelfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcats.Labelfont` + - A dict of string/value properties that will be passed + to the Labelfont constructor + + Returns + ------- + plotly.graph_objs.parcats.Labelfont + """ + return self["labelfont"] + + @labelfont.setter + def labelfont(self, val): + self["labelfont"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcats.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.parcats.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcats.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.parcats.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def sortpaths(self): + """ + Sets the path sorting algorithm. If `forward`, sort paths based + on dimension categories from left to right. If `backward`, sort + paths based on dimensions categories from right to left. + + The 'sortpaths' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['forward', 'backward'] + + Returns + ------- + Any + """ + return self["sortpaths"] + + @sortpaths.setter + def sortpaths(self, val): + self["sortpaths"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcats.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.parcats.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def tickfont(self): + """ + Sets the font for the `category` labels. + + The 'tickfont' property is an instance of Tickfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcats.Tickfont` + - A dict of string/value properties that will be passed + to the Tickfont constructor + + Returns + ------- + plotly.graph_objs.parcats.Tickfont + """ + return self["tickfont"] + + @tickfont.setter + def tickfont(self, val): + self["tickfont"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + arrangement + Sets the drag interaction mode for categories and + dimensions. If `perpendicular`, the categories can only + move along a line perpendicular to the paths. If + `freeform`, the categories can freely move on the + plane. If `fixed`, the categories and dimensions are + stationary. + bundlecolors + Sort paths so that like colors are bundled together + within each category. + counts + The number of observations represented by each state. + Defaults to 1 so that each state represents one + observation + countssrc + Sets the source reference on Chart Studio Cloud for + `counts`. + dimensions + The dimensions (variables) of the parallel categories + diagram. + dimensiondefaults + When used in a template (as + layout.template.data.parcats.dimensiondefaults), sets + the default property values to use for elements of + parcats.dimensions + domain + :class:`plotly.graph_objects.parcats.Domain` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoveron + Sets the hover interaction mode for the parcats + diagram. If `category`, hover interaction take place + per category. If `color`, hover interactions take place + per color per category. If `dimension`, hover + interactions take place across all categories per + dimension. + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `count`, `probability`, `category`, + `categorycount`, `colorcount` and `bandcolorcount`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + labelfont + Sets the font for the `dimension` labels. + legendgrouptitle + :class:`plotly.graph_objects.parcats.Legendgrouptitle` + instance or dict with compatible properties + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.parcats.Line` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + sortpaths + Sets the path sorting algorithm. If `forward`, sort + paths based on dimension categories from left to right. + If `backward`, sort paths based on dimensions + categories from right to left. + stream + :class:`plotly.graph_objects.parcats.Stream` instance + or dict with compatible properties + tickfont + Sets the font for the `category` labels. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + arrangement=None, + bundlecolors=None, + counts=None, + countssrc=None, + dimensions=None, + dimensiondefaults=None, + domain=None, + hoverinfo=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + labelfont=None, + legendgrouptitle=None, + legendwidth=None, + line=None, + meta=None, + metasrc=None, + name=None, + sortpaths=None, + stream=None, + tickfont=None, + uid=None, + uirevision=None, + visible=None, + **kwargs, + ): + """ + Construct a new Parcats object + + Parallel categories diagram for multidimensional categorical + data. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Parcats` + arrangement + Sets the drag interaction mode for categories and + dimensions. If `perpendicular`, the categories can only + move along a line perpendicular to the paths. If + `freeform`, the categories can freely move on the + plane. If `fixed`, the categories and dimensions are + stationary. + bundlecolors + Sort paths so that like colors are bundled together + within each category. + counts + The number of observations represented by each state. + Defaults to 1 so that each state represents one + observation + countssrc + Sets the source reference on Chart Studio Cloud for + `counts`. + dimensions + The dimensions (variables) of the parallel categories + diagram. + dimensiondefaults + When used in a template (as + layout.template.data.parcats.dimensiondefaults), sets + the default property values to use for elements of + parcats.dimensions + domain + :class:`plotly.graph_objects.parcats.Domain` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoveron + Sets the hover interaction mode for the parcats + diagram. If `category`, hover interaction take place + per category. If `color`, hover interactions take place + per color per category. If `dimension`, hover + interactions take place across all categories per + dimension. + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `count`, `probability`, `category`, + `categorycount`, `colorcount` and `bandcolorcount`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + labelfont + Sets the font for the `dimension` labels. + legendgrouptitle + :class:`plotly.graph_objects.parcats.Legendgrouptitle` + instance or dict with compatible properties + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.parcats.Line` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + sortpaths + Sets the path sorting algorithm. If `forward`, sort + paths based on dimension categories from left to right. + If `backward`, sort paths based on dimensions + categories from right to left. + stream + :class:`plotly.graph_objects.parcats.Stream` instance + or dict with compatible properties + tickfont + Sets the font for the `category` labels. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Parcats + """ + super().__init__("parcats") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Parcats +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Parcats`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("arrangement", arg, arrangement) + self._set_property("bundlecolors", arg, bundlecolors) + self._set_property("counts", arg, counts) + self._set_property("countssrc", arg, countssrc) + self._set_property("dimensions", arg, dimensions) + self._set_property("dimensiondefaults", arg, dimensiondefaults) + self._set_property("domain", arg, domain) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoveron", arg, hoveron) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("labelfont", arg, labelfont) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("sortpaths", arg, sortpaths) + self._set_property("stream", arg, stream) + self._set_property("tickfont", arg, tickfont) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + + self._props["type"] = "parcats" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_parcoords.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_parcoords.py new file mode 100644 index 0000000000000000000000000000000000000000..b2ab85ef2b77b26b0422437b3c4ece9cc16d249d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_parcoords.py @@ -0,0 +1,919 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Parcoords(_BaseTraceType): + _parent_path_str = "" + _path_str = "parcoords" + _valid_props = { + "customdata", + "customdatasrc", + "dimensiondefaults", + "dimensions", + "domain", + "ids", + "idssrc", + "labelangle", + "labelfont", + "labelside", + "legend", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "meta", + "metasrc", + "name", + "rangefont", + "stream", + "tickfont", + "type", + "uid", + "uirevision", + "unselected", + "visible", + } + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def dimensions(self): + """ + The dimensions (variables) of the parallel coordinates chart. + 2..60 dimensions are supported. + + The 'dimensions' property is a tuple of instances of + Dimension that may be specified as: + - A list or tuple of instances of plotly.graph_objs.parcoords.Dimension + - A list or tuple of dicts of string/value properties that + will be passed to the Dimension constructor + + Returns + ------- + tuple[plotly.graph_objs.parcoords.Dimension] + """ + return self["dimensions"] + + @dimensions.setter + def dimensions(self, val): + self["dimensions"] = val + + @property + def dimensiondefaults(self): + """ + When used in a template (as + layout.template.data.parcoords.dimensiondefaults), sets the + default property values to use for elements of + parcoords.dimensions + + The 'dimensiondefaults' property is an instance of Dimension + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcoords.Dimension` + - A dict of string/value properties that will be passed + to the Dimension constructor + + Returns + ------- + plotly.graph_objs.parcoords.Dimension + """ + return self["dimensiondefaults"] + + @dimensiondefaults.setter + def dimensiondefaults(self, val): + self["dimensiondefaults"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcoords.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.parcoords.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def labelangle(self): + """ + Sets the angle of the labels with respect to the horizontal. + For example, a `tickangle` of -90 draws the labels vertically. + Tilted labels with "labelangle" may be positioned better inside + margins when `labelposition` is set to "bottom". + + The 'labelangle' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["labelangle"] + + @labelangle.setter + def labelangle(self, val): + self["labelangle"] = val + + @property + def labelfont(self): + """ + Sets the font for the `dimension` labels. + + The 'labelfont' property is an instance of Labelfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcoords.Labelfont` + - A dict of string/value properties that will be passed + to the Labelfont constructor + + Returns + ------- + plotly.graph_objs.parcoords.Labelfont + """ + return self["labelfont"] + + @labelfont.setter + def labelfont(self, val): + self["labelfont"] = val + + @property + def labelside(self): + """ + Specifies the location of the `label`. "top" positions labels + above, next to the title "bottom" positions labels below the + graph Tilted labels with "labelangle" may be positioned better + inside margins when `labelposition` is set to "bottom". + + The 'labelside' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top', 'bottom'] + + Returns + ------- + Any + """ + return self["labelside"] + + @labelside.setter + def labelside(self, val): + self["labelside"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcoords.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.parcoords.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcoords.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.parcoords.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def rangefont(self): + """ + Sets the font for the `dimension` range values. + + The 'rangefont' property is an instance of Rangefont + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcoords.Rangefont` + - A dict of string/value properties that will be passed + to the Rangefont constructor + + Returns + ------- + plotly.graph_objs.parcoords.Rangefont + """ + return self["rangefont"] + + @rangefont.setter + def rangefont(self, val): + self["rangefont"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcoords.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.parcoords.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def tickfont(self): + """ + Sets the font for the `dimension` tick values. + + The 'tickfont' property is an instance of Tickfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcoords.Tickfont` + - A dict of string/value properties that will be passed + to the Tickfont constructor + + Returns + ------- + plotly.graph_objs.parcoords.Tickfont + """ + return self["tickfont"] + + @tickfont.setter + def tickfont(self, val): + self["tickfont"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcoords.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.parcoords.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dimensions + The dimensions (variables) of the parallel coordinates + chart. 2..60 dimensions are supported. + dimensiondefaults + When used in a template (as + layout.template.data.parcoords.dimensiondefaults), sets + the default property values to use for elements of + parcoords.dimensions + domain + :class:`plotly.graph_objects.parcoords.Domain` instance + or dict with compatible properties + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + labelangle + Sets the angle of the labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + labels vertically. Tilted labels with "labelangle" may + be positioned better inside margins when + `labelposition` is set to "bottom". + labelfont + Sets the font for the `dimension` labels. + labelside + Specifies the location of the `label`. "top" positions + labels above, next to the title "bottom" positions + labels below the graph Tilted labels with "labelangle" + may be positioned better inside margins when + `labelposition` is set to "bottom". + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.parcoords.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.parcoords.Line` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + rangefont + Sets the font for the `dimension` range values. + stream + :class:`plotly.graph_objects.parcoords.Stream` instance + or dict with compatible properties + tickfont + Sets the font for the `dimension` tick values. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.parcoords.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + customdata=None, + customdatasrc=None, + dimensions=None, + dimensiondefaults=None, + domain=None, + ids=None, + idssrc=None, + labelangle=None, + labelfont=None, + labelside=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + meta=None, + metasrc=None, + name=None, + rangefont=None, + stream=None, + tickfont=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + **kwargs, + ): + """ + Construct a new Parcoords object + + Parallel coordinates for multidimensional exploratory data + analysis. The samples are specified in `dimensions`. The colors + are set in `line.color`. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Parcoords` + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dimensions + The dimensions (variables) of the parallel coordinates + chart. 2..60 dimensions are supported. + dimensiondefaults + When used in a template (as + layout.template.data.parcoords.dimensiondefaults), sets + the default property values to use for elements of + parcoords.dimensions + domain + :class:`plotly.graph_objects.parcoords.Domain` instance + or dict with compatible properties + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + labelangle + Sets the angle of the labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + labels vertically. Tilted labels with "labelangle" may + be positioned better inside margins when + `labelposition` is set to "bottom". + labelfont + Sets the font for the `dimension` labels. + labelside + Specifies the location of the `label`. "top" positions + labels above, next to the title "bottom" positions + labels below the graph Tilted labels with "labelangle" + may be positioned better inside margins when + `labelposition` is set to "bottom". + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.parcoords.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.parcoords.Line` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + rangefont + Sets the font for the `dimension` range values. + stream + :class:`plotly.graph_objects.parcoords.Stream` instance + or dict with compatible properties + tickfont + Sets the font for the `dimension` tick values. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.parcoords.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Parcoords + """ + super().__init__("parcoords") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Parcoords +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Parcoords`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("dimensions", arg, dimensions) + self._set_property("dimensiondefaults", arg, dimensiondefaults) + self._set_property("domain", arg, domain) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("labelangle", arg, labelangle) + self._set_property("labelfont", arg, labelfont) + self._set_property("labelside", arg, labelside) + self._set_property("legend", arg, legend) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("rangefont", arg, rangefont) + self._set_property("stream", arg, stream) + self._set_property("tickfont", arg, tickfont) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + + self._props["type"] = "parcoords" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_pie.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_pie.py new file mode 100644 index 0000000000000000000000000000000000000000..b18aad3e2df889dda419921fed6ceee7a30e3695 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_pie.py @@ -0,0 +1,2032 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Pie(_BaseTraceType): + _parent_path_str = "" + _path_str = "pie" + _valid_props = { + "automargin", + "customdata", + "customdatasrc", + "direction", + "dlabel", + "domain", + "hole", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "insidetextfont", + "insidetextorientation", + "label0", + "labels", + "labelssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendsrc", + "legendwidth", + "marker", + "meta", + "metasrc", + "name", + "opacity", + "outsidetextfont", + "pull", + "pullsrc", + "rotation", + "scalegroup", + "showlegend", + "showlegendsrc", + "sort", + "stream", + "text", + "textfont", + "textinfo", + "textposition", + "textpositionsrc", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "title", + "type", + "uid", + "uirevision", + "values", + "valuessrc", + "visible", + } + + @property + def automargin(self): + """ + Determines whether outside text labels can push the margins. + + The 'automargin' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["automargin"] + + @automargin.setter + def automargin(self, val): + self["automargin"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def direction(self): + """ + Specifies the direction at which succeeding sectors follow one + another. + + The 'direction' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['clockwise', 'counterclockwise'] + + Returns + ------- + Any + """ + return self["direction"] + + @direction.setter + def direction(self, val): + self["direction"] = val + + @property + def dlabel(self): + """ + Sets the label step. See `label0` for more info. + + The 'dlabel' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dlabel"] + + @dlabel.setter + def dlabel(self, val): + self["dlabel"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.pie.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.pie.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def hole(self): + """ + Sets the fraction of the radius to cut out of the pie. Use this + to make a donut chart. + + The 'hole' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["hole"] + + @hole.setter + def hole(self, val): + self["hole"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['label', 'text', 'value', 'percent', 'name'] joined with '+' characters + (e.g. 'label+text') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.pie.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.pie.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables `label`, + `color`, `value`, `percent` and `text`. Anything contained in + tag `` is displayed in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each sector. If a + single string, the same string appears for all data points. If + an array of string, the items are mapped in order of this + trace's sectors. To be seen, trace `hoverinfo` must contain a + "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def insidetextfont(self): + """ + Sets the font used for `textinfo` lying inside the sector. + + The 'insidetextfont' property is an instance of Insidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.pie.Insidetextfont` + - A dict of string/value properties that will be passed + to the Insidetextfont constructor + + Returns + ------- + plotly.graph_objs.pie.Insidetextfont + """ + return self["insidetextfont"] + + @insidetextfont.setter + def insidetextfont(self, val): + self["insidetextfont"] = val + + @property + def insidetextorientation(self): + """ + Controls the orientation of the text inside chart sectors. When + set to "auto", text may be oriented in any direction in order + to be as big as possible in the middle of a sector. The + "horizontal" option orients text to be parallel with the bottom + of the chart, and may make text smaller in order to achieve + that goal. The "radial" option orients text along the radius of + the sector. The "tangential" option orients text perpendicular + to the radius of the sector. + + The 'insidetextorientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['horizontal', 'radial', 'tangential', 'auto'] + + Returns + ------- + Any + """ + return self["insidetextorientation"] + + @insidetextorientation.setter + def insidetextorientation(self, val): + self["insidetextorientation"] = val + + @property + def label0(self): + """ + Alternate to `labels`. Builds a numeric set of labels. Use with + `dlabel` where `label0` is the starting label and `dlabel` the + step. + + The 'label0' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["label0"] + + @label0.setter + def label0(self, val): + self["label0"] = val + + @property + def labels(self): + """ + Sets the sector labels. If `labels` entries are duplicated, we + sum associated `values` or simply count occurrences if `values` + is not provided. For other array attributes (including color) + we use the first non-empty entry among all occurrences of the + label. + + The 'labels' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["labels"] + + @labels.setter + def labels(self, val): + self["labels"] = val + + @property + def labelssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `labels`. + + The 'labelssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["labelssrc"] + + @labelssrc.setter + def labelssrc(self, val): + self["labelssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show the pie slices in. Can + be an array if `values` is set. In that case, each entry + specifies the legend reference for one slice. References to + these legends are "legend", "legend2", "legend3", etc. Settings + for these legends are set in the layout, under `layout.legend`, + `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + - A tuple or list of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.pie.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.pie.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `legend`. + + The 'legendsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["legendsrc"] + + @legendsrc.setter + def legendsrc(self, val): + self["legendsrc"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.pie.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.pie.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def outsidetextfont(self): + """ + Sets the font used for `textinfo` lying outside the sector. + + The 'outsidetextfont' property is an instance of Outsidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.pie.Outsidetextfont` + - A dict of string/value properties that will be passed + to the Outsidetextfont constructor + + Returns + ------- + plotly.graph_objs.pie.Outsidetextfont + """ + return self["outsidetextfont"] + + @outsidetextfont.setter + def outsidetextfont(self, val): + self["outsidetextfont"] = val + + @property + def pull(self): + """ + Sets the fraction of larger radius to pull the sectors out from + the center. This can be a constant to pull all slices apart + from each other equally or an array to highlight one or more + slices. + + The 'pull' property is a number and may be specified as: + - An int or float in the interval [0, 1] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["pull"] + + @pull.setter + def pull(self, val): + self["pull"] = val + + @property + def pullsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `pull`. + + The 'pullsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["pullsrc"] + + @pullsrc.setter + def pullsrc(self, val): + self["pullsrc"] = val + + @property + def rotation(self): + """ + Instead of the first slice starting at 12 o'clock, rotate to + some other angle. + + The 'rotation' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["rotation"] + + @rotation.setter + def rotation(self, val): + self["rotation"] = val + + @property + def scalegroup(self): + """ + If there are multiple pie charts that should be sized according + to their totals, link them by providing a non-empty group id + here shared by every trace in the same group. + + The 'scalegroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["scalegroup"] + + @scalegroup.setter + def scalegroup(self, val): + self["scalegroup"] = val + + @property + def showlegend(self): + """ + Determines whether or not items corresponding to the pie slices + are shown in the legend. Can be an array if `values` is set. In + that case, each entry specifies appearance in the legend for + one slice. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + - A tuple or list of the above + + Returns + ------- + bool|numpy.ndarray + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showlegendsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `showlegend`. + + The 'showlegendsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["showlegendsrc"] + + @showlegendsrc.setter + def showlegendsrc(self, val): + self["showlegendsrc"] = val + + @property + def sort(self): + """ + Determines whether or not the sectors are reordered from + largest to smallest. + + The 'sort' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["sort"] + + @sort.setter + def sort(self, val): + self["sort"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.pie.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.pie.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets text elements associated with each sector. If trace + `textinfo` contains a "text" flag, these elements will be seen + on the chart. If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in the + hover labels. + + The 'text' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the font used for `textinfo`. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.pie.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.pie.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textinfo(self): + """ + Determines which trace information appear on the graph. + + The 'textinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['label', 'text', 'value', 'percent'] joined with '+' characters + (e.g. 'label+text') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["textinfo"] + + @textinfo.setter + def textinfo(self, val): + self["textinfo"] = val + + @property + def textposition(self): + """ + Specifies the location of the `textinfo`. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['inside', 'outside', 'auto', 'none'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textpositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `textposition`. + + The 'textpositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textpositionsrc"] + + @textpositionsrc.setter + def textpositionsrc(self, val): + self["textpositionsrc"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `label`, `color`, `value`, `percent` and `text`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def title(self): + """ + The 'title' property is an instance of Title + that may be specified as: + - An instance of :class:`plotly.graph_objs.pie.Title` + - A dict of string/value properties that will be passed + to the Title constructor + + Returns + ------- + plotly.graph_objs.pie.Title + """ + return self["title"] + + @title.setter + def title(self, val): + self["title"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def values(self): + """ + Sets the values of the sectors. If omitted, we count + occurrences of each label. + + The 'values' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["values"] + + @values.setter + def values(self, val): + self["values"] = val + + @property + def valuessrc(self): + """ + Sets the source reference on Chart Studio Cloud for `values`. + + The 'valuessrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["valuessrc"] + + @valuessrc.setter + def valuessrc(self, val): + self["valuessrc"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + automargin + Determines whether outside text labels can push the + margins. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + direction + Specifies the direction at which succeeding sectors + follow one another. + dlabel + Sets the label step. See `label0` for more info. + domain + :class:`plotly.graph_objects.pie.Domain` instance or + dict with compatible properties + hole + Sets the fraction of the radius to cut out of the pie. + Use this to make a donut chart. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.pie.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `percent` and + `text`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + insidetextorientation + Controls the orientation of the text inside chart + sectors. When set to "auto", text may be oriented in + any direction in order to be as big as possible in the + middle of a sector. The "horizontal" option orients + text to be parallel with the bottom of the chart, and + may make text smaller in order to achieve that goal. + The "radial" option orients text along the radius of + the sector. The "tangential" option orients text + perpendicular to the radius of the sector. + label0 + Alternate to `labels`. Builds a numeric set of labels. + Use with `dlabel` where `label0` is the starting label + and `dlabel` the step. + labels + Sets the sector labels. If `labels` entries are + duplicated, we sum associated `values` or simply count + occurrences if `values` is not provided. For other + array attributes (including color) we use the first + non-empty entry among all occurrences of the label. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + legend + Sets the reference to a legend to show the pie slices + in. Can be an array if `values` is set. In that case, + each entry specifies the legend reference for one + slice. References to these legends are "legend", + "legend2", "legend3", etc. Settings for these legends + are set in the layout, under `layout.legend`, + `layout.legend2`, etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.pie.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendsrc + Sets the source reference on Chart Studio Cloud for + `legend`. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.pie.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. + pull + Sets the fraction of larger radius to pull the sectors + out from the center. This can be a constant to pull all + slices apart from each other equally or an array to + highlight one or more slices. + pullsrc + Sets the source reference on Chart Studio Cloud for + `pull`. + rotation + Instead of the first slice starting at 12 o'clock, + rotate to some other angle. + scalegroup + If there are multiple pie charts that should be sized + according to their totals, link them by providing a + non-empty group id here shared by every trace in the + same group. + showlegend + Determines whether or not items corresponding to the + pie slices are shown in the legend. Can be an array if + `values` is set. In that case, each entry specifies + appearance in the legend for one slice. + showlegendsrc + Sets the source reference on Chart Studio Cloud for + `showlegend`. + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.pie.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Specifies the location of the `textinfo`. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `percent` and + `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + title + :class:`plotly.graph_objects.pie.Title` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values of the sectors. If omitted, we count + occurrences of each label. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + automargin=None, + customdata=None, + customdatasrc=None, + direction=None, + dlabel=None, + domain=None, + hole=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextfont=None, + insidetextorientation=None, + label0=None, + labels=None, + labelssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendsrc=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + outsidetextfont=None, + pull=None, + pullsrc=None, + rotation=None, + scalegroup=None, + showlegend=None, + showlegendsrc=None, + sort=None, + stream=None, + text=None, + textfont=None, + textinfo=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + title=None, + uid=None, + uirevision=None, + values=None, + valuessrc=None, + visible=None, + **kwargs, + ): + """ + Construct a new Pie object + + A data visualized by the sectors of the pie is set in `values`. + The sector labels are set in `labels`. The sector colors are + set in `marker.colors` + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Pie` + automargin + Determines whether outside text labels can push the + margins. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + direction + Specifies the direction at which succeeding sectors + follow one another. + dlabel + Sets the label step. See `label0` for more info. + domain + :class:`plotly.graph_objects.pie.Domain` instance or + dict with compatible properties + hole + Sets the fraction of the radius to cut out of the pie. + Use this to make a donut chart. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.pie.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `percent` and + `text`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + insidetextorientation + Controls the orientation of the text inside chart + sectors. When set to "auto", text may be oriented in + any direction in order to be as big as possible in the + middle of a sector. The "horizontal" option orients + text to be parallel with the bottom of the chart, and + may make text smaller in order to achieve that goal. + The "radial" option orients text along the radius of + the sector. The "tangential" option orients text + perpendicular to the radius of the sector. + label0 + Alternate to `labels`. Builds a numeric set of labels. + Use with `dlabel` where `label0` is the starting label + and `dlabel` the step. + labels + Sets the sector labels. If `labels` entries are + duplicated, we sum associated `values` or simply count + occurrences if `values` is not provided. For other + array attributes (including color) we use the first + non-empty entry among all occurrences of the label. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + legend + Sets the reference to a legend to show the pie slices + in. Can be an array if `values` is set. In that case, + each entry specifies the legend reference for one + slice. References to these legends are "legend", + "legend2", "legend3", etc. Settings for these legends + are set in the layout, under `layout.legend`, + `layout.legend2`, etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.pie.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendsrc + Sets the source reference on Chart Studio Cloud for + `legend`. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.pie.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. + pull + Sets the fraction of larger radius to pull the sectors + out from the center. This can be a constant to pull all + slices apart from each other equally or an array to + highlight one or more slices. + pullsrc + Sets the source reference on Chart Studio Cloud for + `pull`. + rotation + Instead of the first slice starting at 12 o'clock, + rotate to some other angle. + scalegroup + If there are multiple pie charts that should be sized + according to their totals, link them by providing a + non-empty group id here shared by every trace in the + same group. + showlegend + Determines whether or not items corresponding to the + pie slices are shown in the legend. Can be an array if + `values` is set. In that case, each entry specifies + appearance in the legend for one slice. + showlegendsrc + Sets the source reference on Chart Studio Cloud for + `showlegend`. + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.pie.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Specifies the location of the `textinfo`. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `label`, `color`, `value`, `percent` and + `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + title + :class:`plotly.graph_objects.pie.Title` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values of the sectors. If omitted, we count + occurrences of each label. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Pie + """ + super().__init__("pie") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Pie +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Pie`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("automargin", arg, automargin) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("direction", arg, direction) + self._set_property("dlabel", arg, dlabel) + self._set_property("domain", arg, domain) + self._set_property("hole", arg, hole) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("insidetextfont", arg, insidetextfont) + self._set_property("insidetextorientation", arg, insidetextorientation) + self._set_property("label0", arg, label0) + self._set_property("labels", arg, labels) + self._set_property("labelssrc", arg, labelssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendsrc", arg, legendsrc) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("outsidetextfont", arg, outsidetextfont) + self._set_property("pull", arg, pull) + self._set_property("pullsrc", arg, pullsrc) + self._set_property("rotation", arg, rotation) + self._set_property("scalegroup", arg, scalegroup) + self._set_property("showlegend", arg, showlegend) + self._set_property("showlegendsrc", arg, showlegendsrc) + self._set_property("sort", arg, sort) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textinfo", arg, textinfo) + self._set_property("textposition", arg, textposition) + self._set_property("textpositionsrc", arg, textpositionsrc) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("title", arg, title) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("values", arg, values) + self._set_property("valuessrc", arg, valuessrc) + self._set_property("visible", arg, visible) + + self._props["type"] = "pie" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_sankey.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_sankey.py new file mode 100644 index 0000000000000000000000000000000000000000..f32d44f6fdd2979235f5f961de1f02c6123ec00f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_sankey.py @@ -0,0 +1,966 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Sankey(_BaseTraceType): + _parent_path_str = "" + _path_str = "sankey" + _valid_props = { + "arrangement", + "customdata", + "customdatasrc", + "domain", + "hoverinfo", + "hoverlabel", + "ids", + "idssrc", + "legend", + "legendgrouptitle", + "legendrank", + "legendwidth", + "link", + "meta", + "metasrc", + "name", + "node", + "orientation", + "selectedpoints", + "stream", + "textfont", + "type", + "uid", + "uirevision", + "valueformat", + "valuesuffix", + "visible", + } + + @property + def arrangement(self): + """ + If value is `snap` (the default), the node arrangement is + assisted by automatic snapping of elements to preserve space + between nodes specified via `nodepad`. If value is + `perpendicular`, the nodes can only move along a line + perpendicular to the flow. If value is `freeform`, the nodes + can freely move on the plane. If value is `fixed`, the nodes + are stationary. + + The 'arrangement' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['snap', 'perpendicular', 'freeform', 'fixed'] + + Returns + ------- + Any + """ + return self["arrangement"] + + @arrangement.setter + def arrangement(self, val): + self["arrangement"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.sankey.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.sankey.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + Note that this attribute is superseded by `node.hoverinfo` and + `node.hoverinfo` for nodes and links respectively. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of [] joined with '+' characters + (e.g. '') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + + Returns + ------- + Any + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.sankey.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.sankey.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.sankey.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.sankey.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def link(self): + """ + The links of the Sankey plot. + + The 'link' property is an instance of Link + that may be specified as: + - An instance of :class:`plotly.graph_objs.sankey.Link` + - A dict of string/value properties that will be passed + to the Link constructor + + Returns + ------- + plotly.graph_objs.sankey.Link + """ + return self["link"] + + @link.setter + def link(self, val): + self["link"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def node(self): + """ + The nodes of the Sankey plot. + + The 'node' property is an instance of Node + that may be specified as: + - An instance of :class:`plotly.graph_objs.sankey.Node` + - A dict of string/value properties that will be passed + to the Node constructor + + Returns + ------- + plotly.graph_objs.sankey.Node + """ + return self["node"] + + @node.setter + def node(self, val): + self["node"] = val + + @property + def orientation(self): + """ + Sets the orientation of the Sankey diagram. + + The 'orientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['v', 'h'] + + Returns + ------- + Any + """ + return self["orientation"] + + @orientation.setter + def orientation(self, val): + self["orientation"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.sankey.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.sankey.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def textfont(self): + """ + Sets the font for node labels + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.sankey.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.sankey.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def valueformat(self): + """ + Sets the value formatting rule using d3 formatting mini- + languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + + The 'valueformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["valueformat"] + + @valueformat.setter + def valueformat(self, val): + self["valueformat"] = val + + @property + def valuesuffix(self): + """ + Adds a unit to follow the value in the hover tooltip. Add a + space if a separation is necessary from the value. + + The 'valuesuffix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["valuesuffix"] + + @valuesuffix.setter + def valuesuffix(self, val): + self["valuesuffix"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + arrangement + If value is `snap` (the default), the node arrangement + is assisted by automatic snapping of elements to + preserve space between nodes specified via `nodepad`. + If value is `perpendicular`, the nodes can only move + along a line perpendicular to the flow. If value is + `freeform`, the nodes can freely move on the plane. If + value is `fixed`, the nodes are stationary. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.sankey.Domain` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. Note that this attribute is + superseded by `node.hoverinfo` and `node.hoverinfo` for + nodes and links respectively. + hoverlabel + :class:`plotly.graph_objects.sankey.Hoverlabel` + instance or dict with compatible properties + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.sankey.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + link + The links of the Sankey plot. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + node + The nodes of the Sankey plot. + orientation + Sets the orientation of the Sankey diagram. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + stream + :class:`plotly.graph_objects.sankey.Stream` instance or + dict with compatible properties + textfont + Sets the font for node labels + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + valueformat + Sets the value formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + valuesuffix + Adds a unit to follow the value in the hover tooltip. + Add a space if a separation is necessary from the + value. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + arrangement=None, + customdata=None, + customdatasrc=None, + domain=None, + hoverinfo=None, + hoverlabel=None, + ids=None, + idssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + link=None, + meta=None, + metasrc=None, + name=None, + node=None, + orientation=None, + selectedpoints=None, + stream=None, + textfont=None, + uid=None, + uirevision=None, + valueformat=None, + valuesuffix=None, + visible=None, + **kwargs, + ): + """ + Construct a new Sankey object + + Sankey plots for network flow data analysis. The nodes are + specified in `nodes` and the links between sources and targets + in `links`. The colors are set in `nodes[i].color` and + `links[i].color`, otherwise defaults are used. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Sankey` + arrangement + If value is `snap` (the default), the node arrangement + is assisted by automatic snapping of elements to + preserve space between nodes specified via `nodepad`. + If value is `perpendicular`, the nodes can only move + along a line perpendicular to the flow. If value is + `freeform`, the nodes can freely move on the plane. If + value is `fixed`, the nodes are stationary. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.sankey.Domain` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. Note that this attribute is + superseded by `node.hoverinfo` and `node.hoverinfo` for + nodes and links respectively. + hoverlabel + :class:`plotly.graph_objects.sankey.Hoverlabel` + instance or dict with compatible properties + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.sankey.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + link + The links of the Sankey plot. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + node + The nodes of the Sankey plot. + orientation + Sets the orientation of the Sankey diagram. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + stream + :class:`plotly.graph_objects.sankey.Stream` instance or + dict with compatible properties + textfont + Sets the font for node labels + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + valueformat + Sets the value formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + valuesuffix + Adds a unit to follow the value in the hover tooltip. + Add a space if a separation is necessary from the + value. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Sankey + """ + super().__init__("sankey") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Sankey +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Sankey`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("arrangement", arg, arrangement) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("domain", arg, domain) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("link", arg, link) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("node", arg, node) + self._set_property("orientation", arg, orientation) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("stream", arg, stream) + self._set_property("textfont", arg, textfont) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("valueformat", arg, valueformat) + self._set_property("valuesuffix", arg, valuesuffix) + self._set_property("visible", arg, visible) + + self._props["type"] = "sankey" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scatter.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scatter.py new file mode 100644 index 0000000000000000000000000000000000000000..ad5ab6b624f7a339f8206cfcb8d1c03049285603 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scatter.py @@ -0,0 +1,2846 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Scatter(_BaseTraceType): + _parent_path_str = "" + _path_str = "scatter" + _valid_props = { + "alignmentgroup", + "cliponaxis", + "connectgaps", + "customdata", + "customdatasrc", + "dx", + "dy", + "error_x", + "error_y", + "fill", + "fillcolor", + "fillgradient", + "fillpattern", + "groupnorm", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hoveron", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "marker", + "meta", + "metasrc", + "mode", + "name", + "offsetgroup", + "opacity", + "orientation", + "selected", + "selectedpoints", + "showlegend", + "stackgaps", + "stackgroup", + "stream", + "text", + "textfont", + "textposition", + "textpositionsrc", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "type", + "uid", + "uirevision", + "unselected", + "visible", + "x", + "x0", + "xaxis", + "xcalendar", + "xhoverformat", + "xperiod", + "xperiod0", + "xperiodalignment", + "xsrc", + "y", + "y0", + "yaxis", + "ycalendar", + "yhoverformat", + "yperiod", + "yperiod0", + "yperiodalignment", + "ysrc", + "zorder", + } + + @property + def alignmentgroup(self): + """ + Set several traces linked to the same position axis or matching + axes to the same alignmentgroup. This controls whether bars + compute their positional range dependently or independently. + + The 'alignmentgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["alignmentgroup"] + + @alignmentgroup.setter + def alignmentgroup(self, val): + self["alignmentgroup"] = val + + @property + def cliponaxis(self): + """ + Determines whether or not markers and text nodes are clipped + about the subplot axes. To show markers and text nodes above + axis lines and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + + The 'cliponaxis' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cliponaxis"] + + @cliponaxis.setter + def cliponaxis(self, val): + self["cliponaxis"] = val + + @property + def connectgaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the provided data arrays are connected. + + The 'connectgaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["connectgaps"] + + @connectgaps.setter + def connectgaps(self, val): + self["connectgaps"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def dx(self): + """ + Sets the x coordinate step. See `x0` for more info. + + The 'dx' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dx"] + + @dx.setter + def dx(self, val): + self["dx"] = val + + @property + def dy(self): + """ + Sets the y coordinate step. See `y0` for more info. + + The 'dy' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dy"] + + @dy.setter + def dy(self, val): + self["dy"] = val + + @property + def error_x(self): + """ + The 'error_x' property is an instance of ErrorX + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter.ErrorX` + - A dict of string/value properties that will be passed + to the ErrorX constructor + + Returns + ------- + plotly.graph_objs.scatter.ErrorX + """ + return self["error_x"] + + @error_x.setter + def error_x(self, val): + self["error_x"] = val + + @property + def error_y(self): + """ + The 'error_y' property is an instance of ErrorY + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter.ErrorY` + - A dict of string/value properties that will be passed + to the ErrorY constructor + + Returns + ------- + plotly.graph_objs.scatter.ErrorY + """ + return self["error_y"] + + @error_y.setter + def error_y(self, val): + self["error_y"] = val + + @property + def fill(self): + """ + Sets the area to fill with a solid color. Defaults to "none" + unless this trace is stacked, then it gets "tonexty" + ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` + if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 + respectively. "tonextx" and "tonexty" fill between the + endpoints of this trace and the endpoints of the trace before + it, connecting those endpoints with straight lines (to make a + stacked area graph); if there is no trace before it, they + behave like "tozerox" and "tozeroy". "toself" connects the + endpoints of the trace (or each segment of the trace if it has + gaps) into a closed shape. "tonext" fills the space between two + traces if one completely encloses the other (eg consecutive + contour lines), and behaves like "toself" if there is no trace + before it. "tonext" should not be used if one trace does not + enclose the other. Traces in a `stackgroup` will only fill to + (or be filled to) other traces in the same group. With multiple + `stackgroup`s or some traces stacked and some not, if fill- + linked traces are not already consecutive, the later ones will + be pushed down in the drawing order. + + The 'fill' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'tozeroy', 'tozerox', 'tonexty', 'tonextx', + 'toself', 'tonext'] + + Returns + ------- + Any + """ + return self["fill"] + + @fill.setter + def fill(self, val): + self["fill"] = val + + @property + def fillcolor(self): + """ + Sets the fill color. Defaults to a half-transparent variant of + the line color, marker color, or marker line color, whichever + is available. If fillgradient is specified, fillcolor is + ignored except for setting the background color of the hover + label, if any. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def fillgradient(self): + """ + Sets a fill gradient. If not specified, the fillcolor is used + instead. + + The 'fillgradient' property is an instance of Fillgradient + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter.Fillgradient` + - A dict of string/value properties that will be passed + to the Fillgradient constructor + + Returns + ------- + plotly.graph_objs.scatter.Fillgradient + """ + return self["fillgradient"] + + @fillgradient.setter + def fillgradient(self, val): + self["fillgradient"] = val + + @property + def fillpattern(self): + """ + Sets the pattern within the marker. + + The 'fillpattern' property is an instance of Fillpattern + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter.Fillpattern` + - A dict of string/value properties that will be passed + to the Fillpattern constructor + + Returns + ------- + plotly.graph_objs.scatter.Fillpattern + """ + return self["fillpattern"] + + @fillpattern.setter + def fillpattern(self, val): + self["fillpattern"] = val + + @property + def groupnorm(self): + """ + Only relevant when `stackgroup` is used, and only the first + `groupnorm` found in the `stackgroup` will be used - including + if `visible` is "legendonly" but not if it is `false`. Sets the + normalization for the sum of this `stackgroup`. With + "fraction", the value of each trace at each location is divided + by the sum of all trace values at that location. "percent" is + the same but multiplied by 100 to show percentages. If there + are multiple subplots, or multiple `stackgroup`s on one + subplot, each will be normalized within its own set. + + The 'groupnorm' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['', 'fraction', 'percent'] + + Returns + ------- + Any + """ + return self["groupnorm"] + + @groupnorm.setter + def groupnorm(self, val): + self["groupnorm"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.scatter.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hoveron(self): + """ + Do the hover effects highlight individual points (markers or + line points) or do they highlight filled regions? If the fill + is "toself" or "tonext" and there are no markers or text, then + the default is "fills", otherwise it is "points". + + The 'hoveron' property is a flaglist and may be specified + as a string containing: + - Any combination of ['points', 'fills'] joined with '+' characters + (e.g. 'points+fills') + + Returns + ------- + Any + """ + return self["hoveron"] + + @hoveron.setter + def hoveron(self, val): + self["hoveron"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each (x,y) pair. If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (x,y) coordinates. To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.scatter.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.scatter.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scatter.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def mode(self): + """ + Determines the drawing mode for this scatter trace. If the + provided `mode` includes "text" then the `text` elements appear + at the coordinates. Otherwise, the `text` elements appear on + hover. If there are less than 20 points and the trace is not + stacked then the default is "lines+markers". Otherwise, + "lines". + + The 'mode' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lines', 'markers', 'text'] joined with '+' characters + (e.g. 'lines+markers') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["mode"] + + @mode.setter + def mode(self, val): + self["mode"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def offsetgroup(self): + """ + Set several traces linked to the same position axis or matching + axes to the same offsetgroup where bars of the same position + coordinate will line up. + + The 'offsetgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["offsetgroup"] + + @offsetgroup.setter + def offsetgroup(self, val): + self["offsetgroup"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def orientation(self): + """ + Only relevant in the following cases: 1. when `scattermode` is + set to "group". 2. when `stackgroup` is used, and only the + first `orientation` found in the `stackgroup` will be used - + including if `visible` is "legendonly" but not if it is + `false`. Sets the stacking direction. With "v" ("h"), the y (x) + values of subsequent traces are added. Also affects the default + value of `fill`. + + The 'orientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['v', 'h'] + + Returns + ------- + Any + """ + return self["orientation"] + + @orientation.setter + def orientation(self, val): + self["orientation"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.scatter.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stackgaps(self): + """ + Only relevant when `stackgroup` is used, and only the first + `stackgaps` found in the `stackgroup` will be used - including + if `visible` is "legendonly" but not if it is `false`. + Determines how we handle locations at which other traces in + this group have data but this one does not. With *infer zero* + we insert a zero at these locations. With "interpolate" we + linearly interpolate between existing values, and extrapolate a + constant beyond the existing values. + + The 'stackgaps' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['infer zero', 'interpolate'] + + Returns + ------- + Any + """ + return self["stackgaps"] + + @stackgaps.setter + def stackgaps(self, val): + self["stackgaps"] = val + + @property + def stackgroup(self): + """ + Set several scatter traces (on the same subplot) to the same + stackgroup in order to add their y values (or their x values if + `orientation` is "h"). If blank or omitted this trace will not + be stacked. Stacking also turns `fill` on by default, using + "tonexty" ("tonextx") if `orientation` is "h" ("v") and sets + the default `mode` to "lines" irrespective of point count. You + can only stack on a numeric (linear or log) axis. Traces in a + `stackgroup` will only fill to (or be filled to) other traces + in the same group. With multiple `stackgroup`s or some traces + stacked and some not, if fill-linked traces are not already + consecutive, the later ones will be pushed down in the drawing + order. + + The 'stackgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["stackgroup"] + + @stackgroup.setter + def stackgroup(self, val): + self["stackgroup"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.scatter.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets text elements associated with each (x,y) pair. If a single + string, the same string appears over all the data points. If an + array of string, the items are mapped in order to the this + trace's (x,y) coordinates. If trace `hoverinfo` contains a + "text" flag and "hovertext" is not set, these elements will be + seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the text font. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.scatter.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textposition(self): + """ + Sets the positions of the `text` elements with respects to the + (x,y) coordinates. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top left', 'top center', 'top right', 'middle left', + 'middle center', 'middle right', 'bottom left', 'bottom + center', 'bottom right'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textpositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `textposition`. + + The 'textpositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textpositionsrc"] + + @textpositionsrc.setter + def textpositionsrc(self, val): + self["textpositionsrc"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.scatter.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the x coordinates. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def x0(self): + """ + Alternate to `x`. Builds a linear space of x coordinates. Use + with `dx` where `x0` is the starting coordinate and `dx` the + step. + + The 'x0' property accepts values of any type + + Returns + ------- + Any + """ + return self["x0"] + + @x0.setter + def x0(self, val): + self["x0"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def xcalendar(self): + """ + Sets the calendar system to use with `x` date data. + + The 'xcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["xcalendar"] + + @xcalendar.setter + def xcalendar(self, val): + self["xcalendar"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the x axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'xperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod"] + + @xperiod.setter + def xperiod(self, val): + self["xperiod"] = val + + @property + def xperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the x0 + axis. When `x0period` is round number of weeks, the `x0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'xperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod0"] + + @xperiod0.setter + def xperiod0(self, val): + self["xperiod0"] = val + + @property + def xperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + + The 'xperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["xperiodalignment"] + + @xperiodalignment.setter + def xperiodalignment(self, val): + self["xperiodalignment"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the y coordinates. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def y0(self): + """ + Alternate to `y`. Builds a linear space of y coordinates. Use + with `dy` where `y0` is the starting coordinate and `dy` the + step. + + The 'y0' property accepts values of any type + + Returns + ------- + Any + """ + return self["y0"] + + @y0.setter + def y0(self, val): + self["y0"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def ycalendar(self): + """ + Sets the calendar system to use with `y` date data. + + The 'ycalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["ycalendar"] + + @ycalendar.setter + def ycalendar(self, val): + self["ycalendar"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def yperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the y axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'yperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod"] + + @yperiod.setter + def yperiod(self, val): + self["yperiod"] = val + + @property + def yperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the y0 + axis. When `y0period` is round number of weeks, the `y0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'yperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod0"] + + @yperiod0.setter + def yperiod0(self, val): + self["yperiod0"] = val + + @property + def yperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + + The 'yperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["yperiodalignment"] + + @yperiodalignment.setter + def yperiodalignment(self, val): + self["yperiodalignment"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def zorder(self): + """ + Sets the layer on which this trace is displayed, relative to + other SVG traces on the same subplot. SVG traces with higher + `zorder` appear in front of those with lower `zorder`. + + The 'zorder' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["zorder"] + + @zorder.setter + def zorder(self, val): + self["zorder"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + error_x + :class:`plotly.graph_objects.scatter.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.scatter.ErrorY` instance + or dict with compatible properties + fill + Sets the area to fill with a solid color. Defaults to + "none" unless this trace is stacked, then it gets + "tonexty" ("tonextx") if `orientation` is "v" ("h") Use + with `fillcolor` if not "none". "tozerox" and "tozeroy" + fill to x=0 and y=0 respectively. "tonextx" and + "tonexty" fill between the endpoints of this trace and + the endpoints of the trace before it, connecting those + endpoints with straight lines (to make a stacked area + graph); if there is no trace before it, they behave + like "tozerox" and "tozeroy". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. Traces in a `stackgroup` will only fill to (or + be filled to) other traces in the same group. With + multiple `stackgroup`s or some traces stacked and some + not, if fill-linked traces are not already consecutive, + the later ones will be pushed down in the drawing + order. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. If fillgradient is + specified, fillcolor is ignored except for setting the + background color of the hover label, if any. + fillgradient + Sets a fill gradient. If not specified, the fillcolor + is used instead. + fillpattern + Sets the pattern within the marker. + groupnorm + Only relevant when `stackgroup` is used, and only the + first `groupnorm` found in the `stackgroup` will be + used - including if `visible` is "legendonly" but not + if it is `false`. Sets the normalization for the sum of + this `stackgroup`. With "fraction", the value of each + trace at each location is divided by the sum of all + trace values at that location. "percent" is the same + but multiplied by 100 to show percentages. If there are + multiple subplots, or multiple `stackgroup`s on one + subplot, each will be normalized within its own set. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatter.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatter.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatter.Line` instance or + dict with compatible properties + marker + :class:`plotly.graph_objects.scatter.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Only relevant in the following cases: 1. when + `scattermode` is set to "group". 2. when `stackgroup` + is used, and only the first `orientation` found in the + `stackgroup` will be used - including if `visible` is + "legendonly" but not if it is `false`. Sets the + stacking direction. With "v" ("h"), the y (x) values of + subsequent traces are added. Also affects the default + value of `fill`. + selected + :class:`plotly.graph_objects.scatter.Selected` instance + or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stackgaps + Only relevant when `stackgroup` is used, and only the + first `stackgaps` found in the `stackgroup` will be + used - including if `visible` is "legendonly" but not + if it is `false`. Determines how we handle locations at + which other traces in this group have data but this one + does not. With *infer zero* we insert a zero at these + locations. With "interpolate" we linearly interpolate + between existing values, and extrapolate a constant + beyond the existing values. + stackgroup + Set several scatter traces (on the same subplot) to the + same stackgroup in order to add their y values (or + their x values if `orientation` is "h"). If blank or + omitted this trace will not be stacked. Stacking also + turns `fill` on by default, using "tonexty" ("tonextx") + if `orientation` is "h" ("v") and sets the default + `mode` to "lines" irrespective of point count. You can + only stack on a numeric (linear or log) axis. Traces in + a `stackgroup` will only fill to (or be filled to) + other traces in the same group. With multiple + `stackgroup`s or some traces stacked and some not, if + fill-linked traces are not already consecutive, the + later ones will be pushed down in the drawing order. + stream + :class:`plotly.graph_objects.scatter.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatter.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + """ + + def __init__( + self, + arg=None, + alignmentgroup=None, + cliponaxis=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + error_x=None, + error_y=None, + fill=None, + fillcolor=None, + fillgradient=None, + fillpattern=None, + groupnorm=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + offsetgroup=None, + opacity=None, + orientation=None, + selected=None, + selectedpoints=None, + showlegend=None, + stackgaps=None, + stackgroup=None, + stream=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + zorder=None, + **kwargs, + ): + """ + Construct a new Scatter object + + The scatter trace type encompasses line charts, scatter charts, + text charts, and bubble charts. The data visualized as scatter + point or lines is set in `x` and `y`. Text (appearing either on + the chart or on hover only) is via `text`. Bubble charts are + achieved by setting `marker.size` and/or `marker.color` to + numerical arrays. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Scatter` + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + error_x + :class:`plotly.graph_objects.scatter.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.scatter.ErrorY` instance + or dict with compatible properties + fill + Sets the area to fill with a solid color. Defaults to + "none" unless this trace is stacked, then it gets + "tonexty" ("tonextx") if `orientation` is "v" ("h") Use + with `fillcolor` if not "none". "tozerox" and "tozeroy" + fill to x=0 and y=0 respectively. "tonextx" and + "tonexty" fill between the endpoints of this trace and + the endpoints of the trace before it, connecting those + endpoints with straight lines (to make a stacked area + graph); if there is no trace before it, they behave + like "tozerox" and "tozeroy". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. Traces in a `stackgroup` will only fill to (or + be filled to) other traces in the same group. With + multiple `stackgroup`s or some traces stacked and some + not, if fill-linked traces are not already consecutive, + the later ones will be pushed down in the drawing + order. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. If fillgradient is + specified, fillcolor is ignored except for setting the + background color of the hover label, if any. + fillgradient + Sets a fill gradient. If not specified, the fillcolor + is used instead. + fillpattern + Sets the pattern within the marker. + groupnorm + Only relevant when `stackgroup` is used, and only the + first `groupnorm` found in the `stackgroup` will be + used - including if `visible` is "legendonly" but not + if it is `false`. Sets the normalization for the sum of + this `stackgroup`. With "fraction", the value of each + trace at each location is divided by the sum of all + trace values at that location. "percent" is the same + but multiplied by 100 to show percentages. If there are + multiple subplots, or multiple `stackgroup`s on one + subplot, each will be normalized within its own set. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatter.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatter.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatter.Line` instance or + dict with compatible properties + marker + :class:`plotly.graph_objects.scatter.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Only relevant in the following cases: 1. when + `scattermode` is set to "group". 2. when `stackgroup` + is used, and only the first `orientation` found in the + `stackgroup` will be used - including if `visible` is + "legendonly" but not if it is `false`. Sets the + stacking direction. With "v" ("h"), the y (x) values of + subsequent traces are added. Also affects the default + value of `fill`. + selected + :class:`plotly.graph_objects.scatter.Selected` instance + or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stackgaps + Only relevant when `stackgroup` is used, and only the + first `stackgaps` found in the `stackgroup` will be + used - including if `visible` is "legendonly" but not + if it is `false`. Determines how we handle locations at + which other traces in this group have data but this one + does not. With *infer zero* we insert a zero at these + locations. With "interpolate" we linearly interpolate + between existing values, and extrapolate a constant + beyond the existing values. + stackgroup + Set several scatter traces (on the same subplot) to the + same stackgroup in order to add their y values (or + their x values if `orientation` is "h"). If blank or + omitted this trace will not be stacked. Stacking also + turns `fill` on by default, using "tonexty" ("tonextx") + if `orientation` is "h" ("v") and sets the default + `mode` to "lines" irrespective of point count. You can + only stack on a numeric (linear or log) axis. Traces in + a `stackgroup` will only fill to (or be filled to) + other traces in the same group. With multiple + `stackgroup`s or some traces stacked and some not, if + fill-linked traces are not already consecutive, the + later ones will be pushed down in the drawing order. + stream + :class:`plotly.graph_objects.scatter.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatter.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + + Returns + ------- + Scatter + """ + super().__init__("scatter") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Scatter +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Scatter`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("alignmentgroup", arg, alignmentgroup) + self._set_property("cliponaxis", arg, cliponaxis) + self._set_property("connectgaps", arg, connectgaps) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("dx", arg, dx) + self._set_property("dy", arg, dy) + self._set_property("error_x", arg, error_x) + self._set_property("error_y", arg, error_y) + self._set_property("fill", arg, fill) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("fillgradient", arg, fillgradient) + self._set_property("fillpattern", arg, fillpattern) + self._set_property("groupnorm", arg, groupnorm) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hoveron", arg, hoveron) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("mode", arg, mode) + self._set_property("name", arg, name) + self._set_property("offsetgroup", arg, offsetgroup) + self._set_property("opacity", arg, opacity) + self._set_property("orientation", arg, orientation) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stackgaps", arg, stackgaps) + self._set_property("stackgroup", arg, stackgroup) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textposition", arg, textposition) + self._set_property("textpositionsrc", arg, textpositionsrc) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("x0", arg, x0) + self._set_property("xaxis", arg, xaxis) + self._set_property("xcalendar", arg, xcalendar) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xperiod", arg, xperiod) + self._set_property("xperiod0", arg, xperiod0) + self._set_property("xperiodalignment", arg, xperiodalignment) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("y0", arg, y0) + self._set_property("yaxis", arg, yaxis) + self._set_property("ycalendar", arg, ycalendar) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("yperiod", arg, yperiod) + self._set_property("yperiod0", arg, yperiod0) + self._set_property("yperiodalignment", arg, yperiodalignment) + self._set_property("ysrc", arg, ysrc) + self._set_property("zorder", arg, zorder) + + self._props["type"] = "scatter" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scatter3d.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scatter3d.py new file mode 100644 index 0000000000000000000000000000000000000000..8247116c7da0299523110e9927242214a0163f24 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scatter3d.py @@ -0,0 +1,2091 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Scatter3d(_BaseTraceType): + _parent_path_str = "" + _path_str = "scatter3d" + _valid_props = { + "connectgaps", + "customdata", + "customdatasrc", + "error_x", + "error_y", + "error_z", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "marker", + "meta", + "metasrc", + "mode", + "name", + "opacity", + "projection", + "scene", + "showlegend", + "stream", + "surfaceaxis", + "surfacecolor", + "text", + "textfont", + "textposition", + "textpositionsrc", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "type", + "uid", + "uirevision", + "visible", + "x", + "xcalendar", + "xhoverformat", + "xsrc", + "y", + "ycalendar", + "yhoverformat", + "ysrc", + "z", + "zcalendar", + "zhoverformat", + "zsrc", + } + + @property + def connectgaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the provided data arrays are connected. + + The 'connectgaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["connectgaps"] + + @connectgaps.setter + def connectgaps(self, val): + self["connectgaps"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def error_x(self): + """ + The 'error_x' property is an instance of ErrorX + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter3d.ErrorX` + - A dict of string/value properties that will be passed + to the ErrorX constructor + + Returns + ------- + plotly.graph_objs.scatter3d.ErrorX + """ + return self["error_x"] + + @error_x.setter + def error_x(self, val): + self["error_x"] = val + + @property + def error_y(self): + """ + The 'error_y' property is an instance of ErrorY + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter3d.ErrorY` + - A dict of string/value properties that will be passed + to the ErrorY constructor + + Returns + ------- + plotly.graph_objs.scatter3d.ErrorY + """ + return self["error_y"] + + @error_y.setter + def error_y(self, val): + self["error_y"] = val + + @property + def error_z(self): + """ + The 'error_z' property is an instance of ErrorZ + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter3d.ErrorZ` + - A dict of string/value properties that will be passed + to the ErrorZ constructor + + Returns + ------- + plotly.graph_objs.scatter3d.ErrorZ + """ + return self["error_z"] + + @error_z.setter + def error_z(self, val): + self["error_z"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter3d.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.scatter3d.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets text elements associated with each (x,y,z) triplet. If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (x,y,z) coordinates. To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter3d.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.scatter3d.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter3d.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.scatter3d.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter3d.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scatter3d.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def mode(self): + """ + Determines the drawing mode for this scatter trace. If the + provided `mode` includes "text" then the `text` elements appear + at the coordinates. Otherwise, the `text` elements appear on + hover. If there are less than 20 points and the trace is not + stacked then the default is "lines+markers". Otherwise, + "lines". + + The 'mode' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lines', 'markers', 'text'] joined with '+' characters + (e.g. 'lines+markers') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["mode"] + + @mode.setter + def mode(self, val): + self["mode"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def projection(self): + """ + The 'projection' property is an instance of Projection + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter3d.Projection` + - A dict of string/value properties that will be passed + to the Projection constructor + + Returns + ------- + plotly.graph_objs.scatter3d.Projection + """ + return self["projection"] + + @projection.setter + def projection(self, val): + self["projection"] = val + + @property + def scene(self): + """ + Sets a reference between this trace's 3D coordinate system and + a 3D scene. If "scene" (the default value), the (x,y,z) + coordinates refer to `layout.scene`. If "scene2", the (x,y,z) + coordinates refer to `layout.scene2`, and so on. + + The 'scene' property is an identifier of a particular + subplot, of type 'scene', that may be specified as: + - the string 'scene' optionally followed by an integer >= 1 + (e.g. 'scene', 'scene1', 'scene2', 'scene3', etc.) + + Returns + ------- + str + """ + return self["scene"] + + @scene.setter + def scene(self, val): + self["scene"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter3d.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.scatter3d.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def surfaceaxis(self): + """ + If "-1", the scatter points are not fill with a surface If 0, + 1, 2, the scatter points are filled with a Delaunay surface + about the x, y, z respectively. + + The 'surfaceaxis' property is an enumeration that may be specified as: + - One of the following enumeration values: + [-1, 0, 1, 2] + + Returns + ------- + Any + """ + return self["surfaceaxis"] + + @surfaceaxis.setter + def surfaceaxis(self, val): + self["surfaceaxis"] = val + + @property + def surfacecolor(self): + """ + Sets the surface fill color. + + The 'surfacecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["surfacecolor"] + + @surfacecolor.setter + def surfacecolor(self, val): + self["surfacecolor"] = val + + @property + def text(self): + """ + Sets text elements associated with each (x,y,z) triplet. If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (x,y,z) coordinates. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, these + elements will be seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the text font. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatter3d.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.scatter3d.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textposition(self): + """ + Sets the positions of the `text` elements with respects to the + (x,y) coordinates. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top left', 'top center', 'top right', 'middle left', + 'middle center', 'middle right', 'bottom left', 'bottom + center', 'bottom right'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textpositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `textposition`. + + The 'textpositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textpositionsrc"] + + @textpositionsrc.setter + def textpositionsrc(self, val): + self["textpositionsrc"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the x coordinates. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xcalendar(self): + """ + Sets the calendar system to use with `x` date data. + + The 'xcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["xcalendar"] + + @xcalendar.setter + def xcalendar(self, val): + self["xcalendar"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the y coordinates. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def ycalendar(self): + """ + Sets the calendar system to use with `y` date data. + + The 'ycalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["ycalendar"] + + @ycalendar.setter + def ycalendar(self, val): + self["ycalendar"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def z(self): + """ + Sets the z coordinates. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zcalendar(self): + """ + Sets the calendar system to use with `z` date data. + + The 'zcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["zcalendar"] + + @zcalendar.setter + def zcalendar(self, val): + self["zcalendar"] = val + + @property + def zhoverformat(self): + """ + Sets the hover text formatting rulefor `z` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `zaxis.hoverformat`. + + The 'zhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["zhoverformat"] + + @zhoverformat.setter + def zhoverformat(self, val): + self["zhoverformat"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + error_x + :class:`plotly.graph_objects.scatter3d.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.scatter3d.ErrorY` instance + or dict with compatible properties + error_z + :class:`plotly.graph_objects.scatter3d.ErrorZ` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatter3d.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets text elements associated with each (x,y,z) + triplet. If a single string, the same string appears + over all the data points. If an array of string, the + items are mapped in order to the this trace's (x,y,z) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatter3d.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatter3d.Line` instance + or dict with compatible properties + marker + :class:`plotly.graph_objects.scatter3d.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + projection + :class:`plotly.graph_objects.scatter3d.Projection` + instance or dict with compatible properties + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatter3d.Stream` instance + or dict with compatible properties + surfaceaxis + If "-1", the scatter points are not fill with a surface + If 0, 1, 2, the scatter points are filled with a + Delaunay surface about the x, y, z respectively. + surfacecolor + Sets the surface fill color. + text + Sets text elements associated with each (x,y,z) + triplet. If a single string, the same string appears + over all the data points. If an array of string, the + items are mapped in order to the this trace's (x,y,z) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates. + zcalendar + Sets the calendar system to use with `z` date data. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + error_x=None, + error_y=None, + error_z=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + projection=None, + scene=None, + showlegend=None, + stream=None, + surfaceaxis=None, + surfacecolor=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xcalendar=None, + xhoverformat=None, + xsrc=None, + y=None, + ycalendar=None, + yhoverformat=None, + ysrc=None, + z=None, + zcalendar=None, + zhoverformat=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Scatter3d object + + The data visualized as scatter point or lines in 3D dimension + is set in `x`, `y`, `z`. Text (appearing either on the chart or + on hover only) is via `text`. Bubble charts are achieved by + setting `marker.size` and/or `marker.color` Projections are + achieved via `projection`. Surface fills are achieved via + `surfaceaxis`. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Scatter3d` + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + error_x + :class:`plotly.graph_objects.scatter3d.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.scatter3d.ErrorY` instance + or dict with compatible properties + error_z + :class:`plotly.graph_objects.scatter3d.ErrorZ` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatter3d.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets text elements associated with each (x,y,z) + triplet. If a single string, the same string appears + over all the data points. If an array of string, the + items are mapped in order to the this trace's (x,y,z) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatter3d.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatter3d.Line` instance + or dict with compatible properties + marker + :class:`plotly.graph_objects.scatter3d.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + projection + :class:`plotly.graph_objects.scatter3d.Projection` + instance or dict with compatible properties + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatter3d.Stream` instance + or dict with compatible properties + surfaceaxis + If "-1", the scatter points are not fill with a surface + If 0, 1, 2, the scatter points are filled with a + Delaunay surface about the x, y, z respectively. + surfacecolor + Sets the surface fill color. + text + Sets text elements associated with each (x,y,z) + triplet. If a single string, the same string appears + over all the data points. If an array of string, the + items are mapped in order to the this trace's (x,y,z) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates. + zcalendar + Sets the calendar system to use with `z` date data. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Scatter3d + """ + super().__init__("scatter3d") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Scatter3d +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Scatter3d`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("connectgaps", arg, connectgaps) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("error_x", arg, error_x) + self._set_property("error_y", arg, error_y) + self._set_property("error_z", arg, error_z) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("mode", arg, mode) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("projection", arg, projection) + self._set_property("scene", arg, scene) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("surfaceaxis", arg, surfaceaxis) + self._set_property("surfacecolor", arg, surfacecolor) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textposition", arg, textposition) + self._set_property("textpositionsrc", arg, textpositionsrc) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("xcalendar", arg, xcalendar) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("ycalendar", arg, ycalendar) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("ysrc", arg, ysrc) + self._set_property("z", arg, z) + self._set_property("zcalendar", arg, zcalendar) + self._set_property("zhoverformat", arg, zhoverformat) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "scatter3d" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattercarpet.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattercarpet.py new file mode 100644 index 0000000000000000000000000000000000000000..769556f1fb2f367d8256d8817b26b7492a6a5df5 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattercarpet.py @@ -0,0 +1,1921 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Scattercarpet(_BaseTraceType): + _parent_path_str = "" + _path_str = "scattercarpet" + _valid_props = { + "a", + "asrc", + "b", + "bsrc", + "carpet", + "connectgaps", + "customdata", + "customdatasrc", + "fill", + "fillcolor", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hoveron", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "marker", + "meta", + "metasrc", + "mode", + "name", + "opacity", + "selected", + "selectedpoints", + "showlegend", + "stream", + "text", + "textfont", + "textposition", + "textpositionsrc", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "type", + "uid", + "uirevision", + "unselected", + "visible", + "xaxis", + "yaxis", + "zorder", + } + + @property + def a(self): + """ + Sets the a-axis coordinates. + + The 'a' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["a"] + + @a.setter + def a(self, val): + self["a"] = val + + @property + def asrc(self): + """ + Sets the source reference on Chart Studio Cloud for `a`. + + The 'asrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["asrc"] + + @asrc.setter + def asrc(self, val): + self["asrc"] = val + + @property + def b(self): + """ + Sets the b-axis coordinates. + + The 'b' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["b"] + + @b.setter + def b(self, val): + self["b"] = val + + @property + def bsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `b`. + + The 'bsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bsrc"] + + @bsrc.setter + def bsrc(self, val): + self["bsrc"] = val + + @property + def carpet(self): + """ + An identifier for this carpet, so that `scattercarpet` and + `contourcarpet` traces can specify a carpet plot on which they + lie + + The 'carpet' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["carpet"] + + @carpet.setter + def carpet(self, val): + self["carpet"] = val + + @property + def connectgaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the provided data arrays are connected. + + The 'connectgaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["connectgaps"] + + @connectgaps.setter + def connectgaps(self, val): + self["connectgaps"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def fill(self): + """ + Sets the area to fill with a solid color. Use with `fillcolor` + if not "none". scatterternary has a subset of the options + available to scatter. "toself" connects the endpoints of the + trace (or each segment of the trace if it has gaps) into a + closed shape. "tonext" fills the space between two traces if + one completely encloses the other (eg consecutive contour + lines), and behaves like "toself" if there is no trace before + it. "tonext" should not be used if one trace does not enclose + the other. + + The 'fill' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'toself', 'tonext'] + + Returns + ------- + Any + """ + return self["fill"] + + @fill.setter + def fill(self, val): + self["fill"] = val + + @property + def fillcolor(self): + """ + Sets the fill color. Defaults to a half-transparent variant of + the line color, marker color, or marker line color, whichever + is available. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['a', 'b', 'text', 'name'] joined with '+' characters + (e.g. 'a+b') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattercarpet.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.scattercarpet.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hoveron(self): + """ + Do the hover effects highlight individual points (markers or + line points) or do they highlight filled regions? If the fill + is "toself" or "tonext" and there are no markers or text, then + the default is "fills", otherwise it is "points". + + The 'hoveron' property is a flaglist and may be specified + as a string containing: + - Any combination of ['points', 'fills'] joined with '+' characters + (e.g. 'points+fills') + + Returns + ------- + Any + """ + return self["hoveron"] + + @hoveron.setter + def hoveron(self, val): + self["hoveron"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each (a,b) point. If a + single string, the same string appears over all the data + points. If an array of strings, the items are mapped in order + to the the data points in (a,b). To be seen, trace `hoverinfo` + must contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattercarpet.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.scattercarpet.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattercarpet.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.scattercarpet.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattercarpet.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scattercarpet.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def mode(self): + """ + Determines the drawing mode for this scatter trace. If the + provided `mode` includes "text" then the `text` elements appear + at the coordinates. Otherwise, the `text` elements appear on + hover. If there are less than 20 points and the trace is not + stacked then the default is "lines+markers". Otherwise, + "lines". + + The 'mode' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lines', 'markers', 'text'] joined with '+' characters + (e.g. 'lines+markers') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["mode"] + + @mode.setter + def mode(self, val): + self["mode"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattercarpet.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.scattercarpet.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattercarpet.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.scattercarpet.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets text elements associated with each (a,b) point. If a + single string, the same string appears over all the data + points. If an array of strings, the items are mapped in order + to the the data points in (a,b). If trace `hoverinfo` contains + a "text" flag and "hovertext" is not set, these elements will + be seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the text font. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattercarpet.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.scattercarpet.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textposition(self): + """ + Sets the positions of the `text` elements with respects to the + (x,y) coordinates. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top left', 'top center', 'top right', 'middle left', + 'middle center', 'middle right', 'bottom left', 'bottom + center', 'bottom right'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textpositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `textposition`. + + The 'textpositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textpositionsrc"] + + @textpositionsrc.setter + def textpositionsrc(self, val): + self["textpositionsrc"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `a`, `b` and `text`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattercarpet.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.scattercarpet.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def zorder(self): + """ + Sets the layer on which this trace is displayed, relative to + other SVG traces on the same subplot. SVG traces with higher + `zorder` appear in front of those with lower `zorder`. + + The 'zorder' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["zorder"] + + @zorder.setter + def zorder(self, val): + self["zorder"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + a + Sets the a-axis coordinates. + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + b + Sets the b-axis coordinates. + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + carpet + An identifier for this carpet, so that `scattercarpet` + and `contourcarpet` traces can specify a carpet plot on + which they lie + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scatterternary has a subset + of the options available to scatter. "toself" connects + the endpoints of the trace (or each segment of the + trace if it has gaps) into a closed shape. "tonext" + fills the space between two traces if one completely + encloses the other (eg consecutive contour lines), and + behaves like "toself" if there is no trace before it. + "tonext" should not be used if one trace does not + enclose the other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattercarpet.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (a,b) + point. If a single string, the same string appears over + all the data points. If an array of strings, the items + are mapped in order to the the data points in (a,b). To + be seen, trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattercarpet.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattercarpet.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scattercarpet.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattercarpet.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattercarpet.Stream` + instance or dict with compatible properties + text + Sets text elements associated with each (a,b) point. If + a single string, the same string appears over all the + data points. If an array of strings, the items are + mapped in order to the the data points in (a,b). If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `a`, `b` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattercarpet.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + """ + + def __init__( + self, + arg=None, + a=None, + asrc=None, + b=None, + bsrc=None, + carpet=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + xaxis=None, + yaxis=None, + zorder=None, + **kwargs, + ): + """ + Construct a new Scattercarpet object + + Plots a scatter trace on either the first carpet axis or the + carpet axis with a matching `carpet` attribute. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Scattercarpet` + a + Sets the a-axis coordinates. + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + b + Sets the b-axis coordinates. + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + carpet + An identifier for this carpet, so that `scattercarpet` + and `contourcarpet` traces can specify a carpet plot on + which they lie + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scatterternary has a subset + of the options available to scatter. "toself" connects + the endpoints of the trace (or each segment of the + trace if it has gaps) into a closed shape. "tonext" + fills the space between two traces if one completely + encloses the other (eg consecutive contour lines), and + behaves like "toself" if there is no trace before it. + "tonext" should not be used if one trace does not + enclose the other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattercarpet.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (a,b) + point. If a single string, the same string appears over + all the data points. If an array of strings, the items + are mapped in order to the the data points in (a,b). To + be seen, trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattercarpet.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattercarpet.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scattercarpet.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattercarpet.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattercarpet.Stream` + instance or dict with compatible properties + text + Sets text elements associated with each (a,b) point. If + a single string, the same string appears over all the + data points. If an array of strings, the items are + mapped in order to the the data points in (a,b). If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `a`, `b` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattercarpet.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + + Returns + ------- + Scattercarpet + """ + super().__init__("scattercarpet") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Scattercarpet +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Scattercarpet`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("a", arg, a) + self._set_property("asrc", arg, asrc) + self._set_property("b", arg, b) + self._set_property("bsrc", arg, bsrc) + self._set_property("carpet", arg, carpet) + self._set_property("connectgaps", arg, connectgaps) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("fill", arg, fill) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hoveron", arg, hoveron) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("mode", arg, mode) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textposition", arg, textposition) + self._set_property("textpositionsrc", arg, textpositionsrc) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + self._set_property("xaxis", arg, xaxis) + self._set_property("yaxis", arg, yaxis) + self._set_property("zorder", arg, zorder) + + self._props["type"] = "scattercarpet" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattergeo.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattergeo.py new file mode 100644 index 0000000000000000000000000000000000000000..dc45749a6ec9ed3de419e1736b55cb55aba27154 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattergeo.py @@ -0,0 +1,1968 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy +import warnings + + +class Scattergeo(_BaseTraceType): + _parent_path_str = "" + _path_str = "scattergeo" + _valid_props = { + "connectgaps", + "customdata", + "customdatasrc", + "featureidkey", + "fill", + "fillcolor", + "geo", + "geojson", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "lat", + "latsrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "locationmode", + "locations", + "locationssrc", + "lon", + "lonsrc", + "marker", + "meta", + "metasrc", + "mode", + "name", + "opacity", + "selected", + "selectedpoints", + "showlegend", + "stream", + "text", + "textfont", + "textposition", + "textpositionsrc", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "type", + "uid", + "uirevision", + "unselected", + "visible", + } + + @property + def connectgaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the provided data arrays are connected. + + The 'connectgaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["connectgaps"] + + @connectgaps.setter + def connectgaps(self, val): + self["connectgaps"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def featureidkey(self): + """ + Sets the key in GeoJSON features which is used as id to match + the items included in the `locations` array. Only has an effect + when `geojson` is set. Support nested property, for example + "properties.name". + + The 'featureidkey' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["featureidkey"] + + @featureidkey.setter + def featureidkey(self, val): + self["featureidkey"] = val + + @property + def fill(self): + """ + Sets the area to fill with a solid color. Use with `fillcolor` + if not "none". "toself" connects the endpoints of the trace (or + each segment of the trace if it has gaps) into a closed shape. + + The 'fill' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'toself'] + + Returns + ------- + Any + """ + return self["fill"] + + @fill.setter + def fill(self, val): + self["fill"] = val + + @property + def fillcolor(self): + """ + Sets the fill color. Defaults to a half-transparent variant of + the line color, marker color, or marker line color, whichever + is available. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def geo(self): + """ + Sets a reference between this trace's geospatial coordinates + and a geographic map. If "geo" (the default value), the + geospatial coordinates refer to `layout.geo`. If "geo2", the + geospatial coordinates refer to `layout.geo2`, and so on. + + The 'geo' property is an identifier of a particular + subplot, of type 'geo', that may be specified as: + - the string 'geo' optionally followed by an integer >= 1 + (e.g. 'geo', 'geo1', 'geo2', 'geo3', etc.) + + Returns + ------- + str + """ + return self["geo"] + + @geo.setter + def geo(self, val): + self["geo"] = val + + @property + def geojson(self): + """ + Sets optional GeoJSON data associated with this trace. If not + given, the features on the base map are used when `locations` + is set. It can be set as a valid GeoJSON object or as a URL + string. Note that we only accept GeoJSONs of type + "FeatureCollection" or "Feature" with geometries of type + "Polygon" or "MultiPolygon". + + The 'geojson' property accepts values of any type + + Returns + ------- + Any + """ + return self["geojson"] + + @geojson.setter + def geojson(self, val): + self["geojson"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lon', 'lat', 'location', 'text', 'name'] joined with '+' characters + (e.g. 'lon+lat') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergeo.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.scattergeo.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each (lon,lat) pair or + item in `locations`. If a single string, the same string + appears over all the data points. If an array of string, the + items are mapped in order to the this trace's (lon,lat) or + `locations` coordinates. To be seen, trace `hoverinfo` must + contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def lat(self): + """ + Sets the latitude coordinates (in degrees North). + + The 'lat' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["lat"] + + @lat.setter + def lat(self, val): + self["lat"] = val + + @property + def latsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `lat`. + + The 'latsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["latsrc"] + + @latsrc.setter + def latsrc(self, val): + self["latsrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergeo.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.scattergeo.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergeo.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.scattergeo.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def locationmode(self): + """ + The library used by the *country names* `locationmode` option + is changing in an upcoming version. Country names in existing + plots may not work in the new version. Determines the set of + locations used to match entries in `locations` to regions on + the map. Values "ISO-3", "USA-states", *country names* + correspond to features on the base map and value "geojson-id" + corresponds to features from a custom GeoJSON linked to the + `geojson` attribute. + + The 'locationmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['ISO-3', 'USA-states', 'country names', 'geojson-id'] + + Returns + ------- + Any + """ + return self["locationmode"] + + @locationmode.setter + def locationmode(self, val): + self["locationmode"] = val + + @property + def locations(self): + """ + Sets the coordinates via location IDs or names. Coordinates + correspond to the centroid of each location given. See + `locationmode` for more info. + + The 'locations' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["locations"] + + @locations.setter + def locations(self, val): + self["locations"] = val + + @property + def locationssrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `locations`. + + The 'locationssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["locationssrc"] + + @locationssrc.setter + def locationssrc(self, val): + self["locationssrc"] = val + + @property + def lon(self): + """ + Sets the longitude coordinates (in degrees East). + + The 'lon' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["lon"] + + @lon.setter + def lon(self, val): + self["lon"] = val + + @property + def lonsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `lon`. + + The 'lonsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["lonsrc"] + + @lonsrc.setter + def lonsrc(self, val): + self["lonsrc"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergeo.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scattergeo.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def mode(self): + """ + Determines the drawing mode for this scatter trace. If the + provided `mode` includes "text" then the `text` elements appear + at the coordinates. Otherwise, the `text` elements appear on + hover. If there are less than 20 points and the trace is not + stacked then the default is "lines+markers". Otherwise, + "lines". + + The 'mode' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lines', 'markers', 'text'] joined with '+' characters + (e.g. 'lines+markers') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["mode"] + + @mode.setter + def mode(self, val): + self["mode"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergeo.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.scattergeo.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergeo.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.scattergeo.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets text elements associated with each (lon,lat) pair or item + in `locations`. If a single string, the same string appears + over all the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) or `locations` + coordinates. If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in the + hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the text font. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergeo.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.scattergeo.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textposition(self): + """ + Sets the positions of the `text` elements with respects to the + (x,y) coordinates. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top left', 'top center', 'top right', 'middle left', + 'middle center', 'middle right', 'bottom left', 'bottom + center', 'bottom right'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textpositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `textposition`. + + The 'textpositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textpositionsrc"] + + @textpositionsrc.setter + def textpositionsrc(self, val): + self["textpositionsrc"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `lat`, `lon`, `location` and `text`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergeo.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.scattergeo.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. Only + has an effect when `geojson` is set. Support nested + property, for example "properties.name". + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + geo + Sets a reference between this trace's geospatial + coordinates and a geographic map. If "geo" (the default + value), the geospatial coordinates refer to + `layout.geo`. If "geo2", the geospatial coordinates + refer to `layout.geo2`, and so on. + geojson + Sets optional GeoJSON data associated with this trace. + If not given, the features on the base map are used + when `locations` is set. It can be set as a valid + GeoJSON object or as a URL string. Note that we only + accept GeoJSONs of type "FeatureCollection" or + "Feature" with geometries of type "Polygon" or + "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattergeo.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair or item in `locations`. If a single string, the + same string appears over all the data points. If an + array of string, the items are mapped in order to the + this trace's (lon,lat) or `locations` coordinates. To + be seen, trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattergeo.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattergeo.Line` instance + or dict with compatible properties + locationmode + The library used by the *country names* `locationmode` + option is changing in an upcoming version. Country + names in existing plots may not work in the new + version. Determines the set of locations used to match + entries in `locations` to regions on the map. Values + "ISO-3", "USA-states", *country names* correspond to + features on the base map and value "geojson-id" + corresponds to features from a custom GeoJSON linked to + the `geojson` attribute. + locations + Sets the coordinates via location IDs or names. + Coordinates correspond to the centroid of each location + given. See `locationmode` for more info. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + marker + :class:`plotly.graph_objects.scattergeo.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattergeo.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattergeo.Stream` + instance or dict with compatible properties + text + Sets text elements associated with each (lon,lat) pair + or item in `locations`. If a single string, the same + string appears over all the data points. If an array of + string, the items are mapped in order to the this + trace's (lon,lat) or `locations` coordinates. If trace + `hoverinfo` contains a "text" flag and "hovertext" is + not set, these elements will be seen in the hover + labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `lat`, `lon`, `location` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattergeo.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + featureidkey=None, + fill=None, + fillcolor=None, + geo=None, + geojson=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + lat=None, + latsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + locationmode=None, + locations=None, + locationssrc=None, + lon=None, + lonsrc=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + **kwargs, + ): + """ + Construct a new Scattergeo object + + The data visualized as scatter point or lines on a geographic + map is provided either by longitude/latitude pairs in `lon` and + `lat` respectively or by geographic location IDs or names in + `locations`. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Scattergeo` + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + featureidkey + Sets the key in GeoJSON features which is used as id to + match the items included in the `locations` array. Only + has an effect when `geojson` is set. Support nested + property, for example "properties.name". + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + geo + Sets a reference between this trace's geospatial + coordinates and a geographic map. If "geo" (the default + value), the geospatial coordinates refer to + `layout.geo`. If "geo2", the geospatial coordinates + refer to `layout.geo2`, and so on. + geojson + Sets optional GeoJSON data associated with this trace. + If not given, the features on the base map are used + when `locations` is set. It can be set as a valid + GeoJSON object or as a URL string. Note that we only + accept GeoJSONs of type "FeatureCollection" or + "Feature" with geometries of type "Polygon" or + "MultiPolygon". + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattergeo.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair or item in `locations`. If a single string, the + same string appears over all the data points. If an + array of string, the items are mapped in order to the + this trace's (lon,lat) or `locations` coordinates. To + be seen, trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattergeo.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattergeo.Line` instance + or dict with compatible properties + locationmode + The library used by the *country names* `locationmode` + option is changing in an upcoming version. Country + names in existing plots may not work in the new + version. Determines the set of locations used to match + entries in `locations` to regions on the map. Values + "ISO-3", "USA-states", *country names* correspond to + features on the base map and value "geojson-id" + corresponds to features from a custom GeoJSON linked to + the `geojson` attribute. + locations + Sets the coordinates via location IDs or names. + Coordinates correspond to the centroid of each location + given. See `locationmode` for more info. + locationssrc + Sets the source reference on Chart Studio Cloud for + `locations`. + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + marker + :class:`plotly.graph_objects.scattergeo.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattergeo.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattergeo.Stream` + instance or dict with compatible properties + text + Sets text elements associated with each (lon,lat) pair + or item in `locations`. If a single string, the same + string appears over all the data points. If an array of + string, the items are mapped in order to the this + trace's (lon,lat) or `locations` coordinates. If trace + `hoverinfo` contains a "text" flag and "hovertext" is + not set, these elements will be seen in the hover + labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `lat`, `lon`, `location` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattergeo.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Scattergeo + """ + super().__init__("scattergeo") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Scattergeo +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Scattergeo`""") + + if locationmode == "country names" and kwargs.get("_validate"): + warnings.warn( + "The library used by the *country names* `locationmode` option is changing in an upcoming version. " + "Country names in existing plots may not work in the new version. " + "To ensure consistent behavior, consider setting `locationmode` to *ISO-3*.", + DeprecationWarning, + stacklevel=5, + ) + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("connectgaps", arg, connectgaps) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("featureidkey", arg, featureidkey) + self._set_property("fill", arg, fill) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("geo", arg, geo) + self._set_property("geojson", arg, geojson) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("lat", arg, lat) + self._set_property("latsrc", arg, latsrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("locationmode", arg, locationmode) + self._set_property("locations", arg, locations) + self._set_property("locationssrc", arg, locationssrc) + self._set_property("lon", arg, lon) + self._set_property("lonsrc", arg, lonsrc) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("mode", arg, mode) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textposition", arg, textposition) + self._set_property("textpositionsrc", arg, textpositionsrc) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + + self._props["type"] = "scattergeo" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattergl.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattergl.py new file mode 100644 index 0000000000000000000000000000000000000000..e2054bc71ca7b51d94482acbc1ac56ec82ea9b74 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattergl.py @@ -0,0 +1,2383 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Scattergl(_BaseTraceType): + _parent_path_str = "" + _path_str = "scattergl" + _valid_props = { + "connectgaps", + "customdata", + "customdatasrc", + "dx", + "dy", + "error_x", + "error_y", + "fill", + "fillcolor", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "marker", + "meta", + "metasrc", + "mode", + "name", + "opacity", + "selected", + "selectedpoints", + "showlegend", + "stream", + "text", + "textfont", + "textposition", + "textpositionsrc", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "type", + "uid", + "uirevision", + "unselected", + "visible", + "x", + "x0", + "xaxis", + "xcalendar", + "xhoverformat", + "xperiod", + "xperiod0", + "xperiodalignment", + "xsrc", + "y", + "y0", + "yaxis", + "ycalendar", + "yhoverformat", + "yperiod", + "yperiod0", + "yperiodalignment", + "ysrc", + } + + @property + def connectgaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the provided data arrays are connected. + + The 'connectgaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["connectgaps"] + + @connectgaps.setter + def connectgaps(self, val): + self["connectgaps"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def dx(self): + """ + Sets the x coordinate step. See `x0` for more info. + + The 'dx' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dx"] + + @dx.setter + def dx(self, val): + self["dx"] = val + + @property + def dy(self): + """ + Sets the y coordinate step. See `y0` for more info. + + The 'dy' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dy"] + + @dy.setter + def dy(self, val): + self["dy"] = val + + @property + def error_x(self): + """ + The 'error_x' property is an instance of ErrorX + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.ErrorX` + - A dict of string/value properties that will be passed + to the ErrorX constructor + + Returns + ------- + plotly.graph_objs.scattergl.ErrorX + """ + return self["error_x"] + + @error_x.setter + def error_x(self, val): + self["error_x"] = val + + @property + def error_y(self): + """ + The 'error_y' property is an instance of ErrorY + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.ErrorY` + - A dict of string/value properties that will be passed + to the ErrorY constructor + + Returns + ------- + plotly.graph_objs.scattergl.ErrorY + """ + return self["error_y"] + + @error_y.setter + def error_y(self, val): + self["error_y"] = val + + @property + def fill(self): + """ + Sets the area to fill with a solid color. Defaults to "none" + unless this trace is stacked, then it gets "tonexty" + ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` + if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 + respectively. "tonextx" and "tonexty" fill between the + endpoints of this trace and the endpoints of the trace before + it, connecting those endpoints with straight lines (to make a + stacked area graph); if there is no trace before it, they + behave like "tozerox" and "tozeroy". "toself" connects the + endpoints of the trace (or each segment of the trace if it has + gaps) into a closed shape. "tonext" fills the space between two + traces if one completely encloses the other (eg consecutive + contour lines), and behaves like "toself" if there is no trace + before it. "tonext" should not be used if one trace does not + enclose the other. Traces in a `stackgroup` will only fill to + (or be filled to) other traces in the same group. With multiple + `stackgroup`s or some traces stacked and some not, if fill- + linked traces are not already consecutive, the later ones will + be pushed down in the drawing order. + + The 'fill' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'tozeroy', 'tozerox', 'tonexty', 'tonextx', + 'toself', 'tonext'] + + Returns + ------- + Any + """ + return self["fill"] + + @fill.setter + def fill(self, val): + self["fill"] = val + + @property + def fillcolor(self): + """ + Sets the fill color. Defaults to a half-transparent variant of + the line color, marker color, or marker line color, whichever + is available. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.scattergl.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each (x,y) pair. If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (x,y) coordinates. To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.scattergl.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.scattergl.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scattergl.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def mode(self): + """ + Determines the drawing mode for this scatter trace. + + The 'mode' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lines', 'markers', 'text'] joined with '+' characters + (e.g. 'lines+markers') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["mode"] + + @mode.setter + def mode(self, val): + self["mode"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.scattergl.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.scattergl.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets text elements associated with each (x,y) pair. If a single + string, the same string appears over all the data points. If an + array of string, the items are mapped in order to the this + trace's (x,y) coordinates. If trace `hoverinfo` contains a + "text" flag and "hovertext" is not set, these elements will be + seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the text font. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.scattergl.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textposition(self): + """ + Sets the positions of the `text` elements with respects to the + (x,y) coordinates. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top left', 'top center', 'top right', 'middle left', + 'middle center', 'middle right', 'bottom left', 'bottom + center', 'bottom right'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textpositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `textposition`. + + The 'textpositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textpositionsrc"] + + @textpositionsrc.setter + def textpositionsrc(self, val): + self["textpositionsrc"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.scattergl.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the x coordinates. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def x0(self): + """ + Alternate to `x`. Builds a linear space of x coordinates. Use + with `dx` where `x0` is the starting coordinate and `dx` the + step. + + The 'x0' property accepts values of any type + + Returns + ------- + Any + """ + return self["x0"] + + @x0.setter + def x0(self, val): + self["x0"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def xcalendar(self): + """ + Sets the calendar system to use with `x` date data. + + The 'xcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["xcalendar"] + + @xcalendar.setter + def xcalendar(self, val): + self["xcalendar"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the x axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'xperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod"] + + @xperiod.setter + def xperiod(self, val): + self["xperiod"] = val + + @property + def xperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the x0 + axis. When `x0period` is round number of weeks, the `x0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'xperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod0"] + + @xperiod0.setter + def xperiod0(self, val): + self["xperiod0"] = val + + @property + def xperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + + The 'xperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["xperiodalignment"] + + @xperiodalignment.setter + def xperiodalignment(self, val): + self["xperiodalignment"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the y coordinates. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def y0(self): + """ + Alternate to `y`. Builds a linear space of y coordinates. Use + with `dy` where `y0` is the starting coordinate and `dy` the + step. + + The 'y0' property accepts values of any type + + Returns + ------- + Any + """ + return self["y0"] + + @y0.setter + def y0(self, val): + self["y0"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def ycalendar(self): + """ + Sets the calendar system to use with `y` date data. + + The 'ycalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["ycalendar"] + + @ycalendar.setter + def ycalendar(self, val): + self["ycalendar"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def yperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the y axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'yperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod"] + + @yperiod.setter + def yperiod(self, val): + self["yperiod"] = val + + @property + def yperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the y0 + axis. When `y0period` is round number of weeks, the `y0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'yperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod0"] + + @yperiod0.setter + def yperiod0(self, val): + self["yperiod0"] = val + + @property + def yperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + + The 'yperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["yperiodalignment"] + + @yperiodalignment.setter + def yperiodalignment(self, val): + self["yperiodalignment"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + error_x + :class:`plotly.graph_objects.scattergl.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.scattergl.ErrorY` instance + or dict with compatible properties + fill + Sets the area to fill with a solid color. Defaults to + "none" unless this trace is stacked, then it gets + "tonexty" ("tonextx") if `orientation` is "v" ("h") Use + with `fillcolor` if not "none". "tozerox" and "tozeroy" + fill to x=0 and y=0 respectively. "tonextx" and + "tonexty" fill between the endpoints of this trace and + the endpoints of the trace before it, connecting those + endpoints with straight lines (to make a stacked area + graph); if there is no trace before it, they behave + like "tozerox" and "tozeroy". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. Traces in a `stackgroup` will only fill to (or + be filled to) other traces in the same group. With + multiple `stackgroup`s or some traces stacked and some + not, if fill-linked traces are not already consecutive, + the later ones will be pushed down in the drawing + order. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattergl.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattergl.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattergl.Line` instance + or dict with compatible properties + marker + :class:`plotly.graph_objects.scattergl.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattergl.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattergl.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattergl.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + """ + + def __init__( + self, + arg=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + dx=None, + dy=None, + error_x=None, + error_y=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + x=None, + x0=None, + xaxis=None, + xcalendar=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + ycalendar=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + **kwargs, + ): + """ + Construct a new Scattergl object + + The data visualized as scatter point or lines is set in `x` and + `y` using the WebGL plotting engine. Bubble charts are achieved + by setting `marker.size` and/or `marker.color` to a numerical + arrays. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Scattergl` + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + error_x + :class:`plotly.graph_objects.scattergl.ErrorX` instance + or dict with compatible properties + error_y + :class:`plotly.graph_objects.scattergl.ErrorY` instance + or dict with compatible properties + fill + Sets the area to fill with a solid color. Defaults to + "none" unless this trace is stacked, then it gets + "tonexty" ("tonextx") if `orientation` is "v" ("h") Use + with `fillcolor` if not "none". "tozerox" and "tozeroy" + fill to x=0 and y=0 respectively. "tonextx" and + "tonexty" fill between the endpoints of this trace and + the endpoints of the trace before it, connecting those + endpoints with straight lines (to make a stacked area + graph); if there is no trace before it, they behave + like "tozerox" and "tozeroy". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. Traces in a `stackgroup` will only fill to (or + be filled to) other traces in the same group. With + multiple `stackgroup`s or some traces stacked and some + not, if fill-linked traces are not already consecutive, + the later ones will be pushed down in the drawing + order. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattergl.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattergl.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattergl.Line` instance + or dict with compatible properties + marker + :class:`plotly.graph_objects.scattergl.Marker` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattergl.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattergl.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattergl.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + + Returns + ------- + Scattergl + """ + super().__init__("scattergl") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Scattergl +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Scattergl`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("connectgaps", arg, connectgaps) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("dx", arg, dx) + self._set_property("dy", arg, dy) + self._set_property("error_x", arg, error_x) + self._set_property("error_y", arg, error_y) + self._set_property("fill", arg, fill) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("mode", arg, mode) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textposition", arg, textposition) + self._set_property("textpositionsrc", arg, textpositionsrc) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("x0", arg, x0) + self._set_property("xaxis", arg, xaxis) + self._set_property("xcalendar", arg, xcalendar) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xperiod", arg, xperiod) + self._set_property("xperiod0", arg, xperiod0) + self._set_property("xperiodalignment", arg, xperiodalignment) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("y0", arg, y0) + self._set_property("yaxis", arg, yaxis) + self._set_property("ycalendar", arg, ycalendar) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("yperiod", arg, yperiod) + self._set_property("yperiod0", arg, yperiod0) + self._set_property("yperiodalignment", arg, yperiodalignment) + self._set_property("ysrc", arg, ysrc) + + self._props["type"] = "scattergl" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattermap.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattermap.py new file mode 100644 index 0000000000000000000000000000000000000000..9d55304bacaf4cc762ffa5e7c3abf6b065000041 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattermap.py @@ -0,0 +1,1803 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Scattermap(_BaseTraceType): + _parent_path_str = "" + _path_str = "scattermap" + _valid_props = { + "below", + "cluster", + "connectgaps", + "customdata", + "customdatasrc", + "fill", + "fillcolor", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "lat", + "latsrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "lon", + "lonsrc", + "marker", + "meta", + "metasrc", + "mode", + "name", + "opacity", + "selected", + "selectedpoints", + "showlegend", + "stream", + "subplot", + "text", + "textfont", + "textposition", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "type", + "uid", + "uirevision", + "unselected", + "visible", + } + + @property + def below(self): + """ + Determines if this scattermap trace's layers are to be inserted + before the layer with the specified ID. By default, scattermap + layers are inserted above all the base layers. To place the + scattermap layers above every other layer, set `below` to "''". + + The 'below' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["below"] + + @below.setter + def below(self, val): + self["below"] = val + + @property + def cluster(self): + """ + The 'cluster' property is an instance of Cluster + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermap.Cluster` + - A dict of string/value properties that will be passed + to the Cluster constructor + + Returns + ------- + plotly.graph_objs.scattermap.Cluster + """ + return self["cluster"] + + @cluster.setter + def cluster(self, val): + self["cluster"] = val + + @property + def connectgaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the provided data arrays are connected. + + The 'connectgaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["connectgaps"] + + @connectgaps.setter + def connectgaps(self, val): + self["connectgaps"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def fill(self): + """ + Sets the area to fill with a solid color. Use with `fillcolor` + if not "none". "toself" connects the endpoints of the trace (or + each segment of the trace if it has gaps) into a closed shape. + + The 'fill' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'toself'] + + Returns + ------- + Any + """ + return self["fill"] + + @fill.setter + def fill(self, val): + self["fill"] = val + + @property + def fillcolor(self): + """ + Sets the fill color. Defaults to a half-transparent variant of + the line color, marker color, or marker line color, whichever + is available. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lon', 'lat', 'text', 'name'] joined with '+' characters + (e.g. 'lon+lat') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermap.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.scattermap.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each (lon,lat) pair If + a single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (lon,lat) coordinates. To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def lat(self): + """ + Sets the latitude coordinates (in degrees North). + + The 'lat' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["lat"] + + @lat.setter + def lat(self, val): + self["lat"] = val + + @property + def latsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `lat`. + + The 'latsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["latsrc"] + + @latsrc.setter + def latsrc(self, val): + self["latsrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermap.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.scattermap.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermap.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.scattermap.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def lon(self): + """ + Sets the longitude coordinates (in degrees East). + + The 'lon' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["lon"] + + @lon.setter + def lon(self, val): + self["lon"] = val + + @property + def lonsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `lon`. + + The 'lonsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["lonsrc"] + + @lonsrc.setter + def lonsrc(self, val): + self["lonsrc"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermap.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scattermap.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def mode(self): + """ + Determines the drawing mode for this scatter trace. If the + provided `mode` includes "text" then the `text` elements appear + at the coordinates. Otherwise, the `text` elements appear on + hover. + + The 'mode' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lines', 'markers', 'text'] joined with '+' characters + (e.g. 'lines+markers') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["mode"] + + @mode.setter + def mode(self, val): + self["mode"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermap.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.scattermap.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermap.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.scattermap.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def subplot(self): + """ + Sets a reference between this trace's data coordinates and a + map subplot. If "map" (the default value), the data refer to + `layout.map`. If "map2", the data refer to `layout.map2`, and + so on. + + The 'subplot' property is an identifier of a particular + subplot, of type 'map', that may be specified as: + - the string 'map' optionally followed by an integer >= 1 + (e.g. 'map', 'map1', 'map2', 'map3', etc.) + + Returns + ------- + str + """ + return self["subplot"] + + @subplot.setter + def subplot(self, val): + self["subplot"] = val + + @property + def text(self): + """ + Sets text elements associated with each (lon,lat) pair If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (lon,lat) coordinates. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, these + elements will be seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the icon text font (color=map.layer.paint.text-color, + size=map.layer.layout.text-size). Has an effect only when + `type` is set to "symbol". + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermap.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.scattermap.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textposition(self): + """ + Sets the positions of the `text` elements with respects to the + (x,y) coordinates. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top left', 'top center', 'top right', 'middle left', + 'middle center', 'middle right', 'bottom left', 'bottom + center', 'bottom right'] + + Returns + ------- + Any + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `lat`, `lon` and `text`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermap.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.scattermap.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + below + Determines if this scattermap trace's layers are to be + inserted before the layer with the specified ID. By + default, scattermap layers are inserted above all the + base layers. To place the scattermap layers above every + other layer, set `below` to "''". + cluster + :class:`plotly.graph_objects.scattermap.Cluster` + instance or dict with compatible properties + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattermap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattermap.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattermap.Line` instance + or dict with compatible properties + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + marker + :class:`plotly.graph_objects.scattermap.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattermap.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattermap.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a map subplot. If "map" (the default value), the + data refer to `layout.map`. If "map2", the data refer + to `layout.map2`, and so on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textfont + Sets the icon text font (color=map.layer.paint.text- + color, size=map.layer.layout.text-size). Has an effect + only when `type` is set to "symbol". + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `lat`, `lon` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattermap.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + below=None, + cluster=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + lat=None, + latsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + lon=None, + lonsrc=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textfont=None, + textposition=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + **kwargs, + ): + """ + Construct a new Scattermap object + + The data visualized as scatter point, lines or marker symbols + on a MapLibre GL geographic map is provided by + longitude/latitude pairs in `lon` and `lat`. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Scattermap` + below + Determines if this scattermap trace's layers are to be + inserted before the layer with the specified ID. By + default, scattermap layers are inserted above all the + base layers. To place the scattermap layers above every + other layer, set `below` to "''". + cluster + :class:`plotly.graph_objects.scattermap.Cluster` + instance or dict with compatible properties + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattermap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattermap.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattermap.Line` instance + or dict with compatible properties + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + marker + :class:`plotly.graph_objects.scattermap.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattermap.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattermap.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a map subplot. If "map" (the default value), the + data refer to `layout.map`. If "map2", the data refer + to `layout.map2`, and so on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textfont + Sets the icon text font (color=map.layer.paint.text- + color, size=map.layer.layout.text-size). Has an effect + only when `type` is set to "symbol". + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `lat`, `lon` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattermap.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Scattermap + """ + super().__init__("scattermap") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Scattermap +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Scattermap`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("below", arg, below) + self._set_property("cluster", arg, cluster) + self._set_property("connectgaps", arg, connectgaps) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("fill", arg, fill) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("lat", arg, lat) + self._set_property("latsrc", arg, latsrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("lon", arg, lon) + self._set_property("lonsrc", arg, lonsrc) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("mode", arg, mode) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("subplot", arg, subplot) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textposition", arg, textposition) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + + self._props["type"] = "scattermap" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattermapbox.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattermapbox.py new file mode 100644 index 0000000000000000000000000000000000000000..e6fe0cef217d377f0da9debb7f776ccf7b6687ac --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattermapbox.py @@ -0,0 +1,1831 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy +import warnings + + +class Scattermapbox(_BaseTraceType): + _parent_path_str = "" + _path_str = "scattermapbox" + _valid_props = { + "below", + "cluster", + "connectgaps", + "customdata", + "customdatasrc", + "fill", + "fillcolor", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "lat", + "latsrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "lon", + "lonsrc", + "marker", + "meta", + "metasrc", + "mode", + "name", + "opacity", + "selected", + "selectedpoints", + "showlegend", + "stream", + "subplot", + "text", + "textfont", + "textposition", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "type", + "uid", + "uirevision", + "unselected", + "visible", + } + + @property + def below(self): + """ + Determines if this scattermapbox trace's layers are to be + inserted before the layer with the specified ID. By default, + scattermapbox layers are inserted above all the base layers. To + place the scattermapbox layers above every other layer, set + `below` to "''". + + The 'below' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["below"] + + @below.setter + def below(self, val): + self["below"] = val + + @property + def cluster(self): + """ + The 'cluster' property is an instance of Cluster + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermapbox.Cluster` + - A dict of string/value properties that will be passed + to the Cluster constructor + + Returns + ------- + plotly.graph_objs.scattermapbox.Cluster + """ + return self["cluster"] + + @cluster.setter + def cluster(self, val): + self["cluster"] = val + + @property + def connectgaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the provided data arrays are connected. + + The 'connectgaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["connectgaps"] + + @connectgaps.setter + def connectgaps(self, val): + self["connectgaps"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def fill(self): + """ + Sets the area to fill with a solid color. Use with `fillcolor` + if not "none". "toself" connects the endpoints of the trace (or + each segment of the trace if it has gaps) into a closed shape. + + The 'fill' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'toself'] + + Returns + ------- + Any + """ + return self["fill"] + + @fill.setter + def fill(self, val): + self["fill"] = val + + @property + def fillcolor(self): + """ + Sets the fill color. Defaults to a half-transparent variant of + the line color, marker color, or marker line color, whichever + is available. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lon', 'lat', 'text', 'name'] joined with '+' characters + (e.g. 'lon+lat') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermapbox.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.scattermapbox.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each (lon,lat) pair If + a single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (lon,lat) coordinates. To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def lat(self): + """ + Sets the latitude coordinates (in degrees North). + + The 'lat' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["lat"] + + @lat.setter + def lat(self, val): + self["lat"] = val + + @property + def latsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `lat`. + + The 'latsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["latsrc"] + + @latsrc.setter + def latsrc(self, val): + self["latsrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermapbox.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.scattermapbox.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermapbox.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.scattermapbox.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def lon(self): + """ + Sets the longitude coordinates (in degrees East). + + The 'lon' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["lon"] + + @lon.setter + def lon(self, val): + self["lon"] = val + + @property + def lonsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `lon`. + + The 'lonsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["lonsrc"] + + @lonsrc.setter + def lonsrc(self, val): + self["lonsrc"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermapbox.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scattermapbox.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def mode(self): + """ + Determines the drawing mode for this scatter trace. If the + provided `mode` includes "text" then the `text` elements appear + at the coordinates. Otherwise, the `text` elements appear on + hover. + + The 'mode' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lines', 'markers', 'text'] joined with '+' characters + (e.g. 'lines+markers') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["mode"] + + @mode.setter + def mode(self, val): + self["mode"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermapbox.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.scattermapbox.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermapbox.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.scattermapbox.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def subplot(self): + """ + mapbox subplots and traces are deprecated! Please consider + switching to `map` subplots and traces. Learn more at: + https://plotly.com/python/maplibre-migration/ as well as + https://plotly.com/javascript/maplibre-migration/ Sets a + reference between this trace's data coordinates and a mapbox + subplot. If "mapbox" (the default value), the data refer to + `layout.mapbox`. If "mapbox2", the data refer to + `layout.mapbox2`, and so on. + + The 'subplot' property is an identifier of a particular + subplot, of type 'mapbox', that may be specified as: + - the string 'mapbox' optionally followed by an integer >= 1 + (e.g. 'mapbox', 'mapbox1', 'mapbox2', 'mapbox3', etc.) + + Returns + ------- + str + """ + return self["subplot"] + + @subplot.setter + def subplot(self, val): + self["subplot"] = val + + @property + def text(self): + """ + Sets text elements associated with each (lon,lat) pair If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (lon,lat) coordinates. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, these + elements will be seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the icon text font (color=mapbox.layer.paint.text-color, + size=mapbox.layer.layout.text-size). Has an effect only when + `type` is set to "symbol". + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermapbox.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.scattermapbox.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textposition(self): + """ + Sets the positions of the `text` elements with respects to the + (x,y) coordinates. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top left', 'top center', 'top right', 'middle left', + 'middle center', 'middle right', 'bottom left', 'bottom + center', 'bottom right'] + + Returns + ------- + Any + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `lat`, `lon` and `text`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermapbox.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.scattermapbox.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + below + Determines if this scattermapbox trace's layers are to + be inserted before the layer with the specified ID. By + default, scattermapbox layers are inserted above all + the base layers. To place the scattermapbox layers + above every other layer, set `below` to "''". + cluster + :class:`plotly.graph_objects.scattermapbox.Cluster` + instance or dict with compatible properties + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattermapbox.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattermapbox.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattermapbox.Line` + instance or dict with compatible properties + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + marker + :class:`plotly.graph_objects.scattermapbox.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattermapbox.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattermapbox.Stream` + instance or dict with compatible properties + subplot + mapbox subplots and traces are deprecated! Please + consider switching to `map` subplots and traces. Learn + more at: https://plotly.com/python/maplibre-migration/ + as well as https://plotly.com/javascript/maplibre- + migration/ Sets a reference between this trace's data + coordinates and a mapbox subplot. If "mapbox" (the + default value), the data refer to `layout.mapbox`. If + "mapbox2", the data refer to `layout.mapbox2`, and so + on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textfont + Sets the icon text font (color=mapbox.layer.paint.text- + color, size=mapbox.layer.layout.text-size). Has an + effect only when `type` is set to "symbol". + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `lat`, `lon` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattermapbox.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + below=None, + cluster=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + lat=None, + latsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + lon=None, + lonsrc=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textfont=None, + textposition=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + **kwargs, + ): + """ + Construct a new Scattermapbox object + + "scattermapbox" trace is deprecated! Please consider switching + to the "scattermap" trace type and `map` subplots. Learn more + at: https://plotly.com/python/maplibre-migration/ as well as + https://plotly.com/javascript/maplibre-migration/ The data + visualized as scatter point, lines or marker symbols on a + Mapbox GL geographic map is provided by longitude/latitude + pairs in `lon` and `lat`. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Scattermapbox` + below + Determines if this scattermapbox trace's layers are to + be inserted before the layer with the specified ID. By + default, scattermapbox layers are inserted above all + the base layers. To place the scattermapbox layers + above every other layer, set `below` to "''". + cluster + :class:`plotly.graph_objects.scattermapbox.Cluster` + instance or dict with compatible properties + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattermapbox.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (lon,lat) + pair If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (lon,lat) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + lat + Sets the latitude coordinates (in degrees North). + latsrc + Sets the source reference on Chart Studio Cloud for + `lat`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattermapbox.Legendgroupt + itle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattermapbox.Line` + instance or dict with compatible properties + lon + Sets the longitude coordinates (in degrees East). + lonsrc + Sets the source reference on Chart Studio Cloud for + `lon`. + marker + :class:`plotly.graph_objects.scattermapbox.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scattermapbox.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattermapbox.Stream` + instance or dict with compatible properties + subplot + mapbox subplots and traces are deprecated! Please + consider switching to `map` subplots and traces. Learn + more at: https://plotly.com/python/maplibre-migration/ + as well as https://plotly.com/javascript/maplibre- + migration/ Sets a reference between this trace's data + coordinates and a mapbox subplot. If "mapbox" (the + default value), the data refer to `layout.mapbox`. If + "mapbox2", the data refer to `layout.mapbox2`, and so + on. + text + Sets text elements associated with each (lon,lat) pair + If a single string, the same string appears over all + the data points. If an array of string, the items are + mapped in order to the this trace's (lon,lat) + coordinates. If trace `hoverinfo` contains a "text" + flag and "hovertext" is not set, these elements will be + seen in the hover labels. + textfont + Sets the icon text font (color=mapbox.layer.paint.text- + color, size=mapbox.layer.layout.text-size). Has an + effect only when `type` is set to "symbol". + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `lat`, `lon` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattermapbox.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Scattermapbox + """ + super().__init__("scattermapbox") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Scattermapbox +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Scattermapbox`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("below", arg, below) + self._set_property("cluster", arg, cluster) + self._set_property("connectgaps", arg, connectgaps) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("fill", arg, fill) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("lat", arg, lat) + self._set_property("latsrc", arg, latsrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("lon", arg, lon) + self._set_property("lonsrc", arg, lonsrc) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("mode", arg, mode) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("subplot", arg, subplot) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textposition", arg, textposition) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + + self._props["type"] = "scattermapbox" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False + + warnings.warn( + "*scattermapbox* is deprecated!" + + " Use *scattermap* instead." + + " Learn more at: https://plotly.com/python/mapbox-to-maplibre/", + stacklevel=2, + category=DeprecationWarning, + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scatterpolar.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scatterpolar.py new file mode 100644 index 0000000000000000000000000000000000000000..f982f73965935198068e0bd4c776272d2fff5939 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scatterpolar.py @@ -0,0 +1,2008 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Scatterpolar(_BaseTraceType): + _parent_path_str = "" + _path_str = "scatterpolar" + _valid_props = { + "cliponaxis", + "connectgaps", + "customdata", + "customdatasrc", + "dr", + "dtheta", + "fill", + "fillcolor", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hoveron", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "marker", + "meta", + "metasrc", + "mode", + "name", + "opacity", + "r", + "r0", + "rsrc", + "selected", + "selectedpoints", + "showlegend", + "stream", + "subplot", + "text", + "textfont", + "textposition", + "textpositionsrc", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "theta", + "theta0", + "thetasrc", + "thetaunit", + "type", + "uid", + "uirevision", + "unselected", + "visible", + } + + @property + def cliponaxis(self): + """ + Determines whether or not markers and text nodes are clipped + about the subplot axes. To show markers and text nodes above + axis lines and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + + The 'cliponaxis' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cliponaxis"] + + @cliponaxis.setter + def cliponaxis(self, val): + self["cliponaxis"] = val + + @property + def connectgaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the provided data arrays are connected. + + The 'connectgaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["connectgaps"] + + @connectgaps.setter + def connectgaps(self, val): + self["connectgaps"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def dr(self): + """ + Sets the r coordinate step. + + The 'dr' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dr"] + + @dr.setter + def dr(self, val): + self["dr"] = val + + @property + def dtheta(self): + """ + Sets the theta coordinate step. By default, the `dtheta` step + equals the subplot's period divided by the length of the `r` + coordinates. + + The 'dtheta' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dtheta"] + + @dtheta.setter + def dtheta(self, val): + self["dtheta"] = val + + @property + def fill(self): + """ + Sets the area to fill with a solid color. Use with `fillcolor` + if not "none". scatterpolar has a subset of the options + available to scatter. "toself" connects the endpoints of the + trace (or each segment of the trace if it has gaps) into a + closed shape. "tonext" fills the space between two traces if + one completely encloses the other (eg consecutive contour + lines), and behaves like "toself" if there is no trace before + it. "tonext" should not be used if one trace does not enclose + the other. + + The 'fill' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'toself', 'tonext'] + + Returns + ------- + Any + """ + return self["fill"] + + @fill.setter + def fill(self, val): + self["fill"] = val + + @property + def fillcolor(self): + """ + Sets the fill color. Defaults to a half-transparent variant of + the line color, marker color, or marker line color, whichever + is available. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['r', 'theta', 'text', 'name'] joined with '+' characters + (e.g. 'r+theta') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolar.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.scatterpolar.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hoveron(self): + """ + Do the hover effects highlight individual points (markers or + line points) or do they highlight filled regions? If the fill + is "toself" or "tonext" and there are no markers or text, then + the default is "fills", otherwise it is "points". + + The 'hoveron' property is a flaglist and may be specified + as a string containing: + - Any combination of ['points', 'fills'] joined with '+' characters + (e.g. 'points+fills') + + Returns + ------- + Any + """ + return self["hoveron"] + + @hoveron.setter + def hoveron(self, val): + self["hoveron"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each (x,y) pair. If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (x,y) coordinates. To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolar.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.scatterpolar.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolar.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.scatterpolar.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolar.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scatterpolar.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def mode(self): + """ + Determines the drawing mode for this scatter trace. If the + provided `mode` includes "text" then the `text` elements appear + at the coordinates. Otherwise, the `text` elements appear on + hover. If there are less than 20 points and the trace is not + stacked then the default is "lines+markers". Otherwise, + "lines". + + The 'mode' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lines', 'markers', 'text'] joined with '+' characters + (e.g. 'lines+markers') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["mode"] + + @mode.setter + def mode(self, val): + self["mode"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def r(self): + """ + Sets the radial coordinates + + The 'r' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["r"] + + @r.setter + def r(self, val): + self["r"] = val + + @property + def r0(self): + """ + Alternate to `r`. Builds a linear space of r coordinates. Use + with `dr` where `r0` is the starting coordinate and `dr` the + step. + + The 'r0' property accepts values of any type + + Returns + ------- + Any + """ + return self["r0"] + + @r0.setter + def r0(self, val): + self["r0"] = val + + @property + def rsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `r`. + + The 'rsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["rsrc"] + + @rsrc.setter + def rsrc(self, val): + self["rsrc"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolar.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.scatterpolar.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolar.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.scatterpolar.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def subplot(self): + """ + Sets a reference between this trace's data coordinates and a + polar subplot. If "polar" (the default value), the data refer + to `layout.polar`. If "polar2", the data refer to + `layout.polar2`, and so on. + + The 'subplot' property is an identifier of a particular + subplot, of type 'polar', that may be specified as: + - the string 'polar' optionally followed by an integer >= 1 + (e.g. 'polar', 'polar1', 'polar2', 'polar3', etc.) + + Returns + ------- + str + """ + return self["subplot"] + + @subplot.setter + def subplot(self, val): + self["subplot"] = val + + @property + def text(self): + """ + Sets text elements associated with each (x,y) pair. If a single + string, the same string appears over all the data points. If an + array of string, the items are mapped in order to the this + trace's (x,y) coordinates. If trace `hoverinfo` contains a + "text" flag and "hovertext" is not set, these elements will be + seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the text font. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolar.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.scatterpolar.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textposition(self): + """ + Sets the positions of the `text` elements with respects to the + (x,y) coordinates. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top left', 'top center', 'top right', 'middle left', + 'middle center', 'middle right', 'bottom left', 'bottom + center', 'bottom right'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textpositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `textposition`. + + The 'textpositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textpositionsrc"] + + @textpositionsrc.setter + def textpositionsrc(self, val): + self["textpositionsrc"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `r`, `theta` and `text`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def theta(self): + """ + Sets the angular coordinates + + The 'theta' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["theta"] + + @theta.setter + def theta(self, val): + self["theta"] = val + + @property + def theta0(self): + """ + Alternate to `theta`. Builds a linear space of theta + coordinates. Use with `dtheta` where `theta0` is the starting + coordinate and `dtheta` the step. + + The 'theta0' property accepts values of any type + + Returns + ------- + Any + """ + return self["theta0"] + + @theta0.setter + def theta0(self, val): + self["theta0"] = val + + @property + def thetasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `theta`. + + The 'thetasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["thetasrc"] + + @thetasrc.setter + def thetasrc(self, val): + self["thetasrc"] = val + + @property + def thetaunit(self): + """ + Sets the unit of input "theta" values. Has an effect only when + on "linear" angular axes. + + The 'thetaunit' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['radians', 'degrees', 'gradians'] + + Returns + ------- + Any + """ + return self["thetaunit"] + + @thetaunit.setter + def thetaunit(self, val): + self["thetaunit"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolar.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.scatterpolar.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dr + Sets the r coordinate step. + dtheta + Sets the theta coordinate step. By default, the + `dtheta` step equals the subplot's period divided by + the length of the `r` coordinates. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scatterpolar has a subset of + the options available to scatter. "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatterpolar.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatterpolar.Legendgroupti + tle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatterpolar.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scatterpolar.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + r + Sets the radial coordinates + r0 + Alternate to `r`. Builds a linear space of r + coordinates. Use with `dr` where `r0` is the starting + coordinate and `dr` the step. + rsrc + Sets the source reference on Chart Studio Cloud for + `r`. + selected + :class:`plotly.graph_objects.scatterpolar.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatterpolar.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a polar subplot. If "polar" (the default value), + the data refer to `layout.polar`. If "polar2", the data + refer to `layout.polar2`, and so on. + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `r`, `theta` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + theta + Sets the angular coordinates + theta0 + Alternate to `theta`. Builds a linear space of theta + coordinates. Use with `dtheta` where `theta0` is the + starting coordinate and `dtheta` the step. + thetasrc + Sets the source reference on Chart Studio Cloud for + `theta`. + thetaunit + Sets the unit of input "theta" values. Has an effect + only when on "linear" angular axes. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatterpolar.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + cliponaxis=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + dr=None, + dtheta=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + r=None, + r0=None, + rsrc=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + theta=None, + theta0=None, + thetasrc=None, + thetaunit=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + **kwargs, + ): + """ + Construct a new Scatterpolar object + + The scatterpolar trace type encompasses line charts, scatter + charts, text charts, and bubble charts in polar coordinates. + The data visualized as scatter point or lines is set in `r` + (radial) and `theta` (angular) coordinates Text (appearing + either on the chart or on hover only) is via `text`. Bubble + charts are achieved by setting `marker.size` and/or + `marker.color` to numerical arrays. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Scatterpolar` + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dr + Sets the r coordinate step. + dtheta + Sets the theta coordinate step. By default, the + `dtheta` step equals the subplot's period divided by + the length of the `r` coordinates. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scatterpolar has a subset of + the options available to scatter. "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatterpolar.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatterpolar.Legendgroupti + tle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatterpolar.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scatterpolar.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + r + Sets the radial coordinates + r0 + Alternate to `r`. Builds a linear space of r + coordinates. Use with `dr` where `r0` is the starting + coordinate and `dr` the step. + rsrc + Sets the source reference on Chart Studio Cloud for + `r`. + selected + :class:`plotly.graph_objects.scatterpolar.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatterpolar.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a polar subplot. If "polar" (the default value), + the data refer to `layout.polar`. If "polar2", the data + refer to `layout.polar2`, and so on. + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `r`, `theta` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + theta + Sets the angular coordinates + theta0 + Alternate to `theta`. Builds a linear space of theta + coordinates. Use with `dtheta` where `theta0` is the + starting coordinate and `dtheta` the step. + thetasrc + Sets the source reference on Chart Studio Cloud for + `theta`. + thetaunit + Sets the unit of input "theta" values. Has an effect + only when on "linear" angular axes. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatterpolar.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Scatterpolar + """ + super().__init__("scatterpolar") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Scatterpolar +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Scatterpolar`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("cliponaxis", arg, cliponaxis) + self._set_property("connectgaps", arg, connectgaps) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("dr", arg, dr) + self._set_property("dtheta", arg, dtheta) + self._set_property("fill", arg, fill) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hoveron", arg, hoveron) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("mode", arg, mode) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("r", arg, r) + self._set_property("r0", arg, r0) + self._set_property("rsrc", arg, rsrc) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("subplot", arg, subplot) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textposition", arg, textposition) + self._set_property("textpositionsrc", arg, textpositionsrc) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("theta", arg, theta) + self._set_property("theta0", arg, theta0) + self._set_property("thetasrc", arg, thetasrc) + self._set_property("thetaunit", arg, thetaunit) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + + self._props["type"] = "scatterpolar" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scatterpolargl.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scatterpolargl.py new file mode 100644 index 0000000000000000000000000000000000000000..0205d08dbcf0aebc24705253f8ad99e20a23f8ea --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scatterpolargl.py @@ -0,0 +1,1969 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Scatterpolargl(_BaseTraceType): + _parent_path_str = "" + _path_str = "scatterpolargl" + _valid_props = { + "connectgaps", + "customdata", + "customdatasrc", + "dr", + "dtheta", + "fill", + "fillcolor", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "marker", + "meta", + "metasrc", + "mode", + "name", + "opacity", + "r", + "r0", + "rsrc", + "selected", + "selectedpoints", + "showlegend", + "stream", + "subplot", + "text", + "textfont", + "textposition", + "textpositionsrc", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "theta", + "theta0", + "thetasrc", + "thetaunit", + "type", + "uid", + "uirevision", + "unselected", + "visible", + } + + @property + def connectgaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the provided data arrays are connected. + + The 'connectgaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["connectgaps"] + + @connectgaps.setter + def connectgaps(self, val): + self["connectgaps"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def dr(self): + """ + Sets the r coordinate step. + + The 'dr' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dr"] + + @dr.setter + def dr(self, val): + self["dr"] = val + + @property + def dtheta(self): + """ + Sets the theta coordinate step. By default, the `dtheta` step + equals the subplot's period divided by the length of the `r` + coordinates. + + The 'dtheta' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dtheta"] + + @dtheta.setter + def dtheta(self, val): + self["dtheta"] = val + + @property + def fill(self): + """ + Sets the area to fill with a solid color. Defaults to "none" + unless this trace is stacked, then it gets "tonexty" + ("tonextx") if `orientation` is "v" ("h") Use with `fillcolor` + if not "none". "tozerox" and "tozeroy" fill to x=0 and y=0 + respectively. "tonextx" and "tonexty" fill between the + endpoints of this trace and the endpoints of the trace before + it, connecting those endpoints with straight lines (to make a + stacked area graph); if there is no trace before it, they + behave like "tozerox" and "tozeroy". "toself" connects the + endpoints of the trace (or each segment of the trace if it has + gaps) into a closed shape. "tonext" fills the space between two + traces if one completely encloses the other (eg consecutive + contour lines), and behaves like "toself" if there is no trace + before it. "tonext" should not be used if one trace does not + enclose the other. Traces in a `stackgroup` will only fill to + (or be filled to) other traces in the same group. With multiple + `stackgroup`s or some traces stacked and some not, if fill- + linked traces are not already consecutive, the later ones will + be pushed down in the drawing order. + + The 'fill' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'tozeroy', 'tozerox', 'tonexty', 'tonextx', + 'toself', 'tonext'] + + Returns + ------- + Any + """ + return self["fill"] + + @fill.setter + def fill(self, val): + self["fill"] = val + + @property + def fillcolor(self): + """ + Sets the fill color. Defaults to a half-transparent variant of + the line color, marker color, or marker line color, whichever + is available. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['r', 'theta', 'text', 'name'] joined with '+' characters + (e.g. 'r+theta') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolargl.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.scatterpolargl.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each (x,y) pair. If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (x,y) coordinates. To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolargl.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.scatterpolargl.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolargl.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.scatterpolargl.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolargl.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scatterpolargl.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def mode(self): + """ + Determines the drawing mode for this scatter trace. If the + provided `mode` includes "text" then the `text` elements appear + at the coordinates. Otherwise, the `text` elements appear on + hover. If there are less than 20 points and the trace is not + stacked then the default is "lines+markers". Otherwise, + "lines". + + The 'mode' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lines', 'markers', 'text'] joined with '+' characters + (e.g. 'lines+markers') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["mode"] + + @mode.setter + def mode(self, val): + self["mode"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def r(self): + """ + Sets the radial coordinates + + The 'r' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["r"] + + @r.setter + def r(self, val): + self["r"] = val + + @property + def r0(self): + """ + Alternate to `r`. Builds a linear space of r coordinates. Use + with `dr` where `r0` is the starting coordinate and `dr` the + step. + + The 'r0' property accepts values of any type + + Returns + ------- + Any + """ + return self["r0"] + + @r0.setter + def r0(self, val): + self["r0"] = val + + @property + def rsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `r`. + + The 'rsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["rsrc"] + + @rsrc.setter + def rsrc(self, val): + self["rsrc"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolargl.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.scatterpolargl.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolargl.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.scatterpolargl.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def subplot(self): + """ + Sets a reference between this trace's data coordinates and a + polar subplot. If "polar" (the default value), the data refer + to `layout.polar`. If "polar2", the data refer to + `layout.polar2`, and so on. + + The 'subplot' property is an identifier of a particular + subplot, of type 'polar', that may be specified as: + - the string 'polar' optionally followed by an integer >= 1 + (e.g. 'polar', 'polar1', 'polar2', 'polar3', etc.) + + Returns + ------- + str + """ + return self["subplot"] + + @subplot.setter + def subplot(self, val): + self["subplot"] = val + + @property + def text(self): + """ + Sets text elements associated with each (x,y) pair. If a single + string, the same string appears over all the data points. If an + array of string, the items are mapped in order to the this + trace's (x,y) coordinates. If trace `hoverinfo` contains a + "text" flag and "hovertext" is not set, these elements will be + seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the text font. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolargl.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.scatterpolargl.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textposition(self): + """ + Sets the positions of the `text` elements with respects to the + (x,y) coordinates. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top left', 'top center', 'top right', 'middle left', + 'middle center', 'middle right', 'bottom left', 'bottom + center', 'bottom right'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textpositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `textposition`. + + The 'textpositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textpositionsrc"] + + @textpositionsrc.setter + def textpositionsrc(self, val): + self["textpositionsrc"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `r`, `theta` and `text`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def theta(self): + """ + Sets the angular coordinates + + The 'theta' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["theta"] + + @theta.setter + def theta(self, val): + self["theta"] = val + + @property + def theta0(self): + """ + Alternate to `theta`. Builds a linear space of theta + coordinates. Use with `dtheta` where `theta0` is the starting + coordinate and `dtheta` the step. + + The 'theta0' property accepts values of any type + + Returns + ------- + Any + """ + return self["theta0"] + + @theta0.setter + def theta0(self, val): + self["theta0"] = val + + @property + def thetasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `theta`. + + The 'thetasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["thetasrc"] + + @thetasrc.setter + def thetasrc(self, val): + self["thetasrc"] = val + + @property + def thetaunit(self): + """ + Sets the unit of input "theta" values. Has an effect only when + on "linear" angular axes. + + The 'thetaunit' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['radians', 'degrees', 'gradians'] + + Returns + ------- + Any + """ + return self["thetaunit"] + + @thetaunit.setter + def thetaunit(self, val): + self["thetaunit"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterpolargl.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.scatterpolargl.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dr + Sets the r coordinate step. + dtheta + Sets the theta coordinate step. By default, the + `dtheta` step equals the subplot's period divided by + the length of the `r` coordinates. + fill + Sets the area to fill with a solid color. Defaults to + "none" unless this trace is stacked, then it gets + "tonexty" ("tonextx") if `orientation` is "v" ("h") Use + with `fillcolor` if not "none". "tozerox" and "tozeroy" + fill to x=0 and y=0 respectively. "tonextx" and + "tonexty" fill between the endpoints of this trace and + the endpoints of the trace before it, connecting those + endpoints with straight lines (to make a stacked area + graph); if there is no trace before it, they behave + like "tozerox" and "tozeroy". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. Traces in a `stackgroup` will only fill to (or + be filled to) other traces in the same group. With + multiple `stackgroup`s or some traces stacked and some + not, if fill-linked traces are not already consecutive, + the later ones will be pushed down in the drawing + order. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatterpolargl.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatterpolargl.Legendgroup + title` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatterpolargl.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scatterpolargl.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + r + Sets the radial coordinates + r0 + Alternate to `r`. Builds a linear space of r + coordinates. Use with `dr` where `r0` is the starting + coordinate and `dr` the step. + rsrc + Sets the source reference on Chart Studio Cloud for + `r`. + selected + :class:`plotly.graph_objects.scatterpolargl.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatterpolargl.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a polar subplot. If "polar" (the default value), + the data refer to `layout.polar`. If "polar2", the data + refer to `layout.polar2`, and so on. + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `r`, `theta` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + theta + Sets the angular coordinates + theta0 + Alternate to `theta`. Builds a linear space of theta + coordinates. Use with `dtheta` where `theta0` is the + starting coordinate and `dtheta` the step. + thetasrc + Sets the source reference on Chart Studio Cloud for + `theta`. + thetaunit + Sets the unit of input "theta" values. Has an effect + only when on "linear" angular axes. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatterpolargl.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + dr=None, + dtheta=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + r=None, + r0=None, + rsrc=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + theta=None, + theta0=None, + thetasrc=None, + thetaunit=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + **kwargs, + ): + """ + Construct a new Scatterpolargl object + + The scatterpolargl trace type encompasses line charts, scatter + charts, and bubble charts in polar coordinates using the WebGL + plotting engine. The data visualized as scatter point or lines + is set in `r` (radial) and `theta` (angular) coordinates Bubble + charts are achieved by setting `marker.size` and/or + `marker.color` to numerical arrays. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.Scatterpolargl` + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + dr + Sets the r coordinate step. + dtheta + Sets the theta coordinate step. By default, the + `dtheta` step equals the subplot's period divided by + the length of the `r` coordinates. + fill + Sets the area to fill with a solid color. Defaults to + "none" unless this trace is stacked, then it gets + "tonexty" ("tonextx") if `orientation` is "v" ("h") Use + with `fillcolor` if not "none". "tozerox" and "tozeroy" + fill to x=0 and y=0 respectively. "tonextx" and + "tonexty" fill between the endpoints of this trace and + the endpoints of the trace before it, connecting those + endpoints with straight lines (to make a stacked area + graph); if there is no trace before it, they behave + like "tozerox" and "tozeroy". "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. Traces in a `stackgroup` will only fill to (or + be filled to) other traces in the same group. With + multiple `stackgroup`s or some traces stacked and some + not, if fill-linked traces are not already consecutive, + the later ones will be pushed down in the drawing + order. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatterpolargl.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatterpolargl.Legendgroup + title` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatterpolargl.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scatterpolargl.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + r + Sets the radial coordinates + r0 + Alternate to `r`. Builds a linear space of r + coordinates. Use with `dr` where `r0` is the starting + coordinate and `dr` the step. + rsrc + Sets the source reference on Chart Studio Cloud for + `r`. + selected + :class:`plotly.graph_objects.scatterpolargl.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatterpolargl.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a polar subplot. If "polar" (the default value), + the data refer to `layout.polar`. If "polar2", the data + refer to `layout.polar2`, and so on. + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `r`, `theta` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + theta + Sets the angular coordinates + theta0 + Alternate to `theta`. Builds a linear space of theta + coordinates. Use with `dtheta` where `theta0` is the + starting coordinate and `dtheta` the step. + thetasrc + Sets the source reference on Chart Studio Cloud for + `theta`. + thetaunit + Sets the unit of input "theta" values. Has an effect + only when on "linear" angular axes. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatterpolargl.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Scatterpolargl + """ + super().__init__("scatterpolargl") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Scatterpolargl +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Scatterpolargl`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("connectgaps", arg, connectgaps) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("dr", arg, dr) + self._set_property("dtheta", arg, dtheta) + self._set_property("fill", arg, fill) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("mode", arg, mode) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("r", arg, r) + self._set_property("r0", arg, r0) + self._set_property("rsrc", arg, rsrc) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("subplot", arg, subplot) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textposition", arg, textposition) + self._set_property("textpositionsrc", arg, textpositionsrc) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("theta", arg, theta) + self._set_property("theta0", arg, theta0) + self._set_property("thetasrc", arg, thetasrc) + self._set_property("thetaunit", arg, thetaunit) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + + self._props["type"] = "scatterpolargl" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattersmith.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattersmith.py new file mode 100644 index 0000000000000000000000000000000000000000..7d9fa8e76a1353369a35ac10ce5084100aa328bf --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scattersmith.py @@ -0,0 +1,1874 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Scattersmith(_BaseTraceType): + _parent_path_str = "" + _path_str = "scattersmith" + _valid_props = { + "cliponaxis", + "connectgaps", + "customdata", + "customdatasrc", + "fill", + "fillcolor", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hoveron", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "imag", + "imagsrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "marker", + "meta", + "metasrc", + "mode", + "name", + "opacity", + "real", + "realsrc", + "selected", + "selectedpoints", + "showlegend", + "stream", + "subplot", + "text", + "textfont", + "textposition", + "textpositionsrc", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "type", + "uid", + "uirevision", + "unselected", + "visible", + } + + @property + def cliponaxis(self): + """ + Determines whether or not markers and text nodes are clipped + about the subplot axes. To show markers and text nodes above + axis lines and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + + The 'cliponaxis' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cliponaxis"] + + @cliponaxis.setter + def cliponaxis(self, val): + self["cliponaxis"] = val + + @property + def connectgaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the provided data arrays are connected. + + The 'connectgaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["connectgaps"] + + @connectgaps.setter + def connectgaps(self, val): + self["connectgaps"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def fill(self): + """ + Sets the area to fill with a solid color. Use with `fillcolor` + if not "none". scattersmith has a subset of the options + available to scatter. "toself" connects the endpoints of the + trace (or each segment of the trace if it has gaps) into a + closed shape. "tonext" fills the space between two traces if + one completely encloses the other (eg consecutive contour + lines), and behaves like "toself" if there is no trace before + it. "tonext" should not be used if one trace does not enclose + the other. + + The 'fill' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'toself', 'tonext'] + + Returns + ------- + Any + """ + return self["fill"] + + @fill.setter + def fill(self, val): + self["fill"] = val + + @property + def fillcolor(self): + """ + Sets the fill color. Defaults to a half-transparent variant of + the line color, marker color, or marker line color, whichever + is available. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['real', 'imag', 'text', 'name'] joined with '+' characters + (e.g. 'real+imag') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattersmith.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.scattersmith.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hoveron(self): + """ + Do the hover effects highlight individual points (markers or + line points) or do they highlight filled regions? If the fill + is "toself" or "tonext" and there are no markers or text, then + the default is "fills", otherwise it is "points". + + The 'hoveron' property is a flaglist and may be specified + as a string containing: + - Any combination of ['points', 'fills'] joined with '+' characters + (e.g. 'points+fills') + + Returns + ------- + Any + """ + return self["hoveron"] + + @hoveron.setter + def hoveron(self, val): + self["hoveron"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each (x,y) pair. If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (x,y) coordinates. To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def imag(self): + """ + Sets the imaginary component of the data, in units of + normalized impedance such that real=1, imag=0 is the center of + the chart. + + The 'imag' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["imag"] + + @imag.setter + def imag(self, val): + self["imag"] = val + + @property + def imagsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `imag`. + + The 'imagsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["imagsrc"] + + @imagsrc.setter + def imagsrc(self, val): + self["imagsrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattersmith.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.scattersmith.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattersmith.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.scattersmith.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattersmith.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scattersmith.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def mode(self): + """ + Determines the drawing mode for this scatter trace. If the + provided `mode` includes "text" then the `text` elements appear + at the coordinates. Otherwise, the `text` elements appear on + hover. If there are less than 20 points and the trace is not + stacked then the default is "lines+markers". Otherwise, + "lines". + + The 'mode' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lines', 'markers', 'text'] joined with '+' characters + (e.g. 'lines+markers') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["mode"] + + @mode.setter + def mode(self, val): + self["mode"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def real(self): + """ + Sets the real component of the data, in units of normalized + impedance such that real=1, imag=0 is the center of the chart. + + The 'real' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["real"] + + @real.setter + def real(self, val): + self["real"] = val + + @property + def realsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `real`. + + The 'realsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["realsrc"] + + @realsrc.setter + def realsrc(self, val): + self["realsrc"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattersmith.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.scattersmith.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattersmith.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.scattersmith.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def subplot(self): + """ + Sets a reference between this trace's data coordinates and a + smith subplot. If "smith" (the default value), the data refer + to `layout.smith`. If "smith2", the data refer to + `layout.smith2`, and so on. + + The 'subplot' property is an identifier of a particular + subplot, of type 'smith', that may be specified as: + - the string 'smith' optionally followed by an integer >= 1 + (e.g. 'smith', 'smith1', 'smith2', 'smith3', etc.) + + Returns + ------- + str + """ + return self["subplot"] + + @subplot.setter + def subplot(self, val): + self["subplot"] = val + + @property + def text(self): + """ + Sets text elements associated with each (x,y) pair. If a single + string, the same string appears over all the data points. If an + array of string, the items are mapped in order to the this + trace's (x,y) coordinates. If trace `hoverinfo` contains a + "text" flag and "hovertext" is not set, these elements will be + seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the text font. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattersmith.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.scattersmith.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textposition(self): + """ + Sets the positions of the `text` elements with respects to the + (x,y) coordinates. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top left', 'top center', 'top right', 'middle left', + 'middle center', 'middle right', 'bottom left', 'bottom + center', 'bottom right'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textpositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `textposition`. + + The 'textpositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textpositionsrc"] + + @textpositionsrc.setter + def textpositionsrc(self, val): + self["textpositionsrc"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `real`, `imag` and `text`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattersmith.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.scattersmith.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scattersmith has a subset of + the options available to scatter. "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattersmith.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + imag + Sets the imaginary component of the data, in units of + normalized impedance such that real=1, imag=0 is the + center of the chart. + imagsrc + Sets the source reference on Chart Studio Cloud for + `imag`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattersmith.Legendgroupti + tle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattersmith.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scattersmith.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + real + Sets the real component of the data, in units of + normalized impedance such that real=1, imag=0 is the + center of the chart. + realsrc + Sets the source reference on Chart Studio Cloud for + `real`. + selected + :class:`plotly.graph_objects.scattersmith.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattersmith.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a smith subplot. If "smith" (the default value), + the data refer to `layout.smith`. If "smith2", the data + refer to `layout.smith2`, and so on. + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `real`, `imag` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattersmith.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + cliponaxis=None, + connectgaps=None, + customdata=None, + customdatasrc=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + imag=None, + imagsrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + real=None, + realsrc=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + **kwargs, + ): + """ + Construct a new Scattersmith object + + The scattersmith trace type encompasses line charts, scatter + charts, text charts, and bubble charts in smith coordinates. + The data visualized as scatter point or lines is set in `real` + and `imag` (imaginary) coordinates Text (appearing either on + the chart or on hover only) is via `text`. Bubble charts are + achieved by setting `marker.size` and/or `marker.color` to + numerical arrays. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Scattersmith` + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scattersmith has a subset of + the options available to scatter. "toself" connects the + endpoints of the trace (or each segment of the trace if + it has gaps) into a closed shape. "tonext" fills the + space between two traces if one completely encloses the + other (eg consecutive contour lines), and behaves like + "toself" if there is no trace before it. "tonext" + should not be used if one trace does not enclose the + other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scattersmith.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + imag + Sets the imaginary component of the data, in units of + normalized impedance such that real=1, imag=0 is the + center of the chart. + imagsrc + Sets the source reference on Chart Studio Cloud for + `imag`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scattersmith.Legendgroupti + tle` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scattersmith.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scattersmith.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + real + Sets the real component of the data, in units of + normalized impedance such that real=1, imag=0 is the + center of the chart. + realsrc + Sets the source reference on Chart Studio Cloud for + `real`. + selected + :class:`plotly.graph_objects.scattersmith.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scattersmith.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a smith subplot. If "smith" (the default value), + the data refer to `layout.smith`. If "smith2", the data + refer to `layout.smith2`, and so on. + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `real`, `imag` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scattersmith.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Scattersmith + """ + super().__init__("scattersmith") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Scattersmith +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Scattersmith`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("cliponaxis", arg, cliponaxis) + self._set_property("connectgaps", arg, connectgaps) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("fill", arg, fill) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hoveron", arg, hoveron) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("imag", arg, imag) + self._set_property("imagsrc", arg, imagsrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("mode", arg, mode) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("real", arg, real) + self._set_property("realsrc", arg, realsrc) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("subplot", arg, subplot) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textposition", arg, textposition) + self._set_property("textpositionsrc", arg, textpositionsrc) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + + self._props["type"] = "scattersmith" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scatterternary.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scatterternary.py new file mode 100644 index 0000000000000000000000000000000000000000..2e80db08384619e8c4081973456ee7b444159e83 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_scatterternary.py @@ -0,0 +1,1984 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Scatterternary(_BaseTraceType): + _parent_path_str = "" + _path_str = "scatterternary" + _valid_props = { + "a", + "asrc", + "b", + "bsrc", + "c", + "cliponaxis", + "connectgaps", + "csrc", + "customdata", + "customdatasrc", + "fill", + "fillcolor", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hoveron", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "marker", + "meta", + "metasrc", + "mode", + "name", + "opacity", + "selected", + "selectedpoints", + "showlegend", + "stream", + "subplot", + "sum", + "text", + "textfont", + "textposition", + "textpositionsrc", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "type", + "uid", + "uirevision", + "unselected", + "visible", + } + + @property + def a(self): + """ + Sets the quantity of component `a` in each data point. If `a`, + `b`, and `c` are all provided, they need not be normalized, + only the relative values matter. If only two arrays are + provided they must be normalized to match `ternary.sum`. + + The 'a' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["a"] + + @a.setter + def a(self, val): + self["a"] = val + + @property + def asrc(self): + """ + Sets the source reference on Chart Studio Cloud for `a`. + + The 'asrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["asrc"] + + @asrc.setter + def asrc(self, val): + self["asrc"] = val + + @property + def b(self): + """ + Sets the quantity of component `a` in each data point. If `a`, + `b`, and `c` are all provided, they need not be normalized, + only the relative values matter. If only two arrays are + provided they must be normalized to match `ternary.sum`. + + The 'b' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["b"] + + @b.setter + def b(self, val): + self["b"] = val + + @property + def bsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `b`. + + The 'bsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bsrc"] + + @bsrc.setter + def bsrc(self, val): + self["bsrc"] = val + + @property + def c(self): + """ + Sets the quantity of component `a` in each data point. If `a`, + `b`, and `c` are all provided, they need not be normalized, + only the relative values matter. If only two arrays are + provided they must be normalized to match `ternary.sum`. + + The 'c' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["c"] + + @c.setter + def c(self, val): + self["c"] = val + + @property + def cliponaxis(self): + """ + Determines whether or not markers and text nodes are clipped + about the subplot axes. To show markers and text nodes above + axis lines and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + + The 'cliponaxis' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cliponaxis"] + + @cliponaxis.setter + def cliponaxis(self, val): + self["cliponaxis"] = val + + @property + def connectgaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the provided data arrays are connected. + + The 'connectgaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["connectgaps"] + + @connectgaps.setter + def connectgaps(self, val): + self["connectgaps"] = val + + @property + def csrc(self): + """ + Sets the source reference on Chart Studio Cloud for `c`. + + The 'csrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["csrc"] + + @csrc.setter + def csrc(self, val): + self["csrc"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def fill(self): + """ + Sets the area to fill with a solid color. Use with `fillcolor` + if not "none". scatterternary has a subset of the options + available to scatter. "toself" connects the endpoints of the + trace (or each segment of the trace if it has gaps) into a + closed shape. "tonext" fills the space between two traces if + one completely encloses the other (eg consecutive contour + lines), and behaves like "toself" if there is no trace before + it. "tonext" should not be used if one trace does not enclose + the other. + + The 'fill' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'toself', 'tonext'] + + Returns + ------- + Any + """ + return self["fill"] + + @fill.setter + def fill(self, val): + self["fill"] = val + + @property + def fillcolor(self): + """ + Sets the fill color. Defaults to a half-transparent variant of + the line color, marker color, or marker line color, whichever + is available. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['a', 'b', 'c', 'text', 'name'] joined with '+' characters + (e.g. 'a+b') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.scatterternary.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hoveron(self): + """ + Do the hover effects highlight individual points (markers or + line points) or do they highlight filled regions? If the fill + is "toself" or "tonext" and there are no markers or text, then + the default is "fills", otherwise it is "points". + + The 'hoveron' property is a flaglist and may be specified + as a string containing: + - Any combination of ['points', 'fills'] joined with '+' characters + (e.g. 'points+fills') + + Returns + ------- + Any + """ + return self["hoveron"] + + @hoveron.setter + def hoveron(self, val): + self["hoveron"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each (a,b,c) point. If + a single string, the same string appears over all the data + points. If an array of strings, the items are mapped in order + to the the data points in (a,b,c). To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.scatterternary.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.scatterternary.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scatterternary.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def mode(self): + """ + Determines the drawing mode for this scatter trace. If the + provided `mode` includes "text" then the `text` elements appear + at the coordinates. Otherwise, the `text` elements appear on + hover. If there are less than 20 points and the trace is not + stacked then the default is "lines+markers". Otherwise, + "lines". + + The 'mode' property is a flaglist and may be specified + as a string containing: + - Any combination of ['lines', 'markers', 'text'] joined with '+' characters + (e.g. 'lines+markers') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["mode"] + + @mode.setter + def mode(self, val): + self["mode"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.scatterternary.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.scatterternary.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def subplot(self): + """ + Sets a reference between this trace's data coordinates and a + ternary subplot. If "ternary" (the default value), the data + refer to `layout.ternary`. If "ternary2", the data refer to + `layout.ternary2`, and so on. + + The 'subplot' property is an identifier of a particular + subplot, of type 'ternary', that may be specified as: + - the string 'ternary' optionally followed by an integer >= 1 + (e.g. 'ternary', 'ternary1', 'ternary2', 'ternary3', etc.) + + Returns + ------- + str + """ + return self["subplot"] + + @subplot.setter + def subplot(self, val): + self["subplot"] = val + + @property + def sum(self): + """ + The number each triplet should sum to, if only two of `a`, `b`, + and `c` are provided. This overrides `ternary.sum` to + normalize this specific trace, but does not affect the values + displayed on the axes. 0 (or missing) means to use + ternary.sum + + The 'sum' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["sum"] + + @sum.setter + def sum(self, val): + self["sum"] = val + + @property + def text(self): + """ + Sets text elements associated with each (a,b,c) point. If a + single string, the same string appears over all the data + points. If an array of strings, the items are mapped in order + to the the data points in (a,b,c). If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, these + elements will be seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the text font. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.scatterternary.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textposition(self): + """ + Sets the positions of the `text` elements with respects to the + (x,y) coordinates. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top left', 'top center', 'top right', 'middle left', + 'middle center', 'middle right', 'bottom left', 'bottom + center', 'bottom right'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textpositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `textposition`. + + The 'textpositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textpositionsrc"] + + @textpositionsrc.setter + def textpositionsrc(self, val): + self["textpositionsrc"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `a`, `b`, `c` and `text`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.scatterternary.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + a + Sets the quantity of component `a` in each data point. + If `a`, `b`, and `c` are all provided, they need not be + normalized, only the relative values matter. If only + two arrays are provided they must be normalized to + match `ternary.sum`. + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + b + Sets the quantity of component `a` in each data point. + If `a`, `b`, and `c` are all provided, they need not be + normalized, only the relative values matter. If only + two arrays are provided they must be normalized to + match `ternary.sum`. + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + c + Sets the quantity of component `a` in each data point. + If `a`, `b`, and `c` are all provided, they need not be + normalized, only the relative values matter. If only + two arrays are provided they must be normalized to + match `ternary.sum`. + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + csrc + Sets the source reference on Chart Studio Cloud for + `c`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scatterternary has a subset + of the options available to scatter. "toself" connects + the endpoints of the trace (or each segment of the + trace if it has gaps) into a closed shape. "tonext" + fills the space between two traces if one completely + encloses the other (eg consecutive contour lines), and + behaves like "toself" if there is no trace before it. + "tonext" should not be used if one trace does not + enclose the other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatterternary.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (a,b,c) + point. If a single string, the same string appears over + all the data points. If an array of strings, the items + are mapped in order to the the data points in (a,b,c). + To be seen, trace `hoverinfo` must contain a "text" + flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatterternary.Legendgroup + title` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatterternary.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scatterternary.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scatterternary.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatterternary.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a ternary subplot. If "ternary" (the default + value), the data refer to `layout.ternary`. If + "ternary2", the data refer to `layout.ternary2`, and so + on. + sum + The number each triplet should sum to, if only two of + `a`, `b`, and `c` are provided. This overrides + `ternary.sum` to normalize this specific trace, but + does not affect the values displayed on the axes. 0 (or + missing) means to use ternary.sum + text + Sets text elements associated with each (a,b,c) point. + If a single string, the same string appears over all + the data points. If an array of strings, the items are + mapped in order to the the data points in (a,b,c). If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `a`, `b`, `c` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatterternary.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + a=None, + asrc=None, + b=None, + bsrc=None, + c=None, + cliponaxis=None, + connectgaps=None, + csrc=None, + customdata=None, + customdatasrc=None, + fill=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meta=None, + metasrc=None, + mode=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + stream=None, + subplot=None, + sum=None, + text=None, + textfont=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + **kwargs, + ): + """ + Construct a new Scatterternary object + + Provides similar functionality to the "scatter" type but on a + ternary phase diagram. The data is provided by at least two + arrays out of `a`, `b`, `c` triplets. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.Scatterternary` + a + Sets the quantity of component `a` in each data point. + If `a`, `b`, and `c` are all provided, they need not be + normalized, only the relative values matter. If only + two arrays are provided they must be normalized to + match `ternary.sum`. + asrc + Sets the source reference on Chart Studio Cloud for + `a`. + b + Sets the quantity of component `a` in each data point. + If `a`, `b`, and `c` are all provided, they need not be + normalized, only the relative values matter. If only + two arrays are provided they must be normalized to + match `ternary.sum`. + bsrc + Sets the source reference on Chart Studio Cloud for + `b`. + c + Sets the quantity of component `a` in each data point. + If `a`, `b`, and `c` are all provided, they need not be + normalized, only the relative values matter. If only + two arrays are provided they must be normalized to + match `ternary.sum`. + cliponaxis + Determines whether or not markers and text nodes are + clipped about the subplot axes. To show markers and + text nodes above axis lines and tick labels, make sure + to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the provided data arrays are connected. + csrc + Sets the source reference on Chart Studio Cloud for + `c`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fill + Sets the area to fill with a solid color. Use with + `fillcolor` if not "none". scatterternary has a subset + of the options available to scatter. "toself" connects + the endpoints of the trace (or each segment of the + trace if it has gaps) into a closed shape. "tonext" + fills the space between two traces if one completely + encloses the other (eg consecutive contour lines), and + behaves like "toself" if there is no trace before it. + "tonext" should not be used if one trace does not + enclose the other. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.scatterternary.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual points + (markers or line points) or do they highlight filled + regions? If the fill is "toself" or "tonext" and there + are no markers or text, then the default is "fills", + otherwise it is "points". + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (a,b,c) + point. If a single string, the same string appears over + all the data points. If an array of strings, the items + are mapped in order to the the data points in (a,b,c). + To be seen, trace `hoverinfo` must contain a "text" + flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.scatterternary.Legendgroup + title` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.scatterternary.Line` + instance or dict with compatible properties + marker + :class:`plotly.graph_objects.scatterternary.Marker` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + mode + Determines the drawing mode for this scatter trace. If + the provided `mode` includes "text" then the `text` + elements appear at the coordinates. Otherwise, the + `text` elements appear on hover. If there are less than + 20 points and the trace is not stacked then the default + is "lines+markers". Otherwise, "lines". + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.scatterternary.Selected` + instance or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.scatterternary.Stream` + instance or dict with compatible properties + subplot + Sets a reference between this trace's data coordinates + and a ternary subplot. If "ternary" (the default + value), the data refer to `layout.ternary`. If + "ternary2", the data refer to `layout.ternary2`, and so + on. + sum + The number each triplet should sum to, if only two of + `a`, `b`, and `c` are provided. This overrides + `ternary.sum` to normalize this specific trace, but + does not affect the values displayed on the axes. 0 (or + missing) means to use ternary.sum + text + Sets text elements associated with each (a,b,c) point. + If a single string, the same string appears over all + the data points. If an array of strings, the items are + mapped in order to the the data points in (a,b,c). If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textfont + Sets the text font. + textposition + Sets the positions of the `text` elements with respects + to the (x,y) coordinates. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `a`, `b`, `c` and `text`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.scatterternary.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Scatterternary + """ + super().__init__("scatterternary") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Scatterternary +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Scatterternary`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("a", arg, a) + self._set_property("asrc", arg, asrc) + self._set_property("b", arg, b) + self._set_property("bsrc", arg, bsrc) + self._set_property("c", arg, c) + self._set_property("cliponaxis", arg, cliponaxis) + self._set_property("connectgaps", arg, connectgaps) + self._set_property("csrc", arg, csrc) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("fill", arg, fill) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hoveron", arg, hoveron) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("mode", arg, mode) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("subplot", arg, subplot) + self._set_property("sum", arg, sum) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textposition", arg, textposition) + self._set_property("textpositionsrc", arg, textpositionsrc) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + + self._props["type"] = "scatterternary" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_splom.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_splom.py new file mode 100644 index 0000000000000000000000000000000000000000..c80229a70446a866eefea5ee5a7b4b83c6c05f43 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_splom.py @@ -0,0 +1,1569 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Splom(_BaseTraceType): + _parent_path_str = "" + _path_str = "splom" + _valid_props = { + "customdata", + "customdatasrc", + "diagonal", + "dimensiondefaults", + "dimensions", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "marker", + "meta", + "metasrc", + "name", + "opacity", + "selected", + "selectedpoints", + "showlegend", + "showlowerhalf", + "showupperhalf", + "stream", + "text", + "textsrc", + "type", + "uid", + "uirevision", + "unselected", + "visible", + "xaxes", + "xhoverformat", + "yaxes", + "yhoverformat", + } + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def diagonal(self): + """ + The 'diagonal' property is an instance of Diagonal + that may be specified as: + - An instance of :class:`plotly.graph_objs.splom.Diagonal` + - A dict of string/value properties that will be passed + to the Diagonal constructor + + Returns + ------- + plotly.graph_objs.splom.Diagonal + """ + return self["diagonal"] + + @diagonal.setter + def diagonal(self, val): + self["diagonal"] = val + + @property + def dimensions(self): + """ + The 'dimensions' property is a tuple of instances of + Dimension that may be specified as: + - A list or tuple of instances of plotly.graph_objs.splom.Dimension + - A list or tuple of dicts of string/value properties that + will be passed to the Dimension constructor + + Returns + ------- + tuple[plotly.graph_objs.splom.Dimension] + """ + return self["dimensions"] + + @dimensions.setter + def dimensions(self, val): + self["dimensions"] = val + + @property + def dimensiondefaults(self): + """ + When used in a template (as + layout.template.data.splom.dimensiondefaults), sets the default + property values to use for elements of splom.dimensions + + The 'dimensiondefaults' property is an instance of Dimension + that may be specified as: + - An instance of :class:`plotly.graph_objs.splom.Dimension` + - A dict of string/value properties that will be passed + to the Dimension constructor + + Returns + ------- + plotly.graph_objs.splom.Dimension + """ + return self["dimensiondefaults"] + + @dimensiondefaults.setter + def dimensiondefaults(self, val): + self["dimensiondefaults"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.splom.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.splom.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.splom.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.splom.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.splom.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.splom.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.splom.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.splom.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showlowerhalf(self): + """ + Determines whether or not subplots on the lower half from the + diagonal are displayed. + + The 'showlowerhalf' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlowerhalf"] + + @showlowerhalf.setter + def showlowerhalf(self, val): + self["showlowerhalf"] = val + + @property + def showupperhalf(self): + """ + Determines whether or not subplots on the upper half from the + diagonal are displayed. + + The 'showupperhalf' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showupperhalf"] + + @showupperhalf.setter + def showupperhalf(self, val): + self["showupperhalf"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.splom.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.splom.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets text elements associated with each (x,y) pair to appear on + hover. If a single string, the same string appears over all the + data points. If an array of string, the items are mapped in + order to the this trace's (x,y) coordinates. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.splom.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.splom.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def xaxes(self): + """ + Sets the list of x axes corresponding to dimensions of this + splom trace. By default, a splom will match the first N xaxes + where N is the number of input dimensions. Note that, in case + where `diagonal.visible` is false and `showupperhalf` or + `showlowerhalf` is false, this splom trace will generate one + less x-axis and one less y-axis. + + The 'xaxes' property is an info array that may be specified as: + * a list of elements where: + The 'xaxes[i]' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + list + """ + return self["xaxes"] + + @xaxes.setter + def xaxes(self, val): + self["xaxes"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def yaxes(self): + """ + Sets the list of y axes corresponding to dimensions of this + splom trace. By default, a splom will match the first N yaxes + where N is the number of input dimensions. Note that, in case + where `diagonal.visible` is false and `showupperhalf` or + `showlowerhalf` is false, this splom trace will generate one + less x-axis and one less y-axis. + + The 'yaxes' property is an info array that may be specified as: + * a list of elements where: + The 'yaxes[i]' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + list + """ + return self["yaxes"] + + @yaxes.setter + def yaxes(self, val): + self["yaxes"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + diagonal + :class:`plotly.graph_objects.splom.Diagonal` instance + or dict with compatible properties + dimensions + A tuple of + :class:`plotly.graph_objects.splom.Dimension` instances + or dicts with compatible properties + dimensiondefaults + When used in a template (as + layout.template.data.splom.dimensiondefaults), sets the + default property values to use for elements of + splom.dimensions + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.splom.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.splom.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.splom.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.splom.Selected` instance + or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showlowerhalf + Determines whether or not subplots on the lower half + from the diagonal are displayed. + showupperhalf + Determines whether or not subplots on the upper half + from the diagonal are displayed. + stream + :class:`plotly.graph_objects.splom.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each (x,y) pair to + appear on hover. If a single string, the same string + appears over all the data points. If an array of + string, the items are mapped in order to the this + trace's (x,y) coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.splom.Unselected` instance + or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + xaxes + Sets the list of x axes corresponding to dimensions of + this splom trace. By default, a splom will match the + first N xaxes where N is the number of input + dimensions. Note that, in case where `diagonal.visible` + is false and `showupperhalf` or `showlowerhalf` is + false, this splom trace will generate one less x-axis + and one less y-axis. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + yaxes + Sets the list of y axes corresponding to dimensions of + this splom trace. By default, a splom will match the + first N yaxes where N is the number of input + dimensions. Note that, in case where `diagonal.visible` + is false and `showupperhalf` or `showlowerhalf` is + false, this splom trace will generate one less x-axis + and one less y-axis. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + """ + + def __init__( + self, + arg=None, + customdata=None, + customdatasrc=None, + diagonal=None, + dimensions=None, + dimensiondefaults=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + marker=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + selected=None, + selectedpoints=None, + showlegend=None, + showlowerhalf=None, + showupperhalf=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + xaxes=None, + xhoverformat=None, + yaxes=None, + yhoverformat=None, + **kwargs, + ): + """ + Construct a new Splom object + + Splom traces generate scatter plot matrix visualizations. Each + splom `dimensions` items correspond to a generated axis. Values + for each of those dimensions are set in `dimensions[i].values`. + Splom traces support all `scattergl` marker style attributes. + Specify `layout.grid` attributes and/or layout x-axis and + y-axis attributes for more control over the axis positioning + and style. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Splom` + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + diagonal + :class:`plotly.graph_objects.splom.Diagonal` instance + or dict with compatible properties + dimensions + A tuple of + :class:`plotly.graph_objects.splom.Dimension` instances + or dicts with compatible properties + dimensiondefaults + When used in a template (as + layout.template.data.splom.dimensiondefaults), sets the + default property values to use for elements of + splom.dimensions + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.splom.Hoverlabel` instance + or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.splom.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + marker + :class:`plotly.graph_objects.splom.Marker` instance or + dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + selected + :class:`plotly.graph_objects.splom.Selected` instance + or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showlowerhalf + Determines whether or not subplots on the lower half + from the diagonal are displayed. + showupperhalf + Determines whether or not subplots on the upper half + from the diagonal are displayed. + stream + :class:`plotly.graph_objects.splom.Stream` instance or + dict with compatible properties + text + Sets text elements associated with each (x,y) pair to + appear on hover. If a single string, the same string + appears over all the data points. If an array of + string, the items are mapped in order to the this + trace's (x,y) coordinates. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.splom.Unselected` instance + or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + xaxes + Sets the list of x axes corresponding to dimensions of + this splom trace. By default, a splom will match the + first N xaxes where N is the number of input + dimensions. Note that, in case where `diagonal.visible` + is false and `showupperhalf` or `showlowerhalf` is + false, this splom trace will generate one less x-axis + and one less y-axis. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + yaxes + Sets the list of y axes corresponding to dimensions of + this splom trace. By default, a splom will match the + first N yaxes where N is the number of input + dimensions. Note that, in case where `diagonal.visible` + is false and `showupperhalf` or `showlowerhalf` is + false, this splom trace will generate one less x-axis + and one less y-axis. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + + Returns + ------- + Splom + """ + super().__init__("splom") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Splom +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Splom`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("diagonal", arg, diagonal) + self._set_property("dimensions", arg, dimensions) + self._set_property("dimensiondefaults", arg, dimensiondefaults) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("marker", arg, marker) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("showlowerhalf", arg, showlowerhalf) + self._set_property("showupperhalf", arg, showupperhalf) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + self._set_property("xaxes", arg, xaxes) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("yaxes", arg, yaxes) + self._set_property("yhoverformat", arg, yhoverformat) + + self._props["type"] = "splom" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_streamtube.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_streamtube.py new file mode 100644 index 0000000000000000000000000000000000000000..fe6bd78ffd7228dd187b109051ddc8274ea1a7ed --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_streamtube.py @@ -0,0 +1,2214 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Streamtube(_BaseTraceType): + _parent_path_str = "" + _path_str = "streamtube" + _valid_props = { + "autocolorscale", + "cauto", + "cmax", + "cmid", + "cmin", + "coloraxis", + "colorbar", + "colorscale", + "customdata", + "customdatasrc", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "lighting", + "lightposition", + "maxdisplayed", + "meta", + "metasrc", + "name", + "opacity", + "reversescale", + "scene", + "showlegend", + "showscale", + "sizeref", + "starts", + "stream", + "text", + "type", + "u", + "uhoverformat", + "uid", + "uirevision", + "usrc", + "v", + "vhoverformat", + "visible", + "vsrc", + "w", + "whoverformat", + "wsrc", + "x", + "xhoverformat", + "xsrc", + "y", + "yhoverformat", + "ysrc", + "z", + "zhoverformat", + "zsrc", + } + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def cauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here u/v/w norm) or the bounds set + in `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` + are set by the user. + + The 'cauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cauto"] + + @cauto.setter + def cauto(self, val): + self["cauto"] = val + + @property + def cmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as u/v/w norm and if set, `cmin` must be set as + well. + + The 'cmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmax"] + + @cmax.setter + def cmax(self, val): + self["cmax"] = val + + @property + def cmid(self): + """ + Sets the mid-point of the color domain by scaling `cmin` and/or + `cmax` to be equidistant to this point. Value should have the + same units as u/v/w norm. Has no effect when `cauto` is + `false`. + + The 'cmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmid"] + + @cmid.setter + def cmid(self, val): + self["cmid"] = val + + @property + def cmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as u/v/w norm and if set, `cmax` must be set as + well. + + The 'cmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmin"] + + @cmin.setter + def cmin(self, val): + self["cmin"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.streamtube.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.streamtube.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'u', 'v', 'w', 'norm', 'divergence', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.streamtube.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.streamtube.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables `tubex`, + `tubey`, `tubez`, `tubeu`, `tubev`, `tubew`, `norm` and + `divergence`. Anything contained in tag `` is displayed + in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.streamtube.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.streamtube.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def lighting(self): + """ + The 'lighting' property is an instance of Lighting + that may be specified as: + - An instance of :class:`plotly.graph_objs.streamtube.Lighting` + - A dict of string/value properties that will be passed + to the Lighting constructor + + Returns + ------- + plotly.graph_objs.streamtube.Lighting + """ + return self["lighting"] + + @lighting.setter + def lighting(self, val): + self["lighting"] = val + + @property + def lightposition(self): + """ + The 'lightposition' property is an instance of Lightposition + that may be specified as: + - An instance of :class:`plotly.graph_objs.streamtube.Lightposition` + - A dict of string/value properties that will be passed + to the Lightposition constructor + + Returns + ------- + plotly.graph_objs.streamtube.Lightposition + """ + return self["lightposition"] + + @lightposition.setter + def lightposition(self, val): + self["lightposition"] = val + + @property + def maxdisplayed(self): + """ + The maximum number of displayed segments in a streamtube. + + The 'maxdisplayed' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["maxdisplayed"] + + @maxdisplayed.setter + def maxdisplayed(self, val): + self["maxdisplayed"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the surface. Please note that in the case + of using high `opacity` values for example a value greater than + or equal to 0.5 on two surfaces (and 0.25 with four surfaces), + an overlay of multiple transparent surfaces may not perfectly + be sorted in depth by the webgl API. This behavior may be + improved in the near future and is subject to change. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `cmin` will + correspond to the last color in the array and `cmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def scene(self): + """ + Sets a reference between this trace's 3D coordinate system and + a 3D scene. If "scene" (the default value), the (x,y,z) + coordinates refer to `layout.scene`. If "scene2", the (x,y,z) + coordinates refer to `layout.scene2`, and so on. + + The 'scene' property is an identifier of a particular + subplot, of type 'scene', that may be specified as: + - the string 'scene' optionally followed by an integer >= 1 + (e.g. 'scene', 'scene1', 'scene2', 'scene3', etc.) + + Returns + ------- + str + """ + return self["scene"] + + @scene.setter + def scene(self, val): + self["scene"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def sizeref(self): + """ + The scaling factor for the streamtubes. The default is 1, which + avoids two max divergence tubes from touching at adjacent + starting positions. + + The 'sizeref' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["sizeref"] + + @sizeref.setter + def sizeref(self, val): + self["sizeref"] = val + + @property + def starts(self): + """ + The 'starts' property is an instance of Starts + that may be specified as: + - An instance of :class:`plotly.graph_objs.streamtube.Starts` + - A dict of string/value properties that will be passed + to the Starts constructor + + Returns + ------- + plotly.graph_objs.streamtube.Starts + """ + return self["starts"] + + @starts.setter + def starts(self, val): + self["starts"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.streamtube.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.streamtube.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets a text element associated with this trace. If trace + `hoverinfo` contains a "text" flag, this text element will be + seen in all hover labels. Note that streamtube traces do not + support array `text` values. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def u(self): + """ + Sets the x components of the vector field. + + The 'u' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["u"] + + @u.setter + def u(self, val): + self["u"] = val + + @property + def uhoverformat(self): + """ + Sets the hover text formatting rulefor `u` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format.By + default the values are formatted using generic number format. + + The 'uhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uhoverformat"] + + @uhoverformat.setter + def uhoverformat(self, val): + self["uhoverformat"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def usrc(self): + """ + Sets the source reference on Chart Studio Cloud for `u`. + + The 'usrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["usrc"] + + @usrc.setter + def usrc(self, val): + self["usrc"] = val + + @property + def v(self): + """ + Sets the y components of the vector field. + + The 'v' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["v"] + + @v.setter + def v(self, val): + self["v"] = val + + @property + def vhoverformat(self): + """ + Sets the hover text formatting rulefor `v` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format.By + default the values are formatted using generic number format. + + The 'vhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["vhoverformat"] + + @vhoverformat.setter + def vhoverformat(self, val): + self["vhoverformat"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def vsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `v`. + + The 'vsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["vsrc"] + + @vsrc.setter + def vsrc(self, val): + self["vsrc"] = val + + @property + def w(self): + """ + Sets the z components of the vector field. + + The 'w' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["w"] + + @w.setter + def w(self, val): + self["w"] = val + + @property + def whoverformat(self): + """ + Sets the hover text formatting rulefor `w` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format.By + default the values are formatted using generic number format. + + The 'whoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["whoverformat"] + + @whoverformat.setter + def whoverformat(self, val): + self["whoverformat"] = val + + @property + def wsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `w`. + + The 'wsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["wsrc"] + + @wsrc.setter + def wsrc(self, val): + self["wsrc"] = val + + @property + def x(self): + """ + Sets the x coordinates of the vector field. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the y coordinates of the vector field. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def z(self): + """ + Sets the z coordinates of the vector field. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zhoverformat(self): + """ + Sets the hover text formatting rulefor `z` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `zaxis.hoverformat`. + + The 'zhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["zhoverformat"] + + @zhoverformat.setter + def zhoverformat(self, val): + self["zhoverformat"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here u/v/w norm) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmin` + must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as u/v/w norm. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmax` + must be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.streamtube.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.streamtube.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `tubex`, `tubey`, `tubez`, `tubeu`, + `tubev`, `tubew`, `norm` and `divergence`. Anything + contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.streamtube.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.streamtube.Lighting` + instance or dict with compatible properties + lightposition + :class:`plotly.graph_objects.streamtube.Lightposition` + instance or dict with compatible properties + maxdisplayed + The maximum number of displayed segments in a + streamtube. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + sizeref + The scaling factor for the streamtubes. The default is + 1, which avoids two max divergence tubes from touching + at adjacent starting positions. + starts + :class:`plotly.graph_objects.streamtube.Starts` + instance or dict with compatible properties + stream + :class:`plotly.graph_objects.streamtube.Stream` + instance or dict with compatible properties + text + Sets a text element associated with this trace. If + trace `hoverinfo` contains a "text" flag, this text + element will be seen in all hover labels. Note that + streamtube traces do not support array `text` values. + u + Sets the x components of the vector field. + uhoverformat + Sets the hover text formatting rulefor `u` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + usrc + Sets the source reference on Chart Studio Cloud for + `u`. + v + Sets the y components of the vector field. + vhoverformat + Sets the hover text formatting rulefor `v` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + vsrc + Sets the source reference on Chart Studio Cloud for + `v`. + w + Sets the z components of the vector field. + whoverformat + Sets the hover text formatting rulefor `w` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + wsrc + Sets the source reference on Chart Studio Cloud for + `w`. + x + Sets the x coordinates of the vector field. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates of the vector field. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates of the vector field. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + coloraxis=None, + colorbar=None, + colorscale=None, + customdata=None, + customdatasrc=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + maxdisplayed=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + sizeref=None, + starts=None, + stream=None, + text=None, + u=None, + uhoverformat=None, + uid=None, + uirevision=None, + usrc=None, + v=None, + vhoverformat=None, + visible=None, + vsrc=None, + w=None, + whoverformat=None, + wsrc=None, + x=None, + xhoverformat=None, + xsrc=None, + y=None, + yhoverformat=None, + ysrc=None, + z=None, + zhoverformat=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Streamtube object + + Use a streamtube trace to visualize flow in a vector field. + Specify a vector field using 6 1D arrays of equal length, 3 + position arrays `x`, `y` and `z` and 3 vector component arrays + `u`, `v`, and `w`. By default, the tubes' starting positions + will be cut from the vector field's x-z plane at its minimum y + value. To specify your own starting position, use attributes + `starts.x`, `starts.y` and `starts.z`. The color is encoded by + the norm of (u, v, w), and the local radius by the divergence + of (u, v, w). + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Streamtube` + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here u/v/w norm) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmin` + must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as u/v/w norm. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as u/v/w norm and if set, `cmax` + must be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.streamtube.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.streamtube.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `tubex`, `tubey`, `tubez`, `tubeu`, + `tubev`, `tubew`, `norm` and `divergence`. Anything + contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.streamtube.Legendgrouptitl + e` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.streamtube.Lighting` + instance or dict with compatible properties + lightposition + :class:`plotly.graph_objects.streamtube.Lightposition` + instance or dict with compatible properties + maxdisplayed + The maximum number of displayed segments in a + streamtube. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + sizeref + The scaling factor for the streamtubes. The default is + 1, which avoids two max divergence tubes from touching + at adjacent starting positions. + starts + :class:`plotly.graph_objects.streamtube.Starts` + instance or dict with compatible properties + stream + :class:`plotly.graph_objects.streamtube.Stream` + instance or dict with compatible properties + text + Sets a text element associated with this trace. If + trace `hoverinfo` contains a "text" flag, this text + element will be seen in all hover labels. Note that + streamtube traces do not support array `text` values. + u + Sets the x components of the vector field. + uhoverformat + Sets the hover text formatting rulefor `u` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + usrc + Sets the source reference on Chart Studio Cloud for + `u`. + v + Sets the y components of the vector field. + vhoverformat + Sets the hover text formatting rulefor `v` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + vsrc + Sets the source reference on Chart Studio Cloud for + `v`. + w + Sets the z components of the vector field. + whoverformat + Sets the hover text formatting rulefor `w` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + wsrc + Sets the source reference on Chart Studio Cloud for + `w`. + x + Sets the x coordinates of the vector field. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates of the vector field. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates of the vector field. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Streamtube + """ + super().__init__("streamtube") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Streamtube +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Streamtube`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("cauto", arg, cauto) + self._set_property("cmax", arg, cmax) + self._set_property("cmid", arg, cmid) + self._set_property("cmin", arg, cmin) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("lighting", arg, lighting) + self._set_property("lightposition", arg, lightposition) + self._set_property("maxdisplayed", arg, maxdisplayed) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("reversescale", arg, reversescale) + self._set_property("scene", arg, scene) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("sizeref", arg, sizeref) + self._set_property("starts", arg, starts) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("u", arg, u) + self._set_property("uhoverformat", arg, uhoverformat) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("usrc", arg, usrc) + self._set_property("v", arg, v) + self._set_property("vhoverformat", arg, vhoverformat) + self._set_property("visible", arg, visible) + self._set_property("vsrc", arg, vsrc) + self._set_property("w", arg, w) + self._set_property("whoverformat", arg, whoverformat) + self._set_property("wsrc", arg, wsrc) + self._set_property("x", arg, x) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("ysrc", arg, ysrc) + self._set_property("z", arg, z) + self._set_property("zhoverformat", arg, zhoverformat) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "streamtube" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_sunburst.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_sunburst.py new file mode 100644 index 0000000000000000000000000000000000000000..b7df56bfa016a9f715129a40f01442701d6dc39a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_sunburst.py @@ -0,0 +1,1854 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Sunburst(_BaseTraceType): + _parent_path_str = "" + _path_str = "sunburst" + _valid_props = { + "branchvalues", + "count", + "customdata", + "customdatasrc", + "domain", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "insidetextfont", + "insidetextorientation", + "labels", + "labelssrc", + "leaf", + "legend", + "legendgrouptitle", + "legendrank", + "legendwidth", + "level", + "marker", + "maxdepth", + "meta", + "metasrc", + "name", + "opacity", + "outsidetextfont", + "parents", + "parentssrc", + "root", + "rotation", + "sort", + "stream", + "text", + "textfont", + "textinfo", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "type", + "uid", + "uirevision", + "values", + "valuessrc", + "visible", + } + + @property + def branchvalues(self): + """ + Determines how the items in `values` are summed. When set to + "total", items in `values` are taken to be value of all its + descendants. When set to "remainder", items in `values` + corresponding to the root and the branches sectors are taken to + be the extra part not part of the sum of the values at their + leaves. + + The 'branchvalues' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['remainder', 'total'] + + Returns + ------- + Any + """ + return self["branchvalues"] + + @branchvalues.setter + def branchvalues(self, val): + self["branchvalues"] = val + + @property + def count(self): + """ + Determines default for `values` when it is not provided, by + inferring a 1 for each of the "leaves" and/or "branches", + otherwise 0. + + The 'count' property is a flaglist and may be specified + as a string containing: + - Any combination of ['branches', 'leaves'] joined with '+' characters + (e.g. 'branches+leaves') + + Returns + ------- + Any + """ + return self["count"] + + @count.setter + def count(self, val): + self["count"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.sunburst.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.sunburst.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['label', 'text', 'value', 'name', 'current path', 'percent root', 'percent entry', 'percent parent'] joined with '+' characters + (e.g. 'label+text') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.sunburst.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.sunburst.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables + `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry` + and `percentParent`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each sector. If a + single string, the same string appears for all data points. If + an array of string, the items are mapped in order of this + trace's sectors. To be seen, trace `hoverinfo` must contain a + "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def insidetextfont(self): + """ + Sets the font used for `textinfo` lying inside the sector. + + The 'insidetextfont' property is an instance of Insidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.sunburst.Insidetextfont` + - A dict of string/value properties that will be passed + to the Insidetextfont constructor + + Returns + ------- + plotly.graph_objs.sunburst.Insidetextfont + """ + return self["insidetextfont"] + + @insidetextfont.setter + def insidetextfont(self, val): + self["insidetextfont"] = val + + @property + def insidetextorientation(self): + """ + Controls the orientation of the text inside chart sectors. When + set to "auto", text may be oriented in any direction in order + to be as big as possible in the middle of a sector. The + "horizontal" option orients text to be parallel with the bottom + of the chart, and may make text smaller in order to achieve + that goal. The "radial" option orients text along the radius of + the sector. The "tangential" option orients text perpendicular + to the radius of the sector. + + The 'insidetextorientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['horizontal', 'radial', 'tangential', 'auto'] + + Returns + ------- + Any + """ + return self["insidetextorientation"] + + @insidetextorientation.setter + def insidetextorientation(self, val): + self["insidetextorientation"] = val + + @property + def labels(self): + """ + Sets the labels of each of the sectors. + + The 'labels' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["labels"] + + @labels.setter + def labels(self, val): + self["labels"] = val + + @property + def labelssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `labels`. + + The 'labelssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["labelssrc"] + + @labelssrc.setter + def labelssrc(self, val): + self["labelssrc"] = val + + @property + def leaf(self): + """ + The 'leaf' property is an instance of Leaf + that may be specified as: + - An instance of :class:`plotly.graph_objs.sunburst.Leaf` + - A dict of string/value properties that will be passed + to the Leaf constructor + + Returns + ------- + plotly.graph_objs.sunburst.Leaf + """ + return self["leaf"] + + @leaf.setter + def leaf(self, val): + self["leaf"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.sunburst.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.sunburst.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def level(self): + """ + Sets the level from which this trace hierarchy is rendered. Set + `level` to `''` to start from the root node in the hierarchy. + Must be an "id" if `ids` is filled in, otherwise plotly + attempts to find a matching item in `labels`. + + The 'level' property accepts values of any type + + Returns + ------- + Any + """ + return self["level"] + + @level.setter + def level(self, val): + self["level"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.sunburst.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.sunburst.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def maxdepth(self): + """ + Sets the number of rendered sectors from any given `level`. Set + `maxdepth` to "-1" to render all the levels in the hierarchy. + + The 'maxdepth' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["maxdepth"] + + @maxdepth.setter + def maxdepth(self, val): + self["maxdepth"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def outsidetextfont(self): + """ + Sets the font used for `textinfo` lying outside the sector. + This option refers to the root of the hierarchy presented at + the center of a sunburst graph. Please note that if a hierarchy + has multiple root nodes, this option won't have any effect and + `insidetextfont` would be used. + + The 'outsidetextfont' property is an instance of Outsidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.sunburst.Outsidetextfont` + - A dict of string/value properties that will be passed + to the Outsidetextfont constructor + + Returns + ------- + plotly.graph_objs.sunburst.Outsidetextfont + """ + return self["outsidetextfont"] + + @outsidetextfont.setter + def outsidetextfont(self, val): + self["outsidetextfont"] = val + + @property + def parents(self): + """ + Sets the parent sectors for each of the sectors. Empty string + items '' are understood to reference the root node in the + hierarchy. If `ids` is filled, `parents` items are understood + to be "ids" themselves. When `ids` is not set, plotly attempts + to find matching items in `labels`, but beware they must be + unique. + + The 'parents' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["parents"] + + @parents.setter + def parents(self, val): + self["parents"] = val + + @property + def parentssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `parents`. + + The 'parentssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["parentssrc"] + + @parentssrc.setter + def parentssrc(self, val): + self["parentssrc"] = val + + @property + def root(self): + """ + The 'root' property is an instance of Root + that may be specified as: + - An instance of :class:`plotly.graph_objs.sunburst.Root` + - A dict of string/value properties that will be passed + to the Root constructor + + Returns + ------- + plotly.graph_objs.sunburst.Root + """ + return self["root"] + + @root.setter + def root(self, val): + self["root"] = val + + @property + def rotation(self): + """ + Rotates the whole diagram counterclockwise by some angle. By + default the first slice starts at 3 o'clock. + + The 'rotation' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["rotation"] + + @rotation.setter + def rotation(self, val): + self["rotation"] = val + + @property + def sort(self): + """ + Determines whether or not the sectors are reordered from + largest to smallest. + + The 'sort' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["sort"] + + @sort.setter + def sort(self, val): + self["sort"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.sunburst.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.sunburst.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets text elements associated with each sector. If trace + `textinfo` contains a "text" flag, these elements will be seen + on the chart. If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in the + hover labels. + + The 'text' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the font used for `textinfo`. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.sunburst.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.sunburst.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textinfo(self): + """ + Determines which trace information appear on the graph. + + The 'textinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['label', 'text', 'value', 'current path', 'percent root', 'percent entry', 'percent parent'] joined with '+' characters + (e.g. 'label+text') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["textinfo"] + + @textinfo.setter + def textinfo(self, val): + self["textinfo"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry`, + `percentParent`, `label` and `value`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def values(self): + """ + Sets the values associated with each of the sectors. Use with + `branchvalues` to determine how the values are summed. + + The 'values' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["values"] + + @values.setter + def values(self, val): + self["values"] = val + + @property + def valuessrc(self): + """ + Sets the source reference on Chart Studio Cloud for `values`. + + The 'valuessrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["valuessrc"] + + @valuessrc.setter + def valuessrc(self, val): + self["valuessrc"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + branchvalues + Determines how the items in `values` are summed. When + set to "total", items in `values` are taken to be value + of all its descendants. When set to "remainder", items + in `values` corresponding to the root and the branches + sectors are taken to be the extra part not part of the + sum of the values at their leaves. + count + Determines default for `values` when it is not + provided, by inferring a 1 for each of the "leaves" + and/or "branches", otherwise 0. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.sunburst.Domain` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.sunburst.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry` and `percentParent`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + insidetextorientation + Controls the orientation of the text inside chart + sectors. When set to "auto", text may be oriented in + any direction in order to be as big as possible in the + middle of a sector. The "horizontal" option orients + text to be parallel with the bottom of the chart, and + may make text smaller in order to achieve that goal. + The "radial" option orients text along the radius of + the sector. The "tangential" option orients text + perpendicular to the radius of the sector. + labels + Sets the labels of each of the sectors. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + leaf + :class:`plotly.graph_objects.sunburst.Leaf` instance or + dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.sunburst.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + level + Sets the level from which this trace hierarchy is + rendered. Set `level` to `''` to start from the root + node in the hierarchy. Must be an "id" if `ids` is + filled in, otherwise plotly attempts to find a matching + item in `labels`. + marker + :class:`plotly.graph_objects.sunburst.Marker` instance + or dict with compatible properties + maxdepth + Sets the number of rendered sectors from any given + `level`. Set `maxdepth` to "-1" to render all the + levels in the hierarchy. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. This option refers to the root of the hierarchy + presented at the center of a sunburst graph. Please + note that if a hierarchy has multiple root nodes, this + option won't have any effect and `insidetextfont` would + be used. + parents + Sets the parent sectors for each of the sectors. Empty + string items '' are understood to reference the root + node in the hierarchy. If `ids` is filled, `parents` + items are understood to be "ids" themselves. When `ids` + is not set, plotly attempts to find matching items in + `labels`, but beware they must be unique. + parentssrc + Sets the source reference on Chart Studio Cloud for + `parents`. + root + :class:`plotly.graph_objects.sunburst.Root` instance or + dict with compatible properties + rotation + Rotates the whole diagram counterclockwise by some + angle. By default the first slice starts at 3 o'clock. + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.sunburst.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry`, `percentParent`, `label` + and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values associated with each of the sectors. + Use with `branchvalues` to determine how the values are + summed. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + branchvalues=None, + count=None, + customdata=None, + customdatasrc=None, + domain=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextfont=None, + insidetextorientation=None, + labels=None, + labelssrc=None, + leaf=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + level=None, + marker=None, + maxdepth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + outsidetextfont=None, + parents=None, + parentssrc=None, + root=None, + rotation=None, + sort=None, + stream=None, + text=None, + textfont=None, + textinfo=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + uid=None, + uirevision=None, + values=None, + valuessrc=None, + visible=None, + **kwargs, + ): + """ + Construct a new Sunburst object + + Visualize hierarchal data spanning outward radially from root + to leaves. The sunburst sectors are determined by the entries + in "labels" or "ids" and in "parents". + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Sunburst` + branchvalues + Determines how the items in `values` are summed. When + set to "total", items in `values` are taken to be value + of all its descendants. When set to "remainder", items + in `values` corresponding to the root and the branches + sectors are taken to be the extra part not part of the + sum of the values at their leaves. + count + Determines default for `values` when it is not + provided, by inferring a 1 for each of the "leaves" + and/or "branches", otherwise 0. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.sunburst.Domain` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.sunburst.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry` and `percentParent`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + insidetextorientation + Controls the orientation of the text inside chart + sectors. When set to "auto", text may be oriented in + any direction in order to be as big as possible in the + middle of a sector. The "horizontal" option orients + text to be parallel with the bottom of the chart, and + may make text smaller in order to achieve that goal. + The "radial" option orients text along the radius of + the sector. The "tangential" option orients text + perpendicular to the radius of the sector. + labels + Sets the labels of each of the sectors. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + leaf + :class:`plotly.graph_objects.sunburst.Leaf` instance or + dict with compatible properties + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.sunburst.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + level + Sets the level from which this trace hierarchy is + rendered. Set `level` to `''` to start from the root + node in the hierarchy. Must be an "id" if `ids` is + filled in, otherwise plotly attempts to find a matching + item in `labels`. + marker + :class:`plotly.graph_objects.sunburst.Marker` instance + or dict with compatible properties + maxdepth + Sets the number of rendered sectors from any given + `level`. Set `maxdepth` to "-1" to render all the + levels in the hierarchy. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. This option refers to the root of the hierarchy + presented at the center of a sunburst graph. Please + note that if a hierarchy has multiple root nodes, this + option won't have any effect and `insidetextfont` would + be used. + parents + Sets the parent sectors for each of the sectors. Empty + string items '' are understood to reference the root + node in the hierarchy. If `ids` is filled, `parents` + items are understood to be "ids" themselves. When `ids` + is not set, plotly attempts to find matching items in + `labels`, but beware they must be unique. + parentssrc + Sets the source reference on Chart Studio Cloud for + `parents`. + root + :class:`plotly.graph_objects.sunburst.Root` instance or + dict with compatible properties + rotation + Rotates the whole diagram counterclockwise by some + angle. By default the first slice starts at 3 o'clock. + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.sunburst.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry`, `percentParent`, `label` + and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values associated with each of the sectors. + Use with `branchvalues` to determine how the values are + summed. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Sunburst + """ + super().__init__("sunburst") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Sunburst +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Sunburst`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("branchvalues", arg, branchvalues) + self._set_property("count", arg, count) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("domain", arg, domain) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("insidetextfont", arg, insidetextfont) + self._set_property("insidetextorientation", arg, insidetextorientation) + self._set_property("labels", arg, labels) + self._set_property("labelssrc", arg, labelssrc) + self._set_property("leaf", arg, leaf) + self._set_property("legend", arg, legend) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("level", arg, level) + self._set_property("marker", arg, marker) + self._set_property("maxdepth", arg, maxdepth) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("outsidetextfont", arg, outsidetextfont) + self._set_property("parents", arg, parents) + self._set_property("parentssrc", arg, parentssrc) + self._set_property("root", arg, root) + self._set_property("rotation", arg, rotation) + self._set_property("sort", arg, sort) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textinfo", arg, textinfo) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("values", arg, values) + self._set_property("valuessrc", arg, valuessrc) + self._set_property("visible", arg, visible) + + self._props["type"] = "sunburst" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_surface.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_surface.py new file mode 100644 index 0000000000000000000000000000000000000000..8a1dddc8b7193a3016e3e04c2bd12e9d314738af --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_surface.py @@ -0,0 +1,2187 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Surface(_BaseTraceType): + _parent_path_str = "" + _path_str = "surface" + _valid_props = { + "autocolorscale", + "cauto", + "cmax", + "cmid", + "cmin", + "coloraxis", + "colorbar", + "colorscale", + "connectgaps", + "contours", + "customdata", + "customdatasrc", + "hidesurface", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "lighting", + "lightposition", + "meta", + "metasrc", + "name", + "opacity", + "opacityscale", + "reversescale", + "scene", + "showlegend", + "showscale", + "stream", + "surfacecolor", + "surfacecolorsrc", + "text", + "textsrc", + "type", + "uid", + "uirevision", + "visible", + "x", + "xcalendar", + "xhoverformat", + "xsrc", + "y", + "ycalendar", + "yhoverformat", + "ysrc", + "z", + "zcalendar", + "zhoverformat", + "zsrc", + } + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def cauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here z or surfacecolor) or the + bounds set in `cmin` and `cmax` Defaults to `false` when `cmin` + and `cmax` are set by the user. + + The 'cauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cauto"] + + @cauto.setter + def cauto(self, val): + self["cauto"] = val + + @property + def cmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as z or surfacecolor and if set, `cmin` must be set + as well. + + The 'cmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmax"] + + @cmax.setter + def cmax(self, val): + self["cmax"] = val + + @property + def cmid(self): + """ + Sets the mid-point of the color domain by scaling `cmin` and/or + `cmax` to be equidistant to this point. Value should have the + same units as z or surfacecolor. Has no effect when `cauto` is + `false`. + + The 'cmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmid"] + + @cmid.setter + def cmid(self, val): + self["cmid"] = val + + @property + def cmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as z or surfacecolor and if set, `cmax` must be set + as well. + + The 'cmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmin"] + + @cmin.setter + def cmin(self, val): + self["cmin"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.surface.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.surface.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def connectgaps(self): + """ + Determines whether or not gaps (i.e. {nan} or missing values) + in the `z` data are filled in. + + The 'connectgaps' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["connectgaps"] + + @connectgaps.setter + def connectgaps(self, val): + self["connectgaps"] = val + + @property + def contours(self): + """ + The 'contours' property is an instance of Contours + that may be specified as: + - An instance of :class:`plotly.graph_objs.surface.Contours` + - A dict of string/value properties that will be passed + to the Contours constructor + + Returns + ------- + plotly.graph_objs.surface.Contours + """ + return self["contours"] + + @contours.setter + def contours(self, val): + self["contours"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def hidesurface(self): + """ + Determines whether or not a surface is drawn. For example, set + `hidesurface` to False `contours.x.show` to True and + `contours.y.show` to True to draw a wire frame plot. + + The 'hidesurface' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["hidesurface"] + + @hidesurface.setter + def hidesurface(self, val): + self["hidesurface"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.surface.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.surface.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.surface.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.surface.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def lighting(self): + """ + The 'lighting' property is an instance of Lighting + that may be specified as: + - An instance of :class:`plotly.graph_objs.surface.Lighting` + - A dict of string/value properties that will be passed + to the Lighting constructor + + Returns + ------- + plotly.graph_objs.surface.Lighting + """ + return self["lighting"] + + @lighting.setter + def lighting(self, val): + self["lighting"] = val + + @property + def lightposition(self): + """ + The 'lightposition' property is an instance of Lightposition + that may be specified as: + - An instance of :class:`plotly.graph_objs.surface.Lightposition` + - A dict of string/value properties that will be passed + to the Lightposition constructor + + Returns + ------- + plotly.graph_objs.surface.Lightposition + """ + return self["lightposition"] + + @lightposition.setter + def lightposition(self, val): + self["lightposition"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the surface. Please note that in the case + of using high `opacity` values for example a value greater than + or equal to 0.5 on two surfaces (and 0.25 with four surfaces), + an overlay of multiple transparent surfaces may not perfectly + be sorted in depth by the webgl API. This behavior may be + improved in the near future and is subject to change. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def opacityscale(self): + """ + Sets the opacityscale. The opacityscale must be an array + containing arrays mapping a normalized value to an opacity + value. At minimum, a mapping for the lowest (0) and highest (1) + values are required. For example, `[[0, 1], [0.5, 0.2], [1, + 1]]` means that higher/lower values would have higher opacity + values and those in the middle would be more transparent + Alternatively, `opacityscale` may be a palette name string of + the following list: 'min', 'max', 'extremes' and 'uniform'. The + default is 'uniform'. + + The 'opacityscale' property accepts values of any type + + Returns + ------- + Any + """ + return self["opacityscale"] + + @opacityscale.setter + def opacityscale(self, val): + self["opacityscale"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `cmin` will + correspond to the last color in the array and `cmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def scene(self): + """ + Sets a reference between this trace's 3D coordinate system and + a 3D scene. If "scene" (the default value), the (x,y,z) + coordinates refer to `layout.scene`. If "scene2", the (x,y,z) + coordinates refer to `layout.scene2`, and so on. + + The 'scene' property is an identifier of a particular + subplot, of type 'scene', that may be specified as: + - the string 'scene' optionally followed by an integer >= 1 + (e.g. 'scene', 'scene1', 'scene2', 'scene3', etc.) + + Returns + ------- + str + """ + return self["scene"] + + @scene.setter + def scene(self, val): + self["scene"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.surface.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.surface.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def surfacecolor(self): + """ + Sets the surface color values, used for setting a color scale + independent of `z`. + + The 'surfacecolor' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["surfacecolor"] + + @surfacecolor.setter + def surfacecolor(self, val): + self["surfacecolor"] = val + + @property + def surfacecolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `surfacecolor`. + + The 'surfacecolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["surfacecolorsrc"] + + @surfacecolorsrc.setter + def surfacecolorsrc(self, val): + self["surfacecolorsrc"] = val + + @property + def text(self): + """ + Sets the text elements associated with each z value. If trace + `hoverinfo` contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the x coordinates. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xcalendar(self): + """ + Sets the calendar system to use with `x` date data. + + The 'xcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["xcalendar"] + + @xcalendar.setter + def xcalendar(self, val): + self["xcalendar"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the y coordinates. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def ycalendar(self): + """ + Sets the calendar system to use with `y` date data. + + The 'ycalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["ycalendar"] + + @ycalendar.setter + def ycalendar(self, val): + self["ycalendar"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def z(self): + """ + Sets the z coordinates. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zcalendar(self): + """ + Sets the calendar system to use with `z` date data. + + The 'zcalendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["zcalendar"] + + @zcalendar.setter + def zcalendar(self, val): + self["zcalendar"] = val + + @property + def zhoverformat(self): + """ + Sets the hover text formatting rulefor `z` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `zaxis.hoverformat`. + + The 'zhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["zhoverformat"] + + @zhoverformat.setter + def zhoverformat(self, val): + self["zhoverformat"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here z or surfacecolor) + or the bounds set in `cmin` and `cmax` Defaults to + `false` when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as z or surfacecolor and if set, + `cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as z or surfacecolor. + Has no effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as z or surfacecolor and if set, + `cmax` must be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.surface.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data are filled in. + contours + :class:`plotly.graph_objects.surface.Contours` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hidesurface + Determines whether or not a surface is drawn. For + example, set `hidesurface` to False `contours.x.show` + to True and `contours.y.show` to True to draw a wire + frame plot. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.surface.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.surface.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.surface.Lighting` instance + or dict with compatible properties + lightposition + :class:`plotly.graph_objects.surface.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + opacityscale + Sets the opacityscale. The opacityscale must be an + array containing arrays mapping a normalized value to + an opacity value. At minimum, a mapping for the lowest + (0) and highest (1) values are required. For example, + `[[0, 1], [0.5, 0.2], [1, 1]]` means that higher/lower + values would have higher opacity values and those in + the middle would be more transparent Alternatively, + `opacityscale` may be a palette name string of the + following list: 'min', 'max', 'extremes' and 'uniform'. + The default is 'uniform'. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.surface.Stream` instance + or dict with compatible properties + surfacecolor + Sets the surface color values, used for setting a color + scale independent of `z`. + surfacecolorsrc + Sets the source reference on Chart Studio Cloud for + `surfacecolor`. + text + Sets the text elements associated with each z value. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates. + zcalendar + Sets the calendar system to use with `z` date data. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + coloraxis=None, + colorbar=None, + colorscale=None, + connectgaps=None, + contours=None, + customdata=None, + customdatasrc=None, + hidesurface=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + opacityscale=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + stream=None, + surfacecolor=None, + surfacecolorsrc=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + visible=None, + x=None, + xcalendar=None, + xhoverformat=None, + xsrc=None, + y=None, + ycalendar=None, + yhoverformat=None, + ysrc=None, + z=None, + zcalendar=None, + zhoverformat=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Surface object + + The data the describes the coordinates of the surface is set in + `z`. Data in `z` should be a 2D list. Coordinates in `x` and + `y` can either be 1D lists or 2D lists (e.g. to graph + parametric surfaces). If not provided in `x` and `y`, the x and + y coordinates are assumed to be linear starting at 0 with a + unit step. The color scale corresponds to the `z` values by + default. For custom color scales, use `surfacecolor` which + should be a 2D list, where its bounds can be controlled using + `cmin` and `cmax`. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Surface` + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here z or surfacecolor) + or the bounds set in `cmin` and `cmax` Defaults to + `false` when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as z or surfacecolor and if set, + `cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as z or surfacecolor. + Has no effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as z or surfacecolor and if set, + `cmax` must be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.surface.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + connectgaps + Determines whether or not gaps (i.e. {nan} or missing + values) in the `z` data are filled in. + contours + :class:`plotly.graph_objects.surface.Contours` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hidesurface + Determines whether or not a surface is drawn. For + example, set `hidesurface` to False `contours.x.show` + to True and `contours.y.show` to True to draw a wire + frame plot. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.surface.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.surface.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.surface.Lighting` instance + or dict with compatible properties + lightposition + :class:`plotly.graph_objects.surface.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + opacityscale + Sets the opacityscale. The opacityscale must be an + array containing arrays mapping a normalized value to + an opacity value. At minimum, a mapping for the lowest + (0) and highest (1) values are required. For example, + `[[0, 1], [0.5, 0.2], [1, 1]]` means that higher/lower + values would have higher opacity values and those in + the middle would be more transparent Alternatively, + `opacityscale` may be a palette name string of the + following list: 'min', 'max', 'extremes' and 'uniform'. + The default is 'uniform'. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + stream + :class:`plotly.graph_objects.surface.Stream` instance + or dict with compatible properties + surfacecolor + Sets the surface color values, used for setting a color + scale independent of `z`. + surfacecolorsrc + Sets the source reference on Chart Studio Cloud for + `surfacecolor`. + text + Sets the text elements associated with each z value. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the x coordinates. + xcalendar + Sets the calendar system to use with `x` date data. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + ycalendar + Sets the calendar system to use with `y` date data. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z coordinates. + zcalendar + Sets the calendar system to use with `z` date data. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Surface + """ + super().__init__("surface") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Surface +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Surface`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("cauto", arg, cauto) + self._set_property("cmax", arg, cmax) + self._set_property("cmid", arg, cmid) + self._set_property("cmin", arg, cmin) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("connectgaps", arg, connectgaps) + self._set_property("contours", arg, contours) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("hidesurface", arg, hidesurface) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("lighting", arg, lighting) + self._set_property("lightposition", arg, lightposition) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("opacityscale", arg, opacityscale) + self._set_property("reversescale", arg, reversescale) + self._set_property("scene", arg, scene) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("stream", arg, stream) + self._set_property("surfacecolor", arg, surfacecolor) + self._set_property("surfacecolorsrc", arg, surfacecolorsrc) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("xcalendar", arg, xcalendar) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("ycalendar", arg, ycalendar) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("ysrc", arg, ysrc) + self._set_property("z", arg, z) + self._set_property("zcalendar", arg, zcalendar) + self._set_property("zhoverformat", arg, zhoverformat) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "surface" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_table.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_table.py new file mode 100644 index 0000000000000000000000000000000000000000..e58ec78d7d56dd784a30cdda735459e13b7d0b2a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_table.py @@ -0,0 +1,908 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Table(_BaseTraceType): + _parent_path_str = "" + _path_str = "table" + _valid_props = { + "cells", + "columnorder", + "columnordersrc", + "columnwidth", + "columnwidthsrc", + "customdata", + "customdatasrc", + "domain", + "header", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "ids", + "idssrc", + "legend", + "legendgrouptitle", + "legendrank", + "legendwidth", + "meta", + "metasrc", + "name", + "stream", + "type", + "uid", + "uirevision", + "visible", + } + + @property + def cells(self): + """ + The 'cells' property is an instance of Cells + that may be specified as: + - An instance of :class:`plotly.graph_objs.table.Cells` + - A dict of string/value properties that will be passed + to the Cells constructor + + Returns + ------- + plotly.graph_objs.table.Cells + """ + return self["cells"] + + @cells.setter + def cells(self, val): + self["cells"] = val + + @property + def columnorder(self): + """ + Specifies the rendered order of the data columns; for example, + a value `2` at position `0` means that column index `0` in the + data will be rendered as the third column, as columns have an + index base of zero. + + The 'columnorder' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["columnorder"] + + @columnorder.setter + def columnorder(self, val): + self["columnorder"] = val + + @property + def columnordersrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `columnorder`. + + The 'columnordersrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["columnordersrc"] + + @columnordersrc.setter + def columnordersrc(self, val): + self["columnordersrc"] = val + + @property + def columnwidth(self): + """ + The width of columns expressed as a ratio. Columns fill the + available width in proportion of their specified column widths. + + The 'columnwidth' property is a number and may be specified as: + - An int or float + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["columnwidth"] + + @columnwidth.setter + def columnwidth(self, val): + self["columnwidth"] = val + + @property + def columnwidthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `columnwidth`. + + The 'columnwidthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["columnwidthsrc"] + + @columnwidthsrc.setter + def columnwidthsrc(self, val): + self["columnwidthsrc"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.table.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.table.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def header(self): + """ + The 'header' property is an instance of Header + that may be specified as: + - An instance of :class:`plotly.graph_objs.table.Header` + - A dict of string/value properties that will be passed + to the Header constructor + + Returns + ------- + plotly.graph_objs.table.Header + """ + return self["header"] + + @header.setter + def header(self, val): + self["header"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.table.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.table.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.table.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.table.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.table.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.table.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + cells + :class:`plotly.graph_objects.table.Cells` instance or + dict with compatible properties + columnorder + Specifies the rendered order of the data columns; for + example, a value `2` at position `0` means that column + index `0` in the data will be rendered as the third + column, as columns have an index base of zero. + columnordersrc + Sets the source reference on Chart Studio Cloud for + `columnorder`. + columnwidth + The width of columns expressed as a ratio. Columns fill + the available width in proportion of their specified + column widths. + columnwidthsrc + Sets the source reference on Chart Studio Cloud for + `columnwidth`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.table.Domain` instance or + dict with compatible properties + header + :class:`plotly.graph_objects.table.Header` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.table.Hoverlabel` instance + or dict with compatible properties + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.table.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + stream + :class:`plotly.graph_objects.table.Stream` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + cells=None, + columnorder=None, + columnordersrc=None, + columnwidth=None, + columnwidthsrc=None, + customdata=None, + customdatasrc=None, + domain=None, + header=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + ids=None, + idssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + meta=None, + metasrc=None, + name=None, + stream=None, + uid=None, + uirevision=None, + visible=None, + **kwargs, + ): + """ + Construct a new Table object + + Table view for detailed data viewing. The data are arranged in + a grid of rows and columns. Most styling can be specified for + columns, rows or individual cells. Table is using a column- + major order, ie. the grid is represented as a vector of column + vectors. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Table` + cells + :class:`plotly.graph_objects.table.Cells` instance or + dict with compatible properties + columnorder + Specifies the rendered order of the data columns; for + example, a value `2` at position `0` means that column + index `0` in the data will be rendered as the third + column, as columns have an index base of zero. + columnordersrc + Sets the source reference on Chart Studio Cloud for + `columnorder`. + columnwidth + The width of columns expressed as a ratio. Columns fill + the available width in proportion of their specified + column widths. + columnwidthsrc + Sets the source reference on Chart Studio Cloud for + `columnwidth`. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.table.Domain` instance or + dict with compatible properties + header + :class:`plotly.graph_objects.table.Header` instance or + dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.table.Hoverlabel` instance + or dict with compatible properties + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.table.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + stream + :class:`plotly.graph_objects.table.Stream` instance or + dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Table + """ + super().__init__("table") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Table +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Table`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("cells", arg, cells) + self._set_property("columnorder", arg, columnorder) + self._set_property("columnordersrc", arg, columnordersrc) + self._set_property("columnwidth", arg, columnwidth) + self._set_property("columnwidthsrc", arg, columnwidthsrc) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("domain", arg, domain) + self._set_property("header", arg, header) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("stream", arg, stream) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + + self._props["type"] = "table" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_treemap.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_treemap.py new file mode 100644 index 0000000000000000000000000000000000000000..4cced036174cfa39f2cc7a89facd809b24884379 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_treemap.py @@ -0,0 +1,1832 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Treemap(_BaseTraceType): + _parent_path_str = "" + _path_str = "treemap" + _valid_props = { + "branchvalues", + "count", + "customdata", + "customdatasrc", + "domain", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "insidetextfont", + "labels", + "labelssrc", + "legend", + "legendgrouptitle", + "legendrank", + "legendwidth", + "level", + "marker", + "maxdepth", + "meta", + "metasrc", + "name", + "opacity", + "outsidetextfont", + "parents", + "parentssrc", + "pathbar", + "root", + "sort", + "stream", + "text", + "textfont", + "textinfo", + "textposition", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "tiling", + "type", + "uid", + "uirevision", + "values", + "valuessrc", + "visible", + } + + @property + def branchvalues(self): + """ + Determines how the items in `values` are summed. When set to + "total", items in `values` are taken to be value of all its + descendants. When set to "remainder", items in `values` + corresponding to the root and the branches sectors are taken to + be the extra part not part of the sum of the values at their + leaves. + + The 'branchvalues' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['remainder', 'total'] + + Returns + ------- + Any + """ + return self["branchvalues"] + + @branchvalues.setter + def branchvalues(self, val): + self["branchvalues"] = val + + @property + def count(self): + """ + Determines default for `values` when it is not provided, by + inferring a 1 for each of the "leaves" and/or "branches", + otherwise 0. + + The 'count' property is a flaglist and may be specified + as a string containing: + - Any combination of ['branches', 'leaves'] joined with '+' characters + (e.g. 'branches+leaves') + + Returns + ------- + Any + """ + return self["count"] + + @count.setter + def count(self, val): + self["count"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.treemap.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.treemap.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['label', 'text', 'value', 'name', 'current path', 'percent root', 'percent entry', 'percent parent'] joined with '+' characters + (e.g. 'label+text') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.treemap.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.treemap.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables + `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry` + and `percentParent`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each sector. If a + single string, the same string appears for all data points. If + an array of string, the items are mapped in order of this + trace's sectors. To be seen, trace `hoverinfo` must contain a + "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def insidetextfont(self): + """ + Sets the font used for `textinfo` lying inside the sector. + + The 'insidetextfont' property is an instance of Insidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.treemap.Insidetextfont` + - A dict of string/value properties that will be passed + to the Insidetextfont constructor + + Returns + ------- + plotly.graph_objs.treemap.Insidetextfont + """ + return self["insidetextfont"] + + @insidetextfont.setter + def insidetextfont(self, val): + self["insidetextfont"] = val + + @property + def labels(self): + """ + Sets the labels of each of the sectors. + + The 'labels' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["labels"] + + @labels.setter + def labels(self, val): + self["labels"] = val + + @property + def labelssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `labels`. + + The 'labelssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["labelssrc"] + + @labelssrc.setter + def labelssrc(self, val): + self["labelssrc"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.treemap.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.treemap.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def level(self): + """ + Sets the level from which this trace hierarchy is rendered. Set + `level` to `''` to start from the root node in the hierarchy. + Must be an "id" if `ids` is filled in, otherwise plotly + attempts to find a matching item in `labels`. + + The 'level' property accepts values of any type + + Returns + ------- + Any + """ + return self["level"] + + @level.setter + def level(self, val): + self["level"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.treemap.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.treemap.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def maxdepth(self): + """ + Sets the number of rendered sectors from any given `level`. Set + `maxdepth` to "-1" to render all the levels in the hierarchy. + + The 'maxdepth' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["maxdepth"] + + @maxdepth.setter + def maxdepth(self, val): + self["maxdepth"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def outsidetextfont(self): + """ + Sets the font used for `textinfo` lying outside the sector. + This option refers to the root of the hierarchy presented on + top left corner of a treemap graph. Please note that if a + hierarchy has multiple root nodes, this option won't have any + effect and `insidetextfont` would be used. + + The 'outsidetextfont' property is an instance of Outsidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.treemap.Outsidetextfont` + - A dict of string/value properties that will be passed + to the Outsidetextfont constructor + + Returns + ------- + plotly.graph_objs.treemap.Outsidetextfont + """ + return self["outsidetextfont"] + + @outsidetextfont.setter + def outsidetextfont(self, val): + self["outsidetextfont"] = val + + @property + def parents(self): + """ + Sets the parent sectors for each of the sectors. Empty string + items '' are understood to reference the root node in the + hierarchy. If `ids` is filled, `parents` items are understood + to be "ids" themselves. When `ids` is not set, plotly attempts + to find matching items in `labels`, but beware they must be + unique. + + The 'parents' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["parents"] + + @parents.setter + def parents(self, val): + self["parents"] = val + + @property + def parentssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `parents`. + + The 'parentssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["parentssrc"] + + @parentssrc.setter + def parentssrc(self, val): + self["parentssrc"] = val + + @property + def pathbar(self): + """ + The 'pathbar' property is an instance of Pathbar + that may be specified as: + - An instance of :class:`plotly.graph_objs.treemap.Pathbar` + - A dict of string/value properties that will be passed + to the Pathbar constructor + + Returns + ------- + plotly.graph_objs.treemap.Pathbar + """ + return self["pathbar"] + + @pathbar.setter + def pathbar(self, val): + self["pathbar"] = val + + @property + def root(self): + """ + The 'root' property is an instance of Root + that may be specified as: + - An instance of :class:`plotly.graph_objs.treemap.Root` + - A dict of string/value properties that will be passed + to the Root constructor + + Returns + ------- + plotly.graph_objs.treemap.Root + """ + return self["root"] + + @root.setter + def root(self, val): + self["root"] = val + + @property + def sort(self): + """ + Determines whether or not the sectors are reordered from + largest to smallest. + + The 'sort' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["sort"] + + @sort.setter + def sort(self, val): + self["sort"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.treemap.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.treemap.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets text elements associated with each sector. If trace + `textinfo` contains a "text" flag, these elements will be seen + on the chart. If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in the + hover labels. + + The 'text' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textfont(self): + """ + Sets the font used for `textinfo`. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.treemap.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.treemap.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textinfo(self): + """ + Determines which trace information appear on the graph. + + The 'textinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['label', 'text', 'value', 'current path', 'percent root', 'percent entry', 'percent parent'] joined with '+' characters + (e.g. 'label+text') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["textinfo"] + + @textinfo.setter + def textinfo(self, val): + self["textinfo"] = val + + @property + def textposition(self): + """ + Sets the positions of the `text` elements. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top left', 'top center', 'top right', 'middle left', + 'middle center', 'middle right', 'bottom left', 'bottom + center', 'bottom right'] + + Returns + ------- + Any + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `currentPath`, `root`, `entry`, `percentRoot`, `percentEntry`, + `percentParent`, `label` and `value`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def tiling(self): + """ + The 'tiling' property is an instance of Tiling + that may be specified as: + - An instance of :class:`plotly.graph_objs.treemap.Tiling` + - A dict of string/value properties that will be passed + to the Tiling constructor + + Returns + ------- + plotly.graph_objs.treemap.Tiling + """ + return self["tiling"] + + @tiling.setter + def tiling(self, val): + self["tiling"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def values(self): + """ + Sets the values associated with each of the sectors. Use with + `branchvalues` to determine how the values are summed. + + The 'values' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["values"] + + @values.setter + def values(self, val): + self["values"] = val + + @property + def valuessrc(self): + """ + Sets the source reference on Chart Studio Cloud for `values`. + + The 'valuessrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["valuessrc"] + + @valuessrc.setter + def valuessrc(self, val): + self["valuessrc"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + branchvalues + Determines how the items in `values` are summed. When + set to "total", items in `values` are taken to be value + of all its descendants. When set to "remainder", items + in `values` corresponding to the root and the branches + sectors are taken to be the extra part not part of the + sum of the values at their leaves. + count + Determines default for `values` when it is not + provided, by inferring a 1 for each of the "leaves" + and/or "branches", otherwise 0. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.treemap.Domain` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.treemap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry` and `percentParent`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + labels + Sets the labels of each of the sectors. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.treemap.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + level + Sets the level from which this trace hierarchy is + rendered. Set `level` to `''` to start from the root + node in the hierarchy. Must be an "id" if `ids` is + filled in, otherwise plotly attempts to find a matching + item in `labels`. + marker + :class:`plotly.graph_objects.treemap.Marker` instance + or dict with compatible properties + maxdepth + Sets the number of rendered sectors from any given + `level`. Set `maxdepth` to "-1" to render all the + levels in the hierarchy. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. This option refers to the root of the hierarchy + presented on top left corner of a treemap graph. Please + note that if a hierarchy has multiple root nodes, this + option won't have any effect and `insidetextfont` would + be used. + parents + Sets the parent sectors for each of the sectors. Empty + string items '' are understood to reference the root + node in the hierarchy. If `ids` is filled, `parents` + items are understood to be "ids" themselves. When `ids` + is not set, plotly attempts to find matching items in + `labels`, but beware they must be unique. + parentssrc + Sets the source reference on Chart Studio Cloud for + `parents`. + pathbar + :class:`plotly.graph_objects.treemap.Pathbar` instance + or dict with compatible properties + root + :class:`plotly.graph_objects.treemap.Root` instance or + dict with compatible properties + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.treemap.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Sets the positions of the `text` elements. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry`, `percentParent`, `label` + and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + tiling + :class:`plotly.graph_objects.treemap.Tiling` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values associated with each of the sectors. + Use with `branchvalues` to determine how the values are + summed. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + branchvalues=None, + count=None, + customdata=None, + customdatasrc=None, + domain=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + insidetextfont=None, + labels=None, + labelssrc=None, + legend=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + level=None, + marker=None, + maxdepth=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + outsidetextfont=None, + parents=None, + parentssrc=None, + pathbar=None, + root=None, + sort=None, + stream=None, + text=None, + textfont=None, + textinfo=None, + textposition=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + tiling=None, + uid=None, + uirevision=None, + values=None, + valuessrc=None, + visible=None, + **kwargs, + ): + """ + Construct a new Treemap object + + Visualize hierarchal data from leaves (and/or outer branches) + towards root with rectangles. The treemap sectors are + determined by the entries in "labels" or "ids" and in + "parents". + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Treemap` + branchvalues + Determines how the items in `values` are summed. When + set to "total", items in `values` are taken to be value + of all its descendants. When set to "remainder", items + in `values` corresponding to the root and the branches + sectors are taken to be the extra part not part of the + sum of the values at their leaves. + count + Determines default for `values` when it is not + provided, by inferring a 1 for each of the "leaves" + and/or "branches", otherwise 0. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + domain + :class:`plotly.graph_objects.treemap.Domain` instance + or dict with compatible properties + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.treemap.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry` and `percentParent`. + Anything contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each sector. + If a single string, the same string appears for all + data points. If an array of string, the items are + mapped in order of this trace's sectors. To be seen, + trace `hoverinfo` must contain a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + insidetextfont + Sets the font used for `textinfo` lying inside the + sector. + labels + Sets the labels of each of the sectors. + labelssrc + Sets the source reference on Chart Studio Cloud for + `labels`. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgrouptitle + :class:`plotly.graph_objects.treemap.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + level + Sets the level from which this trace hierarchy is + rendered. Set `level` to `''` to start from the root + node in the hierarchy. Must be an "id" if `ids` is + filled in, otherwise plotly attempts to find a matching + item in `labels`. + marker + :class:`plotly.graph_objects.treemap.Marker` instance + or dict with compatible properties + maxdepth + Sets the number of rendered sectors from any given + `level`. Set `maxdepth` to "-1" to render all the + levels in the hierarchy. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the trace. + outsidetextfont + Sets the font used for `textinfo` lying outside the + sector. This option refers to the root of the hierarchy + presented on top left corner of a treemap graph. Please + note that if a hierarchy has multiple root nodes, this + option won't have any effect and `insidetextfont` would + be used. + parents + Sets the parent sectors for each of the sectors. Empty + string items '' are understood to reference the root + node in the hierarchy. If `ids` is filled, `parents` + items are understood to be "ids" themselves. When `ids` + is not set, plotly attempts to find matching items in + `labels`, but beware they must be unique. + parentssrc + Sets the source reference on Chart Studio Cloud for + `parents`. + pathbar + :class:`plotly.graph_objects.treemap.Pathbar` instance + or dict with compatible properties + root + :class:`plotly.graph_objects.treemap.Root` instance or + dict with compatible properties + sort + Determines whether or not the sectors are reordered + from largest to smallest. + stream + :class:`plotly.graph_objects.treemap.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each sector. If + trace `textinfo` contains a "text" flag, these elements + will be seen on the chart. If trace `hoverinfo` + contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + textfont + Sets the font used for `textinfo`. + textinfo + Determines which trace information appear on the graph. + textposition + Sets the positions of the `text` elements. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `currentPath`, `root`, `entry`, + `percentRoot`, `percentEntry`, `percentParent`, `label` + and `value`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + tiling + :class:`plotly.graph_objects.treemap.Tiling` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + values + Sets the values associated with each of the sectors. + Use with `branchvalues` to determine how the values are + summed. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Treemap + """ + super().__init__("treemap") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Treemap +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Treemap`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("branchvalues", arg, branchvalues) + self._set_property("count", arg, count) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("domain", arg, domain) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("insidetextfont", arg, insidetextfont) + self._set_property("labels", arg, labels) + self._set_property("labelssrc", arg, labelssrc) + self._set_property("legend", arg, legend) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("level", arg, level) + self._set_property("marker", arg, marker) + self._set_property("maxdepth", arg, maxdepth) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("outsidetextfont", arg, outsidetextfont) + self._set_property("parents", arg, parents) + self._set_property("parentssrc", arg, parentssrc) + self._set_property("pathbar", arg, pathbar) + self._set_property("root", arg, root) + self._set_property("sort", arg, sort) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textfont", arg, textfont) + self._set_property("textinfo", arg, textinfo) + self._set_property("textposition", arg, textposition) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("tiling", arg, tiling) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("values", arg, values) + self._set_property("valuessrc", arg, valuessrc) + self._set_property("visible", arg, visible) + + self._props["type"] = "treemap" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_violin.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_violin.py new file mode 100644 index 0000000000000000000000000000000000000000..ca03026d6756cc60fa47aa78c636329b655eca81 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_violin.py @@ -0,0 +1,2313 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Violin(_BaseTraceType): + _parent_path_str = "" + _path_str = "violin" + _valid_props = { + "alignmentgroup", + "bandwidth", + "box", + "customdata", + "customdatasrc", + "fillcolor", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hoveron", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "jitter", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "marker", + "meanline", + "meta", + "metasrc", + "name", + "offsetgroup", + "opacity", + "orientation", + "pointpos", + "points", + "quartilemethod", + "scalegroup", + "scalemode", + "selected", + "selectedpoints", + "showlegend", + "side", + "span", + "spanmode", + "stream", + "text", + "textsrc", + "type", + "uid", + "uirevision", + "unselected", + "visible", + "width", + "x", + "x0", + "xaxis", + "xhoverformat", + "xsrc", + "y", + "y0", + "yaxis", + "yhoverformat", + "ysrc", + "zorder", + } + + @property + def alignmentgroup(self): + """ + Set several traces linked to the same position axis or matching + axes to the same alignmentgroup. This controls whether bars + compute their positional range dependently or independently. + + The 'alignmentgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["alignmentgroup"] + + @alignmentgroup.setter + def alignmentgroup(self, val): + self["alignmentgroup"] = val + + @property + def bandwidth(self): + """ + Sets the bandwidth used to compute the kernel density estimate. + By default, the bandwidth is determined by Silverman's rule of + thumb. + + The 'bandwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["bandwidth"] + + @bandwidth.setter + def bandwidth(self, val): + self["bandwidth"] = val + + @property + def box(self): + """ + The 'box' property is an instance of Box + that may be specified as: + - An instance of :class:`plotly.graph_objs.violin.Box` + - A dict of string/value properties that will be passed + to the Box constructor + + Returns + ------- + plotly.graph_objs.violin.Box + """ + return self["box"] + + @box.setter + def box(self, val): + self["box"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def fillcolor(self): + """ + Sets the fill color. Defaults to a half-transparent variant of + the line color, marker color, or marker line color, whichever + is available. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.violin.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.violin.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hoveron(self): + """ + Do the hover effects highlight individual violins or sample + points or the kernel density estimate or any combination of + them? + + The 'hoveron' property is a flaglist and may be specified + as a string containing: + - Any combination of ['violins', 'points', 'kde'] joined with '+' characters + (e.g. 'violins+points') + OR exactly one of ['all'] (e.g. 'all') + + Returns + ------- + Any + """ + return self["hoveron"] + + @hoveron.setter + def hoveron(self, val): + self["hoveron"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def jitter(self): + """ + Sets the amount of jitter in the sample points drawn. If 0, the + sample points align along the distribution axis. If 1, the + sample points are drawn in a random jitter of width equal to + the width of the violins. + + The 'jitter' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["jitter"] + + @jitter.setter + def jitter(self, val): + self["jitter"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.violin.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.violin.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.violin.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.violin.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.violin.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.violin.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def meanline(self): + """ + The 'meanline' property is an instance of Meanline + that may be specified as: + - An instance of :class:`plotly.graph_objs.violin.Meanline` + - A dict of string/value properties that will be passed + to the Meanline constructor + + Returns + ------- + plotly.graph_objs.violin.Meanline + """ + return self["meanline"] + + @meanline.setter + def meanline(self, val): + self["meanline"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. For violin traces, the name will also be used for + the position coordinate, if `x` and `x0` (`y` and `y0` if + horizontal) are missing and the position axis is categorical. + Note that the trace name is also used as a default value for + attribute `scalegroup` (please see its description for + details). + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def offsetgroup(self): + """ + Set several traces linked to the same position axis or matching + axes to the same offsetgroup where bars of the same position + coordinate will line up. + + The 'offsetgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["offsetgroup"] + + @offsetgroup.setter + def offsetgroup(self, val): + self["offsetgroup"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def orientation(self): + """ + Sets the orientation of the violin(s). If "v" ("h"), the + distribution is visualized along the vertical (horizontal). + + The 'orientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['v', 'h'] + + Returns + ------- + Any + """ + return self["orientation"] + + @orientation.setter + def orientation(self, val): + self["orientation"] = val + + @property + def pointpos(self): + """ + Sets the position of the sample points in relation to the + violins. If 0, the sample points are places over the center of + the violins. Positive (negative) values correspond to positions + to the right (left) for vertical violins and above (below) for + horizontal violins. + + The 'pointpos' property is a number and may be specified as: + - An int or float in the interval [-2, 2] + + Returns + ------- + int|float + """ + return self["pointpos"] + + @pointpos.setter + def pointpos(self, val): + self["pointpos"] = val + + @property + def points(self): + """ + If "outliers", only the sample points lying outside the + whiskers are shown If "suspectedoutliers", the outlier points + are shown and points either less than 4*Q1-3*Q3 or greater than + 4*Q3-3*Q1 are highlighted (see `outliercolor`) If "all", all + sample points are shown If False, only the violins are shown + with no sample points. Defaults to "suspectedoutliers" when + `marker.outliercolor` or `marker.line.outliercolor` is set, + otherwise defaults to "outliers". + + The 'points' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'outliers', 'suspectedoutliers', False] + + Returns + ------- + Any + """ + return self["points"] + + @points.setter + def points(self, val): + self["points"] = val + + @property + def quartilemethod(self): + """ + Sets the method used to compute the sample's Q1 and Q3 + quartiles. The "linear" method uses the 25th percentile for Q1 + and 75th percentile for Q3 as computed using method #10 (listed + on http://jse.amstat.org/v14n3/langford.html). The "exclusive" + method uses the median to divide the ordered dataset into two + halves if the sample is odd, it does not include the median in + either half - Q1 is then the median of the lower half and Q3 + the median of the upper half. The "inclusive" method also uses + the median to divide the ordered dataset into two halves but if + the sample is odd, it includes the median in both halves - Q1 + is then the median of the lower half and Q3 the median of the + upper half. + + The 'quartilemethod' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['linear', 'exclusive', 'inclusive'] + + Returns + ------- + Any + """ + return self["quartilemethod"] + + @quartilemethod.setter + def quartilemethod(self, val): + self["quartilemethod"] = val + + @property + def scalegroup(self): + """ + If there are multiple violins that should be sized according to + to some metric (see `scalemode`), link them by providing a non- + empty group id here shared by every trace in the same group. If + a violin's `width` is undefined, `scalegroup` will default to + the trace's name. In this case, violins with the same names + will be linked together + + The 'scalegroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["scalegroup"] + + @scalegroup.setter + def scalegroup(self, val): + self["scalegroup"] = val + + @property + def scalemode(self): + """ + Sets the metric by which the width of each violin is + determined. "width" means each violin has the same (max) width + "count" means the violins are scaled by the number of sample + points making up each violin. + + The 'scalemode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['width', 'count'] + + Returns + ------- + Any + """ + return self["scalemode"] + + @scalemode.setter + def scalemode(self, val): + self["scalemode"] = val + + @property + def selected(self): + """ + The 'selected' property is an instance of Selected + that may be specified as: + - An instance of :class:`plotly.graph_objs.violin.Selected` + - A dict of string/value properties that will be passed + to the Selected constructor + + Returns + ------- + plotly.graph_objs.violin.Selected + """ + return self["selected"] + + @selected.setter + def selected(self, val): + self["selected"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def side(self): + """ + Determines on which side of the position value the density + function making up one half of a violin is plotted. Useful when + comparing two violin traces under "overlay" mode, where one + trace has `side` set to "positive" and the other to "negative". + + The 'side' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['both', 'positive', 'negative'] + + Returns + ------- + Any + """ + return self["side"] + + @side.setter + def side(self, val): + self["side"] = val + + @property + def span(self): + """ + Sets the span in data space for which the density function will + be computed. Has an effect only when `spanmode` is set to + "manual". + + The 'span' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'span[0]' property accepts values of any type + (1) The 'span[1]' property accepts values of any type + + Returns + ------- + list + """ + return self["span"] + + @span.setter + def span(self, val): + self["span"] = val + + @property + def spanmode(self): + """ + Sets the method by which the span in data space where the + density function will be computed. "soft" means the span goes + from the sample's minimum value minus two bandwidths to the + sample's maximum value plus two bandwidths. "hard" means the + span goes from the sample's minimum to its maximum value. For + custom span settings, use mode "manual" and fill in the `span` + attribute. + + The 'spanmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['soft', 'hard', 'manual'] + + Returns + ------- + Any + """ + return self["spanmode"] + + @spanmode.setter + def spanmode(self, val): + self["spanmode"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.violin.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.violin.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets the text elements associated with each sample value. If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (x,y) coordinates. To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unselected(self): + """ + The 'unselected' property is an instance of Unselected + that may be specified as: + - An instance of :class:`plotly.graph_objs.violin.Unselected` + - A dict of string/value properties that will be passed + to the Unselected constructor + + Returns + ------- + plotly.graph_objs.violin.Unselected + """ + return self["unselected"] + + @unselected.setter + def unselected(self, val): + self["unselected"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def width(self): + """ + Sets the width of the violin in data coordinates. If 0 (default + value) the width is automatically selected based on the + positions of other violin traces in the same subplot. + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def x(self): + """ + Sets the x sample data or coordinates. See overview for more + info. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def x0(self): + """ + Sets the x coordinate for single-box traces or the starting + coordinate for multi-box traces set using q1/median/q3. See + overview for more info. + + The 'x0' property accepts values of any type + + Returns + ------- + Any + """ + return self["x0"] + + @x0.setter + def x0(self, val): + self["x0"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the y sample data or coordinates. See overview for more + info. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def y0(self): + """ + Sets the y coordinate for single-box traces or the starting + coordinate for multi-box traces set using q1/median/q3. See + overview for more info. + + The 'y0' property accepts values of any type + + Returns + ------- + Any + """ + return self["y0"] + + @y0.setter + def y0(self, val): + self["y0"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def zorder(self): + """ + Sets the layer on which this trace is displayed, relative to + other SVG traces on the same subplot. SVG traces with higher + `zorder` appear in front of those with lower `zorder`. + + The 'zorder' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["zorder"] + + @zorder.setter + def zorder(self, val): + self["zorder"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + bandwidth + Sets the bandwidth used to compute the kernel density + estimate. By default, the bandwidth is determined by + Silverman's rule of thumb. + box + :class:`plotly.graph_objects.violin.Box` instance or + dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.violin.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual violins or + sample points or the kernel density estimate or any + combination of them? + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + jitter + Sets the amount of jitter in the sample points drawn. + If 0, the sample points align along the distribution + axis. If 1, the sample points are drawn in a random + jitter of width equal to the width of the violins. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.violin.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.violin.Line` instance or + dict with compatible properties + marker + :class:`plotly.graph_objects.violin.Marker` instance or + dict with compatible properties + meanline + :class:`plotly.graph_objects.violin.Meanline` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. For violin traces, the name + will also be used for the position coordinate, if `x` + and `x0` (`y` and `y0` if horizontal) are missing and + the position axis is categorical. Note that the trace + name is also used as a default value for attribute + `scalegroup` (please see its description for details). + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the violin(s). If "v" ("h"), + the distribution is visualized along the vertical + (horizontal). + pointpos + Sets the position of the sample points in relation to + the violins. If 0, the sample points are places over + the center of the violins. Positive (negative) values + correspond to positions to the right (left) for + vertical violins and above (below) for horizontal + violins. + points + If "outliers", only the sample points lying outside the + whiskers are shown If "suspectedoutliers", the outlier + points are shown and points either less than 4*Q1-3*Q3 + or greater than 4*Q3-3*Q1 are highlighted (see + `outliercolor`) If "all", all sample points are shown + If False, only the violins are shown with no sample + points. Defaults to "suspectedoutliers" when + `marker.outliercolor` or `marker.line.outliercolor` is + set, otherwise defaults to "outliers". + quartilemethod + Sets the method used to compute the sample's Q1 and Q3 + quartiles. The "linear" method uses the 25th percentile + for Q1 and 75th percentile for Q3 as computed using + method #10 (listed on + http://jse.amstat.org/v14n3/langford.html). The + "exclusive" method uses the median to divide the + ordered dataset into two halves if the sample is odd, + it does not include the median in either half - Q1 is + then the median of the lower half and Q3 the median of + the upper half. The "inclusive" method also uses the + median to divide the ordered dataset into two halves + but if the sample is odd, it includes the median in + both halves - Q1 is then the median of the lower half + and Q3 the median of the upper half. + scalegroup + If there are multiple violins that should be sized + according to to some metric (see `scalemode`), link + them by providing a non-empty group id here shared by + every trace in the same group. If a violin's `width` is + undefined, `scalegroup` will default to the trace's + name. In this case, violins with the same names will be + linked together + scalemode + Sets the metric by which the width of each violin is + determined. "width" means each violin has the same + (max) width "count" means the violins are scaled by the + number of sample points making up each violin. + selected + :class:`plotly.graph_objects.violin.Selected` instance + or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + side + Determines on which side of the position value the + density function making up one half of a violin is + plotted. Useful when comparing two violin traces under + "overlay" mode, where one trace has `side` set to + "positive" and the other to "negative". + span + Sets the span in data space for which the density + function will be computed. Has an effect only when + `spanmode` is set to "manual". + spanmode + Sets the method by which the span in data space where + the density function will be computed. "soft" means the + span goes from the sample's minimum value minus two + bandwidths to the sample's maximum value plus two + bandwidths. "hard" means the span goes from the + sample's minimum to its maximum value. For custom span + settings, use mode "manual" and fill in the `span` + attribute. + stream + :class:`plotly.graph_objects.violin.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with each sample + value. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.violin.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the width of the violin in data coordinates. If 0 + (default value) the width is automatically selected + based on the positions of other violin traces in the + same subplot. + x + Sets the x sample data or coordinates. See overview for + more info. + x0 + Sets the x coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y sample data or coordinates. See overview for + more info. + y0 + Sets the y coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + """ + + def __init__( + self, + arg=None, + alignmentgroup=None, + bandwidth=None, + box=None, + customdata=None, + customdatasrc=None, + fillcolor=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hoveron=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + jitter=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + marker=None, + meanline=None, + meta=None, + metasrc=None, + name=None, + offsetgroup=None, + opacity=None, + orientation=None, + pointpos=None, + points=None, + quartilemethod=None, + scalegroup=None, + scalemode=None, + selected=None, + selectedpoints=None, + showlegend=None, + side=None, + span=None, + spanmode=None, + stream=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + unselected=None, + visible=None, + width=None, + x=None, + x0=None, + xaxis=None, + xhoverformat=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + yhoverformat=None, + ysrc=None, + zorder=None, + **kwargs, + ): + """ + Construct a new Violin object + + In vertical (horizontal) violin plots, statistics are computed + using `y` (`x`) values. By supplying an `x` (`y`) array, one + violin per distinct x (y) value is drawn If no `x` (`y`) list + is provided, a single violin is drawn. That violin position is + then positioned with with `name` or with `x0` (`y0`) if + provided. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Violin` + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + bandwidth + Sets the bandwidth used to compute the kernel density + estimate. By default, the bandwidth is determined by + Silverman's rule of thumb. + box + :class:`plotly.graph_objects.violin.Box` instance or + dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + fillcolor + Sets the fill color. Defaults to a half-transparent + variant of the line color, marker color, or marker line + color, whichever is available. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.violin.Hoverlabel` + instance or dict with compatible properties + hoveron + Do the hover effects highlight individual violins or + sample points or the kernel density estimate or any + combination of them? + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + jitter + Sets the amount of jitter in the sample points drawn. + If 0, the sample points align along the distribution + axis. If 1, the sample points are drawn in a random + jitter of width equal to the width of the violins. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.violin.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + line + :class:`plotly.graph_objects.violin.Line` instance or + dict with compatible properties + marker + :class:`plotly.graph_objects.violin.Marker` instance or + dict with compatible properties + meanline + :class:`plotly.graph_objects.violin.Meanline` instance + or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. For violin traces, the name + will also be used for the position coordinate, if `x` + and `x0` (`y` and `y0` if horizontal) are missing and + the position axis is categorical. Note that the trace + name is also used as a default value for attribute + `scalegroup` (please see its description for details). + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the violin(s). If "v" ("h"), + the distribution is visualized along the vertical + (horizontal). + pointpos + Sets the position of the sample points in relation to + the violins. If 0, the sample points are places over + the center of the violins. Positive (negative) values + correspond to positions to the right (left) for + vertical violins and above (below) for horizontal + violins. + points + If "outliers", only the sample points lying outside the + whiskers are shown If "suspectedoutliers", the outlier + points are shown and points either less than 4*Q1-3*Q3 + or greater than 4*Q3-3*Q1 are highlighted (see + `outliercolor`) If "all", all sample points are shown + If False, only the violins are shown with no sample + points. Defaults to "suspectedoutliers" when + `marker.outliercolor` or `marker.line.outliercolor` is + set, otherwise defaults to "outliers". + quartilemethod + Sets the method used to compute the sample's Q1 and Q3 + quartiles. The "linear" method uses the 25th percentile + for Q1 and 75th percentile for Q3 as computed using + method #10 (listed on + http://jse.amstat.org/v14n3/langford.html). The + "exclusive" method uses the median to divide the + ordered dataset into two halves if the sample is odd, + it does not include the median in either half - Q1 is + then the median of the lower half and Q3 the median of + the upper half. The "inclusive" method also uses the + median to divide the ordered dataset into two halves + but if the sample is odd, it includes the median in + both halves - Q1 is then the median of the lower half + and Q3 the median of the upper half. + scalegroup + If there are multiple violins that should be sized + according to to some metric (see `scalemode`), link + them by providing a non-empty group id here shared by + every trace in the same group. If a violin's `width` is + undefined, `scalegroup` will default to the trace's + name. In this case, violins with the same names will be + linked together + scalemode + Sets the metric by which the width of each violin is + determined. "width" means each violin has the same + (max) width "count" means the violins are scaled by the + number of sample points making up each violin. + selected + :class:`plotly.graph_objects.violin.Selected` instance + or dict with compatible properties + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + side + Determines on which side of the position value the + density function making up one half of a violin is + plotted. Useful when comparing two violin traces under + "overlay" mode, where one trace has `side` set to + "positive" and the other to "negative". + span + Sets the span in data space for which the density + function will be computed. Has an effect only when + `spanmode` is set to "manual". + spanmode + Sets the method by which the span in data space where + the density function will be computed. "soft" means the + span goes from the sample's minimum value minus two + bandwidths to the sample's maximum value plus two + bandwidths. "hard" means the span goes from the + sample's minimum to its maximum value. For custom span + settings, use mode "manual" and fill in the `span` + attribute. + stream + :class:`plotly.graph_objects.violin.Stream` instance or + dict with compatible properties + text + Sets the text elements associated with each sample + value. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + unselected + :class:`plotly.graph_objects.violin.Unselected` + instance or dict with compatible properties + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the width of the violin in data coordinates. If 0 + (default value) the width is automatically selected + based on the positions of other violin traces in the + same subplot. + x + Sets the x sample data or coordinates. See overview for + more info. + x0 + Sets the x coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y sample data or coordinates. See overview for + more info. + y0 + Sets the y coordinate for single-box traces or the + starting coordinate for multi-box traces set using + q1/median/q3. See overview for more info. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + + Returns + ------- + Violin + """ + super().__init__("violin") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Violin +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Violin`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("alignmentgroup", arg, alignmentgroup) + self._set_property("bandwidth", arg, bandwidth) + self._set_property("box", arg, box) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hoveron", arg, hoveron) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("jitter", arg, jitter) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("marker", arg, marker) + self._set_property("meanline", arg, meanline) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("offsetgroup", arg, offsetgroup) + self._set_property("opacity", arg, opacity) + self._set_property("orientation", arg, orientation) + self._set_property("pointpos", arg, pointpos) + self._set_property("points", arg, points) + self._set_property("quartilemethod", arg, quartilemethod) + self._set_property("scalegroup", arg, scalegroup) + self._set_property("scalemode", arg, scalemode) + self._set_property("selected", arg, selected) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("side", arg, side) + self._set_property("span", arg, span) + self._set_property("spanmode", arg, spanmode) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("unselected", arg, unselected) + self._set_property("visible", arg, visible) + self._set_property("width", arg, width) + self._set_property("x", arg, x) + self._set_property("x0", arg, x0) + self._set_property("xaxis", arg, xaxis) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("y0", arg, y0) + self._set_property("yaxis", arg, yaxis) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("ysrc", arg, ysrc) + self._set_property("zorder", arg, zorder) + + self._props["type"] = "violin" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_volume.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_volume.py new file mode 100644 index 0000000000000000000000000000000000000000..28edde3a074ff6b14f79c6388c8ca9f17ee230a5 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_volume.py @@ -0,0 +1,2260 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Volume(_BaseTraceType): + _parent_path_str = "" + _path_str = "volume" + _valid_props = { + "autocolorscale", + "caps", + "cauto", + "cmax", + "cmid", + "cmin", + "coloraxis", + "colorbar", + "colorscale", + "contour", + "customdata", + "customdatasrc", + "flatshading", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "isomax", + "isomin", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "lighting", + "lightposition", + "meta", + "metasrc", + "name", + "opacity", + "opacityscale", + "reversescale", + "scene", + "showlegend", + "showscale", + "slices", + "spaceframe", + "stream", + "surface", + "text", + "textsrc", + "type", + "uid", + "uirevision", + "value", + "valuehoverformat", + "valuesrc", + "visible", + "x", + "xhoverformat", + "xsrc", + "y", + "yhoverformat", + "ysrc", + "z", + "zhoverformat", + "zsrc", + } + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def caps(self): + """ + The 'caps' property is an instance of Caps + that may be specified as: + - An instance of :class:`plotly.graph_objs.volume.Caps` + - A dict of string/value properties that will be passed + to the Caps constructor + + Returns + ------- + plotly.graph_objs.volume.Caps + """ + return self["caps"] + + @caps.setter + def caps(self, val): + self["caps"] = val + + @property + def cauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here `value`) or the bounds set in + `cmin` and `cmax` Defaults to `false` when `cmin` and `cmax` + are set by the user. + + The 'cauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cauto"] + + @cauto.setter + def cauto(self, val): + self["cauto"] = val + + @property + def cmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as `value` and if set, `cmin` must be set as well. + + The 'cmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmax"] + + @cmax.setter + def cmax(self, val): + self["cmax"] = val + + @property + def cmid(self): + """ + Sets the mid-point of the color domain by scaling `cmin` and/or + `cmax` to be equidistant to this point. Value should have the + same units as `value`. Has no effect when `cauto` is `false`. + + The 'cmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmid"] + + @cmid.setter + def cmid(self, val): + self["cmid"] = val + + @property + def cmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as `value` and if set, `cmax` must be set as well. + + The 'cmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmin"] + + @cmin.setter + def cmin(self, val): + self["cmin"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.volume.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.volume.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def contour(self): + """ + The 'contour' property is an instance of Contour + that may be specified as: + - An instance of :class:`plotly.graph_objs.volume.Contour` + - A dict of string/value properties that will be passed + to the Contour constructor + + Returns + ------- + plotly.graph_objs.volume.Contour + """ + return self["contour"] + + @contour.setter + def contour(self, val): + self["contour"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def flatshading(self): + """ + Determines whether or not normal smoothing is applied to the + meshes, creating meshes with an angular, low-poly look via flat + reflections. + + The 'flatshading' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["flatshading"] + + @flatshading.setter + def flatshading(self, val): + self["flatshading"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['x', 'y', 'z', 'text', 'name'] joined with '+' characters + (e.g. 'x+y') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.volume.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.volume.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Anything contained in tag `` is displayed in the + secondary box, for example `%{fullData.name}`. + To hide the secondary box completely, use an empty tag + ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Same as `text`. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def isomax(self): + """ + Sets the maximum boundary for iso-surface plot. + + The 'isomax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["isomax"] + + @isomax.setter + def isomax(self, val): + self["isomax"] = val + + @property + def isomin(self): + """ + Sets the minimum boundary for iso-surface plot. + + The 'isomin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["isomin"] + + @isomin.setter + def isomin(self, val): + self["isomin"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.volume.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.volume.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def lighting(self): + """ + The 'lighting' property is an instance of Lighting + that may be specified as: + - An instance of :class:`plotly.graph_objs.volume.Lighting` + - A dict of string/value properties that will be passed + to the Lighting constructor + + Returns + ------- + plotly.graph_objs.volume.Lighting + """ + return self["lighting"] + + @lighting.setter + def lighting(self, val): + self["lighting"] = val + + @property + def lightposition(self): + """ + The 'lightposition' property is an instance of Lightposition + that may be specified as: + - An instance of :class:`plotly.graph_objs.volume.Lightposition` + - A dict of string/value properties that will be passed + to the Lightposition constructor + + Returns + ------- + plotly.graph_objs.volume.Lightposition + """ + return self["lightposition"] + + @lightposition.setter + def lightposition(self, val): + self["lightposition"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the surface. Please note that in the case + of using high `opacity` values for example a value greater than + or equal to 0.5 on two surfaces (and 0.25 with four surfaces), + an overlay of multiple transparent surfaces may not perfectly + be sorted in depth by the webgl API. This behavior may be + improved in the near future and is subject to change. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def opacityscale(self): + """ + Sets the opacityscale. The opacityscale must be an array + containing arrays mapping a normalized value to an opacity + value. At minimum, a mapping for the lowest (0) and highest (1) + values are required. For example, `[[0, 1], [0.5, 0.2], [1, + 1]]` means that higher/lower values would have higher opacity + values and those in the middle would be more transparent + Alternatively, `opacityscale` may be a palette name string of + the following list: 'min', 'max', 'extremes' and 'uniform'. The + default is 'uniform'. + + The 'opacityscale' property accepts values of any type + + Returns + ------- + Any + """ + return self["opacityscale"] + + @opacityscale.setter + def opacityscale(self, val): + self["opacityscale"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `cmin` will + correspond to the last color in the array and `cmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def scene(self): + """ + Sets a reference between this trace's 3D coordinate system and + a 3D scene. If "scene" (the default value), the (x,y,z) + coordinates refer to `layout.scene`. If "scene2", the (x,y,z) + coordinates refer to `layout.scene2`, and so on. + + The 'scene' property is an identifier of a particular + subplot, of type 'scene', that may be specified as: + - the string 'scene' optionally followed by an integer >= 1 + (e.g. 'scene', 'scene1', 'scene2', 'scene3', etc.) + + Returns + ------- + str + """ + return self["scene"] + + @scene.setter + def scene(self, val): + self["scene"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def slices(self): + """ + The 'slices' property is an instance of Slices + that may be specified as: + - An instance of :class:`plotly.graph_objs.volume.Slices` + - A dict of string/value properties that will be passed + to the Slices constructor + + Returns + ------- + plotly.graph_objs.volume.Slices + """ + return self["slices"] + + @slices.setter + def slices(self, val): + self["slices"] = val + + @property + def spaceframe(self): + """ + The 'spaceframe' property is an instance of Spaceframe + that may be specified as: + - An instance of :class:`plotly.graph_objs.volume.Spaceframe` + - A dict of string/value properties that will be passed + to the Spaceframe constructor + + Returns + ------- + plotly.graph_objs.volume.Spaceframe + """ + return self["spaceframe"] + + @spaceframe.setter + def spaceframe(self, val): + self["spaceframe"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.volume.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.volume.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def surface(self): + """ + The 'surface' property is an instance of Surface + that may be specified as: + - An instance of :class:`plotly.graph_objs.volume.Surface` + - A dict of string/value properties that will be passed + to the Surface constructor + + Returns + ------- + plotly.graph_objs.volume.Surface + """ + return self["surface"] + + @surface.setter + def surface(self, val): + self["surface"] = val + + @property + def text(self): + """ + Sets the text elements associated with the vertices. If trace + `hoverinfo` contains a "text" flag and "hovertext" is not set, + these elements will be seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def value(self): + """ + Sets the 4th dimension (value) of the vertices. + + The 'value' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["value"] + + @value.setter + def value(self, val): + self["value"] = val + + @property + def valuehoverformat(self): + """ + Sets the hover text formatting rulefor `value` using d3 + formatting mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format.By + default the values are formatted using generic number format. + + The 'valuehoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["valuehoverformat"] + + @valuehoverformat.setter + def valuehoverformat(self, val): + self["valuehoverformat"] = val + + @property + def valuesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `value`. + + The 'valuesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["valuesrc"] + + @valuesrc.setter + def valuesrc(self, val): + self["valuesrc"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the X coordinates of the vertices on X axis. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the Y coordinates of the vertices on Y axis. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def z(self): + """ + Sets the Z coordinates of the vertices on Z axis. + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zhoverformat(self): + """ + Sets the hover text formatting rulefor `z` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `zaxis.hoverformat`. + + The 'zhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["zhoverformat"] + + @zhoverformat.setter + def zhoverformat(self, val): + self["zhoverformat"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + caps + :class:`plotly.graph_objects.volume.Caps` instance or + dict with compatible properties + cauto + Determines whether or not the color domain is computed + with respect to the input data (here `value`) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as `value` and if set, `cmin` must + be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as `value`. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as `value` and if set, `cmax` must + be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.volume.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contour + :class:`plotly.graph_objects.volume.Contour` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + flatshading + Determines whether or not normal smoothing is applied + to the meshes, creating meshes with an angular, low- + poly look via flat reflections. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.volume.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + isomax + Sets the maximum boundary for iso-surface plot. + isomin + Sets the minimum boundary for iso-surface plot. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.volume.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.volume.Lighting` instance + or dict with compatible properties + lightposition + :class:`plotly.graph_objects.volume.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + opacityscale + Sets the opacityscale. The opacityscale must be an + array containing arrays mapping a normalized value to + an opacity value. At minimum, a mapping for the lowest + (0) and highest (1) values are required. For example, + `[[0, 1], [0.5, 0.2], [1, 1]]` means that higher/lower + values would have higher opacity values and those in + the middle would be more transparent Alternatively, + `opacityscale` may be a palette name string of the + following list: 'min', 'max', 'extremes' and 'uniform'. + The default is 'uniform'. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + slices + :class:`plotly.graph_objects.volume.Slices` instance or + dict with compatible properties + spaceframe + :class:`plotly.graph_objects.volume.Spaceframe` + instance or dict with compatible properties + stream + :class:`plotly.graph_objects.volume.Stream` instance or + dict with compatible properties + surface + :class:`plotly.graph_objects.volume.Surface` instance + or dict with compatible properties + text + Sets the text elements associated with the vertices. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + value + Sets the 4th dimension (value) of the vertices. + valuehoverformat + Sets the hover text formatting rulefor `value` using + d3 formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + valuesrc + Sets the source reference on Chart Studio Cloud for + `value`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the X coordinates of the vertices on X axis. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the Y coordinates of the vertices on Y axis. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the Z coordinates of the vertices on Z axis. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + autocolorscale=None, + caps=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + coloraxis=None, + colorbar=None, + colorscale=None, + contour=None, + customdata=None, + customdatasrc=None, + flatshading=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + isomax=None, + isomin=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + lighting=None, + lightposition=None, + meta=None, + metasrc=None, + name=None, + opacity=None, + opacityscale=None, + reversescale=None, + scene=None, + showlegend=None, + showscale=None, + slices=None, + spaceframe=None, + stream=None, + surface=None, + text=None, + textsrc=None, + uid=None, + uirevision=None, + value=None, + valuehoverformat=None, + valuesrc=None, + visible=None, + x=None, + xhoverformat=None, + xsrc=None, + y=None, + yhoverformat=None, + ysrc=None, + z=None, + zhoverformat=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Volume object + + Draws volume trace between iso-min and iso-max values with + coordinates given by four 1-dimensional arrays containing the + `value`, `x`, `y` and `z` of every vertex of a uniform or non- + uniform 3-D grid. Horizontal or vertical slices, caps as well + as spaceframe between iso-min and iso-max values could also be + drawn using this trace. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Volume` + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + caps + :class:`plotly.graph_objects.volume.Caps` instance or + dict with compatible properties + cauto + Determines whether or not the color domain is computed + with respect to the input data (here `value`) or the + bounds set in `cmin` and `cmax` Defaults to `false` + when `cmin` and `cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as `value` and if set, `cmin` must + be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as `value`. Has no + effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as `value` and if set, `cmax` must + be set as well. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.volume.ColorBar` instance + or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + contour + :class:`plotly.graph_objects.volume.Contour` instance + or dict with compatible properties + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + flatshading + Determines whether or not normal smoothing is applied + to the meshes, creating meshes with an angular, low- + poly look via flat reflections. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.volume.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Same as `text`. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + isomax + Sets the maximum boundary for iso-surface plot. + isomin + Sets the minimum boundary for iso-surface plot. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.volume.Legendgrouptitle` + instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + lighting + :class:`plotly.graph_objects.volume.Lighting` instance + or dict with compatible properties + lightposition + :class:`plotly.graph_objects.volume.Lightposition` + instance or dict with compatible properties + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + opacity + Sets the opacity of the surface. Please note that in + the case of using high `opacity` values for example a + value greater than or equal to 0.5 on two surfaces (and + 0.25 with four surfaces), an overlay of multiple + transparent surfaces may not perfectly be sorted in + depth by the webgl API. This behavior may be improved + in the near future and is subject to change. + opacityscale + Sets the opacityscale. The opacityscale must be an + array containing arrays mapping a normalized value to + an opacity value. At minimum, a mapping for the lowest + (0) and highest (1) values are required. For example, + `[[0, 1], [0.5, 0.2], [1, 1]]` means that higher/lower + values would have higher opacity values and those in + the middle would be more transparent Alternatively, + `opacityscale` may be a palette name string of the + following list: 'min', 'max', 'extremes' and 'uniform'. + The default is 'uniform'. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + scene + Sets a reference between this trace's 3D coordinate + system and a 3D scene. If "scene" (the default value), + the (x,y,z) coordinates refer to `layout.scene`. If + "scene2", the (x,y,z) coordinates refer to + `layout.scene2`, and so on. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + showscale + Determines whether or not a colorbar is displayed for + this trace. + slices + :class:`plotly.graph_objects.volume.Slices` instance or + dict with compatible properties + spaceframe + :class:`plotly.graph_objects.volume.Spaceframe` + instance or dict with compatible properties + stream + :class:`plotly.graph_objects.volume.Stream` instance or + dict with compatible properties + surface + :class:`plotly.graph_objects.volume.Surface` instance + or dict with compatible properties + text + Sets the text elements associated with the vertices. If + trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + value + Sets the 4th dimension (value) of the vertices. + valuehoverformat + Sets the hover text formatting rulefor `value` using + d3 formatting mini-languages which are very similar to + those in Python. For numbers, see: https://github.com/d + 3/d3-format/tree/v1.4.5#d3-format.By default the values + are formatted using generic number format. + valuesrc + Sets the source reference on Chart Studio Cloud for + `value`. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x + Sets the X coordinates of the vertices on X axis. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the Y coordinates of the vertices on Y axis. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the Z coordinates of the vertices on Z axis. + zhoverformat + Sets the hover text formatting rulefor `z` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `zaxis.hoverformat`. + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Volume + """ + super().__init__("volume") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Volume +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Volume`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("caps", arg, caps) + self._set_property("cauto", arg, cauto) + self._set_property("cmax", arg, cmax) + self._set_property("cmid", arg, cmid) + self._set_property("cmin", arg, cmin) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("contour", arg, contour) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("flatshading", arg, flatshading) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("isomax", arg, isomax) + self._set_property("isomin", arg, isomin) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("lighting", arg, lighting) + self._set_property("lightposition", arg, lightposition) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("opacityscale", arg, opacityscale) + self._set_property("reversescale", arg, reversescale) + self._set_property("scene", arg, scene) + self._set_property("showlegend", arg, showlegend) + self._set_property("showscale", arg, showscale) + self._set_property("slices", arg, slices) + self._set_property("spaceframe", arg, spaceframe) + self._set_property("stream", arg, stream) + self._set_property("surface", arg, surface) + self._set_property("text", arg, text) + self._set_property("textsrc", arg, textsrc) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("value", arg, value) + self._set_property("valuehoverformat", arg, valuehoverformat) + self._set_property("valuesrc", arg, valuesrc) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("ysrc", arg, ysrc) + self._set_property("z", arg, z) + self._set_property("zhoverformat", arg, zhoverformat) + self._set_property("zsrc", arg, zsrc) + + self._props["type"] = "volume" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_waterfall.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_waterfall.py new file mode 100644 index 0000000000000000000000000000000000000000..ad71ced965275d2426389e31cafa0f680016b370 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/_waterfall.py @@ -0,0 +1,2674 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceType as _BaseTraceType +import copy as _copy + + +class Waterfall(_BaseTraceType): + _parent_path_str = "" + _path_str = "waterfall" + _valid_props = { + "alignmentgroup", + "base", + "cliponaxis", + "connector", + "constraintext", + "customdata", + "customdatasrc", + "decreasing", + "dx", + "dy", + "hoverinfo", + "hoverinfosrc", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "hovertext", + "hovertextsrc", + "ids", + "idssrc", + "increasing", + "insidetextanchor", + "insidetextfont", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "measure", + "measuresrc", + "meta", + "metasrc", + "name", + "offset", + "offsetgroup", + "offsetsrc", + "opacity", + "orientation", + "outsidetextfont", + "selectedpoints", + "showlegend", + "stream", + "text", + "textangle", + "textfont", + "textinfo", + "textposition", + "textpositionsrc", + "textsrc", + "texttemplate", + "texttemplatefallback", + "texttemplatesrc", + "totals", + "type", + "uid", + "uirevision", + "visible", + "width", + "widthsrc", + "x", + "x0", + "xaxis", + "xhoverformat", + "xperiod", + "xperiod0", + "xperiodalignment", + "xsrc", + "y", + "y0", + "yaxis", + "yhoverformat", + "yperiod", + "yperiod0", + "yperiodalignment", + "ysrc", + "zorder", + } + + @property + def alignmentgroup(self): + """ + Set several traces linked to the same position axis or matching + axes to the same alignmentgroup. This controls whether bars + compute their positional range dependently or independently. + + The 'alignmentgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["alignmentgroup"] + + @alignmentgroup.setter + def alignmentgroup(self, val): + self["alignmentgroup"] = val + + @property + def base(self): + """ + Sets where the bar base is drawn (in position axis units). + + The 'base' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["base"] + + @base.setter + def base(self, val): + self["base"] = val + + @property + def cliponaxis(self): + """ + Determines whether the text nodes are clipped about the subplot + axes. To show the text nodes above axis lines and tick labels, + make sure to set `xaxis.layer` and `yaxis.layer` to *below + traces*. + + The 'cliponaxis' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cliponaxis"] + + @cliponaxis.setter + def cliponaxis(self, val): + self["cliponaxis"] = val + + @property + def connector(self): + """ + The 'connector' property is an instance of Connector + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.Connector` + - A dict of string/value properties that will be passed + to the Connector constructor + + Returns + ------- + plotly.graph_objs.waterfall.Connector + """ + return self["connector"] + + @connector.setter + def connector(self, val): + self["connector"] = val + + @property + def constraintext(self): + """ + Constrain the size of text inside or outside a bar to be no + larger than the bar itself. + + The 'constraintext' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['inside', 'outside', 'both', 'none'] + + Returns + ------- + Any + """ + return self["constraintext"] + + @constraintext.setter + def constraintext(self, val): + self["constraintext"] = val + + @property + def customdata(self): + """ + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note that, + "scatter" traces also appends customdata items in the markers + DOM elements + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def decreasing(self): + """ + The 'decreasing' property is an instance of Decreasing + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.Decreasing` + - A dict of string/value properties that will be passed + to the Decreasing constructor + + Returns + ------- + plotly.graph_objs.waterfall.Decreasing + """ + return self["decreasing"] + + @decreasing.setter + def decreasing(self, val): + self["decreasing"] = val + + @property + def dx(self): + """ + Sets the x coordinate step. See `x0` for more info. + + The 'dx' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dx"] + + @dx.setter + def dx(self, val): + self["dx"] = val + + @property + def dy(self): + """ + Sets the y coordinate step. See `y0` for more info. + + The 'dy' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dy"] + + @dy.setter + def dy(self, val): + self["dy"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear on hover. If `none` + or `skip` are set, no information is displayed upon hovering. + But, if `none` is set, click and hover events are still fired. + + The 'hoverinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['name', 'x', 'y', 'text', 'initial', 'delta', 'final'] joined with '+' characters + (e.g. 'name+x') + OR exactly one of ['all', 'none', 'skip'] (e.g. 'skip') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverinfosrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + + The 'hoverinfosrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hoverinfosrc"] + + @hoverinfosrc.setter + def hoverinfosrc(self, val): + self["hoverinfosrc"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.waterfall.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables `initial`, + `delta` and `final`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def hovertext(self): + """ + Sets hover text elements associated with each (x,y) pair. If a + single string, the same string appears over all the data + points. If an array of string, the items are mapped in order to + the this trace's (x,y) coordinates. To be seen, trace + `hoverinfo` must contain a "text" flag. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def hovertextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertext`. + + The 'hovertextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertextsrc"] + + @hovertextsrc.setter + def hovertextsrc(self, val): + self["hovertextsrc"] = val + + @property + def ids(self): + """ + Assigns id labels to each datum. These ids for object constancy + of data points during animation. Should be an array of strings, + not numbers or any other type. + + The 'ids' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ids"] + + @ids.setter + def ids(self, val): + self["ids"] = val + + @property + def idssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ids`. + + The 'idssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["idssrc"] + + @idssrc.setter + def idssrc(self, val): + self["idssrc"] = val + + @property + def increasing(self): + """ + The 'increasing' property is an instance of Increasing + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.Increasing` + - A dict of string/value properties that will be passed + to the Increasing constructor + + Returns + ------- + plotly.graph_objs.waterfall.Increasing + """ + return self["increasing"] + + @increasing.setter + def increasing(self, val): + self["increasing"] = val + + @property + def insidetextanchor(self): + """ + Determines if texts are kept at center or start/end points in + `textposition` "inside" mode. + + The 'insidetextanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['end', 'middle', 'start'] + + Returns + ------- + Any + """ + return self["insidetextanchor"] + + @insidetextanchor.setter + def insidetextanchor(self, val): + self["insidetextanchor"] = val + + @property + def insidetextfont(self): + """ + Sets the font used for `text` lying inside the bar. + + The 'insidetextfont' property is an instance of Insidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.Insidetextfont` + - A dict of string/value properties that will be passed + to the Insidetextfont constructor + + Returns + ------- + plotly.graph_objs.waterfall.Insidetextfont + """ + return self["insidetextfont"] + + @insidetextfont.setter + def insidetextfont(self, val): + self["insidetextfont"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this trace. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.waterfall.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this trace. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + trace. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def measure(self): + """ + An array containing types of values. By default the values are + considered as 'relative'. However; it is possible to use + 'total' to compute the sums. Also 'absolute' could be applied + to reset the computed total or to declare an initial value + where needed. + + The 'measure' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["measure"] + + @measure.setter + def measure(self, val): + self["measure"] = val + + @property + def measuresrc(self): + """ + Sets the source reference on Chart Studio Cloud for `measure`. + + The 'measuresrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["measuresrc"] + + @measuresrc.setter + def measuresrc(self, val): + self["measuresrc"] = val + + @property + def meta(self): + """ + Assigns extra meta information associated with this trace that + can be used in various text attributes. Attributes such as + trace `name`, graph, axis and colorbar `title.text`, annotation + `text` `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` values in + an attribute in the same trace, simply use `%{meta[i]}` where + `i` is the index or key of the `meta` item in question. To + access trace `meta` in layout attributes, use + `%{data[n[.meta[i]}` where `i` is the index or key of the + `meta` and `n` is the trace index. + + The 'meta' property accepts values of any type + + Returns + ------- + Any|numpy.ndarray + """ + return self["meta"] + + @meta.setter + def meta(self, val): + self["meta"] = val + + @property + def metasrc(self): + """ + Sets the source reference on Chart Studio Cloud for `meta`. + + The 'metasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["metasrc"] + + @metasrc.setter + def metasrc(self, val): + self["metasrc"] = val + + @property + def name(self): + """ + Sets the trace name. The trace name appears as the legend item + and on hover. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def offset(self): + """ + Shifts the position where the bar is drawn (in position axis + units). In "group" barmode, traces that set "offset" will be + excluded and drawn in "overlay" mode instead. + + The 'offset' property is a number and may be specified as: + - An int or float + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["offset"] + + @offset.setter + def offset(self, val): + self["offset"] = val + + @property + def offsetgroup(self): + """ + Set several traces linked to the same position axis or matching + axes to the same offsetgroup where bars of the same position + coordinate will line up. + + The 'offsetgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["offsetgroup"] + + @offsetgroup.setter + def offsetgroup(self, val): + self["offsetgroup"] = val + + @property + def offsetsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `offset`. + + The 'offsetsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["offsetsrc"] + + @offsetsrc.setter + def offsetsrc(self, val): + self["offsetsrc"] = val + + @property + def opacity(self): + """ + Sets the opacity of the trace. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def orientation(self): + """ + Sets the orientation of the bars. With "v" ("h"), the value of + the each bar spans along the vertical (horizontal). + + The 'orientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['v', 'h'] + + Returns + ------- + Any + """ + return self["orientation"] + + @orientation.setter + def orientation(self, val): + self["orientation"] = val + + @property + def outsidetextfont(self): + """ + Sets the font used for `text` lying outside the bar. + + The 'outsidetextfont' property is an instance of Outsidetextfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.Outsidetextfont` + - A dict of string/value properties that will be passed + to the Outsidetextfont constructor + + Returns + ------- + plotly.graph_objs.waterfall.Outsidetextfont + """ + return self["outsidetextfont"] + + @outsidetextfont.setter + def outsidetextfont(self, val): + self["outsidetextfont"] = val + + @property + def selectedpoints(self): + """ + Array containing integer indices of selected points. Has an + effect only for traces that support selections. Note that an + empty array means an empty selection where the `unselected` are + turned on for all points, whereas, any other non-array values + means no selection all where the `selected` and `unselected` + styles have no effect. + + The 'selectedpoints' property accepts values of any type + + Returns + ------- + Any + """ + return self["selectedpoints"] + + @selectedpoints.setter + def selectedpoints(self, val): + self["selectedpoints"] = val + + @property + def showlegend(self): + """ + Determines whether or not an item corresponding to this trace + is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def stream(self): + """ + The 'stream' property is an instance of Stream + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.Stream` + - A dict of string/value properties that will be passed + to the Stream constructor + + Returns + ------- + plotly.graph_objs.waterfall.Stream + """ + return self["stream"] + + @stream.setter + def stream(self, val): + self["stream"] = val + + @property + def text(self): + """ + Sets text elements associated with each (x,y) pair. If a single + string, the same string appears over all the data points. If an + array of string, the items are mapped in order to the this + trace's (x,y) coordinates. If trace `hoverinfo` contains a + "text" flag and "hovertext" is not set, these elements will be + seen in the hover labels. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textangle(self): + """ + Sets the angle of the tick labels with respect to the bar. For + example, a `tickangle` of -90 draws the tick labels vertically. + With "auto" the texts may automatically be rotated to fit with + the maximum size in bars. + + The 'textangle' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["textangle"] + + @textangle.setter + def textangle(self, val): + self["textangle"] = val + + @property + def textfont(self): + """ + Sets the font used for `text`. + + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.waterfall.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def textinfo(self): + """ + Determines which trace information appear on the graph. In the + case of having multiple waterfalls, totals are computed + separately (per trace). + + The 'textinfo' property is a flaglist and may be specified + as a string containing: + - Any combination of ['label', 'text', 'initial', 'delta', 'final'] joined with '+' characters + (e.g. 'label+text') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["textinfo"] + + @textinfo.setter + def textinfo(self, val): + self["textinfo"] = val + + @property + def textposition(self): + """ + Specifies the location of the `text`. "inside" positions `text` + inside, next to the bar end (rotated and scaled if needed). + "outside" positions `text` outside, next to the bar end (scaled + if needed), unless there is another bar stacked on this one, + then the text gets pushed inside. "auto" tries to position + `text` inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If "none", no + text appears. + + The 'textposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['inside', 'outside', 'auto', 'none'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textposition"] + + @textposition.setter + def textposition(self, val): + self["textposition"] = val + + @property + def textpositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `textposition`. + + The 'textpositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textpositionsrc"] + + @textpositionsrc.setter + def textpositionsrc(self, val): + self["textpositionsrc"] = val + + @property + def textsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `text`. + + The 'textsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textsrc"] + + @textsrc.setter + def textsrc(self, val): + self["textsrc"] = val + + @property + def texttemplate(self): + """ + Template string used for rendering the information text that + appears on points. Note that this will override `textinfo`. + Variables are inserted using %{variable}, for example "y: + %{y}". Numbers are formatted using d3-format's syntax + %{variable:d3-format}, for example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) are + available. Finally, the template string has access to variables + `initial`, `delta`, `final` and `label`. + + The 'texttemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["texttemplate"] + + @texttemplate.setter + def texttemplate(self, val): + self["texttemplate"] = val + + @property + def texttemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'texttemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["texttemplatefallback"] + + @texttemplatefallback.setter + def texttemplatefallback(self, val): + self["texttemplatefallback"] = val + + @property + def texttemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + + The 'texttemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["texttemplatesrc"] + + @texttemplatesrc.setter + def texttemplatesrc(self, val): + self["texttemplatesrc"] = val + + @property + def totals(self): + """ + The 'totals' property is an instance of Totals + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.Totals` + - A dict of string/value properties that will be passed + to the Totals constructor + + Returns + ------- + plotly.graph_objs.waterfall.Totals + """ + return self["totals"] + + @totals.setter + def totals(self, val): + self["totals"] = val + + @property + def uid(self): + """ + Assign an id to this trace, Use this to provide object + constancy between traces during animations and transitions. + + The 'uid' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["uid"] + + @uid.setter + def uid(self, val): + self["uid"] = val + + @property + def uirevision(self): + """ + Controls persistence of some user-driven changes to the trace: + `constraintrange` in `parcoords` traces, as well as some + `editable: true` modifications such as `name` and + `colorbar.title`. Defaults to `layout.uirevision`. Note that + other user-driven trace attribute changes are controlled by + `layout` attributes: `trace.visible` is controlled by + `layout.legend.uirevision`, `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` (accessible + with `config: {editable: true}`) is controlled by + `layout.editrevision`. Trace changes are tracked by `uid`, + which only falls back on trace index if no `uid` is provided. + So if your app can add/remove traces before the end of the + `data` array, such that the same trace has a different index, + you can still preserve user-driven changes if you give each + trace a `uid` that stays with it as it moves. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def width(self): + """ + Sets the bar width (in position axis units). + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def widthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `width`. + + The 'widthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["widthsrc"] + + @widthsrc.setter + def widthsrc(self, val): + self["widthsrc"] = val + + @property + def x(self): + """ + Sets the x coordinates. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def x0(self): + """ + Alternate to `x`. Builds a linear space of x coordinates. Use + with `dx` where `x0` is the starting coordinate and `dx` the + step. + + The 'x0' property accepts values of any type + + Returns + ------- + Any + """ + return self["x0"] + + @x0.setter + def x0(self, val): + self["x0"] = val + + @property + def xaxis(self): + """ + Sets a reference between this trace's x coordinates and a 2D + cartesian x axis. If "x" (the default value), the x coordinates + refer to `layout.xaxis`. If "x2", the x coordinates refer to + `layout.xaxis2`, and so on. + + The 'xaxis' property is an identifier of a particular + subplot, of type 'x', that may be specified as: + - the string 'x' optionally followed by an integer >= 1 + (e.g. 'x', 'x1', 'x2', 'x3', etc.) + + Returns + ------- + str + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def xhoverformat(self): + """ + Sets the hover text formatting rulefor `x` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `xaxis.hoverformat`. + + The 'xhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["xhoverformat"] + + @xhoverformat.setter + def xhoverformat(self, val): + self["xhoverformat"] = val + + @property + def xperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the x axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'xperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod"] + + @xperiod.setter + def xperiod(self, val): + self["xperiod"] = val + + @property + def xperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the x0 + axis. When `x0period` is round number of weeks, the `x0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'xperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["xperiod0"] + + @xperiod0.setter + def xperiod0(self, val): + self["xperiod0"] = val + + @property + def xperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + + The 'xperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["xperiodalignment"] + + @xperiodalignment.setter + def xperiodalignment(self, val): + self["xperiodalignment"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the y coordinates. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def y0(self): + """ + Alternate to `y`. Builds a linear space of y coordinates. Use + with `dy` where `y0` is the starting coordinate and `dy` the + step. + + The 'y0' property accepts values of any type + + Returns + ------- + Any + """ + return self["y0"] + + @y0.setter + def y0(self, val): + self["y0"] = val + + @property + def yaxis(self): + """ + Sets a reference between this trace's y coordinates and a 2D + cartesian y axis. If "y" (the default value), the y coordinates + refer to `layout.yaxis`. If "y2", the y coordinates refer to + `layout.yaxis2`, and so on. + + The 'yaxis' property is an identifier of a particular + subplot, of type 'y', that may be specified as: + - the string 'y' optionally followed by an integer >= 1 + (e.g. 'y', 'y1', 'y2', 'y3', etc.) + + Returns + ------- + str + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def yhoverformat(self): + """ + Sets the hover text formatting rulefor `y` using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display *09~15~23.46*By default the values + are formatted using `yaxis.hoverformat`. + + The 'yhoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["yhoverformat"] + + @yhoverformat.setter + def yhoverformat(self, val): + self["yhoverformat"] = val + + @property + def yperiod(self): + """ + Only relevant when the axis `type` is "date". Sets the period + positioning in milliseconds or "M" on the y axis. Special + values in the form of "M" could be used to declare the + number of months. In this case `n` must be a positive integer. + + The 'yperiod' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod"] + + @yperiod.setter + def yperiod(self, val): + self["yperiod"] = val + + @property + def yperiod0(self): + """ + Only relevant when the axis `type` is "date". Sets the base for + period positioning in milliseconds or date string on the y0 + axis. When `y0period` is round number of weeks, the `y0period0` + by default would be on a Sunday i.e. 2000-01-02, otherwise it + would be at 2000-01-01. + + The 'yperiod0' property accepts values of any type + + Returns + ------- + Any + """ + return self["yperiod0"] + + @yperiod0.setter + def yperiod0(self, val): + self["yperiod0"] = val + + @property + def yperiodalignment(self): + """ + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + + The 'yperiodalignment' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['start', 'middle', 'end'] + + Returns + ------- + Any + """ + return self["yperiodalignment"] + + @yperiodalignment.setter + def yperiodalignment(self, val): + self["yperiodalignment"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def zorder(self): + """ + Sets the layer on which this trace is displayed, relative to + other SVG traces on the same subplot. SVG traces with higher + `zorder` appear in front of those with lower `zorder`. + + The 'zorder' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["zorder"] + + @zorder.setter + def zorder(self, val): + self["zorder"] = val + + @property + def type(self): + return self._props["type"] + + @property + def _prop_descriptions(self): + return """\ + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + base + Sets where the bar base is drawn (in position axis + units). + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + connector + :class:`plotly.graph_objects.waterfall.Connector` + instance or dict with compatible properties + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + decreasing + :class:`plotly.graph_objects.waterfall.Decreasing` + instance or dict with compatible properties + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.waterfall.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `initial`, `delta` and `final`. Anything + contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + increasing + :class:`plotly.graph_objects.waterfall.Increasing` + instance or dict with compatible properties + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.waterfall.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + measure + An array containing types of values. By default the + values are considered as 'relative'. However; it is + possible to use 'total' to compute the sums. Also + 'absolute' could be applied to reset the computed total + or to declare an initial value where needed. + measuresrc + Sets the source reference on Chart Studio Cloud for + `measure`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the position where the bar is drawn (in position + axis units). In "group" barmode, traces that set + "offset" will be excluded and drawn in "overlay" mode + instead. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + offsetsrc + Sets the source reference on Chart Studio Cloud for + `offset`. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the bars. With "v" ("h"), the + value of the each bar spans along the vertical + (horizontal). + outsidetextfont + Sets the font used for `text` lying outside the bar. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.waterfall.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the font used for `text`. + textinfo + Determines which trace information appear on the graph. + In the case of having multiple waterfalls, totals are + computed separately (per trace). + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `initial`, `delta`, `final` and `label`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + totals + :class:`plotly.graph_objects.waterfall.Totals` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar width (in position axis units). + widthsrc + Sets the source reference on Chart Studio Cloud for + `width`. + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + """ + + def __init__( + self, + arg=None, + alignmentgroup=None, + base=None, + cliponaxis=None, + connector=None, + constraintext=None, + customdata=None, + customdatasrc=None, + decreasing=None, + dx=None, + dy=None, + hoverinfo=None, + hoverinfosrc=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + hovertext=None, + hovertextsrc=None, + ids=None, + idssrc=None, + increasing=None, + insidetextanchor=None, + insidetextfont=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + measure=None, + measuresrc=None, + meta=None, + metasrc=None, + name=None, + offset=None, + offsetgroup=None, + offsetsrc=None, + opacity=None, + orientation=None, + outsidetextfont=None, + selectedpoints=None, + showlegend=None, + stream=None, + text=None, + textangle=None, + textfont=None, + textinfo=None, + textposition=None, + textpositionsrc=None, + textsrc=None, + texttemplate=None, + texttemplatefallback=None, + texttemplatesrc=None, + totals=None, + uid=None, + uirevision=None, + visible=None, + width=None, + widthsrc=None, + x=None, + x0=None, + xaxis=None, + xhoverformat=None, + xperiod=None, + xperiod0=None, + xperiodalignment=None, + xsrc=None, + y=None, + y0=None, + yaxis=None, + yhoverformat=None, + yperiod=None, + yperiod0=None, + yperiodalignment=None, + ysrc=None, + zorder=None, + **kwargs, + ): + """ + Construct a new Waterfall object + + Draws waterfall trace which is useful graph to displays the + contribution of various elements (either positive or negative) + in a bar chart. The data visualized by the span of the bars is + set in `y` if `orientation` is set to "v" (the default) and the + labels are set in `x`. By setting `orientation` to "h", the + roles are interchanged. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.Waterfall` + alignmentgroup + Set several traces linked to the same position axis or + matching axes to the same alignmentgroup. This controls + whether bars compute their positional range dependently + or independently. + base + Sets where the bar base is drawn (in position axis + units). + cliponaxis + Determines whether the text nodes are clipped about the + subplot axes. To show the text nodes above axis lines + and tick labels, make sure to set `xaxis.layer` and + `yaxis.layer` to *below traces*. + connector + :class:`plotly.graph_objects.waterfall.Connector` + instance or dict with compatible properties + constraintext + Constrain the size of text inside or outside a bar to + be no larger than the bar itself. + customdata + Assigns extra data each datum. This may be useful when + listening to hover, click and selection events. Note + that, "scatter" traces also appends customdata items in + the markers DOM elements + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + decreasing + :class:`plotly.graph_objects.waterfall.Decreasing` + instance or dict with compatible properties + dx + Sets the x coordinate step. See `x0` for more info. + dy + Sets the y coordinate step. See `y0` for more info. + hoverinfo + Determines which trace information appear on hover. If + `none` or `skip` are set, no information is displayed + upon hovering. But, if `none` is set, click and hover + events are still fired. + hoverinfosrc + Sets the source reference on Chart Studio Cloud for + `hoverinfo`. + hoverlabel + :class:`plotly.graph_objects.waterfall.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `initial`, `delta` and `final`. Anything + contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + hovertext + Sets hover text elements associated with each (x,y) + pair. If a single string, the same string appears over + all the data points. If an array of string, the items + are mapped in order to the this trace's (x,y) + coordinates. To be seen, trace `hoverinfo` must contain + a "text" flag. + hovertextsrc + Sets the source reference on Chart Studio Cloud for + `hovertext`. + ids + Assigns id labels to each datum. These ids for object + constancy of data points during animation. Should be an + array of strings, not numbers or any other type. + idssrc + Sets the source reference on Chart Studio Cloud for + `ids`. + increasing + :class:`plotly.graph_objects.waterfall.Increasing` + instance or dict with compatible properties + insidetextanchor + Determines if texts are kept at center or start/end + points in `textposition` "inside" mode. + insidetextfont + Sets the font used for `text` lying inside the bar. + legend + Sets the reference to a legend to show this trace in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this trace. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.waterfall.Legendgrouptitle + ` instance or dict with compatible properties + legendrank + Sets the legend rank for this trace. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this trace. + measure + An array containing types of values. By default the + values are considered as 'relative'. However; it is + possible to use 'total' to compute the sums. Also + 'absolute' could be applied to reset the computed total + or to declare an initial value where needed. + measuresrc + Sets the source reference on Chart Studio Cloud for + `measure`. + meta + Assigns extra meta information associated with this + trace that can be used in various text attributes. + Attributes such as trace `name`, graph, axis and + colorbar `title.text`, annotation `text` + `rangeselector`, `updatemenues` and `sliders` `label` + text all support `meta`. To access the trace `meta` + values in an attribute in the same trace, simply use + `%{meta[i]}` where `i` is the index or key of the + `meta` item in question. To access trace `meta` in + layout attributes, use `%{data[n[.meta[i]}` where `i` + is the index or key of the `meta` and `n` is the trace + index. + metasrc + Sets the source reference on Chart Studio Cloud for + `meta`. + name + Sets the trace name. The trace name appears as the + legend item and on hover. + offset + Shifts the position where the bar is drawn (in position + axis units). In "group" barmode, traces that set + "offset" will be excluded and drawn in "overlay" mode + instead. + offsetgroup + Set several traces linked to the same position axis or + matching axes to the same offsetgroup where bars of the + same position coordinate will line up. + offsetsrc + Sets the source reference on Chart Studio Cloud for + `offset`. + opacity + Sets the opacity of the trace. + orientation + Sets the orientation of the bars. With "v" ("h"), the + value of the each bar spans along the vertical + (horizontal). + outsidetextfont + Sets the font used for `text` lying outside the bar. + selectedpoints + Array containing integer indices of selected points. + Has an effect only for traces that support selections. + Note that an empty array means an empty selection where + the `unselected` are turned on for all points, whereas, + any other non-array values means no selection all where + the `selected` and `unselected` styles have no effect. + showlegend + Determines whether or not an item corresponding to this + trace is shown in the legend. + stream + :class:`plotly.graph_objects.waterfall.Stream` instance + or dict with compatible properties + text + Sets text elements associated with each (x,y) pair. If + a single string, the same string appears over all the + data points. If an array of string, the items are + mapped in order to the this trace's (x,y) coordinates. + If trace `hoverinfo` contains a "text" flag and + "hovertext" is not set, these elements will be seen in + the hover labels. + textangle + Sets the angle of the tick labels with respect to the + bar. For example, a `tickangle` of -90 draws the tick + labels vertically. With "auto" the texts may + automatically be rotated to fit with the maximum size + in bars. + textfont + Sets the font used for `text`. + textinfo + Determines which trace information appear on the graph. + In the case of having multiple waterfalls, totals are + computed separately (per trace). + textposition + Specifies the location of the `text`. "inside" + positions `text` inside, next to the bar end (rotated + and scaled if needed). "outside" positions `text` + outside, next to the bar end (scaled if needed), unless + there is another bar stacked on this one, then the text + gets pushed inside. "auto" tries to position `text` + inside the bar, but if the bar is too small and no bar + is stacked on this one the text is moved outside. If + "none", no text appears. + textpositionsrc + Sets the source reference on Chart Studio Cloud for + `textposition`. + textsrc + Sets the source reference on Chart Studio Cloud for + `text`. + texttemplate + Template string used for rendering the information text + that appears on points. Note that this will override + `textinfo`. Variables are inserted using %{variable}, + for example "y: %{y}". Numbers are formatted using + d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. All attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `initial`, `delta`, `final` and `label`. + texttemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + texttemplatesrc + Sets the source reference on Chart Studio Cloud for + `texttemplate`. + totals + :class:`plotly.graph_objects.waterfall.Totals` instance + or dict with compatible properties + uid + Assign an id to this trace, Use this to provide object + constancy between traces during animations and + transitions. + uirevision + Controls persistence of some user-driven changes to the + trace: `constraintrange` in `parcoords` traces, as well + as some `editable: true` modifications such as `name` + and `colorbar.title`. Defaults to `layout.uirevision`. + Note that other user-driven trace attribute changes are + controlled by `layout` attributes: `trace.visible` is + controlled by `layout.legend.uirevision`, + `selectedpoints` is controlled by + `layout.selectionrevision`, and `colorbar.(x|y)` + (accessible with `config: {editable: true}`) is + controlled by `layout.editrevision`. Trace changes are + tracked by `uid`, which only falls back on trace index + if no `uid` is provided. So if your app can add/remove + traces before the end of the `data` array, such that + the same trace has a different index, you can still + preserve user-driven changes if you give each trace a + `uid` that stays with it as it moves. + visible + Determines whether or not this trace is visible. If + "legendonly", the trace is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + width + Sets the bar width (in position axis units). + widthsrc + Sets the source reference on Chart Studio Cloud for + `width`. + x + Sets the x coordinates. + x0 + Alternate to `x`. Builds a linear space of x + coordinates. Use with `dx` where `x0` is the starting + coordinate and `dx` the step. + xaxis + Sets a reference between this trace's x coordinates and + a 2D cartesian x axis. If "x" (the default value), the + x coordinates refer to `layout.xaxis`. If "x2", the x + coordinates refer to `layout.xaxis2`, and so on. + xhoverformat + Sets the hover text formatting rulefor `x` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `xaxis.hoverformat`. + xperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the x + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + xperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the x0 axis. When `x0period` is round number + of weeks, the `x0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + xperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the x axis. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y coordinates. + y0 + Alternate to `y`. Builds a linear space of y + coordinates. Use with `dy` where `y0` is the starting + coordinate and `dy` the step. + yaxis + Sets a reference between this trace's y coordinates and + a 2D cartesian y axis. If "y" (the default value), the + y coordinates refer to `layout.yaxis`. If "y2", the y + coordinates refer to `layout.yaxis2`, and so on. + yhoverformat + Sets the hover text formatting rulefor `y` using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display *09~15~23.46*By default the values are + formatted using `yaxis.hoverformat`. + yperiod + Only relevant when the axis `type` is "date". Sets the + period positioning in milliseconds or "M" on the y + axis. Special values in the form of "M" could be + used to declare the number of months. In this case `n` + must be a positive integer. + yperiod0 + Only relevant when the axis `type` is "date". Sets the + base for period positioning in milliseconds or date + string on the y0 axis. When `y0period` is round number + of weeks, the `y0period0` by default would be on a + Sunday i.e. 2000-01-02, otherwise it would be at + 2000-01-01. + yperiodalignment + Only relevant when the axis `type` is "date". Sets the + alignment of data points on the y axis. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + zorder + Sets the layer on which this trace is displayed, + relative to other SVG traces on the same subplot. SVG + traces with higher `zorder` appear in front of those + with lower `zorder`. + + Returns + ------- + Waterfall + """ + super().__init__("waterfall") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.Waterfall +constructor must be a dict or +an instance of :class:`plotly.graph_objs.Waterfall`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("alignmentgroup", arg, alignmentgroup) + self._set_property("base", arg, base) + self._set_property("cliponaxis", arg, cliponaxis) + self._set_property("connector", arg, connector) + self._set_property("constraintext", arg, constraintext) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("decreasing", arg, decreasing) + self._set_property("dx", arg, dx) + self._set_property("dy", arg, dy) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverinfosrc", arg, hoverinfosrc) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("hovertext", arg, hovertext) + self._set_property("hovertextsrc", arg, hovertextsrc) + self._set_property("ids", arg, ids) + self._set_property("idssrc", arg, idssrc) + self._set_property("increasing", arg, increasing) + self._set_property("insidetextanchor", arg, insidetextanchor) + self._set_property("insidetextfont", arg, insidetextfont) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("measure", arg, measure) + self._set_property("measuresrc", arg, measuresrc) + self._set_property("meta", arg, meta) + self._set_property("metasrc", arg, metasrc) + self._set_property("name", arg, name) + self._set_property("offset", arg, offset) + self._set_property("offsetgroup", arg, offsetgroup) + self._set_property("offsetsrc", arg, offsetsrc) + self._set_property("opacity", arg, opacity) + self._set_property("orientation", arg, orientation) + self._set_property("outsidetextfont", arg, outsidetextfont) + self._set_property("selectedpoints", arg, selectedpoints) + self._set_property("showlegend", arg, showlegend) + self._set_property("stream", arg, stream) + self._set_property("text", arg, text) + self._set_property("textangle", arg, textangle) + self._set_property("textfont", arg, textfont) + self._set_property("textinfo", arg, textinfo) + self._set_property("textposition", arg, textposition) + self._set_property("textpositionsrc", arg, textpositionsrc) + self._set_property("textsrc", arg, textsrc) + self._set_property("texttemplate", arg, texttemplate) + self._set_property("texttemplatefallback", arg, texttemplatefallback) + self._set_property("texttemplatesrc", arg, texttemplatesrc) + self._set_property("totals", arg, totals) + self._set_property("uid", arg, uid) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._set_property("width", arg, width) + self._set_property("widthsrc", arg, widthsrc) + self._set_property("x", arg, x) + self._set_property("x0", arg, x0) + self._set_property("xaxis", arg, xaxis) + self._set_property("xhoverformat", arg, xhoverformat) + self._set_property("xperiod", arg, xperiod) + self._set_property("xperiod0", arg, xperiod0) + self._set_property("xperiodalignment", arg, xperiodalignment) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("y0", arg, y0) + self._set_property("yaxis", arg, yaxis) + self._set_property("yhoverformat", arg, yhoverformat) + self._set_property("yperiod", arg, yperiod) + self._set_property("yperiod0", arg, yperiod0) + self._set_property("yperiodalignment", arg, yperiodalignment) + self._set_property("ysrc", arg, ysrc) + self._set_property("zorder", arg, zorder) + + self._props["type"] = "waterfall" + arg.pop("type", None) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..f9bb46ff8ab9cacf4311ed515d569df1e55c7978 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/__init__.py @@ -0,0 +1,32 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._hoverlabel import Hoverlabel + from ._legendgrouptitle import Legendgrouptitle + from ._line import Line + from ._marker import Marker + from ._selected import Selected + from ._stream import Stream + from ._unselected import Unselected + from . import hoverlabel + from . import legendgrouptitle + from . import marker + from . import selected + from . import unselected +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [".hoverlabel", ".legendgrouptitle", ".marker", ".selected", ".unselected"], + [ + "._hoverlabel.Hoverlabel", + "._legendgrouptitle.Legendgrouptitle", + "._line.Line", + "._marker.Marker", + "._selected.Selected", + "._stream.Stream", + "._unselected.Unselected", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_hoverlabel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_hoverlabel.py new file mode 100644 index 0000000000000000000000000000000000000000..6955298406e7ce5769a35af754bead5449435e62 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_hoverlabel.py @@ -0,0 +1,366 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Hoverlabel(_BaseTraceHierarchyType): + _parent_path_str = "box" + _path_str = "box.hoverlabel" + _valid_props = { + "align", + "alignsrc", + "bgcolor", + "bgcolorsrc", + "bordercolor", + "bordercolorsrc", + "font", + "namelength", + "namelengthsrc", + "showarrow", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the text content within hover + label box. Has an effect only if the hover label text spans + more two or more lines + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'auto'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def alignsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `align`. + + The 'alignsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["alignsrc"] + + @alignsrc.setter + def alignsrc(self, val): + self["alignsrc"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the hover labels for this trace + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bgcolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `bgcolor`. + + The 'bgcolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bgcolorsrc"] + + @bgcolorsrc.setter + def bgcolorsrc(self, val): + self["bgcolorsrc"] = val + + @property + def bordercolor(self): + """ + Sets the border color of the hover labels for this trace. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def bordercolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + + The 'bordercolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bordercolorsrc"] + + @bordercolorsrc.setter + def bordercolorsrc(self, val): + self["bordercolorsrc"] = val + + @property + def font(self): + """ + Sets the font used in hover labels. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.box.hoverlabel.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.box.hoverlabel.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def namelength(self): + """ + Sets the default length (in number of characters) of the trace + name in the hover labels for all traces. -1 shows the whole + name regardless of length. 0-3 shows the first 0-3 characters, + and an integer >3 will show the whole name if it is less than + that many characters, but if it is longer, will truncate to + `namelength - 3` characters and add an ellipsis. + + The 'namelength' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["namelength"] + + @namelength.setter + def namelength(self, val): + self["namelength"] = val + + @property + def namelengthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `namelength`. + + The 'namelengthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["namelengthsrc"] + + @namelengthsrc.setter + def namelengthsrc(self, val): + self["namelengthsrc"] = val + + @property + def showarrow(self): + """ + Sets whether or not to show the hover label arrow/triangle + pointing to the data point. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + """ + + def __init__( + self, + arg=None, + align=None, + alignsrc=None, + bgcolor=None, + bgcolorsrc=None, + bordercolor=None, + bordercolorsrc=None, + font=None, + namelength=None, + namelengthsrc=None, + showarrow=None, + **kwargs, + ): + """ + Construct a new Hoverlabel object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.box.Hoverlabel` + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + + Returns + ------- + Hoverlabel + """ + super().__init__("hoverlabel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.box.Hoverlabel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.box.Hoverlabel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("alignsrc", arg, alignsrc) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bgcolorsrc", arg, bgcolorsrc) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("bordercolorsrc", arg, bordercolorsrc) + self._set_property("font", arg, font) + self._set_property("namelength", arg, namelength) + self._set_property("namelengthsrc", arg, namelengthsrc) + self._set_property("showarrow", arg, showarrow) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..a2c2541baecd17856bb10308c81f6082cfda9891 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "box" + _path_str = "box.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.box.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.box.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.box.Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.box.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.box.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_line.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_line.py new file mode 100644 index 0000000000000000000000000000000000000000..4887c7e2517ba0b3c3661d939a8f09ba0a654076 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_line.py @@ -0,0 +1,103 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Line(_BaseTraceHierarchyType): + _parent_path_str = "box" + _path_str = "box.line" + _valid_props = {"color", "width"} + + @property + def color(self): + """ + Sets the color of line bounding the box(es). + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def width(self): + """ + Sets the width (in px) of line bounding the box(es). + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def _prop_descriptions(self): + return """\ + color + Sets the color of line bounding the box(es). + width + Sets the width (in px) of line bounding the box(es). + """ + + def __init__(self, arg=None, color=None, width=None, **kwargs): + """ + Construct a new Line object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.box.Line` + color + Sets the color of line bounding the box(es). + width + Sets the width (in px) of line bounding the box(es). + + Returns + ------- + Line + """ + super().__init__("line") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.box.Line +constructor must be a dict or +an instance of :class:`plotly.graph_objs.box.Line`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("width", arg, width) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_marker.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_marker.py new file mode 100644 index 0000000000000000000000000000000000000000..eaf4f80d4f0aa60d98223ee8a33d4a8c3b9a9fb8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_marker.py @@ -0,0 +1,357 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Marker(_BaseTraceHierarchyType): + _parent_path_str = "box" + _path_str = "box.marker" + _valid_props = { + "angle", + "color", + "line", + "opacity", + "outliercolor", + "size", + "symbol", + } + + @property + def angle(self): + """ + Sets the marker angle in respect to `angleref`. + + The 'angle' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["angle"] + + @angle.setter + def angle(self, val): + self["angle"] = val + + @property + def color(self): + """ + Sets the marker color. It accepts either a specific color or an + array of numbers that are mapped to the colorscale relative to + the max and min values of the array or relative to + `marker.cmin` and `marker.cmax` if set. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.box.marker.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.box.marker.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def opacity(self): + """ + Sets the marker opacity. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def outliercolor(self): + """ + Sets the color of the outlier sample points. + + The 'outliercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["outliercolor"] + + @outliercolor.setter + def outliercolor(self, val): + self["outliercolor"] = val + + @property + def size(self): + """ + Sets the marker size (in px). + + The 'size' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def symbol(self): + """ + Sets the marker symbol type. Adding 100 is equivalent to + appending "-open" to a symbol name. Adding 200 is equivalent to + appending "-dot" to a symbol name. Adding 300 is equivalent to + appending "-open-dot" or "dot-open" to a symbol name. + + The 'symbol' property is an enumeration that may be specified as: + - One of the following enumeration values: + [0, '0', 'circle', 100, '100', 'circle-open', 200, '200', + 'circle-dot', 300, '300', 'circle-open-dot', 1, '1', + 'square', 101, '101', 'square-open', 201, '201', + 'square-dot', 301, '301', 'square-open-dot', 2, '2', + 'diamond', 102, '102', 'diamond-open', 202, '202', + 'diamond-dot', 302, '302', 'diamond-open-dot', 3, '3', + 'cross', 103, '103', 'cross-open', 203, '203', + 'cross-dot', 303, '303', 'cross-open-dot', 4, '4', 'x', + 104, '104', 'x-open', 204, '204', 'x-dot', 304, '304', + 'x-open-dot', 5, '5', 'triangle-up', 105, '105', + 'triangle-up-open', 205, '205', 'triangle-up-dot', 305, + '305', 'triangle-up-open-dot', 6, '6', 'triangle-down', + 106, '106', 'triangle-down-open', 206, '206', + 'triangle-down-dot', 306, '306', 'triangle-down-open-dot', + 7, '7', 'triangle-left', 107, '107', 'triangle-left-open', + 207, '207', 'triangle-left-dot', 307, '307', + 'triangle-left-open-dot', 8, '8', 'triangle-right', 108, + '108', 'triangle-right-open', 208, '208', + 'triangle-right-dot', 308, '308', + 'triangle-right-open-dot', 9, '9', 'triangle-ne', 109, + '109', 'triangle-ne-open', 209, '209', 'triangle-ne-dot', + 309, '309', 'triangle-ne-open-dot', 10, '10', + 'triangle-se', 110, '110', 'triangle-se-open', 210, '210', + 'triangle-se-dot', 310, '310', 'triangle-se-open-dot', 11, + '11', 'triangle-sw', 111, '111', 'triangle-sw-open', 211, + '211', 'triangle-sw-dot', 311, '311', + 'triangle-sw-open-dot', 12, '12', 'triangle-nw', 112, + '112', 'triangle-nw-open', 212, '212', 'triangle-nw-dot', + 312, '312', 'triangle-nw-open-dot', 13, '13', 'pentagon', + 113, '113', 'pentagon-open', 213, '213', 'pentagon-dot', + 313, '313', 'pentagon-open-dot', 14, '14', 'hexagon', 114, + '114', 'hexagon-open', 214, '214', 'hexagon-dot', 314, + '314', 'hexagon-open-dot', 15, '15', 'hexagon2', 115, + '115', 'hexagon2-open', 215, '215', 'hexagon2-dot', 315, + '315', 'hexagon2-open-dot', 16, '16', 'octagon', 116, + '116', 'octagon-open', 216, '216', 'octagon-dot', 316, + '316', 'octagon-open-dot', 17, '17', 'star', 117, '117', + 'star-open', 217, '217', 'star-dot', 317, '317', + 'star-open-dot', 18, '18', 'hexagram', 118, '118', + 'hexagram-open', 218, '218', 'hexagram-dot', 318, '318', + 'hexagram-open-dot', 19, '19', 'star-triangle-up', 119, + '119', 'star-triangle-up-open', 219, '219', + 'star-triangle-up-dot', 319, '319', + 'star-triangle-up-open-dot', 20, '20', + 'star-triangle-down', 120, '120', + 'star-triangle-down-open', 220, '220', + 'star-triangle-down-dot', 320, '320', + 'star-triangle-down-open-dot', 21, '21', 'star-square', + 121, '121', 'star-square-open', 221, '221', + 'star-square-dot', 321, '321', 'star-square-open-dot', 22, + '22', 'star-diamond', 122, '122', 'star-diamond-open', + 222, '222', 'star-diamond-dot', 322, '322', + 'star-diamond-open-dot', 23, '23', 'diamond-tall', 123, + '123', 'diamond-tall-open', 223, '223', + 'diamond-tall-dot', 323, '323', 'diamond-tall-open-dot', + 24, '24', 'diamond-wide', 124, '124', 'diamond-wide-open', + 224, '224', 'diamond-wide-dot', 324, '324', + 'diamond-wide-open-dot', 25, '25', 'hourglass', 125, + '125', 'hourglass-open', 26, '26', 'bowtie', 126, '126', + 'bowtie-open', 27, '27', 'circle-cross', 127, '127', + 'circle-cross-open', 28, '28', 'circle-x', 128, '128', + 'circle-x-open', 29, '29', 'square-cross', 129, '129', + 'square-cross-open', 30, '30', 'square-x', 130, '130', + 'square-x-open', 31, '31', 'diamond-cross', 131, '131', + 'diamond-cross-open', 32, '32', 'diamond-x', 132, '132', + 'diamond-x-open', 33, '33', 'cross-thin', 133, '133', + 'cross-thin-open', 34, '34', 'x-thin', 134, '134', + 'x-thin-open', 35, '35', 'asterisk', 135, '135', + 'asterisk-open', 36, '36', 'hash', 136, '136', + 'hash-open', 236, '236', 'hash-dot', 336, '336', + 'hash-open-dot', 37, '37', 'y-up', 137, '137', + 'y-up-open', 38, '38', 'y-down', 138, '138', + 'y-down-open', 39, '39', 'y-left', 139, '139', + 'y-left-open', 40, '40', 'y-right', 140, '140', + 'y-right-open', 41, '41', 'line-ew', 141, '141', + 'line-ew-open', 42, '42', 'line-ns', 142, '142', + 'line-ns-open', 43, '43', 'line-ne', 143, '143', + 'line-ne-open', 44, '44', 'line-nw', 144, '144', + 'line-nw-open', 45, '45', 'arrow-up', 145, '145', + 'arrow-up-open', 46, '46', 'arrow-down', 146, '146', + 'arrow-down-open', 47, '47', 'arrow-left', 147, '147', + 'arrow-left-open', 48, '48', 'arrow-right', 148, '148', + 'arrow-right-open', 49, '49', 'arrow-bar-up', 149, '149', + 'arrow-bar-up-open', 50, '50', 'arrow-bar-down', 150, + '150', 'arrow-bar-down-open', 51, '51', 'arrow-bar-left', + 151, '151', 'arrow-bar-left-open', 52, '52', + 'arrow-bar-right', 152, '152', 'arrow-bar-right-open', 53, + '53', 'arrow', 153, '153', 'arrow-open', 54, '54', + 'arrow-wide', 154, '154', 'arrow-wide-open'] + + Returns + ------- + Any + """ + return self["symbol"] + + @symbol.setter + def symbol(self, val): + self["symbol"] = val + + @property + def _prop_descriptions(self): + return """\ + angle + Sets the marker angle in respect to `angleref`. + color + Sets the marker color. It accepts either a specific + color or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `marker.cmin` and `marker.cmax` if + set. + line + :class:`plotly.graph_objects.box.marker.Line` instance + or dict with compatible properties + opacity + Sets the marker opacity. + outliercolor + Sets the color of the outlier sample points. + size + Sets the marker size (in px). + symbol + Sets the marker symbol type. Adding 100 is equivalent + to appending "-open" to a symbol name. Adding 200 is + equivalent to appending "-dot" to a symbol name. Adding + 300 is equivalent to appending "-open-dot" or "dot- + open" to a symbol name. + """ + + def __init__( + self, + arg=None, + angle=None, + color=None, + line=None, + opacity=None, + outliercolor=None, + size=None, + symbol=None, + **kwargs, + ): + """ + Construct a new Marker object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.box.Marker` + angle + Sets the marker angle in respect to `angleref`. + color + Sets the marker color. It accepts either a specific + color or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `marker.cmin` and `marker.cmax` if + set. + line + :class:`plotly.graph_objects.box.marker.Line` instance + or dict with compatible properties + opacity + Sets the marker opacity. + outliercolor + Sets the color of the outlier sample points. + size + Sets the marker size (in px). + symbol + Sets the marker symbol type. Adding 100 is equivalent + to appending "-open" to a symbol name. Adding 200 is + equivalent to appending "-dot" to a symbol name. Adding + 300 is equivalent to appending "-open-dot" or "dot- + open" to a symbol name. + + Returns + ------- + Marker + """ + super().__init__("marker") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.box.Marker +constructor must be a dict or +an instance of :class:`plotly.graph_objs.box.Marker`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("angle", arg, angle) + self._set_property("color", arg, color) + self._set_property("line", arg, line) + self._set_property("opacity", arg, opacity) + self._set_property("outliercolor", arg, outliercolor) + self._set_property("size", arg, size) + self._set_property("symbol", arg, symbol) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_selected.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_selected.py new file mode 100644 index 0000000000000000000000000000000000000000..cb94773b85a8ea6eafc262cd3e560f537dcb0d35 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_selected.py @@ -0,0 +1,79 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Selected(_BaseTraceHierarchyType): + _parent_path_str = "box" + _path_str = "box.selected" + _valid_props = {"marker"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.box.selected.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.box.selected.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.box.selected.Marker` + instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, **kwargs): + """ + Construct a new Selected object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.box.Selected` + marker + :class:`plotly.graph_objects.box.selected.Marker` + instance or dict with compatible properties + + Returns + ------- + Selected + """ + super().__init__("selected") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.box.Selected +constructor must be a dict or +an instance of :class:`plotly.graph_objs.box.Selected`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..b6cd0eb667cd9113dee3ce795baa8073ab138e29 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_stream.py @@ -0,0 +1,113 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "box" + _path_str = "box.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.box.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.box.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.box.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_unselected.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_unselected.py new file mode 100644 index 0000000000000000000000000000000000000000..9db72eb4501306c8eea557bef63d6dba1817d97e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/box/_unselected.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Unselected(_BaseTraceHierarchyType): + _parent_path_str = "box" + _path_str = "box.unselected" + _valid_props = {"marker"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.box.unselected.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.box.unselected.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.box.unselected.Marker` + instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, **kwargs): + """ + Construct a new Unselected object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.box.Unselected` + marker + :class:`plotly.graph_objects.box.unselected.Marker` + instance or dict with compatible properties + + Returns + ------- + Unselected + """ + super().__init__("unselected") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.box.Unselected +constructor must be a dict or +an instance of :class:`plotly.graph_objs.box.Unselected`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..bbdf79a35a765428a67b80fc7e9703117398bc32 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/__init__.py @@ -0,0 +1,40 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._colorbar import ColorBar + from ._hoverlabel import Hoverlabel + from ._legendgrouptitle import Legendgrouptitle + from ._marker import Marker + from ._selected import Selected + from ._stream import Stream + from ._unselected import Unselected + from . import colorbar + from . import hoverlabel + from . import legendgrouptitle + from . import marker + from . import selected + from . import unselected +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [ + ".colorbar", + ".hoverlabel", + ".legendgrouptitle", + ".marker", + ".selected", + ".unselected", + ], + [ + "._colorbar.ColorBar", + "._hoverlabel.Hoverlabel", + "._legendgrouptitle.Legendgrouptitle", + "._marker.Marker", + "._selected.Selected", + "._stream.Stream", + "._unselected.Unselected", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_colorbar.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_colorbar.py new file mode 100644 index 0000000000000000000000000000000000000000..a09c2a2714825f9a3cf49e91308f0239bd38a1f2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_colorbar.py @@ -0,0 +1,1739 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class ColorBar(_BaseTraceHierarchyType): + _parent_path_str = "choroplethmap" + _path_str = "choroplethmap.colorbar" + _valid_props = { + "bgcolor", + "bordercolor", + "borderwidth", + "dtick", + "exponentformat", + "labelalias", + "len", + "lenmode", + "minexponent", + "nticks", + "orientation", + "outlinecolor", + "outlinewidth", + "separatethousands", + "showexponent", + "showticklabels", + "showtickprefix", + "showticksuffix", + "thickness", + "thicknessmode", + "tick0", + "tickangle", + "tickcolor", + "tickfont", + "tickformat", + "tickformatstopdefaults", + "tickformatstops", + "ticklabeloverflow", + "ticklabelposition", + "ticklabelstep", + "ticklen", + "tickmode", + "tickprefix", + "ticks", + "ticksuffix", + "ticktext", + "ticktextsrc", + "tickvals", + "tickvalssrc", + "tickwidth", + "title", + "x", + "xanchor", + "xpad", + "xref", + "y", + "yanchor", + "ypad", + "yref", + } + + @property + def bgcolor(self): + """ + Sets the color of padded area. + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bordercolor(self): + """ + Sets the axis line color. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def borderwidth(self): + """ + Sets the width (in px) or the border enclosing this color bar. + + The 'borderwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["borderwidth"] + + @borderwidth.setter + def borderwidth(self, val): + self["borderwidth"] = val + + @property + def dtick(self): + """ + Sets the step in-between ticks on this axis. Use with `tick0`. + Must be a positive number, or special strings available to + "log" and "date" axes. If the axis `type` is "log", then ticks + are set every 10^(n*dtick) where n is the tick number. For + example, to set a tick mark at 1, 10, 100, 1000, ... set dtick + to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. + To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special values; + "L", where `f` is a positive number, gives ticks linearly + spaced in value (but not position). For example `tick0` = 0.1, + `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To + show powers of 10 plus small digits between, use "D1" (all + digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and + "D2". If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval between + ticks to one day, set `dtick` to 86400000.0. "date" also has + special values "M" gives ticks spaced by a number of months. + `n` must be a positive integer. To set ticks on the 15th of + every third month, set `tick0` to "2000-01-15" and `dtick` to + "M3". To set ticks every 4 years, set `dtick` to "M48" + + The 'dtick' property accepts values of any type + + Returns + ------- + Any + """ + return self["dtick"] + + @dtick.setter + def dtick(self, val): + self["dtick"] = val + + @property + def exponentformat(self): + """ + Determines a formatting rule for the tick exponents. For + example, consider the number 1,000,000,000. If "none", it + appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If + "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If + "B", 1B. "SI" uses prefixes from "femto" f (10^-15) to "tera" T + (10^12). *SI extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or *SI + extended* is used and the exponent is beyond the above ranges, + the formatting rule will automatically be switched to the power + notation. + + The 'exponentformat' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'e', 'E', 'power', 'SI', 'B', 'SI extended'] + + Returns + ------- + Any + """ + return self["exponentformat"] + + @exponentformat.setter + def exponentformat(self, val): + self["exponentformat"] = val + + @property + def labelalias(self): + """ + Replacement text for specific tick or hover labels. For example + using {US: 'USA', CA: 'Canada'} changes US to USA and CA to + Canada. The labels we would have shown must match the keys + exactly, after adding any tickprefix or ticksuffix. For + negative numbers the minus sign symbol used (U+2212) is wider + than the regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis type, and + both keys (if needed) and values (if desired) can include html- + like tags or MathJax. + + The 'labelalias' property accepts values of any type + + Returns + ------- + Any + """ + return self["labelalias"] + + @labelalias.setter + def labelalias(self, val): + self["labelalias"] = val + + @property + def len(self): + """ + Sets the length of the color bar This measure excludes the + padding of both ends. That is, the color bar length is this + length minus the padding on both ends. + + The 'len' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["len"] + + @len.setter + def len(self, val): + self["len"] = val + + @property + def lenmode(self): + """ + Determines whether this color bar's length (i.e. the measure in + the color variation direction) is set in units of plot + "fraction" or in *pixels. Use `len` to set the value. + + The 'lenmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fraction', 'pixels'] + + Returns + ------- + Any + """ + return self["lenmode"] + + @lenmode.setter + def lenmode(self, val): + self["lenmode"] = val + + @property + def minexponent(self): + """ + Hide SI prefix for 10^n if |n| is below this number. This only + has an effect when `tickformat` is "SI" or "B". + + The 'minexponent' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["minexponent"] + + @minexponent.setter + def minexponent(self, val): + self["minexponent"] = val + + @property + def nticks(self): + """ + Specifies the maximum number of ticks for the particular axis. + The actual number of ticks will be chosen automatically to be + less than or equal to `nticks`. Has an effect only if + `tickmode` is set to "auto". + + The 'nticks' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["nticks"] + + @nticks.setter + def nticks(self, val): + self["nticks"] = val + + @property + def orientation(self): + """ + Sets the orientation of the colorbar. + + The 'orientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['h', 'v'] + + Returns + ------- + Any + """ + return self["orientation"] + + @orientation.setter + def orientation(self, val): + self["orientation"] = val + + @property + def outlinecolor(self): + """ + Sets the axis line color. + + The 'outlinecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["outlinecolor"] + + @outlinecolor.setter + def outlinecolor(self, val): + self["outlinecolor"] = val + + @property + def outlinewidth(self): + """ + Sets the width (in px) of the axis line. + + The 'outlinewidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["outlinewidth"] + + @outlinewidth.setter + def outlinewidth(self, val): + self["outlinewidth"] = val + + @property + def separatethousands(self): + """ + If "true", even 4-digit integers are separated + + The 'separatethousands' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["separatethousands"] + + @separatethousands.setter + def separatethousands(self, val): + self["separatethousands"] = val + + @property + def showexponent(self): + """ + If "all", all exponents are shown besides their significands. + If "first", only the exponent of the first tick is shown. If + "last", only the exponent of the last tick is shown. If "none", + no exponents appear. + + The 'showexponent' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showexponent"] + + @showexponent.setter + def showexponent(self, val): + self["showexponent"] = val + + @property + def showticklabels(self): + """ + Determines whether or not the tick labels are drawn. + + The 'showticklabels' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showticklabels"] + + @showticklabels.setter + def showticklabels(self, val): + self["showticklabels"] = val + + @property + def showtickprefix(self): + """ + If "all", all tick labels are displayed with a prefix. If + "first", only the first tick is displayed with a prefix. If + "last", only the last tick is displayed with a suffix. If + "none", tick prefixes are hidden. + + The 'showtickprefix' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showtickprefix"] + + @showtickprefix.setter + def showtickprefix(self, val): + self["showtickprefix"] = val + + @property + def showticksuffix(self): + """ + Same as `showtickprefix` but for tick suffixes. + + The 'showticksuffix' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showticksuffix"] + + @showticksuffix.setter + def showticksuffix(self, val): + self["showticksuffix"] = val + + @property + def thickness(self): + """ + Sets the thickness of the color bar This measure excludes the + size of the padding, ticks and labels. + + The 'thickness' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["thickness"] + + @thickness.setter + def thickness(self, val): + self["thickness"] = val + + @property + def thicknessmode(self): + """ + Determines whether this color bar's thickness (i.e. the measure + in the constant color direction) is set in units of plot + "fraction" or in "pixels". Use `thickness` to set the value. + + The 'thicknessmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fraction', 'pixels'] + + Returns + ------- + Any + """ + return self["thicknessmode"] + + @thicknessmode.setter + def thicknessmode(self, val): + self["thicknessmode"] = val + + @property + def tick0(self): + """ + Sets the placement of the first tick on this axis. Use with + `dtick`. If the axis `type` is "log", then you must take the + log of your starting tick (e.g. to set the starting tick to + 100, set the `tick0` to 2) except when `dtick`=*L* (see + `dtick` for more info). If the axis `type` is "date", it should + be a date string, like date data. If the axis `type` is + "category", it should be a number, using the scale where each + category is assigned a serial number from zero in the order it + appears. + + The 'tick0' property accepts values of any type + + Returns + ------- + Any + """ + return self["tick0"] + + @tick0.setter + def tick0(self, val): + self["tick0"] = val + + @property + def tickangle(self): + """ + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the tick + labels vertically. + + The 'tickangle' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["tickangle"] + + @tickangle.setter + def tickangle(self, val): + self["tickangle"] = val + + @property + def tickcolor(self): + """ + Sets the tick color. + + The 'tickcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["tickcolor"] + + @tickcolor.setter + def tickcolor(self, val): + self["tickcolor"] = val + + @property + def tickfont(self): + """ + Sets the color bar's tick label font + + The 'tickfont' property is an instance of Tickfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmap.colorbar.Tickfont` + - A dict of string/value properties that will be passed + to the Tickfont constructor + + Returns + ------- + plotly.graph_objs.choroplethmap.colorbar.Tickfont + """ + return self["tickfont"] + + @tickfont.setter + def tickfont(self, val): + self["tickfont"] = val + + @property + def tickformat(self): + """ + Sets the tick label formatting rule using d3 formatting mini- + languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display "09~15~23.46" + + The 'tickformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["tickformat"] + + @tickformat.setter + def tickformat(self, val): + self["tickformat"] = val + + @property + def tickformatstops(self): + """ + The 'tickformatstops' property is a tuple of instances of + Tickformatstop that may be specified as: + - A list or tuple of instances of plotly.graph_objs.choroplethmap.colorbar.Tickformatstop + - A list or tuple of dicts of string/value properties that + will be passed to the Tickformatstop constructor + + Returns + ------- + tuple[plotly.graph_objs.choroplethmap.colorbar.Tickformatstop] + """ + return self["tickformatstops"] + + @tickformatstops.setter + def tickformatstops(self, val): + self["tickformatstops"] = val + + @property + def tickformatstopdefaults(self): + """ + When used in a template (as layout.template.data.choroplethmap. + colorbar.tickformatstopdefaults), sets the default property + values to use for elements of + choroplethmap.colorbar.tickformatstops + + The 'tickformatstopdefaults' property is an instance of Tickformatstop + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmap.colorbar.Tickformatstop` + - A dict of string/value properties that will be passed + to the Tickformatstop constructor + + Returns + ------- + plotly.graph_objs.choroplethmap.colorbar.Tickformatstop + """ + return self["tickformatstopdefaults"] + + @tickformatstopdefaults.setter + def tickformatstopdefaults(self, val): + self["tickformatstopdefaults"] = val + + @property + def ticklabeloverflow(self): + """ + Determines how we handle tick labels that would overflow either + the graph div or the domain of the axis. The default value for + inside tick labels is *hide past domain*. In other cases the + default is *hide past div*. + + The 'ticklabeloverflow' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['allow', 'hide past div', 'hide past domain'] + + Returns + ------- + Any + """ + return self["ticklabeloverflow"] + + @ticklabeloverflow.setter + def ticklabeloverflow(self, val): + self["ticklabeloverflow"] = val + + @property + def ticklabelposition(self): + """ + Determines where tick labels are drawn relative to the ticks. + Left and right options are used when `orientation` is "h", top + and bottom when `orientation` is "v". + + The 'ticklabelposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['outside', 'inside', 'outside top', 'inside top', + 'outside left', 'inside left', 'outside right', 'inside + right', 'outside bottom', 'inside bottom'] + + Returns + ------- + Any + """ + return self["ticklabelposition"] + + @ticklabelposition.setter + def ticklabelposition(self, val): + self["ticklabelposition"] = val + + @property + def ticklabelstep(self): + """ + Sets the spacing between tick labels as compared to the spacing + between ticks. A value of 1 (default) means each tick gets a + label. A value of 2 means shows every 2nd label. A larger value + n means only every nth tick is labeled. `tick0` determines + which labels are shown. Not implemented for axes with `type` + "log" or "multicategory", or when `tickmode` is "array". + + The 'ticklabelstep' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 9223372036854775807] + + Returns + ------- + int + """ + return self["ticklabelstep"] + + @ticklabelstep.setter + def ticklabelstep(self, val): + self["ticklabelstep"] = val + + @property + def ticklen(self): + """ + Sets the tick length (in px). + + The 'ticklen' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["ticklen"] + + @ticklen.setter + def ticklen(self, val): + self["ticklen"] = val + + @property + def tickmode(self): + """ + Sets the tick mode for this axis. If "auto", the number of + ticks is set via `nticks`. If "linear", the placement of the + ticks is determined by a starting position `tick0` and a tick + step `dtick` ("linear" is the default value if `tick0` and + `dtick` are provided). If "array", the placement of the ticks + is set via `tickvals` and the tick text is `ticktext`. ("array" + is the default value if `tickvals` is provided). + + The 'tickmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'linear', 'array'] + + Returns + ------- + Any + """ + return self["tickmode"] + + @tickmode.setter + def tickmode(self, val): + self["tickmode"] = val + + @property + def tickprefix(self): + """ + Sets a tick label prefix. + + The 'tickprefix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["tickprefix"] + + @tickprefix.setter + def tickprefix(self, val): + self["tickprefix"] = val + + @property + def ticks(self): + """ + Determines whether ticks are drawn or not. If "", this axis' + ticks are not drawn. If "outside" ("inside"), this axis' are + drawn outside (inside) the axis lines. + + The 'ticks' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['outside', 'inside', ''] + + Returns + ------- + Any + """ + return self["ticks"] + + @ticks.setter + def ticks(self, val): + self["ticks"] = val + + @property + def ticksuffix(self): + """ + Sets a tick label suffix. + + The 'ticksuffix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["ticksuffix"] + + @ticksuffix.setter + def ticksuffix(self, val): + self["ticksuffix"] = val + + @property + def ticktext(self): + """ + Sets the text displayed at the ticks position via `tickvals`. + Only has an effect if `tickmode` is set to "array". Used with + `tickvals`. + + The 'ticktext' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ticktext"] + + @ticktext.setter + def ticktext(self, val): + self["ticktext"] = val + + @property + def ticktextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ticktext`. + + The 'ticktextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ticktextsrc"] + + @ticktextsrc.setter + def ticktextsrc(self, val): + self["ticktextsrc"] = val + + @property + def tickvals(self): + """ + Sets the values at which ticks on this axis appear. Only has an + effect if `tickmode` is set to "array". Used with `ticktext`. + + The 'tickvals' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["tickvals"] + + @tickvals.setter + def tickvals(self, val): + self["tickvals"] = val + + @property + def tickvalssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `tickvals`. + + The 'tickvalssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["tickvalssrc"] + + @tickvalssrc.setter + def tickvalssrc(self, val): + self["tickvalssrc"] = val + + @property + def tickwidth(self): + """ + Sets the tick width (in px). + + The 'tickwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["tickwidth"] + + @tickwidth.setter + def tickwidth(self, val): + self["tickwidth"] = val + + @property + def title(self): + """ + The 'title' property is an instance of Title + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmap.colorbar.Title` + - A dict of string/value properties that will be passed + to the Title constructor + + Returns + ------- + plotly.graph_objs.choroplethmap.colorbar.Title + """ + return self["title"] + + @title.setter + def title(self, val): + self["title"] = val + + @property + def x(self): + """ + Sets the x position with respect to `xref` of the color bar (in + plot fraction). When `xref` is "paper", defaults to 1.02 when + `orientation` is "v" and 0.5 when `orientation` is "h". When + `xref` is "container", defaults to 1 when `orientation` is "v" + and 0.5 when `orientation` is "h". Must be between 0 and 1 if + `xref` is "container" and between "-2" and 3 if `xref` is + "paper". + + The 'x' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xanchor(self): + """ + Sets this color bar's horizontal position anchor. This anchor + binds the `x` position to the "left", "center" or "right" of + the color bar. Defaults to "left" when `orientation` is "v" and + "center" when `orientation` is "h". + + The 'xanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'center', 'right'] + + Returns + ------- + Any + """ + return self["xanchor"] + + @xanchor.setter + def xanchor(self, val): + self["xanchor"] = val + + @property + def xpad(self): + """ + Sets the amount of padding (in px) along the x direction. + + The 'xpad' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["xpad"] + + @xpad.setter + def xpad(self, val): + self["xpad"] = val + + @property + def xref(self): + """ + Sets the container `x` refers to. "container" spans the entire + `width` of the plot. "paper" refers to the width of the + plotting area only. + + The 'xref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['container', 'paper'] + + Returns + ------- + Any + """ + return self["xref"] + + @xref.setter + def xref(self, val): + self["xref"] = val + + @property + def y(self): + """ + Sets the y position with respect to `yref` of the color bar (in + plot fraction). When `yref` is "paper", defaults to 0.5 when + `orientation` is "v" and 1.02 when `orientation` is "h". When + `yref` is "container", defaults to 0.5 when `orientation` is + "v" and 1 when `orientation` is "h". Must be between 0 and 1 if + `yref` is "container" and between "-2" and 3 if `yref` is + "paper". + + The 'y' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yanchor(self): + """ + Sets this color bar's vertical position anchor This anchor + binds the `y` position to the "top", "middle" or "bottom" of + the color bar. Defaults to "middle" when `orientation` is "v" + and "bottom" when `orientation` is "h". + + The 'yanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top', 'middle', 'bottom'] + + Returns + ------- + Any + """ + return self["yanchor"] + + @yanchor.setter + def yanchor(self, val): + self["yanchor"] = val + + @property + def ypad(self): + """ + Sets the amount of padding (in px) along the y direction. + + The 'ypad' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["ypad"] + + @ypad.setter + def ypad(self, val): + self["ypad"] = val + + @property + def yref(self): + """ + Sets the container `y` refers to. "container" spans the entire + `height` of the plot. "paper" refers to the height of the + plotting area only. + + The 'yref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['container', 'paper'] + + Returns + ------- + Any + """ + return self["yref"] + + @yref.setter + def yref(self, val): + self["yref"] = val + + @property + def _prop_descriptions(self): + return """\ + bgcolor + Sets the color of padded area. + bordercolor + Sets the axis line color. + borderwidth + Sets the width (in px) or the border enclosing this + color bar. + dtick + Sets the step in-between ticks on this axis. Use with + `tick0`. Must be a positive number, or special strings + available to "log" and "date" axes. If the axis `type` + is "log", then ticks are set every 10^(n*dtick) where n + is the tick number. For example, to set a tick mark at + 1, 10, 100, 1000, ... set dtick to 1. To set tick marks + at 1, 100, 10000, ... set dtick to 2. To set tick marks + at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special + values; "L", where `f` is a positive number, gives + ticks linearly spaced in value (but not position). For + example `tick0` = 0.1, `dtick` = "L0.5" will put ticks + at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus + small digits between, use "D1" (all digits) or "D2" + (only 2 and 5). `tick0` is ignored for "D1" and "D2". + If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval + between ticks to one day, set `dtick` to 86400000.0. + "date" also has special values "M" gives ticks + spaced by a number of months. `n` must be a positive + integer. To set ticks on the 15th of every third month, + set `tick0` to "2000-01-15" and `dtick` to "M3". To set + ticks every 4 years, set `dtick` to "M48" + exponentformat + Determines a formatting rule for the tick exponents. + For example, consider the number 1,000,000,000. If + "none", it appears as 1,000,000,000. If "e", 1e+9. If + "E", 1E+9. If "power", 1x10^9 (with 9 in a super + script). If "SI", 1G. If "B", 1B. "SI" uses prefixes + from "femto" f (10^-15) to "tera" T (10^12). *SI + extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or + *SI extended* is used and the exponent is beyond the + above ranges, the formatting rule will automatically be + switched to the power notation. + labelalias + Replacement text for specific tick or hover labels. For + example using {US: 'USA', CA: 'Canada'} changes US to + USA and CA to Canada. The labels we would have shown + must match the keys exactly, after adding any + tickprefix or ticksuffix. For negative numbers the + minus sign symbol used (U+2212) is wider than the + regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis + type, and both keys (if needed) and values (if desired) + can include html-like tags or MathJax. + len + Sets the length of the color bar This measure excludes + the padding of both ends. That is, the color bar length + is this length minus the padding on both ends. + lenmode + Determines whether this color bar's length (i.e. the + measure in the color variation direction) is set in + units of plot "fraction" or in *pixels. Use `len` to + set the value. + minexponent + Hide SI prefix for 10^n if |n| is below this number. + This only has an effect when `tickformat` is "SI" or + "B". + nticks + Specifies the maximum number of ticks for the + particular axis. The actual number of ticks will be + chosen automatically to be less than or equal to + `nticks`. Has an effect only if `tickmode` is set to + "auto". + orientation + Sets the orientation of the colorbar. + outlinecolor + Sets the axis line color. + outlinewidth + Sets the width (in px) of the axis line. + separatethousands + If "true", even 4-digit integers are separated + showexponent + If "all", all exponents are shown besides their + significands. If "first", only the exponent of the + first tick is shown. If "last", only the exponent of + the last tick is shown. If "none", no exponents appear. + showticklabels + Determines whether or not the tick labels are drawn. + showtickprefix + If "all", all tick labels are displayed with a prefix. + If "first", only the first tick is displayed with a + prefix. If "last", only the last tick is displayed with + a suffix. If "none", tick prefixes are hidden. + showticksuffix + Same as `showtickprefix` but for tick suffixes. + thickness + Sets the thickness of the color bar This measure + excludes the size of the padding, ticks and labels. + thicknessmode + Determines whether this color bar's thickness (i.e. the + measure in the constant color direction) is set in + units of plot "fraction" or in "pixels". Use + `thickness` to set the value. + tick0 + Sets the placement of the first tick on this axis. Use + with `dtick`. If the axis `type` is "log", then you + must take the log of your starting tick (e.g. to set + the starting tick to 100, set the `tick0` to 2) except + when `dtick`=*L* (see `dtick` for more info). If the + axis `type` is "date", it should be a date string, like + date data. If the axis `type` is "category", it should + be a number, using the scale where each category is + assigned a serial number from zero in the order it + appears. + tickangle + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + tick labels vertically. + tickcolor + Sets the tick color. + tickfont + Sets the color bar's tick label font + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + tickformatstops + A tuple of :class:`plotly.graph_objects.choroplethmap.c + olorbar.Tickformatstop` instances or dicts with + compatible properties + tickformatstopdefaults + When used in a template (as layout.template.data.chorop + lethmap.colorbar.tickformatstopdefaults), sets the + default property values to use for elements of + choroplethmap.colorbar.tickformatstops + ticklabeloverflow + Determines how we handle tick labels that would + overflow either the graph div or the domain of the + axis. The default value for inside tick labels is *hide + past domain*. In other cases the default is *hide past + div*. + ticklabelposition + Determines where tick labels are drawn relative to the + ticks. Left and right options are used when + `orientation` is "h", top and bottom when `orientation` + is "v". + ticklabelstep + Sets the spacing between tick labels as compared to the + spacing between ticks. A value of 1 (default) means + each tick gets a label. A value of 2 means shows every + 2nd label. A larger value n means only every nth tick + is labeled. `tick0` determines which labels are shown. + Not implemented for axes with `type` "log" or + "multicategory", or when `tickmode` is "array". + ticklen + Sets the tick length (in px). + tickmode + Sets the tick mode for this axis. If "auto", the number + of ticks is set via `nticks`. If "linear", the + placement of the ticks is determined by a starting + position `tick0` and a tick step `dtick` ("linear" is + the default value if `tick0` and `dtick` are provided). + If "array", the placement of the ticks is set via + `tickvals` and the tick text is `ticktext`. ("array" is + the default value if `tickvals` is provided). + tickprefix + Sets a tick label prefix. + ticks + Determines whether ticks are drawn or not. If "", this + axis' ticks are not drawn. If "outside" ("inside"), + this axis' are drawn outside (inside) the axis lines. + ticksuffix + Sets a tick label suffix. + ticktext + Sets the text displayed at the ticks position via + `tickvals`. Only has an effect if `tickmode` is set to + "array". Used with `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + Only has an effect if `tickmode` is set to "array". + Used with `ticktext`. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + tickwidth + Sets the tick width (in px). + title + :class:`plotly.graph_objects.choroplethmap.colorbar.Tit + le` instance or dict with compatible properties + x + Sets the x position with respect to `xref` of the color + bar (in plot fraction). When `xref` is "paper", + defaults to 1.02 when `orientation` is "v" and 0.5 when + `orientation` is "h". When `xref` is "container", + defaults to 1 when `orientation` is "v" and 0.5 when + `orientation` is "h". Must be between 0 and 1 if `xref` + is "container" and between "-2" and 3 if `xref` is + "paper". + xanchor + Sets this color bar's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the color bar. Defaults to "left" when + `orientation` is "v" and "center" when `orientation` is + "h". + xpad + Sets the amount of padding (in px) along the x + direction. + xref + Sets the container `x` refers to. "container" spans the + entire `width` of the plot. "paper" refers to the width + of the plotting area only. + y + Sets the y position with respect to `yref` of the color + bar (in plot fraction). When `yref` is "paper", + defaults to 0.5 when `orientation` is "v" and 1.02 when + `orientation` is "h". When `yref` is "container", + defaults to 0.5 when `orientation` is "v" and 1 when + `orientation` is "h". Must be between 0 and 1 if `yref` + is "container" and between "-2" and 3 if `yref` is + "paper". + yanchor + Sets this color bar's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the color bar. Defaults to "middle" when + `orientation` is "v" and "bottom" when `orientation` is + "h". + ypad + Sets the amount of padding (in px) along the y + direction. + yref + Sets the container `y` refers to. "container" spans the + entire `height` of the plot. "paper" refers to the + height of the plotting area only. + """ + + def __init__( + self, + arg=None, + bgcolor=None, + bordercolor=None, + borderwidth=None, + dtick=None, + exponentformat=None, + labelalias=None, + len=None, + lenmode=None, + minexponent=None, + nticks=None, + orientation=None, + outlinecolor=None, + outlinewidth=None, + separatethousands=None, + showexponent=None, + showticklabels=None, + showtickprefix=None, + showticksuffix=None, + thickness=None, + thicknessmode=None, + tick0=None, + tickangle=None, + tickcolor=None, + tickfont=None, + tickformat=None, + tickformatstops=None, + tickformatstopdefaults=None, + ticklabeloverflow=None, + ticklabelposition=None, + ticklabelstep=None, + ticklen=None, + tickmode=None, + tickprefix=None, + ticks=None, + ticksuffix=None, + ticktext=None, + ticktextsrc=None, + tickvals=None, + tickvalssrc=None, + tickwidth=None, + title=None, + x=None, + xanchor=None, + xpad=None, + xref=None, + y=None, + yanchor=None, + ypad=None, + yref=None, + **kwargs, + ): + """ + Construct a new ColorBar object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.choroplethmap.ColorBar` + bgcolor + Sets the color of padded area. + bordercolor + Sets the axis line color. + borderwidth + Sets the width (in px) or the border enclosing this + color bar. + dtick + Sets the step in-between ticks on this axis. Use with + `tick0`. Must be a positive number, or special strings + available to "log" and "date" axes. If the axis `type` + is "log", then ticks are set every 10^(n*dtick) where n + is the tick number. For example, to set a tick mark at + 1, 10, 100, 1000, ... set dtick to 1. To set tick marks + at 1, 100, 10000, ... set dtick to 2. To set tick marks + at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special + values; "L", where `f` is a positive number, gives + ticks linearly spaced in value (but not position). For + example `tick0` = 0.1, `dtick` = "L0.5" will put ticks + at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus + small digits between, use "D1" (all digits) or "D2" + (only 2 and 5). `tick0` is ignored for "D1" and "D2". + If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval + between ticks to one day, set `dtick` to 86400000.0. + "date" also has special values "M" gives ticks + spaced by a number of months. `n` must be a positive + integer. To set ticks on the 15th of every third month, + set `tick0` to "2000-01-15" and `dtick` to "M3". To set + ticks every 4 years, set `dtick` to "M48" + exponentformat + Determines a formatting rule for the tick exponents. + For example, consider the number 1,000,000,000. If + "none", it appears as 1,000,000,000. If "e", 1e+9. If + "E", 1E+9. If "power", 1x10^9 (with 9 in a super + script). If "SI", 1G. If "B", 1B. "SI" uses prefixes + from "femto" f (10^-15) to "tera" T (10^12). *SI + extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or + *SI extended* is used and the exponent is beyond the + above ranges, the formatting rule will automatically be + switched to the power notation. + labelalias + Replacement text for specific tick or hover labels. For + example using {US: 'USA', CA: 'Canada'} changes US to + USA and CA to Canada. The labels we would have shown + must match the keys exactly, after adding any + tickprefix or ticksuffix. For negative numbers the + minus sign symbol used (U+2212) is wider than the + regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis + type, and both keys (if needed) and values (if desired) + can include html-like tags or MathJax. + len + Sets the length of the color bar This measure excludes + the padding of both ends. That is, the color bar length + is this length minus the padding on both ends. + lenmode + Determines whether this color bar's length (i.e. the + measure in the color variation direction) is set in + units of plot "fraction" or in *pixels. Use `len` to + set the value. + minexponent + Hide SI prefix for 10^n if |n| is below this number. + This only has an effect when `tickformat` is "SI" or + "B". + nticks + Specifies the maximum number of ticks for the + particular axis. The actual number of ticks will be + chosen automatically to be less than or equal to + `nticks`. Has an effect only if `tickmode` is set to + "auto". + orientation + Sets the orientation of the colorbar. + outlinecolor + Sets the axis line color. + outlinewidth + Sets the width (in px) of the axis line. + separatethousands + If "true", even 4-digit integers are separated + showexponent + If "all", all exponents are shown besides their + significands. If "first", only the exponent of the + first tick is shown. If "last", only the exponent of + the last tick is shown. If "none", no exponents appear. + showticklabels + Determines whether or not the tick labels are drawn. + showtickprefix + If "all", all tick labels are displayed with a prefix. + If "first", only the first tick is displayed with a + prefix. If "last", only the last tick is displayed with + a suffix. If "none", tick prefixes are hidden. + showticksuffix + Same as `showtickprefix` but for tick suffixes. + thickness + Sets the thickness of the color bar This measure + excludes the size of the padding, ticks and labels. + thicknessmode + Determines whether this color bar's thickness (i.e. the + measure in the constant color direction) is set in + units of plot "fraction" or in "pixels". Use + `thickness` to set the value. + tick0 + Sets the placement of the first tick on this axis. Use + with `dtick`. If the axis `type` is "log", then you + must take the log of your starting tick (e.g. to set + the starting tick to 100, set the `tick0` to 2) except + when `dtick`=*L* (see `dtick` for more info). If the + axis `type` is "date", it should be a date string, like + date data. If the axis `type` is "category", it should + be a number, using the scale where each category is + assigned a serial number from zero in the order it + appears. + tickangle + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + tick labels vertically. + tickcolor + Sets the tick color. + tickfont + Sets the color bar's tick label font + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + tickformatstops + A tuple of :class:`plotly.graph_objects.choroplethmap.c + olorbar.Tickformatstop` instances or dicts with + compatible properties + tickformatstopdefaults + When used in a template (as layout.template.data.chorop + lethmap.colorbar.tickformatstopdefaults), sets the + default property values to use for elements of + choroplethmap.colorbar.tickformatstops + ticklabeloverflow + Determines how we handle tick labels that would + overflow either the graph div or the domain of the + axis. The default value for inside tick labels is *hide + past domain*. In other cases the default is *hide past + div*. + ticklabelposition + Determines where tick labels are drawn relative to the + ticks. Left and right options are used when + `orientation` is "h", top and bottom when `orientation` + is "v". + ticklabelstep + Sets the spacing between tick labels as compared to the + spacing between ticks. A value of 1 (default) means + each tick gets a label. A value of 2 means shows every + 2nd label. A larger value n means only every nth tick + is labeled. `tick0` determines which labels are shown. + Not implemented for axes with `type` "log" or + "multicategory", or when `tickmode` is "array". + ticklen + Sets the tick length (in px). + tickmode + Sets the tick mode for this axis. If "auto", the number + of ticks is set via `nticks`. If "linear", the + placement of the ticks is determined by a starting + position `tick0` and a tick step `dtick` ("linear" is + the default value if `tick0` and `dtick` are provided). + If "array", the placement of the ticks is set via + `tickvals` and the tick text is `ticktext`. ("array" is + the default value if `tickvals` is provided). + tickprefix + Sets a tick label prefix. + ticks + Determines whether ticks are drawn or not. If "", this + axis' ticks are not drawn. If "outside" ("inside"), + this axis' are drawn outside (inside) the axis lines. + ticksuffix + Sets a tick label suffix. + ticktext + Sets the text displayed at the ticks position via + `tickvals`. Only has an effect if `tickmode` is set to + "array". Used with `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + Only has an effect if `tickmode` is set to "array". + Used with `ticktext`. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + tickwidth + Sets the tick width (in px). + title + :class:`plotly.graph_objects.choroplethmap.colorbar.Tit + le` instance or dict with compatible properties + x + Sets the x position with respect to `xref` of the color + bar (in plot fraction). When `xref` is "paper", + defaults to 1.02 when `orientation` is "v" and 0.5 when + `orientation` is "h". When `xref` is "container", + defaults to 1 when `orientation` is "v" and 0.5 when + `orientation` is "h". Must be between 0 and 1 if `xref` + is "container" and between "-2" and 3 if `xref` is + "paper". + xanchor + Sets this color bar's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the color bar. Defaults to "left" when + `orientation` is "v" and "center" when `orientation` is + "h". + xpad + Sets the amount of padding (in px) along the x + direction. + xref + Sets the container `x` refers to. "container" spans the + entire `width` of the plot. "paper" refers to the width + of the plotting area only. + y + Sets the y position with respect to `yref` of the color + bar (in plot fraction). When `yref` is "paper", + defaults to 0.5 when `orientation` is "v" and 1.02 when + `orientation` is "h". When `yref` is "container", + defaults to 0.5 when `orientation` is "v" and 1 when + `orientation` is "h". Must be between 0 and 1 if `yref` + is "container" and between "-2" and 3 if `yref` is + "paper". + yanchor + Sets this color bar's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the color bar. Defaults to "middle" when + `orientation` is "v" and "bottom" when `orientation` is + "h". + ypad + Sets the amount of padding (in px) along the y + direction. + yref + Sets the container `y` refers to. "container" spans the + entire `height` of the plot. "paper" refers to the + height of the plotting area only. + + Returns + ------- + ColorBar + """ + super().__init__("colorbar") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.choroplethmap.ColorBar +constructor must be a dict or +an instance of :class:`plotly.graph_objs.choroplethmap.ColorBar`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("borderwidth", arg, borderwidth) + self._set_property("dtick", arg, dtick) + self._set_property("exponentformat", arg, exponentformat) + self._set_property("labelalias", arg, labelalias) + self._set_property("len", arg, len) + self._set_property("lenmode", arg, lenmode) + self._set_property("minexponent", arg, minexponent) + self._set_property("nticks", arg, nticks) + self._set_property("orientation", arg, orientation) + self._set_property("outlinecolor", arg, outlinecolor) + self._set_property("outlinewidth", arg, outlinewidth) + self._set_property("separatethousands", arg, separatethousands) + self._set_property("showexponent", arg, showexponent) + self._set_property("showticklabels", arg, showticklabels) + self._set_property("showtickprefix", arg, showtickprefix) + self._set_property("showticksuffix", arg, showticksuffix) + self._set_property("thickness", arg, thickness) + self._set_property("thicknessmode", arg, thicknessmode) + self._set_property("tick0", arg, tick0) + self._set_property("tickangle", arg, tickangle) + self._set_property("tickcolor", arg, tickcolor) + self._set_property("tickfont", arg, tickfont) + self._set_property("tickformat", arg, tickformat) + self._set_property("tickformatstops", arg, tickformatstops) + self._set_property("tickformatstopdefaults", arg, tickformatstopdefaults) + self._set_property("ticklabeloverflow", arg, ticklabeloverflow) + self._set_property("ticklabelposition", arg, ticklabelposition) + self._set_property("ticklabelstep", arg, ticklabelstep) + self._set_property("ticklen", arg, ticklen) + self._set_property("tickmode", arg, tickmode) + self._set_property("tickprefix", arg, tickprefix) + self._set_property("ticks", arg, ticks) + self._set_property("ticksuffix", arg, ticksuffix) + self._set_property("ticktext", arg, ticktext) + self._set_property("ticktextsrc", arg, ticktextsrc) + self._set_property("tickvals", arg, tickvals) + self._set_property("tickvalssrc", arg, tickvalssrc) + self._set_property("tickwidth", arg, tickwidth) + self._set_property("title", arg, title) + self._set_property("x", arg, x) + self._set_property("xanchor", arg, xanchor) + self._set_property("xpad", arg, xpad) + self._set_property("xref", arg, xref) + self._set_property("y", arg, y) + self._set_property("yanchor", arg, yanchor) + self._set_property("ypad", arg, ypad) + self._set_property("yref", arg, yref) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_hoverlabel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_hoverlabel.py new file mode 100644 index 0000000000000000000000000000000000000000..c1d92e416950e12f9f99ed287edf90e367c5752d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_hoverlabel.py @@ -0,0 +1,366 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Hoverlabel(_BaseTraceHierarchyType): + _parent_path_str = "choroplethmap" + _path_str = "choroplethmap.hoverlabel" + _valid_props = { + "align", + "alignsrc", + "bgcolor", + "bgcolorsrc", + "bordercolor", + "bordercolorsrc", + "font", + "namelength", + "namelengthsrc", + "showarrow", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the text content within hover + label box. Has an effect only if the hover label text spans + more two or more lines + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'auto'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def alignsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `align`. + + The 'alignsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["alignsrc"] + + @alignsrc.setter + def alignsrc(self, val): + self["alignsrc"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the hover labels for this trace + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bgcolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `bgcolor`. + + The 'bgcolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bgcolorsrc"] + + @bgcolorsrc.setter + def bgcolorsrc(self, val): + self["bgcolorsrc"] = val + + @property + def bordercolor(self): + """ + Sets the border color of the hover labels for this trace. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def bordercolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + + The 'bordercolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bordercolorsrc"] + + @bordercolorsrc.setter + def bordercolorsrc(self, val): + self["bordercolorsrc"] = val + + @property + def font(self): + """ + Sets the font used in hover labels. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmap.hoverlabel.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.choroplethmap.hoverlabel.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def namelength(self): + """ + Sets the default length (in number of characters) of the trace + name in the hover labels for all traces. -1 shows the whole + name regardless of length. 0-3 shows the first 0-3 characters, + and an integer >3 will show the whole name if it is less than + that many characters, but if it is longer, will truncate to + `namelength - 3` characters and add an ellipsis. + + The 'namelength' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["namelength"] + + @namelength.setter + def namelength(self, val): + self["namelength"] = val + + @property + def namelengthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `namelength`. + + The 'namelengthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["namelengthsrc"] + + @namelengthsrc.setter + def namelengthsrc(self, val): + self["namelengthsrc"] = val + + @property + def showarrow(self): + """ + Sets whether or not to show the hover label arrow/triangle + pointing to the data point. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + """ + + def __init__( + self, + arg=None, + align=None, + alignsrc=None, + bgcolor=None, + bgcolorsrc=None, + bordercolor=None, + bordercolorsrc=None, + font=None, + namelength=None, + namelengthsrc=None, + showarrow=None, + **kwargs, + ): + """ + Construct a new Hoverlabel object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.choroplethmap.Hoverlabel` + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + + Returns + ------- + Hoverlabel + """ + super().__init__("hoverlabel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.choroplethmap.Hoverlabel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.choroplethmap.Hoverlabel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("alignsrc", arg, alignsrc) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bgcolorsrc", arg, bgcolorsrc) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("bordercolorsrc", arg, bordercolorsrc) + self._set_property("font", arg, font) + self._set_property("namelength", arg, namelength) + self._set_property("namelengthsrc", arg, namelengthsrc) + self._set_property("showarrow", arg, showarrow) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..ddfbdfdf11c7276057c858d7360856325b386227 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "choroplethmap" + _path_str = "choroplethmap.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmap.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.choroplethmap.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.choroplethmap. + Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.choroplethmap.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.choroplethmap.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_marker.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_marker.py new file mode 100644 index 0000000000000000000000000000000000000000..0f7f498b9288dc28961e83c33924cfe4bd110594 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_marker.py @@ -0,0 +1,129 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Marker(_BaseTraceHierarchyType): + _parent_path_str = "choroplethmap" + _path_str = "choroplethmap.marker" + _valid_props = {"line", "opacity", "opacitysrc"} + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmap.marker.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.choroplethmap.marker.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def opacity(self): + """ + Sets the opacity of the locations. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def opacitysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `opacity`. + + The 'opacitysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["opacitysrc"] + + @opacitysrc.setter + def opacitysrc(self, val): + self["opacitysrc"] = val + + @property + def _prop_descriptions(self): + return """\ + line + :class:`plotly.graph_objects.choroplethmap.marker.Line` + instance or dict with compatible properties + opacity + Sets the opacity of the locations. + opacitysrc + Sets the source reference on Chart Studio Cloud for + `opacity`. + """ + + def __init__(self, arg=None, line=None, opacity=None, opacitysrc=None, **kwargs): + """ + Construct a new Marker object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.choroplethmap.Marker` + line + :class:`plotly.graph_objects.choroplethmap.marker.Line` + instance or dict with compatible properties + opacity + Sets the opacity of the locations. + opacitysrc + Sets the source reference on Chart Studio Cloud for + `opacity`. + + Returns + ------- + Marker + """ + super().__init__("marker") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.choroplethmap.Marker +constructor must be a dict or +an instance of :class:`plotly.graph_objs.choroplethmap.Marker`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("line", arg, line) + self._set_property("opacity", arg, opacity) + self._set_property("opacitysrc", arg, opacitysrc) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_selected.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_selected.py new file mode 100644 index 0000000000000000000000000000000000000000..e68c38fe4806b4e76a804dfb368897a9265af076 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_selected.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Selected(_BaseTraceHierarchyType): + _parent_path_str = "choroplethmap" + _path_str = "choroplethmap.selected" + _valid_props = {"marker"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmap.selected.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.choroplethmap.selected.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.choroplethmap.selected.Mar + ker` instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, **kwargs): + """ + Construct a new Selected object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.choroplethmap.Selected` + marker + :class:`plotly.graph_objects.choroplethmap.selected.Mar + ker` instance or dict with compatible properties + + Returns + ------- + Selected + """ + super().__init__("selected") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.choroplethmap.Selected +constructor must be a dict or +an instance of :class:`plotly.graph_objs.choroplethmap.Selected`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..348b27d96429133ed7168c2657e8d294d159ad19 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_stream.py @@ -0,0 +1,114 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "choroplethmap" + _path_str = "choroplethmap.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.choroplethmap.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.choroplethmap.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.choroplethmap.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_unselected.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_unselected.py new file mode 100644 index 0000000000000000000000000000000000000000..fcbf6a8fb82746da20103c9948ab561968dbc5f1 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/choroplethmap/_unselected.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Unselected(_BaseTraceHierarchyType): + _parent_path_str = "choroplethmap" + _path_str = "choroplethmap.unselected" + _valid_props = {"marker"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.choroplethmap.unselected.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.choroplethmap.unselected.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.choroplethmap.unselected.M + arker` instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, **kwargs): + """ + Construct a new Unselected object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.choroplethmap.Unselected` + marker + :class:`plotly.graph_objects.choroplethmap.unselected.M + arker` instance or dict with compatible properties + + Returns + ------- + Unselected + """ + super().__init__("unselected") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.choroplethmap.Unselected +constructor must be a dict or +an instance of :class:`plotly.graph_objs.choroplethmap.Unselected`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/contour/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/contour/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..335ba2577d1676cf0689398d6f0328e3b7e2ab0f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/contour/__init__.py @@ -0,0 +1,31 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._colorbar import ColorBar + from ._contours import Contours + from ._hoverlabel import Hoverlabel + from ._legendgrouptitle import Legendgrouptitle + from ._line import Line + from ._stream import Stream + from ._textfont import Textfont + from . import colorbar + from . import contours + from . import hoverlabel + from . import legendgrouptitle +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [".colorbar", ".contours", ".hoverlabel", ".legendgrouptitle"], + [ + "._colorbar.ColorBar", + "._contours.Contours", + "._hoverlabel.Hoverlabel", + "._legendgrouptitle.Legendgrouptitle", + "._line.Line", + "._stream.Stream", + "._textfont.Textfont", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/contour/_colorbar.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/contour/_colorbar.py new file mode 100644 index 0000000000000000000000000000000000000000..f51584db1623506e7013c58abedc006156459681 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/contour/_colorbar.py @@ -0,0 +1,1739 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class ColorBar(_BaseTraceHierarchyType): + _parent_path_str = "contour" + _path_str = "contour.colorbar" + _valid_props = { + "bgcolor", + "bordercolor", + "borderwidth", + "dtick", + "exponentformat", + "labelalias", + "len", + "lenmode", + "minexponent", + "nticks", + "orientation", + "outlinecolor", + "outlinewidth", + "separatethousands", + "showexponent", + "showticklabels", + "showtickprefix", + "showticksuffix", + "thickness", + "thicknessmode", + "tick0", + "tickangle", + "tickcolor", + "tickfont", + "tickformat", + "tickformatstopdefaults", + "tickformatstops", + "ticklabeloverflow", + "ticklabelposition", + "ticklabelstep", + "ticklen", + "tickmode", + "tickprefix", + "ticks", + "ticksuffix", + "ticktext", + "ticktextsrc", + "tickvals", + "tickvalssrc", + "tickwidth", + "title", + "x", + "xanchor", + "xpad", + "xref", + "y", + "yanchor", + "ypad", + "yref", + } + + @property + def bgcolor(self): + """ + Sets the color of padded area. + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bordercolor(self): + """ + Sets the axis line color. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def borderwidth(self): + """ + Sets the width (in px) or the border enclosing this color bar. + + The 'borderwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["borderwidth"] + + @borderwidth.setter + def borderwidth(self, val): + self["borderwidth"] = val + + @property + def dtick(self): + """ + Sets the step in-between ticks on this axis. Use with `tick0`. + Must be a positive number, or special strings available to + "log" and "date" axes. If the axis `type` is "log", then ticks + are set every 10^(n*dtick) where n is the tick number. For + example, to set a tick mark at 1, 10, 100, 1000, ... set dtick + to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. + To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special values; + "L", where `f` is a positive number, gives ticks linearly + spaced in value (but not position). For example `tick0` = 0.1, + `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To + show powers of 10 plus small digits between, use "D1" (all + digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and + "D2". If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval between + ticks to one day, set `dtick` to 86400000.0. "date" also has + special values "M" gives ticks spaced by a number of months. + `n` must be a positive integer. To set ticks on the 15th of + every third month, set `tick0` to "2000-01-15" and `dtick` to + "M3". To set ticks every 4 years, set `dtick` to "M48" + + The 'dtick' property accepts values of any type + + Returns + ------- + Any + """ + return self["dtick"] + + @dtick.setter + def dtick(self, val): + self["dtick"] = val + + @property + def exponentformat(self): + """ + Determines a formatting rule for the tick exponents. For + example, consider the number 1,000,000,000. If "none", it + appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If + "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If + "B", 1B. "SI" uses prefixes from "femto" f (10^-15) to "tera" T + (10^12). *SI extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or *SI + extended* is used and the exponent is beyond the above ranges, + the formatting rule will automatically be switched to the power + notation. + + The 'exponentformat' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'e', 'E', 'power', 'SI', 'B', 'SI extended'] + + Returns + ------- + Any + """ + return self["exponentformat"] + + @exponentformat.setter + def exponentformat(self, val): + self["exponentformat"] = val + + @property + def labelalias(self): + """ + Replacement text for specific tick or hover labels. For example + using {US: 'USA', CA: 'Canada'} changes US to USA and CA to + Canada. The labels we would have shown must match the keys + exactly, after adding any tickprefix or ticksuffix. For + negative numbers the minus sign symbol used (U+2212) is wider + than the regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis type, and + both keys (if needed) and values (if desired) can include html- + like tags or MathJax. + + The 'labelalias' property accepts values of any type + + Returns + ------- + Any + """ + return self["labelalias"] + + @labelalias.setter + def labelalias(self, val): + self["labelalias"] = val + + @property + def len(self): + """ + Sets the length of the color bar This measure excludes the + padding of both ends. That is, the color bar length is this + length minus the padding on both ends. + + The 'len' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["len"] + + @len.setter + def len(self, val): + self["len"] = val + + @property + def lenmode(self): + """ + Determines whether this color bar's length (i.e. the measure in + the color variation direction) is set in units of plot + "fraction" or in *pixels. Use `len` to set the value. + + The 'lenmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fraction', 'pixels'] + + Returns + ------- + Any + """ + return self["lenmode"] + + @lenmode.setter + def lenmode(self, val): + self["lenmode"] = val + + @property + def minexponent(self): + """ + Hide SI prefix for 10^n if |n| is below this number. This only + has an effect when `tickformat` is "SI" or "B". + + The 'minexponent' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["minexponent"] + + @minexponent.setter + def minexponent(self, val): + self["minexponent"] = val + + @property + def nticks(self): + """ + Specifies the maximum number of ticks for the particular axis. + The actual number of ticks will be chosen automatically to be + less than or equal to `nticks`. Has an effect only if + `tickmode` is set to "auto". + + The 'nticks' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["nticks"] + + @nticks.setter + def nticks(self, val): + self["nticks"] = val + + @property + def orientation(self): + """ + Sets the orientation of the colorbar. + + The 'orientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['h', 'v'] + + Returns + ------- + Any + """ + return self["orientation"] + + @orientation.setter + def orientation(self, val): + self["orientation"] = val + + @property + def outlinecolor(self): + """ + Sets the axis line color. + + The 'outlinecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["outlinecolor"] + + @outlinecolor.setter + def outlinecolor(self, val): + self["outlinecolor"] = val + + @property + def outlinewidth(self): + """ + Sets the width (in px) of the axis line. + + The 'outlinewidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["outlinewidth"] + + @outlinewidth.setter + def outlinewidth(self, val): + self["outlinewidth"] = val + + @property + def separatethousands(self): + """ + If "true", even 4-digit integers are separated + + The 'separatethousands' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["separatethousands"] + + @separatethousands.setter + def separatethousands(self, val): + self["separatethousands"] = val + + @property + def showexponent(self): + """ + If "all", all exponents are shown besides their significands. + If "first", only the exponent of the first tick is shown. If + "last", only the exponent of the last tick is shown. If "none", + no exponents appear. + + The 'showexponent' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showexponent"] + + @showexponent.setter + def showexponent(self, val): + self["showexponent"] = val + + @property + def showticklabels(self): + """ + Determines whether or not the tick labels are drawn. + + The 'showticklabels' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showticklabels"] + + @showticklabels.setter + def showticklabels(self, val): + self["showticklabels"] = val + + @property + def showtickprefix(self): + """ + If "all", all tick labels are displayed with a prefix. If + "first", only the first tick is displayed with a prefix. If + "last", only the last tick is displayed with a suffix. If + "none", tick prefixes are hidden. + + The 'showtickprefix' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showtickprefix"] + + @showtickprefix.setter + def showtickprefix(self, val): + self["showtickprefix"] = val + + @property + def showticksuffix(self): + """ + Same as `showtickprefix` but for tick suffixes. + + The 'showticksuffix' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showticksuffix"] + + @showticksuffix.setter + def showticksuffix(self, val): + self["showticksuffix"] = val + + @property + def thickness(self): + """ + Sets the thickness of the color bar This measure excludes the + size of the padding, ticks and labels. + + The 'thickness' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["thickness"] + + @thickness.setter + def thickness(self, val): + self["thickness"] = val + + @property + def thicknessmode(self): + """ + Determines whether this color bar's thickness (i.e. the measure + in the constant color direction) is set in units of plot + "fraction" or in "pixels". Use `thickness` to set the value. + + The 'thicknessmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fraction', 'pixels'] + + Returns + ------- + Any + """ + return self["thicknessmode"] + + @thicknessmode.setter + def thicknessmode(self, val): + self["thicknessmode"] = val + + @property + def tick0(self): + """ + Sets the placement of the first tick on this axis. Use with + `dtick`. If the axis `type` is "log", then you must take the + log of your starting tick (e.g. to set the starting tick to + 100, set the `tick0` to 2) except when `dtick`=*L* (see + `dtick` for more info). If the axis `type` is "date", it should + be a date string, like date data. If the axis `type` is + "category", it should be a number, using the scale where each + category is assigned a serial number from zero in the order it + appears. + + The 'tick0' property accepts values of any type + + Returns + ------- + Any + """ + return self["tick0"] + + @tick0.setter + def tick0(self, val): + self["tick0"] = val + + @property + def tickangle(self): + """ + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the tick + labels vertically. + + The 'tickangle' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["tickangle"] + + @tickangle.setter + def tickangle(self, val): + self["tickangle"] = val + + @property + def tickcolor(self): + """ + Sets the tick color. + + The 'tickcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["tickcolor"] + + @tickcolor.setter + def tickcolor(self, val): + self["tickcolor"] = val + + @property + def tickfont(self): + """ + Sets the color bar's tick label font + + The 'tickfont' property is an instance of Tickfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.contour.colorbar.Tickfont` + - A dict of string/value properties that will be passed + to the Tickfont constructor + + Returns + ------- + plotly.graph_objs.contour.colorbar.Tickfont + """ + return self["tickfont"] + + @tickfont.setter + def tickfont(self, val): + self["tickfont"] = val + + @property + def tickformat(self): + """ + Sets the tick label formatting rule using d3 formatting mini- + languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display "09~15~23.46" + + The 'tickformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["tickformat"] + + @tickformat.setter + def tickformat(self, val): + self["tickformat"] = val + + @property + def tickformatstops(self): + """ + The 'tickformatstops' property is a tuple of instances of + Tickformatstop that may be specified as: + - A list or tuple of instances of plotly.graph_objs.contour.colorbar.Tickformatstop + - A list or tuple of dicts of string/value properties that + will be passed to the Tickformatstop constructor + + Returns + ------- + tuple[plotly.graph_objs.contour.colorbar.Tickformatstop] + """ + return self["tickformatstops"] + + @tickformatstops.setter + def tickformatstops(self, val): + self["tickformatstops"] = val + + @property + def tickformatstopdefaults(self): + """ + When used in a template (as + layout.template.data.contour.colorbar.tickformatstopdefaults), + sets the default property values to use for elements of + contour.colorbar.tickformatstops + + The 'tickformatstopdefaults' property is an instance of Tickformatstop + that may be specified as: + - An instance of :class:`plotly.graph_objs.contour.colorbar.Tickformatstop` + - A dict of string/value properties that will be passed + to the Tickformatstop constructor + + Returns + ------- + plotly.graph_objs.contour.colorbar.Tickformatstop + """ + return self["tickformatstopdefaults"] + + @tickformatstopdefaults.setter + def tickformatstopdefaults(self, val): + self["tickformatstopdefaults"] = val + + @property + def ticklabeloverflow(self): + """ + Determines how we handle tick labels that would overflow either + the graph div or the domain of the axis. The default value for + inside tick labels is *hide past domain*. In other cases the + default is *hide past div*. + + The 'ticklabeloverflow' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['allow', 'hide past div', 'hide past domain'] + + Returns + ------- + Any + """ + return self["ticklabeloverflow"] + + @ticklabeloverflow.setter + def ticklabeloverflow(self, val): + self["ticklabeloverflow"] = val + + @property + def ticklabelposition(self): + """ + Determines where tick labels are drawn relative to the ticks. + Left and right options are used when `orientation` is "h", top + and bottom when `orientation` is "v". + + The 'ticklabelposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['outside', 'inside', 'outside top', 'inside top', + 'outside left', 'inside left', 'outside right', 'inside + right', 'outside bottom', 'inside bottom'] + + Returns + ------- + Any + """ + return self["ticklabelposition"] + + @ticklabelposition.setter + def ticklabelposition(self, val): + self["ticklabelposition"] = val + + @property + def ticklabelstep(self): + """ + Sets the spacing between tick labels as compared to the spacing + between ticks. A value of 1 (default) means each tick gets a + label. A value of 2 means shows every 2nd label. A larger value + n means only every nth tick is labeled. `tick0` determines + which labels are shown. Not implemented for axes with `type` + "log" or "multicategory", or when `tickmode` is "array". + + The 'ticklabelstep' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 9223372036854775807] + + Returns + ------- + int + """ + return self["ticklabelstep"] + + @ticklabelstep.setter + def ticklabelstep(self, val): + self["ticklabelstep"] = val + + @property + def ticklen(self): + """ + Sets the tick length (in px). + + The 'ticklen' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["ticklen"] + + @ticklen.setter + def ticklen(self, val): + self["ticklen"] = val + + @property + def tickmode(self): + """ + Sets the tick mode for this axis. If "auto", the number of + ticks is set via `nticks`. If "linear", the placement of the + ticks is determined by a starting position `tick0` and a tick + step `dtick` ("linear" is the default value if `tick0` and + `dtick` are provided). If "array", the placement of the ticks + is set via `tickvals` and the tick text is `ticktext`. ("array" + is the default value if `tickvals` is provided). + + The 'tickmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'linear', 'array'] + + Returns + ------- + Any + """ + return self["tickmode"] + + @tickmode.setter + def tickmode(self, val): + self["tickmode"] = val + + @property + def tickprefix(self): + """ + Sets a tick label prefix. + + The 'tickprefix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["tickprefix"] + + @tickprefix.setter + def tickprefix(self, val): + self["tickprefix"] = val + + @property + def ticks(self): + """ + Determines whether ticks are drawn or not. If "", this axis' + ticks are not drawn. If "outside" ("inside"), this axis' are + drawn outside (inside) the axis lines. + + The 'ticks' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['outside', 'inside', ''] + + Returns + ------- + Any + """ + return self["ticks"] + + @ticks.setter + def ticks(self, val): + self["ticks"] = val + + @property + def ticksuffix(self): + """ + Sets a tick label suffix. + + The 'ticksuffix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["ticksuffix"] + + @ticksuffix.setter + def ticksuffix(self, val): + self["ticksuffix"] = val + + @property + def ticktext(self): + """ + Sets the text displayed at the ticks position via `tickvals`. + Only has an effect if `tickmode` is set to "array". Used with + `tickvals`. + + The 'ticktext' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ticktext"] + + @ticktext.setter + def ticktext(self, val): + self["ticktext"] = val + + @property + def ticktextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ticktext`. + + The 'ticktextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ticktextsrc"] + + @ticktextsrc.setter + def ticktextsrc(self, val): + self["ticktextsrc"] = val + + @property + def tickvals(self): + """ + Sets the values at which ticks on this axis appear. Only has an + effect if `tickmode` is set to "array". Used with `ticktext`. + + The 'tickvals' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["tickvals"] + + @tickvals.setter + def tickvals(self, val): + self["tickvals"] = val + + @property + def tickvalssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `tickvals`. + + The 'tickvalssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["tickvalssrc"] + + @tickvalssrc.setter + def tickvalssrc(self, val): + self["tickvalssrc"] = val + + @property + def tickwidth(self): + """ + Sets the tick width (in px). + + The 'tickwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["tickwidth"] + + @tickwidth.setter + def tickwidth(self, val): + self["tickwidth"] = val + + @property + def title(self): + """ + The 'title' property is an instance of Title + that may be specified as: + - An instance of :class:`plotly.graph_objs.contour.colorbar.Title` + - A dict of string/value properties that will be passed + to the Title constructor + + Returns + ------- + plotly.graph_objs.contour.colorbar.Title + """ + return self["title"] + + @title.setter + def title(self, val): + self["title"] = val + + @property + def x(self): + """ + Sets the x position with respect to `xref` of the color bar (in + plot fraction). When `xref` is "paper", defaults to 1.02 when + `orientation` is "v" and 0.5 when `orientation` is "h". When + `xref` is "container", defaults to 1 when `orientation` is "v" + and 0.5 when `orientation` is "h". Must be between 0 and 1 if + `xref` is "container" and between "-2" and 3 if `xref` is + "paper". + + The 'x' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xanchor(self): + """ + Sets this color bar's horizontal position anchor. This anchor + binds the `x` position to the "left", "center" or "right" of + the color bar. Defaults to "left" when `orientation` is "v" and + "center" when `orientation` is "h". + + The 'xanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'center', 'right'] + + Returns + ------- + Any + """ + return self["xanchor"] + + @xanchor.setter + def xanchor(self, val): + self["xanchor"] = val + + @property + def xpad(self): + """ + Sets the amount of padding (in px) along the x direction. + + The 'xpad' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["xpad"] + + @xpad.setter + def xpad(self, val): + self["xpad"] = val + + @property + def xref(self): + """ + Sets the container `x` refers to. "container" spans the entire + `width` of the plot. "paper" refers to the width of the + plotting area only. + + The 'xref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['container', 'paper'] + + Returns + ------- + Any + """ + return self["xref"] + + @xref.setter + def xref(self, val): + self["xref"] = val + + @property + def y(self): + """ + Sets the y position with respect to `yref` of the color bar (in + plot fraction). When `yref` is "paper", defaults to 0.5 when + `orientation` is "v" and 1.02 when `orientation` is "h". When + `yref` is "container", defaults to 0.5 when `orientation` is + "v" and 1 when `orientation` is "h". Must be between 0 and 1 if + `yref` is "container" and between "-2" and 3 if `yref` is + "paper". + + The 'y' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yanchor(self): + """ + Sets this color bar's vertical position anchor This anchor + binds the `y` position to the "top", "middle" or "bottom" of + the color bar. Defaults to "middle" when `orientation` is "v" + and "bottom" when `orientation` is "h". + + The 'yanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top', 'middle', 'bottom'] + + Returns + ------- + Any + """ + return self["yanchor"] + + @yanchor.setter + def yanchor(self, val): + self["yanchor"] = val + + @property + def ypad(self): + """ + Sets the amount of padding (in px) along the y direction. + + The 'ypad' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["ypad"] + + @ypad.setter + def ypad(self, val): + self["ypad"] = val + + @property + def yref(self): + """ + Sets the container `y` refers to. "container" spans the entire + `height` of the plot. "paper" refers to the height of the + plotting area only. + + The 'yref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['container', 'paper'] + + Returns + ------- + Any + """ + return self["yref"] + + @yref.setter + def yref(self, val): + self["yref"] = val + + @property + def _prop_descriptions(self): + return """\ + bgcolor + Sets the color of padded area. + bordercolor + Sets the axis line color. + borderwidth + Sets the width (in px) or the border enclosing this + color bar. + dtick + Sets the step in-between ticks on this axis. Use with + `tick0`. Must be a positive number, or special strings + available to "log" and "date" axes. If the axis `type` + is "log", then ticks are set every 10^(n*dtick) where n + is the tick number. For example, to set a tick mark at + 1, 10, 100, 1000, ... set dtick to 1. To set tick marks + at 1, 100, 10000, ... set dtick to 2. To set tick marks + at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special + values; "L", where `f` is a positive number, gives + ticks linearly spaced in value (but not position). For + example `tick0` = 0.1, `dtick` = "L0.5" will put ticks + at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus + small digits between, use "D1" (all digits) or "D2" + (only 2 and 5). `tick0` is ignored for "D1" and "D2". + If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval + between ticks to one day, set `dtick` to 86400000.0. + "date" also has special values "M" gives ticks + spaced by a number of months. `n` must be a positive + integer. To set ticks on the 15th of every third month, + set `tick0` to "2000-01-15" and `dtick` to "M3". To set + ticks every 4 years, set `dtick` to "M48" + exponentformat + Determines a formatting rule for the tick exponents. + For example, consider the number 1,000,000,000. If + "none", it appears as 1,000,000,000. If "e", 1e+9. If + "E", 1E+9. If "power", 1x10^9 (with 9 in a super + script). If "SI", 1G. If "B", 1B. "SI" uses prefixes + from "femto" f (10^-15) to "tera" T (10^12). *SI + extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or + *SI extended* is used and the exponent is beyond the + above ranges, the formatting rule will automatically be + switched to the power notation. + labelalias + Replacement text for specific tick or hover labels. For + example using {US: 'USA', CA: 'Canada'} changes US to + USA and CA to Canada. The labels we would have shown + must match the keys exactly, after adding any + tickprefix or ticksuffix. For negative numbers the + minus sign symbol used (U+2212) is wider than the + regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis + type, and both keys (if needed) and values (if desired) + can include html-like tags or MathJax. + len + Sets the length of the color bar This measure excludes + the padding of both ends. That is, the color bar length + is this length minus the padding on both ends. + lenmode + Determines whether this color bar's length (i.e. the + measure in the color variation direction) is set in + units of plot "fraction" or in *pixels. Use `len` to + set the value. + minexponent + Hide SI prefix for 10^n if |n| is below this number. + This only has an effect when `tickformat` is "SI" or + "B". + nticks + Specifies the maximum number of ticks for the + particular axis. The actual number of ticks will be + chosen automatically to be less than or equal to + `nticks`. Has an effect only if `tickmode` is set to + "auto". + orientation + Sets the orientation of the colorbar. + outlinecolor + Sets the axis line color. + outlinewidth + Sets the width (in px) of the axis line. + separatethousands + If "true", even 4-digit integers are separated + showexponent + If "all", all exponents are shown besides their + significands. If "first", only the exponent of the + first tick is shown. If "last", only the exponent of + the last tick is shown. If "none", no exponents appear. + showticklabels + Determines whether or not the tick labels are drawn. + showtickprefix + If "all", all tick labels are displayed with a prefix. + If "first", only the first tick is displayed with a + prefix. If "last", only the last tick is displayed with + a suffix. If "none", tick prefixes are hidden. + showticksuffix + Same as `showtickprefix` but for tick suffixes. + thickness + Sets the thickness of the color bar This measure + excludes the size of the padding, ticks and labels. + thicknessmode + Determines whether this color bar's thickness (i.e. the + measure in the constant color direction) is set in + units of plot "fraction" or in "pixels". Use + `thickness` to set the value. + tick0 + Sets the placement of the first tick on this axis. Use + with `dtick`. If the axis `type` is "log", then you + must take the log of your starting tick (e.g. to set + the starting tick to 100, set the `tick0` to 2) except + when `dtick`=*L* (see `dtick` for more info). If the + axis `type` is "date", it should be a date string, like + date data. If the axis `type` is "category", it should + be a number, using the scale where each category is + assigned a serial number from zero in the order it + appears. + tickangle + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + tick labels vertically. + tickcolor + Sets the tick color. + tickfont + Sets the color bar's tick label font + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + tickformatstops + A tuple of :class:`plotly.graph_objects.contour.colorba + r.Tickformatstop` instances or dicts with compatible + properties + tickformatstopdefaults + When used in a template (as layout.template.data.contou + r.colorbar.tickformatstopdefaults), sets the default + property values to use for elements of + contour.colorbar.tickformatstops + ticklabeloverflow + Determines how we handle tick labels that would + overflow either the graph div or the domain of the + axis. The default value for inside tick labels is *hide + past domain*. In other cases the default is *hide past + div*. + ticklabelposition + Determines where tick labels are drawn relative to the + ticks. Left and right options are used when + `orientation` is "h", top and bottom when `orientation` + is "v". + ticklabelstep + Sets the spacing between tick labels as compared to the + spacing between ticks. A value of 1 (default) means + each tick gets a label. A value of 2 means shows every + 2nd label. A larger value n means only every nth tick + is labeled. `tick0` determines which labels are shown. + Not implemented for axes with `type` "log" or + "multicategory", or when `tickmode` is "array". + ticklen + Sets the tick length (in px). + tickmode + Sets the tick mode for this axis. If "auto", the number + of ticks is set via `nticks`. If "linear", the + placement of the ticks is determined by a starting + position `tick0` and a tick step `dtick` ("linear" is + the default value if `tick0` and `dtick` are provided). + If "array", the placement of the ticks is set via + `tickvals` and the tick text is `ticktext`. ("array" is + the default value if `tickvals` is provided). + tickprefix + Sets a tick label prefix. + ticks + Determines whether ticks are drawn or not. If "", this + axis' ticks are not drawn. If "outside" ("inside"), + this axis' are drawn outside (inside) the axis lines. + ticksuffix + Sets a tick label suffix. + ticktext + Sets the text displayed at the ticks position via + `tickvals`. Only has an effect if `tickmode` is set to + "array". Used with `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + Only has an effect if `tickmode` is set to "array". + Used with `ticktext`. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + tickwidth + Sets the tick width (in px). + title + :class:`plotly.graph_objects.contour.colorbar.Title` + instance or dict with compatible properties + x + Sets the x position with respect to `xref` of the color + bar (in plot fraction). When `xref` is "paper", + defaults to 1.02 when `orientation` is "v" and 0.5 when + `orientation` is "h". When `xref` is "container", + defaults to 1 when `orientation` is "v" and 0.5 when + `orientation` is "h". Must be between 0 and 1 if `xref` + is "container" and between "-2" and 3 if `xref` is + "paper". + xanchor + Sets this color bar's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the color bar. Defaults to "left" when + `orientation` is "v" and "center" when `orientation` is + "h". + xpad + Sets the amount of padding (in px) along the x + direction. + xref + Sets the container `x` refers to. "container" spans the + entire `width` of the plot. "paper" refers to the width + of the plotting area only. + y + Sets the y position with respect to `yref` of the color + bar (in plot fraction). When `yref` is "paper", + defaults to 0.5 when `orientation` is "v" and 1.02 when + `orientation` is "h". When `yref` is "container", + defaults to 0.5 when `orientation` is "v" and 1 when + `orientation` is "h". Must be between 0 and 1 if `yref` + is "container" and between "-2" and 3 if `yref` is + "paper". + yanchor + Sets this color bar's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the color bar. Defaults to "middle" when + `orientation` is "v" and "bottom" when `orientation` is + "h". + ypad + Sets the amount of padding (in px) along the y + direction. + yref + Sets the container `y` refers to. "container" spans the + entire `height` of the plot. "paper" refers to the + height of the plotting area only. + """ + + def __init__( + self, + arg=None, + bgcolor=None, + bordercolor=None, + borderwidth=None, + dtick=None, + exponentformat=None, + labelalias=None, + len=None, + lenmode=None, + minexponent=None, + nticks=None, + orientation=None, + outlinecolor=None, + outlinewidth=None, + separatethousands=None, + showexponent=None, + showticklabels=None, + showtickprefix=None, + showticksuffix=None, + thickness=None, + thicknessmode=None, + tick0=None, + tickangle=None, + tickcolor=None, + tickfont=None, + tickformat=None, + tickformatstops=None, + tickformatstopdefaults=None, + ticklabeloverflow=None, + ticklabelposition=None, + ticklabelstep=None, + ticklen=None, + tickmode=None, + tickprefix=None, + ticks=None, + ticksuffix=None, + ticktext=None, + ticktextsrc=None, + tickvals=None, + tickvalssrc=None, + tickwidth=None, + title=None, + x=None, + xanchor=None, + xpad=None, + xref=None, + y=None, + yanchor=None, + ypad=None, + yref=None, + **kwargs, + ): + """ + Construct a new ColorBar object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.contour.ColorBar` + bgcolor + Sets the color of padded area. + bordercolor + Sets the axis line color. + borderwidth + Sets the width (in px) or the border enclosing this + color bar. + dtick + Sets the step in-between ticks on this axis. Use with + `tick0`. Must be a positive number, or special strings + available to "log" and "date" axes. If the axis `type` + is "log", then ticks are set every 10^(n*dtick) where n + is the tick number. For example, to set a tick mark at + 1, 10, 100, 1000, ... set dtick to 1. To set tick marks + at 1, 100, 10000, ... set dtick to 2. To set tick marks + at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special + values; "L", where `f` is a positive number, gives + ticks linearly spaced in value (but not position). For + example `tick0` = 0.1, `dtick` = "L0.5" will put ticks + at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus + small digits between, use "D1" (all digits) or "D2" + (only 2 and 5). `tick0` is ignored for "D1" and "D2". + If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval + between ticks to one day, set `dtick` to 86400000.0. + "date" also has special values "M" gives ticks + spaced by a number of months. `n` must be a positive + integer. To set ticks on the 15th of every third month, + set `tick0` to "2000-01-15" and `dtick` to "M3". To set + ticks every 4 years, set `dtick` to "M48" + exponentformat + Determines a formatting rule for the tick exponents. + For example, consider the number 1,000,000,000. If + "none", it appears as 1,000,000,000. If "e", 1e+9. If + "E", 1E+9. If "power", 1x10^9 (with 9 in a super + script). If "SI", 1G. If "B", 1B. "SI" uses prefixes + from "femto" f (10^-15) to "tera" T (10^12). *SI + extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or + *SI extended* is used and the exponent is beyond the + above ranges, the formatting rule will automatically be + switched to the power notation. + labelalias + Replacement text for specific tick or hover labels. For + example using {US: 'USA', CA: 'Canada'} changes US to + USA and CA to Canada. The labels we would have shown + must match the keys exactly, after adding any + tickprefix or ticksuffix. For negative numbers the + minus sign symbol used (U+2212) is wider than the + regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis + type, and both keys (if needed) and values (if desired) + can include html-like tags or MathJax. + len + Sets the length of the color bar This measure excludes + the padding of both ends. That is, the color bar length + is this length minus the padding on both ends. + lenmode + Determines whether this color bar's length (i.e. the + measure in the color variation direction) is set in + units of plot "fraction" or in *pixels. Use `len` to + set the value. + minexponent + Hide SI prefix for 10^n if |n| is below this number. + This only has an effect when `tickformat` is "SI" or + "B". + nticks + Specifies the maximum number of ticks for the + particular axis. The actual number of ticks will be + chosen automatically to be less than or equal to + `nticks`. Has an effect only if `tickmode` is set to + "auto". + orientation + Sets the orientation of the colorbar. + outlinecolor + Sets the axis line color. + outlinewidth + Sets the width (in px) of the axis line. + separatethousands + If "true", even 4-digit integers are separated + showexponent + If "all", all exponents are shown besides their + significands. If "first", only the exponent of the + first tick is shown. If "last", only the exponent of + the last tick is shown. If "none", no exponents appear. + showticklabels + Determines whether or not the tick labels are drawn. + showtickprefix + If "all", all tick labels are displayed with a prefix. + If "first", only the first tick is displayed with a + prefix. If "last", only the last tick is displayed with + a suffix. If "none", tick prefixes are hidden. + showticksuffix + Same as `showtickprefix` but for tick suffixes. + thickness + Sets the thickness of the color bar This measure + excludes the size of the padding, ticks and labels. + thicknessmode + Determines whether this color bar's thickness (i.e. the + measure in the constant color direction) is set in + units of plot "fraction" or in "pixels". Use + `thickness` to set the value. + tick0 + Sets the placement of the first tick on this axis. Use + with `dtick`. If the axis `type` is "log", then you + must take the log of your starting tick (e.g. to set + the starting tick to 100, set the `tick0` to 2) except + when `dtick`=*L* (see `dtick` for more info). If the + axis `type` is "date", it should be a date string, like + date data. If the axis `type` is "category", it should + be a number, using the scale where each category is + assigned a serial number from zero in the order it + appears. + tickangle + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + tick labels vertically. + tickcolor + Sets the tick color. + tickfont + Sets the color bar's tick label font + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + tickformatstops + A tuple of :class:`plotly.graph_objects.contour.colorba + r.Tickformatstop` instances or dicts with compatible + properties + tickformatstopdefaults + When used in a template (as layout.template.data.contou + r.colorbar.tickformatstopdefaults), sets the default + property values to use for elements of + contour.colorbar.tickformatstops + ticklabeloverflow + Determines how we handle tick labels that would + overflow either the graph div or the domain of the + axis. The default value for inside tick labels is *hide + past domain*. In other cases the default is *hide past + div*. + ticklabelposition + Determines where tick labels are drawn relative to the + ticks. Left and right options are used when + `orientation` is "h", top and bottom when `orientation` + is "v". + ticklabelstep + Sets the spacing between tick labels as compared to the + spacing between ticks. A value of 1 (default) means + each tick gets a label. A value of 2 means shows every + 2nd label. A larger value n means only every nth tick + is labeled. `tick0` determines which labels are shown. + Not implemented for axes with `type` "log" or + "multicategory", or when `tickmode` is "array". + ticklen + Sets the tick length (in px). + tickmode + Sets the tick mode for this axis. If "auto", the number + of ticks is set via `nticks`. If "linear", the + placement of the ticks is determined by a starting + position `tick0` and a tick step `dtick` ("linear" is + the default value if `tick0` and `dtick` are provided). + If "array", the placement of the ticks is set via + `tickvals` and the tick text is `ticktext`. ("array" is + the default value if `tickvals` is provided). + tickprefix + Sets a tick label prefix. + ticks + Determines whether ticks are drawn or not. If "", this + axis' ticks are not drawn. If "outside" ("inside"), + this axis' are drawn outside (inside) the axis lines. + ticksuffix + Sets a tick label suffix. + ticktext + Sets the text displayed at the ticks position via + `tickvals`. Only has an effect if `tickmode` is set to + "array". Used with `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + Only has an effect if `tickmode` is set to "array". + Used with `ticktext`. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + tickwidth + Sets the tick width (in px). + title + :class:`plotly.graph_objects.contour.colorbar.Title` + instance or dict with compatible properties + x + Sets the x position with respect to `xref` of the color + bar (in plot fraction). When `xref` is "paper", + defaults to 1.02 when `orientation` is "v" and 0.5 when + `orientation` is "h". When `xref` is "container", + defaults to 1 when `orientation` is "v" and 0.5 when + `orientation` is "h". Must be between 0 and 1 if `xref` + is "container" and between "-2" and 3 if `xref` is + "paper". + xanchor + Sets this color bar's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the color bar. Defaults to "left" when + `orientation` is "v" and "center" when `orientation` is + "h". + xpad + Sets the amount of padding (in px) along the x + direction. + xref + Sets the container `x` refers to. "container" spans the + entire `width` of the plot. "paper" refers to the width + of the plotting area only. + y + Sets the y position with respect to `yref` of the color + bar (in plot fraction). When `yref` is "paper", + defaults to 0.5 when `orientation` is "v" and 1.02 when + `orientation` is "h". When `yref` is "container", + defaults to 0.5 when `orientation` is "v" and 1 when + `orientation` is "h". Must be between 0 and 1 if `yref` + is "container" and between "-2" and 3 if `yref` is + "paper". + yanchor + Sets this color bar's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the color bar. Defaults to "middle" when + `orientation` is "v" and "bottom" when `orientation` is + "h". + ypad + Sets the amount of padding (in px) along the y + direction. + yref + Sets the container `y` refers to. "container" spans the + entire `height` of the plot. "paper" refers to the + height of the plotting area only. + + Returns + ------- + ColorBar + """ + super().__init__("colorbar") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.contour.ColorBar +constructor must be a dict or +an instance of :class:`plotly.graph_objs.contour.ColorBar`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("borderwidth", arg, borderwidth) + self._set_property("dtick", arg, dtick) + self._set_property("exponentformat", arg, exponentformat) + self._set_property("labelalias", arg, labelalias) + self._set_property("len", arg, len) + self._set_property("lenmode", arg, lenmode) + self._set_property("minexponent", arg, minexponent) + self._set_property("nticks", arg, nticks) + self._set_property("orientation", arg, orientation) + self._set_property("outlinecolor", arg, outlinecolor) + self._set_property("outlinewidth", arg, outlinewidth) + self._set_property("separatethousands", arg, separatethousands) + self._set_property("showexponent", arg, showexponent) + self._set_property("showticklabels", arg, showticklabels) + self._set_property("showtickprefix", arg, showtickprefix) + self._set_property("showticksuffix", arg, showticksuffix) + self._set_property("thickness", arg, thickness) + self._set_property("thicknessmode", arg, thicknessmode) + self._set_property("tick0", arg, tick0) + self._set_property("tickangle", arg, tickangle) + self._set_property("tickcolor", arg, tickcolor) + self._set_property("tickfont", arg, tickfont) + self._set_property("tickformat", arg, tickformat) + self._set_property("tickformatstops", arg, tickformatstops) + self._set_property("tickformatstopdefaults", arg, tickformatstopdefaults) + self._set_property("ticklabeloverflow", arg, ticklabeloverflow) + self._set_property("ticklabelposition", arg, ticklabelposition) + self._set_property("ticklabelstep", arg, ticklabelstep) + self._set_property("ticklen", arg, ticklen) + self._set_property("tickmode", arg, tickmode) + self._set_property("tickprefix", arg, tickprefix) + self._set_property("ticks", arg, ticks) + self._set_property("ticksuffix", arg, ticksuffix) + self._set_property("ticktext", arg, ticktext) + self._set_property("ticktextsrc", arg, ticktextsrc) + self._set_property("tickvals", arg, tickvals) + self._set_property("tickvalssrc", arg, tickvalssrc) + self._set_property("tickwidth", arg, tickwidth) + self._set_property("title", arg, title) + self._set_property("x", arg, x) + self._set_property("xanchor", arg, xanchor) + self._set_property("xpad", arg, xpad) + self._set_property("xref", arg, xref) + self._set_property("y", arg, y) + self._set_property("yanchor", arg, yanchor) + self._set_property("ypad", arg, ypad) + self._set_property("yref", arg, yref) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/contour/_contours.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/contour/_contours.py new file mode 100644 index 0000000000000000000000000000000000000000..6668dbcc7c261d3a6d058dd5893d2d2f093a45b9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/contour/_contours.py @@ -0,0 +1,436 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Contours(_BaseTraceHierarchyType): + _parent_path_str = "contour" + _path_str = "contour.contours" + _valid_props = { + "coloring", + "end", + "labelfont", + "labelformat", + "operation", + "showlabels", + "showlines", + "size", + "start", + "type", + "value", + } + + @property + def coloring(self): + """ + Determines the coloring method showing the contour values. If + "fill", coloring is done evenly between each contour level If + "heatmap", a heatmap gradient coloring is applied between each + contour level. If "lines", coloring is done on the contour + lines. If "none", no coloring is applied on this trace. + + The 'coloring' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fill', 'heatmap', 'lines', 'none'] + + Returns + ------- + Any + """ + return self["coloring"] + + @coloring.setter + def coloring(self, val): + self["coloring"] = val + + @property + def end(self): + """ + Sets the end contour level value. Must be more than + `contours.start` + + The 'end' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["end"] + + @end.setter + def end(self, val): + self["end"] = val + + @property + def labelfont(self): + """ + Sets the font used for labeling the contour levels. The default + color comes from the lines, if shown. The default family and + size come from `layout.font`. + + The 'labelfont' property is an instance of Labelfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.contour.contours.Labelfont` + - A dict of string/value properties that will be passed + to the Labelfont constructor + + Returns + ------- + plotly.graph_objs.contour.contours.Labelfont + """ + return self["labelfont"] + + @labelfont.setter + def labelfont(self, val): + self["labelfont"] = val + + @property + def labelformat(self): + """ + Sets the contour label formatting rule using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + + The 'labelformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["labelformat"] + + @labelformat.setter + def labelformat(self, val): + self["labelformat"] = val + + @property + def operation(self): + """ + Sets the constraint operation. "=" keeps regions equal to + `value` "<" and "<=" keep regions less than `value` ">" and + ">=" keep regions greater than `value` "[]", "()", "[)", and + "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", + "](", ")[" keep regions outside `value[0]` to value[1]` Open + vs. closed intervals make no difference to constraint display, + but all versions are allowed for consistency with filter + transforms. + + The 'operation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['=', '<', '>=', '>', '<=', '[]', '()', '[)', '(]', '][', + ')(', '](', ')['] + + Returns + ------- + Any + """ + return self["operation"] + + @operation.setter + def operation(self, val): + self["operation"] = val + + @property + def showlabels(self): + """ + Determines whether to label the contour lines with their + values. + + The 'showlabels' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlabels"] + + @showlabels.setter + def showlabels(self, val): + self["showlabels"] = val + + @property + def showlines(self): + """ + Determines whether or not the contour lines are drawn. Has an + effect only if `contours.coloring` is set to "fill". + + The 'showlines' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlines"] + + @showlines.setter + def showlines(self, val): + self["showlines"] = val + + @property + def size(self): + """ + Sets the step between each contour level. Must be positive. + + The 'size' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def start(self): + """ + Sets the starting contour level value. Must be less than + `contours.end` + + The 'start' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["start"] + + @start.setter + def start(self, val): + self["start"] = val + + @property + def type(self): + """ + If `levels`, the data is represented as a contour plot with + multiple levels displayed. If `constraint`, the data is + represented as constraints with the invalid region shaded as + specified by the `operation` and `value` parameters. + + The 'type' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['levels', 'constraint'] + + Returns + ------- + Any + """ + return self["type"] + + @type.setter + def type(self, val): + self["type"] = val + + @property + def value(self): + """ + Sets the value or values of the constraint boundary. When + `operation` is set to one of the comparison values + (`=,<,>=,>,<=`) "value" is expected to be a number. When + `operation` is set to one of the interval values + (`[],(),[),(],][,)(,](,)[`) "value" is expected to be an array + of two numbers where the first is the lower bound and the + second is the upper bound. + + The 'value' property accepts values of any type + + Returns + ------- + Any + """ + return self["value"] + + @value.setter + def value(self, val): + self["value"] = val + + @property + def _prop_descriptions(self): + return """\ + coloring + Determines the coloring method showing the contour + values. If "fill", coloring is done evenly between each + contour level If "heatmap", a heatmap gradient coloring + is applied between each contour level. If "lines", + coloring is done on the contour lines. If "none", no + coloring is applied on this trace. + end + Sets the end contour level value. Must be more than + `contours.start` + labelfont + Sets the font used for labeling the contour levels. The + default color comes from the lines, if shown. The + default family and size come from `layout.font`. + labelformat + Sets the contour label formatting rule using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + operation + Sets the constraint operation. "=" keeps regions equal + to `value` "<" and "<=" keep regions less than `value` + ">" and ">=" keep regions greater than `value` "[]", + "()", "[)", and "(]" keep regions inside `value[0]` to + `value[1]` "][", ")(", "](", ")[" keep regions outside + `value[0]` to value[1]` Open vs. closed intervals make + no difference to constraint display, but all versions + are allowed for consistency with filter transforms. + showlabels + Determines whether to label the contour lines with + their values. + showlines + Determines whether or not the contour lines are drawn. + Has an effect only if `contours.coloring` is set to + "fill". + size + Sets the step between each contour level. Must be + positive. + start + Sets the starting contour level value. Must be less + than `contours.end` + type + If `levels`, the data is represented as a contour plot + with multiple levels displayed. If `constraint`, the + data is represented as constraints with the invalid + region shaded as specified by the `operation` and + `value` parameters. + value + Sets the value or values of the constraint boundary. + When `operation` is set to one of the comparison values + (`=,<,>=,>,<=`) "value" is expected to be a number. + When `operation` is set to one of the interval values + (`[],(),[),(],][,)(,](,)[`) "value" is expected to be + an array of two numbers where the first is the lower + bound and the second is the upper bound. + """ + + def __init__( + self, + arg=None, + coloring=None, + end=None, + labelfont=None, + labelformat=None, + operation=None, + showlabels=None, + showlines=None, + size=None, + start=None, + type=None, + value=None, + **kwargs, + ): + """ + Construct a new Contours object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.contour.Contours` + coloring + Determines the coloring method showing the contour + values. If "fill", coloring is done evenly between each + contour level If "heatmap", a heatmap gradient coloring + is applied between each contour level. If "lines", + coloring is done on the contour lines. If "none", no + coloring is applied on this trace. + end + Sets the end contour level value. Must be more than + `contours.start` + labelfont + Sets the font used for labeling the contour levels. The + default color comes from the lines, if shown. The + default family and size come from `layout.font`. + labelformat + Sets the contour label formatting rule using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + operation + Sets the constraint operation. "=" keeps regions equal + to `value` "<" and "<=" keep regions less than `value` + ">" and ">=" keep regions greater than `value` "[]", + "()", "[)", and "(]" keep regions inside `value[0]` to + `value[1]` "][", ")(", "](", ")[" keep regions outside + `value[0]` to value[1]` Open vs. closed intervals make + no difference to constraint display, but all versions + are allowed for consistency with filter transforms. + showlabels + Determines whether to label the contour lines with + their values. + showlines + Determines whether or not the contour lines are drawn. + Has an effect only if `contours.coloring` is set to + "fill". + size + Sets the step between each contour level. Must be + positive. + start + Sets the starting contour level value. Must be less + than `contours.end` + type + If `levels`, the data is represented as a contour plot + with multiple levels displayed. If `constraint`, the + data is represented as constraints with the invalid + region shaded as specified by the `operation` and + `value` parameters. + value + Sets the value or values of the constraint boundary. + When `operation` is set to one of the comparison values + (`=,<,>=,>,<=`) "value" is expected to be a number. + When `operation` is set to one of the interval values + (`[],(),[),(],][,)(,](,)[`) "value" is expected to be + an array of two numbers where the first is the lower + bound and the second is the upper bound. + + Returns + ------- + Contours + """ + super().__init__("contours") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.contour.Contours +constructor must be a dict or +an instance of :class:`plotly.graph_objs.contour.Contours`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("coloring", arg, coloring) + self._set_property("end", arg, end) + self._set_property("labelfont", arg, labelfont) + self._set_property("labelformat", arg, labelformat) + self._set_property("operation", arg, operation) + self._set_property("showlabels", arg, showlabels) + self._set_property("showlines", arg, showlines) + self._set_property("size", arg, size) + self._set_property("start", arg, start) + self._set_property("type", arg, type) + self._set_property("value", arg, value) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/contour/_hoverlabel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/contour/_hoverlabel.py new file mode 100644 index 0000000000000000000000000000000000000000..7a5d88b7b6c28c48fb5983329a00d5ce90b2e106 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/contour/_hoverlabel.py @@ -0,0 +1,366 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Hoverlabel(_BaseTraceHierarchyType): + _parent_path_str = "contour" + _path_str = "contour.hoverlabel" + _valid_props = { + "align", + "alignsrc", + "bgcolor", + "bgcolorsrc", + "bordercolor", + "bordercolorsrc", + "font", + "namelength", + "namelengthsrc", + "showarrow", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the text content within hover + label box. Has an effect only if the hover label text spans + more two or more lines + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'auto'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def alignsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `align`. + + The 'alignsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["alignsrc"] + + @alignsrc.setter + def alignsrc(self, val): + self["alignsrc"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the hover labels for this trace + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bgcolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `bgcolor`. + + The 'bgcolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bgcolorsrc"] + + @bgcolorsrc.setter + def bgcolorsrc(self, val): + self["bgcolorsrc"] = val + + @property + def bordercolor(self): + """ + Sets the border color of the hover labels for this trace. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def bordercolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + + The 'bordercolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bordercolorsrc"] + + @bordercolorsrc.setter + def bordercolorsrc(self, val): + self["bordercolorsrc"] = val + + @property + def font(self): + """ + Sets the font used in hover labels. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.contour.hoverlabel.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.contour.hoverlabel.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def namelength(self): + """ + Sets the default length (in number of characters) of the trace + name in the hover labels for all traces. -1 shows the whole + name regardless of length. 0-3 shows the first 0-3 characters, + and an integer >3 will show the whole name if it is less than + that many characters, but if it is longer, will truncate to + `namelength - 3` characters and add an ellipsis. + + The 'namelength' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["namelength"] + + @namelength.setter + def namelength(self, val): + self["namelength"] = val + + @property + def namelengthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `namelength`. + + The 'namelengthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["namelengthsrc"] + + @namelengthsrc.setter + def namelengthsrc(self, val): + self["namelengthsrc"] = val + + @property + def showarrow(self): + """ + Sets whether or not to show the hover label arrow/triangle + pointing to the data point. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + """ + + def __init__( + self, + arg=None, + align=None, + alignsrc=None, + bgcolor=None, + bgcolorsrc=None, + bordercolor=None, + bordercolorsrc=None, + font=None, + namelength=None, + namelengthsrc=None, + showarrow=None, + **kwargs, + ): + """ + Construct a new Hoverlabel object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.contour.Hoverlabel` + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + + Returns + ------- + Hoverlabel + """ + super().__init__("hoverlabel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.contour.Hoverlabel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.contour.Hoverlabel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("alignsrc", arg, alignsrc) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bgcolorsrc", arg, bgcolorsrc) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("bordercolorsrc", arg, bordercolorsrc) + self._set_property("font", arg, font) + self._set_property("namelength", arg, namelength) + self._set_property("namelengthsrc", arg, namelengthsrc) + self._set_property("showarrow", arg, showarrow) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/contour/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/contour/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..9566a13db0cd096e3b1f9461f89214dbd27ebc5f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/contour/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "contour" + _path_str = "contour.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.contour.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.contour.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.contour.Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.contour.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.contour.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/graph_objs.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/graph_objs.py new file mode 100644 index 0000000000000000000000000000000000000000..60189f94311adfa7da508b4739b39e68aa4f04d7 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/graph_objs.py @@ -0,0 +1 @@ +from plotly.graph_objs import * diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..406ff7199e0317ecad79becd5801a4273bab010b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/__init__.py @@ -0,0 +1,37 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._colorbar import ColorBar + from ._contours import Contours + from ._hoverlabel import Hoverlabel + from ._legendgrouptitle import Legendgrouptitle + from ._line import Line + from ._marker import Marker + from ._stream import Stream + from ._textfont import Textfont + from ._xbins import XBins + from ._ybins import YBins + from . import colorbar + from . import contours + from . import hoverlabel + from . import legendgrouptitle +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [".colorbar", ".contours", ".hoverlabel", ".legendgrouptitle"], + [ + "._colorbar.ColorBar", + "._contours.Contours", + "._hoverlabel.Hoverlabel", + "._legendgrouptitle.Legendgrouptitle", + "._line.Line", + "._marker.Marker", + "._stream.Stream", + "._textfont.Textfont", + "._xbins.XBins", + "._ybins.YBins", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_colorbar.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_colorbar.py new file mode 100644 index 0000000000000000000000000000000000000000..8f286c2f9218d3dcef2a4609b318fff2dfca76f9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_colorbar.py @@ -0,0 +1,1739 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class ColorBar(_BaseTraceHierarchyType): + _parent_path_str = "histogram2dcontour" + _path_str = "histogram2dcontour.colorbar" + _valid_props = { + "bgcolor", + "bordercolor", + "borderwidth", + "dtick", + "exponentformat", + "labelalias", + "len", + "lenmode", + "minexponent", + "nticks", + "orientation", + "outlinecolor", + "outlinewidth", + "separatethousands", + "showexponent", + "showticklabels", + "showtickprefix", + "showticksuffix", + "thickness", + "thicknessmode", + "tick0", + "tickangle", + "tickcolor", + "tickfont", + "tickformat", + "tickformatstopdefaults", + "tickformatstops", + "ticklabeloverflow", + "ticklabelposition", + "ticklabelstep", + "ticklen", + "tickmode", + "tickprefix", + "ticks", + "ticksuffix", + "ticktext", + "ticktextsrc", + "tickvals", + "tickvalssrc", + "tickwidth", + "title", + "x", + "xanchor", + "xpad", + "xref", + "y", + "yanchor", + "ypad", + "yref", + } + + @property + def bgcolor(self): + """ + Sets the color of padded area. + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bordercolor(self): + """ + Sets the axis line color. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def borderwidth(self): + """ + Sets the width (in px) or the border enclosing this color bar. + + The 'borderwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["borderwidth"] + + @borderwidth.setter + def borderwidth(self, val): + self["borderwidth"] = val + + @property + def dtick(self): + """ + Sets the step in-between ticks on this axis. Use with `tick0`. + Must be a positive number, or special strings available to + "log" and "date" axes. If the axis `type` is "log", then ticks + are set every 10^(n*dtick) where n is the tick number. For + example, to set a tick mark at 1, 10, 100, 1000, ... set dtick + to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. + To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special values; + "L", where `f` is a positive number, gives ticks linearly + spaced in value (but not position). For example `tick0` = 0.1, + `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To + show powers of 10 plus small digits between, use "D1" (all + digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and + "D2". If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval between + ticks to one day, set `dtick` to 86400000.0. "date" also has + special values "M" gives ticks spaced by a number of months. + `n` must be a positive integer. To set ticks on the 15th of + every third month, set `tick0` to "2000-01-15" and `dtick` to + "M3". To set ticks every 4 years, set `dtick` to "M48" + + The 'dtick' property accepts values of any type + + Returns + ------- + Any + """ + return self["dtick"] + + @dtick.setter + def dtick(self, val): + self["dtick"] = val + + @property + def exponentformat(self): + """ + Determines a formatting rule for the tick exponents. For + example, consider the number 1,000,000,000. If "none", it + appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If + "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If + "B", 1B. "SI" uses prefixes from "femto" f (10^-15) to "tera" T + (10^12). *SI extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or *SI + extended* is used and the exponent is beyond the above ranges, + the formatting rule will automatically be switched to the power + notation. + + The 'exponentformat' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'e', 'E', 'power', 'SI', 'B', 'SI extended'] + + Returns + ------- + Any + """ + return self["exponentformat"] + + @exponentformat.setter + def exponentformat(self, val): + self["exponentformat"] = val + + @property + def labelalias(self): + """ + Replacement text for specific tick or hover labels. For example + using {US: 'USA', CA: 'Canada'} changes US to USA and CA to + Canada. The labels we would have shown must match the keys + exactly, after adding any tickprefix or ticksuffix. For + negative numbers the minus sign symbol used (U+2212) is wider + than the regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis type, and + both keys (if needed) and values (if desired) can include html- + like tags or MathJax. + + The 'labelalias' property accepts values of any type + + Returns + ------- + Any + """ + return self["labelalias"] + + @labelalias.setter + def labelalias(self, val): + self["labelalias"] = val + + @property + def len(self): + """ + Sets the length of the color bar This measure excludes the + padding of both ends. That is, the color bar length is this + length minus the padding on both ends. + + The 'len' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["len"] + + @len.setter + def len(self, val): + self["len"] = val + + @property + def lenmode(self): + """ + Determines whether this color bar's length (i.e. the measure in + the color variation direction) is set in units of plot + "fraction" or in *pixels. Use `len` to set the value. + + The 'lenmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fraction', 'pixels'] + + Returns + ------- + Any + """ + return self["lenmode"] + + @lenmode.setter + def lenmode(self, val): + self["lenmode"] = val + + @property + def minexponent(self): + """ + Hide SI prefix for 10^n if |n| is below this number. This only + has an effect when `tickformat` is "SI" or "B". + + The 'minexponent' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["minexponent"] + + @minexponent.setter + def minexponent(self, val): + self["minexponent"] = val + + @property + def nticks(self): + """ + Specifies the maximum number of ticks for the particular axis. + The actual number of ticks will be chosen automatically to be + less than or equal to `nticks`. Has an effect only if + `tickmode` is set to "auto". + + The 'nticks' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["nticks"] + + @nticks.setter + def nticks(self, val): + self["nticks"] = val + + @property + def orientation(self): + """ + Sets the orientation of the colorbar. + + The 'orientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['h', 'v'] + + Returns + ------- + Any + """ + return self["orientation"] + + @orientation.setter + def orientation(self, val): + self["orientation"] = val + + @property + def outlinecolor(self): + """ + Sets the axis line color. + + The 'outlinecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["outlinecolor"] + + @outlinecolor.setter + def outlinecolor(self, val): + self["outlinecolor"] = val + + @property + def outlinewidth(self): + """ + Sets the width (in px) of the axis line. + + The 'outlinewidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["outlinewidth"] + + @outlinewidth.setter + def outlinewidth(self, val): + self["outlinewidth"] = val + + @property + def separatethousands(self): + """ + If "true", even 4-digit integers are separated + + The 'separatethousands' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["separatethousands"] + + @separatethousands.setter + def separatethousands(self, val): + self["separatethousands"] = val + + @property + def showexponent(self): + """ + If "all", all exponents are shown besides their significands. + If "first", only the exponent of the first tick is shown. If + "last", only the exponent of the last tick is shown. If "none", + no exponents appear. + + The 'showexponent' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showexponent"] + + @showexponent.setter + def showexponent(self, val): + self["showexponent"] = val + + @property + def showticklabels(self): + """ + Determines whether or not the tick labels are drawn. + + The 'showticklabels' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showticklabels"] + + @showticklabels.setter + def showticklabels(self, val): + self["showticklabels"] = val + + @property + def showtickprefix(self): + """ + If "all", all tick labels are displayed with a prefix. If + "first", only the first tick is displayed with a prefix. If + "last", only the last tick is displayed with a suffix. If + "none", tick prefixes are hidden. + + The 'showtickprefix' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showtickprefix"] + + @showtickprefix.setter + def showtickprefix(self, val): + self["showtickprefix"] = val + + @property + def showticksuffix(self): + """ + Same as `showtickprefix` but for tick suffixes. + + The 'showticksuffix' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showticksuffix"] + + @showticksuffix.setter + def showticksuffix(self, val): + self["showticksuffix"] = val + + @property + def thickness(self): + """ + Sets the thickness of the color bar This measure excludes the + size of the padding, ticks and labels. + + The 'thickness' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["thickness"] + + @thickness.setter + def thickness(self, val): + self["thickness"] = val + + @property + def thicknessmode(self): + """ + Determines whether this color bar's thickness (i.e. the measure + in the constant color direction) is set in units of plot + "fraction" or in "pixels". Use `thickness` to set the value. + + The 'thicknessmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fraction', 'pixels'] + + Returns + ------- + Any + """ + return self["thicknessmode"] + + @thicknessmode.setter + def thicknessmode(self, val): + self["thicknessmode"] = val + + @property + def tick0(self): + """ + Sets the placement of the first tick on this axis. Use with + `dtick`. If the axis `type` is "log", then you must take the + log of your starting tick (e.g. to set the starting tick to + 100, set the `tick0` to 2) except when `dtick`=*L* (see + `dtick` for more info). If the axis `type` is "date", it should + be a date string, like date data. If the axis `type` is + "category", it should be a number, using the scale where each + category is assigned a serial number from zero in the order it + appears. + + The 'tick0' property accepts values of any type + + Returns + ------- + Any + """ + return self["tick0"] + + @tick0.setter + def tick0(self, val): + self["tick0"] = val + + @property + def tickangle(self): + """ + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the tick + labels vertically. + + The 'tickangle' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["tickangle"] + + @tickangle.setter + def tickangle(self, val): + self["tickangle"] = val + + @property + def tickcolor(self): + """ + Sets the tick color. + + The 'tickcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["tickcolor"] + + @tickcolor.setter + def tickcolor(self, val): + self["tickcolor"] = val + + @property + def tickfont(self): + """ + Sets the color bar's tick label font + + The 'tickfont' property is an instance of Tickfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.colorbar.Tickfont` + - A dict of string/value properties that will be passed + to the Tickfont constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.colorbar.Tickfont + """ + return self["tickfont"] + + @tickfont.setter + def tickfont(self, val): + self["tickfont"] = val + + @property + def tickformat(self): + """ + Sets the tick label formatting rule using d3 formatting mini- + languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display "09~15~23.46" + + The 'tickformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["tickformat"] + + @tickformat.setter + def tickformat(self, val): + self["tickformat"] = val + + @property + def tickformatstops(self): + """ + The 'tickformatstops' property is a tuple of instances of + Tickformatstop that may be specified as: + - A list or tuple of instances of plotly.graph_objs.histogram2dcontour.colorbar.Tickformatstop + - A list or tuple of dicts of string/value properties that + will be passed to the Tickformatstop constructor + + Returns + ------- + tuple[plotly.graph_objs.histogram2dcontour.colorbar.Tickformatstop] + """ + return self["tickformatstops"] + + @tickformatstops.setter + def tickformatstops(self, val): + self["tickformatstops"] = val + + @property + def tickformatstopdefaults(self): + """ + When used in a template (as layout.template.data.histogram2dcon + tour.colorbar.tickformatstopdefaults), sets the default + property values to use for elements of + histogram2dcontour.colorbar.tickformatstops + + The 'tickformatstopdefaults' property is an instance of Tickformatstop + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.colorbar.Tickformatstop` + - A dict of string/value properties that will be passed + to the Tickformatstop constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.colorbar.Tickformatstop + """ + return self["tickformatstopdefaults"] + + @tickformatstopdefaults.setter + def tickformatstopdefaults(self, val): + self["tickformatstopdefaults"] = val + + @property + def ticklabeloverflow(self): + """ + Determines how we handle tick labels that would overflow either + the graph div or the domain of the axis. The default value for + inside tick labels is *hide past domain*. In other cases the + default is *hide past div*. + + The 'ticklabeloverflow' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['allow', 'hide past div', 'hide past domain'] + + Returns + ------- + Any + """ + return self["ticklabeloverflow"] + + @ticklabeloverflow.setter + def ticklabeloverflow(self, val): + self["ticklabeloverflow"] = val + + @property + def ticklabelposition(self): + """ + Determines where tick labels are drawn relative to the ticks. + Left and right options are used when `orientation` is "h", top + and bottom when `orientation` is "v". + + The 'ticklabelposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['outside', 'inside', 'outside top', 'inside top', + 'outside left', 'inside left', 'outside right', 'inside + right', 'outside bottom', 'inside bottom'] + + Returns + ------- + Any + """ + return self["ticklabelposition"] + + @ticklabelposition.setter + def ticklabelposition(self, val): + self["ticklabelposition"] = val + + @property + def ticklabelstep(self): + """ + Sets the spacing between tick labels as compared to the spacing + between ticks. A value of 1 (default) means each tick gets a + label. A value of 2 means shows every 2nd label. A larger value + n means only every nth tick is labeled. `tick0` determines + which labels are shown. Not implemented for axes with `type` + "log" or "multicategory", or when `tickmode` is "array". + + The 'ticklabelstep' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 9223372036854775807] + + Returns + ------- + int + """ + return self["ticklabelstep"] + + @ticklabelstep.setter + def ticklabelstep(self, val): + self["ticklabelstep"] = val + + @property + def ticklen(self): + """ + Sets the tick length (in px). + + The 'ticklen' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["ticklen"] + + @ticklen.setter + def ticklen(self, val): + self["ticklen"] = val + + @property + def tickmode(self): + """ + Sets the tick mode for this axis. If "auto", the number of + ticks is set via `nticks`. If "linear", the placement of the + ticks is determined by a starting position `tick0` and a tick + step `dtick` ("linear" is the default value if `tick0` and + `dtick` are provided). If "array", the placement of the ticks + is set via `tickvals` and the tick text is `ticktext`. ("array" + is the default value if `tickvals` is provided). + + The 'tickmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'linear', 'array'] + + Returns + ------- + Any + """ + return self["tickmode"] + + @tickmode.setter + def tickmode(self, val): + self["tickmode"] = val + + @property + def tickprefix(self): + """ + Sets a tick label prefix. + + The 'tickprefix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["tickprefix"] + + @tickprefix.setter + def tickprefix(self, val): + self["tickprefix"] = val + + @property + def ticks(self): + """ + Determines whether ticks are drawn or not. If "", this axis' + ticks are not drawn. If "outside" ("inside"), this axis' are + drawn outside (inside) the axis lines. + + The 'ticks' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['outside', 'inside', ''] + + Returns + ------- + Any + """ + return self["ticks"] + + @ticks.setter + def ticks(self, val): + self["ticks"] = val + + @property + def ticksuffix(self): + """ + Sets a tick label suffix. + + The 'ticksuffix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["ticksuffix"] + + @ticksuffix.setter + def ticksuffix(self, val): + self["ticksuffix"] = val + + @property + def ticktext(self): + """ + Sets the text displayed at the ticks position via `tickvals`. + Only has an effect if `tickmode` is set to "array". Used with + `tickvals`. + + The 'ticktext' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ticktext"] + + @ticktext.setter + def ticktext(self, val): + self["ticktext"] = val + + @property + def ticktextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ticktext`. + + The 'ticktextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ticktextsrc"] + + @ticktextsrc.setter + def ticktextsrc(self, val): + self["ticktextsrc"] = val + + @property + def tickvals(self): + """ + Sets the values at which ticks on this axis appear. Only has an + effect if `tickmode` is set to "array". Used with `ticktext`. + + The 'tickvals' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["tickvals"] + + @tickvals.setter + def tickvals(self, val): + self["tickvals"] = val + + @property + def tickvalssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `tickvals`. + + The 'tickvalssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["tickvalssrc"] + + @tickvalssrc.setter + def tickvalssrc(self, val): + self["tickvalssrc"] = val + + @property + def tickwidth(self): + """ + Sets the tick width (in px). + + The 'tickwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["tickwidth"] + + @tickwidth.setter + def tickwidth(self, val): + self["tickwidth"] = val + + @property + def title(self): + """ + The 'title' property is an instance of Title + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.colorbar.Title` + - A dict of string/value properties that will be passed + to the Title constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.colorbar.Title + """ + return self["title"] + + @title.setter + def title(self, val): + self["title"] = val + + @property + def x(self): + """ + Sets the x position with respect to `xref` of the color bar (in + plot fraction). When `xref` is "paper", defaults to 1.02 when + `orientation` is "v" and 0.5 when `orientation` is "h". When + `xref` is "container", defaults to 1 when `orientation` is "v" + and 0.5 when `orientation` is "h". Must be between 0 and 1 if + `xref` is "container" and between "-2" and 3 if `xref` is + "paper". + + The 'x' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xanchor(self): + """ + Sets this color bar's horizontal position anchor. This anchor + binds the `x` position to the "left", "center" or "right" of + the color bar. Defaults to "left" when `orientation` is "v" and + "center" when `orientation` is "h". + + The 'xanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'center', 'right'] + + Returns + ------- + Any + """ + return self["xanchor"] + + @xanchor.setter + def xanchor(self, val): + self["xanchor"] = val + + @property + def xpad(self): + """ + Sets the amount of padding (in px) along the x direction. + + The 'xpad' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["xpad"] + + @xpad.setter + def xpad(self, val): + self["xpad"] = val + + @property + def xref(self): + """ + Sets the container `x` refers to. "container" spans the entire + `width` of the plot. "paper" refers to the width of the + plotting area only. + + The 'xref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['container', 'paper'] + + Returns + ------- + Any + """ + return self["xref"] + + @xref.setter + def xref(self, val): + self["xref"] = val + + @property + def y(self): + """ + Sets the y position with respect to `yref` of the color bar (in + plot fraction). When `yref` is "paper", defaults to 0.5 when + `orientation` is "v" and 1.02 when `orientation` is "h". When + `yref` is "container", defaults to 0.5 when `orientation` is + "v" and 1 when `orientation` is "h". Must be between 0 and 1 if + `yref` is "container" and between "-2" and 3 if `yref` is + "paper". + + The 'y' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yanchor(self): + """ + Sets this color bar's vertical position anchor This anchor + binds the `y` position to the "top", "middle" or "bottom" of + the color bar. Defaults to "middle" when `orientation` is "v" + and "bottom" when `orientation` is "h". + + The 'yanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top', 'middle', 'bottom'] + + Returns + ------- + Any + """ + return self["yanchor"] + + @yanchor.setter + def yanchor(self, val): + self["yanchor"] = val + + @property + def ypad(self): + """ + Sets the amount of padding (in px) along the y direction. + + The 'ypad' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["ypad"] + + @ypad.setter + def ypad(self, val): + self["ypad"] = val + + @property + def yref(self): + """ + Sets the container `y` refers to. "container" spans the entire + `height` of the plot. "paper" refers to the height of the + plotting area only. + + The 'yref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['container', 'paper'] + + Returns + ------- + Any + """ + return self["yref"] + + @yref.setter + def yref(self, val): + self["yref"] = val + + @property + def _prop_descriptions(self): + return """\ + bgcolor + Sets the color of padded area. + bordercolor + Sets the axis line color. + borderwidth + Sets the width (in px) or the border enclosing this + color bar. + dtick + Sets the step in-between ticks on this axis. Use with + `tick0`. Must be a positive number, or special strings + available to "log" and "date" axes. If the axis `type` + is "log", then ticks are set every 10^(n*dtick) where n + is the tick number. For example, to set a tick mark at + 1, 10, 100, 1000, ... set dtick to 1. To set tick marks + at 1, 100, 10000, ... set dtick to 2. To set tick marks + at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special + values; "L", where `f` is a positive number, gives + ticks linearly spaced in value (but not position). For + example `tick0` = 0.1, `dtick` = "L0.5" will put ticks + at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus + small digits between, use "D1" (all digits) or "D2" + (only 2 and 5). `tick0` is ignored for "D1" and "D2". + If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval + between ticks to one day, set `dtick` to 86400000.0. + "date" also has special values "M" gives ticks + spaced by a number of months. `n` must be a positive + integer. To set ticks on the 15th of every third month, + set `tick0` to "2000-01-15" and `dtick` to "M3". To set + ticks every 4 years, set `dtick` to "M48" + exponentformat + Determines a formatting rule for the tick exponents. + For example, consider the number 1,000,000,000. If + "none", it appears as 1,000,000,000. If "e", 1e+9. If + "E", 1E+9. If "power", 1x10^9 (with 9 in a super + script). If "SI", 1G. If "B", 1B. "SI" uses prefixes + from "femto" f (10^-15) to "tera" T (10^12). *SI + extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or + *SI extended* is used and the exponent is beyond the + above ranges, the formatting rule will automatically be + switched to the power notation. + labelalias + Replacement text for specific tick or hover labels. For + example using {US: 'USA', CA: 'Canada'} changes US to + USA and CA to Canada. The labels we would have shown + must match the keys exactly, after adding any + tickprefix or ticksuffix. For negative numbers the + minus sign symbol used (U+2212) is wider than the + regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis + type, and both keys (if needed) and values (if desired) + can include html-like tags or MathJax. + len + Sets the length of the color bar This measure excludes + the padding of both ends. That is, the color bar length + is this length minus the padding on both ends. + lenmode + Determines whether this color bar's length (i.e. the + measure in the color variation direction) is set in + units of plot "fraction" or in *pixels. Use `len` to + set the value. + minexponent + Hide SI prefix for 10^n if |n| is below this number. + This only has an effect when `tickformat` is "SI" or + "B". + nticks + Specifies the maximum number of ticks for the + particular axis. The actual number of ticks will be + chosen automatically to be less than or equal to + `nticks`. Has an effect only if `tickmode` is set to + "auto". + orientation + Sets the orientation of the colorbar. + outlinecolor + Sets the axis line color. + outlinewidth + Sets the width (in px) of the axis line. + separatethousands + If "true", even 4-digit integers are separated + showexponent + If "all", all exponents are shown besides their + significands. If "first", only the exponent of the + first tick is shown. If "last", only the exponent of + the last tick is shown. If "none", no exponents appear. + showticklabels + Determines whether or not the tick labels are drawn. + showtickprefix + If "all", all tick labels are displayed with a prefix. + If "first", only the first tick is displayed with a + prefix. If "last", only the last tick is displayed with + a suffix. If "none", tick prefixes are hidden. + showticksuffix + Same as `showtickprefix` but for tick suffixes. + thickness + Sets the thickness of the color bar This measure + excludes the size of the padding, ticks and labels. + thicknessmode + Determines whether this color bar's thickness (i.e. the + measure in the constant color direction) is set in + units of plot "fraction" or in "pixels". Use + `thickness` to set the value. + tick0 + Sets the placement of the first tick on this axis. Use + with `dtick`. If the axis `type` is "log", then you + must take the log of your starting tick (e.g. to set + the starting tick to 100, set the `tick0` to 2) except + when `dtick`=*L* (see `dtick` for more info). If the + axis `type` is "date", it should be a date string, like + date data. If the axis `type` is "category", it should + be a number, using the scale where each category is + assigned a serial number from zero in the order it + appears. + tickangle + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + tick labels vertically. + tickcolor + Sets the tick color. + tickfont + Sets the color bar's tick label font + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + tickformatstops + A tuple of :class:`plotly.graph_objects.histogram2dcont + our.colorbar.Tickformatstop` instances or dicts with + compatible properties + tickformatstopdefaults + When used in a template (as layout.template.data.histog + ram2dcontour.colorbar.tickformatstopdefaults), sets the + default property values to use for elements of + histogram2dcontour.colorbar.tickformatstops + ticklabeloverflow + Determines how we handle tick labels that would + overflow either the graph div or the domain of the + axis. The default value for inside tick labels is *hide + past domain*. In other cases the default is *hide past + div*. + ticklabelposition + Determines where tick labels are drawn relative to the + ticks. Left and right options are used when + `orientation` is "h", top and bottom when `orientation` + is "v". + ticklabelstep + Sets the spacing between tick labels as compared to the + spacing between ticks. A value of 1 (default) means + each tick gets a label. A value of 2 means shows every + 2nd label. A larger value n means only every nth tick + is labeled. `tick0` determines which labels are shown. + Not implemented for axes with `type` "log" or + "multicategory", or when `tickmode` is "array". + ticklen + Sets the tick length (in px). + tickmode + Sets the tick mode for this axis. If "auto", the number + of ticks is set via `nticks`. If "linear", the + placement of the ticks is determined by a starting + position `tick0` and a tick step `dtick` ("linear" is + the default value if `tick0` and `dtick` are provided). + If "array", the placement of the ticks is set via + `tickvals` and the tick text is `ticktext`. ("array" is + the default value if `tickvals` is provided). + tickprefix + Sets a tick label prefix. + ticks + Determines whether ticks are drawn or not. If "", this + axis' ticks are not drawn. If "outside" ("inside"), + this axis' are drawn outside (inside) the axis lines. + ticksuffix + Sets a tick label suffix. + ticktext + Sets the text displayed at the ticks position via + `tickvals`. Only has an effect if `tickmode` is set to + "array". Used with `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + Only has an effect if `tickmode` is set to "array". + Used with `ticktext`. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + tickwidth + Sets the tick width (in px). + title + :class:`plotly.graph_objects.histogram2dcontour.colorba + r.Title` instance or dict with compatible properties + x + Sets the x position with respect to `xref` of the color + bar (in plot fraction). When `xref` is "paper", + defaults to 1.02 when `orientation` is "v" and 0.5 when + `orientation` is "h". When `xref` is "container", + defaults to 1 when `orientation` is "v" and 0.5 when + `orientation` is "h". Must be between 0 and 1 if `xref` + is "container" and between "-2" and 3 if `xref` is + "paper". + xanchor + Sets this color bar's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the color bar. Defaults to "left" when + `orientation` is "v" and "center" when `orientation` is + "h". + xpad + Sets the amount of padding (in px) along the x + direction. + xref + Sets the container `x` refers to. "container" spans the + entire `width` of the plot. "paper" refers to the width + of the plotting area only. + y + Sets the y position with respect to `yref` of the color + bar (in plot fraction). When `yref` is "paper", + defaults to 0.5 when `orientation` is "v" and 1.02 when + `orientation` is "h". When `yref` is "container", + defaults to 0.5 when `orientation` is "v" and 1 when + `orientation` is "h". Must be between 0 and 1 if `yref` + is "container" and between "-2" and 3 if `yref` is + "paper". + yanchor + Sets this color bar's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the color bar. Defaults to "middle" when + `orientation` is "v" and "bottom" when `orientation` is + "h". + ypad + Sets the amount of padding (in px) along the y + direction. + yref + Sets the container `y` refers to. "container" spans the + entire `height` of the plot. "paper" refers to the + height of the plotting area only. + """ + + def __init__( + self, + arg=None, + bgcolor=None, + bordercolor=None, + borderwidth=None, + dtick=None, + exponentformat=None, + labelalias=None, + len=None, + lenmode=None, + minexponent=None, + nticks=None, + orientation=None, + outlinecolor=None, + outlinewidth=None, + separatethousands=None, + showexponent=None, + showticklabels=None, + showtickprefix=None, + showticksuffix=None, + thickness=None, + thicknessmode=None, + tick0=None, + tickangle=None, + tickcolor=None, + tickfont=None, + tickformat=None, + tickformatstops=None, + tickformatstopdefaults=None, + ticklabeloverflow=None, + ticklabelposition=None, + ticklabelstep=None, + ticklen=None, + tickmode=None, + tickprefix=None, + ticks=None, + ticksuffix=None, + ticktext=None, + ticktextsrc=None, + tickvals=None, + tickvalssrc=None, + tickwidth=None, + title=None, + x=None, + xanchor=None, + xpad=None, + xref=None, + y=None, + yanchor=None, + ypad=None, + yref=None, + **kwargs, + ): + """ + Construct a new ColorBar object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.histogram2dcontour.ColorBar` + bgcolor + Sets the color of padded area. + bordercolor + Sets the axis line color. + borderwidth + Sets the width (in px) or the border enclosing this + color bar. + dtick + Sets the step in-between ticks on this axis. Use with + `tick0`. Must be a positive number, or special strings + available to "log" and "date" axes. If the axis `type` + is "log", then ticks are set every 10^(n*dtick) where n + is the tick number. For example, to set a tick mark at + 1, 10, 100, 1000, ... set dtick to 1. To set tick marks + at 1, 100, 10000, ... set dtick to 2. To set tick marks + at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special + values; "L", where `f` is a positive number, gives + ticks linearly spaced in value (but not position). For + example `tick0` = 0.1, `dtick` = "L0.5" will put ticks + at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus + small digits between, use "D1" (all digits) or "D2" + (only 2 and 5). `tick0` is ignored for "D1" and "D2". + If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval + between ticks to one day, set `dtick` to 86400000.0. + "date" also has special values "M" gives ticks + spaced by a number of months. `n` must be a positive + integer. To set ticks on the 15th of every third month, + set `tick0` to "2000-01-15" and `dtick` to "M3". To set + ticks every 4 years, set `dtick` to "M48" + exponentformat + Determines a formatting rule for the tick exponents. + For example, consider the number 1,000,000,000. If + "none", it appears as 1,000,000,000. If "e", 1e+9. If + "E", 1E+9. If "power", 1x10^9 (with 9 in a super + script). If "SI", 1G. If "B", 1B. "SI" uses prefixes + from "femto" f (10^-15) to "tera" T (10^12). *SI + extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or + *SI extended* is used and the exponent is beyond the + above ranges, the formatting rule will automatically be + switched to the power notation. + labelalias + Replacement text for specific tick or hover labels. For + example using {US: 'USA', CA: 'Canada'} changes US to + USA and CA to Canada. The labels we would have shown + must match the keys exactly, after adding any + tickprefix or ticksuffix. For negative numbers the + minus sign symbol used (U+2212) is wider than the + regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis + type, and both keys (if needed) and values (if desired) + can include html-like tags or MathJax. + len + Sets the length of the color bar This measure excludes + the padding of both ends. That is, the color bar length + is this length minus the padding on both ends. + lenmode + Determines whether this color bar's length (i.e. the + measure in the color variation direction) is set in + units of plot "fraction" or in *pixels. Use `len` to + set the value. + minexponent + Hide SI prefix for 10^n if |n| is below this number. + This only has an effect when `tickformat` is "SI" or + "B". + nticks + Specifies the maximum number of ticks for the + particular axis. The actual number of ticks will be + chosen automatically to be less than or equal to + `nticks`. Has an effect only if `tickmode` is set to + "auto". + orientation + Sets the orientation of the colorbar. + outlinecolor + Sets the axis line color. + outlinewidth + Sets the width (in px) of the axis line. + separatethousands + If "true", even 4-digit integers are separated + showexponent + If "all", all exponents are shown besides their + significands. If "first", only the exponent of the + first tick is shown. If "last", only the exponent of + the last tick is shown. If "none", no exponents appear. + showticklabels + Determines whether or not the tick labels are drawn. + showtickprefix + If "all", all tick labels are displayed with a prefix. + If "first", only the first tick is displayed with a + prefix. If "last", only the last tick is displayed with + a suffix. If "none", tick prefixes are hidden. + showticksuffix + Same as `showtickprefix` but for tick suffixes. + thickness + Sets the thickness of the color bar This measure + excludes the size of the padding, ticks and labels. + thicknessmode + Determines whether this color bar's thickness (i.e. the + measure in the constant color direction) is set in + units of plot "fraction" or in "pixels". Use + `thickness` to set the value. + tick0 + Sets the placement of the first tick on this axis. Use + with `dtick`. If the axis `type` is "log", then you + must take the log of your starting tick (e.g. to set + the starting tick to 100, set the `tick0` to 2) except + when `dtick`=*L* (see `dtick` for more info). If the + axis `type` is "date", it should be a date string, like + date data. If the axis `type` is "category", it should + be a number, using the scale where each category is + assigned a serial number from zero in the order it + appears. + tickangle + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + tick labels vertically. + tickcolor + Sets the tick color. + tickfont + Sets the color bar's tick label font + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + tickformatstops + A tuple of :class:`plotly.graph_objects.histogram2dcont + our.colorbar.Tickformatstop` instances or dicts with + compatible properties + tickformatstopdefaults + When used in a template (as layout.template.data.histog + ram2dcontour.colorbar.tickformatstopdefaults), sets the + default property values to use for elements of + histogram2dcontour.colorbar.tickformatstops + ticklabeloverflow + Determines how we handle tick labels that would + overflow either the graph div or the domain of the + axis. The default value for inside tick labels is *hide + past domain*. In other cases the default is *hide past + div*. + ticklabelposition + Determines where tick labels are drawn relative to the + ticks. Left and right options are used when + `orientation` is "h", top and bottom when `orientation` + is "v". + ticklabelstep + Sets the spacing between tick labels as compared to the + spacing between ticks. A value of 1 (default) means + each tick gets a label. A value of 2 means shows every + 2nd label. A larger value n means only every nth tick + is labeled. `tick0` determines which labels are shown. + Not implemented for axes with `type` "log" or + "multicategory", or when `tickmode` is "array". + ticklen + Sets the tick length (in px). + tickmode + Sets the tick mode for this axis. If "auto", the number + of ticks is set via `nticks`. If "linear", the + placement of the ticks is determined by a starting + position `tick0` and a tick step `dtick` ("linear" is + the default value if `tick0` and `dtick` are provided). + If "array", the placement of the ticks is set via + `tickvals` and the tick text is `ticktext`. ("array" is + the default value if `tickvals` is provided). + tickprefix + Sets a tick label prefix. + ticks + Determines whether ticks are drawn or not. If "", this + axis' ticks are not drawn. If "outside" ("inside"), + this axis' are drawn outside (inside) the axis lines. + ticksuffix + Sets a tick label suffix. + ticktext + Sets the text displayed at the ticks position via + `tickvals`. Only has an effect if `tickmode` is set to + "array". Used with `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + Only has an effect if `tickmode` is set to "array". + Used with `ticktext`. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + tickwidth + Sets the tick width (in px). + title + :class:`plotly.graph_objects.histogram2dcontour.colorba + r.Title` instance or dict with compatible properties + x + Sets the x position with respect to `xref` of the color + bar (in plot fraction). When `xref` is "paper", + defaults to 1.02 when `orientation` is "v" and 0.5 when + `orientation` is "h". When `xref` is "container", + defaults to 1 when `orientation` is "v" and 0.5 when + `orientation` is "h". Must be between 0 and 1 if `xref` + is "container" and between "-2" and 3 if `xref` is + "paper". + xanchor + Sets this color bar's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the color bar. Defaults to "left" when + `orientation` is "v" and "center" when `orientation` is + "h". + xpad + Sets the amount of padding (in px) along the x + direction. + xref + Sets the container `x` refers to. "container" spans the + entire `width` of the plot. "paper" refers to the width + of the plotting area only. + y + Sets the y position with respect to `yref` of the color + bar (in plot fraction). When `yref` is "paper", + defaults to 0.5 when `orientation` is "v" and 1.02 when + `orientation` is "h". When `yref` is "container", + defaults to 0.5 when `orientation` is "v" and 1 when + `orientation` is "h". Must be between 0 and 1 if `yref` + is "container" and between "-2" and 3 if `yref` is + "paper". + yanchor + Sets this color bar's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the color bar. Defaults to "middle" when + `orientation` is "v" and "bottom" when `orientation` is + "h". + ypad + Sets the amount of padding (in px) along the y + direction. + yref + Sets the container `y` refers to. "container" spans the + entire `height` of the plot. "paper" refers to the + height of the plotting area only. + + Returns + ------- + ColorBar + """ + super().__init__("colorbar") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.histogram2dcontour.ColorBar +constructor must be a dict or +an instance of :class:`plotly.graph_objs.histogram2dcontour.ColorBar`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("borderwidth", arg, borderwidth) + self._set_property("dtick", arg, dtick) + self._set_property("exponentformat", arg, exponentformat) + self._set_property("labelalias", arg, labelalias) + self._set_property("len", arg, len) + self._set_property("lenmode", arg, lenmode) + self._set_property("minexponent", arg, minexponent) + self._set_property("nticks", arg, nticks) + self._set_property("orientation", arg, orientation) + self._set_property("outlinecolor", arg, outlinecolor) + self._set_property("outlinewidth", arg, outlinewidth) + self._set_property("separatethousands", arg, separatethousands) + self._set_property("showexponent", arg, showexponent) + self._set_property("showticklabels", arg, showticklabels) + self._set_property("showtickprefix", arg, showtickprefix) + self._set_property("showticksuffix", arg, showticksuffix) + self._set_property("thickness", arg, thickness) + self._set_property("thicknessmode", arg, thicknessmode) + self._set_property("tick0", arg, tick0) + self._set_property("tickangle", arg, tickangle) + self._set_property("tickcolor", arg, tickcolor) + self._set_property("tickfont", arg, tickfont) + self._set_property("tickformat", arg, tickformat) + self._set_property("tickformatstops", arg, tickformatstops) + self._set_property("tickformatstopdefaults", arg, tickformatstopdefaults) + self._set_property("ticklabeloverflow", arg, ticklabeloverflow) + self._set_property("ticklabelposition", arg, ticklabelposition) + self._set_property("ticklabelstep", arg, ticklabelstep) + self._set_property("ticklen", arg, ticklen) + self._set_property("tickmode", arg, tickmode) + self._set_property("tickprefix", arg, tickprefix) + self._set_property("ticks", arg, ticks) + self._set_property("ticksuffix", arg, ticksuffix) + self._set_property("ticktext", arg, ticktext) + self._set_property("ticktextsrc", arg, ticktextsrc) + self._set_property("tickvals", arg, tickvals) + self._set_property("tickvalssrc", arg, tickvalssrc) + self._set_property("tickwidth", arg, tickwidth) + self._set_property("title", arg, title) + self._set_property("x", arg, x) + self._set_property("xanchor", arg, xanchor) + self._set_property("xpad", arg, xpad) + self._set_property("xref", arg, xref) + self._set_property("y", arg, y) + self._set_property("yanchor", arg, yanchor) + self._set_property("ypad", arg, ypad) + self._set_property("yref", arg, yref) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_contours.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_contours.py new file mode 100644 index 0000000000000000000000000000000000000000..3ba60716af15a881b303d334aa3f3993692c12e4 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_contours.py @@ -0,0 +1,436 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Contours(_BaseTraceHierarchyType): + _parent_path_str = "histogram2dcontour" + _path_str = "histogram2dcontour.contours" + _valid_props = { + "coloring", + "end", + "labelfont", + "labelformat", + "operation", + "showlabels", + "showlines", + "size", + "start", + "type", + "value", + } + + @property + def coloring(self): + """ + Determines the coloring method showing the contour values. If + "fill", coloring is done evenly between each contour level If + "heatmap", a heatmap gradient coloring is applied between each + contour level. If "lines", coloring is done on the contour + lines. If "none", no coloring is applied on this trace. + + The 'coloring' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fill', 'heatmap', 'lines', 'none'] + + Returns + ------- + Any + """ + return self["coloring"] + + @coloring.setter + def coloring(self, val): + self["coloring"] = val + + @property + def end(self): + """ + Sets the end contour level value. Must be more than + `contours.start` + + The 'end' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["end"] + + @end.setter + def end(self, val): + self["end"] = val + + @property + def labelfont(self): + """ + Sets the font used for labeling the contour levels. The default + color comes from the lines, if shown. The default family and + size come from `layout.font`. + + The 'labelfont' property is an instance of Labelfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.contours.Labelfont` + - A dict of string/value properties that will be passed + to the Labelfont constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.contours.Labelfont + """ + return self["labelfont"] + + @labelfont.setter + def labelfont(self, val): + self["labelfont"] = val + + @property + def labelformat(self): + """ + Sets the contour label formatting rule using d3 formatting + mini-languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + + The 'labelformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["labelformat"] + + @labelformat.setter + def labelformat(self, val): + self["labelformat"] = val + + @property + def operation(self): + """ + Sets the constraint operation. "=" keeps regions equal to + `value` "<" and "<=" keep regions less than `value` ">" and + ">=" keep regions greater than `value` "[]", "()", "[)", and + "(]" keep regions inside `value[0]` to `value[1]` "][", ")(", + "](", ")[" keep regions outside `value[0]` to value[1]` Open + vs. closed intervals make no difference to constraint display, + but all versions are allowed for consistency with filter + transforms. + + The 'operation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['=', '<', '>=', '>', '<=', '[]', '()', '[)', '(]', '][', + ')(', '](', ')['] + + Returns + ------- + Any + """ + return self["operation"] + + @operation.setter + def operation(self, val): + self["operation"] = val + + @property + def showlabels(self): + """ + Determines whether to label the contour lines with their + values. + + The 'showlabels' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlabels"] + + @showlabels.setter + def showlabels(self, val): + self["showlabels"] = val + + @property + def showlines(self): + """ + Determines whether or not the contour lines are drawn. Has an + effect only if `contours.coloring` is set to "fill". + + The 'showlines' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlines"] + + @showlines.setter + def showlines(self, val): + self["showlines"] = val + + @property + def size(self): + """ + Sets the step between each contour level. Must be positive. + + The 'size' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def start(self): + """ + Sets the starting contour level value. Must be less than + `contours.end` + + The 'start' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["start"] + + @start.setter + def start(self, val): + self["start"] = val + + @property + def type(self): + """ + If `levels`, the data is represented as a contour plot with + multiple levels displayed. If `constraint`, the data is + represented as constraints with the invalid region shaded as + specified by the `operation` and `value` parameters. + + The 'type' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['levels', 'constraint'] + + Returns + ------- + Any + """ + return self["type"] + + @type.setter + def type(self, val): + self["type"] = val + + @property + def value(self): + """ + Sets the value or values of the constraint boundary. When + `operation` is set to one of the comparison values + (`=,<,>=,>,<=`) "value" is expected to be a number. When + `operation` is set to one of the interval values + (`[],(),[),(],][,)(,](,)[`) "value" is expected to be an array + of two numbers where the first is the lower bound and the + second is the upper bound. + + The 'value' property accepts values of any type + + Returns + ------- + Any + """ + return self["value"] + + @value.setter + def value(self, val): + self["value"] = val + + @property + def _prop_descriptions(self): + return """\ + coloring + Determines the coloring method showing the contour + values. If "fill", coloring is done evenly between each + contour level If "heatmap", a heatmap gradient coloring + is applied between each contour level. If "lines", + coloring is done on the contour lines. If "none", no + coloring is applied on this trace. + end + Sets the end contour level value. Must be more than + `contours.start` + labelfont + Sets the font used for labeling the contour levels. The + default color comes from the lines, if shown. The + default family and size come from `layout.font`. + labelformat + Sets the contour label formatting rule using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + operation + Sets the constraint operation. "=" keeps regions equal + to `value` "<" and "<=" keep regions less than `value` + ">" and ">=" keep regions greater than `value` "[]", + "()", "[)", and "(]" keep regions inside `value[0]` to + `value[1]` "][", ")(", "](", ")[" keep regions outside + `value[0]` to value[1]` Open vs. closed intervals make + no difference to constraint display, but all versions + are allowed for consistency with filter transforms. + showlabels + Determines whether to label the contour lines with + their values. + showlines + Determines whether or not the contour lines are drawn. + Has an effect only if `contours.coloring` is set to + "fill". + size + Sets the step between each contour level. Must be + positive. + start + Sets the starting contour level value. Must be less + than `contours.end` + type + If `levels`, the data is represented as a contour plot + with multiple levels displayed. If `constraint`, the + data is represented as constraints with the invalid + region shaded as specified by the `operation` and + `value` parameters. + value + Sets the value or values of the constraint boundary. + When `operation` is set to one of the comparison values + (`=,<,>=,>,<=`) "value" is expected to be a number. + When `operation` is set to one of the interval values + (`[],(),[),(],][,)(,](,)[`) "value" is expected to be + an array of two numbers where the first is the lower + bound and the second is the upper bound. + """ + + def __init__( + self, + arg=None, + coloring=None, + end=None, + labelfont=None, + labelformat=None, + operation=None, + showlabels=None, + showlines=None, + size=None, + start=None, + type=None, + value=None, + **kwargs, + ): + """ + Construct a new Contours object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.histogram2dcontour.Contours` + coloring + Determines the coloring method showing the contour + values. If "fill", coloring is done evenly between each + contour level If "heatmap", a heatmap gradient coloring + is applied between each contour level. If "lines", + coloring is done on the contour lines. If "none", no + coloring is applied on this trace. + end + Sets the end contour level value. Must be more than + `contours.start` + labelfont + Sets the font used for labeling the contour levels. The + default color comes from the lines, if shown. The + default family and size come from `layout.font`. + labelformat + Sets the contour label formatting rule using d3 + formatting mini-languages which are very similar to + those in Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + operation + Sets the constraint operation. "=" keeps regions equal + to `value` "<" and "<=" keep regions less than `value` + ">" and ">=" keep regions greater than `value` "[]", + "()", "[)", and "(]" keep regions inside `value[0]` to + `value[1]` "][", ")(", "](", ")[" keep regions outside + `value[0]` to value[1]` Open vs. closed intervals make + no difference to constraint display, but all versions + are allowed for consistency with filter transforms. + showlabels + Determines whether to label the contour lines with + their values. + showlines + Determines whether or not the contour lines are drawn. + Has an effect only if `contours.coloring` is set to + "fill". + size + Sets the step between each contour level. Must be + positive. + start + Sets the starting contour level value. Must be less + than `contours.end` + type + If `levels`, the data is represented as a contour plot + with multiple levels displayed. If `constraint`, the + data is represented as constraints with the invalid + region shaded as specified by the `operation` and + `value` parameters. + value + Sets the value or values of the constraint boundary. + When `operation` is set to one of the comparison values + (`=,<,>=,>,<=`) "value" is expected to be a number. + When `operation` is set to one of the interval values + (`[],(),[),(],][,)(,](,)[`) "value" is expected to be + an array of two numbers where the first is the lower + bound and the second is the upper bound. + + Returns + ------- + Contours + """ + super().__init__("contours") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.histogram2dcontour.Contours +constructor must be a dict or +an instance of :class:`plotly.graph_objs.histogram2dcontour.Contours`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("coloring", arg, coloring) + self._set_property("end", arg, end) + self._set_property("labelfont", arg, labelfont) + self._set_property("labelformat", arg, labelformat) + self._set_property("operation", arg, operation) + self._set_property("showlabels", arg, showlabels) + self._set_property("showlines", arg, showlines) + self._set_property("size", arg, size) + self._set_property("start", arg, start) + self._set_property("type", arg, type) + self._set_property("value", arg, value) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_hoverlabel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_hoverlabel.py new file mode 100644 index 0000000000000000000000000000000000000000..907db44d7d914282c30504fa3d40251c205c146f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_hoverlabel.py @@ -0,0 +1,366 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Hoverlabel(_BaseTraceHierarchyType): + _parent_path_str = "histogram2dcontour" + _path_str = "histogram2dcontour.hoverlabel" + _valid_props = { + "align", + "alignsrc", + "bgcolor", + "bgcolorsrc", + "bordercolor", + "bordercolorsrc", + "font", + "namelength", + "namelengthsrc", + "showarrow", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the text content within hover + label box. Has an effect only if the hover label text spans + more two or more lines + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'auto'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def alignsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `align`. + + The 'alignsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["alignsrc"] + + @alignsrc.setter + def alignsrc(self, val): + self["alignsrc"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the hover labels for this trace + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bgcolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `bgcolor`. + + The 'bgcolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bgcolorsrc"] + + @bgcolorsrc.setter + def bgcolorsrc(self, val): + self["bgcolorsrc"] = val + + @property + def bordercolor(self): + """ + Sets the border color of the hover labels for this trace. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def bordercolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + + The 'bordercolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bordercolorsrc"] + + @bordercolorsrc.setter + def bordercolorsrc(self, val): + self["bordercolorsrc"] = val + + @property + def font(self): + """ + Sets the font used in hover labels. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.hoverlabel.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.hoverlabel.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def namelength(self): + """ + Sets the default length (in number of characters) of the trace + name in the hover labels for all traces. -1 shows the whole + name regardless of length. 0-3 shows the first 0-3 characters, + and an integer >3 will show the whole name if it is less than + that many characters, but if it is longer, will truncate to + `namelength - 3` characters and add an ellipsis. + + The 'namelength' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["namelength"] + + @namelength.setter + def namelength(self, val): + self["namelength"] = val + + @property + def namelengthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `namelength`. + + The 'namelengthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["namelengthsrc"] + + @namelengthsrc.setter + def namelengthsrc(self, val): + self["namelengthsrc"] = val + + @property + def showarrow(self): + """ + Sets whether or not to show the hover label arrow/triangle + pointing to the data point. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + """ + + def __init__( + self, + arg=None, + align=None, + alignsrc=None, + bgcolor=None, + bgcolorsrc=None, + bordercolor=None, + bordercolorsrc=None, + font=None, + namelength=None, + namelengthsrc=None, + showarrow=None, + **kwargs, + ): + """ + Construct a new Hoverlabel object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.histogram2dcon + tour.Hoverlabel` + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + + Returns + ------- + Hoverlabel + """ + super().__init__("hoverlabel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.histogram2dcontour.Hoverlabel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.histogram2dcontour.Hoverlabel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("alignsrc", arg, alignsrc) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bgcolorsrc", arg, bgcolorsrc) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("bordercolorsrc", arg, bordercolorsrc) + self._set_property("font", arg, font) + self._set_property("namelength", arg, namelength) + self._set_property("namelengthsrc", arg, namelengthsrc) + self._set_property("showarrow", arg, showarrow) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..b32756095166ff7e3eb850c8c5eeb8f9c3868037 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "histogram2dcontour" + _path_str = "histogram2dcontour.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.histogram2dcontour.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.histogram2dcontour.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.histogram2dcon + tour.Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.histogram2dcontour.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.histogram2dcontour.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_line.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_line.py new file mode 100644 index 0000000000000000000000000000000000000000..c57d618dd73732df59ed579b03b5d2d1d9b948a1 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_line.py @@ -0,0 +1,170 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Line(_BaseTraceHierarchyType): + _parent_path_str = "histogram2dcontour" + _path_str = "histogram2dcontour.line" + _valid_props = {"color", "dash", "smoothing", "width"} + + @property + def color(self): + """ + Sets the color of the contour level. Has no effect if + `contours.coloring` is set to "lines". + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def dash(self): + """ + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + + The 'dash' property is an enumeration that may be specified as: + - One of the following dash styles: + ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] + - A string containing a dash length list in pixels or percentages + (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) + + Returns + ------- + str + """ + return self["dash"] + + @dash.setter + def dash(self, val): + self["dash"] = val + + @property + def smoothing(self): + """ + Sets the amount of smoothing for the contour lines, where 0 + corresponds to no smoothing. + + The 'smoothing' property is a number and may be specified as: + - An int or float in the interval [0, 1.3] + + Returns + ------- + int|float + """ + return self["smoothing"] + + @smoothing.setter + def smoothing(self, val): + self["smoothing"] = val + + @property + def width(self): + """ + Sets the contour line width in (in px) + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def _prop_descriptions(self): + return """\ + color + Sets the color of the contour level. Has no effect if + `contours.coloring` is set to "lines". + dash + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + smoothing + Sets the amount of smoothing for the contour lines, + where 0 corresponds to no smoothing. + width + Sets the contour line width in (in px) + """ + + def __init__( + self, arg=None, color=None, dash=None, smoothing=None, width=None, **kwargs + ): + """ + Construct a new Line object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.histogram2dcontour.Line` + color + Sets the color of the contour level. Has no effect if + `contours.coloring` is set to "lines". + dash + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + smoothing + Sets the amount of smoothing for the contour lines, + where 0 corresponds to no smoothing. + width + Sets the contour line width in (in px) + + Returns + ------- + Line + """ + super().__init__("line") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.histogram2dcontour.Line +constructor must be a dict or +an instance of :class:`plotly.graph_objs.histogram2dcontour.Line`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("dash", arg, dash) + self._set_property("smoothing", arg, smoothing) + self._set_property("width", arg, width) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_marker.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_marker.py new file mode 100644 index 0000000000000000000000000000000000000000..146412afab905ca74d14d6ecf58813ae3a386c0f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_marker.py @@ -0,0 +1,102 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Marker(_BaseTraceHierarchyType): + _parent_path_str = "histogram2dcontour" + _path_str = "histogram2dcontour.marker" + _valid_props = {"color", "colorsrc"} + + @property + def color(self): + """ + Sets the aggregation data. + + The 'color' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def colorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `color`. + + The 'colorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["colorsrc"] + + @colorsrc.setter + def colorsrc(self, val): + self["colorsrc"] = val + + @property + def _prop_descriptions(self): + return """\ + color + Sets the aggregation data. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + """ + + def __init__(self, arg=None, color=None, colorsrc=None, **kwargs): + """ + Construct a new Marker object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.histogram2dcontour.Marker` + color + Sets the aggregation data. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + + Returns + ------- + Marker + """ + super().__init__("marker") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.histogram2dcontour.Marker +constructor must be a dict or +an instance of :class:`plotly.graph_objs.histogram2dcontour.Marker`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("colorsrc", arg, colorsrc) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..59dbafd499132bda9c8ba375220b3cd23ce4867f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_stream.py @@ -0,0 +1,114 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "histogram2dcontour" + _path_str = "histogram2dcontour.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.histogram2dcontour.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.histogram2dcontour.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.histogram2dcontour.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_textfont.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_textfont.py new file mode 100644 index 0000000000000000000000000000000000000000..36f7542b158925cd88f9ad70eea9ac17fb1247ed --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_textfont.py @@ -0,0 +1,335 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Textfont(_BaseTraceHierarchyType): + _parent_path_str = "histogram2dcontour" + _path_str = "histogram2dcontour.textfont" + _valid_props = { + "color", + "family", + "lineposition", + "shadow", + "size", + "style", + "textcase", + "variant", + "weight", + } + + @property + def color(self): + """ + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def family(self): + """ + HTML font family - the typeface that will be applied by the web + browser. The web browser can only apply a font if it is + available on the system where it runs. Provide multiple font + families, separated by commas, to indicate the order in which + to apply fonts if they aren't available. + + The 'family' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["family"] + + @family.setter + def family(self, val): + self["family"] = val + + @property + def lineposition(self): + """ + Sets the kind of decoration line(s) with text, such as an + "under", "over" or "through" as well as combinations e.g. + "under+over", etc. + + The 'lineposition' property is a flaglist and may be specified + as a string containing: + - Any combination of ['under', 'over', 'through'] joined with '+' characters + (e.g. 'under+over') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["lineposition"] + + @lineposition.setter + def lineposition(self, val): + self["lineposition"] = val + + @property + def shadow(self): + """ + Sets the shape and color of the shadow behind text. "auto" + places minimal shadow and applies contrast text font color. See + https://developer.mozilla.org/en-US/docs/Web/CSS/text-shadow + for additional options. + + The 'shadow' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["shadow"] + + @shadow.setter + def shadow(self, val): + self["shadow"] = val + + @property + def size(self): + """ + The 'size' property is a number and may be specified as: + - An int or float in the interval [1, inf] + + Returns + ------- + int|float + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def style(self): + """ + Sets whether a font should be styled with a normal or italic + face from its family. + + The 'style' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'italic'] + + Returns + ------- + Any + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def textcase(self): + """ + Sets capitalization of text. It can be used to make text appear + in all-uppercase or all-lowercase, or with each word + capitalized. + + The 'textcase' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'word caps', 'upper', 'lower'] + + Returns + ------- + Any + """ + return self["textcase"] + + @textcase.setter + def textcase(self, val): + self["textcase"] = val + + @property + def variant(self): + """ + Sets the variant of the font. + + The 'variant' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'small-caps', 'all-small-caps', + 'all-petite-caps', 'petite-caps', 'unicase'] + + Returns + ------- + Any + """ + return self["variant"] + + @variant.setter + def variant(self, val): + self["variant"] = val + + @property + def weight(self): + """ + Sets the weight (or boldness) of the font. + + The 'weight' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 1000] + OR exactly one of ['normal', 'bold'] (e.g. 'bold') + + Returns + ------- + int + """ + return self["weight"] + + @weight.setter + def weight(self, val): + self["weight"] = val + + @property + def _prop_descriptions(self): + return """\ + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + """ + + def __init__( + self, + arg=None, + color=None, + family=None, + lineposition=None, + shadow=None, + size=None, + style=None, + textcase=None, + variant=None, + weight=None, + **kwargs, + ): + """ + Construct a new Textfont object + + For this trace it only has an effect if `coloring` is set to + "heatmap". Sets the text font. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.histogram2dcontour.Textfont` + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + + Returns + ------- + Textfont + """ + super().__init__("textfont") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.histogram2dcontour.Textfont +constructor must be a dict or +an instance of :class:`plotly.graph_objs.histogram2dcontour.Textfont`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("family", arg, family) + self._set_property("lineposition", arg, lineposition) + self._set_property("shadow", arg, shadow) + self._set_property("size", arg, size) + self._set_property("style", arg, style) + self._set_property("textcase", arg, textcase) + self._set_property("variant", arg, variant) + self._set_property("weight", arg, weight) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_xbins.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_xbins.py new file mode 100644 index 0000000000000000000000000000000000000000..80a4aca6f845fe655dfc9543c449d8af9a7f8cf2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_xbins.py @@ -0,0 +1,187 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class XBins(_BaseTraceHierarchyType): + _parent_path_str = "histogram2dcontour" + _path_str = "histogram2dcontour.xbins" + _valid_props = {"end", "size", "start"} + + @property + def end(self): + """ + Sets the end value for the x axis bins. The last bin may not + end exactly at this value, we increment the bin edge by `size` + from `start` until we reach or exceed `end`. Defaults to the + maximum data value. Like `start`, for dates use a date string, + and for category data `end` is based on the category serial + numbers. + + The 'end' property accepts values of any type + + Returns + ------- + Any + """ + return self["end"] + + @end.setter + def end(self, val): + self["end"] = val + + @property + def size(self): + """ + Sets the size of each x axis bin. Default behavior: If `nbinsx` + is 0 or omitted, we choose a nice round bin size such that the + number of bins is about the same as the typical number of + samples in each bin. If `nbinsx` is provided, we choose a nice + round bin size giving no more than that many bins. For date + data, use milliseconds or "M" for months, as in + `axis.dtick`. For category data, the number of categories to + bin together (always defaults to 1). + + The 'size' property accepts values of any type + + Returns + ------- + Any + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def start(self): + """ + Sets the starting value for the x axis bins. Defaults to the + minimum data value, shifted down if necessary to make nice + round values and to remove ambiguous bin edges. For example, if + most of the data is integers we shift the bin edges 0.5 down, + so a `size` of 5 would have a default `start` of -0.5, so it is + clear that 0-4 are in the first bin, 5-9 in the second, but + continuous data gets a start of 0 and bins [0,5), [5,10) etc. + Dates behave similarly, and `start` should be a date string. + For category data, `start` is based on the category serial + numbers, and defaults to -0.5. + + The 'start' property accepts values of any type + + Returns + ------- + Any + """ + return self["start"] + + @start.setter + def start(self, val): + self["start"] = val + + @property + def _prop_descriptions(self): + return """\ + end + Sets the end value for the x axis bins. The last bin + may not end exactly at this value, we increment the bin + edge by `size` from `start` until we reach or exceed + `end`. Defaults to the maximum data value. Like + `start`, for dates use a date string, and for category + data `end` is based on the category serial numbers. + size + Sets the size of each x axis bin. Default behavior: If + `nbinsx` is 0 or omitted, we choose a nice round bin + size such that the number of bins is about the same as + the typical number of samples in each bin. If `nbinsx` + is provided, we choose a nice round bin size giving no + more than that many bins. For date data, use + milliseconds or "M" for months, as in `axis.dtick`. + For category data, the number of categories to bin + together (always defaults to 1). + start + Sets the starting value for the x axis bins. Defaults + to the minimum data value, shifted down if necessary to + make nice round values and to remove ambiguous bin + edges. For example, if most of the data is integers we + shift the bin edges 0.5 down, so a `size` of 5 would + have a default `start` of -0.5, so it is clear that 0-4 + are in the first bin, 5-9 in the second, but continuous + data gets a start of 0 and bins [0,5), [5,10) etc. + Dates behave similarly, and `start` should be a date + string. For category data, `start` is based on the + category serial numbers, and defaults to -0.5. + """ + + def __init__(self, arg=None, end=None, size=None, start=None, **kwargs): + """ + Construct a new XBins object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.histogram2dcontour.XBins` + end + Sets the end value for the x axis bins. The last bin + may not end exactly at this value, we increment the bin + edge by `size` from `start` until we reach or exceed + `end`. Defaults to the maximum data value. Like + `start`, for dates use a date string, and for category + data `end` is based on the category serial numbers. + size + Sets the size of each x axis bin. Default behavior: If + `nbinsx` is 0 or omitted, we choose a nice round bin + size such that the number of bins is about the same as + the typical number of samples in each bin. If `nbinsx` + is provided, we choose a nice round bin size giving no + more than that many bins. For date data, use + milliseconds or "M" for months, as in `axis.dtick`. + For category data, the number of categories to bin + together (always defaults to 1). + start + Sets the starting value for the x axis bins. Defaults + to the minimum data value, shifted down if necessary to + make nice round values and to remove ambiguous bin + edges. For example, if most of the data is integers we + shift the bin edges 0.5 down, so a `size` of 5 would + have a default `start` of -0.5, so it is clear that 0-4 + are in the first bin, 5-9 in the second, but continuous + data gets a start of 0 and bins [0,5), [5,10) etc. + Dates behave similarly, and `start` should be a date + string. For category data, `start` is based on the + category serial numbers, and defaults to -0.5. + + Returns + ------- + XBins + """ + super().__init__("xbins") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.histogram2dcontour.XBins +constructor must be a dict or +an instance of :class:`plotly.graph_objs.histogram2dcontour.XBins`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("end", arg, end) + self._set_property("size", arg, size) + self._set_property("start", arg, start) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_ybins.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_ybins.py new file mode 100644 index 0000000000000000000000000000000000000000..f73dc70ab9a08fb5808113cb258a3b818ddb6bc7 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/histogram2dcontour/_ybins.py @@ -0,0 +1,187 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class YBins(_BaseTraceHierarchyType): + _parent_path_str = "histogram2dcontour" + _path_str = "histogram2dcontour.ybins" + _valid_props = {"end", "size", "start"} + + @property + def end(self): + """ + Sets the end value for the y axis bins. The last bin may not + end exactly at this value, we increment the bin edge by `size` + from `start` until we reach or exceed `end`. Defaults to the + maximum data value. Like `start`, for dates use a date string, + and for category data `end` is based on the category serial + numbers. + + The 'end' property accepts values of any type + + Returns + ------- + Any + """ + return self["end"] + + @end.setter + def end(self, val): + self["end"] = val + + @property + def size(self): + """ + Sets the size of each y axis bin. Default behavior: If `nbinsy` + is 0 or omitted, we choose a nice round bin size such that the + number of bins is about the same as the typical number of + samples in each bin. If `nbinsy` is provided, we choose a nice + round bin size giving no more than that many bins. For date + data, use milliseconds or "M" for months, as in + `axis.dtick`. For category data, the number of categories to + bin together (always defaults to 1). + + The 'size' property accepts values of any type + + Returns + ------- + Any + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def start(self): + """ + Sets the starting value for the y axis bins. Defaults to the + minimum data value, shifted down if necessary to make nice + round values and to remove ambiguous bin edges. For example, if + most of the data is integers we shift the bin edges 0.5 down, + so a `size` of 5 would have a default `start` of -0.5, so it is + clear that 0-4 are in the first bin, 5-9 in the second, but + continuous data gets a start of 0 and bins [0,5), [5,10) etc. + Dates behave similarly, and `start` should be a date string. + For category data, `start` is based on the category serial + numbers, and defaults to -0.5. + + The 'start' property accepts values of any type + + Returns + ------- + Any + """ + return self["start"] + + @start.setter + def start(self, val): + self["start"] = val + + @property + def _prop_descriptions(self): + return """\ + end + Sets the end value for the y axis bins. The last bin + may not end exactly at this value, we increment the bin + edge by `size` from `start` until we reach or exceed + `end`. Defaults to the maximum data value. Like + `start`, for dates use a date string, and for category + data `end` is based on the category serial numbers. + size + Sets the size of each y axis bin. Default behavior: If + `nbinsy` is 0 or omitted, we choose a nice round bin + size such that the number of bins is about the same as + the typical number of samples in each bin. If `nbinsy` + is provided, we choose a nice round bin size giving no + more than that many bins. For date data, use + milliseconds or "M" for months, as in `axis.dtick`. + For category data, the number of categories to bin + together (always defaults to 1). + start + Sets the starting value for the y axis bins. Defaults + to the minimum data value, shifted down if necessary to + make nice round values and to remove ambiguous bin + edges. For example, if most of the data is integers we + shift the bin edges 0.5 down, so a `size` of 5 would + have a default `start` of -0.5, so it is clear that 0-4 + are in the first bin, 5-9 in the second, but continuous + data gets a start of 0 and bins [0,5), [5,10) etc. + Dates behave similarly, and `start` should be a date + string. For category data, `start` is based on the + category serial numbers, and defaults to -0.5. + """ + + def __init__(self, arg=None, end=None, size=None, start=None, **kwargs): + """ + Construct a new YBins object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.histogram2dcontour.YBins` + end + Sets the end value for the y axis bins. The last bin + may not end exactly at this value, we increment the bin + edge by `size` from `start` until we reach or exceed + `end`. Defaults to the maximum data value. Like + `start`, for dates use a date string, and for category + data `end` is based on the category serial numbers. + size + Sets the size of each y axis bin. Default behavior: If + `nbinsy` is 0 or omitted, we choose a nice round bin + size such that the number of bins is about the same as + the typical number of samples in each bin. If `nbinsy` + is provided, we choose a nice round bin size giving no + more than that many bins. For date data, use + milliseconds or "M" for months, as in `axis.dtick`. + For category data, the number of categories to bin + together (always defaults to 1). + start + Sets the starting value for the y axis bins. Defaults + to the minimum data value, shifted down if necessary to + make nice round values and to remove ambiguous bin + edges. For example, if most of the data is integers we + shift the bin edges 0.5 down, so a `size` of 5 would + have a default `start` of -0.5, so it is clear that 0-4 + are in the first bin, 5-9 in the second, but continuous + data gets a start of 0 and bins [0,5), [5,10) etc. + Dates behave similarly, and `start` should be a date + string. For category data, `start` is based on the + category serial numbers, and defaults to -0.5. + + Returns + ------- + YBins + """ + super().__init__("ybins") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.histogram2dcontour.YBins +constructor must be a dict or +an instance of :class:`plotly.graph_objs.histogram2dcontour.YBins`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("end", arg, end) + self._set_property("size", arg, size) + self._set_property("start", arg, start) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..d1ed63eda0945c125adca59d5c33c979ec927129 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/__init__.py @@ -0,0 +1,32 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._delta import Delta + from ._domain import Domain + from ._gauge import Gauge + from ._legendgrouptitle import Legendgrouptitle + from ._number import Number + from ._stream import Stream + from ._title import Title + from . import delta + from . import gauge + from . import legendgrouptitle + from . import number + from . import title +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [".delta", ".gauge", ".legendgrouptitle", ".number", ".title"], + [ + "._delta.Delta", + "._domain.Domain", + "._gauge.Gauge", + "._legendgrouptitle.Legendgrouptitle", + "._number.Number", + "._stream.Stream", + "._title.Title", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_delta.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_delta.py new file mode 100644 index 0000000000000000000000000000000000000000..6c40ef637ebdfdcba460909861f6380818f52d78 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_delta.py @@ -0,0 +1,309 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Delta(_BaseTraceHierarchyType): + _parent_path_str = "indicator" + _path_str = "indicator.delta" + _valid_props = { + "decreasing", + "font", + "increasing", + "position", + "prefix", + "reference", + "relative", + "suffix", + "valueformat", + } + + @property + def decreasing(self): + """ + The 'decreasing' property is an instance of Decreasing + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.delta.Decreasing` + - A dict of string/value properties that will be passed + to the Decreasing constructor + + Returns + ------- + plotly.graph_objs.indicator.delta.Decreasing + """ + return self["decreasing"] + + @decreasing.setter + def decreasing(self, val): + self["decreasing"] = val + + @property + def font(self): + """ + Set the font used to display the delta + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.delta.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.indicator.delta.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def increasing(self): + """ + The 'increasing' property is an instance of Increasing + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.delta.Increasing` + - A dict of string/value properties that will be passed + to the Increasing constructor + + Returns + ------- + plotly.graph_objs.indicator.delta.Increasing + """ + return self["increasing"] + + @increasing.setter + def increasing(self, val): + self["increasing"] = val + + @property + def position(self): + """ + Sets the position of delta with respect to the number. + + The 'position' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top', 'bottom', 'left', 'right'] + + Returns + ------- + Any + """ + return self["position"] + + @position.setter + def position(self, val): + self["position"] = val + + @property + def prefix(self): + """ + Sets a prefix appearing before the delta. + + The 'prefix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["prefix"] + + @prefix.setter + def prefix(self, val): + self["prefix"] = val + + @property + def reference(self): + """ + Sets the reference value to compute the delta. By default, it + is set to the current value. + + The 'reference' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["reference"] + + @reference.setter + def reference(self, val): + self["reference"] = val + + @property + def relative(self): + """ + Show relative change + + The 'relative' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["relative"] + + @relative.setter + def relative(self, val): + self["relative"] = val + + @property + def suffix(self): + """ + Sets a suffix appearing next to the delta. + + The 'suffix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["suffix"] + + @suffix.setter + def suffix(self, val): + self["suffix"] = val + + @property + def valueformat(self): + """ + Sets the value formatting rule using d3 formatting mini- + languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + + The 'valueformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["valueformat"] + + @valueformat.setter + def valueformat(self, val): + self["valueformat"] = val + + @property + def _prop_descriptions(self): + return """\ + decreasing + :class:`plotly.graph_objects.indicator.delta.Decreasing + ` instance or dict with compatible properties + font + Set the font used to display the delta + increasing + :class:`plotly.graph_objects.indicator.delta.Increasing + ` instance or dict with compatible properties + position + Sets the position of delta with respect to the number. + prefix + Sets a prefix appearing before the delta. + reference + Sets the reference value to compute the delta. By + default, it is set to the current value. + relative + Show relative change + suffix + Sets a suffix appearing next to the delta. + valueformat + Sets the value formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + """ + + def __init__( + self, + arg=None, + decreasing=None, + font=None, + increasing=None, + position=None, + prefix=None, + reference=None, + relative=None, + suffix=None, + valueformat=None, + **kwargs, + ): + """ + Construct a new Delta object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.indicator.Delta` + decreasing + :class:`plotly.graph_objects.indicator.delta.Decreasing + ` instance or dict with compatible properties + font + Set the font used to display the delta + increasing + :class:`plotly.graph_objects.indicator.delta.Increasing + ` instance or dict with compatible properties + position + Sets the position of delta with respect to the number. + prefix + Sets a prefix appearing before the delta. + reference + Sets the reference value to compute the delta. By + default, it is set to the current value. + relative + Show relative change + suffix + Sets a suffix appearing next to the delta. + valueformat + Sets the value formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + + Returns + ------- + Delta + """ + super().__init__("delta") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.indicator.Delta +constructor must be a dict or +an instance of :class:`plotly.graph_objs.indicator.Delta`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("decreasing", arg, decreasing) + self._set_property("font", arg, font) + self._set_property("increasing", arg, increasing) + self._set_property("position", arg, position) + self._set_property("prefix", arg, prefix) + self._set_property("reference", arg, reference) + self._set_property("relative", arg, relative) + self._set_property("suffix", arg, suffix) + self._set_property("valueformat", arg, valueformat) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_domain.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_domain.py new file mode 100644 index 0000000000000000000000000000000000000000..1aaf4e66a6f08635b116c9c5a7ba26308db77bed --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_domain.py @@ -0,0 +1,170 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Domain(_BaseTraceHierarchyType): + _parent_path_str = "indicator" + _path_str = "indicator.domain" + _valid_props = {"column", "row", "x", "y"} + + @property + def column(self): + """ + If there is a layout grid, use the domain for this column in + the grid for this indicator trace . + + The 'column' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["column"] + + @column.setter + def column(self, val): + self["column"] = val + + @property + def row(self): + """ + If there is a layout grid, use the domain for this row in the + grid for this indicator trace . + + The 'row' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["row"] + + @row.setter + def row(self, val): + self["row"] = val + + @property + def x(self): + """ + Sets the horizontal domain of this indicator trace (in plot + fraction). + + The 'x' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'x[0]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + (1) The 'x[1]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + list + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def y(self): + """ + Sets the vertical domain of this indicator trace (in plot + fraction). + + The 'y' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'y[0]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + (1) The 'y[1]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + list + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def _prop_descriptions(self): + return """\ + column + If there is a layout grid, use the domain for this + column in the grid for this indicator trace . + row + If there is a layout grid, use the domain for this row + in the grid for this indicator trace . + x + Sets the horizontal domain of this indicator trace (in + plot fraction). + y + Sets the vertical domain of this indicator trace (in + plot fraction). + """ + + def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): + """ + Construct a new Domain object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.indicator.Domain` + column + If there is a layout grid, use the domain for this + column in the grid for this indicator trace . + row + If there is a layout grid, use the domain for this row + in the grid for this indicator trace . + x + Sets the horizontal domain of this indicator trace (in + plot fraction). + y + Sets the vertical domain of this indicator trace (in + plot fraction). + + Returns + ------- + Domain + """ + super().__init__("domain") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.indicator.Domain +constructor must be a dict or +an instance of :class:`plotly.graph_objs.indicator.Domain`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("column", arg, column) + self._set_property("row", arg, row) + self._set_property("x", arg, x) + self._set_property("y", arg, y) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_gauge.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_gauge.py new file mode 100644 index 0000000000000000000000000000000000000000..1fde32d64cfcf2ef42189715500c5d7fc1e8ed72 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_gauge.py @@ -0,0 +1,323 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Gauge(_BaseTraceHierarchyType): + _parent_path_str = "indicator" + _path_str = "indicator.gauge" + _valid_props = { + "axis", + "bar", + "bgcolor", + "bordercolor", + "borderwidth", + "shape", + "stepdefaults", + "steps", + "threshold", + } + + @property + def axis(self): + """ + The 'axis' property is an instance of Axis + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.gauge.Axis` + - A dict of string/value properties that will be passed + to the Axis constructor + + Returns + ------- + plotly.graph_objs.indicator.gauge.Axis + """ + return self["axis"] + + @axis.setter + def axis(self, val): + self["axis"] = val + + @property + def bar(self): + """ + Set the appearance of the gauge's value + + The 'bar' property is an instance of Bar + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.gauge.Bar` + - A dict of string/value properties that will be passed + to the Bar constructor + + Returns + ------- + plotly.graph_objs.indicator.gauge.Bar + """ + return self["bar"] + + @bar.setter + def bar(self, val): + self["bar"] = val + + @property + def bgcolor(self): + """ + Sets the gauge background color. + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bordercolor(self): + """ + Sets the color of the border enclosing the gauge. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def borderwidth(self): + """ + Sets the width (in px) of the border enclosing the gauge. + + The 'borderwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["borderwidth"] + + @borderwidth.setter + def borderwidth(self, val): + self["borderwidth"] = val + + @property + def shape(self): + """ + Set the shape of the gauge + + The 'shape' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['angular', 'bullet'] + + Returns + ------- + Any + """ + return self["shape"] + + @shape.setter + def shape(self, val): + self["shape"] = val + + @property + def steps(self): + """ + The 'steps' property is a tuple of instances of + Step that may be specified as: + - A list or tuple of instances of plotly.graph_objs.indicator.gauge.Step + - A list or tuple of dicts of string/value properties that + will be passed to the Step constructor + + Returns + ------- + tuple[plotly.graph_objs.indicator.gauge.Step] + """ + return self["steps"] + + @steps.setter + def steps(self, val): + self["steps"] = val + + @property + def stepdefaults(self): + """ + When used in a template (as + layout.template.data.indicator.gauge.stepdefaults), sets the + default property values to use for elements of + indicator.gauge.steps + + The 'stepdefaults' property is an instance of Step + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.gauge.Step` + - A dict of string/value properties that will be passed + to the Step constructor + + Returns + ------- + plotly.graph_objs.indicator.gauge.Step + """ + return self["stepdefaults"] + + @stepdefaults.setter + def stepdefaults(self, val): + self["stepdefaults"] = val + + @property + def threshold(self): + """ + The 'threshold' property is an instance of Threshold + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.gauge.Threshold` + - A dict of string/value properties that will be passed + to the Threshold constructor + + Returns + ------- + plotly.graph_objs.indicator.gauge.Threshold + """ + return self["threshold"] + + @threshold.setter + def threshold(self, val): + self["threshold"] = val + + @property + def _prop_descriptions(self): + return """\ + axis + :class:`plotly.graph_objects.indicator.gauge.Axis` + instance or dict with compatible properties + bar + Set the appearance of the gauge's value + bgcolor + Sets the gauge background color. + bordercolor + Sets the color of the border enclosing the gauge. + borderwidth + Sets the width (in px) of the border enclosing the + gauge. + shape + Set the shape of the gauge + steps + A tuple of + :class:`plotly.graph_objects.indicator.gauge.Step` + instances or dicts with compatible properties + stepdefaults + When used in a template (as + layout.template.data.indicator.gauge.stepdefaults), + sets the default property values to use for elements of + indicator.gauge.steps + threshold + :class:`plotly.graph_objects.indicator.gauge.Threshold` + instance or dict with compatible properties + """ + + def __init__( + self, + arg=None, + axis=None, + bar=None, + bgcolor=None, + bordercolor=None, + borderwidth=None, + shape=None, + steps=None, + stepdefaults=None, + threshold=None, + **kwargs, + ): + """ + Construct a new Gauge object + + The gauge of the Indicator plot. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.indicator.Gauge` + axis + :class:`plotly.graph_objects.indicator.gauge.Axis` + instance or dict with compatible properties + bar + Set the appearance of the gauge's value + bgcolor + Sets the gauge background color. + bordercolor + Sets the color of the border enclosing the gauge. + borderwidth + Sets the width (in px) of the border enclosing the + gauge. + shape + Set the shape of the gauge + steps + A tuple of + :class:`plotly.graph_objects.indicator.gauge.Step` + instances or dicts with compatible properties + stepdefaults + When used in a template (as + layout.template.data.indicator.gauge.stepdefaults), + sets the default property values to use for elements of + indicator.gauge.steps + threshold + :class:`plotly.graph_objects.indicator.gauge.Threshold` + instance or dict with compatible properties + + Returns + ------- + Gauge + """ + super().__init__("gauge") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.indicator.Gauge +constructor must be a dict or +an instance of :class:`plotly.graph_objs.indicator.Gauge`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("axis", arg, axis) + self._set_property("bar", arg, bar) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("borderwidth", arg, borderwidth) + self._set_property("shape", arg, shape) + self._set_property("steps", arg, steps) + self._set_property("stepdefaults", arg, stepdefaults) + self._set_property("threshold", arg, threshold) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..d4767c7ed415187801696b2c7c72589ec421709a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "indicator" + _path_str = "indicator.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.indicator.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.indicator.Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.indicator.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.indicator.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_number.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_number.py new file mode 100644 index 0000000000000000000000000000000000000000..487d4fdc7886e2729e1498f8b898183b34943c6d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_number.py @@ -0,0 +1,163 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Number(_BaseTraceHierarchyType): + _parent_path_str = "indicator" + _path_str = "indicator.number" + _valid_props = {"font", "prefix", "suffix", "valueformat"} + + @property + def font(self): + """ + Set the font used to display main number + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.number.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.indicator.number.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def prefix(self): + """ + Sets a prefix appearing before the number. + + The 'prefix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["prefix"] + + @prefix.setter + def prefix(self, val): + self["prefix"] = val + + @property + def suffix(self): + """ + Sets a suffix appearing next to the number. + + The 'suffix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["suffix"] + + @suffix.setter + def suffix(self, val): + self["suffix"] = val + + @property + def valueformat(self): + """ + Sets the value formatting rule using d3 formatting mini- + languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + + The 'valueformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["valueformat"] + + @valueformat.setter + def valueformat(self, val): + self["valueformat"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Set the font used to display main number + prefix + Sets a prefix appearing before the number. + suffix + Sets a suffix appearing next to the number. + valueformat + Sets the value formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + """ + + def __init__( + self, arg=None, font=None, prefix=None, suffix=None, valueformat=None, **kwargs + ): + """ + Construct a new Number object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.indicator.Number` + font + Set the font used to display main number + prefix + Sets a prefix appearing before the number. + suffix + Sets a suffix appearing next to the number. + valueformat + Sets the value formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + + Returns + ------- + Number + """ + super().__init__("number") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.indicator.Number +constructor must be a dict or +an instance of :class:`plotly.graph_objs.indicator.Number`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("prefix", arg, prefix) + self._set_property("suffix", arg, suffix) + self._set_property("valueformat", arg, valueformat) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..0b793d0465096e3404436787aabc41c28fb7acf7 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_stream.py @@ -0,0 +1,114 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "indicator" + _path_str = "indicator.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.indicator.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.indicator.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.indicator.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_title.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_title.py new file mode 100644 index 0000000000000000000000000000000000000000..68f71ab024df2c1d3b2b03536767d604a69d4e25 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/indicator/_title.py @@ -0,0 +1,134 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Title(_BaseTraceHierarchyType): + _parent_path_str = "indicator" + _path_str = "indicator.title" + _valid_props = {"align", "font", "text"} + + @property + def align(self): + """ + Sets the horizontal alignment of the title. It defaults to + `center` except for bullet charts for which it defaults to + right. + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'center', 'right'] + + Returns + ------- + Any + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def font(self): + """ + Set the font used to display the title + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.indicator.title.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.indicator.title.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of this indicator. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the title. It defaults + to `center` except for bullet charts for which it + defaults to right. + font + Set the font used to display the title + text + Sets the title of this indicator. + """ + + def __init__(self, arg=None, align=None, font=None, text=None, **kwargs): + """ + Construct a new Title object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.indicator.Title` + align + Sets the horizontal alignment of the title. It defaults + to `center` except for bullet charts for which it + defaults to right. + font + Set the font used to display the title + text + Sets the title of this indicator. + + Returns + ------- + Title + """ + super().__init__("title") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.indicator.Title +constructor must be a dict or +an instance of :class:`plotly.graph_objs.indicator.Title`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..9fe6cadd55c30fdb555fcb9e92a93d8fe322ec1c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/__init__.py @@ -0,0 +1,120 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._activeselection import Activeselection + from ._activeshape import Activeshape + from ._annotation import Annotation + from ._coloraxis import Coloraxis + from ._colorscale import Colorscale + from ._font import Font + from ._geo import Geo + from ._grid import Grid + from ._hoverlabel import Hoverlabel + from ._image import Image + from ._legend import Legend + from ._map import Map + from ._mapbox import Mapbox + from ._margin import Margin + from ._modebar import Modebar + from ._newselection import Newselection + from ._newshape import Newshape + from ._polar import Polar + from ._scene import Scene + from ._selection import Selection + from ._shape import Shape + from ._slider import Slider + from ._smith import Smith + from ._template import Template + from ._ternary import Ternary + from ._title import Title + from ._transition import Transition + from ._uniformtext import Uniformtext + from ._updatemenu import Updatemenu + from ._xaxis import XAxis + from ._yaxis import YAxis + from . import annotation + from . import coloraxis + from . import geo + from . import grid + from . import hoverlabel + from . import legend + from . import map + from . import mapbox + from . import newselection + from . import newshape + from . import polar + from . import scene + from . import selection + from . import shape + from . import slider + from . import smith + from . import template + from . import ternary + from . import title + from . import updatemenu + from . import xaxis + from . import yaxis +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [ + ".annotation", + ".coloraxis", + ".geo", + ".grid", + ".hoverlabel", + ".legend", + ".map", + ".mapbox", + ".newselection", + ".newshape", + ".polar", + ".scene", + ".selection", + ".shape", + ".slider", + ".smith", + ".template", + ".ternary", + ".title", + ".updatemenu", + ".xaxis", + ".yaxis", + ], + [ + "._activeselection.Activeselection", + "._activeshape.Activeshape", + "._annotation.Annotation", + "._coloraxis.Coloraxis", + "._colorscale.Colorscale", + "._font.Font", + "._geo.Geo", + "._grid.Grid", + "._hoverlabel.Hoverlabel", + "._image.Image", + "._legend.Legend", + "._map.Map", + "._mapbox.Mapbox", + "._margin.Margin", + "._modebar.Modebar", + "._newselection.Newselection", + "._newshape.Newshape", + "._polar.Polar", + "._scene.Scene", + "._selection.Selection", + "._shape.Shape", + "._slider.Slider", + "._smith.Smith", + "._template.Template", + "._ternary.Ternary", + "._title.Title", + "._transition.Transition", + "._uniformtext.Uniformtext", + "._updatemenu.Updatemenu", + "._xaxis.XAxis", + "._yaxis.YAxis", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_activeselection.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_activeselection.py new file mode 100644 index 0000000000000000000000000000000000000000..df8947603fd1a8ba6aa18393e1528b58b8f36fa9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_activeselection.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Activeselection(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.activeselection" + _valid_props = {"fillcolor", "opacity"} + + @property + def fillcolor(self): + """ + Sets the color filling the active selection' interior. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def opacity(self): + """ + Sets the opacity of the active selection. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def _prop_descriptions(self): + return """\ + fillcolor + Sets the color filling the active selection' interior. + opacity + Sets the opacity of the active selection. + """ + + def __init__(self, arg=None, fillcolor=None, opacity=None, **kwargs): + """ + Construct a new Activeselection object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.layout.Activeselection` + fillcolor + Sets the color filling the active selection' interior. + opacity + Sets the opacity of the active selection. + + Returns + ------- + Activeselection + """ + super().__init__("activeselection") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Activeselection +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Activeselection`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("fillcolor", arg, fillcolor) + self._set_property("opacity", arg, opacity) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_activeshape.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_activeshape.py new file mode 100644 index 0000000000000000000000000000000000000000..e350187dc671ed74cb4b4cdcb3d9e45a3b1eb874 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_activeshape.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Activeshape(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.activeshape" + _valid_props = {"fillcolor", "opacity"} + + @property + def fillcolor(self): + """ + Sets the color filling the active shape' interior. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def opacity(self): + """ + Sets the opacity of the active shape. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def _prop_descriptions(self): + return """\ + fillcolor + Sets the color filling the active shape' interior. + opacity + Sets the opacity of the active shape. + """ + + def __init__(self, arg=None, fillcolor=None, opacity=None, **kwargs): + """ + Construct a new Activeshape object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.layout.Activeshape` + fillcolor + Sets the color filling the active shape' interior. + opacity + Sets the opacity of the active shape. + + Returns + ------- + Activeshape + """ + super().__init__("activeshape") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Activeshape +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Activeshape`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("fillcolor", arg, fillcolor) + self._set_property("opacity", arg, opacity) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_annotation.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_annotation.py new file mode 100644 index 0000000000000000000000000000000000000000..981373d9f53162044045593fa1787132df4430e8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_annotation.py @@ -0,0 +1,1717 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Annotation(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.annotation" + _valid_props = { + "align", + "arrowcolor", + "arrowhead", + "arrowside", + "arrowsize", + "arrowwidth", + "ax", + "axref", + "ay", + "ayref", + "bgcolor", + "bordercolor", + "borderpad", + "borderwidth", + "captureevents", + "clicktoshow", + "font", + "height", + "hoverlabel", + "hovertext", + "name", + "opacity", + "showarrow", + "standoff", + "startarrowhead", + "startarrowsize", + "startstandoff", + "templateitemname", + "text", + "textangle", + "valign", + "visible", + "width", + "x", + "xanchor", + "xclick", + "xref", + "xshift", + "y", + "yanchor", + "yclick", + "yref", + "yshift", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the `text` within the box. Has + an effect only if `text` spans two or more lines (i.e. `text` + contains one or more
HTML tags) or if an explicit width is + set to override the text width. + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'center', 'right'] + + Returns + ------- + Any + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def arrowcolor(self): + """ + Sets the color of the annotation arrow. + + The 'arrowcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["arrowcolor"] + + @arrowcolor.setter + def arrowcolor(self, val): + self["arrowcolor"] = val + + @property + def arrowhead(self): + """ + Sets the end annotation arrow head style. + + The 'arrowhead' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 8] + + Returns + ------- + int + """ + return self["arrowhead"] + + @arrowhead.setter + def arrowhead(self, val): + self["arrowhead"] = val + + @property + def arrowside(self): + """ + Sets the annotation arrow head position. + + The 'arrowside' property is a flaglist and may be specified + as a string containing: + - Any combination of ['end', 'start'] joined with '+' characters + (e.g. 'end+start') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["arrowside"] + + @arrowside.setter + def arrowside(self, val): + self["arrowside"] = val + + @property + def arrowsize(self): + """ + Sets the size of the end annotation arrow head, relative to + `arrowwidth`. A value of 1 (default) gives a head about 3x as + wide as the line. + + The 'arrowsize' property is a number and may be specified as: + - An int or float in the interval [0.3, inf] + + Returns + ------- + int|float + """ + return self["arrowsize"] + + @arrowsize.setter + def arrowsize(self, val): + self["arrowsize"] = val + + @property + def arrowwidth(self): + """ + Sets the width (in px) of annotation arrow line. + + The 'arrowwidth' property is a number and may be specified as: + - An int or float in the interval [0.1, inf] + + Returns + ------- + int|float + """ + return self["arrowwidth"] + + @arrowwidth.setter + def arrowwidth(self, val): + self["arrowwidth"] = val + + @property + def ax(self): + """ + Sets the x component of the arrow tail about the arrow head. If + `axref` is `pixel`, a positive (negative) component corresponds + to an arrow pointing from right to left (left to right). If + `axref` is not `pixel` and is exactly the same as `xref`, this + is an absolute value on that axis, like `x`, specified in the + same coordinates as `xref`. + + The 'ax' property accepts values of any type + + Returns + ------- + Any + """ + return self["ax"] + + @ax.setter + def ax(self, val): + self["ax"] = val + + @property + def axref(self): + """ + Indicates in what coordinates the tail of the annotation + (ax,ay) is specified. If set to a x axis id (e.g. "x" or "x2"), + the `x` position refers to a x coordinate. If set to "paper", + the `x` position refers to the distance from the left of the + plotting area in normalized coordinates where 0 (1) corresponds + to the left (right). If set to a x axis ID followed by "domain" + (separated by a space), the position behaves like for "paper", + but refers to the distance in fractions of the domain length + from the left of the domain of that axis: e.g., *x2 domain* + refers to the domain of the second x axis and a x position of + 0.5 refers to the point between the left and the right of the + domain of the second x axis. In order for absolute positioning + of the arrow to work, "axref" must be exactly the same as + "xref", otherwise "axref" will revert to "pixel" (explained + next). For relative positioning, "axref" can be set to "pixel", + in which case the "ax" value is specified in pixels relative to + "x". Absolute positioning is useful for trendline annotations + which should continue to indicate the correct trend when + zoomed. Relative positioning is useful for specifying the text + offset for an annotated point. + + The 'axref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['pixel'] + - A string that matches one of the following regular expressions: + ['^x([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["axref"] + + @axref.setter + def axref(self, val): + self["axref"] = val + + @property + def ay(self): + """ + Sets the y component of the arrow tail about the arrow head. If + `ayref` is `pixel`, a positive (negative) component corresponds + to an arrow pointing from bottom to top (top to bottom). If + `ayref` is not `pixel` and is exactly the same as `yref`, this + is an absolute value on that axis, like `y`, specified in the + same coordinates as `yref`. + + The 'ay' property accepts values of any type + + Returns + ------- + Any + """ + return self["ay"] + + @ay.setter + def ay(self, val): + self["ay"] = val + + @property + def ayref(self): + """ + Indicates in what coordinates the tail of the annotation + (ax,ay) is specified. If set to a y axis id (e.g. "y" or "y2"), + the `y` position refers to a y coordinate. If set to "paper", + the `y` position refers to the distance from the bottom of the + plotting area in normalized coordinates where 0 (1) corresponds + to the bottom (top). If set to a y axis ID followed by "domain" + (separated by a space), the position behaves like for "paper", + but refers to the distance in fractions of the domain length + from the bottom of the domain of that axis: e.g., *y2 domain* + refers to the domain of the second y axis and a y position of + 0.5 refers to the point between the bottom and the top of the + domain of the second y axis. In order for absolute positioning + of the arrow to work, "ayref" must be exactly the same as + "yref", otherwise "ayref" will revert to "pixel" (explained + next). For relative positioning, "ayref" can be set to "pixel", + in which case the "ay" value is specified in pixels relative to + "y". Absolute positioning is useful for trendline annotations + which should continue to indicate the correct trend when + zoomed. Relative positioning is useful for specifying the text + offset for an annotated point. + + The 'ayref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['pixel'] + - A string that matches one of the following regular expressions: + ['^y([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["ayref"] + + @ayref.setter + def ayref(self, val): + self["ayref"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the annotation. + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bordercolor(self): + """ + Sets the color of the border enclosing the annotation `text`. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def borderpad(self): + """ + Sets the padding (in px) between the `text` and the enclosing + border. + + The 'borderpad' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["borderpad"] + + @borderpad.setter + def borderpad(self, val): + self["borderpad"] = val + + @property + def borderwidth(self): + """ + Sets the width (in px) of the border enclosing the annotation + `text`. + + The 'borderwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["borderwidth"] + + @borderwidth.setter + def borderwidth(self, val): + self["borderwidth"] = val + + @property + def captureevents(self): + """ + Determines whether the annotation text box captures mouse move + and click events, or allows those events to pass through to + data points in the plot that may be behind the annotation. By + default `captureevents` is False unless `hovertext` is + provided. If you use the event `plotly_clickannotation` without + `hovertext` you must explicitly enable `captureevents`. + + The 'captureevents' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["captureevents"] + + @captureevents.setter + def captureevents(self, val): + self["captureevents"] = val + + @property + def clicktoshow(self): + """ + Makes this annotation respond to clicks on the plot. If you + click a data point that exactly matches the `x` and `y` values + of this annotation, and it is hidden (visible: false), it will + appear. In "onoff" mode, you must click the same point again to + make it disappear, so if you click multiple points, you can + show multiple annotations. In "onout" mode, a click anywhere + else in the plot (on another data point or not) will hide this + annotation. If you need to show/hide this annotation in + response to different `x` or `y` values, you can set `xclick` + and/or `yclick`. This is useful for example to label the side + of a bar. To label markers though, `standoff` is preferred over + `xclick` and `yclick`. + + The 'clicktoshow' property is an enumeration that may be specified as: + - One of the following enumeration values: + [False, 'onoff', 'onout'] + + Returns + ------- + Any + """ + return self["clicktoshow"] + + @clicktoshow.setter + def clicktoshow(self, val): + self["clicktoshow"] = val + + @property + def font(self): + """ + Sets the annotation text font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.annotation.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.layout.annotation.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def height(self): + """ + Sets an explicit height for the text box. null (default) lets + the text set the box height. Taller text will be clipped. + + The 'height' property is a number and may be specified as: + - An int or float in the interval [1, inf] + + Returns + ------- + int|float + """ + return self["height"] + + @height.setter + def height(self, val): + self["height"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.annotation.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.layout.annotation.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertext(self): + """ + Sets text to appear when hovering over this annotation. If + omitted or blank, no hover label will appear. + + The 'hovertext' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["hovertext"] + + @hovertext.setter + def hovertext(self, val): + self["hovertext"] = val + + @property + def name(self): + """ + When used in a template, named items are created in the output + figure in addition to any items the figure already has in this + array. You can modify these items in the output figure by + making your own item with `templateitemname` matching this + `name` alongside your modifications (including `visible: false` + or `enabled: false` to hide it). Has no effect outside of a + template. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the annotation (text + arrow). + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def showarrow(self): + """ + Determines whether or not the annotation is drawn with an + arrow. If True, `text` is placed near the arrow's tail. If + False, `text` lines up with the `x` and `y` provided. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def standoff(self): + """ + Sets a distance, in pixels, to move the end arrowhead away from + the position it is pointing at, for example to point at the + edge of a marker independent of zoom. Note that this shortens + the arrow from the `ax` / `ay` vector, in contrast to `xshift` + / `yshift` which moves everything by this amount. + + The 'standoff' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["standoff"] + + @standoff.setter + def standoff(self, val): + self["standoff"] = val + + @property + def startarrowhead(self): + """ + Sets the start annotation arrow head style. + + The 'startarrowhead' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 8] + + Returns + ------- + int + """ + return self["startarrowhead"] + + @startarrowhead.setter + def startarrowhead(self, val): + self["startarrowhead"] = val + + @property + def startarrowsize(self): + """ + Sets the size of the start annotation arrow head, relative to + `arrowwidth`. A value of 1 (default) gives a head about 3x as + wide as the line. + + The 'startarrowsize' property is a number and may be specified as: + - An int or float in the interval [0.3, inf] + + Returns + ------- + int|float + """ + return self["startarrowsize"] + + @startarrowsize.setter + def startarrowsize(self, val): + self["startarrowsize"] = val + + @property + def startstandoff(self): + """ + Sets a distance, in pixels, to move the start arrowhead away + from the position it is pointing at, for example to point at + the edge of a marker independent of zoom. Note that this + shortens the arrow from the `ax` / `ay` vector, in contrast to + `xshift` / `yshift` which moves everything by this amount. + + The 'startstandoff' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["startstandoff"] + + @startstandoff.setter + def startstandoff(self, val): + self["startstandoff"] = val + + @property + def templateitemname(self): + """ + Used to refer to a named item in this array in the template. + Named items from the template will be created even without a + matching item in the input figure, but you can modify one by + making an item with `templateitemname` matching its `name`, + alongside your modifications (including `visible: false` or + `enabled: false` to hide it). If there is no template or no + matching item, this item will be hidden unless you explicitly + show it with `visible: true`. + + The 'templateitemname' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["templateitemname"] + + @templateitemname.setter + def templateitemname(self, val): + self["templateitemname"] = val + + @property + def text(self): + """ + Sets the text associated with this annotation. Plotly uses a + subset of HTML tags to do things like newline (`
`), bold + (``), italics (``), hyperlinks (``). Tags ``, ``, ``, ``, ``, + and `` are also supported. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def textangle(self): + """ + Sets the angle at which the `text` is drawn with respect to the + horizontal. + + The 'textangle' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["textangle"] + + @textangle.setter + def textangle(self, val): + self["textangle"] = val + + @property + def valign(self): + """ + Sets the vertical alignment of the `text` within the box. Has + an effect only if an explicit height is set to override the + text height. + + The 'valign' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top', 'middle', 'bottom'] + + Returns + ------- + Any + """ + return self["valign"] + + @valign.setter + def valign(self, val): + self["valign"] = val + + @property + def visible(self): + """ + Determines whether or not this annotation is visible. + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def width(self): + """ + Sets an explicit width for the text box. null (default) lets + the text set the box width. Wider text will be clipped. There + is no automatic wrapping; use
to start a new line. + + The 'width' property is a number and may be specified as: + - An int or float in the interval [1, inf] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def x(self): + """ + Sets the annotation's x position. If the axis `type` is "log", + then you must take the log of your desired range. If the axis + `type` is "date", it should be date strings, like date data, + though Date objects and unix milliseconds will be accepted and + converted to strings. If the axis `type` is "category", it + should be numbers, using the scale where each category is + assigned a serial number from zero in the order it appears. + + The 'x' property accepts values of any type + + Returns + ------- + Any + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xanchor(self): + """ + Sets the text box's horizontal position anchor This anchor + binds the `x` position to the "left", "center" or "right" of + the annotation. For example, if `x` is set to 1, `xref` to + "paper" and `xanchor` to "right" then the right-most portion of + the annotation lines up with the right-most edge of the + plotting area. If "auto", the anchor is equivalent to "center" + for data-referenced annotations or if there is an arrow, + whereas for paper-referenced with no arrow, the anchor picked + corresponds to the closest side. + + The 'xanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'left', 'center', 'right'] + + Returns + ------- + Any + """ + return self["xanchor"] + + @xanchor.setter + def xanchor(self, val): + self["xanchor"] = val + + @property + def xclick(self): + """ + Toggle this annotation when clicking a data point whose `x` + value is `xclick` rather than the annotation's `x` value. + + The 'xclick' property accepts values of any type + + Returns + ------- + Any + """ + return self["xclick"] + + @xclick.setter + def xclick(self, val): + self["xclick"] = val + + @property + def xref(self): + """ + Sets the annotation's x coordinate axis. If set to a x axis id + (e.g. "x" or "x2"), the `x` position refers to a x coordinate. + If set to "paper", the `x` position refers to the distance from + the left of the plotting area in normalized coordinates where 0 + (1) corresponds to the left (right). If set to a x axis ID + followed by "domain" (separated by a space), the position + behaves like for "paper", but refers to the distance in + fractions of the domain length from the left of the domain of + that axis: e.g., *x2 domain* refers to the domain of the second + x axis and a x position of 0.5 refers to the point between the + left and the right of the domain of the second x axis. + + The 'xref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['paper'] + - A string that matches one of the following regular expressions: + ['^x([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["xref"] + + @xref.setter + def xref(self, val): + self["xref"] = val + + @property + def xshift(self): + """ + Shifts the position of the whole annotation and arrow to the + right (positive) or left (negative) by this many pixels. + + The 'xshift' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["xshift"] + + @xshift.setter + def xshift(self, val): + self["xshift"] = val + + @property + def y(self): + """ + Sets the annotation's y position. If the axis `type` is "log", + then you must take the log of your desired range. If the axis + `type` is "date", it should be date strings, like date data, + though Date objects and unix milliseconds will be accepted and + converted to strings. If the axis `type` is "category", it + should be numbers, using the scale where each category is + assigned a serial number from zero in the order it appears. + + The 'y' property accepts values of any type + + Returns + ------- + Any + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yanchor(self): + """ + Sets the text box's vertical position anchor This anchor binds + the `y` position to the "top", "middle" or "bottom" of the + annotation. For example, if `y` is set to 1, `yref` to "paper" + and `yanchor` to "top" then the top-most portion of the + annotation lines up with the top-most edge of the plotting + area. If "auto", the anchor is equivalent to "middle" for data- + referenced annotations or if there is an arrow, whereas for + paper-referenced with no arrow, the anchor picked corresponds + to the closest side. + + The 'yanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'top', 'middle', 'bottom'] + + Returns + ------- + Any + """ + return self["yanchor"] + + @yanchor.setter + def yanchor(self, val): + self["yanchor"] = val + + @property + def yclick(self): + """ + Toggle this annotation when clicking a data point whose `y` + value is `yclick` rather than the annotation's `y` value. + + The 'yclick' property accepts values of any type + + Returns + ------- + Any + """ + return self["yclick"] + + @yclick.setter + def yclick(self, val): + self["yclick"] = val + + @property + def yref(self): + """ + Sets the annotation's y coordinate axis. If set to a y axis id + (e.g. "y" or "y2"), the `y` position refers to a y coordinate. + If set to "paper", the `y` position refers to the distance from + the bottom of the plotting area in normalized coordinates where + 0 (1) corresponds to the bottom (top). If set to a y axis ID + followed by "domain" (separated by a space), the position + behaves like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the domain of + that axis: e.g., *y2 domain* refers to the domain of the second + y axis and a y position of 0.5 refers to the point between the + bottom and the top of the domain of the second y axis. + + The 'yref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['paper'] + - A string that matches one of the following regular expressions: + ['^y([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["yref"] + + @yref.setter + def yref(self, val): + self["yref"] = val + + @property + def yshift(self): + """ + Shifts the position of the whole annotation and arrow up + (positive) or down (negative) by this many pixels. + + The 'yshift' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["yshift"] + + @yshift.setter + def yshift(self, val): + self["yshift"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the `text` within the + box. Has an effect only if `text` spans two or more + lines (i.e. `text` contains one or more
HTML tags) + or if an explicit width is set to override the text + width. + arrowcolor + Sets the color of the annotation arrow. + arrowhead + Sets the end annotation arrow head style. + arrowside + Sets the annotation arrow head position. + arrowsize + Sets the size of the end annotation arrow head, + relative to `arrowwidth`. A value of 1 (default) gives + a head about 3x as wide as the line. + arrowwidth + Sets the width (in px) of annotation arrow line. + ax + Sets the x component of the arrow tail about the arrow + head. If `axref` is `pixel`, a positive (negative) + component corresponds to an arrow pointing from right + to left (left to right). If `axref` is not `pixel` and + is exactly the same as `xref`, this is an absolute + value on that axis, like `x`, specified in the same + coordinates as `xref`. + axref + Indicates in what coordinates the tail of the + annotation (ax,ay) is specified. If set to a x axis id + (e.g. "x" or "x2"), the `x` position refers to a x + coordinate. If set to "paper", the `x` position refers + to the distance from the left of the plotting area in + normalized coordinates where 0 (1) corresponds to the + left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. In order for absolute + positioning of the arrow to work, "axref" must be + exactly the same as "xref", otherwise "axref" will + revert to "pixel" (explained next). For relative + positioning, "axref" can be set to "pixel", in which + case the "ax" value is specified in pixels relative to + "x". Absolute positioning is useful for trendline + annotations which should continue to indicate the + correct trend when zoomed. Relative positioning is + useful for specifying the text offset for an annotated + point. + ay + Sets the y component of the arrow tail about the arrow + head. If `ayref` is `pixel`, a positive (negative) + component corresponds to an arrow pointing from bottom + to top (top to bottom). If `ayref` is not `pixel` and + is exactly the same as `yref`, this is an absolute + value on that axis, like `y`, specified in the same + coordinates as `yref`. + ayref + Indicates in what coordinates the tail of the + annotation (ax,ay) is specified. If set to a y axis id + (e.g. "y" or "y2"), the `y` position refers to a y + coordinate. If set to "paper", the `y` position refers + to the distance from the bottom of the plotting area in + normalized coordinates where 0 (1) corresponds to the + bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. In order for absolute + positioning of the arrow to work, "ayref" must be + exactly the same as "yref", otherwise "ayref" will + revert to "pixel" (explained next). For relative + positioning, "ayref" can be set to "pixel", in which + case the "ay" value is specified in pixels relative to + "y". Absolute positioning is useful for trendline + annotations which should continue to indicate the + correct trend when zoomed. Relative positioning is + useful for specifying the text offset for an annotated + point. + bgcolor + Sets the background color of the annotation. + bordercolor + Sets the color of the border enclosing the annotation + `text`. + borderpad + Sets the padding (in px) between the `text` and the + enclosing border. + borderwidth + Sets the width (in px) of the border enclosing the + annotation `text`. + captureevents + Determines whether the annotation text box captures + mouse move and click events, or allows those events to + pass through to data points in the plot that may be + behind the annotation. By default `captureevents` is + False unless `hovertext` is provided. If you use the + event `plotly_clickannotation` without `hovertext` you + must explicitly enable `captureevents`. + clicktoshow + Makes this annotation respond to clicks on the plot. If + you click a data point that exactly matches the `x` and + `y` values of this annotation, and it is hidden + (visible: false), it will appear. In "onoff" mode, you + must click the same point again to make it disappear, + so if you click multiple points, you can show multiple + annotations. In "onout" mode, a click anywhere else in + the plot (on another data point or not) will hide this + annotation. If you need to show/hide this annotation in + response to different `x` or `y` values, you can set + `xclick` and/or `yclick`. This is useful for example to + label the side of a bar. To label markers though, + `standoff` is preferred over `xclick` and `yclick`. + font + Sets the annotation text font. + height + Sets an explicit height for the text box. null + (default) lets the text set the box height. Taller text + will be clipped. + hoverlabel + :class:`plotly.graph_objects.layout.annotation.Hoverlab + el` instance or dict with compatible properties + hovertext + Sets text to appear when hovering over this annotation. + If omitted or blank, no hover label will appear. + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the annotation (text + arrow). + showarrow + Determines whether or not the annotation is drawn with + an arrow. If True, `text` is placed near the arrow's + tail. If False, `text` lines up with the `x` and `y` + provided. + standoff + Sets a distance, in pixels, to move the end arrowhead + away from the position it is pointing at, for example + to point at the edge of a marker independent of zoom. + Note that this shortens the arrow from the `ax` / `ay` + vector, in contrast to `xshift` / `yshift` which moves + everything by this amount. + startarrowhead + Sets the start annotation arrow head style. + startarrowsize + Sets the size of the start annotation arrow head, + relative to `arrowwidth`. A value of 1 (default) gives + a head about 3x as wide as the line. + startstandoff + Sets a distance, in pixels, to move the start arrowhead + away from the position it is pointing at, for example + to point at the edge of a marker independent of zoom. + Note that this shortens the arrow from the `ax` / `ay` + vector, in contrast to `xshift` / `yshift` which moves + everything by this amount. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + text + Sets the text associated with this annotation. Plotly + uses a subset of HTML tags to do things like newline + (`
`), bold (``), italics (``), + hyperlinks (``). Tags ``, + ``, ``, ``, ``, and `` are also + supported. + textangle + Sets the angle at which the `text` is drawn with + respect to the horizontal. + valign + Sets the vertical alignment of the `text` within the + box. Has an effect only if an explicit height is set to + override the text height. + visible + Determines whether or not this annotation is visible. + width + Sets an explicit width for the text box. null (default) + lets the text set the box width. Wider text will be + clipped. There is no automatic wrapping; use
to + start a new line. + x + Sets the annotation's x position. If the axis `type` is + "log", then you must take the log of your desired + range. If the axis `type` is "date", it should be date + strings, like date data, though Date objects and unix + milliseconds will be accepted and converted to strings. + If the axis `type` is "category", it should be numbers, + using the scale where each category is assigned a + serial number from zero in the order it appears. + xanchor + Sets the text box's horizontal position anchor This + anchor binds the `x` position to the "left", "center" + or "right" of the annotation. For example, if `x` is + set to 1, `xref` to "paper" and `xanchor` to "right" + then the right-most portion of the annotation lines up + with the right-most edge of the plotting area. If + "auto", the anchor is equivalent to "center" for data- + referenced annotations or if there is an arrow, whereas + for paper-referenced with no arrow, the anchor picked + corresponds to the closest side. + xclick + Toggle this annotation when clicking a data point whose + `x` value is `xclick` rather than the annotation's `x` + value. + xref + Sets the annotation's x coordinate axis. If set to a x + axis id (e.g. "x" or "x2"), the `x` position refers to + a x coordinate. If set to "paper", the `x` position + refers to the distance from the left of the plotting + area in normalized coordinates where 0 (1) corresponds + to the left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + xshift + Shifts the position of the whole annotation and arrow + to the right (positive) or left (negative) by this many + pixels. + y + Sets the annotation's y position. If the axis `type` is + "log", then you must take the log of your desired + range. If the axis `type` is "date", it should be date + strings, like date data, though Date objects and unix + milliseconds will be accepted and converted to strings. + If the axis `type` is "category", it should be numbers, + using the scale where each category is assigned a + serial number from zero in the order it appears. + yanchor + Sets the text box's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the annotation. For example, if `y` is set + to 1, `yref` to "paper" and `yanchor` to "top" then the + top-most portion of the annotation lines up with the + top-most edge of the plotting area. If "auto", the + anchor is equivalent to "middle" for data-referenced + annotations or if there is an arrow, whereas for paper- + referenced with no arrow, the anchor picked corresponds + to the closest side. + yclick + Toggle this annotation when clicking a data point whose + `y` value is `yclick` rather than the annotation's `y` + value. + yref + Sets the annotation's y coordinate axis. If set to a y + axis id (e.g. "y" or "y2"), the `y` position refers to + a y coordinate. If set to "paper", the `y` position + refers to the distance from the bottom of the plotting + area in normalized coordinates where 0 (1) corresponds + to the bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + yshift + Shifts the position of the whole annotation and arrow + up (positive) or down (negative) by this many pixels. + """ + + def __init__( + self, + arg=None, + align=None, + arrowcolor=None, + arrowhead=None, + arrowside=None, + arrowsize=None, + arrowwidth=None, + ax=None, + axref=None, + ay=None, + ayref=None, + bgcolor=None, + bordercolor=None, + borderpad=None, + borderwidth=None, + captureevents=None, + clicktoshow=None, + font=None, + height=None, + hoverlabel=None, + hovertext=None, + name=None, + opacity=None, + showarrow=None, + standoff=None, + startarrowhead=None, + startarrowsize=None, + startstandoff=None, + templateitemname=None, + text=None, + textangle=None, + valign=None, + visible=None, + width=None, + x=None, + xanchor=None, + xclick=None, + xref=None, + xshift=None, + y=None, + yanchor=None, + yclick=None, + yref=None, + yshift=None, + **kwargs, + ): + """ + Construct a new Annotation object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.layout.Annotation` + align + Sets the horizontal alignment of the `text` within the + box. Has an effect only if `text` spans two or more + lines (i.e. `text` contains one or more
HTML tags) + or if an explicit width is set to override the text + width. + arrowcolor + Sets the color of the annotation arrow. + arrowhead + Sets the end annotation arrow head style. + arrowside + Sets the annotation arrow head position. + arrowsize + Sets the size of the end annotation arrow head, + relative to `arrowwidth`. A value of 1 (default) gives + a head about 3x as wide as the line. + arrowwidth + Sets the width (in px) of annotation arrow line. + ax + Sets the x component of the arrow tail about the arrow + head. If `axref` is `pixel`, a positive (negative) + component corresponds to an arrow pointing from right + to left (left to right). If `axref` is not `pixel` and + is exactly the same as `xref`, this is an absolute + value on that axis, like `x`, specified in the same + coordinates as `xref`. + axref + Indicates in what coordinates the tail of the + annotation (ax,ay) is specified. If set to a x axis id + (e.g. "x" or "x2"), the `x` position refers to a x + coordinate. If set to "paper", the `x` position refers + to the distance from the left of the plotting area in + normalized coordinates where 0 (1) corresponds to the + left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. In order for absolute + positioning of the arrow to work, "axref" must be + exactly the same as "xref", otherwise "axref" will + revert to "pixel" (explained next). For relative + positioning, "axref" can be set to "pixel", in which + case the "ax" value is specified in pixels relative to + "x". Absolute positioning is useful for trendline + annotations which should continue to indicate the + correct trend when zoomed. Relative positioning is + useful for specifying the text offset for an annotated + point. + ay + Sets the y component of the arrow tail about the arrow + head. If `ayref` is `pixel`, a positive (negative) + component corresponds to an arrow pointing from bottom + to top (top to bottom). If `ayref` is not `pixel` and + is exactly the same as `yref`, this is an absolute + value on that axis, like `y`, specified in the same + coordinates as `yref`. + ayref + Indicates in what coordinates the tail of the + annotation (ax,ay) is specified. If set to a y axis id + (e.g. "y" or "y2"), the `y` position refers to a y + coordinate. If set to "paper", the `y` position refers + to the distance from the bottom of the plotting area in + normalized coordinates where 0 (1) corresponds to the + bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. In order for absolute + positioning of the arrow to work, "ayref" must be + exactly the same as "yref", otherwise "ayref" will + revert to "pixel" (explained next). For relative + positioning, "ayref" can be set to "pixel", in which + case the "ay" value is specified in pixels relative to + "y". Absolute positioning is useful for trendline + annotations which should continue to indicate the + correct trend when zoomed. Relative positioning is + useful for specifying the text offset for an annotated + point. + bgcolor + Sets the background color of the annotation. + bordercolor + Sets the color of the border enclosing the annotation + `text`. + borderpad + Sets the padding (in px) between the `text` and the + enclosing border. + borderwidth + Sets the width (in px) of the border enclosing the + annotation `text`. + captureevents + Determines whether the annotation text box captures + mouse move and click events, or allows those events to + pass through to data points in the plot that may be + behind the annotation. By default `captureevents` is + False unless `hovertext` is provided. If you use the + event `plotly_clickannotation` without `hovertext` you + must explicitly enable `captureevents`. + clicktoshow + Makes this annotation respond to clicks on the plot. If + you click a data point that exactly matches the `x` and + `y` values of this annotation, and it is hidden + (visible: false), it will appear. In "onoff" mode, you + must click the same point again to make it disappear, + so if you click multiple points, you can show multiple + annotations. In "onout" mode, a click anywhere else in + the plot (on another data point or not) will hide this + annotation. If you need to show/hide this annotation in + response to different `x` or `y` values, you can set + `xclick` and/or `yclick`. This is useful for example to + label the side of a bar. To label markers though, + `standoff` is preferred over `xclick` and `yclick`. + font + Sets the annotation text font. + height + Sets an explicit height for the text box. null + (default) lets the text set the box height. Taller text + will be clipped. + hoverlabel + :class:`plotly.graph_objects.layout.annotation.Hoverlab + el` instance or dict with compatible properties + hovertext + Sets text to appear when hovering over this annotation. + If omitted or blank, no hover label will appear. + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the annotation (text + arrow). + showarrow + Determines whether or not the annotation is drawn with + an arrow. If True, `text` is placed near the arrow's + tail. If False, `text` lines up with the `x` and `y` + provided. + standoff + Sets a distance, in pixels, to move the end arrowhead + away from the position it is pointing at, for example + to point at the edge of a marker independent of zoom. + Note that this shortens the arrow from the `ax` / `ay` + vector, in contrast to `xshift` / `yshift` which moves + everything by this amount. + startarrowhead + Sets the start annotation arrow head style. + startarrowsize + Sets the size of the start annotation arrow head, + relative to `arrowwidth`. A value of 1 (default) gives + a head about 3x as wide as the line. + startstandoff + Sets a distance, in pixels, to move the start arrowhead + away from the position it is pointing at, for example + to point at the edge of a marker independent of zoom. + Note that this shortens the arrow from the `ax` / `ay` + vector, in contrast to `xshift` / `yshift` which moves + everything by this amount. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + text + Sets the text associated with this annotation. Plotly + uses a subset of HTML tags to do things like newline + (`
`), bold (``), italics (``), + hyperlinks (``). Tags ``, + ``, ``, ``, ``, and `` are also + supported. + textangle + Sets the angle at which the `text` is drawn with + respect to the horizontal. + valign + Sets the vertical alignment of the `text` within the + box. Has an effect only if an explicit height is set to + override the text height. + visible + Determines whether or not this annotation is visible. + width + Sets an explicit width for the text box. null (default) + lets the text set the box width. Wider text will be + clipped. There is no automatic wrapping; use
to + start a new line. + x + Sets the annotation's x position. If the axis `type` is + "log", then you must take the log of your desired + range. If the axis `type` is "date", it should be date + strings, like date data, though Date objects and unix + milliseconds will be accepted and converted to strings. + If the axis `type` is "category", it should be numbers, + using the scale where each category is assigned a + serial number from zero in the order it appears. + xanchor + Sets the text box's horizontal position anchor This + anchor binds the `x` position to the "left", "center" + or "right" of the annotation. For example, if `x` is + set to 1, `xref` to "paper" and `xanchor` to "right" + then the right-most portion of the annotation lines up + with the right-most edge of the plotting area. If + "auto", the anchor is equivalent to "center" for data- + referenced annotations or if there is an arrow, whereas + for paper-referenced with no arrow, the anchor picked + corresponds to the closest side. + xclick + Toggle this annotation when clicking a data point whose + `x` value is `xclick` rather than the annotation's `x` + value. + xref + Sets the annotation's x coordinate axis. If set to a x + axis id (e.g. "x" or "x2"), the `x` position refers to + a x coordinate. If set to "paper", the `x` position + refers to the distance from the left of the plotting + area in normalized coordinates where 0 (1) corresponds + to the left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + xshift + Shifts the position of the whole annotation and arrow + to the right (positive) or left (negative) by this many + pixels. + y + Sets the annotation's y position. If the axis `type` is + "log", then you must take the log of your desired + range. If the axis `type` is "date", it should be date + strings, like date data, though Date objects and unix + milliseconds will be accepted and converted to strings. + If the axis `type` is "category", it should be numbers, + using the scale where each category is assigned a + serial number from zero in the order it appears. + yanchor + Sets the text box's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the annotation. For example, if `y` is set + to 1, `yref` to "paper" and `yanchor` to "top" then the + top-most portion of the annotation lines up with the + top-most edge of the plotting area. If "auto", the + anchor is equivalent to "middle" for data-referenced + annotations or if there is an arrow, whereas for paper- + referenced with no arrow, the anchor picked corresponds + to the closest side. + yclick + Toggle this annotation when clicking a data point whose + `y` value is `yclick` rather than the annotation's `y` + value. + yref + Sets the annotation's y coordinate axis. If set to a y + axis id (e.g. "y" or "y2"), the `y` position refers to + a y coordinate. If set to "paper", the `y` position + refers to the distance from the bottom of the plotting + area in normalized coordinates where 0 (1) corresponds + to the bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + yshift + Shifts the position of the whole annotation and arrow + up (positive) or down (negative) by this many pixels. + + Returns + ------- + Annotation + """ + super().__init__("annotations") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Annotation +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Annotation`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("arrowcolor", arg, arrowcolor) + self._set_property("arrowhead", arg, arrowhead) + self._set_property("arrowside", arg, arrowside) + self._set_property("arrowsize", arg, arrowsize) + self._set_property("arrowwidth", arg, arrowwidth) + self._set_property("ax", arg, ax) + self._set_property("axref", arg, axref) + self._set_property("ay", arg, ay) + self._set_property("ayref", arg, ayref) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("borderpad", arg, borderpad) + self._set_property("borderwidth", arg, borderwidth) + self._set_property("captureevents", arg, captureevents) + self._set_property("clicktoshow", arg, clicktoshow) + self._set_property("font", arg, font) + self._set_property("height", arg, height) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertext", arg, hovertext) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("showarrow", arg, showarrow) + self._set_property("standoff", arg, standoff) + self._set_property("startarrowhead", arg, startarrowhead) + self._set_property("startarrowsize", arg, startarrowsize) + self._set_property("startstandoff", arg, startstandoff) + self._set_property("templateitemname", arg, templateitemname) + self._set_property("text", arg, text) + self._set_property("textangle", arg, textangle) + self._set_property("valign", arg, valign) + self._set_property("visible", arg, visible) + self._set_property("width", arg, width) + self._set_property("x", arg, x) + self._set_property("xanchor", arg, xanchor) + self._set_property("xclick", arg, xclick) + self._set_property("xref", arg, xref) + self._set_property("xshift", arg, xshift) + self._set_property("y", arg, y) + self._set_property("yanchor", arg, yanchor) + self._set_property("yclick", arg, yclick) + self._set_property("yref", arg, yref) + self._set_property("yshift", arg, yshift) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_coloraxis.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_coloraxis.py new file mode 100644 index 0000000000000000000000000000000000000000..0b4ec2edad61e5c7b6071eaa8e05bfcaf0e6c563 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_coloraxis.py @@ -0,0 +1,396 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Coloraxis(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.coloraxis" + _valid_props = { + "autocolorscale", + "cauto", + "cmax", + "cmid", + "cmin", + "colorbar", + "colorscale", + "reversescale", + "showscale", + } + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def cauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here corresponding trace color + array(s)) or the bounds set in `cmin` and `cmax` Defaults to + `false` when `cmin` and `cmax` are set by the user. + + The 'cauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cauto"] + + @cauto.setter + def cauto(self, val): + self["cauto"] = val + + @property + def cmax(self): + """ + Sets the upper bound of the color domain. Value should have the + same units as corresponding trace color array(s) and if set, + `cmin` must be set as well. + + The 'cmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmax"] + + @cmax.setter + def cmax(self, val): + self["cmax"] = val + + @property + def cmid(self): + """ + Sets the mid-point of the color domain by scaling `cmin` and/or + `cmax` to be equidistant to this point. Value should have the + same units as corresponding trace color array(s). Has no effect + when `cauto` is `false`. + + The 'cmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmid"] + + @cmid.setter + def cmid(self, val): + self["cmid"] = val + + @property + def cmin(self): + """ + Sets the lower bound of the color domain. Value should have the + same units as corresponding trace color array(s) and if set, + `cmax` must be set as well. + + The 'cmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmin"] + + @cmin.setter + def cmin(self, val): + self["cmin"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.coloraxis.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.layout.coloraxis.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. The colorscale must be an array containing + arrays mapping a normalized value to an rgb, rgba, hex, hsl, + hsv, or named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For example, + `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To control the + bounds of the colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,Electric, + Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,RdBu,Reds,Viridis, + YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. If true, `cmin` will + correspond to the last color in the array and `cmax` will + correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def _prop_descriptions(self): + return """\ + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here corresponding + trace color array(s)) or the bounds set in `cmin` and + `cmax` Defaults to `false` when `cmin` and `cmax` are + set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as corresponding trace color + array(s) and if set, `cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as corresponding trace + color array(s). Has no effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as corresponding trace color + array(s) and if set, `cmax` must be set as well. + colorbar + :class:`plotly.graph_objects.layout.coloraxis.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + showscale + Determines whether or not a colorbar is displayed for + this trace. + """ + + def __init__( + self, + arg=None, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + colorbar=None, + colorscale=None, + reversescale=None, + showscale=None, + **kwargs, + ): + """ + Construct a new Coloraxis object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.layout.Coloraxis` + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `colorscale`. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be + chosen according to whether numbers in the `color` + array are all positive, all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here corresponding + trace color array(s)) or the bounds set in `cmin` and + `cmax` Defaults to `false` when `cmin` and `cmax` are + set by the user. + cmax + Sets the upper bound of the color domain. Value should + have the same units as corresponding trace color + array(s) and if set, `cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `cmin` and/or `cmax` to be equidistant to this point. + Value should have the same units as corresponding trace + color array(s). Has no effect when `cauto` is `false`. + cmin + Sets the lower bound of the color domain. Value should + have the same units as corresponding trace color + array(s) and if set, `cmax` must be set as well. + colorbar + :class:`plotly.graph_objects.layout.coloraxis.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, + rgba, hex, hsl, hsv, or named color string. At minimum, + a mapping for the lowest (0) and highest (1) values are + required. For example, `[[0, 'rgb(0,0,255)'], [1, + 'rgb(255,0,0)']]`. To control the bounds of the + colorscale in color space, use `cmin` and `cmax`. + Alternatively, `colorscale` may be a palette name + string of the following list: Blackbody,Bluered,Blues,C + ividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portl + and,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + reversescale + Reverses the color mapping if true. If true, `cmin` + will correspond to the last color in the array and + `cmax` will correspond to the first color. + showscale + Determines whether or not a colorbar is displayed for + this trace. + + Returns + ------- + Coloraxis + """ + super().__init__("coloraxis") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Coloraxis +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Coloraxis`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("cauto", arg, cauto) + self._set_property("cmax", arg, cmax) + self._set_property("cmid", arg, cmid) + self._set_property("cmin", arg, cmin) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("reversescale", arg, reversescale) + self._set_property("showscale", arg, showscale) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_colorscale.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_colorscale.py new file mode 100644 index 0000000000000000000000000000000000000000..b65ed87fe79b264f7530b2eeeed55a05e5a3d31e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_colorscale.py @@ -0,0 +1,214 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Colorscale(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.colorscale" + _valid_props = {"diverging", "sequential", "sequentialminus"} + + @property + def diverging(self): + """ + Sets the default diverging colorscale. Note that + `autocolorscale` must be true for this attribute to work. + + The 'diverging' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["diverging"] + + @diverging.setter + def diverging(self, val): + self["diverging"] = val + + @property + def sequential(self): + """ + Sets the default sequential colorscale for positive values. + Note that `autocolorscale` must be true for this attribute to + work. + + The 'sequential' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["sequential"] + + @sequential.setter + def sequential(self, val): + self["sequential"] = val + + @property + def sequentialminus(self): + """ + Sets the default sequential colorscale for negative values. + Note that `autocolorscale` must be true for this attribute to + work. + + The 'sequentialminus' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["sequentialminus"] + + @sequentialminus.setter + def sequentialminus(self, val): + self["sequentialminus"] = val + + @property + def _prop_descriptions(self): + return """\ + diverging + Sets the default diverging colorscale. Note that + `autocolorscale` must be true for this attribute to + work. + sequential + Sets the default sequential colorscale for positive + values. Note that `autocolorscale` must be true for + this attribute to work. + sequentialminus + Sets the default sequential colorscale for negative + values. Note that `autocolorscale` must be true for + this attribute to work. + """ + + def __init__( + self, arg=None, diverging=None, sequential=None, sequentialminus=None, **kwargs + ): + """ + Construct a new Colorscale object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.layout.Colorscale` + diverging + Sets the default diverging colorscale. Note that + `autocolorscale` must be true for this attribute to + work. + sequential + Sets the default sequential colorscale for positive + values. Note that `autocolorscale` must be true for + this attribute to work. + sequentialminus + Sets the default sequential colorscale for negative + values. Note that `autocolorscale` must be true for + this attribute to work. + + Returns + ------- + Colorscale + """ + super().__init__("colorscale") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Colorscale +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Colorscale`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("diverging", arg, diverging) + self._set_property("sequential", arg, sequential) + self._set_property("sequentialminus", arg, sequentialminus) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_font.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_font.py new file mode 100644 index 0000000000000000000000000000000000000000..c691e7018c785e1c70a21cd021ba57b3bb205a20 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_font.py @@ -0,0 +1,334 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Font(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.font" + _valid_props = { + "color", + "family", + "lineposition", + "shadow", + "size", + "style", + "textcase", + "variant", + "weight", + } + + @property + def color(self): + """ + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def family(self): + """ + HTML font family - the typeface that will be applied by the web + browser. The web browser can only apply a font if it is + available on the system where it runs. Provide multiple font + families, separated by commas, to indicate the order in which + to apply fonts if they aren't available. + + The 'family' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["family"] + + @family.setter + def family(self, val): + self["family"] = val + + @property + def lineposition(self): + """ + Sets the kind of decoration line(s) with text, such as an + "under", "over" or "through" as well as combinations e.g. + "under+over", etc. + + The 'lineposition' property is a flaglist and may be specified + as a string containing: + - Any combination of ['under', 'over', 'through'] joined with '+' characters + (e.g. 'under+over') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["lineposition"] + + @lineposition.setter + def lineposition(self, val): + self["lineposition"] = val + + @property + def shadow(self): + """ + Sets the shape and color of the shadow behind text. "auto" + places minimal shadow and applies contrast text font color. See + https://developer.mozilla.org/en-US/docs/Web/CSS/text-shadow + for additional options. + + The 'shadow' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["shadow"] + + @shadow.setter + def shadow(self, val): + self["shadow"] = val + + @property + def size(self): + """ + The 'size' property is a number and may be specified as: + - An int or float in the interval [1, inf] + + Returns + ------- + int|float + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def style(self): + """ + Sets whether a font should be styled with a normal or italic + face from its family. + + The 'style' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'italic'] + + Returns + ------- + Any + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def textcase(self): + """ + Sets capitalization of text. It can be used to make text appear + in all-uppercase or all-lowercase, or with each word + capitalized. + + The 'textcase' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'word caps', 'upper', 'lower'] + + Returns + ------- + Any + """ + return self["textcase"] + + @textcase.setter + def textcase(self, val): + self["textcase"] = val + + @property + def variant(self): + """ + Sets the variant of the font. + + The 'variant' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'small-caps', 'all-small-caps', + 'all-petite-caps', 'petite-caps', 'unicase'] + + Returns + ------- + Any + """ + return self["variant"] + + @variant.setter + def variant(self, val): + self["variant"] = val + + @property + def weight(self): + """ + Sets the weight (or boldness) of the font. + + The 'weight' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 1000] + OR exactly one of ['normal', 'bold'] (e.g. 'bold') + + Returns + ------- + int + """ + return self["weight"] + + @weight.setter + def weight(self, val): + self["weight"] = val + + @property + def _prop_descriptions(self): + return """\ + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + """ + + def __init__( + self, + arg=None, + color=None, + family=None, + lineposition=None, + shadow=None, + size=None, + style=None, + textcase=None, + variant=None, + weight=None, + **kwargs, + ): + """ + Construct a new Font object + + Sets the global font. Note that fonts used in traces and other + layout components inherit from the global font. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.Font` + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + + Returns + ------- + Font + """ + super().__init__("font") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Font +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Font`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("family", arg, family) + self._set_property("lineposition", arg, lineposition) + self._set_property("shadow", arg, shadow) + self._set_property("size", arg, size) + self._set_property("style", arg, style) + self._set_property("textcase", arg, textcase) + self._set_property("variant", arg, variant) + self._set_property("weight", arg, weight) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_geo.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_geo.py new file mode 100644 index 0000000000000000000000000000000000000000..bee07ae65126c9e40946599afad8305de8a483bd --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_geo.py @@ -0,0 +1,968 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Geo(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.geo" + _valid_props = { + "bgcolor", + "center", + "coastlinecolor", + "coastlinewidth", + "countrycolor", + "countrywidth", + "domain", + "fitbounds", + "framecolor", + "framewidth", + "lakecolor", + "landcolor", + "lataxis", + "lonaxis", + "oceancolor", + "projection", + "resolution", + "rivercolor", + "riverwidth", + "scope", + "showcoastlines", + "showcountries", + "showframe", + "showlakes", + "showland", + "showocean", + "showrivers", + "showsubunits", + "subunitcolor", + "subunitwidth", + "uirevision", + "visible", + } + + @property + def bgcolor(self): + """ + Set the background color of the map + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def center(self): + """ + The 'center' property is an instance of Center + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.geo.Center` + - A dict of string/value properties that will be passed + to the Center constructor + + Returns + ------- + plotly.graph_objs.layout.geo.Center + """ + return self["center"] + + @center.setter + def center(self, val): + self["center"] = val + + @property + def coastlinecolor(self): + """ + Sets the coastline color. + + The 'coastlinecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["coastlinecolor"] + + @coastlinecolor.setter + def coastlinecolor(self, val): + self["coastlinecolor"] = val + + @property + def coastlinewidth(self): + """ + Sets the coastline stroke width (in px). + + The 'coastlinewidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["coastlinewidth"] + + @coastlinewidth.setter + def coastlinewidth(self, val): + self["coastlinewidth"] = val + + @property + def countrycolor(self): + """ + Sets line color of the country boundaries. + + The 'countrycolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["countrycolor"] + + @countrycolor.setter + def countrycolor(self, val): + self["countrycolor"] = val + + @property + def countrywidth(self): + """ + Sets line width (in px) of the country boundaries. + + The 'countrywidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["countrywidth"] + + @countrywidth.setter + def countrywidth(self, val): + self["countrywidth"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.geo.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.layout.geo.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def fitbounds(self): + """ + Determines if this subplot's view settings are auto-computed to + fit trace data. On scoped maps, setting `fitbounds` leads to + `center.lon` and `center.lat` getting auto-filled. On maps with + a non-clipped projection, setting `fitbounds` leads to + `center.lon`, `center.lat`, and `projection.rotation.lon` + getting auto-filled. On maps with a clipped projection, setting + `fitbounds` leads to `center.lon`, `center.lat`, + `projection.rotation.lon`, `projection.rotation.lat`, + `lonaxis.range` and `lataxis.range` getting auto-filled. If + "locations", only the trace's visible locations are considered + in the `fitbounds` computations. If "geojson", the entire trace + input `geojson` (if provided) is considered in the `fitbounds` + computations, Defaults to False. + + The 'fitbounds' property is an enumeration that may be specified as: + - One of the following enumeration values: + [False, 'locations', 'geojson'] + + Returns + ------- + Any + """ + return self["fitbounds"] + + @fitbounds.setter + def fitbounds(self, val): + self["fitbounds"] = val + + @property + def framecolor(self): + """ + Sets the color the frame. + + The 'framecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["framecolor"] + + @framecolor.setter + def framecolor(self, val): + self["framecolor"] = val + + @property + def framewidth(self): + """ + Sets the stroke width (in px) of the frame. + + The 'framewidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["framewidth"] + + @framewidth.setter + def framewidth(self, val): + self["framewidth"] = val + + @property + def lakecolor(self): + """ + Sets the color of the lakes. + + The 'lakecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["lakecolor"] + + @lakecolor.setter + def lakecolor(self, val): + self["lakecolor"] = val + + @property + def landcolor(self): + """ + Sets the land mass color. + + The 'landcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["landcolor"] + + @landcolor.setter + def landcolor(self, val): + self["landcolor"] = val + + @property + def lataxis(self): + """ + The 'lataxis' property is an instance of Lataxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.geo.Lataxis` + - A dict of string/value properties that will be passed + to the Lataxis constructor + + Returns + ------- + plotly.graph_objs.layout.geo.Lataxis + """ + return self["lataxis"] + + @lataxis.setter + def lataxis(self, val): + self["lataxis"] = val + + @property + def lonaxis(self): + """ + The 'lonaxis' property is an instance of Lonaxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.geo.Lonaxis` + - A dict of string/value properties that will be passed + to the Lonaxis constructor + + Returns + ------- + plotly.graph_objs.layout.geo.Lonaxis + """ + return self["lonaxis"] + + @lonaxis.setter + def lonaxis(self, val): + self["lonaxis"] = val + + @property + def oceancolor(self): + """ + Sets the ocean color + + The 'oceancolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["oceancolor"] + + @oceancolor.setter + def oceancolor(self, val): + self["oceancolor"] = val + + @property + def projection(self): + """ + The 'projection' property is an instance of Projection + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.geo.Projection` + - A dict of string/value properties that will be passed + to the Projection constructor + + Returns + ------- + plotly.graph_objs.layout.geo.Projection + """ + return self["projection"] + + @projection.setter + def projection(self, val): + self["projection"] = val + + @property + def resolution(self): + """ + Sets the resolution of the base layers. The values have units + of km/mm e.g. 110 corresponds to a scale ratio of + 1:110,000,000. + + The 'resolution' property is an enumeration that may be specified as: + - One of the following enumeration values: + [110, 50] + + Returns + ------- + Any + """ + return self["resolution"] + + @resolution.setter + def resolution(self, val): + self["resolution"] = val + + @property + def rivercolor(self): + """ + Sets color of the rivers. + + The 'rivercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["rivercolor"] + + @rivercolor.setter + def rivercolor(self, val): + self["rivercolor"] = val + + @property + def riverwidth(self): + """ + Sets the stroke width (in px) of the rivers. + + The 'riverwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["riverwidth"] + + @riverwidth.setter + def riverwidth(self, val): + self["riverwidth"] = val + + @property + def scope(self): + """ + Set the scope of the map. + + The 'scope' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['africa', 'antarctica', 'asia', 'europe', 'north + america', 'oceania', 'south america', 'usa', 'world'] + + Returns + ------- + Any + """ + return self["scope"] + + @scope.setter + def scope(self, val): + self["scope"] = val + + @property + def showcoastlines(self): + """ + Sets whether or not the coastlines are drawn. + + The 'showcoastlines' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showcoastlines"] + + @showcoastlines.setter + def showcoastlines(self, val): + self["showcoastlines"] = val + + @property + def showcountries(self): + """ + Sets whether or not country boundaries are drawn. + + The 'showcountries' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showcountries"] + + @showcountries.setter + def showcountries(self, val): + self["showcountries"] = val + + @property + def showframe(self): + """ + Sets whether or not a frame is drawn around the map. + + The 'showframe' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showframe"] + + @showframe.setter + def showframe(self, val): + self["showframe"] = val + + @property + def showlakes(self): + """ + Sets whether or not lakes are drawn. + + The 'showlakes' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlakes"] + + @showlakes.setter + def showlakes(self, val): + self["showlakes"] = val + + @property + def showland(self): + """ + Sets whether or not land masses are filled in color. + + The 'showland' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showland"] + + @showland.setter + def showland(self, val): + self["showland"] = val + + @property + def showocean(self): + """ + Sets whether or not oceans are filled in color. + + The 'showocean' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showocean"] + + @showocean.setter + def showocean(self, val): + self["showocean"] = val + + @property + def showrivers(self): + """ + Sets whether or not rivers are drawn. + + The 'showrivers' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showrivers"] + + @showrivers.setter + def showrivers(self, val): + self["showrivers"] = val + + @property + def showsubunits(self): + """ + Sets whether or not boundaries of subunits within countries + (e.g. states, provinces) are drawn. + + The 'showsubunits' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showsubunits"] + + @showsubunits.setter + def showsubunits(self, val): + self["showsubunits"] = val + + @property + def subunitcolor(self): + """ + Sets the color of the subunits boundaries. + + The 'subunitcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["subunitcolor"] + + @subunitcolor.setter + def subunitcolor(self, val): + self["subunitcolor"] = val + + @property + def subunitwidth(self): + """ + Sets the stroke width (in px) of the subunits boundaries. + + The 'subunitwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["subunitwidth"] + + @subunitwidth.setter + def subunitwidth(self, val): + self["subunitwidth"] = val + + @property + def uirevision(self): + """ + Controls persistence of user-driven changes in the view + (projection and center). Defaults to `layout.uirevision`. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def visible(self): + """ + Sets the default visibility of the base layers. + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def _prop_descriptions(self): + return """\ + bgcolor + Set the background color of the map + center + :class:`plotly.graph_objects.layout.geo.Center` + instance or dict with compatible properties + coastlinecolor + Sets the coastline color. + coastlinewidth + Sets the coastline stroke width (in px). + countrycolor + Sets line color of the country boundaries. + countrywidth + Sets line width (in px) of the country boundaries. + domain + :class:`plotly.graph_objects.layout.geo.Domain` + instance or dict with compatible properties + fitbounds + Determines if this subplot's view settings are auto- + computed to fit trace data. On scoped maps, setting + `fitbounds` leads to `center.lon` and `center.lat` + getting auto-filled. On maps with a non-clipped + projection, setting `fitbounds` leads to `center.lon`, + `center.lat`, and `projection.rotation.lon` getting + auto-filled. On maps with a clipped projection, setting + `fitbounds` leads to `center.lon`, `center.lat`, + `projection.rotation.lon`, `projection.rotation.lat`, + `lonaxis.range` and `lataxis.range` getting auto- + filled. If "locations", only the trace's visible + locations are considered in the `fitbounds` + computations. If "geojson", the entire trace input + `geojson` (if provided) is considered in the + `fitbounds` computations, Defaults to False. + framecolor + Sets the color the frame. + framewidth + Sets the stroke width (in px) of the frame. + lakecolor + Sets the color of the lakes. + landcolor + Sets the land mass color. + lataxis + :class:`plotly.graph_objects.layout.geo.Lataxis` + instance or dict with compatible properties + lonaxis + :class:`plotly.graph_objects.layout.geo.Lonaxis` + instance or dict with compatible properties + oceancolor + Sets the ocean color + projection + :class:`plotly.graph_objects.layout.geo.Projection` + instance or dict with compatible properties + resolution + Sets the resolution of the base layers. The values have + units of km/mm e.g. 110 corresponds to a scale ratio of + 1:110,000,000. + rivercolor + Sets color of the rivers. + riverwidth + Sets the stroke width (in px) of the rivers. + scope + Set the scope of the map. + showcoastlines + Sets whether or not the coastlines are drawn. + showcountries + Sets whether or not country boundaries are drawn. + showframe + Sets whether or not a frame is drawn around the map. + showlakes + Sets whether or not lakes are drawn. + showland + Sets whether or not land masses are filled in color. + showocean + Sets whether or not oceans are filled in color. + showrivers + Sets whether or not rivers are drawn. + showsubunits + Sets whether or not boundaries of subunits within + countries (e.g. states, provinces) are drawn. + subunitcolor + Sets the color of the subunits boundaries. + subunitwidth + Sets the stroke width (in px) of the subunits + boundaries. + uirevision + Controls persistence of user-driven changes in the view + (projection and center). Defaults to + `layout.uirevision`. + visible + Sets the default visibility of the base layers. + """ + + def __init__( + self, + arg=None, + bgcolor=None, + center=None, + coastlinecolor=None, + coastlinewidth=None, + countrycolor=None, + countrywidth=None, + domain=None, + fitbounds=None, + framecolor=None, + framewidth=None, + lakecolor=None, + landcolor=None, + lataxis=None, + lonaxis=None, + oceancolor=None, + projection=None, + resolution=None, + rivercolor=None, + riverwidth=None, + scope=None, + showcoastlines=None, + showcountries=None, + showframe=None, + showlakes=None, + showland=None, + showocean=None, + showrivers=None, + showsubunits=None, + subunitcolor=None, + subunitwidth=None, + uirevision=None, + visible=None, + **kwargs, + ): + """ + Construct a new Geo object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.Geo` + bgcolor + Set the background color of the map + center + :class:`plotly.graph_objects.layout.geo.Center` + instance or dict with compatible properties + coastlinecolor + Sets the coastline color. + coastlinewidth + Sets the coastline stroke width (in px). + countrycolor + Sets line color of the country boundaries. + countrywidth + Sets line width (in px) of the country boundaries. + domain + :class:`plotly.graph_objects.layout.geo.Domain` + instance or dict with compatible properties + fitbounds + Determines if this subplot's view settings are auto- + computed to fit trace data. On scoped maps, setting + `fitbounds` leads to `center.lon` and `center.lat` + getting auto-filled. On maps with a non-clipped + projection, setting `fitbounds` leads to `center.lon`, + `center.lat`, and `projection.rotation.lon` getting + auto-filled. On maps with a clipped projection, setting + `fitbounds` leads to `center.lon`, `center.lat`, + `projection.rotation.lon`, `projection.rotation.lat`, + `lonaxis.range` and `lataxis.range` getting auto- + filled. If "locations", only the trace's visible + locations are considered in the `fitbounds` + computations. If "geojson", the entire trace input + `geojson` (if provided) is considered in the + `fitbounds` computations, Defaults to False. + framecolor + Sets the color the frame. + framewidth + Sets the stroke width (in px) of the frame. + lakecolor + Sets the color of the lakes. + landcolor + Sets the land mass color. + lataxis + :class:`plotly.graph_objects.layout.geo.Lataxis` + instance or dict with compatible properties + lonaxis + :class:`plotly.graph_objects.layout.geo.Lonaxis` + instance or dict with compatible properties + oceancolor + Sets the ocean color + projection + :class:`plotly.graph_objects.layout.geo.Projection` + instance or dict with compatible properties + resolution + Sets the resolution of the base layers. The values have + units of km/mm e.g. 110 corresponds to a scale ratio of + 1:110,000,000. + rivercolor + Sets color of the rivers. + riverwidth + Sets the stroke width (in px) of the rivers. + scope + Set the scope of the map. + showcoastlines + Sets whether or not the coastlines are drawn. + showcountries + Sets whether or not country boundaries are drawn. + showframe + Sets whether or not a frame is drawn around the map. + showlakes + Sets whether or not lakes are drawn. + showland + Sets whether or not land masses are filled in color. + showocean + Sets whether or not oceans are filled in color. + showrivers + Sets whether or not rivers are drawn. + showsubunits + Sets whether or not boundaries of subunits within + countries (e.g. states, provinces) are drawn. + subunitcolor + Sets the color of the subunits boundaries. + subunitwidth + Sets the stroke width (in px) of the subunits + boundaries. + uirevision + Controls persistence of user-driven changes in the view + (projection and center). Defaults to + `layout.uirevision`. + visible + Sets the default visibility of the base layers. + + Returns + ------- + Geo + """ + super().__init__("geo") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Geo +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Geo`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("bgcolor", arg, bgcolor) + self._set_property("center", arg, center) + self._set_property("coastlinecolor", arg, coastlinecolor) + self._set_property("coastlinewidth", arg, coastlinewidth) + self._set_property("countrycolor", arg, countrycolor) + self._set_property("countrywidth", arg, countrywidth) + self._set_property("domain", arg, domain) + self._set_property("fitbounds", arg, fitbounds) + self._set_property("framecolor", arg, framecolor) + self._set_property("framewidth", arg, framewidth) + self._set_property("lakecolor", arg, lakecolor) + self._set_property("landcolor", arg, landcolor) + self._set_property("lataxis", arg, lataxis) + self._set_property("lonaxis", arg, lonaxis) + self._set_property("oceancolor", arg, oceancolor) + self._set_property("projection", arg, projection) + self._set_property("resolution", arg, resolution) + self._set_property("rivercolor", arg, rivercolor) + self._set_property("riverwidth", arg, riverwidth) + self._set_property("scope", arg, scope) + self._set_property("showcoastlines", arg, showcoastlines) + self._set_property("showcountries", arg, showcountries) + self._set_property("showframe", arg, showframe) + self._set_property("showlakes", arg, showlakes) + self._set_property("showland", arg, showland) + self._set_property("showocean", arg, showocean) + self._set_property("showrivers", arg, showrivers) + self._set_property("showsubunits", arg, showsubunits) + self._set_property("subunitcolor", arg, subunitcolor) + self._set_property("subunitwidth", arg, subunitwidth) + self._set_property("uirevision", arg, uirevision) + self._set_property("visible", arg, visible) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_grid.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_grid.py new file mode 100644 index 0000000000000000000000000000000000000000..8788027b3a4c6a9c4c0aa50b9fc515b04cf44a0b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_grid.py @@ -0,0 +1,511 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Grid(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.grid" + _valid_props = { + "columns", + "domain", + "pattern", + "roworder", + "rows", + "subplots", + "xaxes", + "xgap", + "xside", + "yaxes", + "ygap", + "yside", + } + + @property + def columns(self): + """ + The number of columns in the grid. If you provide a 2D + `subplots` array, the length of its longest row is used as the + default. If you give an `xaxes` array, its length is used as + the default. But it's also possible to have a different length, + if you want to leave a row at the end for non-cartesian + subplots. + + The 'columns' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 9223372036854775807] + + Returns + ------- + int + """ + return self["columns"] + + @columns.setter + def columns(self, val): + self["columns"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.grid.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.layout.grid.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def pattern(self): + """ + If no `subplots`, `xaxes`, or `yaxes` are given but we do have + `rows` and `columns`, we can generate defaults using + consecutive axis IDs, in two ways: "coupled" gives one x axis + per column and one y axis per row. "independent" uses a new xy + pair for each cell, left-to-right across each row then + iterating rows according to `roworder`. + + The 'pattern' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['independent', 'coupled'] + + Returns + ------- + Any + """ + return self["pattern"] + + @pattern.setter + def pattern(self, val): + self["pattern"] = val + + @property + def roworder(self): + """ + Is the first row the top or the bottom? Note that columns are + always enumerated from left to right. + + The 'roworder' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top to bottom', 'bottom to top'] + + Returns + ------- + Any + """ + return self["roworder"] + + @roworder.setter + def roworder(self, val): + self["roworder"] = val + + @property + def rows(self): + """ + The number of rows in the grid. If you provide a 2D `subplots` + array or a `yaxes` array, its length is used as the default. + But it's also possible to have a different length, if you want + to leave a row at the end for non-cartesian subplots. + + The 'rows' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 9223372036854775807] + + Returns + ------- + int + """ + return self["rows"] + + @rows.setter + def rows(self, val): + self["rows"] = val + + @property + def subplots(self): + """ + Used for freeform grids, where some axes may be shared across + subplots but others are not. Each entry should be a cartesian + subplot id, like "xy" or "x3y2", or "" to leave that cell + empty. You may reuse x axes within the same column, and y axes + within the same row. Non-cartesian subplots and traces that + support `domain` can place themselves in this grid separately + using the `gridcell` attribute. + + The 'subplots' property is an info array that may be specified as: + * a 2D list where: + The 'subplots[i][j]' property is an enumeration that may be specified as: + - One of the following enumeration values: + [''] + - A string that matches one of the following regular expressions: + ['^x([2-9]|[1-9][0-9]+)?y([2-9]|[1-9][0-9]+)?$'] + + Returns + ------- + list + """ + return self["subplots"] + + @subplots.setter + def subplots(self, val): + self["subplots"] = val + + @property + def xaxes(self): + """ + Used with `yaxes` when the x and y axes are shared across + columns and rows. Each entry should be an x axis id like "x", + "x2", etc., or "" to not put an x axis in that column. Entries + other than "" must be unique. Ignored if `subplots` is present. + If missing but `yaxes` is present, will generate consecutive + IDs. + + The 'xaxes' property is an info array that may be specified as: + * a list of elements where: + The 'xaxes[i]' property is an enumeration that may be specified as: + - One of the following enumeration values: + [''] + - A string that matches one of the following regular expressions: + ['^x([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + list + """ + return self["xaxes"] + + @xaxes.setter + def xaxes(self, val): + self["xaxes"] = val + + @property + def xgap(self): + """ + Horizontal space between grid cells, expressed as a fraction of + the total width available to one cell. Defaults to 0.1 for + coupled-axes grids and 0.2 for independent grids. + + The 'xgap' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["xgap"] + + @xgap.setter + def xgap(self, val): + self["xgap"] = val + + @property + def xside(self): + """ + Sets where the x axis labels and titles go. "bottom" means the + very bottom of the grid. "bottom plot" is the lowest plot that + each x axis is used in. "top" and "top plot" are similar. + + The 'xside' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['bottom', 'bottom plot', 'top plot', 'top'] + + Returns + ------- + Any + """ + return self["xside"] + + @xside.setter + def xside(self, val): + self["xside"] = val + + @property + def yaxes(self): + """ + Used with `yaxes` when the x and y axes are shared across + columns and rows. Each entry should be an y axis id like "y", + "y2", etc., or "" to not put a y axis in that row. Entries + other than "" must be unique. Ignored if `subplots` is present. + If missing but `xaxes` is present, will generate consecutive + IDs. + + The 'yaxes' property is an info array that may be specified as: + * a list of elements where: + The 'yaxes[i]' property is an enumeration that may be specified as: + - One of the following enumeration values: + [''] + - A string that matches one of the following regular expressions: + ['^y([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + list + """ + return self["yaxes"] + + @yaxes.setter + def yaxes(self, val): + self["yaxes"] = val + + @property + def ygap(self): + """ + Vertical space between grid cells, expressed as a fraction of + the total height available to one cell. Defaults to 0.1 for + coupled-axes grids and 0.3 for independent grids. + + The 'ygap' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["ygap"] + + @ygap.setter + def ygap(self, val): + self["ygap"] = val + + @property + def yside(self): + """ + Sets where the y axis labels and titles go. "left" means the + very left edge of the grid. *left plot* is the leftmost plot + that each y axis is used in. "right" and *right plot* are + similar. + + The 'yside' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'left plot', 'right plot', 'right'] + + Returns + ------- + Any + """ + return self["yside"] + + @yside.setter + def yside(self, val): + self["yside"] = val + + @property + def _prop_descriptions(self): + return """\ + columns + The number of columns in the grid. If you provide a 2D + `subplots` array, the length of its longest row is used + as the default. If you give an `xaxes` array, its + length is used as the default. But it's also possible + to have a different length, if you want to leave a row + at the end for non-cartesian subplots. + domain + :class:`plotly.graph_objects.layout.grid.Domain` + instance or dict with compatible properties + pattern + If no `subplots`, `xaxes`, or `yaxes` are given but we + do have `rows` and `columns`, we can generate defaults + using consecutive axis IDs, in two ways: "coupled" + gives one x axis per column and one y axis per row. + "independent" uses a new xy pair for each cell, left- + to-right across each row then iterating rows according + to `roworder`. + roworder + Is the first row the top or the bottom? Note that + columns are always enumerated from left to right. + rows + The number of rows in the grid. If you provide a 2D + `subplots` array or a `yaxes` array, its length is used + as the default. But it's also possible to have a + different length, if you want to leave a row at the end + for non-cartesian subplots. + subplots + Used for freeform grids, where some axes may be shared + across subplots but others are not. Each entry should + be a cartesian subplot id, like "xy" or "x3y2", or "" + to leave that cell empty. You may reuse x axes within + the same column, and y axes within the same row. Non- + cartesian subplots and traces that support `domain` can + place themselves in this grid separately using the + `gridcell` attribute. + xaxes + Used with `yaxes` when the x and y axes are shared + across columns and rows. Each entry should be an x axis + id like "x", "x2", etc., or "" to not put an x axis in + that column. Entries other than "" must be unique. + Ignored if `subplots` is present. If missing but + `yaxes` is present, will generate consecutive IDs. + xgap + Horizontal space between grid cells, expressed as a + fraction of the total width available to one cell. + Defaults to 0.1 for coupled-axes grids and 0.2 for + independent grids. + xside + Sets where the x axis labels and titles go. "bottom" + means the very bottom of the grid. "bottom plot" is the + lowest plot that each x axis is used in. "top" and "top + plot" are similar. + yaxes + Used with `yaxes` when the x and y axes are shared + across columns and rows. Each entry should be an y axis + id like "y", "y2", etc., or "" to not put a y axis in + that row. Entries other than "" must be unique. Ignored + if `subplots` is present. If missing but `xaxes` is + present, will generate consecutive IDs. + ygap + Vertical space between grid cells, expressed as a + fraction of the total height available to one cell. + Defaults to 0.1 for coupled-axes grids and 0.3 for + independent grids. + yside + Sets where the y axis labels and titles go. "left" + means the very left edge of the grid. *left plot* is + the leftmost plot that each y axis is used in. "right" + and *right plot* are similar. + """ + + def __init__( + self, + arg=None, + columns=None, + domain=None, + pattern=None, + roworder=None, + rows=None, + subplots=None, + xaxes=None, + xgap=None, + xside=None, + yaxes=None, + ygap=None, + yside=None, + **kwargs, + ): + """ + Construct a new Grid object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.Grid` + columns + The number of columns in the grid. If you provide a 2D + `subplots` array, the length of its longest row is used + as the default. If you give an `xaxes` array, its + length is used as the default. But it's also possible + to have a different length, if you want to leave a row + at the end for non-cartesian subplots. + domain + :class:`plotly.graph_objects.layout.grid.Domain` + instance or dict with compatible properties + pattern + If no `subplots`, `xaxes`, or `yaxes` are given but we + do have `rows` and `columns`, we can generate defaults + using consecutive axis IDs, in two ways: "coupled" + gives one x axis per column and one y axis per row. + "independent" uses a new xy pair for each cell, left- + to-right across each row then iterating rows according + to `roworder`. + roworder + Is the first row the top or the bottom? Note that + columns are always enumerated from left to right. + rows + The number of rows in the grid. If you provide a 2D + `subplots` array or a `yaxes` array, its length is used + as the default. But it's also possible to have a + different length, if you want to leave a row at the end + for non-cartesian subplots. + subplots + Used for freeform grids, where some axes may be shared + across subplots but others are not. Each entry should + be a cartesian subplot id, like "xy" or "x3y2", or "" + to leave that cell empty. You may reuse x axes within + the same column, and y axes within the same row. Non- + cartesian subplots and traces that support `domain` can + place themselves in this grid separately using the + `gridcell` attribute. + xaxes + Used with `yaxes` when the x and y axes are shared + across columns and rows. Each entry should be an x axis + id like "x", "x2", etc., or "" to not put an x axis in + that column. Entries other than "" must be unique. + Ignored if `subplots` is present. If missing but + `yaxes` is present, will generate consecutive IDs. + xgap + Horizontal space between grid cells, expressed as a + fraction of the total width available to one cell. + Defaults to 0.1 for coupled-axes grids and 0.2 for + independent grids. + xside + Sets where the x axis labels and titles go. "bottom" + means the very bottom of the grid. "bottom plot" is the + lowest plot that each x axis is used in. "top" and "top + plot" are similar. + yaxes + Used with `yaxes` when the x and y axes are shared + across columns and rows. Each entry should be an y axis + id like "y", "y2", etc., or "" to not put a y axis in + that row. Entries other than "" must be unique. Ignored + if `subplots` is present. If missing but `xaxes` is + present, will generate consecutive IDs. + ygap + Vertical space between grid cells, expressed as a + fraction of the total height available to one cell. + Defaults to 0.1 for coupled-axes grids and 0.3 for + independent grids. + yside + Sets where the y axis labels and titles go. "left" + means the very left edge of the grid. *left plot* is + the leftmost plot that each y axis is used in. "right" + and *right plot* are similar. + + Returns + ------- + Grid + """ + super().__init__("grid") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Grid +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Grid`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("columns", arg, columns) + self._set_property("domain", arg, domain) + self._set_property("pattern", arg, pattern) + self._set_property("roworder", arg, roworder) + self._set_property("rows", arg, rows) + self._set_property("subplots", arg, subplots) + self._set_property("xaxes", arg, xaxes) + self._set_property("xgap", arg, xgap) + self._set_property("xside", arg, xside) + self._set_property("yaxes", arg, yaxes) + self._set_property("ygap", arg, ygap) + self._set_property("yside", arg, yside) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_hoverlabel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_hoverlabel.py new file mode 100644 index 0000000000000000000000000000000000000000..644ed5469b474fda4f2be5cf6242e35614fa8164 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_hoverlabel.py @@ -0,0 +1,282 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Hoverlabel(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.hoverlabel" + _valid_props = { + "align", + "bgcolor", + "bordercolor", + "font", + "grouptitlefont", + "namelength", + "showarrow", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the text content within hover + label box. Has an effect only if the hover label text spans + more two or more lines + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'auto'] + + Returns + ------- + Any + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def bgcolor(self): + """ + Sets the background color of all hover labels on graph + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bordercolor(self): + """ + Sets the border color of all hover labels on graph. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def font(self): + """ + Sets the default hover label font used by all traces on the + graph. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.hoverlabel.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.layout.hoverlabel.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def grouptitlefont(self): + """ + Sets the font for group titles in hover (unified modes). + Defaults to `hoverlabel.font`. + + The 'grouptitlefont' property is an instance of Grouptitlefont + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.hoverlabel.Grouptitlefont` + - A dict of string/value properties that will be passed + to the Grouptitlefont constructor + + Returns + ------- + plotly.graph_objs.layout.hoverlabel.Grouptitlefont + """ + return self["grouptitlefont"] + + @grouptitlefont.setter + def grouptitlefont(self, val): + self["grouptitlefont"] = val + + @property + def namelength(self): + """ + Sets the default length (in number of characters) of the trace + name in the hover labels for all traces. -1 shows the whole + name regardless of length. 0-3 shows the first 0-3 characters, + and an integer >3 will show the whole name if it is less than + that many characters, but if it is longer, will truncate to + `namelength - 3` characters and add an ellipsis. + + The 'namelength' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + + Returns + ------- + int + """ + return self["namelength"] + + @namelength.setter + def namelength(self, val): + self["namelength"] = val + + @property + def showarrow(self): + """ + Sets whether or not to show the hover label arrow/triangle + pointing to the data point. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + bgcolor + Sets the background color of all hover labels on graph + bordercolor + Sets the border color of all hover labels on graph. + font + Sets the default hover label font used by all traces on + the graph. + grouptitlefont + Sets the font for group titles in hover (unified + modes). Defaults to `hoverlabel.font`. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + """ + + def __init__( + self, + arg=None, + align=None, + bgcolor=None, + bordercolor=None, + font=None, + grouptitlefont=None, + namelength=None, + showarrow=None, + **kwargs, + ): + """ + Construct a new Hoverlabel object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.layout.Hoverlabel` + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + bgcolor + Sets the background color of all hover labels on graph + bordercolor + Sets the border color of all hover labels on graph. + font + Sets the default hover label font used by all traces on + the graph. + grouptitlefont + Sets the font for group titles in hover (unified + modes). Defaults to `hoverlabel.font`. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + + Returns + ------- + Hoverlabel + """ + super().__init__("hoverlabel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Hoverlabel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Hoverlabel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("font", arg, font) + self._set_property("grouptitlefont", arg, grouptitlefont) + self._set_property("namelength", arg, namelength) + self._set_property("showarrow", arg, showarrow) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_image.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_image.py new file mode 100644 index 0000000000000000000000000000000000000000..943ff247797f66c69fb2c5874aa9981f1db29d7a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_image.py @@ -0,0 +1,608 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Image(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.image" + _valid_props = { + "layer", + "name", + "opacity", + "sizex", + "sizey", + "sizing", + "source", + "templateitemname", + "visible", + "x", + "xanchor", + "xref", + "y", + "yanchor", + "yref", + } + + @property + def layer(self): + """ + Specifies whether images are drawn below or above traces. When + `xref` and `yref` are both set to `paper`, image is drawn below + the entire plot area. + + The 'layer' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['below', 'above'] + + Returns + ------- + Any + """ + return self["layer"] + + @layer.setter + def layer(self, val): + self["layer"] = val + + @property + def name(self): + """ + When used in a template, named items are created in the output + figure in addition to any items the figure already has in this + array. You can modify these items in the output figure by + making your own item with `templateitemname` matching this + `name` alongside your modifications (including `visible: false` + or `enabled: false` to hide it). Has no effect outside of a + template. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the image. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def sizex(self): + """ + Sets the image container size horizontally. The image will be + sized based on the `position` value. When `xref` is set to + `paper`, units are sized relative to the plot width. When + `xref` ends with ` domain`, units are sized relative to the + axis width. + + The 'sizex' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["sizex"] + + @sizex.setter + def sizex(self, val): + self["sizex"] = val + + @property + def sizey(self): + """ + Sets the image container size vertically. The image will be + sized based on the `position` value. When `yref` is set to + `paper`, units are sized relative to the plot height. When + `yref` ends with ` domain`, units are sized relative to the + axis height. + + The 'sizey' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["sizey"] + + @sizey.setter + def sizey(self, val): + self["sizey"] = val + + @property + def sizing(self): + """ + Specifies which dimension of the image to constrain. + + The 'sizing' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fill', 'contain', 'stretch'] + + Returns + ------- + Any + """ + return self["sizing"] + + @sizing.setter + def sizing(self, val): + self["sizing"] = val + + @property + def source(self): + """ + Specifies the URL of the image to be used. The URL must be + accessible from the domain where the plot code is run, and can + be either relative or absolute. + + The 'source' property is an image URI that may be specified as: + - A remote image URI string + (e.g. 'http://www.somewhere.com/image.png') + - A data URI image string + (e.g. 'data:image/png;base64,iVBORw0KGgoAAAANSU') + - A PIL.Image.Image object which will be immediately converted + to a data URI image string + See http://pillow.readthedocs.io/en/latest/reference/Image.html + + Returns + ------- + str + """ + return self["source"] + + @source.setter + def source(self, val): + self["source"] = val + + @property + def templateitemname(self): + """ + Used to refer to a named item in this array in the template. + Named items from the template will be created even without a + matching item in the input figure, but you can modify one by + making an item with `templateitemname` matching its `name`, + alongside your modifications (including `visible: false` or + `enabled: false` to hide it). If there is no template or no + matching item, this item will be hidden unless you explicitly + show it with `visible: true`. + + The 'templateitemname' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["templateitemname"] + + @templateitemname.setter + def templateitemname(self, val): + self["templateitemname"] = val + + @property + def visible(self): + """ + Determines whether or not this image is visible. + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the image's x position. When `xref` is set to `paper`, + units are sized relative to the plot height. See `xref` for + more info + + The 'x' property accepts values of any type + + Returns + ------- + Any + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xanchor(self): + """ + Sets the anchor for the x position + + The 'xanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'center', 'right'] + + Returns + ------- + Any + """ + return self["xanchor"] + + @xanchor.setter + def xanchor(self, val): + self["xanchor"] = val + + @property + def xref(self): + """ + Sets the images's x coordinate axis. If set to a x axis id + (e.g. "x" or "x2"), the `x` position refers to a x coordinate. + If set to "paper", the `x` position refers to the distance from + the left of the plotting area in normalized coordinates where 0 + (1) corresponds to the left (right). If set to a x axis ID + followed by "domain" (separated by a space), the position + behaves like for "paper", but refers to the distance in + fractions of the domain length from the left of the domain of + that axis: e.g., *x2 domain* refers to the domain of the second + x axis and a x position of 0.5 refers to the point between the + left and the right of the domain of the second x axis. + + The 'xref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['paper'] + - A string that matches one of the following regular expressions: + ['^x([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["xref"] + + @xref.setter + def xref(self, val): + self["xref"] = val + + @property + def y(self): + """ + Sets the image's y position. When `yref` is set to `paper`, + units are sized relative to the plot height. See `yref` for + more info + + The 'y' property accepts values of any type + + Returns + ------- + Any + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yanchor(self): + """ + Sets the anchor for the y position. + + The 'yanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top', 'middle', 'bottom'] + + Returns + ------- + Any + """ + return self["yanchor"] + + @yanchor.setter + def yanchor(self, val): + self["yanchor"] = val + + @property + def yref(self): + """ + Sets the images's y coordinate axis. If set to a y axis id + (e.g. "y" or "y2"), the `y` position refers to a y coordinate. + If set to "paper", the `y` position refers to the distance from + the bottom of the plotting area in normalized coordinates where + 0 (1) corresponds to the bottom (top). If set to a y axis ID + followed by "domain" (separated by a space), the position + behaves like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the domain of + that axis: e.g., *y2 domain* refers to the domain of the second + y axis and a y position of 0.5 refers to the point between the + bottom and the top of the domain of the second y axis. + + The 'yref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['paper'] + - A string that matches one of the following regular expressions: + ['^y([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["yref"] + + @yref.setter + def yref(self, val): + self["yref"] = val + + @property + def _prop_descriptions(self): + return """\ + layer + Specifies whether images are drawn below or above + traces. When `xref` and `yref` are both set to `paper`, + image is drawn below the entire plot area. + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the image. + sizex + Sets the image container size horizontally. The image + will be sized based on the `position` value. When + `xref` is set to `paper`, units are sized relative to + the plot width. When `xref` ends with ` domain`, units + are sized relative to the axis width. + sizey + Sets the image container size vertically. The image + will be sized based on the `position` value. When + `yref` is set to `paper`, units are sized relative to + the plot height. When `yref` ends with ` domain`, units + are sized relative to the axis height. + sizing + Specifies which dimension of the image to constrain. + source + Specifies the URL of the image to be used. The URL must + be accessible from the domain where the plot code is + run, and can be either relative or absolute. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + visible + Determines whether or not this image is visible. + x + Sets the image's x position. When `xref` is set to + `paper`, units are sized relative to the plot height. + See `xref` for more info + xanchor + Sets the anchor for the x position + xref + Sets the images's x coordinate axis. If set to a x axis + id (e.g. "x" or "x2"), the `x` position refers to a x + coordinate. If set to "paper", the `x` position refers + to the distance from the left of the plotting area in + normalized coordinates where 0 (1) corresponds to the + left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + y + Sets the image's y position. When `yref` is set to + `paper`, units are sized relative to the plot height. + See `yref` for more info + yanchor + Sets the anchor for the y position. + yref + Sets the images's y coordinate axis. If set to a y axis + id (e.g. "y" or "y2"), the `y` position refers to a y + coordinate. If set to "paper", the `y` position refers + to the distance from the bottom of the plotting area in + normalized coordinates where 0 (1) corresponds to the + bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + """ + + def __init__( + self, + arg=None, + layer=None, + name=None, + opacity=None, + sizex=None, + sizey=None, + sizing=None, + source=None, + templateitemname=None, + visible=None, + x=None, + xanchor=None, + xref=None, + y=None, + yanchor=None, + yref=None, + **kwargs, + ): + """ + Construct a new Image object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.Image` + layer + Specifies whether images are drawn below or above + traces. When `xref` and `yref` are both set to `paper`, + image is drawn below the entire plot area. + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the image. + sizex + Sets the image container size horizontally. The image + will be sized based on the `position` value. When + `xref` is set to `paper`, units are sized relative to + the plot width. When `xref` ends with ` domain`, units + are sized relative to the axis width. + sizey + Sets the image container size vertically. The image + will be sized based on the `position` value. When + `yref` is set to `paper`, units are sized relative to + the plot height. When `yref` ends with ` domain`, units + are sized relative to the axis height. + sizing + Specifies which dimension of the image to constrain. + source + Specifies the URL of the image to be used. The URL must + be accessible from the domain where the plot code is + run, and can be either relative or absolute. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + visible + Determines whether or not this image is visible. + x + Sets the image's x position. When `xref` is set to + `paper`, units are sized relative to the plot height. + See `xref` for more info + xanchor + Sets the anchor for the x position + xref + Sets the images's x coordinate axis. If set to a x axis + id (e.g. "x" or "x2"), the `x` position refers to a x + coordinate. If set to "paper", the `x` position refers + to the distance from the left of the plotting area in + normalized coordinates where 0 (1) corresponds to the + left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + y + Sets the image's y position. When `yref` is set to + `paper`, units are sized relative to the plot height. + See `yref` for more info + yanchor + Sets the anchor for the y position. + yref + Sets the images's y coordinate axis. If set to a y axis + id (e.g. "y" or "y2"), the `y` position refers to a y + coordinate. If set to "paper", the `y` position refers + to the distance from the bottom of the plotting area in + normalized coordinates where 0 (1) corresponds to the + bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + + Returns + ------- + Image + """ + super().__init__("images") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Image +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Image`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("layer", arg, layer) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("sizex", arg, sizex) + self._set_property("sizey", arg, sizey) + self._set_property("sizing", arg, sizing) + self._set_property("source", arg, source) + self._set_property("templateitemname", arg, templateitemname) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("xanchor", arg, xanchor) + self._set_property("xref", arg, xref) + self._set_property("y", arg, y) + self._set_property("yanchor", arg, yanchor) + self._set_property("yref", arg, yref) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_legend.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_legend.py new file mode 100644 index 0000000000000000000000000000000000000000..618f90f3afcb66ee9fdb95fec443e06a38ec4994 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_legend.py @@ -0,0 +1,969 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Legend(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.legend" + _valid_props = { + "bgcolor", + "bordercolor", + "borderwidth", + "entrywidth", + "entrywidthmode", + "font", + "groupclick", + "grouptitlefont", + "indentation", + "itemclick", + "itemdoubleclick", + "itemsizing", + "itemwidth", + "maxheight", + "orientation", + "title", + "tracegroupgap", + "traceorder", + "uirevision", + "valign", + "visible", + "x", + "xanchor", + "xref", + "y", + "yanchor", + "yref", + } + + @property + def bgcolor(self): + """ + Sets the legend background color. Defaults to + `layout.paper_bgcolor`. + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bordercolor(self): + """ + Sets the color of the border enclosing the legend. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def borderwidth(self): + """ + Sets the width (in px) of the border enclosing the legend. + + The 'borderwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["borderwidth"] + + @borderwidth.setter + def borderwidth(self, val): + self["borderwidth"] = val + + @property + def entrywidth(self): + """ + Sets the width (in px or fraction) of the legend. Use 0 to size + the entry based on the text width, when `entrywidthmode` is set + to "pixels". + + The 'entrywidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["entrywidth"] + + @entrywidth.setter + def entrywidth(self, val): + self["entrywidth"] = val + + @property + def entrywidthmode(self): + """ + Determines what entrywidth means. + + The 'entrywidthmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fraction', 'pixels'] + + Returns + ------- + Any + """ + return self["entrywidthmode"] + + @entrywidthmode.setter + def entrywidthmode(self, val): + self["entrywidthmode"] = val + + @property + def font(self): + """ + Sets the font used to text the legend items. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.legend.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.layout.legend.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def groupclick(self): + """ + Determines the behavior on legend group item click. + "toggleitem" toggles the visibility of the individual item + clicked on the graph. "togglegroup" toggles the visibility of + all items in the same legendgroup as the item clicked on the + graph. + + The 'groupclick' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['toggleitem', 'togglegroup'] + + Returns + ------- + Any + """ + return self["groupclick"] + + @groupclick.setter + def groupclick(self, val): + self["groupclick"] = val + + @property + def grouptitlefont(self): + """ + Sets the font for group titles in legend. Defaults to + `legend.font` with its size increased about 10%. + + The 'grouptitlefont' property is an instance of Grouptitlefont + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.legend.Grouptitlefont` + - A dict of string/value properties that will be passed + to the Grouptitlefont constructor + + Returns + ------- + plotly.graph_objs.layout.legend.Grouptitlefont + """ + return self["grouptitlefont"] + + @grouptitlefont.setter + def grouptitlefont(self, val): + self["grouptitlefont"] = val + + @property + def indentation(self): + """ + Sets the indentation (in px) of the legend entries. + + The 'indentation' property is a number and may be specified as: + - An int or float in the interval [-15, inf] + + Returns + ------- + int|float + """ + return self["indentation"] + + @indentation.setter + def indentation(self, val): + self["indentation"] = val + + @property + def itemclick(self): + """ + Determines the behavior on legend item click. "toggle" toggles + the visibility of the item clicked on the graph. "toggleothers" + makes the clicked item the sole visible item on the graph. + False disables legend item click interactions. + + The 'itemclick' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['toggle', 'toggleothers', False] + + Returns + ------- + Any + """ + return self["itemclick"] + + @itemclick.setter + def itemclick(self, val): + self["itemclick"] = val + + @property + def itemdoubleclick(self): + """ + Determines the behavior on legend item double-click. "toggle" + toggles the visibility of the item clicked on the graph. + "toggleothers" makes the clicked item the sole visible item on + the graph. False disables legend item double-click + interactions. + + The 'itemdoubleclick' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['toggle', 'toggleothers', False] + + Returns + ------- + Any + """ + return self["itemdoubleclick"] + + @itemdoubleclick.setter + def itemdoubleclick(self, val): + self["itemdoubleclick"] = val + + @property + def itemsizing(self): + """ + Determines if the legend items symbols scale with their + corresponding "trace" attributes or remain "constant" + independent of the symbol size on the graph. + + The 'itemsizing' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['trace', 'constant'] + + Returns + ------- + Any + """ + return self["itemsizing"] + + @itemsizing.setter + def itemsizing(self, val): + self["itemsizing"] = val + + @property + def itemwidth(self): + """ + Sets the width (in px) of the legend item symbols (the part + other than the title.text). + + The 'itemwidth' property is a number and may be specified as: + - An int or float in the interval [30, inf] + + Returns + ------- + int|float + """ + return self["itemwidth"] + + @itemwidth.setter + def itemwidth(self, val): + self["itemwidth"] = val + + @property + def maxheight(self): + """ + Sets the max height (in px) of the legend, or max height ratio + (reference height * ratio) if less than or equal to 1. Default + value is: 0.5 for horizontal legends; 1 for vertical legends. + The minimum allowed height is 30px. For a ratio of 0.5, the + legend will take up to 50% of the reference height before + displaying a scrollbar. The reference height is the full layout + height with the following exception: vertically oriented + legends with a `yref` of `"paper", located to the side of the + plot. In this case, the reference height is the plot height. + + The 'maxheight' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["maxheight"] + + @maxheight.setter + def maxheight(self, val): + self["maxheight"] = val + + @property + def orientation(self): + """ + Sets the orientation of the legend. + + The 'orientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['v', 'h'] + + Returns + ------- + Any + """ + return self["orientation"] + + @orientation.setter + def orientation(self, val): + self["orientation"] = val + + @property + def title(self): + """ + The 'title' property is an instance of Title + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.legend.Title` + - A dict of string/value properties that will be passed + to the Title constructor + + Returns + ------- + plotly.graph_objs.layout.legend.Title + """ + return self["title"] + + @title.setter + def title(self, val): + self["title"] = val + + @property + def tracegroupgap(self): + """ + Sets the amount of vertical space (in px) between legend + groups. + + The 'tracegroupgap' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["tracegroupgap"] + + @tracegroupgap.setter + def tracegroupgap(self, val): + self["tracegroupgap"] = val + + @property + def traceorder(self): + """ + Determines the order at which the legend items are displayed. + If "normal", the items are displayed top-to-bottom in the same + order as the input data. If "reversed", the items are displayed + in the opposite order as "normal". If "grouped", the items are + displayed in groups (when a trace `legendgroup` is provided). + if "grouped+reversed", the items are displayed in the opposite + order as "grouped". + + The 'traceorder' property is a flaglist and may be specified + as a string containing: + - Any combination of ['reversed', 'grouped'] joined with '+' characters + (e.g. 'reversed+grouped') + OR exactly one of ['normal'] (e.g. 'normal') + + Returns + ------- + Any + """ + return self["traceorder"] + + @traceorder.setter + def traceorder(self, val): + self["traceorder"] = val + + @property + def uirevision(self): + """ + Controls persistence of legend-driven changes in trace and pie + label visibility. Defaults to `layout.uirevision`. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def valign(self): + """ + Sets the vertical alignment of the symbols with respect to + their associated text. + + The 'valign' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top', 'middle', 'bottom'] + + Returns + ------- + Any + """ + return self["valign"] + + @valign.setter + def valign(self, val): + self["valign"] = val + + @property + def visible(self): + """ + Determines whether or not this legend is visible. + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the x position with respect to `xref` (in normalized + coordinates) of the legend. When `xref` is "paper", defaults to + 1.02 for vertical legends and defaults to 0 for horizontal + legends. When `xref` is "container", defaults to 1 for vertical + legends and defaults to 0 for horizontal legends. Must be + between 0 and 1 if `xref` is "container". and between "-2" and + 3 if `xref` is "paper". + + The 'x' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xanchor(self): + """ + Sets the legend's horizontal position anchor. This anchor binds + the `x` position to the "left", "center" or "right" of the + legend. Value "auto" anchors legends to the right for `x` + values greater than or equal to 2/3, anchors legends to the + left for `x` values less than or equal to 1/3 and anchors + legends with respect to their center otherwise. + + The 'xanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'left', 'center', 'right'] + + Returns + ------- + Any + """ + return self["xanchor"] + + @xanchor.setter + def xanchor(self, val): + self["xanchor"] = val + + @property + def xref(self): + """ + Sets the container `x` refers to. "container" spans the entire + `width` of the plot. "paper" refers to the width of the + plotting area only. + + The 'xref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['container', 'paper'] + + Returns + ------- + Any + """ + return self["xref"] + + @xref.setter + def xref(self, val): + self["xref"] = val + + @property + def y(self): + """ + Sets the y position with respect to `yref` (in normalized + coordinates) of the legend. When `yref` is "paper", defaults to + 1 for vertical legends, defaults to "-0.1" for horizontal + legends on graphs w/o range sliders and defaults to 1.1 for + horizontal legends on graph with one or multiple range sliders. + When `yref` is "container", defaults to 1. Must be between 0 + and 1 if `yref` is "container" and between "-2" and 3 if `yref` + is "paper". + + The 'y' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yanchor(self): + """ + Sets the legend's vertical position anchor. This anchor binds + the `y` position to the "top", "middle" or "bottom" of the + legend. Value "auto" anchors legends at their bottom for `y` + values less than or equal to 1/3, anchors legends to at their + top for `y` values greater than or equal to 2/3 and anchors + legends with respect to their middle otherwise. + + The 'yanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'top', 'middle', 'bottom'] + + Returns + ------- + Any + """ + return self["yanchor"] + + @yanchor.setter + def yanchor(self, val): + self["yanchor"] = val + + @property + def yref(self): + """ + Sets the container `y` refers to. "container" spans the entire + `height` of the plot. "paper" refers to the height of the + plotting area only. + + The 'yref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['container', 'paper'] + + Returns + ------- + Any + """ + return self["yref"] + + @yref.setter + def yref(self, val): + self["yref"] = val + + @property + def _prop_descriptions(self): + return """\ + bgcolor + Sets the legend background color. Defaults to + `layout.paper_bgcolor`. + bordercolor + Sets the color of the border enclosing the legend. + borderwidth + Sets the width (in px) of the border enclosing the + legend. + entrywidth + Sets the width (in px or fraction) of the legend. Use 0 + to size the entry based on the text width, when + `entrywidthmode` is set to "pixels". + entrywidthmode + Determines what entrywidth means. + font + Sets the font used to text the legend items. + groupclick + Determines the behavior on legend group item click. + "toggleitem" toggles the visibility of the individual + item clicked on the graph. "togglegroup" toggles the + visibility of all items in the same legendgroup as the + item clicked on the graph. + grouptitlefont + Sets the font for group titles in legend. Defaults to + `legend.font` with its size increased about 10%. + indentation + Sets the indentation (in px) of the legend entries. + itemclick + Determines the behavior on legend item click. "toggle" + toggles the visibility of the item clicked on the + graph. "toggleothers" makes the clicked item the sole + visible item on the graph. False disables legend item + click interactions. + itemdoubleclick + Determines the behavior on legend item double-click. + "toggle" toggles the visibility of the item clicked on + the graph. "toggleothers" makes the clicked item the + sole visible item on the graph. False disables legend + item double-click interactions. + itemsizing + Determines if the legend items symbols scale with their + corresponding "trace" attributes or remain "constant" + independent of the symbol size on the graph. + itemwidth + Sets the width (in px) of the legend item symbols (the + part other than the title.text). + maxheight + Sets the max height (in px) of the legend, or max + height ratio (reference height * ratio) if less than or + equal to 1. Default value is: 0.5 for horizontal + legends; 1 for vertical legends. The minimum allowed + height is 30px. For a ratio of 0.5, the legend will + take up to 50% of the reference height before + displaying a scrollbar. The reference height is the + full layout height with the following exception: + vertically oriented legends with a `yref` of `"paper", + located to the side of the plot. In this case, the + reference height is the plot height. + orientation + Sets the orientation of the legend. + title + :class:`plotly.graph_objects.layout.legend.Title` + instance or dict with compatible properties + tracegroupgap + Sets the amount of vertical space (in px) between + legend groups. + traceorder + Determines the order at which the legend items are + displayed. If "normal", the items are displayed top-to- + bottom in the same order as the input data. If + "reversed", the items are displayed in the opposite + order as "normal". If "grouped", the items are + displayed in groups (when a trace `legendgroup` is + provided). if "grouped+reversed", the items are + displayed in the opposite order as "grouped". + uirevision + Controls persistence of legend-driven changes in trace + and pie label visibility. Defaults to + `layout.uirevision`. + valign + Sets the vertical alignment of the symbols with respect + to their associated text. + visible + Determines whether or not this legend is visible. + x + Sets the x position with respect to `xref` (in + normalized coordinates) of the legend. When `xref` is + "paper", defaults to 1.02 for vertical legends and + defaults to 0 for horizontal legends. When `xref` is + "container", defaults to 1 for vertical legends and + defaults to 0 for horizontal legends. Must be between 0 + and 1 if `xref` is "container". and between "-2" and 3 + if `xref` is "paper". + xanchor + Sets the legend's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the legend. Value "auto" anchors legends + to the right for `x` values greater than or equal to + 2/3, anchors legends to the left for `x` values less + than or equal to 1/3 and anchors legends with respect + to their center otherwise. + xref + Sets the container `x` refers to. "container" spans the + entire `width` of the plot. "paper" refers to the width + of the plotting area only. + y + Sets the y position with respect to `yref` (in + normalized coordinates) of the legend. When `yref` is + "paper", defaults to 1 for vertical legends, defaults + to "-0.1" for horizontal legends on graphs w/o range + sliders and defaults to 1.1 for horizontal legends on + graph with one or multiple range sliders. When `yref` + is "container", defaults to 1. Must be between 0 and 1 + if `yref` is "container" and between "-2" and 3 if + `yref` is "paper". + yanchor + Sets the legend's vertical position anchor. This anchor + binds the `y` position to the "top", "middle" or + "bottom" of the legend. Value "auto" anchors legends at + their bottom for `y` values less than or equal to 1/3, + anchors legends to at their top for `y` values greater + than or equal to 2/3 and anchors legends with respect + to their middle otherwise. + yref + Sets the container `y` refers to. "container" spans the + entire `height` of the plot. "paper" refers to the + height of the plotting area only. + """ + + def __init__( + self, + arg=None, + bgcolor=None, + bordercolor=None, + borderwidth=None, + entrywidth=None, + entrywidthmode=None, + font=None, + groupclick=None, + grouptitlefont=None, + indentation=None, + itemclick=None, + itemdoubleclick=None, + itemsizing=None, + itemwidth=None, + maxheight=None, + orientation=None, + title=None, + tracegroupgap=None, + traceorder=None, + uirevision=None, + valign=None, + visible=None, + x=None, + xanchor=None, + xref=None, + y=None, + yanchor=None, + yref=None, + **kwargs, + ): + """ + Construct a new Legend object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.Legend` + bgcolor + Sets the legend background color. Defaults to + `layout.paper_bgcolor`. + bordercolor + Sets the color of the border enclosing the legend. + borderwidth + Sets the width (in px) of the border enclosing the + legend. + entrywidth + Sets the width (in px or fraction) of the legend. Use 0 + to size the entry based on the text width, when + `entrywidthmode` is set to "pixels". + entrywidthmode + Determines what entrywidth means. + font + Sets the font used to text the legend items. + groupclick + Determines the behavior on legend group item click. + "toggleitem" toggles the visibility of the individual + item clicked on the graph. "togglegroup" toggles the + visibility of all items in the same legendgroup as the + item clicked on the graph. + grouptitlefont + Sets the font for group titles in legend. Defaults to + `legend.font` with its size increased about 10%. + indentation + Sets the indentation (in px) of the legend entries. + itemclick + Determines the behavior on legend item click. "toggle" + toggles the visibility of the item clicked on the + graph. "toggleothers" makes the clicked item the sole + visible item on the graph. False disables legend item + click interactions. + itemdoubleclick + Determines the behavior on legend item double-click. + "toggle" toggles the visibility of the item clicked on + the graph. "toggleothers" makes the clicked item the + sole visible item on the graph. False disables legend + item double-click interactions. + itemsizing + Determines if the legend items symbols scale with their + corresponding "trace" attributes or remain "constant" + independent of the symbol size on the graph. + itemwidth + Sets the width (in px) of the legend item symbols (the + part other than the title.text). + maxheight + Sets the max height (in px) of the legend, or max + height ratio (reference height * ratio) if less than or + equal to 1. Default value is: 0.5 for horizontal + legends; 1 for vertical legends. The minimum allowed + height is 30px. For a ratio of 0.5, the legend will + take up to 50% of the reference height before + displaying a scrollbar. The reference height is the + full layout height with the following exception: + vertically oriented legends with a `yref` of `"paper", + located to the side of the plot. In this case, the + reference height is the plot height. + orientation + Sets the orientation of the legend. + title + :class:`plotly.graph_objects.layout.legend.Title` + instance or dict with compatible properties + tracegroupgap + Sets the amount of vertical space (in px) between + legend groups. + traceorder + Determines the order at which the legend items are + displayed. If "normal", the items are displayed top-to- + bottom in the same order as the input data. If + "reversed", the items are displayed in the opposite + order as "normal". If "grouped", the items are + displayed in groups (when a trace `legendgroup` is + provided). if "grouped+reversed", the items are + displayed in the opposite order as "grouped". + uirevision + Controls persistence of legend-driven changes in trace + and pie label visibility. Defaults to + `layout.uirevision`. + valign + Sets the vertical alignment of the symbols with respect + to their associated text. + visible + Determines whether or not this legend is visible. + x + Sets the x position with respect to `xref` (in + normalized coordinates) of the legend. When `xref` is + "paper", defaults to 1.02 for vertical legends and + defaults to 0 for horizontal legends. When `xref` is + "container", defaults to 1 for vertical legends and + defaults to 0 for horizontal legends. Must be between 0 + and 1 if `xref` is "container". and between "-2" and 3 + if `xref` is "paper". + xanchor + Sets the legend's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the legend. Value "auto" anchors legends + to the right for `x` values greater than or equal to + 2/3, anchors legends to the left for `x` values less + than or equal to 1/3 and anchors legends with respect + to their center otherwise. + xref + Sets the container `x` refers to. "container" spans the + entire `width` of the plot. "paper" refers to the width + of the plotting area only. + y + Sets the y position with respect to `yref` (in + normalized coordinates) of the legend. When `yref` is + "paper", defaults to 1 for vertical legends, defaults + to "-0.1" for horizontal legends on graphs w/o range + sliders and defaults to 1.1 for horizontal legends on + graph with one or multiple range sliders. When `yref` + is "container", defaults to 1. Must be between 0 and 1 + if `yref` is "container" and between "-2" and 3 if + `yref` is "paper". + yanchor + Sets the legend's vertical position anchor. This anchor + binds the `y` position to the "top", "middle" or + "bottom" of the legend. Value "auto" anchors legends at + their bottom for `y` values less than or equal to 1/3, + anchors legends to at their top for `y` values greater + than or equal to 2/3 and anchors legends with respect + to their middle otherwise. + yref + Sets the container `y` refers to. "container" spans the + entire `height` of the plot. "paper" refers to the + height of the plotting area only. + + Returns + ------- + Legend + """ + super().__init__("legend") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Legend +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Legend`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("borderwidth", arg, borderwidth) + self._set_property("entrywidth", arg, entrywidth) + self._set_property("entrywidthmode", arg, entrywidthmode) + self._set_property("font", arg, font) + self._set_property("groupclick", arg, groupclick) + self._set_property("grouptitlefont", arg, grouptitlefont) + self._set_property("indentation", arg, indentation) + self._set_property("itemclick", arg, itemclick) + self._set_property("itemdoubleclick", arg, itemdoubleclick) + self._set_property("itemsizing", arg, itemsizing) + self._set_property("itemwidth", arg, itemwidth) + self._set_property("maxheight", arg, maxheight) + self._set_property("orientation", arg, orientation) + self._set_property("title", arg, title) + self._set_property("tracegroupgap", arg, tracegroupgap) + self._set_property("traceorder", arg, traceorder) + self._set_property("uirevision", arg, uirevision) + self._set_property("valign", arg, valign) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("xanchor", arg, xanchor) + self._set_property("xref", arg, xref) + self._set_property("y", arg, y) + self._set_property("yanchor", arg, yanchor) + self._set_property("yref", arg, yref) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_map.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_map.py new file mode 100644 index 0000000000000000000000000000000000000000..f54257cd6fe46599c71681faf52c0872f7e801cd --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_map.py @@ -0,0 +1,392 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Map(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.map" + _valid_props = { + "bearing", + "bounds", + "center", + "domain", + "layerdefaults", + "layers", + "pitch", + "style", + "uirevision", + "zoom", + } + + @property + def bearing(self): + """ + Sets the bearing angle of the map in degrees counter-clockwise + from North (map.bearing). + + The 'bearing' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["bearing"] + + @bearing.setter + def bearing(self, val): + self["bearing"] = val + + @property + def bounds(self): + """ + The 'bounds' property is an instance of Bounds + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.map.Bounds` + - A dict of string/value properties that will be passed + to the Bounds constructor + + Returns + ------- + plotly.graph_objs.layout.map.Bounds + """ + return self["bounds"] + + @bounds.setter + def bounds(self, val): + self["bounds"] = val + + @property + def center(self): + """ + The 'center' property is an instance of Center + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.map.Center` + - A dict of string/value properties that will be passed + to the Center constructor + + Returns + ------- + plotly.graph_objs.layout.map.Center + """ + return self["center"] + + @center.setter + def center(self, val): + self["center"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.map.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.layout.map.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def layers(self): + """ + The 'layers' property is a tuple of instances of + Layer that may be specified as: + - A list or tuple of instances of plotly.graph_objs.layout.map.Layer + - A list or tuple of dicts of string/value properties that + will be passed to the Layer constructor + + Returns + ------- + tuple[plotly.graph_objs.layout.map.Layer] + """ + return self["layers"] + + @layers.setter + def layers(self, val): + self["layers"] = val + + @property + def layerdefaults(self): + """ + When used in a template (as + layout.template.layout.map.layerdefaults), sets the default + property values to use for elements of layout.map.layers + + The 'layerdefaults' property is an instance of Layer + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.map.Layer` + - A dict of string/value properties that will be passed + to the Layer constructor + + Returns + ------- + plotly.graph_objs.layout.map.Layer + """ + return self["layerdefaults"] + + @layerdefaults.setter + def layerdefaults(self, val): + self["layerdefaults"] = val + + @property + def pitch(self): + """ + Sets the pitch angle of the map (in degrees, where 0 means + perpendicular to the surface of the map) (map.pitch). + + The 'pitch' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["pitch"] + + @pitch.setter + def pitch(self, val): + self["pitch"] = val + + @property + def style(self): + """ + Defines the map layers that are rendered by default below the + trace layers defined in `data`, which are themselves by default + rendered below the layers defined in `layout.map.layers`. + These layers can be defined either explicitly as a Map Style + object which can contain multiple layer definitions that load + data from any public or private Tile Map Service (TMS or XYZ) + or Web Map Service (WMS) or implicitly by using one of the + built-in style objects which use WMSes or by using a custom + style URL Map Style objects are of the form described in the + MapLibre GL JS documentation available at + https://maplibre.org/maplibre-style-spec/ The built-in + plotly.js styles objects are: basic, carto-darkmatter, carto- + darkmatter-nolabels, carto-positron, carto-positron-nolabels, + carto-voyager, carto-voyager-nolabels, dark, light, open- + street-map, outdoors, satellite, satellite-streets, streets, + white-bg. + + The 'style' property accepts values of any type + + Returns + ------- + Any + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def uirevision(self): + """ + Controls persistence of user-driven changes in the view: + `center`, `zoom`, `bearing`, `pitch`. Defaults to + `layout.uirevision`. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def zoom(self): + """ + Sets the zoom level of the map (map.zoom). + + The 'zoom' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zoom"] + + @zoom.setter + def zoom(self, val): + self["zoom"] = val + + @property + def _prop_descriptions(self): + return """\ + bearing + Sets the bearing angle of the map in degrees counter- + clockwise from North (map.bearing). + bounds + :class:`plotly.graph_objects.layout.map.Bounds` + instance or dict with compatible properties + center + :class:`plotly.graph_objects.layout.map.Center` + instance or dict with compatible properties + domain + :class:`plotly.graph_objects.layout.map.Domain` + instance or dict with compatible properties + layers + A tuple of + :class:`plotly.graph_objects.layout.map.Layer` + instances or dicts with compatible properties + layerdefaults + When used in a template (as + layout.template.layout.map.layerdefaults), sets the + default property values to use for elements of + layout.map.layers + pitch + Sets the pitch angle of the map (in degrees, where 0 + means perpendicular to the surface of the map) + (map.pitch). + style + Defines the map layers that are rendered by default + below the trace layers defined in `data`, which are + themselves by default rendered below the layers defined + in `layout.map.layers`. These layers can be defined + either explicitly as a Map Style object which can + contain multiple layer definitions that load data from + any public or private Tile Map Service (TMS or XYZ) or + Web Map Service (WMS) or implicitly by using one of the + built-in style objects which use WMSes or by using a + custom style URL Map Style objects are of the form + described in the MapLibre GL JS documentation available + at https://maplibre.org/maplibre-style-spec/ The + built-in plotly.js styles objects are: basic, carto- + darkmatter, carto-darkmatter-nolabels, carto-positron, + carto-positron-nolabels, carto-voyager, carto-voyager- + nolabels, dark, light, open-street-map, outdoors, + satellite, satellite-streets, streets, white-bg. + uirevision + Controls persistence of user-driven changes in the + view: `center`, `zoom`, `bearing`, `pitch`. Defaults to + `layout.uirevision`. + zoom + Sets the zoom level of the map (map.zoom). + """ + + def __init__( + self, + arg=None, + bearing=None, + bounds=None, + center=None, + domain=None, + layers=None, + layerdefaults=None, + pitch=None, + style=None, + uirevision=None, + zoom=None, + **kwargs, + ): + """ + Construct a new Map object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.Map` + bearing + Sets the bearing angle of the map in degrees counter- + clockwise from North (map.bearing). + bounds + :class:`plotly.graph_objects.layout.map.Bounds` + instance or dict with compatible properties + center + :class:`plotly.graph_objects.layout.map.Center` + instance or dict with compatible properties + domain + :class:`plotly.graph_objects.layout.map.Domain` + instance or dict with compatible properties + layers + A tuple of + :class:`plotly.graph_objects.layout.map.Layer` + instances or dicts with compatible properties + layerdefaults + When used in a template (as + layout.template.layout.map.layerdefaults), sets the + default property values to use for elements of + layout.map.layers + pitch + Sets the pitch angle of the map (in degrees, where 0 + means perpendicular to the surface of the map) + (map.pitch). + style + Defines the map layers that are rendered by default + below the trace layers defined in `data`, which are + themselves by default rendered below the layers defined + in `layout.map.layers`. These layers can be defined + either explicitly as a Map Style object which can + contain multiple layer definitions that load data from + any public or private Tile Map Service (TMS or XYZ) or + Web Map Service (WMS) or implicitly by using one of the + built-in style objects which use WMSes or by using a + custom style URL Map Style objects are of the form + described in the MapLibre GL JS documentation available + at https://maplibre.org/maplibre-style-spec/ The + built-in plotly.js styles objects are: basic, carto- + darkmatter, carto-darkmatter-nolabels, carto-positron, + carto-positron-nolabels, carto-voyager, carto-voyager- + nolabels, dark, light, open-street-map, outdoors, + satellite, satellite-streets, streets, white-bg. + uirevision + Controls persistence of user-driven changes in the + view: `center`, `zoom`, `bearing`, `pitch`. Defaults to + `layout.uirevision`. + zoom + Sets the zoom level of the map (map.zoom). + + Returns + ------- + Map + """ + super().__init__("map") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Map +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Map`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("bearing", arg, bearing) + self._set_property("bounds", arg, bounds) + self._set_property("center", arg, center) + self._set_property("domain", arg, domain) + self._set_property("layers", arg, layers) + self._set_property("layerdefaults", arg, layerdefaults) + self._set_property("pitch", arg, pitch) + self._set_property("style", arg, style) + self._set_property("uirevision", arg, uirevision) + self._set_property("zoom", arg, zoom) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_mapbox.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_mapbox.py new file mode 100644 index 0000000000000000000000000000000000000000..b0f5e4e4c3db8d3a2a4dc298161be45a0f75bb02 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_mapbox.py @@ -0,0 +1,452 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Mapbox(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.mapbox" + _valid_props = { + "accesstoken", + "bearing", + "bounds", + "center", + "domain", + "layerdefaults", + "layers", + "pitch", + "style", + "uirevision", + "zoom", + } + + @property + def accesstoken(self): + """ + Sets the mapbox access token to be used for this mapbox map. + Alternatively, the mapbox access token can be set in the + configuration options under `mapboxAccessToken`. Note that + accessToken are only required when `style` (e.g with values : + basic, streets, outdoors, light, dark, satellite, satellite- + streets ) and/or a layout layer references the Mapbox server. + + The 'accesstoken' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["accesstoken"] + + @accesstoken.setter + def accesstoken(self, val): + self["accesstoken"] = val + + @property + def bearing(self): + """ + Sets the bearing angle of the map in degrees counter-clockwise + from North (mapbox.bearing). + + The 'bearing' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["bearing"] + + @bearing.setter + def bearing(self, val): + self["bearing"] = val + + @property + def bounds(self): + """ + The 'bounds' property is an instance of Bounds + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.mapbox.Bounds` + - A dict of string/value properties that will be passed + to the Bounds constructor + + Returns + ------- + plotly.graph_objs.layout.mapbox.Bounds + """ + return self["bounds"] + + @bounds.setter + def bounds(self, val): + self["bounds"] = val + + @property + def center(self): + """ + The 'center' property is an instance of Center + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.mapbox.Center` + - A dict of string/value properties that will be passed + to the Center constructor + + Returns + ------- + plotly.graph_objs.layout.mapbox.Center + """ + return self["center"] + + @center.setter + def center(self, val): + self["center"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.mapbox.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.layout.mapbox.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def layers(self): + """ + The 'layers' property is a tuple of instances of + Layer that may be specified as: + - A list or tuple of instances of plotly.graph_objs.layout.mapbox.Layer + - A list or tuple of dicts of string/value properties that + will be passed to the Layer constructor + + Returns + ------- + tuple[plotly.graph_objs.layout.mapbox.Layer] + """ + return self["layers"] + + @layers.setter + def layers(self, val): + self["layers"] = val + + @property + def layerdefaults(self): + """ + When used in a template (as + layout.template.layout.mapbox.layerdefaults), sets the default + property values to use for elements of layout.mapbox.layers + + The 'layerdefaults' property is an instance of Layer + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.mapbox.Layer` + - A dict of string/value properties that will be passed + to the Layer constructor + + Returns + ------- + plotly.graph_objs.layout.mapbox.Layer + """ + return self["layerdefaults"] + + @layerdefaults.setter + def layerdefaults(self, val): + self["layerdefaults"] = val + + @property + def pitch(self): + """ + Sets the pitch angle of the map (in degrees, where 0 means + perpendicular to the surface of the map) (mapbox.pitch). + + The 'pitch' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["pitch"] + + @pitch.setter + def pitch(self, val): + self["pitch"] = val + + @property + def style(self): + """ + Defines the map layers that are rendered by default below the + trace layers defined in `data`, which are themselves by default + rendered below the layers defined in `layout.mapbox.layers`. + These layers can be defined either explicitly as a Mapbox Style + object which can contain multiple layer definitions that load + data from any public or private Tile Map Service (TMS or XYZ) + or Web Map Service (WMS) or implicitly by using one of the + built-in style objects which use WMSes which do not require any + access tokens, or by using a default Mapbox style or custom + Mapbox style URL, both of which require a Mapbox access token + Note that Mapbox access token can be set in the `accesstoken` + attribute or in the `mapboxAccessToken` config option. Mapbox + Style objects are of the form described in the Mapbox GL JS + documentation available at https://docs.mapbox.com/mapbox-gl- + js/style-spec The built-in plotly.js styles objects are: + carto-darkmatter, carto-positron, open-street-map, stamen- + terrain, stamen-toner, stamen-watercolor, white-bg The built- + in Mapbox styles are: basic, streets, outdoors, light, dark, + satellite, satellite-streets Mapbox style URLs are of the + form: mapbox://mapbox.mapbox-- + + The 'style' property accepts values of any type + + Returns + ------- + Any + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def uirevision(self): + """ + Controls persistence of user-driven changes in the view: + `center`, `zoom`, `bearing`, `pitch`. Defaults to + `layout.uirevision`. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def zoom(self): + """ + Sets the zoom level of the map (mapbox.zoom). + + The 'zoom' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zoom"] + + @zoom.setter + def zoom(self, val): + self["zoom"] = val + + @property + def _prop_descriptions(self): + return """\ + accesstoken + Sets the mapbox access token to be used for this mapbox + map. Alternatively, the mapbox access token can be set + in the configuration options under `mapboxAccessToken`. + Note that accessToken are only required when `style` + (e.g with values : basic, streets, outdoors, light, + dark, satellite, satellite-streets ) and/or a layout + layer references the Mapbox server. + bearing + Sets the bearing angle of the map in degrees counter- + clockwise from North (mapbox.bearing). + bounds + :class:`plotly.graph_objects.layout.mapbox.Bounds` + instance or dict with compatible properties + center + :class:`plotly.graph_objects.layout.mapbox.Center` + instance or dict with compatible properties + domain + :class:`plotly.graph_objects.layout.mapbox.Domain` + instance or dict with compatible properties + layers + A tuple of + :class:`plotly.graph_objects.layout.mapbox.Layer` + instances or dicts with compatible properties + layerdefaults + When used in a template (as + layout.template.layout.mapbox.layerdefaults), sets the + default property values to use for elements of + layout.mapbox.layers + pitch + Sets the pitch angle of the map (in degrees, where 0 + means perpendicular to the surface of the map) + (mapbox.pitch). + style + Defines the map layers that are rendered by default + below the trace layers defined in `data`, which are + themselves by default rendered below the layers defined + in `layout.mapbox.layers`. These layers can be defined + either explicitly as a Mapbox Style object which can + contain multiple layer definitions that load data from + any public or private Tile Map Service (TMS or XYZ) or + Web Map Service (WMS) or implicitly by using one of the + built-in style objects which use WMSes which do not + require any access tokens, or by using a default Mapbox + style or custom Mapbox style URL, both of which require + a Mapbox access token Note that Mapbox access token + can be set in the `accesstoken` attribute or in the + `mapboxAccessToken` config option. Mapbox Style + objects are of the form described in the Mapbox GL JS + documentation available at + https://docs.mapbox.com/mapbox-gl-js/style-spec The + built-in plotly.js styles objects are: carto- + darkmatter, carto-positron, open-street-map, stamen- + terrain, stamen-toner, stamen-watercolor, white-bg The + built-in Mapbox styles are: basic, streets, outdoors, + light, dark, satellite, satellite-streets Mapbox style + URLs are of the form: + mapbox://mapbox.mapbox-- + uirevision + Controls persistence of user-driven changes in the + view: `center`, `zoom`, `bearing`, `pitch`. Defaults to + `layout.uirevision`. + zoom + Sets the zoom level of the map (mapbox.zoom). + """ + + def __init__( + self, + arg=None, + accesstoken=None, + bearing=None, + bounds=None, + center=None, + domain=None, + layers=None, + layerdefaults=None, + pitch=None, + style=None, + uirevision=None, + zoom=None, + **kwargs, + ): + """ + Construct a new Mapbox object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.Mapbox` + accesstoken + Sets the mapbox access token to be used for this mapbox + map. Alternatively, the mapbox access token can be set + in the configuration options under `mapboxAccessToken`. + Note that accessToken are only required when `style` + (e.g with values : basic, streets, outdoors, light, + dark, satellite, satellite-streets ) and/or a layout + layer references the Mapbox server. + bearing + Sets the bearing angle of the map in degrees counter- + clockwise from North (mapbox.bearing). + bounds + :class:`plotly.graph_objects.layout.mapbox.Bounds` + instance or dict with compatible properties + center + :class:`plotly.graph_objects.layout.mapbox.Center` + instance or dict with compatible properties + domain + :class:`plotly.graph_objects.layout.mapbox.Domain` + instance or dict with compatible properties + layers + A tuple of + :class:`plotly.graph_objects.layout.mapbox.Layer` + instances or dicts with compatible properties + layerdefaults + When used in a template (as + layout.template.layout.mapbox.layerdefaults), sets the + default property values to use for elements of + layout.mapbox.layers + pitch + Sets the pitch angle of the map (in degrees, where 0 + means perpendicular to the surface of the map) + (mapbox.pitch). + style + Defines the map layers that are rendered by default + below the trace layers defined in `data`, which are + themselves by default rendered below the layers defined + in `layout.mapbox.layers`. These layers can be defined + either explicitly as a Mapbox Style object which can + contain multiple layer definitions that load data from + any public or private Tile Map Service (TMS or XYZ) or + Web Map Service (WMS) or implicitly by using one of the + built-in style objects which use WMSes which do not + require any access tokens, or by using a default Mapbox + style or custom Mapbox style URL, both of which require + a Mapbox access token Note that Mapbox access token + can be set in the `accesstoken` attribute or in the + `mapboxAccessToken` config option. Mapbox Style + objects are of the form described in the Mapbox GL JS + documentation available at + https://docs.mapbox.com/mapbox-gl-js/style-spec The + built-in plotly.js styles objects are: carto- + darkmatter, carto-positron, open-street-map, stamen- + terrain, stamen-toner, stamen-watercolor, white-bg The + built-in Mapbox styles are: basic, streets, outdoors, + light, dark, satellite, satellite-streets Mapbox style + URLs are of the form: + mapbox://mapbox.mapbox-- + uirevision + Controls persistence of user-driven changes in the + view: `center`, `zoom`, `bearing`, `pitch`. Defaults to + `layout.uirevision`. + zoom + Sets the zoom level of the map (mapbox.zoom). + + Returns + ------- + Mapbox + """ + super().__init__("mapbox") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Mapbox +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Mapbox`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("accesstoken", arg, accesstoken) + self._set_property("bearing", arg, bearing) + self._set_property("bounds", arg, bounds) + self._set_property("center", arg, center) + self._set_property("domain", arg, domain) + self._set_property("layers", arg, layers) + self._set_property("layerdefaults", arg, layerdefaults) + self._set_property("pitch", arg, pitch) + self._set_property("style", arg, style) + self._set_property("uirevision", arg, uirevision) + self._set_property("zoom", arg, zoom) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_margin.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_margin.py new file mode 100644 index 0000000000000000000000000000000000000000..b574b3f9f4eebf04fd20ec96dff94c61ce0a581f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_margin.py @@ -0,0 +1,212 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Margin(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.margin" + _valid_props = {"autoexpand", "b", "l", "pad", "r", "t"} + + @property + def autoexpand(self): + """ + Turns on/off margin expansion computations. Legends, colorbars, + updatemenus, sliders, axis rangeselector and rangeslider are + allowed to push the margins by defaults. + + The 'autoexpand' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autoexpand"] + + @autoexpand.setter + def autoexpand(self, val): + self["autoexpand"] = val + + @property + def b(self): + """ + Sets the bottom margin (in px). + + The 'b' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["b"] + + @b.setter + def b(self, val): + self["b"] = val + + @property + def l(self): + """ + Sets the left margin (in px). + + The 'l' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["l"] + + @l.setter + def l(self, val): + self["l"] = val + + @property + def pad(self): + """ + Sets the amount of padding (in px) between the plotting area + and the axis lines + + The 'pad' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["pad"] + + @pad.setter + def pad(self, val): + self["pad"] = val + + @property + def r(self): + """ + Sets the right margin (in px). + + The 'r' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["r"] + + @r.setter + def r(self, val): + self["r"] = val + + @property + def t(self): + """ + Sets the top margin (in px). + + The 't' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["t"] + + @t.setter + def t(self, val): + self["t"] = val + + @property + def _prop_descriptions(self): + return """\ + autoexpand + Turns on/off margin expansion computations. Legends, + colorbars, updatemenus, sliders, axis rangeselector and + rangeslider are allowed to push the margins by + defaults. + b + Sets the bottom margin (in px). + l + Sets the left margin (in px). + pad + Sets the amount of padding (in px) between the plotting + area and the axis lines + r + Sets the right margin (in px). + t + Sets the top margin (in px). + """ + + def __init__( + self, + arg=None, + autoexpand=None, + b=None, + l=None, + pad=None, + r=None, + t=None, + **kwargs, + ): + """ + Construct a new Margin object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.Margin` + autoexpand + Turns on/off margin expansion computations. Legends, + colorbars, updatemenus, sliders, axis rangeselector and + rangeslider are allowed to push the margins by + defaults. + b + Sets the bottom margin (in px). + l + Sets the left margin (in px). + pad + Sets the amount of padding (in px) between the plotting + area and the axis lines + r + Sets the right margin (in px). + t + Sets the top margin (in px). + + Returns + ------- + Margin + """ + super().__init__("margin") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Margin +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Margin`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autoexpand", arg, autoexpand) + self._set_property("b", arg, b) + self._set_property("l", arg, l) + self._set_property("pad", arg, pad) + self._set_property("r", arg, r) + self._set_property("t", arg, t) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_modebar.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_modebar.py new file mode 100644 index 0000000000000000000000000000000000000000..34b9180f290f473a5644f5cc287405d6dfb8bc45 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_modebar.py @@ -0,0 +1,387 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Modebar(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.modebar" + _valid_props = { + "activecolor", + "add", + "addsrc", + "bgcolor", + "color", + "orientation", + "remove", + "removesrc", + "uirevision", + } + + @property + def activecolor(self): + """ + Sets the color of the active or hovered on icons in the + modebar. + + The 'activecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["activecolor"] + + @activecolor.setter + def activecolor(self, val): + self["activecolor"] = val + + @property + def add(self): + """ + Determines which predefined modebar buttons to add. Please note + that these buttons will only be shown if they are compatible + with all trace types used in a graph. Similar to + `config.modeBarButtonsToAdd` option. This may include + "v1hovermode", "hoverclosest", "hovercompare", "togglehover", + "togglespikelines", "drawline", "drawopenpath", + "drawclosedpath", "drawcircle", "drawrect", "eraseshape". + + The 'add' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["add"] + + @add.setter + def add(self, val): + self["add"] = val + + @property + def addsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `add`. + + The 'addsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["addsrc"] + + @addsrc.setter + def addsrc(self, val): + self["addsrc"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the modebar. + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def color(self): + """ + Sets the color of the icons in the modebar. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def orientation(self): + """ + Sets the orientation of the modebar. + + The 'orientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['v', 'h'] + + Returns + ------- + Any + """ + return self["orientation"] + + @orientation.setter + def orientation(self, val): + self["orientation"] = val + + @property + def remove(self): + """ + Determines which predefined modebar buttons to remove. Similar + to `config.modeBarButtonsToRemove` option. This may include + "autoScale2d", "autoscale", "editInChartStudio", + "editinchartstudio", "hoverCompareCartesian", "hovercompare", + "lasso", "lasso2d", "orbitRotation", "orbitrotation", "pan", + "pan2d", "pan3d", "reset", "resetCameraDefault3d", + "resetCameraLastSave3d", "resetGeo", "resetSankeyGroup", + "resetScale2d", "resetViewMap", "resetViewMapbox", + "resetViews", "resetcameradefault", "resetcameralastsave", + "resetsankeygroup", "resetscale", "resetview", "resetviews", + "select", "select2d", "sendDataToCloud", "senddatatocloud", + "tableRotation", "tablerotation", "toImage", "toggleHover", + "toggleSpikelines", "togglehover", "togglespikelines", + "toimage", "zoom", "zoom2d", "zoom3d", "zoomIn2d", "zoomInGeo", + "zoomInMap", "zoomInMapbox", "zoomOut2d", "zoomOutGeo", + "zoomOutMap", "zoomOutMapbox", "zoomin", "zoomout". + + The 'remove' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["remove"] + + @remove.setter + def remove(self, val): + self["remove"] = val + + @property + def removesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `remove`. + + The 'removesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["removesrc"] + + @removesrc.setter + def removesrc(self, val): + self["removesrc"] = val + + @property + def uirevision(self): + """ + Controls persistence of user-driven changes related to the + modebar, including `hovermode`, `dragmode`, and `showspikes` at + both the root level and inside subplots. Defaults to + `layout.uirevision`. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def _prop_descriptions(self): + return """\ + activecolor + Sets the color of the active or hovered on icons in the + modebar. + add + Determines which predefined modebar buttons to add. + Please note that these buttons will only be shown if + they are compatible with all trace types used in a + graph. Similar to `config.modeBarButtonsToAdd` option. + This may include "v1hovermode", "hoverclosest", + "hovercompare", "togglehover", "togglespikelines", + "drawline", "drawopenpath", "drawclosedpath", + "drawcircle", "drawrect", "eraseshape". + addsrc + Sets the source reference on Chart Studio Cloud for + `add`. + bgcolor + Sets the background color of the modebar. + color + Sets the color of the icons in the modebar. + orientation + Sets the orientation of the modebar. + remove + Determines which predefined modebar buttons to remove. + Similar to `config.modeBarButtonsToRemove` option. This + may include "autoScale2d", "autoscale", + "editInChartStudio", "editinchartstudio", + "hoverCompareCartesian", "hovercompare", "lasso", + "lasso2d", "orbitRotation", "orbitrotation", "pan", + "pan2d", "pan3d", "reset", "resetCameraDefault3d", + "resetCameraLastSave3d", "resetGeo", + "resetSankeyGroup", "resetScale2d", "resetViewMap", + "resetViewMapbox", "resetViews", "resetcameradefault", + "resetcameralastsave", "resetsankeygroup", + "resetscale", "resetview", "resetviews", "select", + "select2d", "sendDataToCloud", "senddatatocloud", + "tableRotation", "tablerotation", "toImage", + "toggleHover", "toggleSpikelines", "togglehover", + "togglespikelines", "toimage", "zoom", "zoom2d", + "zoom3d", "zoomIn2d", "zoomInGeo", "zoomInMap", + "zoomInMapbox", "zoomOut2d", "zoomOutGeo", + "zoomOutMap", "zoomOutMapbox", "zoomin", "zoomout". + removesrc + Sets the source reference on Chart Studio Cloud for + `remove`. + uirevision + Controls persistence of user-driven changes related to + the modebar, including `hovermode`, `dragmode`, and + `showspikes` at both the root level and inside + subplots. Defaults to `layout.uirevision`. + """ + + def __init__( + self, + arg=None, + activecolor=None, + add=None, + addsrc=None, + bgcolor=None, + color=None, + orientation=None, + remove=None, + removesrc=None, + uirevision=None, + **kwargs, + ): + """ + Construct a new Modebar object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.layout.Modebar` + activecolor + Sets the color of the active or hovered on icons in the + modebar. + add + Determines which predefined modebar buttons to add. + Please note that these buttons will only be shown if + they are compatible with all trace types used in a + graph. Similar to `config.modeBarButtonsToAdd` option. + This may include "v1hovermode", "hoverclosest", + "hovercompare", "togglehover", "togglespikelines", + "drawline", "drawopenpath", "drawclosedpath", + "drawcircle", "drawrect", "eraseshape". + addsrc + Sets the source reference on Chart Studio Cloud for + `add`. + bgcolor + Sets the background color of the modebar. + color + Sets the color of the icons in the modebar. + orientation + Sets the orientation of the modebar. + remove + Determines which predefined modebar buttons to remove. + Similar to `config.modeBarButtonsToRemove` option. This + may include "autoScale2d", "autoscale", + "editInChartStudio", "editinchartstudio", + "hoverCompareCartesian", "hovercompare", "lasso", + "lasso2d", "orbitRotation", "orbitrotation", "pan", + "pan2d", "pan3d", "reset", "resetCameraDefault3d", + "resetCameraLastSave3d", "resetGeo", + "resetSankeyGroup", "resetScale2d", "resetViewMap", + "resetViewMapbox", "resetViews", "resetcameradefault", + "resetcameralastsave", "resetsankeygroup", + "resetscale", "resetview", "resetviews", "select", + "select2d", "sendDataToCloud", "senddatatocloud", + "tableRotation", "tablerotation", "toImage", + "toggleHover", "toggleSpikelines", "togglehover", + "togglespikelines", "toimage", "zoom", "zoom2d", + "zoom3d", "zoomIn2d", "zoomInGeo", "zoomInMap", + "zoomInMapbox", "zoomOut2d", "zoomOutGeo", + "zoomOutMap", "zoomOutMapbox", "zoomin", "zoomout". + removesrc + Sets the source reference on Chart Studio Cloud for + `remove`. + uirevision + Controls persistence of user-driven changes related to + the modebar, including `hovermode`, `dragmode`, and + `showspikes` at both the root level and inside + subplots. Defaults to `layout.uirevision`. + + Returns + ------- + Modebar + """ + super().__init__("modebar") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Modebar +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Modebar`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("activecolor", arg, activecolor) + self._set_property("add", arg, add) + self._set_property("addsrc", arg, addsrc) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("color", arg, color) + self._set_property("orientation", arg, orientation) + self._set_property("remove", arg, remove) + self._set_property("removesrc", arg, removesrc) + self._set_property("uirevision", arg, uirevision) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_newselection.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_newselection.py new file mode 100644 index 0000000000000000000000000000000000000000..4f065710fa0fba6814988cf7e381b9afccf4f022 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_newselection.py @@ -0,0 +1,118 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Newselection(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.newselection" + _valid_props = {"line", "mode"} + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.newselection.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.layout.newselection.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def mode(self): + """ + Describes how a new selection is created. If `immediate`, a new + selection is created after first mouse up. If `gradual`, a new + selection is not created after first mouse. By adding to and + subtracting from the initial selection, this option allows + declaring extra outlines of the selection. + + The 'mode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['immediate', 'gradual'] + + Returns + ------- + Any + """ + return self["mode"] + + @mode.setter + def mode(self, val): + self["mode"] = val + + @property + def _prop_descriptions(self): + return """\ + line + :class:`plotly.graph_objects.layout.newselection.Line` + instance or dict with compatible properties + mode + Describes how a new selection is created. If + `immediate`, a new selection is created after first + mouse up. If `gradual`, a new selection is not created + after first mouse. By adding to and subtracting from + the initial selection, this option allows declaring + extra outlines of the selection. + """ + + def __init__(self, arg=None, line=None, mode=None, **kwargs): + """ + Construct a new Newselection object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.layout.Newselection` + line + :class:`plotly.graph_objects.layout.newselection.Line` + instance or dict with compatible properties + mode + Describes how a new selection is created. If + `immediate`, a new selection is created after first + mouse up. If `gradual`, a new selection is not created + after first mouse. By adding to and subtracting from + the initial selection, this option allows declaring + extra outlines of the selection. + + Returns + ------- + Newselection + """ + super().__init__("newselection") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Newselection +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Newselection`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("line", arg, line) + self._set_property("mode", arg, mode) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_newshape.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_newshape.py new file mode 100644 index 0000000000000000000000000000000000000000..269a258664776509080c8c672df676433ac05bd6 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_newshape.py @@ -0,0 +1,543 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Newshape(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.newshape" + _valid_props = { + "drawdirection", + "fillcolor", + "fillrule", + "label", + "layer", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "name", + "opacity", + "showlegend", + "visible", + } + + @property + def drawdirection(self): + """ + When `dragmode` is set to "drawrect", "drawline" or + "drawcircle" this limits the drag to be horizontal, vertical or + diagonal. Using "diagonal" there is no limit e.g. in drawing + lines in any direction. "ortho" limits the draw to be either + horizontal or vertical. "horizontal" allows horizontal extend. + "vertical" allows vertical extend. + + The 'drawdirection' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['ortho', 'horizontal', 'vertical', 'diagonal'] + + Returns + ------- + Any + """ + return self["drawdirection"] + + @drawdirection.setter + def drawdirection(self, val): + self["drawdirection"] = val + + @property + def fillcolor(self): + """ + Sets the color filling new shapes' interior. Please note that + if using a fillcolor with alpha greater than half, drag inside + the active shape starts moving the shape underneath, otherwise + a new shape could be started over. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def fillrule(self): + """ + Determines the path's interior. For more info please visit + https://developer.mozilla.org/en- + US/docs/Web/SVG/Attribute/fill-rule + + The 'fillrule' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['evenodd', 'nonzero'] + + Returns + ------- + Any + """ + return self["fillrule"] + + @fillrule.setter + def fillrule(self, val): + self["fillrule"] = val + + @property + def label(self): + """ + The 'label' property is an instance of Label + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.newshape.Label` + - A dict of string/value properties that will be passed + to the Label constructor + + Returns + ------- + plotly.graph_objs.layout.newshape.Label + """ + return self["label"] + + @label.setter + def label(self, val): + self["label"] = val + + @property + def layer(self): + """ + Specifies whether new shapes are drawn below gridlines + ("below"), between gridlines and traces ("between") or above + traces ("above"). + + The 'layer' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['below', 'above', 'between'] + + Returns + ------- + Any + """ + return self["layer"] + + @layer.setter + def layer(self, val): + self["layer"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show new shape in. References + to these legends are "legend", "legend2", "legend3", etc. + Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for new shape. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.newshape.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.layout.newshape.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for new shape. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for new shape. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.newshape.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.layout.newshape.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def name(self): + """ + Sets new shape name. The name appears as the legend item. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of new shapes. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def showlegend(self): + """ + Determines whether or not new shape is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def visible(self): + """ + Determines whether or not new shape is visible. If + "legendonly", the shape is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def _prop_descriptions(self): + return """\ + drawdirection + When `dragmode` is set to "drawrect", "drawline" or + "drawcircle" this limits the drag to be horizontal, + vertical or diagonal. Using "diagonal" there is no + limit e.g. in drawing lines in any direction. "ortho" + limits the draw to be either horizontal or vertical. + "horizontal" allows horizontal extend. "vertical" + allows vertical extend. + fillcolor + Sets the color filling new shapes' interior. Please + note that if using a fillcolor with alpha greater than + half, drag inside the active shape starts moving the + shape underneath, otherwise a new shape could be + started over. + fillrule + Determines the path's interior. For more info please + visit https://developer.mozilla.org/en- + US/docs/Web/SVG/Attribute/fill-rule + label + :class:`plotly.graph_objects.layout.newshape.Label` + instance or dict with compatible properties + layer + Specifies whether new shapes are drawn below gridlines + ("below"), between gridlines and traces ("between") or + above traces ("above"). + legend + Sets the reference to a legend to show new shape in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for new shape. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.layout.newshape.Legendgrou + ptitle` instance or dict with compatible properties + legendrank + Sets the legend rank for new shape. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. + legendwidth + Sets the width (in px or fraction) of the legend for + new shape. + line + :class:`plotly.graph_objects.layout.newshape.Line` + instance or dict with compatible properties + name + Sets new shape name. The name appears as the legend + item. + opacity + Sets the opacity of new shapes. + showlegend + Determines whether or not new shape is shown in the + legend. + visible + Determines whether or not new shape is visible. If + "legendonly", the shape is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + """ + + def __init__( + self, + arg=None, + drawdirection=None, + fillcolor=None, + fillrule=None, + label=None, + layer=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + name=None, + opacity=None, + showlegend=None, + visible=None, + **kwargs, + ): + """ + Construct a new Newshape object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.layout.Newshape` + drawdirection + When `dragmode` is set to "drawrect", "drawline" or + "drawcircle" this limits the drag to be horizontal, + vertical or diagonal. Using "diagonal" there is no + limit e.g. in drawing lines in any direction. "ortho" + limits the draw to be either horizontal or vertical. + "horizontal" allows horizontal extend. "vertical" + allows vertical extend. + fillcolor + Sets the color filling new shapes' interior. Please + note that if using a fillcolor with alpha greater than + half, drag inside the active shape starts moving the + shape underneath, otherwise a new shape could be + started over. + fillrule + Determines the path's interior. For more info please + visit https://developer.mozilla.org/en- + US/docs/Web/SVG/Attribute/fill-rule + label + :class:`plotly.graph_objects.layout.newshape.Label` + instance or dict with compatible properties + layer + Specifies whether new shapes are drawn below gridlines + ("below"), between gridlines and traces ("between") or + above traces ("above"). + legend + Sets the reference to a legend to show new shape in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for new shape. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.layout.newshape.Legendgrou + ptitle` instance or dict with compatible properties + legendrank + Sets the legend rank for new shape. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. + legendwidth + Sets the width (in px or fraction) of the legend for + new shape. + line + :class:`plotly.graph_objects.layout.newshape.Line` + instance or dict with compatible properties + name + Sets new shape name. The name appears as the legend + item. + opacity + Sets the opacity of new shapes. + showlegend + Determines whether or not new shape is shown in the + legend. + visible + Determines whether or not new shape is visible. If + "legendonly", the shape is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + + Returns + ------- + Newshape + """ + super().__init__("newshape") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Newshape +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Newshape`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("drawdirection", arg, drawdirection) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("fillrule", arg, fillrule) + self._set_property("label", arg, label) + self._set_property("layer", arg, layer) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("showlegend", arg, showlegend) + self._set_property("visible", arg, visible) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_polar.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_polar.py new file mode 100644 index 0000000000000000000000000000000000000000..51d76209a0d5e4431be4bd4b9f045e4f61258185 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_polar.py @@ -0,0 +1,382 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Polar(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.polar" + _valid_props = { + "angularaxis", + "bargap", + "barmode", + "bgcolor", + "domain", + "gridshape", + "hole", + "radialaxis", + "sector", + "uirevision", + } + + @property + def angularaxis(self): + """ + The 'angularaxis' property is an instance of AngularAxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.polar.AngularAxis` + - A dict of string/value properties that will be passed + to the AngularAxis constructor + + Returns + ------- + plotly.graph_objs.layout.polar.AngularAxis + """ + return self["angularaxis"] + + @angularaxis.setter + def angularaxis(self, val): + self["angularaxis"] = val + + @property + def bargap(self): + """ + Sets the gap between bars of adjacent location coordinates. + Values are unitless, they represent fractions of the minimum + difference in bar positions in the data. + + The 'bargap' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["bargap"] + + @bargap.setter + def bargap(self, val): + self["bargap"] = val + + @property + def barmode(self): + """ + Determines how bars at the same location coordinate are + displayed on the graph. With "stack", the bars are stacked on + top of one another With "overlay", the bars are plotted over + one another, you might need to reduce "opacity" to see multiple + bars. + + The 'barmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['stack', 'overlay'] + + Returns + ------- + Any + """ + return self["barmode"] + + @barmode.setter + def barmode(self, val): + self["barmode"] = val + + @property + def bgcolor(self): + """ + Set the background color of the subplot + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.polar.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.layout.polar.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def gridshape(self): + """ + Determines if the radial axis grid lines and angular axis line + are drawn as "circular" sectors or as "linear" (polygon) + sectors. Has an effect only when the angular axis has `type` + "category". Note that `radialaxis.angle` is snapped to the + angle of the closest vertex when `gridshape` is "circular" (so + that radial axis scale is the same as the data scale). + + The 'gridshape' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['circular', 'linear'] + + Returns + ------- + Any + """ + return self["gridshape"] + + @gridshape.setter + def gridshape(self, val): + self["gridshape"] = val + + @property + def hole(self): + """ + Sets the fraction of the radius to cut out of the polar + subplot. + + The 'hole' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["hole"] + + @hole.setter + def hole(self, val): + self["hole"] = val + + @property + def radialaxis(self): + """ + The 'radialaxis' property is an instance of RadialAxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.polar.RadialAxis` + - A dict of string/value properties that will be passed + to the RadialAxis constructor + + Returns + ------- + plotly.graph_objs.layout.polar.RadialAxis + """ + return self["radialaxis"] + + @radialaxis.setter + def radialaxis(self, val): + self["radialaxis"] = val + + @property + def sector(self): + """ + Sets angular span of this polar subplot with two angles (in + degrees). Sector are assumed to be spanned in the + counterclockwise direction with 0 corresponding to rightmost + limit of the polar subplot. + + The 'sector' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'sector[0]' property is a number and may be specified as: + - An int or float + (1) The 'sector[1]' property is a number and may be specified as: + - An int or float + + Returns + ------- + list + """ + return self["sector"] + + @sector.setter + def sector(self, val): + self["sector"] = val + + @property + def uirevision(self): + """ + Controls persistence of user-driven changes in axis attributes, + if not overridden in the individual axes. Defaults to + `layout.uirevision`. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def _prop_descriptions(self): + return """\ + angularaxis + :class:`plotly.graph_objects.layout.polar.AngularAxis` + instance or dict with compatible properties + bargap + Sets the gap between bars of adjacent location + coordinates. Values are unitless, they represent + fractions of the minimum difference in bar positions in + the data. + barmode + Determines how bars at the same location coordinate are + displayed on the graph. With "stack", the bars are + stacked on top of one another With "overlay", the bars + are plotted over one another, you might need to reduce + "opacity" to see multiple bars. + bgcolor + Set the background color of the subplot + domain + :class:`plotly.graph_objects.layout.polar.Domain` + instance or dict with compatible properties + gridshape + Determines if the radial axis grid lines and angular + axis line are drawn as "circular" sectors or as + "linear" (polygon) sectors. Has an effect only when the + angular axis has `type` "category". Note that + `radialaxis.angle` is snapped to the angle of the + closest vertex when `gridshape` is "circular" (so that + radial axis scale is the same as the data scale). + hole + Sets the fraction of the radius to cut out of the polar + subplot. + radialaxis + :class:`plotly.graph_objects.layout.polar.RadialAxis` + instance or dict with compatible properties + sector + Sets angular span of this polar subplot with two angles + (in degrees). Sector are assumed to be spanned in the + counterclockwise direction with 0 corresponding to + rightmost limit of the polar subplot. + uirevision + Controls persistence of user-driven changes in axis + attributes, if not overridden in the individual axes. + Defaults to `layout.uirevision`. + """ + + def __init__( + self, + arg=None, + angularaxis=None, + bargap=None, + barmode=None, + bgcolor=None, + domain=None, + gridshape=None, + hole=None, + radialaxis=None, + sector=None, + uirevision=None, + **kwargs, + ): + """ + Construct a new Polar object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.Polar` + angularaxis + :class:`plotly.graph_objects.layout.polar.AngularAxis` + instance or dict with compatible properties + bargap + Sets the gap between bars of adjacent location + coordinates. Values are unitless, they represent + fractions of the minimum difference in bar positions in + the data. + barmode + Determines how bars at the same location coordinate are + displayed on the graph. With "stack", the bars are + stacked on top of one another With "overlay", the bars + are plotted over one another, you might need to reduce + "opacity" to see multiple bars. + bgcolor + Set the background color of the subplot + domain + :class:`plotly.graph_objects.layout.polar.Domain` + instance or dict with compatible properties + gridshape + Determines if the radial axis grid lines and angular + axis line are drawn as "circular" sectors or as + "linear" (polygon) sectors. Has an effect only when the + angular axis has `type` "category". Note that + `radialaxis.angle` is snapped to the angle of the + closest vertex when `gridshape` is "circular" (so that + radial axis scale is the same as the data scale). + hole + Sets the fraction of the radius to cut out of the polar + subplot. + radialaxis + :class:`plotly.graph_objects.layout.polar.RadialAxis` + instance or dict with compatible properties + sector + Sets angular span of this polar subplot with two angles + (in degrees). Sector are assumed to be spanned in the + counterclockwise direction with 0 corresponding to + rightmost limit of the polar subplot. + uirevision + Controls persistence of user-driven changes in axis + attributes, if not overridden in the individual axes. + Defaults to `layout.uirevision`. + + Returns + ------- + Polar + """ + super().__init__("polar") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Polar +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Polar`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("angularaxis", arg, angularaxis) + self._set_property("bargap", arg, bargap) + self._set_property("barmode", arg, barmode) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("domain", arg, domain) + self._set_property("gridshape", arg, gridshape) + self._set_property("hole", arg, hole) + self._set_property("radialaxis", arg, radialaxis) + self._set_property("sector", arg, sector) + self._set_property("uirevision", arg, uirevision) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_scene.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_scene.py new file mode 100644 index 0000000000000000000000000000000000000000..2d08ae1b23b2bd81c07a86d9b19da132228f1130 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_scene.py @@ -0,0 +1,454 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Scene(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.scene" + _valid_props = { + "annotationdefaults", + "annotations", + "aspectmode", + "aspectratio", + "bgcolor", + "camera", + "domain", + "dragmode", + "hovermode", + "uirevision", + "xaxis", + "yaxis", + "zaxis", + } + + @property + def annotations(self): + """ + The 'annotations' property is a tuple of instances of + Annotation that may be specified as: + - A list or tuple of instances of plotly.graph_objs.layout.scene.Annotation + - A list or tuple of dicts of string/value properties that + will be passed to the Annotation constructor + + Returns + ------- + tuple[plotly.graph_objs.layout.scene.Annotation] + """ + return self["annotations"] + + @annotations.setter + def annotations(self, val): + self["annotations"] = val + + @property + def annotationdefaults(self): + """ + When used in a template (as + layout.template.layout.scene.annotationdefaults), sets the + default property values to use for elements of + layout.scene.annotations + + The 'annotationdefaults' property is an instance of Annotation + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.scene.Annotation` + - A dict of string/value properties that will be passed + to the Annotation constructor + + Returns + ------- + plotly.graph_objs.layout.scene.Annotation + """ + return self["annotationdefaults"] + + @annotationdefaults.setter + def annotationdefaults(self, val): + self["annotationdefaults"] = val + + @property + def aspectmode(self): + """ + If "cube", this scene's axes are drawn as a cube, regardless of + the axes' ranges. If "data", this scene's axes are drawn in + proportion with the axes' ranges. If "manual", this scene's + axes are drawn in proportion with the input of "aspectratio" + (the default behavior if "aspectratio" is provided). If "auto", + this scene's axes are drawn using the results of "data" except + when one axis is more than four times the size of the two + others, where in that case the results of "cube" are used. + + The 'aspectmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'cube', 'data', 'manual'] + + Returns + ------- + Any + """ + return self["aspectmode"] + + @aspectmode.setter + def aspectmode(self, val): + self["aspectmode"] = val + + @property + def aspectratio(self): + """ + Sets this scene's axis aspectratio. + + The 'aspectratio' property is an instance of Aspectratio + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.scene.Aspectratio` + - A dict of string/value properties that will be passed + to the Aspectratio constructor + + Returns + ------- + plotly.graph_objs.layout.scene.Aspectratio + """ + return self["aspectratio"] + + @aspectratio.setter + def aspectratio(self, val): + self["aspectratio"] = val + + @property + def bgcolor(self): + """ + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def camera(self): + """ + The 'camera' property is an instance of Camera + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.scene.Camera` + - A dict of string/value properties that will be passed + to the Camera constructor + + Returns + ------- + plotly.graph_objs.layout.scene.Camera + """ + return self["camera"] + + @camera.setter + def camera(self, val): + self["camera"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.scene.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.layout.scene.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def dragmode(self): + """ + Determines the mode of drag interactions for this scene. + + The 'dragmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['orbit', 'turntable', 'zoom', 'pan', False] + + Returns + ------- + Any + """ + return self["dragmode"] + + @dragmode.setter + def dragmode(self, val): + self["dragmode"] = val + + @property + def hovermode(self): + """ + Determines the mode of hover interactions for this scene. + + The 'hovermode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['closest', False] + + Returns + ------- + Any + """ + return self["hovermode"] + + @hovermode.setter + def hovermode(self, val): + self["hovermode"] = val + + @property + def uirevision(self): + """ + Controls persistence of user-driven changes in camera + attributes. Defaults to `layout.uirevision`. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def xaxis(self): + """ + The 'xaxis' property is an instance of XAxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.scene.XAxis` + - A dict of string/value properties that will be passed + to the XAxis constructor + + Returns + ------- + plotly.graph_objs.layout.scene.XAxis + """ + return self["xaxis"] + + @xaxis.setter + def xaxis(self, val): + self["xaxis"] = val + + @property + def yaxis(self): + """ + The 'yaxis' property is an instance of YAxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.scene.YAxis` + - A dict of string/value properties that will be passed + to the YAxis constructor + + Returns + ------- + plotly.graph_objs.layout.scene.YAxis + """ + return self["yaxis"] + + @yaxis.setter + def yaxis(self, val): + self["yaxis"] = val + + @property + def zaxis(self): + """ + The 'zaxis' property is an instance of ZAxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.scene.ZAxis` + - A dict of string/value properties that will be passed + to the ZAxis constructor + + Returns + ------- + plotly.graph_objs.layout.scene.ZAxis + """ + return self["zaxis"] + + @zaxis.setter + def zaxis(self, val): + self["zaxis"] = val + + @property + def _prop_descriptions(self): + return """\ + annotations + A tuple of + :class:`plotly.graph_objects.layout.scene.Annotation` + instances or dicts with compatible properties + annotationdefaults + When used in a template (as + layout.template.layout.scene.annotationdefaults), sets + the default property values to use for elements of + layout.scene.annotations + aspectmode + If "cube", this scene's axes are drawn as a cube, + regardless of the axes' ranges. If "data", this scene's + axes are drawn in proportion with the axes' ranges. If + "manual", this scene's axes are drawn in proportion + with the input of "aspectratio" (the default behavior + if "aspectratio" is provided). If "auto", this scene's + axes are drawn using the results of "data" except when + one axis is more than four times the size of the two + others, where in that case the results of "cube" are + used. + aspectratio + Sets this scene's axis aspectratio. + bgcolor + + camera + :class:`plotly.graph_objects.layout.scene.Camera` + instance or dict with compatible properties + domain + :class:`plotly.graph_objects.layout.scene.Domain` + instance or dict with compatible properties + dragmode + Determines the mode of drag interactions for this + scene. + hovermode + Determines the mode of hover interactions for this + scene. + uirevision + Controls persistence of user-driven changes in camera + attributes. Defaults to `layout.uirevision`. + xaxis + :class:`plotly.graph_objects.layout.scene.XAxis` + instance or dict with compatible properties + yaxis + :class:`plotly.graph_objects.layout.scene.YAxis` + instance or dict with compatible properties + zaxis + :class:`plotly.graph_objects.layout.scene.ZAxis` + instance or dict with compatible properties + """ + + def __init__( + self, + arg=None, + annotations=None, + annotationdefaults=None, + aspectmode=None, + aspectratio=None, + bgcolor=None, + camera=None, + domain=None, + dragmode=None, + hovermode=None, + uirevision=None, + xaxis=None, + yaxis=None, + zaxis=None, + **kwargs, + ): + """ + Construct a new Scene object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.Scene` + annotations + A tuple of + :class:`plotly.graph_objects.layout.scene.Annotation` + instances or dicts with compatible properties + annotationdefaults + When used in a template (as + layout.template.layout.scene.annotationdefaults), sets + the default property values to use for elements of + layout.scene.annotations + aspectmode + If "cube", this scene's axes are drawn as a cube, + regardless of the axes' ranges. If "data", this scene's + axes are drawn in proportion with the axes' ranges. If + "manual", this scene's axes are drawn in proportion + with the input of "aspectratio" (the default behavior + if "aspectratio" is provided). If "auto", this scene's + axes are drawn using the results of "data" except when + one axis is more than four times the size of the two + others, where in that case the results of "cube" are + used. + aspectratio + Sets this scene's axis aspectratio. + bgcolor + + camera + :class:`plotly.graph_objects.layout.scene.Camera` + instance or dict with compatible properties + domain + :class:`plotly.graph_objects.layout.scene.Domain` + instance or dict with compatible properties + dragmode + Determines the mode of drag interactions for this + scene. + hovermode + Determines the mode of hover interactions for this + scene. + uirevision + Controls persistence of user-driven changes in camera + attributes. Defaults to `layout.uirevision`. + xaxis + :class:`plotly.graph_objects.layout.scene.XAxis` + instance or dict with compatible properties + yaxis + :class:`plotly.graph_objects.layout.scene.YAxis` + instance or dict with compatible properties + zaxis + :class:`plotly.graph_objects.layout.scene.ZAxis` + instance or dict with compatible properties + + Returns + ------- + Scene + """ + super().__init__("scene") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Scene +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Scene`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("annotations", arg, annotations) + self._set_property("annotationdefaults", arg, annotationdefaults) + self._set_property("aspectmode", arg, aspectmode) + self._set_property("aspectratio", arg, aspectratio) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("camera", arg, camera) + self._set_property("domain", arg, domain) + self._set_property("dragmode", arg, dragmode) + self._set_property("hovermode", arg, hovermode) + self._set_property("uirevision", arg, uirevision) + self._set_property("xaxis", arg, xaxis) + self._set_property("yaxis", arg, yaxis) + self._set_property("zaxis", arg, zaxis) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_selection.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_selection.py new file mode 100644 index 0000000000000000000000000000000000000000..3ebf7419c326133c744f471c35101134b9bce023 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_selection.py @@ -0,0 +1,493 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Selection(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.selection" + _valid_props = { + "line", + "name", + "opacity", + "path", + "templateitemname", + "type", + "x0", + "x1", + "xref", + "y0", + "y1", + "yref", + } + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.selection.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.layout.selection.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def name(self): + """ + When used in a template, named items are created in the output + figure in addition to any items the figure already has in this + array. You can modify these items in the output figure by + making your own item with `templateitemname` matching this + `name` alongside your modifications (including `visible: false` + or `enabled: false` to hide it). Has no effect outside of a + template. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the selection. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def path(self): + """ + For `type` "path" - a valid SVG path similar to `shapes.path` + in data coordinates. Allowed segments are: M, L and Z. + + The 'path' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["path"] + + @path.setter + def path(self, val): + self["path"] = val + + @property + def templateitemname(self): + """ + Used to refer to a named item in this array in the template. + Named items from the template will be created even without a + matching item in the input figure, but you can modify one by + making an item with `templateitemname` matching its `name`, + alongside your modifications (including `visible: false` or + `enabled: false` to hide it). If there is no template or no + matching item, this item will be hidden unless you explicitly + show it with `visible: true`. + + The 'templateitemname' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["templateitemname"] + + @templateitemname.setter + def templateitemname(self, val): + self["templateitemname"] = val + + @property + def type(self): + """ + Specifies the selection type to be drawn. If "rect", a + rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), + (`x1`,`y1`) and (`x0`,`y1`). If "path", draw a custom SVG path + using `path`. + + The 'type' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['rect', 'path'] + + Returns + ------- + Any + """ + return self["type"] + + @type.setter + def type(self, val): + self["type"] = val + + @property + def x0(self): + """ + Sets the selection's starting x position. + + The 'x0' property accepts values of any type + + Returns + ------- + Any + """ + return self["x0"] + + @x0.setter + def x0(self, val): + self["x0"] = val + + @property + def x1(self): + """ + Sets the selection's end x position. + + The 'x1' property accepts values of any type + + Returns + ------- + Any + """ + return self["x1"] + + @x1.setter + def x1(self, val): + self["x1"] = val + + @property + def xref(self): + """ + Sets the selection's x coordinate axis. If set to a x axis id + (e.g. "x" or "x2"), the `x` position refers to a x coordinate. + If set to "paper", the `x` position refers to the distance from + the left of the plotting area in normalized coordinates where 0 + (1) corresponds to the left (right). If set to a x axis ID + followed by "domain" (separated by a space), the position + behaves like for "paper", but refers to the distance in + fractions of the domain length from the left of the domain of + that axis: e.g., *x2 domain* refers to the domain of the second + x axis and a x position of 0.5 refers to the point between the + left and the right of the domain of the second x axis. + + The 'xref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['paper'] + - A string that matches one of the following regular expressions: + ['^x([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["xref"] + + @xref.setter + def xref(self, val): + self["xref"] = val + + @property + def y0(self): + """ + Sets the selection's starting y position. + + The 'y0' property accepts values of any type + + Returns + ------- + Any + """ + return self["y0"] + + @y0.setter + def y0(self, val): + self["y0"] = val + + @property + def y1(self): + """ + Sets the selection's end y position. + + The 'y1' property accepts values of any type + + Returns + ------- + Any + """ + return self["y1"] + + @y1.setter + def y1(self, val): + self["y1"] = val + + @property + def yref(self): + """ + Sets the selection's x coordinate axis. If set to a y axis id + (e.g. "y" or "y2"), the `y` position refers to a y coordinate. + If set to "paper", the `y` position refers to the distance from + the bottom of the plotting area in normalized coordinates where + 0 (1) corresponds to the bottom (top). If set to a y axis ID + followed by "domain" (separated by a space), the position + behaves like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the domain of + that axis: e.g., *y2 domain* refers to the domain of the second + y axis and a y position of 0.5 refers to the point between the + bottom and the top of the domain of the second y axis. + + The 'yref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['paper'] + - A string that matches one of the following regular expressions: + ['^y([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["yref"] + + @yref.setter + def yref(self, val): + self["yref"] = val + + @property + def _prop_descriptions(self): + return """\ + line + :class:`plotly.graph_objects.layout.selection.Line` + instance or dict with compatible properties + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the selection. + path + For `type` "path" - a valid SVG path similar to + `shapes.path` in data coordinates. Allowed segments + are: M, L and Z. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + type + Specifies the selection type to be drawn. If "rect", a + rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), + (`x1`,`y1`) and (`x0`,`y1`). If "path", draw a custom + SVG path using `path`. + x0 + Sets the selection's starting x position. + x1 + Sets the selection's end x position. + xref + Sets the selection's x coordinate axis. If set to a x + axis id (e.g. "x" or "x2"), the `x` position refers to + a x coordinate. If set to "paper", the `x` position + refers to the distance from the left of the plotting + area in normalized coordinates where 0 (1) corresponds + to the left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + y0 + Sets the selection's starting y position. + y1 + Sets the selection's end y position. + yref + Sets the selection's x coordinate axis. If set to a y + axis id (e.g. "y" or "y2"), the `y` position refers to + a y coordinate. If set to "paper", the `y` position + refers to the distance from the bottom of the plotting + area in normalized coordinates where 0 (1) corresponds + to the bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + """ + + def __init__( + self, + arg=None, + line=None, + name=None, + opacity=None, + path=None, + templateitemname=None, + type=None, + x0=None, + x1=None, + xref=None, + y0=None, + y1=None, + yref=None, + **kwargs, + ): + """ + Construct a new Selection object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.layout.Selection` + line + :class:`plotly.graph_objects.layout.selection.Line` + instance or dict with compatible properties + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the selection. + path + For `type` "path" - a valid SVG path similar to + `shapes.path` in data coordinates. Allowed segments + are: M, L and Z. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + type + Specifies the selection type to be drawn. If "rect", a + rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), + (`x1`,`y1`) and (`x0`,`y1`). If "path", draw a custom + SVG path using `path`. + x0 + Sets the selection's starting x position. + x1 + Sets the selection's end x position. + xref + Sets the selection's x coordinate axis. If set to a x + axis id (e.g. "x" or "x2"), the `x` position refers to + a x coordinate. If set to "paper", the `x` position + refers to the distance from the left of the plotting + area in normalized coordinates where 0 (1) corresponds + to the left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + y0 + Sets the selection's starting y position. + y1 + Sets the selection's end y position. + yref + Sets the selection's x coordinate axis. If set to a y + axis id (e.g. "y" or "y2"), the `y` position refers to + a y coordinate. If set to "paper", the `y` position + refers to the distance from the bottom of the plotting + area in normalized coordinates where 0 (1) corresponds + to the bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + + Returns + ------- + Selection + """ + super().__init__("selections") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Selection +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Selection`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("line", arg, line) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("path", arg, path) + self._set_property("templateitemname", arg, templateitemname) + self._set_property("type", arg, type) + self._set_property("x0", arg, x0) + self._set_property("x1", arg, x1) + self._set_property("xref", arg, xref) + self._set_property("y0", arg, y0) + self._set_property("y1", arg, y1) + self._set_property("yref", arg, yref) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_shape.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_shape.py new file mode 100644 index 0000000000000000000000000000000000000000..480bfa440bf26febe160aa7b5106eb2a347b469f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_shape.py @@ -0,0 +1,1287 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Shape(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.shape" + _valid_props = { + "editable", + "fillcolor", + "fillrule", + "label", + "layer", + "legend", + "legendgroup", + "legendgrouptitle", + "legendrank", + "legendwidth", + "line", + "name", + "opacity", + "path", + "showlegend", + "templateitemname", + "type", + "visible", + "x0", + "x0shift", + "x1", + "x1shift", + "xanchor", + "xref", + "xsizemode", + "y0", + "y0shift", + "y1", + "y1shift", + "yanchor", + "yref", + "ysizemode", + } + + @property + def editable(self): + """ + Determines whether the shape could be activated for edit or + not. Has no effect when the older editable shapes mode is + enabled via `config.editable` or `config.edits.shapePosition`. + + The 'editable' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["editable"] + + @editable.setter + def editable(self, val): + self["editable"] = val + + @property + def fillcolor(self): + """ + Sets the color filling the shape's interior. Only applies to + closed shapes. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def fillrule(self): + """ + Determines which regions of complex paths constitute the + interior. For more info please visit + https://developer.mozilla.org/en- + US/docs/Web/SVG/Attribute/fill-rule + + The 'fillrule' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['evenodd', 'nonzero'] + + Returns + ------- + Any + """ + return self["fillrule"] + + @fillrule.setter + def fillrule(self, val): + self["fillrule"] = val + + @property + def label(self): + """ + The 'label' property is an instance of Label + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.shape.Label` + - A dict of string/value properties that will be passed + to the Label constructor + + Returns + ------- + plotly.graph_objs.layout.shape.Label + """ + return self["label"] + + @label.setter + def label(self, val): + self["label"] = val + + @property + def layer(self): + """ + Specifies whether shapes are drawn below gridlines ("below"), + between gridlines and traces ("between") or above traces + ("above"). + + The 'layer' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['below', 'above', 'between'] + + Returns + ------- + Any + """ + return self["layer"] + + @layer.setter + def layer(self, val): + self["layer"] = val + + @property + def legend(self): + """ + Sets the reference to a legend to show this shape in. + References to these legends are "legend", "legend2", "legend3", + etc. Settings for these legends are set in the layout, under + `layout.legend`, `layout.legend2`, etc. + + The 'legend' property is an identifier of a particular + subplot, of type 'legend', that may be specified as: + - the string 'legend' optionally followed by an integer >= 1 + (e.g. 'legend', 'legend1', 'legend2', 'legend3', etc.) + + Returns + ------- + str + """ + return self["legend"] + + @legend.setter + def legend(self, val): + self["legend"] = val + + @property + def legendgroup(self): + """ + Sets the legend group for this shape. Traces and shapes part of + the same legend group hide/show at the same time when toggling + legend items. + + The 'legendgroup' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["legendgroup"] + + @legendgroup.setter + def legendgroup(self, val): + self["legendgroup"] = val + + @property + def legendgrouptitle(self): + """ + The 'legendgrouptitle' property is an instance of Legendgrouptitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.shape.Legendgrouptitle` + - A dict of string/value properties that will be passed + to the Legendgrouptitle constructor + + Returns + ------- + plotly.graph_objs.layout.shape.Legendgrouptitle + """ + return self["legendgrouptitle"] + + @legendgrouptitle.setter + def legendgrouptitle(self, val): + self["legendgrouptitle"] = val + + @property + def legendrank(self): + """ + Sets the legend rank for this shape. Items and groups with + smaller ranks are presented on top/left side while with + "reversed" `legend.traceorder` they are on bottom/right side. + The default legendrank is 1000, so that you can use ranks less + than 1000 to place certain items before all unranked items, and + ranks greater than 1000 to go after all unranked items. When + having unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and layout. + + The 'legendrank' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["legendrank"] + + @legendrank.setter + def legendrank(self, val): + self["legendrank"] = val + + @property + def legendwidth(self): + """ + Sets the width (in px or fraction) of the legend for this + shape. + + The 'legendwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["legendwidth"] + + @legendwidth.setter + def legendwidth(self, val): + self["legendwidth"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.shape.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.layout.shape.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def name(self): + """ + When used in a template, named items are created in the output + figure in addition to any items the figure already has in this + array. You can modify these items in the output figure by + making your own item with `templateitemname` matching this + `name` alongside your modifications (including `visible: false` + or `enabled: false` to hide it). Has no effect outside of a + template. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def opacity(self): + """ + Sets the opacity of the shape. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def path(self): + """ + For `type` "path" - a valid SVG path with the pixel values + replaced by data values in `xsizemode`/`ysizemode` being + "scaled" and taken unmodified as pixels relative to `xanchor` + and `yanchor` in case of "pixel" size mode. There are a few + restrictions / quirks only absolute instructions, not relative. + So the allowed segments are: M, L, H, V, Q, C, T, S, and Z arcs + (A) are not allowed because radius rx and ry are relative. In + the future we could consider supporting relative commands, but + we would have to decide on how to handle date and log axes. + Note that even as is, Q and C Bezier paths that are smooth on + linear axes may not be smooth on log, and vice versa. no + chained "polybezier" commands - specify the segment type for + each one. On category axes, values are numbers scaled to the + serial numbers of categories because using the categories + themselves there would be no way to describe fractional + positions On data axes: because space and T are both normal + components of path strings, we can't use either to separate + date from time parts. Therefore we'll use underscore for this + purpose: 2015-02-21_13:45:56.789 + + The 'path' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["path"] + + @path.setter + def path(self, val): + self["path"] = val + + @property + def showlegend(self): + """ + Determines whether or not this shape is shown in the legend. + + The 'showlegend' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showlegend"] + + @showlegend.setter + def showlegend(self, val): + self["showlegend"] = val + + @property + def templateitemname(self): + """ + Used to refer to a named item in this array in the template. + Named items from the template will be created even without a + matching item in the input figure, but you can modify one by + making an item with `templateitemname` matching its `name`, + alongside your modifications (including `visible: false` or + `enabled: false` to hide it). If there is no template or no + matching item, this item will be hidden unless you explicitly + show it with `visible: true`. + + The 'templateitemname' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["templateitemname"] + + @templateitemname.setter + def templateitemname(self, val): + self["templateitemname"] = val + + @property + def type(self): + """ + Specifies the shape type to be drawn. If "line", a line is + drawn from (`x0`,`y0`) to (`x1`,`y1`) with respect to the axes' + sizing mode. If "circle", a circle is drawn from + ((`x0`+`x1`)/2, (`y0`+`y1`)/2)) with radius (|(`x0`+`x1`)/2 - + `x0`|, |(`y0`+`y1`)/2 -`y0`)|) with respect to the axes' sizing + mode. If "rect", a rectangle is drawn linking (`x0`,`y0`), + (`x1`,`y0`), (`x1`,`y1`), (`x0`,`y1`), (`x0`,`y0`) with respect + to the axes' sizing mode. If "path", draw a custom SVG path + using `path`. with respect to the axes' sizing mode. + + The 'type' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['circle', 'rect', 'path', 'line'] + + Returns + ------- + Any + """ + return self["type"] + + @type.setter + def type(self, val): + self["type"] = val + + @property + def visible(self): + """ + Determines whether or not this shape is visible. If + "legendonly", the shape is not drawn, but can appear as a + legend item (provided that the legend itself is visible). + + The 'visible' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'legendonly'] + + Returns + ------- + Any + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x0(self): + """ + Sets the shape's starting x position. See `type` and + `xsizemode` for more info. + + The 'x0' property accepts values of any type + + Returns + ------- + Any + """ + return self["x0"] + + @x0.setter + def x0(self, val): + self["x0"] = val + + @property + def x0shift(self): + """ + Shifts `x0` away from the center of the category when `xref` is + a "category" or "multicategory" axis. -0.5 corresponds to the + start of the category and 0.5 corresponds to the end of the + category. + + The 'x0shift' property is a number and may be specified as: + - An int or float in the interval [-1, 1] + + Returns + ------- + int|float + """ + return self["x0shift"] + + @x0shift.setter + def x0shift(self, val): + self["x0shift"] = val + + @property + def x1(self): + """ + Sets the shape's end x position. See `type` and `xsizemode` for + more info. + + The 'x1' property accepts values of any type + + Returns + ------- + Any + """ + return self["x1"] + + @x1.setter + def x1(self, val): + self["x1"] = val + + @property + def x1shift(self): + """ + Shifts `x1` away from the center of the category when `xref` is + a "category" or "multicategory" axis. -0.5 corresponds to the + start of the category and 0.5 corresponds to the end of the + category. + + The 'x1shift' property is a number and may be specified as: + - An int or float in the interval [-1, 1] + + Returns + ------- + int|float + """ + return self["x1shift"] + + @x1shift.setter + def x1shift(self, val): + self["x1shift"] = val + + @property + def xanchor(self): + """ + Only relevant in conjunction with `xsizemode` set to "pixel". + Specifies the anchor point on the x axis to which `x0`, `x1` + and x coordinates within `path` are relative to. E.g. useful to + attach a pixel sized shape to a certain data value. No effect + when `xsizemode` not set to "pixel". + + The 'xanchor' property accepts values of any type + + Returns + ------- + Any + """ + return self["xanchor"] + + @xanchor.setter + def xanchor(self, val): + self["xanchor"] = val + + @property + def xref(self): + """ + Sets the shape's x coordinate axis. If set to a x axis id (e.g. + "x" or "x2"), the `x` position refers to a x coordinate. If set + to "paper", the `x` position refers to the distance from the + left of the plotting area in normalized coordinates where 0 (1) + corresponds to the left (right). If set to a x axis ID followed + by "domain" (separated by a space), the position behaves like + for "paper", but refers to the distance in fractions of the + domain length from the left of the domain of that axis: e.g., + *x2 domain* refers to the domain of the second x axis and a x + position of 0.5 refers to the point between the left and the + right of the domain of the second x axis. + + The 'xref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['paper'] + - A string that matches one of the following regular expressions: + ['^x([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["xref"] + + @xref.setter + def xref(self, val): + self["xref"] = val + + @property + def xsizemode(self): + """ + Sets the shapes's sizing mode along the x axis. If set to + "scaled", `x0`, `x1` and x coordinates within `path` refer to + data values on the x axis or a fraction of the plot area's + width (`xref` set to "paper"). If set to "pixel", `xanchor` + specifies the x position in terms of data or plot fraction but + `x0`, `x1` and x coordinates within `path` are pixels relative + to `xanchor`. This way, the shape can have a fixed width while + maintaining a position relative to data or plot fraction. + + The 'xsizemode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['scaled', 'pixel'] + + Returns + ------- + Any + """ + return self["xsizemode"] + + @xsizemode.setter + def xsizemode(self, val): + self["xsizemode"] = val + + @property + def y0(self): + """ + Sets the shape's starting y position. See `type` and + `ysizemode` for more info. + + The 'y0' property accepts values of any type + + Returns + ------- + Any + """ + return self["y0"] + + @y0.setter + def y0(self, val): + self["y0"] = val + + @property + def y0shift(self): + """ + Shifts `y0` away from the center of the category when `yref` is + a "category" or "multicategory" axis. -0.5 corresponds to the + start of the category and 0.5 corresponds to the end of the + category. + + The 'y0shift' property is a number and may be specified as: + - An int or float in the interval [-1, 1] + + Returns + ------- + int|float + """ + return self["y0shift"] + + @y0shift.setter + def y0shift(self, val): + self["y0shift"] = val + + @property + def y1(self): + """ + Sets the shape's end y position. See `type` and `ysizemode` for + more info. + + The 'y1' property accepts values of any type + + Returns + ------- + Any + """ + return self["y1"] + + @y1.setter + def y1(self, val): + self["y1"] = val + + @property + def y1shift(self): + """ + Shifts `y1` away from the center of the category when `yref` is + a "category" or "multicategory" axis. -0.5 corresponds to the + start of the category and 0.5 corresponds to the end of the + category. + + The 'y1shift' property is a number and may be specified as: + - An int or float in the interval [-1, 1] + + Returns + ------- + int|float + """ + return self["y1shift"] + + @y1shift.setter + def y1shift(self, val): + self["y1shift"] = val + + @property + def yanchor(self): + """ + Only relevant in conjunction with `ysizemode` set to "pixel". + Specifies the anchor point on the y axis to which `y0`, `y1` + and y coordinates within `path` are relative to. E.g. useful to + attach a pixel sized shape to a certain data value. No effect + when `ysizemode` not set to "pixel". + + The 'yanchor' property accepts values of any type + + Returns + ------- + Any + """ + return self["yanchor"] + + @yanchor.setter + def yanchor(self, val): + self["yanchor"] = val + + @property + def yref(self): + """ + Sets the shape's y coordinate axis. If set to a y axis id (e.g. + "y" or "y2"), the `y` position refers to a y coordinate. If set + to "paper", the `y` position refers to the distance from the + bottom of the plotting area in normalized coordinates where 0 + (1) corresponds to the bottom (top). If set to a y axis ID + followed by "domain" (separated by a space), the position + behaves like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the domain of + that axis: e.g., *y2 domain* refers to the domain of the second + y axis and a y position of 0.5 refers to the point between the + bottom and the top of the domain of the second y axis. + + The 'yref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['paper'] + - A string that matches one of the following regular expressions: + ['^y([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["yref"] + + @yref.setter + def yref(self, val): + self["yref"] = val + + @property + def ysizemode(self): + """ + Sets the shapes's sizing mode along the y axis. If set to + "scaled", `y0`, `y1` and y coordinates within `path` refer to + data values on the y axis or a fraction of the plot area's + height (`yref` set to "paper"). If set to "pixel", `yanchor` + specifies the y position in terms of data or plot fraction but + `y0`, `y1` and y coordinates within `path` are pixels relative + to `yanchor`. This way, the shape can have a fixed height while + maintaining a position relative to data or plot fraction. + + The 'ysizemode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['scaled', 'pixel'] + + Returns + ------- + Any + """ + return self["ysizemode"] + + @ysizemode.setter + def ysizemode(self, val): + self["ysizemode"] = val + + @property + def _prop_descriptions(self): + return """\ + editable + Determines whether the shape could be activated for + edit or not. Has no effect when the older editable + shapes mode is enabled via `config.editable` or + `config.edits.shapePosition`. + fillcolor + Sets the color filling the shape's interior. Only + applies to closed shapes. + fillrule + Determines which regions of complex paths constitute + the interior. For more info please visit + https://developer.mozilla.org/en- + US/docs/Web/SVG/Attribute/fill-rule + label + :class:`plotly.graph_objects.layout.shape.Label` + instance or dict with compatible properties + layer + Specifies whether shapes are drawn below gridlines + ("below"), between gridlines and traces ("between") or + above traces ("above"). + legend + Sets the reference to a legend to show this shape in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this shape. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.layout.shape.Legendgroupti + tle` instance or dict with compatible properties + legendrank + Sets the legend rank for this shape. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this shape. + line + :class:`plotly.graph_objects.layout.shape.Line` + instance or dict with compatible properties + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the shape. + path + For `type` "path" - a valid SVG path with the pixel + values replaced by data values in + `xsizemode`/`ysizemode` being "scaled" and taken + unmodified as pixels relative to `xanchor` and + `yanchor` in case of "pixel" size mode. There are a few + restrictions / quirks only absolute instructions, not + relative. So the allowed segments are: M, L, H, V, Q, + C, T, S, and Z arcs (A) are not allowed because radius + rx and ry are relative. In the future we could consider + supporting relative commands, but we would have to + decide on how to handle date and log axes. Note that + even as is, Q and C Bezier paths that are smooth on + linear axes may not be smooth on log, and vice versa. + no chained "polybezier" commands - specify the segment + type for each one. On category axes, values are numbers + scaled to the serial numbers of categories because + using the categories themselves there would be no way + to describe fractional positions On data axes: because + space and T are both normal components of path strings, + we can't use either to separate date from time parts. + Therefore we'll use underscore for this purpose: + 2015-02-21_13:45:56.789 + showlegend + Determines whether or not this shape is shown in the + legend. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + type + Specifies the shape type to be drawn. If "line", a line + is drawn from (`x0`,`y0`) to (`x1`,`y1`) with respect + to the axes' sizing mode. If "circle", a circle is + drawn from ((`x0`+`x1`)/2, (`y0`+`y1`)/2)) with radius + (|(`x0`+`x1`)/2 - `x0`|, |(`y0`+`y1`)/2 -`y0`)|) with + respect to the axes' sizing mode. If "rect", a + rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), + (`x1`,`y1`), (`x0`,`y1`), (`x0`,`y0`) with respect to + the axes' sizing mode. If "path", draw a custom SVG + path using `path`. with respect to the axes' sizing + mode. + visible + Determines whether or not this shape is visible. If + "legendonly", the shape is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x0 + Sets the shape's starting x position. See `type` and + `xsizemode` for more info. + x0shift + Shifts `x0` away from the center of the category when + `xref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + x1 + Sets the shape's end x position. See `type` and + `xsizemode` for more info. + x1shift + Shifts `x1` away from the center of the category when + `xref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + xanchor + Only relevant in conjunction with `xsizemode` set to + "pixel". Specifies the anchor point on the x axis to + which `x0`, `x1` and x coordinates within `path` are + relative to. E.g. useful to attach a pixel sized shape + to a certain data value. No effect when `xsizemode` not + set to "pixel". + xref + Sets the shape's x coordinate axis. If set to a x axis + id (e.g. "x" or "x2"), the `x` position refers to a x + coordinate. If set to "paper", the `x` position refers + to the distance from the left of the plotting area in + normalized coordinates where 0 (1) corresponds to the + left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + xsizemode + Sets the shapes's sizing mode along the x axis. If set + to "scaled", `x0`, `x1` and x coordinates within `path` + refer to data values on the x axis or a fraction of the + plot area's width (`xref` set to "paper"). If set to + "pixel", `xanchor` specifies the x position in terms of + data or plot fraction but `x0`, `x1` and x coordinates + within `path` are pixels relative to `xanchor`. This + way, the shape can have a fixed width while maintaining + a position relative to data or plot fraction. + y0 + Sets the shape's starting y position. See `type` and + `ysizemode` for more info. + y0shift + Shifts `y0` away from the center of the category when + `yref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + y1 + Sets the shape's end y position. See `type` and + `ysizemode` for more info. + y1shift + Shifts `y1` away from the center of the category when + `yref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + yanchor + Only relevant in conjunction with `ysizemode` set to + "pixel". Specifies the anchor point on the y axis to + which `y0`, `y1` and y coordinates within `path` are + relative to. E.g. useful to attach a pixel sized shape + to a certain data value. No effect when `ysizemode` not + set to "pixel". + yref + Sets the shape's y coordinate axis. If set to a y axis + id (e.g. "y" or "y2"), the `y` position refers to a y + coordinate. If set to "paper", the `y` position refers + to the distance from the bottom of the plotting area in + normalized coordinates where 0 (1) corresponds to the + bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + ysizemode + Sets the shapes's sizing mode along the y axis. If set + to "scaled", `y0`, `y1` and y coordinates within `path` + refer to data values on the y axis or a fraction of the + plot area's height (`yref` set to "paper"). If set to + "pixel", `yanchor` specifies the y position in terms of + data or plot fraction but `y0`, `y1` and y coordinates + within `path` are pixels relative to `yanchor`. This + way, the shape can have a fixed height while + maintaining a position relative to data or plot + fraction. + """ + + def __init__( + self, + arg=None, + editable=None, + fillcolor=None, + fillrule=None, + label=None, + layer=None, + legend=None, + legendgroup=None, + legendgrouptitle=None, + legendrank=None, + legendwidth=None, + line=None, + name=None, + opacity=None, + path=None, + showlegend=None, + templateitemname=None, + type=None, + visible=None, + x0=None, + x0shift=None, + x1=None, + x1shift=None, + xanchor=None, + xref=None, + xsizemode=None, + y0=None, + y0shift=None, + y1=None, + y1shift=None, + yanchor=None, + yref=None, + ysizemode=None, + **kwargs, + ): + """ + Construct a new Shape object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.Shape` + editable + Determines whether the shape could be activated for + edit or not. Has no effect when the older editable + shapes mode is enabled via `config.editable` or + `config.edits.shapePosition`. + fillcolor + Sets the color filling the shape's interior. Only + applies to closed shapes. + fillrule + Determines which regions of complex paths constitute + the interior. For more info please visit + https://developer.mozilla.org/en- + US/docs/Web/SVG/Attribute/fill-rule + label + :class:`plotly.graph_objects.layout.shape.Label` + instance or dict with compatible properties + layer + Specifies whether shapes are drawn below gridlines + ("below"), between gridlines and traces ("between") or + above traces ("above"). + legend + Sets the reference to a legend to show this shape in. + References to these legends are "legend", "legend2", + "legend3", etc. Settings for these legends are set in + the layout, under `layout.legend`, `layout.legend2`, + etc. + legendgroup + Sets the legend group for this shape. Traces and shapes + part of the same legend group hide/show at the same + time when toggling legend items. + legendgrouptitle + :class:`plotly.graph_objects.layout.shape.Legendgroupti + tle` instance or dict with compatible properties + legendrank + Sets the legend rank for this shape. Items and groups + with smaller ranks are presented on top/left side while + with "reversed" `legend.traceorder` they are on + bottom/right side. The default legendrank is 1000, so + that you can use ranks less than 1000 to place certain + items before all unranked items, and ranks greater than + 1000 to go after all unranked items. When having + unranked or equal rank items shapes would be displayed + after traces i.e. according to their order in data and + layout. + legendwidth + Sets the width (in px or fraction) of the legend for + this shape. + line + :class:`plotly.graph_objects.layout.shape.Line` + instance or dict with compatible properties + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + opacity + Sets the opacity of the shape. + path + For `type` "path" - a valid SVG path with the pixel + values replaced by data values in + `xsizemode`/`ysizemode` being "scaled" and taken + unmodified as pixels relative to `xanchor` and + `yanchor` in case of "pixel" size mode. There are a few + restrictions / quirks only absolute instructions, not + relative. So the allowed segments are: M, L, H, V, Q, + C, T, S, and Z arcs (A) are not allowed because radius + rx and ry are relative. In the future we could consider + supporting relative commands, but we would have to + decide on how to handle date and log axes. Note that + even as is, Q and C Bezier paths that are smooth on + linear axes may not be smooth on log, and vice versa. + no chained "polybezier" commands - specify the segment + type for each one. On category axes, values are numbers + scaled to the serial numbers of categories because + using the categories themselves there would be no way + to describe fractional positions On data axes: because + space and T are both normal components of path strings, + we can't use either to separate date from time parts. + Therefore we'll use underscore for this purpose: + 2015-02-21_13:45:56.789 + showlegend + Determines whether or not this shape is shown in the + legend. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + type + Specifies the shape type to be drawn. If "line", a line + is drawn from (`x0`,`y0`) to (`x1`,`y1`) with respect + to the axes' sizing mode. If "circle", a circle is + drawn from ((`x0`+`x1`)/2, (`y0`+`y1`)/2)) with radius + (|(`x0`+`x1`)/2 - `x0`|, |(`y0`+`y1`)/2 -`y0`)|) with + respect to the axes' sizing mode. If "rect", a + rectangle is drawn linking (`x0`,`y0`), (`x1`,`y0`), + (`x1`,`y1`), (`x0`,`y1`), (`x0`,`y0`) with respect to + the axes' sizing mode. If "path", draw a custom SVG + path using `path`. with respect to the axes' sizing + mode. + visible + Determines whether or not this shape is visible. If + "legendonly", the shape is not drawn, but can appear as + a legend item (provided that the legend itself is + visible). + x0 + Sets the shape's starting x position. See `type` and + `xsizemode` for more info. + x0shift + Shifts `x0` away from the center of the category when + `xref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + x1 + Sets the shape's end x position. See `type` and + `xsizemode` for more info. + x1shift + Shifts `x1` away from the center of the category when + `xref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + xanchor + Only relevant in conjunction with `xsizemode` set to + "pixel". Specifies the anchor point on the x axis to + which `x0`, `x1` and x coordinates within `path` are + relative to. E.g. useful to attach a pixel sized shape + to a certain data value. No effect when `xsizemode` not + set to "pixel". + xref + Sets the shape's x coordinate axis. If set to a x axis + id (e.g. "x" or "x2"), the `x` position refers to a x + coordinate. If set to "paper", the `x` position refers + to the distance from the left of the plotting area in + normalized coordinates where 0 (1) corresponds to the + left (right). If set to a x axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the left of the + domain of that axis: e.g., *x2 domain* refers to the + domain of the second x axis and a x position of 0.5 + refers to the point between the left and the right of + the domain of the second x axis. + xsizemode + Sets the shapes's sizing mode along the x axis. If set + to "scaled", `x0`, `x1` and x coordinates within `path` + refer to data values on the x axis or a fraction of the + plot area's width (`xref` set to "paper"). If set to + "pixel", `xanchor` specifies the x position in terms of + data or plot fraction but `x0`, `x1` and x coordinates + within `path` are pixels relative to `xanchor`. This + way, the shape can have a fixed width while maintaining + a position relative to data or plot fraction. + y0 + Sets the shape's starting y position. See `type` and + `ysizemode` for more info. + y0shift + Shifts `y0` away from the center of the category when + `yref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + y1 + Sets the shape's end y position. See `type` and + `ysizemode` for more info. + y1shift + Shifts `y1` away from the center of the category when + `yref` is a "category" or "multicategory" axis. -0.5 + corresponds to the start of the category and 0.5 + corresponds to the end of the category. + yanchor + Only relevant in conjunction with `ysizemode` set to + "pixel". Specifies the anchor point on the y axis to + which `y0`, `y1` and y coordinates within `path` are + relative to. E.g. useful to attach a pixel sized shape + to a certain data value. No effect when `ysizemode` not + set to "pixel". + yref + Sets the shape's y coordinate axis. If set to a y axis + id (e.g. "y" or "y2"), the `y` position refers to a y + coordinate. If set to "paper", the `y` position refers + to the distance from the bottom of the plotting area in + normalized coordinates where 0 (1) corresponds to the + bottom (top). If set to a y axis ID followed by + "domain" (separated by a space), the position behaves + like for "paper", but refers to the distance in + fractions of the domain length from the bottom of the + domain of that axis: e.g., *y2 domain* refers to the + domain of the second y axis and a y position of 0.5 + refers to the point between the bottom and the top of + the domain of the second y axis. + ysizemode + Sets the shapes's sizing mode along the y axis. If set + to "scaled", `y0`, `y1` and y coordinates within `path` + refer to data values on the y axis or a fraction of the + plot area's height (`yref` set to "paper"). If set to + "pixel", `yanchor` specifies the y position in terms of + data or plot fraction but `y0`, `y1` and y coordinates + within `path` are pixels relative to `yanchor`. This + way, the shape can have a fixed height while + maintaining a position relative to data or plot + fraction. + + Returns + ------- + Shape + """ + super().__init__("shapes") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Shape +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Shape`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("editable", arg, editable) + self._set_property("fillcolor", arg, fillcolor) + self._set_property("fillrule", arg, fillrule) + self._set_property("label", arg, label) + self._set_property("layer", arg, layer) + self._set_property("legend", arg, legend) + self._set_property("legendgroup", arg, legendgroup) + self._set_property("legendgrouptitle", arg, legendgrouptitle) + self._set_property("legendrank", arg, legendrank) + self._set_property("legendwidth", arg, legendwidth) + self._set_property("line", arg, line) + self._set_property("name", arg, name) + self._set_property("opacity", arg, opacity) + self._set_property("path", arg, path) + self._set_property("showlegend", arg, showlegend) + self._set_property("templateitemname", arg, templateitemname) + self._set_property("type", arg, type) + self._set_property("visible", arg, visible) + self._set_property("x0", arg, x0) + self._set_property("x0shift", arg, x0shift) + self._set_property("x1", arg, x1) + self._set_property("x1shift", arg, x1shift) + self._set_property("xanchor", arg, xanchor) + self._set_property("xref", arg, xref) + self._set_property("xsizemode", arg, xsizemode) + self._set_property("y0", arg, y0) + self._set_property("y0shift", arg, y0shift) + self._set_property("y1", arg, y1) + self._set_property("y1shift", arg, y1shift) + self._set_property("yanchor", arg, yanchor) + self._set_property("yref", arg, yref) + self._set_property("ysizemode", arg, ysizemode) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_slider.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_slider.py new file mode 100644 index 0000000000000000000000000000000000000000..cfafd2479018624682bee944e2f3510f0b89d582 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_slider.py @@ -0,0 +1,786 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Slider(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.slider" + _valid_props = { + "active", + "activebgcolor", + "bgcolor", + "bordercolor", + "borderwidth", + "currentvalue", + "font", + "len", + "lenmode", + "minorticklen", + "name", + "pad", + "stepdefaults", + "steps", + "templateitemname", + "tickcolor", + "ticklen", + "tickwidth", + "transition", + "visible", + "x", + "xanchor", + "y", + "yanchor", + } + + @property + def active(self): + """ + Determines which button (by index starting from 0) is + considered active. + + The 'active' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["active"] + + @active.setter + def active(self, val): + self["active"] = val + + @property + def activebgcolor(self): + """ + Sets the background color of the slider grip while dragging. + + The 'activebgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["activebgcolor"] + + @activebgcolor.setter + def activebgcolor(self, val): + self["activebgcolor"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the slider. + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bordercolor(self): + """ + Sets the color of the border enclosing the slider. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def borderwidth(self): + """ + Sets the width (in px) of the border enclosing the slider. + + The 'borderwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["borderwidth"] + + @borderwidth.setter + def borderwidth(self, val): + self["borderwidth"] = val + + @property + def currentvalue(self): + """ + The 'currentvalue' property is an instance of Currentvalue + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.slider.Currentvalue` + - A dict of string/value properties that will be passed + to the Currentvalue constructor + + Returns + ------- + plotly.graph_objs.layout.slider.Currentvalue + """ + return self["currentvalue"] + + @currentvalue.setter + def currentvalue(self, val): + self["currentvalue"] = val + + @property + def font(self): + """ + Sets the font of the slider step labels. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.slider.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.layout.slider.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def len(self): + """ + Sets the length of the slider This measure excludes the padding + of both ends. That is, the slider's length is this length minus + the padding on both ends. + + The 'len' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["len"] + + @len.setter + def len(self, val): + self["len"] = val + + @property + def lenmode(self): + """ + Determines whether this slider length is set in units of plot + "fraction" or in *pixels. Use `len` to set the value. + + The 'lenmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fraction', 'pixels'] + + Returns + ------- + Any + """ + return self["lenmode"] + + @lenmode.setter + def lenmode(self, val): + self["lenmode"] = val + + @property + def minorticklen(self): + """ + Sets the length in pixels of minor step tick marks + + The 'minorticklen' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["minorticklen"] + + @minorticklen.setter + def minorticklen(self, val): + self["minorticklen"] = val + + @property + def name(self): + """ + When used in a template, named items are created in the output + figure in addition to any items the figure already has in this + array. You can modify these items in the output figure by + making your own item with `templateitemname` matching this + `name` alongside your modifications (including `visible: false` + or `enabled: false` to hide it). Has no effect outside of a + template. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def pad(self): + """ + Set the padding of the slider component along each side. + + The 'pad' property is an instance of Pad + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.slider.Pad` + - A dict of string/value properties that will be passed + to the Pad constructor + + Returns + ------- + plotly.graph_objs.layout.slider.Pad + """ + return self["pad"] + + @pad.setter + def pad(self, val): + self["pad"] = val + + @property + def steps(self): + """ + The 'steps' property is a tuple of instances of + Step that may be specified as: + - A list or tuple of instances of plotly.graph_objs.layout.slider.Step + - A list or tuple of dicts of string/value properties that + will be passed to the Step constructor + + Returns + ------- + tuple[plotly.graph_objs.layout.slider.Step] + """ + return self["steps"] + + @steps.setter + def steps(self, val): + self["steps"] = val + + @property + def stepdefaults(self): + """ + When used in a template (as + layout.template.layout.slider.stepdefaults), sets the default + property values to use for elements of layout.slider.steps + + The 'stepdefaults' property is an instance of Step + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.slider.Step` + - A dict of string/value properties that will be passed + to the Step constructor + + Returns + ------- + plotly.graph_objs.layout.slider.Step + """ + return self["stepdefaults"] + + @stepdefaults.setter + def stepdefaults(self, val): + self["stepdefaults"] = val + + @property + def templateitemname(self): + """ + Used to refer to a named item in this array in the template. + Named items from the template will be created even without a + matching item in the input figure, but you can modify one by + making an item with `templateitemname` matching its `name`, + alongside your modifications (including `visible: false` or + `enabled: false` to hide it). If there is no template or no + matching item, this item will be hidden unless you explicitly + show it with `visible: true`. + + The 'templateitemname' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["templateitemname"] + + @templateitemname.setter + def templateitemname(self, val): + self["templateitemname"] = val + + @property + def tickcolor(self): + """ + Sets the color of the border enclosing the slider. + + The 'tickcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["tickcolor"] + + @tickcolor.setter + def tickcolor(self, val): + self["tickcolor"] = val + + @property + def ticklen(self): + """ + Sets the length in pixels of step tick marks + + The 'ticklen' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["ticklen"] + + @ticklen.setter + def ticklen(self, val): + self["ticklen"] = val + + @property + def tickwidth(self): + """ + Sets the tick width (in px). + + The 'tickwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["tickwidth"] + + @tickwidth.setter + def tickwidth(self, val): + self["tickwidth"] = val + + @property + def transition(self): + """ + The 'transition' property is an instance of Transition + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.slider.Transition` + - A dict of string/value properties that will be passed + to the Transition constructor + + Returns + ------- + plotly.graph_objs.layout.slider.Transition + """ + return self["transition"] + + @transition.setter + def transition(self, val): + self["transition"] = val + + @property + def visible(self): + """ + Determines whether or not the slider is visible. + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the x position (in normalized coordinates) of the slider. + + The 'x' property is a number and may be specified as: + - An int or float in the interval [-2, 3] + + Returns + ------- + int|float + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xanchor(self): + """ + Sets the slider's horizontal position anchor. This anchor binds + the `x` position to the "left", "center" or "right" of the + range selector. + + The 'xanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'left', 'center', 'right'] + + Returns + ------- + Any + """ + return self["xanchor"] + + @xanchor.setter + def xanchor(self, val): + self["xanchor"] = val + + @property + def y(self): + """ + Sets the y position (in normalized coordinates) of the slider. + + The 'y' property is a number and may be specified as: + - An int or float in the interval [-2, 3] + + Returns + ------- + int|float + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yanchor(self): + """ + Sets the slider's vertical position anchor This anchor binds + the `y` position to the "top", "middle" or "bottom" of the + range selector. + + The 'yanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'top', 'middle', 'bottom'] + + Returns + ------- + Any + """ + return self["yanchor"] + + @yanchor.setter + def yanchor(self, val): + self["yanchor"] = val + + @property + def _prop_descriptions(self): + return """\ + active + Determines which button (by index starting from 0) is + considered active. + activebgcolor + Sets the background color of the slider grip while + dragging. + bgcolor + Sets the background color of the slider. + bordercolor + Sets the color of the border enclosing the slider. + borderwidth + Sets the width (in px) of the border enclosing the + slider. + currentvalue + :class:`plotly.graph_objects.layout.slider.Currentvalue + ` instance or dict with compatible properties + font + Sets the font of the slider step labels. + len + Sets the length of the slider This measure excludes the + padding of both ends. That is, the slider's length is + this length minus the padding on both ends. + lenmode + Determines whether this slider length is set in units + of plot "fraction" or in *pixels. Use `len` to set the + value. + minorticklen + Sets the length in pixels of minor step tick marks + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + pad + Set the padding of the slider component along each + side. + steps + A tuple of + :class:`plotly.graph_objects.layout.slider.Step` + instances or dicts with compatible properties + stepdefaults + When used in a template (as + layout.template.layout.slider.stepdefaults), sets the + default property values to use for elements of + layout.slider.steps + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + tickcolor + Sets the color of the border enclosing the slider. + ticklen + Sets the length in pixels of step tick marks + tickwidth + Sets the tick width (in px). + transition + :class:`plotly.graph_objects.layout.slider.Transition` + instance or dict with compatible properties + visible + Determines whether or not the slider is visible. + x + Sets the x position (in normalized coordinates) of the + slider. + xanchor + Sets the slider's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the range selector. + y + Sets the y position (in normalized coordinates) of the + slider. + yanchor + Sets the slider's vertical position anchor This anchor + binds the `y` position to the "top", "middle" or + "bottom" of the range selector. + """ + + def __init__( + self, + arg=None, + active=None, + activebgcolor=None, + bgcolor=None, + bordercolor=None, + borderwidth=None, + currentvalue=None, + font=None, + len=None, + lenmode=None, + minorticklen=None, + name=None, + pad=None, + steps=None, + stepdefaults=None, + templateitemname=None, + tickcolor=None, + ticklen=None, + tickwidth=None, + transition=None, + visible=None, + x=None, + xanchor=None, + y=None, + yanchor=None, + **kwargs, + ): + """ + Construct a new Slider object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.Slider` + active + Determines which button (by index starting from 0) is + considered active. + activebgcolor + Sets the background color of the slider grip while + dragging. + bgcolor + Sets the background color of the slider. + bordercolor + Sets the color of the border enclosing the slider. + borderwidth + Sets the width (in px) of the border enclosing the + slider. + currentvalue + :class:`plotly.graph_objects.layout.slider.Currentvalue + ` instance or dict with compatible properties + font + Sets the font of the slider step labels. + len + Sets the length of the slider This measure excludes the + padding of both ends. That is, the slider's length is + this length minus the padding on both ends. + lenmode + Determines whether this slider length is set in units + of plot "fraction" or in *pixels. Use `len` to set the + value. + minorticklen + Sets the length in pixels of minor step tick marks + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + pad + Set the padding of the slider component along each + side. + steps + A tuple of + :class:`plotly.graph_objects.layout.slider.Step` + instances or dicts with compatible properties + stepdefaults + When used in a template (as + layout.template.layout.slider.stepdefaults), sets the + default property values to use for elements of + layout.slider.steps + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + tickcolor + Sets the color of the border enclosing the slider. + ticklen + Sets the length in pixels of step tick marks + tickwidth + Sets the tick width (in px). + transition + :class:`plotly.graph_objects.layout.slider.Transition` + instance or dict with compatible properties + visible + Determines whether or not the slider is visible. + x + Sets the x position (in normalized coordinates) of the + slider. + xanchor + Sets the slider's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the range selector. + y + Sets the y position (in normalized coordinates) of the + slider. + yanchor + Sets the slider's vertical position anchor This anchor + binds the `y` position to the "top", "middle" or + "bottom" of the range selector. + + Returns + ------- + Slider + """ + super().__init__("sliders") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Slider +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Slider`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("active", arg, active) + self._set_property("activebgcolor", arg, activebgcolor) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("borderwidth", arg, borderwidth) + self._set_property("currentvalue", arg, currentvalue) + self._set_property("font", arg, font) + self._set_property("len", arg, len) + self._set_property("lenmode", arg, lenmode) + self._set_property("minorticklen", arg, minorticklen) + self._set_property("name", arg, name) + self._set_property("pad", arg, pad) + self._set_property("steps", arg, steps) + self._set_property("stepdefaults", arg, stepdefaults) + self._set_property("templateitemname", arg, templateitemname) + self._set_property("tickcolor", arg, tickcolor) + self._set_property("ticklen", arg, ticklen) + self._set_property("tickwidth", arg, tickwidth) + self._set_property("transition", arg, transition) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("xanchor", arg, xanchor) + self._set_property("y", arg, y) + self._set_property("yanchor", arg, yanchor) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_smith.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_smith.py new file mode 100644 index 0000000000000000000000000000000000000000..061e67992a131ee9b092c7f3c6a6bb352e9c2901 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_smith.py @@ -0,0 +1,166 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Smith(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.smith" + _valid_props = {"bgcolor", "domain", "imaginaryaxis", "realaxis"} + + @property + def bgcolor(self): + """ + Set the background color of the subplot + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.smith.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.layout.smith.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def imaginaryaxis(self): + """ + The 'imaginaryaxis' property is an instance of Imaginaryaxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.smith.Imaginaryaxis` + - A dict of string/value properties that will be passed + to the Imaginaryaxis constructor + + Returns + ------- + plotly.graph_objs.layout.smith.Imaginaryaxis + """ + return self["imaginaryaxis"] + + @imaginaryaxis.setter + def imaginaryaxis(self, val): + self["imaginaryaxis"] = val + + @property + def realaxis(self): + """ + The 'realaxis' property is an instance of Realaxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.smith.Realaxis` + - A dict of string/value properties that will be passed + to the Realaxis constructor + + Returns + ------- + plotly.graph_objs.layout.smith.Realaxis + """ + return self["realaxis"] + + @realaxis.setter + def realaxis(self, val): + self["realaxis"] = val + + @property + def _prop_descriptions(self): + return """\ + bgcolor + Set the background color of the subplot + domain + :class:`plotly.graph_objects.layout.smith.Domain` + instance or dict with compatible properties + imaginaryaxis + :class:`plotly.graph_objects.layout.smith.Imaginaryaxis + ` instance or dict with compatible properties + realaxis + :class:`plotly.graph_objects.layout.smith.Realaxis` + instance or dict with compatible properties + """ + + def __init__( + self, + arg=None, + bgcolor=None, + domain=None, + imaginaryaxis=None, + realaxis=None, + **kwargs, + ): + """ + Construct a new Smith object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.Smith` + bgcolor + Set the background color of the subplot + domain + :class:`plotly.graph_objects.layout.smith.Domain` + instance or dict with compatible properties + imaginaryaxis + :class:`plotly.graph_objects.layout.smith.Imaginaryaxis + ` instance or dict with compatible properties + realaxis + :class:`plotly.graph_objects.layout.smith.Realaxis` + instance or dict with compatible properties + + Returns + ------- + Smith + """ + super().__init__("smith") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Smith +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Smith`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("bgcolor", arg, bgcolor) + self._set_property("domain", arg, domain) + self._set_property("imaginaryaxis", arg, imaginaryaxis) + self._set_property("realaxis", arg, realaxis) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_template.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_template.py new file mode 100644 index 0000000000000000000000000000000000000000..90eb3f6602b189920bbadc86635192654bc3d4be --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_template.py @@ -0,0 +1,133 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy +import warnings + + +class Template(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.template" + _valid_props = {"data", "layout"} + + @property + def data(self): + """ + The 'data' property is an instance of Data + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.template.Data` + - A dict of string/value properties that will be passed + to the Data constructor + + Returns + ------- + plotly.graph_objs.layout.template.Data + """ + return self["data"] + + @data.setter + def data(self, val): + self["data"] = val + + @property + def layout(self): + """ + The 'layout' property is an instance of Layout + that may be specified as: + - An instance of :class:`plotly.graph_objs.Layout` + - A dict of string/value properties that will be passed + to the Layout constructor + + Returns + ------- + plotly.graph_objs.layout.template.Layout + """ + return self["layout"] + + @layout.setter + def layout(self, val): + self["layout"] = val + + @property + def _prop_descriptions(self): + return """\ + data + :class:`plotly.graph_objects.layout.template.Data` + instance or dict with compatible properties + layout + :class:`plotly.graph_objects.Layout` instance or dict + with compatible properties + """ + + def __init__(self, arg=None, data=None, layout=None, **kwargs): + """ + Construct a new Template object + + Default attributes to be applied to the plot. This should be a + dict with format: `{'layout': layoutTemplate, 'data': + {trace_type: [traceTemplate, ...], ...}}` where + `layoutTemplate` is a dict matching the structure of + `figure.layout` and `traceTemplate` is a dict matching the + structure of the trace with type `trace_type` (e.g. 'scatter'). + Alternatively, this may be specified as an instance of + plotly.graph_objs.layout.Template. Trace templates are applied + cyclically to traces of each type. Container arrays (eg + `annotations`) have special handling: An object ending in + `defaults` (eg `annotationdefaults`) is applied to each array + item. But if an item has a `templateitemname` key we look in + the template array for an item with matching `name` and apply + that instead. If no matching `name` is found we mark the item + invisible. Any named template item not referenced is appended + to the end of the array, so this can be used to add a watermark + annotation or a logo image, for example. To omit one of these + items on the plot, make an item with matching + `templateitemname` and `visible: false`. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.layout.Template` + data + :class:`plotly.graph_objects.layout.template.Data` + instance or dict with compatible properties + layout + :class:`plotly.graph_objects.Layout` instance or dict + with compatible properties + + Returns + ------- + Template + """ + super().__init__("template") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Template +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Template`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + # Template.data contains a 'scattermapbox' key, which causes a + # go.Scattermapbox trace object to be created during validation. + # In order to prevent false deprecation warnings from surfacing, + # we suppress deprecation warnings for this line only. + with warnings.catch_warnings(): + warnings.filterwarnings("ignore", category=DeprecationWarning) + self._set_property("data", arg, data) + self._set_property("layout", arg, layout) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_ternary.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_ternary.py new file mode 100644 index 0000000000000000000000000000000000000000..c8cb58fbb9f85dc8ab3adf252ae7ec7cb062957c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_ternary.py @@ -0,0 +1,250 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Ternary(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.ternary" + _valid_props = {"aaxis", "baxis", "bgcolor", "caxis", "domain", "sum", "uirevision"} + + @property + def aaxis(self): + """ + The 'aaxis' property is an instance of Aaxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.ternary.Aaxis` + - A dict of string/value properties that will be passed + to the Aaxis constructor + + Returns + ------- + plotly.graph_objs.layout.ternary.Aaxis + """ + return self["aaxis"] + + @aaxis.setter + def aaxis(self, val): + self["aaxis"] = val + + @property + def baxis(self): + """ + The 'baxis' property is an instance of Baxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.ternary.Baxis` + - A dict of string/value properties that will be passed + to the Baxis constructor + + Returns + ------- + plotly.graph_objs.layout.ternary.Baxis + """ + return self["baxis"] + + @baxis.setter + def baxis(self, val): + self["baxis"] = val + + @property + def bgcolor(self): + """ + Set the background color of the subplot + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def caxis(self): + """ + The 'caxis' property is an instance of Caxis + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.ternary.Caxis` + - A dict of string/value properties that will be passed + to the Caxis constructor + + Returns + ------- + plotly.graph_objs.layout.ternary.Caxis + """ + return self["caxis"] + + @caxis.setter + def caxis(self, val): + self["caxis"] = val + + @property + def domain(self): + """ + The 'domain' property is an instance of Domain + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.ternary.Domain` + - A dict of string/value properties that will be passed + to the Domain constructor + + Returns + ------- + plotly.graph_objs.layout.ternary.Domain + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def sum(self): + """ + The number each triplet should sum to, and the maximum range of + each axis + + The 'sum' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["sum"] + + @sum.setter + def sum(self, val): + self["sum"] = val + + @property + def uirevision(self): + """ + Controls persistence of user-driven changes in axis `min` and + `title`, if not overridden in the individual axes. Defaults to + `layout.uirevision`. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def _prop_descriptions(self): + return """\ + aaxis + :class:`plotly.graph_objects.layout.ternary.Aaxis` + instance or dict with compatible properties + baxis + :class:`plotly.graph_objects.layout.ternary.Baxis` + instance or dict with compatible properties + bgcolor + Set the background color of the subplot + caxis + :class:`plotly.graph_objects.layout.ternary.Caxis` + instance or dict with compatible properties + domain + :class:`plotly.graph_objects.layout.ternary.Domain` + instance or dict with compatible properties + sum + The number each triplet should sum to, and the maximum + range of each axis + uirevision + Controls persistence of user-driven changes in axis + `min` and `title`, if not overridden in the individual + axes. Defaults to `layout.uirevision`. + """ + + def __init__( + self, + arg=None, + aaxis=None, + baxis=None, + bgcolor=None, + caxis=None, + domain=None, + sum=None, + uirevision=None, + **kwargs, + ): + """ + Construct a new Ternary object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.layout.Ternary` + aaxis + :class:`plotly.graph_objects.layout.ternary.Aaxis` + instance or dict with compatible properties + baxis + :class:`plotly.graph_objects.layout.ternary.Baxis` + instance or dict with compatible properties + bgcolor + Set the background color of the subplot + caxis + :class:`plotly.graph_objects.layout.ternary.Caxis` + instance or dict with compatible properties + domain + :class:`plotly.graph_objects.layout.ternary.Domain` + instance or dict with compatible properties + sum + The number each triplet should sum to, and the maximum + range of each axis + uirevision + Controls persistence of user-driven changes in axis + `min` and `title`, if not overridden in the individual + axes. Defaults to `layout.uirevision`. + + Returns + ------- + Ternary + """ + super().__init__("ternary") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Ternary +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Ternary`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("aaxis", arg, aaxis) + self._set_property("baxis", arg, baxis) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("caxis", arg, caxis) + self._set_property("domain", arg, domain) + self._set_property("sum", arg, sum) + self._set_property("uirevision", arg, uirevision) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_title.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_title.py new file mode 100644 index 0000000000000000000000000000000000000000..379ed507d6d12a2ef4d027dfef1d9f2a4890d8f4 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_title.py @@ -0,0 +1,450 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Title(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.title" + _valid_props = { + "automargin", + "font", + "pad", + "subtitle", + "text", + "x", + "xanchor", + "xref", + "y", + "yanchor", + "yref", + } + + @property + def automargin(self): + """ + Determines whether the title can automatically push the figure + margins. If `yref='paper'` then the margin will expand to + ensure that the title doesn’t overlap with the edges of the + container. If `yref='container'` then the margins will ensure + that the title doesn’t overlap with the plot area, tick labels, + and axis titles. If `automargin=true` and the margins need to + be expanded, then y will be set to a default 1 and yanchor will + be set to an appropriate default to ensure that minimal margin + space is needed. Note that when `yref='paper'`, only 1 or 0 are + allowed y values. Invalid values will be reset to the default + 1. + + The 'automargin' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["automargin"] + + @automargin.setter + def automargin(self, val): + self["automargin"] = val + + @property + def font(self): + """ + Sets the title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.title.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.layout.title.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def pad(self): + """ + Sets the padding of the title. Each padding value only applies + when the corresponding `xanchor`/`yanchor` value is set + accordingly. E.g. for left padding to take effect, `xanchor` + must be set to "left". The same rule applies if + `xanchor`/`yanchor` is determined automatically. Padding is + muted if the respective anchor value is "middle*/*center". + + The 'pad' property is an instance of Pad + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.title.Pad` + - A dict of string/value properties that will be passed + to the Pad constructor + + Returns + ------- + plotly.graph_objs.layout.title.Pad + """ + return self["pad"] + + @pad.setter + def pad(self, val): + self["pad"] = val + + @property + def subtitle(self): + """ + The 'subtitle' property is an instance of Subtitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.title.Subtitle` + - A dict of string/value properties that will be passed + to the Subtitle constructor + + Returns + ------- + plotly.graph_objs.layout.title.Subtitle + """ + return self["subtitle"] + + @subtitle.setter + def subtitle(self, val): + self["subtitle"] = val + + @property + def text(self): + """ + Sets the plot's title. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def x(self): + """ + Sets the x position with respect to `xref` in normalized + coordinates from 0 (left) to 1 (right). + + The 'x' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xanchor(self): + """ + Sets the title's horizontal alignment with respect to its x + position. "left" means that the title starts at x, "right" + means that the title ends at x and "center" means that the + title's center is at x. "auto" divides `xref` by three and + calculates the `xanchor` value automatically based on the value + of `x`. + + The 'xanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'left', 'center', 'right'] + + Returns + ------- + Any + """ + return self["xanchor"] + + @xanchor.setter + def xanchor(self, val): + self["xanchor"] = val + + @property + def xref(self): + """ + Sets the container `x` refers to. "container" spans the entire + `width` of the plot. "paper" refers to the width of the + plotting area only. + + The 'xref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['container', 'paper'] + + Returns + ------- + Any + """ + return self["xref"] + + @xref.setter + def xref(self, val): + self["xref"] = val + + @property + def y(self): + """ + Sets the y position with respect to `yref` in normalized + coordinates from 0 (bottom) to 1 (top). "auto" places the + baseline of the title onto the vertical center of the top + margin. + + The 'y' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yanchor(self): + """ + Sets the title's vertical alignment with respect to its y + position. "top" means that the title's cap line is at y, + "bottom" means that the title's baseline is at y and "middle" + means that the title's midline is at y. "auto" divides `yref` + by three and calculates the `yanchor` value automatically based + on the value of `y`. + + The 'yanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'top', 'middle', 'bottom'] + + Returns + ------- + Any + """ + return self["yanchor"] + + @yanchor.setter + def yanchor(self, val): + self["yanchor"] = val + + @property + def yref(self): + """ + Sets the container `y` refers to. "container" spans the entire + `height` of the plot. "paper" refers to the height of the + plotting area only. + + The 'yref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['container', 'paper'] + + Returns + ------- + Any + """ + return self["yref"] + + @yref.setter + def yref(self, val): + self["yref"] = val + + @property + def _prop_descriptions(self): + return """\ + automargin + Determines whether the title can automatically push the + figure margins. If `yref='paper'` then the margin will + expand to ensure that the title doesn’t overlap with + the edges of the container. If `yref='container'` then + the margins will ensure that the title doesn’t overlap + with the plot area, tick labels, and axis titles. If + `automargin=true` and the margins need to be expanded, + then y will be set to a default 1 and yanchor will be + set to an appropriate default to ensure that minimal + margin space is needed. Note that when `yref='paper'`, + only 1 or 0 are allowed y values. Invalid values will + be reset to the default 1. + font + Sets the title font. + pad + Sets the padding of the title. Each padding value only + applies when the corresponding `xanchor`/`yanchor` + value is set accordingly. E.g. for left padding to take + effect, `xanchor` must be set to "left". The same rule + applies if `xanchor`/`yanchor` is determined + automatically. Padding is muted if the respective + anchor value is "middle*/*center". + subtitle + :class:`plotly.graph_objects.layout.title.Subtitle` + instance or dict with compatible properties + text + Sets the plot's title. + x + Sets the x position with respect to `xref` in + normalized coordinates from 0 (left) to 1 (right). + xanchor + Sets the title's horizontal alignment with respect to + its x position. "left" means that the title starts at + x, "right" means that the title ends at x and "center" + means that the title's center is at x. "auto" divides + `xref` by three and calculates the `xanchor` value + automatically based on the value of `x`. + xref + Sets the container `x` refers to. "container" spans the + entire `width` of the plot. "paper" refers to the width + of the plotting area only. + y + Sets the y position with respect to `yref` in + normalized coordinates from 0 (bottom) to 1 (top). + "auto" places the baseline of the title onto the + vertical center of the top margin. + yanchor + Sets the title's vertical alignment with respect to its + y position. "top" means that the title's cap line is at + y, "bottom" means that the title's baseline is at y and + "middle" means that the title's midline is at y. "auto" + divides `yref` by three and calculates the `yanchor` + value automatically based on the value of `y`. + yref + Sets the container `y` refers to. "container" spans the + entire `height` of the plot. "paper" refers to the + height of the plotting area only. + """ + + def __init__( + self, + arg=None, + automargin=None, + font=None, + pad=None, + subtitle=None, + text=None, + x=None, + xanchor=None, + xref=None, + y=None, + yanchor=None, + yref=None, + **kwargs, + ): + """ + Construct a new Title object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.Title` + automargin + Determines whether the title can automatically push the + figure margins. If `yref='paper'` then the margin will + expand to ensure that the title doesn’t overlap with + the edges of the container. If `yref='container'` then + the margins will ensure that the title doesn’t overlap + with the plot area, tick labels, and axis titles. If + `automargin=true` and the margins need to be expanded, + then y will be set to a default 1 and yanchor will be + set to an appropriate default to ensure that minimal + margin space is needed. Note that when `yref='paper'`, + only 1 or 0 are allowed y values. Invalid values will + be reset to the default 1. + font + Sets the title font. + pad + Sets the padding of the title. Each padding value only + applies when the corresponding `xanchor`/`yanchor` + value is set accordingly. E.g. for left padding to take + effect, `xanchor` must be set to "left". The same rule + applies if `xanchor`/`yanchor` is determined + automatically. Padding is muted if the respective + anchor value is "middle*/*center". + subtitle + :class:`plotly.graph_objects.layout.title.Subtitle` + instance or dict with compatible properties + text + Sets the plot's title. + x + Sets the x position with respect to `xref` in + normalized coordinates from 0 (left) to 1 (right). + xanchor + Sets the title's horizontal alignment with respect to + its x position. "left" means that the title starts at + x, "right" means that the title ends at x and "center" + means that the title's center is at x. "auto" divides + `xref` by three and calculates the `xanchor` value + automatically based on the value of `x`. + xref + Sets the container `x` refers to. "container" spans the + entire `width` of the plot. "paper" refers to the width + of the plotting area only. + y + Sets the y position with respect to `yref` in + normalized coordinates from 0 (bottom) to 1 (top). + "auto" places the baseline of the title onto the + vertical center of the top margin. + yanchor + Sets the title's vertical alignment with respect to its + y position. "top" means that the title's cap line is at + y, "bottom" means that the title's baseline is at y and + "middle" means that the title's midline is at y. "auto" + divides `yref` by three and calculates the `yanchor` + value automatically based on the value of `y`. + yref + Sets the container `y` refers to. "container" spans the + entire `height` of the plot. "paper" refers to the + height of the plotting area only. + + Returns + ------- + Title + """ + super().__init__("title") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Title +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Title`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("automargin", arg, automargin) + self._set_property("font", arg, font) + self._set_property("pad", arg, pad) + self._set_property("subtitle", arg, subtitle) + self._set_property("text", arg, text) + self._set_property("x", arg, x) + self._set_property("xanchor", arg, xanchor) + self._set_property("xref", arg, xref) + self._set_property("y", arg, y) + self._set_property("yanchor", arg, yanchor) + self._set_property("yref", arg, yref) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_transition.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_transition.py new file mode 100644 index 0000000000000000000000000000000000000000..fec6a2827087a85aa32e0afd298a9fce42c09efd --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_transition.py @@ -0,0 +1,144 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Transition(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.transition" + _valid_props = {"duration", "easing", "ordering"} + + @property + def duration(self): + """ + The duration of the transition, in milliseconds. If equal to + zero, updates are synchronous. + + The 'duration' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["duration"] + + @duration.setter + def duration(self, val): + self["duration"] = val + + @property + def easing(self): + """ + The easing function used for the transition + + The 'easing' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['linear', 'quad', 'cubic', 'sin', 'exp', 'circle', + 'elastic', 'back', 'bounce', 'linear-in', 'quad-in', + 'cubic-in', 'sin-in', 'exp-in', 'circle-in', 'elastic-in', + 'back-in', 'bounce-in', 'linear-out', 'quad-out', + 'cubic-out', 'sin-out', 'exp-out', 'circle-out', + 'elastic-out', 'back-out', 'bounce-out', 'linear-in-out', + 'quad-in-out', 'cubic-in-out', 'sin-in-out', 'exp-in-out', + 'circle-in-out', 'elastic-in-out', 'back-in-out', + 'bounce-in-out'] + + Returns + ------- + Any + """ + return self["easing"] + + @easing.setter + def easing(self, val): + self["easing"] = val + + @property + def ordering(self): + """ + Determines whether the figure's layout or traces smoothly + transitions during updates that make both traces and layout + change. + + The 'ordering' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['layout first', 'traces first'] + + Returns + ------- + Any + """ + return self["ordering"] + + @ordering.setter + def ordering(self, val): + self["ordering"] = val + + @property + def _prop_descriptions(self): + return """\ + duration + The duration of the transition, in milliseconds. If + equal to zero, updates are synchronous. + easing + The easing function used for the transition + ordering + Determines whether the figure's layout or traces + smoothly transitions during updates that make both + traces and layout change. + """ + + def __init__(self, arg=None, duration=None, easing=None, ordering=None, **kwargs): + """ + Construct a new Transition object + + Sets transition options used during Plotly.react updates. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.layout.Transition` + duration + The duration of the transition, in milliseconds. If + equal to zero, updates are synchronous. + easing + The easing function used for the transition + ordering + Determines whether the figure's layout or traces + smoothly transitions during updates that make both + traces and layout change. + + Returns + ------- + Transition + """ + super().__init__("transition") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Transition +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Transition`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("duration", arg, duration) + self._set_property("easing", arg, easing) + self._set_property("ordering", arg, ordering) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_uniformtext.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_uniformtext.py new file mode 100644 index 0000000000000000000000000000000000000000..a47da28903fa3ca6e14536956a439f30678a44d9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_uniformtext.py @@ -0,0 +1,124 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Uniformtext(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.uniformtext" + _valid_props = {"minsize", "mode"} + + @property + def minsize(self): + """ + Sets the minimum text size between traces of the same type. + + The 'minsize' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["minsize"] + + @minsize.setter + def minsize(self, val): + self["minsize"] = val + + @property + def mode(self): + """ + Determines how the font size for various text elements are + uniformed between each trace type. If the computed text sizes + were smaller than the minimum size defined by + `uniformtext.minsize` using "hide" option hides the text; and + using "show" option shows the text without further downscaling. + Please note that if the size defined by `minsize` is greater + than the font size defined by trace, then the `minsize` is + used. + + The 'mode' property is an enumeration that may be specified as: + - One of the following enumeration values: + [False, 'hide', 'show'] + + Returns + ------- + Any + """ + return self["mode"] + + @mode.setter + def mode(self, val): + self["mode"] = val + + @property + def _prop_descriptions(self): + return """\ + minsize + Sets the minimum text size between traces of the same + type. + mode + Determines how the font size for various text elements + are uniformed between each trace type. If the computed + text sizes were smaller than the minimum size defined + by `uniformtext.minsize` using "hide" option hides the + text; and using "show" option shows the text without + further downscaling. Please note that if the size + defined by `minsize` is greater than the font size + defined by trace, then the `minsize` is used. + """ + + def __init__(self, arg=None, minsize=None, mode=None, **kwargs): + """ + Construct a new Uniformtext object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.layout.Uniformtext` + minsize + Sets the minimum text size between traces of the same + type. + mode + Determines how the font size for various text elements + are uniformed between each trace type. If the computed + text sizes were smaller than the minimum size defined + by `uniformtext.minsize` using "hide" option hides the + text; and using "show" option shows the text without + further downscaling. Please note that if the size + defined by `minsize` is greater than the font size + defined by trace, then the `minsize` is used. + + Returns + ------- + Uniformtext + """ + super().__init__("uniformtext") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Uniformtext +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Uniformtext`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("minsize", arg, minsize) + self._set_property("mode", arg, mode) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_updatemenu.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_updatemenu.py new file mode 100644 index 0000000000000000000000000000000000000000..fe5abd7960e44100c7dd7d21d13d871e9ec6fcb6 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_updatemenu.py @@ -0,0 +1,632 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class Updatemenu(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.updatemenu" + _valid_props = { + "active", + "bgcolor", + "bordercolor", + "borderwidth", + "buttondefaults", + "buttons", + "direction", + "font", + "name", + "pad", + "showactive", + "templateitemname", + "type", + "visible", + "x", + "xanchor", + "y", + "yanchor", + } + + @property + def active(self): + """ + Determines which button (by index starting from 0) is + considered active. + + The 'active' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + + Returns + ------- + int + """ + return self["active"] + + @active.setter + def active(self, val): + self["active"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the update menu buttons. + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bordercolor(self): + """ + Sets the color of the border enclosing the update menu. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def borderwidth(self): + """ + Sets the width (in px) of the border enclosing the update menu. + + The 'borderwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["borderwidth"] + + @borderwidth.setter + def borderwidth(self, val): + self["borderwidth"] = val + + @property + def buttons(self): + """ + The 'buttons' property is a tuple of instances of + Button that may be specified as: + - A list or tuple of instances of plotly.graph_objs.layout.updatemenu.Button + - A list or tuple of dicts of string/value properties that + will be passed to the Button constructor + + Returns + ------- + tuple[plotly.graph_objs.layout.updatemenu.Button] + """ + return self["buttons"] + + @buttons.setter + def buttons(self, val): + self["buttons"] = val + + @property + def buttondefaults(self): + """ + When used in a template (as + layout.template.layout.updatemenu.buttondefaults), sets the + default property values to use for elements of + layout.updatemenu.buttons + + The 'buttondefaults' property is an instance of Button + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.updatemenu.Button` + - A dict of string/value properties that will be passed + to the Button constructor + + Returns + ------- + plotly.graph_objs.layout.updatemenu.Button + """ + return self["buttondefaults"] + + @buttondefaults.setter + def buttondefaults(self, val): + self["buttondefaults"] = val + + @property + def direction(self): + """ + Determines the direction in which the buttons are laid out, + whether in a dropdown menu or a row/column of buttons. For + `left` and `up`, the buttons will still appear in left-to-right + or top-to-bottom order respectively. + + The 'direction' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'up', 'down'] + + Returns + ------- + Any + """ + return self["direction"] + + @direction.setter + def direction(self, val): + self["direction"] = val + + @property + def font(self): + """ + Sets the font of the update menu button text. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.updatemenu.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.layout.updatemenu.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def name(self): + """ + When used in a template, named items are created in the output + figure in addition to any items the figure already has in this + array. You can modify these items in the output figure by + making your own item with `templateitemname` matching this + `name` alongside your modifications (including `visible: false` + or `enabled: false` to hide it). Has no effect outside of a + template. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def pad(self): + """ + Sets the padding around the buttons or dropdown menu. + + The 'pad' property is an instance of Pad + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.updatemenu.Pad` + - A dict of string/value properties that will be passed + to the Pad constructor + + Returns + ------- + plotly.graph_objs.layout.updatemenu.Pad + """ + return self["pad"] + + @pad.setter + def pad(self, val): + self["pad"] = val + + @property + def showactive(self): + """ + Highlights active dropdown item or active button if true. + + The 'showactive' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showactive"] + + @showactive.setter + def showactive(self, val): + self["showactive"] = val + + @property + def templateitemname(self): + """ + Used to refer to a named item in this array in the template. + Named items from the template will be created even without a + matching item in the input figure, but you can modify one by + making an item with `templateitemname` matching its `name`, + alongside your modifications (including `visible: false` or + `enabled: false` to hide it). If there is no template or no + matching item, this item will be hidden unless you explicitly + show it with `visible: true`. + + The 'templateitemname' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["templateitemname"] + + @templateitemname.setter + def templateitemname(self, val): + self["templateitemname"] = val + + @property + def type(self): + """ + Determines whether the buttons are accessible via a dropdown + menu or whether the buttons are stacked horizontally or + vertically + + The 'type' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['dropdown', 'buttons'] + + Returns + ------- + Any + """ + return self["type"] + + @type.setter + def type(self, val): + self["type"] = val + + @property + def visible(self): + """ + Determines whether or not the update menu is visible. + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def x(self): + """ + Sets the x position (in normalized coordinates) of the update + menu. + + The 'x' property is a number and may be specified as: + - An int or float in the interval [-2, 3] + + Returns + ------- + int|float + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xanchor(self): + """ + Sets the update menu's horizontal position anchor. This anchor + binds the `x` position to the "left", "center" or "right" of + the range selector. + + The 'xanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'left', 'center', 'right'] + + Returns + ------- + Any + """ + return self["xanchor"] + + @xanchor.setter + def xanchor(self, val): + self["xanchor"] = val + + @property + def y(self): + """ + Sets the y position (in normalized coordinates) of the update + menu. + + The 'y' property is a number and may be specified as: + - An int or float in the interval [-2, 3] + + Returns + ------- + int|float + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yanchor(self): + """ + Sets the update menu's vertical position anchor This anchor + binds the `y` position to the "top", "middle" or "bottom" of + the range selector. + + The 'yanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'top', 'middle', 'bottom'] + + Returns + ------- + Any + """ + return self["yanchor"] + + @yanchor.setter + def yanchor(self, val): + self["yanchor"] = val + + @property + def _prop_descriptions(self): + return """\ + active + Determines which button (by index starting from 0) is + considered active. + bgcolor + Sets the background color of the update menu buttons. + bordercolor + Sets the color of the border enclosing the update menu. + borderwidth + Sets the width (in px) of the border enclosing the + update menu. + buttons + A tuple of + :class:`plotly.graph_objects.layout.updatemenu.Button` + instances or dicts with compatible properties + buttondefaults + When used in a template (as + layout.template.layout.updatemenu.buttondefaults), sets + the default property values to use for elements of + layout.updatemenu.buttons + direction + Determines the direction in which the buttons are laid + out, whether in a dropdown menu or a row/column of + buttons. For `left` and `up`, the buttons will still + appear in left-to-right or top-to-bottom order + respectively. + font + Sets the font of the update menu button text. + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + pad + Sets the padding around the buttons or dropdown menu. + showactive + Highlights active dropdown item or active button if + true. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + type + Determines whether the buttons are accessible via a + dropdown menu or whether the buttons are stacked + horizontally or vertically + visible + Determines whether or not the update menu is visible. + x + Sets the x position (in normalized coordinates) of the + update menu. + xanchor + Sets the update menu's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the range selector. + y + Sets the y position (in normalized coordinates) of the + update menu. + yanchor + Sets the update menu's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the range selector. + """ + + def __init__( + self, + arg=None, + active=None, + bgcolor=None, + bordercolor=None, + borderwidth=None, + buttons=None, + buttondefaults=None, + direction=None, + font=None, + name=None, + pad=None, + showactive=None, + templateitemname=None, + type=None, + visible=None, + x=None, + xanchor=None, + y=None, + yanchor=None, + **kwargs, + ): + """ + Construct a new Updatemenu object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.layout.Updatemenu` + active + Determines which button (by index starting from 0) is + considered active. + bgcolor + Sets the background color of the update menu buttons. + bordercolor + Sets the color of the border enclosing the update menu. + borderwidth + Sets the width (in px) of the border enclosing the + update menu. + buttons + A tuple of + :class:`plotly.graph_objects.layout.updatemenu.Button` + instances or dicts with compatible properties + buttondefaults + When used in a template (as + layout.template.layout.updatemenu.buttondefaults), sets + the default property values to use for elements of + layout.updatemenu.buttons + direction + Determines the direction in which the buttons are laid + out, whether in a dropdown menu or a row/column of + buttons. For `left` and `up`, the buttons will still + appear in left-to-right or top-to-bottom order + respectively. + font + Sets the font of the update menu button text. + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + pad + Sets the padding around the buttons or dropdown menu. + showactive + Highlights active dropdown item or active button if + true. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + type + Determines whether the buttons are accessible via a + dropdown menu or whether the buttons are stacked + horizontally or vertically + visible + Determines whether or not the update menu is visible. + x + Sets the x position (in normalized coordinates) of the + update menu. + xanchor + Sets the update menu's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the range selector. + y + Sets the y position (in normalized coordinates) of the + update menu. + yanchor + Sets the update menu's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the range selector. + + Returns + ------- + Updatemenu + """ + super().__init__("updatemenus") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.Updatemenu +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.Updatemenu`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("active", arg, active) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("borderwidth", arg, borderwidth) + self._set_property("buttons", arg, buttons) + self._set_property("buttondefaults", arg, buttondefaults) + self._set_property("direction", arg, direction) + self._set_property("font", arg, font) + self._set_property("name", arg, name) + self._set_property("pad", arg, pad) + self._set_property("showactive", arg, showactive) + self._set_property("templateitemname", arg, templateitemname) + self._set_property("type", arg, type) + self._set_property("visible", arg, visible) + self._set_property("x", arg, x) + self._set_property("xanchor", arg, xanchor) + self._set_property("y", arg, y) + self._set_property("yanchor", arg, yanchor) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_xaxis.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_xaxis.py new file mode 100644 index 0000000000000000000000000000000000000000..a146cb6898a29c69fc3edeca7ff01d82a5d80ade --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_xaxis.py @@ -0,0 +1,3575 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class XAxis(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.xaxis" + _valid_props = { + "anchor", + "automargin", + "autorange", + "autorangeoptions", + "autotickangles", + "autotypenumbers", + "calendar", + "categoryarray", + "categoryarraysrc", + "categoryorder", + "color", + "constrain", + "constraintoward", + "dividercolor", + "dividerwidth", + "domain", + "dtick", + "exponentformat", + "fixedrange", + "gridcolor", + "griddash", + "gridwidth", + "hoverformat", + "insiderange", + "labelalias", + "layer", + "linecolor", + "linewidth", + "matches", + "maxallowed", + "minallowed", + "minexponent", + "minor", + "minorloglabels", + "mirror", + "modebardisable", + "nticks", + "overlaying", + "position", + "range", + "rangebreakdefaults", + "rangebreaks", + "rangemode", + "rangeselector", + "rangeslider", + "scaleanchor", + "scaleratio", + "separatethousands", + "showdividers", + "showexponent", + "showgrid", + "showline", + "showspikes", + "showticklabels", + "showtickprefix", + "showticksuffix", + "side", + "spikecolor", + "spikedash", + "spikemode", + "spikesnap", + "spikethickness", + "tick0", + "tickangle", + "tickcolor", + "tickfont", + "tickformat", + "tickformatstopdefaults", + "tickformatstops", + "ticklabelindex", + "ticklabelindexsrc", + "ticklabelmode", + "ticklabeloverflow", + "ticklabelposition", + "ticklabelshift", + "ticklabelstandoff", + "ticklabelstep", + "ticklen", + "tickmode", + "tickprefix", + "ticks", + "tickson", + "ticksuffix", + "ticktext", + "ticktextsrc", + "tickvals", + "tickvalssrc", + "tickwidth", + "title", + "type", + "uirevision", + "unifiedhovertitle", + "visible", + "zeroline", + "zerolinecolor", + "zerolinelayer", + "zerolinewidth", + } + + @property + def anchor(self): + """ + If set to an opposite-letter axis id (e.g. `x2`, `y`), this + axis is bound to the corresponding opposite-letter axis. If set + to "free", this axis' position is determined by `position`. + + The 'anchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['free'] + - A string that matches one of the following regular expressions: + ['^x([2-9]|[1-9][0-9]+)?( domain)?$', + '^y([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["anchor"] + + @anchor.setter + def anchor(self, val): + self["anchor"] = val + + @property + def automargin(self): + """ + Determines whether long tick labels automatically grow the + figure margins. + + The 'automargin' property is a flaglist and may be specified + as a string containing: + - Any combination of ['height', 'width', 'left', 'right', 'top', 'bottom'] joined with '+' characters + (e.g. 'height+width') + OR exactly one of [True, False] (e.g. 'False') + + Returns + ------- + Any + """ + return self["automargin"] + + @automargin.setter + def automargin(self, val): + self["automargin"] = val + + @property + def autorange(self): + """ + Determines whether or not the range of this axis is computed in + relation to the input data. See `rangemode` for more info. If + `range` is provided and it has a value for both the lower and + upper bound, `autorange` is set to False. Using "min" applies + autorange only to set the minimum. Using "max" applies + autorange only to set the maximum. Using *min reversed* applies + autorange only to set the minimum on a reversed axis. Using + *max reversed* applies autorange only to set the maximum on a + reversed axis. Using "reversed" applies autorange on both ends + and reverses the axis direction. + + The 'autorange' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'reversed', 'min reversed', 'max reversed', + 'min', 'max'] + + Returns + ------- + Any + """ + return self["autorange"] + + @autorange.setter + def autorange(self, val): + self["autorange"] = val + + @property + def autorangeoptions(self): + """ + The 'autorangeoptions' property is an instance of Autorangeoptions + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.xaxis.Autorangeoptions` + - A dict of string/value properties that will be passed + to the Autorangeoptions constructor + + Returns + ------- + plotly.graph_objs.layout.xaxis.Autorangeoptions + """ + return self["autorangeoptions"] + + @autorangeoptions.setter + def autorangeoptions(self, val): + self["autorangeoptions"] = val + + @property + def autotickangles(self): + """ + When `tickangle` is set to "auto", it will be set to the first + angle in this array that is large enough to prevent label + overlap. + + The 'autotickangles' property is an info array that may be specified as: + * a list of elements where: + The 'autotickangles[i]' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + list + """ + return self["autotickangles"] + + @autotickangles.setter + def autotickangles(self, val): + self["autotickangles"] = val + + @property + def autotypenumbers(self): + """ + Using "strict" a numeric string in trace data is not converted + to a number. Using *convert types* a numeric string in trace + data may be treated as a number during automatic axis `type` + detection. Defaults to layout.autotypenumbers. + + The 'autotypenumbers' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['convert types', 'strict'] + + Returns + ------- + Any + """ + return self["autotypenumbers"] + + @autotypenumbers.setter + def autotypenumbers(self, val): + self["autotypenumbers"] = val + + @property + def calendar(self): + """ + Sets the calendar system to use for `range` and `tick0` if this + is a date axis. This does not set the calendar for interpreting + data on this axis, that's specified in the trace or via the + global `layout.calendar` + + The 'calendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["calendar"] + + @calendar.setter + def calendar(self, val): + self["calendar"] = val + + @property + def categoryarray(self): + """ + Sets the order in which categories on this axis appear. Only + has an effect if `categoryorder` is set to "array". Used with + `categoryorder`. + + The 'categoryarray' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["categoryarray"] + + @categoryarray.setter + def categoryarray(self, val): + self["categoryarray"] = val + + @property + def categoryarraysrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `categoryarray`. + + The 'categoryarraysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["categoryarraysrc"] + + @categoryarraysrc.setter + def categoryarraysrc(self, val): + self["categoryarraysrc"] = val + + @property + def categoryorder(self): + """ + Specifies the ordering logic for the case of categorical + variables. By default, plotly uses "trace", which specifies the + order that is present in the data supplied. Set `categoryorder` + to *category ascending* or *category descending* if order + should be determined by the alphanumerical order of the + category names. Set `categoryorder` to "array" to derive the + ordering from the attribute `categoryarray`. If a category is + not found in the `categoryarray` array, the sorting behavior + for that attribute will be identical to the "trace" mode. The + unspecified categories will follow the categories in + `categoryarray`. Set `categoryorder` to *total ascending* or + *total descending* if order should be determined by the + numerical order of the values. Similarly, the order can be + determined by the min, max, sum, mean, geometric mean or median + of all the values. + + The 'categoryorder' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['trace', 'category ascending', 'category descending', + 'array', 'total ascending', 'total descending', 'min + ascending', 'min descending', 'max ascending', 'max + descending', 'sum ascending', 'sum descending', 'mean + ascending', 'mean descending', 'geometric mean ascending', + 'geometric mean descending', 'median ascending', 'median + descending'] + + Returns + ------- + Any + """ + return self["categoryorder"] + + @categoryorder.setter + def categoryorder(self, val): + self["categoryorder"] = val + + @property + def color(self): + """ + Sets default for all colors associated with this axis all at + once: line, font, tick, and grid colors. Grid color is + lightened by blending this with the plot background Individual + pieces can override this. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def constrain(self): + """ + If this axis needs to be compressed (either due to its own + `scaleanchor` and `scaleratio` or those of the other axis), + determines how that happens: by increasing the "range", or by + decreasing the "domain". Default is "domain" for axes + containing image traces, "range" otherwise. + + The 'constrain' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['range', 'domain'] + + Returns + ------- + Any + """ + return self["constrain"] + + @constrain.setter + def constrain(self, val): + self["constrain"] = val + + @property + def constraintoward(self): + """ + If this axis needs to be compressed (either due to its own + `scaleanchor` and `scaleratio` or those of the other axis), + determines which direction we push the originally specified + plot area. Options are "left", "center" (default), and "right" + for x axes, and "top", "middle" (default), and "bottom" for y + axes. + + The 'constraintoward' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'center', 'right', 'top', 'middle', 'bottom'] + + Returns + ------- + Any + """ + return self["constraintoward"] + + @constraintoward.setter + def constraintoward(self, val): + self["constraintoward"] = val + + @property + def dividercolor(self): + """ + Sets the color of the dividers Only has an effect on + "multicategory" axes. + + The 'dividercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["dividercolor"] + + @dividercolor.setter + def dividercolor(self, val): + self["dividercolor"] = val + + @property + def dividerwidth(self): + """ + Sets the width (in px) of the dividers Only has an effect on + "multicategory" axes. + + The 'dividerwidth' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dividerwidth"] + + @dividerwidth.setter + def dividerwidth(self, val): + self["dividerwidth"] = val + + @property + def domain(self): + """ + Sets the domain of this axis (in plot fraction). + + The 'domain' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'domain[0]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + (1) The 'domain[1]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + list + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def dtick(self): + """ + Sets the step in-between ticks on this axis. Use with `tick0`. + Must be a positive number, or special strings available to + "log" and "date" axes. If the axis `type` is "log", then ticks + are set every 10^(n*dtick) where n is the tick number. For + example, to set a tick mark at 1, 10, 100, 1000, ... set dtick + to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. + To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special values; + "L", where `f` is a positive number, gives ticks linearly + spaced in value (but not position). For example `tick0` = 0.1, + `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To + show powers of 10 plus small digits between, use "D1" (all + digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and + "D2". If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval between + ticks to one day, set `dtick` to 86400000.0. "date" also has + special values "M" gives ticks spaced by a number of months. + `n` must be a positive integer. To set ticks on the 15th of + every third month, set `tick0` to "2000-01-15" and `dtick` to + "M3". To set ticks every 4 years, set `dtick` to "M48" + + The 'dtick' property accepts values of any type + + Returns + ------- + Any + """ + return self["dtick"] + + @dtick.setter + def dtick(self, val): + self["dtick"] = val + + @property + def exponentformat(self): + """ + Determines a formatting rule for the tick exponents. For + example, consider the number 1,000,000,000. If "none", it + appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If + "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If + "B", 1B. "SI" uses prefixes from "femto" f (10^-15) to "tera" T + (10^12). *SI extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or *SI + extended* is used and the exponent is beyond the above ranges, + the formatting rule will automatically be switched to the power + notation. + + The 'exponentformat' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'e', 'E', 'power', 'SI', 'B', 'SI extended'] + + Returns + ------- + Any + """ + return self["exponentformat"] + + @exponentformat.setter + def exponentformat(self, val): + self["exponentformat"] = val + + @property + def fixedrange(self): + """ + Determines whether or not this axis is zoom-able. If true, then + zoom is disabled. + + The 'fixedrange' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["fixedrange"] + + @fixedrange.setter + def fixedrange(self, val): + self["fixedrange"] = val + + @property + def gridcolor(self): + """ + Sets the color of the grid lines. + + The 'gridcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["gridcolor"] + + @gridcolor.setter + def gridcolor(self, val): + self["gridcolor"] = val + + @property + def griddash(self): + """ + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + + The 'griddash' property is an enumeration that may be specified as: + - One of the following dash styles: + ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] + - A string containing a dash length list in pixels or percentages + (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) + + Returns + ------- + str + """ + return self["griddash"] + + @griddash.setter + def griddash(self, val): + self["griddash"] = val + + @property + def gridwidth(self): + """ + Sets the width (in px) of the grid lines. + + The 'gridwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["gridwidth"] + + @gridwidth.setter + def gridwidth(self, val): + self["gridwidth"] = val + + @property + def hoverformat(self): + """ + Sets the hover text formatting rule using d3 formatting mini- + languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display "09~15~23.46" + + The 'hoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["hoverformat"] + + @hoverformat.setter + def hoverformat(self, val): + self["hoverformat"] = val + + @property + def insiderange(self): + """ + Could be used to set the desired inside range of this axis + (excluding the labels) when `ticklabelposition` of the anchored + axis has "inside". Not implemented for axes with `type` "log". + This would be ignored when `range` is provided. + + The 'insiderange' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'insiderange[0]' property accepts values of any type + (1) The 'insiderange[1]' property accepts values of any type + + Returns + ------- + list + """ + return self["insiderange"] + + @insiderange.setter + def insiderange(self, val): + self["insiderange"] = val + + @property + def labelalias(self): + """ + Replacement text for specific tick or hover labels. For example + using {US: 'USA', CA: 'Canada'} changes US to USA and CA to + Canada. The labels we would have shown must match the keys + exactly, after adding any tickprefix or ticksuffix. For + negative numbers the minus sign symbol used (U+2212) is wider + than the regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis type, and + both keys (if needed) and values (if desired) can include html- + like tags or MathJax. + + The 'labelalias' property accepts values of any type + + Returns + ------- + Any + """ + return self["labelalias"] + + @labelalias.setter + def labelalias(self, val): + self["labelalias"] = val + + @property + def layer(self): + """ + Sets the layer on which this axis is displayed. If *above + traces*, this axis is displayed above all the subplot's traces + If *below traces*, this axis is displayed below all the + subplot's traces, but above the grid lines. Useful when used + together with scatter-like traces with `cliponaxis` set to + False to show markers and/or text nodes above this axis. + + The 'layer' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['above traces', 'below traces'] + + Returns + ------- + Any + """ + return self["layer"] + + @layer.setter + def layer(self, val): + self["layer"] = val + + @property + def linecolor(self): + """ + Sets the axis line color. + + The 'linecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["linecolor"] + + @linecolor.setter + def linecolor(self, val): + self["linecolor"] = val + + @property + def linewidth(self): + """ + Sets the width (in px) of the axis line. + + The 'linewidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["linewidth"] + + @linewidth.setter + def linewidth(self, val): + self["linewidth"] = val + + @property + def matches(self): + """ + If set to another axis id (e.g. `x2`, `y`), the range of this + axis will match the range of the corresponding axis in data- + coordinates space. Moreover, matching axes share auto-range + values, category lists and histogram auto-bins. Note that + setting axes simultaneously in both a `scaleanchor` and a + `matches` constraint is currently forbidden. Moreover, note + that matching axes must have the same `type`. + + The 'matches' property is an enumeration that may be specified as: + - A string that matches one of the following regular expressions: + ['^x([2-9]|[1-9][0-9]+)?( domain)?$', + '^y([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["matches"] + + @matches.setter + def matches(self, val): + self["matches"] = val + + @property + def maxallowed(self): + """ + Determines the maximum range of this axis. + + The 'maxallowed' property accepts values of any type + + Returns + ------- + Any + """ + return self["maxallowed"] + + @maxallowed.setter + def maxallowed(self, val): + self["maxallowed"] = val + + @property + def minallowed(self): + """ + Determines the minimum range of this axis. + + The 'minallowed' property accepts values of any type + + Returns + ------- + Any + """ + return self["minallowed"] + + @minallowed.setter + def minallowed(self, val): + self["minallowed"] = val + + @property + def minexponent(self): + """ + Hide SI prefix for 10^n if |n| is below this number. This only + has an effect when `tickformat` is "SI" or "B". + + The 'minexponent' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["minexponent"] + + @minexponent.setter + def minexponent(self, val): + self["minexponent"] = val + + @property + def minor(self): + """ + The 'minor' property is an instance of Minor + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.xaxis.Minor` + - A dict of string/value properties that will be passed + to the Minor constructor + + Returns + ------- + plotly.graph_objs.layout.xaxis.Minor + """ + return self["minor"] + + @minor.setter + def minor(self, val): + self["minor"] = val + + @property + def minorloglabels(self): + """ + Determines how minor log labels are displayed. If *small + digits*, small digits i.e. 2 or 5 are displayed. If "complete", + complete digits are displayed. If "none", no labels are + displayed. + + The 'minorloglabels' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['small digits', 'complete', 'none'] + + Returns + ------- + Any + """ + return self["minorloglabels"] + + @minorloglabels.setter + def minorloglabels(self, val): + self["minorloglabels"] = val + + @property + def mirror(self): + """ + Determines if the axis lines or/and ticks are mirrored to the + opposite side of the plotting area. If True, the axis lines are + mirrored. If "ticks", the axis lines and ticks are mirrored. If + False, mirroring is disable. If "all", axis lines are mirrored + on all shared-axes subplots. If "allticks", axis lines and + ticks are mirrored on all shared-axes subplots. + + The 'mirror' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, 'ticks', False, 'all', 'allticks'] + + Returns + ------- + Any + """ + return self["mirror"] + + @mirror.setter + def mirror(self, val): + self["mirror"] = val + + @property + def modebardisable(self): + """ + Disables certain modebar buttons for this axis. "autoscale" + disables the autoscale buttons, "zoominout" disables the zoom- + in and zoom-out buttons. + + The 'modebardisable' property is a flaglist and may be specified + as a string containing: + - Any combination of ['autoscale', 'zoominout'] joined with '+' characters + (e.g. 'autoscale+zoominout') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["modebardisable"] + + @modebardisable.setter + def modebardisable(self, val): + self["modebardisable"] = val + + @property + def nticks(self): + """ + Specifies the maximum number of ticks for the particular axis. + The actual number of ticks will be chosen automatically to be + less than or equal to `nticks`. Has an effect only if + `tickmode` is set to "auto". + + The 'nticks' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["nticks"] + + @nticks.setter + def nticks(self, val): + self["nticks"] = val + + @property + def overlaying(self): + """ + If set a same-letter axis id, this axis is overlaid on top of + the corresponding same-letter axis, with traces and axes + visible for both axes. If False, this axis does not overlay any + same-letter axes. In this case, for axes with overlapping + domains only the highest-numbered axis will be visible. + + The 'overlaying' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['free'] + - A string that matches one of the following regular expressions: + ['^x([2-9]|[1-9][0-9]+)?( domain)?$', + '^y([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["overlaying"] + + @overlaying.setter + def overlaying(self, val): + self["overlaying"] = val + + @property + def position(self): + """ + Sets the position of this axis in the plotting space (in + normalized coordinates). Only has an effect if `anchor` is set + to "free". + + The 'position' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["position"] + + @position.setter + def position(self, val): + self["position"] = val + + @property + def range(self): + """ + Sets the range of this axis. If the axis `type` is "log", then + you must take the log of your desired range (e.g. to set the + range from 1 to 100, set the range from 0 to 2). If the axis + `type` is "date", it should be date strings, like date data, + though Date objects and unix milliseconds will be accepted and + converted to strings. If the axis `type` is "category", it + should be numbers, using the scale where each category is + assigned a serial number from zero in the order it appears. + Leaving either or both elements `null` impacts the default + `autorange`. + + The 'range' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'range[0]' property accepts values of any type + (1) The 'range[1]' property accepts values of any type + + Returns + ------- + list + """ + return self["range"] + + @range.setter + def range(self, val): + self["range"] = val + + @property + def rangebreaks(self): + """ + The 'rangebreaks' property is a tuple of instances of + Rangebreak that may be specified as: + - A list or tuple of instances of plotly.graph_objs.layout.xaxis.Rangebreak + - A list or tuple of dicts of string/value properties that + will be passed to the Rangebreak constructor + + Returns + ------- + tuple[plotly.graph_objs.layout.xaxis.Rangebreak] + """ + return self["rangebreaks"] + + @rangebreaks.setter + def rangebreaks(self, val): + self["rangebreaks"] = val + + @property + def rangebreakdefaults(self): + """ + When used in a template (as + layout.template.layout.xaxis.rangebreakdefaults), sets the + default property values to use for elements of + layout.xaxis.rangebreaks + + The 'rangebreakdefaults' property is an instance of Rangebreak + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.xaxis.Rangebreak` + - A dict of string/value properties that will be passed + to the Rangebreak constructor + + Returns + ------- + plotly.graph_objs.layout.xaxis.Rangebreak + """ + return self["rangebreakdefaults"] + + @rangebreakdefaults.setter + def rangebreakdefaults(self, val): + self["rangebreakdefaults"] = val + + @property + def rangemode(self): + """ + If "normal", the range is computed in relation to the extrema + of the input data. If "tozero", the range extends to 0, + regardless of the input data If "nonnegative", the range is + non-negative, regardless of the input data. Applies only to + linear axes. + + The 'rangemode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'tozero', 'nonnegative'] + + Returns + ------- + Any + """ + return self["rangemode"] + + @rangemode.setter + def rangemode(self, val): + self["rangemode"] = val + + @property + def rangeselector(self): + """ + The 'rangeselector' property is an instance of Rangeselector + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.xaxis.Rangeselector` + - A dict of string/value properties that will be passed + to the Rangeselector constructor + + Returns + ------- + plotly.graph_objs.layout.xaxis.Rangeselector + """ + return self["rangeselector"] + + @rangeselector.setter + def rangeselector(self, val): + self["rangeselector"] = val + + @property + def rangeslider(self): + """ + The 'rangeslider' property is an instance of Rangeslider + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.xaxis.Rangeslider` + - A dict of string/value properties that will be passed + to the Rangeslider constructor + + Returns + ------- + plotly.graph_objs.layout.xaxis.Rangeslider + """ + return self["rangeslider"] + + @rangeslider.setter + def rangeslider(self, val): + self["rangeslider"] = val + + @property + def scaleanchor(self): + """ + If set to another axis id (e.g. `x2`, `y`), the range of this + axis changes together with the range of the corresponding axis + such that the scale of pixels per unit is in a constant ratio. + Both axes are still zoomable, but when you zoom one, the other + will zoom the same amount, keeping a fixed midpoint. + `constrain` and `constraintoward` determine how we enforce the + constraint. You can chain these, ie `yaxis: {scaleanchor: *x*}, + xaxis2: {scaleanchor: *y*}` but you can only link axes of the + same `type`. The linked axis can have the opposite letter (to + constrain the aspect ratio) or the same letter (to match scales + across subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: + {scaleanchor: *y*}` or longer) are redundant and the last + constraint encountered will be ignored to avoid possible + inconsistent constraints via `scaleratio`. Note that setting + axes simultaneously in both a `scaleanchor` and a `matches` + constraint is currently forbidden. Setting `false` allows to + remove a default constraint (occasionally, you may need to + prevent a default `scaleanchor` constraint from being applied, + eg. when having an image trace `yaxis: {scaleanchor: "x"}` is + set automatically in order for pixels to be rendered as + squares, setting `yaxis: {scaleanchor: false}` allows to remove + the constraint). + + The 'scaleanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + [False] + - A string that matches one of the following regular expressions: + ['^x([2-9]|[1-9][0-9]+)?( domain)?$', + '^y([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["scaleanchor"] + + @scaleanchor.setter + def scaleanchor(self, val): + self["scaleanchor"] = val + + @property + def scaleratio(self): + """ + If this axis is linked to another by `scaleanchor`, this + determines the pixel to unit scale ratio. For example, if this + value is 10, then every unit on this axis spans 10 times the + number of pixels as a unit on the linked axis. Use this for + example to create an elevation profile where the vertical scale + is exaggerated a fixed amount with respect to the horizontal. + + The 'scaleratio' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["scaleratio"] + + @scaleratio.setter + def scaleratio(self, val): + self["scaleratio"] = val + + @property + def separatethousands(self): + """ + If "true", even 4-digit integers are separated + + The 'separatethousands' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["separatethousands"] + + @separatethousands.setter + def separatethousands(self, val): + self["separatethousands"] = val + + @property + def showdividers(self): + """ + Determines whether or not a dividers are drawn between the + category levels of this axis. Only has an effect on + "multicategory" axes. + + The 'showdividers' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showdividers"] + + @showdividers.setter + def showdividers(self, val): + self["showdividers"] = val + + @property + def showexponent(self): + """ + If "all", all exponents are shown besides their significands. + If "first", only the exponent of the first tick is shown. If + "last", only the exponent of the last tick is shown. If "none", + no exponents appear. + + The 'showexponent' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showexponent"] + + @showexponent.setter + def showexponent(self, val): + self["showexponent"] = val + + @property + def showgrid(self): + """ + Determines whether or not grid lines are drawn. If True, the + grid lines are drawn at every tick mark. + + The 'showgrid' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showgrid"] + + @showgrid.setter + def showgrid(self, val): + self["showgrid"] = val + + @property + def showline(self): + """ + Determines whether or not a line bounding this axis is drawn. + + The 'showline' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showline"] + + @showline.setter + def showline(self, val): + self["showline"] = val + + @property + def showspikes(self): + """ + Determines whether or not spikes (aka droplines) are drawn for + this axis. Note: This only takes affect when hovermode = + closest + + The 'showspikes' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showspikes"] + + @showspikes.setter + def showspikes(self, val): + self["showspikes"] = val + + @property + def showticklabels(self): + """ + Determines whether or not the tick labels are drawn. + + The 'showticklabels' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showticklabels"] + + @showticklabels.setter + def showticklabels(self, val): + self["showticklabels"] = val + + @property + def showtickprefix(self): + """ + If "all", all tick labels are displayed with a prefix. If + "first", only the first tick is displayed with a prefix. If + "last", only the last tick is displayed with a suffix. If + "none", tick prefixes are hidden. + + The 'showtickprefix' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showtickprefix"] + + @showtickprefix.setter + def showtickprefix(self, val): + self["showtickprefix"] = val + + @property + def showticksuffix(self): + """ + Same as `showtickprefix` but for tick suffixes. + + The 'showticksuffix' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showticksuffix"] + + @showticksuffix.setter + def showticksuffix(self, val): + self["showticksuffix"] = val + + @property + def side(self): + """ + Determines whether a x (y) axis is positioned at the "bottom" + ("left") or "top" ("right") of the plotting area. + + The 'side' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top', 'bottom', 'left', 'right'] + + Returns + ------- + Any + """ + return self["side"] + + @side.setter + def side(self, val): + self["side"] = val + + @property + def spikecolor(self): + """ + Sets the spike color. If undefined, will use the series color + + The 'spikecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["spikecolor"] + + @spikecolor.setter + def spikecolor(self, val): + self["spikecolor"] = val + + @property + def spikedash(self): + """ + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + + The 'spikedash' property is an enumeration that may be specified as: + - One of the following dash styles: + ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] + - A string containing a dash length list in pixels or percentages + (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) + + Returns + ------- + str + """ + return self["spikedash"] + + @spikedash.setter + def spikedash(self, val): + self["spikedash"] = val + + @property + def spikemode(self): + """ + Determines the drawing mode for the spike line If "toaxis", the + line is drawn from the data point to the axis the series is + plotted on. If "across", the line is drawn across the entire + plot area, and supercedes "toaxis". If "marker", then a marker + dot is drawn on the axis the series is plotted on + + The 'spikemode' property is a flaglist and may be specified + as a string containing: + - Any combination of ['toaxis', 'across', 'marker'] joined with '+' characters + (e.g. 'toaxis+across') + + Returns + ------- + Any + """ + return self["spikemode"] + + @spikemode.setter + def spikemode(self, val): + self["spikemode"] = val + + @property + def spikesnap(self): + """ + Determines whether spikelines are stuck to the cursor or to the + closest datapoints. + + The 'spikesnap' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['data', 'cursor', 'hovered data'] + + Returns + ------- + Any + """ + return self["spikesnap"] + + @spikesnap.setter + def spikesnap(self, val): + self["spikesnap"] = val + + @property + def spikethickness(self): + """ + Sets the width (in px) of the zero line. + + The 'spikethickness' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["spikethickness"] + + @spikethickness.setter + def spikethickness(self, val): + self["spikethickness"] = val + + @property + def tick0(self): + """ + Sets the placement of the first tick on this axis. Use with + `dtick`. If the axis `type` is "log", then you must take the + log of your starting tick (e.g. to set the starting tick to + 100, set the `tick0` to 2) except when `dtick`=*L* (see + `dtick` for more info). If the axis `type` is "date", it should + be a date string, like date data. If the axis `type` is + "category", it should be a number, using the scale where each + category is assigned a serial number from zero in the order it + appears. + + The 'tick0' property accepts values of any type + + Returns + ------- + Any + """ + return self["tick0"] + + @tick0.setter + def tick0(self, val): + self["tick0"] = val + + @property + def tickangle(self): + """ + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the tick + labels vertically. + + The 'tickangle' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["tickangle"] + + @tickangle.setter + def tickangle(self, val): + self["tickangle"] = val + + @property + def tickcolor(self): + """ + Sets the tick color. + + The 'tickcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["tickcolor"] + + @tickcolor.setter + def tickcolor(self, val): + self["tickcolor"] = val + + @property + def tickfont(self): + """ + Sets the tick font. + + The 'tickfont' property is an instance of Tickfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.xaxis.Tickfont` + - A dict of string/value properties that will be passed + to the Tickfont constructor + + Returns + ------- + plotly.graph_objs.layout.xaxis.Tickfont + """ + return self["tickfont"] + + @tickfont.setter + def tickfont(self, val): + self["tickfont"] = val + + @property + def tickformat(self): + """ + Sets the tick label formatting rule using d3 formatting mini- + languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display "09~15~23.46" + + The 'tickformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["tickformat"] + + @tickformat.setter + def tickformat(self, val): + self["tickformat"] = val + + @property + def tickformatstops(self): + """ + The 'tickformatstops' property is a tuple of instances of + Tickformatstop that may be specified as: + - A list or tuple of instances of plotly.graph_objs.layout.xaxis.Tickformatstop + - A list or tuple of dicts of string/value properties that + will be passed to the Tickformatstop constructor + + Returns + ------- + tuple[plotly.graph_objs.layout.xaxis.Tickformatstop] + """ + return self["tickformatstops"] + + @tickformatstops.setter + def tickformatstops(self, val): + self["tickformatstops"] = val + + @property + def tickformatstopdefaults(self): + """ + When used in a template (as + layout.template.layout.xaxis.tickformatstopdefaults), sets the + default property values to use for elements of + layout.xaxis.tickformatstops + + The 'tickformatstopdefaults' property is an instance of Tickformatstop + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.xaxis.Tickformatstop` + - A dict of string/value properties that will be passed + to the Tickformatstop constructor + + Returns + ------- + plotly.graph_objs.layout.xaxis.Tickformatstop + """ + return self["tickformatstopdefaults"] + + @tickformatstopdefaults.setter + def tickformatstopdefaults(self, val): + self["tickformatstopdefaults"] = val + + @property + def ticklabelindex(self): + """ + Only for axes with `type` "date" or "linear". Instead of + drawing the major tick label, draw the label for the minor tick + that is n positions away from the major tick. E.g. to always + draw the label for the minor tick before each major tick, + choose `ticklabelindex` -1. This is useful for date axes with + `ticklabelmode` "period" if you want to label the period that + ends with each major tick instead of the period that begins + there. + + The 'ticklabelindex' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["ticklabelindex"] + + @ticklabelindex.setter + def ticklabelindex(self, val): + self["ticklabelindex"] = val + + @property + def ticklabelindexsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `ticklabelindex`. + + The 'ticklabelindexsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ticklabelindexsrc"] + + @ticklabelindexsrc.setter + def ticklabelindexsrc(self, val): + self["ticklabelindexsrc"] = val + + @property + def ticklabelmode(self): + """ + Determines where tick labels are drawn with respect to their + corresponding ticks and grid lines. Only has an effect for axes + of `type` "date" When set to "period", tick labels are drawn in + the middle of the period between ticks. + + The 'ticklabelmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['instant', 'period'] + + Returns + ------- + Any + """ + return self["ticklabelmode"] + + @ticklabelmode.setter + def ticklabelmode(self, val): + self["ticklabelmode"] = val + + @property + def ticklabeloverflow(self): + """ + Determines how we handle tick labels that would overflow either + the graph div or the domain of the axis. The default value for + inside tick labels is *hide past domain*. Otherwise on + "category" and "multicategory" axes the default is "allow". In + other cases the default is *hide past div*. + + The 'ticklabeloverflow' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['allow', 'hide past div', 'hide past domain'] + + Returns + ------- + Any + """ + return self["ticklabeloverflow"] + + @ticklabeloverflow.setter + def ticklabeloverflow(self, val): + self["ticklabeloverflow"] = val + + @property + def ticklabelposition(self): + """ + Determines where tick labels are drawn with respect to the + axis. Please note that top or bottom has no effect on x axes or + when `ticklabelmode` is set to "period" or when `tickson` is + set to "boundaries". Similarly, left or right has no effect on + y axes or when `ticklabelmode` is set to "period" or when + `tickson` is set to "boundaries". Has no effect on + "multicategory" axes. When used on axes linked by `matches` or + `scaleanchor`, no extra padding for inside labels would be + added by autorange, so that the scales could match. + + The 'ticklabelposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['outside', 'inside', 'outside top', 'inside top', + 'outside left', 'inside left', 'outside right', 'inside + right', 'outside bottom', 'inside bottom'] + + Returns + ------- + Any + """ + return self["ticklabelposition"] + + @ticklabelposition.setter + def ticklabelposition(self, val): + self["ticklabelposition"] = val + + @property + def ticklabelshift(self): + """ + Shifts the tick labels by the specified number of pixels in + parallel to the axis. Positive values move the labels in the + positive direction of the axis. + + The 'ticklabelshift' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["ticklabelshift"] + + @ticklabelshift.setter + def ticklabelshift(self, val): + self["ticklabelshift"] = val + + @property + def ticklabelstandoff(self): + """ + Sets the standoff distance (in px) between the axis tick labels + and their default position. A positive `ticklabelstandoff` + moves the labels farther away from the plot area if + `ticklabelposition` is "outside", and deeper into the plot area + if `ticklabelposition` is "inside". A negative + `ticklabelstandoff` works in the opposite direction, moving + outside ticks towards the plot area and inside ticks towards + the outside. If the negative value is large enough, inside + ticks can even end up outside and vice versa. + + The 'ticklabelstandoff' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["ticklabelstandoff"] + + @ticklabelstandoff.setter + def ticklabelstandoff(self, val): + self["ticklabelstandoff"] = val + + @property + def ticklabelstep(self): + """ + Sets the spacing between tick labels as compared to the spacing + between ticks. A value of 1 (default) means each tick gets a + label. A value of 2 means shows every 2nd label. A larger value + n means only every nth tick is labeled. `tick0` determines + which labels are shown. Not implemented for axes with `type` + "log" or "multicategory", or when `tickmode` is "array". + + The 'ticklabelstep' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 9223372036854775807] + + Returns + ------- + int + """ + return self["ticklabelstep"] + + @ticklabelstep.setter + def ticklabelstep(self, val): + self["ticklabelstep"] = val + + @property + def ticklen(self): + """ + Sets the tick length (in px). + + The 'ticklen' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["ticklen"] + + @ticklen.setter + def ticklen(self, val): + self["ticklen"] = val + + @property + def tickmode(self): + """ + Sets the tick mode for this axis. If "auto", the number of + ticks is set via `nticks`. If "linear", the placement of the + ticks is determined by a starting position `tick0` and a tick + step `dtick` ("linear" is the default value if `tick0` and + `dtick` are provided). If "array", the placement of the ticks + is set via `tickvals` and the tick text is `ticktext`. ("array" + is the default value if `tickvals` is provided). If "sync", the + number of ticks will sync with the overlayed axis set by + `overlaying` property. + + The 'tickmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'linear', 'array', 'sync'] + + Returns + ------- + Any + """ + return self["tickmode"] + + @tickmode.setter + def tickmode(self, val): + self["tickmode"] = val + + @property + def tickprefix(self): + """ + Sets a tick label prefix. + + The 'tickprefix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["tickprefix"] + + @tickprefix.setter + def tickprefix(self, val): + self["tickprefix"] = val + + @property + def ticks(self): + """ + Determines whether ticks are drawn or not. If "", this axis' + ticks are not drawn. If "outside" ("inside"), this axis' are + drawn outside (inside) the axis lines. + + The 'ticks' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['outside', 'inside', ''] + + Returns + ------- + Any + """ + return self["ticks"] + + @ticks.setter + def ticks(self, val): + self["ticks"] = val + + @property + def tickson(self): + """ + Determines where ticks and grid lines are drawn with respect to + their corresponding tick labels. Only has an effect for axes of + `type` "category" or "multicategory". When set to "boundaries", + ticks and grid lines are drawn half a category to the + left/bottom of labels. + + The 'tickson' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['labels', 'boundaries'] + + Returns + ------- + Any + """ + return self["tickson"] + + @tickson.setter + def tickson(self, val): + self["tickson"] = val + + @property + def ticksuffix(self): + """ + Sets a tick label suffix. + + The 'ticksuffix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["ticksuffix"] + + @ticksuffix.setter + def ticksuffix(self, val): + self["ticksuffix"] = val + + @property + def ticktext(self): + """ + Sets the text displayed at the ticks position via `tickvals`. + Only has an effect if `tickmode` is set to "array". Used with + `tickvals`. + + The 'ticktext' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ticktext"] + + @ticktext.setter + def ticktext(self, val): + self["ticktext"] = val + + @property + def ticktextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ticktext`. + + The 'ticktextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ticktextsrc"] + + @ticktextsrc.setter + def ticktextsrc(self, val): + self["ticktextsrc"] = val + + @property + def tickvals(self): + """ + Sets the values at which ticks on this axis appear. Only has an + effect if `tickmode` is set to "array". Used with `ticktext`. + + The 'tickvals' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["tickvals"] + + @tickvals.setter + def tickvals(self, val): + self["tickvals"] = val + + @property + def tickvalssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `tickvals`. + + The 'tickvalssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["tickvalssrc"] + + @tickvalssrc.setter + def tickvalssrc(self, val): + self["tickvalssrc"] = val + + @property + def tickwidth(self): + """ + Sets the tick width (in px). + + The 'tickwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["tickwidth"] + + @tickwidth.setter + def tickwidth(self, val): + self["tickwidth"] = val + + @property + def title(self): + """ + The 'title' property is an instance of Title + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.xaxis.Title` + - A dict of string/value properties that will be passed + to the Title constructor + + Returns + ------- + plotly.graph_objs.layout.xaxis.Title + """ + return self["title"] + + @title.setter + def title(self, val): + self["title"] = val + + @property + def type(self): + """ + Sets the axis type. By default, plotly attempts to determined + the axis type by looking into the data of the traces that + referenced the axis in question. + + The 'type' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['-', 'linear', 'log', 'date', 'category', + 'multicategory'] + + Returns + ------- + Any + """ + return self["type"] + + @type.setter + def type(self, val): + self["type"] = val + + @property + def uirevision(self): + """ + Controls persistence of user-driven changes in axis `range`, + `autorange`, and `title` if in `editable: true` configuration. + Defaults to `layout.uirevision`. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unifiedhovertitle(self): + """ + The 'unifiedhovertitle' property is an instance of Unifiedhovertitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.xaxis.Unifiedhovertitle` + - A dict of string/value properties that will be passed + to the Unifiedhovertitle constructor + + Returns + ------- + plotly.graph_objs.layout.xaxis.Unifiedhovertitle + """ + return self["unifiedhovertitle"] + + @unifiedhovertitle.setter + def unifiedhovertitle(self, val): + self["unifiedhovertitle"] = val + + @property + def visible(self): + """ + A single toggle to hide the axis while preserving interaction + like dragging. Default is true when a cheater plot is present + on the axis, otherwise false + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def zeroline(self): + """ + Determines whether or not a line is drawn at along the 0 value + of this axis. If True, the zero line is drawn on top of the + grid lines. + + The 'zeroline' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["zeroline"] + + @zeroline.setter + def zeroline(self, val): + self["zeroline"] = val + + @property + def zerolinecolor(self): + """ + Sets the line color of the zero line. + + The 'zerolinecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["zerolinecolor"] + + @zerolinecolor.setter + def zerolinecolor(self, val): + self["zerolinecolor"] = val + + @property + def zerolinelayer(self): + """ + Sets the layer on which this zeroline is displayed. If *above + traces*, this zeroline is displayed above all the subplot's + traces If *below traces*, this zeroline is displayed below all + the subplot's traces, but above the grid lines. Limitation: + "zerolinelayer" currently has no effect if the "zorder" + property is set on any trace. + + The 'zerolinelayer' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['above traces', 'below traces'] + + Returns + ------- + Any + """ + return self["zerolinelayer"] + + @zerolinelayer.setter + def zerolinelayer(self, val): + self["zerolinelayer"] = val + + @property + def zerolinewidth(self): + """ + Sets the width (in px) of the zero line. + + The 'zerolinewidth' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zerolinewidth"] + + @zerolinewidth.setter + def zerolinewidth(self, val): + self["zerolinewidth"] = val + + @property + def _prop_descriptions(self): + return """\ + anchor + If set to an opposite-letter axis id (e.g. `x2`, `y`), + this axis is bound to the corresponding opposite-letter + axis. If set to "free", this axis' position is + determined by `position`. + automargin + Determines whether long tick labels automatically grow + the figure margins. + autorange + Determines whether or not the range of this axis is + computed in relation to the input data. See `rangemode` + for more info. If `range` is provided and it has a + value for both the lower and upper bound, `autorange` + is set to False. Using "min" applies autorange only to + set the minimum. Using "max" applies autorange only to + set the maximum. Using *min reversed* applies autorange + only to set the minimum on a reversed axis. Using *max + reversed* applies autorange only to set the maximum on + a reversed axis. Using "reversed" applies autorange on + both ends and reverses the axis direction. + autorangeoptions + :class:`plotly.graph_objects.layout.xaxis.Autorangeopti + ons` instance or dict with compatible properties + autotickangles + When `tickangle` is set to "auto", it will be set to + the first angle in this array that is large enough to + prevent label overlap. + autotypenumbers + Using "strict" a numeric string in trace data is not + converted to a number. Using *convert types* a numeric + string in trace data may be treated as a number during + automatic axis `type` detection. Defaults to + layout.autotypenumbers. + calendar + Sets the calendar system to use for `range` and `tick0` + if this is a date axis. This does not set the calendar + for interpreting data on this axis, that's specified in + the trace or via the global `layout.calendar` + categoryarray + Sets the order in which categories on this axis appear. + Only has an effect if `categoryorder` is set to + "array". Used with `categoryorder`. + categoryarraysrc + Sets the source reference on Chart Studio Cloud for + `categoryarray`. + categoryorder + Specifies the ordering logic for the case of + categorical variables. By default, plotly uses "trace", + which specifies the order that is present in the data + supplied. Set `categoryorder` to *category ascending* + or *category descending* if order should be determined + by the alphanumerical order of the category names. Set + `categoryorder` to "array" to derive the ordering from + the attribute `categoryarray`. If a category is not + found in the `categoryarray` array, the sorting + behavior for that attribute will be identical to the + "trace" mode. The unspecified categories will follow + the categories in `categoryarray`. Set `categoryorder` + to *total ascending* or *total descending* if order + should be determined by the numerical order of the + values. Similarly, the order can be determined by the + min, max, sum, mean, geometric mean or median of all + the values. + color + Sets default for all colors associated with this axis + all at once: line, font, tick, and grid colors. Grid + color is lightened by blending this with the plot + background Individual pieces can override this. + constrain + If this axis needs to be compressed (either due to its + own `scaleanchor` and `scaleratio` or those of the + other axis), determines how that happens: by increasing + the "range", or by decreasing the "domain". Default is + "domain" for axes containing image traces, "range" + otherwise. + constraintoward + If this axis needs to be compressed (either due to its + own `scaleanchor` and `scaleratio` or those of the + other axis), determines which direction we push the + originally specified plot area. Options are "left", + "center" (default), and "right" for x axes, and "top", + "middle" (default), and "bottom" for y axes. + dividercolor + Sets the color of the dividers Only has an effect on + "multicategory" axes. + dividerwidth + Sets the width (in px) of the dividers Only has an + effect on "multicategory" axes. + domain + Sets the domain of this axis (in plot fraction). + dtick + Sets the step in-between ticks on this axis. Use with + `tick0`. Must be a positive number, or special strings + available to "log" and "date" axes. If the axis `type` + is "log", then ticks are set every 10^(n*dtick) where n + is the tick number. For example, to set a tick mark at + 1, 10, 100, 1000, ... set dtick to 1. To set tick marks + at 1, 100, 10000, ... set dtick to 2. To set tick marks + at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special + values; "L", where `f` is a positive number, gives + ticks linearly spaced in value (but not position). For + example `tick0` = 0.1, `dtick` = "L0.5" will put ticks + at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus + small digits between, use "D1" (all digits) or "D2" + (only 2 and 5). `tick0` is ignored for "D1" and "D2". + If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval + between ticks to one day, set `dtick` to 86400000.0. + "date" also has special values "M" gives ticks + spaced by a number of months. `n` must be a positive + integer. To set ticks on the 15th of every third month, + set `tick0` to "2000-01-15" and `dtick` to "M3". To set + ticks every 4 years, set `dtick` to "M48" + exponentformat + Determines a formatting rule for the tick exponents. + For example, consider the number 1,000,000,000. If + "none", it appears as 1,000,000,000. If "e", 1e+9. If + "E", 1E+9. If "power", 1x10^9 (with 9 in a super + script). If "SI", 1G. If "B", 1B. "SI" uses prefixes + from "femto" f (10^-15) to "tera" T (10^12). *SI + extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or + *SI extended* is used and the exponent is beyond the + above ranges, the formatting rule will automatically be + switched to the power notation. + fixedrange + Determines whether or not this axis is zoom-able. If + true, then zoom is disabled. + gridcolor + Sets the color of the grid lines. + griddash + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + gridwidth + Sets the width (in px) of the grid lines. + hoverformat + Sets the hover text formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + insiderange + Could be used to set the desired inside range of this + axis (excluding the labels) when `ticklabelposition` of + the anchored axis has "inside". Not implemented for + axes with `type` "log". This would be ignored when + `range` is provided. + labelalias + Replacement text for specific tick or hover labels. For + example using {US: 'USA', CA: 'Canada'} changes US to + USA and CA to Canada. The labels we would have shown + must match the keys exactly, after adding any + tickprefix or ticksuffix. For negative numbers the + minus sign symbol used (U+2212) is wider than the + regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis + type, and both keys (if needed) and values (if desired) + can include html-like tags or MathJax. + layer + Sets the layer on which this axis is displayed. If + *above traces*, this axis is displayed above all the + subplot's traces If *below traces*, this axis is + displayed below all the subplot's traces, but above the + grid lines. Useful when used together with scatter-like + traces with `cliponaxis` set to False to show markers + and/or text nodes above this axis. + linecolor + Sets the axis line color. + linewidth + Sets the width (in px) of the axis line. + matches + If set to another axis id (e.g. `x2`, `y`), the range + of this axis will match the range of the corresponding + axis in data-coordinates space. Moreover, matching axes + share auto-range values, category lists and histogram + auto-bins. Note that setting axes simultaneously in + both a `scaleanchor` and a `matches` constraint is + currently forbidden. Moreover, note that matching axes + must have the same `type`. + maxallowed + Determines the maximum range of this axis. + minallowed + Determines the minimum range of this axis. + minexponent + Hide SI prefix for 10^n if |n| is below this number. + This only has an effect when `tickformat` is "SI" or + "B". + minor + :class:`plotly.graph_objects.layout.xaxis.Minor` + instance or dict with compatible properties + minorloglabels + Determines how minor log labels are displayed. If + *small digits*, small digits i.e. 2 or 5 are displayed. + If "complete", complete digits are displayed. If + "none", no labels are displayed. + mirror + Determines if the axis lines or/and ticks are mirrored + to the opposite side of the plotting area. If True, the + axis lines are mirrored. If "ticks", the axis lines and + ticks are mirrored. If False, mirroring is disable. If + "all", axis lines are mirrored on all shared-axes + subplots. If "allticks", axis lines and ticks are + mirrored on all shared-axes subplots. + modebardisable + Disables certain modebar buttons for this axis. + "autoscale" disables the autoscale buttons, "zoominout" + disables the zoom-in and zoom-out buttons. + nticks + Specifies the maximum number of ticks for the + particular axis. The actual number of ticks will be + chosen automatically to be less than or equal to + `nticks`. Has an effect only if `tickmode` is set to + "auto". + overlaying + If set a same-letter axis id, this axis is overlaid on + top of the corresponding same-letter axis, with traces + and axes visible for both axes. If False, this axis + does not overlay any same-letter axes. In this case, + for axes with overlapping domains only the highest- + numbered axis will be visible. + position + Sets the position of this axis in the plotting space + (in normalized coordinates). Only has an effect if + `anchor` is set to "free". + range + Sets the range of this axis. If the axis `type` is + "log", then you must take the log of your desired range + (e.g. to set the range from 1 to 100, set the range + from 0 to 2). If the axis `type` is "date", it should + be date strings, like date data, though Date objects + and unix milliseconds will be accepted and converted to + strings. If the axis `type` is "category", it should be + numbers, using the scale where each category is + assigned a serial number from zero in the order it + appears. Leaving either or both elements `null` impacts + the default `autorange`. + rangebreaks + A tuple of + :class:`plotly.graph_objects.layout.xaxis.Rangebreak` + instances or dicts with compatible properties + rangebreakdefaults + When used in a template (as + layout.template.layout.xaxis.rangebreakdefaults), sets + the default property values to use for elements of + layout.xaxis.rangebreaks + rangemode + If "normal", the range is computed in relation to the + extrema of the input data. If "tozero", the range + extends to 0, regardless of the input data If + "nonnegative", the range is non-negative, regardless of + the input data. Applies only to linear axes. + rangeselector + :class:`plotly.graph_objects.layout.xaxis.Rangeselector + ` instance or dict with compatible properties + rangeslider + :class:`plotly.graph_objects.layout.xaxis.Rangeslider` + instance or dict with compatible properties + scaleanchor + If set to another axis id (e.g. `x2`, `y`), the range + of this axis changes together with the range of the + corresponding axis such that the scale of pixels per + unit is in a constant ratio. Both axes are still + zoomable, but when you zoom one, the other will zoom + the same amount, keeping a fixed midpoint. `constrain` + and `constraintoward` determine how we enforce the + constraint. You can chain these, ie `yaxis: + {scaleanchor: *x*}, xaxis2: {scaleanchor: *y*}` but you + can only link axes of the same `type`. The linked axis + can have the opposite letter (to constrain the aspect + ratio) or the same letter (to match scales across + subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: + {scaleanchor: *y*}` or longer) are redundant and the + last constraint encountered will be ignored to avoid + possible inconsistent constraints via `scaleratio`. + Note that setting axes simultaneously in both a + `scaleanchor` and a `matches` constraint is currently + forbidden. Setting `false` allows to remove a default + constraint (occasionally, you may need to prevent a + default `scaleanchor` constraint from being applied, + eg. when having an image trace `yaxis: {scaleanchor: + "x"}` is set automatically in order for pixels to be + rendered as squares, setting `yaxis: {scaleanchor: + false}` allows to remove the constraint). + scaleratio + If this axis is linked to another by `scaleanchor`, + this determines the pixel to unit scale ratio. For + example, if this value is 10, then every unit on this + axis spans 10 times the number of pixels as a unit on + the linked axis. Use this for example to create an + elevation profile where the vertical scale is + exaggerated a fixed amount with respect to the + horizontal. + separatethousands + If "true", even 4-digit integers are separated + showdividers + Determines whether or not a dividers are drawn between + the category levels of this axis. Only has an effect on + "multicategory" axes. + showexponent + If "all", all exponents are shown besides their + significands. If "first", only the exponent of the + first tick is shown. If "last", only the exponent of + the last tick is shown. If "none", no exponents appear. + showgrid + Determines whether or not grid lines are drawn. If + True, the grid lines are drawn at every tick mark. + showline + Determines whether or not a line bounding this axis is + drawn. + showspikes + Determines whether or not spikes (aka droplines) are + drawn for this axis. Note: This only takes affect when + hovermode = closest + showticklabels + Determines whether or not the tick labels are drawn. + showtickprefix + If "all", all tick labels are displayed with a prefix. + If "first", only the first tick is displayed with a + prefix. If "last", only the last tick is displayed with + a suffix. If "none", tick prefixes are hidden. + showticksuffix + Same as `showtickprefix` but for tick suffixes. + side + Determines whether a x (y) axis is positioned at the + "bottom" ("left") or "top" ("right") of the plotting + area. + spikecolor + Sets the spike color. If undefined, will use the series + color + spikedash + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + spikemode + Determines the drawing mode for the spike line If + "toaxis", the line is drawn from the data point to the + axis the series is plotted on. If "across", the line + is drawn across the entire plot area, and supercedes + "toaxis". If "marker", then a marker dot is drawn on + the axis the series is plotted on + spikesnap + Determines whether spikelines are stuck to the cursor + or to the closest datapoints. + spikethickness + Sets the width (in px) of the zero line. + tick0 + Sets the placement of the first tick on this axis. Use + with `dtick`. If the axis `type` is "log", then you + must take the log of your starting tick (e.g. to set + the starting tick to 100, set the `tick0` to 2) except + when `dtick`=*L* (see `dtick` for more info). If the + axis `type` is "date", it should be a date string, like + date data. If the axis `type` is "category", it should + be a number, using the scale where each category is + assigned a serial number from zero in the order it + appears. + tickangle + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + tick labels vertically. + tickcolor + Sets the tick color. + tickfont + Sets the tick font. + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + tickformatstops + A tuple of :class:`plotly.graph_objects.layout.xaxis.Ti + ckformatstop` instances or dicts with compatible + properties + tickformatstopdefaults + When used in a template (as + layout.template.layout.xaxis.tickformatstopdefaults), + sets the default property values to use for elements of + layout.xaxis.tickformatstops + ticklabelindex + Only for axes with `type` "date" or "linear". Instead + of drawing the major tick label, draw the label for the + minor tick that is n positions away from the major + tick. E.g. to always draw the label for the minor tick + before each major tick, choose `ticklabelindex` -1. + This is useful for date axes with `ticklabelmode` + "period" if you want to label the period that ends with + each major tick instead of the period that begins + there. + ticklabelindexsrc + Sets the source reference on Chart Studio Cloud for + `ticklabelindex`. + ticklabelmode + Determines where tick labels are drawn with respect to + their corresponding ticks and grid lines. Only has an + effect for axes of `type` "date" When set to "period", + tick labels are drawn in the middle of the period + between ticks. + ticklabeloverflow + Determines how we handle tick labels that would + overflow either the graph div or the domain of the + axis. The default value for inside tick labels is *hide + past domain*. Otherwise on "category" and + "multicategory" axes the default is "allow". In other + cases the default is *hide past div*. + ticklabelposition + Determines where tick labels are drawn with respect to + the axis. Please note that top or bottom has no effect + on x axes or when `ticklabelmode` is set to "period" or + when `tickson` is set to "boundaries". Similarly, left + or right has no effect on y axes or when + `ticklabelmode` is set to "period" or when `tickson` is + set to "boundaries". Has no effect on "multicategory" + axes. When used on axes linked by `matches` or + `scaleanchor`, no extra padding for inside labels would + be added by autorange, so that the scales could match. + ticklabelshift + Shifts the tick labels by the specified number of + pixels in parallel to the axis. Positive values move + the labels in the positive direction of the axis. + ticklabelstandoff + Sets the standoff distance (in px) between the axis + tick labels and their default position. A positive + `ticklabelstandoff` moves the labels farther away from + the plot area if `ticklabelposition` is "outside", and + deeper into the plot area if `ticklabelposition` is + "inside". A negative `ticklabelstandoff` works in the + opposite direction, moving outside ticks towards the + plot area and inside ticks towards the outside. If the + negative value is large enough, inside ticks can even + end up outside and vice versa. + ticklabelstep + Sets the spacing between tick labels as compared to the + spacing between ticks. A value of 1 (default) means + each tick gets a label. A value of 2 means shows every + 2nd label. A larger value n means only every nth tick + is labeled. `tick0` determines which labels are shown. + Not implemented for axes with `type` "log" or + "multicategory", or when `tickmode` is "array". + ticklen + Sets the tick length (in px). + tickmode + Sets the tick mode for this axis. If "auto", the number + of ticks is set via `nticks`. If "linear", the + placement of the ticks is determined by a starting + position `tick0` and a tick step `dtick` ("linear" is + the default value if `tick0` and `dtick` are provided). + If "array", the placement of the ticks is set via + `tickvals` and the tick text is `ticktext`. ("array" is + the default value if `tickvals` is provided). If + "sync", the number of ticks will sync with the + overlayed axis set by `overlaying` property. + tickprefix + Sets a tick label prefix. + ticks + Determines whether ticks are drawn or not. If "", this + axis' ticks are not drawn. If "outside" ("inside"), + this axis' are drawn outside (inside) the axis lines. + tickson + Determines where ticks and grid lines are drawn with + respect to their corresponding tick labels. Only has an + effect for axes of `type` "category" or + "multicategory". When set to "boundaries", ticks and + grid lines are drawn half a category to the left/bottom + of labels. + ticksuffix + Sets a tick label suffix. + ticktext + Sets the text displayed at the ticks position via + `tickvals`. Only has an effect if `tickmode` is set to + "array". Used with `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + Only has an effect if `tickmode` is set to "array". + Used with `ticktext`. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + tickwidth + Sets the tick width (in px). + title + :class:`plotly.graph_objects.layout.xaxis.Title` + instance or dict with compatible properties + type + Sets the axis type. By default, plotly attempts to + determined the axis type by looking into the data of + the traces that referenced the axis in question. + uirevision + Controls persistence of user-driven changes in axis + `range`, `autorange`, and `title` if in `editable: + true` configuration. Defaults to `layout.uirevision`. + unifiedhovertitle + :class:`plotly.graph_objects.layout.xaxis.Unifiedhovert + itle` instance or dict with compatible properties + visible + A single toggle to hide the axis while preserving + interaction like dragging. Default is true when a + cheater plot is present on the axis, otherwise false + zeroline + Determines whether or not a line is drawn at along the + 0 value of this axis. If True, the zero line is drawn + on top of the grid lines. + zerolinecolor + Sets the line color of the zero line. + zerolinelayer + Sets the layer on which this zeroline is displayed. If + *above traces*, this zeroline is displayed above all + the subplot's traces If *below traces*, this zeroline + is displayed below all the subplot's traces, but above + the grid lines. Limitation: "zerolinelayer" currently + has no effect if the "zorder" property is set on any + trace. + zerolinewidth + Sets the width (in px) of the zero line. + """ + + def __init__( + self, + arg=None, + anchor=None, + automargin=None, + autorange=None, + autorangeoptions=None, + autotickangles=None, + autotypenumbers=None, + calendar=None, + categoryarray=None, + categoryarraysrc=None, + categoryorder=None, + color=None, + constrain=None, + constraintoward=None, + dividercolor=None, + dividerwidth=None, + domain=None, + dtick=None, + exponentformat=None, + fixedrange=None, + gridcolor=None, + griddash=None, + gridwidth=None, + hoverformat=None, + insiderange=None, + labelalias=None, + layer=None, + linecolor=None, + linewidth=None, + matches=None, + maxallowed=None, + minallowed=None, + minexponent=None, + minor=None, + minorloglabels=None, + mirror=None, + modebardisable=None, + nticks=None, + overlaying=None, + position=None, + range=None, + rangebreaks=None, + rangebreakdefaults=None, + rangemode=None, + rangeselector=None, + rangeslider=None, + scaleanchor=None, + scaleratio=None, + separatethousands=None, + showdividers=None, + showexponent=None, + showgrid=None, + showline=None, + showspikes=None, + showticklabels=None, + showtickprefix=None, + showticksuffix=None, + side=None, + spikecolor=None, + spikedash=None, + spikemode=None, + spikesnap=None, + spikethickness=None, + tick0=None, + tickangle=None, + tickcolor=None, + tickfont=None, + tickformat=None, + tickformatstops=None, + tickformatstopdefaults=None, + ticklabelindex=None, + ticklabelindexsrc=None, + ticklabelmode=None, + ticklabeloverflow=None, + ticklabelposition=None, + ticklabelshift=None, + ticklabelstandoff=None, + ticklabelstep=None, + ticklen=None, + tickmode=None, + tickprefix=None, + ticks=None, + tickson=None, + ticksuffix=None, + ticktext=None, + ticktextsrc=None, + tickvals=None, + tickvalssrc=None, + tickwidth=None, + title=None, + type=None, + uirevision=None, + unifiedhovertitle=None, + visible=None, + zeroline=None, + zerolinecolor=None, + zerolinelayer=None, + zerolinewidth=None, + **kwargs, + ): + """ + Construct a new XAxis object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.XAxis` + anchor + If set to an opposite-letter axis id (e.g. `x2`, `y`), + this axis is bound to the corresponding opposite-letter + axis. If set to "free", this axis' position is + determined by `position`. + automargin + Determines whether long tick labels automatically grow + the figure margins. + autorange + Determines whether or not the range of this axis is + computed in relation to the input data. See `rangemode` + for more info. If `range` is provided and it has a + value for both the lower and upper bound, `autorange` + is set to False. Using "min" applies autorange only to + set the minimum. Using "max" applies autorange only to + set the maximum. Using *min reversed* applies autorange + only to set the minimum on a reversed axis. Using *max + reversed* applies autorange only to set the maximum on + a reversed axis. Using "reversed" applies autorange on + both ends and reverses the axis direction. + autorangeoptions + :class:`plotly.graph_objects.layout.xaxis.Autorangeopti + ons` instance or dict with compatible properties + autotickangles + When `tickangle` is set to "auto", it will be set to + the first angle in this array that is large enough to + prevent label overlap. + autotypenumbers + Using "strict" a numeric string in trace data is not + converted to a number. Using *convert types* a numeric + string in trace data may be treated as a number during + automatic axis `type` detection. Defaults to + layout.autotypenumbers. + calendar + Sets the calendar system to use for `range` and `tick0` + if this is a date axis. This does not set the calendar + for interpreting data on this axis, that's specified in + the trace or via the global `layout.calendar` + categoryarray + Sets the order in which categories on this axis appear. + Only has an effect if `categoryorder` is set to + "array". Used with `categoryorder`. + categoryarraysrc + Sets the source reference on Chart Studio Cloud for + `categoryarray`. + categoryorder + Specifies the ordering logic for the case of + categorical variables. By default, plotly uses "trace", + which specifies the order that is present in the data + supplied. Set `categoryorder` to *category ascending* + or *category descending* if order should be determined + by the alphanumerical order of the category names. Set + `categoryorder` to "array" to derive the ordering from + the attribute `categoryarray`. If a category is not + found in the `categoryarray` array, the sorting + behavior for that attribute will be identical to the + "trace" mode. The unspecified categories will follow + the categories in `categoryarray`. Set `categoryorder` + to *total ascending* or *total descending* if order + should be determined by the numerical order of the + values. Similarly, the order can be determined by the + min, max, sum, mean, geometric mean or median of all + the values. + color + Sets default for all colors associated with this axis + all at once: line, font, tick, and grid colors. Grid + color is lightened by blending this with the plot + background Individual pieces can override this. + constrain + If this axis needs to be compressed (either due to its + own `scaleanchor` and `scaleratio` or those of the + other axis), determines how that happens: by increasing + the "range", or by decreasing the "domain". Default is + "domain" for axes containing image traces, "range" + otherwise. + constraintoward + If this axis needs to be compressed (either due to its + own `scaleanchor` and `scaleratio` or those of the + other axis), determines which direction we push the + originally specified plot area. Options are "left", + "center" (default), and "right" for x axes, and "top", + "middle" (default), and "bottom" for y axes. + dividercolor + Sets the color of the dividers Only has an effect on + "multicategory" axes. + dividerwidth + Sets the width (in px) of the dividers Only has an + effect on "multicategory" axes. + domain + Sets the domain of this axis (in plot fraction). + dtick + Sets the step in-between ticks on this axis. Use with + `tick0`. Must be a positive number, or special strings + available to "log" and "date" axes. If the axis `type` + is "log", then ticks are set every 10^(n*dtick) where n + is the tick number. For example, to set a tick mark at + 1, 10, 100, 1000, ... set dtick to 1. To set tick marks + at 1, 100, 10000, ... set dtick to 2. To set tick marks + at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special + values; "L", where `f` is a positive number, gives + ticks linearly spaced in value (but not position). For + example `tick0` = 0.1, `dtick` = "L0.5" will put ticks + at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus + small digits between, use "D1" (all digits) or "D2" + (only 2 and 5). `tick0` is ignored for "D1" and "D2". + If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval + between ticks to one day, set `dtick` to 86400000.0. + "date" also has special values "M" gives ticks + spaced by a number of months. `n` must be a positive + integer. To set ticks on the 15th of every third month, + set `tick0` to "2000-01-15" and `dtick` to "M3". To set + ticks every 4 years, set `dtick` to "M48" + exponentformat + Determines a formatting rule for the tick exponents. + For example, consider the number 1,000,000,000. If + "none", it appears as 1,000,000,000. If "e", 1e+9. If + "E", 1E+9. If "power", 1x10^9 (with 9 in a super + script). If "SI", 1G. If "B", 1B. "SI" uses prefixes + from "femto" f (10^-15) to "tera" T (10^12). *SI + extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or + *SI extended* is used and the exponent is beyond the + above ranges, the formatting rule will automatically be + switched to the power notation. + fixedrange + Determines whether or not this axis is zoom-able. If + true, then zoom is disabled. + gridcolor + Sets the color of the grid lines. + griddash + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + gridwidth + Sets the width (in px) of the grid lines. + hoverformat + Sets the hover text formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + insiderange + Could be used to set the desired inside range of this + axis (excluding the labels) when `ticklabelposition` of + the anchored axis has "inside". Not implemented for + axes with `type` "log". This would be ignored when + `range` is provided. + labelalias + Replacement text for specific tick or hover labels. For + example using {US: 'USA', CA: 'Canada'} changes US to + USA and CA to Canada. The labels we would have shown + must match the keys exactly, after adding any + tickprefix or ticksuffix. For negative numbers the + minus sign symbol used (U+2212) is wider than the + regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis + type, and both keys (if needed) and values (if desired) + can include html-like tags or MathJax. + layer + Sets the layer on which this axis is displayed. If + *above traces*, this axis is displayed above all the + subplot's traces If *below traces*, this axis is + displayed below all the subplot's traces, but above the + grid lines. Useful when used together with scatter-like + traces with `cliponaxis` set to False to show markers + and/or text nodes above this axis. + linecolor + Sets the axis line color. + linewidth + Sets the width (in px) of the axis line. + matches + If set to another axis id (e.g. `x2`, `y`), the range + of this axis will match the range of the corresponding + axis in data-coordinates space. Moreover, matching axes + share auto-range values, category lists and histogram + auto-bins. Note that setting axes simultaneously in + both a `scaleanchor` and a `matches` constraint is + currently forbidden. Moreover, note that matching axes + must have the same `type`. + maxallowed + Determines the maximum range of this axis. + minallowed + Determines the minimum range of this axis. + minexponent + Hide SI prefix for 10^n if |n| is below this number. + This only has an effect when `tickformat` is "SI" or + "B". + minor + :class:`plotly.graph_objects.layout.xaxis.Minor` + instance or dict with compatible properties + minorloglabels + Determines how minor log labels are displayed. If + *small digits*, small digits i.e. 2 or 5 are displayed. + If "complete", complete digits are displayed. If + "none", no labels are displayed. + mirror + Determines if the axis lines or/and ticks are mirrored + to the opposite side of the plotting area. If True, the + axis lines are mirrored. If "ticks", the axis lines and + ticks are mirrored. If False, mirroring is disable. If + "all", axis lines are mirrored on all shared-axes + subplots. If "allticks", axis lines and ticks are + mirrored on all shared-axes subplots. + modebardisable + Disables certain modebar buttons for this axis. + "autoscale" disables the autoscale buttons, "zoominout" + disables the zoom-in and zoom-out buttons. + nticks + Specifies the maximum number of ticks for the + particular axis. The actual number of ticks will be + chosen automatically to be less than or equal to + `nticks`. Has an effect only if `tickmode` is set to + "auto". + overlaying + If set a same-letter axis id, this axis is overlaid on + top of the corresponding same-letter axis, with traces + and axes visible for both axes. If False, this axis + does not overlay any same-letter axes. In this case, + for axes with overlapping domains only the highest- + numbered axis will be visible. + position + Sets the position of this axis in the plotting space + (in normalized coordinates). Only has an effect if + `anchor` is set to "free". + range + Sets the range of this axis. If the axis `type` is + "log", then you must take the log of your desired range + (e.g. to set the range from 1 to 100, set the range + from 0 to 2). If the axis `type` is "date", it should + be date strings, like date data, though Date objects + and unix milliseconds will be accepted and converted to + strings. If the axis `type` is "category", it should be + numbers, using the scale where each category is + assigned a serial number from zero in the order it + appears. Leaving either or both elements `null` impacts + the default `autorange`. + rangebreaks + A tuple of + :class:`plotly.graph_objects.layout.xaxis.Rangebreak` + instances or dicts with compatible properties + rangebreakdefaults + When used in a template (as + layout.template.layout.xaxis.rangebreakdefaults), sets + the default property values to use for elements of + layout.xaxis.rangebreaks + rangemode + If "normal", the range is computed in relation to the + extrema of the input data. If "tozero", the range + extends to 0, regardless of the input data If + "nonnegative", the range is non-negative, regardless of + the input data. Applies only to linear axes. + rangeselector + :class:`plotly.graph_objects.layout.xaxis.Rangeselector + ` instance or dict with compatible properties + rangeslider + :class:`plotly.graph_objects.layout.xaxis.Rangeslider` + instance or dict with compatible properties + scaleanchor + If set to another axis id (e.g. `x2`, `y`), the range + of this axis changes together with the range of the + corresponding axis such that the scale of pixels per + unit is in a constant ratio. Both axes are still + zoomable, but when you zoom one, the other will zoom + the same amount, keeping a fixed midpoint. `constrain` + and `constraintoward` determine how we enforce the + constraint. You can chain these, ie `yaxis: + {scaleanchor: *x*}, xaxis2: {scaleanchor: *y*}` but you + can only link axes of the same `type`. The linked axis + can have the opposite letter (to constrain the aspect + ratio) or the same letter (to match scales across + subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: + {scaleanchor: *y*}` or longer) are redundant and the + last constraint encountered will be ignored to avoid + possible inconsistent constraints via `scaleratio`. + Note that setting axes simultaneously in both a + `scaleanchor` and a `matches` constraint is currently + forbidden. Setting `false` allows to remove a default + constraint (occasionally, you may need to prevent a + default `scaleanchor` constraint from being applied, + eg. when having an image trace `yaxis: {scaleanchor: + "x"}` is set automatically in order for pixels to be + rendered as squares, setting `yaxis: {scaleanchor: + false}` allows to remove the constraint). + scaleratio + If this axis is linked to another by `scaleanchor`, + this determines the pixel to unit scale ratio. For + example, if this value is 10, then every unit on this + axis spans 10 times the number of pixels as a unit on + the linked axis. Use this for example to create an + elevation profile where the vertical scale is + exaggerated a fixed amount with respect to the + horizontal. + separatethousands + If "true", even 4-digit integers are separated + showdividers + Determines whether or not a dividers are drawn between + the category levels of this axis. Only has an effect on + "multicategory" axes. + showexponent + If "all", all exponents are shown besides their + significands. If "first", only the exponent of the + first tick is shown. If "last", only the exponent of + the last tick is shown. If "none", no exponents appear. + showgrid + Determines whether or not grid lines are drawn. If + True, the grid lines are drawn at every tick mark. + showline + Determines whether or not a line bounding this axis is + drawn. + showspikes + Determines whether or not spikes (aka droplines) are + drawn for this axis. Note: This only takes affect when + hovermode = closest + showticklabels + Determines whether or not the tick labels are drawn. + showtickprefix + If "all", all tick labels are displayed with a prefix. + If "first", only the first tick is displayed with a + prefix. If "last", only the last tick is displayed with + a suffix. If "none", tick prefixes are hidden. + showticksuffix + Same as `showtickprefix` but for tick suffixes. + side + Determines whether a x (y) axis is positioned at the + "bottom" ("left") or "top" ("right") of the plotting + area. + spikecolor + Sets the spike color. If undefined, will use the series + color + spikedash + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + spikemode + Determines the drawing mode for the spike line If + "toaxis", the line is drawn from the data point to the + axis the series is plotted on. If "across", the line + is drawn across the entire plot area, and supercedes + "toaxis". If "marker", then a marker dot is drawn on + the axis the series is plotted on + spikesnap + Determines whether spikelines are stuck to the cursor + or to the closest datapoints. + spikethickness + Sets the width (in px) of the zero line. + tick0 + Sets the placement of the first tick on this axis. Use + with `dtick`. If the axis `type` is "log", then you + must take the log of your starting tick (e.g. to set + the starting tick to 100, set the `tick0` to 2) except + when `dtick`=*L* (see `dtick` for more info). If the + axis `type` is "date", it should be a date string, like + date data. If the axis `type` is "category", it should + be a number, using the scale where each category is + assigned a serial number from zero in the order it + appears. + tickangle + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + tick labels vertically. + tickcolor + Sets the tick color. + tickfont + Sets the tick font. + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + tickformatstops + A tuple of :class:`plotly.graph_objects.layout.xaxis.Ti + ckformatstop` instances or dicts with compatible + properties + tickformatstopdefaults + When used in a template (as + layout.template.layout.xaxis.tickformatstopdefaults), + sets the default property values to use for elements of + layout.xaxis.tickformatstops + ticklabelindex + Only for axes with `type` "date" or "linear". Instead + of drawing the major tick label, draw the label for the + minor tick that is n positions away from the major + tick. E.g. to always draw the label for the minor tick + before each major tick, choose `ticklabelindex` -1. + This is useful for date axes with `ticklabelmode` + "period" if you want to label the period that ends with + each major tick instead of the period that begins + there. + ticklabelindexsrc + Sets the source reference on Chart Studio Cloud for + `ticklabelindex`. + ticklabelmode + Determines where tick labels are drawn with respect to + their corresponding ticks and grid lines. Only has an + effect for axes of `type` "date" When set to "period", + tick labels are drawn in the middle of the period + between ticks. + ticklabeloverflow + Determines how we handle tick labels that would + overflow either the graph div or the domain of the + axis. The default value for inside tick labels is *hide + past domain*. Otherwise on "category" and + "multicategory" axes the default is "allow". In other + cases the default is *hide past div*. + ticklabelposition + Determines where tick labels are drawn with respect to + the axis. Please note that top or bottom has no effect + on x axes or when `ticklabelmode` is set to "period" or + when `tickson` is set to "boundaries". Similarly, left + or right has no effect on y axes or when + `ticklabelmode` is set to "period" or when `tickson` is + set to "boundaries". Has no effect on "multicategory" + axes. When used on axes linked by `matches` or + `scaleanchor`, no extra padding for inside labels would + be added by autorange, so that the scales could match. + ticklabelshift + Shifts the tick labels by the specified number of + pixels in parallel to the axis. Positive values move + the labels in the positive direction of the axis. + ticklabelstandoff + Sets the standoff distance (in px) between the axis + tick labels and their default position. A positive + `ticklabelstandoff` moves the labels farther away from + the plot area if `ticklabelposition` is "outside", and + deeper into the plot area if `ticklabelposition` is + "inside". A negative `ticklabelstandoff` works in the + opposite direction, moving outside ticks towards the + plot area and inside ticks towards the outside. If the + negative value is large enough, inside ticks can even + end up outside and vice versa. + ticklabelstep + Sets the spacing between tick labels as compared to the + spacing between ticks. A value of 1 (default) means + each tick gets a label. A value of 2 means shows every + 2nd label. A larger value n means only every nth tick + is labeled. `tick0` determines which labels are shown. + Not implemented for axes with `type` "log" or + "multicategory", or when `tickmode` is "array". + ticklen + Sets the tick length (in px). + tickmode + Sets the tick mode for this axis. If "auto", the number + of ticks is set via `nticks`. If "linear", the + placement of the ticks is determined by a starting + position `tick0` and a tick step `dtick` ("linear" is + the default value if `tick0` and `dtick` are provided). + If "array", the placement of the ticks is set via + `tickvals` and the tick text is `ticktext`. ("array" is + the default value if `tickvals` is provided). If + "sync", the number of ticks will sync with the + overlayed axis set by `overlaying` property. + tickprefix + Sets a tick label prefix. + ticks + Determines whether ticks are drawn or not. If "", this + axis' ticks are not drawn. If "outside" ("inside"), + this axis' are drawn outside (inside) the axis lines. + tickson + Determines where ticks and grid lines are drawn with + respect to their corresponding tick labels. Only has an + effect for axes of `type` "category" or + "multicategory". When set to "boundaries", ticks and + grid lines are drawn half a category to the left/bottom + of labels. + ticksuffix + Sets a tick label suffix. + ticktext + Sets the text displayed at the ticks position via + `tickvals`. Only has an effect if `tickmode` is set to + "array". Used with `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + Only has an effect if `tickmode` is set to "array". + Used with `ticktext`. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + tickwidth + Sets the tick width (in px). + title + :class:`plotly.graph_objects.layout.xaxis.Title` + instance or dict with compatible properties + type + Sets the axis type. By default, plotly attempts to + determined the axis type by looking into the data of + the traces that referenced the axis in question. + uirevision + Controls persistence of user-driven changes in axis + `range`, `autorange`, and `title` if in `editable: + true` configuration. Defaults to `layout.uirevision`. + unifiedhovertitle + :class:`plotly.graph_objects.layout.xaxis.Unifiedhovert + itle` instance or dict with compatible properties + visible + A single toggle to hide the axis while preserving + interaction like dragging. Default is true when a + cheater plot is present on the axis, otherwise false + zeroline + Determines whether or not a line is drawn at along the + 0 value of this axis. If True, the zero line is drawn + on top of the grid lines. + zerolinecolor + Sets the line color of the zero line. + zerolinelayer + Sets the layer on which this zeroline is displayed. If + *above traces*, this zeroline is displayed above all + the subplot's traces If *below traces*, this zeroline + is displayed below all the subplot's traces, but above + the grid lines. Limitation: "zerolinelayer" currently + has no effect if the "zorder" property is set on any + trace. + zerolinewidth + Sets the width (in px) of the zero line. + + Returns + ------- + XAxis + """ + super().__init__("xaxis") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.XAxis +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.XAxis`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("anchor", arg, anchor) + self._set_property("automargin", arg, automargin) + self._set_property("autorange", arg, autorange) + self._set_property("autorangeoptions", arg, autorangeoptions) + self._set_property("autotickangles", arg, autotickangles) + self._set_property("autotypenumbers", arg, autotypenumbers) + self._set_property("calendar", arg, calendar) + self._set_property("categoryarray", arg, categoryarray) + self._set_property("categoryarraysrc", arg, categoryarraysrc) + self._set_property("categoryorder", arg, categoryorder) + self._set_property("color", arg, color) + self._set_property("constrain", arg, constrain) + self._set_property("constraintoward", arg, constraintoward) + self._set_property("dividercolor", arg, dividercolor) + self._set_property("dividerwidth", arg, dividerwidth) + self._set_property("domain", arg, domain) + self._set_property("dtick", arg, dtick) + self._set_property("exponentformat", arg, exponentformat) + self._set_property("fixedrange", arg, fixedrange) + self._set_property("gridcolor", arg, gridcolor) + self._set_property("griddash", arg, griddash) + self._set_property("gridwidth", arg, gridwidth) + self._set_property("hoverformat", arg, hoverformat) + self._set_property("insiderange", arg, insiderange) + self._set_property("labelalias", arg, labelalias) + self._set_property("layer", arg, layer) + self._set_property("linecolor", arg, linecolor) + self._set_property("linewidth", arg, linewidth) + self._set_property("matches", arg, matches) + self._set_property("maxallowed", arg, maxallowed) + self._set_property("minallowed", arg, minallowed) + self._set_property("minexponent", arg, minexponent) + self._set_property("minor", arg, minor) + self._set_property("minorloglabels", arg, minorloglabels) + self._set_property("mirror", arg, mirror) + self._set_property("modebardisable", arg, modebardisable) + self._set_property("nticks", arg, nticks) + self._set_property("overlaying", arg, overlaying) + self._set_property("position", arg, position) + self._set_property("range", arg, range) + self._set_property("rangebreaks", arg, rangebreaks) + self._set_property("rangebreakdefaults", arg, rangebreakdefaults) + self._set_property("rangemode", arg, rangemode) + self._set_property("rangeselector", arg, rangeselector) + self._set_property("rangeslider", arg, rangeslider) + self._set_property("scaleanchor", arg, scaleanchor) + self._set_property("scaleratio", arg, scaleratio) + self._set_property("separatethousands", arg, separatethousands) + self._set_property("showdividers", arg, showdividers) + self._set_property("showexponent", arg, showexponent) + self._set_property("showgrid", arg, showgrid) + self._set_property("showline", arg, showline) + self._set_property("showspikes", arg, showspikes) + self._set_property("showticklabels", arg, showticklabels) + self._set_property("showtickprefix", arg, showtickprefix) + self._set_property("showticksuffix", arg, showticksuffix) + self._set_property("side", arg, side) + self._set_property("spikecolor", arg, spikecolor) + self._set_property("spikedash", arg, spikedash) + self._set_property("spikemode", arg, spikemode) + self._set_property("spikesnap", arg, spikesnap) + self._set_property("spikethickness", arg, spikethickness) + self._set_property("tick0", arg, tick0) + self._set_property("tickangle", arg, tickangle) + self._set_property("tickcolor", arg, tickcolor) + self._set_property("tickfont", arg, tickfont) + self._set_property("tickformat", arg, tickformat) + self._set_property("tickformatstops", arg, tickformatstops) + self._set_property("tickformatstopdefaults", arg, tickformatstopdefaults) + self._set_property("ticklabelindex", arg, ticklabelindex) + self._set_property("ticklabelindexsrc", arg, ticklabelindexsrc) + self._set_property("ticklabelmode", arg, ticklabelmode) + self._set_property("ticklabeloverflow", arg, ticklabeloverflow) + self._set_property("ticklabelposition", arg, ticklabelposition) + self._set_property("ticklabelshift", arg, ticklabelshift) + self._set_property("ticklabelstandoff", arg, ticklabelstandoff) + self._set_property("ticklabelstep", arg, ticklabelstep) + self._set_property("ticklen", arg, ticklen) + self._set_property("tickmode", arg, tickmode) + self._set_property("tickprefix", arg, tickprefix) + self._set_property("ticks", arg, ticks) + self._set_property("tickson", arg, tickson) + self._set_property("ticksuffix", arg, ticksuffix) + self._set_property("ticktext", arg, ticktext) + self._set_property("ticktextsrc", arg, ticktextsrc) + self._set_property("tickvals", arg, tickvals) + self._set_property("tickvalssrc", arg, tickvalssrc) + self._set_property("tickwidth", arg, tickwidth) + self._set_property("title", arg, title) + self._set_property("type", arg, type) + self._set_property("uirevision", arg, uirevision) + self._set_property("unifiedhovertitle", arg, unifiedhovertitle) + self._set_property("visible", arg, visible) + self._set_property("zeroline", arg, zeroline) + self._set_property("zerolinecolor", arg, zerolinecolor) + self._set_property("zerolinelayer", arg, zerolinelayer) + self._set_property("zerolinewidth", arg, zerolinewidth) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_yaxis.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_yaxis.py new file mode 100644 index 0000000000000000000000000000000000000000..4e81f347a4e7073f8b48fb8e2e49b3d246beb6c2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/layout/_yaxis.py @@ -0,0 +1,3603 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseLayoutHierarchyType as _BaseLayoutHierarchyType +import copy as _copy + + +class YAxis(_BaseLayoutHierarchyType): + _parent_path_str = "layout" + _path_str = "layout.yaxis" + _valid_props = { + "anchor", + "automargin", + "autorange", + "autorangeoptions", + "autoshift", + "autotickangles", + "autotypenumbers", + "calendar", + "categoryarray", + "categoryarraysrc", + "categoryorder", + "color", + "constrain", + "constraintoward", + "dividercolor", + "dividerwidth", + "domain", + "dtick", + "exponentformat", + "fixedrange", + "gridcolor", + "griddash", + "gridwidth", + "hoverformat", + "insiderange", + "labelalias", + "layer", + "linecolor", + "linewidth", + "matches", + "maxallowed", + "minallowed", + "minexponent", + "minor", + "minorloglabels", + "mirror", + "modebardisable", + "nticks", + "overlaying", + "position", + "range", + "rangebreakdefaults", + "rangebreaks", + "rangemode", + "scaleanchor", + "scaleratio", + "separatethousands", + "shift", + "showdividers", + "showexponent", + "showgrid", + "showline", + "showspikes", + "showticklabels", + "showtickprefix", + "showticksuffix", + "side", + "spikecolor", + "spikedash", + "spikemode", + "spikesnap", + "spikethickness", + "tick0", + "tickangle", + "tickcolor", + "tickfont", + "tickformat", + "tickformatstopdefaults", + "tickformatstops", + "ticklabelindex", + "ticklabelindexsrc", + "ticklabelmode", + "ticklabeloverflow", + "ticklabelposition", + "ticklabelshift", + "ticklabelstandoff", + "ticklabelstep", + "ticklen", + "tickmode", + "tickprefix", + "ticks", + "tickson", + "ticksuffix", + "ticktext", + "ticktextsrc", + "tickvals", + "tickvalssrc", + "tickwidth", + "title", + "type", + "uirevision", + "unifiedhovertitle", + "visible", + "zeroline", + "zerolinecolor", + "zerolinelayer", + "zerolinewidth", + } + + @property + def anchor(self): + """ + If set to an opposite-letter axis id (e.g. `x2`, `y`), this + axis is bound to the corresponding opposite-letter axis. If set + to "free", this axis' position is determined by `position`. + + The 'anchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['free'] + - A string that matches one of the following regular expressions: + ['^x([2-9]|[1-9][0-9]+)?( domain)?$', + '^y([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["anchor"] + + @anchor.setter + def anchor(self, val): + self["anchor"] = val + + @property + def automargin(self): + """ + Determines whether long tick labels automatically grow the + figure margins. + + The 'automargin' property is a flaglist and may be specified + as a string containing: + - Any combination of ['height', 'width', 'left', 'right', 'top', 'bottom'] joined with '+' characters + (e.g. 'height+width') + OR exactly one of [True, False] (e.g. 'False') + + Returns + ------- + Any + """ + return self["automargin"] + + @automargin.setter + def automargin(self, val): + self["automargin"] = val + + @property + def autorange(self): + """ + Determines whether or not the range of this axis is computed in + relation to the input data. See `rangemode` for more info. If + `range` is provided and it has a value for both the lower and + upper bound, `autorange` is set to False. Using "min" applies + autorange only to set the minimum. Using "max" applies + autorange only to set the maximum. Using *min reversed* applies + autorange only to set the minimum on a reversed axis. Using + *max reversed* applies autorange only to set the maximum on a + reversed axis. Using "reversed" applies autorange on both ends + and reverses the axis direction. + + The 'autorange' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, False, 'reversed', 'min reversed', 'max reversed', + 'min', 'max'] + + Returns + ------- + Any + """ + return self["autorange"] + + @autorange.setter + def autorange(self, val): + self["autorange"] = val + + @property + def autorangeoptions(self): + """ + The 'autorangeoptions' property is an instance of Autorangeoptions + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.yaxis.Autorangeoptions` + - A dict of string/value properties that will be passed + to the Autorangeoptions constructor + + Returns + ------- + plotly.graph_objs.layout.yaxis.Autorangeoptions + """ + return self["autorangeoptions"] + + @autorangeoptions.setter + def autorangeoptions(self, val): + self["autorangeoptions"] = val + + @property + def autoshift(self): + """ + Automatically reposition the axis to avoid overlap with other + axes with the same `overlaying` value. This repositioning will + account for any `shift` amount applied to other axes on the + same side with `autoshift` is set to true. Only has an effect + if `anchor` is set to "free". + + The 'autoshift' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autoshift"] + + @autoshift.setter + def autoshift(self, val): + self["autoshift"] = val + + @property + def autotickangles(self): + """ + When `tickangle` is set to "auto", it will be set to the first + angle in this array that is large enough to prevent label + overlap. + + The 'autotickangles' property is an info array that may be specified as: + * a list of elements where: + The 'autotickangles[i]' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + list + """ + return self["autotickangles"] + + @autotickangles.setter + def autotickangles(self, val): + self["autotickangles"] = val + + @property + def autotypenumbers(self): + """ + Using "strict" a numeric string in trace data is not converted + to a number. Using *convert types* a numeric string in trace + data may be treated as a number during automatic axis `type` + detection. Defaults to layout.autotypenumbers. + + The 'autotypenumbers' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['convert types', 'strict'] + + Returns + ------- + Any + """ + return self["autotypenumbers"] + + @autotypenumbers.setter + def autotypenumbers(self, val): + self["autotypenumbers"] = val + + @property + def calendar(self): + """ + Sets the calendar system to use for `range` and `tick0` if this + is a date axis. This does not set the calendar for interpreting + data on this axis, that's specified in the trace or via the + global `layout.calendar` + + The 'calendar' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['chinese', 'coptic', 'discworld', 'ethiopian', + 'gregorian', 'hebrew', 'islamic', 'jalali', 'julian', + 'mayan', 'nanakshahi', 'nepali', 'persian', 'taiwan', + 'thai', 'ummalqura'] + + Returns + ------- + Any + """ + return self["calendar"] + + @calendar.setter + def calendar(self, val): + self["calendar"] = val + + @property + def categoryarray(self): + """ + Sets the order in which categories on this axis appear. Only + has an effect if `categoryorder` is set to "array". Used with + `categoryorder`. + + The 'categoryarray' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["categoryarray"] + + @categoryarray.setter + def categoryarray(self, val): + self["categoryarray"] = val + + @property + def categoryarraysrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `categoryarray`. + + The 'categoryarraysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["categoryarraysrc"] + + @categoryarraysrc.setter + def categoryarraysrc(self, val): + self["categoryarraysrc"] = val + + @property + def categoryorder(self): + """ + Specifies the ordering logic for the case of categorical + variables. By default, plotly uses "trace", which specifies the + order that is present in the data supplied. Set `categoryorder` + to *category ascending* or *category descending* if order + should be determined by the alphanumerical order of the + category names. Set `categoryorder` to "array" to derive the + ordering from the attribute `categoryarray`. If a category is + not found in the `categoryarray` array, the sorting behavior + for that attribute will be identical to the "trace" mode. The + unspecified categories will follow the categories in + `categoryarray`. Set `categoryorder` to *total ascending* or + *total descending* if order should be determined by the + numerical order of the values. Similarly, the order can be + determined by the min, max, sum, mean, geometric mean or median + of all the values. + + The 'categoryorder' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['trace', 'category ascending', 'category descending', + 'array', 'total ascending', 'total descending', 'min + ascending', 'min descending', 'max ascending', 'max + descending', 'sum ascending', 'sum descending', 'mean + ascending', 'mean descending', 'geometric mean ascending', + 'geometric mean descending', 'median ascending', 'median + descending'] + + Returns + ------- + Any + """ + return self["categoryorder"] + + @categoryorder.setter + def categoryorder(self, val): + self["categoryorder"] = val + + @property + def color(self): + """ + Sets default for all colors associated with this axis all at + once: line, font, tick, and grid colors. Grid color is + lightened by blending this with the plot background Individual + pieces can override this. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def constrain(self): + """ + If this axis needs to be compressed (either due to its own + `scaleanchor` and `scaleratio` or those of the other axis), + determines how that happens: by increasing the "range", or by + decreasing the "domain". Default is "domain" for axes + containing image traces, "range" otherwise. + + The 'constrain' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['range', 'domain'] + + Returns + ------- + Any + """ + return self["constrain"] + + @constrain.setter + def constrain(self, val): + self["constrain"] = val + + @property + def constraintoward(self): + """ + If this axis needs to be compressed (either due to its own + `scaleanchor` and `scaleratio` or those of the other axis), + determines which direction we push the originally specified + plot area. Options are "left", "center" (default), and "right" + for x axes, and "top", "middle" (default), and "bottom" for y + axes. + + The 'constraintoward' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'center', 'right', 'top', 'middle', 'bottom'] + + Returns + ------- + Any + """ + return self["constraintoward"] + + @constraintoward.setter + def constraintoward(self, val): + self["constraintoward"] = val + + @property + def dividercolor(self): + """ + Sets the color of the dividers Only has an effect on + "multicategory" axes. + + The 'dividercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["dividercolor"] + + @dividercolor.setter + def dividercolor(self, val): + self["dividercolor"] = val + + @property + def dividerwidth(self): + """ + Sets the width (in px) of the dividers Only has an effect on + "multicategory" axes. + + The 'dividerwidth' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["dividerwidth"] + + @dividerwidth.setter + def dividerwidth(self, val): + self["dividerwidth"] = val + + @property + def domain(self): + """ + Sets the domain of this axis (in plot fraction). + + The 'domain' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'domain[0]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + (1) The 'domain[1]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + list + """ + return self["domain"] + + @domain.setter + def domain(self, val): + self["domain"] = val + + @property + def dtick(self): + """ + Sets the step in-between ticks on this axis. Use with `tick0`. + Must be a positive number, or special strings available to + "log" and "date" axes. If the axis `type` is "log", then ticks + are set every 10^(n*dtick) where n is the tick number. For + example, to set a tick mark at 1, 10, 100, 1000, ... set dtick + to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. + To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special values; + "L", where `f` is a positive number, gives ticks linearly + spaced in value (but not position). For example `tick0` = 0.1, + `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To + show powers of 10 plus small digits between, use "D1" (all + digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and + "D2". If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval between + ticks to one day, set `dtick` to 86400000.0. "date" also has + special values "M" gives ticks spaced by a number of months. + `n` must be a positive integer. To set ticks on the 15th of + every third month, set `tick0` to "2000-01-15" and `dtick` to + "M3". To set ticks every 4 years, set `dtick` to "M48" + + The 'dtick' property accepts values of any type + + Returns + ------- + Any + """ + return self["dtick"] + + @dtick.setter + def dtick(self, val): + self["dtick"] = val + + @property + def exponentformat(self): + """ + Determines a formatting rule for the tick exponents. For + example, consider the number 1,000,000,000. If "none", it + appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If + "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If + "B", 1B. "SI" uses prefixes from "femto" f (10^-15) to "tera" T + (10^12). *SI extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or *SI + extended* is used and the exponent is beyond the above ranges, + the formatting rule will automatically be switched to the power + notation. + + The 'exponentformat' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'e', 'E', 'power', 'SI', 'B', 'SI extended'] + + Returns + ------- + Any + """ + return self["exponentformat"] + + @exponentformat.setter + def exponentformat(self, val): + self["exponentformat"] = val + + @property + def fixedrange(self): + """ + Determines whether or not this axis is zoom-able. If true, then + zoom is disabled. + + The 'fixedrange' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["fixedrange"] + + @fixedrange.setter + def fixedrange(self, val): + self["fixedrange"] = val + + @property + def gridcolor(self): + """ + Sets the color of the grid lines. + + The 'gridcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["gridcolor"] + + @gridcolor.setter + def gridcolor(self, val): + self["gridcolor"] = val + + @property + def griddash(self): + """ + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + + The 'griddash' property is an enumeration that may be specified as: + - One of the following dash styles: + ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] + - A string containing a dash length list in pixels or percentages + (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) + + Returns + ------- + str + """ + return self["griddash"] + + @griddash.setter + def griddash(self, val): + self["griddash"] = val + + @property + def gridwidth(self): + """ + Sets the width (in px) of the grid lines. + + The 'gridwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["gridwidth"] + + @gridwidth.setter + def gridwidth(self, val): + self["gridwidth"] = val + + @property + def hoverformat(self): + """ + Sets the hover text formatting rule using d3 formatting mini- + languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display "09~15~23.46" + + The 'hoverformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["hoverformat"] + + @hoverformat.setter + def hoverformat(self, val): + self["hoverformat"] = val + + @property + def insiderange(self): + """ + Could be used to set the desired inside range of this axis + (excluding the labels) when `ticklabelposition` of the anchored + axis has "inside". Not implemented for axes with `type` "log". + This would be ignored when `range` is provided. + + The 'insiderange' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'insiderange[0]' property accepts values of any type + (1) The 'insiderange[1]' property accepts values of any type + + Returns + ------- + list + """ + return self["insiderange"] + + @insiderange.setter + def insiderange(self, val): + self["insiderange"] = val + + @property + def labelalias(self): + """ + Replacement text for specific tick or hover labels. For example + using {US: 'USA', CA: 'Canada'} changes US to USA and CA to + Canada. The labels we would have shown must match the keys + exactly, after adding any tickprefix or ticksuffix. For + negative numbers the minus sign symbol used (U+2212) is wider + than the regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis type, and + both keys (if needed) and values (if desired) can include html- + like tags or MathJax. + + The 'labelalias' property accepts values of any type + + Returns + ------- + Any + """ + return self["labelalias"] + + @labelalias.setter + def labelalias(self, val): + self["labelalias"] = val + + @property + def layer(self): + """ + Sets the layer on which this axis is displayed. If *above + traces*, this axis is displayed above all the subplot's traces + If *below traces*, this axis is displayed below all the + subplot's traces, but above the grid lines. Useful when used + together with scatter-like traces with `cliponaxis` set to + False to show markers and/or text nodes above this axis. + + The 'layer' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['above traces', 'below traces'] + + Returns + ------- + Any + """ + return self["layer"] + + @layer.setter + def layer(self, val): + self["layer"] = val + + @property + def linecolor(self): + """ + Sets the axis line color. + + The 'linecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["linecolor"] + + @linecolor.setter + def linecolor(self, val): + self["linecolor"] = val + + @property + def linewidth(self): + """ + Sets the width (in px) of the axis line. + + The 'linewidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["linewidth"] + + @linewidth.setter + def linewidth(self, val): + self["linewidth"] = val + + @property + def matches(self): + """ + If set to another axis id (e.g. `x2`, `y`), the range of this + axis will match the range of the corresponding axis in data- + coordinates space. Moreover, matching axes share auto-range + values, category lists and histogram auto-bins. Note that + setting axes simultaneously in both a `scaleanchor` and a + `matches` constraint is currently forbidden. Moreover, note + that matching axes must have the same `type`. + + The 'matches' property is an enumeration that may be specified as: + - A string that matches one of the following regular expressions: + ['^x([2-9]|[1-9][0-9]+)?( domain)?$', + '^y([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["matches"] + + @matches.setter + def matches(self, val): + self["matches"] = val + + @property + def maxallowed(self): + """ + Determines the maximum range of this axis. + + The 'maxallowed' property accepts values of any type + + Returns + ------- + Any + """ + return self["maxallowed"] + + @maxallowed.setter + def maxallowed(self, val): + self["maxallowed"] = val + + @property + def minallowed(self): + """ + Determines the minimum range of this axis. + + The 'minallowed' property accepts values of any type + + Returns + ------- + Any + """ + return self["minallowed"] + + @minallowed.setter + def minallowed(self, val): + self["minallowed"] = val + + @property + def minexponent(self): + """ + Hide SI prefix for 10^n if |n| is below this number. This only + has an effect when `tickformat` is "SI" or "B". + + The 'minexponent' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["minexponent"] + + @minexponent.setter + def minexponent(self, val): + self["minexponent"] = val + + @property + def minor(self): + """ + The 'minor' property is an instance of Minor + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.yaxis.Minor` + - A dict of string/value properties that will be passed + to the Minor constructor + + Returns + ------- + plotly.graph_objs.layout.yaxis.Minor + """ + return self["minor"] + + @minor.setter + def minor(self, val): + self["minor"] = val + + @property + def minorloglabels(self): + """ + Determines how minor log labels are displayed. If *small + digits*, small digits i.e. 2 or 5 are displayed. If "complete", + complete digits are displayed. If "none", no labels are + displayed. + + The 'minorloglabels' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['small digits', 'complete', 'none'] + + Returns + ------- + Any + """ + return self["minorloglabels"] + + @minorloglabels.setter + def minorloglabels(self, val): + self["minorloglabels"] = val + + @property + def mirror(self): + """ + Determines if the axis lines or/and ticks are mirrored to the + opposite side of the plotting area. If True, the axis lines are + mirrored. If "ticks", the axis lines and ticks are mirrored. If + False, mirroring is disable. If "all", axis lines are mirrored + on all shared-axes subplots. If "allticks", axis lines and + ticks are mirrored on all shared-axes subplots. + + The 'mirror' property is an enumeration that may be specified as: + - One of the following enumeration values: + [True, 'ticks', False, 'all', 'allticks'] + + Returns + ------- + Any + """ + return self["mirror"] + + @mirror.setter + def mirror(self, val): + self["mirror"] = val + + @property + def modebardisable(self): + """ + Disables certain modebar buttons for this axis. "autoscale" + disables the autoscale buttons, "zoominout" disables the zoom- + in and zoom-out buttons. + + The 'modebardisable' property is a flaglist and may be specified + as a string containing: + - Any combination of ['autoscale', 'zoominout'] joined with '+' characters + (e.g. 'autoscale+zoominout') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["modebardisable"] + + @modebardisable.setter + def modebardisable(self, val): + self["modebardisable"] = val + + @property + def nticks(self): + """ + Specifies the maximum number of ticks for the particular axis. + The actual number of ticks will be chosen automatically to be + less than or equal to `nticks`. Has an effect only if + `tickmode` is set to "auto". + + The 'nticks' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["nticks"] + + @nticks.setter + def nticks(self, val): + self["nticks"] = val + + @property + def overlaying(self): + """ + If set a same-letter axis id, this axis is overlaid on top of + the corresponding same-letter axis, with traces and axes + visible for both axes. If False, this axis does not overlay any + same-letter axes. In this case, for axes with overlapping + domains only the highest-numbered axis will be visible. + + The 'overlaying' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['free'] + - A string that matches one of the following regular expressions: + ['^x([2-9]|[1-9][0-9]+)?( domain)?$', + '^y([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["overlaying"] + + @overlaying.setter + def overlaying(self, val): + self["overlaying"] = val + + @property + def position(self): + """ + Sets the position of this axis in the plotting space (in + normalized coordinates). Only has an effect if `anchor` is set + to "free". + + The 'position' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["position"] + + @position.setter + def position(self, val): + self["position"] = val + + @property + def range(self): + """ + Sets the range of this axis. If the axis `type` is "log", then + you must take the log of your desired range (e.g. to set the + range from 1 to 100, set the range from 0 to 2). If the axis + `type` is "date", it should be date strings, like date data, + though Date objects and unix milliseconds will be accepted and + converted to strings. If the axis `type` is "category", it + should be numbers, using the scale where each category is + assigned a serial number from zero in the order it appears. + Leaving either or both elements `null` impacts the default + `autorange`. + + The 'range' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'range[0]' property accepts values of any type + (1) The 'range[1]' property accepts values of any type + + Returns + ------- + list + """ + return self["range"] + + @range.setter + def range(self, val): + self["range"] = val + + @property + def rangebreaks(self): + """ + The 'rangebreaks' property is a tuple of instances of + Rangebreak that may be specified as: + - A list or tuple of instances of plotly.graph_objs.layout.yaxis.Rangebreak + - A list or tuple of dicts of string/value properties that + will be passed to the Rangebreak constructor + + Returns + ------- + tuple[plotly.graph_objs.layout.yaxis.Rangebreak] + """ + return self["rangebreaks"] + + @rangebreaks.setter + def rangebreaks(self, val): + self["rangebreaks"] = val + + @property + def rangebreakdefaults(self): + """ + When used in a template (as + layout.template.layout.yaxis.rangebreakdefaults), sets the + default property values to use for elements of + layout.yaxis.rangebreaks + + The 'rangebreakdefaults' property is an instance of Rangebreak + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.yaxis.Rangebreak` + - A dict of string/value properties that will be passed + to the Rangebreak constructor + + Returns + ------- + plotly.graph_objs.layout.yaxis.Rangebreak + """ + return self["rangebreakdefaults"] + + @rangebreakdefaults.setter + def rangebreakdefaults(self, val): + self["rangebreakdefaults"] = val + + @property + def rangemode(self): + """ + If "normal", the range is computed in relation to the extrema + of the input data. If "tozero", the range extends to 0, + regardless of the input data If "nonnegative", the range is + non-negative, regardless of the input data. Applies only to + linear axes. + + The 'rangemode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'tozero', 'nonnegative'] + + Returns + ------- + Any + """ + return self["rangemode"] + + @rangemode.setter + def rangemode(self, val): + self["rangemode"] = val + + @property + def scaleanchor(self): + """ + If set to another axis id (e.g. `x2`, `y`), the range of this + axis changes together with the range of the corresponding axis + such that the scale of pixels per unit is in a constant ratio. + Both axes are still zoomable, but when you zoom one, the other + will zoom the same amount, keeping a fixed midpoint. + `constrain` and `constraintoward` determine how we enforce the + constraint. You can chain these, ie `yaxis: {scaleanchor: *x*}, + xaxis2: {scaleanchor: *y*}` but you can only link axes of the + same `type`. The linked axis can have the opposite letter (to + constrain the aspect ratio) or the same letter (to match scales + across subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: + {scaleanchor: *y*}` or longer) are redundant and the last + constraint encountered will be ignored to avoid possible + inconsistent constraints via `scaleratio`. Note that setting + axes simultaneously in both a `scaleanchor` and a `matches` + constraint is currently forbidden. Setting `false` allows to + remove a default constraint (occasionally, you may need to + prevent a default `scaleanchor` constraint from being applied, + eg. when having an image trace `yaxis: {scaleanchor: "x"}` is + set automatically in order for pixels to be rendered as + squares, setting `yaxis: {scaleanchor: false}` allows to remove + the constraint). + + The 'scaleanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + [False] + - A string that matches one of the following regular expressions: + ['^x([2-9]|[1-9][0-9]+)?( domain)?$', + '^y([2-9]|[1-9][0-9]+)?( domain)?$'] + + Returns + ------- + Any + """ + return self["scaleanchor"] + + @scaleanchor.setter + def scaleanchor(self, val): + self["scaleanchor"] = val + + @property + def scaleratio(self): + """ + If this axis is linked to another by `scaleanchor`, this + determines the pixel to unit scale ratio. For example, if this + value is 10, then every unit on this axis spans 10 times the + number of pixels as a unit on the linked axis. Use this for + example to create an elevation profile where the vertical scale + is exaggerated a fixed amount with respect to the horizontal. + + The 'scaleratio' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["scaleratio"] + + @scaleratio.setter + def scaleratio(self, val): + self["scaleratio"] = val + + @property + def separatethousands(self): + """ + If "true", even 4-digit integers are separated + + The 'separatethousands' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["separatethousands"] + + @separatethousands.setter + def separatethousands(self, val): + self["separatethousands"] = val + + @property + def shift(self): + """ + Moves the axis a given number of pixels from where it would + have been otherwise. Accepts both positive and negative values, + which will shift the axis either right or left, respectively. + If `autoshift` is set to true, then this defaults to a padding + of -3 if `side` is set to "left". and defaults to +3 if `side` + is set to "right". Defaults to 0 if `autoshift` is set to + false. Only has an effect if `anchor` is set to "free". + + The 'shift' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["shift"] + + @shift.setter + def shift(self, val): + self["shift"] = val + + @property + def showdividers(self): + """ + Determines whether or not a dividers are drawn between the + category levels of this axis. Only has an effect on + "multicategory" axes. + + The 'showdividers' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showdividers"] + + @showdividers.setter + def showdividers(self, val): + self["showdividers"] = val + + @property + def showexponent(self): + """ + If "all", all exponents are shown besides their significands. + If "first", only the exponent of the first tick is shown. If + "last", only the exponent of the last tick is shown. If "none", + no exponents appear. + + The 'showexponent' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showexponent"] + + @showexponent.setter + def showexponent(self, val): + self["showexponent"] = val + + @property + def showgrid(self): + """ + Determines whether or not grid lines are drawn. If True, the + grid lines are drawn at every tick mark. + + The 'showgrid' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showgrid"] + + @showgrid.setter + def showgrid(self, val): + self["showgrid"] = val + + @property + def showline(self): + """ + Determines whether or not a line bounding this axis is drawn. + + The 'showline' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showline"] + + @showline.setter + def showline(self, val): + self["showline"] = val + + @property + def showspikes(self): + """ + Determines whether or not spikes (aka droplines) are drawn for + this axis. Note: This only takes affect when hovermode = + closest + + The 'showspikes' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showspikes"] + + @showspikes.setter + def showspikes(self, val): + self["showspikes"] = val + + @property + def showticklabels(self): + """ + Determines whether or not the tick labels are drawn. + + The 'showticklabels' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showticklabels"] + + @showticklabels.setter + def showticklabels(self, val): + self["showticklabels"] = val + + @property + def showtickprefix(self): + """ + If "all", all tick labels are displayed with a prefix. If + "first", only the first tick is displayed with a prefix. If + "last", only the last tick is displayed with a suffix. If + "none", tick prefixes are hidden. + + The 'showtickprefix' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showtickprefix"] + + @showtickprefix.setter + def showtickprefix(self, val): + self["showtickprefix"] = val + + @property + def showticksuffix(self): + """ + Same as `showtickprefix` but for tick suffixes. + + The 'showticksuffix' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showticksuffix"] + + @showticksuffix.setter + def showticksuffix(self, val): + self["showticksuffix"] = val + + @property + def side(self): + """ + Determines whether a x (y) axis is positioned at the "bottom" + ("left") or "top" ("right") of the plotting area. + + The 'side' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top', 'bottom', 'left', 'right'] + + Returns + ------- + Any + """ + return self["side"] + + @side.setter + def side(self, val): + self["side"] = val + + @property + def spikecolor(self): + """ + Sets the spike color. If undefined, will use the series color + + The 'spikecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["spikecolor"] + + @spikecolor.setter + def spikecolor(self, val): + self["spikecolor"] = val + + @property + def spikedash(self): + """ + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + + The 'spikedash' property is an enumeration that may be specified as: + - One of the following dash styles: + ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] + - A string containing a dash length list in pixels or percentages + (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) + + Returns + ------- + str + """ + return self["spikedash"] + + @spikedash.setter + def spikedash(self, val): + self["spikedash"] = val + + @property + def spikemode(self): + """ + Determines the drawing mode for the spike line If "toaxis", the + line is drawn from the data point to the axis the series is + plotted on. If "across", the line is drawn across the entire + plot area, and supercedes "toaxis". If "marker", then a marker + dot is drawn on the axis the series is plotted on + + The 'spikemode' property is a flaglist and may be specified + as a string containing: + - Any combination of ['toaxis', 'across', 'marker'] joined with '+' characters + (e.g. 'toaxis+across') + + Returns + ------- + Any + """ + return self["spikemode"] + + @spikemode.setter + def spikemode(self, val): + self["spikemode"] = val + + @property + def spikesnap(self): + """ + Determines whether spikelines are stuck to the cursor or to the + closest datapoints. + + The 'spikesnap' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['data', 'cursor', 'hovered data'] + + Returns + ------- + Any + """ + return self["spikesnap"] + + @spikesnap.setter + def spikesnap(self, val): + self["spikesnap"] = val + + @property + def spikethickness(self): + """ + Sets the width (in px) of the zero line. + + The 'spikethickness' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["spikethickness"] + + @spikethickness.setter + def spikethickness(self, val): + self["spikethickness"] = val + + @property + def tick0(self): + """ + Sets the placement of the first tick on this axis. Use with + `dtick`. If the axis `type` is "log", then you must take the + log of your starting tick (e.g. to set the starting tick to + 100, set the `tick0` to 2) except when `dtick`=*L* (see + `dtick` for more info). If the axis `type` is "date", it should + be a date string, like date data. If the axis `type` is + "category", it should be a number, using the scale where each + category is assigned a serial number from zero in the order it + appears. + + The 'tick0' property accepts values of any type + + Returns + ------- + Any + """ + return self["tick0"] + + @tick0.setter + def tick0(self, val): + self["tick0"] = val + + @property + def tickangle(self): + """ + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the tick + labels vertically. + + The 'tickangle' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["tickangle"] + + @tickangle.setter + def tickangle(self, val): + self["tickangle"] = val + + @property + def tickcolor(self): + """ + Sets the tick color. + + The 'tickcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["tickcolor"] + + @tickcolor.setter + def tickcolor(self, val): + self["tickcolor"] = val + + @property + def tickfont(self): + """ + Sets the tick font. + + The 'tickfont' property is an instance of Tickfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.yaxis.Tickfont` + - A dict of string/value properties that will be passed + to the Tickfont constructor + + Returns + ------- + plotly.graph_objs.layout.yaxis.Tickfont + """ + return self["tickfont"] + + @tickfont.setter + def tickfont(self, val): + self["tickfont"] = val + + @property + def tickformat(self): + """ + Sets the tick label formatting rule using d3 formatting mini- + languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display "09~15~23.46" + + The 'tickformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["tickformat"] + + @tickformat.setter + def tickformat(self, val): + self["tickformat"] = val + + @property + def tickformatstops(self): + """ + The 'tickformatstops' property is a tuple of instances of + Tickformatstop that may be specified as: + - A list or tuple of instances of plotly.graph_objs.layout.yaxis.Tickformatstop + - A list or tuple of dicts of string/value properties that + will be passed to the Tickformatstop constructor + + Returns + ------- + tuple[plotly.graph_objs.layout.yaxis.Tickformatstop] + """ + return self["tickformatstops"] + + @tickformatstops.setter + def tickformatstops(self, val): + self["tickformatstops"] = val + + @property + def tickformatstopdefaults(self): + """ + When used in a template (as + layout.template.layout.yaxis.tickformatstopdefaults), sets the + default property values to use for elements of + layout.yaxis.tickformatstops + + The 'tickformatstopdefaults' property is an instance of Tickformatstop + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.yaxis.Tickformatstop` + - A dict of string/value properties that will be passed + to the Tickformatstop constructor + + Returns + ------- + plotly.graph_objs.layout.yaxis.Tickformatstop + """ + return self["tickformatstopdefaults"] + + @tickformatstopdefaults.setter + def tickformatstopdefaults(self, val): + self["tickformatstopdefaults"] = val + + @property + def ticklabelindex(self): + """ + Only for axes with `type` "date" or "linear". Instead of + drawing the major tick label, draw the label for the minor tick + that is n positions away from the major tick. E.g. to always + draw the label for the minor tick before each major tick, + choose `ticklabelindex` -1. This is useful for date axes with + `ticklabelmode` "period" if you want to label the period that + ends with each major tick instead of the period that begins + there. + + The 'ticklabelindex' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["ticklabelindex"] + + @ticklabelindex.setter + def ticklabelindex(self, val): + self["ticklabelindex"] = val + + @property + def ticklabelindexsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `ticklabelindex`. + + The 'ticklabelindexsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ticklabelindexsrc"] + + @ticklabelindexsrc.setter + def ticklabelindexsrc(self, val): + self["ticklabelindexsrc"] = val + + @property + def ticklabelmode(self): + """ + Determines where tick labels are drawn with respect to their + corresponding ticks and grid lines. Only has an effect for axes + of `type` "date" When set to "period", tick labels are drawn in + the middle of the period between ticks. + + The 'ticklabelmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['instant', 'period'] + + Returns + ------- + Any + """ + return self["ticklabelmode"] + + @ticklabelmode.setter + def ticklabelmode(self, val): + self["ticklabelmode"] = val + + @property + def ticklabeloverflow(self): + """ + Determines how we handle tick labels that would overflow either + the graph div or the domain of the axis. The default value for + inside tick labels is *hide past domain*. Otherwise on + "category" and "multicategory" axes the default is "allow". In + other cases the default is *hide past div*. + + The 'ticklabeloverflow' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['allow', 'hide past div', 'hide past domain'] + + Returns + ------- + Any + """ + return self["ticklabeloverflow"] + + @ticklabeloverflow.setter + def ticklabeloverflow(self, val): + self["ticklabeloverflow"] = val + + @property + def ticklabelposition(self): + """ + Determines where tick labels are drawn with respect to the + axis. Please note that top or bottom has no effect on x axes or + when `ticklabelmode` is set to "period" or when `tickson` is + set to "boundaries". Similarly, left or right has no effect on + y axes or when `ticklabelmode` is set to "period" or when + `tickson` is set to "boundaries". Has no effect on + "multicategory" axes. When used on axes linked by `matches` or + `scaleanchor`, no extra padding for inside labels would be + added by autorange, so that the scales could match. + + The 'ticklabelposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['outside', 'inside', 'outside top', 'inside top', + 'outside left', 'inside left', 'outside right', 'inside + right', 'outside bottom', 'inside bottom'] + + Returns + ------- + Any + """ + return self["ticklabelposition"] + + @ticklabelposition.setter + def ticklabelposition(self, val): + self["ticklabelposition"] = val + + @property + def ticklabelshift(self): + """ + Shifts the tick labels by the specified number of pixels in + parallel to the axis. Positive values move the labels in the + positive direction of the axis. + + The 'ticklabelshift' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["ticklabelshift"] + + @ticklabelshift.setter + def ticklabelshift(self, val): + self["ticklabelshift"] = val + + @property + def ticklabelstandoff(self): + """ + Sets the standoff distance (in px) between the axis tick labels + and their default position. A positive `ticklabelstandoff` + moves the labels farther away from the plot area if + `ticklabelposition` is "outside", and deeper into the plot area + if `ticklabelposition` is "inside". A negative + `ticklabelstandoff` works in the opposite direction, moving + outside ticks towards the plot area and inside ticks towards + the outside. If the negative value is large enough, inside + ticks can even end up outside and vice versa. + + The 'ticklabelstandoff' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["ticklabelstandoff"] + + @ticklabelstandoff.setter + def ticklabelstandoff(self, val): + self["ticklabelstandoff"] = val + + @property + def ticklabelstep(self): + """ + Sets the spacing between tick labels as compared to the spacing + between ticks. A value of 1 (default) means each tick gets a + label. A value of 2 means shows every 2nd label. A larger value + n means only every nth tick is labeled. `tick0` determines + which labels are shown. Not implemented for axes with `type` + "log" or "multicategory", or when `tickmode` is "array". + + The 'ticklabelstep' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 9223372036854775807] + + Returns + ------- + int + """ + return self["ticklabelstep"] + + @ticklabelstep.setter + def ticklabelstep(self, val): + self["ticklabelstep"] = val + + @property + def ticklen(self): + """ + Sets the tick length (in px). + + The 'ticklen' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["ticklen"] + + @ticklen.setter + def ticklen(self, val): + self["ticklen"] = val + + @property + def tickmode(self): + """ + Sets the tick mode for this axis. If "auto", the number of + ticks is set via `nticks`. If "linear", the placement of the + ticks is determined by a starting position `tick0` and a tick + step `dtick` ("linear" is the default value if `tick0` and + `dtick` are provided). If "array", the placement of the ticks + is set via `tickvals` and the tick text is `ticktext`. ("array" + is the default value if `tickvals` is provided). If "sync", the + number of ticks will sync with the overlayed axis set by + `overlaying` property. + + The 'tickmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'linear', 'array', 'sync'] + + Returns + ------- + Any + """ + return self["tickmode"] + + @tickmode.setter + def tickmode(self, val): + self["tickmode"] = val + + @property + def tickprefix(self): + """ + Sets a tick label prefix. + + The 'tickprefix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["tickprefix"] + + @tickprefix.setter + def tickprefix(self, val): + self["tickprefix"] = val + + @property + def ticks(self): + """ + Determines whether ticks are drawn or not. If "", this axis' + ticks are not drawn. If "outside" ("inside"), this axis' are + drawn outside (inside) the axis lines. + + The 'ticks' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['outside', 'inside', ''] + + Returns + ------- + Any + """ + return self["ticks"] + + @ticks.setter + def ticks(self, val): + self["ticks"] = val + + @property + def tickson(self): + """ + Determines where ticks and grid lines are drawn with respect to + their corresponding tick labels. Only has an effect for axes of + `type` "category" or "multicategory". When set to "boundaries", + ticks and grid lines are drawn half a category to the + left/bottom of labels. + + The 'tickson' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['labels', 'boundaries'] + + Returns + ------- + Any + """ + return self["tickson"] + + @tickson.setter + def tickson(self, val): + self["tickson"] = val + + @property + def ticksuffix(self): + """ + Sets a tick label suffix. + + The 'ticksuffix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["ticksuffix"] + + @ticksuffix.setter + def ticksuffix(self, val): + self["ticksuffix"] = val + + @property + def ticktext(self): + """ + Sets the text displayed at the ticks position via `tickvals`. + Only has an effect if `tickmode` is set to "array". Used with + `tickvals`. + + The 'ticktext' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ticktext"] + + @ticktext.setter + def ticktext(self, val): + self["ticktext"] = val + + @property + def ticktextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ticktext`. + + The 'ticktextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ticktextsrc"] + + @ticktextsrc.setter + def ticktextsrc(self, val): + self["ticktextsrc"] = val + + @property + def tickvals(self): + """ + Sets the values at which ticks on this axis appear. Only has an + effect if `tickmode` is set to "array". Used with `ticktext`. + + The 'tickvals' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["tickvals"] + + @tickvals.setter + def tickvals(self, val): + self["tickvals"] = val + + @property + def tickvalssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `tickvals`. + + The 'tickvalssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["tickvalssrc"] + + @tickvalssrc.setter + def tickvalssrc(self, val): + self["tickvalssrc"] = val + + @property + def tickwidth(self): + """ + Sets the tick width (in px). + + The 'tickwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["tickwidth"] + + @tickwidth.setter + def tickwidth(self, val): + self["tickwidth"] = val + + @property + def title(self): + """ + The 'title' property is an instance of Title + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.yaxis.Title` + - A dict of string/value properties that will be passed + to the Title constructor + + Returns + ------- + plotly.graph_objs.layout.yaxis.Title + """ + return self["title"] + + @title.setter + def title(self, val): + self["title"] = val + + @property + def type(self): + """ + Sets the axis type. By default, plotly attempts to determined + the axis type by looking into the data of the traces that + referenced the axis in question. + + The 'type' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['-', 'linear', 'log', 'date', 'category', + 'multicategory'] + + Returns + ------- + Any + """ + return self["type"] + + @type.setter + def type(self, val): + self["type"] = val + + @property + def uirevision(self): + """ + Controls persistence of user-driven changes in axis `range`, + `autorange`, and `title` if in `editable: true` configuration. + Defaults to `layout.uirevision`. + + The 'uirevision' property accepts values of any type + + Returns + ------- + Any + """ + return self["uirevision"] + + @uirevision.setter + def uirevision(self, val): + self["uirevision"] = val + + @property + def unifiedhovertitle(self): + """ + The 'unifiedhovertitle' property is an instance of Unifiedhovertitle + that may be specified as: + - An instance of :class:`plotly.graph_objs.layout.yaxis.Unifiedhovertitle` + - A dict of string/value properties that will be passed + to the Unifiedhovertitle constructor + + Returns + ------- + plotly.graph_objs.layout.yaxis.Unifiedhovertitle + """ + return self["unifiedhovertitle"] + + @unifiedhovertitle.setter + def unifiedhovertitle(self, val): + self["unifiedhovertitle"] = val + + @property + def visible(self): + """ + A single toggle to hide the axis while preserving interaction + like dragging. Default is true when a cheater plot is present + on the axis, otherwise false + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def zeroline(self): + """ + Determines whether or not a line is drawn at along the 0 value + of this axis. If True, the zero line is drawn on top of the + grid lines. + + The 'zeroline' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["zeroline"] + + @zeroline.setter + def zeroline(self, val): + self["zeroline"] = val + + @property + def zerolinecolor(self): + """ + Sets the line color of the zero line. + + The 'zerolinecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["zerolinecolor"] + + @zerolinecolor.setter + def zerolinecolor(self, val): + self["zerolinecolor"] = val + + @property + def zerolinelayer(self): + """ + Sets the layer on which this zeroline is displayed. If *above + traces*, this zeroline is displayed above all the subplot's + traces If *below traces*, this zeroline is displayed below all + the subplot's traces, but above the grid lines. Limitation: + "zerolinelayer" currently has no effect if the "zorder" + property is set on any trace. + + The 'zerolinelayer' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['above traces', 'below traces'] + + Returns + ------- + Any + """ + return self["zerolinelayer"] + + @zerolinelayer.setter + def zerolinelayer(self, val): + self["zerolinelayer"] = val + + @property + def zerolinewidth(self): + """ + Sets the width (in px) of the zero line. + + The 'zerolinewidth' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["zerolinewidth"] + + @zerolinewidth.setter + def zerolinewidth(self, val): + self["zerolinewidth"] = val + + @property + def _prop_descriptions(self): + return """\ + anchor + If set to an opposite-letter axis id (e.g. `x2`, `y`), + this axis is bound to the corresponding opposite-letter + axis. If set to "free", this axis' position is + determined by `position`. + automargin + Determines whether long tick labels automatically grow + the figure margins. + autorange + Determines whether or not the range of this axis is + computed in relation to the input data. See `rangemode` + for more info. If `range` is provided and it has a + value for both the lower and upper bound, `autorange` + is set to False. Using "min" applies autorange only to + set the minimum. Using "max" applies autorange only to + set the maximum. Using *min reversed* applies autorange + only to set the minimum on a reversed axis. Using *max + reversed* applies autorange only to set the maximum on + a reversed axis. Using "reversed" applies autorange on + both ends and reverses the axis direction. + autorangeoptions + :class:`plotly.graph_objects.layout.yaxis.Autorangeopti + ons` instance or dict with compatible properties + autoshift + Automatically reposition the axis to avoid overlap with + other axes with the same `overlaying` value. This + repositioning will account for any `shift` amount + applied to other axes on the same side with `autoshift` + is set to true. Only has an effect if `anchor` is set + to "free". + autotickangles + When `tickangle` is set to "auto", it will be set to + the first angle in this array that is large enough to + prevent label overlap. + autotypenumbers + Using "strict" a numeric string in trace data is not + converted to a number. Using *convert types* a numeric + string in trace data may be treated as a number during + automatic axis `type` detection. Defaults to + layout.autotypenumbers. + calendar + Sets the calendar system to use for `range` and `tick0` + if this is a date axis. This does not set the calendar + for interpreting data on this axis, that's specified in + the trace or via the global `layout.calendar` + categoryarray + Sets the order in which categories on this axis appear. + Only has an effect if `categoryorder` is set to + "array". Used with `categoryorder`. + categoryarraysrc + Sets the source reference on Chart Studio Cloud for + `categoryarray`. + categoryorder + Specifies the ordering logic for the case of + categorical variables. By default, plotly uses "trace", + which specifies the order that is present in the data + supplied. Set `categoryorder` to *category ascending* + or *category descending* if order should be determined + by the alphanumerical order of the category names. Set + `categoryorder` to "array" to derive the ordering from + the attribute `categoryarray`. If a category is not + found in the `categoryarray` array, the sorting + behavior for that attribute will be identical to the + "trace" mode. The unspecified categories will follow + the categories in `categoryarray`. Set `categoryorder` + to *total ascending* or *total descending* if order + should be determined by the numerical order of the + values. Similarly, the order can be determined by the + min, max, sum, mean, geometric mean or median of all + the values. + color + Sets default for all colors associated with this axis + all at once: line, font, tick, and grid colors. Grid + color is lightened by blending this with the plot + background Individual pieces can override this. + constrain + If this axis needs to be compressed (either due to its + own `scaleanchor` and `scaleratio` or those of the + other axis), determines how that happens: by increasing + the "range", or by decreasing the "domain". Default is + "domain" for axes containing image traces, "range" + otherwise. + constraintoward + If this axis needs to be compressed (either due to its + own `scaleanchor` and `scaleratio` or those of the + other axis), determines which direction we push the + originally specified plot area. Options are "left", + "center" (default), and "right" for x axes, and "top", + "middle" (default), and "bottom" for y axes. + dividercolor + Sets the color of the dividers Only has an effect on + "multicategory" axes. + dividerwidth + Sets the width (in px) of the dividers Only has an + effect on "multicategory" axes. + domain + Sets the domain of this axis (in plot fraction). + dtick + Sets the step in-between ticks on this axis. Use with + `tick0`. Must be a positive number, or special strings + available to "log" and "date" axes. If the axis `type` + is "log", then ticks are set every 10^(n*dtick) where n + is the tick number. For example, to set a tick mark at + 1, 10, 100, 1000, ... set dtick to 1. To set tick marks + at 1, 100, 10000, ... set dtick to 2. To set tick marks + at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special + values; "L", where `f` is a positive number, gives + ticks linearly spaced in value (but not position). For + example `tick0` = 0.1, `dtick` = "L0.5" will put ticks + at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus + small digits between, use "D1" (all digits) or "D2" + (only 2 and 5). `tick0` is ignored for "D1" and "D2". + If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval + between ticks to one day, set `dtick` to 86400000.0. + "date" also has special values "M" gives ticks + spaced by a number of months. `n` must be a positive + integer. To set ticks on the 15th of every third month, + set `tick0` to "2000-01-15" and `dtick` to "M3". To set + ticks every 4 years, set `dtick` to "M48" + exponentformat + Determines a formatting rule for the tick exponents. + For example, consider the number 1,000,000,000. If + "none", it appears as 1,000,000,000. If "e", 1e+9. If + "E", 1E+9. If "power", 1x10^9 (with 9 in a super + script). If "SI", 1G. If "B", 1B. "SI" uses prefixes + from "femto" f (10^-15) to "tera" T (10^12). *SI + extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or + *SI extended* is used and the exponent is beyond the + above ranges, the formatting rule will automatically be + switched to the power notation. + fixedrange + Determines whether or not this axis is zoom-able. If + true, then zoom is disabled. + gridcolor + Sets the color of the grid lines. + griddash + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + gridwidth + Sets the width (in px) of the grid lines. + hoverformat + Sets the hover text formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + insiderange + Could be used to set the desired inside range of this + axis (excluding the labels) when `ticklabelposition` of + the anchored axis has "inside". Not implemented for + axes with `type` "log". This would be ignored when + `range` is provided. + labelalias + Replacement text for specific tick or hover labels. For + example using {US: 'USA', CA: 'Canada'} changes US to + USA and CA to Canada. The labels we would have shown + must match the keys exactly, after adding any + tickprefix or ticksuffix. For negative numbers the + minus sign symbol used (U+2212) is wider than the + regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis + type, and both keys (if needed) and values (if desired) + can include html-like tags or MathJax. + layer + Sets the layer on which this axis is displayed. If + *above traces*, this axis is displayed above all the + subplot's traces If *below traces*, this axis is + displayed below all the subplot's traces, but above the + grid lines. Useful when used together with scatter-like + traces with `cliponaxis` set to False to show markers + and/or text nodes above this axis. + linecolor + Sets the axis line color. + linewidth + Sets the width (in px) of the axis line. + matches + If set to another axis id (e.g. `x2`, `y`), the range + of this axis will match the range of the corresponding + axis in data-coordinates space. Moreover, matching axes + share auto-range values, category lists and histogram + auto-bins. Note that setting axes simultaneously in + both a `scaleanchor` and a `matches` constraint is + currently forbidden. Moreover, note that matching axes + must have the same `type`. + maxallowed + Determines the maximum range of this axis. + minallowed + Determines the minimum range of this axis. + minexponent + Hide SI prefix for 10^n if |n| is below this number. + This only has an effect when `tickformat` is "SI" or + "B". + minor + :class:`plotly.graph_objects.layout.yaxis.Minor` + instance or dict with compatible properties + minorloglabels + Determines how minor log labels are displayed. If + *small digits*, small digits i.e. 2 or 5 are displayed. + If "complete", complete digits are displayed. If + "none", no labels are displayed. + mirror + Determines if the axis lines or/and ticks are mirrored + to the opposite side of the plotting area. If True, the + axis lines are mirrored. If "ticks", the axis lines and + ticks are mirrored. If False, mirroring is disable. If + "all", axis lines are mirrored on all shared-axes + subplots. If "allticks", axis lines and ticks are + mirrored on all shared-axes subplots. + modebardisable + Disables certain modebar buttons for this axis. + "autoscale" disables the autoscale buttons, "zoominout" + disables the zoom-in and zoom-out buttons. + nticks + Specifies the maximum number of ticks for the + particular axis. The actual number of ticks will be + chosen automatically to be less than or equal to + `nticks`. Has an effect only if `tickmode` is set to + "auto". + overlaying + If set a same-letter axis id, this axis is overlaid on + top of the corresponding same-letter axis, with traces + and axes visible for both axes. If False, this axis + does not overlay any same-letter axes. In this case, + for axes with overlapping domains only the highest- + numbered axis will be visible. + position + Sets the position of this axis in the plotting space + (in normalized coordinates). Only has an effect if + `anchor` is set to "free". + range + Sets the range of this axis. If the axis `type` is + "log", then you must take the log of your desired range + (e.g. to set the range from 1 to 100, set the range + from 0 to 2). If the axis `type` is "date", it should + be date strings, like date data, though Date objects + and unix milliseconds will be accepted and converted to + strings. If the axis `type` is "category", it should be + numbers, using the scale where each category is + assigned a serial number from zero in the order it + appears. Leaving either or both elements `null` impacts + the default `autorange`. + rangebreaks + A tuple of + :class:`plotly.graph_objects.layout.yaxis.Rangebreak` + instances or dicts with compatible properties + rangebreakdefaults + When used in a template (as + layout.template.layout.yaxis.rangebreakdefaults), sets + the default property values to use for elements of + layout.yaxis.rangebreaks + rangemode + If "normal", the range is computed in relation to the + extrema of the input data. If "tozero", the range + extends to 0, regardless of the input data If + "nonnegative", the range is non-negative, regardless of + the input data. Applies only to linear axes. + scaleanchor + If set to another axis id (e.g. `x2`, `y`), the range + of this axis changes together with the range of the + corresponding axis such that the scale of pixels per + unit is in a constant ratio. Both axes are still + zoomable, but when you zoom one, the other will zoom + the same amount, keeping a fixed midpoint. `constrain` + and `constraintoward` determine how we enforce the + constraint. You can chain these, ie `yaxis: + {scaleanchor: *x*}, xaxis2: {scaleanchor: *y*}` but you + can only link axes of the same `type`. The linked axis + can have the opposite letter (to constrain the aspect + ratio) or the same letter (to match scales across + subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: + {scaleanchor: *y*}` or longer) are redundant and the + last constraint encountered will be ignored to avoid + possible inconsistent constraints via `scaleratio`. + Note that setting axes simultaneously in both a + `scaleanchor` and a `matches` constraint is currently + forbidden. Setting `false` allows to remove a default + constraint (occasionally, you may need to prevent a + default `scaleanchor` constraint from being applied, + eg. when having an image trace `yaxis: {scaleanchor: + "x"}` is set automatically in order for pixels to be + rendered as squares, setting `yaxis: {scaleanchor: + false}` allows to remove the constraint). + scaleratio + If this axis is linked to another by `scaleanchor`, + this determines the pixel to unit scale ratio. For + example, if this value is 10, then every unit on this + axis spans 10 times the number of pixels as a unit on + the linked axis. Use this for example to create an + elevation profile where the vertical scale is + exaggerated a fixed amount with respect to the + horizontal. + separatethousands + If "true", even 4-digit integers are separated + shift + Moves the axis a given number of pixels from where it + would have been otherwise. Accepts both positive and + negative values, which will shift the axis either right + or left, respectively. If `autoshift` is set to true, + then this defaults to a padding of -3 if `side` is set + to "left". and defaults to +3 if `side` is set to + "right". Defaults to 0 if `autoshift` is set to false. + Only has an effect if `anchor` is set to "free". + showdividers + Determines whether or not a dividers are drawn between + the category levels of this axis. Only has an effect on + "multicategory" axes. + showexponent + If "all", all exponents are shown besides their + significands. If "first", only the exponent of the + first tick is shown. If "last", only the exponent of + the last tick is shown. If "none", no exponents appear. + showgrid + Determines whether or not grid lines are drawn. If + True, the grid lines are drawn at every tick mark. + showline + Determines whether or not a line bounding this axis is + drawn. + showspikes + Determines whether or not spikes (aka droplines) are + drawn for this axis. Note: This only takes affect when + hovermode = closest + showticklabels + Determines whether or not the tick labels are drawn. + showtickprefix + If "all", all tick labels are displayed with a prefix. + If "first", only the first tick is displayed with a + prefix. If "last", only the last tick is displayed with + a suffix. If "none", tick prefixes are hidden. + showticksuffix + Same as `showtickprefix` but for tick suffixes. + side + Determines whether a x (y) axis is positioned at the + "bottom" ("left") or "top" ("right") of the plotting + area. + spikecolor + Sets the spike color. If undefined, will use the series + color + spikedash + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + spikemode + Determines the drawing mode for the spike line If + "toaxis", the line is drawn from the data point to the + axis the series is plotted on. If "across", the line + is drawn across the entire plot area, and supercedes + "toaxis". If "marker", then a marker dot is drawn on + the axis the series is plotted on + spikesnap + Determines whether spikelines are stuck to the cursor + or to the closest datapoints. + spikethickness + Sets the width (in px) of the zero line. + tick0 + Sets the placement of the first tick on this axis. Use + with `dtick`. If the axis `type` is "log", then you + must take the log of your starting tick (e.g. to set + the starting tick to 100, set the `tick0` to 2) except + when `dtick`=*L* (see `dtick` for more info). If the + axis `type` is "date", it should be a date string, like + date data. If the axis `type` is "category", it should + be a number, using the scale where each category is + assigned a serial number from zero in the order it + appears. + tickangle + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + tick labels vertically. + tickcolor + Sets the tick color. + tickfont + Sets the tick font. + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + tickformatstops + A tuple of :class:`plotly.graph_objects.layout.yaxis.Ti + ckformatstop` instances or dicts with compatible + properties + tickformatstopdefaults + When used in a template (as + layout.template.layout.yaxis.tickformatstopdefaults), + sets the default property values to use for elements of + layout.yaxis.tickformatstops + ticklabelindex + Only for axes with `type` "date" or "linear". Instead + of drawing the major tick label, draw the label for the + minor tick that is n positions away from the major + tick. E.g. to always draw the label for the minor tick + before each major tick, choose `ticklabelindex` -1. + This is useful for date axes with `ticklabelmode` + "period" if you want to label the period that ends with + each major tick instead of the period that begins + there. + ticklabelindexsrc + Sets the source reference on Chart Studio Cloud for + `ticklabelindex`. + ticklabelmode + Determines where tick labels are drawn with respect to + their corresponding ticks and grid lines. Only has an + effect for axes of `type` "date" When set to "period", + tick labels are drawn in the middle of the period + between ticks. + ticklabeloverflow + Determines how we handle tick labels that would + overflow either the graph div or the domain of the + axis. The default value for inside tick labels is *hide + past domain*. Otherwise on "category" and + "multicategory" axes the default is "allow". In other + cases the default is *hide past div*. + ticklabelposition + Determines where tick labels are drawn with respect to + the axis. Please note that top or bottom has no effect + on x axes or when `ticklabelmode` is set to "period" or + when `tickson` is set to "boundaries". Similarly, left + or right has no effect on y axes or when + `ticklabelmode` is set to "period" or when `tickson` is + set to "boundaries". Has no effect on "multicategory" + axes. When used on axes linked by `matches` or + `scaleanchor`, no extra padding for inside labels would + be added by autorange, so that the scales could match. + ticklabelshift + Shifts the tick labels by the specified number of + pixels in parallel to the axis. Positive values move + the labels in the positive direction of the axis. + ticklabelstandoff + Sets the standoff distance (in px) between the axis + tick labels and their default position. A positive + `ticklabelstandoff` moves the labels farther away from + the plot area if `ticklabelposition` is "outside", and + deeper into the plot area if `ticklabelposition` is + "inside". A negative `ticklabelstandoff` works in the + opposite direction, moving outside ticks towards the + plot area and inside ticks towards the outside. If the + negative value is large enough, inside ticks can even + end up outside and vice versa. + ticklabelstep + Sets the spacing between tick labels as compared to the + spacing between ticks. A value of 1 (default) means + each tick gets a label. A value of 2 means shows every + 2nd label. A larger value n means only every nth tick + is labeled. `tick0` determines which labels are shown. + Not implemented for axes with `type` "log" or + "multicategory", or when `tickmode` is "array". + ticklen + Sets the tick length (in px). + tickmode + Sets the tick mode for this axis. If "auto", the number + of ticks is set via `nticks`. If "linear", the + placement of the ticks is determined by a starting + position `tick0` and a tick step `dtick` ("linear" is + the default value if `tick0` and `dtick` are provided). + If "array", the placement of the ticks is set via + `tickvals` and the tick text is `ticktext`. ("array" is + the default value if `tickvals` is provided). If + "sync", the number of ticks will sync with the + overlayed axis set by `overlaying` property. + tickprefix + Sets a tick label prefix. + ticks + Determines whether ticks are drawn or not. If "", this + axis' ticks are not drawn. If "outside" ("inside"), + this axis' are drawn outside (inside) the axis lines. + tickson + Determines where ticks and grid lines are drawn with + respect to their corresponding tick labels. Only has an + effect for axes of `type` "category" or + "multicategory". When set to "boundaries", ticks and + grid lines are drawn half a category to the left/bottom + of labels. + ticksuffix + Sets a tick label suffix. + ticktext + Sets the text displayed at the ticks position via + `tickvals`. Only has an effect if `tickmode` is set to + "array". Used with `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + Only has an effect if `tickmode` is set to "array". + Used with `ticktext`. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + tickwidth + Sets the tick width (in px). + title + :class:`plotly.graph_objects.layout.yaxis.Title` + instance or dict with compatible properties + type + Sets the axis type. By default, plotly attempts to + determined the axis type by looking into the data of + the traces that referenced the axis in question. + uirevision + Controls persistence of user-driven changes in axis + `range`, `autorange`, and `title` if in `editable: + true` configuration. Defaults to `layout.uirevision`. + unifiedhovertitle + :class:`plotly.graph_objects.layout.yaxis.Unifiedhovert + itle` instance or dict with compatible properties + visible + A single toggle to hide the axis while preserving + interaction like dragging. Default is true when a + cheater plot is present on the axis, otherwise false + zeroline + Determines whether or not a line is drawn at along the + 0 value of this axis. If True, the zero line is drawn + on top of the grid lines. + zerolinecolor + Sets the line color of the zero line. + zerolinelayer + Sets the layer on which this zeroline is displayed. If + *above traces*, this zeroline is displayed above all + the subplot's traces If *below traces*, this zeroline + is displayed below all the subplot's traces, but above + the grid lines. Limitation: "zerolinelayer" currently + has no effect if the "zorder" property is set on any + trace. + zerolinewidth + Sets the width (in px) of the zero line. + """ + + def __init__( + self, + arg=None, + anchor=None, + automargin=None, + autorange=None, + autorangeoptions=None, + autoshift=None, + autotickangles=None, + autotypenumbers=None, + calendar=None, + categoryarray=None, + categoryarraysrc=None, + categoryorder=None, + color=None, + constrain=None, + constraintoward=None, + dividercolor=None, + dividerwidth=None, + domain=None, + dtick=None, + exponentformat=None, + fixedrange=None, + gridcolor=None, + griddash=None, + gridwidth=None, + hoverformat=None, + insiderange=None, + labelalias=None, + layer=None, + linecolor=None, + linewidth=None, + matches=None, + maxallowed=None, + minallowed=None, + minexponent=None, + minor=None, + minorloglabels=None, + mirror=None, + modebardisable=None, + nticks=None, + overlaying=None, + position=None, + range=None, + rangebreaks=None, + rangebreakdefaults=None, + rangemode=None, + scaleanchor=None, + scaleratio=None, + separatethousands=None, + shift=None, + showdividers=None, + showexponent=None, + showgrid=None, + showline=None, + showspikes=None, + showticklabels=None, + showtickprefix=None, + showticksuffix=None, + side=None, + spikecolor=None, + spikedash=None, + spikemode=None, + spikesnap=None, + spikethickness=None, + tick0=None, + tickangle=None, + tickcolor=None, + tickfont=None, + tickformat=None, + tickformatstops=None, + tickformatstopdefaults=None, + ticklabelindex=None, + ticklabelindexsrc=None, + ticklabelmode=None, + ticklabeloverflow=None, + ticklabelposition=None, + ticklabelshift=None, + ticklabelstandoff=None, + ticklabelstep=None, + ticklen=None, + tickmode=None, + tickprefix=None, + ticks=None, + tickson=None, + ticksuffix=None, + ticktext=None, + ticktextsrc=None, + tickvals=None, + tickvalssrc=None, + tickwidth=None, + title=None, + type=None, + uirevision=None, + unifiedhovertitle=None, + visible=None, + zeroline=None, + zerolinecolor=None, + zerolinelayer=None, + zerolinewidth=None, + **kwargs, + ): + """ + Construct a new YAxis object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.layout.YAxis` + anchor + If set to an opposite-letter axis id (e.g. `x2`, `y`), + this axis is bound to the corresponding opposite-letter + axis. If set to "free", this axis' position is + determined by `position`. + automargin + Determines whether long tick labels automatically grow + the figure margins. + autorange + Determines whether or not the range of this axis is + computed in relation to the input data. See `rangemode` + for more info. If `range` is provided and it has a + value for both the lower and upper bound, `autorange` + is set to False. Using "min" applies autorange only to + set the minimum. Using "max" applies autorange only to + set the maximum. Using *min reversed* applies autorange + only to set the minimum on a reversed axis. Using *max + reversed* applies autorange only to set the maximum on + a reversed axis. Using "reversed" applies autorange on + both ends and reverses the axis direction. + autorangeoptions + :class:`plotly.graph_objects.layout.yaxis.Autorangeopti + ons` instance or dict with compatible properties + autoshift + Automatically reposition the axis to avoid overlap with + other axes with the same `overlaying` value. This + repositioning will account for any `shift` amount + applied to other axes on the same side with `autoshift` + is set to true. Only has an effect if `anchor` is set + to "free". + autotickangles + When `tickangle` is set to "auto", it will be set to + the first angle in this array that is large enough to + prevent label overlap. + autotypenumbers + Using "strict" a numeric string in trace data is not + converted to a number. Using *convert types* a numeric + string in trace data may be treated as a number during + automatic axis `type` detection. Defaults to + layout.autotypenumbers. + calendar + Sets the calendar system to use for `range` and `tick0` + if this is a date axis. This does not set the calendar + for interpreting data on this axis, that's specified in + the trace or via the global `layout.calendar` + categoryarray + Sets the order in which categories on this axis appear. + Only has an effect if `categoryorder` is set to + "array". Used with `categoryorder`. + categoryarraysrc + Sets the source reference on Chart Studio Cloud for + `categoryarray`. + categoryorder + Specifies the ordering logic for the case of + categorical variables. By default, plotly uses "trace", + which specifies the order that is present in the data + supplied. Set `categoryorder` to *category ascending* + or *category descending* if order should be determined + by the alphanumerical order of the category names. Set + `categoryorder` to "array" to derive the ordering from + the attribute `categoryarray`. If a category is not + found in the `categoryarray` array, the sorting + behavior for that attribute will be identical to the + "trace" mode. The unspecified categories will follow + the categories in `categoryarray`. Set `categoryorder` + to *total ascending* or *total descending* if order + should be determined by the numerical order of the + values. Similarly, the order can be determined by the + min, max, sum, mean, geometric mean or median of all + the values. + color + Sets default for all colors associated with this axis + all at once: line, font, tick, and grid colors. Grid + color is lightened by blending this with the plot + background Individual pieces can override this. + constrain + If this axis needs to be compressed (either due to its + own `scaleanchor` and `scaleratio` or those of the + other axis), determines how that happens: by increasing + the "range", or by decreasing the "domain". Default is + "domain" for axes containing image traces, "range" + otherwise. + constraintoward + If this axis needs to be compressed (either due to its + own `scaleanchor` and `scaleratio` or those of the + other axis), determines which direction we push the + originally specified plot area. Options are "left", + "center" (default), and "right" for x axes, and "top", + "middle" (default), and "bottom" for y axes. + dividercolor + Sets the color of the dividers Only has an effect on + "multicategory" axes. + dividerwidth + Sets the width (in px) of the dividers Only has an + effect on "multicategory" axes. + domain + Sets the domain of this axis (in plot fraction). + dtick + Sets the step in-between ticks on this axis. Use with + `tick0`. Must be a positive number, or special strings + available to "log" and "date" axes. If the axis `type` + is "log", then ticks are set every 10^(n*dtick) where n + is the tick number. For example, to set a tick mark at + 1, 10, 100, 1000, ... set dtick to 1. To set tick marks + at 1, 100, 10000, ... set dtick to 2. To set tick marks + at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special + values; "L", where `f` is a positive number, gives + ticks linearly spaced in value (but not position). For + example `tick0` = 0.1, `dtick` = "L0.5" will put ticks + at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus + small digits between, use "D1" (all digits) or "D2" + (only 2 and 5). `tick0` is ignored for "D1" and "D2". + If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval + between ticks to one day, set `dtick` to 86400000.0. + "date" also has special values "M" gives ticks + spaced by a number of months. `n` must be a positive + integer. To set ticks on the 15th of every third month, + set `tick0` to "2000-01-15" and `dtick` to "M3". To set + ticks every 4 years, set `dtick` to "M48" + exponentformat + Determines a formatting rule for the tick exponents. + For example, consider the number 1,000,000,000. If + "none", it appears as 1,000,000,000. If "e", 1e+9. If + "E", 1E+9. If "power", 1x10^9 (with 9 in a super + script). If "SI", 1G. If "B", 1B. "SI" uses prefixes + from "femto" f (10^-15) to "tera" T (10^12). *SI + extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or + *SI extended* is used and the exponent is beyond the + above ranges, the formatting rule will automatically be + switched to the power notation. + fixedrange + Determines whether or not this axis is zoom-able. If + true, then zoom is disabled. + gridcolor + Sets the color of the grid lines. + griddash + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + gridwidth + Sets the width (in px) of the grid lines. + hoverformat + Sets the hover text formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + insiderange + Could be used to set the desired inside range of this + axis (excluding the labels) when `ticklabelposition` of + the anchored axis has "inside". Not implemented for + axes with `type` "log". This would be ignored when + `range` is provided. + labelalias + Replacement text for specific tick or hover labels. For + example using {US: 'USA', CA: 'Canada'} changes US to + USA and CA to Canada. The labels we would have shown + must match the keys exactly, after adding any + tickprefix or ticksuffix. For negative numbers the + minus sign symbol used (U+2212) is wider than the + regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis + type, and both keys (if needed) and values (if desired) + can include html-like tags or MathJax. + layer + Sets the layer on which this axis is displayed. If + *above traces*, this axis is displayed above all the + subplot's traces If *below traces*, this axis is + displayed below all the subplot's traces, but above the + grid lines. Useful when used together with scatter-like + traces with `cliponaxis` set to False to show markers + and/or text nodes above this axis. + linecolor + Sets the axis line color. + linewidth + Sets the width (in px) of the axis line. + matches + If set to another axis id (e.g. `x2`, `y`), the range + of this axis will match the range of the corresponding + axis in data-coordinates space. Moreover, matching axes + share auto-range values, category lists and histogram + auto-bins. Note that setting axes simultaneously in + both a `scaleanchor` and a `matches` constraint is + currently forbidden. Moreover, note that matching axes + must have the same `type`. + maxallowed + Determines the maximum range of this axis. + minallowed + Determines the minimum range of this axis. + minexponent + Hide SI prefix for 10^n if |n| is below this number. + This only has an effect when `tickformat` is "SI" or + "B". + minor + :class:`plotly.graph_objects.layout.yaxis.Minor` + instance or dict with compatible properties + minorloglabels + Determines how minor log labels are displayed. If + *small digits*, small digits i.e. 2 or 5 are displayed. + If "complete", complete digits are displayed. If + "none", no labels are displayed. + mirror + Determines if the axis lines or/and ticks are mirrored + to the opposite side of the plotting area. If True, the + axis lines are mirrored. If "ticks", the axis lines and + ticks are mirrored. If False, mirroring is disable. If + "all", axis lines are mirrored on all shared-axes + subplots. If "allticks", axis lines and ticks are + mirrored on all shared-axes subplots. + modebardisable + Disables certain modebar buttons for this axis. + "autoscale" disables the autoscale buttons, "zoominout" + disables the zoom-in and zoom-out buttons. + nticks + Specifies the maximum number of ticks for the + particular axis. The actual number of ticks will be + chosen automatically to be less than or equal to + `nticks`. Has an effect only if `tickmode` is set to + "auto". + overlaying + If set a same-letter axis id, this axis is overlaid on + top of the corresponding same-letter axis, with traces + and axes visible for both axes. If False, this axis + does not overlay any same-letter axes. In this case, + for axes with overlapping domains only the highest- + numbered axis will be visible. + position + Sets the position of this axis in the plotting space + (in normalized coordinates). Only has an effect if + `anchor` is set to "free". + range + Sets the range of this axis. If the axis `type` is + "log", then you must take the log of your desired range + (e.g. to set the range from 1 to 100, set the range + from 0 to 2). If the axis `type` is "date", it should + be date strings, like date data, though Date objects + and unix milliseconds will be accepted and converted to + strings. If the axis `type` is "category", it should be + numbers, using the scale where each category is + assigned a serial number from zero in the order it + appears. Leaving either or both elements `null` impacts + the default `autorange`. + rangebreaks + A tuple of + :class:`plotly.graph_objects.layout.yaxis.Rangebreak` + instances or dicts with compatible properties + rangebreakdefaults + When used in a template (as + layout.template.layout.yaxis.rangebreakdefaults), sets + the default property values to use for elements of + layout.yaxis.rangebreaks + rangemode + If "normal", the range is computed in relation to the + extrema of the input data. If "tozero", the range + extends to 0, regardless of the input data If + "nonnegative", the range is non-negative, regardless of + the input data. Applies only to linear axes. + scaleanchor + If set to another axis id (e.g. `x2`, `y`), the range + of this axis changes together with the range of the + corresponding axis such that the scale of pixels per + unit is in a constant ratio. Both axes are still + zoomable, but when you zoom one, the other will zoom + the same amount, keeping a fixed midpoint. `constrain` + and `constraintoward` determine how we enforce the + constraint. You can chain these, ie `yaxis: + {scaleanchor: *x*}, xaxis2: {scaleanchor: *y*}` but you + can only link axes of the same `type`. The linked axis + can have the opposite letter (to constrain the aspect + ratio) or the same letter (to match scales across + subplots). Loops (`yaxis: {scaleanchor: *x*}, xaxis: + {scaleanchor: *y*}` or longer) are redundant and the + last constraint encountered will be ignored to avoid + possible inconsistent constraints via `scaleratio`. + Note that setting axes simultaneously in both a + `scaleanchor` and a `matches` constraint is currently + forbidden. Setting `false` allows to remove a default + constraint (occasionally, you may need to prevent a + default `scaleanchor` constraint from being applied, + eg. when having an image trace `yaxis: {scaleanchor: + "x"}` is set automatically in order for pixels to be + rendered as squares, setting `yaxis: {scaleanchor: + false}` allows to remove the constraint). + scaleratio + If this axis is linked to another by `scaleanchor`, + this determines the pixel to unit scale ratio. For + example, if this value is 10, then every unit on this + axis spans 10 times the number of pixels as a unit on + the linked axis. Use this for example to create an + elevation profile where the vertical scale is + exaggerated a fixed amount with respect to the + horizontal. + separatethousands + If "true", even 4-digit integers are separated + shift + Moves the axis a given number of pixels from where it + would have been otherwise. Accepts both positive and + negative values, which will shift the axis either right + or left, respectively. If `autoshift` is set to true, + then this defaults to a padding of -3 if `side` is set + to "left". and defaults to +3 if `side` is set to + "right". Defaults to 0 if `autoshift` is set to false. + Only has an effect if `anchor` is set to "free". + showdividers + Determines whether or not a dividers are drawn between + the category levels of this axis. Only has an effect on + "multicategory" axes. + showexponent + If "all", all exponents are shown besides their + significands. If "first", only the exponent of the + first tick is shown. If "last", only the exponent of + the last tick is shown. If "none", no exponents appear. + showgrid + Determines whether or not grid lines are drawn. If + True, the grid lines are drawn at every tick mark. + showline + Determines whether or not a line bounding this axis is + drawn. + showspikes + Determines whether or not spikes (aka droplines) are + drawn for this axis. Note: This only takes affect when + hovermode = closest + showticklabels + Determines whether or not the tick labels are drawn. + showtickprefix + If "all", all tick labels are displayed with a prefix. + If "first", only the first tick is displayed with a + prefix. If "last", only the last tick is displayed with + a suffix. If "none", tick prefixes are hidden. + showticksuffix + Same as `showtickprefix` but for tick suffixes. + side + Determines whether a x (y) axis is positioned at the + "bottom" ("left") or "top" ("right") of the plotting + area. + spikecolor + Sets the spike color. If undefined, will use the series + color + spikedash + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + spikemode + Determines the drawing mode for the spike line If + "toaxis", the line is drawn from the data point to the + axis the series is plotted on. If "across", the line + is drawn across the entire plot area, and supercedes + "toaxis". If "marker", then a marker dot is drawn on + the axis the series is plotted on + spikesnap + Determines whether spikelines are stuck to the cursor + or to the closest datapoints. + spikethickness + Sets the width (in px) of the zero line. + tick0 + Sets the placement of the first tick on this axis. Use + with `dtick`. If the axis `type` is "log", then you + must take the log of your starting tick (e.g. to set + the starting tick to 100, set the `tick0` to 2) except + when `dtick`=*L* (see `dtick` for more info). If the + axis `type` is "date", it should be a date string, like + date data. If the axis `type` is "category", it should + be a number, using the scale where each category is + assigned a serial number from zero in the order it + appears. + tickangle + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + tick labels vertically. + tickcolor + Sets the tick color. + tickfont + Sets the tick font. + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + tickformatstops + A tuple of :class:`plotly.graph_objects.layout.yaxis.Ti + ckformatstop` instances or dicts with compatible + properties + tickformatstopdefaults + When used in a template (as + layout.template.layout.yaxis.tickformatstopdefaults), + sets the default property values to use for elements of + layout.yaxis.tickformatstops + ticklabelindex + Only for axes with `type` "date" or "linear". Instead + of drawing the major tick label, draw the label for the + minor tick that is n positions away from the major + tick. E.g. to always draw the label for the minor tick + before each major tick, choose `ticklabelindex` -1. + This is useful for date axes with `ticklabelmode` + "period" if you want to label the period that ends with + each major tick instead of the period that begins + there. + ticklabelindexsrc + Sets the source reference on Chart Studio Cloud for + `ticklabelindex`. + ticklabelmode + Determines where tick labels are drawn with respect to + their corresponding ticks and grid lines. Only has an + effect for axes of `type` "date" When set to "period", + tick labels are drawn in the middle of the period + between ticks. + ticklabeloverflow + Determines how we handle tick labels that would + overflow either the graph div or the domain of the + axis. The default value for inside tick labels is *hide + past domain*. Otherwise on "category" and + "multicategory" axes the default is "allow". In other + cases the default is *hide past div*. + ticklabelposition + Determines where tick labels are drawn with respect to + the axis. Please note that top or bottom has no effect + on x axes or when `ticklabelmode` is set to "period" or + when `tickson` is set to "boundaries". Similarly, left + or right has no effect on y axes or when + `ticklabelmode` is set to "period" or when `tickson` is + set to "boundaries". Has no effect on "multicategory" + axes. When used on axes linked by `matches` or + `scaleanchor`, no extra padding for inside labels would + be added by autorange, so that the scales could match. + ticklabelshift + Shifts the tick labels by the specified number of + pixels in parallel to the axis. Positive values move + the labels in the positive direction of the axis. + ticklabelstandoff + Sets the standoff distance (in px) between the axis + tick labels and their default position. A positive + `ticklabelstandoff` moves the labels farther away from + the plot area if `ticklabelposition` is "outside", and + deeper into the plot area if `ticklabelposition` is + "inside". A negative `ticklabelstandoff` works in the + opposite direction, moving outside ticks towards the + plot area and inside ticks towards the outside. If the + negative value is large enough, inside ticks can even + end up outside and vice versa. + ticklabelstep + Sets the spacing between tick labels as compared to the + spacing between ticks. A value of 1 (default) means + each tick gets a label. A value of 2 means shows every + 2nd label. A larger value n means only every nth tick + is labeled. `tick0` determines which labels are shown. + Not implemented for axes with `type` "log" or + "multicategory", or when `tickmode` is "array". + ticklen + Sets the tick length (in px). + tickmode + Sets the tick mode for this axis. If "auto", the number + of ticks is set via `nticks`. If "linear", the + placement of the ticks is determined by a starting + position `tick0` and a tick step `dtick` ("linear" is + the default value if `tick0` and `dtick` are provided). + If "array", the placement of the ticks is set via + `tickvals` and the tick text is `ticktext`. ("array" is + the default value if `tickvals` is provided). If + "sync", the number of ticks will sync with the + overlayed axis set by `overlaying` property. + tickprefix + Sets a tick label prefix. + ticks + Determines whether ticks are drawn or not. If "", this + axis' ticks are not drawn. If "outside" ("inside"), + this axis' are drawn outside (inside) the axis lines. + tickson + Determines where ticks and grid lines are drawn with + respect to their corresponding tick labels. Only has an + effect for axes of `type` "category" or + "multicategory". When set to "boundaries", ticks and + grid lines are drawn half a category to the left/bottom + of labels. + ticksuffix + Sets a tick label suffix. + ticktext + Sets the text displayed at the ticks position via + `tickvals`. Only has an effect if `tickmode` is set to + "array". Used with `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + Only has an effect if `tickmode` is set to "array". + Used with `ticktext`. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + tickwidth + Sets the tick width (in px). + title + :class:`plotly.graph_objects.layout.yaxis.Title` + instance or dict with compatible properties + type + Sets the axis type. By default, plotly attempts to + determined the axis type by looking into the data of + the traces that referenced the axis in question. + uirevision + Controls persistence of user-driven changes in axis + `range`, `autorange`, and `title` if in `editable: + true` configuration. Defaults to `layout.uirevision`. + unifiedhovertitle + :class:`plotly.graph_objects.layout.yaxis.Unifiedhovert + itle` instance or dict with compatible properties + visible + A single toggle to hide the axis while preserving + interaction like dragging. Default is true when a + cheater plot is present on the axis, otherwise false + zeroline + Determines whether or not a line is drawn at along the + 0 value of this axis. If True, the zero line is drawn + on top of the grid lines. + zerolinecolor + Sets the line color of the zero line. + zerolinelayer + Sets the layer on which this zeroline is displayed. If + *above traces*, this zeroline is displayed above all + the subplot's traces If *below traces*, this zeroline + is displayed below all the subplot's traces, but above + the grid lines. Limitation: "zerolinelayer" currently + has no effect if the "zorder" property is set on any + trace. + zerolinewidth + Sets the width (in px) of the zero line. + + Returns + ------- + YAxis + """ + super().__init__("yaxis") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.layout.YAxis +constructor must be a dict or +an instance of :class:`plotly.graph_objs.layout.YAxis`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("anchor", arg, anchor) + self._set_property("automargin", arg, automargin) + self._set_property("autorange", arg, autorange) + self._set_property("autorangeoptions", arg, autorangeoptions) + self._set_property("autoshift", arg, autoshift) + self._set_property("autotickangles", arg, autotickangles) + self._set_property("autotypenumbers", arg, autotypenumbers) + self._set_property("calendar", arg, calendar) + self._set_property("categoryarray", arg, categoryarray) + self._set_property("categoryarraysrc", arg, categoryarraysrc) + self._set_property("categoryorder", arg, categoryorder) + self._set_property("color", arg, color) + self._set_property("constrain", arg, constrain) + self._set_property("constraintoward", arg, constraintoward) + self._set_property("dividercolor", arg, dividercolor) + self._set_property("dividerwidth", arg, dividerwidth) + self._set_property("domain", arg, domain) + self._set_property("dtick", arg, dtick) + self._set_property("exponentformat", arg, exponentformat) + self._set_property("fixedrange", arg, fixedrange) + self._set_property("gridcolor", arg, gridcolor) + self._set_property("griddash", arg, griddash) + self._set_property("gridwidth", arg, gridwidth) + self._set_property("hoverformat", arg, hoverformat) + self._set_property("insiderange", arg, insiderange) + self._set_property("labelalias", arg, labelalias) + self._set_property("layer", arg, layer) + self._set_property("linecolor", arg, linecolor) + self._set_property("linewidth", arg, linewidth) + self._set_property("matches", arg, matches) + self._set_property("maxallowed", arg, maxallowed) + self._set_property("minallowed", arg, minallowed) + self._set_property("minexponent", arg, minexponent) + self._set_property("minor", arg, minor) + self._set_property("minorloglabels", arg, minorloglabels) + self._set_property("mirror", arg, mirror) + self._set_property("modebardisable", arg, modebardisable) + self._set_property("nticks", arg, nticks) + self._set_property("overlaying", arg, overlaying) + self._set_property("position", arg, position) + self._set_property("range", arg, range) + self._set_property("rangebreaks", arg, rangebreaks) + self._set_property("rangebreakdefaults", arg, rangebreakdefaults) + self._set_property("rangemode", arg, rangemode) + self._set_property("scaleanchor", arg, scaleanchor) + self._set_property("scaleratio", arg, scaleratio) + self._set_property("separatethousands", arg, separatethousands) + self._set_property("shift", arg, shift) + self._set_property("showdividers", arg, showdividers) + self._set_property("showexponent", arg, showexponent) + self._set_property("showgrid", arg, showgrid) + self._set_property("showline", arg, showline) + self._set_property("showspikes", arg, showspikes) + self._set_property("showticklabels", arg, showticklabels) + self._set_property("showtickprefix", arg, showtickprefix) + self._set_property("showticksuffix", arg, showticksuffix) + self._set_property("side", arg, side) + self._set_property("spikecolor", arg, spikecolor) + self._set_property("spikedash", arg, spikedash) + self._set_property("spikemode", arg, spikemode) + self._set_property("spikesnap", arg, spikesnap) + self._set_property("spikethickness", arg, spikethickness) + self._set_property("tick0", arg, tick0) + self._set_property("tickangle", arg, tickangle) + self._set_property("tickcolor", arg, tickcolor) + self._set_property("tickfont", arg, tickfont) + self._set_property("tickformat", arg, tickformat) + self._set_property("tickformatstops", arg, tickformatstops) + self._set_property("tickformatstopdefaults", arg, tickformatstopdefaults) + self._set_property("ticklabelindex", arg, ticklabelindex) + self._set_property("ticklabelindexsrc", arg, ticklabelindexsrc) + self._set_property("ticklabelmode", arg, ticklabelmode) + self._set_property("ticklabeloverflow", arg, ticklabeloverflow) + self._set_property("ticklabelposition", arg, ticklabelposition) + self._set_property("ticklabelshift", arg, ticklabelshift) + self._set_property("ticklabelstandoff", arg, ticklabelstandoff) + self._set_property("ticklabelstep", arg, ticklabelstep) + self._set_property("ticklen", arg, ticklen) + self._set_property("tickmode", arg, tickmode) + self._set_property("tickprefix", arg, tickprefix) + self._set_property("ticks", arg, ticks) + self._set_property("tickson", arg, tickson) + self._set_property("ticksuffix", arg, ticksuffix) + self._set_property("ticktext", arg, ticktext) + self._set_property("ticktextsrc", arg, ticktextsrc) + self._set_property("tickvals", arg, tickvals) + self._set_property("tickvalssrc", arg, tickvalssrc) + self._set_property("tickwidth", arg, tickwidth) + self._set_property("title", arg, title) + self._set_property("type", arg, type) + self._set_property("uirevision", arg, uirevision) + self._set_property("unifiedhovertitle", arg, unifiedhovertitle) + self._set_property("visible", arg, visible) + self._set_property("zeroline", arg, zeroline) + self._set_property("zerolinecolor", arg, zerolinecolor) + self._set_property("zerolinelayer", arg, zerolinelayer) + self._set_property("zerolinewidth", arg, zerolinewidth) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..b818b1a4607f7e650b9fe8effc5552ae1d42874f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/__init__.py @@ -0,0 +1,30 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._colorbar import ColorBar + from ._contour import Contour + from ._hoverlabel import Hoverlabel + from ._legendgrouptitle import Legendgrouptitle + from ._lighting import Lighting + from ._lightposition import Lightposition + from ._stream import Stream + from . import colorbar + from . import hoverlabel + from . import legendgrouptitle +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [".colorbar", ".hoverlabel", ".legendgrouptitle"], + [ + "._colorbar.ColorBar", + "._contour.Contour", + "._hoverlabel.Hoverlabel", + "._legendgrouptitle.Legendgrouptitle", + "._lighting.Lighting", + "._lightposition.Lightposition", + "._stream.Stream", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_colorbar.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_colorbar.py new file mode 100644 index 0000000000000000000000000000000000000000..8803871da67897ec18c653f90280937aed545707 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_colorbar.py @@ -0,0 +1,1739 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class ColorBar(_BaseTraceHierarchyType): + _parent_path_str = "mesh3d" + _path_str = "mesh3d.colorbar" + _valid_props = { + "bgcolor", + "bordercolor", + "borderwidth", + "dtick", + "exponentformat", + "labelalias", + "len", + "lenmode", + "minexponent", + "nticks", + "orientation", + "outlinecolor", + "outlinewidth", + "separatethousands", + "showexponent", + "showticklabels", + "showtickprefix", + "showticksuffix", + "thickness", + "thicknessmode", + "tick0", + "tickangle", + "tickcolor", + "tickfont", + "tickformat", + "tickformatstopdefaults", + "tickformatstops", + "ticklabeloverflow", + "ticklabelposition", + "ticklabelstep", + "ticklen", + "tickmode", + "tickprefix", + "ticks", + "ticksuffix", + "ticktext", + "ticktextsrc", + "tickvals", + "tickvalssrc", + "tickwidth", + "title", + "x", + "xanchor", + "xpad", + "xref", + "y", + "yanchor", + "ypad", + "yref", + } + + @property + def bgcolor(self): + """ + Sets the color of padded area. + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bordercolor(self): + """ + Sets the axis line color. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def borderwidth(self): + """ + Sets the width (in px) or the border enclosing this color bar. + + The 'borderwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["borderwidth"] + + @borderwidth.setter + def borderwidth(self, val): + self["borderwidth"] = val + + @property + def dtick(self): + """ + Sets the step in-between ticks on this axis. Use with `tick0`. + Must be a positive number, or special strings available to + "log" and "date" axes. If the axis `type` is "log", then ticks + are set every 10^(n*dtick) where n is the tick number. For + example, to set a tick mark at 1, 10, 100, 1000, ... set dtick + to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. + To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special values; + "L", where `f` is a positive number, gives ticks linearly + spaced in value (but not position). For example `tick0` = 0.1, + `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To + show powers of 10 plus small digits between, use "D1" (all + digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and + "D2". If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval between + ticks to one day, set `dtick` to 86400000.0. "date" also has + special values "M" gives ticks spaced by a number of months. + `n` must be a positive integer. To set ticks on the 15th of + every third month, set `tick0` to "2000-01-15" and `dtick` to + "M3". To set ticks every 4 years, set `dtick` to "M48" + + The 'dtick' property accepts values of any type + + Returns + ------- + Any + """ + return self["dtick"] + + @dtick.setter + def dtick(self, val): + self["dtick"] = val + + @property + def exponentformat(self): + """ + Determines a formatting rule for the tick exponents. For + example, consider the number 1,000,000,000. If "none", it + appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If + "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If + "B", 1B. "SI" uses prefixes from "femto" f (10^-15) to "tera" T + (10^12). *SI extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or *SI + extended* is used and the exponent is beyond the above ranges, + the formatting rule will automatically be switched to the power + notation. + + The 'exponentformat' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'e', 'E', 'power', 'SI', 'B', 'SI extended'] + + Returns + ------- + Any + """ + return self["exponentformat"] + + @exponentformat.setter + def exponentformat(self, val): + self["exponentformat"] = val + + @property + def labelalias(self): + """ + Replacement text for specific tick or hover labels. For example + using {US: 'USA', CA: 'Canada'} changes US to USA and CA to + Canada. The labels we would have shown must match the keys + exactly, after adding any tickprefix or ticksuffix. For + negative numbers the minus sign symbol used (U+2212) is wider + than the regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis type, and + both keys (if needed) and values (if desired) can include html- + like tags or MathJax. + + The 'labelalias' property accepts values of any type + + Returns + ------- + Any + """ + return self["labelalias"] + + @labelalias.setter + def labelalias(self, val): + self["labelalias"] = val + + @property + def len(self): + """ + Sets the length of the color bar This measure excludes the + padding of both ends. That is, the color bar length is this + length minus the padding on both ends. + + The 'len' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["len"] + + @len.setter + def len(self, val): + self["len"] = val + + @property + def lenmode(self): + """ + Determines whether this color bar's length (i.e. the measure in + the color variation direction) is set in units of plot + "fraction" or in *pixels. Use `len` to set the value. + + The 'lenmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fraction', 'pixels'] + + Returns + ------- + Any + """ + return self["lenmode"] + + @lenmode.setter + def lenmode(self, val): + self["lenmode"] = val + + @property + def minexponent(self): + """ + Hide SI prefix for 10^n if |n| is below this number. This only + has an effect when `tickformat` is "SI" or "B". + + The 'minexponent' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["minexponent"] + + @minexponent.setter + def minexponent(self, val): + self["minexponent"] = val + + @property + def nticks(self): + """ + Specifies the maximum number of ticks for the particular axis. + The actual number of ticks will be chosen automatically to be + less than or equal to `nticks`. Has an effect only if + `tickmode` is set to "auto". + + The 'nticks' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["nticks"] + + @nticks.setter + def nticks(self, val): + self["nticks"] = val + + @property + def orientation(self): + """ + Sets the orientation of the colorbar. + + The 'orientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['h', 'v'] + + Returns + ------- + Any + """ + return self["orientation"] + + @orientation.setter + def orientation(self, val): + self["orientation"] = val + + @property + def outlinecolor(self): + """ + Sets the axis line color. + + The 'outlinecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["outlinecolor"] + + @outlinecolor.setter + def outlinecolor(self, val): + self["outlinecolor"] = val + + @property + def outlinewidth(self): + """ + Sets the width (in px) of the axis line. + + The 'outlinewidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["outlinewidth"] + + @outlinewidth.setter + def outlinewidth(self, val): + self["outlinewidth"] = val + + @property + def separatethousands(self): + """ + If "true", even 4-digit integers are separated + + The 'separatethousands' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["separatethousands"] + + @separatethousands.setter + def separatethousands(self, val): + self["separatethousands"] = val + + @property + def showexponent(self): + """ + If "all", all exponents are shown besides their significands. + If "first", only the exponent of the first tick is shown. If + "last", only the exponent of the last tick is shown. If "none", + no exponents appear. + + The 'showexponent' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showexponent"] + + @showexponent.setter + def showexponent(self, val): + self["showexponent"] = val + + @property + def showticklabels(self): + """ + Determines whether or not the tick labels are drawn. + + The 'showticklabels' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showticklabels"] + + @showticklabels.setter + def showticklabels(self, val): + self["showticklabels"] = val + + @property + def showtickprefix(self): + """ + If "all", all tick labels are displayed with a prefix. If + "first", only the first tick is displayed with a prefix. If + "last", only the last tick is displayed with a suffix. If + "none", tick prefixes are hidden. + + The 'showtickprefix' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showtickprefix"] + + @showtickprefix.setter + def showtickprefix(self, val): + self["showtickprefix"] = val + + @property + def showticksuffix(self): + """ + Same as `showtickprefix` but for tick suffixes. + + The 'showticksuffix' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showticksuffix"] + + @showticksuffix.setter + def showticksuffix(self, val): + self["showticksuffix"] = val + + @property + def thickness(self): + """ + Sets the thickness of the color bar This measure excludes the + size of the padding, ticks and labels. + + The 'thickness' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["thickness"] + + @thickness.setter + def thickness(self, val): + self["thickness"] = val + + @property + def thicknessmode(self): + """ + Determines whether this color bar's thickness (i.e. the measure + in the constant color direction) is set in units of plot + "fraction" or in "pixels". Use `thickness` to set the value. + + The 'thicknessmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fraction', 'pixels'] + + Returns + ------- + Any + """ + return self["thicknessmode"] + + @thicknessmode.setter + def thicknessmode(self, val): + self["thicknessmode"] = val + + @property + def tick0(self): + """ + Sets the placement of the first tick on this axis. Use with + `dtick`. If the axis `type` is "log", then you must take the + log of your starting tick (e.g. to set the starting tick to + 100, set the `tick0` to 2) except when `dtick`=*L* (see + `dtick` for more info). If the axis `type` is "date", it should + be a date string, like date data. If the axis `type` is + "category", it should be a number, using the scale where each + category is assigned a serial number from zero in the order it + appears. + + The 'tick0' property accepts values of any type + + Returns + ------- + Any + """ + return self["tick0"] + + @tick0.setter + def tick0(self, val): + self["tick0"] = val + + @property + def tickangle(self): + """ + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the tick + labels vertically. + + The 'tickangle' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["tickangle"] + + @tickangle.setter + def tickangle(self, val): + self["tickangle"] = val + + @property + def tickcolor(self): + """ + Sets the tick color. + + The 'tickcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["tickcolor"] + + @tickcolor.setter + def tickcolor(self, val): + self["tickcolor"] = val + + @property + def tickfont(self): + """ + Sets the color bar's tick label font + + The 'tickfont' property is an instance of Tickfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.mesh3d.colorbar.Tickfont` + - A dict of string/value properties that will be passed + to the Tickfont constructor + + Returns + ------- + plotly.graph_objs.mesh3d.colorbar.Tickfont + """ + return self["tickfont"] + + @tickfont.setter + def tickfont(self, val): + self["tickfont"] = val + + @property + def tickformat(self): + """ + Sets the tick label formatting rule using d3 formatting mini- + languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display "09~15~23.46" + + The 'tickformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["tickformat"] + + @tickformat.setter + def tickformat(self, val): + self["tickformat"] = val + + @property + def tickformatstops(self): + """ + The 'tickformatstops' property is a tuple of instances of + Tickformatstop that may be specified as: + - A list or tuple of instances of plotly.graph_objs.mesh3d.colorbar.Tickformatstop + - A list or tuple of dicts of string/value properties that + will be passed to the Tickformatstop constructor + + Returns + ------- + tuple[plotly.graph_objs.mesh3d.colorbar.Tickformatstop] + """ + return self["tickformatstops"] + + @tickformatstops.setter + def tickformatstops(self, val): + self["tickformatstops"] = val + + @property + def tickformatstopdefaults(self): + """ + When used in a template (as + layout.template.data.mesh3d.colorbar.tickformatstopdefaults), + sets the default property values to use for elements of + mesh3d.colorbar.tickformatstops + + The 'tickformatstopdefaults' property is an instance of Tickformatstop + that may be specified as: + - An instance of :class:`plotly.graph_objs.mesh3d.colorbar.Tickformatstop` + - A dict of string/value properties that will be passed + to the Tickformatstop constructor + + Returns + ------- + plotly.graph_objs.mesh3d.colorbar.Tickformatstop + """ + return self["tickformatstopdefaults"] + + @tickformatstopdefaults.setter + def tickformatstopdefaults(self, val): + self["tickformatstopdefaults"] = val + + @property + def ticklabeloverflow(self): + """ + Determines how we handle tick labels that would overflow either + the graph div or the domain of the axis. The default value for + inside tick labels is *hide past domain*. In other cases the + default is *hide past div*. + + The 'ticklabeloverflow' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['allow', 'hide past div', 'hide past domain'] + + Returns + ------- + Any + """ + return self["ticklabeloverflow"] + + @ticklabeloverflow.setter + def ticklabeloverflow(self, val): + self["ticklabeloverflow"] = val + + @property + def ticklabelposition(self): + """ + Determines where tick labels are drawn relative to the ticks. + Left and right options are used when `orientation` is "h", top + and bottom when `orientation` is "v". + + The 'ticklabelposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['outside', 'inside', 'outside top', 'inside top', + 'outside left', 'inside left', 'outside right', 'inside + right', 'outside bottom', 'inside bottom'] + + Returns + ------- + Any + """ + return self["ticklabelposition"] + + @ticklabelposition.setter + def ticklabelposition(self, val): + self["ticklabelposition"] = val + + @property + def ticklabelstep(self): + """ + Sets the spacing between tick labels as compared to the spacing + between ticks. A value of 1 (default) means each tick gets a + label. A value of 2 means shows every 2nd label. A larger value + n means only every nth tick is labeled. `tick0` determines + which labels are shown. Not implemented for axes with `type` + "log" or "multicategory", or when `tickmode` is "array". + + The 'ticklabelstep' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 9223372036854775807] + + Returns + ------- + int + """ + return self["ticklabelstep"] + + @ticklabelstep.setter + def ticklabelstep(self, val): + self["ticklabelstep"] = val + + @property + def ticklen(self): + """ + Sets the tick length (in px). + + The 'ticklen' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["ticklen"] + + @ticklen.setter + def ticklen(self, val): + self["ticklen"] = val + + @property + def tickmode(self): + """ + Sets the tick mode for this axis. If "auto", the number of + ticks is set via `nticks`. If "linear", the placement of the + ticks is determined by a starting position `tick0` and a tick + step `dtick` ("linear" is the default value if `tick0` and + `dtick` are provided). If "array", the placement of the ticks + is set via `tickvals` and the tick text is `ticktext`. ("array" + is the default value if `tickvals` is provided). + + The 'tickmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'linear', 'array'] + + Returns + ------- + Any + """ + return self["tickmode"] + + @tickmode.setter + def tickmode(self, val): + self["tickmode"] = val + + @property + def tickprefix(self): + """ + Sets a tick label prefix. + + The 'tickprefix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["tickprefix"] + + @tickprefix.setter + def tickprefix(self, val): + self["tickprefix"] = val + + @property + def ticks(self): + """ + Determines whether ticks are drawn or not. If "", this axis' + ticks are not drawn. If "outside" ("inside"), this axis' are + drawn outside (inside) the axis lines. + + The 'ticks' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['outside', 'inside', ''] + + Returns + ------- + Any + """ + return self["ticks"] + + @ticks.setter + def ticks(self, val): + self["ticks"] = val + + @property + def ticksuffix(self): + """ + Sets a tick label suffix. + + The 'ticksuffix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["ticksuffix"] + + @ticksuffix.setter + def ticksuffix(self, val): + self["ticksuffix"] = val + + @property + def ticktext(self): + """ + Sets the text displayed at the ticks position via `tickvals`. + Only has an effect if `tickmode` is set to "array". Used with + `tickvals`. + + The 'ticktext' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ticktext"] + + @ticktext.setter + def ticktext(self, val): + self["ticktext"] = val + + @property + def ticktextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ticktext`. + + The 'ticktextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ticktextsrc"] + + @ticktextsrc.setter + def ticktextsrc(self, val): + self["ticktextsrc"] = val + + @property + def tickvals(self): + """ + Sets the values at which ticks on this axis appear. Only has an + effect if `tickmode` is set to "array". Used with `ticktext`. + + The 'tickvals' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["tickvals"] + + @tickvals.setter + def tickvals(self, val): + self["tickvals"] = val + + @property + def tickvalssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `tickvals`. + + The 'tickvalssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["tickvalssrc"] + + @tickvalssrc.setter + def tickvalssrc(self, val): + self["tickvalssrc"] = val + + @property + def tickwidth(self): + """ + Sets the tick width (in px). + + The 'tickwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["tickwidth"] + + @tickwidth.setter + def tickwidth(self, val): + self["tickwidth"] = val + + @property + def title(self): + """ + The 'title' property is an instance of Title + that may be specified as: + - An instance of :class:`plotly.graph_objs.mesh3d.colorbar.Title` + - A dict of string/value properties that will be passed + to the Title constructor + + Returns + ------- + plotly.graph_objs.mesh3d.colorbar.Title + """ + return self["title"] + + @title.setter + def title(self, val): + self["title"] = val + + @property + def x(self): + """ + Sets the x position with respect to `xref` of the color bar (in + plot fraction). When `xref` is "paper", defaults to 1.02 when + `orientation` is "v" and 0.5 when `orientation` is "h". When + `xref` is "container", defaults to 1 when `orientation` is "v" + and 0.5 when `orientation` is "h". Must be between 0 and 1 if + `xref` is "container" and between "-2" and 3 if `xref` is + "paper". + + The 'x' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xanchor(self): + """ + Sets this color bar's horizontal position anchor. This anchor + binds the `x` position to the "left", "center" or "right" of + the color bar. Defaults to "left" when `orientation` is "v" and + "center" when `orientation` is "h". + + The 'xanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'center', 'right'] + + Returns + ------- + Any + """ + return self["xanchor"] + + @xanchor.setter + def xanchor(self, val): + self["xanchor"] = val + + @property + def xpad(self): + """ + Sets the amount of padding (in px) along the x direction. + + The 'xpad' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["xpad"] + + @xpad.setter + def xpad(self, val): + self["xpad"] = val + + @property + def xref(self): + """ + Sets the container `x` refers to. "container" spans the entire + `width` of the plot. "paper" refers to the width of the + plotting area only. + + The 'xref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['container', 'paper'] + + Returns + ------- + Any + """ + return self["xref"] + + @xref.setter + def xref(self, val): + self["xref"] = val + + @property + def y(self): + """ + Sets the y position with respect to `yref` of the color bar (in + plot fraction). When `yref` is "paper", defaults to 0.5 when + `orientation` is "v" and 1.02 when `orientation` is "h". When + `yref` is "container", defaults to 0.5 when `orientation` is + "v" and 1 when `orientation` is "h". Must be between 0 and 1 if + `yref` is "container" and between "-2" and 3 if `yref` is + "paper". + + The 'y' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yanchor(self): + """ + Sets this color bar's vertical position anchor This anchor + binds the `y` position to the "top", "middle" or "bottom" of + the color bar. Defaults to "middle" when `orientation` is "v" + and "bottom" when `orientation` is "h". + + The 'yanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top', 'middle', 'bottom'] + + Returns + ------- + Any + """ + return self["yanchor"] + + @yanchor.setter + def yanchor(self, val): + self["yanchor"] = val + + @property + def ypad(self): + """ + Sets the amount of padding (in px) along the y direction. + + The 'ypad' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["ypad"] + + @ypad.setter + def ypad(self, val): + self["ypad"] = val + + @property + def yref(self): + """ + Sets the container `y` refers to. "container" spans the entire + `height` of the plot. "paper" refers to the height of the + plotting area only. + + The 'yref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['container', 'paper'] + + Returns + ------- + Any + """ + return self["yref"] + + @yref.setter + def yref(self, val): + self["yref"] = val + + @property + def _prop_descriptions(self): + return """\ + bgcolor + Sets the color of padded area. + bordercolor + Sets the axis line color. + borderwidth + Sets the width (in px) or the border enclosing this + color bar. + dtick + Sets the step in-between ticks on this axis. Use with + `tick0`. Must be a positive number, or special strings + available to "log" and "date" axes. If the axis `type` + is "log", then ticks are set every 10^(n*dtick) where n + is the tick number. For example, to set a tick mark at + 1, 10, 100, 1000, ... set dtick to 1. To set tick marks + at 1, 100, 10000, ... set dtick to 2. To set tick marks + at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special + values; "L", where `f` is a positive number, gives + ticks linearly spaced in value (but not position). For + example `tick0` = 0.1, `dtick` = "L0.5" will put ticks + at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus + small digits between, use "D1" (all digits) or "D2" + (only 2 and 5). `tick0` is ignored for "D1" and "D2". + If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval + between ticks to one day, set `dtick` to 86400000.0. + "date" also has special values "M" gives ticks + spaced by a number of months. `n` must be a positive + integer. To set ticks on the 15th of every third month, + set `tick0` to "2000-01-15" and `dtick` to "M3". To set + ticks every 4 years, set `dtick` to "M48" + exponentformat + Determines a formatting rule for the tick exponents. + For example, consider the number 1,000,000,000. If + "none", it appears as 1,000,000,000. If "e", 1e+9. If + "E", 1E+9. If "power", 1x10^9 (with 9 in a super + script). If "SI", 1G. If "B", 1B. "SI" uses prefixes + from "femto" f (10^-15) to "tera" T (10^12). *SI + extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or + *SI extended* is used and the exponent is beyond the + above ranges, the formatting rule will automatically be + switched to the power notation. + labelalias + Replacement text for specific tick or hover labels. For + example using {US: 'USA', CA: 'Canada'} changes US to + USA and CA to Canada. The labels we would have shown + must match the keys exactly, after adding any + tickprefix or ticksuffix. For negative numbers the + minus sign symbol used (U+2212) is wider than the + regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis + type, and both keys (if needed) and values (if desired) + can include html-like tags or MathJax. + len + Sets the length of the color bar This measure excludes + the padding of both ends. That is, the color bar length + is this length minus the padding on both ends. + lenmode + Determines whether this color bar's length (i.e. the + measure in the color variation direction) is set in + units of plot "fraction" or in *pixels. Use `len` to + set the value. + minexponent + Hide SI prefix for 10^n if |n| is below this number. + This only has an effect when `tickformat` is "SI" or + "B". + nticks + Specifies the maximum number of ticks for the + particular axis. The actual number of ticks will be + chosen automatically to be less than or equal to + `nticks`. Has an effect only if `tickmode` is set to + "auto". + orientation + Sets the orientation of the colorbar. + outlinecolor + Sets the axis line color. + outlinewidth + Sets the width (in px) of the axis line. + separatethousands + If "true", even 4-digit integers are separated + showexponent + If "all", all exponents are shown besides their + significands. If "first", only the exponent of the + first tick is shown. If "last", only the exponent of + the last tick is shown. If "none", no exponents appear. + showticklabels + Determines whether or not the tick labels are drawn. + showtickprefix + If "all", all tick labels are displayed with a prefix. + If "first", only the first tick is displayed with a + prefix. If "last", only the last tick is displayed with + a suffix. If "none", tick prefixes are hidden. + showticksuffix + Same as `showtickprefix` but for tick suffixes. + thickness + Sets the thickness of the color bar This measure + excludes the size of the padding, ticks and labels. + thicknessmode + Determines whether this color bar's thickness (i.e. the + measure in the constant color direction) is set in + units of plot "fraction" or in "pixels". Use + `thickness` to set the value. + tick0 + Sets the placement of the first tick on this axis. Use + with `dtick`. If the axis `type` is "log", then you + must take the log of your starting tick (e.g. to set + the starting tick to 100, set the `tick0` to 2) except + when `dtick`=*L* (see `dtick` for more info). If the + axis `type` is "date", it should be a date string, like + date data. If the axis `type` is "category", it should + be a number, using the scale where each category is + assigned a serial number from zero in the order it + appears. + tickangle + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + tick labels vertically. + tickcolor + Sets the tick color. + tickfont + Sets the color bar's tick label font + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + tickformatstops + A tuple of :class:`plotly.graph_objects.mesh3d.colorbar + .Tickformatstop` instances or dicts with compatible + properties + tickformatstopdefaults + When used in a template (as layout.template.data.mesh3d + .colorbar.tickformatstopdefaults), sets the default + property values to use for elements of + mesh3d.colorbar.tickformatstops + ticklabeloverflow + Determines how we handle tick labels that would + overflow either the graph div or the domain of the + axis. The default value for inside tick labels is *hide + past domain*. In other cases the default is *hide past + div*. + ticklabelposition + Determines where tick labels are drawn relative to the + ticks. Left and right options are used when + `orientation` is "h", top and bottom when `orientation` + is "v". + ticklabelstep + Sets the spacing between tick labels as compared to the + spacing between ticks. A value of 1 (default) means + each tick gets a label. A value of 2 means shows every + 2nd label. A larger value n means only every nth tick + is labeled. `tick0` determines which labels are shown. + Not implemented for axes with `type` "log" or + "multicategory", or when `tickmode` is "array". + ticklen + Sets the tick length (in px). + tickmode + Sets the tick mode for this axis. If "auto", the number + of ticks is set via `nticks`. If "linear", the + placement of the ticks is determined by a starting + position `tick0` and a tick step `dtick` ("linear" is + the default value if `tick0` and `dtick` are provided). + If "array", the placement of the ticks is set via + `tickvals` and the tick text is `ticktext`. ("array" is + the default value if `tickvals` is provided). + tickprefix + Sets a tick label prefix. + ticks + Determines whether ticks are drawn or not. If "", this + axis' ticks are not drawn. If "outside" ("inside"), + this axis' are drawn outside (inside) the axis lines. + ticksuffix + Sets a tick label suffix. + ticktext + Sets the text displayed at the ticks position via + `tickvals`. Only has an effect if `tickmode` is set to + "array". Used with `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + Only has an effect if `tickmode` is set to "array". + Used with `ticktext`. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + tickwidth + Sets the tick width (in px). + title + :class:`plotly.graph_objects.mesh3d.colorbar.Title` + instance or dict with compatible properties + x + Sets the x position with respect to `xref` of the color + bar (in plot fraction). When `xref` is "paper", + defaults to 1.02 when `orientation` is "v" and 0.5 when + `orientation` is "h". When `xref` is "container", + defaults to 1 when `orientation` is "v" and 0.5 when + `orientation` is "h". Must be between 0 and 1 if `xref` + is "container" and between "-2" and 3 if `xref` is + "paper". + xanchor + Sets this color bar's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the color bar. Defaults to "left" when + `orientation` is "v" and "center" when `orientation` is + "h". + xpad + Sets the amount of padding (in px) along the x + direction. + xref + Sets the container `x` refers to. "container" spans the + entire `width` of the plot. "paper" refers to the width + of the plotting area only. + y + Sets the y position with respect to `yref` of the color + bar (in plot fraction). When `yref` is "paper", + defaults to 0.5 when `orientation` is "v" and 1.02 when + `orientation` is "h". When `yref` is "container", + defaults to 0.5 when `orientation` is "v" and 1 when + `orientation` is "h". Must be between 0 and 1 if `yref` + is "container" and between "-2" and 3 if `yref` is + "paper". + yanchor + Sets this color bar's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the color bar. Defaults to "middle" when + `orientation` is "v" and "bottom" when `orientation` is + "h". + ypad + Sets the amount of padding (in px) along the y + direction. + yref + Sets the container `y` refers to. "container" spans the + entire `height` of the plot. "paper" refers to the + height of the plotting area only. + """ + + def __init__( + self, + arg=None, + bgcolor=None, + bordercolor=None, + borderwidth=None, + dtick=None, + exponentformat=None, + labelalias=None, + len=None, + lenmode=None, + minexponent=None, + nticks=None, + orientation=None, + outlinecolor=None, + outlinewidth=None, + separatethousands=None, + showexponent=None, + showticklabels=None, + showtickprefix=None, + showticksuffix=None, + thickness=None, + thicknessmode=None, + tick0=None, + tickangle=None, + tickcolor=None, + tickfont=None, + tickformat=None, + tickformatstops=None, + tickformatstopdefaults=None, + ticklabeloverflow=None, + ticklabelposition=None, + ticklabelstep=None, + ticklen=None, + tickmode=None, + tickprefix=None, + ticks=None, + ticksuffix=None, + ticktext=None, + ticktextsrc=None, + tickvals=None, + tickvalssrc=None, + tickwidth=None, + title=None, + x=None, + xanchor=None, + xpad=None, + xref=None, + y=None, + yanchor=None, + ypad=None, + yref=None, + **kwargs, + ): + """ + Construct a new ColorBar object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.mesh3d.ColorBar` + bgcolor + Sets the color of padded area. + bordercolor + Sets the axis line color. + borderwidth + Sets the width (in px) or the border enclosing this + color bar. + dtick + Sets the step in-between ticks on this axis. Use with + `tick0`. Must be a positive number, or special strings + available to "log" and "date" axes. If the axis `type` + is "log", then ticks are set every 10^(n*dtick) where n + is the tick number. For example, to set a tick mark at + 1, 10, 100, 1000, ... set dtick to 1. To set tick marks + at 1, 100, 10000, ... set dtick to 2. To set tick marks + at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special + values; "L", where `f` is a positive number, gives + ticks linearly spaced in value (but not position). For + example `tick0` = 0.1, `dtick` = "L0.5" will put ticks + at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus + small digits between, use "D1" (all digits) or "D2" + (only 2 and 5). `tick0` is ignored for "D1" and "D2". + If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval + between ticks to one day, set `dtick` to 86400000.0. + "date" also has special values "M" gives ticks + spaced by a number of months. `n` must be a positive + integer. To set ticks on the 15th of every third month, + set `tick0` to "2000-01-15" and `dtick` to "M3". To set + ticks every 4 years, set `dtick` to "M48" + exponentformat + Determines a formatting rule for the tick exponents. + For example, consider the number 1,000,000,000. If + "none", it appears as 1,000,000,000. If "e", 1e+9. If + "E", 1E+9. If "power", 1x10^9 (with 9 in a super + script). If "SI", 1G. If "B", 1B. "SI" uses prefixes + from "femto" f (10^-15) to "tera" T (10^12). *SI + extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or + *SI extended* is used and the exponent is beyond the + above ranges, the formatting rule will automatically be + switched to the power notation. + labelalias + Replacement text for specific tick or hover labels. For + example using {US: 'USA', CA: 'Canada'} changes US to + USA and CA to Canada. The labels we would have shown + must match the keys exactly, after adding any + tickprefix or ticksuffix. For negative numbers the + minus sign symbol used (U+2212) is wider than the + regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis + type, and both keys (if needed) and values (if desired) + can include html-like tags or MathJax. + len + Sets the length of the color bar This measure excludes + the padding of both ends. That is, the color bar length + is this length minus the padding on both ends. + lenmode + Determines whether this color bar's length (i.e. the + measure in the color variation direction) is set in + units of plot "fraction" or in *pixels. Use `len` to + set the value. + minexponent + Hide SI prefix for 10^n if |n| is below this number. + This only has an effect when `tickformat` is "SI" or + "B". + nticks + Specifies the maximum number of ticks for the + particular axis. The actual number of ticks will be + chosen automatically to be less than or equal to + `nticks`. Has an effect only if `tickmode` is set to + "auto". + orientation + Sets the orientation of the colorbar. + outlinecolor + Sets the axis line color. + outlinewidth + Sets the width (in px) of the axis line. + separatethousands + If "true", even 4-digit integers are separated + showexponent + If "all", all exponents are shown besides their + significands. If "first", only the exponent of the + first tick is shown. If "last", only the exponent of + the last tick is shown. If "none", no exponents appear. + showticklabels + Determines whether or not the tick labels are drawn. + showtickprefix + If "all", all tick labels are displayed with a prefix. + If "first", only the first tick is displayed with a + prefix. If "last", only the last tick is displayed with + a suffix. If "none", tick prefixes are hidden. + showticksuffix + Same as `showtickprefix` but for tick suffixes. + thickness + Sets the thickness of the color bar This measure + excludes the size of the padding, ticks and labels. + thicknessmode + Determines whether this color bar's thickness (i.e. the + measure in the constant color direction) is set in + units of plot "fraction" or in "pixels". Use + `thickness` to set the value. + tick0 + Sets the placement of the first tick on this axis. Use + with `dtick`. If the axis `type` is "log", then you + must take the log of your starting tick (e.g. to set + the starting tick to 100, set the `tick0` to 2) except + when `dtick`=*L* (see `dtick` for more info). If the + axis `type` is "date", it should be a date string, like + date data. If the axis `type` is "category", it should + be a number, using the scale where each category is + assigned a serial number from zero in the order it + appears. + tickangle + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + tick labels vertically. + tickcolor + Sets the tick color. + tickfont + Sets the color bar's tick label font + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + tickformatstops + A tuple of :class:`plotly.graph_objects.mesh3d.colorbar + .Tickformatstop` instances or dicts with compatible + properties + tickformatstopdefaults + When used in a template (as layout.template.data.mesh3d + .colorbar.tickformatstopdefaults), sets the default + property values to use for elements of + mesh3d.colorbar.tickformatstops + ticklabeloverflow + Determines how we handle tick labels that would + overflow either the graph div or the domain of the + axis. The default value for inside tick labels is *hide + past domain*. In other cases the default is *hide past + div*. + ticklabelposition + Determines where tick labels are drawn relative to the + ticks. Left and right options are used when + `orientation` is "h", top and bottom when `orientation` + is "v". + ticklabelstep + Sets the spacing between tick labels as compared to the + spacing between ticks. A value of 1 (default) means + each tick gets a label. A value of 2 means shows every + 2nd label. A larger value n means only every nth tick + is labeled. `tick0` determines which labels are shown. + Not implemented for axes with `type` "log" or + "multicategory", or when `tickmode` is "array". + ticklen + Sets the tick length (in px). + tickmode + Sets the tick mode for this axis. If "auto", the number + of ticks is set via `nticks`. If "linear", the + placement of the ticks is determined by a starting + position `tick0` and a tick step `dtick` ("linear" is + the default value if `tick0` and `dtick` are provided). + If "array", the placement of the ticks is set via + `tickvals` and the tick text is `ticktext`. ("array" is + the default value if `tickvals` is provided). + tickprefix + Sets a tick label prefix. + ticks + Determines whether ticks are drawn or not. If "", this + axis' ticks are not drawn. If "outside" ("inside"), + this axis' are drawn outside (inside) the axis lines. + ticksuffix + Sets a tick label suffix. + ticktext + Sets the text displayed at the ticks position via + `tickvals`. Only has an effect if `tickmode` is set to + "array". Used with `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + Only has an effect if `tickmode` is set to "array". + Used with `ticktext`. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + tickwidth + Sets the tick width (in px). + title + :class:`plotly.graph_objects.mesh3d.colorbar.Title` + instance or dict with compatible properties + x + Sets the x position with respect to `xref` of the color + bar (in plot fraction). When `xref` is "paper", + defaults to 1.02 when `orientation` is "v" and 0.5 when + `orientation` is "h". When `xref` is "container", + defaults to 1 when `orientation` is "v" and 0.5 when + `orientation` is "h". Must be between 0 and 1 if `xref` + is "container" and between "-2" and 3 if `xref` is + "paper". + xanchor + Sets this color bar's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the color bar. Defaults to "left" when + `orientation` is "v" and "center" when `orientation` is + "h". + xpad + Sets the amount of padding (in px) along the x + direction. + xref + Sets the container `x` refers to. "container" spans the + entire `width` of the plot. "paper" refers to the width + of the plotting area only. + y + Sets the y position with respect to `yref` of the color + bar (in plot fraction). When `yref` is "paper", + defaults to 0.5 when `orientation` is "v" and 1.02 when + `orientation` is "h". When `yref` is "container", + defaults to 0.5 when `orientation` is "v" and 1 when + `orientation` is "h". Must be between 0 and 1 if `yref` + is "container" and between "-2" and 3 if `yref` is + "paper". + yanchor + Sets this color bar's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the color bar. Defaults to "middle" when + `orientation` is "v" and "bottom" when `orientation` is + "h". + ypad + Sets the amount of padding (in px) along the y + direction. + yref + Sets the container `y` refers to. "container" spans the + entire `height` of the plot. "paper" refers to the + height of the plotting area only. + + Returns + ------- + ColorBar + """ + super().__init__("colorbar") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.mesh3d.ColorBar +constructor must be a dict or +an instance of :class:`plotly.graph_objs.mesh3d.ColorBar`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("borderwidth", arg, borderwidth) + self._set_property("dtick", arg, dtick) + self._set_property("exponentformat", arg, exponentformat) + self._set_property("labelalias", arg, labelalias) + self._set_property("len", arg, len) + self._set_property("lenmode", arg, lenmode) + self._set_property("minexponent", arg, minexponent) + self._set_property("nticks", arg, nticks) + self._set_property("orientation", arg, orientation) + self._set_property("outlinecolor", arg, outlinecolor) + self._set_property("outlinewidth", arg, outlinewidth) + self._set_property("separatethousands", arg, separatethousands) + self._set_property("showexponent", arg, showexponent) + self._set_property("showticklabels", arg, showticklabels) + self._set_property("showtickprefix", arg, showtickprefix) + self._set_property("showticksuffix", arg, showticksuffix) + self._set_property("thickness", arg, thickness) + self._set_property("thicknessmode", arg, thicknessmode) + self._set_property("tick0", arg, tick0) + self._set_property("tickangle", arg, tickangle) + self._set_property("tickcolor", arg, tickcolor) + self._set_property("tickfont", arg, tickfont) + self._set_property("tickformat", arg, tickformat) + self._set_property("tickformatstops", arg, tickformatstops) + self._set_property("tickformatstopdefaults", arg, tickformatstopdefaults) + self._set_property("ticklabeloverflow", arg, ticklabeloverflow) + self._set_property("ticklabelposition", arg, ticklabelposition) + self._set_property("ticklabelstep", arg, ticklabelstep) + self._set_property("ticklen", arg, ticklen) + self._set_property("tickmode", arg, tickmode) + self._set_property("tickprefix", arg, tickprefix) + self._set_property("ticks", arg, ticks) + self._set_property("ticksuffix", arg, ticksuffix) + self._set_property("ticktext", arg, ticktext) + self._set_property("ticktextsrc", arg, ticktextsrc) + self._set_property("tickvals", arg, tickvals) + self._set_property("tickvalssrc", arg, tickvalssrc) + self._set_property("tickwidth", arg, tickwidth) + self._set_property("title", arg, title) + self._set_property("x", arg, x) + self._set_property("xanchor", arg, xanchor) + self._set_property("xpad", arg, xpad) + self._set_property("xref", arg, xref) + self._set_property("y", arg, y) + self._set_property("yanchor", arg, yanchor) + self._set_property("ypad", arg, ypad) + self._set_property("yref", arg, yref) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_contour.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_contour.py new file mode 100644 index 0000000000000000000000000000000000000000..fd831f39e5337438473dad253fb9857497e51aab --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_contour.py @@ -0,0 +1,127 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Contour(_BaseTraceHierarchyType): + _parent_path_str = "mesh3d" + _path_str = "mesh3d.contour" + _valid_props = {"color", "show", "width"} + + @property + def color(self): + """ + Sets the color of the contour lines. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def show(self): + """ + Sets whether or not dynamic contours are shown on hover + + The 'show' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["show"] + + @show.setter + def show(self, val): + self["show"] = val + + @property + def width(self): + """ + Sets the width of the contour lines. + + The 'width' property is a number and may be specified as: + - An int or float in the interval [1, 16] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def _prop_descriptions(self): + return """\ + color + Sets the color of the contour lines. + show + Sets whether or not dynamic contours are shown on hover + width + Sets the width of the contour lines. + """ + + def __init__(self, arg=None, color=None, show=None, width=None, **kwargs): + """ + Construct a new Contour object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.mesh3d.Contour` + color + Sets the color of the contour lines. + show + Sets whether or not dynamic contours are shown on hover + width + Sets the width of the contour lines. + + Returns + ------- + Contour + """ + super().__init__("contour") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.mesh3d.Contour +constructor must be a dict or +an instance of :class:`plotly.graph_objs.mesh3d.Contour`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("show", arg, show) + self._set_property("width", arg, width) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_hoverlabel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_hoverlabel.py new file mode 100644 index 0000000000000000000000000000000000000000..7cad9294c399f7e0740aae9e08e1e125550329c5 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_hoverlabel.py @@ -0,0 +1,366 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Hoverlabel(_BaseTraceHierarchyType): + _parent_path_str = "mesh3d" + _path_str = "mesh3d.hoverlabel" + _valid_props = { + "align", + "alignsrc", + "bgcolor", + "bgcolorsrc", + "bordercolor", + "bordercolorsrc", + "font", + "namelength", + "namelengthsrc", + "showarrow", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the text content within hover + label box. Has an effect only if the hover label text spans + more two or more lines + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'auto'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def alignsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `align`. + + The 'alignsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["alignsrc"] + + @alignsrc.setter + def alignsrc(self, val): + self["alignsrc"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the hover labels for this trace + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bgcolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `bgcolor`. + + The 'bgcolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bgcolorsrc"] + + @bgcolorsrc.setter + def bgcolorsrc(self, val): + self["bgcolorsrc"] = val + + @property + def bordercolor(self): + """ + Sets the border color of the hover labels for this trace. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def bordercolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + + The 'bordercolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bordercolorsrc"] + + @bordercolorsrc.setter + def bordercolorsrc(self, val): + self["bordercolorsrc"] = val + + @property + def font(self): + """ + Sets the font used in hover labels. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.mesh3d.hoverlabel.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.mesh3d.hoverlabel.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def namelength(self): + """ + Sets the default length (in number of characters) of the trace + name in the hover labels for all traces. -1 shows the whole + name regardless of length. 0-3 shows the first 0-3 characters, + and an integer >3 will show the whole name if it is less than + that many characters, but if it is longer, will truncate to + `namelength - 3` characters and add an ellipsis. + + The 'namelength' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["namelength"] + + @namelength.setter + def namelength(self, val): + self["namelength"] = val + + @property + def namelengthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `namelength`. + + The 'namelengthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["namelengthsrc"] + + @namelengthsrc.setter + def namelengthsrc(self, val): + self["namelengthsrc"] = val + + @property + def showarrow(self): + """ + Sets whether or not to show the hover label arrow/triangle + pointing to the data point. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + """ + + def __init__( + self, + arg=None, + align=None, + alignsrc=None, + bgcolor=None, + bgcolorsrc=None, + bordercolor=None, + bordercolorsrc=None, + font=None, + namelength=None, + namelengthsrc=None, + showarrow=None, + **kwargs, + ): + """ + Construct a new Hoverlabel object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.mesh3d.Hoverlabel` + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + + Returns + ------- + Hoverlabel + """ + super().__init__("hoverlabel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.mesh3d.Hoverlabel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.mesh3d.Hoverlabel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("alignsrc", arg, alignsrc) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bgcolorsrc", arg, bgcolorsrc) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("bordercolorsrc", arg, bordercolorsrc) + self._set_property("font", arg, font) + self._set_property("namelength", arg, namelength) + self._set_property("namelengthsrc", arg, namelengthsrc) + self._set_property("showarrow", arg, showarrow) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..19ae382d553e81cd0a05c5040acbee1dbc772222 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "mesh3d" + _path_str = "mesh3d.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.mesh3d.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.mesh3d.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.mesh3d.Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.mesh3d.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.mesh3d.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_lighting.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_lighting.py new file mode 100644 index 0000000000000000000000000000000000000000..18a57ff7e34ea6b9f589b25b076ce893c9f62536 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_lighting.py @@ -0,0 +1,260 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Lighting(_BaseTraceHierarchyType): + _parent_path_str = "mesh3d" + _path_str = "mesh3d.lighting" + _valid_props = { + "ambient", + "diffuse", + "facenormalsepsilon", + "fresnel", + "roughness", + "specular", + "vertexnormalsepsilon", + } + + @property + def ambient(self): + """ + Ambient light increases overall color visibility but can wash + out the image. + + The 'ambient' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["ambient"] + + @ambient.setter + def ambient(self, val): + self["ambient"] = val + + @property + def diffuse(self): + """ + Represents the extent that incident rays are reflected in a + range of angles. + + The 'diffuse' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["diffuse"] + + @diffuse.setter + def diffuse(self, val): + self["diffuse"] = val + + @property + def facenormalsepsilon(self): + """ + Epsilon for face normals calculation avoids math issues arising + from degenerate geometry. + + The 'facenormalsepsilon' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["facenormalsepsilon"] + + @facenormalsepsilon.setter + def facenormalsepsilon(self, val): + self["facenormalsepsilon"] = val + + @property + def fresnel(self): + """ + Represents the reflectance as a dependency of the viewing + angle; e.g. paper is reflective when viewing it from the edge + of the paper (almost 90 degrees), causing shine. + + The 'fresnel' property is a number and may be specified as: + - An int or float in the interval [0, 5] + + Returns + ------- + int|float + """ + return self["fresnel"] + + @fresnel.setter + def fresnel(self, val): + self["fresnel"] = val + + @property + def roughness(self): + """ + Alters specular reflection; the rougher the surface, the wider + and less contrasty the shine. + + The 'roughness' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["roughness"] + + @roughness.setter + def roughness(self, val): + self["roughness"] = val + + @property + def specular(self): + """ + Represents the level that incident rays are reflected in a + single direction, causing shine. + + The 'specular' property is a number and may be specified as: + - An int or float in the interval [0, 2] + + Returns + ------- + int|float + """ + return self["specular"] + + @specular.setter + def specular(self, val): + self["specular"] = val + + @property + def vertexnormalsepsilon(self): + """ + Epsilon for vertex normals calculation avoids math issues + arising from degenerate geometry. + + The 'vertexnormalsepsilon' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["vertexnormalsepsilon"] + + @vertexnormalsepsilon.setter + def vertexnormalsepsilon(self, val): + self["vertexnormalsepsilon"] = val + + @property + def _prop_descriptions(self): + return """\ + ambient + Ambient light increases overall color visibility but + can wash out the image. + diffuse + Represents the extent that incident rays are reflected + in a range of angles. + facenormalsepsilon + Epsilon for face normals calculation avoids math issues + arising from degenerate geometry. + fresnel + Represents the reflectance as a dependency of the + viewing angle; e.g. paper is reflective when viewing it + from the edge of the paper (almost 90 degrees), causing + shine. + roughness + Alters specular reflection; the rougher the surface, + the wider and less contrasty the shine. + specular + Represents the level that incident rays are reflected + in a single direction, causing shine. + vertexnormalsepsilon + Epsilon for vertex normals calculation avoids math + issues arising from degenerate geometry. + """ + + def __init__( + self, + arg=None, + ambient=None, + diffuse=None, + facenormalsepsilon=None, + fresnel=None, + roughness=None, + specular=None, + vertexnormalsepsilon=None, + **kwargs, + ): + """ + Construct a new Lighting object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.mesh3d.Lighting` + ambient + Ambient light increases overall color visibility but + can wash out the image. + diffuse + Represents the extent that incident rays are reflected + in a range of angles. + facenormalsepsilon + Epsilon for face normals calculation avoids math issues + arising from degenerate geometry. + fresnel + Represents the reflectance as a dependency of the + viewing angle; e.g. paper is reflective when viewing it + from the edge of the paper (almost 90 degrees), causing + shine. + roughness + Alters specular reflection; the rougher the surface, + the wider and less contrasty the shine. + specular + Represents the level that incident rays are reflected + in a single direction, causing shine. + vertexnormalsepsilon + Epsilon for vertex normals calculation avoids math + issues arising from degenerate geometry. + + Returns + ------- + Lighting + """ + super().__init__("lighting") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.mesh3d.Lighting +constructor must be a dict or +an instance of :class:`plotly.graph_objs.mesh3d.Lighting`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("ambient", arg, ambient) + self._set_property("diffuse", arg, diffuse) + self._set_property("facenormalsepsilon", arg, facenormalsepsilon) + self._set_property("fresnel", arg, fresnel) + self._set_property("roughness", arg, roughness) + self._set_property("specular", arg, specular) + self._set_property("vertexnormalsepsilon", arg, vertexnormalsepsilon) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_lightposition.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_lightposition.py new file mode 100644 index 0000000000000000000000000000000000000000..00b35d6945e2a5cc153a5ef712f3e4a2523cda65 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_lightposition.py @@ -0,0 +1,129 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Lightposition(_BaseTraceHierarchyType): + _parent_path_str = "mesh3d" + _path_str = "mesh3d.lightposition" + _valid_props = {"x", "y", "z"} + + @property + def x(self): + """ + Numeric vector, representing the X coordinate for each vertex. + + The 'x' property is a number and may be specified as: + - An int or float in the interval [-100000, 100000] + + Returns + ------- + int|float + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def y(self): + """ + Numeric vector, representing the Y coordinate for each vertex. + + The 'y' property is a number and may be specified as: + - An int or float in the interval [-100000, 100000] + + Returns + ------- + int|float + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def z(self): + """ + Numeric vector, representing the Z coordinate for each vertex. + + The 'z' property is a number and may be specified as: + - An int or float in the interval [-100000, 100000] + + Returns + ------- + int|float + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def _prop_descriptions(self): + return """\ + x + Numeric vector, representing the X coordinate for each + vertex. + y + Numeric vector, representing the Y coordinate for each + vertex. + z + Numeric vector, representing the Z coordinate for each + vertex. + """ + + def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): + """ + Construct a new Lightposition object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.mesh3d.Lightposition` + x + Numeric vector, representing the X coordinate for each + vertex. + y + Numeric vector, representing the Y coordinate for each + vertex. + z + Numeric vector, representing the Z coordinate for each + vertex. + + Returns + ------- + Lightposition + """ + super().__init__("lightposition") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.mesh3d.Lightposition +constructor must be a dict or +an instance of :class:`plotly.graph_objs.mesh3d.Lightposition`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("x", arg, x) + self._set_property("y", arg, y) + self._set_property("z", arg, z) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..b3b00d69d047129db206b2ab3e263646b78e3b43 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/mesh3d/_stream.py @@ -0,0 +1,113 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "mesh3d" + _path_str = "mesh3d.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.mesh3d.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.mesh3d.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.mesh3d.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..464258ceedc20c6dd9712eaae044bdfb4a521f07 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/__init__.py @@ -0,0 +1,29 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._decreasing import Decreasing + from ._hoverlabel import Hoverlabel + from ._increasing import Increasing + from ._legendgrouptitle import Legendgrouptitle + from ._line import Line + from ._stream import Stream + from . import decreasing + from . import hoverlabel + from . import increasing + from . import legendgrouptitle +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [".decreasing", ".hoverlabel", ".increasing", ".legendgrouptitle"], + [ + "._decreasing.Decreasing", + "._hoverlabel.Hoverlabel", + "._increasing.Increasing", + "._legendgrouptitle.Legendgrouptitle", + "._line.Line", + "._stream.Stream", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_decreasing.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_decreasing.py new file mode 100644 index 0000000000000000000000000000000000000000..bed49343199db3f74d2089ce949de22f75fb8da9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_decreasing.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Decreasing(_BaseTraceHierarchyType): + _parent_path_str = "ohlc" + _path_str = "ohlc.decreasing" + _valid_props = {"line"} + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.ohlc.decreasing.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.ohlc.decreasing.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def _prop_descriptions(self): + return """\ + line + :class:`plotly.graph_objects.ohlc.decreasing.Line` + instance or dict with compatible properties + """ + + def __init__(self, arg=None, line=None, **kwargs): + """ + Construct a new Decreasing object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.ohlc.Decreasing` + line + :class:`plotly.graph_objects.ohlc.decreasing.Line` + instance or dict with compatible properties + + Returns + ------- + Decreasing + """ + super().__init__("decreasing") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.ohlc.Decreasing +constructor must be a dict or +an instance of :class:`plotly.graph_objs.ohlc.Decreasing`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("line", arg, line) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_hoverlabel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_hoverlabel.py new file mode 100644 index 0000000000000000000000000000000000000000..c91cfbbd1899ee6c01997021471f2b9b1eac2e24 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_hoverlabel.py @@ -0,0 +1,399 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Hoverlabel(_BaseTraceHierarchyType): + _parent_path_str = "ohlc" + _path_str = "ohlc.hoverlabel" + _valid_props = { + "align", + "alignsrc", + "bgcolor", + "bgcolorsrc", + "bordercolor", + "bordercolorsrc", + "font", + "namelength", + "namelengthsrc", + "showarrow", + "split", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the text content within hover + label box. Has an effect only if the hover label text spans + more two or more lines + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'auto'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def alignsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `align`. + + The 'alignsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["alignsrc"] + + @alignsrc.setter + def alignsrc(self, val): + self["alignsrc"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the hover labels for this trace + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bgcolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `bgcolor`. + + The 'bgcolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bgcolorsrc"] + + @bgcolorsrc.setter + def bgcolorsrc(self, val): + self["bgcolorsrc"] = val + + @property + def bordercolor(self): + """ + Sets the border color of the hover labels for this trace. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def bordercolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + + The 'bordercolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bordercolorsrc"] + + @bordercolorsrc.setter + def bordercolorsrc(self, val): + self["bordercolorsrc"] = val + + @property + def font(self): + """ + Sets the font used in hover labels. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.ohlc.hoverlabel.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.ohlc.hoverlabel.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def namelength(self): + """ + Sets the default length (in number of characters) of the trace + name in the hover labels for all traces. -1 shows the whole + name regardless of length. 0-3 shows the first 0-3 characters, + and an integer >3 will show the whole name if it is less than + that many characters, but if it is longer, will truncate to + `namelength - 3` characters and add an ellipsis. + + The 'namelength' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["namelength"] + + @namelength.setter + def namelength(self, val): + self["namelength"] = val + + @property + def namelengthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `namelength`. + + The 'namelengthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["namelengthsrc"] + + @namelengthsrc.setter + def namelengthsrc(self, val): + self["namelengthsrc"] = val + + @property + def showarrow(self): + """ + Sets whether or not to show the hover label arrow/triangle + pointing to the data point. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def split(self): + """ + Show hover information (open, close, high, low) in separate + labels, rather than a single unified label. Default: False. + When set to True, `hovertemplate` is ignored. + + The 'split' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["split"] + + @split.setter + def split(self, val): + self["split"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + split + Show hover information (open, close, high, low) in + separate labels, rather than a single unified label. + Default: False. When set to True, `hovertemplate` is + ignored. + """ + + def __init__( + self, + arg=None, + align=None, + alignsrc=None, + bgcolor=None, + bgcolorsrc=None, + bordercolor=None, + bordercolorsrc=None, + font=None, + namelength=None, + namelengthsrc=None, + showarrow=None, + split=None, + **kwargs, + ): + """ + Construct a new Hoverlabel object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.ohlc.Hoverlabel` + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + split + Show hover information (open, close, high, low) in + separate labels, rather than a single unified label. + Default: False. When set to True, `hovertemplate` is + ignored. + + Returns + ------- + Hoverlabel + """ + super().__init__("hoverlabel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.ohlc.Hoverlabel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.ohlc.Hoverlabel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("alignsrc", arg, alignsrc) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bgcolorsrc", arg, bgcolorsrc) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("bordercolorsrc", arg, bordercolorsrc) + self._set_property("font", arg, font) + self._set_property("namelength", arg, namelength) + self._set_property("namelengthsrc", arg, namelengthsrc) + self._set_property("showarrow", arg, showarrow) + self._set_property("split", arg, split) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_increasing.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_increasing.py new file mode 100644 index 0000000000000000000000000000000000000000..77ff3e426977b69b0a0d9e16b3c707990c6dbfb2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_increasing.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Increasing(_BaseTraceHierarchyType): + _parent_path_str = "ohlc" + _path_str = "ohlc.increasing" + _valid_props = {"line"} + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.ohlc.increasing.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.ohlc.increasing.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def _prop_descriptions(self): + return """\ + line + :class:`plotly.graph_objects.ohlc.increasing.Line` + instance or dict with compatible properties + """ + + def __init__(self, arg=None, line=None, **kwargs): + """ + Construct a new Increasing object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.ohlc.Increasing` + line + :class:`plotly.graph_objects.ohlc.increasing.Line` + instance or dict with compatible properties + + Returns + ------- + Increasing + """ + super().__init__("increasing") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.ohlc.Increasing +constructor must be a dict or +an instance of :class:`plotly.graph_objs.ohlc.Increasing`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("line", arg, line) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..b21b4403954ec663405d39db8ddc9b8dbebf005b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "ohlc" + _path_str = "ohlc.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.ohlc.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.ohlc.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.ohlc.Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.ohlc.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.ohlc.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_line.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_line.py new file mode 100644 index 0000000000000000000000000000000000000000..0090896dd64e28dfc5cf4b3bd12e0501f2d3a27d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_line.py @@ -0,0 +1,123 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Line(_BaseTraceHierarchyType): + _parent_path_str = "ohlc" + _path_str = "ohlc.line" + _valid_props = {"dash", "width"} + + @property + def dash(self): + """ + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). Note that this style setting can also be + set per direction via `increasing.line.dash` and + `decreasing.line.dash`. + + The 'dash' property is an enumeration that may be specified as: + - One of the following dash styles: + ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] + - A string containing a dash length list in pixels or percentages + (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) + + Returns + ------- + str + """ + return self["dash"] + + @dash.setter + def dash(self, val): + self["dash"] = val + + @property + def width(self): + """ + [object Object] Note that this style setting can also be set + per direction via `increasing.line.width` and + `decreasing.line.width`. + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def _prop_descriptions(self): + return """\ + dash + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). Note that this style setting can + also be set per direction via `increasing.line.dash` + and `decreasing.line.dash`. + width + [object Object] Note that this style setting can also + be set per direction via `increasing.line.width` and + `decreasing.line.width`. + """ + + def __init__(self, arg=None, dash=None, width=None, **kwargs): + """ + Construct a new Line object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.ohlc.Line` + dash + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). Note that this style setting can + also be set per direction via `increasing.line.dash` + and `decreasing.line.dash`. + width + [object Object] Note that this style setting can also + be set per direction via `increasing.line.width` and + `decreasing.line.width`. + + Returns + ------- + Line + """ + super().__init__("line") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.ohlc.Line +constructor must be a dict or +an instance of :class:`plotly.graph_objs.ohlc.Line`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("dash", arg, dash) + self._set_property("width", arg, width) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..5e753fbde7d43e7d71bcd8e6e2c96caac007ad9b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/ohlc/_stream.py @@ -0,0 +1,113 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "ohlc" + _path_str = "ohlc.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.ohlc.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.ohlc.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.ohlc.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..5289c29f5477cb4af8a9d0d8bfa709204c56ba68 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/__init__.py @@ -0,0 +1,29 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._dimension import Dimension + from ._domain import Domain + from ._labelfont import Labelfont + from ._legendgrouptitle import Legendgrouptitle + from ._line import Line + from ._stream import Stream + from ._tickfont import Tickfont + from . import legendgrouptitle + from . import line +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [".legendgrouptitle", ".line"], + [ + "._dimension.Dimension", + "._domain.Domain", + "._labelfont.Labelfont", + "._legendgrouptitle.Legendgrouptitle", + "._line.Line", + "._stream.Stream", + "._tickfont.Tickfont", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_dimension.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_dimension.py new file mode 100644 index 0000000000000000000000000000000000000000..e2bdcb60ba8e7f69ab5036c11cdbae2539b48391 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_dimension.py @@ -0,0 +1,383 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Dimension(_BaseTraceHierarchyType): + _parent_path_str = "parcats" + _path_str = "parcats.dimension" + _valid_props = { + "categoryarray", + "categoryarraysrc", + "categoryorder", + "displayindex", + "label", + "ticktext", + "ticktextsrc", + "values", + "valuessrc", + "visible", + } + + @property + def categoryarray(self): + """ + Sets the order in which categories in this dimension appear. + Only has an effect if `categoryorder` is set to "array". Used + with `categoryorder`. + + The 'categoryarray' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["categoryarray"] + + @categoryarray.setter + def categoryarray(self, val): + self["categoryarray"] = val + + @property + def categoryarraysrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `categoryarray`. + + The 'categoryarraysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["categoryarraysrc"] + + @categoryarraysrc.setter + def categoryarraysrc(self, val): + self["categoryarraysrc"] = val + + @property + def categoryorder(self): + """ + Specifies the ordering logic for the categories in the + dimension. By default, plotly uses "trace", which specifies the + order that is present in the data supplied. Set `categoryorder` + to *category ascending* or *category descending* if order + should be determined by the alphanumerical order of the + category names. Set `categoryorder` to "array" to derive the + ordering from the attribute `categoryarray`. If a category is + not found in the `categoryarray` array, the sorting behavior + for that attribute will be identical to the "trace" mode. The + unspecified categories will follow the categories in + `categoryarray`. + + The 'categoryorder' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['trace', 'category ascending', 'category descending', + 'array'] + + Returns + ------- + Any + """ + return self["categoryorder"] + + @categoryorder.setter + def categoryorder(self, val): + self["categoryorder"] = val + + @property + def displayindex(self): + """ + The display index of dimension, from left to right, zero + indexed, defaults to dimension index. + + The 'displayindex' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + + Returns + ------- + int + """ + return self["displayindex"] + + @displayindex.setter + def displayindex(self, val): + self["displayindex"] = val + + @property + def label(self): + """ + The shown name of the dimension. + + The 'label' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["label"] + + @label.setter + def label(self, val): + self["label"] = val + + @property + def ticktext(self): + """ + Sets alternative tick labels for the categories in this + dimension. Only has an effect if `categoryorder` is set to + "array". Should be an array the same length as `categoryarray` + Used with `categoryorder`. + + The 'ticktext' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ticktext"] + + @ticktext.setter + def ticktext(self, val): + self["ticktext"] = val + + @property + def ticktextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ticktext`. + + The 'ticktextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ticktextsrc"] + + @ticktextsrc.setter + def ticktextsrc(self, val): + self["ticktextsrc"] = val + + @property + def values(self): + """ + Dimension values. `values[n]` represents the category value of + the `n`th point in the dataset, therefore the `values` vector + for all dimensions must be the same (longer vectors will be + truncated). + + The 'values' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["values"] + + @values.setter + def values(self, val): + self["values"] = val + + @property + def valuessrc(self): + """ + Sets the source reference on Chart Studio Cloud for `values`. + + The 'valuessrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["valuessrc"] + + @valuessrc.setter + def valuessrc(self, val): + self["valuessrc"] = val + + @property + def visible(self): + """ + Shows the dimension when set to `true` (the default). Hides the + dimension for `false`. + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def _prop_descriptions(self): + return """\ + categoryarray + Sets the order in which categories in this dimension + appear. Only has an effect if `categoryorder` is set to + "array". Used with `categoryorder`. + categoryarraysrc + Sets the source reference on Chart Studio Cloud for + `categoryarray`. + categoryorder + Specifies the ordering logic for the categories in the + dimension. By default, plotly uses "trace", which + specifies the order that is present in the data + supplied. Set `categoryorder` to *category ascending* + or *category descending* if order should be determined + by the alphanumerical order of the category names. Set + `categoryorder` to "array" to derive the ordering from + the attribute `categoryarray`. If a category is not + found in the `categoryarray` array, the sorting + behavior for that attribute will be identical to the + "trace" mode. The unspecified categories will follow + the categories in `categoryarray`. + displayindex + The display index of dimension, from left to right, + zero indexed, defaults to dimension index. + label + The shown name of the dimension. + ticktext + Sets alternative tick labels for the categories in this + dimension. Only has an effect if `categoryorder` is set + to "array". Should be an array the same length as + `categoryarray` Used with `categoryorder`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + values + Dimension values. `values[n]` represents the category + value of the `n`th point in the dataset, therefore the + `values` vector for all dimensions must be the same + (longer vectors will be truncated). + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Shows the dimension when set to `true` (the default). + Hides the dimension for `false`. + """ + + def __init__( + self, + arg=None, + categoryarray=None, + categoryarraysrc=None, + categoryorder=None, + displayindex=None, + label=None, + ticktext=None, + ticktextsrc=None, + values=None, + valuessrc=None, + visible=None, + **kwargs, + ): + """ + Construct a new Dimension object + + The dimensions (variables) of the parallel categories diagram. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.parcats.Dimension` + categoryarray + Sets the order in which categories in this dimension + appear. Only has an effect if `categoryorder` is set to + "array". Used with `categoryorder`. + categoryarraysrc + Sets the source reference on Chart Studio Cloud for + `categoryarray`. + categoryorder + Specifies the ordering logic for the categories in the + dimension. By default, plotly uses "trace", which + specifies the order that is present in the data + supplied. Set `categoryorder` to *category ascending* + or *category descending* if order should be determined + by the alphanumerical order of the category names. Set + `categoryorder` to "array" to derive the ordering from + the attribute `categoryarray`. If a category is not + found in the `categoryarray` array, the sorting + behavior for that attribute will be identical to the + "trace" mode. The unspecified categories will follow + the categories in `categoryarray`. + displayindex + The display index of dimension, from left to right, + zero indexed, defaults to dimension index. + label + The shown name of the dimension. + ticktext + Sets alternative tick labels for the categories in this + dimension. Only has an effect if `categoryorder` is set + to "array". Should be an array the same length as + `categoryarray` Used with `categoryorder`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + values + Dimension values. `values[n]` represents the category + value of the `n`th point in the dataset, therefore the + `values` vector for all dimensions must be the same + (longer vectors will be truncated). + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Shows the dimension when set to `true` (the default). + Hides the dimension for `false`. + + Returns + ------- + Dimension + """ + super().__init__("dimensions") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcats.Dimension +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcats.Dimension`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("categoryarray", arg, categoryarray) + self._set_property("categoryarraysrc", arg, categoryarraysrc) + self._set_property("categoryorder", arg, categoryorder) + self._set_property("displayindex", arg, displayindex) + self._set_property("label", arg, label) + self._set_property("ticktext", arg, ticktext) + self._set_property("ticktextsrc", arg, ticktextsrc) + self._set_property("values", arg, values) + self._set_property("valuessrc", arg, valuessrc) + self._set_property("visible", arg, visible) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_domain.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_domain.py new file mode 100644 index 0000000000000000000000000000000000000000..6699f7bb108c0023bb836149cb816e2d38bf4cb4 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_domain.py @@ -0,0 +1,170 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Domain(_BaseTraceHierarchyType): + _parent_path_str = "parcats" + _path_str = "parcats.domain" + _valid_props = {"column", "row", "x", "y"} + + @property + def column(self): + """ + If there is a layout grid, use the domain for this column in + the grid for this parcats trace . + + The 'column' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["column"] + + @column.setter + def column(self, val): + self["column"] = val + + @property + def row(self): + """ + If there is a layout grid, use the domain for this row in the + grid for this parcats trace . + + The 'row' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["row"] + + @row.setter + def row(self, val): + self["row"] = val + + @property + def x(self): + """ + Sets the horizontal domain of this parcats trace (in plot + fraction). + + The 'x' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'x[0]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + (1) The 'x[1]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + list + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def y(self): + """ + Sets the vertical domain of this parcats trace (in plot + fraction). + + The 'y' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'y[0]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + (1) The 'y[1]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + list + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def _prop_descriptions(self): + return """\ + column + If there is a layout grid, use the domain for this + column in the grid for this parcats trace . + row + If there is a layout grid, use the domain for this row + in the grid for this parcats trace . + x + Sets the horizontal domain of this parcats trace (in + plot fraction). + y + Sets the vertical domain of this parcats trace (in plot + fraction). + """ + + def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): + """ + Construct a new Domain object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.parcats.Domain` + column + If there is a layout grid, use the domain for this + column in the grid for this parcats trace . + row + If there is a layout grid, use the domain for this row + in the grid for this parcats trace . + x + Sets the horizontal domain of this parcats trace (in + plot fraction). + y + Sets the vertical domain of this parcats trace (in plot + fraction). + + Returns + ------- + Domain + """ + super().__init__("domain") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcats.Domain +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcats.Domain`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("column", arg, column) + self._set_property("row", arg, row) + self._set_property("x", arg, x) + self._set_property("y", arg, y) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_labelfont.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_labelfont.py new file mode 100644 index 0000000000000000000000000000000000000000..8f3bd58e3ac9b398729db653da2fe964b26372c8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_labelfont.py @@ -0,0 +1,334 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Labelfont(_BaseTraceHierarchyType): + _parent_path_str = "parcats" + _path_str = "parcats.labelfont" + _valid_props = { + "color", + "family", + "lineposition", + "shadow", + "size", + "style", + "textcase", + "variant", + "weight", + } + + @property + def color(self): + """ + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def family(self): + """ + HTML font family - the typeface that will be applied by the web + browser. The web browser can only apply a font if it is + available on the system where it runs. Provide multiple font + families, separated by commas, to indicate the order in which + to apply fonts if they aren't available. + + The 'family' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["family"] + + @family.setter + def family(self, val): + self["family"] = val + + @property + def lineposition(self): + """ + Sets the kind of decoration line(s) with text, such as an + "under", "over" or "through" as well as combinations e.g. + "under+over", etc. + + The 'lineposition' property is a flaglist and may be specified + as a string containing: + - Any combination of ['under', 'over', 'through'] joined with '+' characters + (e.g. 'under+over') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["lineposition"] + + @lineposition.setter + def lineposition(self, val): + self["lineposition"] = val + + @property + def shadow(self): + """ + Sets the shape and color of the shadow behind text. "auto" + places minimal shadow and applies contrast text font color. See + https://developer.mozilla.org/en-US/docs/Web/CSS/text-shadow + for additional options. + + The 'shadow' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["shadow"] + + @shadow.setter + def shadow(self, val): + self["shadow"] = val + + @property + def size(self): + """ + The 'size' property is a number and may be specified as: + - An int or float in the interval [1, inf] + + Returns + ------- + int|float + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def style(self): + """ + Sets whether a font should be styled with a normal or italic + face from its family. + + The 'style' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'italic'] + + Returns + ------- + Any + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def textcase(self): + """ + Sets capitalization of text. It can be used to make text appear + in all-uppercase or all-lowercase, or with each word + capitalized. + + The 'textcase' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'word caps', 'upper', 'lower'] + + Returns + ------- + Any + """ + return self["textcase"] + + @textcase.setter + def textcase(self, val): + self["textcase"] = val + + @property + def variant(self): + """ + Sets the variant of the font. + + The 'variant' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'small-caps', 'all-small-caps', + 'all-petite-caps', 'petite-caps', 'unicase'] + + Returns + ------- + Any + """ + return self["variant"] + + @variant.setter + def variant(self, val): + self["variant"] = val + + @property + def weight(self): + """ + Sets the weight (or boldness) of the font. + + The 'weight' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 1000] + OR exactly one of ['normal', 'bold'] (e.g. 'bold') + + Returns + ------- + int + """ + return self["weight"] + + @weight.setter + def weight(self, val): + self["weight"] = val + + @property + def _prop_descriptions(self): + return """\ + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + """ + + def __init__( + self, + arg=None, + color=None, + family=None, + lineposition=None, + shadow=None, + size=None, + style=None, + textcase=None, + variant=None, + weight=None, + **kwargs, + ): + """ + Construct a new Labelfont object + + Sets the font for the `dimension` labels. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.parcats.Labelfont` + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + + Returns + ------- + Labelfont + """ + super().__init__("labelfont") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcats.Labelfont +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcats.Labelfont`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("family", arg, family) + self._set_property("lineposition", arg, lineposition) + self._set_property("shadow", arg, shadow) + self._set_property("size", arg, size) + self._set_property("style", arg, style) + self._set_property("textcase", arg, textcase) + self._set_property("variant", arg, variant) + self._set_property("weight", arg, weight) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..180f8f8b4cdc84fe1b73e9b547b37a6e606df34e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "parcats" + _path_str = "parcats.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcats.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.parcats.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.parcats.Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcats.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcats.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_line.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_line.py new file mode 100644 index 0000000000000000000000000000000000000000..7080c271639c4df95afd8575285c90530488495f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_line.py @@ -0,0 +1,725 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Line(_BaseTraceHierarchyType): + _parent_path_str = "parcats" + _path_str = "parcats.line" + _valid_props = { + "autocolorscale", + "cauto", + "cmax", + "cmid", + "cmin", + "color", + "coloraxis", + "colorbar", + "colorscale", + "colorsrc", + "hovertemplate", + "hovertemplatefallback", + "reversescale", + "shape", + "showscale", + } + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `line.colorscale`. Has an effect only if in `line.color` is set + to a numerical array. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def cauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `line.color`) or the bounds + set in `line.cmin` and `line.cmax` Has an effect only if in + `line.color` is set to a numerical array. Defaults to `false` + when `line.cmin` and `line.cmax` are set by the user. + + The 'cauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cauto"] + + @cauto.setter + def cauto(self, val): + self["cauto"] = val + + @property + def cmax(self): + """ + Sets the upper bound of the color domain. Has an effect only if + in `line.color` is set to a numerical array. Value should have + the same units as in `line.color` and if set, `line.cmin` must + be set as well. + + The 'cmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmax"] + + @cmax.setter + def cmax(self, val): + self["cmax"] = val + + @property + def cmid(self): + """ + Sets the mid-point of the color domain by scaling `line.cmin` + and/or `line.cmax` to be equidistant to this point. Has an + effect only if in `line.color` is set to a numerical array. + Value should have the same units as in `line.color`. Has no + effect when `line.cauto` is `false`. + + The 'cmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmid"] + + @cmid.setter + def cmid(self, val): + self["cmid"] = val + + @property + def cmin(self): + """ + Sets the lower bound of the color domain. Has an effect only if + in `line.color` is set to a numerical array. Value should have + the same units as in `line.color` and if set, `line.cmax` must + be set as well. + + The 'cmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmin"] + + @cmin.setter + def cmin(self, val): + self["cmin"] = val + + @property + def color(self): + """ + Sets the line color. It accepts either a specific color or an + array of numbers that are mapped to the colorscale relative to + the max and min values of the array or relative to `line.cmin` + and `line.cmax` if set. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A number that will be interpreted as a color + according to parcats.line.colorscale + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcats.line.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.parcats.line.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. Has an effect only if in `line.color` is + set to a numerical array. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, rgba, + hex, hsl, hsv, or named color string. At minimum, a mapping for + the lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To + control the bounds of the colorscale in color space, use + `line.cmin` and `line.cmax`. Alternatively, `colorscale` may be + a palette name string of the following list: Blackbody,Bluered, + Blues,Cividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portla + nd,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def colorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `color`. + + The 'colorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["colorsrc"] + + @colorsrc.setter + def colorsrc(self, val): + self["colorsrc"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables `count` + and `probability`. Anything contained in tag `` is + displayed in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. Has an effect only if in + `line.color` is set to a numerical array. If true, `line.cmin` + will correspond to the last color in the array and `line.cmax` + will correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def shape(self): + """ + Sets the shape of the paths. If `linear`, paths are composed of + straight lines. If `hspline`, paths are composed of horizontal + curved splines + + The 'shape' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['linear', 'hspline'] + + Returns + ------- + Any + """ + return self["shape"] + + @shape.setter + def shape(self, val): + self["shape"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. Has an effect only if in `line.color` is set to a + numerical array. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def _prop_descriptions(self): + return """\ + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `line.colorscale`. Has an effect only if in + `line.color` is set to a numerical array. In case + `colorscale` is unspecified or `autocolorscale` is + true, the default palette will be chosen according to + whether numbers in the `color` array are all positive, + all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here in `line.color`) + or the bounds set in `line.cmin` and `line.cmax` Has an + effect only if in `line.color` is set to a numerical + array. Defaults to `false` when `line.cmin` and + `line.cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Has an effect + only if in `line.color` is set to a numerical array. + Value should have the same units as in `line.color` and + if set, `line.cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `line.cmin` and/or `line.cmax` to be equidistant to + this point. Has an effect only if in `line.color` is + set to a numerical array. Value should have the same + units as in `line.color`. Has no effect when + `line.cauto` is `false`. + cmin + Sets the lower bound of the color domain. Has an effect + only if in `line.color` is set to a numerical array. + Value should have the same units as in `line.color` and + if set, `line.cmax` must be set as well. + color + Sets the line color. It accepts either a specific color + or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `line.cmin` and `line.cmax` if + set. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.parcats.line.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. Has an effect only if in + `line.color` is set to a numerical array. The + colorscale must be an array containing arrays mapping a + normalized value to an rgb, rgba, hex, hsl, hsv, or + named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. + To control the bounds of the colorscale in color space, + use `line.cmin` and `line.cmax`. Alternatively, + `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,E + lectric,Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,Rd + Bu,Reds,Viridis,YlGnBu,YlOrRd. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `count` and `probability`. Anything + contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + reversescale + Reverses the color mapping if true. Has an effect only + if in `line.color` is set to a numerical array. If + true, `line.cmin` will correspond to the last color in + the array and `line.cmax` will correspond to the first + color. + shape + Sets the shape of the paths. If `linear`, paths are + composed of straight lines. If `hspline`, paths are + composed of horizontal curved splines + showscale + Determines whether or not a colorbar is displayed for + this trace. Has an effect only if in `line.color` is + set to a numerical array. + """ + + def __init__( + self, + arg=None, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + color=None, + coloraxis=None, + colorbar=None, + colorscale=None, + colorsrc=None, + hovertemplate=None, + hovertemplatefallback=None, + reversescale=None, + shape=None, + showscale=None, + **kwargs, + ): + """ + Construct a new Line object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.parcats.Line` + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `line.colorscale`. Has an effect only if in + `line.color` is set to a numerical array. In case + `colorscale` is unspecified or `autocolorscale` is + true, the default palette will be chosen according to + whether numbers in the `color` array are all positive, + all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here in `line.color`) + or the bounds set in `line.cmin` and `line.cmax` Has an + effect only if in `line.color` is set to a numerical + array. Defaults to `false` when `line.cmin` and + `line.cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Has an effect + only if in `line.color` is set to a numerical array. + Value should have the same units as in `line.color` and + if set, `line.cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `line.cmin` and/or `line.cmax` to be equidistant to + this point. Has an effect only if in `line.color` is + set to a numerical array. Value should have the same + units as in `line.color`. Has no effect when + `line.cauto` is `false`. + cmin + Sets the lower bound of the color domain. Has an effect + only if in `line.color` is set to a numerical array. + Value should have the same units as in `line.color` and + if set, `line.cmax` must be set as well. + color + Sets the line color. It accepts either a specific color + or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `line.cmin` and `line.cmax` if + set. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.parcats.line.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. Has an effect only if in + `line.color` is set to a numerical array. The + colorscale must be an array containing arrays mapping a + normalized value to an rgb, rgba, hex, hsl, hsv, or + named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. + To control the bounds of the colorscale in color space, + use `line.cmin` and `line.cmax`. Alternatively, + `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,E + lectric,Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,Rd + Bu,Reds,Viridis,YlGnBu,YlOrRd. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `count` and `probability`. Anything + contained in tag `` is displayed in the + secondary box, for example + `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + reversescale + Reverses the color mapping if true. Has an effect only + if in `line.color` is set to a numerical array. If + true, `line.cmin` will correspond to the last color in + the array and `line.cmax` will correspond to the first + color. + shape + Sets the shape of the paths. If `linear`, paths are + composed of straight lines. If `hspline`, paths are + composed of horizontal curved splines + showscale + Determines whether or not a colorbar is displayed for + this trace. Has an effect only if in `line.color` is + set to a numerical array. + + Returns + ------- + Line + """ + super().__init__("line") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcats.Line +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcats.Line`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("cauto", arg, cauto) + self._set_property("cmax", arg, cmax) + self._set_property("cmid", arg, cmid) + self._set_property("cmin", arg, cmin) + self._set_property("color", arg, color) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("colorsrc", arg, colorsrc) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("reversescale", arg, reversescale) + self._set_property("shape", arg, shape) + self._set_property("showscale", arg, showscale) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..8d0707800b6d0952d819d16697f23f8c4d161b90 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_stream.py @@ -0,0 +1,114 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "parcats" + _path_str = "parcats.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.parcats.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcats.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcats.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_tickfont.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_tickfont.py new file mode 100644 index 0000000000000000000000000000000000000000..630d6dc72c9e7440a6ba7a386911a0aeb125cdf5 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcats/_tickfont.py @@ -0,0 +1,334 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Tickfont(_BaseTraceHierarchyType): + _parent_path_str = "parcats" + _path_str = "parcats.tickfont" + _valid_props = { + "color", + "family", + "lineposition", + "shadow", + "size", + "style", + "textcase", + "variant", + "weight", + } + + @property + def color(self): + """ + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def family(self): + """ + HTML font family - the typeface that will be applied by the web + browser. The web browser can only apply a font if it is + available on the system where it runs. Provide multiple font + families, separated by commas, to indicate the order in which + to apply fonts if they aren't available. + + The 'family' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["family"] + + @family.setter + def family(self, val): + self["family"] = val + + @property + def lineposition(self): + """ + Sets the kind of decoration line(s) with text, such as an + "under", "over" or "through" as well as combinations e.g. + "under+over", etc. + + The 'lineposition' property is a flaglist and may be specified + as a string containing: + - Any combination of ['under', 'over', 'through'] joined with '+' characters + (e.g. 'under+over') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["lineposition"] + + @lineposition.setter + def lineposition(self, val): + self["lineposition"] = val + + @property + def shadow(self): + """ + Sets the shape and color of the shadow behind text. "auto" + places minimal shadow and applies contrast text font color. See + https://developer.mozilla.org/en-US/docs/Web/CSS/text-shadow + for additional options. + + The 'shadow' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["shadow"] + + @shadow.setter + def shadow(self, val): + self["shadow"] = val + + @property + def size(self): + """ + The 'size' property is a number and may be specified as: + - An int or float in the interval [1, inf] + + Returns + ------- + int|float + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def style(self): + """ + Sets whether a font should be styled with a normal or italic + face from its family. + + The 'style' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'italic'] + + Returns + ------- + Any + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def textcase(self): + """ + Sets capitalization of text. It can be used to make text appear + in all-uppercase or all-lowercase, or with each word + capitalized. + + The 'textcase' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'word caps', 'upper', 'lower'] + + Returns + ------- + Any + """ + return self["textcase"] + + @textcase.setter + def textcase(self, val): + self["textcase"] = val + + @property + def variant(self): + """ + Sets the variant of the font. + + The 'variant' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'small-caps', 'all-small-caps', + 'all-petite-caps', 'petite-caps', 'unicase'] + + Returns + ------- + Any + """ + return self["variant"] + + @variant.setter + def variant(self, val): + self["variant"] = val + + @property + def weight(self): + """ + Sets the weight (or boldness) of the font. + + The 'weight' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 1000] + OR exactly one of ['normal', 'bold'] (e.g. 'bold') + + Returns + ------- + int + """ + return self["weight"] + + @weight.setter + def weight(self, val): + self["weight"] = val + + @property + def _prop_descriptions(self): + return """\ + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + """ + + def __init__( + self, + arg=None, + color=None, + family=None, + lineposition=None, + shadow=None, + size=None, + style=None, + textcase=None, + variant=None, + weight=None, + **kwargs, + ): + """ + Construct a new Tickfont object + + Sets the font for the `category` labels. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.parcats.Tickfont` + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + + Returns + ------- + Tickfont + """ + super().__init__("tickfont") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcats.Tickfont +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcats.Tickfont`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("family", arg, family) + self._set_property("lineposition", arg, lineposition) + self._set_property("shadow", arg, shadow) + self._set_property("size", arg, size) + self._set_property("style", arg, style) + self._set_property("textcase", arg, textcase) + self._set_property("variant", arg, variant) + self._set_property("weight", arg, weight) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..53ed7641b1ca0717d0cbb019a90495a4103d54dc --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/__init__.py @@ -0,0 +1,34 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._dimension import Dimension + from ._domain import Domain + from ._labelfont import Labelfont + from ._legendgrouptitle import Legendgrouptitle + from ._line import Line + from ._rangefont import Rangefont + from ._stream import Stream + from ._tickfont import Tickfont + from ._unselected import Unselected + from . import legendgrouptitle + from . import line + from . import unselected +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [".legendgrouptitle", ".line", ".unselected"], + [ + "._dimension.Dimension", + "._domain.Domain", + "._labelfont.Labelfont", + "._legendgrouptitle.Legendgrouptitle", + "._line.Line", + "._rangefont.Rangefont", + "._stream.Stream", + "._tickfont.Tickfont", + "._unselected.Unselected", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_dimension.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_dimension.py new file mode 100644 index 0000000000000000000000000000000000000000..2fff5f12e3aa7141999066035a576dee45f96a98 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_dimension.py @@ -0,0 +1,546 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Dimension(_BaseTraceHierarchyType): + _parent_path_str = "parcoords" + _path_str = "parcoords.dimension" + _valid_props = { + "constraintrange", + "label", + "multiselect", + "name", + "range", + "templateitemname", + "tickformat", + "ticktext", + "ticktextsrc", + "tickvals", + "tickvalssrc", + "values", + "valuessrc", + "visible", + } + + @property + def constraintrange(self): + """ + The domain range to which the filter on the dimension is + constrained. Must be an array of `[fromValue, toValue]` with + `fromValue <= toValue`, or if `multiselect` is not disabled, + you may give an array of arrays, where each inner array is + `[fromValue, toValue]`. + + The 'constraintrange' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'constraintrange[0]' property accepts values of any type + (1) The 'constraintrange[1]' property accepts values of any type + + * a 2D list where: + (0) The 'constraintrange[i][0]' property accepts values of any type + (1) The 'constraintrange[i][1]' property accepts values of any type + + Returns + ------- + list + """ + return self["constraintrange"] + + @constraintrange.setter + def constraintrange(self, val): + self["constraintrange"] = val + + @property + def label(self): + """ + The shown name of the dimension. + + The 'label' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["label"] + + @label.setter + def label(self, val): + self["label"] = val + + @property + def multiselect(self): + """ + Do we allow multiple selection ranges or just a single range? + + The 'multiselect' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["multiselect"] + + @multiselect.setter + def multiselect(self, val): + self["multiselect"] = val + + @property + def name(self): + """ + When used in a template, named items are created in the output + figure in addition to any items the figure already has in this + array. You can modify these items in the output figure by + making your own item with `templateitemname` matching this + `name` alongside your modifications (including `visible: false` + or `enabled: false` to hide it). Has no effect outside of a + template. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def range(self): + """ + The domain range that represents the full, shown axis extent. + Defaults to the `values` extent. Must be an array of + `[fromValue, toValue]` with finite numbers as elements. + + The 'range' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'range[0]' property is a number and may be specified as: + - An int or float + (1) The 'range[1]' property is a number and may be specified as: + - An int or float + + Returns + ------- + list + """ + return self["range"] + + @range.setter + def range(self, val): + self["range"] = val + + @property + def templateitemname(self): + """ + Used to refer to a named item in this array in the template. + Named items from the template will be created even without a + matching item in the input figure, but you can modify one by + making an item with `templateitemname` matching its `name`, + alongside your modifications (including `visible: false` or + `enabled: false` to hide it). If there is no template or no + matching item, this item will be hidden unless you explicitly + show it with `visible: true`. + + The 'templateitemname' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["templateitemname"] + + @templateitemname.setter + def templateitemname(self, val): + self["templateitemname"] = val + + @property + def tickformat(self): + """ + Sets the tick label formatting rule using d3 formatting mini- + languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display "09~15~23.46" + + The 'tickformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["tickformat"] + + @tickformat.setter + def tickformat(self, val): + self["tickformat"] = val + + @property + def ticktext(self): + """ + Sets the text displayed at the ticks position via `tickvals`. + + The 'ticktext' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ticktext"] + + @ticktext.setter + def ticktext(self, val): + self["ticktext"] = val + + @property + def ticktextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ticktext`. + + The 'ticktextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ticktextsrc"] + + @ticktextsrc.setter + def ticktextsrc(self, val): + self["ticktextsrc"] = val + + @property + def tickvals(self): + """ + Sets the values at which ticks on this axis appear. + + The 'tickvals' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["tickvals"] + + @tickvals.setter + def tickvals(self, val): + self["tickvals"] = val + + @property + def tickvalssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `tickvals`. + + The 'tickvalssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["tickvalssrc"] + + @tickvalssrc.setter + def tickvalssrc(self, val): + self["tickvalssrc"] = val + + @property + def values(self): + """ + Dimension values. `values[n]` represents the value of the `n`th + point in the dataset, therefore the `values` vector for all + dimensions must be the same (longer vectors will be truncated). + Each value must be a finite number. + + The 'values' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["values"] + + @values.setter + def values(self, val): + self["values"] = val + + @property + def valuessrc(self): + """ + Sets the source reference on Chart Studio Cloud for `values`. + + The 'valuessrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["valuessrc"] + + @valuessrc.setter + def valuessrc(self, val): + self["valuessrc"] = val + + @property + def visible(self): + """ + Shows the dimension when set to `true` (the default). Hides the + dimension for `false`. + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def _prop_descriptions(self): + return """\ + constraintrange + The domain range to which the filter on the dimension + is constrained. Must be an array of `[fromValue, + toValue]` with `fromValue <= toValue`, or if + `multiselect` is not disabled, you may give an array of + arrays, where each inner array is `[fromValue, + toValue]`. + label + The shown name of the dimension. + multiselect + Do we allow multiple selection ranges or just a single + range? + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + range + The domain range that represents the full, shown axis + extent. Defaults to the `values` extent. Must be an + array of `[fromValue, toValue]` with finite numbers as + elements. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + ticktext + Sets the text displayed at the ticks position via + `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + values + Dimension values. `values[n]` represents the value of + the `n`th point in the dataset, therefore the `values` + vector for all dimensions must be the same (longer + vectors will be truncated). Each value must be a finite + number. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Shows the dimension when set to `true` (the default). + Hides the dimension for `false`. + """ + + def __init__( + self, + arg=None, + constraintrange=None, + label=None, + multiselect=None, + name=None, + range=None, + templateitemname=None, + tickformat=None, + ticktext=None, + ticktextsrc=None, + tickvals=None, + tickvalssrc=None, + values=None, + valuessrc=None, + visible=None, + **kwargs, + ): + """ + Construct a new Dimension object + + The dimensions (variables) of the parallel coordinates chart. + 2..60 dimensions are supported. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.parcoords.Dimension` + constraintrange + The domain range to which the filter on the dimension + is constrained. Must be an array of `[fromValue, + toValue]` with `fromValue <= toValue`, or if + `multiselect` is not disabled, you may give an array of + arrays, where each inner array is `[fromValue, + toValue]`. + label + The shown name of the dimension. + multiselect + Do we allow multiple selection ranges or just a single + range? + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + range + The domain range that represents the full, shown axis + extent. Defaults to the `values` extent. Must be an + array of `[fromValue, toValue]` with finite numbers as + elements. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + ticktext + Sets the text displayed at the ticks position via + `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + values + Dimension values. `values[n]` represents the value of + the `n`th point in the dataset, therefore the `values` + vector for all dimensions must be the same (longer + vectors will be truncated). Each value must be a finite + number. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Shows the dimension when set to `true` (the default). + Hides the dimension for `false`. + + Returns + ------- + Dimension + """ + super().__init__("dimensions") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcoords.Dimension +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcoords.Dimension`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("constraintrange", arg, constraintrange) + self._set_property("label", arg, label) + self._set_property("multiselect", arg, multiselect) + self._set_property("name", arg, name) + self._set_property("range", arg, range) + self._set_property("templateitemname", arg, templateitemname) + self._set_property("tickformat", arg, tickformat) + self._set_property("ticktext", arg, ticktext) + self._set_property("ticktextsrc", arg, ticktextsrc) + self._set_property("tickvals", arg, tickvals) + self._set_property("tickvalssrc", arg, tickvalssrc) + self._set_property("values", arg, values) + self._set_property("valuessrc", arg, valuessrc) + self._set_property("visible", arg, visible) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_domain.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_domain.py new file mode 100644 index 0000000000000000000000000000000000000000..a1b3f57bcd5a913cff7b53f8fd4d2e847485e885 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_domain.py @@ -0,0 +1,170 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Domain(_BaseTraceHierarchyType): + _parent_path_str = "parcoords" + _path_str = "parcoords.domain" + _valid_props = {"column", "row", "x", "y"} + + @property + def column(self): + """ + If there is a layout grid, use the domain for this column in + the grid for this parcoords trace . + + The 'column' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["column"] + + @column.setter + def column(self, val): + self["column"] = val + + @property + def row(self): + """ + If there is a layout grid, use the domain for this row in the + grid for this parcoords trace . + + The 'row' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["row"] + + @row.setter + def row(self, val): + self["row"] = val + + @property + def x(self): + """ + Sets the horizontal domain of this parcoords trace (in plot + fraction). + + The 'x' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'x[0]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + (1) The 'x[1]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + list + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def y(self): + """ + Sets the vertical domain of this parcoords trace (in plot + fraction). + + The 'y' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'y[0]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + (1) The 'y[1]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + list + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def _prop_descriptions(self): + return """\ + column + If there is a layout grid, use the domain for this + column in the grid for this parcoords trace . + row + If there is a layout grid, use the domain for this row + in the grid for this parcoords trace . + x + Sets the horizontal domain of this parcoords trace (in + plot fraction). + y + Sets the vertical domain of this parcoords trace (in + plot fraction). + """ + + def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): + """ + Construct a new Domain object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.parcoords.Domain` + column + If there is a layout grid, use the domain for this + column in the grid for this parcoords trace . + row + If there is a layout grid, use the domain for this row + in the grid for this parcoords trace . + x + Sets the horizontal domain of this parcoords trace (in + plot fraction). + y + Sets the vertical domain of this parcoords trace (in + plot fraction). + + Returns + ------- + Domain + """ + super().__init__("domain") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcoords.Domain +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcoords.Domain`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("column", arg, column) + self._set_property("row", arg, row) + self._set_property("x", arg, x) + self._set_property("y", arg, y) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_labelfont.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_labelfont.py new file mode 100644 index 0000000000000000000000000000000000000000..b73fe482fb18031888aca99f02c3e24c1e0b382c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_labelfont.py @@ -0,0 +1,334 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Labelfont(_BaseTraceHierarchyType): + _parent_path_str = "parcoords" + _path_str = "parcoords.labelfont" + _valid_props = { + "color", + "family", + "lineposition", + "shadow", + "size", + "style", + "textcase", + "variant", + "weight", + } + + @property + def color(self): + """ + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def family(self): + """ + HTML font family - the typeface that will be applied by the web + browser. The web browser can only apply a font if it is + available on the system where it runs. Provide multiple font + families, separated by commas, to indicate the order in which + to apply fonts if they aren't available. + + The 'family' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["family"] + + @family.setter + def family(self, val): + self["family"] = val + + @property + def lineposition(self): + """ + Sets the kind of decoration line(s) with text, such as an + "under", "over" or "through" as well as combinations e.g. + "under+over", etc. + + The 'lineposition' property is a flaglist and may be specified + as a string containing: + - Any combination of ['under', 'over', 'through'] joined with '+' characters + (e.g. 'under+over') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["lineposition"] + + @lineposition.setter + def lineposition(self, val): + self["lineposition"] = val + + @property + def shadow(self): + """ + Sets the shape and color of the shadow behind text. "auto" + places minimal shadow and applies contrast text font color. See + https://developer.mozilla.org/en-US/docs/Web/CSS/text-shadow + for additional options. + + The 'shadow' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["shadow"] + + @shadow.setter + def shadow(self, val): + self["shadow"] = val + + @property + def size(self): + """ + The 'size' property is a number and may be specified as: + - An int or float in the interval [1, inf] + + Returns + ------- + int|float + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def style(self): + """ + Sets whether a font should be styled with a normal or italic + face from its family. + + The 'style' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'italic'] + + Returns + ------- + Any + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def textcase(self): + """ + Sets capitalization of text. It can be used to make text appear + in all-uppercase or all-lowercase, or with each word + capitalized. + + The 'textcase' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'word caps', 'upper', 'lower'] + + Returns + ------- + Any + """ + return self["textcase"] + + @textcase.setter + def textcase(self, val): + self["textcase"] = val + + @property + def variant(self): + """ + Sets the variant of the font. + + The 'variant' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'small-caps', 'all-small-caps', + 'all-petite-caps', 'petite-caps', 'unicase'] + + Returns + ------- + Any + """ + return self["variant"] + + @variant.setter + def variant(self, val): + self["variant"] = val + + @property + def weight(self): + """ + Sets the weight (or boldness) of the font. + + The 'weight' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 1000] + OR exactly one of ['normal', 'bold'] (e.g. 'bold') + + Returns + ------- + int + """ + return self["weight"] + + @weight.setter + def weight(self, val): + self["weight"] = val + + @property + def _prop_descriptions(self): + return """\ + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + """ + + def __init__( + self, + arg=None, + color=None, + family=None, + lineposition=None, + shadow=None, + size=None, + style=None, + textcase=None, + variant=None, + weight=None, + **kwargs, + ): + """ + Construct a new Labelfont object + + Sets the font for the `dimension` labels. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.parcoords.Labelfont` + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + + Returns + ------- + Labelfont + """ + super().__init__("labelfont") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcoords.Labelfont +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcoords.Labelfont`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("family", arg, family) + self._set_property("lineposition", arg, lineposition) + self._set_property("shadow", arg, shadow) + self._set_property("size", arg, size) + self._set_property("style", arg, style) + self._set_property("textcase", arg, textcase) + self._set_property("variant", arg, variant) + self._set_property("weight", arg, weight) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..67462f33cbb601d208089a0e73336e4d3939fa85 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "parcoords" + _path_str = "parcoords.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcoords.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.parcoords.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.parcoords.Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcoords.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcoords.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_line.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_line.py new file mode 100644 index 0000000000000000000000000000000000000000..5d6799395d25879b452cdf2aa771ccd6423fdcaa --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_line.py @@ -0,0 +1,540 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Line(_BaseTraceHierarchyType): + _parent_path_str = "parcoords" + _path_str = "parcoords.line" + _valid_props = { + "autocolorscale", + "cauto", + "cmax", + "cmid", + "cmin", + "color", + "coloraxis", + "colorbar", + "colorscale", + "colorsrc", + "reversescale", + "showscale", + } + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `line.colorscale`. Has an effect only if in `line.color` is set + to a numerical array. In case `colorscale` is unspecified or + `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def cauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `line.color`) or the bounds + set in `line.cmin` and `line.cmax` Has an effect only if in + `line.color` is set to a numerical array. Defaults to `false` + when `line.cmin` and `line.cmax` are set by the user. + + The 'cauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cauto"] + + @cauto.setter + def cauto(self, val): + self["cauto"] = val + + @property + def cmax(self): + """ + Sets the upper bound of the color domain. Has an effect only if + in `line.color` is set to a numerical array. Value should have + the same units as in `line.color` and if set, `line.cmin` must + be set as well. + + The 'cmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmax"] + + @cmax.setter + def cmax(self, val): + self["cmax"] = val + + @property + def cmid(self): + """ + Sets the mid-point of the color domain by scaling `line.cmin` + and/or `line.cmax` to be equidistant to this point. Has an + effect only if in `line.color` is set to a numerical array. + Value should have the same units as in `line.color`. Has no + effect when `line.cauto` is `false`. + + The 'cmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmid"] + + @cmid.setter + def cmid(self, val): + self["cmid"] = val + + @property + def cmin(self): + """ + Sets the lower bound of the color domain. Has an effect only if + in `line.color` is set to a numerical array. Value should have + the same units as in `line.color` and if set, `line.cmax` must + be set as well. + + The 'cmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmin"] + + @cmin.setter + def cmin(self, val): + self["cmin"] = val + + @property + def color(self): + """ + Sets the line color. It accepts either a specific color or an + array of numbers that are mapped to the colorscale relative to + the max and min values of the array or relative to `line.cmin` + and `line.cmax` if set. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A number that will be interpreted as a color + according to parcoords.line.colorscale + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcoords.line.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.parcoords.line.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. Has an effect only if in `line.color` is + set to a numerical array. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, rgba, + hex, hsl, hsv, or named color string. At minimum, a mapping for + the lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To + control the bounds of the colorscale in color space, use + `line.cmin` and `line.cmax`. Alternatively, `colorscale` may be + a palette name string of the following list: Blackbody,Bluered, + Blues,Cividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic,Portla + nd,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def colorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `color`. + + The 'colorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["colorsrc"] + + @colorsrc.setter + def colorsrc(self, val): + self["colorsrc"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. Has an effect only if in + `line.color` is set to a numerical array. If true, `line.cmin` + will correspond to the last color in the array and `line.cmax` + will correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. Has an effect only if in `line.color` is set to a + numerical array. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def _prop_descriptions(self): + return """\ + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `line.colorscale`. Has an effect only if in + `line.color` is set to a numerical array. In case + `colorscale` is unspecified or `autocolorscale` is + true, the default palette will be chosen according to + whether numbers in the `color` array are all positive, + all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here in `line.color`) + or the bounds set in `line.cmin` and `line.cmax` Has an + effect only if in `line.color` is set to a numerical + array. Defaults to `false` when `line.cmin` and + `line.cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Has an effect + only if in `line.color` is set to a numerical array. + Value should have the same units as in `line.color` and + if set, `line.cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `line.cmin` and/or `line.cmax` to be equidistant to + this point. Has an effect only if in `line.color` is + set to a numerical array. Value should have the same + units as in `line.color`. Has no effect when + `line.cauto` is `false`. + cmin + Sets the lower bound of the color domain. Has an effect + only if in `line.color` is set to a numerical array. + Value should have the same units as in `line.color` and + if set, `line.cmax` must be set as well. + color + Sets the line color. It accepts either a specific color + or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `line.cmin` and `line.cmax` if + set. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.parcoords.line.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. Has an effect only if in + `line.color` is set to a numerical array. The + colorscale must be an array containing arrays mapping a + normalized value to an rgb, rgba, hex, hsl, hsv, or + named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. + To control the bounds of the colorscale in color space, + use `line.cmin` and `line.cmax`. Alternatively, + `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,E + lectric,Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,Rd + Bu,Reds,Viridis,YlGnBu,YlOrRd. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + reversescale + Reverses the color mapping if true. Has an effect only + if in `line.color` is set to a numerical array. If + true, `line.cmin` will correspond to the last color in + the array and `line.cmax` will correspond to the first + color. + showscale + Determines whether or not a colorbar is displayed for + this trace. Has an effect only if in `line.color` is + set to a numerical array. + """ + + def __init__( + self, + arg=None, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + color=None, + coloraxis=None, + colorbar=None, + colorscale=None, + colorsrc=None, + reversescale=None, + showscale=None, + **kwargs, + ): + """ + Construct a new Line object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.parcoords.Line` + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `line.colorscale`. Has an effect only if in + `line.color` is set to a numerical array. In case + `colorscale` is unspecified or `autocolorscale` is + true, the default palette will be chosen according to + whether numbers in the `color` array are all positive, + all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here in `line.color`) + or the bounds set in `line.cmin` and `line.cmax` Has an + effect only if in `line.color` is set to a numerical + array. Defaults to `false` when `line.cmin` and + `line.cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Has an effect + only if in `line.color` is set to a numerical array. + Value should have the same units as in `line.color` and + if set, `line.cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `line.cmin` and/or `line.cmax` to be equidistant to + this point. Has an effect only if in `line.color` is + set to a numerical array. Value should have the same + units as in `line.color`. Has no effect when + `line.cauto` is `false`. + cmin + Sets the lower bound of the color domain. Has an effect + only if in `line.color` is set to a numerical array. + Value should have the same units as in `line.color` and + if set, `line.cmax` must be set as well. + color + Sets the line color. It accepts either a specific color + or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `line.cmin` and `line.cmax` if + set. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.parcoords.line.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. Has an effect only if in + `line.color` is set to a numerical array. The + colorscale must be an array containing arrays mapping a + normalized value to an rgb, rgba, hex, hsl, hsv, or + named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. + To control the bounds of the colorscale in color space, + use `line.cmin` and `line.cmax`. Alternatively, + `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,E + lectric,Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,Rd + Bu,Reds,Viridis,YlGnBu,YlOrRd. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + reversescale + Reverses the color mapping if true. Has an effect only + if in `line.color` is set to a numerical array. If + true, `line.cmin` will correspond to the last color in + the array and `line.cmax` will correspond to the first + color. + showscale + Determines whether or not a colorbar is displayed for + this trace. Has an effect only if in `line.color` is + set to a numerical array. + + Returns + ------- + Line + """ + super().__init__("line") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcoords.Line +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcoords.Line`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("cauto", arg, cauto) + self._set_property("cmax", arg, cmax) + self._set_property("cmid", arg, cmid) + self._set_property("cmin", arg, cmin) + self._set_property("color", arg, color) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("colorsrc", arg, colorsrc) + self._set_property("reversescale", arg, reversescale) + self._set_property("showscale", arg, showscale) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_rangefont.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_rangefont.py new file mode 100644 index 0000000000000000000000000000000000000000..1e19ceff70fdafe2da9a315c8d977592593e7c10 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_rangefont.py @@ -0,0 +1,334 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Rangefont(_BaseTraceHierarchyType): + _parent_path_str = "parcoords" + _path_str = "parcoords.rangefont" + _valid_props = { + "color", + "family", + "lineposition", + "shadow", + "size", + "style", + "textcase", + "variant", + "weight", + } + + @property + def color(self): + """ + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def family(self): + """ + HTML font family - the typeface that will be applied by the web + browser. The web browser can only apply a font if it is + available on the system where it runs. Provide multiple font + families, separated by commas, to indicate the order in which + to apply fonts if they aren't available. + + The 'family' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["family"] + + @family.setter + def family(self, val): + self["family"] = val + + @property + def lineposition(self): + """ + Sets the kind of decoration line(s) with text, such as an + "under", "over" or "through" as well as combinations e.g. + "under+over", etc. + + The 'lineposition' property is a flaglist and may be specified + as a string containing: + - Any combination of ['under', 'over', 'through'] joined with '+' characters + (e.g. 'under+over') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["lineposition"] + + @lineposition.setter + def lineposition(self, val): + self["lineposition"] = val + + @property + def shadow(self): + """ + Sets the shape and color of the shadow behind text. "auto" + places minimal shadow and applies contrast text font color. See + https://developer.mozilla.org/en-US/docs/Web/CSS/text-shadow + for additional options. + + The 'shadow' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["shadow"] + + @shadow.setter + def shadow(self, val): + self["shadow"] = val + + @property + def size(self): + """ + The 'size' property is a number and may be specified as: + - An int or float in the interval [1, inf] + + Returns + ------- + int|float + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def style(self): + """ + Sets whether a font should be styled with a normal or italic + face from its family. + + The 'style' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'italic'] + + Returns + ------- + Any + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def textcase(self): + """ + Sets capitalization of text. It can be used to make text appear + in all-uppercase or all-lowercase, or with each word + capitalized. + + The 'textcase' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'word caps', 'upper', 'lower'] + + Returns + ------- + Any + """ + return self["textcase"] + + @textcase.setter + def textcase(self, val): + self["textcase"] = val + + @property + def variant(self): + """ + Sets the variant of the font. + + The 'variant' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'small-caps', 'all-small-caps', + 'all-petite-caps', 'petite-caps', 'unicase'] + + Returns + ------- + Any + """ + return self["variant"] + + @variant.setter + def variant(self, val): + self["variant"] = val + + @property + def weight(self): + """ + Sets the weight (or boldness) of the font. + + The 'weight' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 1000] + OR exactly one of ['normal', 'bold'] (e.g. 'bold') + + Returns + ------- + int + """ + return self["weight"] + + @weight.setter + def weight(self, val): + self["weight"] = val + + @property + def _prop_descriptions(self): + return """\ + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + """ + + def __init__( + self, + arg=None, + color=None, + family=None, + lineposition=None, + shadow=None, + size=None, + style=None, + textcase=None, + variant=None, + weight=None, + **kwargs, + ): + """ + Construct a new Rangefont object + + Sets the font for the `dimension` range values. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.parcoords.Rangefont` + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + + Returns + ------- + Rangefont + """ + super().__init__("rangefont") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcoords.Rangefont +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcoords.Rangefont`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("family", arg, family) + self._set_property("lineposition", arg, lineposition) + self._set_property("shadow", arg, shadow) + self._set_property("size", arg, size) + self._set_property("style", arg, style) + self._set_property("textcase", arg, textcase) + self._set_property("variant", arg, variant) + self._set_property("weight", arg, weight) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..a3753b10e5253a0a875dc847b955e3c9deccd848 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_stream.py @@ -0,0 +1,114 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "parcoords" + _path_str = "parcoords.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.parcoords.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcoords.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcoords.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_tickfont.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_tickfont.py new file mode 100644 index 0000000000000000000000000000000000000000..676f0ada3fbc3dcf79981221d281bc558ef88d13 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_tickfont.py @@ -0,0 +1,334 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Tickfont(_BaseTraceHierarchyType): + _parent_path_str = "parcoords" + _path_str = "parcoords.tickfont" + _valid_props = { + "color", + "family", + "lineposition", + "shadow", + "size", + "style", + "textcase", + "variant", + "weight", + } + + @property + def color(self): + """ + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def family(self): + """ + HTML font family - the typeface that will be applied by the web + browser. The web browser can only apply a font if it is + available on the system where it runs. Provide multiple font + families, separated by commas, to indicate the order in which + to apply fonts if they aren't available. + + The 'family' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["family"] + + @family.setter + def family(self, val): + self["family"] = val + + @property + def lineposition(self): + """ + Sets the kind of decoration line(s) with text, such as an + "under", "over" or "through" as well as combinations e.g. + "under+over", etc. + + The 'lineposition' property is a flaglist and may be specified + as a string containing: + - Any combination of ['under', 'over', 'through'] joined with '+' characters + (e.g. 'under+over') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["lineposition"] + + @lineposition.setter + def lineposition(self, val): + self["lineposition"] = val + + @property + def shadow(self): + """ + Sets the shape and color of the shadow behind text. "auto" + places minimal shadow and applies contrast text font color. See + https://developer.mozilla.org/en-US/docs/Web/CSS/text-shadow + for additional options. + + The 'shadow' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["shadow"] + + @shadow.setter + def shadow(self, val): + self["shadow"] = val + + @property + def size(self): + """ + The 'size' property is a number and may be specified as: + - An int or float in the interval [1, inf] + + Returns + ------- + int|float + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def style(self): + """ + Sets whether a font should be styled with a normal or italic + face from its family. + + The 'style' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'italic'] + + Returns + ------- + Any + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def textcase(self): + """ + Sets capitalization of text. It can be used to make text appear + in all-uppercase or all-lowercase, or with each word + capitalized. + + The 'textcase' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'word caps', 'upper', 'lower'] + + Returns + ------- + Any + """ + return self["textcase"] + + @textcase.setter + def textcase(self, val): + self["textcase"] = val + + @property + def variant(self): + """ + Sets the variant of the font. + + The 'variant' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'small-caps', 'all-small-caps', + 'all-petite-caps', 'petite-caps', 'unicase'] + + Returns + ------- + Any + """ + return self["variant"] + + @variant.setter + def variant(self, val): + self["variant"] = val + + @property + def weight(self): + """ + Sets the weight (or boldness) of the font. + + The 'weight' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 1000] + OR exactly one of ['normal', 'bold'] (e.g. 'bold') + + Returns + ------- + int + """ + return self["weight"] + + @weight.setter + def weight(self, val): + self["weight"] = val + + @property + def _prop_descriptions(self): + return """\ + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + """ + + def __init__( + self, + arg=None, + color=None, + family=None, + lineposition=None, + shadow=None, + size=None, + style=None, + textcase=None, + variant=None, + weight=None, + **kwargs, + ): + """ + Construct a new Tickfont object + + Sets the font for the `dimension` tick values. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.parcoords.Tickfont` + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + + Returns + ------- + Tickfont + """ + super().__init__("tickfont") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcoords.Tickfont +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcoords.Tickfont`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("family", arg, family) + self._set_property("lineposition", arg, lineposition) + self._set_property("shadow", arg, shadow) + self._set_property("size", arg, size) + self._set_property("style", arg, style) + self._set_property("textcase", arg, textcase) + self._set_property("variant", arg, variant) + self._set_property("weight", arg, weight) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_unselected.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_unselected.py new file mode 100644 index 0000000000000000000000000000000000000000..576feb6c24de6e455156e2265a19b20e7bb9e424 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/parcoords/_unselected.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Unselected(_BaseTraceHierarchyType): + _parent_path_str = "parcoords" + _path_str = "parcoords.unselected" + _valid_props = {"line"} + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.parcoords.unselected.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.parcoords.unselected.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def _prop_descriptions(self): + return """\ + line + :class:`plotly.graph_objects.parcoords.unselected.Line` + instance or dict with compatible properties + """ + + def __init__(self, arg=None, line=None, **kwargs): + """ + Construct a new Unselected object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.parcoords.Unselected` + line + :class:`plotly.graph_objects.parcoords.unselected.Line` + instance or dict with compatible properties + + Returns + ------- + Unselected + """ + super().__init__("unselected") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.parcoords.Unselected +constructor must be a dict or +an instance of :class:`plotly.graph_objs.parcoords.Unselected`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("line", arg, line) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..257626f79582e591bdc5602f9cdeee7c6c08b16c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/__init__.py @@ -0,0 +1,31 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._domain import Domain + from ._hoverlabel import Hoverlabel + from ._legendgrouptitle import Legendgrouptitle + from ._link import Link + from ._node import Node + from ._stream import Stream + from ._textfont import Textfont + from . import hoverlabel + from . import legendgrouptitle + from . import link + from . import node +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [".hoverlabel", ".legendgrouptitle", ".link", ".node"], + [ + "._domain.Domain", + "._hoverlabel.Hoverlabel", + "._legendgrouptitle.Legendgrouptitle", + "._link.Link", + "._node.Node", + "._stream.Stream", + "._textfont.Textfont", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_domain.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_domain.py new file mode 100644 index 0000000000000000000000000000000000000000..c86377e3b213e9baf511cce8afbc63ce198a6f8d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_domain.py @@ -0,0 +1,169 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Domain(_BaseTraceHierarchyType): + _parent_path_str = "sankey" + _path_str = "sankey.domain" + _valid_props = {"column", "row", "x", "y"} + + @property + def column(self): + """ + If there is a layout grid, use the domain for this column in + the grid for this sankey trace . + + The 'column' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["column"] + + @column.setter + def column(self, val): + self["column"] = val + + @property + def row(self): + """ + If there is a layout grid, use the domain for this row in the + grid for this sankey trace . + + The 'row' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["row"] + + @row.setter + def row(self, val): + self["row"] = val + + @property + def x(self): + """ + Sets the horizontal domain of this sankey trace (in plot + fraction). + + The 'x' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'x[0]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + (1) The 'x[1]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + list + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def y(self): + """ + Sets the vertical domain of this sankey trace (in plot + fraction). + + The 'y' property is an info array that may be specified as: + + * a list or tuple of 2 elements where: + (0) The 'y[0]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + (1) The 'y[1]' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + list + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def _prop_descriptions(self): + return """\ + column + If there is a layout grid, use the domain for this + column in the grid for this sankey trace . + row + If there is a layout grid, use the domain for this row + in the grid for this sankey trace . + x + Sets the horizontal domain of this sankey trace (in + plot fraction). + y + Sets the vertical domain of this sankey trace (in plot + fraction). + """ + + def __init__(self, arg=None, column=None, row=None, x=None, y=None, **kwargs): + """ + Construct a new Domain object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.sankey.Domain` + column + If there is a layout grid, use the domain for this + column in the grid for this sankey trace . + row + If there is a layout grid, use the domain for this row + in the grid for this sankey trace . + x + Sets the horizontal domain of this sankey trace (in + plot fraction). + y + Sets the vertical domain of this sankey trace (in plot + fraction). + + Returns + ------- + Domain + """ + super().__init__("domain") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.sankey.Domain +constructor must be a dict or +an instance of :class:`plotly.graph_objs.sankey.Domain`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("column", arg, column) + self._set_property("row", arg, row) + self._set_property("x", arg, x) + self._set_property("y", arg, y) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_hoverlabel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_hoverlabel.py new file mode 100644 index 0000000000000000000000000000000000000000..1050307088ca82b549b9c044077cf2da4baa08e3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_hoverlabel.py @@ -0,0 +1,366 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Hoverlabel(_BaseTraceHierarchyType): + _parent_path_str = "sankey" + _path_str = "sankey.hoverlabel" + _valid_props = { + "align", + "alignsrc", + "bgcolor", + "bgcolorsrc", + "bordercolor", + "bordercolorsrc", + "font", + "namelength", + "namelengthsrc", + "showarrow", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the text content within hover + label box. Has an effect only if the hover label text spans + more two or more lines + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'auto'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def alignsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `align`. + + The 'alignsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["alignsrc"] + + @alignsrc.setter + def alignsrc(self, val): + self["alignsrc"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the hover labels for this trace + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bgcolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `bgcolor`. + + The 'bgcolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bgcolorsrc"] + + @bgcolorsrc.setter + def bgcolorsrc(self, val): + self["bgcolorsrc"] = val + + @property + def bordercolor(self): + """ + Sets the border color of the hover labels for this trace. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def bordercolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + + The 'bordercolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bordercolorsrc"] + + @bordercolorsrc.setter + def bordercolorsrc(self, val): + self["bordercolorsrc"] = val + + @property + def font(self): + """ + Sets the font used in hover labels. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.sankey.hoverlabel.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.sankey.hoverlabel.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def namelength(self): + """ + Sets the default length (in number of characters) of the trace + name in the hover labels for all traces. -1 shows the whole + name regardless of length. 0-3 shows the first 0-3 characters, + and an integer >3 will show the whole name if it is less than + that many characters, but if it is longer, will truncate to + `namelength - 3` characters and add an ellipsis. + + The 'namelength' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["namelength"] + + @namelength.setter + def namelength(self, val): + self["namelength"] = val + + @property + def namelengthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `namelength`. + + The 'namelengthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["namelengthsrc"] + + @namelengthsrc.setter + def namelengthsrc(self, val): + self["namelengthsrc"] = val + + @property + def showarrow(self): + """ + Sets whether or not to show the hover label arrow/triangle + pointing to the data point. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + """ + + def __init__( + self, + arg=None, + align=None, + alignsrc=None, + bgcolor=None, + bgcolorsrc=None, + bordercolor=None, + bordercolorsrc=None, + font=None, + namelength=None, + namelengthsrc=None, + showarrow=None, + **kwargs, + ): + """ + Construct a new Hoverlabel object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.sankey.Hoverlabel` + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + + Returns + ------- + Hoverlabel + """ + super().__init__("hoverlabel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.sankey.Hoverlabel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.sankey.Hoverlabel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("alignsrc", arg, alignsrc) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bgcolorsrc", arg, bgcolorsrc) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("bordercolorsrc", arg, bordercolorsrc) + self._set_property("font", arg, font) + self._set_property("namelength", arg, namelength) + self._set_property("namelengthsrc", arg, namelengthsrc) + self._set_property("showarrow", arg, showarrow) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..8f024639ac43e07479a733d41292b532f339c78a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "sankey" + _path_str = "sankey.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.sankey.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.sankey.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.sankey.Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.sankey.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.sankey.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_link.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_link.py new file mode 100644 index 0000000000000000000000000000000000000000..df844e57973fac1746ec91dbbdc3fa014242973f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_link.py @@ -0,0 +1,828 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Link(_BaseTraceHierarchyType): + _parent_path_str = "sankey" + _path_str = "sankey.link" + _valid_props = { + "arrowlen", + "color", + "colorscaledefaults", + "colorscales", + "colorsrc", + "customdata", + "customdatasrc", + "hovercolor", + "hovercolorsrc", + "hoverinfo", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "label", + "labelsrc", + "line", + "source", + "sourcesrc", + "target", + "targetsrc", + "value", + "valuesrc", + } + + @property + def arrowlen(self): + """ + Sets the length (in px) of the links arrow, if 0 no arrow will + be drawn. + + The 'arrowlen' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["arrowlen"] + + @arrowlen.setter + def arrowlen(self, val): + self["arrowlen"] = val + + @property + def color(self): + """ + Sets the `link` color. It can be a single value, or an array + for specifying color for each `link`. If `link.color` is + omitted, then by default, a translucent grey link will be used. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def colorscales(self): + """ + The 'colorscales' property is a tuple of instances of + Colorscale that may be specified as: + - A list or tuple of instances of plotly.graph_objs.sankey.link.Colorscale + - A list or tuple of dicts of string/value properties that + will be passed to the Colorscale constructor + + Returns + ------- + tuple[plotly.graph_objs.sankey.link.Colorscale] + """ + return self["colorscales"] + + @colorscales.setter + def colorscales(self, val): + self["colorscales"] = val + + @property + def colorscaledefaults(self): + """ + When used in a template (as + layout.template.data.sankey.link.colorscaledefaults), sets the + default property values to use for elements of + sankey.link.colorscales + + The 'colorscaledefaults' property is an instance of Colorscale + that may be specified as: + - An instance of :class:`plotly.graph_objs.sankey.link.Colorscale` + - A dict of string/value properties that will be passed + to the Colorscale constructor + + Returns + ------- + plotly.graph_objs.sankey.link.Colorscale + """ + return self["colorscaledefaults"] + + @colorscaledefaults.setter + def colorscaledefaults(self, val): + self["colorscaledefaults"] = val + + @property + def colorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `color`. + + The 'colorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["colorsrc"] + + @colorsrc.setter + def colorsrc(self, val): + self["colorsrc"] = val + + @property + def customdata(self): + """ + Assigns extra data to each link. + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def hovercolor(self): + """ + Sets the `link` hover color. It can be a single value, or an + array for specifying hover colors for each `link`. If + `link.hovercolor` is omitted, then by default, links will + become slightly more opaque when hovered over. + + The 'hovercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovercolor"] + + @hovercolor.setter + def hovercolor(self, val): + self["hovercolor"] = val + + @property + def hovercolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovercolor`. + + The 'hovercolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovercolorsrc"] + + @hovercolorsrc.setter + def hovercolorsrc(self, val): + self["hovercolorsrc"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear when hovering links. + If `none` or `skip` are set, no information is displayed upon + hovering. But, if `none` is set, click and hover events are + still fired. + + The 'hoverinfo' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'none', 'skip'] + + Returns + ------- + Any + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.sankey.link.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.sankey.link.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables `value` + and `label`. Anything contained in tag `` is displayed + in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def label(self): + """ + The shown name of the link. + + The 'label' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["label"] + + @label.setter + def label(self, val): + self["label"] = val + + @property + def labelsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `label`. + + The 'labelsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["labelsrc"] + + @labelsrc.setter + def labelsrc(self, val): + self["labelsrc"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.sankey.link.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.sankey.link.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def source(self): + """ + An integer number `[0..nodes.length - 1]` that represents the + source node. + + The 'source' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["source"] + + @source.setter + def source(self, val): + self["source"] = val + + @property + def sourcesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `source`. + + The 'sourcesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["sourcesrc"] + + @sourcesrc.setter + def sourcesrc(self, val): + self["sourcesrc"] = val + + @property + def target(self): + """ + An integer number `[0..nodes.length - 1]` that represents the + target node. + + The 'target' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["target"] + + @target.setter + def target(self, val): + self["target"] = val + + @property + def targetsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `target`. + + The 'targetsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["targetsrc"] + + @targetsrc.setter + def targetsrc(self, val): + self["targetsrc"] = val + + @property + def value(self): + """ + A numeric value representing the flow volume value. + + The 'value' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["value"] + + @value.setter + def value(self, val): + self["value"] = val + + @property + def valuesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `value`. + + The 'valuesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["valuesrc"] + + @valuesrc.setter + def valuesrc(self, val): + self["valuesrc"] = val + + @property + def _prop_descriptions(self): + return """\ + arrowlen + Sets the length (in px) of the links arrow, if 0 no + arrow will be drawn. + color + Sets the `link` color. It can be a single value, or an + array for specifying color for each `link`. If + `link.color` is omitted, then by default, a translucent + grey link will be used. + colorscales + A tuple of + :class:`plotly.graph_objects.sankey.link.Colorscale` + instances or dicts with compatible properties + colorscaledefaults + When used in a template (as + layout.template.data.sankey.link.colorscaledefaults), + sets the default property values to use for elements of + sankey.link.colorscales + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + customdata + Assigns extra data to each link. + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hovercolor + Sets the `link` hover color. It can be a single value, + or an array for specifying hover colors for each + `link`. If `link.hovercolor` is omitted, then by + default, links will become slightly more opaque when + hovered over. + hovercolorsrc + Sets the source reference on Chart Studio Cloud for + `hovercolor`. + hoverinfo + Determines which trace information appear when hovering + links. If `none` or `skip` are set, no information is + displayed upon hovering. But, if `none` is set, click + and hover events are still fired. + hoverlabel + :class:`plotly.graph_objects.sankey.link.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `value` and `label`. Anything contained in + tag `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + label + The shown name of the link. + labelsrc + Sets the source reference on Chart Studio Cloud for + `label`. + line + :class:`plotly.graph_objects.sankey.link.Line` instance + or dict with compatible properties + source + An integer number `[0..nodes.length - 1]` that + represents the source node. + sourcesrc + Sets the source reference on Chart Studio Cloud for + `source`. + target + An integer number `[0..nodes.length - 1]` that + represents the target node. + targetsrc + Sets the source reference on Chart Studio Cloud for + `target`. + value + A numeric value representing the flow volume value. + valuesrc + Sets the source reference on Chart Studio Cloud for + `value`. + """ + + def __init__( + self, + arg=None, + arrowlen=None, + color=None, + colorscales=None, + colorscaledefaults=None, + colorsrc=None, + customdata=None, + customdatasrc=None, + hovercolor=None, + hovercolorsrc=None, + hoverinfo=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + label=None, + labelsrc=None, + line=None, + source=None, + sourcesrc=None, + target=None, + targetsrc=None, + value=None, + valuesrc=None, + **kwargs, + ): + """ + Construct a new Link object + + The links of the Sankey plot. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.sankey.Link` + arrowlen + Sets the length (in px) of the links arrow, if 0 no + arrow will be drawn. + color + Sets the `link` color. It can be a single value, or an + array for specifying color for each `link`. If + `link.color` is omitted, then by default, a translucent + grey link will be used. + colorscales + A tuple of + :class:`plotly.graph_objects.sankey.link.Colorscale` + instances or dicts with compatible properties + colorscaledefaults + When used in a template (as + layout.template.data.sankey.link.colorscaledefaults), + sets the default property values to use for elements of + sankey.link.colorscales + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + customdata + Assigns extra data to each link. + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + hovercolor + Sets the `link` hover color. It can be a single value, + or an array for specifying hover colors for each + `link`. If `link.hovercolor` is omitted, then by + default, links will become slightly more opaque when + hovered over. + hovercolorsrc + Sets the source reference on Chart Studio Cloud for + `hovercolor`. + hoverinfo + Determines which trace information appear when hovering + links. If `none` or `skip` are set, no information is + displayed upon hovering. But, if `none` is set, click + and hover events are still fired. + hoverlabel + :class:`plotly.graph_objects.sankey.link.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `value` and `label`. Anything contained in + tag `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + label + The shown name of the link. + labelsrc + Sets the source reference on Chart Studio Cloud for + `label`. + line + :class:`plotly.graph_objects.sankey.link.Line` instance + or dict with compatible properties + source + An integer number `[0..nodes.length - 1]` that + represents the source node. + sourcesrc + Sets the source reference on Chart Studio Cloud for + `source`. + target + An integer number `[0..nodes.length - 1]` that + represents the target node. + targetsrc + Sets the source reference on Chart Studio Cloud for + `target`. + value + A numeric value representing the flow volume value. + valuesrc + Sets the source reference on Chart Studio Cloud for + `value`. + + Returns + ------- + Link + """ + super().__init__("link") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.sankey.Link +constructor must be a dict or +an instance of :class:`plotly.graph_objs.sankey.Link`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("arrowlen", arg, arrowlen) + self._set_property("color", arg, color) + self._set_property("colorscales", arg, colorscales) + self._set_property("colorscaledefaults", arg, colorscaledefaults) + self._set_property("colorsrc", arg, colorsrc) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("hovercolor", arg, hovercolor) + self._set_property("hovercolorsrc", arg, hovercolorsrc) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("label", arg, label) + self._set_property("labelsrc", arg, labelsrc) + self._set_property("line", arg, line) + self._set_property("source", arg, source) + self._set_property("sourcesrc", arg, sourcesrc) + self._set_property("target", arg, target) + self._set_property("targetsrc", arg, targetsrc) + self._set_property("value", arg, value) + self._set_property("valuesrc", arg, valuesrc) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_node.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_node.py new file mode 100644 index 0000000000000000000000000000000000000000..94a1baa231800e155f754fe7068bfe53386ab0d4 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_node.py @@ -0,0 +1,725 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Node(_BaseTraceHierarchyType): + _parent_path_str = "sankey" + _path_str = "sankey.node" + _valid_props = { + "align", + "color", + "colorsrc", + "customdata", + "customdatasrc", + "groups", + "hoverinfo", + "hoverlabel", + "hovertemplate", + "hovertemplatefallback", + "hovertemplatesrc", + "label", + "labelsrc", + "line", + "pad", + "thickness", + "x", + "xsrc", + "y", + "ysrc", + } + + @property + def align(self): + """ + Sets the alignment method used to position the nodes along the + horizontal axis. + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['justify', 'left', 'right', 'center'] + + Returns + ------- + Any + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def color(self): + """ + Sets the `node` color. It can be a single value, or an array + for specifying color for each `node`. If `node.color` is + omitted, then the default `Plotly` color palette will be cycled + through to have a variety of colors. These defaults are not + fully opaque, to allow some visibility of what is beneath the + node. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def colorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `color`. + + The 'colorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["colorsrc"] + + @colorsrc.setter + def colorsrc(self, val): + self["colorsrc"] = val + + @property + def customdata(self): + """ + Assigns extra data to each node. + + The 'customdata' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["customdata"] + + @customdata.setter + def customdata(self, val): + self["customdata"] = val + + @property + def customdatasrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `customdata`. + + The 'customdatasrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["customdatasrc"] + + @customdatasrc.setter + def customdatasrc(self, val): + self["customdatasrc"] = val + + @property + def groups(self): + """ + Groups of nodes. Each group is defined by an array with the + indices of the nodes it contains. Multiple groups can be + specified. + + The 'groups' property is an info array that may be specified as: + * a 2D list where: + The 'groups[i][j]' property is a number and may be specified as: + - An int or float + + Returns + ------- + list + """ + return self["groups"] + + @groups.setter + def groups(self, val): + self["groups"] = val + + @property + def hoverinfo(self): + """ + Determines which trace information appear when hovering nodes. + If `none` or `skip` are set, no information is displayed upon + hovering. But, if `none` is set, click and hover events are + still fired. + + The 'hoverinfo' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'none', 'skip'] + + Returns + ------- + Any + """ + return self["hoverinfo"] + + @hoverinfo.setter + def hoverinfo(self, val): + self["hoverinfo"] = val + + @property + def hoverlabel(self): + """ + The 'hoverlabel' property is an instance of Hoverlabel + that may be specified as: + - An instance of :class:`plotly.graph_objs.sankey.node.Hoverlabel` + - A dict of string/value properties that will be passed + to the Hoverlabel constructor + + Returns + ------- + plotly.graph_objs.sankey.node.Hoverlabel + """ + return self["hoverlabel"] + + @hoverlabel.setter + def hoverlabel(self, val): + self["hoverlabel"] = val + + @property + def hovertemplate(self): + """ + Template string used for rendering the information that appear + on hover box. Note that this will override `hoverinfo`. + Variables are inserted using %{variable}, for example "y: %{y}" + as well as %{xother}, {%_xother}, {%_xother_}, {%xother_}. When + showing info for several points, "xother" will be added to + those with different x positions from the first point. An + underscore before or after "(x|y)other" will add a space on + that side, only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for example + "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format for + details on the formatting syntax. Dates are formatted using + d3-time-format's syntax %{variable|d3-time-format}, for example + "Day: %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the date + formatting syntax. Variables that can't be found will be + replaced with the specifier. For example, a template of "data: + %{x}, %{y}" will result in a value of "data: 1, %{y}" if x is 1 + and y is missing. Variables with an undefined value will be + replaced with the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data described at + this link https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be specified per- + point (the ones that are `arrayOk: true`) are available. + Finally, the template string has access to variables `value` + and `label`. Anything contained in tag `` is displayed + in the secondary box, for example + `%{fullData.name}`. To hide the secondary box + completely, use an empty tag ``. + + The 'hovertemplate' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["hovertemplate"] + + @hovertemplate.setter + def hovertemplate(self, val): + self["hovertemplate"] = val + + @property + def hovertemplatefallback(self): + """ + Fallback string that's displayed when a variable referenced in + a template is missing. If the boolean value 'false' is passed + in, the specifier with the missing variable will be displayed. + + The 'hovertemplatefallback' property accepts values of any type + + Returns + ------- + Any + """ + return self["hovertemplatefallback"] + + @hovertemplatefallback.setter + def hovertemplatefallback(self, val): + self["hovertemplatefallback"] = val + + @property + def hovertemplatesrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + + The 'hovertemplatesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["hovertemplatesrc"] + + @hovertemplatesrc.setter + def hovertemplatesrc(self, val): + self["hovertemplatesrc"] = val + + @property + def label(self): + """ + The shown name of the node. + + The 'label' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["label"] + + @label.setter + def label(self, val): + self["label"] = val + + @property + def labelsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `label`. + + The 'labelsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["labelsrc"] + + @labelsrc.setter + def labelsrc(self, val): + self["labelsrc"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.sankey.node.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.sankey.node.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def pad(self): + """ + Sets the padding (in px) between the `nodes`. + + The 'pad' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["pad"] + + @pad.setter + def pad(self, val): + self["pad"] = val + + @property + def thickness(self): + """ + Sets the thickness (in px) of the `nodes`. + + The 'thickness' property is a number and may be specified as: + - An int or float in the interval [1, inf] + + Returns + ------- + int|float + """ + return self["thickness"] + + @thickness.setter + def thickness(self, val): + self["thickness"] = val + + @property + def x(self): + """ + The normalized horizontal position of the node. + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + The normalized vertical position of the node. + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the alignment method used to position the nodes + along the horizontal axis. + color + Sets the `node` color. It can be a single value, or an + array for specifying color for each `node`. If + `node.color` is omitted, then the default `Plotly` + color palette will be cycled through to have a variety + of colors. These defaults are not fully opaque, to + allow some visibility of what is beneath the node. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + customdata + Assigns extra data to each node. + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + groups + Groups of nodes. Each group is defined by an array with + the indices of the nodes it contains. Multiple groups + can be specified. + hoverinfo + Determines which trace information appear when hovering + nodes. If `none` or `skip` are set, no information is + displayed upon hovering. But, if `none` is set, click + and hover events are still fired. + hoverlabel + :class:`plotly.graph_objects.sankey.node.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `value` and `label`. Anything contained in + tag `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + label + The shown name of the node. + labelsrc + Sets the source reference on Chart Studio Cloud for + `label`. + line + :class:`plotly.graph_objects.sankey.node.Line` instance + or dict with compatible properties + pad + Sets the padding (in px) between the `nodes`. + thickness + Sets the thickness (in px) of the `nodes`. + x + The normalized horizontal position of the node. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + The normalized vertical position of the node. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + """ + + def __init__( + self, + arg=None, + align=None, + color=None, + colorsrc=None, + customdata=None, + customdatasrc=None, + groups=None, + hoverinfo=None, + hoverlabel=None, + hovertemplate=None, + hovertemplatefallback=None, + hovertemplatesrc=None, + label=None, + labelsrc=None, + line=None, + pad=None, + thickness=None, + x=None, + xsrc=None, + y=None, + ysrc=None, + **kwargs, + ): + """ + Construct a new Node object + + The nodes of the Sankey plot. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.sankey.Node` + align + Sets the alignment method used to position the nodes + along the horizontal axis. + color + Sets the `node` color. It can be a single value, or an + array for specifying color for each `node`. If + `node.color` is omitted, then the default `Plotly` + color palette will be cycled through to have a variety + of colors. These defaults are not fully opaque, to + allow some visibility of what is beneath the node. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + customdata + Assigns extra data to each node. + customdatasrc + Sets the source reference on Chart Studio Cloud for + `customdata`. + groups + Groups of nodes. Each group is defined by an array with + the indices of the nodes it contains. Multiple groups + can be specified. + hoverinfo + Determines which trace information appear when hovering + nodes. If `none` or `skip` are set, no information is + displayed upon hovering. But, if `none` is set, click + and hover events are still fired. + hoverlabel + :class:`plotly.graph_objects.sankey.node.Hoverlabel` + instance or dict with compatible properties + hovertemplate + Template string used for rendering the information that + appear on hover box. Note that this will override + `hoverinfo`. Variables are inserted using %{variable}, + for example "y: %{y}" as well as %{xother}, {%_xother}, + {%_xother_}, {%xother_}. When showing info for several + points, "xother" will be added to those with different + x positions from the first point. An underscore before + or after "(x|y)other" will add a space on that side, + only when this field is shown. Numbers are formatted + using d3-format's syntax %{variable:d3-format}, for + example "Price: %{y:$.2f}". + https://github.com/d3/d3-format/tree/v1.4.5#d3-format + for details on the formatting syntax. Dates are + formatted using d3-time-format's syntax + %{variable|d3-time-format}, for example "Day: + %{2019-01-01|%A}". https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format for details on the + date formatting syntax. Variables that can't be found + will be replaced with the specifier. For example, a + template of "data: %{x}, %{y}" will result in a value + of "data: 1, %{y}" if x is 1 and y is missing. + Variables with an undefined value will be replaced with + the fallback value. The variables available in + `hovertemplate` are the ones emitted as event data + described at this link + https://plotly.com/javascript/plotlyjs-events/#event- + data. Additionally, all attributes that can be + specified per-point (the ones that are `arrayOk: true`) + are available. Finally, the template string has access + to variables `value` and `label`. Anything contained in + tag `` is displayed in the secondary box, for + example `%{fullData.name}`. To hide the + secondary box completely, use an empty tag + ``. + hovertemplatefallback + Fallback string that's displayed when a variable + referenced in a template is missing. If the boolean + value 'false' is passed in, the specifier with the + missing variable will be displayed. + hovertemplatesrc + Sets the source reference on Chart Studio Cloud for + `hovertemplate`. + label + The shown name of the node. + labelsrc + Sets the source reference on Chart Studio Cloud for + `label`. + line + :class:`plotly.graph_objects.sankey.node.Line` instance + or dict with compatible properties + pad + Sets the padding (in px) between the `nodes`. + thickness + Sets the thickness (in px) of the `nodes`. + x + The normalized horizontal position of the node. + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + The normalized vertical position of the node. + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + + Returns + ------- + Node + """ + super().__init__("node") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.sankey.Node +constructor must be a dict or +an instance of :class:`plotly.graph_objs.sankey.Node`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("color", arg, color) + self._set_property("colorsrc", arg, colorsrc) + self._set_property("customdata", arg, customdata) + self._set_property("customdatasrc", arg, customdatasrc) + self._set_property("groups", arg, groups) + self._set_property("hoverinfo", arg, hoverinfo) + self._set_property("hoverlabel", arg, hoverlabel) + self._set_property("hovertemplate", arg, hovertemplate) + self._set_property("hovertemplatefallback", arg, hovertemplatefallback) + self._set_property("hovertemplatesrc", arg, hovertemplatesrc) + self._set_property("label", arg, label) + self._set_property("labelsrc", arg, labelsrc) + self._set_property("line", arg, line) + self._set_property("pad", arg, pad) + self._set_property("thickness", arg, thickness) + self._set_property("x", arg, x) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("ysrc", arg, ysrc) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..542d7c1f8eae00f1724586d638786bea458f2cdd --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_stream.py @@ -0,0 +1,113 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "sankey" + _path_str = "sankey.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.sankey.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.sankey.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.sankey.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_textfont.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_textfont.py new file mode 100644 index 0000000000000000000000000000000000000000..d052501252e58014b647901c26e2e3c1ff3d96ba --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/sankey/_textfont.py @@ -0,0 +1,334 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Textfont(_BaseTraceHierarchyType): + _parent_path_str = "sankey" + _path_str = "sankey.textfont" + _valid_props = { + "color", + "family", + "lineposition", + "shadow", + "size", + "style", + "textcase", + "variant", + "weight", + } + + @property + def color(self): + """ + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def family(self): + """ + HTML font family - the typeface that will be applied by the web + browser. The web browser can only apply a font if it is + available on the system where it runs. Provide multiple font + families, separated by commas, to indicate the order in which + to apply fonts if they aren't available. + + The 'family' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["family"] + + @family.setter + def family(self, val): + self["family"] = val + + @property + def lineposition(self): + """ + Sets the kind of decoration line(s) with text, such as an + "under", "over" or "through" as well as combinations e.g. + "under+over", etc. + + The 'lineposition' property is a flaglist and may be specified + as a string containing: + - Any combination of ['under', 'over', 'through'] joined with '+' characters + (e.g. 'under+over') + OR exactly one of ['none'] (e.g. 'none') + + Returns + ------- + Any + """ + return self["lineposition"] + + @lineposition.setter + def lineposition(self, val): + self["lineposition"] = val + + @property + def shadow(self): + """ + Sets the shape and color of the shadow behind text. "auto" + places minimal shadow and applies contrast text font color. See + https://developer.mozilla.org/en-US/docs/Web/CSS/text-shadow + for additional options. + + The 'shadow' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["shadow"] + + @shadow.setter + def shadow(self, val): + self["shadow"] = val + + @property + def size(self): + """ + The 'size' property is a number and may be specified as: + - An int or float in the interval [1, inf] + + Returns + ------- + int|float + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def style(self): + """ + Sets whether a font should be styled with a normal or italic + face from its family. + + The 'style' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'italic'] + + Returns + ------- + Any + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def textcase(self): + """ + Sets capitalization of text. It can be used to make text appear + in all-uppercase or all-lowercase, or with each word + capitalized. + + The 'textcase' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'word caps', 'upper', 'lower'] + + Returns + ------- + Any + """ + return self["textcase"] + + @textcase.setter + def textcase(self, val): + self["textcase"] = val + + @property + def variant(self): + """ + Sets the variant of the font. + + The 'variant' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'small-caps', 'all-small-caps', + 'all-petite-caps', 'petite-caps', 'unicase'] + + Returns + ------- + Any + """ + return self["variant"] + + @variant.setter + def variant(self, val): + self["variant"] = val + + @property + def weight(self): + """ + Sets the weight (or boldness) of the font. + + The 'weight' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 1000] + OR exactly one of ['normal', 'bold'] (e.g. 'bold') + + Returns + ------- + int + """ + return self["weight"] + + @weight.setter + def weight(self, val): + self["weight"] = val + + @property + def _prop_descriptions(self): + return """\ + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + """ + + def __init__( + self, + arg=None, + color=None, + family=None, + lineposition=None, + shadow=None, + size=None, + style=None, + textcase=None, + variant=None, + weight=None, + **kwargs, + ): + """ + Construct a new Textfont object + + Sets the font for node labels + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.sankey.Textfont` + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + variant + Sets the variant of the font. + weight + Sets the weight (or boldness) of the font. + + Returns + ------- + Textfont + """ + super().__init__("textfont") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.sankey.Textfont +constructor must be a dict or +an instance of :class:`plotly.graph_objs.sankey.Textfont`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("family", arg, family) + self._set_property("lineposition", arg, lineposition) + self._set_property("shadow", arg, shadow) + self._set_property("size", arg, size) + self._set_property("style", arg, style) + self._set_property("textcase", arg, textcase) + self._set_property("variant", arg, variant) + self._set_property("weight", arg, weight) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..f3ca4ee76d5ae2ac6955dd9c58fbe80b51819334 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/__init__.py @@ -0,0 +1,38 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._error_x import ErrorX + from ._error_y import ErrorY + from ._hoverlabel import Hoverlabel + from ._legendgrouptitle import Legendgrouptitle + from ._line import Line + from ._marker import Marker + from ._selected import Selected + from ._stream import Stream + from ._textfont import Textfont + from ._unselected import Unselected + from . import hoverlabel + from . import legendgrouptitle + from . import marker + from . import selected + from . import unselected +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [".hoverlabel", ".legendgrouptitle", ".marker", ".selected", ".unselected"], + [ + "._error_x.ErrorX", + "._error_y.ErrorY", + "._hoverlabel.Hoverlabel", + "._legendgrouptitle.Legendgrouptitle", + "._line.Line", + "._marker.Marker", + "._selected.Selected", + "._stream.Stream", + "._textfont.Textfont", + "._unselected.Unselected", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_error_x.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_error_x.py new file mode 100644 index 0000000000000000000000000000000000000000..2cb27d7b8a5ba15f0fcdc86056c728da742933a2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_error_x.py @@ -0,0 +1,503 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class ErrorX(_BaseTraceHierarchyType): + _parent_path_str = "scattergl" + _path_str = "scattergl.error_x" + _valid_props = { + "array", + "arrayminus", + "arrayminussrc", + "arraysrc", + "color", + "copy_ystyle", + "symmetric", + "thickness", + "traceref", + "tracerefminus", + "type", + "value", + "valueminus", + "visible", + "width", + } + + @property + def array(self): + """ + Sets the data corresponding the length of each error bar. + Values are plotted relative to the underlying data. + + The 'array' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["array"] + + @array.setter + def array(self, val): + self["array"] = val + + @property + def arrayminus(self): + """ + Sets the data corresponding the length of each error bar in the + bottom (left) direction for vertical (horizontal) bars Values + are plotted relative to the underlying data. + + The 'arrayminus' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["arrayminus"] + + @arrayminus.setter + def arrayminus(self, val): + self["arrayminus"] = val + + @property + def arrayminussrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `arrayminus`. + + The 'arrayminussrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["arrayminussrc"] + + @arrayminussrc.setter + def arrayminussrc(self, val): + self["arrayminussrc"] = val + + @property + def arraysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `array`. + + The 'arraysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["arraysrc"] + + @arraysrc.setter + def arraysrc(self, val): + self["arraysrc"] = val + + @property + def color(self): + """ + Sets the stroke color of the error bars. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def copy_ystyle(self): + """ + The 'copy_ystyle' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["copy_ystyle"] + + @copy_ystyle.setter + def copy_ystyle(self, val): + self["copy_ystyle"] = val + + @property + def symmetric(self): + """ + Determines whether or not the error bars have the same length + in both direction (top/bottom for vertical bars, left/right for + horizontal bars. + + The 'symmetric' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["symmetric"] + + @symmetric.setter + def symmetric(self, val): + self["symmetric"] = val + + @property + def thickness(self): + """ + Sets the thickness (in px) of the error bars. + + The 'thickness' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["thickness"] + + @thickness.setter + def thickness(self, val): + self["thickness"] = val + + @property + def traceref(self): + """ + The 'traceref' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["traceref"] + + @traceref.setter + def traceref(self, val): + self["traceref"] = val + + @property + def tracerefminus(self): + """ + The 'tracerefminus' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["tracerefminus"] + + @tracerefminus.setter + def tracerefminus(self, val): + self["tracerefminus"] = val + + @property + def type(self): + """ + Determines the rule used to generate the error bars. If + "constant", the bar lengths are of a constant value. Set this + constant in `value`. If "percent", the bar lengths correspond + to a percentage of underlying data. Set this percentage in + `value`. If "sqrt", the bar lengths correspond to the square of + the underlying data. If "data", the bar lengths are set with + data set `array`. + + The 'type' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['percent', 'constant', 'sqrt', 'data'] + + Returns + ------- + Any + """ + return self["type"] + + @type.setter + def type(self, val): + self["type"] = val + + @property + def value(self): + """ + Sets the value of either the percentage (if `type` is set to + "percent") or the constant (if `type` is set to "constant") + corresponding to the lengths of the error bars. + + The 'value' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["value"] + + @value.setter + def value(self, val): + self["value"] = val + + @property + def valueminus(self): + """ + Sets the value of either the percentage (if `type` is set to + "percent") or the constant (if `type` is set to "constant") + corresponding to the lengths of the error bars in the bottom + (left) direction for vertical (horizontal) bars + + The 'valueminus' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["valueminus"] + + @valueminus.setter + def valueminus(self, val): + self["valueminus"] = val + + @property + def visible(self): + """ + Determines whether or not this set of error bars is visible. + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def width(self): + """ + Sets the width (in px) of the cross-bar at both ends of the + error bars. + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def _prop_descriptions(self): + return """\ + array + Sets the data corresponding the length of each error + bar. Values are plotted relative to the underlying + data. + arrayminus + Sets the data corresponding the length of each error + bar in the bottom (left) direction for vertical + (horizontal) bars Values are plotted relative to the + underlying data. + arrayminussrc + Sets the source reference on Chart Studio Cloud for + `arrayminus`. + arraysrc + Sets the source reference on Chart Studio Cloud for + `array`. + color + Sets the stroke color of the error bars. + copy_ystyle + + symmetric + Determines whether or not the error bars have the same + length in both direction (top/bottom for vertical bars, + left/right for horizontal bars. + thickness + Sets the thickness (in px) of the error bars. + traceref + + tracerefminus + + type + Determines the rule used to generate the error bars. If + "constant", the bar lengths are of a constant value. + Set this constant in `value`. If "percent", the bar + lengths correspond to a percentage of underlying data. + Set this percentage in `value`. If "sqrt", the bar + lengths correspond to the square of the underlying + data. If "data", the bar lengths are set with data set + `array`. + value + Sets the value of either the percentage (if `type` is + set to "percent") or the constant (if `type` is set to + "constant") corresponding to the lengths of the error + bars. + valueminus + Sets the value of either the percentage (if `type` is + set to "percent") or the constant (if `type` is set to + "constant") corresponding to the lengths of the error + bars in the bottom (left) direction for vertical + (horizontal) bars + visible + Determines whether or not this set of error bars is + visible. + width + Sets the width (in px) of the cross-bar at both ends of + the error bars. + """ + + def __init__( + self, + arg=None, + array=None, + arrayminus=None, + arrayminussrc=None, + arraysrc=None, + color=None, + copy_ystyle=None, + symmetric=None, + thickness=None, + traceref=None, + tracerefminus=None, + type=None, + value=None, + valueminus=None, + visible=None, + width=None, + **kwargs, + ): + """ + Construct a new ErrorX object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattergl.ErrorX` + array + Sets the data corresponding the length of each error + bar. Values are plotted relative to the underlying + data. + arrayminus + Sets the data corresponding the length of each error + bar in the bottom (left) direction for vertical + (horizontal) bars Values are plotted relative to the + underlying data. + arrayminussrc + Sets the source reference on Chart Studio Cloud for + `arrayminus`. + arraysrc + Sets the source reference on Chart Studio Cloud for + `array`. + color + Sets the stroke color of the error bars. + copy_ystyle + + symmetric + Determines whether or not the error bars have the same + length in both direction (top/bottom for vertical bars, + left/right for horizontal bars. + thickness + Sets the thickness (in px) of the error bars. + traceref + + tracerefminus + + type + Determines the rule used to generate the error bars. If + "constant", the bar lengths are of a constant value. + Set this constant in `value`. If "percent", the bar + lengths correspond to a percentage of underlying data. + Set this percentage in `value`. If "sqrt", the bar + lengths correspond to the square of the underlying + data. If "data", the bar lengths are set with data set + `array`. + value + Sets the value of either the percentage (if `type` is + set to "percent") or the constant (if `type` is set to + "constant") corresponding to the lengths of the error + bars. + valueminus + Sets the value of either the percentage (if `type` is + set to "percent") or the constant (if `type` is set to + "constant") corresponding to the lengths of the error + bars in the bottom (left) direction for vertical + (horizontal) bars + visible + Determines whether or not this set of error bars is + visible. + width + Sets the width (in px) of the cross-bar at both ends of + the error bars. + + Returns + ------- + ErrorX + """ + super().__init__("error_x") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattergl.ErrorX +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattergl.ErrorX`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("array", arg, array) + self._set_property("arrayminus", arg, arrayminus) + self._set_property("arrayminussrc", arg, arrayminussrc) + self._set_property("arraysrc", arg, arraysrc) + self._set_property("color", arg, color) + self._set_property("copy_ystyle", arg, copy_ystyle) + self._set_property("symmetric", arg, symmetric) + self._set_property("thickness", arg, thickness) + self._set_property("traceref", arg, traceref) + self._set_property("tracerefminus", arg, tracerefminus) + self._set_property("type", arg, type) + self._set_property("value", arg, value) + self._set_property("valueminus", arg, valueminus) + self._set_property("visible", arg, visible) + self._set_property("width", arg, width) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_error_y.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_error_y.py new file mode 100644 index 0000000000000000000000000000000000000000..b750644bb53a1af4e23edd1cb15df7280a5419d9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_error_y.py @@ -0,0 +1,480 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class ErrorY(_BaseTraceHierarchyType): + _parent_path_str = "scattergl" + _path_str = "scattergl.error_y" + _valid_props = { + "array", + "arrayminus", + "arrayminussrc", + "arraysrc", + "color", + "symmetric", + "thickness", + "traceref", + "tracerefminus", + "type", + "value", + "valueminus", + "visible", + "width", + } + + @property + def array(self): + """ + Sets the data corresponding the length of each error bar. + Values are plotted relative to the underlying data. + + The 'array' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["array"] + + @array.setter + def array(self, val): + self["array"] = val + + @property + def arrayminus(self): + """ + Sets the data corresponding the length of each error bar in the + bottom (left) direction for vertical (horizontal) bars Values + are plotted relative to the underlying data. + + The 'arrayminus' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["arrayminus"] + + @arrayminus.setter + def arrayminus(self, val): + self["arrayminus"] = val + + @property + def arrayminussrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `arrayminus`. + + The 'arrayminussrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["arrayminussrc"] + + @arrayminussrc.setter + def arrayminussrc(self, val): + self["arrayminussrc"] = val + + @property + def arraysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `array`. + + The 'arraysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["arraysrc"] + + @arraysrc.setter + def arraysrc(self, val): + self["arraysrc"] = val + + @property + def color(self): + """ + Sets the stroke color of the error bars. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def symmetric(self): + """ + Determines whether or not the error bars have the same length + in both direction (top/bottom for vertical bars, left/right for + horizontal bars. + + The 'symmetric' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["symmetric"] + + @symmetric.setter + def symmetric(self, val): + self["symmetric"] = val + + @property + def thickness(self): + """ + Sets the thickness (in px) of the error bars. + + The 'thickness' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["thickness"] + + @thickness.setter + def thickness(self, val): + self["thickness"] = val + + @property + def traceref(self): + """ + The 'traceref' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["traceref"] + + @traceref.setter + def traceref(self, val): + self["traceref"] = val + + @property + def tracerefminus(self): + """ + The 'tracerefminus' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["tracerefminus"] + + @tracerefminus.setter + def tracerefminus(self, val): + self["tracerefminus"] = val + + @property + def type(self): + """ + Determines the rule used to generate the error bars. If + "constant", the bar lengths are of a constant value. Set this + constant in `value`. If "percent", the bar lengths correspond + to a percentage of underlying data. Set this percentage in + `value`. If "sqrt", the bar lengths correspond to the square of + the underlying data. If "data", the bar lengths are set with + data set `array`. + + The 'type' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['percent', 'constant', 'sqrt', 'data'] + + Returns + ------- + Any + """ + return self["type"] + + @type.setter + def type(self, val): + self["type"] = val + + @property + def value(self): + """ + Sets the value of either the percentage (if `type` is set to + "percent") or the constant (if `type` is set to "constant") + corresponding to the lengths of the error bars. + + The 'value' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["value"] + + @value.setter + def value(self, val): + self["value"] = val + + @property + def valueminus(self): + """ + Sets the value of either the percentage (if `type` is set to + "percent") or the constant (if `type` is set to "constant") + corresponding to the lengths of the error bars in the bottom + (left) direction for vertical (horizontal) bars + + The 'valueminus' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["valueminus"] + + @valueminus.setter + def valueminus(self, val): + self["valueminus"] = val + + @property + def visible(self): + """ + Determines whether or not this set of error bars is visible. + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def width(self): + """ + Sets the width (in px) of the cross-bar at both ends of the + error bars. + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def _prop_descriptions(self): + return """\ + array + Sets the data corresponding the length of each error + bar. Values are plotted relative to the underlying + data. + arrayminus + Sets the data corresponding the length of each error + bar in the bottom (left) direction for vertical + (horizontal) bars Values are plotted relative to the + underlying data. + arrayminussrc + Sets the source reference on Chart Studio Cloud for + `arrayminus`. + arraysrc + Sets the source reference on Chart Studio Cloud for + `array`. + color + Sets the stroke color of the error bars. + symmetric + Determines whether or not the error bars have the same + length in both direction (top/bottom for vertical bars, + left/right for horizontal bars. + thickness + Sets the thickness (in px) of the error bars. + traceref + + tracerefminus + + type + Determines the rule used to generate the error bars. If + "constant", the bar lengths are of a constant value. + Set this constant in `value`. If "percent", the bar + lengths correspond to a percentage of underlying data. + Set this percentage in `value`. If "sqrt", the bar + lengths correspond to the square of the underlying + data. If "data", the bar lengths are set with data set + `array`. + value + Sets the value of either the percentage (if `type` is + set to "percent") or the constant (if `type` is set to + "constant") corresponding to the lengths of the error + bars. + valueminus + Sets the value of either the percentage (if `type` is + set to "percent") or the constant (if `type` is set to + "constant") corresponding to the lengths of the error + bars in the bottom (left) direction for vertical + (horizontal) bars + visible + Determines whether or not this set of error bars is + visible. + width + Sets the width (in px) of the cross-bar at both ends of + the error bars. + """ + + def __init__( + self, + arg=None, + array=None, + arrayminus=None, + arrayminussrc=None, + arraysrc=None, + color=None, + symmetric=None, + thickness=None, + traceref=None, + tracerefminus=None, + type=None, + value=None, + valueminus=None, + visible=None, + width=None, + **kwargs, + ): + """ + Construct a new ErrorY object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattergl.ErrorY` + array + Sets the data corresponding the length of each error + bar. Values are plotted relative to the underlying + data. + arrayminus + Sets the data corresponding the length of each error + bar in the bottom (left) direction for vertical + (horizontal) bars Values are plotted relative to the + underlying data. + arrayminussrc + Sets the source reference on Chart Studio Cloud for + `arrayminus`. + arraysrc + Sets the source reference on Chart Studio Cloud for + `array`. + color + Sets the stroke color of the error bars. + symmetric + Determines whether or not the error bars have the same + length in both direction (top/bottom for vertical bars, + left/right for horizontal bars. + thickness + Sets the thickness (in px) of the error bars. + traceref + + tracerefminus + + type + Determines the rule used to generate the error bars. If + "constant", the bar lengths are of a constant value. + Set this constant in `value`. If "percent", the bar + lengths correspond to a percentage of underlying data. + Set this percentage in `value`. If "sqrt", the bar + lengths correspond to the square of the underlying + data. If "data", the bar lengths are set with data set + `array`. + value + Sets the value of either the percentage (if `type` is + set to "percent") or the constant (if `type` is set to + "constant") corresponding to the lengths of the error + bars. + valueminus + Sets the value of either the percentage (if `type` is + set to "percent") or the constant (if `type` is set to + "constant") corresponding to the lengths of the error + bars in the bottom (left) direction for vertical + (horizontal) bars + visible + Determines whether or not this set of error bars is + visible. + width + Sets the width (in px) of the cross-bar at both ends of + the error bars. + + Returns + ------- + ErrorY + """ + super().__init__("error_y") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattergl.ErrorY +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattergl.ErrorY`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("array", arg, array) + self._set_property("arrayminus", arg, arrayminus) + self._set_property("arrayminussrc", arg, arrayminussrc) + self._set_property("arraysrc", arg, arraysrc) + self._set_property("color", arg, color) + self._set_property("symmetric", arg, symmetric) + self._set_property("thickness", arg, thickness) + self._set_property("traceref", arg, traceref) + self._set_property("tracerefminus", arg, tracerefminus) + self._set_property("type", arg, type) + self._set_property("value", arg, value) + self._set_property("valueminus", arg, valueminus) + self._set_property("visible", arg, visible) + self._set_property("width", arg, width) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_hoverlabel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_hoverlabel.py new file mode 100644 index 0000000000000000000000000000000000000000..95fcf655f2db6fcf9f9129e18517561b0ce827e0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_hoverlabel.py @@ -0,0 +1,366 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Hoverlabel(_BaseTraceHierarchyType): + _parent_path_str = "scattergl" + _path_str = "scattergl.hoverlabel" + _valid_props = { + "align", + "alignsrc", + "bgcolor", + "bgcolorsrc", + "bordercolor", + "bordercolorsrc", + "font", + "namelength", + "namelengthsrc", + "showarrow", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the text content within hover + label box. Has an effect only if the hover label text spans + more two or more lines + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'auto'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def alignsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `align`. + + The 'alignsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["alignsrc"] + + @alignsrc.setter + def alignsrc(self, val): + self["alignsrc"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the hover labels for this trace + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bgcolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `bgcolor`. + + The 'bgcolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bgcolorsrc"] + + @bgcolorsrc.setter + def bgcolorsrc(self, val): + self["bgcolorsrc"] = val + + @property + def bordercolor(self): + """ + Sets the border color of the hover labels for this trace. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def bordercolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + + The 'bordercolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bordercolorsrc"] + + @bordercolorsrc.setter + def bordercolorsrc(self, val): + self["bordercolorsrc"] = val + + @property + def font(self): + """ + Sets the font used in hover labels. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.hoverlabel.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.scattergl.hoverlabel.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def namelength(self): + """ + Sets the default length (in number of characters) of the trace + name in the hover labels for all traces. -1 shows the whole + name regardless of length. 0-3 shows the first 0-3 characters, + and an integer >3 will show the whole name if it is less than + that many characters, but if it is longer, will truncate to + `namelength - 3` characters and add an ellipsis. + + The 'namelength' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["namelength"] + + @namelength.setter + def namelength(self, val): + self["namelength"] = val + + @property + def namelengthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `namelength`. + + The 'namelengthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["namelengthsrc"] + + @namelengthsrc.setter + def namelengthsrc(self, val): + self["namelengthsrc"] = val + + @property + def showarrow(self): + """ + Sets whether or not to show the hover label arrow/triangle + pointing to the data point. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + """ + + def __init__( + self, + arg=None, + align=None, + alignsrc=None, + bgcolor=None, + bgcolorsrc=None, + bordercolor=None, + bordercolorsrc=None, + font=None, + namelength=None, + namelengthsrc=None, + showarrow=None, + **kwargs, + ): + """ + Construct a new Hoverlabel object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattergl.Hoverlabel` + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + + Returns + ------- + Hoverlabel + """ + super().__init__("hoverlabel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattergl.Hoverlabel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattergl.Hoverlabel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("alignsrc", arg, alignsrc) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bgcolorsrc", arg, bgcolorsrc) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("bordercolorsrc", arg, bordercolorsrc) + self._set_property("font", arg, font) + self._set_property("namelength", arg, namelength) + self._set_property("namelengthsrc", arg, namelengthsrc) + self._set_property("showarrow", arg, showarrow) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..ac54eda9d68cf1418f3f32c024720ac7272a24f4 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "scattergl" + _path_str = "scattergl.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.scattergl.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattergl.Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattergl.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattergl.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_line.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_line.py new file mode 100644 index 0000000000000000000000000000000000000000..12b641ca4b7ffcd23702646bf881b3f056f26364 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_line.py @@ -0,0 +1,158 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Line(_BaseTraceHierarchyType): + _parent_path_str = "scattergl" + _path_str = "scattergl.line" + _valid_props = {"color", "dash", "shape", "width"} + + @property + def color(self): + """ + Sets the line color. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def dash(self): + """ + Sets the style of the lines. + + The 'dash' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['dash', 'dashdot', 'dot', 'longdash', 'longdashdot', + 'solid'] + + Returns + ------- + Any + """ + return self["dash"] + + @dash.setter + def dash(self, val): + self["dash"] = val + + @property + def shape(self): + """ + Determines the line shape. The values correspond to step-wise + line shapes. + + The 'shape' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['linear', 'hv', 'vh', 'hvh', 'vhv'] + + Returns + ------- + Any + """ + return self["shape"] + + @shape.setter + def shape(self, val): + self["shape"] = val + + @property + def width(self): + """ + Sets the line width (in px). + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def _prop_descriptions(self): + return """\ + color + Sets the line color. + dash + Sets the style of the lines. + shape + Determines the line shape. The values correspond to + step-wise line shapes. + width + Sets the line width (in px). + """ + + def __init__( + self, arg=None, color=None, dash=None, shape=None, width=None, **kwargs + ): + """ + Construct a new Line object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattergl.Line` + color + Sets the line color. + dash + Sets the style of the lines. + shape + Determines the line shape. The values correspond to + step-wise line shapes. + width + Sets the line width (in px). + + Returns + ------- + Line + """ + super().__init__("line") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattergl.Line +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattergl.Line`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("dash", arg, dash) + self._set_property("shape", arg, shape) + self._set_property("width", arg, width) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_marker.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_marker.py new file mode 100644 index 0000000000000000000000000000000000000000..89d2af3b0ab116864191c31bf992539ca5d75cb6 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_marker.py @@ -0,0 +1,978 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Marker(_BaseTraceHierarchyType): + _parent_path_str = "scattergl" + _path_str = "scattergl.marker" + _valid_props = { + "angle", + "anglesrc", + "autocolorscale", + "cauto", + "cmax", + "cmid", + "cmin", + "color", + "coloraxis", + "colorbar", + "colorscale", + "colorsrc", + "line", + "opacity", + "opacitysrc", + "reversescale", + "showscale", + "size", + "sizemin", + "sizemode", + "sizeref", + "sizesrc", + "symbol", + "symbolsrc", + } + + @property + def angle(self): + """ + Sets the marker angle in respect to `angleref`. + + The 'angle' property is a angle (in degrees) that may be + specified as a number between -180 and 180, or a list, numpy array or other iterable thereof. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float|numpy.ndarray + """ + return self["angle"] + + @angle.setter + def angle(self, val): + self["angle"] = val + + @property + def anglesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `angle`. + + The 'anglesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["anglesrc"] + + @anglesrc.setter + def anglesrc(self, val): + self["anglesrc"] = val + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `marker.colorscale`. Has an effect only if in `marker.color` is + set to a numerical array. In case `colorscale` is unspecified + or `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def cauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `marker.color`) or the + bounds set in `marker.cmin` and `marker.cmax` Has an effect + only if in `marker.color` is set to a numerical array. Defaults + to `false` when `marker.cmin` and `marker.cmax` are set by the + user. + + The 'cauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cauto"] + + @cauto.setter + def cauto(self, val): + self["cauto"] = val + + @property + def cmax(self): + """ + Sets the upper bound of the color domain. Has an effect only if + in `marker.color` is set to a numerical array. Value should + have the same units as in `marker.color` and if set, + `marker.cmin` must be set as well. + + The 'cmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmax"] + + @cmax.setter + def cmax(self, val): + self["cmax"] = val + + @property + def cmid(self): + """ + Sets the mid-point of the color domain by scaling `marker.cmin` + and/or `marker.cmax` to be equidistant to this point. Has an + effect only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color`. Has no + effect when `marker.cauto` is `false`. + + The 'cmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmid"] + + @cmid.setter + def cmid(self, val): + self["cmid"] = val + + @property + def cmin(self): + """ + Sets the lower bound of the color domain. Has an effect only if + in `marker.color` is set to a numerical array. Value should + have the same units as in `marker.color` and if set, + `marker.cmax` must be set as well. + + The 'cmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmin"] + + @cmin.setter + def cmin(self, val): + self["cmin"] = val + + @property + def color(self): + """ + Sets the marker color. It accepts either a specific color or an + array of numbers that are mapped to the colorscale relative to + the max and min values of the array or relative to + `marker.cmin` and `marker.cmax` if set. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A number that will be interpreted as a color + according to scattergl.marker.colorscale + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.marker.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.scattergl.marker.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. Has an effect only if in `marker.color` is + set to a numerical array. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, rgba, + hex, hsl, hsv, or named color string. At minimum, a mapping for + the lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To + control the bounds of the colorscale in color space, use + `marker.cmin` and `marker.cmax`. Alternatively, `colorscale` + may be a palette name string of the following list: Blackbody,B + luered,Blues,Cividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic + ,Portland,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def colorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `color`. + + The 'colorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["colorsrc"] + + @colorsrc.setter + def colorsrc(self, val): + self["colorsrc"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.marker.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.scattergl.marker.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def opacity(self): + """ + Sets the marker opacity. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def opacitysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `opacity`. + + The 'opacitysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["opacitysrc"] + + @opacitysrc.setter + def opacitysrc(self, val): + self["opacitysrc"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. Has an effect only if in + `marker.color` is set to a numerical array. If true, + `marker.cmin` will correspond to the last color in the array + and `marker.cmax` will correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. Has an effect only if in `marker.color` is set to a + numerical array. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def size(self): + """ + Sets the marker size (in px). + + The 'size' property is a number and may be specified as: + - An int or float in the interval [0, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def sizemin(self): + """ + Has an effect only if `marker.size` is set to a numerical + array. Sets the minimum size (in px) of the rendered marker + points. + + The 'sizemin' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["sizemin"] + + @sizemin.setter + def sizemin(self, val): + self["sizemin"] = val + + @property + def sizemode(self): + """ + Has an effect only if `marker.size` is set to a numerical + array. Sets the rule for which the data in `size` is converted + to pixels. + + The 'sizemode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['diameter', 'area'] + + Returns + ------- + Any + """ + return self["sizemode"] + + @sizemode.setter + def sizemode(self, val): + self["sizemode"] = val + + @property + def sizeref(self): + """ + Has an effect only if `marker.size` is set to a numerical + array. Sets the scale factor used to determine the rendered + size of marker points. Use with `sizemin` and `sizemode`. + + The 'sizeref' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["sizeref"] + + @sizeref.setter + def sizeref(self, val): + self["sizeref"] = val + + @property + def sizesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `size`. + + The 'sizesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["sizesrc"] + + @sizesrc.setter + def sizesrc(self, val): + self["sizesrc"] = val + + @property + def symbol(self): + """ + Sets the marker symbol type. Adding 100 is equivalent to + appending "-open" to a symbol name. Adding 200 is equivalent to + appending "-dot" to a symbol name. Adding 300 is equivalent to + appending "-open-dot" or "dot-open" to a symbol name. + + The 'symbol' property is an enumeration that may be specified as: + - One of the following enumeration values: + [0, '0', 'circle', 100, '100', 'circle-open', 200, '200', + 'circle-dot', 300, '300', 'circle-open-dot', 1, '1', + 'square', 101, '101', 'square-open', 201, '201', + 'square-dot', 301, '301', 'square-open-dot', 2, '2', + 'diamond', 102, '102', 'diamond-open', 202, '202', + 'diamond-dot', 302, '302', 'diamond-open-dot', 3, '3', + 'cross', 103, '103', 'cross-open', 203, '203', + 'cross-dot', 303, '303', 'cross-open-dot', 4, '4', 'x', + 104, '104', 'x-open', 204, '204', 'x-dot', 304, '304', + 'x-open-dot', 5, '5', 'triangle-up', 105, '105', + 'triangle-up-open', 205, '205', 'triangle-up-dot', 305, + '305', 'triangle-up-open-dot', 6, '6', 'triangle-down', + 106, '106', 'triangle-down-open', 206, '206', + 'triangle-down-dot', 306, '306', 'triangle-down-open-dot', + 7, '7', 'triangle-left', 107, '107', 'triangle-left-open', + 207, '207', 'triangle-left-dot', 307, '307', + 'triangle-left-open-dot', 8, '8', 'triangle-right', 108, + '108', 'triangle-right-open', 208, '208', + 'triangle-right-dot', 308, '308', + 'triangle-right-open-dot', 9, '9', 'triangle-ne', 109, + '109', 'triangle-ne-open', 209, '209', 'triangle-ne-dot', + 309, '309', 'triangle-ne-open-dot', 10, '10', + 'triangle-se', 110, '110', 'triangle-se-open', 210, '210', + 'triangle-se-dot', 310, '310', 'triangle-se-open-dot', 11, + '11', 'triangle-sw', 111, '111', 'triangle-sw-open', 211, + '211', 'triangle-sw-dot', 311, '311', + 'triangle-sw-open-dot', 12, '12', 'triangle-nw', 112, + '112', 'triangle-nw-open', 212, '212', 'triangle-nw-dot', + 312, '312', 'triangle-nw-open-dot', 13, '13', 'pentagon', + 113, '113', 'pentagon-open', 213, '213', 'pentagon-dot', + 313, '313', 'pentagon-open-dot', 14, '14', 'hexagon', 114, + '114', 'hexagon-open', 214, '214', 'hexagon-dot', 314, + '314', 'hexagon-open-dot', 15, '15', 'hexagon2', 115, + '115', 'hexagon2-open', 215, '215', 'hexagon2-dot', 315, + '315', 'hexagon2-open-dot', 16, '16', 'octagon', 116, + '116', 'octagon-open', 216, '216', 'octagon-dot', 316, + '316', 'octagon-open-dot', 17, '17', 'star', 117, '117', + 'star-open', 217, '217', 'star-dot', 317, '317', + 'star-open-dot', 18, '18', 'hexagram', 118, '118', + 'hexagram-open', 218, '218', 'hexagram-dot', 318, '318', + 'hexagram-open-dot', 19, '19', 'star-triangle-up', 119, + '119', 'star-triangle-up-open', 219, '219', + 'star-triangle-up-dot', 319, '319', + 'star-triangle-up-open-dot', 20, '20', + 'star-triangle-down', 120, '120', + 'star-triangle-down-open', 220, '220', + 'star-triangle-down-dot', 320, '320', + 'star-triangle-down-open-dot', 21, '21', 'star-square', + 121, '121', 'star-square-open', 221, '221', + 'star-square-dot', 321, '321', 'star-square-open-dot', 22, + '22', 'star-diamond', 122, '122', 'star-diamond-open', + 222, '222', 'star-diamond-dot', 322, '322', + 'star-diamond-open-dot', 23, '23', 'diamond-tall', 123, + '123', 'diamond-tall-open', 223, '223', + 'diamond-tall-dot', 323, '323', 'diamond-tall-open-dot', + 24, '24', 'diamond-wide', 124, '124', 'diamond-wide-open', + 224, '224', 'diamond-wide-dot', 324, '324', + 'diamond-wide-open-dot', 25, '25', 'hourglass', 125, + '125', 'hourglass-open', 26, '26', 'bowtie', 126, '126', + 'bowtie-open', 27, '27', 'circle-cross', 127, '127', + 'circle-cross-open', 28, '28', 'circle-x', 128, '128', + 'circle-x-open', 29, '29', 'square-cross', 129, '129', + 'square-cross-open', 30, '30', 'square-x', 130, '130', + 'square-x-open', 31, '31', 'diamond-cross', 131, '131', + 'diamond-cross-open', 32, '32', 'diamond-x', 132, '132', + 'diamond-x-open', 33, '33', 'cross-thin', 133, '133', + 'cross-thin-open', 34, '34', 'x-thin', 134, '134', + 'x-thin-open', 35, '35', 'asterisk', 135, '135', + 'asterisk-open', 36, '36', 'hash', 136, '136', + 'hash-open', 236, '236', 'hash-dot', 336, '336', + 'hash-open-dot', 37, '37', 'y-up', 137, '137', + 'y-up-open', 38, '38', 'y-down', 138, '138', + 'y-down-open', 39, '39', 'y-left', 139, '139', + 'y-left-open', 40, '40', 'y-right', 140, '140', + 'y-right-open', 41, '41', 'line-ew', 141, '141', + 'line-ew-open', 42, '42', 'line-ns', 142, '142', + 'line-ns-open', 43, '43', 'line-ne', 143, '143', + 'line-ne-open', 44, '44', 'line-nw', 144, '144', + 'line-nw-open', 45, '45', 'arrow-up', 145, '145', + 'arrow-up-open', 46, '46', 'arrow-down', 146, '146', + 'arrow-down-open', 47, '47', 'arrow-left', 147, '147', + 'arrow-left-open', 48, '48', 'arrow-right', 148, '148', + 'arrow-right-open', 49, '49', 'arrow-bar-up', 149, '149', + 'arrow-bar-up-open', 50, '50', 'arrow-bar-down', 150, + '150', 'arrow-bar-down-open', 51, '51', 'arrow-bar-left', + 151, '151', 'arrow-bar-left-open', 52, '52', + 'arrow-bar-right', 152, '152', 'arrow-bar-right-open', 53, + '53', 'arrow', 153, '153', 'arrow-open', 54, '54', + 'arrow-wide', 154, '154', 'arrow-wide-open'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["symbol"] + + @symbol.setter + def symbol(self, val): + self["symbol"] = val + + @property + def symbolsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `symbol`. + + The 'symbolsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["symbolsrc"] + + @symbolsrc.setter + def symbolsrc(self, val): + self["symbolsrc"] = val + + @property + def _prop_descriptions(self): + return """\ + angle + Sets the marker angle in respect to `angleref`. + anglesrc + Sets the source reference on Chart Studio Cloud for + `angle`. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `marker.colorscale`. Has an effect only if in + `marker.color` is set to a numerical array. In case + `colorscale` is unspecified or `autocolorscale` is + true, the default palette will be chosen according to + whether numbers in the `color` array are all positive, + all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here in `marker.color`) + or the bounds set in `marker.cmin` and `marker.cmax` + Has an effect only if in `marker.color` is set to a + numerical array. Defaults to `false` when `marker.cmin` + and `marker.cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `marker.cmin` and/or `marker.cmax` to be equidistant to + this point. Has an effect only if in `marker.color` is + set to a numerical array. Value should have the same + units as in `marker.color`. Has no effect when + `marker.cauto` is `false`. + cmin + Sets the lower bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmax` must be set as well. + color + Sets the marker color. It accepts either a specific + color or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `marker.cmin` and `marker.cmax` if + set. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.scattergl.marker.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. Has an effect only if in + `marker.color` is set to a numerical array. The + colorscale must be an array containing arrays mapping a + normalized value to an rgb, rgba, hex, hsl, hsv, or + named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. + To control the bounds of the colorscale in color space, + use `marker.cmin` and `marker.cmax`. Alternatively, + `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,E + lectric,Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,Rd + Bu,Reds,Viridis,YlGnBu,YlOrRd. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + line + :class:`plotly.graph_objects.scattergl.marker.Line` + instance or dict with compatible properties + opacity + Sets the marker opacity. + opacitysrc + Sets the source reference on Chart Studio Cloud for + `opacity`. + reversescale + Reverses the color mapping if true. Has an effect only + if in `marker.color` is set to a numerical array. If + true, `marker.cmin` will correspond to the last color + in the array and `marker.cmax` will correspond to the + first color. + showscale + Determines whether or not a colorbar is displayed for + this trace. Has an effect only if in `marker.color` is + set to a numerical array. + size + Sets the marker size (in px). + sizemin + Has an effect only if `marker.size` is set to a + numerical array. Sets the minimum size (in px) of the + rendered marker points. + sizemode + Has an effect only if `marker.size` is set to a + numerical array. Sets the rule for which the data in + `size` is converted to pixels. + sizeref + Has an effect only if `marker.size` is set to a + numerical array. Sets the scale factor used to + determine the rendered size of marker points. Use with + `sizemin` and `sizemode`. + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + symbol + Sets the marker symbol type. Adding 100 is equivalent + to appending "-open" to a symbol name. Adding 200 is + equivalent to appending "-dot" to a symbol name. Adding + 300 is equivalent to appending "-open-dot" or "dot- + open" to a symbol name. + symbolsrc + Sets the source reference on Chart Studio Cloud for + `symbol`. + """ + + def __init__( + self, + arg=None, + angle=None, + anglesrc=None, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + color=None, + coloraxis=None, + colorbar=None, + colorscale=None, + colorsrc=None, + line=None, + opacity=None, + opacitysrc=None, + reversescale=None, + showscale=None, + size=None, + sizemin=None, + sizemode=None, + sizeref=None, + sizesrc=None, + symbol=None, + symbolsrc=None, + **kwargs, + ): + """ + Construct a new Marker object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattergl.Marker` + angle + Sets the marker angle in respect to `angleref`. + anglesrc + Sets the source reference on Chart Studio Cloud for + `angle`. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `marker.colorscale`. Has an effect only if in + `marker.color` is set to a numerical array. In case + `colorscale` is unspecified or `autocolorscale` is + true, the default palette will be chosen according to + whether numbers in the `color` array are all positive, + all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here in `marker.color`) + or the bounds set in `marker.cmin` and `marker.cmax` + Has an effect only if in `marker.color` is set to a + numerical array. Defaults to `false` when `marker.cmin` + and `marker.cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `marker.cmin` and/or `marker.cmax` to be equidistant to + this point. Has an effect only if in `marker.color` is + set to a numerical array. Value should have the same + units as in `marker.color`. Has no effect when + `marker.cauto` is `false`. + cmin + Sets the lower bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmax` must be set as well. + color + Sets the marker color. It accepts either a specific + color or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `marker.cmin` and `marker.cmax` if + set. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.scattergl.marker.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. Has an effect only if in + `marker.color` is set to a numerical array. The + colorscale must be an array containing arrays mapping a + normalized value to an rgb, rgba, hex, hsl, hsv, or + named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. + To control the bounds of the colorscale in color space, + use `marker.cmin` and `marker.cmax`. Alternatively, + `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,E + lectric,Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,Rd + Bu,Reds,Viridis,YlGnBu,YlOrRd. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + line + :class:`plotly.graph_objects.scattergl.marker.Line` + instance or dict with compatible properties + opacity + Sets the marker opacity. + opacitysrc + Sets the source reference on Chart Studio Cloud for + `opacity`. + reversescale + Reverses the color mapping if true. Has an effect only + if in `marker.color` is set to a numerical array. If + true, `marker.cmin` will correspond to the last color + in the array and `marker.cmax` will correspond to the + first color. + showscale + Determines whether or not a colorbar is displayed for + this trace. Has an effect only if in `marker.color` is + set to a numerical array. + size + Sets the marker size (in px). + sizemin + Has an effect only if `marker.size` is set to a + numerical array. Sets the minimum size (in px) of the + rendered marker points. + sizemode + Has an effect only if `marker.size` is set to a + numerical array. Sets the rule for which the data in + `size` is converted to pixels. + sizeref + Has an effect only if `marker.size` is set to a + numerical array. Sets the scale factor used to + determine the rendered size of marker points. Use with + `sizemin` and `sizemode`. + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + symbol + Sets the marker symbol type. Adding 100 is equivalent + to appending "-open" to a symbol name. Adding 200 is + equivalent to appending "-dot" to a symbol name. Adding + 300 is equivalent to appending "-open-dot" or "dot- + open" to a symbol name. + symbolsrc + Sets the source reference on Chart Studio Cloud for + `symbol`. + + Returns + ------- + Marker + """ + super().__init__("marker") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattergl.Marker +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattergl.Marker`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("angle", arg, angle) + self._set_property("anglesrc", arg, anglesrc) + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("cauto", arg, cauto) + self._set_property("cmax", arg, cmax) + self._set_property("cmid", arg, cmid) + self._set_property("cmin", arg, cmin) + self._set_property("color", arg, color) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("colorsrc", arg, colorsrc) + self._set_property("line", arg, line) + self._set_property("opacity", arg, opacity) + self._set_property("opacitysrc", arg, opacitysrc) + self._set_property("reversescale", arg, reversescale) + self._set_property("showscale", arg, showscale) + self._set_property("size", arg, size) + self._set_property("sizemin", arg, sizemin) + self._set_property("sizemode", arg, sizemode) + self._set_property("sizeref", arg, sizeref) + self._set_property("sizesrc", arg, sizesrc) + self._set_property("symbol", arg, symbol) + self._set_property("symbolsrc", arg, symbolsrc) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_selected.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_selected.py new file mode 100644 index 0000000000000000000000000000000000000000..1271cedc7407e3188f65eb35fe29dc16878f5bbe --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_selected.py @@ -0,0 +1,106 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Selected(_BaseTraceHierarchyType): + _parent_path_str = "scattergl" + _path_str = "scattergl.selected" + _valid_props = {"marker", "textfont"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.selected.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scattergl.selected.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def textfont(self): + """ + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.selected.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.scattergl.selected.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.scattergl.selected.Marker` + instance or dict with compatible properties + textfont + :class:`plotly.graph_objects.scattergl.selected.Textfon + t` instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, textfont=None, **kwargs): + """ + Construct a new Selected object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattergl.Selected` + marker + :class:`plotly.graph_objects.scattergl.selected.Marker` + instance or dict with compatible properties + textfont + :class:`plotly.graph_objects.scattergl.selected.Textfon + t` instance or dict with compatible properties + + Returns + ------- + Selected + """ + super().__init__("selected") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattergl.Selected +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattergl.Selected`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._set_property("textfont", arg, textfont) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..108cc9b418470f97b12b527396cf71606c7c820c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_stream.py @@ -0,0 +1,114 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "scattergl" + _path_str = "scattergl.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattergl.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattergl.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattergl.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_textfont.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_textfont.py new file mode 100644 index 0000000000000000000000000000000000000000..ccc8e03f1562738e1d1c19324e61c4a66361972e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_textfont.py @@ -0,0 +1,399 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Textfont(_BaseTraceHierarchyType): + _parent_path_str = "scattergl" + _path_str = "scattergl.textfont" + _valid_props = { + "color", + "colorsrc", + "family", + "familysrc", + "size", + "sizesrc", + "style", + "stylesrc", + "variant", + "variantsrc", + "weight", + "weightsrc", + } + + @property + def color(self): + """ + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def colorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `color`. + + The 'colorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["colorsrc"] + + @colorsrc.setter + def colorsrc(self, val): + self["colorsrc"] = val + + @property + def family(self): + """ + HTML font family - the typeface that will be applied by the web + browser. The web browser can only apply a font if it is + available on the system where it runs. Provide multiple font + families, separated by commas, to indicate the order in which + to apply fonts if they aren't available. + + The 'family' property is a string and must be specified as: + - A non-empty string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["family"] + + @family.setter + def family(self, val): + self["family"] = val + + @property + def familysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `family`. + + The 'familysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["familysrc"] + + @familysrc.setter + def familysrc(self, val): + self["familysrc"] = val + + @property + def size(self): + """ + The 'size' property is a number and may be specified as: + - An int or float in the interval [1, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def sizesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `size`. + + The 'sizesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["sizesrc"] + + @sizesrc.setter + def sizesrc(self, val): + self["sizesrc"] = val + + @property + def style(self): + """ + Sets whether a font should be styled with a normal or italic + face from its family. + + The 'style' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'italic'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def stylesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `style`. + + The 'stylesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["stylesrc"] + + @stylesrc.setter + def stylesrc(self, val): + self["stylesrc"] = val + + @property + def variant(self): + """ + Sets the variant of the font. + + The 'variant' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'small-caps'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["variant"] + + @variant.setter + def variant(self, val): + self["variant"] = val + + @property + def variantsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `variant`. + + The 'variantsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["variantsrc"] + + @variantsrc.setter + def variantsrc(self, val): + self["variantsrc"] = val + + @property + def weight(self): + """ + Sets the weight (or boldness) of the font. + + The 'weight' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'bold'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["weight"] + + @weight.setter + def weight(self, val): + self["weight"] = val + + @property + def weightsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `weight`. + + The 'weightsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["weightsrc"] + + @weightsrc.setter + def weightsrc(self, val): + self["weightsrc"] = val + + @property + def _prop_descriptions(self): + return """\ + color + + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + familysrc + Sets the source reference on Chart Studio Cloud for + `family`. + size + + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + style + Sets whether a font should be styled with a normal or + italic face from its family. + stylesrc + Sets the source reference on Chart Studio Cloud for + `style`. + variant + Sets the variant of the font. + variantsrc + Sets the source reference on Chart Studio Cloud for + `variant`. + weight + Sets the weight (or boldness) of the font. + weightsrc + Sets the source reference on Chart Studio Cloud for + `weight`. + """ + + def __init__( + self, + arg=None, + color=None, + colorsrc=None, + family=None, + familysrc=None, + size=None, + sizesrc=None, + style=None, + stylesrc=None, + variant=None, + variantsrc=None, + weight=None, + weightsrc=None, + **kwargs, + ): + """ + Construct a new Textfont object + + Sets the text font. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattergl.Textfont` + color + + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + familysrc + Sets the source reference on Chart Studio Cloud for + `family`. + size + + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + style + Sets whether a font should be styled with a normal or + italic face from its family. + stylesrc + Sets the source reference on Chart Studio Cloud for + `style`. + variant + Sets the variant of the font. + variantsrc + Sets the source reference on Chart Studio Cloud for + `variant`. + weight + Sets the weight (or boldness) of the font. + weightsrc + Sets the source reference on Chart Studio Cloud for + `weight`. + + Returns + ------- + Textfont + """ + super().__init__("textfont") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattergl.Textfont +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattergl.Textfont`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("colorsrc", arg, colorsrc) + self._set_property("family", arg, family) + self._set_property("familysrc", arg, familysrc) + self._set_property("size", arg, size) + self._set_property("sizesrc", arg, sizesrc) + self._set_property("style", arg, style) + self._set_property("stylesrc", arg, stylesrc) + self._set_property("variant", arg, variant) + self._set_property("variantsrc", arg, variantsrc) + self._set_property("weight", arg, weight) + self._set_property("weightsrc", arg, weightsrc) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_unselected.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_unselected.py new file mode 100644 index 0000000000000000000000000000000000000000..7c2cd4b9b32b75eca0c19e789964f71aab2eb92f --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattergl/_unselected.py @@ -0,0 +1,106 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Unselected(_BaseTraceHierarchyType): + _parent_path_str = "scattergl" + _path_str = "scattergl.unselected" + _valid_props = {"marker", "textfont"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.unselected.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scattergl.unselected.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def textfont(self): + """ + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattergl.unselected.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.scattergl.unselected.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.scattergl.unselected.Marke + r` instance or dict with compatible properties + textfont + :class:`plotly.graph_objects.scattergl.unselected.Textf + ont` instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, textfont=None, **kwargs): + """ + Construct a new Unselected object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattergl.Unselected` + marker + :class:`plotly.graph_objects.scattergl.unselected.Marke + r` instance or dict with compatible properties + textfont + :class:`plotly.graph_objects.scattergl.unselected.Textf + ont` instance or dict with compatible properties + + Returns + ------- + Unselected + """ + super().__init__("unselected") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattergl.Unselected +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattergl.Unselected`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._set_property("textfont", arg, textfont) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..aaeb5c0f63abfffbbc9784e8e1a2c48cda0d1eea --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/__init__.py @@ -0,0 +1,36 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._cluster import Cluster + from ._hoverlabel import Hoverlabel + from ._legendgrouptitle import Legendgrouptitle + from ._line import Line + from ._marker import Marker + from ._selected import Selected + from ._stream import Stream + from ._textfont import Textfont + from ._unselected import Unselected + from . import hoverlabel + from . import legendgrouptitle + from . import marker + from . import selected + from . import unselected +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [".hoverlabel", ".legendgrouptitle", ".marker", ".selected", ".unselected"], + [ + "._cluster.Cluster", + "._hoverlabel.Hoverlabel", + "._legendgrouptitle.Legendgrouptitle", + "._line.Line", + "._marker.Marker", + "._selected.Selected", + "._stream.Stream", + "._textfont.Textfont", + "._unselected.Unselected", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_cluster.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_cluster.py new file mode 100644 index 0000000000000000000000000000000000000000..bd66fd02c538d5e0d25905933e634baa93eb8e58 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_cluster.py @@ -0,0 +1,342 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Cluster(_BaseTraceHierarchyType): + _parent_path_str = "scattermap" + _path_str = "scattermap.cluster" + _valid_props = { + "color", + "colorsrc", + "enabled", + "maxzoom", + "opacity", + "opacitysrc", + "size", + "sizesrc", + "step", + "stepsrc", + } + + @property + def color(self): + """ + Sets the color for each cluster step. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def colorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `color`. + + The 'colorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["colorsrc"] + + @colorsrc.setter + def colorsrc(self, val): + self["colorsrc"] = val + + @property + def enabled(self): + """ + Determines whether clustering is enabled or disabled. + + The 'enabled' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["enabled"] + + @enabled.setter + def enabled(self, val): + self["enabled"] = val + + @property + def maxzoom(self): + """ + Sets the maximum zoom level. At zoom levels equal to or greater + than this, points will never be clustered. + + The 'maxzoom' property is a number and may be specified as: + - An int or float in the interval [0, 24] + + Returns + ------- + int|float + """ + return self["maxzoom"] + + @maxzoom.setter + def maxzoom(self, val): + self["maxzoom"] = val + + @property + def opacity(self): + """ + Sets the marker opacity. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def opacitysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `opacity`. + + The 'opacitysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["opacitysrc"] + + @opacitysrc.setter + def opacitysrc(self, val): + self["opacitysrc"] = val + + @property + def size(self): + """ + Sets the size for each cluster step. + + The 'size' property is a number and may be specified as: + - An int or float in the interval [0, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def sizesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `size`. + + The 'sizesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["sizesrc"] + + @sizesrc.setter + def sizesrc(self, val): + self["sizesrc"] = val + + @property + def step(self): + """ + Sets how many points it takes to create a cluster or advance to + the next cluster step. Use this in conjunction with arrays for + `size` and / or `color`. If an integer, steps start at + multiples of this number. If an array, each step extends from + the given value until one less than the next value. + + The 'step' property is a number and may be specified as: + - An int or float in the interval [-1, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["step"] + + @step.setter + def step(self, val): + self["step"] = val + + @property + def stepsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `step`. + + The 'stepsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["stepsrc"] + + @stepsrc.setter + def stepsrc(self, val): + self["stepsrc"] = val + + @property + def _prop_descriptions(self): + return """\ + color + Sets the color for each cluster step. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + enabled + Determines whether clustering is enabled or disabled. + maxzoom + Sets the maximum zoom level. At zoom levels equal to or + greater than this, points will never be clustered. + opacity + Sets the marker opacity. + opacitysrc + Sets the source reference on Chart Studio Cloud for + `opacity`. + size + Sets the size for each cluster step. + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + step + Sets how many points it takes to create a cluster or + advance to the next cluster step. Use this in + conjunction with arrays for `size` and / or `color`. If + an integer, steps start at multiples of this number. If + an array, each step extends from the given value until + one less than the next value. + stepsrc + Sets the source reference on Chart Studio Cloud for + `step`. + """ + + def __init__( + self, + arg=None, + color=None, + colorsrc=None, + enabled=None, + maxzoom=None, + opacity=None, + opacitysrc=None, + size=None, + sizesrc=None, + step=None, + stepsrc=None, + **kwargs, + ): + """ + Construct a new Cluster object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattermap.Cluster` + color + Sets the color for each cluster step. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + enabled + Determines whether clustering is enabled or disabled. + maxzoom + Sets the maximum zoom level. At zoom levels equal to or + greater than this, points will never be clustered. + opacity + Sets the marker opacity. + opacitysrc + Sets the source reference on Chart Studio Cloud for + `opacity`. + size + Sets the size for each cluster step. + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + step + Sets how many points it takes to create a cluster or + advance to the next cluster step. Use this in + conjunction with arrays for `size` and / or `color`. If + an integer, steps start at multiples of this number. If + an array, each step extends from the given value until + one less than the next value. + stepsrc + Sets the source reference on Chart Studio Cloud for + `step`. + + Returns + ------- + Cluster + """ + super().__init__("cluster") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattermap.Cluster +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattermap.Cluster`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("colorsrc", arg, colorsrc) + self._set_property("enabled", arg, enabled) + self._set_property("maxzoom", arg, maxzoom) + self._set_property("opacity", arg, opacity) + self._set_property("opacitysrc", arg, opacitysrc) + self._set_property("size", arg, size) + self._set_property("sizesrc", arg, sizesrc) + self._set_property("step", arg, step) + self._set_property("stepsrc", arg, stepsrc) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_hoverlabel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_hoverlabel.py new file mode 100644 index 0000000000000000000000000000000000000000..66cbe4592fbfe1fea8a69d170e9798ec30d7fff2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_hoverlabel.py @@ -0,0 +1,366 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Hoverlabel(_BaseTraceHierarchyType): + _parent_path_str = "scattermap" + _path_str = "scattermap.hoverlabel" + _valid_props = { + "align", + "alignsrc", + "bgcolor", + "bgcolorsrc", + "bordercolor", + "bordercolorsrc", + "font", + "namelength", + "namelengthsrc", + "showarrow", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the text content within hover + label box. Has an effect only if the hover label text spans + more two or more lines + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'auto'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def alignsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `align`. + + The 'alignsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["alignsrc"] + + @alignsrc.setter + def alignsrc(self, val): + self["alignsrc"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the hover labels for this trace + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bgcolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `bgcolor`. + + The 'bgcolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bgcolorsrc"] + + @bgcolorsrc.setter + def bgcolorsrc(self, val): + self["bgcolorsrc"] = val + + @property + def bordercolor(self): + """ + Sets the border color of the hover labels for this trace. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def bordercolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + + The 'bordercolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bordercolorsrc"] + + @bordercolorsrc.setter + def bordercolorsrc(self, val): + self["bordercolorsrc"] = val + + @property + def font(self): + """ + Sets the font used in hover labels. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermap.hoverlabel.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.scattermap.hoverlabel.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def namelength(self): + """ + Sets the default length (in number of characters) of the trace + name in the hover labels for all traces. -1 shows the whole + name regardless of length. 0-3 shows the first 0-3 characters, + and an integer >3 will show the whole name if it is less than + that many characters, but if it is longer, will truncate to + `namelength - 3` characters and add an ellipsis. + + The 'namelength' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["namelength"] + + @namelength.setter + def namelength(self, val): + self["namelength"] = val + + @property + def namelengthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `namelength`. + + The 'namelengthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["namelengthsrc"] + + @namelengthsrc.setter + def namelengthsrc(self, val): + self["namelengthsrc"] = val + + @property + def showarrow(self): + """ + Sets whether or not to show the hover label arrow/triangle + pointing to the data point. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + """ + + def __init__( + self, + arg=None, + align=None, + alignsrc=None, + bgcolor=None, + bgcolorsrc=None, + bordercolor=None, + bordercolorsrc=None, + font=None, + namelength=None, + namelengthsrc=None, + showarrow=None, + **kwargs, + ): + """ + Construct a new Hoverlabel object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattermap.Hoverlabel` + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + + Returns + ------- + Hoverlabel + """ + super().__init__("hoverlabel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattermap.Hoverlabel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattermap.Hoverlabel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("alignsrc", arg, alignsrc) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bgcolorsrc", arg, bgcolorsrc) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("bordercolorsrc", arg, bordercolorsrc) + self._set_property("font", arg, font) + self._set_property("namelength", arg, namelength) + self._set_property("namelengthsrc", arg, namelengthsrc) + self._set_property("showarrow", arg, showarrow) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..0dee4c5dd7759cd67d43f14e47998a5d5258b3a2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "scattermap" + _path_str = "scattermap.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermap.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.scattermap.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattermap.Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattermap.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattermap.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_line.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_line.py new file mode 100644 index 0000000000000000000000000000000000000000..6d07e8bbfd413bbf7ef57db083280bbf4c9f1cac --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_line.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Line(_BaseTraceHierarchyType): + _parent_path_str = "scattermap" + _path_str = "scattermap.line" + _valid_props = {"color", "width"} + + @property + def color(self): + """ + Sets the line color. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def width(self): + """ + Sets the line width (in px). + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def _prop_descriptions(self): + return """\ + color + Sets the line color. + width + Sets the line width (in px). + """ + + def __init__(self, arg=None, color=None, width=None, **kwargs): + """ + Construct a new Line object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattermap.Line` + color + Sets the line color. + width + Sets the line width (in px). + + Returns + ------- + Line + """ + super().__init__("line") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattermap.Line +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattermap.Line`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("width", arg, width) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_marker.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_marker.py new file mode 100644 index 0000000000000000000000000000000000000000..98d0d00d04b461266c9ce230f2c95bbf1397fc54 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_marker.py @@ -0,0 +1,892 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Marker(_BaseTraceHierarchyType): + _parent_path_str = "scattermap" + _path_str = "scattermap.marker" + _valid_props = { + "allowoverlap", + "angle", + "anglesrc", + "autocolorscale", + "cauto", + "cmax", + "cmid", + "cmin", + "color", + "coloraxis", + "colorbar", + "colorscale", + "colorsrc", + "opacity", + "opacitysrc", + "reversescale", + "showscale", + "size", + "sizemin", + "sizemode", + "sizeref", + "sizesrc", + "symbol", + "symbolsrc", + } + + @property + def allowoverlap(self): + """ + Flag to draw all symbols, even if they overlap. + + The 'allowoverlap' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["allowoverlap"] + + @allowoverlap.setter + def allowoverlap(self, val): + self["allowoverlap"] = val + + @property + def angle(self): + """ + Sets the marker orientation from true North, in degrees + clockwise. When using the "auto" default, no rotation would be + applied in perspective views which is different from using a + zero angle. + + The 'angle' property is a number and may be specified as: + - An int or float + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["angle"] + + @angle.setter + def angle(self, val): + self["angle"] = val + + @property + def anglesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `angle`. + + The 'anglesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["anglesrc"] + + @anglesrc.setter + def anglesrc(self, val): + self["anglesrc"] = val + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `marker.colorscale`. Has an effect only if in `marker.color` is + set to a numerical array. In case `colorscale` is unspecified + or `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def cauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `marker.color`) or the + bounds set in `marker.cmin` and `marker.cmax` Has an effect + only if in `marker.color` is set to a numerical array. Defaults + to `false` when `marker.cmin` and `marker.cmax` are set by the + user. + + The 'cauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cauto"] + + @cauto.setter + def cauto(self, val): + self["cauto"] = val + + @property + def cmax(self): + """ + Sets the upper bound of the color domain. Has an effect only if + in `marker.color` is set to a numerical array. Value should + have the same units as in `marker.color` and if set, + `marker.cmin` must be set as well. + + The 'cmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmax"] + + @cmax.setter + def cmax(self, val): + self["cmax"] = val + + @property + def cmid(self): + """ + Sets the mid-point of the color domain by scaling `marker.cmin` + and/or `marker.cmax` to be equidistant to this point. Has an + effect only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color`. Has no + effect when `marker.cauto` is `false`. + + The 'cmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmid"] + + @cmid.setter + def cmid(self, val): + self["cmid"] = val + + @property + def cmin(self): + """ + Sets the lower bound of the color domain. Has an effect only if + in `marker.color` is set to a numerical array. Value should + have the same units as in `marker.color` and if set, + `marker.cmax` must be set as well. + + The 'cmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmin"] + + @cmin.setter + def cmin(self, val): + self["cmin"] = val + + @property + def color(self): + """ + Sets the marker color. It accepts either a specific color or an + array of numbers that are mapped to the colorscale relative to + the max and min values of the array or relative to + `marker.cmin` and `marker.cmax` if set. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A number that will be interpreted as a color + according to scattermap.marker.colorscale + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermap.marker.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.scattermap.marker.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. Has an effect only if in `marker.color` is + set to a numerical array. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, rgba, + hex, hsl, hsv, or named color string. At minimum, a mapping for + the lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To + control the bounds of the colorscale in color space, use + `marker.cmin` and `marker.cmax`. Alternatively, `colorscale` + may be a palette name string of the following list: Blackbody,B + luered,Blues,Cividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic + ,Portland,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def colorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `color`. + + The 'colorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["colorsrc"] + + @colorsrc.setter + def colorsrc(self, val): + self["colorsrc"] = val + + @property + def opacity(self): + """ + Sets the marker opacity. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def opacitysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `opacity`. + + The 'opacitysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["opacitysrc"] + + @opacitysrc.setter + def opacitysrc(self, val): + self["opacitysrc"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. Has an effect only if in + `marker.color` is set to a numerical array. If true, + `marker.cmin` will correspond to the last color in the array + and `marker.cmax` will correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. Has an effect only if in `marker.color` is set to a + numerical array. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def size(self): + """ + Sets the marker size (in px). + + The 'size' property is a number and may be specified as: + - An int or float in the interval [0, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def sizemin(self): + """ + Has an effect only if `marker.size` is set to a numerical + array. Sets the minimum size (in px) of the rendered marker + points. + + The 'sizemin' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["sizemin"] + + @sizemin.setter + def sizemin(self, val): + self["sizemin"] = val + + @property + def sizemode(self): + """ + Has an effect only if `marker.size` is set to a numerical + array. Sets the rule for which the data in `size` is converted + to pixels. + + The 'sizemode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['diameter', 'area'] + + Returns + ------- + Any + """ + return self["sizemode"] + + @sizemode.setter + def sizemode(self, val): + self["sizemode"] = val + + @property + def sizeref(self): + """ + Has an effect only if `marker.size` is set to a numerical + array. Sets the scale factor used to determine the rendered + size of marker points. Use with `sizemin` and `sizemode`. + + The 'sizeref' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["sizeref"] + + @sizeref.setter + def sizeref(self, val): + self["sizeref"] = val + + @property + def sizesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `size`. + + The 'sizesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["sizesrc"] + + @sizesrc.setter + def sizesrc(self, val): + self["sizesrc"] = val + + @property + def symbol(self): + """ + Sets the marker symbol. Full list: https://www.mapbox.com/maki- + icons/ Note that the array `marker.color` and `marker.size` are + only available for "circle" symbols. + + The 'symbol' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["symbol"] + + @symbol.setter + def symbol(self, val): + self["symbol"] = val + + @property + def symbolsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `symbol`. + + The 'symbolsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["symbolsrc"] + + @symbolsrc.setter + def symbolsrc(self, val): + self["symbolsrc"] = val + + @property + def _prop_descriptions(self): + return """\ + allowoverlap + Flag to draw all symbols, even if they overlap. + angle + Sets the marker orientation from true North, in degrees + clockwise. When using the "auto" default, no rotation + would be applied in perspective views which is + different from using a zero angle. + anglesrc + Sets the source reference on Chart Studio Cloud for + `angle`. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `marker.colorscale`. Has an effect only if in + `marker.color` is set to a numerical array. In case + `colorscale` is unspecified or `autocolorscale` is + true, the default palette will be chosen according to + whether numbers in the `color` array are all positive, + all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here in `marker.color`) + or the bounds set in `marker.cmin` and `marker.cmax` + Has an effect only if in `marker.color` is set to a + numerical array. Defaults to `false` when `marker.cmin` + and `marker.cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `marker.cmin` and/or `marker.cmax` to be equidistant to + this point. Has an effect only if in `marker.color` is + set to a numerical array. Value should have the same + units as in `marker.color`. Has no effect when + `marker.cauto` is `false`. + cmin + Sets the lower bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmax` must be set as well. + color + Sets the marker color. It accepts either a specific + color or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `marker.cmin` and `marker.cmax` if + set. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.scattermap.marker.ColorBar + ` instance or dict with compatible properties + colorscale + Sets the colorscale. Has an effect only if in + `marker.color` is set to a numerical array. The + colorscale must be an array containing arrays mapping a + normalized value to an rgb, rgba, hex, hsl, hsv, or + named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. + To control the bounds of the colorscale in color space, + use `marker.cmin` and `marker.cmax`. Alternatively, + `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,E + lectric,Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,Rd + Bu,Reds,Viridis,YlGnBu,YlOrRd. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + opacity + Sets the marker opacity. + opacitysrc + Sets the source reference on Chart Studio Cloud for + `opacity`. + reversescale + Reverses the color mapping if true. Has an effect only + if in `marker.color` is set to a numerical array. If + true, `marker.cmin` will correspond to the last color + in the array and `marker.cmax` will correspond to the + first color. + showscale + Determines whether or not a colorbar is displayed for + this trace. Has an effect only if in `marker.color` is + set to a numerical array. + size + Sets the marker size (in px). + sizemin + Has an effect only if `marker.size` is set to a + numerical array. Sets the minimum size (in px) of the + rendered marker points. + sizemode + Has an effect only if `marker.size` is set to a + numerical array. Sets the rule for which the data in + `size` is converted to pixels. + sizeref + Has an effect only if `marker.size` is set to a + numerical array. Sets the scale factor used to + determine the rendered size of marker points. Use with + `sizemin` and `sizemode`. + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + symbol + Sets the marker symbol. Full list: + https://www.mapbox.com/maki-icons/ Note that the array + `marker.color` and `marker.size` are only available for + "circle" symbols. + symbolsrc + Sets the source reference on Chart Studio Cloud for + `symbol`. + """ + + def __init__( + self, + arg=None, + allowoverlap=None, + angle=None, + anglesrc=None, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + color=None, + coloraxis=None, + colorbar=None, + colorscale=None, + colorsrc=None, + opacity=None, + opacitysrc=None, + reversescale=None, + showscale=None, + size=None, + sizemin=None, + sizemode=None, + sizeref=None, + sizesrc=None, + symbol=None, + symbolsrc=None, + **kwargs, + ): + """ + Construct a new Marker object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattermap.Marker` + allowoverlap + Flag to draw all symbols, even if they overlap. + angle + Sets the marker orientation from true North, in degrees + clockwise. When using the "auto" default, no rotation + would be applied in perspective views which is + different from using a zero angle. + anglesrc + Sets the source reference on Chart Studio Cloud for + `angle`. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `marker.colorscale`. Has an effect only if in + `marker.color` is set to a numerical array. In case + `colorscale` is unspecified or `autocolorscale` is + true, the default palette will be chosen according to + whether numbers in the `color` array are all positive, + all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here in `marker.color`) + or the bounds set in `marker.cmin` and `marker.cmax` + Has an effect only if in `marker.color` is set to a + numerical array. Defaults to `false` when `marker.cmin` + and `marker.cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `marker.cmin` and/or `marker.cmax` to be equidistant to + this point. Has an effect only if in `marker.color` is + set to a numerical array. Value should have the same + units as in `marker.color`. Has no effect when + `marker.cauto` is `false`. + cmin + Sets the lower bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmax` must be set as well. + color + Sets the marker color. It accepts either a specific + color or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `marker.cmin` and `marker.cmax` if + set. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.scattermap.marker.ColorBar + ` instance or dict with compatible properties + colorscale + Sets the colorscale. Has an effect only if in + `marker.color` is set to a numerical array. The + colorscale must be an array containing arrays mapping a + normalized value to an rgb, rgba, hex, hsl, hsv, or + named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. + To control the bounds of the colorscale in color space, + use `marker.cmin` and `marker.cmax`. Alternatively, + `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,E + lectric,Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,Rd + Bu,Reds,Viridis,YlGnBu,YlOrRd. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + opacity + Sets the marker opacity. + opacitysrc + Sets the source reference on Chart Studio Cloud for + `opacity`. + reversescale + Reverses the color mapping if true. Has an effect only + if in `marker.color` is set to a numerical array. If + true, `marker.cmin` will correspond to the last color + in the array and `marker.cmax` will correspond to the + first color. + showscale + Determines whether or not a colorbar is displayed for + this trace. Has an effect only if in `marker.color` is + set to a numerical array. + size + Sets the marker size (in px). + sizemin + Has an effect only if `marker.size` is set to a + numerical array. Sets the minimum size (in px) of the + rendered marker points. + sizemode + Has an effect only if `marker.size` is set to a + numerical array. Sets the rule for which the data in + `size` is converted to pixels. + sizeref + Has an effect only if `marker.size` is set to a + numerical array. Sets the scale factor used to + determine the rendered size of marker points. Use with + `sizemin` and `sizemode`. + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + symbol + Sets the marker symbol. Full list: + https://www.mapbox.com/maki-icons/ Note that the array + `marker.color` and `marker.size` are only available for + "circle" symbols. + symbolsrc + Sets the source reference on Chart Studio Cloud for + `symbol`. + + Returns + ------- + Marker + """ + super().__init__("marker") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattermap.Marker +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattermap.Marker`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("allowoverlap", arg, allowoverlap) + self._set_property("angle", arg, angle) + self._set_property("anglesrc", arg, anglesrc) + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("cauto", arg, cauto) + self._set_property("cmax", arg, cmax) + self._set_property("cmid", arg, cmid) + self._set_property("cmin", arg, cmin) + self._set_property("color", arg, color) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("colorsrc", arg, colorsrc) + self._set_property("opacity", arg, opacity) + self._set_property("opacitysrc", arg, opacitysrc) + self._set_property("reversescale", arg, reversescale) + self._set_property("showscale", arg, showscale) + self._set_property("size", arg, size) + self._set_property("sizemin", arg, sizemin) + self._set_property("sizemode", arg, sizemode) + self._set_property("sizeref", arg, sizeref) + self._set_property("sizesrc", arg, sizesrc) + self._set_property("symbol", arg, symbol) + self._set_property("symbolsrc", arg, symbolsrc) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_selected.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_selected.py new file mode 100644 index 0000000000000000000000000000000000000000..fc36d377b9f080a966a1f50ffc789564faaa4dcd --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_selected.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Selected(_BaseTraceHierarchyType): + _parent_path_str = "scattermap" + _path_str = "scattermap.selected" + _valid_props = {"marker"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermap.selected.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scattermap.selected.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.scattermap.selected.Marker + ` instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, **kwargs): + """ + Construct a new Selected object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattermap.Selected` + marker + :class:`plotly.graph_objects.scattermap.selected.Marker + ` instance or dict with compatible properties + + Returns + ------- + Selected + """ + super().__init__("selected") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattermap.Selected +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattermap.Selected`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..cb82bb8b98f33ae102ffd82c61f00bc357cb876e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_stream.py @@ -0,0 +1,114 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "scattermap" + _path_str = "scattermap.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattermap.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattermap.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattermap.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_textfont.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_textfont.py new file mode 100644 index 0000000000000000000000000000000000000000..fda40ac9cdbe19e558d5d5b60ec0c490a8093ad7 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_textfont.py @@ -0,0 +1,202 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Textfont(_BaseTraceHierarchyType): + _parent_path_str = "scattermap" + _path_str = "scattermap.textfont" + _valid_props = {"color", "family", "size", "style", "weight"} + + @property + def color(self): + """ + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def family(self): + """ + HTML font family - the typeface that will be applied by the web + browser. The web browser can only apply a font if it is + available on the system where it runs. Provide multiple font + families, separated by commas, to indicate the order in which + to apply fonts if they aren't available. + + The 'family' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["family"] + + @family.setter + def family(self, val): + self["family"] = val + + @property + def size(self): + """ + The 'size' property is a number and may be specified as: + - An int or float in the interval [1, inf] + + Returns + ------- + int|float + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def style(self): + """ + Sets whether a font should be styled with a normal or italic + face from its family. + + The 'style' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'italic'] + + Returns + ------- + Any + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def weight(self): + """ + Sets the weight (or boldness) of the font. + + The 'weight' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 1000] + OR exactly one of ['normal', 'bold'] (e.g. 'bold') + + Returns + ------- + int + """ + return self["weight"] + + @weight.setter + def weight(self, val): + self["weight"] = val + + @property + def _prop_descriptions(self): + return """\ + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + weight + Sets the weight (or boldness) of the font. + """ + + def __init__( + self, + arg=None, + color=None, + family=None, + size=None, + style=None, + weight=None, + **kwargs, + ): + """ + Construct a new Textfont object + + Sets the icon text font (color=map.layer.paint.text-color, + size=map.layer.layout.text-size). Has an effect only when + `type` is set to "symbol". + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattermap.Textfont` + color + + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + size + + style + Sets whether a font should be styled with a normal or + italic face from its family. + weight + Sets the weight (or boldness) of the font. + + Returns + ------- + Textfont + """ + super().__init__("textfont") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattermap.Textfont +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattermap.Textfont`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("family", arg, family) + self._set_property("size", arg, size) + self._set_property("style", arg, style) + self._set_property("weight", arg, weight) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_unselected.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_unselected.py new file mode 100644 index 0000000000000000000000000000000000000000..6911361a0db0040cb55b2b7d8d9d4fc1c7b39981 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scattermap/_unselected.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Unselected(_BaseTraceHierarchyType): + _parent_path_str = "scattermap" + _path_str = "scattermap.unselected" + _valid_props = {"marker"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scattermap.unselected.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scattermap.unselected.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.scattermap.unselected.Mark + er` instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, **kwargs): + """ + Construct a new Unselected object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scattermap.Unselected` + marker + :class:`plotly.graph_objects.scattermap.unselected.Mark + er` instance or dict with compatible properties + + Returns + ------- + Unselected + """ + super().__init__("unselected") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scattermap.Unselected +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scattermap.Unselected`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..55ee707f4edcd57d1b31c190b9eb71769f6dced3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/__init__.py @@ -0,0 +1,34 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._hoverlabel import Hoverlabel + from ._legendgrouptitle import Legendgrouptitle + from ._line import Line + from ._marker import Marker + from ._selected import Selected + from ._stream import Stream + from ._textfont import Textfont + from ._unselected import Unselected + from . import hoverlabel + from . import legendgrouptitle + from . import marker + from . import selected + from . import unselected +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [".hoverlabel", ".legendgrouptitle", ".marker", ".selected", ".unselected"], + [ + "._hoverlabel.Hoverlabel", + "._legendgrouptitle.Legendgrouptitle", + "._line.Line", + "._marker.Marker", + "._selected.Selected", + "._stream.Stream", + "._textfont.Textfont", + "._unselected.Unselected", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_hoverlabel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_hoverlabel.py new file mode 100644 index 0000000000000000000000000000000000000000..8af023fd88636e9aea786e5677493e9b7d77d125 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_hoverlabel.py @@ -0,0 +1,366 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Hoverlabel(_BaseTraceHierarchyType): + _parent_path_str = "scatterternary" + _path_str = "scatterternary.hoverlabel" + _valid_props = { + "align", + "alignsrc", + "bgcolor", + "bgcolorsrc", + "bordercolor", + "bordercolorsrc", + "font", + "namelength", + "namelengthsrc", + "showarrow", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the text content within hover + label box. Has an effect only if the hover label text spans + more two or more lines + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'auto'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def alignsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `align`. + + The 'alignsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["alignsrc"] + + @alignsrc.setter + def alignsrc(self, val): + self["alignsrc"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the hover labels for this trace + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bgcolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `bgcolor`. + + The 'bgcolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bgcolorsrc"] + + @bgcolorsrc.setter + def bgcolorsrc(self, val): + self["bgcolorsrc"] = val + + @property + def bordercolor(self): + """ + Sets the border color of the hover labels for this trace. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def bordercolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + + The 'bordercolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bordercolorsrc"] + + @bordercolorsrc.setter + def bordercolorsrc(self, val): + self["bordercolorsrc"] = val + + @property + def font(self): + """ + Sets the font used in hover labels. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.hoverlabel.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.scatterternary.hoverlabel.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def namelength(self): + """ + Sets the default length (in number of characters) of the trace + name in the hover labels for all traces. -1 shows the whole + name regardless of length. 0-3 shows the first 0-3 characters, + and an integer >3 will show the whole name if it is less than + that many characters, but if it is longer, will truncate to + `namelength - 3` characters and add an ellipsis. + + The 'namelength' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["namelength"] + + @namelength.setter + def namelength(self, val): + self["namelength"] = val + + @property + def namelengthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `namelength`. + + The 'namelengthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["namelengthsrc"] + + @namelengthsrc.setter + def namelengthsrc(self, val): + self["namelengthsrc"] = val + + @property + def showarrow(self): + """ + Sets whether or not to show the hover label arrow/triangle + pointing to the data point. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + """ + + def __init__( + self, + arg=None, + align=None, + alignsrc=None, + bgcolor=None, + bgcolorsrc=None, + bordercolor=None, + bordercolorsrc=None, + font=None, + namelength=None, + namelengthsrc=None, + showarrow=None, + **kwargs, + ): + """ + Construct a new Hoverlabel object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scatterternary.Hoverlabel` + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + + Returns + ------- + Hoverlabel + """ + super().__init__("hoverlabel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scatterternary.Hoverlabel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scatterternary.Hoverlabel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("alignsrc", arg, alignsrc) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bgcolorsrc", arg, bgcolorsrc) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("bordercolorsrc", arg, bordercolorsrc) + self._set_property("font", arg, font) + self._set_property("namelength", arg, namelength) + self._set_property("namelengthsrc", arg, namelengthsrc) + self._set_property("showarrow", arg, showarrow) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..6d8fe3bbe8396ff6d06cd2801011e62b9be9c8a4 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "scatterternary" + _path_str = "scatterternary.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.scatterternary.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.scatterternary + .Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scatterternary.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scatterternary.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_line.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_line.py new file mode 100644 index 0000000000000000000000000000000000000000..015e0971125c3ca512834d878e2b8db05da71650 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_line.py @@ -0,0 +1,277 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Line(_BaseTraceHierarchyType): + _parent_path_str = "scatterternary" + _path_str = "scatterternary.line" + _valid_props = { + "backoff", + "backoffsrc", + "color", + "dash", + "shape", + "smoothing", + "width", + } + + @property + def backoff(self): + """ + Sets the line back off from the end point of the nth line + segment (in px). This option is useful e.g. to avoid overlap + with arrowhead markers. With "auto" the lines would trim before + markers if `marker.angleref` is set to "previous". + + The 'backoff' property is a number and may be specified as: + - An int or float in the interval [0, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["backoff"] + + @backoff.setter + def backoff(self, val): + self["backoff"] = val + + @property + def backoffsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `backoff`. + + The 'backoffsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["backoffsrc"] + + @backoffsrc.setter + def backoffsrc(self, val): + self["backoffsrc"] = val + + @property + def color(self): + """ + Sets the line color. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def dash(self): + """ + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + + The 'dash' property is an enumeration that may be specified as: + - One of the following dash styles: + ['solid', 'dot', 'dash', 'longdash', 'dashdot', 'longdashdot'] + - A string containing a dash length list in pixels or percentages + (e.g. '5px 10px 2px 2px', '5, 10, 2, 2', '10% 20% 40%', etc.) + + Returns + ------- + str + """ + return self["dash"] + + @dash.setter + def dash(self, val): + self["dash"] = val + + @property + def shape(self): + """ + Determines the line shape. With "spline" the lines are drawn + using spline interpolation. The other available values + correspond to step-wise line shapes. + + The 'shape' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['linear', 'spline'] + + Returns + ------- + Any + """ + return self["shape"] + + @shape.setter + def shape(self, val): + self["shape"] = val + + @property + def smoothing(self): + """ + Has an effect only if `shape` is set to "spline" Sets the + amount of smoothing. 0 corresponds to no smoothing (equivalent + to a "linear" shape). + + The 'smoothing' property is a number and may be specified as: + - An int or float in the interval [0, 1.3] + + Returns + ------- + int|float + """ + return self["smoothing"] + + @smoothing.setter + def smoothing(self, val): + self["smoothing"] = val + + @property + def width(self): + """ + Sets the line width (in px). + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def _prop_descriptions(self): + return """\ + backoff + Sets the line back off from the end point of the nth + line segment (in px). This option is useful e.g. to + avoid overlap with arrowhead markers. With "auto" the + lines would trim before markers if `marker.angleref` is + set to "previous". + backoffsrc + Sets the source reference on Chart Studio Cloud for + `backoff`. + color + Sets the line color. + dash + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + shape + Determines the line shape. With "spline" the lines are + drawn using spline interpolation. The other available + values correspond to step-wise line shapes. + smoothing + Has an effect only if `shape` is set to "spline" Sets + the amount of smoothing. 0 corresponds to no smoothing + (equivalent to a "linear" shape). + width + Sets the line width (in px). + """ + + def __init__( + self, + arg=None, + backoff=None, + backoffsrc=None, + color=None, + dash=None, + shape=None, + smoothing=None, + width=None, + **kwargs, + ): + """ + Construct a new Line object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scatterternary.Line` + backoff + Sets the line back off from the end point of the nth + line segment (in px). This option is useful e.g. to + avoid overlap with arrowhead markers. With "auto" the + lines would trim before markers if `marker.angleref` is + set to "previous". + backoffsrc + Sets the source reference on Chart Studio Cloud for + `backoff`. + color + Sets the line color. + dash + Sets the dash style of lines. Set to a dash type string + ("solid", "dot", "dash", "longdash", "dashdot", or + "longdashdot") or a dash length list in px (eg + "5px,10px,2px,2px"). + shape + Determines the line shape. With "spline" the lines are + drawn using spline interpolation. The other available + values correspond to step-wise line shapes. + smoothing + Has an effect only if `shape` is set to "spline" Sets + the amount of smoothing. 0 corresponds to no smoothing + (equivalent to a "linear" shape). + width + Sets the line width (in px). + + Returns + ------- + Line + """ + super().__init__("line") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scatterternary.Line +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scatterternary.Line`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("backoff", arg, backoff) + self._set_property("backoffsrc", arg, backoffsrc) + self._set_property("color", arg, color) + self._set_property("dash", arg, dash) + self._set_property("shape", arg, shape) + self._set_property("smoothing", arg, smoothing) + self._set_property("width", arg, width) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_marker.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_marker.py new file mode 100644 index 0000000000000000000000000000000000000000..e6f4844c4f7b9513b701f6adc80438eff880eb2d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_marker.py @@ -0,0 +1,1130 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Marker(_BaseTraceHierarchyType): + _parent_path_str = "scatterternary" + _path_str = "scatterternary.marker" + _valid_props = { + "angle", + "angleref", + "anglesrc", + "autocolorscale", + "cauto", + "cmax", + "cmid", + "cmin", + "color", + "coloraxis", + "colorbar", + "colorscale", + "colorsrc", + "gradient", + "line", + "maxdisplayed", + "opacity", + "opacitysrc", + "reversescale", + "showscale", + "size", + "sizemin", + "sizemode", + "sizeref", + "sizesrc", + "standoff", + "standoffsrc", + "symbol", + "symbolsrc", + } + + @property + def angle(self): + """ + Sets the marker angle in respect to `angleref`. + + The 'angle' property is a angle (in degrees) that may be + specified as a number between -180 and 180, or a list, numpy array or other iterable thereof. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float|numpy.ndarray + """ + return self["angle"] + + @angle.setter + def angle(self, val): + self["angle"] = val + + @property + def angleref(self): + """ + Sets the reference for marker angle. With "previous", angle 0 + points along the line from the previous point to this one. With + "up", angle 0 points toward the top of the screen. + + The 'angleref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['previous', 'up'] + + Returns + ------- + Any + """ + return self["angleref"] + + @angleref.setter + def angleref(self, val): + self["angleref"] = val + + @property + def anglesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `angle`. + + The 'anglesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["anglesrc"] + + @anglesrc.setter + def anglesrc(self, val): + self["anglesrc"] = val + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `marker.colorscale`. Has an effect only if in `marker.color` is + set to a numerical array. In case `colorscale` is unspecified + or `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def cauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `marker.color`) or the + bounds set in `marker.cmin` and `marker.cmax` Has an effect + only if in `marker.color` is set to a numerical array. Defaults + to `false` when `marker.cmin` and `marker.cmax` are set by the + user. + + The 'cauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cauto"] + + @cauto.setter + def cauto(self, val): + self["cauto"] = val + + @property + def cmax(self): + """ + Sets the upper bound of the color domain. Has an effect only if + in `marker.color` is set to a numerical array. Value should + have the same units as in `marker.color` and if set, + `marker.cmin` must be set as well. + + The 'cmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmax"] + + @cmax.setter + def cmax(self, val): + self["cmax"] = val + + @property + def cmid(self): + """ + Sets the mid-point of the color domain by scaling `marker.cmin` + and/or `marker.cmax` to be equidistant to this point. Has an + effect only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color`. Has no + effect when `marker.cauto` is `false`. + + The 'cmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmid"] + + @cmid.setter + def cmid(self, val): + self["cmid"] = val + + @property + def cmin(self): + """ + Sets the lower bound of the color domain. Has an effect only if + in `marker.color` is set to a numerical array. Value should + have the same units as in `marker.color` and if set, + `marker.cmax` must be set as well. + + The 'cmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmin"] + + @cmin.setter + def cmin(self, val): + self["cmin"] = val + + @property + def color(self): + """ + Sets the marker color. It accepts either a specific color or an + array of numbers that are mapped to the colorscale relative to + the max and min values of the array or relative to + `marker.cmin` and `marker.cmax` if set. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A number that will be interpreted as a color + according to scatterternary.marker.colorscale + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.marker.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.scatterternary.marker.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. Has an effect only if in `marker.color` is + set to a numerical array. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, rgba, + hex, hsl, hsv, or named color string. At minimum, a mapping for + the lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To + control the bounds of the colorscale in color space, use + `marker.cmin` and `marker.cmax`. Alternatively, `colorscale` + may be a palette name string of the following list: Blackbody,B + luered,Blues,Cividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic + ,Portland,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def colorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `color`. + + The 'colorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["colorsrc"] + + @colorsrc.setter + def colorsrc(self, val): + self["colorsrc"] = val + + @property + def gradient(self): + """ + The 'gradient' property is an instance of Gradient + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.marker.Gradient` + - A dict of string/value properties that will be passed + to the Gradient constructor + + Returns + ------- + plotly.graph_objs.scatterternary.marker.Gradient + """ + return self["gradient"] + + @gradient.setter + def gradient(self, val): + self["gradient"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.marker.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.scatterternary.marker.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def maxdisplayed(self): + """ + Sets a maximum number of points to be drawn on the graph. 0 + corresponds to no limit. + + The 'maxdisplayed' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["maxdisplayed"] + + @maxdisplayed.setter + def maxdisplayed(self, val): + self["maxdisplayed"] = val + + @property + def opacity(self): + """ + Sets the marker opacity. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def opacitysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `opacity`. + + The 'opacitysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["opacitysrc"] + + @opacitysrc.setter + def opacitysrc(self, val): + self["opacitysrc"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. Has an effect only if in + `marker.color` is set to a numerical array. If true, + `marker.cmin` will correspond to the last color in the array + and `marker.cmax` will correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. Has an effect only if in `marker.color` is set to a + numerical array. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def size(self): + """ + Sets the marker size (in px). + + The 'size' property is a number and may be specified as: + - An int or float in the interval [0, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def sizemin(self): + """ + Has an effect only if `marker.size` is set to a numerical + array. Sets the minimum size (in px) of the rendered marker + points. + + The 'sizemin' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["sizemin"] + + @sizemin.setter + def sizemin(self, val): + self["sizemin"] = val + + @property + def sizemode(self): + """ + Has an effect only if `marker.size` is set to a numerical + array. Sets the rule for which the data in `size` is converted + to pixels. + + The 'sizemode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['diameter', 'area'] + + Returns + ------- + Any + """ + return self["sizemode"] + + @sizemode.setter + def sizemode(self, val): + self["sizemode"] = val + + @property + def sizeref(self): + """ + Has an effect only if `marker.size` is set to a numerical + array. Sets the scale factor used to determine the rendered + size of marker points. Use with `sizemin` and `sizemode`. + + The 'sizeref' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["sizeref"] + + @sizeref.setter + def sizeref(self, val): + self["sizeref"] = val + + @property + def sizesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `size`. + + The 'sizesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["sizesrc"] + + @sizesrc.setter + def sizesrc(self, val): + self["sizesrc"] = val + + @property + def standoff(self): + """ + Moves the marker away from the data point in the direction of + `angle` (in px). This can be useful for example if you have + another marker at this location and you want to point an + arrowhead marker at it. + + The 'standoff' property is a number and may be specified as: + - An int or float in the interval [0, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["standoff"] + + @standoff.setter + def standoff(self, val): + self["standoff"] = val + + @property + def standoffsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `standoff`. + + The 'standoffsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["standoffsrc"] + + @standoffsrc.setter + def standoffsrc(self, val): + self["standoffsrc"] = val + + @property + def symbol(self): + """ + Sets the marker symbol type. Adding 100 is equivalent to + appending "-open" to a symbol name. Adding 200 is equivalent to + appending "-dot" to a symbol name. Adding 300 is equivalent to + appending "-open-dot" or "dot-open" to a symbol name. + + The 'symbol' property is an enumeration that may be specified as: + - One of the following enumeration values: + [0, '0', 'circle', 100, '100', 'circle-open', 200, '200', + 'circle-dot', 300, '300', 'circle-open-dot', 1, '1', + 'square', 101, '101', 'square-open', 201, '201', + 'square-dot', 301, '301', 'square-open-dot', 2, '2', + 'diamond', 102, '102', 'diamond-open', 202, '202', + 'diamond-dot', 302, '302', 'diamond-open-dot', 3, '3', + 'cross', 103, '103', 'cross-open', 203, '203', + 'cross-dot', 303, '303', 'cross-open-dot', 4, '4', 'x', + 104, '104', 'x-open', 204, '204', 'x-dot', 304, '304', + 'x-open-dot', 5, '5', 'triangle-up', 105, '105', + 'triangle-up-open', 205, '205', 'triangle-up-dot', 305, + '305', 'triangle-up-open-dot', 6, '6', 'triangle-down', + 106, '106', 'triangle-down-open', 206, '206', + 'triangle-down-dot', 306, '306', 'triangle-down-open-dot', + 7, '7', 'triangle-left', 107, '107', 'triangle-left-open', + 207, '207', 'triangle-left-dot', 307, '307', + 'triangle-left-open-dot', 8, '8', 'triangle-right', 108, + '108', 'triangle-right-open', 208, '208', + 'triangle-right-dot', 308, '308', + 'triangle-right-open-dot', 9, '9', 'triangle-ne', 109, + '109', 'triangle-ne-open', 209, '209', 'triangle-ne-dot', + 309, '309', 'triangle-ne-open-dot', 10, '10', + 'triangle-se', 110, '110', 'triangle-se-open', 210, '210', + 'triangle-se-dot', 310, '310', 'triangle-se-open-dot', 11, + '11', 'triangle-sw', 111, '111', 'triangle-sw-open', 211, + '211', 'triangle-sw-dot', 311, '311', + 'triangle-sw-open-dot', 12, '12', 'triangle-nw', 112, + '112', 'triangle-nw-open', 212, '212', 'triangle-nw-dot', + 312, '312', 'triangle-nw-open-dot', 13, '13', 'pentagon', + 113, '113', 'pentagon-open', 213, '213', 'pentagon-dot', + 313, '313', 'pentagon-open-dot', 14, '14', 'hexagon', 114, + '114', 'hexagon-open', 214, '214', 'hexagon-dot', 314, + '314', 'hexagon-open-dot', 15, '15', 'hexagon2', 115, + '115', 'hexagon2-open', 215, '215', 'hexagon2-dot', 315, + '315', 'hexagon2-open-dot', 16, '16', 'octagon', 116, + '116', 'octagon-open', 216, '216', 'octagon-dot', 316, + '316', 'octagon-open-dot', 17, '17', 'star', 117, '117', + 'star-open', 217, '217', 'star-dot', 317, '317', + 'star-open-dot', 18, '18', 'hexagram', 118, '118', + 'hexagram-open', 218, '218', 'hexagram-dot', 318, '318', + 'hexagram-open-dot', 19, '19', 'star-triangle-up', 119, + '119', 'star-triangle-up-open', 219, '219', + 'star-triangle-up-dot', 319, '319', + 'star-triangle-up-open-dot', 20, '20', + 'star-triangle-down', 120, '120', + 'star-triangle-down-open', 220, '220', + 'star-triangle-down-dot', 320, '320', + 'star-triangle-down-open-dot', 21, '21', 'star-square', + 121, '121', 'star-square-open', 221, '221', + 'star-square-dot', 321, '321', 'star-square-open-dot', 22, + '22', 'star-diamond', 122, '122', 'star-diamond-open', + 222, '222', 'star-diamond-dot', 322, '322', + 'star-diamond-open-dot', 23, '23', 'diamond-tall', 123, + '123', 'diamond-tall-open', 223, '223', + 'diamond-tall-dot', 323, '323', 'diamond-tall-open-dot', + 24, '24', 'diamond-wide', 124, '124', 'diamond-wide-open', + 224, '224', 'diamond-wide-dot', 324, '324', + 'diamond-wide-open-dot', 25, '25', 'hourglass', 125, + '125', 'hourglass-open', 26, '26', 'bowtie', 126, '126', + 'bowtie-open', 27, '27', 'circle-cross', 127, '127', + 'circle-cross-open', 28, '28', 'circle-x', 128, '128', + 'circle-x-open', 29, '29', 'square-cross', 129, '129', + 'square-cross-open', 30, '30', 'square-x', 130, '130', + 'square-x-open', 31, '31', 'diamond-cross', 131, '131', + 'diamond-cross-open', 32, '32', 'diamond-x', 132, '132', + 'diamond-x-open', 33, '33', 'cross-thin', 133, '133', + 'cross-thin-open', 34, '34', 'x-thin', 134, '134', + 'x-thin-open', 35, '35', 'asterisk', 135, '135', + 'asterisk-open', 36, '36', 'hash', 136, '136', + 'hash-open', 236, '236', 'hash-dot', 336, '336', + 'hash-open-dot', 37, '37', 'y-up', 137, '137', + 'y-up-open', 38, '38', 'y-down', 138, '138', + 'y-down-open', 39, '39', 'y-left', 139, '139', + 'y-left-open', 40, '40', 'y-right', 140, '140', + 'y-right-open', 41, '41', 'line-ew', 141, '141', + 'line-ew-open', 42, '42', 'line-ns', 142, '142', + 'line-ns-open', 43, '43', 'line-ne', 143, '143', + 'line-ne-open', 44, '44', 'line-nw', 144, '144', + 'line-nw-open', 45, '45', 'arrow-up', 145, '145', + 'arrow-up-open', 46, '46', 'arrow-down', 146, '146', + 'arrow-down-open', 47, '47', 'arrow-left', 147, '147', + 'arrow-left-open', 48, '48', 'arrow-right', 148, '148', + 'arrow-right-open', 49, '49', 'arrow-bar-up', 149, '149', + 'arrow-bar-up-open', 50, '50', 'arrow-bar-down', 150, + '150', 'arrow-bar-down-open', 51, '51', 'arrow-bar-left', + 151, '151', 'arrow-bar-left-open', 52, '52', + 'arrow-bar-right', 152, '152', 'arrow-bar-right-open', 53, + '53', 'arrow', 153, '153', 'arrow-open', 54, '54', + 'arrow-wide', 154, '154', 'arrow-wide-open'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["symbol"] + + @symbol.setter + def symbol(self, val): + self["symbol"] = val + + @property + def symbolsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `symbol`. + + The 'symbolsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["symbolsrc"] + + @symbolsrc.setter + def symbolsrc(self, val): + self["symbolsrc"] = val + + @property + def _prop_descriptions(self): + return """\ + angle + Sets the marker angle in respect to `angleref`. + angleref + Sets the reference for marker angle. With "previous", + angle 0 points along the line from the previous point + to this one. With "up", angle 0 points toward the top + of the screen. + anglesrc + Sets the source reference on Chart Studio Cloud for + `angle`. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `marker.colorscale`. Has an effect only if in + `marker.color` is set to a numerical array. In case + `colorscale` is unspecified or `autocolorscale` is + true, the default palette will be chosen according to + whether numbers in the `color` array are all positive, + all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here in `marker.color`) + or the bounds set in `marker.cmin` and `marker.cmax` + Has an effect only if in `marker.color` is set to a + numerical array. Defaults to `false` when `marker.cmin` + and `marker.cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `marker.cmin` and/or `marker.cmax` to be equidistant to + this point. Has an effect only if in `marker.color` is + set to a numerical array. Value should have the same + units as in `marker.color`. Has no effect when + `marker.cauto` is `false`. + cmin + Sets the lower bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmax` must be set as well. + color + Sets the marker color. It accepts either a specific + color or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `marker.cmin` and `marker.cmax` if + set. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.scatterternary.marker.Colo + rBar` instance or dict with compatible properties + colorscale + Sets the colorscale. Has an effect only if in + `marker.color` is set to a numerical array. The + colorscale must be an array containing arrays mapping a + normalized value to an rgb, rgba, hex, hsl, hsv, or + named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. + To control the bounds of the colorscale in color space, + use `marker.cmin` and `marker.cmax`. Alternatively, + `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,E + lectric,Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,Rd + Bu,Reds,Viridis,YlGnBu,YlOrRd. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + gradient + :class:`plotly.graph_objects.scatterternary.marker.Grad + ient` instance or dict with compatible properties + line + :class:`plotly.graph_objects.scatterternary.marker.Line + ` instance or dict with compatible properties + maxdisplayed + Sets a maximum number of points to be drawn on the + graph. 0 corresponds to no limit. + opacity + Sets the marker opacity. + opacitysrc + Sets the source reference on Chart Studio Cloud for + `opacity`. + reversescale + Reverses the color mapping if true. Has an effect only + if in `marker.color` is set to a numerical array. If + true, `marker.cmin` will correspond to the last color + in the array and `marker.cmax` will correspond to the + first color. + showscale + Determines whether or not a colorbar is displayed for + this trace. Has an effect only if in `marker.color` is + set to a numerical array. + size + Sets the marker size (in px). + sizemin + Has an effect only if `marker.size` is set to a + numerical array. Sets the minimum size (in px) of the + rendered marker points. + sizemode + Has an effect only if `marker.size` is set to a + numerical array. Sets the rule for which the data in + `size` is converted to pixels. + sizeref + Has an effect only if `marker.size` is set to a + numerical array. Sets the scale factor used to + determine the rendered size of marker points. Use with + `sizemin` and `sizemode`. + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + standoff + Moves the marker away from the data point in the + direction of `angle` (in px). This can be useful for + example if you have another marker at this location and + you want to point an arrowhead marker at it. + standoffsrc + Sets the source reference on Chart Studio Cloud for + `standoff`. + symbol + Sets the marker symbol type. Adding 100 is equivalent + to appending "-open" to a symbol name. Adding 200 is + equivalent to appending "-dot" to a symbol name. Adding + 300 is equivalent to appending "-open-dot" or "dot- + open" to a symbol name. + symbolsrc + Sets the source reference on Chart Studio Cloud for + `symbol`. + """ + + def __init__( + self, + arg=None, + angle=None, + angleref=None, + anglesrc=None, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + color=None, + coloraxis=None, + colorbar=None, + colorscale=None, + colorsrc=None, + gradient=None, + line=None, + maxdisplayed=None, + opacity=None, + opacitysrc=None, + reversescale=None, + showscale=None, + size=None, + sizemin=None, + sizemode=None, + sizeref=None, + sizesrc=None, + standoff=None, + standoffsrc=None, + symbol=None, + symbolsrc=None, + **kwargs, + ): + """ + Construct a new Marker object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scatterternary.Marker` + angle + Sets the marker angle in respect to `angleref`. + angleref + Sets the reference for marker angle. With "previous", + angle 0 points along the line from the previous point + to this one. With "up", angle 0 points toward the top + of the screen. + anglesrc + Sets the source reference on Chart Studio Cloud for + `angle`. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `marker.colorscale`. Has an effect only if in + `marker.color` is set to a numerical array. In case + `colorscale` is unspecified or `autocolorscale` is + true, the default palette will be chosen according to + whether numbers in the `color` array are all positive, + all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here in `marker.color`) + or the bounds set in `marker.cmin` and `marker.cmax` + Has an effect only if in `marker.color` is set to a + numerical array. Defaults to `false` when `marker.cmin` + and `marker.cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `marker.cmin` and/or `marker.cmax` to be equidistant to + this point. Has an effect only if in `marker.color` is + set to a numerical array. Value should have the same + units as in `marker.color`. Has no effect when + `marker.cauto` is `false`. + cmin + Sets the lower bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmax` must be set as well. + color + Sets the marker color. It accepts either a specific + color or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `marker.cmin` and `marker.cmax` if + set. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.scatterternary.marker.Colo + rBar` instance or dict with compatible properties + colorscale + Sets the colorscale. Has an effect only if in + `marker.color` is set to a numerical array. The + colorscale must be an array containing arrays mapping a + normalized value to an rgb, rgba, hex, hsl, hsv, or + named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. + To control the bounds of the colorscale in color space, + use `marker.cmin` and `marker.cmax`. Alternatively, + `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,E + lectric,Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,Rd + Bu,Reds,Viridis,YlGnBu,YlOrRd. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + gradient + :class:`plotly.graph_objects.scatterternary.marker.Grad + ient` instance or dict with compatible properties + line + :class:`plotly.graph_objects.scatterternary.marker.Line + ` instance or dict with compatible properties + maxdisplayed + Sets a maximum number of points to be drawn on the + graph. 0 corresponds to no limit. + opacity + Sets the marker opacity. + opacitysrc + Sets the source reference on Chart Studio Cloud for + `opacity`. + reversescale + Reverses the color mapping if true. Has an effect only + if in `marker.color` is set to a numerical array. If + true, `marker.cmin` will correspond to the last color + in the array and `marker.cmax` will correspond to the + first color. + showscale + Determines whether or not a colorbar is displayed for + this trace. Has an effect only if in `marker.color` is + set to a numerical array. + size + Sets the marker size (in px). + sizemin + Has an effect only if `marker.size` is set to a + numerical array. Sets the minimum size (in px) of the + rendered marker points. + sizemode + Has an effect only if `marker.size` is set to a + numerical array. Sets the rule for which the data in + `size` is converted to pixels. + sizeref + Has an effect only if `marker.size` is set to a + numerical array. Sets the scale factor used to + determine the rendered size of marker points. Use with + `sizemin` and `sizemode`. + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + standoff + Moves the marker away from the data point in the + direction of `angle` (in px). This can be useful for + example if you have another marker at this location and + you want to point an arrowhead marker at it. + standoffsrc + Sets the source reference on Chart Studio Cloud for + `standoff`. + symbol + Sets the marker symbol type. Adding 100 is equivalent + to appending "-open" to a symbol name. Adding 200 is + equivalent to appending "-dot" to a symbol name. Adding + 300 is equivalent to appending "-open-dot" or "dot- + open" to a symbol name. + symbolsrc + Sets the source reference on Chart Studio Cloud for + `symbol`. + + Returns + ------- + Marker + """ + super().__init__("marker") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scatterternary.Marker +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scatterternary.Marker`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("angle", arg, angle) + self._set_property("angleref", arg, angleref) + self._set_property("anglesrc", arg, anglesrc) + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("cauto", arg, cauto) + self._set_property("cmax", arg, cmax) + self._set_property("cmid", arg, cmid) + self._set_property("cmin", arg, cmin) + self._set_property("color", arg, color) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("colorsrc", arg, colorsrc) + self._set_property("gradient", arg, gradient) + self._set_property("line", arg, line) + self._set_property("maxdisplayed", arg, maxdisplayed) + self._set_property("opacity", arg, opacity) + self._set_property("opacitysrc", arg, opacitysrc) + self._set_property("reversescale", arg, reversescale) + self._set_property("showscale", arg, showscale) + self._set_property("size", arg, size) + self._set_property("sizemin", arg, sizemin) + self._set_property("sizemode", arg, sizemode) + self._set_property("sizeref", arg, sizeref) + self._set_property("sizesrc", arg, sizesrc) + self._set_property("standoff", arg, standoff) + self._set_property("standoffsrc", arg, standoffsrc) + self._set_property("symbol", arg, symbol) + self._set_property("symbolsrc", arg, symbolsrc) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_selected.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_selected.py new file mode 100644 index 0000000000000000000000000000000000000000..9259834e78635f859c672a751fc3e42c39264f2d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_selected.py @@ -0,0 +1,106 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Selected(_BaseTraceHierarchyType): + _parent_path_str = "scatterternary" + _path_str = "scatterternary.selected" + _valid_props = {"marker", "textfont"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.selected.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scatterternary.selected.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def textfont(self): + """ + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.selected.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.scatterternary.selected.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.scatterternary.selected.Ma + rker` instance or dict with compatible properties + textfont + :class:`plotly.graph_objects.scatterternary.selected.Te + xtfont` instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, textfont=None, **kwargs): + """ + Construct a new Selected object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scatterternary.Selected` + marker + :class:`plotly.graph_objects.scatterternary.selected.Ma + rker` instance or dict with compatible properties + textfont + :class:`plotly.graph_objects.scatterternary.selected.Te + xtfont` instance or dict with compatible properties + + Returns + ------- + Selected + """ + super().__init__("selected") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scatterternary.Selected +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scatterternary.Selected`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._set_property("textfont", arg, textfont) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..54c0e1e01354cf6ea498329bb37e5b69cff55f30 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_stream.py @@ -0,0 +1,114 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "scatterternary" + _path_str = "scatterternary.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scatterternary.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scatterternary.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scatterternary.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_textfont.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_textfont.py new file mode 100644 index 0000000000000000000000000000000000000000..6a41c4858a085a7ccf7eb855235066dac0fb3bb2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_textfont.py @@ -0,0 +1,587 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Textfont(_BaseTraceHierarchyType): + _parent_path_str = "scatterternary" + _path_str = "scatterternary.textfont" + _valid_props = { + "color", + "colorsrc", + "family", + "familysrc", + "lineposition", + "linepositionsrc", + "shadow", + "shadowsrc", + "size", + "sizesrc", + "style", + "stylesrc", + "textcase", + "textcasesrc", + "variant", + "variantsrc", + "weight", + "weightsrc", + } + + @property + def color(self): + """ + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def colorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `color`. + + The 'colorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["colorsrc"] + + @colorsrc.setter + def colorsrc(self, val): + self["colorsrc"] = val + + @property + def family(self): + """ + HTML font family - the typeface that will be applied by the web + browser. The web browser can only apply a font if it is + available on the system where it runs. Provide multiple font + families, separated by commas, to indicate the order in which + to apply fonts if they aren't available. + + The 'family' property is a string and must be specified as: + - A non-empty string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["family"] + + @family.setter + def family(self, val): + self["family"] = val + + @property + def familysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `family`. + + The 'familysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["familysrc"] + + @familysrc.setter + def familysrc(self, val): + self["familysrc"] = val + + @property + def lineposition(self): + """ + Sets the kind of decoration line(s) with text, such as an + "under", "over" or "through" as well as combinations e.g. + "under+over", etc. + + The 'lineposition' property is a flaglist and may be specified + as a string containing: + - Any combination of ['under', 'over', 'through'] joined with '+' characters + (e.g. 'under+over') + OR exactly one of ['none'] (e.g. 'none') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["lineposition"] + + @lineposition.setter + def lineposition(self, val): + self["lineposition"] = val + + @property + def linepositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `lineposition`. + + The 'linepositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["linepositionsrc"] + + @linepositionsrc.setter + def linepositionsrc(self, val): + self["linepositionsrc"] = val + + @property + def shadow(self): + """ + Sets the shape and color of the shadow behind text. "auto" + places minimal shadow and applies contrast text font color. See + https://developer.mozilla.org/en-US/docs/Web/CSS/text-shadow + for additional options. + + The 'shadow' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["shadow"] + + @shadow.setter + def shadow(self, val): + self["shadow"] = val + + @property + def shadowsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `shadow`. + + The 'shadowsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["shadowsrc"] + + @shadowsrc.setter + def shadowsrc(self, val): + self["shadowsrc"] = val + + @property + def size(self): + """ + The 'size' property is a number and may be specified as: + - An int or float in the interval [1, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def sizesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `size`. + + The 'sizesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["sizesrc"] + + @sizesrc.setter + def sizesrc(self, val): + self["sizesrc"] = val + + @property + def style(self): + """ + Sets whether a font should be styled with a normal or italic + face from its family. + + The 'style' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'italic'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def stylesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `style`. + + The 'stylesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["stylesrc"] + + @stylesrc.setter + def stylesrc(self, val): + self["stylesrc"] = val + + @property + def textcase(self): + """ + Sets capitalization of text. It can be used to make text appear + in all-uppercase or all-lowercase, or with each word + capitalized. + + The 'textcase' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'word caps', 'upper', 'lower'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textcase"] + + @textcase.setter + def textcase(self, val): + self["textcase"] = val + + @property + def textcasesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `textcase`. + + The 'textcasesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textcasesrc"] + + @textcasesrc.setter + def textcasesrc(self, val): + self["textcasesrc"] = val + + @property + def variant(self): + """ + Sets the variant of the font. + + The 'variant' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'small-caps', 'all-small-caps', + 'all-petite-caps', 'petite-caps', 'unicase'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["variant"] + + @variant.setter + def variant(self, val): + self["variant"] = val + + @property + def variantsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `variant`. + + The 'variantsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["variantsrc"] + + @variantsrc.setter + def variantsrc(self, val): + self["variantsrc"] = val + + @property + def weight(self): + """ + Sets the weight (or boldness) of the font. + + The 'weight' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 1000] + OR exactly one of ['normal', 'bold'] (e.g. 'bold') + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["weight"] + + @weight.setter + def weight(self, val): + self["weight"] = val + + @property + def weightsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `weight`. + + The 'weightsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["weightsrc"] + + @weightsrc.setter + def weightsrc(self, val): + self["weightsrc"] = val + + @property + def _prop_descriptions(self): + return """\ + color + + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + familysrc + Sets the source reference on Chart Studio Cloud for + `family`. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + linepositionsrc + Sets the source reference on Chart Studio Cloud for + `lineposition`. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + shadowsrc + Sets the source reference on Chart Studio Cloud for + `shadow`. + size + + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + style + Sets whether a font should be styled with a normal or + italic face from its family. + stylesrc + Sets the source reference on Chart Studio Cloud for + `style`. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + textcasesrc + Sets the source reference on Chart Studio Cloud for + `textcase`. + variant + Sets the variant of the font. + variantsrc + Sets the source reference on Chart Studio Cloud for + `variant`. + weight + Sets the weight (or boldness) of the font. + weightsrc + Sets the source reference on Chart Studio Cloud for + `weight`. + """ + + def __init__( + self, + arg=None, + color=None, + colorsrc=None, + family=None, + familysrc=None, + lineposition=None, + linepositionsrc=None, + shadow=None, + shadowsrc=None, + size=None, + sizesrc=None, + style=None, + stylesrc=None, + textcase=None, + textcasesrc=None, + variant=None, + variantsrc=None, + weight=None, + weightsrc=None, + **kwargs, + ): + """ + Construct a new Textfont object + + Sets the text font. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scatterternary.Textfont` + color + + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + familysrc + Sets the source reference on Chart Studio Cloud for + `family`. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + linepositionsrc + Sets the source reference on Chart Studio Cloud for + `lineposition`. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + shadowsrc + Sets the source reference on Chart Studio Cloud for + `shadow`. + size + + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + style + Sets whether a font should be styled with a normal or + italic face from its family. + stylesrc + Sets the source reference on Chart Studio Cloud for + `style`. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + textcasesrc + Sets the source reference on Chart Studio Cloud for + `textcase`. + variant + Sets the variant of the font. + variantsrc + Sets the source reference on Chart Studio Cloud for + `variant`. + weight + Sets the weight (or boldness) of the font. + weightsrc + Sets the source reference on Chart Studio Cloud for + `weight`. + + Returns + ------- + Textfont + """ + super().__init__("textfont") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scatterternary.Textfont +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scatterternary.Textfont`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("colorsrc", arg, colorsrc) + self._set_property("family", arg, family) + self._set_property("familysrc", arg, familysrc) + self._set_property("lineposition", arg, lineposition) + self._set_property("linepositionsrc", arg, linepositionsrc) + self._set_property("shadow", arg, shadow) + self._set_property("shadowsrc", arg, shadowsrc) + self._set_property("size", arg, size) + self._set_property("sizesrc", arg, sizesrc) + self._set_property("style", arg, style) + self._set_property("stylesrc", arg, stylesrc) + self._set_property("textcase", arg, textcase) + self._set_property("textcasesrc", arg, textcasesrc) + self._set_property("variant", arg, variant) + self._set_property("variantsrc", arg, variantsrc) + self._set_property("weight", arg, weight) + self._set_property("weightsrc", arg, weightsrc) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_unselected.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_unselected.py new file mode 100644 index 0000000000000000000000000000000000000000..f02bb39a2329313cf132c688e08bf0662e8c6c15 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/scatterternary/_unselected.py @@ -0,0 +1,106 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Unselected(_BaseTraceHierarchyType): + _parent_path_str = "scatterternary" + _path_str = "scatterternary.unselected" + _valid_props = {"marker", "textfont"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.unselected.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.scatterternary.unselected.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def textfont(self): + """ + The 'textfont' property is an instance of Textfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.scatterternary.unselected.Textfont` + - A dict of string/value properties that will be passed + to the Textfont constructor + + Returns + ------- + plotly.graph_objs.scatterternary.unselected.Textfont + """ + return self["textfont"] + + @textfont.setter + def textfont(self, val): + self["textfont"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.scatterternary.unselected. + Marker` instance or dict with compatible properties + textfont + :class:`plotly.graph_objects.scatterternary.unselected. + Textfont` instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, textfont=None, **kwargs): + """ + Construct a new Unselected object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.scatterternary.Unselected` + marker + :class:`plotly.graph_objects.scatterternary.unselected. + Marker` instance or dict with compatible properties + textfont + :class:`plotly.graph_objects.scatterternary.unselected. + Textfont` instance or dict with compatible properties + + Returns + ------- + Unselected + """ + super().__init__("unselected") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.scatterternary.Unselected +constructor must be a dict or +an instance of :class:`plotly.graph_objs.scatterternary.Unselected`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._set_property("textfont", arg, textfont) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..200342cb23a6f85c4bf689fb26f396d9d18db5ad --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/__init__.py @@ -0,0 +1,42 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._diagonal import Diagonal + from ._dimension import Dimension + from ._hoverlabel import Hoverlabel + from ._legendgrouptitle import Legendgrouptitle + from ._marker import Marker + from ._selected import Selected + from ._stream import Stream + from ._unselected import Unselected + from . import dimension + from . import hoverlabel + from . import legendgrouptitle + from . import marker + from . import selected + from . import unselected +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [ + ".dimension", + ".hoverlabel", + ".legendgrouptitle", + ".marker", + ".selected", + ".unselected", + ], + [ + "._diagonal.Diagonal", + "._dimension.Dimension", + "._hoverlabel.Hoverlabel", + "._legendgrouptitle.Legendgrouptitle", + "._marker.Marker", + "._selected.Selected", + "._stream.Stream", + "._unselected.Unselected", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_diagonal.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_diagonal.py new file mode 100644 index 0000000000000000000000000000000000000000..49a9cf75097e127f54a2da0c7487c8c4947d67be --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_diagonal.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Diagonal(_BaseTraceHierarchyType): + _parent_path_str = "splom" + _path_str = "splom.diagonal" + _valid_props = {"visible"} + + @property + def visible(self): + """ + Determines whether or not subplots on the diagonal are + displayed. + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def _prop_descriptions(self): + return """\ + visible + Determines whether or not subplots on the diagonal are + displayed. + """ + + def __init__(self, arg=None, visible=None, **kwargs): + """ + Construct a new Diagonal object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.splom.Diagonal` + visible + Determines whether or not subplots on the diagonal are + displayed. + + Returns + ------- + Diagonal + """ + super().__init__("diagonal") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.splom.Diagonal +constructor must be a dict or +an instance of :class:`plotly.graph_objs.splom.Diagonal`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("visible", arg, visible) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_dimension.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_dimension.py new file mode 100644 index 0000000000000000000000000000000000000000..14f8d5e28b1715daec4b27f656538d6e8d43bb5a --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_dimension.py @@ -0,0 +1,293 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Dimension(_BaseTraceHierarchyType): + _parent_path_str = "splom" + _path_str = "splom.dimension" + _valid_props = { + "axis", + "label", + "name", + "templateitemname", + "values", + "valuessrc", + "visible", + } + + @property + def axis(self): + """ + The 'axis' property is an instance of Axis + that may be specified as: + - An instance of :class:`plotly.graph_objs.splom.dimension.Axis` + - A dict of string/value properties that will be passed + to the Axis constructor + + Returns + ------- + plotly.graph_objs.splom.dimension.Axis + """ + return self["axis"] + + @axis.setter + def axis(self, val): + self["axis"] = val + + @property + def label(self): + """ + Sets the label corresponding to this splom dimension. + + The 'label' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["label"] + + @label.setter + def label(self, val): + self["label"] = val + + @property + def name(self): + """ + When used in a template, named items are created in the output + figure in addition to any items the figure already has in this + array. You can modify these items in the output figure by + making your own item with `templateitemname` matching this + `name` alongside your modifications (including `visible: false` + or `enabled: false` to hide it). Has no effect outside of a + template. + + The 'name' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["name"] + + @name.setter + def name(self, val): + self["name"] = val + + @property + def templateitemname(self): + """ + Used to refer to a named item in this array in the template. + Named items from the template will be created even without a + matching item in the input figure, but you can modify one by + making an item with `templateitemname` matching its `name`, + alongside your modifications (including `visible: false` or + `enabled: false` to hide it). If there is no template or no + matching item, this item will be hidden unless you explicitly + show it with `visible: true`. + + The 'templateitemname' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["templateitemname"] + + @templateitemname.setter + def templateitemname(self, val): + self["templateitemname"] = val + + @property + def values(self): + """ + Sets the dimension values to be plotted. + + The 'values' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["values"] + + @values.setter + def values(self, val): + self["values"] = val + + @property + def valuessrc(self): + """ + Sets the source reference on Chart Studio Cloud for `values`. + + The 'valuessrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["valuessrc"] + + @valuessrc.setter + def valuessrc(self, val): + self["valuessrc"] = val + + @property + def visible(self): + """ + Determines whether or not this dimension is shown on the graph. + Note that even visible false dimension contribute to the + default grid generate by this splom trace. + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def _prop_descriptions(self): + return """\ + axis + :class:`plotly.graph_objects.splom.dimension.Axis` + instance or dict with compatible properties + label + Sets the label corresponding to this splom dimension. + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + values + Sets the dimension values to be plotted. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this dimension is shown on + the graph. Note that even visible false dimension + contribute to the default grid generate by this splom + trace. + """ + + def __init__( + self, + arg=None, + axis=None, + label=None, + name=None, + templateitemname=None, + values=None, + valuessrc=None, + visible=None, + **kwargs, + ): + """ + Construct a new Dimension object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.splom.Dimension` + axis + :class:`plotly.graph_objects.splom.dimension.Axis` + instance or dict with compatible properties + label + Sets the label corresponding to this splom dimension. + name + When used in a template, named items are created in the + output figure in addition to any items the figure + already has in this array. You can modify these items + in the output figure by making your own item with + `templateitemname` matching this `name` alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). Has no effect outside of a + template. + templateitemname + Used to refer to a named item in this array in the + template. Named items from the template will be created + even without a matching item in the input figure, but + you can modify one by making an item with + `templateitemname` matching its `name`, alongside your + modifications (including `visible: false` or `enabled: + false` to hide it). If there is no template or no + matching item, this item will be hidden unless you + explicitly show it with `visible: true`. + values + Sets the dimension values to be plotted. + valuessrc + Sets the source reference on Chart Studio Cloud for + `values`. + visible + Determines whether or not this dimension is shown on + the graph. Note that even visible false dimension + contribute to the default grid generate by this splom + trace. + + Returns + ------- + Dimension + """ + super().__init__("dimensions") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.splom.Dimension +constructor must be a dict or +an instance of :class:`plotly.graph_objs.splom.Dimension`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("axis", arg, axis) + self._set_property("label", arg, label) + self._set_property("name", arg, name) + self._set_property("templateitemname", arg, templateitemname) + self._set_property("values", arg, values) + self._set_property("valuessrc", arg, valuessrc) + self._set_property("visible", arg, visible) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_hoverlabel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_hoverlabel.py new file mode 100644 index 0000000000000000000000000000000000000000..36b2c5eeb4a9d838782f30cbcb31a57786e19b06 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_hoverlabel.py @@ -0,0 +1,366 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Hoverlabel(_BaseTraceHierarchyType): + _parent_path_str = "splom" + _path_str = "splom.hoverlabel" + _valid_props = { + "align", + "alignsrc", + "bgcolor", + "bgcolorsrc", + "bordercolor", + "bordercolorsrc", + "font", + "namelength", + "namelengthsrc", + "showarrow", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the text content within hover + label box. Has an effect only if the hover label text spans + more two or more lines + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'auto'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def alignsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `align`. + + The 'alignsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["alignsrc"] + + @alignsrc.setter + def alignsrc(self, val): + self["alignsrc"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the hover labels for this trace + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bgcolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `bgcolor`. + + The 'bgcolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bgcolorsrc"] + + @bgcolorsrc.setter + def bgcolorsrc(self, val): + self["bgcolorsrc"] = val + + @property + def bordercolor(self): + """ + Sets the border color of the hover labels for this trace. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def bordercolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + + The 'bordercolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bordercolorsrc"] + + @bordercolorsrc.setter + def bordercolorsrc(self, val): + self["bordercolorsrc"] = val + + @property + def font(self): + """ + Sets the font used in hover labels. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.splom.hoverlabel.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.splom.hoverlabel.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def namelength(self): + """ + Sets the default length (in number of characters) of the trace + name in the hover labels for all traces. -1 shows the whole + name regardless of length. 0-3 shows the first 0-3 characters, + and an integer >3 will show the whole name if it is less than + that many characters, but if it is longer, will truncate to + `namelength - 3` characters and add an ellipsis. + + The 'namelength' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["namelength"] + + @namelength.setter + def namelength(self, val): + self["namelength"] = val + + @property + def namelengthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `namelength`. + + The 'namelengthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["namelengthsrc"] + + @namelengthsrc.setter + def namelengthsrc(self, val): + self["namelengthsrc"] = val + + @property + def showarrow(self): + """ + Sets whether or not to show the hover label arrow/triangle + pointing to the data point. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + """ + + def __init__( + self, + arg=None, + align=None, + alignsrc=None, + bgcolor=None, + bgcolorsrc=None, + bordercolor=None, + bordercolorsrc=None, + font=None, + namelength=None, + namelengthsrc=None, + showarrow=None, + **kwargs, + ): + """ + Construct a new Hoverlabel object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.splom.Hoverlabel` + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + + Returns + ------- + Hoverlabel + """ + super().__init__("hoverlabel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.splom.Hoverlabel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.splom.Hoverlabel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("alignsrc", arg, alignsrc) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bgcolorsrc", arg, bgcolorsrc) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("bordercolorsrc", arg, bordercolorsrc) + self._set_property("font", arg, font) + self._set_property("namelength", arg, namelength) + self._set_property("namelengthsrc", arg, namelengthsrc) + self._set_property("showarrow", arg, showarrow) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..e2def1938b088fac71a3965f67f47e3004d38cc8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "splom" + _path_str = "splom.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.splom.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.splom.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.splom.Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.splom.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.splom.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_marker.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_marker.py new file mode 100644 index 0000000000000000000000000000000000000000..f42ce026a6275e026639c22174b09931802c5630 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_marker.py @@ -0,0 +1,977 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Marker(_BaseTraceHierarchyType): + _parent_path_str = "splom" + _path_str = "splom.marker" + _valid_props = { + "angle", + "anglesrc", + "autocolorscale", + "cauto", + "cmax", + "cmid", + "cmin", + "color", + "coloraxis", + "colorbar", + "colorscale", + "colorsrc", + "line", + "opacity", + "opacitysrc", + "reversescale", + "showscale", + "size", + "sizemin", + "sizemode", + "sizeref", + "sizesrc", + "symbol", + "symbolsrc", + } + + @property + def angle(self): + """ + Sets the marker angle in respect to `angleref`. + + The 'angle' property is a angle (in degrees) that may be + specified as a number between -180 and 180, or a list, numpy array or other iterable thereof. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float|numpy.ndarray + """ + return self["angle"] + + @angle.setter + def angle(self, val): + self["angle"] = val + + @property + def anglesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `angle`. + + The 'anglesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["anglesrc"] + + @anglesrc.setter + def anglesrc(self, val): + self["anglesrc"] = val + + @property + def autocolorscale(self): + """ + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `marker.colorscale`. Has an effect only if in `marker.color` is + set to a numerical array. In case `colorscale` is unspecified + or `autocolorscale` is true, the default palette will be chosen + according to whether numbers in the `color` array are all + positive, all negative or mixed. + + The 'autocolorscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["autocolorscale"] + + @autocolorscale.setter + def autocolorscale(self, val): + self["autocolorscale"] = val + + @property + def cauto(self): + """ + Determines whether or not the color domain is computed with + respect to the input data (here in `marker.color`) or the + bounds set in `marker.cmin` and `marker.cmax` Has an effect + only if in `marker.color` is set to a numerical array. Defaults + to `false` when `marker.cmin` and `marker.cmax` are set by the + user. + + The 'cauto' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["cauto"] + + @cauto.setter + def cauto(self, val): + self["cauto"] = val + + @property + def cmax(self): + """ + Sets the upper bound of the color domain. Has an effect only if + in `marker.color` is set to a numerical array. Value should + have the same units as in `marker.color` and if set, + `marker.cmin` must be set as well. + + The 'cmax' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmax"] + + @cmax.setter + def cmax(self, val): + self["cmax"] = val + + @property + def cmid(self): + """ + Sets the mid-point of the color domain by scaling `marker.cmin` + and/or `marker.cmax` to be equidistant to this point. Has an + effect only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color`. Has no + effect when `marker.cauto` is `false`. + + The 'cmid' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmid"] + + @cmid.setter + def cmid(self, val): + self["cmid"] = val + + @property + def cmin(self): + """ + Sets the lower bound of the color domain. Has an effect only if + in `marker.color` is set to a numerical array. Value should + have the same units as in `marker.color` and if set, + `marker.cmax` must be set as well. + + The 'cmin' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["cmin"] + + @cmin.setter + def cmin(self, val): + self["cmin"] = val + + @property + def color(self): + """ + Sets the marker color. It accepts either a specific color or an + array of numbers that are mapped to the colorscale relative to + the max and min values of the array or relative to + `marker.cmin` and `marker.cmax` if set. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A number that will be interpreted as a color + according to splom.marker.colorscale + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def coloraxis(self): + """ + Sets a reference to a shared color axis. References to these + shared color axes are "coloraxis", "coloraxis2", "coloraxis3", + etc. Settings for these shared color axes are set in the + layout, under `layout.coloraxis`, `layout.coloraxis2`, etc. + Note that multiple color scales can be linked to the same color + axis. + + The 'coloraxis' property is an identifier of a particular + subplot, of type 'coloraxis', that may be specified as: + - the string 'coloraxis' optionally followed by an integer >= 1 + (e.g. 'coloraxis', 'coloraxis1', 'coloraxis2', 'coloraxis3', etc.) + + Returns + ------- + str + """ + return self["coloraxis"] + + @coloraxis.setter + def coloraxis(self, val): + self["coloraxis"] = val + + @property + def colorbar(self): + """ + The 'colorbar' property is an instance of ColorBar + that may be specified as: + - An instance of :class:`plotly.graph_objs.splom.marker.ColorBar` + - A dict of string/value properties that will be passed + to the ColorBar constructor + + Returns + ------- + plotly.graph_objs.splom.marker.ColorBar + """ + return self["colorbar"] + + @colorbar.setter + def colorbar(self, val): + self["colorbar"] = val + + @property + def colorscale(self): + """ + Sets the colorscale. Has an effect only if in `marker.color` is + set to a numerical array. The colorscale must be an array + containing arrays mapping a normalized value to an rgb, rgba, + hex, hsl, hsv, or named color string. At minimum, a mapping for + the lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. To + control the bounds of the colorscale in color space, use + `marker.cmin` and `marker.cmax`. Alternatively, `colorscale` + may be a palette name string of the following list: Blackbody,B + luered,Blues,Cividis,Earth,Electric,Greens,Greys,Hot,Jet,Picnic + ,Portland,Rainbow,RdBu,Reds,Viridis,YlGnBu,YlOrRd. + + The 'colorscale' property is a colorscale and may be + specified as: + - A list of colors that will be spaced evenly to create the colorscale. + Many predefined colorscale lists are included in the sequential, diverging, + and cyclical modules in the plotly.colors package. + - A list of 2-element lists where the first element is the + normalized color level value (starting at 0 and ending at 1), + and the second item is a valid color string. + (e.g. [[0, 'green'], [0.5, 'red'], [1.0, 'rgb(0, 0, 255)']]) + - One of the following named colorscales: + ['aggrnyl', 'agsunset', 'algae', 'amp', 'armyrose', 'balance', + 'blackbody', 'bluered', 'blues', 'blugrn', 'bluyl', 'brbg', + 'brwnyl', 'bugn', 'bupu', 'burg', 'burgyl', 'cividis', 'curl', + 'darkmint', 'deep', 'delta', 'dense', 'earth', 'edge', 'electric', + 'emrld', 'fall', 'geyser', 'gnbu', 'gray', 'greens', 'greys', + 'haline', 'hot', 'hsv', 'ice', 'icefire', 'inferno', 'jet', + 'magenta', 'magma', 'matter', 'mint', 'mrybm', 'mygbm', 'oranges', + 'orrd', 'oryel', 'oxy', 'peach', 'phase', 'picnic', 'pinkyl', + 'piyg', 'plasma', 'plotly3', 'portland', 'prgn', 'pubu', 'pubugn', + 'puor', 'purd', 'purp', 'purples', 'purpor', 'rainbow', 'rdbu', + 'rdgy', 'rdpu', 'rdylbu', 'rdylgn', 'redor', 'reds', 'solar', + 'spectral', 'speed', 'sunset', 'sunsetdark', 'teal', 'tealgrn', + 'tealrose', 'tempo', 'temps', 'thermal', 'tropic', 'turbid', + 'turbo', 'twilight', 'viridis', 'ylgn', 'ylgnbu', 'ylorbr', + 'ylorrd']. + Appending '_r' to a named colorscale reverses it. + + Returns + ------- + str + """ + return self["colorscale"] + + @colorscale.setter + def colorscale(self, val): + self["colorscale"] = val + + @property + def colorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `color`. + + The 'colorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["colorsrc"] + + @colorsrc.setter + def colorsrc(self, val): + self["colorsrc"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.splom.marker.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.splom.marker.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def opacity(self): + """ + Sets the marker opacity. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def opacitysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `opacity`. + + The 'opacitysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["opacitysrc"] + + @opacitysrc.setter + def opacitysrc(self, val): + self["opacitysrc"] = val + + @property + def reversescale(self): + """ + Reverses the color mapping if true. Has an effect only if in + `marker.color` is set to a numerical array. If true, + `marker.cmin` will correspond to the last color in the array + and `marker.cmax` will correspond to the first color. + + The 'reversescale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["reversescale"] + + @reversescale.setter + def reversescale(self, val): + self["reversescale"] = val + + @property + def showscale(self): + """ + Determines whether or not a colorbar is displayed for this + trace. Has an effect only if in `marker.color` is set to a + numerical array. + + The 'showscale' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showscale"] + + @showscale.setter + def showscale(self, val): + self["showscale"] = val + + @property + def size(self): + """ + Sets the marker size (in px). + + The 'size' property is a number and may be specified as: + - An int or float in the interval [0, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def sizemin(self): + """ + Has an effect only if `marker.size` is set to a numerical + array. Sets the minimum size (in px) of the rendered marker + points. + + The 'sizemin' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["sizemin"] + + @sizemin.setter + def sizemin(self, val): + self["sizemin"] = val + + @property + def sizemode(self): + """ + Has an effect only if `marker.size` is set to a numerical + array. Sets the rule for which the data in `size` is converted + to pixels. + + The 'sizemode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['diameter', 'area'] + + Returns + ------- + Any + """ + return self["sizemode"] + + @sizemode.setter + def sizemode(self, val): + self["sizemode"] = val + + @property + def sizeref(self): + """ + Has an effect only if `marker.size` is set to a numerical + array. Sets the scale factor used to determine the rendered + size of marker points. Use with `sizemin` and `sizemode`. + + The 'sizeref' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["sizeref"] + + @sizeref.setter + def sizeref(self, val): + self["sizeref"] = val + + @property + def sizesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `size`. + + The 'sizesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["sizesrc"] + + @sizesrc.setter + def sizesrc(self, val): + self["sizesrc"] = val + + @property + def symbol(self): + """ + Sets the marker symbol type. Adding 100 is equivalent to + appending "-open" to a symbol name. Adding 200 is equivalent to + appending "-dot" to a symbol name. Adding 300 is equivalent to + appending "-open-dot" or "dot-open" to a symbol name. + + The 'symbol' property is an enumeration that may be specified as: + - One of the following enumeration values: + [0, '0', 'circle', 100, '100', 'circle-open', 200, '200', + 'circle-dot', 300, '300', 'circle-open-dot', 1, '1', + 'square', 101, '101', 'square-open', 201, '201', + 'square-dot', 301, '301', 'square-open-dot', 2, '2', + 'diamond', 102, '102', 'diamond-open', 202, '202', + 'diamond-dot', 302, '302', 'diamond-open-dot', 3, '3', + 'cross', 103, '103', 'cross-open', 203, '203', + 'cross-dot', 303, '303', 'cross-open-dot', 4, '4', 'x', + 104, '104', 'x-open', 204, '204', 'x-dot', 304, '304', + 'x-open-dot', 5, '5', 'triangle-up', 105, '105', + 'triangle-up-open', 205, '205', 'triangle-up-dot', 305, + '305', 'triangle-up-open-dot', 6, '6', 'triangle-down', + 106, '106', 'triangle-down-open', 206, '206', + 'triangle-down-dot', 306, '306', 'triangle-down-open-dot', + 7, '7', 'triangle-left', 107, '107', 'triangle-left-open', + 207, '207', 'triangle-left-dot', 307, '307', + 'triangle-left-open-dot', 8, '8', 'triangle-right', 108, + '108', 'triangle-right-open', 208, '208', + 'triangle-right-dot', 308, '308', + 'triangle-right-open-dot', 9, '9', 'triangle-ne', 109, + '109', 'triangle-ne-open', 209, '209', 'triangle-ne-dot', + 309, '309', 'triangle-ne-open-dot', 10, '10', + 'triangle-se', 110, '110', 'triangle-se-open', 210, '210', + 'triangle-se-dot', 310, '310', 'triangle-se-open-dot', 11, + '11', 'triangle-sw', 111, '111', 'triangle-sw-open', 211, + '211', 'triangle-sw-dot', 311, '311', + 'triangle-sw-open-dot', 12, '12', 'triangle-nw', 112, + '112', 'triangle-nw-open', 212, '212', 'triangle-nw-dot', + 312, '312', 'triangle-nw-open-dot', 13, '13', 'pentagon', + 113, '113', 'pentagon-open', 213, '213', 'pentagon-dot', + 313, '313', 'pentagon-open-dot', 14, '14', 'hexagon', 114, + '114', 'hexagon-open', 214, '214', 'hexagon-dot', 314, + '314', 'hexagon-open-dot', 15, '15', 'hexagon2', 115, + '115', 'hexagon2-open', 215, '215', 'hexagon2-dot', 315, + '315', 'hexagon2-open-dot', 16, '16', 'octagon', 116, + '116', 'octagon-open', 216, '216', 'octagon-dot', 316, + '316', 'octagon-open-dot', 17, '17', 'star', 117, '117', + 'star-open', 217, '217', 'star-dot', 317, '317', + 'star-open-dot', 18, '18', 'hexagram', 118, '118', + 'hexagram-open', 218, '218', 'hexagram-dot', 318, '318', + 'hexagram-open-dot', 19, '19', 'star-triangle-up', 119, + '119', 'star-triangle-up-open', 219, '219', + 'star-triangle-up-dot', 319, '319', + 'star-triangle-up-open-dot', 20, '20', + 'star-triangle-down', 120, '120', + 'star-triangle-down-open', 220, '220', + 'star-triangle-down-dot', 320, '320', + 'star-triangle-down-open-dot', 21, '21', 'star-square', + 121, '121', 'star-square-open', 221, '221', + 'star-square-dot', 321, '321', 'star-square-open-dot', 22, + '22', 'star-diamond', 122, '122', 'star-diamond-open', + 222, '222', 'star-diamond-dot', 322, '322', + 'star-diamond-open-dot', 23, '23', 'diamond-tall', 123, + '123', 'diamond-tall-open', 223, '223', + 'diamond-tall-dot', 323, '323', 'diamond-tall-open-dot', + 24, '24', 'diamond-wide', 124, '124', 'diamond-wide-open', + 224, '224', 'diamond-wide-dot', 324, '324', + 'diamond-wide-open-dot', 25, '25', 'hourglass', 125, + '125', 'hourglass-open', 26, '26', 'bowtie', 126, '126', + 'bowtie-open', 27, '27', 'circle-cross', 127, '127', + 'circle-cross-open', 28, '28', 'circle-x', 128, '128', + 'circle-x-open', 29, '29', 'square-cross', 129, '129', + 'square-cross-open', 30, '30', 'square-x', 130, '130', + 'square-x-open', 31, '31', 'diamond-cross', 131, '131', + 'diamond-cross-open', 32, '32', 'diamond-x', 132, '132', + 'diamond-x-open', 33, '33', 'cross-thin', 133, '133', + 'cross-thin-open', 34, '34', 'x-thin', 134, '134', + 'x-thin-open', 35, '35', 'asterisk', 135, '135', + 'asterisk-open', 36, '36', 'hash', 136, '136', + 'hash-open', 236, '236', 'hash-dot', 336, '336', + 'hash-open-dot', 37, '37', 'y-up', 137, '137', + 'y-up-open', 38, '38', 'y-down', 138, '138', + 'y-down-open', 39, '39', 'y-left', 139, '139', + 'y-left-open', 40, '40', 'y-right', 140, '140', + 'y-right-open', 41, '41', 'line-ew', 141, '141', + 'line-ew-open', 42, '42', 'line-ns', 142, '142', + 'line-ns-open', 43, '43', 'line-ne', 143, '143', + 'line-ne-open', 44, '44', 'line-nw', 144, '144', + 'line-nw-open', 45, '45', 'arrow-up', 145, '145', + 'arrow-up-open', 46, '46', 'arrow-down', 146, '146', + 'arrow-down-open', 47, '47', 'arrow-left', 147, '147', + 'arrow-left-open', 48, '48', 'arrow-right', 148, '148', + 'arrow-right-open', 49, '49', 'arrow-bar-up', 149, '149', + 'arrow-bar-up-open', 50, '50', 'arrow-bar-down', 150, + '150', 'arrow-bar-down-open', 51, '51', 'arrow-bar-left', + 151, '151', 'arrow-bar-left-open', 52, '52', + 'arrow-bar-right', 152, '152', 'arrow-bar-right-open', 53, + '53', 'arrow', 153, '153', 'arrow-open', 54, '54', + 'arrow-wide', 154, '154', 'arrow-wide-open'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["symbol"] + + @symbol.setter + def symbol(self, val): + self["symbol"] = val + + @property + def symbolsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `symbol`. + + The 'symbolsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["symbolsrc"] + + @symbolsrc.setter + def symbolsrc(self, val): + self["symbolsrc"] = val + + @property + def _prop_descriptions(self): + return """\ + angle + Sets the marker angle in respect to `angleref`. + anglesrc + Sets the source reference on Chart Studio Cloud for + `angle`. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `marker.colorscale`. Has an effect only if in + `marker.color` is set to a numerical array. In case + `colorscale` is unspecified or `autocolorscale` is + true, the default palette will be chosen according to + whether numbers in the `color` array are all positive, + all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here in `marker.color`) + or the bounds set in `marker.cmin` and `marker.cmax` + Has an effect only if in `marker.color` is set to a + numerical array. Defaults to `false` when `marker.cmin` + and `marker.cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `marker.cmin` and/or `marker.cmax` to be equidistant to + this point. Has an effect only if in `marker.color` is + set to a numerical array. Value should have the same + units as in `marker.color`. Has no effect when + `marker.cauto` is `false`. + cmin + Sets the lower bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmax` must be set as well. + color + Sets the marker color. It accepts either a specific + color or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `marker.cmin` and `marker.cmax` if + set. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.splom.marker.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. Has an effect only if in + `marker.color` is set to a numerical array. The + colorscale must be an array containing arrays mapping a + normalized value to an rgb, rgba, hex, hsl, hsv, or + named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. + To control the bounds of the colorscale in color space, + use `marker.cmin` and `marker.cmax`. Alternatively, + `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,E + lectric,Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,Rd + Bu,Reds,Viridis,YlGnBu,YlOrRd. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + line + :class:`plotly.graph_objects.splom.marker.Line` + instance or dict with compatible properties + opacity + Sets the marker opacity. + opacitysrc + Sets the source reference on Chart Studio Cloud for + `opacity`. + reversescale + Reverses the color mapping if true. Has an effect only + if in `marker.color` is set to a numerical array. If + true, `marker.cmin` will correspond to the last color + in the array and `marker.cmax` will correspond to the + first color. + showscale + Determines whether or not a colorbar is displayed for + this trace. Has an effect only if in `marker.color` is + set to a numerical array. + size + Sets the marker size (in px). + sizemin + Has an effect only if `marker.size` is set to a + numerical array. Sets the minimum size (in px) of the + rendered marker points. + sizemode + Has an effect only if `marker.size` is set to a + numerical array. Sets the rule for which the data in + `size` is converted to pixels. + sizeref + Has an effect only if `marker.size` is set to a + numerical array. Sets the scale factor used to + determine the rendered size of marker points. Use with + `sizemin` and `sizemode`. + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + symbol + Sets the marker symbol type. Adding 100 is equivalent + to appending "-open" to a symbol name. Adding 200 is + equivalent to appending "-dot" to a symbol name. Adding + 300 is equivalent to appending "-open-dot" or "dot- + open" to a symbol name. + symbolsrc + Sets the source reference on Chart Studio Cloud for + `symbol`. + """ + + def __init__( + self, + arg=None, + angle=None, + anglesrc=None, + autocolorscale=None, + cauto=None, + cmax=None, + cmid=None, + cmin=None, + color=None, + coloraxis=None, + colorbar=None, + colorscale=None, + colorsrc=None, + line=None, + opacity=None, + opacitysrc=None, + reversescale=None, + showscale=None, + size=None, + sizemin=None, + sizemode=None, + sizeref=None, + sizesrc=None, + symbol=None, + symbolsrc=None, + **kwargs, + ): + """ + Construct a new Marker object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.splom.Marker` + angle + Sets the marker angle in respect to `angleref`. + anglesrc + Sets the source reference on Chart Studio Cloud for + `angle`. + autocolorscale + Determines whether the colorscale is a default palette + (`autocolorscale: true`) or the palette determined by + `marker.colorscale`. Has an effect only if in + `marker.color` is set to a numerical array. In case + `colorscale` is unspecified or `autocolorscale` is + true, the default palette will be chosen according to + whether numbers in the `color` array are all positive, + all negative or mixed. + cauto + Determines whether or not the color domain is computed + with respect to the input data (here in `marker.color`) + or the bounds set in `marker.cmin` and `marker.cmax` + Has an effect only if in `marker.color` is set to a + numerical array. Defaults to `false` when `marker.cmin` + and `marker.cmax` are set by the user. + cmax + Sets the upper bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmin` must be set as well. + cmid + Sets the mid-point of the color domain by scaling + `marker.cmin` and/or `marker.cmax` to be equidistant to + this point. Has an effect only if in `marker.color` is + set to a numerical array. Value should have the same + units as in `marker.color`. Has no effect when + `marker.cauto` is `false`. + cmin + Sets the lower bound of the color domain. Has an effect + only if in `marker.color` is set to a numerical array. + Value should have the same units as in `marker.color` + and if set, `marker.cmax` must be set as well. + color + Sets the marker color. It accepts either a specific + color or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `marker.cmin` and `marker.cmax` if + set. + coloraxis + Sets a reference to a shared color axis. References to + these shared color axes are "coloraxis", "coloraxis2", + "coloraxis3", etc. Settings for these shared color axes + are set in the layout, under `layout.coloraxis`, + `layout.coloraxis2`, etc. Note that multiple color + scales can be linked to the same color axis. + colorbar + :class:`plotly.graph_objects.splom.marker.ColorBar` + instance or dict with compatible properties + colorscale + Sets the colorscale. Has an effect only if in + `marker.color` is set to a numerical array. The + colorscale must be an array containing arrays mapping a + normalized value to an rgb, rgba, hex, hsl, hsv, or + named color string. At minimum, a mapping for the + lowest (0) and highest (1) values are required. For + example, `[[0, 'rgb(0,0,255)'], [1, 'rgb(255,0,0)']]`. + To control the bounds of the colorscale in color space, + use `marker.cmin` and `marker.cmax`. Alternatively, + `colorscale` may be a palette name string of the + following list: Blackbody,Bluered,Blues,Cividis,Earth,E + lectric,Greens,Greys,Hot,Jet,Picnic,Portland,Rainbow,Rd + Bu,Reds,Viridis,YlGnBu,YlOrRd. + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + line + :class:`plotly.graph_objects.splom.marker.Line` + instance or dict with compatible properties + opacity + Sets the marker opacity. + opacitysrc + Sets the source reference on Chart Studio Cloud for + `opacity`. + reversescale + Reverses the color mapping if true. Has an effect only + if in `marker.color` is set to a numerical array. If + true, `marker.cmin` will correspond to the last color + in the array and `marker.cmax` will correspond to the + first color. + showscale + Determines whether or not a colorbar is displayed for + this trace. Has an effect only if in `marker.color` is + set to a numerical array. + size + Sets the marker size (in px). + sizemin + Has an effect only if `marker.size` is set to a + numerical array. Sets the minimum size (in px) of the + rendered marker points. + sizemode + Has an effect only if `marker.size` is set to a + numerical array. Sets the rule for which the data in + `size` is converted to pixels. + sizeref + Has an effect only if `marker.size` is set to a + numerical array. Sets the scale factor used to + determine the rendered size of marker points. Use with + `sizemin` and `sizemode`. + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + symbol + Sets the marker symbol type. Adding 100 is equivalent + to appending "-open" to a symbol name. Adding 200 is + equivalent to appending "-dot" to a symbol name. Adding + 300 is equivalent to appending "-open-dot" or "dot- + open" to a symbol name. + symbolsrc + Sets the source reference on Chart Studio Cloud for + `symbol`. + + Returns + ------- + Marker + """ + super().__init__("marker") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.splom.Marker +constructor must be a dict or +an instance of :class:`plotly.graph_objs.splom.Marker`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("angle", arg, angle) + self._set_property("anglesrc", arg, anglesrc) + self._set_property("autocolorscale", arg, autocolorscale) + self._set_property("cauto", arg, cauto) + self._set_property("cmax", arg, cmax) + self._set_property("cmid", arg, cmid) + self._set_property("cmin", arg, cmin) + self._set_property("color", arg, color) + self._set_property("coloraxis", arg, coloraxis) + self._set_property("colorbar", arg, colorbar) + self._set_property("colorscale", arg, colorscale) + self._set_property("colorsrc", arg, colorsrc) + self._set_property("line", arg, line) + self._set_property("opacity", arg, opacity) + self._set_property("opacitysrc", arg, opacitysrc) + self._set_property("reversescale", arg, reversescale) + self._set_property("showscale", arg, showscale) + self._set_property("size", arg, size) + self._set_property("sizemin", arg, sizemin) + self._set_property("sizemode", arg, sizemode) + self._set_property("sizeref", arg, sizeref) + self._set_property("sizesrc", arg, sizesrc) + self._set_property("symbol", arg, symbol) + self._set_property("symbolsrc", arg, symbolsrc) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_selected.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_selected.py new file mode 100644 index 0000000000000000000000000000000000000000..964b3a6a5998e26e3feffa0b4f872ad5d7319b6c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_selected.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Selected(_BaseTraceHierarchyType): + _parent_path_str = "splom" + _path_str = "splom.selected" + _valid_props = {"marker"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.splom.selected.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.splom.selected.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.splom.selected.Marker` + instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, **kwargs): + """ + Construct a new Selected object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.splom.Selected` + marker + :class:`plotly.graph_objects.splom.selected.Marker` + instance or dict with compatible properties + + Returns + ------- + Selected + """ + super().__init__("selected") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.splom.Selected +constructor must be a dict or +an instance of :class:`plotly.graph_objs.splom.Selected`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..169722514fba680575658599e0286634eba7bfa9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_stream.py @@ -0,0 +1,113 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "splom" + _path_str = "splom.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.splom.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.splom.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.splom.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_unselected.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_unselected.py new file mode 100644 index 0000000000000000000000000000000000000000..bcf6df6f77d89e0b0c2bacac86f9ac0d21c4beb8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/splom/_unselected.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Unselected(_BaseTraceHierarchyType): + _parent_path_str = "splom" + _path_str = "splom.unselected" + _valid_props = {"marker"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.splom.unselected.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.splom.unselected.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.splom.unselected.Marker` + instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, **kwargs): + """ + Construct a new Unselected object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.splom.Unselected` + marker + :class:`plotly.graph_objects.splom.unselected.Marker` + instance or dict with compatible properties + + Returns + ------- + Unselected + """ + super().__init__("unselected") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.splom.Unselected +constructor must be a dict or +an instance of :class:`plotly.graph_objs.splom.Unselected`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..d141858f537a7fe51589ee6f936f7b815c44230e --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/__init__.py @@ -0,0 +1,30 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._colorbar import ColorBar + from ._hoverlabel import Hoverlabel + from ._legendgrouptitle import Legendgrouptitle + from ._lighting import Lighting + from ._lightposition import Lightposition + from ._starts import Starts + from ._stream import Stream + from . import colorbar + from . import hoverlabel + from . import legendgrouptitle +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [".colorbar", ".hoverlabel", ".legendgrouptitle"], + [ + "._colorbar.ColorBar", + "._hoverlabel.Hoverlabel", + "._legendgrouptitle.Legendgrouptitle", + "._lighting.Lighting", + "._lightposition.Lightposition", + "._starts.Starts", + "._stream.Stream", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_colorbar.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_colorbar.py new file mode 100644 index 0000000000000000000000000000000000000000..50ec9e8ea39029f8c255367bca3b7fe6feeaa3b3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_colorbar.py @@ -0,0 +1,1738 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class ColorBar(_BaseTraceHierarchyType): + _parent_path_str = "streamtube" + _path_str = "streamtube.colorbar" + _valid_props = { + "bgcolor", + "bordercolor", + "borderwidth", + "dtick", + "exponentformat", + "labelalias", + "len", + "lenmode", + "minexponent", + "nticks", + "orientation", + "outlinecolor", + "outlinewidth", + "separatethousands", + "showexponent", + "showticklabels", + "showtickprefix", + "showticksuffix", + "thickness", + "thicknessmode", + "tick0", + "tickangle", + "tickcolor", + "tickfont", + "tickformat", + "tickformatstopdefaults", + "tickformatstops", + "ticklabeloverflow", + "ticklabelposition", + "ticklabelstep", + "ticklen", + "tickmode", + "tickprefix", + "ticks", + "ticksuffix", + "ticktext", + "ticktextsrc", + "tickvals", + "tickvalssrc", + "tickwidth", + "title", + "x", + "xanchor", + "xpad", + "xref", + "y", + "yanchor", + "ypad", + "yref", + } + + @property + def bgcolor(self): + """ + Sets the color of padded area. + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bordercolor(self): + """ + Sets the axis line color. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def borderwidth(self): + """ + Sets the width (in px) or the border enclosing this color bar. + + The 'borderwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["borderwidth"] + + @borderwidth.setter + def borderwidth(self, val): + self["borderwidth"] = val + + @property + def dtick(self): + """ + Sets the step in-between ticks on this axis. Use with `tick0`. + Must be a positive number, or special strings available to + "log" and "date" axes. If the axis `type` is "log", then ticks + are set every 10^(n*dtick) where n is the tick number. For + example, to set a tick mark at 1, 10, 100, 1000, ... set dtick + to 1. To set tick marks at 1, 100, 10000, ... set dtick to 2. + To set tick marks at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special values; + "L", where `f` is a positive number, gives ticks linearly + spaced in value (but not position). For example `tick0` = 0.1, + `dtick` = "L0.5" will put ticks at 0.1, 0.6, 1.1, 1.6 etc. To + show powers of 10 plus small digits between, use "D1" (all + digits) or "D2" (only 2 and 5). `tick0` is ignored for "D1" and + "D2". If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval between + ticks to one day, set `dtick` to 86400000.0. "date" also has + special values "M" gives ticks spaced by a number of months. + `n` must be a positive integer. To set ticks on the 15th of + every third month, set `tick0` to "2000-01-15" and `dtick` to + "M3". To set ticks every 4 years, set `dtick` to "M48" + + The 'dtick' property accepts values of any type + + Returns + ------- + Any + """ + return self["dtick"] + + @dtick.setter + def dtick(self, val): + self["dtick"] = val + + @property + def exponentformat(self): + """ + Determines a formatting rule for the tick exponents. For + example, consider the number 1,000,000,000. If "none", it + appears as 1,000,000,000. If "e", 1e+9. If "E", 1E+9. If + "power", 1x10^9 (with 9 in a super script). If "SI", 1G. If + "B", 1B. "SI" uses prefixes from "femto" f (10^-15) to "tera" T + (10^12). *SI extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or *SI + extended* is used and the exponent is beyond the above ranges, + the formatting rule will automatically be switched to the power + notation. + + The 'exponentformat' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['none', 'e', 'E', 'power', 'SI', 'B', 'SI extended'] + + Returns + ------- + Any + """ + return self["exponentformat"] + + @exponentformat.setter + def exponentformat(self, val): + self["exponentformat"] = val + + @property + def labelalias(self): + """ + Replacement text for specific tick or hover labels. For example + using {US: 'USA', CA: 'Canada'} changes US to USA and CA to + Canada. The labels we would have shown must match the keys + exactly, after adding any tickprefix or ticksuffix. For + negative numbers the minus sign symbol used (U+2212) is wider + than the regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis type, and + both keys (if needed) and values (if desired) can include html- + like tags or MathJax. + + The 'labelalias' property accepts values of any type + + Returns + ------- + Any + """ + return self["labelalias"] + + @labelalias.setter + def labelalias(self, val): + self["labelalias"] = val + + @property + def len(self): + """ + Sets the length of the color bar This measure excludes the + padding of both ends. That is, the color bar length is this + length minus the padding on both ends. + + The 'len' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["len"] + + @len.setter + def len(self, val): + self["len"] = val + + @property + def lenmode(self): + """ + Determines whether this color bar's length (i.e. the measure in + the color variation direction) is set in units of plot + "fraction" or in *pixels. Use `len` to set the value. + + The 'lenmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fraction', 'pixels'] + + Returns + ------- + Any + """ + return self["lenmode"] + + @lenmode.setter + def lenmode(self, val): + self["lenmode"] = val + + @property + def minexponent(self): + """ + Hide SI prefix for 10^n if |n| is below this number. This only + has an effect when `tickformat` is "SI" or "B". + + The 'minexponent' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["minexponent"] + + @minexponent.setter + def minexponent(self, val): + self["minexponent"] = val + + @property + def nticks(self): + """ + Specifies the maximum number of ticks for the particular axis. + The actual number of ticks will be chosen automatically to be + less than or equal to `nticks`. Has an effect only if + `tickmode` is set to "auto". + + The 'nticks' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [0, 9223372036854775807] + + Returns + ------- + int + """ + return self["nticks"] + + @nticks.setter + def nticks(self, val): + self["nticks"] = val + + @property + def orientation(self): + """ + Sets the orientation of the colorbar. + + The 'orientation' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['h', 'v'] + + Returns + ------- + Any + """ + return self["orientation"] + + @orientation.setter + def orientation(self, val): + self["orientation"] = val + + @property + def outlinecolor(self): + """ + Sets the axis line color. + + The 'outlinecolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["outlinecolor"] + + @outlinecolor.setter + def outlinecolor(self, val): + self["outlinecolor"] = val + + @property + def outlinewidth(self): + """ + Sets the width (in px) of the axis line. + + The 'outlinewidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["outlinewidth"] + + @outlinewidth.setter + def outlinewidth(self, val): + self["outlinewidth"] = val + + @property + def separatethousands(self): + """ + If "true", even 4-digit integers are separated + + The 'separatethousands' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["separatethousands"] + + @separatethousands.setter + def separatethousands(self, val): + self["separatethousands"] = val + + @property + def showexponent(self): + """ + If "all", all exponents are shown besides their significands. + If "first", only the exponent of the first tick is shown. If + "last", only the exponent of the last tick is shown. If "none", + no exponents appear. + + The 'showexponent' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showexponent"] + + @showexponent.setter + def showexponent(self, val): + self["showexponent"] = val + + @property + def showticklabels(self): + """ + Determines whether or not the tick labels are drawn. + + The 'showticklabels' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showticklabels"] + + @showticklabels.setter + def showticklabels(self, val): + self["showticklabels"] = val + + @property + def showtickprefix(self): + """ + If "all", all tick labels are displayed with a prefix. If + "first", only the first tick is displayed with a prefix. If + "last", only the last tick is displayed with a suffix. If + "none", tick prefixes are hidden. + + The 'showtickprefix' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showtickprefix"] + + @showtickprefix.setter + def showtickprefix(self, val): + self["showtickprefix"] = val + + @property + def showticksuffix(self): + """ + Same as `showtickprefix` but for tick suffixes. + + The 'showticksuffix' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['all', 'first', 'last', 'none'] + + Returns + ------- + Any + """ + return self["showticksuffix"] + + @showticksuffix.setter + def showticksuffix(self, val): + self["showticksuffix"] = val + + @property + def thickness(self): + """ + Sets the thickness of the color bar This measure excludes the + size of the padding, ticks and labels. + + The 'thickness' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["thickness"] + + @thickness.setter + def thickness(self, val): + self["thickness"] = val + + @property + def thicknessmode(self): + """ + Determines whether this color bar's thickness (i.e. the measure + in the constant color direction) is set in units of plot + "fraction" or in "pixels". Use `thickness` to set the value. + + The 'thicknessmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['fraction', 'pixels'] + + Returns + ------- + Any + """ + return self["thicknessmode"] + + @thicknessmode.setter + def thicknessmode(self, val): + self["thicknessmode"] = val + + @property + def tick0(self): + """ + Sets the placement of the first tick on this axis. Use with + `dtick`. If the axis `type` is "log", then you must take the + log of your starting tick (e.g. to set the starting tick to + 100, set the `tick0` to 2) except when `dtick`=*L* (see + `dtick` for more info). If the axis `type` is "date", it should + be a date string, like date data. If the axis `type` is + "category", it should be a number, using the scale where each + category is assigned a serial number from zero in the order it + appears. + + The 'tick0' property accepts values of any type + + Returns + ------- + Any + """ + return self["tick0"] + + @tick0.setter + def tick0(self, val): + self["tick0"] = val + + @property + def tickangle(self): + """ + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the tick + labels vertically. + + The 'tickangle' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["tickangle"] + + @tickangle.setter + def tickangle(self, val): + self["tickangle"] = val + + @property + def tickcolor(self): + """ + Sets the tick color. + + The 'tickcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["tickcolor"] + + @tickcolor.setter + def tickcolor(self, val): + self["tickcolor"] = val + + @property + def tickfont(self): + """ + Sets the color bar's tick label font + + The 'tickfont' property is an instance of Tickfont + that may be specified as: + - An instance of :class:`plotly.graph_objs.streamtube.colorbar.Tickfont` + - A dict of string/value properties that will be passed + to the Tickfont constructor + + Returns + ------- + plotly.graph_objs.streamtube.colorbar.Tickfont + """ + return self["tickfont"] + + @tickfont.setter + def tickfont(self, val): + self["tickfont"] = val + + @property + def tickformat(self): + """ + Sets the tick label formatting rule using d3 formatting mini- + languages which are very similar to those in Python. For + numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. And for + dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to d3's date + formatter: "%h" for half of the year as a decimal number as + well as "%{n}f" for fractional seconds with n digits. For + example, *2016-10-13 09:15:23.456* with tickformat + "%H~%M~%S.%2f" would display "09~15~23.46" + + The 'tickformat' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["tickformat"] + + @tickformat.setter + def tickformat(self, val): + self["tickformat"] = val + + @property + def tickformatstops(self): + """ + The 'tickformatstops' property is a tuple of instances of + Tickformatstop that may be specified as: + - A list or tuple of instances of plotly.graph_objs.streamtube.colorbar.Tickformatstop + - A list or tuple of dicts of string/value properties that + will be passed to the Tickformatstop constructor + + Returns + ------- + tuple[plotly.graph_objs.streamtube.colorbar.Tickformatstop] + """ + return self["tickformatstops"] + + @tickformatstops.setter + def tickformatstops(self, val): + self["tickformatstops"] = val + + @property + def tickformatstopdefaults(self): + """ + When used in a template (as layout.template.data.streamtube.col + orbar.tickformatstopdefaults), sets the default property values + to use for elements of streamtube.colorbar.tickformatstops + + The 'tickformatstopdefaults' property is an instance of Tickformatstop + that may be specified as: + - An instance of :class:`plotly.graph_objs.streamtube.colorbar.Tickformatstop` + - A dict of string/value properties that will be passed + to the Tickformatstop constructor + + Returns + ------- + plotly.graph_objs.streamtube.colorbar.Tickformatstop + """ + return self["tickformatstopdefaults"] + + @tickformatstopdefaults.setter + def tickformatstopdefaults(self, val): + self["tickformatstopdefaults"] = val + + @property + def ticklabeloverflow(self): + """ + Determines how we handle tick labels that would overflow either + the graph div or the domain of the axis. The default value for + inside tick labels is *hide past domain*. In other cases the + default is *hide past div*. + + The 'ticklabeloverflow' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['allow', 'hide past div', 'hide past domain'] + + Returns + ------- + Any + """ + return self["ticklabeloverflow"] + + @ticklabeloverflow.setter + def ticklabeloverflow(self, val): + self["ticklabeloverflow"] = val + + @property + def ticklabelposition(self): + """ + Determines where tick labels are drawn relative to the ticks. + Left and right options are used when `orientation` is "h", top + and bottom when `orientation` is "v". + + The 'ticklabelposition' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['outside', 'inside', 'outside top', 'inside top', + 'outside left', 'inside left', 'outside right', 'inside + right', 'outside bottom', 'inside bottom'] + + Returns + ------- + Any + """ + return self["ticklabelposition"] + + @ticklabelposition.setter + def ticklabelposition(self, val): + self["ticklabelposition"] = val + + @property + def ticklabelstep(self): + """ + Sets the spacing between tick labels as compared to the spacing + between ticks. A value of 1 (default) means each tick gets a + label. A value of 2 means shows every 2nd label. A larger value + n means only every nth tick is labeled. `tick0` determines + which labels are shown. Not implemented for axes with `type` + "log" or "multicategory", or when `tickmode` is "array". + + The 'ticklabelstep' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 9223372036854775807] + + Returns + ------- + int + """ + return self["ticklabelstep"] + + @ticklabelstep.setter + def ticklabelstep(self, val): + self["ticklabelstep"] = val + + @property + def ticklen(self): + """ + Sets the tick length (in px). + + The 'ticklen' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["ticklen"] + + @ticklen.setter + def ticklen(self, val): + self["ticklen"] = val + + @property + def tickmode(self): + """ + Sets the tick mode for this axis. If "auto", the number of + ticks is set via `nticks`. If "linear", the placement of the + ticks is determined by a starting position `tick0` and a tick + step `dtick` ("linear" is the default value if `tick0` and + `dtick` are provided). If "array", the placement of the ticks + is set via `tickvals` and the tick text is `ticktext`. ("array" + is the default value if `tickvals` is provided). + + The 'tickmode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['auto', 'linear', 'array'] + + Returns + ------- + Any + """ + return self["tickmode"] + + @tickmode.setter + def tickmode(self, val): + self["tickmode"] = val + + @property + def tickprefix(self): + """ + Sets a tick label prefix. + + The 'tickprefix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["tickprefix"] + + @tickprefix.setter + def tickprefix(self, val): + self["tickprefix"] = val + + @property + def ticks(self): + """ + Determines whether ticks are drawn or not. If "", this axis' + ticks are not drawn. If "outside" ("inside"), this axis' are + drawn outside (inside) the axis lines. + + The 'ticks' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['outside', 'inside', ''] + + Returns + ------- + Any + """ + return self["ticks"] + + @ticks.setter + def ticks(self, val): + self["ticks"] = val + + @property + def ticksuffix(self): + """ + Sets a tick label suffix. + + The 'ticksuffix' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["ticksuffix"] + + @ticksuffix.setter + def ticksuffix(self, val): + self["ticksuffix"] = val + + @property + def ticktext(self): + """ + Sets the text displayed at the ticks position via `tickvals`. + Only has an effect if `tickmode` is set to "array". Used with + `tickvals`. + + The 'ticktext' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["ticktext"] + + @ticktext.setter + def ticktext(self, val): + self["ticktext"] = val + + @property + def ticktextsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `ticktext`. + + The 'ticktextsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ticktextsrc"] + + @ticktextsrc.setter + def ticktextsrc(self, val): + self["ticktextsrc"] = val + + @property + def tickvals(self): + """ + Sets the values at which ticks on this axis appear. Only has an + effect if `tickmode` is set to "array". Used with `ticktext`. + + The 'tickvals' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["tickvals"] + + @tickvals.setter + def tickvals(self, val): + self["tickvals"] = val + + @property + def tickvalssrc(self): + """ + Sets the source reference on Chart Studio Cloud for `tickvals`. + + The 'tickvalssrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["tickvalssrc"] + + @tickvalssrc.setter + def tickvalssrc(self, val): + self["tickvalssrc"] = val + + @property + def tickwidth(self): + """ + Sets the tick width (in px). + + The 'tickwidth' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["tickwidth"] + + @tickwidth.setter + def tickwidth(self, val): + self["tickwidth"] = val + + @property + def title(self): + """ + The 'title' property is an instance of Title + that may be specified as: + - An instance of :class:`plotly.graph_objs.streamtube.colorbar.Title` + - A dict of string/value properties that will be passed + to the Title constructor + + Returns + ------- + plotly.graph_objs.streamtube.colorbar.Title + """ + return self["title"] + + @title.setter + def title(self, val): + self["title"] = val + + @property + def x(self): + """ + Sets the x position with respect to `xref` of the color bar (in + plot fraction). When `xref` is "paper", defaults to 1.02 when + `orientation` is "v" and 0.5 when `orientation` is "h". When + `xref` is "container", defaults to 1 when `orientation` is "v" + and 0.5 when `orientation` is "h". Must be between 0 and 1 if + `xref` is "container" and between "-2" and 3 if `xref` is + "paper". + + The 'x' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xanchor(self): + """ + Sets this color bar's horizontal position anchor. This anchor + binds the `x` position to the "left", "center" or "right" of + the color bar. Defaults to "left" when `orientation` is "v" and + "center" when `orientation` is "h". + + The 'xanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'center', 'right'] + + Returns + ------- + Any + """ + return self["xanchor"] + + @xanchor.setter + def xanchor(self, val): + self["xanchor"] = val + + @property + def xpad(self): + """ + Sets the amount of padding (in px) along the x direction. + + The 'xpad' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["xpad"] + + @xpad.setter + def xpad(self, val): + self["xpad"] = val + + @property + def xref(self): + """ + Sets the container `x` refers to. "container" spans the entire + `width` of the plot. "paper" refers to the width of the + plotting area only. + + The 'xref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['container', 'paper'] + + Returns + ------- + Any + """ + return self["xref"] + + @xref.setter + def xref(self, val): + self["xref"] = val + + @property + def y(self): + """ + Sets the y position with respect to `yref` of the color bar (in + plot fraction). When `yref` is "paper", defaults to 0.5 when + `orientation` is "v" and 1.02 when `orientation` is "h". When + `yref` is "container", defaults to 0.5 when `orientation` is + "v" and 1 when `orientation` is "h". Must be between 0 and 1 if + `yref` is "container" and between "-2" and 3 if `yref` is + "paper". + + The 'y' property is a number and may be specified as: + - An int or float + + Returns + ------- + int|float + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def yanchor(self): + """ + Sets this color bar's vertical position anchor This anchor + binds the `y` position to the "top", "middle" or "bottom" of + the color bar. Defaults to "middle" when `orientation` is "v" + and "bottom" when `orientation` is "h". + + The 'yanchor' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['top', 'middle', 'bottom'] + + Returns + ------- + Any + """ + return self["yanchor"] + + @yanchor.setter + def yanchor(self, val): + self["yanchor"] = val + + @property + def ypad(self): + """ + Sets the amount of padding (in px) along the y direction. + + The 'ypad' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["ypad"] + + @ypad.setter + def ypad(self, val): + self["ypad"] = val + + @property + def yref(self): + """ + Sets the container `y` refers to. "container" spans the entire + `height` of the plot. "paper" refers to the height of the + plotting area only. + + The 'yref' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['container', 'paper'] + + Returns + ------- + Any + """ + return self["yref"] + + @yref.setter + def yref(self, val): + self["yref"] = val + + @property + def _prop_descriptions(self): + return """\ + bgcolor + Sets the color of padded area. + bordercolor + Sets the axis line color. + borderwidth + Sets the width (in px) or the border enclosing this + color bar. + dtick + Sets the step in-between ticks on this axis. Use with + `tick0`. Must be a positive number, or special strings + available to "log" and "date" axes. If the axis `type` + is "log", then ticks are set every 10^(n*dtick) where n + is the tick number. For example, to set a tick mark at + 1, 10, 100, 1000, ... set dtick to 1. To set tick marks + at 1, 100, 10000, ... set dtick to 2. To set tick marks + at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special + values; "L", where `f` is a positive number, gives + ticks linearly spaced in value (but not position). For + example `tick0` = 0.1, `dtick` = "L0.5" will put ticks + at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus + small digits between, use "D1" (all digits) or "D2" + (only 2 and 5). `tick0` is ignored for "D1" and "D2". + If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval + between ticks to one day, set `dtick` to 86400000.0. + "date" also has special values "M" gives ticks + spaced by a number of months. `n` must be a positive + integer. To set ticks on the 15th of every third month, + set `tick0` to "2000-01-15" and `dtick` to "M3". To set + ticks every 4 years, set `dtick` to "M48" + exponentformat + Determines a formatting rule for the tick exponents. + For example, consider the number 1,000,000,000. If + "none", it appears as 1,000,000,000. If "e", 1e+9. If + "E", 1E+9. If "power", 1x10^9 (with 9 in a super + script). If "SI", 1G. If "B", 1B. "SI" uses prefixes + from "femto" f (10^-15) to "tera" T (10^12). *SI + extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or + *SI extended* is used and the exponent is beyond the + above ranges, the formatting rule will automatically be + switched to the power notation. + labelalias + Replacement text for specific tick or hover labels. For + example using {US: 'USA', CA: 'Canada'} changes US to + USA and CA to Canada. The labels we would have shown + must match the keys exactly, after adding any + tickprefix or ticksuffix. For negative numbers the + minus sign symbol used (U+2212) is wider than the + regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis + type, and both keys (if needed) and values (if desired) + can include html-like tags or MathJax. + len + Sets the length of the color bar This measure excludes + the padding of both ends. That is, the color bar length + is this length minus the padding on both ends. + lenmode + Determines whether this color bar's length (i.e. the + measure in the color variation direction) is set in + units of plot "fraction" or in *pixels. Use `len` to + set the value. + minexponent + Hide SI prefix for 10^n if |n| is below this number. + This only has an effect when `tickformat` is "SI" or + "B". + nticks + Specifies the maximum number of ticks for the + particular axis. The actual number of ticks will be + chosen automatically to be less than or equal to + `nticks`. Has an effect only if `tickmode` is set to + "auto". + orientation + Sets the orientation of the colorbar. + outlinecolor + Sets the axis line color. + outlinewidth + Sets the width (in px) of the axis line. + separatethousands + If "true", even 4-digit integers are separated + showexponent + If "all", all exponents are shown besides their + significands. If "first", only the exponent of the + first tick is shown. If "last", only the exponent of + the last tick is shown. If "none", no exponents appear. + showticklabels + Determines whether or not the tick labels are drawn. + showtickprefix + If "all", all tick labels are displayed with a prefix. + If "first", only the first tick is displayed with a + prefix. If "last", only the last tick is displayed with + a suffix. If "none", tick prefixes are hidden. + showticksuffix + Same as `showtickprefix` but for tick suffixes. + thickness + Sets the thickness of the color bar This measure + excludes the size of the padding, ticks and labels. + thicknessmode + Determines whether this color bar's thickness (i.e. the + measure in the constant color direction) is set in + units of plot "fraction" or in "pixels". Use + `thickness` to set the value. + tick0 + Sets the placement of the first tick on this axis. Use + with `dtick`. If the axis `type` is "log", then you + must take the log of your starting tick (e.g. to set + the starting tick to 100, set the `tick0` to 2) except + when `dtick`=*L* (see `dtick` for more info). If the + axis `type` is "date", it should be a date string, like + date data. If the axis `type` is "category", it should + be a number, using the scale where each category is + assigned a serial number from zero in the order it + appears. + tickangle + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + tick labels vertically. + tickcolor + Sets the tick color. + tickfont + Sets the color bar's tick label font + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + tickformatstops + A tuple of :class:`plotly.graph_objects.streamtube.colo + rbar.Tickformatstop` instances or dicts with compatible + properties + tickformatstopdefaults + When used in a template (as layout.template.data.stream + tube.colorbar.tickformatstopdefaults), sets the default + property values to use for elements of + streamtube.colorbar.tickformatstops + ticklabeloverflow + Determines how we handle tick labels that would + overflow either the graph div or the domain of the + axis. The default value for inside tick labels is *hide + past domain*. In other cases the default is *hide past + div*. + ticklabelposition + Determines where tick labels are drawn relative to the + ticks. Left and right options are used when + `orientation` is "h", top and bottom when `orientation` + is "v". + ticklabelstep + Sets the spacing between tick labels as compared to the + spacing between ticks. A value of 1 (default) means + each tick gets a label. A value of 2 means shows every + 2nd label. A larger value n means only every nth tick + is labeled. `tick0` determines which labels are shown. + Not implemented for axes with `type` "log" or + "multicategory", or when `tickmode` is "array". + ticklen + Sets the tick length (in px). + tickmode + Sets the tick mode for this axis. If "auto", the number + of ticks is set via `nticks`. If "linear", the + placement of the ticks is determined by a starting + position `tick0` and a tick step `dtick` ("linear" is + the default value if `tick0` and `dtick` are provided). + If "array", the placement of the ticks is set via + `tickvals` and the tick text is `ticktext`. ("array" is + the default value if `tickvals` is provided). + tickprefix + Sets a tick label prefix. + ticks + Determines whether ticks are drawn or not. If "", this + axis' ticks are not drawn. If "outside" ("inside"), + this axis' are drawn outside (inside) the axis lines. + ticksuffix + Sets a tick label suffix. + ticktext + Sets the text displayed at the ticks position via + `tickvals`. Only has an effect if `tickmode` is set to + "array". Used with `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + Only has an effect if `tickmode` is set to "array". + Used with `ticktext`. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + tickwidth + Sets the tick width (in px). + title + :class:`plotly.graph_objects.streamtube.colorbar.Title` + instance or dict with compatible properties + x + Sets the x position with respect to `xref` of the color + bar (in plot fraction). When `xref` is "paper", + defaults to 1.02 when `orientation` is "v" and 0.5 when + `orientation` is "h". When `xref` is "container", + defaults to 1 when `orientation` is "v" and 0.5 when + `orientation` is "h". Must be between 0 and 1 if `xref` + is "container" and between "-2" and 3 if `xref` is + "paper". + xanchor + Sets this color bar's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the color bar. Defaults to "left" when + `orientation` is "v" and "center" when `orientation` is + "h". + xpad + Sets the amount of padding (in px) along the x + direction. + xref + Sets the container `x` refers to. "container" spans the + entire `width` of the plot. "paper" refers to the width + of the plotting area only. + y + Sets the y position with respect to `yref` of the color + bar (in plot fraction). When `yref` is "paper", + defaults to 0.5 when `orientation` is "v" and 1.02 when + `orientation` is "h". When `yref` is "container", + defaults to 0.5 when `orientation` is "v" and 1 when + `orientation` is "h". Must be between 0 and 1 if `yref` + is "container" and between "-2" and 3 if `yref` is + "paper". + yanchor + Sets this color bar's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the color bar. Defaults to "middle" when + `orientation` is "v" and "bottom" when `orientation` is + "h". + ypad + Sets the amount of padding (in px) along the y + direction. + yref + Sets the container `y` refers to. "container" spans the + entire `height` of the plot. "paper" refers to the + height of the plotting area only. + """ + + def __init__( + self, + arg=None, + bgcolor=None, + bordercolor=None, + borderwidth=None, + dtick=None, + exponentformat=None, + labelalias=None, + len=None, + lenmode=None, + minexponent=None, + nticks=None, + orientation=None, + outlinecolor=None, + outlinewidth=None, + separatethousands=None, + showexponent=None, + showticklabels=None, + showtickprefix=None, + showticksuffix=None, + thickness=None, + thicknessmode=None, + tick0=None, + tickangle=None, + tickcolor=None, + tickfont=None, + tickformat=None, + tickformatstops=None, + tickformatstopdefaults=None, + ticklabeloverflow=None, + ticklabelposition=None, + ticklabelstep=None, + ticklen=None, + tickmode=None, + tickprefix=None, + ticks=None, + ticksuffix=None, + ticktext=None, + ticktextsrc=None, + tickvals=None, + tickvalssrc=None, + tickwidth=None, + title=None, + x=None, + xanchor=None, + xpad=None, + xref=None, + y=None, + yanchor=None, + ypad=None, + yref=None, + **kwargs, + ): + """ + Construct a new ColorBar object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.streamtube.ColorBar` + bgcolor + Sets the color of padded area. + bordercolor + Sets the axis line color. + borderwidth + Sets the width (in px) or the border enclosing this + color bar. + dtick + Sets the step in-between ticks on this axis. Use with + `tick0`. Must be a positive number, or special strings + available to "log" and "date" axes. If the axis `type` + is "log", then ticks are set every 10^(n*dtick) where n + is the tick number. For example, to set a tick mark at + 1, 10, 100, 1000, ... set dtick to 1. To set tick marks + at 1, 100, 10000, ... set dtick to 2. To set tick marks + at 1, 5, 25, 125, 625, 3125, ... set dtick to + log_10(5), or 0.69897000433. "log" has several special + values; "L", where `f` is a positive number, gives + ticks linearly spaced in value (but not position). For + example `tick0` = 0.1, `dtick` = "L0.5" will put ticks + at 0.1, 0.6, 1.1, 1.6 etc. To show powers of 10 plus + small digits between, use "D1" (all digits) or "D2" + (only 2 and 5). `tick0` is ignored for "D1" and "D2". + If the axis `type` is "date", then you must convert the + time to milliseconds. For example, to set the interval + between ticks to one day, set `dtick` to 86400000.0. + "date" also has special values "M" gives ticks + spaced by a number of months. `n` must be a positive + integer. To set ticks on the 15th of every third month, + set `tick0` to "2000-01-15" and `dtick` to "M3". To set + ticks every 4 years, set `dtick` to "M48" + exponentformat + Determines a formatting rule for the tick exponents. + For example, consider the number 1,000,000,000. If + "none", it appears as 1,000,000,000. If "e", 1e+9. If + "E", 1E+9. If "power", 1x10^9 (with 9 in a super + script). If "SI", 1G. If "B", 1B. "SI" uses prefixes + from "femto" f (10^-15) to "tera" T (10^12). *SI + extended* covers instead the full SI range from + "quecto" q (10^-30) to "quetta" Q (10^30). If "SI" or + *SI extended* is used and the exponent is beyond the + above ranges, the formatting rule will automatically be + switched to the power notation. + labelalias + Replacement text for specific tick or hover labels. For + example using {US: 'USA', CA: 'Canada'} changes US to + USA and CA to Canada. The labels we would have shown + must match the keys exactly, after adding any + tickprefix or ticksuffix. For negative numbers the + minus sign symbol used (U+2212) is wider than the + regular ascii dash. That means you need to use −1 + instead of -1. labelalias can be used with any axis + type, and both keys (if needed) and values (if desired) + can include html-like tags or MathJax. + len + Sets the length of the color bar This measure excludes + the padding of both ends. That is, the color bar length + is this length minus the padding on both ends. + lenmode + Determines whether this color bar's length (i.e. the + measure in the color variation direction) is set in + units of plot "fraction" or in *pixels. Use `len` to + set the value. + minexponent + Hide SI prefix for 10^n if |n| is below this number. + This only has an effect when `tickformat` is "SI" or + "B". + nticks + Specifies the maximum number of ticks for the + particular axis. The actual number of ticks will be + chosen automatically to be less than or equal to + `nticks`. Has an effect only if `tickmode` is set to + "auto". + orientation + Sets the orientation of the colorbar. + outlinecolor + Sets the axis line color. + outlinewidth + Sets the width (in px) of the axis line. + separatethousands + If "true", even 4-digit integers are separated + showexponent + If "all", all exponents are shown besides their + significands. If "first", only the exponent of the + first tick is shown. If "last", only the exponent of + the last tick is shown. If "none", no exponents appear. + showticklabels + Determines whether or not the tick labels are drawn. + showtickprefix + If "all", all tick labels are displayed with a prefix. + If "first", only the first tick is displayed with a + prefix. If "last", only the last tick is displayed with + a suffix. If "none", tick prefixes are hidden. + showticksuffix + Same as `showtickprefix` but for tick suffixes. + thickness + Sets the thickness of the color bar This measure + excludes the size of the padding, ticks and labels. + thicknessmode + Determines whether this color bar's thickness (i.e. the + measure in the constant color direction) is set in + units of plot "fraction" or in "pixels". Use + `thickness` to set the value. + tick0 + Sets the placement of the first tick on this axis. Use + with `dtick`. If the axis `type` is "log", then you + must take the log of your starting tick (e.g. to set + the starting tick to 100, set the `tick0` to 2) except + when `dtick`=*L* (see `dtick` for more info). If the + axis `type` is "date", it should be a date string, like + date data. If the axis `type` is "category", it should + be a number, using the scale where each category is + assigned a serial number from zero in the order it + appears. + tickangle + Sets the angle of the tick labels with respect to the + horizontal. For example, a `tickangle` of -90 draws the + tick labels vertically. + tickcolor + Sets the tick color. + tickfont + Sets the color bar's tick label font + tickformat + Sets the tick label formatting rule using d3 formatting + mini-languages which are very similar to those in + Python. For numbers, see: + https://github.com/d3/d3-format/tree/v1.4.5#d3-format. + And for dates see: https://github.com/d3/d3-time- + format/tree/v2.2.3#locale_format. We add two items to + d3's date formatter: "%h" for half of the year as a + decimal number as well as "%{n}f" for fractional + seconds with n digits. For example, *2016-10-13 + 09:15:23.456* with tickformat "%H~%M~%S.%2f" would + display "09~15~23.46" + tickformatstops + A tuple of :class:`plotly.graph_objects.streamtube.colo + rbar.Tickformatstop` instances or dicts with compatible + properties + tickformatstopdefaults + When used in a template (as layout.template.data.stream + tube.colorbar.tickformatstopdefaults), sets the default + property values to use for elements of + streamtube.colorbar.tickformatstops + ticklabeloverflow + Determines how we handle tick labels that would + overflow either the graph div or the domain of the + axis. The default value for inside tick labels is *hide + past domain*. In other cases the default is *hide past + div*. + ticklabelposition + Determines where tick labels are drawn relative to the + ticks. Left and right options are used when + `orientation` is "h", top and bottom when `orientation` + is "v". + ticklabelstep + Sets the spacing between tick labels as compared to the + spacing between ticks. A value of 1 (default) means + each tick gets a label. A value of 2 means shows every + 2nd label. A larger value n means only every nth tick + is labeled. `tick0` determines which labels are shown. + Not implemented for axes with `type` "log" or + "multicategory", or when `tickmode` is "array". + ticklen + Sets the tick length (in px). + tickmode + Sets the tick mode for this axis. If "auto", the number + of ticks is set via `nticks`. If "linear", the + placement of the ticks is determined by a starting + position `tick0` and a tick step `dtick` ("linear" is + the default value if `tick0` and `dtick` are provided). + If "array", the placement of the ticks is set via + `tickvals` and the tick text is `ticktext`. ("array" is + the default value if `tickvals` is provided). + tickprefix + Sets a tick label prefix. + ticks + Determines whether ticks are drawn or not. If "", this + axis' ticks are not drawn. If "outside" ("inside"), + this axis' are drawn outside (inside) the axis lines. + ticksuffix + Sets a tick label suffix. + ticktext + Sets the text displayed at the ticks position via + `tickvals`. Only has an effect if `tickmode` is set to + "array". Used with `tickvals`. + ticktextsrc + Sets the source reference on Chart Studio Cloud for + `ticktext`. + tickvals + Sets the values at which ticks on this axis appear. + Only has an effect if `tickmode` is set to "array". + Used with `ticktext`. + tickvalssrc + Sets the source reference on Chart Studio Cloud for + `tickvals`. + tickwidth + Sets the tick width (in px). + title + :class:`plotly.graph_objects.streamtube.colorbar.Title` + instance or dict with compatible properties + x + Sets the x position with respect to `xref` of the color + bar (in plot fraction). When `xref` is "paper", + defaults to 1.02 when `orientation` is "v" and 0.5 when + `orientation` is "h". When `xref` is "container", + defaults to 1 when `orientation` is "v" and 0.5 when + `orientation` is "h". Must be between 0 and 1 if `xref` + is "container" and between "-2" and 3 if `xref` is + "paper". + xanchor + Sets this color bar's horizontal position anchor. This + anchor binds the `x` position to the "left", "center" + or "right" of the color bar. Defaults to "left" when + `orientation` is "v" and "center" when `orientation` is + "h". + xpad + Sets the amount of padding (in px) along the x + direction. + xref + Sets the container `x` refers to. "container" spans the + entire `width` of the plot. "paper" refers to the width + of the plotting area only. + y + Sets the y position with respect to `yref` of the color + bar (in plot fraction). When `yref` is "paper", + defaults to 0.5 when `orientation` is "v" and 1.02 when + `orientation` is "h". When `yref` is "container", + defaults to 0.5 when `orientation` is "v" and 1 when + `orientation` is "h". Must be between 0 and 1 if `yref` + is "container" and between "-2" and 3 if `yref` is + "paper". + yanchor + Sets this color bar's vertical position anchor This + anchor binds the `y` position to the "top", "middle" or + "bottom" of the color bar. Defaults to "middle" when + `orientation` is "v" and "bottom" when `orientation` is + "h". + ypad + Sets the amount of padding (in px) along the y + direction. + yref + Sets the container `y` refers to. "container" spans the + entire `height` of the plot. "paper" refers to the + height of the plotting area only. + + Returns + ------- + ColorBar + """ + super().__init__("colorbar") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.streamtube.ColorBar +constructor must be a dict or +an instance of :class:`plotly.graph_objs.streamtube.ColorBar`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("borderwidth", arg, borderwidth) + self._set_property("dtick", arg, dtick) + self._set_property("exponentformat", arg, exponentformat) + self._set_property("labelalias", arg, labelalias) + self._set_property("len", arg, len) + self._set_property("lenmode", arg, lenmode) + self._set_property("minexponent", arg, minexponent) + self._set_property("nticks", arg, nticks) + self._set_property("orientation", arg, orientation) + self._set_property("outlinecolor", arg, outlinecolor) + self._set_property("outlinewidth", arg, outlinewidth) + self._set_property("separatethousands", arg, separatethousands) + self._set_property("showexponent", arg, showexponent) + self._set_property("showticklabels", arg, showticklabels) + self._set_property("showtickprefix", arg, showtickprefix) + self._set_property("showticksuffix", arg, showticksuffix) + self._set_property("thickness", arg, thickness) + self._set_property("thicknessmode", arg, thicknessmode) + self._set_property("tick0", arg, tick0) + self._set_property("tickangle", arg, tickangle) + self._set_property("tickcolor", arg, tickcolor) + self._set_property("tickfont", arg, tickfont) + self._set_property("tickformat", arg, tickformat) + self._set_property("tickformatstops", arg, tickformatstops) + self._set_property("tickformatstopdefaults", arg, tickformatstopdefaults) + self._set_property("ticklabeloverflow", arg, ticklabeloverflow) + self._set_property("ticklabelposition", arg, ticklabelposition) + self._set_property("ticklabelstep", arg, ticklabelstep) + self._set_property("ticklen", arg, ticklen) + self._set_property("tickmode", arg, tickmode) + self._set_property("tickprefix", arg, tickprefix) + self._set_property("ticks", arg, ticks) + self._set_property("ticksuffix", arg, ticksuffix) + self._set_property("ticktext", arg, ticktext) + self._set_property("ticktextsrc", arg, ticktextsrc) + self._set_property("tickvals", arg, tickvals) + self._set_property("tickvalssrc", arg, tickvalssrc) + self._set_property("tickwidth", arg, tickwidth) + self._set_property("title", arg, title) + self._set_property("x", arg, x) + self._set_property("xanchor", arg, xanchor) + self._set_property("xpad", arg, xpad) + self._set_property("xref", arg, xref) + self._set_property("y", arg, y) + self._set_property("yanchor", arg, yanchor) + self._set_property("ypad", arg, ypad) + self._set_property("yref", arg, yref) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_hoverlabel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_hoverlabel.py new file mode 100644 index 0000000000000000000000000000000000000000..cadef33fa6c4381b8a4b751484680ab484314c2d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_hoverlabel.py @@ -0,0 +1,366 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Hoverlabel(_BaseTraceHierarchyType): + _parent_path_str = "streamtube" + _path_str = "streamtube.hoverlabel" + _valid_props = { + "align", + "alignsrc", + "bgcolor", + "bgcolorsrc", + "bordercolor", + "bordercolorsrc", + "font", + "namelength", + "namelengthsrc", + "showarrow", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the text content within hover + label box. Has an effect only if the hover label text spans + more two or more lines + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'auto'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def alignsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `align`. + + The 'alignsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["alignsrc"] + + @alignsrc.setter + def alignsrc(self, val): + self["alignsrc"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the hover labels for this trace + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bgcolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `bgcolor`. + + The 'bgcolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bgcolorsrc"] + + @bgcolorsrc.setter + def bgcolorsrc(self, val): + self["bgcolorsrc"] = val + + @property + def bordercolor(self): + """ + Sets the border color of the hover labels for this trace. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def bordercolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + + The 'bordercolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bordercolorsrc"] + + @bordercolorsrc.setter + def bordercolorsrc(self, val): + self["bordercolorsrc"] = val + + @property + def font(self): + """ + Sets the font used in hover labels. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.streamtube.hoverlabel.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.streamtube.hoverlabel.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def namelength(self): + """ + Sets the default length (in number of characters) of the trace + name in the hover labels for all traces. -1 shows the whole + name regardless of length. 0-3 shows the first 0-3 characters, + and an integer >3 will show the whole name if it is less than + that many characters, but if it is longer, will truncate to + `namelength - 3` characters and add an ellipsis. + + The 'namelength' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["namelength"] + + @namelength.setter + def namelength(self, val): + self["namelength"] = val + + @property + def namelengthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `namelength`. + + The 'namelengthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["namelengthsrc"] + + @namelengthsrc.setter + def namelengthsrc(self, val): + self["namelengthsrc"] = val + + @property + def showarrow(self): + """ + Sets whether or not to show the hover label arrow/triangle + pointing to the data point. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + """ + + def __init__( + self, + arg=None, + align=None, + alignsrc=None, + bgcolor=None, + bgcolorsrc=None, + bordercolor=None, + bordercolorsrc=None, + font=None, + namelength=None, + namelengthsrc=None, + showarrow=None, + **kwargs, + ): + """ + Construct a new Hoverlabel object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.streamtube.Hoverlabel` + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + + Returns + ------- + Hoverlabel + """ + super().__init__("hoverlabel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.streamtube.Hoverlabel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.streamtube.Hoverlabel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("alignsrc", arg, alignsrc) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bgcolorsrc", arg, bgcolorsrc) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("bordercolorsrc", arg, bordercolorsrc) + self._set_property("font", arg, font) + self._set_property("namelength", arg, namelength) + self._set_property("namelengthsrc", arg, namelengthsrc) + self._set_property("showarrow", arg, showarrow) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..0cb32975c08788bcd69307dfcdf93ff6266f5a0c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "streamtube" + _path_str = "streamtube.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.streamtube.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.streamtube.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.streamtube.Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.streamtube.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.streamtube.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_lighting.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_lighting.py new file mode 100644 index 0000000000000000000000000000000000000000..0e1dd46c191f8702ab3786a678e42db51706fb84 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_lighting.py @@ -0,0 +1,260 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Lighting(_BaseTraceHierarchyType): + _parent_path_str = "streamtube" + _path_str = "streamtube.lighting" + _valid_props = { + "ambient", + "diffuse", + "facenormalsepsilon", + "fresnel", + "roughness", + "specular", + "vertexnormalsepsilon", + } + + @property + def ambient(self): + """ + Ambient light increases overall color visibility but can wash + out the image. + + The 'ambient' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["ambient"] + + @ambient.setter + def ambient(self, val): + self["ambient"] = val + + @property + def diffuse(self): + """ + Represents the extent that incident rays are reflected in a + range of angles. + + The 'diffuse' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["diffuse"] + + @diffuse.setter + def diffuse(self, val): + self["diffuse"] = val + + @property + def facenormalsepsilon(self): + """ + Epsilon for face normals calculation avoids math issues arising + from degenerate geometry. + + The 'facenormalsepsilon' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["facenormalsepsilon"] + + @facenormalsepsilon.setter + def facenormalsepsilon(self, val): + self["facenormalsepsilon"] = val + + @property + def fresnel(self): + """ + Represents the reflectance as a dependency of the viewing + angle; e.g. paper is reflective when viewing it from the edge + of the paper (almost 90 degrees), causing shine. + + The 'fresnel' property is a number and may be specified as: + - An int or float in the interval [0, 5] + + Returns + ------- + int|float + """ + return self["fresnel"] + + @fresnel.setter + def fresnel(self, val): + self["fresnel"] = val + + @property + def roughness(self): + """ + Alters specular reflection; the rougher the surface, the wider + and less contrasty the shine. + + The 'roughness' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["roughness"] + + @roughness.setter + def roughness(self, val): + self["roughness"] = val + + @property + def specular(self): + """ + Represents the level that incident rays are reflected in a + single direction, causing shine. + + The 'specular' property is a number and may be specified as: + - An int or float in the interval [0, 2] + + Returns + ------- + int|float + """ + return self["specular"] + + @specular.setter + def specular(self, val): + self["specular"] = val + + @property + def vertexnormalsepsilon(self): + """ + Epsilon for vertex normals calculation avoids math issues + arising from degenerate geometry. + + The 'vertexnormalsepsilon' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["vertexnormalsepsilon"] + + @vertexnormalsepsilon.setter + def vertexnormalsepsilon(self, val): + self["vertexnormalsepsilon"] = val + + @property + def _prop_descriptions(self): + return """\ + ambient + Ambient light increases overall color visibility but + can wash out the image. + diffuse + Represents the extent that incident rays are reflected + in a range of angles. + facenormalsepsilon + Epsilon for face normals calculation avoids math issues + arising from degenerate geometry. + fresnel + Represents the reflectance as a dependency of the + viewing angle; e.g. paper is reflective when viewing it + from the edge of the paper (almost 90 degrees), causing + shine. + roughness + Alters specular reflection; the rougher the surface, + the wider and less contrasty the shine. + specular + Represents the level that incident rays are reflected + in a single direction, causing shine. + vertexnormalsepsilon + Epsilon for vertex normals calculation avoids math + issues arising from degenerate geometry. + """ + + def __init__( + self, + arg=None, + ambient=None, + diffuse=None, + facenormalsepsilon=None, + fresnel=None, + roughness=None, + specular=None, + vertexnormalsepsilon=None, + **kwargs, + ): + """ + Construct a new Lighting object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.streamtube.Lighting` + ambient + Ambient light increases overall color visibility but + can wash out the image. + diffuse + Represents the extent that incident rays are reflected + in a range of angles. + facenormalsepsilon + Epsilon for face normals calculation avoids math issues + arising from degenerate geometry. + fresnel + Represents the reflectance as a dependency of the + viewing angle; e.g. paper is reflective when viewing it + from the edge of the paper (almost 90 degrees), causing + shine. + roughness + Alters specular reflection; the rougher the surface, + the wider and less contrasty the shine. + specular + Represents the level that incident rays are reflected + in a single direction, causing shine. + vertexnormalsepsilon + Epsilon for vertex normals calculation avoids math + issues arising from degenerate geometry. + + Returns + ------- + Lighting + """ + super().__init__("lighting") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.streamtube.Lighting +constructor must be a dict or +an instance of :class:`plotly.graph_objs.streamtube.Lighting`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("ambient", arg, ambient) + self._set_property("diffuse", arg, diffuse) + self._set_property("facenormalsepsilon", arg, facenormalsepsilon) + self._set_property("fresnel", arg, fresnel) + self._set_property("roughness", arg, roughness) + self._set_property("specular", arg, specular) + self._set_property("vertexnormalsepsilon", arg, vertexnormalsepsilon) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_lightposition.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_lightposition.py new file mode 100644 index 0000000000000000000000000000000000000000..0c6c7f7dbf0c0263a49c09f25b2415375ec54e29 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_lightposition.py @@ -0,0 +1,129 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Lightposition(_BaseTraceHierarchyType): + _parent_path_str = "streamtube" + _path_str = "streamtube.lightposition" + _valid_props = {"x", "y", "z"} + + @property + def x(self): + """ + Numeric vector, representing the X coordinate for each vertex. + + The 'x' property is a number and may be specified as: + - An int or float in the interval [-100000, 100000] + + Returns + ------- + int|float + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def y(self): + """ + Numeric vector, representing the Y coordinate for each vertex. + + The 'y' property is a number and may be specified as: + - An int or float in the interval [-100000, 100000] + + Returns + ------- + int|float + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def z(self): + """ + Numeric vector, representing the Z coordinate for each vertex. + + The 'z' property is a number and may be specified as: + - An int or float in the interval [-100000, 100000] + + Returns + ------- + int|float + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def _prop_descriptions(self): + return """\ + x + Numeric vector, representing the X coordinate for each + vertex. + y + Numeric vector, representing the Y coordinate for each + vertex. + z + Numeric vector, representing the Z coordinate for each + vertex. + """ + + def __init__(self, arg=None, x=None, y=None, z=None, **kwargs): + """ + Construct a new Lightposition object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.streamtube.Lightposition` + x + Numeric vector, representing the X coordinate for each + vertex. + y + Numeric vector, representing the Y coordinate for each + vertex. + z + Numeric vector, representing the Z coordinate for each + vertex. + + Returns + ------- + Lightposition + """ + super().__init__("lightposition") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.streamtube.Lightposition +constructor must be a dict or +an instance of :class:`plotly.graph_objs.streamtube.Lightposition`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("x", arg, x) + self._set_property("y", arg, y) + self._set_property("z", arg, z) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_starts.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_starts.py new file mode 100644 index 0000000000000000000000000000000000000000..eccda6490de3a2f0cd5345a27a7cf7b7d6ea6790 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_starts.py @@ -0,0 +1,217 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Starts(_BaseTraceHierarchyType): + _parent_path_str = "streamtube" + _path_str = "streamtube.starts" + _valid_props = {"x", "xsrc", "y", "ysrc", "z", "zsrc"} + + @property + def x(self): + """ + Sets the x components of the starting position of the + streamtubes + + The 'x' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["x"] + + @x.setter + def x(self, val): + self["x"] = val + + @property + def xsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `x`. + + The 'xsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["xsrc"] + + @xsrc.setter + def xsrc(self, val): + self["xsrc"] = val + + @property + def y(self): + """ + Sets the y components of the starting position of the + streamtubes + + The 'y' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["y"] + + @y.setter + def y(self, val): + self["y"] = val + + @property + def ysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `y`. + + The 'ysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["ysrc"] + + @ysrc.setter + def ysrc(self, val): + self["ysrc"] = val + + @property + def z(self): + """ + Sets the z components of the starting position of the + streamtubes + + The 'z' property is an array that may be specified as a tuple, + list, numpy array, or pandas Series + + Returns + ------- + numpy.ndarray + """ + return self["z"] + + @z.setter + def z(self, val): + self["z"] = val + + @property + def zsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `z`. + + The 'zsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["zsrc"] + + @zsrc.setter + def zsrc(self, val): + self["zsrc"] = val + + @property + def _prop_descriptions(self): + return """\ + x + Sets the x components of the starting position of the + streamtubes + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y components of the starting position of the + streamtubes + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z components of the starting position of the + streamtubes + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + """ + + def __init__( + self, + arg=None, + x=None, + xsrc=None, + y=None, + ysrc=None, + z=None, + zsrc=None, + **kwargs, + ): + """ + Construct a new Starts object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.streamtube.Starts` + x + Sets the x components of the starting position of the + streamtubes + xsrc + Sets the source reference on Chart Studio Cloud for + `x`. + y + Sets the y components of the starting position of the + streamtubes + ysrc + Sets the source reference on Chart Studio Cloud for + `y`. + z + Sets the z components of the starting position of the + streamtubes + zsrc + Sets the source reference on Chart Studio Cloud for + `z`. + + Returns + ------- + Starts + """ + super().__init__("starts") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.streamtube.Starts +constructor must be a dict or +an instance of :class:`plotly.graph_objs.streamtube.Starts`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("x", arg, x) + self._set_property("xsrc", arg, xsrc) + self._set_property("y", arg, y) + self._set_property("ysrc", arg, ysrc) + self._set_property("z", arg, z) + self._set_property("zsrc", arg, zsrc) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..46d9371fa7014911c2cbdcffe8d95dd656ec5f99 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/streamtube/_stream.py @@ -0,0 +1,114 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "streamtube" + _path_str = "streamtube.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.streamtube.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.streamtube.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.streamtube.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..bcd588d164bc93f83113ce1eecfbb609ad369bde --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/__init__.py @@ -0,0 +1,44 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._box import Box + from ._hoverlabel import Hoverlabel + from ._legendgrouptitle import Legendgrouptitle + from ._line import Line + from ._marker import Marker + from ._meanline import Meanline + from ._selected import Selected + from ._stream import Stream + from ._unselected import Unselected + from . import box + from . import hoverlabel + from . import legendgrouptitle + from . import marker + from . import selected + from . import unselected +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [ + ".box", + ".hoverlabel", + ".legendgrouptitle", + ".marker", + ".selected", + ".unselected", + ], + [ + "._box.Box", + "._hoverlabel.Hoverlabel", + "._legendgrouptitle.Legendgrouptitle", + "._line.Line", + "._marker.Marker", + "._meanline.Meanline", + "._selected.Selected", + "._stream.Stream", + "._unselected.Unselected", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_box.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_box.py new file mode 100644 index 0000000000000000000000000000000000000000..ebb18b16f155ca8ea2e5660eab3b23188071ef01 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_box.py @@ -0,0 +1,163 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Box(_BaseTraceHierarchyType): + _parent_path_str = "violin" + _path_str = "violin.box" + _valid_props = {"fillcolor", "line", "visible", "width"} + + @property + def fillcolor(self): + """ + Sets the inner box plot fill color. + + The 'fillcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["fillcolor"] + + @fillcolor.setter + def fillcolor(self, val): + self["fillcolor"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.violin.box.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.violin.box.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def visible(self): + """ + Determines if an miniature box plot is drawn inside the + violins. + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def width(self): + """ + Sets the width of the inner box plots relative to the violins' + width. For example, with 1, the inner box plots are as wide as + the violins. + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def _prop_descriptions(self): + return """\ + fillcolor + Sets the inner box plot fill color. + line + :class:`plotly.graph_objects.violin.box.Line` instance + or dict with compatible properties + visible + Determines if an miniature box plot is drawn inside the + violins. + width + Sets the width of the inner box plots relative to the + violins' width. For example, with 1, the inner box + plots are as wide as the violins. + """ + + def __init__( + self, arg=None, fillcolor=None, line=None, visible=None, width=None, **kwargs + ): + """ + Construct a new Box object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.violin.Box` + fillcolor + Sets the inner box plot fill color. + line + :class:`plotly.graph_objects.violin.box.Line` instance + or dict with compatible properties + visible + Determines if an miniature box plot is drawn inside the + violins. + width + Sets the width of the inner box plots relative to the + violins' width. For example, with 1, the inner box + plots are as wide as the violins. + + Returns + ------- + Box + """ + super().__init__("box") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.violin.Box +constructor must be a dict or +an instance of :class:`plotly.graph_objs.violin.Box`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("fillcolor", arg, fillcolor) + self._set_property("line", arg, line) + self._set_property("visible", arg, visible) + self._set_property("width", arg, width) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_hoverlabel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_hoverlabel.py new file mode 100644 index 0000000000000000000000000000000000000000..b52dde907cf870349b6de9ff5f9af2ae7721448d --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_hoverlabel.py @@ -0,0 +1,366 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Hoverlabel(_BaseTraceHierarchyType): + _parent_path_str = "violin" + _path_str = "violin.hoverlabel" + _valid_props = { + "align", + "alignsrc", + "bgcolor", + "bgcolorsrc", + "bordercolor", + "bordercolorsrc", + "font", + "namelength", + "namelengthsrc", + "showarrow", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the text content within hover + label box. Has an effect only if the hover label text spans + more two or more lines + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'auto'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def alignsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `align`. + + The 'alignsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["alignsrc"] + + @alignsrc.setter + def alignsrc(self, val): + self["alignsrc"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the hover labels for this trace + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bgcolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `bgcolor`. + + The 'bgcolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bgcolorsrc"] + + @bgcolorsrc.setter + def bgcolorsrc(self, val): + self["bgcolorsrc"] = val + + @property + def bordercolor(self): + """ + Sets the border color of the hover labels for this trace. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def bordercolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + + The 'bordercolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bordercolorsrc"] + + @bordercolorsrc.setter + def bordercolorsrc(self, val): + self["bordercolorsrc"] = val + + @property + def font(self): + """ + Sets the font used in hover labels. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.violin.hoverlabel.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.violin.hoverlabel.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def namelength(self): + """ + Sets the default length (in number of characters) of the trace + name in the hover labels for all traces. -1 shows the whole + name regardless of length. 0-3 shows the first 0-3 characters, + and an integer >3 will show the whole name if it is less than + that many characters, but if it is longer, will truncate to + `namelength - 3` characters and add an ellipsis. + + The 'namelength' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["namelength"] + + @namelength.setter + def namelength(self, val): + self["namelength"] = val + + @property + def namelengthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `namelength`. + + The 'namelengthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["namelengthsrc"] + + @namelengthsrc.setter + def namelengthsrc(self, val): + self["namelengthsrc"] = val + + @property + def showarrow(self): + """ + Sets whether or not to show the hover label arrow/triangle + pointing to the data point. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + """ + + def __init__( + self, + arg=None, + align=None, + alignsrc=None, + bgcolor=None, + bgcolorsrc=None, + bordercolor=None, + bordercolorsrc=None, + font=None, + namelength=None, + namelengthsrc=None, + showarrow=None, + **kwargs, + ): + """ + Construct a new Hoverlabel object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.violin.Hoverlabel` + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + + Returns + ------- + Hoverlabel + """ + super().__init__("hoverlabel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.violin.Hoverlabel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.violin.Hoverlabel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("alignsrc", arg, alignsrc) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bgcolorsrc", arg, bgcolorsrc) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("bordercolorsrc", arg, bordercolorsrc) + self._set_property("font", arg, font) + self._set_property("namelength", arg, namelength) + self._set_property("namelengthsrc", arg, namelengthsrc) + self._set_property("showarrow", arg, showarrow) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..2345d2780603f9d627321ee3b8c991271cf03143 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "violin" + _path_str = "violin.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.violin.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.violin.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.violin.Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.violin.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.violin.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_line.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_line.py new file mode 100644 index 0000000000000000000000000000000000000000..e4b50d69819ba50dd3372c5a601f47a9f59a75f0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_line.py @@ -0,0 +1,103 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Line(_BaseTraceHierarchyType): + _parent_path_str = "violin" + _path_str = "violin.line" + _valid_props = {"color", "width"} + + @property + def color(self): + """ + Sets the color of line bounding the violin(s). + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def width(self): + """ + Sets the width (in px) of line bounding the violin(s). + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def _prop_descriptions(self): + return """\ + color + Sets the color of line bounding the violin(s). + width + Sets the width (in px) of line bounding the violin(s). + """ + + def __init__(self, arg=None, color=None, width=None, **kwargs): + """ + Construct a new Line object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.violin.Line` + color + Sets the color of line bounding the violin(s). + width + Sets the width (in px) of line bounding the violin(s). + + Returns + ------- + Line + """ + super().__init__("line") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.violin.Line +constructor must be a dict or +an instance of :class:`plotly.graph_objs.violin.Line`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("width", arg, width) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_marker.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_marker.py new file mode 100644 index 0000000000000000000000000000000000000000..6389cae0948c048fd793f792a490d1368ed03e36 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_marker.py @@ -0,0 +1,357 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Marker(_BaseTraceHierarchyType): + _parent_path_str = "violin" + _path_str = "violin.marker" + _valid_props = { + "angle", + "color", + "line", + "opacity", + "outliercolor", + "size", + "symbol", + } + + @property + def angle(self): + """ + Sets the marker angle in respect to `angleref`. + + The 'angle' property is a angle (in degrees) that may be + specified as a number between -180 and 180. + Numeric values outside this range are converted to the equivalent value + (e.g. 270 is converted to -90). + + Returns + ------- + int|float + """ + return self["angle"] + + @angle.setter + def angle(self, val): + self["angle"] = val + + @property + def color(self): + """ + Sets the marker color. It accepts either a specific color or an + array of numbers that are mapped to the colorscale relative to + the max and min values of the array or relative to + `marker.cmin` and `marker.cmax` if set. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.violin.marker.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.violin.marker.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def opacity(self): + """ + Sets the marker opacity. + + The 'opacity' property is a number and may be specified as: + - An int or float in the interval [0, 1] + + Returns + ------- + int|float + """ + return self["opacity"] + + @opacity.setter + def opacity(self, val): + self["opacity"] = val + + @property + def outliercolor(self): + """ + Sets the color of the outlier sample points. + + The 'outliercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["outliercolor"] + + @outliercolor.setter + def outliercolor(self, val): + self["outliercolor"] = val + + @property + def size(self): + """ + Sets the marker size (in px). + + The 'size' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def symbol(self): + """ + Sets the marker symbol type. Adding 100 is equivalent to + appending "-open" to a symbol name. Adding 200 is equivalent to + appending "-dot" to a symbol name. Adding 300 is equivalent to + appending "-open-dot" or "dot-open" to a symbol name. + + The 'symbol' property is an enumeration that may be specified as: + - One of the following enumeration values: + [0, '0', 'circle', 100, '100', 'circle-open', 200, '200', + 'circle-dot', 300, '300', 'circle-open-dot', 1, '1', + 'square', 101, '101', 'square-open', 201, '201', + 'square-dot', 301, '301', 'square-open-dot', 2, '2', + 'diamond', 102, '102', 'diamond-open', 202, '202', + 'diamond-dot', 302, '302', 'diamond-open-dot', 3, '3', + 'cross', 103, '103', 'cross-open', 203, '203', + 'cross-dot', 303, '303', 'cross-open-dot', 4, '4', 'x', + 104, '104', 'x-open', 204, '204', 'x-dot', 304, '304', + 'x-open-dot', 5, '5', 'triangle-up', 105, '105', + 'triangle-up-open', 205, '205', 'triangle-up-dot', 305, + '305', 'triangle-up-open-dot', 6, '6', 'triangle-down', + 106, '106', 'triangle-down-open', 206, '206', + 'triangle-down-dot', 306, '306', 'triangle-down-open-dot', + 7, '7', 'triangle-left', 107, '107', 'triangle-left-open', + 207, '207', 'triangle-left-dot', 307, '307', + 'triangle-left-open-dot', 8, '8', 'triangle-right', 108, + '108', 'triangle-right-open', 208, '208', + 'triangle-right-dot', 308, '308', + 'triangle-right-open-dot', 9, '9', 'triangle-ne', 109, + '109', 'triangle-ne-open', 209, '209', 'triangle-ne-dot', + 309, '309', 'triangle-ne-open-dot', 10, '10', + 'triangle-se', 110, '110', 'triangle-se-open', 210, '210', + 'triangle-se-dot', 310, '310', 'triangle-se-open-dot', 11, + '11', 'triangle-sw', 111, '111', 'triangle-sw-open', 211, + '211', 'triangle-sw-dot', 311, '311', + 'triangle-sw-open-dot', 12, '12', 'triangle-nw', 112, + '112', 'triangle-nw-open', 212, '212', 'triangle-nw-dot', + 312, '312', 'triangle-nw-open-dot', 13, '13', 'pentagon', + 113, '113', 'pentagon-open', 213, '213', 'pentagon-dot', + 313, '313', 'pentagon-open-dot', 14, '14', 'hexagon', 114, + '114', 'hexagon-open', 214, '214', 'hexagon-dot', 314, + '314', 'hexagon-open-dot', 15, '15', 'hexagon2', 115, + '115', 'hexagon2-open', 215, '215', 'hexagon2-dot', 315, + '315', 'hexagon2-open-dot', 16, '16', 'octagon', 116, + '116', 'octagon-open', 216, '216', 'octagon-dot', 316, + '316', 'octagon-open-dot', 17, '17', 'star', 117, '117', + 'star-open', 217, '217', 'star-dot', 317, '317', + 'star-open-dot', 18, '18', 'hexagram', 118, '118', + 'hexagram-open', 218, '218', 'hexagram-dot', 318, '318', + 'hexagram-open-dot', 19, '19', 'star-triangle-up', 119, + '119', 'star-triangle-up-open', 219, '219', + 'star-triangle-up-dot', 319, '319', + 'star-triangle-up-open-dot', 20, '20', + 'star-triangle-down', 120, '120', + 'star-triangle-down-open', 220, '220', + 'star-triangle-down-dot', 320, '320', + 'star-triangle-down-open-dot', 21, '21', 'star-square', + 121, '121', 'star-square-open', 221, '221', + 'star-square-dot', 321, '321', 'star-square-open-dot', 22, + '22', 'star-diamond', 122, '122', 'star-diamond-open', + 222, '222', 'star-diamond-dot', 322, '322', + 'star-diamond-open-dot', 23, '23', 'diamond-tall', 123, + '123', 'diamond-tall-open', 223, '223', + 'diamond-tall-dot', 323, '323', 'diamond-tall-open-dot', + 24, '24', 'diamond-wide', 124, '124', 'diamond-wide-open', + 224, '224', 'diamond-wide-dot', 324, '324', + 'diamond-wide-open-dot', 25, '25', 'hourglass', 125, + '125', 'hourglass-open', 26, '26', 'bowtie', 126, '126', + 'bowtie-open', 27, '27', 'circle-cross', 127, '127', + 'circle-cross-open', 28, '28', 'circle-x', 128, '128', + 'circle-x-open', 29, '29', 'square-cross', 129, '129', + 'square-cross-open', 30, '30', 'square-x', 130, '130', + 'square-x-open', 31, '31', 'diamond-cross', 131, '131', + 'diamond-cross-open', 32, '32', 'diamond-x', 132, '132', + 'diamond-x-open', 33, '33', 'cross-thin', 133, '133', + 'cross-thin-open', 34, '34', 'x-thin', 134, '134', + 'x-thin-open', 35, '35', 'asterisk', 135, '135', + 'asterisk-open', 36, '36', 'hash', 136, '136', + 'hash-open', 236, '236', 'hash-dot', 336, '336', + 'hash-open-dot', 37, '37', 'y-up', 137, '137', + 'y-up-open', 38, '38', 'y-down', 138, '138', + 'y-down-open', 39, '39', 'y-left', 139, '139', + 'y-left-open', 40, '40', 'y-right', 140, '140', + 'y-right-open', 41, '41', 'line-ew', 141, '141', + 'line-ew-open', 42, '42', 'line-ns', 142, '142', + 'line-ns-open', 43, '43', 'line-ne', 143, '143', + 'line-ne-open', 44, '44', 'line-nw', 144, '144', + 'line-nw-open', 45, '45', 'arrow-up', 145, '145', + 'arrow-up-open', 46, '46', 'arrow-down', 146, '146', + 'arrow-down-open', 47, '47', 'arrow-left', 147, '147', + 'arrow-left-open', 48, '48', 'arrow-right', 148, '148', + 'arrow-right-open', 49, '49', 'arrow-bar-up', 149, '149', + 'arrow-bar-up-open', 50, '50', 'arrow-bar-down', 150, + '150', 'arrow-bar-down-open', 51, '51', 'arrow-bar-left', + 151, '151', 'arrow-bar-left-open', 52, '52', + 'arrow-bar-right', 152, '152', 'arrow-bar-right-open', 53, + '53', 'arrow', 153, '153', 'arrow-open', 54, '54', + 'arrow-wide', 154, '154', 'arrow-wide-open'] + + Returns + ------- + Any + """ + return self["symbol"] + + @symbol.setter + def symbol(self, val): + self["symbol"] = val + + @property + def _prop_descriptions(self): + return """\ + angle + Sets the marker angle in respect to `angleref`. + color + Sets the marker color. It accepts either a specific + color or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `marker.cmin` and `marker.cmax` if + set. + line + :class:`plotly.graph_objects.violin.marker.Line` + instance or dict with compatible properties + opacity + Sets the marker opacity. + outliercolor + Sets the color of the outlier sample points. + size + Sets the marker size (in px). + symbol + Sets the marker symbol type. Adding 100 is equivalent + to appending "-open" to a symbol name. Adding 200 is + equivalent to appending "-dot" to a symbol name. Adding + 300 is equivalent to appending "-open-dot" or "dot- + open" to a symbol name. + """ + + def __init__( + self, + arg=None, + angle=None, + color=None, + line=None, + opacity=None, + outliercolor=None, + size=None, + symbol=None, + **kwargs, + ): + """ + Construct a new Marker object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.violin.Marker` + angle + Sets the marker angle in respect to `angleref`. + color + Sets the marker color. It accepts either a specific + color or an array of numbers that are mapped to the + colorscale relative to the max and min values of the + array or relative to `marker.cmin` and `marker.cmax` if + set. + line + :class:`plotly.graph_objects.violin.marker.Line` + instance or dict with compatible properties + opacity + Sets the marker opacity. + outliercolor + Sets the color of the outlier sample points. + size + Sets the marker size (in px). + symbol + Sets the marker symbol type. Adding 100 is equivalent + to appending "-open" to a symbol name. Adding 200 is + equivalent to appending "-dot" to a symbol name. Adding + 300 is equivalent to appending "-open-dot" or "dot- + open" to a symbol name. + + Returns + ------- + Marker + """ + super().__init__("marker") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.violin.Marker +constructor must be a dict or +an instance of :class:`plotly.graph_objs.violin.Marker`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("angle", arg, angle) + self._set_property("color", arg, color) + self._set_property("line", arg, line) + self._set_property("opacity", arg, opacity) + self._set_property("outliercolor", arg, outliercolor) + self._set_property("size", arg, size) + self._set_property("symbol", arg, symbol) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_meanline.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_meanline.py new file mode 100644 index 0000000000000000000000000000000000000000..75a34cd5793a080999d8b2fc1fb3db89f0556a98 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_meanline.py @@ -0,0 +1,138 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Meanline(_BaseTraceHierarchyType): + _parent_path_str = "violin" + _path_str = "violin.meanline" + _valid_props = {"color", "visible", "width"} + + @property + def color(self): + """ + Sets the mean line color. + + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + + Returns + ------- + str + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def visible(self): + """ + Determines if a line corresponding to the sample's mean is + shown inside the violins. If `box.visible` is turned on, the + mean line is drawn inside the inner box. Otherwise, the mean + line is drawn from one side of the violin to other. + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def width(self): + """ + Sets the mean line width. + + The 'width' property is a number and may be specified as: + - An int or float in the interval [0, inf] + + Returns + ------- + int|float + """ + return self["width"] + + @width.setter + def width(self, val): + self["width"] = val + + @property + def _prop_descriptions(self): + return """\ + color + Sets the mean line color. + visible + Determines if a line corresponding to the sample's mean + is shown inside the violins. If `box.visible` is turned + on, the mean line is drawn inside the inner box. + Otherwise, the mean line is drawn from one side of the + violin to other. + width + Sets the mean line width. + """ + + def __init__(self, arg=None, color=None, visible=None, width=None, **kwargs): + """ + Construct a new Meanline object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.violin.Meanline` + color + Sets the mean line color. + visible + Determines if a line corresponding to the sample's mean + is shown inside the violins. If `box.visible` is turned + on, the mean line is drawn inside the inner box. + Otherwise, the mean line is drawn from one side of the + violin to other. + width + Sets the mean line width. + + Returns + ------- + Meanline + """ + super().__init__("meanline") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.violin.Meanline +constructor must be a dict or +an instance of :class:`plotly.graph_objs.violin.Meanline`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("visible", arg, visible) + self._set_property("width", arg, width) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_selected.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_selected.py new file mode 100644 index 0000000000000000000000000000000000000000..ec18b8f8fb7188a7e72b4bda6f09c11e8f1449e2 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_selected.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Selected(_BaseTraceHierarchyType): + _parent_path_str = "violin" + _path_str = "violin.selected" + _valid_props = {"marker"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.violin.selected.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.violin.selected.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.violin.selected.Marker` + instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, **kwargs): + """ + Construct a new Selected object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.violin.Selected` + marker + :class:`plotly.graph_objects.violin.selected.Marker` + instance or dict with compatible properties + + Returns + ------- + Selected + """ + super().__init__("selected") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.violin.Selected +constructor must be a dict or +an instance of :class:`plotly.graph_objs.violin.Selected`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..959e45539e7a504db11388e068e8f8bb7ba01968 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_stream.py @@ -0,0 +1,113 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "violin" + _path_str = "violin.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of :class:`plotly.graph_objs.violin.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.violin.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.violin.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_unselected.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_unselected.py new file mode 100644 index 0000000000000000000000000000000000000000..9e13dda8d040a1722b3951dabb81cde8e85851b3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/violin/_unselected.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Unselected(_BaseTraceHierarchyType): + _parent_path_str = "violin" + _path_str = "violin.unselected" + _valid_props = {"marker"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.violin.unselected.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.violin.unselected.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.violin.unselected.Marker` + instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, **kwargs): + """ + Construct a new Unselected object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.violin.Unselected` + marker + :class:`plotly.graph_objects.violin.unselected.Marker` + instance or dict with compatible properties + + Returns + ------- + Unselected + """ + super().__init__("unselected") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.violin.Unselected +constructor must be a dict or +an instance of :class:`plotly.graph_objs.violin.Unselected`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e6bb5e4e4e44e853e916bd3d82b117e0cde34f55 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/__init__.py @@ -0,0 +1,46 @@ +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._connector import Connector + from ._decreasing import Decreasing + from ._hoverlabel import Hoverlabel + from ._increasing import Increasing + from ._insidetextfont import Insidetextfont + from ._legendgrouptitle import Legendgrouptitle + from ._outsidetextfont import Outsidetextfont + from ._stream import Stream + from ._textfont import Textfont + from ._totals import Totals + from . import connector + from . import decreasing + from . import hoverlabel + from . import increasing + from . import legendgrouptitle + from . import totals +else: + from _plotly_utils.importers import relative_import + + __all__, __getattr__, __dir__ = relative_import( + __name__, + [ + ".connector", + ".decreasing", + ".hoverlabel", + ".increasing", + ".legendgrouptitle", + ".totals", + ], + [ + "._connector.Connector", + "._decreasing.Decreasing", + "._hoverlabel.Hoverlabel", + "._increasing.Increasing", + "._insidetextfont.Insidetextfont", + "._legendgrouptitle.Legendgrouptitle", + "._outsidetextfont.Outsidetextfont", + "._stream.Stream", + "._textfont.Textfont", + "._totals.Totals", + ], + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_connector.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_connector.py new file mode 100644 index 0000000000000000000000000000000000000000..413dfb738e442c607da48e9dad95443dc1b2c50b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_connector.py @@ -0,0 +1,127 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Connector(_BaseTraceHierarchyType): + _parent_path_str = "waterfall" + _path_str = "waterfall.connector" + _valid_props = {"line", "mode", "visible"} + + @property + def line(self): + """ + The 'line' property is an instance of Line + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.connector.Line` + - A dict of string/value properties that will be passed + to the Line constructor + + Returns + ------- + plotly.graph_objs.waterfall.connector.Line + """ + return self["line"] + + @line.setter + def line(self, val): + self["line"] = val + + @property + def mode(self): + """ + Sets the shape of connector lines. + + The 'mode' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['spanning', 'between'] + + Returns + ------- + Any + """ + return self["mode"] + + @mode.setter + def mode(self, val): + self["mode"] = val + + @property + def visible(self): + """ + Determines if connector lines are drawn. + + The 'visible' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["visible"] + + @visible.setter + def visible(self, val): + self["visible"] = val + + @property + def _prop_descriptions(self): + return """\ + line + :class:`plotly.graph_objects.waterfall.connector.Line` + instance or dict with compatible properties + mode + Sets the shape of connector lines. + visible + Determines if connector lines are drawn. + """ + + def __init__(self, arg=None, line=None, mode=None, visible=None, **kwargs): + """ + Construct a new Connector object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.waterfall.Connector` + line + :class:`plotly.graph_objects.waterfall.connector.Line` + instance or dict with compatible properties + mode + Sets the shape of connector lines. + visible + Determines if connector lines are drawn. + + Returns + ------- + Connector + """ + super().__init__("connector") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.waterfall.Connector +constructor must be a dict or +an instance of :class:`plotly.graph_objs.waterfall.Connector`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("line", arg, line) + self._set_property("mode", arg, mode) + self._set_property("visible", arg, visible) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_decreasing.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_decreasing.py new file mode 100644 index 0000000000000000000000000000000000000000..b472b42da768f577372daacac2a3bc3539383744 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_decreasing.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Decreasing(_BaseTraceHierarchyType): + _parent_path_str = "waterfall" + _path_str = "waterfall.decreasing" + _valid_props = {"marker"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.decreasing.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.waterfall.decreasing.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.waterfall.decreasing.Marke + r` instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, **kwargs): + """ + Construct a new Decreasing object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.waterfall.Decreasing` + marker + :class:`plotly.graph_objects.waterfall.decreasing.Marke + r` instance or dict with compatible properties + + Returns + ------- + Decreasing + """ + super().__init__("decreasing") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.waterfall.Decreasing +constructor must be a dict or +an instance of :class:`plotly.graph_objs.waterfall.Decreasing`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_hoverlabel.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_hoverlabel.py new file mode 100644 index 0000000000000000000000000000000000000000..784e0db27d6dd50f780b3c56a3b317cb26d83bb9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_hoverlabel.py @@ -0,0 +1,366 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Hoverlabel(_BaseTraceHierarchyType): + _parent_path_str = "waterfall" + _path_str = "waterfall.hoverlabel" + _valid_props = { + "align", + "alignsrc", + "bgcolor", + "bgcolorsrc", + "bordercolor", + "bordercolorsrc", + "font", + "namelength", + "namelengthsrc", + "showarrow", + } + + @property + def align(self): + """ + Sets the horizontal alignment of the text content within hover + label box. Has an effect only if the hover label text spans + more two or more lines + + The 'align' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['left', 'right', 'auto'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["align"] + + @align.setter + def align(self, val): + self["align"] = val + + @property + def alignsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `align`. + + The 'alignsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["alignsrc"] + + @alignsrc.setter + def alignsrc(self, val): + self["alignsrc"] = val + + @property + def bgcolor(self): + """ + Sets the background color of the hover labels for this trace + + The 'bgcolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bgcolor"] + + @bgcolor.setter + def bgcolor(self, val): + self["bgcolor"] = val + + @property + def bgcolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `bgcolor`. + + The 'bgcolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bgcolorsrc"] + + @bgcolorsrc.setter + def bgcolorsrc(self, val): + self["bgcolorsrc"] = val + + @property + def bordercolor(self): + """ + Sets the border color of the hover labels for this trace. + + The 'bordercolor' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["bordercolor"] + + @bordercolor.setter + def bordercolor(self, val): + self["bordercolor"] = val + + @property + def bordercolorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + + The 'bordercolorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["bordercolorsrc"] + + @bordercolorsrc.setter + def bordercolorsrc(self, val): + self["bordercolorsrc"] = val + + @property + def font(self): + """ + Sets the font used in hover labels. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.hoverlabel.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.waterfall.hoverlabel.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def namelength(self): + """ + Sets the default length (in number of characters) of the trace + name in the hover labels for all traces. -1 shows the whole + name regardless of length. 0-3 shows the first 0-3 characters, + and an integer >3 will show the whole name if it is less than + that many characters, but if it is longer, will truncate to + `namelength - 3` characters and add an ellipsis. + + The 'namelength' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [-1, 9223372036854775807] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["namelength"] + + @namelength.setter + def namelength(self, val): + self["namelength"] = val + + @property + def namelengthsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `namelength`. + + The 'namelengthsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["namelengthsrc"] + + @namelengthsrc.setter + def namelengthsrc(self, val): + self["namelengthsrc"] = val + + @property + def showarrow(self): + """ + Sets whether or not to show the hover label arrow/triangle + pointing to the data point. + + The 'showarrow' property is a boolean and must be specified as: + - A boolean value: True or False + + Returns + ------- + bool + """ + return self["showarrow"] + + @showarrow.setter + def showarrow(self, val): + self["showarrow"] = val + + @property + def _prop_descriptions(self): + return """\ + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + """ + + def __init__( + self, + arg=None, + align=None, + alignsrc=None, + bgcolor=None, + bgcolorsrc=None, + bordercolor=None, + bordercolorsrc=None, + font=None, + namelength=None, + namelengthsrc=None, + showarrow=None, + **kwargs, + ): + """ + Construct a new Hoverlabel object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.waterfall.Hoverlabel` + align + Sets the horizontal alignment of the text content + within hover label box. Has an effect only if the hover + label text spans more two or more lines + alignsrc + Sets the source reference on Chart Studio Cloud for + `align`. + bgcolor + Sets the background color of the hover labels for this + trace + bgcolorsrc + Sets the source reference on Chart Studio Cloud for + `bgcolor`. + bordercolor + Sets the border color of the hover labels for this + trace. + bordercolorsrc + Sets the source reference on Chart Studio Cloud for + `bordercolor`. + font + Sets the font used in hover labels. + namelength + Sets the default length (in number of characters) of + the trace name in the hover labels for all traces. -1 + shows the whole name regardless of length. 0-3 shows + the first 0-3 characters, and an integer >3 will show + the whole name if it is less than that many characters, + but if it is longer, will truncate to `namelength - 3` + characters and add an ellipsis. + namelengthsrc + Sets the source reference on Chart Studio Cloud for + `namelength`. + showarrow + Sets whether or not to show the hover label + arrow/triangle pointing to the data point. + + Returns + ------- + Hoverlabel + """ + super().__init__("hoverlabel") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.waterfall.Hoverlabel +constructor must be a dict or +an instance of :class:`plotly.graph_objs.waterfall.Hoverlabel`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("align", arg, align) + self._set_property("alignsrc", arg, alignsrc) + self._set_property("bgcolor", arg, bgcolor) + self._set_property("bgcolorsrc", arg, bgcolorsrc) + self._set_property("bordercolor", arg, bordercolor) + self._set_property("bordercolorsrc", arg, bordercolorsrc) + self._set_property("font", arg, font) + self._set_property("namelength", arg, namelength) + self._set_property("namelengthsrc", arg, namelengthsrc) + self._set_property("showarrow", arg, showarrow) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_increasing.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_increasing.py new file mode 100644 index 0000000000000000000000000000000000000000..1a2d447084b21d74778ad7aa6c8bb3384d0e649c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_increasing.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Increasing(_BaseTraceHierarchyType): + _parent_path_str = "waterfall" + _path_str = "waterfall.increasing" + _valid_props = {"marker"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.increasing.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.waterfall.increasing.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.waterfall.increasing.Marke + r` instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, **kwargs): + """ + Construct a new Increasing object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.waterfall.Increasing` + marker + :class:`plotly.graph_objects.waterfall.increasing.Marke + r` instance or dict with compatible properties + + Returns + ------- + Increasing + """ + super().__init__("increasing") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.waterfall.Increasing +constructor must be a dict or +an instance of :class:`plotly.graph_objs.waterfall.Increasing`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_insidetextfont.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_insidetextfont.py new file mode 100644 index 0000000000000000000000000000000000000000..a316c5ff6a5fb694209389f584a0135de21967d3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_insidetextfont.py @@ -0,0 +1,587 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Insidetextfont(_BaseTraceHierarchyType): + _parent_path_str = "waterfall" + _path_str = "waterfall.insidetextfont" + _valid_props = { + "color", + "colorsrc", + "family", + "familysrc", + "lineposition", + "linepositionsrc", + "shadow", + "shadowsrc", + "size", + "sizesrc", + "style", + "stylesrc", + "textcase", + "textcasesrc", + "variant", + "variantsrc", + "weight", + "weightsrc", + } + + @property + def color(self): + """ + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def colorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `color`. + + The 'colorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["colorsrc"] + + @colorsrc.setter + def colorsrc(self, val): + self["colorsrc"] = val + + @property + def family(self): + """ + HTML font family - the typeface that will be applied by the web + browser. The web browser can only apply a font if it is + available on the system where it runs. Provide multiple font + families, separated by commas, to indicate the order in which + to apply fonts if they aren't available. + + The 'family' property is a string and must be specified as: + - A non-empty string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["family"] + + @family.setter + def family(self, val): + self["family"] = val + + @property + def familysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `family`. + + The 'familysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["familysrc"] + + @familysrc.setter + def familysrc(self, val): + self["familysrc"] = val + + @property + def lineposition(self): + """ + Sets the kind of decoration line(s) with text, such as an + "under", "over" or "through" as well as combinations e.g. + "under+over", etc. + + The 'lineposition' property is a flaglist and may be specified + as a string containing: + - Any combination of ['under', 'over', 'through'] joined with '+' characters + (e.g. 'under+over') + OR exactly one of ['none'] (e.g. 'none') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["lineposition"] + + @lineposition.setter + def lineposition(self, val): + self["lineposition"] = val + + @property + def linepositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `lineposition`. + + The 'linepositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["linepositionsrc"] + + @linepositionsrc.setter + def linepositionsrc(self, val): + self["linepositionsrc"] = val + + @property + def shadow(self): + """ + Sets the shape and color of the shadow behind text. "auto" + places minimal shadow and applies contrast text font color. See + https://developer.mozilla.org/en-US/docs/Web/CSS/text-shadow + for additional options. + + The 'shadow' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["shadow"] + + @shadow.setter + def shadow(self, val): + self["shadow"] = val + + @property + def shadowsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `shadow`. + + The 'shadowsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["shadowsrc"] + + @shadowsrc.setter + def shadowsrc(self, val): + self["shadowsrc"] = val + + @property + def size(self): + """ + The 'size' property is a number and may be specified as: + - An int or float in the interval [1, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def sizesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `size`. + + The 'sizesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["sizesrc"] + + @sizesrc.setter + def sizesrc(self, val): + self["sizesrc"] = val + + @property + def style(self): + """ + Sets whether a font should be styled with a normal or italic + face from its family. + + The 'style' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'italic'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def stylesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `style`. + + The 'stylesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["stylesrc"] + + @stylesrc.setter + def stylesrc(self, val): + self["stylesrc"] = val + + @property + def textcase(self): + """ + Sets capitalization of text. It can be used to make text appear + in all-uppercase or all-lowercase, or with each word + capitalized. + + The 'textcase' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'word caps', 'upper', 'lower'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textcase"] + + @textcase.setter + def textcase(self, val): + self["textcase"] = val + + @property + def textcasesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `textcase`. + + The 'textcasesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textcasesrc"] + + @textcasesrc.setter + def textcasesrc(self, val): + self["textcasesrc"] = val + + @property + def variant(self): + """ + Sets the variant of the font. + + The 'variant' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'small-caps', 'all-small-caps', + 'all-petite-caps', 'petite-caps', 'unicase'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["variant"] + + @variant.setter + def variant(self, val): + self["variant"] = val + + @property + def variantsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `variant`. + + The 'variantsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["variantsrc"] + + @variantsrc.setter + def variantsrc(self, val): + self["variantsrc"] = val + + @property + def weight(self): + """ + Sets the weight (or boldness) of the font. + + The 'weight' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 1000] + OR exactly one of ['normal', 'bold'] (e.g. 'bold') + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["weight"] + + @weight.setter + def weight(self, val): + self["weight"] = val + + @property + def weightsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `weight`. + + The 'weightsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["weightsrc"] + + @weightsrc.setter + def weightsrc(self, val): + self["weightsrc"] = val + + @property + def _prop_descriptions(self): + return """\ + color + + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + familysrc + Sets the source reference on Chart Studio Cloud for + `family`. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + linepositionsrc + Sets the source reference on Chart Studio Cloud for + `lineposition`. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + shadowsrc + Sets the source reference on Chart Studio Cloud for + `shadow`. + size + + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + style + Sets whether a font should be styled with a normal or + italic face from its family. + stylesrc + Sets the source reference on Chart Studio Cloud for + `style`. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + textcasesrc + Sets the source reference on Chart Studio Cloud for + `textcase`. + variant + Sets the variant of the font. + variantsrc + Sets the source reference on Chart Studio Cloud for + `variant`. + weight + Sets the weight (or boldness) of the font. + weightsrc + Sets the source reference on Chart Studio Cloud for + `weight`. + """ + + def __init__( + self, + arg=None, + color=None, + colorsrc=None, + family=None, + familysrc=None, + lineposition=None, + linepositionsrc=None, + shadow=None, + shadowsrc=None, + size=None, + sizesrc=None, + style=None, + stylesrc=None, + textcase=None, + textcasesrc=None, + variant=None, + variantsrc=None, + weight=None, + weightsrc=None, + **kwargs, + ): + """ + Construct a new Insidetextfont object + + Sets the font used for `text` lying inside the bar. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.waterfall.Insidetextfont` + color + + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + familysrc + Sets the source reference on Chart Studio Cloud for + `family`. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + linepositionsrc + Sets the source reference on Chart Studio Cloud for + `lineposition`. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + shadowsrc + Sets the source reference on Chart Studio Cloud for + `shadow`. + size + + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + style + Sets whether a font should be styled with a normal or + italic face from its family. + stylesrc + Sets the source reference on Chart Studio Cloud for + `style`. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + textcasesrc + Sets the source reference on Chart Studio Cloud for + `textcase`. + variant + Sets the variant of the font. + variantsrc + Sets the source reference on Chart Studio Cloud for + `variant`. + weight + Sets the weight (or boldness) of the font. + weightsrc + Sets the source reference on Chart Studio Cloud for + `weight`. + + Returns + ------- + Insidetextfont + """ + super().__init__("insidetextfont") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.waterfall.Insidetextfont +constructor must be a dict or +an instance of :class:`plotly.graph_objs.waterfall.Insidetextfont`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("colorsrc", arg, colorsrc) + self._set_property("family", arg, family) + self._set_property("familysrc", arg, familysrc) + self._set_property("lineposition", arg, lineposition) + self._set_property("linepositionsrc", arg, linepositionsrc) + self._set_property("shadow", arg, shadow) + self._set_property("shadowsrc", arg, shadowsrc) + self._set_property("size", arg, size) + self._set_property("sizesrc", arg, sizesrc) + self._set_property("style", arg, style) + self._set_property("stylesrc", arg, stylesrc) + self._set_property("textcase", arg, textcase) + self._set_property("textcasesrc", arg, textcasesrc) + self._set_property("variant", arg, variant) + self._set_property("variantsrc", arg, variantsrc) + self._set_property("weight", arg, weight) + self._set_property("weightsrc", arg, weightsrc) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_legendgrouptitle.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_legendgrouptitle.py new file mode 100644 index 0000000000000000000000000000000000000000..9b2950152d501ca0b588fc1d6afc17244bd1aaf8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_legendgrouptitle.py @@ -0,0 +1,104 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Legendgrouptitle(_BaseTraceHierarchyType): + _parent_path_str = "waterfall" + _path_str = "waterfall.legendgrouptitle" + _valid_props = {"font", "text"} + + @property + def font(self): + """ + Sets this legend group's title font. + + The 'font' property is an instance of Font + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.legendgrouptitle.Font` + - A dict of string/value properties that will be passed + to the Font constructor + + Returns + ------- + plotly.graph_objs.waterfall.legendgrouptitle.Font + """ + return self["font"] + + @font.setter + def font(self, val): + self["font"] = val + + @property + def text(self): + """ + Sets the title of the legend group. + + The 'text' property is a string and must be specified as: + - A string + - A number that will be converted to a string + + Returns + ------- + str + """ + return self["text"] + + @text.setter + def text(self, val): + self["text"] = val + + @property + def _prop_descriptions(self): + return """\ + font + Sets this legend group's title font. + text + Sets the title of the legend group. + """ + + def __init__(self, arg=None, font=None, text=None, **kwargs): + """ + Construct a new Legendgrouptitle object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.waterfall.Legendgrouptitle` + font + Sets this legend group's title font. + text + Sets the title of the legend group. + + Returns + ------- + Legendgrouptitle + """ + super().__init__("legendgrouptitle") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.waterfall.Legendgrouptitle +constructor must be a dict or +an instance of :class:`plotly.graph_objs.waterfall.Legendgrouptitle`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("font", arg, font) + self._set_property("text", arg, text) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_outsidetextfont.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_outsidetextfont.py new file mode 100644 index 0000000000000000000000000000000000000000..8e1371b9277fbd70938e40bead124876d9c65f53 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_outsidetextfont.py @@ -0,0 +1,587 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Outsidetextfont(_BaseTraceHierarchyType): + _parent_path_str = "waterfall" + _path_str = "waterfall.outsidetextfont" + _valid_props = { + "color", + "colorsrc", + "family", + "familysrc", + "lineposition", + "linepositionsrc", + "shadow", + "shadowsrc", + "size", + "sizesrc", + "style", + "stylesrc", + "textcase", + "textcasesrc", + "variant", + "variantsrc", + "weight", + "weightsrc", + } + + @property + def color(self): + """ + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def colorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `color`. + + The 'colorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["colorsrc"] + + @colorsrc.setter + def colorsrc(self, val): + self["colorsrc"] = val + + @property + def family(self): + """ + HTML font family - the typeface that will be applied by the web + browser. The web browser can only apply a font if it is + available on the system where it runs. Provide multiple font + families, separated by commas, to indicate the order in which + to apply fonts if they aren't available. + + The 'family' property is a string and must be specified as: + - A non-empty string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["family"] + + @family.setter + def family(self, val): + self["family"] = val + + @property + def familysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `family`. + + The 'familysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["familysrc"] + + @familysrc.setter + def familysrc(self, val): + self["familysrc"] = val + + @property + def lineposition(self): + """ + Sets the kind of decoration line(s) with text, such as an + "under", "over" or "through" as well as combinations e.g. + "under+over", etc. + + The 'lineposition' property is a flaglist and may be specified + as a string containing: + - Any combination of ['under', 'over', 'through'] joined with '+' characters + (e.g. 'under+over') + OR exactly one of ['none'] (e.g. 'none') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["lineposition"] + + @lineposition.setter + def lineposition(self, val): + self["lineposition"] = val + + @property + def linepositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `lineposition`. + + The 'linepositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["linepositionsrc"] + + @linepositionsrc.setter + def linepositionsrc(self, val): + self["linepositionsrc"] = val + + @property + def shadow(self): + """ + Sets the shape and color of the shadow behind text. "auto" + places minimal shadow and applies contrast text font color. See + https://developer.mozilla.org/en-US/docs/Web/CSS/text-shadow + for additional options. + + The 'shadow' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["shadow"] + + @shadow.setter + def shadow(self, val): + self["shadow"] = val + + @property + def shadowsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `shadow`. + + The 'shadowsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["shadowsrc"] + + @shadowsrc.setter + def shadowsrc(self, val): + self["shadowsrc"] = val + + @property + def size(self): + """ + The 'size' property is a number and may be specified as: + - An int or float in the interval [1, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def sizesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `size`. + + The 'sizesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["sizesrc"] + + @sizesrc.setter + def sizesrc(self, val): + self["sizesrc"] = val + + @property + def style(self): + """ + Sets whether a font should be styled with a normal or italic + face from its family. + + The 'style' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'italic'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def stylesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `style`. + + The 'stylesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["stylesrc"] + + @stylesrc.setter + def stylesrc(self, val): + self["stylesrc"] = val + + @property + def textcase(self): + """ + Sets capitalization of text. It can be used to make text appear + in all-uppercase or all-lowercase, or with each word + capitalized. + + The 'textcase' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'word caps', 'upper', 'lower'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textcase"] + + @textcase.setter + def textcase(self, val): + self["textcase"] = val + + @property + def textcasesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `textcase`. + + The 'textcasesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textcasesrc"] + + @textcasesrc.setter + def textcasesrc(self, val): + self["textcasesrc"] = val + + @property + def variant(self): + """ + Sets the variant of the font. + + The 'variant' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'small-caps', 'all-small-caps', + 'all-petite-caps', 'petite-caps', 'unicase'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["variant"] + + @variant.setter + def variant(self, val): + self["variant"] = val + + @property + def variantsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `variant`. + + The 'variantsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["variantsrc"] + + @variantsrc.setter + def variantsrc(self, val): + self["variantsrc"] = val + + @property + def weight(self): + """ + Sets the weight (or boldness) of the font. + + The 'weight' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 1000] + OR exactly one of ['normal', 'bold'] (e.g. 'bold') + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["weight"] + + @weight.setter + def weight(self, val): + self["weight"] = val + + @property + def weightsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `weight`. + + The 'weightsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["weightsrc"] + + @weightsrc.setter + def weightsrc(self, val): + self["weightsrc"] = val + + @property + def _prop_descriptions(self): + return """\ + color + + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + familysrc + Sets the source reference on Chart Studio Cloud for + `family`. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + linepositionsrc + Sets the source reference on Chart Studio Cloud for + `lineposition`. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + shadowsrc + Sets the source reference on Chart Studio Cloud for + `shadow`. + size + + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + style + Sets whether a font should be styled with a normal or + italic face from its family. + stylesrc + Sets the source reference on Chart Studio Cloud for + `style`. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + textcasesrc + Sets the source reference on Chart Studio Cloud for + `textcase`. + variant + Sets the variant of the font. + variantsrc + Sets the source reference on Chart Studio Cloud for + `variant`. + weight + Sets the weight (or boldness) of the font. + weightsrc + Sets the source reference on Chart Studio Cloud for + `weight`. + """ + + def __init__( + self, + arg=None, + color=None, + colorsrc=None, + family=None, + familysrc=None, + lineposition=None, + linepositionsrc=None, + shadow=None, + shadowsrc=None, + size=None, + sizesrc=None, + style=None, + stylesrc=None, + textcase=None, + textcasesrc=None, + variant=None, + variantsrc=None, + weight=None, + weightsrc=None, + **kwargs, + ): + """ + Construct a new Outsidetextfont object + + Sets the font used for `text` lying outside the bar. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.waterfall.Outsidetextfont` + color + + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + familysrc + Sets the source reference on Chart Studio Cloud for + `family`. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + linepositionsrc + Sets the source reference on Chart Studio Cloud for + `lineposition`. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + shadowsrc + Sets the source reference on Chart Studio Cloud for + `shadow`. + size + + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + style + Sets whether a font should be styled with a normal or + italic face from its family. + stylesrc + Sets the source reference on Chart Studio Cloud for + `style`. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + textcasesrc + Sets the source reference on Chart Studio Cloud for + `textcase`. + variant + Sets the variant of the font. + variantsrc + Sets the source reference on Chart Studio Cloud for + `variant`. + weight + Sets the weight (or boldness) of the font. + weightsrc + Sets the source reference on Chart Studio Cloud for + `weight`. + + Returns + ------- + Outsidetextfont + """ + super().__init__("outsidetextfont") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.waterfall.Outsidetextfont +constructor must be a dict or +an instance of :class:`plotly.graph_objs.waterfall.Outsidetextfont`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("colorsrc", arg, colorsrc) + self._set_property("family", arg, family) + self._set_property("familysrc", arg, familysrc) + self._set_property("lineposition", arg, lineposition) + self._set_property("linepositionsrc", arg, linepositionsrc) + self._set_property("shadow", arg, shadow) + self._set_property("shadowsrc", arg, shadowsrc) + self._set_property("size", arg, size) + self._set_property("sizesrc", arg, sizesrc) + self._set_property("style", arg, style) + self._set_property("stylesrc", arg, stylesrc) + self._set_property("textcase", arg, textcase) + self._set_property("textcasesrc", arg, textcasesrc) + self._set_property("variant", arg, variant) + self._set_property("variantsrc", arg, variantsrc) + self._set_property("weight", arg, weight) + self._set_property("weightsrc", arg, weightsrc) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_stream.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_stream.py new file mode 100644 index 0000000000000000000000000000000000000000..488e44dfcecc1fb0359a40d677357bff1202db24 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_stream.py @@ -0,0 +1,114 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Stream(_BaseTraceHierarchyType): + _parent_path_str = "waterfall" + _path_str = "waterfall.stream" + _valid_props = {"maxpoints", "token"} + + @property + def maxpoints(self): + """ + Sets the maximum number of points to keep on the plots from an + incoming stream. If `maxpoints` is set to 50, only the newest + 50 points will be displayed on the plot. + + The 'maxpoints' property is a number and may be specified as: + - An int or float in the interval [0, 10000] + + Returns + ------- + int|float + """ + return self["maxpoints"] + + @maxpoints.setter + def maxpoints(self, val): + self["maxpoints"] = val + + @property + def token(self): + """ + The stream id number links a data trace on a plot with a + stream. See https://chart-studio.plotly.com/settings for more + details. + + The 'token' property is a string and must be specified as: + - A non-empty string + + Returns + ------- + str + """ + return self["token"] + + @token.setter + def token(self, val): + self["token"] = val + + @property + def _prop_descriptions(self): + return """\ + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + """ + + def __init__(self, arg=None, maxpoints=None, token=None, **kwargs): + """ + Construct a new Stream object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.waterfall.Stream` + maxpoints + Sets the maximum number of points to keep on the plots + from an incoming stream. If `maxpoints` is set to 50, + only the newest 50 points will be displayed on the + plot. + token + The stream id number links a data trace on a plot with + a stream. See https://chart-studio.plotly.com/settings + for more details. + + Returns + ------- + Stream + """ + super().__init__("stream") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.waterfall.Stream +constructor must be a dict or +an instance of :class:`plotly.graph_objs.waterfall.Stream`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("maxpoints", arg, maxpoints) + self._set_property("token", arg, token) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_textfont.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_textfont.py new file mode 100644 index 0000000000000000000000000000000000000000..5f6640e5f99a267275ab63daf08ed7e27e86db70 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_textfont.py @@ -0,0 +1,587 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Textfont(_BaseTraceHierarchyType): + _parent_path_str = "waterfall" + _path_str = "waterfall.textfont" + _valid_props = { + "color", + "colorsrc", + "family", + "familysrc", + "lineposition", + "linepositionsrc", + "shadow", + "shadowsrc", + "size", + "sizesrc", + "style", + "stylesrc", + "textcase", + "textcasesrc", + "variant", + "variantsrc", + "weight", + "weightsrc", + } + + @property + def color(self): + """ + The 'color' property is a color and may be specified as: + - A hex string (e.g. '#ff0000') + - An rgb/rgba string (e.g. 'rgb(255,0,0)') + - An hsl/hsla string (e.g. 'hsl(0,100%,50%)') + - An hsv/hsva string (e.g. 'hsv(0,100%,100%)') + - A named CSS color: see https://plotly.com/python/css-colors/ for a list + - A list or array of any of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["color"] + + @color.setter + def color(self, val): + self["color"] = val + + @property + def colorsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `color`. + + The 'colorsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["colorsrc"] + + @colorsrc.setter + def colorsrc(self, val): + self["colorsrc"] = val + + @property + def family(self): + """ + HTML font family - the typeface that will be applied by the web + browser. The web browser can only apply a font if it is + available on the system where it runs. Provide multiple font + families, separated by commas, to indicate the order in which + to apply fonts if they aren't available. + + The 'family' property is a string and must be specified as: + - A non-empty string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["family"] + + @family.setter + def family(self, val): + self["family"] = val + + @property + def familysrc(self): + """ + Sets the source reference on Chart Studio Cloud for `family`. + + The 'familysrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["familysrc"] + + @familysrc.setter + def familysrc(self, val): + self["familysrc"] = val + + @property + def lineposition(self): + """ + Sets the kind of decoration line(s) with text, such as an + "under", "over" or "through" as well as combinations e.g. + "under+over", etc. + + The 'lineposition' property is a flaglist and may be specified + as a string containing: + - Any combination of ['under', 'over', 'through'] joined with '+' characters + (e.g. 'under+over') + OR exactly one of ['none'] (e.g. 'none') + - A list or array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["lineposition"] + + @lineposition.setter + def lineposition(self, val): + self["lineposition"] = val + + @property + def linepositionsrc(self): + """ + Sets the source reference on Chart Studio Cloud for + `lineposition`. + + The 'linepositionsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["linepositionsrc"] + + @linepositionsrc.setter + def linepositionsrc(self, val): + self["linepositionsrc"] = val + + @property + def shadow(self): + """ + Sets the shape and color of the shadow behind text. "auto" + places minimal shadow and applies contrast text font color. See + https://developer.mozilla.org/en-US/docs/Web/CSS/text-shadow + for additional options. + + The 'shadow' property is a string and must be specified as: + - A string + - A number that will be converted to a string + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + str|numpy.ndarray + """ + return self["shadow"] + + @shadow.setter + def shadow(self, val): + self["shadow"] = val + + @property + def shadowsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `shadow`. + + The 'shadowsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["shadowsrc"] + + @shadowsrc.setter + def shadowsrc(self, val): + self["shadowsrc"] = val + + @property + def size(self): + """ + The 'size' property is a number and may be specified as: + - An int or float in the interval [1, inf] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|float|numpy.ndarray + """ + return self["size"] + + @size.setter + def size(self, val): + self["size"] = val + + @property + def sizesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `size`. + + The 'sizesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["sizesrc"] + + @sizesrc.setter + def sizesrc(self, val): + self["sizesrc"] = val + + @property + def style(self): + """ + Sets whether a font should be styled with a normal or italic + face from its family. + + The 'style' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'italic'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["style"] + + @style.setter + def style(self, val): + self["style"] = val + + @property + def stylesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `style`. + + The 'stylesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["stylesrc"] + + @stylesrc.setter + def stylesrc(self, val): + self["stylesrc"] = val + + @property + def textcase(self): + """ + Sets capitalization of text. It can be used to make text appear + in all-uppercase or all-lowercase, or with each word + capitalized. + + The 'textcase' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'word caps', 'upper', 'lower'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["textcase"] + + @textcase.setter + def textcase(self, val): + self["textcase"] = val + + @property + def textcasesrc(self): + """ + Sets the source reference on Chart Studio Cloud for `textcase`. + + The 'textcasesrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["textcasesrc"] + + @textcasesrc.setter + def textcasesrc(self, val): + self["textcasesrc"] = val + + @property + def variant(self): + """ + Sets the variant of the font. + + The 'variant' property is an enumeration that may be specified as: + - One of the following enumeration values: + ['normal', 'small-caps', 'all-small-caps', + 'all-petite-caps', 'petite-caps', 'unicase'] + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + Any|numpy.ndarray + """ + return self["variant"] + + @variant.setter + def variant(self, val): + self["variant"] = val + + @property + def variantsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `variant`. + + The 'variantsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["variantsrc"] + + @variantsrc.setter + def variantsrc(self, val): + self["variantsrc"] = val + + @property + def weight(self): + """ + Sets the weight (or boldness) of the font. + + The 'weight' property is a integer and may be specified as: + - An int (or float that will be cast to an int) + in the interval [1, 1000] + OR exactly one of ['normal', 'bold'] (e.g. 'bold') + - A tuple, list, or one-dimensional numpy array of the above + + Returns + ------- + int|numpy.ndarray + """ + return self["weight"] + + @weight.setter + def weight(self, val): + self["weight"] = val + + @property + def weightsrc(self): + """ + Sets the source reference on Chart Studio Cloud for `weight`. + + The 'weightsrc' property must be specified as a string or + as a plotly.grid_objs.Column object + + Returns + ------- + str + """ + return self["weightsrc"] + + @weightsrc.setter + def weightsrc(self, val): + self["weightsrc"] = val + + @property + def _prop_descriptions(self): + return """\ + color + + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + familysrc + Sets the source reference on Chart Studio Cloud for + `family`. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + linepositionsrc + Sets the source reference on Chart Studio Cloud for + `lineposition`. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + shadowsrc + Sets the source reference on Chart Studio Cloud for + `shadow`. + size + + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + style + Sets whether a font should be styled with a normal or + italic face from its family. + stylesrc + Sets the source reference on Chart Studio Cloud for + `style`. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + textcasesrc + Sets the source reference on Chart Studio Cloud for + `textcase`. + variant + Sets the variant of the font. + variantsrc + Sets the source reference on Chart Studio Cloud for + `variant`. + weight + Sets the weight (or boldness) of the font. + weightsrc + Sets the source reference on Chart Studio Cloud for + `weight`. + """ + + def __init__( + self, + arg=None, + color=None, + colorsrc=None, + family=None, + familysrc=None, + lineposition=None, + linepositionsrc=None, + shadow=None, + shadowsrc=None, + size=None, + sizesrc=None, + style=None, + stylesrc=None, + textcase=None, + textcasesrc=None, + variant=None, + variantsrc=None, + weight=None, + weightsrc=None, + **kwargs, + ): + """ + Construct a new Textfont object + + Sets the font used for `text`. + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.waterfall.Textfont` + color + + colorsrc + Sets the source reference on Chart Studio Cloud for + `color`. + family + HTML font family - the typeface that will be applied by + the web browser. The web browser can only apply a font + if it is available on the system where it runs. Provide + multiple font families, separated by commas, to + indicate the order in which to apply fonts if they + aren't available. + familysrc + Sets the source reference on Chart Studio Cloud for + `family`. + lineposition + Sets the kind of decoration line(s) with text, such as + an "under", "over" or "through" as well as combinations + e.g. "under+over", etc. + linepositionsrc + Sets the source reference on Chart Studio Cloud for + `lineposition`. + shadow + Sets the shape and color of the shadow behind text. + "auto" places minimal shadow and applies contrast text + font color. See https://developer.mozilla.org/en- + US/docs/Web/CSS/text-shadow for additional options. + shadowsrc + Sets the source reference on Chart Studio Cloud for + `shadow`. + size + + sizesrc + Sets the source reference on Chart Studio Cloud for + `size`. + style + Sets whether a font should be styled with a normal or + italic face from its family. + stylesrc + Sets the source reference on Chart Studio Cloud for + `style`. + textcase + Sets capitalization of text. It can be used to make + text appear in all-uppercase or all-lowercase, or with + each word capitalized. + textcasesrc + Sets the source reference on Chart Studio Cloud for + `textcase`. + variant + Sets the variant of the font. + variantsrc + Sets the source reference on Chart Studio Cloud for + `variant`. + weight + Sets the weight (or boldness) of the font. + weightsrc + Sets the source reference on Chart Studio Cloud for + `weight`. + + Returns + ------- + Textfont + """ + super().__init__("textfont") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.waterfall.Textfont +constructor must be a dict or +an instance of :class:`plotly.graph_objs.waterfall.Textfont`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("color", arg, color) + self._set_property("colorsrc", arg, colorsrc) + self._set_property("family", arg, family) + self._set_property("familysrc", arg, familysrc) + self._set_property("lineposition", arg, lineposition) + self._set_property("linepositionsrc", arg, linepositionsrc) + self._set_property("shadow", arg, shadow) + self._set_property("shadowsrc", arg, shadowsrc) + self._set_property("size", arg, size) + self._set_property("sizesrc", arg, sizesrc) + self._set_property("style", arg, style) + self._set_property("stylesrc", arg, stylesrc) + self._set_property("textcase", arg, textcase) + self._set_property("textcasesrc", arg, textcasesrc) + self._set_property("variant", arg, variant) + self._set_property("variantsrc", arg, variantsrc) + self._set_property("weight", arg, weight) + self._set_property("weightsrc", arg, weightsrc) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_totals.py b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_totals.py new file mode 100644 index 0000000000000000000000000000000000000000..d7f4431f3b80339af145fa1748b5b2c9d5037d7c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/graph_objs/waterfall/_totals.py @@ -0,0 +1,80 @@ +# --- THIS FILE IS AUTO-GENERATED --- +# Modifications will be overwitten the next time code generation run. + +from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType +import copy as _copy + + +class Totals(_BaseTraceHierarchyType): + _parent_path_str = "waterfall" + _path_str = "waterfall.totals" + _valid_props = {"marker"} + + @property + def marker(self): + """ + The 'marker' property is an instance of Marker + that may be specified as: + - An instance of :class:`plotly.graph_objs.waterfall.totals.Marker` + - A dict of string/value properties that will be passed + to the Marker constructor + + Returns + ------- + plotly.graph_objs.waterfall.totals.Marker + """ + return self["marker"] + + @marker.setter + def marker(self, val): + self["marker"] = val + + @property + def _prop_descriptions(self): + return """\ + marker + :class:`plotly.graph_objects.waterfall.totals.Marker` + instance or dict with compatible properties + """ + + def __init__(self, arg=None, marker=None, **kwargs): + """ + Construct a new Totals object + + Parameters + ---------- + arg + dict of properties compatible with this constructor or + an instance of + :class:`plotly.graph_objs.waterfall.Totals` + marker + :class:`plotly.graph_objects.waterfall.totals.Marker` + instance or dict with compatible properties + + Returns + ------- + Totals + """ + super().__init__("totals") + if "_parent" in kwargs: + self._parent = kwargs["_parent"] + return + + if arg is None: + arg = {} + elif isinstance(arg, self.__class__): + arg = arg.to_plotly_json() + elif isinstance(arg, dict): + arg = _copy.copy(arg) + else: + raise ValueError("""\ +The first argument to the plotly.graph_objs.waterfall.Totals +constructor must be a dict or +an instance of :class:`plotly.graph_objs.waterfall.Totals`""") + + self._skip_invalid = kwargs.pop("skip_invalid", False) + self._validate = kwargs.pop("_validate", True) + + self._set_property("marker", arg, marker) + self._process_kwargs(**dict(arg, **kwargs)) + self._skip_invalid = False diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/io/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..e2d68242da14a4f867529a602d1ae15c100dfbd7 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/io/__init__.py @@ -0,0 +1,70 @@ +# ruff: noqa: F401 + +from _plotly_utils.importers import relative_import +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from ._kaleido import ( + to_image, + write_image, + write_images, + full_figure_for_development, + ) + from . import orca, kaleido + from . import json + from ._json import to_json, from_json, read_json, write_json + from ._templates import templates, to_templated + from ._html import to_html, write_html + from ._renderers import renderers, show + from . import base_renderers + from ._kaleido import defaults, get_chrome + + __all__ = [ + "to_image", + "write_image", + "write_images", + "orca", + "json", + "to_json", + "from_json", + "read_json", + "write_json", + "templates", + "to_templated", + "to_html", + "write_html", + "renderers", + "show", + "base_renderers", + "full_figure_for_development", + "defaults", + "get_chrome", + ] +else: + __all__, __getattr__, __dir__ = relative_import( + __name__, + [".orca", ".kaleido", ".json", ".base_renderers"], + [ + "._kaleido.to_image", + "._kaleido.write_image", + "._kaleido.write_images", + "._kaleido.full_figure_for_development", + "._json.to_json", + "._json.from_json", + "._json.read_json", + "._json.write_json", + "._templates.templates", + "._templates.to_templated", + "._html.to_html", + "._html.write_html", + "._renderers.renderers", + "._renderers.show", + "._kaleido.defaults", + "._kaleido.get_chrome", + ], + ) + + # Set default template (for < 3.7 this is done in ploty/__init__.py) + from plotly.io import templates + + templates._default = "plotly" diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/__pycache__/__init__.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/plotly/io/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..42a5db44c8a5fe6f7950b38a81580af4a16b07cc Binary files /dev/null and b/.venv_haddock/lib/python3.12/site-packages/plotly/io/__pycache__/__init__.cpython-312.pyc differ diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/__pycache__/_base_renderers.cpython-312.pyc 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BaseHTTPRequestHandler, HTTPServer +except ImportError: + # Python 2.7 + from BaseHTTPServer import BaseHTTPRequestHandler, HTTPServer + + +class BaseRenderer(object): + """ + Base class for all renderers + """ + + def activate(self): + pass + + def __repr__(self): + try: + init_sig = inspect.signature(self.__init__) + init_args = list(init_sig.parameters.keys()) + except AttributeError: + # Python 2.7 + argspec = inspect.getargspec(self.__init__) + init_args = [a for a in argspec.args if a != "self"] + + return "{cls}({attrs})\n{doc}".format( + cls=self.__class__.__name__, + attrs=", ".join("{}={!r}".format(k, self.__dict__[k]) for k in init_args), + doc=self.__doc__, + ) + + def __hash__(self): + # Constructor args fully define uniqueness + return hash(repr(self)) + + +class MimetypeRenderer(BaseRenderer): + """ + Base class for all mime type renderers + """ + + def to_mimebundle(self, fig_dict): + raise NotImplementedError() + + +class JsonRenderer(MimetypeRenderer): + """ + Renderer to display figures as JSON hierarchies. This renderer is + compatible with JupyterLab and VSCode. + + mime type: 'application/json' + """ + + def to_mimebundle(self, fig_dict): + value = json.loads(to_json(fig_dict, validate=False, remove_uids=False)) + return {"application/json": value} + + +# Plotly mimetype +class PlotlyRenderer(MimetypeRenderer): + """ + Renderer to display figures using the plotly mime type. This renderer is + compatible with VSCode and nteract. + + mime type: 'application/vnd.plotly.v1+json' + """ + + def __init__(self, config=None): + self.config = dict(config) if config else {} + + def to_mimebundle(self, fig_dict): + config = _get_jconfig(self.config) + if config: + fig_dict["config"] = config + + json_compatible_fig_dict = json.loads( + to_json(fig_dict, validate=False, remove_uids=False) + ) + + return {"application/vnd.plotly.v1+json": json_compatible_fig_dict} + + +# Static Image +class ImageRenderer(MimetypeRenderer): + """ + Base class for all static image renderers + """ + + def __init__( + self, + mime_type, + b64_encode=False, + format=None, + width=None, + height=None, + scale=None, + engine="auto", + ): + self.mime_type = mime_type + self.b64_encode = b64_encode + self.format = format + self.width = width + self.height = height + self.scale = scale + self.engine = engine + + def to_mimebundle(self, fig_dict): + image_bytes = to_image( + fig_dict, + format=self.format, + width=self.width, + height=self.height, + scale=self.scale, + validate=False, + engine=self.engine, + ) + + if self.b64_encode: + image_str = base64.b64encode(image_bytes).decode("utf8") + else: + image_str = image_bytes.decode("utf8") + + return {self.mime_type: image_str} + + +class PngRenderer(ImageRenderer): + """ + Renderer to display figures as static PNG images. This renderer requires + either the kaleido package or the orca command-line utility and is broadly + compatible across IPython environments (classic Jupyter Notebook, JupyterLab, + QtConsole, VSCode, PyCharm, etc) and nbconvert targets (HTML, PDF, etc.). + + mime type: 'image/png' + """ + + def __init__(self, width=None, height=None, scale=None, engine=None): + super(PngRenderer, self).__init__( + mime_type="image/png", + b64_encode=True, + format="png", + width=width, + height=height, + scale=scale, + engine=engine, + ) + + +class SvgRenderer(ImageRenderer): + """ + Renderer to display figures as static SVG images. This renderer requires + either the kaleido package or the orca command-line utility and is broadly + compatible across IPython environments (classic Jupyter Notebook, JupyterLab, + QtConsole, VSCode, PyCharm, etc) and nbconvert targets (HTML, PDF, etc.). + + mime type: 'image/svg+xml' + """ + + def __init__(self, width=None, height=None, scale=None, engine=None): + super(SvgRenderer, self).__init__( + mime_type="image/svg+xml", + b64_encode=False, + format="svg", + width=width, + height=height, + scale=scale, + engine=engine, + ) + + +class JpegRenderer(ImageRenderer): + """ + Renderer to display figures as static JPEG images. This renderer requires + either the kaleido package or the orca command-line utility and is broadly + compatible across IPython environments (classic Jupyter Notebook, JupyterLab, + QtConsole, VSCode, PyCharm, etc) and nbconvert targets (HTML, PDF, etc.). + + mime type: 'image/jpeg' + """ + + def __init__(self, width=None, height=None, scale=None, engine=None): + super(JpegRenderer, self).__init__( + mime_type="image/jpeg", + b64_encode=True, + format="jpg", + width=width, + height=height, + scale=scale, + engine=engine, + ) + + +class PdfRenderer(ImageRenderer): + """ + Renderer to display figures as static PDF images. This renderer requires + either the kaleido package or the orca command-line utility and is compatible + with JupyterLab and the LaTeX-based nbconvert export to PDF. + + mime type: 'application/pdf' + """ + + def __init__(self, width=None, height=None, scale=None, engine=None): + super(PdfRenderer, self).__init__( + mime_type="application/pdf", + b64_encode=True, + format="pdf", + width=width, + height=height, + scale=scale, + engine=engine, + ) + + +# HTML +# Build script to set global PlotlyConfig object. This must execute before +# plotly.js is loaded. +_window_plotly_config = """\ +window.PlotlyConfig = {MathJaxConfig: 'local'};""" + +_mathjax_config = """\ +if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: "STIX-Web"}});}""" + + +class HtmlRenderer(MimetypeRenderer): + """ + Base class for all HTML mime type renderers + + mime type: 'text/html' + """ + + def __init__( + self, + connected=False, + full_html=False, + global_init=False, + config=None, + auto_play=False, + post_script=None, + animation_opts=None, + include_plotlyjs=True, + ): + self.config = dict(config) if config else {} + self.auto_play = auto_play + self.connected = connected + self.global_init = global_init + self.full_html = full_html + self.animation_opts = animation_opts + self.post_script = post_script + self.include_plotlyjs = "cdn" if self.connected else include_plotlyjs + + def activate(self): + if self.global_init: + if not ipython_display: + raise ValueError( + "The {cls} class requires ipython but it is not installed".format( + cls=self.__class__.__name__ + ) + ) + + if self.connected: + script = """\ + + + """.format( + win_config=_window_plotly_config, + mathjax_config=_mathjax_config, + plotly_cdn=plotly_cdn_url().rstrip(".js"), + ) + + else: + # If not connected then we embed a copy of the plotly.js + # library in the notebook + script = """\ + + + """.format( + script=get_plotlyjs(), + win_config=_window_plotly_config, + mathjax_config=_mathjax_config, + ) + + ipython_display.display_html(script, raw=True) + + def to_mimebundle(self, fig_dict): + from plotly.io import to_html + + include_mathjax = "cdn" + + # build post script + post_script = [ + """ +var gd = document.getElementById('{plot_id}'); +var x = new MutationObserver(function (mutations, observer) {{ + var display = window.getComputedStyle(gd).display; + if (!display || display === 'none') {{ + console.log([gd, 'removed!']); + Plotly.purge(gd); + observer.disconnect(); + }} +}}); + +// Listen for the removal of the full notebook cells +var notebookContainer = gd.closest('#notebook-container'); +if (notebookContainer) {{ + x.observe(notebookContainer, {childList: true}); +}} + +// Listen for the clearing of the current output cell +var outputEl = gd.closest('.output'); +if (outputEl) {{ + x.observe(outputEl, {childList: true}); +}} +""" + ] + + # Add user defined post script + if self.post_script: + if not isinstance(self.post_script, (list, tuple)): + post_script.append(self.post_script) + else: + post_script.extend(self.post_script) + + html = to_html( + fig_dict, + config=self.config, + auto_play=self.auto_play, + include_plotlyjs=self.include_plotlyjs, + include_mathjax=include_mathjax, + post_script=post_script, + full_html=self.full_html, + animation_opts=self.animation_opts, + default_width="100%", + default_height=525, + validate=False, + ) + + return {"text/html": html} + + +class NotebookRenderer(HtmlRenderer): + """ + Renderer to display interactive figures in the classic Jupyter Notebook. + This renderer is also useful for notebooks that will be converted to + HTML using nbconvert/nbviewer as it will produce standalone HTML files + that include interactive figures. + + This renderer automatically performs global notebook initialization when + activated. + + mime type: 'text/html' + """ + + def __init__( + self, + connected=False, + config=None, + auto_play=False, + post_script=None, + animation_opts=None, + include_plotlyjs=False, + ): + super(NotebookRenderer, self).__init__( + connected=connected, + full_html=False, + global_init=True, + config=config, + auto_play=auto_play, + post_script=post_script, + animation_opts=animation_opts, + include_plotlyjs=include_plotlyjs, + ) + + +class KaggleRenderer(HtmlRenderer): + """ + Renderer to display interactive figures in Kaggle Notebooks. + + Same as NotebookRenderer but with connected=True so that the plotly.js + bundle is loaded from a CDN rather than being embedded in the notebook. + + This renderer is enabled by default when running in a Kaggle notebook. + + mime type: 'text/html' + """ + + def __init__( + self, config=None, auto_play=False, post_script=None, animation_opts=None + ): + super(KaggleRenderer, self).__init__( + connected=True, + full_html=False, + global_init=True, + config=config, + auto_play=auto_play, + post_script=post_script, + animation_opts=animation_opts, + include_plotlyjs=False, + ) + + +class AzureRenderer(HtmlRenderer): + """ + Renderer to display interactive figures in Azure Notebooks. + + Same as NotebookRenderer but with connected=True so that the plotly.js + bundle is loaded from a CDN rather than being embedded in the notebook. + + This renderer is enabled by default when running in an Azure notebook. + + mime type: 'text/html' + """ + + def __init__( + self, config=None, auto_play=False, post_script=None, animation_opts=None + ): + super(AzureRenderer, self).__init__( + connected=True, + full_html=False, + global_init=True, + config=config, + auto_play=auto_play, + post_script=post_script, + animation_opts=animation_opts, + include_plotlyjs=False, + ) + + +class ColabRenderer(HtmlRenderer): + """ + Renderer to display interactive figures in Google Colab Notebooks. + + This renderer is enabled by default when running in a Colab notebook. + + mime type: 'text/html' + """ + + def __init__( + self, config=None, auto_play=False, post_script=None, animation_opts=None + ): + super(ColabRenderer, self).__init__( + connected=True, + full_html=True, + global_init=False, + config=config, + auto_play=auto_play, + post_script=post_script, + animation_opts=animation_opts, + ) + + +class IFrameRenderer(MimetypeRenderer): + """ + Renderer to display interactive figures using an IFrame. HTML + representations of Figures are saved to an `iframe_figures/` directory and + iframe HTML elements that reference these files are inserted into the + notebook. + + With this approach, neither plotly.js nor the figure data are embedded in + the notebook, so this is a good choice for notebooks that contain so many + large figures that basic operations (like saving and opening) become + very slow. + + Notebooks using this renderer will display properly when exported to HTML + as long as the `iframe_figures/` directory is placed in the same directory + as the exported html file. + + Note that the HTML files in `iframe_figures/` are numbered according to + the IPython cell execution count and so they will start being overwritten + each time the kernel is restarted. This directory may be deleted whenever + the kernel is restarted and it will be automatically recreated. + + mime type: 'text/html' + """ + + def __init__( + self, + config=None, + auto_play=False, + post_script=None, + animation_opts=None, + include_plotlyjs=True, + html_directory="iframe_figures", + ): + self.config = config + self.auto_play = auto_play + self.post_script = post_script + self.animation_opts = animation_opts + self.include_plotlyjs = include_plotlyjs + self.html_directory = html_directory + + def to_mimebundle(self, fig_dict): + from plotly.io import write_html + + # Make iframe size slightly larger than figure size to avoid + # having iframe have its own scroll bar. + iframe_buffer = 20 + layout = fig_dict.get("layout", {}) + + if layout.get("width", False): + iframe_width = str(layout["width"] + iframe_buffer) + "px" + else: + iframe_width = "100%" + + if layout.get("height", False): + iframe_height = layout["height"] + iframe_buffer + else: + iframe_height = str(525 + iframe_buffer) + "px" + + # Build filename using ipython cell number + filename = self.build_filename() + + # Make directory for + try: + os.makedirs(self.html_directory) + except OSError: + if not isdir(self.html_directory): + raise + + write_html( + fig_dict, + filename, + config=self.config, + auto_play=self.auto_play, + include_plotlyjs=self.include_plotlyjs, + include_mathjax="cdn", + auto_open=False, + post_script=self.post_script, + animation_opts=self.animation_opts, + default_width="100%", + default_height=525, + validate=False, + ) + + # Build IFrame + iframe_html = """\ + +""".format(width=iframe_width, height=iframe_height, src=self.build_url(filename)) + + return {"text/html": iframe_html} + + def build_filename(self): + ip = IPython.get_ipython() if IPython else None + try: + cell_number = list(ip.history_manager.get_tail(1))[0][1] + 1 if ip else 0 + except Exception: + cell_number = 0 + return "{dirname}/figure_{cell_number}.html".format( + dirname=self.html_directory, cell_number=cell_number + ) + + def build_url(self, filename): + return filename + + +class CoCalcRenderer(IFrameRenderer): + _render_count = 0 + + def build_filename(self): + filename = "{dirname}/figure_{render_count}.html".format( + dirname=self.html_directory, render_count=CoCalcRenderer._render_count + ) + + CoCalcRenderer._render_count += 1 + return filename + + def build_url(self, filename): + return "{filename}?fullscreen=kiosk".format(filename=filename) + + +class ExternalRenderer(BaseRenderer): + """ + Base class for external renderers. ExternalRenderer subclasses + do not display figures inline in a notebook environment, but render + figures by some external means (e.g. a separate browser tab). + + Unlike MimetypeRenderer subclasses, ExternalRenderer subclasses are not + invoked when a figure is asked to display itself in the notebook. + Instead, they are invoked when the plotly.io.show function is called + on a figure. + """ + + def render(self, fig): + raise NotImplementedError() + + +def open_html_in_browser(html, using=None, new=0, autoraise=True): + """ + Display html in a web browser without creating a temp file. + + Instantiates a trivial http server and uses the webbrowser module to + open a URL to retrieve html from that server. + + Parameters + ---------- + html: str + HTML string to display + using, new, autoraise: + See docstrings in webbrowser.get and webbrowser.open + """ + if isinstance(html, str): + html = html.encode("utf8") + + browser = None + + if using is None: + browser = webbrowser.get(None) + else: + if not isinstance(using, tuple): + using = (using,) + for browser_key in using: + try: + browser = webbrowser.get(browser_key) + if browser is not None: + break + except webbrowser.Error: + pass + + if browser is None: + raise ValueError("Can't locate a browser with key in " + str(using)) + + class OneShotRequestHandler(BaseHTTPRequestHandler): + def do_GET(self): + self.send_response(200) + self.send_header("Content-type", "text/html") + self.end_headers() + + bufferSize = 1024 * 1024 + for i in range(0, len(html), bufferSize): + self.wfile.write(html[i : i + bufferSize]) + + def log_message(self, format, *args): + # Silence stderr logging + pass + + server = HTTPServer(("127.0.0.1", 0), OneShotRequestHandler) + browser.open( + "http://127.0.0.1:%s" % server.server_port, new=new, autoraise=autoraise + ) + + server.handle_request() + + +class BrowserRenderer(ExternalRenderer): + """ + Renderer to display interactive figures in an external web browser. + This renderer will open a new browser window or tab when the + plotly.io.show function is called on a figure. + + This renderer has no ipython/jupyter dependencies and is a good choice + for use in environments that do not support the inline display of + interactive figures. + + mime type: 'text/html' + """ + + def __init__( + self, + config=None, + auto_play=False, + using=None, + new=0, + autoraise=True, + post_script=None, + animation_opts=None, + ): + self.config = config + self.auto_play = auto_play + self.using = using + self.new = new + self.autoraise = autoraise + self.post_script = post_script + self.animation_opts = animation_opts + + def render(self, fig_dict): + from plotly.io import to_html + + html = to_html( + fig_dict, + config=self.config, + auto_play=self.auto_play, + include_plotlyjs=True, + include_mathjax="cdn", + post_script=self.post_script, + full_html=True, + animation_opts=self.animation_opts, + default_width="100%", + default_height="100%", + validate=False, + ) + open_html_in_browser(html, self.using, self.new, self.autoraise) + + +class DatabricksRenderer(ExternalRenderer): + def __init__( + self, + config=None, + auto_play=False, + post_script=None, + animation_opts=None, + include_plotlyjs="cdn", + ): + self.config = config + self.auto_play = auto_play + self.post_script = post_script + self.animation_opts = animation_opts + self.include_plotlyjs = include_plotlyjs + self._displayHTML = None + + @property + def displayHTML(self): + import inspect + + if self._displayHTML is None: + for frame in inspect.getouterframes(inspect.currentframe()): + global_names = set(frame.frame.f_globals) + # Check for displayHTML plus a few others to reduce chance of a false + # hit. + if all(v in global_names for v in ["displayHTML", "display", "spark"]): + self._displayHTML = frame.frame.f_globals["displayHTML"] + break + + if self._displayHTML is None: + raise EnvironmentError( + """ +Unable to detect the Databricks displayHTML function. The 'databricks' renderer is only +supported when called from within the Databricks notebook environment.""" + ) + + return self._displayHTML + + def render(self, fig_dict): + from plotly.io import to_html + + html = to_html( + fig_dict, + config=self.config, + auto_play=self.auto_play, + include_plotlyjs=self.include_plotlyjs, + include_mathjax="cdn", + post_script=self.post_script, + full_html=True, + animation_opts=self.animation_opts, + default_width="100%", + default_height="100%", + validate=False, + ) + + # displayHTML is a Databricks notebook built-in function + self.displayHTML(html) + + +class SphinxGalleryHtmlRenderer(HtmlRenderer): + def __init__( + self, + connected=True, + config=None, + auto_play=False, + post_script=None, + animation_opts=None, + ): + super(SphinxGalleryHtmlRenderer, self).__init__( + connected=connected, + full_html=False, + global_init=False, + config=config, + auto_play=auto_play, + post_script=post_script, + animation_opts=animation_opts, + ) + + def to_mimebundle(self, fig_dict): + from plotly.io import to_html + + if self.connected: + include_plotlyjs = "cdn" + include_mathjax = "cdn" + else: + include_plotlyjs = True + include_mathjax = "cdn" + + html = to_html( + fig_dict, + config=self.config, + auto_play=self.auto_play, + include_plotlyjs=include_plotlyjs, + include_mathjax=include_mathjax, + full_html=self.full_html, + animation_opts=self.animation_opts, + default_width="100%", + default_height=525, + validate=False, + ) + + return {"text/html": html} + + +class SphinxGalleryOrcaRenderer(ExternalRenderer): + def render(self, fig_dict): + stack = inspect.stack() + # Name of script from which plot function was called is retrieved + try: + filename = stack[3].filename # let's hope this is robust... + except Exception: # python 2 + filename = stack[3][1] + filename_root, _ = os.path.splitext(filename) + filename_html = filename_root + ".html" + filename_png = filename_root + ".png" + figure = return_figure_from_figure_or_data(fig_dict, True) + _ = write_html(fig_dict, file=filename_html, include_plotlyjs="cdn") + try: + write_image(figure, filename_png) + except (ValueError, ImportError): + raise ImportError( + "orca and psutil are required to use the `sphinx-gallery-orca` renderer. " + "See https://plotly.com/python/static-image-export/ for instructions on " + "how to install orca. Alternatively, you can use the `sphinx-gallery` " + "renderer (note that png thumbnails can only be generated with " + "the `sphinx-gallery-orca` renderer)." + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/_defaults.py b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_defaults.py new file mode 100644 index 0000000000000000000000000000000000000000..c36530c342d61468dd11beae1c5515d994af8141 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_defaults.py @@ -0,0 +1,19 @@ +# Default settings for image generation + + +class _Defaults(object): + """ + Class to store default settings for image generation. + """ + + def __init__(self): + self.default_format = "png" + self.default_width = 700 + self.default_height = 500 + self.default_scale = 1 + self.mathjax = None + self.topojson = None + self.plotlyjs = None + + +defaults = _Defaults() diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/_html.py b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_html.py new file mode 100644 index 0000000000000000000000000000000000000000..3e7b89c7d2ff2f847c81f41cda250cedfb8313db --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_html.py @@ -0,0 +1,517 @@ +import uuid +from pathlib import Path +import webbrowser +import hashlib +import base64 + +from _plotly_utils.optional_imports import get_module +from plotly.io._utils import validate_coerce_fig_to_dict, plotly_cdn_url +from plotly.offline.offline import _get_jconfig, get_plotlyjs + +_json = get_module("json") + + +def _generate_sri_hash(content): + """Generate SHA256 hash for SRI (Subresource Integrity)""" + if isinstance(content, str): + content = content.encode("utf-8") + sha256_hash = hashlib.sha256(content).digest() + return "sha256-" + base64.b64encode(sha256_hash).decode("utf-8") + + +# Build script to set global PlotlyConfig object. This must execute before +# plotly.js is loaded. +_window_plotly_config = """\ +""" + +_mathjax_config = """\ +""" + + +def to_html( + fig, + config=None, + auto_play=True, + include_plotlyjs=True, + include_mathjax=False, + post_script=None, + full_html=True, + animation_opts=None, + default_width="100%", + default_height="100%", + validate=True, + div_id=None, +): + """ + Convert a figure to an HTML string representation. + + Parameters + ---------- + fig: + Figure object or dict representing a figure + config: dict or None (default None) + Plotly.js figure config options + auto_play: bool (default=True) + Whether to automatically start the animation sequence on page load + if the figure contains frames. Has no effect if the figure does not + contain frames. + include_plotlyjs: bool or string (default True) + Specifies how the plotly.js library is included/loaded in the output + div string. + + If True, a script tag containing the plotly.js source code (~3MB) + is included in the output. HTML files generated with this option are + fully self-contained and can be used offline. + + If 'cdn', a script tag that references the plotly.js CDN is included + in the output. The url used is versioned to match the bundled plotly.js. + HTML files generated with this option are about 3MB smaller than those + generated with include_plotlyjs=True, but they require an active + internet connection in order to load the plotly.js library. + + If 'directory', a script tag is included that references an external + plotly.min.js bundle that is assumed to reside in the same + directory as the HTML file. + + If a string that ends in '.js', a script tag is included that + references the specified path. This approach can be used to point + the resulting HTML file to an alternative CDN or local bundle. + + If False, no script tag referencing plotly.js is included. This is + useful when the resulting div string will be placed inside an HTML + document that already loads plotly.js. This option is not advised + when full_html=True as it will result in a non-functional html file. + include_mathjax: bool or string (default False) + Specifies how the MathJax.js library is included in the output html + div string. MathJax is required in order to display labels + with LaTeX typesetting. + + If False, no script tag referencing MathJax.js will be included in the + output. + + If 'cdn', a script tag that references a MathJax CDN location will be + included in the output. HTML div strings generated with this option + will be able to display LaTeX typesetting as long as internet access + is available. + + If a string that ends in '.js', a script tag is included that + references the specified path. This approach can be used to point the + resulting HTML div string to an alternative CDN. + post_script: str or list or None (default None) + JavaScript snippet(s) to be included in the resulting div just after + plot creation. The string(s) may include '{plot_id}' placeholders + that will then be replaced by the `id` of the div element that the + plotly.js figure is associated with. One application for this script + is to install custom plotly.js event handlers. + full_html: bool (default True) + If True, produce a string containing a complete HTML document + starting with an tag. If False, produce a string containing + a single
element. + animation_opts: dict or None (default None) + dict of custom animation parameters to be passed to the function + Plotly.animate in Plotly.js. See + https://github.com/plotly/plotly.js/blob/master/src/plots/animation_attributes.js + for available options. Has no effect if the figure does not contain + frames, or auto_play is False. + default_width, default_height: number or str (default '100%') + The default figure width/height to use if the provided figure does not + specify its own layout.width/layout.height property. May be + specified in pixels as an integer (e.g. 500), or as a css width style + string (e.g. '500px', '100%'). + validate: bool (default True) + True if the figure should be validated before being converted to + JSON, False otherwise. + div_id: str (default None) + If provided, this is the value of the id attribute of the div tag. If None, the + id attribute is a UUID. + + Returns + ------- + str + Representation of figure as an HTML div string + """ + from plotly.io.json import to_json_plotly + + # ## Validate figure ## + fig_dict = validate_coerce_fig_to_dict(fig, validate) + + # ## Generate div id ## + plotdivid = div_id or str(uuid.uuid4()) + + # ## Serialize figure ## + jdata = to_json_plotly(fig_dict.get("data", [])) + jlayout = to_json_plotly(fig_dict.get("layout", {})) + + if fig_dict.get("frames", None): + jframes = to_json_plotly(fig_dict.get("frames", [])) + else: + jframes = None + + # ## Serialize figure config ## + config = _get_jconfig(config) + + # Set responsive + config.setdefault("responsive", True) + + # Get div width/height + layout_dict = fig_dict.get("layout", {}) + template_dict = fig_dict.get("layout", {}).get("template", {}).get("layout", {}) + + div_width = layout_dict.get("width", template_dict.get("width", default_width)) + div_height = layout_dict.get("height", template_dict.get("height", default_height)) + + # Add 'px' suffix to numeric widths + try: + float(div_width) + except (ValueError, TypeError): + pass + else: + div_width = str(div_width) + "px" + + try: + float(div_height) + except (ValueError, TypeError): + pass + else: + div_height = str(div_height) + "px" + + # ## Get platform URL ## + if config.get("showLink", False) or config.get("showSendToCloud", False): + # Figure is going to include a Chart Studio link or send-to-cloud button, + # So we need to configure the PLOTLYENV.BASE_URL property + base_url_line = """ + window.PLOTLYENV.BASE_URL='{plotly_platform_url}';\ +""".format(plotly_platform_url=config.get("plotlyServerURL", "https://plot.ly")) + else: + # Figure is not going to include a Chart Studio link or send-to-cloud button, + # In this case we don't want https://plot.ly to show up anywhere in the HTML + # output + config.pop("plotlyServerURL", None) + config.pop("linkText", None) + config.pop("showLink", None) + base_url_line = "" + + # ## Build script body ## + # This is the part that actually calls Plotly.js + + # build post script snippet(s) + then_post_script = "" + if post_script: + if not isinstance(post_script, (list, tuple)): + post_script = [post_script] + for ps in post_script: + then_post_script += """.then(function(){{ + {post_script} + }})""".format(post_script=ps.replace("{plot_id}", plotdivid)) + + then_addframes = "" + then_animate = "" + if jframes: + then_addframes = """.then(function(){{ + Plotly.addFrames('{id}', {frames}); + }})""".format(id=plotdivid, frames=jframes) + + if auto_play: + if animation_opts: + animation_opts_arg = ", " + _json.dumps(animation_opts) + else: + animation_opts_arg = "" + then_animate = """.then(function(){{ + Plotly.animate('{id}', null{animation_opts}); + }})""".format(id=plotdivid, animation_opts=animation_opts_arg) + + # Serialize config dict to JSON + jconfig = _json.dumps(config) + + script = """\ + if (document.getElementById("{id}")) {{\ + Plotly.newPlot(\ + "{id}",\ + {data},\ + {layout},\ + {config}\ + ){then_addframes}{then_animate}{then_post_script}\ + }}""".format( + id=plotdivid, + data=jdata, + layout=jlayout, + config=jconfig, + then_addframes=then_addframes, + then_animate=then_animate, + then_post_script=then_post_script, + ) + + # ## Handle loading/initializing plotly.js ## + include_plotlyjs_orig = include_plotlyjs + if isinstance(include_plotlyjs, str): + include_plotlyjs = include_plotlyjs.lower() + + # Init and load + load_plotlyjs = "" + + if include_plotlyjs == "cdn": + # Generate SRI hash from the bundled plotly.js content + plotlyjs_content = get_plotlyjs() + sri_hash = _generate_sri_hash(plotlyjs_content) + + load_plotlyjs = """\ + {win_config} + \ + """.format( + win_config=_window_plotly_config, + cdn_url=plotly_cdn_url(), + integrity=sri_hash, + ) + + elif include_plotlyjs == "directory": + load_plotlyjs = """\ + {win_config} + \ + """.format(win_config=_window_plotly_config) + + elif isinstance(include_plotlyjs, str) and include_plotlyjs.endswith(".js"): + load_plotlyjs = """\ + {win_config} + \ + """.format(win_config=_window_plotly_config, url=include_plotlyjs_orig) + + elif include_plotlyjs: + load_plotlyjs = """\ + {win_config} + \ + """.format(win_config=_window_plotly_config, plotlyjs=get_plotlyjs()) + + # ## Handle loading/initializing MathJax ## + include_mathjax_orig = include_mathjax + if isinstance(include_mathjax, str): + include_mathjax = include_mathjax.lower() + + mathjax_template = """\ + """ + + if include_mathjax == "cdn": + mathjax_script = ( + mathjax_template.format( + url=("https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js") + ) + + _mathjax_config + ) + + elif isinstance(include_mathjax, str) and include_mathjax.endswith(".js"): + mathjax_script = ( + mathjax_template.format(url=include_mathjax_orig) + _mathjax_config + ) + elif not include_mathjax: + mathjax_script = "" + else: + raise ValueError( + """\ +Invalid value of type {typ} received as the include_mathjax argument + Received value: {val} + +include_mathjax may be specified as False, 'cdn', or a string ending with '.js' + """.format(typ=type(include_mathjax), val=repr(include_mathjax)) + ) + + plotly_html_div = """\ +
\ + {mathjax_script}\ + {load_plotlyjs}\ +
\ + \ +
""".format( + mathjax_script=mathjax_script, + load_plotlyjs=load_plotlyjs, + id=plotdivid, + width=div_width, + height=div_height, + base_url_line=base_url_line, + script=script, + ).strip() + + if full_html: + return """\ + + + + {div} + +""".format(div=plotly_html_div) + else: + return plotly_html_div + + +def write_html( + fig, + file, + config=None, + auto_play=True, + include_plotlyjs=True, + include_mathjax=False, + post_script=None, + full_html=True, + animation_opts=None, + validate=True, + default_width="100%", + default_height="100%", + auto_open=False, + div_id=None, +): + """ + Write a figure to an HTML file representation + + Parameters + ---------- + fig: + Figure object or dict representing a figure + file: str or writeable + A string representing a local file path or a writeable object + (e.g. a pathlib.Path object or an open file descriptor) + config: dict or None (default None) + Plotly.js figure config options + auto_play: bool (default=True) + Whether to automatically start the animation sequence on page load + if the figure contains frames. Has no effect if the figure does not + contain frames. + include_plotlyjs: bool or string (default True) + Specifies how the plotly.js library is included/loaded in the output + div string. + + If True, a script tag containing the plotly.js source code (~3MB) + is included in the output. HTML files generated with this option are + fully self-contained and can be used offline. + + If 'cdn', a script tag that references the plotly.js CDN is included + in the output. The url used is versioned to match the bundled plotly.js. + HTML files generated with this option are about 3MB smaller than those + generated with include_plotlyjs=True, but they require an active + internet connection in order to load the plotly.js library. + + If 'directory', a script tag is included that references an external + plotly.min.js bundle that is assumed to reside in the same + directory as the HTML file. If `file` is a string to a local file + path and `full_html` is True, then the plotly.min.js bundle is copied + into the directory of the resulting HTML file. If a file named + plotly.min.js already exists in the output directory then this file + is left unmodified and no copy is performed. HTML files generated + with this option can be used offline, but they require a copy of + the plotly.min.js bundle in the same directory. This option is + useful when many figures will be saved as HTML files in the same + directory because the plotly.js source code will be included only + once per output directory, rather than once per output file. + + If a string that ends in '.js', a script tag is included that + references the specified path. This approach can be used to point + the resulting HTML file to an alternative CDN or local bundle. + + If False, no script tag referencing plotly.js is included. This is + useful when the resulting div string will be placed inside an HTML + document that already loads plotly.js. This option is not advised + when full_html=True as it will result in a non-functional html file. + + include_mathjax: bool or string (default False) + Specifies how the MathJax.js library is included in the output html + div string. MathJax is required in order to display labels + with LaTeX typesetting. + + If False, no script tag referencing MathJax.js will be included in the + output. + + If 'cdn', a script tag that references a MathJax CDN location will be + included in the output. HTML div strings generated with this option + will be able to display LaTeX typesetting as long as internet access + is available. + + If a string that ends in '.js', a script tag is included that + references the specified path. This approach can be used to point the + resulting HTML div string to an alternative CDN. + post_script: str or list or None (default None) + JavaScript snippet(s) to be included in the resulting div just after + plot creation. The string(s) may include '{plot_id}' placeholders + that will then be replaced by the `id` of the div element that the + plotly.js figure is associated with. One application for this script + is to install custom plotly.js event handlers. + full_html: bool (default True) + If True, produce a string containing a complete HTML document + starting with an tag. If False, produce a string containing + a single
element. + animation_opts: dict or None (default None) + dict of custom animation parameters to be passed to the function + Plotly.animate in Plotly.js. See + https://github.com/plotly/plotly.js/blob/master/src/plots/animation_attributes.js + for available options. Has no effect if the figure does not contain + frames, or auto_play is False. + default_width, default_height: number or str (default '100%') + The default figure width/height to use if the provided figure does not + specify its own layout.width/layout.height property. May be + specified in pixels as an integer (e.g. 500), or as a css width style + string (e.g. '500px', '100%'). + validate: bool (default True) + True if the figure should be validated before being converted to + JSON, False otherwise. + auto_open: bool (default True) + If True, open the saved file in a web browser after saving. + This argument only applies if `full_html` is True. + div_id: str (default None) + If provided, this is the value of the id attribute of the div tag. If None, the + id attribute is a UUID. + + Returns + ------- + None + """ + + # Build HTML string + html_str = to_html( + fig, + config=config, + auto_play=auto_play, + include_plotlyjs=include_plotlyjs, + include_mathjax=include_mathjax, + post_script=post_script, + full_html=full_html, + animation_opts=animation_opts, + default_width=default_width, + default_height=default_height, + validate=validate, + div_id=div_id, + ) + + # Check if file is a string + if isinstance(file, str): + # Use the standard pathlib constructor to make a pathlib object. + path = Path(file) + elif isinstance(file, Path): # PurePath is the most general pathlib object. + # `file` is already a pathlib object. + path = file + else: + # We could not make a pathlib object out of file. Either `file` is an open file + # descriptor with a `write()` method or it's an invalid object. + path = None + + # Write HTML string + if path is not None: + # To use a different file encoding, pass a file descriptor + path.write_text(html_str, "utf-8") + else: + file.write(html_str) + + # Check if we should copy plotly.min.js to output directory + if path is not None and full_html and include_plotlyjs == "directory": + bundle_path = path.parent / "plotly.min.js" + + if not bundle_path.exists(): + bundle_path.write_text(get_plotlyjs(), encoding="utf-8") + + # Handle auto_open + if path is not None and full_html and auto_open: + url = path.absolute().as_uri() + webbrowser.open(url) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/_json.py b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_json.py new file mode 100644 index 0000000000000000000000000000000000000000..0e741711f4ff770fded7f10f60fc9694c9925750 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_json.py @@ -0,0 +1,598 @@ +import json +import decimal +import datetime +import warnings +from pathlib import Path + +from plotly.io._utils import validate_coerce_fig_to_dict, validate_coerce_output_type +from _plotly_utils.optional_imports import get_module +from _plotly_utils.basevalidators import ImageUriValidator + + +# Orca configuration class +# ------------------------ +class JsonConfig(object): + _valid_engines = ("json", "orjson", "auto") + + def __init__(self): + self._default_engine = "auto" + + @property + def default_engine(self): + return self._default_engine + + @default_engine.setter + def default_engine(self, val): + if val not in JsonConfig._valid_engines: + raise ValueError( + "Supported JSON engines include {valid}\n Received {val}".format( + valid=JsonConfig._valid_engines, val=val + ) + ) + + if val == "orjson": + self.validate_orjson() + + self._default_engine = val + + @classmethod + def validate_orjson(cls): + orjson = get_module("orjson") + if orjson is None: + raise ValueError("The orjson engine requires the orjson package") + + +config = JsonConfig() + + +def coerce_to_strict(const): + """ + This is used to ultimately *encode* into strict JSON, see `encode` + + """ + # before python 2.7, 'true', 'false', 'null', were include here. + if const in ("Infinity", "-Infinity", "NaN"): + return None + else: + return const + + +_swap_json = ( + ("<", "\\u003c"), + (">", "\\u003e"), + ("/", "\\u002f"), +) +_swap_orjson = _swap_json + ( + ("\u2028", "\\u2028"), + ("\u2029", "\\u2029"), +) + + +def _safe(json_str, _swap): + out = json_str + for unsafe_char, safe_char in _swap: + if unsafe_char in out: + out = out.replace(unsafe_char, safe_char) + return out + + +def to_json_plotly(plotly_object, pretty=False, engine=None): + """ + Convert a plotly/Dash object to a JSON string representation + + Parameters + ---------- + plotly_object: + A plotly/Dash object represented as a dict, graph_object, or Dash component + + pretty: bool (default False) + True if JSON representation should be pretty-printed, False if + representation should be as compact as possible. + + engine: str (default None) + The JSON encoding engine to use. One of: + - "json" for an engine based on the built-in Python json module + - "orjson" for a faster engine that requires the orjson package + - "auto" for the "orjson" engine if available, otherwise "json" + If not specified, the default engine is set to the current value of + plotly.io.json.config.default_engine. + + Returns + ------- + str + Representation of input object as a JSON string + + See Also + -------- + to_json : Convert a plotly Figure to JSON with validation + """ + orjson = get_module("orjson", should_load=True) + + # Determine json engine + if engine is None: + engine = config.default_engine + + if engine == "auto": + if orjson is not None: + engine = "orjson" + else: + engine = "json" + elif engine not in ["orjson", "json"]: + raise ValueError("Invalid json engine: %s" % engine) + + modules = { + "sage_all": get_module("sage.all", should_load=False), + "np": get_module("numpy", should_load=False), + "pd": get_module("pandas", should_load=False), + "image": get_module("PIL.Image", should_load=False), + } + + # Dump to a JSON string and return + # -------------------------------- + if engine == "json": + opts = {} + if pretty: + opts["indent"] = 2 + else: + # Remove all whitespace + opts["separators"] = (",", ":") + + from _plotly_utils.utils import PlotlyJSONEncoder + + return _safe( + json.dumps(plotly_object, cls=PlotlyJSONEncoder, **opts), _swap_json + ) + elif engine == "orjson": + JsonConfig.validate_orjson() + opts = orjson.OPT_NON_STR_KEYS | orjson.OPT_SERIALIZE_NUMPY + + if pretty: + opts |= orjson.OPT_INDENT_2 + + # Plotly + try: + plotly_object = plotly_object.to_plotly_json() + except AttributeError: + pass + + # Try without cleaning + try: + return _safe( + orjson.dumps(plotly_object, option=opts).decode("utf8"), _swap_orjson + ) + except TypeError: + pass + + cleaned = clean_to_json_compatible( + plotly_object, + numpy_allowed=True, + datetime_allowed=True, + modules=modules, + ) + return _safe(orjson.dumps(cleaned, option=opts).decode("utf8"), _swap_orjson) + + +def to_json(fig, validate=True, pretty=False, remove_uids=True, engine=None): + """ + Convert a figure to a JSON string representation + + Parameters + ---------- + fig: + Figure object or dict representing a figure + + validate: bool (default True) + True if the figure should be validated before being converted to + JSON, False otherwise. + + pretty: bool (default False) + True if JSON representation should be pretty-printed, False if + representation should be as compact as possible. + + remove_uids: bool (default True) + True if trace UIDs should be omitted from the JSON representation + + engine: str (default None) + The JSON encoding engine to use. One of: + - "json" for an engine based on the built-in Python json module + - "orjson" for a faster engine that requires the orjson package + - "auto" for the "orjson" engine if available, otherwise "json" + If not specified, the default engine is set to the current value of + plotly.io.json.config.default_engine. + + Returns + ------- + str + Representation of figure as a JSON string + + See Also + -------- + to_json_plotly : Convert an arbitrary plotly graph_object or Dash component to JSON + """ + # Validate figure + # --------------- + fig_dict = validate_coerce_fig_to_dict(fig, validate) + + # Remove trace uid + # ---------------- + if remove_uids: + for trace in fig_dict.get("data", []): + trace.pop("uid", None) + + return to_json_plotly(fig_dict, pretty=pretty, engine=engine) + + +def write_json(fig, file, validate=True, pretty=False, remove_uids=True, engine=None): + """ + Convert a figure to JSON and write it to a file or writeable + object. + + Note: A figure converted to JSON with one version of Plotly.py may not be compatible with another version. + + Parameters + ---------- + fig: + Figure object or dict representing a figure + + file: str or writeable + A string representing a local file path or a writeable object + (e.g. a pathlib.Path object or an open file descriptor) + + pretty: bool (default False) + True if JSON representation should be pretty-printed, False if + representation should be as compact as possible. + + remove_uids: bool (default True) + True if trace UIDs should be omitted from the JSON representation + + engine: str (default None) + The JSON encoding engine to use. One of: + - "json" for an engine based on the built-in Python json module + - "orjson" for a faster engine that requires the orjson package + - "auto" for the "orjson" engine if available, otherwise "json" + If not specified, the default engine is set to the current value of + plotly.io.json.config.default_engine. + Returns + ------- + None + """ + + # Get JSON string + # --------------- + # Pass through validate argument and let to_json handle validation logic + json_str = to_json( + fig, validate=validate, pretty=pretty, remove_uids=remove_uids, engine=engine + ) + + # Try to cast `file` as a pathlib object `path`. + # ---------------------------------------------- + if isinstance(file, str): + # Use the standard Path constructor to make a pathlib object. + path = Path(file) + elif isinstance(file, Path): + # `file` is already a Path object. + path = file + else: + # We could not make a Path object out of file. Either `file` is an open file + # descriptor with a `write()` method or it's an invalid object. + path = None + + # Open file + # --------- + if path is None: + # We previously failed to make sense of `file` as a pathlib object. + # Attempt to write to `file` as an open file descriptor. + try: + file.write(json_str) + return + except AttributeError: + pass + raise ValueError( + """ +The 'file' argument '{file}' is not a string, pathlib.Path object, or file descriptor. +""".format(file=file) + ) + else: + # We previously succeeded in interpreting `file` as a pathlib object. + # Now we can use `write_bytes()`. + path.write_text(json_str) + + +def from_json_plotly(value, engine=None): + """ + Parse JSON string using the specified JSON engine + + Parameters + ---------- + value: str or bytes + A JSON string or bytes object + + engine: str (default None) + The JSON decoding engine to use. One of: + - if "json", parse JSON using built in json module + - if "orjson", parse using the faster orjson module, requires the orjson + package + - if "auto" use orjson module if available, otherwise use the json module + + If not specified, the default engine is set to the current value of + plotly.io.json.config.default_engine. + + Returns + ------- + dict + + See Also + -------- + from_json_plotly : Parse JSON with plotly conventions into a dict + """ + orjson = get_module("orjson", should_load=True) + + # Validate value + # -------------- + if not isinstance(value, (str, bytes)): + raise ValueError( + """ +from_json_plotly requires a string or bytes argument but received value of type {typ} + Received value: {value}""".format(typ=type(value), value=value) + ) + + # Determine json engine + if engine is None: + engine = config.default_engine + + if engine == "auto": + if orjson is not None: + engine = "orjson" + else: + engine = "json" + elif engine not in ["orjson", "json"]: + raise ValueError("Invalid json engine: %s" % engine) + + if engine == "orjson": + JsonConfig.validate_orjson() + # orjson handles bytes input natively + value_dict = orjson.loads(value) + else: + # decode bytes to str for built-in json module + if isinstance(value, bytes): + value = value.decode("utf-8") + value_dict = json.loads(value) + + return value_dict + + +def from_json(value, output_type="Figure", skip_invalid=False, engine=None): + """ + Construct a figure from a JSON string + + Parameters + ---------- + value: str or bytes + String or bytes object containing the JSON representation of a figure + + output_type: type or str (default 'Figure') + The output figure type or type name. + One of: graph_objs.Figure, 'Figure', graph_objs.FigureWidget, 'FigureWidget' + + skip_invalid: bool (default False) + False if invalid figure properties should result in an exception. + True if invalid figure properties should be silently ignored. + + engine: str (default None) + The JSON decoding engine to use. One of: + - if "json", parse JSON using built in json module + - if "orjson", parse using the faster orjson module, requires the orjson + package + - if "auto" use orjson module if available, otherwise use the json module + + If not specified, the default engine is set to the current value of + plotly.io.json.config.default_engine. + + Raises + ------ + ValueError + if value is not a string, or if skip_invalid=False and value contains + invalid figure properties + + Returns + ------- + Figure or FigureWidget + """ + + # Decode JSON + # ----------- + fig_dict = from_json_plotly(value, engine=engine) + + # Validate coerce output type + # --------------------------- + cls = validate_coerce_output_type(output_type) + + # Create and return figure + # ------------------------ + fig = cls(fig_dict, skip_invalid=skip_invalid) + return fig + + +def read_json(file, output_type="Figure", skip_invalid=False, engine=None): + """ + Construct a figure from the JSON contents of a local file or readable + Python object. + + Note: A figure converted to JSON with one version of Plotly.py may not be compatible with another version. + + Parameters + ---------- + file: str or readable + A string containing the path to a local file or a read-able Python + object (e.g. a pathlib.Path object or an open file descriptor) + + output_type: type or str (default 'Figure') + The output figure type or type name. + One of: graph_objs.Figure, 'Figure', graph_objs.FigureWidget, 'FigureWidget' + + skip_invalid: bool (default False) + False if invalid figure properties should result in an exception. + True if invalid figure properties should be silently ignored. + + engine: str (default None) + The JSON decoding engine to use. One of: + - if "json", parse JSON using built in json module + - if "orjson", parse using the faster orjson module, requires the orjson + package + - if "auto" use orjson module if available, otherwise use the json module + + If not specified, the default engine is set to the current value of + plotly.io.json.config.default_engine. + + Returns + ------- + Figure or FigureWidget + """ + + # Try to cast `file` as a pathlib object `path`. + if isinstance(file, str): + # Use the standard Path constructor to make a pathlib object. + path = Path(file) + elif isinstance(file, Path): + # `file` is already a Path object. + path = file + else: + # We could not make a Path object out of file. Either `file` is an open file + # descriptor with a `write()` method or it's an invalid object. + path = None + + # Read file contents into JSON string + # ----------------------------------- + if path is not None: + json_str = path.read_text() + else: + json_str = file.read() + + # Construct and return figure + # --------------------------- + return from_json( + json_str, skip_invalid=skip_invalid, output_type=output_type, engine=engine + ) + + +def clean_to_json_compatible(obj, **kwargs): + # Try handling value as a scalar value that we have a conversion for. + # Return immediately if we know we've hit a primitive value + + # Bail out fast for simple scalar types + if isinstance(obj, (int, float, str)): + return obj + + if isinstance(obj, dict): + return {k: clean_to_json_compatible(v, **kwargs) for k, v in obj.items()} + elif isinstance(obj, (list, tuple)): + if obj: + # Must process list recursively even though it may be slow + return [clean_to_json_compatible(v, **kwargs) for v in obj] + + # unpack kwargs + numpy_allowed = kwargs.get("numpy_allowed", False) + datetime_allowed = kwargs.get("datetime_allowed", False) + + modules = kwargs.get("modules", {}) + sage_all = modules["sage_all"] + np = modules["np"] + pd = modules["pd"] + image = modules["image"] + + # Sage + if sage_all is not None: + if obj in sage_all.RR: + return float(obj) + elif obj in sage_all.ZZ: + return int(obj) + + # numpy + if np is not None: + if obj is np.ma.core.masked: + return float("nan") + elif isinstance(obj, np.ndarray): + if numpy_allowed and obj.dtype.kind in ("b", "i", "u", "f"): + return np.ascontiguousarray(obj) + elif obj.dtype.kind == "M": + # datetime64 array + return np.datetime_as_string(obj).tolist() + elif obj.dtype.kind == "U": + return obj.tolist() + elif obj.dtype.kind == "O": + # Treat object array as a lists, continue processing + obj = obj.tolist() + elif isinstance(obj, np.datetime64): + return str(obj) + + # pandas + if pd is not None: + if obj is pd.NaT or obj is pd.NA: + return None + elif isinstance(obj, (pd.Series, pd.DatetimeIndex)): + if numpy_allowed and obj.dtype.kind in ("b", "i", "u", "f"): + return np.ascontiguousarray(obj.values) + elif obj.dtype.kind == "M": + if isinstance(obj, pd.Series): + with warnings.catch_warnings(): + warnings.simplefilter("ignore", FutureWarning) + # Series.dt.to_pydatetime will return Index[object] + # https://github.com/pandas-dev/pandas/pull/52459 + dt_values = np.array(obj.dt.to_pydatetime()).tolist() + else: # DatetimeIndex + dt_values = obj.to_pydatetime().tolist() + + if not datetime_allowed: + # Note: We don't need to handle dropping timezones here because + # numpy's datetime64 doesn't support them and pandas's tz_localize + # above drops them. + for i in range(len(dt_values)): + dt_values[i] = dt_values[i].isoformat() + + return dt_values + + # datetime and date + try: + # Need to drop timezone for scalar datetimes. Don't need to convert + # to string since engine can do that + obj = obj.to_pydatetime() + except (TypeError, AttributeError): + pass + + if not datetime_allowed: + try: + return obj.isoformat() + except (TypeError, AttributeError): + pass + elif isinstance(obj, datetime.datetime): + return obj + + # Try .tolist() convertible, do not recurse inside + try: + return obj.tolist() + except AttributeError: + pass + + # Do best we can with decimal + if isinstance(obj, decimal.Decimal): + return float(obj) + + # PIL + if image is not None and isinstance(obj, image.Image): + return ImageUriValidator.pil_image_to_uri(obj) + + # Plotly + try: + obj = obj.to_plotly_json() + except AttributeError: + pass + + # Recurse into lists and dictionaries + if isinstance(obj, dict): + return {k: clean_to_json_compatible(v, **kwargs) for k, v in obj.items()} + elif isinstance(obj, (list, tuple)): + if obj: + # Must process list recursively even though it may be slow + return [clean_to_json_compatible(v, **kwargs) for v in obj] + + return obj diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/_kaleido.py b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_kaleido.py new file mode 100644 index 0000000000000000000000000000000000000000..29fa845d7628fd4f40fe867edf816983a81babf0 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_kaleido.py @@ -0,0 +1,918 @@ +import os +import json +from pathlib import Path +from typing import Union, List +import importlib.metadata as importlib_metadata +from packaging.version import Version +import warnings + +import plotly +from plotly.io._utils import validate_coerce_fig_to_dict, broadcast_args_to_dicts +from plotly.io._defaults import defaults + +ENGINE_SUPPORT_TIMELINE = "September 2025" +ENABLE_KALEIDO_V0_DEPRECATION_WARNINGS = True + +PLOTLY_GET_CHROME_ERROR_MSG = """ + +Kaleido requires Google Chrome to be installed. + +Either download and install Chrome yourself following Google's instructions for your operating system, +or install it from your terminal by running: + + $ plotly_get_chrome + +""" + +KALEIDO_DEPRECATION_MSG = f""" +Support for Kaleido versions less than 1.0.0 is deprecated and will be removed after {ENGINE_SUPPORT_TIMELINE}. +Please upgrade Kaleido to version 1.0.0 or greater (`pip install 'kaleido>=1.0.0'` or `pip install 'plotly[kaleido]'`). +""" +ORCA_DEPRECATION_MSG = f""" +Support for the Orca engine is deprecated and will be removed after {ENGINE_SUPPORT_TIMELINE}. +Please install Kaleido (`pip install 'kaleido>=1.0.0'` or `pip install 'plotly[kaleido]'`) to use the Kaleido engine. +""" +ENGINE_PARAM_DEPRECATION_MSG = f""" +Support for the 'engine' argument is deprecated and will be removed after {ENGINE_SUPPORT_TIMELINE}. +Kaleido will be the only supported engine at that time. +""" + +_KALEIDO_AVAILABLE = None +_KALEIDO_MAJOR = None + + +def kaleido_scope_default_warning_func(x): + return f""" +Use of plotly.io.kaleido.scope.{x} is deprecated and support will be removed after {ENGINE_SUPPORT_TIMELINE}. +Please use plotly.io.defaults.{x} instead. +""" + + +def bad_attribute_error_msg_func(x): + return f""" +Attribute plotly.io.defaults.{x} is not valid. +Also, use of plotly.io.kaleido.scope.* is deprecated and support will be removed after {ENGINE_SUPPORT_TIMELINE}. +Please use plotly.io.defaults.* instead. +""" + + +def kaleido_available() -> bool: + """ + Returns True if any version of Kaleido is installed, otherwise False. + """ + global _KALEIDO_AVAILABLE + global _KALEIDO_MAJOR + if _KALEIDO_AVAILABLE is not None: + return _KALEIDO_AVAILABLE + try: + import kaleido # noqa: F401 + + _KALEIDO_AVAILABLE = True + except ImportError: + _KALEIDO_AVAILABLE = False + return _KALEIDO_AVAILABLE + + +def kaleido_major() -> int: + """ + Returns the major version number of Kaleido if it is installed, + otherwise raises a ValueError. + """ + global _KALEIDO_MAJOR + if _KALEIDO_MAJOR is not None: + return _KALEIDO_MAJOR + if not kaleido_available(): + raise ValueError("Kaleido is not installed.") + else: + _KALEIDO_MAJOR = Version(importlib_metadata.version("kaleido")).major + return _KALEIDO_MAJOR + + +try: + if kaleido_available() and kaleido_major() < 1: + # Kaleido v0 + import kaleido + from kaleido.scopes.plotly import PlotlyScope + + # Show a deprecation warning if the old method of setting defaults is used + class PlotlyScopeWrapper(PlotlyScope): + def __setattr__(self, name, value): + if name in defaults.__dict__: + if ENABLE_KALEIDO_V0_DEPRECATION_WARNINGS: + warnings.warn( + kaleido_scope_default_warning_func(name), + DeprecationWarning, + stacklevel=2, + ) + super().__setattr__(name, value) + + def __getattr__(self, name): + if hasattr(defaults, name): + if ENABLE_KALEIDO_V0_DEPRECATION_WARNINGS: + warnings.warn( + kaleido_scope_default_warning_func(name), + DeprecationWarning, + stacklevel=2, + ) + return super().__getattr__(name) + + # Ensure the new method of setting defaults is backwards compatible with Kaleido v0 + # DefaultsBackwardsCompatible sets the attributes on `scope` object at the same time + # as they are set on the `defaults` object + class DefaultsBackwardsCompatible(defaults.__class__): + def __init__(self, scope): + self._scope = scope + super().__init__() + + def __setattr__(self, name, value): + if not name == "_scope": + if ( + hasattr(self._scope, name) + and getattr(self._scope, name) != value + ): + setattr(self._scope, name, value) + super().__setattr__(name, value) + + scope = PlotlyScopeWrapper() + defaults = DefaultsBackwardsCompatible(scope) + # Compute absolute path to the 'plotly/package_data/' directory + root_dir = os.path.dirname(os.path.abspath(plotly.__file__)) + package_dir = os.path.join(root_dir, "package_data") + scope.plotlyjs = os.path.join(package_dir, "plotly.min.js") + if scope.mathjax is None: + with warnings.catch_warnings(): + warnings.filterwarnings( + "ignore", message=r".*scope\.mathjax.*", category=DeprecationWarning + ) + scope.mathjax = ( + "https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" + ) + else: + # Kaleido v1 + import kaleido + + # Show a deprecation warning if the old method of setting defaults is used + class DefaultsWrapper: + def __getattr__(self, name): + if hasattr(defaults, name): + if ENABLE_KALEIDO_V0_DEPRECATION_WARNINGS: + warnings.warn( + kaleido_scope_default_warning_func(name), + DeprecationWarning, + stacklevel=2, + ) + return getattr(defaults, name) + else: + raise AttributeError(bad_attribute_error_msg_func(name)) + + def __setattr__(self, name, value): + if hasattr(defaults, name): + if ENABLE_KALEIDO_V0_DEPRECATION_WARNINGS: + warnings.warn( + kaleido_scope_default_warning_func(name), + DeprecationWarning, + stacklevel=2, + ) + setattr(defaults, name, value) + else: + raise AttributeError(bad_attribute_error_msg_func(name)) + + scope = DefaultsWrapper() + +except ImportError: + PlotlyScope = None + scope = None + + +def as_path_object(file: Union[str, Path]) -> Union[Path, None]: + """ + Cast the `file` argument, which may be either a string or a Path object, + to a Path object. + If `file` is neither a string nor a Path object, None will be returned. + """ + if isinstance(file, str): + # Use the standard Path constructor to make a pathlib object. + path = Path(file) + elif isinstance(file, Path): + # `file` is already a Path object. + path = file + else: + # We could not make a Path object out of file. Either `file` is an open file + # descriptor with a `write()` method or it's an invalid object. + path = None + return path + + +def infer_format(path: Union[Path, None], format: Union[str, None]) -> Union[str, None]: + if path is not None and format is None: + ext = path.suffix + if ext: + format = ext.lstrip(".") + else: + raise ValueError( + f""" +Cannot infer image type from output path '{path}'. +Please specify the type using the format parameter, or add a file extension. +For example: + + >>> import plotly.io as pio + >>> pio.write_image(fig, file_path, format='png') +""" + ) + return format + + +def to_image( + fig: Union[dict, plotly.graph_objects.Figure], + format: Union[str, None] = None, + width: Union[int, None] = None, + height: Union[int, None] = None, + scale: Union[int, float, None] = None, + validate: bool = True, + # Deprecated + engine: Union[str, None] = None, +) -> bytes: + """ + Convert a figure to a static image bytes string + + Parameters + ---------- + fig: + Figure object or dict representing a figure + + format: str or None + The desired image format. One of + - 'png' + - 'jpg' or 'jpeg' + - 'webp' + - 'svg' + - 'pdf' + - 'eps' (deprecated) (Requires the poppler library to be installed and on the PATH) + + If not specified, will default to: + - `plotly.io.defaults.default_format` if engine is "kaleido" + - `plotly.io.orca.config.default_format` if engine is "orca" (deprecated) + + width: int or None + The width of the exported image in layout pixels. If the `scale` + property is 1.0, this will also be the width of the exported image + in physical pixels. + + If not specified, will default to: + - `plotly.io.defaults.default_width` if engine is "kaleido" + - `plotly.io.orca.config.default_width` if engine is "orca" (deprecated) + + height: int or None + The height of the exported image in layout pixels. If the `scale` + property is 1.0, this will also be the height of the exported image + in physical pixels. + + If not specified, will default to: + - `plotly.io.defaults.default_height` if engine is "kaleido" + - `plotly.io.orca.config.default_height` if engine is "orca" (deprecated) + + scale: int or float or None + The scale factor to use when exporting the figure. A scale factor + larger than 1.0 will increase the image resolution with respect + to the figure's layout pixel dimensions. Whereas as scale factor of + less than 1.0 will decrease the image resolution. + + If not specified, will default to: + - `plotly.io.defaults.default_scale` if engine is "kaleido" + - `plotly.io.orca.config.default_scale` if engine is "orca" (deprecated) + + validate: bool + True if the figure should be validated before being converted to + an image, False otherwise. + + engine (deprecated): str + Image export engine to use. This parameter is deprecated and Orca engine support will be + dropped in the next major Plotly version. Until then, the following values are supported: + - "kaleido": Use Kaleido for image export + - "orca": Use Orca for image export + - "auto" (default): Use Kaleido if installed, otherwise use Orca + + Returns + ------- + bytes + The image data + """ + + # Handle engine + if engine is not None: + if ENABLE_KALEIDO_V0_DEPRECATION_WARNINGS: + warnings.warn( + ENGINE_PARAM_DEPRECATION_MSG, DeprecationWarning, stacklevel=2 + ) + else: + engine = "auto" + + if engine == "auto": + if kaleido_available(): + # Default to kaleido if available + engine = "kaleido" + else: + # See if orca is available + from ._orca import validate_executable + + try: + validate_executable() + engine = "orca" + except Exception: + # If orca not configured properly, make sure we display the error + # message advising the installation of kaleido + engine = "kaleido" + + if engine == "orca": + if ENABLE_KALEIDO_V0_DEPRECATION_WARNINGS: + warnings.warn(ORCA_DEPRECATION_MSG, DeprecationWarning, stacklevel=2) + # Fall back to legacy orca image export path + from ._orca import to_image as to_image_orca + + return to_image_orca( + fig, + format=format, + width=width, + height=height, + scale=scale, + validate=validate, + ) + elif engine != "kaleido": + raise ValueError(f"Invalid image export engine specified: {repr(engine)}") + + # Raise informative error message if Kaleido is not installed + if not kaleido_available(): + raise ValueError( + """ +Image export using the "kaleido" engine requires the Kaleido package, +which can be installed using pip: + + $ pip install --upgrade kaleido +""" + ) + + # Convert figure to dict (and validate if requested) + fig_dict = validate_coerce_fig_to_dict(fig, validate) + + # Request image bytes + if kaleido_major() > 0: + # Kaleido v1 + # Check if trying to export to EPS format, which is not supported in Kaleido v1 + if format == "eps": + raise ValueError( + f""" +EPS export is not supported by Kaleido v1. Please use SVG or PDF instead. +You can also downgrade to Kaleido v0, but support for Kaleido v0 will be removed after {ENGINE_SUPPORT_TIMELINE}. +To downgrade to Kaleido v0, run: + $ pip install 'kaleido<1.0.0' +""" + ) + from kaleido.errors import ChromeNotFoundError + + try: + kopts = {} + if defaults.plotlyjs: + kopts["plotlyjs"] = defaults.plotlyjs + if defaults.mathjax: + kopts["mathjax"] = defaults.mathjax + + width = ( + width + or fig_dict.get("layout", {}).get("width") + or fig_dict.get("layout", {}) + .get("template", {}) + .get("layout", {}) + .get("width") + or defaults.default_width + ) + height = ( + height + or fig_dict.get("layout", {}).get("height") + or fig_dict.get("layout", {}) + .get("template", {}) + .get("layout", {}) + .get("height") + or defaults.default_height + ) + + img_bytes = kaleido.calc_fig_sync( + fig_dict, + opts=dict( + format=format or defaults.default_format, + width=width, + height=height, + scale=scale or defaults.default_scale, + ), + topojson=defaults.topojson, + kopts=kopts, + ) + except ChromeNotFoundError: + raise RuntimeError(PLOTLY_GET_CHROME_ERROR_MSG) + + else: + # Kaleido v0 + if ENABLE_KALEIDO_V0_DEPRECATION_WARNINGS: + warnings.warn(KALEIDO_DEPRECATION_MSG, DeprecationWarning, stacklevel=2) + img_bytes = scope.transform( + fig_dict, format=format, width=width, height=height, scale=scale + ) + + return img_bytes + + +def write_image( + fig: Union[dict, plotly.graph_objects.Figure], + file: Union[str, Path], + format: Union[str, None] = None, + scale: Union[int, float, None] = None, + width: Union[int, None] = None, + height: Union[int, None] = None, + validate: bool = True, + # Deprecated + engine: Union[str, None] = "auto", +): + """ + Convert a figure to a static image and write it to a file or writeable + object + + Parameters + ---------- + fig: + Figure object or dict representing a figure + + file: str or writeable + A string representing a local file path or a writeable object + (e.g. a pathlib.Path object or an open file descriptor) + + format: str or None + The desired image format. One of + - 'png' + - 'jpg' or 'jpeg' + - 'webp' + - 'svg' + - 'pdf' + - 'eps' (deprecated) (Requires the poppler library to be installed and on the PATH) + + If not specified and `file` is a string then this will default to the + file extension. If not specified and `file` is not a string then this + will default to: + - `plotly.io.defaults.default_format` if engine is "kaleido" + - `plotly.io.orca.config.default_format` if engine is "orca" (deprecated) + + width: int or None + The width of the exported image in layout pixels. If the `scale` + property is 1.0, this will also be the width of the exported image + in physical pixels. + + If not specified, will default to: + - `plotly.io.defaults.default_width` if engine is "kaleido" + - `plotly.io.orca.config.default_width` if engine is "orca" (deprecated) + + height: int or None + The height of the exported image in layout pixels. If the `scale` + property is 1.0, this will also be the height of the exported image + in physical pixels. + + If not specified, will default to: + - `plotly.io.defaults.default_height` if engine is "kaleido" + - `plotly.io.orca.config.default_height` if engine is "orca" (deprecated) + + scale: int or float or None + The scale factor to use when exporting the figure. A scale factor + larger than 1.0 will increase the image resolution with respect + to the figure's layout pixel dimensions. Whereas as scale factor of + less than 1.0 will decrease the image resolution. + + If not specified, will default to: + - `plotly.io.defaults.default_scale` if engine is "kaleido" + - `plotly.io.orca.config.default_scale` if engine is "orca" (deprecated) + + validate: bool + True if the figure should be validated before being converted to + an image, False otherwise. + + engine (deprecated): str + Image export engine to use. This parameter is deprecated and Orca engine support will be + dropped in the next major Plotly version. Until then, the following values are supported: + - "kaleido": Use Kaleido for image export + - "orca": Use Orca for image export + - "auto" (default): Use Kaleido if installed, otherwise use Orca + + Returns + ------- + None + """ + # Show Kaleido deprecation warning if needed + if ENABLE_KALEIDO_V0_DEPRECATION_WARNINGS: + if ( + engine in {None, "auto", "kaleido"} + and kaleido_available() + and kaleido_major() < 1 + ): + warnings.warn(KALEIDO_DEPRECATION_MSG, DeprecationWarning, stacklevel=2) + if engine == "orca": + warnings.warn(ORCA_DEPRECATION_MSG, DeprecationWarning, stacklevel=2) + if engine not in {None, "auto"}: + warnings.warn( + ENGINE_PARAM_DEPRECATION_MSG, DeprecationWarning, stacklevel=2 + ) + + # Try to cast `file` as a pathlib object `path`. + path = as_path_object(file) + + # Infer image format if not specified + format = infer_format(path, format) + + # Request image + # Do this first so we don't create a file if image conversion fails + img_data = to_image( + fig, + format=format, + scale=scale, + width=width, + height=height, + validate=validate, + engine=engine, + ) + + # Open file + if path is None: + # We previously failed to make sense of `file` as a pathlib object. + # Attempt to write to `file` as an open file descriptor. + try: + file.write(img_data) + return + except AttributeError: + pass + raise ValueError( + f""" +The 'file' argument '{file}' is not a string, pathlib.Path object, or file descriptor. +""" + ) + else: + # We previously succeeded in interpreting `file` as a pathlib object. + # Now we can use `write_bytes()`. + path.write_bytes(img_data) + + +def write_images( + fig: Union[ + List[Union[dict, plotly.graph_objects.Figure]], + Union[dict, plotly.graph_objects.Figure], + ], + file: Union[List[Union[str, Path]], Union[str, Path]], + format: Union[List[Union[str, None]], Union[str, None]] = None, + scale: Union[List[Union[int, float, None]], Union[int, float, None]] = None, + width: Union[List[Union[int, None]], Union[int, None]] = None, + height: Union[List[Union[int, None]], Union[int, None]] = None, + validate: Union[List[bool], bool] = True, +) -> None: + """ + Write multiple images to files or writeable objects. This is much faster than + calling write_image() multiple times. This function can only be used with the Kaleido + engine, v1.0.0 or greater. + + This function accepts the same arguments as write_image() (minus the `engine` argument), + except that any of the arguments may be either a single value or an iterable of values. + If multiple arguments are iterable, they must all have the same length. + + Parameters + ---------- + fig: + List of figure objects or dicts representing a figure. + Also accepts a single figure or dict representing a figure. + + file: str, pathlib.Path, or list of (str or pathlib.Path) + List of str or pathlib.Path objects representing local file paths to write to. + Can also be a single str or pathlib.Path object if fig argument is + a single figure or dict representing a figure. + + format: str, None, or list of (str or None) + The image format to use for exported images. + Supported formats are: + - 'png' + - 'jpg' or 'jpeg' + - 'webp' + - 'svg' + - 'pdf' + + Use a list to specify formats for each figure or dict in the list + provided to the `fig` argument. + Specify format as a `str` to apply the same format to all exported images. + If not specified, and the corresponding `file` argument has a file extension, then `format` will default to the + file extension. Otherwise, will default to `plotly.io.defaults.default_format`. + + width: int, None, or list of (int or None) + The width of the exported image in layout pixels. If the `scale` + property is 1.0, this will also be the width of the exported image + in physical pixels. + + Use a list to specify widths for each figure or dict in the list + provided to the `fig` argument. + Specify width as an `int` to apply the same width to all exported images. + If not specified, will default to `plotly.io.defaults.default_width`. + + height: int, None, or list of (int or None) + The height of the exported image in layout pixels. If the `scale` + property is 1.0, this will also be the height of the exported image + in physical pixels. + + Use a list to specify heights for each figure or dict in the list + provided to the `fig` argument. + Specify height as an `int` to apply the same height to all exported images. + If not specified, will default to `plotly.io.defaults.default_height`. + + scale: int, float, None, or list of (int, float, or None) + The scale factor to use when exporting the figure. A scale factor + larger than 1.0 will increase the image resolution with respect + to the figure's layout pixel dimensions. Whereas as scale factor of + less than 1.0 will decrease the image resolution. + + Use a list to specify scale for each figure or dict in the list + provided to the `fig` argument. + Specify scale as an `int` or `float` to apply the same scale to all exported images. + If not specified, will default to `plotly.io.defaults.default_scale`. + + validate: bool or list of bool + True if the figure should be validated before being converted to + an image, False otherwise. + + Use a list to specify validation setting for each figure in the list + provided to the `fig` argument. + Specify validate as a boolean to apply the same validation setting to all figures. + + Returns + ------- + None + """ + + # Raise informative error message if Kaleido v1 is not installed + if not kaleido_available(): + raise ValueError( + """ +The `write_images()` function requires the Kaleido package, +which can be installed using pip: + + $ pip install --upgrade kaleido +""" + ) + elif kaleido_major() < 1: + raise ValueError( + f""" +You have Kaleido version {Version(importlib_metadata.version("kaleido"))} installed. +The `write_images()` function requires the Kaleido package version 1.0.0 or greater, +which can be installed using pip: + + $ pip install 'kaleido>=1.0.0' +""" + ) + + # Broadcast arguments into correct format for passing to Kaleido + arg_dicts = broadcast_args_to_dicts( + fig=fig, + file=file, + format=format, + scale=scale, + width=width, + height=height, + validate=validate, + ) + + # For each dict: + # - convert figures to dicts (and validate if requested) + # - try to cast `file` as a Path object + for d in arg_dicts: + d["fig"] = validate_coerce_fig_to_dict(d["fig"], d["validate"]) + d["file"] = as_path_object(d["file"]) + + # Reshape arg_dicts into correct format for passing to Kaleido + # We call infer_format() here rather than above so that the `file` argument + # has already been cast to a Path object. + # Also insert defaults for any missing arguments as needed + kaleido_specs = [ + dict( + fig=d["fig"], + path=d["file"], + opts=dict( + format=infer_format(d["file"], d["format"]) or defaults.default_format, + width=d["width"] or defaults.default_width, + height=d["height"] or defaults.default_height, + scale=d["scale"] or defaults.default_scale, + ), + topojson=defaults.topojson, + ) + for d in arg_dicts + ] + + from kaleido.errors import ChromeNotFoundError + + try: + kopts = {} + if defaults.plotlyjs: + kopts["plotlyjs"] = defaults.plotlyjs + if defaults.mathjax: + kopts["mathjax"] = defaults.mathjax + kaleido.write_fig_from_object_sync( + kaleido_specs, + kopts=kopts, + ) + except ChromeNotFoundError: + raise RuntimeError(PLOTLY_GET_CHROME_ERROR_MSG) + + +def full_figure_for_development( + fig: Union[dict, plotly.graph_objects.Figure], + warn: bool = True, + as_dict: bool = False, +) -> Union[plotly.graph_objects.Figure, dict]: + """ + Compute default values for all attributes not specified in the input figure and + returns the output as a "full" figure. This function calls Plotly.js via Kaleido + to populate unspecified attributes. This function is intended for interactive use + during development to learn more about how Plotly.js computes default values and is + not generally necessary or recommended for production use. + + Parameters + ---------- + fig: + Figure object or dict representing a figure + + warn: bool + If False, suppress warnings about not using this in production. + + as_dict: bool + If True, output is a dict with some keys that go.Figure can't parse. + If False, output is a go.Figure with unparseable keys skipped. + + Returns + ------- + plotly.graph_objects.Figure or dict + The full figure + """ + + # Raise informative error message if Kaleido is not installed + if not kaleido_available(): + raise ValueError( + """ +Full figure generation requires the Kaleido package, +which can be installed using pip: + + $ pip install --upgrade kaleido +""" + ) + + if warn: + warnings.warn( + "full_figure_for_development is not recommended or necessary for " + "production use in most circumstances. \n" + "To suppress this warning, set warn=False" + ) + + if kaleido_available() and kaleido_major() > 0: + # Kaleido v1 + bytes = kaleido.calc_fig_sync( + fig, + opts=dict(format="json"), + ) + fig = json.loads(bytes.decode("utf-8")) + else: + # Kaleido v0 + if ENABLE_KALEIDO_V0_DEPRECATION_WARNINGS: + warnings.warn( + f"Support for Kaleido versions less than 1.0.0 is deprecated and will be removed after {ENGINE_SUPPORT_TIMELINE}. " + + "Please upgrade Kaleido to version 1.0.0 or greater (`pip install 'kaleido>=1.0.0'`).", + DeprecationWarning, + ) + fig = json.loads(scope.transform(fig, format="json").decode("utf-8")) + + if as_dict: + return fig + else: + import plotly.graph_objects as go + + return go.Figure(fig, skip_invalid=True) + + +def plotly_get_chrome() -> None: + """ + Install Google Chrome for Kaleido (Required for Plotly image export). + This function is a command-line wrapper for `plotly.io.get_chrome()`. + + When running from the command line, use the command `plotly_get_chrome`; + when calling from Python code, use `plotly.io.get_chrome()`. + """ + + usage = """ +Usage: plotly_get_chrome [-y] [--path PATH] + +Installs Google Chrome for Plotly image export. + +Options: + -y Skip confirmation prompt + --path PATH Specify the path to install Chrome. Must be a path to an existing directory. + --help Show this message and exit. +""" + + if not kaleido_available() or kaleido_major() < 1: + raise ValueError( + """ +This command requires Kaleido v1.0.0 or greater. +Install it using `pip install 'kaleido>=1.0.0'` or `pip install 'plotly[kaleido]'`." +""" + ) + + # Handle command line arguments + import sys + + cli_args = sys.argv + + # Handle "-y" flag + cli_yes = "-y" in cli_args + if cli_yes: + cli_args.remove("-y") + + # Handle "--path" flag + chrome_install_path = None + if "--path" in cli_args: + path_index = cli_args.index("--path") + 1 + if path_index < len(cli_args): + chrome_install_path = cli_args[path_index] + cli_args.remove("--path") + cli_args.remove(chrome_install_path) + chrome_install_path = Path(chrome_install_path) + + # If any arguments remain, command syntax was incorrect -- print usage and exit + if len(cli_args) > 1: + print(usage) + sys.exit(1) + + if not cli_yes: + print( + f""" +Plotly will install a copy of Google Chrome to be used for generating static images of plots. +Chrome will be installed at: {chrome_install_path}""" + ) + response = input("Do you want to proceed? [y/n] ") + if not response or response[0].lower() != "y": + print("Cancelled") + return + print("Installing Chrome for Plotly...") + exe_path = get_chrome(chrome_install_path) + print("Chrome installed successfully.") + print(f"The Chrome executable is now located at: {exe_path}") + + +def get_chrome(path: Union[str, Path, None] = None) -> Path: + """ + Get the path to the Chrome executable for Kaleido. + This function is used by the `plotly_get_chrome` command line utility. + + Parameters + ---------- + path: str or Path or None + The path to the directory where Chrome should be installed. + If None, the default download path will be used. + """ + if not kaleido_available() or kaleido_major() < 1: + raise ValueError( + """ +This command requires Kaleido v1.0.0 or greater. +Install it using `pip install 'kaleido>=1.0.0'` or `pip install 'plotly[kaleido]'`." +""" + ) + + # Use default download path if no path was specified + if path: + user_specified_path = True + chrome_install_path = Path(path) # Ensure it's a Path object + else: + user_specified_path = False + from choreographer.cli.defaults import default_download_path + + chrome_install_path = default_download_path + + # If install path was chosen by user, make sure there is an existing directory + # located at chrome_install_path; otherwise fail + if user_specified_path: + if not chrome_install_path.exists(): + raise ValueError( + f""" +The specified install path '{chrome_install_path}' does not exist. +Please specify a path to an existing directory using the --path argument, +or omit the --path argument to use the default download path. +""" + ) + # Make sure the path is a directory + if not chrome_install_path.is_dir(): + raise ValueError( + f""" +The specified install path '{chrome_install_path}' already exists but is not a directory. +Please specify a path to an existing directory using the --path argument, +or omit the --path argument to use the default download path. +""" + ) + + return kaleido.get_chrome_sync(path=chrome_install_path) + + +__all__ = ["to_image", "write_image", "scope", "full_figure_for_development"] diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/_orca.py b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_orca.py new file mode 100644 index 0000000000000000000000000000000000000000..2984210edcebb1332d0a723d53f8aeb834c688e9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_orca.py @@ -0,0 +1,1670 @@ +import atexit +import functools +import json +import os +import random +import socket +import subprocess +import sys +import threading +import time +import warnings +from contextlib import contextmanager +from copy import copy +from pathlib import Path +from shutil import which + +import plotly +from plotly.files import PLOTLY_DIR, ensure_writable_plotly_dir +from plotly.io._utils import validate_coerce_fig_to_dict +from plotly.optional_imports import get_module + +psutil = get_module("psutil") + +# Valid image format constants +# ---------------------------- +valid_formats = ("png", "jpeg", "webp", "svg", "pdf", "eps") +format_conversions = {fmt: fmt for fmt in valid_formats} +format_conversions.update({"jpg": "jpeg"}) + + +# Utility functions +# ----------------- +def raise_format_value_error(val): + raise ValueError( + """ +Invalid value of type {typ} receive as an image format specification. + Received value: {v} + +An image format must be specified as one of the following string values: + {valid_formats}""".format( + typ=type(val), v=val, valid_formats=sorted(format_conversions.keys()) + ) + ) + + +def validate_coerce_format(fmt): + """ + Validate / coerce a user specified image format, and raise an informative + exception if format is invalid. + + Parameters + ---------- + fmt + A value that may or may not be a valid image format string. + + Returns + ------- + str or None + A valid image format string as supported by orca. This may not + be identical to the input image designation. For example, + the resulting string will always be lower case and 'jpg' is + converted to 'jpeg'. + + If the input format value is None, then no exception is raised and + None is returned. + + Raises + ------ + ValueError + if the input `fmt` cannot be interpreted as a valid image format. + """ + + # Let None pass through + if fmt is None: + return None + + # Check format type + if not isinstance(fmt, str) or not fmt: + raise_format_value_error(fmt) + + # Make lower case + fmt = fmt.lower() + + # Remove leading period, if any. + # For example '.png' is accepted and converted to 'png' + if fmt[0] == ".": + fmt = fmt[1:] + + # Check string value + if fmt not in format_conversions: + raise_format_value_error(fmt) + + # Return converted string specification + return format_conversions[fmt] + + +def find_open_port(): + """ + Use the socket module to find an open port. + + Returns + ------- + int + An open port + """ + s = socket.socket() + s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) + s.bind(("", 0)) + _, port = s.getsockname() + s.close() + + return port + + +def retry(min_wait=5, max_wait=10, max_delay=60000): + def decorator(func): + @functools.wraps(func) + def wrapper(*args, **kwargs): + start_time = time.time() + + while True: + try: + return func(*args, **kwargs) + except Exception as e: + elapsed_time = time.time() - start_time + if elapsed_time * 1000 >= max_delay: + raise TimeoutError( + f"Retry limit of {max_delay} milliseconds reached." + ) from e + + wait_time = random.uniform(min_wait, max_wait) + print(f"Retrying in {wait_time:.2f} seconds due to {e}...") + time.sleep(wait_time) + + return wrapper + + return decorator + + +# Orca configuration class +# ------------------------ +class OrcaConfig(object): + """ + Singleton object containing the current user defined configuration + properties for orca. + + These parameters may optionally be saved to the user's ~/.plotly + directory using the `save` method, in which case they are automatically + restored in future sessions. + """ + + def __init__(self): + # Initialize properties dict + self._props = {} + + # Compute absolute path to the 'plotly/package_data/' directory + root_dir = os.path.dirname(os.path.abspath(plotly.__file__)) + self.package_dir = os.path.join(root_dir, "package_data") + + # Load pre-existing configuration + self.reload(warn=False) + + # Compute constants + plotlyjs = os.path.join(self.package_dir, "plotly.min.js") + self._constants = { + "plotlyjs": plotlyjs, + "config_file": os.path.join(PLOTLY_DIR, ".orca"), + } + + def restore_defaults(self, reset_server=True): + """ + Reset all orca configuration properties to their default values + """ + self._props = {} + + if reset_server: + # Server must restart before setting is active + reset_status() + + def update(self, d={}, **kwargs): + """ + Update one or more properties from a dict or from input keyword + arguments. + + Parameters + ---------- + d: dict + Dictionary from property names to new property values. + + kwargs + Named argument value pairs where the name is a configuration + property name and the value is the new property value. + + Returns + ------- + None + + Examples + -------- + Update configuration properties using a dictionary + + >>> import plotly.io as pio + >>> pio.orca.config.update({'timeout': 30, 'default_format': 'svg'}) + + Update configuration properties using keyword arguments + + >>> pio.orca.config.update(timeout=30, default_format='svg'}) + """ + # Combine d and kwargs + if not isinstance(d, dict): + raise ValueError( + """ +The first argument to update must be a dict, \ +but received value of type {typ}l + Received value: {val}""".format(typ=type(d), val=d) + ) + + updates = copy(d) + updates.update(kwargs) + + # Validate keys + for k in updates: + if k not in self._props: + raise ValueError("Invalid property name: {k}".format(k=k)) + + # Apply keys + for k, v in updates.items(): + setattr(self, k, v) + + def reload(self, warn=True): + """ + Reload orca settings from ~/.plotly/.orca, if any. + + Note: Settings are loaded automatically when plotly is imported. + This method is only needed if the setting are changed by some outside + process (e.g. a text editor) during an interactive session. + + Parameters + ---------- + warn: bool + If True, raise informative warnings if settings cannot be restored. + If False, do not raise warnings if setting cannot be restored. + + Returns + ------- + None + """ + if os.path.exists(self.config_file): + # ### Load file into a string ### + try: + with open(self.config_file, "r") as f: + orca_str = f.read() + except Exception: + if warn: + warnings.warn( + """\ +Unable to read orca configuration file at {path}""".format(path=self.config_file) + ) + return + + # ### Parse as JSON ### + try: + orca_props = json.loads(orca_str) + except ValueError: + if warn: + warnings.warn( + """\ +Orca configuration file at {path} is not valid JSON""".format(path=self.config_file) + ) + return + + # ### Update _props ### + for k, v in orca_props.items(): + self._props[k] = v + + elif warn: + warnings.warn( + """\ +Orca configuration file at {path} not found""".format(path=self.config_file) + ) + + def save(self): + """ + Attempt to save current settings to disk, so that they are + automatically restored for future sessions. + + This operation requires write access to the path returned by + in the `config_file` property. + + Returns + ------- + None + """ + if ensure_writable_plotly_dir(): + with open(self.config_file, "w") as f: + json.dump(self._props, f, indent=4) + else: + warnings.warn( + """\ +Failed to write orca configuration file at '{path}'""".format(path=self.config_file) + ) + + @property + def server_url(self): + """ + The server URL to use for an external orca server, or None if orca + should be managed locally + + Overrides executable, port, timeout, mathjax, topojson, + and mapbox_access_token + + Returns + ------- + str or None + """ + return self._props.get("server_url", None) + + @server_url.setter + def server_url(self, val): + if val is None: + self._props.pop("server_url", None) + return + if not isinstance(val, str): + raise ValueError( + """ +The server_url property must be a string, but received value of type {typ}. + Received value: {val}""".format(typ=type(val), val=val) + ) + + if not val.startswith("http://") and not val.startswith("https://"): + val = "http://" + val + + shutdown_server() + self.executable = None + self.port = None + self.timeout = None + self.mathjax = None + self.topojson = None + self.mapbox_access_token = None + self._props["server_url"] = val + + @property + def port(self): + """ + The specific port to use to communicate with the orca server, or + None if the port is to be chosen automatically. + + If an orca server is active, the port in use is stored in the + plotly.io.orca.status.port property. + + Returns + ------- + int or None + """ + return self._props.get("port", None) + + @port.setter + def port(self, val): + if val is None: + self._props.pop("port", None) + return + if not isinstance(val, int): + raise ValueError( + """ +The port property must be an integer, but received value of type {typ}. + Received value: {val}""".format(typ=type(val), val=val) + ) + + self._props["port"] = val + + @property + def executable(self): + """ + The name or full path of the orca executable. + + - If a name (e.g. 'orca'), then it should be the name of an orca + executable on the PATH. The directories on the PATH can be + displayed by running the following command: + + >>> import os + >>> print(os.environ.get('PATH').replace(os.pathsep, os.linesep)) + + - If a full path (e.g. '/path/to/orca'), then + it should be the full path to an orca executable. In this case + the executable does not need to reside on the PATH. + + If an orca server has been validated, then the full path to the + validated orca executable is stored in the + plotly.io.orca.status.executable property. + + Returns + ------- + str + """ + executable_list = self._props.get("executable_list", ["orca"]) + if executable_list is None: + return None + else: + return " ".join(executable_list) + + @executable.setter + def executable(self, val): + if val is None: + self._props.pop("executable", None) + else: + if not isinstance(val, str): + raise ValueError( + """ +The executable property must be a string, but received value of type {typ}. + Received value: {val}""".format(typ=type(val), val=val) + ) + if isinstance(val, str): + val = [val] + self._props["executable_list"] = val + + # Server and validation must restart before setting is active + reset_status() + + @property + def timeout(self): + """ + The number of seconds of inactivity required before the orca server + is shut down. + + For example, if timeout is set to 20, then the orca + server will shutdown once is has not been used for at least + 20 seconds. If timeout is set to None, then the server will not be + automatically shut down due to inactivity. + + Regardless of the value of timeout, a running orca server may be + manually shut down like this: + + >>> import plotly.io as pio + >>> pio.orca.shutdown_server() + + Returns + ------- + int or float or None + """ + return self._props.get("timeout", None) + + @timeout.setter + def timeout(self, val): + if val is None: + self._props.pop("timeout", None) + else: + if not isinstance(val, (int, float)): + raise ValueError( + """ +The timeout property must be a number, but received value of type {typ}. + Received value: {val}""".format(typ=type(val), val=val) + ) + self._props["timeout"] = val + + # Server must restart before setting is active + shutdown_server() + + @property + def default_width(self): + """ + The default width to use on image export. This value is only + applied if no width value is supplied to the plotly.io + to_image or write_image functions. + + Returns + ------- + int or None + """ + return self._props.get("default_width", None) + + @default_width.setter + def default_width(self, val): + if val is None: + self._props.pop("default_width", None) + return + if not isinstance(val, int): + raise ValueError( + """ +The default_width property must be an int, but received value of type {typ}. + Received value: {val}""".format(typ=type(val), val=val) + ) + self._props["default_width"] = val + + @property + def default_height(self): + """ + The default height to use on image export. This value is only + applied if no height value is supplied to the plotly.io + to_image or write_image functions. + + Returns + ------- + int or None + """ + return self._props.get("default_height", None) + + @default_height.setter + def default_height(self, val): + if val is None: + self._props.pop("default_height", None) + return + if not isinstance(val, int): + raise ValueError( + """ +The default_height property must be an int, but received value of type {typ}. + Received value: {val}""".format(typ=type(val), val=val) + ) + self._props["default_height"] = val + + @property + def default_format(self): + """ + The default image format to use on image export. + + Valid image formats strings are: + - 'png' + - 'jpg' or 'jpeg' + - 'webp' + - 'svg' + - 'pdf' + - 'eps' (Requires the poppler library to be installed) + + This value is only applied if no format value is supplied to the + plotly.io to_image or write_image functions. + + Returns + ------- + str or None + """ + return self._props.get("default_format", "png") + + @default_format.setter + def default_format(self, val): + if val is None: + self._props.pop("default_format", None) + return + + val = validate_coerce_format(val) + self._props["default_format"] = val + + @property + def default_scale(self): + """ + The default image scaling factor to use on image export. + This value is only applied if no scale value is supplied to the + plotly.io to_image or write_image functions. + + Returns + ------- + int or None + """ + return self._props.get("default_scale", 1) + + @default_scale.setter + def default_scale(self, val): + if val is None: + self._props.pop("default_scale", None) + return + if not isinstance(val, (int, float)): + raise ValueError( + """ +The default_scale property must be a number, but received value of type {typ}. + Received value: {val}""".format(typ=type(val), val=val) + ) + self._props["default_scale"] = val + + @property + def topojson(self): + """ + Path to the topojson files needed to render choropleth traces. + + If None, topojson files from the plot.ly CDN are used. + + Returns + ------- + str + """ + return self._props.get("topojson", None) + + @topojson.setter + def topojson(self, val): + if val is None: + self._props.pop("topojson", None) + else: + if not isinstance(val, str): + raise ValueError( + """ +The topojson property must be a string, but received value of type {typ}. + Received value: {val}""".format(typ=type(val), val=val) + ) + self._props["topojson"] = val + + # Server must restart before setting is active + shutdown_server() + + @property + def mathjax(self): + """ + Path to the MathJax bundle needed to render LaTeX characters + + Returns + ------- + str + """ + return self._props.get( + "mathjax", + "https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js", + ) + + @mathjax.setter + def mathjax(self, val): + if val is None: + self._props.pop("mathjax", None) + else: + if not isinstance(val, str): + raise ValueError( + """ +The mathjax property must be a string, but received value of type {typ}. + Received value: {val}""".format(typ=type(val), val=val) + ) + self._props["mathjax"] = val + + # Server must restart before setting is active + shutdown_server() + + @property + def mapbox_access_token(self): + """ + Mapbox access token required to render mapbox traces. + + Returns + ------- + str + """ + return self._props.get("mapbox_access_token", None) + + @mapbox_access_token.setter + def mapbox_access_token(self, val): + if val is None: + self._props.pop("mapbox_access_token", None) + else: + if not isinstance(val, str): + raise ValueError( + """ +The mapbox_access_token property must be a string, \ +but received value of type {typ}. + Received value: {val}""".format(typ=type(val), val=val) + ) + self._props["mapbox_access_token"] = val + + # Server must restart before setting is active + shutdown_server() + + @property + def use_xvfb(self): + dflt = "auto" + return self._props.get("use_xvfb", dflt) + + @use_xvfb.setter + def use_xvfb(self, val): + valid_vals = [True, False, "auto"] + if val is None: + self._props.pop("use_xvfb", None) + else: + if val not in valid_vals: + raise ValueError( + """ +The use_xvfb property must be one of {valid_vals} + Received value of type {typ}: {val}""".format( + valid_vals=valid_vals, typ=type(val), val=repr(val) + ) + ) + + self._props["use_xvfb"] = val + + # Server and validation must restart before setting is active + reset_status() + + @property + def plotlyjs(self): + """ + The plotly.js bundle being used for image rendering. + + Returns + ------- + str + """ + return self._constants.get("plotlyjs", None) + + @property + def config_file(self): + """ + Path to orca configuration file + + Using the `plotly.io.config.save()` method will save the current + configuration settings to this file. Settings in this file are + restored at the beginning of each sessions. + + Returns + ------- + str + """ + return os.path.join(PLOTLY_DIR, ".orca") + + def __repr__(self): + """ + Display a nice representation of the current orca configuration. + """ + return """\ +orca configuration +------------------ + server_url: {server_url} + executable: {executable} + port: {port} + timeout: {timeout} + default_width: {default_width} + default_height: {default_height} + default_scale: {default_scale} + default_format: {default_format} + mathjax: {mathjax} + topojson: {topojson} + mapbox_access_token: {mapbox_access_token} + use_xvfb: {use_xvfb} + +constants +--------- + plotlyjs: {plotlyjs} + config_file: {config_file} + +""".format( + server_url=self.server_url, + port=self.port, + executable=self.executable, + timeout=self.timeout, + default_width=self.default_width, + default_height=self.default_height, + default_scale=self.default_scale, + default_format=self.default_format, + mathjax=self.mathjax, + topojson=self.topojson, + mapbox_access_token=self.mapbox_access_token, + plotlyjs=self.plotlyjs, + config_file=self.config_file, + use_xvfb=self.use_xvfb, + ) + + +# Make config a singleton object +# ------------------------------ +config = OrcaConfig() +del OrcaConfig + + +# Orca status class +# ------------------------ +class OrcaStatus(object): + """ + Class to store information about the current status of the orca server. + """ + + _props = { + "state": "unvalidated", # or 'validated' or 'running' + "executable_list": None, + "version": None, + "pid": None, + "port": None, + "command": None, + } + + @property + def state(self): + """ + A string representing the state of the orca server process + + One of: + - unvalidated: The orca executable has not yet been searched for or + tested to make sure its valid. + - validated: The orca executable has been located and tested for + validity, but it is not running. + - running: The orca server process is currently running. + """ + return self._props["state"] + + @property + def executable(self): + """ + If the `state` property is 'validated' or 'running', this property + contains the full path to the orca executable. + + This path can be specified explicitly by setting the `executable` + property of the `plotly.io.orca.config` object. + + This property will be None if the `state` is 'unvalidated'. + """ + executable_list = self._props["executable_list"] + if executable_list is None: + return None + else: + return " ".join(executable_list) + + @property + def version(self): + """ + If the `state` property is 'validated' or 'running', this property + contains the version of the validated orca executable. + + This property will be None if the `state` is 'unvalidated'. + """ + return self._props["version"] + + @property + def pid(self): + """ + The process id of the orca server process, if any. This property + will be None if the `state` is not 'running'. + """ + return self._props["pid"] + + @property + def port(self): + """ + The port number that the orca server process is listening to, if any. + This property will be None if the `state` is not 'running'. + + This port can be specified explicitly by setting the `port` + property of the `plotly.io.orca.config` object. + """ + return self._props["port"] + + @property + def command(self): + """ + The command arguments used to launch the running orca server, if any. + This property will be None if the `state` is not 'running'. + """ + return self._props["command"] + + def __repr__(self): + """ + Display a nice representation of the current orca server status. + """ + return """\ +orca status +----------- + state: {state} + executable: {executable} + version: {version} + port: {port} + pid: {pid} + command: {command} + +""".format( + executable=self.executable, + version=self.version, + port=self.port, + pid=self.pid, + state=self.state, + command=self.command, + ) + + +# Make status a singleton object +# ------------------------------ +status = OrcaStatus() +del OrcaStatus + + +@contextmanager +def orca_env(): + """ + Context manager to clear and restore environment variables that are + problematic for orca to function properly + + NODE_OPTIONS: When this variable is set, orca >> plotly.io.orca.config.executable = '/path/to/orca' + +After updating this executable property, try the export operation again. +If it is successful then you may want to save this configuration so that it +will be applied automatically in future sessions. You can do this as follows: + + >>> plotly.io.orca.config.save() + +If you're still having trouble, feel free to ask for help on the forums at +https://community.plot.ly/c/api/python +""" + + # Try to find an executable + # ------------------------- + # Search for executable name or path in config.executable + executable = which(config.executable) + path = os.environ.get("PATH", os.defpath) + formatted_path = path.replace(os.pathsep, "\n ") + + if executable is None: + raise ValueError( + """ +The orca executable is required to export figures as static images, +but it could not be found on the system path. + +Searched for executable '{executable}' on the following path: + {formatted_path} + +{instructions}""".format( + executable=config.executable, + formatted_path=formatted_path, + instructions=install_location_instructions, + ) + ) + + # Check if we should run with Xvfb + # -------------------------------- + xvfb_args = [ + "--auto-servernum", + "--server-args", + "-screen 0 640x480x24 +extension RANDR +extension GLX", + executable, + ] + + if config.use_xvfb: + # Use xvfb + xvfb_run_executable = which("xvfb-run") + if not xvfb_run_executable: + raise ValueError( + """ +The plotly.io.orca.config.use_xvfb property is set to True, but the +xvfb-run executable could not be found on the system path. + +Searched for the executable 'xvfb-run' on the following path: + {formatted_path}""".format(formatted_path=formatted_path) + ) + + executable_list = [xvfb_run_executable] + xvfb_args + elif ( + config.use_xvfb == "auto" + and sys.platform.startswith("linux") + and not os.environ.get("DISPLAY") + and which("xvfb-run") + ): + # use_xvfb is 'auto', we're on linux without a display server, + # and xvfb-run is available. Use it. + xvfb_run_executable = which("xvfb-run") + executable_list = [xvfb_run_executable] + xvfb_args + else: + # Do not use xvfb + executable_list = [executable] + + # Run executable with --help and see if it's our orca + # --------------------------------------------------- + invalid_executable_msg = """ +The orca executable is required in order to export figures as static images, +but the executable that was found at '{executable}' +does not seem to be a valid plotly orca executable. Please refer to the end of +this message for details on what went wrong. + +{instructions}""".format( + executable=executable, instructions=install_location_instructions + ) + + # ### Run with Popen so we get access to stdout and stderr + with orca_env(): + p = subprocess.Popen( + executable_list + ["--help"], stdout=subprocess.PIPE, stderr=subprocess.PIPE + ) + + help_result, help_error = p.communicate() + + if p.returncode != 0: + err_msg = ( + invalid_executable_msg + + """ +Here is the error that was returned by the command + $ {executable} --help + +[Return code: {returncode}] +{err_msg} +""".format( + executable=" ".join(executable_list), + err_msg=help_error.decode("utf-8"), + returncode=p.returncode, + ) + ) + + # Check for Linux without X installed. + if sys.platform.startswith("linux") and not os.environ.get("DISPLAY"): + err_msg += """\ +Note: When used on Linux, orca requires an X11 display server, but none was +detected. Please install Xvfb and configure plotly.py to run orca using Xvfb +as follows: + + >>> import plotly.io as pio + >>> pio.orca.config.use_xvfb = True + +You can save this configuration for use in future sessions as follows: + + >>> pio.orca.config.save() + +See https://www.x.org/releases/X11R7.6/doc/man/man1/Xvfb.1.xhtml +for more info on Xvfb +""" + raise ValueError(err_msg) + + if not help_result: + raise ValueError( + invalid_executable_msg + + """ +The error encountered is that no output was returned by the command + $ {executable} --help +""".format(executable=" ".join(executable_list)) + ) + + if "Plotly's image-exporting utilities" not in help_result.decode("utf-8"): + raise ValueError( + invalid_executable_msg + + """ +The error encountered is that unexpected output was returned by the command + $ {executable} --help + +{help_result} +""".format(executable=" ".join(executable_list), help_result=help_result) + ) + + # Get orca version + # ---------------- + # ### Run with Popen so we get access to stdout and stderr + with orca_env(): + p = subprocess.Popen( + executable_list + ["--version"], + stdout=subprocess.PIPE, + stderr=subprocess.PIPE, + ) + + version_result, version_error = p.communicate() + + if p.returncode != 0: + raise ValueError( + invalid_executable_msg + + """ +An error occurred while trying to get the version of the orca executable. +Here is the command that plotly.py ran to request the version + $ {executable} --version + +This command returned the following error: + +[Return code: {returncode}] +{err_msg} + """.format( + executable=" ".join(executable_list), + err_msg=version_error.decode("utf-8"), + returncode=p.returncode, + ) + ) + + if not version_result: + raise ValueError( + invalid_executable_msg + + """ +The error encountered is that no version was reported by the orca executable. +Here is the command that plotly.py ran to request the version: + + $ {executable} --version +""".format(executable=" ".join(executable_list)) + ) + else: + version_result = version_result.decode() + + status._props["executable_list"] = executable_list + status._props["version"] = version_result.strip() + status._props["state"] = "validated" + + +def reset_status(): + """ + Shutdown the running orca server, if any, and reset the orca status + to unvalidated. + + This command is only needed if the desired orca executable is changed + during an interactive session. + + Returns + ------- + None + """ + shutdown_server() + status._props["executable_list"] = None + status._props["version"] = None + status._props["state"] = "unvalidated" + + +# Initialze process control variables +# ----------------------------------- +orca_lock = threading.Lock() +orca_state = {"proc": None, "shutdown_timer": None} + + +# Shutdown +# -------- +# The @atexit.register annotation ensures that the shutdown function is +# is run when the Python process is terminated +@atexit.register +def cleanup(): + shutdown_server() + + +def shutdown_server(): + """ + Shutdown the running orca server process, if any + + Returns + ------- + None + """ + # Use double-check locking to make sure the properties of orca_state + # are updated consistently across threads. + if orca_state["proc"] is not None: + with orca_lock: + if orca_state["proc"] is not None: + # We use psutil to kill all child processes of the main orca + # process. This prevents any zombie processes from being + # left over, and it saves us from needing to write + # OS-specific process management code here. + + parent = psutil.Process(orca_state["proc"].pid) + for child in parent.children(recursive=True): + try: + child.terminate() + except Exception: + # We tried, move on + pass + + try: + # Kill parent process + orca_state["proc"].terminate() + + # Wait for the process to shutdown + orca_state["proc"].wait() + except Exception: + # We tried, move on + pass + + # Update our internal process management state + orca_state["proc"] = None + + if orca_state["shutdown_timer"] is not None: + orca_state["shutdown_timer"].cancel() + orca_state["shutdown_timer"] = None + + orca_state["port"] = None + + # Update orca.status so the user has an accurate view + # of the state of the orca server + status._props["state"] = "validated" + status._props["pid"] = None + status._props["port"] = None + status._props["command"] = None + + +# Launch or get server +def ensure_server(): + """ + Start an orca server if none is running. If a server is already running, + then reset the timeout countdown + + Returns + ------- + None + """ + + # Validate psutil + if psutil is None: + raise ValueError( + """\ +Image generation requires the psutil package. + +Install using pip: + $ pip install psutil + +Install using conda: + $ conda install psutil +""" + ) + + # Validate requests + if not get_module("requests"): + raise ValueError( + """\ +Image generation requires the requests package. + +Install using pip: + $ pip install requests + +Install using conda: + $ conda install requests +""" + ) + + if not config.server_url: + # Validate orca executable only if server_url is not provided + if status.state == "unvalidated": + validate_executable() + # Acquire lock to make sure that we keep the properties of orca_state + # consistent across threads + with orca_lock: + # Cancel the current shutdown timer, if any + if orca_state["shutdown_timer"] is not None: + orca_state["shutdown_timer"].cancel() + + # Start a new server process if none is active + if orca_state["proc"] is None: + # Determine server port + if config.port is None: + orca_state["port"] = find_open_port() + else: + orca_state["port"] = config.port + + # Build orca command list + cmd_list = status._props["executable_list"] + [ + "serve", + "-p", + str(orca_state["port"]), + "--plotly", + config.plotlyjs, + "--graph-only", + ] + + if config.topojson: + cmd_list.extend(["--topojson", config.topojson]) + + if config.mathjax: + cmd_list.extend(["--mathjax", config.mathjax]) + + if config.mapbox_access_token: + cmd_list.extend( + ["--mapbox-access-token", config.mapbox_access_token] + ) + + # Create subprocess that launches the orca server on the + # specified port. + DEVNULL = open(os.devnull, "wb") + with orca_env(): + stderr = DEVNULL if "CI" in os.environ else None # fix for CI + orca_state["proc"] = subprocess.Popen( + cmd_list, stdout=DEVNULL, stderr=stderr + ) + + # Update orca.status so the user has an accurate view + # of the state of the orca server + status._props["state"] = "running" + status._props["pid"] = orca_state["proc"].pid + status._props["port"] = orca_state["port"] + status._props["command"] = cmd_list + + # Create new shutdown timer if a timeout was specified + if config.timeout is not None: + t = threading.Timer(config.timeout, shutdown_server) + # Make it a daemon thread so that exit won't wait for timer to + # complete + t.daemon = True + t.start() + orca_state["shutdown_timer"] = t + + +@retry(min_wait=5, max_wait=10, max_delay=60000) +def request_image_with_retrying(**kwargs): + """ + Helper method to perform an image request to a running orca server process + with retrying logic. + """ + from requests import post + from plotly.io.json import to_json_plotly + + if config.server_url: + server_url = config.server_url + else: + server_url = "http://{hostname}:{port}".format( + hostname="localhost", port=orca_state["port"] + ) + + request_params = {k: v for k, v in kwargs.items() if v is not None} + json_str = to_json_plotly(request_params) + response = post(server_url + "/", data=json_str) + + if response.status_code == 522: + # On "522: client socket timeout", return server and keep trying + shutdown_server() + ensure_server() + raise OSError("522: client socket timeout") + + return response + + +def to_image(fig, format=None, width=None, height=None, scale=None, validate=True): + """ + Convert a figure to a static image bytes string + + Parameters + ---------- + fig: + Figure object or dict representing a figure + + format: str or None + The desired image format. One of + - 'png' + - 'jpg' or 'jpeg' + - 'webp' + - 'svg' + - 'pdf' + - 'eps' (Requires the poppler library to be installed) + + If not specified, will default to `plotly.io.config.default_format` + + width: int or None + The width of the exported image in layout pixels. If the `scale` + property is 1.0, this will also be the width of the exported image + in physical pixels. + + If not specified, will default to `plotly.io.config.default_width` + + height: int or None + The height of the exported image in layout pixels. If the `scale` + property is 1.0, this will also be the height of the exported image + in physical pixels. + + If not specified, will default to `plotly.io.config.default_height` + + scale: int or float or None + The scale factor to use when exporting the figure. A scale factor + larger than 1.0 will increase the image resolution with respect + to the figure's layout pixel dimensions. Whereas as scale factor of + less than 1.0 will decrease the image resolution. + + If not specified, will default to `plotly.io.config.default_scale` + + validate: bool + True if the figure should be validated before being converted to + an image, False otherwise. + + Returns + ------- + bytes + The image data + """ + # Make sure orca sever is running + # ------------------------------- + ensure_server() + + # Handle defaults + # --------------- + # Apply configuration defaults to unspecified arguments + if format is None: + format = config.default_format + + format = validate_coerce_format(format) + + if scale is None: + scale = config.default_scale + + if width is None: + width = config.default_width + + if height is None: + height = config.default_height + + # Validate figure + # --------------- + fig_dict = validate_coerce_fig_to_dict(fig, validate) + + # Request image from server + # ------------------------- + try: + response = request_image_with_retrying( + figure=fig_dict, format=format, scale=scale, width=width, height=height + ) + except OSError: + # Get current status string + status_str = repr(status) + + if config.server_url: + raise ValueError( + """ +Plotly.py was unable to communicate with the orca server at {server_url} + +Please check that the server is running and accessible. +""".format(server_url=config.server_url) + ) + + else: + # Check if the orca server process exists + pid_exists = psutil.pid_exists(status.pid) + + # Raise error message based on whether the server process existed + if pid_exists: + raise ValueError( + """ +For some reason plotly.py was unable to communicate with the +local orca server process, even though the server process seems to be running. + +Please review the process and connection information below: + +{info} +""".format(info=status_str) + ) + else: + # Reset the status so that if the user tries again, we'll try to + # start the server again + reset_status() + raise ValueError( + """ +For some reason the orca server process is no longer running. + +Please review the process and connection information below: + +{info} +plotly.py will attempt to start the local server process again the next time +an image export operation is performed. +""".format(info=status_str) + ) + + # Check response + # -------------- + if response.status_code == 200: + # All good + return response.content + else: + # ### Something went wrong ### + err_message = """ +The image request was rejected by the orca conversion utility +with the following error: + {status}: {msg} +""".format(status=response.status_code, msg=response.content.decode("utf-8")) + + # ### Try to be helpful ### + # Status codes from /src/component/plotly-graph/constants.js in the + # orca code base. + # statusMsg: { + # 400: 'invalid or malformed request syntax', + # 522: client socket timeout + # 525: 'plotly.js error', + # 526: 'plotly.js version 1.11.0 or up required', + # 530: 'image conversion error' + # } + if response.status_code == 400 and isinstance(fig, dict) and not validate: + err_message += """ +Try setting the `validate` argument to True to check for errors in the +figure specification""" + elif response.status_code == 525: + any_mapbox = any( + [ + trace.get("type", None) == "scattermapbox" + for trace in fig_dict.get("data", []) + ] + ) + if any_mapbox and config.mapbox_access_token is None: + err_message += """ +Exporting scattermapbox traces requires a mapbox access token. +Create a token in your mapbox account and then set it using: + +>>> plotly.io.orca.config.mapbox_access_token = 'pk.abc...' + +If you would like this token to be applied automatically in +future sessions, then save your orca configuration as follows: + +>>> plotly.io.orca.config.save() +""" + elif response.status_code == 530 and format == "eps": + err_message += """ +Exporting to EPS format requires the poppler library. You can install +poppler on MacOS or Linux with: + + $ conda install poppler + +Or, you can install it on MacOS using homebrew with: + + $ brew install poppler + +Or, you can install it on Linux using your distribution's package manager to +install the 'poppler-utils' package. + +Unfortunately, we don't yet know of an easy way to install poppler on Windows. +""" + raise ValueError(err_message) + + +def write_image( + fig, file, format=None, scale=None, width=None, height=None, validate=True +): + """ + Convert a figure to a static image and write it to a file or writeable + object + + Parameters + ---------- + fig: + Figure object or dict representing a figure + + file: str or writeable + A string representing a local file path or a writeable object + (e.g. a pathlib.Path object or an open file descriptor) + + format: str or None + The desired image format. One of + - 'png' + - 'jpg' or 'jpeg' + - 'webp' + - 'svg' + - 'pdf' + - 'eps' (Requires the poppler library to be installed) + + If not specified and `file` is a string then this will default to the + file extension. If not specified and `file` is not a string then this + will default to `plotly.io.config.default_format` + + width: int or None + The width of the exported image in layout pixels. If the `scale` + property is 1.0, this will also be the width of the exported image + in physical pixels. + + If not specified, will default to `plotly.io.config.default_width` + + height: int or None + The height of the exported image in layout pixels. If the `scale` + property is 1.0, this will also be the height of the exported image + in physical pixels. + + If not specified, will default to `plotly.io.config.default_height` + + scale: int or float or None + The scale factor to use when exporting the figure. A scale factor + larger than 1.0 will increase the image resolution with respect + to the figure's layout pixel dimensions. Whereas as scale factor of + less than 1.0 will decrease the image resolution. + + If not specified, will default to `plotly.io.config.default_scale` + + validate: bool + True if the figure should be validated before being converted to + an image, False otherwise. + + Returns + ------- + None + """ + + # Try to cast `file` as a pathlib object `path`. + # ---------------------------------------------- + if isinstance(file, str): + # Use the standard Path constructor to make a pathlib object. + path = Path(file) + elif isinstance(file, Path): + # `file` is already a Path object. + path = file + else: + # We could not make a Path object out of file. Either `file` is an open file + # descriptor with a `write()` method or it's an invalid object. + path = None + + # Infer format if not specified + # ----------------------------- + if path is not None and format is None: + ext = path.suffix + if ext: + format = ext.lstrip(".") + else: + raise ValueError( + """ +Cannot infer image type from output path '{file}'. +Please add a file extension or specify the type using the format parameter. +For example: + + >>> import plotly.io as pio + >>> pio.write_image(fig, file_path, format='png') +""".format(file=file) + ) + + # Request image + # ------------- + # Do this first so we don't create a file if image conversion fails + img_data = to_image( + fig, format=format, scale=scale, width=width, height=height, validate=validate + ) + + # Open file + # --------- + if path is None: + # We previously failed to make sense of `file` as a pathlib object. + # Attempt to write to `file` as an open file descriptor. + try: + file.write(img_data) + return + except AttributeError: + pass + raise ValueError( + """ +The 'file' argument '{file}' is not a string, pathlib.Path object, or file descriptor. +""".format(file=file) + ) + else: + # We previously succeeded in interpreting `file` as a pathlib object. + # Now we can use `write_bytes()`. + path.write_bytes(img_data) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/_renderers.py b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_renderers.py new file mode 100644 index 0000000000000000000000000000000000000000..4c21760bb0aa264b21096bb9869f478af3cd15f8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_renderers.py @@ -0,0 +1,567 @@ +import textwrap +from copy import copy +import os +from packaging.version import Version +import warnings + +from plotly import optional_imports + +from plotly.io._base_renderers import ( + MimetypeRenderer, + ExternalRenderer, + PlotlyRenderer, + NotebookRenderer, + KaggleRenderer, + AzureRenderer, + ColabRenderer, + JsonRenderer, + PngRenderer, + JpegRenderer, + SvgRenderer, + PdfRenderer, + BrowserRenderer, + IFrameRenderer, + SphinxGalleryHtmlRenderer, + SphinxGalleryOrcaRenderer, + CoCalcRenderer, + DatabricksRenderer, +) +from plotly.io._utils import validate_coerce_fig_to_dict + +ipython = optional_imports.get_module("IPython") +ipython_display = optional_imports.get_module("IPython.display") +nbformat = optional_imports.get_module("nbformat") + + +def display_jupyter_version_warnings(): + parent_process = None + try: + psutil = optional_imports.get_module("psutil") + if psutil is not None: + parent_process = psutil.Process().parent().cmdline()[-1] + except Exception: + pass + + if parent_process is None: + return + elif "jupyter-notebook" in parent_process: + jupyter_notebook = optional_imports.get_module("notebook") + if jupyter_notebook is not None and jupyter_notebook.__version__ < "7": + # Add warning about upgrading notebook + warnings.warn( + f"Plotly version >= 6 requires Jupyter Notebook >= 7 but you have {jupyter_notebook.__version__} installed.\n To upgrade Jupyter Notebook, please run `pip install notebook --upgrade`." + ) + elif "jupyter-lab" in parent_process: + jupyter_lab = optional_imports.get_module("jupyterlab") + if jupyter_lab is not None and jupyter_lab.__version__ < "3": + # Add warning about upgrading jupyterlab + warnings.warn( + f"Plotly version >= 6 requires JupyterLab >= 3 but you have {jupyter_lab.__version__} installed. To upgrade JupyterLab, please run `pip install jupyterlab --upgrade`." + ) + + +# Renderer configuration class +# ----------------------------- +class RenderersConfig(object): + """ + Singleton object containing the current renderer configurations + """ + + def __init__(self): + self._renderers = {} + self._default_name = None + self._default_renderers = [] + self._render_on_display = False + self._to_activate = [] + + # ### Magic methods ### + # Make this act as a dict of renderers + def __len__(self): + return len(self._renderers) + + def __contains__(self, item): + return item in self._renderers + + def __iter__(self): + return iter(self._renderers) + + def __getitem__(self, item): + renderer = self._renderers[item] + return renderer + + def __setitem__(self, key, value): + if not isinstance(value, (MimetypeRenderer, ExternalRenderer)): + raise ValueError( + """\ +Renderer must be a subclass of MimetypeRenderer or ExternalRenderer. + Received value with type: {typ}""".format(typ=type(value)) + ) + + self._renderers[key] = value + + def __delitem__(self, key): + # Remove template + del self._renderers[key] + + # Check if we need to remove it as the default + if self._default == key: + self._default = None + + def keys(self): + return self._renderers.keys() + + def items(self): + return self._renderers.items() + + def update(self, d={}, **kwargs): + """ + Update one or more renderers from a dict or from input keyword + arguments. + + Parameters + ---------- + d: dict + Dictionary from renderer names to new renderer objects. + + kwargs + Named argument value pairs where the name is a renderer name + and the value is a new renderer object + """ + for k, v in dict(d, **kwargs).items(): + self[k] = v + + # ### Properties ### + @property + def default(self): + """ + The default renderer, or None if no there is no default + + If not None, the default renderer is used to render + figures when the `plotly.io.show` function is called on a Figure. + + If `plotly.io.renderers.render_on_display` is True, then the default + renderer will also be used to display Figures automatically when + displayed in the Jupyter Notebook + + Multiple renderers may be registered by separating their names with + '+' characters. For example, to specify rendering compatible with + the classic Jupyter Notebook, JupyterLab, and PDF export: + + >>> import plotly.io as pio + >>> pio.renderers.default = 'notebook+jupyterlab+pdf' + + The names of available renderers may be retrieved with: + + >>> import plotly.io as pio + >>> list(pio.renderers) + + Returns + ------- + str + """ + return self._default_name + + @default.setter + def default(self, value): + # Handle None + if not value: + # _default_name should always be a string so we can do + # pio.renderers.default.split('+') + self._default_name = "" + self._default_renderers = [] + return + + # Store defaults name and list of renderer(s) + renderer_names = self._validate_coerce_renderers(value) + self._default_name = value + self._default_renderers = [self[name] for name in renderer_names] + + # Register renderers for activation before their next use + self._to_activate = list(self._default_renderers) + + @property + def render_on_display(self): + """ + If True, the default mimetype renderers will be used to render + figures when they are displayed in an IPython context. + + Returns + ------- + bool + """ + return self._render_on_display + + @render_on_display.setter + def render_on_display(self, val): + self._render_on_display = bool(val) + + def _activate_pending_renderers(self, cls=object): + """ + Activate all renderers that are waiting in the _to_activate list + + Parameters + ---------- + cls + Only activate renders that are subclasses of this class + """ + to_activate_with_cls = [ + r for r in self._to_activate if cls and isinstance(r, cls) + ] + + while to_activate_with_cls: + # Activate renderers from left to right so that right-most + # renderers take precedence + renderer = to_activate_with_cls.pop(0) + renderer.activate() + + self._to_activate = [ + r for r in self._to_activate if not (cls and isinstance(r, cls)) + ] + + def _validate_coerce_renderers(self, renderers_string): + """ + Input a string and validate that it contains the names of one or more + valid renderers separated on '+' characters. If valid, return + a list of the renderer names + + Parameters + ---------- + renderers_string: str + + Returns + ------- + list of str + """ + # Validate value + if not isinstance(renderers_string, str): + raise ValueError("Renderer must be specified as a string") + + renderer_names = renderers_string.split("+") + invalid = [name for name in renderer_names if name not in self] + if invalid: + raise ValueError( + """ +Invalid named renderer(s) received: {}""".format(str(invalid)) + ) + + return renderer_names + + def __repr__(self): + return """\ +Renderers configuration +----------------------- + Default renderer: {default} + Available renderers: +{available} +""".format(default=repr(self.default), available=self._available_renderers_str()) + + def _available_renderers_str(self): + """ + Return nicely wrapped string representation of all + available renderer names + """ + available = "\n".join( + textwrap.wrap( + repr(list(self)), + width=79 - 8, + initial_indent=" " * 8, + subsequent_indent=" " * 9, + ) + ) + return available + + def _build_mime_bundle(self, fig_dict, renderers_string=None, **kwargs): + """ + Build a mime bundle dict containing a kev/value pair for each + MimetypeRenderer specified in either the default renderer string, + or in the supplied renderers_string argument. + + Note that this method skips any renderers that are not subclasses + of MimetypeRenderer. + + Parameters + ---------- + fig_dict: dict + Figure dictionary + renderers_string: str or None (default None) + Renderer string to process rather than the current default + renderer string + + Returns + ------- + dict + """ + if renderers_string: + renderer_names = self._validate_coerce_renderers(renderers_string) + renderers_list = [self[name] for name in renderer_names] + + # Activate these non-default renderers + for renderer in renderers_list: + if isinstance(renderer, MimetypeRenderer): + renderer.activate() + else: + # Activate any pending default renderers + self._activate_pending_renderers(cls=MimetypeRenderer) + renderers_list = self._default_renderers + + bundle = {} + for renderer in renderers_list: + if isinstance(renderer, MimetypeRenderer): + renderer = copy(renderer) + for k, v in kwargs.items(): + if hasattr(renderer, k): + setattr(renderer, k, v) + + bundle.update(renderer.to_mimebundle(fig_dict)) + + return bundle + + def _perform_external_rendering(self, fig_dict, renderers_string=None, **kwargs): + """ + Perform external rendering for each ExternalRenderer specified + in either the default renderer string, or in the supplied + renderers_string argument. + + Note that this method skips any renderers that are not subclasses + of ExternalRenderer. + + Parameters + ---------- + fig_dict: dict + Figure dictionary + renderers_string: str or None (default None) + Renderer string to process rather than the current default + renderer string + + Returns + ------- + None + """ + if renderers_string: + renderer_names = self._validate_coerce_renderers(renderers_string) + renderers_list = [self[name] for name in renderer_names] + + # Activate these non-default renderers + for renderer in renderers_list: + if isinstance(renderer, ExternalRenderer): + renderer.activate() + else: + self._activate_pending_renderers(cls=ExternalRenderer) + renderers_list = self._default_renderers + + for renderer in renderers_list: + if isinstance(renderer, ExternalRenderer): + renderer = copy(renderer) + for k, v in kwargs.items(): + if hasattr(renderer, k): + setattr(renderer, k, v) + + renderer.render(fig_dict) + + +# Make renderers a singleton object +# --------------------------------- +renderers = RenderersConfig() +del RenderersConfig + + +# Show +def show(fig, renderer=None, validate=True, **kwargs): + """ + Show a figure using either the default renderer(s) or the renderer(s) + specified by the renderer argument + + Parameters + ---------- + fig: dict of Figure + The Figure object or figure dict to display + + renderer: str or None (default None) + A string containing the names of one or more registered renderers + (separated by '+' characters) or None. If None, then the default + renderers specified in plotly.io.renderers.default are used. + + validate: bool (default True) + True if the figure should be validated before being shown, + False otherwise. + + width: int or float + An integer or float that determines the number of pixels wide the + plot is. The default is set in plotly.js. + + height: int or float + An integer or float specifying the height of the plot in pixels. + The default is set in plotly.js. + + config: dict + A dict of parameters to configure the figure. The defaults are set + in plotly.js. + + Returns + ------- + None + """ + fig_dict = validate_coerce_fig_to_dict(fig, validate) + + # Mimetype renderers + bundle = renderers._build_mime_bundle(fig_dict, renderers_string=renderer, **kwargs) + if bundle: + if not ipython_display: + raise ValueError( + "Mime type rendering requires ipython but it is not installed" + ) + + if not nbformat or Version(nbformat.__version__) < Version("4.2.0"): + raise ValueError( + "Mime type rendering requires nbformat>=4.2.0 but it is not installed" + ) + + display_jupyter_version_warnings() + + ipython_display.display(bundle, raw=True) + + # external renderers + renderers._perform_external_rendering(fig_dict, renderers_string=renderer, **kwargs) + + +# Register renderers +# ------------------ + +# Plotly mime type +plotly_renderer = PlotlyRenderer() +renderers["plotly_mimetype"] = plotly_renderer +renderers["jupyterlab"] = plotly_renderer +renderers["nteract"] = plotly_renderer +renderers["vscode"] = plotly_renderer + +# HTML-based +config = {} +renderers["notebook"] = NotebookRenderer(config=config) +renderers["notebook_connected"] = NotebookRenderer(config=config, connected=True) +renderers["kaggle"] = KaggleRenderer(config=config) +renderers["azure"] = AzureRenderer(config=config) +renderers["colab"] = ColabRenderer(config=config) +renderers["cocalc"] = CoCalcRenderer() +renderers["databricks"] = DatabricksRenderer() + +# JSON +renderers["json"] = JsonRenderer() + +# Static Image +renderers["png"] = PngRenderer() +jpeg_renderer = JpegRenderer() +renderers["jpeg"] = jpeg_renderer +renderers["jpg"] = jpeg_renderer +renderers["svg"] = SvgRenderer() +renderers["pdf"] = PdfRenderer() + +# External +renderers["browser"] = BrowserRenderer(config=config) +renderers["firefox"] = BrowserRenderer(config=config, using=("firefox")) +renderers["chrome"] = BrowserRenderer(config=config, using=("chrome", "google-chrome")) +renderers["chromium"] = BrowserRenderer( + config=config, using=("chromium", "chromium-browser") +) +renderers["iframe"] = IFrameRenderer(config=config, include_plotlyjs=True) +renderers["iframe_connected"] = IFrameRenderer(config=config, include_plotlyjs="cdn") +renderers["sphinx_gallery"] = SphinxGalleryHtmlRenderer() +renderers["sphinx_gallery_png"] = SphinxGalleryOrcaRenderer() + +# Set default renderer +# -------------------- +# Version 4 renderer configuration +default_renderer = None + +# Handle the PLOTLY_RENDERER environment variable +env_renderer = os.environ.get("PLOTLY_RENDERER", None) +if env_renderer: + try: + renderers._validate_coerce_renderers(env_renderer) + except ValueError: + raise ValueError( + """ +Invalid named renderer(s) specified in the 'PLOTLY_RENDERER' +environment variable: {env_renderer}""".format(env_renderer=env_renderer) + ) + + default_renderer = env_renderer +elif ipython and ipython.get_ipython(): + # Try to detect environment so that we can enable a useful + # default renderer + if not default_renderer: + try: + import google.colab # noqa: F401 + + default_renderer = "colab" + except ImportError: + pass + + # Check if we're running in a Kaggle notebook + if not default_renderer and os.path.exists("/kaggle/input"): + default_renderer = "kaggle" + + # Check if we're running in an Azure Notebook + if not default_renderer and "AZURE_NOTEBOOKS_HOST" in os.environ: + default_renderer = "azure" + + # Check if we're running in VSCode + if not default_renderer and "VSCODE_PID" in os.environ: + default_renderer = "vscode" + + # Check if we're running in nteract + if not default_renderer and "NTERACT_EXE" in os.environ: + default_renderer = "nteract" + + # Check if we're running in CoCalc + if not default_renderer and "COCALC_PROJECT_ID" in os.environ: + default_renderer = "cocalc" + + if not default_renderer and "DATABRICKS_RUNTIME_VERSION" in os.environ: + default_renderer = "databricks" + + # Check if we're running in spyder and orca is installed + if not default_renderer and "SPYDER_ARGS" in os.environ: + try: + from plotly.io.orca import validate_executable + + validate_executable() + default_renderer = "svg" + except ValueError: + # orca not found + pass + + # Check if we're running in ipython terminal + ipython_info = ipython.get_ipython() + shell = ipython_info.__class__.__name__ + if not default_renderer and (shell == "TerminalInteractiveShell"): + default_renderer = "browser" + + # Check if we're running in a Jupyter notebook or JupyterLab + if ( + not default_renderer + and (shell == "ZMQInteractiveShell") + and (type(ipython_info).__module__.startswith("ipykernel.")) + ): + default_renderer = "plotly_mimetype" + + # Fallback to renderer combination that will work automatically + # in the jupyter notebook, jupyterlab, nteract, vscode, and + # nbconvert HTML export. + if not default_renderer: + default_renderer = "plotly_mimetype+notebook" +else: + # If ipython isn't available, try to display figures in the default + # browser + try: + import webbrowser + + webbrowser.get() + default_renderer = "browser" + except Exception: + # Many things could have gone wrong + # There could not be a webbrowser Python module, + # or the module may be a dumb placeholder + pass + +renderers.render_on_display = True +renderers.default = default_renderer diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/_sg_scraper.py b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_sg_scraper.py new file mode 100644 index 0000000000000000000000000000000000000000..af15b7d1c3317c173859749df2259e4b8c19037b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_sg_scraper.py @@ -0,0 +1,100 @@ +# This module defines an image scraper for sphinx-gallery +# https://sphinx-gallery.github.io/ +# which can be used by projects using plotly in their documentation. +from glob import glob +import os +import shutil + +import plotly + +plotly.io.renderers.default = "sphinx_gallery_png" + + +def plotly_sg_scraper(block, block_vars, gallery_conf, **kwargs): + """Scrape Plotly figures for galleries of examples using + sphinx-gallery. + + Examples should use ``plotly.io.show()`` to display the figure with + the custom sphinx_gallery renderer. + + Since the sphinx_gallery renderer generates both html and static png + files, we simply crawl these files and give them the appropriate path. + + Parameters + ---------- + block : tuple + A tuple containing the (label, content, line_number) of the block. + block_vars : dict + Dict of block variables. + gallery_conf : dict + Contains the configuration of Sphinx-Gallery + **kwargs : dict + Additional keyword arguments to pass to + :meth:`~matplotlib.figure.Figure.savefig`, e.g. ``format='svg'``. + The ``format`` kwarg in particular is used to set the file extension + of the output file (currently only 'png' and 'svg' are supported). + + Returns + ------- + rst : str + The ReSTructuredText that will be rendered to HTML containing + the images. + + Notes + ----- + Add this function to the image scrapers + """ + examples_dir = os.path.dirname(block_vars["src_file"]) + pngs = sorted(glob(os.path.join(examples_dir, "*.png"))) + htmls = sorted(glob(os.path.join(examples_dir, "*.html"))) + image_path_iterator = block_vars["image_path_iterator"] + image_names = list() + seen = set() + for html, png in zip(htmls, pngs): + if png not in seen: + seen |= set(png) + this_image_path_png = next(image_path_iterator) + this_image_path_html = os.path.splitext(this_image_path_png)[0] + ".html" + image_names.append(this_image_path_html) + shutil.move(png, this_image_path_png) + shutil.move(html, this_image_path_html) + # Use the `figure_rst` helper function to generate rST for image files + return figure_rst(image_names, gallery_conf["src_dir"]) + + +def figure_rst(figure_list, sources_dir): + """Generate RST for a list of PNG filenames. + + Depending on whether we have one or more figures, we use a + single rst call to 'image' or a horizontal list. + + Parameters + ---------- + figure_list : list + List of strings of the figures' absolute paths. + sources_dir : str + absolute path of Sphinx documentation sources + + Returns + ------- + images_rst : str + rst code to embed the images in the document + """ + + figure_paths = [ + os.path.relpath(figure_path, sources_dir).replace(os.sep, "/").lstrip("/") + for figure_path in figure_list + ] + images_rst = "" + if not figure_paths: + return images_rst + figure_name = figure_paths[0] + figure_path = os.path.join("images", os.path.basename(figure_name)) + images_rst = SINGLE_HTML % figure_path + return images_rst + + +SINGLE_HTML = """ +.. raw:: html + :file: %s +""" diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/_templates.py b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_templates.py new file mode 100644 index 0000000000000000000000000000000000000000..160ee7c4075aa9993eeaebe00fd3e32a2321c780 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_templates.py @@ -0,0 +1,492 @@ +import textwrap +import pkgutil + +import copy +import os +import json +from functools import reduce + +try: + from math import gcd +except ImportError: + # Python 2 + from fractions import gcd + +# Create Lazy sentinal object to indicate that a template should be loaded +# on-demand from package_data +Lazy = object() + + +# Templates configuration class +# ----------------------------- +class TemplatesConfig(object): + """ + Singleton object containing the current figure templates (aka themes) + """ + + def __init__(self): + # Initialize properties dict + self._templates = {} + + # Initialize built-in templates + default_templates = [ + "ggplot2", + "seaborn", + "simple_white", + "plotly", + "plotly_white", + "plotly_dark", + "presentation", + "xgridoff", + "ygridoff", + "gridon", + "none", + ] + + for template_name in default_templates: + self._templates[template_name] = Lazy + + self._validator = None + self._default = None + + # ### Magic methods ### + # Make this act as a dict of templates + def __len__(self): + return len(self._templates) + + def __contains__(self, item): + return item in self._templates + + def __iter__(self): + return iter(self._templates) + + def __getitem__(self, item): + if isinstance(item, str): + template_names = item.split("+") + else: + template_names = [item] + + templates = [] + for template_name in template_names: + template = self._templates[template_name] + if template is Lazy: + from plotly.graph_objs.layout import Template + + if template_name == "none": + # "none" is a special built-in named template that applied no defaults + template = Template(data_scatter=[{}]) + self._templates[template_name] = template + else: + # Load template from package data + path = os.path.join( + "package_data", "templates", template_name + ".json" + ) + template_str = pkgutil.get_data("plotly", path).decode("utf-8") + template_dict = json.loads(template_str) + template = Template(template_dict, _validate=False) + + self._templates[template_name] = template + templates.append(self._templates[template_name]) + + return self.merge_templates(*templates) + + def __setitem__(self, key, value): + self._templates[key] = self._validate(value) + + def __delitem__(self, key): + # Remove template + del self._templates[key] + + # Check if we need to remove it as the default + if self._default == key: + self._default = None + + def _validate(self, value): + if not self._validator: + from plotly.validator_cache import ValidatorCache + + self._validator = ValidatorCache.get_validator("layout", "template") + + return self._validator.validate_coerce(value) + + def keys(self): + return self._templates.keys() + + def items(self): + return self._templates.items() + + def update(self, d={}, **kwargs): + """ + Update one or more templates from a dict or from input keyword + arguments. + + Parameters + ---------- + d: dict + Dictionary from template names to new template values. + + kwargs + Named argument value pairs where the name is a template name + and the value is a new template value. + """ + for k, v in dict(d, **kwargs).items(): + self[k] = v + + # ### Properties ### + @property + def default(self): + """ + The name of the default template, or None if no there is no default + + If not None, the default template is automatically applied to all + figures during figure construction if no explicit template is + specified. + + The names of available templates may be retrieved with: + + >>> import plotly.io as pio + >>> list(pio.templates) + + Returns + ------- + str + """ + return self._default + + @default.setter + def default(self, value): + # Validate value + # Could be a Template object, the key of a registered template, + # Or a string containing the names of multiple templates joined on + # '+' characters + self._validate(value) + self._default = value + + def __repr__(self): + return """\ +Templates configuration +----------------------- + Default template: {default} + Available templates: +{available} +""".format(default=repr(self.default), available=self._available_templates_str()) + + def _available_templates_str(self): + """ + Return nicely wrapped string representation of all + available template names + """ + available = "\n".join( + textwrap.wrap( + repr(list(self)), + width=79 - 8, + initial_indent=" " * 8, + subsequent_indent=" " * 9, + ) + ) + return available + + def merge_templates(self, *args): + """ + Merge a collection of templates into a single combined template. + Templates are process from left to right so if multiple templates + specify the same propery, the right-most template will take + precedence. + + Parameters + ---------- + args: list of Template + Zero or more template objects (or dicts with compatible properties) + + Returns + ------- + template: + A combined template object + + Examples + -------- + + >>> pio.templates.merge_templates( + ... go.layout.Template(layout={'font': {'size': 20}}), + ... go.layout.Template(data={'scatter': [{'mode': 'markers'}]}), + ... go.layout.Template(layout={'font': {'family': 'Courier'}})) + layout.Template({ + 'data': {'scatter': [{'mode': 'markers', 'type': 'scatter'}]}, + 'layout': {'font': {'family': 'Courier', 'size': 20}} + }) + """ + if args: + return reduce(self._merge_2_templates, args) + else: + from plotly.graph_objs.layout import Template + + return Template() + + def _merge_2_templates(self, template1, template2): + """ + Helper function for merge_templates that merges exactly two templates + + Parameters + ---------- + template1: Template + template2: Template + + Returns + ------- + Template: + merged template + """ + # Validate/copy input templates + result = self._validate(template1) + other = self._validate(template2) + + # Cycle traces + for trace_type in result.data: + result_traces = result.data[trace_type] + other_traces = other.data[trace_type] + + if result_traces and other_traces: + lcm = ( + len(result_traces) + * len(other_traces) + // gcd(len(result_traces), len(other_traces)) + ) + + # Cycle result traces + result.data[trace_type] = result_traces * (lcm // len(result_traces)) + + # Cycle other traces + other.data[trace_type] = other_traces * (lcm // len(other_traces)) + + # Perform update + result.update(other) + + return result + + +# Make config a singleton object +# ------------------------------ +templates = TemplatesConfig() +del TemplatesConfig + + +# Template utilities +# ------------------ +def walk_push_to_template(fig_obj, template_obj, skip): + """ + Move style properties from fig_obj to template_obj. + + Parameters + ---------- + fig_obj: plotly.basedatatypes.BasePlotlyType + template_obj: plotly.basedatatypes.BasePlotlyType + skip: set of str + Set of names of properties to skip + """ + from _plotly_utils.basevalidators import ( + CompoundValidator, + CompoundArrayValidator, + is_array, + ) + + for prop in list(fig_obj._props): + if prop == "template" or prop in skip: + # Avoid infinite recursion + continue + + fig_val = fig_obj[prop] + template_val = template_obj[prop] + + validator = fig_obj._get_validator(prop) + + if isinstance(validator, CompoundValidator): + walk_push_to_template(fig_val, template_val, skip) + if not fig_val._props: + # Check if we can remove prop itself + fig_obj[prop] = None + elif isinstance(validator, CompoundArrayValidator) and fig_val: + template_elements = list(template_val) + template_element_names = [el.name for el in template_elements] + template_propdefaults = template_obj[prop[:-1] + "defaults"] + + for fig_el in fig_val: + element_name = fig_el.name + if element_name: + # No properties are skipped inside a named array element + skip = set() + if fig_el.name in template_element_names: + item_index = template_element_names.index(fig_el.name) + template_el = template_elements[item_index] + walk_push_to_template(fig_el, template_el, skip) + else: + template_el = fig_el.__class__() + walk_push_to_template(fig_el, template_el, skip) + template_elements.append(template_el) + template_element_names.append(fig_el.name) + + # Restore element name + # since it was pushed to template above + fig_el.name = element_name + else: + walk_push_to_template(fig_el, template_propdefaults, skip) + + template_obj[prop] = template_elements + + elif not validator.array_ok or not is_array(fig_val): + # Move property value from figure to template + template_obj[prop] = fig_val + try: + fig_obj[prop] = None + except ValueError: + # Property cannot be set to None, move on. + pass + + +def to_templated(fig, skip=("title", "text")): + """ + Return a copy of a figure where all styling properties have been moved + into the figure's template. The template property of the resulting figure + may then be used to set the default styling of other figures. + + Parameters + ---------- + fig + Figure object or dict representing a figure + skip + A collection of names of properties to skip when moving properties to + the template. Defaults to ('title', 'text') so that the text + of figure titles, axis titles, and annotations does not become part of + the template + + Examples + -------- + Imports + + >>> import plotly.graph_objs as go + >>> import plotly.io as pio + + Construct a figure with large courier text + + >>> fig = go.Figure(layout={'title': 'Figure Title', + ... 'font': {'size': 20, 'family': 'Courier'}, + ... 'template':"none"}) + >>> fig # doctest: +NORMALIZE_WHITESPACE + Figure({ + 'data': [], + 'layout': {'font': {'family': 'Courier', 'size': 20}, + 'template': '...', 'title': {'text': 'Figure Title'}} + }) + + Convert to a figure with a template. Note how the 'font' properties have + been moved into the template property. + + >>> templated_fig = pio.to_templated(fig) + >>> templated_fig.layout.template + layout.Template({ + 'layout': {'font': {'family': 'Courier', 'size': 20}} + }) + >>> templated_fig + Figure({ + 'data': [], 'layout': {'template': '...', 'title': {'text': 'Figure Title'}} + }) + + + Next create a new figure with this template + + >>> fig2 = go.Figure(layout={ + ... 'title': 'Figure 2 Title', + ... 'template': templated_fig.layout.template}) + >>> fig2.layout.template + layout.Template({ + 'layout': {'font': {'family': 'Courier', 'size': 20}} + }) + + The default font in fig2 will now be size 20 Courier. + + Next, register as a named template... + + >>> pio.templates['large_courier'] = templated_fig.layout.template + + and specify this template by name when constructing a figure. + + >>> go.Figure(layout={ + ... 'title': 'Figure 3 Title', + ... 'template': 'large_courier'}) # doctest: +ELLIPSIS + Figure(...) + + Finally, set this as the default template to be applied to all new figures + + >>> pio.templates.default = 'large_courier' + >>> fig = go.Figure(layout={'title': 'Figure 4 Title'}) + >>> fig.layout.template + layout.Template({ + 'layout': {'font': {'family': 'Courier', 'size': 20}} + }) + + Returns + ------- + go.Figure + """ + + # process fig + from plotly.basedatatypes import BaseFigure + from plotly.graph_objs import Figure + + if not isinstance(fig, BaseFigure): + fig = Figure(fig) + + # Process skip + if not skip: + skip = set() + else: + skip = set(skip) + + # Always skip uids + skip.add("uid") + + # Initialize templated figure with deep copy of input figure + templated_fig = copy.deepcopy(fig) + + # Handle layout + walk_push_to_template( + templated_fig.layout, templated_fig.layout.template.layout, skip=skip + ) + + # Handle traces + trace_type_indexes = {} + for trace in list(templated_fig.data): + template_index = trace_type_indexes.get(trace.type, 0) + + # Extend template traces if necessary + template_traces = list(templated_fig.layout.template.data[trace.type]) + while len(template_traces) <= template_index: + # Append empty trace + template_traces.append(trace.__class__()) + + # Get corresponding template trace + template_trace = template_traces[template_index] + + # Perform push properties to template + walk_push_to_template(trace, template_trace, skip=skip) + + # Update template traces in templated_fig + templated_fig.layout.template.data[trace.type] = template_traces + + # Update trace_type_indexes + trace_type_indexes[trace.type] = template_index + 1 + + # Remove useless trace arrays + any_non_empty = False + for trace_type in templated_fig.layout.template.data: + traces = templated_fig.layout.template.data[trace_type] + is_empty = [trace.to_plotly_json() == {"type": trace_type} for trace in traces] + if all(is_empty): + templated_fig.layout.template.data[trace_type] = None + else: + any_non_empty = True + + # Check if we can remove the data altogether key + if not any_non_empty: + templated_fig.layout.template.data = None + + return templated_fig diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/_utils.py b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..4d27e0326c07ecef8890239429399a5991df56db --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/io/_utils.py @@ -0,0 +1,93 @@ +from typing import List + +import plotly +import plotly.graph_objs as go +from plotly.offline import get_plotlyjs_version + + +def validate_coerce_fig_to_dict(fig, validate): + from plotly.basedatatypes import BaseFigure + + if isinstance(fig, BaseFigure): + fig_dict = fig.to_dict() + elif isinstance(fig, dict): + if validate: + # This will raise an exception if fig is not a valid plotly figure + fig_dict = plotly.graph_objs.Figure(fig).to_plotly_json() + else: + fig_dict = fig + elif hasattr(fig, "to_plotly_json"): + fig_dict = fig.to_plotly_json() + else: + raise ValueError( + """ +The fig parameter must be a dict or Figure. + Received value of type {typ}: {v}""".format(typ=type(fig), v=fig) + ) + return fig_dict + + +def validate_coerce_output_type(output_type): + if output_type == "Figure" or output_type == go.Figure: + cls = go.Figure + elif output_type == "FigureWidget" or ( + hasattr(go, "FigureWidget") and output_type == go.FigureWidget + ): + cls = go.FigureWidget + else: + raise ValueError( + """ +Invalid output type: {output_type} + Must be one of: 'Figure', 'FigureWidget'""" + ) + return cls + + +def broadcast_args_to_dicts(**kwargs: dict) -> List[dict]: + """ + Given one or more keyword arguments which may be either a single value or a list of values, + return a list of keyword dictionaries by broadcasting the single valuesacross all the dicts. + If more than one item in the input is a list, all lists must be the same length. + + Parameters + ---------- + **kwargs: dict + The keyword arguments + + Returns + ------- + list of dicts + A list of dictionaries + + Raises + ------ + ValueError + If any of the input lists are not the same length + """ + # Check that all list arguments have the same length, + # and find out what that length is + # If there are no list arguments, length is 1 + list_lengths = [len(v) for v in tuple(kwargs.values()) if isinstance(v, list)] + if list_lengths and len(set(list_lengths)) > 1: + raise ValueError("All list arguments must have the same length.") + list_length = list_lengths[0] if list_lengths else 1 + + # Expand all arguments to lists of the same length + expanded_kwargs = { + k: [v] * list_length if not isinstance(v, list) else v + for k, v in kwargs.items() + } + # Reshape into a list of dictionaries + # Each dictionary represents the keyword arguments for a single function call + list_of_kwargs = [ + {k: v[i] for k, v in expanded_kwargs.items()} for i in range(list_length) + ] + + return list_of_kwargs + + +def plotly_cdn_url(cdn_ver=get_plotlyjs_version()): + """Return a valid plotly CDN url.""" + return "https://cdn.plot.ly/plotly-{cdn_ver}.min.js".format( + cdn_ver=cdn_ver, + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/base_renderers.py b/.venv_haddock/lib/python3.12/site-packages/plotly/io/base_renderers.py new file mode 100644 index 0000000000000000000000000000000000000000..78c1d86b440b22321a86bdb53ce2eb6ba06c2392 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/io/base_renderers.py @@ -0,0 +1,17 @@ +# ruff: noqa: F401 +from ._base_renderers import ( + MimetypeRenderer, + PlotlyRenderer, + JsonRenderer, + ImageRenderer, + PngRenderer, + SvgRenderer, + PdfRenderer, + JpegRenderer, + HtmlRenderer, + ColabRenderer, + KaggleRenderer, + NotebookRenderer, + ExternalRenderer, + BrowserRenderer, +) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/json.py b/.venv_haddock/lib/python3.12/site-packages/plotly/io/json.py new file mode 100644 index 0000000000000000000000000000000000000000..86c320d2f4a01e151392cfd70cab5cd3a7223225 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/io/json.py @@ -0,0 +1,10 @@ +# ruff: noqa: F401 +from ._json import ( + to_json, + write_json, + from_json, + read_json, + config, + to_json_plotly, + from_json_plotly, +) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/kaleido.py b/.venv_haddock/lib/python3.12/site-packages/plotly/io/kaleido.py new file mode 100644 index 0000000000000000000000000000000000000000..c086ea39ffe52a4293cf33c904887e178ba072df --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/io/kaleido.py @@ -0,0 +1,12 @@ +# ruff: noqa: F401 +from ._kaleido import ( + to_image, + write_image, + scope, + kaleido_available, + kaleido_major, + ENABLE_KALEIDO_V0_DEPRECATION_WARNINGS, + KALEIDO_DEPRECATION_MSG, + ORCA_DEPRECATION_MSG, + ENGINE_PARAM_DEPRECATION_MSG, +) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/io/orca.py b/.venv_haddock/lib/python3.12/site-packages/plotly/io/orca.py new file mode 100644 index 0000000000000000000000000000000000000000..4fd5c19250fe64efb73344f1a8476a52ae10add9 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/io/orca.py @@ -0,0 +1,9 @@ +# ruff: noqa: F401 +from ._orca import ( + ensure_server, + shutdown_server, + validate_executable, + reset_status, + config, + status, +) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/labextension/package.json b/.venv_haddock/lib/python3.12/site-packages/plotly/labextension/package.json new file mode 100644 index 0000000000000000000000000000000000000000..204b98e34d923544e56fefcdac34b7d46120ea28 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/labextension/package.json @@ -0,0 +1,39 @@ +{ + "name": "jupyterlab-plotly", + "main": "lib/mimeExtension.js", + "version": "6.0.1", + "repository": { + "type": "git", + "url": "https://github.com/plotly/plotly.py" + }, + "description": "The plotly Jupyter extension", + "author": "The plotly.py team", + "license": "MIT", + "scripts": { + "build:widget": "esbuild --bundle --alias:plotly.js=plotly.js/dist/plotly --format=esm --minify --outfile=../plotly/package_data/widgetbundle.js src/widget.ts", + "build:mimerenderer": "esbuild --bundle --alias:plotly.js=plotly.js/dist/plotly --format=esm --minify --outfile=lib/mimeExtension.js src/mimeExtension.ts", + "build:labextension": "jupyter labextension build .", + "build": "npm run build:widget && npm run build:mimerenderer && npm run build:labextension", + "watch": "npm run build -- --watch --sourcemap=inline", + "typecheck": "tsc --noEmit" + }, + "dependencies": { + "lodash-es": "^4.17.21", + "plotly.js": "3.3.1", + "@lumino/widgets": "~2.4.0" + }, + "devDependencies": { + "@jupyterlab/builder": "^4.3.6 || ^3.6.8", + "@types/plotly.js": "^2.33.4", + "esbuild": "^0.23.1", + 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5.1V5s0-1-1-1m0 2.5a3.5 3.5 0 1 1 0 7 3.5 3.5 0 1 1 0-7'/%3E%3Ccircle cx='10' cy='10' r='2'/%3E%3C/svg%3E\")}.maplibregl-ctrl button.maplibregl-ctrl-geolocate.maplibregl-ctrl-geolocate-background .maplibregl-ctrl-icon{background-image:url(\"data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' width='29' height='29' fill='%2333b5e5' viewBox='0 0 20 20'%3E%3Cpath d='M10 4C9 4 9 5 9 5v.1A5 5 0 0 0 5.1 9H5s-1 0-1 1 1 1 1 1h.1A5 5 0 0 0 9 14.9v.1s0 1 1 1 1-1 1-1v-.1a5 5 0 0 0 3.9-3.9h.1s1 0 1-1-1-1-1-1h-.1A5 5 0 0 0 11 5.1V5s0-1-1-1m0 2.5a3.5 3.5 0 1 1 0 7 3.5 3.5 0 1 1 0-7'/%3E%3C/svg%3E\")}.maplibregl-ctrl button.maplibregl-ctrl-geolocate.maplibregl-ctrl-geolocate-background-error .maplibregl-ctrl-icon{background-image:url(\"data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' width='29' height='29' fill='%23e54e33' viewBox='0 0 20 20'%3E%3Cpath d='M10 4C9 4 9 5 9 5v.1A5 5 0 0 0 5.1 9H5s-1 0-1 1 1 1 1 1h.1A5 5 0 0 0 9 14.9v.1s0 1 1 1 1-1 1-1v-.1a5 5 0 0 0 3.9-3.9h.1s1 0 1-1-1-1-1-1h-.1A5 5 0 0 0 11 5.1V5s0-1-1-1m0 2.5a3.5 3.5 0 1 1 0 7 3.5 3.5 0 1 1 0-7'/%3E%3C/svg%3E\")}.maplibregl-ctrl button.maplibregl-ctrl-geolocate.maplibregl-ctrl-geolocate-waiting .maplibregl-ctrl-icon{animation:maplibregl-spin 2s linear infinite}@media (forced-colors:active){.maplibregl-ctrl button.maplibregl-ctrl-geolocate .maplibregl-ctrl-icon{background-image:url(\"data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' width='29' height='29' fill='%23fff' viewBox='0 0 20 20'%3E%3Cpath d='M10 4C9 4 9 5 9 5v.1A5 5 0 0 0 5.1 9H5s-1 0-1 1 1 1 1 1h.1A5 5 0 0 0 9 14.9v.1s0 1 1 1 1-1 1-1v-.1a5 5 0 0 0 3.9-3.9h.1s1 0 1-1-1-1-1-1h-.1A5 5 0 0 0 11 5.1V5s0-1-1-1m0 2.5a3.5 3.5 0 1 1 0 7 3.5 3.5 0 1 1 0-7'/%3E%3Ccircle cx='10' cy='10' r='2'/%3E%3C/svg%3E\")}.maplibregl-ctrl button.maplibregl-ctrl-geolocate:disabled .maplibregl-ctrl-icon{background-image:url(\"data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' width='29' height='29' fill='%23999' viewBox='0 0 20 20'%3E%3Cpath d='M10 4C9 4 9 5 9 5v.1A5 5 0 0 0 5.1 9H5s-1 0-1 1 1 1 1 1h.1A5 5 0 0 0 9 14.9v.1s0 1 1 1 1-1 1-1v-.1a5 5 0 0 0 3.9-3.9h.1s1 0 1-1-1-1-1-1h-.1A5 5 0 0 0 11 5.1V5s0-1-1-1m0 2.5a3.5 3.5 0 1 1 0 7 3.5 3.5 0 1 1 0-7'/%3E%3Ccircle cx='10' cy='10' r='2'/%3E%3Cpath fill='red' d='m14 5 1 1-9 9-1-1z'/%3E%3C/svg%3E\")}.maplibregl-ctrl button.maplibregl-ctrl-geolocate.maplibregl-ctrl-geolocate-active .maplibregl-ctrl-icon{background-image:url(\"data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' width='29' height='29' fill='%2333b5e5' viewBox='0 0 20 20'%3E%3Cpath d='M10 4C9 4 9 5 9 5v.1A5 5 0 0 0 5.1 9H5s-1 0-1 1 1 1 1 1h.1A5 5 0 0 0 9 14.9v.1s0 1 1 1 1-1 1-1v-.1a5 5 0 0 0 3.9-3.9h.1s1 0 1-1-1-1-1-1h-.1A5 5 0 0 0 11 5.1V5s0-1-1-1m0 2.5a3.5 3.5 0 1 1 0 7 3.5 3.5 0 1 1 0-7'/%3E%3Ccircle cx='10' cy='10' r='2'/%3E%3C/svg%3E\")}.maplibregl-ctrl button.maplibregl-ctrl-geolocate.maplibregl-ctrl-geolocate-active-error .maplibregl-ctrl-icon{background-image:url(\"data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' width='29' height='29' fill='%23e58978' viewBox='0 0 20 20'%3E%3Cpath d='M10 4C9 4 9 5 9 5v.1A5 5 0 0 0 5.1 9H5s-1 0-1 1 1 1 1 1h.1A5 5 0 0 0 9 14.9v.1s0 1 1 1 1-1 1-1v-.1a5 5 0 0 0 3.9-3.9h.1s1 0 1-1-1-1-1-1h-.1A5 5 0 0 0 11 5.1V5s0-1-1-1m0 2.5a3.5 3.5 0 1 1 0 7 3.5 3.5 0 1 1 0-7'/%3E%3Ccircle cx='10' cy='10' r='2'/%3E%3C/svg%3E\")}.maplibregl-ctrl button.maplibregl-ctrl-geolocate.maplibregl-ctrl-geolocate-background .maplibregl-ctrl-icon{background-image:url(\"data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' width='29' height='29' fill='%2333b5e5' viewBox='0 0 20 20'%3E%3Cpath d='M10 4C9 4 9 5 9 5v.1A5 5 0 0 0 5.1 9H5s-1 0-1 1 1 1 1 1h.1A5 5 0 0 0 9 14.9v.1s0 1 1 1 1-1 1-1v-.1a5 5 0 0 0 3.9-3.9h.1s1 0 1-1-1-1-1-1h-.1A5 5 0 0 0 11 5.1V5s0-1-1-1m0 2.5a3.5 3.5 0 1 1 0 7 3.5 3.5 0 1 1 0-7'/%3E%3C/svg%3E\")}.maplibregl-ctrl button.maplibregl-ctrl-geolocate.maplibregl-ctrl-geolocate-background-error .maplibregl-ctrl-icon{background-image:url(\"data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' width='29' height='29' fill='%23e54e33' viewBox='0 0 20 20'%3E%3Cpath d='M10 4C9 4 9 5 9 5v.1A5 5 0 0 0 5.1 9H5s-1 0-1 1 1 1 1 1h.1A5 5 0 0 0 9 14.9v.1s0 1 1 1 1-1 1-1v-.1a5 5 0 0 0 3.9-3.9h.1s1 0 1-1-1-1-1-1h-.1A5 5 0 0 0 11 5.1V5s0-1-1-1m0 2.5a3.5 3.5 0 1 1 0 7 3.5 3.5 0 1 1 0-7'/%3E%3C/svg%3E\")}}@media (forced-colors:active) and (prefers-color-scheme:light){.maplibregl-ctrl button.maplibregl-ctrl-geolocate .maplibregl-ctrl-icon{background-image:url(\"data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' width='29' height='29' viewBox='0 0 20 20'%3E%3Cpath d='M10 4C9 4 9 5 9 5v.1A5 5 0 0 0 5.1 9H5s-1 0-1 1 1 1 1 1h.1A5 5 0 0 0 9 14.9v.1s0 1 1 1 1-1 1-1v-.1a5 5 0 0 0 3.9-3.9h.1s1 0 1-1-1-1-1-1h-.1A5 5 0 0 0 11 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v=m.plotgroup,x=i+"-x",_=i+"-y";e.minorGridlayer=m.minorGridlayer,e.gridlayer=m.gridlayer,e.zerolinelayer=m.zerolinelayer,e.zerolinelayerAbove=m.zerolinelayerAbove,u(m.overlinesBelow,"path",x),u(m.overlinesBelow,"path",_),u(m.overaxesBelow,"g",x),u(m.overaxesBelow,"g",_),e.plot=u(m.overplot,"g",i),u(m.overlinesAbove,"path",x),u(m.overlinesAbove,"path",_),u(m.overaxesAbove,"g",x),u(m.overaxesAbove,"g",_),e.xlines=v.select(".overlines-"+o).select("."+x),e.ylines=v.select(".overlines-"+c).select("."+_),e.xaxislayer=v.select(".overaxes-"+o).select("."+x),e.yaxislayer=v.select(".overaxes-"+c).select("."+_)}a||(p||(h(e.minorGridlayer,"g",e.xaxis._id),h(e.minorGridlayer,"g",e.yaxis._id),e.minorGridlayer.selectAll("g").map((function(t){return t[0]})).sort(s.idSort),h(e.gridlayer,"g",e.xaxis._id),h(e.gridlayer,"g",e.yaxis._id),e.gridlayer.selectAll("g").map((function(t){return t[0]})).sort(s.idSort)),e.xlines.style("fill","none").classed("crisp",!0),e.ylines.style("fill","none").classed("crisp",!0))}function m(t,r){if(t){var n={};for(var i in t.each((function(t){var i=t[0];e.select(this).remove(),g(i,r),n[i]=!0})),r._plots)for(var a=r._plots[i].overlays||[],o=0;o0){var g=m.id;if(-1!==g.indexOf(f))continue;g+=f+(u+1),m=n.extendFlat({},m,{id:g,plot:o._cartesianlayer.selectAll(".subplot").select("."+g)})}for(var y,v=[],x=0;x1&&(w+=f+b),_.push(n+w),r=0;r=0,x=e.indexOf("end")>=0,_=d.backoff*g+a.standoff,b=m.backoff*y+a.startstandoff;if("line"===p.nodeName){c={x:+t.attr("x1"),y:+t.attr("y1")},u={x:+t.attr("x2"),y:+t.attr("y2")};var w=c.x-u.x,T=c.y-u.y;if(f=(h=Math.atan2(T,w))+Math.PI,_&&b&&_+b>Math.sqrt(w*w+T*T))return void D();if(_){if(_*_>w*w+T*T)return void D();var k=_*Math.cos(h),A=_*Math.sin(h);u.x+=k,u.y+=A,t.attr({x2:u.x,y2:u.y})}if(b){if(b*b>w*w+T*T)return void D();var M=b*Math.cos(h),S=b*Math.sin(h);c.x-=M,c.y-=S,t.attr({x1:c.x,y1:c.y})}}else if("path"===p.nodeName){var E=p.getTotalLength(),C="";if(E<_+b)return void D();var I=p.getPointAtLength(0),L=p.getPointAtLength(.1);h=Math.atan2(I.y-L.y,I.x-L.x),c=p.getPointAtLength(Math.min(b,E)),C="0px,"+b+"px,";var P=p.getPointAtLength(E),z=p.getPointAtLength(E-.1);f=Math.atan2(P.y-z.y,P.x-z.x),u=p.getPointAtLength(Math.max(0,E-_)),C+=E-(C?b+_:_)+"px,"+E+"px",t.style("stroke-dasharray",C)}function D(){t.style("stroke-dasharray","0px,100px")}function O(e,i,c,u){e.path&&(e.noRotate&&(c=0),r.select(p.parentNode).append("path").attr({class:t.attr("class"),d:e.path,transform:l(i.x,i.y)+s(180*c/Math.PI)+o(u)}).style({fill:n.rgb(a.arrowcolor),"stroke-width":0}))}v&&O(m,c,h,y),x&&O(d,u,f,g)}}}),Li=m({"src/components/annotations/draw.js"(t,e){var r=b(),n=Ht(),i=Ae(),a=ce(),o=a.strTranslate,s=ar(),l=W(),c=tr(),u=Or(),h=Ee(),f=dr(),p=pr(),d=ve().arrayEditor,m=Ii();function g(t,e){var r=t._fullLayout.annotations[e]||{},n=s.getFromId(t,r.xref),i=s.getFromId(t,r.yref);n&&n.setScale(),i&&i.setScale(),v(t,r,e,!1,n,i)}function y(t,e,r,n,i){var a=i[r],o=i[r+"ref"],l=-1!==r.indexOf("y"),c="domain"===s.getRefType(o),u=l?n.h:n.w;return t?c?a+(l?-e:e)/t._length:t.p2r(t.r2p(a)+e):a+(l?-e:e)/u}function v(t,e,i,g,v,x){var _,b,w=t._fullLayout,T=t._fullLayout._size,k=t._context.edits;g?(_="annotation-"+g,b=g+".annotations"):(_="annotation",b="annotations");var A=d(t.layout,b,e),M=A.modifyBase,S=A.modifyItem,E=A.getUpdateObj;w._infolayer.selectAll("."+_+'[data-index="'+i+'"]').remove();var C="clip"+w._uid+"_ann"+i;if(e._input&&!1!==e.visible){var I={x:{},y:{}},L=+e.textangle||0,P=w._infolayer.append("g").classed(_,!0).attr("data-index",String(i)).style("opacity",e.opacity),z=P.append("g").classed("annotation-text-g",!0),D=k[e.showarrow?"annotationTail":"annotationPosition"],O=e.captureevents||k.annotationText||D,R=z.append("g").style("pointer-events",O?"all":null).call(f,"pointer").on("click",(function(){t._dragging=!1,t.emit("plotly_clickannotation",W(r.event))}));e.hovertext&&R.on("mouseover",(function(){var r=e.hoverlabel,n=r.font,i=this.getBoundingClientRect(),a=t.getBoundingClientRect();u.loneHover({x0:i.left-a.left,x1:i.right-a.left,y:(i.top+i.bottom)/2-a.top,text:e.hovertext,color:r.bgcolor,borderColor:r.bordercolor,fontFamily:n.family,fontSize:n.size,fontColor:n.color,fontWeight:n.weight,fontStyle:n.style,fontVariant:n.variant,fontShadow:n.fontShadow,fontLineposition:n.fontLineposition,fontTextcase:n.fontTextcase},{container:w._hoverlayer.node(),outerContainer:w._paper.node(),gd:t})})).on("mouseout",(function(){u.loneUnhover(w._hoverlayer.node())}));var F=e.borderwidth,B=e.borderpad,j=F+B,N=R.append("rect").attr("class","bg").style("stroke-width",F+"px").call(l.stroke,e.bordercolor).call(l.fill,e.bgcolor),U=e.width||e.height,V=w._topclips.selectAll("#"+C).data(U?[0]:[]);V.enter().append("clipPath").classed("annclip",!0).attr("id",C).append("rect"),V.exit().remove();var q=e.font,H=w._meta?a.templateString(e.text,w._meta):e.text,G=R.append("text").classed("annotation-text",!0).text(H);k.annotationText?G.call(h.makeEditable,{delegate:R,gd:t}).call(Z).on("edit",(function(r){e.text=r,this.call(Z),S("text",r),v&&v.autorange&&M(v._name+".autorange",!0),x&&x.autorange&&M(x._name+".autorange",!0),n.call("_guiRelayout",t,E())})):G.call(Z)}else r.selectAll("#"+C).remove();function W(t){var r={index:i,annotation:e._input,fullAnnotation:e,event:t};return g&&(r.subplotId=g),r}function Z(r){return r.call(c.font,q).attr({"text-anchor":{left:"start",right:"end"}[e.align]||"middle"}),h.convertToTspans(r,t,Y),r}function Y(){var r=G.selectAll("a");1===r.size()&&r.text()===G.text()&&R.insert("a",":first-child").attr({"xlink:xlink:href":r.attr("xlink:href"),"xlink:xlink:show":r.attr("xlink:show")}).style({cursor:"pointer"}).node().appendChild(N.node());var i=R.select(".annotation-text-math-group"),u=!i.empty(),d=c.bBox((u?i:G).node()),_=d.width,b=d.height,A=e.width||_,O=e.height||b,B=Math.round(A+2*j),q=Math.round(O+2*j);function H(t,e){return"auto"===e&&(e=t<1/3?"left":t>2/3?"right":"center"),{center:0,middle:0,left:.5,bottom:-.5,right:-.5,top:.5}[e]}for(var Z=!1,Y=["x","y"],X=0;X1)&&(nt===rt?((pt=it.r2fraction(e["a"+et]))<0||pt>1)&&(Z=!0):Z=!0),$=it._offset+it.r2p(e[et]),Q=.5}else{var dt="domain"===ft;"x"===et?(J=e[et],$=dt?it._offset+it._length*J:$=T.l+T.w*J):(J=1-e[et],$=dt?it._offset+it._length*J:$=T.t+T.h*J),Q=e.showarrow?.5:J}if(e.showarrow){ht.head=$;var mt=e["a"+et];if(tt=ot*H(.5,e.xanchor)-st*H(.5,e.yanchor),nt===rt){var gt=s.getRefType(nt);"domain"===gt?("y"===et&&(mt=1-mt),ht.tail=it._offset+it._length*mt):"paper"===gt?"y"===et?(mt=1-mt,ht.tail=T.t+T.h*mt):ht.tail=T.l+T.w*mt:ht.tail=it._offset+it.r2p(mt),K=tt}else ht.tail=$+mt,K=tt+mt;ht.text=ht.tail+tt;var yt=w["x"===et?"width":"height"];if("paper"===rt&&(ht.head=a.constrain(ht.head,1,yt-1)),"pixel"===nt){var vt=-Math.max(ht.tail-3,ht.text),xt=Math.min(ht.tail+3,ht.text)-yt;vt>0?(ht.tail+=vt,ht.text+=vt):xt>0&&(ht.tail-=xt,ht.text-=xt)}ht.tail+=ut,ht.head+=ut}else K=tt=lt*H(Q,ct),ht.text=$+tt;ht.text+=ut,tt+=ut,K+=ut,e["_"+et+"padplus"]=lt/2+K,e["_"+et+"padminus"]=lt/2-K,e["_"+et+"size"]=lt,e["_"+et+"shift"]=tt}if(Z)R.remove();else{var _t=0,bt=0;if("left"!==e.align&&(_t=(A-_)*("center"===e.align?.5:1)),"top"!==e.valign&&(bt=(O-b)*("middle"===e.valign?.5:1)),u)i.select("svg").attr({x:j+_t-1,y:j+bt}).call(c.setClipUrl,U?C:null,t);else{var wt=j+bt-d.top,Tt=j+_t-d.left;G.call(h.positionText,Tt,wt).call(c.setClipUrl,U?C:null,t)}V.select("rect").call(c.setRect,j,j,A,O),N.call(c.setRect,F/2,F/2,B-F,q-F),R.call(c.setTranslate,Math.round(I.x.text-B/2),Math.round(I.y.text-q/2)),z.attr({transform:"rotate("+L+","+I.x.text+","+I.y.text+")"});var kt,At=function(r,i){P.selectAll(".annotation-arrow-g").remove();var s=I.x.head,u=I.y.head,h=I.x.tail+r,f=I.y.tail+i,d=I.x.text+r,_=I.y.text+i,b=a.rotationXYMatrix(L,d,_),w=a.apply2DTransform(b),A=a.apply2DTransform2(b),C=+N.attr("width"),D=+N.attr("height"),O=d-.5*C,F=O+C,B=_-.5*D,j=B+D,U=[[O,B,O,j],[O,j,F,j],[F,j,F,B],[F,B,O,B]].map(A);if(!U.reduce((function(t,e){return t^!!a.segmentsIntersect(s,u,s+1e6,u+1e6,e[0],e[1],e[2],e[3])}),!1)){U.forEach((function(t){var e=a.segmentsIntersect(h,f,s,u,t[0],t[1],t[2],t[3]);e&&(h=e.x,f=e.y)}));var V=e.arrowwidth,q=e.arrowcolor,H=e.arrowside,G=P.append("g").style({opacity:l.opacity(q)}).classed("annotation-arrow-g",!0),W=G.append("path").attr("d","M"+h+","+f+"L"+s+","+u).style("stroke-width",V+"px").call(l.stroke,l.rgb(q));if(m(W,H,e),k.annotationPosition&&W.node().parentNode&&!g){var Z=s,Y=u;if(e.standoff){var X=Math.sqrt(Math.pow(s-h,2)+Math.pow(u-f,2));Z+=e.standoff*(h-s)/X,Y+=e.standoff*(f-u)/X}var $,K,J=G.append("path").classed("annotation-arrow",!0).classed("anndrag",!0).classed("cursor-move",!0).attr({d:"M3,3H-3V-3H3ZM0,0L"+(h-Z)+","+(f-Y),transform:o(Z,Y)}).style("stroke-width",V+6+"px").call(l.stroke,"rgba(0,0,0,0)").call(l.fill,"rgba(0,0,0,0)");p.init({element:J.node(),gd:t,prepFn:function(){var t=c.getTranslate(R);$=t.x,K=t.y,v&&v.autorange&&M(v._name+".autorange",!0),x&&x.autorange&&M(x._name+".autorange",!0)},moveFn:function(t,r){var n=w($,K),i=n[0]+t,a=n[1]+r;R.call(c.setTranslate,i,a),S("x",y(v,t,"x",T,e)),S("y",y(x,r,"y",T,e)),e.axref===e.xref&&S("ax",y(v,t,"ax",T,e)),e.ayref===e.yref&&S("ay",y(x,r,"ay",T,e)),G.attr("transform",o(t,r)),z.attr({transform:"rotate("+L+","+i+","+a+")"})},doneFn:function(){n.call("_guiRelayout",t,E());var e=document.querySelector(".js-notes-box-panel");e&&e.redraw(e.selectedObj)}})}}};e.showarrow&&At(0,0),D&&p.init({element:R.node(),gd:t,prepFn:function(){kt=z.attr("transform")},moveFn:function(t,r){var n="pointer";if(e.showarrow)e.axref===e.xref?S("ax",y(v,t,"ax",T,e)):S("ax",e.ax+t),e.ayref===e.yref?S("ay",y(x,r,"ay",T.w,e)):S("ay",e.ay+r),At(t,r);else{if(g)return;var i,a;if(v)i=y(v,t,"x",T,e);else{var s=e._xsize/T.w,l=e.x+(e._xshift-e.xshift)/T.w-s/2;i=p.align(l+t/T.w,s,0,1,e.xanchor)}if(x)a=y(x,r,"y",T,e);else{var c=e._ysize/T.h,u=e.y-(e._yshift+e.yshift)/T.h-c/2;a=p.align(u-r/T.h,c,0,1,e.yanchor)}S("x",i),S("y",a),(!v||!x)&&(n=p.getCursor(v?.5:i,x?.5:a,e.xanchor,e.yanchor))}z.attr({transform:o(t,r)+kt}),f(R,n)},clickFn:function(r,n){e.captureevents&&t.emit("plotly_clickannotation",W(n))},doneFn:function(){f(R),n.call("_guiRelayout",t,E());var e=document.querySelector(".js-notes-box-panel");e&&e.redraw(e.selectedObj)}})}}}e.exports={draw:function(t){var e=t._fullLayout;e._infolayer.selectAll(".annotation").remove();for(var r=0;r0||r.explicitOff.length>0},onClick:function(t,e){var o,s,l=a(t,e),c=l.on,u=l.off.concat(l.explicitOff),h={},f=t._fullLayout.annotations;if(c.length||u.length){for(o=0;o1){c=!0;break}}c?t.fullLayout._infolayer.select(".annotation-"+t.id+'[data-index="'+s+'"]').remove():(l._pdata=n(t.glplot.cameraParams,[e.xaxis.r2l(l.x)*a[0],e.yaxis.r2l(l.y)*a[1],e.zaxis.r2l(l.z)*a[2]]),r(t.graphDiv,l,s,t.id,l._xa,l._ya))}}}}),qi=m({"src/components/annotations3d/index.js"(t,e){var r=Ht(),n=ce();e.exports={moduleType:"component",name:"annotations3d",schema:{subplots:{scene:{annotations:Bi()}}},layoutAttributes:Bi(),handleDefaults:ji(),includeBasePlot:function(t,e){var i=r.subplotsRegistry.gl3d;if(i)for(var a=i.attrRegex,o=Object.keys(t),s=0;s0?f+c:c;return{ppad:c,ppadplus:u?d:m,ppadminus:u?m:d}}return{ppad:c}}function l(t,e,r){var n,o,s="x"===t._id.charAt(0)?"x":"y",l="category"===t.type||"multicategory"===t.type,c=0,u=0,h=l?t.r2c:t.d2c;if("scaled"===e[s+"sizemode"]?(n=e[s+"0"],o=e[s+"1"],l&&(c=e[s+"0shift"],u=e[s+"1shift"])):(n=e[s+"anchor"],o=e[s+"anchor"]),void 0!==n)return[h(n)+c,h(o)+u];if(e.path){var f,p,d,m,g=1/0,y=-1/0,v=e.path.match(i.segmentRE);for("date"===t.type&&(h=a.decodeDate(h)),f=0;fy&&(y=m));if(y>=g)return[g,y]}}e.exports=function(t){var e,a=t._fullLayout,c=r.filterVisible(a.shapes);if(c.length&&t._fullData.length)for(var u=0;u0)&&(o("active"),o("direction"),o("type"),o("showactive"),o("x"),o("y"),r.noneOrAll(t,e,["x","y"]),o("xanchor"),o("yanchor"),o("pad.t"),o("pad.r"),o("pad.b"),o("pad.l"),r.coerceFont(o,"font",a.font),o("bgcolor",a.paper_bgcolor),o("bordercolor"),o("borderwidth"))}function l(t,e){function n(n,i){return r.coerce(t,e,o,n,i)}n("visible","skip"===t.method||Array.isArray(t.args))&&(n("method"),n("args"),n("args2"),n("label"),n("execute"))}e.exports=function(t,e){n(t,e,{name:a,handleItemDefaults:s})}}}),na=m({"src/components/updatemenus/scrollbox.js"(t,e){e.exports=o;var r=b(),n=W(),i=tr(),a=ce();function o(t,e,r){this.gd=t,this.container=e,this.id=r,this.position=null,this.translateX=null,this.translateY=null,this.hbar=null,this.vbar=null,this.bg=this.container.selectAll("rect.scrollbox-bg").data([0]),this.bg.exit().on(".drag",null).on("wheel",null).remove(),this.bg.enter().append("rect").classed("scrollbox-bg",!0).style("pointer-events","all").attr({opacity:0,x:0,y:0,width:0,height:0})}o.barWidth=2,o.barLength=20,o.barRadius=2,o.barPad=1,o.barColor="#808BA4",o.prototype.enable=function(t,e,a){var s=this.gd._fullLayout,l=s.width,c=s.height;this.position=t;var u,h,f,p,d=this.position.l,m=this.position.w,g=this.position.t,y=this.position.h,v=this.position.direction,x="down"===v,_="left"===v,b="up"===v,w=m,T=y;!x&&!_&&!("right"===v)&&!b&&(this.position.direction="down",x=!0),x||b?(h=(u=d)+w,x?(f=g,T=(p=Math.min(f+T,c))-f):T=(p=g+T)-(f=Math.max(p-T,0))):(p=(f=g)+T,_?w=(h=d+w)-(u=Math.max(h-w,0)):(u=d,w=(h=Math.min(u+w,l))-u)),this._box={l:u,t:f,w,h:T};var k=m>w,A=o.barLength+2*o.barPad,M=o.barWidth+2*o.barPad,S=d,E=g+y;E+M>c&&(E=c-M);var C=this.container.selectAll("rect.scrollbar-horizontal").data(k?[0]:[]);C.exit().on(".drag",null).remove(),C.enter().append("rect").classed("scrollbar-horizontal",!0).call(n.fill,o.barColor),k?(this.hbar=C.attr({rx:o.barRadius,ry:o.barRadius,x:S,y:E,width:A,height:M}),this._hbarXMin=S+A/2,this._hbarTranslateMax=w-A):(delete this.hbar,delete this._hbarXMin,delete this._hbarTranslateMax);var I=y>T,L=o.barWidth+2*o.barPad,P=o.barLength+2*o.barPad,z=d+m,D=g;z+L>l&&(z=l-L);var O=this.container.selectAll("rect.scrollbar-vertical").data(I?[0]:[]);O.exit().on(".drag",null).remove(),O.enter().append("rect").classed("scrollbar-vertical",!0).call(n.fill,o.barColor),I?(this.vbar=O.attr({rx:o.barRadius,ry:o.barRadius,x:z,y:D,width:L,height:P}),this._vbarYMin=D+P/2,this._vbarTranslateMax=T-P):(delete this.vbar,delete this._vbarYMin,delete this._vbarTranslateMax);var R=this.id,F=u-.5,B=I?h+L+.5:h+.5,j=f-.5,N=k?p+M+.5:p+.5,U=s._topdefs.selectAll("#"+R).data(k||I?[0]:[]);if(U.exit().remove(),U.enter().append("clipPath").attr("id",R).append("rect"),k||I?(this._clipRect=U.select("rect").attr({x:Math.floor(F),y:Math.floor(j),width:Math.ceil(B)-Math.floor(F),height:Math.ceil(N)-Math.floor(j)}),this.container.call(i.setClipUrl,R,this.gd),this.bg.attr({x:d,y:g,width:m,height:y})):(this.bg.attr({width:0,height:0}),this.container.on("wheel",null).on(".drag",null).call(i.setClipUrl,null),delete this._clipRect),k||I){var V=r.behavior.drag().on("dragstart",(function(){r.event.sourceEvent.preventDefault()})).on("drag",this._onBoxDrag.bind(this));this.container.on("wheel",null).on("wheel",this._onBoxWheel.bind(this)).on(".drag",null).call(V);var q=r.behavior.drag().on("dragstart",(function(){r.event.sourceEvent.preventDefault(),r.event.sourceEvent.stopPropagation()})).on("drag",this._onBarDrag.bind(this));k&&this.hbar.on(".drag",null).call(q),I&&this.vbar.on(".drag",null).call(q)}this.setTranslate(e,a)},o.prototype.disable=function(){(this.hbar||this.vbar)&&(this.bg.attr({width:0,height:0}),this.container.on("wheel",null).on(".drag",null).call(i.setClipUrl,null),delete this._clipRect),this.hbar&&(this.hbar.on(".drag",null),this.hbar.remove(),delete this.hbar,delete this._hbarXMin,delete this._hbarTranslateMax),this.vbar&&(this.vbar.on(".drag",null),this.vbar.remove(),delete this.vbar,delete this._vbarYMin,delete this._vbarTranslateMax)},o.prototype._onBoxDrag=function(){var t=this.translateX,e=this.translateY;this.hbar&&(t-=r.event.dx),this.vbar&&(e-=r.event.dy),this.setTranslate(t,e)},o.prototype._onBoxWheel=function(){var t=this.translateX,e=this.translateY;this.hbar&&(t+=r.event.deltaY),this.vbar&&(e+=r.event.deltaY),this.setTranslate(t,e)},o.prototype._onBarDrag=function(){var t=this.translateX,e=this.translateY;if(this.hbar){var n=t+this._hbarXMin,i=n+this._hbarTranslateMax;t=(a.constrain(r.event.x,n,i)-n)/(i-n)*(this.position.w-this._box.w)}if(this.vbar){var o=e+this._vbarYMin,s=o+this._vbarTranslateMax;e=(a.constrain(r.event.y,o,s)-o)/(s-o)*(this.position.h-this._box.h)}this.setTranslate(t,e)},o.prototype.setTranslate=function(t,e){var r=this.position.w-this._box.w,n=this.position.h-this._box.h;if(t=a.constrain(t||0,0,r),e=a.constrain(e||0,0,n),this.translateX=t,this.translateY=e,this.container.call(i.setTranslate,this._box.l-this.position.l-t,this._box.t-this.position.t-e),this._clipRect&&this._clipRect.attr({x:Math.floor(this.position.l+t-.5),y:Math.floor(this.position.t+e-.5)}),this.hbar){var o=t/r;this.hbar.call(i.setTranslate,t+o*this._hbarTranslateMax,e)}if(this.vbar){var s=e/n;this.vbar.call(i.setTranslate,t,e+s*this._vbarTranslateMax)}}}}),ia=m({"src/components/updatemenus/draw.js"(t,e){var r=b(),n=Ae(),i=W(),a=tr(),o=ce(),s=Ee(),l=ve().arrayEditor,c=Se().LINE_SPACING,u=ta(),h=na();function f(t){return t._index}function p(t,e){return+t.attr(u.menuIndexAttrName)===e._index}function d(t,e,r,n,i,a,o,s){e.active=o,l(t.layout,u.name,e).applyUpdate("active",o),"buttons"===e.type?g(t,n,null,null,e):"dropdown"===e.type&&(i.attr(u.menuIndexAttrName,"-1"),m(t,n,i,a,e),s||g(t,n,i,a,e))}function m(t,e,r,n,i){var s=o.ensureSingle(e,"g",u.headerClassName,(function(t){t.style("pointer-events","all")})),l=i._dims,c=i.active,h=i.buttons[c]||u.blankHeaderOpts,f={y:i.pad.t,yPad:0,x:i.pad.l,xPad:0,index:0},d={width:l.headerWidth,height:l.headerHeight};s.call(y,i,h,t).call(M,i,f,d),o.ensureSingle(e,"text",u.headerArrowClassName,(function(t){t.attr("text-anchor","end").call(a.font,i.font).text(u.arrowSymbol[i.direction])})).attr({x:l.headerWidth-u.arrowOffsetX+i.pad.l,y:l.headerHeight/2+u.textOffsetY+i.pad.t}),s.on("click",(function(){r.call(S,String(p(r,i)?-1:i._index)),g(t,e,r,n,i)})),s.on("mouseover",(function(){s.call(w)})),s.on("mouseout",(function(){s.call(T,i)})),a.setTranslate(e,l.lx,l.ly)}function g(t,e,i,a,s){i||(i=e).attr("pointer-events","all");var l=function(t){return-1==+t.attr(u.menuIndexAttrName)}(i)&&"buttons"!==s.type?[]:s.buttons,c="dropdown"===s.type?u.dropdownButtonClassName:u.buttonClassName,h=i.selectAll("g."+c).data(o.filterVisible(l)),f=h.enter().append("g").classed(c,!0),p=h.exit();"dropdown"===s.type?(f.attr("opacity","0").transition().attr("opacity","1"),p.transition().attr("opacity","0").remove()):p.remove();var m=0,g=0,v=s._dims,x=-1!==["up","down"].indexOf(s.direction);"dropdown"===s.type&&(x?g=v.headerHeight+u.gapButtonHeader:m=v.headerWidth+u.gapButtonHeader),"dropdown"===s.type&&"up"===s.direction&&(g=-u.gapButtonHeader+u.gapButton-v.openHeight),"dropdown"===s.type&&"left"===s.direction&&(m=-u.gapButtonHeader+u.gapButton-v.openWidth);var b={x:v.lx+m+s.pad.l,y:v.ly+g+s.pad.t,yPad:u.gapButton,xPad:u.gapButton,index:0},k={l:b.x+s.borderwidth,t:b.y+s.borderwidth};h.each((function(o,l){var c=r.select(this);c.call(y,s,o,t).call(M,s,b),c.on("click",(function(){r.event.defaultPrevented||(o.execute&&(o.args2&&s.active===l?(d(t,s,0,e,i,a,-1),n.executeAPICommand(t,o.method,o.args2)):(d(t,s,0,e,i,a,l),n.executeAPICommand(t,o.method,o.args))),t.emit("plotly_buttonclicked",{menu:s,button:o,active:s.active}))})),c.on("mouseover",(function(){c.call(w)})),c.on("mouseout",(function(){c.call(T,s),h.call(_,s)}))})),h.call(_,s),x?(k.w=Math.max(v.openWidth,v.headerWidth),k.h=b.y-k.t):(k.w=b.x-k.l,k.h=Math.max(v.openHeight,v.headerHeight)),k.direction=s.direction,a&&(h.size()?function(t,e,r,n,i,a){var o,s,l,c=i.direction,h="up"===c||"down"===c,f=i._dims,p=i.active;if(h)for(s=0,l=0;l0?[0]:[]);if(s.enter().append("g").classed(u.containerClassName,!0).style("cursor","pointer"),s.exit().each((function(){r.select(this).selectAll("g."+u.headerGroupClassName).each(a)})).remove(),0!==i.length){var l=s.selectAll("g."+u.headerGroupClassName).data(i,f);l.enter().append("g").classed(u.headerGroupClassName,!0);for(var c=o.ensureSingle(s,"g",u.dropdownButtonGroupClassName,(function(t){t.style("pointer-events","all")})),y=0;y0&&(l=l.transition().duration(e.transition.duration).ease(e.transition.easing)),l.attr("transform",s(o-.5*u.gripWidth,e._dims.currentValueTotalHeight))}}function E(t,e){var r=t._dims;return r.inputAreaStart+u.stepInset+(r.inputAreaLength-2*u.stepInset)*Math.min(1,Math.max(0,e))}function C(t,e){var r=t._dims;return Math.min(1,Math.max(0,(e-u.stepInset-r.inputAreaStart)/(r.inputAreaLength-2*u.stepInset-2*r.inputAreaStart)))}function I(t,e,r){var n=r._dims,s=o.ensureSingle(t,"rect",u.railTouchRectClass,(function(n){n.call(A,e,t,r).style("pointer-events","all")}));s.attr({width:n.inputAreaLength,height:Math.max(n.inputAreaWidth,u.tickOffset+r.ticklen+n.labelHeight)}).call(i.fill,r.bgcolor).attr("opacity",0),a.setTranslate(s,0,n.currentValueTotalHeight)}function L(t,e){var r=e._dims,n=r.inputAreaLength-2*u.railInset,s=o.ensureSingle(t,"rect",u.railRectClass);s.attr({width:n,height:u.railWidth,rx:u.railRadius,ry:u.railRadius,"shape-rendering":"crispEdges"}).call(i.stroke,e.bordercolor).call(i.fill,e.bgcolor).style("stroke-width",e.borderwidth+"px"),a.setTranslate(s,u.railInset,.5*(r.inputAreaWidth-u.railWidth)+r.currentValueTotalHeight)}e.exports=function(t){var e=t._context.staticPlot,i=t._fullLayout,o=function(t,e){for(var r=t[u.name],n=[],i=0;i0?[0]:[]);function l(e){e._commandObserver&&(e._commandObserver.remove(),delete e._commandObserver),n.autoMargin(t,m(e))}if(s.enter().append("g").classed(u.containerClassName,!0).style("cursor",e?null:"ew-resize"),s.exit().each((function(){r.select(this).selectAll("g."+u.groupClassName).each(l)})).remove(),0!==o.length){var c=s.selectAll("g."+u.groupClassName).data(o,g);c.enter().append("g").classed(u.groupClassName,!0),c.exit().each(l).remove();for(var h=0;h0?t.touches[0].clientX:0}function g(t,e,r,n){var i=a.ensureSingle(t,"rect",d.bgClassName,(function(t){t.attr({x:0,y:0,"shape-rendering":"crispEdges"})})),c=n.borderwidth%2==0?n.borderwidth:n.borderwidth-1,u=-n._offsetShift,h=s.crispRound(e,n.borderwidth);i.attr({width:n._width+c,height:n._height+c,transform:o(u,u),"stroke-width":h}).call(l.stroke,n.bordercolor).call(l.fill,n.bgcolor)}function y(t,e,r,n){var i=e._fullLayout;a.ensureSingleById(i._topdefs,"clipPath",n._clipId,(function(t){t.append("rect").attr({x:0,y:0})})).select("rect").attr({width:n._width,height:n._height})}function v(t,e,n,o){var l,c=e.calcdata,f=t.selectAll("g."+d.rangePlotClassName).data(n._subplotsWith,a.identity);f.enter().append("g").attr("class",(function(t){return d.rangePlotClassName+" "+t})).call(s.setClipUrl,o._clipId,e),f.order(),f.exit().remove(),f.each((function(t,a){var s=r.select(this),f=0===a,p=h.getFromId(e,t,"y"),d=p._name,m=o[d],g={data:[],layout:{xaxis:{type:n.type,domain:[0,1],range:o.range.slice(),calendar:n.calendar},width:o._width,height:o._height,margin:{t:0,b:0,l:0,r:0}},_context:e._context};n.rangebreaks&&(g.layout.xaxis.rangebreaks=n.rangebreaks),g.layout[d]={type:p.type,domain:[0,1],range:"match"!==m.rangemode?m.range.slice():p.range.slice(),calendar:p.calendar},p.rangebreaks&&(g.layout[d].rangebreaks=p.rangebreaks),i.supplyDefaults(g);var y=g._fullLayout.xaxis,v=g._fullLayout[d];y.clearCalc(),y.setScale(),v.clearCalc(),v.setScale();var x={id:t,plotgroup:s,xaxis:y,yaxis:v,isRangePlot:!0};f?l=x:(x.mainplot="xy",x.mainplotinfo=l),u.rangePlot(e,x,function(t,e){for(var r=[],n=0;n=n.max)e=B[r+1];else if(t=n.pmax)e=B[r+1];else if(ti._length||v+b<0)return;u=y+b,f=v+b;break;case l:if(_="col-resize",y+b>i._length)return;u=y+b,f=v;break;case c:if(_="col-resize",v+b<0)return;u=y,f=v+b;break;default:_="ew-resize",u=g,f=g+b}if(f0)){var m=function(t,e,r){for(var n=r.filter((function(r){return e[r].anchor===t._id})),i=0,a=0;a1){f||p||d||"independent"===k("pattern")&&(f=!0),g._hasSubplotGrid=f;var x,_,b="top to bottom"===k("roworder"),w=f?.2:.1,T=f?.3:.1;m&&e._splomGridDflt&&(x=e._splomGridDflt.xside,_=e._splomGridDflt.yside),g._domains={x:c("x",k,w,x,v),y:c("y",k,T,_,y,b)}}else delete e.grid}function k(t,e){return r.coerce(n,g,s,t,e)}},contentDefaults:function(t,e){var r=e.grid;if(r&&r._domains){var n,i,a,o,s,c,h,f=t.grid||{},p=e._subplots,d=r._hasSubplotGrid,m=r.rows,g=r.columns,y="independent"===r.pattern,v=r._axisMap={};if(d){var x=f.subplots||[];c=r.subplots=new Array(m);var _=1;for(n=0;n0,h=t._context.staticPlot;e.each((function(e){var f,p=e[0].trace,d=p.error_x||{},m=p.error_y||{};p.ids&&(f=function(t){return t.id});var g=a.hasMarkers(p)&&p.marker.maxdisplayed>0;!m.visible&&!d.visible&&(e=[]);var y=r.select(this).selectAll("g.errorbar").data(e,f);if(y.exit().remove(),e.length){d.visible||y.selectAll("path.xerror").remove(),m.visible||y.selectAll("path.yerror").remove(),y.style("opacity",1);var v=y.enter().append("g").classed("errorbar",!0);u&&v.style("opacity",0).transition().duration(s.duration).style("opacity",1),i.setClipUrl(y,o.layerClipId,t),y.each((function(t){var e=r.select(this),i=function(t,e,r){var i={x:e.c2p(t.x),y:r.c2p(t.y)};return void 0!==t.yh&&(i.yh=r.c2p(t.yh),i.ys=r.c2p(t.ys),n(i.ys)||(i.noYS=!0,i.ys=r.c2p(t.ys,!0))),void 0!==t.xh&&(i.xh=e.c2p(t.xh),i.xs=e.c2p(t.xs),n(i.xs)||(i.noXS=!0,i.xs=e.c2p(t.xs,!0))),i}(t,l,c);if(!g||t.vis){var a,o=e.select("path.yerror");if(m.visible&&n(i.x)&&n(i.yh)&&n(i.ys)){var f=m.width;a="M"+(i.x-f)+","+i.yh+"h"+2*f+"m-"+f+",0V"+i.ys,i.noYS||(a+="m-"+f+",0h"+2*f),o.size()?u&&(o=o.transition().duration(s.duration).ease(s.easing)):o=e.append("path").style("vector-effect",h?"none":"non-scaling-stroke").classed("yerror",!0),o.attr("d",a)}else o.remove();var p=e.select("path.xerror");if(d.visible&&n(i.y)&&n(i.xh)&&n(i.xs)){var y=(d.copy_ystyle?m:d).width;a="M"+i.xh+","+(i.y-y)+"v"+2*y+"m0,-"+y+"H"+i.xs,i.noXS||(a+="m0,-"+y+"v"+2*y),p.size()?u&&(p=p.transition().duration(s.duration).ease(s.easing)):p=e.append("path").style("vector-effect",h?"none":"non-scaling-stroke").classed("xerror",!0),p.attr("d",a)}else p.remove()}}))}}))}}}),Pa=m({"src/components/errorbars/style.js"(t,e){var r=b(),n=W();e.exports=function(t){t.each((function(t){var e=t[0].trace,i=e.error_y||{},a=e.error_x||{},o=r.select(this);o.selectAll("path.yerror").style("stroke-width",i.thickness+"px").call(n.stroke,i.color),a.copy_ystyle&&(a=i),o.selectAll("path.xerror").style("stroke-width",a.thickness+"px").call(n.stroke,a.color)}))}}}),za=m({"src/components/errorbars/index.js"(t,e){var r=ce(),n=Dt().overrideAll,i=Sa(),a={error_x:r.extendFlat({},i),error_y:r.extendFlat({},i)};delete a.error_x.copy_zstyle,delete a.error_y.copy_zstyle,delete a.error_y.copy_ystyle;var o={error_x:r.extendFlat({},i),error_y:r.extendFlat({},i),error_z:r.extendFlat({},i)};delete o.error_x.copy_ystyle,delete o.error_y.copy_ystyle,delete o.error_z.copy_ystyle,delete o.error_z.copy_zstyle,e.exports={moduleType:"component",name:"errorbars",schema:{traces:{scatter:a,bar:a,histogram:a,scatter3d:n(o,"calc","nested"),scattergl:n(a,"calc","nested")}},supplyDefaults:Ea(),calc:Ia(),makeComputeError:Ca(),plot:La(),style:Pa(),hoverInfo:function(t,e,r){(e.error_y||{}).visible&&(r.yerr=t.yh-t.y,e.error_y.symmetric||(r.yerrneg=t.y-t.ys)),(e.error_x||{}).visible&&(r.xerr=t.xh-t.x,e.error_x.symmetric||(r.xerrneg=t.x-t.xs))}}}}),Da=m({"src/components/colorbar/constants.js"(t,e){e.exports={cn:{colorbar:"colorbar",cbbg:"cbbg",cbfill:"cbfill",cbfills:"cbfills",cbline:"cbline",cblines:"cblines",cbaxis:"cbaxis",cbtitleunshift:"cbtitleunshift",cbtitle:"cbtitle",cboutline:"cboutline",crisp:"crisp",jsPlaceholder:"js-placeholder"}}}}),Oa=m({"src/components/colorbar/draw.js"(t,e){var r=b(),n=F(),i=Ae(),a=Ht(),o=ar(),s=pr(),l=ce(),c=l.strTranslate,u=B().extendFlat,h=dr(),f=tr(),p=W(),d=er(),m=Ee(),g=Ce().flipScale,y=ki(),v=Ai(),x=Le(),_=Se(),w=_.LINE_SPACING,T=_.FROM_TL,k=_.FROM_BR,A=Da().cn;e.exports={draw:function(t){var e=t._fullLayout._infolayer.selectAll("g."+A.colorbar).data(function(t){var e,r,n,i,a=t._fullLayout,o=t.calcdata,s=[];function l(t){return u(t,{_fillcolor:null,_line:{color:null,width:null,dash:null},_levels:{start:null,end:null,size:null},_filllevels:null,_fillgradient:null,_zrange:null})}function c(){"function"==typeof i.calc?i.calc(t,n,e):(e._fillgradient=r.reversescale?g(r.colorscale):r.colorscale,e._zrange=[r[i.min],r[i.max]])}for(var h=0;h0?n>=l:n<=l));i++)n>u&&n0?n>=l:n<=l));i++)n>r[0]&&n1){var 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t,e;(s&&ct||!s&&!ct)&&("top"===V&&(t=L+B.l+tt*z,e=P+B.t+et*(1-ot-Q)+3+.75*yt),"bottom"===V&&(t=L+B.l+tt*z,e=P+B.t+et*(1-ot)-3-.25*yt),"right"===V&&(e=P+B.t+et*D+3+.75*yt,t=L+B.l+tt*ot),bt(lt._id+"title",{attributes:{x:t,y:e,"text-anchor":s?"start":"middle"}}))},function(){if(!s&&!ct||s&&ct){var i,u=t.select("."+A.cbtitle),h=u.select("text"),p=[-M/2,M/2],d=u.select(".h"+lt._id+"title-math-group").node(),g=15.6;if(h.node()&&(g=parseInt(h.node().style.fontSize,10)*w),d?(i=f.bBox(d),_t=i.width,(xt=i.height)>g&&(p[1]-=(xt-g)/2)):h.node()&&!h.classed(A.jsPlaceholder)&&(i=f.bBox(h.node()),_t=i.width,xt=i.height),s){if(xt){if(xt+=5,"top"===V)lt.domain[1]-=xt/B.h,p[1]*=-1;else{lt.domain[0]+=xt/B.h;var y=m.lineCount(h);p[1]+=(1-y)*g}u.attr("transform",c(p[0],p[1])),lt.setScale()}}else 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u=n(a+"points",c);u?(n("jitter","all"===u?.3:0),n("pointpos","all"===u?-1.5:0),n("marker.symbol"),n("marker.opacity"),n("marker.size"),n("marker.angle"),n("marker.color",e.line.color),n("marker.line.color"),n("marker.line.width"),"suspectedoutliers"===u&&(n("marker.line.outliercolor",e.marker.color),n("marker.line.outlierwidth")),n("selected.marker.color"),n("unselected.marker.color"),n("selected.marker.size"),n("unselected.marker.size"),n("text"),n("hovertext")):delete e.marker;var h=n("hoveron");("all"===h||-1!==h.indexOf("points"))&&(n("hovertemplate"),n("hovertemplatefallback")),r.coerceSelectionMarkerOpacity(e,n)}e.exports={supplyDefaults:function(t,e,n,o){function s(n,i){return r.coerce(t,e,l,n,i)}if(c(t,e,s,o),!1!==e.visible){a(t,e,o,s),s("xhoverformat"),s("yhoverformat");var h=e._hasPreCompStats;h&&(s("lowerfence"),s("upperfence")),s("line.color",(t.marker||{}).color||n),s("line.width"),s("fillcolor",i.addOpacity(e.line.color,.5));var f=!1;if(h){var 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n=t._fullLayout,a=t.calcdata,o=n._subplots[i],s=0;s0){var _,b,w,T,k,A=t.xa,M=t.ya;"h"===d.orientation?(k=e,_="y",w=M,b="x",T=A):(k=s,_="x",w=A,b="y",T=M);var S=p[t.index];if(k>=S.span[0]&&k<=S.span[1]){var E=n.extendFlat({},t),C=T.c2p(k,!0),I=o.getKdeValue(S,d,k),L=o.getPositionOnKdePath(S,d,C),P=w._offset,z=w._length;E[_+"0"]=L[0],E[_+"1"]=L[1],E[b+"0"]=E[b+"1"]=C,E[b+"Label"]=b+": "+i.hoverLabelText(T,k,d[b+"hoverformat"])+", "+p[0].t.labels.kde+" "+I.toFixed(3);for(var D=0,O=0;O path").each((function(t){if(!t.isBlank){var e=s.marker;r.select(this).call(i.fill,t.mc||e.color).call(i.stroke,t.mlc||e.line.color).call(n.dashLine,e.line.dash,t.mlw||e.line.width).style("opacity",s.selectedpoints&&!t.selected?a:1)}})),l(o,s,t),o.selectAll(".regions").each((function(){r.select(this).selectAll("path").style("stroke-width",0).call(i.fill,s.connector.fillcolor)})),o.selectAll(".lines").each((function(){var 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k=n.ensureSingle(d,"g","slicetext"),S=n.ensureSingle(k,"text","",(function(t){t.attr("data-notex",1)})),D=n.ensureUniformFontSize(t,c.determineTextFont(I,o,C.font));S.text(o._text||" ").classed("slicetext",!0).attr("text-anchor",P?"end":L?"start":"middle").call(i.font,D).call(a.convertToTspans,t),o.textBB=i.bBox(S.node()),o.transform=b(o,{fontSize:D.size}),o.transform.fontSize=D.size,T?S.transition().attrTween("transform",(function(t){var e=M(t,f,j(),[g,y]);return function(t){return w(e(t))}})):S.attr("transform",w(o))})),F}}}),Od=m({"src/traces/icicle/plot.js"(t,e){var r=bd(),n=Dd();e.exports=function(t,e,i,a){return 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vertices.\n// These vertices are used to make up the triangles of the cone by the following:\n// segment + 0 top vertex\n// segment + 1 perimeter vertex a+1\n// segment + 2 perimeter vertex a\n// segment + 3 center base vertex\n// segment + 4 perimeter vertex a\n// segment + 5 perimeter vertex a+1\n// Where segment is the number of the radial segment * 6 and a is the angle at that radial segment.\n// To go from index to segment, floor(index / 6)\n// To go from segment to angle, 2*pi * (segment/segmentCount)\n// To go from index to segment index, index - (segment*6)\n//\nvec3 getConePosition(vec3 d, float rawIndex, float coneOffset, out vec3 normal) {\n\n const float segmentCount = 8.0;\n\n float index = rawIndex - floor(rawIndex /\n (segmentCount * 6.0)) *\n (segmentCount * 6.0);\n\n float segment = floor(0.001 + index/6.0);\n float segmentIndex = index - (segment*6.0);\n\n normal = -normalize(d);\n\n if (segmentIndex > 2.99 && segmentIndex < 3.01) {\n return mix(vec3(0.0), -d, coneOffset);\n }\n\n float nextAngle = (\n (segmentIndex > 0.99 && segmentIndex < 1.01) ||\n (segmentIndex > 4.99 && segmentIndex < 5.01)\n ) ? 1.0 : 0.0;\n float angle = 2.0 * 3.14159 * ((segment + nextAngle) / segmentCount);\n\n vec3 v1 = mix(d, vec3(0.0), coneOffset);\n vec3 v2 = v1 - d;\n\n vec3 u = getOrthogonalVector(d);\n vec3 v = normalize(cross(u, d));\n\n vec3 x = u * cos(angle) * length(d)*0.25;\n vec3 y = v * sin(angle) * length(d)*0.25;\n vec3 v3 = v2 + x + y;\n if (segmentIndex < 3.0) {\n vec3 tx = u * sin(angle);\n vec3 ty = v * -cos(angle);\n vec3 tangent = tx + ty;\n normal = normalize(cross(v3 - v1, tangent));\n }\n\n if (segmentIndex == 0.0) {\n return mix(d, vec3(0.0), coneOffset);\n }\n return v3;\n}\n\nattribute vec3 vector;\nattribute vec4 color, position;\nattribute vec2 uv;\n\nuniform float vectorScale, coneScale, coneOffset;\nuniform mat4 model, view, projection, inverseModel;\nuniform vec3 eyePosition, lightPosition;\n\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n // Scale the vector magnitude to stay constant with\n // model & view changes.\n vec3 normal;\n vec3 XYZ = getConePosition(mat3(model) * ((vectorScale * coneScale) * vector), position.w, coneOffset, normal);\n vec4 conePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\n\n //Lighting geometry parameters\n vec4 cameraCoordinate = view * conePosition;\n cameraCoordinate.xyz /= cameraCoordinate.w;\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\n\n // vec4 m_position = model * vec4(conePosition, 1.0);\n vec4 t_position = view * conePosition;\n gl_Position = projection * t_position;\n\n f_color = color;\n f_data = conePosition.xyz;\n f_position = position.xyz;\n f_uv = uv;\n}\n"]),a=n(["#extension GL_OES_standard_derivatives : enable\n\nprecision highp float;\n#define GLSLIFY 1\n\nfloat beckmannDistribution(float x, float roughness) {\n float NdotH = max(x, 0.0001);\n float cos2Alpha = NdotH * NdotH;\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\n float roughness2 = roughness * roughness;\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\n return exp(tan2Alpha / roughness2) / denom;\n}\n\nfloat cookTorranceSpecular(\n vec3 lightDirection,\n vec3 viewDirection,\n vec3 surfaceNormal,\n float roughness,\n float fresnel) {\n\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\n\n //Half angle vector\n vec3 H = normalize(lightDirection + viewDirection);\n\n //Geometric term\n float NdotH = max(dot(surfaceNormal, H), 0.0);\n float VdotH = max(dot(viewDirection, H), 0.000001);\n float LdotH = max(dot(lightDirection, H), 0.000001);\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\n float G = min(1.0, min(G1, G2));\n \n //Distribution term\n float D = beckmannDistribution(NdotH, roughness);\n\n //Fresnel term\n float F = pow(1.0 - VdotN, fresnel);\n\n //Multiply terms and done\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\n}\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\nuniform sampler2D texture;\n\nvarying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position;\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n vec3 N = normalize(f_normal);\n vec3 L = normalize(f_lightDirection);\n vec3 V = normalize(f_eyeDirection);\n\n if(gl_FrontFacing) {\n N = -N;\n }\n\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n\n vec4 surfaceColor = f_color * texture2D(texture, f_uv);\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\n\n gl_FragColor = litColor * opacity;\n}\n"]),o=n(["precision highp float;\n\nprecision highp float;\n#define GLSLIFY 1\n\nvec3 getOrthogonalVector(vec3 v) {\n // Return up-vector for only-z vector.\n // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0).\n // From the above if-statement we have ||a|| > 0 U ||b|| > 0.\n // Assign z = 0, x = -b, y = a:\n // a*-b + b*a + c*0 = -ba + ba + 0 = 0\n if 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",35665:"FLOAT_VEC3",35666:"FLOAT_VEC4",35667:"INT_VEC2",35668:"INT_VEC3",35669:"INT_VEC4",35670:"BOOL",35671:"BOOL_VEC2",35672:"BOOL_VEC3",35673:"BOOL_VEC4",35674:"FLOAT_MAT2",35675:"FLOAT_MAT3",35676:"FLOAT_MAT4",35678:"SAMPLER_2D",35680:"SAMPLER_CUBE",35712:"DELETE_STATUS",35713:"COMPILE_STATUS",35714:"LINK_STATUS",35715:"VALIDATE_STATUS",35716:"INFO_LOG_LENGTH",35717:"ATTACHED_SHADERS",35718:"ACTIVE_UNIFORMS",35719:"ACTIVE_UNIFORM_MAX_LENGTH",35720:"SHADER_SOURCE_LENGTH",35721:"ACTIVE_ATTRIBUTES",35722:"ACTIVE_ATTRIBUTE_MAX_LENGTH",35724:"SHADING_LANGUAGE_VERSION",35725:"CURRENT_PROGRAM",36003:"STENCIL_BACK_REF",36004:"STENCIL_BACK_VALUE_MASK",36005:"STENCIL_BACK_WRITEMASK",36006:"FRAMEBUFFER_BINDING",36007:"RENDERBUFFER_BINDING",36048:"FRAMEBUFFER_ATTACHMENT_OBJECT_TYPE",36049:"FRAMEBUFFER_ATTACHMENT_OBJECT_NAME",36050:"FRAMEBUFFER_ATTACHMENT_TEXTURE_LEVEL",36051:"FRAMEBUFFER_ATTACHMENT_TEXTURE_CUBE_MAP_FACE",36053:"FRAMEBUFFER_COMPLETE",36054:"FRAMEBUFFER_INCOMPLETE_ATTACHMENT",36055:"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT",36057:"FRAMEBUFFER_INCOMPLETE_DIMENSIONS",36061:"FRAMEBUFFER_UNSUPPORTED",36064:"COLOR_ATTACHMENT0",36096:"DEPTH_ATTACHMENT",36128:"STENCIL_ATTACHMENT",36160:"FRAMEBUFFER",36161:"RENDERBUFFER",36162:"RENDERBUFFER_WIDTH",36163:"RENDERBUFFER_HEIGHT",36164:"RENDERBUFFER_INTERNAL_FORMAT",36168:"STENCIL_INDEX8",36176:"RENDERBUFFER_RED_SIZE",36177:"RENDERBUFFER_GREEN_SIZE",36178:"RENDERBUFFER_BLUE_SIZE",36179:"RENDERBUFFER_ALPHA_SIZE",36180:"RENDERBUFFER_DEPTH_SIZE",36181:"RENDERBUFFER_STENCIL_SIZE",36194:"RGB565",36336:"LOW_FLOAT",36337:"MEDIUM_FLOAT",36338:"HIGH_FLOAT",36339:"LOW_INT",36340:"MEDIUM_INT",36341:"HIGH_INT",36346:"SHADER_COMPILER",36347:"MAX_VERTEX_UNIFORM_VECTORS",36348:"MAX_VARYING_VECTORS",36349:"MAX_FRAGMENT_UNIFORM_VECTORS",37440:"UNPACK_FLIP_Y_WEBGL",37441:"UNPACK_PREMULTIPLY_ALPHA_WEBGL",37442:"CONTEXT_LOST_WEBGL",37443:"UNPACK_COLORSPACE_CONVERSION_WEBGL",37444:"BROWSER_DEFAULT_WEBGL"}},781:function(t,e,r){t.exports=function(t,e){var r=[];return e=+e||0,n(t.hi(t.shape[0]-1),r,e),r};var n=r(3349)},783:function(t){t.exports=function(t,e,r,n){var i,a,o,s,l,c=e[0],u=e[1],h=e[2],f=e[3],p=r[0],d=r[1],m=r[2],g=r[3];return(a=c*p+u*d+h*m+f*g)<0&&(a=-a,p=-p,d=-d,m=-m,g=-g),1-a>1e-6?(i=Math.acos(a),o=Math.sin(i),s=Math.sin((1-n)*i)/o,l=Math.sin(n*i)/o):(s=1-n,l=n),t[0]=s*c+l*p,t[1]=s*u+l*d,t[2]=s*h+l*m,t[3]=s*f+l*g,t}},799:function(t,e,r){var n=r(3236),i=r(9405),a=n(["precision mediump float;\n#define GLSLIFY 1\nattribute vec2 position;\nvarying vec2 uv;\nvoid main() {\n uv = position;\n gl_Position = vec4(position, 0, 1);\n}"]),o=n(["precision mediump float;\n#define GLSLIFY 1\n\nuniform sampler2D accumBuffer;\nvarying vec2 uv;\n\nvoid main() {\n vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0));\n gl_FragColor = min(vec4(1,1,1,1), accum);\n}"]);t.exports=function(t){return i(t,a,o,null,[{name:"position",type:"vec2"}])}},811:function(t){t.exports=function(t,e){return t[0]=1/e[0],t[1]=1/e[1],t[2]=1/e[2],t}},840:function(t,e,r){var n=r(3236),i=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position, normal;\nattribute vec4 color;\nattribute vec2 uv;\n\nuniform mat4 model\n , view\n , projection\n , inverseModel;\nuniform vec3 eyePosition\n , lightPosition;\n\nvarying vec3 f_normal\n , f_lightDirection\n , f_eyeDirection\n , f_data;\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvec4 project(vec3 p) {\n return projection * (view * (model * vec4(p, 1.0)));\n}\n\nvoid main() {\n gl_Position = project(position);\n\n //Lighting geometry parameters\n vec4 cameraCoordinate = view * vec4(position , 1.0);\n cameraCoordinate.xyz /= cameraCoordinate.w;\n f_lightDirection = lightPosition - cameraCoordinate.xyz;\n f_eyeDirection = eyePosition - cameraCoordinate.xyz;\n f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz);\n\n f_color = color;\n f_data = position;\n f_uv = uv;\n}\n"]),a=n(["#extension GL_OES_standard_derivatives : enable\n\nprecision highp float;\n#define GLSLIFY 1\n\nfloat beckmannDistribution(float x, float roughness) {\n float NdotH = max(x, 0.0001);\n float cos2Alpha = NdotH * NdotH;\n float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha;\n float roughness2 = roughness * roughness;\n float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha;\n return exp(tan2Alpha / roughness2) / denom;\n}\n\nfloat cookTorranceSpecular(\n vec3 lightDirection,\n vec3 viewDirection,\n vec3 surfaceNormal,\n float roughness,\n float fresnel) {\n\n float VdotN = max(dot(viewDirection, surfaceNormal), 0.0);\n float LdotN = max(dot(lightDirection, surfaceNormal), 0.0);\n\n //Half angle vector\n vec3 H = normalize(lightDirection + viewDirection);\n\n //Geometric term\n float NdotH = max(dot(surfaceNormal, H), 0.0);\n float VdotH = max(dot(viewDirection, H), 0.000001);\n float LdotH = max(dot(lightDirection, H), 0.000001);\n float G1 = (2.0 * NdotH * VdotN) / VdotH;\n float G2 = (2.0 * NdotH * LdotN) / LdotH;\n float G = min(1.0, min(G1, G2));\n \n //Distribution term\n float D = beckmannDistribution(NdotH, roughness);\n\n //Fresnel term\n float F = pow(1.0 - VdotN, fresnel);\n\n //Multiply terms and done\n return G * F * D / max(3.14159265 * VdotN, 0.000001);\n}\n\n//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform float roughness\n , fresnel\n , kambient\n , kdiffuse\n , kspecular;\nuniform sampler2D texture;\n\nvarying vec3 f_normal\n , f_lightDirection\n , f_eyeDirection\n , f_data;\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n if (f_color.a == 0.0 ||\n outOfRange(clipBounds[0], clipBounds[1], f_data)\n ) discard;\n\n vec3 N = normalize(f_normal);\n vec3 L = normalize(f_lightDirection);\n vec3 V = normalize(f_eyeDirection);\n\n if(gl_FrontFacing) {\n N = -N;\n }\n\n float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\n //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\n\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n\n vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\n\n gl_FragColor = litColor * f_color.a;\n}\n"]),o=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position;\nattribute vec4 color;\nattribute vec2 uv;\n\nuniform mat4 model, view, projection;\n\nvarying vec4 f_color;\nvarying vec3 f_data;\nvarying vec2 f_uv;\n\nvoid main() {\n gl_Position = projection * (view * (model * vec4(position, 1.0)));\n f_color = color;\n f_data = position;\n f_uv = uv;\n}"]),s=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform sampler2D texture;\nuniform float opacity;\n\nvarying vec4 f_color;\nvarying vec3 f_data;\nvarying vec2 f_uv;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard;\n\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\n}"]),l=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nattribute vec3 position;\nattribute vec4 color;\nattribute vec2 uv;\nattribute float pointSize;\n\nuniform mat4 model, view, projection;\nuniform vec3 clipBounds[2];\n\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n\n gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0);\n } else {\n gl_Position = projection * (view * (model * vec4(position, 1.0)));\n }\n gl_PointSize = pointSize;\n f_color = color;\n f_uv = uv;\n}"]),c=n(["precision highp float;\n#define GLSLIFY 1\n\nuniform sampler2D texture;\nuniform float opacity;\n\nvarying vec4 f_color;\nvarying vec2 f_uv;\n\nvoid main() {\n vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5);\n if(dot(pointR, pointR) > 0.25) {\n discard;\n }\n gl_FragColor = f_color * texture2D(texture, f_uv) * opacity;\n}"]),u=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position;\nattribute vec4 id;\n\nuniform mat4 model, view, projection;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n gl_Position = projection * (view * (model * vec4(position, 1.0)));\n f_id = id;\n f_position = position;\n}"]),h=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform float pickId;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard;\n\n gl_FragColor = vec4(pickId, f_id.xyz);\n}"]),f=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nattribute vec3 position;\nattribute float pointSize;\nattribute vec4 id;\n\nuniform mat4 model, view, projection;\nuniform vec3 clipBounds[2];\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n\n gl_Position = vec4(0.0, 0.0, 0.0, 0.0);\n } else {\n gl_Position = projection * (view * (model * vec4(position, 1.0)));\n gl_PointSize = pointSize;\n }\n f_id = id;\n f_position = position;\n}"]),p=n(["precision highp float;\n#define GLSLIFY 1\n\nattribute vec3 position;\n\nuniform mat4 model, view, projection;\n\nvoid main() {\n gl_Position = projection * (view * (model * vec4(position, 1.0)));\n}"]),d=n(["precision highp float;\n#define GLSLIFY 1\n\nuniform vec3 contourColor;\n\nvoid main() {\n gl_FragColor = vec4(contourColor, 1.0);\n}\n"]);e.meshShader={vertex:i,fragment:a,attributes:[{name:"position",type:"vec3"},{name:"normal",type:"vec3"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"}]},e.wireShader={vertex:o,fragment:s,attributes:[{name:"position",type:"vec3"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"}]},e.pointShader={vertex:l,fragment:c,attributes:[{name:"position",type:"vec3"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"},{name:"pointSize",type:"float"}]},e.pickShader={vertex:u,fragment:h,attributes:[{name:"position",type:"vec3"},{name:"id",type:"vec4"}]},e.pointPickShader={vertex:f,fragment:h,attributes:[{name:"position",type:"vec3"},{name:"pointSize",type:"float"},{name:"id",type:"vec4"}]},e.contourShader={vertex:p,fragment:d,attributes:[{name:"position",type:"vec3"}]}},855:function(t,e,r){t.exports={init:function(t){var e=i.nextPow2(t);l.length>>1;a(d,S);var E=0,C=0;for(T=0;T=o)m(u,h,C--,I=I-o|0);else if(I>=0)m(l,c,E--,I);else if(I<=-o){I=-I-o|0;for(var L=0;L>>1;a(d,E);var C=0,I=0,L=0;for(k=0;k>1==d[2*k+3]>>1&&(z=2,k+=1),P<0){for(var D=-(P>>1)-1,O=0;O>1)-1,0===z?m(l,c,C--,D):1===z?m(u,h,I--,D):2===z&&m(f,p,L--,D)}},scanBipartite:function(t,e,r,n,i,s,u,h,f,p,y,v){var x=0,_=2*t,b=e,w=e+t,T=1,k=1;n?k=o:T=o;for(var A=i;A>>1;a(d,C);var I=0;for(A=0;A=o?(P=!n,M-=o):(P=!!n,M-=1),P)g(l,c,I++,M);else{var z=v[M],D=_*M,O=y[D+e+1],R=y[D+e+1+t];t:for(var F=0;F>>1;a(d,T);var k=0;for(x=0;x=o)l[k++]=_-o;else{var M=p[_-=1],S=g*_,E=f[S+e+1],C=f[S+e+1+t];t:for(var I=0;I=0;--I)if(l[I]===_){for(D=I+1;D max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 lowerBound, upperBound;\nuniform float contourTint;\nuniform vec4 contourColor;\nuniform sampler2D colormap;\nuniform vec3 clipBounds[2];\nuniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity;\nuniform float vertexColor;\n\nvarying float value, kill;\nvarying vec3 worldCoordinate;\nvarying vec3 lightDirection, eyeDirection, surfaceNormal;\nvarying vec4 vColor;\n\nvoid main() {\n if (\n kill > 0.0 ||\n vColor.a == 0.0 ||\n outOfRange(clipBounds[0], clipBounds[1], worldCoordinate)\n ) discard;\n\n vec3 N = normalize(surfaceNormal);\n vec3 V = normalize(eyeDirection);\n vec3 L = normalize(lightDirection);\n\n if(gl_FrontFacing) {\n N = -N;\n }\n\n float specular = max(beckmannSpecular(L, V, N, roughness), 0.);\n float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n\n //decide how to interpolate color — in vertex or in fragment\n vec4 surfaceColor =\n step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) +\n step(.5, vertexColor) * vColor;\n\n vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb 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objectOffset.z;\n kill = -1.0;\n planeCoordinate = uv.zw;\n\n vColor = texture2D(colormap, vec2(value, value));\n\n //Don't do lighting for contours\n surfaceNormal = vec3(1,0,0);\n eyeDirection = vec3(0,1,0);\n lightDirection = vec3(0,0,1);\n}\n"]),l=i(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec2 shape;\nuniform vec3 clipBounds[2];\nuniform float pickId;\n\nvarying float value, kill;\nvarying vec3 worldCoordinate;\nvarying vec2 planeCoordinate;\nvarying vec3 surfaceNormal;\n\nvec2 splitFloat(float v) {\n float vh = 255.0 * 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r=n.hi(t),o=n.lo(t);return e>t==t>0?o===a?(r+=1,o=0):o+=1:0===o?(o=a,r-=1):o-=1,n.pack(o,r)}},1283:function(t,e,r){var n=r(9405),i=r(3236),a=i(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nattribute vec3 position;\nattribute vec4 color;\nattribute vec2 glyph;\nattribute vec4 id;\n\nuniform vec4 highlightId;\nuniform float highlightScale;\nuniform mat4 model, view, projection;\nuniform vec3 clipBounds[2];\n\nvarying vec4 interpColor;\nvarying vec4 pickId;\nvarying vec3 dataCoordinate;\n\nvoid main() {\n if (outOfRange(clipBounds[0], 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if(distance(highlightId, id) < 0.0001) {\n lscale *= highlightScale;\n }\n\n vec4 clipCenter = projection * (view * (model * vec4(position, 1)));\n vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y;\n vec4 clipPosition = projection * (view * (model * vec4(dataPosition, 1)));\n\n gl_Position = clipPosition;\n interpColor = color;\n pickId = id;\n dataCoordinate = dataPosition;\n }\n}\n"]),l=i(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 fragClipBounds[2];\nuniform 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y=[{family:this.labelFont[0],style:this.labelFontStyle[0],weight:this.labelFontWeight[0],variant:this.labelFontVariant[0]},{family:this.labelFont[1],style:this.labelFontStyle[1],weight:this.labelFontWeight[1],variant:this.labelFontVariant[1]},{family:this.labelFont[2],style:this.labelFontStyle[2],weight:this.labelFontWeight[2],variant:this.labelFontVariant[2]}],v=[{family:this.tickFont[0],style:this.tickFontStyle[0],weight:this.tickFontWeight[0],variant:this.tickFontVariant[0]},{family:this.tickFont[1],style:this.tickFontStyle[1],weight:this.tickFontWeight[1],variant:this.tickFontVariant[1]},{family:this.tickFont[2],style:this.tickFontStyle[2],weight:this.tickFontWeight[2],variant:this.tickFontVariant[2]}];this._text?this._text&&(g||u)&&this._text.update(this.bounds,this.labels,y,this.ticks,v):this._text=n(this.gl,this.bounds,this.labels,y,this.ticks,v),this._lines&&u&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=i(this.gl,this.bounds,this.ticks))};var g=[new 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tubeScale;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() {\n vec3 normal;\n vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal);\n vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0);\n\n gl_Position = projection * (view * tubePosition);\n f_id = id;\n f_position = position.xyz;\n}\n"]),s=n(["precision highp float;\n#define GLSLIFY 1\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform float pickId;\n\nvarying vec3 f_position;\nvarying vec4 f_id;\n\nvoid main() 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c=1;c>>26,h=67108863&l,f=Math.min(c,e.length-1),p=Math.max(0,c-t.length+1);p<=f;p++){var d=c-p|0;u+=(o=(i=0|t.words[d])*(a=0|e.words[p])+h)/67108864|0,h=67108863&o}r.words[c]=0|h,l=0|u}return 0!==l?r.words[c]=0|l:r.length--,r.strip()}a.prototype.toString=function(t,e){var r;if(e=0|e||1,16===(t=t||10)||"hex"===t){r="";for(var i=0,a=0,o=0;o>>24-i&16777215)||o!==this.length-1?u[6-l.length]+l+r:l+r,(i+=2)>=26&&(i-=26,o--)}for(0!==a&&(r=a.toString(16)+r);r.length%e!=0;)r="0"+r;return 0!==this.negative&&(r="-"+r),r}if(t===(0|t)&&t>=2&&t<=36){var c=h[t],p=f[t];r="";var d=this.clone();for(d.negative=0;!d.isZero();){var m=d.modn(p).toString(t);r=(d=d.idivn(p)).isZero()?m+r:u[c-m.length]+m+r}for(this.isZero()&&(r="0"+r);r.length%e!=0;)r="0"+r;return 0!==this.negative&&(r="-"+r),r}n(!1,"Base should be between 2 and 36")},a.prototype.toNumber=function(){var t=this.words[0];return 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wt=(c+(n=n+Math.imul(h,at)|0)|0)+((8191&(i=(i=i+Math.imul(h,ot)|0)+Math.imul(f,at)|0))<<13)|0;c=((a=a+Math.imul(f,ot)|0)+(i>>>13)|0)+(wt>>>26)|0,wt&=67108863,n=Math.imul(P,U),i=(i=Math.imul(P,V))+Math.imul(z,U)|0,a=Math.imul(z,V),n=n+Math.imul(C,H)|0,i=(i=i+Math.imul(C,G)|0)+Math.imul(I,H)|0,a=a+Math.imul(I,G)|0,n=n+Math.imul(M,Z)|0,i=(i=i+Math.imul(M,Y)|0)+Math.imul(S,Z)|0,a=a+Math.imul(S,Y)|0,n=n+Math.imul(T,$)|0,i=(i=i+Math.imul(T,K)|0)+Math.imul(k,$)|0,a=a+Math.imul(k,K)|0,n=n+Math.imul(_,Q)|0,i=(i=i+Math.imul(_,tt)|0)+Math.imul(b,Q)|0,a=a+Math.imul(b,tt)|0,n=n+Math.imul(y,rt)|0,i=(i=i+Math.imul(y,nt)|0)+Math.imul(v,rt)|0,a=a+Math.imul(v,nt)|0,n=n+Math.imul(d,at)|0,i=(i=i+Math.imul(d,ot)|0)+Math.imul(m,at)|0,a=a+Math.imul(m,ot)|0;var Tt=(c+(n=n+Math.imul(h,lt)|0)|0)+((8191&(i=(i=i+Math.imul(h,ct)|0)+Math.imul(f,lt)|0))<<13)|0;c=((a=a+Math.imul(f,ct)|0)+(i>>>13)|0)+(Tt>>>26)|0,Tt&=67108863,n=Math.imul(O,U),i=(i=Math.imul(O,V))+Math.imul(R,U)|0,a=Math.imul(R,V),n=n+Math.imul(P,H)|0,i=(i=i+Math.imul(P,G)|0)+Math.imul(z,H)|0,a=a+Math.imul(z,G)|0,n=n+Math.imul(C,Z)|0,i=(i=i+Math.imul(C,Y)|0)+Math.imul(I,Z)|0,a=a+Math.imul(I,Y)|0,n=n+Math.imul(M,$)|0,i=(i=i+Math.imul(M,K)|0)+Math.imul(S,$)|0,a=a+Math.imul(S,K)|0,n=n+Math.imul(T,Q)|0,i=(i=i+Math.imul(T,tt)|0)+Math.imul(k,Q)|0,a=a+Math.imul(k,tt)|0,n=n+Math.imul(_,rt)|0,i=(i=i+Math.imul(_,nt)|0)+Math.imul(b,rt)|0,a=a+Math.imul(b,nt)|0,n=n+Math.imul(y,at)|0,i=(i=i+Math.imul(y,ot)|0)+Math.imul(v,at)|0,a=a+Math.imul(v,ot)|0,n=n+Math.imul(d,lt)|0,i=(i=i+Math.imul(d,ct)|0)+Math.imul(m,lt)|0,a=a+Math.imul(m,ct)|0;var kt=(c+(n=n+Math.imul(h,ht)|0)|0)+((8191&(i=(i=i+Math.imul(h,ft)|0)+Math.imul(f,ht)|0))<<13)|0;c=((a=a+Math.imul(f,ft)|0)+(i>>>13)|0)+(kt>>>26)|0,kt&=67108863,n=Math.imul(B,U),i=(i=Math.imul(B,V))+Math.imul(j,U)|0,a=Math.imul(j,V),n=n+Math.imul(O,H)|0,i=(i=i+Math.imul(O,G)|0)+Math.imul(R,H)|0,a=a+Math.imul(R,G)|0,n=n+Math.imul(P,Z)|0,i=(i=i+Math.imul(P,Y)|0)+Math.imul(z,Z)|0,a=a+Math.imul(z,Y)|0,n=n+Math.imul(C,$)|0,i=(i=i+Math.imul(C,K)|0)+Math.imul(I,$)|0,a=a+Math.imul(I,K)|0,n=n+Math.imul(M,Q)|0,i=(i=i+Math.imul(M,tt)|0)+Math.imul(S,Q)|0,a=a+Math.imul(S,tt)|0,n=n+Math.imul(T,rt)|0,i=(i=i+Math.imul(T,nt)|0)+Math.imul(k,rt)|0,a=a+Math.imul(k,nt)|0,n=n+Math.imul(_,at)|0,i=(i=i+Math.imul(_,ot)|0)+Math.imul(b,at)|0,a=a+Math.imul(b,ot)|0,n=n+Math.imul(y,lt)|0,i=(i=i+Math.imul(y,ct)|0)+Math.imul(v,lt)|0,a=a+Math.imul(v,ct)|0,n=n+Math.imul(d,ht)|0,i=(i=i+Math.imul(d,ft)|0)+Math.imul(m,ht)|0,a=a+Math.imul(m,ft)|0;var At=(c+(n=n+Math.imul(h,dt)|0)|0)+((8191&(i=(i=i+Math.imul(h,mt)|0)+Math.imul(f,dt)|0))<<13)|0;c=((a=a+Math.imul(f,mt)|0)+(i>>>13)|0)+(At>>>26)|0,At&=67108863,n=Math.imul(B,H),i=(i=Math.imul(B,G))+Math.imul(j,H)|0,a=Math.imul(j,G),n=n+Math.imul(O,Z)|0,i=(i=i+Math.imul(O,Y)|0)+Math.imul(R,Z)|0,a=a+Math.imul(R,Y)|0,n=n+Math.imul(P,$)|0,i=(i=i+Math.imul(P,K)|0)+Math.imul(z,$)|0,a=a+Math.imul(z,K)|0,n=n+Math.imul(C,Q)|0,i=(i=i+Math.imul(C,tt)|0)+Math.imul(I,Q)|0,a=a+Math.imul(I,tt)|0,n=n+Math.imul(M,rt)|0,i=(i=i+Math.imul(M,nt)|0)+Math.imul(S,rt)|0,a=a+Math.imul(S,nt)|0,n=n+Math.imul(T,at)|0,i=(i=i+Math.imul(T,ot)|0)+Math.imul(k,at)|0,a=a+Math.imul(k,ot)|0,n=n+Math.imul(_,lt)|0,i=(i=i+Math.imul(_,ct)|0)+Math.imul(b,lt)|0,a=a+Math.imul(b,ct)|0,n=n+Math.imul(y,ht)|0,i=(i=i+Math.imul(y,ft)|0)+Math.imul(v,ht)|0,a=a+Math.imul(v,ft)|0;var Mt=(c+(n=n+Math.imul(d,dt)|0)|0)+((8191&(i=(i=i+Math.imul(d,mt)|0)+Math.imul(m,dt)|0))<<13)|0;c=((a=a+Math.imul(m,mt)|0)+(i>>>13)|0)+(Mt>>>26)|0,Mt&=67108863,n=Math.imul(B,Z),i=(i=Math.imul(B,Y))+Math.imul(j,Z)|0,a=Math.imul(j,Y),n=n+Math.imul(O,$)|0,i=(i=i+Math.imul(O,K)|0)+Math.imul(R,$)|0,a=a+Math.imul(R,K)|0,n=n+Math.imul(P,Q)|0,i=(i=i+Math.imul(P,tt)|0)+Math.imul(z,Q)|0,a=a+Math.imul(z,tt)|0,n=n+Math.imul(C,rt)|0,i=(i=i+Math.imul(C,nt)|0)+Math.imul(I,rt)|0,a=a+Math.imul(I,nt)|0,n=n+Math.imul(M,at)|0,i=(i=i+Math.imul(M,ot)|0)+Math.imul(S,at)|0,a=a+Math.imul(S,ot)|0,n=n+Math.imul(T,lt)|0,i=(i=i+Math.imul(T,ct)|0)+Math.imul(k,lt)|0,a=a+Math.imul(k,ct)|0,n=n+Math.imul(_,ht)|0,i=(i=i+Math.imul(_,ft)|0)+Math.imul(b,ht)|0,a=a+Math.imul(b,ft)|0;var St=(c+(n=n+Math.imul(y,dt)|0)|0)+((8191&(i=(i=i+Math.imul(y,mt)|0)+Math.imul(v,dt)|0))<<13)|0;c=((a=a+Math.imul(v,mt)|0)+(i>>>13)|0)+(St>>>26)|0,St&=67108863,n=Math.imul(B,$),i=(i=Math.imul(B,K))+Math.imul(j,$)|0,a=Math.imul(j,K),n=n+Math.imul(O,Q)|0,i=(i=i+Math.imul(O,tt)|0)+Math.imul(R,Q)|0,a=a+Math.imul(R,tt)|0,n=n+Math.imul(P,rt)|0,i=(i=i+Math.imul(P,nt)|0)+Math.imul(z,rt)|0,a=a+Math.imul(z,nt)|0,n=n+Math.imul(C,at)|0,i=(i=i+Math.imul(C,ot)|0)+Math.imul(I,at)|0,a=a+Math.imul(I,ot)|0,n=n+Math.imul(M,lt)|0,i=(i=i+Math.imul(M,ct)|0)+Math.imul(S,lt)|0,a=a+Math.imul(S,ct)|0,n=n+Math.imul(T,ht)|0,i=(i=i+Math.imul(T,ft)|0)+Math.imul(k,ht)|0,a=a+Math.imul(k,ft)|0;var Et=(c+(n=n+Math.imul(_,dt)|0)|0)+((8191&(i=(i=i+Math.imul(_,mt)|0)+Math.imul(b,dt)|0))<<13)|0;c=((a=a+Math.imul(b,mt)|0)+(i>>>13)|0)+(Et>>>26)|0,Et&=67108863,n=Math.imul(B,Q),i=(i=Math.imul(B,tt))+Math.imul(j,Q)|0,a=Math.imul(j,tt),n=n+Math.imul(O,rt)|0,i=(i=i+Math.imul(O,nt)|0)+Math.imul(R,rt)|0,a=a+Math.imul(R,nt)|0,n=n+Math.imul(P,at)|0,i=(i=i+Math.imul(P,ot)|0)+Math.imul(z,at)|0,a=a+Math.imul(z,ot)|0,n=n+Math.imul(C,lt)|0,i=(i=i+Math.imul(C,ct)|0)+Math.imul(I,lt)|0,a=a+Math.imul(I,ct)|0,n=n+Math.imul(M,ht)|0,i=(i=i+Math.imul(M,ft)|0)+Math.imul(S,ht)|0,a=a+Math.imul(S,ft)|0;var Ct=(c+(n=n+Math.imul(T,dt)|0)|0)+((8191&(i=(i=i+Math.imul(T,mt)|0)+Math.imul(k,dt)|0))<<13)|0;c=((a=a+Math.imul(k,mt)|0)+(i>>>13)|0)+(Ct>>>26)|0,Ct&=67108863,n=Math.imul(B,rt),i=(i=Math.imul(B,nt))+Math.imul(j,rt)|0,a=Math.imul(j,nt),n=n+Math.imul(O,at)|0,i=(i=i+Math.imul(O,ot)|0)+Math.imul(R,at)|0,a=a+Math.imul(R,ot)|0,n=n+Math.imul(P,lt)|0,i=(i=i+Math.imul(P,ct)|0)+Math.imul(z,lt)|0,a=a+Math.imul(z,ct)|0,n=n+Math.imul(C,ht)|0,i=(i=i+Math.imul(C,ft)|0)+Math.imul(I,ht)|0,a=a+Math.imul(I,ft)|0;var It=(c+(n=n+Math.imul(M,dt)|0)|0)+((8191&(i=(i=i+Math.imul(M,mt)|0)+Math.imul(S,dt)|0))<<13)|0;c=((a=a+Math.imul(S,mt)|0)+(i>>>13)|0)+(It>>>26)|0,It&=67108863,n=Math.imul(B,at),i=(i=Math.imul(B,ot))+Math.imul(j,at)|0,a=Math.imul(j,ot),n=n+Math.imul(O,lt)|0,i=(i=i+Math.imul(O,ct)|0)+Math.imul(R,lt)|0,a=a+Math.imul(R,ct)|0,n=n+Math.imul(P,ht)|0,i=(i=i+Math.imul(P,ft)|0)+Math.imul(z,ht)|0,a=a+Math.imul(z,ft)|0;var Lt=(c+(n=n+Math.imul(C,dt)|0)|0)+((8191&(i=(i=i+Math.imul(C,mt)|0)+Math.imul(I,dt)|0))<<13)|0;c=((a=a+Math.imul(I,mt)|0)+(i>>>13)|0)+(Lt>>>26)|0,Lt&=67108863,n=Math.imul(B,lt),i=(i=Math.imul(B,ct))+Math.imul(j,lt)|0,a=Math.imul(j,ct),n=n+Math.imul(O,ht)|0,i=(i=i+Math.imul(O,ft)|0)+Math.imul(R,ht)|0,a=a+Math.imul(R,ft)|0;var Pt=(c+(n=n+Math.imul(P,dt)|0)|0)+((8191&(i=(i=i+Math.imul(P,mt)|0)+Math.imul(z,dt)|0))<<13)|0;c=((a=a+Math.imul(z,mt)|0)+(i>>>13)|0)+(Pt>>>26)|0,Pt&=67108863,n=Math.imul(B,ht),i=(i=Math.imul(B,ft))+Math.imul(j,ht)|0,a=Math.imul(j,ft);var zt=(c+(n=n+Math.imul(O,dt)|0)|0)+((8191&(i=(i=i+Math.imul(O,mt)|0)+Math.imul(R,dt)|0))<<13)|0;c=((a=a+Math.imul(R,mt)|0)+(i>>>13)|0)+(zt>>>26)|0,zt&=67108863;var Dt=(c+(n=Math.imul(B,dt))|0)+((8191&(i=(i=Math.imul(B,mt))+Math.imul(j,dt)|0))<<13)|0;return c=((a=Math.imul(j,mt))+(i>>>13)|0)+(Dt>>>26)|0,Dt&=67108863,l[0]=gt,l[1]=yt,l[2]=vt,l[3]=xt,l[4]=_t,l[5]=bt,l[6]=wt,l[7]=Tt,l[8]=kt,l[9]=At,l[10]=Mt,l[11]=St,l[12]=Et,l[13]=Ct,l[14]=It,l[15]=Lt,l[16]=Pt,l[17]=zt,l[18]=Dt,0!==c&&(l[19]=c,r.length++),r};function m(t,e,r){return(new g).mulp(t,e,r)}function g(t,e){this.x=t,this.y=e}Math.imul||(d=p),a.prototype.mulTo=function(t,e){var r,n=this.length+t.length;return r=10===this.length&&10===t.length?d(this,t,e):n<63?p(this,t,e):n<1024?function(t,e,r){r.negative=e.negative^t.negative,r.length=t.length+e.length;for(var n=0,i=0,a=0;a>>26)|0)>>>26,o&=67108863}r.words[a]=s,n=o,o=i}return 0!==n?r.words[a]=n:r.length--,r.strip()}(this,t,e):m(this,t,e),r},g.prototype.makeRBT=function(t){for(var e=new Array(t),r=a.prototype._countBits(t)-1,n=0;n>=1;return n},g.prototype.permute=function(t,e,r,n,i,a){for(var o=0;o>>=1)i++;return 1<>>=13,r[2*o+1]=8191&a,a>>>=13;for(o=2*e;o>=26,e+=i/67108864|0,e+=a>>>26,this.words[r]=67108863&a}return 0!==e&&(this.words[r]=e,this.length++),this},a.prototype.muln=function(t){return this.clone().imuln(t)},a.prototype.sqr=function(){return this.mul(this)},a.prototype.isqr=function(){return this.imul(this.clone())},a.prototype.pow=function(t){var e=function(t){for(var e=new Array(t.bitLength()),r=0;r>>i}return e}(t);if(0===e.length)return new a(1);for(var r=this,n=0;n=0);var e,r=t%26,i=(t-r)/26,a=67108863>>>26-r<<26-r;if(0!==r){var o=0;for(e=0;e>>26-r}o&&(this.words[e]=o,this.length++)}if(0!==i){for(e=this.length-1;e>=0;e--)this.words[e+i]=this.words[e];for(e=0;e=0),i=e?(e-e%26)/26:0;var a=t%26,o=Math.min((t-a)/26,this.length),s=67108863^67108863>>>a<o)for(this.length-=o,c=0;c=0&&(0!==u||c>=i);c--){var h=0|this.words[c];this.words[c]=u<<26-a|h>>>a,u=h&s}return l&&0!==u&&(l.words[l.length++]=u),0===this.length&&(this.words[0]=0,this.length=1),this.strip()},a.prototype.ishrn=function(t,e,r){return n(0===this.negative),this.iushrn(t,e,r)},a.prototype.shln=function(t){return this.clone().ishln(t)},a.prototype.ushln=function(t){return this.clone().iushln(t)},a.prototype.shrn=function(t){return this.clone().ishrn(t)},a.prototype.ushrn=function(t){return this.clone().iushrn(t)},a.prototype.testn=function(t){n("number"==typeof t&&t>=0);var e=t%26,r=(t-e)/26,i=1<=0);var e=t%26,r=(t-e)/26;if(n(0===this.negative,"imaskn works only with positive numbers"),this.length<=r)return this;if(0!==e&&r++,this.length=Math.min(r,this.length),0!==e){var i=67108863^67108863>>>e<=67108864;e++)this.words[e]-=67108864,e===this.length-1?this.words[e+1]=1:this.words[e+1]++;return this.length=Math.max(this.length,e+1),this},a.prototype.isubn=function(t){if(n("number"==typeof t),n(t<67108864),t<0)return this.iaddn(-t);if(0!==this.negative)return this.negative=0,this.iaddn(t),this.negative=1,this;if(this.words[0]-=t,1===this.length&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var e=0;e>26)-(l/67108864|0),this.words[i+r]=67108863&o}for(;i>26,this.words[i+r]=67108863&o;if(0===s)return this.strip();for(n(-1===s),s=0,i=0;i>26,this.words[i]=67108863&o;return this.negative=1,this.strip()},a.prototype._wordDiv=function(t,e){var r=(this.length,t.length),n=this.clone(),i=t,o=0|i.words[i.length-1];0!=(r=26-this._countBits(o))&&(i=i.ushln(r),n.iushln(r),o=0|i.words[i.length-1]);var s,l=n.length-i.length;if("mod"!==e){(s=new a(null)).length=l+1,s.words=new Array(s.length);for(var c=0;c=0;h--){var f=67108864*(0|n.words[i.length+h])+(0|n.words[i.length+h-1]);for(f=Math.min(f/o|0,67108863),n._ishlnsubmul(i,f,h);0!==n.negative;)f--,n.negative=0,n._ishlnsubmul(i,1,h),n.isZero()||(n.negative^=1);s&&(s.words[h]=f)}return s&&s.strip(),n.strip(),"div"!==e&&0!==r&&n.iushrn(r),{div:s||null,mod:n}},a.prototype.divmod=function(t,e,r){return n(!t.isZero()),this.isZero()?{div:new a(0),mod:new a(0)}:0!==this.negative&&0===t.negative?(s=this.neg().divmod(t,e),"mod"!==e&&(i=s.div.neg()),"div"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.iadd(t)),{div:i,mod:o}):0===this.negative&&0!==t.negative?(s=this.divmod(t.neg(),e),"mod"!==e&&(i=s.div.neg()),{div:i,mod:s.mod}):this.negative&t.negative?(s=this.neg().divmod(t.neg(),e),"div"!==e&&(o=s.mod.neg(),r&&0!==o.negative&&o.isub(t)),{div:s.div,mod:o}):t.length>this.length||this.cmp(t)<0?{div:new a(0),mod:this}:1===t.length?"div"===e?{div:this.divn(t.words[0]),mod:null}:"mod"===e?{div:null,mod:new a(this.modn(t.words[0]))}:{div:this.divn(t.words[0]),mod:new a(this.modn(t.words[0]))}:this._wordDiv(t,e);var i,o,s},a.prototype.div=function(t){return this.divmod(t,"div",!1).div},a.prototype.mod=function(t){return this.divmod(t,"mod",!1).mod},a.prototype.umod=function(t){return this.divmod(t,"mod",!0).mod},a.prototype.divRound=function(t){var e=this.divmod(t);if(e.mod.isZero())return e.div;var r=0!==e.div.negative?e.mod.isub(t):e.mod,n=t.ushrn(1),i=t.andln(1),a=r.cmp(n);return a<0||1===i&&0===a?e.div:0!==e.div.negative?e.div.isubn(1):e.div.iaddn(1)},a.prototype.modn=function(t){n(t<=67108863);for(var e=(1<<26)%t,r=0,i=this.length-1;i>=0;i--)r=(e*r+(0|this.words[i]))%t;return r},a.prototype.idivn=function(t){n(t<=67108863);for(var e=0,r=this.length-1;r>=0;r--){var i=(0|this.words[r])+67108864*e;this.words[r]=i/t|0,e=i%t}return this.strip()},a.prototype.divn=function(t){return this.clone().idivn(t)},a.prototype.egcd=function(t){n(0===t.negative),n(!t.isZero());var e=this,r=t.clone();e=0!==e.negative?e.umod(t):e.clone();for(var i=new a(1),o=new a(0),s=new a(0),l=new a(1),c=0;e.isEven()&&r.isEven();)e.iushrn(1),r.iushrn(1),++c;for(var u=r.clone(),h=e.clone();!e.isZero();){for(var f=0,p=1;!(e.words[0]&p)&&f<26;++f,p<<=1);if(f>0)for(e.iushrn(f);f-- >0;)(i.isOdd()||o.isOdd())&&(i.iadd(u),o.isub(h)),i.iushrn(1),o.iushrn(1);for(var d=0,m=1;!(r.words[0]&m)&&d<26;++d,m<<=1);if(d>0)for(r.iushrn(d);d-- >0;)(s.isOdd()||l.isOdd())&&(s.iadd(u),l.isub(h)),s.iushrn(1),l.iushrn(1);e.cmp(r)>=0?(e.isub(r),i.isub(s),o.isub(l)):(r.isub(e),s.isub(i),l.isub(o))}return{a:s,b:l,gcd:r.iushln(c)}},a.prototype._invmp=function(t){n(0===t.negative),n(!t.isZero());var e,r=this,i=t.clone();r=0!==r.negative?r.umod(t):r.clone();for(var o=new a(1),s=new a(0),l=i.clone();r.cmpn(1)>0&&i.cmpn(1)>0;){for(var c=0,u=1;!(r.words[0]&u)&&c<26;++c,u<<=1);if(c>0)for(r.iushrn(c);c-- >0;)o.isOdd()&&o.iadd(l),o.iushrn(1);for(var h=0,f=1;!(i.words[0]&f)&&h<26;++h,f<<=1);if(h>0)for(i.iushrn(h);h-- >0;)s.isOdd()&&s.iadd(l),s.iushrn(1);r.cmp(i)>=0?(r.isub(i),o.isub(s)):(i.isub(r),s.isub(o))}return(e=0===r.cmpn(1)?o:s).cmpn(0)<0&&e.iadd(t),e},a.prototype.gcd=function(t){if(this.isZero())return t.abs();if(t.isZero())return this.abs();var e=this.clone(),r=t.clone();e.negative=0,r.negative=0;for(var n=0;e.isEven()&&r.isEven();n++)e.iushrn(1),r.iushrn(1);for(;;){for(;e.isEven();)e.iushrn(1);for(;r.isEven();)r.iushrn(1);var i=e.cmp(r);if(i<0){var a=e;e=r,r=a}else if(0===i||0===r.cmpn(1))break;e.isub(r)}return r.iushln(n)},a.prototype.invm=function(t){return this.egcd(t).a.umod(t)},a.prototype.isEven=function(){return!(1&this.words[0])},a.prototype.isOdd=function(){return!(1&~this.words[0])},a.prototype.andln=function(t){return this.words[0]&t},a.prototype.bincn=function(t){n("number"==typeof t);var e=t%26,r=(t-e)/26,i=1<>>26,s&=67108863,this.words[o]=s}return 0!==a&&(this.words[o]=a,this.length++),this},a.prototype.isZero=function(){return 1===this.length&&0===this.words[0]},a.prototype.cmpn=function(t){var e,r=t<0;if(0!==this.negative&&!r)return-1;if(0===this.negative&&r)return 1;if(this.strip(),this.length>1)e=1;else{r&&(t=-t),n(t<=67108863,"Number is too big");var i=0|this.words[0];e=i===t?0:it.length)return 1;if(this.length=0;r--){var n=0|this.words[r],i=0|t.words[r];if(n!==i){ni&&(e=1);break}}return e},a.prototype.gtn=function(t){return 1===this.cmpn(t)},a.prototype.gt=function(t){return 1===this.cmp(t)},a.prototype.gten=function(t){return this.cmpn(t)>=0},a.prototype.gte=function(t){return this.cmp(t)>=0},a.prototype.ltn=function(t){return-1===this.cmpn(t)},a.prototype.lt=function(t){return-1===this.cmp(t)},a.prototype.lten=function(t){return this.cmpn(t)<=0},a.prototype.lte=function(t){return this.cmp(t)<=0},a.prototype.eqn=function(t){return 0===this.cmpn(t)},a.prototype.eq=function(t){return 0===this.cmp(t)},a.red=function(t){return new T(t)},a.prototype.toRed=function(t){return n(!this.red,"Already a number in reduction context"),n(0===this.negative,"red works only with positives"),t.convertTo(this)._forceRed(t)},a.prototype.fromRed=function(){return n(this.red,"fromRed works only with numbers in reduction context"),this.red.convertFrom(this)},a.prototype._forceRed=function(t){return this.red=t,this},a.prototype.forceRed=function(t){return n(!this.red,"Already a number in reduction context"),this._forceRed(t)},a.prototype.redAdd=function(t){return n(this.red,"redAdd works only with red numbers"),this.red.add(this,t)},a.prototype.redIAdd=function(t){return n(this.red,"redIAdd works only with red numbers"),this.red.iadd(this,t)},a.prototype.redSub=function(t){return n(this.red,"redSub works only with red numbers"),this.red.sub(this,t)},a.prototype.redISub=function(t){return n(this.red,"redISub works only with red numbers"),this.red.isub(this,t)},a.prototype.redShl=function(t){return n(this.red,"redShl works only with red numbers"),this.red.shl(this,t)},a.prototype.redMul=function(t){return n(this.red,"redMul works only with red numbers"),this.red._verify2(this,t),this.red.mul(this,t)},a.prototype.redIMul=function(t){return n(this.red,"redMul works only with red numbers"),this.red._verify2(this,t),this.red.imul(this,t)},a.prototype.redSqr=function(){return n(this.red,"redSqr works only with red numbers"),this.red._verify1(this),this.red.sqr(this)},a.prototype.redISqr=function(){return n(this.red,"redISqr works only with red numbers"),this.red._verify1(this),this.red.isqr(this)},a.prototype.redSqrt=function(){return n(this.red,"redSqrt works only with red numbers"),this.red._verify1(this),this.red.sqrt(this)},a.prototype.redInvm=function(){return n(this.red,"redInvm works only with red numbers"),this.red._verify1(this),this.red.invm(this)},a.prototype.redNeg=function(){return n(this.red,"redNeg works only with red numbers"),this.red._verify1(this),this.red.neg(this)},a.prototype.redPow=function(t){return n(this.red&&!t.red,"redPow(normalNum)"),this.red._verify1(this),this.red.pow(this,t)};var y={k256:null,p224:null,p192:null,p25519:null};function v(t,e){this.name=t,this.p=new a(e,16),this.n=this.p.bitLength(),this.k=new a(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}function x(){v.call(this,"k256","ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f")}function _(){v.call(this,"p224","ffffffff ffffffff ffffffff ffffffff 00000000 00000000 00000001")}function b(){v.call(this,"p192","ffffffff ffffffff ffffffff fffffffe ffffffff ffffffff")}function w(){v.call(this,"25519","7fffffffffffffff ffffffffffffffff ffffffffffffffff ffffffffffffffed")}function T(t){if("string"==typeof t){var e=a._prime(t);this.m=e.p,this.prime=e}else n(t.gtn(1),"modulus must be greater than 1"),this.m=t,this.prime=null}function k(t){T.call(this,t),this.shift=this.m.bitLength(),this.shift%26!=0&&(this.shift+=26-this.shift%26),this.r=new a(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}v.prototype._tmp=function(){var t=new a(null);return t.words=new Array(Math.ceil(this.n/13)),t},v.prototype.ireduce=function(t){var e,r=t;do{this.split(r,this.tmp),e=(r=(r=this.imulK(r)).iadd(this.tmp)).bitLength()}while(e>this.n);var n=e0?r.isub(this.p):void 0!==r.strip?r.strip():r._strip(),r},v.prototype.split=function(t,e){t.iushrn(this.n,0,e)},v.prototype.imulK=function(t){return t.imul(this.k)},i(x,v),x.prototype.split=function(t,e){for(var r=4194303,n=Math.min(t.length,9),i=0;i>>22,a=o}a>>>=22,t.words[i-10]=a,0===a&&t.length>10?t.length-=10:t.length-=9},x.prototype.imulK=function(t){t.words[t.length]=0,t.words[t.length+1]=0,t.length+=2;for(var e=0,r=0;r>>=26,t.words[r]=i,e=n}return 0!==e&&(t.words[t.length++]=e),t},a._prime=function(t){if(y[t])return y[t];var e;if("k256"===t)e=new x;else if("p224"===t)e=new _;else if("p192"===t)e=new b;else{if("p25519"!==t)throw new Error("Unknown prime "+t);e=new w}return y[t]=e,e},T.prototype._verify1=function(t){n(0===t.negative,"red works only with positives"),n(t.red,"red works only with red numbers")},T.prototype._verify2=function(t,e){n(!(t.negative|e.negative),"red works only with positives"),n(t.red&&t.red===e.red,"red works only with red numbers")},T.prototype.imod=function(t){return this.prime?this.prime.ireduce(t)._forceRed(this):t.umod(this.m)._forceRed(this)},T.prototype.neg=function(t){return t.isZero()?t.clone():this.m.sub(t)._forceRed(this)},T.prototype.add=function(t,e){this._verify2(t,e);var r=t.add(e);return r.cmp(this.m)>=0&&r.isub(this.m),r._forceRed(this)},T.prototype.iadd=function(t,e){this._verify2(t,e);var r=t.iadd(e);return r.cmp(this.m)>=0&&r.isub(this.m),r},T.prototype.sub=function(t,e){this._verify2(t,e);var r=t.sub(e);return r.cmpn(0)<0&&r.iadd(this.m),r._forceRed(this)},T.prototype.isub=function(t,e){this._verify2(t,e);var r=t.isub(e);return r.cmpn(0)<0&&r.iadd(this.m),r},T.prototype.shl=function(t,e){return this._verify1(t),this.imod(t.ushln(e))},T.prototype.imul=function(t,e){return this._verify2(t,e),this.imod(t.imul(e))},T.prototype.mul=function(t,e){return this._verify2(t,e),this.imod(t.mul(e))},T.prototype.isqr=function(t){return this.imul(t,t.clone())},T.prototype.sqr=function(t){return this.mul(t,t)},T.prototype.sqrt=function(t){if(t.isZero())return t.clone();var e=this.m.andln(3);if(n(e%2==1),3===e){var r=this.m.add(new a(1)).iushrn(2);return this.pow(t,r)}for(var i=this.m.subn(1),o=0;!i.isZero()&&0===i.andln(1);)o++,i.iushrn(1);n(!i.isZero());var s=new a(1).toRed(this),l=s.redNeg(),c=this.m.subn(1).iushrn(1),u=this.m.bitLength();for(u=new a(2*u*u).toRed(this);0!==this.pow(u,c).cmp(l);)u.redIAdd(l);for(var h=this.pow(u,i),f=this.pow(t,i.addn(1).iushrn(1)),p=this.pow(t,i),d=o;0!==p.cmp(s);){for(var m=p,g=0;0!==m.cmp(s);g++)m=m.redSqr();n(g=0;n--){for(var c=e.words[n],u=l-1;u>=0;u--){var h=c>>u&1;i!==r[0]&&(i=this.sqr(i)),0!==h||0!==o?(o<<=1,o|=h,(4==++s||0===n&&0===u)&&(i=this.mul(i,r[o]),s=0,o=0)):s=0}l=26}return i},T.prototype.convertTo=function(t){var e=t.umod(this.m);return e===t?e.clone():e},T.prototype.convertFrom=function(t){var e=t.clone();return e.red=null,e},a.mont=function(t){return new k(t)},i(k,T),k.prototype.convertTo=function(t){return this.imod(t.ushln(this.shift))},k.prototype.convertFrom=function(t){var e=this.imod(t.mul(this.rinv));return e.red=null,e},k.prototype.imul=function(t,e){if(t.isZero()||e.isZero())return t.words[0]=0,t.length=1,t;var r=t.imul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),a=i;return i.cmp(this.m)>=0?a=i.isub(this.m):i.cmpn(0)<0&&(a=i.iadd(this.m)),a._forceRed(this)},k.prototype.mul=function(t,e){if(t.isZero()||e.isZero())return new a(0)._forceRed(this);var r=t.mul(e),n=r.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),i=r.isub(n).iushrn(this.shift),o=i;return i.cmp(this.m)>=0?o=i.isub(this.m):i.cmpn(0)<0&&(o=i.iadd(this.m)),o._forceRed(this)},k.prototype.invm=function(t){return this.imod(t._invmp(this.m).mul(this.r2))._forceRed(this)}}(t=r.nmd(t),this)},6860:function(t){t.exports=function(t,e,r){return t[0]=e[0]-r[0],t[1]=e[1]-r[1],t[2]=e[2]-r[2],t[3]=e[3]-r[3],t}},6864:function(t){t.exports=function(){var t=new Float32Array(16);return t[0]=1,t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[5]=1,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[10]=1,t[11]=0,t[12]=0,t[13]=0,t[14]=0,t[15]=1,t}},6867:function(t,e,r){t.exports=function(t,e,r){switch(arguments.length){case 1:return function(t){return n=[],c(t,t,u,!0),n}(t);case 2:return"function"==typeof e?c(t,t,e,!0):function(t,e){return n=[],c(t,e,u,!1),n}(t,e);case 3:return c(t,e,r,!1);default:throw new Error("box-intersect: Invalid arguments")}};var n,i=r(1888),a=r(855),o=r(7150);function s(t,e){for(var r=0;r>>1;if(!(u<=0)){var h,f=i.mallocDouble(2*u*s),p=i.mallocInt32(s);if((s=l(t,u,f,p))>0){if(1===u&&n)a.init(s),h=a.sweepComplete(u,r,0,s,f,p,0,s,f,p);else{var d=i.mallocDouble(2*u*c),m=i.mallocInt32(c);(c=l(e,u,d,m))>0&&(a.init(s+c),h=1===u?a.sweepBipartite(u,r,0,s,f,p,0,c,d,m):o(u,r,n,s,f,p,c,d,m),i.free(d),i.free(m))}i.free(f),i.free(p)}return h}}}function u(t,e){n.push([t,e])}},6894:function(t){t.exports=function(t,e,r,n){var i=r[1],a=r[2],o=e[1]-i,s=e[2]-a,l=Math.sin(n),c=Math.cos(n);return t[0]=e[0],t[1]=i+o*c-s*l,t[2]=a+o*l+s*c,t}},7004:function(t){t.exports=function(t){for(var e=t.length,r=t[t.length-1],n=e,i=e-2;i>=0;--i){var a=r;(l=(s=t[i])-((r=a+s)-a))&&(t[--n]=r,r=l)}var o=0;for(i=n;i0;){var D=(P-=1)*_,O=w[D],R=w[D+1],F=w[D+2],B=w[D+3],j=w[D+4],N=w[D+5],U=P*b,V=T[U],q=T[U+1],H=1&N,G=!!(16&N),W=u,Z=S,Y=C,X=I;if(H&&(W=C,Z=I,Y=u,X=S),!(2&N&&(F=g(t,O,R,F,W,Z,q),R>=F)||4&N&&(R=y(t,O,R,F,W,Z,V),R>=F))){var $=F-R,K=j-B;if(G){if(t*$*($+K)=p0)&&!(p1>=hi)"),m=u("lo===p0"),g=u("lo"u"?r(1538):WeakMap,i=r(2762),a=r(8116),o=new n;t.exports=function(t){var e=o.get(t),r=e&&(e._triangleBuffer.handle||e._triangleBuffer.buffer);if(!r||!t.isBuffer(r)){var n=i(t,new Float32Array([-1,-1,-1,4,4,-1]));(e=a(t,[{buffer:n,type:t.FLOAT,size:2}]))._triangleBuffer=n,o.set(t,e)}e.bind(),t.drawArrays(t.TRIANGLES,0,3),e.unbind()}},7182:function(t,e,r){var n={identity:r(7894),translate:r(7656),multiply:r(6760),create:r(6864),scale:r(2504),fromRotationTranslation:r(6743)},i=(n.create(),n.create());t.exports=function(t,e,r,a,o,s){return n.identity(t),n.fromRotationTranslation(t,s,e),t[3]=o[0],t[7]=o[1],t[11]=o[2],t[15]=o[3],n.identity(i),0!==a[2]&&(i[9]=a[2],n.multiply(t,t,i)),0!==a[1]&&(i[9]=0,i[8]=a[1],n.multiply(t,t,i)),0!==a[0]&&(i[8]=0,i[4]=a[0],n.multiply(t,t,i)),n.scale(t,t,r),t}},7201:function(t,e,r){var n=r(9405),i=r(2762),a=r(8116),o=r(7766),s=r(8406),l=r(6760),c=r(7608),u=r(9618),h=r(6729),f=r(7765),p=r(1888),d=r(840),m=r(7626),g=d.meshShader,y=d.wireShader,v=d.pointShader,x=d.pickShader,_=d.pointPickShader,b=d.contourShader,w=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function T(t,e,r,n,i,a,o,s,l,c,u,h,f,p,d,m,g,y,v,x,_,b,T,k,A,M,S){this.gl=t,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=e,this.dirty=!0,this.triShader=r,this.lineShader=n,this.pointShader=i,this.pickShader=a,this.pointPickShader=o,this.contourShader=s,this.trianglePositions=l,this.triangleColors=u,this.triangleNormals=f,this.triangleUVs=h,this.triangleIds=c,this.triangleVAO=p,this.triangleCount=0,this.lineWidth=1,this.edgePositions=d,this.edgeColors=g,this.edgeUVs=y,this.edgeIds=m,this.edgeVAO=v,this.edgeCount=0,this.pointPositions=x,this.pointColors=b,this.pointUVs=T,this.pointSizes=k,this.pointIds=_,this.pointVAO=A,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=M,this.contourVAO=S,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=w,this._view=w,this._projection=w,this._resolution=[1,1]}var k=T.prototype;function A(t,e){if(!e||!e.length)return 1;for(var r=0;rt&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}k.isOpaque=function(){return!this.hasAlpha},k.isTransparent=function(){return this.hasAlpha},k.pickSlots=1,k.setPickBase=function(t){this.pickId=t},k.highlight=function(t){if(t&&this.contourEnable){for(var e=f(this.cells,this.intensity,t.intensity),r=e.cells,n=e.vertexIds,i=e.vertexWeights,a=r.length,o=p.mallocFloat32(6*a),s=0,l=0;l0&&((u=this.triShader).bind(),u.uniforms=s,this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&this.lineWidth>0&&((u=this.lineShader).bind(),u.uniforms=s,this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((u=this.pointShader).bind(),u.uniforms=s,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind()),this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0&&((u=this.contourShader).bind(),u.uniforms=s,this.contourVAO.bind(),e.drawArrays(e.LINES,0,this.contourCount),this.contourVAO.unbind())},k.drawPick=function(t){t=t||{};for(var e=this.gl,r=t.model||w,n=t.view||w,i=t.projection||w,a=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],o=0;o<3;++o)a[0][o]=Math.max(a[0][o],this.clipBounds[0][o]),a[1][o]=Math.min(a[1][o],this.clipBounds[1][o]);this._model=[].slice.call(r),this._view=[].slice.call(n),this._projection=[].slice.call(i),this._resolution=[e.drawingBufferWidth,e.drawingBufferHeight];var s,l={model:r,view:n,projection:i,clipBounds:a,pickId:this.pickId/255};(s=this.pickShader).bind(),s.uniforms=l,this.triangleCount>0&&(this.triangleVAO.bind(),e.drawArrays(e.TRIANGLES,0,3*this.triangleCount),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),e.lineWidth(this.lineWidth*this.pixelRatio),e.drawArrays(e.LINES,0,2*this.edgeCount),this.edgeVAO.unbind()),this.pointCount>0&&((s=this.pointPickShader).bind(),s.uniforms=l,this.pointVAO.bind(),e.drawArrays(e.POINTS,0,this.pointCount),this.pointVAO.unbind())},k.pick=function(t){if(!t||t.id!==this.pickId)return null;for(var e=t.value[0]+256*t.value[1]+65536*t.value[2],r=this.cells[e],n=this.positions,i=new Array(r.length),a=0;aMath.max(r,n)?i[2]=1:r>Math.max(e,n)?i[0]=1:i[1]=1;for(var a=0,o=0,l=0;l<3;++l)a+=t[l]*t[l],o+=i[l]*t[l];for(l=0;l<3;++l)i[l]-=o/a*t[l];return s(i,i),i}function f(t,e,r,i,a,o,s,l){this.center=n(r),this.up=n(i),this.right=n(a),this.radius=n([o]),this.angle=n([s,l]),this.angle.bounds=[[-1/0,-Math.PI/2],[1/0,Math.PI/2]],this.setDistanceLimits(t,e),this.computedCenter=this.center.curve(0),this.computedUp=this.up.curve(0),this.computedRight=this.right.curve(0),this.computedRadius=this.radius.curve(0),this.computedAngle=this.angle.curve(0),this.computedToward=[0,0,0],this.computedEye=[0,0,0],this.computedMatrix=new Array(16);for(var c=0;c<16;++c)this.computedMatrix[c]=.5;this.recalcMatrix(0)}var p=f.prototype;p.setDistanceLimits=function(t,e){t=t>0?Math.log(t):-1/0,e=e>0?Math.log(e):1/0,e=Math.max(e,t),this.radius.bounds[0][0]=t,this.radius.bounds[1][0]=e},p.getDistanceLimits=function(t){var e=this.radius.bounds[0];return t?(t[0]=Math.exp(e[0][0]),t[1]=Math.exp(e[1][0]),t):[Math.exp(e[0][0]),Math.exp(e[1][0])]},p.recalcMatrix=function(t){this.center.curve(t),this.up.curve(t),this.right.curve(t),this.radius.curve(t),this.angle.curve(t);for(var e=this.computedUp,r=this.computedRight,n=0,i=0,a=0;a<3;++a)i+=e[a]*r[a],n+=e[a]*e[a];var l=Math.sqrt(n),u=0;for(a=0;a<3;++a)r[a]-=e[a]*i/n,u+=r[a]*r[a],e[a]/=l;var h=Math.sqrt(u);for(a=0;a<3;++a)r[a]/=h;var f=this.computedToward;o(f,e,r),s(f,f);var p=Math.exp(this.computedRadius[0]),d=this.computedAngle[0],m=this.computedAngle[1],g=Math.cos(d),y=Math.sin(d),v=Math.cos(m),x=Math.sin(m),_=this.computedCenter,b=g*v,w=y*v,T=x,k=-g*x,A=-y*x,M=v,S=this.computedEye,E=this.computedMatrix;for(a=0;a<3;++a){var C=b*r[a]+w*f[a]+T*e[a];E[4*a+1]=k*r[a]+A*f[a]+M*e[a],E[4*a+2]=C,E[4*a+3]=0}var I=E[1],L=E[5],P=E[9],z=E[2],D=E[6],O=E[10],R=L*O-P*D,F=P*z-I*O,B=I*D-L*z,j=c(R,F,B);for(R/=j,F/=j,B/=j,E[0]=R,E[4]=F,E[8]=B,a=0;a<3;++a)S[a]=_[a]+E[2+4*a]*p;for(a=0;a<3;++a){u=0;for(var N=0;N<3;++N)u+=E[a+4*N]*S[N];E[12+a]=-u}E[15]=1},p.getMatrix=function(t,e){this.recalcMatrix(t);var r=this.computedMatrix;if(e){for(var n=0;n<16;++n)e[n]=r[n];return e}return r};var d=[0,0,0];p.rotate=function(t,e,r,n){if(this.angle.move(t,e,r),n){this.recalcMatrix(t);var i=this.computedMatrix;d[0]=i[2],d[1]=i[6],d[2]=i[10];for(var o=this.computedUp,s=this.computedRight,l=this.computedToward,c=0;c<3;++c)i[4*c]=o[c],i[4*c+1]=s[c],i[4*c+2]=l[c];for(a(i,i,n,d),c=0;c<3;++c)o[c]=i[4*c],s[c]=i[4*c+1];this.up.set(t,o[0],o[1],o[2]),this.right.set(t,s[0],s[1],s[2])}},p.pan=function(t,e,r,n){e=e||0,r=r||0,n=n||0,this.recalcMatrix(t);var i=this.computedMatrix,a=(Math.exp(this.computedRadius[0]),i[1]),o=i[5],s=i[9],l=c(a,o,s);a/=l,o/=l,s/=l;var u=i[0],h=i[4],f=i[8],p=u*a+h*o+f*s,d=c(u-=a*p,h-=o*p,f-=s*p),m=(u/=d)*e+a*r,g=(h/=d)*e+o*r,y=(f/=d)*e+s*r;this.center.move(t,m,g,y);var v=Math.exp(this.computedRadius[0]);v=Math.max(1e-4,v+n),this.radius.set(t,Math.log(v))},p.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},p.setMatrix=function(t,e,r,n){var a=1;"number"==typeof r&&(a=0|r),(a<0||a>3)&&(a=1);var o=(a+2)%3;e||(this.recalcMatrix(t),e=this.computedMatrix);var s=e[a],l=e[a+4],h=e[a+8];if(n){var f=Math.abs(s),p=Math.abs(l),d=Math.abs(h),m=Math.max(f,p,d);f===m?(s=s<0?-1:1,l=h=0):d===m?(h=h<0?-1:1,s=l=0):(l=l<0?-1:1,s=h=0)}else{var g=c(s,l,h);s/=g,l/=g,h/=g}var y,v,x=e[o],_=e[o+4],b=e[o+8],w=x*s+_*l+b*h,T=c(x-=s*w,_-=l*w,b-=h*w),k=l*(b/=T)-h*(_/=T),A=h*(x/=T)-s*b,M=s*_-l*x,S=c(k,A,M);if(k/=S,A/=S,M/=S,this.center.jump(t,H,G,W),this.radius.idle(t),this.up.jump(t,s,l,h),this.right.jump(t,x,_,b),2===a){var E=e[1],C=e[5],I=e[9],L=E*x+C*_+I*b,P=E*k+C*A+I*M;y=R<0?-Math.PI/2:Math.PI/2,v=Math.atan2(P,L)}else{var z=e[2],D=e[6],O=e[10],R=z*s+D*l+O*h,F=z*x+D*_+O*b,B=z*k+D*A+O*M;y=Math.asin(u(R)),v=Math.atan2(B,F)}this.angle.jump(t,v,y),this.recalcMatrix(t);var j=e[2],N=e[6],U=e[10],V=this.computedMatrix;i(V,e);var q=V[15],H=V[12]/q,G=V[13]/q,W=V[14]/q,Z=Math.exp(this.computedRadius[0]);this.center.jump(t,H-j*Z,G-N*Z,W-U*Z)},p.lastT=function(){return Math.max(this.center.lastT(),this.up.lastT(),this.right.lastT(),this.radius.lastT(),this.angle.lastT())},p.idle=function(t){this.center.idle(t),this.up.idle(t),this.right.idle(t),this.radius.idle(t),this.angle.idle(t)},p.flush=function(t){this.center.flush(t),this.up.flush(t),this.right.flush(t),this.radius.flush(t),this.angle.flush(t)},p.setDistance=function(t,e){e>0&&this.radius.set(t,Math.log(e))},p.lookAt=function(t,e,r,n){this.recalcMatrix(t),e=e||this.computedEye,r=r||this.computedCenter;var i=(n=n||this.computedUp)[0],a=n[1],o=n[2],s=c(i,a,o);if(!(s<1e-6)){i/=s,a/=s,o/=s;var l=e[0]-r[0],h=e[1]-r[1],f=e[2]-r[2],p=c(l,h,f);if(!(p<1e-6)){l/=p,h/=p,f/=p;var d=this.computedRight,m=d[0],g=d[1],y=d[2],v=i*m+a*g+o*y,x=c(m-=v*i,g-=v*a,y-=v*o);if(!(x<.01&&(m=a*f-o*h,g=o*l-i*f,y=i*h-a*l,x=c(m,g,y),x<1e-6))){m/=x,g/=x,y/=x,this.up.set(t,i,a,o),this.right.set(t,m,g,y),this.center.set(t,r[0],r[1],r[2]),this.radius.set(t,Math.log(p));var _=a*y-o*g,b=o*m-i*y,w=i*g-a*m,T=c(_,b,w),k=i*l+a*h+o*f,A=m*l+g*h+y*f,M=(_/=T)*l+(b/=T)*h+(w/=T)*f,S=Math.asin(u(k)),E=Math.atan2(M,A),C=this.angle._state,I=C[C.length-1],L=C[C.length-2];I%=2*Math.PI;var P=Math.abs(I+2*Math.PI-E),z=Math.abs(I-E),D=Math.abs(I-2*Math.PI-E);P max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform vec3 clipBounds[2];\nuniform sampler2D dashTexture;\nuniform float dashScale;\nuniform float opacity;\n\nvarying vec3 worldPosition;\nvarying float pixelArcLength;\nvarying vec4 fragColor;\n\nvoid main() {\n if (\n outOfRange(clipBounds[0], clipBounds[1], worldPosition) ||\n fragColor.a * opacity == 0.\n ) discard;\n\n float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r;\n if(dashWeight < 0.5) {\n discard;\n }\n gl_FragColor = fragColor * opacity;\n}\n"]),s=n(["precision highp float;\n#define GLSLIFY 1\n\n#define FLOAT_MAX 1.70141184e38\n#define FLOAT_MIN 1.17549435e-38\n\n// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl\nvec4 packFloat(float v) {\n float av = abs(v);\n\n //Handle special cases\n if(av < FLOAT_MIN) {\n return vec4(0.0, 0.0, 0.0, 0.0);\n } else if(v > FLOAT_MAX) {\n return vec4(127.0, 128.0, 0.0, 0.0) / 255.0;\n } else if(v < -FLOAT_MAX) {\n return vec4(255.0, 128.0, 0.0, 0.0) / 255.0;\n }\n\n vec4 c = vec4(0,0,0,0);\n\n //Compute exponent and mantissa\n float e = floor(log2(av));\n float m = av * pow(2.0, -e) - 1.0;\n\n //Unpack mantissa\n c[1] = floor(128.0 * m);\n m -= c[1] / 128.0;\n c[2] = floor(32768.0 * m);\n m -= c[2] / 32768.0;\n c[3] = floor(8388608.0 * m);\n\n //Unpack exponent\n float ebias = e + 127.0;\n c[0] = floor(ebias / 2.0);\n ebias -= c[0] * 2.0;\n c[1] += floor(ebias) * 128.0;\n\n //Unpack sign bit\n c[0] += 128.0 * step(0.0, -v);\n\n //Scale back to range\n return c / 255.0;\n}\n\nbool outOfRange(float a, float b, float p) {\n return ((p > max(a, b)) || \n (p < min(a, b)));\n}\n\nbool outOfRange(vec2 a, vec2 b, vec2 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y));\n}\n\nbool outOfRange(vec3 a, vec3 b, vec3 p) {\n return (outOfRange(a.x, b.x, p.x) ||\n outOfRange(a.y, b.y, p.y) ||\n outOfRange(a.z, b.z, p.z));\n}\n\nbool outOfRange(vec4 a, vec4 b, vec4 p) {\n return outOfRange(a.xyz, b.xyz, p.xyz);\n}\n\nuniform float pickId;\nuniform vec3 clipBounds[2];\n\nvarying vec3 worldPosition;\nvarying float pixelArcLength;\nvarying vec4 fragColor;\n\nvoid main() {\n if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard;\n\n gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz);\n}"]),l=[{name:"position",type:"vec3"},{name:"nextPosition",type:"vec3"},{name:"arcLength",type:"float"},{name:"lineWidth",type:"float"},{name:"color",type:"vec4"}];e.createShader=function(t){return i(t,a,o,null,l)},e.createPickShader=function(t){return i(t,a,s,null,l)}},7352:function(t,e,r){var n=r(5721),i=r(4750),a=r(2690);t.exports=function(t){var e=t.length;if(0===e)return[];if(1===e)return[[0]];var r=t[0].length;return 0===r?[]:1===r?n(t):2===r?i(t):a(t,r)}},7399:function(t){t.exports=function(t,e){var 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e=t.gl,r=n(e),o=i(e,[{buffer:r,type:e.FLOAT,size:3,offset:0,stride:40},{buffer:r,type:e.FLOAT,size:4,offset:12,stride:40},{buffer:r,type:e.FLOAT,size:3,offset:28,stride:40}]),l=a(e);l.attributes.position.location=0,l.attributes.color.location=1,l.attributes.offset.location=2;var c=new s(e,r,o,l);return c.update(t),c};var n=r(2762),i=r(8116),a=r(3436),o=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function s(t,e,r,n){this.gl=t,this.shader=n,this.buffer=e,this.vao=r,this.pixelRatio=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lineWidth=[1,1,1],this.capSize=[10,10,10],this.lineCount=[0,0,0],this.lineOffset=[0,0,0],this.opacity=1,this.hasAlpha=!1}var l=s.prototype;function c(t,e){for(var r=0;r<3;++r)t[0][r]=Math.min(t[0][r],e[r]),t[1][r]=Math.max(t[1][r],e[r])}l.isOpaque=function(){return!this.hasAlpha},l.isTransparent=function(){return this.hasAlpha},l.drawTransparent=l.draw=function(t){var e=this.gl,r=this.shader.uniforms;this.shader.bind();var n=r.view=t.view||o,i=r.projection=t.projection||o;r.model=t.model||o,r.clipBounds=this.clipBounds,r.opacity=this.opacity;var a=n[12],s=n[13],l=n[14],c=n[15],u=(t._ortho?2:1)*this.pixelRatio*(i[3]*a+i[7]*s+i[11]*l+i[15]*c)/e.drawingBufferHeight;this.vao.bind();for(var h=0;h<3;++h)e.lineWidth(this.lineWidth[h]*this.pixelRatio),r.capSize=this.capSize[h]*u,this.lineCount[h]&&e.drawArrays(e.LINES,this.lineOffset[h],this.lineCount[h]);this.vao.unbind()};var u=function(){for(var t=new Array(3),e=0;e<3;++e){for(var r=[],n=1;n<=2;++n)for(var i=-1;i<=1;i+=2){var a=[0,0,0];a[(n+e)%3]=i,r.push(a)}t[e]=r}return t}();function h(t,e,r,n){for(var i=u[n],a=0;a0&&((p=u.slice())[s]+=d[1][s],i.push(u[0],u[1],u[2],m[0],m[1],m[2],m[3],0,0,0,p[0],p[1],p[2],m[0],m[1],m[2],m[3],0,0,0),c(this.bounds,p),o+=2+h(i,p,m,s)))}this.lineCount[s]=o-this.lineOffset[s]}this.buffer.update(i)}},l.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()}},9215:function(t,e,r){t.exports=function(t,e,r){switch(arguments.length){case 0:return new o([0],[0],0);case 1:return"number"==typeof t?new o(n=l(t),n,0):new o(t,l(t.length),0);case 2:var n;if("number"==typeof e)return new o(t,n=l(t.length),+e);r=0;case 3:if(t.length!==e.length)throw new Error("state and velocity lengths must match");return new o(t,e,r)}};var n=r(4769),i=r(2478);function a(t,e,r){return Math.min(e,Math.max(t,r))}function o(t,e,r){this.dimension=t.length,this.bounds=[new Array(this.dimension),new Array(this.dimension)];for(var n=0;n=r-1){f=l.length-1;var d=t-e[r-1];for(p=0;p=r-1)for(var u=s.length-1,h=(e[r-1],0);h=0;--r)if(t[--e])return!1;return!0},s.jump=function(t){var e=this.lastT(),r=this.dimension;if(!(t0;--h)n.push(a(l[h-1],c[h-1],arguments[h])),i.push(0)}},s.push=function(t){var e=this.lastT(),r=this.dimension;if(!(t1e-6?1/s:0;this._time.push(t);for(var f=r;f>0;--f){var p=a(c[f-1],u[f-1],arguments[f]);n.push(p),i.push((p-n[o++])*h)}}},s.set=function(t){var e=this.dimension;if(!(t0;--l)r.push(a(o[l-1],s[l-1],arguments[l])),n.push(0)}},s.move=function(t){var e=this.lastT(),r=this.dimension;if(!(t<=e||arguments.length!==r+1)){var n=this._state,i=this._velocity,o=n.length-this.dimension,s=this.bounds,l=s[0],c=s[1],u=t-e,h=u>1e-6?1/u:0;this._time.push(t);for(var f=r;f>0;--f){var p=arguments[f];n.push(a(l[f-1],c[f-1],n[o++]+p)),i.push(p*h)}}},s.idle=function(t){var e=this.lastT();if(!(t=0;--h)n.push(a(l[h],c[h],n[o]+u*i[o])),i.push(0),o+=1}}},9216:function(t){t.exports=i,t.exports.isMobile=i,t.exports.default=i;var e=/(android|bb\d+|meego).+mobile|armv7l|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\/|plucker|pocket|psp|series[46]0|samsungbrowser.*mobile|symbian|treo|up\.(browser|link)|vodafone|wap|windows (ce|phone)|xda|xiino/i,r=/CrOS/,n=/android|ipad|playbook|silk/i;function i(t){t||(t={});var i=t.ua;if(!i&&typeof navigator<"u"&&(i=navigator.userAgent),i&&i.headers&&"string"==typeof i.headers["user-agent"]&&(i=i.headers["user-agent"]),"string"!=typeof i)return!1;var a=e.test(i)&&!r.test(i)||!!t.tablet&&n.test(i);return!a&&t.tablet&&t.featureDetect&&navigator&&navigator.maxTouchPoints>1&&-1!==i.indexOf("Macintosh")&&-1!==i.indexOf("Safari")&&(a=!0),a}},9226:function(t){t.exports=function(t,e){return t[0]=Math.ceil(e[0]),t[1]=Math.ceil(e[1]),t[2]=Math.ceil(e[2]),t}},9265:function(t){t.exports=function(t,e){return t[0]===e[0]&&t[1]===e[1]&&t[2]===e[2]}},9288:function(t){t.exports=function(t,e,r){return t[0]=e[0]*r,t[1]=e[1]*r,t[2]=e[2]*r,t[3]=e[3]*r,t}},9346:function(t){var e=new Float64Array(4),r=new Float64Array(4),n=new Float64Array(4);t.exports=function(t,i,a,o,s){e.length=c?(k=1,v=c+2*f+d):v=f*(k=-f/c)+d):(k=0,p>=0?(A=0,v=d):-p>=h?(A=1,v=h+2*p+d):v=p*(A=-p/h)+d);else if(A<0)A=0,f>=0?(k=0,v=d):-f>=c?(k=1,v=c+2*f+d):v=f*(k=-f/c)+d;else{var M=1/T;v=(k*=M)*(c*k+u*(A*=M)+2*f)+A*(u*k+h*A+2*p)+d}else k<0?(_=h+p)>(x=u+f)?(b=_-x)>=(w=c-2*u+h)?(k=1,A=0,v=c+2*f+d):v=(k=b/w)*(c*k+u*(A=1-k)+2*f)+A*(u*k+h*A+2*p)+d:(k=0,_<=0?(A=1,v=h+2*p+d):p>=0?(A=0,v=d):v=p*(A=-p/h)+d):A<0?(_=c+f)>(x=u+p)?(b=_-x)>=(w=c-2*u+h)?(A=1,k=0,v=h+2*p+d):v=(k=1-(A=b/w))*(c*k+u*A+2*f)+A*(u*k+h*A+2*p)+d:(A=0,_<=0?(k=1,v=c+2*f+d):f>=0?(k=0,v=d):v=f*(k=-f/c)+d):(b=h+p-u-f)<=0?(k=0,A=1,v=h+2*p+d):b>=(w=c-2*u+h)?(k=1,A=0,v=c+2*f+d):v=(k=b/w)*(c*k+u*(A=1-k)+2*f)+A*(u*k+h*A+2*p)+d;var S=1-k-A;for(l=0;lr)for(t=r;te)for(t=e;t=0){for(var T=0|w.type.charAt(w.type.length-1),k=new Array(T),A=0;A=0;)M+=1;b[v]=M}var S=new Array(r.length);function E(){f.program=o.program(p,f._vref,f._fref,_,b);for(var t=0;tt&&r>0){var n=(e[r][0]-t)/(e[r][0]-e[r-1][0]);return e[r][1]*(1-n)+n*e[r-1][1]}}return 1}(n/255,e):t[3];return i<1&&(r=!0),[t[0],t[1],t[2],255*i]}))]);return c.divseq(n,255),this.hasAlphaScale=r,n},C.isTransparent=function(){return this.opacity<1||this.hasAlphaScale},C.isOpaque=function(){return!this.isTransparent()},C.pickSlots=1,C.setPickBase=function(t){this.pickId=t};var I=[0,0,0],L={showSurface:!1,showContour:!1,projections:[T.slice(),T.slice(),T.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function P(t,e){var r,n,i,a=e.axes&&e.axes.lastCubeProps.axis||I,o=e.showSurface,s=e.showContour;for(r=0;r<3;++r)for(o=o||e.surfaceProject[r],n=0;n<3;++n)s=s||e.contourProject[r][n];for(r=0;r<3;++r){var l=L.projections[r];for(n=0;n<16;++n)l[n]=0;for(n=0;n<4;++n)l[5*n]=1;l[5*r]=0,l[12+r]=e.axesBounds[+(a[r]>0)][r],p(l,t.model,l);var c=L.clipBounds[r];for(i=0;i<2;++i)for(n=0;n<3;++n)c[i][n]=t.clipBounds[i][n];c[0][r]=-1e8,c[1][r]=1e8}return L.showSurface=o,L.showContour=s,L}var z={model:T,view:T,projection:T,inverseModel:T.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},D=T.slice(),O=[1,0,0,0,1,0,0,0,1];function R(t,e){t=t||{};var r=this.gl;r.disable(r.CULL_FACE),this._colorMap.bind(0);var n=z;n.model=t.model||T,n.view=t.view||T,n.projection=t.projection||T,n.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],n.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],n.objectOffset=this.objectOffset,n.contourColor=this.contourColor[0],n.inverseModel=d(n.inverseModel,n.model);for(var i=0;i<2;++i)for(var a=n.clipBounds[i],o=0;o<3;++o)a[o]=Math.min(Math.max(this.clipBounds[i][o],-1e8),1e8);n.kambient=this.ambientLight,n.kdiffuse=this.diffuseLight,n.kspecular=this.specularLight,n.roughness=this.roughness,n.fresnel=this.fresnel,n.opacity=this.opacity,n.height=0,n.permutation=O,n.vertexColor=this.vertexColor;var s=D;for(p(s,n.view,n.model),p(s,n.projection,s),d(s,s),i=0;i<3;++i)n.eyePosition[i]=s[12+i]/s[15];var l=s[15];for(i=0;i<3;++i)l+=this.lightPosition[i]*s[4*i+3];for(i=0;i<3;++i){var c=s[12+i];for(o=0;o<3;++o)c+=s[4*o+i]*this.lightPosition[o];n.lightPosition[i]=c/l}var u=P(n,this);if(u.showSurface){for(this._shader.bind(),this._shader.uniforms=n,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(r.TRIANGLES,this._vertexCount),i=0;i<3;++i)!this.surfaceProject[i]||!this.vertexCount||(this._shader.uniforms.model=u.projections[i],this._shader.uniforms.clipBounds=u.clipBounds[i],this._vao.draw(r.TRIANGLES,this._vertexCount));this._vao.unbind()}if(u.showContour){var h=this._contourShader;n.kambient=1,n.kdiffuse=0,n.kspecular=0,n.opacity=1,h.bind(),h.uniforms=n;var f=this._contourVAO;for(f.bind(),i=0;i<3;++i)for(h.uniforms.permutation=A[i],r.lineWidth(this.contourWidth[i]*this.pixelRatio),o=0;o>4)/16)/255,i=Math.floor(n),a=n-i,o=e[1]*(t.value[1]+(15&t.value[2])/16)/255,s=Math.floor(o),l=o-s;i+=1,s+=1;var c=r.position;c[0]=c[1]=c[2]=0;for(var u=0;u<2;++u)for(var h=u?a:1-a,f=0;f<2;++f)for(var p=i+u,d=s+f,g=h*(f?l:1-l),y=0;y<3;++y)c[y]+=this._field[y].get(p,d)*g;for(var v=this._pickResult.level,x=0;x<3;++x)if(v[x]=m.le(this.contourLevels[x],c[x]),v[x]<0)this.contourLevels[x].length>0&&(v[x]=0);else if(v[x]Math.abs(b-c[x])&&(v[x]+=1)}for(r.index[0]=a<.5?i:i+1,r.index[1]=l<.5?s:s+1,r.uv[0]=n/e[0],r.uv[1]=o/e[1],y=0;y<3;++y)r.dataCoordinate[y]=this._field[y].get(r.index[0],r.index[1]);return r},C.padField=function(t,e){var r=e.shape.slice(),n=t.shape.slice();c.assign(t.lo(1,1).hi(r[0],r[1]),e),c.assign(t.lo(1).hi(r[0],1),e.hi(r[0],1)),c.assign(t.lo(1,n[1]-1).hi(r[0],1),e.lo(0,r[1]-1).hi(r[0],1)),c.assign(t.lo(0,1).hi(1,r[1]),e.hi(1)),c.assign(t.lo(n[0]-1,1).hi(1,r[1]),e.lo(r[0]-1)),t.set(0,0,e.get(0,0)),t.set(0,n[1]-1,e.get(0,r[1]-1)),t.set(n[0]-1,0,e.get(r[0]-1,0)),t.set(n[0]-1,n[1]-1,e.get(r[0]-1,r[1]-1))},C.update=function(t){t=t||{},this.objectOffset=t.objectOffset||this.objectOffset,this.dirty=!0,"contourWidth"in t&&(this.contourWidth=B(t.contourWidth,Number)),"showContour"in t&&(this.showContour=B(t.showContour,Boolean)),"showSurface"in t&&(this.showSurface=!!t.showSurface),"contourTint"in t&&(this.contourTint=B(t.contourTint,Boolean)),"contourColor"in t&&(this.contourColor=N(t.contourColor)),"contourProject"in t&&(this.contourProject=B(t.contourProject,(function(t){return B(t,Boolean)}))),"surfaceProject"in t&&(this.surfaceProject=t.surfaceProject),"dynamicColor"in t&&(this.dynamicColor=N(t.dynamicColor)),"dynamicTint"in t&&(this.dynamicTint=B(t.dynamicTint,Number)),"dynamicWidth"in t&&(this.dynamicWidth=B(t.dynamicWidth,Number)),"opacity"in t&&(this.opacity=t.opacity),"opacityscale"in t&&(this.opacityscale=t.opacityscale),"colorBounds"in t&&(this.colorBounds=t.colorBounds),"vertexColor"in t&&(this.vertexColor=t.vertexColor?1:0),"colormap"in t&&this._colorMap.setPixels(this.genColormap(t.colormap,this.opacityscale));var e=t.field||t.coords&&t.coords[2]||null,r=!1;if(e||(e=this._field[2].shape[0]||this._field[2].shape[2]?this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):this._field[2].hi(0,0)),"field"in t||"coords"in t){var i=(e.shape[0]+2)*(e.shape[1]+2);i>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(n.nextPow2(i))),this._field[2]=h(this._field[2].data,[e.shape[0]+2,e.shape[1]+2]),this.padField(this._field[2],e),this.shape=e.shape.slice();for(var a=this.shape,o=0;o<2;++o)this._field[2].size>this._field[o].data.length&&(s.freeFloat(this._field[o].data),this._field[o].data=s.mallocFloat(this._field[2].size)),this._field[o]=h(this._field[o].data,[a[0]+2,a[1]+2]);if(t.coords){var l=t.coords;if(!Array.isArray(l)||3!==l.length)throw new Error("gl-surface: invalid coordinates for x/y");for(o=0;o<2;++o){var c=l[o];for(y=0;y<2;++y)if(c.shape[y]!==a[y])throw new Error("gl-surface: coords have incorrect shape");this.padField(this._field[o],c)}}else if(t.ticks){var u=t.ticks;if(!Array.isArray(u)||2!==u.length)throw new Error("gl-surface: invalid ticks");for(o=0;o<2;++o){var p=u[o];if((Array.isArray(p)||p.length)&&(p=h(p)),p.shape[0]!==a[o])throw new Error("gl-surface: invalid tick length");var d=h(p.data,a);d.stride[o]=p.stride[0],d.stride[1^o]=0,this.padField(this._field[o],d)}}else{for(o=0;o<2;++o){var m=[0,0];m[o]=1,this._field[o]=h(this._field[o].data,[a[0]+2,a[1]+2],m,0)}this._field[0].set(0,0,0);for(var y=0;y0){for(var xt=0;xt<5;++xt)J.pop();U-=1}continue t}J.push(nt[0],nt[1],ot[0],ot[1],nt[2]),U+=1}}rt.push(U)}this._contourOffsets[Q]=et,this._contourCounts[Q]=rt}var _t=s.mallocFloat(J.length);for(o=0;o=0&&(e+=a*(r=0|t),i-=r),new n(this.data,i,a,e)},i.step=function(t){var e=this.shape[0],r=this.stride[0],i=this.offset,a=0,o=Math.ceil;return"number"==typeof t&&((a=0|t)<0?(i+=r*(e-1),e=o(-e/a)):e=o(e/a),r*=a),new n(this.data,e,r,i)},i.transpose=function(t){t=void 0===t?0:0|t;var e=this.shape,r=this.stride;return new n(this.data,e[t],r[t],this.offset)},i.pick=function(t){var r=[],n=[],i=this.offset;return"number"==typeof t&&t>=0?i=i+this.stride[0]*t|0:(r.push(this.shape[0]),n.push(this.stride[0])),(0,e[r.length+1])(this.data,r,n,i)},function(t,e,r,i){return new n(t,e[0],r[0],i)}},2:function(t,e,r){function n(t,e,r,n,i,a){this.data=t,this.shape=[e,r],this.stride=[n,i],this.offset=0|a}var i=n.prototype;return i.dtype=t,i.dimension=2,Object.defineProperty(i,"size",{get:function(){return this.shape[0]*this.shape[1]}}),Object.defineProperty(i,"order",{get:function(){return Math.abs(this.stride[0])>Math.abs(this.stride[1])?[1,0]:[0,1]}}),i.set=function(e,r,n){return"generic"===t?this.data.set(this.offset+this.stride[0]*e+this.stride[1]*r,n):this.data[this.offset+this.stride[0]*e+this.stride[1]*r]=n},i.get=function(e,r){return"generic"===t?this.data.get(this.offset+this.stride[0]*e+this.stride[1]*r):this.data[this.offset+this.stride[0]*e+this.stride[1]*r]},i.index=function(t,e){return this.offset+this.stride[0]*t+this.stride[1]*e},i.hi=function(t,e){return new n(this.data,"number"!=typeof t||t<0?this.shape[0]:0|t,"number"!=typeof e||e<0?this.shape[1]:0|e,this.stride[0],this.stride[1],this.offset)},i.lo=function(t,e){var r=this.offset,i=0,a=this.shape[0],o=this.shape[1],s=this.stride[0],l=this.stride[1];return"number"==typeof t&&t>=0&&(r+=s*(i=0|t),a-=i),"number"==typeof e&&e>=0&&(r+=l*(i=0|e),o-=i),new n(this.data,a,o,s,l,r)},i.step=function(t,e){var r=this.shape[0],i=this.shape[1],a=this.stride[0],o=this.stride[1],s=this.offset,l=0,c=Math.ceil;return"number"==typeof t&&((l=0|t)<0?(s+=a*(r-1),r=c(-r/l)):r=c(r/l),a*=l),"number"==typeof e&&((l=0|e)<0?(s+=o*(i-1),i=c(-i/l)):i=c(i/l),o*=l),new n(this.data,r,i,a,o,s)},i.transpose=function(t,e){t=void 0===t?0:0|t,e=void 0===e?1:0|e;var r=this.shape,i=this.stride;return new n(this.data,r[t],r[e],i[t],i[e],this.offset)},i.pick=function(t,r){var n=[],i=[],a=this.offset;return"number"==typeof t&&t>=0?a=a+this.stride[0]*t|0:(n.push(this.shape[0]),i.push(this.stride[0])),"number"==typeof r&&r>=0?a=a+this.stride[1]*r|0:(n.push(this.shape[1]),i.push(this.stride[1])),(0,e[n.length+1])(this.data,n,i,a)},function(t,e,r,i){return new n(t,e[0],e[1],r[0],r[1],i)}},3:function(t,e,r){function n(t,e,r,n,i,a,o,s){this.data=t,this.shape=[e,r,n],this.stride=[i,a,o],this.offset=0|s}var i=n.prototype;return i.dtype=t,i.dimension=3,Object.defineProperty(i,"size",{get:function(){return 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r},f.idle=function(t){this.center.idle(t),this.radius.idle(t),this.rotation.idle(t)},f.flush=function(t){this.center.flush(t),this.radius.flush(t),this.rotation.flush(t)},f.pan=function(t,e,r,n){e=e||0,r=r||0,n=n||0,this.recalcMatrix(t);var i=this.computedMatrix,a=i[1],o=i[5],s=i[9],c=l(a,o,s);a/=c,o/=c,s/=c;var u=i[0],h=i[4],f=i[8],p=u*a+h*o+f*s,d=l(u-=a*p,h-=o*p,f-=s*p);u/=d,h/=d,f/=d;var m=i[2],g=i[6],y=i[10],v=m*a+g*o+y*s,x=m*u+g*h+y*f,_=l(m-=v*a+x*u,g-=v*o+x*h,y-=v*s+x*f);m/=_,g/=_,y/=_;var b=u*e+a*r,w=h*e+o*r,T=f*e+s*r;this.center.move(t,b,w,T);var k=Math.exp(this.computedRadius[0]);k=Math.max(1e-4,k+n),this.radius.set(t,Math.log(k))},f.rotate=function(t,e,r,n){this.recalcMatrix(t),e=e||0,r=r||0;var i=this.computedMatrix,a=i[0],o=i[4],s=i[8],u=i[1],h=i[5],f=i[9],p=i[2],d=i[6],m=i[10],g=e*a+r*u,y=e*o+r*h,v=e*s+r*f,x=-(d*v-m*y),_=-(m*g-p*v),b=-(p*y-d*g),w=Math.sqrt(Math.max(0,1-Math.pow(x,2)-Math.pow(_,2)-Math.pow(b,2))),T=c(x,_,b,w);T>1e-6?(x/=T,_/=T,b/=T,w/=T):(x=_=b=0,w=1);var k=this.computedRotation,A=k[0],M=k[1],S=k[2],E=k[3],C=A*w+E*x+M*b-S*_,I=M*w+E*_+S*x-A*b,L=S*w+E*b+A*_-M*x,P=E*w-A*x-M*_-S*b;if(n){x=p,_=d,b=m;var z=Math.sin(n)/l(x,_,b);x*=z,_*=z,b*=z,P=P*(w=Math.cos(e))-(C=C*w+P*x+I*b-L*_)*x-(I=I*w+P*_+L*x-C*b)*_-(L=L*w+P*b+C*_-I*x)*b}var D=c(C,I,L,P);D>1e-6?(C/=D,I/=D,L/=D,P/=D):(C=I=L=0,P=1),this.rotation.set(t,C,I,L,P)},f.lookAt=function(t,e,r,n){this.recalcMatrix(t),r=r||this.computedCenter,e=e||this.computedEye,n=n||this.computedUp;var a=this.computedMatrix;i(a,e,r,n);var o=this.computedRotation;s(o,a[0],a[1],a[2],a[4],a[5],a[6],a[8],a[9],a[10]),u(o,o),this.rotation.set(t,o[0],o[1],o[2],o[3]);for(var l=0,c=0;c<3;++c)l+=Math.pow(r[c]-e[c],2);this.radius.set(t,.5*Math.log(Math.max(l,1e-6))),this.center.set(t,r[0],r[1],r[2])},f.translate=function(t,e,r,n){this.center.move(t,e||0,r||0,n||0)},f.setMatrix=function(t,e){var r=this.computedRotation;s(r,e[0],e[1],e[2],e[4],e[5],e[6],e[8],e[9],e[10]),u(r,r),this.rotation.set(t,r[0],r[1],r[2],r[3]);var 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r=Xd();e.exports=function(t){var e,i,a=[],o=1;if("string"==typeof t)if(t=t.toLowerCase(),r[t])a=r[t].slice(),i="rgb";else if("transparent"===t)o=0,i="rgb",a=[0,0,0];else if(/^#[A-Fa-f0-9]+$/.test(t)){var s=t.slice(1);o=1,(u=s.length)<=4?(a=[parseInt(s[0]+s[0],16),parseInt(s[1]+s[1],16),parseInt(s[2]+s[2],16)],4===u&&(o=parseInt(s[3]+s[3],16)/255)):(a=[parseInt(s[0]+s[1],16),parseInt(s[2]+s[3],16),parseInt(s[4]+s[5],16)],8===u&&(o=parseInt(s[6]+s[7],16)/255)),a[0]||(a[0]=0),a[1]||(a[1]=0),a[2]||(a[2]=0),i="rgb"}else if(e=/^((?:rgb|hs[lvb]|hwb|cmyk?|xy[zy]|gray|lab|lchu?v?|[ly]uv|lms)a?)\s*\(([^\)]*)\)/.exec(t)){var l=e[1],c="rgb"===l;i=s=l.replace(/a$/,"");var u="cmyk"===s?4:"gray"===s?1:3;a=e[2].trim().split(/\s*[,\/]\s*|\s+/).map((function(t,e){if(/%$/.test(t))return e===u?parseFloat(t)/100:"rgb"===s?255*parseFloat(t)/100:parseFloat(t);if("h"===s[e]){if(/deg$/.test(t))return parseFloat(t);if(void 0!==n[t])return n[t]}return parseFloat(t)})),l===s&&a.push(1),o=c||void 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e.geoProjection(Nr).scale(146.153)},t.geoTimesRaw=Nr,t.geoTwoPointAzimuthal=qr,t.geoTwoPointAzimuthalRaw=Vr,t.geoTwoPointAzimuthalUsa=function(){return qr([-158,21.5],[-77,39]).clipAngle(60).scale(400)},t.geoTwoPointEquidistant=Gr,t.geoTwoPointEquidistantRaw=Hr,t.geoTwoPointEquidistantUsa=function(){return Gr([-158,21.5],[-77,39]).clipAngle(130).scale(122.571)},t.geoVanDerGrinten=function(){return e.geoProjection(Wr).scale(79.4183)},t.geoVanDerGrintenRaw=Wr,t.geoVanDerGrinten2=function(){return e.geoProjection(Zr).scale(79.4183)},t.geoVanDerGrinten2Raw=Zr,t.geoVanDerGrinten3=function(){return e.geoProjection(Yr).scale(79.4183)},t.geoVanDerGrinten3Raw=Yr,t.geoVanDerGrinten4=function(){return e.geoProjection(Xr).scale(127.16)},t.geoVanDerGrinten4Raw=Xr,t.geoWagner=Kr,t.geoWagner7=function(){return Kr().poleline(65).parallels(60).inflation(0).ratio(200).scale(172.633)},t.geoWagnerRaw=$r,t.geoWagner4=function(){return e.geoProjection(tn).scale(176.84)},t.geoWagner4Raw=tn,t.geoWagner6=function(){return e.geoProjection(en).scale(152.63)},t.geoWagner6Raw=en,t.geoWiechel=function(){return e.geoProjection(rn).rotate([0,-90,45]).scale(124.75).clipAngle(179.999)},t.geoWiechelRaw=rn,t.geoWinkel3=function(){return e.geoProjection(nn).scale(158.837)},t.geoWinkel3Raw=nn,Object.defineProperty(t,"__esModule",{value:!0})},"object"==typeof t&&typeof e<"u"?n(t,Eg(),Sg()):n(r.d3=r.d3||{},r.d3,r.d3)}}),Ig=m({"src/plots/geo/zoom.js"(t,e){var r=b(),n=ce(),i=Ht(),a=Math.PI/180,o=180/Math.PI,s={cursor:"pointer"},l={cursor:"auto"};function c(t,e){return r.behavior.zoom().translate(e.translate()).scale(e.scale())}function u(t,e,r){var a=t.id,o=t.graphDiv,s=o.layout,l=s[a],c=o._fullLayout,u=c[a],h={},f={};function p(t,e){h[a+"."+t]=n.nestedProperty(l,t).get(),i.call("_storeDirectGUIEdit",s,c._preGUI,h);var r=n.nestedProperty(u,t);r.get()!==e&&(r.set(e),n.nestedProperty(l,t).set(e),f[a+"."+t]=e)}r(p),p("projection.scale",e.scale()/t.fitScale),p("fitbounds",!1),o.emit("plotly_relayout",f)}function h(t,e){var n=c(0,e);function i(r){var n=e.invert(t.midPt);r("center.lon",n[0]),r("center.lat",n[1])}return n.on("zoomstart",(function(){r.select(this).style(s)})).on("zoom",(function(){e.scale(r.event.scale).translate(r.event.translate),t.render(!0);var n=e.invert(t.midPt);t.graphDiv.emit("plotly_relayouting",{"geo.projection.scale":e.scale()/t.fitScale,"geo.center.lon":n[0],"geo.center.lat":n[1]})})).on("zoomend",(function(){r.select(this).style(l),u(t,e,i)})),n}function f(t,e){var n,i,a,o,h,f,p,d,m,g=c(0,e);function y(t){return e.invert(t)}function v(r){var n=e.rotate(),i=e.invert(t.midPt);r("projection.rotation.lon",-n[0]),r("center.lon",i[0]),r("center.lat",i[1])}return g.on("zoomstart",(function(){r.select(this).style(s),n=r.mouse(this),i=e.rotate(),a=e.translate(),o=i,h=y(n)})).on("zoom",(function(){if(f=r.mouse(this),function(t){var r=y(t);if(!r)return!0;var n=e(r);return Math.abs(n[0]-t[0])>2||Math.abs(n[1]-t[1])>2}(n))return g.scale(e.scale()),void g.translate(e.translate());e.scale(r.event.scale),e.translate([a[0],r.event.translate[1]]),h?y(f)&&(d=y(f),p=[o[0]+(d[0]-h[0]),i[1],i[2]],e.rotate(p),o=p):h=y(n=f),m=!0,t.render(!0);var s=e.rotate(),l=e.invert(t.midPt);t.graphDiv.emit("plotly_relayouting",{"geo.projection.scale":e.scale()/t.fitScale,"geo.center.lon":l[0],"geo.center.lat":l[1],"geo.projection.rotation.lon":-s[0]})})).on("zoomend",(function(){r.select(this).style(l),m&&u(t,e,v)})),g}function p(t,e){var n,i={r:e.rotate(),k:e.scale()},h=c(0,e),f=function(t){for(var e=0,n=arguments.length,i=[];++ed?(a=(h>0?90:-90)-p,i=0):(a=Math.asin(h/d)*o-p,i=Math.sqrt(d*d-h*h));var g=180-a-2*p,v=(Math.atan2(f,u)-Math.atan2(c,i))*o,x=(Math.atan2(f,u)-Math.atan2(c,-i))*o;return m(r[0],r[1],a,v)<=m(r[0],r[1],g,x)?[a,v,r[2]]:[g,x,r[2]]}(p,n,c);(!isFinite(g[0])||!isFinite(g[1])||!isFinite(g[2]))&&(g=c),e.rotate(g),c=g}}else n=d(e,t=a);!function(t){t({type:"zoom"})}(f.of(this,arguments))})),function(t){p++||t({type:"zoomstart"})}(f.of(this,arguments))})).on("zoomend",(function(){var n;r.select(this).style(l),g.call(h,"zoom",null),n=f.of(this,arguments),--p||n({type:"zoomend"}),u(t,e,x)})).on("zoom.redraw",(function(){t.render(!0);var r=e.rotate();t.graphDiv.emit("plotly_relayouting",{"geo.projection.scale":e.scale()/t.fitScale,"geo.projection.rotation.lon":-r[0],"geo.projection.rotation.lat":-r[1]})})),r.rebind(h,f,"on")}function d(t,e){var r=t.invert(e);return r&&isFinite(r[0])&&isFinite(r[1])&&function(t){var e=t[0]*a,r=t[1]*a,n=Math.cos(r);return[n*Math.cos(e),n*Math.sin(e),Math.sin(r)]}(r)}function m(t,e,r,n){var i=g(r-t),a=g(n-e);return Math.sqrt(i*i+a*a)}function g(t){return(t%360+540)%360-180}function y(t,e,r){var n=r*a,i=t.slice(),o=0===e?1:0,s=2===e?1:2,l=Math.cos(n),c=Math.sin(n);return i[o]=t[o]*l-t[s]*c,i[s]=t[s]*l+t[o]*c,i}function v(t,e){for(var r=0,n=0,i=t.length;n0&&i<0&&(i+=360);var s=(i-n)/4;return{type:"Polygon",coordinates:[[[n,a],[n,o],[n+s,o],[n+2*s,o],[n+3*s,o],[i,o],[i,a],[i-s,a],[i-2*s,a],[i-3*s,a],[n,a]]]}}e.exports=function(t){return new M(t)},S.plot=function(t,e,r,n){var i=this;if(n)return i.update(t,e,!0);i._geoCalcData=t,i._fullLayout=e;var a=e[this.id],o=[],s=!1;for(var l in w.layerNameToAdjective)if("frame"!==l&&a["show"+l]){s=!0;break}for(var c=!1,u=0;u0&&o._module.calcGeoJSON(a,e)}if(!r){if(this.updateProjection(t,e))return;(!this.viewInitial||this.scope!==n.scope)&&this.saveViewInitial(n)}this.scope=n.scope,this.updateBaseLayers(e,n),this.updateDims(e,n),this.updateFx(e,n),p.generalUpdatePerTraceModule(this.graphDiv,this,t,n);var s=this.layers.frontplot.select(".scatterlayer");this.dataPoints.point=s.selectAll(".point"),this.dataPoints.text=s.selectAll("text"),this.dataPaths.line=s.selectAll(".js-line");var l=this.layers.backplot.select(".choroplethlayer");this.dataPaths.choropleth=l.selectAll("path"),this._render()},S.updateProjection=function(t,e){var r=this.graphDiv,s=e[this.id],c=e._size,u=s.domain,h=s.projection,f=s.lonaxis,p=s.lataxis,d=f._ax,g=p._ax,y=this.projection=function(t){var e=t.projection,r=e.type,s=w.projNames[r];s="geo"+l.titleCase(s);for(var c=(n[s]||o[s])(),u=t._isSatellite?180*Math.acos(1/e.distance)/Math.PI:t._isClipped?w.lonaxisSpan[r]/2:null,h=["center","rotate","parallels","clipExtent"],f=function(t){return t?c:[]},p=0;pu*Math.PI/180}return!1},c.getPath=function(){return i().projection(c)},c.getBounds=function(t){return c.getPath().bounds(t)},c.precision(w.precision),t._isSatellite&&c.tilt(e.tilt).distance(e.distance),u&&c.clipAngle(u-w.clipPad),c}(s),v=[[c.l+c.w*u.x[0],c.t+c.h*(1-u.y[1])],[c.l+c.w*u.x[1],c.t+c.h*(1-u.y[0])]],x=s.center||{},_=h.rotation||{},b=f.range||[],T=p.range||[];if(s.fitbounds){d._length=v[1][0]-v[0][0],g._length=v[1][1]-v[0][1],d.range=m(r,d),g.range=m(r,g);var k=(d.range[0]+d.range[1])/2,A=(g.range[0]+g.range[1])/2;if(s._isScoped)x={lon:k,lat:A};else if(s._isClipped){x={lon:k,lat:A},_={lon:k,lat:A,roll:_.roll};var M=h.type,S=w.lonaxisSpan[M]/2||180,C=w.lataxisSpan[M]/2||90;b=[k-S,k+S],T=[A-C,A+C]}else x={lon:k,lat:A},_={lon:k,lat:_.lat,roll:_.roll}}y.center([x.lon-_.lon,x.lat-_.lat]).rotate([-_.lon,-_.lat,_.roll]).parallels(h.parallels);var I=E(b,T);y.fitExtent(v,I);var L=this.bounds=y.getBounds(I),P=this.fitScale=y.scale(),z=y.translate();if(s.fitbounds){var D=y.getBounds(E(d.range,g.range)),O=Math.min((L[1][0]-L[0][0])/(D[1][0]-D[0][0]),(L[1][1]-L[0][1])/(D[1][1]-D[0][1]));isFinite(O)?y.scale(O*P):l.warn("Something went wrong during"+this.id+"fitbounds computations.")}else y.scale(h.scale*P);var R=this.midPt=[(L[0][0]+L[1][0])/2,(L[0][1]+L[1][1])/2];if(y.translate([z[0]+(R[0]-z[0]),z[1]+(R[1]-z[1])]).clipExtent(L),s._isAlbersUsa){var F=y([x.lon,x.lat]),B=y.translate();y.translate([B[0]-(F[0]-B[0]),B[1]-(F[1]-B[1])])}},S.updateBaseLayers=function(t,e){var n=this,i=n.topojson,a=n.layers,o=n.basePaths;function s(t){return"lonaxis"===t||"lataxis"===t}function l(t){return!!w.lineLayers[t]}function c(t){return!!w.fillLayers[t]}var f=(this.hasChoropleth?w.layersForChoropleth:w.layers).filter((function(t){return l(t)||c(t)?e["show"+t]:!s(t)||e[t].showgrid})),p=n.framework.selectAll(".layer").data(f,String);p.exit().each((function(t){delete a[t],delete o[t],r.select(this).remove()})),p.enter().append("g").attr("class",(function(t){return"layer 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Array(u),f=0;f-1&&x(r.event,i,[n.xaxis],[n.yaxis],n.id,u),c.indexOf("event")>-1&&f.click(i,r.event))}))}function h(t){return n.projection.invert([t[0]+n.xaxis._offset,t[1]+n.yaxis._offset])}},S.makeFramework=function(){var t=this,e=t.graphDiv,n=e._fullLayout,i="clip"+n._uid+t.id;t.clipDef=n._clips.append("clipPath").attr("id",i),t.clipRect=t.clipDef.append("rect"),t.framework=r.select(t.container).append("g").attr("class","geo "+t.id).call(h.setClipUrl,i,e),t.project=function(e){var r=t.projection(e);return r?[r[0]-t.xaxis._offset,r[1]-t.yaxis._offset]:[null,null]},t.xaxis={_id:"x",c2p:function(e){return t.project(e)[0]}},t.yaxis={_id:"y",c2p:function(e){return t.project(e)[1]}},t.mockAxis={type:"linear",showexponent:"all",exponentformat:"B"},d.setConvert(t.mockAxis,n)},S.saveViewInitial=function(t){var e,r=t.center||{},n=t.projection,i=n.rotation||{};this.viewInitial={fitbounds:t.fitbounds,"projection.scale":n.scale},e=t._isScoped?{"center.lon":r.lon,"center.lat":r.lat}:t._isClipped?{"projection.rotation.lon":i.lon,"projection.rotation.lat":i.lat}:{"center.lon":r.lon,"center.lat":r.lat,"projection.rotation.lon":i.lon},l.extendFlat(this.viewInitial,e)},S.render=function(t){this._hasMarkerAngles&&t?this.plot(this._geoCalcData,this._fullLayout,[],!0):this._render()},S._render=function(){var t,e=this.projection,r=e.getPath();function n(t){var r=e(t.lonlat);return r?c(r[0],r[1]):null}function i(t){return e.isLonLatOverEdges(t.lonlat)?"none":null}for(t in this.basePaths)this.basePaths[t].attr("d",r);for(t in this.dataPaths)this.dataPaths[t].attr("d",(function(t){return r(t.geojson)}));for(t in this.dataPoints)this.dataPoints[t].attr("display",i).attr("transform",n)}}}),Pg=m({"src/plots/geo/layout_attributes.js"(t,e){var r=G(),n=Aa().attributes,i=Ot().dash,a=hg(),o=Dt().overrideAll,s=Yt(),l={range:{valType:"info_array",items:[{valType:"number"},{valType:"number"}]},showgrid:{valType:"boolean",dflt:!1},tick0:{valType:"number",dflt:0},dtick:{valType:"number"},gridcolor:{valType:"color",dflt:r.lightLine},gridwidth:{valType:"number",min:0,dflt:1},griddash:i};(e.exports=o({domain:n({name:"geo"},{}),fitbounds:{valType:"enumerated",values:[!1,"locations","geojson"],dflt:!1,editType:"plot"},resolution:{valType:"enumerated",values:[110,50],dflt:110,coerceNumber:!0},scope:{valType:"enumerated",values:s(a.scopeDefaults),dflt:"world"},projection:{type:{valType:"enumerated",values:s(a.projNames)},rotation:{lon:{valType:"number"},lat:{valType:"number"},roll:{valType:"number"}},tilt:{valType:"number",dflt:0},distance:{valType:"number",min:1.001,dflt:2},parallels:{valType:"info_array",items:[{valType:"number"},{valType:"number"}]},scale:{valType:"number",min:0,dflt:1}},center:{lon:{valType:"number"},lat:{valType:"number"}},visible:{valType:"boolean",dflt:!0},showcoastlines:{valType:"boolean"},coastlinecolor:{valType:"color",dflt:r.defaultLine},coastlinewidth:{valType:"number",min:0,dflt:1},showland:{valType:"boolean",dflt:!1},landcolor:{valType:"color",dflt:a.landColor},showocean:{valType:"boolean",dflt:!1},oceancolor:{valType:"color",dflt:a.waterColor},showlakes:{valType:"boolean",dflt:!1},lakecolor:{valType:"color",dflt:a.waterColor},showrivers:{valType:"boolean",dflt:!1},rivercolor:{valType:"color",dflt:a.waterColor},riverwidth:{valType:"number",min:0,dflt:1},showcountries:{valType:"boolean"},countrycolor:{valType:"color",dflt:r.defaultLine},countrywidth:{valType:"number",min:0,dflt:1},showsubunits:{valType:"boolean"},subunitcolor:{valType:"color",dflt:r.defaultLine},subunitwidth:{valType:"number",min:0,dflt:1},showframe:{valType:"boolean"},framecolor:{valType:"color",dflt:r.defaultLine},framewidth:{valType:"number",min:0,dflt:1},bgcolor:{valType:"color",dflt:r.background},lonaxis:l,lataxis:l},"plot","from-root")).uirevision={valType:"any",editType:"none"}}}),zg=m({"src/plots/geo/layout_defaults.js"(t,e){var r=ce(),n=Gs(),i=Te().getSubplotData,a=hg(),o=Pg(),s=a.axesNames;function l(t,e,n,o){var l=i(o.fullData,"geo",o.id).map((function(t){return t.index})),c=n("resolution"),u=n("scope"),h=a.scopeDefaults[u],f=n("projection.type",h.projType),p=e._isAlbersUsa="albers usa"===f;p&&(u=e.scope="usa");var d=e._isScoped="world"!==u,m=e._isSatellite="satellite"===f,g=e._isConic=-1!==f.indexOf("conic")||"albers"===f,y=e._isClipped=!!a.lonaxisSpan[f];if(!1===t.visible){var v=r.extendDeep({},e._template);v.showcoastlines=!1,v.showcountries=!1,v.showframe=!1,v.showlakes=!1,v.showland=!1,v.showocean=!1,v.showrivers=!1,v.showsubunits=!1,v.lonaxis&&(v.lonaxis.showgrid=!1),v.lataxis&&(v.lataxis.showgrid=!1),e._template=v}for(var x=n("visible"),_=0;_0&&L<0&&(L+=360);var P,z,D,O=(I+L)/2;if(!p){var 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vec2 aCoord, bCoord, nextCoord, prevCoord;\nattribute vec4 aColor, bColor;\nattribute float lineEnd, lineTop;\n\nuniform vec2 scale, translate;\nuniform float thickness, pixelRatio, id, depth;\nuniform vec4 viewport;\nuniform float miterLimit, miterMode;\n\nvarying vec4 fragColor;\nvarying vec4 startCutoff, endCutoff;\nvarying vec2 tangent;\nvarying vec2 startCoord, endCoord;\nvarying float enableStartMiter, enableEndMiter;\n\nconst float REVERSE_THRESHOLD = -.875;\nconst float MIN_DIFF = 1e-6;\n\n// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead\n// TODO: precalculate dot products, normalize things beforehead etc.\n// TODO: refactor to rectangular algorithm\n\nfloat distToLine(vec2 p, vec2 a, vec2 b) {\n\tvec2 diff = b - a;\n\tvec2 perp = normalize(vec2(-diff.y, diff.x));\n\treturn dot(p - a, perp);\n}\n\nbool isNaN( float val ){\n return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true;\n}\n\nvoid main() {\n\tvec2 aCoord = 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normalize(prevTangent - currTangent);\n\tvec2 endJoinDirection = normalize(currTangent - nextTangent);\n\n\t// collapsed/unidirectional segment cases\n\t// FIXME: there should be more elegant solution\n\tvec2 prevTanDiff = abs(prevTangent - currTangent);\n\tvec2 nextTanDiff = abs(nextTangent - currTangent);\n\tif (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) {\n\t\tstartJoinDirection = currNormal;\n\t}\n\tif (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) {\n\t\tendJoinDirection = currNormal;\n\t}\n\tif (aCoord == bCoord) {\n\t\tendJoinDirection = startJoinDirection;\n\t\tcurrNormal = prevNormal;\n\t\tcurrTangent = prevTangent;\n\t}\n\n\ttangent = currTangent;\n\n\t//calculate join shifts relative to normals\n\tfloat startJoinShift = dot(currNormal, startJoinDirection);\n\tfloat endJoinShift = dot(currNormal, endJoinDirection);\n\n\tfloat startMiterRatio = abs(1. / startJoinShift);\n\tfloat endMiterRatio = abs(1. / endJoinShift);\n\n\tvec2 startJoin = startJoinDirection * startMiterRatio;\n\tvec2 endJoin = endJoinDirection * endMiterRatio;\n\n\tvec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin;\n\tstartTopJoin = sign(startJoinShift) * startJoin * .5;\n\tstartBotJoin = -startTopJoin;\n\n\tendTopJoin = sign(endJoinShift) * endJoin * .5;\n\tendBotJoin = -endTopJoin;\n\n\tvec2 aTopCoord = aCoord + normalWidth * startTopJoin;\n\tvec2 bTopCoord = bCoord + normalWidth * endTopJoin;\n\tvec2 aBotCoord = aCoord + normalWidth * startBotJoin;\n\tvec2 bBotCoord = bCoord + normalWidth * endBotJoin;\n\n\t//miter anti-clipping\n\tfloat baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x)));\n\tfloat abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x)));\n\n\t//prevent close to reverse direction switch\n\tbool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) < length(normalWidth * currNormal);\n\tbool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) < length(normalWidth * currNormal);\n\n\tif (prevReverse) {\n\t\t//make join rectangular\n\t\tvec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5;\n\t\tfloat normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.);\n\t\taBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\n\t\taTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\n\t}\n\telse if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) {\n\t\t//handle miter clipping\n\t\tbTopCoord -= normalWidth * endTopJoin;\n\t\tbTopCoord += normalize(endTopJoin * normalWidth) * baClipping;\n\t}\n\n\tif (nextReverse) {\n\t\t//make join rectangular\n\t\tvec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5;\n\t\tfloat normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.);\n\t\tbBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5;\n\t\tbTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5;\n\t}\n\telse if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) {\n\t\t//handle miter clipping\n\t\taBotCoord -= normalWidth * startBotJoin;\n\t\taBotCoord += normalize(startBotJoin * normalWidth) * abClipping;\n\t}\n\n\tvec2 aTopPosition = (aTopCoord) * adjustedScale + translate;\n\tvec2 aBotPosition = (aBotCoord) * adjustedScale + translate;\n\n\tvec2 bTopPosition = (bTopCoord) * adjustedScale + translate;\n\tvec2 bBotPosition = (bBotCoord) * adjustedScale + translate;\n\n\t//position is normalized 0..1 coord on the screen\n\tvec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * 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r=e.brush,i=r.filter,a=r.svgBrush;a._dragging||(T(t,e),w(t,e),e.brush.svgBrush.wasDragged=!1),a._dragging=!1,n.event.sourceEvent.stopPropagation();var o=a.grabbingBar;if(a.grabbingBar=!1,a.grabLocation=void 0,e.parent.inBrushDrag=!1,y(),!a.wasDragged)return a.wasDragged=void 0,a.clickableOrdinalRange?r.filterSpecified&&e.multiselect?a.extent.push(a.clickableOrdinalRange):(a.extent=[a.clickableOrdinalRange],r.filterSpecified=!0):o?(a.extent=a.stayingIntervals,0===a.extent.length&&M(r)):M(r),a.brushCallback(e),x(t.parentNode),void a.brushEndCallback(r.filterSpecified?i.getConsolidated():[]);var s=function(){i.set(i.getConsolidated())};if(e.ordinal){var l=e.unitTickvals;l[l.length-1]a.newExtent[0];a.extent=a.stayingIntervals.concat(c?[a.newExtent]:[]),a.extent.length||M(r),a.brushCallback(e),c?x(t.parentNode,s):(s(),x(t.parentNode))}else s();a.brushEndCallback(r.filterSpecified?i.getConsolidated():[])}(this,t)})))}function A(t,e){return t[0]-e[0]}function M(t){t.filterSpecified=!1,t.svgBrush.extent=[[-1/0,1/0]]}function S(t){return function(e){var r=e.brush,n=function(t){return t.svgBrush.extent.map((function(t){return t.slice()}))}(r),i=n.slice();r.filter.set(i),t()}}function E(t){for(var e,r=t.slice(),n=[],i=r.shift();i;){for(e=i.slice();(i=r.shift())&&i[0]<=e[1];)e[1]=Math.max(e[1],i[1]);n.push(e)}return 1===n.length&&n[0][0]>n[0][1]&&(n=[]),n}e.exports={makeBrush:function(t,e,r,n,i,a){var s=function(){var t,e,r=[];return{set:function(n){1===(r=n.map((function(t){return t.slice().sort(o)})).sort(A)).length&&r[0][0]===-1/0&&r[0][1]===1/0&&(r=[[0,-1]]),t=E(r),e=r.reduce((function(t,e){return[Math.min(t[0],e[0]),Math.max(t[1],e[1])]}),[1/0,-1/0])},get:function(){return r.slice()},getConsolidated:function(){return t},getBounds:function(){return e}}}();return s.set(r),{filter:s,filterSpecified:e,svgBrush:{extent:[],brushStartCallback:n,brushCallback:S(i),brushEndCallback:a}}},ensureAxisBrush:function(t,e,n){var o=t.selectAll("."+r.cn.axisBrush).data(a,i);o.enter().append("g").classed(r.cn.axisBrush,!0),function(t,e,n){var i=n._context.staticPlot,o=t.selectAll(".background").data(a);o.enter().append("rect").classed("background",!0).call(p).call(d).style("pointer-events",i?"none":"auto").attr("transform",s(0,r.verticalPadding)),o.call(k).attr("height",(function(t){return t.height-r.verticalPadding}));var l=t.selectAll(".highlight-shadow").data(a);l.enter().append("line").classed("highlight-shadow",!0).attr("x",-r.bar.width/2).attr("stroke-width",r.bar.width+r.bar.strokeWidth).attr("stroke",e).attr("opacity",r.bar.strokeOpacity).attr("stroke-linecap","butt"),l.attr("y1",(function(t){return t.height})).call(v);var c=t.selectAll(".highlight").data(a);c.enter().append("line").classed("highlight",!0).attr("x",-r.bar.width/2).attr("stroke-width",r.bar.width-r.bar.strokeWidth).attr("stroke",r.bar.fillColor).attr("opacity",r.bar.fillOpacity).attr("stroke-linecap","butt"),c.attr("y1",(function(t){return t.height})).call(v)}(o,e,n)},cleanRanges:function(t,e){if(Array.isArray(t[0])?(t=t.map((function(t){return t.sort(o)})),t=e.multiselect?E(t.sort(A)):[t[0]]):t=[t.sort(o)],e.tickvals){var r=e.tickvals.slice().sort(o);if(!(t=t.map((function(t){var e=[f(0,r,t[0],[]),f(1,r,t[1],[])];if(e[1]>e[0])return e})).filter((function(t){return t}))).length)return}return t.length>1?t:t[0]}}}}),Jx=m({"src/traces/parcoords/defaults.js"(t,e){var r=ce(),n=Ce().hasColorscale,i=He(),a=Aa().defaults,o=Ne(),s=ar(),l=Yx(),c=Kx(),u=Xx().maxDimensionCount,h=Lx();function f(t,e,n,i){function a(n,i){return r.coerce(t,e,l.dimensions,n,i)}var o=a("values"),u=a("visible");if(o&&o.length||(u=e.visible=!1),u){a("label"),a("tickvals"),a("ticktext"),a("tickformat");var h=a("range");e._ax={_id:"y",type:"linear",showexponent:"all",exponentformat:"B",range:h},s.setConvert(e._ax,i.layout),a("multiselect");var f=a("constraintrange");f&&(e.constraintrange=c.cleanRanges(f,e))}}e.exports=function(t,e,s,c){function p(n,i){return 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r=ce(),n=Xe(),i=Yn(),a=Xn(),o=Kn(),s=Jn(),l=I_(),c=L_().isSupportedFont;e.exports=function(t,e,u,h){function f(n,i){return r.coerce(t,e,l,n,i)}function p(n,i){return r.coerce2(t,e,l,n,i)}var d=function(t,e,r){var n=r("lon")||[],i=r("lat")||[],a=Math.min(n.length,i.length);return e._length=a,a}(0,e,f);if(d){if(f("text"),f("texttemplate"),f("texttemplatefallback"),f("hovertext"),f("hovertemplate"),f("hovertemplatefallback"),f("mode"),f("below"),n.hasMarkers(e)){i(t,e,u,h,f,{noLine:!0,noAngle:!0}),f("marker.allowoverlap"),f("marker.angle");var m=e.marker;"circle"!==m.symbol&&(r.isArrayOrTypedArray(m.size)&&(m.size=m.size[0]),r.isArrayOrTypedArray(m.color)&&(m.color=m.color[0]))}n.hasLines(e)&&(a(t,e,u,h,f,{noDash:!0}),f("connectgaps"));var g=p("cluster.maxzoom"),y=p("cluster.step"),v=p("cluster.color",e.marker&&e.marker.color||u),x=p("cluster.size"),_=p("cluster.opacity");if(f("cluster.enabled",!1!==g||!1!==y||!1!==v||!1!==x||!1!==_)||n.hasText(e)){var 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this.int16[v+0]=e,this.int16[v+1]=r,this.uint16[v+2]=n,this.uint16[v+3]=i,this.uint32[x+2]=a,this.uint32[x+3]=o,this.uint32[x+4]=s,this.uint16[v+10]=l,this.uint16[v+11]=c,this.uint16[v+12]=u,this.float32[x+7]=h,this.float32[x+8]=f,this.uint8[_+36]=p,this.uint8[_+37]=d,this.uint8[_+38]=m,this.uint32[x+10]=g,this.int16[v+22]=y,t},e}(Ji);ma.prototype.bytesPerElement=48,ii("StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48",ma);var ga=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n,i,a,o,s,l,c,u,h,f,p,d,m,g,y,v,x,_,b,w,T,k,A,M,S){var E=this.length;return this.resize(E+1),this.emplace(E,t,e,r,n,i,a,o,s,l,c,u,h,f,p,d,m,g,y,v,x,_,b,w,T,k,A,M,S)},e.prototype.emplace=function(t,e,r,n,i,a,o,s,l,c,u,h,f,p,d,m,g,y,v,x,_,b,w,T,k,A,M,S,E){var C=34*t,I=17*t;return this.int16[C+0]=e,this.int16[C+1]=r,this.int16[C+2]=n,this.int16[C+3]=i,this.int16[C+4]=a,this.int16[C+5]=o,this.int16[C+6]=s,this.int16[C+7]=l,this.uint16[C+8]=c,this.uint16[C+9]=u,this.uint16[C+10]=h,this.uint16[C+11]=f,this.uint16[C+12]=p,this.uint16[C+13]=d,this.uint16[C+14]=m,this.uint16[C+15]=g,this.uint16[C+16]=y,this.uint16[C+17]=v,this.uint16[C+18]=x,this.uint16[C+19]=_,this.uint16[C+20]=b,this.uint16[C+21]=w,this.uint16[C+22]=T,this.uint32[I+12]=k,this.float32[I+13]=A,this.float32[I+14]=M,this.float32[I+15]=S,this.float32[I+16]=E,t},e}(Ji);ga.prototype.bytesPerElement=68,ii("StructArrayLayout8i15ui1ul4f68",ga);var ya=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.float32[r+0]=e,t},e}(Ji);ya.prototype.bytesPerElement=4,ii("StructArrayLayout1f4",ya);var va=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=3*t;return this.int16[i+0]=e,this.int16[i+1]=r,this.int16[i+2]=n,t},e}(Ji);va.prototype.bytesPerElement=6,ii("StructArrayLayout3i6",va);var xa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r){var n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)},e.prototype.emplace=function(t,e,r,n){var i=2*t,a=4*t;return this.uint32[i+0]=e,this.uint16[a+2]=r,this.uint16[a+3]=n,t},e}(Ji);xa.prototype.bytesPerElement=8,ii("StructArrayLayout1ul2ui8",xa);var _a=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e){var r=this.length;return this.resize(r+1),this.emplace(r,t,e)},e.prototype.emplace=function(t,e,r){var n=2*t;return this.uint16[n+0]=e,this.uint16[n+1]=r,t},e}(Ji);_a.prototype.bytesPerElement=4,ii("StructArrayLayout2ui4",_a);var ba=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t){var e=this.length;return this.resize(e+1),this.emplace(e,t)},e.prototype.emplace=function(t,e){var r=1*t;return this.uint16[r+0]=e,t},e}(Ji);ba.prototype.bytesPerElement=2,ii("StructArrayLayout1ui2",ba);var wa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},e.prototype.emplaceBack=function(t,e,r,n){var i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)},e.prototype.emplace=function(t,e,r,n,i){var a=4*t;return this.float32[a+0]=e,this.float32[a+1]=r,this.float32[a+2]=n,this.float32[a+3]=i,t},e}(Ji);wa.prototype.bytesPerElement=16,ii("StructArrayLayout4f16",wa);var Ta=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorPointX:{configurable:!0},anchorPointY:{configurable:!0},x1:{configurable:!0},y1:{configurable:!0},x2:{configurable:!0},y2:{configurable:!0},featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0},anchorPoint:{configurable:!0}};return r.anchorPointX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorPointY.get=function(){return this._structArray.int16[this._pos2+1]},r.x1.get=function(){return this._structArray.int16[this._pos2+2]},r.y1.get=function(){return this._structArray.int16[this._pos2+3]},r.x2.get=function(){return this._structArray.int16[this._pos2+4]},r.y2.get=function(){return this._structArray.int16[this._pos2+5]},r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+8]},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.anchorPoint.get=function(){return new a(this.anchorPointX,this.anchorPointY)},Object.defineProperties(e.prototype,r),e}(Ki);Ta.prototype.size=20;var ka=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new Ta(this,t)},e}(ua);ii("CollisionBoxArray",ka);var Aa=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},glyphStartIndex:{configurable:!0},numGlyphs:{configurable:!0},vertexStartIndex:{configurable:!0},lineStartIndex:{configurable:!0},lineLength:{configurable:!0},segment:{configurable:!0},lowerSize:{configurable:!0},upperSize:{configurable:!0},lineOffsetX:{configurable:!0},lineOffsetY:{configurable:!0},writingMode:{configurable:!0},placedOrientation:{configurable:!0},hidden:{configurable:!0},crossTileID:{configurable:!0},associatedIconIndex:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.glyphStartIndex.get=function(){return this._structArray.uint16[this._pos2+2]},r.numGlyphs.get=function(){return this._structArray.uint16[this._pos2+3]},r.vertexStartIndex.get=function(){return this._structArray.uint32[this._pos4+2]},r.lineStartIndex.get=function(){return this._structArray.uint32[this._pos4+3]},r.lineLength.get=function(){return this._structArray.uint32[this._pos4+4]},r.segment.get=function(){return this._structArray.uint16[this._pos2+10]},r.lowerSize.get=function(){return this._structArray.uint16[this._pos2+11]},r.upperSize.get=function(){return this._structArray.uint16[this._pos2+12]},r.lineOffsetX.get=function(){return this._structArray.float32[this._pos4+7]},r.lineOffsetY.get=function(){return this._structArray.float32[this._pos4+8]},r.writingMode.get=function(){return this._structArray.uint8[this._pos1+36]},r.placedOrientation.get=function(){return this._structArray.uint8[this._pos1+37]},r.placedOrientation.set=function(t){this._structArray.uint8[this._pos1+37]=t},r.hidden.get=function(){return this._structArray.uint8[this._pos1+38]},r.hidden.set=function(t){this._structArray.uint8[this._pos1+38]=t},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+10]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+10]=t},r.associatedIconIndex.get=function(){return this._structArray.int16[this._pos2+22]},Object.defineProperties(e.prototype,r),e}(Ki);Aa.prototype.size=48;var Ma=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new Aa(this,t)},e}(ma);ii("PlacedSymbolArray",Ma);var Sa=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={anchorX:{configurable:!0},anchorY:{configurable:!0},rightJustifiedTextSymbolIndex:{configurable:!0},centerJustifiedTextSymbolIndex:{configurable:!0},leftJustifiedTextSymbolIndex:{configurable:!0},verticalPlacedTextSymbolIndex:{configurable:!0},placedIconSymbolIndex:{configurable:!0},verticalPlacedIconSymbolIndex:{configurable:!0},key:{configurable:!0},textBoxStartIndex:{configurable:!0},textBoxEndIndex:{configurable:!0},verticalTextBoxStartIndex:{configurable:!0},verticalTextBoxEndIndex:{configurable:!0},iconBoxStartIndex:{configurable:!0},iconBoxEndIndex:{configurable:!0},verticalIconBoxStartIndex:{configurable:!0},verticalIconBoxEndIndex:{configurable:!0},featureIndex:{configurable:!0},numHorizontalGlyphVertices:{configurable:!0},numVerticalGlyphVertices:{configurable:!0},numIconVertices:{configurable:!0},numVerticalIconVertices:{configurable:!0},useRuntimeCollisionCircles:{configurable:!0},crossTileID:{configurable:!0},textBoxScale:{configurable:!0},textOffset0:{configurable:!0},textOffset1:{configurable:!0},collisionCircleDiameter:{configurable:!0}};return r.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},r.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},r.rightJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+2]},r.centerJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+3]},r.leftJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+4]},r.verticalPlacedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+5]},r.placedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+6]},r.verticalPlacedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+7]},r.key.get=function(){return this._structArray.uint16[this._pos2+8]},r.textBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+9]},r.textBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+10]},r.verticalTextBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+11]},r.verticalTextBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+12]},r.iconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+13]},r.iconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+14]},r.verticalIconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+15]},r.verticalIconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+16]},r.featureIndex.get=function(){return this._structArray.uint16[this._pos2+17]},r.numHorizontalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+18]},r.numVerticalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+19]},r.numIconVertices.get=function(){return this._structArray.uint16[this._pos2+20]},r.numVerticalIconVertices.get=function(){return this._structArray.uint16[this._pos2+21]},r.useRuntimeCollisionCircles.get=function(){return this._structArray.uint16[this._pos2+22]},r.crossTileID.get=function(){return this._structArray.uint32[this._pos4+12]},r.crossTileID.set=function(t){this._structArray.uint32[this._pos4+12]=t},r.textBoxScale.get=function(){return this._structArray.float32[this._pos4+13]},r.textOffset0.get=function(){return this._structArray.float32[this._pos4+14]},r.textOffset1.get=function(){return this._structArray.float32[this._pos4+15]},r.collisionCircleDiameter.get=function(){return this._structArray.float32[this._pos4+16]},Object.defineProperties(e.prototype,r),e}(Ki);Sa.prototype.size=68;var Ea=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new Sa(this,t)},e}(ga);ii("SymbolInstanceArray",Ea);var Ca=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getoffsetX=function(t){return this.float32[1*t+0]},e}(ya);ii("GlyphOffsetArray",Ca);var Ia=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.getx=function(t){return this.int16[3*t+0]},e.prototype.gety=function(t){return this.int16[3*t+1]},e.prototype.gettileUnitDistanceFromAnchor=function(t){return this.int16[3*t+2]},e}(va);ii("SymbolLineVertexArray",Ia);var La=function(t){function e(){t.apply(this,arguments)}t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e;var r={featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0}};return r.featureIndex.get=function(){return this._structArray.uint32[this._pos4+0]},r.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+2]},r.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+3]},Object.defineProperties(e.prototype,r),e}(Ki);La.prototype.size=8;var Pa=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.get=function(t){return new La(this,t)},e}(xa);ii("FeatureIndexArray",Pa);var za=Qi([{name:"a_pos",components:2,type:"Int16"}],4).members,Da=function(t){void 0===t&&(t=[]),this.segments=t};function Oa(t,e){return 256*(t=h(Math.floor(t),0,255))+h(Math.floor(e),0,255)}Da.prototype.prepareSegment=function(t,e,r,n){var i=this.segments[this.segments.length-1];return t>Da.MAX_VERTEX_ARRAY_LENGTH&&k("Max vertices per segment is "+Da.MAX_VERTEX_ARRAY_LENGTH+": bucket requested "+t),(!i||i.vertexLength+t>Da.MAX_VERTEX_ARRAY_LENGTH||i.sortKey!==n)&&(i={vertexOffset:e.length,primitiveOffset:r.length,vertexLength:0,primitiveLength:0},void 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h=o.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,h),o.primitiveLength++),i?this.e2=h:this.e1=h},pl.prototype.updateScaledDistance=function(){this.scaledDistance=this.lineClips?this.lineClips.start+(this.lineClips.end-this.lineClips.start)*this.distance/this.totalDistance:this.distance},pl.prototype.updateDistance=function(t,e){this.distance+=t.dist(e),this.updateScaledDistance()},ii("LineBucket",pl,{omit:["layers","patternFeatures"]});var dl=new Zi({"line-cap":new Vi(Ot.layout_line["line-cap"]),"line-join":new qi(Ot.layout_line["line-join"]),"line-miter-limit":new Vi(Ot.layout_line["line-miter-limit"]),"line-round-limit":new Vi(Ot.layout_line["line-round-limit"]),"line-sort-key":new qi(Ot.layout_line["line-sort-key"])}),ml={paint:new Zi({"line-opacity":new qi(Ot.paint_line["line-opacity"]),"line-color":new qi(Ot.paint_line["line-color"]),"line-translate":new Vi(Ot.paint_line["line-translate"]),"line-translate-anchor":new 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vl=function(t){function e(e){t.call(this,e,ml),this.gradientVersion=0}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype._handleSpecialPaintPropertyUpdate=function(t){if("line-gradient"===t){var e=this._transitionablePaint._values["line-gradient"].value.expression;this.stepInterpolant=e._styleExpression.expression instanceof Qe,this.gradientVersion=(this.gradientVersion+1)%l}},e.prototype.gradientExpression=function(){return this._transitionablePaint._values["line-gradient"].value.expression},e.prototype.recalculate=function(e,r){t.prototype.recalculate.call(this,e,r),this.paint._values["line-floorwidth"]=yl.possiblyEvaluate(this._transitioningPaint._values["line-width"].value,e)},e.prototype.createBucket=function(t){return new pl(t)},e.prototype.queryRadius=function(t){var e=t,r=xl(Lo("line-width",this,e),Lo("line-gap-width",this,e)),n=Lo("line-offset",this,e);return 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t.sections.forEach((function(t){t.text=function(t,e,r){var 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r=(7&t)<<4;e.buf[e.pos++]|=r|((t>>>=3)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t)))))}(n,e)}(t,this):(this.realloc(4),this.buf[this.pos++]=127&t|(t>127?128:0),!(t<=127)&&(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),!(t<=127)&&(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),!(t<=127)&&(this.buf[this.pos++]=t>>>7&127))))},writeSVarint:function(t){this.writeVarint(t<0?2*-t-1:2*t)},writeBoolean:function(t){this.writeVarint(!!t)},writeString:function(t){t=String(t),this.realloc(4*t.length),this.pos++;var e=this.pos;this.pos=function(t,e,r){for(var n,i,a=0;a55295&&n<57344){if(!i){n>56319||a+1===e.length?(t[r++]=239,t[r++]=191,t[r++]=189):i=n;continue}if(n<56320){t[r++]=239,t[r++]=191,t[r++]=189,i=n;continue}n=i-55296<<10|n-56320|65536,i=null}else 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r=0;r=128&&Rl(r,n,this),this.pos=r-1,this.writeVarint(n),this.pos+=n},writeMessage:function(t,e,r){this.writeTag(t,Ll.Bytes),this.writeRawMessage(e,r)},writePackedVarint:function(t,e){e.length&&this.writeMessage(t,Fl,e)},writePackedSVarint:function(t,e){e.length&&this.writeMessage(t,Bl,e)},writePackedBoolean:function(t,e){e.length&&this.writeMessage(t,Ul,e)},writePackedFloat:function(t,e){e.length&&this.writeMessage(t,jl,e)},writePackedDouble:function(t,e){e.length&&this.writeMessage(t,Nl,e)},writePackedFixed32:function(t,e){e.length&&this.writeMessage(t,Vl,e)},writePackedSFixed32:function(t,e){e.length&&this.writeMessage(t,ql,e)},writePackedFixed64:function(t,e){e.length&&this.writeMessage(t,Hl,e)},writePackedSFixed64:function(t,e){e.length&&this.writeMessage(t,Gl,e)},writeBytesField:function(t,e){this.writeTag(t,Ll.Bytes),this.writeBytes(e)},writeFixed32Field:function(t,e){this.writeTag(t,Ll.Fixed32),this.writeFixed32(e)},writeSFixed32Field:function(t,e){this.writeTag(t,Ll.Fixed32),this.writeSFixed32(e)},writeFixed64Field:function(t,e){this.writeTag(t,Ll.Fixed64),this.writeFixed64(e)},writeSFixed64Field:function(t,e){this.writeTag(t,Ll.Fixed64),this.writeSFixed64(e)},writeVarintField:function(t,e){this.writeTag(t,Ll.Varint),this.writeVarint(e)},writeSVarintField:function(t,e){this.writeTag(t,Ll.Varint),this.writeSVarint(e)},writeStringField:function(t,e){this.writeTag(t,Ll.Bytes),this.writeString(e)},writeFloatField:function(t,e){this.writeTag(t,Ll.Fixed32),this.writeFloat(e)},writeDoubleField:function(t,e){this.writeTag(t,Ll.Fixed64),this.writeDouble(e)},writeBooleanField:function(t,e){this.writeVarintField(t,!!e)}};var Ql=function(t,e){var r=e.pixelRatio,n=e.version,i=e.stretchX,a=e.stretchY,o=e.content;this.paddedRect=t,this.pixelRatio=r,this.stretchX=i,this.stretchY=a,this.content=o,this.version=n},tc={tl:{configurable:!0},br:{configurable:!0},tlbr:{configurable:!0},displaySize:{configurable:!0}};tc.tl.get=function(){return[this.paddedRect.x+1,this.paddedRect.y+1]},tc.br.get=function(){return[this.paddedRect.x+this.paddedRect.w-1,this.paddedRect.y+this.paddedRect.h-1]},tc.tlbr.get=function(){return this.tl.concat(this.br)},tc.displaySize.get=function(){return[(this.paddedRect.w-2)/this.pixelRatio,(this.paddedRect.h-2)/this.pixelRatio]},Object.defineProperties(Ql.prototype,tc);var ec=function(t,e){var r={},n={};this.haveRenderCallbacks=[];var i=[];this.addImages(t,r,i),this.addImages(e,n,i);var a=Jl(i),o=a.w,s=a.h,l=new Xo({width:o||1,height:s||1});for(var c in t){var u=t[c],h=r[c].paddedRect;Xo.copy(u.data,l,{x:0,y:0},{x:h.x+1,y:h.y+1},u.data)}for(var f in e){var p=e[f],d=n[f].paddedRect,m=d.x+1,g=d.y+1,y=p.data.width,v=p.data.height;Xo.copy(p.data,l,{x:0,y:0},{x:m,y:g},p.data),Xo.copy(p.data,l,{x:0,y:v-1},{x:m,y:g-1},{width:y,height:1}),Xo.copy(p.data,l,{x:0,y:0},{x:m,y:g+v},{width:y,height:1}),Xo.copy(p.data,l,{x:y-1,y:0},{x:m-1,y:g},{width:1,height:v}),Xo.copy(p.data,l,{x:0,y:0},{x:m+y,y:g},{width:1,height:v})}this.image=l,this.iconPositions=r,this.patternPositions=n};ec.prototype.addImages=function(t,e,r){for(var n in t){var i=t[n],a={x:0,y:0,w:i.data.width+2,h:i.data.height+2};r.push(a),e[n]=new Ql(a,i),i.hasRenderCallback&&this.haveRenderCallbacks.push(n)}},ec.prototype.patchUpdatedImages=function(t,e){for(var r in t.dispatchRenderCallbacks(this.haveRenderCallbacks),t.updatedImages)this.patchUpdatedImage(this.iconPositions[r],t.getImage(r),e),this.patchUpdatedImage(this.patternPositions[r],t.getImage(r),e)},ec.prototype.patchUpdatedImage=function(t,e,r){if(t&&e&&t.version!==e.version){t.version=e.version;var 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S=o.content;x=zc(f,0,S[0]),b=zc(p,0,S[1]),_=zc(f,S[0],S[2]),w=zc(p,S[1],S[3]),T=S[0]-x,A=S[1]-b,k=S[2]-S[0]-_,M=S[3]-S[1]-w}var E=function(n,i,l,c){var f=Oc(n.stretch-x,_,u,t.left),p=Rc(n.fixed-T,k,n.stretch,m),d=Oc(i.stretch-b,w,h,t.top),y=Rc(i.fixed-A,M,i.stretch,g),v=Oc(l.stretch-x,_,u,t.left),S=Rc(l.fixed-T,k,l.stretch,m),E=Oc(c.stretch-b,w,h,t.top),C=Rc(c.fixed-A,M,c.stretch,g),I=new a(f,d),L=new a(v,d),P=new a(v,E),z=new a(f,E),D=new a(p/s,y/s),O=new a(S/s,C/s),R=e*Math.PI/180;if(R){var F=Math.sin(R),B=Math.cos(R),j=[B,-F,F,B];I._matMult(j),L._matMult(j),z._matMult(j),P._matMult(j)}var N=n.stretch+n.fixed,U=l.stretch+l.fixed,V=i.stretch+i.fixed,q=c.stretch+c.fixed;return{tl:I,tr:L,bl:z,br:P,tex:{x:o.paddedRect.x+1+N,y:o.paddedRect.y+1+V,w:U-N,h:q-V},writingMode:void 0,glyphOffset:[0,0],sectionIndex:0,pixelOffsetTL:D,pixelOffsetBR:O,minFontScaleX:k/s/u,minFontScaleY:M/s/h,isSDF:r}};if(n&&(o.stretchX||o.stretchY))for(var C=Dc(f,y,m),I=Dc(p,v,g),L=0;L0&&(d=Math.max(10,d),this.circleDiameter=d)}else{var m=o.top*s-l,g=o.bottom*s+l,y=o.left*s-l,v=o.right*s+l,x=o.collisionPadding;if(x&&(y-=x[0]*s,m-=x[1]*s,v+=x[2]*s,g+=x[3]*s),u){var _=new a(y,m),b=new a(v,m),w=new a(y,g),T=new a(v,g),k=u*Math.PI/180;_._rotate(k),b._rotate(k),w._rotate(k),T._rotate(k),y=Math.min(_.x,b.x,w.x,T.x),v=Math.max(_.x,b.x,w.x,T.x),m=Math.min(_.y,b.y,w.y,T.y),g=Math.max(_.y,b.y,w.y,T.y)}t.emplaceBack(e.x,e.y,y,m,v,g,r,n,i)}this.boxEndIndex=t.length},Bc=function(t,e){if(void 0===t&&(t=[]),void 0===e&&(e=jc),this.data=t,this.length=this.data.length,this.compare=e,this.length>0)for(var r=(this.length>>1)-1;r>=0;r--)this._down(r)};function jc(t,e){return te?1:0}function Nc(t,e,r){void 0===e&&(e=1),void 0===r&&(r=!1);for(var n=1/0,i=1/0,o=-1/0,s=-1/0,l=t[0],c=0;co)&&(o=u.x),(!c||u.y>s)&&(s=u.y)}var h=o-n,f=s-i,p=Math.min(h,f),d=p/2,m=new Bc([],Uc);if(0===p)return new a(n,i);for(var g=n;gv.d||!v.d)&&(v=_,r&&console.log("found best %d 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i=t-1>>1,a=e[i];if(r(n,a)>=0)break;e[t]=a,t=i}e[t]=n},Bc.prototype._down=function(t){for(var e=this.data,r=this.compare,n=this.length>>1,i=e[t];t=0)break;e[t]=o,t=a}e[t]=i};var qc=Number.POSITIVE_INFINITY;function Hc(t,e){return e[1]!==qc?function(t,e,r){var n=0,i=0;switch(e=Math.abs(e),r=Math.abs(r),t){case"top-right":case"top-left":case"top":i=r-7;break;case"bottom-right":case"bottom-left":case"bottom":i=7-r}switch(t){case"top-right":case"bottom-right":case"right":n=-e;break;case"top-left":case"bottom-left":case"left":n=e}return[n,i]}(t,e[0],e[1]):function(t,e){var r=0,n=0;e<0&&(e=0);var i=e/Math.sqrt(2);switch(t){case"top-right":case"top-left":n=i-7;break;case"bottom-right":case"bottom-left":n=7-i;break;case"bottom":n=7-e;break;case"top":n=e-7}switch(t){case"top-right":case"bottom-right":r=-i;break;case"top-left":case"bottom-left":r=i;break;case"left":r=e;break;case"right":r=-e}return[r,n]}(t,e[0])}function 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Reduce your "text-size".'):"composite"===y.kind&&((v=[xc*d.compositeTextSizes[0].evaluate(s,{},m),xc*d.compositeTextSizes[1].evaluate(s,{},m)])[0]>Zc||v[1]>Zc)&&k(t.layerIds[0]+': Value for "text-size" is >= '+Wc+'. Reduce your "text-size".'),t.addSymbols(t.text,g,v,l,o,s,u,e,c.lineStartIndex,c.lineLength,p,m);for(var x=0,_=h;x<_.length;x+=1)f[_[x]]=t.text.placedSymbolArray.length-1;return 4*g.length}function Xc(t){for(var e in t)return t[e];return null}function $c(t,e,r,n){var i=t.compareText;if(e in i){for(var a=i[e],o=a.length-1;o>=0;o--)if(n.dist(a[o])0)&&("constant"!==a.value.kind||a.value.value.length>0),c="constant"!==s.value.kind||!!s.value.value||Object.keys(s.parameters).length>0,u=i.get("symbol-sort-key");if(this.features=[],l||c){for(var h=e.iconDependencies,f=e.glyphDependencies,p=e.availableImages,d=new zi(this.zoom),m=0,g=t;m=0;for(var z=0,D=k.sections;z=0;s--)a[s]={x:e[s].x,y:e[s].y,tileUnitDistanceFromAnchor:i},s>0&&(i+=e[s-1].dist(e[s]));for(var l=0;l0},iu.prototype.hasIconData=function(){return this.icon.segments.get().length>0},iu.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},iu.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},iu.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},iu.prototype.addIndicesForPlacedSymbol=function(t,e){for(var r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs,i=r.vertexStartIndex;i1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var r=0,n=this.symbolInstanceIndexes;r=0&&n.indexOf(t)===r&&e.addIndicesForPlacedSymbol(e.text,t)})),a.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,a.verticalPlacedTextSymbolIndex),a.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.placedIconSymbolIndex),a.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,a.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},ii("SymbolBucket",iu,{omit:["layers","collisionBoxArray","features","compareText"]}),iu.MAX_GLYPHS=65535,iu.addDynamicAttributes=tu;var au=new Zi({"symbol-placement":new Vi(Ot.layout_symbol["symbol-placement"]),"symbol-spacing":new Vi(Ot.layout_symbol["symbol-spacing"]),"symbol-avoid-edges":new Vi(Ot.layout_symbol["symbol-avoid-edges"]),"symbol-sort-key":new qi(Ot.layout_symbol["symbol-sort-key"]),"symbol-z-order":new Vi(Ot.layout_symbol["symbol-z-order"]),"icon-allow-overlap":new Vi(Ot.layout_symbol["icon-allow-overlap"]),"icon-ignore-placement":new Vi(Ot.layout_symbol["icon-ignore-placement"]),"icon-optional":new Vi(Ot.layout_symbol["icon-optional"]),"icon-rotation-alignment":new Vi(Ot.layout_symbol["icon-rotation-alignment"]),"icon-size":new qi(Ot.layout_symbol["icon-size"]),"icon-text-fit":new Vi(Ot.layout_symbol["icon-text-fit"]),"icon-text-fit-padding":new Vi(Ot.layout_symbol["icon-text-fit-padding"]),"icon-image":new qi(Ot.layout_symbol["icon-image"]),"icon-rotate":new qi(Ot.layout_symbol["icon-rotate"]),"icon-padding":new Vi(Ot.layout_symbol["icon-padding"]),"icon-keep-upright":new Vi(Ot.layout_symbol["icon-keep-upright"]),"icon-offset":new qi(Ot.layout_symbol["icon-offset"]),"icon-anchor":new qi(Ot.layout_symbol["icon-anchor"]),"icon-pitch-alignment":new Vi(Ot.layout_symbol["icon-pitch-alignment"]),"text-pitch-alignment":new Vi(Ot.layout_symbol["text-pitch-alignment"]),"text-rotation-alignment":new Vi(Ot.layout_symbol["text-rotation-alignment"]),"text-field":new qi(Ot.layout_symbol["text-field"]),"text-font":new qi(Ot.layout_symbol["text-font"]),"text-size":new qi(Ot.layout_symbol["text-size"]),"text-max-width":new qi(Ot.layout_symbol["text-max-width"]),"text-line-height":new Vi(Ot.layout_symbol["text-line-height"]),"text-letter-spacing":new qi(Ot.layout_symbol["text-letter-spacing"]),"text-justify":new qi(Ot.layout_symbol["text-justify"]),"text-radial-offset":new qi(Ot.layout_symbol["text-radial-offset"]),"text-variable-anchor":new Vi(Ot.layout_symbol["text-variable-anchor"]),"text-anchor":new qi(Ot.layout_symbol["text-anchor"]),"text-max-angle":new Vi(Ot.layout_symbol["text-max-angle"]),"text-writing-mode":new Vi(Ot.layout_symbol["text-writing-mode"]),"text-rotate":new qi(Ot.layout_symbol["text-rotate"]),"text-padding":new Vi(Ot.layout_symbol["text-padding"]),"text-keep-upright":new Vi(Ot.layout_symbol["text-keep-upright"]),"text-transform":new qi(Ot.layout_symbol["text-transform"]),"text-offset":new qi(Ot.layout_symbol["text-offset"]),"text-allow-overlap":new Vi(Ot.layout_symbol["text-allow-overlap"]),"text-ignore-placement":new Vi(Ot.layout_symbol["text-ignore-placement"]),"text-optional":new Vi(Ot.layout_symbol["text-optional"])}),ou=new Zi({"icon-opacity":new qi(Ot.paint_symbol["icon-opacity"]),"icon-color":new qi(Ot.paint_symbol["icon-color"]),"icon-halo-color":new qi(Ot.paint_symbol["icon-halo-color"]),"icon-halo-width":new qi(Ot.paint_symbol["icon-halo-width"]),"icon-halo-blur":new qi(Ot.paint_symbol["icon-halo-blur"]),"icon-translate":new Vi(Ot.paint_symbol["icon-translate"]),"icon-translate-anchor":new Vi(Ot.paint_symbol["icon-translate-anchor"]),"text-opacity":new qi(Ot.paint_symbol["text-opacity"]),"text-color":new qi(Ot.paint_symbol["text-color"],{runtimeType:Zt,getOverride:function(t){return t.textColor},hasOverride:function(t){return!!t.textColor}}),"text-halo-color":new qi(Ot.paint_symbol["text-halo-color"]),"text-halo-width":new qi(Ot.paint_symbol["text-halo-width"]),"text-halo-blur":new qi(Ot.paint_symbol["text-halo-blur"]),"text-translate":new Vi(Ot.paint_symbol["text-translate"]),"text-translate-anchor":new Vi(Ot.paint_symbol["text-translate-anchor"])}),su={paint:ou,layout:au},lu=function(t){this.type=t.property.overrides?t.property.overrides.runtimeType:qt,this.defaultValue=t};lu.prototype.evaluate=function(t){if(t.formattedSection){var e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default},lu.prototype.eachChild=function(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)},lu.prototype.outputDefined=function(){return!1},lu.prototype.serialize=function(){return null},ii("FormatSectionOverride",lu,{omit:["defaultValue"]});var cu=function(t){function e(e){t.call(this,e,su)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.recalculate=function(e,r){if(t.prototype.recalculate.call(this,e,r),"auto"===this.layout.get("icon-rotation-alignment")&&("point"!==this.layout.get("symbol-placement")?this.layout._values["icon-rotation-alignment"]="map":this.layout._values["icon-rotation-alignment"]="viewport"),"auto"===this.layout.get("text-rotation-alignment")&&("point"!==this.layout.get("symbol-placement")?this.layout._values["text-rotation-alignment"]="map":this.layout._values["text-rotation-alignment"]="viewport"),"auto"===this.layout.get("text-pitch-alignment")&&(this.layout._values["text-pitch-alignment"]=this.layout.get("text-rotation-alignment")),"auto"===this.layout.get("icon-pitch-alignment")&&(this.layout._values["icon-pitch-alignment"]=this.layout.get("icon-rotation-alignment")),"point"===this.layout.get("symbol-placement")){var n=this.layout.get("text-writing-mode");if(n){for(var i=[],a=0,o=n;a",targetMapId:n,sourceMapId:a.mapId})}}},Tu.prototype.receive=function(t){var e=t.data,r=e.id;if(r&&(!e.targetMapId||this.mapId===e.targetMapId))if(""===e.type){delete this.tasks[r];var n=this.cancelCallbacks[r];delete this.cancelCallbacks[r],n&&n()}else S()||e.mustQueue?(this.tasks[r]=e,this.taskQueue.push(r),this.invoker.trigger()):this.processTask(r,e)},Tu.prototype.process=function(){if(this.taskQueue.length){var t=this.taskQueue.shift(),e=this.tasks[t];delete this.tasks[t],this.taskQueue.length&&this.invoker.trigger(),e&&this.processTask(t,e)}},Tu.prototype.processTask=function(t,e){var r=this;if(""===e.type){var n=this.callbacks[t];delete this.callbacks[t],n&&(e.error?n(ci(e.error)):n(null,ci(e.data)))}else{var i=!1,a=I(this.globalScope)?void 0:[],o=e.hasCallback?function(e,n){i=!0,delete r.cancelCallbacks[t],r.target.postMessage({id:t,type:"",sourceMapId:r.mapId,error:e?li(e):null,data:li(n,a)},a)}:function(t){i=!0},s=null,l=ci(e.data);if(this.parent[e.type])s=this.parent[e.type](e.sourceMapId,l,o);else if(this.parent.getWorkerSource){var c=e.type.split(".");s=this.parent.getWorkerSource(e.sourceMapId,c[0],l.source)[c[1]](l,o)}else o(new Error("Could not find function "+e.type));!i&&s&&s.cancel&&(this.cancelCallbacks[t]=s.cancel)}},Tu.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener("message",this.receive,!1)};var Au=function(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1]))};Au.prototype.setNorthEast=function(t){return this._ne=t instanceof Su?new Su(t.lng,t.lat):Su.convert(t),this},Au.prototype.setSouthWest=function(t){return this._sw=t instanceof Su?new Su(t.lng,t.lat):Su.convert(t),this},Au.prototype.extend=function(t){var e,r,n=this._sw,i=this._ne;if(t instanceof Su)e=t,r=t;else{if(!(t instanceof Au)){if(Array.isArray(t)){if(4===t.length||t.every(Array.isArray)){var a=t;return this.extend(Au.convert(a))}var o=t;return this.extend(Su.convert(o))}return this}if(e=t._sw,r=t._ne,!e||!r)return this}return n||i?(n.lng=Math.min(e.lng,n.lng),n.lat=Math.min(e.lat,n.lat),i.lng=Math.max(r.lng,i.lng),i.lat=Math.max(r.lat,i.lat)):(this._sw=new Su(e.lng,e.lat),this._ne=new Su(r.lng,r.lat)),this},Au.prototype.getCenter=function(){return new Su((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Au.prototype.getSouthWest=function(){return this._sw},Au.prototype.getNorthEast=function(){return this._ne},Au.prototype.getNorthWest=function(){return new Su(this.getWest(),this.getNorth())},Au.prototype.getSouthEast=function(){return new Su(this.getEast(),this.getSouth())},Au.prototype.getWest=function(){return this._sw.lng},Au.prototype.getSouth=function(){return this._sw.lat},Au.prototype.getEast=function(){return this._ne.lng},Au.prototype.getNorth=function(){return this._ne.lat},Au.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Au.prototype.toString=function(){return"LngLatBounds("+this._sw.toString()+", "+this._ne.toString()+")"},Au.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Au.prototype.contains=function(t){var e=Su.convert(t),r=e.lng,n=e.lat,i=this._sw.lat<=n&&n<=this._ne.lat,a=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(a=this._sw.lng>=r&&r>=this._ne.lng),i&&a},Au.convert=function(t){return!t||t instanceof Au?t:new Au(t)};var Mu=6371008.8,Su=function(t,e){if(isNaN(t)||isNaN(e))throw new Error("Invalid LngLat object: ("+t+", "+e+")");if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error("Invalid LngLat latitude value: must be between -90 and 90")};Su.prototype.wrap=function(){return new Su(f(this.lng,-180,180),this.lat)},Su.prototype.toArray=function(){return[this.lng,this.lat]},Su.prototype.toString=function(){return"LngLat("+this.lng+", "+this.lat+")"},Su.prototype.distanceTo=function(t){var e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return Mu*Math.acos(Math.min(i,1))},Su.prototype.toBounds=function(t){void 0===t&&(t=0);var e=360*t/40075017,r=e/Math.cos(Math.PI/180*this.lat);return new Au(new Su(this.lng-r,this.lat-e),new Su(this.lng+r,this.lat+e))},Su.convert=function(t){if(t instanceof Su)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Su(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&"object"==typeof t&&null!==t)return new Su(Number("lng"in t?t.lng:t.lon),Number(t.lat));throw new Error("`LngLatLike` argument must be specified as a LngLat instance, an object {lng: , lat: }, an object {lon: , lat: }, or an array of [, ]")};var Eu=2*Math.PI*Mu;function Cu(t){return Eu*Math.cos(t*Math.PI/180)}function Iu(t){return(180+t)/360}function Lu(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Pu(t,e){return t/Cu(e)}function zu(t){var e=180-360*t;return 360/Math.PI*Math.atan(Math.exp(e*Math.PI/180))-90}var Du=function(t,e,r){void 0===r&&(r=0),this.x=+t,this.y=+e,this.z=+r};Du.fromLngLat=function(t,e){void 0===e&&(e=0);var r=Su.convert(t);return new Du(Iu(r.lng),Lu(r.lat),Pu(e,r.lat))},Du.prototype.toLngLat=function(){return new Su(function(t){return 360*t-180}(this.x),zu(this.y))},Du.prototype.toAltitude=function(){return function(t,e){return t*Cu(zu(e))}(this.z,this.y)},Du.prototype.meterInMercatorCoordinateUnits=function(){return 1/Eu*function(t){return 1/Math.cos(t*Math.PI/180)}(zu(this.y))};var Ou=function(t,e,r){this.z=t,this.x=e,this.y=r,this.key=Bu(0,t,t,e,r)};Ou.prototype.equals=function(t){return this.z===t.z&&this.x===t.x&&this.y===t.y},Ou.prototype.url=function(t,e){var r=function(t,e,r){var n=ku(256*t,256*(e=Math.pow(2,r)-e-1),r),i=ku(256*(t+1),256*(e+1),r);return n[0]+","+n[1]+","+i[0]+","+i[1]}(this.x,this.y,this.z),n=function(t,e,r){for(var n,i="",a=t;a>0;a--)i+=(e&(n=1<this.canonical.z?new Fu(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new Fu(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)},Fu.prototype.calculateScaledKey=function(t,e){var r=this.canonical.z-t;return t>this.canonical.z?Bu(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):Bu(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)},Fu.prototype.isChildOf=function(t){if(t.wrap!==this.wrap)return!1;var e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ>e&&t.canonical.y===this.canonical.y>>e},Fu.prototype.children=function(t){if(this.overscaledZ>=t)return[new Fu(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new Fu(e,this.wrap,e,r,n),new Fu(e,this.wrap,e,r+1,n),new Fu(e,this.wrap,e,r,n+1),new Fu(e,this.wrap,e,r+1,n+1)]},Fu.prototype.isLessThan=function(t){return this.wrapt.wrap)&&(this.overscaledZt.overscaledZ)&&(this.canonical.xt.canonical.x)&&this.canonical.y=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError("out of range source coordinates for DEM data");return(e+1)*this.stride+(t+1)},ju.prototype._unpackMapbox=function(t,e,r){return(256*t*256+256*e+r)/10-1e4},ju.prototype._unpackTerrarium=function(t,e,r){return 256*t+e+r/256-32768},ju.prototype.getPixels=function(){return new Xo({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},ju.prototype.backfillBorder=function(t,e,r){if(this.dim!==t.dim)throw new Error("dem dimension mismatch");var n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}for(var s=-e*this.dim,l=-r*this.dim,c=a;c=0&&u[3]>=0&&s.insert(o,u[0],u[1],u[2],u[3])}},Hu.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new Ks.VectorTile(new Il(this.rawTileData)).layers,this.sourceLayerCoder=new Nu(this.vtLayers?Object.keys(this.vtLayers).sort():["_geojsonTileLayer"])),this.vtLayers},Hu.prototype.query=function(t,e,r,n){var i=this;this.loadVTLayers();for(var o=t.params||{},s=fo/t.tileSize/t.scale,l=Tn(o.filter),c=t.queryGeometry,u=t.queryPadding*s,h=Wu(c),f=this.grid.query(h.minX-u,h.minY-u,h.maxX+u,h.maxY+u),p=Wu(t.cameraQueryGeometry),d=this.grid3D.query(p.minX-u,p.minY-u,p.maxX+u,p.maxY+u,(function(e,r,n,i){return function(t,e,r,n,i){for(var o=0,s=t;o=l.x&&i>=l.y)return!0}var c=[new a(e,r),new a(e,i),new a(n,i),new a(n,r)];if(t.length>2)for(var u=0,h=c;u=0)return!0;return!1}(a,h)){var f=this.sourceLayerCoder.decode(r),d=this.vtLayers[f].feature(n);if(i.needGeometry){var m=yo(d,!0);if(!i.filter(new zi(this.tileID.overscaledZ),m,this.tileID.canonical))return}else if(!i.filter(new zi(this.tileID.overscaledZ),d))return;for(var g=this.getId(d,f),y=0;yn)i=!1;else if(e)if(this.expirationTimeft&&(t.getActor().send("enforceCacheSizeLimit",ht),gt=0)},t.clamp=h,t.clearTileCache=function(t){var e=s.caches.delete(ut);t&&e.catch(t).then((function(){return t()}))},t.clipLine=Lc,t.clone=function(t){var e=new Ro(16);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e[3]=t[3],e[4]=t[4],e[5]=t[5],e[6]=t[6],e[7]=t[7],e[8]=t[8],e[9]=t[9],e[10]=t[10],e[11]=t[11],e[12]=t[12],e[13]=t[13],e[14]=t[14],e[15]=t[15],e},t.clone$1=w,t.clone$2=function(t){var e=new Ro(3);return e[0]=t[0],e[1]=t[1],e[2]=t[2],e},t.collisionCircleLayout=kl,t.config=N,t.create=function(){var t=new Ro(16);return Ro!=Float32Array&&(t[1]=0,t[2]=0,t[3]=0,t[4]=0,t[6]=0,t[7]=0,t[8]=0,t[9]=0,t[11]=0,t[12]=0,t[13]=0,t[14]=0),t[0]=1,t[5]=1,t[10]=1,t[15]=1,t},t.create$1=function(){var t=new Ro(9);return 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Il(t).readFields(Xl,[])},t.pbf=Il,t.performSymbolLayout=function(t,e,r,n,i,a,o){t.createArrays();var s=512*t.overscaling;t.tilePixelRatio=fo/s,t.compareText={},t.iconsNeedLinear=!1;var l=t.layers[0].layout,c=t.layers[0]._unevaluatedLayout._values,u={};if("composite"===t.textSizeData.kind){var h=t.textSizeData,f=h.minZoom,p=h.maxZoom;u.compositeTextSizes=[c["text-size"].possiblyEvaluate(new zi(f),o),c["text-size"].possiblyEvaluate(new zi(p),o)]}if("composite"===t.iconSizeData.kind){var d=t.iconSizeData,m=d.minZoom,g=d.maxZoom;u.compositeIconSizes=[c["icon-size"].possiblyEvaluate(new zi(m),o),c["icon-size"].possiblyEvaluate(new zi(g),o)]}u.layoutTextSize=c["text-size"].possiblyEvaluate(new zi(t.zoom+1),o),u.layoutIconSize=c["icon-size"].possiblyEvaluate(new zi(t.zoom+1),o),u.textMaxSize=c["text-size"].possiblyEvaluate(new zi(18));for(var 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if("MultiLineString"===f)pt(h,m,r,n,i,!1);else if("Polygon"===f)pt(h,m,r,n,i,!0);else if("MultiPolygon"===f)for(var g=0;g=r&&o<=n&&(e.push(t[a]),e.push(t[a+1]),e.push(t[a+2]))}}function ht(t,e,r,n,i,a,o){for(var s,l,c=ft(t),u=0===i?mt:gt,h=t.start,f=0;fr&&(l=u(c,p,d,g,y,r),o&&(c.start=h+s*l)):v>n?x=r&&(l=u(c,p,d,g,y,r),_=!0),x>n&&v<=n&&(l=u(c,p,d,g,y,n),_=!0),!a&&_&&(o&&(c.end=h+s*l),e.push(c),c=ft(t)),o&&(h+=s)}var b=t.length-3;p=t[b],d=t[b+1],m=t[b+2],(v=0===i?p:d)>=r&&v<=n&&dt(c,p,d,m),b=c.length-3,a&&b>=3&&(c[b]!==c[0]||c[b+1]!==c[1])&&dt(c,c[0],c[1],c[2]),c.length&&e.push(c)}function ft(t){var e=[];return e.size=t.size,e.start=t.start,e.end=t.end,e}function pt(t,e,r,n,i,a){for(var o=0;oo.maxX&&(o.maxX=u),h>o.maxY&&(o.maxY=h)}return o}function wt(t,e,r,n){var i=e.geometry,a=e.type,o=[];if("Point"===a||"MultiPoint"===a)for(var s=0;s0&&e.size<(i?o:n))r.numPoints+=e.length/3;else{for(var s=[],l=0;lo)&&(r.numSimplified++,s.push(e[l]),s.push(e[l+1])),r.numPoints++;i&&function(t,e){for(var r=0,n=0,i=t.length,a=i-2;n0===e)for(n=0,i=t.length;n24)throw new Error("maxZoom should be in the 0-24 range");if(e.promoteId&&e.generateId)throw new Error("promoteId and generateId cannot be used together.");var n=function(t,e){var r=[];if("FeatureCollection"===t.type)for(var n=0;n=n;c--){var u=+Date.now();s=this._cluster(s,c),this.trees[c]=new j(s,K,J,a,Float32Array),r&&console.log("z%d: %d clusters in %dms",c,s.length,+Date.now()-u)}return r&&console.timeEnd("total time"),this},U.prototype.getClusters=function(t,e){var r=((t[0]+180)%360+360)%360-180,n=Math.max(-90,Math.min(90,t[1])),i=180===t[2]?180:((t[2]+180)%360+360)%360-180,a=Math.max(-90,Math.min(90,t[3]));if(t[2]-t[0]>=360)r=-180,i=180;else if(r>i){var o=this.getClusters([r,n,180,a],e),s=this.getClusters([-180,n,i,a],e);return o.concat(s)}for(var l=this.trees[this._limitZoom(e)],c=[],u=0,h=l.range(W(r),Z(a),W(i),Z(n));ue&&(d+=v.numPoints||1)}if(d>=s){for(var x=u.x*p,_=u.y*p,b=o&&p>1?this._map(u,!0):null,w=(c<<5)+(e+1)+this.points.length,T=0,k=f;T1)for(var E=0,C=f;E>5},U.prototype._getOriginZoom=function(t){return(t-this.points.length)%32},U.prototype._map=function(t,e){if(t.numPoints)return e?$({},t.properties):t.properties;var r=this.points[t.index].properties,n=this.options.map(r);return e&&n===r?$({},n):n},kt.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},kt.prototype.splitTile=function(t,e,r,n,i,a,o){for(var s=[t,e,r,n],l=this.options,c=l.debug;s.length;){n=s.pop(),r=s.pop(),e=s.pop(),t=s.pop();var u=1<1&&console.time("creation"),f=this.tiles[h]=bt(t,e,r,n,l),this.tileCoords.push({z:e,x:r,y:n}),c)){c>1&&(console.log("tile z%d-%d-%d (features: %d, points: %d, simplified: %d)",e,r,n,f.numFeatures,f.numPoints,f.numSimplified),console.timeEnd("creation"));var p="z"+e;this.stats[p]=(this.stats[p]||0)+1,this.total++}if(f.source=t,i){if(e===l.maxZoom||e===i)continue;var d=1<1&&console.time("clipping");var m,g,y,v,x,_,b=.5*l.buffer/l.extent,w=.5-b,T=.5+b,k=1+b;m=g=y=v=null,x=ct(t,u,r-b,r+T,0,f.minX,f.maxX,l),_=ct(t,u,r+w,r+k,0,f.minX,f.maxX,l),t=null,x&&(m=ct(x,u,n-b,n+T,1,f.minY,f.maxY,l),g=ct(x,u,n+w,n+k,1,f.minY,f.maxY,l),x=null),_&&(y=ct(_,u,n-b,n+T,1,f.minY,f.maxY,l),v=ct(_,u,n+w,n+k,1,f.minY,f.maxY,l),_=null),c>1&&console.timeEnd("clipping"),s.push(m||[],e+1,2*r,2*n),s.push(g||[],e+1,2*r,2*n+1),s.push(y||[],e+1,2*r+1,2*n),s.push(v||[],e+1,2*r+1,2*n+1)}}},kt.prototype.getTile=function(t,e,r){var n=this.options,i=n.extent,a=n.debug;if(t<0||t>24)return null;var o=1<1&&console.log("drilling down to z%d-%d-%d",t,e,r);for(var l,c=t,u=e,h=r;!l&&c>0;)c--,u=Math.floor(u/2),h=Math.floor(h/2),l=this.tiles[At(c,u,h)];return l&&l.source?(a>1&&console.log("found parent tile z%d-%d-%d",c,u,h),a>1&&console.time("drilling down"),this.splitTile(l.source,c,u,h,t,e,r),a>1&&console.timeEnd("drilling down"),this.tiles[s]?xt(this.tiles[s],i):null):null};var St=function(e){function r(t,r,n,i){e.call(this,t,r,n,Mt),i&&(this.loadGeoJSON=i)}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.loadData=function(t,e){this._pendingCallback&&this._pendingCallback(null,{abandoned:!0}),this._pendingCallback=e,this._pendingLoadDataParams=t,this._state&&"Idle"!==this._state?this._state="NeedsLoadData":(this._state="Coalescing",this._loadData())},r.prototype._loadData=function(){var e=this;if(this._pendingCallback&&this._pendingLoadDataParams){var r=this._pendingCallback,n=this._pendingLoadDataParams;delete this._pendingCallback,delete this._pendingLoadDataParams;var i=!!(n&&n.request&&n.request.collectResourceTiming)&&new t.RequestPerformance(n.request);this.loadGeoJSON(n,(function(a,o){if(a||!o)return r(a);if("object"!=typeof o)return r(new Error("Input data given to '"+n.source+"' is not a valid GeoJSON object."));h(o,!0);try{if(n.filter){var s=t.createExpression(n.filter,{type:"boolean","property-type":"data-driven",overridable:!1,transition:!1});if("error"===s.result)throw new Error(s.value.map((function(t){return t.key+": "+t.message})).join(", "));var l=o.features.filter((function(t){return s.value.evaluate({zoom:0},t)}));o={type:"FeatureCollection",features:l}}e._geoJSONIndex=n.cluster?new U(function(e){var r=e.superclusterOptions,n=e.clusterProperties;if(!n||!r)return r;for(var i={},a={},o={accumulated:null,zoom:0},s={properties:null},l=Object.keys(n),c=0,u=l;c=0?0:e.button},r.remove=function(t){t.parentNode&&t.parentNode.removeChild(t)};var f=function(e){function r(){e.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new t.RGBAImage({width:1,height:1}),this.dirty=!0}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.isLoaded=function(){return this.loaded},r.prototype.setLoaded=function(t){if(this.loaded!==t&&(this.loaded=t,t)){for(var e=0,r=this.requestors;e=0?1.2:1))}function y(t,e,r,n,i,a,o){for(var s=0;s65535)e(new Error("glyphs > 65535 not supported"));else if(a.ranges[s])e(null,{stack:r,id:i,glyph:o});else{var l=a.requests[s];l||(l=a.requests[s]=[],x.loadGlyphRange(r,s,n.url,n.requestManager,(function(t,e){if(e){for(var r in e)n._doesCharSupportLocalGlyph(+r)||(a.glyphs[+r]=e[+r]);a.ranges[s]=!0}for(var i=0,o=l;i1&&(l=t[++s]);var u=Math.abs(c-l.left),h=Math.abs(c-l.right),f=Math.min(u,h),p=void 0,d=i/r*(n+1);if(l.isDash){var m=n-Math.abs(d);p=Math.sqrt(f*f+m*m)}else p=n-Math.sqrt(f*f+d*d);this.data[o+c]=Math.max(0,Math.min(255,p+128))}},T.prototype.addRegularDash=function(t){for(var e=t.length-1;e>=0;--e){var r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}var i=t[0],a=t[t.length-1];i.isDash===a.isDash&&(i.left=a.left-this.width,a.right=i.right+this.width);for(var o=this.width*this.nextRow,s=0,l=t[s],c=0;c1&&(l=t[++s]);var u=Math.abs(c-l.left),h=Math.abs(c-l.right),f=Math.min(u,h),p=l.isDash?f:-f;this.data[o+c]=Math.max(0,Math.min(255,p+128))}},T.prototype.addDash=function(e,r){var n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return t.warnOnce("LineAtlas out of space"),null;for(var a=0,o=0;o=n&&e.x=i&&e.y0&&(l[new t.OverscaledTileID(e.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,e.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new t.OverscaledTileID(e.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+10&&(n.resourceTiming=e._resourceTiming,e._resourceTiming=[]),e.fire(new t.Event("data",n))}}))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setData=function(e){var r=this;return this._data=e,this.fire(new t.Event("dataloading",{dataType:"source"})),this._updateWorkerData((function(e){if(e)r.fire(new t.ErrorEvent(e));else{var n={dataType:"source",sourceDataType:"content"};r._collectResourceTiming&&r._resourceTiming&&r._resourceTiming.length>0&&(n.resourceTiming=r._resourceTiming,r._resourceTiming=[]),r.fire(new t.Event("data",n))}})),this},r.prototype.getClusterExpansionZoom=function(t,e){return this.actor.send("geojson.getClusterExpansionZoom",{clusterId:t,source:this.id},e),this},r.prototype.getClusterChildren=function(t,e){return this.actor.send("geojson.getClusterChildren",{clusterId:t,source:this.id},e),this},r.prototype.getClusterLeaves=function(t,e,r,n){return this.actor.send("geojson.getClusterLeaves",{source:this.id,clusterId:t,limit:e,offset:r},n),this},r.prototype._updateWorkerData=function(e){var r=this;this._loaded=!1;var n=t.extend({},this.workerOptions),i=this._data;"string"==typeof i?(n.request=this.map._requestManager.transformRequest(t.browser.resolveURL(i),t.ResourceType.Source),n.request.collectResourceTiming=this._collectResourceTiming):n.data=JSON.stringify(i),this.actor.send(this.type+".loadData",n,(function(t,i){r._removed||i&&i.abandoned||(r._loaded=!0,i&&i.resourceTiming&&i.resourceTiming[r.id]&&(r._resourceTiming=i.resourceTiming[r.id].slice(0)),r.actor.send(r.type+".coalesce",{source:n.source},null),e(t))}))},r.prototype.loaded=function(){return this._loaded},r.prototype.loadTile=function(e,r){var n=this,i=e.actor?"reloadTile":"loadTile";e.actor=this.actor;var a={type:this.type,uid:e.uid,tileID:e.tileID,zoom:e.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:t.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};e.request=this.actor.send(i,a,(function(t,a){return delete e.request,e.unloadVectorData(),e.aborted?r(null):t?r(t):(e.loadVectorData(a,n.map.painter,"reloadTile"===i),r(null))}))},r.prototype.abortTile=function(t){t.request&&(t.request.cancel(),delete t.request),t.aborted=!0},r.prototype.unloadTile=function(t){t.unloadVectorData(),this.actor.send("removeTile",{uid:t.uid,type:this.type,source:this.id})},r.prototype.onRemove=function(){this._removed=!0,this.actor.send("removeSource",{type:this.type,source:this.id})},r.prototype.serialize=function(){return t.extend({},this._options,{type:this.type,data:this._data})},r.prototype.hasTransition=function(){return!1},r}(t.Evented),L=t.createLayout([{name:"a_pos",type:"Int16",components:2},{name:"a_texture_pos",type:"Int16",components:2}]),P=function(e){function r(t,r,n,i){e.call(this),this.id=t,this.dispatcher=n,this.coordinates=r.coordinates,this.type="image",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(i),this.options=r}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(e,r){var n=this;this._loaded=!1,this.fire(new t.Event("dataloading",{dataType:"source"})),this.url=this.options.url,t.getImage(this.map._requestManager.transformRequest(this.url,t.ResourceType.Image),(function(i,a){n._loaded=!0,i?n.fire(new t.ErrorEvent(i)):a&&(n.image=a,e&&(n.coordinates=e),r&&r(),n._finishLoading())}))},r.prototype.loaded=function(){return this._loaded},r.prototype.updateImage=function(t){var e=this;return this.image&&t.url?(this.options.url=t.url,this.load(t.coordinates,(function(){e.texture=null})),this):this},r.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.Event("data",{dataType:"source",sourceDataType:"metadata"})))},r.prototype.onAdd=function(t){this.map=t,this.load()},r.prototype.setCoordinates=function(e){var r=this;this.coordinates=e;var n=e.map(t.MercatorCoordinate.fromLngLat);this.tileID=function(e){for(var r=1/0,n=1/0,i=-1/0,a=-1/0,o=0,s=e;or.end(0)?this.fire(new t.ErrorEvent(new t.ValidationError("sources."+this.id,null,"Playback for this video can be set only between the "+r.start(0)+" and "+r.end(0)+"-second mark."))):this.video.currentTime=e}},r.prototype.getVideo=function(){return this.video},r.prototype.onAdd=function(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},r.prototype.prepare=function(){if(!(0===Object.keys(this.tiles).length||this.video.readyState<2)){var e=this.map.painter.context,r=e.gl;for(var n in this.boundsBuffer||(this.boundsBuffer=e.createVertexBuffer(this._boundsArray,L.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new t.Texture(e,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE)),this.tiles){var i=this.tiles[n];"loaded"!==i.state&&(i.state="loaded",i.texture=this.texture)}}},r.prototype.serialize=function(){return{type:"video",urls:this.urls,coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this.video&&!this.video.paused},r}(P),D=function(e){function r(r,n,i,a){e.call(this,r,n,i,a),n.coordinates?(!Array.isArray(n.coordinates)||4!==n.coordinates.length||n.coordinates.some((function(t){return!Array.isArray(t)||2!==t.length||t.some((function(t){return"number"!=typeof t}))})))&&this.fire(new t.ErrorEvent(new t.ValidationError("sources."+r,null,'"coordinates" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.ErrorEvent(new t.ValidationError("sources."+r,null,'missing required property "coordinates"'))),n.animate&&"boolean"!=typeof n.animate&&this.fire(new t.ErrorEvent(new t.ValidationError("sources."+r,null,'optional "animate" property must be a boolean value'))),n.canvas?"string"!=typeof n.canvas&&!(n.canvas instanceof t.window.HTMLCanvasElement)&&this.fire(new t.ErrorEvent(new t.ValidationError("sources."+r,null,'"canvas" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.ErrorEvent(new t.ValidationError("sources."+r,null,'missing required property "canvas"'))),this.options=n,this.animate=void 0===n.animate||n.animate}return e&&(r.__proto__=e),r.prototype=Object.create(e&&e.prototype),r.prototype.constructor=r,r.prototype.load=function(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof t.window.HTMLCanvasElement?this.options.canvas:t.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.ErrorEvent(new Error("Canvas dimensions cannot be less than or equal to zero."))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())},r.prototype.getCanvas=function(){return this.canvas},r.prototype.onAdd=function(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()},r.prototype.onRemove=function(){this.pause()},r.prototype.prepare=function(){var e=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,e=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,e=!0),!this._hasInvalidDimensions()&&0!==Object.keys(this.tiles).length){var r=this.map.painter.context,n=r.gl;for(var i in this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,L.members)),this.boundsSegments||(this.boundsSegments=t.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(e||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new t.Texture(r,this.canvas,n.RGBA,{premultiply:!0}),this.tiles){var a=this.tiles[i];"loaded"!==a.state&&(a.state="loaded",a.texture=this.texture)}}},r.prototype.serialize=function(){return{type:"canvas",coordinates:this.coordinates}},r.prototype.hasTransition=function(){return this._playing},r.prototype._hasInvalidDimensions=function(){for(var t=0,e=[this.canvas.width,this.canvas.height];tthis.max){var o=this._getAndRemoveByKey(this.order[0]);o&&this.onRemove(o)}return this},j.prototype.has=function(t){return t.wrapped().key in this.data},j.prototype.getAndRemove=function(t){return this.has(t)?this._getAndRemoveByKey(t.wrapped().key):null},j.prototype._getAndRemoveByKey=function(t){var e=this.data[t].shift();return e.timeout&&clearTimeout(e.timeout),0===this.data[t].length&&delete this.data[t],this.order.splice(this.order.indexOf(t),1),e.value},j.prototype.getByKey=function(t){var e=this.data[t];return e?e[0].value:null},j.prototype.get=function(t){return this.has(t)?this.data[t.wrapped().key][0].value:null},j.prototype.remove=function(t,e){if(!this.has(t))return this;var r=t.wrapped().key,n=void 0===e?0:this.data[r].indexOf(e),i=this.data[r][n];return this.data[r].splice(n,1),i.timeout&&clearTimeout(i.timeout),0===this.data[r].length&&delete this.data[r],this.onRemove(i.value),this.order.splice(this.order.indexOf(r),1),this},j.prototype.setMaxSize=function(t){for(this.max=t;this.order.length>this.max;){var e=this._getAndRemoveByKey(this.order[0]);e&&this.onRemove(e)}return this},j.prototype.filter=function(t){var e=[];for(var r in this.data)for(var n=0,i=this.data[r];n1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}},r.prototype.getTile=function(t){return this.getTileByID(t.key)},r.prototype.getTileByID=function(t){return this._tiles[t]},r.prototype._retainLoadedChildren=function(t,e,r,n){for(var i in this._tiles){var a=this._tiles[i];if(!(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)){for(var o=a.tileID;a&&a.tileID.overscaledZ>e+1;){var s=a.tileID.scaledTo(a.tileID.overscaledZ-1);(a=this._tiles[s.key])&&a.hasData()&&(o=s)}for(var l=o;l.overscaledZ>e;)if(t[(l=l.scaledTo(l.overscaledZ-1)).key]){n[o.key]=o;break}}}},r.prototype.findLoadedParent=function(t,e){if(t.key in this._loadedParentTiles){var r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(var n=t.overscaledZ-1;n>=e;n--){var i=t.scaledTo(n),a=this._getLoadedTile(i);if(a)return a}},r.prototype._getLoadedTile=function(t){var e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)},r.prototype.updateCacheSize=function(t){var e=(Math.ceil(t.width/this._source.tileSize)+1)*(Math.ceil(t.height/this._source.tileSize)+1),r=Math.floor(5*e),n="number"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,r):r;this._cache.setMaxSize(n)},r.prototype.handleWrapJump=function(t){var e=(t-(void 0===this._prevLng?t:this._prevLng))/360,r=Math.round(e);if(this._prevLng=t,r){var n={};for(var i in this._tiles){var a=this._tiles[i];a.tileID=a.tileID.unwrapTo(a.tileID.wrap+r),n[a.tileID.key]=a}for(var o in this._tiles=n,this._timers)clearTimeout(this._timers[o]),delete this._timers[o];for(var s in this._tiles){var l=this._tiles[s];this._setTileReloadTimer(s,l)}}},r.prototype.update=function(e){var n=this;if(this.transform=e,this._sourceLoaded&&!this._paused){var i;this.updateCacheSize(e),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used?this._source.tileID?i=e.getVisibleUnwrappedCoordinates(this._source.tileID).map((function(e){return new t.OverscaledTileID(e.canonical.z,e.wrap,e.canonical.z,e.canonical.x,e.canonical.y)})):(i=e.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(i=i.filter((function(t){return n._source.hasTile(t)})))):i=[];var a=e.coveringZoomLevel(this._source),o=Math.max(a-r.maxOverzooming,this._source.minzoom),s=Math.max(a+r.maxUnderzooming,this._source.minzoom),l=this._updateRetainedTiles(i,a);if(zt(this._source.type)){for(var c={},u={},h=0,f=Object.keys(l);hthis._source.maxzoom){var g=d.children(this._source.maxzoom)[0],y=this.getTile(g);if(y&&y.hasData()){n[g.key]=g;continue}}else{var v=d.children(this._source.maxzoom);if(n[v[0].key]&&n[v[1].key]&&n[v[2].key]&&n[v[3].key])continue}for(var x=m.wasRequested(),_=d.overscaledZ-1;_>=a;--_){var b=d.scaledTo(_);if(i[b.key]||(i[b.key]=!0,!(m=this.getTile(b))&&x&&(m=this._addTile(b)),m&&(n[b.key]=b,x=m.wasRequested(),m.hasData())))break}}}return n},r.prototype._updateLoadedParentTileCache=function(){for(var t in this._loadedParentTiles={},this._tiles){for(var e=[],r=void 0,n=this._tiles[t].tileID;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){r=this._loadedParentTiles[n.key];break}e.push(n.key);var i=n.scaledTo(n.overscaledZ-1);if(r=this._getLoadedTile(i))break;n=i}for(var a=0,o=e;a0)&&(e.hasData()&&"reloading"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))},r.prototype.clearTiles=function(){for(var t in this._shouldReloadOnResume=!1,this._paused=!1,this._tiles)this._removeTile(t);this._cache.reset()},r.prototype.tilesIn=function(e,r,n){var i=this,a=[],o=this.transform;if(!o)return a;for(var s=n?o.getCameraQueryGeometry(e):e,l=e.map((function(t){return o.pointCoordinate(t)})),c=s.map((function(t){return o.pointCoordinate(t)})),u=this.getIds(),h=1/0,f=1/0,p=-1/0,d=-1/0,m=0,g=c;m=0&&y[1].y+g>=0){var v=l.map((function(t){return s.getTilePoint(t)})),x=c.map((function(t){return s.getTilePoint(t)}));a.push({tile:n,tileID:s,queryGeometry:v,cameraQueryGeometry:x,scale:m})}}},x=0;x=t.browser.now())return!0}return!1},r.prototype.setFeatureState=function(t,e,r){t=t||"_geojsonTileLayer",this._state.updateState(t,e,r)},r.prototype.removeFeatureState=function(t,e,r){t=t||"_geojsonTileLayer",this._state.removeFeatureState(t,e,r)},r.prototype.getFeatureState=function(t,e){return t=t||"_geojsonTileLayer",this._state.getState(t,e)},r.prototype.setDependencies=function(t,e,r){var n=this._tiles[t];n&&n.setDependencies(e,r)},r.prototype.reloadTilesForDependencies=function(t,e){for(var r in this._tiles)this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,"reloading");this._cache.filter((function(r){return!r.hasDependency(t,e)}))},r}(t.Evented);function Pt(t,e){var r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function zt(t){return"raster"===t||"image"===t||"video"===t}function Dt(){return new t.window.Worker(na.workerUrl)}Lt.maxOverzooming=10,Lt.maxUnderzooming=3;var Ot="mapboxgl_preloaded_worker_pool",Rt=function(){this.active={}};Rt.prototype.acquire=function(t){if(!this.workers)for(this.workers=[];this.workers.length0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))};var Kt=function(t,e,r){var n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(var a=0;a=-e[0]&&r<=e[0]&&n>=-e[1]&&n<=e[1]}function ne(e,r,n,i,a,o,s,l){var c=i?e.textSizeData:e.iconSizeData,u=t.evaluateSizeForZoom(c,n.transform.zoom),h=[256/n.width*2+1,256/n.height*2+1],f=i?e.text.dynamicLayoutVertexArray:e.icon.dynamicLayoutVertexArray;f.clear();for(var p=e.lineVertexArray,d=i?e.text.placedSymbolArray:e.icon.placedSymbolArray,m=n.transform.width/n.transform.height,g=!1,y=0;yMath.abs(n.x-r.x)*i?{useVertical:!0}:(e===t.WritingMode.vertical?r.yn.x)?{needsFlipping:!0}:null}function oe(e,r,n,i,a,o,s,l,c,u,h,f,p,d){var m,g=r/24,y=e.lineOffsetX*g,v=e.lineOffsetY*g;if(e.numGlyphs>1){var x=e.glyphStartIndex+e.numGlyphs,_=e.lineStartIndex,b=e.lineStartIndex+e.lineLength,w=ie(g,l,y,v,n,h,f,e,c,o,p);if(!w)return{notEnoughRoom:!0};var T=te(w.first.point,s).point,k=te(w.last.point,s).point;if(i&&!n){var A=ae(e.writingMode,T,k,d);if(A)return A}m=[w.first];for(var M=e.glyphStartIndex+1;M0?I.point:se(f,C,S,1,a),P=ae(e.writingMode,S,L,d);if(P)return P}var z=le(g*l.getoffsetX(e.glyphStartIndex),y,v,n,h,f,e.segment,e.lineStartIndex,e.lineStartIndex+e.lineLength,c,o,p);if(!z)return{notEnoughRoom:!0};m=[z]}for(var D=0,O=m;D0?1:-1,m=0;i&&(d*=-1,m=Math.PI),d<0&&(m+=Math.PI);for(var g=d>0?l+s:l+s+1,y=a,v=a,x=0,_=0,b=Math.abs(p),w=[];x+_<=b;){if((g+=d)=c)return null;if(v=y,w.push(y),void 0===(y=f[g])){var T=new t.Point(u.getx(g),u.gety(g)),k=te(T,h);if(k.signedDistanceFromCamera>0)y=f[g]=k.point;else{var A=g-d;y=se(0===x?o:new t.Point(u.getx(A),u.gety(A)),T,v,b-x+1,h)}}x+=_,_=v.dist(y)}var M=(b-x)/_,S=y.sub(v),E=S.mult(M)._add(v);E._add(S._unit()._perp()._mult(n*d));var C=m+Math.atan2(y.y-v.y,y.x-v.x);return w.push(E),{point:E,angle:C,path:w}}Kt.prototype.keysLength=function(){return this.boxKeys.length+this.circleKeys.length},Kt.prototype.insert=function(t,e,r,n,i){this._forEachCell(e,r,n,i,this._insertBoxCell,this.boxUid++),this.boxKeys.push(t),this.bboxes.push(e),this.bboxes.push(r),this.bboxes.push(n),this.bboxes.push(i)},Kt.prototype.insertCircle=function(t,e,r,n){this._forEachCell(e-n,r-n,e+n,r+n,this._insertCircleCell,this.circleUid++),this.circleKeys.push(t),this.circles.push(e),this.circles.push(r),this.circles.push(n)},Kt.prototype._insertBoxCell=function(t,e,r,n,i,a){this.boxCells[i].push(a)},Kt.prototype._insertCircleCell=function(t,e,r,n,i,a){this.circleCells[i].push(a)},Kt.prototype._query=function(t,e,r,n,i,a){if(r<0||t>this.width||n<0||e>this.height)return!i&&[];var o=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return!0;for(var s=0;s0:o},Kt.prototype._queryCircle=function(t,e,r,n,i){var a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!n&&[];var c=[],u={hitTest:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}};return this._forEachCell(a,s,o,l,this._queryCellCircle,c,u,i),n?c.length>0:c},Kt.prototype.query=function(t,e,r,n,i){return this._query(t,e,r,n,!1,i)},Kt.prototype.hitTest=function(t,e,r,n,i){return this._query(t,e,r,n,!0,i)},Kt.prototype.hitTestCircle=function(t,e,r,n){return this._queryCircle(t,e,r,!0,n)},Kt.prototype._queryCell=function(t,e,r,n,i,a,o,s){var l=o.seenUids,c=this.boxCells[i];if(null!==c)for(var u=this.bboxes,h=0,f=c;h=u[d+0]&&n>=u[d+1]&&(!s||s(this.boxKeys[p]))){if(o.hitTest)return a.push(!0),!0;a.push({key:this.boxKeys[p],x1:u[d],y1:u[d+1],x2:u[d+2],y2:u[d+3]})}}}var m=this.circleCells[i];if(null!==m)for(var g=this.circles,y=0,v=m;yo*o+s*s},Kt.prototype._circleAndRectCollide=function(t,e,r,n,i,a,o){var s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;var c=(o-i)/2,u=Math.abs(e-(i+c));if(u>c+r)return!1;if(l<=s||u<=c)return!0;var h=l-s,f=u-c;return h*h+f*f<=r*r};var ce=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function ue(t,e){for(var r=0;r=1;L--)I.push(E.path[L]);for(var P=1;P0){for(var R=I[0].clone(),F=I[0].clone(),B=1;B=A.x&&F.x<=M.x&&R.y>=A.y&&F.y<=M.y?[I]:F.xM.x||F.yM.y?[]:t.clipLine([I],A.x,A.y,M.x,M.y)}for(var j=0,N=O;j=this.screenRightBoundary||nthis.screenBottomBoundary},pe.prototype.isInsideGrid=function(t,e,r,n){return r>=0&&t=0&&e0?(this.prevPlacement&&this.prevPlacement.variableOffsets[h.crossTileID]&&this.prevPlacement.placements[h.crossTileID]&&this.prevPlacement.placements[h.crossTileID].text&&(m=this.prevPlacement.variableOffsets[h.crossTileID].anchor),this.variableOffsets[h.crossTileID]={textOffset:g,width:r,height:n,anchor:t,textBoxScale:i,prevAnchor:m},this.markUsedJustification(f,t,h,p),f.allowVerticalPlacement&&(this.markUsedOrientation(f,p,h),this.placedOrientations[h.crossTileID]=p),{shift:y,placedGlyphBoxes:v}):void 0},Te.prototype.placeLayerBucketPart=function(e,r,n){var i=this,a=e.parameters,o=a.bucket,s=a.layout,l=a.posMatrix,c=a.textLabelPlaneMatrix,u=a.labelToScreenMatrix,h=a.textPixelRatio,f=a.holdingForFade,p=a.collisionBoxArray,d=a.partiallyEvaluatedTextSize,m=a.collisionGroup,g=s.get("text-optional"),y=s.get("icon-optional"),v=s.get("text-allow-overlap"),x=s.get("icon-allow-overlap"),_="map"===s.get("text-rotation-alignment"),b="map"===s.get("text-pitch-alignment"),w="none"!==s.get("icon-text-fit"),T="viewport-y"===s.get("symbol-z-order"),k=v&&(x||!o.hasIconData()||y),A=x&&(v||!o.hasTextData()||g);!o.collisionArrays&&p&&o.deserializeCollisionBoxes(p);var M=function(e,a){if(!r[e.crossTileID]){if(f)return void(i.placements[e.crossTileID]=new ye(!1,!1,!1));var p,T=!1,M=!1,S=!0,E=null,C={box:null,offscreen:null},I={box:null,offscreen:null},L=null,P=null,z=0,D=0,O=0;a.textFeatureIndex?z=a.textFeatureIndex:e.useRuntimeCollisionCircles&&(z=e.featureIndex),a.verticalTextFeatureIndex&&(D=a.verticalTextFeatureIndex);var R=a.textBox;if(R){var F=function(r){var n=t.WritingMode.horizontal;if(o.allowVerticalPlacement&&!r&&i.prevPlacement){var a=i.prevPlacement.placedOrientations[e.crossTileID];a&&(i.placedOrientations[e.crossTileID]=a,n=a,i.markUsedOrientation(o,n,e))}return n},B=function(r,n){if(o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&a.verticalTextBox)for(var i=0,s=o.writingModes;i0&&(j=j.filter((function(t){return t!==N.anchor}))).unshift(N.anchor)}var U=function(t,r,n){for(var a=t.x2-t.x1,s=t.y2-t.y1,c=e.textBoxScale,u=w&&!x?r:null,f={box:[],offscreen:!1},p=v?2*j.length:j.length,d=0;d=j.length,k=i.attemptAnchorPlacement(g,t,a,s,c,_,b,h,l,m,y,e,o,n,u);if(k&&(f=k.placedGlyphBoxes)&&f.box&&f.box.length){T=!0,E=k.shift;break}}return f};B((function(){return U(R,a.iconBox,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox,n=C&&C.box&&C.box.length;return o.allowVerticalPlacement&&!n&&e.numVerticalGlyphVertices>0&&r?U(r,a.verticalIconBox,t.WritingMode.vertical):{box:null,offscreen:null}})),C&&(T=C.box,S=C.offscreen);var V=F(C&&C.box);if(!T&&i.prevPlacement){var q=i.prevPlacement.variableOffsets[e.crossTileID];q&&(i.variableOffsets[e.crossTileID]=q,i.markUsedJustification(o,q.anchor,e,V))}}else{var H=function(t,r){var n=i.collisionIndex.placeCollisionBox(t,v,h,l,m.predicate);return n&&n.box&&n.box.length&&(i.markUsedOrientation(o,r,e),i.placedOrientations[e.crossTileID]=r),n};B((function(){return H(R,t.WritingMode.horizontal)}),(function(){var r=a.verticalTextBox;return o.allowVerticalPlacement&&e.numVerticalGlyphVertices>0&&r?H(r,t.WritingMode.vertical):{box:null,offscreen:null}})),F(C&&C.box&&C.box.length)}}if(T=(p=C)&&p.box&&p.box.length>0,S=p&&p.offscreen,e.useRuntimeCollisionCircles){var G=o.text.placedSymbolArray.get(e.centerJustifiedTextSymbolIndex),W=t.evaluateSizeForFeature(o.textSizeData,d,G),Z=s.get("text-padding"),Y=e.collisionCircleDiameter;L=i.collisionIndex.placeCollisionCircles(v,G,o.lineVertexArray,o.glyphOffsetArray,W,l,c,u,n,b,m.predicate,Y,Z),T=v||L.circles.length>0&&!L.collisionDetected,S=S&&L.offscreen}if(a.iconFeatureIndex&&(O=a.iconFeatureIndex),a.iconBox){var X=function(t){var e=w&&E?we(t,E.x,E.y,_,b,i.transform.angle):t;return i.collisionIndex.placeCollisionBox(e,x,h,l,m.predicate)};M=I&&I.box&&I.box.length&&a.verticalIconBox?(P=X(a.verticalIconBox)).box.length>0:(P=X(a.iconBox)).box.length>0,S=S&&P.offscreen}var $=g||0===e.numHorizontalGlyphVertices&&0===e.numVerticalGlyphVertices,K=y||0===e.numIconVertices;if($||K?K?$||(M=M&&T):T=M&&T:M=T=M&&T,T&&p&&p.box&&(I&&I.box&&D?i.collisionIndex.insertCollisionBox(p.box,s.get("text-ignore-placement"),o.bucketInstanceId,D,m.ID):i.collisionIndex.insertCollisionBox(p.box,s.get("text-ignore-placement"),o.bucketInstanceId,z,m.ID)),M&&P&&i.collisionIndex.insertCollisionBox(P.box,s.get("icon-ignore-placement"),o.bucketInstanceId,O,m.ID),L&&(T&&i.collisionIndex.insertCollisionCircles(L.circles,s.get("text-ignore-placement"),o.bucketInstanceId,z,m.ID),n)){var J=o.bucketInstanceId,Q=i.collisionCircleArrays[J];void 0===Q&&(Q=i.collisionCircleArrays[J]=new ve);for(var tt=0;tt=0;--E){var C=S[E];M(o.symbolInstances.get(C),o.collisionArrays[C])}else for(var I=e.symbolInstanceStart;I=0&&(e.text.placedSymbolArray.get(c).crossTileID=a>=0&&c!==a?0:n.crossTileID)}},Te.prototype.markUsedOrientation=function(e,r,n){for(var i=r===t.WritingMode.horizontal||r===t.WritingMode.horizontalOnly?r:0,a=r===t.WritingMode.vertical?r:0,o=0,s=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];o0||l>0,x=a.numIconVertices>0,_=i.placedOrientations[a.crossTileID],b=_===t.WritingMode.vertical,w=_===t.WritingMode.horizontal||_===t.WritingMode.horizontalOnly;if(v){var T=Pe(y.text),k=b?ze:T;d(e.text,s,k);var A=w?ze:T;d(e.text,l,A);var M=y.text.isHidden();[a.rightJustifiedTextSymbolIndex,a.centerJustifiedTextSymbolIndex,a.leftJustifiedTextSymbolIndex].forEach((function(t){t>=0&&(e.text.placedSymbolArray.get(t).hidden=M||b?1:0)})),a.verticalPlacedTextSymbolIndex>=0&&(e.text.placedSymbolArray.get(a.verticalPlacedTextSymbolIndex).hidden=M||w?1:0);var S=i.variableOffsets[a.crossTileID];S&&i.markUsedJustification(e,S.anchor,a,_);var E=i.placedOrientations[a.crossTileID];E&&(i.markUsedJustification(e,"left",a,E),i.markUsedOrientation(e,E,a))}if(x){var C=Pe(y.icon),I=!(f&&a.verticalPlacedIconSymbolIndex&&b);if(a.placedIconSymbolIndex>=0){var L=I?C:ze;d(e.icon,a.numIconVertices,L),e.icon.placedSymbolArray.get(a.placedIconSymbolIndex).hidden=y.icon.isHidden()}if(a.verticalPlacedIconSymbolIndex>=0){var P=I?ze:C;d(e.icon,a.numVerticalIconVertices,P),e.icon.placedSymbolArray.get(a.verticalPlacedIconSymbolIndex).hidden=y.icon.isHidden()}}if(e.hasIconCollisionBoxData()||e.hasTextCollisionBoxData()){var z=e.collisionArrays[n];if(z){var D=new t.Point(0,0);if(z.textBox||z.verticalTextBox){var O=!0;if(c){var R=i.variableOffsets[m];R?(D=be(R.anchor,R.width,R.height,R.textOffset,R.textBoxScale),u&&D._rotate(h?i.transform.angle:-i.transform.angle)):O=!1}z.textBox&&ke(e.textCollisionBox.collisionVertexArray,y.text.placed,!O||b,D.x,D.y),z.verticalTextBox&&ke(e.textCollisionBox.collisionVertexArray,y.text.placed,!O||w,D.x,D.y)}var F=!(w||!z.verticalIconBox);z.iconBox&&ke(e.iconCollisionBox.collisionVertexArray,y.icon.placed,F,f?D.x:0,f?D.y:0),z.verticalIconBox&&ke(e.iconCollisionBox.collisionVertexArray,y.icon.placed,!F,f?D.x:0,f?D.y:0)}}},g=0;gt},Te.prototype.setStale=function(){this.stale=!0};var Ae=Math.pow(2,25),Me=Math.pow(2,24),Se=Math.pow(2,17),Ee=Math.pow(2,16),Ce=Math.pow(2,9),Ie=Math.pow(2,8),Le=Math.pow(2,1);function Pe(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;var e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*Ae+e*Me+r*Se+e*Ee+r*Ce+e*Ie+r*Le+e}var ze=0,De=function(t){this._sortAcrossTiles="viewport-y"!==t.layout.get("symbol-z-order")&&void 0!==t.layout.get("symbol-sort-key").constantOr(1),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};De.prototype.continuePlacement=function(t,e,r,n,i){for(var a=this._bucketParts;this._currentTileIndex2};this._currentPlacementIndex>=0;){var s=r[e[this._currentPlacementIndex]],l=this.placement.collisionIndex.transform.zoom;if("symbol"===s.type&&(!s.minzoom||s.minzoom<=l)&&(!s.maxzoom||s.maxzoom>l)){if(this._inProgressLayer||(this._inProgressLayer=new De(s)),this._inProgressLayer.continuePlacement(n[s.source],this.placement,this._showCollisionBoxes,s,o))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},Oe.prototype.commit=function(t){return this.placement.commit(t),this.placement};var Re=512/t.EXTENT/2,Fe=function(t,e,r){this.tileID=t,this.indexedSymbolInstances={},this.bucketInstanceId=r;for(var n=0;nt.overscaledZ)for(var s in o){var l=o[s];l.tileID.isChildOf(t)&&l.findMatches(e.symbolInstances,t,i)}else{var c=o[t.scaledTo(Number(a)).key];c&&c.findMatches(e.symbolInstances,t,i)}}for(var u=0;u1?"@2x":"",l=t.getJSON(r.transformRequest(r.normalizeSpriteURL(e,s,".json"),t.ResourceType.SpriteJSON),(function(t,e){l=null,o||(o=t,i=e,u())})),c=t.getImage(r.transformRequest(r.normalizeSpriteURL(e,s,".png"),t.ResourceType.SpriteImage),(function(t,e){c=null,o||(o=t,a=e,u())}));function u(){if(o)n(o);else if(i&&a){var e=t.browser.getImageData(a),r={};for(var s in i){var l=i[s],c=l.width,u=l.height,h=l.x,f=l.y,p=l.sdf,d=l.pixelRatio,m=l.stretchX,g=l.stretchY,y=l.content,v=new t.RGBAImage({width:c,height:u});t.RGBAImage.copy(e,v,{x:h,y:f},{x:0,y:0},{width:c,height:u}),r[s]={data:v,pixelRatio:d,sdf:p,stretchX:m,stretchY:g,content:y}}n(null,r)}}return{cancel:function(){l&&(l.cancel(),l=null),c&&(c.cancel(),c=null)}}}(e,this.map._requestManager,(function(e,n){if(r._spriteRequest=null,e)r.fire(new t.ErrorEvent(e));else if(n)for(var i in n)r.imageManager.addImage(i,n[i]);r.imageManager.setLoaded(!0),r._availableImages=r.imageManager.listImages(),r.dispatcher.broadcast("setImages",r._availableImages),r.fire(new t.Event("data",{dataType:"style"}))}))},r.prototype._validateLayer=function(e){var r=this.sourceCaches[e.source];if(r){var n=e.sourceLayer;if(n){var i=r.getSource();("geojson"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new t.ErrorEvent(new Error('Source layer "'+n+'" does not exist on source "'+i.id+'" as specified by style layer "'+e.id+'"')))}}},r.prototype.loaded=function(){if(!this._loaded||Object.keys(this._updatedSources).length)return!1;for(var t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()},r.prototype._serializeLayers=function(t){for(var e=[],r=0,n=t;r0)throw new Error("Unimplemented: "+i.map((function(t){return t.command})).join(", ")+".");return n.forEach((function(t){"setTransition"!==t.command&&r[t.command].apply(r,t.args)})),this.stylesheet=e,!0},r.prototype.addImage=function(e,r){if(this.getImage(e))return this.fire(new t.ErrorEvent(new Error("An image with this name already exists.")));this.imageManager.addImage(e,r),this._afterImageUpdated(e)},r.prototype.updateImage=function(t,e){this.imageManager.updateImage(t,e)},r.prototype.getImage=function(t){return this.imageManager.getImage(t)},r.prototype.removeImage=function(e){if(!this.getImage(e))return this.fire(new t.ErrorEvent(new Error("No image with this name exists.")));this.imageManager.removeImage(e),this._afterImageUpdated(e)},r.prototype._afterImageUpdated=function(e){this._availableImages=this.imageManager.listImages(),this._changedImages[e]=!0,this._changed=!0,this.dispatcher.broadcast("setImages",this._availableImages),this.fire(new t.Event("data",{dataType:"style"}))},r.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},r.prototype.addSource=function(e,r,n){var i=this;if(void 0===n&&(n={}),this._checkLoaded(),void 0!==this.sourceCaches[e])throw new Error("There is already a source with this ID");if(!r.type)throw new Error("The type property must be defined, but only the following properties were given: "+Object.keys(r).join(", ")+".");if(!(["vector","raster","geojson","video","image"].indexOf(r.type)>=0&&this._validate(t.validateStyle.source,"sources."+e,r,null,n))){this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);var a=this.sourceCaches[e]=new Lt(e,r,this.dispatcher);a.style=this,a.setEventedParent(this,(function(){return{isSourceLoaded:i.loaded(),source:a.serialize(),sourceId:e}})),a.onAdd(this.map),this._changed=!0}},r.prototype.removeSource=function(e){if(this._checkLoaded(),void 0===this.sourceCaches[e])throw new Error("There is no source with this ID");for(var r in this._layers)if(this._layers[r].source===e)return this.fire(new t.ErrorEvent(new Error('Source "'+e+'" cannot be removed while layer "'+r+'" is using it.')));var n=this.sourceCaches[e];delete this.sourceCaches[e],delete this._updatedSources[e],n.fire(new t.Event("data",{sourceDataType:"metadata",dataType:"source",sourceId:e})),n.setEventedParent(null),n.clearTiles(),n.onRemove&&n.onRemove(this.map),this._changed=!0},r.prototype.setGeoJSONSourceData=function(t,e){this._checkLoaded(),this.sourceCaches[t].getSource().setData(e),this._changed=!0},r.prototype.getSource=function(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()},r.prototype.addLayer=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=e.id;if(this.getLayer(i))this.fire(new t.ErrorEvent(new Error('Layer with id "'+i+'" already exists on this map')));else{var a;if("custom"===e.type){if(Ue(this,t.validateCustomStyleLayer(e)))return;a=t.createStyleLayer(e)}else{if("object"==typeof e.source&&(this.addSource(i,e.source),e=t.clone$1(e),e=t.extend(e,{source:i})),this._validate(t.validateStyle.layer,"layers."+i,e,{arrayIndex:-1},n))return;a=t.createStyleLayer(e),this._validateLayer(a),a.setEventedParent(this,{layer:{id:i}}),this._serializedLayers[a.id]=a.serialize()}var o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new t.ErrorEvent(new Error('Layer with id "'+r+'" does not exist on this map.')));else{if(this._order.splice(o,0,i),this._layerOrderChanged=!0,this._layers[i]=a,this._removedLayers[i]&&a.source&&"custom"!==a.type){var s=this._removedLayers[i];delete this._removedLayers[i],s.type!==a.type?this._updatedSources[a.source]="clear":(this._updatedSources[a.source]="reload",this.sourceCaches[a.source].pause())}this._updateLayer(a),a.onAdd&&a.onAdd(this.map)}}},r.prototype.moveLayer=function(e,r){if(this._checkLoaded(),this._changed=!0,this._layers[e]){if(e!==r){var n=this._order.indexOf(e);this._order.splice(n,1);var i=r?this._order.indexOf(r):this._order.length;if(r&&-1===i)return void this.fire(new t.ErrorEvent(new Error('Layer with id "'+r+'" does not exist on this map.')));this._order.splice(i,0,e),this._layerOrderChanged=!0}}else this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot be moved.")))},r.prototype.removeLayer=function(e){this._checkLoaded();var r=this._layers[e];if(r){r.setEventedParent(null);var n=this._order.indexOf(e);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[e]=r,delete this._layers[e],delete this._serializedLayers[e],delete this._updatedLayers[e],delete this._updatedPaintProps[e],r.onRemove&&r.onRemove(this.map)}else this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot be removed.")))},r.prototype.getLayer=function(t){return this._layers[t]},r.prototype.hasLayer=function(t){return t in this._layers},r.prototype.setLayerZoomRange=function(e,r,n){this._checkLoaded();var i=this.getLayer(e);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot have zoom extent.")))},r.prototype.setFilter=function(e,r,n){void 0===n&&(n={}),this._checkLoaded();var i=this.getLayer(e);if(i){if(!t.deepEqual(i.filter,r)){if(null==r)return i.filter=void 0,void this._updateLayer(i);this._validate(t.validateStyle.filter,"layers."+i.id+".filter",r,null,n)||(i.filter=t.clone$1(r),this._updateLayer(i))}}else this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot be filtered.")))},r.prototype.getFilter=function(e){return t.clone$1(this.getLayer(e).filter)},r.prototype.setLayoutProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot be styled.")))},r.prototype.getLayoutProperty=function(e,r){var n=this.getLayer(e);if(n)return n.getLayoutProperty(r);this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style.")))},r.prototype.setPaintProperty=function(e,r,n,i){void 0===i&&(i={}),this._checkLoaded();var a=this.getLayer(e);a?t.deepEqual(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[e]=!0):this.fire(new t.ErrorEvent(new Error("The layer '"+e+"' does not exist in the map's style and cannot be styled.")))},r.prototype.getPaintProperty=function(t,e){return this.getLayer(t).getPaintProperty(e)},r.prototype.setFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=e.sourceLayer,a=this.sourceCaches[n];if(void 0!==a){var o=a.getSource().type;"geojson"===o&&i?this.fire(new t.ErrorEvent(new Error("GeoJSON sources cannot have a sourceLayer parameter."))):"vector"!==o||i?(void 0===e.id&&this.fire(new t.ErrorEvent(new Error("The feature id parameter must be provided."))),a.setFeatureState(i,e.id,r)):this.fire(new t.ErrorEvent(new Error("The sourceLayer parameter must be provided for vector source types.")))}else this.fire(new t.ErrorEvent(new Error("The source '"+n+"' does not exist in the map's style.")))},r.prototype.removeFeatureState=function(e,r){this._checkLoaded();var n=e.source,i=this.sourceCaches[n];if(void 0!==i){var a=i.getSource().type,o="vector"===a?e.sourceLayer:void 0;"vector"!==a||o?r&&"string"!=typeof e.id&&"number"!=typeof e.id?this.fire(new t.ErrorEvent(new Error("A feature id is required to remove its specific state property."))):i.removeFeatureState(o,e.id,r):this.fire(new t.ErrorEvent(new Error("The sourceLayer parameter must be provided for vector source types.")))}else this.fire(new t.ErrorEvent(new Error("The source '"+n+"' does not exist in the map's style.")))},r.prototype.getFeatureState=function(e){this._checkLoaded();var r=e.source,n=e.sourceLayer,i=this.sourceCaches[r];if(void 0!==i){if("vector"!==i.getSource().type||n)return void 0===e.id&&this.fire(new t.ErrorEvent(new Error("The feature id parameter must be provided."))),i.getFeatureState(n,e.id);this.fire(new t.ErrorEvent(new Error("The sourceLayer parameter must be provided for vector source types.")))}else this.fire(new t.ErrorEvent(new Error("The source '"+r+"' does not exist in the map's style.")))},r.prototype.getTransition=function(){return t.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},r.prototype.serialize=function(){return t.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:t.mapObject(this.sourceCaches,(function(t){return t.serialize()})),layers:this._serializeLayers(this._order)},(function(t){return void 0!==t}))},r.prototype._updateLayer=function(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&"raster"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]="reload",this.sourceCaches[t.source].pause()),this._changed=!0},r.prototype._flattenAndSortRenderedFeatures=function(t){for(var e=this,r=function(t){return"fill-extrusion"===e._layers[t].type},n={},i=[],a=this._order.length-1;a>=0;a--){var o=this._order[a];if(r(o)){n[o]=a;for(var s=0,l=t;s=0;d--){var m=this._order[d];if(r(m))for(var g=i.length-1;g>=0;g--){var y=i[g].feature;if(n[y.layer.id] 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}","attribute vec2 a_pos;attribute vec2 a_anchor_pos;attribute vec2 a_extrude;attribute vec2 a_placed;attribute vec2 a_shift;uniform mat4 u_matrix;uniform vec2 u_extrude_scale;uniform float u_camera_to_center_distance;varying float v_placed;varying float v_notUsed;void main() {vec4 projectedPoint=u_matrix*vec4(a_anchor_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);gl_Position=u_matrix*vec4(a_pos,0.0,1.0);gl_Position.xy+=(a_extrude+a_shift)*u_extrude_scale*gl_Position.w*collision_perspective_ratio;v_placed=a_placed.x;v_notUsed=a_placed.y;}"),er=xr("varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}","attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}"),rr=xr("uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}","attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,0,1);}"),nr=xr("#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float opacity\ngl_FragColor=color*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","attribute vec2 a_pos;uniform mat4 u_matrix;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float opacity\ngl_Position=u_matrix*vec4(a_pos,0,1);}"),ir=xr("varying vec2 v_pos;\n#pragma mapbox: define highp vec4 outline_color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 outline_color\n#pragma mapbox: initialize lowp float opacity\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\n#pragma mapbox: define highp vec4 outline_color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 outline_color\n#pragma mapbox: initialize lowp float opacity\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}"),ar=xr("uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}"),or=xr("uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}"),sr=xr("varying vec4 v_color;void main() {gl_FragColor=v_color;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec4 v_color;\n#pragma mapbox: define highp float base\n#pragma mapbox: define highp float height\n#pragma mapbox: define highp vec4 color\nvoid main() {\n#pragma mapbox: initialize highp float base\n#pragma mapbox: initialize highp float height\n#pragma mapbox: initialize highp vec4 color\nvec3 normal=a_normal_ed.xyz;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}"),lr=xr("uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\n#pragma mapbox: define lowp float base\n#pragma mapbox: define lowp float height\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float base\n#pragma mapbox: initialize lowp float height\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\n#pragma mapbox: define lowp float base\n#pragma mapbox: define lowp float height\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float base\n#pragma mapbox: initialize lowp float height\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\n? a_pos\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}"),cr=xr("#ifdef GL_ES\nprecision highp float;\n#endif\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggerationFactor=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;float exaggeration=u_zoom < 15.0 ? (u_zoom-15.0)*exaggerationFactor : 0.0;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/pow(2.0,exaggeration+(19.2562-u_zoom));gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}"),ur=xr("uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\n#define PI 3.141592653589793\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}"),hr=xr("uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define scale 0.015873016\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float width\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float width\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}"),fr=xr("uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp vec2 v_uv;\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,v_uv);gl_FragColor=color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define scale 0.015873016\nattribute vec2 a_pos_normal;attribute vec4 a_data;attribute float a_uv_x;attribute float a_split_index;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;uniform float u_image_height;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp vec2 v_uv;\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float width\nvoid main() {\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float width\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;highp float texel_height=1.0/u_image_height;highp float half_texel_height=0.5*texel_height;v_uv=vec2(a_uv_x,a_split_index*texel_height-half_texel_height);vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}"),pr=xr("uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define scale 0.015873016\n#define LINE_DISTANCE_SCALE 2.0\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define mediump float width\n#pragma mapbox: define lowp float floorwidth\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize mediump float width\n#pragma mapbox: initialize lowp float floorwidth\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}"),dr=xr("uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float width\n#pragma mapbox: define lowp float floorwidth\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float width\n#pragma mapbox: initialize lowp float floorwidth\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define scale 0.015873016\n#define LINE_DISTANCE_SCALE 2.0\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float width\n#pragma mapbox: define lowp float floorwidth\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float width\n#pragma mapbox: initialize lowp float floorwidth\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}"),mr=xr("uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}"),gr=xr("uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity;\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\ncamera_to_anchor_distance/u_camera_to_center_distance :\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}"),yr=xr("#define SDF_PX 8.0\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1;\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\ncamera_to_anchor_distance/u_camera_to_center_distance :\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}"),vr=xr("#define SDF_PX 8.0\n#define SDF 1.0\n#define ICON 0.0\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1;\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\ncamera_to_anchor_distance/u_camera_to_center_distance :\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}");function xr(t,e){var r=/#pragma mapbox: ([\w]+) ([\w]+) ([\w]+) ([\w]+)/g,n=e.match(/attribute ([\w]+) ([\w]+)/g),i=t.match(/uniform ([\w]+) ([\w]+)([\s]*)([\w]*)/g),a=e.match(/uniform ([\w]+) ([\w]+)([\s]*)([\w]*)/g),o=a?a.concat(i):i,s={};return{fragmentSource:t=t.replace(r,(function(t,e,r,n,i){return s[i]=!0,"define"===e?"\n#ifndef HAS_UNIFORM_u_"+i+"\nvarying "+r+" "+n+" "+i+";\n#else\nuniform "+r+" "+n+" u_"+i+";\n#endif\n":"\n#ifdef HAS_UNIFORM_u_"+i+"\n "+r+" "+n+" "+i+" = u_"+i+";\n#endif\n"})),vertexSource:e=e.replace(r,(function(t,e,r,n,i){var a="float"===n?"vec2":"vec4",o=i.match(/color/)?"color":a;return s[i]?"define"===e?"\n#ifndef HAS_UNIFORM_u_"+i+"\nuniform lowp float u_"+i+"_t;\nattribute "+r+" "+a+" a_"+i+";\nvarying "+r+" "+n+" "+i+";\n#else\nuniform "+r+" "+n+" u_"+i+";\n#endif\n":"vec4"===o?"\n#ifndef HAS_UNIFORM_u_"+i+"\n "+i+" = a_"+i+";\n#else\n "+r+" "+n+" "+i+" = u_"+i+";\n#endif\n":"\n#ifndef HAS_UNIFORM_u_"+i+"\n "+i+" = unpack_mix_"+o+"(a_"+i+", u_"+i+"_t);\n#else\n "+r+" "+n+" "+i+" = u_"+i+";\n#endif\n":"define"===e?"\n#ifndef HAS_UNIFORM_u_"+i+"\nuniform lowp float u_"+i+"_t;\nattribute "+r+" "+a+" a_"+i+";\n#else\nuniform "+r+" "+n+" u_"+i+";\n#endif\n":"vec4"===o?"\n#ifndef HAS_UNIFORM_u_"+i+"\n "+r+" "+n+" "+i+" = a_"+i+";\n#else\n "+r+" "+n+" "+i+" = u_"+i+";\n#endif\n":"\n#ifndef HAS_UNIFORM_u_"+i+"\n "+r+" "+n+" "+i+" = unpack_mix_"+o+"(a_"+i+", u_"+i+"_t);\n#else\n "+r+" "+n+" "+i+" = u_"+i+";\n#endif\n"})),staticAttributes:n,staticUniforms:o}}var _r=Object.freeze({__proto__:null,prelude:Ze,background:Ye,backgroundPattern:Xe,circle:$e,clippingMask:Ke,heatmap:Je,heatmapTexture:Qe,collisionBox:tr,collisionCircle:er,debug:rr,fill:nr,fillOutline:ir,fillOutlinePattern:ar,fillPattern:or,fillExtrusion:sr,fillExtrusionPattern:lr,hillshadePrepare:cr,hillshade:ur,line:hr,lineGradient:fr,linePattern:pr,lineSDF:dr,raster:mr,symbolIcon:gr,symbolSDF:yr,symbolTextAndIcon:vr}),br=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};function wr(t){for(var e=[],r=0;r>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}Tr.prototype.draw=function(t,e,r,n,i,a,o,s,l,c,u,h,f,p,d,m){var g,y=t.gl;if(!this.failedToCreate){for(var v in t.program.set(this.program),t.setDepthMode(r),t.setStencilMode(n),t.setColorMode(i),t.setCullFace(a),this.fixedUniforms)this.fixedUniforms[v].set(o[v]);p&&p.setUniforms(t,this.binderUniforms,h,{zoom:f});for(var x=(g={},g[y.LINES]=2,g[y.TRIANGLES]=3,g[y.LINE_STRIP]=1,g)[e],_=0,b=u.get();_0?1/(1-t):1+t}function Zr(t){return t>0?1-1/(1.001-t):-t}var Yr,Xr=function(t,e,r,n,i,a,o,s,l,c){var u=i.transform;return{u_is_size_zoom_constant:+("constant"===t||"source"===t),u_is_size_feature_constant:+("constant"===t||"camera"===t),u_size_t:e?e.uSizeT:0,u_size:e?e.uSize:0,u_camera_to_center_distance:u.cameraToCenterDistance,u_pitch:u.pitch/360*2*Math.PI,u_rotate_symbol:+r,u_aspect_ratio:u.width/u.height,u_fade_change:i.options.fadeDuration?i.symbolFadeChange:1,u_matrix:a,u_label_plane_matrix:o,u_coord_matrix:s,u_is_text:+l,u_pitch_with_map:+n,u_texsize:c,u_texture:0}},$r=function(e,r,n,i,a,o,s,l,c,u,h){var f=a.transform;return t.extend(Xr(e,r,n,i,a,o,s,l,c,u),{u_gamma_scale:i?Math.cos(f._pitch)*f.cameraToCenterDistance:1,u_device_pixel_ratio:t.browser.devicePixelRatio,u_is_halo:+h})},Kr=function(e,r,n,i,a,o,s,l,c,u){return t.extend($r(e,r,n,i,a,o,s,l,!0,c,!0),{u_texsize_icon:u,u_texture_icon:1})},Jr=function(t,e,r){return{u_matrix:t,u_opacity:e,u_color:r}},Qr=function(e,r,n,i,a,o){return t.extend(function(t,e,r,n){var i=r.imageManager.getPattern(t.from.toString()),a=r.imageManager.getPattern(t.to.toString()),o=r.imageManager.getPixelSize(),s=o.width,l=o.height,c=Math.pow(2,n.tileID.overscaledZ),u=n.tileSize*Math.pow(2,r.transform.tileZoom)/c,h=u*(n.tileID.canonical.x+n.tileID.wrap*c),f=u*n.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:i.tl,u_pattern_br_a:i.br,u_pattern_tl_b:a.tl,u_pattern_br_b:a.br,u_texsize:[s,l],u_mix:e.t,u_pattern_size_a:i.displaySize,u_pattern_size_b:a.displaySize,u_scale_a:e.fromScale,u_scale_b:e.toScale,u_tile_units_to_pixels:1/de(n,1,r.transform.tileZoom),u_pixel_coord_upper:[h>>16,f>>16],u_pixel_coord_lower:[65535&h,65535&f]}}(i,o,n,a),{u_matrix:e,u_opacity:r})},tn={fillExtrusion:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fillExtrusionPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_lightpos:new t.Uniform3f(e,r.u_lightpos),u_lightintensity:new t.Uniform1f(e,r.u_lightintensity),u_lightcolor:new t.Uniform3f(e,r.u_lightcolor),u_vertical_gradient:new t.Uniform1f(e,r.u_vertical_gradient),u_height_factor:new t.Uniform1f(e,r.u_height_factor),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade),u_opacity:new t.Uniform1f(e,r.u_opacity)}},fill:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},fillPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},fillOutline:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world)}},fillOutlinePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_texsize:new t.Uniform2f(e,r.u_texsize),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},circle:function(e,r){return{u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_scale_with_map:new t.Uniform1i(e,r.u_scale_with_map),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},collisionBox:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pixels_to_tile_units:new t.Uniform1f(e,r.u_pixels_to_tile_units),u_extrude_scale:new t.Uniform2f(e,r.u_extrude_scale),u_overscale_factor:new t.Uniform1f(e,r.u_overscale_factor)}},collisionCircle:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_inv_matrix:new t.UniformMatrix4f(e,r.u_inv_matrix),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_viewport_size:new t.Uniform2f(e,r.u_viewport_size)}},debug:function(e,r){return{u_color:new t.UniformColor(e,r.u_color),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_overlay:new t.Uniform1i(e,r.u_overlay),u_overlay_scale:new t.Uniform1f(e,r.u_overlay_scale)}},clippingMask:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmap:function(e,r){return{u_extrude_scale:new t.Uniform1f(e,r.u_extrude_scale),u_intensity:new t.Uniform1f(e,r.u_intensity),u_matrix:new t.UniformMatrix4f(e,r.u_matrix)}},heatmapTexture:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_world:new t.Uniform2f(e,r.u_world),u_image:new t.Uniform1i(e,r.u_image),u_color_ramp:new t.Uniform1i(e,r.u_color_ramp),u_opacity:new t.Uniform1f(e,r.u_opacity)}},hillshade:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_latrange:new t.Uniform2f(e,r.u_latrange),u_light:new t.Uniform2f(e,r.u_light),u_shadow:new t.UniformColor(e,r.u_shadow),u_highlight:new t.UniformColor(e,r.u_highlight),u_accent:new t.UniformColor(e,r.u_accent)}},hillshadePrepare:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_image:new t.Uniform1i(e,r.u_image),u_dimension:new t.Uniform2f(e,r.u_dimension),u_zoom:new t.Uniform1f(e,r.u_zoom),u_unpack:new t.Uniform4f(e,r.u_unpack)}},line:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels)}},lineGradient:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_image:new t.Uniform1i(e,r.u_image),u_image_height:new t.Uniform1f(e,r.u_image_height)}},linePattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_texsize:new t.Uniform2f(e,r.u_texsize),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_image:new t.Uniform1i(e,r.u_image),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_scale:new t.Uniform3f(e,r.u_scale),u_fade:new t.Uniform1f(e,r.u_fade)}},lineSDF:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_ratio:new t.Uniform1f(e,r.u_ratio),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_units_to_pixels:new t.Uniform2f(e,r.u_units_to_pixels),u_patternscale_a:new t.Uniform2f(e,r.u_patternscale_a),u_patternscale_b:new t.Uniform2f(e,r.u_patternscale_b),u_sdfgamma:new t.Uniform1f(e,r.u_sdfgamma),u_image:new t.Uniform1i(e,r.u_image),u_tex_y_a:new t.Uniform1f(e,r.u_tex_y_a),u_tex_y_b:new t.Uniform1f(e,r.u_tex_y_b),u_mix:new t.Uniform1f(e,r.u_mix)}},raster:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_tl_parent:new t.Uniform2f(e,r.u_tl_parent),u_scale_parent:new t.Uniform1f(e,r.u_scale_parent),u_buffer_scale:new t.Uniform1f(e,r.u_buffer_scale),u_fade_t:new t.Uniform1f(e,r.u_fade_t),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image0:new t.Uniform1i(e,r.u_image0),u_image1:new t.Uniform1i(e,r.u_image1),u_brightness_low:new t.Uniform1f(e,r.u_brightness_low),u_brightness_high:new t.Uniform1f(e,r.u_brightness_high),u_saturation_factor:new t.Uniform1f(e,r.u_saturation_factor),u_contrast_factor:new t.Uniform1f(e,r.u_contrast_factor),u_spin_weights:new t.Uniform3f(e,r.u_spin_weights)}},symbolIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture)}},symbolSDF:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texture:new t.Uniform1i(e,r.u_texture),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},symbolTextAndIcon:function(e,r){return{u_is_size_zoom_constant:new t.Uniform1i(e,r.u_is_size_zoom_constant),u_is_size_feature_constant:new t.Uniform1i(e,r.u_is_size_feature_constant),u_size_t:new t.Uniform1f(e,r.u_size_t),u_size:new t.Uniform1f(e,r.u_size),u_camera_to_center_distance:new t.Uniform1f(e,r.u_camera_to_center_distance),u_pitch:new t.Uniform1f(e,r.u_pitch),u_rotate_symbol:new t.Uniform1i(e,r.u_rotate_symbol),u_aspect_ratio:new t.Uniform1f(e,r.u_aspect_ratio),u_fade_change:new t.Uniform1f(e,r.u_fade_change),u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_label_plane_matrix:new t.UniformMatrix4f(e,r.u_label_plane_matrix),u_coord_matrix:new t.UniformMatrix4f(e,r.u_coord_matrix),u_is_text:new t.Uniform1i(e,r.u_is_text),u_pitch_with_map:new t.Uniform1i(e,r.u_pitch_with_map),u_texsize:new t.Uniform2f(e,r.u_texsize),u_texsize_icon:new t.Uniform2f(e,r.u_texsize_icon),u_texture:new t.Uniform1i(e,r.u_texture),u_texture_icon:new t.Uniform1i(e,r.u_texture_icon),u_gamma_scale:new t.Uniform1f(e,r.u_gamma_scale),u_device_pixel_ratio:new t.Uniform1f(e,r.u_device_pixel_ratio),u_is_halo:new t.Uniform1i(e,r.u_is_halo)}},background:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_color:new t.UniformColor(e,r.u_color)}},backgroundPattern:function(e,r){return{u_matrix:new t.UniformMatrix4f(e,r.u_matrix),u_opacity:new t.Uniform1f(e,r.u_opacity),u_image:new t.Uniform1i(e,r.u_image),u_pattern_tl_a:new t.Uniform2f(e,r.u_pattern_tl_a),u_pattern_br_a:new t.Uniform2f(e,r.u_pattern_br_a),u_pattern_tl_b:new t.Uniform2f(e,r.u_pattern_tl_b),u_pattern_br_b:new t.Uniform2f(e,r.u_pattern_br_b),u_texsize:new t.Uniform2f(e,r.u_texsize),u_mix:new t.Uniform1f(e,r.u_mix),u_pattern_size_a:new t.Uniform2f(e,r.u_pattern_size_a),u_pattern_size_b:new t.Uniform2f(e,r.u_pattern_size_b),u_scale_a:new t.Uniform1f(e,r.u_scale_a),u_scale_b:new t.Uniform1f(e,r.u_scale_b),u_pixel_coord_upper:new t.Uniform2f(e,r.u_pixel_coord_upper),u_pixel_coord_lower:new t.Uniform2f(e,r.u_pixel_coord_lower),u_tile_units_to_pixels:new t.Uniform1f(e,r.u_tile_units_to_pixels)}}};function en(e,r,n,i,a,o,s){for(var l=e.context,c=l.gl,u=e.useProgram("collisionBox"),h=[],f=0,p=0,d=0;d0){var b=t.create(),w=v;t.mul(b,y.placementInvProjMatrix,e.transform.glCoordMatrix),t.mul(b,b,y.placementViewportMatrix),h.push({circleArray:_,circleOffset:p,transform:w,invTransform:b}),p=f+=_.length/4}x&&u.draw(l,c.LINES,At.disabled,St.disabled,e.colorModeForRenderPass(),Ct.disabled,Pr(v,e.transform,g),n.id,x.layoutVertexBuffer,x.indexBuffer,x.segments,null,e.transform.zoom,null,null,x.collisionVertexBuffer)}}if(s&&h.length){var T=e.useProgram("collisionCircle"),k=new t.StructArrayLayout2f1f2i16;k.resize(4*f),k._trim();for(var A=0,M=0,S=h;M=0&&(m[y.associatedIconIndex]={shiftedAnchor:S,angle:E})}else ue(y.numGlyphs,p)}if(h){d.clear();for(var I=e.icon.placedSymbolArray,L=0;L0){var s=t.browser.now(),l=(s-e.timeAdded)/o,c=r?(s-r.timeAdded)/o:-1,u=n.getSource(),h=a.coveringZoomLevel({tileSize:u.tileSize,roundZoom:u.roundZoom}),f=!r||Math.abs(r.tileID.overscaledZ-h)>Math.abs(e.tileID.overscaledZ-h),p=f&&e.refreshedUponExpiration?1:t.clamp(f?l:1-c,0,1);return e.refreshedUponExpiration&&l>=1&&(e.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}var dn=new t.Color(1,0,0,1),mn=new t.Color(0,1,0,1),gn=new t.Color(0,0,1,1),yn=new t.Color(1,0,1,1),vn=new t.Color(0,1,1,1);function xn(t,e,r,n){bn(t,0,e+r/2,t.transform.width,r,n)}function _n(t,e,r,n){bn(t,e-r/2,0,r,t.transform.height,n)}function bn(e,r,n,i,a,o){var s=e.context,l=s.gl;l.enable(l.SCISSOR_TEST),l.scissor(r*t.browser.devicePixelRatio,n*t.browser.devicePixelRatio,i*t.browser.devicePixelRatio,a*t.browser.devicePixelRatio),s.clear({color:o}),l.disable(l.SCISSOR_TEST)}function wn(e,r,n){var i=e.context,a=i.gl,o=n.posMatrix,s=e.useProgram("debug"),l=At.disabled,c=St.disabled,u=e.colorModeForRenderPass(),h="$debug";i.activeTexture.set(a.TEXTURE0),e.emptyTexture.bind(a.LINEAR,a.CLAMP_TO_EDGE),s.draw(i,a.LINE_STRIP,l,c,u,Ct.disabled,Dr(o,t.Color.red),h,e.debugBuffer,e.tileBorderIndexBuffer,e.debugSegments);var f=r.getTileByID(n.key).latestRawTileData,p=f&&f.byteLength||0,d=Math.floor(p/1024),m=r.getTile(n).tileSize,g=512/Math.min(m,512)*(n.overscaledZ/e.transform.zoom)*.5,y=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(y+=" => "+n.overscaledZ),function(t,e){t.initDebugOverlayCanvas();var r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext("2d");i.clearRect(0,0,r.width,r.height),i.shadowColor="white",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle="white",i.textBaseline="top",i.font="bold 36px Open Sans, sans-serif",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(e,y+" "+d+"kb"),s.draw(i,a.TRIANGLES,l,c,Et.alphaBlended,Ct.disabled,Dr(o,t.Color.transparent,g),h,e.debugBuffer,e.quadTriangleIndexBuffer,e.debugSegments)}var Tn={symbol:function(e,r,n,i,a){if("translucent"===e.renderPass){var o=St.disabled,s=e.colorModeForRenderPass();n.layout.get("text-variable-anchor")&&function(e,r,n,i,a,o,s){for(var l=r.transform,c="map"===a,u="map"===o,h=0,f=e;h256&&this.clearStencil(),r.setColorMode(Et.disabled),r.setDepthMode(At.disabled);var i=this.useProgram("clippingMask");this._tileClippingMaskIDs={};for(var a=0,o=e;a256&&this.clearStencil();var t=this.nextStencilID++,e=this.context.gl;return new St({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)},kn.prototype.stencilModeForClipping=function(t){var e=this.context.gl;return new St({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)},kn.prototype.stencilConfigForOverlap=function(t){var e,r=this.context.gl,n=t.sort((function(t,e){return e.overscaledZ-t.overscaledZ})),i=n[n.length-1].overscaledZ,a=n[0].overscaledZ-i+1;if(a>1){this.currentStencilSource=void 0,this.nextStencilID+a>256&&this.clearStencil();for(var o={},s=0;s=0;this.currentLayer--){var w=this.style._layers[i[this.currentLayer]],T=a[w.source],k=u[w.source];this._renderTileClippingMasks(w,k),this.renderLayer(this,T,w,k)}for(this.renderPass="translucent",this.currentLayer=0;this.currentLayer0?e.pop():null},kn.prototype.isPatternMissing=function(t){if(!t)return!1;if(!t.from||!t.to)return!0;var e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r},kn.prototype.useProgram=function(t,e){this.cache=this.cache||{};var r=""+t+(e?e.cacheKey:"")+(this._showOverdrawInspector?"/overdraw":"");return this.cache[r]||(this.cache[r]=new Tr(this.context,t,_r[t],e,tn[t],this._showOverdrawInspector)),this.cache[r]},kn.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},kn.prototype.setBaseState=function(){var t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)},kn.prototype.initDebugOverlayCanvas=function(){if(null==this.debugOverlayCanvas){this.debugOverlayCanvas=t.window.document.createElement("canvas"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var e=this.context.gl;this.debugOverlayTexture=new t.Texture(this.context,this.debugOverlayCanvas,e.RGBA)}},kn.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var An=function(t,e){this.points=t,this.planes=e};An.fromInvProjectionMatrix=function(e,r,n){var i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((function(r){return t.transformMat4([],r,e)})).map((function(e){return t.scale$1([],e,1/e[3]/r*i)})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((function(e){var r=t.sub([],a[e[0]],a[e[1]]),n=t.sub([],a[e[2]],a[e[1]]),i=t.normalize([],t.cross([],r,n)),o=-t.dot(i,a[e[1]]);return i.concat(o)}));return new An(a,o)};var Mn=function(e,r){this.min=e,this.max=r,this.center=t.scale$2([],t.add([],this.min,this.max),.5)};Mn.prototype.quadrant=function(e){for(var r=[e%2==0,e<2],n=t.clone$2(this.min),i=t.clone$2(this.max),a=0;a=0;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(var l=0;l<3;l++){for(var c=Number.MAX_VALUE,u=-Number.MAX_VALUE,h=0;hthis.max[l]-this.min[l])return 0}return 1};var Sn=function(t,e,r,n){if(void 0===t&&(t=0),void 0===e&&(e=0),void 0===r&&(r=0),void 0===n&&(n=0),isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error("Invalid value for edge-insets, top, bottom, left and right must all be numbers");this.top=t,this.bottom=e,this.left=r,this.right=n};Sn.prototype.interpolate=function(e,r,n){return null!=r.top&&null!=e.top&&(this.top=t.number(e.top,r.top,n)),null!=r.bottom&&null!=e.bottom&&(this.bottom=t.number(e.bottom,r.bottom,n)),null!=r.left&&null!=e.left&&(this.left=t.number(e.left,r.left,n)),null!=r.right&&null!=e.right&&(this.right=t.number(e.right,r.right,n)),this},Sn.prototype.getCenter=function(e,r){var n=t.clamp((this.left+e-this.right)/2,0,e),i=t.clamp((this.top+r-this.bottom)/2,0,r);return new t.Point(n,i)},Sn.prototype.equals=function(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right},Sn.prototype.clone=function(){return new Sn(this.top,this.bottom,this.left,this.right)},Sn.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var En=function(e,r,n,i,a){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=void 0===a||a,this._minZoom=e||0,this._maxZoom=r||22,this._minPitch=n??0,this._maxPitch=i??60,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new Sn,this._posMatrixCache={},this._alignedPosMatrixCache={}},Cn={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};En.prototype.clone=function(){var t=new En(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.tileSize=this.tileSize,t.latRange=this.latRange,t.width=this.width,t.height=this.height,t._center=this._center,t.zoom=this.zoom,t.angle=this.angle,t._fov=this._fov,t._pitch=this._pitch,t._unmodified=this._unmodified,t._edgeInsets=this._edgeInsets.clone(),t._calcMatrices(),t},Cn.minZoom.get=function(){return this._minZoom},Cn.minZoom.set=function(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))},Cn.maxZoom.get=function(){return this._maxZoom},Cn.maxZoom.set=function(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))},Cn.minPitch.get=function(){return this._minPitch},Cn.minPitch.set=function(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))},Cn.maxPitch.get=function(){return this._maxPitch},Cn.maxPitch.set=function(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))},Cn.renderWorldCopies.get=function(){return this._renderWorldCopies},Cn.renderWorldCopies.set=function(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t},Cn.worldSize.get=function(){return this.tileSize*this.scale},Cn.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},Cn.size.get=function(){return new t.Point(this.width,this.height)},Cn.bearing.get=function(){return-this.angle/Math.PI*180},Cn.bearing.set=function(e){var r=-t.wrap(e,-180,180)*Math.PI/180;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=t.create$2(),t.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},Cn.pitch.get=function(){return this._pitch/Math.PI*180},Cn.pitch.set=function(e){var r=t.clamp(e,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())},Cn.fov.get=function(){return this._fov/Math.PI*180},Cn.fov.set=function(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())},Cn.zoom.get=function(){return this._zoom},Cn.zoom.set=function(t){var e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.scale=this.zoomScale(e),this.tileZoom=Math.floor(e),this.zoomFraction=e-this.tileZoom,this._constrain(),this._calcMatrices())},Cn.center.get=function(){return this._center},Cn.center.set=function(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())},Cn.padding.get=function(){return this._edgeInsets.toJSON()},Cn.padding.set=function(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())},Cn.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},En.prototype.isPaddingEqual=function(t){return this._edgeInsets.equals(t)},En.prototype.interpolatePadding=function(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()},En.prototype.coveringZoomLevel=function(t){var e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)},En.prototype.getVisibleUnwrappedCoordinates=function(e){var r=[new t.UnwrappedTileID(0,e)];if(this._renderWorldCopies)for(var n=this.pointCoordinate(new t.Point(0,0)),i=this.pointCoordinate(new t.Point(this.width,0)),a=this.pointCoordinate(new t.Point(this.width,this.height)),o=this.pointCoordinate(new t.Point(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),c=s-1;c<=l+1;c++)0!==c&&r.push(new t.UnwrappedTileID(c,e));return r},En.prototype.coveringTiles=function(e){var r=this.coveringZoomLevel(e),n=r;if(void 0!==e.minzoom&&re.maxzoom&&(r=e.maxzoom);var i=t.MercatorCoordinate.fromLngLat(this.center),a=Math.pow(2,r),o=[a*i.x,a*i.y,0],s=An.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,r),l=e.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(l=r);var c=function(t){return{aabb:new Mn([t*a,0,0],[(t+1)*a,a,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}},u=[],h=[],f=r,p=e.reparseOverscaled?n:r;if(this._renderWorldCopies)for(var d=1;d<=3;d++)u.push(c(-d)),u.push(c(d));for(u.push(c(0));u.length>0;){var m=u.pop(),g=m.x,y=m.y,v=m.fullyVisible;if(!v){var x=m.aabb.intersects(s);if(0===x)continue;v=2===x}var _=m.aabb.distanceX(o),b=m.aabb.distanceY(o),w=Math.max(Math.abs(_),Math.abs(b)),T=3+(1<T&&m.zoom>=l)h.push({tileID:new t.OverscaledTileID(m.zoom===f?p:m.zoom,m.wrap,m.zoom,g,y),distanceSq:t.sqrLen([o[0]-.5-g,o[1]-.5-y])});else for(var k=0;k<4;k++){var A=(g<<1)+k%2,M=(y<<1)+(k>>1);u.push({aabb:m.aabb.quadrant(k),zoom:m.zoom+1,x:A,y:M,wrap:m.wrap,fullyVisible:v})}}return h.sort((function(t,e){return t.distanceSq-e.distanceSq})).map((function(t){return t.tileID}))},En.prototype.resize=function(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()},Cn.unmodified.get=function(){return this._unmodified},En.prototype.zoomScale=function(t){return Math.pow(2,t)},En.prototype.scaleZoom=function(t){return Math.log(t)/Math.LN2},En.prototype.project=function(e){var r=t.clamp(e.lat,-this.maxValidLatitude,this.maxValidLatitude);return new t.Point(t.mercatorXfromLng(e.lng)*this.worldSize,t.mercatorYfromLat(r)*this.worldSize)},En.prototype.unproject=function(e){return new t.MercatorCoordinate(e.x/this.worldSize,e.y/this.worldSize).toLngLat()},Cn.point.get=function(){return this.project(this.center)},En.prototype.setLocationAtPoint=function(e,r){var n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(e),o=new t.MercatorCoordinate(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())},En.prototype.locationPoint=function(t){return this.coordinatePoint(this.locationCoordinate(t))},En.prototype.pointLocation=function(t){return this.coordinateLocation(this.pointCoordinate(t))},En.prototype.locationCoordinate=function(e){return t.MercatorCoordinate.fromLngLat(e)},En.prototype.coordinateLocation=function(t){return t.toLngLat()},En.prototype.pointCoordinate=function(e){var r=[e.x,e.y,0,1],n=[e.x,e.y,1,1];t.transformMat4(r,r,this.pixelMatrixInverse),t.transformMat4(n,n,this.pixelMatrixInverse);var i=r[3],a=n[3],o=r[0]/i,s=n[0]/a,l=r[1]/i,c=n[1]/a,u=r[2]/i,h=n[2]/a,f=u===h?0:(0-u)/(h-u);return new t.MercatorCoordinate(t.number(o,s,f)/this.worldSize,t.number(l,c,f)/this.worldSize)},En.prototype.coordinatePoint=function(e){var r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix),new t.Point(r[0]/r[3],r[1]/r[3])},En.prototype.getBounds=function(){return(new t.LngLatBounds).extend(this.pointLocation(new t.Point(0,0))).extend(this.pointLocation(new t.Point(this.width,0))).extend(this.pointLocation(new t.Point(this.width,this.height))).extend(this.pointLocation(new t.Point(0,this.height)))},En.prototype.getMaxBounds=function(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new t.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null},En.prototype.setMaxBounds=function(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},En.prototype.calculatePosMatrix=function(e,r){void 0===r&&(r=!1);var n=e.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];var a=e.canonical,o=this.worldSize/this.zoomScale(a.z),s=a.x+Math.pow(2,a.z)*e.wrap,l=t.identity(new Float64Array(16));return t.translate(l,l,[s*o,a.y*o,0]),t.scale(l,l,[o/t.EXTENT,o/t.EXTENT,1]),t.multiply(l,r?this.alignedProjMatrix:this.projMatrix,l),i[n]=new Float32Array(l),i[n]},En.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},En.prototype._constrain=function(){if(this.center&&this.width&&this.height&&!this._constraining){this._constraining=!0;var e,r,n,i,a=-90,o=90,s=-180,l=180,c=this.size,u=this._unmodified;if(this.latRange){var h=this.latRange;a=t.mercatorYfromLat(h[1])*this.worldSize,e=(o=t.mercatorYfromLat(h[0])*this.worldSize)-ao&&(i=o-g)}if(this.lngRange){var y=p.x,v=c.x/2;y-vl&&(n=l-v)}(void 0!==n||void 0!==i)&&(this.center=this.unproject(new t.Point(void 0!==n?n:p.x,void 0!==i?i:p.y))),this._unmodified=u,this._constraining=!1}},En.prototype._calcMatrices=function(){if(this.height){var e=this._fov/2,r=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(e)*this.height;var n=Math.PI/2+this._pitch,i=this._fov*(.5+r.y/this.height),a=Math.sin(i)*this.cameraToCenterDistance/Math.sin(t.clamp(Math.PI-n-i,.01,Math.PI-.01)),o=this.point,s=o.x,l=o.y,c=1.01*(Math.cos(Math.PI/2-this._pitch)*a+this.cameraToCenterDistance),u=this.height/50,h=new Float64Array(16);t.perspective(h,this._fov,this.width/this.height,u,c),h[8]=2*-r.x/this.width,h[9]=2*r.y/this.height,t.scale(h,h,[1,-1,1]),t.translate(h,h,[0,0,-this.cameraToCenterDistance]),t.rotateX(h,h,this._pitch),t.rotateZ(h,h,this.angle),t.translate(h,h,[-s,-l,0]),this.mercatorMatrix=t.scale([],h,[this.worldSize,this.worldSize,this.worldSize]),t.scale(h,h,[1,1,t.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=h,this.invProjMatrix=t.invert([],this.projMatrix);var f=this.width%2/2,p=this.height%2/2,d=Math.cos(this.angle),m=Math.sin(this.angle),g=s-Math.round(s)+d*f+m*p,y=l-Math.round(l)+d*p+m*f,v=new Float64Array(h);if(t.translate(v,v,[g>.5?g-1:g,y>.5?y-1:y,0]),this.alignedProjMatrix=v,h=t.create(),t.scale(h,h,[this.width/2,-this.height/2,1]),t.translate(h,h,[1,-1,0]),this.labelPlaneMatrix=h,h=t.create(),t.scale(h,h,[1,-1,1]),t.translate(h,h,[-1,-1,0]),t.scale(h,h,[2/this.width,2/this.height,1]),this.glCoordMatrix=h,this.pixelMatrix=t.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),!(h=t.invert(new Float64Array(16),this.pixelMatrix)))throw new Error("failed to invert matrix");this.pixelMatrixInverse=h,this._posMatrixCache={},this._alignedPosMatrixCache={}}},En.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var e=this.pointCoordinate(new t.Point(0,0)),r=[e.x*this.worldSize,e.y*this.worldSize,0,1];return t.transformMat4(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance},En.prototype.getCameraPoint=function(){var e=this._pitch,r=Math.tan(e)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.Point(0,r))},En.prototype.getCameraQueryGeometry=function(e){var r=this.getCameraPoint();if(1===e.length)return[e[0],r];for(var n=r.x,i=r.y,a=r.x,o=r.y,s=0,l=e;s=3&&!t.some((function(t){return isNaN(t)}))){var e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},In.prototype._updateHashUnthrottled=function(){var e=t.window.location.href.replace(/(#.+)?$/,this.getHashString());try{t.window.history.replaceState(t.window.history.state,null,e)}catch{}};var Ln={linearity:.3,easing:t.bezier(0,0,.3,1)},Pn=t.extend({deceleration:2500,maxSpeed:1400},Ln),zn=t.extend({deceleration:20,maxSpeed:1400},Ln),Dn=t.extend({deceleration:1e3,maxSpeed:360},Ln),On=t.extend({deceleration:1e3,maxSpeed:90},Ln),Rn=function(t){this._map=t,this.clear()};function Fn(t,e){(!t.duration||t.duration0&&r-e[0].time>160;)e.shift()},Rn.prototype._onMoveEnd=function(e){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var r={zoom:0,bearing:0,pitch:0,pan:new t.Point(0,0),pinchAround:void 0,around:void 0},n=0,i=this._inertiaBuffer;n=this._clickTolerance||this._map.fire(new jn(t.type,this._map,t))},Vn.prototype.dblclick=function(t){return this._firePreventable(new jn(t.type,this._map,t))},Vn.prototype.mouseover=function(t){this._map.fire(new jn(t.type,this._map,t))},Vn.prototype.mouseout=function(t){this._map.fire(new jn(t.type,this._map,t))},Vn.prototype.touchstart=function(t){return this._firePreventable(new Nn(t.type,this._map,t))},Vn.prototype.touchmove=function(t){this._map.fire(new Nn(t.type,this._map,t))},Vn.prototype.touchend=function(t){this._map.fire(new Nn(t.type,this._map,t))},Vn.prototype.touchcancel=function(t){this._map.fire(new Nn(t.type,this._map,t))},Vn.prototype._firePreventable=function(t){if(this._map.fire(t),t.defaultPrevented)return{}},Vn.prototype.isEnabled=function(){return!0},Vn.prototype.isActive=function(){return!1},Vn.prototype.enable=function(){},Vn.prototype.disable=function(){};var qn=function(t){this._map=t};qn.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},qn.prototype.mousemove=function(t){this._map.fire(new jn(t.type,this._map,t))},qn.prototype.mousedown=function(){this._delayContextMenu=!0},qn.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new jn("contextmenu",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},qn.prototype.contextmenu=function(t){this._delayContextMenu?this._contextMenuEvent=t:this._map.fire(new jn(t.type,this._map,t)),this._map.listens("contextmenu")&&t.preventDefault()},qn.prototype.isEnabled=function(){return!0},qn.prototype.isActive=function(){return!1},qn.prototype.enable=function(){},qn.prototype.disable=function(){};var Hn=function(t,e){this._map=t,this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1};function Gn(t,e){for(var r={},n=0;nthis.numTouches)&&(this.aborted=!0),!this.aborted&&(void 0===this.startTime&&(this.startTime=e.timeStamp),n.length===this.numTouches&&(this.centroid=function(e){for(var r=new t.Point(0,0),n=0,i=e;n30)&&(this.aborted=!0)}}},Wn.prototype.touchend=function(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){var n=!this.aborted&&this.centroid;if(this.reset(),n)return n}};var Zn=function(t){this.singleTap=new Wn(t),this.numTaps=t.numTaps,this.reset()};Zn.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},Zn.prototype.touchstart=function(t,e,r){this.singleTap.touchstart(t,e,r)},Zn.prototype.touchmove=function(t,e,r){this.singleTap.touchmove(t,e,r)},Zn.prototype.touchend=function(t,e,r){var n=this.singleTap.touchend(t,e,r);if(n){var i=t.timeStamp-this.lastTime<500,a=!this.lastTap||this.lastTap.dist(n)<30;if((!i||!a)&&this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}};var Yn=function(){this._zoomIn=new Zn({numTouches:1,numTaps:2}),this._zoomOut=new Zn({numTouches:2,numTaps:1}),this.reset()};Yn.prototype.reset=function(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()},Yn.prototype.touchstart=function(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)},Yn.prototype.touchmove=function(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)},Yn.prototype.touchend=function(t,e,r){var n=this,i=this._zoomIn.touchend(t,e,r),a=this._zoomOut.touchend(t,e,r);return i?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()+1,around:e.unproject(i)},{originalEvent:t})}}):a?(this._active=!0,t.preventDefault(),setTimeout((function(){return n.reset()}),0),{cameraAnimation:function(e){return e.easeTo({duration:300,zoom:e.getZoom()-1,around:e.unproject(a)},{originalEvent:t})}}):void 0},Yn.prototype.touchcancel=function(){this.reset()},Yn.prototype.enable=function(){this._enabled=!0},Yn.prototype.disable=function(){this._enabled=!1,this.reset()},Yn.prototype.isEnabled=function(){return this._enabled},Yn.prototype.isActive=function(){return this._active};var Xn={0:1,2:2},$n=function(t){this.reset(),this._clickTolerance=t.clickTolerance||1};$n.prototype.reset=function(){this._active=!1,this._moved=!1,delete this._lastPoint,delete this._eventButton},$n.prototype._correctButton=function(t,e){return!1},$n.prototype._move=function(t,e){return{}},$n.prototype.mousedown=function(t,e){if(!this._lastPoint){var n=r.mouseButton(t);this._correctButton(t,n)&&(this._lastPoint=e,this._eventButton=n)}},$n.prototype.mousemoveWindow=function(t,e){var r=this._lastPoint;if(r){if(t.preventDefault(),function(t,e){var r=Xn[e];return void 0===t.buttons||(t.buttons&r)!==r}(t,this._eventButton))return void this.reset();if(this._moved||!(e.dist(r)0&&(this._active=!0);var i=Gn(n,r),a=new t.Point(0,0),o=new t.Point(0,0),s=0;for(var l in i){var c=i[l],u=this._touches[l];u&&(a._add(c),o._add(c.sub(u)),s++,i[l]=c)}if(this._touches=i,!(sMath.abs(t.x)}var li=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e.prototype.reset=function(){t.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},e.prototype._start=function(t){this._lastPoints=t,si(t[0].sub(t[1]))&&(this._valid=!1)},e.prototype._move=function(t,e,r){var n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid)return this._lastPoints=t,this._active=!0,{pitchDelta:(n.y+i.y)/2*-.5}},e.prototype.gestureBeginsVertically=function(t,e,r){if(void 0!==this._valid)return this._valid;var n=t.mag()>=2,i=e.mag()>=2;if(n||i){if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;var a=t.y>0==e.y>0;return si(t)&&si(e)&&a}},e}(ei),ci={panStep:100,bearingStep:15,pitchStep:10},ui=function(){var t=ci;this._panStep=t.panStep,this._bearingStep=t.bearingStep,this._pitchStep=t.pitchStep,this._rotationDisabled=!1};function hi(t){return t*(2-t)}ui.prototype.reset=function(){this._active=!1},ui.prototype.keydown=function(t){var e=this;if(!(t.altKey||t.ctrlKey||t.metaKey)){var r=0,n=0,i=0,a=0,o=0;switch(t.keyCode){case 61:case 107:case 171:case 187:r=1;break;case 189:case 109:case 173:r=-1;break;case 37:t.shiftKey?n=-1:(t.preventDefault(),a=-1);break;case 39:t.shiftKey?n=1:(t.preventDefault(),a=1);break;case 38:t.shiftKey?i=1:(t.preventDefault(),o=-1);break;case 40:t.shiftKey?i=-1:(t.preventDefault(),o=1);break;default:return}return this._rotationDisabled&&(n=0,i=0),{cameraAnimation:function(s){var l=s.getZoom();s.easeTo({duration:300,easeId:"keyboardHandler",easing:hi,zoom:r?Math.round(l)+r*(t.shiftKey?2:1):l,bearing:s.getBearing()+n*e._bearingStep,pitch:s.getPitch()+i*e._pitchStep,offset:[-a*e._panStep,-o*e._panStep],center:s.getCenter()},{originalEvent:t})}}}},ui.prototype.enable=function(){this._enabled=!0},ui.prototype.disable=function(){this._enabled=!1,this.reset()},ui.prototype.isEnabled=function(){return this._enabled},ui.prototype.isActive=function(){return this._active},ui.prototype.disableRotation=function(){this._rotationDisabled=!0},ui.prototype.enableRotation=function(){this._rotationDisabled=!1};var fi=4.000244140625,pi=1/450,di=function(e,r){this._map=e,this._el=e.getCanvasContainer(),this._handler=r,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=pi,t.bindAll(["_onTimeout"],this)};di.prototype.setZoomRate=function(t){this._defaultZoomRate=t},di.prototype.setWheelZoomRate=function(t){this._wheelZoomRate=t},di.prototype.isEnabled=function(){return!!this._enabled},di.prototype.isActive=function(){return!!this._active||void 0!==this._finishTimeout},di.prototype.isZooming=function(){return!!this._zooming},di.prototype.enable=function(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=t&&"center"===t.around)},di.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},di.prototype.wheel=function(e){if(this.isEnabled()){var r=e.deltaMode===t.window.WheelEvent.DOM_DELTA_LINE?40*e.deltaY:e.deltaY,n=t.browser.now(),i=n-(this._lastWheelEventTime||0);this._lastWheelEventTime=n,0!==r&&r%fi==0?this._type="wheel":0!==r&&Math.abs(r)<4?this._type="trackpad":i>400?(this._type=null,this._lastValue=r,this._timeout=setTimeout(this._onTimeout,40,e)):this._type||(this._type=Math.abs(i*r)<200?"trackpad":"wheel",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,r+=this._lastValue)),e.shiftKey&&r&&(r/=4),this._type&&(this._lastWheelEvent=e,this._delta-=r,this._active||this._start(e)),e.preventDefault()}},di.prototype._onTimeout=function(t){this._type="wheel",this._delta-=this._lastValue,this._active||this._start(t)},di.prototype._start=function(e){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var n=r.mousePos(this._el,e);this._around=t.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(n)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},di.prototype.renderFrame=function(){var e=this;if(this._frameId&&(this._frameId=null,this.isActive())){var r=this._map.transform;if(0!==this._delta){var n="wheel"===this._type&&Math.abs(this._delta)>fi?this._wheelZoomRate:this._defaultZoomRate,i=2/(1+Math.exp(-Math.abs(this._delta*n)));this._delta<0&&0!==i&&(i=1/i);var a="number"==typeof this._targetZoom?r.zoomScale(this._targetZoom):r.scale;this._targetZoom=Math.min(r.maxZoom,Math.max(r.minZoom,r.scaleZoom(a*i))),"wheel"===this._type&&(this._startZoom=r.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var o,s="number"==typeof this._targetZoom?this._targetZoom:r.zoom,l=this._startZoom,c=this._easing,u=!1;if("wheel"===this._type&&l&&c){var h=Math.min((t.browser.now()-this._lastWheelEventTime)/200,1),f=c(h);o=t.number(l,s,f),h<1?this._frameId||(this._frameId=!0):u=!0}else o=s,u=!0;return this._active=!0,u&&(this._active=!1,this._finishTimeout=setTimeout((function(){e._zooming=!1,e._handler._triggerRenderFrame(),delete e._targetZoom,delete e._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!u,zoomDelta:o-r.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},di.prototype._smoothOutEasing=function(e){var r=t.ease;if(this._prevEase){var n=this._prevEase,i=(t.browser.now()-n.start)/n.duration,a=n.easing(i+.01)-n.easing(i),o=.27/Math.sqrt(a*a+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=t.bezier(o,s,.25,1)}return this._prevEase={start:t.browser.now(),duration:e,easing:r},r},di.prototype.reset=function(){this._active=!1};var mi=function(t,e){this._clickZoom=t,this._tapZoom=e};mi.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},mi.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},mi.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},mi.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var gi=function(){this.reset()};gi.prototype.reset=function(){this._active=!1},gi.prototype.dblclick=function(t,e){return t.preventDefault(),{cameraAnimation:function(r){r.easeTo({duration:300,zoom:r.getZoom()+(t.shiftKey?-1:1),around:r.unproject(e)},{originalEvent:t})}}},gi.prototype.enable=function(){this._enabled=!0},gi.prototype.disable=function(){this._enabled=!1,this.reset()},gi.prototype.isEnabled=function(){return this._enabled},gi.prototype.isActive=function(){return this._active};var yi=function(){this._tap=new Zn({numTouches:1,numTaps:1}),this.reset()};yi.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},yi.prototype.touchstart=function(t,e,r){this._swipePoint||(this._tapTime&&t.timeStamp-this._tapTime>500&&this.reset(),this._tapTime?r.length>0&&(this._swipePoint=e[0],this._swipeTouch=r[0].identifier):this._tap.touchstart(t,e,r))},yi.prototype.touchmove=function(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;var n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)},yi.prototype.touchend=function(t,e,r){this._tapTime?this._swipePoint&&0===r.length&&this.reset():this._tap.touchend(t,e,r)&&(this._tapTime=t.timeStamp)},yi.prototype.touchcancel=function(){this.reset()},yi.prototype.enable=function(){this._enabled=!0},yi.prototype.disable=function(){this._enabled=!1,this.reset()},yi.prototype.isEnabled=function(){return this._enabled},yi.prototype.isActive=function(){return this._active};var vi=function(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r};vi.prototype.enable=function(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add("mapboxgl-touch-drag-pan")},vi.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove("mapboxgl-touch-drag-pan")},vi.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},vi.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var xi=function(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r};xi.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},xi.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},xi.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},xi.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var _i=function(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0};_i.prototype.enable=function(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add("mapboxgl-touch-zoom-rotate")},_i.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove("mapboxgl-touch-zoom-rotate")},_i.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},_i.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},_i.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},_i.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var bi=function(t){return t.zoom||t.drag||t.pitch||t.rotate},wi=function(t){function e(){t.apply(this,arguments)}return t&&(e.__proto__=t),e.prototype=Object.create(t&&t.prototype),e.prototype.constructor=e,e}(t.Event);function Ti(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}var ki=function(e,n){this._map=e,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Rn(e),this._bearingSnap=n.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(n),t.bindAll(["handleEvent","handleWindowEvent"],this);var i=this._el;this._listeners=[[i,"touchstart",{passive:!0}],[i,"touchmove",{passive:!1}],[i,"touchend",void 0],[i,"touchcancel",void 0],[i,"mousedown",void 0],[i,"mousemove",void 0],[i,"mouseup",void 0],[t.window.document,"mousemove",{capture:!0}],[t.window.document,"mouseup",void 0],[i,"mouseover",void 0],[i,"mouseout",void 0],[i,"dblclick",void 0],[i,"click",void 0],[i,"keydown",{capture:!1}],[i,"keyup",void 0],[i,"wheel",{passive:!1}],[i,"contextmenu",void 0],[t.window,"blur",void 0]];for(var a=0,o=this._listeners;aa?Math.min(2,b):Math.max(.5,b),w=Math.pow(g,1-e),T=i.unproject(x.add(_.mult(e*w)).mult(m));i.setLocationAtPoint(i.renderWorldCopies?T.wrap():T,d)}n._fireMoveEvents(r)}),(function(t){n._afterEase(r,t)}),e),this},r.prototype._prepareEase=function(e,r,n){void 0===n&&(n={}),this._moving=!0,!r&&!n.moving&&this.fire(new t.Event("movestart",e)),this._zooming&&!n.zooming&&this.fire(new t.Event("zoomstart",e)),this._rotating&&!n.rotating&&this.fire(new t.Event("rotatestart",e)),this._pitching&&!n.pitching&&this.fire(new t.Event("pitchstart",e))},r.prototype._fireMoveEvents=function(e){this.fire(new t.Event("move",e)),this._zooming&&this.fire(new t.Event("zoom",e)),this._rotating&&this.fire(new t.Event("rotate",e)),this._pitching&&this.fire(new t.Event("pitch",e))},r.prototype._afterEase=function(e,r){if(!this._easeId||!r||this._easeId!==r){delete this._easeId;var n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new t.Event("zoomend",e)),i&&this.fire(new t.Event("rotateend",e)),a&&this.fire(new t.Event("pitchend",e)),this.fire(new t.Event("moveend",e))}},r.prototype.flyTo=function(e,r){var n=this;if(!e.essential&&t.browser.prefersReducedMotion){var i=t.pick(e,["center","zoom","bearing","pitch","around"]);return this.jumpTo(i,r)}this.stop(),e=t.extend({offset:[0,0],speed:1.2,curve:1.42,easing:t.ease},e);var a=this.transform,o=this.getZoom(),s=this.getBearing(),l=this.getPitch(),c=this.getPadding(),u="zoom"in e?t.clamp(+e.zoom,a.minZoom,a.maxZoom):o,h="bearing"in e?this._normalizeBearing(e.bearing,s):s,f="pitch"in e?+e.pitch:l,p="padding"in e?e.padding:a.padding,d=a.zoomScale(u-o),m=t.Point.convert(e.offset),g=a.centerPoint.add(m),y=a.pointLocation(g),v=t.LngLat.convert(e.center||y);this._normalizeCenter(v);var x=a.project(y),_=a.project(v).sub(x),b=e.curve,w=Math.max(a.width,a.height),T=w/d,k=_.mag();if("minZoom"in e){var A=t.clamp(Math.min(e.minZoom,o,u),a.minZoom,a.maxZoom),M=w/a.zoomScale(A-o);b=Math.sqrt(M/k*2)}var S=b*b;function E(t){var e=(T*T-w*w+(t?-1:1)*S*S*k*k)/(2*(t?T:w)*S*k);return Math.log(Math.sqrt(e*e+1)-e)}function C(t){return(Math.exp(t)-Math.exp(-t))/2}function I(t){return(Math.exp(t)+Math.exp(-t))/2}var L=E(0),P=function(t){return I(L)/I(L+b*t)},z=function(t){return w*((I(L)*function(t){return C(t)/I(t)}(L+b*t)-C(L))/S)/k},D=(E(1)-L)/b;if(Math.abs(k)<1e-6||!isFinite(D)){if(Math.abs(w-T)<1e-6)return this.easeTo(e,r);var O=Te.maxDuration&&(e.duration=0),this._zooming=!0,this._rotating=s!==h,this._pitching=f!==l,this._padding=!a.isPaddingEqual(p),this._prepareEase(r,!1),this._ease((function(e){var i=e*D,d=1/P(i);a.zoom=1===e?u:o+a.scaleZoom(d),n._rotating&&(a.bearing=t.number(s,h,e)),n._pitching&&(a.pitch=t.number(l,f,e)),n._padding&&(a.interpolatePadding(c,p,e),g=a.centerPoint.add(m));var y=1===e?v:a.unproject(x.add(_.mult(z(i))).mult(d));a.setLocationAtPoint(a.renderWorldCopies?y.wrap():y,g),n._fireMoveEvents(r)}),(function(){return n._afterEase(r)}),e),this},r.prototype.isEasing=function(){return!!this._easeFrameId},r.prototype.stop=function(){return this._stop()},r.prototype._stop=function(t,e){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var r=this._onEaseEnd;delete this._onEaseEnd,r.call(this,e)}if(!t){var n=this.handlers;n&&n.stop(!1)}return this},r.prototype._ease=function(e,r,n){!1===n.animate||0===n.duration?(e(1),r()):(this._easeStart=t.browser.now(),this._easeOptions=n,this._onEaseFrame=e,this._onEaseEnd=r,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},r.prototype._renderFrameCallback=function(){var e=Math.min((t.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(e)),e<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},r.prototype._normalizeBearing=function(e,r){e=t.wrap(e,-180,180);var n=Math.abs(e-r);return Math.abs(e-360-r)180?-360:r<-180?360:0}},r}(t.Evented),Mi=function(e){void 0===e&&(e={}),this.options=e,t.bindAll(["_toggleAttribution","_updateEditLink","_updateData","_updateCompact"],this)};Mi.prototype.getDefaultPosition=function(){return"bottom-right"},Mi.prototype.onAdd=function(t){var e=this.options&&this.options.compact;return this._map=t,this._container=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-attrib"),this._compactButton=r.create("button","mapboxgl-ctrl-attrib-button",this._container),this._compactButton.addEventListener("click",this._toggleAttribution),this._setElementTitle(this._compactButton,"ToggleAttribution"),this._innerContainer=r.create("div","mapboxgl-ctrl-attrib-inner",this._container),this._innerContainer.setAttribute("role","list"),e&&this._container.classList.add("mapboxgl-compact"),this._updateAttributions(),this._updateEditLink(),this._map.on("styledata",this._updateData),this._map.on("sourcedata",this._updateData),this._map.on("moveend",this._updateEditLink),void 0===e&&(this._map.on("resize",this._updateCompact),this._updateCompact()),this._container},Mi.prototype.onRemove=function(){r.remove(this._container),this._map.off("styledata",this._updateData),this._map.off("sourcedata",this._updateData),this._map.off("moveend",this._updateEditLink),this._map.off("resize",this._updateCompact),this._map=void 0,this._attribHTML=void 0},Mi.prototype._setElementTitle=function(t,e){var r=this._map._getUIString("AttributionControl."+e);t.title=r,t.setAttribute("aria-label",r)},Mi.prototype._toggleAttribution=function(){this._container.classList.contains("mapboxgl-compact-show")?(this._container.classList.remove("mapboxgl-compact-show"),this._compactButton.setAttribute("aria-pressed","false")):(this._container.classList.add("mapboxgl-compact-show"),this._compactButton.setAttribute("aria-pressed","true"))},Mi.prototype._updateEditLink=function(){var e=this._editLink;e||(e=this._editLink=this._container.querySelector(".mapbox-improve-map"));var r=[{key:"owner",value:this.styleOwner},{key:"id",value:this.styleId},{key:"access_token",value:this._map._requestManager._customAccessToken||t.config.ACCESS_TOKEN}];if(e){var n=r.reduce((function(t,e,n){return e.value&&(t+=e.key+"="+e.value+(n=0)return!1;return!0}))).join(" | ");o!==this._attribHTML&&(this._attribHTML=o,t.length?(this._innerContainer.innerHTML=o,this._container.classList.remove("mapboxgl-attrib-empty")):this._container.classList.add("mapboxgl-attrib-empty"),this._editLink=null)}},Mi.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add("mapboxgl-compact"):this._container.classList.remove("mapboxgl-compact","mapboxgl-compact-show")};var Si=function(){t.bindAll(["_updateLogo"],this),t.bindAll(["_updateCompact"],this)};Si.prototype.onAdd=function(t){this._map=t,this._container=r.create("div","mapboxgl-ctrl");var e=r.create("a","mapboxgl-ctrl-logo");return e.target="_blank",e.rel="noopener nofollow",e.href="https://www.mapbox.com/",e.setAttribute("aria-label",this._map._getUIString("LogoControl.Title")),e.setAttribute("rel","noopener nofollow"),this._container.appendChild(e),this._container.style.display="none",this._map.on("sourcedata",this._updateLogo),this._updateLogo(),this._map.on("resize",this._updateCompact),this._updateCompact(),this._container},Si.prototype.onRemove=function(){r.remove(this._container),this._map.off("sourcedata",this._updateLogo),this._map.off("resize",this._updateCompact)},Si.prototype.getDefaultPosition=function(){return"bottom-left"},Si.prototype._updateLogo=function(t){(!t||"metadata"===t.sourceDataType)&&(this._container.style.display=this._logoRequired()?"block":"none")},Si.prototype._logoRequired=function(){if(this._map.style){var t=this._map.style.sourceCaches;for(var e in t)if(t[e].getSource().mapbox_logo)return!0;return!1}},Si.prototype._updateCompact=function(){var t=this._container.children;if(t.length){var e=t[0];this._map.getCanvasContainer().offsetWidth<250?e.classList.add("mapboxgl-compact"):e.classList.remove("mapboxgl-compact")}};var Ei=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};Ei.prototype.add=function(t){var e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e},Ei.prototype.remove=function(t){for(var e=this._currentlyRunning,r=0,n=e?this._queue.concat(e):this._queue;re.maxZoom)throw new Error("maxZoom must be greater than or equal to minZoom");if(null!=e.minPitch&&null!=e.maxPitch&&e.minPitch>e.maxPitch)throw new Error("maxPitch must be greater than or equal to minPitch");if(null!=e.minPitch&&e.minPitch<0)throw new Error("minPitch must be greater than or equal to 0");if(null!=e.maxPitch&&e.maxPitch>60)throw new Error("maxPitch must be less than or equal to 60");var i=new En(e.minZoom,e.maxZoom,e.minPitch,e.maxPitch,e.renderWorldCopies);if(n.call(this,i,e),this._interactive=e.interactive,this._maxTileCacheSize=e.maxTileCacheSize,this._failIfMajorPerformanceCaveat=e.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=e.preserveDrawingBuffer,this._antialias=e.antialias,this._trackResize=e.trackResize,this._bearingSnap=e.bearingSnap,this._refreshExpiredTiles=e.refreshExpiredTiles,this._fadeDuration=e.fadeDuration,this._crossSourceCollisions=e.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=e.collectResourceTiming,this._renderTaskQueue=new Ei,this._controls=[],this._mapId=t.uniqueId(),this._locale=t.extend({},Ci,e.locale),this._clickTolerance=e.clickTolerance,this._requestManager=new t.RequestManager(e.transformRequest,e.accessToken),"string"==typeof e.container){if(this._container=t.window.document.getElementById(e.container),!this._container)throw new Error("Container '"+e.container+"' not found.")}else{if(!(e.container instanceof Li))throw new Error("Invalid type: 'container' must be a String or HTMLElement.");this._container=e.container}if(e.maxBounds&&this.setMaxBounds(e.maxBounds),t.bindAll(["_onWindowOnline","_onWindowResize","_onMapScroll","_contextLost","_contextRestored"],this),this._setupContainer(),this._setupPainter(),void 0===this.painter)throw new Error("Failed to initialize WebGL.");this.on("move",(function(){return r._update(!1)})),this.on("moveend",(function(){return r._update(!1)})),this.on("zoom",(function(){return r._update(!0)})),typeof t.window<"u"&&(t.window.addEventListener("online",this._onWindowOnline,!1),t.window.addEventListener("resize",this._onWindowResize,!1),t.window.addEventListener("orientationchange",this._onWindowResize,!1)),this.handlers=new ki(this,e);var a="string"==typeof e.hash&&e.hash||void 0;this._hash=e.hash&&new In(a).addTo(this),(!this._hash||!this._hash._onHashChange())&&(this.jumpTo({center:e.center,zoom:e.zoom,bearing:e.bearing,pitch:e.pitch}),e.bounds&&(this.resize(),this.fitBounds(e.bounds,t.extend({},e.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=e.localIdeographFontFamily,e.style&&this.setStyle(e.style,{localIdeographFontFamily:e.localIdeographFontFamily}),e.attributionControl&&this.addControl(new Mi({customAttribution:e.customAttribution})),this.addControl(new Si,e.logoPosition),this.on("style.load",(function(){r.transform.unmodified&&r.jumpTo(r.style.stylesheet)})),this.on("data",(function(e){r._update("style"===e.dataType),r.fire(new t.Event(e.dataType+"data",e))})),this.on("dataloading",(function(e){r.fire(new t.Event(e.dataType+"dataloading",e))}))}n&&(i.__proto__=n),i.prototype=Object.create(n&&n.prototype),i.prototype.constructor=i;var a={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return i.prototype._getMapId=function(){return this._mapId},i.prototype.addControl=function(e,r){if(void 0===r&&(r=e.getDefaultPosition?e.getDefaultPosition():"top-right"),!e||!e.onAdd)return this.fire(new t.ErrorEvent(new Error("Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.")));var n=e.onAdd(this);this._controls.push(e);var i=this._controlPositions[r];return-1!==r.indexOf("bottom")?i.insertBefore(n,i.firstChild):i.appendChild(n),this},i.prototype.removeControl=function(e){if(!e||!e.onRemove)return this.fire(new t.ErrorEvent(new Error("Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.")));var r=this._controls.indexOf(e);return r>-1&&this._controls.splice(r,1),e.onRemove(this),this},i.prototype.hasControl=function(t){return this._controls.indexOf(t)>-1},i.prototype.resize=function(e){var r=this._containerDimensions(),n=r[0],i=r[1];this._resizeCanvas(n,i),this.transform.resize(n,i),this.painter.resize(n,i);var a=!this._moving;return a&&(this.stop(),this.fire(new t.Event("movestart",e)).fire(new t.Event("move",e))),this.fire(new t.Event("resize",e)),a&&this.fire(new t.Event("moveend",e)),this},i.prototype.getBounds=function(){return this.transform.getBounds()},i.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},i.prototype.setMaxBounds=function(e){return this.transform.setMaxBounds(t.LngLatBounds.convert(e)),this._update()},i.prototype.setMinZoom=function(t){if((t=t??-2)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error("maxZoom must be greater than the current minZoom")},i.prototype.getMaxZoom=function(){return this.transform.maxZoom},i.prototype.setMinPitch=function(t){if((t=t??0)<0)throw new Error("minPitch must be greater than or equal to 0");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()60)throw new Error("maxPitch must be less than or equal to 60");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error("maxPitch must be greater than the current minPitch")},i.prototype.getMaxPitch=function(){return this.transform.maxPitch},i.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},i.prototype.setRenderWorldCopies=function(t){return this.transform.renderWorldCopies=t,this._update()},i.prototype.project=function(e){return this.transform.locationPoint(t.LngLat.convert(e))},i.prototype.unproject=function(e){return this.transform.pointLocation(t.Point.convert(e))},i.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},i.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},i.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},i.prototype._createDelegatedListener=function(t,e,r){var n,i=this;if("mouseenter"===t||"mouseover"===t){var a=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){var o=i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[];o.length?a||(a=!0,r.call(i,new jn(t,i,n.originalEvent,{features:o}))):a=!1},mouseout:function(){a=!1}}}}if("mouseleave"===t||"mouseout"===t){var o=!1;return{layer:e,listener:r,delegates:{mousemove:function(n){(i.getLayer(e)?i.queryRenderedFeatures(n.point,{layers:[e]}):[]).length?o=!0:o&&(o=!1,r.call(i,new jn(t,i,n.originalEvent)))},mouseout:function(e){o&&(o=!1,r.call(i,new jn(t,i,e.originalEvent)))}}}}return{layer:e,listener:r,delegates:(n={},n[t]=function(t){var n=i.getLayer(e)?i.queryRenderedFeatures(t.point,{layers:[e]}):[];n.length&&(t.features=n,r.call(i,t),delete t.features)},n)}},i.prototype.on=function(t,e,r){if(void 0===r)return n.prototype.on.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(i),i.delegates)this.on(a,i.delegates[a]);return this},i.prototype.once=function(t,e,r){if(void 0===r)return n.prototype.once.call(this,t,e);var i=this._createDelegatedListener(t,e,r);for(var a in i.delegates)this.once(a,i.delegates[a]);return this},i.prototype.off=function(t,e,r){var i=this;return void 0===r?n.prototype.off.call(this,t,e):(this._delegatedListeners&&this._delegatedListeners[t]&&function(n){for(var a=n[t],o=0;o180;){var s=n.locationPoint(e);if(s.x>=0&&s.y>=0&&s.x<=n.width&&s.y<=n.height)break;e.lng>n.center.lng?e.lng-=360:e.lng+=360}return e}Bi.prototype.down=function(t,e){this.mouseRotate.mousedown(t,e),this.mousePitch&&this.mousePitch.mousedown(t,e),r.disableDrag()},Bi.prototype.move=function(t,e){var r=this.map,n=this.mouseRotate.mousemoveWindow(t,e);if(n&&n.bearingDelta&&r.setBearing(r.getBearing()+n.bearingDelta),this.mousePitch){var i=this.mousePitch.mousemoveWindow(t,e);i&&i.pitchDelta&&r.setPitch(r.getPitch()+i.pitchDelta)}},Bi.prototype.off=function(){var t=this.element;r.removeEventListener(t,"mousedown",this.mousedown),r.removeEventListener(t,"touchstart",this.touchstart,{passive:!1}),r.removeEventListener(t,"touchmove",this.touchmove),r.removeEventListener(t,"touchend",this.touchend),r.removeEventListener(t,"touchcancel",this.reset),this.offTemp()},Bi.prototype.offTemp=function(){r.enableDrag(),r.removeEventListener(t.window,"mousemove",this.mousemove),r.removeEventListener(t.window,"mouseup",this.mouseup)},Bi.prototype.mousedown=function(e){this.down(t.extend({},e,{ctrlKey:!0,preventDefault:function(){return e.preventDefault()}}),r.mousePos(this.element,e)),r.addEventListener(t.window,"mousemove",this.mousemove),r.addEventListener(t.window,"mouseup",this.mouseup)},Bi.prototype.mousemove=function(t){this.move(t,r.mousePos(this.element,t))},Bi.prototype.mouseup=function(t){this.mouseRotate.mouseupWindow(t),this.mousePitch&&this.mousePitch.mouseupWindow(t),this.offTemp()},Bi.prototype.touchstart=function(t){1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.down({type:"mousedown",button:0,ctrlKey:!0,preventDefault:function(){return t.preventDefault()}},this._startPos))},Bi.prototype.touchmove=function(t){1!==t.targetTouches.length?this.reset():(this._lastPos=r.touchPos(this.element,t.targetTouches)[0],this.move({preventDefault:function(){return t.preventDefault()}},this._lastPos))},Bi.prototype.touchend=function(t){0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos)=r}this._isDragging&&(this._pos=e.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents="none","pending"===this._state&&(this._state="active",this.fire(new t.Event("dragstart"))),this.fire(new t.Event("drag")))},n.prototype._onUp=function(){this._element.style.pointerEvents="auto",this._positionDelta=null,this._pointerdownPos=null,this._isDragging=!1,this._map.off("mousemove",this._onMove),this._map.off("touchmove",this._onMove),"active"===this._state&&this.fire(new t.Event("dragend")),this._state="inactive"},n.prototype._addDragHandler=function(t){this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._pointerdownPos=t.point,this._state="pending",this._map.on("mousemove",this._onMove),this._map.on("touchmove",this._onMove),this._map.once("mouseup",this._onUp),this._map.once("touchend",this._onUp))},n.prototype.setDraggable=function(t){return this._draggable=!!t,this._map&&(t?(this._map.on("mousedown",this._addDragHandler),this._map.on("touchstart",this._addDragHandler)):(this._map.off("mousedown",this._addDragHandler),this._map.off("touchstart",this._addDragHandler))),this},n.prototype.isDraggable=function(){return this._draggable},n.prototype.setRotation=function(t){return this._rotation=t||0,this._update(),this},n.prototype.getRotation=function(){return this._rotation},n.prototype.setRotationAlignment=function(t){return this._rotationAlignment=t||"auto",this._update(),this},n.prototype.getRotationAlignment=function(){return this._rotationAlignment},n.prototype.setPitchAlignment=function(t){return this._pitchAlignment=t&&"auto"!==t?t:this._rotationAlignment,this._update(),this},n.prototype.getPitchAlignment=function(){return this._pitchAlignment},n}(t.Evented),Hi={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0},Gi=0,Wi=!1,Zi=function(e){function n(r){e.call(this),this.options=t.extend({},Hi,r),t.bindAll(["_onSuccess","_onError","_onZoom","_finish","_setupUI","_updateCamera","_updateMarker"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.onAdd=function(e){return this._map=e,this._container=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-group"),function(e){void 0!==Vi?e(Vi):void 0!==t.window.navigator.permissions?t.window.navigator.permissions.query({name:"geolocation"}).then((function(t){Vi="denied"!==t.state,e(Vi)})):(Vi=!!t.window.navigator.geolocation,e(Vi))}(this._setupUI),this._container},n.prototype.onRemove=function(){void 0!==this._geolocationWatchID&&(t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),r.remove(this._container),this._map.off("zoom",this._onZoom),this._map=void 0,Gi=0,Wi=!1},n.prototype._isOutOfMapMaxBounds=function(t){var e=this._map.getMaxBounds(),r=t.coords;return e&&(r.longitudee.getEast()||r.latitudee.getNorth())},n.prototype._setErrorState=function(){switch(this._watchState){case"WAITING_ACTIVE":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active-error");break;case"ACTIVE_LOCK":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting");break;case"BACKGROUND":this._watchState="BACKGROUND_ERROR",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting")}},n.prototype._onSuccess=function(e){if(this._map){if(this._isOutOfMapMaxBounds(e))return this._setErrorState(),this.fire(new t.Event("outofmaxbounds",e)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=e,this._watchState){case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active");break;case"BACKGROUND":case"BACKGROUND_ERROR":this._watchState="BACKGROUND",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background")}this.options.showUserLocation&&"OFF"!==this._watchState&&this._updateMarker(e),(!this.options.trackUserLocation||"ACTIVE_LOCK"===this._watchState)&&this._updateCamera(e),this.options.showUserLocation&&this._dotElement.classList.remove("mapboxgl-user-location-dot-stale"),this.fire(new t.Event("geolocate",e)),this._finish()}},n.prototype._updateCamera=function(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude),n=e.coords.accuracy,i=this._map.getBearing(),a=t.extend({bearing:i},this.options.fitBoundsOptions);this._map.fitBounds(r.toBounds(n),a,{geolocateSource:!0})},n.prototype._updateMarker=function(e){if(e){var r=new t.LngLat(e.coords.longitude,e.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=e.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},n.prototype._updateCircleRadius=function(){var t=this._map._container.clientHeight/2,e=this._map.unproject([0,t]),r=this._map.unproject([1,t]),n=e.distanceTo(r),i=Math.ceil(2*this._accuracy/n);this._circleElement.style.width=i+"px",this._circleElement.style.height=i+"px"},n.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},n.prototype._onError=function(e){if(this._map){if(this.options.trackUserLocation)if(1===e.code){this._watchState="OFF",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background-error"),this._geolocateButton.disabled=!0;var r=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.title=r,this._geolocateButton.setAttribute("aria-label",r),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===e.code&&Wi)return;this._setErrorState()}"OFF"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add("mapboxgl-user-location-dot-stale"),this.fire(new t.Event("error",e)),this._finish()}},n.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},n.prototype._setupUI=function(e){var n=this;if(this._container.addEventListener("contextmenu",(function(t){return t.preventDefault()})),this._geolocateButton=r.create("button","mapboxgl-ctrl-geolocate",this._container),r.create("span","mapboxgl-ctrl-icon",this._geolocateButton).setAttribute("aria-hidden",!0),this._geolocateButton.type="button",!1===e){t.warnOnce("Geolocation support is not available so the GeolocateControl will be disabled.");var i=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.disabled=!0,this._geolocateButton.title=i,this._geolocateButton.setAttribute("aria-label",i)}else{var a=this._map._getUIString("GeolocateControl.FindMyLocation");this._geolocateButton.title=a,this._geolocateButton.setAttribute("aria-label",a)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute("aria-pressed","false"),this._watchState="OFF"),this.options.showUserLocation&&(this._dotElement=r.create("div","mapboxgl-user-location-dot"),this._userLocationDotMarker=new qi(this._dotElement),this._circleElement=r.create("div","mapboxgl-user-location-accuracy-circle"),this._accuracyCircleMarker=new qi({element:this._circleElement,pitchAlignment:"map"}),this.options.trackUserLocation&&(this._watchState="OFF"),this._map.on("zoom",this._onZoom)),this._geolocateButton.addEventListener("click",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on("movestart",(function(e){var r=e.originalEvent&&"resize"===e.originalEvent.type;!e.geolocateSource&&"ACTIVE_LOCK"===n._watchState&&!r&&(n._watchState="BACKGROUND",n._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background"),n._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),n.fire(new t.Event("trackuserlocationend")))}))},n.prototype.trigger=function(){if(!this._setup)return t.warnOnce("Geolocate control triggered before added to a map"),!1;if(this.options.trackUserLocation){switch(this._watchState){case"OFF":this._watchState="WAITING_ACTIVE",this.fire(new t.Event("trackuserlocationstart"));break;case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":case"BACKGROUND_ERROR":Gi--,Wi=!1,this._watchState="OFF",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background-error"),this.fire(new t.Event("trackuserlocationend"));break;case"BACKGROUND":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.Event("trackuserlocationstart"))}switch(this._watchState){case"WAITING_ACTIVE":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active");break;case"ACTIVE_LOCK":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active");break;case"ACTIVE_ERROR":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active-error");break;case"BACKGROUND":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background");break;case"BACKGROUND_ERROR":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background-error")}if("OFF"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){var e;this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","true"),++Gi>1?(e={maximumAge:6e5,timeout:0},Wi=!0):(e=this.options.positionOptions,Wi=!1),this._geolocationWatchID=t.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,e)}}else t.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},n.prototype._clearWatch=function(){t.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","false"),this.options.showUserLocation&&this._updateMarker(null)},n}(t.Evented),Yi={maxWidth:100,unit:"metric"},Xi=function(e){this.options=t.extend({},Yi,e),t.bindAll(["_onMove","setUnit"],this)};function $i(t,e,r){var n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&"imperial"===r.unit){var l=3.2808*s;l>5280?Ki(e,n,l/5280,t._getUIString("ScaleControl.Miles")):Ki(e,n,l,t._getUIString("ScaleControl.Feet"))}else r&&"nautical"===r.unit?Ki(e,n,s/1852,t._getUIString("ScaleControl.NauticalMiles")):s>=1e3?Ki(e,n,s/1e3,t._getUIString("ScaleControl.Kilometers")):Ki(e,n,s,t._getUIString("ScaleControl.Meters"))}function Ki(t,e,r,n){var i=function(t){var e=Math.pow(10,(""+Math.floor(t)).length-1),r=t/e;return r=r>=10?10:r>=5?5:r>=3?3:r>=2?2:r>=1?1:function(t){var e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(r),e*r}(r),a=i/r;t.style.width=e*a+"px",t.innerHTML=i+" "+n}Xi.prototype.getDefaultPosition=function(){return"bottom-left"},Xi.prototype._onMove=function(){$i(this._map,this._container,this.options)},Xi.prototype.onAdd=function(t){return this._map=t,this._container=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-scale",t.getContainer()),this._map.on("move",this._onMove),this._onMove(),this._container},Xi.prototype.onRemove=function(){r.remove(this._container),this._map.off("move",this._onMove),this._map=void 0},Xi.prototype.setUnit=function(t){this.options.unit=t,$i(this._map,this._container,this.options)};var Ji=function(e){this._fullscreen=!1,e&&e.container&&(e.container instanceof t.window.HTMLElement?this._container=e.container:t.warnOnce("Full screen control 'container' must be a DOM element.")),t.bindAll(["_onClickFullscreen","_changeIcon"],this),"onfullscreenchange"in t.window.document?this._fullscreenchange="fullscreenchange":"onmozfullscreenchange"in t.window.document?this._fullscreenchange="mozfullscreenchange":"onwebkitfullscreenchange"in t.window.document?this._fullscreenchange="webkitfullscreenchange":"onmsfullscreenchange"in t.window.document&&(this._fullscreenchange="MSFullscreenChange")};Ji.prototype.onAdd=function(e){return this._map=e,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-group"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display="none",t.warnOnce("This device does not support fullscreen mode.")),this._controlContainer},Ji.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,t.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},Ji.prototype._checkFullscreenSupport=function(){return!!(t.window.document.fullscreenEnabled||t.window.document.mozFullScreenEnabled||t.window.document.msFullscreenEnabled||t.window.document.webkitFullscreenEnabled)},Ji.prototype._setupUI=function(){var e=this._fullscreenButton=r.create("button","mapboxgl-ctrl-fullscreen",this._controlContainer);r.create("span","mapboxgl-ctrl-icon",e).setAttribute("aria-hidden",!0),e.type="button",this._updateTitle(),this._fullscreenButton.addEventListener("click",this._onClickFullscreen),t.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},Ji.prototype._updateTitle=function(){var t=this._getTitle();this._fullscreenButton.setAttribute("aria-label",t),this._fullscreenButton.title=t},Ji.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?"FullscreenControl.Exit":"FullscreenControl.Enter")},Ji.prototype._isFullscreen=function(){return this._fullscreen},Ji.prototype._changeIcon=function(){(t.window.document.fullscreenElement||t.window.document.mozFullScreenElement||t.window.document.webkitFullscreenElement||t.window.document.msFullscreenElement)===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle("mapboxgl-ctrl-shrink"),this._fullscreenButton.classList.toggle("mapboxgl-ctrl-fullscreen"),this._updateTitle())},Ji.prototype._onClickFullscreen=function(){this._isFullscreen()?t.window.document.exitFullscreen?t.window.document.exitFullscreen():t.window.document.mozCancelFullScreen?t.window.document.mozCancelFullScreen():t.window.document.msExitFullscreen?t.window.document.msExitFullscreen():t.window.document.webkitCancelFullScreen&&t.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var Qi={closeButton:!0,closeOnClick:!0,focusAfterOpen:!0,className:"",maxWidth:"240px"},ta=["a[href]","[tabindex]:not([tabindex='-1'])","[contenteditable]:not([contenteditable='false'])","button:not([disabled])","input:not([disabled])","select:not([disabled])","textarea:not([disabled])"].join(", "),ea=function(e){function n(r){e.call(this),this.options=t.extend(Object.create(Qi),r),t.bindAll(["_update","_onClose","remove","_onMouseMove","_onMouseUp","_onDrag"],this)}return e&&(n.__proto__=e),n.prototype=Object.create(e&&e.prototype),n.prototype.constructor=n,n.prototype.addTo=function(e){return this._map&&this.remove(),this._map=e,this.options.closeOnClick&&this._map.on("click",this._onClose),this.options.closeOnMove&&this._map.on("move",this._onClose),this._map.on("remove",this.remove),this._update(),this._focusFirstElement(),this._trackPointer?(this._map.on("mousemove",this._onMouseMove),this._map.on("mouseup",this._onMouseUp),this._container&&this._container.classList.add("mapboxgl-popup-track-pointer"),this._map._canvasContainer.classList.add("mapboxgl-track-pointer")):this._map.on("move",this._update),this.fire(new t.Event("open")),this},n.prototype.isOpen=function(){return!!this._map},n.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off("move",this._update),this._map.off("move",this._onClose),this._map.off("click",this._onClose),this._map.off("remove",this.remove),this._map.off("mousemove",this._onMouseMove),this._map.off("mouseup",this._onMouseUp),this._map.off("drag",this._onDrag),delete this._map),this.fire(new t.Event("close")),this},n.prototype.getLngLat=function(){return this._lngLat},n.prototype.setLngLat=function(e){return this._lngLat=t.LngLat.convert(e),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on("move",this._update),this._map.off("mousemove",this._onMouseMove),this._container&&this._container.classList.remove("mapboxgl-popup-track-pointer"),this._map._canvasContainer.classList.remove("mapboxgl-track-pointer")),this},n.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off("move",this._update),this._map.on("mousemove",this._onMouseMove),this._map.on("drag",this._onDrag),this._container&&this._container.classList.add("mapboxgl-popup-track-pointer"),this._map._canvasContainer.classList.add("mapboxgl-track-pointer")),this},n.prototype.getElement=function(){return this._container},n.prototype.setText=function(e){return this.setDOMContent(t.window.document.createTextNode(e))},n.prototype.setHTML=function(e){var r,n=t.window.document.createDocumentFragment(),i=t.window.document.createElement("body");for(i.innerHTML=e;r=i.firstChild;)n.appendChild(r);return this.setDOMContent(n)},n.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},n.prototype.setMaxWidth=function(t){return this.options.maxWidth=t,this._update(),this},n.prototype.setDOMContent=function(t){if(this._content)for(;this._content.hasChildNodes();)this._content.firstChild&&this._content.removeChild(this._content.firstChild);else this._content=r.create("div","mapboxgl-popup-content",this._container);return this._content.appendChild(t),this._createCloseButton(),this._update(),this._focusFirstElement(),this},n.prototype.addClassName=function(t){this._container&&this._container.classList.add(t)},n.prototype.removeClassName=function(t){this._container&&this._container.classList.remove(t)},n.prototype.setOffset=function(t){return this.options.offset=t,this._update(),this},n.prototype.toggleClassName=function(t){if(this._container)return this._container.classList.toggle(t)},n.prototype._createCloseButton=function(){this.options.closeButton&&(this._closeButton=r.create("button","mapboxgl-popup-close-button",this._content),this._closeButton.type="button",this._closeButton.setAttribute("aria-label","Close 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e._container.classList.add(t)})),this._trackPointer&&this._container.classList.add("mapboxgl-popup-track-pointer")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=ji(this._lngLat,this._pos,this._map.transform)),!this._trackPointer||t)){var i=this._pos=this._trackPointer&&t?t:this._map.project(this._lngLat),a=this.options.anchor,o=ra(this.options.offset);if(!a){var s,l=this._container.offsetWidth,c=this._container.offsetHeight;s=i.y+o.bottom.ythis._map.transform.height-c?["bottom"]:[],i.xthis._map.transform.width-l/2&&s.push("right"),a=0===s.length?"bottom":s.join("-")}var u=i.add(o[a]).round();r.setTransform(this._container,Ni[a]+" translate("+u.x+"px,"+u.y+"px)"),Ui(this._container,a,"popup")}},n.prototype._focusFirstElement=function(){if(this.options.focusAfterOpen&&this._container){var t=this._container.querySelector(ta);t&&t.focus()}},n.prototype._onClose=function(){this.remove()},n}(t.Evented);function ra(e){if(e){if("number"==typeof e){var r=Math.round(Math.sqrt(.5*Math.pow(e,2)));return{center:new t.Point(0,0),top:new t.Point(0,e),"top-left":new t.Point(r,r),"top-right":new t.Point(-r,r),bottom:new t.Point(0,-e),"bottom-left":new t.Point(r,-r),"bottom-right":new t.Point(-r,-r),left:new t.Point(e,0),right:new t.Point(-e,0)}}if(e instanceof t.Point||Array.isArray(e)){var 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a=t.symbol,o=i(a.textposition,a.iconsize);r.extendFlat(e,{"icon-image":a.icon+"-15","icon-size":a.iconsize/10,"text-field":a.text,"text-size":a.textfont.size,"text-anchor":o.anchor,"text-offset":o.offset,"symbol-placement":a.placement}),r.extendFlat(n,{"icon-color":t.color,"text-color":a.textfont.color,"text-opacity":t.opacity});break;case"raster":r.extendFlat(n,{"raster-fade-duration":0,"raster-opacity":t.opacity})}return{layout:e,paint:n}}s.update=function(t){this.visible?this.needsNewImage(t)?this.updateImage(t):this.needsNewSource(t)?(this.removeLayer(),this.updateSource(t),this.updateLayer(t)):this.needsNewLayer(t)?this.updateLayer(t):this.updateStyle(t):(this.updateSource(t),this.updateLayer(t)),this.visible=l(t)},s.needsNewImage=function(t){return this.subplot.map.getSource(this.idSource)&&"image"===this.sourceType&&"image"===t.sourcetype&&(this.source!==t.source||JSON.stringify(this.coordinates)!==JSON.stringify(t.coordinates))},s.needsNewSource=function(t){return this.sourceType!==t.sourcetype||JSON.stringify(this.source)!==JSON.stringify(t.source)||this.layerType!==t.type},s.needsNewLayer=function(t){return this.layerType!==t.type||this.below!==this.subplot.belowLookup["layout-"+this.index]},s.lookupBelow=function(){return this.subplot.belowLookup["layout-"+this.index]},s.updateImage=function(t){this.subplot.map.getSource(this.idSource).updateImage({url:t.source,coordinates:t.coordinates});var e=this.findFollowingMapboxLayerId(this.lookupBelow());null!==e&&this.subplot.map.moveLayer(this.idLayer,e)},s.updateSource=function(t){var e=this.subplot.map;if(e.getSource(this.idSource)&&e.removeSource(this.idSource),this.sourceType=t.sourcetype,this.source=t.source,l(t)){var r=function(t){var e,r=t.sourcetype,i=t.source,a={type:r};return"geojson"===r?e="data":"vector"===r?e="string"==typeof 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l=e.dragOptions;e.dragOptions=n.extendDeep(l||{},{dragmode:t.dragmode,element:e.div,gd:i,plotinfo:{id:e.id,domain:t[e.id].domain,xaxis:e.xaxis,yaxis:e.yaxis,fillRangeItems:a},xaxes:[e.xaxis],yaxes:[e.yaxis],subplot:e.id}),r.off("click",e.onClickInPanHandler),h(o)||u(o)?(r.dragPan.disable(),r.on("zoomstart",e.clearOutline),e.dragOptions.prepFn=function(t,r,n){f(t,r,n,e.dragOptions,o)},s.init(e.dragOptions)):(r.dragPan.enable(),r.off("zoomstart",e.clearOutline),e.div.onmousedown=null,e.div.ontouchstart=null,e.div.removeEventListener("touchstart",e.div._ontouchstart),e.onClickInPanHandler=e.onClickInPanFn(e.dragOptions),r.on("click",e.onClickInPanHandler))}function c(t){var r=e.map.unproject(t);return[r.lng,r.lat]}},x.updateFramework=function(t){var e=t[this.id].domain,r=t._size,n=this.div.style;n.width=r.w*(e.x[1]-e.x[0])+"px",n.height=r.h*(e.y[1]-e.y[0])+"px",n.left=r.l+e.x[0]*r.w+"px",n.top=r.t+(1-e.y[1])*r.h+"px",this.xaxis._offset=r.l+e.x[0]*r.w,this.xaxis._length=r.w*(e.x[1]-e.x[0]),this.yaxis._offset=r.t+(1-e.y[1])*r.h,this.yaxis._length=r.h*(e.y[1]-e.y[0])},x.updateLayers=function(t){var e,r=t[this.id].layers,n=this.layerList;if(r.length!==n.length){for(e=0;e1&&r.warn(f.multipleTokensErrorMsg),i[0]):(a.length&&r.log(["Listed mapbox access token(s)",a.join(","),"but did not use a Mapbox map style, ignoring token(s)."].join(" ")),"")}(t,o);e.accessToken=s;for(var l=0;lw/2){var T=v.split("|").join("
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t.map.addSource(o,{type:"geojson",data:s.geojson}),a._addLayers(s,l),a}}}),ib=m({"src/traces/densitymapbox/hover.js"(t,e){var r=ar(),n=F_().hoverPoints,i=F_().getExtraText;e.exports=function(t,e,a){var o=n(t,e,a);if(o){var s=o[0],l=s.cd,c=l[0].trace,u=l[s.index];if(delete s.color,"z"in u){var h=s.subplot.mockAxis;s.z=u.z,s.zLabel=r.tickText(h,h.c2l(u.z),"hover").text}return s.extraText=i(c,u,l[0].t.labels),[s]}}}}),ab=m({"src/traces/densitymapbox/event_data.js"(t,e){e.exports=function(t,e){return t.lon=e.lon,t.lat=e.lat,t.z=e.z,t}}}),ob=m({"src/traces/densitymapbox/index.js"(t,e){["*densitymapbox* trace is deprecated!","Please consider switching to the *densitymap* trace type and `map` subplots.","Learn more at: https://plotly.com/python/maplibre-migration/","as well as https://plotly.com/javascript/maplibre-migration/"].join(" 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r=e.getMapLayers(),n=0;nESRI"},ortoInstaMaps:{type:"raster",tiles:["https://tilemaps.icgc.cat/mapfactory/wmts/orto_8_12/CAT3857/{z}/{x}/{y}.png"],tileSize:256,maxzoom:13},ortoICGC:{type:"raster",tiles:["https://geoserveis.icgc.cat/icc_mapesmultibase/noutm/wmts/orto/GRID3857/{z}/{x}/{y}.jpeg"],tileSize:256,minzoom:13.1,maxzoom:20},openmaptiles:{type:"vector",url:"https://geoserveis.icgc.cat/contextmaps/basemap.json"}},sprite:"https://geoserveis.icgc.cat/contextmaps/sprites/sprite@1",glyphs:"https://geoserveis.icgc.cat/contextmaps/glyphs/{fontstack}/{range}.pbf",layers:[{id:"background",type:"background",paint:{"background-color":"#F4F9F4"}},{id:"ortoEsri",type:"raster",source:"ortoEsri",maxzoom:16,layout:{visibility:"visible"}},{id:"ortoICGC",type:"raster",source:"ortoICGC",minzoom:13.1,maxzoom:19,layout:{visibility:"visible"}},{id:"ortoInstaMaps",type:"raster",source:"ortoInstaMaps",maxzoom:13,layout:{visibility:"visible"}},{id:"waterway_tunnel",type:"line",source:"openmaptiles","source-layer":"waterway",minzoom:14,filter:["all",["in","class","river","stream","canal"],["==","brunnel","tunnel"]],layout:{"line-cap":"round"},paint:{"line-color":"#a0c8f0","line-width":{base:1.3,stops:[[13,.5],[20,6]]},"line-dasharray":[2,4]}},{id:"waterway-other",type:"line",metadata:{"mapbox:group":"1444849382550.77"},source:"openmaptiles","source-layer":"waterway",filter:["!in","class","canal","river","stream"],layout:{"line-cap":"round"},paint:{"line-color":"#a0c8f0","line-width":{base:1.3,stops:[[13,.5],[20,2]]}}},{id:"waterway-stream-canal",type:"line",metadata:{"mapbox:group":"1444849382550.77"},source:"openmaptiles","source-layer":"waterway",filter:["all",["in","class","canal","stream"],["!=","brunnel","tunnel"]],layout:{"line-cap":"round"},paint:{"line-color":"#a0c8f0","line-width":{base:1.3,stops:[[13,.5],[20,6]]}}},{id:"waterway-river",type:"line",metadata:{"mapbox:group":"1444849382550.77"},source:"openmaptiles","source-layer":"waterway",filter:["all",["==","class","river"],["!=","brunnel","tunnel"]],layout:{"line-cap":"round"},paint:{"line-color":"#a0c8f0","line-width":{base:1.2,stops:[[10,.8],[20,4]]},"line-opacity":.5}},{id:"water-offset",type:"fill",metadata:{"mapbox:group":"1444849382550.77"},source:"openmaptiles","source-layer":"water",maxzoom:8,filter:["==","$type","Polygon"],layout:{visibility:"visible"},paint:{"fill-opacity":0,"fill-color":"#a0c8f0","fill-translate":{base:1,stops:[[6,[2,0]],[8,[0,0]]]}}},{id:"water",type:"fill",metadata:{"mapbox:group":"1444849382550.77"},source:"openmaptiles","source-layer":"water",layout:{visibility:"visible"},paint:{"fill-color":"hsl(210, 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Xt{constructor(t,e,r,n=1,i=!0){this.r=t,this.g=e,this.b=r,this.a=n,i||(this.r*=n,this.g*=n,this.b*=n,n||this.overwriteGetter("rgb",[t,e,r,n]))}static parse(t){if(t instanceof Xt)return t;if("string"!=typeof t)return;let e=function(t){if("transparent"===(t=t.toLowerCase().trim()))return[0,0,0,0];let e=Yt[t];if(e){let[t,r,n]=e;return[t/255,r/255,n/255,1]}if(t.startsWith("#")&&/^#(?:[0-9a-f]{3,4}|[0-9a-f]{6}|[0-9a-f]{8})$/.test(t)){let e=t.length<6?1:2,r=1;return[Ht(t.slice(r,r+=e)),Ht(t.slice(r,r+=e)),Ht(t.slice(r,r+=e)),Ht(t.slice(r,r+e)||"ff")]}if(t.startsWith("rgb")){let e=t.match(/^rgba?\(\s*([\de.+-]+)(%)?(?:\s+|\s*(,)\s*)([\de.+-]+)(%)?(?:\s+|\s*(,)\s*)([\de.+-]+)(%)?(?:\s*([,\/])\s*([\de.+-]+)(%)?)?\s*\)$/);if(e){let[t,r,n,i,a,o,s,l,c,u,h,f]=e,p=[i||" ",s||" ",u].join("");if(" "===p||" /"===p||",,"===p||",,,"===p){let t=[n,o,c].join(""),e="%%%"===t?100:""===t?255:0;if(e){let t=[Wt(+r/e,0,1),Wt(+a/e,0,1),Wt(+l/e,0,1),h?Gt(+h,f):1];if(Zt(t))return t}}return}}let r=t.match(/^hsla?\(\s*([\de.+-]+)(?:deg)?(?:\s+|\s*(,)\s*)([\de.+-]+)%(?:\s+|\s*(,)\s*)([\de.+-]+)%(?:\s*([,\/])\s*([\de.+-]+)(%)?)?\s*\)$/);if(r){let[t,e,n,i,a,o,s,l,c]=r,u=[n||" ",a||" ",s].join("");if(" "===u||" /"===u||",,"===u||",,,"===u){let t=[+e,Wt(+i,0,100),Wt(+o,0,100),l?Gt(+l,c):1];if(Zt(t))return function([t,e,r,n]){function i(n){let i=(n+t/30)%12,a=e*Math.min(r,1-r);return r-a*Math.max(-1,Math.min(i-3,9-i,1))}return t=Ft(t),e/=100,r/=100,[i(0),i(8),i(4),n]}(t)}}}(t);return e?new Xt(...e,!1):void 0}get rgb(){let{r:t,g:e,b:r,a:n}=this,i=n||1/0;return this.overwriteGetter("rgb",[t/i,e/i,r/i,n])}get hcl(){return this.overwriteGetter("hcl",function(t){let[e,r,n,i]=Bt(t),a=Math.sqrt(r*r+n*n);return[Math.round(1e4*a)?Ft(Math.atan2(n,r)*Rt):NaN,a,e,i]}(this.rgb))}get lab(){return this.overwriteGetter("lab",Bt(this.rgb))}overwriteGetter(t,e){return 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le(r||`Could not parse color from value '${"string"==typeof e?e:JSON.stringify(e)}'`)}case"padding":{let e;for(let r of this.args){e=r.evaluate(t);let n=Qt.parse(e);if(n)return n}throw new le(`Could not parse padding from value '${"string"==typeof e?e:JSON.stringify(e)}'`)}case"variableAnchorOffsetCollection":{let e;for(let r of this.args){e=r.evaluate(t);let n=ee.parse(e);if(n)return n}throw new le(`Could not parse variableAnchorOffsetCollection from value '${"string"==typeof e?e:JSON.stringify(e)}'`)}case"number":{let e=null;for(let r of this.args){if(e=r.evaluate(t),null===e)return 0;let n=Number(e);if(!isNaN(n))return n}throw new le(`Could not convert ${JSON.stringify(e)} to number.`)}case"formatted":return Jt.fromString(oe(this.args[0].evaluate(t)));case"resolvedImage":return re.fromString(oe(this.args[0].evaluate(t)));default:return oe(this.args[0].evaluate(t))}}eachChild(t){this.args.forEach(t)}outputDefined(){return this.args.every((t=>t.outputDefined()))}}let pe=["Unknown","Point","LineString","Polygon"];class de{constructor(){this.globals=null,this.feature=null,this.featureState=null,this.formattedSection=null,this._parseColorCache={},this.availableImages=null,this.canonical=null}id(){return this.feature&&"id"in this.feature?this.feature.id:null}geometryType(){return this.feature?"number"==typeof this.feature.type?pe[this.feature.type]:this.feature.type:null}geometry(){return this.feature&&"geometry"in this.feature?this.feature.geometry:null}canonicalID(){return this.canonical}properties(){return this.feature&&this.feature.properties||{}}parseColor(t){let e=this._parseColorCache[t];return e||(e=this._parseColorCache[t]=Xt.parse(t)),e}}class me{constructor(t,e,r=[],n,i=new ct,a=[]){this.registry=t,this.path=r,this.key=r.map((t=>`[${t}]`)).join(""),this.scope=i,this.errors=a,this.expectedType=n,this._isConstant=e}parse(t,e,r,n,i={}){return e?this.concat(e,r,n)._parse(t,i):this._parse(t,i)}_parse(t,e){function r(t,e,r){return"assert"===r?new ue(e,[t]):"coerce"===r?new fe(e,[t]):t}if(null!==t&&"string"!=typeof t&&"boolean"!=typeof t&&"number"!=typeof t||(t=["literal",t]),Array.isArray(t)){if(0===t.length)return this.error('Expected an array with at least one element. 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xe{constructor(t,e){this.type=pt,this.needle=t,this.haystack=e}static parse(t,e){if(3!==t.length)return e.error(`Expected 2 arguments, but found ${t.length-1} instead.`);let r=e.parse(t[1],1,gt),n=e.parse(t[2],2,gt);return r&&n?Mt(r.type,[pt,ft,ht,ut,gt])?new xe(r,n):e.error(`Expected first argument to be of type boolean, string, number or null, but found ${Tt(r.type)} instead`):null}evaluate(t){let e=this.needle.evaluate(t),r=this.haystack.evaluate(t);if(!r)return!1;if(!St(e,["boolean","string","number","null"]))throw new le(`Expected first argument to be of type boolean, string, number or null, but found ${Tt(ae(e))} instead.`);if(!St(r,["string","array"]))throw new le(`Expected second argument to be of type array or string, but found ${Tt(ae(r))} instead.`);return r.indexOf(e)>=0}eachChild(t){t(this.needle),t(this.haystack)}outputDefined(){return!0}}class _e{constructor(t,e,r){this.type=ht,this.needle=t,this.haystack=e,this.fromIndex=r}static parse(t,e){if(t.length<=2||t.length>=5)return e.error(`Expected 3 or 4 arguments, but found ${t.length-1} instead.`);let r=e.parse(t[1],1,gt),n=e.parse(t[2],2,gt);if(!r||!n)return null;if(!Mt(r.type,[pt,ft,ht,ut,gt]))return e.error(`Expected first argument to be of type boolean, string, number or null, but found ${Tt(r.type)} instead`);if(4===t.length){let i=e.parse(t[3],3,ht);return i?new _e(r,n,i):null}return new _e(r,n)}evaluate(t){let e,r=this.needle.evaluate(t),n=this.haystack.evaluate(t);if(!St(r,["boolean","string","number","null"]))throw new le(`Expected first argument to be of type boolean, string, number or null, but found ${Tt(ae(r))} instead.`);if(this.fromIndex&&(e=this.fromIndex.evaluate(t)),St(n,["string"])){let t=n.indexOf(r,e);return-1===t?-1:[...n.slice(0,t)].length}if(St(n,["array"]))return n.indexOf(r,e);throw new le(`Expected second argument to be of type array or string, but found ${Tt(ae(n))} 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e)if(r.evaluate(t))return!0;return!1}]]},"!":[pt,[pt],(t,[e])=>!e.evaluate(t)],"is-supported-script":[pt,[ft],(t,[e])=>{let r=t.globals&&t.globals.isSupportedScript;return!r||r(e.evaluate(t))}],upcase:[ft,[ft],(t,[e])=>e.evaluate(t).toUpperCase()],downcase:[ft,[ft],(t,[e])=>e.evaluate(t).toLowerCase()],concat:[ft,tn(gt),(t,e)=>e.map((e=>oe(e.evaluate(t)))).join("")],"resolved-locale":[ft,[yt],(t,[e])=>e.evaluate(t).resolvedLocale()]});class _n{constructor(t,e){var r;this.expression=t,this._warningHistory={},this._evaluator=new de,this._defaultValue=e?"color"===(r=e).type&&fn(r.default)?new Xt(0,0,0,0):"color"===r.type?Xt.parse(r.default)||null:"padding"===r.type?Qt.parse(r.default)||null:"variableAnchorOffsetCollection"===r.type?ee.parse(r.default)||null:void 0===r.default?null:r.default:null,this._enumValues=e&&"enum"===e.type?e.values:null}evaluateWithoutErrorHandling(t,e,r,n,i,a){return this._evaluator.globals=t,this._evaluator.feature=e,this._evaluator.featureState=r,this._evaluator.canonical=n,this._evaluator.availableImages=i||null,this._evaluator.formattedSection=a,this.expression.evaluate(this._evaluator)}evaluate(t,e,r,n,i,a){this._evaluator.globals=t,this._evaluator.feature=e||null,this._evaluator.featureState=r||null,this._evaluator.canonical=n,this._evaluator.availableImages=i||null,this._evaluator.formattedSection=a||null;try{let t=this.expression.evaluate(this._evaluator);if(null==t||"number"==typeof t&&t!=t)return this._defaultValue;if(this._enumValues&&!(t in this._enumValues))throw new le(`Expected value to be one of ${Object.keys(this._enumValues).map((t=>JSON.stringify(t))).join(", ")}, but found ${JSON.stringify(t)} instead.`);return t}catch(t){return this._warningHistory[t.message]||(this._warningHistory[t.message]=!0,typeof console<"u"&&console.warn(t.message)),this._defaultValue}}}function bn(t){return Array.isArray(t)&&t.length>0&&"string"==typeof t[0]&&t[0]in Xr}function wn(t,e){let r=new me(Xr,en,[],e?function(t){let e={color:dt,string:ft,number:ht,enum:ft,boolean:pt,formatted:vt,padding:xt,resolvedImage:_t,variableAnchorOffsetCollection:bt};return"array"===t.type?wt(e[t.value]||gt,t.length):e[t.type]}(e):void 0),n=r.parse(t,void 0,void 0,void 0,e&&"string"===e.type?{typeAnnotation:"coerce"}:void 0);return n?on(new _n(n,e)):sn(r.errors)}class Tn{constructor(t,e){this.kind=t,this._styleExpression=e,this.isStateDependent="constant"!==t&&!nn(e.expression)}evaluateWithoutErrorHandling(t,e,r,n,i,a){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n,i,a)}evaluate(t,e,r,n,i,a){return this._styleExpression.evaluate(t,e,r,n,i,a)}}class kn{constructor(t,e,r,n){this.kind=t,this.zoomStops=r,this._styleExpression=e,this.isStateDependent="camera"!==t&&!nn(e.expression),this.interpolationType=n}evaluateWithoutErrorHandling(t,e,r,n,i,a){return this._styleExpression.evaluateWithoutErrorHandling(t,e,r,n,i,a)}evaluate(t,e,r,n,i,a){return this._styleExpression.evaluate(t,e,r,n,i,a)}interpolationFactor(t,e,r){return this.interpolationType?ze.interpolationFactor(this.interpolationType,t,e,r):0}}function An(t,e){let r=wn(t,e);if("error"===r.result)return r;let n=r.value.expression,i=rn(n);if(!i&&!ln(e))return sn([new lt("","data expressions not supported")]);let a=an(n,["zoom"]);if(!a&&!cn(e))return sn([new lt("","zoom expressions not supported")]);let o=Sn(n);return o||a?o instanceof lt?sn([o]):o instanceof ze&&!un(e)?sn([new lt("",'"interpolate" expressions cannot be used with this property')]):on(o?new kn(i?"camera":"composite",r.value,o.labels,o instanceof ze?o.interpolation:void 0):new Tn(i?"constant":"source",r.value)):sn([new lt("",'"zoom" expression may only be used as input to a top-level "step" or "interpolate" expression.')])}class Mn{constructor(t,e){this._parameters=t,this._specification=e,st(this,dn(this._parameters,this._specification))}static deserialize(t){return new Mn(t._parameters,t._specification)}static serialize(t){return{_parameters:t._parameters,_specification:t._specification}}}function Sn(t){let e=null;if(t instanceof ge)e=Sn(t.result);else if(t instanceof Oe){for(let r of t.args)if(e=Sn(r),e)break}else(t instanceof Ae||t instanceof ze)&&t.input instanceof $r&&"zoom"===t.input.name&&(e=t);return e instanceof lt||t.eachChild((t=>{let r=Sn(t);r instanceof lt?e=r:!e&&r?e=new lt("",'"zoom" expression may only be used as input to a top-level "step" or "interpolate" expression.'):e&&r&&e!==r&&(e=new lt("",'Only one zoom-based "step" or "interpolate" subexpression may be used in an expression.'))})),e}function En(t){if(!0===t||!1===t)return!0;if(!Array.isArray(t)||0===t.length)return!1;switch(t[0]){case"has":return t.length>=2&&"$id"!==t[1]&&"$type"!==t[1];case"in":return t.length>=3&&("string"!=typeof t[1]||Array.isArray(t[2]));case"!in":case"!has":case"none":return!1;case"==":case"!=":case">":case">=":case"<":case"<=":return 3!==t.length||Array.isArray(t[1])||Array.isArray(t[2]);case"any":case"all":for(let e of t.slice(1))if(!En(e)&&"boolean"!=typeof e)return!1;return!0;default:return!0}}let Cn={type:"boolean",default:!1,transition:!1,"property-type":"data-driven",expression:{interpolated:!1,parameters:["zoom","feature"]}};function In(t){if(null==t)return{filter:()=>!0,needGeometry:!1};En(t)||(t=zn(t));let e=wn(t,Cn);if("error"===e.result)throw new Error(e.value.map((t=>`${t.key}: ${t.message}`)).join(", "));return{filter:(t,r,n)=>e.value.evaluate(t,r,{},n),needGeometry:Pn(t)}}function Ln(t,e){return te?1:0}function Pn(t){if(!Array.isArray(t))return!1;if("within"===t[0]||"distance"===t[0])return!0;for(let e=1;e"===e||"<="===e||">="===e?Dn(t[1],t[2],e):"any"===e?(r=t.slice(1),["any"].concat(r.map(zn))):"all"===e?["all"].concat(t.slice(1).map(zn)):"none"===e?["all"].concat(t.slice(1).map(zn).map(Fn)):"in"===e?On(t[1],t.slice(2)):"!in"===e?Fn(On(t[1],t.slice(2))):"has"===e?Rn(t[1]):"!has"!==e||Fn(Rn(t[1]));var r}function Dn(t,e,r){switch(t){case"$type":return[`filter-type-${r}`,e];case"$id":return[`filter-id-${r}`,e];default:return[`filter-${r}`,t,e]}}function On(t,e){if(0===e.length)return!1;switch(t){case"$type":return["filter-type-in",["literal",e]];case"$id":return["filter-id-in",["literal",e]];default:return e.length>200&&!e.some((t=>typeof t!=typeof e[0]))?["filter-in-large",t,["literal",e.sort(Ln)]]:["filter-in-small",t,["literal",e]]}}function Rn(t){switch(t){case"$type":return!0;case"$id":return["filter-has-id"];default:return["filter-has",t]}}function Fn(t){return["!",t]}function Bn(t){let e=typeof t;if("number"===e||"boolean"===e||"string"===e||null==t)return JSON.stringify(t);if(Array.isArray(t)){let e="[";for(let r of t)e+=`${Bn(r)},`;return`${e}]`}let r=Object.keys(t).sort(),n="{";for(let e=0;en.maximum?[new ot(e,r,`${r} is greater than the maximum value ${n.maximum}`)]:[]}function Wn(t){let e,r,n,i=t.valueSpec,a=Un(t.value.type),o={},s="categorical"!==a&&void 0===t.value.property,l=!s,c="array"===hn(t.value.stops)&&"array"===hn(t.value.stops[0])&&"object"===hn(t.value.stops[0][0]),u=qn({key:t.key,value:t.value,valueSpec:t.styleSpec.function,validateSpec:t.validateSpec,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{stops:function(t){if("identity"===a)return[new ot(t.key,t.value,'identity function may not have a "stops" property')];let e=[],r=t.value;return e=e.concat(Hn({key:t.key,value:r,valueSpec:t.valueSpec,validateSpec:t.validateSpec,style:t.style,styleSpec:t.styleSpec,arrayElementValidator:h})),"array"===hn(r)&&0===r.length&&e.push(new ot(t.key,r,"array must have at least one stop")),e},default:function(t){return t.validateSpec({key:t.key,value:t.value,valueSpec:i,validateSpec:t.validateSpec,style:t.style,styleSpec:t.styleSpec})}}});return"identity"===a&&s&&u.push(new ot(t.key,t.value,'missing required property "property"')),"identity"===a||t.value.stops||u.push(new ot(t.key,t.value,'missing required property "stops"')),"exponential"===a&&t.valueSpec.expression&&!un(t.valueSpec)&&u.push(new ot(t.key,t.value,"exponential functions not supported")),t.styleSpec.$version>=8&&(l&&!ln(t.valueSpec)?u.push(new ot(t.key,t.value,"property functions not supported")):s&&!cn(t.valueSpec)&&u.push(new ot(t.key,t.value,"zoom functions not supported"))),"categorical"!==a&&!c||void 0!==t.value.property||u.push(new ot(t.key,t.value,'"property" property is required')),u;function h(t){let e=[],a=t.value,s=t.key;if("array"!==hn(a))return[new ot(s,a,`array expected, ${hn(a)} found`)];if(2!==a.length)return[new ot(s,a,`array length 2 expected, length ${a.length} found`)];if(c){if("object"!==hn(a[0]))return[new ot(s,a,`object expected, ${hn(a[0])} found`)];if(void 0===a[0].zoom)return[new ot(s,a,"object stop key must have zoom")];if(void 0===a[0].value)return[new ot(s,a,"object stop key must have value")];if(n&&n>Un(a[0].zoom))return[new ot(s,a[0].zoom,"stop zoom values must appear in ascending order")];Un(a[0].zoom)!==n&&(n=Un(a[0].zoom),r=void 0,o={}),e=e.concat(qn({key:`${s}[0]`,value:a[0],valueSpec:{zoom:{}},validateSpec:t.validateSpec,style:t.style,styleSpec:t.styleSpec,objectElementValidators:{zoom:Gn,value:f}}))}else e=e.concat(f({key:`${s}[0]`,value:a[0],valueSpec:{},validateSpec:t.validateSpec,style:t.style,styleSpec:t.styleSpec},a));return bn(Vn(a[1]))?e.concat([new ot(`${s}[1]`,a[1],"expressions are not allowed in function stops.")]):e.concat(t.validateSpec({key:`${s}[1]`,value:a[1],valueSpec:i,validateSpec:t.validateSpec,style:t.style,styleSpec:t.styleSpec}))}function f(t,n){let s=hn(t.value),l=Un(t.value),c=null!==t.value?t.value:n;if(e){if(s!==e)return[new ot(t.key,c,`${s} stop domain type must match previous stop domain type ${e}`)]}else e=s;if("number"!==s&&"string"!==s&&"boolean"!==s)return[new ot(t.key,c,"stop domain value must be a number, string, or boolean")];if("number"!==s&&"categorical"!==a){let e=`number expected, ${s} found`;return ln(i)&&void 0===a&&(e+='\nIf you intended to use a categorical function, specify `"type": "categorical"`.'),[new ot(t.key,c,e)]}return"categorical"!==a||"number"!==s||isFinite(l)&&Math.floor(l)===l?"categorical"!==a&&"number"===s&&void 0!==r&&lnew ot(`${t.key}${e.key}`,t.value,e.message)));let r=e.value.expression||e.value._styleExpression.expression;if("property"===t.expressionContext&&"text-font"===t.propertyKey&&!r.outputDefined())return[new ot(t.key,t.value,`Invalid data expression for "${t.propertyKey}". Output values must be contained as literals within the expression.`)];if("property"===t.expressionContext&&"layout"===t.propertyType&&!nn(r))return[new ot(t.key,t.value,'"feature-state" data expressions are not supported with layout properties.')];if("filter"===t.expressionContext&&!nn(r))return[new ot(t.key,t.value,'"feature-state" data expressions are not supported with filters.')];if(t.expressionContext&&0===t.expressionContext.indexOf("cluster")){if(!an(r,["zoom","feature-state"]))return[new ot(t.key,t.value,'"zoom" and "feature-state" expressions are not supported with cluster properties.')];if("cluster-initial"===t.expressionContext&&!rn(r))return[new ot(t.key,t.value,"Feature data expressions are not supported with initial expression part of cluster properties.")]}return[]}function Yn(t){let e=t.key,r=t.value,n=t.valueSpec,i=[];return Array.isArray(n.values)?-1===n.values.indexOf(Un(r))&&i.push(new ot(e,r,`expected one of [${n.values.join(", ")}], ${JSON.stringify(r)} found`)):-1===Object.keys(n.values).indexOf(Un(r))&&i.push(new ot(e,r,`expected one of [${Object.keys(n.values).join(", ")}], ${JSON.stringify(r)} found`)),i}function Xn(t){return En(Vn(t.value))?Zn(st({},t,{expressionContext:"filter",valueSpec:{value:"boolean"}})):$n(t)}function $n(t){let e=t.value,r=t.key;if("array"!==hn(e))return[new ot(r,e,`array expected, ${hn(e)} found`)];let n,i=t.styleSpec,a=[];if(e.length<1)return[new ot(r,e,"filter array must have at least 1 element")];switch(a=a.concat(Yn({key:`${r}[0]`,value:e[0],valueSpec:i.filter_operator,style:t.style,styleSpec:t.styleSpec})),Un(e[0])){case"<":case"<=":case">":case">=":e.length>=2&&"$type"===Un(e[1])&&a.push(new ot(r,e,`"$type" cannot be use with operator "${e[0]}"`));case"==":case"!=":3!==e.length&&a.push(new ot(r,e,`filter array for operator "${e[0]}" must have 3 elements`));case"in":case"!in":e.length>=2&&(n=hn(e[1]),"string"!==n&&a.push(new ot(`${r}[1]`,e[1],`string expected, ${n} found`)));for(let o=2;o{t in r&&e.push(new ot(n,r[t],`"${t}" is prohibited for ref layers`))})),i.layers.forEach((e=>{Un(e.id)===s&&(t=e)})),t?t.ref?e.push(new ot(n,r.ref,"ref cannot reference another ref layer")):o=Un(t.type):e.push(new ot(n,r.ref,`ref layer "${s}" not found`))}else if("background"!==o)if(r.source){let t=i.sources&&i.sources[r.source],a=t&&Un(t.type);t?"vector"===a&&"raster"===o?e.push(new ot(n,r.source,`layer "${r.id}" requires a raster source`)):"raster-dem"!==a&&"hillshade"===o?e.push(new ot(n,r.source,`layer "${r.id}" requires a raster-dem source`)):"raster"===a&&"raster"!==o?e.push(new ot(n,r.source,`layer "${r.id}" requires a vector source`)):"vector"!==a||r["source-layer"]?"raster-dem"===a&&"hillshade"!==o?e.push(new ot(n,r.source,"raster-dem source can only be used with layer type 'hillshade'.")):"line"!==o||!r.paint||!r.paint["line-gradient"]||"geojson"===a&&t.lineMetrics||e.push(new ot(n,r,`layer "${r.id}" specifies a line-gradient, which requires a GeoJSON source with \`lineMetrics\` 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ri={promoteId:function({key:t,value:e}){if("string"===hn(e))return ei({key:t,value:e});{let r=[];for(let n in e)r.push(...ei({key:`${t}.${n}`,value:e[n]}));return r}}};function ni(t){let e=t.value,r=t.key,n=t.styleSpec,i=t.style,a=t.validateSpec;if(!e.type)return[new ot(r,e,'"type" is required')];let o,s=Un(e.type);switch(s){case"vector":case"raster":return o=qn({key:r,value:e,valueSpec:n[`source_${s.replace("-","_")}`],style:t.style,styleSpec:n,objectElementValidators:ri,validateSpec:a}),o;case"raster-dem":return o=function(t){var e;let r=null!==(e=t.sourceName)&&void 0!==e?e:"",n=t.value,i=t.styleSpec,a=i.source_raster_dem,o=t.style,s=[],l=hn(n);if(void 0===n)return s;if("object"!==l)return s.push(new ot("source_raster_dem",n,`object expected, ${l} found`)),s;let c="custom"===Un(n.encoding),u=["redFactor","greenFactor","blueFactor","baseShift"],h=t.value.encoding?`"${t.value.encoding}"`:"Default";for(let e in n)!c&&u.includes(e)?s.push(new ot(e,n[e],`In "${r}": "${e}" is only valid 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of e)t.fire(new W(new Error(n.message))),r=!0;return r}class bi{constructor(t,e,r){let n=this.cells=[];if(t instanceof ArrayBuffer){this.arrayBuffer=t;let i=new Int32Array(this.arrayBuffer);t=i[0],this.d=(e=i[1])+2*(r=i[2]);for(let t=0;t=c[l+0]&&n>=c[l+1])?(o[h]=!0,a.push(i[h])):o[h]=!1}}}}_forEachCell(t,e,r,n,i,a,o,s){let l=this._convertToCellCoord(t),c=this._convertToCellCoord(e),u=this._convertToCellCoord(r),h=this._convertToCellCoord(n);for(let f=l;f<=u;f++)for(let l=c;l<=h;l++){let c=this.d*l+f;if((!s||s(this._convertFromCellCoord(f),this._convertFromCellCoord(l),this._convertFromCellCoord(f+1),this._convertFromCellCoord(l+1)))&&i.call(this,t,e,r,n,c,a,o,s))return}}_convertFromCellCoord(t){return(t-this.padding)/this.scale}_convertToCellCoord(t){return Math.max(0,Math.min(this.d-1,Math.floor(t*this.scale)+this.padding))}toArrayBuffer(){if(this.arrayBuffer)return this.arrayBuffer;let t=this.cells,e=3+this.cells.length+1+1,r=0;for(let t=0;t=0)continue;let a=t[n];i[n]=wi[r].shallow.indexOf(n)>=0?a:Si(a,e)}t instanceof Error&&(i.message=t.message)}if(i.$name)throw new Error("$name property is reserved for worker serialization logic.");return"Object"!==r&&(i.$name=r),i}function Ei(t){if(Mi(t))return t;if(Array.isArray(t))return t.map(Ei);if("object"!=typeof t)throw new Error("can't deserialize object of type "+typeof t);let e=Ai(t)||"Object";if(!wi[e])throw new Error(`can't deserialize unregistered class ${e}`);let{klass:r}=wi[e];if(!r)throw new Error(`can't deserialize unregistered class ${e}`);if(r.deserialize)return r.deserialize(t);let n=Object.create(r.prototype);for(let r of Object.keys(t)){if("$name"===r)continue;let i=t[r];n[r]=wi[e].shallow.indexOf(r)>=0?i:Ei(i)}return n}class Ci{constructor(){this.first=!0}update(t,e){let r=Math.floor(t);return this.first?(this.first=!1,this.lastIntegerZoom=r,this.lastIntegerZoomTime=0,this.lastZoom=t,this.lastFloorZoom=r,!0):(this.lastFloorZoom>r?(this.lastIntegerZoom=r+1,this.lastIntegerZoomTime=e):this.lastFloorZoomt>=12272&&t<=12287,Li=t=>t>=12288&&t<=12351,Pi=t=>t>=12448&&t<=12543,zi=t=>t>=12736&&t<=12783,Di=t=>t>=12800&&t<=13055,Oi=t=>t>=13056&&t<=13311,Ri=t=>t>=65040&&t<=65055,Fi=t=>t>=65072&&t<=65103,Bi=t=>t>=65104&&t<=65135,ji=t=>t>=65280&&t<=65519;function Ni(t){for(let e of t)if(Wi(e.charCodeAt(0)))return!0;return!1}function Ui(t){for(let e of t)if(!Hi(e.charCodeAt(0)))return!1;return!0}function Vi(t){let e=t.map((t=>{try{return new RegExp(`\\p{sc=${t}}`,"u").source}catch{return null}})).filter((t=>t));return new RegExp(e.join("|"),"u")}let qi=Vi(["Arab","Dupl","Mong","Ougr","Syrc"]);function Hi(t){return!qi.test(String.fromCodePoint(t))}let Gi=Vi(["Bopo","Hani","Hira","Kana","Kits","Nshu","Tang","Yiii"]);function Wi(t){return!(746!==t&&747!==t&&(t<4352||!(Fi(t)&&!(t>=65097&&t<=65103)||Oi(t)||zi(t)||!(!Li(t)||t>=12296&&t<=12305||t>=12308&&t<=12319||12336===t)||Di(t)||Ii(t)||(t=>t>=12688&&t<=12703)(t)||Pi(t)&&12540!==t||!(!ji(t)||65288===t||65289===t||65293===t||t>=65306&&t<=65310||65339===t||65341===t||65343===t||t>=65371&&t<=65503||65507===t||t>=65512&&t<=65519)||!(!Bi(t)||t>=65112&&t<=65118||t>=65123&&t<=65126)||Ri(t)||(t=>t>=19904&&t<=19967)(t)||new RegExp("\\p{sc=Cans}","u").test(String.fromCodePoint(t))||new RegExp("\\p{sc=Hang}","u").test(String.fromCodePoint(t))||Gi.test(String.fromCodePoint(t)))))}function Zi(t){return!(Wi(t)||(e=t,(t=>t>=128&&t<=255)(e)&&(167===e||169===e||174===e||177===e||188===e||189===e||190===e||215===e||247===e)||(t=>t>=8192&&t<=8303)(e)&&(8214===e||8224===e||8225===e||8240===e||8241===e||8251===e||8252===e||8258===e||8263===e||8264===e||8265===e||8273===e)||(t=>t>=8448&&t<=8527)(e)||(t=>t>=8528&&t<=8591)(e)||(t=>t>=8960&&t<=9215)(e)&&(e>=8960&&e<=8967||e>=8972&&e<=8991||e>=8996&&e<=9e3||9003===e||e>=9085&&e<=9114||e>=9150&&e<=9165||9167===e||e>=9169&&e<=9179||e>=9186&&e<=9215)||(t=>t>=9216&&t<=9279)(e)&&9251!==e||(t=>t>=9280&&t<=9311)(e)||(t=>t>=9312&&t<=9471)(e)||(t=>t>=9632&&t<=9727)(e)||(t=>t>=9728&&t<=9983)(e)&&!(e>=9754&&e<=9759)||(t=>t>=11008&&t<=11263)(e)&&(e>=11026&&e<=11055||e>=11088&&e<=11097||e>=11192&&e<=11243)||Li(e)||Pi(e)||(t=>t>=57344&&t<=63743)(e)||Fi(e)||Bi(e)||ji(e)||8734===e||8756===e||8757===e||e>=9984&&e<=10087||e>=10102&&e<=10131||65532===e||65533===e));var e}let Yi=Vi(["Adlm","Arab","Armi","Avst","Chrs","Cprt","Egyp","Elym","Gara","Hatr","Hebr","Hung","Khar","Lydi","Mand","Mani","Mend","Merc","Mero","Narb","Nbat","Nkoo","Orkh","Palm","Phli","Phlp","Phnx","Prti","Rohg","Samr","Sarb","Sogo","Syrc","Thaa","Todr","Yezi"]);function Xi(t){return Yi.test(String.fromCodePoint(t))}function $i(t,e){return!(!e&&Xi(t)||t>=2304&&t<=3583||t>=3840&&t<=4255||(t=>t>=6016&&t<=6143)(t))}function Ki(t){for(let e of t)if(Xi(e.charCodeAt(0)))return!0;return!1}let Ji=new class{constructor(){this.applyArabicShaping=null,this.processBidirectionalText=null,this.processStyledBidirectionalText=null,this.pluginStatus="unavailable",this.pluginURL=null}setState(t){this.pluginStatus=t.pluginStatus,this.pluginURL=t.pluginURL}getState(){return{pluginStatus:this.pluginStatus,pluginURL:this.pluginURL}}setMethods(t){this.applyArabicShaping=t.applyArabicShaping,this.processBidirectionalText=t.processBidirectionalText,this.processStyledBidirectionalText=t.processStyledBidirectionalText}isParsed(){return null!=this.applyArabicShaping&&null!=this.processBidirectionalText&&null!=this.processStyledBidirectionalText}getPluginURL(){return this.pluginURL}getRTLTextPluginStatus(){return this.pluginStatus}};class Qi{constructor(t,e){this.zoom=t,e?(this.now=e.now,this.fadeDuration=e.fadeDuration,this.zoomHistory=e.zoomHistory,this.transition=e.transition):(this.now=0,this.fadeDuration=0,this.zoomHistory=new Ci,this.transition={})}isSupportedScript(t){return function(t,e){for(let r of t)if(!$i(r.charCodeAt(0),e))return!1;return!0}(t,"loaded"===Ji.getRTLTextPluginStatus())}crossFadingFactor(){return 0===this.fadeDuration?1:Math.min((this.now-this.zoomHistory.lastIntegerZoomTime)/this.fadeDuration,1)}getCrossfadeParameters(){let t=this.zoom,e=t-Math.floor(t),r=this.crossFadingFactor();return t>this.zoomHistory.lastIntegerZoom?{fromScale:2,toScale:1,t:e+(1-e)*r}:{fromScale:.5,toScale:1,t:1-(1-r)*e}}}class ta{constructor(t,e){this.property=t,this.value=e,this.expression=function(t,e){if(fn(t))return new Mn(t,e);if(bn(t)){let r=An(t,e);if("error"===r.result)throw new Error(r.value.map((t=>`${t.key}: ${t.message}`)).join(", "));return r.value}{let r=t;return"color"===e.type&&"string"==typeof t?r=Xt.parse(t):"padding"!==e.type||"number"!=typeof t&&!Array.isArray(t)?"variableAnchorOffsetCollection"===e.type&&Array.isArray(t)&&(r=ee.parse(t)):r=Qt.parse(t),{kind:"constant",evaluate:()=>r}}}(void 0===e?t.specification.default:e,t.specification)}isDataDriven(){return"source"===this.expression.kind||"composite"===this.expression.kind}possiblyEvaluate(t,e,r){return this.property.possiblyEvaluate(this,t,e,r)}}class ea{constructor(t){this.property=t,this.value=new ta(t,void 0)}transitioned(t,e){return new na(this.property,this.value,e,x({},t.transition,this.transition),t.now)}untransitioned(){return new na(this.property,this.value,null,{},0)}}class ra{constructor(t){this._properties=t,this._values=Object.create(t.defaultTransitionablePropertyValues)}getValue(t){return T(this._values[t].value.value)}setValue(t,e){Object.prototype.hasOwnProperty.call(this._values,t)||(this._values[t]=new ea(this._values[t].property)),this._values[t].value=new ta(this._values[t].property,null===e?void 0:T(e))}getTransition(t){return T(this._values[t].transition)}setTransition(t,e){Object.prototype.hasOwnProperty.call(this._values,t)||(this._values[t]=new ea(this._values[t].property)),this._values[t].transition=T(e)||void 0}serialize(){let t={};for(let e of Object.keys(this._values)){let r=this.getValue(e);void 0!==r&&(t[e]=r);let n=this.getTransition(e);void 0!==n&&(t[`${e}-transition`]=n)}return t}transitioned(t,e){let r=new ia(this._properties);for(let n of Object.keys(this._values))r._values[n]=this._values[n].transitioned(t,e._values[n]);return r}untransitioned(){let t=new ia(this._properties);for(let e of Object.keys(this._values))t._values[e]=this._values[e].untransitioned();return t}}class na{constructor(t,e,r,n,i){this.property=t,this.value=e,this.begin=i+n.delay||0,this.end=this.begin+n.duration||0,t.specification.transition&&(n.delay||n.duration)&&(this.prior=r)}possiblyEvaluate(t,e,r){let n=t.now||0,i=this.value.possiblyEvaluate(t,e,r),a=this.prior;if(a){if(n>this.end)return this.prior=null,i;if(this.value.isDataDriven())return this.prior=null,i;if(n=1)return 1;let e=t*t,r=e*t;return 4*(t<.5?r:3*(t-e)+r-.75)}(o))}}return i}}class ia{constructor(t){this._properties=t,this._values=Object.create(t.defaultTransitioningPropertyValues)}possiblyEvaluate(t,e,r){let n=new sa(this._properties);for(let i of Object.keys(this._values))n._values[i]=this._values[i].possiblyEvaluate(t,e,r);return n}hasTransition(){for(let t of Object.keys(this._values))if(this._values[t].prior)return!0;return!1}}class aa{constructor(t){this._properties=t,this._values=Object.create(t.defaultPropertyValues)}hasValue(t){return void 0!==this._values[t].value}getValue(t){return T(this._values[t].value)}setValue(t,e){this._values[t]=new ta(this._values[t].property,null===e?void 0:T(e))}serialize(){let t={};for(let e of Object.keys(this._values)){let r=this.getValue(e);void 0!==r&&(t[e]=r)}return t}possiblyEvaluate(t,e,r){let n=new sa(this._properties);for(let i of Object.keys(this._values))n._values[i]=this._values[i].possiblyEvaluate(t,e,r);return n}}class oa{constructor(t,e,r){this.property=t,this.value=e,this.parameters=r}isConstant(){return"constant"===this.value.kind}constantOr(t){return"constant"===this.value.kind?this.value.value:t}evaluate(t,e,r,n){return this.property.evaluate(this.value,this.parameters,t,e,r,n)}}class sa{constructor(t){this._properties=t,this._values=Object.create(t.defaultPossiblyEvaluatedValues)}get(t){return this._values[t]}}class la{constructor(t){this.specification=t}possiblyEvaluate(t,e){if(t.isDataDriven())throw new Error("Value should not be data driven");return t.expression.evaluate(e)}interpolate(t,e,r){let n=Pe[this.specification.type];return n?n(t,e,r):t}}class ca{constructor(t,e){this.specification=t,this.overrides=e}possiblyEvaluate(t,e,r,n){return new oa(this,"constant"===t.expression.kind||"camera"===t.expression.kind?{kind:"constant",value:t.expression.evaluate(e,null,{},r,n)}:t.expression,e)}interpolate(t,e,r){if("constant"!==t.value.kind||"constant"!==e.value.kind)return t;if(void 0===t.value.value||void 0===e.value.value)return new oa(this,{kind:"constant",value:void 0},t.parameters);let n=Pe[this.specification.type];if(n){let i=n(t.value.value,e.value.value,r);return new oa(this,{kind:"constant",value:i},t.parameters)}return t}evaluate(t,e,r,n,i,a){return"constant"===t.kind?t.value:t.evaluate(e,r,n,i,a)}}class ua extends ca{possiblyEvaluate(t,e,r,n){if(void 0===t.value)return new oa(this,{kind:"constant",value:void 0},e);if("constant"===t.expression.kind){let i=t.expression.evaluate(e,null,{},r,n),a="resolvedImage"===t.property.specification.type&&"string"!=typeof i?i.name:i,o=this._calculate(a,a,a,e);return new oa(this,{kind:"constant",value:o},e)}if("camera"===t.expression.kind){let r=this._calculate(t.expression.evaluate({zoom:e.zoom-1}),t.expression.evaluate({zoom:e.zoom}),t.expression.evaluate({zoom:e.zoom+1}),e);return new oa(this,{kind:"constant",value:r},e)}return new oa(this,t.expression,e)}evaluate(t,e,r,n,i,a){if("source"===t.kind){let o=t.evaluate(e,r,n,i,a);return this._calculate(o,o,o,e)}return"composite"===t.kind?this._calculate(t.evaluate({zoom:Math.floor(e.zoom)-1},r,n),t.evaluate({zoom:Math.floor(e.zoom)},r,n),t.evaluate({zoom:Math.floor(e.zoom)+1},r,n),e):t.value}_calculate(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}}interpolate(t){return t}}class ha{constructor(t){this.specification=t}possiblyEvaluate(t,e,r,n){if(void 0!==t.value){if("constant"===t.expression.kind){let i=t.expression.evaluate(e,null,{},r,n);return this._calculate(i,i,i,e)}return this._calculate(t.expression.evaluate(new Qi(Math.floor(e.zoom-1),e)),t.expression.evaluate(new Qi(Math.floor(e.zoom),e)),t.expression.evaluate(new Qi(Math.floor(e.zoom+1),e)),e)}}_calculate(t,e,r,n){return n.zoom>n.zoomHistory.lastIntegerZoom?{from:t,to:e}:{from:r,to:e}}interpolate(t){return t}}class fa{constructor(t){this.specification=t}possiblyEvaluate(t,e,r,n){return!!t.expression.evaluate(e,null,{},r,n)}interpolate(){return!1}}class pa{constructor(t){this.properties=t,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[];for(let e in t){let r=t[e];r.specification.overridable&&this.overridableProperties.push(e);let n=this.defaultPropertyValues[e]=new ta(r,void 0),i=this.defaultTransitionablePropertyValues[e]=new ea(r);this.defaultTransitioningPropertyValues[e]=i.untransitioned(),this.defaultPossiblyEvaluatedValues[e]=n.possiblyEvaluate({})}}}Ti("DataDrivenProperty",ca),Ti("DataConstantProperty",la),Ti("CrossFadedDataDrivenProperty",ua),Ti("CrossFadedProperty",ha),Ti("ColorRampProperty",fa);let da="-transition";class ma extends Z{constructor(t,e){if(super(),this.id=t.id,this.type=t.type,this._featureFilter={filter:()=>!0,needGeometry:!1},"custom"!==t.type&&(this.metadata=t.metadata,this.minzoom=t.minzoom,this.maxzoom=t.maxzoom,"background"!==t.type&&(this.source=t.source,this.sourceLayer=t["source-layer"],this.filter=t.filter),e.layout&&(this._unevaluatedLayout=new aa(e.layout)),e.paint)){this._transitionablePaint=new ra(e.paint);for(let e in t.paint)this.setPaintProperty(e,t.paint[e],{validate:!1});for(let e in t.layout)this.setLayoutProperty(e,t.layout[e],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned(),this.paint=new sa(e.paint)}}getCrossfadeParameters(){return this._crossfadeParameters}getLayoutProperty(t){return"visibility"===t?this.visibility:this._unevaluatedLayout.getValue(t)}setLayoutProperty(t,e,r={}){null!=e&&this._validate(xi,`layers.${this.id}.layout.${t}`,t,e,r)||("visibility"!==t?this._unevaluatedLayout.setValue(t,e):this.visibility=e)}getPaintProperty(t){return t.endsWith(da)?this._transitionablePaint.getTransition(t.slice(0,-11)):this._transitionablePaint.getValue(t)}setPaintProperty(t,e,r={}){if(null!=e&&this._validate(vi,`layers.${this.id}.paint.${t}`,t,e,r))return!1;if(t.endsWith(da))return this._transitionablePaint.setTransition(t.slice(0,-11),e||void 0),!1;{let r=this._transitionablePaint._values[t],n="cross-faded-data-driven"===r.property.specification["property-type"],i=r.value.isDataDriven(),a=r.value;this._transitionablePaint.setValue(t,e),this._handleSpecialPaintPropertyUpdate(t);let o=this._transitionablePaint._values[t].value;return o.isDataDriven()||i||n||this._handleOverridablePaintPropertyUpdate(t,a,o)}}_handleSpecialPaintPropertyUpdate(t){}_handleOverridablePaintPropertyUpdate(t,e,r){return!1}isHidden(t){return!!(this.minzoom&&t=this.maxzoom)||"none"===this.visibility}updateTransitions(t){this._transitioningPaint=this._transitionablePaint.transitioned(t,this._transitioningPaint)}hasTransition(){return this._transitioningPaint.hasTransition()}recalculate(t,e){t.getCrossfadeParameters&&(this._crossfadeParameters=t.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(t,void 0,e)),this.paint=this._transitioningPaint.possiblyEvaluate(t,void 0,e)}serialize(){let t={id:this.id,type:this.type,source:this.source,"source-layer":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(t.layout=t.layout||{},t.layout.visibility=this.visibility),w(t,((t,e)=>!(void 0===t||"layout"===e&&!Object.keys(t).length||"paint"===e&&!Object.keys(t).length)))}_validate(t,e,r,n,i={}){return(!i||!1!==i.validate)&&_i(this,t.call(mi,{key:e,layerType:this.type,objectKey:r,value:n,styleSpec:Y,style:{glyphs:!0,sprite:!0}}))}is3D(){return!1}isTileClipped(){return!1}hasOffscreenPass(){return!1}resize(){}isStateDependent(){for(let t in this.paint._values){let e=this.paint.get(t);if(e instanceof oa&&ln(e.property.specification)&&("source"===e.value.kind||"composite"===e.value.kind)&&e.value.isStateDependent)return!0}return!1}}let ga={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array};class ya{constructor(t,e){this._structArray=t,this._pos1=e*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8}}class va{constructor(){this.isTransferred=!1,this.capacity=-1,this.resize(0)}static serialize(t,e){return t._trim(),e&&(t.isTransferred=!0,e.push(t.arrayBuffer)),{length:t.length,arrayBuffer:t.arrayBuffer}}static deserialize(t){let e=Object.create(this.prototype);return e.arrayBuffer=t.arrayBuffer,e.length=t.length,e.capacity=t.arrayBuffer.byteLength/e.bytesPerElement,e._refreshViews(),e}_trim(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())}clear(){this.length=0}resize(t){this.reserve(t),this.length=t}reserve(t){if(t>this.capacity){this.capacity=Math.max(t,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);let e=this.uint8;this._refreshViews(),e&&this.uint8.set(e)}}_refreshViews(){throw new Error("_refreshViews() must be implemented by each concrete StructArray layout")}}function xa(t,e=1){let r=0,n=0;return{members:t.map((t=>{let i=ga[t.type].BYTES_PER_ELEMENT,a=r=_a(r,Math.max(e,i)),o=t.components||1;return n=Math.max(n,i),r+=i*o,{name:t.name,type:t.type,components:o,offset:a}})),size:_a(r,Math.max(n,e)),alignment:e}}function _a(t,e){return Math.ceil(t/e)*e}class ba extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(t,e){let r=this.length;return this.resize(r+1),this.emplace(r,t,e)}emplace(t,e,r){let n=2*t;return this.int16[n+0]=e,this.int16[n+1]=r,t}}ba.prototype.bytesPerElement=4,Ti("StructArrayLayout2i4",ba);class wa extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(t,e,r){let n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)}emplace(t,e,r,n){let i=3*t;return this.int16[i+0]=e,this.int16[i+1]=r,this.int16[i+2]=n,t}}wa.prototype.bytesPerElement=6,Ti("StructArrayLayout3i6",wa);class Ta extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(t,e,r,n){let i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)}emplace(t,e,r,n,i){let a=4*t;return this.int16[a+0]=e,this.int16[a+1]=r,this.int16[a+2]=n,this.int16[a+3]=i,t}}Ta.prototype.bytesPerElement=8,Ti("StructArrayLayout4i8",Ta);class ka extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(t,e,r,n,i,a){let o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)}emplace(t,e,r,n,i,a,o){let s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t}}ka.prototype.bytesPerElement=12,Ti("StructArrayLayout2i4i12",ka);class Aa extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(t,e,r,n,i,a){let o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)}emplace(t,e,r,n,i,a,o){let s=4*t,l=8*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.uint8[l+4]=n,this.uint8[l+5]=i,this.uint8[l+6]=a,this.uint8[l+7]=o,t}}Aa.prototype.bytesPerElement=8,Ti("StructArrayLayout2i4ub8",Aa);class Ma extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(t,e){let r=this.length;return this.resize(r+1),this.emplace(r,t,e)}emplace(t,e,r){let n=2*t;return this.float32[n+0]=e,this.float32[n+1]=r,t}}Ma.prototype.bytesPerElement=8,Ti("StructArrayLayout2f8",Ma);class Sa extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(t,e,r,n,i,a,o,s,l,c){let u=this.length;return this.resize(u+1),this.emplace(u,t,e,r,n,i,a,o,s,l,c)}emplace(t,e,r,n,i,a,o,s,l,c,u){let h=10*t;return this.uint16[h+0]=e,this.uint16[h+1]=r,this.uint16[h+2]=n,this.uint16[h+3]=i,this.uint16[h+4]=a,this.uint16[h+5]=o,this.uint16[h+6]=s,this.uint16[h+7]=l,this.uint16[h+8]=c,this.uint16[h+9]=u,t}}Sa.prototype.bytesPerElement=20,Ti("StructArrayLayout10ui20",Sa);class Ea extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(t,e,r,n,i,a,o,s,l,c,u,h){let f=this.length;return this.resize(f+1),this.emplace(f,t,e,r,n,i,a,o,s,l,c,u,h)}emplace(t,e,r,n,i,a,o,s,l,c,u,h,f){let p=12*t;return this.int16[p+0]=e,this.int16[p+1]=r,this.int16[p+2]=n,this.int16[p+3]=i,this.uint16[p+4]=a,this.uint16[p+5]=o,this.uint16[p+6]=s,this.uint16[p+7]=l,this.int16[p+8]=c,this.int16[p+9]=u,this.int16[p+10]=h,this.int16[p+11]=f,t}}Ea.prototype.bytesPerElement=24,Ti("StructArrayLayout4i4ui4i24",Ea);class Ca extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(t,e,r){let n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)}emplace(t,e,r,n){let i=3*t;return this.float32[i+0]=e,this.float32[i+1]=r,this.float32[i+2]=n,t}}Ca.prototype.bytesPerElement=12,Ti("StructArrayLayout3f12",Ca);class Ia extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)}emplaceBack(t){let e=this.length;return this.resize(e+1),this.emplace(e,t)}emplace(t,e){return this.uint32[1*t+0]=e,t}}Ia.prototype.bytesPerElement=4,Ti("StructArrayLayout1ul4",Ia);class La extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(t,e,r,n,i,a,o,s,l){let c=this.length;return this.resize(c+1),this.emplace(c,t,e,r,n,i,a,o,s,l)}emplace(t,e,r,n,i,a,o,s,l,c){let u=10*t,h=5*t;return this.int16[u+0]=e,this.int16[u+1]=r,this.int16[u+2]=n,this.int16[u+3]=i,this.int16[u+4]=a,this.int16[u+5]=o,this.uint32[h+3]=s,this.uint16[u+8]=l,this.uint16[u+9]=c,t}}La.prototype.bytesPerElement=20,Ti("StructArrayLayout6i1ul2ui20",La);class Pa extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(t,e,r,n,i,a){let o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)}emplace(t,e,r,n,i,a,o){let s=6*t;return this.int16[s+0]=e,this.int16[s+1]=r,this.int16[s+2]=n,this.int16[s+3]=i,this.int16[s+4]=a,this.int16[s+5]=o,t}}Pa.prototype.bytesPerElement=12,Ti("StructArrayLayout2i2i2i12",Pa);class za extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(t,e,r,n,i){let a=this.length;return this.resize(a+1),this.emplace(a,t,e,r,n,i)}emplace(t,e,r,n,i,a){let o=4*t,s=8*t;return this.float32[o+0]=e,this.float32[o+1]=r,this.float32[o+2]=n,this.int16[s+6]=i,this.int16[s+7]=a,t}}za.prototype.bytesPerElement=16,Ti("StructArrayLayout2f1f2i16",za);class Da extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(t,e,r,n,i,a){let o=this.length;return this.resize(o+1),this.emplace(o,t,e,r,n,i,a)}emplace(t,e,r,n,i,a,o){let s=16*t,l=4*t,c=8*t;return this.uint8[s+0]=e,this.uint8[s+1]=r,this.float32[l+1]=n,this.float32[l+2]=i,this.int16[c+6]=a,this.int16[c+7]=o,t}}Da.prototype.bytesPerElement=16,Ti("StructArrayLayout2ub2f2i16",Da);class Oa extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(t,e,r){let n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)}emplace(t,e,r,n){let i=3*t;return this.uint16[i+0]=e,this.uint16[i+1]=r,this.uint16[i+2]=n,t}}Oa.prototype.bytesPerElement=6,Ti("StructArrayLayout3ui6",Oa);class Ra extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(t,e,r,n,i,a,o,s,l,c,u,h,f,p,d,m,g){let y=this.length;return this.resize(y+1),this.emplace(y,t,e,r,n,i,a,o,s,l,c,u,h,f,p,d,m,g)}emplace(t,e,r,n,i,a,o,s,l,c,u,h,f,p,d,m,g,y){let v=24*t,x=12*t,_=48*t;return this.int16[v+0]=e,this.int16[v+1]=r,this.uint16[v+2]=n,this.uint16[v+3]=i,this.uint32[x+2]=a,this.uint32[x+3]=o,this.uint32[x+4]=s,this.uint16[v+10]=l,this.uint16[v+11]=c,this.uint16[v+12]=u,this.float32[x+7]=h,this.float32[x+8]=f,this.uint8[_+36]=p,this.uint8[_+37]=d,this.uint8[_+38]=m,this.uint32[x+10]=g,this.int16[v+22]=y,t}}Ra.prototype.bytesPerElement=48,Ti("StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48",Ra);class Fa extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(t,e,r,n,i,a,o,s,l,c,u,h,f,p,d,m,g,y,v,x,_,b,w,T,k,A,M,S){let E=this.length;return this.resize(E+1),this.emplace(E,t,e,r,n,i,a,o,s,l,c,u,h,f,p,d,m,g,y,v,x,_,b,w,T,k,A,M,S)}emplace(t,e,r,n,i,a,o,s,l,c,u,h,f,p,d,m,g,y,v,x,_,b,w,T,k,A,M,S,E){let C=32*t,I=16*t;return this.int16[C+0]=e,this.int16[C+1]=r,this.int16[C+2]=n,this.int16[C+3]=i,this.int16[C+4]=a,this.int16[C+5]=o,this.int16[C+6]=s,this.int16[C+7]=l,this.uint16[C+8]=c,this.uint16[C+9]=u,this.uint16[C+10]=h,this.uint16[C+11]=f,this.uint16[C+12]=p,this.uint16[C+13]=d,this.uint16[C+14]=m,this.uint16[C+15]=g,this.uint16[C+16]=y,this.uint16[C+17]=v,this.uint16[C+18]=x,this.uint16[C+19]=_,this.uint16[C+20]=b,this.uint16[C+21]=w,this.uint16[C+22]=T,this.uint32[I+12]=k,this.float32[I+13]=A,this.float32[I+14]=M,this.uint16[C+30]=S,this.uint16[C+31]=E,t}}Fa.prototype.bytesPerElement=64,Ti("StructArrayLayout8i15ui1ul2f2ui64",Fa);class Ba extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(t){let e=this.length;return this.resize(e+1),this.emplace(e,t)}emplace(t,e){return this.float32[1*t+0]=e,t}}Ba.prototype.bytesPerElement=4,Ti("StructArrayLayout1f4",Ba);class ja extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(t,e,r){let n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)}emplace(t,e,r,n){let i=3*t;return this.uint16[6*t+0]=e,this.float32[i+1]=r,this.float32[i+2]=n,t}}ja.prototype.bytesPerElement=12,Ti("StructArrayLayout1ui2f12",ja);class Na extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(t,e,r){let n=this.length;return this.resize(n+1),this.emplace(n,t,e,r)}emplace(t,e,r,n){let i=4*t;return this.uint32[2*t+0]=e,this.uint16[i+2]=r,this.uint16[i+3]=n,t}}Na.prototype.bytesPerElement=8,Ti("StructArrayLayout1ul2ui8",Na);class Ua extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(t,e){let r=this.length;return this.resize(r+1),this.emplace(r,t,e)}emplace(t,e,r){let n=2*t;return this.uint16[n+0]=e,this.uint16[n+1]=r,t}}Ua.prototype.bytesPerElement=4,Ti("StructArrayLayout2ui4",Ua);class Va extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(t){let e=this.length;return this.resize(e+1),this.emplace(e,t)}emplace(t,e){return this.uint16[1*t+0]=e,t}}Va.prototype.bytesPerElement=2,Ti("StructArrayLayout1ui2",Va);class qa extends va{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(t,e,r,n){let i=this.length;return this.resize(i+1),this.emplace(i,t,e,r,n)}emplace(t,e,r,n,i){let a=4*t;return this.float32[a+0]=e,this.float32[a+1]=r,this.float32[a+2]=n,this.float32[a+3]=i,t}}qa.prototype.bytesPerElement=16,Ti("StructArrayLayout4f16",qa);class Ha extends ya{get anchorPointX(){return this._structArray.int16[this._pos2+0]}get anchorPointY(){return this._structArray.int16[this._pos2+1]}get x1(){return this._structArray.int16[this._pos2+2]}get y1(){return this._structArray.int16[this._pos2+3]}get x2(){return this._structArray.int16[this._pos2+4]}get y2(){return this._structArray.int16[this._pos2+5]}get featureIndex(){return this._structArray.uint32[this._pos4+3]}get sourceLayerIndex(){return this._structArray.uint16[this._pos2+8]}get bucketIndex(){return this._structArray.uint16[this._pos2+9]}get anchorPoint(){return new a(this.anchorPointX,this.anchorPointY)}}Ha.prototype.size=20;class Ga extends La{get(t){return new Ha(this,t)}}Ti("CollisionBoxArray",Ga);class Wa extends ya{get anchorX(){return this._structArray.int16[this._pos2+0]}get anchorY(){return this._structArray.int16[this._pos2+1]}get glyphStartIndex(){return this._structArray.uint16[this._pos2+2]}get numGlyphs(){return this._structArray.uint16[this._pos2+3]}get vertexStartIndex(){return this._structArray.uint32[this._pos4+2]}get lineStartIndex(){return this._structArray.uint32[this._pos4+3]}get lineLength(){return this._structArray.uint32[this._pos4+4]}get segment(){return this._structArray.uint16[this._pos2+10]}get lowerSize(){return this._structArray.uint16[this._pos2+11]}get upperSize(){return this._structArray.uint16[this._pos2+12]}get lineOffsetX(){return this._structArray.float32[this._pos4+7]}get lineOffsetY(){return this._structArray.float32[this._pos4+8]}get writingMode(){return this._structArray.uint8[this._pos1+36]}get placedOrientation(){return this._structArray.uint8[this._pos1+37]}set placedOrientation(t){this._structArray.uint8[this._pos1+37]=t}get hidden(){return this._structArray.uint8[this._pos1+38]}set hidden(t){this._structArray.uint8[this._pos1+38]=t}get crossTileID(){return this._structArray.uint32[this._pos4+10]}set crossTileID(t){this._structArray.uint32[this._pos4+10]=t}get associatedIconIndex(){return this._structArray.int16[this._pos2+22]}}Wa.prototype.size=48;class Za extends Ra{get(t){return new Wa(this,t)}}Ti("PlacedSymbolArray",Za);class Ya extends ya{get anchorX(){return this._structArray.int16[this._pos2+0]}get anchorY(){return this._structArray.int16[this._pos2+1]}get rightJustifiedTextSymbolIndex(){return this._structArray.int16[this._pos2+2]}get centerJustifiedTextSymbolIndex(){return this._structArray.int16[this._pos2+3]}get leftJustifiedTextSymbolIndex(){return this._structArray.int16[this._pos2+4]}get verticalPlacedTextSymbolIndex(){return this._structArray.int16[this._pos2+5]}get placedIconSymbolIndex(){return this._structArray.int16[this._pos2+6]}get verticalPlacedIconSymbolIndex(){return this._structArray.int16[this._pos2+7]}get key(){return this._structArray.uint16[this._pos2+8]}get textBoxStartIndex(){return this._structArray.uint16[this._pos2+9]}get textBoxEndIndex(){return this._structArray.uint16[this._pos2+10]}get verticalTextBoxStartIndex(){return this._structArray.uint16[this._pos2+11]}get verticalTextBoxEndIndex(){return this._structArray.uint16[this._pos2+12]}get iconBoxStartIndex(){return this._structArray.uint16[this._pos2+13]}get iconBoxEndIndex(){return this._structArray.uint16[this._pos2+14]}get verticalIconBoxStartIndex(){return this._structArray.uint16[this._pos2+15]}get verticalIconBoxEndIndex(){return this._structArray.uint16[this._pos2+16]}get featureIndex(){return this._structArray.uint16[this._pos2+17]}get numHorizontalGlyphVertices(){return this._structArray.uint16[this._pos2+18]}get numVerticalGlyphVertices(){return this._structArray.uint16[this._pos2+19]}get numIconVertices(){return this._structArray.uint16[this._pos2+20]}get numVerticalIconVertices(){return this._structArray.uint16[this._pos2+21]}get useRuntimeCollisionCircles(){return this._structArray.uint16[this._pos2+22]}get crossTileID(){return this._structArray.uint32[this._pos4+12]}set crossTileID(t){this._structArray.uint32[this._pos4+12]=t}get textBoxScale(){return this._structArray.float32[this._pos4+13]}get collisionCircleDiameter(){return this._structArray.float32[this._pos4+14]}get textAnchorOffsetStartIndex(){return this._structArray.uint16[this._pos2+30]}get textAnchorOffsetEndIndex(){return this._structArray.uint16[this._pos2+31]}}Ya.prototype.size=64;class Xa extends Fa{get(t){return new Ya(this,t)}}Ti("SymbolInstanceArray",Xa);class $a extends Ba{getoffsetX(t){return this.float32[1*t+0]}}Ti("GlyphOffsetArray",$a);class Ka extends wa{getx(t){return this.int16[3*t+0]}gety(t){return this.int16[3*t+1]}gettileUnitDistanceFromAnchor(t){return this.int16[3*t+2]}}Ti("SymbolLineVertexArray",Ka);class Ja extends ya{get textAnchor(){return this._structArray.uint16[this._pos2+0]}get textOffset0(){return this._structArray.float32[this._pos4+1]}get textOffset1(){return this._structArray.float32[this._pos4+2]}}Ja.prototype.size=12;class Qa extends ja{get(t){return new Ja(this,t)}}Ti("TextAnchorOffsetArray",Qa);class to extends ya{get featureIndex(){return this._structArray.uint32[this._pos4+0]}get sourceLayerIndex(){return this._structArray.uint16[this._pos2+2]}get bucketIndex(){return this._structArray.uint16[this._pos2+3]}}to.prototype.size=8;class eo extends Na{get(t){return new to(this,t)}}Ti("FeatureIndexArray",eo);class ro extends ba{}class no extends ba{}class io extends ba{}class ao extends ka{}class oo extends Aa{}class so extends Ma{}class lo extends Sa{}class co extends Ea{}class uo extends Ca{}class ho extends Ia{}class fo extends Pa{}class po extends Da{}class mo extends Oa{}class go extends Ua{}let yo=xa([{name:"a_pos",components:2,type:"Int16"}],4),{members:vo}=yo;class xo{constructor(t=[]){this.segments=t}prepareSegment(t,e,r,n){let i=this.segments[this.segments.length-1];return t>xo.MAX_VERTEX_ARRAY_LENGTH&&A(`Max vertices per segment is ${xo.MAX_VERTEX_ARRAY_LENGTH}: bucket requested 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r,n,i,a,o,s,l,c;for(n=t.length-(r=3&t.length),i=e,o=3432918353,s=461845907,c=0;c>>16)*o&65535)<<16)&4294967295)<<15|l>>>17))*s+(((l>>>16)*s&65535)<<16)&4294967295)<<13|i>>>19))+((5*(i>>>16)&65535)<<16)&4294967295))+((58964+(a>>>16)&65535)<<16);switch(l=0,r){case 3:l^=(255&t.charCodeAt(c+2))<<16;case 2:l^=(255&t.charCodeAt(c+1))<<8;case 1:i^=l=(65535&(l=(l=(65535&(l^=255&t.charCodeAt(c)))*o+(((l>>>16)*o&65535)<<16)&4294967295)<<15|l>>>17))*s+(((l>>>16)*s&65535)<<16)&4294967295}return i^=t.length,i=2246822507*(65535&(i^=i>>>16))+((2246822507*(i>>>16)&65535)<<16)&4294967295,i=3266489909*(65535&(i^=i>>>13))+((3266489909*(i>>>16)&65535)<<16)&4294967295,(i^=i>>>16)>>>0},ko=function(t,e){for(var r,n=t.length,i=e^n,a=0;n>=4;)r=1540483477*(65535&(r=255&t.charCodeAt(a)|(255&t.charCodeAt(++a))<<8|(255&t.charCodeAt(++a))<<16|(255&t.charCodeAt(++a))<<24))+((1540483477*(r>>>16)&65535)<<16),i=1540483477*(65535&i)+((1540483477*(i>>>16)&65535)<<16)^(r=1540483477*(65535&(r^=r>>>24))+((1540483477*(r>>>16)&65535)<<16)),n-=4,++a;switch(n){case 3:i^=(255&t.charCodeAt(a+2))<<16;case 2:i^=(255&t.charCodeAt(a+1))<<8;case 1:i=1540483477*(65535&(i^=255&t.charCodeAt(a)))+((1540483477*(i>>>16)&65535)<<16)}return i=1540483477*(65535&(i^=i>>>13))+((1540483477*(i>>>16)&65535)<<16),(i^=i>>>15)>>>0};wo.exports=To,wo.exports.murmur3=To,wo.exports.murmur2=ko;var Ao=r(wo.exports);class Mo{constructor(){this.ids=[],this.positions=[],this.indexed=!1}add(t,e,r,n){this.ids.push(So(t)),this.positions.push(e,r,n)}getPositions(t){if(!this.indexed)throw new Error("Trying to get index, but feature positions are not indexed");let e=So(t),r=0,n=this.ids.length-1;for(;r>1;this.ids[t]>=e?n=t:r=t+1}let i=[];for(;this.ids[r]===e;)i.push({index:this.positions[3*r],start:this.positions[3*r+1],end:this.positions[3*r+2]}),r++;return i}static serialize(t,e){let r=new Float64Array(t.ids),n=new Uint32Array(t.positions);return Eo(r,n,0,r.length-1),e&&e.push(r.buffer,n.buffer),{ids:r,positions:n}}static deserialize(t){let e=new Mo;return e.ids=t.ids,e.positions=t.positions,e.indexed=!0,e}}function So(t){let e=+t;return!isNaN(e)&&e<=Number.MAX_SAFE_INTEGER?e:Ao(String(t))}function Eo(t,e,r,n){for(;r>1],a=r-1,o=n+1;for(;;){do{a++}while(t[a]i);if(a>=o)break;Co(t,a,o),Co(e,3*a,3*o),Co(e,3*a+1,3*o+1),Co(e,3*a+2,3*o+2)}o-r`u_${t}`)),this.type=r}setUniform(t,e,r){t.set(r.constantOr(this.value))}getBinding(t,e,r){return"color"===this.type?new zo(t,e):new Lo(t,e)}}class Fo{constructor(t,e){this.uniformNames=e.map((t=>`u_${t}`)),this.patternFrom=null,this.patternTo=null,this.pixelRatioFrom=1,this.pixelRatioTo=1}setConstantPatternPositions(t,e){this.pixelRatioFrom=e.pixelRatio,this.pixelRatioTo=t.pixelRatio,this.patternFrom=e.tlbr,this.patternTo=t.tlbr}setUniform(t,e,r,n){let i="u_pattern_to"===n?this.patternTo:"u_pattern_from"===n?this.patternFrom:"u_pixel_ratio_to"===n?this.pixelRatioTo:"u_pixel_ratio_from"===n?this.pixelRatioFrom:null;i&&t.set(i)}getBinding(t,e,r){return"u_pattern"===r.substr(0,9)?new Po(t,e):new Lo(t,e)}}class Bo{constructor(t,e,r,n){this.expression=t,this.type=r,this.maxValue=0,this.paintVertexAttributes=e.map((t=>({name:`a_${t}`,type:"Float32",components:"color"===r?2:1,offset:0}))),this.paintVertexArray=new n}populatePaintArray(t,e,r,n,i){let a=this.paintVertexArray.length,o=this.expression.evaluate(new Qi(0),e,{},n,[],i);this.paintVertexArray.resize(t),this._setPaintValue(a,t,o)}updatePaintArray(t,e,r,n){let i=this.expression.evaluate({zoom:0},r,n);this._setPaintValue(t,e,i)}_setPaintValue(t,e,r){if("color"===this.type){let n=Oo(r);for(let r=t;r`u_${t}_t`)),this.type=r,this.useIntegerZoom=n,this.zoom=i,this.maxValue=0,this.paintVertexAttributes=e.map((t=>({name:`a_${t}`,type:"Float32",components:"color"===r?4:2,offset:0}))),this.paintVertexArray=new a}populatePaintArray(t,e,r,n,i){let a=this.expression.evaluate(new Qi(this.zoom),e,{},n,[],i),o=this.expression.evaluate(new Qi(this.zoom+1),e,{},n,[],i),s=this.paintVertexArray.length;this.paintVertexArray.resize(t),this._setPaintValue(s,t,a,o)}updatePaintArray(t,e,r,n){let i=this.expression.evaluate({zoom:this.zoom},r,n),a=this.expression.evaluate({zoom:this.zoom+1},r,n);this._setPaintValue(t,e,i,a)}_setPaintValue(t,e,r,n){if("color"===this.type){let i=Oo(r),a=Oo(n);for(let r=t;r`#define HAS_UNIFORM_${t}`)))}return t}getBinderAttributes(){let t=[];for(let e in this.binders){let r=this.binders[e];if(r instanceof Bo||r instanceof jo)for(let e=0;e!0){this.programConfigurations={};for(let n of t)this.programConfigurations[n.id]=new Uo(n,e,r);this.needsUpload=!1,this._featureMap=new Mo,this._bufferOffset=0}populatePaintArrays(t,e,r,n,i,a){for(let r in this.programConfigurations)this.programConfigurations[r].populatePaintArrays(t,e,n,i,a);void 0!==e.id&&this._featureMap.add(e.id,r,this._bufferOffset,t),this._bufferOffset=t,this.needsUpload=!0}updatePaintArrays(t,e,r,n){for(let i of r)this.needsUpload=this.programConfigurations[i.id].updatePaintArrays(t,this._featureMap,e,i,n)||this.needsUpload}get(t){return this.programConfigurations[t]}upload(t){if(this.needsUpload){for(let e in this.programConfigurations)this.programConfigurations[e].upload(t);this.needsUpload=!1}}destroy(){for(let t in this.programConfigurations)this.programConfigurations[t].destroy()}}function qo(t,e){return{"text-opacity":["opacity"],"icon-opacity":["opacity"],"text-color":["fill_color"],"icon-color":["fill_color"],"text-halo-color":["halo_color"],"icon-halo-color":["halo_color"],"text-halo-blur":["halo_blur"],"icon-halo-blur":["halo_blur"],"text-halo-width":["halo_width"],"icon-halo-width":["halo_width"],"line-gap-width":["gapwidth"],"line-pattern":["pattern_to","pattern_from","pixel_ratio_to","pixel_ratio_from"],"fill-pattern":["pattern_to","pattern_from","pixel_ratio_to","pixel_ratio_from"],"fill-extrusion-pattern":["pattern_to","pattern_from","pixel_ratio_to","pixel_ratio_from"]}[t]||[t.replace(`${e}-`,"").replace(/-/g,"_")]}function Ho(t,e,r){let n={color:{source:Ma,composite:qa},number:{source:Ba,composite:Ma}},i={"line-pattern":{source:lo,composite:lo},"fill-pattern":{source:lo,composite:lo},"fill-extrusion-pattern":{source:lo,composite:lo}}[t];return i&&i[r]||n[e][r]}Ti("ConstantBinder",Ro),Ti("CrossFadedConstantBinder",Fo),Ti("SourceExpressionBinder",Bo),Ti("CrossFadedCompositeBinder",No),Ti("CompositeExpressionBinder",jo),Ti("ProgramConfiguration",Uo,{omit:["_buffers"]}),Ti("ProgramConfigurationSet",Vo);let Go,Wo,Zo=8192,Yo=Math.pow(2,14)-1,Xo=-Yo-1;function $o(t){let e=Zo/t.extent,r=t.loadGeometry();for(let t=0;tr.x+1||ar.y+1)&&A("Geometry exceeds allowed extent, reduce your vector tile buffer size")}}return r}function Ko(t,e){return{type:t.type,id:t.id,properties:t.properties,geometry:e?$o(t):[]}}function Jo(t,e,r,n,i){t.emplaceBack(2*e+(n+1)/2,2*r+(i+1)/2)}class Qo{constructor(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((t=>t.id)),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new no,this.indexArray=new mo,this.segments=new xo,this.programConfigurations=new Vo(t.layers,t.zoom),this.stateDependentLayerIds=this.layers.filter((t=>t.isStateDependent())).map((t=>t.id))}populate(t,e,r){let n=this.layers[0],i=[],a=null,o=!1;"circle"===n.type&&(a=n.layout.get("circle-sort-key"),o=!a.isConstant());for(let{feature:e,id:n,index:s,sourceLayerIndex:l}of t){let t=this.layers[0]._featureFilter.needGeometry,c=Ko(e,t);if(!this.layers[0]._featureFilter.filter(new Qi(this.zoom),c,r))continue;let u=o?a.evaluate(c,{},r):void 0,h={id:n,properties:e.properties,type:e.type,sourceLayerIndex:l,index:s,geometry:t?c.geometry:$o(e),patterns:{},sortKey:u};i.push(h)}o&&i.sort(((t,e)=>t.sortKey-e.sortKey));for(let n of i){let{geometry:i,index:a,sourceLayerIndex:o}=n,s=t[a].feature;this.addFeature(n,i,a,r),e.featureIndex.insert(s,i,a,o,this.index)}}update(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)}isEmpty(){return 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n=r.prev,i=r.next.next;!il(n,i)&&al(n,r,r.next,i)&&ll(n,i)&&ll(i,n)&&(e.push(n.i,r.i,i.i),hl(r),hl(r.next),r=t=i),r=r.next}while(r!==t);return Hs(r)}function Xs(t,e,r,n,i,a){let o=t;do{let t=o.next.next;for(;t!==o.prev;){if(o.i!==t.i&&rl(o,t)){let s=cl(o,t);return o=Hs(o,o.next),s=Hs(s,s.next),Gs(o,e,r,n,i,a,0),void Gs(s,e,r,n,i,a,0)}t=t.next}o=o.next}while(o!==t)}function $s(t,e){return t.x-e.x}function Ks(t,e){let r=function(t,e){let r,n=e,i=t.x,a=t.y,o=-1/0;do{if(a<=n.y&&a>=n.next.y&&n.next.y!==n.y){let t=n.x+(a-n.y)*(n.next.x-n.x)/(n.next.y-n.y);if(t<=i&&t>o&&(o=t,r=n.x=n.x&&n.x>=l&&i!==n.x&&el(ar.x||n.x===r.x&&Js(r,n)))&&(r=n,u=e)}n=n.next}while(n!==s);return r}(t,e);if(!r)return e;let n=cl(r,t);return Hs(n,n.next),Hs(r,r.next)}function Js(t,e){return nl(t.prev,t,e.prev)<0&&nl(e.next,t,t.next)<0}function 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i=sl(nl(t,e,r)),a=sl(nl(t,e,n)),o=sl(nl(r,n,t)),s=sl(nl(r,n,e));return i!==a&&o!==s||!(0!==i||!ol(t,r,e))||!(0!==a||!ol(t,n,e))||!(0!==o||!ol(r,t,n))||!(0!==s||!ol(r,e,n))}function ol(t,e,r){return e.x<=Math.max(t.x,r.x)&&e.x>=Math.min(t.x,r.x)&&e.y<=Math.max(t.y,r.y)&&e.y>=Math.min(t.y,r.y)}function sl(t){return t>0?1:t<0?-1:0}function ll(t,e){return nl(t.prev,t,t.next)<0?nl(t,e,t.next)>=0&&nl(t,t.prev,e)>=0:nl(t,e,t.prev)<0||nl(t,t.next,e)<0}function cl(t,e){let r=fl(t.i,t.x,t.y),n=fl(e.i,e.x,e.y),i=t.next,a=e.prev;return t.next=e,e.prev=t,r.next=i,i.prev=r,n.next=r,r.prev=n,a.next=n,n.prev=a,n}function ul(t,e,r,n){let i=fl(t,e,r);return n?(i.next=n.next,i.prev=n,n.next.prev=i,n.next=i):(i.prev=i,i.next=i),i}function hl(t){t.next.prev=t.prev,t.prev.next=t.next,t.prevZ&&(t.prevZ.nextZ=t.nextZ),t.nextZ&&(t.nextZ.prevZ=t.prevZ)}function fl(t,e,r){return{i:t,x:e,y:r,prev:null,next:null,z:0,prevZ:null,nextZ:null,steiner:!1}}function pl(t,e,r){let n=r.patternDependencies,i=!1;for(let r of e){let e=r.paint.get(`${t}-pattern`);e.isConstant()||(i=!0);let a=e.constantOr(null);a&&(i=!0,n[a.to]=!0,n[a.from]=!0)}return i}function dl(t,e,r,n,i){let a=i.patternDependencies;for(let o of e){let e=o.paint.get(`${t}-pattern`).value;if("constant"!==e.kind){let t=e.evaluate({zoom:n-1},r,{},i.availableImages),s=e.evaluate({zoom:n},r,{},i.availableImages),l=e.evaluate({zoom:n+1},r,{},i.availableImages);t=t&&t.name?t.name:t,s=s&&s.name?s.name:s,l=l&&l.name?l.name:l,a[t]=!0,a[s]=!0,a[l]=!0,r.patterns[o.id]={min:t,mid:s,max:l}}}return r}class ml{constructor(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((t=>t.id)),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.layoutVertexArray=new io,this.indexArray=new mo,this.indexArray2=new go,this.programConfigurations=new Vo(t.layers,t.zoom),this.segments=new xo,this.segments2=new xo,this.stateDependentLayerIds=this.layers.filter((t=>t.isStateDependent())).map((t=>t.id))}populate(t,e,r){this.hasPattern=pl("fill",this.layers,e);let n=this.layers[0].layout.get("fill-sort-key"),i=!n.isConstant(),a=[];for(let{feature:o,id:s,index:l,sourceLayerIndex:c}of t){let t=this.layers[0]._featureFilter.needGeometry,u=Ko(o,t);if(!this.layers[0]._featureFilter.filter(new Qi(this.zoom),u,r))continue;let h=i?n.evaluate(u,{},r,e.availableImages):void 0,f={id:s,properties:o.properties,type:o.type,sourceLayerIndex:c,index:l,geometry:t?u.geometry:$o(o),patterns:{},sortKey:h};a.push(f)}i&&a.sort(((t,e)=>t.sortKey-e.sortKey));for(let n of a){let{geometry:i,index:a,sourceLayerIndex:o}=n;if(this.hasPattern){let t=dl("fill",this.layers,n,this.zoom,e);this.patternFeatures.push(t)}else this.addFeature(n,i,a,r,{});e.featureIndex.insert(t[a].feature,i,a,o,this.index)}}update(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)}addFeatures(t,e,r){for(let t of this.patternFeatures)this.addFeature(t,t.geometry,t.index,e,r)}isEmpty(){return 0===this.layoutVertexArray.length}uploadPending(){return!this.uploaded||this.programConfigurations.needsUpload}upload(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Us),this.indexBuffer=t.createIndexBuffer(this.indexArray),this.indexBuffer2=t.createIndexBuffer(this.indexArray2)),this.programConfigurations.upload(t),this.uploaded=!0}destroy(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.indexBuffer2.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.segments2.destroy())}addFeature(t,e,r,n,i){for(let t of _r(e,500)){let e=0;for(let r of t)e+=r.length;let r=this.segments.prepareSegment(e,this.layoutVertexArray,this.indexArray),n=r.vertexLength,i=[],a=[];for(let e of t){if(0===e.length)continue;e!==t[0]&&a.push(i.length/2);let r=this.segments2.prepareSegment(e.length,this.layoutVertexArray,this.indexArray2),n=r.vertexLength;this.layoutVertexArray.emplaceBack(e[0].x,e[0].y),this.indexArray2.emplaceBack(n+e.length-1,n),i.push(e[0].x),i.push(e[0].y);for(let t=1;t>3}if(i--,1===n||2===n)a+=t.readSVarint(),o+=t.readSVarint(),1===n&&(e&&s.push(e),e=[]),e.push(new wl(a,o));else{if(7!==n)throw new Error("unknown command "+n);e&&e.push(e[0].clone())}}return e&&s.push(e),s},kl.prototype.bbox=function(){var t=this._pbf;t.pos=this._geometry;for(var e=t.readVarint()+t.pos,r=1,n=0,i=0,a=0,o=1/0,s=-1/0,l=1/0,c=-1/0;t.pos>3}if(n--,1===r||2===r)(i+=t.readSVarint())s&&(s=i),(a+=t.readSVarint())c&&(c=a);else if(7!==r)throw new Error("unknown command "+r)}return[o,l,s,c]},kl.prototype.toGeoJSON=function(t,e,r){var n,i,a=this.extent*Math.pow(2,r),o=this.extent*t,s=this.extent*e,l=this.loadGeometry(),c=kl.types[this.type];function u(t){for(var e=0;e>3;e=1===n?t.readString():2===n?t.readFloat():3===n?t.readDouble():4===n?t.readVarint64():5===n?t.readVarint():6===n?t.readSVarint():7===n?t.readBoolean():null}return e}(r))}Cl.prototype.feature=function(t){if(t<0||t>=this._features.length)throw new Error("feature index out of bounds");this._pbf.pos=this._features[t];var e=this._pbf.readVarint()+this._pbf.pos;return new Sl(this._pbf,e,this.extent,this._keys,this._values)};var Ll=El;function Pl(t,e,r){if(3===t){var n=new Ll(r,r.readVarint()+r.pos);n.length&&(e[n.name]=n)}}bl.VectorTile=function(t,e){this.layers=t.readFields(Pl,{},e)},bl.VectorTileFeature=Tl,bl.VectorTileLayer=El;let zl,Dl=bl.VectorTileFeature.types,Ol=Math.pow(2,13);function Rl(t,e,r,n,i,a,o,s){t.emplaceBack(e,r,2*Math.floor(n*Ol)+o,i*Ol*2,a*Ol*2,Math.round(s))}class Fl{constructor(t){this.zoom=t.zoom,this.overscaling=t.overscaling,this.layers=t.layers,this.layerIds=this.layers.map((t=>t.id)),this.index=t.index,this.hasPattern=!1,this.layoutVertexArray=new ao,this.centroidVertexArray=new ro,this.indexArray=new mo,this.programConfigurations=new Vo(t.layers,t.zoom),this.segments=new xo,this.stateDependentLayerIds=this.layers.filter((t=>t.isStateDependent())).map((t=>t.id))}populate(t,e,r){this.features=[],this.hasPattern=pl("fill-extrusion",this.layers,e);for(let{feature:n,id:i,index:a,sourceLayerIndex:o}of t){let t=this.layers[0]._featureFilter.needGeometry,s=Ko(n,t);if(!this.layers[0]._featureFilter.filter(new Qi(this.zoom),s,r))continue;let l={id:i,sourceLayerIndex:o,index:a,geometry:t?s.geometry:$o(n),properties:n.properties,type:n.type,patterns:{}};this.hasPattern?this.features.push(dl("fill-extrusion",this.layers,l,this.zoom,e)):this.addFeature(l,l.geometry,a,r,{}),e.featureIndex.insert(n,l.geometry,a,o,this.index,!0)}}addFeatures(t,e,r){for(let t of this.features){let{geometry:n}=t;this.addFeature(t,n,t.index,e,r)}}update(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)}isEmpty(){return 0===this.layoutVertexArray.length&&0===this.centroidVertexArray.length}uploadPending(){return!this.uploaded||this.programConfigurations.needsUpload}upload(t){this.uploaded||(this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,_l),this.centroidVertexBuffer=t.createVertexBuffer(this.centroidVertexArray,xl.members,!0),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0}destroy(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.centroidVertexBuffer.destroy())}addFeature(t,e,r,n,i){for(let r of _r(e,500)){let e={x:0,y:0,vertexCount:0},n=0;for(let t of r)n+=t.length;let i=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray);for(let t of r){if(0===t.length||jl(t))continue;let r=0;for(let n=0;n=1){let o=t[n-1];if(!Bl(a,o)){i.vertexLength+4>xo.MAX_VERTEX_ARRAY_LENGTH&&(i=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));let t=a.sub(o)._perp()._unit(),n=o.dist(a);r+n>32768&&(r=0),Rl(this.layoutVertexArray,a.x,a.y,t.x,t.y,0,0,r),Rl(this.layoutVertexArray,a.x,a.y,t.x,t.y,0,1,r),e.x+=2*a.x,e.y+=2*a.y,e.vertexCount+=2,r+=n,Rl(this.layoutVertexArray,o.x,o.y,t.x,t.y,0,0,r),Rl(this.layoutVertexArray,o.x,o.y,t.x,t.y,0,1,r),e.x+=2*o.x,e.y+=2*o.y,e.vertexCount+=2;let s=i.vertexLength;this.indexArray.emplaceBack(s,s+2,s+1),this.indexArray.emplaceBack(s+1,s+2,s+3),i.vertexLength+=4,i.primitiveLength+=2}}}}if(i.vertexLength+n>xo.MAX_VERTEX_ARRAY_LENGTH&&(i=this.segments.prepareSegment(n,this.layoutVertexArray,this.indexArray)),"Polygon"!==Dl[t.type])continue;let a=[],o=[],s=i.vertexLength;for(let t of r)if(0!==t.length){t!==r[0]&&o.push(a.length/2);for(let r=0;rZo)||t.y===e.y&&(t.y<0||t.y>Zo)}function jl(t){return t.every((t=>t.x<0))||t.every((t=>t.x>Zo))||t.every((t=>t.y<0))||t.every((t=>t.y>Zo))}Ti("FillExtrusionBucket",Fl,{omit:["layers","features"]});var Nl={get paint(){return zl=zl||new pa({"fill-extrusion-opacity":new la(Y["paint_fill-extrusion"]["fill-extrusion-opacity"]),"fill-extrusion-color":new ca(Y["paint_fill-extrusion"]["fill-extrusion-color"]),"fill-extrusion-translate":new la(Y["paint_fill-extrusion"]["fill-extrusion-translate"]),"fill-extrusion-translate-anchor":new la(Y["paint_fill-extrusion"]["fill-extrusion-translate-anchor"]),"fill-extrusion-pattern":new ua(Y["paint_fill-extrusion"]["fill-extrusion-pattern"]),"fill-extrusion-height":new ca(Y["paint_fill-extrusion"]["fill-extrusion-height"]),"fill-extrusion-base":new ca(Y["paint_fill-extrusion"]["fill-extrusion-base"]),"fill-extrusion-vertical-gradient":new la(Y["paint_fill-extrusion"]["fill-extrusion-vertical-gradient"])})}};class Ul extends ma{constructor(t){super(t,Nl)}createBucket(t){return new Fl(t)}queryRadius(){return fs(this.paint.get("fill-extrusion-translate"))}is3D(){return!0}queryIntersectsFeature(t,e,r,n,i,o,s,l){let c=ps(t,this.paint.get("fill-extrusion-translate"),this.paint.get("fill-extrusion-translate-anchor"),o.angle,s),u=this.paint.get("fill-extrusion-height").evaluate(e,r),h=this.paint.get("fill-extrusion-base").evaluate(e,r),f=function(t,e){let r=[];for(let n of t){let t=[n.x,n.y,0,1];bs(t,t,e),r.push(new a(t[0]/t[3],t[1]/t[3]))}return r}(c,l),p=function(t,e,r,n){let i=[],o=[],s=n[8]*e,l=n[9]*e,c=n[10]*e,u=n[11]*e,h=n[8]*r,f=n[9]*r,p=n[10]*r,d=n[11]*r;for(let e of t){let t=[],r=[];for(let i of e){let e=i.x,o=i.y,m=n[0]*e+n[4]*o+n[12],g=n[1]*e+n[5]*o+n[13],y=n[2]*e+n[6]*o+n[14],v=n[3]*e+n[7]*o+n[15],x=y+c,_=v+u,b=m+h,w=g+f,T=y+p,k=v+d,A=new a((m+s)/_,(g+l)/_);A.z=x/_,t.push(A);let M=new a(b/k,w/k);M.z=T/k,r.push(M)}i.push(t),o.push(r)}return[i,o]}(n,h,u,l);return function(t,e,r){let n=1/0;rs(r,e)&&(n=ql(r,e[0]));for(let i=0;it.id)),this.index=t.index,this.hasPattern=!1,this.patternFeatures=[],this.lineClipsArray=[],this.gradients={},this.layers.forEach((t=>{this.gradients[t.id]={}})),this.layoutVertexArray=new oo,this.layoutVertexArray2=new so,this.indexArray=new mo,this.programConfigurations=new Vo(t.layers,t.zoom),this.segments=new xo,this.maxLineLength=0,this.stateDependentLayerIds=this.layers.filter((t=>t.isStateDependent())).map((t=>t.id))}populate(t,e,r){this.hasPattern=pl("line",this.layers,e);let n=this.layers[0].layout.get("line-sort-key"),i=!n.isConstant(),a=[];for(let{feature:e,id:o,index:s,sourceLayerIndex:l}of t){let t=this.layers[0]._featureFilter.needGeometry,c=Ko(e,t);if(!this.layers[0]._featureFilter.filter(new Qi(this.zoom),c,r))continue;let u=i?n.evaluate(c,{},r):void 0,h={id:o,properties:e.properties,type:e.type,sourceLayerIndex:l,index:s,geometry:t?c.geometry:$o(e),patterns:{},sortKey:u};a.push(h)}i&&a.sort(((t,e)=>t.sortKey-e.sortKey));for(let n of a){let{geometry:i,index:a,sourceLayerIndex:o}=n;if(this.hasPattern){let t=dl("line",this.layers,n,this.zoom,e);this.patternFeatures.push(t)}else this.addFeature(n,i,a,r,{});e.featureIndex.insert(t[a].feature,i,a,o,this.index)}}update(t,e,r){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(t,e,this.stateDependentLayers,r)}addFeatures(t,e,r){for(let t of this.patternFeatures)this.addFeature(t,t.geometry,t.index,e,r)}isEmpty(){return 0===this.layoutVertexArray.length}uploadPending(){return!this.uploaded||this.programConfigurations.needsUpload}upload(t){this.uploaded||(0!==this.layoutVertexArray2.length&&(this.layoutVertexBuffer2=t.createVertexBuffer(this.layoutVertexArray2,Xl)),this.layoutVertexBuffer=t.createVertexBuffer(this.layoutVertexArray,Zl),this.indexBuffer=t.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(t),this.uploaded=!0}destroy(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())}lineFeatureClips(t){if(t.properties&&Object.prototype.hasOwnProperty.call(t.properties,"mapbox_clip_start")&&Object.prototype.hasOwnProperty.call(t.properties,"mapbox_clip_end"))return{start:+t.properties.mapbox_clip_start,end:+t.properties.mapbox_clip_end}}addFeature(t,e,r,n,i){let a=this.layers[0].layout,o=a.get("line-join").evaluate(t,{}),s=a.get("line-cap"),l=a.get("line-miter-limit"),c=a.get("line-round-limit");this.lineClips=this.lineFeatureClips(t);for(let r of e)this.addLine(r,t,o,s,l,c);this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,t,r,i,n)}addLine(t,e,r,n,i,a){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,this.lineClips){this.lineClipsArray.push(this.lineClips);for(let e=0;e=2&&t[s-1].equals(t[s-2]);)s--;let l=0;for(;l0;if(b&&e>l){let t=c.dist(u);if(t>2*d){let e=c.sub(c.sub(u)._mult(d/t)._round());this.updateDistance(u,e),this.addCurrentVertex(e,f,0,0,m),u=e}}let T=u&&h,k=T?r:o?"butt":n;if(T&&"round"===k&&(xi&&(k="bevel"),"bevel"===k&&(x>2&&(k="flipbevel"),x100)g=p.mult(-1);else{let t=x*f.add(p).mag()/f.sub(p).mag();g._perp()._mult(t*(w?-1:1))}this.addCurrentVertex(c,g,0,0,m),this.addCurrentVertex(c,g.mult(-1),0,0,m)}else if("bevel"===k||"fakeround"===k){let t=-Math.sqrt(x*x-1),e=w?t:0,r=w?0:t;if(u&&this.addCurrentVertex(c,f,e,r,m),"fakeround"===k){let t=Math.round(180*_/Math.PI/20);for(let e=1;e2*d){let e=c.add(h.sub(c)._mult(d/t)._round());this.updateDistance(c,e),this.addCurrentVertex(e,p,0,0,m),c=e}}}}addCurrentVertex(t,e,r,n,i,a=!1){let o=e.y*n-e.x,s=-e.y-e.x*n;this.addHalfVertex(t,e.x+e.y*r,e.y-e.x*r,a,!1,r,i),this.addHalfVertex(t,o,s,a,!0,-n,i),this.distance>Jl/2&&0===this.totalDistance&&(this.distance=0,this.updateScaledDistance(),this.addCurrentVertex(t,e,r,n,i,a))}addHalfVertex({x:t,y:e},r,n,i,a,o,s){let l=.5*(this.lineClips?this.scaledDistance*(Jl-1):this.scaledDistance);this.layoutVertexArray.emplaceBack((t<<1)+(i?1:0),(e<<1)+(a?1:0),Math.round(63*r)+128,Math.round(63*n)+128,1+(0===o?0:o<0?-1:1)|(63&l)<<2,l>>6),this.lineClips&&this.layoutVertexArray2.emplaceBack((this.scaledDistance-this.lineClips.start)/(this.lineClips.end-this.lineClips.start),this.lineClipsArray.length);let c=s.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,c),s.primitiveLength++),a?this.e2=c:this.e1=c}updateScaledDistance(){this.scaledDistance=this.lineClips?this.lineClips.start+(this.lineClips.end-this.lineClips.start)*this.distance/this.totalDistance:this.distance}updateDistance(t,e){this.distance+=t.dist(e),this.updateScaledDistance()}}Ti("LineBucket",Ql,{omit:["layers","patternFeatures"]});var tc={get paint(){return Gl=Gl||new pa({"line-opacity":new ca(Y.paint_line["line-opacity"]),"line-color":new ca(Y.paint_line["line-color"]),"line-translate":new la(Y.paint_line["line-translate"]),"line-translate-anchor":new la(Y.paint_line["line-translate-anchor"]),"line-width":new ca(Y.paint_line["line-width"]),"line-gap-width":new ca(Y.paint_line["line-gap-width"]),"line-offset":new ca(Y.paint_line["line-offset"]),"line-blur":new ca(Y.paint_line["line-blur"]),"line-dasharray":new ha(Y.paint_line["line-dasharray"]),"line-pattern":new ua(Y.paint_line["line-pattern"]),"line-gradient":new fa(Y.paint_line["line-gradient"])})},get layout(){return Hl=Hl||new pa({"line-cap":new la(Y.layout_line["line-cap"]),"line-join":new ca(Y.layout_line["line-join"]),"line-miter-limit":new la(Y.layout_line["line-miter-limit"]),"line-round-limit":new la(Y.layout_line["line-round-limit"]),"line-sort-key":new ca(Y.layout_line["line-sort-key"])})}};class ec extends ca{possiblyEvaluate(t,e){return e=new Qi(Math.floor(e.zoom),{now:e.now,fadeDuration:e.fadeDuration,zoomHistory:e.zoomHistory,transition:e.transition}),super.possiblyEvaluate(t,e)}evaluate(t,e,r,n){return e=x({},e,{zoom:Math.floor(e.zoom)}),super.evaluate(t,e,r,n)}}let rc;class nc extends ma{constructor(t){super(t,tc),this.gradientVersion=0,rc||(rc=new ec(tc.paint.properties["line-width"].specification),rc.useIntegerZoom=!0)}_handleSpecialPaintPropertyUpdate(t){if("line-gradient"===t){let t=this.gradientExpression();this.stepInterpolant=!(void 0===t._styleExpression)&&t._styleExpression.expression instanceof Ae,this.gradientVersion=(this.gradientVersion+1)%Number.MAX_SAFE_INTEGER}}gradientExpression(){return this._transitionablePaint._values["line-gradient"].value.expression}recalculate(t,e){super.recalculate(t,e),this.paint._values["line-floorwidth"]=rc.possiblyEvaluate(this._transitioningPaint._values["line-width"].value,t)}createBucket(t){return new Ql(t)}queryRadius(t){let e=t,r=ic(hs("line-width",this,e),hs("line-gap-width",this,e)),n=hs("line-offset",this,e);return r/2+Math.abs(n)+fs(this.paint.get("line-translate"))}queryIntersectsFeature(t,e,r,n,i,o,s){let l=ps(t,this.paint.get("line-translate"),this.paint.get("line-translate-anchor"),o.angle,s),c=s/2*ic(this.paint.get("line-width").evaluate(e,r),this.paint.get("line-gap-width").evaluate(e,r)),u=this.paint.get("line-offset").evaluate(e,r);return u&&(n=function(t,e){let r=[];for(let n=0;n=3)for(let e=0;e0?e+2*t:t}let ac=xa([{name:"a_pos_offset",components:4,type:"Int16"},{name:"a_data",components:4,type:"Uint16"},{name:"a_pixeloffset",components:4,type:"Int16"}],4),oc=xa([{name:"a_projected_pos",components:3,type:"Float32"}],4);xa([{name:"a_fade_opacity",components:1,type:"Uint32"}],4);let sc=xa([{name:"a_placed",components:2,type:"Uint8"},{name:"a_shift",components:2,type:"Float32"},{name:"a_box_real",components:2,type:"Int16"}]);xa([{type:"Int16",name:"anchorPointX"},{type:"Int16",name:"anchorPointY"},{type:"Int16",name:"x1"},{type:"Int16",name:"y1"},{type:"Int16",name:"x2"},{type:"Int16",name:"y2"},{type:"Uint32",name:"featureIndex"},{type:"Uint16",name:"sourceLayerIndex"},{type:"Uint16",name:"bucketIndex"}]);let lc=xa([{name:"a_pos",components:2,type:"Int16"},{name:"a_anchor_pos",components:2,type:"Int16"},{name:"a_extrude",components:2,type:"Int16"}],4),cc=xa([{name:"a_pos",components:2,type:"Float32"},{name:"a_radius",components:1,type:"Float32"},{name:"a_flags",components:2,type:"Int16"}],4);function uc(t,e,r){return t.sections.forEach((t=>{t.text=function(t,e,r){let n=e.layout.get("text-transform").evaluate(r,{});return"uppercase"===n?t=t.toLocaleUpperCase():"lowercase"===n&&(t=t.toLocaleLowerCase()),Ji.applyArabicShaping&&(t=Ji.applyArabicShaping(t)),t}(t.text,e,r)})),t}xa([{name:"triangle",components:3,type:"Uint16"}]),xa([{type:"Int16",name:"anchorX"},{type:"Int16",name:"anchorY"},{type:"Uint16",name:"glyphStartIndex"},{type:"Uint16",name:"numGlyphs"},{type:"Uint32",name:"vertexStartIndex"},{type:"Uint32",name:"lineStartIndex"},{type:"Uint32",name:"lineLength"},{type:"Uint16",name:"segment"},{type:"Uint16",name:"lowerSize"},{type:"Uint16",name:"upperSize"},{type:"Float32",name:"lineOffsetX"},{type:"Float32",name:"lineOffsetY"},{type:"Uint8",name:"writingMode"},{type:"Uint8",name:"placedOrientation"},{type:"Uint8",name:"hidden"},{type:"Uint32",name:"crossTileID"},{type:"Int16",name:"associatedIconIndex"}]),xa([{type:"Int16",name:"anchorX"},{type:"Int16",name:"anchorY"},{type:"Int16",name:"rightJustifiedTextSymbolIndex"},{type:"Int16",name:"centerJustifiedTextSymbolIndex"},{type:"Int16",name:"leftJustifiedTextSymbolIndex"},{type:"Int16",name:"verticalPlacedTextSymbolIndex"},{type:"Int16",name:"placedIconSymbolIndex"},{type:"Int16",name:"verticalPlacedIconSymbolIndex"},{type:"Uint16",name:"key"},{type:"Uint16",name:"textBoxStartIndex"},{type:"Uint16",name:"textBoxEndIndex"},{type:"Uint16",name:"verticalTextBoxStartIndex"},{type:"Uint16",name:"verticalTextBoxEndIndex"},{type:"Uint16",name:"iconBoxStartIndex"},{type:"Uint16",name:"iconBoxEndIndex"},{type:"Uint16",name:"verticalIconBoxStartIndex"},{type:"Uint16",name:"verticalIconBoxEndIndex"},{type:"Uint16",name:"featureIndex"},{type:"Uint16",name:"numHorizontalGlyphVertices"},{type:"Uint16",name:"numVerticalGlyphVertices"},{type:"Uint16",name:"numIconVertices"},{type:"Uint16",name:"numVerticalIconVertices"},{type:"Uint16",name:"useRuntimeCollisionCircles"},{type:"Uint32",name:"crossTileID"},{type:"Float32",name:"textBoxScale"},{type:"Float32",name:"collisionCircleDiameter"},{type:"Uint16",name:"textAnchorOffsetStartIndex"},{type:"Uint16",name:"textAnchorOffsetEndIndex"}]),xa([{type:"Float32",name:"offsetX"}]),xa([{type:"Int16",name:"x"},{type:"Int16",name:"y"},{type:"Int16",name:"tileUnitDistanceFromAnchor"}]),xa([{type:"Uint16",name:"textAnchor"},{type:"Float32",components:2,name:"textOffset"}]);let hc={"!":"︕","#":"＃",$:"＄","%":"％","&":"＆","(":"︵",")":"︶","*":"＊","+":"＋",",":"︐","-":"︲",".":"・","/":"／",":":"︓",";":"︔","<":"︿","=":"＝",">":"﹀","?":"︖","@":"＠","[":"﹇","\\":"＼","]":"﹈","^":"＾",_:"︳","`":"｀","{":"︷","|":"―","}":"︸","~":"～","¢":"￠","£":"￡","¥":"￥","¦":"￤","¬":"￢","¯":"￣","–":"︲","—":"︱","‘":"﹃","’":"﹄","“":"﹁","”":"﹂","…":"︙","‧":"・","₩":"￦","、":"︑","。":"︒","〈":"︿","〉":"﹀","《":"︽","》":"︾","「":"﹁","」":"﹂","『":"﹃","』":"﹄","【":"︻","】":"︼","〔":"︹","〕":"︺","〖":"︗","〗":"︘","！":"︕","（":"︵","）":"︶","，":"︐","－":"︲","．":"・","：":"︓","；":"︔","＜":"︿","＞":"﹀","？":"︖","［":"﹇","］":"﹈","＿":"︳","｛":"︷","｜":"―","｝":"︸","｟":"︵","｠":"︶","｡":"︒","｢":"﹁","｣":"﹂"};var fc=24,pc=gc,dc=function(t,e,r,n,i){var a,o,s=8*i-n-1,l=(1<>1,u=-7,h=r?i-1:0,f=r?-1:1,p=t[e+h];for(h+=f,a=p&(1<<-u)-1,p>>=-u,u+=s;u>0;a=256*a+t[e+h],h+=f,u-=8);for(o=a&(1<<-u)-1,a>>=-u,u+=n;u>0;o=256*o+t[e+h],h+=f,u-=8);if(0===a)a=1-c;else{if(a===l)return o?NaN:1/0*(p?-1:1);o+=Math.pow(2,n),a-=c}return(p?-1:1)*o*Math.pow(2,a-n)},mc=function(t,e,r,n,i,a){var o,s,l,c=8*a-i-1,u=(1<>1,f=23===i?Math.pow(2,-24)-Math.pow(2,-77):0,p=n?0:a-1,d=n?1:-1,m=e<0||0===e&&1/e<0?1:0;for(e=Math.abs(e),isNaN(e)||e===1/0?(s=isNaN(e)?1:0,o=u):(o=Math.floor(Math.log(e)/Math.LN2),e*(l=Math.pow(2,-o))<1&&(o--,l*=2),(e+=o+h>=1?f/l:f*Math.pow(2,1-h))*l>=2&&(o++,l/=2),o+h>=u?(s=0,o=u):o+h>=1?(s=(e*l-1)*Math.pow(2,i),o+=h):(s=e*Math.pow(2,h-1)*Math.pow(2,i),o=0));i>=8;t[r+p]=255&s,p+=d,s/=256,i-=8);for(o=o<0;t[r+p]=255&o,p+=d,o/=256,c-=8);t[r+p-d]|=128*m};function gc(t){this.buf=ArrayBuffer.isView&&ArrayBuffer.isView(t)?t:new Uint8Array(t||0),this.pos=0,this.type=0,this.length=this.buf.length}gc.Varint=0,gc.Fixed64=1,gc.Bytes=2,gc.Fixed32=5;var yc=4294967296,vc=1/yc,xc=typeof TextDecoder>"u"?null:new TextDecoder("utf-8");function _c(t){return t.type===gc.Bytes?t.readVarint()+t.pos:t.pos+1}function bc(t,e,r){var n=e<=16383?1:e<=2097151?2:e<=268435455?3:Math.floor(Math.log(e)/(7*Math.LN2));r.realloc(n);for(var i=r.pos-1;i>=t;i--)r.buf[i+n]=r.buf[i]}function wc(t,e){for(var r=0;r>>8,t[r+2]=e>>>16,t[r+3]=e>>>24}function zc(t,e){return(t[e]|t[e+1]<<8|t[e+2]<<16)+(t[e+3]<<24)}gc.prototype={destroy:function(){this.buf=null},readFields:function(t,e,r){for(r=r||this.length;this.pos>3,a=this.pos;this.type=7&n,t(i,e,this),this.pos===a&&this.skip(n)}return e},readMessage:function(t,e){return this.readFields(t,e,this.readVarint()+this.pos)},readFixed32:function(){var t=Lc(this.buf,this.pos);return this.pos+=4,t},readSFixed32:function(){var t=zc(this.buf,this.pos);return this.pos+=4,t},readFixed64:function(){var t=Lc(this.buf,this.pos)+Lc(this.buf,this.pos+4)*yc;return this.pos+=8,t},readSFixed64:function(){var t=Lc(this.buf,this.pos)+zc(this.buf,this.pos+4)*yc;return this.pos+=8,t},readFloat:function(){var t=dc(this.buf,this.pos,!0,23,4);return this.pos+=4,t},readDouble:function(){var t=dc(this.buf,this.pos,!0,52,8);return this.pos+=8,t},readVarint:function(t){var e,r,n=this.buf;return e=127&(r=n[this.pos++]),r<128?e:(e|=(127&(r=n[this.pos++]))<<7,r<128?e:(e|=(127&(r=n[this.pos++]))<<14,r<128?e:(e|=(127&(r=n[this.pos++]))<<21,r<128?e:function(t,e,r){var n,i,a=r.buf;if(n=(112&(i=a[r.pos++]))>>4,i<128||(n|=(127&(i=a[r.pos++]))<<3,i<128)||(n|=(127&(i=a[r.pos++]))<<10,i<128)||(n|=(127&(i=a[r.pos++]))<<17,i<128)||(n|=(127&(i=a[r.pos++]))<<24,i<128)||(n|=(1&(i=a[r.pos++]))<<31,i<128))return function(t,e,r){return r?4294967296*e+(t>>>0):4294967296*(e>>>0)+(t>>>0)}(t,n,e);throw new Error("Expected varint not more than 10 bytes")}(e|=(15&(r=n[this.pos]))<<28,t,this))))},readVarint64:function(){return this.readVarint(!0)},readSVarint:function(){var t=this.readVarint();return t%2==1?(t+1)/-2:t/2},readBoolean:function(){return!!this.readVarint()},readString:function(){var t,e,r,n=this.readVarint()+this.pos,i=this.pos;return this.pos=n,n-i>=12&&xc?(t=this.buf,e=i,r=n,xc.decode(t.subarray(e,r))):function(t,e,r){for(var n="",i=e;i239?4:l>223?3:l>191?2:1;if(i+u>r)break;1===u?l<128&&(c=l):2===u?128==(192&(a=t[i+1]))&&(c=(31&l)<<6|63&a)<=127&&(c=null):3===u?(o=t[i+2],128==(192&(a=t[i+1]))&&128==(192&o)&&((c=(15&l)<<12|(63&a)<<6|63&o)<=2047||c>=55296&&c<=57343)&&(c=null)):4===u&&(o=t[i+2],s=t[i+3],128==(192&(a=t[i+1]))&&128==(192&o)&&128==(192&s)&&((c=(15&l)<<18|(63&a)<<12|(63&o)<<6|63&s)<=65535||c>=1114112)&&(c=null)),null===c?(c=65533,u=1):c>65535&&(c-=65536,n+=String.fromCharCode(c>>>10&1023|55296),c=56320|1023&c),n+=String.fromCharCode(c),i+=u}return n}(this.buf,i,n)},readBytes:function(){var t=this.readVarint()+this.pos,e=this.buf.subarray(this.pos,t);return this.pos=t,e},readPackedVarint:function(t,e){if(this.type!==gc.Bytes)return t.push(this.readVarint(e));var r=_c(this);for(t=t||[];this.pos127;);else if(e===gc.Bytes)this.pos=this.readVarint()+this.pos;else if(e===gc.Fixed32)this.pos+=4;else{if(e!==gc.Fixed64)throw new Error("Unimplemented type: "+e);this.pos+=8}},writeTag:function(t,e){this.writeVarint(t<<3|e)},realloc:function(t){for(var e=this.length||16;e268435455||t<0?function(t,e){var r,n,i,a;if(t>=0?(r=t%4294967296|0,n=t/4294967296|0):(n=~(-t/4294967296),4294967295^(r=~(-t%4294967296))?r=r+1|0:(r=0,n=n+1|0)),t>=0x10000000000000000||t<-0x10000000000000000)throw new Error("Given varint doesn't fit into 10 bytes");e.realloc(10),i=r,(a=e).buf[a.pos++]=127&i|128,i>>>=7,a.buf[a.pos++]=127&i|128,i>>>=7,a.buf[a.pos++]=127&i|128,i>>>=7,a.buf[a.pos++]=127&i|128,a.buf[a.pos]=127&(i>>>=7),function(t,e){var r=(7&t)<<4;e.buf[e.pos++]|=r|((t>>>=3)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t|((t>>>=7)?128:0),t&&(e.buf[e.pos++]=127&t)))))}(n,e)}(t,this):(this.realloc(4),this.buf[this.pos++]=127&t|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=127&(t>>>=7)|(t>127?128:0),t<=127||(this.buf[this.pos++]=t>>>7&127))))},writeSVarint:function(t){this.writeVarint(t<0?2*-t-1:2*t)},writeBoolean:function(t){this.writeVarint(!!t)},writeString:function(t){t=String(t),this.realloc(4*t.length),this.pos++;var e=this.pos;this.pos=function(t,e,r){for(var n,i,a=0;a55295&&n<57344){if(!i){n>56319||a+1===e.length?(t[r++]=239,t[r++]=191,t[r++]=189):i=n;continue}if(n<56320){t[r++]=239,t[r++]=191,t[r++]=189,i=n;continue}n=i-55296<<10|n-56320|65536,i=null}else i&&(t[r++]=239,t[r++]=191,t[r++]=189,i=null);n<128?t[r++]=n:(n<2048?t[r++]=n>>6|192:(n<65536?t[r++]=n>>12|224:(t[r++]=n>>18|240,t[r++]=n>>12&63|128),t[r++]=n>>6&63|128),t[r++]=63&n|128)}return r}(this.buf,t,this.pos);var r=this.pos-e;r>=128&&bc(e,r,this),this.pos=e-1,this.writeVarint(r),this.pos+=r},writeFloat:function(t){this.realloc(4),mc(this.buf,t,this.pos,!0,23,4),this.pos+=4},writeDouble:function(t){this.realloc(8),mc(this.buf,t,this.pos,!0,52,8),this.pos+=8},writeBytes:function(t){var e=t.length;this.writeVarint(e),this.realloc(e);for(var r=0;r=128&&bc(r,n,this),this.pos=r-1,this.writeVarint(n),this.pos+=n},writeMessage:function(t,e,r){this.writeTag(t,gc.Bytes),this.writeRawMessage(e,r)},writePackedVarint:function(t,e){e.length&&this.writeMessage(t,wc,e)},writePackedSVarint:function(t,e){e.length&&this.writeMessage(t,Tc,e)},writePackedBoolean:function(t,e){e.length&&this.writeMessage(t,Mc,e)},writePackedFloat:function(t,e){e.length&&this.writeMessage(t,kc,e)},writePackedDouble:function(t,e){e.length&&this.writeMessage(t,Ac,e)},writePackedFixed32:function(t,e){e.length&&this.writeMessage(t,Sc,e)},writePackedSFixed32:function(t,e){e.length&&this.writeMessage(t,Ec,e)},writePackedFixed64:function(t,e){e.length&&this.writeMessage(t,Cc,e)},writePackedSFixed64:function(t,e){e.length&&this.writeMessage(t,Ic,e)},writeBytesField:function(t,e){this.writeTag(t,gc.Bytes),this.writeBytes(e)},writeFixed32Field:function(t,e){this.writeTag(t,gc.Fixed32),this.writeFixed32(e)},writeSFixed32Field:function(t,e){this.writeTag(t,gc.Fixed32),this.writeSFixed32(e)},writeFixed64Field:function(t,e){this.writeTag(t,gc.Fixed64),this.writeFixed64(e)},writeSFixed64Field:function(t,e){this.writeTag(t,gc.Fixed64),this.writeSFixed64(e)},writeVarintField:function(t,e){this.writeTag(t,gc.Varint),this.writeVarint(e)},writeSVarintField:function(t,e){this.writeTag(t,gc.Varint),this.writeSVarint(e)},writeStringField:function(t,e){this.writeTag(t,gc.Bytes),this.writeString(e)},writeFloatField:function(t,e){this.writeTag(t,gc.Fixed32),this.writeFloat(e)},writeDoubleField:function(t,e){this.writeTag(t,gc.Fixed64),this.writeDouble(e)},writeBooleanField:function(t,e){this.writeVarintField(t,!!e)}};var Dc,Oc=r(pc);function Rc(t,e,r){1===t&&r.readMessage(Fc,e)}function Fc(t,e,r){if(3===t){let{id:t,bitmap:n,width:i,height:a,left:o,top:s,advance:l}=r.readMessage(Bc,{});e.push({id:t,bitmap:new Is({width:i+6,height:a+6},n),metrics:{width:i,height:a,left:o,top:s,advance:l}})}}function Bc(t,e,r){1===t?e.id=r.readVarint():2===t?e.bitmap=r.readBytes():3===t?e.width=r.readVarint():4===t?e.height=r.readVarint():5===t?e.left=r.readSVarint():6===t?e.top=r.readSVarint():7===t&&(e.advance=r.readVarint())}function jc(t){let e=0,r=0;for(let n of t)e+=n.w*n.h,r=Math.max(r,n.w);t.sort(((t,e)=>e.h-t.h));let n=[{x:0,y:0,w:Math.max(Math.ceil(Math.sqrt(e/.95)),r),h:1/0}],i=0,a=0;for(let e of t)for(let t=n.length-1;t>=0;t--){let r=n[t];if(!(e.w>r.w||e.h>r.h)){if(e.x=r.x,e.y=r.y,a=Math.max(a,e.y+e.h),i=Math.max(i,e.x+e.w),e.w===r.w&&e.h===r.h){let e=n.pop();t=0&&r>=t&&Wc[this.text.charCodeAt(r)];r--)e--;this.text=this.text.substring(t,e),this.sectionIndex=this.sectionIndex.slice(t,e)}substring(t,e){let r=new Hc;return r.text=this.text.substring(t,e),r.sectionIndex=this.sectionIndex.slice(t,e),r.sections=this.sections,r}toString(){return this.text}getMaxScale(){return this.sectionIndex.reduce(((t,e)=>Math.max(t,this.sections[e].scale)),0)}addTextSection(t,e){this.text+=t.text,this.sections.push(qc.forText(t.scale,t.fontStack||e));let r=this.sections.length-1;for(let e=0;e=63743?null:++this.imageSectionID:(this.imageSectionID=57344,this.imageSectionID)}}function Gc(e,r,n,i,a,o,s,l,c,u,h,f,p,d,m){let g,y=Hc.fromFeature(e,a);f===t.ah.vertical&&y.verticalizePunctuation();let{processBidirectionalText:v,processStyledBidirectionalText:x}=Ji;if(v&&1===y.sections.length){g=[];let t=v(y.toString(),tu(y,u,o,r,i,d));for(let e of t){let t=new Hc;t.text=e,t.sections=y.sections;for(let r=0;r0&&n>w&&(w=n)}else{let t=n[m.fontStack],e=t&&t[y];if(e&&e.rect)T=e.rect,_=e.metrics;else{let t=r[m.fontStack],e=t&&t[y];if(!e)continue;_=e.metrics}v=(a-m.scale)*fc}M?(e.verticalizable=!0,b.push({glyph:y,imageName:k,x:p,y:d+v,vertical:M,scale:m.scale,fontStack:m.fontStack,sectionIndex:g,metrics:_,rect:T}),p+=A*m.scale+u):(b.push({glyph:y,imageName:k,x:p,y:d+v,vertical:M,scale:m.scale,fontStack:m.fontStack,sectionIndex:g,metrics:_,rect:T}),p+=_.advance*m.scale+u)}0!==b.length&&(m=Math.max(p-u,m),ru(b,0,b.length-1,y,w)),p=0;let T=o*a+w;_.lineOffset=Math.max(w,l),d+=T,g=Math.max(T,g),++v}var x;let _=d-Vc,{horizontalAlign:b,verticalAlign:w}=eu(s);(function(t,e,r,n,i,a,o,s,l){let c=(e-r)*i,u=0;u=a!==o?-s*n-Vc:(-n*l+.5)*o;for(let e of t)for(let t of e.positionedGlyphs)t.x+=c,t.y+=u})(e.positionedLines,y,b,w,m,g,o,_,a.length),e.top+=-w*_,e.bottom=e.top+_,e.left+=-b*m,e.right=e.left+m}(b,r,n,i,g,s,l,c,f,u,p,m),!function(t){for(let e of t)if(0!==e.positionedGlyphs.length)return!1;return!0}(_)&&b}let Wc={9:!0,10:!0,11:!0,12:!0,13:!0,32:!0},Zc={10:!0,32:!0,38:!0,41:!0,43:!0,45:!0,47:!0,173:!0,183:!0,8203:!0,8208:!0,8211:!0,8231:!0},Yc={40:!0};function Xc(t,e,r,n,i,a){if(e.imageName){let t=n[e.imageName];return t?t.displaySize[0]*e.scale*fc/a+i:0}{let n=r[e.fontStack],a=n&&n[t];return a?a.metrics.advance*e.scale+i:0}}function $c(t,e,r,n){let i=Math.pow(t-e,2);return n?t=0,c=0;for(let r=0;rc){let t=Math.ceil(a/c);i*=t/o,o=t}return{x1:n,y1:i,x2:n+a,y2:i+o}}function au(t,e,r,n,i,a){let o,s=t.image;if(s.content){let t=s.content,e=s.pixelRatio||1;o=[t[0]/e,t[1]/e,s.displaySize[0]-t[2]/e,s.displaySize[1]-t[3]/e]}let l,c,u,h,f=e.left*a,p=e.right*a;"width"===r||"both"===r?(h=i[0]+f-n[3],c=i[0]+p+n[1]):(h=i[0]+(f+p-s.displaySize[0])/2,c=h+s.displaySize[0]);let d=e.top*a,m=e.bottom*a;return"height"===r||"both"===r?(l=i[1]+d-n[0],u=i[1]+m+n[2]):(l=i[1]+(d+m-s.displaySize[1])/2,u=l+s.displaySize[1]),{image:s,top:l,right:c,bottom:u,left:h,collisionPadding:o}}let ou=128,su=32640;function lu(t,e){let{expression:r}=e;if("constant"===r.kind)return{kind:"constant",layoutSize:r.evaluate(new Qi(t+1))};if("source"===r.kind)return{kind:"source"};{let{zoomStops:e,interpolationType:n}=r,i=0;for(;it.id)),this.index=e.index,this.pixelRatio=e.pixelRatio,this.sourceLayerIndex=e.sourceLayerIndex,this.hasPattern=!1,this.hasRTLText=!1,this.sortKeyRanges=[],this.collisionCircleArray=[],this.placementInvProjMatrix=ys([]),this.placementViewportMatrix=ys([]);let r=this.layers[0]._unevaluatedLayout._values;this.textSizeData=lu(this.zoom,r["text-size"]),this.iconSizeData=lu(this.zoom,r["icon-size"]);let n=this.layers[0].layout,i=n.get("symbol-sort-key"),a=n.get("symbol-z-order");this.canOverlap="never"!==cu(n,"text-overlap","text-allow-overlap")||"never"!==cu(n,"icon-overlap","icon-allow-overlap")||n.get("text-ignore-placement")||n.get("icon-ignore-placement"),this.sortFeaturesByKey="viewport-y"!==a&&!i.isConstant(),this.sortFeaturesByY=("viewport-y"===a||"auto"===a&&!this.sortFeaturesByKey)&&this.canOverlap,"point"===n.get("symbol-placement")&&(this.writingModes=n.get("text-writing-mode").map((e=>t.ah[e]))),this.stateDependentLayerIds=this.layers.filter((t=>t.isStateDependent())).map((t=>t.id)),this.sourceID=e.sourceID}createArrays(){this.text=new yu(new Vo(this.layers,this.zoom,(t=>/^text/.test(t)))),this.icon=new yu(new Vo(this.layers,this.zoom,(t=>/^icon/.test(t)))),this.glyphOffsetArray=new $a,this.lineVertexArray=new Ka,this.symbolInstances=new Xa,this.textAnchorOffsets=new Qa}calculateGlyphDependencies(t,e,r,n,i){for(let a=0;a0)&&("constant"!==o.value.kind||o.value.value.length>0),u="constant"!==l.value.kind||!!l.value.value||Object.keys(l.parameters).length>0,h=a.get("symbol-sort-key");if(this.features=[],!c&&!u)return;let f=r.iconDependencies,p=r.glyphDependencies,d=r.availableImages,m=new Qi(this.zoom);for(let{feature:r,id:s,index:l,sourceLayerIndex:g}of e){let e,y,v=i._featureFilter.needGeometry,x=Ko(r,v);if(!i._featureFilter.filter(m,x,n))continue;if(v||(x.geometry=$o(r)),c){let t=i.getValueAndResolveTokens("text-field",x,n,d),r=Jt.factory(t),a=this.hasRTLText=this.hasRTLText||gu(r);(!a||"unavailable"===Ji.getRTLTextPluginStatus()||a&&Ji.isParsed())&&(e=uc(r,i,x))}if(u){let t=i.getValueAndResolveTokens("icon-image",x,n,d);y=t instanceof re?t:re.fromString(t)}if(!e&&!y)continue;let _=this.sortFeaturesByKey?h.evaluate(x,{},n):void 0;if(this.features.push({id:s,text:e,icon:y,index:l,sourceLayerIndex:g,geometry:x.geometry,properties:r.properties,type:fu[r.type],sortKey:_}),y&&(f[y.name]=!0),e){let r=o.evaluate(x,{},n).join(","),i="viewport"!==a.get("text-rotation-alignment")&&"point"!==a.get("symbol-placement");this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(t.ah.vertical)>=0;for(let t of e.sections)if(t.image)f[t.image.name]=!0;else{let n=Ni(e.toString()),a=t.fontStack||r,o=p[a]=p[a]||{};this.calculateGlyphDependencies(t.text,o,i,this.allowVerticalPlacement,n)}}}"line"===a.get("symbol-placement")&&(this.features=function(t){let e={},r={},n=[],i=0;function a(e){n.push(t[e]),i++}function o(t,e,i){let a=r[t];return delete r[t],r[e]=a,n[a].geometry[0].pop(),n[a].geometry[0]=n[a].geometry[0].concat(i[0]),a}function s(t,r,i){let a=e[r];return delete e[r],e[t]=a,n[a].geometry[0].shift(),n[a].geometry[0]=i[0].concat(n[a].geometry[0]),a}function l(t,e,r){let n=r?e[0][e[0].length-1]:e[0][0];return`${t}:${n.x}:${n.y}`}for(let c=0;ct.geometry))}(this.features)),this.sortFeaturesByKey&&this.features.sort(((t,e)=>t.sortKey-e.sortKey))}update(t,e,r){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(t,e,this.layers,r),this.icon.programConfigurations.updatePaintArrays(t,e,this.layers,r))}isEmpty(){return 0===this.symbolInstances.length&&!this.hasRTLText}uploadPending(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload}upload(t){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(t),this.iconCollisionBox.upload(t)),this.text.upload(t,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(t,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0}destroyDebugData(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()}destroy(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()}addToLineVertexArray(t,e){let r=this.lineVertexArray.length;if(void 0!==t.segment){let r=t.dist(e[t.segment+1]),n=t.dist(e[t.segment]),i={};for(let n=t.segment+1;n=0;r--)i[r]={x:e[r].x,y:e[r].y,tileUnitDistanceFromAnchor:n},r>0&&(n+=e[r-1].dist(e[r]));for(let t=0;t0}hasIconData(){return this.icon.segments.get().length>0}hasDebugData(){return this.textCollisionBox&&this.iconCollisionBox}hasTextCollisionBoxData(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0}hasIconCollisionBoxData(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0}addIndicesForPlacedSymbol(t,e){let r=t.placedSymbolArray.get(e),n=r.vertexStartIndex+4*r.numGlyphs;for(let e=r.vertexStartIndex;en[t]-n[e]||i[e]-i[t])),a}addToSortKeyRanges(t,e){let r=this.sortKeyRanges[this.sortKeyRanges.length-1];r&&r.sortKey===e?r.symbolInstanceEnd=t+1:this.sortKeyRanges.push({sortKey:e,symbolInstanceStart:t,symbolInstanceEnd:t+1})}sortFeatures(t){if(this.sortFeaturesByY&&this.sortedAngle!==t&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(t),this.sortedAngle=t,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(let t of this.symbolInstanceIndexes){let e=this.symbolInstances.get(t);this.featureSortOrder.push(e.featureIndex),[e.rightJustifiedTextSymbolIndex,e.centerJustifiedTextSymbolIndex,e.leftJustifiedTextSymbolIndex].forEach(((t,e,r)=>{t>=0&&r.indexOf(t)===e&&this.addIndicesForPlacedSymbol(this.text,t)})),e.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,e.verticalPlacedTextSymbolIndex),e.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,e.placedIconSymbolIndex),e.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,e.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}}}Ti("SymbolBucket",xu,{omit:["layers","collisionBoxArray","features","compareText"]}),xu.MAX_GLYPHS=65535,xu.addDynamicAttributes=mu;var _u={get paint(){return hu=hu||new pa({"icon-opacity":new ca(Y.paint_symbol["icon-opacity"]),"icon-color":new ca(Y.paint_symbol["icon-color"]),"icon-halo-color":new ca(Y.paint_symbol["icon-halo-color"]),"icon-halo-width":new ca(Y.paint_symbol["icon-halo-width"]),"icon-halo-blur":new ca(Y.paint_symbol["icon-halo-blur"]),"icon-translate":new la(Y.paint_symbol["icon-translate"]),"icon-translate-anchor":new la(Y.paint_symbol["icon-translate-anchor"]),"text-opacity":new ca(Y.paint_symbol["text-opacity"]),"text-color":new ca(Y.paint_symbol["text-color"],{runtimeType:dt,getOverride:t=>t.textColor,hasOverride:t=>!!t.textColor}),"text-halo-color":new ca(Y.paint_symbol["text-halo-color"]),"text-halo-width":new ca(Y.paint_symbol["text-halo-width"]),"text-halo-blur":new ca(Y.paint_symbol["text-halo-blur"]),"text-translate":new la(Y.paint_symbol["text-translate"]),"text-translate-anchor":new la(Y.paint_symbol["text-translate-anchor"])})},get layout(){return uu=uu||new pa({"symbol-placement":new la(Y.layout_symbol["symbol-placement"]),"symbol-spacing":new la(Y.layout_symbol["symbol-spacing"]),"symbol-avoid-edges":new la(Y.layout_symbol["symbol-avoid-edges"]),"symbol-sort-key":new ca(Y.layout_symbol["symbol-sort-key"]),"symbol-z-order":new la(Y.layout_symbol["symbol-z-order"]),"icon-allow-overlap":new la(Y.layout_symbol["icon-allow-overlap"]),"icon-overlap":new la(Y.layout_symbol["icon-overlap"]),"icon-ignore-placement":new la(Y.layout_symbol["icon-ignore-placement"]),"icon-optional":new la(Y.layout_symbol["icon-optional"]),"icon-rotation-alignment":new la(Y.layout_symbol["icon-rotation-alignment"]),"icon-size":new ca(Y.layout_symbol["icon-size"]),"icon-text-fit":new la(Y.layout_symbol["icon-text-fit"]),"icon-text-fit-padding":new la(Y.layout_symbol["icon-text-fit-padding"]),"icon-image":new ca(Y.layout_symbol["icon-image"]),"icon-rotate":new ca(Y.layout_symbol["icon-rotate"]),"icon-padding":new ca(Y.layout_symbol["icon-padding"]),"icon-keep-upright":new la(Y.layout_symbol["icon-keep-upright"]),"icon-offset":new ca(Y.layout_symbol["icon-offset"]),"icon-anchor":new ca(Y.layout_symbol["icon-anchor"]),"icon-pitch-alignment":new la(Y.layout_symbol["icon-pitch-alignment"]),"text-pitch-alignment":new la(Y.layout_symbol["text-pitch-alignment"]),"text-rotation-alignment":new la(Y.layout_symbol["text-rotation-alignment"]),"text-field":new ca(Y.layout_symbol["text-field"]),"text-font":new ca(Y.layout_symbol["text-font"]),"text-size":new ca(Y.layout_symbol["text-size"]),"text-max-width":new ca(Y.layout_symbol["text-max-width"]),"text-line-height":new la(Y.layout_symbol["text-line-height"]),"text-letter-spacing":new ca(Y.layout_symbol["text-letter-spacing"]),"text-justify":new ca(Y.layout_symbol["text-justify"]),"text-radial-offset":new ca(Y.layout_symbol["text-radial-offset"]),"text-variable-anchor":new la(Y.layout_symbol["text-variable-anchor"]),"text-variable-anchor-offset":new ca(Y.layout_symbol["text-variable-anchor-offset"]),"text-anchor":new ca(Y.layout_symbol["text-anchor"]),"text-max-angle":new la(Y.layout_symbol["text-max-angle"]),"text-writing-mode":new la(Y.layout_symbol["text-writing-mode"]),"text-rotate":new ca(Y.layout_symbol["text-rotate"]),"text-padding":new la(Y.layout_symbol["text-padding"]),"text-keep-upright":new la(Y.layout_symbol["text-keep-upright"]),"text-transform":new ca(Y.layout_symbol["text-transform"]),"text-offset":new ca(Y.layout_symbol["text-offset"]),"text-allow-overlap":new la(Y.layout_symbol["text-allow-overlap"]),"text-overlap":new la(Y.layout_symbol["text-overlap"]),"text-ignore-placement":new la(Y.layout_symbol["text-ignore-placement"]),"text-optional":new la(Y.layout_symbol["text-optional"])})}};class bu{constructor(t){if(void 0===t.property.overrides)throw new Error("overrides must be provided to instantiate FormatSectionOverride class");this.type=t.property.overrides?t.property.overrides.runtimeType:ut,this.defaultValue=t}evaluate(t){if(t.formattedSection){let e=this.defaultValue.property.overrides;if(e&&e.hasOverride(t.formattedSection))return e.getOverride(t.formattedSection)}return t.feature&&t.featureState?this.defaultValue.evaluate(t.feature,t.featureState):this.defaultValue.property.specification.default}eachChild(t){this.defaultValue.isConstant()||t(this.defaultValue.value._styleExpression.expression)}outputDefined(){return!1}serialize(){return null}}Ti("FormatSectionOverride",bu,{omit:["defaultValue"]});class wu extends ma{constructor(t){super(t,_u)}recalculate(t,e){if(super.recalculate(t,e),"auto"===this.layout.get("icon-rotation-alignment")&&(this.layout._values["icon-rotation-alignment"]="point"!==this.layout.get("symbol-placement")?"map":"viewport"),"auto"===this.layout.get("text-rotation-alignment")&&(this.layout._values["text-rotation-alignment"]="point"!==this.layout.get("symbol-placement")?"map":"viewport"),"auto"===this.layout.get("text-pitch-alignment")&&(this.layout._values["text-pitch-alignment"]="map"===this.layout.get("text-rotation-alignment")?"map":"viewport"),"auto"===this.layout.get("icon-pitch-alignment")&&(this.layout._values["icon-pitch-alignment"]=this.layout.get("icon-rotation-alignment")),"point"===this.layout.get("symbol-placement")){let t=this.layout.get("text-writing-mode");if(t){let e=[];for(let r of t)e.indexOf(r)<0&&e.push(r);this.layout._values["text-writing-mode"]=e}else this.layout._values["text-writing-mode"]=["horizontal"]}this._setPaintOverrides()}getValueAndResolveTokens(t,e,r,n){let i=this.layout.get(t).evaluate(e,{},r,n),a=this._unevaluatedLayout._values[t];return a.isDataDriven()||bn(a.value)||!i?i:(o=e.properties,i.replace(/{([^{}]+)}/g,((t,e)=>o&&e in o?String(o[e]):"")));var o}createBucket(t){return new xu(t)}queryRadius(){return 0}queryIntersectsFeature(){throw new Error("Should take a different path in FeatureIndex")}_setPaintOverrides(){for(let t of _u.paint.overridableProperties){if(!wu.hasPaintOverride(this.layout,t))continue;let e=this.paint.get(t),r=new bu(e),n=new _n(r,e.property.specification),i=null;i="constant"===e.value.kind||"source"===e.value.kind?new Tn("source",n):new kn("composite",n,e.value.zoomStops),this.paint._values[t]=new oa(e.property,i,e.parameters)}}_handleOverridablePaintPropertyUpdate(t,e,r){return!(!this.layout||e.isDataDriven()||r.isDataDriven())&&wu.hasPaintOverride(this.layout,t)}static hasPaintOverride(t,e){let r=t.get("text-field"),n=_u.paint.properties[e],i=!1,a=t=>{for(let e of t)if(n.overrides&&n.overrides.hasOverride(e))return void(i=!0)};if("constant"===r.value.kind&&r.value.value instanceof Jt)a(r.value.value.sections);else if("source"===r.value.kind){let t=e=>{i||(e instanceof se&&ae(e.value)===vt?a(e.value.sections):e instanceof Ze?a(e.sections):e.eachChild(t))},e=r.value;e._styleExpression&&t(e._styleExpression.expression)}return i}}let Tu;var ku={get paint(){return Tu=Tu||new pa({"background-color":new la(Y.paint_background["background-color"]),"background-pattern":new ha(Y.paint_background["background-pattern"]),"background-opacity":new la(Y.paint_background["background-opacity"])})}};class Au extends ma{constructor(t){super(t,ku)}}let Mu;var Su={get paint(){return Mu=Mu||new pa({"raster-opacity":new la(Y.paint_raster["raster-opacity"]),"raster-hue-rotate":new la(Y.paint_raster["raster-hue-rotate"]),"raster-brightness-min":new la(Y.paint_raster["raster-brightness-min"]),"raster-brightness-max":new la(Y.paint_raster["raster-brightness-max"]),"raster-saturation":new la(Y.paint_raster["raster-saturation"]),"raster-contrast":new la(Y.paint_raster["raster-contrast"]),"raster-resampling":new la(Y.paint_raster["raster-resampling"]),"raster-fade-duration":new la(Y.paint_raster["raster-fade-duration"])})}};class Eu extends ma{constructor(t){super(t,Su)}}class Cu extends ma{constructor(t){super(t,{}),this.onAdd=t=>{this.implementation.onAdd&&this.implementation.onAdd(t,t.painter.context.gl)},this.onRemove=t=>{this.implementation.onRemove&&this.implementation.onRemove(t,t.painter.context.gl)},this.implementation=t}is3D(){return"3d"===this.implementation.renderingMode}hasOffscreenPass(){return void 0!==this.implementation.prerender}recalculate(){}updateTransitions(){}hasTransition(){return!1}serialize(){throw new Error("Custom layers cannot be serialized")}}class Iu{constructor(t){this._methodToThrottle=t,this._triggered=!1,typeof MessageChannel<"u"&&(this._channel=new MessageChannel,this._channel.port2.onmessage=()=>{this._triggered=!1,this._methodToThrottle()})}trigger(){this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout((()=>{this._triggered=!1,this._methodToThrottle()}),0))}remove(){delete this._channel,this._methodToThrottle=()=>{}}}let Lu=6371008.8;class Pu{constructor(t,e){if(isNaN(t)||isNaN(e))throw new Error(`Invalid LngLat object: (${t}, ${e})`);if(this.lng=+t,this.lat=+e,this.lat>90||this.lat<-90)throw new Error("Invalid LngLat latitude value: must be between -90 and 90")}wrap(){return new Pu(v(this.lng,-180,180),this.lat)}toArray(){return[this.lng,this.lat]}toString(){return`LngLat(${this.lng}, ${this.lat})`}distanceTo(t){let e=Math.PI/180,r=this.lat*e,n=t.lat*e,i=Math.sin(r)*Math.sin(n)+Math.cos(r)*Math.cos(n)*Math.cos((t.lng-this.lng)*e);return Lu*Math.acos(Math.min(i,1))}static convert(t){if(t instanceof Pu)return t;if(Array.isArray(t)&&(2===t.length||3===t.length))return new Pu(Number(t[0]),Number(t[1]));if(!Array.isArray(t)&&"object"==typeof t&&null!==t)return new Pu(Number("lng"in t?t.lng:t.lon),Number(t.lat));throw new Error("`LngLatLike` argument must be specified as a LngLat instance, an object {lng: , lat: }, an object {lon: , lat: }, or an array of [, ]")}}let zu=2*Math.PI*Lu;function Du(t){return zu*Math.cos(t*Math.PI/180)}function Ou(t){return(180+t)/360}function Ru(t){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+t*Math.PI/360)))/360}function Fu(t,e){return t/Du(e)}function Bu(t){return 360/Math.PI*Math.atan(Math.exp((180-360*t)*Math.PI/180))-90}class ju{constructor(t,e,r=0){this.x=+t,this.y=+e,this.z=+r}static fromLngLat(t,e=0){let r=Pu.convert(t);return new ju(Ou(r.lng),Ru(r.lat),Fu(e,r.lat))}toLngLat(){return new Pu(360*this.x-180,Bu(this.y))}toAltitude(){return this.z*Du(Bu(this.y))}meterInMercatorCoordinateUnits(){return 1/zu*(t=Bu(this.y),1/Math.cos(t*Math.PI/180));var t}}function Nu(t,e,r){var n=2*Math.PI*6378137/256/Math.pow(2,r);return[t*n-2*Math.PI*6378137/2,e*n-2*Math.PI*6378137/2]}class Uu{constructor(t,e,r){if(i=e,a=r,(n=t)<0||n>25||a<0||a>=Math.pow(2,n)||i<0||i>=Math.pow(2,n))throw new Error(`x=${e}, y=${r}, z=${t} outside of bounds. 0<=x<${Math.pow(2,t)}, 0<=y<${Math.pow(2,t)} 0<=z<=25 `);var n,i,a;this.z=t,this.x=e,this.y=r,this.key=Hu(0,t,t,e,r)}equals(t){return this.z===t.z&&this.x===t.x&&this.y===t.y}url(t,e,r){let n=(a=this.y,o=this.z,s=Nu(256*(i=this.x),256*(a=Math.pow(2,o)-a-1),o),l=Nu(256*(i+1),256*(a+1),o),s[0]+","+s[1]+","+l[0]+","+l[1]);var i,a,o,s,l;let c=function(t,e,r){let n,i="";for(let a=t;a>0;a--)n=1<1?"@2x":"").replace(/{quadkey}/g,c).replace(/{bbox-epsg-3857}/g,n)}isChildOf(t){let e=this.z-t.z;return e>0&&t.x===this.x>>e&&t.y===this.y>>e}getTilePoint(t){let e=Math.pow(2,this.z);return new a((t.x*e-this.x)*Zo,(t.y*e-this.y)*Zo)}toString(){return`${this.z}/${this.x}/${this.y}`}}class Vu{constructor(t,e){this.wrap=t,this.canonical=e,this.key=Hu(t,e.z,e.z,e.x,e.y)}}class qu{constructor(t,e,r,n,i){if(t= z; overscaledZ = ${t}; z = ${r}`);this.overscaledZ=t,this.wrap=e,this.canonical=new Uu(r,+n,+i),this.key=Hu(e,t,r,n,i)}clone(){return new qu(this.overscaledZ,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)}equals(t){return this.overscaledZ===t.overscaledZ&&this.wrap===t.wrap&&this.canonical.equals(t.canonical)}scaledTo(t){if(t>this.overscaledZ)throw new Error(`targetZ > this.overscaledZ; targetZ = ${t}; overscaledZ = ${this.overscaledZ}`);let e=this.canonical.z-t;return t>this.canonical.z?new qu(t,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new qu(t,this.wrap,t,this.canonical.x>>e,this.canonical.y>>e)}calculateScaledKey(t,e){if(t>this.overscaledZ)throw new Error(`targetZ > this.overscaledZ; targetZ = ${t}; overscaledZ = ${this.overscaledZ}`);let r=this.canonical.z-t;return t>this.canonical.z?Hu(this.wrap*+e,t,this.canonical.z,this.canonical.x,this.canonical.y):Hu(this.wrap*+e,t,t,this.canonical.x>>r,this.canonical.y>>r)}isChildOf(t){if(t.wrap!==this.wrap)return!1;let e=this.canonical.z-t.canonical.z;return 0===t.overscaledZ||t.overscaledZ>e&&t.canonical.y===this.canonical.y>>e}children(t){if(this.overscaledZ>=t)return[new qu(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];let e=this.canonical.z+1,r=2*this.canonical.x,n=2*this.canonical.y;return[new qu(e,this.wrap,e,r,n),new qu(e,this.wrap,e,r+1,n),new qu(e,this.wrap,e,r,n+1),new qu(e,this.wrap,e,r+1,n+1)]}isLessThan(t){return this.wrapt.wrap)&&(this.overscaledZt.overscaledZ)&&(this.canonical.xt.canonical.x)&&this.canonical.ythis.max&&(this.max=r),r=this.dim+1||e<-1||e>=this.dim+1)throw new RangeError("out of range source coordinates for DEM data");return(e+1)*this.stride+(t+1)}unpack(t,e,r){return t*this.redFactor+e*this.greenFactor+r*this.blueFactor-this.baseShift}getPixels(){return new Ls({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))}backfillBorder(t,e,r){if(this.dim!==t.dim)throw new Error("dem dimension mismatch");let n=e*this.dim,i=e*this.dim+this.dim,a=r*this.dim,o=r*this.dim+this.dim;switch(e){case-1:n=i-1;break;case 1:i=n+1}switch(r){case-1:a=o-1;break;case 1:o=a+1}let s=-e*this.dim,l=-r*this.dim;for(let e=a;e=this._numberToString.length)throw new Error(`Out of bounds. Index requested n=${t} can't be >= this._numberToString.length ${this._numberToString.length}`);return this._numberToString[t]}}class Zu{constructor(t,e,r,n,i){this.type="Feature",this._vectorTileFeature=t,t._z=e,t._x=r,t._y=n,this.properties=t.properties,this.id=i}get geometry(){return void 0===this._geometry&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry}set geometry(t){this._geometry=t}toJSON(){let t={geometry:this.geometry};for(let e in this)"_geometry"!==e&&"_vectorTileFeature"!==e&&(t[e]=this[e]);return t}}class Yu{constructor(t,e){this.tileID=t,this.x=t.canonical.x,this.y=t.canonical.y,this.z=t.canonical.z,this.grid=new bi(Zo,16,0),this.grid3D=new bi(Zo,16,0),this.featureIndexArray=new eo,this.promoteId=e}insert(t,e,r,n,i,a){let o=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(r,n,i);let s=a?this.grid3D:this.grid;for(let t=0;t=0&&n[3]>=0&&s.insert(o,n[0],n[1],n[2],n[3])}}loadVTLayers(){return this.vtLayers||(this.vtLayers=new bl.VectorTile(new Oc(this.rawTileData)).layers,this.sourceLayerCoder=new Wu(this.vtLayers?Object.keys(this.vtLayers).sort():["_geojsonTileLayer"])),this.vtLayers}query(t,e,r,n){this.loadVTLayers();let i=t.params||{},o=Zo/t.tileSize/t.scale,s=In(i.filter),l=t.queryGeometry,c=t.queryPadding*o,u=$u(l),h=this.grid.query(u.minX-c,u.minY-c,u.maxX+c,u.maxY+c),f=$u(t.cameraQueryGeometry),p=this.grid3D.query(f.minX-c,f.minY-c,f.maxX+c,f.maxY+c,((e,r,n,i)=>function(t,e,r,n,i){for(let a of t)if(e<=a.x&&r<=a.y&&n>=a.x&&i>=a.y)return!0;let o=[new a(e,r),new a(e,i),new a(n,i),new a(n,r)];if(t.length>2)for(let e of o)if(cs(t,e))return!0;for(let e=0;e(f||(f=$o(e)),r.queryIntersectsFeature(l,e,n,f,this.z,t.transform,o,t.pixelPosMatrix))))}return m}loadMatchingFeature(t,e,r,n,i,a,o,s,l,c,u){let h=this.bucketLayerIDs[e];if(a&&!function(t,e){for(let r=0;r=0)return!0;return!1}(a,h))return;let f=this.sourceLayerCoder.decode(r),p=this.vtLayers[f].feature(n);if(i.needGeometry){let t=Ko(p,!0);if(!i.filter(new Qi(this.tileID.overscaledZ),t,this.tileID.canonical))return}else if(!i.filter(new Qi(this.tileID.overscaledZ),p))return;let d=this.getId(p,f);for(let e=0;e{let o=e instanceof sa?e.get(a):null;return o&&o.evaluate?o.evaluate(r,n,i):o}))}function $u(t){let e=1/0,r=1/0,n=-1/0,i=-1/0;for(let a of t)e=Math.min(e,a.x),r=Math.min(r,a.y),n=Math.max(n,a.x),i=Math.max(i,a.y);return{minX:e,minY:r,maxX:n,maxY:i}}function Ku(t,e){return e-t}function Ju(t,e,r,n,i){let o=[];for(let s=0;s=n&&u.x>=n||(s.x>=n?s=new a(n,s.y+(n-s.x)/(u.x-s.x)*(u.y-s.y))._round():u.x>=n&&(u=new a(n,s.y+(n-s.x)/(u.x-s.x)*(u.y-s.y))._round()),s.y>=i&&u.y>=i||(s.y>=i?s=new a(s.x+(i-s.y)/(u.y-s.y)*(u.x-s.x),i)._round():u.y>=i&&(u=new a(s.x+(i-s.y)/(u.y-s.y)*(u.x-s.x),i)._round()),l&&s.equals(l[l.length-1])||(l=[s],o.push(l)),l.push(u)))))}}return o}Ti("FeatureIndex",Yu,{omit:["rawTileData","sourceLayerCoder"]});class Qu extends a{constructor(t,e,r,n){super(t,e),this.angle=r,void 0!==n&&(this.segment=n)}clone(){return new Qu(this.x,this.y,this.angle,this.segment)}}function th(t,e,r,n,i){if(void 0===e.segment||0===r)return!0;let a=e,o=e.segment+1,s=0;for(;s>-r/2;){if(o--,o<0)return!1;s-=t[o].dist(a),a=t[o]}s+=t[o].dist(t[o+1]),o++;let l=[],c=0;for(;sn;)c-=l.shift().angleDelta;if(c>i)return!1;o++,s+=e.dist(r)}return!0}function eh(t){let e=0;for(let r=0;rc){let u=(c-l)/a,h=Pe.number(n.x,i.x,u),f=Pe.number(n.y,i.y,u),p=new Qu(h,f,i.angleTo(n),r);return p._round(),!o||th(t,p,s,o,e)?p:void 0}l+=a}}function ah(t,e,r,n,i,a,o,s,l){let c=rh(n,a,o),u=nh(n,i),h=u*o,f=0===t[0].x||t[0].x===l||0===t[0].y||t[0].y===l;return e-h=0&&y=0&&v=0&&f+c<=u){let r=new Qu(y,v,m,e);r._round(),n&&!th(t,r,a,n,i)||p.push(r)}}h+=d}return s||p.length||o||(p=oh(t,h/2,r,n,i,a,o,!0,l)),p}function sh(t,e,r,n){let i=[],o=t.image,s=o.pixelRatio,l=o.paddedRect.w-2,c=o.paddedRect.h-2,u={x1:t.left,y1:t.top,x2:t.right,y2:t.bottom},h=o.stretchX||[[0,l]],f=o.stretchY||[[0,c]],p=(t,e)=>t+e[1]-e[0],d=h.reduce(p,0),m=f.reduce(p,0),g=l-d,y=c-m,v=0,x=d,_=0,b=m,w=0,T=g,k=0,A=y;if(o.content&&n){let e=o.content,r=e[2]-e[0],n=e[3]-e[1];(o.textFitWidth||o.textFitHeight)&&(u=iu(t)),v=lh(h,0,e[0]),_=lh(f,0,e[1]),x=lh(h,e[0],e[2]),b=lh(f,e[1],e[3]),w=e[0]-v,k=e[1]-_,T=r-x,A=n-b}let M=u.x1,S=u.y1,E=u.x2-M,C=u.y2-S,I=(t,n,i,l)=>{let c=uh(t.stretch-v,x,E,M),u=hh(t.fixed-w,T,t.stretch,d),h=uh(n.stretch-_,b,C,S),f=hh(n.fixed-k,A,n.stretch,m),p=uh(i.stretch-v,x,E,M),g=hh(i.fixed-w,T,i.stretch,d),y=uh(l.stretch-_,b,C,S),I=hh(l.fixed-k,A,l.stretch,m),L=new a(c,h),P=new a(p,h),z=new a(p,y),D=new a(c,y),O=new a(u/s,f/s),R=new a(g/s,I/s),F=e*Math.PI/180;if(F){let t=Math.sin(F),e=Math.cos(F),r=[e,-t,t,e];L._matMult(r),P._matMult(r),D._matMult(r),z._matMult(r)}let 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t.R({width:c,height:u},yield t.bw(i,-1,-1,c,u)):i,f=new t.bx(r,h,n,a,o,s,l);return this.loaded=this.loaded||{},this.loaded[r]=f,f}))}removeTile(t){let e=this.loaded,r=t.uid;e&&e[r]&&delete e[r]}}function s(t,e){if(0!==t.length){l(t[0],e);for(var r=1;r=Math.abs(s)?r-l+s:s-l+r,r=l}r+n>=0!=!!e&&t.reverse()}var c=t.by((function t(e,r){var n,i=e&&e.type;if("FeatureCollection"===i)for(n=0;n>31}function A(t,e){for(var r=t.loadGeometry(),n=t.type,i=0,a=0,o=r.length,s=0;st},C=Math.fround||(I=new Float32Array(1),t=>(I[0]=+t,I[0]));var I;class L{constructor(t){this.options=Object.assign(Object.create(E),t),this.trees=new Array(this.options.maxZoom+1),this.stride=this.options.reduce?7:6,this.clusterProps=[]}load(t){let{log:e,minZoom:r,maxZoom:n}=this.options;e&&console.time("total time");let i=`prepare ${t.length} points`;e&&console.time(i),this.points=t;let a=[];for(let e=0;e=r;t--){let r=+Date.now();o=this.trees[t]=this._createTree(this._cluster(o,t)),e&&console.log("z%d: %d clusters in 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p=.5*l.buffer/l.extent,d=.5-p,m=.5+p,g=1+p,y=null,v=null,x=null,_=null,b=Z(t,u,r-p,r+m,0,f.minX,f.maxX,l),w=Z(t,u,r+d,r+g,0,f.minX,f.maxX,l);t=null,b&&(y=Z(b,u,n-p,n+m,1,f.minY,f.maxY,l),v=Z(b,u,n+d,n+g,1,f.minY,f.maxY,l),b=null),w&&(x=Z(w,u,n-p,n+m,1,f.minY,f.maxY,l),_=Z(w,u,n+d,n+g,1,f.minY,f.maxY,l),w=null),c>1&&console.timeEnd("clipping"),s.push(y||[],e+1,2*r,2*n),s.push(v||[],e+1,2*r,2*n+1),s.push(x||[],e+1,2*r+1,2*n),s.push(_||[],e+1,2*r+1,2*n+1)}}getTile(t,e,r){t=+t,e=+e,r=+r;let n=this.options,{extent:i,debug:a}=n;if(t<0||t>24)return null;let o=1<1&&console.log("drilling down to z%d-%d-%d",t,e,r);let l,c=t,u=e,h=r;for(;!l&&c>0;)c--,u>>=1,h>>=1,l=this.tiles[ut(c,u,h)];return l&&l.source?(a>1&&(console.log("found parent tile z%d-%d-%d",c,u,h),console.time("drilling down")),this.splitTile(l.source,c,u,h,t,e,r),a>1&&console.timeEnd("drilling down"),this.tiles[s]?nt(this.tiles[s],i):null):null}}function ut(t,e,r){return 32*((1<{o.properties=t;let e={};for(let t of 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r=t.bC(e.filter,{type:"boolean","property-type":"data-driven",overridable:!1,transition:!1});if("error"===r.result)throw new Error(r.value.map((t=>`${t.key}: ${t.message}`)).join(", "));n={type:"FeatureCollection",features:n.features.filter((t=>r.value.evaluate({zoom:0},t)))}}return n}))}loadGeoJSON(e,r){return t._(this,void 0,void 0,(function*(){let{promoteId:n}=e;if(e.request){let i=yield t.h(e.request,r);return this._dataUpdateable=ft(i.data,n)?pt(i.data,n):void 0,i.data}if("string"==typeof e.data)try{let t=JSON.parse(e.data);return this._dataUpdateable=ft(t,n)?pt(t,n):void 0,t}catch{throw new Error(`Input data given to '${e.source}' is not a valid GeoJSON object.`)}if(!e.dataDiff)throw new Error(`Input data given to '${e.source}' is not a valid GeoJSON object.`);if(!this._dataUpdateable)throw new Error(`Cannot update existing geojson data in ${e.source}`);return function(t,e,r){var n,i,a,o;if(e.removeAll&&t.clear(),e.remove)for(let r of e.remove)t.delete(r);if(e.add)for(let n of e.add){let e=ht(n,r);null!=e&&t.set(e,n)}if(e.update)for(let r of e.update){let e=t.get(r.id);if(null==e)continue;let s=!r.removeAllProperties&&((null===(n=r.removeProperties)||void 0===n?void 0:n.length)>0||(null===(i=r.addOrUpdateProperties)||void 0===i?void 0:i.length)>0);if((r.newGeometry||r.removeAllProperties||s)&&(e=Object.assign({},e),t.set(r.id,e),s&&(e.properties=Object.assign({},e.properties))),r.newGeometry&&(e.geometry=r.newGeometry),r.removeAllProperties)e.properties={};else if((null===(a=r.removeProperties)||void 0===a?void 0:a.length)>0)for(let t of r.removeProperties)Object.prototype.hasOwnProperty.call(e.properties,t)&&delete e.properties[t];if((null===(o=r.addOrUpdateProperties)||void 0===o?void 0:o.length)>0)for(let{key:t,value:n}of r.addOrUpdateProperties)e.properties[t]=n}}(this._dataUpdateable,e.dataDiff,n),{type:"FeatureCollection",features:Array.from(this._dataUpdateable.values())}}))}removeSource(e){return t._(this,void 0,void 0,(function*(){this._pendingRequest&&this._pendingRequest.abort()}))}getClusterExpansionZoom(t){return this._geoJSONIndex.getClusterExpansionZoom(t.clusterId)}getClusterChildren(t){return this._geoJSONIndex.getChildren(t.clusterId)}getClusterLeaves(t){return this._geoJSONIndex.getLeaves(t.clusterId,t.limit,t.offset)}}class mt{constructor(e){this.self=e,this.actor=new t.F(e),this.layerIndexes={},this.availableImages={},this.workerSources={},this.demWorkerSources={},this.externalWorkerSourceTypes={},this.self.registerWorkerSource=(t,e)=>{if(this.externalWorkerSourceTypes[t])throw new Error(`Worker source with name "${t}" already registered.`);this.externalWorkerSourceTypes[t]=e},this.self.addProtocol=t.bi,this.self.removeProtocol=t.bj,this.self.registerRTLTextPlugin=e=>{if(t.bD.isParsed())throw new Error("RTL text plugin already registered.");t.bD.setMethods(e)},this.actor.registerMessageHandler("LDT",((t,e)=>this._getDEMWorkerSource(t,e.source).loadTile(e))),this.actor.registerMessageHandler("RDT",((e,r)=>t._(this,void 0,void 0,(function*(){this._getDEMWorkerSource(e,r.source).removeTile(r)})))),this.actor.registerMessageHandler("GCEZ",((e,r)=>t._(this,void 0,void 0,(function*(){return this._getWorkerSource(e,r.type,r.source).getClusterExpansionZoom(r)})))),this.actor.registerMessageHandler("GCC",((e,r)=>t._(this,void 0,void 0,(function*(){return this._getWorkerSource(e,r.type,r.source).getClusterChildren(r)})))),this.actor.registerMessageHandler("GCL",((e,r)=>t._(this,void 0,void 0,(function*(){return this._getWorkerSource(e,r.type,r.source).getClusterLeaves(r)})))),this.actor.registerMessageHandler("LD",((t,e)=>this._getWorkerSource(t,e.type,e.source).loadData(e))),this.actor.registerMessageHandler("GD",((t,e)=>this._getWorkerSource(t,e.type,e.source).getData())),this.actor.registerMessageHandler("LT",((t,e)=>this._getWorkerSource(t,e.type,e.source).loadTile(e))),this.actor.registerMessageHandler("RT",((t,e)=>this._getWorkerSource(t,e.type,e.source).reloadTile(e))),this.actor.registerMessageHandler("AT",((t,e)=>this._getWorkerSource(t,e.type,e.source).abortTile(e))),this.actor.registerMessageHandler("RMT",((t,e)=>this._getWorkerSource(t,e.type,e.source).removeTile(e))),this.actor.registerMessageHandler("RS",((e,r)=>t._(this,void 0,void 0,(function*(){if(!this.workerSources[e]||!this.workerSources[e][r.type]||!this.workerSources[e][r.type][r.source])return;let t=this.workerSources[e][r.type][r.source];delete this.workerSources[e][r.type][r.source],void 0!==t.removeSource&&t.removeSource(r)})))),this.actor.registerMessageHandler("RM",(e=>t._(this,void 0,void 0,(function*(){delete this.layerIndexes[e],delete this.availableImages[e],delete this.workerSources[e],delete this.demWorkerSources[e]})))),this.actor.registerMessageHandler("SR",((e,r)=>t._(this,void 0,void 0,(function*(){this.referrer=r})))),this.actor.registerMessageHandler("SRPS",((t,e)=>this._syncRTLPluginState(t,e))),this.actor.registerMessageHandler("IS",((e,r)=>t._(this,void 0,void 0,(function*(){this.self.importScripts(r)})))),this.actor.registerMessageHandler("SI",((t,e)=>this._setImages(t,e))),this.actor.registerMessageHandler("UL",((e,r)=>t._(this,void 0,void 0,(function*(){this._getLayerIndex(e).update(r.layers,r.removedIds)})))),this.actor.registerMessageHandler("SL",((e,r)=>t._(this,void 0,void 0,(function*(){this._getLayerIndex(e).replace(r)}))))}_setImages(e,r){return t._(this,void 0,void 0,(function*(){this.availableImages[e]=r;for(let t in this.workerSources[e]){let n=this.workerSources[e][t];for(let t in n)n[t].availableImages=r}}))}_syncRTLPluginState(e,r){return t._(this,void 0,void 0,(function*(){if(t.bD.isParsed())return t.bD.getState();if("loading"!==r.pluginStatus)return t.bD.setState(r),r;let e=r.pluginURL;if(this.self.importScripts(e),t.bD.isParsed()){let r={pluginStatus:"loaded",pluginURL:e};return t.bD.setState(r),r}throw t.bD.setState({pluginStatus:"error",pluginURL:""}),new Error(`RTL Text Plugin failed to import scripts from ${e}`)}))}_getAvailableImages(t){let e=this.availableImages[t];return e||(e=[]),e}_getLayerIndex(t){let r=this.layerIndexes[t];return r||(r=this.layerIndexes[t]=new e),r}_getWorkerSource(t,e,r){if(this.workerSources[t]||(this.workerSources[t]={}),this.workerSources[t][e]||(this.workerSources[t][e]={}),!this.workerSources[t][e][r]){let n={sendAsync:(e,r)=>(e.targetMapId=t,this.actor.sendAsync(e,r))};switch(e){case"vector":this.workerSources[t][e][r]=new a(n,this._getLayerIndex(t),this._getAvailableImages(t));break;case"geojson":this.workerSources[t][e][r]=new dt(n,this._getLayerIndex(t),this._getAvailableImages(t));break;default:this.workerSources[t][e][r]=new this.externalWorkerSourceTypes[e](n,this._getLayerIndex(t),this._getAvailableImages(t))}}return this.workerSources[t][e][r]}_getDEMWorkerSource(t,e){return this.demWorkerSources[t]||(this.demWorkerSources[t]={}),this.demWorkerSources[t][e]||(this.demWorkerSources[t][e]=new o),this.demWorkerSources[t][e]}}return t.i(self)&&(self.worker=new mt(self)),mt})),r("index",0,(function(t,e){var r="4.7.1";let n,i,a={now:typeof performance<"u"&&performance&&performance.now?performance.now.bind(performance):Date.now.bind(Date),frameAsync:t=>new Promise(((r,n)=>{let i=requestAnimationFrame(r);t.signal.addEventListener("abort",(()=>{cancelAnimationFrame(i),n(e.c())}))})),getImageData(t,e=0){return this.getImageCanvasContext(t).getImageData(-e,-e,t.width+2*e,t.height+2*e)},getImageCanvasContext(t){let e=window.document.createElement("canvas"),r=e.getContext("2d",{willReadFrequently:!0});if(!r)throw new Error("failed to create canvas 2d context");return e.width=t.width,e.height=t.height,r.drawImage(t,0,0,t.width,t.height),r},resolveURL:t=>(n||(n=document.createElement("a")),n.href=t,n.href),hardwareConcurrency:typeof navigator<"u"&&navigator.hardwareConcurrency||4,get prefersReducedMotion(){return!!matchMedia&&(null==i&&(i=matchMedia("(prefers-reduced-motion: reduce)")),i.matches)}};class o{static testProp(t){if(!o.docStyle)return t[0];for(let e=0;e{window.removeEventListener("click",o.suppressClickInternal,!0)}),0)}static getScale(t){let e=t.getBoundingClientRect();return{x:e.width/t.offsetWidth||1,y:e.height/t.offsetHeight||1,boundingClientRect:e}}static getPoint(t,r,n){let i=r.boundingClientRect;return new e.P((n.clientX-i.left)/r.x-t.clientLeft,(n.clientY-i.top)/r.y-t.clientTop)}static mousePos(t,e){let r=o.getScale(t);return o.getPoint(t,r,e)}static touchPos(t,e){let r=[],n=o.getScale(t);for(let i=0;i{s&&f(s),s=null,h=!0},l.onerror=()=>{u=!0,s=null},l.src="data:image/webp;base64,UklGRh4AAABXRUJQVlA4TBEAAAAvAQAAAAfQ//73v/+BiOh/AAA="),function(t){let r,n,i,a;t.resetRequestQueue=()=>{r=[],n=0,i=0,a={}},t.addThrottleControl=t=>{let e=i++;return a[e]=t,e},t.removeThrottleControl=t=>{delete a[t],s()},t.getImage=(t,n,i=!0)=>new Promise(((a,o)=>{c.supported&&(t.headers||(t.headers={}),t.headers.accept="image/webp,*/*"),e.e(t,{type:"image"}),r.push({abortController:n,requestParameters:t,supportImageRefresh:i,state:"queued",onError:t=>{o(t)},onSuccess:t=>{a(t)}}),s()}));let o=t=>e._(this,void 0,void 0,(function*(){t.state="running";let{requestParameters:r,supportImageRefresh:i,onError:a,onSuccess:o,abortController:c}=t,u=!1===i&&!e.i(self)&&!e.g(r.url)&&(!r.headers||Object.keys(r.headers).reduce(((t,e)=>t&&"accept"===e),!0));n++;let h=u?l(r,c):e.m(r,c);try{let r=yield h;delete t.abortController,t.state="completed",r.data instanceof HTMLImageElement||e.b(r.data)?o(r):r.data&&o({data:yield(f=r.data,"function"==typeof createImageBitmap?e.d(f):e.f(f)),cacheControl:r.cacheControl,expires:r.expires})}catch(e){delete t.abortController,a(e)}finally{n--,s()}var f})),s=()=>{let t=(()=>{for(let t of Object.keys(a))if(a[t]())return!0;return!1})()?e.a.MAX_PARALLEL_IMAGE_REQUESTS_PER_FRAME:e.a.MAX_PARALLEL_IMAGE_REQUESTS;for(let e=n;e0;e++){let t=r.shift();t.abortController.signal.aborted?e--:o(t)}},l=(t,r)=>new Promise(((n,i)=>{let a=new 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this.patterns){let{bin:r}=this.patterns[t],n=r.x+1,a=r.y+1,o=this.getImage(t).data,s=o.width,l=o.height;e.R.copy(o,i,{x:0,y:0},{x:n,y:a},{width:s,height:l}),e.R.copy(o,i,{x:0,y:l-1},{x:n,y:a-1},{width:s,height:1}),e.R.copy(o,i,{x:0,y:0},{x:n,y:a+l},{width:s,height:1}),e.R.copy(o,i,{x:s-1,y:0},{x:n-1,y:a},{width:1,height:l}),e.R.copy(o,i,{x:0,y:0},{x:n+s,y:a},{width:1,height:l})}this.dirty=!0}beginFrame(){this.callbackDispatchedThisFrame={}}dispatchRenderCallbacks(t){for(let r of t){if(this.callbackDispatchedThisFrame[r])continue;this.callbackDispatchedThisFrame[r]=!0;let t=this.getImage(r);t||e.w(`Image with ID: "${r}" was not found`),T(t)&&this.updateImage(r,t)}}}let A,M=1e20;function S(t,e,r,n,i,a,o,s,l){for(let c=e;c-1);l++,a[l]=s,o[l]=c,o[l+1]=M}for(let s=0,l=0;s65535)throw new Error("glyphs > 65535 not supported");if(e.ranges[i])return{stack:t,id:r,glyph:n};if(!this.url)throw new Error("glyphsUrl is not set");if(!e.requests[i]){let r=C.loadGlyphRange(t,i,this.url,this.requestManager);e.requests[i]=r}let a=yield e.requests[i];for(let t in a)this._doesCharSupportLocalGlyph(+t)||(e.glyphs[+t]=a[+t]);return e.ranges[i]=!0,{stack:t,id:r,glyph:a[r]||null}}))}_doesCharSupportLocalGlyph(t){return!!this.localIdeographFontFamily&&new RegExp("\\p{Ideo}|\\p{sc=Hang}|\\p{sc=Hira}|\\p{sc=Kana}","u").test(String.fromCodePoint(t))}_tinySDF(t,r,n){let i=this.localIdeographFontFamily;if(!i||!this._doesCharSupportLocalGlyph(n))return;let a=t.tinySDF;if(!a){let e="400";/bold/i.test(r)?e="900":/medium/i.test(r)?e="500":/light/i.test(r)&&(e="200"),a=t.tinySDF=new C.TinySDF({fontSize:48,buffer:6,radius:16,cutoff:.25,fontFamily:i,fontWeight:e})}let o=a.draw(String.fromCharCode(n));return{id:n,bitmap:new 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l,c=Math.abs(s-o.left),u=Math.abs(s-o.right),h=Math.min(c,u),f=e/r*(n+1);if(o.isDash){let t=n-Math.abs(f);l=Math.sqrt(h*h+t*t)}else l=n-Math.sqrt(h*h+f*f);this.data[i+s]=Math.max(0,Math.min(255,l+128))}}}addRegularDash(t){for(let e=t.length-1;e>=0;--e){let r=t[e],n=t[e+1];r.zeroLength?t.splice(e,1):n&&n.isDash===r.isDash&&(n.left=r.left,t.splice(e,1))}let e=t[0],r=t[t.length-1];e.isDash===r.isDash&&(e.left=r.left-this.width,r.right=e.right+this.width);let n=this.width*this.nextRow,i=0,a=t[i];for(let e=0;e1&&(a=t[++i]);let r=Math.abs(e-a.left),o=Math.abs(e-a.right),s=Math.min(r,o);this.data[n+e]=Math.max(0,Math.min(255,(a.isDash?s:-s)+128))}}addDash(t,r){let n=r?7:0,i=2*n+1;if(this.nextRow+i>this.height)return e.w("LineAtlas out of space"),null;let a=0;for(let e=0;e{t.terminate()})),this.workers=null)}isPreloaded(){return!!this.active[O]}numActive(){return Object.keys(this.active).length}}let F,B,j=Math.floor(a.hardwareConcurrency/2);function N(){return F||(F=new R),F}R.workerCount=e.C(globalThis)?Math.max(Math.min(j,3),1):1;class U{constructor(t,r){this.workerPool=t,this.actors=[],this.currentActor=0,this.id=r;let n=this.workerPool.acquire(r);for(let t=0;t{t.remove()})),this.actors=[],t&&this.workerPool.release(this.id)}registerMessageHandler(t,e){for(let r of this.actors)r.registerMessageHandler(t,e)}}function V(){return B||(B=new U(N(),e.G),B.registerMessageHandler("GR",((t,r,n)=>e.m(r,n)))),B}function q(t,r){let n=e.H();return e.J(n,n,[1,1,0]),e.K(n,n,[.5*t.width,.5*t.height,1]),e.L(n,n,t.calculatePosMatrix(r.toUnwrapped()))}function H(t,e,r,n,i,a){let o=function(t,e,r){if(t)for(let n of t){let t=e[n];if(t&&t.source===r&&"fill-extrusion"===t.type)return!0}else for(let t in e){let n=e[t];if(n.source===r&&"fill-extrusion"===n.type)return!0}return!1}(i&&i.layers,e,t.id),s=a.maxPitchScaleFactor(),l=t.tilesIn(n,s,o);l.sort(G);let c=[];for(let n of l)c.push({wrappedTileID:n.tileID.wrapped().key,queryResults:n.tile.queryRenderedFeatures(e,r,t._state,n.queryGeometry,n.cameraQueryGeometry,n.scale,i,a,s,q(t.transform,n.tileID))});let u=function(t){let e={},r={};for(let n of t){let t=n.queryResults,i=n.wrappedTileID,a=r[i]=r[i]||{};for(let r in t){let n=t[r],i=a[r]=a[r]||{},o=e[r]=e[r]||[];for(let t of n)i[t.featureIndex]||(i[t.featureIndex]=!0,o.push(t))}}return e}(c);for(let e in u)u[e].forEach((e=>{let r=e.feature,n=t.getFeatureState(r.layer["source-layer"],r.id);r.source=r.layer.source,r.layer["source-layer"]&&(r.sourceLayer=r.layer["source-layer"]),r.state=n}));return u}function G(t,e){let r=t.tileID,n=e.tileID;return r.overscaledZ-n.overscaledZ||r.canonical.y-n.canonical.y||r.wrap-n.wrap||r.canonical.x-n.canonical.x}function W(t,r,n){return e._(this,void 0,void 0,(function*(){let i=t;if(t.url?i=(yield e.h(r.transformRequest(t.url,"Source"),n)).data:yield a.frameAsync(n),!i)return null;let o=e.M(e.e(i,t),["tiles","minzoom","maxzoom","attribution","bounds","scheme","tileSize","encoding"]);return"vector_layers"in i&&i.vector_layers&&(o.vectorLayerIds=i.vector_layers.map((t=>t.id))),o}))}class Z{constructor(t,e){t&&(e?this.setSouthWest(t).setNorthEast(e):Array.isArray(t)&&(4===t.length?this.setSouthWest([t[0],t[1]]).setNorthEast([t[2],t[3]]):this.setSouthWest(t[0]).setNorthEast(t[1])))}setNorthEast(t){return this._ne=t instanceof e.N?new e.N(t.lng,t.lat):e.N.convert(t),this}setSouthWest(t){return this._sw=t instanceof e.N?new e.N(t.lng,t.lat):e.N.convert(t),this}extend(t){let r,n,i=this._sw,a=this._ne;if(t instanceof e.N)r=t,n=t;else{if(!(t instanceof Z))return Array.isArray(t)?4===t.length||t.every(Array.isArray)?this.extend(Z.convert(t)):this.extend(e.N.convert(t)):t&&("lng"in t||"lon"in t)&&"lat"in t?this.extend(e.N.convert(t)):this;if(r=t._sw,n=t._ne,!r||!n)return this}return i||a?(i.lng=Math.min(r.lng,i.lng),i.lat=Math.min(r.lat,i.lat),a.lng=Math.max(n.lng,a.lng),a.lat=Math.max(n.lat,a.lat)):(this._sw=new e.N(r.lng,r.lat),this._ne=new e.N(n.lng,n.lat)),this}getCenter(){return new e.N((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)}getSouthWest(){return this._sw}getNorthEast(){return this._ne}getNorthWest(){return new e.N(this.getWest(),this.getNorth())}getSouthEast(){return new e.N(this.getEast(),this.getSouth())}getWest(){return this._sw.lng}getSouth(){return this._sw.lat}getEast(){return this._ne.lng}getNorth(){return this._ne.lat}toArray(){return[this._sw.toArray(),this._ne.toArray()]}toString(){return`LngLatBounds(${this._sw.toString()}, ${this._ne.toString()})`}isEmpty(){return!(this._sw&&this._ne)}contains(t){let{lng:r,lat:n}=e.N.convert(t),i=this._sw.lng<=r&&r<=this._ne.lng;return this._sw.lng>this._ne.lng&&(i=this._sw.lng>=r&&r>=this._ne.lng),this._sw.lat<=n&&n<=this._ne.lat&&i}static convert(t){return t instanceof Z?t:t&&new Z(t)}static fromLngLat(t,r=0){let n=360*r/40075017,i=n/Math.cos(Math.PI/180*t.lat);return new Z(new e.N(t.lng-i,t.lat-n),new e.N(t.lng+i,t.lat+n))}adjustAntiMeridian(){let t=new e.N(this._sw.lng,this._sw.lat),r=new e.N(this._ne.lng,this._ne.lat);return new Z(t,t.lng>r.lng?new e.N(r.lng+360,r.lat):r)}}class Y{constructor(t,e,r){this.bounds=Z.convert(this.validateBounds(t)),this.minzoom=e||0,this.maxzoom=r||24}validateBounds(t){return Array.isArray(t)&&4===t.length?[Math.max(-180,t[0]),Math.max(-90,t[1]),Math.min(180,t[2]),Math.min(90,t[3])]:[-180,-90,180,90]}contains(t){let r=Math.pow(2,t.z),n=Math.floor(e.O(this.bounds.getWest())*r),i=Math.floor(e.Q(this.bounds.getNorth())*r),a=Math.ceil(e.O(this.bounds.getEast())*r),o=Math.ceil(e.Q(this.bounds.getSouth())*r);return t.x>=n&&t.x=i&&t.y{this._options.tiles=t})),this}setUrl(t){return this.setSourceProperty((()=>{this.url=t,this._options.url=t})),this}onRemove(){this._tileJSONRequest&&(this._tileJSONRequest.abort(),this._tileJSONRequest=null)}serialize(){return e.e({},this._options)}loadTile(t){return e._(this,void 0,void 0,(function*(){let e=t.tileID.canonical.url(this.tiles,this.map.getPixelRatio(),this.scheme),r={request:this.map._requestManager.transformRequest(e,"Tile"),uid:t.uid,tileID:t.tileID,zoom:t.tileID.overscaledZ,tileSize:this.tileSize*t.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:this.map.getPixelRatio(),showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};r.request.collectResourceTiming=this._collectResourceTiming;let n="RT";if(t.actor&&"expired"!==t.state){if("loading"===t.state)return new Promise(((e,r)=>{t.reloadPromise={resolve:e,reject:r}}))}else t.actor=this.dispatcher.getActor(),n="LT";t.abortController=new AbortController;try{let e=yield t.actor.sendAsync({type:n,data:r},t.abortController);if(delete t.abortController,t.aborted)return;this._afterTileLoadWorkerResponse(t,e)}catch(e){if(delete t.abortController,t.aborted)return;if(e&&404!==e.status)throw e;this._afterTileLoadWorkerResponse(t,null)}}))}_afterTileLoadWorkerResponse(t,e){if(e&&e.resourceTiming&&(t.resourceTiming=e.resourceTiming),e&&this.map._refreshExpiredTiles&&t.setExpiryData(e),t.loadVectorData(e,this.map.painter),t.reloadPromise){let e=t.reloadPromise;t.reloadPromise=null,this.loadTile(t).then(e.resolve).catch(e.reject)}}abortTile(t){return e._(this,void 0,void 0,(function*(){t.abortController&&(t.abortController.abort(),delete t.abortController),t.actor&&(yield t.actor.sendAsync({type:"AT",data:{uid:t.uid,type:this.type,source:this.id}}))}))}unloadTile(t){return e._(this,void 0,void 0,(function*(){t.unloadVectorData(),t.actor&&(yield t.actor.sendAsync({type:"RMT",data:{uid:t.uid,type:this.type,source:this.id}}))}))}hasTransition(){return!1}}class $ extends e.E{constructor(t,r,n,i){super(),this.id=t,this.dispatcher=n,this.setEventedParent(i),this.type="raster",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme="xyz",this.tileSize=512,this._loaded=!1,this._options=e.e({type:"raster"},r),e.e(this,e.M(r,["url","scheme","tileSize"]))}load(){return e._(this,void 0,void 0,(function*(){this._loaded=!1,this.fire(new e.k("dataloading",{dataType:"source"})),this._tileJSONRequest=new AbortController;try{let t=yield W(this._options,this.map._requestManager,this._tileJSONRequest);this._tileJSONRequest=null,this._loaded=!0,t&&(e.e(this,t),t.bounds&&(this.tileBounds=new Y(t.bounds,this.minzoom,this.maxzoom)),this.fire(new e.k("data",{dataType:"source",sourceDataType:"metadata"})),this.fire(new e.k("data",{dataType:"source",sourceDataType:"content"})))}catch(t){this._tileJSONRequest=null,this.fire(new e.j(t))}}))}loaded(){return this._loaded}onAdd(t){this.map=t,this.load()}onRemove(){this._tileJSONRequest&&(this._tileJSONRequest.abort(),this._tileJSONRequest=null)}setSourceProperty(t){this._tileJSONRequest&&(this._tileJSONRequest.abort(),this._tileJSONRequest=null),t(),this.load()}setTiles(t){return this.setSourceProperty((()=>{this._options.tiles=t})),this}setUrl(t){return this.setSourceProperty((()=>{this.url=t,this._options.url=t})),this}serialize(){return e.e({},this._options)}hasTile(t){return!this.tileBounds||this.tileBounds.contains(t.canonical)}loadTile(t){return e._(this,void 0,void 0,(function*(){let e=t.tileID.canonical.url(this.tiles,this.map.getPixelRatio(),this.scheme);t.abortController=new AbortController;try{let r=yield p.getImage(this.map._requestManager.transformRequest(e,"Tile"),t.abortController,this.map._refreshExpiredTiles);if(delete t.abortController,t.aborted)return void(t.state="unloaded");if(r&&r.data){this.map._refreshExpiredTiles&&r.cacheControl&&r.expires&&t.setExpiryData({cacheControl:r.cacheControl,expires:r.expires});let e=this.map.painter.context,n=e.gl,i=r.data;t.texture=this.map.painter.getTileTexture(i.width),t.texture?t.texture.update(i,{useMipmap:!0}):(t.texture=new w(e,i,n.RGBA,{useMipmap:!0}),t.texture.bind(n.LINEAR,n.CLAMP_TO_EDGE,n.LINEAR_MIPMAP_NEAREST)),t.state="loaded"}}catch(e){if(delete t.abortController,t.aborted)t.state="unloaded";else if(e)throw t.state="errored",e}}))}abortTile(t){return e._(this,void 0,void 0,(function*(){t.abortController&&(t.abortController.abort(),delete t.abortController)}))}unloadTile(t){return e._(this,void 0,void 0,(function*(){t.texture&&this.map.painter.saveTileTexture(t.texture)}))}hasTransition(){return!1}}class K extends ${constructor(t,r,n,i){super(t,r,n,i),this.type="raster-dem",this.maxzoom=22,this._options=e.e({type:"raster-dem"},r),this.encoding=r.encoding||"mapbox",this.redFactor=r.redFactor,this.greenFactor=r.greenFactor,this.blueFactor=r.blueFactor,this.baseShift=r.baseShift}loadTile(t){return e._(this,void 0,void 0,(function*(){let r=t.tileID.canonical.url(this.tiles,this.map.getPixelRatio(),this.scheme),n=this.map._requestManager.transformRequest(r,"Tile");t.neighboringTiles=this._getNeighboringTiles(t.tileID),t.abortController=new AbortController;try{let r=yield p.getImage(n,t.abortController,this.map._refreshExpiredTiles);if(delete t.abortController,t.aborted)return void(t.state="unloaded");if(r&&r.data){let n=r.data;this.map._refreshExpiredTiles&&r.cacheControl&&r.expires&&t.setExpiryData({cacheControl:r.cacheControl,expires:r.expires});let i=e.b(n)&&e.U()?n:yield this.readImageNow(n),a={type:this.type,uid:t.uid,source:this.id,rawImageData:i,encoding:this.encoding,redFactor:this.redFactor,greenFactor:this.greenFactor,blueFactor:this.blueFactor,baseShift:this.baseShift};if(!t.actor||"expired"===t.state){t.actor=this.dispatcher.getActor();let e=yield t.actor.sendAsync({type:"LDT",data:a});t.dem=e,t.needsHillshadePrepare=!0,t.needsTerrainPrepare=!0,t.state="loaded"}}}catch(e){if(delete t.abortController,t.aborted)t.state="unloaded";else if(e)throw t.state="errored",e}}))}readImageNow(t){return e._(this,void 0,void 0,(function*(){if(typeof VideoFrame<"u"&&e.V()){let r=t.width+2,n=t.height+2;try{return new e.R({width:r,height:n},yield e.W(t,-1,-1,r,n))}catch{}}return a.getImageData(t,1)}))}_getNeighboringTiles(t){let r=t.canonical,n=Math.pow(2,r.z),i=(r.x-1+n)%n,a=0===r.x?t.wrap-1:t.wrap,o=(r.x+1+n)%n,s=r.x+1===n?t.wrap+1:t.wrap,l={};return l[new e.S(t.overscaledZ,a,r.z,i,r.y).key]={backfilled:!1},l[new e.S(t.overscaledZ,s,r.z,o,r.y).key]={backfilled:!1},r.y>0&&(l[new e.S(t.overscaledZ,a,r.z,i,r.y-1).key]={backfilled:!1},l[new e.S(t.overscaledZ,t.wrap,r.z,r.x,r.y-1).key]={backfilled:!1},l[new e.S(t.overscaledZ,s,r.z,o,r.y-1).key]={backfilled:!1}),r.y+10&&e.e(i,{resourceTiming:n}),this.fire(new e.k("data",Object.assign(Object.assign({},i),{sourceDataType:"metadata"}))),this.fire(new e.k("data",Object.assign(Object.assign({},i),{sourceDataType:"content"})))}catch(t){if(this._pendingLoads--,this._removed)return void this.fire(new e.k("dataabort",{dataType:"source"}));this.fire(new e.j(t))}}))}loaded(){return 0===this._pendingLoads}loadTile(t){return e._(this,void 0,void 0,(function*(){let e=t.actor?"RT":"LT";t.actor=this.actor;let r={type:this.type,uid:t.uid,tileID:t.tileID,zoom:t.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:this.map.getPixelRatio(),showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};t.abortController=new AbortController;let n=yield this.actor.sendAsync({type:e,data:r},t.abortController);delete t.abortController,t.unloadVectorData(),t.aborted||t.loadVectorData(n,this.map.painter,"RT"===e)}))}abortTile(t){return e._(this,void 0,void 0,(function*(){t.abortController&&(t.abortController.abort(),delete t.abortController),t.aborted=!0}))}unloadTile(t){return e._(this,void 0,void 0,(function*(){t.unloadVectorData(),yield this.actor.sendAsync({type:"RMT",data:{uid:t.uid,type:this.type,source:this.id}})}))}onRemove(){this._removed=!0,this.actor.sendAsync({type:"RS",data:{type:this.type,source:this.id}})}serialize(){return e.e({},this._options,{type:this.type,data:this._data})}hasTransition(){return!1}}var Q=e.Y([{name:"a_pos",type:"Int16",components:2},{name:"a_texture_pos",type:"Int16",components:2}]);class tt extends e.E{constructor(t,e,r,n){super(),this.id=t,this.dispatcher=r,this.coordinates=e.coordinates,this.type="image",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(n),this.options=e}load(t){return e._(this,void 0,void 0,(function*(){this._loaded=!1,this.fire(new e.k("dataloading",{dataType:"source"})),this.url=this.options.url,this._request=new AbortController;try{let e=yield p.getImage(this.map._requestManager.transformRequest(this.url,"Image"),this._request);this._request=null,this._loaded=!0,e&&e.data&&(this.image=e.data,t&&(this.coordinates=t),this._finishLoading())}catch(t){this._request=null,this._loaded=!0,this.fire(new e.j(t))}}))}loaded(){return this._loaded}updateImage(t){return t.url?(this._request&&(this._request.abort(),this._request=null),this.options.url=t.url,this.load(t.coordinates).finally((()=>{this.texture=null})),this):this}_finishLoading(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new e.k("data",{dataType:"source",sourceDataType:"metadata"})))}onAdd(t){this.map=t,this.load()}onRemove(){this._request&&(this._request.abort(),this._request=null)}setCoordinates(t){this.coordinates=t;let r=t.map(e.Z.fromLngLat);this.tileID=function(t){let r=1/0,n=1/0,i=-1/0,a=-1/0;for(let e of t)r=Math.min(r,e.x),n=Math.min(n,e.y),i=Math.max(i,e.x),a=Math.max(a,e.y);let o=Math.max(i-r,a-n),s=Math.max(0,Math.floor(-Math.log(o)/Math.LN2)),l=Math.pow(2,s);return new e.a1(s,Math.floor((r+i)/2*l),Math.floor((n+a)/2*l))}(r),this.minzoom=this.maxzoom=this.tileID.z;let n=r.map((t=>this.tileID.getTilePoint(t)._round()));return this._boundsArray=new e.$,this._boundsArray.emplaceBack(n[0].x,n[0].y,0,0),this._boundsArray.emplaceBack(n[1].x,n[1].y,e.X,0),this._boundsArray.emplaceBack(n[3].x,n[3].y,0,e.X),this._boundsArray.emplaceBack(n[2].x,n[2].y,e.X,e.X),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new e.k("data",{dataType:"source",sourceDataType:"content"})),this}prepare(){if(0===Object.keys(this.tiles).length||!this.image)return;let t=this.map.painter.context,r=t.gl;this.boundsBuffer||(this.boundsBuffer=t.createVertexBuffer(this._boundsArray,Q.members)),this.boundsSegments||(this.boundsSegments=e.a0.simpleSegment(0,0,4,2)),this.texture||(this.texture=new w(t,this.image,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE));let n=!1;for(let t in this.tiles){let e=this.tiles[t];"loaded"!==e.state&&(e.state="loaded",e.texture=this.texture,n=!0)}n&&this.fire(new e.k("data",{dataType:"source",sourceDataType:"idle",sourceId:this.id}))}loadTile(t){return e._(this,void 0,void 0,(function*(){this.tileID&&this.tileID.equals(t.tileID.canonical)?(this.tiles[String(t.tileID.wrap)]=t,t.buckets={}):t.state="errored"}))}serialize(){return{type:"image",url:this.options.url,coordinates:this.coordinates}}hasTransition(){return!1}}class et extends tt{constructor(t,e,r,n){super(t,e,r,n),this.roundZoom=!0,this.type="video",this.options=e}load(){return e._(this,void 0,void 0,(function*(){this._loaded=!1;let t=this.options;this.urls=[];for(let e of t.urls)this.urls.push(this.map._requestManager.transformRequest(e,"Source").url);try{let t=yield e.a3(this.urls);if(this._loaded=!0,!t)return;this.video=t,this.video.loop=!0,this.video.addEventListener("playing",(()=>{this.map.triggerRepaint()})),this.map&&this.video.play(),this._finishLoading()}catch(t){this.fire(new e.j(t))}}))}pause(){this.video&&this.video.pause()}play(){this.video&&this.video.play()}seek(t){if(this.video){let r=this.video.seekable;tr.end(0)?this.fire(new e.j(new e.a2(`sources.${this.id}`,null,`Playback for this video can be set only between the ${r.start(0)} and ${r.end(0)}-second mark.`))):this.video.currentTime=t}}getVideo(){return this.video}onAdd(t){this.map||(this.map=t,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))}prepare(){if(0===Object.keys(this.tiles).length||this.video.readyState<2)return;let t=this.map.painter.context,r=t.gl;this.boundsBuffer||(this.boundsBuffer=t.createVertexBuffer(this._boundsArray,Q.members)),this.boundsSegments||(this.boundsSegments=e.a0.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE),r.texSubImage2D(r.TEXTURE_2D,0,0,0,r.RGBA,r.UNSIGNED_BYTE,this.video)):(this.texture=new w(t,this.video,r.RGBA),this.texture.bind(r.LINEAR,r.CLAMP_TO_EDGE));let n=!1;for(let t in this.tiles){let e=this.tiles[t];"loaded"!==e.state&&(e.state="loaded",e.texture=this.texture,n=!0)}n&&this.fire(new e.k("data",{dataType:"source",sourceDataType:"idle",sourceId:this.id}))}serialize(){return{type:"video",urls:this.urls,coordinates:this.coordinates}}hasTransition(){return this.video&&!this.video.paused}}class rt extends tt{constructor(t,r,n,i){super(t,r,n,i),r.coordinates?Array.isArray(r.coordinates)&&4===r.coordinates.length&&!r.coordinates.some((t=>!Array.isArray(t)||2!==t.length||t.some((t=>"number"!=typeof t))))||this.fire(new e.j(new e.a2(`sources.${t}`,null,'"coordinates" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new e.j(new e.a2(`sources.${t}`,null,'missing required property "coordinates"'))),r.animate&&"boolean"!=typeof r.animate&&this.fire(new e.j(new e.a2(`sources.${t}`,null,'optional "animate" property must be a boolean value'))),r.canvas?"string"==typeof r.canvas||r.canvas instanceof HTMLCanvasElement||this.fire(new e.j(new e.a2(`sources.${t}`,null,'"canvas" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new e.j(new e.a2(`sources.${t}`,null,'missing required property "canvas"'))),this.options=r,this.animate=void 0===r.animate||r.animate}load(){return e._(this,void 0,void 0,(function*(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof HTMLCanvasElement?this.options.canvas:document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new e.j(new Error("Canvas dimensions cannot be less than or equal to zero."))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())}))}getCanvas(){return this.canvas}onAdd(t){this.map=t,this.load(),this.canvas&&this.animate&&this.play()}onRemove(){this.pause()}prepare(){let t=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,t=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,t=!0),this._hasInvalidDimensions()||0===Object.keys(this.tiles).length)return;let r=this.map.painter.context,n=r.gl;this.boundsBuffer||(this.boundsBuffer=r.createVertexBuffer(this._boundsArray,Q.members)),this.boundsSegments||(this.boundsSegments=e.a0.simpleSegment(0,0,4,2)),this.texture?(t||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new w(r,this.canvas,n.RGBA,{premultiply:!0});let i=!1;for(let t in this.tiles){let e=this.tiles[t];"loaded"!==e.state&&(e.state="loaded",e.texture=this.texture,i=!0)}i&&this.fire(new e.k("data",{dataType:"source",sourceDataType:"idle",sourceId:this.id}))}serialize(){return{type:"canvas",coordinates:this.coordinates}}hasTransition(){return this._playing}_hasInvalidDimensions(){for(let t of[this.canvas.width,this.canvas.height])if(isNaN(t)||t<=0)return!0;return!1}}let nt={},it=t=>{switch(t){case"geojson":return J;case"image":return tt;case"raster":return $;case"raster-dem":return K;case"vector":return X;case"video":return et;case"canvas":return rt}return nt[t]},at="RTLPluginLoaded";class ot extends e.E{constructor(){super(...arguments),this.status="unavailable",this.url=null,this.dispatcher=V()}_syncState(t){return this.status=t,this.dispatcher.broadcast("SRPS",{pluginStatus:t,pluginURL:this.url}).catch((t=>{throw this.status="error",t}))}getRTLTextPluginStatus(){return this.status}clearRTLTextPlugin(){this.status="unavailable",this.url=null}setRTLTextPlugin(t){return e._(this,arguments,void 0,(function*(t,e=!1){if(this.url)throw new Error("setRTLTextPlugin cannot be called multiple times.");if(this.url=a.resolveURL(t),!this.url)throw new Error(`requested url ${t} is invalid`);if("unavailable"===this.status){if(!e)return this._requestImport();this.status="deferred",this._syncState(this.status)}else if("requested"===this.status)return this._requestImport()}))}_requestImport(){return e._(this,void 0,void 0,(function*(){yield this._syncState("loading"),this.status="loaded",this.fire(new e.k(at))}))}lazyLoad(){"unavailable"===this.status?this.status="requested":"deferred"===this.status&&this._requestImport()}}let st=null;function lt(){return st||(st=new ot),st}class ct{constructor(t,r){this.timeAdded=0,this.fadeEndTime=0,this.tileID=t,this.uid=e.a4(),this.uses=0,this.tileSize=r,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.rtt=[],this.rttCoords={},this.expiredRequestCount=0,this.state="loading"}registerFadeDuration(t){let e=t+this.timeAdded;ee.getLayer(t))).filter(Boolean);if(0!==t.length){n.layers=t,n.stateDependentLayerIds&&(n.stateDependentLayers=n.stateDependentLayerIds.map((e=>t.filter((t=>t.id===e))[0])));for(let e of t)r[e.id]=n}}return r}(t.buckets,r.style),this.hasSymbolBuckets=!1;for(let t in this.buckets){let r=this.buckets[t];if(r instanceof e.a6){if(this.hasSymbolBuckets=!0,!n)break;r.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(let t in this.buckets){let r=this.buckets[t];if(r instanceof e.a6&&r.hasRTLText){this.hasRTLText=!0,lt().lazyLoad();break}}this.queryPadding=0;for(let t in this.buckets){let e=this.buckets[t];this.queryPadding=Math.max(this.queryPadding,r.style.getLayer(t).queryRadius(e))}t.imageAtlas&&(this.imageAtlas=t.imageAtlas),t.glyphAtlasImage&&(this.glyphAtlasImage=t.glyphAtlasImage)}else this.collisionBoxArray=new e.a5}unloadVectorData(){for(let t in this.buckets)this.buckets[t].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state="unloaded"}getBucket(t){return this.buckets[t.id]}upload(t){for(let e in this.buckets){let r=this.buckets[e];r.uploadPending()&&r.upload(t)}let e=t.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new w(t,this.imageAtlas.image,e.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new w(t,this.glyphAtlasImage,e.ALPHA),this.glyphAtlasImage=null)}prepare(t){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(t,this.imageAtlasTexture)}queryRenderedFeatures(t,e,r,n,i,a,o,s,l,c){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:n,cameraQueryGeometry:i,scale:a,tileSize:this.tileSize,pixelPosMatrix:c,transform:s,params:o,queryPadding:this.queryPadding*l},t,e,r):{}}querySourceFeatures(t,r){let n=this.latestFeatureIndex;if(!n||!n.rawTileData)return;let i=n.loadVTLayers(),a=r&&r.sourceLayer?r.sourceLayer:"",o=i._geojsonTileLayer||i[a];if(!o)return;let s=e.a7(r&&r.filter),{z:l,x:c,y:u}=this.tileID.canonical,h={z:l,x:c,y:u};for(let r=0;rt)e=!1;else if(r)if(this.expirationTime{this.remove(t,i)}),r)),this.data[n].push(i),this.order.push(n),this.order.length>this.max){let t=this._getAndRemoveByKey(this.order[0]);t&&this.onRemove(t)}return this}has(t){return t.wrapped().key in this.data}getAndRemove(t){return this.has(t)?this._getAndRemoveByKey(t.wrapped().key):null}_getAndRemoveByKey(t){let e=this.data[t].shift();return e.timeout&&clearTimeout(e.timeout),0===this.data[t].length&&delete this.data[t],this.order.splice(this.order.indexOf(t),1),e.value}getByKey(t){let e=this.data[t];return e?e[0].value:null}get(t){return this.has(t)?this.data[t.wrapped().key][0].value:null}remove(t,e){if(!this.has(t))return this;let r=t.wrapped().key,n=void 0===e?0:this.data[r].indexOf(e),i=this.data[r][n];return this.data[r].splice(n,1),i.timeout&&clearTimeout(i.timeout),0===this.data[r].length&&delete this.data[r],this.onRemove(i.value),this.order.splice(this.order.indexOf(r),1),this}setMaxSize(t){for(this.max=t;this.order.length>this.max;){let t=this._getAndRemoveByKey(this.order[0]);t&&this.onRemove(t)}return this}filter(t){let e=[];for(let r in this.data)for(let n of this.data[r])t(n.value)||e.push(n);for(let t of e)this.remove(t.value.tileID,t)}}class ht{constructor(){this.state={},this.stateChanges={},this.deletedStates={}}updateState(t,r,n){let i=String(r);if(this.stateChanges[t]=this.stateChanges[t]||{},this.stateChanges[t][i]=this.stateChanges[t][i]||{},e.e(this.stateChanges[t][i],n),null===this.deletedStates[t]){this.deletedStates[t]={};for(let e in this.state[t])e!==i&&(this.deletedStates[t][e]=null)}else if(this.deletedStates[t]&&null===this.deletedStates[t][i]){this.deletedStates[t][i]={};for(let e in this.state[t][i])n[e]||(this.deletedStates[t][i][e]=null)}else for(let e in n)this.deletedStates[t]&&this.deletedStates[t][i]&&null===this.deletedStates[t][i][e]&&delete this.deletedStates[t][i][e]}removeFeatureState(t,e,r){if(null===this.deletedStates[t])return;let n=String(e);if(this.deletedStates[t]=this.deletedStates[t]||{},r&&void 0!==e)null!==this.deletedStates[t][n]&&(this.deletedStates[t][n]=this.deletedStates[t][n]||{},this.deletedStates[t][n][r]=null);else if(void 0!==e)if(this.stateChanges[t]&&this.stateChanges[t][n])for(r in this.deletedStates[t][n]={},this.stateChanges[t][n])this.deletedStates[t][n][r]=null;else this.deletedStates[t][n]=null;else this.deletedStates[t]=null}getState(t,r){let n=String(r),i=e.e({},(this.state[t]||{})[n],(this.stateChanges[t]||{})[n]);if(null===this.deletedStates[t])return{};if(this.deletedStates[t]){let e=this.deletedStates[t][r];if(null===e)return{};for(let t in e)delete i[t]}return i}initializeTileState(t,e){t.setFeatureState(this.state,e)}coalesceChanges(t,r){let n={};for(let t in this.stateChanges){this.state[t]=this.state[t]||{};let r={};for(let n in this.stateChanges[t])this.state[t][n]||(this.state[t][n]={}),e.e(this.state[t][n],this.stateChanges[t][n]),r[n]=this.state[t][n];n[t]=r}for(let t in this.deletedStates){this.state[t]=this.state[t]||{};let r={};if(null===this.deletedStates[t])for(let e in this.state[t])r[e]={},this.state[t][e]={};else for(let e in this.deletedStates[t]){if(null===this.deletedStates[t][e])this.state[t][e]={};else for(let r of Object.keys(this.deletedStates[t][e]))delete this.state[t][e][r];r[e]=this.state[t][e]}n[t]=n[t]||{},e.e(n[t],r)}if(this.stateChanges={},this.deletedStates={},0!==Object.keys(n).length)for(let e in t)t[e].setFeatureState(n,r)}}class ft extends e.E{constructor(t,e,r){super(),this.id=t,this.dispatcher=r,this.on("data",(t=>this._dataHandler(t))),this.on("dataloading",(()=>{this._sourceErrored=!1})),this.on("error",(()=>{this._sourceErrored=this._source.loaded()})),this._source=((t,e,r,n)=>{let i=new(it(e.type))(t,e,r,n);if(i.id!==t)throw new Error(`Expected Source id to be ${t} instead of ${i.id}`);return i})(t,e,r,this),this._tiles={},this._cache=new ut(0,(t=>this._unloadTile(t))),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._maxTileCacheZoomLevels=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new ht,this._didEmitContent=!1,this._updated=!1}onAdd(t){this.map=t,this._maxTileCacheSize=t?t._maxTileCacheSize:null,this._maxTileCacheZoomLevels=t?t._maxTileCacheZoomLevels:null,this._source&&this._source.onAdd&&this._source.onAdd(t)}onRemove(t){this.clearTiles(),this._source&&this._source.onRemove&&this._source.onRemove(t)}loaded(){if(this._sourceErrored)return!0;if(!this._sourceLoaded||!this._source.loaded())return!1;if(!(void 0===this.used&&void 0===this.usedForTerrain||this.used||this.usedForTerrain))return!0;if(!this._updated)return!1;for(let t in this._tiles){let e=this._tiles[t];if("loaded"!==e.state&&"errored"!==e.state)return!1}return!0}getSource(){return this._source}pause(){this._paused=!0}resume(){if(!this._paused)return;let t=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,t&&this.reload(),this.transform&&this.update(this.transform,this.terrain)}_loadTile(t,r,n){return e._(this,void 0,void 0,(function*(){try{yield this._source.loadTile(t),this._tileLoaded(t,r,n)}catch(r){t.state="errored",404!==r.status?this._source.fire(new e.j(r,{tile:t})):this.update(this.transform,this.terrain)}}))}_unloadTile(t){this._source.unloadTile&&this._source.unloadTile(t)}_abortTile(t){this._source.abortTile&&this._source.abortTile(t),this._source.fire(new e.k("dataabort",{tile:t,coord:t.tileID,dataType:"source"}))}serialize(){return this._source.serialize()}prepare(t){this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null);for(let e in this._tiles){let r=this._tiles[e];r.upload(t),r.prepare(this.map.style.imageManager)}}getIds(){return Object.values(this._tiles).map((t=>t.tileID)).sort(pt).map((t=>t.key))}getRenderableIds(t){let r=[];for(let e in this._tiles)this._isIdRenderable(e,t)&&r.push(this._tiles[e]);return t?r.sort(((t,r)=>{let n=t.tileID,i=r.tileID,a=new e.P(n.canonical.x,n.canonical.y)._rotate(this.transform.angle),o=new e.P(i.canonical.x,i.canonical.y)._rotate(this.transform.angle);return n.overscaledZ-i.overscaledZ||o.y-a.y||o.x-a.x})).map((t=>t.tileID.key)):r.map((t=>t.tileID)).sort(pt).map((t=>t.key))}hasRenderableParent(t){let e=this.findLoadedParent(t,0);return!!e&&this._isIdRenderable(e.tileID.key)}_isIdRenderable(t,e){return this._tiles[t]&&this._tiles[t].hasData()&&!this._coveredTiles[t]&&(e||!this._tiles[t].holdingForFade())}reload(){if(this._paused)this._shouldReloadOnResume=!0;else{this._cache.reset();for(let t in this._tiles)"errored"!==this._tiles[t].state&&this._reloadTile(t,"reloading")}}_reloadTile(t,r){return e._(this,void 0,void 0,(function*(){let e=this._tiles[t];e&&("loading"!==e.state&&(e.state=r),yield this._loadTile(e,t,r))}))}_tileLoaded(t,r,n){t.timeAdded=a.now(),"expired"===n&&(t.refreshedUponExpiration=!0),this._setTileReloadTimer(r,t),"raster-dem"===this.getSource().type&&t.dem&&this._backfillDEM(t),this._state.initializeTileState(t,this.map?this.map.painter:null),t.aborted||this._source.fire(new e.k("data",{dataType:"source",tile:t,coord:t.tileID}))}_backfillDEM(t){let e=this.getRenderableIds();for(let n=0;n1||(Math.abs(r)>1&&(1===Math.abs(r+i)?r+=i:1===Math.abs(r-i)&&(r-=i)),e.dem&&t.dem&&(t.dem.backfillBorder(e.dem,r,n),t.neighboringTiles&&t.neighboringTiles[a]&&(t.neighboringTiles[a].backfilled=!0)))}}getTile(t){return this.getTileByID(t.key)}getTileByID(t){return this._tiles[t]}_retainLoadedChildren(t,e,r,n){for(let i in this._tiles){let a=this._tiles[i];if(n[i]||!a.hasData()||a.tileID.overscaledZ<=e||a.tileID.overscaledZ>r)continue;let o=a.tileID;for(;a&&a.tileID.overscaledZ>e+1;){let t=a.tileID.scaledTo(a.tileID.overscaledZ-1);a=this._tiles[t.key],a&&a.hasData()&&(o=t)}let s=o;for(;s.overscaledZ>e;)if(s=s.scaledTo(s.overscaledZ-1),t[s.key]){n[o.key]=o;break}}}findLoadedParent(t,e){if(t.key in this._loadedParentTiles){let r=this._loadedParentTiles[t.key];return r&&r.tileID.overscaledZ>=e?r:null}for(let r=t.overscaledZ-1;r>=e;r--){let e=t.scaledTo(r),n=this._getLoadedTile(e);if(n)return n}}findLoadedSibling(t){return this._getLoadedTile(t)}_getLoadedTile(t){let e=this._tiles[t.key];return e&&e.hasData()?e:this._cache.getByKey(t.wrapped().key)}updateCacheSize(t){let r=Math.ceil(t.width/this._source.tileSize)+1,n=Math.ceil(t.height/this._source.tileSize)+1,i=Math.floor(r*n*(null===this._maxTileCacheZoomLevels?e.a.MAX_TILE_CACHE_ZOOM_LEVELS:this._maxTileCacheZoomLevels)),a="number"==typeof this._maxTileCacheSize?Math.min(this._maxTileCacheSize,i):i;this._cache.setMaxSize(a)}handleWrapJump(t){let e=Math.round((t-(void 0===this._prevLng?t:this._prevLng))/360);if(this._prevLng=t,e){let t={};for(let r in this._tiles){let n=this._tiles[r];n.tileID=n.tileID.unwrapTo(n.tileID.wrap+e),t[n.tileID.key]=n}this._tiles=t;for(let t in this._timers)clearTimeout(this._timers[t]),delete this._timers[t];for(let t in this._tiles)this._setTileReloadTimer(t,this._tiles[t])}}_updateCoveredAndRetainedTiles(t,e,r,n,i,o){let s={},l={},c=Object.keys(t),u=a.now();for(let r of c){let n=t[r],i=this._tiles[r];if(!i||0!==i.fadeEndTime&&i.fadeEndTime<=u)continue;let a=this.findLoadedParent(n,e),o=this.findLoadedSibling(n),c=a||o||null;c&&(this._addTile(c.tileID),s[c.tileID.key]=c.tileID),l[r]=n}this._retainLoadedChildren(l,n,r,t);for(let e in s)t[e]||(this._coveredTiles[e]=!0,t[e]=s[e]);if(o){let e={},r={};for(let t of i)this._tiles[t.key].hasData()?e[t.key]=t:r[t.key]=t;for(let n in r){let i=r[n].children(this._source.maxzoom);this._tiles[i[0].key]&&this._tiles[i[1].key]&&this._tiles[i[2].key]&&this._tiles[i[3].key]&&(e[i[0].key]=t[i[0].key]=i[0],e[i[1].key]=t[i[1].key]=i[1],e[i[2].key]=t[i[2].key]=i[2],e[i[3].key]=t[i[3].key]=i[3],delete r[n])}for(let n in r){let i=r[n],a=this.findLoadedParent(i,this._source.minzoom),o=this.findLoadedSibling(i),s=a||o||null;if(s){e[s.tileID.key]=t[s.tileID.key]=s.tileID;for(let t in e)e[t].isChildOf(s.tileID)&&delete e[t]}}for(let t in this._tiles)e[t]||(this._coveredTiles[t]=!0)}}update(t,r){if(!this._sourceLoaded||this._paused)return;let n;this.transform=t,this.terrain=r,this.updateCacheSize(t),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used||this.usedForTerrain?this._source.tileID?n=t.getVisibleUnwrappedCoordinates(this._source.tileID).map((t=>new e.S(t.canonical.z,t.wrap,t.canonical.z,t.canonical.x,t.canonical.y))):(n=t.coveringTiles({tileSize:this.usedForTerrain?this.tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:!this.usedForTerrain&&this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled,terrain:r}),this._source.hasTile&&(n=n.filter((t=>this._source.hasTile(t))))):n=[];let i=t.coveringZoomLevel(this._source),a=Math.max(i-ft.maxOverzooming,this._source.minzoom),o=Math.max(i+ft.maxUnderzooming,this._source.minzoom);if(this.usedForTerrain){let t={};for(let e of n)if(e.canonical.z>this._source.minzoom){let r=e.scaledTo(e.canonical.z-1);t[r.key]=r;let n=e.scaledTo(Math.max(this._source.minzoom,Math.min(e.canonical.z,5)));t[n.key]=n}n=n.concat(Object.values(t))}let s=0===n.length&&!this._updated&&this._didEmitContent;this._updated=!0,s&&this.fire(new e.k("data",{sourceDataType:"idle",dataType:"source",sourceId:this.id}));let l=this._updateRetainedTiles(n,i);dt(this._source.type)&&this._updateCoveredAndRetainedTiles(l,a,o,i,n,r);for(let t in l)this._tiles[t].clearFadeHold();let c=e.ab(this._tiles,l);for(let t of c){let e=this._tiles[t];e.hasSymbolBuckets&&!e.holdingForFade()?e.setHoldDuration(this.map._fadeDuration):e.hasSymbolBuckets&&!e.symbolFadeFinished()||this._removeTile(t)}this._updateLoadedParentTileCache(),this._updateLoadedSiblingTileCache()}releaseSymbolFadeTiles(){for(let t in this._tiles)this._tiles[t].holdingForFade()&&this._removeTile(t)}_updateRetainedTiles(t,e){var r;let n={},i={},a=Math.max(e-ft.maxOverzooming,this._source.minzoom),o=Math.max(e+ft.maxUnderzooming,this._source.minzoom),s={};for(let r of t){let t=this._addTile(r);n[r.key]=r,t.hasData()||ethis._source.maxzoom){let t=o.children(this._source.maxzoom)[0],e=this.getTile(t);if(e&&e.hasData()){n[t.key]=t;continue}}else{let t=o.children(this._source.maxzoom);if(n[t[0].key]&&n[t[1].key]&&n[t[2].key]&&n[t[3].key])continue}let s=t.wasRequested();for(let e=o.overscaledZ-1;e>=a;--e){let a=o.scaledTo(e);if(i[a.key])break;if(i[a.key]=!0,t=this.getTile(a),!t&&s&&(t=this._addTile(a)),t){let e=t.hasData();if((e||!(null!==(r=this.map)&&void 0!==r&&r.cancelPendingTileRequestsWhileZooming)||s)&&(n[a.key]=a),s=t.wasRequested(),e)break}}}return n}_updateLoadedParentTileCache(){this._loadedParentTiles={};for(let t in this._tiles){let e,r=[],n=this._tiles[t].tileID;for(;n.overscaledZ>0;){if(n.key in this._loadedParentTiles){e=this._loadedParentTiles[n.key];break}r.push(n.key);let t=n.scaledTo(n.overscaledZ-1);if(e=this._getLoadedTile(t),e)break;n=t}for(let t of r)this._loadedParentTiles[t]=e}}_updateLoadedSiblingTileCache(){this._loadedSiblingTiles={};for(let t in this._tiles){let e=this._tiles[t].tileID,r=this._getLoadedTile(e);this._loadedSiblingTiles[e.key]=r}}_addTile(t){let r=this._tiles[t.key];if(r)return r;r=this._cache.getAndRemove(t),r&&(this._setTileReloadTimer(t.key,r),r.tileID=t,this._state.initializeTileState(r,this.map?this.map.painter:null),this._cacheTimers[t.key]&&(clearTimeout(this._cacheTimers[t.key]),delete this._cacheTimers[t.key],this._setTileReloadTimer(t.key,r)));let n=r;return r||(r=new ct(t,this._source.tileSize*t.overscaleFactor()),this._loadTile(r,t.key,r.state)),r.uses++,this._tiles[t.key]=r,n||this._source.fire(new e.k("dataloading",{tile:r,coord:r.tileID,dataType:"source"})),r}_setTileReloadTimer(t,e){t in this._timers&&(clearTimeout(this._timers[t]),delete this._timers[t]);let r=e.getExpiryTimeout();r&&(this._timers[t]=setTimeout((()=>{this._reloadTile(t,"expired"),delete this._timers[t]}),r))}_removeTile(t){let e=this._tiles[t];e&&(e.uses--,delete this._tiles[t],this._timers[t]&&(clearTimeout(this._timers[t]),delete this._timers[t]),e.uses>0||(e.hasData()&&"reloading"!==e.state?this._cache.add(e.tileID,e,e.getExpiryTimeout()):(e.aborted=!0,this._abortTile(e),this._unloadTile(e))))}_dataHandler(t){let e=t.sourceDataType;"source"===t.dataType&&"metadata"===e&&(this._sourceLoaded=!0),this._sourceLoaded&&!this._paused&&"source"===t.dataType&&"content"===e&&(this.reload(),this.transform&&this.update(this.transform,this.terrain),this._didEmitContent=!0)}clearTiles(){this._shouldReloadOnResume=!1,this._paused=!1;for(let t in this._tiles)this._removeTile(t);this._cache.reset()}tilesIn(t,r,n){let i=[],a=this.transform;if(!a)return i;let o=n?a.getCameraQueryGeometry(t):t,s=t.map((t=>a.pointCoordinate(t,this.terrain))),l=o.map((t=>a.pointCoordinate(t,this.terrain))),c=this.getIds(),u=1/0,h=1/0,f=-1/0,p=-1/0;for(let t of l)u=Math.min(u,t.x),h=Math.min(h,t.y),f=Math.max(f,t.x),p=Math.max(p,t.y);for(let t=0;t=0&&g[1].y+m>=0){let t=s.map((t=>o.getTilePoint(t))),e=l.map((t=>o.getTilePoint(t)));i.push({tile:n,tileID:o,queryGeometry:t,cameraQueryGeometry:e,scale:d})}}return i}getVisibleCoordinates(t){let e=this.getRenderableIds(t).map((t=>this._tiles[t].tileID));for(let t of e)t.posMatrix=this.transform.calculatePosMatrix(t.toUnwrapped());return e}hasTransition(){if(this._source.hasTransition())return!0;if(dt(this._source.type)){let t=a.now();for(let e in this._tiles)if(this._tiles[e].fadeEndTime>=t)return!0}return!1}setFeatureState(t,e,r){this._state.updateState(t=t||"_geojsonTileLayer",e,r)}removeFeatureState(t,e,r){this._state.removeFeatureState(t=t||"_geojsonTileLayer",e,r)}getFeatureState(t,e){return this._state.getState(t=t||"_geojsonTileLayer",e)}setDependencies(t,e,r){let n=this._tiles[t];n&&n.setDependencies(e,r)}reloadTilesForDependencies(t,e){for(let r in this._tiles)this._tiles[r].hasDependency(t,e)&&this._reloadTile(r,"reloading");this._cache.filter((r=>!r.hasDependency(t,e)))}}function pt(t,e){let r=Math.abs(2*t.wrap)-+(t.wrap<0),n=Math.abs(2*e.wrap)-+(e.wrap<0);return t.overscaledZ-e.overscaledZ||n-r||e.canonical.y-t.canonical.y||e.canonical.x-t.canonical.x}function dt(t){return"raster"===t||"image"===t||"video"===t}ft.maxOverzooming=10,ft.maxUnderzooming=3;class mt{constructor(t,e){this.reset(t,e)}reset(t,e){this.points=t||[],this._distances=[0];for(let t=1;t0?(i-o)/s:0;return this.points[a].mult(1-l).add(this.points[r].mult(l))}}function gt(t,e){let r=!0;return"always"===t||"never"!==t&&"never"!==e||(r=!1),r}class yt{constructor(t,e,r){let n=this.boxCells=[],i=this.circleCells=[];this.xCellCount=Math.ceil(t/r),this.yCellCount=Math.ceil(e/r);for(let t=0;tthis.width||n<0||e>this.height)return[];let s=[];if(t<=0&&e<=0&&this.width<=r&&this.height<=n){if(i)return[{key:null,x1:t,y1:e,x2:r,y2:n}];for(let t=0;t0}hitTestCircle(t,e,r,n,i){let a=t-r,o=t+r,s=e-r,l=e+r;if(o<0||a>this.width||l<0||s>this.height)return!1;let c=[];return this._forEachCell(a,s,o,l,this._queryCellCircle,c,{hitTest:!0,overlapMode:n,circle:{x:t,y:e,radius:r},seenUids:{box:{},circle:{}}},i),c.length>0}_queryCell(t,e,r,n,i,a,o,s){let{seenUids:l,hitTest:c,overlapMode:u}=o,h=this.boxCells[i];if(null!==h){let i=this.bboxes;for(let o of h)if(!l.box[o]){l.box[o]=!0;let h=4*o,f=this.boxKeys[o];if(t<=i[h+2]&&e<=i[h+3]&&r>=i[h+0]&&n>=i[h+1]&&(!s||s(f))&&(!c||!gt(u,f.overlapMode))&&(a.push({key:f,x1:i[h],y1:i[h+1],x2:i[h+2],y2:i[h+3]}),c))return!0}}let f=this.circleCells[i];if(null!==f){let i=this.circles;for(let o of f)if(!l.circle[o]){l.circle[o]=!0;let h=3*o,f=this.circleKeys[o];if(this._circleAndRectCollide(i[h],i[h+1],i[h+2],t,e,r,n)&&(!s||s(f))&&(!c||!gt(u,f.overlapMode))){let t=i[h],e=i[h+1],r=i[h+2];if(a.push({key:f,x1:t-r,y1:e-r,x2:t+r,y2:e+r}),c)return!0}}}return!1}_queryCellCircle(t,e,r,n,i,a,o,s){let{circle:l,seenUids:c,overlapMode:u}=o,h=this.boxCells[i];if(null!==h){let t=this.bboxes;for(let e of h)if(!c.box[e]){c.box[e]=!0;let r=4*e,n=this.boxKeys[e];if(this._circleAndRectCollide(l.x,l.y,l.radius,t[r+0],t[r+1],t[r+2],t[r+3])&&(!s||s(n))&&!gt(u,n.overlapMode))return a.push(!0),!0}}let f=this.circleCells[i];if(null!==f){let t=this.circles;for(let e of f)if(!c.circle[e]){c.circle[e]=!0;let r=3*e,n=this.circleKeys[e];if(this._circlesCollide(t[r],t[r+1],t[r+2],l.x,l.y,l.radius)&&(!s||s(n))&&!gt(u,n.overlapMode))return a.push(!0),!0}}}_forEachCell(t,e,r,n,i,a,o,s){let l=this._convertToXCellCoord(t),c=this._convertToYCellCoord(e),u=this._convertToXCellCoord(r),h=this._convertToYCellCoord(n);for(let f=l;f<=u;f++)for(let l=c;l<=h;l++)if(i.call(this,t,e,r,n,this.xCellCount*l+f,a,o,s))return}_convertToXCellCoord(t){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(t*this.xScale)))}_convertToYCellCoord(t){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(t*this.yScale)))}_circlesCollide(t,e,r,n,i,a){let o=n-t,s=i-e,l=r+a;return l*l>o*o+s*s}_circleAndRectCollide(t,e,r,n,i,a,o){let s=(a-n)/2,l=Math.abs(t-(n+s));if(l>s+r)return!1;let c=(o-i)/2,u=Math.abs(e-(i+c));if(u>c+r)return!1;if(l<=s||u<=c)return!0;let h=l-s,f=u-c;return h*h+f*f<=r*r}}function vt(t,r,n,i,a){let o=e.H();return r?(e.K(o,o,[1/a,1/a,1]),n||e.ad(o,o,i.angle)):e.L(o,i.labelPlaneMatrix,t),o}function xt(t,r,n,i,a){if(r){let r=e.ae(t);return e.K(r,r,[a,a,1]),n||e.ad(r,r,-i.angle),r}return i.glCoordMatrix}function _t(t,r,n,i){let a;i?(a=[t,r,i(t,r),1],e.af(a,a,n)):(a=[t,r,0,1],Ot(a,a,n));let o=a[3];return{point:new e.P(a[0]/o,a[1]/o),signedDistanceFromCamera:o,isOccluded:!1}}function bt(t,e){return.5+t/e*.5}function wt(t,e){return t.x>=-e[0]&&t.x<=e[0]&&t.y>=-e[1]&&t.y<=e[1]}function Tt(t,r,n,i,a,o,s,l,c,u,h,f,p,d,m){let g=i?t.textSizeData:t.iconSizeData,y=e.ag(g,n.transform.zoom),v=[256/n.width*2+1,256/n.height*2+1],x=i?t.text.dynamicLayoutVertexArray:t.icon.dynamicLayoutVertexArray;x.clear();let _=t.lineVertexArray,b=i?t.text.placedSymbolArray:t.icon.placedSymbolArray,w=n.transform.width/n.transform.height,T=!1;for(let i=0;iMath.abs(n.x-r.x)*i?{useVertical:!0}:(t===e.ah.vertical?r.yn.x)?{needsFlipping:!0}:null}function Mt(t,r,n,i,a,o,s,l,c,u,h){let f,p=n/24,d=r.lineOffsetX*p,m=r.lineOffsetY*p;if(r.numGlyphs>1){let e=r.glyphStartIndex+r.numGlyphs,n=r.lineStartIndex,o=r.lineStartIndex+r.lineLength,c=kt(p,l,d,m,i,r,h,t);if(!c)return{notEnoughRoom:!0};let g=_t(c.first.point.x,c.first.point.y,s,t.getElevation).point,y=_t(c.last.point.x,c.last.point.y,s,t.getElevation).point;if(a&&!i){let t=At(r.writingMode,g,y,u);if(t)return t}f=[c.first];for(let a=r.glyphStartIndex+1;a0?s.point:St(t.tileAnchorPoint,a,n,1,o,t),c=At(r.writingMode,n,l,u);if(c)return c}let n=Pt(p*l.getoffsetX(r.glyphStartIndex),d,m,i,r.segment,r.lineStartIndex,r.lineStartIndex+r.lineLength,t,h);if(!n||t.projectionCache.anyProjectionOccluded)return{notEnoughRoom:!0};f=[n]}for(let t of f)e.aj(c,t.point,t.angle);return{}}function St(t,e,r,n,i,a){let o=t.add(t.sub(e)._unit()),s=void 0!==i?_t(o.x,o.y,i,a.getElevation).point:Ct(o.x,o.y,a).point,l=r.sub(s);return r.add(l._mult(n/l.mag()))}function Et(t,r,n){let i=r.projectionCache;if(i.projections[t])return i.projections[t];let a=new e.P(r.lineVertexArray.getx(t),r.lineVertexArray.gety(t)),o=Ct(a.x,a.y,r);if(o.signedDistanceFromCamera>0)return i.projections[t]=o.point,i.anyProjectionOccluded=i.anyProjectionOccluded||o.isOccluded,o.point;let s=t-n.direction;return St(0===n.distanceFromAnchor?r.tileAnchorPoint:new e.P(r.lineVertexArray.getx(s),r.lineVertexArray.gety(s)),a,n.previousVertex,n.absOffsetX-n.distanceFromAnchor+1,void 0,r)}function Ct(t,e,r){let n,i=t+r.translation[0],a=e+r.translation[1];return!r.pitchWithMap&&r.projection.useSpecialProjectionForSymbols?(n=r.projection.projectTileCoordinates(i,a,r.unwrappedTileID,r.getElevation),n.point.x=(.5*n.point.x+.5)*r.width,n.point.y=(.5*-n.point.y+.5)*r.height):(n=_t(i,a,r.labelPlaneMatrix,r.getElevation),n.isOccluded=!1),n}function It(t,e,r){return t._unit()._perp()._mult(e*r)}function Lt(t,r,n,i,a,o,s,l,c){if(l.projectionCache.offsets[t])return l.projectionCache.offsets[t];let u=n.add(r);if(t+c.direction=a)return l.projectionCache.offsets[t]=u,u;let h=Et(t+c.direction,l,c),f=It(h.sub(n),s,c.direction),p=n.add(f),d=h.add(f);return l.projectionCache.offsets[t]=e.ak(o,u,p,d)||u,l.projectionCache.offsets[t]}function Pt(t,e,r,n,i,a,o,s,l){let c=n?t-e:t+e,u=c>0?1:-1,h=0;n&&(u*=-1,h=Math.PI),u<0&&(h+=Math.PI);let f,p=u>0?a+i:a+i+1;s.projectionCache.cachedAnchorPoint?f=s.projectionCache.cachedAnchorPoint:(f=Ct(s.tileAnchorPoint.x,s.tileAnchorPoint.y,s).point,s.projectionCache.cachedAnchorPoint=f);let d,m,g,y=f,v=f,x=0,_=0,b=Math.abs(c),w=[];for(;x+_<=b;){if(p+=u,p=o)return null;x+=_,v=y,m=d;let t={absOffsetX:b,direction:u,distanceFromAnchor:x,previousVertex:v};if(y=Et(p,s,t),0===r)w.push(v),g=y.sub(v);else{let e,n=y.sub(v);e=0===n.mag()?It(Et(p+u,s,t).sub(y),r,u):It(n,r,u),m||(m=v.add(e)),d=Lt(p,e,y,a,o,m,r,s,t),w.push(m),g=d.sub(m)}_=g.mag()}let T=g._mult((b-x)/_)._add(m||v),k=h+Math.atan2(y.y-v.y,y.x-v.x);return w.push(T),{point:T,angle:l?k:0,path:w}}let zt=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function Dt(t,e){for(let r=0;r=1;t--)l.push(o.path[t]);for(let t=1;tt.signedDistanceFromCamera<=0))?[]:t.map((t=>t.point))}let m=[];if(l.length>0){let t=l[0].clone(),r=l[0].clone();for(let e=1;e=n.x&&r.x<=i.x&&t.y>=n.y&&r.y<=i.y?[l]:r.xi.x||r.yi.y?[]:e.al([l],n.x,n.y,i.x,i.y)}for(let e of m){a.reset(e,.25*r);let n=0;n=a.length<=.5*r?1:Math.ceil(a.paddedLength/h)+1;for(let e=0;e_t(t.x,t.y,r,e.getElevation)))}queryRenderedSymbols(t){if(0===t.length||0===this.grid.keysLength()&&0===this.ignoredGrid.keysLength())return{};let r=[],n=1/0,i=1/0,a=-1/0,o=-1/0;for(let s of t){let t=new e.P(s.x+Rt,s.y+Rt);n=Math.min(n,t.x),i=Math.min(i,t.y),a=Math.max(a,t.x),o=Math.max(o,t.y),r.push(t)}let s=this.grid.query(n,i,a,o).concat(this.ignoredGrid.query(n,i,a,o)),l={},c={};for(let t of s){let n=t.key;if(void 0===l[n.bucketInstanceId]&&(l[n.bucketInstanceId]={}),l[n.bucketInstanceId][n.featureIndex])continue;let i=[new e.P(t.x1,t.y1),new e.P(t.x2,t.y1),new e.P(t.x2,t.y2),new e.P(t.x1,t.y2)];e.am(r,i)&&(l[n.bucketInstanceId][n.featureIndex]=!0,void 0===c[n.bucketInstanceId]&&(c[n.bucketInstanceId]=[]),c[n.bucketInstanceId].push(n.featureIndex))}return c}insertCollisionBox(t,e,r,n,i,a){(r?this.ignoredGrid:this.grid).insert({bucketInstanceId:n,featureIndex:i,collisionGroupID:a,overlapMode:e},t[0],t[1],t[2],t[3])}insertCollisionCircles(t,e,r,n,i,a){let o=r?this.ignoredGrid:this.grid,s={bucketInstanceId:n,featureIndex:i,collisionGroupID:a,overlapMode:e};for(let e=0;e=this.screenRightBoundary||nthis.screenBottomBoundary}isInsideGrid(t,e,r,n){return r>=0&&t=0&&ethis.projectAndGetPerspectiveRatio(n,t.x,t.y,i,c)));k=t.some((t=>!t.isOccluded)),T=t.map((t=>t.point))}else k=!0;return{box:e.ao(T),allPointsOccluded:!k}}}function Bt(t,r,n){return r*(e.X/(t.tileSize*Math.pow(2,n-t.tileID.overscaledZ)))}class jt{constructor(t,e,r,n){this.opacity=t?Math.max(0,Math.min(1,t.opacity+(t.placed?e:-e))):n&&r?1:0,this.placed=r}isHidden(){return 0===this.opacity&&!this.placed}}class Nt{constructor(t,e,r,n,i){this.text=new jt(t?t.text:null,e,r,i),this.icon=new jt(t?t.icon:null,e,n,i)}isHidden(){return this.text.isHidden()&&this.icon.isHidden()}}class Ut{constructor(t,e,r){this.text=t,this.icon=e,this.skipFade=r}}class Vt{constructor(){this.invProjMatrix=e.H(),this.viewportMatrix=e.H(),this.circles=[]}}class qt{constructor(t,e,r,n,i){this.bucketInstanceId=t,this.featureIndex=e,this.sourceLayerIndex=r,this.bucketIndex=n,this.tileID=i}}class Ht{constructor(t){this.crossSourceCollisions=t,this.maxGroupID=0,this.collisionGroups={}}get(t){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[t]){let e=++this.maxGroupID;this.collisionGroups[t]={ID:e,predicate:t=>t.collisionGroupID===e}}return this.collisionGroups[t]}}function Gt(t,r,n,i,a){let{horizontalAlign:o,verticalAlign:s}=e.au(t);return new e.P(-(o-.5)*r+i[0]*a,-(s-.5)*n+i[1]*a)}class Wt{constructor(t,e,r,n,i,a){this.transform=t.clone(),this.terrain=r,this.collisionIndex=new Ft(this.transform,e),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=n,this.retainedQueryData={},this.collisionGroups=new Ht(i),this.collisionCircleArrays={},this.collisionBoxArrays=new Map,this.prevPlacement=a,a&&(a.prevPlacement=void 0),this.placedOrientations={}}_getTerrainElevationFunc(t){let e=this.terrain;return e?(r,n)=>e.getElevation(t,r,n):null}getBucketParts(t,r,n,i){let a=n.getBucket(r),o=n.latestFeatureIndex;if(!a||!o||r.id!==a.layerIds[0])return;let s=n.collisionBoxArray,l=a.layers[0].layout,c=a.layers[0].paint,u=Math.pow(2,this.transform.zoom-n.tileID.overscaledZ),h=n.tileSize/e.X,f=n.tileID.toUnwrapped(),p=this.transform.calculatePosMatrix(f),d="map"===l.get("text-pitch-alignment"),m="map"===l.get("text-rotation-alignment"),g=Bt(n,1,this.transform.zoom),y=this.collisionIndex.mapProjection.translatePosition(this.transform,n,c.get("text-translate"),c.get("text-translate-anchor")),v=this.collisionIndex.mapProjection.translatePosition(this.transform,n,c.get("icon-translate"),c.get("icon-translate-anchor")),x=vt(p,d,m,this.transform,g),_=null;if(d){let t=xt(p,d,m,this.transform,g);_=e.L([],this.transform.labelPlaneMatrix,t)}this.retainedQueryData[a.bucketInstanceId]=new qt(a.bucketInstanceId,o,a.sourceLayerIndex,a.index,n.tileID);let b={bucket:a,layout:l,translationText:y,translationIcon:v,posMatrix:p,unwrappedTileID:f,textLabelPlaneMatrix:x,labelToScreenMatrix:_,scale:u,textPixelRatio:h,holdingForFade:n.holdingForFade(),collisionBoxArray:s,partiallyEvaluatedTextSize:e.ag(a.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(a.sourceID)};if(i)for(let e of a.sortKeyRanges){let{sortKey:r,symbolInstanceStart:n,symbolInstanceEnd:i}=e;t.push({sortKey:r,symbolInstanceStart:n,symbolInstanceEnd:i,parameters:b})}else t.push({symbolInstanceStart:0,symbolInstanceEnd:a.symbolInstances.length,parameters:b})}attemptAnchorPlacement(t,r,n,i,a,o,s,l,c,u,h,f,p,d,m,g,y,v,x){let _=e.aq[t.textAnchor],b=[t.textOffset0,t.textOffset1],w=Gt(_,n,i,b,a),T=this.collisionIndex.placeCollisionBox(r,f,l,c,u,s,o,g,h.predicate,x,w);if((!v||this.collisionIndex.placeCollisionBox(v,f,l,c,u,s,o,y,h.predicate,x,w).placeable)&&T.placeable){let t;if(this.prevPlacement&&this.prevPlacement.variableOffsets[p.crossTileID]&&this.prevPlacement.placements[p.crossTileID]&&this.prevPlacement.placements[p.crossTileID].text&&(t=this.prevPlacement.variableOffsets[p.crossTileID].anchor),0===p.crossTileID)throw new Error("symbolInstance.crossTileID can't be 0");return this.variableOffsets[p.crossTileID]={textOffset:b,width:n,height:i,anchor:_,textBoxScale:a,prevAnchor:t},this.markUsedJustification(d,_,p,m),d.allowVerticalPlacement&&(this.markUsedOrientation(d,m,p),this.placedOrientations[p.crossTileID]=m),{shift:w,placedGlyphBoxes:T}}}placeLayerBucketPart(t,r,n){let{bucket:i,layout:a,translationText:o,translationIcon:s,posMatrix:l,unwrappedTileID:c,textLabelPlaneMatrix:u,labelToScreenMatrix:h,textPixelRatio:f,holdingForFade:p,collisionBoxArray:d,partiallyEvaluatedTextSize:m,collisionGroup:g}=t.parameters,y=a.get("text-optional"),v=a.get("icon-optional"),x=e.ar(a,"text-overlap","text-allow-overlap"),_="always"===x,b=e.ar(a,"icon-overlap","icon-allow-overlap"),w="always"===b,T="map"===a.get("text-rotation-alignment"),k="map"===a.get("text-pitch-alignment"),A="none"!==a.get("icon-text-fit"),M="viewport-y"===a.get("symbol-z-order"),S=_&&(w||!i.hasIconData()||v),E=w&&(_||!i.hasTextData()||y);!i.collisionArrays&&d&&i.deserializeCollisionBoxes(d);let C=this._getTerrainElevationFunc(this.retainedQueryData[i.bucketInstanceId].tileID),I=(t,d,w)=>{var M,I;if(r[t.crossTileID])return;if(p)return void(this.placements[t.crossTileID]=new Ut(!1,!1,!1));let L=!1,P=!1,z=!0,D=null,O={box:null,placeable:!1,offscreen:null},R={box:null,placeable:!1,offscreen:null},F=null,B=null,j=null,N=0,U=0,V=0;d.textFeatureIndex?N=d.textFeatureIndex:t.useRuntimeCollisionCircles&&(N=t.featureIndex),d.verticalTextFeatureIndex&&(U=d.verticalTextFeatureIndex);let q=d.textBox;if(q){let r=r=>{let n=e.ah.horizontal;if(i.allowVerticalPlacement&&!r&&this.prevPlacement){let e=this.prevPlacement.placedOrientations[t.crossTileID];e&&(this.placedOrientations[t.crossTileID]=e,n=e,this.markUsedOrientation(i,n,t))}return n},a=(r,n)=>{if(i.allowVerticalPlacement&&t.numVerticalGlyphVertices>0&&d.verticalTextBox){for(let t of i.writingModes)if(t===e.ah.vertical?(O=n(),R=O):O=r(),O&&O.placeable)break}else O=r()},u=t.textAnchorOffsetStartIndex,h=t.textAnchorOffsetEndIndex;if(h===u){let n=(e,r)=>{let n=this.collisionIndex.placeCollisionBox(e,x,f,l,c,k,T,o,g.predicate,C);return n&&n.placeable&&(this.markUsedOrientation(i,r,t),this.placedOrientations[t.crossTileID]=r),n};a((()=>n(q,e.ah.horizontal)),(()=>{let r=d.verticalTextBox;return i.allowVerticalPlacement&&t.numVerticalGlyphVertices>0&&r?n(r,e.ah.vertical):{box:null,offscreen:null}})),r(O&&O.placeable)}else{let p=e.aq[null===(I=null===(M=this.prevPlacement)||void 0===M?void 0:M.variableOffsets[t.crossTileID])||void 0===I?void 0:I.anchor],m=(r,a,d)=>{let m=r.x2-r.x1,y=r.y2-r.y1,v=t.textBoxScale,_=A&&"never"===b?a:null,w=null,M="never"===x?1:2,S="never";p&&M++;for(let e=0;em(q,d.iconBox,e.ah.horizontal)),(()=>{let r=d.verticalTextBox;return i.allowVerticalPlacement&&(!O||!O.placeable)&&t.numVerticalGlyphVertices>0&&r?m(r,d.verticalIconBox,e.ah.vertical):{box:null,occluded:!0,offscreen:null}})),O&&(L=O.placeable,z=O.offscreen);let y=r(O&&O.placeable);if(!L&&this.prevPlacement){let e=this.prevPlacement.variableOffsets[t.crossTileID];e&&(this.variableOffsets[t.crossTileID]=e,this.markUsedJustification(i,e.anchor,t,y))}}}if(F=O,L=F&&F.placeable,z=F&&F.offscreen,t.useRuntimeCollisionCircles){let r=i.text.placedSymbolArray.get(t.centerJustifiedTextSymbolIndex),s=e.ai(i.textSizeData,m,r),f=a.get("text-padding");B=this.collisionIndex.placeCollisionCircles(x,r,i.lineVertexArray,i.glyphOffsetArray,s,l,c,u,h,n,k,g.predicate,t.collisionCircleDiameter,f,o,C),B.circles.length&&B.collisionDetected&&!n&&e.w("Collisions detected, but collision boxes are not shown"),L=_||B.circles.length>0&&!B.collisionDetected,z=z&&B.offscreen}if(d.iconFeatureIndex&&(V=d.iconFeatureIndex),d.iconBox){let t=t=>this.collisionIndex.placeCollisionBox(t,b,f,l,c,k,T,s,g.predicate,C,A&&D?D:void 0);R&&R.placeable&&d.verticalIconBox?(j=t(d.verticalIconBox),P=j.placeable):(j=t(d.iconBox),P=j.placeable),z=z&&j.offscreen}let H=y||0===t.numHorizontalGlyphVertices&&0===t.numVerticalGlyphVertices,G=v||0===t.numIconVertices;H||G?G?H||(P=P&&L):L=P&&L:P=L=P&&L;let W=P&&j.placeable;if(L&&F.placeable&&this.collisionIndex.insertCollisionBox(F.box,x,a.get("text-ignore-placement"),i.bucketInstanceId,R&&R.placeable&&U?U:N,g.ID),W&&this.collisionIndex.insertCollisionBox(j.box,b,a.get("icon-ignore-placement"),i.bucketInstanceId,V,g.ID),B&&L&&this.collisionIndex.insertCollisionCircles(B.circles,x,a.get("text-ignore-placement"),i.bucketInstanceId,N,g.ID),n&&this.storeCollisionData(i.bucketInstanceId,w,d,F,j,B),0===t.crossTileID)throw new Error("symbolInstance.crossTileID can't be 0");if(0===i.bucketInstanceId)throw new Error("bucket.bucketInstanceId can't be 0");this.placements[t.crossTileID]=new Ut(L||S,P||E,z||i.justReloaded),r[t.crossTileID]=!0};if(M){if(0!==t.symbolInstanceStart)throw new Error("bucket.bucketInstanceId should be 0");let e=i.getSortedSymbolIndexes(this.transform.angle);for(let t=e.length-1;t>=0;--t){let r=e[t];I(i.symbolInstances.get(r),i.collisionArrays[r],r)}}else for(let e=t.symbolInstanceStart;e=0&&(t.text.placedSymbolArray.get(e).crossTileID=a>=0&&e!==a?0:n.crossTileID)}markUsedOrientation(t,r,n){let i=r===e.ah.horizontal||r===e.ah.horizontalOnly?r:0,a=r===e.ah.vertical?r:0,o=[n.leftJustifiedTextSymbolIndex,n.centerJustifiedTextSymbolIndex,n.rightJustifiedTextSymbolIndex];for(let e of o)t.text.placedSymbolArray.get(e).placedOrientation=i;n.verticalPlacedTextSymbolIndex&&(t.text.placedSymbolArray.get(n.verticalPlacedTextSymbolIndex).placedOrientation=a)}commit(t){this.commitTime=t,this.zoomAtLastRecencyCheck=this.transform.zoom;let e=this.prevPlacement,r=!1;this.prevZoomAdjustment=e?e.zoomAdjustment(this.transform.zoom):0;let n=e?e.symbolFadeChange(t):1,i=e?e.opacities:{},a=e?e.variableOffsets:{},o=e?e.placedOrientations:{};for(let t in this.placements){let e=this.placements[t],a=i[t];a?(this.opacities[t]=new Nt(a,n,e.text,e.icon),r=r||e.text!==a.text.placed||e.icon!==a.icon.placed):(this.opacities[t]=new Nt(null,n,e.text,e.icon,e.skipFade),r=r||e.text||e.icon)}for(let t in i){let e=i[t];if(!this.opacities[t]){let i=new Nt(e,n,!1,!1);i.isHidden()||(this.opacities[t]=i,r=r||e.text.placed||e.icon.placed)}}for(let t in a)this.variableOffsets[t]||!this.opacities[t]||this.opacities[t].isHidden()||(this.variableOffsets[t]=a[t]);for(let t in o)this.placedOrientations[t]||!this.opacities[t]||this.opacities[t].isHidden()||(this.placedOrientations[t]=o[t]);if(e&&void 0===e.lastPlacementChangeTime)throw new Error("Last placement time for previous placement is not defined");r?this.lastPlacementChangeTime=t:"number"!=typeof this.lastPlacementChangeTime&&(this.lastPlacementChangeTime=e?e.lastPlacementChangeTime:t)}updateLayerOpacities(t,e){let r={};for(let n of e){let e=n.getBucket(t);e&&n.latestFeatureIndex&&t.id===e.layerIds[0]&&this.updateBucketOpacities(e,n.tileID,r,n.collisionBoxArray)}}updateBucketOpacities(t,r,n,i){t.hasTextData()&&(t.text.opacityVertexArray.clear(),t.text.hasVisibleVertices=!1),t.hasIconData()&&(t.icon.opacityVertexArray.clear(),t.icon.hasVisibleVertices=!1),t.hasIconCollisionBoxData()&&t.iconCollisionBox.collisionVertexArray.clear(),t.hasTextCollisionBoxData()&&t.textCollisionBox.collisionVertexArray.clear();let a=t.layers[0],o=a.layout,s=new Nt(null,0,!1,!1,!0),l=o.get("text-allow-overlap"),c=o.get("icon-allow-overlap"),u=a._unevaluatedLayout.hasValue("text-variable-anchor")||a._unevaluatedLayout.hasValue("text-variable-anchor-offset"),h="map"===o.get("text-rotation-alignment"),f="map"===o.get("text-pitch-alignment"),p="none"!==o.get("icon-text-fit"),d=new Nt(null,0,l&&(c||!t.hasIconData()||o.get("icon-optional")),c&&(l||!t.hasTextData()||o.get("text-optional")),!0);!t.collisionArrays&&i&&(t.hasIconCollisionBoxData()||t.hasTextCollisionBoxData())&&t.deserializeCollisionBoxes(i);let m=(t,e,r)=>{for(let n=0;n0,v=this.placedOrientations[i.crossTileID],x=v===e.ah.vertical,_=v===e.ah.horizontal||v===e.ah.horizontalOnly;if(a>0||o>0){let e=ee(c.text);m(t.text,a,x?re:e),m(t.text,o,_?re:e);let r=c.text.isHidden();[i.rightJustifiedTextSymbolIndex,i.centerJustifiedTextSymbolIndex,i.leftJustifiedTextSymbolIndex].forEach((e=>{e>=0&&(t.text.placedSymbolArray.get(e).hidden=r||x?1:0)})),i.verticalPlacedTextSymbolIndex>=0&&(t.text.placedSymbolArray.get(i.verticalPlacedTextSymbolIndex).hidden=r||_?1:0);let n=this.variableOffsets[i.crossTileID];n&&this.markUsedJustification(t,n.anchor,i,v);let s=this.placedOrientations[i.crossTileID];s&&(this.markUsedJustification(t,"left",i,s),this.markUsedOrientation(t,s,i))}if(y){let e=ee(c.icon),r=!(p&&i.verticalPlacedIconSymbolIndex&&x);i.placedIconSymbolIndex>=0&&(m(t.icon,i.numIconVertices,r?e:re),t.icon.placedSymbolArray.get(i.placedIconSymbolIndex).hidden=c.icon.isHidden()),i.verticalPlacedIconSymbolIndex>=0&&(m(t.icon,i.numVerticalIconVertices,r?re:e),t.icon.placedSymbolArray.get(i.verticalPlacedIconSymbolIndex).hidden=c.icon.isHidden())}let b=g&&g.has(r)?g.get(r):{text:null,icon:null};if(t.hasIconCollisionBoxData()||t.hasTextCollisionBoxData()){let n=t.collisionArrays[r];if(n){let r=new e.P(0,0);if(n.textBox||n.verticalTextBox){let e=!0;if(u){let t=this.variableOffsets[l];t?(r=Gt(t.anchor,t.width,t.height,t.textOffset,t.textBoxScale),h&&r._rotate(f?this.transform.angle:-this.transform.angle)):e=!1}if(n.textBox||n.verticalTextBox){let i;n.textBox&&(i=x),n.verticalTextBox&&(i=_),Zt(t.textCollisionBox.collisionVertexArray,c.text.placed,!e||i,b.text,r.x,r.y)}}if(n.iconBox||n.verticalIconBox){let e,i=!(_||!n.verticalIconBox);n.iconBox&&(e=i),n.verticalIconBox&&(e=!i),Zt(t.iconCollisionBox.collisionVertexArray,c.icon.placed,e,b.icon,p?r.x:0,p?r.y:0)}}}}if(t.sortFeatures(this.transform.angle),this.retainedQueryData[t.bucketInstanceId]&&(this.retainedQueryData[t.bucketInstanceId].featureSortOrder=t.featureSortOrder),t.hasTextData()&&t.text.opacityVertexBuffer&&t.text.opacityVertexBuffer.updateData(t.text.opacityVertexArray),t.hasIconData()&&t.icon.opacityVertexBuffer&&t.icon.opacityVertexBuffer.updateData(t.icon.opacityVertexArray),t.hasIconCollisionBoxData()&&t.iconCollisionBox.collisionVertexBuffer&&t.iconCollisionBox.collisionVertexBuffer.updateData(t.iconCollisionBox.collisionVertexArray),t.hasTextCollisionBoxData()&&t.textCollisionBox.collisionVertexBuffer&&t.textCollisionBox.collisionVertexBuffer.updateData(t.textCollisionBox.collisionVertexArray),t.text.opacityVertexArray.length!==t.text.layoutVertexArray.length/4)throw new Error(`bucket.text.opacityVertexArray.length (= ${t.text.opacityVertexArray.length}) !== bucket.text.layoutVertexArray.length (= ${t.text.layoutVertexArray.length}) / 4`);if(t.icon.opacityVertexArray.length!==t.icon.layoutVertexArray.length/4)throw new Error(`bucket.icon.opacityVertexArray.length (= ${t.icon.opacityVertexArray.length}) !== bucket.icon.layoutVertexArray.length (= ${t.icon.layoutVertexArray.length}) / 4`);if(t.bucketInstanceId in this.collisionCircleArrays){let e=this.collisionCircleArrays[t.bucketInstanceId];t.placementInvProjMatrix=e.invProjMatrix,t.placementViewportMatrix=e.viewportMatrix,t.collisionCircleArray=e.circles,delete this.collisionCircleArrays[t.bucketInstanceId]}}symbolFadeChange(t){return 0===this.fadeDuration?1:(t-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment}zoomAdjustment(t){return Math.max(0,(this.transform.zoom-t)/1.5)}hasTransitions(t){return this.stale||t-this.lastPlacementChangeTimet}setStale(){this.stale=!0}}function Zt(t,e,r,n,i,a){n&&0!==n.length||(n=[0,0,0,0]);let o=n[0]-Rt,s=n[1]-Rt,l=n[2]-Rt,c=n[3]-Rt;t.emplaceBack(e?1:0,r?1:0,i||0,a||0,o,s),t.emplaceBack(e?1:0,r?1:0,i||0,a||0,l,s),t.emplaceBack(e?1:0,r?1:0,i||0,a||0,l,c),t.emplaceBack(e?1:0,r?1:0,i||0,a||0,o,c)}let Yt=Math.pow(2,25),Xt=Math.pow(2,24),$t=Math.pow(2,17),Kt=Math.pow(2,16),Jt=Math.pow(2,9),Qt=Math.pow(2,8),te=Math.pow(2,1);function ee(t){if(0===t.opacity&&!t.placed)return 0;if(1===t.opacity&&t.placed)return 4294967295;let e=t.placed?1:0,r=Math.floor(127*t.opacity);return r*Yt+e*Xt+r*$t+e*Kt+r*Jt+e*Qt+r*te+e}let re=0;function ne(){return{isOccluded:(t,e,r)=>!1,getPitchedTextCorrection:(t,e,r)=>1,get useSpecialProjectionForSymbols(){return!1},projectTileCoordinates(t,e,r,n){throw new Error("Not implemented.")},translatePosition:(t,e,r,n)=>function(t,e,r,n,i=!1){if(!r[0]&&!r[1])return[0,0];let a=i?"map"===n?t.angle:0:"viewport"===n?-t.angle:0;if(a){let t=Math.sin(a),e=Math.cos(a);r=[r[0]*e-r[1]*t,r[0]*t+r[1]*e]}return[i?r[0]:Bt(e,r[0],t.zoom),i?r[1]:Bt(e,r[1],t.zoom)]}(t,e,r,n),getCircleRadiusCorrection:t=>1}}class ie{constructor(t){this._sortAcrossTiles="viewport-y"!==t.layout.get("symbol-z-order")&&!t.layout.get("symbol-sort-key").isConstant(),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]}continuePlacement(t,e,r,n,i){let a=this._bucketParts;for(;this._currentTileIndext.sortKey-e.sortKey)));this._currentPartIndex!this._forceFullPlacement&&a.now()-n>2;for(;this._currentPlacementIndex>=0;){let n=e[t[this._currentPlacementIndex]],a=this.placement.collisionIndex.transform.zoom;if("symbol"===n.type&&(!n.minzoom||n.minzoom<=a)&&(!n.maxzoom||n.maxzoom>a)){if(this._inProgressLayer||(this._inProgressLayer=new ie(n)),this._inProgressLayer.continuePlacement(r[n.source],this.placement,this._showCollisionBoxes,n,i))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0}commit(t){return this.placement.commit(t),this.placement}}let oe=512/e.X/2;class se{constructor(t,r,n){this.tileID=t,this.bucketInstanceId=n,this._symbolsByKey={};let i=new Map;for(let t=0;t({x:Math.floor(t.anchorX*oe),y:Math.floor(t.anchorY*oe)}))),crossTileIDs:r.map((t=>t.crossTileID))};if(n.positions.length>128){let t=new e.av(n.positions.length,16,Uint16Array);for(let{x:e,y:r}of n.positions)t.add(e,r);t.finish(),delete n.positions,n.index=t}this._symbolsByKey[t]=n}}getScaledCoordinates(t,r){let{x:n,y:i,z:a}=this.tileID.canonical,{x:o,y:s,z:l}=r.canonical,c=oe/Math.pow(2,l-a),u=(s*e.X+t.anchorY)*c,h=i*e.X*oe;return{x:Math.floor((o*e.X+t.anchorX)*c-n*e.X*oe),y:Math.floor(u-h)}}findMatches(t,e,r){let n=this.tileID.canonical.zt))}}class le{constructor(){this.maxCrossTileID=0}generate(){return++this.maxCrossTileID}}class ce{constructor(){this.indexes={},this.usedCrossTileIDs={},this.lng=0}handleWrapJump(t){let e=Math.round((t-this.lng)/360);if(0!==e)for(let t in this.indexes){let r=this.indexes[t],n={};for(let t in r){let i=r[t];i.tileID=i.tileID.unwrapTo(i.tileID.wrap+e),n[i.tileID.key]=i}this.indexes[t]=n}this.lng=t}addBucket(t,e,r){if(this.indexes[t.overscaledZ]&&this.indexes[t.overscaledZ][t.key]){if(this.indexes[t.overscaledZ][t.key].bucketInstanceId===e.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(t.overscaledZ,this.indexes[t.overscaledZ][t.key])}for(let t=0;tt.overscaledZ)for(let r in i){let a=i[r];a.tileID.isChildOf(t)&&a.findMatches(e.symbolInstances,t,n)}else{let a=i[t.scaledTo(Number(r)).key];a&&a.findMatches(e.symbolInstances,t,n)}}for(let t=0;t{e[t]=!0}));for(let t in this.layerIndexes)e[t]||delete this.layerIndexes[t]}}let he=(t,r)=>e.t(t,r&&r.filter((t=>"source.canvas"!==t.identifier))),fe=e.aw();class pe extends e.E{constructor(t,r={}){super(),this._rtlPluginLoaded=()=>{for(let t in this.sourceCaches){let e=this.sourceCaches[t].getSource().type;"vector"!==e&&"geojson"!==e||this.sourceCaches[t].reload()}},this.map=t,this.dispatcher=new U(N(),t._getMapId()),this.dispatcher.registerMessageHandler("GG",((t,e)=>this.getGlyphs(t,e))),this.dispatcher.registerMessageHandler("GI",((t,e)=>this.getImages(t,e))),this.imageManager=new k,this.imageManager.setEventedParent(this),this.glyphManager=new C(t._requestManager,r.localIdeographFontFamily),this.lineAtlas=new D(256,512),this.crossTileSymbolIndex=new ue,this._spritesImagesIds={},this._layers={},this._order=[],this.sourceCaches={},this.zoomHistory=new e.ax,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast("SR",e.ay()),lt().on(at,this._rtlPluginLoaded),this.on("data",(t=>{if("source"!==t.dataType||"metadata"!==t.sourceDataType)return;let e=this.sourceCaches[t.sourceId];if(!e)return;let r=e.getSource();if(r&&r.vectorLayerIds)for(let t in this._layers){let e=this._layers[t];e.source===r.id&&this._validateLayer(e)}}))}loadURL(t,r={},n){this.fire(new e.k("dataloading",{dataType:"style"})),r.validate="boolean"!=typeof r.validate||r.validate;let i=this.map._requestManager.transformRequest(t,"Style");this._loadStyleRequest=new AbortController;let a=this._loadStyleRequest;e.h(i,this._loadStyleRequest).then((t=>{this._loadStyleRequest=null,this._load(t.data,r,n)})).catch((t=>{this._loadStyleRequest=null,t&&!a.signal.aborted&&this.fire(new e.j(t))}))}loadJSON(t,r={},n){this.fire(new e.k("dataloading",{dataType:"style"})),this._frameRequest=new AbortController,a.frameAsync(this._frameRequest).then((()=>{this._frameRequest=null,r.validate=!1!==r.validate,this._load(t,r,n)})).catch((()=>{}))}loadEmpty(){this.fire(new e.k("dataloading",{dataType:"style"})),this._load(fe,{validate:!1})}_load(t,r,n){var i;let a=r.transformStyle?r.transformStyle(n,t):t;if(!r.validate||!he(this,e.u(a))){this._loaded=!0,this.stylesheet=a;for(let t in a.sources)this.addSource(t,a.sources[t],{validate:!1});a.sprite?this._loadSprite(a.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(a.glyphs),this._createLayers(),this.light=new L(this.stylesheet.light),this.sky=new z(this.stylesheet.sky),this.map.setTerrain(null!==(i=this.stylesheet.terrain)&&void 0!==i?i:null),this.fire(new e.k("data",{dataType:"style"})),this.fire(new e.k("style.load"))}}_createLayers(){let t=e.az(this.stylesheet.layers);this.dispatcher.broadcast("SL",t),this._order=t.map((t=>t.id)),this._layers={},this._serializedLayers=null;for(let r of t){let t=e.aA(r);t.setEventedParent(this,{layer:{id:r.id}}),this._layers[r.id]=t}}_loadSprite(t,r=!1,n=void 0){let i;this.imageManager.setLoaded(!1),this._spriteRequest=new AbortController,function(t,r,n,i){return e._(this,void 0,void 0,(function*(){let o=_(t),s=n>1?"@2x":"",l={},c={};for(let{id:t,url:n}of o){let a=r.transformRequest(b(n,s,".json"),"SpriteJSON");l[t]=e.h(a,i);let o=r.transformRequest(b(n,s,".png"),"SpriteImage");c[t]=p.getImage(o,i)}return yield Promise.all([...Object.values(l),...Object.values(c)]),function(t,r){return e._(this,void 0,void 0,(function*(){let e={};for(let n in t){e[n]={};let i=a.getImageCanvasContext((yield r[n]).data),o=(yield t[n]).data;for(let t in o){let{width:r,height:a,x:s,y:l,sdf:c,pixelRatio:u,stretchX:h,stretchY:f,content:p,textFitWidth:d,textFitHeight:m}=o[t];e[n][t]={data:null,pixelRatio:u,sdf:c,stretchX:h,stretchY:f,content:p,textFitWidth:d,textFitHeight:m,spriteData:{width:r,height:a,x:s,y:l,context:i}}}}return e}))}(l,c)}))}(t,this.map._requestManager,this.map.getPixelRatio(),this._spriteRequest).then((t=>{if(this._spriteRequest=null,t)for(let e in t){this._spritesImagesIds[e]=[];let n=this._spritesImagesIds[e]?this._spritesImagesIds[e].filter((e=>!(e in t))):[];for(let t of n)this.imageManager.removeImage(t),this._changedImages[t]=!0;for(let n in t[e]){let i="default"===e?n:`${e}:${n}`;this._spritesImagesIds[e].push(i),i in this.imageManager.images?this.imageManager.updateImage(i,t[e][n],!1):this.imageManager.addImage(i,t[e][n]),r&&(this._changedImages[i]=!0)}}})).catch((t=>{this._spriteRequest=null,i=t,this.fire(new e.j(i))})).finally((()=>{this.imageManager.setLoaded(!0),this._availableImages=this.imageManager.listImages(),r&&(this._changed=!0),this.dispatcher.broadcast("SI",this._availableImages),this.fire(new e.k("data",{dataType:"style"})),n&&n(i)}))}_unloadSprite(){for(let t of Object.values(this._spritesImagesIds).flat())this.imageManager.removeImage(t),this._changedImages[t]=!0;this._spritesImagesIds={},this._availableImages=this.imageManager.listImages(),this._changed=!0,this.dispatcher.broadcast("SI",this._availableImages),this.fire(new e.k("data",{dataType:"style"}))}_validateLayer(t){let r=this.sourceCaches[t.source];if(!r)return;let n=t.sourceLayer;if(!n)return;let i=r.getSource();("geojson"===i.type||i.vectorLayerIds&&-1===i.vectorLayerIds.indexOf(n))&&this.fire(new e.j(new Error(`Source layer "${n}" does not exist on source "${i.id}" as specified by style layer "${t.id}".`)))}loaded(){if(!this._loaded||Object.keys(this._updatedSources).length)return!1;for(let t in this.sourceCaches)if(!this.sourceCaches[t].loaded())return!1;return!!this.imageManager.isLoaded()}_serializeByIds(t,r=!1){let n=this._serializedAllLayers();if(!t||0===t.length)return Object.values(r?e.aB(n):n);let i=[];for(let a of t)if(n[a]){let t=r?e.aB(n[a]):n[a];i.push(t)}return i}_serializedAllLayers(){let t=this._serializedLayers;if(t)return t;t=this._serializedLayers={};let e=Object.keys(this._layers);for(let r of e){let e=this._layers[r];"custom"!==e.type&&(t[r]=e.serialize())}return t}hasTransitions(){if(this.light&&this.light.hasTransition()||this.sky&&this.sky.hasTransition())return!0;for(let t in this.sourceCaches)if(this.sourceCaches[t].hasTransition())return!0;for(let t in this._layers)if(this._layers[t].hasTransition())return!0;return!1}_checkLoaded(){if(!this._loaded)throw new Error("Style is not done loading.")}update(t){if(!this._loaded)return;let r=this._changed;if(r){let e=Object.keys(this._updatedLayers),r=Object.keys(this._removedLayers);(e.length||r.length)&&this._updateWorkerLayers(e,r);for(let t in this._updatedSources){let e=this._updatedSources[t];if("reload"===e)this._reloadSource(t);else{if("clear"!==e)throw new Error(`Invalid action ${e}`);this._clearSource(t)}}this._updateTilesForChangedImages(),this._updateTilesForChangedGlyphs();for(let e in this._updatedPaintProps)this._layers[e].updateTransitions(t);this.light.updateTransitions(t),this.sky.updateTransitions(t),this._resetUpdates()}let n={};for(let t in this.sourceCaches){let e=this.sourceCaches[t];n[t]=e.used,e.used=!1}for(let e of this._order){let r=this._layers[e];r.recalculate(t,this._availableImages),!r.isHidden(t.zoom)&&r.source&&(this.sourceCaches[r.source].used=!0)}for(let t in n){let r=this.sourceCaches[t];!!n[t]!=!!r.used&&r.fire(new e.k("data",{sourceDataType:"visibility",dataType:"source",sourceId:t}))}this.light.recalculate(t),this.sky.recalculate(t),this.z=t.zoom,r&&this.fire(new e.k("data",{dataType:"style"}))}_updateTilesForChangedImages(){let t=Object.keys(this._changedImages);if(t.length){for(let e in this.sourceCaches)this.sourceCaches[e].reloadTilesForDependencies(["icons","patterns"],t);this._changedImages={}}}_updateTilesForChangedGlyphs(){if(this._glyphsDidChange){for(let t in this.sourceCaches)this.sourceCaches[t].reloadTilesForDependencies(["glyphs"],[""]);this._glyphsDidChange=!1}}_updateWorkerLayers(t,e){this.dispatcher.broadcast("UL",{layers:this._serializeByIds(t,!1),removedIds:e})}_resetUpdates(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={},this._glyphsDidChange=!1}setState(t,r={}){var n;this._checkLoaded();let i=this.serialize();if(t=r.transformStyle?r.transformStyle(i,t):t,(null===(n=r.validate)||void 0===n||n)&&he(this,e.u(t)))return!1;(t=e.aB(t)).layers=e.az(t.layers);let a=e.aC(i,t),o=this._getOperationsToPerform(a);if(o.unimplemented.length>0)throw new Error(`Unimplemented: ${o.unimplemented.join(", ")}.`);if(0===o.operations.length)return!1;for(let t of o.operations)t();return this.stylesheet=t,this._serializedLayers=null,!0}_getOperationsToPerform(t){let e=[],r=[];for(let n of t)switch(n.command){case"setCenter":case"setZoom":case"setBearing":case"setPitch":continue;case"addLayer":e.push((()=>this.addLayer.apply(this,n.args)));break;case"removeLayer":e.push((()=>this.removeLayer.apply(this,n.args)));break;case"setPaintProperty":e.push((()=>this.setPaintProperty.apply(this,n.args)));break;case"setLayoutProperty":e.push((()=>this.setLayoutProperty.apply(this,n.args)));break;case"setFilter":e.push((()=>this.setFilter.apply(this,n.args)));break;case"addSource":e.push((()=>this.addSource.apply(this,n.args)));break;case"removeSource":e.push((()=>this.removeSource.apply(this,n.args)));break;case"setLayerZoomRange":e.push((()=>this.setLayerZoomRange.apply(this,n.args)));break;case"setLight":e.push((()=>this.setLight.apply(this,n.args)));break;case"setGeoJSONSourceData":e.push((()=>this.setGeoJSONSourceData.apply(this,n.args)));break;case"setGlyphs":e.push((()=>this.setGlyphs.apply(this,n.args)));break;case"setSprite":e.push((()=>this.setSprite.apply(this,n.args)));break;case"setSky":e.push((()=>this.setSky.apply(this,n.args)));break;case"setTerrain":e.push((()=>this.map.setTerrain.apply(this,n.args)));break;case"setTransition":e.push((()=>{}));break;default:r.push(n.command)}return{operations:e,unimplemented:r}}addImage(t,r){if(this.getImage(t))return this.fire(new e.j(new Error(`An image named "${t}" already exists.`)));this.imageManager.addImage(t,r),this._afterImageUpdated(t)}updateImage(t,e){this.imageManager.updateImage(t,e)}getImage(t){return this.imageManager.getImage(t)}removeImage(t){if(!this.getImage(t))return this.fire(new e.j(new Error(`An image named "${t}" does not exist.`)));this.imageManager.removeImage(t),this._afterImageUpdated(t)}_afterImageUpdated(t){this._availableImages=this.imageManager.listImages(),this._changedImages[t]=!0,this._changed=!0,this.dispatcher.broadcast("SI",this._availableImages),this.fire(new e.k("data",{dataType:"style"}))}listImages(){return this._checkLoaded(),this.imageManager.listImages()}addSource(t,r,n={}){if(this._checkLoaded(),void 0!==this.sourceCaches[t])throw new Error(`Source "${t}" already exists.`);if(!r.type)throw new Error(`The type property must be defined, but only the following properties were given: ${Object.keys(r).join(", ")}.`);if(["vector","raster","geojson","video","image"].indexOf(r.type)>=0&&this._validate(e.u.source,`sources.${t}`,r,null,n))return;this.map&&this.map._collectResourceTiming&&(r.collectResourceTiming=!0);let i=this.sourceCaches[t]=new ft(t,r,this.dispatcher);i.style=this,i.setEventedParent(this,(()=>({isSourceLoaded:i.loaded(),source:i.serialize(),sourceId:t}))),i.onAdd(this.map),this._changed=!0}removeSource(t){if(this._checkLoaded(),void 0===this.sourceCaches[t])throw new Error("There is no source with this ID");for(let r in this._layers)if(this._layers[r].source===t)return this.fire(new e.j(new Error(`Source "${t}" cannot be removed while layer "${r}" is using it.`)));let r=this.sourceCaches[t];delete this.sourceCaches[t],delete this._updatedSources[t],r.fire(new e.k("data",{sourceDataType:"metadata",dataType:"source",sourceId:t})),r.setEventedParent(null),r.onRemove(this.map),this._changed=!0}setGeoJSONSourceData(t,e){if(this._checkLoaded(),void 0===this.sourceCaches[t])throw new Error(`There is no source with this ID=${t}`);let r=this.sourceCaches[t].getSource();if("geojson"!==r.type)throw new Error(`geojsonSource.type is ${r.type}, which is !== 'geojson`);r.setData(e),this._changed=!0}getSource(t){return this.sourceCaches[t]&&this.sourceCaches[t].getSource()}addLayer(t,r,n={}){this._checkLoaded();let i,a=t.id;if(this.getLayer(a))return void this.fire(new e.j(new Error(`Layer "${a}" already exists on this map.`)));if("custom"===t.type){if(he(this,e.aD(t)))return;i=e.aA(t)}else{if("source"in t&&"object"==typeof t.source&&(this.addSource(a,t.source),t=e.aB(t),t=e.e(t,{source:a})),this._validate(e.u.layer,`layers.${a}`,t,{arrayIndex:-1},n))return;i=e.aA(t),this._validateLayer(i),i.setEventedParent(this,{layer:{id:a}})}let o=r?this._order.indexOf(r):this._order.length;if(r&&-1===o)this.fire(new e.j(new Error(`Cannot add layer "${a}" before non-existing layer "${r}".`)));else{if(this._order.splice(o,0,a),this._layerOrderChanged=!0,this._layers[a]=i,this._removedLayers[a]&&i.source&&"custom"!==i.type){let t=this._removedLayers[a];delete this._removedLayers[a],t.type!==i.type?this._updatedSources[i.source]="clear":(this._updatedSources[i.source]="reload",this.sourceCaches[i.source].pause())}this._updateLayer(i),i.onAdd&&i.onAdd(this.map)}}moveLayer(t,r){if(this._checkLoaded(),this._changed=!0,!this._layers[t])return void this.fire(new e.j(new Error(`The layer '${t}' does not exist in the map's style and cannot be moved.`)));if(t===r)return;let n=this._order.indexOf(t);this._order.splice(n,1);let i=r?this._order.indexOf(r):this._order.length;r&&-1===i?this.fire(new e.j(new Error(`Cannot move layer "${t}" before non-existing layer "${r}".`))):(this._order.splice(i,0,t),this._layerOrderChanged=!0)}removeLayer(t){this._checkLoaded();let r=this._layers[t];if(!r)return void this.fire(new e.j(new Error(`Cannot remove non-existing layer "${t}".`)));r.setEventedParent(null);let n=this._order.indexOf(t);this._order.splice(n,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[t]=r,delete this._layers[t],this._serializedLayers&&delete this._serializedLayers[t],delete this._updatedLayers[t],delete this._updatedPaintProps[t],r.onRemove&&r.onRemove(this.map)}getLayer(t){return this._layers[t]}getLayersOrder(){return[...this._order]}hasLayer(t){return t in this._layers}setLayerZoomRange(t,r,n){this._checkLoaded();let i=this.getLayer(t);i?i.minzoom===r&&i.maxzoom===n||(null!=r&&(i.minzoom=r),null!=n&&(i.maxzoom=n),this._updateLayer(i)):this.fire(new e.j(new Error(`Cannot set the zoom range of non-existing layer "${t}".`)))}setFilter(t,r,n={}){this._checkLoaded();let i=this.getLayer(t);if(i){if(!e.aE(i.filter,r))return null==r?(i.filter=void 0,void this._updateLayer(i)):void(this._validate(e.u.filter,`layers.${i.id}.filter`,r,null,n)||(i.filter=e.aB(r),this._updateLayer(i)))}else this.fire(new e.j(new Error(`Cannot filter non-existing layer "${t}".`)))}getFilter(t){return e.aB(this.getLayer(t).filter)}setLayoutProperty(t,r,n,i={}){this._checkLoaded();let a=this.getLayer(t);a?e.aE(a.getLayoutProperty(r),n)||(a.setLayoutProperty(r,n,i),this._updateLayer(a)):this.fire(new e.j(new Error(`Cannot style non-existing layer "${t}".`)))}getLayoutProperty(t,r){let n=this.getLayer(t);if(n)return n.getLayoutProperty(r);this.fire(new e.j(new Error(`Cannot get style of non-existing layer "${t}".`)))}setPaintProperty(t,r,n,i={}){this._checkLoaded();let a=this.getLayer(t);a?e.aE(a.getPaintProperty(r),n)||(a.setPaintProperty(r,n,i)&&this._updateLayer(a),this._changed=!0,this._updatedPaintProps[t]=!0,this._serializedLayers=null):this.fire(new e.j(new Error(`Cannot style non-existing layer "${t}".`)))}getPaintProperty(t,e){return this.getLayer(t).getPaintProperty(e)}setFeatureState(t,r){this._checkLoaded();let n=t.source,i=t.sourceLayer,a=this.sourceCaches[n];if(void 0===a)return void this.fire(new e.j(new Error(`The source '${n}' does not exist in the map's style.`)));let o=a.getSource().type;"geojson"===o&&i?this.fire(new e.j(new Error("GeoJSON sources cannot have a sourceLayer parameter."))):"vector"!==o||i?(void 0===t.id&&this.fire(new e.j(new Error("The feature id parameter must be provided."))),a.setFeatureState(i,t.id,r)):this.fire(new e.j(new Error("The sourceLayer parameter must be provided for vector source types.")))}removeFeatureState(t,r){this._checkLoaded();let n=t.source,i=this.sourceCaches[n];if(void 0===i)return void this.fire(new e.j(new Error(`The source '${n}' does not exist in the map's style.`)));let a=i.getSource().type,o="vector"===a?t.sourceLayer:void 0;"vector"!==a||o?r&&"string"!=typeof t.id&&"number"!=typeof t.id?this.fire(new e.j(new Error("A feature id is required to remove its specific state property."))):i.removeFeatureState(o,t.id,r):this.fire(new e.j(new Error("The sourceLayer parameter must be provided for vector source types.")))}getFeatureState(t){this._checkLoaded();let r=t.source,n=t.sourceLayer,i=this.sourceCaches[r];if(void 0!==i)return"vector"!==i.getSource().type||n?(void 0===t.id&&this.fire(new e.j(new Error("The feature id parameter must be provided."))),i.getFeatureState(n,t.id)):void this.fire(new e.j(new Error("The sourceLayer parameter must be provided for vector source types.")));this.fire(new e.j(new Error(`The source '${r}' does not exist in the map's style.`)))}getTransition(){return e.e({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)}serialize(){if(!this._loaded)return;let t=e.aF(this.sourceCaches,(t=>t.serialize())),r=this._serializeByIds(this._order,!0),n=this.map.getTerrain()||void 0,i=this.stylesheet;return e.aG({version:i.version,name:i.name,metadata:i.metadata,light:i.light,sky:i.sky,center:i.center,zoom:i.zoom,bearing:i.bearing,pitch:i.pitch,sprite:i.sprite,glyphs:i.glyphs,transition:i.transition,sources:t,layers:r,terrain:n},(t=>void 0!==t))}_updateLayer(t){this._updatedLayers[t.id]=!0,t.source&&!this._updatedSources[t.source]&&"raster"!==this.sourceCaches[t.source].getSource().type&&(this._updatedSources[t.source]="reload",this.sourceCaches[t.source].pause()),this._serializedLayers=null,this._changed=!0}_flattenAndSortRenderedFeatures(t){let e=t=>"fill-extrusion"===this._layers[t].type,r={},n=[];for(let i=this._order.length-1;i>=0;i--){let a=this._order[i];if(e(a)){r[a]=i;for(let e of t){let t=e[a];if(t)for(let e of t)n.push(e)}}}n.sort(((t,e)=>e.intersectionZ-t.intersectionZ));let i=[];for(let a=this._order.length-1;a>=0;a--){let o=this._order[a];if(e(o))for(let t=n.length-1;t>=0;t--){let e=n[t].feature;if(r[e.layer.id]{let n=r.featureSortOrder;if(n){let r=n.indexOf(t.featureIndex);return n.indexOf(e.featureIndex)-r}return e.featureIndex-t.featureIndex}));for(let t of i)e.push(t)}}for(let e in s)s[e].forEach((n=>{let i=n.feature,a=r[t[e].source].getFeatureState(i.layer["source-layer"],i.id);i.source=i.layer.source,i.layer["source-layer"]&&(i.sourceLayer=i.layer["source-layer"]),i.state=a}));return s}(this._layers,o,this.sourceCaches,t,r,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(a)}querySourceFeatures(t,r){r&&r.filter&&this._validate(e.u.filter,"querySourceFeatures.filter",r.filter,null,r);let n=this.sourceCaches[t];return n?function(t,e){let r=t.getRenderableIds().map((e=>t.getTileByID(e))),n=[],i={};for(let t=0;tt.getTileByID(e))).sort(((t,e)=>e.tileID.overscaledZ-t.tileID.overscaledZ||(t.tileID.isLessThan(e.tileID)?-1:1)))}let n=this.crossTileSymbolIndex.addLayer(r,l[r.source],t.center.lng);o=o||n}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((i=i||this._layerOrderChanged||0===r)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(a.now(),t.zoom))&&(this.pauseablePlacement=new ae(t,this.map.terrain,this._order,i,e,r,n,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,l),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(a.now()),s=!0),o&&this.pauseablePlacement.placement.setStale()),s||o)for(let t of this._order){let e=this._layers[t];"symbol"===e.type&&this.placement.updateLayerOpacities(e,l[e.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(a.now())}_releaseSymbolFadeTiles(){for(let t in this.sourceCaches)this.sourceCaches[t].releaseSymbolFadeTiles()}getImages(t,r){return e._(this,void 0,void 0,(function*(){let t=yield this.imageManager.getImages(r.icons);this._updateTilesForChangedImages();let e=this.sourceCaches[r.source];return e&&e.setDependencies(r.tileID.key,r.type,r.icons),t}))}getGlyphs(t,r){return e._(this,void 0,void 0,(function*(){let t=yield this.glyphManager.getGlyphs(r.stacks),e=this.sourceCaches[r.source];return e&&e.setDependencies(r.tileID.key,r.type,[""]),t}))}getGlyphsUrl(){return this.stylesheet.glyphs||null}setGlyphs(t,r={}){this._checkLoaded(),t&&this._validate(e.u.glyphs,"glyphs",t,null,r)||(this._glyphsDidChange=!0,this.stylesheet.glyphs=t,this.glyphManager.entries={},this.glyphManager.setURL(t))}addSprite(t,r,n={},i){this._checkLoaded();let a=[{id:t,url:r}],o=[..._(this.stylesheet.sprite),...a];this._validate(e.u.sprite,"sprite",o,null,n)||(this.stylesheet.sprite=o,this._loadSprite(a,!0,i))}removeSprite(t){this._checkLoaded();let r=_(this.stylesheet.sprite);if(r.find((e=>e.id===t))){if(this._spritesImagesIds[t])for(let e of this._spritesImagesIds[t])this.imageManager.removeImage(e),this._changedImages[e]=!0;r.splice(r.findIndex((e=>e.id===t)),1),this.stylesheet.sprite=r.length>0?r:void 0,delete this._spritesImagesIds[t],this._availableImages=this.imageManager.listImages(),this._changed=!0,this.dispatcher.broadcast("SI",this._availableImages),this.fire(new e.k("data",{dataType:"style"}))}else this.fire(new e.j(new Error(`Sprite "${t}" doesn't exists on this map.`)))}getSprite(){return _(this.stylesheet.sprite)}setSprite(t,r={},n){this._checkLoaded(),t&&this._validate(e.u.sprite,"sprite",t,null,r)||(this.stylesheet.sprite=t,t?this._loadSprite(t,!0,n):(this._unloadSprite(),n&&n(null)))}}var de=e.Y([{name:"a_pos",type:"Int16",components:2}]);let me={prelude:ge("#ifdef GL_ES\nprecision mediump float;\n#else\n#if !defined(lowp)\n#define lowp\n#endif\n#if !defined(mediump)\n#define mediump\n#endif\n#if !defined(highp)\n#define highp\n#endif\n#endif\n","#ifdef GL_ES\nprecision highp float;\n#else\n#if !defined(lowp)\n#define lowp\n#endif\n#if !defined(mediump)\n#define mediump\n#endif\n#if !defined(highp)\n#define highp\n#endif\n#endif\nvec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0\n);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;}\n#ifdef TERRAIN3D\nuniform sampler2D u_terrain;uniform float u_terrain_dim;uniform mat4 u_terrain_matrix;uniform vec4 u_terrain_unpack;uniform float u_terrain_exaggeration;uniform highp sampler2D u_depth;\n#endif\nconst highp vec4 bitSh=vec4(256.*256.*256.,256.*256.,256.,1.);const highp vec4 bitShifts=vec4(1.)/bitSh;highp float unpack(highp vec4 color) {return dot(color,bitShifts);}highp float depthOpacity(vec3 frag) {\n#ifdef TERRAIN3D\nhighp float d=unpack(texture2D(u_depth,frag.xy*0.5+0.5))+0.0001-frag.z;return 1.0-max(0.0,min(1.0,-d*500.0));\n#else\nreturn 1.0;\n#endif\n}float calculate_visibility(vec4 pos) {\n#ifdef TERRAIN3D\nvec3 frag=pos.xyz/pos.w;highp float d=depthOpacity(frag);if (d > 0.95) return 1.0;return (d+depthOpacity(frag+vec3(0.0,0.01,0.0)))/2.0;\n#else\nreturn 1.0;\n#endif\n}float ele(vec2 pos) {\n#ifdef TERRAIN3D\nvec4 rgb=(texture2D(u_terrain,pos)*255.0)*u_terrain_unpack;return rgb.r+rgb.g+rgb.b-u_terrain_unpack.a;\n#else\nreturn 0.0;\n#endif\n}float get_elevation(vec2 pos) {\n#ifdef TERRAIN3D\nvec2 coord=(u_terrain_matrix*vec4(pos,0.0,1.0)).xy*u_terrain_dim+1.0;vec2 f=fract(coord);vec2 c=(floor(coord)+0.5)/(u_terrain_dim+2.0);float d=1.0/(u_terrain_dim+2.0);float tl=ele(c);float tr=ele(c+vec2(d,0.0));float bl=ele(c+vec2(0.0,d));float br=ele(c+vec2(d,d));float elevation=mix(mix(tl,tr,f.x),mix(bl,br,f.x),f.y);return elevation*u_terrain_exaggeration;\n#else\nreturn 0.0;\n#endif\n}"),background:ge("uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}"),backgroundPattern:ge("uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}"),circle:ge("varying vec3 v_data;varying float v_visibility;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define mediump float radius\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define highp vec4 stroke_color\n#pragma mapbox: define mediump float stroke_width\n#pragma mapbox: define lowp float stroke_opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize mediump float radius\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize highp vec4 stroke_color\n#pragma mapbox: initialize mediump float stroke_width\n#pragma mapbox: initialize lowp float stroke_opacity\nvec2 extrude=v_data.xy;float extrude_length=length(extrude);float antialiased_blur=v_data.z;float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=v_visibility*opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;varying float v_visibility;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define mediump float radius\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define highp vec4 stroke_color\n#pragma mapbox: define mediump float stroke_width\n#pragma mapbox: define lowp float stroke_opacity\nvoid main(void) {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize mediump float radius\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize highp vec4 stroke_color\n#pragma mapbox: initialize mediump float stroke_width\n#pragma mapbox: initialize lowp float stroke_opacity\nvec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);float ele=get_elevation(circle_center);v_visibility=calculate_visibility(u_matrix*vec4(circle_center,ele,1.0));if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,ele,1);} else {gl_Position=u_matrix*vec4(circle_center,ele,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}float antialiasblur=-max(1.0/u_device_pixel_ratio/(radius+stroke_width),blur);v_data=vec3(extrude.x,extrude.y,antialiasblur);}"),clippingMask:ge("void main() {gl_FragColor=vec4(1.0);}","attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}"),heatmap:ge("uniform highp float u_intensity;varying vec2 v_extrude;\n#pragma mapbox: define highp float weight\n#define GAUSS_COEF 0.3989422804014327\nvoid main() {\n#pragma mapbox: initialize highp float weight\nfloat d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude;\n#pragma mapbox: define highp float weight\n#pragma mapbox: define mediump float radius\nconst highp float ZERO=1.0/255.0/16.0;\n#define GAUSS_COEF 0.3989422804014327\nvoid main(void) {\n#pragma mapbox: initialize highp float weight\n#pragma mapbox: initialize mediump float radius\nvec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,get_elevation(floor(a_pos*0.5)),1);gl_Position=u_matrix*pos;}"),heatmapTexture:ge("uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(0.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}"),collisionBox:ge("varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}","attribute vec2 a_anchor_pos;attribute vec2 a_placed;attribute vec2 a_box_real;uniform mat4 u_matrix;uniform vec2 u_pixel_extrude_scale;varying float v_placed;varying float v_notUsed;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);}void main() {gl_Position=projectTileWithElevation(a_anchor_pos,get_elevation(a_anchor_pos));gl_Position.xy=((a_box_real+0.5)*u_pixel_extrude_scale*2.0-1.0)*vec2(1.0,-1.0)*gl_Position.w;if (gl_Position.z/gl_Position.w < 1.1) {gl_Position.z=0.5;}v_placed=a_placed.x;v_notUsed=a_placed.y;}"),collisionCircle:ge("varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}","attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}"),debug:ge("uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}","attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,get_elevation(a_pos),1);}"),fill:ge("#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float opacity\ngl_FragColor=color*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","attribute vec2 a_pos;uniform mat4 u_matrix;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float opacity\ngl_Position=u_matrix*vec4(a_pos,0,1);}"),fillOutline:ge("varying vec2 v_pos;\n#pragma mapbox: define highp vec4 outline_color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 outline_color\n#pragma mapbox: initialize lowp float opacity\nfloat dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos;\n#pragma mapbox: define highp vec4 outline_color\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 outline_color\n#pragma mapbox: initialize lowp float opacity\ngl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}"),fillOutlinePattern:ge("uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}"),fillPattern:ge("#ifdef GL_ES\nprecision highp float;\n#endif\nuniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}"),fillExtrusion:ge("varying vec4 v_color;void main() {gl_FragColor=v_color;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed;\n#ifdef TERRAIN3D\nattribute vec2 a_centroid;\n#endif\nvarying vec4 v_color;\n#pragma mapbox: define highp float base\n#pragma mapbox: define highp float height\n#pragma mapbox: define highp vec4 color\nvoid main() {\n#pragma mapbox: initialize highp float base\n#pragma mapbox: initialize highp float height\n#pragma mapbox: initialize highp vec4 color\nvec3 normal=a_normal_ed.xyz;\n#ifdef TERRAIN3D\nfloat height_terrain3d_offset=get_elevation(a_centroid);float base_terrain3d_offset=height_terrain3d_offset-(base > 0.0 ? 0.0 : 10.0);\n#else\nfloat height_terrain3d_offset=0.0;float base_terrain3d_offset=0.0;\n#endif\nbase=max(0.0,base)+base_terrain3d_offset;height=max(0.0,height)+height_terrain3d_offset;float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}"),fillExtrusionPattern:ge("uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\n#pragma mapbox: define lowp float base\n#pragma mapbox: define lowp float height\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float base\n#pragma mapbox: initialize lowp float height\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;\n#ifdef TERRAIN3D\nattribute vec2 a_centroid;\n#endif\nvarying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting;\n#pragma mapbox: define lowp float base\n#pragma mapbox: define lowp float height\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float base\n#pragma mapbox: initialize lowp float height\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;\n#ifdef TERRAIN3D\nfloat height_terrain3d_offset=get_elevation(a_centroid);float base_terrain3d_offset=height_terrain3d_offset-(base > 0.0 ? 0.0 : 10.0);\n#else\nfloat height_terrain3d_offset=0.0;float base_terrain3d_offset=0.0;\n#endif\nbase=max(0.0,base)+base_terrain3d_offset;height=max(0.0,height)+height_terrain3d_offset;float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0\n? a_pos\n: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}"),hillshadePrepare:ge("#ifdef GL_ES\nprecision highp float;\n#endif\nuniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggerationFactor=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;float exaggeration=u_zoom < 15.0 ? (u_zoom-15.0)*exaggerationFactor : 0.0;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/pow(2.0,exaggeration+(19.2562-u_zoom));gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}"),hillshade:ge("uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent;\n#define PI 3.141592653589793\nvoid main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}"),line:ge("uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define scale 0.015873016\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float width\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float width\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;\n#ifdef TERRAIN3D\nv_gamma_scale=1.0;\n#else\nfloat extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;\n#endif\nv_width2=vec2(outset,inset);}"),lineGradient:ge("uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp vec2 v_uv;\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,v_uv);gl_FragColor=color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define scale 0.015873016\nattribute vec2 a_pos_normal;attribute vec4 a_data;attribute float a_uv_x;attribute float a_split_index;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;uniform float u_image_height;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp vec2 v_uv;\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float width\nvoid main() {\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float width\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;highp float texel_height=1.0/u_image_height;highp float half_texel_height=0.5*texel_height;v_uv=vec2(a_uv_x,a_split_index*texel_height-half_texel_height);vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;\n#ifdef TERRAIN3D\nv_gamma_scale=1.0;\n#else\nfloat extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;\n#endif\nv_width2=vec2(outset,inset);}"),linePattern:ge("#ifdef GL_ES\nprecision highp float;\n#endif\nuniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\nvec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define scale 0.015873016\n#define LINE_DISTANCE_SCALE 2.0\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width;\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define mediump float width\n#pragma mapbox: define lowp float floorwidth\n#pragma mapbox: define lowp vec4 pattern_from\n#pragma mapbox: define lowp vec4 pattern_to\n#pragma mapbox: define lowp float pixel_ratio_from\n#pragma mapbox: define lowp float pixel_ratio_to\nvoid main() {\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize mediump float width\n#pragma mapbox: initialize lowp float floorwidth\n#pragma mapbox: initialize mediump vec4 pattern_from\n#pragma mapbox: initialize mediump vec4 pattern_to\n#pragma mapbox: initialize lowp float pixel_ratio_from\n#pragma mapbox: initialize lowp float pixel_ratio_to\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;\n#ifdef TERRAIN3D\nv_gamma_scale=1.0;\n#else\nfloat extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;\n#endif\nv_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}"),lineSDF:ge("uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float width\n#pragma mapbox: define lowp float floorwidth\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float width\n#pragma mapbox: initialize lowp float floorwidth\nfloat dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","\n#define scale 0.015873016\n#define LINE_DISTANCE_SCALE 2.0\nattribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale;\n#pragma mapbox: define highp vec4 color\n#pragma mapbox: define lowp float blur\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define mediump float gapwidth\n#pragma mapbox: define lowp float offset\n#pragma mapbox: define mediump float width\n#pragma mapbox: define lowp float floorwidth\nvoid main() {\n#pragma mapbox: initialize highp vec4 color\n#pragma mapbox: initialize lowp float blur\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize mediump float gapwidth\n#pragma mapbox: initialize lowp float offset\n#pragma mapbox: initialize mediump float width\n#pragma mapbox: initialize lowp float floorwidth\nfloat ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;\n#ifdef TERRAIN3D\nv_gamma_scale=1.0;\n#else\nfloat extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;\n#endif\nv_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}"),raster:ge("uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}"),symbolIcon:ge("uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity;\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\nlowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;uniform bool u_is_along_line;uniform bool u_is_variable_anchor;uniform vec2 u_translation;uniform float u_pitched_scale;varying vec2 v_tex;varying float v_fade_opacity;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);}\n#pragma mapbox: define lowp float opacity\nvoid main() {\n#pragma mapbox: initialize lowp float opacity\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;float ele=get_elevation(a_pos);highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec2 translated_a_pos=a_pos+u_translation;vec4 projectedPoint=projectTileWithElevation(translated_a_pos,ele);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\ncamera_to_anchor_distance/u_camera_to_center_distance :\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=projectTileWithElevation(translated_a_pos+vec2(1,0),ele);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos;if (u_is_along_line || u_is_variable_anchor) {projected_pos=vec4(a_projected_pos.xy,ele,1.0);} else if (u_pitch_with_map) {projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy+u_translation,ele,1.0);} else {projected_pos=u_label_plane_matrix*projectTileWithElevation(a_projected_pos.xy+u_translation,ele);}float z=float(u_pitch_with_map)*projected_pos.z/projected_pos.w;float projectionScaling=1.0;vec4 finalPos=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0)*projectionScaling,z,1.0);if(u_pitch_with_map) {finalPos=projectTileWithElevation(finalPos.xy,finalPos.z);}gl_Position=finalPos;v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float visibility=calculate_visibility(projectedPoint);v_fade_opacity=max(0.0,min(visibility,fade_opacity[0]+fade_change));}"),symbolSDF:ge("#define SDF_PX 8.0\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1;\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nfloat EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float inner_edge=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);inner_edge=inner_edge+gamma*gamma_scale;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(inner_edge-gamma_scaled,inner_edge+gamma_scaled,dist);if (u_is_halo) {lowp float halo_edge=(6.0-halo_width/fontScale)/SDF_PX;alpha=min(smoothstep(halo_edge-gamma_scaled,halo_edge+gamma_scaled,dist),1.0-alpha);}gl_FragColor=color*(alpha*opacity*fade_opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform bool u_is_along_line;uniform bool u_is_variable_anchor;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_translation;uniform float u_pitched_scale;varying vec2 v_data0;varying vec3 v_data1;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);}\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;float ele=get_elevation(a_pos);highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec2 translated_a_pos=a_pos+u_translation;vec4 projectedPoint=projectTileWithElevation(translated_a_pos,ele);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\ncamera_to_anchor_distance/u_camera_to_center_distance :\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=projectTileWithElevation(translated_a_pos+vec2(1,0),ele);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos;if (u_is_along_line || u_is_variable_anchor) {projected_pos=vec4(a_projected_pos.xy,ele,1.0);} else if (u_pitch_with_map) {projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy+u_translation,ele,1.0);} else {projected_pos=u_label_plane_matrix*projectTileWithElevation(a_projected_pos.xy+u_translation,ele);}float z=float(u_pitch_with_map)*projected_pos.z/projected_pos.w;float projectionScaling=1.0;vec4 finalPos=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset)*projectionScaling,z,1.0);if(u_pitch_with_map) {finalPos=projectTileWithElevation(finalPos.xy,finalPos.z);}float gamma_scale=finalPos.w;gl_Position=finalPos;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float visibility=calculate_visibility(projectedPoint);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(visibility,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}"),symbolTextAndIcon:ge("#define SDF_PX 8.0\n#define SDF 1.0\n#define ICON 0.0\nuniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1;\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nfloat fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha;\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\nreturn;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity);\n#ifdef OVERDRAW_INSPECTOR\ngl_FragColor=vec4(1.0);\n#endif\n}","attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;uniform bool u_is_along_line;uniform bool u_is_variable_anchor;uniform vec2 u_translation;uniform float u_pitched_scale;varying vec4 v_data0;varying vec4 v_data1;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);}\n#pragma mapbox: define highp vec4 fill_color\n#pragma mapbox: define highp vec4 halo_color\n#pragma mapbox: define lowp float opacity\n#pragma mapbox: define lowp float halo_width\n#pragma mapbox: define lowp float halo_blur\nvoid main() {\n#pragma mapbox: initialize highp vec4 fill_color\n#pragma mapbox: initialize highp vec4 halo_color\n#pragma mapbox: initialize lowp float opacity\n#pragma mapbox: initialize lowp float halo_width\n#pragma mapbox: initialize lowp float halo_blur\nvec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;float ele=get_elevation(a_pos);highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec2 translated_a_pos=a_pos+u_translation;vec4 projectedPoint=projectTileWithElevation(translated_a_pos,ele);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ?\ncamera_to_anchor_distance/u_camera_to_center_distance :\nu_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=projectTileWithElevation(translated_a_pos+vec2(1,0),ele);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos;if (u_is_along_line || u_is_variable_anchor) {projected_pos=vec4(a_projected_pos.xy,ele,1.0);} else if (u_pitch_with_map) {projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy+u_translation,ele,1.0);} else {projected_pos=u_label_plane_matrix*projectTileWithElevation(a_projected_pos.xy+u_translation,ele);}float z=float(u_pitch_with_map)*projected_pos.z/projected_pos.w;float projectionScaling=1.0;vec4 finalPos=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale)*projectionScaling,z,1.0);if(u_pitch_with_map) {finalPos=projectTileWithElevation(finalPos.xy,finalPos.z);}float gamma_scale=finalPos.w;gl_Position=finalPos;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float visibility=calculate_visibility(projectedPoint);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(visibility,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}"),terrain:ge("uniform sampler2D u_texture;uniform vec4 u_fog_color;uniform vec4 u_horizon_color;uniform float u_fog_ground_blend;uniform float u_fog_ground_blend_opacity;uniform float u_horizon_fog_blend;varying vec2 v_texture_pos;varying float v_fog_depth;const float gamma=2.2;vec4 gammaToLinear(vec4 color) {return pow(color,vec4(gamma));}vec4 linearToGamma(vec4 color) {return pow(color,vec4(1.0/gamma));}void main() {vec4 surface_color=texture2D(u_texture,v_texture_pos);if (v_fog_depth > u_fog_ground_blend) {vec4 surface_color_linear=gammaToLinear(surface_color);float blend_color=smoothstep(0.0,1.0,max((v_fog_depth-u_horizon_fog_blend)/(1.0-u_horizon_fog_blend),0.0));vec4 fog_horizon_color_linear=mix(gammaToLinear(u_fog_color),gammaToLinear(u_horizon_color),blend_color);float factor_fog=max(v_fog_depth-u_fog_ground_blend,0.0)/(1.0-u_fog_ground_blend);gl_FragColor=linearToGamma(mix(surface_color_linear,fog_horizon_color_linear,pow(factor_fog,2.0)*u_fog_ground_blend_opacity));} else {gl_FragColor=surface_color;}}","attribute vec3 a_pos3d;uniform mat4 u_matrix;uniform mat4 u_fog_matrix;uniform float u_ele_delta;varying vec2 v_texture_pos;varying float v_fog_depth;void main() {float ele=get_elevation(a_pos3d.xy);float ele_delta=a_pos3d.z==1.0 ? u_ele_delta : 0.0;v_texture_pos=a_pos3d.xy/8192.0;gl_Position=u_matrix*vec4(a_pos3d.xy,ele-ele_delta,1.0);vec4 pos=u_fog_matrix*vec4(a_pos3d.xy,ele,1.0);v_fog_depth=pos.z/pos.w*0.5+0.5;}"),terrainDepth:ge("varying float v_depth;const highp vec4 bitSh=vec4(256.*256.*256.,256.*256.,256.,1.);const highp vec4 bitMsk=vec4(0.,vec3(1./256.0));highp vec4 pack(highp float value) {highp vec4 comp=fract(value*bitSh);comp-=comp.xxyz*bitMsk;return comp;}void main() {gl_FragColor=pack(v_depth);}","attribute vec3 a_pos3d;uniform mat4 u_matrix;uniform float u_ele_delta;varying float v_depth;void main() {float ele=get_elevation(a_pos3d.xy);float ele_delta=a_pos3d.z==1.0 ? u_ele_delta : 0.0;gl_Position=u_matrix*vec4(a_pos3d.xy,ele-ele_delta,1.0);v_depth=gl_Position.z/gl_Position.w;}"),terrainCoords:ge("precision mediump float;uniform sampler2D u_texture;uniform float u_terrain_coords_id;varying vec2 v_texture_pos;void main() {vec4 rgba=texture2D(u_texture,v_texture_pos);gl_FragColor=vec4(rgba.r,rgba.g,rgba.b,u_terrain_coords_id);}","attribute vec3 a_pos3d;uniform mat4 u_matrix;uniform float u_ele_delta;varying vec2 v_texture_pos;void main() {float ele=get_elevation(a_pos3d.xy);float ele_delta=a_pos3d.z==1.0 ? u_ele_delta : 0.0;v_texture_pos=a_pos3d.xy/8192.0;gl_Position=u_matrix*vec4(a_pos3d.xy,ele-ele_delta,1.0);}"),sky:ge("uniform vec4 u_sky_color;uniform vec4 u_horizon_color;uniform float u_horizon;uniform float u_sky_horizon_blend;void main() {float y=gl_FragCoord.y;if (y > u_horizon) {float blend=y-u_horizon;if (blend < u_sky_horizon_blend) {gl_FragColor=mix(u_sky_color,u_horizon_color,pow(1.0-blend/u_sky_horizon_blend,2.0));} else {gl_FragColor=u_sky_color;}}}","attribute vec2 a_pos;void main() {gl_Position=vec4(a_pos,1.0,1.0);}")};function ge(t,e){let r=/#pragma mapbox: ([\w]+) ([\w]+) ([\w]+) ([\w]+)/g,n=e.match(/attribute ([\w]+) ([\w]+)/g),i=t.match(/uniform ([\w]+) ([\w]+)([\s]*)([\w]*)/g),a=e.match(/uniform ([\w]+) ([\w]+)([\s]*)([\w]*)/g),o=a?a.concat(i):i,s={};return{fragmentSource:t=t.replace(r,((t,e,r,n,i)=>(s[i]=!0,"define"===e?`\n#ifndef HAS_UNIFORM_u_${i}\nvarying ${r} ${n} ${i};\n#else\nuniform ${r} ${n} u_${i};\n#endif\n`:`\n#ifdef HAS_UNIFORM_u_${i}\n ${r} ${n} ${i} = u_${i};\n#endif\n`))),vertexSource:e=e.replace(r,((t,e,r,n,i)=>{let a="float"===n?"vec2":"vec4",o=i.match(/color/)?"color":a;return s[i]?"define"===e?`\n#ifndef HAS_UNIFORM_u_${i}\nuniform lowp float u_${i}_t;\nattribute ${r} ${a} a_${i};\nvarying ${r} ${n} ${i};\n#else\nuniform ${r} ${n} u_${i};\n#endif\n`:"vec4"===o?`\n#ifndef HAS_UNIFORM_u_${i}\n ${i} = a_${i};\n#else\n ${r} ${n} ${i} = u_${i};\n#endif\n`:`\n#ifndef HAS_UNIFORM_u_${i}\n ${i} = unpack_mix_${o}(a_${i}, u_${i}_t);\n#else\n ${r} ${n} ${i} = u_${i};\n#endif\n`:"define"===e?`\n#ifndef HAS_UNIFORM_u_${i}\nuniform lowp float u_${i}_t;\nattribute ${r} ${a} a_${i};\n#else\nuniform ${r} ${n} u_${i};\n#endif\n`:"vec4"===o?`\n#ifndef HAS_UNIFORM_u_${i}\n ${r} ${n} ${i} = a_${i};\n#else\n ${r} ${n} ${i} = u_${i};\n#endif\n`:`\n#ifndef HAS_UNIFORM_u_${i}\n ${r} ${n} ${i} = unpack_mix_${o}(a_${i}, u_${i}_t);\n#else\n ${r} ${n} ${i} = u_${i};\n#endif\n`})),staticAttributes:n,staticUniforms:o}}class ye{constructor(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null}bind(t,e,r,n,i,a,o,s,l){this.context=t;let c=this.boundPaintVertexBuffers.length!==n.length;for(let t=0;!c&&t({u_matrix:t,u_texture:0,u_ele_delta:r,u_fog_matrix:n,u_fog_color:i?i.properties.get("fog-color"):e.aM.white,u_fog_ground_blend:i?i.properties.get("fog-ground-blend"):1,u_fog_ground_blend_opacity:i?i.calculateFogBlendOpacity(a):0,u_horizon_color:i?i.properties.get("horizon-color"):e.aM.white,u_horizon_fog_blend:i?i.properties.get("horizon-fog-blend"):1});function xe(t){let e=[];for(let r=0;r>16,s>>16],u_pixel_coord_lower:[65535&o,65535&s]}}let we=(t,r,n,i)=>{let a=r.style.light,o=a.properties.get("position"),s=[o.x,o.y,o.z],l=(c=new e.A(9),e.A!=Float32Array&&(c[1]=0,c[2]=0,c[3]=0,c[5]=0,c[6]=0,c[7]=0),c[0]=1,c[4]=1,c[8]=1,c);var c;"viewport"===a.properties.get("anchor")&&function(t,e){var r=Math.sin(e),n=Math.cos(e);t[0]=n,t[1]=r,t[2]=0,t[3]=-r,t[4]=n,t[5]=0,t[6]=0,t[7]=0,t[8]=1}(l,-r.transform.angle),function(t,e,r){var n=e[0],i=e[1],a=e[2];t[0]=n*r[0]+i*r[3]+a*r[6],t[1]=n*r[1]+i*r[4]+a*r[7],t[2]=n*r[2]+i*r[5]+a*r[8]}(s,s,l);let u=a.properties.get("color");return{u_matrix:t,u_lightpos:s,u_lightintensity:a.properties.get("intensity"),u_lightcolor:[u.r,u.g,u.b],u_vertical_gradient:+n,u_opacity:i}},Te=(t,r,n,i,a,o,s)=>e.e(we(t,r,n,i),be(o,r,s),{u_height_factor:-Math.pow(2,a.overscaledZ)/s.tileSize/8}),ke=t=>({u_matrix:t}),Ae=(t,r,n,i)=>e.e(ke(t),be(n,r,i)),Me=(t,e)=>({u_matrix:t,u_world:e}),Se=(t,r,n,i,a)=>e.e(Ae(t,r,n,i),{u_world:a}),Ee=(t,e,r,n)=>{let i,a,o=t.transform;if("map"===n.paint.get("circle-pitch-alignment")){let t=Bt(r,1,o.zoom);i=!0,a=[t,t]}else 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e=this.context.gl;if(!this.dynamicDraw)throw new Error("Attempted to update data while not in dynamic mode.");this.context.unbindVAO(),this.bind(),e.bufferSubData(e.ELEMENT_ARRAY_BUFFER,0,t.arrayBuffer)}destroy(){this.buffer&&(this.context.gl.deleteBuffer(this.buffer),delete this.buffer)}}let $e={Int8:"BYTE",Uint8:"UNSIGNED_BYTE",Int16:"SHORT",Uint16:"UNSIGNED_SHORT",Int32:"INT",Uint32:"UNSIGNED_INT",Float32:"FLOAT"};class Ke{constructor(t,e,r,n){this.length=e.length,this.attributes=r,this.itemSize=e.bytesPerElement,this.dynamicDraw=n,this.context=t;let i=t.gl;this.buffer=i.createBuffer(),t.bindVertexBuffer.set(this.buffer),i.bufferData(i.ARRAY_BUFFER,e.arrayBuffer,this.dynamicDraw?i.DYNAMIC_DRAW:i.STATIC_DRAW),this.dynamicDraw||delete e.arrayBuffer}bind(){this.context.bindVertexBuffer.set(this.buffer)}updateData(t){if(t.length!==this.length)throw new Error(`Length of new data is ${t.length}, which doesn't match current length of ${this.length}`);let 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t=0;tt.style.map.terrain.getElevation(l,e,r):null,r="map"===n.layout.get("text-rotation-alignment");Tt(c,l.posMatrix,t,a,N,V,v,u,r,g,l.toUnwrapped(),m.width,m.height,q,e)}let W,Z=l.posMatrix,Y=a&&A||G,X=x||Y?Gr:N,$=U,K=I&&0!==n.paint.get(a?"text-halo-width":"icon-halo-width").constantOr(1);W=I?c.iconsInText?Ge(L.kind,D,_,v,x,Y,t,Z,X,$,q,f,R,S):He(L.kind,D,_,v,x,Y,t,Z,X,$,q,a,f,!0,S):qe(L.kind,D,_,v,x,Y,t,Z,X,$,q,a,f,S);let J={program:z,buffers:h,uniformValues:W,atlasTexture:p,atlasTextureIcon:F,atlasInterpolation:k,atlasInterpolationIcon:E,isSDF:I,hasHalo:K};if(w&&c.canOverlap){T=!0;let t=h.segments.get();for(let r of t)M.push({segments:new e.a0([r]),sortKey:r.sortKey,state:J,terrainData:O})}else M.push({segments:h.segments,sortKey:0,state:J,terrainData:O})}T&&M.sort(((t,e)=>t.sortKey-e.sortKey));for(let e of M){let r=e.state;if(p.activeTexture.set(d.TEXTURE0),r.atlasTexture.bind(r.atlasInterpolation,d.CLAMP_TO_EDGE),r.atlasTextureIcon&&(p.activeTexture.set(d.TEXTURE1),r.atlasTextureIcon&&r.atlasTextureIcon.bind(r.atlasInterpolationIcon,d.CLAMP_TO_EDGE)),r.isSDF){let i=r.uniformValues;r.hasHalo&&(i.u_is_halo=1,Kr(r.buffers,e.segments,n,t,r.program,k,h,f,i,e.terrainData)),i.u_is_halo=0}Kr(r.buffers,e.segments,n,t,r.program,k,h,f,r.uniformValues,e.terrainData)}}function Kr(t,e,r,n,i,a,o,s,l,c){let u=n.context;i.draw(u,u.gl.TRIANGLES,a,o,s,qr.disabled,l,c,r.id,t.layoutVertexBuffer,t.indexBuffer,e,r.paint,n.transform.zoom,t.programConfigurations.get(r.id),t.dynamicLayoutVertexBuffer,t.opacityVertexBuffer)}function Jr(t,r,n,i){let a=t.context,o=a.gl,s=Vr.disabled,l=new Fr([o.ONE,o.ONE],e.aM.transparent,[!0,!0,!0,!0]),c=r.getBucket(n);if(!c)return;let u=i.key,h=n.heatmapFbos.get(u);h||(h=tn(a,r.tileSize,r.tileSize),n.heatmapFbos.set(u,h)),a.bindFramebuffer.set(h.framebuffer),a.viewport.set([0,0,r.tileSize,r.tileSize]),a.clear({color:e.aM.transparent});let f=c.programConfigurations.get(n.id),p=t.useProgram("heatmap",f),d=t.style.map.terrain.getTerrainData(i);p.draw(a,o.TRIANGLES,jr.disabled,s,l,qr.disabled,Pe(i.posMatrix,r,t.transform.zoom,n.paint.get("heatmap-intensity")),d,n.id,c.layoutVertexBuffer,c.indexBuffer,c.segments,n.paint,t.transform.zoom,f)}function Qr(t,e,r){let n=t.context,i=n.gl;n.setColorMode(t.colorModeForRenderPass());let a=en(n,e),o=r.key,s=e.heatmapFbos.get(o);s&&(n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,s.colorAttachment.get()),n.activeTexture.set(i.TEXTURE1),a.bind(i.LINEAR,i.CLAMP_TO_EDGE),t.useProgram("heatmapTexture").draw(n,i.TRIANGLES,jr.disabled,Vr.disabled,t.colorModeForRenderPass(),qr.disabled,ze(t,e,0,1),null,e.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments,e.paint,t.transform.zoom),s.destroy(),e.heatmapFbos.delete(o))}function tn(t,e,r){var n,i;let a=t.gl,o=a.createTexture();a.bindTexture(a.TEXTURE_2D,o),a.texParameteri(a.TEXTURE_2D,a.TEXTURE_WRAP_S,a.CLAMP_TO_EDGE),a.texParameteri(a.TEXTURE_2D,a.TEXTURE_WRAP_T,a.CLAMP_TO_EDGE),a.texParameteri(a.TEXTURE_2D,a.TEXTURE_MIN_FILTER,a.LINEAR),a.texParameteri(a.TEXTURE_2D,a.TEXTURE_MAG_FILTER,a.LINEAR);let s=null!==(n=t.HALF_FLOAT)&&void 0!==n?n:a.UNSIGNED_BYTE,l=null!==(i=t.RGBA16F)&&void 0!==i?i:a.RGBA;a.texImage2D(a.TEXTURE_2D,0,l,e,r,0,a.RGBA,s,null);let c=t.createFramebuffer(e,r,!1,!1);return c.colorAttachment.set(o),c}function en(t,e){return e.colorRampTexture||(e.colorRampTexture=new w(t,e.colorRamp,t.gl.RGBA)),e.colorRampTexture}function rn(t,e,r,n,i){if(!r||!n||!n.imageAtlas)return;let a=n.imageAtlas.patternPositions,o=a[r.to.toString()],s=a[r.from.toString()];if(!o&&s&&(o=s),!s&&o&&(s=o),!o||!s){let t=i.getPaintProperty(e);o=a[t],s=a[t]}o&&s&&t.setConstantPatternPositions(o,s)}function nn(t,e,r,n,i,a,o){let s,l,c,u,h,f=t.context.gl,p="fill-pattern",d=r.paint.get(p),m=d&&d.constantOr(1),g=r.getCrossfadeParameters();o?(l=m&&!r.getPaintProperty("fill-outline-color")?"fillOutlinePattern":"fillOutline",s=f.LINES):(l=m?"fillPattern":"fill",s=f.TRIANGLES);let y=d.constantOr(null);for(let d of n){let n=e.getTile(d);if(m&&!n.patternsLoaded())continue;let v=n.getBucket(r);if(!v)continue;let x=v.programConfigurations.get(r.id),_=t.useProgram(l,x),b=t.style.map.terrain&&t.style.map.terrain.getTerrainData(d);m&&(t.context.activeTexture.set(f.TEXTURE0),n.imageAtlasTexture.bind(f.LINEAR,f.CLAMP_TO_EDGE),x.updatePaintBuffers(g)),rn(x,p,y,n,r);let w=b?d:null,T=t.translatePosMatrix(w?w.posMatrix:d.posMatrix,n,r.paint.get("fill-translate"),r.paint.get("fill-translate-anchor"));if(o){u=v.indexBuffer2,h=v.segments2;let e=[f.drawingBufferWidth,f.drawingBufferHeight];c="fillOutlinePattern"===l&&m?Se(T,t,g,n,e):Me(T,e)}else u=v.indexBuffer,h=v.segments,c=m?Ae(T,t,g,n):ke(T);_.draw(t.context,s,i,t.stencilModeForClipping(d),a,qr.disabled,c,b,r.id,v.layoutVertexBuffer,u,h,r.paint,t.transform.zoom,x)}}function an(t,e,r,n,i,a,o){let s=t.context,l=s.gl,c="fill-extrusion-pattern",u=r.paint.get(c),h=u.constantOr(1),f=r.getCrossfadeParameters(),p=r.paint.get("fill-extrusion-opacity"),d=u.constantOr(null);for(let u of n){let n=e.getTile(u),m=n.getBucket(r);if(!m)continue;let g=t.style.map.terrain&&t.style.map.terrain.getTerrainData(u),y=m.programConfigurations.get(r.id),v=t.useProgram(h?"fillExtrusionPattern":"fillExtrusion",y);h&&(t.context.activeTexture.set(l.TEXTURE0),n.imageAtlasTexture.bind(l.LINEAR,l.CLAMP_TO_EDGE),y.updatePaintBuffers(f)),rn(y,c,d,n,r);let x=t.translatePosMatrix(u.posMatrix,n,r.paint.get("fill-extrusion-translate"),r.paint.get("fill-extrusion-translate-anchor")),_=r.paint.get("fill-extrusion-vertical-gradient"),b=h?Te(x,t,_,p,u,f,n):we(x,t,_,p);v.draw(s,s.gl.TRIANGLES,i,a,o,qr.backCCW,b,g,r.id,m.layoutVertexBuffer,m.indexBuffer,m.segments,r.paint,t.transform.zoom,y,t.style.map.terrain&&m.centroidVertexBuffer)}}function on(t,e,r,n,i,a,o){let s=t.context,l=s.gl,c=r.fbo;if(!c)return;let u=t.useProgram("hillshade"),h=t.style.map.terrain&&t.style.map.terrain.getTerrainData(e);s.activeTexture.set(l.TEXTURE0),l.bindTexture(l.TEXTURE_2D,c.colorAttachment.get()),u.draw(s,l.TRIANGLES,i,a,o,qr.disabled,((t,e,r,n)=>{let i=r.paint.get("hillshade-shadow-color"),a=r.paint.get("hillshade-highlight-color"),o=r.paint.get("hillshade-accent-color"),s=r.paint.get("hillshade-illumination-direction")*(Math.PI/180);"viewport"===r.paint.get("hillshade-illumination-anchor")&&(s-=t.transform.angle);let l=!t.options.moving;return{u_matrix:n?n.posMatrix:t.transform.calculatePosMatrix(e.tileID.toUnwrapped(),l),u_image:0,u_latrange:De(0,e.tileID),u_light:[r.paint.get("hillshade-exaggeration"),s],u_shadow:i,u_highlight:a,u_accent:o}})(t,r,n,h?e:null),h,n.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}function sn(t,r,n,i,a,o){let s=t.context,l=s.gl,c=r.dem;if(c&&c.data){let u=c.dim,h=c.stride,f=c.getPixels();if(s.activeTexture.set(l.TEXTURE1),s.pixelStoreUnpackPremultiplyAlpha.set(!1),r.demTexture=r.demTexture||t.getTileTexture(h),r.demTexture){let t=r.demTexture;t.update(f,{premultiply:!1}),t.bind(l.NEAREST,l.CLAMP_TO_EDGE)}else r.demTexture=new w(s,f,l.RGBA,{premultiply:!1}),r.demTexture.bind(l.NEAREST,l.CLAMP_TO_EDGE);s.activeTexture.set(l.TEXTURE0);let p=r.fbo;if(!p){let t=new w(s,{width:u,height:u,data:null},l.RGBA);t.bind(l.LINEAR,l.CLAMP_TO_EDGE),p=r.fbo=s.createFramebuffer(u,u,!0,!1),p.colorAttachment.set(t.texture)}s.bindFramebuffer.set(p.framebuffer),s.viewport.set([0,0,u,u]),t.useProgram("hillshadePrepare").draw(s,l.TRIANGLES,i,a,o,qr.disabled,((t,r)=>{let n=r.stride,i=e.H();return e.aP(i,0,e.X,-e.X,0,0,1),e.J(i,i,[0,-e.X,0]),{u_matrix:i,u_image:1,u_dimension:[n,n],u_zoom:t.overscaledZ,u_unpack:r.getUnpackVector()}})(r.tileID,c),null,n.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments),r.needsHillshadePrepare=!1}}function ln(t,r,n,i,o,s){let l=i.paint.get("raster-fade-duration");if(!s&&l>0){let i=a.now(),s=(i-t.timeAdded)/l,c=r?(i-r.timeAdded)/l:-1,u=n.getSource(),h=o.coveringZoomLevel({tileSize:u.tileSize,roundZoom:u.roundZoom}),f=!r||Math.abs(r.tileID.overscaledZ-h)>Math.abs(t.tileID.overscaledZ-h),p=f&&t.refreshedUponExpiration?1:e.ac(f?s:1-c,0,1);return t.refreshedUponExpiration&&s>=1&&(t.refreshedUponExpiration=!1),r?{opacity:1,mix:1-p}:{opacity:p,mix:0}}return{opacity:1,mix:0}}let cn=new e.aM(1,0,0,1),un=new e.aM(0,1,0,1),hn=new e.aM(0,0,1,1),fn=new e.aM(1,0,1,1),pn=new e.aM(0,1,1,1);function dn(t,e,r,n){gn(t,0,e+r/2,t.transform.width,r,n)}function mn(t,e,r,n){gn(t,e-r/2,0,r,t.transform.height,n)}function gn(t,e,r,n,i,a){let o=t.context,s=o.gl;s.enable(s.SCISSOR_TEST),s.scissor(e*t.pixelRatio,r*t.pixelRatio,n*t.pixelRatio,i*t.pixelRatio),o.clear({color:a}),s.disable(s.SCISSOR_TEST)}function yn(t,r,n){let i=t.context,a=i.gl,o=n.posMatrix,s=t.useProgram("debug"),l=jr.disabled,c=Vr.disabled,u=t.colorModeForRenderPass(),h="$debug",f=t.style.map.terrain&&t.style.map.terrain.getTerrainData(n);i.activeTexture.set(a.TEXTURE0);let p=r.getTileByID(n.key).latestRawTileData,d=Math.floor((p&&p.byteLength||0)/1024),m=r.getTile(n).tileSize,g=512/Math.min(m,512)*(n.overscaledZ/t.transform.zoom)*.5,y=n.canonical.toString();n.overscaledZ!==n.canonical.z&&(y+=` => ${n.overscaledZ}`),function(t,e){t.initDebugOverlayCanvas();let r=t.debugOverlayCanvas,n=t.context.gl,i=t.debugOverlayCanvas.getContext("2d");i.clearRect(0,0,r.width,r.height),i.shadowColor="white",i.shadowBlur=2,i.lineWidth=1.5,i.strokeStyle="white",i.textBaseline="top",i.font="bold 36px Open Sans, sans-serif",i.fillText(e,5,5),i.strokeText(e,5,5),t.debugOverlayTexture.update(r),t.debugOverlayTexture.bind(n.LINEAR,n.CLAMP_TO_EDGE)}(t,`${y} ${d}kB`),s.draw(i,a.TRIANGLES,l,c,Fr.alphaBlended,qr.disabled,Ie(o,e.aM.transparent,g),null,h,t.debugBuffer,t.quadTriangleIndexBuffer,t.debugSegments),s.draw(i,a.LINE_STRIP,l,c,u,qr.disabled,Ie(o,e.aM.red),f,h,t.debugBuffer,t.tileBorderIndexBuffer,t.debugSegments)}function vn(t,e,r){let n=t.context,i=n.gl,a=t.colorModeForRenderPass(),o=new jr(i.LEQUAL,jr.ReadWrite,t.depthRangeFor3D),s=t.useProgram("terrain"),l=e.getTerrainMesh();n.bindFramebuffer.set(null),n.viewport.set([0,0,t.width,t.height]);for(let c of r){let r=t.renderToTexture.getTexture(c),u=e.getTerrainData(c.tileID);n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,r.texture);let h=t.transform.calculatePosMatrix(c.tileID.toUnwrapped()),f=e.getMeshFrameDelta(t.transform.zoom),p=t.transform.calculateFogMatrix(c.tileID.toUnwrapped()),d=ve(h,f,p,t.style.sky,t.transform.pitch);s.draw(n,i.TRIANGLES,o,Vr.disabled,a,qr.backCCW,d,u,"terrain",l.vertexBuffer,l.indexBuffer,l.segments)}}class xn{constructor(t,e,r){this.vertexBuffer=t,this.indexBuffer=e,this.segments=r}destroy(){this.vertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.vertexBuffer=null,this.indexBuffer=null,this.segments=null}}class _n{constructor(t,r){this.context=new Br(t),this.transform=r,this._tileTextures={},this.terrainFacilitator={dirty:!0,matrix:e.an(new Float64Array(16)),renderTime:0},this.setup(),this.numSublayers=ft.maxUnderzooming+ft.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new ue}resize(t,e,r){if(this.width=Math.floor(t*r),this.height=Math.floor(e*r),this.pixelRatio=r,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(let t of this.style._order)this.style._layers[t].resize()}setup(){let t=this.context,r=new e.aX;r.emplaceBack(0,0),r.emplaceBack(e.X,0),r.emplaceBack(0,e.X),r.emplaceBack(e.X,e.X),this.tileExtentBuffer=t.createVertexBuffer(r,de.members),this.tileExtentSegments=e.a0.simpleSegment(0,0,4,2);let n=new e.aX;n.emplaceBack(0,0),n.emplaceBack(e.X,0),n.emplaceBack(0,e.X),n.emplaceBack(e.X,e.X),this.debugBuffer=t.createVertexBuffer(n,de.members),this.debugSegments=e.a0.simpleSegment(0,0,4,5);let i=new e.$;i.emplaceBack(0,0,0,0),i.emplaceBack(e.X,0,e.X,0),i.emplaceBack(0,e.X,0,e.X),i.emplaceBack(e.X,e.X,e.X,e.X),this.rasterBoundsBuffer=t.createVertexBuffer(i,Q.members),this.rasterBoundsSegments=e.a0.simpleSegment(0,0,4,2);let a=new e.aX;a.emplaceBack(0,0),a.emplaceBack(1,0),a.emplaceBack(0,1),a.emplaceBack(1,1),this.viewportBuffer=t.createVertexBuffer(a,de.members),this.viewportSegments=e.a0.simpleSegment(0,0,4,2);let o=new e.aZ;o.emplaceBack(0),o.emplaceBack(1),o.emplaceBack(3),o.emplaceBack(2),o.emplaceBack(0),this.tileBorderIndexBuffer=t.createIndexBuffer(o);let s=new e.aY;s.emplaceBack(0,1,2),s.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=t.createIndexBuffer(s);let l=this.context.gl;this.stencilClearMode=new Vr({func:l.ALWAYS,mask:0},0,255,l.ZERO,l.ZERO,l.ZERO)}clearStencil(){let t=this.context,r=t.gl;this.nextStencilID=1,this.currentStencilSource=void 0;let n=e.H();e.aP(n,0,this.width,this.height,0,0,1),e.K(n,n,[r.drawingBufferWidth,r.drawingBufferHeight,0]),this.useProgram("clippingMask").draw(t,r.TRIANGLES,jr.disabled,this.stencilClearMode,Fr.disabled,qr.disabled,Le(n),null,"$clipping",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)}_renderTileClippingMasks(t,e){if(this.currentStencilSource===t.source||!t.isTileClipped()||!e||!e.length)return;this.currentStencilSource=t.source;let r=this.context,n=r.gl;this.nextStencilID+e.length>256&&this.clearStencil(),r.setColorMode(Fr.disabled),r.setDepthMode(jr.disabled);let i=this.useProgram("clippingMask");this._tileClippingMaskIDs={};for(let t of e){let e=this._tileClippingMaskIDs[t.key]=this.nextStencilID++,a=this.style.map.terrain&&this.style.map.terrain.getTerrainData(t);i.draw(r,n.TRIANGLES,jr.disabled,new Vr({func:n.ALWAYS,mask:0},e,255,n.KEEP,n.KEEP,n.REPLACE),Fr.disabled,qr.disabled,Le(t.posMatrix),a,"$clipping",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}stencilModeFor3D(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();let t=this.nextStencilID++,e=this.context.gl;return new Vr({func:e.NOTEQUAL,mask:255},t,255,e.KEEP,e.KEEP,e.REPLACE)}stencilModeForClipping(t){let e=this.context.gl;return new Vr({func:e.EQUAL,mask:255},this._tileClippingMaskIDs[t.key],0,e.KEEP,e.KEEP,e.REPLACE)}stencilConfigForOverlap(t){let e=this.context.gl,r=t.sort(((t,e)=>e.overscaledZ-t.overscaledZ)),n=r[r.length-1].overscaledZ,i=r[0].overscaledZ-n+1;if(i>1){this.currentStencilSource=void 0,this.nextStencilID+i>256&&this.clearStencil();let t={};for(let r=0;r=0;this.currentLayer--){let t=this.style._layers[n[this.currentLayer]],e=i[t.source],r=o[t.source];this._renderTileClippingMasks(t,r),this.renderLayer(this,e,t,r)}for(this.renderPass="translucent",this.currentLayer=0;this.currentLayerr.source&&!r.isHidden(e)?[t.sourceCaches[r.source]]:[])),i=n.filter((t=>"vector"===t.getSource().type)),a=n.filter((t=>"vector"!==t.getSource().type)),o=t=>{(!r||r.getSource().maxzoomo(t))),r||a.forEach((t=>o(t))),r}(this.style,this.transform.zoom);t&&function(t,e,r){for(let n=0;n0),i&&(e.b0(r,n),this.terrainFacilitator.renderTime=Date.now(),this.terrainFacilitator.dirty=!1,function(t,r){let n=t.context,i=n.gl,a=Fr.unblended,o=new jr(i.LEQUAL,jr.ReadWrite,[0,1]),s=r.getTerrainMesh(),l=r.sourceCache.getRenderableTiles(),c=t.useProgram("terrainDepth");n.bindFramebuffer.set(r.getFramebuffer("depth").framebuffer),n.viewport.set([0,0,t.width/devicePixelRatio,t.height/devicePixelRatio]),n.clear({color:e.aM.transparent,depth:1});for(let e of l){let l=r.getTerrainData(e.tileID),u={u_matrix:t.transform.calculatePosMatrix(e.tileID.toUnwrapped()),u_ele_delta:r.getMeshFrameDelta(t.transform.zoom)};c.draw(n,i.TRIANGLES,o,Vr.disabled,a,qr.backCCW,u,l,"terrain",s.vertexBuffer,s.indexBuffer,s.segments)}n.bindFramebuffer.set(null),n.viewport.set([0,0,t.width,t.height])}(this,this.style.map.terrain),function(t,r){let n=t.context,i=n.gl,a=Fr.unblended,o=new jr(i.LEQUAL,jr.ReadWrite,[0,1]),s=r.getTerrainMesh(),l=r.getCoordsTexture(),c=r.sourceCache.getRenderableTiles(),u=t.useProgram("terrainCoords");n.bindFramebuffer.set(r.getFramebuffer("coords").framebuffer),n.viewport.set([0,0,t.width/devicePixelRatio,t.height/devicePixelRatio]),n.clear({color:e.aM.transparent,depth:1}),r.coordsIndex=[];for(let e of c){let c=r.getTerrainData(e.tileID);n.activeTexture.set(i.TEXTURE0),i.bindTexture(i.TEXTURE_2D,l.texture);let h={u_matrix:t.transform.calculatePosMatrix(e.tileID.toUnwrapped()),u_terrain_coords_id:(255-r.coordsIndex.length)/255,u_texture:0,u_ele_delta:r.getMeshFrameDelta(t.transform.zoom)};u.draw(n,i.TRIANGLES,o,Vr.disabled,a,qr.backCCW,h,c,"terrain",s.vertexBuffer,s.indexBuffer,s.segments),r.coordsIndex.push(e.tileID.key)}n.bindFramebuffer.set(null),n.viewport.set([0,0,t.width,t.height])}(this,this.style.map.terrain))}renderLayer(t,r,n,i){if(!n.isHidden(this.transform.zoom)&&("background"===n.type||"custom"===n.type||(i||[]).length))switch(this.id=n.id,n.type){case"symbol":!function(t,r,n,i,a){if("translucent"!==t.renderPass)return;let o=Vr.disabled,s=t.colorModeForRenderPass();(n._unevaluatedLayout.hasValue("text-variable-anchor")||n._unevaluatedLayout.hasValue("text-variable-anchor-offset"))&&function(t,r,n,i,a,o,s,l,c){let u=r.transform,h=ne(),f="map"===a,p="map"===o;for(let a of t){let t=i.getTile(a),o=t.getBucket(n);if(!o||!o.text||!o.text.segments.get().length)continue;let d=e.ag(o.textSizeData,u.zoom),m=Bt(t,1,r.transform.zoom),g=vt(a.posMatrix,p,f,r.transform,m),y="none"!==n.layout.get("icon-text-fit")&&o.hasIconData();if(d){let e=Math.pow(2,u.zoom-t.tileID.overscaledZ),n=r.style.map.terrain?(t,e)=>r.style.map.terrain.getElevation(a,t,e):null,i=h.translatePosition(u,t,s,l);Yr(o,f,p,c,u,g,a.posMatrix,e,d,y,h,i,a.toUnwrapped(),n)}}}(i,t,n,r,n.layout.get("text-rotation-alignment"),n.layout.get("text-pitch-alignment"),n.paint.get("text-translate"),n.paint.get("text-translate-anchor"),a),0!==n.paint.get("icon-opacity").constantOr(1)&&$r(t,r,n,i,!1,n.paint.get("icon-translate"),n.paint.get("icon-translate-anchor"),n.layout.get("icon-rotation-alignment"),n.layout.get("icon-pitch-alignment"),n.layout.get("icon-keep-upright"),o,s),0!==n.paint.get("text-opacity").constantOr(1)&&$r(t,r,n,i,!0,n.paint.get("text-translate"),n.paint.get("text-translate-anchor"),n.layout.get("text-rotation-alignment"),n.layout.get("text-pitch-alignment"),n.layout.get("text-keep-upright"),o,s),r.map.showCollisionBoxes&&(Hr(t,r,n,i,!0),Hr(t,r,n,i,!1))}(t,r,n,i,this.style.placement.variableOffsets);break;case"circle":!function(t,r,n,i){if("translucent"!==t.renderPass)return;let a=n.paint.get("circle-opacity"),o=n.paint.get("circle-stroke-width"),s=n.paint.get("circle-stroke-opacity"),l=!n.layout.get("circle-sort-key").isConstant();if(0===a.constantOr(1)&&(0===o.constantOr(1)||0===s.constantOr(1)))return;let c=t.context,u=c.gl,h=t.depthModeForSublayer(0,jr.ReadOnly),f=Vr.disabled,p=t.colorModeForRenderPass(),d=[];for(let a=0;at.sortKey-e.sortKey));for(let e of d){let{programConfiguration:r,program:i,layoutVertexBuffer:a,indexBuffer:o,uniformValues:s,terrainData:l}=e.state;i.draw(c,u.TRIANGLES,h,f,p,qr.disabled,s,l,n.id,a,o,e.segments,n.paint,t.transform.zoom,r)}}(t,r,n,i);break;case"heatmap":!function(t,r,n,i){if(0===n.paint.get("heatmap-opacity"))return;let a=t.context;if(t.style.map.terrain){for(let e of i){let i=r.getTile(e);r.hasRenderableParent(e)||("offscreen"===t.renderPass?Jr(t,i,n,e):"translucent"===t.renderPass&&Qr(t,n,e))}a.viewport.set([0,0,t.width,t.height])}else"offscreen"===t.renderPass?function(t,r,n,i){let a=t.context,o=a.gl,s=Vr.disabled,l=new Fr([o.ONE,o.ONE],e.aM.transparent,[!0,!0,!0,!0]);(function(t,r,n){let i=t.gl;t.activeTexture.set(i.TEXTURE1),t.viewport.set([0,0,r.width/4,r.height/4]);let a=n.heatmapFbos.get(e.aU);a?(i.bindTexture(i.TEXTURE_2D,a.colorAttachment.get()),t.bindFramebuffer.set(a.framebuffer)):(a=tn(t,r.width/4,r.height/4),n.heatmapFbos.set(e.aU,a))})(a,t,n),a.clear({color:e.aM.transparent});for(let e=0;e20&&a.texParameterf(a.TEXTURE_2D,i.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,i.extTextureFilterAnisotropicMax);let _=t.style.map.terrain&&t.style.map.terrain.getTerrainData(n),b=_?n:null,w=b?b.posMatrix:t.transform.calculatePosMatrix(n.toUnwrapped(),f),T=Ue(w,m||[0,0],d||1,v,r);o instanceof tt?s.draw(i,a.TRIANGLES,u,Vr.disabled,l,qr.disabled,T,_,r.id,o.boundsBuffer,t.quadTriangleIndexBuffer,o.boundsSegments):s.draw(i,a.TRIANGLES,u,c[n.overscaledZ],l,qr.disabled,T,_,r.id,t.rasterBoundsBuffer,t.quadTriangleIndexBuffer,t.rasterBoundsSegments)}}(t,r,n,i);break;case"background":!function(t,e,r,n){let i=r.paint.get("background-color"),a=r.paint.get("background-opacity");if(0===a)return;let o=t.context,s=o.gl,l=t.transform,c=l.tileSize,u=r.paint.get("background-pattern");if(t.isPatternMissing(u))return;let h=!u&&1===i.a&&1===a&&t.opaquePassEnabledForLayer()?"opaque":"translucent";if(t.renderPass!==h)return;let f=Vr.disabled,p=t.depthModeForSublayer(0,"opaque"===h?jr.ReadWrite:jr.ReadOnly),d=t.colorModeForRenderPass(),m=t.useProgram(u?"backgroundPattern":"background"),g=n||l.coveringTiles({tileSize:c,terrain:t.style.map.terrain});u&&(o.activeTexture.set(s.TEXTURE0),t.imageManager.bind(t.context));let y=r.getCrossfadeParameters();for(let e of g){let l=n?e.posMatrix:t.transform.calculatePosMatrix(e.toUnwrapped()),h=u?Ze(l,a,t,u,{tileID:e,tileSize:c},y):We(l,a,i),g=t.style.map.terrain&&t.style.map.terrain.getTerrainData(e);m.draw(o,s.TRIANGLES,p,f,d,qr.disabled,h,g,r.id,t.tileExtentBuffer,t.quadTriangleIndexBuffer,t.tileExtentSegments)}}(t,0,n,i);break;case"custom":!function(t,e,r){let n=t.context,i=r.implementation;if("offscreen"===t.renderPass){let e=i.prerender;e&&(t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),e.call(i,n.gl,t.transform.customLayerMatrix()),n.setDirty(),t.setBaseState())}else if("translucent"===t.renderPass){t.setCustomLayerDefaults(),n.setColorMode(t.colorModeForRenderPass()),n.setStencilMode(Vr.disabled);let e="3d"===i.renderingMode?new jr(t.context.gl.LEQUAL,jr.ReadWrite,t.depthRangeFor3D):t.depthModeForSublayer(0,jr.ReadOnly);n.setDepthMode(e),i.render(n.gl,t.transform.customLayerMatrix(),{farZ:t.transform.farZ,nearZ:t.transform.nearZ,fov:t.transform._fov,modelViewProjectionMatrix:t.transform.modelViewProjectionMatrix,projectionMatrix:t.transform.projectionMatrix}),n.setDirty(),t.setBaseState(),n.bindFramebuffer.set(null)}}(t,0,n)}}translatePosMatrix(t,r,n,i,a){if(!n[0]&&!n[1])return t;let o=a?"map"===i?this.transform.angle:0:"viewport"===i?-this.transform.angle:0;if(o){let t=Math.sin(o),e=Math.cos(o);n=[n[0]*e-n[1]*t,n[0]*t+n[1]*e]}let s=[a?n[0]:Bt(r,n[0],this.transform.zoom),a?n[1]:Bt(r,n[1],this.transform.zoom),0],l=new Float32Array(16);return e.J(l,t,s),l}saveTileTexture(t){let e=this._tileTextures[t.size[0]];e?e.push(t):this._tileTextures[t.size[0]]=[t]}getTileTexture(t){let e=this._tileTextures[t];return e&&e.length>0?e.pop():null}isPatternMissing(t){if(!t)return!1;if(!t.from||!t.to)return!0;let e=this.imageManager.getPattern(t.from.toString()),r=this.imageManager.getPattern(t.to.toString());return!e||!r}useProgram(t,e){this.cache=this.cache||{};let r=t+(e?e.cacheKey:"")+(this._showOverdrawInspector?"/overdraw":"")+(this.style.map.terrain?"/terrain":"");return this.cache[r]||(this.cache[r]=new _e(this.context,me[t],e,Ye[t],this._showOverdrawInspector,this.style.map.terrain)),this.cache[r]}setCustomLayerDefaults(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()}setBaseState(){let t=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(t.FUNC_ADD)}initDebugOverlayCanvas(){null==this.debugOverlayCanvas&&(this.debugOverlayCanvas=document.createElement("canvas"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512,this.debugOverlayTexture=new w(this.context,this.debugOverlayCanvas,this.context.gl.RGBA))}destroy(){this.debugOverlayTexture&&this.debugOverlayTexture.destroy()}overLimit(){let{drawingBufferWidth:t,drawingBufferHeight:e}=this.context.gl;return this.width!==t||this.height!==e}}class bn{constructor(t,e){this.points=t,this.planes=e}static fromInvProjectionMatrix(t,r,n){let i=Math.pow(2,n),a=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map((n=>{let a=1/(n=e.af([],n,t))[3]/r*i;return e.b1(n,n,[a,a,1/n[3],a])})),o=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map((t=>{let e=function(t,e){var r=e[0],n=e[1],i=e[2],a=r*r+n*n+i*i;return a>0&&(a=1/Math.sqrt(a)),t[0]=e[0]*a,t[1]=e[1]*a,t[2]=e[2]*a,t}([],(n=[],i=y([],a[t[0]],a[t[1]]),o=y([],a[t[2]],a[t[1]]),s=i[0],l=i[1],c=i[2],u=o[0],h=o[1],f=o[2],n[0]=l*f-c*h,n[1]=c*u-s*f,n[2]=s*h-l*u,n)),r=-((p=e)[0]*(d=a[t[1]])[0]+p[1]*d[1]+p[2]*d[2]);var n,i,o,s,l,c,u,h,f,p,d;return e.concat(r)}));return new bn(a,o)}}class wn{constructor(t,e){var r,n,i;this.min=t,this.max=e,this.center=function(t,e){return t[0]=.5*e[0],t[1]=.5*e[1],t[2]=.5*e[2],t}([],(r=[],n=this.min,i=this.max,r[0]=n[0]+i[0],r[1]=n[1]+i[1],r[2]=n[2]+i[2],r))}quadrant(t){let e=[t%2==0,t<2],r=m(this.min),n=m(this.max);for(let t=0;t=0&&o++;if(0===o)return 0;o!==r.length&&(n=!1)}if(n)return 2;for(let e=0;e<3;e++){let r=Number.MAX_VALUE,n=-Number.MAX_VALUE;for(let i=0;ithis.max[e]-this.min[e])return 0}return 1}}class Tn{constructor(t=0,e=0,r=0,n=0){if(isNaN(t)||t<0||isNaN(e)||e<0||isNaN(r)||r<0||isNaN(n)||n<0)throw new Error("Invalid value for edge-insets, top, bottom, left and right must all be numbers");this.top=t,this.bottom=e,this.left=r,this.right=n}interpolate(t,r,n){return null!=r.top&&null!=t.top&&(this.top=e.y.number(t.top,r.top,n)),null!=r.bottom&&null!=t.bottom&&(this.bottom=e.y.number(t.bottom,r.bottom,n)),null!=r.left&&null!=t.left&&(this.left=e.y.number(t.left,r.left,n)),null!=r.right&&null!=t.right&&(this.right=e.y.number(t.right,r.right,n)),this}getCenter(t,r){let n=e.ac((this.left+t-this.right)/2,0,t),i=e.ac((this.top+r-this.bottom)/2,0,r);return new e.P(n,i)}equals(t){return this.top===t.top&&this.bottom===t.bottom&&this.left===t.left&&this.right===t.right}clone(){return new Tn(this.top,this.bottom,this.left,this.right)}toJSON(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}}}let kn=85.051129;class An{constructor(t,r,n,i,a){this.tileSize=512,this._renderWorldCopies=void 0===a||!!a,this._minZoom=t||0,this._maxZoom=r||22,this._minPitch=n??0,this._maxPitch=i??60,this.setMaxBounds(),this.width=0,this.height=0,this._center=new e.N(0,0),this._elevation=0,this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new Tn,this._posMatrixCache={},this._alignedPosMatrixCache={},this._fogMatrixCache={},this.minElevationForCurrentTile=0}clone(){let t=new An(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return t.apply(this),t}apply(t){this.tileSize=t.tileSize,this.latRange=t.latRange,this.lngRange=t.lngRange,this.width=t.width,this.height=t.height,this._center=t._center,this._elevation=t._elevation,this.minElevationForCurrentTile=t.minElevationForCurrentTile,this.zoom=t.zoom,this.angle=t.angle,this._fov=t._fov,this._pitch=t._pitch,this._unmodified=t._unmodified,this._edgeInsets=t._edgeInsets.clone(),this._calcMatrices()}get minZoom(){return this._minZoom}set minZoom(t){this._minZoom!==t&&(this._minZoom=t,this.zoom=Math.max(this.zoom,t))}get maxZoom(){return this._maxZoom}set maxZoom(t){this._maxZoom!==t&&(this._maxZoom=t,this.zoom=Math.min(this.zoom,t))}get minPitch(){return this._minPitch}set minPitch(t){this._minPitch!==t&&(this._minPitch=t,this.pitch=Math.max(this.pitch,t))}get maxPitch(){return this._maxPitch}set maxPitch(t){this._maxPitch!==t&&(this._maxPitch=t,this.pitch=Math.min(this.pitch,t))}get renderWorldCopies(){return this._renderWorldCopies}set renderWorldCopies(t){void 0===t?t=!0:null===t&&(t=!1),this._renderWorldCopies=t}get worldSize(){return this.tileSize*this.scale}get centerOffset(){return this.centerPoint._sub(this.size._div(2))}get size(){return new e.P(this.width,this.height)}get bearing(){return-this.angle/Math.PI*180}set bearing(t){let r=-e.b3(t,-180,180)*Math.PI/180;var n;this.angle!==r&&(this._unmodified=!1,this.angle=r,this._calcMatrices(),this.rotationMatrix=(n=new e.A(4),e.A!=Float32Array&&(n[1]=0,n[2]=0),n[0]=1,n[3]=1,n),function(t,e,r){var n=e[0],i=e[1],a=e[2],o=e[3],s=Math.sin(r),l=Math.cos(r);t[0]=n*l+a*s,t[1]=i*l+o*s,t[2]=n*-s+a*l,t[3]=i*-s+o*l}(this.rotationMatrix,this.rotationMatrix,this.angle))}get pitch(){return this._pitch/Math.PI*180}set pitch(t){let r=e.ac(t,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==r&&(this._unmodified=!1,this._pitch=r,this._calcMatrices())}get fov(){return this._fov/Math.PI*180}set fov(t){t=Math.max(.01,Math.min(60,t)),this._fov!==t&&(this._unmodified=!1,this._fov=t/180*Math.PI,this._calcMatrices())}get zoom(){return this._zoom}set zoom(t){let e=Math.min(Math.max(t,this.minZoom),this.maxZoom);this._zoom!==e&&(this._unmodified=!1,this._zoom=e,this.tileZoom=Math.max(0,Math.floor(e)),this.scale=this.zoomScale(e),this._constrain(),this._calcMatrices())}get center(){return this._center}set center(t){t.lat===this._center.lat&&t.lng===this._center.lng||(this._unmodified=!1,this._center=t,this._constrain(),this._calcMatrices())}get elevation(){return this._elevation}set elevation(t){t!==this._elevation&&(this._elevation=t,this._constrain(),this._calcMatrices())}get padding(){return this._edgeInsets.toJSON()}set padding(t){this._edgeInsets.equals(t)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,t,1),this._calcMatrices())}get centerPoint(){return this._edgeInsets.getCenter(this.width,this.height)}isPaddingEqual(t){return this._edgeInsets.equals(t)}interpolatePadding(t,e,r){this._unmodified=!1,this._edgeInsets.interpolate(t,e,r),this._constrain(),this._calcMatrices()}coveringZoomLevel(t){let e=(t.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/t.tileSize));return Math.max(0,e)}getVisibleUnwrappedCoordinates(t){let r=[new e.b4(0,t)];if(this._renderWorldCopies){let n=this.pointCoordinate(new e.P(0,0)),i=this.pointCoordinate(new e.P(this.width,0)),a=this.pointCoordinate(new e.P(this.width,this.height)),o=this.pointCoordinate(new e.P(0,this.height)),s=Math.floor(Math.min(n.x,i.x,a.x,o.x)),l=Math.floor(Math.max(n.x,i.x,a.x,o.x)),c=1;for(let n=s-c;n<=l+c;n++)0!==n&&r.push(new e.b4(n,t))}return r}coveringTiles(t){var r,n;let i=this.coveringZoomLevel(t),a=i;if(void 0!==t.minzoom&&it.maxzoom&&(i=t.maxzoom);let o=this.pointCoordinate(this.getCameraPoint()),s=e.Z.fromLngLat(this.center),l=Math.pow(2,i),c=[l*o.x,l*o.y,0],u=[l*s.x,l*s.y,0],h=bn.fromInvProjectionMatrix(this.invModelViewProjectionMatrix,this.worldSize,i),f=t.minzoom||0;!t.terrain&&this.pitch<=60&&this._edgeInsets.top<.1&&(f=i);let p=t.terrain?2/Math.min(this.tileSize,t.tileSize)*this.tileSize:3,d=t=>({aabb:new wn([t*l,0,0],[(t+1)*l,l,0]),zoom:0,x:0,y:0,wrap:t,fullyVisible:!1}),m=[],g=[],y=i,v=t.reparseOverscaled?a:i;if(this._renderWorldCopies)for(let t=1;t<=3;t++)m.push(d(-t)),m.push(d(t));for(m.push(d(0));m.length>0;){let i=m.pop(),a=i.x,o=i.y,s=i.fullyVisible;if(!s){let t=i.aabb.intersects(h);if(0===t)continue;s=2===t}let l=t.terrain?c:u,d=i.aabb.distanceX(l),_=i.aabb.distanceY(l),b=Math.max(Math.abs(d),Math.abs(_));if(i.zoom===y||b>p+(1<=f){let t=y-i.zoom,r=c[0]-.5-(a<>1),h=i.zoom+1,f=i.aabb.quadrant(l);if(t.terrain){let a=new e.S(h,i.wrap,h,c,u),o=t.terrain.getMinMaxElevation(a),s=null!==(r=o.minElevation)&&void 0!==r?r:this.elevation,l=null!==(n=o.maxElevation)&&void 0!==n?n:this.elevation;f=new wn([f.min[0],f.min[1],s],[f.max[0],f.max[1],l])}m.push({aabb:f,zoom:h,x:c,y:u,wrap:i.wrap,fullyVisible:s})}}return g.sort(((t,e)=>t.distanceSq-e.distanceSq)).map((t=>t.tileID))}resize(t,e){this.width=t,this.height=e,this.pixelsToGLUnits=[2/t,-2/e],this._constrain(),this._calcMatrices()}get unmodified(){return this._unmodified}zoomScale(t){return Math.pow(2,t)}scaleZoom(t){return Math.log(t)/Math.LN2}project(t){let r=e.ac(t.lat,-85.051129,kn);return new e.P(e.O(t.lng)*this.worldSize,e.Q(r)*this.worldSize)}unproject(t){return new e.Z(t.x/this.worldSize,t.y/this.worldSize).toLngLat()}get point(){return this.project(this.center)}getCameraPosition(){return{lngLat:this.pointLocation(this.getCameraPoint()),altitude:Math.cos(this._pitch)*this.cameraToCenterDistance/this._pixelPerMeter+this.elevation}}recalculateZoom(t){let r=this.elevation,n=Math.cos(this._pitch)*this.cameraToCenterDistance/this._pixelPerMeter,i=this.pointLocation(this.centerPoint,t),a=t.getElevationForLngLatZoom(i,this.tileZoom);if(!(this.elevation-a))return;let o=n+r-a,s=Math.cos(this._pitch)*this.cameraToCenterDistance/o/e.b5(1,i.lat),l=this.scaleZoom(s/this.tileSize);this._elevation=a,this._center=i,this.zoom=l}setLocationAtPoint(t,r){let n=this.pointCoordinate(r),i=this.pointCoordinate(this.centerPoint),a=this.locationCoordinate(t),o=new e.Z(a.x-(n.x-i.x),a.y-(n.y-i.y));this.center=this.coordinateLocation(o),this._renderWorldCopies&&(this.center=this.center.wrap())}locationPoint(t,e){return e?this.coordinatePoint(this.locationCoordinate(t),e.getElevationForLngLatZoom(t,this.tileZoom),this.pixelMatrix3D):this.coordinatePoint(this.locationCoordinate(t))}pointLocation(t,e){return this.coordinateLocation(this.pointCoordinate(t,e))}locationCoordinate(t){return e.Z.fromLngLat(t)}coordinateLocation(t){return t&&t.toLngLat()}pointCoordinate(t,r){if(r){let e=r.pointCoordinate(t);if(null!=e)return e}let n=[t.x,t.y,0,1],i=[t.x,t.y,1,1];e.af(n,n,this.pixelMatrixInverse),e.af(i,i,this.pixelMatrixInverse);let a=n[3],o=i[3],s=n[1]/a,l=i[1]/o,c=n[2]/a,u=i[2]/o,h=c===u?0:(0-c)/(u-c);return new e.Z(e.y.number(n[0]/a,i[0]/o,h)/this.worldSize,e.y.number(s,l,h)/this.worldSize)}coordinatePoint(t,r=0,n=this.pixelMatrix){let i=[t.x*this.worldSize,t.y*this.worldSize,r,1];return e.af(i,i,n),new e.P(i[0]/i[3],i[1]/i[3])}getBounds(){let t=Math.max(0,this.height/2-this.getHorizon());return(new Z).extend(this.pointLocation(new e.P(0,t))).extend(this.pointLocation(new e.P(this.width,t))).extend(this.pointLocation(new e.P(this.width,this.height))).extend(this.pointLocation(new e.P(0,this.height)))}getMaxBounds(){return this.latRange&&2===this.latRange.length&&this.lngRange&&2===this.lngRange.length?new Z([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null}getHorizon(){return Math.tan(Math.PI/2-this._pitch)*this.cameraToCenterDistance*.85}setMaxBounds(t){t?(this.lngRange=[t.getWest(),t.getEast()],this.latRange=[t.getSouth(),t.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-85.051129,kn])}calculateTileMatrix(t){let r=t.canonical,n=this.worldSize/this.zoomScale(r.z),i=r.x+Math.pow(2,r.z)*t.wrap,a=e.an(new Float64Array(16));return e.J(a,a,[i*n,r.y*n,0]),e.K(a,a,[n/e.X,n/e.X,1]),a}calculatePosMatrix(t,r=!1){let n=t.key,i=r?this._alignedPosMatrixCache:this._posMatrixCache;if(i[n])return i[n];let a=this.calculateTileMatrix(t);return e.L(a,r?this.alignedModelViewProjectionMatrix:this.modelViewProjectionMatrix,a),i[n]=new Float32Array(a),i[n]}calculateFogMatrix(t){let r=t.key,n=this._fogMatrixCache;if(n[r])return n[r];let i=this.calculateTileMatrix(t);return e.L(i,this.fogMatrix,i),n[r]=new Float32Array(i),n[r]}customLayerMatrix(){return this.mercatorMatrix.slice()}getConstrained(t,r){r=e.ac(+r,this.minZoom,this.maxZoom);let n={center:new e.N(t.lng,t.lat),zoom:r},i=this.lngRange;if(!this._renderWorldCopies&&null===i){let t=179.9999999999;i=[-t,t]}let a=this.tileSize*this.zoomScale(n.zoom),o=0,s=a,l=0,c=a,u=0,h=0,{x:f,y:p}=this.size;if(this.latRange){let t=this.latRange;o=e.Q(t[1])*a,s=e.Q(t[0])*a,s-os&&(m=s-t)}if(i){let t=(l+c)/2,r=g;this._renderWorldCopies&&(r=e.b3(g,t-a/2,t+a/2));let n=f/2;r-nc&&(d=c-n)}if(void 0!==d||void 0!==m){let t=new e.P(d??g,m??y);n.center=this.unproject.call({worldSize:a},t).wrap()}return n}_constrain(){if(!this.center||!this.width||!this.height||this._constraining)return;this._constraining=!0;let t=this._unmodified,{center:e,zoom:r}=this.getConstrained(this.center,this.zoom);this.center=e,this.zoom=r,this._unmodified=t,this._constraining=!1}_calcMatrices(){if(!this.height)return;let t=this.centerOffset,r=this.point.x,n=this.point.y;this.cameraToCenterDistance=.5/Math.tan(this._fov/2)*this.height,this._pixelPerMeter=e.b5(1,this.center.lat)*this.worldSize;let i=e.an(new Float64Array(16));e.K(i,i,[this.width/2,-this.height/2,1]),e.J(i,i,[1,-1,0]),this.labelPlaneMatrix=i,i=e.an(new Float64Array(16)),e.K(i,i,[1,-1,1]),e.J(i,i,[-1,-1,0]),e.K(i,i,[2/this.width,2/this.height,1]),this.glCoordMatrix=i;let a=this.cameraToCenterDistance+this._elevation*this._pixelPerMeter/Math.cos(this._pitch),o=Math.min(this.elevation,this.minElevationForCurrentTile),s=a-o*this._pixelPerMeter/Math.cos(this._pitch),l=o<0?s:a,c=Math.PI/2+this._pitch,u=this._fov*(.5+t.y/this.height),h=Math.sin(u)*l/Math.sin(e.ac(Math.PI-c-u,.01,Math.PI-.01)),f=this.getHorizon(),p=2*Math.atan(f/this.cameraToCenterDistance)*(.5+t.y/(2*f)),d=Math.sin(p)*l/Math.sin(e.ac(Math.PI-c-p,.01,Math.PI-.01)),m=Math.min(h,d);this.farZ=1.01*(Math.cos(Math.PI/2-this._pitch)*m+l),this.nearZ=this.height/50,i=new Float64Array(16),e.b6(i,this._fov,this.width/this.height,this.nearZ,this.farZ),i[8]=2*-t.x/this.width,i[9]=2*t.y/this.height,this.projectionMatrix=e.ae(i),e.K(i,i,[1,-1,1]),e.J(i,i,[0,0,-this.cameraToCenterDistance]),e.b7(i,i,this._pitch),e.ad(i,i,this.angle),e.J(i,i,[-r,-n,0]),this.mercatorMatrix=e.K([],i,[this.worldSize,this.worldSize,this.worldSize]),e.K(i,i,[1,1,this._pixelPerMeter]),this.pixelMatrix=e.L(new Float64Array(16),this.labelPlaneMatrix,i),e.J(i,i,[0,0,-this.elevation]),this.modelViewProjectionMatrix=i,this.invModelViewProjectionMatrix=e.as([],i),this.fogMatrix=new Float64Array(16),e.b6(this.fogMatrix,this._fov,this.width/this.height,a,this.farZ),this.fogMatrix[8]=2*-t.x/this.width,this.fogMatrix[9]=2*t.y/this.height,e.K(this.fogMatrix,this.fogMatrix,[1,-1,1]),e.J(this.fogMatrix,this.fogMatrix,[0,0,-this.cameraToCenterDistance]),e.b7(this.fogMatrix,this.fogMatrix,this._pitch),e.ad(this.fogMatrix,this.fogMatrix,this.angle),e.J(this.fogMatrix,this.fogMatrix,[-r,-n,0]),e.K(this.fogMatrix,this.fogMatrix,[1,1,this._pixelPerMeter]),e.J(this.fogMatrix,this.fogMatrix,[0,0,-this.elevation]),this.pixelMatrix3D=e.L(new Float64Array(16),this.labelPlaneMatrix,i);let g=this.width%2/2,y=this.height%2/2,v=Math.cos(this.angle),x=Math.sin(this.angle),_=r-Math.round(r)+v*g+x*y,b=n-Math.round(n)+v*y+x*g,w=new Float64Array(i);if(e.J(w,w,[_>.5?_-1:_,b>.5?b-1:b,0]),this.alignedModelViewProjectionMatrix=w,i=e.as(new Float64Array(16),this.pixelMatrix),!i)throw new Error("failed to invert matrix");this.pixelMatrixInverse=i,this._posMatrixCache={},this._alignedPosMatrixCache={},this._fogMatrixCache={}}maxPitchScaleFactor(){if(!this.pixelMatrixInverse)return 1;let t=this.pointCoordinate(new e.P(0,0)),r=[t.x*this.worldSize,t.y*this.worldSize,0,1];return e.af(r,r,this.pixelMatrix)[3]/this.cameraToCenterDistance}getCameraPoint(){let t=Math.tan(this._pitch)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new e.P(0,t))}getCameraQueryGeometry(t){let r=this.getCameraPoint();if(1===t.length)return[t[0],r];{let n=r.x,i=r.y,a=r.x,o=r.y;for(let e of t)n=Math.min(n,e.x),i=Math.min(i,e.y),a=Math.max(a,e.x),o=Math.max(o,e.y);return[new e.P(n,i),new e.P(a,i),new e.P(a,o),new e.P(n,o),new e.P(n,i)]}}lngLatToCameraDepth(t,r){let n=this.locationCoordinate(t),i=[n.x*this.worldSize,n.y*this.worldSize,r,1];return e.af(i,i,this.modelViewProjectionMatrix),i[2]/i[3]}}function Mn(t,e){let r,n=!1,i=null,a=null,o=()=>{i=null,n&&(t.apply(a,r),i=setTimeout(o,e),n=!1)};return(...t)=>(n=!0,a=this,r=t,i||o(),i)}class Sn{constructor(t){this._getCurrentHash=()=>{let t=window.location.hash.replace("#","");if(this._hashName){let e;return t.split("&").map((t=>t.split("="))).forEach((t=>{t[0]===this._hashName&&(e=t)})),(e&&e[1]||"").split("/")}return t.split("/")},this._onHashChange=()=>{let t=this._getCurrentHash();if(t.length>=3&&!t.some((t=>isNaN(t)))){let e=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(t[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+t[2],+t[1]],zoom:+t[0],bearing:e,pitch:+(t[4]||0)}),!0}return!1},this._updateHashUnthrottled=()=>{let t=window.location.href.replace(/(#.*)?$/,this.getHashString());window.history.replaceState(window.history.state,null,t)},this._removeHash=()=>{let t=this._getCurrentHash();if(0===t.length)return;let e=t.join("/"),r=e;r.split("&").length>0&&(r=r.split("&")[0]),this._hashName&&(r=`${this._hashName}=${e}`);let n=window.location.hash.replace(r,"");n.startsWith("#&")?n=n.slice(0,1)+n.slice(2):"#"===n&&(n="");let i=window.location.href.replace(/(#.+)?$/,n);i=i.replace("&&","&"),window.history.replaceState(window.history.state,null,i)},this._updateHash=Mn(this._updateHashUnthrottled,300),this._hashName=t&&encodeURIComponent(t)}addTo(t){return this._map=t,addEventListener("hashchange",this._onHashChange,!1),this._map.on("moveend",this._updateHash),this}remove(){return removeEventListener("hashchange",this._onHashChange,!1),this._map.off("moveend",this._updateHash),clearTimeout(this._updateHash()),this._removeHash(),delete this._map,this}getHashString(t){let e=this._map.getCenter(),r=Math.round(100*this._map.getZoom())/100,n=Math.ceil((r*Math.LN2+Math.log(512/360/.5))/Math.LN10),i=Math.pow(10,n),a=Math.round(e.lng*i)/i,o=Math.round(e.lat*i)/i,s=this._map.getBearing(),l=this._map.getPitch(),c="";if(c+=t?`/${a}/${o}/${r}`:`${r}/${o}/${a}`,(s||l)&&(c+="/"+Math.round(10*s)/10),l&&(c+=`/${Math.round(l)}`),this._hashName){let t=this._hashName,e=!1,r=window.location.hash.slice(1).split("&").map((r=>{let n=r.split("=")[0];return n===t?(e=!0,`${n}=${c}`):r})).filter((t=>t));return e||r.push(`${t}=${c}`),`#${r.join("&")}`}return`#${c}`}}let En={linearity:.3,easing:e.b8(0,0,.3,1)},Cn=e.e({deceleration:2500,maxSpeed:1400},En),In=e.e({deceleration:20,maxSpeed:1400},En),Ln=e.e({deceleration:1e3,maxSpeed:360},En),Pn=e.e({deceleration:1e3,maxSpeed:90},En);class zn{constructor(t){this._map=t,this.clear()}clear(){this._inertiaBuffer=[]}record(t){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:a.now(),settings:t})}_drainInertiaBuffer(){let t=this._inertiaBuffer,e=a.now();for(;t.length>0&&e-t[0].time>160;)t.shift()}_onMoveEnd(t){if(this._drainInertiaBuffer(),this._inertiaBuffer.length<2)return;let r={zoom:0,bearing:0,pitch:0,pan:new e.P(0,0),pinchAround:void 0,around:void 0};for(let{settings:t}of this._inertiaBuffer)r.zoom+=t.zoomDelta||0,r.bearing+=t.bearingDelta||0,r.pitch+=t.pitchDelta||0,t.panDelta&&r.pan._add(t.panDelta),t.around&&(r.around=t.around),t.pinchAround&&(r.pinchAround=t.pinchAround);let n=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,i={};if(r.pan.mag()){let a=On(r.pan.mag(),n,e.e({},Cn,t||{}));i.offset=r.pan.mult(a.amount/r.pan.mag()),i.center=this._map.transform.center,Dn(i,a)}if(r.zoom){let t=On(r.zoom,n,In);i.zoom=this._map.transform.zoom+t.amount,Dn(i,t)}if(r.bearing){let t=On(r.bearing,n,Ln);i.bearing=this._map.transform.bearing+e.ac(t.amount,-179,179),Dn(i,t)}if(r.pitch){let t=On(r.pitch,n,Pn);i.pitch=this._map.transform.pitch+t.amount,Dn(i,t)}if(i.zoom||i.bearing){let t=void 0===r.pinchAround?r.around:r.pinchAround;i.around=t?this._map.unproject(t):this._map.getCenter()}return this.clear(),e.e(i,{noMoveStart:!0})}}function Dn(t,e){(!t.duration||t.durationr.unproject(t))),l=a.reduce(((t,e,r,n)=>t.add(e.div(n.length))),new e.P(0,0));super(t,{points:a,point:l,lngLats:s,lngLat:r.unproject(l),originalEvent:n}),this._defaultPrevented=!1}}class Bn extends e.k{preventDefault(){this._defaultPrevented=!0}get defaultPrevented(){return this._defaultPrevented}constructor(t,e,r){super(t,{originalEvent:r}),this._defaultPrevented=!1}}class jn{constructor(t,e){this._map=t,this._clickTolerance=e.clickTolerance}reset(){delete this._mousedownPos}wheel(t){return this._firePreventable(new Bn(t.type,this._map,t))}mousedown(t,e){return this._mousedownPos=e,this._firePreventable(new Rn(t.type,this._map,t))}mouseup(t){this._map.fire(new Rn(t.type,this._map,t))}click(t,e){this._mousedownPos&&this._mousedownPos.dist(e)>=this._clickTolerance||this._map.fire(new Rn(t.type,this._map,t))}dblclick(t){return this._firePreventable(new Rn(t.type,this._map,t))}mouseover(t){this._map.fire(new Rn(t.type,this._map,t))}mouseout(t){this._map.fire(new Rn(t.type,this._map,t))}touchstart(t){return this._firePreventable(new Fn(t.type,this._map,t))}touchmove(t){this._map.fire(new Fn(t.type,this._map,t))}touchend(t){this._map.fire(new Fn(t.type,this._map,t))}touchcancel(t){this._map.fire(new Fn(t.type,this._map,t))}_firePreventable(t){if(this._map.fire(t),t.defaultPrevented)return{}}isEnabled(){return!0}isActive(){return!1}enable(){}disable(){}}class Nn{constructor(t){this._map=t}reset(){this._delayContextMenu=!1,this._ignoreContextMenu=!0,delete this._contextMenuEvent}mousemove(t){this._map.fire(new Rn(t.type,this._map,t))}mousedown(){this._delayContextMenu=!0,this._ignoreContextMenu=!1}mouseup(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new Rn("contextmenu",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)}contextmenu(t){this._delayContextMenu?this._contextMenuEvent=t:this._ignoreContextMenu||this._map.fire(new Rn(t.type,this._map,t)),this._map.listens("contextmenu")&&t.preventDefault()}isEnabled(){return!0}isActive(){return!1}enable(){}disable(){}}class Un{constructor(t){this._map=t}get transform(){return this._map._requestedCameraState||this._map.transform}get center(){return{lng:this.transform.center.lng,lat:this.transform.center.lat}}get zoom(){return this.transform.zoom}get pitch(){return this.transform.pitch}get bearing(){return this.transform.bearing}unproject(t){return this.transform.pointLocation(e.P.convert(t),this._map.terrain)}}class Vn{constructor(t,e){this._map=t,this._tr=new Un(t),this._el=t.getCanvasContainer(),this._container=t.getContainer(),this._clickTolerance=e.clickTolerance||1}isEnabled(){return!!this._enabled}isActive(){return!!this._active}enable(){this.isEnabled()||(this._enabled=!0)}disable(){this.isEnabled()&&(this._enabled=!1)}mousedown(t,e){this.isEnabled()&&t.shiftKey&&0===t.button&&(o.disableDrag(),this._startPos=this._lastPos=e,this._active=!0)}mousemoveWindow(t,e){if(!this._active)return;let r=e;if(this._lastPos.equals(r)||!this._box&&r.dist(this._startPos)t.fitScreenCoordinates(n,i,this._tr.bearing,{linear:!0})};this._fireEvent("boxzoomcancel",t)}keydown(t){this._active&&27===t.keyCode&&(this.reset(),this._fireEvent("boxzoomcancel",t))}reset(){this._active=!1,this._container.classList.remove("maplibregl-crosshair"),this._box&&(o.remove(this._box),this._box=null),o.enableDrag(),delete this._startPos,delete this._lastPos}_fireEvent(t,r){return this._map.fire(new e.k(t,{originalEvent:r}))}}function qn(t,e){if(t.length!==e.length)throw new Error(`The number of touches and points are not equal - touches ${t.length}, points ${e.length}`);let r={};for(let n=0;nthis.numTouches)&&(this.aborted=!0),this.aborted||(void 0===this.startTime&&(this.startTime=t.timeStamp),n.length===this.numTouches&&(this.centroid=function(t){let r=new e.P(0,0);for(let e of t)r._add(e);return r.div(t.length)}(r),this.touches=qn(n,r)))}touchmove(t,e,r){if(this.aborted||!this.centroid)return;let n=qn(r,e);for(let t in this.touches){let e=n[t];(!e||e.dist(this.touches[t])>30)&&(this.aborted=!0)}}touchend(t,e,r){if((!this.centroid||t.timeStamp-this.startTime>500)&&(this.aborted=!0),0===r.length){let t=!this.aborted&&this.centroid;if(this.reset(),t)return t}}}class Gn{constructor(t){this.singleTap=new Hn(t),this.numTaps=t.numTaps,this.reset()}reset(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()}touchstart(t,e,r){this.singleTap.touchstart(t,e,r)}touchmove(t,e,r){this.singleTap.touchmove(t,e,r)}touchend(t,e,r){let n=this.singleTap.touchend(t,e,r);if(n){let e=t.timeStamp-this.lastTime<500,r=!this.lastTap||this.lastTap.dist(n)<30;if(e&&r||this.reset(),this.count++,this.lastTime=t.timeStamp,this.lastTap=n,this.count===this.numTaps)return this.reset(),n}}}class Wn{constructor(t){this._tr=new Un(t),this._zoomIn=new Gn({numTouches:1,numTaps:2}),this._zoomOut=new Gn({numTouches:2,numTaps:1}),this.reset()}reset(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()}touchstart(t,e,r){this._zoomIn.touchstart(t,e,r),this._zoomOut.touchstart(t,e,r)}touchmove(t,e,r){this._zoomIn.touchmove(t,e,r),this._zoomOut.touchmove(t,e,r)}touchend(t,e,r){let n=this._zoomIn.touchend(t,e,r),i=this._zoomOut.touchend(t,e,r),a=this._tr;return n?(this._active=!0,t.preventDefault(),setTimeout((()=>this.reset()),0),{cameraAnimation:e=>e.easeTo({duration:300,zoom:a.zoom+1,around:a.unproject(n)},{originalEvent:t})}):i?(this._active=!0,t.preventDefault(),setTimeout((()=>this.reset()),0),{cameraAnimation:e=>e.easeTo({duration:300,zoom:a.zoom-1,around:a.unproject(i)},{originalEvent:t})}):void 0}touchcancel(){this.reset()}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}}class Zn{constructor(t){this._enabled=!!t.enable,this._moveStateManager=t.moveStateManager,this._clickTolerance=t.clickTolerance||1,this._moveFunction=t.move,this._activateOnStart=!!t.activateOnStart,t.assignEvents(this),this.reset()}reset(t){this._active=!1,this._moved=!1,delete this._lastPoint,this._moveStateManager.endMove(t)}_move(...t){let e=this._moveFunction(...t);if(e.bearingDelta||e.pitchDelta||e.around||e.panDelta)return this._active=!0,e}dragStart(t,e){this.isEnabled()&&!this._lastPoint&&this._moveStateManager.isValidStartEvent(t)&&(this._moveStateManager.startMove(t),this._lastPoint=e.length?e[0]:e,this._activateOnStart&&this._lastPoint&&(this._active=!0))}dragMove(t,e){if(!this.isEnabled())return;let r=this._lastPoint;if(!r)return;if(t.preventDefault(),!this._moveStateManager.isValidMoveEvent(t))return void this.reset(t);let n=e.length?e[0]:e;return!this._moved&&n.dist(r){t.mousedown=t.dragStart,t.mousemoveWindow=t.dragMove,t.mouseup=t.dragEnd,t.contextmenu=t=>{t.preventDefault()}},Jn=({enable:t,clickTolerance:e,bearingDegreesPerPixelMoved:r=.8})=>{let n=new Xn({checkCorrectEvent:t=>0===o.mouseButton(t)&&t.ctrlKey||2===o.mouseButton(t)});return new Zn({clickTolerance:e,move:(t,e)=>({bearingDelta:(e.x-t.x)*r}),moveStateManager:n,enable:t,assignEvents:Kn})},Qn=({enable:t,clickTolerance:e,pitchDegreesPerPixelMoved:r=-.5})=>{let n=new Xn({checkCorrectEvent:t=>0===o.mouseButton(t)&&t.ctrlKey||2===o.mouseButton(t)});return new Zn({clickTolerance:e,move:(t,e)=>({pitchDelta:(e.y-t.y)*r}),moveStateManager:n,enable:t,assignEvents:Kn})};class ti{constructor(t,e){this._clickTolerance=t.clickTolerance||1,this._map=e,this.reset()}reset(){this._active=!1,this._touches={},this._sum=new e.P(0,0)}_shouldBePrevented(t){return t<(this._map.cooperativeGestures.isEnabled()?2:1)}touchstart(t,e,r){return this._calculateTransform(t,e,r)}touchmove(t,e,r){if(this._active){if(!this._shouldBePrevented(r.length))return t.preventDefault(),this._calculateTransform(t,e,r);this._map.cooperativeGestures.notifyGestureBlocked("touch_pan",t)}}touchend(t,e,r){this._calculateTransform(t,e,r),this._active&&this._shouldBePrevented(r.length)&&this.reset()}touchcancel(){this.reset()}_calculateTransform(t,r,n){n.length>0&&(this._active=!0);let i=qn(n,r),a=new e.P(0,0),o=new e.P(0,0),s=0;for(let t in i){let e=i[t],r=this._touches[t];r&&(a._add(e),o._add(e.sub(r)),s++,i[t]=e)}if(this._touches=i,this._shouldBePrevented(s)||!o.mag())return;let l=o.div(s);return this._sum._add(l),this._sum.mag()Math.abs(t.x)}class li extends ei{constructor(t){super(),this._currentTouchCount=0,this._map=t}reset(){super.reset(),this._valid=void 0,delete this._firstMove,delete this._lastPoints}touchstart(t,e,r){super.touchstart(t,e,r),this._currentTouchCount=r.length}_start(t){this._lastPoints=t,si(t[0].sub(t[1]))&&(this._valid=!1)}_move(t,e,r){if(this._map.cooperativeGestures.isEnabled()&&this._currentTouchCount<3)return;let n=t[0].sub(this._lastPoints[0]),i=t[1].sub(this._lastPoints[1]);return this._valid=this.gestureBeginsVertically(n,i,r.timeStamp),this._valid?(this._lastPoints=t,this._active=!0,{pitchDelta:(n.y+i.y)/2*-.5}):void 0}gestureBeginsVertically(t,e,r){if(void 0!==this._valid)return this._valid;let n=t.mag()>=2,i=e.mag()>=2;if(!n&&!i)return;if(!n||!i)return void 0===this._firstMove&&(this._firstMove=r),r-this._firstMove<100&&void 0;let a=t.y>0==e.y>0;return si(t)&&si(e)&&a}}let ci={panStep:100,bearingStep:15,pitchStep:10};class ui{constructor(t){this._tr=new Un(t);let e=ci;this._panStep=e.panStep,this._bearingStep=e.bearingStep,this._pitchStep=e.pitchStep,this._rotationDisabled=!1}reset(){this._active=!1}keydown(t){if(t.altKey||t.ctrlKey||t.metaKey)return;let e=0,r=0,n=0,i=0,a=0;switch(t.keyCode){case 61:case 107:case 171:case 187:e=1;break;case 189:case 109:case 173:e=-1;break;case 37:t.shiftKey?r=-1:(t.preventDefault(),i=-1);break;case 39:t.shiftKey?r=1:(t.preventDefault(),i=1);break;case 38:t.shiftKey?n=1:(t.preventDefault(),a=-1);break;case 40:t.shiftKey?n=-1:(t.preventDefault(),a=1);break;default:return}return this._rotationDisabled&&(r=0,n=0),{cameraAnimation:o=>{let s=this._tr;o.easeTo({duration:300,easeId:"keyboardHandler",easing:hi,zoom:e?Math.round(s.zoom)+e*(t.shiftKey?2:1):s.zoom,bearing:s.bearing+r*this._bearingStep,pitch:s.pitch+n*this._pitchStep,offset:[-i*this._panStep,-a*this._panStep],center:s.center},{originalEvent:t})}}}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}disableRotation(){this._rotationDisabled=!0}enableRotation(){this._rotationDisabled=!1}}function hi(t){return t*(2-t)}let fi=4.000244140625;class pi{constructor(t,e){this._onTimeout=t=>{this._type="wheel",this._delta-=this._lastValue,this._active||this._start(t)},this._map=t,this._tr=new Un(t),this._triggerRenderFrame=e,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=.0022222222222222222}setZoomRate(t){this._defaultZoomRate=t}setWheelZoomRate(t){this._wheelZoomRate=t}isEnabled(){return!!this._enabled}isActive(){return!!this._active||void 0!==this._finishTimeout}isZooming(){return!!this._zooming}enable(t){this.isEnabled()||(this._enabled=!0,this._aroundCenter=!!t&&"center"===t.around)}disable(){this.isEnabled()&&(this._enabled=!1)}_shouldBePrevented(t){return!!this._map.cooperativeGestures.isEnabled()&&!(t.ctrlKey||this._map.cooperativeGestures.isBypassed(t))}wheel(t){if(!this.isEnabled())return;if(this._shouldBePrevented(t))return void this._map.cooperativeGestures.notifyGestureBlocked("wheel_zoom",t);let e=t.deltaMode===WheelEvent.DOM_DELTA_LINE?40*t.deltaY:t.deltaY,r=a.now(),n=r-(this._lastWheelEventTime||0);this._lastWheelEventTime=r,0!==e&&e%fi==0?this._type="wheel":0!==e&&Math.abs(e)<4?this._type="trackpad":n>400?(this._type=null,this._lastValue=e,this._timeout=setTimeout(this._onTimeout,40,t)):this._type||(this._type=Math.abs(n*e)<200?"trackpad":"wheel",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,e+=this._lastValue)),t.shiftKey&&e&&(e/=4),this._type&&(this._lastWheelEvent=t,this._delta-=e,this._active||this._start(t)),t.preventDefault()}_start(t){if(!this._delta)return;this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);let r=o.mousePos(this._map.getCanvas(),t),n=this._tr;this._around=r.y>n.transform.height/2-n.transform.getHorizon()?e.N.convert(this._aroundCenter?n.center:n.unproject(r)):e.N.convert(n.center),this._aroundPoint=n.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._triggerRenderFrame())}renderFrame(){if(!this._frameId||(this._frameId=null,!this.isActive()))return;let t=this._tr.transform;if(0!==this._delta){let e="wheel"===this._type&&Math.abs(this._delta)>fi?this._wheelZoomRate:this._defaultZoomRate,r=2/(1+Math.exp(-Math.abs(this._delta*e)));this._delta<0&&0!==r&&(r=1/r);let n="number"==typeof this._targetZoom?t.zoomScale(this._targetZoom):t.scale;this._targetZoom=Math.min(t.maxZoom,Math.max(t.minZoom,t.scaleZoom(n*r))),"wheel"===this._type&&(this._startZoom=t.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}let r,n="number"==typeof this._targetZoom?this._targetZoom:t.zoom,i=this._startZoom,o=this._easing,s=!1,l=a.now()-this._lastWheelEventTime;if("wheel"===this._type&&i&&o&&l){let t=Math.min(l/200,1),a=o(t);r=e.y.number(i,n,a),t<1?this._frameId||(this._frameId=!0):s=!0}else r=n,s=!0;return this._active=!0,s&&(this._active=!1,this._finishTimeout=setTimeout((()=>{this._zooming=!1,this._triggerRenderFrame(),delete this._targetZoom,delete this._finishTimeout}),200)),{noInertia:!0,needsRenderFrame:!s,zoomDelta:r-t.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}_smoothOutEasing(t){let r=e.b9;if(this._prevEase){let t=this._prevEase,n=(a.now()-t.start)/t.duration,i=t.easing(n+.01)-t.easing(n),o=.27/Math.sqrt(i*i+1e-4)*.01,s=Math.sqrt(.0729-o*o);r=e.b8(o,s,.25,1)}return this._prevEase={start:a.now(),duration:t,easing:r},r}reset(){this._active=!1,this._zooming=!1,delete this._targetZoom,this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout)}}class di{constructor(t,e){this._clickZoom=t,this._tapZoom=e}enable(){this._clickZoom.enable(),this._tapZoom.enable()}disable(){this._clickZoom.disable(),this._tapZoom.disable()}isEnabled(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()}isActive(){return this._clickZoom.isActive()||this._tapZoom.isActive()}}class mi{constructor(t){this._tr=new Un(t),this.reset()}reset(){this._active=!1}dblclick(t,e){return t.preventDefault(),{cameraAnimation:r=>{r.easeTo({duration:300,zoom:this._tr.zoom+(t.shiftKey?-1:1),around:this._tr.unproject(e)},{originalEvent:t})}}}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}}class gi{constructor(){this._tap=new Gn({numTouches:1,numTaps:1}),this.reset()}reset(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,delete this._tapPoint,this._tap.reset()}touchstart(t,e,r){if(!this._swipePoint)if(this._tapTime){let n=e[0],i=t.timeStamp-this._tapTime<500,a=this._tapPoint.dist(n)<30;i&&a?r.length>0&&(this._swipePoint=n,this._swipeTouch=r[0].identifier):this.reset()}else this._tap.touchstart(t,e,r)}touchmove(t,e,r){if(this._tapTime){if(this._swipePoint){if(r[0].identifier!==this._swipeTouch)return;let n=e[0],i=n.y-this._swipePoint.y;return this._swipePoint=n,t.preventDefault(),this._active=!0,{zoomDelta:i/128}}}else this._tap.touchmove(t,e,r)}touchend(t,e,r){if(this._tapTime)this._swipePoint&&0===r.length&&this.reset();else{let n=this._tap.touchend(t,e,r);n&&(this._tapTime=t.timeStamp,this._tapPoint=n)}}touchcancel(){this.reset()}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}}class yi{constructor(t,e,r){this._el=t,this._mousePan=e,this._touchPan=r}enable(t){this._inertiaOptions=t||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add("maplibregl-touch-drag-pan")}disable(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove("maplibregl-touch-drag-pan")}isEnabled(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()}isActive(){return this._mousePan.isActive()||this._touchPan.isActive()}}class vi{constructor(t,e,r){this._pitchWithRotate=t.pitchWithRotate,this._mouseRotate=e,this._mousePitch=r}enable(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()}disable(){this._mouseRotate.disable(),this._mousePitch.disable()}isEnabled(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())}isActive(){return this._mouseRotate.isActive()||this._mousePitch.isActive()}}class xi{constructor(t,e,r,n){this._el=t,this._touchZoom=e,this._touchRotate=r,this._tapDragZoom=n,this._rotationDisabled=!1,this._enabled=!0}enable(t){this._touchZoom.enable(t),this._rotationDisabled||this._touchRotate.enable(t),this._tapDragZoom.enable(),this._el.classList.add("maplibregl-touch-zoom-rotate")}disable(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove("maplibregl-touch-zoom-rotate")}isEnabled(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()}isActive(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()}disableRotation(){this._rotationDisabled=!0,this._touchRotate.disable()}enableRotation(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()}}class _i{constructor(t,e){this._bypassKey=-1!==navigator.userAgent.indexOf("Mac")?"metaKey":"ctrlKey",this._map=t,this._options=e,this._enabled=!1}isActive(){return!1}reset(){}_setupUI(){if(this._container)return;let t=this._map.getCanvasContainer();t.classList.add("maplibregl-cooperative-gestures"),this._container=o.create("div","maplibregl-cooperative-gesture-screen",t);let e=this._map._getUIString("CooperativeGesturesHandler.WindowsHelpText");"metaKey"===this._bypassKey&&(e=this._map._getUIString("CooperativeGesturesHandler.MacHelpText"));let r=this._map._getUIString("CooperativeGesturesHandler.MobileHelpText"),n=document.createElement("div");n.className="maplibregl-desktop-message",n.textContent=e,this._container.appendChild(n);let i=document.createElement("div");i.className="maplibregl-mobile-message",i.textContent=r,this._container.appendChild(i),this._container.setAttribute("aria-hidden","true")}_destroyUI(){this._container&&(o.remove(this._container),this._map.getCanvasContainer().classList.remove("maplibregl-cooperative-gestures")),delete this._container}enable(){this._setupUI(),this._enabled=!0}disable(){this._enabled=!1,this._destroyUI()}isEnabled(){return this._enabled}isBypassed(t){return t[this._bypassKey]}notifyGestureBlocked(t,r){this._enabled&&(this._map.fire(new e.k("cooperativegestureprevented",{gestureType:t,originalEvent:r})),this._container.classList.add("maplibregl-show"),setTimeout((()=>{this._container.classList.remove("maplibregl-show")}),100))}}let bi=t=>t.zoom||t.drag||t.pitch||t.rotate;class wi extends e.k{}function Ti(t){return t.panDelta&&t.panDelta.mag()||t.zoomDelta||t.bearingDelta||t.pitchDelta}class ki{constructor(t,e){this.handleWindowEvent=t=>{this.handleEvent(t,`${t.type}Window`)},this.handleEvent=(t,e)=>{if("blur"===t.type)return void this.stop(!0);this._updatingCamera=!0;let r="renderFrame"===t.type?void 0:t,n={needsRenderFrame:!1},i={},a={},s=t.touches,l=s?this._getMapTouches(s):void 0,c=l?o.touchPos(this._map.getCanvas(),l):o.mousePos(this._map.getCanvas(),t);for(let{handlerName:o,handler:s,allowed:u}of this._handlers){if(!s.isEnabled())continue;let h;this._blockedByActive(a,u,o)?s.reset():s[e||t.type]&&(h=s[e||t.type](t,c,l),this.mergeHandlerResult(n,i,h,o,r),h&&h.needsRenderFrame&&this._triggerRenderFrame()),(h||s.isActive())&&(a[o]=s)}let u={};for(let t in this._previousActiveHandlers)a[t]||(u[t]=r);this._previousActiveHandlers=a,(Object.keys(u).length||Ti(n))&&(this._changes.push([n,i,u]),this._triggerRenderFrame()),(Object.keys(a).length||Ti(n))&&this._map._stop(!0),this._updatingCamera=!1;let{cameraAnimation:h}=n;h&&(this._inertia.clear(),this._fireEvents({},{},!0),this._changes=[],h(this._map))},this._map=t,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new zn(t),this._bearingSnap=e.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(e);let r=this._el;this._listeners=[[r,"touchstart",{passive:!0}],[r,"touchmove",{passive:!1}],[r,"touchend",void 0],[r,"touchcancel",void 0],[r,"mousedown",void 0],[r,"mousemove",void 0],[r,"mouseup",void 0],[document,"mousemove",{capture:!0}],[document,"mouseup",void 0],[r,"mouseover",void 0],[r,"mouseout",void 0],[r,"dblclick",void 0],[r,"click",void 0],[r,"keydown",{capture:!1}],[r,"keyup",void 0],[r,"wheel",{passive:!1}],[r,"contextmenu",void 0],[window,"blur",void 0]];for(let[t,e,r]of this._listeners)o.addEventListener(t,e,t===document?this.handleWindowEvent:this.handleEvent,r)}destroy(){for(let[t,e,r]of this._listeners)o.removeEventListener(t,e,t===document?this.handleWindowEvent:this.handleEvent,r)}_addDefaultHandlers(t){let e=this._map,r=e.getCanvasContainer();this._add("mapEvent",new jn(e,t));let n=e.boxZoom=new Vn(e,t);this._add("boxZoom",n),t.interactive&&t.boxZoom&&n.enable();let i=e.cooperativeGestures=new _i(e,t.cooperativeGestures);this._add("cooperativeGestures",i),t.cooperativeGestures&&i.enable();let a=new Wn(e),s=new mi(e);e.doubleClickZoom=new di(s,a),this._add("tapZoom",a),this._add("clickZoom",s),t.interactive&&t.doubleClickZoom&&e.doubleClickZoom.enable();let l=new gi;this._add("tapDragZoom",l);let c=e.touchPitch=new li(e);this._add("touchPitch",c),t.interactive&&t.touchPitch&&e.touchPitch.enable(t.touchPitch);let u=Jn(t),h=Qn(t);e.dragRotate=new vi(t,u,h),this._add("mouseRotate",u,["mousePitch"]),this._add("mousePitch",h,["mouseRotate"]),t.interactive&&t.dragRotate&&e.dragRotate.enable();let f=(({enable:t,clickTolerance:e})=>{let r=new Xn({checkCorrectEvent:t=>0===o.mouseButton(t)&&!t.ctrlKey});return new Zn({clickTolerance:e,move:(t,e)=>({around:e,panDelta:e.sub(t)}),activateOnStart:!0,moveStateManager:r,enable:t,assignEvents:Kn})})(t),p=new ti(t,e);e.dragPan=new yi(r,f,p),this._add("mousePan",f),this._add("touchPan",p,["touchZoom","touchRotate"]),t.interactive&&t.dragPan&&e.dragPan.enable(t.dragPan);let d=new oi,m=new ii;e.touchZoomRotate=new xi(r,m,d,l),this._add("touchRotate",d,["touchPan","touchZoom"]),this._add("touchZoom",m,["touchPan","touchRotate"]),t.interactive&&t.touchZoomRotate&&e.touchZoomRotate.enable(t.touchZoomRotate);let g=e.scrollZoom=new pi(e,(()=>this._triggerRenderFrame()));this._add("scrollZoom",g,["mousePan"]),t.interactive&&t.scrollZoom&&e.scrollZoom.enable(t.scrollZoom);let y=e.keyboard=new ui(e);this._add("keyboard",y),t.interactive&&t.keyboard&&e.keyboard.enable(),this._add("blockableMapEvent",new Nn(e))}_add(t,e,r){this._handlers.push({handlerName:t,handler:e,allowed:r}),this._handlersById[t]=e}stop(t){if(!this._updatingCamera){for(let{handler:t}of this._handlers)t.reset();this._inertia.clear(),this._fireEvents({},{},t),this._changes=[]}}isActive(){for(let{handler:t}of this._handlers)if(t.isActive())return!0;return!1}isZooming(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()}isRotating(){return!!this._eventsInProgress.rotate}isMoving(){return!!bi(this._eventsInProgress)||this.isZooming()}_blockedByActive(t,e,r){for(let n in t)if(n!==r&&(!e||e.indexOf(n)<0))return!0;return!1}_getMapTouches(t){let e=[];for(let r of t)this._el.contains(r.target)&&e.push(r);return e}mergeHandlerResult(t,r,n,i,a){if(!n)return;e.e(t,n);let o={handlerName:i,originalEvent:n.originalEvent||a};void 0!==n.zoomDelta&&(r.zoom=o),void 0!==n.panDelta&&(r.drag=o),void 0!==n.pitchDelta&&(r.pitch=o),void 0!==n.bearingDelta&&(r.rotate=o)}_applyChanges(){let t={},r={},n={};for(let[i,a,o]of this._changes)i.panDelta&&(t.panDelta=(t.panDelta||new e.P(0,0))._add(i.panDelta)),i.zoomDelta&&(t.zoomDelta=(t.zoomDelta||0)+i.zoomDelta),i.bearingDelta&&(t.bearingDelta=(t.bearingDelta||0)+i.bearingDelta),i.pitchDelta&&(t.pitchDelta=(t.pitchDelta||0)+i.pitchDelta),void 0!==i.around&&(t.around=i.around),void 0!==i.pinchAround&&(t.pinchAround=i.pinchAround),i.noInertia&&(t.noInertia=i.noInertia),e.e(r,a),e.e(n,o);this._updateMapTransform(t,r,n),this._changes=[]}_updateMapTransform(t,e,r){let n=this._map,i=n._getTransformForUpdate(),a=n.terrain;if(!(Ti(t)||a&&this._terrainMovement))return this._fireEvents(e,r,!0);let{panDelta:o,zoomDelta:s,bearingDelta:l,pitchDelta:c,around:u,pinchAround:h}=t;void 0!==h&&(u=h),n._stop(!0),u=u||n.transform.centerPoint;let f=i.pointLocation(o?u.sub(o):u);l&&(i.bearing+=l),c&&(i.pitch+=c),s&&(i.zoom+=s),a?this._terrainMovement||!e.drag&&!e.zoom?e.drag&&this._terrainMovement?i.center=i.pointLocation(i.centerPoint.sub(o)):i.setLocationAtPoint(f,u):(this._terrainMovement=!0,this._map._elevationFreeze=!0,i.setLocationAtPoint(f,u)):i.setLocationAtPoint(f,u),n._applyUpdatedTransform(i),this._map._update(),t.noInertia||this._inertia.record(t),this._fireEvents(e,r,!0)}_fireEvents(t,r,n){let i=bi(this._eventsInProgress),o=bi(t),s={};for(let e in t){let{originalEvent:r}=t[e];this._eventsInProgress[e]||(s[`${e}start`]=r),this._eventsInProgress[e]=t[e]}!i&&o&&this._fireEvent("movestart",o.originalEvent);for(let t in s)this._fireEvent(t,s[t]);o&&this._fireEvent("move",o.originalEvent);for(let e in t){let{originalEvent:r}=t[e];this._fireEvent(e,r)}let l,c={};for(let t in this._eventsInProgress){let{handlerName:e,originalEvent:n}=this._eventsInProgress[t];this._handlersById[e].isActive()||(delete this._eventsInProgress[t],l=r[e]||n,c[`${t}end`]=l)}for(let t in c)this._fireEvent(t,c[t]);let u=bi(this._eventsInProgress),h=(i||o)&&!u;if(h&&this._terrainMovement){this._map._elevationFreeze=!1,this._terrainMovement=!1;let t=this._map._getTransformForUpdate();t.recalculateZoom(this._map.terrain),this._map._applyUpdatedTransform(t)}if(n&&h){this._updatingCamera=!0;let t=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),r=t=>0!==t&&-this._bearingSnap{delete this._frameId,this.handleEvent(new wi("renderFrame",{timeStamp:t})),this._applyChanges()}))}_triggerRenderFrame(){void 0===this._frameId&&(this._frameId=this._requestFrame())}}class Ai extends e.E{constructor(t,e){super(),this._renderFrameCallback=()=>{let t=Math.min((a.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(t)),t<1&&this._easeFrameId?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},this._moving=!1,this._zooming=!1,this.transform=t,this._bearingSnap=e.bearingSnap,this.on("moveend",(()=>{delete this._requestedCameraState}))}getCenter(){return new e.N(this.transform.center.lng,this.transform.center.lat)}setCenter(t,e){return this.jumpTo({center:t},e)}panBy(t,r,n){return t=e.P.convert(t).mult(-1),this.panTo(this.transform.center,e.e({offset:t},r),n)}panTo(t,r,n){return this.easeTo(e.e({center:t},r),n)}getZoom(){return this.transform.zoom}setZoom(t,e){return this.jumpTo({zoom:t},e),this}zoomTo(t,r,n){return this.easeTo(e.e({zoom:t},r),n)}zoomIn(t,e){return this.zoomTo(this.getZoom()+1,t,e),this}zoomOut(t,e){return this.zoomTo(this.getZoom()-1,t,e),this}getBearing(){return this.transform.bearing}setBearing(t,e){return this.jumpTo({bearing:t},e),this}getPadding(){return this.transform.padding}setPadding(t,e){return this.jumpTo({padding:t},e),this}rotateTo(t,r,n){return this.easeTo(e.e({bearing:t},r),n)}resetNorth(t,r){return this.rotateTo(0,e.e({duration:1e3},t),r),this}resetNorthPitch(t,r){return this.easeTo(e.e({bearing:0,pitch:0,duration:1e3},t),r),this}snapToNorth(t,e){return Math.abs(this.getBearing()){if(this._zooming&&(i.zoom=e.y.number(o,y,n)),this._rotating&&(i.bearing=e.y.number(s,u,n)),this._pitching&&(i.pitch=e.y.number(l,h,n)),this._padding&&(i.interpolatePadding(c,f,n),d=i.centerPoint.add(p)),this.terrain&&!t.freezeElevation&&this._updateElevation(n),v)i.setLocationAtPoint(v,x);else{let t=i.zoomScale(i.zoom-o),e=y>o?Math.min(2,w):Math.max(.5,w),r=Math.pow(e,1-n),a=i.unproject(_.add(b.mult(n*r)).mult(t));i.setLocationAtPoint(i.renderWorldCopies?a.wrap():a,d)}this._applyUpdatedTransform(i),this._fireMoveEvents(r)}),(e=>{this.terrain&&t.freezeElevation&&this._finalizeElevation(),this._afterEase(r,e)}),t),this}_prepareEase(t,r,n={}){this._moving=!0,r||n.moving||this.fire(new e.k("movestart",t)),this._zooming&&!n.zooming&&this.fire(new e.k("zoomstart",t)),this._rotating&&!n.rotating&&this.fire(new e.k("rotatestart",t)),this._pitching&&!n.pitching&&this.fire(new e.k("pitchstart",t))}_prepareElevation(t){this._elevationCenter=t,this._elevationStart=this.transform.elevation,this._elevationTarget=this.terrain.getElevationForLngLatZoom(t,this.transform.tileZoom),this._elevationFreeze=!0}_updateElevation(t){this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this._elevationCenter,this.transform.tileZoom);let r=this.terrain.getElevationForLngLatZoom(this._elevationCenter,this.transform.tileZoom);if(t<1&&r!==this._elevationTarget){let e=this._elevationTarget-this._elevationStart;this._elevationStart+=t*(e-(r-(e*t+this._elevationStart))/(1-t)),this._elevationTarget=r}this.transform.elevation=e.y.number(this._elevationStart,this._elevationTarget,t)}_finalizeElevation(){this._elevationFreeze=!1,this.transform.recalculateZoom(this.terrain)}_getTransformForUpdate(){return this.transformCameraUpdate||this.terrain?(this._requestedCameraState||(this._requestedCameraState=this.transform.clone()),this._requestedCameraState):this.transform}_elevateCameraIfInsideTerrain(t){let e=t.getCameraPosition(),r=this.terrain.getElevationForLngLatZoom(e.lngLat,t.zoom);if(e.altitudethis._elevateCameraIfInsideTerrain(t))),this.transformCameraUpdate&&e.push((t=>this.transformCameraUpdate(t))),!e.length)return;let r=t.clone();for(let t of e){let e=r.clone(),{center:n,zoom:i,pitch:a,bearing:o,elevation:s}=t(e);n&&(e.center=n),void 0!==i&&(e.zoom=i),void 0!==a&&(e.pitch=a),void 0!==o&&(e.bearing=o),void 0!==s&&(e.elevation=s),r.apply(e)}this.transform.apply(r)}_fireMoveEvents(t){this.fire(new e.k("move",t)),this._zooming&&this.fire(new e.k("zoom",t)),this._rotating&&this.fire(new e.k("rotate",t)),this._pitching&&this.fire(new e.k("pitch",t))}_afterEase(t,r){if(this._easeId&&r&&this._easeId===r)return;delete this._easeId;let n=this._zooming,i=this._rotating,a=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,n&&this.fire(new e.k("zoomend",t)),i&&this.fire(new e.k("rotateend",t)),a&&this.fire(new e.k("pitchend",t)),this.fire(new e.k("moveend",t))}flyTo(t,r){var n;if(!t.essential&&a.prefersReducedMotion){let n=e.M(t,["center","zoom","bearing","pitch","around"]);return this.jumpTo(n,r)}this.stop(),t=e.e({offset:[0,0],speed:1.2,curve:1.42,easing:e.b9},t);let i=this._getTransformForUpdate(),o=i.zoom,s=i.bearing,l=i.pitch,c=i.padding,u="bearing"in t?this._normalizeBearing(t.bearing,s):s,h="pitch"in t?+t.pitch:l,f="padding"in t?t.padding:i.padding,p=e.P.convert(t.offset),d=i.centerPoint.add(p),m=i.pointLocation(d),{center:g,zoom:y}=i.getConstrained(e.N.convert(t.center||m),null!==(n=t.zoom)&&void 0!==n?n:o);this._normalizeCenter(g,i);let v=i.zoomScale(y-o),x=i.project(m),_=i.project(g).sub(x),b=t.curve,w=Math.max(i.width,i.height),T=w/v,k=_.mag();if("minZoom"in t){let r=e.ac(Math.min(t.minZoom,o,y),i.minZoom,i.maxZoom),n=w/i.zoomScale(r-o);b=Math.sqrt(n/k*2)}let A=b*b;function M(t){let e=(T*T-w*w+(t?-1:1)*A*A*k*k)/(2*(t?T:w)*A*k);return Math.log(Math.sqrt(e*e+1)-e)}function S(t){return(Math.exp(t)-Math.exp(-t))/2}function E(t){return(Math.exp(t)+Math.exp(-t))/2}let C=M(!1),I=function(t){return E(C)/E(C+b*t)},L=function(t){return w*((E(C)*(S(e=C+b*t)/E(e))-S(C))/A)/k;var e},P=(M(!0)-C)/b;if(Math.abs(k)<1e-6||!isFinite(P)){if(Math.abs(w-T)<1e-6)return this.easeTo(t,r);let e=T0,I=t=>Math.exp(e*b*t)}return t.duration="duration"in t?+t.duration:1e3*P/("screenSpeed"in t?+t.screenSpeed/b:+t.speed),t.maxDuration&&t.duration>t.maxDuration&&(t.duration=0),this._zooming=!0,this._rotating=s!==u,this._pitching=h!==l,this._padding=!i.isPaddingEqual(f),this._prepareEase(r,!1),this.terrain&&this._prepareElevation(g),this._ease((n=>{let a=n*P,m=1/I(a);i.zoom=1===n?y:o+i.scaleZoom(m),this._rotating&&(i.bearing=e.y.number(s,u,n)),this._pitching&&(i.pitch=e.y.number(l,h,n)),this._padding&&(i.interpolatePadding(c,f,n),d=i.centerPoint.add(p)),this.terrain&&!t.freezeElevation&&this._updateElevation(n);let v=1===n?g:i.unproject(x.add(_.mult(L(a))).mult(m));i.setLocationAtPoint(i.renderWorldCopies?v.wrap():v,d),this._applyUpdatedTransform(i),this._fireMoveEvents(r)}),(()=>{this.terrain&&t.freezeElevation&&this._finalizeElevation(),this._afterEase(r)}),t),this}isEasing(){return!!this._easeFrameId}stop(){return this._stop()}_stop(t,e){var r;if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){let t=this._onEaseEnd;delete this._onEaseEnd,t.call(this,e)}return t||null===(r=this.handlers)||void 0===r||r.stop(!1),this}_ease(t,e,r){!1===r.animate||0===r.duration?(t(1),e()):(this._easeStart=a.now(),this._easeOptions=r,this._onEaseFrame=t,this._onEaseEnd=e,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))}_normalizeBearing(t,r){t=e.b3(t,-180,180);let n=Math.abs(t-r);return Math.abs(t-360-r)180?-360:r<-180?360:0}queryTerrainElevation(t){return this.terrain?this.terrain.getElevationForLngLatZoom(e.N.convert(t),this.transform.tileZoom)-this.transform.elevation:null}}let Mi={compact:!0,customAttribution:'MapLibre'};class Si{constructor(t=Mi){this._toggleAttribution=()=>{this._container.classList.contains("maplibregl-compact")&&(this._container.classList.contains("maplibregl-compact-show")?(this._container.setAttribute("open",""),this._container.classList.remove("maplibregl-compact-show")):(this._container.classList.add("maplibregl-compact-show"),this._container.removeAttribute("open")))},this._updateData=t=>{!t||"metadata"!==t.sourceDataType&&"visibility"!==t.sourceDataType&&"style"!==t.dataType&&"terrain"!==t.type||this._updateAttributions()},this._updateCompact=()=>{this._map.getCanvasContainer().offsetWidth<=640||this._compact?!1===this._compact?this._container.setAttribute("open",""):this._container.classList.contains("maplibregl-compact")||this._container.classList.contains("maplibregl-attrib-empty")||(this._container.setAttribute("open",""),this._container.classList.add("maplibregl-compact","maplibregl-compact-show")):(this._container.setAttribute("open",""),this._container.classList.contains("maplibregl-compact")&&this._container.classList.remove("maplibregl-compact","maplibregl-compact-show"))},this._updateCompactMinimize=()=>{this._container.classList.contains("maplibregl-compact")&&this._container.classList.contains("maplibregl-compact-show")&&this._container.classList.remove("maplibregl-compact-show")},this.options=t}getDefaultPosition(){return"bottom-right"}onAdd(t){return this._map=t,this._compact=this.options.compact,this._container=o.create("details","maplibregl-ctrl maplibregl-ctrl-attrib"),this._compactButton=o.create("summary","maplibregl-ctrl-attrib-button",this._container),this._compactButton.addEventListener("click",this._toggleAttribution),this._setElementTitle(this._compactButton,"ToggleAttribution"),this._innerContainer=o.create("div","maplibregl-ctrl-attrib-inner",this._container),this._updateAttributions(),this._updateCompact(),this._map.on("styledata",this._updateData),this._map.on("sourcedata",this._updateData),this._map.on("terrain",this._updateData),this._map.on("resize",this._updateCompact),this._map.on("drag",this._updateCompactMinimize),this._container}onRemove(){o.remove(this._container),this._map.off("styledata",this._updateData),this._map.off("sourcedata",this._updateData),this._map.off("terrain",this._updateData),this._map.off("resize",this._updateCompact),this._map.off("drag",this._updateCompactMinimize),this._map=void 0,this._compact=void 0,this._attribHTML=void 0}_setElementTitle(t,e){let r=this._map._getUIString(`AttributionControl.${e}`);t.title=r,t.setAttribute("aria-label",r)}_updateAttributions(){if(!this._map.style)return;let t=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?t=t.concat(this.options.customAttribution.map((t=>"string"!=typeof t?"":t))):"string"==typeof this.options.customAttribution&&t.push(this.options.customAttribution)),this._map.style.stylesheet){let t=this._map.style.stylesheet;this.styleOwner=t.owner,this.styleId=t.id}let e=this._map.style.sourceCaches;for(let r in e){let n=e[r];if(n.used||n.usedForTerrain){let e=n.getSource();e.attribution&&t.indexOf(e.attribution)<0&&t.push(e.attribution)}}t=t.filter((t=>String(t).trim())),t.sort(((t,e)=>t.length-e.length)),t=t.filter(((e,r)=>{for(let n=r+1;n=0)return!1;return!0}));let r=t.join(" | ");r!==this._attribHTML&&(this._attribHTML=r,t.length?(this._innerContainer.innerHTML=r,this._container.classList.remove("maplibregl-attrib-empty")):this._container.classList.add("maplibregl-attrib-empty"),this._updateCompact(),this._editLink=null)}}class Ei{constructor(t={}){this._updateCompact=()=>{let t=this._container.children;if(t.length){let e=t[0];this._map.getCanvasContainer().offsetWidth<=640||this._compact?!1!==this._compact&&e.classList.add("maplibregl-compact"):e.classList.remove("maplibregl-compact")}},this.options=t}getDefaultPosition(){return"bottom-left"}onAdd(t){this._map=t,this._compact=this.options&&this.options.compact,this._container=o.create("div","maplibregl-ctrl");let e=o.create("a","maplibregl-ctrl-logo");return e.target="_blank",e.rel="noopener nofollow",e.href="https://maplibre.org/",e.setAttribute("aria-label",this._map._getUIString("LogoControl.Title")),e.setAttribute("rel","noopener nofollow"),this._container.appendChild(e),this._container.style.display="block",this._map.on("resize",this._updateCompact),this._updateCompact(),this._container}onRemove(){o.remove(this._container),this._map.off("resize",this._updateCompact),this._map=void 0,this._compact=void 0}}class Ci{constructor(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1}add(t){let e=++this._id;return this._queue.push({callback:t,id:e,cancelled:!1}),e}remove(t){let e=this._currentlyRunning,r=e?this._queue.concat(e):this._queue;for(let e of r)if(e.id===t)return void(e.cancelled=!0)}run(t=0){if(this._currentlyRunning)throw new Error("Attempting to run(), but is already running.");let e=this._currentlyRunning=this._queue;this._queue=[];for(let r of e)if(!r.cancelled&&(r.callback(t),this._cleared))break;this._cleared=!1,this._currentlyRunning=!1}clear(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]}}var Ii=e.Y([{name:"a_pos3d",type:"Int16",components:3}]);class Li extends e.E{constructor(t){super(),this.sourceCache=t,this._tiles={},this._renderableTilesKeys=[],this._sourceTileCache={},this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.deltaZoom=1,t.usedForTerrain=!0,t.tileSize=this.tileSize*2**this.deltaZoom}destruct(){this.sourceCache.usedForTerrain=!1,this.sourceCache.tileSize=null}update(t,r){this.sourceCache.update(t,r),this._renderableTilesKeys=[];let n={};for(let i of t.coveringTiles({tileSize:this.tileSize,minzoom:this.minzoom,maxzoom:this.maxzoom,reparseOverscaled:!1,terrain:r}))n[i.key]=!0,this._renderableTilesKeys.push(i.key),this._tiles[i.key]||(i.posMatrix=new Float64Array(16),e.aP(i.posMatrix,0,e.X,0,e.X,0,1),this._tiles[i.key]=new ct(i,this.tileSize));for(let t in this._tiles)n[t]||delete this._tiles[t]}freeRtt(t){for(let e in this._tiles){let r=this._tiles[e];(!t||r.tileID.equals(t)||r.tileID.isChildOf(t)||t.isChildOf(r.tileID))&&(r.rtt=[])}}getRenderableTiles(){return this._renderableTilesKeys.map((t=>this.getTileByID(t)))}getTileByID(t){return this._tiles[t]}getTerrainCoords(t){let r={};for(let n of this._renderableTilesKeys){let i=this._tiles[n].tileID;if(i.canonical.equals(t.canonical)){let i=t.clone();i.posMatrix=new Float64Array(16),e.aP(i.posMatrix,0,e.X,0,e.X,0,1),r[n]=i}else if(i.canonical.isChildOf(t.canonical)){let a=t.clone();a.posMatrix=new Float64Array(16);let o=i.canonical.z-t.canonical.z,s=i.canonical.x-(i.canonical.x>>o<>o<>o;e.aP(a.posMatrix,0,c,0,c,0,1),e.J(a.posMatrix,a.posMatrix,[-s*c,-l*c,0]),r[n]=a}else if(t.canonical.isChildOf(i.canonical)){let a=t.clone();a.posMatrix=new Float64Array(16);let o=t.canonical.z-i.canonical.z,s=t.canonical.x-(t.canonical.x>>o<>o<>o;e.aP(a.posMatrix,0,e.X,0,e.X,0,1),e.J(a.posMatrix,a.posMatrix,[s*c,l*c,0]),e.K(a.posMatrix,a.posMatrix,[1/2**o,1/2**o,0]),r[n]=a}}return r}getSourceTile(t,e){let r=this.sourceCache._source,n=t.overscaledZ-this.deltaZoom;if(n>r.maxzoom&&(n=r.maxzoom),n=r.minzoom&&(!i||!i.dem);)i=this.sourceCache.getTileByID(t.scaledTo(n--).key);return i}tilesAfterTime(t=Date.now()){return Object.values(this._tiles).filter((e=>e.timeAdded>=t))}}class Pi{constructor(t,e,r){this.painter=t,this.sourceCache=new Li(e),this.options=r,this.exaggeration="number"==typeof r.exaggeration?r.exaggeration:1,this.qualityFactor=2,this.meshSize=128,this._demMatrixCache={},this.coordsIndex=[],this._coordsTextureSize=1024}getDEMElevation(t,r,n,i=e.X){var a;if(!(r>=0&&r=0&&nt.canonical.z&&(t.canonical.z>=n?i=t.canonical.z-n:e.w("cannot calculate elevation if elevation maxzoom > source.maxzoom"));let a=t.canonical.x-(t.canonical.x>>i<>i<>8<<4|t>>8,r[e+3]=0;let n=new e.R({width:this._coordsTextureSize,height:this._coordsTextureSize},new Uint8Array(r.buffer)),i=new w(t,n,t.gl.RGBA,{premultiply:!1});return i.bind(t.gl.NEAREST,t.gl.CLAMP_TO_EDGE),this._coordsTexture=i,i}pointCoordinate(t){this.painter.maybeDrawDepthAndCoords(!0);let r=new Uint8Array(4),n=this.painter.context,i=n.gl,a=Math.round(t.x*this.painter.pixelRatio/devicePixelRatio),o=Math.round(t.y*this.painter.pixelRatio/devicePixelRatio),s=Math.round(this.painter.height/devicePixelRatio);n.bindFramebuffer.set(this.getFramebuffer("coords").framebuffer),i.readPixels(a,s-o-1,1,1,i.RGBA,i.UNSIGNED_BYTE,r),n.bindFramebuffer.set(null);let l=r[0]+(r[2]>>4<<8),c=r[1]+((15&r[2])<<8),u=this.coordsIndex[255-r[3]],h=u&&this.sourceCache.getTileByID(u);if(!h)return null;let f=this._coordsTextureSize,p=(1<t.id!==e)),this._recentlyUsed.push(t.id)}stampObject(t){t.stamp=++this._stamp}getOrCreateFreeObject(){for(let t of this._recentlyUsed)if(!this._objects[t].inUse)return this._objects[t];if(this._objects.length>=this._size)throw new Error("No free RenderPool available, call freeAllObjects() required!");let t=this._createObject(this._objects.length);return this._objects.push(t),t}freeObject(t){t.inUse=!1}freeAllObjects(){for(let t of this._objects)this.freeObject(t)}isFull(){return!(this._objects.length!t.inUse))}}let Di={background:!0,fill:!0,line:!0,raster:!0,hillshade:!0};class Oi{constructor(t,e){this.painter=t,this.terrain=e,this.pool=new zi(t.context,30,e.sourceCache.tileSize*e.qualityFactor)}destruct(){this.pool.destruct()}getTexture(t){return this.pool.getObjectForId(t.rtt[this._stacks.length-1].id).texture}prepareForRender(t,e){this._stacks=[],this._prevType=null,this._rttTiles=[],this._renderableTiles=this.terrain.sourceCache.getRenderableTiles(),this._renderableLayerIds=t._order.filter((r=>!t._layers[r].isHidden(e))),this._coordsDescendingInv={};for(let e in t.sourceCaches){this._coordsDescendingInv[e]={};let r=t.sourceCaches[e].getVisibleCoordinates();for(let t of r){let r=this.terrain.sourceCache.getTerrainCoords(t);for(let t in r)this._coordsDescendingInv[e][t]||(this._coordsDescendingInv[e][t]=[]),this._coordsDescendingInv[e][t].push(r[t])}}this._coordsDescendingInvStr={};for(let e of t._order){let r=t._layers[e],n=r.source;if(Di[r.type]&&!this._coordsDescendingInvStr[n]){this._coordsDescendingInvStr[n]={};for(let t in this._coordsDescendingInv[n])this._coordsDescendingInvStr[n][t]=this._coordsDescendingInv[n][t].map((t=>t.key)).sort().join()}}for(let t of this._renderableTiles)for(let e in this._coordsDescendingInvStr){let r=this._coordsDescendingInvStr[e][t.tileID.key];r&&r!==t.rttCoords[e]&&(t.rtt=[])}}renderLayer(t){if(t.isHidden(this.painter.transform.zoom))return!1;let r=t.type,n=this.painter,i=this._renderableLayerIds[this._renderableLayerIds.length-1]===t.id;if(Di[r]&&(this._prevType&&Di[this._prevType]||this._stacks.push([]),this._prevType=r,this._stacks[this._stacks.length-1].push(t.id),!i))return!0;if(Di[this._prevType]||Di[r]&&i){this._prevType=r;let t=this._stacks.length-1,i=this._stacks[t]||[];for(let r of this._renderableTiles){if(this.pool.isFull()&&(vn(this.painter,this.terrain,this._rttTiles),this._rttTiles=[],this.pool.freeAllObjects()),this._rttTiles.push(r),r.rtt[t]){let e=this.pool.getObjectForId(r.rtt[t].id);if(e.stamp===r.rtt[t].stamp){this.pool.useObject(e);continue}}let a=this.pool.getOrCreateFreeObject();this.pool.useObject(a),this.pool.stampObject(a),r.rtt[t]={id:a.id,stamp:a.stamp},n.context.bindFramebuffer.set(a.fbo.framebuffer),n.context.clear({color:e.aM.transparent,stencil:0}),n.currentStencilSource=void 0;for(let t=0;t{t.touchstart=t.dragStart,t.touchmoveWindow=t.dragMove,t.touchend=t.dragEnd},Ui={showCompass:!0,showZoom:!0,visualizePitch:!1};class Vi{constructor(t,r,n=!1){this.mousedown=t=>{this.startMouse(e.e({},t,{ctrlKey:!0,preventDefault:()=>t.preventDefault()}),o.mousePos(this.element,t)),o.addEventListener(window,"mousemove",this.mousemove),o.addEventListener(window,"mouseup",this.mouseup)},this.mousemove=t=>{this.moveMouse(t,o.mousePos(this.element,t))},this.mouseup=t=>{this.mouseRotate.dragEnd(t),this.mousePitch&&this.mousePitch.dragEnd(t),this.offTemp()},this.touchstart=t=>{1!==t.targetTouches.length?this.reset():(this._startPos=this._lastPos=o.touchPos(this.element,t.targetTouches)[0],this.startTouch(t,this._startPos),o.addEventListener(window,"touchmove",this.touchmove,{passive:!1}),o.addEventListener(window,"touchend",this.touchend))},this.touchmove=t=>{1!==t.targetTouches.length?this.reset():(this._lastPos=o.touchPos(this.element,t.targetTouches)[0],this.moveTouch(t,this._lastPos))},this.touchend=t=>{0===t.targetTouches.length&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),this.touchRotate.reset(),this.touchPitch&&this.touchPitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()},this._clickTolerance=10;let i=t.dragRotate._mouseRotate.getClickTolerance(),a=t.dragRotate._mousePitch.getClickTolerance();this.element=r,this.mouseRotate=Jn({clickTolerance:i,enable:!0}),this.touchRotate=(({enable:t,clickTolerance:e,bearingDegreesPerPixelMoved:r=.8})=>{let n=new $n;return new Zn({clickTolerance:e,move:(t,e)=>({bearingDelta:(e.x-t.x)*r}),moveStateManager:n,enable:t,assignEvents:Ni})})({clickTolerance:i,enable:!0}),this.map=t,n&&(this.mousePitch=Qn({clickTolerance:a,enable:!0}),this.touchPitch=(({enable:t,clickTolerance:e,pitchDegreesPerPixelMoved:r=-.5})=>{let n=new $n;return new Zn({clickTolerance:e,move:(t,e)=>({pitchDelta:(e.y-t.y)*r}),moveStateManager:n,enable:t,assignEvents:Ni})})({clickTolerance:a,enable:!0})),o.addEventListener(r,"mousedown",this.mousedown),o.addEventListener(r,"touchstart",this.touchstart,{passive:!1}),o.addEventListener(r,"touchcancel",this.reset)}startMouse(t,e){this.mouseRotate.dragStart(t,e),this.mousePitch&&this.mousePitch.dragStart(t,e),o.disableDrag()}startTouch(t,e){this.touchRotate.dragStart(t,e),this.touchPitch&&this.touchPitch.dragStart(t,e),o.disableDrag()}moveMouse(t,e){let r=this.map,{bearingDelta:n}=this.mouseRotate.dragMove(t,e)||{};if(n&&r.setBearing(r.getBearing()+n),this.mousePitch){let{pitchDelta:n}=this.mousePitch.dragMove(t,e)||{};n&&r.setPitch(r.getPitch()+n)}}moveTouch(t,e){let r=this.map,{bearingDelta:n}=this.touchRotate.dragMove(t,e)||{};if(n&&r.setBearing(r.getBearing()+n),this.touchPitch){let{pitchDelta:n}=this.touchPitch.dragMove(t,e)||{};n&&r.setPitch(r.getPitch()+n)}}off(){let t=this.element;o.removeEventListener(t,"mousedown",this.mousedown),o.removeEventListener(t,"touchstart",this.touchstart,{passive:!1}),o.removeEventListener(window,"touchmove",this.touchmove,{passive:!1}),o.removeEventListener(window,"touchend",this.touchend),o.removeEventListener(t,"touchcancel",this.reset),this.offTemp()}offTemp(){o.enableDrag(),o.removeEventListener(window,"mousemove",this.mousemove),o.removeEventListener(window,"mouseup",this.mouseup),o.removeEventListener(window,"touchmove",this.touchmove,{passive:!1}),o.removeEventListener(window,"touchend",this.touchend)}}function qi(t,r,n){let i=new e.N(t.lng,t.lat);if(t=new e.N(t.lng,t.lat),r){let i=new e.N(t.lng-360,t.lat),a=new e.N(t.lng+360,t.lat),o=n.locationPoint(t).distSqr(r);n.locationPoint(i).distSqr(r)180;){let e=n.locationPoint(t);if(e.x>=0&&e.y>=0&&e.x<=n.width&&e.y<=n.height)break;t.lng>n.center.lng?t.lng-=360:t.lng+=360}return t.lng!==i.lng&&n.locationPoint(t).y>n.height/2-n.getHorizon()?t:i}let Hi={center:"translate(-50%,-50%)",top:"translate(-50%,0)","top-left":"translate(0,0)","top-right":"translate(-100%,0)",bottom:"translate(-50%,-100%)","bottom-left":"translate(0,-100%)","bottom-right":"translate(-100%,-100%)",left:"translate(0,-50%)",right:"translate(-100%,-50%)"};function Gi(t,e,r){let n=t.classList;for(let t in Hi)n.remove(`maplibregl-${r}-anchor-${t}`);n.add(`maplibregl-${r}-anchor-${e}`)}class Wi extends e.E{constructor(t){if(super(),this._onKeyPress=t=>{let e=t.code,r=t.charCode||t.keyCode;"Space"!==e&&"Enter"!==e&&32!==r&&13!==r||this.togglePopup()},this._onMapClick=t=>{let e=t.originalEvent.target,r=this._element;this._popup&&(e===r||r.contains(e))&&this.togglePopup()},this._update=t=>{var e;if(!this._map)return;let r=this._map.loaded()&&!this._map.isMoving();("terrain"===t?.type||"render"===t?.type&&!r)&&this._map.once("render",this._update),this._lngLat=this._map.transform.renderWorldCopies?qi(this._lngLat,this._flatPos,this._map.transform):null===(e=this._lngLat)||void 0===e?void 0:e.wrap(),this._flatPos=this._pos=this._map.project(this._lngLat)._add(this._offset),this._map.terrain&&(this._flatPos=this._map.transform.locationPoint(this._lngLat)._add(this._offset));let n="";"viewport"===this._rotationAlignment||"auto"===this._rotationAlignment?n=`rotateZ(${this._rotation}deg)`:"map"===this._rotationAlignment&&(n=`rotateZ(${this._rotation-this._map.getBearing()}deg)`);let i="";"viewport"===this._pitchAlignment||"auto"===this._pitchAlignment?i="rotateX(0deg)":"map"===this._pitchAlignment&&(i=`rotateX(${this._map.getPitch()}deg)`),this._subpixelPositioning||t&&"moveend"!==t.type||(this._pos=this._pos.round()),o.setTransform(this._element,`${Hi[this._anchor]} translate(${this._pos.x}px, ${this._pos.y}px) ${i} ${n}`),a.frameAsync(new AbortController).then((()=>{this._updateOpacity(t&&"moveend"===t.type)})).catch((()=>{}))},this._onMove=t=>{if(!this._isDragging){let e=this._clickTolerance||this._map._clickTolerance;this._isDragging=t.point.dist(this._pointerdownPos)>=e}this._isDragging&&(this._pos=t.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents="none","pending"===this._state&&(this._state="active",this.fire(new e.k("dragstart"))),this.fire(new e.k("drag")))},this._onUp=()=>{this._element.style.pointerEvents="auto",this._positionDelta=null,this._pointerdownPos=null,this._isDragging=!1,this._map.off("mousemove",this._onMove),this._map.off("touchmove",this._onMove),"active"===this._state&&this.fire(new e.k("dragend")),this._state="inactive"},this._addDragHandler=t=>{this._element.contains(t.originalEvent.target)&&(t.preventDefault(),this._positionDelta=t.point.sub(this._pos).add(this._offset),this._pointerdownPos=t.point,this._state="pending",this._map.on("mousemove",this._onMove),this._map.on("touchmove",this._onMove),this._map.once("mouseup",this._onUp),this._map.once("touchend",this._onUp))},this._anchor=t&&t.anchor||"center",this._color=t&&t.color||"#3FB1CE",this._scale=t&&t.scale||1,this._draggable=t&&t.draggable||!1,this._clickTolerance=t&&t.clickTolerance||0,this._subpixelPositioning=t&&t.subpixelPositioning||!1,this._isDragging=!1,this._state="inactive",this._rotation=t&&t.rotation||0,this._rotationAlignment=t&&t.rotationAlignment||"auto",this._pitchAlignment=t&&t.pitchAlignment&&"auto"!==t.pitchAlignment?t.pitchAlignment:this._rotationAlignment,this.setOpacity(),this.setOpacity(t?.opacity,t?.opacityWhenCovered),t&&t.element)this._element=t.element,this._offset=e.P.convert(t&&t.offset||[0,0]);else{this._defaultMarker=!0,this._element=o.create("div");let r=o.createNS("http://www.w3.org/2000/svg","svg"),n=41,i=27;r.setAttributeNS(null,"display","block"),r.setAttributeNS(null,"height",`${n}px`),r.setAttributeNS(null,"width",`${i}px`),r.setAttributeNS(null,"viewBox",`0 0 ${i} ${n}`);let a=o.createNS("http://www.w3.org/2000/svg","g");a.setAttributeNS(null,"stroke","none"),a.setAttributeNS(null,"stroke-width","1"),a.setAttributeNS(null,"fill","none"),a.setAttributeNS(null,"fill-rule","evenodd");let s=o.createNS("http://www.w3.org/2000/svg","g");s.setAttributeNS(null,"fill-rule","nonzero");let l=o.createNS("http://www.w3.org/2000/svg","g");l.setAttributeNS(null,"transform","translate(3.0, 29.0)"),l.setAttributeNS(null,"fill","#000000");let c=[{rx:"10.5",ry:"5.25002273"},{rx:"10.5",ry:"5.25002273"},{rx:"9.5",ry:"4.77275007"},{rx:"8.5",ry:"4.29549936"},{rx:"7.5",ry:"3.81822308"},{rx:"6.5",ry:"3.34094679"},{rx:"5.5",ry:"2.86367051"},{rx:"4.5",ry:"2.38636864"}];for(let t of c){let e=o.createNS("http://www.w3.org/2000/svg","ellipse");e.setAttributeNS(null,"opacity","0.04"),e.setAttributeNS(null,"cx","10.5"),e.setAttributeNS(null,"cy","5.80029008"),e.setAttributeNS(null,"rx",t.rx),e.setAttributeNS(null,"ry",t.ry),l.appendChild(e)}let u=o.createNS("http://www.w3.org/2000/svg","g");u.setAttributeNS(null,"fill",this._color);let h=o.createNS("http://www.w3.org/2000/svg","path");h.setAttributeNS(null,"d","M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z"),u.appendChild(h);let f=o.createNS("http://www.w3.org/2000/svg","g");f.setAttributeNS(null,"opacity","0.25"),f.setAttributeNS(null,"fill","#000000");let p=o.createNS("http://www.w3.org/2000/svg","path");p.setAttributeNS(null,"d","M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 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g=o.createNS("http://www.w3.org/2000/svg","circle");g.setAttributeNS(null,"fill","#000000"),g.setAttributeNS(null,"opacity","0.25"),g.setAttributeNS(null,"cx","5.5"),g.setAttributeNS(null,"cy","5.5"),g.setAttributeNS(null,"r","5.4999962");let y=o.createNS("http://www.w3.org/2000/svg","circle");y.setAttributeNS(null,"fill","#FFFFFF"),y.setAttributeNS(null,"cx","5.5"),y.setAttributeNS(null,"cy","5.5"),y.setAttributeNS(null,"r","5.4999962"),m.appendChild(g),m.appendChild(y),s.appendChild(l),s.appendChild(u),s.appendChild(f),s.appendChild(d),s.appendChild(m),r.appendChild(s),r.setAttributeNS(null,"height",n*this._scale+"px"),r.setAttributeNS(null,"width",i*this._scale+"px"),this._element.appendChild(r),this._offset=e.P.convert(t&&t.offset||[0,-14])}if(this._element.classList.add("maplibregl-marker"),this._element.addEventListener("dragstart",(t=>{t.preventDefault()})),this._element.addEventListener("mousedown",(t=>{t.preventDefault()})),Gi(this._element,this._anchor,"marker"),t&&t.className)for(let e of t.className.split(" "))this._element.classList.add(e);this._popup=null}addTo(t){return this.remove(),this._map=t,this._element.setAttribute("aria-label",t._getUIString("Marker.Title")),t.getCanvasContainer().appendChild(this._element),t.on("move",this._update),t.on("moveend",this._update),t.on("terrain",this._update),this.setDraggable(this._draggable),this._update(),this._map.on("click",this._onMapClick),this}remove(){return this._opacityTimeout&&(clearTimeout(this._opacityTimeout),delete this._opacityTimeout),this._map&&(this._map.off("click",this._onMapClick),this._map.off("move",this._update),this._map.off("moveend",this._update),this._map.off("terrain",this._update),this._map.off("mousedown",this._addDragHandler),this._map.off("touchstart",this._addDragHandler),this._map.off("mouseup",this._onUp),this._map.off("touchend",this._onUp),this._map.off("mousemove",this._onMove),this._map.off("touchmove",this._onMove),delete this._map),o.remove(this._element),this._popup&&this._popup.remove(),this}getLngLat(){return this._lngLat}setLngLat(t){return this._lngLat=e.N.convert(t),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this}getElement(){return this._element}setPopup(t){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener("keypress",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute("tabindex")),t){if(!("offset"in t.options)){let e=Math.abs(13.5)/Math.SQRT2;t.options.offset=this._defaultMarker?{top:[0,0],"top-left":[0,0],"top-right":[0,0],bottom:[0,-38.1],"bottom-left":[e,-1*(24.6+e)],"bottom-right":[-e,-1*(24.6+e)],left:[13.5,-24.6],right:[-13.5,-24.6]}:this._offset}this._popup=t,this._originalTabIndex=this._element.getAttribute("tabindex"),this._originalTabIndex||this._element.setAttribute("tabindex","0"),this._element.addEventListener("keypress",this._onKeyPress)}return this}setSubpixelPositioning(t){return this._subpixelPositioning=t,this}getPopup(){return this._popup}togglePopup(){let t=this._popup;return this._element.style.opacity===this._opacityWhenCovered?this:t?(t.isOpen()?t.remove():(t.setLngLat(this._lngLat),t.addTo(this._map)),this):this}_updateOpacity(t=!1){var r,n;if(null===(r=this._map)||void 0===r||!r.terrain)return void(this._element.style.opacity!==this._opacity&&(this._element.style.opacity=this._opacity));if(t)this._opacityTimeout=null;else{if(this._opacityTimeout)return;this._opacityTimeout=setTimeout((()=>{this._opacityTimeout=null}),100)}let i=this._map,a=i.terrain.depthAtPoint(this._pos),o=i.terrain.getElevationForLngLatZoom(this._lngLat,i.transform.tileZoom);if(i.transform.lngLatToCameraDepth(this._lngLat,o)-a<.006)return void(this._element.style.opacity=this._opacity);let s=-this._offset.y/i.transform._pixelPerMeter,l=Math.sin(i.getPitch()*Math.PI/180)*s,c=i.terrain.depthAtPoint(new e.P(this._pos.x,this._pos.y-this._offset.y)),u=i.transform.lngLatToCameraDepth(this._lngLat,o+l)-c>.006;!(null===(n=this._popup)||void 0===n)&&n.isOpen()&&u&&this._popup.remove(),this._element.style.opacity=u?this._opacityWhenCovered:this._opacity}getOffset(){return this._offset}setOffset(t){return this._offset=e.P.convert(t),this._update(),this}addClassName(t){this._element.classList.add(t)}removeClassName(t){this._element.classList.remove(t)}toggleClassName(t){return this._element.classList.toggle(t)}setDraggable(t){return this._draggable=!!t,this._map&&(t?(this._map.on("mousedown",this._addDragHandler),this._map.on("touchstart",this._addDragHandler)):(this._map.off("mousedown",this._addDragHandler),this._map.off("touchstart",this._addDragHandler))),this}isDraggable(){return this._draggable}setRotation(t){return this._rotation=t||0,this._update(),this}getRotation(){return this._rotation}setRotationAlignment(t){return this._rotationAlignment=t||"auto",this._update(),this}getRotationAlignment(){return this._rotationAlignment}setPitchAlignment(t){return this._pitchAlignment=t&&"auto"!==t?t:this._rotationAlignment,this._update(),this}getPitchAlignment(){return this._pitchAlignment}setOpacity(t,e){return void 0===t&&void 0===e&&(this._opacity="1",this._opacityWhenCovered="0.2"),void 0!==t&&(this._opacity=t),void 0!==e&&(this._opacityWhenCovered=e),this._map&&this._updateOpacity(!0),this}}let Zi={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0},Yi=0,Xi=!1,$i={maxWidth:100,unit:"metric"};function Ki(t,e,r){let n=r&&r.maxWidth||100,i=t._container.clientHeight/2,a=t.unproject([0,i]),o=t.unproject([n,i]),s=a.distanceTo(o);if(r&&"imperial"===r.unit){let r=3.2808*s;r>5280?Ji(e,n,r/5280,t._getUIString("ScaleControl.Miles")):Ji(e,n,r,t._getUIString("ScaleControl.Feet"))}else r&&"nautical"===r.unit?Ji(e,n,s/1852,t._getUIString("ScaleControl.NauticalMiles")):s>=1e3?Ji(e,n,s/1e3,t._getUIString("ScaleControl.Kilometers")):Ji(e,n,s,t._getUIString("ScaleControl.Meters"))}function Ji(t,e,r,n){let i=function(t){let e=Math.pow(10,`${Math.floor(t)}`.length-1),r=t/e;return r=r>=10?10:r>=5?5:r>=3?3:r>=2?2:r>=1?1:function(t){let e=Math.pow(10,Math.ceil(-Math.log(t)/Math.LN10));return Math.round(t*e)/e}(r),e*r}(r);t.style.width=e*(i/r)+"px",t.innerHTML=`${i} ${n}`}let Qi={closeButton:!0,closeOnClick:!0,focusAfterOpen:!0,className:"",maxWidth:"240px",subpixelPositioning:!1},ta=["a[href]","[tabindex]:not([tabindex='-1'])","[contenteditable]:not([contenteditable='false'])","button:not([disabled])","input:not([disabled])","select:not([disabled])","textarea:not([disabled])"].join(", ");function ea(t){if(t){if("number"==typeof t){let r=Math.round(Math.abs(t)/Math.SQRT2);return{center:new e.P(0,0),top:new e.P(0,t),"top-left":new e.P(r,r),"top-right":new e.P(-r,r),bottom:new e.P(0,-t),"bottom-left":new e.P(r,-r),"bottom-right":new e.P(-r,-r),left:new e.P(t,0),right:new e.P(-t,0)}}if(t instanceof e.P||Array.isArray(t)){let r=e.P.convert(t);return{center:r,top:r,"top-left":r,"top-right":r,bottom:r,"bottom-left":r,"bottom-right":r,left:r,right:r}}return{center:e.P.convert(t.center||[0,0]),top:e.P.convert(t.top||[0,0]),"top-left":e.P.convert(t["top-left"]||[0,0]),"top-right":e.P.convert(t["top-right"]||[0,0]),bottom:e.P.convert(t.bottom||[0,0]),"bottom-left":e.P.convert(t["bottom-left"]||[0,0]),"bottom-right":e.P.convert(t["bottom-right"]||[0,0]),left:e.P.convert(t.left||[0,0]),right:e.P.convert(t.right||[0,0])}}return ea(new e.P(0,0))}let ra=r;t.AJAXError=e.bh,t.Evented=e.E,t.LngLat=e.N,t.MercatorCoordinate=e.Z,t.Point=e.P,t.addProtocol=e.bi,t.config=e.a,t.removeProtocol=e.bj,t.AttributionControl=Si,t.BoxZoomHandler=Vn,t.CanvasSource=rt,t.CooperativeGesturesHandler=_i,t.DoubleClickZoomHandler=di,t.DragPanHandler=yi,t.DragRotateHandler=vi,t.EdgeInsets=Tn,t.FullscreenControl=class extends e.E{constructor(t={}){super(),this._onFullscreenChange=()=>{var t;let e=window.document.fullscreenElement||window.document.mozFullScreenElement||window.document.webkitFullscreenElement||window.document.msFullscreenElement;for(;null!==(t=e?.shadowRoot)&&void 0!==t&&t.fullscreenElement;)e=e.shadowRoot.fullscreenElement;e===this._container!==this._fullscreen&&this._handleFullscreenChange()},this._onClickFullscreen=()=>{this._isFullscreen()?this._exitFullscreen():this._requestFullscreen()},this._fullscreen=!1,t&&t.container&&(t.container instanceof HTMLElement?this._container=t.container:e.w("Full screen control 'container' must be a DOM element.")),"onfullscreenchange"in document?this._fullscreenchange="fullscreenchange":"onmozfullscreenchange"in document?this._fullscreenchange="mozfullscreenchange":"onwebkitfullscreenchange"in document?this._fullscreenchange="webkitfullscreenchange":"onmsfullscreenchange"in document&&(this._fullscreenchange="MSFullscreenChange")}onAdd(t){return this._map=t,this._container||(this._container=this._map.getContainer()),this._controlContainer=o.create("div","maplibregl-ctrl maplibregl-ctrl-group"),this._setupUI(),this._controlContainer}onRemove(){o.remove(this._controlContainer),this._map=null,window.document.removeEventListener(this._fullscreenchange,this._onFullscreenChange)}_setupUI(){let t=this._fullscreenButton=o.create("button","maplibregl-ctrl-fullscreen",this._controlContainer);o.create("span","maplibregl-ctrl-icon",t).setAttribute("aria-hidden","true"),t.type="button",this._updateTitle(),this._fullscreenButton.addEventListener("click",this._onClickFullscreen),window.document.addEventListener(this._fullscreenchange,this._onFullscreenChange)}_updateTitle(){let t=this._getTitle();this._fullscreenButton.setAttribute("aria-label",t),this._fullscreenButton.title=t}_getTitle(){return this._map._getUIString(this._isFullscreen()?"FullscreenControl.Exit":"FullscreenControl.Enter")}_isFullscreen(){return this._fullscreen}_handleFullscreenChange(){this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle("maplibregl-ctrl-shrink"),this._fullscreenButton.classList.toggle("maplibregl-ctrl-fullscreen"),this._updateTitle(),this._fullscreen?(this.fire(new e.k("fullscreenstart")),this._prevCooperativeGesturesEnabled=this._map.cooperativeGestures.isEnabled(),this._map.cooperativeGestures.disable()):(this.fire(new e.k("fullscreenend")),this._prevCooperativeGesturesEnabled&&this._map.cooperativeGestures.enable())}_exitFullscreen(){window.document.exitFullscreen?window.document.exitFullscreen():window.document.mozCancelFullScreen?window.document.mozCancelFullScreen():window.document.msExitFullscreen?window.document.msExitFullscreen():window.document.webkitCancelFullScreen?window.document.webkitCancelFullScreen():this._togglePseudoFullScreen()}_requestFullscreen(){this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen?this._container.webkitRequestFullscreen():this._togglePseudoFullScreen()}_togglePseudoFullScreen(){this._container.classList.toggle("maplibregl-pseudo-fullscreen"),this._handleFullscreenChange(),this._map.resize()}},t.GeoJSONSource=J,t.GeolocateControl=class extends e.E{constructor(t){super(),this._onSuccess=t=>{if(this._map){if(this._isOutOfMapMaxBounds(t))return this._setErrorState(),this.fire(new e.k("outofmaxbounds",t)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=t,this._watchState){case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-active");break;case"BACKGROUND":case"BACKGROUND_ERROR":this._watchState="BACKGROUND",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-background");break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}this.options.showUserLocation&&"OFF"!==this._watchState&&this._updateMarker(t),this.options.trackUserLocation&&"ACTIVE_LOCK"!==this._watchState||this._updateCamera(t),this.options.showUserLocation&&this._dotElement.classList.remove("maplibregl-user-location-dot-stale"),this.fire(new e.k("geolocate",t)),this._finish()}},this._updateCamera=t=>{let r=new e.N(t.coords.longitude,t.coords.latitude),n=t.coords.accuracy,i=this._map.getBearing(),a=e.e({bearing:i},this.options.fitBoundsOptions),o=Z.fromLngLat(r,n);this._map.fitBounds(o,a,{geolocateSource:!0})},this._updateMarker=t=>{if(t){let r=new e.N(t.coords.longitude,t.coords.latitude);this._accuracyCircleMarker.setLngLat(r).addTo(this._map),this._userLocationDotMarker.setLngLat(r).addTo(this._map),this._accuracy=t.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},this._onZoom=()=>{this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},this._onError=t=>{if(this._map){if(this.options.trackUserLocation)if(1===t.code){this._watchState="OFF",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background-error"),this._geolocateButton.disabled=!0;let t=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.title=t,this._geolocateButton.setAttribute("aria-label",t),void 0!==this._geolocationWatchID&&this._clearWatch()}else{if(3===t.code&&Xi)return;this._setErrorState()}"OFF"!==this._watchState&&this.options.showUserLocation&&this._dotElement.classList.add("maplibregl-user-location-dot-stale"),this.fire(new e.k("error",t)),this._finish()}},this._finish=()=>{this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},this._setupUI=()=>{this._map&&(this._container.addEventListener("contextmenu",(t=>t.preventDefault())),this._geolocateButton=o.create("button","maplibregl-ctrl-geolocate",this._container),o.create("span","maplibregl-ctrl-icon",this._geolocateButton).setAttribute("aria-hidden","true"),this._geolocateButton.type="button",this._geolocateButton.disabled=!0)},this._finishSetupUI=t=>{if(this._map){if(!1===t){e.w("Geolocation support is not available so the GeolocateControl will be disabled.");let t=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.disabled=!0,this._geolocateButton.title=t,this._geolocateButton.setAttribute("aria-label",t)}else{let t=this._map._getUIString("GeolocateControl.FindMyLocation");this._geolocateButton.disabled=!1,this._geolocateButton.title=t,this._geolocateButton.setAttribute("aria-label",t)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute("aria-pressed","false"),this._watchState="OFF"),this.options.showUserLocation&&(this._dotElement=o.create("div","maplibregl-user-location-dot"),this._userLocationDotMarker=new Wi({element:this._dotElement}),this._circleElement=o.create("div","maplibregl-user-location-accuracy-circle"),this._accuracyCircleMarker=new Wi({element:this._circleElement,pitchAlignment:"map"}),this.options.trackUserLocation&&(this._watchState="OFF"),this._map.on("zoom",this._onZoom)),this._geolocateButton.addEventListener("click",(()=>this.trigger())),this._setup=!0,this.options.trackUserLocation&&this._map.on("movestart",(t=>{t.geolocateSource||"ACTIVE_LOCK"!==this._watchState||t.originalEvent&&"resize"===t.originalEvent.type||(this._watchState="BACKGROUND",this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active"),this.fire(new e.k("trackuserlocationend")),this.fire(new e.k("userlocationlostfocus")))}))}},this.options=e.e({},Zi,t)}onAdd(t){return this._map=t,this._container=o.create("div","maplibregl-ctrl maplibregl-ctrl-group"),this._setupUI(),function(){return e._(this,arguments,void 0,(function*(t=!1){if(void 0!==Ri&&!t)return Ri;if(void 0===window.navigator.permissions)return Ri=!!window.navigator.geolocation,Ri;try{Ri="denied"!==(yield window.navigator.permissions.query({name:"geolocation"})).state}catch{Ri=!!window.navigator.geolocation}return Ri}))}().then((t=>this._finishSetupUI(t))),this._container}onRemove(){void 0!==this._geolocationWatchID&&(window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),o.remove(this._container),this._map.off("zoom",this._onZoom),this._map=void 0,Yi=0,Xi=!1}_isOutOfMapMaxBounds(t){let e=this._map.getMaxBounds(),r=t.coords;return e&&(r.longitudee.getEast()||r.latitudee.getNorth())}_setErrorState(){switch(this._watchState){case"WAITING_ACTIVE":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-active-error");break;case"ACTIVE_LOCK":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-waiting");break;case"BACKGROUND":this._watchState="BACKGROUND_ERROR",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-waiting");break;case"ACTIVE_ERROR":break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}}_updateCircleRadius(){let t=this._map.getBounds(),e=t.getSouthEast(),r=t.getNorthEast(),n=e.distanceTo(r),i=Math.ceil(this._accuracy/(n/this._map._container.clientHeight)*2);this._circleElement.style.width=`${i}px`,this._circleElement.style.height=`${i}px`}trigger(){if(!this._setup)return e.w("Geolocate control triggered before added to a map"),!1;if(this.options.trackUserLocation){switch(this._watchState){case"OFF":this._watchState="WAITING_ACTIVE",this.fire(new e.k("trackuserlocationstart"));break;case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":case"BACKGROUND_ERROR":Yi--,Xi=!1,this._watchState="OFF",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background-error"),this.fire(new e.k("trackuserlocationend"));break;case"BACKGROUND":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new e.k("trackuserlocationstart")),this.fire(new e.k("userlocationfocus"));break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}switch(this._watchState){case"WAITING_ACTIVE":this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-active");break;case"ACTIVE_LOCK":this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-active");break;case"OFF":break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}if("OFF"===this._watchState&&void 0!==this._geolocationWatchID)this._clearWatch();else if(void 0===this._geolocationWatchID){let t;this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","true"),Yi++,Yi>1?(t={maximumAge:6e5,timeout:0},Xi=!0):(t=this.options.positionOptions,Xi=!1),this._geolocationWatchID=window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,t)}}else window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0}_clearWatch(){window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","false"),this.options.showUserLocation&&this._updateMarker(null)}},t.Hash=Sn,t.ImageSource=tt,t.KeyboardHandler=ui,t.LngLatBounds=Z,t.LogoControl=Ei,t.Map=class extends Ai{constructor(t){e.bf.mark(e.bg.create);let r=Object.assign(Object.assign({},ji),t);if(null!=r.minZoom&&null!=r.maxZoom&&r.minZoom>r.maxZoom)throw new Error("maxZoom must be greater than or equal to minZoom");if(null!=r.minPitch&&null!=r.maxPitch&&r.minPitch>r.maxPitch)throw new Error("maxPitch must be greater than or equal to minPitch");if(null!=r.minPitch&&r.minPitch<0)throw new Error("minPitch must be greater than or equal to 0");if(null!=r.maxPitch&&r.maxPitch>85)throw new Error("maxPitch must be less than or equal to 85");if(super(new An(r.minZoom,r.maxZoom,r.minPitch,r.maxPitch,r.renderWorldCopies),{bearingSnap:r.bearingSnap}),this._idleTriggered=!1,this._crossFadingFactor=1,this._renderTaskQueue=new Ci,this._controls=[],this._mapId=e.a4(),this._contextLost=t=>{t.preventDefault(),this._frameRequest&&(this._frameRequest.abort(),this._frameRequest=null),this.fire(new e.k("webglcontextlost",{originalEvent:t}))},this._contextRestored=t=>{this._setupPainter(),this.resize(),this._update(),this.fire(new e.k("webglcontextrestored",{originalEvent:t}))},this._onMapScroll=t=>{if(t.target===this._container)return this._container.scrollTop=0,this._container.scrollLeft=0,!1},this._onWindowOnline=()=>{this._update()},this._interactive=r.interactive,this._maxTileCacheSize=r.maxTileCacheSize,this._maxTileCacheZoomLevels=r.maxTileCacheZoomLevels,this._failIfMajorPerformanceCaveat=!0===r.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=!0===r.preserveDrawingBuffer,this._antialias=!0===r.antialias,this._trackResize=!0===r.trackResize,this._bearingSnap=r.bearingSnap,this._refreshExpiredTiles=!0===r.refreshExpiredTiles,this._fadeDuration=r.fadeDuration,this._crossSourceCollisions=!0===r.crossSourceCollisions,this._collectResourceTiming=!0===r.collectResourceTiming,this._locale=Object.assign(Object.assign({},Fi),r.locale),this._clickTolerance=r.clickTolerance,this._overridePixelRatio=r.pixelRatio,this._maxCanvasSize=r.maxCanvasSize,this.transformCameraUpdate=r.transformCameraUpdate,this.cancelPendingTileRequestsWhileZooming=!0===r.cancelPendingTileRequestsWhileZooming,this._imageQueueHandle=p.addThrottleControl((()=>this.isMoving())),this._requestManager=new d(r.transformRequest),"string"==typeof r.container){if(this._container=document.getElementById(r.container),!this._container)throw new Error(`Container '${r.container}' not found.`)}else{if(!(r.container instanceof HTMLElement))throw new Error("Invalid type: 'container' must be a String or HTMLElement.");this._container=r.container}if(r.maxBounds&&this.setMaxBounds(r.maxBounds),this._setupContainer(),this._setupPainter(),this.on("move",(()=>this._update(!1))).on("moveend",(()=>this._update(!1))).on("zoom",(()=>this._update(!0))).on("terrain",(()=>{this.painter.terrainFacilitator.dirty=!0,this._update(!0)})).once("idle",(()=>{this._idleTriggered=!0})),typeof window<"u"){addEventListener("online",this._onWindowOnline,!1);let t=!1,e=Mn((t=>{this._trackResize&&!this._removed&&(this.resize(t),this.redraw())}),50);this._resizeObserver=new ResizeObserver((r=>{t?e(r):t=!0})),this._resizeObserver.observe(this._container)}this.handlers=new ki(this,r),this._hash=r.hash&&new Sn("string"==typeof r.hash&&r.hash||void 0).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:r.center,zoom:r.zoom,bearing:r.bearing,pitch:r.pitch}),r.bounds&&(this.resize(),this.fitBounds(r.bounds,e.e({},r.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=r.localIdeographFontFamily,this._validateStyle=r.validateStyle,r.style&&this.setStyle(r.style,{localIdeographFontFamily:r.localIdeographFontFamily}),r.attributionControl&&this.addControl(new Si("boolean"==typeof r.attributionControl?void 0:r.attributionControl)),r.maplibreLogo&&this.addControl(new Ei,r.logoPosition),this.on("style.load",(()=>{this.transform.unmodified&&this.jumpTo(this.style.stylesheet)})),this.on("data",(t=>{this._update("style"===t.dataType),this.fire(new e.k(`${t.dataType}data`,t))})),this.on("dataloading",(t=>{this.fire(new e.k(`${t.dataType}dataloading`,t))})),this.on("dataabort",(t=>{this.fire(new e.k("sourcedataabort",t))}))}_getMapId(){return this._mapId}addControl(t,r){if(void 0===r&&(r=t.getDefaultPosition?t.getDefaultPosition():"top-right"),!t||!t.onAdd)return this.fire(new e.j(new Error("Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.")));let n=t.onAdd(this);this._controls.push(t);let i=this._controlPositions[r];return-1!==r.indexOf("bottom")?i.insertBefore(n,i.firstChild):i.appendChild(n),this}removeControl(t){if(!t||!t.onRemove)return this.fire(new e.j(new Error("Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.")));let r=this._controls.indexOf(t);return r>-1&&this._controls.splice(r,1),t.onRemove(this),this}hasControl(t){return this._controls.indexOf(t)>-1}calculateCameraOptionsFromTo(t,e,r,n){return null==n&&this.terrain&&(n=this.terrain.getElevationForLngLatZoom(r,this.transform.tileZoom)),super.calculateCameraOptionsFromTo(t,e,r,n)}resize(t){var r;let n=this._containerDimensions(),i=n[0],a=n[1],o=this._getClampedPixelRatio(i,a);if(this._resizeCanvas(i,a,o),this.painter.resize(i,a,o),this.painter.overLimit()){let t=this.painter.context.gl;this._maxCanvasSize=[t.drawingBufferWidth,t.drawingBufferHeight];let e=this._getClampedPixelRatio(i,a);this._resizeCanvas(i,a,e),this.painter.resize(i,a,e)}this.transform.resize(i,a),null===(r=this._requestedCameraState)||void 0===r||r.resize(i,a);let s=!this._moving;return s&&(this.stop(),this.fire(new e.k("movestart",t)).fire(new e.k("move",t))),this.fire(new e.k("resize",t)),s&&this.fire(new e.k("moveend",t)),this}_getClampedPixelRatio(t,e){let{0:r,1:n}=this._maxCanvasSize,i=this.getPixelRatio(),a=t*i,o=e*i;return Math.min(a>r?r/a:1,o>n?n/o:1)*i}getPixelRatio(){var t;return null!==(t=this._overridePixelRatio)&&void 0!==t?t:devicePixelRatio}setPixelRatio(t){this._overridePixelRatio=t,this.resize()}getBounds(){return this.transform.getBounds()}getMaxBounds(){return this.transform.getMaxBounds()}setMaxBounds(t){return this.transform.setMaxBounds(Z.convert(t)),this._update()}setMinZoom(t){if((t=t??-2)>=-2&&t<=this.transform.maxZoom)return this.transform.minZoom=t,this._update(),this.getZoom()=this.transform.minZoom)return this.transform.maxZoom=t,this._update(),this.getZoom()>t&&this.setZoom(t),this;throw new Error("maxZoom must be greater than the current minZoom")}getMaxZoom(){return this.transform.maxZoom}setMinPitch(t){if((t=t??0)<0)throw new Error("minPitch must be greater than or equal to 0");if(t>=0&&t<=this.transform.maxPitch)return this.transform.minPitch=t,this._update(),this.getPitch()85)throw new Error("maxPitch must be less than or equal to 85");if(t>=this.transform.minPitch)return this.transform.maxPitch=t,this._update(),this.getPitch()>t&&this.setPitch(t),this;throw new Error("maxPitch must be greater than the current minPitch")}getMaxPitch(){return this.transform.maxPitch}getRenderWorldCopies(){return this.transform.renderWorldCopies}setRenderWorldCopies(t){return this.transform.renderWorldCopies=t,this._update()}project(t){return this.transform.locationPoint(e.N.convert(t),this.style&&this.terrain)}unproject(t){return this.transform.pointLocation(e.P.convert(t),this.terrain)}isMoving(){var t;return this._moving||(null===(t=this.handlers)||void 0===t?void 0:t.isMoving())}isZooming(){var t;return this._zooming||(null===(t=this.handlers)||void 0===t?void 0:t.isZooming())}isRotating(){var t;return this._rotating||(null===(t=this.handlers)||void 0===t?void 0:t.isRotating())}_createDelegatedListener(t,e,r){if("mouseenter"===t||"mouseover"===t){let n=!1;return{layers:e,listener:r,delegates:{mousemove:i=>{let a=e.filter((t=>this.getLayer(t))),o=0!==a.length?this.queryRenderedFeatures(i.point,{layers:a}):[];o.length?n||(n=!0,r.call(this,new Rn(t,this,i.originalEvent,{features:o}))):n=!1},mouseout:()=>{n=!1}}}}if("mouseleave"===t||"mouseout"===t){let n=!1;return{layers:e,listener:r,delegates:{mousemove:i=>{let a=e.filter((t=>this.getLayer(t)));(0!==a.length?this.queryRenderedFeatures(i.point,{layers:a}):[]).length?n=!0:n&&(n=!1,r.call(this,new Rn(t,this,i.originalEvent)))},mouseout:e=>{n&&(n=!1,r.call(this,new Rn(t,this,e.originalEvent)))}}}}{let n=t=>{let n=e.filter((t=>this.getLayer(t))),i=0!==n.length?this.queryRenderedFeatures(t.point,{layers:n}):[];i.length&&(t.features=i,r.call(this,t),delete t.features)};return{layers:e,listener:r,delegates:{[t]:n}}}}_saveDelegatedListener(t,e){this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[t]=this._delegatedListeners[t]||[],this._delegatedListeners[t].push(e)}_removeDelegatedListener(t,e,r){if(!this._delegatedListeners||!this._delegatedListeners[t])return;let n=this._delegatedListeners[t];for(let t=0;te.includes(t)))){for(let t in i.delegates)this.off(t,i.delegates[t]);return void n.splice(t,1)}}}on(t,e,r){if(void 0===r)return super.on(t,e);let n=this._createDelegatedListener(t,"string"==typeof e?[e]:e,r);this._saveDelegatedListener(t,n);for(let t in n.delegates)this.on(t,n.delegates[t]);return this}once(t,e,r){if(void 0===r)return super.once(t,e);let n="string"==typeof e?[e]:e,i=this._createDelegatedListener(t,n,r);for(let e in i.delegates){let a=i.delegates[e];i.delegates[e]=(...e)=>{this._removeDelegatedListener(t,n,r),a(...e)}}this._saveDelegatedListener(t,i);for(let t in i.delegates)this.once(t,i.delegates[t]);return this}off(t,e,r){return void 0===r?super.off(t,e):(this._removeDelegatedListener(t,"string"==typeof e?[e]:e,r),this)}queryRenderedFeatures(t,r){if(!this.style)return[];let n,i=t instanceof e.P||Array.isArray(t),a=i?t:[[0,0],[this.transform.width,this.transform.height]];if(r=r||(i?{}:t)||{},a instanceof e.P||"number"==typeof a[0])n=[e.P.convert(a)];else{let t=e.P.convert(a[0]),r=e.P.convert(a[1]);n=[t,new e.P(r.x,t.y),r,new e.P(t.x,r.y),t]}return this.style.queryRenderedFeatures(n,r,this.transform)}querySourceFeatures(t,e){return this.style.querySourceFeatures(t,e)}setStyle(t,r){return!1!==(r=e.e({},{localIdeographFontFamily:this._localIdeographFontFamily,validate:this._validateStyle},r)).diff&&r.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&t?(this._diffStyle(t,r),this):(this._localIdeographFontFamily=r.localIdeographFontFamily,this._updateStyle(t,r))}setTransformRequest(t){return this._requestManager.setTransformRequest(t),this}_getUIString(t){let e=this._locale[t];if(null==e)throw new Error(`Missing UI string '${t}'`);return e}_updateStyle(t,e){if(e.transformStyle&&this.style&&!this.style._loaded)return void this.style.once("style.load",(()=>this._updateStyle(t,e)));let r=this.style&&e.transformStyle?this.style.serialize():void 0;return this.style&&(this.style.setEventedParent(null),this.style._remove(!t)),t?(this.style=new pe(this,e||{}),this.style.setEventedParent(this,{style:this.style}),"string"==typeof t?this.style.loadURL(t,e,r):this.style.loadJSON(t,e,r),this):(delete this.style,this)}_lazyInitEmptyStyle(){this.style||(this.style=new pe(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())}_diffStyle(t,r){if("string"==typeof t){let n=this._requestManager.transformRequest(t,"Style");e.h(n,new AbortController).then((t=>{this._updateDiff(t.data,r)})).catch((t=>{t&&this.fire(new e.j(t))}))}else"object"==typeof t&&this._updateDiff(t,r)}_updateDiff(t,r){try{this.style.setState(t,r)&&this._update(!0)}catch(n){e.w(`Unable to perform style diff: ${n.message||n.error||n}. Rebuilding the style from scratch.`),this._updateStyle(t,r)}}getStyle(){if(this.style)return this.style.serialize()}isStyleLoaded(){return this.style?this.style.loaded():e.w("There is no style added to the map.")}addSource(t,e){return this._lazyInitEmptyStyle(),this.style.addSource(t,e),this._update(!0)}isSourceLoaded(t){let r=this.style&&this.style.sourceCaches[t];if(void 0!==r)return r.loaded();this.fire(new e.j(new Error(`There is no source with ID '${t}'`)))}setTerrain(t){if(this.style._checkLoaded(),this._terrainDataCallback&&this.style.off("data",this._terrainDataCallback),t){let r=this.style.sourceCaches[t.source];if(!r)throw new Error(`cannot load terrain, because there exists no source with ID: ${t.source}`);null===this.terrain&&r.reload();for(let r in this.style._layers){let n=this.style._layers[r];"hillshade"===n.type&&n.source===t.source&&e.w("You are using the same source for a hillshade layer and for 3D terrain. Please consider using two separate sources to improve rendering quality.")}this.terrain=new Pi(this.painter,r,t),this.painter.renderToTexture=new Oi(this.painter,this.terrain),this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this.transform.elevation=this.terrain.getElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this._terrainDataCallback=e=>{"style"===e.dataType?this.terrain.sourceCache.freeRtt():"source"===e.dataType&&e.tile&&(e.sourceId!==t.source||this._elevationFreeze||(this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this.transform.elevation=this.terrain.getElevationForLngLatZoom(this.transform.center,this.transform.tileZoom)),this.terrain.sourceCache.freeRtt(e.tile.tileID))},this.style.on("data",this._terrainDataCallback)}else this.terrain&&this.terrain.sourceCache.destruct(),this.terrain=null,this.painter.renderToTexture&&this.painter.renderToTexture.destruct(),this.painter.renderToTexture=null,this.transform.minElevationForCurrentTile=0,this.transform.elevation=0;return this.fire(new e.k("terrain",{terrain:t})),this}getTerrain(){var t,e;return null!==(e=null===(t=this.terrain)||void 0===t?void 0:t.options)&&void 0!==e?e:null}areTilesLoaded(){let t=this.style&&this.style.sourceCaches;for(let e in t){let r=t[e]._tiles;for(let t in r){let e=r[t];if("loaded"!==e.state&&"errored"!==e.state)return!1}}return!0}removeSource(t){return this.style.removeSource(t),this._update(!0)}getSource(t){return this.style.getSource(t)}addImage(t,r,n={}){let{pixelRatio:i=1,sdf:o=!1,stretchX:s,stretchY:l,content:c,textFitWidth:u,textFitHeight:h}=n;if(this._lazyInitEmptyStyle(),!(r instanceof HTMLImageElement||e.b(r))){if(void 0===r.width||void 0===r.height)return this.fire(new e.j(new Error("Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`")));{let{width:n,height:a,data:f}=r,p=r;return this.style.addImage(t,{data:new e.R({width:n,height:a},new Uint8Array(f)),pixelRatio:i,stretchX:s,stretchY:l,content:c,textFitWidth:u,textFitHeight:h,sdf:o,version:0,userImage:p}),p.onAdd&&p.onAdd(this,t),this}}{let{width:n,height:f,data:p}=a.getImageData(r);this.style.addImage(t,{data:new e.R({width:n,height:f},p),pixelRatio:i,stretchX:s,stretchY:l,content:c,textFitWidth:u,textFitHeight:h,sdf:o,version:0})}}updateImage(t,r){let n=this.style.getImage(t);if(!n)return this.fire(new e.j(new Error("The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.")));let i=r instanceof HTMLImageElement||e.b(r)?a.getImageData(r):r,{width:o,height:s,data:l}=i;if(void 0===o||void 0===s)return this.fire(new e.j(new Error("Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`")));if(o!==n.data.width||s!==n.data.height)return this.fire(new e.j(new Error("The width and height of the updated image must be that same as the previous version of the image")));let c=!(r instanceof HTMLImageElement||e.b(r));return n.data.replace(l,c),this.style.updateImage(t,n),this}getImage(t){return this.style.getImage(t)}hasImage(t){return t?!!this.style.getImage(t):(this.fire(new e.j(new Error("Missing required image id"))),!1)}removeImage(t){this.style.removeImage(t)}loadImage(t){return p.getImage(this._requestManager.transformRequest(t,"Image"),new AbortController)}listImages(){return this.style.listImages()}addLayer(t,e){return this._lazyInitEmptyStyle(),this.style.addLayer(t,e),this._update(!0)}moveLayer(t,e){return this.style.moveLayer(t,e),this._update(!0)}removeLayer(t){return this.style.removeLayer(t),this._update(!0)}getLayer(t){return this.style.getLayer(t)}getLayersOrder(){return this.style.getLayersOrder()}setLayerZoomRange(t,e,r){return this.style.setLayerZoomRange(t,e,r),this._update(!0)}setFilter(t,e,r={}){return this.style.setFilter(t,e,r),this._update(!0)}getFilter(t){return this.style.getFilter(t)}setPaintProperty(t,e,r,n={}){return this.style.setPaintProperty(t,e,r,n),this._update(!0)}getPaintProperty(t,e){return this.style.getPaintProperty(t,e)}setLayoutProperty(t,e,r,n={}){return this.style.setLayoutProperty(t,e,r,n),this._update(!0)}getLayoutProperty(t,e){return this.style.getLayoutProperty(t,e)}setGlyphs(t,e={}){return this._lazyInitEmptyStyle(),this.style.setGlyphs(t,e),this._update(!0)}getGlyphs(){return this.style.getGlyphsUrl()}addSprite(t,e,r={}){return this._lazyInitEmptyStyle(),this.style.addSprite(t,e,r,(t=>{t||this._update(!0)})),this}removeSprite(t){return this._lazyInitEmptyStyle(),this.style.removeSprite(t),this._update(!0)}getSprite(){return this.style.getSprite()}setSprite(t,e={}){return this._lazyInitEmptyStyle(),this.style.setSprite(t,e,(t=>{t||this._update(!0)})),this}setLight(t,e={}){return this._lazyInitEmptyStyle(),this.style.setLight(t,e),this._update(!0)}getLight(){return this.style.getLight()}setSky(t){return this._lazyInitEmptyStyle(),this.style.setSky(t),this._update(!0)}getSky(){return this.style.getSky()}setFeatureState(t,e){return this.style.setFeatureState(t,e),this._update()}removeFeatureState(t,e){return this.style.removeFeatureState(t,e),this._update()}getFeatureState(t){return this.style.getFeatureState(t)}getContainer(){return this._container}getCanvasContainer(){return this._canvasContainer}getCanvas(){return this._canvas}_containerDimensions(){let t=0,e=0;return this._container&&(t=this._container.clientWidth||400,e=this._container.clientHeight||300),[t,e]}_setupContainer(){let t=this._container;t.classList.add("maplibregl-map");let e=this._canvasContainer=o.create("div","maplibregl-canvas-container",t);this._interactive&&e.classList.add("maplibregl-interactive"),this._canvas=o.create("canvas","maplibregl-canvas",e),this._canvas.addEventListener("webglcontextlost",this._contextLost,!1),this._canvas.addEventListener("webglcontextrestored",this._contextRestored,!1),this._canvas.setAttribute("tabindex",this._interactive?"0":"-1"),this._canvas.setAttribute("aria-label",this._getUIString("Map.Title")),this._canvas.setAttribute("role","region");let r=this._containerDimensions(),n=this._getClampedPixelRatio(r[0],r[1]);this._resizeCanvas(r[0],r[1],n);let i=this._controlContainer=o.create("div","maplibregl-control-container",t),a=this._controlPositions={};["top-left","top-right","bottom-left","bottom-right"].forEach((t=>{a[t]=o.create("div",`maplibregl-ctrl-${t} `,i)})),this._container.addEventListener("scroll",this._onMapScroll,!1)}_resizeCanvas(t,e,r){this._canvas.width=Math.floor(r*t),this._canvas.height=Math.floor(r*e),this._canvas.style.width=`${t}px`,this._canvas.style.height=`${e}px`}_setupPainter(){let t={alpha:!0,stencil:!0,depth:!0,failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1},e=null;this._canvas.addEventListener("webglcontextcreationerror",(r=>{e={requestedAttributes:t},r&&(e.statusMessage=r.statusMessage,e.type=r.type)}),{once:!0});let r=this._canvas.getContext("webgl2",t)||this._canvas.getContext("webgl",t);if(!r){let t="Failed to initialize WebGL";throw e?(e.message=t,new Error(JSON.stringify(e))):new Error(t)}this.painter=new _n(r,this.transform),c.testSupport(r)}loaded(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()}_update(t){return this.style&&this.style._loaded?(this._styleDirty=this._styleDirty||t,this._sourcesDirty=!0,this.triggerRepaint(),this):this}_requestRenderFrame(t){return this._update(),this._renderTaskQueue.add(t)}_cancelRenderFrame(t){this._renderTaskQueue.remove(t)}_render(t){let r=this._idleTriggered?this._fadeDuration:0;if(this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(t),this._removed)return;let n=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;let t=this.transform.zoom,i=a.now();this.style.zoomHistory.update(t,i);let o=new e.z(t,{now:i,fadeDuration:r,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),s=o.crossFadingFactor();1===s&&s===this._crossFadingFactor||(n=!0,this._crossFadingFactor=s),this.style.update(o)}this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this.terrain?(this.terrain.sourceCache.update(this.transform,this.terrain),this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this._elevationFreeze||(this.transform.elevation=this.terrain.getElevationForLngLatZoom(this.transform.center,this.transform.tileZoom))):(this.transform.minElevationForCurrentTile=0,this.transform.elevation=0),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,r,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:r,showPadding:this.showPadding}),this.fire(new e.k("render")),this.loaded()&&!this._loaded&&(this._loaded=!0,e.bf.mark(e.bg.load),this.fire(new e.k("load"))),this.style&&(this.style.hasTransitions()||n)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles();let i=this._sourcesDirty||this._styleDirty||this._placementDirty;return i||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&this.fire(new e.k("idle")),!this._loaded||this._fullyLoaded||i||(this._fullyLoaded=!0,e.bf.mark(e.bg.fullLoad)),this}redraw(){return this.style&&(this._frameRequest&&(this._frameRequest.abort(),this._frameRequest=null),this._render(0)),this}remove(){var t;this._hash&&this._hash.remove();for(let t of this._controls)t.onRemove(this);this._controls=[],this._frameRequest&&(this._frameRequest.abort(),this._frameRequest=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),typeof window<"u"&&removeEventListener("online",this._onWindowOnline,!1),p.removeThrottleControl(this._imageQueueHandle),null===(t=this._resizeObserver)||void 0===t||t.disconnect();let r=this.painter.context.gl.getExtension("WEBGL_lose_context");r?.loseContext&&r.loseContext(),this._canvas.removeEventListener("webglcontextrestored",this._contextRestored,!1),this._canvas.removeEventListener("webglcontextlost",this._contextLost,!1),o.remove(this._canvasContainer),o.remove(this._controlContainer),this._container.classList.remove("maplibregl-map"),e.bf.clearMetrics(),this._removed=!0,this.fire(new e.k("remove"))}triggerRepaint(){this.style&&!this._frameRequest&&(this._frameRequest=new AbortController,a.frameAsync(this._frameRequest).then((t=>{e.bf.frame(t),this._frameRequest=null,this._render(t)})).catch((()=>{})))}get showTileBoundaries(){return!!this._showTileBoundaries}set showTileBoundaries(t){this._showTileBoundaries!==t&&(this._showTileBoundaries=t,this._update())}get showPadding(){return!!this._showPadding}set showPadding(t){this._showPadding!==t&&(this._showPadding=t,this._update())}get showCollisionBoxes(){return!!this._showCollisionBoxes}set showCollisionBoxes(t){this._showCollisionBoxes!==t&&(this._showCollisionBoxes=t,t?this.style._generateCollisionBoxes():this._update())}get showOverdrawInspector(){return!!this._showOverdrawInspector}set showOverdrawInspector(t){this._showOverdrawInspector!==t&&(this._showOverdrawInspector=t,this._update())}get repaint(){return!!this._repaint}set repaint(t){this._repaint!==t&&(this._repaint=t,this.triggerRepaint())}get vertices(){return!!this._vertices}set vertices(t){this._vertices=t,this._update()}get version(){return Bi}getCameraTargetElevation(){return this.transform.elevation}},t.MapMouseEvent=Rn,t.MapTouchEvent=Fn,t.MapWheelEvent=Bn,t.Marker=Wi,t.NavigationControl=class{constructor(t){this._updateZoomButtons=()=>{let t=this._map.getZoom(),e=t===this._map.getMaxZoom(),r=t===this._map.getMinZoom();this._zoomInButton.disabled=e,this._zoomOutButton.disabled=r,this._zoomInButton.setAttribute("aria-disabled",e.toString()),this._zoomOutButton.setAttribute("aria-disabled",r.toString())},this._rotateCompassArrow=()=>{let t=this.options.visualizePitch?`scale(${1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)}) rotateX(${this._map.transform.pitch}deg) rotateZ(${this._map.transform.angle*(180/Math.PI)}deg)`:`rotate(${this._map.transform.angle*(180/Math.PI)}deg)`;this._compassIcon.style.transform=t},this._setButtonTitle=(t,e)=>{let r=this._map._getUIString(`NavigationControl.${e}`);t.title=r,t.setAttribute("aria-label",r)},this.options=e.e({},Ui,t),this._container=o.create("div","maplibregl-ctrl maplibregl-ctrl-group"),this._container.addEventListener("contextmenu",(t=>t.preventDefault())),this.options.showZoom&&(this._zoomInButton=this._createButton("maplibregl-ctrl-zoom-in",(t=>this._map.zoomIn({},{originalEvent:t}))),o.create("span","maplibregl-ctrl-icon",this._zoomInButton).setAttribute("aria-hidden","true"),this._zoomOutButton=this._createButton("maplibregl-ctrl-zoom-out",(t=>this._map.zoomOut({},{originalEvent:t}))),o.create("span","maplibregl-ctrl-icon",this._zoomOutButton).setAttribute("aria-hidden","true")),this.options.showCompass&&(this._compass=this._createButton("maplibregl-ctrl-compass",(t=>{this.options.visualizePitch?this._map.resetNorthPitch({},{originalEvent:t}):this._map.resetNorth({},{originalEvent:t})})),this._compassIcon=o.create("span","maplibregl-ctrl-icon",this._compass),this._compassIcon.setAttribute("aria-hidden","true"))}onAdd(t){return this._map=t,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,"ZoomIn"),this._setButtonTitle(this._zoomOutButton,"ZoomOut"),this._map.on("zoom",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,"ResetBearing"),this.options.visualizePitch&&this._map.on("pitch",this._rotateCompassArrow),this._map.on("rotate",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Vi(this._map,this._compass,this.options.visualizePitch)),this._container}onRemove(){o.remove(this._container),this.options.showZoom&&this._map.off("zoom",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off("pitch",this._rotateCompassArrow),this._map.off("rotate",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map}_createButton(t,e){let r=o.create("button",t,this._container);return r.type="button",r.addEventListener("click",e),r}},t.Popup=class extends e.E{constructor(t){super(),this.remove=()=>(this._content&&o.remove(this._content),this._container&&(o.remove(this._container),delete this._container),this._map&&(this._map.off("move",this._update),this._map.off("move",this._onClose),this._map.off("click",this._onClose),this._map.off("remove",this.remove),this._map.off("mousemove",this._onMouseMove),this._map.off("mouseup",this._onMouseUp),this._map.off("drag",this._onDrag),this._map._canvasContainer.classList.remove("maplibregl-track-pointer"),delete this._map,this.fire(new e.k("close"))),this),this._onMouseUp=t=>{this._update(t.point)},this._onMouseMove=t=>{this._update(t.point)},this._onDrag=t=>{this._update(t.point)},this._update=t=>{var e;if(!this._map||!this._lngLat&&!this._trackPointer||!this._content)return;if(!this._container){if(this._container=o.create("div","maplibregl-popup",this._map.getContainer()),this._tip=o.create("div","maplibregl-popup-tip",this._container),this._container.appendChild(this._content),this.options.className)for(let t of this.options.className.split(" "))this._container.classList.add(t);this._closeButton&&this._closeButton.setAttribute("aria-label",this._map._getUIString("Popup.Close")),this._trackPointer&&this._container.classList.add("maplibregl-popup-track-pointer")}if(this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._lngLat=this._map.transform.renderWorldCopies&&!this._trackPointer?qi(this._lngLat,this._flatPos,this._map.transform):null===(e=this._lngLat)||void 0===e?void 0:e.wrap(),this._trackPointer&&!t)return;let r=this._flatPos=this._pos=this._trackPointer&&t?t:this._map.project(this._lngLat);this._map.terrain&&(this._flatPos=this._trackPointer&&t?t:this._map.transform.locationPoint(this._lngLat));let n=this.options.anchor,i=ea(this.options.offset);if(!n){let t,e=this._container.offsetWidth,a=this._container.offsetHeight;t=r.y+i.bottom.ythis._map.transform.height-a?["bottom"]:[],r.xthis._map.transform.width-e/2&&t.push("right"),n=0===t.length?"bottom":t.join("-")}let a=r.add(i[n]);this.options.subpixelPositioning||(a=a.round()),o.setTransform(this._container,`${Hi[n]} translate(${a.x}px,${a.y}px)`),Gi(this._container,n,"popup")},this._onClose=()=>{this.remove()},this.options=e.e(Object.create(Qi),t)}addTo(t){return this._map&&this.remove(),this._map=t,this.options.closeOnClick&&this._map.on("click",this._onClose),this.options.closeOnMove&&this._map.on("move",this._onClose),this._map.on("remove",this.remove),this._update(),this._focusFirstElement(),this._trackPointer?(this._map.on("mousemove",this._onMouseMove),this._map.on("mouseup",this._onMouseUp),this._container&&this._container.classList.add("maplibregl-popup-track-pointer"),this._map._canvasContainer.classList.add("maplibregl-track-pointer")):this._map.on("move",this._update),this.fire(new e.k("open")),this}isOpen(){return!!this._map}getLngLat(){return this._lngLat}setLngLat(t){return this._lngLat=e.N.convert(t),this._pos=null,this._flatPos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on("move",this._update),this._map.off("mousemove",this._onMouseMove),this._container&&this._container.classList.remove("maplibregl-popup-track-pointer"),this._map._canvasContainer.classList.remove("maplibregl-track-pointer")),this}trackPointer(){return this._trackPointer=!0,this._pos=null,this._flatPos=null,this._update(),this._map&&(this._map.off("move",this._update),this._map.on("mousemove",this._onMouseMove),this._map.on("drag",this._onDrag),this._container&&this._container.classList.add("maplibregl-popup-track-pointer"),this._map._canvasContainer.classList.add("maplibregl-track-pointer")),this}getElement(){return this._container}setText(t){return this.setDOMContent(document.createTextNode(t))}setHTML(t){let e,r=document.createDocumentFragment(),n=document.createElement("body");for(n.innerHTML=t;e=n.firstChild,e;)r.appendChild(e);return this.setDOMContent(r)}getMaxWidth(){var t;return null===(t=this._container)||void 0===t?void 0:t.style.maxWidth}setMaxWidth(t){return this.options.maxWidth=t,this._update(),this}setDOMContent(t){if(this._content)for(;this._content.hasChildNodes();)this._content.firstChild&&this._content.removeChild(this._content.firstChild);else this._content=o.create("div","maplibregl-popup-content",this._container);return this._content.appendChild(t),this._createCloseButton(),this._update(),this._focusFirstElement(),this}addClassName(t){return this._container&&this._container.classList.add(t),this}removeClassName(t){return this._container&&this._container.classList.remove(t),this}setOffset(t){return this.options.offset=t,this._update(),this}toggleClassName(t){if(this._container)return this._container.classList.toggle(t)}setSubpixelPositioning(t){this.options.subpixelPositioning=t}_createCloseButton(){this.options.closeButton&&(this._closeButton=o.create("button","maplibregl-popup-close-button",this._content),this._closeButton.type="button",this._closeButton.innerHTML="×",this._closeButton.addEventListener("click",this._onClose))}_focusFirstElement(){if(!this.options.focusAfterOpen||!this._container)return;let t=this._container.querySelector(ta);t&&t.focus()}},t.RasterDEMTileSource=K,t.RasterTileSource=$,t.ScaleControl=class{constructor(t){this._onMove=()=>{Ki(this._map,this._container,this.options)},this.setUnit=t=>{this.options.unit=t,Ki(this._map,this._container,this.options)},this.options=Object.assign(Object.assign({},$i),t)}getDefaultPosition(){return"bottom-left"}onAdd(t){return this._map=t,this._container=o.create("div","maplibregl-ctrl 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R,F,B=[(c.left+c.right)/2,(c.top+c.bottom)/2],j=[(h.left+h.right)/2,(h.top+h.bottom)/2],N=.75*m.delta.font.size;"left"===m.delta.position&&(R=E(m,"deltaPos",0,-1*(c.width*_[m.align]+h.width*(1-_[m.align])+N),O,Math.min),F=B[1]-j[1],d={width:c.width+h.width+N,height:Math.max(c.height,h.height),left:h.left+R,right:c.right,top:Math.min(c.top,h.top+F),bottom:Math.max(c.bottom,h.bottom+F)}),"right"===m.delta.position&&(R=E(m,"deltaPos",0,c.width*(1-_[m.align])+h.width*_[m.align]+N,O,Math.max),F=B[1]-j[1],d={width:c.width+h.width+N,height:Math.max(c.height,h.height),left:c.left,right:h.right+R,top:Math.min(c.top,h.top+F),bottom:Math.max(c.bottom,h.bottom+F)}),"bottom"===m.delta.position&&(R=null,F=h.height,d={width:Math.max(c.width,h.width),height:c.height+h.height,left:Math.min(c.left,h.left),right:Math.max(c.right,h.right),top:c.bottom-c.height,bottom:c.bottom+h.height}),"top"===m.delta.position&&(R=null,F=c.top,d={width:Math.max(c.width,h.width),height:c.height+h.height,left:Math.min(c.left,h.left),right:Math.max(c.right,h.right),top:c.bottom-c.height-h.height,bottom:c.bottom}),D.attr({dx:R,dy:F})}(m._hasNumber||m._hasDelta)&&I.attr("transform",(function(){var t=l.numbersScaler(d);O+=t[2];var e,r=E(m,"numbersScale",1,t[0],O,Math.min);m._scaleNumbers||(r=1),e=m._isAngular?v-r*d.bottom:v-r*(d.top+d.bottom)/2,m._numbersTop=r*d.top+e;var n=d[b];"center"===b&&(n=(d.left+d.right)/2);var i=g-r*n;return i=E(m,"numbersTranslate",0,i,O,Math.max),s(i,e)+o(r)}))}(t,z,e,{numbersX:m,numbersY:b,numbersScaler:C,transitionOpts:d,onComplete:g}),D&&(I={range:P.gauge.axis.range,color:P.gauge.bgcolor,line:{color:P.gauge.bordercolor,width:0},thickness:1},L={range:P.gauge.axis.range,color:"rgba(0, 0, 0, 0)",line:{color:P.gauge.bordercolor,width:P.gauge.borderwidth},thickness:1});var W=z.selectAll("g.angular").data(O?e:[]);W.exit().remove();var Z=z.selectAll("g.angularaxis").data(O?e:[]);Z.exit().remove(),O&&function(t,e,i,a){var o,u,h,f,d=i[0].trace,m=a.size,g=a.radius,y=a.innerRadius,v=a.gaugeBg,x=a.gaugeOutline,_=[m.l+m.w/2,m.t+m.h/2+g/2],b=a.gauge,w=a.layer,M=a.transitionOpts,S=a.onComplete,E=Math.PI/2;function C(t){var e=d.gauge.axis.range[0],r=(t-e)/(d.gauge.axis.range[1]-e)*Math.PI-E;return r<-E?-E:r>E?E:r}function I(t){return r.svg.arc().innerRadius((y+g)/2-t/2*(g-y)).outerRadius((y+g)/2+t/2*(g-y)).startAngle(-E)}function L(t){t.attr("d",(function(t){return I(t.thickness).startAngle(C(t.range[0])).endAngle(C(t.range[1]))()}))}b.enter().append("g").classed("angular",!0),b.attr("transform",s(_[0],_[1])),w.enter().append("g").classed("angularaxis",!0).classed("crisp",!0),w.selectAll("g.xangularaxistick,path,text").remove(),(o=A(t,d.gauge.axis)).type="linear",o.range=d.gauge.axis.range,o._id="xangularaxis",o.ticklabeloverflow="allow",o.setScale();var P=function(t){return(o.range[0]-t.x)/(o.range[1]-o.range[0])*Math.PI+Math.PI},z={},D=p.makeLabelFns(o,0).labelStandoff;z.xFn=function(t){var e=P(t);return Math.cos(e)*D},z.yFn=function(t){var e=P(t),r=Math.sin(e)>0?.2:1;return-Math.sin(e)*(D+t.fontSize*r)+Math.abs(Math.cos(e))*(t.fontSize*c)},z.anchorFn=function(t){var e=P(t),r=Math.cos(e);return 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U=N.select("path");T(M)?(U.transition().duration(M.duration).ease(M.easing).each("end",(function(){S&&S()})).each("interrupt",(function(){S&&S()})).attrTween("d",function(t,e,r){return function(){var i=n(e,r);return function(e){return t.endAngle(i(e))()}}}(j,C(i[0].lastY),C(i[0].y))),d._lastValue=i[0].y):U.attr("d","number"==typeof i[0].y?j.endAngle(C(i[0].y)):"M0,0Z"),U.call(k),N.exit().remove(),F=[];var V=d.gauge.threshold.value;(V||0===V)&&F.push({range:[V,V],color:d.gauge.threshold.color,line:{color:d.gauge.threshold.line.color,width:d.gauge.threshold.line.width},thickness:d.gauge.threshold.thickness});var q=b.selectAll("g.threshold-arc").data(F);q.enter().append("g").classed("threshold-arc",!0).append("path"),q.select("path").call(L).call(k),q.exit().remove();var H=b.selectAll("g.gauge-outline").data([x]);H.enter().append("g").classed("gauge-outline",!0).append("path"),H.select("path").call(L).call(k),H.exit().remove()}(t,0,e,{radius:U,innerRadius:V,gauge:W,layer:Z,size:B,gaugeBg:I,gaugeOutline:L,transitionOpts:d,onComplete:g});var Y=z.selectAll("g.bullet").data(R?e:[]);Y.exit().remove();var X=z.selectAll("g.bulletaxis").data(R?e:[]);X.exit().remove(),R&&function(t,e,r,n){var i,a,o,l,c,u=r[0].trace,f=n.gauge,d=n.layer,m=n.gaugeBg,g=n.gaugeOutline,v=n.size,x=u.domain,_=n.transitionOpts,b=n.onComplete;f.enter().append("g").classed("bullet",!0),f.attr("transform",s(v.l,v.t)),d.enter().append("g").classed("bulletaxis",!0).classed("crisp",!0),d.selectAll("g.xbulletaxistick,path,text").remove();var w=v.h,M=u.gauge.bar.thickness*w,S=x.x[0],E=x.x[0]+(x.x[1]-x.x[0])*(u._hasNumber||u._hasDelta?1-h.bulletNumberDomainSize:1);function C(t){t.attr("width",(function(t){return Math.max(0,i.c2p(t.range[1])-i.c2p(t.range[0]))})).attr("x",(function(t){return i.c2p(t.range[0])})).attr("y",(function(t){return.5*(1-t.thickness)*w})).attr("height",(function(t){return t.thickness*w}))}(i=A(t,u.gauge.axis))._id="xbulletaxis",i.domain=[S,E],i.setScale(),a=p.calcTicks(i),o=p.makeTransTickFn(i),l=p.getTickSigns(i)[2],c=v.t+v.h,i.visible&&(p.drawTicks(t,i,{vals:"inside"===i.ticks?p.clipEnds(i,a):a,layer:d,path:p.makeTickPath(i,c,l),transFn:o}),p.drawLabels(t,i,{vals:a,layer:d,transFn:o,labelFns:p.makeLabelFns(i,c)}));var I=[m].concat(u.gauge.steps),L=f.selectAll("g.bg-bullet").data(I);L.enter().append("g").classed("bg-bullet",!0).append("rect"),L.select("rect").call(C).call(k),L.exit().remove();var P=f.selectAll("g.value-bullet").data([u.gauge.bar]);P.enter().append("g").classed("value-bullet",!0).append("rect"),P.select("rect").attr("height",M).attr("y",(w-M)/2).call(k),T(_)?P.select("rect").transition().duration(_.duration).ease(_.easing).each("end",(function(){b&&b()})).each("interrupt",(function(){b&&b()})).attr("width",Math.max(0,i.c2p(Math.min(u.gauge.axis.range[1],r[0].y)))):P.select("rect").attr("width","number"==typeof r[0].y?Math.max(0,i.c2p(Math.min(u.gauge.axis.range[1],r[0].y))):0),P.exit().remove();var z=r.filter((function(){return u.gauge.threshold.value||0===u.gauge.threshold.value})),D=f.selectAll("g.threshold-bullet").data(z);D.enter().append("g").classed("threshold-bullet",!0).append("line"),D.select("line").attr("x1",i.c2p(u.gauge.threshold.value)).attr("x2",i.c2p(u.gauge.threshold.value)).attr("y1",(1-u.gauge.threshold.thickness)/2*w).attr("y2",(1-(1-u.gauge.threshold.thickness)/2)*w).call(y.stroke,u.gauge.threshold.line.color).style("stroke-width",u.gauge.threshold.line.width),D.exit().remove();var O=f.selectAll("g.gauge-outline").data([g]);O.enter().append("g").classed("gauge-outline",!0).append("rect"),O.select("rect").call(C).call(k),O.exit().remove()}(t,0,e,{gauge:Y,layer:X,size:B,gaugeBg:I,gaugeOutline:L,transitionOpts:d,onComplete:g});var $=z.selectAll("text.title").data(e);$.exit().remove(),$.enter().append("text").classed("title",!0),$.attr("text-anchor",(function(){return R?x.right:x[P.title.align]})).text(P.title.text).call(u.font,P.title.font).call(f.convertToTspans,t),$.attr("transform",(function(){var t,e=B.l+B.w*_[P.title.align],r=h.titlePadding,n=u.bBox($.node());return D?(O&&(t=P.gauge.axis.visible?u.bBox(Z.node()).top-r-n.bottom:B.t+B.h/2-U/2-n.bottom-r),R&&(t=b-(n.top+n.bottom)/2,e=B.l-h.bulletPadding*B.w)):t=P._numbersTop-r-n.bottom,s(e,t)}))}))}}}),yw=m({"src/traces/indicator/index.js"(t,e){e.exports={moduleType:"trace",name:"indicator",basePlotModule:hw(),categories:["svg","noOpacity","noHover"],animatable:!0,attributes:fw(),supplyDefaults:dw().supplyDefaults,calc:mw().calc,plot:gw(),meta:{}}}}),vw=m({"lib/indicator.js"(t,e){e.exports=yw()}}),xw=m({"src/traces/table/attributes.js"(t,e){var r=bn(),n=B().extendFlat,i=Dt().overrideAll,a=j(),o=Aa().attributes,s=Ie().descriptionOnlyNumbers;e.exports=i({domain:o({name:"table",trace:!0}),columnwidth:{valType:"number",arrayOk:!0,dflt:null},columnorder:{valType:"data_array"},header:{values:{valType:"data_array",dflt:[]},format:{valType:"data_array",dflt:[],description:s("cell value")},prefix:{valType:"string",arrayOk:!0,dflt:null},suffix:{valType:"string",arrayOk:!0,dflt:null},height:{valType:"number",dflt:28},align:n({},r.align,{arrayOk:!0}),line:{width:{valType:"number",arrayOk:!0,dflt:1},color:{valType:"color",arrayOk:!0,dflt:"grey"}},fill:{color:{valType:"color",arrayOk:!0,dflt:"white"}},font:n({},a({arrayOk:!0}))},cells:{values:{valType:"data_array",dflt:[]},format:{valType:"data_array",dflt:[],description:s("cell 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a=c(e.cells.values),d=function(t){return t.slice(e.header.values.length,t.length)},m=c(e.header.values);m.length&&!m[0].length&&(m[0]=[""],m=c(m));var g=m.concat(d(a).map((function(){return u((m[0]||[""]).length)}))),y=e.domain,v=Math.floor(t._fullLayout._size.w*(y.x[1]-y.x[0])),x=Math.floor(t._fullLayout._size.h*(y.y[1]-y.y[0])),_=e.header.values.length?g[0].map((function(){return e.header.height})):[r.emptyHeaderHeight],b=a.length?a[0].map((function(){return e.cells.height})):[],w=_.reduce(l,0),T=p(b,x-w+r.uplift),k=f(p(_,w),[]),A=f(T,k),M={},S=e._fullInput.columnorder;o(S)&&(S=Array.from(S)),S=S.concat(d(a.map((function(t,e){return e}))));var E=g.map((function(t,r){var n=o(e.columnwidth)?e.columnwidth[Math.min(r,e.columnwidth.length-1)]:e.columnwidth;return i(n)?Number(n):1})),C=E.reduce(l,0);E=E.map((function(t){return t/C*v}));var I=Math.max(s(e.header.line.width),s(e.cells.line.width)),L={key:e.uid+t._context.staticPlot,translateX:y.x[0]*t._fullLayout._size.w,translateY:t._fullLayout._size.h*(1-y.y[1]),size:t._fullLayout._size,width:v,maxLineWidth:I,height:x,columnOrder:S,groupHeight:x,rowBlocks:A,headerRowBlocks:k,scrollY:0,cells:n({},e.cells,{values:a}),headerCells:n({},e.header,{values:g}),gdColumns:g.map((function(t){return t[0]})),gdColumnsOriginalOrder:g.map((function(t){return t[0]})),prevPages:[0,0],scrollbarState:{scrollbarScrollInProgress:!1},columns:g.map((function(t,e){var r=M[t];return M[t]=(r||0)+1,{key:t+"__"+M[t],label:t,specIndex:e,xIndex:S[e],xScale:h,x:void 0,calcdata:void 0,columnWidth:E[e]}}))};return L.columns.forEach((function(t){t.calcdata=L,t.x=h(t)})),L}}}),kw=m({"src/traces/table/data_split_helpers.js"(t){var e=B().extendFlat;t.splitToPanels=function(t){var r=[0,0],n=e({},t,{key:"header",type:"header",page:0,prevPages:r,currentRepaint:[null,null],dragHandle:!0,values:t.calcdata.headerCells.values[t.specIndex],rowBlocks:t.calcdata.headerRowBlocks,calcdata:e({},t.calcdata,{cells:t.calcdata.headerCells})});return[e({},t,{key:"cells1",type:"cells",page:0,prevPages:r,currentRepaint:[null,null],dragHandle:!1,values:t.calcdata.cells.values[t.specIndex],rowBlocks:t.calcdata.rowBlocks}),e({},t,{key:"cells2",type:"cells",page:1,prevPages:r,currentRepaint:[null,null],dragHandle:!1,values:t.calcdata.cells.values[t.specIndex],rowBlocks:t.calcdata.rowBlocks}),n]},t.splitToCells=function(t){var e=function(t){var e=t.rowBlocks[t.page],r=e?e.rows[0].rowIndex:0;return[r,e?r+e.rows.length:0]}(t);return(t.values||[]).slice(e[0],e[1]).map((function(r,n){return{keyWithinBlock:n+("string"==typeof r&&r.match(/[<$&> 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r=G(),n=Le(),i=Aa().attributes,a=ce().extendFlat,o=Dt().overrideAll,s=o({color:n.color,showline:a({},n.showline,{dflt:!0}),linecolor:n.linecolor,linewidth:n.linewidth,showgrid:a({},n.showgrid,{dflt:!0}),gridcolor:n.gridcolor,gridwidth:n.gridwidth,griddash:n.griddash},"plot","from-root"),l=o({ticklen:n.ticklen,tickwidth:a({},n.tickwidth,{dflt:2}),tickcolor:n.tickcolor,showticklabels:n.showticklabels,labelalias:n.labelalias,showtickprefix:n.showtickprefix,tickprefix:n.tickprefix,showticksuffix:n.showticksuffix,ticksuffix:n.ticksuffix,tickfont:n.tickfont,tickformat:n.tickformat,hoverformat:n.hoverformat,layer:n.layer},"plot","from-root"),c=a({visible:a({},n.visible,{dflt:!0}),tickvals:{dflt:[.2,.5,1,2,5],valType:"data_array",editType:"plot"},tickangle:a({},n.tickangle,{dflt:90}),ticks:{valType:"enumerated",values:["top","bottom",""],editType:"ticks"},side:{valType:"enumerated",values:["top","bottom"],dflt:"top",editType:"plot"},editType:"calc"},s,l),u=a({visible:a({},n.visible,{dflt:!0}),tickvals:{valType:"data_array",editType:"plot"},ticks:n.ticks,editType:"calc"},s,l);e.exports={domain:i({name:"smith",editType:"plot"}),bgcolor:{valType:"color",editType:"plot",dflt:r.background},realaxis:c,imaginaryaxis:u,editType:"calc"}}}),mk=m({"src/plots/smith/layout_defaults.js"(t,e){var r,n,i,a=ce(),o=W(),s=ve(),l=Gs(),c=Te().getSubplotData,u=Ve(),h=Ue(),f=Ti(),p=rr(),d=dk(),m=pk(),g=m.axisNames,y=(r=function(t){return a.isTypedArray(t)&&(t=Array.from(t)),t.slice().reverse().map((function(t){return-t})).concat([0]).concat(t)},n=String,i={},function(t){var e=n?n(t):t;if(e in i)return i[e];var a=r(t);return i[e]=a,a});function v(t,e,r,n){var i=r("bgcolor");n.bgColor=o.combine(i,n.paper_bgcolor);var l,v=c(n.fullData,m.name,n.id),x=n.layoutOut;function _(t,e){return r(l+"."+t,e)}for(var b=0;b")}}e.exports={hoverPoints:function(t,e,i,a){var o=r(t,e,i,a);if(o&&!1!==o[0].index){var s=o[0];if(void 0===s.index)return o;var l=t.subplot,c=s.cd[s.index],u=s.trace;if(l.isPtInside(c))return s.xLabelVal=void 0,s.yLabelVal=void 0,n(c,u,l,s),s.hovertemplate=u.hovertemplate,o}},makeHoverPointText:n}}}),Tk=m({"src/traces/scattersmith/index.js"(t,e){e.exports={moduleType:"trace",name:"scattersmith",basePlotModule:gk(),categories:["smith","symbols","showLegend","scatter-like"],attributes:yk(),supplyDefaults:vk(),colorbar:di(),formatLabels:xk(),calc:_k(),plot:bk(),style:gi().style,styleOnSelect:gi().styleOnSelect,hoverPoints:wk().hoverPoints,selectPoints:xi(),meta:{}}}}),kk=m({"lib/scattersmith.js"(t,e){e.exports=Tk()}}),Ak=m({"node_modules/world-calendars/dist/main.js"(t,e){var r=Ay();function n(){this.regionalOptions=[],this.regionalOptions[""]={invalidCalendar:"Calendar {0} not found",invalidDate:"Invalid {0} date",invalidMonth:"Invalid {0} month",invalidYear:"Invalid {0} year",differentCalendars:"Cannot mix {0} and {1} dates"},this.local=this.regionalOptions[""],this.calendars={},this._localCals={}}function i(t,e,r,n){if(this._calendar=t,this._year=e,this._month=r,this._day=n,0===this._calendar._validateLevel&&!this._calendar.isValid(this._year,this._month,this._day))throw(l.local.invalidDate||l.regionalOptions[""].invalidDate).replace(/\{0\}/,this._calendar.local.name)}function a(t,e){return"000000".substring(0,e-(t=""+t).length)+t}function o(){this.shortYearCutoff="+10"}function s(t){this.local=this.regionalOptions[t]||this.regionalOptions[""]}r(n.prototype,{instance:function(t,e){t=(t||"gregorian").toLowerCase(),e=e||"";var r=this._localCals[t+"-"+e];if(!r&&this.calendars[t]&&(r=new this.calendars[t](e),this._localCals[t+"-"+e]=r),!r)throw(this.local.invalidCalendar||this.regionalOptions[""].invalidCalendar).replace(/\{0\}/,t);return r},newDate:function(t,e,r,n,i){return(n=(null!=t&&t.year?t.calendar():"string"==typeof n?this.instance(n,i):n)||this.instance()).newDate(t,e,r)},substituteDigits:function(t){return function(e){return(e+"").replace(/[0-9]/g,(function(e){return 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n=this._validate(t,e,r,l.local.invalidDate||l.regionalOptions[""].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(t,e,r){return this._validate(t,e,r,l.local.invalidDate||l.regionalOptions[""].invalidDate),{}},add:function(t,e,r){return this._validate(t,this.minMonth,this.minDay,l.local.invalidDate||l.regionalOptions[""].invalidDate),this._correctAdd(t,this._add(t,e,r),e,r)},_add:function(t,e,r){if(this._validateLevel++,"d"===r||"w"===r){var n=t.toJD()+e*("w"===r?this.daysInWeek():1),i=t.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=t.year()+("y"===r?e:0),o=t.monthOfYear()+("m"===r?e:0);i=t.day(),"y"===r?(t.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,t.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):"m"===r&&(function(t){for(;oe-1+t.minMonth;)a++,o-=e,e=t.monthsInYear(a)}(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var s=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,s}catch(t){throw this._validateLevel--,t}},_correctAdd:function(t,e,r,n){if(!(this.hasYearZero||"y"!==n&&"m"!==n||0!==e[0]&&t.year()>0==e[0]>0)){var i={y:[1,1,"y"],m:[1,this.monthsInYear(-1),"m"],w:[this.daysInWeek(),this.daysInYear(-1),"d"],d:[1,this.daysInYear(-1),"d"]}[n],a=r<0?-1:1;e=this._add(t,r*i[0]+a*i[1],i[2])}return t.date(e[0],e[1],e[2])},set:function(t,e,r){this._validate(t,this.minMonth,this.minDay,l.local.invalidDate||l.regionalOptions[""].invalidDate);var n="y"===r?e:t.year(),i="m"===r?e:t.month(),a="d"===r?e:t.day();return("y"===r||"m"===r)&&(a=Math.min(a,this.daysInMonth(n,i))),t.date(n,i,a)},isValid:function(t,e,r){this._validateLevel++;var n=this.hasYearZero||0!==t;if(n){var i=this.newDate(t,e,this.minDay);n=e>=this.minMonth&&e-this.minMonth=this.minDay&&r-this.minDay13.5?13:1),c=i-(l>2.5?4716:4715);return c<=0&&c--,this.newDate(c,l,s)},toJSDate:function(t,e,r){var n=this._validate(t,e,r,l.local.invalidDate||l.regionalOptions[""].invalidDate),i=new Date(n.year(),n.month()-1,n.day());return i.setHours(0),i.setMinutes(0),i.setSeconds(0),i.setMilliseconds(0),i.setHours(i.getHours()>12?i.getHours()+2:0),i},fromJSDate:function(t){return this.newDate(t.getFullYear(),t.getMonth()+1,t.getDate())}});var l=e.exports=new n;l.cdate=i,l.baseCalendar=o,l.calendars.gregorian=s}}),Mk=m({"node_modules/world-calendars/dist/plus.js"(){var t=Ay(),e=Ak();t(e.regionalOptions[""],{invalidArguments:"Invalid arguments",invalidFormat:"Cannot format a date 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i=(n=n||{}).dayNamesShort||this.local.dayNamesShort,a=n.dayNames||this.local.dayNames,o=n.monthNumbers||this.local.monthNumbers,s=n.monthNamesShort||this.local.monthNamesShort,l=n.monthNames||this.local.monthNames,c=(n.calculateWeek||this.local.calculateWeek,function(e,r){for(var n=1;v+n1}),u=function(t,e,r,n){var i=""+e;if(c(t,n))for(;i.length1},x=function(t,n){var i=v(t,n),a=[2,3,i?4:2,i?4:2,10,11,20]["oyYJ@!".indexOf(t)+1],o=new RegExp("^-?\\d{1,"+a+"}"),s=r.substring(A).match(o);if(!s)throw(e.local.missingNumberAt||e.regionalOptions[""].missingNumberAt).replace(/\{0\}/,A);return A+=s[0].length,parseInt(s[0],10)},_=this,b=function(){if("function"==typeof l){v("m");var t=l.call(_,r.substring(A));return A+=t.length,t}return x("m")},w=function(t,n,i,a){for(var o=v(t,a)?i:n,s=0;s-1){p=1,d=m;for(var E=this.daysInMonth(f,p);d>E;E=this.daysInMonth(f,p))p++,d-=E}return h>-1?this.fromJD(h):this.newDate(f,p,d)},determineDate:function(t,e,r,n,i){r&&"object"!=typeof 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e&&o.length<2&&(o="0"+o),this.isIntercalaryMonth(n,i)&&(o+="i"),o},monthNames:function(t){if("string"==typeof t){var e=t.match(o);return e?e[0]:""}var r=this._validateYear(t),n=t.month(),i=["一月","二月","三月","四月","五月","六月","七月","八月","九月","十月","十一月","十二月"][this.toChineseMonth(r,n)-1];return this.isIntercalaryMonth(r,n)&&(i="闰"+i),i},monthNamesShort:function(t){if("string"==typeof t){var e=t.match(s);return e?e[0]:""}var r=this._validateYear(t),n=t.month(),i=["一","二","三","四","五","六","七","八","九","十","十一","十二"][this.toChineseMonth(r,n)-1];return this.isIntercalaryMonth(r,n)&&(i="闰"+i),i},parseMonth:function(t,e){t=this._validateYear(t);var r,n=parseInt(e);if(isNaN(n))"闰"===e[0]&&(r=!0,e=e.substring(1)),"月"===e[e.length-1]&&(e=e.substring(0,e.length-1)),n=1+["一","二","三","四","五","六","七","八","九","十","十一","十二"].indexOf(e);else{var i=e[e.length-1];r="i"===i||"I"===i}return 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e=i.year(),r=i.month(),e=e<=0?e+1:e,(n=i.day())+Math.ceil(29.5*(r-1))+354*(e-1)+Math.floor((3+11*e)/30)+this.jdEpoch-1},fromJD:function(t){t=Math.floor(t)+.5;var e=Math.floor((30*(t-this.jdEpoch)+10646)/10631);e=e<=0?e-1:e;var r=Math.min(12,Math.ceil((t-29-this.toJD(e,1,1))/29.5)+1),n=t-this.toJD(e,r,1)+1;return this.newDate(e,r,n)}}),t.calendars.islamic=r}}),zk=m({"node_modules/world-calendars/dist/calendars/julian.js"(){var t=Ak(),e=Ay();function r(t){this.local=this.regionalOptions[t||""]||this.regionalOptions[""]}r.prototype=new 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n=this._validate(e,r,this.minDay,t.local.invalidMonth);return this.daysPerMonth[n.month()-1]+(2===n.month()&&this.leapYear(n.year())?1:0)},weekDay:function(t,e,r){return(this.dayOfWeek(t,e,r)||7)<6},toJD:function(e,r,n){var i=this._validate(e,r,n,t.local.invalidDate);return e=i.year(),r=i.month(),n=i.day(),e<0&&e++,r<=2&&(e--,r+=12),Math.floor(365.25*(e+4716))+Math.floor(30.6001*(r+1))+n-1524.5},fromJD:function(t){var e=Math.floor(t+.5)+1524,r=Math.floor((e-122.1)/365.25),n=Math.floor(365.25*r),i=Math.floor((e-n)/30.6001),a=i-Math.floor(i<14?1:13),o=r-Math.floor(a>2?4716:4715),s=e-n-Math.floor(30.6001*i);return o<=0&&o--,this.newDate(o,a,s)}}),t.calendars.julian=r}}),Dk=m({"node_modules/world-calendars/dist/calendars/mayan.js"(){var t=Ak(),e=Ay();function r(t){this.local=this.regionalOptions[t||""]||this.regionalOptions[""]}function n(t,e){return t-e*Math.floor(t/e)}function i(t,e){return n(t-1,e)+1}r.prototype=new 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this._validate(e,this.minMonth,this.minDay,t.local.invalidYear),!1},formatYear:function(e){e=this._validate(e,this.minMonth,this.minDay,t.local.invalidYear).year();var r=Math.floor(e/400);return e%=400,e+=e<0?400:0,r+"."+Math.floor(e/20)+"."+e%20},forYear:function(t){if((t=t.split(".")).length<3)throw"Invalid Mayan year";for(var e=0,r=0;r19||r>0&&n<0)throw"Invalid Mayan year";e=20*e+n}return e},monthsInYear:function(e){return this._validate(e,this.minMonth,this.minDay,t.local.invalidYear),18},weekOfYear:function(e,r,n){return this._validate(e,r,n,t.local.invalidDate),0},daysInYear:function(e){return this._validate(e,this.minMonth,this.minDay,t.local.invalidYear),360},daysInMonth:function(e,r){return this._validate(e,r,this.minDay,t.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(e,r,n){return this._validate(e,r,n,t.local.invalidDate).day()},weekDay:function(e,r,n){return this._validate(e,r,n,t.local.invalidDate),!0},extraInfo:function(e,r,n){var i=this._validate(e,r,n,t.local.invalidDate).toJD(),a=this._toHaab(i),o=this._toTzolkin(i);return{haabMonthName:this.local.haabMonths[a[0]-1],haabMonth:a[0],haabDay:a[1],tzolkinDayName:this.local.tzolkinMonths[o[0]-1],tzolkinDay:o[0],tzolkinTrecena:o[1]}},_toHaab:function(t){var e=n(8+(t-=this.jdEpoch)+340,365);return[Math.floor(e/20)+1,n(e,20)]},_toTzolkin:function(t){return[i(20+(t-=this.jdEpoch),20),i(t+4,13)]},toJD:function(e,r,n){var i=this._validate(e,r,n,t.local.invalidDate);return i.day()+20*i.month()+360*i.year()+this.jdEpoch},fromJD:function(t){t=Math.floor(t)+.5-this.jdEpoch;var e=Math.floor(t/360);t%=360,t+=t<0?360:0;var r=Math.floor(t/20),n=t%20;return this.newDate(e,r,n)}}),t.calendars.mayan=r}}),Ok=m({"node_modules/world-calendars/dist/calendars/nanakshahi.js"(){var t=Ak(),e=Ay();function r(t){this.local=this.regionalOptions[t||""]||this.regionalOptions[""]}r.prototype=new t.baseCalendar;var 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t.baseCalendar,e(n.prototype,{name:"Thai",jdEpoch:1523098.5,yearsOffset:543,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{"":{name:"Thai",epochs:["BBE","BE"],monthNames:["January","February","March","April","May","June","July","August","September","October","November","December"],monthNamesShort:["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"],dayNames:["Sunday","Monday","Tuesday","Wednesday","Thursday","Friday","Saturday"],dayNamesShort:["Sun","Mon","Tue","Wed","Thu","Fri","Sat"],dayNamesMin:["Su","Mo","Tu","We","Th","Fr","Sa"],digits:null,dateFormat:"dd/mm/yyyy",firstDay:0,isRTL:!1}},leapYear:function(e){var n=this._validate(e,this.minMonth,this.minDay,t.local.invalidYear);return e=this._t2gYear(n.year()),r.leapYear(e)},weekOfYear:function(e,n,i){var a=this._validate(e,this.minMonth,this.minDay,t.local.invalidYear);return 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attached.");M.sendMessage(e,t.Msg.BeforeAttach),r.insertBefore(e.node,n),M.sendMessage(e,t.Msg.AfterAttach)},t.detach=function(e){if(e.parent)throw new Error("Cannot detach a child widget.");if(!e.isAttached||!e.node.isConnected)throw new Error("Widget is not attached.");M.sendMessage(e,t.Msg.BeforeDetach),e.node.parentNode.removeChild(e.node),M.sendMessage(e,t.Msg.AfterDetach)}}(nt||(nt={})),function(t){t.titleProperty=new I({name:"title",create:t=>new rt({owner:t})}),t.createNode=function(t){return t.node||document.createElement(t.tag||"div")}}(et||(et={}));var it=class{constructor(t={}){this._disposed=!1,this._parent=null,this._fitPolicy=t.fitPolicy||"set-min-size"}dispose(){this._parent=null,this._disposed=!0,z.clearData(this),I.clearData(this)}get isDisposed(){return this._disposed}get parent(){return this._parent}set parent(t){if(this._parent!==t){if(this._parent)throw new Error("Cannot change parent widget.");if(t.layout!==this)throw new Error("Invalid parent widget.");this._parent=t,this.init()}}get fitPolicy(){return this._fitPolicy}set fitPolicy(t){if(this._fitPolicy!==t&&(this._fitPolicy=t,this._parent)){let t=this._parent.node.style;t.minWidth="",t.minHeight="",t.maxWidth="",t.maxHeight="",this._parent.fit()}}processParentMessage(t){switch(t.type){case"resize":this.onResize(t);break;case"update-request":this.onUpdateRequest(t);break;case"fit-request":this.onFitRequest(t);break;case"before-show":this.onBeforeShow(t);break;case"after-show":this.onAfterShow(t);break;case"before-hide":this.onBeforeHide(t);break;case"after-hide":this.onAfterHide(t);break;case"before-attach":this.onBeforeAttach(t);break;case"after-attach":this.onAfterAttach(t);break;case"before-detach":this.onBeforeDetach(t);break;case"after-detach":this.onAfterDetach(t);break;case"child-removed":this.onChildRemoved(t);break;case"child-shown":this.onChildShown(t);break;case"child-hidden":this.onChildHidden(t)}}init(){for(let t of this)t.parent=this.parent}onResize(t){for(let t of this)M.sendMessage(t,nt.ResizeMessage.UnknownSize)}onUpdateRequest(t){for(let t of this)M.sendMessage(t,nt.ResizeMessage.UnknownSize)}onBeforeAttach(t){for(let e of this)M.sendMessage(e,t)}onAfterAttach(t){for(let e of this)M.sendMessage(e,t)}onBeforeDetach(t){for(let e of this)M.sendMessage(e,t)}onAfterDetach(t){for(let e of this)M.sendMessage(e,t)}onBeforeShow(t){for(let e of this)e.isHidden||M.sendMessage(e,t)}onAfterShow(t){for(let e of this)e.isHidden||M.sendMessage(e,t)}onBeforeHide(t){for(let e of this)e.isHidden||M.sendMessage(e,t)}onAfterHide(t){for(let e of this)e.isHidden||M.sendMessage(e,t)}onChildRemoved(t){this.removeWidget(t.child)}onFitRequest(t){}onChildShown(t){}onChildHidden(t){}};!function(t){t.getHorizontalAlignment=function(t){return at.horizontalAlignmentProperty.get(t)},t.setHorizontalAlignment=function(t,e){at.horizontalAlignmentProperty.set(t,e)},t.getVerticalAlignment=function(t){return at.verticalAlignmentProperty.get(t)},t.setVerticalAlignment=function(t,e){at.verticalAlignmentProperty.set(t,e)}}(it||(it={}));var at,ot=class{constructor(t){this._top=NaN,this._left=NaN,this._width=NaN,this._height=NaN,this._minWidth=0,this._minHeight=0,this._maxWidth=1/0,this._maxHeight=1/0,this._disposed=!1,this.widget=t,this.widget.node.style.position="absolute",this.widget.node.style.contain="strict"}dispose(){if(this._disposed)return;this._disposed=!0;let t=this.widget.node.style;t.position="",t.top="",t.left="",t.width="",t.height="",t.contain=""}get minWidth(){return this._minWidth}get minHeight(){return this._minHeight}get maxWidth(){return this._maxWidth}get maxHeight(){return this._maxHeight}get isDisposed(){return this._disposed}get isHidden(){return this.widget.isHidden}get isVisible(){return this.widget.isVisible}get isAttached(){return this.widget.isAttached}fit(){let t=i.sizeLimits(this.widget.node);this._minWidth=t.minWidth,this._minHeight=t.minHeight,this._maxWidth=t.maxWidth,this._maxHeight=t.maxHeight}update(t,e,r,n){let i=Math.max(this._minWidth,Math.min(r,this._maxWidth)),a=Math.max(this._minHeight,Math.min(n,this._maxHeight));if(i"center",changed:e}),t.verticalAlignmentProperty=new I({name:"verticalAlignment",create:()=>"top",changed:e})}(at||(at={}));var st,lt=class extends it{constructor(){super(...arguments),this._widgets=[]}dispose(){for(;this._widgets.length>0;)this._widgets.pop().dispose();super.dispose()}get widgets(){return this._widgets}*[Symbol.iterator](){yield*this._widgets}addWidget(t){this.insertWidget(this._widgets.length,t)}insertWidget(t,e){e.parent=this.parent;let r=this._widgets.indexOf(e),n=Math.max(0,Math.min(t,this._widgets.length));if(-1===r)return b.ArrayExt.insert(this._widgets,n,e),void(this.parent&&this.attachWidget(n,e));n===this._widgets.length&&n--,r!==n&&(b.ArrayExt.move(this._widgets,r,n),this.parent&&this.moveWidget(r,n,e))}removeWidget(t){this.removeWidgetAt(this._widgets.indexOf(t))}removeWidgetAt(t){let e=b.ArrayExt.removeAt(this._widgets,t);e&&this.parent&&this.detachWidget(t,e)}init(){super.init();let t=0;for(let e of this)this.attachWidget(t++,e)}attachWidget(t,e){let r=this.parent.node.children[t];this.parent.isAttached&&M.sendMessage(e,nt.Msg.BeforeAttach),this.parent.node.insertBefore(e.node,r),this.parent.isAttached&&M.sendMessage(e,nt.Msg.AfterAttach)}moveWidget(t,e,r){this.parent.isAttached&&M.sendMessage(r,nt.Msg.BeforeDetach),this.parent.node.removeChild(r.node),this.parent.isAttached&&M.sendMessage(r,nt.Msg.AfterDetach);let n=this.parent.node.children[e];this.parent.isAttached&&M.sendMessage(r,nt.Msg.BeforeAttach),this.parent.node.insertBefore(r.node,n),this.parent.isAttached&&M.sendMessage(r,nt.Msg.AfterAttach)}detachWidget(t,e){this.parent.isAttached&&M.sendMessage(e,nt.Msg.BeforeDetach),this.parent.node.removeChild(e.node),this.parent.isAttached&&M.sendMessage(e,nt.Msg.AfterDetach)}};!function(t){t.clampDimension=function(t){return Math.max(0,Math.floor(t))}}(st||(st={}));var ct,ut=st,ht=class t extends lt{constructor(t){super(),this.widgetOffset=0,this._fixed=0,this._spacing=4,this._dirty=!1,this._hasNormedSizes=!1,this._sizers=[],this._items=[],this._handles=[],this._box=null,this._alignment="start",this._orientation="horizontal",this.renderer=t.renderer,void 0!==t.orientation&&(this._orientation=t.orientation),void 0!==t.alignment&&(this._alignment=t.alignment),void 0!==t.spacing&&(this._spacing=st.clampDimension(t.spacing))}dispose(){for(let t of this._items)t.dispose();this._box=null,this._items.length=0,this._sizers.length=0,this._handles.length=0,super.dispose()}get orientation(){return this._orientation}set orientation(t){this._orientation!==t&&(this._orientation=t,this.parent&&(this.parent.dataset.orientation=t,this.parent.fit()))}get alignment(){return this._alignment}set alignment(t){this._alignment!==t&&(this._alignment=t,this.parent&&(this.parent.dataset.alignment=t,this.parent.update()))}get spacing(){return this._spacing}set spacing(t){t=st.clampDimension(t),this._spacing!==t&&(this._spacing=t,this.parent&&this.parent.fit())}get handles(){return this._handles}absoluteSizes(){return this._sizers.map((t=>t.size))}relativeSizes(){return ct.normalize(this._sizers.map((t=>t.size)))}setRelativeSizes(t,e=!0){let r=this._sizers.length,n=t.slice(0,r);for(;n.length0&&(t.sizeHint=t.size);Q.adjust(this._sizers,t,r),this.parent&&this.parent.update()}}init(){this.parent.dataset.orientation=this.orientation,this.parent.dataset.alignment=this.alignment,super.init()}attachWidget(t,e){let r=new ot(e),n=ct.createHandle(this.renderer),i=ct.averageSize(this._sizers),a=ct.createSizer(i);b.ArrayExt.insert(this._items,t,r),b.ArrayExt.insert(this._sizers,t,a),b.ArrayExt.insert(this._handles,t,n),this.parent.isAttached&&M.sendMessage(e,nt.Msg.BeforeAttach),this.parent.node.appendChild(e.node),this.parent.node.appendChild(n),this.parent.isAttached&&M.sendMessage(e,nt.Msg.AfterAttach),this.parent.fit()}moveWidget(t,e,r){b.ArrayExt.move(this._items,t,e),b.ArrayExt.move(this._sizers,t,e),b.ArrayExt.move(this._handles,t,e),this.parent.fit()}detachWidget(t,e){let r=b.ArrayExt.removeAt(this._items,t),n=b.ArrayExt.removeAt(this._handles,t);b.ArrayExt.removeAt(this._sizers,t),this.parent.isAttached&&M.sendMessage(e,nt.Msg.BeforeDetach),this.parent.node.removeChild(e.node),this.parent.node.removeChild(n),this.parent.isAttached&&M.sendMessage(e,nt.Msg.AfterDetach),r.dispose(),this.parent.fit()}onBeforeShow(t){super.onBeforeShow(t),this.parent.update()}onBeforeAttach(t){super.onBeforeAttach(t),this.parent.fit()}onChildShown(t){this.parent.fit()}onChildHidden(t){this.parent.fit()}onResize(t){this.parent.isVisible&&this._update(t.width,t.height)}onUpdateRequest(t){this.parent.isVisible&&this._update(-1,-1)}onFitRequest(t){this.parent.isAttached&&this._fit()}updateItemPosition(t,e,r,n,i,a,o){let s=this._items[t];if(s.isHidden)return;let l=this._handles[t].style;e?(r+=this.widgetOffset,s.update(r,n,o,i),r+=o,l.top=`${n}px`,l.left=`${r}px`,l.width=`${this._spacing}px`,l.height=`${i}px`):(n+=this.widgetOffset,s.update(r,n,a,o),n+=o,l.top=`${n}px`,l.left=`${r}px`,l.width=`${a}px`,l.height=`${this._spacing}px`)}_fit(){let e=0,r=-1;for(let t=0,n=this._items.length;t0&&(i.sizeHint=i.size),r.isHidden?(i.minSize=0,i.maxSize=0):(r.fit(),i.stretch=t.getStretch(r.widget),n?(i.minSize=r.minWidth,i.maxSize=r.maxWidth,a+=r.minWidth,o=Math.max(o,r.minHeight)):(i.minSize=r.minHeight,i.maxSize=r.maxHeight,o+=r.minHeight,a=Math.max(a,r.minWidth)))}let s=this._box=i.boxSizing(this.parent.node);a+=s.horizontalSum,o+=s.verticalSum;let l=this.parent.node.style;l.minWidth=`${a}px`,l.minHeight=`${o}px`,this._dirty=!0,this.parent.parent&&M.sendMessage(this.parent.parent,nt.Msg.FitRequest),this._dirty&&M.sendMessage(this.parent,nt.Msg.UpdateRequest)}_update(t,e){this._dirty=!1;let r=0;for(let t=0,e=this._items.length;t0){let t;if(t=u?Math.max(0,o-this._fixed):Math.max(0,s-this._fixed),this._hasNormedSizes){for(let e of this._sizers)e.sizeHint*=t;this._hasNormedSizes=!1}let e=Q.calc(this._sizers,t);if(e>0)switch(this._alignment){case"start":break;case"center":l=0,c=e/2;break;case"end":l=0,c=e;break;case"justify":l=e/r,c=0;break;default:throw"unreachable"}}for(let t=0,e=this._items.length;t0,coerce:(t,e)=>Math.max(0,Math.floor(e)),changed:function(t){t.parent&&t.parent.layout instanceof ht&&t.parent.fit()}}),t.createSizer=function(t){let e=new tt;return e.sizeHint=Math.floor(t),e},t.createHandle=function(t){let e=t.createHandle();return e.style.position="absolute",e.style.contain="style",e},t.averageSize=function(t){return t.reduce(((t,e)=>t+e.size),0)/t.length||0},t.normalize=function(t){let e=t.length;if(0===e)return[];let r=t.reduce(((t,e)=>t+Math.abs(e)),0);return 0===r?t.map((t=>1/e)):t.map((t=>t/r))}}(ct||(ct={}));var ft,pt=class extends ht{constructor(t){super({...t,orientation:t.orientation||"vertical"}),this._titles=[],this.titleSpace=t.titleSpace||22}get titleSpace(){return this.widgetOffset}set titleSpace(t){t=ut.clampDimension(t),this.widgetOffset!==t&&(this.widgetOffset=t,this.parent&&this.parent.fit())}get titles(){return this._titles}dispose(){this.isDisposed||(this._titles.length=0,super.dispose())}updateTitle(t,e){let r=this._titles[t],n=r.classList.contains("lm-mod-expanded"),i=ft.createTitle(this.renderer,e.title,n);this._titles[t]=i,this.parent.node.replaceChild(i,r)}insertWidget(t,e){e.id||(e.id=`id-${w.UUID.uuid4()}`),super.insertWidget(t,e)}attachWidget(t,e){let r=ft.createTitle(this.renderer,e.title);b.ArrayExt.insert(this._titles,t,r),this.parent.node.appendChild(r),e.node.setAttribute("role","region"),e.node.setAttribute("aria-labelledby",r.id),super.attachWidget(t,e)}moveWidget(t,e,r){b.ArrayExt.move(this._titles,t,e),super.moveWidget(t,e,r)}detachWidget(t,e){let r=b.ArrayExt.removeAt(this._titles,t);this.parent.node.removeChild(r),super.detachWidget(t,e)}updateItemPosition(t,e,r,n,i,a,o){let s=this._titles[t].style;s.top=`${n}px`,s.left=`${r}px`,s.height=`${this.widgetOffset}px`,s.width=e?`${i}px`:`${a}px`,super.updateItemPosition(t,e,r,n,i,a,o)}};!function(t){t.createTitle=function(t,e,r=!0){let n=t.createSectionTitle(e);return n.style.position="absolute",n.style.contain="strict",n.setAttribute("aria-label",`${e.label} Section`),n.setAttribute("aria-expanded",r?"true":"false"),n.setAttribute("aria-controls",e.owner.id),r&&n.classList.add("lm-mod-expanded"),n}}(ft||(ft={}));var dt,mt=class extends nt{constructor(t={}){super(),this.addClass("lm-Panel"),this.layout=dt.createLayout(t)}get widgets(){return this.layout.widgets}addWidget(t){this.layout.addWidget(t)}insertWidget(t,e){this.layout.insertWidget(t,e)}};!function(t){t.createLayout=function(t){return t.layout||new lt}}(dt||(dt={}));var gt,yt=class extends mt{constructor(t={}){super({layout:gt.createLayout(t)}),this._handleMoved=new z(this),this._pressData=null,this.addClass("lm-SplitPanel")}dispose(){this._releaseMouse(),super.dispose()}get orientation(){return this.layout.orientation}set orientation(t){this.layout.orientation=t}get alignment(){return this.layout.alignment}set alignment(t){this.layout.alignment=t}get spacing(){return this.layout.spacing}set spacing(t){this.layout.spacing=t}get renderer(){return this.layout.renderer}get handleMoved(){return this._handleMoved}get handles(){return this.layout.handles}relativeSizes(){return this.layout.relativeSizes()}setRelativeSizes(t,e=!0){this.layout.setRelativeSizes(t,e)}handleEvent(t){switch(t.type){case"pointerdown":this._evtPointerDown(t);break;case"pointermove":this._evtPointerMove(t);break;case"pointerup":this._evtPointerUp(t);break;case"keydown":this._evtKeyDown(t);break;case"contextmenu":t.preventDefault(),t.stopPropagation()}}onBeforeAttach(t){this.node.addEventListener("pointerdown",this)}onAfterDetach(t){this.node.removeEventListener("pointerdown",this),this._releaseMouse()}onChildAdded(t){t.child.addClass("lm-SplitPanel-child"),this._releaseMouse()}onChildRemoved(t){t.child.removeClass("lm-SplitPanel-child"),this._releaseMouse()}_evtKeyDown(t){this._pressData&&(t.preventDefault(),t.stopPropagation()),27===t.keyCode&&this._releaseMouse()}_evtPointerDown(t){if(0!==t.button)return;let e=this.layout,r=b.ArrayExt.findFirstIndex(e.handles,(e=>e.contains(t.target)));if(-1===r)return;t.preventDefault(),t.stopPropagation(),document.addEventListener("pointerup",this,!0),document.addEventListener("pointermove",this,!0),document.addEventListener("keydown",this,!0),document.addEventListener("contextmenu",this,!0);let n,i=e.handles[r],a=i.getBoundingClientRect();n="horizontal"===e.orientation?t.clientX-a.left:t.clientY-a.top;let o=window.getComputedStyle(i),s=B.overrideCursor(o.cursor);this._pressData={index:r,delta:n,override:s}}_evtPointerMove(t){t.preventDefault(),t.stopPropagation();let e,r=this.layout,n=this.node.getBoundingClientRect();e="horizontal"===r.orientation?t.clientX-n.left-this._pressData.delta:t.clientY-n.top-this._pressData.delta,r.moveHandle(this._pressData.index,e)}_evtPointerUp(t){0===t.button&&(t.preventDefault(),t.stopPropagation(),this._releaseMouse())}_releaseMouse(){this._pressData&&(this._pressData.override.dispose(),this._pressData=null,this._handleMoved.emit(),document.removeEventListener("keydown",this,!0),document.removeEventListener("pointerup",this,!0),document.removeEventListener("pointermove",this,!0),document.removeEventListener("contextmenu",this,!0))}};!function(t){class e{createHandle(){let t=document.createElement("div");return t.className="lm-SplitPanel-handle",t}}t.Renderer=e,t.defaultRenderer=new e,t.getStretch=function(t){return ht.getStretch(t)},t.setStretch=function(t,e){ht.setStretch(t,e)}}(yt||(yt={})),function(t){t.createLayout=function(t){return t.layout||new ht({renderer:t.renderer||yt.defaultRenderer,orientation:t.orientation,alignment:t.alignment,spacing:t.spacing})}}(gt||(gt={}));var vt,xt=class extends yt{constructor(t={}){super({...t,layout:vt.createLayout(t)}),this._widgetSizesCache=new WeakMap,this._expansionToggled=new z(this),this.addClass("lm-AccordionPanel")}get renderer(){return this.layout.renderer}get titleSpace(){return this.layout.titleSpace}set titleSpace(t){this.layout.titleSpace=t}get titles(){return this.layout.titles}get expansionToggled(){return this._expansionToggled}addWidget(t){super.addWidget(t),t.title.changed.connect(this._onTitleChanged,this)}collapse(t){let e=this.layout.widgets[t];e&&!e.isHidden&&this._toggleExpansion(t)}expand(t){let e=this.layout.widgets[t];e&&e.isHidden&&this._toggleExpansion(t)}insertWidget(t,e){super.insertWidget(t,e),e.title.changed.connect(this._onTitleChanged,this)}handleEvent(t){switch(super.handleEvent(t),t.type){case"click":this._evtClick(t);break;case"keydown":this._eventKeyDown(t)}}onBeforeAttach(t){this.node.addEventListener("click",this),this.node.addEventListener("keydown",this),super.onBeforeAttach(t)}onAfterDetach(t){super.onAfterDetach(t),this.node.removeEventListener("click",this),this.node.removeEventListener("keydown",this)}_onTitleChanged(t){let e=b.ArrayExt.findFirstIndex(this.widgets,(e=>e.contains(t.owner)));e>=0&&(this.layout.updateTitle(e,t.owner),this.update())}_computeWidgetSize(t){let e=this.layout,r=e.widgets[t];if(!r)return;let n=r.isHidden,i=e.absoluteSizes(),a=(n?-1:1)*this.spacing,o=i.reduce(((t,e)=>t+e)),s=[...i];if(n){let e=this._widgetSizesCache.get(r);if(!e)return;s[t]+=e;let n=s.map((t=>t-e>0)).lastIndexOf(!0);-1===n?s.forEach(((r,n)=>{n!==t&&(s[n]-=i[n]/o*(e-a))})):s[n]-=e-a}else{let e=i[t];this._widgetSizesCache.set(r,e),s[t]=0;let n=s.map((t=>t>0)).lastIndexOf(!0);if(-1===n)return;s[n]=i[n]+e+a}return s.map((t=>t/(o+a)))}_evtClick(t){let e=t.target;if(e){let r=b.ArrayExt.findFirstIndex(this.titles,(t=>t.contains(e)));r>=0&&(t.preventDefault(),t.stopPropagation(),this._toggleExpansion(r))}}_eventKeyDown(t){if(t.defaultPrevented)return;let e=t.target,r=!1;if(e){let n=b.ArrayExt.findFirstIndex(this.titles,(t=>t.contains(e)));if(n>=0){let i=t.keyCode.toString();if(t.key.match(/Space|Enter/)||i.match(/13|32/))e.click(),r=!0;else if("horizontal"===this.orientation?t.key.match(/ArrowLeft|ArrowRight/)||i.match(/37|39/):t.key.match(/ArrowUp|ArrowDown/)||i.match(/38|40/)){let e=t.key.match(/ArrowLeft|ArrowUp/)||i.match(/37|38/)?-1:1,a=this.titles.length,o=(n+a+e)%a;this.titles[o].focus(),r=!0}else"End"===t.key||"35"===i?(this.titles[this.titles.length-1].focus(),r=!0):("Home"===t.key||"36"===i)&&(this.titles[0].focus(),r=!0)}r&&t.preventDefault()}}_toggleExpansion(t){let e=this.titles[t],r=this.layout.widgets[t],n=this._computeWidgetSize(t);n&&this.setRelativeSizes(n,!1),r.isHidden?(e.classList.add("lm-mod-expanded"),e.setAttribute("aria-expanded","true"),r.show()):(e.classList.remove("lm-mod-expanded"),e.setAttribute("aria-expanded","false"),r.hide()),this._expansionToggled.emit(t)}};!function(t){class e extends yt.Renderer{constructor(){super(),this.titleClassName="lm-AccordionPanel-title",this._titleID=0,this._titleKeys=new WeakMap,this._uuid=++e._nInstance}createCollapseIcon(t){return document.createElement("span")}createSectionTitle(t){let e=document.createElement("h3");e.setAttribute("tabindex","0"),e.id=this.createTitleKey(t),e.className=this.titleClassName;for(let r in t.dataset)e.dataset[r]=t.dataset[r];e.appendChild(this.createCollapseIcon(t)).className="lm-AccordionPanel-titleCollapser";let r=e.appendChild(document.createElement("span"));return r.className="lm-AccordionPanel-titleLabel",r.textContent=t.label,r.title=t.caption||t.label,e}createTitleKey(t){let e=this._titleKeys.get(t);return void 0===e&&(e=`title-key-${this._uuid}-${this._titleID++}`,this._titleKeys.set(t,e)),e}}e._nInstance=0,t.Renderer=e,t.defaultRenderer=new e}(xt||(xt={})),function(t){t.createLayout=function(t){return t.layout||new pt({renderer:t.renderer||xt.defaultRenderer,orientation:t.orientation,alignment:t.alignment,spacing:t.spacing,titleSpace:t.titleSpace})}}(vt||(vt={}));var _t,bt=class t extends lt{constructor(t={}){super(),this._fixed=0,this._spacing=4,this._dirty=!1,this._sizers=[],this._items=[],this._box=null,this._alignment="start",this._direction="top-to-bottom",void 0!==t.direction&&(this._direction=t.direction),void 0!==t.alignment&&(this._alignment=t.alignment),void 0!==t.spacing&&(this._spacing=ut.clampDimension(t.spacing))}dispose(){for(let t of this._items)t.dispose();this._box=null,this._items.length=0,this._sizers.length=0,super.dispose()}get direction(){return this._direction}set direction(t){this._direction!==t&&(this._direction=t,this.parent&&(this.parent.dataset.direction=t,this.parent.fit()))}get alignment(){return this._alignment}set alignment(t){this._alignment!==t&&(this._alignment=t,this.parent&&(this.parent.dataset.alignment=t,this.parent.update()))}get spacing(){return this._spacing}set spacing(t){t=ut.clampDimension(t),this._spacing!==t&&(this._spacing=t,this.parent&&this.parent.fit())}init(){this.parent.dataset.direction=this.direction,this.parent.dataset.alignment=this.alignment,super.init()}attachWidget(t,e){b.ArrayExt.insert(this._items,t,new ot(e)),b.ArrayExt.insert(this._sizers,t,new tt),this.parent.isAttached&&M.sendMessage(e,nt.Msg.BeforeAttach),this.parent.node.appendChild(e.node),this.parent.isAttached&&M.sendMessage(e,nt.Msg.AfterAttach),this.parent.fit()}moveWidget(t,e,r){b.ArrayExt.move(this._items,t,e),b.ArrayExt.move(this._sizers,t,e),this.parent.update()}detachWidget(t,e){let r=b.ArrayExt.removeAt(this._items,t);b.ArrayExt.removeAt(this._sizers,t),this.parent.isAttached&&M.sendMessage(e,nt.Msg.BeforeDetach),this.parent.node.removeChild(e.node),this.parent.isAttached&&M.sendMessage(e,nt.Msg.AfterDetach),r.dispose(),this.parent.fit()}onBeforeShow(t){super.onBeforeShow(t),this.parent.update()}onBeforeAttach(t){super.onBeforeAttach(t),this.parent.fit()}onChildShown(t){this.parent.fit()}onChildHidden(t){this.parent.fit()}onResize(t){this.parent.isVisible&&this._update(t.width,t.height)}onUpdateRequest(t){this.parent.isVisible&&this._update(-1,-1)}onFitRequest(t){this.parent.isAttached&&this._fit()}_fit(){let e=0;for(let t=0,r=this._items.length;t0)switch(this._alignment){case"start":break;case"center":c=0,u=n/2;break;case"end":c=0,u=n;break;case"justify":c=n/r,u=0;break;default:throw"unreachable"}for(let t=0,e=this._items.length;t0,coerce:(t,e)=>Math.max(0,Math.floor(e)),changed:e}),t.sizeBasisProperty=new I({name:"sizeBasis",create:()=>0,coerce:(t,e)=>Math.max(0,Math.floor(e)),changed:e}),t.isHorizontal=function(t){return"left-to-right"===t||"right-to-left"===t},t.clampSpacing=function(t){return Math.max(0,Math.floor(t))}}(_t||(_t={}));var wt,Tt=class extends mt{constructor(t={}){super({layout:wt.createLayout(t)}),this.addClass("lm-BoxPanel")}get direction(){return this.layout.direction}set direction(t){this.layout.direction=t}get alignment(){return this.layout.alignment}set alignment(t){this.layout.alignment=t}get spacing(){return this.layout.spacing}set spacing(t){this.layout.spacing=t}onChildAdded(t){t.child.addClass("lm-BoxPanel-child")}onChildRemoved(t){t.child.removeClass("lm-BoxPanel-child")}};!function(t){t.getStretch=function(t){return bt.getStretch(t)},t.setStretch=function(t,e){bt.setStretch(t,e)},t.getSizeBasis=function(t){return bt.getSizeBasis(t)},t.setSizeBasis=function(t,e){bt.setSizeBasis(t,e)}}(Tt||(Tt={})),function(t){t.createLayout=function(t){return t.layout||new bt(t)}}(wt||(wt={}));var kt,At=class t extends nt{constructor(e){super({node:kt.createNode()}),this._activeIndex=-1,this._items=[],this._results=null,this.addClass("lm-CommandPalette"),this.setFlag(nt.Flag.DisallowLayout),this.commands=e.commands,this.renderer=e.renderer||t.defaultRenderer,this.commands.commandChanged.connect(this._onGenericChange,this),this.commands.keyBindingChanged.connect(this._onGenericChange,this)}dispose(){this._items.length=0,this._results=null,super.dispose()}get searchNode(){return this.node.getElementsByClassName("lm-CommandPalette-search")[0]}get inputNode(){return this.node.getElementsByClassName("lm-CommandPalette-input")[0]}get contentNode(){return this.node.getElementsByClassName("lm-CommandPalette-content")[0]}get items(){return this._items}addItem(t){let e=kt.createItem(this.commands,t);return this._items.push(e),this.refresh(),e}addItems(t){let e=t.map((t=>kt.createItem(this.commands,t)));return e.forEach((t=>this._items.push(t))),this.refresh(),e}removeItem(t){this.removeItemAt(this._items.indexOf(t))}removeItemAt(t){b.ArrayExt.removeAt(this._items,t)&&this.refresh()}clearItems(){0!==this._items.length&&(this._items.length=0,this.refresh())}refresh(){this._results=null,""!==this.inputNode.value?this.node.getElementsByClassName("lm-close-icon")[0].style.display="inherit":this.node.getElementsByClassName("lm-close-icon")[0].style.display="none",this.update()}handleEvent(t){switch(t.type){case"click":this._evtClick(t);break;case"keydown":this._evtKeyDown(t);break;case"input":this.refresh();break;case"focus":case"blur":this._toggleFocused()}}onBeforeAttach(t){this.node.addEventListener("click",this),this.node.addEventListener("keydown",this),this.node.addEventListener("input",this),this.node.addEventListener("focus",this,!0),this.node.addEventListener("blur",this,!0)}onAfterDetach(t){this.node.removeEventListener("click",this),this.node.removeEventListener("keydown",this),this.node.removeEventListener("input",this),this.node.removeEventListener("focus",this,!0),this.node.removeEventListener("blur",this,!0)}onAfterShow(t){this.update(),super.onAfterShow(t)}onActivateRequest(t){if(this.isAttached){let t=this.inputNode;t.focus(),t.select()}}onUpdateRequest(t){if(this.isHidden)return;let e=this.inputNode.value,r=this.contentNode,n=this._results;if(n||(n=this._results=kt.search(this._items,e),this._activeIndex=e?b.ArrayExt.findFirstIndex(n,kt.canActivate):-1),!e&&0===n.length)return void Z.render(null,r);if(e&&0===n.length){let t=this.renderer.renderEmptyMessage({query:e});return void Z.render(t,r)}let a=this.renderer,o=this._activeIndex,s=new Array(n.length);for(let t=0,e=n.length;t=n.length)r.scrollTop=0;else{let t=r.children[o];i.scrollIntoViewIfNeeded(r,t)}}_evtClick(t){if(0!==t.button)return;if(t.target.classList.contains("lm-close-icon"))return this.inputNode.value="",void this.refresh();let e=b.ArrayExt.findFirstIndex(this.contentNode.children,(e=>e.contains(t.target)));-1!==e&&(t.preventDefault(),t.stopPropagation(),this._execute(e))}_evtKeyDown(t){if(!(t.altKey||t.ctrlKey||t.metaKey||t.shiftKey))switch(t.keyCode){case 13:t.preventDefault(),t.stopPropagation(),this._execute(this._activeIndex);break;case 38:t.preventDefault(),t.stopPropagation(),this._activatePreviousItem();break;case 40:t.preventDefault(),t.stopPropagation(),this._activateNextItem()}}_activateNextItem(){if(!this._results||0===this._results.length)return;let t=this._activeIndex,e=this._results.length,r=tt-e)),c=a.slice(0,l),u=a.slice(l);for(let t=0,e=u.length;tr.command===t&&w.JSONExt.deepEqual(r.args,e)))||null}}}(kt||(kt={}));var Mt,St,Et=class t extends nt{constructor(e){super({node:Mt.createNode()}),this._childIndex=-1,this._activeIndex=-1,this._openTimerID=0,this._closeTimerID=0,this._items=[],this._childMenu=null,this._parentMenu=null,this._aboutToClose=new z(this),this._menuRequested=new z(this),this.addClass("lm-Menu"),this.setFlag(nt.Flag.DisallowLayout),this.commands=e.commands,this.renderer=e.renderer||t.defaultRenderer}dispose(){this.close(),this._items.length=0,super.dispose()}get aboutToClose(){return this._aboutToClose}get menuRequested(){return this._menuRequested}get parentMenu(){return this._parentMenu}get childMenu(){return this._childMenu}get rootMenu(){let t=this;for(;t._parentMenu;)t=t._parentMenu;return t}get leafMenu(){let t=this;for(;t._childMenu;)t=t._childMenu;return t}get contentNode(){return this.node.getElementsByClassName("lm-Menu-content")[0]}get activeItem(){return this._items[this._activeIndex]||null}set activeItem(t){this.activeIndex=t?this._items.indexOf(t):-1}get activeIndex(){return this._activeIndex}set activeIndex(t){(t<0||t>=this._items.length)&&(t=-1),-1!==t&&!Mt.canActivate(this._items[t])&&(t=-1),this._activeIndex!==t&&(this._activeIndex=t,this._activeIndex>=0&&this.contentNode.childNodes[this._activeIndex]&&this.contentNode.childNodes[this._activeIndex].focus(),this.update())}get items(){return this._items}activateNextItem(){let t=this._items.length,e=this._activeIndex,r=e{this.activeIndex=t}})}Z.render(a,this.contentNode)}onCloseRequest(t){this._cancelOpenTimer(),this._cancelCloseTimer(),this.activeIndex=-1;let e=this._childMenu;e&&(this._childIndex=-1,this._childMenu=null,e._parentMenu=null,e.close());let r=this._parentMenu;r&&(this._parentMenu=null,r._childIndex=-1,r._childMenu=null,r.activate()),this.isAttached&&this._aboutToClose.emit(void 0),super.onCloseRequest(t)}_evtKeyDown(t){t.preventDefault(),t.stopPropagation();let e=t.keyCode;if(13===e)return void this.triggerActiveItem();if(27===e)return void this.close();if(37===e)return void(this._parentMenu?this.close():this._menuRequested.emit("previous"));if(38===e)return void this.activatePreviousItem();if(39===e){let t=this.activeItem;return void(t&&"submenu"===t.type?this.triggerActiveItem():this.rootMenu._menuRequested.emit("next"))}if(40===e)return void this.activateNextItem();let r=U().keyForKeydownEvent(t);if(!r)return;let n=this._activeIndex+1,i=Mt.findMnemonic(this._items,r,n);-1===i.index||i.multiple?-1!==i.index?this.activeIndex=i.index:-1!==i.auto&&(this.activeIndex=i.auto):(this.activeIndex=i.index,this.triggerActiveItem())}_evtMouseUp(t){0===t.button&&(t.preventDefault(),t.stopPropagation(),this.triggerActiveItem())}_evtMouseMove(t){let e=b.ArrayExt.findFirstIndex(this.contentNode.children,(e=>i.hitTest(e,t.clientX,t.clientY)));if(e===this._activeIndex)return;if(this.activeIndex=e,e=this.activeIndex,e===this._childIndex)return this._cancelOpenTimer(),void this._cancelCloseTimer();-1!==this._childIndex&&this._startCloseTimer(),this._cancelOpenTimer();let r=this.activeItem;!r||"submenu"!==r.type||!r.submenu||this._startOpenTimer()}_evtMouseEnter(t){for(let t=this._parentMenu;t;t=t._parentMenu)t._cancelOpenTimer(),t._cancelCloseTimer(),t.activeIndex=t._childIndex}_evtMouseLeave(t){if(this._cancelOpenTimer(),!this._childMenu)return void(this.activeIndex=-1);let{clientX:e,clientY:r}=t;i.hitTest(this._childMenu.node,e,r)?this._cancelCloseTimer():(this.activeIndex=-1,this._startCloseTimer())}_evtMouseDown(t){this._parentMenu||(Mt.hitTestMenus(this,t.clientX,t.clientY)?(t.preventDefault(),t.stopPropagation()):this.close())}_openChildMenu(e=!1){let r=this.activeItem;if(!r||"submenu"!==r.type||!r.submenu)return void this._closeChildMenu();let n=r.submenu;if(n===this._childMenu)return;t.saveWindowData(),this._closeChildMenu(),this._childMenu=n,this._childIndex=this._activeIndex,n._parentMenu=this,M.sendMessage(this,nt.Msg.UpdateRequest);let i=this.contentNode.children[this._activeIndex];Mt.openSubmenu(n,i),e&&(n.activeIndex=-1,n.activateNextItem()),n.activate()}_closeChildMenu(){this._childMenu&&this._childMenu.close()}_startOpenTimer(){0===this._openTimerID&&(this._openTimerID=window.setTimeout((()=>{this._openTimerID=0,this._openChildMenu()}),Mt.TIMER_DELAY))}_startCloseTimer(){0===this._closeTimerID&&(this._closeTimerID=window.setTimeout((()=>{this._closeTimerID=0,this._closeChildMenu()}),Mt.TIMER_DELAY))}_cancelOpenTimer(){0!==this._openTimerID&&(clearTimeout(this._openTimerID),this._openTimerID=0)}_cancelCloseTimer(){0!==this._closeTimerID&&(clearTimeout(this._closeTimerID),this._closeTimerID=0)}static saveWindowData(){Mt.saveWindowData()}};!function(t){class e{renderItem(t){let e=this.createItemClass(t),r=this.createItemDataset(t),n=this.createItemARIA(t);return J.li({className:e,dataset:r,tabindex:"0",onfocus:t.onfocus,...n},this.renderIcon(t),this.renderLabel(t),this.renderShortcut(t),this.renderSubmenu(t))}renderIcon(t){let e=this.createIconClass(t);return J.div({className:e},t.item.icon,t.item.iconLabel)}renderLabel(t){let e=this.formatLabel(t);return J.div({className:"lm-Menu-itemLabel"},e)}renderShortcut(t){let e=this.formatShortcut(t);return J.div({className:"lm-Menu-itemShortcut"},e)}renderSubmenu(t){return J.div({className:"lm-Menu-itemSubmenuIcon"})}createItemClass(t){let e="lm-Menu-item";t.item.isEnabled||(e+=" lm-mod-disabled"),t.item.isToggled&&(e+=" lm-mod-toggled"),t.item.isVisible||(e+=" lm-mod-hidden"),t.active&&(e+=" lm-mod-active"),t.collapsed&&(e+=" lm-mod-collapsed");let r=t.item.className;return r&&(e+=` ${r}`),e}createItemDataset(t){let e,{type:r,command:n,dataset:i}=t.item;return e="command"===r?{...i,type:r,command:n}:{...i,type:r},e}createIconClass(t){let e="lm-Menu-itemIcon",r=t.item.iconClass;return r?`${e} ${r}`:e}createItemARIA(t){let e={};switch(t.item.type){case"separator":e.role="presentation";break;case"submenu":e["aria-haspopup"]="true",t.item.isEnabled||(e["aria-disabled"]="true");break;default:t.item.isEnabled||(e["aria-disabled"]="true"),e.role="menuitem"}return e}formatLabel(t){let{label:e,mnemonic:r}=t.item;if(r<0||r>=e.length)return e;let n=e.slice(0,r),i=e.slice(r+1),a=e[r];return[n,J.span({className:"lm-Menu-itemMnemonic"},a),i]}formatShortcut(t){let e=t.item.keyBinding;return e?W.formatKeystroke(e.keys):null}}t.Renderer=e,t.defaultRenderer=new e}(Et||(Et={})),function(t){t.TIMER_DELAY=300,t.SUBMENU_OVERLAP=3;let e=null,r=0;function n(){return r>0?(r--,e):o()}function a(t){return"separator"!==t.type&&t.isEnabled&&t.isVisible}function o(){return{pageXOffset:window.pageXOffset,pageYOffset:window.pageYOffset,clientWidth:document.documentElement.clientWidth,clientHeight:document.documentElement.clientHeight}}t.saveWindowData=function(){e=o(),r++},t.createNode=function(){let t=document.createElement("div"),e=document.createElement("ul");return e.className="lm-Menu-content",t.appendChild(e),e.setAttribute("role","menu"),t.tabIndex=0,t},t.canActivate=a,t.createItem=function(t,e){return new s(t.commands,e)},t.hitTestMenus=function(t,e,r){for(let n=t;n;n=n.childMenu)if(i.hitTest(n.node,e,r))return!0;return!1},t.computeCollapsed=function(t){let e=new Array(t.length);b.ArrayExt.fill(e,!1);let r=0,n=t.length;for(;r=0;--i){let r=t[i];if(r.isVisible){if("separator"!==r.type)break;e[i]=!0}}let a=!1;for(;++rc+h&&(e=c+h-g),!a&&r+y>u+f&&(r>u+f?r=u+f-y:r-=y),m.transform=`translate(${Math.max(0,e)}px, ${Math.max(0,r)}px`,m.opacity="1"},t.openSubmenu=function(e,r){let a=n(),o=a.pageXOffset,s=a.pageYOffset,l=a.clientWidth,c=a.clientHeight;M.sendMessage(e,nt.Msg.UpdateRequest);let u=c,h=e.node,f=h.style;f.opacity="0",f.maxHeight=`${u}px`,nt.attach(e,document.body);let{width:p,height:d}=h.getBoundingClientRect(),m=i.boxSizing(e.node),g=r.getBoundingClientRect(),y=g.right-t.SUBMENU_OVERLAP;y+p>o+l&&(y=g.left+t.SUBMENU_OVERLAP-p);let v=g.top-m.borderTop-m.paddingTop;v+d>s+c&&(v=g.bottom+m.borderBottom+m.paddingBottom-d),f.transform=`translate(${Math.max(0,y)}px, ${Math.max(0,v)}px`,f.opacity="1"},t.findMnemonic=function(t,e,r){let n=-1,i=-1,o=!1,s=e.toUpperCase();for(let e=0,l=t.length;e=0&&fr.command===t&&w.JSONExt.deepEqual(r.args,e)))||null}return null}}}(Mt||(Mt={})),function(t){function e(t,e){let r=t.rank,n=e.rank;return r!==n?r=this._titles.length)&&(t=-1),this._currentIndex===t)return;let e=this._currentIndex,r=this._titles[e]||null,n=t,i=this._titles[n]||null;this._currentIndex=n,this._previousTitle=r,this.update(),this._currentChanged.emit({previousIndex:e,previousTitle:r,currentIndex:n,currentTitle:i})}get name(){return this._name}set name(t){this._name=t,t?this.contentNode.setAttribute("aria-label",t):this.contentNode.removeAttribute("aria-label")}get orientation(){return this._orientation}set orientation(t){this._orientation!==t&&(this._releaseMouse(),this._orientation=t,this.dataset.orientation=t,this.contentNode.setAttribute("aria-orientation",t))}get addButtonEnabled(){return this._addButtonEnabled}set addButtonEnabled(t){this._addButtonEnabled!==t&&(this._addButtonEnabled=t,t?this.addButtonNode.classList.remove("lm-mod-hidden"):this.addButtonNode.classList.add("lm-mod-hidden"))}get titles(){return this._titles}get contentNode(){return this.node.getElementsByClassName("lm-TabBar-content")[0]}get addButtonNode(){return this.node.getElementsByClassName("lm-TabBar-addButton")[0]}addTab(t){return this.insertTab(this._titles.length,t)}insertTab(t,e){this._releaseMouse();let r=Ct.asTitle(e),n=this._titles.indexOf(r),i=Math.max(0,Math.min(t,this._titles.length));return-1===n?(b.ArrayExt.insert(this._titles,i,r),r.changed.connect(this._onTitleChanged,this),this.update(),this._adjustCurrentForInsert(i,r),r):(i===this._titles.length&&i--,n===i||(b.ArrayExt.move(this._titles,n,i),this.update(),this._adjustCurrentForMove(n,i)),r)}removeTab(t){this.removeTabAt(this._titles.indexOf(t))}removeTabAt(t){this._releaseMouse();let e=b.ArrayExt.removeAt(this._titles,t);e&&(e.changed.disconnect(this._onTitleChanged,this),e===this._previousTitle&&(this._previousTitle=null),this.update(),this._adjustCurrentForRemove(t,e))}clearTabs(){if(0===this._titles.length)return;this._releaseMouse();for(let t of this._titles)t.changed.disconnect(this._onTitleChanged,this);let t=this.currentIndex,e=this.currentTitle;this._currentIndex=-1,this._previousTitle=null,this._titles.length=0,this.update(),-1!==t&&this._currentChanged.emit({previousIndex:t,previousTitle:e,currentIndex:-1,currentTitle:null})}releaseMouse(){this._releaseMouse()}handleEvent(t){switch(t.type){case"pointerdown":this._evtPointerDown(t);break;case"pointermove":this._evtPointerMove(t);break;case"pointerup":this._evtPointerUp(t);break;case"dblclick":this._evtDblClick(t);break;case"keydown":t.eventPhase===Event.CAPTURING_PHASE?this._evtKeyDownCapturing(t):this._evtKeyDown(t);break;case"contextmenu":t.preventDefault(),t.stopPropagation()}}onBeforeAttach(t){this.node.addEventListener("pointerdown",this),this.node.addEventListener("dblclick",this),this.node.addEventListener("keydown",this)}onAfterDetach(t){this.node.removeEventListener("pointerdown",this),this.node.removeEventListener("dblclick",this),this.node.removeEventListener("keydown",this),this._releaseMouse()}onUpdateRequest(t){var e;let r=this._titles,n=this.renderer,i=this.currentTitle,a=new Array(r.length),o=null!==(e=this._getCurrentTabindex())&&void 0!==e?e:this._currentIndex>-1?this._currentIndex:0;for(let t=0,e=r.length;ti.hitTest(e,t.clientX,t.clientY)));if(-1===r)return;let n=this.titles[r],a=e[r].querySelector(".lm-TabBar-tabLabel");if(a&&a.contains(t.target)){let t=n.label||"",e=a.innerHTML;a.innerHTML="";let r=document.createElement("input");r.classList.add("lm-TabBar-tabInput"),r.value=t,a.appendChild(r);let i=()=>{r.removeEventListener("blur",i),a.innerHTML=e,this.node.addEventListener("keydown",this)};r.addEventListener("dblclick",(t=>t.stopPropagation())),r.addEventListener("blur",i),r.addEventListener("keydown",(t=>{"Enter"===t.key?(""!==r.value&&(n.label=n.caption=r.value),i()):"Escape"===t.key&&i()})),this.node.removeEventListener("keydown",this),r.select(),r.focus(),a.children.length>0&&a.children[0].focus()}}_evtKeyDownCapturing(t){t.eventPhase===Event.CAPTURING_PHASE&&(t.preventDefault(),t.stopPropagation(),"Escape"===t.key&&this._releaseMouse())}_evtKeyDown(t){var e,r,n;if("Tab"!==t.key&&t.eventPhase!==Event.CAPTURING_PHASE)if("Enter"===t.key||"Spacebar"===t.key||" "===t.key){let e=document.activeElement;if(this.addButtonEnabled&&this.addButtonNode.contains(e))t.preventDefault(),t.stopPropagation(),this._addRequested.emit();else{let r=b.ArrayExt.findFirstIndex(this.contentNode.children,(t=>t.contains(e)));r>=0&&(t.preventDefault(),t.stopPropagation(),this.currentIndex=r)}}else if(It.includes(t.key)){let i=[...this.contentNode.children];if(this.addButtonEnabled&&i.push(this.addButtonNode),i.length<=1)return;t.preventDefault(),t.stopPropagation();let a,o=i.indexOf(document.activeElement);-1===o&&(o=this._currentIndex),"ArrowRight"===t.key&&"horizontal"===this._orientation||"ArrowDown"===t.key&&"vertical"===this._orientation?a=null!==(e=i[o+1])&&void 0!==e?e:i[0]:"ArrowLeft"===t.key&&"horizontal"===this._orientation||"ArrowUp"===t.key&&"vertical"===this._orientation?a=null!==(r=i[o-1])&&void 0!==r?r:i[i.length-1]:"Home"===t.key?a=i[0]:"End"===t.key&&(a=i[i.length-1]),a&&(null===(n=i[o])||void 0===n||n.setAttribute("tabindex","-1"),a?.setAttribute("tabindex","0"),a.focus())}}_evtPointerDown(t){if(0!==t.button&&1!==t.button||this._dragData||t.target.classList.contains("lm-TabBar-tabInput"))return;let e=this.addButtonEnabled&&this.addButtonNode.contains(t.target),r=this.contentNode.children,n=b.ArrayExt.findFirstIndex(r,(e=>i.hitTest(e,t.clientX,t.clientY)));if(-1===n&&!e||(t.preventDefault(),t.stopPropagation(),this._dragData={tab:r[n],index:n,pressX:t.clientX,pressY:t.clientY,tabPos:-1,tabSize:-1,tabPressPos:-1,targetIndex:-1,tabLayout:null,contentRect:null,override:null,dragActive:!1,dragAborted:!1,detachRequested:!1},this.document.addEventListener("pointerup",this,!0),1===t.button||e))return;let a=r[n].querySelector(this.renderer.closeIconSelector);a&&a.contains(t.target)||(this.tabsMovable&&(this.document.addEventListener("pointermove",this,!0),this.document.addEventListener("keydown",this,!0),this.document.addEventListener("contextmenu",this,!0)),this.allowDeselect&&this.currentIndex===n?this.currentIndex=-1:this.currentIndex=n,-1!==this.currentIndex&&this._tabActivateRequested.emit({index:this.currentIndex,title:this.currentTitle}))}_evtPointerMove(t){let e=this._dragData;if(!e)return;t.preventDefault(),t.stopPropagation();let r=this.contentNode.children;if(e.dragActive||Ct.dragExceeded(e,t)){if(!e.dragActive){let t=e.tab.getBoundingClientRect();"horizontal"===this._orientation?(e.tabPos=e.tab.offsetLeft,e.tabSize=t.width,e.tabPressPos=e.pressX-t.left):(e.tabPos=e.tab.offsetTop,e.tabSize=t.height,e.tabPressPos=e.pressY-t.top),e.tabPressOffset={x:e.pressX-t.left,y:e.pressY-t.top},e.tabLayout=Ct.snapTabLayout(r,this._orientation),e.contentRect=this.contentNode.getBoundingClientRect(),e.override=B.overrideCursor("default"),e.tab.classList.add("lm-mod-dragging"),this.addClass("lm-mod-dragging"),e.dragActive=!0}if(!e.detachRequested&&Ct.detachExceeded(e,t)){e.detachRequested=!0;let n=e.index,i=t.clientX,a=t.clientY,o=r[n],s=this._titles[n];if(this._tabDetachRequested.emit({index:n,title:s,tab:o,clientX:i,clientY:a,offset:e.tabPressOffset}),e.dragAborted)return}Ct.layoutTabs(r,e,t,this._orientation)}}_evtPointerUp(t){if(0!==t.button&&1!==t.button)return;let e=this._dragData;if(!e)return;if(t.preventDefault(),t.stopPropagation(),this.document.removeEventListener("pointermove",this,!0),this.document.removeEventListener("pointerup",this,!0),this.document.removeEventListener("keydown",this,!0),this.document.removeEventListener("contextmenu",this,!0),!e.dragActive){if(this._dragData=null,this.addButtonEnabled&&this.addButtonNode.contains(t.target))return void this._addRequested.emit(void 0);let r=this.contentNode.children,n=b.ArrayExt.findFirstIndex(r,(e=>i.hitTest(e,t.clientX,t.clientY)));if(n!==e.index)return;let a=this._titles[n];if(!a.closable)return;if(1===t.button)return void this._tabCloseRequested.emit({index:n,title:a});let o=r[n].querySelector(this.renderer.closeIconSelector);return o&&o.contains(t.target)?void this._tabCloseRequested.emit({index:n,title:a}):void 0}if(0!==t.button)return;Ct.finalizeTabPosition(e,this._orientation),e.tab.classList.remove("lm-mod-dragging");let r=Ct.parseTransitionDuration(e.tab);setTimeout((()=>{if(e.dragAborted)return;this._dragData=null,Ct.resetTabPositions(this.contentNode.children,this._orientation),e.override.dispose(),this.removeClass("lm-mod-dragging");let t=e.index,r=e.targetIndex;-1===r||t===r||(b.ArrayExt.move(this._titles,t,r),this._adjustCurrentForMove(t,r),this._tabMoved.emit({fromIndex:t,toIndex:r,title:this._titles[r]}),M.sendMessage(this,nt.Msg.UpdateRequest))}),r)}_releaseMouse(){let t=this._dragData;t&&(this._dragData=null,this.document.removeEventListener("pointermove",this,!0),this.document.removeEventListener("pointerup",this,!0),this.document.removeEventListener("keydown",this,!0),this.document.removeEventListener("contextmenu",this,!0),t.dragAborted=!0,t.dragActive&&(Ct.resetTabPositions(this.contentNode.children,this._orientation),t.override.dispose(),t.tab.classList.remove("lm-mod-dragging"),this.removeClass("lm-mod-dragging")))}_adjustCurrentForInsert(t,e){let r=this.currentTitle,n=this._currentIndex,i=this.insertBehavior;if("select-tab"===i||"select-tab-if-needed"===i&&-1===n)return this._currentIndex=t,this._previousTitle=r,void this._currentChanged.emit({previousIndex:n,previousTitle:r,currentIndex:t,currentTitle:e});n>=t&&this._currentIndex++}_adjustCurrentForMove(t,e){this._currentIndex===t?this._currentIndex=e:this._currentIndex=e?this._currentIndex++:this._currentIndex>t&&this._currentIndex<=e&&this._currentIndex--}_adjustCurrentForRemove(t,e){let r=this._currentIndex,n=this.removeBehavior;if(r===t)return 0===this._titles.length?(this._currentIndex=-1,void this._currentChanged.emit({previousIndex:t,previousTitle:e,currentIndex:-1,currentTitle:null})):"select-tab-after"===n?(this._currentIndex=Math.min(t,this._titles.length-1),void this._currentChanged.emit({previousIndex:t,previousTitle:e,currentIndex:this._currentIndex,currentTitle:this.currentTitle})):"select-tab-before"===n?(this._currentIndex=Math.max(0,t-1),void this._currentChanged.emit({previousIndex:t,previousTitle:e,currentIndex:this._currentIndex,currentTitle:this.currentTitle})):"select-previous-tab"===n?(this._previousTitle?(this._currentIndex=this._titles.indexOf(this._previousTitle),this._previousTitle=null):this._currentIndex=Math.min(t,this._titles.length-1),void this._currentChanged.emit({previousIndex:t,previousTitle:e,currentIndex:this._currentIndex,currentTitle:this.currentTitle})):(this._currentIndex=-1,void this._currentChanged.emit({previousIndex:t,previousTitle:e,currentIndex:-1,currentTitle:null}));r>t&&this._currentIndex--}_onTitleChanged(t){this.update()}};!function(t){class e{constructor(){this.closeIconSelector=".lm-TabBar-tabCloseIcon",this._tabID=0,this._tabKeys=new WeakMap,this._uuid=++e._nInstance}renderTab(t){let e=t.title.caption,r=this.createTabKey(t),n=r,i=this.createTabStyle(t),a=this.createTabClass(t),o=this.createTabDataset(t),s=this.createTabARIA(t);return t.title.closable?J.li({id:n,key:r,className:a,title:e,style:i,dataset:o,...s},this.renderIcon(t),this.renderLabel(t),this.renderCloseIcon(t)):J.li({id:n,key:r,className:a,title:e,style:i,dataset:o,...s},this.renderIcon(t),this.renderLabel(t))}renderIcon(t){let{title:e}=t,r=this.createIconClass(t);return J.div({className:r},e.icon,e.iconLabel)}renderLabel(t){return J.div({className:"lm-TabBar-tabLabel"},t.title.label)}renderCloseIcon(t){return J.div({className:"lm-TabBar-tabCloseIcon"})}createTabKey(t){let e=this._tabKeys.get(t.title);return void 0===e&&(e=`tab-key-${this._uuid}-${this._tabID++}`,this._tabKeys.set(t.title,e)),e}createTabStyle(t){return{zIndex:`${t.zIndex}`}}createTabClass(t){let e="lm-TabBar-tab";return t.title.className&&(e+=` ${t.title.className}`),t.title.closable&&(e+=" lm-mod-closable"),t.current&&(e+=" lm-mod-current"),e}createTabDataset(t){return t.title.dataset}createTabARIA(t){var e;return{role:"tab","aria-selected":t.current.toString(),tabindex:`${null!==(e=t.tabIndex)&&void 0!==e?e:"-1"}`}}createIconClass(t){let e="lm-TabBar-tabIcon",r=t.title.iconClass;return r?`${e} ${r}`:e}}e._nInstance=0,t.Renderer=e,t.defaultRenderer=new e,t.addButtonSelector=".lm-TabBar-addButton"}(Lt||(Lt={})),function(t){t.DRAG_THRESHOLD=5,t.DETACH_THRESHOLD=20,t.createNode=function(){let t=document.createElement("div"),e=document.createElement("ul");e.setAttribute("role","tablist"),e.className="lm-TabBar-content",t.appendChild(e);let r=document.createElement("div");return r.className="lm-TabBar-addButton lm-mod-hidden",r.setAttribute("tabindex","-1"),r.setAttribute("role","button"),t.appendChild(r),t},t.asTitle=function(t){return t instanceof rt?t:new rt(t)},t.parseTransitionDuration=function(t){let e=window.getComputedStyle(t);return 1e3*(parseFloat(e.transitionDuration)||0)},t.snapTabLayout=function(t,e){let r=new Array(t.length);for(let n=0,i=t.length;n=t.DRAG_THRESHOLD||i>=t.DRAG_THRESHOLD},t.detachExceeded=function(e,r){let n=e.contentRect;return r.clientX=n.right+t.DETACH_THRESHOLD||r.clientY=n.bottom+t.DETACH_THRESHOLD},t.layoutTabs=function(t,e,r,n){let i,a,o,s;"horizontal"===n?(i=e.pressX,a=r.clientX-e.contentRect.left,o=r.clientX,s=e.contentRect.width):(i=e.pressY,a=r.clientY-e.contentRect.top,o=r.clientY,s=e.contentRect.height);let l=e.index,c=a-e.tabPressPos,u=c+e.tabSize;for(let r=0,a=t.length;r>1);if(re.index&&u>f)a=-e.tabSize-h.margin+"px",l=Math.max(l,r);else if(r===e.index){let t=o-i,r=s-(e.tabPos+e.tabSize);a=`${Math.max(-e.tabPos,Math.min(t,r))}px`}else a="";"horizontal"===n?t[r].style.left=a:t[r].style.top=a}e.targetIndex=l},t.finalizeTabPosition=function(t,e){let r,n;if(r="horizontal"===e?t.contentRect.width:t.contentRect.height,t.targetIndex===t.index)n=0;else if(t.targetIndex>t.index){let e=t.tabLayout[t.targetIndex];n=e.pos+e.size-t.tabSize-t.tabPos}else n=t.tabLayout[t.targetIndex].pos-t.tabPos;let i=r-(t.tabPos+t.tabSize),a=Math.max(-t.tabPos,Math.min(n,i));"horizontal"===e?t.tab.style.left=`${a}px`:t.tab.style.top=`${a}px`},t.resetTabPositions=function(t,e){for(let r of t)"horizontal"===e?r.style.left="":r.style.top=""}}(Ct||(Ct={}));var Pt,zt=class extends it{constructor(t){super(),this._spacing=4,this._dirty=!1,this._root=null,this._box=null,this._items=new Map,this.renderer=t.renderer,void 0!==t.spacing&&(this._spacing=ut.clampDimension(t.spacing)),this._document=t.document||document,this._hiddenMode=void 0!==t.hiddenMode?t.hiddenMode:nt.HiddenMode.Display}dispose(){let t=this[Symbol.iterator]();this._items.forEach((t=>{t.dispose()})),this._box=null,this._root=null,this._items.clear();for(let e of t)e.dispose();super.dispose()}get hiddenMode(){return this._hiddenMode}set hiddenMode(t){if(this._hiddenMode!==t){this._hiddenMode=t;for(let t of this.tabBars())if(t.titles.length>1)for(let e of t.titles)e.owner.hiddenMode=this._hiddenMode}}get spacing(){return this._spacing}set spacing(t){t=ut.clampDimension(t),this._spacing!==t&&(this._spacing=t,this.parent&&this.parent.fit())}get isEmpty(){return null===this._root}[Symbol.iterator](){return this._root?this._root.iterAllWidgets():(0,b.empty)()}widgets(){return this._root?this._root.iterUserWidgets():(0,b.empty)()}selectedWidgets(){return this._root?this._root.iterSelectedWidgets():(0,b.empty)()}tabBars(){return this._root?this._root.iterTabBars():(0,b.empty)()}handles(){return this._root?this._root.iterHandles():(0,b.empty)()}moveHandle(t,e,r){let n=t.classList.contains("lm-mod-hidden");if(!this._root||n)return;let i,a=this._root.findSplitNode(t);a&&(i="horizontal"===a.node.orientation?e-t.offsetLeft:r-t.offsetTop,0!==i&&(a.node.holdSizes(),Q.adjust(a.node.sizers,a.index,i),this.parent&&this.parent.update()))}saveLayout(){return this._root?(this._root.holdAllSizes(),{main:this._root.createConfig()}):{main:null}}restoreLayout(t){let e,r=new Set;e=t.main?Pt.normalizeAreaConfig(t.main,r):null;let n=this.widgets(),i=this.tabBars(),a=this.handles();this._root=null;for(let t of n)r.has(t)||(t.parent=null);for(let t of i)t.dispose();for(let t of a)t.parentNode&&t.parentNode.removeChild(t);for(let t of r)t.parent=this.parent;this._root=e?Pt.realizeAreaConfig(e,{createTabBar:t=>this._createTabBar(),createHandle:()=>this._createHandle()},this._document):null,this.parent&&(r.forEach((t=>{this.attachWidget(t)})),this.parent.fit())}addWidget(t,e={}){let r=e.ref||null,n=e.mode||"tab-after",i=null;if(this._root&&r&&(i=this._root.findTabNode(r)),r&&!i)throw new Error("Reference widget is not in the layout.");switch(t.parent=this.parent,n){case"tab-after":this._insertTab(t,r,i,!0);break;case"tab-before":this._insertTab(t,r,i,!1);break;case"split-top":this._insertSplit(t,r,i,"vertical",!1);break;case"split-left":this._insertSplit(t,r,i,"horizontal",!1);break;case"split-right":this._insertSplit(t,r,i,"horizontal",!0);break;case"split-bottom":this._insertSplit(t,r,i,"vertical",!0);break;case"merge-top":this._insertSplit(t,r,i,"vertical",!1,!0);break;case"merge-left":this._insertSplit(t,r,i,"horizontal",!1,!0);break;case"merge-right":this._insertSplit(t,r,i,"horizontal",!0,!0);break;case"merge-bottom":this._insertSplit(t,r,i,"vertical",!0,!0)}this.parent&&(this.attachWidget(t),this.parent.fit())}removeWidget(t){this._removeWidget(t),this.parent&&(this.detachWidget(t),this.parent.fit())}hitTestTabAreas(t,e){if(!this._root||!this.parent||!this.parent.isVisible)return null;this._box||(this._box=i.boxSizing(this.parent.node));let r=this.parent.node.getBoundingClientRect(),n=t-r.left-this._box.borderLeft,a=e-r.top-this._box.borderTop,o=this._root.hitTestTabNodes(n,a);if(!o)return null;let{tabBar:s,top:l,left:c,width:u,height:h}=o,f=this._box.borderLeft+this._box.borderRight,p=this._box.borderTop+this._box.borderBottom;return{tabBar:s,x:n,y:a,top:l,left:c,right:r.width-f-(c+u),bottom:r.height-p-(l+h),width:u,height:h}}init(){super.init();for(let t of this)this.attachWidget(t);for(let t of this.handles())this.parent.node.appendChild(t);this.parent.fit()}attachWidget(t){this.parent.node!==t.node.parentNode&&(this._items.set(t,new ot(t)),this.parent.isAttached&&M.sendMessage(t,nt.Msg.BeforeAttach),this.parent.node.appendChild(t.node),this.parent.isAttached&&M.sendMessage(t,nt.Msg.AfterAttach))}detachWidget(t){if(this.parent.node!==t.node.parentNode)return;this.parent.isAttached&&M.sendMessage(t,nt.Msg.BeforeDetach),this.parent.node.removeChild(t.node),this.parent.isAttached&&M.sendMessage(t,nt.Msg.AfterDetach);let e=this._items.get(t);e&&(this._items.delete(t),e.dispose())}onBeforeShow(t){super.onBeforeShow(t),this.parent.update()}onBeforeAttach(t){super.onBeforeAttach(t),this.parent.fit()}onChildShown(t){this.parent.fit()}onChildHidden(t){this.parent.fit()}onResize(t){this.parent.isVisible&&this._update(t.width,t.height)}onUpdateRequest(t){this.parent.isVisible&&this._update(-1,-1)}onFitRequest(t){this.parent.isAttached&&this._fit()}_removeWidget(t){if(!this._root)return;let e=this._root.findTabNode(t);if(!e)return;if(Pt.removeAria(t),e.tabBar.titles.length>1)return e.tabBar.removeTab(t.title),void(this._hiddenMode===nt.HiddenMode.Scale&&1==e.tabBar.titles.length&&(e.tabBar.titles[0].owner.hiddenMode=nt.HiddenMode.Display));if(e.tabBar.dispose(),this._root===e)return void(this._root=null);this._root.holdAllSizes();let r=e.parent;e.parent=null;let n=b.ArrayExt.removeFirstOf(r.children,e),i=b.ArrayExt.removeAt(r.handles,n);if(b.ArrayExt.removeAt(r.sizers,n),i.parentNode&&i.parentNode.removeChild(i),r.children.length>1)return void r.syncHandles();let a=r.parent;r.parent=null;let o=r.children[0],s=r.handles[0];if(r.children.length=0,r.handles.length=0,r.sizers.length=0,s.parentNode&&s.parentNode.removeChild(s),this._root===r)return o.parent=null,void(this._root=o);let l=a,c=l.children.indexOf(r);if(o instanceof Pt.TabLayoutNode)return o.parent=l,void(l.children[c]=o);let u=b.ArrayExt.removeAt(l.handles,c);b.ArrayExt.removeAt(l.children,c),b.ArrayExt.removeAt(l.sizers,c),u.parentNode&&u.parentNode.removeChild(u);for(let t=0,e=o.children.length;t=r.length)&&(n=0),{type:"tab-area",widgets:r,currentIndex:n}}(e,r):function(e,r){let n=e.orientation,i=[],a=[];for(let o=0,s=e.children.length;o{let l=i(n,r,a),c=e(t.sizes[s]),u=r.createHandle();o.children.push(l),o.handles.push(u),o.sizers.push(c),l.parent=o})),o.syncHandles(),o.normalizeSizes(),o}(a,o,s),l};class r{constructor(t){this.parent=null,this._top=0,this._left=0,this._width=0,this._height=0;let e=new tt,r=new tt;e.stretch=0,r.stretch=1,this.tabBar=t,this.sizers=[e,r]}get top(){return this._top}get left(){return this._left}get width(){return this._width}get height(){return this._height}*iterAllWidgets(){yield this.tabBar,yield*this.iterUserWidgets()}*iterUserWidgets(){for(let t of this.tabBar.titles)yield t.owner}*iterSelectedWidgets(){let t=this.tabBar.currentTitle;t&&(yield t.owner)}*iterTabBars(){yield this.tabBar}*iterHandles(){}findTabNode(t){return-1!==this.tabBar.titles.indexOf(t.title)?this:null}findSplitNode(t){return null}findFirstTabNode(){return this}hitTestTabNodes(t,e){return t=this._left+this._width||e=this._top+this._height?null:this}createConfig(){return{type:"tab-area",widgets:this.tabBar.titles.map((t=>t.owner)),currentIndex:this.tabBar.currentIndex}}holdAllSizes(){}fit(t,e){let r=0,n=0,i=e.get(this.tabBar),a=this.tabBar.currentTitle,o=a?e.get(a.owner):void 0,[s,l]=this.sizers;return i&&i.fit(),o&&o.fit(),i&&!i.isHidden?(r=Math.max(r,i.minWidth),n+=i.minHeight,s.minSize=i.minHeight,s.maxSize=i.maxHeight):(s.minSize=0,s.maxSize=0),o&&!o.isHidden?(r=Math.max(r,o.minWidth),n+=o.minHeight,l.minSize=o.minHeight,l.maxSize=1/0):(l.minSize=0,l.maxSize=1/0),{minWidth:r,minHeight:n,maxWidth:1/0,maxHeight:1/0}}update(t,e,r,n,i,a){this._top=e,this._left=t,this._width=r,this._height=n;let o=a.get(this.tabBar),s=this.tabBar.currentTitle,l=s?a.get(s.owner):void 0;if(Q.calc(this.sizers,n),o&&!o.isHidden){let n=this.sizers[0].size;o.update(t,e,r,n),e+=n}if(l&&!l.isHidden){let n=this.sizers[1].size;l.update(t,e,r,n)}}}t.TabLayoutNode=r;class n{constructor(t){this.parent=null,this.normalized=!1,this.children=[],this.sizers=[],this.handles=[],this.orientation=t}*iterAllWidgets(){for(let t of this.children)yield*t.iterAllWidgets()}*iterUserWidgets(){for(let t of this.children)yield*t.iterUserWidgets()}*iterSelectedWidgets(){for(let t of this.children)yield*t.iterSelectedWidgets()}*iterTabBars(){for(let t of this.children)yield*t.iterTabBars()}*iterHandles(){yield*this.handles;for(let t of this.children)yield*t.iterHandles()}findTabNode(t){for(let e=0,r=this.children.length;et.createConfig())),sizes:e}}syncHandles(){this.handles.forEach(((t,e)=>{t.setAttribute("data-orientation",this.orientation),e===this.handles.length-1?t.classList.add("lm-mod-hidden"):t.classList.remove("lm-mod-hidden")}))}holdSizes(){for(let t of this.sizers)t.sizeHint=t.size}holdAllSizes(){for(let t of this.children)t.holdAllSizes();this.holdSizes()}normalizeSizes(){let t=this.sizers.length;if(0===t)return;this.holdSizes();let e=this.sizers.reduce(((t,e)=>t+e.sizeHint),0);if(0===e)for(let e of this.sizers)e.size=e.sizeHint=1/t;else for(let t of this.sizers)t.size=t.sizeHint/=e;this.normalized=!0}createNormalizedSizes(){let t=this.sizers.length;if(0===t)return[];let e=this.sizers.map((t=>t.size)),r=e.reduce(((t,e)=>t+e),0);if(0===r)for(let r=e.length-1;r>-1;r--)e[r]=1/t;else for(let t=e.length-1;t>-1;t--)e[t]/=r;return e}fit(t,e){let r="horizontal"===this.orientation,n=Math.max(0,this.children.length-1)*t,i=r?n:0,a=r?0:n;for(let n=0,o=this.children.length;nthis._createTabBar(),createHandle:()=>this._createHandle()};this.layout=new zt({document:this._document,renderer:r,spacing:e.spacing,hiddenMode:e.hiddenMode}),this.overlay=e.overlay||new t.Overlay,this.node.appendChild(this.overlay.node)}dispose(){this._releaseMouse(),this.overlay.hide(0),this._drag&&this._drag.dispose(),super.dispose()}get hiddenMode(){return this.layout.hiddenMode}set hiddenMode(t){this.layout.hiddenMode=t}get layoutModified(){return this._layoutModified}get addRequested(){return this._addRequested}get renderer(){return this.layout.renderer}get spacing(){return this.layout.spacing}set spacing(t){this.layout.spacing=t}get mode(){return this._mode}set mode(t){if(this._mode===t)return;this._mode=t,this.dataset.mode=t;let e=this.layout;switch(t){case"multiple-document":for(let t of e.tabBars())t.show();break;case"single-document":e.restoreLayout(Dt.createSingleDocumentConfig(this));break;default:throw"unreachable"}M.postMessage(this,Dt.LayoutModified)}get tabsMovable(){return this._tabsMovable}set tabsMovable(t){this._tabsMovable=t;for(let e of this.tabBars())e.tabsMovable=t}get tabsConstrained(){return this._tabsConstrained}set tabsConstrained(t){this._tabsConstrained=t}get addButtonEnabled(){return this._addButtonEnabled}set addButtonEnabled(t){this._addButtonEnabled=t;for(let e of this.tabBars())e.addButtonEnabled=t}get isEmpty(){return this.layout.isEmpty}*widgets(){yield*this.layout.widgets()}*selectedWidgets(){yield*this.layout.selectedWidgets()}*tabBars(){yield*this.layout.tabBars()}*handles(){yield*this.layout.handles()}selectWidget(t){let e=(0,b.find)(this.tabBars(),(e=>-1!==e.titles.indexOf(t.title)));if(!e)throw new Error("Widget is not contained in the dock panel.");e.currentTitle=t.title}activateWidget(t){this.selectWidget(t),t.activate()}saveLayout(){return this.layout.saveLayout()}restoreLayout(t){this._mode="multiple-document",this.layout.restoreLayout(t),(a.IS_EDGE||a.IS_IE)&&M.flush(),M.postMessage(this,Dt.LayoutModified)}addWidget(t,e={}){"single-document"===this._mode?this.layout.addWidget(t):this.layout.addWidget(t,e),M.postMessage(this,Dt.LayoutModified)}processMessage(t){"layout-modified"===t.type?this._layoutModified.emit(void 0):super.processMessage(t)}handleEvent(t){switch(t.type){case"lm-dragenter":this._evtDragEnter(t);break;case"lm-dragleave":this._evtDragLeave(t);break;case"lm-dragover":this._evtDragOver(t);break;case"lm-drop":this._evtDrop(t);break;case"pointerdown":this._evtPointerDown(t);break;case"pointermove":this._evtPointerMove(t);break;case"pointerup":this._evtPointerUp(t);break;case"keydown":this._evtKeyDown(t);break;case"contextmenu":t.preventDefault(),t.stopPropagation()}}onBeforeAttach(t){this.node.addEventListener("lm-dragenter",this),this.node.addEventListener("lm-dragleave",this),this.node.addEventListener("lm-dragover",this),this.node.addEventListener("lm-drop",this),this.node.addEventListener("pointerdown",this)}onAfterDetach(t){this.node.removeEventListener("lm-dragenter",this),this.node.removeEventListener("lm-dragleave",this),this.node.removeEventListener("lm-dragover",this),this.node.removeEventListener("lm-drop",this),this.node.removeEventListener("pointerdown",this),this._releaseMouse()}onChildAdded(t){Dt.isGeneratedTabBarProperty.get(t.child)||t.child.addClass("lm-DockPanel-widget")}onChildRemoved(t){Dt.isGeneratedTabBarProperty.get(t.child)||(t.child.removeClass("lm-DockPanel-widget"),M.postMessage(this,Dt.LayoutModified))}_evtDragEnter(t){t.mimeData.hasData("application/vnd.lumino.widget-factory")&&(t.preventDefault(),t.stopPropagation())}_evtDragLeave(t){t.preventDefault(),(!this._tabsConstrained||t.source===this)&&(t.stopPropagation(),this.overlay.hide(1))}_evtDragOver(t){t.preventDefault(),this._tabsConstrained&&t.source!==this||"invalid"===this._showOverlay(t.clientX,t.clientY)?t.dropAction="none":(t.stopPropagation(),t.dropAction=t.proposedAction)}_evtDrop(t){if(t.preventDefault(),this.overlay.hide(0),"none"===t.proposedAction)return void(t.dropAction="none");let{clientX:e,clientY:r}=t,{zone:n,target:i}=Dt.findDropTarget(this,e,r,this._edges);if(this._tabsConstrained&&t.source!==this||"invalid"===n)return void(t.dropAction="none");let a=t.mimeData.getData("application/vnd.lumino.widget-factory");if("function"!=typeof a)return void(t.dropAction="none");let o=a();if(!(o instanceof nt))return void(t.dropAction="none");if(o.contains(this))return void(t.dropAction="none");let s=i?Dt.getDropRef(i.tabBar):null;switch(n){case"root-all":this.addWidget(o);break;case"root-top":this.addWidget(o,{mode:"split-top"});break;case"root-left":this.addWidget(o,{mode:"split-left"});break;case"root-right":this.addWidget(o,{mode:"split-right"});break;case"root-bottom":this.addWidget(o,{mode:"split-bottom"});break;case"widget-all":case"widget-tab":this.addWidget(o,{mode:"tab-after",ref:s});break;case"widget-top":this.addWidget(o,{mode:"split-top",ref:s});break;case"widget-left":this.addWidget(o,{mode:"split-left",ref:s});break;case"widget-right":this.addWidget(o,{mode:"split-right",ref:s});break;case"widget-bottom":this.addWidget(o,{mode:"split-bottom",ref:s});break;default:throw"unreachable"}t.dropAction=t.proposedAction,t.stopPropagation(),this.activateWidget(o)}_evtKeyDown(t){t.preventDefault(),t.stopPropagation(),27===t.keyCode&&(this._releaseMouse(),M.postMessage(this,Dt.LayoutModified))}_evtPointerDown(t){if(0!==t.button)return;let e=this.layout,r=t.target,n=(0,b.find)(e.handles(),(t=>t.contains(r)));if(!n)return;t.preventDefault(),t.stopPropagation(),this._document.addEventListener("keydown",this,!0),this._document.addEventListener("pointerup",this,!0),this._document.addEventListener("pointermove",this,!0),this._document.addEventListener("contextmenu",this,!0);let i=n.getBoundingClientRect(),a=t.clientX-i.left,o=t.clientY-i.top,s=window.getComputedStyle(n),l=B.overrideCursor(s.cursor,this._document);this._pressData={handle:n,deltaX:a,deltaY:o,override:l}}_evtPointerMove(t){if(!this._pressData)return;t.preventDefault(),t.stopPropagation();let e=this.node.getBoundingClientRect(),r=t.clientX-e.left-this._pressData.deltaX,n=t.clientY-e.top-this._pressData.deltaY;this.layout.moveHandle(this._pressData.handle,r,n)}_evtPointerUp(t){0===t.button&&(t.preventDefault(),t.stopPropagation(),this._releaseMouse(),M.postMessage(this,Dt.LayoutModified))}_releaseMouse(){this._pressData&&(this._pressData.override.dispose(),this._pressData=null,this._document.removeEventListener("keydown",this,!0),this._document.removeEventListener("pointerup",this,!0),this._document.removeEventListener("pointermove",this,!0),this._document.removeEventListener("contextmenu",this,!0))}_showOverlay(t,e){let{zone:r,target:n}=Dt.findDropTarget(this,t,e,this._edges);if("invalid"===r)return this.overlay.hide(100),r;let a,o,s,l,c=i.boxSizing(this.node),u=this.node.getBoundingClientRect();switch(r){case"root-all":a=c.paddingTop,o=c.paddingLeft,s=c.paddingRight,l=c.paddingBottom;break;case"root-top":a=c.paddingTop,o=c.paddingLeft,s=c.paddingRight,l=u.height*Dt.GOLDEN_RATIO;break;case"root-left":a=c.paddingTop,o=c.paddingLeft,s=u.width*Dt.GOLDEN_RATIO,l=c.paddingBottom;break;case"root-right":a=c.paddingTop,o=u.width*Dt.GOLDEN_RATIO,s=c.paddingRight,l=c.paddingBottom;break;case"root-bottom":a=u.height*Dt.GOLDEN_RATIO,o=c.paddingLeft,s=c.paddingRight,l=c.paddingBottom;break;case"widget-all":a=n.top,o=n.left,s=n.right,l=n.bottom;break;case"widget-top":a=n.top,o=n.left,s=n.right,l=n.bottom+n.height/2;break;case"widget-left":a=n.top,o=n.left,s=n.right+n.width/2,l=n.bottom;break;case"widget-right":a=n.top,o=n.left+n.width/2,s=n.right,l=n.bottom;break;case"widget-bottom":a=n.top+n.height/2,o=n.left,s=n.right,l=n.bottom;break;case"widget-tab":{let t=n.tabBar.node.getBoundingClientRect().height;a=n.top,o=n.left,s=n.right,l=n.bottom+n.height-t;break}default:throw"unreachable"}return this.overlay.show({top:a,left:o,right:s,bottom:l}),r}_createTabBar(){let t=this._renderer.createTabBar(this._document);return Dt.isGeneratedTabBarProperty.set(t,!0),"single-document"===this._mode&&t.hide(),t.tabsMovable=this._tabsMovable,t.allowDeselect=!1,t.addButtonEnabled=this._addButtonEnabled,t.removeBehavior="select-previous-tab",t.insertBehavior="select-tab-if-needed",t.tabMoved.connect(this._onTabMoved,this),t.currentChanged.connect(this._onCurrentChanged,this),t.tabCloseRequested.connect(this._onTabCloseRequested,this),t.tabDetachRequested.connect(this._onTabDetachRequested,this),t.tabActivateRequested.connect(this._onTabActivateRequested,this),t.addRequested.connect(this._onTabAddRequested,this),t}_createHandle(){return this._renderer.createHandle()}_onTabMoved(){M.postMessage(this,Dt.LayoutModified)}_onCurrentChanged(t,e){let{previousTitle:r,currentTitle:n}=e;r&&r.owner.hide(),n&&n.owner.show(),(a.IS_EDGE||a.IS_IE)&&M.flush(),M.postMessage(this,Dt.LayoutModified)}_onTabAddRequested(t){this._addRequested.emit(t)}_onTabActivateRequested(t,e){e.title.owner.activate()}_onTabCloseRequested(t,e){e.title.owner.close()}_onTabDetachRequested(t,e){if(this._drag)return;t.releaseMouse();let{title:r,tab:n,clientX:i,clientY:a,offset:o}=e,s=new w.MimeData;s.setData("application/vnd.lumino.widget-factory",(()=>r.owner));let l=n.cloneNode(!0);o&&(l.style.top=`-${o.y}px`,l.style.left=`-${o.x}px`),this._drag=new B({document:this._document,mimeData:s,dragImage:l,proposedAction:"move",supportedActions:"move",source:this}),n.classList.add("lm-mod-hidden"),this._drag.start(i,a).then((()=>{this._drag=null,n.classList.remove("lm-mod-hidden")}))}};!function(t){t.Overlay=class{constructor(){this._timer=-1,this._hidden=!0,this.node=document.createElement("div"),this.node.classList.add("lm-DockPanel-overlay"),this.node.classList.add("lm-mod-hidden"),this.node.style.position="absolute",this.node.style.contain="strict"}show(t){let e=this.node.style;e.top=`${t.top}px`,e.left=`${t.left}px`,e.right=`${t.right}px`,e.bottom=`${t.bottom}px`,clearTimeout(this._timer),this._timer=-1,this._hidden&&(this._hidden=!1,this.node.classList.remove("lm-mod-hidden"))}hide(t){if(!this._hidden){if(t<=0)return clearTimeout(this._timer),this._timer=-1,this._hidden=!0,void this.node.classList.add("lm-mod-hidden");-1===this._timer&&(this._timer=window.setTimeout((()=>{this._timer=-1,this._hidden=!0,this.node.classList.add("lm-mod-hidden")}),t))}}};class e{createTabBar(t){let e=new Lt({document:t});return e.addClass("lm-DockPanel-tabBar"),e}createHandle(){let t=document.createElement("div");return t.className="lm-DockPanel-handle",t}}t.Renderer=e,t.defaultRenderer=new e}(Ot||(Ot={})),function(t){t.GOLDEN_RATIO=.618,t.DEFAULT_EDGES={top:12,right:40,bottom:40,left:40},t.LayoutModified=new E("layout-modified"),t.isGeneratedTabBarProperty=new I({name:"isGeneratedTabBar",create:()=>!1}),t.createSingleDocumentConfig=function(t){if(t.isEmpty)return{main:null};let e=Array.from(t.widgets()),r=t.selectedWidgets().next().value,n=r?e.indexOf(r):-1;return{main:{type:"tab-area",widgets:e,currentIndex:n}}},t.findDropTarget=function(t,e,r,n){if(!i.hitTest(t.node,e,r))return{zone:"invalid",target:null};let a=t.layout;if(a.isEmpty)return{zone:"root-all",target:null};if("multiple-document"===t.mode){let i=t.node.getBoundingClientRect(),a=e-i.left+1,o=r-i.top+1,s=i.right-e,l=i.bottom-r;switch(Math.min(o,s,l,a)){case o:if(of&&c>f&&l>p&&u>p)return{zone:"widget-all",target:o};switch(s/=f,l/=p,c/=f,u/=p,Math.min(s,l,c,u)){case s:h="widget-left";break;case l:h="widget-top";break;case c:h="widget-right";break;case u:h="widget-bottom";break;default:throw"unreachable"}return{zone:h,target:o}},t.getDropRef=function(t){return 0===t.titles.length?null:t.currentTitle?t.currentTitle.owner:t.titles[t.titles.length-1].owner}}(Dt||(Dt={}));var Rt,Ft=class t extends it{constructor(t={}){super(t),this._dirty=!1,this._rowSpacing=4,this._columnSpacing=4,this._items=[],this._rowStarts=[],this._columnStarts=[],this._rowSizers=[new tt],this._columnSizers=[new tt],this._box=null,void 0!==t.rowCount&&Rt.reallocSizers(this._rowSizers,t.rowCount),void 0!==t.columnCount&&Rt.reallocSizers(this._columnSizers,t.columnCount),void 0!==t.rowSpacing&&(this._rowSpacing=Rt.clampValue(t.rowSpacing)),void 0!==t.columnSpacing&&(this._columnSpacing=Rt.clampValue(t.columnSpacing))}dispose(){for(let t of this._items){let e=t.widget;t.dispose(),e.dispose()}this._box=null,this._items.length=0,this._rowStarts.length=0,this._rowSizers.length=0,this._columnStarts.length=0,this._columnSizers.length=0,super.dispose()}get rowCount(){return this._rowSizers.length}set rowCount(t){t!==this.rowCount&&(Rt.reallocSizers(this._rowSizers,t),this.parent&&this.parent.fit())}get columnCount(){return this._columnSizers.length}set columnCount(t){t!==this.columnCount&&(Rt.reallocSizers(this._columnSizers,t),this.parent&&this.parent.fit())}get rowSpacing(){return this._rowSpacing}set rowSpacing(t){t=Rt.clampValue(t),this._rowSpacing!==t&&(this._rowSpacing=t,this.parent&&this.parent.fit())}get columnSpacing(){return this._columnSpacing}set columnSpacing(t){t=Rt.clampValue(t),this._columnSpacing!==t&&(this._columnSpacing=t,this.parent&&this.parent.fit())}rowStretch(t){let e=this._rowSizers[t];return e?e.stretch:-1}setRowStretch(t,e){let r=this._rowSizers[t];r&&(e=Rt.clampValue(e),r.stretch!==e&&(r.stretch=e,this.parent&&this.parent.update()))}columnStretch(t){let e=this._columnSizers[t];return e?e.stretch:-1}setColumnStretch(t,e){let r=this._columnSizers[t];r&&(e=Rt.clampValue(e),r.stretch!==e&&(r.stretch=e,this.parent&&this.parent.update()))}*[Symbol.iterator](){for(let t of this._items)yield t.widget}addWidget(t){-1===b.ArrayExt.findFirstIndex(this._items,(e=>e.widget===t))&&(this._items.push(new ot(t)),this.parent&&this.attachWidget(t))}removeWidget(t){let e=b.ArrayExt.findFirstIndex(this._items,(e=>e.widget===t));if(-1===e)return;let r=b.ArrayExt.removeAt(this._items,e);this.parent&&this.detachWidget(t),r.dispose()}init(){super.init();for(let t of this)this.attachWidget(t)}attachWidget(t){this.parent.isAttached&&M.sendMessage(t,nt.Msg.BeforeAttach),this.parent.node.appendChild(t.node),this.parent.isAttached&&M.sendMessage(t,nt.Msg.AfterAttach),this.parent.fit()}detachWidget(t){this.parent.isAttached&&M.sendMessage(t,nt.Msg.BeforeDetach),this.parent.node.removeChild(t.node),this.parent.isAttached&&M.sendMessage(t,nt.Msg.AfterDetach),this.parent.fit()}onBeforeShow(t){super.onBeforeShow(t),this.parent.update()}onBeforeAttach(t){super.onBeforeAttach(t),this.parent.fit()}onChildShown(t){this.parent.fit()}onChildHidden(t){this.parent.fit()}onResize(t){this.parent.isVisible&&this._update(t.width,t.height)}onUpdateRequest(t){this.parent.isVisible&&this._update(-1,-1)}onFitRequest(t){this.parent.isAttached&&this._fit()}_fit(){for(let t=0,e=this.rowCount;t!t.isHidden));for(let t=0,r=e.length;t({row:0,column:0,rowSpan:1,columnSpan:1}),changed:function(t){t.parent&&t.parent.layout instanceof Ft&&t.parent.fit()}}),t.normalizeConfig=function(t){return{row:Math.max(0,Math.floor(t.row||0)),column:Math.max(0,Math.floor(t.column||0)),rowSpan:Math.max(1,Math.floor(t.rowSpan||0)),columnSpan:Math.max(1,Math.floor(t.columnSpan||0))}},t.clampValue=function(t){return Math.max(0,Math.floor(t))},t.rowSpanCmp=function(e,r){let n=t.cellConfigProperty.get(e.widget),i=t.cellConfigProperty.get(r.widget);return n.rowSpan-i.rowSpan},t.columnSpanCmp=function(e,r){let n=t.cellConfigProperty.get(e.widget),i=t.cellConfigProperty.get(r.widget);return n.columnSpan-i.columnSpan},t.reallocSizers=function(t,e){for(e=Math.max(1,Math.floor(e));t.lengthe&&(t.length=e)},t.distributeMin=function(t,e,r,n){if(r=n)return;let a=(n-i)/(r-e+1);for(let n=e;n<=r;++n)t[n].minSize+=a}}(Rt||(Rt={}));var Bt,jt,Nt=class t extends nt{constructor(e={}){super({node:Bt.createNode()}),this._activeIndex=-1,this._tabFocusIndex=0,this._menus=[],this._childMenu=null,this._overflowMenu=null,this._menuItemSizes=[],this._overflowIndex=-1,this.addClass("lm-MenuBar"),this.setFlag(nt.Flag.DisallowLayout),this.renderer=e.renderer||t.defaultRenderer,this._forceItemsPosition=e.forceItemsPosition||{forceX:!0,forceY:!0},this._overflowMenuOptions=e.overflowMenuOptions||{isVisible:!0}}dispose(){this._closeChildMenu(),this._menus.length=0,super.dispose()}get childMenu(){return this._childMenu}get overflowIndex(){return this._overflowIndex}get overflowMenu(){return this._overflowMenu}get contentNode(){return this.node.getElementsByClassName("lm-MenuBar-content")[0]}get activeMenu(){return this._menus[this._activeIndex]||null}set activeMenu(t){this.activeIndex=t?this._menus.indexOf(t):-1}get activeIndex(){return this._activeIndex}set activeIndex(t){(t<0||t>=this._menus.length)&&(t=-1),t>-1&&0===this._menus[t].items.length&&(t=-1),this._activeIndex!==t&&(this._activeIndex=t,this.update())}get menus(){return this._menus}openActiveMenu(){-1!==this._activeIndex&&(this._openChildMenu(),this._childMenu&&(this._childMenu.activeIndex=-1,this._childMenu.activateNextItem()))}addMenu(t,e=!0){this.insertMenu(this._menus.length,t,e)}insertMenu(t,e,r=!0){this._closeChildMenu();let n=this._menus.indexOf(e),i=Math.max(0,Math.min(t,this._menus.length));if(-1===n)return b.ArrayExt.insert(this._menus,i,e),e.addClass("lm-MenuBar-menu"),e.aboutToClose.connect(this._onMenuAboutToClose,this),e.menuRequested.connect(this._onMenuMenuRequested,this),e.title.changed.connect(this._onTitleChanged,this),void(r&&this.update());i===this._menus.length&&i--,n!==i&&(b.ArrayExt.move(this._menus,n,i),r&&this.update())}removeMenu(t,e=!0){this.removeMenuAt(this._menus.indexOf(t),e)}removeMenuAt(t,e=!0){this._closeChildMenu();let r=b.ArrayExt.removeAt(this._menus,t);r&&(r.aboutToClose.disconnect(this._onMenuAboutToClose,this),r.menuRequested.disconnect(this._onMenuMenuRequested,this),r.title.changed.disconnect(this._onTitleChanged,this),r.removeClass("lm-MenuBar-menu"),e&&this.update())}clearMenus(){if(0!==this._menus.length){this._closeChildMenu();for(let t of this._menus)t.aboutToClose.disconnect(this._onMenuAboutToClose,this),t.menuRequested.disconnect(this._onMenuMenuRequested,this),t.title.changed.disconnect(this._onTitleChanged,this),t.removeClass("lm-MenuBar-menu");this._menus.length=0,this.update()}}handleEvent(t){switch(t.type){case"keydown":this._evtKeyDown(t);break;case"mousedown":this._evtMouseDown(t);break;case"mousemove":this._evtMouseMove(t);break;case"focusout":this._evtFocusOut(t);break;case"contextmenu":t.preventDefault(),t.stopPropagation()}}onBeforeAttach(t){this.node.addEventListener("keydown",this),this.node.addEventListener("mousedown",this),this.node.addEventListener("mousemove",this),this.node.addEventListener("focusout",this),this.node.addEventListener("contextmenu",this)}onAfterDetach(t){this.node.removeEventListener("keydown",this),this.node.removeEventListener("mousedown",this),this.node.removeEventListener("mousemove",this),this.node.removeEventListener("focusout",this),this.node.removeEventListener("contextmenu",this),this._closeChildMenu()}onActivateRequest(t){this.isAttached&&this._focusItemAt(0)}onResize(t){this.update(),super.onResize(t)}onUpdateRequest(t){var 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0),o)){var n=t&&("load"===t.type?"missing":t.type),i=t&&t.target&&t.target.src;l.message="Loading chunk "+r+" failed.\n("+n+": "+i+")",l.name="ChunkLoadError",l.type=n,l.request=i,o[1](l)}}),"chunk-"+r,r)}};var r=(r,t)=>{var o,n,[i,l,u]=t,p=0;if(i.some((r=>0!==e[r]))){for(o in l)a.o(l,o)&&(a.m[o]=l[o]);u&&u(a)}for(r&&r(t);p"data", "after"->"screen". + styles: dictionary + A dictionary in which each value is a list of length N, containing + the style(s) for the paths. + mplobj : matplotlib object + the matplotlib plot element which generated this collection + """ + if offset_order == "before": + raise NotImplementedError("offset before transform") + + for tup in self._iter_path_collection(paths, path_transforms, offsets, styles): + (path, path_transform, offset, ec, lw, fc) = tup + vertices, pathcodes = path + path_transform = transforms.Affine2D(path_transform) + vertices = path_transform.transform(vertices) + # This is a hack: + if path_coordinates == "figure": + path_coordinates = "points" + style = { + "edgecolor": utils.export_color(ec), + "facecolor": utils.export_color(fc), + "edgewidth": lw, + "dasharray": "10,0", + "alpha": styles["alpha"], + "zorder": styles["zorder"], + } + self.draw_path( + data=vertices, + coordinates=path_coordinates, + pathcodes=pathcodes, + style=style, + offset=offset, + offset_coordinates=offset_coordinates, + mplobj=mplobj, + ) + + def draw_markers(self, data, coordinates, style, label, mplobj=None): + """ + Draw a set of markers. By default, this is done by repeatedly + calling draw_path(), but renderers should generally overload + this method to provide a more efficient implementation. + + In matplotlib, markers are created using the plt.plot() command. + + Parameters + ---------- + data : array_like + A shape (N, 2) array of datapoints. + coordinates : string + A string code, which should be either 'data' for data coordinates, + or 'figure' for figure (pixel) coordinates. + style : dictionary + a dictionary specifying the appearance of the markers. + mplobj : matplotlib object + the matplotlib plot element which generated this marker collection + """ + vertices, pathcodes = style["markerpath"] + pathstyle = dict( + (key, style[key]) + for key in ["alpha", "edgecolor", "facecolor", "zorder", "edgewidth"] + ) + pathstyle["dasharray"] = "10,0" + for vertex in data: + self.draw_path( + data=vertices, + coordinates="points", + pathcodes=pathcodes, + style=pathstyle, + offset=vertex, + offset_coordinates=coordinates, + mplobj=mplobj, + ) + + def draw_text( + self, text, position, coordinates, style, text_type=None, mplobj=None + ): + """ + Draw text on the image. + + Parameters + ---------- + text : string + The text to draw + position : tuple + The (x, y) position of the text + coordinates : string + A string code, which should be either 'data' for data coordinates, + or 'figure' for figure (pixel) coordinates. + style : dictionary + a dictionary specifying the appearance of the text. + text_type : string or None + if specified, a type of text such as "xlabel", "ylabel", "title" + mplobj : matplotlib object + the matplotlib plot element which generated this text + """ + raise NotImplementedError() + + def draw_path( + self, + data, + coordinates, + pathcodes, + style, + offset=None, + offset_coordinates="data", + mplobj=None, + ): + """ + Draw a path. + + In matplotlib, paths are created by filled regions, histograms, + contour plots, patches, etc. + + Parameters + ---------- + data : array_like + A shape (N, 2) array of datapoints. + coordinates : string + A string code, which should be either 'data' for data coordinates, + 'figure' for figure (pixel) coordinates, or "points" for raw + point coordinates (useful in conjunction with offsets, below). + pathcodes : list + A list of single-character SVG pathcodes associated with the data. + Path codes are one of ['M', 'm', 'L', 'l', 'Q', 'q', 'T', 't', + 'S', 's', 'C', 'c', 'Z', 'z'] + See the SVG specification for details. Note that some path codes + consume more than one datapoint (while 'Z' consumes none), so + in general, the length of the pathcodes list will not be the same + as that of the data array. + style : dictionary + a dictionary specifying the appearance of the line. + offset : list (optional) + the (x, y) offset of the path. If not given, no offset will + be used. + offset_coordinates : string (optional) + A string code, which should be either 'data' for data coordinates, + or 'figure' for figure (pixel) coordinates. + mplobj : matplotlib object + the matplotlib plot element which generated this path + """ + raise NotImplementedError() + + def draw_image(self, imdata, extent, coordinates, style, mplobj=None): + """ + Draw an image. + + Parameters + ---------- + imdata : string + base64 encoded png representation of the image + extent : list + the axes extent of the image: [xmin, xmax, ymin, ymax] + coordinates: string + A string code, which should be either 'data' for data coordinates, + or 'figure' for figure (pixel) coordinates. + style : dictionary + a dictionary specifying the appearance of the image + mplobj : matplotlib object + the matplotlib plot object which generated this image + """ + raise NotImplementedError() diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/renderers/fake_renderer.py b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/renderers/fake_renderer.py new file mode 100644 index 0000000000000000000000000000000000000000..de2ae40efa7b118bed975ffa7780b4dc46a2759c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/renderers/fake_renderer.py @@ -0,0 +1,88 @@ +from .base import Renderer + + +class FakeRenderer(Renderer): + """ + Fake Renderer + + This is a fake renderer which simply outputs a text tree representing the + elements found in the plot(s). This is used in the unit tests for the + package. + + Below are the methods your renderer must implement. You are free to do + anything you wish within the renderer (i.e. build an XML or JSON + representation, call an external API, etc.) Here the renderer just + builds a simple string representation for testing purposes. + """ + + def __init__(self): + self.output = "" + + def open_figure(self, fig, props): + self.output += "opening figure\n" + + def close_figure(self, fig): + self.output += "closing figure\n" + + def open_axes(self, ax, props): + self.output += " opening axes\n" + + def close_axes(self, ax): + self.output += " closing axes\n" + + def open_legend(self, legend, props): + self.output += " opening legend\n" + + def close_legend(self, legend): + self.output += " closing legend\n" + + def draw_text( + self, text, position, coordinates, style, text_type=None, mplobj=None + ): + self.output += " draw text '{0}' {1}\n".format(text, text_type) + + def draw_path( + self, + data, + coordinates, + pathcodes, + style, + offset=None, + offset_coordinates="data", + mplobj=None, + ): + self.output += " draw path with {0} vertices\n".format(data.shape[0]) + + def draw_image(self, imdata, extent, coordinates, style, mplobj=None): + self.output += " draw image of size {0}\n".format(len(imdata)) + + +class FullFakeRenderer(FakeRenderer): + """ + Renderer with the full complement of methods. + + When the following are left undefined, they will be implemented via + other methods in the class. They can be defined explicitly for + more efficient or specialized use within the renderer implementation. + """ + + def draw_line(self, data, coordinates, style, label, mplobj=None): + self.output += " draw line with {0} points\n".format(data.shape[0]) + + def draw_markers(self, data, coordinates, style, label, mplobj=None): + self.output += " draw {0} markers\n".format(data.shape[0]) + + def draw_path_collection( + self, + paths, + path_coordinates, + path_transforms, + offsets, + offset_coordinates, + offset_order, + styles, + mplobj=None, + ): + self.output += " draw path collection with {0} offsets\n".format( + offsets.shape[0] + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/renderers/vega_renderer.py b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/renderers/vega_renderer.py new file mode 100644 index 0000000000000000000000000000000000000000..eab02e1f3298a3ea626e11372bdbd5829ceba374 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/renderers/vega_renderer.py @@ -0,0 +1,155 @@ +import warnings +import json +import random +from .base import Renderer +from ..exporter import Exporter + + +class VegaRenderer(Renderer): + def open_figure(self, fig, props): + self.props = props + self.figwidth = int(props["figwidth"] * props["dpi"]) + self.figheight = int(props["figheight"] * props["dpi"]) + self.data = [] + self.scales = [] + self.axes = [] + self.marks = [] + + def open_axes(self, ax, props): + if len(self.axes) > 0: + warnings.warn("multiple axes not yet supported") + self.axes = [ + dict(type="x", scale="x", ticks=10), + dict(type="y", scale="y", ticks=10), + ] + self.scales = [ + dict( + name="x", + domain=props["xlim"], + type="linear", + range="width", + ), + dict( + name="y", + domain=props["ylim"], + type="linear", + range="height", + ), + ] + + def draw_line(self, data, coordinates, style, label, mplobj=None): + if coordinates != "data": + warnings.warn("Only data coordinates supported. Skipping this") + dataname = "table{0:03d}".format(len(self.data) + 1) + + # TODO: respect the other style settings + self.data.append( + {"name": dataname, "values": [dict(x=d[0], y=d[1]) for d in data]} + ) + self.marks.append( + { + "type": "line", + "from": {"data": dataname}, + "properties": { + "enter": { + "interpolate": {"value": "monotone"}, + "x": {"scale": "x", "field": "data.x"}, + "y": {"scale": "y", "field": "data.y"}, + "stroke": {"value": style["color"]}, + "strokeOpacity": {"value": style["alpha"]}, + "strokeWidth": {"value": style["linewidth"]}, + } + }, + } + ) + + def draw_markers(self, data, coordinates, style, label, mplobj=None): + if coordinates != "data": + warnings.warn("Only data coordinates supported. Skipping this") + dataname = "table{0:03d}".format(len(self.data) + 1) + + # TODO: respect the other style settings + self.data.append( + {"name": dataname, "values": [dict(x=d[0], y=d[1]) for d in data]} + ) + self.marks.append( + { + "type": "symbol", + "from": {"data": dataname}, + "properties": { + "enter": { + "interpolate": {"value": "monotone"}, + "x": {"scale": "x", "field": "data.x"}, + "y": {"scale": "y", "field": "data.y"}, + "fill": {"value": style["facecolor"]}, + "fillOpacity": {"value": style["alpha"]}, + "stroke": {"value": style["edgecolor"]}, + "strokeOpacity": {"value": style["alpha"]}, + "strokeWidth": {"value": style["edgewidth"]}, + } + }, + } + ) + + def draw_text( + self, text, position, coordinates, style, text_type=None, mplobj=None + ): + if text_type == "xlabel": + self.axes[0]["title"] = text + elif text_type == "ylabel": + self.axes[1]["title"] = text + + +class VegaHTML(object): + def __init__(self, renderer): + self.specification = dict( + width=renderer.figwidth, + height=renderer.figheight, + data=renderer.data, + scales=renderer.scales, + axes=renderer.axes, + marks=renderer.marks, + ) + + def html(self): + """Build the HTML representation for IPython.""" + id = random.randint(0, 2**16) + html = '
' % id + html += "\n" + return html + + def _repr_html_(self): + return self.html() + + +def fig_to_vega(fig, notebook=False): + """Convert a matplotlib figure to vega dictionary + + if notebook=True, then return an object which will display in a notebook + otherwise, return an HTML string. + """ + renderer = VegaRenderer() + Exporter(renderer).run(fig) + vega_html = VegaHTML(renderer) + if notebook: + return vega_html + else: + return vega_html.html() + + +VEGA_TEMPLATE = """ +( function() { + var _do_plot = function() { + if ( (typeof vg == 'undefined') && (typeof IPython != 'undefined')) { + $([IPython.events]).on("vega_loaded.vincent", _do_plot); + return; + } + vg.parse.spec(%s, function(chart) { + chart({el: "#vis%d"}).update(); + }); + }; + _do_plot(); +})(); +""" diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/renderers/vincent_renderer.py b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/renderers/vincent_renderer.py new file mode 100644 index 0000000000000000000000000000000000000000..36074f6a73caa522aa6a5b9fdd944713875fdf9b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/renderers/vincent_renderer.py @@ -0,0 +1,54 @@ +import warnings +from .base import Renderer +from ..exporter import Exporter + + +class VincentRenderer(Renderer): + def open_figure(self, fig, props): + self.chart = None + self.figwidth = int(props["figwidth"] * props["dpi"]) + self.figheight = int(props["figheight"] * props["dpi"]) + + def draw_line(self, data, coordinates, style, label, mplobj=None): + import vincent # only import if VincentRenderer is used + + if coordinates != "data": + warnings.warn("Only data coordinates supported. Skipping this") + linedata = {"x": data[:, 0], "y": data[:, 1]} + line = vincent.Line( + linedata, iter_idx="x", width=self.figwidth, height=self.figheight + ) + + # TODO: respect the other style settings + line.scales["color"].range = [style["color"]] + + if self.chart is None: + self.chart = line + else: + warnings.warn("Multiple plot elements not yet supported") + + def draw_markers(self, data, coordinates, style, label, mplobj=None): + import vincent # only import if VincentRenderer is used + + if coordinates != "data": + warnings.warn("Only data coordinates supported. Skipping this") + markerdata = {"x": data[:, 0], "y": data[:, 1]} + markers = vincent.Scatter( + markerdata, iter_idx="x", width=self.figwidth, height=self.figheight + ) + + # TODO: respect the other style settings + markers.scales["color"].range = [style["facecolor"]] + + if self.chart is None: + self.chart = markers + else: + warnings.warn("Multiple plot elements not yet supported") + + +def fig_to_vincent(fig): + """Convert a matplotlib figure to a vincent object""" + renderer = VincentRenderer() + exporter = Exporter(renderer) + exporter.run(fig) + return renderer.chart diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/tests/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/tests/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..290cc21f99dcac0262fbe6b9ad3a4f96fcfea3f8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/tests/__init__.py @@ -0,0 +1,3 @@ +import matplotlib + +matplotlib.use("Agg") diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/tests/__pycache__/__init__.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/tests/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..966cc2d366dbe3277dc6bb8b37f8e3be174291aa Binary files /dev/null and b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/tests/__pycache__/__init__.cpython-312.pyc differ diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/tests/__pycache__/test_basic.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/tests/__pycache__/test_basic.cpython-312.pyc new file mode 100644 index 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0000000000000000000000000000000000000000..3739e1303eddcc2082adffd0fa6c062528413b19 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/tests/test_basic.py @@ -0,0 +1,257 @@ +import matplotlib +import numpy as np +import pytest +from packaging.version import Version + +from ..exporter import Exporter +from ..renderers import FakeRenderer, FullFakeRenderer +import matplotlib.pyplot as plt + + +def fake_renderer_output(fig, Renderer): + renderer = Renderer() + exporter = Exporter(renderer) + exporter.run(fig) + return renderer.output + + +def _assert_output_equal(text1, text2): + for line1, line2 in zip(text1.strip().split(), text2.strip().split()): + assert line1 == line2 + + +def test_lines(): + fig, ax = plt.subplots() + ax.plot(range(20), "-k") + + _assert_output_equal( + fake_renderer_output(fig, FakeRenderer), + """ + opening figure + opening axes + draw path with 20 vertices + closing axes + closing figure + """, + ) + + _assert_output_equal( + fake_renderer_output(fig, FullFakeRenderer), + """ + opening figure + opening axes + draw line with 20 points + closing axes + closing figure + """, + ) + + +def test_markers(): + fig, ax = plt.subplots() + ax.plot(range(2), "ok") + + _assert_output_equal( + fake_renderer_output(fig, FakeRenderer), + """ + opening figure + opening axes + draw path with 25 vertices + draw path with 25 vertices + closing axes + closing figure + """, + ) + + _assert_output_equal( + fake_renderer_output(fig, FullFakeRenderer), + """ + opening figure + opening axes + draw 2 markers + closing axes + closing figure + """, + ) + + +def test_path_collection(): + fig, ax = plt.subplots() + ax.scatter(range(3), range(3)) + + _assert_output_equal( + fake_renderer_output(fig, FakeRenderer), + """ + opening figure + opening axes + draw path with 25 vertices + draw path with 25 vertices + draw path with 25 vertices + closing axes + closing figure + """, + ) + + _assert_output_equal( + fake_renderer_output(fig, FullFakeRenderer), + """ + opening figure + opening axes + draw path collection with 3 offsets + closing axes + closing figure + """, + ) + + +def test_text(): + fig, ax = plt.subplots() + ax.set_xlabel("my x label") + ax.set_ylabel("my y label") + ax.set_title("my title") + ax.text(0.5, 0.5, "my text") + + _assert_output_equal( + fake_renderer_output(fig, FakeRenderer), + """ + opening figure + opening axes + draw text 'my text' None + draw text 'my x label' xlabel + draw text 'my y label' ylabel + draw text 'my title' title + closing axes + closing figure + """, + ) + + +def test_path(): + fig, ax = plt.subplots() + ax.add_patch(plt.Circle((0, 0), 1)) + ax.add_patch(plt.Rectangle((0, 0), 1, 2)) + + _assert_output_equal( + fake_renderer_output(fig, FakeRenderer), + """ + opening figure + opening axes + draw path with 25 vertices + draw path with 4 vertices + closing axes + closing figure + """, + ) + + +def test_Figure(): + """if the fig is not associated with a canvas, FakeRenderer shall + not fail.""" + fig = plt.Figure() + ax = fig.add_subplot(111) + ax.add_patch(plt.Circle((0, 0), 1)) + ax.add_patch(plt.Rectangle((0, 0), 1, 2)) + + _assert_output_equal( + fake_renderer_output(fig, FakeRenderer), + """ + opening figure + opening axes + draw path with 25 vertices + draw path with 4 vertices + closing axes + closing figure + """, + ) + + +def test_multiaxes(): + fig, ax = plt.subplots(2) + ax[0].plot(range(4)) + ax[1].plot(range(10)) + + _assert_output_equal( + fake_renderer_output(fig, FakeRenderer), + """ + opening figure + opening axes + draw path with 4 vertices + closing axes + opening axes + draw path with 10 vertices + closing axes + closing figure + """, + ) + + +def test_image(): + # Test fails for matplotlib 1.5+ because the size of the image + # generated by matplotlib has changed. + if Version(matplotlib.__version__) == Version("3.4.1"): + image_size = 432 + else: + pytest.skip("Test fails for older matplotlib") + np.random.seed(0) # image size depends on the seed + fig, ax = plt.subplots(figsize=(2, 2)) + ax.imshow(np.random.random((10, 10)), cmap=plt.cm.jet, interpolation="nearest") + _assert_output_equal( + fake_renderer_output(fig, FakeRenderer), + f""" + opening figure + opening axes + draw image of size {image_size} + closing axes + closing figure + """, + ) + + +def test_legend(): + fig, ax = plt.subplots() + ax.plot([1, 2, 3], label="label") + ax.legend().set_visible(False) + _assert_output_equal( + fake_renderer_output(fig, FakeRenderer), + """ + opening figure + opening axes + draw path with 3 vertices + opening legend + closing legend + closing axes + closing figure + """, + ) + + +def test_legend_dots(): + fig, ax = plt.subplots() + ax.plot([1, 2, 3], label="label") + ax.plot([2, 2, 2], "o", label="dots") + ax.legend().set_visible(True) + # legend draws 1 line and 1 marker + # path around legend now has 13 vertices?? + _assert_output_equal( + fake_renderer_output(fig, FullFakeRenderer), + """ + opening figure + opening axes + draw line with 3 points + draw 3 markers + opening legend + draw line with 2 points + draw text 'label' None + draw 1 markers + draw text 'dots' None + draw path with 13 vertices + closing legend + closing axes + closing figure + """, + ) + + +def test_blended(): + fig, ax = plt.subplots() + ax.axvline(0) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/tests/test_utils.py b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/tests/test_utils.py new file mode 100644 index 0000000000000000000000000000000000000000..9c302d749184c4e2230b70ec8ed8ffe58b329dfd --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/tests/test_utils.py @@ -0,0 +1,41 @@ +import matplotlib.pyplot as plt +from numpy.testing import assert_allclose, assert_equal + +from .. import utils + + +def test_path_data(): + circle = plt.Circle((0, 0), 1) + vertices, codes = utils.SVG_path(circle.get_path()) + + assert_allclose(vertices.shape, (25, 2)) + assert_equal(codes, ["M", "C", "C", "C", "C", "C", "C", "C", "C", "Z"]) + + +def test_linestyle(): + linestyles = { + "solid": "none", + "-": "none", + "dashed": "5.550000000000001,2.4000000000000004", + "--": "5.550000000000001,2.4000000000000004", + "dotted": "1.5,2.4749999999999996", + ":": "1.5,2.4749999999999996", + "dashdot": "9.600000000000001,2.4000000000000004,1.5,2.4000000000000004", + "-.": "9.600000000000001,2.4000000000000004,1.5,2.4000000000000004", + "": None, + "None": None, + } + + for ls, result in linestyles.items(): + (line,) = plt.plot([1, 2, 3], linestyle=ls) + assert_equal(utils.get_dasharray(line), result) + + +def test_axis_w_fixed_formatter(): + positions, labels = [0, 1, 10], ["A", "B", "C"] + + plt.xticks(positions, labels) + props = utils.get_axis_properties(plt.gca().xaxis) + + assert_equal(props["tickvalues"], positions) + assert_equal(props["tickformat"], labels) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/tools.py b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/tools.py new file mode 100644 index 0000000000000000000000000000000000000000..f66fdfb138cad433dcb0397941408eabe1a3ffe3 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/tools.py @@ -0,0 +1,55 @@ +""" +Tools for matplotlib plot exporting +""" + + +def ipynb_vega_init(): + """Initialize the IPython notebook display elements + + This function borrows heavily from the excellent vincent package: + http://github.com/wrobstory/vincent + """ + try: + from IPython.core.display import display, HTML + except ImportError: + print("IPython Notebook could not be loaded.") + + require_js = """ + if (window['d3'] === undefined) {{ + require.config({{ paths: {{d3: "http://d3js.org/d3.v3.min"}} }}); + require(["d3"], function(d3) {{ + window.d3 = d3; + {0} + }}); + }}; + if (window['topojson'] === undefined) {{ + require.config( + {{ paths: {{topojson: "http://d3js.org/topojson.v1.min"}} }} + ); + require(["topojson"], function(topojson) {{ + window.topojson = topojson; + }}); + }}; + """ + d3_geo_projection_js_url = "http://d3js.org/d3.geo.projection.v0.min.js" + d3_layout_cloud_js_url = "http://wrobstory.github.io/d3-cloud/d3.layout.cloud.js" + topojson_js_url = "http://d3js.org/topojson.v1.min.js" + vega_js_url = "http://trifacta.github.com/vega/vega.js" + + dep_libs = """$.getScript("%s", function() { + $.getScript("%s", function() { + $.getScript("%s", function() { + $.getScript("%s", function() { + $([IPython.events]).trigger("vega_loaded.vincent"); + }) + }) + }) + });""" % ( + d3_geo_projection_js_url, + d3_layout_cloud_js_url, + topojson_js_url, + vega_js_url, + ) + load_js = require_js.format(dep_libs) + html = "" + display(HTML(html)) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/utils.py b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/utils.py new file mode 100644 index 0000000000000000000000000000000000000000..646e11e2f8653e29863fed30ef411902a5f6a366 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mplexporter/utils.py @@ -0,0 +1,382 @@ +""" +Utility Routines for Working with Matplotlib Objects +==================================================== +""" + +import itertools +import io +import base64 + +import numpy as np + +import warnings + +import matplotlib +from matplotlib.colors import colorConverter +from matplotlib.path import Path +from matplotlib.markers import MarkerStyle +from matplotlib.transforms import Affine2D +from matplotlib import ticker + + +def export_color(color): + """Convert matplotlib color code to hex color or RGBA color""" + if color is None or colorConverter.to_rgba(color)[3] == 0: + return "none" + elif colorConverter.to_rgba(color)[3] == 1: + rgb = colorConverter.to_rgb(color) + return "#{0:02X}{1:02X}{2:02X}".format(*(int(255 * c) for c in rgb)) + else: + c = colorConverter.to_rgba(color) + return ( + "rgba(" + + ", ".join(str(int(np.round(val * 255))) for val in c[:3]) + + ", " + + str(c[3]) + + ")" + ) + + +def _many_to_one(input_dict): + """Convert a many-to-one mapping to a one-to-one mapping""" + return dict((key, val) for keys, val in input_dict.items() for key in keys) + + +LINESTYLES = _many_to_one( + { + ("solid", "-", (None, None)): "none", + ("dashed", "--"): "6,6", + ("dotted", ":"): "2,2", + ("dashdot", "-."): "4,4,2,4", + ("", " ", "None", "none"): None, + } +) + + +def get_dasharray(obj): + """Get an SVG dash array for the given matplotlib linestyle + + Parameters + ---------- + obj : matplotlib object + The matplotlib line or path object, which must have a get_linestyle() + method which returns a valid matplotlib line code + + Returns + ------- + dasharray : string + The HTML/SVG dasharray code associated with the object. + """ + if obj.__dict__.get("_dashSeq", None) is not None: + return ",".join(map(str, obj._dashSeq)) + else: + ls = obj.get_linestyle() + dasharray = LINESTYLES.get(ls, "not found") + if dasharray == "not found": + warnings.warn( + "line style '{0}' not understood: defaulting to solid line.".format(ls) + ) + dasharray = LINESTYLES["solid"] + return dasharray + + +PATH_DICT = { + Path.LINETO: "L", + Path.MOVETO: "M", + Path.CURVE3: "S", + Path.CURVE4: "C", + Path.CLOSEPOLY: "Z", +} + + +def SVG_path(path, transform=None, simplify=False): + """Construct the vertices and SVG codes for the path + + Parameters + ---------- + path : matplotlib.Path object + + transform : matplotlib transform (optional) + if specified, the path will be transformed before computing the output. + + Returns + ------- + vertices : array + The shape (M, 2) array of vertices of the Path. Note that some Path + codes require multiple vertices, so the length of these vertices may + be longer than the list of path codes. + path_codes : list + A length N list of single-character path codes, N <= M. Each code is + a single character, in ['L','M','S','C','Z']. See the standard SVG + path specification for a description of these. + """ + if transform is not None: + path = path.transformed(transform) + + vc_tuples = [ + (vertices if path_code != Path.CLOSEPOLY else [], PATH_DICT[path_code]) + for (vertices, path_code) in path.iter_segments(simplify=simplify) + ] + + if not vc_tuples: + # empty path is a special case + return np.zeros((0, 2)), [] + else: + vertices, codes = zip(*vc_tuples) + vertices = np.array(list(itertools.chain(*vertices))).reshape(-1, 2) + return vertices, list(codes) + + +def get_path_style(path, fill=True): + """Get the style dictionary for matplotlib path objects""" + style = {} + style["alpha"] = path.get_alpha() + if style["alpha"] is None: + style["alpha"] = 1 + style["edgecolor"] = export_color(path.get_edgecolor()) + if fill: + style["facecolor"] = export_color(path.get_facecolor()) + else: + style["facecolor"] = "none" + style["edgewidth"] = path.get_linewidth() + style["dasharray"] = get_dasharray(path) + style["zorder"] = path.get_zorder() + return style + + +def get_line_style(line): + """Get the style dictionary for matplotlib line objects""" + style = {} + style["alpha"] = line.get_alpha() + if style["alpha"] is None: + style["alpha"] = 1 + style["color"] = export_color(line.get_color()) + style["linewidth"] = line.get_linewidth() + style["dasharray"] = get_dasharray(line) + style["zorder"] = line.get_zorder() + style["drawstyle"] = line.get_drawstyle() + return style + + +def get_marker_style(line): + """Get the style dictionary for matplotlib marker objects""" + style = {} + style["alpha"] = line.get_alpha() + if style["alpha"] is None: + style["alpha"] = 1 + + style["facecolor"] = export_color(line.get_markerfacecolor()) + style["edgecolor"] = export_color(line.get_markeredgecolor()) + style["edgewidth"] = line.get_markeredgewidth() + + style["marker"] = line.get_marker() + markerstyle = MarkerStyle(line.get_marker()) + markersize = line.get_markersize() + markertransform = markerstyle.get_transform() + Affine2D().scale( + markersize, -markersize + ) + style["markerpath"] = SVG_path(markerstyle.get_path(), markertransform) + style["markersize"] = markersize + style["zorder"] = line.get_zorder() + return style + + +def get_text_style(text): + """Return the text style dict for a text instance""" + style = {} + style["alpha"] = text.get_alpha() + if style["alpha"] is None: + style["alpha"] = 1 + style["fontsize"] = text.get_size() + style["color"] = export_color(text.get_color()) + style["halign"] = text.get_horizontalalignment() # left, center, right + style["valign"] = text.get_verticalalignment() # baseline, center, top + style["malign"] = text._multialignment # text alignment when '\n' in text + style["rotation"] = text.get_rotation() + style["zorder"] = text.get_zorder() + return style + + +def get_axis_properties(axis): + """Return the property dictionary for a matplotlib.Axis instance""" + props = {} + label1On = axis._major_tick_kw.get("label1On", True) + + if isinstance(axis, matplotlib.axis.XAxis): + if label1On: + props["position"] = "bottom" + else: + props["position"] = "top" + elif isinstance(axis, matplotlib.axis.YAxis): + if label1On: + props["position"] = "left" + else: + props["position"] = "right" + else: + raise ValueError("{0} should be an Axis instance".format(axis)) + + # Use tick values if appropriate + locator = axis.get_major_locator() + props["nticks"] = len(locator()) + if isinstance(locator, ticker.FixedLocator): + props["tickvalues"] = list(locator()) + else: + props["tickvalues"] = None + + # Find tick formats + formatter = axis.get_major_formatter() + if isinstance(formatter, ticker.NullFormatter): + props["tickformat"] = "" + elif isinstance(formatter, ticker.FixedFormatter): + props["tickformat"] = list(formatter.seq) + elif isinstance(formatter, ticker.FuncFormatter): + props["tickformat"] = list(formatter.func.args[0].values()) + elif not any(label.get_visible() for label in axis.get_ticklabels()): + props["tickformat"] = "" + else: + props["tickformat"] = None + + # Get axis scale + props["scale"] = axis.get_scale() + + # Get major tick label size (assumes that's all we really care about!) + labels = axis.get_ticklabels() + if labels: + props["fontsize"] = labels[0].get_fontsize() + else: + props["fontsize"] = None + + # Get associated grid + props["grid"] = get_grid_style(axis) + + # get axis visibility + props["visible"] = axis.get_visible() + + return props + + +def get_grid_style(axis): + gridlines = axis.get_gridlines() + if axis._major_tick_kw["gridOn"] and len(gridlines) > 0: + color = export_color(gridlines[0].get_color()) + alpha = gridlines[0].get_alpha() + dasharray = get_dasharray(gridlines[0]) + return dict(gridOn=True, color=color, dasharray=dasharray, alpha=alpha) + else: + return {"gridOn": False} + + +def get_figure_properties(fig): + return { + "figwidth": fig.get_figwidth(), + "figheight": fig.get_figheight(), + "dpi": fig.dpi, + } + + +def get_axes_properties(ax): + props = { + "axesbg": export_color(ax.patch.get_facecolor()), + "axesbgalpha": ax.patch.get_alpha(), + "bounds": ax.get_position().bounds, + "dynamic": ax.get_navigate(), + "axison": ax.axison, + "frame_on": ax.get_frame_on(), + "patch_visible": ax.patch.get_visible(), + "axes": [get_axis_properties(ax.xaxis), get_axis_properties(ax.yaxis)], + } + + for axname in ["x", "y"]: + axis = getattr(ax, axname + "axis") + domain = getattr(ax, "get_{0}lim".format(axname))() + lim = domain + if isinstance(axis.converter, matplotlib.dates.DateConverter): + scale = "date" + try: + import pandas as pd + from pandas.tseries.converter import PeriodConverter + except ImportError: + pd = None + + if pd is not None and isinstance(axis.converter, PeriodConverter): + _dates = [pd.Period(ordinal=int(d), freq=axis.freq) for d in domain] + domain = [ + (d.year, d.month - 1, d.day, d.hour, d.minute, d.second, 0) + for d in _dates + ] + else: + domain = [ + ( + d.year, + d.month - 1, + d.day, + d.hour, + d.minute, + d.second, + d.microsecond * 1e-3, + ) + for d in matplotlib.dates.num2date(domain) + ] + else: + scale = axis.get_scale() + + if scale not in ["date", "linear", "log"]: + raise ValueError("Unknown axis scale: {0}".format(axis.get_scale())) + + props[axname + "scale"] = scale + props[axname + "lim"] = lim + props[axname + "domain"] = domain + + return props + + +def iter_all_children(obj, skipContainers=False): + """ + Returns an iterator over all childen and nested children using + obj's get_children() method + + if skipContainers is true, only childless objects are returned. + """ + if hasattr(obj, "get_children") and len(obj.get_children()) > 0: + for child in obj.get_children(): + if not skipContainers: + yield child + # could use `yield from` in python 3... + for grandchild in iter_all_children(child, skipContainers): + yield grandchild + else: + yield obj + + +def get_legend_properties(ax, legend): + handles, labels = ax.get_legend_handles_labels() + visible = legend.get_visible() + return {"handles": handles, "labels": labels, "visible": visible} + + +def image_to_base64(image): + """ + Convert a matplotlib image to a base64 png representation + + Parameters + ---------- + image : matplotlib image object + The image to be converted. + + Returns + ------- + image_base64 : string + The UTF8-encoded base64 string representation of the png image. + """ + ax = image.axes + binary_buffer = io.BytesIO() + + # image is saved in axes coordinates: we need to temporarily + # set the correct limits to get the correct image + lim = ax.axis() + ax.axis(image.get_extent()) + image.write_png(binary_buffer) + ax.axis(lim) + + binary_buffer.seek(0) + return base64.b64encode(binary_buffer.read()).decode("utf-8") diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mpltools.py b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mpltools.py new file mode 100644 index 0000000000000000000000000000000000000000..42681360030f33a18f5125aa440c1561d78c0068 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/mpltools.py @@ -0,0 +1,610 @@ +""" +Tools + +A module for converting from mpl language to plotly language. + +""" + +import math + +import warnings +import matplotlib.dates + + +def check_bar_match(old_bar, new_bar): + """Check if two bars belong in the same collection (bar chart). + + Positional arguments: + old_bar -- a previously sorted bar dictionary. + new_bar -- a new bar dictionary that needs to be sorted. + + """ + tests = [] + tests += (new_bar["orientation"] == old_bar["orientation"],) + tests += (new_bar["facecolor"] == old_bar["facecolor"],) + if new_bar["orientation"] == "v": + new_width = new_bar["x1"] - new_bar["x0"] + old_width = old_bar["x1"] - old_bar["x0"] + tests += (new_width - old_width < 0.000001,) + tests += (new_bar["y0"] == old_bar["y0"],) + elif new_bar["orientation"] == "h": + new_height = new_bar["y1"] - new_bar["y0"] + old_height = old_bar["y1"] - old_bar["y0"] + tests += (new_height - old_height < 0.000001,) + tests += (new_bar["x0"] == old_bar["x0"],) + if all(tests): + return True + else: + return False + + +def check_corners(inner_obj, outer_obj): + inner_corners = inner_obj.get_window_extent().corners() + outer_corners = outer_obj.get_window_extent().corners() + if inner_corners[0][0] < outer_corners[0][0]: + return False + elif inner_corners[0][1] < outer_corners[0][1]: + return False + elif inner_corners[3][0] > outer_corners[3][0]: + return False + elif inner_corners[3][1] > outer_corners[3][1]: + return False + else: + return True + + +def convert_dash(mpl_dash): + """Convert mpl line symbol to plotly line symbol and return symbol.""" + if mpl_dash in DASH_MAP: + return DASH_MAP[mpl_dash] + else: + dash_array = mpl_dash.split(",") + + if len(dash_array) < 2: + return "solid" + + # Catch the exception where the off length is zero, in case + # matplotlib 'solid' changes from '10,0' to 'N,0' + if math.isclose(float(dash_array[1]), 0.0): + return "solid" + + # If we can't find the dash pattern in the map, convert it + # into custom values in px, e.g. '7,5' -> '7px,5px' + dashpx = ",".join([x + "px" for x in dash_array]) + + # TODO: rewrite the convert_dash code + # only strings 'solid', 'dashed', etc allowed + if dashpx == "7.4px,3.2px": + dashpx = "dashed" + elif dashpx == "12.8px,3.2px,2.0px,3.2px": + dashpx = "dashdot" + elif dashpx == "2.0px,3.3px": + dashpx = "dotted" + return dashpx + + +def convert_path(path): + code = tuple(path[1]) + if code in PATH_MAP: + return PATH_MAP[code] + else: + return None + + +def convert_symbol(mpl_symbol): + """Convert mpl marker symbol to plotly symbol and return symbol.""" + if isinstance(mpl_symbol, list): + symbol = list() + for s in mpl_symbol: + symbol += [convert_symbol(s)] + return symbol + elif mpl_symbol in SYMBOL_MAP: + return SYMBOL_MAP[mpl_symbol] + else: + return "circle" # default + + +def hex_to_rgb(value): + """ + Change a hex color to an rgb tuple + + :param (str|unicode) value: The hex string we want to convert. + :return: (int, int, int) The red, green, blue int-tuple. + + Example: + + '#FFFFFF' --> (255, 255, 255) + + """ + value = value.lstrip("#") + lv = len(value) + return tuple(int(value[i : i + lv // 3], 16) for i in range(0, lv, lv // 3)) + + +def merge_color_and_opacity(color, opacity): + """ + Merge hex color with an alpha (opacity) to get an rgba tuple. + + :param (str|unicode) color: A hex color string. + :param (float|int) opacity: A value [0, 1] for the 'a' in 'rgba'. + :return: (int, int, int, float) The rgba color and alpha tuple. + + """ + if color is None: # None can be used as a placeholder, just bail. + return None + + rgb_tup = hex_to_rgb(color) + if opacity is None: + return "rgb {}".format(rgb_tup) + + rgba_tup = rgb_tup + (opacity,) + return "rgba {}".format(rgba_tup) + + +def convert_va(mpl_va): + """Convert mpl vertical alignment word to equivalent HTML word. + + Text alignment specifiers from mpl differ very slightly from those used + in HTML. See the VA_MAP for more details. + + Positional arguments: + mpl_va -- vertical mpl text alignment spec. + + """ + if mpl_va in VA_MAP: + return VA_MAP[mpl_va] + else: + return None # let plotly figure it out! + + +def convert_x_domain(mpl_plot_bounds, mpl_max_x_bounds): + """Map x dimension of current plot to plotly's domain space. + + The bbox used to locate an axes object in mpl differs from the + method used to locate axes in plotly. The mpl version locates each + axes in the figure so that axes in a single-plot figure might have + the bounds, [0.125, 0.125, 0.775, 0.775] (x0, y0, width, height), + in mpl's figure coordinates. However, the axes all share one space in + plotly such that the domain will always be [0, 0, 1, 1] + (x0, y0, x1, y1). To convert between the two, the mpl figure bounds + need to be mapped to a [0, 1] domain for x and y. The margins set + upon opening a new figure will appropriately match the mpl margins. + + Optionally, setting margins=0 and simply copying the domains from + mpl to plotly would place axes appropriately. However, + this would throw off axis and title labeling. + + Positional arguments: + mpl_plot_bounds -- the (x0, y0, width, height) params for current ax ** + mpl_max_x_bounds -- overall (x0, x1) bounds for all axes ** + + ** these are all specified in mpl figure coordinates + + """ + mpl_x_dom = [mpl_plot_bounds[0], mpl_plot_bounds[0] + mpl_plot_bounds[2]] + plotting_width = mpl_max_x_bounds[1] - mpl_max_x_bounds[0] + x0 = (mpl_x_dom[0] - mpl_max_x_bounds[0]) / plotting_width + x1 = (mpl_x_dom[1] - mpl_max_x_bounds[0]) / plotting_width + return [x0, x1] + + +def convert_y_domain(mpl_plot_bounds, mpl_max_y_bounds): + """Map y dimension of current plot to plotly's domain space. + + The bbox used to locate an axes object in mpl differs from the + method used to locate axes in plotly. The mpl version locates each + axes in the figure so that axes in a single-plot figure might have + the bounds, [0.125, 0.125, 0.775, 0.775] (x0, y0, width, height), + in mpl's figure coordinates. However, the axes all share one space in + plotly such that the domain will always be [0, 0, 1, 1] + (x0, y0, x1, y1). To convert between the two, the mpl figure bounds + need to be mapped to a [0, 1] domain for x and y. The margins set + upon opening a new figure will appropriately match the mpl margins. + + Optionally, setting margins=0 and simply copying the domains from + mpl to plotly would place axes appropriately. However, + this would throw off axis and title labeling. + + Positional arguments: + mpl_plot_bounds -- the (x0, y0, width, height) params for current ax ** + mpl_max_y_bounds -- overall (y0, y1) bounds for all axes ** + + ** these are all specified in mpl figure coordinates + + """ + mpl_y_dom = [mpl_plot_bounds[1], mpl_plot_bounds[1] + mpl_plot_bounds[3]] + plotting_height = mpl_max_y_bounds[1] - mpl_max_y_bounds[0] + y0 = (mpl_y_dom[0] - mpl_max_y_bounds[0]) / plotting_height + y1 = (mpl_y_dom[1] - mpl_max_y_bounds[0]) / plotting_height + return [y0, y1] + + +def display_to_paper(x, y, layout): + """Convert mpl display coordinates to plotly paper coordinates. + + Plotly references object positions with an (x, y) coordinate pair in either + 'data' or 'paper' coordinates which reference actual data in a plot or + the entire plotly axes space where the bottom-left of the bottom-left + plot has the location (x, y) = (0, 0) and the top-right of the top-right + plot has the location (x, y) = (1, 1). Display coordinates in mpl reference + objects with an (x, y) pair in pixel coordinates, where the bottom-left + corner is at the location (x, y) = (0, 0) and the top-right corner is at + the location (x, y) = (figwidth*dpi, figheight*dpi). Here, figwidth and + figheight are in inches and dpi are the dots per inch resolution. + + """ + num_x = x - layout["margin"]["l"] + den_x = layout["width"] - (layout["margin"]["l"] + layout["margin"]["r"]) + num_y = y - layout["margin"]["b"] + den_y = layout["height"] - (layout["margin"]["b"] + layout["margin"]["t"]) + return num_x / den_x, num_y / den_y + + +def get_axes_bounds(fig): + """Return the entire axes space for figure. + + An axes object in mpl is specified by its relation to the figure where + (0,0) corresponds to the bottom-left part of the figure and (1,1) + corresponds to the top-right. Margins exist in matplotlib because axes + objects normally don't go to the edges of the figure. + + In plotly, the axes area (where all subplots go) is always specified with + the domain [0,1] for both x and y. This function finds the smallest box, + specified by two points, that all of the mpl axes objects fit into. This + box is then used to map mpl axes domains to plotly axes domains. + + """ + x_min, x_max, y_min, y_max = [], [], [], [] + for axes_obj in fig.get_axes(): + bounds = axes_obj.get_position().bounds + x_min.append(bounds[0]) + x_max.append(bounds[0] + bounds[2]) + y_min.append(bounds[1]) + y_max.append(bounds[1] + bounds[3]) + x_min, y_min, x_max, y_max = min(x_min), min(y_min), max(x_max), max(y_max) + return (x_min, x_max), (y_min, y_max) + + +def get_axis_mirror(main_spine, mirror_spine): + if main_spine and mirror_spine: + return "ticks" + elif main_spine and not mirror_spine: + return False + elif not main_spine and mirror_spine: + return False # can't handle this case yet! + else: + return False # nuttin'! + + +def get_bar_gap(bar_starts, bar_ends, tol=1e-10): + if len(bar_starts) == len(bar_ends) and len(bar_starts) > 1: + sides1 = bar_starts[1:] + sides2 = bar_ends[:-1] + gaps = [s2 - s1 for s2, s1 in zip(sides1, sides2)] + gap0 = gaps[0] + uniform = all([abs(gap0 - gap) < tol for gap in gaps]) + if uniform: + return gap0 + + +def convert_rgba_array(color_list): + clean_color_list = list() + for c in color_list: + clean_color_list += [ + dict(r=int(c[0] * 255), g=int(c[1] * 255), b=int(c[2] * 255), a=c[3]) + ] + plotly_colors = list() + for rgba in clean_color_list: + plotly_colors += ["rgba({r},{g},{b},{a})".format(**rgba)] + if len(plotly_colors) == 1: + return plotly_colors[0] + else: + return plotly_colors + + +def convert_path_array(path_array): + symbols = list() + for path in path_array: + symbols += [convert_path(path)] + if len(symbols) == 1: + return symbols[0] + else: + return symbols + + +def convert_linewidth_array(width_array): + if len(width_array) == 1: + return width_array[0] + else: + return width_array + + +def convert_size_array(size_array): + size = [math.sqrt(s) for s in size_array] + if len(size) == 1: + return size[0] + else: + return size + + +def get_markerstyle_from_collection(props): + markerstyle = dict( + alpha=None, + facecolor=convert_rgba_array(props["styles"]["facecolor"]), + marker=convert_path_array(props["paths"]), + edgewidth=convert_linewidth_array(props["styles"]["linewidth"]), + # markersize=convert_size_array(props['styles']['size']), # TODO! + markersize=convert_size_array(props["mplobj"].get_sizes()), + edgecolor=convert_rgba_array(props["styles"]["edgecolor"]), + ) + return markerstyle + + +def get_rect_xmin(data): + """Find minimum x value from four (x,y) vertices.""" + return min(data[0][0], data[1][0], data[2][0], data[3][0]) + + +def get_rect_xmax(data): + """Find maximum x value from four (x,y) vertices.""" + return max(data[0][0], data[1][0], data[2][0], data[3][0]) + + +def get_rect_ymin(data): + """Find minimum y value from four (x,y) vertices.""" + return min(data[0][1], data[1][1], data[2][1], data[3][1]) + + +def get_rect_ymax(data): + """Find maximum y value from four (x,y) vertices.""" + return max(data[0][1], data[1][1], data[2][1], data[3][1]) + + +def get_spine_visible(ax, spine_key): + """Return some spine parameters for the spine, `spine_key`.""" + spine = ax.spines[spine_key] + ax_frame_on = ax.get_frame_on() + position = spine._position or ("outward", 0.0) + if isinstance(position, str): + if position == "center": + position = ("axes", 0.5) + elif position == "zero": + position = ("data", 0) + position_type, amount = position + if position_type == "outward" and amount == 0: + spine_frame_like = True + else: + spine_frame_like = False + if not spine.get_visible(): + return False + elif not spine._edgecolor[-1]: # user's may have set edgecolor alpha==0 + return False + elif not ax_frame_on and spine_frame_like: + return False + elif ax_frame_on and spine_frame_like: + return True + elif not ax_frame_on and not spine_frame_like: + return True # we've already checked for that it's visible. + else: + return False # oh man, and i thought we exhausted the options... + + +def is_bar(bar_containers, **props): + """A test to decide whether a path is a bar from a vertical bar chart.""" + + # is this patch in a bar container? + for container in bar_containers: + if props["mplobj"] in container: + return True + return False + + +def make_bar(**props): + """Make an intermediate bar dictionary. + + This creates a bar dictionary which aids in the comparison of new bars to + old bars from other bar chart (patch) collections. This is not the + dictionary that needs to get passed to plotly as a data dictionary. That + happens in PlotlyRenderer in that class's draw_bar method. In other + words, this dictionary describes a SINGLE bar, whereas, plotly will + require a set of bars to be passed in a data dictionary. + + """ + return { + "bar": props["mplobj"], + "x0": get_rect_xmin(props["data"]), + "y0": get_rect_ymin(props["data"]), + "x1": get_rect_xmax(props["data"]), + "y1": get_rect_ymax(props["data"]), + "alpha": props["style"]["alpha"], + "edgecolor": props["style"]["edgecolor"], + "facecolor": props["style"]["facecolor"], + "edgewidth": props["style"]["edgewidth"], + "dasharray": props["style"]["dasharray"], + "zorder": props["style"]["zorder"], + } + + +def prep_ticks(ax, index, ax_type, props): + """Prepare axis obj belonging to axes obj. + + positional arguments: + ax - the mpl axes instance + index - the index of the axis in `props` + ax_type - 'x' or 'y' (for now) + props - an mplexporter poperties dictionary + + """ + axis_dict = dict() + if ax_type == "x": + axis = ax.get_xaxis() + elif ax_type == "y": + axis = ax.get_yaxis() + else: + return dict() # whoops! + + scale = props["axes"][index]["scale"] + if scale == "linear": + # get tick location information + try: + tickvalues = props["axes"][index]["tickvalues"] + tick0 = tickvalues[0] + dticks = [ + round(tickvalues[i] - tickvalues[i - 1], 12) + for i in range(1, len(tickvalues) - 1) + ] + if all([dticks[i] == dticks[i - 1] for i in range(1, len(dticks) - 1)]): + dtick = tickvalues[1] - tickvalues[0] + else: + warnings.warn( + "'linear' {0}-axis tick spacing not even, " + "ignoring mpl tick formatting.".format(ax_type) + ) + raise TypeError + except (IndexError, TypeError): + axis_dict["nticks"] = props["axes"][index]["nticks"] + else: + axis_dict["tick0"] = tick0 + axis_dict["dtick"] = dtick + axis_dict["tickmode"] = None + elif scale == "log": + try: + axis_dict["tick0"] = props["axes"][index]["tickvalues"][0] + axis_dict["dtick"] = ( + props["axes"][index]["tickvalues"][1] + - props["axes"][index]["tickvalues"][0] + ) + axis_dict["tickmode"] = None + except (IndexError, TypeError): + axis_dict = dict(nticks=props["axes"][index]["nticks"]) + base = axis.get_transform().base + if base == 10: + if ax_type == "x": + axis_dict["range"] = [ + math.log10(props["xlim"][0]), + math.log10(props["xlim"][1]), + ] + elif ax_type == "y": + axis_dict["range"] = [ + math.log10(props["ylim"][0]), + math.log10(props["ylim"][1]), + ] + else: + axis_dict = dict(range=None, type="linear") + warnings.warn( + "Converted non-base10 {0}-axis log scale to 'linear'".format(ax_type) + ) + else: + return dict() + # get tick label formatting information + formatter = axis.get_major_formatter().__class__.__name__ + if ax_type == "x" and "DateFormatter" in formatter: + axis_dict["type"] = "date" + try: + axis_dict["tick0"] = mpl_dates_to_datestrings(axis_dict["tick0"], formatter) + except KeyError: + pass + finally: + axis_dict.pop("dtick", None) + axis_dict.pop("tickmode", None) + axis_dict["range"] = mpl_dates_to_datestrings(props["xlim"], formatter) + + if formatter == "LogFormatterMathtext": + axis_dict["exponentformat"] = "e" + return axis_dict + + +def prep_xy_axis(ax, props, x_bounds, y_bounds): + xaxis = dict( + type=props["axes"][0]["scale"], + range=list(props["xlim"]), + showgrid=props["axes"][0]["grid"]["gridOn"], + domain=convert_x_domain(props["bounds"], x_bounds), + side=props["axes"][0]["position"], + tickfont=dict(size=props["axes"][0]["fontsize"]), + ) + xaxis.update(prep_ticks(ax, 0, "x", props)) + yaxis = dict( + type=props["axes"][1]["scale"], + range=list(props["ylim"]), + showgrid=props["axes"][1]["grid"]["gridOn"], + domain=convert_y_domain(props["bounds"], y_bounds), + side=props["axes"][1]["position"], + tickfont=dict(size=props["axes"][1]["fontsize"]), + ) + yaxis.update(prep_ticks(ax, 1, "y", props)) + return xaxis, yaxis + + +def mpl_dates_to_datestrings(dates, mpl_formatter): + """Convert matplotlib dates to iso-formatted-like time strings. + + Plotly's accepted format: "YYYY-MM-DD HH:MM:SS" (e.g., 2001-01-01 00:00:00) + + Info on mpl dates: http://matplotlib.org/api/dates_api.html + + """ + _dates = dates + + # this is a pandas datetime formatter, times show up in floating point days + # since the epoch (1970-01-01T00:00:00+00:00) + if mpl_formatter == "TimeSeries_DateFormatter": + try: + dates = matplotlib.dates.epoch2num([date * 24 * 60 * 60 for date in dates]) + dates = matplotlib.dates.num2date(dates) + except Exception: + return _dates + + # the rest of mpl dates are in floating point days since + # (0001-01-01T00:00:00+00:00) + 1. I.e., (0001-01-01T00:00:00+00:00) == 1.0 + # according to mpl --> try num2date(1) + else: + try: + dates = matplotlib.dates.num2date(dates) + except Exception: + return _dates + + time_stings = [ + " ".join(date.isoformat().split("+")[0].split("T")) for date in dates + ] + return time_stings + + +# dashed is dash in matplotlib +DASH_MAP = { + "10,0": "solid", + "6,6": "dash", + "2,2": "circle", + "4,4,2,4": "dashdot", + "none": "solid", + "7.4,3.2": "dash", +} + +PATH_MAP = { + ("M", "C", "C", "C", "C", "C", "C", "C", "C", "Z"): "o", + ("M", "L", "L", "L", "L", "L", "L", "L", "L", "L", "Z"): "*", + ("M", "L", "L", "L", "L", "L", "L", "L", "Z"): "8", + ("M", "L", "L", "L", "L", "L", "Z"): "h", + ("M", "L", "L", "L", "L", "Z"): "p", + ("M", "L", "M", "L", "M", "L"): "1", + ("M", "L", "L", "L", "Z"): "s", + ("M", "L", "M", "L"): "+", + ("M", "L", "L", "Z"): "^", + ("M", "L"): "|", +} + +SYMBOL_MAP = { + "o": "circle", + "v": "triangle-down", + "^": "triangle-up", + "<": "triangle-left", + ">": "triangle-right", + "s": "square", + "+": "cross", + "x": "x", + "*": "star", + "D": "diamond", + "d": "diamond", +} + +VA_MAP = {"center": "middle", "baseline": "bottom", "top": "top"} diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/renderer.py b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/renderer.py new file mode 100644 index 0000000000000000000000000000000000000000..d55f86ef3c2cef62cb36e2d9e87ec870ef24ff94 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/renderer.py @@ -0,0 +1,826 @@ +""" +Renderer Module + +This module defines the PlotlyRenderer class and a single function, +fig_to_plotly, which is intended to be the main way that user's will interact +with the matplotlylib package. + +""" + +import warnings + +import plotly.graph_objs as go +from plotly.matplotlylib.mplexporter import Renderer +from plotly.matplotlylib import mpltools + + +# Warning format +def warning_on_one_line(msg, category, filename, lineno, file=None, line=None): + return "%s:%s: %s:\n\n%s\n\n" % (filename, lineno, category.__name__, msg) + + +warnings.formatwarning = warning_on_one_line + + +class PlotlyRenderer(Renderer): + """A renderer class inheriting from base for rendering mpl plots in plotly. + + A renderer class to be used with an exporter for rendering matplotlib + plots in Plotly. This module defines the PlotlyRenderer class which handles + the creation of the JSON structures that get sent to plotly. + + All class attributes available are defined in __init__(). + + Basic Usage: + + # (mpl code) # + fig = gcf() + renderer = PlotlyRenderer(fig) + exporter = Exporter(renderer) + exporter.run(fig) # ... et voila + + """ + + def __init__(self): + """Initialize PlotlyRenderer obj. + + PlotlyRenderer obj is called on by an Exporter object to draw + matplotlib objects like figures, axes, text, etc. + + All class attributes are listed here in the __init__ method. + + """ + self.plotly_fig = go.Figure() + self.mpl_fig = None + self.current_mpl_ax = None + self.bar_containers = None + self.current_bars = [] + self.axis_ct = 0 + self.x_is_mpl_date = False + self.mpl_x_bounds = (0, 1) + self.mpl_y_bounds = (0, 1) + self.msg = "Initialized PlotlyRenderer\n" + self._processing_legend = False + self._legend_visible = False + + def open_figure(self, fig, props): + """Creates a new figure by beginning to fill out layout dict. + + The 'autosize' key is set to false so that the figure will mirror + sizes set by mpl. The 'hovermode' key controls what shows up when you + mouse around a figure in plotly, it's set to show the 'closest' point. + + Positional agurments: + fig -- a matplotlib.figure.Figure object. + props.keys(): [ + 'figwidth', + 'figheight', + 'dpi' + ] + + """ + self.msg += "Opening figure\n" + self.mpl_fig = fig + self.plotly_fig["layout"] = go.Layout( + width=int(props["figwidth"] * props["dpi"]), + height=int(props["figheight"] * props["dpi"]), + autosize=False, + hovermode="closest", + ) + self.mpl_x_bounds, self.mpl_y_bounds = mpltools.get_axes_bounds(fig) + margin = go.layout.Margin( + l=int(self.mpl_x_bounds[0] * self.plotly_fig["layout"]["width"]), + r=int((1 - self.mpl_x_bounds[1]) * self.plotly_fig["layout"]["width"]), + t=int((1 - self.mpl_y_bounds[1]) * self.plotly_fig["layout"]["height"]), + b=int(self.mpl_y_bounds[0] * self.plotly_fig["layout"]["height"]), + pad=0, + ) + self.plotly_fig["layout"]["margin"] = margin + + def close_figure(self, fig): + """Closes figure by cleaning up data and layout dictionaries. + + The PlotlyRenderer's job is to create an appropriate set of data and + layout dictionaries. When the figure is closed, some cleanup and + repair is necessary. This method removes inappropriate dictionary + entries, freeing up Plotly to use defaults and best judgements to + complete the entries. This method is called by an Exporter object. + + Positional arguments: + fig -- a matplotlib.figure.Figure object. + + """ + self.msg += "Closing figure\n" + + def open_axes(self, ax, props): + """Setup a new axes object (subplot in plotly). + + Plotly stores information about subplots in different 'xaxis' and + 'yaxis' objects which are numbered. These are just dictionaries + included in the layout dictionary. This function takes information + from the Exporter, fills in appropriate dictionary entries, + and updates the layout dictionary. PlotlyRenderer keeps track of the + number of plots by incrementing the axis_ct attribute. + + Setting the proper plot domain in plotly is a bit tricky. Refer to + the documentation for mpltools.convert_x_domain and + mpltools.convert_y_domain. + + Positional arguments: + ax -- an mpl axes object. This will become a subplot in plotly. + props.keys() -- [ + 'axesbg', (background color for axes obj) + 'axesbgalpha', (alpha, or opacity for background) + 'bounds', ((x0, y0, width, height) for axes) + 'dynamic', (zoom/pan-able?) + 'axes', (list: [xaxis, yaxis]) + 'xscale', (log, linear, or date) + 'yscale', + 'xlim', (range limits for x) + 'ylim', + 'xdomain' (xdomain=xlim, unless it's a date) + 'ydomain' + ] + + """ + self.msg += " Opening axes\n" + self.current_mpl_ax = ax + self.bar_containers = [ + c + for c in ax.containers # empty is OK + if c.__class__.__name__ == "BarContainer" + ] + self.current_bars = [] + self.axis_ct += 1 + # set defaults in axes + xaxis = go.layout.XAxis( + anchor="y{0}".format(self.axis_ct), zeroline=False, ticks="inside" + ) + yaxis = go.layout.YAxis( + anchor="x{0}".format(self.axis_ct), zeroline=False, ticks="inside" + ) + # update defaults with things set in mpl + mpl_xaxis, mpl_yaxis = mpltools.prep_xy_axis( + ax=ax, props=props, x_bounds=self.mpl_x_bounds, y_bounds=self.mpl_y_bounds + ) + xaxis.update(mpl_xaxis) + yaxis.update(mpl_yaxis) + bottom_spine = mpltools.get_spine_visible(ax, "bottom") + top_spine = mpltools.get_spine_visible(ax, "top") + left_spine = mpltools.get_spine_visible(ax, "left") + right_spine = mpltools.get_spine_visible(ax, "right") + xaxis["mirror"] = mpltools.get_axis_mirror(bottom_spine, top_spine) + yaxis["mirror"] = mpltools.get_axis_mirror(left_spine, right_spine) + xaxis["showline"] = bottom_spine + yaxis["showline"] = top_spine + + # put axes in our figure + self.plotly_fig["layout"]["xaxis{0}".format(self.axis_ct)] = xaxis + self.plotly_fig["layout"]["yaxis{0}".format(self.axis_ct)] = yaxis + + # let all subsequent dates be handled properly if required + + if "type" in dir(xaxis) and xaxis["type"] == "date": + self.x_is_mpl_date = True + + def close_axes(self, ax): + """Close the axes object and clean up. + + Bars from bar charts are given to PlotlyRenderer one-by-one, + thus they need to be taken care of at the close of each axes object. + The self.current_bars variable should be empty unless a bar + chart has been created. + + Positional arguments: + ax -- an mpl axes object, not required at this time. + + """ + self.draw_bars(self.current_bars) + self.msg += " Closing axes\n" + self.x_is_mpl_date = False + + def open_legend(self, legend, props): + """Enable Plotly's native legend when matplotlib legend is detected. + + This method is called when a matplotlib legend is found. It enables + Plotly's showlegend only if the matplotlib legend is visible. + + Positional arguments: + legend -- matplotlib.legend.Legend object + props -- legend properties dictionary + """ + self.msg += " Opening legend\n" + self._processing_legend = True + self._legend_visible = props.get("visible", True) + if self._legend_visible: + self.msg += ( + " Enabling native plotly legend (matplotlib legend is visible)\n" + ) + self.plotly_fig["layout"]["showlegend"] = True + else: + self.msg += " Not enabling legend (matplotlib legend is not visible)\n" + + def close_legend(self, legend): + """Finalize legend processing. + + Positional arguments: + legend -- matplotlib.legend.Legend object + """ + self.msg += " Closing legend\n" + self._processing_legend = False + self._legend_visible = False + + def draw_bars(self, bars): + # sort bars according to bar containers + mpl_traces = [] + for container in self.bar_containers: + mpl_traces.append( + [ + bar_props + for bar_props in self.current_bars + if bar_props["mplobj"] in container + ] + ) + for trace in mpl_traces: + self.draw_bar(trace) + + def draw_bar(self, coll): + """Draw a collection of similar patches as a bar chart. + + After bars are sorted, an appropriate data dictionary must be created + to tell plotly about this data. Just like draw_line or draw_markers, + draw_bar translates patch/path information into something plotly + understands. + + Positional arguments: + patch_coll -- a collection of patches to be drawn as a bar chart. + + """ + tol = 1e-10 + trace = [mpltools.make_bar(**bar_props) for bar_props in coll] + widths = [bar_props["x1"] - bar_props["x0"] for bar_props in trace] + heights = [bar_props["y1"] - bar_props["y0"] for bar_props in trace] + vertical = abs(sum(widths[0] - widths[iii] for iii in range(len(widths)))) < tol + horizontal = ( + abs(sum(heights[0] - heights[iii] for iii in range(len(heights)))) < tol + ) + if vertical and horizontal: + # Check for monotonic x. Can't both be true! + x_zeros = [bar_props["x0"] for bar_props in trace] + if all( + (x_zeros[iii + 1] > x_zeros[iii] for iii in range(len(x_zeros[:-1]))) + ): + orientation = "v" + else: + orientation = "h" + elif vertical: + orientation = "v" + else: + orientation = "h" + if orientation == "v": + self.msg += " Attempting to draw a vertical bar chart\n" + old_heights = [bar_props["y1"] for bar_props in trace] + for bar in trace: + bar["y0"], bar["y1"] = 0, bar["y1"] - bar["y0"] + new_heights = [bar_props["y1"] for bar_props in trace] + # check if we're stacked or not... + for old, new in zip(old_heights, new_heights): + if abs(old - new) > tol: + self.plotly_fig["layout"]["barmode"] = "stack" + self.plotly_fig["layout"]["hovermode"] = "x" + x = [bar["x0"] + (bar["x1"] - bar["x0"]) / 2 for bar in trace] + y = [bar["y1"] for bar in trace] + bar_gap = mpltools.get_bar_gap( + [bar["x0"] for bar in trace], [bar["x1"] for bar in trace] + ) + if self.x_is_mpl_date: + x = [bar["x0"] for bar in trace] + formatter = ( + self.current_mpl_ax.get_xaxis() + .get_major_formatter() + .__class__.__name__ + ) + x = mpltools.mpl_dates_to_datestrings(x, formatter) + else: + self.msg += " Attempting to draw a horizontal bar chart\n" + old_rights = [bar_props["x1"] for bar_props in trace] + for bar in trace: + bar["x0"], bar["x1"] = 0, bar["x1"] - bar["x0"] + new_rights = [bar_props["x1"] for bar_props in trace] + # check if we're stacked or not... + for old, new in zip(old_rights, new_rights): + if abs(old - new) > tol: + self.plotly_fig["layout"]["barmode"] = "stack" + self.plotly_fig["layout"]["hovermode"] = "y" + x = [bar["x1"] for bar in trace] + y = [bar["y0"] + (bar["y1"] - bar["y0"]) / 2 for bar in trace] + bar_gap = mpltools.get_bar_gap( + [bar["y0"] for bar in trace], [bar["y1"] for bar in trace] + ) + bar = go.Bar( + orientation=orientation, + x=x, + y=y, + xaxis="x{0}".format(self.axis_ct), + yaxis="y{0}".format(self.axis_ct), + opacity=trace[0]["alpha"], # TODO: get all alphas if array? + marker=go.bar.Marker( + color=trace[0]["facecolor"], # TODO: get all + line=dict(width=trace[0]["edgewidth"]), + ), + ) # TODO ditto + if len(bar["x"]) > 1: + self.msg += " Heck yeah, I drew that bar chart\n" + self.plotly_fig.add_trace(bar) + if bar_gap is not None: + self.plotly_fig["layout"]["bargap"] = bar_gap + else: + self.msg += " Bar chart not drawn\n" + warnings.warn( + "found box chart data with length <= 1, " + "assuming data redundancy, not plotting." + ) + + def draw_marked_line(self, **props): + """Create a data dict for a line obj. + + This will draw 'lines', 'markers', or 'lines+markers'. For legend elements, + this will use layout.shapes, so they can be positioned with paper refs. + + props.keys() -- [ + 'coordinates', ('data', 'axes', 'figure', or 'display') + 'data', (a list of xy pairs) + 'mplobj', (the matplotlib.lines.Line2D obj being rendered) + 'label', (the name of the Line2D obj being rendered) + 'linestyle', (linestyle dict, can be None, see below) + 'markerstyle', (markerstyle dict, can be None, see below) + ] + + props['linestyle'].keys() -- [ + 'alpha', (opacity of Line2D obj) + 'color', (color of the line if it exists, not the marker) + 'linewidth', + 'dasharray', (code for linestyle, see DASH_MAP in mpltools.py) + 'zorder', (viewing precedence when stacked with other objects) + ] + + props['markerstyle'].keys() -- [ + 'alpha', (opacity of Line2D obj) + 'marker', (the mpl marker symbol, see SYMBOL_MAP in mpltools.py) + 'facecolor', (color of the marker face) + 'edgecolor', (color of the marker edge) + 'edgewidth', (width of marker edge) + 'markerpath', (an SVG path for drawing the specified marker) + 'zorder', (viewing precedence when stacked with other objects) + ] + + """ + self.msg += " Attempting to draw a line " + line, marker, shape = {}, {}, {} + if props["linestyle"] and props["markerstyle"]: + self.msg += "... with both lines+markers\n" + mode = "lines+markers" + elif props["linestyle"]: + self.msg += "... with just lines\n" + mode = "lines" + elif props["markerstyle"]: + self.msg += "... with just markers\n" + mode = "markers" + if props["linestyle"]: + color = mpltools.merge_color_and_opacity( + props["linestyle"]["color"], props["linestyle"]["alpha"] + ) + + if props["coordinates"] == "data": + line = go.scatter.Line( + color=color, + width=props["linestyle"]["linewidth"], + dash=mpltools.convert_dash(props["linestyle"]["dasharray"]), + ) + else: + shape = dict( + line=dict( + color=color, + width=props["linestyle"]["linewidth"], + dash=mpltools.convert_dash(props["linestyle"]["dasharray"]), + ) + ) + if props["markerstyle"]: + if props["coordinates"] == "data": + marker = go.scatter.Marker( + opacity=props["markerstyle"]["alpha"], + color=props["markerstyle"]["facecolor"], + symbol=mpltools.convert_symbol(props["markerstyle"]["marker"]), + size=props["markerstyle"]["markersize"], + line=dict( + color=props["markerstyle"]["edgecolor"], + width=props["markerstyle"]["edgewidth"], + ), + ) + else: + shape = dict( + opacity=props["markerstyle"]["alpha"], + fillcolor=props["markerstyle"]["facecolor"], + symbol=mpltools.convert_symbol(props["markerstyle"]["marker"]), + size=props["markerstyle"]["markersize"], + line=dict( + color=props["markerstyle"]["edgecolor"], + width=props["markerstyle"]["edgewidth"], + ), + ) + if props["coordinates"] == "data": + marked_line = go.Scatter( + mode=mode, + name=( + str(props["label"]) + if isinstance(props["label"], str) + else props["label"] + ), + x=[xy_pair[0] for xy_pair in props["data"]], + y=[xy_pair[1] for xy_pair in props["data"]], + xaxis="x{0}".format(self.axis_ct), + yaxis="y{0}".format(self.axis_ct), + line=line, + marker=marker, + ) + if self.x_is_mpl_date: + formatter = ( + self.current_mpl_ax.get_xaxis() + .get_major_formatter() + .__class__.__name__ + ) + marked_line["x"] = mpltools.mpl_dates_to_datestrings( + marked_line["x"], formatter + ) + self.plotly_fig.add_trace(marked_line) + self.msg += " Heck yeah, I drew that line\n" + elif props["coordinates"] == "axes": + # dealing with legend graphical elements + self.msg += " Using native legend\n" + else: + self.msg += " Line didn't have 'data' coordinates, not drawing\n" + warnings.warn( + "Bummer! Plotly can currently only draw Line2D " + "objects from matplotlib that are in 'data' " + "coordinates!" + ) + + def draw_image(self, **props): + """Draw image. + + Not implemented yet! + + """ + self.msg += " Attempting to draw image\n" + self.msg += " Not drawing image\n" + warnings.warn( + "Aw. Snap! You're gonna have to hold off on " + "the selfies for now. Plotly can't import " + "images from matplotlib yet!" + ) + + def draw_path_collection(self, **props): + """Add a path collection to data list as a scatter plot. + + Current implementation defaults such collections as scatter plots. + Matplotlib supports collections that have many of the same parameters + in common like color, size, path, etc. However, they needn't all be + the same. Plotly does not currently support such functionality and + therefore, the style for the first object is taken and used to define + the remaining paths in the collection. + + props.keys() -- [ + 'paths', (structure: [vertices, path_code]) + 'path_coordinates', ('data', 'axes', 'figure', or 'display') + 'path_transforms', (mpl transform, including Affine2D matrix) + 'offsets', (offset from axes, helpful if in 'data') + 'offset_coordinates', ('data', 'axes', 'figure', or 'display') + 'offset_order', + 'styles', (style dict, see below) + 'mplobj' (the collection obj being drawn) + ] + + props['styles'].keys() -- [ + 'linewidth', (one or more linewidths) + 'facecolor', (one or more facecolors for path) + 'edgecolor', (one or more edgecolors for path) + 'alpha', (one or more opacites for path) + 'zorder', (precedence when stacked) + ] + + """ + self.msg += " Attempting to draw a path collection\n" + if props["offset_coordinates"] == "data": + markerstyle = mpltools.get_markerstyle_from_collection(props) + scatter_props = { + "coordinates": "data", + "data": props["offsets"], + "label": None, + "markerstyle": markerstyle, + "linestyle": None, + } + self.msg += " Drawing path collection as markers\n" + self.draw_marked_line(**scatter_props) + else: + self.msg += " Path collection not linked to 'data', not drawing\n" + warnings.warn( + "Dang! That path collection is out of this " + "world. I totally don't know what to do with " + "it yet! Plotly can only import path " + "collections linked to 'data' coordinates" + ) + + def draw_path(self, **props): + """Draw path, currently only attempts to draw bar charts. + + This function attempts to sort a given path into a collection of + horizontal or vertical bar charts. Most of the actual code takes + place in functions from mpltools.py. + + props.keys() -- [ + 'data', (a list of verticies for the path) + 'coordinates', ('data', 'axes', 'figure', or 'display') + 'pathcodes', (code for the path, structure: ['M', 'L', 'Z', etc.]) + 'style', (style dict, see below) + 'mplobj' (the mpl path object) + ] + + props['style'].keys() -- [ + 'alpha', (opacity of path obj) + 'edgecolor', + 'facecolor', + 'edgewidth', + 'dasharray', (style for path's enclosing line) + 'zorder' (precedence of obj when stacked) + ] + + """ + self.msg += " Attempting to draw a path\n" + is_bar = mpltools.is_bar(self.current_mpl_ax.containers, **props) + if is_bar: + self.current_bars += [props] + else: + self.msg += " This path isn't a bar, not drawing\n" + warnings.warn( + "I found a path object that I don't think is part " + "of a bar chart. Ignoring." + ) + + def draw_text(self, **props): + """Create an annotation dict for a text obj. + + Currently, plotly uses either 'page' or 'data' to reference + annotation locations. These refer to 'display' and 'data', + respectively for the 'coordinates' key used in the Exporter. + Appropriate measures are taken to transform text locations to + reference one of these two options. + + props.keys() -- [ + 'text', (actual content string, not the text obj) + 'position', (an x, y pair, not an mpl Bbox) + 'coordinates', ('data', 'axes', 'figure', 'display') + 'text_type', ('title', 'xlabel', or 'ylabel') + 'style', (style dict, see below) + 'mplobj' (actual mpl text object) + ] + + props['style'].keys() -- [ + 'alpha', (opacity of text) + 'fontsize', (size in points of text) + 'color', (hex color) + 'halign', (horizontal alignment, 'left', 'center', or 'right') + 'valign', (vertical alignment, 'baseline', 'center', or 'top') + 'rotation', + 'zorder', (precedence of text when stacked with other objs) + ] + + """ + self.msg += " Attempting to draw an mpl text object\n" + if not mpltools.check_corners(props["mplobj"], self.mpl_fig): + warnings.warn( + "Looks like the annotation(s) you are trying \n" + "to draw lies/lay outside the given figure size.\n\n" + "Therefore, the resulting Plotly figure may not be \n" + "large enough to view the full text. To adjust \n" + "the size of the figure, use the 'width' and \n" + "'height' keys in the Layout object. Alternatively,\n" + "use the Margin object to adjust the figure's margins." + ) + align = props["mplobj"]._multialignment + if not align: + align = props["style"]["halign"] # mpl default + if "annotations" not in self.plotly_fig["layout"]: + self.plotly_fig["layout"]["annotations"] = [] + if props["text_type"] == "xlabel": + self.msg += " Text object is an xlabel\n" + self.draw_xlabel(**props) + elif props["text_type"] == "ylabel": + self.msg += " Text object is a ylabel\n" + self.draw_ylabel(**props) + elif props["text_type"] == "title": + self.msg += " Text object is a title\n" + self.draw_title(**props) + else: # just a regular text annotation... + self.msg += " Text object is a normal annotation\n" + # Skip creating annotations for legend text when using native legend + if ( + self._processing_legend + and self._legend_visible + and props["coordinates"] == "axes" + ): + self.msg += ( + " Skipping legend text annotation (using native legend)\n" + ) + return + if props["coordinates"] != "data": + self.msg += " Text object isn't linked to 'data' coordinates\n" + x_px, y_px = ( + props["mplobj"].get_transform().transform(props["position"]) + ) + x, y = mpltools.display_to_paper(x_px, y_px, self.plotly_fig["layout"]) + xref = "paper" + yref = "paper" + xanchor = props["style"]["halign"] # no difference here! + yanchor = mpltools.convert_va(props["style"]["valign"]) + else: + self.msg += " Text object is linked to 'data' coordinates\n" + x, y = props["position"] + axis_ct = self.axis_ct + xaxis = self.plotly_fig["layout"]["xaxis{0}".format(axis_ct)] + yaxis = self.plotly_fig["layout"]["yaxis{0}".format(axis_ct)] + if ( + xaxis["range"][0] < x < xaxis["range"][1] + and yaxis["range"][0] < y < yaxis["range"][1] + ): + xref = "x{0}".format(self.axis_ct) + yref = "y{0}".format(self.axis_ct) + else: + self.msg += ( + " Text object is outside " + "plotting area, making 'paper' reference.\n" + ) + x_px, y_px = ( + props["mplobj"].get_transform().transform(props["position"]) + ) + x, y = mpltools.display_to_paper( + x_px, y_px, self.plotly_fig["layout"] + ) + xref = "paper" + yref = "paper" + xanchor = props["style"]["halign"] # no difference here! + yanchor = mpltools.convert_va(props["style"]["valign"]) + annotation = go.layout.Annotation( + text=( + str(props["text"]) + if isinstance(props["text"], str) + else props["text"] + ), + opacity=props["style"]["alpha"], + x=x, + y=y, + xref=xref, + yref=yref, + align=align, + xanchor=xanchor, + yanchor=yanchor, + showarrow=False, # change this later? + font=go.layout.annotation.Font( + color=props["style"]["color"], size=props["style"]["fontsize"] + ), + ) + self.plotly_fig["layout"]["annotations"] += (annotation,) + self.msg += " Heck, yeah I drew that annotation\n" + + def draw_title(self, **props): + """Add a title to the current subplot in layout dictionary. + + If there exists more than a single plot in the figure, titles revert + to 'page'-referenced annotations. + + props.keys() -- [ + 'text', (actual content string, not the text obj) + 'position', (an x, y pair, not an mpl Bbox) + 'coordinates', ('data', 'axes', 'figure', 'display') + 'text_type', ('title', 'xlabel', or 'ylabel') + 'style', (style dict, see below) + 'mplobj' (actual mpl text object) + ] + + props['style'].keys() -- [ + 'alpha', (opacity of text) + 'fontsize', (size in points of text) + 'color', (hex color) + 'halign', (horizontal alignment, 'left', 'center', or 'right') + 'valign', (vertical alignment, 'baseline', 'center', or 'top') + 'rotation', + 'zorder', (precedence of text when stacked with other objs) + ] + + """ + self.msg += " Attempting to draw a title\n" + if len(self.mpl_fig.axes) > 1: + self.msg += " More than one subplot, adding title as annotation\n" + x_px, y_px = props["mplobj"].get_transform().transform(props["position"]) + x, y = mpltools.display_to_paper(x_px, y_px, self.plotly_fig["layout"]) + annotation = go.layout.Annotation( + text=props["text"], + font=go.layout.annotation.Font( + color=props["style"]["color"], size=props["style"]["fontsize"] + ), + xref="paper", + yref="paper", + x=x, + y=y, + xanchor="center", + yanchor="bottom", + showarrow=False, # no arrow for a title! + ) + self.plotly_fig["layout"]["annotations"] += (annotation,) + else: + self.msg += " Only one subplot found, adding as a plotly title\n" + self.plotly_fig["layout"]["title"] = props["text"] + title_font = dict( + size=props["style"]["fontsize"], color=props["style"]["color"] + ) + self.plotly_fig["layout"]["title_font"] = title_font + + def draw_xlabel(self, **props): + """Add an xaxis label to the current subplot in layout dictionary. + + props.keys() -- [ + 'text', (actual content string, not the text obj) + 'position', (an x, y pair, not an mpl Bbox) + 'coordinates', ('data', 'axes', 'figure', 'display') + 'text_type', ('title', 'xlabel', or 'ylabel') + 'style', (style dict, see below) + 'mplobj' (actual mpl text object) + ] + + props['style'].keys() -- [ + 'alpha', (opacity of text) + 'fontsize', (size in points of text) + 'color', (hex color) + 'halign', (horizontal alignment, 'left', 'center', or 'right') + 'valign', (vertical alignment, 'baseline', 'center', or 'top') + 'rotation', + 'zorder', (precedence of text when stacked with other objs) + ] + + """ + self.msg += " Adding xlabel\n" + axis_key = "xaxis{0}".format(self.axis_ct) + self.plotly_fig["layout"][axis_key]["title"] = str(props["text"]) + title_font = dict( + size=props["style"]["fontsize"], color=props["style"]["color"] + ) + self.plotly_fig["layout"][axis_key]["title_font"] = title_font + + def draw_ylabel(self, **props): + """Add a yaxis label to the current subplot in layout dictionary. + + props.keys() -- [ + 'text', (actual content string, not the text obj) + 'position', (an x, y pair, not an mpl Bbox) + 'coordinates', ('data', 'axes', 'figure', 'display') + 'text_type', ('title', 'xlabel', or 'ylabel') + 'style', (style dict, see below) + 'mplobj' (actual mpl text object) + ] + + props['style'].keys() -- [ + 'alpha', (opacity of text) + 'fontsize', (size in points of text) + 'color', (hex color) + 'halign', (horizontal alignment, 'left', 'center', or 'right') + 'valign', (vertical alignment, 'baseline', 'center', or 'top') + 'rotation', + 'zorder', (precedence of text when stacked with other objs) + ] + + """ + self.msg += " Adding ylabel\n" + axis_key = "yaxis{0}".format(self.axis_ct) + self.plotly_fig["layout"][axis_key]["title"] = props["text"] + title_font = dict( + size=props["style"]["fontsize"], color=props["style"]["color"] + ) + self.plotly_fig["layout"][axis_key]["title_font"] = title_font + + def resize(self): + """Revert figure layout to allow plotly to resize. + + By default, PlotlyRenderer tries its hardest to precisely mimic an + mpl figure. However, plotly is pretty good with aesthetics. By + running PlotlyRenderer.resize(), layout parameters are deleted. This + lets plotly choose them instead of mpl. + + """ + self.msg += "Resizing figure, deleting keys from layout\n" + for key in ["width", "height", "autosize", "margin"]: + try: + del self.plotly_fig["layout"][key] + except (KeyError, AttributeError): + pass + + def strip_style(self): + self.msg += "Stripping mpl style is no longer supported\n" diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/tests/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/tests/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..c29e9896d6117be9ce19541780968759d12519b8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/tests/__init__.py @@ -0,0 +1,4 @@ +import matplotlib + +matplotlib.use("Agg") +import matplotlib.pyplot as plt diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/tests/__pycache__/__init__.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/tests/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..06c6783ea5f97702673280087d1f5dea04905685 Binary files /dev/null and b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/tests/__pycache__/__init__.cpython-312.pyc differ diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/tests/__pycache__/test_renderer.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/tests/__pycache__/test_renderer.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..794d9b2b3aaa1796e2e03a8b2b70b1f6056c3c6d Binary files /dev/null and b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/tests/__pycache__/test_renderer.cpython-312.pyc differ diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/tests/test_renderer.py b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/tests/test_renderer.py new file mode 100644 index 0000000000000000000000000000000000000000..0d63e4815b94993d609c99e6bbe83f5219a27f9c --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/matplotlylib/tests/test_renderer.py @@ -0,0 +1,86 @@ +import matplotlib.pyplot as plt +import plotly.tools as tls + + +def test_native_legend_enabled_when_matplotlib_legend_present(): + """Test that when matplotlib legend is present, Plotly uses native legend.""" + fig, ax = plt.subplots() + ax.plot([0, 1], [0, 1], label="Line 1") + ax.plot([0, 1], [1, 0], label="Line 2") + ax.legend() + + plotly_fig = tls.mpl_to_plotly(fig) + + # Should enable native legend + assert plotly_fig.layout.showlegend == True + # Should have 2 traces with names + assert len(plotly_fig.data) == 2 + assert plotly_fig.data[0].name == "Line 1" + assert plotly_fig.data[1].name == "Line 2" + + +def test_no_fake_legend_shapes_with_native_legend(): + """Test that fake legend shapes are not created when using native legend.""" + fig, ax = plt.subplots() + ax.plot([0, 1], [0, 1], "o-", label="Data with markers") + ax.legend() + + plotly_fig = tls.mpl_to_plotly(fig) + + # Should use native legend + assert plotly_fig.layout.showlegend == True + # Should not create fake legend elements + assert len(plotly_fig.layout.shapes) == 0 + assert len(plotly_fig.layout.annotations) == 0 + + +def test_legend_disabled_when_no_matplotlib_legend(): + """Test that legend is not enabled when no matplotlib legend is present.""" + fig, ax = plt.subplots() + ax.plot([0, 1], [0, 1], label="Line 1") # Has label but no legend() call + + plotly_fig = tls.mpl_to_plotly(fig) + + # Should not have showlegend explicitly set to True + # (Plotly's default behavior when no legend elements exist) + assert ( + not hasattr(plotly_fig.layout, "showlegend") + or plotly_fig.layout.showlegend != True + ) + + +def test_legend_disabled_when_matplotlib_legend_not_visible(): + """Test that legend is not enabled when no matplotlib legend is not visible.""" + fig, ax = plt.subplots() + ax.plot([0, 1], [0, 1], label="Line 1") + legend = ax.legend() + legend.set_visible(False) # Hide the legend + + plotly_fig = tls.mpl_to_plotly(fig) + + # Should not enable legend when matplotlib legend is hidden + assert ( + not hasattr(plotly_fig.layout, "showlegend") + or plotly_fig.layout.showlegend != True + ) + + +def test_multiple_traces_native_legend(): + """Test native legend works with multiple traces of different types.""" + fig, ax = plt.subplots() + ax.plot([0, 1, 2], [0, 1, 0], "-", label="Line") + ax.plot([0, 1, 2], [1, 0, 1], "o", label="Markers") + ax.plot([0, 1, 2], [0.5, 0.5, 0.5], "s-", label="Line+Markers") + ax.legend() + + plotly_fig = tls.mpl_to_plotly(fig) + + assert plotly_fig.layout.showlegend == True + assert len(plotly_fig.data) == 3 + assert plotly_fig.data[0].name == "Line" + assert plotly_fig.data[1].name == "Markers" + assert plotly_fig.data[2].name == "Line+Markers" + # Verify modes are correct + assert plotly_fig.data[0].mode == "lines" + assert plotly_fig.data[1].mode == "markers" + assert plotly_fig.data[2].mode == "lines+markers" diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/offline/__init__.py b/.venv_haddock/lib/python3.12/site-packages/plotly/offline/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..6088af9bc009d994568524aa679c9612c75f36e8 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/offline/__init__.py @@ -0,0 +1,18 @@ +# ruff: noqa: F401 +""" +offline +====== +This module provides offline functionality. +""" + +from .offline import ( + download_plotlyjs, + get_plotlyjs_version, + get_plotlyjs, + enable_mpl_offline, + init_notebook_mode, + iplot, + iplot_mpl, + plot, + plot_mpl, +) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/offline/__pycache__/__init__.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/plotly/offline/__pycache__/__init__.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..60013754e58b0d118392d56a12a78f43eda2f907 Binary files /dev/null and b/.venv_haddock/lib/python3.12/site-packages/plotly/offline/__pycache__/__init__.cpython-312.pyc differ diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/offline/__pycache__/_plotlyjs_version.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/plotly/offline/__pycache__/_plotlyjs_version.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..47662328a95389eb17fa565260620362127bea2d Binary files /dev/null and b/.venv_haddock/lib/python3.12/site-packages/plotly/offline/__pycache__/_plotlyjs_version.cpython-312.pyc differ diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/offline/__pycache__/offline.cpython-312.pyc b/.venv_haddock/lib/python3.12/site-packages/plotly/offline/__pycache__/offline.cpython-312.pyc new file mode 100644 index 0000000000000000000000000000000000000000..42841a22729b32ed36ae088e656d00a83fba8dd0 Binary files /dev/null and b/.venv_haddock/lib/python3.12/site-packages/plotly/offline/__pycache__/offline.cpython-312.pyc differ diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/offline/_plotlyjs_version.py b/.venv_haddock/lib/python3.12/site-packages/plotly/offline/_plotlyjs_version.py new file mode 100644 index 0000000000000000000000000000000000000000..6c51d692ec501b4cf20af8989a651f906ee89ff5 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/offline/_plotlyjs_version.py @@ -0,0 +1,3 @@ +# DO NOT EDIT +# This file is generated by the updatebundle commands.py command +__plotlyjs_version__ = "3.3.1" diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/offline/offline.py b/.venv_haddock/lib/python3.12/site-packages/plotly/offline/offline.py new file mode 100644 index 0000000000000000000000000000000000000000..bf94f03ecd85e03c8973e9c124ca6d6829af4e0b --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/offline/offline.py @@ -0,0 +1,834 @@ +"""Plotly Offline +A module to use Plotly's graphing library with Python +without connecting to a public or private plotly enterprise +server. +""" + +import os +import warnings +import pkgutil + +from plotly.optional_imports import get_module +from plotly import tools +from ._plotlyjs_version import __plotlyjs_version__ + + +__IMAGE_FORMATS = ["jpeg", "png", "webp", "svg"] + + +def download_plotlyjs(download_url): + warnings.warn( + """ + `download_plotlyjs` is deprecated and will be removed in the + next release. plotly.js is shipped with this module, it is no + longer necessary to download this bundle separately. + """, + DeprecationWarning, + ) + + +def get_plotlyjs_version(): + """ + Returns the version of plotly.js that is bundled with plotly.py. + + Returns + ------- + str + Plotly.js version string + """ + return __plotlyjs_version__ + + +def get_plotlyjs(): + """ + Return the contents of the minified plotly.js library as a string. + + This may be useful when building standalone HTML reports. + + Returns + ------- + str + Contents of the minified plotly.js library as a string + + Examples + -------- + Here is an example of creating a standalone HTML report that contains + two plotly figures, each in their own div. The include_plotlyjs argument + is set to False when creating the divs so that we don't include multiple + copies of the plotly.js library in the output. Instead, a single copy + of plotly.js is included in a script tag in the html head element. + + >>> import plotly.graph_objs as go + >>> from plotly.offline import plot, get_plotlyjs + >>> fig1 = go.Figure(data=[{'type': 'bar', 'y': [1, 3, 2]}], + ... layout={'height': 400}) + >>> fig2 = go.Figure(data=[{'type': 'scatter', 'y': [1, 3, 2]}], + ... layout={'height': 400}) + >>> div1 = plot(fig1, output_type='div', include_plotlyjs=False) + >>> div2 = plot(fig2, output_type='div', include_plotlyjs=False) + + >>> html = ''' + ... + ... + ... + ... + ... + ... {div1} + ... {div2} + ... + ... + ... '''.format(plotlyjs=get_plotlyjs(), div1=div1, div2=div2) + + >>> with open('multi_plot.html', 'w') as f: + ... f.write(html) # doctest: +SKIP + """ + path = os.path.join("package_data", "plotly.min.js") + plotlyjs = pkgutil.get_data("plotly", path).decode("utf-8") + return plotlyjs + + +def _build_resize_script(plotdivid, plotly_root="Plotly"): + resize_script = ( + '" + ).format(plotly_root=plotly_root, id=plotdivid) + return resize_script + + +def _build_mathjax_script(url): + return ''.format(url=url) + + +def _get_jconfig(config=None): + configkeys = ( + "staticPlot", + "plotlyServerURL", + "editable", + "edits", + "autosizable", + "responsive", + "queueLength", + "fillFrame", + "frameMargins", + "scrollZoom", + "doubleClick", + "showTips", + "showAxisDragHandles", + "showAxisRangeEntryBoxes", + "showLink", + "sendData", + "showSendToCloud", + "linkText", + "showSources", + "displayModeBar", + "modeBarButtonsToRemove", + "modeBarButtonsToAdd", + "modeBarButtons", + "toImageButtonOptions", + "displaylogo", + "watermark", + "plotGlPixelRatio", + "setBackground", + "topojsonURL", + "mapboxAccessToken", + "logging", + "globalTransforms", + "locale", + "locales", + "doubleClickDelay", + ) + + if config and isinstance(config, dict): + # Warn user on unrecognized config options. We make this a warning + # rather than an error since we don't have code generation logic in + # place yet to guarantee that the config options in plotly.py are up + # to date + bad_config = [k for k in config if k not in configkeys] + if bad_config: + warnings.warn( + """ +Unrecognized config options supplied: {bad_config}""".format(bad_config=bad_config) + ) + + clean_config = config + else: + clean_config = {} + + plotly_platform_url = tools.get_config_plotly_server_url() + + if not clean_config.get("plotlyServerURL", None): + clean_config["plotlyServerURL"] = plotly_platform_url + + if ( + plotly_platform_url != "https://plot.ly" + and clean_config.get("linkText", None) == "Export to plot.ly" + ): + link_domain = plotly_platform_url.replace("https://", "").replace("http://", "") + link_text = clean_config["linkText"].replace("plot.ly", link_domain) + clean_config["linkText"] = link_text + + return clean_config + + +# Build script to set global PlotlyConfig object. This must execute before +# plotly.js is loaded. +_window_plotly_config = """\ +""" + +_mathjax_config = """\ +""" + + +def get_image_download_script(caller): + """ + This function will return a script that will download an image of a Plotly + plot. + + Keyword Arguments: + caller ('plot', 'iplot') -- specifies which function made the call for the + download script. If `iplot`, then an extra condition is added into the + download script to ensure that download prompts aren't initiated on + page reloads. + """ + + if caller == "iplot": + check_start = "if(document.readyState == 'complete') {{" + check_end = "}}" + elif caller == "plot": + check_start = "" + check_end = "" + else: + raise ValueError("caller should only be one of `iplot` or `plot`") + + return ( + "function downloadimage(format, height, width," + " filename) {{" + "var p = document.getElementById('{{plot_id}}');" + "Plotly.downloadImage(p, {{format: format, height: height, " + "width: width, filename: filename}});}};" + + check_start + + "downloadimage('{format}', {height}, {width}, " + "'{filename}');" + check_end + ) + + +def build_save_image_post_script( + image, image_filename, image_height, image_width, caller +): + if image: + if image not in __IMAGE_FORMATS: + raise ValueError( + "The image parameter must be one of the following: {}".format( + __IMAGE_FORMATS + ) + ) + + script = get_image_download_script(caller) + post_script = script.format( + format=image, + width=image_width, + height=image_height, + filename=image_filename, + ) + else: + post_script = None + + return post_script + + +def init_notebook_mode(connected=False): + """ + Initialize plotly.js in the browser if it hasn't been loaded into the DOM + yet. This is an idempotent method and can and should be called from any + offline methods that require plotly.js to be loaded into the notebook dom. + + Keyword arguments: + + connected (default=False) -- If True, the plotly.js library will be loaded + from an online CDN. If False, the plotly.js library will be loaded locally + from the plotly python package + + Use `connected=True` if you want your notebooks to have smaller file sizes. + In the case where `connected=False`, the entirety of the plotly.js library + will be loaded into the notebook, which will result in a file-size increase + of a couple megabytes. Additionally, because the library will be downloaded + from the web, you and your viewers must be connected to the internet to be + able to view charts within this notebook. + + Use `connected=False` if you want you and your collaborators to be able to + create and view these charts regardless of the availability of an internet + connection. This is the default option since it is the most predictable. + Note that under this setting the library will be included inline inside + your notebook, resulting in much larger notebook sizes compared to the case + where `connected=True`. + """ + import plotly.io as pio + + ipython = get_module("IPython") + if not ipython: + raise ImportError("`iplot` can only run inside an IPython Notebook.") + + if connected: + pio.renderers.default = "plotly_mimetype+notebook_connected" + else: + pio.renderers.default = "plotly_mimetype+notebook" + + # Trigger immediate activation of notebook. This way the plotly.js + # library reference is available to the notebook immediately + pio.renderers._activate_pending_renderers() + + +def iplot( + figure_or_data, + show_link=False, + link_text="Export to plot.ly", + validate=True, + image=None, + filename="plot_image", + image_width=800, + image_height=600, + config=None, + auto_play=True, + animation_opts=None, +): + """ + Draw plotly graphs inside an IPython or Jupyter notebook + + figure_or_data -- a plotly.graph_objs.Figure or plotly.graph_objs.Data or + dict or list that describes a Plotly graph. + See https://plot.ly/python/ for examples of + graph descriptions. + + Keyword arguments: + show_link (default=False) -- display a link in the bottom-right corner of + of the chart that will export the chart to + Plotly Cloud or Plotly Enterprise + link_text (default='Export to plot.ly') -- the text of export link + validate (default=True) -- validate that all of the keys in the figure + are valid? omit if your version of plotly.js + has become outdated with your version of + graph_reference.json or if you need to include + extra, unnecessary keys in your figure. + image (default=None |'png' |'jpeg' |'svg' |'webp') -- This parameter sets + the format of the image to be downloaded, if we choose to download an + image. This parameter has a default value of None indicating that no + image should be downloaded. Please note: for higher resolution images + and more export options, consider using plotly.io.write_image. See + https://plot.ly/python/static-image-export/ for more details. + filename (default='plot') -- Sets the name of the file your image + will be saved to. The extension should not be included. + image_height (default=600) -- Specifies the height of the image in `px`. + image_width (default=800) -- Specifies the width of the image in `px`. + config (default=None) -- Plot view options dictionary. Keyword arguments + `show_link` and `link_text` set the associated options in this + dictionary if it doesn't contain them already. + auto_play (default=True) -- Whether to automatically start the animation + sequence on page load, if the figure contains frames. Has no effect if + the figure does not contain frames. + animation_opts (default=None) -- Dict of custom animation parameters that + are used for the automatically started animation on page load. This + dict is passed to the function Plotly.animate in Plotly.js. See + https://github.com/plotly/plotly.js/blob/master/src/plots/animation_attributes.js + for available options. Has no effect if the figure + does not contain frames, or auto_play is False. + + Example: + ``` + from plotly.offline import init_notebook_mode, iplot + init_notebook_mode() + iplot([{'x': [1, 2, 3], 'y': [5, 2, 7]}]) + # We can also download an image of the plot by setting the image to the + format you want. e.g. `image='png'` + iplot([{'x': [1, 2, 3], 'y': [5, 2, 7]}], image='png') + ``` + + animation_opts Example: + ``` + from plotly.offline import iplot + figure = {'data': [{'x': [0, 1], 'y': [0, 1]}], + 'layout': {'xaxis': {'range': [0, 5], 'autorange': False}, + 'yaxis': {'range': [0, 5], 'autorange': False}, + 'title': 'Start Title'}, + 'frames': [{'data': [{'x': [1, 2], 'y': [1, 2]}]}, + {'data': [{'x': [1, 4], 'y': [1, 4]}]}, + {'data': [{'x': [3, 4], 'y': [3, 4]}], + 'layout': {'title': 'End Title'}}]} + iplot(figure, animation_opts={'frame': {'duration': 1}}) + ``` + """ + import plotly.io as pio + + ipython = get_module("IPython") + if not ipython: + raise ImportError("`iplot` can only run inside an IPython Notebook.") + + config = dict(config) if config else {} + config.setdefault("showLink", show_link) + config.setdefault("linkText", link_text) + + # Get figure + figure = tools.return_figure_from_figure_or_data(figure_or_data, validate) + + # Handle image request + post_script = build_save_image_post_script( + image, filename, image_height, image_width, "iplot" + ) + + # Show figure + pio.show( + figure, + validate=validate, + config=config, + auto_play=auto_play, + post_script=post_script, + animation_opts=animation_opts, + ) + + +def plot( + figure_or_data, + show_link=False, + link_text="Export to plot.ly", + validate=True, + output_type="file", + include_plotlyjs=True, + filename="temp-plot.html", + auto_open=True, + image=None, + image_filename="plot_image", + image_width=800, + image_height=600, + config=None, + include_mathjax=False, + auto_play=True, + animation_opts=None, +): + """Create a plotly graph locally as an HTML document or string. + + Example: + ``` + from plotly.offline import plot + import plotly.graph_objs as go + + plot([go.Scatter(x=[1, 2, 3], y=[3, 2, 6])], filename='my-graph.html') + # We can also download an image of the plot by setting the image parameter + # to the image format we want + plot([go.Scatter(x=[1, 2, 3], y=[3, 2, 6])], filename='my-graph.html', + image='jpeg') + ``` + More examples below. + + figure_or_data -- a plotly.graph_objs.Figure or plotly.graph_objs.Data or + dict or list that describes a Plotly graph. + See https://plot.ly/python/ for examples of + graph descriptions. + + Keyword arguments: + show_link (default=False) -- display a link in the bottom-right corner of + of the chart that will export the chart to Plotly Cloud or + Plotly Enterprise + link_text (default='Export to plot.ly') -- the text of export link + validate (default=True) -- validate that all of the keys in the figure + are valid? omit if your version of plotly.js has become outdated + with your version of graph_reference.json or if you need to include + extra, unnecessary keys in your figure. + output_type ('file' | 'div' - default 'file') -- if 'file', then + the graph is saved as a standalone HTML file and `plot` + returns None. + If 'div', then `plot` returns a string that just contains the + HTML
that contains the graph and the script to generate the + graph. + Use 'file' if you want to save and view a single graph at a time + in a standalone HTML file. + Use 'div' if you are embedding these graphs in an HTML file with + other graphs or HTML markup, like a HTML report or an website. + include_plotlyjs (True | False | 'cdn' | 'directory' | path - default=True) + Specifies how the plotly.js library is included in the output html + file or div string. + + If True, a script tag containing the plotly.js source code (~3MB) + is included in the output. HTML files generated with this option are + fully self-contained and can be used offline. + + If 'cdn', a script tag that references the plotly.js CDN is included + in the output. HTML files generated with this option are about 3MB + smaller than those generated with include_plotlyjs=True, but they + require an active internet connection in order to load the plotly.js + library. + + If 'directory', a script tag is included that references an external + plotly.min.js bundle that is assumed to reside in the same + directory as the HTML file. If output_type='file' then the + plotly.min.js bundle is copied into the directory of the resulting + HTML file. If a file named plotly.min.js already exists in the output + directory then this file is left unmodified and no copy is performed. + HTML files generated with this option can be used offline, but they + require a copy of the plotly.min.js bundle in the same directory. + This option is useful when many figures will be saved as HTML files in + the same directory because the plotly.js source code will be included + only once per output directory, rather than once per output file. + + If a string that ends in '.js', a script tag is included that + references the specified path. This approach can be used to point + the resulting HTML file to an alternative CDN. + + If False, no script tag referencing plotly.js is included. This is + useful when output_type='div' and the resulting div string will be + placed inside an HTML document that already loads plotly.js. This + option is not advised when output_type='file' as it will result in + a non-functional html file. + filename (default='temp-plot.html') -- The local filename to save the + outputted chart to. If the filename already exists, it will be + overwritten. This argument only applies if `output_type` is 'file'. + auto_open (default=True) -- If True, open the saved file in a + web browser after saving. + This argument only applies if `output_type` is 'file'. + image (default=None |'png' |'jpeg' |'svg' |'webp') -- This parameter sets + the format of the image to be downloaded, if we choose to download an + image. This parameter has a default value of None indicating that no + image should be downloaded. Please note: for higher resolution images + and more export options, consider making requests to our image servers. + Type: `help(py.image)` for more details. + image_filename (default='plot_image') -- Sets the name of the file your + image will be saved to. The extension should not be included. + image_height (default=600) -- Specifies the height of the image in `px`. + image_width (default=800) -- Specifies the width of the image in `px`. + config (default=None) -- Plot view options dictionary. Keyword arguments + `show_link` and `link_text` set the associated options in this + dictionary if it doesn't contain them already. + include_mathjax (False | 'cdn' | path - default=False) -- + Specifies how the MathJax.js library is included in the output html + file or div string. MathJax is required in order to display labels + with LaTeX typesetting. + + If False, no script tag referencing MathJax.js will be included in the + output. HTML files generated with this option will not be able to + display LaTeX typesetting. + + If 'cdn', a script tag that references a MathJax CDN location will be + included in the output. HTML files generated with this option will be + able to display LaTeX typesetting as long as they have internet access. + + If a string that ends in '.js', a script tag is included that + references the specified path. This approach can be used to point the + resulting HTML file to an alternative CDN. + auto_play (default=True) -- Whether to automatically start the animation + sequence on page load if the figure contains frames. Has no effect if + the figure does not contain frames. + animation_opts (default=None) -- Dict of custom animation parameters that + are used for the automatically started animation on page load. This + dict is passed to the function Plotly.animate in Plotly.js. See + https://github.com/plotly/plotly.js/blob/master/src/plots/animation_attributes.js + for available options. Has no effect if the figure + does not contain frames, or auto_play is False. + + Example: + ``` + from plotly.offline import plot + figure = {'data': [{'x': [0, 1], 'y': [0, 1]}], + 'layout': {'xaxis': {'range': [0, 5], 'autorange': False}, + 'yaxis': {'range': [0, 5], 'autorange': False}, + 'title': 'Start Title'}, + 'frames': [{'data': [{'x': [1, 2], 'y': [1, 2]}]}, + {'data': [{'x': [1, 4], 'y': [1, 4]}]}, + {'data': [{'x': [3, 4], 'y': [3, 4]}], + 'layout': {'title': 'End Title'}}]} + plot(figure, animation_opts={'frame': {'duration': 1}}) + ``` + """ + import plotly.io as pio + + # Output type + if output_type not in ["div", "file"]: + raise ValueError( + "`output_type` argument must be 'div' or 'file'. " + "You supplied `" + output_type + "``" + ) + if not filename.endswith(".html") and output_type == "file": + warnings.warn( + "Your filename `" + filename + "` didn't end with .html. " + "Adding .html to the end of your file." + ) + filename += ".html" + + # Config + config = dict(config) if config else {} + config.setdefault("showLink", show_link) + config.setdefault("linkText", link_text) + + figure = tools.return_figure_from_figure_or_data(figure_or_data, validate) + width = figure.get("layout", {}).get("width", "100%") + height = figure.get("layout", {}).get("height", "100%") + + if width == "100%" or height == "100%": + config.setdefault("responsive", True) + + # Handle image request + post_script = build_save_image_post_script( + image, image_filename, image_height, image_width, "plot" + ) + + if output_type == "file": + pio.write_html( + figure, + filename, + config=config, + auto_play=auto_play, + include_plotlyjs=include_plotlyjs, + include_mathjax=include_mathjax, + post_script=post_script, + full_html=True, + validate=validate, + animation_opts=animation_opts, + auto_open=auto_open, + ) + return filename + else: + return pio.to_html( + figure, + config=config, + auto_play=auto_play, + include_plotlyjs=include_plotlyjs, + include_mathjax=include_mathjax, + post_script=post_script, + full_html=False, + validate=validate, + animation_opts=animation_opts, + ) + + +def plot_mpl( + mpl_fig, + resize=False, + strip_style=False, + verbose=False, + show_link=False, + link_text="Export to plot.ly", + validate=True, + output_type="file", + include_plotlyjs=True, + filename="temp-plot.html", + auto_open=True, + image=None, + image_filename="plot_image", + image_height=600, + image_width=800, +): + """ + Convert a matplotlib figure to a Plotly graph stored locally as HTML. + + For more information on converting matplotlib visualizations to plotly + graphs, call help(plotly.tools.mpl_to_plotly) + + For more information on creating plotly charts locally as an HTML document + or string, call help(plotly.offline.plot) + + mpl_fig -- a matplotlib figure object to convert to a plotly graph + + Keyword arguments: + resize (default=False) -- allow plotly to choose the figure size. + strip_style (default=False) -- allow plotly to choose style options. + verbose (default=False) -- print message. + show_link (default=False) -- display a link in the bottom-right corner of + of the chart that will export the chart to Plotly Cloud or + Plotly Enterprise + link_text (default='Export to plot.ly') -- the text of export link + validate (default=True) -- validate that all of the keys in the figure + are valid? omit if your version of plotly.js has become outdated + with your version of graph_reference.json or if you need to include + extra, unnecessary keys in your figure. + output_type ('file' | 'div' - default 'file') -- if 'file', then + the graph is saved as a standalone HTML file and `plot` + returns None. + If 'div', then `plot` returns a string that just contains the + HTML
that contains the graph and the script to generate the + graph. + Use 'file' if you want to save and view a single graph at a time + in a standalone HTML file. + Use 'div' if you are embedding these graphs in an HTML file with + other graphs or HTML markup, like a HTML report or an website. + include_plotlyjs (default=True) -- If True, include the plotly.js + source code in the output file or string. + Set as False if your HTML file already contains a copy of the plotly.js + library. + filename (default='temp-plot.html') -- The local filename to save the + outputted chart to. If the filename already exists, it will be + overwritten. This argument only applies if `output_type` is 'file'. + auto_open (default=True) -- If True, open the saved file in a + web browser after saving. + This argument only applies if `output_type` is 'file'. + image (default=None |'png' |'jpeg' |'svg' |'webp') -- This parameter sets + the format of the image to be downloaded, if we choose to download an + image. This parameter has a default value of None indicating that no + image should be downloaded. + image_filename (default='plot_image') -- Sets the name of the file your + image will be saved to. The extension should not be included. + image_height (default=600) -- Specifies the height of the image in `px`. + image_width (default=800) -- Specifies the width of the image in `px`. + + Example: + ``` + from plotly.offline import init_notebook_mode, plot_mpl + import matplotlib.pyplot as plt + + init_notebook_mode() + + fig = plt.figure() + x = [10, 15, 20, 25, 30] + y = [100, 250, 200, 150, 300] + plt.plot(x, y, "o") + + plot_mpl(fig) + # If you want to to download an image of the figure as well + plot_mpl(fig, image='png') + ``` + """ + plotly_plot = tools.mpl_to_plotly(mpl_fig, resize, strip_style, verbose) + return plot( + plotly_plot, + show_link, + link_text, + validate, + output_type, + include_plotlyjs, + filename, + auto_open, + image=image, + image_filename=image_filename, + image_height=image_height, + image_width=image_width, + ) + + +def iplot_mpl( + mpl_fig, + resize=False, + strip_style=False, + verbose=False, + show_link=False, + link_text="Export to plot.ly", + validate=True, + image=None, + image_filename="plot_image", + image_height=600, + image_width=800, +): + """ + Convert a matplotlib figure to a plotly graph and plot inside an IPython + notebook without connecting to an external server. + + To save the chart to Plotly Cloud or Plotly Enterprise, use + `plotly.plotly.plot_mpl`. + + For more information on converting matplotlib visualizations to plotly + graphs call `help(plotly.tools.mpl_to_plotly)` + + For more information on plotting plotly charts offline in an Ipython + notebook call `help(plotly.offline.iplot)` + + mpl_fig -- a matplotlib.figure to convert to a plotly graph + + Keyword arguments: + resize (default=False) -- allow plotly to choose the figure size. + strip_style (default=False) -- allow plotly to choose style options. + verbose (default=False) -- print message. + show_link (default=False) -- display a link in the bottom-right corner of + of the chart that will export the chart to + Plotly Cloud or Plotly Enterprise + link_text (default='Export to plot.ly') -- the text of export link + validate (default=True) -- validate that all of the keys in the figure + are valid? omit if your version of plotly.js + has become outdated with your version of + graph_reference.json or if you need to include + extra, unnecessary keys in your figure. + image (default=None |'png' |'jpeg' |'svg' |'webp') -- This parameter sets + the format of the image to be downloaded, if we choose to download an + image. This parameter has a default value of None indicating that no + image should be downloaded. + image_filename (default='plot_image') -- Sets the name of the file your + image will be saved to. The extension should not be included. + image_height (default=600) -- Specifies the height of the image in `px`. + image_width (default=800) -- Specifies the width of the image in `px`. + + Example: + ``` + from plotly.offline import init_notebook_mode, iplot_mpl + import matplotlib.pyplot as plt + + fig = plt.figure() + x = [10, 15, 20, 25, 30] + y = [100, 250, 200, 150, 300] + plt.plot(x, y, "o") + + init_notebook_mode() + iplot_mpl(fig) + # and if you want to download an image of the figure as well + iplot_mpl(fig, image='jpeg') + ``` + """ + plotly_plot = tools.mpl_to_plotly(mpl_fig, resize, strip_style, verbose) + return iplot( + plotly_plot, + show_link, + link_text, + validate, + image=image, + filename=image_filename, + image_height=image_height, + image_width=image_width, + ) + + +def enable_mpl_offline( + resize=False, + strip_style=False, + verbose=False, + show_link=False, + link_text="Export to plot.ly", + validate=True, +): + """ + Convert mpl plots to locally hosted HTML documents. + + This function should be used with the inline matplotlib backend + that ships with IPython that can be enabled with `%pylab inline` + or `%matplotlib inline`. This works by adding an HTML formatter + for Figure objects; the existing SVG/PNG formatters will remain + enabled. + + (idea taken from `mpld3._display.enable_notebook`) + + Example: + ``` + from plotly.offline import enable_mpl_offline + import matplotlib.pyplot as plt + + enable_mpl_offline() + + fig = plt.figure() + x = [10, 15, 20, 25, 30] + y = [100, 250, 200, 150, 300] + plt.plot(x, y, "o") + fig + ``` + """ + init_notebook_mode() + ipython = get_module("IPython") + matplotlib = get_module("matplotlib") + + ip = ipython.core.getipython.get_ipython() + formatter = ip.display_formatter.formatters["text/html"] + formatter.for_type( + matplotlib.figure.Figure, + lambda fig: iplot_mpl( + fig, resize, strip_style, verbose, show_link, link_text, validate + ), + ) diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/package_data/plotly.min.js b/.venv_haddock/lib/python3.12/site-packages/plotly/package_data/plotly.min.js new file mode 100644 index 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Eot=Eo();hoe.exports=function(t,r){r||(r=2);var n=t.marker,i=n.sizeref||1,a=n.sizemin||0,o=n.sizemode==="area"?function(s){return Math.sqrt(s/i)}:function(s){return s/i};return function(s){var l=o(s/r);return Eot(l)&&l>0?Math.max(l,a):0}}});var ip=ye(mv=>{"use strict";var aL=Dr();mv.getSubplot=function(e){return e.subplot||e.xaxis+e.yaxis||e.geo};mv.isTraceInSubplots=function(e,t){if(e.type==="splom"){for(var r=e.xaxes||[],n=e.yaxes||[],i=0;i=0&&r.index{poe.exports=Iot;var Fq={a:7,c:6,h:1,l:2,m:2,q:4,s:4,t:2,v:1,z:0},Pot=/([astvzqmhlc])([^astvzqmhlc]*)/ig;function Iot(e){var t=[];return e.replace(Pot,function(r,n,i){var a=n.toLowerCase();for(i=Dot(i),a=="m"&&i.length>2&&(t.push([n].concat(i.splice(0,2))),a="l",n=n=="m"?"l":"L");;){if(i.length==Fq[a])return i.unshift(n),t.push(i);if(i.length{"use strict";var Fot=eM(),ca=function(e,t){return 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vs(t,r,"M-"+n+","+i+"H"+n+"L0,-"+a+"Z")}},"triangle-down":{n:6,f:function(e,t,r){if(ds(t))return hs;var n=ca(e*2/i_,2),i=ca(e/2,2),a=ca(e,2);return vs(t,r,"M-"+n+",-"+i+"H"+n+"L0,"+a+"Z")}},"triangle-left":{n:7,f:function(e,t,r){if(ds(t))return hs;var n=ca(e*2/i_,2),i=ca(e/2,2),a=ca(e,2);return vs(t,r,"M"+i+",-"+n+"V"+n+"L-"+a+",0Z")}},"triangle-right":{n:8,f:function(e,t,r){if(ds(t))return hs;var n=ca(e*2/i_,2),i=ca(e/2,2),a=ca(e,2);return vs(t,r,"M-"+i+",-"+n+"V"+n+"L"+a+",0Z")}},"triangle-ne":{n:9,f:function(e,t,r){if(ds(t))return hs;var n=ca(e*.6,2),i=ca(e*1.2,2);return vs(t,r,"M-"+i+",-"+n+"H"+n+"V"+i+"Z")}},"triangle-se":{n:10,f:function(e,t,r){if(ds(t))return hs;var n=ca(e*.6,2),i=ca(e*1.2,2);return vs(t,r,"M"+n+",-"+i+"V"+n+"H-"+i+"Z")}},"triangle-sw":{n:11,f:function(e,t,r){if(ds(t))return hs;var n=ca(e*.6,2),i=ca(e*1.2,2);return vs(t,r,"M"+i+","+n+"H-"+n+"V-"+i+"Z")}},"triangle-nw":{n:12,f:function(e,t,r){if(ds(t))return hs;var n=ca(e*.6,2),i=ca(e*1.2,2);return vs(t,r,"M-"+n+","+i+"V-"+n+"H"+i+"Z")}},pentagon:{n:13,f:function(e,t,r){if(ds(t))return hs;var n=ca(e*.951,2),i=ca(e*.588,2),a=ca(-e,2),o=ca(e*-.309,2),s=ca(e*.809,2);return vs(t,r,"M"+n+","+o+"L"+i+","+s+"H-"+i+"L-"+n+","+o+"L0,"+a+"Z")}},hexagon:{n:14,f:function(e,t,r){if(ds(t))return hs;var n=ca(e,2),i=ca(e/2,2),a=ca(e*i_/2,2);return vs(t,r,"M"+a+",-"+i+"V"+i+"L0,"+n+"L-"+a+","+i+"V-"+i+"L0,-"+n+"Z")}},hexagon2:{n:15,f:function(e,t,r){if(ds(t))return hs;var n=ca(e,2),i=ca(e/2,2),a=ca(e*i_/2,2);return vs(t,r,"M-"+i+","+a+"H"+i+"L"+n+",0L"+i+",-"+a+"H-"+i+"L-"+n+",0Z")}},octagon:{n:16,f:function(e,t,r){if(ds(t))return hs;var n=ca(e*.924,2),i=ca(e*.383,2);return vs(t,r,"M-"+i+",-"+n+"H"+i+"L"+n+",-"+i+"V"+i+"L"+i+","+n+"H-"+i+"L-"+n+","+i+"V-"+i+"Z")}},star:{n:17,f:function(e,t,r){if(ds(t))return hs;var n=e*1.4,i=ca(n*.225,2),a=ca(n*.951,2),o=ca(n*.363,2),s=ca(n*.588,2),l=ca(-n,2),u=ca(n*-.309,2),c=ca(n*.118,2),f=ca(n*.809,2),h=ca(n*.382,2);return vs(t,r,"M"+i+","+u+"H"+a+"L"+o+","+c+"L"+s+","+f+"L0,"+h+"L-"+s+","+f+"L-"+o+","+c+"L-"+a+","+u+"H-"+i+"L0,"+l+"Z")}},hexagram:{n:18,f:function(e,t,r){if(ds(t))return hs;var n=ca(e*.66,2),i=ca(e*.38,2),a=ca(e*.76,2);return vs(t,r,"M-"+a+",0l-"+i+",-"+n+"h"+a+"l"+i+",-"+n+"l"+i+","+n+"h"+a+"l-"+i+","+n+"l"+i+","+n+"h-"+a+"l-"+i+","+n+"l-"+i+",-"+n+"h-"+a+"Z")}},"star-triangle-up":{n:19,f:function(e,t,r){if(ds(t))return hs;var n=ca(e*i_*.8,2),i=ca(e*.8,2),a=ca(e*1.6,2),o=ca(e*4,2),s="A "+o+","+o+" 0 0 1 ";return vs(t,r,"M-"+n+","+i+s+n+","+i+s+"0,-"+a+s+"-"+n+","+i+"Z")}},"star-triangle-down":{n:20,f:function(e,t,r){if(ds(t))return hs;var n=ca(e*i_*.8,2),i=ca(e*.8,2),a=ca(e*1.6,2),o=ca(e*4,2),s="A "+o+","+o+" 0 0 1 ";return vs(t,r,"M"+n+",-"+i+s+"-"+n+",-"+i+s+"0,"+a+s+n+",-"+i+"Z")}},"star-square":{n:21,f:function(e,t,r){if(ds(t))return hs;var n=ca(e*1.1,2),i=ca(e*2,2),a="A "+i+","+i+" 0 0 1 ";return 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k=u.append("g").attr("class","outline-controllers");P(k),Z()}if(f&&n.hasText){var E=u.select(".label-temp"),S=Lct(r,n,n.dragmode);Ict(a,"label-temp",S,E)}function L(j){_=+j.srcElement.getAttribute("data-i"),b=+j.srcElement.getAttribute("data-j"),d[_][b].moveFn=x}function x(j,N){if(t.length){var H=p[_][b][1],te=p[_][b][2],oe=t[_],_e=oe.length;if(rP(oe)){var Ee=j,Ce=N;if(n.isActiveSelection){var me=Fue(oe,b);me[1]===oe[b][1]?Ce=0:Ee=0}for(var ie=0;ie<_e;ie++)if(ie!==b){var Se=oe[ie];Se[1]===oe[b][1]&&(Se[1]=H+Ee),Se[2]===oe[b][2]&&(Se[2]=te+Ce)}if(oe[b][1]=H+Ee,oe[b][2]=te+Ce,!rP(oe))for(var Le=0;Le<_e;Le++)for(var Ae=0;Ae1&&!(j.length===2&&j[1][0]==="Z")&&(b===0&&(j[0][0]="M"),t[_]=j,o(),s())}}function g(j,N){if(j===2){_=+N.srcElement.getAttribute("data-i"),b=+N.srcElement.getAttribute("data-j");var H=t[_];!rP(H)&&!JB(H)&&M()}}function P(j){d=[];for(var N=0;N{"use strict";var Fct=Oa(),Wue=qa(),Uue=Dr(),Y3=ho(),zct=u_().readPaths,Oct=nP(),oP=KB(),Xue=Q1().clearOutlineControllers,QB=ka(),tN=So(),qct=vl().arrayEditor,Vue=yv(),Gue=Sg(),qb=gM(),Ep=f_(),eN=Ep.getPathString;Kue.exports={draw:rN,drawOne:Zue,eraseActiveShape:Uct,drawLabel:oP};function rN(e){var t=e._fullLayout;t._shapeUpperLayer.selectAll("path").remove(),t._shapeLowerLayer.selectAll("path").remove(),t._shapeUpperLayer.selectAll("text").remove(),t._shapeLowerLayer.selectAll("text").remove();for(var r in t._plots){var n=t._plots[r].shapelayer;n&&(n.selectAll("path").remove(),n.selectAll("text").remove())}for(var i=0;io&&Nt>s&&!st.shiftKey?Vue.getCursor(Jt/Gt,1-sr/Nt):"move";Gue(t,wr),Se=wr.split("-")[0]}}function 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Se.indexOf(Lr)!==-1},Qt=St("n"),Vt=St("s"),_t=St("w"),It=St("e"),mt=Qt?E+lt:E,er=Vt?S+lt:S,lr=_t?L+st:L,Tr=It?x+st:x;u&&(Qt&&(mt=E-lt),Vt&&(er=S-lt)),(!u&&er-mt>s||u&&mt-er>s)&&(h(C,r[C]=u?mt:Ce(mt)),h(M,r[M]=u?er:Ce(er))),Tr-lr>o&&(h(g,r[g]=l?lr:Ee(lr)),h(P,r[P]=l?Tr:Ee(Tr)))}t.attr("d",eN(e,r)),ut(i,r),oP(e,n,r,z)}function ut(st,lt){(l||u)&&Gt();function Gt(){var Nt=lt.type!=="path",Jt=st.selectAll(".visual-cue").data([0]),sr=1;Jt.enter().append("path").attr({fill:"#fff","fill-rule":"evenodd",stroke:"#000","stroke-width":sr}).classed("visual-cue",!0);var wr=oe(l?lt.xanchor:Uue.midRange(Nt?[lt.x0,lt.x1]:Ep.extractPathCoords(lt.path,qb.paramIsX))),cr=_e(u?lt.yanchor:Uue.midRange(Nt?[lt.y0,lt.y1]:Ep.extractPathCoords(lt.path,qb.paramIsY)));if(wr=Ep.roundPositionForSharpStrokeRendering(wr,sr),cr=Ep.roundPositionForSharpStrokeRendering(cr,sr),l&&u){var $e="M"+(wr-1-sr)+","+(cr-1-sr)+"h-8v2h8 v8h2v-8 h8v-2h-8 v-8h-2 Z";Jt.attr("d",$e)}else if(l){var St="M"+(wr-1-sr)+","+(cr-9-sr)+"v18 h2 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Uct(e){if(sP(e)){Xue(e);var t=e._fullLayout._activeShapeIndex,r=(e.layout||{}).shapes||[];if(t{"use strict";var A0=qa(),Jue=Mc(),$ue=hf(),Pl=XL(),Vct=lP().eraseActiveShape,uP=Dr(),tl=uP._,Il=ace.exports={};Il.toImage={name:"toImage",title:function(e){var t=e._context.toImageButtonOptions||{},r=t.format||"png";return r==="png"?tl(e,"Download plot as a PNG"):tl(e,"Download plot")},icon:Pl.camera,click:function(e){var t=e._context.toImageButtonOptions,r={format:t.format||"png"};uP.notifier(tl(e,"Taking snapshot - this may take a few seconds"),"long"),["filename","width","height","scale"].forEach(function(n){n in t&&(r[n]=t[n])}),A0.call("downloadImage",e,r).then(function(n){uP.notifier(tl(e,"Snapshot succeeded")+" - "+n,"long")}).catch(function(){uP.notifier(tl(e,"Sorry, there was a problem downloading your snapshot!"),"long")})}};Il.sendDataToCloud={name:"sendDataToCloud",title:function(e){return tl(e,"Edit in Chart 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tl(e,"Autoscale")},attr:"zoom",val:"auto",icon:Pl.autoscale,click:Bv};Il.resetScale2d={name:"resetScale2d",_cat:"resetscale",title:function(e){return tl(e,"Reset axes")},attr:"zoom",val:"reset",icon:Pl.home,click:Bv};Il.hoverClosestCartesian={name:"hoverClosestCartesian",_cat:"hoverclosest",title:function(e){return tl(e,"Show closest data on hover")},attr:"hovermode",val:"closest",icon:Pl.tooltip_basic,gravity:"ne",click:Bv};Il.hoverCompareCartesian={name:"hoverCompareCartesian",_cat:"hoverCompare",title:function(e){return tl(e,"Compare data on hover")},attr:"hovermode",val:function(e){return e._fullLayout._isHoriz?"y":"x"},icon:Pl.tooltip_compare,gravity:"ne",click:Bv};function Bv(e,t){var r=t.currentTarget,n=r.getAttribute("data-attr"),i=r.getAttribute("data-val")||!0,a=e._fullLayout,o={},s=$ue.list(e,null,!0),l=a._cartesianSpikesEnabled,u,c;if(n==="zoom"){var f=i==="in"?.5:2,h=(1+f)/2,d=(1-f)/2,v,_;for(c=0;c{"use strict";var oce=aN(),jct=Object.keys(oce),sce=["drawline","drawopenpath","drawclosedpath","drawcircle","drawrect","eraseshape"],lce=["v1hovermode","hoverclosest","hovercompare","togglehover","togglespikelines"].concat(sce),J3=[],Wct=function(e){if(lce.indexOf(e._cat||e.name)===-1){var t=e.name,r=(e._cat||e.name).toLowerCase();J3.indexOf(t)===-1&&J3.push(t),J3.indexOf(r)===-1&&J3.push(r)}};jct.forEach(function(e){Wct(oce[e])});J3.sort();uce.exports={DRAW_MODES:sce,backButtons:lce,foreButtons:J3}});var sN=ye((Nar,cce)=>{"use strict";var Bar=oN();cce.exports={editType:"modebar",orientation:{valType:"enumerated",values:["v","h"],dflt:"h",editType:"modebar"},bgcolor:{valType:"color",editType:"modebar"},color:{valType:"color",editType:"modebar"},activecolor:{valType:"color",editType:"modebar"},uirevision:{valType:"any",editType:"none"},add:{valType:"string",arrayOk:!0,dflt:"",editType:"modebar"},remove:{valType:"string",arrayOk:!0,dflt:"",editType:"modebar"}}});var hce=ye((Uar,fce)=>{"use strict";var Xct=Dr(),yM=ka(),Zct=vl(),Yct=sN();fce.exports=function(t,r){var n=t.modebar||{},i=Zct.newContainer(r,"modebar");function a(s,l){return Xct.coerce(n,i,Yct,s,l)}a("orientation"),a("bgcolor",yM.addOpacity(r.paper_bgcolor,.5));var o=yM.contrast(yM.rgb(r.modebar.bgcolor));a("color",yM.addOpacity(o,.3)),a("activecolor",yM.addOpacity(o,.7)),a("uirevision",r.uirevision),a("add"),a("remove")}});var gce=ye((Var,pce)=>{"use strict";var lN=Oa(),Kct=Eo(),fP=Dr(),dce=XL(),Jct=l6().version,$ct=new DOMParser;function vce(e){this.container=e.container,this.element=document.createElement("div"),this.update(e.graphInfo,e.buttons),this.container.appendChild(this.element)}var Tm=vce.prototype;Tm.update=function(e,t){this.graphInfo=e;var r=this.graphInfo._context,n=this.graphInfo._fullLayout,i="modebar-"+n._uid;this.element.setAttribute("id",i),this.element.setAttribute("role","toolbar"),this._uid=i,this.element.className="modebar modebar--custom",r.displayModeBar==="hover"&&(this.element.className+=" 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t=Math.floor(Math.min(e.b-e.t,e.r-e.l,np)/2);return"M"+(e.l-3.5)+","+(e.t-.5+t)+"h3v"+-t+"h"+t+"v-3h-"+(t+3)+"ZM"+(e.r+3.5)+","+(e.t-.5+t)+"h-3v"+-t+"h"+-t+"v-3h"+(t+3)+"ZM"+(e.r+3.5)+","+(e.b+.5-t)+"h-3v"+t+"h"+-t+"v3h"+(t+3)+"ZM"+(e.l-3.5)+","+(e.b+.5-t)+"h3v"+t+"h"+t+"v3h-"+(t+3)+"Z"}function hhe(e,t,r,n,i){for(var a=!1,o={},s={},l,u,c,f,h=(i||{}).xaHash,d=(i||{}).yaHash,v=0;v{"use strict";var cdt=Oa(),LP=vf(),fdt=yv(),hdt=Sg(),Lg=NN().makeDragBox,gd=hd().DRAGGERSIZE;PP.initInteractions=function(t){var r=t._fullLayout;if(t._context.staticPlot){cdt.select(t).selectAll(".drag").remove();return}if(!(!r._has("cartesian")&&!r._has("splom"))){var n=Object.keys(r._plots||{}).sort(function(a,o){if((r._plots[a].mainplot&&!0)===(r._plots[o].mainplot&&!0)){var s=a.split("y"),l=o.split("y");return s[0]===l[0]?Number(s[1]||1)-Number(l[1]||1):Number(s[0]||1)-Number(l[0]||1)}return r._plots[a].mainplot?1:-1});n.forEach(function(a){var o=r._plots[a],s=o.xaxis,l=o.yaxis;if(!o.mainplot){var u=Lg(t,o,s._offset,l._offset,s._length,l._length,"ns","ew");u.onmousemove=function(h){t._fullLayout._rehover=function(){t._fullLayout._hoversubplot===a&&t._fullLayout._plots[a]&&LP.hover(t,h,a)},LP.hover(t,h,a),t._fullLayout._lasthover=u,t._fullLayout._hoversubplot=a},u.onmouseout=function(h){t._dragging||(t._fullLayout._hoversubplot=null,fdt.unhover(t,h))},t._context.showAxisDragHandles&&(Lg(t,o,s._offset-gd,l._offset-gd,gd,gd,"n","w"),Lg(t,o,s._offset+s._length,l._offset-gd,gd,gd,"n","e"),Lg(t,o,s._offset-gd,l._offset+l._length,gd,gd,"s","w"),Lg(t,o,s._offset+s._length,l._offset+l._length,gd,gd,"s","e"))}if(t._context.showAxisDragHandles){if(a===s._mainSubplot){var c=s._mainLinePosition;s.side==="top"&&(c-=gd),Lg(t,o,s._offset+s._length*.1,c,s._length*.8,gd,"","ew"),Lg(t,o,s._offset,c,s._length*.1,gd,"","w"),Lg(t,o,s._offset+s._length*.9,c,s._length*.1,gd,"","e")}if(a===l._mainSubplot){var f=l._mainLinePosition;l.side!=="right"&&(f-=gd),Lg(t,o,f,l._offset+l._length*.1,gd,l._length*.8,"ns",""),Lg(t,o,f,l._offset+l._length*.9,gd,l._length*.1,"s",""),Lg(t,o,f,l._offset,gd,l._length*.1,"n","")}}});var i=r._hoverlayer.node();i.onmousemove=function(a){a.target=t._fullLayout._lasthover,LP.hover(t,a,r._hoversubplot)},i.onclick=function(a){a.target=t._fullLayout._lasthover,LP.click(t,a)},i.onmousedown=function(a){t._fullLayout._lasthover.onmousedown(a)},PP.updateFx(t)}};PP.updateFx=function(e){var t=e._fullLayout,r=t.dragmode==="pan"?"move":"crosshair";hdt(t._draggers,r)}});var Ehe=ye((Tor,Mhe)=>{"use strict";var She=qa();Mhe.exports=function(t){for(var r=She.layoutArrayContainers,n=She.layoutArrayRegexes,i=t.split("[")[0],a,o,s=0;s{"use strict";var ddt=my(),VN=w6(),NM=G1(),vdt=R6().sorterAsc,GN=qa();UM.containerArrayMatch=Ehe();var pdt=UM.isAddVal=function(t){return t==="add"||ddt(t)},khe=UM.isRemoveVal=function(t){return 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kc=Ub(),U0t=mc().overrideAll,V0t=vl().templatedArray;Gpe.exports=U0t(V0t("annotation",{visible:kc.visible,x:{valType:"any"},y:{valType:"any"},z:{valType:"any"},ax:{valType:"number"},ay:{valType:"number"},xanchor:kc.xanchor,xshift:kc.xshift,yanchor:kc.yanchor,yshift:kc.yshift,text:kc.text,textangle:kc.textangle,font:kc.font,width:kc.width,height:kc.height,opacity:kc.opacity,align:kc.align,valign:kc.valign,bgcolor:kc.bgcolor,bordercolor:kc.bordercolor,borderpad:kc.borderpad,borderwidth:kc.borderwidth,showarrow:kc.showarrow,arrowcolor:kc.arrowcolor,arrowhead:kc.arrowhead,startarrowhead:kc.startarrowhead,arrowside:kc.arrowside,arrowsize:kc.arrowsize,startarrowsize:kc.startarrowsize,arrowwidth:kc.arrowwidth,standoff:kc.standoff,startstandoff:kc.startstandoff,hovertext:kc.hovertext,hoverlabel:kc.hoverlabel,captureevents:kc.captureevents}),"calc","from-root")});var jpe=ye((Rsr,Hpe)=>{"use strict";var BU=Dr(),G0t=ho(),H0t=Yd(),j0t=FU(),W0t=yI();Hpe.exports=function(t,r,n){H0t(t,r,{name:"annotations",handleItemDefaults:X0t,fullLayout:n.fullLayout})};function X0t(e,t,r,n){function i(s,l){return BU.coerce(e,t,W0t,s,l)}function a(s){var l=s+"axis",u={_fullLayout:{}};return u._fullLayout[l]=r[l],G0t.coercePosition(t,u,i,s,s,.5)}var o=i("visible");o&&(j0t(e,t,n.fullLayout,i),a("x"),a("y"),a("z"),BU.noneOrAll(e,t,["x","y","z"]),t.xref="x",t.yref="y",t.zref="z",i("xanchor"),i("yanchor"),i("xshift"),i("yshift"),t.showarrow&&(t.axref="pixel",t.ayref="pixel",i("ax",-10),i("ay",-30),BU.noneOrAll(e,t,["ax","ay"])))}});var Ype=ye((Dsr,Zpe)=>{"use strict";var Wpe=Dr(),Xpe=ho();Zpe.exports=function(t){for(var r=t.fullSceneLayout,n=r.annotations,i=0;i{"use strict";function NU(e,t){var r=[0,0,0,0],n,i;for(n=0;n<4;++n)for(i=0;i<4;++i)r[i]+=e[4*n+i]*t[n];return r}function Y0t(e,t){var r=NU(e.projection,NU(e.view,NU(e.model,[t[0],t[1],t[2],1])));return r}Kpe.exports=Y0t});var $pe=ye((zsr,Jpe)=>{"use strict";var K0t=mI().drawRaw,J0t=UU(),$0t=["x","y","z"];Jpe.exports=function(t){for(var r=t.fullSceneLayout,n=t.dataScale,i=r.annotations,a=0;a1){s=!0;break}}s?t.fullLayout._infolayer.select(".annotation-"+t.id+'[data-index="'+a+'"]').remove():(o._pdata=J0t(t.glplot.cameraParams,[r.xaxis.r2l(o.x)*n[0],r.yaxis.r2l(o.y)*n[1],r.zaxis.r2l(o.z)*n[2]]),K0t(t.graphDiv,o,a,t.id,o._xa,o._ya))}}});var t0e=ye((Osr,e0e)=>{"use strict";var Q0t=qa(),Qpe=Dr();e0e.exports={moduleType:"component",name:"annotations3d",schema:{subplots:{scene:{annotations:yI()}}},layoutAttributes:yI(),handleDefaults:jpe(),includeBasePlot:egt,convert:Ype(),draw:$pe()};function egt(e,t){var r=Q0t.subplotsRegistry.gl3d;if(r)for(var n=r.attrRegex,i=Object.keys(e),a=0;a{"use strict";var r0e=Ub(),i0e=ec(),n0e=pf().line,tgt=Pd().dash,Og=Ao().extendFlat,rgt=vl().templatedArray,qsr=OM(),vT=Gl(),{shapeTexttemplateAttrs:igt,templatefallbackAttrs:ngt}=Ll(),agt=M6();a0e.exports=rgt("shape",{visible:Og({},vT.visible,{editType:"calc+arraydraw"}),showlegend:{valType:"boolean",dflt:!1,editType:"calc+arraydraw"},legend:Og({},vT.legend,{editType:"calc+arraydraw"}),legendgroup:Og({},vT.legendgroup,{editType:"calc+arraydraw"}),legendgrouptitle:{text:Og({},vT.legendgrouptitle.text,{editType:"calc+arraydraw"}),font:i0e({editType:"calc+arraydraw"}),editType:"calc+arraydraw"},legendrank:Og({},vT.legendrank,{editType:"calc+arraydraw"}),legendwidth:Og({},vT.legendwidth,{editType:"calc+arraydraw"}),type:{valType:"enumerated",values:["circle","rect","path","line"],editType:"calc+arraydraw"},layer:{valType:"enumerated",values:["below","above","between"],dflt:"above",editType:"arraydraw"},xref:Og({},r0e.xref,{}),xsizemode:{valType:"enumerated",values:["scaled","pixel"],dflt:"scaled",editType:"calc+arraydraw"},xanchor:{valType:"any",editType:"calc+arraydraw"},x0:{valType:"any",editType:"calc+arraydraw"},x1:{valType:"any",editType:"calc+arraydraw"},x0shift:{valType:"number",dflt:0,min:-1,max:1,editType:"calc"},x1shift:{valType:"number",dflt:0,min:-1,max:1,editType:"calc"},yref:Og({},r0e.yref,{}),ysizemode:{valType:"enumerated",values:["scaled","pixel"],dflt:"scaled",editType:"calc+arraydraw"},yanchor:{valType:"any",editType:"calc+arraydraw"},y0:{valType:"any",editType:"calc+arraydraw"},y1:{valType:"any",editType:"calc+arraydraw"},y0shift:{valType:"number",dflt:0,min:-1,max:1,editType:"calc"},y1shift:{valType:"number",dflt:0,min:-1,max:1,editType:"calc"},path:{valType:"string",editType:"calc+arraydraw"},opacity:{valType:"number",min:0,max:1,dflt:1,editType:"arraydraw"},line:{color:Og({},n0e.color,{editType:"arraydraw"}),width:Og({},n0e.width,{editType:"calc+arraydraw"}),dash:Og({},tgt,{editType:"arraydraw"}),editType:"calc+arraydraw"},fillcolor:{valType:"color",dflt:"rgba(0,0,0,0)",editType:"arraydraw"},fillrule:{valType:"enumerated",values:["evenodd","nonzero"],dflt:"evenodd",editType:"arraydraw"},editable:{valType:"boolean",dflt:!1,editType:"calc+arraydraw"},label:{text:{valType:"string",dflt:"",editType:"arraydraw"},texttemplate:igt({},{keys:Object.keys(agt)}),texttemplatefallback:ngt({editType:"arraydraw"}),font:i0e({editType:"calc+arraydraw",colorEditType:"arraydraw"}),textposition:{valType:"enumerated",values:["top left","top center","top right","middle left","middle center","middle right","bottom left","bottom center","bottom right","start","middle","end"],editType:"arraydraw"},textangle:{valType:"angle",dflt:"auto",editType:"calc+arraydraw"},xanchor:{valType:"enumerated",values:["auto","left","center","right"],dflt:"auto",editType:"calc+arraydraw"},yanchor:{valType:"enumerated",values:["top","middle","bottom"],editType:"calc+arraydraw"},padding:{valType:"number",dflt:3,min:0,editType:"arraydraw"},editType:"arraydraw"},editType:"arraydraw"})});var l0e=ye((Nsr,s0e)=>{"use strict";var o4=Dr(),pT=ho(),ogt=Yd(),sgt=VU(),o0e=f_();s0e.exports=function(t,r){ogt(t,r,{name:"shapes",handleItemDefaults:ugt})};function lgt(e,t){return e?"bottom":t.indexOf("top")!==-1?"top":t.indexOf("bottom")!==-1?"bottom":"middle"}function ugt(e,t,r){function n(H,te){return o4.coerce(e,t,sgt,H,te)}t._isShape=!0;var i=n("visible");if(i){var a=n("showlegend");a&&(n("legend"),n("legendwidth"),n("legendgroup"),n("legendgrouptitle.text"),o4.coerceFont(n,"legendgrouptitle.font"),n("legendrank"));var o=n("path"),s=o?"path":"rect",l=n("type",s),u=l!=="path";u&&delete t.path,n("editable"),n("layer"),n("opacity"),n("fillcolor"),n("fillrule");var c=n("line.width");c&&(n("line.color"),n("line.dash"));for(var f=n("xsizemode"),h=n("ysizemode"),d=["x","y"],v=0;v<2;v++){var _=d[v],b=_+"anchor",p=_==="x"?f:h,k={_fullLayout:r},E,S,L,x=pT.coerceRef(e,t,k,_,void 0,"paper"),C=pT.getRefType(x);if(C==="range"?(E=pT.getFromId(k,x),E._shapeIndices.push(t._index),L=o0e.rangeToShapePosition(E),S=o0e.shapePositionToRange(E),(E.type==="category"||E.type==="multicategory")&&(n(_+"0shift"),n(_+"1shift"))):S=L=o4.identity,u){var M=.25,g=.75,P=_+"0",T=_+"1",z=e[P],O=e[T];e[P]=S(e[P],!0),e[T]=S(e[T],!0),p==="pixel"?(n(P,0),n(T,10)):(pT.coercePosition(t,k,n,x,P,M),pT.coercePosition(t,k,n,x,T,g)),t[P]=L(t[P]),t[T]=L(t[T]),e[P]=z,e[T]=O}if(p==="pixel"){var V=e[b];e[b]=S(e[b],!0),pT.coercePosition(t,k,n,x,b,.25),t[b]=L(t[b]),e[b]=V}}u&&o4.noneOrAll(e,t,["x0","x1","y0","y1"]);var G=l==="line",Z,j;if(u&&(Z=n("label.texttemplate"),n("label.texttemplatefallback")),Z||(j=n("label.text")),j||Z){n("label.textangle");var N=n("label.textposition",G?"middle":"middle center");n("label.xanchor"),n("label.yanchor",lgt(G,N)),n("label.padding"),o4.coerceFont(n,"label.font",r.font)}}}});var f0e=ye((Usr,c0e)=>{"use strict";var cgt=ka(),u0e=Dr();function fgt(e,t){return e?"bottom":t.indexOf("top")!==-1?"top":t.indexOf("bottom")!==-1?"bottom":"middle"}c0e.exports=function(t,r,n){n("newshape.visible"),n("newshape.name"),n("newshape.showlegend"),n("newshape.legend"),n("newshape.legendwidth"),n("newshape.legendgroup"),n("newshape.legendgrouptitle.text"),u0e.coerceFont(n,"newshape.legendgrouptitle.font"),n("newshape.legendrank"),n("newshape.drawdirection"),n("newshape.layer"),n("newshape.fillcolor"),n("newshape.fillrule"),n("newshape.opacity");var i=n("newshape.line.width");if(i){var a=(t||{}).plot_bgcolor||"#FFF";n("newshape.line.color",cgt.contrast(a)),n("newshape.line.dash")}var o=t.dragmode==="drawline",s=n("newshape.label.text"),l=n("newshape.label.texttemplate");if(n("newshape.label.texttemplatefallback"),s||l){n("newshape.label.textangle");var u=n("newshape.label.textposition",o?"middle":"middle center");n("newshape.label.xanchor"),n("newshape.label.yanchor",fgt(o,u)),n("newshape.label.padding"),u0e.coerceFont(n,"newshape.label.font",r.font)}n("activeshape.fillcolor"),n("activeshape.opacity")}});var g0e=ye((Vsr,p0e)=>{"use strict";var GU=Dr(),gT=ho(),mT=gM(),d0e=f_();p0e.exports=function(t){var r=t._fullLayout,n=GU.filterVisible(r.shapes);if(!(!n.length||!t._fullData.length))for(var i=0;i0?u+o:o;return{ppad:o,ppadplus:s?f:h,ppadminus:s?h:f}}else return{ppad:o}}function h0e(e,t,r){var n=e._id.charAt(0)==="x"?"x":"y",i=e.type==="category"||e.type==="multicategory",a,o,s=0,l=0,u=i?e.r2c:e.d2c,c=t[n+"sizemode"]==="scaled";if(c?(a=t[n+"0"],o=t[n+"1"],i&&(s=t[n+"0shift"],l=t[n+"1shift"])):(a=t[n+"anchor"],o=t[n+"anchor"]),a!==void 0)return[u(a)+s,u(o)+l];if(t.path){var f=1/0,h=-1/0,d=t.path.match(mT.segmentRE),v,_,b,p,k;for(e.type==="date"&&(u=d0e.decodeDate(u)),v=0;vh&&(h=k)));if(h>=f)return[f,h]}}});var _0e=ye((Gsr,y0e)=>{"use strict";var m0e=lP();y0e.exports={moduleType:"component",name:"shapes",layoutAttributes:VU(),supplyLayoutDefaults:l0e(),supplyDrawNewShapeDefaults:f0e(),includeBasePlot:qM()("shapes"),calcAutorange:g0e(),draw:m0e.draw,drawOne:m0e.drawOne}});var HU=ye((jsr,b0e)=>{"use strict";var x0e=hd(),vgt=vl().templatedArray,Hsr=OM();b0e.exports=vgt("image",{visible:{valType:"boolean",dflt:!0,editType:"arraydraw"},source:{valType:"string",editType:"arraydraw"},layer:{valType:"enumerated",values:["below","above"],dflt:"above",editType:"arraydraw"},sizex:{valType:"number",dflt:0,editType:"arraydraw"},sizey:{valType:"number",dflt:0,editType:"arraydraw"},sizing:{valType:"enumerated",values:["fill","contain","stretch"],dflt:"contain",editType:"arraydraw"},opacity:{valType:"number",min:0,max:1,dflt:1,editType:"arraydraw"},x:{valType:"any",dflt:0,editType:"arraydraw"},y:{valType:"any",dflt:0,editType:"arraydraw"},xanchor:{valType:"enumerated",values:["left","center","right"],dflt:"left",editType:"arraydraw"},yanchor:{valType:"enumerated",values:["top","middle","bottom"],dflt:"top",editType:"arraydraw"},xref:{valType:"enumerated",values:["paper",x0e.idRegex.x.toString()],dflt:"paper",editType:"arraydraw"},yref:{valType:"enumerated",values:["paper",x0e.idRegex.y.toString()],dflt:"paper",editType:"arraydraw"},editType:"arraydraw"})});var T0e=ye((Wsr,w0e)=>{"use strict";var pgt=Dr(),jU=ho(),ggt=Yd(),mgt=HU(),ygt="images";w0e.exports=function(t,r){var n={name:ygt,handleItemDefaults:_gt};ggt(t,r,n)};function _gt(e,t,r){function n(h,d){return pgt.coerce(e,t,mgt,h,d)}var i=n("source"),a=n("visible",!!i);if(!a)return t;n("layer"),n("xanchor"),n("yanchor"),n("sizex"),n("sizey"),n("sizing"),n("opacity");for(var o={_fullLayout:r},s=["x","y"],l=0;l<2;l++){var u=s[l],c=jU.coerceRef(e,t,o,u,"paper",void 0);if(c!=="paper"){var f=jU.getFromId(o,c);f._imgIndices.push(t._index)}jU.coercePosition(t,o,n,c,u,0)}return t}});var E0e=ye((Xsr,M0e)=>{"use strict";var A0e=Oa(),xgt=So(),yT=ho(),S0e=hf(),bgt=Wp();M0e.exports=function(t){var r=t._fullLayout,n=[],i={},a=[],o,s;for(s=0;s{"use strict";var k0e=Eo(),wgt=m6();C0e.exports=function(t,r,n,i){r=r||{};var a=n==="log"&&r.type==="linear",o=n==="linear"&&r.type==="log";if(a||o){for(var s=t._fullLayout.images,l=r._id.charAt(0),u,c,f=0;f{"use 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"},minWidth:30,minHeight:30,textPadX:24,arrowPadX:16,rx:2,ry:2,textOffsetX:12,textOffsetY:3,arrowOffsetX:4,gapButtonHeader:5,gapButton:2,activeColor:"#F4FAFF",hoverColor:"#F4FAFF",arrowSymbol:{left:"\u25C4",right:"\u25BA",up:"\u25B2",down:"\u25BC"}}});var WU=ye((Jsr,F0e)=>{"use strict";var Tgt=ec(),Agt=Lh(),Sgt=Ao().extendFlat,Mgt=mc().overrideAll,Egt=E6(),D0e=vl().templatedArray,kgt=D0e("button",{visible:{valType:"boolean"},method:{valType:"enumerated",values:["restyle","relayout","animate","update","skip"],dflt:"restyle"},args:{valType:"info_array",freeLength:!0,items:[{valType:"any"},{valType:"any"},{valType:"any"}]},args2:{valType:"info_array",freeLength:!0,items:[{valType:"any"},{valType:"any"},{valType:"any"}]},label:{valType:"string",dflt:""},execute:{valType:"boolean",dflt:!0}});F0e.exports=Mgt(D0e("updatemenu",{_arrayAttrRegexps:[/^updatemenus\[(0|[1-9][0-9]+)\]\.buttons/],visible:{valType:"boolean"},type:{valType:"enumerated",values:["dropdown","buttons"],dflt:"dropdown"},direction:{valType:"enumerated",values:["left","right","up","down"],dflt:"down"},active:{valType:"integer",min:-1,dflt:0},showactive:{valType:"boolean",dflt:!0},buttons:kgt,x:{valType:"number",min:-2,max:3,dflt:-.05},xanchor:{valType:"enumerated",values:["auto","left","center","right"],dflt:"right"},y:{valType:"number",min:-2,max:3,dflt:1},yanchor:{valType:"enumerated",values:["auto","top","middle","bottom"],dflt:"top"},pad:Sgt(Egt({editType:"arraydraw"}),{}),font:Tgt({}),bgcolor:{valType:"color"},bordercolor:{valType:"color",dflt:Agt.borderLine},borderwidth:{valType:"number",min:0,dflt:1,editType:"arraydraw"}}),"arraydraw","from-root")});var B0e=ye(($sr,q0e)=>{"use strict";var xI=Dr(),z0e=Yd(),O0e=WU(),Cgt=_I(),Lgt=Cgt.name,Pgt=O0e.buttons;q0e.exports=function(t,r){var n={name:Lgt,handleItemDefaults:Igt};z0e(t,r,n)};function Igt(e,t,r){function n(o,s){return xI.coerce(e,t,O0e,o,s)}var i=z0e(e,t,{name:"buttons",handleItemDefaults:Rgt}),a=n("visible",i.length>0);a&&(n("active"),n("direction"),n("type"),n("showactive"),n("x"),n("y"),xI.noneOrAll(e,t,["x","y"]),n("xanchor"),n("yanchor"),n("pad.t"),n("pad.r"),n("pad.b"),n("pad.l"),xI.coerceFont(n,"font",r.font),n("bgcolor",r.paper_bgcolor),n("bordercolor"),n("borderwidth"))}function Rgt(e,t){function r(i,a){return xI.coerce(e,t,Pgt,i,a)}var n=r("visible",e.method==="skip"||Array.isArray(e.args));n&&(r("method"),r("args"),r("args2"),r("label"),r("execute"))}});var V0e=ye((Qsr,U0e)=>{"use strict";U0e.exports=Mf;var qg=Oa(),N0e=ka(),_T=So(),bI=Dr();function Mf(e,t,r){this.gd=e,this.container=t,this.id=r,this.position=null,this.translateX=null,this.translateY=null,this.hbar=null,this.vbar=null,this.bg=this.container.selectAll("rect.scrollbox-bg").data([0]),this.bg.exit().on(".drag",null).on("wheel",null).remove(),this.bg.enter().append("rect").classed("scrollbox-bg",!0).style("pointer-events","all").attr({opacity:0,x:0,y:0,width:0,height:0})}Mf.barWidth=2;Mf.barLength=20;Mf.barRadius=2;Mf.barPad=1;Mf.barColor="#808BA4";Mf.prototype.enable=function(t,r,n){var i=this.gd._fullLayout,a=i.width,o=i.height;this.position=t;var s=this.position.l,l=this.position.w,u=this.position.t,c=this.position.h,f=this.position.direction,h=f==="down",d=f==="left",v=f==="right",_=f==="up",b=l,p=c,k,E,S,L;!h&&!d&&!v&&!_&&(this.position.direction="down",h=!0);var x=h||_;x?(k=s,E=k+b,h?(S=u,L=Math.min(S+p,o),p=L-S):(L=u+p,S=Math.max(L-p,0),p=L-S)):(S=u,L=S+p,d?(E=s+b,k=Math.max(E-b,0),b=E-k):(k=s,E=Math.min(k+b,a),b=E-k)),this._box={l:k,t:S,w:b,h:p};var C=l>b,M=Mf.barLength+2*Mf.barPad,g=Mf.barWidth+2*Mf.barPad,P=s,T=u+c;T+g>o&&(T=o-g);var z=this.container.selectAll("rect.scrollbar-horizontal").data(C?[0]:[]);z.exit().on(".drag",null).remove(),z.enter().append("rect").classed("scrollbar-horizontal",!0).call(N0e.fill,Mf.barColor),C?(this.hbar=z.attr({rx:Mf.barRadius,ry:Mf.barRadius,x:P,y:T,width:M,height:g}),this._hbarXMin=P+M/2,this._hbarTranslateMax=b-M):(delete this.hbar,delete this._hbarXMin,delete this._hbarTranslateMax);var O=c>p,V=Mf.barWidth+2*Mf.barPad,G=Mf.barLength+2*Mf.barPad,Z=s+l,j=u;Z+V>a&&(Z=a-V);var N=this.container.selectAll("rect.scrollbar-vertical").data(O?[0]:[]);N.exit().on(".drag",null).remove(),N.enter().append("rect").classed("scrollbar-vertical",!0).call(N0e.fill,Mf.barColor),O?(this.vbar=N.attr({rx:Mf.barRadius,ry:Mf.barRadius,x:Z,y:j,width:V,height:G}),this._vbarYMin=j+G/2,this._vbarTranslateMax=p-G):(delete this.vbar,delete this._vbarYMin,delete this._vbarTranslateMax);var H=this.id,te=k-.5,oe=O?E+V+.5:E+.5,_e=S-.5,Ee=C?L+g+.5:L+.5,Ce=i._topdefs.selectAll("#"+H).data(C||O?[0]:[]);if(Ce.exit().remove(),Ce.enter().append("clipPath").attr("id",H).append("rect"),C||O?(this._clipRect=Ce.select("rect").attr({x:Math.floor(te),y:Math.floor(_e),width:Math.ceil(oe)-Math.floor(te),height:Math.ceil(Ee)-Math.floor(_e)}),this.container.call(_T.setClipUrl,H,this.gd),this.bg.attr({x:s,y:u,width:l,height:c})):(this.bg.attr({width:0,height:0}),this.container.on("wheel",null).on(".drag",null).call(_T.setClipUrl,null),delete this._clipRect),C||O){var me=qg.behavior.drag().on("dragstart",function(){qg.event.sourceEvent.preventDefault()}).on("drag",this._onBoxDrag.bind(this));this.container.on("wheel",null).on("wheel",this._onBoxWheel.bind(this)).on(".drag",null).call(me);var ie=qg.behavior.drag().on("dragstart",function(){qg.event.sourceEvent.preventDefault(),qg.event.sourceEvent.stopPropagation()}).on("drag",this._onBarDrag.bind(this));C&&this.hbar.on(".drag",null).call(ie),O&&this.vbar.on(".drag",null).call(ie)}this.setTranslate(r,n)};Mf.prototype.disable=function(){(this.hbar||this.vbar)&&(this.bg.attr({width:0,height:0}),this.container.on("wheel",null).on(".drag",null).call(_T.setClipUrl,null),delete this._clipRect),this.hbar&&(this.hbar.on(".drag",null),this.hbar.remove(),delete this.hbar,delete this._hbarXMin,delete this._hbarTranslateMax),this.vbar&&(this.vbar.on(".drag",null),this.vbar.remove(),delete this.vbar,delete this._vbarYMin,delete this._vbarTranslateMax)};Mf.prototype._onBoxDrag=function(){var t=this.translateX,r=this.translateY;this.hbar&&(t-=qg.event.dx),this.vbar&&(r-=qg.event.dy),this.setTranslate(t,r)};Mf.prototype._onBoxWheel=function(){var t=this.translateX,r=this.translateY;this.hbar&&(t+=qg.event.deltaY),this.vbar&&(r+=qg.event.deltaY),this.setTranslate(t,r)};Mf.prototype._onBarDrag=function(){var t=this.translateX,r=this.translateY;if(this.hbar){var n=t+this._hbarXMin,i=n+this._hbarTranslateMax,a=bI.constrain(qg.event.x,n,i),o=(a-n)/(i-n),s=this.position.w-this._box.w;t=o*s}if(this.vbar){var l=r+this._vbarYMin,u=l+this._vbarTranslateMax,c=bI.constrain(qg.event.y,l,u),f=(c-l)/(u-l),h=this.position.h-this._box.h;r=f*h}this.setTranslate(t,r)};Mf.prototype.setTranslate=function(t,r){var n=this.position.w-this._box.w,i=this.position.h-this._box.h;if(t=bI.constrain(t||0,0,n),r=bI.constrain(r||0,0,i),this.translateX=t,this.translateY=r,this.container.call(_T.setTranslate,this._box.l-this.position.l-t,this._box.t-this.position.t-r),this._clipRect&&this._clipRect.attr({x:Math.floor(this.position.l+t-.5),y:Math.floor(this.position.t+r-.5)}),this.hbar){var 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lge=ye((nlr,sge)=>{"use strict";var wT=Dr(),age=Yd(),oge=KU(),Ygt=c4(),Kgt=Ygt.name,Jgt=oge.steps;sge.exports=function(t,r){age(t,r,{name:Kgt,handleItemDefaults:$gt})};function $gt(e,t,r){function n(f,h){return wT.coerce(e,t,oge,f,h)}for(var i=age(e,t,{name:"steps",handleItemDefaults:Qgt}),a=0,o=0;o{"use strict";var Bg=Oa(),TI=Mc(),__=ka(),Ng=So(),t0=Dr(),emt=t0.strTranslate,f4=ru(),tmt=vl().arrayEditor,Rs=c4(),QU=$h(),fge=QU.LINE_SPACING,JU=QU.FROM_TL,$U=QU.FROM_BR;mge.exports=function(t){var r=t._context.staticPlot,n=t._fullLayout,i=rmt(n,t),a=n._infolayer.selectAll("g."+Rs.containerClassName).data(i.length>0?[0]:[]);a.enter().append("g").classed(Rs.containerClassName,!0).style("cursor",r?null:"ew-resize");function o(c){c._commandObserver&&(c._commandObserver.remove(),delete c._commandObserver),TI.autoMargin(t,hge(c))}if(a.exit().each(function(){Bg.select(this).selectAll("g."+Rs.groupClassName).each(o)}).remove(),i.length!==0){var 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r=t._dims,n=r.inputAreaLength-Rs.railInset*2,i=t0.ensureSingle(e,"rect",Rs.railRectClass);i.attr({width:n,height:Rs.railWidth,rx:Rs.railRadius,ry:Rs.railRadius,"shape-rendering":"crispEdges"}).call(__.stroke,t.bordercolor).call(__.fill,t.bgcolor).style("stroke-width",t.borderwidth+"px"),Ng.setTranslate(i,Rs.railInset,(r.inputAreaWidth-Rs.railWidth)*.5+r.currentValueTotalHeight)}});var xge=ye((olr,_ge)=>{"use strict";var hmt=c4();_ge.exports={moduleType:"component",name:hmt.name,layoutAttributes:KU(),supplyLayoutDefaults:lge(),draw:yge()}});var SI=ye((slr,wge)=>{"use strict";var bge=Lh();wge.exports={bgcolor:{valType:"color",dflt:bge.background,editType:"plot"},bordercolor:{valType:"color",dflt:bge.defaultLine,editType:"plot"},borderwidth:{valType:"integer",dflt:0,min:0,editType:"plot"},autorange:{valType:"boolean",dflt:!0,editType:"calc",impliedEdits:{"range[0]":void 0,"range[1]":void 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dmt=hf(),vmt=ru(),Sge=MI(),pmt=$h().LINE_SPACING,EI=Sge.name;function Mge(e){var t=e&&e[EI];return t&&t.visible}kI.isVisible=Mge;kI.makeData=function(e){for(var t=dmt.list({_fullLayout:e},"x",!0),r=e.margin,n=[],i=0;i{"use strict";var CI=Dr(),kge=vl(),Cge=hf(),gmt=SI(),mmt=tV();Lge.exports=function(t,r,n){var i=t[n],a=r[n];if(!(i.rangeslider||r._requestRangeslider[a._id]))return;CI.isPlainObject(i.rangeslider)||(i.rangeslider={});var o=i.rangeslider,s=kge.newContainer(a,"rangeslider");function l(L,x){return CI.coerce(o,s,gmt,L,x)}var u,c;function f(L,x){return CI.coerce(u,c,mmt,L,x)}var h=l("visible");if(h){l("bgcolor",r.plot_bgcolor),l("bordercolor"),l("borderwidth"),l("thickness"),l("autorange",!a.isValidRange(o.range)),l("range");var d=r._subplots;if(d)for(var v=d.cartesian.filter(function(L){return L.slice(0,Math.max(0,L.indexOf("y")))===Cge.name2id(n)}).map(function(L){return L.slice(L.indexOf("y"),L.length)}),_=CI.simpleMap(v,Cge.id2name),b=0;b<_.length;b++){var 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Nmt=ec(),Nge=Lh(),Umt=vl().templatedArray,Vmt=Umt("button",{visible:{valType:"boolean",dflt:!0,editType:"plot"},step:{valType:"enumerated",values:["month","year","day","hour","minute","second","all"],dflt:"month",editType:"plot"},stepmode:{valType:"enumerated",values:["backward","todate"],dflt:"backward",editType:"plot"},count:{valType:"number",min:0,dflt:1,editType:"plot"},label:{valType:"string",editType:"plot"},editType:"plot"});Uge.exports={visible:{valType:"boolean",editType:"plot"},buttons:Vmt,x:{valType:"number",min:-2,max:3,editType:"plot"},xanchor:{valType:"enumerated",values:["auto","left","center","right"],dflt:"left",editType:"plot"},y:{valType:"number",min:-2,max:3,editType:"plot"},yanchor:{valType:"enumerated",values:["auto","top","middle","bottom"],dflt:"bottom",editType:"plot"},font:Nmt({editType:"plot"}),bgcolor:{valType:"color",dflt:Nge.lightLine,editType:"plot"},activecolor:{valType:"color",editType:"plot"},bordercolor:{valType:"color",dflt:Nge.defaultLine,editType:"plot"},borderwidth:{valType:"number",min:0,dflt:0,editType:"plot"},editType:"plot"}});var nV=ye((glr,Vge)=>{"use strict";Vge.exports={yPad:.02,minButtonWidth:30,rx:3,ry:3,lightAmount:25,darkAmount:10}});var jge=ye((mlr,Hge)=>{"use strict";var RI=Dr(),Gmt=ka(),Hmt=vl(),jmt=Yd(),Gge=II(),aV=nV();Hge.exports=function(t,r,n,i,a){var o=t.rangeselector||{},s=Hmt.newContainer(r,"rangeselector");function l(d,v){return RI.coerce(o,s,Gge,d,v)}var u=jmt(o,s,{name:"buttons",handleItemDefaults:Wmt,calendar:a}),c=l("visible",u.length>0);if(c){var f=Xmt(r,n,i);l("x",f[0]),l("y",f[1]),RI.noneOrAll(t,r,["x","y"]),l("xanchor"),l("yanchor"),RI.coerceFont(l,"font",n.font);var h=l("bgcolor");l("activecolor",Gmt.contrast(h,aV.lightAmount,aV.darkAmount)),l("bordercolor"),l("borderwidth")}};function Wmt(e,t,r,n){var i=n.calendar;function a(l,u){return RI.coerce(e,t,Gge.buttons,l,u)}var o=a("visible");if(o){var s=a("step");s!=="all"&&(i&&i!=="gregorian"&&(s==="month"||s==="year")?t.stepmode="backward":a("stepmode"),a("count")),a("label")}}function Xmt(e,t,r){for(var n=r.filter(function(s){return 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i="error_"+n.axis,a=gyt.newContainer(t,i),o=e[i]||{};function s(v,_){return pyt.coerce(o,a,myt,v,_)}var l=o.array!==void 0||o.value!==void 0||o.type==="sqrt",u=s("visible",l);if(u!==!1){var c=s("type","array"in o?"data":"percent"),f=!0;c!=="sqrt"&&(f=s("symmetric",!((c==="data"?"arrayminus":"valueminus")in o))),c==="data"?(s("array"),s("traceref"),f||(s("arrayminus"),s("tracerefminus"))):(c==="percent"||c==="constant")&&(s("value"),f||s("valueminus"));var h="copy_"+n.inherit+"style";if(n.inherit){var d=t["error_"+n.inherit];(d||{}).visible&&s(h,!(o.color||cme(o.thickness)||cme(o.width)))}(!n.inherit||!a[h])&&(s("color",r),s("thickness"),s("width",vyt.traceIs(t,"gl3d")?0:4))}}});var dV=ye((Slr,vme)=>{"use strict";vme.exports=function(t){var r=t.type,n=t.symmetric;if(r==="data"){var i=t.array||[];if(n)return function(u,c){var f=+i[c];return[f,f]};var a=t.arrayminus||[];return function(u,c){var f=+i[c],h=+a[c];return!isNaN(f)||!isNaN(h)?[h||0,f||0]:[NaN,NaN]}}else{var o=dme(r,t.value),s=dme(r,t.valueminus);return n||t.valueminus===void 0?function(u){var c=o(u);return[c,c]}:function(u){return[s(u),o(u)]}}};function dme(e,t){if(e==="percent")return function(r){return Math.abs(r*t/100)};if(e==="constant")return function(){return Math.abs(t)};if(e==="sqrt")return function(r){return Math.sqrt(Math.abs(r))}}});var mme=ye((Mlr,gme)=>{"use strict";var vV=Eo(),yyt=qa(),pV=ho(),_yt=Dr(),xyt=dV();gme.exports=function(t){for(var r=t.calcdata,n=0;n{"use strict";var yme=Oa(),b_=Eo(),byt=So(),wyt=Ru();_me.exports=function(t,r,n,i){var a,o=n.xaxis,s=n.yaxis,l=i&&i.duration>0,u=t._context.staticPlot;r.each(function(c){var f=c[0].trace,h=f.error_x||{},d=f.error_y||{},v;f.ids&&(v=function(k){return k.id});var _=wyt.hasMarkers(f)&&f.marker.maxdisplayed>0;!d.visible&&!h.visible&&(c=[]);var b=yme.select(this).selectAll("g.errorbar").data(c,v);if(b.exit().remove(),!!c.length){h.visible||b.selectAll("path.xerror").remove(),d.visible||b.selectAll("path.yerror").remove(),b.style("opacity",1);var p=b.enter().append("g").classed("errorbar",!0);l&&p.style("opacity",0).transition().duration(i.duration).style("opacity",1),byt.setClipUrl(b,n.layerClipId,t),b.each(function(k){var E=yme.select(this),S=Tyt(k,o,s);if(!(_&&!k.vis)){var L,x=E.select("path.yerror");if(d.visible&&b_(S.x)&&b_(S.yh)&&b_(S.ys)){var C=d.width;L="M"+(S.x-C)+","+S.yh+"h"+2*C+"m-"+C+",0V"+S.ys,S.noYS||(L+="m-"+C+",0h"+2*C),a=!x.size(),a?x=E.append("path").style("vector-effect",u?"none":"non-scaling-stroke").classed("yerror",!0):l&&(x=x.transition().duration(i.duration).ease(i.easing)),x.attr("d",L)}else x.remove();var M=E.select("path.xerror");if(h.visible&&b_(S.y)&&b_(S.xh)&&b_(S.xs)){var g=(h.copy_ystyle?d:h).width;L="M"+S.xh+","+(S.y-g)+"v"+2*g+"m0,-"+g+"H"+S.xs,S.noXS||(L+="m0,-"+g+"v"+2*g),a=!M.size(),a?M=E.append("path").style("vector-effect",u?"none":"non-scaling-stroke").classed("xerror",!0):l&&(M=M.transition().duration(i.duration).ease(i.easing)),M.attr("d",L)}else M.remove()}})}})};function Tyt(e,t,r){var n={x:t.c2p(e.x),y:r.c2p(e.y)};return e.yh!==void 0&&(n.yh=r.c2p(e.yh),n.ys=r.c2p(e.ys),b_(n.ys)||(n.noYS=!0,n.ys=r.c2p(e.ys,!0))),e.xh!==void 0&&(n.xh=t.c2p(e.xh),n.xs=t.c2p(e.xs),b_(n.xs)||(n.noXS=!0,n.xs=t.c2p(e.xs,!0))),n}});var Tme=ye((klr,wme)=>{"use strict";var Ayt=Oa(),bme=ka();wme.exports=function(t){t.each(function(r){var n=r[0].trace,i=n.error_y||{},a=n.error_x||{},o=Ayt.select(this);o.selectAll("path.yerror").style("stroke-width",i.thickness+"px").call(bme.stroke,i.color),a.copy_ystyle&&(a=i),o.selectAll("path.xerror").style("stroke-width",a.thickness+"px").call(bme.stroke,a.color)})}});var Mme=ye((Clr,Sme)=>{"use strict";var h4=Dr(),Ame=mc().overrideAll,d4=hV(),Qb={error_x:h4.extendFlat({},d4),error_y:h4.extendFlat({},d4)};delete Qb.error_x.copy_zstyle;delete Qb.error_y.copy_zstyle;delete Qb.error_y.copy_ystyle;var v4={error_x:h4.extendFlat({},d4),error_y:h4.extendFlat({},d4),error_z:h4.extendFlat({},d4)};delete v4.error_x.copy_ystyle;delete v4.error_y.copy_ystyle;delete v4.error_z.copy_ystyle;delete v4.error_z.copy_zstyle;Sme.exports={moduleType:"component",name:"errorbars",schema:{traces:{scatter:Qb,bar:Qb,histogram:Qb,scatter3d:Ame(v4,"calc","nested"),scattergl:Ame(Qb,"calc","nested")}},supplyDefaults:hme(),calc:mme(),makeComputeError:dV(),plot:xme(),style:Tme(),hoverInfo:Syt};function Syt(e,t,r){(t.error_y||{}).visible&&(r.yerr=e.yh-e.y,t.error_y.symmetric||(r.yerrneg=e.y-e.ys)),(t.error_x||{}).visible&&(r.xerr=e.xh-e.x,t.error_x.symmetric||(r.xerrneg=e.x-e.xs))}});var kme=ye((Llr,Eme)=>{"use 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lt&&(M==="right"&&(Le.domain[0]+=(lt+ut/2)/S.w),cr.attr("transform",Vg(St[0],St[1])),Le.setScale())}e.selectAll("."+gf.cbfills+",."+gf.cblines).attr("transform",n?Vg(0,Math.round(S.h*(1-Le.domain[1]))):Vg(Math.round(S.w*Le.domain[0]),0)),pt.attr("transform",n?Vg(0,Math.round(-S.t)):Vg(Math.round(-S.l),0));var mt=e.select("."+gf.cbfills).selectAll("rect."+gf.cbfill).attr("style","").data(V);mt.enter().append("rect").classed(gf.cbfill,!0).attr("style",""),mt.exit().remove();var er=g.map(Le.c2p).map(Math.round).sort(function(Br,Vr){return Br-Vr});mt.each(function(Br,Vr){var dt=[Vr===0?g[0]:(V[Vr]+V[Vr-1])/2,Vr===V.length-1?g[1]:(V[Vr]+V[Vr+1])/2].map(Le.c2p).map(Math.round);n&&(dt[1]=B0.constrain(dt[1]+(dt[1]>dt[0])?1:-1,er[0],er[1]));var 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Dy.drawTicks(r,Le,{vals:Le.ticks==="inside"?Dy.clipEnds(Le,Lr):Lr,layer:pt,path:Dy.makeTickPath(Le,Tr,ti),transFn:Dy.makeTransTickFn(Le)}),Dy.drawLabels(r,Le,{vals:Lr,layer:pt,transFn:Dy.makeTransTickLabelFn(Le),labelFns:Dy.makeLabelFns(Le,Tr)})}function wr(){var cr,$e=Z+l/2;Ze.indexOf("inside")===-1&&(cr=Ug.bBox(pt.node()),$e+=n?cr.width:cr.height),Zt=ce.select("text");var St=0,Qt=n&&M==="top",Vt=!n&&M==="right",_t=0;if(Zt.node()&&!Zt.classed(gf.jsPlaceholder)){var It,mt=ce.select(".h"+Le._id+"title-math-group").node();mt&&(n&&Ae||!n&&!Ae)?(cr=Ug.bBox(mt),St=cr.width,It=cr.height):(cr=Ug.bBox(ce.node()),St=cr.right-S.l-(n?_e:Se),It=cr.bottom-S.t-(n?Se:_e),!n&&M==="top"&&($e+=cr.height,_t=cr.height)),Vt&&(Zt.attr("transform",Vg(St/2+ut/2,0)),St*=2),$e=Math.max($e,n?St:It)}var er=(n?d:v)*2+$e+u+l/2,lr=0;!n&&C.text&&h==="bottom"&&b<=0&&(lr=er/2,er+=lr,_t+=lr),E._hColorbarMoveTitle=lr,E._hColorbarMoveCBTitle=_t;var 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b4=ye((aur,f1e)=>{"use strict";f1e.exports={boxmode:{valType:"enumerated",values:["group","overlay"],dflt:"overlay",editType:"calc"},boxgap:{valType:"number",min:0,max:1,dflt:.3,editType:"calc"},boxgroupgap:{valType:"number",min:0,max:1,dflt:.3,editType:"calc"}}});var T4=ye((our,p1e)=>{"use strict";var V0=Dr(),f_t=qa(),h_t=ka(),d_t=Ig(),v_t=Hb(),h1e=R3(),w4=x4();function p_t(e,t,r,n){function i(v,_){return V0.coerce(e,t,w4,v,_)}if(d1e(e,t,i,n),t.visible!==!1){d_t(e,t,n,i),i("xhoverformat"),i("yhoverformat");var a=t._hasPreCompStats;a&&(i("lowerfence"),i("upperfence")),i("line.color",(e.marker||{}).color||r),i("line.width"),i("fillcolor",h_t.addOpacity(t.line.color,.5));var o=!1;if(a){var s=i("mean"),l=i("sd");s&&s.length&&(o=!0,l&&l.length&&(o="sd"))}i("whiskerwidth");var u=i("sizemode"),c;u==="quartiles"&&(c=i("boxmean",o)),i("showwhiskers",u==="quartiles"),(u==="sd"||c==="sd")&&i("sdmultiple"),i("width"),i("quartilemethod");var f=!1;if(a){var h=i("notchspan");h&&h.length&&(f=!0)}else 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s=r.makeCalcdata(e,t),l=b_t(e,r,t,s).vals;return[l,s]}var u;a?u=e[t+"0"]:"name"in e&&(r.type==="category"||IV(e.name)&&["linear","log"].indexOf(r.type)!==-1||gh.isDateTime(e.name)&&r.type==="date")?u=e.name:u=n;for(var c=r.type==="multicategory"?r.r2c_just_indices(u):r.d2c(u,0,e[t+"calendar"]),f=e._length,h=new Array(f),d=0;d{"use strict";var E1e=ho(),M_t=Dr(),E_t=Nb().getAxisGroup,k1e=["v","h"];function k_t(e,t){for(var r=e.calcdata,n=t.xaxis,i=t.yaxis,a=0;a1,k=1-a[e+"gap"],E=1-a[e+"groupgap"];for(l=0;l0;if(C==="positive"?(N=M*(x?1:.5),oe=te,H=oe=P):C==="negative"?(N=oe=P,H=M*(x?1:.5),_e=te):(N=H=M,oe=_e=te),Le){var Ae=S.pointpos,Fe=S.jitter,Pe=S.marker.size/2,ge=0;Ae+Fe>=0&&(ge=te*(Ae+Fe),ge>N?(Se=!0,me=Pe,Ee=ge):ge>oe&&(me=Pe,Ee=N)),ge<=N&&(Ee=N);var Re=0;Ae-Fe<=0&&(Re=-te*(Ae-Fe),Re>H?(Se=!0,ie=Pe,Ce=Re):Re>_e&&(ie=Pe,Ce=H)),Re<=H&&(Ce=H)}else Ee=N,Ce=H;var ce=new Array(c.length);for(u=0;u{"use strict";var LT=Oa(),a2=Dr(),C_t=So(),P1e=5,L_t=.01;function P_t(e,t,r,n){var 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n2e=ye((Icr,i2e)=>{"use strict";var t2e=Dr(),d2t=Sm(),BT=Ru(),v2t=$p(),p2t=R0(),r2e=tT(),g2t=D0(),m2t=Rg(),y2t=kG();i2e.exports=function(t,r,n,i){function a(h,d){return t2e.coerce(t,r,y2t,h,d)}var o=a("a"),s=a("b"),l=a("c"),u;if(o?(u=o.length,s?(u=Math.min(u,s.length),l&&(u=Math.min(u,l.length))):l?u=Math.min(u,l.length):u=0):s&&l&&(u=Math.min(s.length,l.length)),!u){r.visible=!1;return}r._length=u,a("sum"),a("text"),a("hovertext"),r.hoveron!=="fills"&&(a("hovertemplate"),a("hovertemplatefallback"));var c=u{"use strict";var CG=ho();a2e.exports=function(t,r,n){var i={},a=n[r.subplot]._subplot;return i.aLabel=CG.tickText(a.aaxis,t.a,!0).text,i.bLabel=CG.tickText(a.baxis,t.b,!0).text,i.cLabel=CG.tickText(a.caxis,t.c,!0).text,i}});var c2e=ye((Dcr,u2e)=>{"use strict";var LG=Eo(),_2t=F0(),x2t=km(),b2t=z0(),w2t=O0().calcMarkerSize,s2e=["a","b","c"],l2e={a:["b","c"],b:["a","c"],c:["a","b"]};u2e.exports=function(t,r){var n=t._fullLayout[r.subplot],i=n.sum,a=r.sum||i,o={a:r.a,b:r.b,c:r.c},s=r.ids,l,u,c,f,h,d;for(l=0;l{"use strict";var T2t=sT();f2e.exports=function(t,r,n){var i=r.plotContainer;i.select(".scatterlayer").selectAll("*").remove();for(var a=r.xaxis,o=r.yaxis,s={xaxis:a,yaxis:o,plot:i,layerClipId:r._hasClipOnAxisFalse?r.clipIdRelative:null},l=r.layers.frontplot.select("g.scatterlayer"),u=0;u{"use strict";var A2t=fT();d2e.exports=function(t,r,n,i){var a=A2t(t,r,n,i);if(!a||a[0].index===!1)return;var o=a[0];if(o.index===void 0){var s=1-o.y0/t.ya._length,l=t.xa._length,u=l*s/2,c=l-u;return o.x0=Math.max(Math.min(o.x0,c),u),o.x1=Math.max(Math.min(o.x1,c),u),a}var f=o.cd[o.index],h=o.trace,d=o.subplot;o.a=f.a,o.b=f.b,o.c=f.c,o.xLabelVal=void 0,o.yLabelVal=void 0;var v={};v[h.subplot]={_subplot:d};var _=h._module.formatLabels(f,h,v);o.aLabel=_.aLabel,o.bLabel=_.bLabel,o.cLabel=_.cLabel;var b=f.hi||h.hoverinfo,p=[];function k(S,L){p.push(S._hovertitle+": "+L)}if(!h.hovertemplate){var 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C=r.caxis=IG({},e.caxis,{range:[c-f-h,d],side:"right",tickangle:(+e.caxis.tickangle||0)+30,domain:[S,S+E*NT],anchor:"free",position:0,_id:"y",_length:b});z4(C,r.graphDiv._fullLayout),C.setScale();var M="M"+v+","+(_+p)+"h"+b+"l-"+b/2+",-"+p+"Z";r.clipDef.select("path").attr("d",M),r.layers.plotbg.select("path").attr("d",M);var g="M0,"+p+"h"+b+"l-"+b/2+",-"+p+"Z";r.clipDefRelative.select("path").attr("d",g);var P=Fm(v,_);r.plotContainer.selectAll(".scatterlayer,.maplayer").attr("transform",P),r.clipDefRelative.select("path").attr("transform",null);var T=Fm(v-x._offset,_+p);r.layers.baxis.attr("transform",T),r.layers.bgrid.attr("transform",T);var z=Fm(v+b/2,_)+"rotate(30)"+Fm(0,-L._offset);r.layers.aaxis.attr("transform",z),r.layers.agrid.attr("transform",z);var 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n=r||q4.select(e).selectAll('g[class^="funnellayer"]').selectAll("g.trace");Hwt(e,n,"funnel"),n.style("opacity",function(i){return i[0].trace.opacity}),n.each(function(i){var a=q4.select(this),o=i[0].trace;a.selectAll(".point > path").each(function(s){if(!s.isBlank){var l=o.marker;q4.select(this).call(QG.fill,s.mc||l.color).call(QG.stroke,s.mlc||l.line.color).call(qwe.dashLine,l.line.dash,s.mlw||l.line.width).style("opacity",o.selectedpoints&&!s.selected?Vwt:1)}}),jwt(a,o,e),a.selectAll(".regions").each(function(){q4.select(this).selectAll("path").style("stroke-width",0).call(QG.fill,o.connector.fillcolor)}),a.selectAll(".lines").each(function(){var s=o.connector.line;qwe.lineGroupStyle(q4.select(this).selectAll("path"),s.width,s.color,s.dash)})})}Bwe.exports={style:Wwt}});var Gwe=ye((dfr,Vwe)=>{"use strict";var Uwe=ka().opacity,Xwt=ET().hoverOnBars,eH=Dr().formatPercent;Vwe.exports=function(t,r,n,i,a){var o=Xwt(t,r,n,i,a);if(o){var s=o.cd,l=s[0].trace,u=l.orientation==="h",c=o.index,f=s[c],h=u?"x":"y";o[h+"LabelVal"]=f.s,o.percentInitial=f.begR,o.percentInitialLabel=eH(f.begR,1),o.percentPrevious=f.difR,o.percentPreviousLabel=eH(f.difR,1),o.percentTotal=f.sumR,o.percentTotalLabel=eH(f.sumR,1);var d=f.hi||l.hoverinfo,v=[];if(d&&d!=="none"&&d!=="skip"){var _=d==="all",b=d.split("+"),p=function(k){return _||b.indexOf(k)!==-1};p("percent initial")&&v.push(o.percentInitialLabel+" of initial"),p("percent previous")&&v.push(o.percentPreviousLabel+" of previous"),p("percent total")&&v.push(o.percentTotalLabel+" of total")}return o.extraText=v.join("
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rH(e){return{marker:{color:WT({},_c.marker.color,{arrayOk:!1,editType:"style"}),line:{color:WT({},_c.marker.line.color,{arrayOk:!1,editType:"style"}),width:WT({},_c.marker.line.width,{arrayOk:!1,editType:"style"}),editType:"style"},editType:"style"},editType:"style"}}t3e.exports={measure:{valType:"data_array",dflt:[],editType:"calc"},base:{valType:"number",dflt:null,arrayOk:!1,editType:"calc"},x:_c.x,x0:_c.x0,dx:_c.dx,y:_c.y,y0:_c.y0,dy:_c.dy,xperiod:_c.xperiod,yperiod:_c.yperiod,xperiod0:_c.xperiod0,yperiod0:_c.yperiod0,xperiodalignment:_c.xperiodalignment,yperiodalignment:_c.yperiodalignment,xhoverformat:$we("x"),yhoverformat:$we("y"),hovertext:_c.hovertext,hovertemplate:Kwt({},{keys:e3e.eventDataKeys}),hovertemplatefallback:Qwe(),hoverinfo:WT({},Ywt.hoverinfo,{flags:["name","x","y","text","initial","delta","final"]}),textinfo:{valType:"flaglist",flags:["label","text","initial","delta","final"],extras:["none"],editType:"plot",arrayOk:!1},texttemplate:Jwt({editType:"plot"},{keys:e3e.eventDataKeys.concat(["label"])}),texttemplatefallback:Qwe({editType:"plot"}),text:_c.text,textposition:_c.textposition,insidetextanchor:_c.insidetextanchor,textangle:_c.textangle,textfont:_c.textfont,insidetextfont:_c.insidetextfont,outsidetextfont:_c.outsidetextfont,constraintext:_c.constraintext,cliponaxis:_c.cliponaxis,orientation:_c.orientation,offset:_c.offset,width:_c.width,increasing:rH("increasing"),decreasing:rH("decreasing"),totals:rH("intermediate 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aH(e,t,r){e(t+".marker.color",r),e(t+".marker.line.color",i3t.defaultLine),e(t+".marker.line.width")}function s3t(e,t,r,n){function i(u,c){return n3e.coerce(e,t,a3e,u,c)}var a=t3t(e,t,n,i);if(!a){t.visible=!1;return}r3t(e,t,n,i),i("xhoverformat"),i("yhoverformat"),i("measure"),i("orientation",t.x&&!t.y?"h":"v"),i("base"),i("offset"),i("width"),i("text"),i("hovertext"),i("hovertemplate"),i("hovertemplatefallback");var o=i("textposition");e3t(e,t,n,i,o,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!0,moduleHasCliponaxis:!0,moduleHasTextangle:!0,moduleHasInsideanchor:!0}),t.textposition!=="none"&&(i("texttemplate"),i("texttemplatefallback"),t.texttemplate||i("textinfo")),aH(i,"increasing",n3t),aH(i,"decreasing",a3t),aH(i,"totals",o3t);var s=i("connector.visible");if(s){i("connector.mode");var l=i("connector.line.width");l&&(i("connector.line.color"),i("connector.line.dash"))}i("zorder")}function l3t(e,t){var r,n;function i(o){return 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e===0&&t===34665||e===0&&t===34853||e===34665&&t===40965};jy.prototype.exif_format_length=function(e){switch(e){case 1:case 2:case 6:case 7:return 1;case 3:case 8:return 2;case 4:case 9:case 11:return 4;case 5:case 10:case 12:return 8;default:return 0}};jy.prototype.exif_format_read=function(e,t){var r;switch(e){case 1:case 2:return r=this.input[t],r;case 6:return r=this.input[t],r|(r&128)*33554430;case 3:return r=this.read_uint16(t),r;case 8:return r=this.read_uint16(t),r|(r&32768)*131070;case 4:return r=this.read_uint32(t),r;case 9:return r=this.read_uint32(t),r|0;case 5:case 10:case 11:case 12:return null;case 7:return null;default:return null}};jy.prototype.scan_ifd=function(e,t,r){var n=this.read_uint16(t);t+=2;for(var i=0;ithis.input.length)throw lD("unexpected EOF","EBADDATA");for(var h=[],d=c,v=0;v0&&(this.ifds_to_read.push({id:a,offset:h[0]}),f=!0);var 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s={width:o.width,height:o.height,type:r.type,mime:r.mime,wUnits:"px",hUnits:"px"};if(o.variants.length>1&&(s.variants=o.variants),o.orientation&&(s.orientation=o.orientation),o.exif_location&&o.exif_location.offset+o.exif_location.length<=e.length){var l=dkt(e,o.exif_location.offset),u=e.slice(o.exif_location.offset+l+4,o.exif_location.offset+o.exif_location.length),c=vkt.get_orientation(u);c>0&&(s.orientation=c)}return s}}}}}}});var Z4e=ye((Adr,X4e)=>{"use strict";var gkt=rc().str2arr,mkt=rc().sliceEq,W4e=rc().readUInt16LE,ykt=gkt("BM");X4e.exports=function(e){if(!(e.length<26)&&mkt(e,0,ykt))return{width:W4e(e,18),height:W4e(e,22),type:"bmp",mime:"image/bmp",wUnits:"px",hUnits:"px"}}});var Q4e=ye((Sdr,$4e)=>{"use strict";var J4e=rc().str2arr,Y4e=rc().sliceEq,K4e=rc().readUInt16LE,_kt=J4e("GIF87a"),xkt=J4e("GIF89a");$4e.exports=function(e){if(!(e.length<10)&&!(!Y4e(e,0,_kt)&&!Y4e(e,0,xkt)))return{width:K4e(e,6),height:K4e(e,8),type:"gif",mime:"image/gif",wUnits:"px",hUnits:"px"}}});var rEe=ye((Mdr,tEe)=>{"use strict";var lW=rc().readUInt16LE,bkt=0,wkt=1,eEe=16;tEe.exports=function(e){var t=lW(e,0),r=lW(e,2),n=lW(e,4);if(!(t!==bkt||r!==wkt||!n)){for(var i=[],a={width:0,height:0},o=0;oa.width||l>a.height)&&(a=u)}return{width:a.width,height:a.height,variants:i,type:"ico",mime:"image/x-icon",wUnits:"px",hUnits:"px"}}}});var nEe=ye((Edr,iEe)=>{"use strict";var uW=rc().readUInt16BE,Tkt=rc().str2arr,Akt=rc().sliceEq,Skt=uD(),Mkt=Tkt("Exif\0\0");iEe.exports=function(e){if(!(e.length<2)&&!(e[0]!==255||e[1]!==216||e[2]!==255))for(var t=2;;){for(;;){if(e.length-t<2)return;if(e[t++]===255)break}for(var r=e[t++],n;r===255;)r=e[t++];if(208<=r&&r<=217||r===1)n=0;else if(192<=r&&r<=254){if(e.length-t<2)return;n=uW(e,t)-2,t+=2}else return;if(r===217||r===218)return;var i;if(r===225&&n>=10&&Akt(e,t,Mkt)&&(i=Skt.get_orientation(e.slice(t+6,t+n))),n>=5&&192<=r&&r<=207&&r!==196&&r!==200&&r!==204){if(e.length-t0&&(a.orientation=i),a}t+=n}}});var uEe=ye((kdr,lEe)=>{"use strict";var sEe=rc().str2arr,aEe=rc().sliceEq,oEe=rc().readUInt32BE,Ekt=sEe(`\x89PNG\r + +`),kkt=sEe("IHDR");lEe.exports=function(e){if(!(e.length<24)&&aEe(e,0,Ekt)&&aEe(e,12,kkt))return{width:oEe(e,16),height:oEe(e,20),type:"png",mime:"image/png",wUnits:"px",hUnits:"px"}}});var hEe=ye((Cdr,fEe)=>{"use strict";var Ckt=rc().str2arr,Lkt=rc().sliceEq,cEe=rc().readUInt32BE,Pkt=Ckt("8BPS\0");fEe.exports=function(e){if(!(e.length<22)&&Lkt(e,0,Pkt))return{width:cEe(e,18),height:cEe(e,14),type:"psd",mime:"image/vnd.adobe.photoshop",wUnits:"px",hUnits:"px"}}});var pEe=ye((Ldr,vEe)=>{"use strict";function Ikt(e){return e===32||e===9||e===13||e===10}function wA(e){return typeof e=="number"&&isFinite(e)&&e>0}function Rkt(e){var 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i=t.cd[0],a=i.trace,o=t.xa,s=t.ya;if(!(BEe.inbox(r-i.x0,r-(i.x0+i.w*a.dx),0)>0||BEe.inbox(n-i.y0,n-(i.y0+i.h*a.dy),0)>0)){var l=Math.floor((r-i.x0)/a.dx),u=Math.floor(Math.abs(n-i.y0)/a.dy),c;if(a._hasZ?c=i.z[u][l]:a._hasSource&&(c=a._canvas.el.getContext("2d",{willReadFrequently:!0}).getImageData(l,u,1,1).data),!!c){var f=i.hi||a.hoverinfo,h;if(f){var d=f.split("+");d.indexOf("all")!==-1&&(d=["color"]),d.indexOf("color")!==-1&&(h=!0)}var v=pCt.colormodel[a.colormodel],_=v.colormodel||a.colormodel,b=_.length,p=a._scaler(c),k=v.suffix,E=[];(a.hovertemplate||h)&&(E.push("["+[p[0]+k[0],p[1]+k[1],p[2]+k[2]].join(", ")),b===4&&E.push(", "+p[3]+k[3]),E.push("]"),E=E.join(""),t.extraText=_.toUpperCase()+": "+E);var S;dD(a.hovertext)&&dD(a.hovertext[u])?S=a.hovertext[u][l]:dD(a.text)&&dD(a.text[u])&&(S=a.text[u][l]);var L=s.c2p(i.y0+(u+.5)*a.dy),x=i.x0+(l+.5)*a.dx,C=i.y0+(u+.5)*a.dy,M="["+c.slice(0,a.colormodel.length).join(", 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vW=Gl(),gCt=Cc().attributes,mCt=ec(),yCt=Lh(),{hovertemplateAttrs:_Ct,texttemplateAttrs:xCt,templatefallbackAttrs:YEe}=Ll(),S2=Ao().extendFlat,bCt=Pd().pattern,vD=mCt({editType:"plot",arrayOk:!0,colorEditType:"plot"});KEe.exports={labels:{valType:"data_array",editType:"calc"},label0:{valType:"number",dflt:0,editType:"calc"},dlabel:{valType:"number",dflt:1,editType:"calc"},values:{valType:"data_array",editType:"calc"},marker:{colors:{valType:"data_array",editType:"calc"},line:{color:{valType:"color",dflt:yCt.defaultLine,arrayOk:!0,editType:"style"},width:{valType:"number",min:0,dflt:0,arrayOk:!0,editType:"style"},editType:"calc"},pattern:bCt,editType:"calc"},text:{valType:"data_array",editType:"plot"},hovertext:{valType:"string",dflt:"",arrayOk:!0,editType:"style"},scalegroup:{valType:"string",dflt:"",editType:"calc"},textinfo:{valType:"flaglist",flags:["label","text","value","percent"],extras:["none"],editType:"calc"},hoverinfo:S2({},vW.hoverinfo,{flags:["label","text","value","percent","name"]}),hovertemplate:_Ct({},{keys:["label","color","value","percent","text"]}),hovertemplatefallback:YEe(),texttemplate:xCt({editType:"plot"},{keys:["label","color","value","percent","text"]}),texttemplatefallback:YEe({editType:"plot"}),textposition:{valType:"enumerated",values:["inside","outside","auto","none"],dflt:"auto",arrayOk:!0,editType:"plot"},textfont:S2({},vD,{}),insidetextorientation:{valType:"enumerated",values:["horizontal","radial","tangential","auto"],dflt:"auto",editType:"plot"},insidetextfont:S2({},vD,{}),outsidetextfont:S2({},vD,{}),automargin:{valType:"boolean",dflt:!1,editType:"plot"},showlegend:S2({},vW.showlegend,{arrayOk:!0}),legend:S2({},vW.legend,{arrayOk:!0}),title:{text:{valType:"string",dflt:"",editType:"plot"},font:S2({},vD,{}),position:{valType:"enumerated",values:["top left","top center","top right","middle center","bottom left","bottom center","bottom right"],editType:"plot"},editType:"plot"},domain:gCt({name:"pie",trace:!0,editType:"calc"}),hole:{valType:"number",min:0,max:1,dflt:0,editType:"calc"},sort:{valType:"boolean",dflt:!0,editType:"calc"},direction:{valType:"enumerated",values:["clockwise","counterclockwise"],dflt:"counterclockwise",editType:"calc"},rotation:{valType:"angle",dflt:0,editType:"calc"},pull:{valType:"number",min:0,max:1,dflt:0,arrayOk:!0,editType:"calc"}}});var E2=ye((Hdr,QEe)=>{"use strict";var wCt=Eo(),kE=Dr(),TCt=M2(),ACt=Cc().defaults,SCt=r0().handleText,MCt=Dr().coercePattern;function JEe(e,t){var r=kE.isArrayOrTypedArray(e),n=kE.isArrayOrTypedArray(t),i=Math.min(r?e.length:1/0,n?t.length:1/0);if(isFinite(i)||(i=0),i&&n){for(var a,o=0;o0){a=!0;break}}a||(i=0)}return{hasLabels:r,hasValues:n,len:i}}function $Ee(e,t,r,n,i){var a=n("marker.line.width");a&&n("marker.line.color",i?void 0:r.paper_bgcolor);var o=n("marker.colors");MCt(n,"marker.pattern",o),e.marker&&!t.marker.pattern.fgcolor&&(t.marker.pattern.fgcolor=e.marker.colors),t.marker.pattern.bgcolor||(t.marker.pattern.bgcolor=r.paper_bgcolor)}function ECt(e,t,r,n){function i(k,E){return kE.coerce(e,t,TCt,k,E)}var a=i("labels"),o=i("values"),s=JEe(a,o),l=s.len;if(t._hasLabels=s.hasLabels,t._hasValues=s.hasValues,!t._hasLabels&&t._hasValues&&(i("label0"),i("dlabel")),!l){t.visible=!1;return}t._length=l,$Ee(e,t,n,i,!0),i("scalegroup");var u=i("text"),c=i("texttemplate");i("texttemplatefallback");var f;if(c||(f=i("textinfo",kE.isArrayOrTypedArray(u)?"text+percent":"percent")),i("hovertext"),i("hovertemplate"),i("hovertemplatefallback"),c||f&&f!=="none"){var h=i("textposition");SCt(e,t,n,i,h,{moduleHasSelected:!1,moduleHasUnselected:!1,moduleHasConstrain:!1,moduleHasCliponaxis:!1,moduleHasTextangle:!1,moduleHasInsideanchor:!1});var d=Array.isArray(h)||h==="auto",v=d||h==="outside";v&&i("automargin"),(h==="inside"||h==="auto"||Array.isArray(h))&&i("insidetextorientation")}else f==="none"&&i("textposition","none");ACt(t,n,i);var _=i("hole"),b=i("title.text");if(b){var p=i("title.position",_?"middle center":"top center");!_&&p==="middle center"&&(t.title.position="top center"),kE.coerceFont(i,"title.font",n.font)}i("sort"),i("direction"),i("rotation"),i("pull")}QEe.exports={handleLabelsAndValues:JEe,handleMarkerDefaults:$Ee,supplyDefaults:ECt}});var pD=ye((jdr,eke)=>{"use strict";eke.exports={hiddenlabels:{valType:"data_array",editType:"calc"},piecolorway:{valType:"colorlist",editType:"calc"},extendpiecolors:{valType:"boolean",dflt:!0,editType:"calc"}}});var rke=ye((Wdr,tke)=>{"use strict";var kCt=Dr(),CCt=pD();tke.exports=function(t,r){function n(i,a){return kCt.coerce(t,r,CCt,i,a)}n("hiddenlabels"),n("piecolorway",r.colorway),n("extendpiecolors")}});var TA=ye((Xdr,ake)=>{"use strict";var LCt=Eo(),pW=cd(),PCt=ka(),ICt={};function RCt(e,t){var r=[],n=e._fullLayout,i=n.hiddenlabels||[],a=t.labels,o=t.marker.colors||[],s=t.values,l=t._length,u=t._hasValues&&l,c,f;if(t.dlabel)for(a=new Array(l),c=0;c=0});var S=t.type==="funnelarea"?_:t.sort;return S&&r.sort(function(L,x){return x.v-L.v}),r[0]&&(r[0].vTotal=v),r}function ike(e){return function(r,n){return!r||(r=pW(r),!r.isValid())?!1:(r=PCt.addOpacity(r,r.getAlpha()),e[n]||(e[n]=r),r)}}function DCt(e,t){var r=(t||{}).type;r||(r="pie");var n=e._fullLayout,i=e.calcdata,a=n[r+"colorway"],o=n["_"+r+"colormap"];n["extend"+r+"colors"]&&(a=nke(a,ICt));for(var s=0,l=0;l{"use strict";var FCt=ip().appendArrayMultiPointValues;oke.exports=function(t,r){var n={curveNumber:r.index,pointNumbers:t.pts,data:r._input,fullData:r,label:t.label,color:t.color,value:t.v,percent:t.percent,text:t.text,bbox:t.bbox,v:t.v};return t.pts.length===1&&(n.pointNumber=n.i=t.pts[0]),FCt(n,r,t.pts),r.type==="funnelarea"&&(delete n.v,delete n.i),n}});var _D=ye((Ydr,kke)=>{"use strict";var Fp=Oa(),zCt=Mc(),gD=vf(),dke=ka(),Wy=So(),rv=Dr(),OCt=rv.strScale,lke=rv.strTranslate,gW=ru(),vke=bv(),qCt=vke.recordMinTextSize,BCt=vke.clearMinTextSize,pke=e2().TEXTPAD,ns=l_(),mD=ske(),uke=Dr().isValidTextValue;function NCt(e,t){var r=e._context.staticPlot,n=e._fullLayout,i=n._size;BCt("pie",n),yke(t,e),Ske(t,i);var a=rv.makeTraceGroups(n._pielayer,t,"trace").each(function(o){var s=Fp.select(this),l=o[0],u=l.trace;YCt(o),s.attr("stroke-linejoin","round"),s.each(function(){var c=Fp.select(this).selectAll("g.slice").data(o);c.enter().append("g").classed("slice",!0),c.exit().remove();var f=[[[],[]],[[],[]]],h=!1;c.each(function(S,L){if(S.hidden){Fp.select(this).selectAll("path,g").remove();return}S.pointNumber=S.i,S.curveNumber=u.index,f[S.pxmid[1]<0?0:1][S.pxmid[0]<0?0:1].push(S);var x=l.cx,C=l.cy,M=Fp.select(this),g=M.selectAll("path.surface").data([S]);if(g.enter().append("path").classed("surface",!0).style({"pointer-events":r?"none":"all"}),M.call(gke,e,o),u.pull){var P=+ns.castOption(u.pull,S.pts)||0;P>0&&(x+=P*S.pxmid[0],C+=P*S.pxmid[1])}S.cxFinal=x,S.cyFinal=C;function T(N,H,te,oe){var _e=oe*(H[0]-N[0]),Ee=oe*(H[1]-N[1]);return"a"+oe*l.r+","+oe*l.r+" 0 "+S.largeArc+(te?" 1 ":" 0 ")+_e+","+Ee}var z=u.hole;if(S.v===l.vTotal){var O="M"+(x+S.px0[0])+","+(C+S.px0[1])+T(S.px0,S.pxmid,!0,1)+T(S.pxmid,S.px0,!0,1)+"Z";z?g.attr("d","M"+(x+z*S.px0[0])+","+(C+z*S.px0[1])+T(S.px0,S.pxmid,!1,z)+T(S.pxmid,S.px0,!1,z)+"Z"+O):g.attr("d",O)}else{var V=T(S.px0,S.px1,!0,1);if(z){var G=1-z;g.attr("d","M"+(x+z*S.px1[0])+","+(C+z*S.px1[1])+T(S.px1,S.px0,!1,z)+"l"+G*S.px0[0]+","+G*S.px0[1]+V+"Z")}else g.attr("d","M"+x+","+C+"l"+S.px0[0]+","+S.px0[1]+V+"Z")}Mke(e,S,l);var Z=ns.castOption(u.textposition,S.pts),j=M.selectAll("g.slicetext").data(S.text&&Z!=="none"?[0]:[]);j.enter().append("g").classed("slicetext",!0),j.exit().remove(),j.each(function(){var N=rv.ensureSingle(Fp.select(this),"text","",function(ie){ie.attr("data-notex",1)}),H=rv.ensureUniformFontSize(e,Z==="outside"?VCt(u,S,n.font):mke(u,S,n.font));N.text(S.text).attr({class:"slicetext",transform:"","text-anchor":"middle"}).call(Wy.font,H).call(gW.convertToTspans,e);var te=Wy.bBox(N.node()),oe;if(Z==="outside")oe=hke(te,S);else if(oe=_ke(te,S,l),Z==="auto"&&oe.scale<1){var _e=rv.ensureUniformFontSize(e,u.outsidetextfont);N.call(Wy.font,_e),te=Wy.bBox(N.node()),oe=hke(te,S)}var Ee=oe.textPosAngle,Ce=Ee===void 0?S.pxmid:yD(l.r,Ee);if(oe.targetX=x+Ce[0]*oe.rCenter+(oe.x||0),oe.targetY=C+Ce[1]*oe.rCenter+(oe.y||0),Eke(oe,te),oe.outside){var me=oe.targetY;S.yLabelMin=me-te.height/2,S.yLabelMid=me,S.yLabelMax=me+te.height/2,S.labelExtraX=0,S.labelExtraY=0,h=!0}oe.fontSize=H.size,qCt(u.type,oe,n),o[L].transform=oe,rv.setTransormAndDisplay(N,oe)})});var d=Fp.select(this).selectAll("g.titletext").data(u.title.text?[0]:[]);if(d.enter().append("g").classed("titletext",!0),d.exit().remove(),d.each(function(){var S=rv.ensureSingle(Fp.select(this),"text","",function(C){C.attr("data-notex",1)}),L=u.title.text;u._meta&&(L=rv.templateString(L,u._meta)),S.text(L).attr({class:"titletext",transform:"","text-anchor":"middle"}).call(Wy.font,u.title.font).call(gW.convertToTspans,e);var x;u.title.position==="middle center"?x=jCt(l):x=Tke(l,i),S.attr("transform",lke(x.x,x.y)+OCt(Math.min(1,x.scale))+lke(x.tx,x.ty))}),h&&XCt(f,u),UCt(c,u),h&&u.automargin){var v=Wy.bBox(s.node()),_=u.domain,b=i.w*(_.x[1]-_.x[0]),p=i.h*(_.y[1]-_.y[0]),k=(.5*b-l.r)/i.w,E=(.5*p-l.r)/i.h;zCt.autoMargin(e,"pie."+u.uid+".automargin",{xl:_.x[0]-k,xr:_.x[1]+k,yb:_.y[0]-E,yt:_.y[1]+E,l:Math.max(l.cx-l.r-v.left,0),r:Math.max(v.right-(l.cx+l.r),0),b:Math.max(v.bottom-(l.cy+l.r),0),t:Math.max(l.cy-l.r-v.top,0),pad:5})}})});setTimeout(function(){a.selectAll("tspan").each(function(){var o=Fp.select(this);o.attr("dy")&&o.attr("dy",o.attr("dy"))})},0)}function UCt(e,t){e.each(function(r){var n=Fp.select(this);if(!r.labelExtraX&&!r.labelExtraY){n.select("path.textline").remove();return}var i=n.select("g.slicetext text");r.transform.targetX+=r.labelExtraX,r.transform.targetY+=r.labelExtraY,rv.setTransormAndDisplay(i,r.transform);var a=r.cxFinal+r.pxmid[0],o=r.cyFinal+r.pxmid[1],s="M"+a+","+o,l=(r.yLabelMax-r.yLabelMin)*(r.pxmid[0]<0?-1:1)/4;if(r.labelExtraX){var u=r.labelExtraX*r.pxmid[1]/r.pxmid[0],c=r.yLabelMid+r.labelExtraY-(r.cyFinal+r.pxmid[1]);Math.abs(u)>Math.abs(c)?s+="l"+c*r.pxmid[0]/r.pxmid[1]+","+c+"H"+(a+r.labelExtraX+l):s+="l"+r.labelExtraX+","+u+"v"+(c-u)+"h"+l}else s+="V"+(r.yLabelMid+r.labelExtraY)+"h"+l;rv.ensureSingle(n,"path","textline").call(dke.stroke,t.outsidetextfont.color).attr({"stroke-width":Math.min(2,t.outsidetextfont.size/8),d:s,fill:"none"})})}function gke(e,t,r){var n=r[0],i=n.cx,a=n.cy,o=n.trace,s=o.type==="funnelarea";"_hasHoverLabel"in o||(o._hasHoverLabel=!1),"_hasHoverEvent"in o||(o._hasHoverEvent=!1),e.on("mouseover",function(l){var u=t._fullLayout,c=t._fullData[o.index];if(!(t._dragging||u.hovermode===!1)){var f=c.hoverinfo;if(Array.isArray(f)&&(f=gD.castHoverinfo({hoverinfo:[ns.castOption(f,l.pts)],_module:o._module},u,0)),f==="all"&&(f="label+text+value+percent+name"),c.hovertemplate||f!=="none"&&f!=="skip"&&f){var h=l.rInscribed||0,d=i+l.pxmid[0]*(1-h),v=a+l.pxmid[1]*(1-h),_=u.separators,b=[];if(f&&f.indexOf("label")!==-1&&b.push(l.label),l.text=ns.castOption(c.hovertext||c.text,l.pts),f&&f.indexOf("text")!==-1){var p=l.text;rv.isValidTextValue(p)&&b.push(p)}l.value=l.v,l.valueLabel=ns.formatPieValue(l.v,_),f&&f.indexOf("value")!==-1&&b.push(l.valueLabel),l.percent=l.v/n.vTotal,l.percentLabel=ns.formatPiePercent(l.percent,_),f&&f.indexOf("percent")!==-1&&b.push(l.percentLabel);var k=c.hoverlabel,E=k.font,S=[];gD.loneHover({trace:o,x0:d-h*n.r,x1:d+h*n.r,y:v,_x0:s?i+l.TL[0]:d-h*n.r,_x1:s?i+l.TR[0]:d+h*n.r,_y0:s?a+l.TL[1]:v-h*n.r,_y1:s?a+l.BL[1]:v+h*n.r,text:b.join("
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u=t._fullLayout,c=t._fullData[o.index],f=Fp.select(this).datum();o._hasHoverEvent&&(l.originalEvent=Fp.event,t.emit("plotly_unhover",{points:[mD(f,c)],event:Fp.event}),o._hasHoverEvent=!1),o._hasHoverLabel&&(gD.loneUnhover(u._hoverlayer.node()),o._hasHoverLabel=!1)}),e.on("click",function(l){var u=t._fullLayout,c=t._fullData[o.index];t._dragging||u.hovermode===!1||(t._hoverdata=[mD(l,c)],gD.click(t,Fp.event))})}function VCt(e,t,r){var n=ns.castOption(e.outsidetextfont.color,t.pts)||ns.castOption(e.textfont.color,t.pts)||r.color,i=ns.castOption(e.outsidetextfont.family,t.pts)||ns.castOption(e.textfont.family,t.pts)||r.family,a=ns.castOption(e.outsidetextfont.size,t.pts)||ns.castOption(e.textfont.size,t.pts)||r.size,o=ns.castOption(e.outsidetextfont.weight,t.pts)||ns.castOption(e.textfont.weight,t.pts)||r.weight,s=ns.castOption(e.outsidetextfont.style,t.pts)||ns.castOption(e.textfont.style,t.pts)||r.style,l=ns.castOption(e.outsidetextfont.variant,t.pts)||ns.castOption(e.textfont.variant,t.pts)||r.variant,u=ns.castOption(e.outsidetextfont.textcase,t.pts)||ns.castOption(e.textfont.textcase,t.pts)||r.textcase,c=ns.castOption(e.outsidetextfont.lineposition,t.pts)||ns.castOption(e.textfont.lineposition,t.pts)||r.lineposition,f=ns.castOption(e.outsidetextfont.shadow,t.pts)||ns.castOption(e.textfont.shadow,t.pts)||r.shadow;return{color:n,family:i,size:a,weight:o,style:s,variant:l,textcase:u,lineposition:c,shadow:f}}function mke(e,t,r){var n=ns.castOption(e.insidetextfont.color,t.pts);!n&&e._input.textfont&&(n=ns.castOption(e._input.textfont.color,t.pts));var i=ns.castOption(e.insidetextfont.family,t.pts)||ns.castOption(e.textfont.family,t.pts)||r.family,a=ns.castOption(e.insidetextfont.size,t.pts)||ns.castOption(e.textfont.size,t.pts)||r.size,o=ns.castOption(e.insidetextfont.weight,t.pts)||ns.castOption(e.textfont.weight,t.pts)||r.weight,s=ns.castOption(e.insidetextfont.style,t.pts)||ns.castOption(e.textfont.style,t.pts)||r.style,l=ns.castOption(e.insidetextfont.variant,t.pts)||ns.castOption(e.textfont.variant,t.pts)||r.variant,u=ns.castOption(e.insidetextfont.textcase,t.pts)||ns.castOption(e.textfont.textcase,t.pts)||r.textcase,c=ns.castOption(e.insidetextfont.lineposition,t.pts)||ns.castOption(e.textfont.lineposition,t.pts)||r.lineposition,f=ns.castOption(e.insidetextfont.shadow,t.pts)||ns.castOption(e.textfont.shadow,t.pts)||r.shadow;return{color:n||dke.contrast(t.color),family:i,size:a,weight:o,style:s,variant:l,textcase:u,lineposition:c,shadow:f}}function yke(e,t){for(var r,n,i=0;i=-4;k-=2)p(Math.PI*k,"tan");for(k=4;k>=-4;k-=2)p(Math.PI*(k+1),"tan")}if(f||d){for(k=4;k>=-4;k-=2)p(Math.PI*(k+1.5),"rad");for(k=4;k>=-4;k-=2)p(Math.PI*(k+.5),"rad")}}if(s||v||f){var E=Math.sqrt(e.width*e.width+e.height*e.height);if(b={scale:i*n*2/E,rCenter:1-i,rotate:0},b.textPosAngle=(t.startangle+t.stopangle)/2,b.scale>=1)return b;_.push(b)}(v||d)&&(b=cke(e,n,o,l,u),b.textPosAngle=(t.startangle+t.stopangle)/2,_.push(b)),(v||h)&&(b=fke(e,n,o,l,u),b.textPosAngle=(t.startangle+t.stopangle)/2,_.push(b));for(var S=0,L=0,x=0;x<_.length;x++){var C=_[x].scale;if(L=1)break}return _[S]}function GCt(e,t){var r=e.startangle,n=e.stopangle;return r>t&&t>n||r0?1:-1)/2,y:a/(1+r*r/(n*n)),outside:!0}}function jCt(e){var t=Math.sqrt(e.titleBox.width*e.titleBox.width+e.titleBox.height*e.titleBox.height);return{x:e.cx,y:e.cy,scale:e.trace.hole*e.r*2/t,tx:0,ty:-e.titleBox.height/2+e.trace.title.font.size}}function Tke(e,t){var r=1,n=1,i,a=e.trace,o={x:e.cx,y:e.cy},s={tx:0,ty:0};s.ty+=a.title.font.size,i=Ake(a),a.title.position.indexOf("top")!==-1?(o.y-=(1+i)*e.r,s.ty-=e.titleBox.height):a.title.position.indexOf("bottom")!==-1&&(o.y+=(1+i)*e.r);var l=WCt(e.r,e.trace.aspectratio),u=t.w*(a.domain.x[1]-a.domain.x[0])/2;return a.title.position.indexOf("left")!==-1?(u=u+l,o.x-=(1+i)*l,s.tx+=e.titleBox.width/2):a.title.position.indexOf("center")!==-1?u*=2:a.title.position.indexOf("right")!==-1&&(u=u+l,o.x+=(1+i)*l,s.tx-=e.titleBox.width/2),r=u/e.titleBox.width,n=mW(e,t)/e.titleBox.height,{x:o.x,y:o.y,scale:Math.min(r,n),tx:s.tx,ty:s.ty}}function WCt(e,t){return e/(t===void 0?1:t)}function mW(e,t){var r=e.trace,n=t.h*(r.domain.y[1]-r.domain.y[0]);return Math.min(e.titleBox.height,n/2)}function Ake(e){var t=e.pull;if(!t)return 0;var r;if(rv.isArrayOrTypedArray(t))for(t=0,r=0;rt&&(t=e.pull[r]);return t}function XCt(e,t){var r,n,i,a,o,s,l,u,c,f,h,d,v;function _(E,S){return E.pxmid[1]-S.pxmid[1]}function b(E,S){return S.pxmid[1]-E.pxmid[1]}function p(E,S){S||(S={});var L=S.labelExtraY+(n?S.yLabelMax:S.yLabelMin),x=n?E.yLabelMin:E.yLabelMax,C=n?E.yLabelMax:E.yLabelMin,M=E.cyFinal+o(E.px0[1],E.px1[1]),g=L-x,P,T,z,O,V,G;if(g*l>0&&(E.labelExtraY=g),!!rv.isArrayOrTypedArray(t.pull))for(T=0;T=(ns.castOption(t.pull,z.pts)||0))&&((E.pxmid[1]-z.pxmid[1])*l>0?(O=z.cyFinal+o(z.px0[1],z.px1[1]),g=O-x-E.labelExtraY,g*l>0&&(E.labelExtraY+=g)):(C+E.labelExtraY-M)*l>0&&(P=3*s*Math.abs(T-f.indexOf(E)),V=z.cxFinal+a(z.px0[0],z.px1[0]),G=V+P-(E.cxFinal+E.pxmid[0])-E.labelExtraX,G*s>0&&(E.labelExtraX+=G)))}for(n=0;n<2;n++)for(i=n?_:b,o=n?Math.max:Math.min,l=n?1:-1,r=0;r<2;r++){for(a=r?Math.max:Math.min,s=r?1:-1,u=e[n][r],u.sort(i),c=e[1-n][r],f=c.concat(u),d=[],h=0;h1?(u=r.r,c=u/i.aspectratio):(c=r.r,u=c*i.aspectratio),u*=(1+i.baseratio)/2,l=u*c}o=Math.min(o,l/r.vTotal)}for(n=0;nt.vTotal/2?1:0,u.halfangle=Math.PI*Math.min(u.v/t.vTotal,.5),u.ring=1-n.hole,u.rInscribed=HCt(u,t))}function yD(e,t){return[e*Math.sin(t),-e*Math.cos(t)]}function Mke(e,t,r){var n=e._fullLayout,i=r.trace,a=i.texttemplate,o=i.textinfo;if(!a&&o&&o!=="none"){var s=o.split("+"),l=function(S){return s.indexOf(S)!==-1},u=l("label"),c=l("text"),f=l("value"),h=l("percent"),d=n.separators,v;if(v=u?[t.label]:[],c){var _=ns.getFirstFilled(i.text,t.pts);uke(_)&&v.push(_)}f&&v.push(ns.formatPieValue(t.v,d)),h&&v.push(ns.formatPiePercent(t.v/r.vTotal,d)),t.text=v.join("
")}function b(S){return{label:S.label,value:S.v,valueLabel:ns.formatPieValue(S.v,n.separators),percent:S.v/r.vTotal,percentLabel:ns.formatPiePercent(S.v/r.vTotal,n.separators),color:S.color,text:S.text,customdata:rv.castOption(i,S.i,"customdata")}}if(a){var p=rv.castOption(i,t.i,"texttemplate");if(!p)t.text="";else{var k=b(t),E=ns.getFirstFilled(i.text,t.pts);(uke(E)||E==="")&&(k.text=E),t.text=rv.texttemplateString({data:[k,i._meta],fallback:i.texttemplatefallback,labels:k,locale:e._fullLayout._d3locale,template:p})}}}function Eke(e,t){var r=e.rotate*Math.PI/180,n=Math.cos(r),i=Math.sin(r),a=(t.left+t.right)/2,o=(t.top+t.bottom)/2;e.textX=a*n-o*i,e.textY=a*i+o*n,e.noCenter=!0}kke.exports={plot:NCt,formatSliceLabel:Mke,transformInsideText:_ke,determineInsideTextFont:mke,positionTitleOutside:Tke,prerenderTitles:yke,layoutAreas:Ske,attachFxHandlers:gke,computeTransform:Eke}});var Pke=ye((Kdr,Lke)=>{"use strict";var Cke=Oa(),KCt=B3(),JCt=bv().resizeText;Lke.exports=function(t){var 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Se=me.select("g.slicetext");Se.attr("opacity",0)}).remove():l.exit().remove(),l.order();var N=null;if(o&&L){var H=Rl.getPtId(L);l.each(function(me){N===null&&Rl.getPtId(me)===H&&(N=me.x1)})}var te=l;o&&(te=te.transition().each("end",function(){var me=jE.select(this);Rl.setSliceCursor(me,e,{hideOnRoot:!0,hideOnLeaves:!0,isTransitioning:!1})})),te.each(function(me){var ie=jE.select(this),Se=Av.ensureSingle(ie,"path","surface",function(Re){Re.style("pointer-events",i?"none":"all")});me.rpx0=O(me.y0),me.rpx1=O(me.y1),me.xmid=(me.x0+me.x1)/2,me.pxmid=V(me.rpx1,me.xmid),me.midangle=-(me.xmid-Math.PI/2),me.startangle=-(me.x0-Math.PI/2),me.stopangle=-(me.x1-Math.PI/2),me.halfangle=.5*Math.min(Av.angleDelta(me.x0,me.x1)||Math.PI,Math.PI),me.ring=1-me.rpx0/me.rpx1,me.rInscribed=uLt(me,c),o?Se.transition().attrTween("d",function(Re){var ce=_e(Re);return function(Ze){return 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ie=Rl.getPtId(me),Se=x[ie],Le=x[Rl.getPtId(h)],Ae;if(Le){var Fe=(me.x1>Le.x1?2*Math.PI:0)+T;Ae=me.rpx1N?2*Math.PI:0)+T;Se={x0:Ae,x1:Ae}}else Se={rpx0:k,rpx1:k},Av.extendFlat(Se,Ce(me));else Se={rpx0:0,rpx1:0};else Se={x0:T,x1:T};return Yg(Se,Le)}function Ee(me){var ie=x[Rl.getPtId(me)],Se,Le=me.transform;if(ie)Se=ie;else if(Se={rpx1:me.rpx1,transform:{textPosAngle:Le.textPosAngle,scale:0,rotate:Le.rotate,rCenter:Le.rCenter,x:Le.x,y:Le.y}},L)if(me.parent)if(N){var Ae=me.x1>N?2*Math.PI:0;Se.x0=Se.x1=Ae}else Av.extendFlat(Se,Ce(me));else Se.x0=Se.x1=T;else Se.x0=Se.x1=T;var Fe=Yg(Se.transform.textPosAngle,me.transform.textPosAngle),Pe=Yg(Se.rpx1,me.rpx1),ge=Yg(Se.x0,me.x0),Re=Yg(Se.x1,me.x1),ce=Yg(Se.transform.scale,Le.scale),Ze=Yg(Se.transform.rotate,Le.rotate),ut=Le.rCenter===0?3:Se.transform.rCenter===0?1/3:1,pt=Yg(Se.transform.rCenter,Le.rCenter),Zt=function(st){return pt(Math.pow(st,ut))};return function(st){var 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ULe=ye((E0r,NLe)=>{"use strict";var OLe=Oa(),ZD=Dr(),qLe=So(),mPt=ru(),yPt=PLe(),BLe=lX().styleOne,uX=O2(),NA=Ky(),_Pt=HE(),xPt=VD().formatSliceLabel,cX=!1;NLe.exports=function(t,r,n,i,a){var o=a.width,s=a.height,l=a.viewX,u=a.viewY,c=a.pathSlice,f=a.toMoveInsideSlice,h=a.strTransform,d=a.hasTransition,v=a.handleSlicesExit,_=a.makeUpdateSliceInterpolator,b=a.makeUpdateTextInterpolator,p=a.prevEntry,k={},E=t._context.staticPlot,S=t._fullLayout,L=r[0],x=L.trace,C=x.textposition.indexOf("left")!==-1,M=x.textposition.indexOf("right")!==-1,g=x.textposition.indexOf("bottom")!==-1,P=yPt(n,[o,s],{flipX:x.tiling.flip.indexOf("x")>-1,flipY:x.tiling.flip.indexOf("y")>-1,orientation:x.tiling.orientation,pad:{inner:x.tiling.pad},maxDepth:x._maxDepth}),T=P.descendants(),z=1/0,O=-1/0;T.forEach(function(N){var 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p=[c,f];function k(S,L,x,C,M,g,P,T){return function(O,V){switch(O.length){case 0:return S(O,V);case 1:return L(O,V);case 2:return x(O,V);case 3:return C(O,V);case 4:return M(O,V);case 5:return g(O,V)}var G=P[O.length];return G||(G=P[O.length]=T(O.length)),G(O,V)}}function E(){for(;p.length1e-6?(k=Math.acos(E),S=Math.sin(k),L=Math.sin((1-u)*k)/S,x=Math.sin(u*k)/S):(L=1-u,x=u),o[0]=L*c+x*v,o[1]=L*f+x*_,o[2]=L*h+x*b,o[3]=L*d+x*p,o}},799:function(i,a,o){var s=o(3236),l=o(9405),u=s([`precision mediump float; +#define GLSLIFY 1 +attribute vec2 position; +varying vec2 uv; +void main() { + uv = position; + gl_Position = vec4(position, 0, 1); +}`]),c=s([`precision mediump float; +#define GLSLIFY 1 + +uniform sampler2D accumBuffer; +varying vec2 uv; + +void main() { + vec4 accum = texture2D(accumBuffer, 0.5 * (uv + 1.0)); + gl_FragColor = min(vec4(1,1,1,1), accum); +}`]);i.exports=function(f){return l(f,u,c,null,[{name:"position",type:"vec2"}])}},811:function(i){i.exports=a;function a(o,s){return o[0]=1/s[0],o[1]=1/s[1],o[2]=1/s[2],o}},840:function(i,a,o){var s=o(3236),l=s([`precision highp float; +#define GLSLIFY 1 + +attribute vec3 position, normal; +attribute vec4 color; +attribute vec2 uv; + +uniform mat4 model + , view + , projection + , inverseModel; +uniform vec3 eyePosition + , lightPosition; + +varying vec3 f_normal + , f_lightDirection + , f_eyeDirection + , f_data; +varying vec4 f_color; +varying vec2 f_uv; + +vec4 project(vec3 p) { + return projection * (view * (model * vec4(p, 1.0))); +} + +void main() { + gl_Position = project(position); + + //Lighting geometry parameters + vec4 cameraCoordinate = view * vec4(position , 1.0); + cameraCoordinate.xyz /= cameraCoordinate.w; + f_lightDirection = lightPosition - cameraCoordinate.xyz; + f_eyeDirection = eyePosition - cameraCoordinate.xyz; + f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz); + + f_color = color; + f_data = position; + f_uv = uv; +} +`]),u=s([`#extension GL_OES_standard_derivatives : enable + +precision highp float; +#define GLSLIFY 1 + +float beckmannDistribution(float x, float roughness) { + float NdotH = max(x, 0.0001); + float cos2Alpha = NdotH * NdotH; + float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha; + float roughness2 = roughness * roughness; + float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha; + return exp(tan2Alpha / roughness2) / denom; +} + +float cookTorranceSpecular( + vec3 lightDirection, + vec3 viewDirection, + vec3 surfaceNormal, + float roughness, + float fresnel) { + + float VdotN = max(dot(viewDirection, surfaceNormal), 0.0); + float LdotN = max(dot(lightDirection, surfaceNormal), 0.0); + + //Half angle vector + vec3 H = normalize(lightDirection + viewDirection); + + //Geometric term + float NdotH = max(dot(surfaceNormal, H), 0.0); + float VdotH = max(dot(viewDirection, H), 0.000001); + float LdotH = max(dot(lightDirection, H), 0.000001); + float G1 = (2.0 * NdotH * VdotN) / VdotH; + float G2 = (2.0 * NdotH * LdotN) / LdotH; + float G = min(1.0, min(G1, G2)); + + //Distribution term + float D = beckmannDistribution(NdotH, roughness); + + //Fresnel term + float F = pow(1.0 - VdotN, fresnel); + + //Multiply terms and done + return G * F * D / max(3.14159265 * VdotN, 0.000001); +} + +//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec3 clipBounds[2]; +uniform float roughness + , fresnel + , kambient + , kdiffuse + , kspecular; +uniform sampler2D texture; + +varying vec3 f_normal + , f_lightDirection + , f_eyeDirection + , f_data; +varying vec4 f_color; +varying vec2 f_uv; + +void main() { + if (f_color.a == 0.0 || + outOfRange(clipBounds[0], clipBounds[1], f_data) + ) discard; + + vec3 N = normalize(f_normal); + vec3 L = normalize(f_lightDirection); + vec3 V = normalize(f_eyeDirection); + + if(gl_FrontFacing) { + N = -N; + } + + float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel))); + //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d + + float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0); + + vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv); + vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0); + + gl_FragColor = litColor * f_color.a; +} +`]),c=s([`precision highp float; +#define GLSLIFY 1 + +attribute vec3 position; +attribute vec4 color; +attribute vec2 uv; + +uniform mat4 model, view, projection; + +varying vec4 f_color; +varying vec3 f_data; +varying vec2 f_uv; + +void main() { + gl_Position = projection * (view * (model * vec4(position, 1.0))); + f_color = color; + f_data = position; + f_uv = uv; +}`]),f=s([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec3 clipBounds[2]; +uniform sampler2D texture; +uniform float opacity; + +varying vec4 f_color; +varying vec3 f_data; +varying vec2 f_uv; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard; + + gl_FragColor = f_color * texture2D(texture, f_uv) * opacity; +}`]),h=s([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +attribute vec3 position; +attribute vec4 color; +attribute vec2 uv; +attribute float pointSize; + +uniform mat4 model, view, projection; +uniform vec3 clipBounds[2]; + +varying vec4 f_color; +varying vec2 f_uv; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], position)) { + + gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0); + } else { + gl_Position = projection * (view * (model * vec4(position, 1.0))); + } + gl_PointSize = pointSize; + f_color = color; + f_uv = uv; +}`]),d=s([`precision highp float; +#define GLSLIFY 1 + +uniform sampler2D texture; +uniform float opacity; + +varying vec4 f_color; +varying vec2 f_uv; + +void main() { + vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5); + if(dot(pointR, pointR) > 0.25) { + discard; + } + gl_FragColor = f_color * texture2D(texture, f_uv) * opacity; +}`]),v=s([`precision highp float; +#define GLSLIFY 1 + +attribute vec3 position; +attribute vec4 id; + +uniform mat4 model, view, projection; + +varying vec3 f_position; +varying vec4 f_id; + +void main() { + gl_Position = projection * (view * (model * vec4(position, 1.0))); + f_id = id; + f_position = position; +}`]),_=s([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec3 clipBounds[2]; +uniform float pickId; + +varying vec3 f_position; +varying vec4 f_id; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard; + + gl_FragColor = vec4(pickId, f_id.xyz); +}`]),b=s([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +attribute vec3 position; +attribute float pointSize; +attribute vec4 id; + +uniform mat4 model, view, projection; +uniform vec3 clipBounds[2]; + +varying vec3 f_position; +varying vec4 f_id; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], position)) { + + gl_Position = vec4(0.0, 0.0, 0.0, 0.0); + } else { + gl_Position = projection * (view * (model * vec4(position, 1.0))); + gl_PointSize = pointSize; + } + f_id = id; + f_position = position; +}`]),p=s([`precision highp float; +#define GLSLIFY 1 + +attribute vec3 position; + +uniform mat4 model, view, projection; + +void main() { + gl_Position = projection * (view * (model * vec4(position, 1.0))); +}`]),k=s([`precision highp float; +#define GLSLIFY 1 + +uniform vec3 contourColor; + +void main() { + gl_FragColor = vec4(contourColor, 1.0); +} +`]);a.meshShader={vertex:l,fragment:u,attributes:[{name:"position",type:"vec3"},{name:"normal",type:"vec3"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"}]},a.wireShader={vertex:c,fragment:f,attributes:[{name:"position",type:"vec3"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"}]},a.pointShader={vertex:h,fragment:d,attributes:[{name:"position",type:"vec3"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"},{name:"pointSize",type:"float"}]},a.pickShader={vertex:v,fragment:_,attributes:[{name:"position",type:"vec3"},{name:"id",type:"vec4"}]},a.pointPickShader={vertex:b,fragment:_,attributes:[{name:"position",type:"vec3"},{name:"pointSize",type:"float"},{name:"id",type:"vec4"}]},a.contourShader={vertex:p,fragment:k,attributes:[{name:"position",type:"vec3"}]}},855:function(i,a,o){"use strict";i.exports={init:E,sweepBipartite:x,sweepComplete:C,scanBipartite:M,scanComplete:g};var s=o(1888),l=o(8828),u=o(4192),c=1<<28,f=1024,h=s.mallocInt32(f),d=s.mallocInt32(f),v=s.mallocInt32(f),_=s.mallocInt32(f),b=s.mallocInt32(f),p=s.mallocInt32(f),k=s.mallocDouble(f*8);function E(P){var T=l.nextPow2(P);h.length>>1;u(k,Le);for(var Ae=0,Fe=0,Ce=0;Ce=c)Pe=Pe-c|0,S(v,_,Fe--,Pe);else if(Pe>=0)S(h,d,Ae--,Pe);else if(Pe<=-c){Pe=-Pe-c|0;for(var ge=0;ge>>1;u(k,Le);for(var Ae=0,Fe=0,Pe=0,Ce=0;Ce>1===k[2*Ce+3]>>1&&(Re=2,Ce+=1),ge<0){for(var ce=-(ge>>1)-1,Ze=0;Ze>1)-1;Re===0?S(h,d,Ae--,ce):Re===1?S(v,_,Fe--,ce):Re===2&&S(b,p,Pe--,ce)}}}function M(P,T,z,O,V,G,Z,j,N,H,te,oe){var _e=0,Ee=2*P,Ce=T,me=T+P,ie=1,Se=1;O?Se=c:ie=c;for(var Le=V;Le>>1;u(k,ge);for(var Re=0,Le=0;Le=c?(Ze=!O,Ae-=c):(Ze=!!O,Ae-=1),Ze)L(h,d,Re++,Ae);else{var ut=oe[Ae],pt=Ee*Ae,Zt=te[pt+T+1],st=te[pt+T+1+P];e:for(var lt=0;lt>>1;u(k,Ae);for(var Fe=0,me=0;me=c)h[Fe++]=ie-c;else{ie-=1;var ge=te[ie],Re=_e*ie,ce=H[Re+T+1],Ze=H[Re+T+1+P];e:for(var ut=0;ut=0;--ut)if(h[ut]===ie){for(var lt=ut+1;lt max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec3 lowerBound, upperBound; +uniform float contourTint; +uniform vec4 contourColor; +uniform sampler2D colormap; +uniform vec3 clipBounds[2]; +uniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity; +uniform float vertexColor; + +varying float value, kill; +varying vec3 worldCoordinate; +varying vec3 lightDirection, eyeDirection, surfaceNormal; +varying vec4 vColor; + +void main() { + if ( + kill > 0.0 || + vColor.a == 0.0 || + outOfRange(clipBounds[0], clipBounds[1], worldCoordinate) + ) discard; + + vec3 N = normalize(surfaceNormal); + vec3 V = normalize(eyeDirection); + vec3 L = normalize(lightDirection); + + if(gl_FrontFacing) { + N = -N; + } + + float specular = max(beckmannSpecular(L, V, N, roughness), 0.); + float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0); + + //decide how to interpolate color \u2014 in vertex or in fragment + vec4 surfaceColor = + step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) + + step(.5, vertexColor) * vColor; + + vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0); + + gl_FragColor = mix(litColor, contourColor, contourTint) * opacity; +} +`]),f=l([`precision highp float; +#define GLSLIFY 1 + +attribute vec4 uv; +attribute float f; + +uniform vec3 objectOffset; +uniform mat3 permutation; +uniform mat4 model, view, projection; +uniform float height, zOffset; +uniform sampler2D colormap; + +varying float value, kill; +varying vec3 worldCoordinate; +varying vec2 planeCoordinate; +varying vec3 lightDirection, eyeDirection, surfaceNormal; +varying vec4 vColor; + +void main() { + vec3 dataCoordinate = permutation * vec3(uv.xy, height); + worldCoordinate = objectOffset + dataCoordinate; + mat4 objectOffsetTranslation = mat4(1.0) + mat4(vec4(0), vec4(0), vec4(0), vec4(objectOffset, 0)); + vec4 worldPosition = (model * objectOffsetTranslation) * vec4(dataCoordinate, 1.0); + + vec4 clipPosition = projection * (view * worldPosition); + clipPosition.z += zOffset; + + gl_Position = clipPosition; + value = f + objectOffset.z; + kill = -1.0; + planeCoordinate = uv.zw; + + vColor = texture2D(colormap, vec2(value, value)); + + //Don't do lighting for contours + surfaceNormal = vec3(1,0,0); + eyeDirection = vec3(0,1,0); + lightDirection = vec3(0,0,1); +} +`]),h=l([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec2 shape; +uniform vec3 clipBounds[2]; +uniform float pickId; + +varying float value, kill; +varying vec3 worldCoordinate; +varying vec2 planeCoordinate; +varying vec3 surfaceNormal; + +vec2 splitFloat(float v) { + float vh = 255.0 * v; + float upper = floor(vh); + float lower = fract(vh); + return vec2(upper / 255.0, floor(lower * 16.0) / 16.0); +} + +void main() { + if ((kill > 0.0) || + (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard; + + vec2 ux = splitFloat(planeCoordinate.x / shape.x); + vec2 uy = splitFloat(planeCoordinate.y / shape.y); + gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0)); +} +`]);a.createShader=function(d){var v=s(d,u,c,null,[{name:"uv",type:"vec4"},{name:"f",type:"vec3"},{name:"normal",type:"vec3"}]);return v.attributes.uv.location=0,v.attributes.f.location=1,v.attributes.normal.location=2,v},a.createPickShader=function(d){var v=s(d,u,h,null,[{name:"uv",type:"vec4"},{name:"f",type:"vec3"},{name:"normal",type:"vec3"}]);return v.attributes.uv.location=0,v.attributes.f.location=1,v.attributes.normal.location=2,v},a.createContourShader=function(d){var v=s(d,f,c,null,[{name:"uv",type:"vec4"},{name:"f",type:"float"}]);return v.attributes.uv.location=0,v.attributes.f.location=1,v},a.createPickContourShader=function(d){var v=s(d,f,h,null,[{name:"uv",type:"vec4"},{name:"f",type:"float"}]);return v.attributes.uv.location=0,v.attributes.f.location=1,v}},1085:function(i,a,o){var s=o(1371);i.exports=l;function l(u,c,f){c=typeof c=="number"?c:1,f=f||": ";var h=u.split(/\r?\n/),d=String(h.length+c-1).length;return h.map(function(v,_){var b=_+c,p=String(b).length,k=s(b,d-p);return k+f+v}).join(` 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outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +attribute vec3 position; +attribute vec4 color; +attribute vec2 glyph; +attribute vec4 id; + +uniform vec4 highlightId; +uniform float highlightScale; +uniform mat4 model, view, projection; +uniform vec3 clipBounds[2]; + +varying vec4 interpColor; +varying vec4 pickId; +varying vec3 dataCoordinate; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], position)) { + + gl_Position = vec4(0,0,0,0); + } else { + float scale = 1.0; + if(distance(highlightId, id) < 0.0001) { + scale = highlightScale; + } + + vec4 worldPosition = model * vec4(position, 1); + vec4 viewPosition = view * worldPosition; + viewPosition = viewPosition / viewPosition.w; + vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0)); + + gl_Position = clipPosition; + interpColor = color; + pickId = id; + dataCoordinate = position; + } +}`]),c=l([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +attribute vec3 position; +attribute vec4 color; +attribute vec2 glyph; +attribute vec4 id; + +uniform mat4 model, view, projection; +uniform vec2 screenSize; +uniform vec3 clipBounds[2]; +uniform float highlightScale, pixelRatio; +uniform vec4 highlightId; + +varying vec4 interpColor; +varying vec4 pickId; +varying vec3 dataCoordinate; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], position)) { + + gl_Position = vec4(0,0,0,0); + } else { + float scale = pixelRatio; + if(distance(highlightId.bgr, id.bgr) < 0.001) { + scale *= highlightScale; + } + + vec4 worldPosition = model * vec4(position, 1.0); + vec4 viewPosition = view * worldPosition; + vec4 clipPosition = projection * viewPosition; + clipPosition /= clipPosition.w; + + gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0); + interpColor = color; + pickId = id; + dataCoordinate = position; + } +}`]),f=l([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +attribute vec3 position; +attribute vec4 color; +attribute vec2 glyph; +attribute vec4 id; + +uniform float highlightScale; +uniform vec4 highlightId; +uniform vec3 axes[2]; +uniform mat4 model, view, projection; +uniform vec2 screenSize; +uniform vec3 clipBounds[2]; +uniform float scale, pixelRatio; + +varying vec4 interpColor; +varying vec4 pickId; +varying vec3 dataCoordinate; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], position)) { + + gl_Position = vec4(0,0,0,0); + } else { + float lscale = pixelRatio * scale; + if(distance(highlightId, id) < 0.0001) { + lscale *= highlightScale; + } + + vec4 clipCenter = projection * (view * (model * vec4(position, 1))); + vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y; + vec4 clipPosition = projection * (view * (model * vec4(dataPosition, 1))); + + gl_Position = clipPosition; + interpColor = color; + pickId = id; + dataCoordinate = dataPosition; + } +} +`]),h=l([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec3 fragClipBounds[2]; +uniform float opacity; + +varying vec4 interpColor; +varying vec3 dataCoordinate; + +void main() { + if ( + outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) || + interpColor.a * opacity == 0. + ) discard; + gl_FragColor = interpColor * opacity; +} +`]),d=l([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec3 fragClipBounds[2]; +uniform float pickGroup; + +varying vec4 pickId; +varying vec3 dataCoordinate; + +void main() { + if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard; + + gl_FragColor = vec4(pickGroup, pickId.bgr); +}`]),v=[{name:"position",type:"vec3"},{name:"color",type:"vec4"},{name:"glyph",type:"vec2"},{name:"id",type:"vec4"}],_={vertex:u,fragment:h,attributes:v},b={vertex:c,fragment:h,attributes:v},p={vertex:f,fragment:h,attributes:v},k={vertex:u,fragment:d,attributes:v},E={vertex:c,fragment:d,attributes:v},S={vertex:f,fragment:d,attributes:v};function L(x,C){var M=s(x,C),g=M.attributes;return g.position.location=0,g.color.location=1,g.glyph.location=2,g.id.location=3,M}a.createPerspective=function(x){return L(x,_)},a.createOrtho=function(x){return L(x,b)},a.createProject=function(x){return L(x,p)},a.createPickPerspective=function(x){return L(x,k)},a.createPickOrtho=function(x){return L(x,E)},a.createPickProject=function(x){return L(x,S)}},1303:function(i,a,o){"use strict";i.exports=u;var s=o(3250);function l(c,f){var h,d;if(f[0][0]f[1][0])h=f[1],d=f[0];else{var v=Math.min(c[0][1],c[1][1]),_=Math.max(c[0][1],c[1][1]),b=Math.min(f[0][1],f[1][1]),p=Math.max(f[0][1],f[1][1]);return 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k;_>1,E=f[2*k+1];if(E===_)return k;_ HALF_PI) && (b <= ONE_AND_HALF_PI)) ? + b - PI : + b; +} + +float look_horizontal_or_vertical(float a, float ratio) { + // ratio controls the ratio between being horizontal to (vertical + horizontal) + // if ratio is set to 0.5 then it is 50%, 50%. + // when using a higher ratio e.g. 0.75 the result would + // likely be more horizontal than vertical. + + float b = positive_angle(a); + + return + (b < ( ratio) * HALF_PI) ? 0.0 : + (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI : + (b < (2.0 + ratio) * HALF_PI) ? 0.0 : + (b < (4.0 - ratio) * HALF_PI) ? HALF_PI : + 0.0; +} + +float roundTo(float a, float b) { + return float(b * floor((a + 0.5 * b) / b)); +} + +float look_round_n_directions(float a, int n) { + float b = positive_angle(a); + float div = TWO_PI / float(n); + float c = roundTo(b, div); + return look_upwards(c); +} + +float applyAlignOption(float rawAngle, float delta) { + return + (option > 2) ? look_round_n_directions(rawAngle + delta, option) : // option 3-n: round to n directions + (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical + (option == 1) ? rawAngle + delta : // use free angle, and flip to align with one direction of the axis + (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards + (option ==-1) ? 0.0 : // useful for backward compatibility, all texts remains horizontal + rawAngle; // otherwise return back raw input angle +} + +bool isAxisTitle = (axis.x == 0.0) && + (axis.y == 0.0) && + (axis.z == 0.0); + +void main() { + //Compute world offset + float axisDistance = position.z; + vec3 dataPosition = axisDistance * axis + offset; + + float beta = angle; // i.e. user defined attributes for each tick + + float axisAngle; + float clipAngle; + float flip; + + if (enableAlign) { + axisAngle = (isAxisTitle) ? HALF_PI : + computeViewAngle(dataPosition, dataPosition + axis); + clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir); + + axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0; + clipAngle += (sin(clipAngle) < 0.0) ? 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Se=[{family:this.labelFont[0],style:this.labelFontStyle[0],weight:this.labelFontWeight[0],variant:this.labelFontVariant[0]},{family:this.labelFont[1],style:this.labelFontStyle[1],weight:this.labelFontWeight[1],variant:this.labelFontVariant[1]},{family:this.labelFont[2],style:this.labelFontStyle[2],weight:this.labelFontWeight[2],variant:this.labelFontVariant[2]}],Le=[{family:this.tickFont[0],style:this.tickFontStyle[0],weight:this.tickFontWeight[0],variant:this.tickFontVariant[0]},{family:this.tickFont[1],style:this.tickFontStyle[1],weight:this.tickFontWeight[1],variant:this.tickFontVariant[1]},{family:this.tickFont[2],style:this.tickFontStyle[2],weight:this.tickFontWeight[2],variant:this.tickFontVariant[2]}];this._text?this._text&&(ie||oe)&&this._text.update(this.bounds,this.labels,Se,this.ticks,Le):this._text=s(this.gl,this.bounds,this.labels,Se,this.ticks,Le),this._lines&&oe&&(this._lines.dispose(),this._lines=null),this._lines||(this._lines=l(this.gl,this.bounds,this.ticks))};function S(){this.primalOffset=[0,0,0],this.primalMinor=[0,0,0],this.mirrorOffset=[0,0,0],this.mirrorMinor=[0,0,0]}var L=[new S,new S,new S];function x(V,G,Z,j,N){for(var H=V.primalOffset,te=V.primalMinor,oe=V.mirrorOffset,_e=V.mirrorMinor,Ee=j[G],Ce=0;Ce<3;++Ce)if(G!==Ce){var me=H,ie=oe,Se=te,Le=_e;Ee&1<0?(Se[Ce]=-1,Le[Ce]=0):(Se[Ce]=0,Le[Ce]=1)}}var C=[0,0,0],M={model:h,view:h,projection:h,_ortho:!1};E.isOpaque=function(){return!0},E.isTransparent=function(){return!1},E.drawTransparent=function(V){};var g=0,P=[0,0,0],T=[0,0,0],z=[0,0,0];E.draw=function(V){V=V||M;for(var Pe=this.gl,G=V.model||h,Z=V.view||h,j=V.projection||h,N=this.bounds,H=V._ortho||!1,te=c(G,Z,j,N,H),oe=te.cubeEdges,_e=te.axis,Ee=Z[12],Ce=Z[13],me=Z[14],ie=Z[15],Se=H?2:1,Le=Se*this.pixelRatio*(j[3]*Ee+j[7]*Ce+j[11]*me+j[15]*ie)/Pe.drawingBufferHeight,Ae=0;Ae<3;++Ae)this.lastCubeProps.cubeEdges[Ae]=oe[Ae],this.lastCubeProps.axis[Ae]=_e[Ae];for(var Fe=L,Ae=0;Ae<3;++Ae)x(L[Ae],Ae,this.bounds,oe,_e);for(var Pe=this.gl,ge=C,Ae=0;Ae<3;++Ae)this.backgroundEnable[Ae]?ge[Ae]=_e[Ae]:ge[Ae]=0;this._background.draw(G,Z,j,N,ge,this.backgroundColor),this._lines.bind(G,Z,j,this);for(var Ae=0;Ae<3;++Ae){var Re=[0,0,0];_e[Ae]>0?Re[Ae]=N[1][Ae]:Re[Ae]=N[0][Ae];for(var ce=0;ce<2;++ce){var Ze=(Ae+1+ce)%3,ut=(Ae+1+(ce^1))%3;this.gridEnable[Ze]&&this._lines.drawGrid(Ze,ut,this.bounds,Re,this.gridColor[Ze],this.gridWidth[Ze]*this.pixelRatio)}for(var ce=0;ce<2;++ce){var Ze=(Ae+1+ce)%3,ut=(Ae+1+(ce^1))%3;this.zeroEnable[ut]&&Math.min(N[0][ut],N[1][ut])<=0&&Math.max(N[0][ut],N[1][ut])>=0&&this._lines.drawZero(Ze,ut,this.bounds,Re,this.zeroLineColor[ut],this.zeroLineWidth[ut]*this.pixelRatio)}}for(var Ae=0;Ae<3;++Ae){this.lineEnable[Ae]&&this._lines.drawAxisLine(Ae,this.bounds,Fe[Ae].primalOffset,this.lineColor[Ae],this.lineWidth[Ae]*this.pixelRatio),this.lineMirror[Ae]&&this._lines.drawAxisLine(Ae,this.bounds,Fe[Ae].mirrorOffset,this.lineColor[Ae],this.lineWidth[Ae]*this.pixelRatio);for(var pt=p(P,Fe[Ae].primalMinor),Zt=p(T,Fe[Ae].mirrorMinor),st=this.lineTickLength,ce=0;ce<3;++ce){var lt=Le/G[5*ce];pt[ce]*=st[ce]*lt,Zt[ce]*=st[ce]*lt}this.lineTickEnable[Ae]&&this._lines.drawAxisTicks(Ae,Fe[Ae].primalOffset,pt,this.lineTickColor[Ae],this.lineTickWidth[Ae]*this.pixelRatio),this.lineTickMirror[Ae]&&this._lines.drawAxisTicks(Ae,Fe[Ae].mirrorOffset,Zt,this.lineTickColor[Ae],this.lineTickWidth[Ae]*this.pixelRatio)}this._lines.unbind(),this._text.bind(G,Z,j,this.pixelRatio);var Gt,Nt=.5,Jt,sr;function wr(_t){sr=[0,0,0],sr[_t]=1}function cr(_t,It,mt){var er=(_t+1)%3,lr=(_t+2)%3,Tr=It[er],Lr=It[lr],ti=mt[er],Br=mt[lr];if(Tr>0&&Br>0){wr(er);return}else if(Tr>0&&Br<0){wr(er);return}else if(Tr<0&&Br>0){wr(er);return}else if(Tr<0&&Br<0){wr(er);return}else if(Lr>0&&ti>0){wr(lr);return}else if(Lr>0&&ti<0){wr(lr);return}else if(Lr<0&&ti>0){wr(lr);return}else if(Lr<0&&ti<0){wr(lr);return}}for(var Ae=0;Ae<3;++Ae){for(var $e=Fe[Ae].primalMinor,St=Fe[Ae].mirrorMinor,Qt=p(z,Fe[Ae].primalOffset),ce=0;ce<3;++ce)this.lineTickEnable[Ae]&&(Qt[ce]+=Le*$e[ce]*Math.max(this.lineTickLength[ce],0)/G[5*ce]);var Vt=[0,0,0];if(Vt[Ae]=1,this.tickEnable[Ae]){this.tickAngle[Ae]===-3600?(this.tickAngle[Ae]=0,this.tickAlign[Ae]="auto"):this.tickAlign[Ae]=-1,Jt=1,Gt=[this.tickAlign[Ae],Nt,Jt],Gt[0]==="auto"?Gt[0]=g:Gt[0]=parseInt(""+Gt[0]),sr=[0,0,0],cr(Ae,$e,St);for(var ce=0;ce<3;++ce)Qt[ce]+=Le*$e[ce]*this.tickPad[ce]/G[5*ce];this._text.drawTicks(Ae,this.tickSize[Ae],this.tickAngle[Ae],Qt,this.tickColor[Ae],Vt,sr,Gt)}if(this.labelEnable[Ae]){Jt=0,sr=[0,0,0],this.labels[Ae].length>4&&(wr(Ae),Jt=1),Gt=[this.labelAlign[Ae],Nt,Jt],Gt[0]==="auto"?Gt[0]=g:Gt[0]=parseInt(""+Gt[0]);for(var ce=0;ce<3;++ce)Qt[ce]+=Le*$e[ce]*this.labelPad[ce]/G[5*ce];Qt[Ae]+=.5*(N[0][Ae]+N[1][Ae]),this._text.drawLabel(Ae,this.labelSize[Ae],this.labelAngle[Ae],Qt,this.labelColor[Ae],[0,0,0],sr,Gt)}}this._text.unbind()},E.dispose=function(){this._text.dispose(),this._lines.dispose(),this._background.dispose(),this._lines=null,this._text=null,this._background=null,this.gl=null};function O(V,G){var Z=new k(V);return Z.update(G),Z}},3840:function(i){"use strict";i.exports=L;var a=0,o=1;function s(x,C,M,g,P,T){this._color=x,this.key=C,this.value=M,this.left=g,this.right=P,this._count=T}function l(x){return new s(x._color,x.key,x.value,x.left,x.right,x._count)}function u(x,C){return new s(x,C.key,C.value,C.left,C.right,C._count)}function c(x){x._count=1+(x.left?x.left._count:0)+(x.right?x.right._count:0)}function f(x,C){this._compare=x,this.root=C}var h=f.prototype;Object.defineProperty(h,"keys",{get:function(){var x=[];return 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g=d,P=v,T=0;T<3;++T)M&&M[T]<0?(g[T]=this.bounds[0][T],P[T]=this.bounds[1][T]):(g[T]=this.bounds[1][T],P[T]=this.bounds[0][T]);_[0]=k.drawingBufferWidth,_[1]=k.drawingBufferHeight,S.uniforms.model=L,S.uniforms.view=x,S.uniforms.projection=C,S.uniforms.coordinates=[this.position,g,P],S.uniforms.colors=this.colors,S.uniforms.screenShape=_;for(var T=0;T<3;++T)S.uniforms.lineWidth=this.lineWidth[T]*this.pixelRatio,this.enabled[T]&&(E.draw(k.TRIANGLES,6,6*T),this.drawSides[T]&&E.draw(k.TRIANGLES,12,18+12*T));E.unbind()},h.update=function(p){p&&("bounds"in p&&(this.bounds=p.bounds),"position"in p&&(this.position=p.position),"lineWidth"in p&&(this.lineWidth=p.lineWidth),"colors"in p&&(this.colors=p.colors),"enabled"in p&&(this.enabled=p.enabled),"drawSides"in p&&(this.drawSides=p.drawSides))},h.dispose=function(){this.vao.dispose(),this.buffer.dispose(),this.shader.dispose()};function b(p,k){var E=[];function S(g,P,T,z,O,V){var 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inverseModel; +uniform vec3 eyePosition, lightPosition; + +varying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position; +varying vec4 f_color; +varying vec2 f_uv; + +void main() { + // Scale the vector magnitude to stay constant with + // model & view changes. + vec3 normal; + vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal); + vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0); + + //Lighting geometry parameters + vec4 cameraCoordinate = view * tubePosition; + cameraCoordinate.xyz /= cameraCoordinate.w; + f_lightDirection = lightPosition - cameraCoordinate.xyz; + f_eyeDirection = eyePosition - cameraCoordinate.xyz; + f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz); + + // vec4 m_position = model * vec4(tubePosition, 1.0); + vec4 t_position = view * tubePosition; + gl_Position = projection * t_position; + + f_color = color; + f_data = tubePosition.xyz; + f_position = position.xyz; 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+varying vec4 f_color; +varying vec2 f_uv; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard; + vec3 N = normalize(f_normal); + vec3 L = normalize(f_lightDirection); + vec3 V = normalize(f_eyeDirection); + + if(gl_FrontFacing) { + N = -N; + } + + float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel))); + float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0); + + vec4 surfaceColor = f_color * texture2D(texture, f_uv); + vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0); + + gl_FragColor = litColor * opacity; +} +`]),c=s([`precision highp float; + +precision highp float; +#define GLSLIFY 1 + +vec3 getOrthogonalVector(vec3 v) { + // Return up-vector for only-z vector. + // Return ax + by + cz = 0, a point that lies on the plane that has v as a normal and that isn't (0,0,0). + // From the above if-statement we have ||a|| > 0 U ||b|| > 0. + // Assign z = 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oe=0;oe=H;oe-=2)Ce=v(N,H,oe)<<_e,this.words[Ee]|=Ce&67108863,_e>=18?(_e-=18,Ee+=1,this.words[Ee]|=Ce>>>26):_e+=8;else{var me=N.length-H;for(oe=me%2===0?H+1:H;oe=18?(_e-=18,Ee+=1,this.words[Ee]|=Ce>>>26):_e+=8}this.strip()};function _(j,N,H,te){for(var oe=0,_e=Math.min(j.length,H),Ee=N;Ee<_e;Ee++){var Ce=j.charCodeAt(Ee)-48;oe*=te,Ce>=49?oe+=Ce-49+10:Ce>=17?oe+=Ce-17+10:oe+=Ce}return oe}f.prototype._parseBase=function(N,H,te){this.words=[0],this.length=1;for(var oe=0,_e=1;_e<=67108863;_e*=H)oe++;oe--,_e=_e/H|0;for(var Ee=N.length-te,Ce=Ee%oe,me=Math.min(Ee,Ee-Ce)+te,ie=0,Se=te;Se1&&this.words[this.length-1]===0;)this.length--;return this._normSign()},f.prototype._normSign=function(){return this.length===1&&this.words[0]===0&&(this.negative=0),this},f.prototype.inspect=function(){return(this.red?""};var b=["","0","00","000","0000","00000","000000","0000000","00000000","000000000","0000000000","00000000000","000000000000","0000000000000","00000000000000","000000000000000","0000000000000000","00000000000000000","000000000000000000","0000000000000000000","00000000000000000000","000000000000000000000","0000000000000000000000","00000000000000000000000","000000000000000000000000","0000000000000000000000000"],p=[0,0,25,16,12,11,10,9,8,8,7,7,7,7,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5],k=[0,0,33554432,43046721,16777216,48828125,60466176,40353607,16777216,43046721,1e7,19487171,35831808,62748517,7529536,11390625,16777216,24137569,34012224,47045881,64e6,4084101,5153632,6436343,7962624,9765625,11881376,14348907,17210368,20511149,243e5,28629151,33554432,39135393,45435424,52521875,60466176];f.prototype.toString=function(N,H){N=N||10,H=H|0||1;var te;if(N===16||N==="hex"){te="";for(var oe=0,_e=0,Ee=0;Ee>>24-oe&16777215,_e!==0||Ee!==this.length-1?te=b[6-me.length]+me+te:te=me+te,oe+=2,oe>=26&&(oe-=26,Ee--)}for(_e!==0&&(te=_e.toString(16)+te);te.length%H!==0;)te="0"+te;return this.negative!==0&&(te="-"+te),te}if(N===(N|0)&&N>=2&&N<=36){var ie=p[N],Se=k[N];te="";var Le=this.clone();for(Le.negative=0;!Le.isZero();){var Ae=Le.modn(Se).toString(N);Le=Le.idivn(Se),Le.isZero()?te=Ae+te:te=b[ie-Ae.length]+Ae+te}for(this.isZero()&&(te="0"+te);te.length%H!==0;)te="0"+te;return this.negative!==0&&(te="-"+te),te}u(!1,"Base should be between 2 and 36")},f.prototype.toNumber=function(){var N=this.words[0];return this.length===2?N+=this.words[1]*67108864:this.length===3&&this.words[2]===1?N+=4503599627370496+this.words[1]*67108864:this.length>2&&u(!1,"Number can only safely store up to 53 bits"),this.negative!==0?-N:N},f.prototype.toJSON=function(){return this.toString(16)},f.prototype.toBuffer=function(N,H){return u(typeof h!="undefined"),this.toArrayLike(h,N,H)},f.prototype.toArray=function(N,H){return this.toArrayLike(Array,N,H)},f.prototype.toArrayLike=function(N,H,te){var oe=this.byteLength(),_e=te||Math.max(1,oe);u(oe<=_e,"byte array longer than desired length"),u(_e>0,"Requested array length <= 0"),this.strip();var Ee=H==="le",Ce=new N(_e),me,ie,Se=this.clone();if(Ee){for(ie=0;!Se.isZero();ie++)me=Se.andln(255),Se.iushrn(8),Ce[ie]=me;for(;ie<_e;ie++)Ce[ie]=0}else{for(ie=0;ie<_e-oe;ie++)Ce[ie]=0;for(ie=0;!Se.isZero();ie++)me=Se.andln(255),Se.iushrn(8),Ce[_e-ie-1]=me}return Ce},Math.clz32?f.prototype._countBits=function(N){return 32-Math.clz32(N)}:f.prototype._countBits=function(N){var H=N,te=0;return H>=4096&&(te+=13,H>>>=13),H>=64&&(te+=7,H>>>=7),H>=8&&(te+=4,H>>>=4),H>=2&&(te+=2,H>>>=2),te+H},f.prototype._zeroBits=function(N){if(N===0)return 26;var H=N,te=0;return(H&8191)===0&&(te+=13,H>>>=13),(H&127)===0&&(te+=7,H>>>=7),(H&15)===0&&(te+=4,H>>>=4),(H&3)===0&&(te+=2,H>>>=2),(H&1)===0&&te++,te},f.prototype.bitLength=function(){var N=this.words[this.length-1],H=this._countBits(N);return(this.length-1)*26+H};function E(j){for(var N=new Array(j.bitLength()),H=0;H>>oe}return N}f.prototype.zeroBits=function(){if(this.isZero())return 0;for(var N=0,H=0;HN.length?this.clone().ior(N):N.clone().ior(this)},f.prototype.uor=function(N){return this.length>N.length?this.clone().iuor(N):N.clone().iuor(this)},f.prototype.iuand=function(N){var H;this.length>N.length?H=N:H=this;for(var te=0;teN.length?this.clone().iand(N):N.clone().iand(this)},f.prototype.uand=function(N){return this.length>N.length?this.clone().iuand(N):N.clone().iuand(this)},f.prototype.iuxor=function(N){var H,te;this.length>N.length?(H=this,te=N):(H=N,te=this);for(var oe=0;oeN.length?this.clone().ixor(N):N.clone().ixor(this)},f.prototype.uxor=function(N){return this.length>N.length?this.clone().iuxor(N):N.clone().iuxor(this)},f.prototype.inotn=function(N){u(typeof N=="number"&&N>=0);var H=Math.ceil(N/26)|0,te=N%26;this._expand(H),te>0&&H--;for(var oe=0;oe0&&(this.words[oe]=~this.words[oe]&67108863>>26-te),this.strip()},f.prototype.notn=function(N){return this.clone().inotn(N)},f.prototype.setn=function(N,H){u(typeof N=="number"&&N>=0);var te=N/26|0,oe=N%26;return this._expand(te+1),H?this.words[te]=this.words[te]|1<N.length?(te=this,oe=N):(te=N,oe=this);for(var _e=0,Ee=0;Ee>>26;for(;_e!==0&&Ee>>26;if(this.length=te.length,_e!==0)this.words[this.length]=_e,this.length++;else if(te!==this)for(;EeN.length?this.clone().iadd(N):N.clone().iadd(this)},f.prototype.isub=function(N){if(N.negative!==0){N.negative=0;var H=this.iadd(N);return N.negative=1,H._normSign()}else if(this.negative!==0)return this.negative=0,this.iadd(N),this.negative=1,this._normSign();var te=this.cmp(N);if(te===0)return this.negative=0,this.length=1,this.words[0]=0,this;var oe,_e;te>0?(oe=this,_e=N):(oe=N,_e=this);for(var Ee=0,Ce=0;Ce<_e.length;Ce++)H=(oe.words[Ce]|0)-(_e.words[Ce]|0)+Ee,Ee=H>>26,this.words[Ce]=H&67108863;for(;Ee!==0&&Ce>26,this.words[Ce]=H&67108863;if(Ee===0&&Ce>>26,Le=me&67108863,Ae=Math.min(ie,N.length-1),Fe=Math.max(0,ie-j.length+1);Fe<=Ae;Fe++){var Pe=ie-Fe|0;oe=j.words[Pe]|0,_e=N.words[Fe]|0,Ee=oe*_e+Le,Se+=Ee/67108864|0,Le=Ee&67108863}H.words[ie]=Le|0,me=Se|0}return me!==0?H.words[ie]=me|0:H.length--,H.strip()}var L=function(N,H,te){var oe=N.words,_e=H.words,Ee=te.words,Ce=0,me,ie,Se,Le=oe[0]|0,Ae=Le&8191,Fe=Le>>>13,Pe=oe[1]|0,ge=Pe&8191,Re=Pe>>>13,ce=oe[2]|0,Ze=ce&8191,ut=ce>>>13,pt=oe[3]|0,Zt=pt&8191,st=pt>>>13,lt=oe[4]|0,Gt=lt&8191,Nt=lt>>>13,Jt=oe[5]|0,sr=Jt&8191,wr=Jt>>>13,cr=oe[6]|0,$e=cr&8191,St=cr>>>13,Qt=oe[7]|0,Vt=Qt&8191,_t=Qt>>>13,It=oe[8]|0,mt=It&8191,er=It>>>13,lr=oe[9]|0,Tr=lr&8191,Lr=lr>>>13,ti=_e[0]|0,Br=ti&8191,Vr=ti>>>13,dt=_e[1]|0,Ge=dt&8191,Je=dt>>>13,je=_e[2]|0,tt=je&8191,xt=je>>>13,Ie=_e[3]|0,xe=Ie&8191,ke=Ie>>>13,vt=_e[4]|0,ir=vt&8191,ar=vt>>>13,vr=_e[5]|0,ii=vr&8191,pi=vr>>>13,$r=_e[6]|0,di=$r&8191,ji=$r>>>13,In=_e[7]|0,wi=In&8191,On=In>>>13,qn=_e[8]|0,Fn=qn&8191,ra=qn>>>13,la=_e[9]|0,Ut=la&8191,wt=la>>>13;te.negative=N.negative^H.negative,te.length=19,me=Math.imul(Ae,Br),ie=Math.imul(Ae,Vr),ie=ie+Math.imul(Fe,Br)|0,Se=Math.imul(Fe,Vr);var rr=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(rr>>>26)|0,rr&=67108863,me=Math.imul(ge,Br),ie=Math.imul(ge,Vr),ie=ie+Math.imul(Re,Br)|0,Se=Math.imul(Re,Vr),me=me+Math.imul(Ae,Ge)|0,ie=ie+Math.imul(Ae,Je)|0,ie=ie+Math.imul(Fe,Ge)|0,Se=Se+Math.imul(Fe,Je)|0;var nr=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(nr>>>26)|0,nr&=67108863,me=Math.imul(Ze,Br),ie=Math.imul(Ze,Vr),ie=ie+Math.imul(ut,Br)|0,Se=Math.imul(ut,Vr),me=me+Math.imul(ge,Ge)|0,ie=ie+Math.imul(ge,Je)|0,ie=ie+Math.imul(Re,Ge)|0,Se=Se+Math.imul(Re,Je)|0,me=me+Math.imul(Ae,tt)|0,ie=ie+Math.imul(Ae,xt)|0,ie=ie+Math.imul(Fe,tt)|0,Se=Se+Math.imul(Fe,xt)|0;var Er=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Er>>>26)|0,Er&=67108863,me=Math.imul(Zt,Br),ie=Math.imul(Zt,Vr),ie=ie+Math.imul(st,Br)|0,Se=Math.imul(st,Vr),me=me+Math.imul(Ze,Ge)|0,ie=ie+Math.imul(Ze,Je)|0,ie=ie+Math.imul(ut,Ge)|0,Se=Se+Math.imul(ut,Je)|0,me=me+Math.imul(ge,tt)|0,ie=ie+Math.imul(ge,xt)|0,ie=ie+Math.imul(Re,tt)|0,Se=Se+Math.imul(Re,xt)|0,me=me+Math.imul(Ae,xe)|0,ie=ie+Math.imul(Ae,ke)|0,ie=ie+Math.imul(Fe,xe)|0,Se=Se+Math.imul(Fe,ke)|0;var Xr=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Xr>>>26)|0,Xr&=67108863,me=Math.imul(Gt,Br),ie=Math.imul(Gt,Vr),ie=ie+Math.imul(Nt,Br)|0,Se=Math.imul(Nt,Vr),me=me+Math.imul(Zt,Ge)|0,ie=ie+Math.imul(Zt,Je)|0,ie=ie+Math.imul(st,Ge)|0,Se=Se+Math.imul(st,Je)|0,me=me+Math.imul(Ze,tt)|0,ie=ie+Math.imul(Ze,xt)|0,ie=ie+Math.imul(ut,tt)|0,Se=Se+Math.imul(ut,xt)|0,me=me+Math.imul(ge,xe)|0,ie=ie+Math.imul(ge,ke)|0,ie=ie+Math.imul(Re,xe)|0,Se=Se+Math.imul(Re,ke)|0,me=me+Math.imul(Ae,ir)|0,ie=ie+Math.imul(Ae,ar)|0,ie=ie+Math.imul(Fe,ir)|0,Se=Se+Math.imul(Fe,ar)|0;var ri=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(ri>>>26)|0,ri&=67108863,me=Math.imul(sr,Br),ie=Math.imul(sr,Vr),ie=ie+Math.imul(wr,Br)|0,Se=Math.imul(wr,Vr),me=me+Math.imul(Gt,Ge)|0,ie=ie+Math.imul(Gt,Je)|0,ie=ie+Math.imul(Nt,Ge)|0,Se=Se+Math.imul(Nt,Je)|0,me=me+Math.imul(Zt,tt)|0,ie=ie+Math.imul(Zt,xt)|0,ie=ie+Math.imul(st,tt)|0,Se=Se+Math.imul(st,xt)|0,me=me+Math.imul(Ze,xe)|0,ie=ie+Math.imul(Ze,ke)|0,ie=ie+Math.imul(ut,xe)|0,Se=Se+Math.imul(ut,ke)|0,me=me+Math.imul(ge,ir)|0,ie=ie+Math.imul(ge,ar)|0,ie=ie+Math.imul(Re,ir)|0,Se=Se+Math.imul(Re,ar)|0,me=me+Math.imul(Ae,ii)|0,ie=ie+Math.imul(Ae,pi)|0,ie=ie+Math.imul(Fe,ii)|0,Se=Se+Math.imul(Fe,pi)|0;var Qr=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Qr>>>26)|0,Qr&=67108863,me=Math.imul($e,Br),ie=Math.imul($e,Vr),ie=ie+Math.imul(St,Br)|0,Se=Math.imul(St,Vr),me=me+Math.imul(sr,Ge)|0,ie=ie+Math.imul(sr,Je)|0,ie=ie+Math.imul(wr,Ge)|0,Se=Se+Math.imul(wr,Je)|0,me=me+Math.imul(Gt,tt)|0,ie=ie+Math.imul(Gt,xt)|0,ie=ie+Math.imul(Nt,tt)|0,Se=Se+Math.imul(Nt,xt)|0,me=me+Math.imul(Zt,xe)|0,ie=ie+Math.imul(Zt,ke)|0,ie=ie+Math.imul(st,xe)|0,Se=Se+Math.imul(st,ke)|0,me=me+Math.imul(Ze,ir)|0,ie=ie+Math.imul(Ze,ar)|0,ie=ie+Math.imul(ut,ir)|0,Se=Se+Math.imul(ut,ar)|0,me=me+Math.imul(ge,ii)|0,ie=ie+Math.imul(ge,pi)|0,ie=ie+Math.imul(Re,ii)|0,Se=Se+Math.imul(Re,pi)|0,me=me+Math.imul(Ae,di)|0,ie=ie+Math.imul(Ae,ji)|0,ie=ie+Math.imul(Fe,di)|0,Se=Se+Math.imul(Fe,ji)|0;var Oi=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Oi>>>26)|0,Oi&=67108863,me=Math.imul(Vt,Br),ie=Math.imul(Vt,Vr),ie=ie+Math.imul(_t,Br)|0,Se=Math.imul(_t,Vr),me=me+Math.imul($e,Ge)|0,ie=ie+Math.imul($e,Je)|0,ie=ie+Math.imul(St,Ge)|0,Se=Se+Math.imul(St,Je)|0,me=me+Math.imul(sr,tt)|0,ie=ie+Math.imul(sr,xt)|0,ie=ie+Math.imul(wr,tt)|0,Se=Se+Math.imul(wr,xt)|0,me=me+Math.imul(Gt,xe)|0,ie=ie+Math.imul(Gt,ke)|0,ie=ie+Math.imul(Nt,xe)|0,Se=Se+Math.imul(Nt,ke)|0,me=me+Math.imul(Zt,ir)|0,ie=ie+Math.imul(Zt,ar)|0,ie=ie+Math.imul(st,ir)|0,Se=Se+Math.imul(st,ar)|0,me=me+Math.imul(Ze,ii)|0,ie=ie+Math.imul(Ze,pi)|0,ie=ie+Math.imul(ut,ii)|0,Se=Se+Math.imul(ut,pi)|0,me=me+Math.imul(ge,di)|0,ie=ie+Math.imul(ge,ji)|0,ie=ie+Math.imul(Re,di)|0,Se=Se+Math.imul(Re,ji)|0,me=me+Math.imul(Ae,wi)|0,ie=ie+Math.imul(Ae,On)|0,ie=ie+Math.imul(Fe,wi)|0,Se=Se+Math.imul(Fe,On)|0;var $i=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+($i>>>26)|0,$i&=67108863,me=Math.imul(mt,Br),ie=Math.imul(mt,Vr),ie=ie+Math.imul(er,Br)|0,Se=Math.imul(er,Vr),me=me+Math.imul(Vt,Ge)|0,ie=ie+Math.imul(Vt,Je)|0,ie=ie+Math.imul(_t,Ge)|0,Se=Se+Math.imul(_t,Je)|0,me=me+Math.imul($e,tt)|0,ie=ie+Math.imul($e,xt)|0,ie=ie+Math.imul(St,tt)|0,Se=Se+Math.imul(St,xt)|0,me=me+Math.imul(sr,xe)|0,ie=ie+Math.imul(sr,ke)|0,ie=ie+Math.imul(wr,xe)|0,Se=Se+Math.imul(wr,ke)|0,me=me+Math.imul(Gt,ir)|0,ie=ie+Math.imul(Gt,ar)|0,ie=ie+Math.imul(Nt,ir)|0,Se=Se+Math.imul(Nt,ar)|0,me=me+Math.imul(Zt,ii)|0,ie=ie+Math.imul(Zt,pi)|0,ie=ie+Math.imul(st,ii)|0,Se=Se+Math.imul(st,pi)|0,me=me+Math.imul(Ze,di)|0,ie=ie+Math.imul(Ze,ji)|0,ie=ie+Math.imul(ut,di)|0,Se=Se+Math.imul(ut,ji)|0,me=me+Math.imul(ge,wi)|0,ie=ie+Math.imul(ge,On)|0,ie=ie+Math.imul(Re,wi)|0,Se=Se+Math.imul(Re,On)|0,me=me+Math.imul(Ae,Fn)|0,ie=ie+Math.imul(Ae,ra)|0,ie=ie+Math.imul(Fe,Fn)|0,Se=Se+Math.imul(Fe,ra)|0;var tn=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(tn>>>26)|0,tn&=67108863,me=Math.imul(Tr,Br),ie=Math.imul(Tr,Vr),ie=ie+Math.imul(Lr,Br)|0,Se=Math.imul(Lr,Vr),me=me+Math.imul(mt,Ge)|0,ie=ie+Math.imul(mt,Je)|0,ie=ie+Math.imul(er,Ge)|0,Se=Se+Math.imul(er,Je)|0,me=me+Math.imul(Vt,tt)|0,ie=ie+Math.imul(Vt,xt)|0,ie=ie+Math.imul(_t,tt)|0,Se=Se+Math.imul(_t,xt)|0,me=me+Math.imul($e,xe)|0,ie=ie+Math.imul($e,ke)|0,ie=ie+Math.imul(St,xe)|0,Se=Se+Math.imul(St,ke)|0,me=me+Math.imul(sr,ir)|0,ie=ie+Math.imul(sr,ar)|0,ie=ie+Math.imul(wr,ir)|0,Se=Se+Math.imul(wr,ar)|0,me=me+Math.imul(Gt,ii)|0,ie=ie+Math.imul(Gt,pi)|0,ie=ie+Math.imul(Nt,ii)|0,Se=Se+Math.imul(Nt,pi)|0,me=me+Math.imul(Zt,di)|0,ie=ie+Math.imul(Zt,ji)|0,ie=ie+Math.imul(st,di)|0,Se=Se+Math.imul(st,ji)|0,me=me+Math.imul(Ze,wi)|0,ie=ie+Math.imul(Ze,On)|0,ie=ie+Math.imul(ut,wi)|0,Se=Se+Math.imul(ut,On)|0,me=me+Math.imul(ge,Fn)|0,ie=ie+Math.imul(ge,ra)|0,ie=ie+Math.imul(Re,Fn)|0,Se=Se+Math.imul(Re,ra)|0,me=me+Math.imul(Ae,Ut)|0,ie=ie+Math.imul(Ae,wt)|0,ie=ie+Math.imul(Fe,Ut)|0,Se=Se+Math.imul(Fe,wt)|0;var fn=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(fn>>>26)|0,fn&=67108863,me=Math.imul(Tr,Ge),ie=Math.imul(Tr,Je),ie=ie+Math.imul(Lr,Ge)|0,Se=Math.imul(Lr,Je),me=me+Math.imul(mt,tt)|0,ie=ie+Math.imul(mt,xt)|0,ie=ie+Math.imul(er,tt)|0,Se=Se+Math.imul(er,xt)|0,me=me+Math.imul(Vt,xe)|0,ie=ie+Math.imul(Vt,ke)|0,ie=ie+Math.imul(_t,xe)|0,Se=Se+Math.imul(_t,ke)|0,me=me+Math.imul($e,ir)|0,ie=ie+Math.imul($e,ar)|0,ie=ie+Math.imul(St,ir)|0,Se=Se+Math.imul(St,ar)|0,me=me+Math.imul(sr,ii)|0,ie=ie+Math.imul(sr,pi)|0,ie=ie+Math.imul(wr,ii)|0,Se=Se+Math.imul(wr,pi)|0,me=me+Math.imul(Gt,di)|0,ie=ie+Math.imul(Gt,ji)|0,ie=ie+Math.imul(Nt,di)|0,Se=Se+Math.imul(Nt,ji)|0,me=me+Math.imul(Zt,wi)|0,ie=ie+Math.imul(Zt,On)|0,ie=ie+Math.imul(st,wi)|0,Se=Se+Math.imul(st,On)|0,me=me+Math.imul(Ze,Fn)|0,ie=ie+Math.imul(Ze,ra)|0,ie=ie+Math.imul(ut,Fn)|0,Se=Se+Math.imul(ut,ra)|0,me=me+Math.imul(ge,Ut)|0,ie=ie+Math.imul(ge,wt)|0,ie=ie+Math.imul(Re,Ut)|0,Se=Se+Math.imul(Re,wt)|0;var yn=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(yn>>>26)|0,yn&=67108863,me=Math.imul(Tr,tt),ie=Math.imul(Tr,xt),ie=ie+Math.imul(Lr,tt)|0,Se=Math.imul(Lr,xt),me=me+Math.imul(mt,xe)|0,ie=ie+Math.imul(mt,ke)|0,ie=ie+Math.imul(er,xe)|0,Se=Se+Math.imul(er,ke)|0,me=me+Math.imul(Vt,ir)|0,ie=ie+Math.imul(Vt,ar)|0,ie=ie+Math.imul(_t,ir)|0,Se=Se+Math.imul(_t,ar)|0,me=me+Math.imul($e,ii)|0,ie=ie+Math.imul($e,pi)|0,ie=ie+Math.imul(St,ii)|0,Se=Se+Math.imul(St,pi)|0,me=me+Math.imul(sr,di)|0,ie=ie+Math.imul(sr,ji)|0,ie=ie+Math.imul(wr,di)|0,Se=Se+Math.imul(wr,ji)|0,me=me+Math.imul(Gt,wi)|0,ie=ie+Math.imul(Gt,On)|0,ie=ie+Math.imul(Nt,wi)|0,Se=Se+Math.imul(Nt,On)|0,me=me+Math.imul(Zt,Fn)|0,ie=ie+Math.imul(Zt,ra)|0,ie=ie+Math.imul(st,Fn)|0,Se=Se+Math.imul(st,ra)|0,me=me+Math.imul(Ze,Ut)|0,ie=ie+Math.imul(Ze,wt)|0,ie=ie+Math.imul(ut,Ut)|0,Se=Se+Math.imul(ut,wt)|0;var Sn=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Sn>>>26)|0,Sn&=67108863,me=Math.imul(Tr,xe),ie=Math.imul(Tr,ke),ie=ie+Math.imul(Lr,xe)|0,Se=Math.imul(Lr,ke),me=me+Math.imul(mt,ir)|0,ie=ie+Math.imul(mt,ar)|0,ie=ie+Math.imul(er,ir)|0,Se=Se+Math.imul(er,ar)|0,me=me+Math.imul(Vt,ii)|0,ie=ie+Math.imul(Vt,pi)|0,ie=ie+Math.imul(_t,ii)|0,Se=Se+Math.imul(_t,pi)|0,me=me+Math.imul($e,di)|0,ie=ie+Math.imul($e,ji)|0,ie=ie+Math.imul(St,di)|0,Se=Se+Math.imul(St,ji)|0,me=me+Math.imul(sr,wi)|0,ie=ie+Math.imul(sr,On)|0,ie=ie+Math.imul(wr,wi)|0,Se=Se+Math.imul(wr,On)|0,me=me+Math.imul(Gt,Fn)|0,ie=ie+Math.imul(Gt,ra)|0,ie=ie+Math.imul(Nt,Fn)|0,Se=Se+Math.imul(Nt,ra)|0,me=me+Math.imul(Zt,Ut)|0,ie=ie+Math.imul(Zt,wt)|0,ie=ie+Math.imul(st,Ut)|0,Se=Se+Math.imul(st,wt)|0;var Ba=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Ba>>>26)|0,Ba&=67108863,me=Math.imul(Tr,ir),ie=Math.imul(Tr,ar),ie=ie+Math.imul(Lr,ir)|0,Se=Math.imul(Lr,ar),me=me+Math.imul(mt,ii)|0,ie=ie+Math.imul(mt,pi)|0,ie=ie+Math.imul(er,ii)|0,Se=Se+Math.imul(er,pi)|0,me=me+Math.imul(Vt,di)|0,ie=ie+Math.imul(Vt,ji)|0,ie=ie+Math.imul(_t,di)|0,Se=Se+Math.imul(_t,ji)|0,me=me+Math.imul($e,wi)|0,ie=ie+Math.imul($e,On)|0,ie=ie+Math.imul(St,wi)|0,Se=Se+Math.imul(St,On)|0,me=me+Math.imul(sr,Fn)|0,ie=ie+Math.imul(sr,ra)|0,ie=ie+Math.imul(wr,Fn)|0,Se=Se+Math.imul(wr,ra)|0,me=me+Math.imul(Gt,Ut)|0,ie=ie+Math.imul(Gt,wt)|0,ie=ie+Math.imul(Nt,Ut)|0,Se=Se+Math.imul(Nt,wt)|0;var ua=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(ua>>>26)|0,ua&=67108863,me=Math.imul(Tr,ii),ie=Math.imul(Tr,pi),ie=ie+Math.imul(Lr,ii)|0,Se=Math.imul(Lr,pi),me=me+Math.imul(mt,di)|0,ie=ie+Math.imul(mt,ji)|0,ie=ie+Math.imul(er,di)|0,Se=Se+Math.imul(er,ji)|0,me=me+Math.imul(Vt,wi)|0,ie=ie+Math.imul(Vt,On)|0,ie=ie+Math.imul(_t,wi)|0,Se=Se+Math.imul(_t,On)|0,me=me+Math.imul($e,Fn)|0,ie=ie+Math.imul($e,ra)|0,ie=ie+Math.imul(St,Fn)|0,Se=Se+Math.imul(St,ra)|0,me=me+Math.imul(sr,Ut)|0,ie=ie+Math.imul(sr,wt)|0,ie=ie+Math.imul(wr,Ut)|0,Se=Se+Math.imul(wr,wt)|0;var ma=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(ma>>>26)|0,ma&=67108863,me=Math.imul(Tr,di),ie=Math.imul(Tr,ji),ie=ie+Math.imul(Lr,di)|0,Se=Math.imul(Lr,ji),me=me+Math.imul(mt,wi)|0,ie=ie+Math.imul(mt,On)|0,ie=ie+Math.imul(er,wi)|0,Se=Se+Math.imul(er,On)|0,me=me+Math.imul(Vt,Fn)|0,ie=ie+Math.imul(Vt,ra)|0,ie=ie+Math.imul(_t,Fn)|0,Se=Se+Math.imul(_t,ra)|0,me=me+Math.imul($e,Ut)|0,ie=ie+Math.imul($e,wt)|0,ie=ie+Math.imul(St,Ut)|0,Se=Se+Math.imul(St,wt)|0;var Wa=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Wa>>>26)|0,Wa&=67108863,me=Math.imul(Tr,wi),ie=Math.imul(Tr,On),ie=ie+Math.imul(Lr,wi)|0,Se=Math.imul(Lr,On),me=me+Math.imul(mt,Fn)|0,ie=ie+Math.imul(mt,ra)|0,ie=ie+Math.imul(er,Fn)|0,Se=Se+Math.imul(er,ra)|0,me=me+Math.imul(Vt,Ut)|0,ie=ie+Math.imul(Vt,wt)|0,ie=ie+Math.imul(_t,Ut)|0,Se=Se+Math.imul(_t,wt)|0;var Fa=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Fa>>>26)|0,Fa&=67108863,me=Math.imul(Tr,Fn),ie=Math.imul(Tr,ra),ie=ie+Math.imul(Lr,Fn)|0,Se=Math.imul(Lr,ra),me=me+Math.imul(mt,Ut)|0,ie=ie+Math.imul(mt,wt)|0,ie=ie+Math.imul(er,Ut)|0,Se=Se+Math.imul(er,wt)|0;var Wo=(Ce+me|0)+((ie&8191)<<13)|0;Ce=(Se+(ie>>>13)|0)+(Wo>>>26)|0,Wo&=67108863,me=Math.imul(Tr,Ut),ie=Math.imul(Tr,wt),ie=ie+Math.imul(Lr,Ut)|0,Se=Math.imul(Lr,wt);var da=(Ce+me|0)+((ie&8191)<<13)|0;return Ce=(Se+(ie>>>13)|0)+(da>>>26)|0,da&=67108863,Ee[0]=rr,Ee[1]=nr,Ee[2]=Er,Ee[3]=Xr,Ee[4]=ri,Ee[5]=Qr,Ee[6]=Oi,Ee[7]=$i,Ee[8]=tn,Ee[9]=fn,Ee[10]=yn,Ee[11]=Sn,Ee[12]=Ba,Ee[13]=ua,Ee[14]=ma,Ee[15]=Wa,Ee[16]=Fa,Ee[17]=Wo,Ee[18]=da,Ce!==0&&(Ee[19]=Ce,te.length++),te};Math.imul||(L=S);function x(j,N,H){H.negative=N.negative^j.negative,H.length=j.length+N.length;for(var te=0,oe=0,_e=0;_e>>26)|0,oe+=Ee>>>26,Ee&=67108863}H.words[_e]=Ce,te=Ee,Ee=oe}return te!==0?H.words[_e]=te:H.length--,H.strip()}function C(j,N,H){var te=new M;return te.mulp(j,N,H)}f.prototype.mulTo=function(N,H){var te,oe=this.length+N.length;return this.length===10&&N.length===10?te=L(this,N,H):oe<63?te=S(this,N,H):oe<1024?te=x(this,N,H):te=C(this,N,H),te};function M(j,N){this.x=j,this.y=N}M.prototype.makeRBT=function(N){for(var H=new Array(N),te=f.prototype._countBits(N)-1,oe=0;oe>=1;return oe},M.prototype.permute=function(N,H,te,oe,_e,Ee){for(var Ce=0;Ce>>1)_e++;return 1<<_e+1+oe},M.prototype.conjugate=function(N,H,te){if(!(te<=1))for(var oe=0;oe>>13,te[2*Ee+1]=_e&8191,_e=_e>>>13;for(Ee=2*H;Ee>=26,H+=oe/67108864|0,H+=_e>>>26,this.words[te]=_e&67108863}return H!==0&&(this.words[te]=H,this.length++),this},f.prototype.muln=function(N){return this.clone().imuln(N)},f.prototype.sqr=function(){return this.mul(this)},f.prototype.isqr=function(){return this.imul(this.clone())},f.prototype.pow=function(N){var H=E(N);if(H.length===0)return new f(1);for(var te=this,oe=0;oe=0);var H=N%26,te=(N-H)/26,oe=67108863>>>26-H<<26-H,_e;if(H!==0){var Ee=0;for(_e=0;_e>>26-H}Ee&&(this.words[_e]=Ee,this.length++)}if(te!==0){for(_e=this.length-1;_e>=0;_e--)this.words[_e+te]=this.words[_e];for(_e=0;_e=0);var oe;H?oe=(H-H%26)/26:oe=0;var _e=N%26,Ee=Math.min((N-_e)/26,this.length),Ce=67108863^67108863>>>_e<<_e,me=te;if(oe-=Ee,oe=Math.max(0,oe),me){for(var ie=0;ieEe)for(this.length-=Ee,ie=0;ie=0&&(Se!==0||ie>=oe);ie--){var Le=this.words[ie]|0;this.words[ie]=Se<<26-_e|Le>>>_e,Se=Le&Ce}return me&&Se!==0&&(me.words[me.length++]=Se),this.length===0&&(this.words[0]=0,this.length=1),this.strip()},f.prototype.ishrn=function(N,H,te){return u(this.negative===0),this.iushrn(N,H,te)},f.prototype.shln=function(N){return this.clone().ishln(N)},f.prototype.ushln=function(N){return this.clone().iushln(N)},f.prototype.shrn=function(N){return this.clone().ishrn(N)},f.prototype.ushrn=function(N){return this.clone().iushrn(N)},f.prototype.testn=function(N){u(typeof N=="number"&&N>=0);var H=N%26,te=(N-H)/26,oe=1<=0);var H=N%26,te=(N-H)/26;if(u(this.negative===0,"imaskn works only with positive numbers"),this.length<=te)return this;if(H!==0&&te++,this.length=Math.min(te,this.length),H!==0){var oe=67108863^67108863>>>H<=67108864;H++)this.words[H]-=67108864,H===this.length-1?this.words[H+1]=1:this.words[H+1]++;return this.length=Math.max(this.length,H+1),this},f.prototype.isubn=function(N){if(u(typeof N=="number"),u(N<67108864),N<0)return this.iaddn(-N);if(this.negative!==0)return this.negative=0,this.iaddn(N),this.negative=1,this;if(this.words[0]-=N,this.length===1&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var H=0;H>26)-(me/67108864|0),this.words[_e+te]=Ee&67108863}for(;_e>26,this.words[_e+te]=Ee&67108863;if(Ce===0)return this.strip();for(u(Ce===-1),Ce=0,_e=0;_e>26,this.words[_e]=Ee&67108863;return this.negative=1,this.strip()},f.prototype._wordDiv=function(N,H){var te=this.length-N.length,oe=this.clone(),_e=N,Ee=_e.words[_e.length-1]|0,Ce=this._countBits(Ee);te=26-Ce,te!==0&&(_e=_e.ushln(te),oe.iushln(te),Ee=_e.words[_e.length-1]|0);var me=oe.length-_e.length,ie;if(H!=="mod"){ie=new f(null),ie.length=me+1,ie.words=new Array(ie.length);for(var Se=0;Se=0;Ae--){var Fe=(oe.words[_e.length+Ae]|0)*67108864+(oe.words[_e.length+Ae-1]|0);for(Fe=Math.min(Fe/Ee|0,67108863),oe._ishlnsubmul(_e,Fe,Ae);oe.negative!==0;)Fe--,oe.negative=0,oe._ishlnsubmul(_e,1,Ae),oe.isZero()||(oe.negative^=1);ie&&(ie.words[Ae]=Fe)}return ie&&ie.strip(),oe.strip(),H!=="div"&&te!==0&&oe.iushrn(te),{div:ie||null,mod:oe}},f.prototype.divmod=function(N,H,te){if(u(!N.isZero()),this.isZero())return{div:new f(0),mod:new f(0)};var oe,_e,Ee;return this.negative!==0&&N.negative===0?(Ee=this.neg().divmod(N,H),H!=="mod"&&(oe=Ee.div.neg()),H!=="div"&&(_e=Ee.mod.neg(),te&&_e.negative!==0&&_e.iadd(N)),{div:oe,mod:_e}):this.negative===0&&N.negative!==0?(Ee=this.divmod(N.neg(),H),H!=="mod"&&(oe=Ee.div.neg()),{div:oe,mod:Ee.mod}):(this.negative&N.negative)!==0?(Ee=this.neg().divmod(N.neg(),H),H!=="div"&&(_e=Ee.mod.neg(),te&&_e.negative!==0&&_e.isub(N)),{div:Ee.div,mod:_e}):N.length>this.length||this.cmp(N)<0?{div:new f(0),mod:this}:N.length===1?H==="div"?{div:this.divn(N.words[0]),mod:null}:H==="mod"?{div:null,mod:new f(this.modn(N.words[0]))}:{div:this.divn(N.words[0]),mod:new f(this.modn(N.words[0]))}:this._wordDiv(N,H)},f.prototype.div=function(N){return this.divmod(N,"div",!1).div},f.prototype.mod=function(N){return this.divmod(N,"mod",!1).mod},f.prototype.umod=function(N){return this.divmod(N,"mod",!0).mod},f.prototype.divRound=function(N){var H=this.divmod(N);if(H.mod.isZero())return H.div;var te=H.div.negative!==0?H.mod.isub(N):H.mod,oe=N.ushrn(1),_e=N.andln(1),Ee=te.cmp(oe);return Ee<0||_e===1&&Ee===0?H.div:H.div.negative!==0?H.div.isubn(1):H.div.iaddn(1)},f.prototype.modn=function(N){u(N<=67108863);for(var H=(1<<26)%N,te=0,oe=this.length-1;oe>=0;oe--)te=(H*te+(this.words[oe]|0))%N;return te},f.prototype.idivn=function(N){u(N<=67108863);for(var H=0,te=this.length-1;te>=0;te--){var oe=(this.words[te]|0)+H*67108864;this.words[te]=oe/N|0,H=oe%N}return this.strip()},f.prototype.divn=function(N){return this.clone().idivn(N)},f.prototype.egcd=function(N){u(N.negative===0),u(!N.isZero());var H=this,te=N.clone();H.negative!==0?H=H.umod(N):H=H.clone();for(var oe=new f(1),_e=new f(0),Ee=new f(0),Ce=new f(1),me=0;H.isEven()&&te.isEven();)H.iushrn(1),te.iushrn(1),++me;for(var ie=te.clone(),Se=H.clone();!H.isZero();){for(var Le=0,Ae=1;(H.words[0]&Ae)===0&&Le<26;++Le,Ae<<=1);if(Le>0)for(H.iushrn(Le);Le-- >0;)(oe.isOdd()||_e.isOdd())&&(oe.iadd(ie),_e.isub(Se)),oe.iushrn(1),_e.iushrn(1);for(var Fe=0,Pe=1;(te.words[0]&Pe)===0&&Fe<26;++Fe,Pe<<=1);if(Fe>0)for(te.iushrn(Fe);Fe-- >0;)(Ee.isOdd()||Ce.isOdd())&&(Ee.iadd(ie),Ce.isub(Se)),Ee.iushrn(1),Ce.iushrn(1);H.cmp(te)>=0?(H.isub(te),oe.isub(Ee),_e.isub(Ce)):(te.isub(H),Ee.isub(oe),Ce.isub(_e))}return{a:Ee,b:Ce,gcd:te.iushln(me)}},f.prototype._invmp=function(N){u(N.negative===0),u(!N.isZero());var H=this,te=N.clone();H.negative!==0?H=H.umod(N):H=H.clone();for(var oe=new f(1),_e=new f(0),Ee=te.clone();H.cmpn(1)>0&&te.cmpn(1)>0;){for(var Ce=0,me=1;(H.words[0]&me)===0&&Ce<26;++Ce,me<<=1);if(Ce>0)for(H.iushrn(Ce);Ce-- >0;)oe.isOdd()&&oe.iadd(Ee),oe.iushrn(1);for(var ie=0,Se=1;(te.words[0]&Se)===0&&ie<26;++ie,Se<<=1);if(ie>0)for(te.iushrn(ie);ie-- >0;)_e.isOdd()&&_e.iadd(Ee),_e.iushrn(1);H.cmp(te)>=0?(H.isub(te),oe.isub(_e)):(te.isub(H),_e.isub(oe))}var Le;return H.cmpn(1)===0?Le=oe:Le=_e,Le.cmpn(0)<0&&Le.iadd(N),Le},f.prototype.gcd=function(N){if(this.isZero())return N.abs();if(N.isZero())return this.abs();var H=this.clone(),te=N.clone();H.negative=0,te.negative=0;for(var oe=0;H.isEven()&&te.isEven();oe++)H.iushrn(1),te.iushrn(1);do{for(;H.isEven();)H.iushrn(1);for(;te.isEven();)te.iushrn(1);var _e=H.cmp(te);if(_e<0){var Ee=H;H=te,te=Ee}else if(_e===0||te.cmpn(1)===0)break;H.isub(te)}while(!0);return te.iushln(oe)},f.prototype.invm=function(N){return this.egcd(N).a.umod(N)},f.prototype.isEven=function(){return(this.words[0]&1)===0},f.prototype.isOdd=function(){return(this.words[0]&1)===1},f.prototype.andln=function(N){return this.words[0]&N},f.prototype.bincn=function(N){u(typeof N=="number");var H=N%26,te=(N-H)/26,oe=1<>>26,Ce&=67108863,this.words[Ee]=Ce}return _e!==0&&(this.words[Ee]=_e,this.length++),this},f.prototype.isZero=function(){return this.length===1&&this.words[0]===0},f.prototype.cmpn=function(N){var H=N<0;if(this.negative!==0&&!H)return-1;if(this.negative===0&&H)return 1;this.strip();var te;if(this.length>1)te=1;else{H&&(N=-N),u(N<=67108863,"Number is too big");var oe=this.words[0]|0;te=oe===N?0:oeN.length)return 1;if(this.length=0;te--){var oe=this.words[te]|0,_e=N.words[te]|0;if(oe!==_e){oe<_e?H=-1:oe>_e&&(H=1);break}}return H},f.prototype.gtn=function(N){return this.cmpn(N)===1},f.prototype.gt=function(N){return this.cmp(N)===1},f.prototype.gten=function(N){return this.cmpn(N)>=0},f.prototype.gte=function(N){return this.cmp(N)>=0},f.prototype.ltn=function(N){return this.cmpn(N)===-1},f.prototype.lt=function(N){return this.cmp(N)===-1},f.prototype.lten=function(N){return this.cmpn(N)<=0},f.prototype.lte=function(N){return this.cmp(N)<=0},f.prototype.eqn=function(N){return this.cmpn(N)===0},f.prototype.eq=function(N){return this.cmp(N)===0},f.red=function(N){return new G(N)},f.prototype.toRed=function(N){return u(!this.red,"Already a number in reduction context"),u(this.negative===0,"red works only with positives"),N.convertTo(this)._forceRed(N)},f.prototype.fromRed=function(){return u(this.red,"fromRed works only with numbers in reduction context"),this.red.convertFrom(this)},f.prototype._forceRed=function(N){return this.red=N,this},f.prototype.forceRed=function(N){return u(!this.red,"Already a number in reduction context"),this._forceRed(N)},f.prototype.redAdd=function(N){return u(this.red,"redAdd works only with red numbers"),this.red.add(this,N)},f.prototype.redIAdd=function(N){return u(this.red,"redIAdd works only with red numbers"),this.red.iadd(this,N)},f.prototype.redSub=function(N){return u(this.red,"redSub works only with red numbers"),this.red.sub(this,N)},f.prototype.redISub=function(N){return u(this.red,"redISub works only with red numbers"),this.red.isub(this,N)},f.prototype.redShl=function(N){return u(this.red,"redShl works only with red numbers"),this.red.shl(this,N)},f.prototype.redMul=function(N){return u(this.red,"redMul works only with red numbers"),this.red._verify2(this,N),this.red.mul(this,N)},f.prototype.redIMul=function(N){return u(this.red,"redMul works only with red numbers"),this.red._verify2(this,N),this.red.imul(this,N)},f.prototype.redSqr=function(){return u(this.red,"redSqr works only with red numbers"),this.red._verify1(this),this.red.sqr(this)},f.prototype.redISqr=function(){return u(this.red,"redISqr works only with red numbers"),this.red._verify1(this),this.red.isqr(this)},f.prototype.redSqrt=function(){return u(this.red,"redSqrt works only with red numbers"),this.red._verify1(this),this.red.sqrt(this)},f.prototype.redInvm=function(){return u(this.red,"redInvm works only with red numbers"),this.red._verify1(this),this.red.invm(this)},f.prototype.redNeg=function(){return u(this.red,"redNeg works only with red numbers"),this.red._verify1(this),this.red.neg(this)},f.prototype.redPow=function(N){return u(this.red&&!N.red,"redPow(normalNum)"),this.red._verify1(this),this.red.pow(this,N)};var g={k256:null,p224:null,p192:null,p25519:null};function P(j,N){this.name=j,this.p=new f(N,16),this.n=this.p.bitLength(),this.k=new f(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}P.prototype._tmp=function(){var N=new f(null);return N.words=new Array(Math.ceil(this.n/13)),N},P.prototype.ireduce=function(N){var H=N,te;do this.split(H,this.tmp),H=this.imulK(H),H=H.iadd(this.tmp),te=H.bitLength();while(te>this.n);var oe=te0?H.isub(this.p):H.strip!==void 0?H.strip():H._strip(),H},P.prototype.split=function(N,H){N.iushrn(this.n,0,H)},P.prototype.imulK=function(N){return N.imul(this.k)};function T(){P.call(this,"k256","ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f")}c(T,P),T.prototype.split=function(N,H){for(var te=4194303,oe=Math.min(N.length,9),_e=0;_e>>22,Ee=Ce}Ee>>>=22,N.words[_e-10]=Ee,Ee===0&&N.length>10?N.length-=10:N.length-=9},T.prototype.imulK=function(N){N.words[N.length]=0,N.words[N.length+1]=0,N.length+=2;for(var H=0,te=0;te>>=26,N.words[te]=_e,H=oe}return H!==0&&(N.words[N.length++]=H),N},f._prime=function(N){if(g[N])return g[N];var H;if(N==="k256")H=new T;else if(N==="p224")H=new z;else if(N==="p192")H=new O;else if(N==="p25519")H=new V;else throw new Error("Unknown prime "+N);return g[N]=H,H};function G(j){if(typeof j=="string"){var N=f._prime(j);this.m=N.p,this.prime=N}else u(j.gtn(1),"modulus must be greater than 1"),this.m=j,this.prime=null}G.prototype._verify1=function(N){u(N.negative===0,"red works only with positives"),u(N.red,"red works only with red numbers")},G.prototype._verify2=function(N,H){u((N.negative|H.negative)===0,"red works only with positives"),u(N.red&&N.red===H.red,"red works only with red numbers")},G.prototype.imod=function(N){return this.prime?this.prime.ireduce(N)._forceRed(this):N.umod(this.m)._forceRed(this)},G.prototype.neg=function(N){return N.isZero()?N.clone():this.m.sub(N)._forceRed(this)},G.prototype.add=function(N,H){this._verify2(N,H);var te=N.add(H);return te.cmp(this.m)>=0&&te.isub(this.m),te._forceRed(this)},G.prototype.iadd=function(N,H){this._verify2(N,H);var te=N.iadd(H);return te.cmp(this.m)>=0&&te.isub(this.m),te},G.prototype.sub=function(N,H){this._verify2(N,H);var te=N.sub(H);return te.cmpn(0)<0&&te.iadd(this.m),te._forceRed(this)},G.prototype.isub=function(N,H){this._verify2(N,H);var te=N.isub(H);return te.cmpn(0)<0&&te.iadd(this.m),te},G.prototype.shl=function(N,H){return this._verify1(N),this.imod(N.ushln(H))},G.prototype.imul=function(N,H){return this._verify2(N,H),this.imod(N.imul(H))},G.prototype.mul=function(N,H){return this._verify2(N,H),this.imod(N.mul(H))},G.prototype.isqr=function(N){return this.imul(N,N.clone())},G.prototype.sqr=function(N){return this.mul(N,N)},G.prototype.sqrt=function(N){if(N.isZero())return N.clone();var H=this.m.andln(3);if(u(H%2===1),H===3){var te=this.m.add(new f(1)).iushrn(2);return this.pow(N,te)}for(var oe=this.m.subn(1),_e=0;!oe.isZero()&&oe.andln(1)===0;)_e++,oe.iushrn(1);u(!oe.isZero());var Ee=new f(1).toRed(this),Ce=Ee.redNeg(),me=this.m.subn(1).iushrn(1),ie=this.m.bitLength();for(ie=new f(2*ie*ie).toRed(this);this.pow(ie,me).cmp(Ce)!==0;)ie.redIAdd(Ce);for(var Se=this.pow(ie,oe),Le=this.pow(N,oe.addn(1).iushrn(1)),Ae=this.pow(N,oe),Fe=_e;Ae.cmp(Ee)!==0;){for(var Pe=Ae,ge=0;Pe.cmp(Ee)!==0;ge++)Pe=Pe.redSqr();u(ge=0;_e--){for(var Se=H.words[_e],Le=ie-1;Le>=0;Le--){var Ae=Se>>Le&1;if(Ee!==oe[0]&&(Ee=this.sqr(Ee)),Ae===0&&Ce===0){me=0;continue}Ce<<=1,Ce|=Ae,me++,!(me!==te&&(_e!==0||Le!==0))&&(Ee=this.mul(Ee,oe[Ce]),me=0,Ce=0)}ie=26}return Ee},G.prototype.convertTo=function(N){var H=N.umod(this.m);return H===N?H.clone():H},G.prototype.convertFrom=function(N){var H=N.clone();return H.red=null,H},f.mont=function(N){return new Z(N)};function Z(j){G.call(this,j),this.shift=this.m.bitLength(),this.shift%26!==0&&(this.shift+=26-this.shift%26),this.r=new f(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}c(Z,G),Z.prototype.convertTo=function(N){return this.imod(N.ushln(this.shift))},Z.prototype.convertFrom=function(N){var H=this.imod(N.mul(this.rinv));return H.red=null,H},Z.prototype.imul=function(N,H){if(N.isZero()||H.isZero())return N.words[0]=0,N.length=1,N;var te=N.imul(H),oe=te.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),_e=te.isub(oe).iushrn(this.shift),Ee=_e;return _e.cmp(this.m)>=0?Ee=_e.isub(this.m):_e.cmpn(0)<0&&(Ee=_e.iadd(this.m)),Ee._forceRed(this)},Z.prototype.mul=function(N,H){if(N.isZero()||H.isZero())return new f(0)._forceRed(this);var te=N.mul(H),oe=te.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),_e=te.isub(oe).iushrn(this.shift),Ee=_e;return _e.cmp(this.m)>=0?Ee=_e.isub(this.m):_e.cmpn(0)<0&&(Ee=_e.iadd(this.m)),Ee._forceRed(this)},Z.prototype.invm=function(N){var H=this.imod(N._invmp(this.m).mul(this.r2));return H._forceRed(this)}}(i,this)},6860:function(i){i.exports=a;function a(o,s,l){return o[0]=s[0]-l[0],o[1]=s[1]-l[1],o[2]=s[2]-l[2],o[3]=s[3]-l[3],o}},6864:function(i){i.exports=a;function a(){var o=new Float32Array(16);return o[0]=1,o[1]=0,o[2]=0,o[3]=0,o[4]=0,o[5]=1,o[6]=0,o[7]=0,o[8]=0,o[9]=0,o[10]=1,o[11]=0,o[12]=0,o[13]=0,o[14]=0,o[15]=1,o}},6867:function(i,a,o){"use strict";i.exports=p;var s=o(1888),l=o(855),u=o(7150);function c(k,E){for(var S=0;S>>1;if(!(M<=0)){var g,P=s.mallocDouble(2*M*x),T=s.mallocInt32(x);if(x=f(k,M,P,T),x>0){if(M===1&&L)l.init(x),g=l.sweepComplete(M,S,0,x,P,T,0,x,P,T);else{var z=s.mallocDouble(2*M*C),O=s.mallocInt32(C);C=f(E,M,z,O),C>0&&(l.init(x+C),M===1?g=l.sweepBipartite(M,S,0,x,P,T,0,C,z,O):g=u(M,S,L,x,P,T,C,z,O),s.free(z),s.free(O))}s.free(P),s.free(T)}return g}}}var d;function v(k,E){d.push([k,E])}function _(k){return d=[],h(k,k,v,!0),d}function b(k,E){return d=[],h(k,E,v,!1),d}function p(k,E,S){switch(arguments.length){case 1:return _(k);case 2:return typeof E=="function"?h(k,k,E,!0):b(k,E);case 3:return h(k,E,S,!1);default:throw new Error("box-intersect: Invalid arguments")}}},6894:function(i){i.exports=a;function a(o,s,l,u){var c=l[1],f=l[2],h=s[1]-c,d=s[2]-f,v=Math.sin(u),_=Math.cos(u);return o[0]=s[0],o[1]=c+h*_-d*v,o[2]=f+h*v+d*_,o}},7004:function(i){"use strict";i.exports=a;function a(o){for(var s=o.length,l=o[o.length-1],u=s,c=s-2;c>=0;--c){var f=l,h=o[c];l=f+h;var d=l-f,v=h-d;v&&(o[--u]=l,l=v)}for(var _=0,c=u;c=p0)&&!(p1>=hi)"),E=v("lo===p0"),S=v("lo0;){Se-=1;var Fe=Se*M,Pe=T[Fe],ge=T[Fe+1],Re=T[Fe+2],ce=T[Fe+3],Ze=T[Fe+4],ut=T[Fe+5],pt=Se*g,Zt=z[pt],st=z[pt+1],lt=ut&1,Gt=!!(ut&16),Nt=_e,Jt=Ee,sr=me,wr=ie;if(lt&&(Nt=me,Jt=ie,sr=_e,wr=Ee),!(ut&2&&(Re=S(N,Pe,ge,Re,Nt,Jt,st),ge>=Re))&&!(ut&4&&(ge=L(N,Pe,ge,Re,Nt,Jt,Zt),ge>=Re))){var cr=Re-ge,$e=Ze-ce;if(Gt){if(N*cr*(cr+$e)me&&Se>0){var Le=(ie[Se][0]-me)/(ie[Se][0]-ie[Se-1][0]);return ie[Se][1]*(1-Le)+Le*ie[Se-1][1]}}return 1}function Z(me,ie){for(var Se=p({colormap:me,nshades:256,format:"rgba"}),Le=new Uint8Array(256*4),Ae=0;Ae<256;++Ae){for(var Fe=Se[Ae],Pe=0;Pe<3;++Pe)Le[4*Ae+Pe]=Fe[Pe];ie?Le[4*Ae+3]=255*G(Ae/255,ie):Le[4*Ae+3]=255*Fe[3]}return b(Le,[256,256,4],[4,0,1])}function j(me){for(var ie=me.length,Se=new Array(ie),Le=0;Le0){var pt=this.triShader;pt.bind(),pt.uniforms=ge,this.triangleVAO.bind(),ie.drawArrays(ie.TRIANGLES,0,this.triangleCount*3),this.triangleVAO.unbind()}if(this.edgeCount>0&&this.lineWidth>0){var pt=this.lineShader;pt.bind(),pt.uniforms=ge,this.edgeVAO.bind(),ie.lineWidth(this.lineWidth*this.pixelRatio),ie.drawArrays(ie.LINES,0,this.edgeCount*2),this.edgeVAO.unbind()}if(this.pointCount>0){var pt=this.pointShader;pt.bind(),pt.uniforms=ge,this.pointVAO.bind(),ie.drawArrays(ie.POINTS,0,this.pointCount),this.pointVAO.unbind()}if(this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0){var pt=this.contourShader;pt.bind(),pt.uniforms=ge,this.contourVAO.bind(),ie.drawArrays(ie.LINES,0,this.contourCount),this.contourVAO.unbind()}},V.drawPick=function(me){me=me||{};for(var ie=this.gl,Se=me.model||z,Le=me.view||z,Ae=me.projection||z,Fe=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],Pe=0;Pe<3;++Pe)Fe[0][Pe]=Math.max(Fe[0][Pe],this.clipBounds[0][Pe]),Fe[1][Pe]=Math.min(Fe[1][Pe],this.clipBounds[1][Pe]);this._model=[].slice.call(Se),this._view=[].slice.call(Le),this._projection=[].slice.call(Ae),this._resolution=[ie.drawingBufferWidth,ie.drawingBufferHeight];var ge={model:Se,view:Le,projection:Ae,clipBounds:Fe,pickId:this.pickId/255},Re=this.pickShader;if(Re.bind(),Re.uniforms=ge,this.triangleCount>0&&(this.triangleVAO.bind(),ie.drawArrays(ie.TRIANGLES,0,this.triangleCount*3),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),ie.lineWidth(this.lineWidth*this.pixelRatio),ie.drawArrays(ie.LINES,0,this.edgeCount*2),this.edgeVAO.unbind()),this.pointCount>0){var Re=this.pointPickShader;Re.bind(),Re.uniforms=ge,this.pointVAO.bind(),ie.drawArrays(ie.POINTS,0,this.pointCount),this.pointVAO.unbind()}},V.pick=function(me){if(!me||me.id!==this.pickId)return null;for(var ie=me.value[0]+256*me.value[1]+65536*me.value[2],Se=this.cells[ie],Le=this.positions,Ae=new Array(Se.length),Fe=0;FeMath.max(x,C)?M[2]=1:x>Math.max(L,C)?M[0]=1:M[1]=1;for(var g=0,P=0,T=0;T<3;++T)g+=S[T]*S[T],P+=M[T]*S[T];for(var T=0;T<3;++T)M[T]-=P/g*S[T];return f(M,M),M}function b(S,L,x,C,M,g,P,T){this.center=s(x),this.up=s(C),this.right=s(M),this.radius=s([g]),this.angle=s([P,T]),this.angle.bounds=[[-1/0,-Math.PI/2],[1/0,Math.PI/2]],this.setDistanceLimits(S,L),this.computedCenter=this.center.curve(0),this.computedUp=this.up.curve(0),this.computedRight=this.right.curve(0),this.computedRadius=this.radius.curve(0),this.computedAngle=this.angle.curve(0),this.computedToward=[0,0,0],this.computedEye=[0,0,0],this.computedMatrix=new Array(16);for(var z=0;z<16;++z)this.computedMatrix[z]=.5;this.recalcMatrix(0)}var p=b.prototype;p.setDistanceLimits=function(S,L){S>0?S=Math.log(S):S=-1/0,L>0?L=Math.log(L):L=1/0,L=Math.max(L,S),this.radius.bounds[0][0]=S,this.radius.bounds[1][0]=L},p.getDistanceLimits=function(S){var L=this.radius.bounds[0];return S?(S[0]=Math.exp(L[0][0]),S[1]=Math.exp(L[1][0]),S):[Math.exp(L[0][0]),Math.exp(L[1][0])]},p.recalcMatrix=function(S){this.center.curve(S),this.up.curve(S),this.right.curve(S),this.radius.curve(S),this.angle.curve(S);for(var L=this.computedUp,x=this.computedRight,C=0,M=0,g=0;g<3;++g)M+=L[g]*x[g],C+=L[g]*L[g];for(var P=Math.sqrt(C),T=0,g=0;g<3;++g)x[g]-=L[g]*M/C,T+=x[g]*x[g],L[g]/=P;for(var z=Math.sqrt(T),g=0;g<3;++g)x[g]/=z;var O=this.computedToward;c(O,L,x),f(O,O);for(var V=Math.exp(this.computedRadius[0]),G=this.computedAngle[0],Z=this.computedAngle[1],j=Math.cos(G),N=Math.sin(G),H=Math.cos(Z),te=Math.sin(Z),oe=this.computedCenter,_e=j*H,Ee=N*H,Ce=te,me=-j*te,ie=-N*te,Se=H,Le=this.computedEye,Ae=this.computedMatrix,g=0;g<3;++g){var Fe=_e*x[g]+Ee*O[g]+Ce*L[g];Ae[4*g+1]=me*x[g]+ie*O[g]+Se*L[g],Ae[4*g+2]=Fe,Ae[4*g+3]=0}var Pe=Ae[1],ge=Ae[5],Re=Ae[9],ce=Ae[2],Ze=Ae[6],ut=Ae[10],pt=ge*ut-Re*Ze,Zt=Re*ce-Pe*ut,st=Pe*Ze-ge*ce,lt=d(pt,Zt,st);pt/=lt,Zt/=lt,st/=lt,Ae[0]=pt,Ae[4]=Zt,Ae[8]=st;for(var g=0;g<3;++g)Le[g]=oe[g]+Ae[2+4*g]*V;for(var g=0;g<3;++g){for(var T=0,Gt=0;Gt<3;++Gt)T+=Ae[g+4*Gt]*Le[Gt];Ae[12+g]=-T}Ae[15]=1},p.getMatrix=function(S,L){this.recalcMatrix(S);var x=this.computedMatrix;if(L){for(var C=0;C<16;++C)L[C]=x[C];return L}return x};var k=[0,0,0];p.rotate=function(S,L,x,C){if(this.angle.move(S,L,x),C){this.recalcMatrix(S);var M=this.computedMatrix;k[0]=M[2],k[1]=M[6],k[2]=M[10];for(var g=this.computedUp,P=this.computedRight,T=this.computedToward,z=0;z<3;++z)M[4*z]=g[z],M[4*z+1]=P[z],M[4*z+2]=T[z];u(M,M,C,k);for(var z=0;z<3;++z)g[z]=M[4*z],P[z]=M[4*z+1];this.up.set(S,g[0],g[1],g[2]),this.right.set(S,P[0],P[1],P[2])}},p.pan=function(S,L,x,C){L=L||0,x=x||0,C=C||0,this.recalcMatrix(S);var M=this.computedMatrix,g=Math.exp(this.computedRadius[0]),P=M[1],T=M[5],z=M[9],O=d(P,T,z);P/=O,T/=O,z/=O;var V=M[0],G=M[4],Z=M[8],j=V*P+G*T+Z*z;V-=P*j,G-=T*j,Z-=z*j;var N=d(V,G,Z);V/=N,G/=N,Z/=N;var H=V*L+P*x,te=G*L+T*x,oe=Z*L+z*x;this.center.move(S,H,te,oe);var _e=Math.exp(this.computedRadius[0]);_e=Math.max(1e-4,_e+C),this.radius.set(S,Math.log(_e))},p.translate=function(S,L,x,C){this.center.move(S,L||0,x||0,C||0)},p.setMatrix=function(S,L,x,C){var M=1;typeof x=="number"&&(M=x|0),(M<0||M>3)&&(M=1);var g=(M+2)%3,P=(M+1)%3;L||(this.recalcMatrix(S),L=this.computedMatrix);var T=L[M],z=L[M+4],O=L[M+8];if(C){var G=Math.abs(T),Z=Math.abs(z),j=Math.abs(O),N=Math.max(G,Z,j);G===N?(T=T<0?-1:1,z=O=0):j===N?(O=O<0?-1:1,T=z=0):(z=z<0?-1:1,T=O=0)}else{var V=d(T,z,O);T/=V,z/=V,O/=V}var H=L[g],te=L[g+4],oe=L[g+8],_e=H*T+te*z+oe*O;H-=T*_e,te-=z*_e,oe-=O*_e;var Ee=d(H,te,oe);H/=Ee,te/=Ee,oe/=Ee;var Ce=z*oe-O*te,me=O*H-T*oe,ie=T*te-z*H,Se=d(Ce,me,ie);Ce/=Se,me/=Se,ie/=Se,this.center.jump(S,cr,$e,St),this.radius.idle(S),this.up.jump(S,T,z,O),this.right.jump(S,H,te,oe);var Le,Ae;if(M===2){var Fe=L[1],Pe=L[5],ge=L[9],Re=Fe*H+Pe*te+ge*oe,ce=Fe*Ce+Pe*me+ge*ie;Zt<0?Le=-Math.PI/2:Le=Math.PI/2,Ae=Math.atan2(ce,Re)}else{var Ze=L[2],ut=L[6],pt=L[10],Zt=Ze*T+ut*z+pt*O,st=Ze*H+ut*te+pt*oe,lt=Ze*Ce+ut*me+pt*ie;Le=Math.asin(v(Zt)),Ae=Math.atan2(lt,st)}this.angle.jump(S,Ae,Le),this.recalcMatrix(S);var Gt=L[2],Nt=L[6],Jt=L[10],sr=this.computedMatrix;l(sr,L);var wr=sr[15],cr=sr[12]/wr,$e=sr[13]/wr,St=sr[14]/wr,Qt=Math.exp(this.computedRadius[0]);this.center.jump(S,cr-Gt*Qt,$e-Nt*Qt,St-Jt*Qt)},p.lastT=function(){return Math.max(this.center.lastT(),this.up.lastT(),this.right.lastT(),this.radius.lastT(),this.angle.lastT())},p.idle=function(S){this.center.idle(S),this.up.idle(S),this.right.idle(S),this.radius.idle(S),this.angle.idle(S)},p.flush=function(S){this.center.flush(S),this.up.flush(S),this.right.flush(S),this.radius.flush(S),this.angle.flush(S)},p.setDistance=function(S,L){L>0&&this.radius.set(S,Math.log(L))},p.lookAt=function(S,L,x,C){this.recalcMatrix(S),L=L||this.computedEye,x=x||this.computedCenter,C=C||this.computedUp;var M=C[0],g=C[1],P=C[2],T=d(M,g,P);if(!(T<1e-6)){M/=T,g/=T,P/=T;var z=L[0]-x[0],O=L[1]-x[1],V=L[2]-x[2],G=d(z,O,V);if(!(G<1e-6)){z/=G,O/=G,V/=G;var Z=this.computedRight,j=Z[0],N=Z[1],H=Z[2],te=M*j+g*N+P*H;j-=te*M,N-=te*g,H-=te*P;var 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float dashScale; +uniform float opacity; + +varying vec3 worldPosition; +varying float pixelArcLength; +varying vec4 fragColor; + +void main() { + if ( + outOfRange(clipBounds[0], clipBounds[1], worldPosition) || + fragColor.a * opacity == 0. + ) discard; + + float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r; + if(dashWeight < 0.5) { + discard; + } + gl_FragColor = fragColor * opacity; +} +`]),f=s([`precision highp float; +#define GLSLIFY 1 + +#define FLOAT_MAX 1.70141184e38 +#define FLOAT_MIN 1.17549435e-38 + +// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl +vec4 packFloat(float v) { + float av = abs(v); + + //Handle special cases + if(av < FLOAT_MIN) { + return vec4(0.0, 0.0, 0.0, 0.0); + } else if(v > FLOAT_MAX) { + return vec4(127.0, 128.0, 0.0, 0.0) / 255.0; + } else if(v < -FLOAT_MAX) { + return vec4(255.0, 128.0, 0.0, 0.0) / 255.0; + } + + vec4 c = vec4(0,0,0,0); + + //Compute exponent and mantissa + float e = floor(log2(av)); + float m = av * pow(2.0, -e) - 1.0; + + //Unpack mantissa + c[1] = floor(128.0 * m); + m -= c[1] / 128.0; + c[2] = floor(32768.0 * m); + m -= c[2] / 32768.0; + c[3] = floor(8388608.0 * m); + + //Unpack exponent + float ebias = e + 127.0; + c[0] = floor(ebias / 2.0); + ebias -= c[0] * 2.0; + c[1] += floor(ebias) * 128.0; + + //Unpack sign bit + c[0] += 128.0 * step(0.0, -v); + + //Scale back to range + return c / 255.0; +} + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform float pickId; +uniform vec3 clipBounds[2]; + +varying vec3 worldPosition; +varying float pixelArcLength; +varying vec4 fragColor; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard; + + gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz); +}`]),h=[{name:"position",type:"vec3"},{name:"nextPosition",type:"vec3"},{name:"arcLength",type:"float"},{name:"lineWidth",type:"float"},{name:"color",type:"vec4"}];a.createShader=function(d){return l(d,u,c,null,h)},a.createPickShader=function(d){return l(d,u,f,null,h)}},7352:function(i,a,o){"use strict";var s=o(5721),l=o(4750),u=o(2690);i.exports=c;function c(f){var h=f.length;if(h===0)return[];if(h===1)return[[0]];var d=f[0].length;return d===0?[]:d===1?s(f):d===2?l(f):u(f,d)}},7399:function(i){i.exports=a;function a(o,s){var l=s[0],u=s[1],c=s[2],f=s[3],h=l+l,d=u+u,v=c+c,_=l*h,b=u*h,p=u*d,k=c*h,E=c*d,S=c*v,L=f*h,x=f*d,C=f*v;return 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T=this._anisoSamples;if(this._anisoSamples=Math.max(P,1)|0,T!==this._anisoSamples){var z=this.gl.getExtension("EXT_texture_filter_anisotropic");z&&this.gl.texParameterf(this.gl.TEXTURE_2D,z.TEXTURE_MAX_ANISOTROPY_EXT,this._anisoSamples)}return this._anisoSamples}},wrapS:{get:function(){return this._wrapS},set:function(P){if(this.bind(),h.indexOf(P)<0)throw new Error("gl-texture2d: Unknown wrap mode "+P);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_S,P),this._wrapS=P}},wrapT:{get:function(){return this._wrapT},set:function(P){if(this.bind(),h.indexOf(P)<0)throw new Error("gl-texture2d: Unknown wrap mode "+P);return this.gl.texParameteri(this.gl.TEXTURE_2D,this.gl.TEXTURE_WRAP_T,P),this._wrapT=P}},wrap:{get:function(){return this._wrapVector},set:function(P){if(Array.isArray(P)||(P=[P,P]),P.length!==2)throw new Error("gl-texture2d: Must specify wrap mode for rows and columns");for(var T=0;T<2;++T)if(h.indexOf(P[T])<0)throw new Error("gl-texture2d: Unknown wrap 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P=Math.min(this._shape[0],this._shape[1]),T=0;P>0;++T,P>>>=1)this._mipLevels.indexOf(T)<0&&this._mipLevels.push(T)},k.setPixels=function(P,T,z,O){var V=this.gl;this.bind(),Array.isArray(T)?(O=z,z=T[1]|0,T=T[0]|0):(T=T||0,z=z||0),O=O||0;var G=v(P)?P:P.raw;if(G){var Z=this._mipLevels.indexOf(O)<0;Z?(V.texImage2D(V.TEXTURE_2D,0,this.format,this.format,this.type,G),this._mipLevels.push(O)):V.texSubImage2D(V.TEXTURE_2D,O,T,z,this.format,this.type,G)}else if(P.shape&&P.stride&&P.data){if(P.shape.length<2||T+P.shape[1]>this._shape[1]>>>O||z+P.shape[0]>this._shape[0]>>>O||T<0||z<0)throw new Error("gl-texture2d: Texture dimensions are out of bounds");S(V,T,z,O,this.format,this.type,this._mipLevels,P)}else throw new Error("gl-texture2d: Unsupported data type")};function E(P,T){return P.length===3?T[2]===1&&T[1]===P[0]*P[2]&&T[0]===P[2]:T[0]===1&&T[1]===P[0]}function S(P,T,z,O,V,G,Z,j){var N=j.dtype,H=j.shape.slice();if(H.length<2||H.length>3)throw new Error("gl-texture2d: Invalid ndarray, must 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Ce=j.size,me=Z.indexOf(O)<0;if(me&&Z.push(O),te===G&&_e)j.offset===0&&j.data.length===Ce?me?P.texImage2D(P.TEXTURE_2D,O,V,H[0],H[1],0,V,G,j.data):P.texSubImage2D(P.TEXTURE_2D,O,T,z,H[0],H[1],V,G,j.data):me?P.texImage2D(P.TEXTURE_2D,O,V,H[0],H[1],0,V,G,j.data.subarray(j.offset,j.offset+Ce)):P.texSubImage2D(P.TEXTURE_2D,O,T,z,H[0],H[1],V,G,j.data.subarray(j.offset,j.offset+Ce));else{var ie;G===P.FLOAT?ie=u.mallocFloat32(Ce):ie=u.mallocUint8(Ce);var Se=s(ie,H,[H[2],H[2]*H[0],1]);te===P.FLOAT&&G===P.UNSIGNED_BYTE?_(Se,j):l.assign(Se,j),me?P.texImage2D(P.TEXTURE_2D,O,V,H[0],H[1],0,V,G,ie.subarray(0,Ce)):P.texSubImage2D(P.TEXTURE_2D,O,T,z,H[0],H[1],V,G,ie.subarray(0,Ce)),G===P.FLOAT?u.freeFloat32(ie):u.freeUint8(ie)}}function L(P){var T=P.createTexture();return P.bindTexture(P.TEXTURE_2D,T),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_MIN_FILTER,P.NEAREST),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_MAG_FILTER,P.NEAREST),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_WRAP_S,P.CLAMP_TO_EDGE),P.texParameteri(P.TEXTURE_2D,P.TEXTURE_WRAP_T,P.CLAMP_TO_EDGE),T}function x(P,T,z,O,V){var G=P.getParameter(P.MAX_TEXTURE_SIZE);if(T<0||T>G||z<0||z>G)throw new Error("gl-texture2d: Invalid texture shape");if(V===P.FLOAT&&!P.getExtension("OES_texture_float"))throw new Error("gl-texture2d: Floating point textures not supported on this platform");var Z=L(P);return P.texImage2D(P.TEXTURE_2D,0,O,T,z,0,O,V,null),new p(P,Z,T,z,O,V)}function C(P,T,z,O,V,G){var Z=L(P);return P.texImage2D(P.TEXTURE_2D,0,V,V,G,T),new p(P,Z,z,O,V,G)}function M(P,T){var z=T.dtype,O=T.shape.slice(),V=P.getParameter(P.MAX_TEXTURE_SIZE);if(O[0]<0||O[0]>V||O[1]<0||O[1]>V)throw new Error("gl-texture2d: Invalid texture size");var G=E(O,T.stride.slice()),Z=0;z==="float32"?Z=P.FLOAT:z==="float64"?(Z=P.FLOAT,G=!1,z="float32"):z==="uint8"?Z=P.UNSIGNED_BYTE:(Z=P.UNSIGNED_BYTE,G=!1,z="uint8");var j=0;if(O.length===2)j=P.LUMINANCE,O=[O[0],O[1],1],T=s(T.data,O,[T.stride[0],T.stride[1],1],T.offset);else if(O.length===3)if(O[2]===1)j=P.ALPHA;else if(O[2]===2)j=P.LUMINANCE_ALPHA;else if(O[2]===3)j=P.RGB;else if(O[2]===4)j=P.RGBA;else throw new Error("gl-texture2d: Invalid shape for pixel coords");else throw new Error("gl-texture2d: Invalid shape for texture");Z===P.FLOAT&&!P.getExtension("OES_texture_float")&&(Z=P.UNSIGNED_BYTE,G=!1);var N,H,te=T.size;if(G)T.offset===0&&T.data.length===te?N=T.data:N=T.data.subarray(T.offset,T.offset+te);else{var oe=[O[2],O[2]*O[0],1];H=u.malloc(te,z);var _e=s(H,O,oe,0);(z==="float32"||z==="float64")&&Z===P.UNSIGNED_BYTE?_(_e,T):l.assign(_e,T),N=H.subarray(0,te)}var Ee=L(P);return P.texImage2D(P.TEXTURE_2D,0,j,O[0],O[1],0,j,Z,N),G||u.free(H),new p(P,Ee,O[0],O[1],j,Z)}function g(P){if(arguments.length<=1)throw new Error("gl-texture2d: Missing arguments for texture2d constructor");if(c||d(P),typeof arguments[1]=="number")return x(P,arguments[1],arguments[2],arguments[3]||P.RGBA,arguments[4]||P.UNSIGNED_BYTE);if(Array.isArray(arguments[1]))return x(P,arguments[1][0]|0,arguments[1][1]|0,arguments[2]||P.RGBA,arguments[3]||P.UNSIGNED_BYTE);if(typeof arguments[1]=="object"){var T=arguments[1],z=v(T)?T:T.raw;if(z)return C(P,z,T.width|0,T.height|0,arguments[2]||P.RGBA,arguments[3]||P.UNSIGNED_BYTE);if(T.shape&&T.data&&T.stride)return M(P,T)}throw new Error("gl-texture2d: Invalid arguments for texture2d constructor")}},7790:function(){},7815:function(i,a,o){"use strict";var s=o(2931),l=o(9970),u=["xyz","xzy","yxz","yzx","zxy","zyx"],c=function(S,L,x,C){for(var M=S.points,g=S.velocities,P=S.divergences,T=[],z=[],O=[],V=[],G=[],Z=[],j=0,N=0,H=l.create(),te=l.create(),oe=8,_e=0;_e0)for(var ie=0;ieL)return C-1}return C},d=function(S,L,x){return 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ut=C[Fe+ge+ce],pt=C[Fe+ge+Ze],Zt=C[Fe+Re+ce],st=C[Fe+Re+Ze],lt=C[Pe+ge+ce],Gt=C[Pe+ge+Ze],Nt=C[Pe+Re+ce],Jt=C[Pe+Re+Ze],sr=s.create(),wr=s.create(),cr=s.create(),$e=s.create();s.lerp(sr,ut,lt,Se),s.lerp(wr,pt,Gt,Se),s.lerp(cr,Zt,Nt,Se),s.lerp($e,st,Jt,Se);var St=s.create(),Qt=s.create();s.lerp(St,sr,cr,Le),s.lerp(Qt,wr,$e,Le);var Vt=s.create();return s.lerp(Vt,St,Qt,Ae),Vt},_=function(S,L){var x=L[0],C=L[1],M=L[2];return S[0]=x<0?-x:x,S[1]=C<0?-C:C,S[2]=M<0?-M:M,S},b=function(S){var L=1/0;S.sort(function(g,P){return g-P});for(var x=S.length,C=1;CN||JtH||srte)},_e=s.distance(L[0],L[1]),Ee=10*_e/C,Ce=Ee*Ee,me=1,ie=0,Se=x.length;Se>1&&(me=p(x));for(var Le=0;Leie&&(ie=ut),ce.push(ut),V.push({points:Fe,velocities:Pe,divergences:ce});for(var pt=0;ptCe&&s.scale(Zt,Zt,Ee/Math.sqrt(st)),s.add(Zt,Zt,Ae),ge=z(Zt),s.squaredDistance(Re,Zt)-Ce>-1e-4*Ce){Fe.push(Zt),Re=Zt,Pe.push(ge);var Ze=O(Zt,ge),ut=s.length(Ze);isFinite(ut)&&ut>ie&&(ie=ut),ce.push(ut)}Ae=Zt}}var lt=f(V,S.colormap,ie,me);return 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s=o(620);i.exports=s.slice().concat(["layout","centroid","smooth","case","mat2x2","mat2x3","mat2x4","mat3x2","mat3x3","mat3x4","mat4x2","mat4x3","mat4x4","uvec2","uvec3","uvec4","samplerCubeShadow","sampler2DArray","sampler2DArrayShadow","isampler2D","isampler3D","isamplerCube","isampler2DArray","usampler2D","usampler3D","usamplerCube","usampler2DArray","coherent","restrict","readonly","writeonly","resource","atomic_uint","noperspective","patch","sample","subroutine","common","partition","active","filter","image1D","image2D","image3D","imageCube","iimage1D","iimage2D","iimage3D","iimageCube","uimage1D","uimage2D","uimage3D","uimageCube","image1DArray","image2DArray","iimage1DArray","iimage2DArray","uimage1DArray","uimage2DArray","image1DShadow","image2DShadow","image1DArrayShadow","image2DArrayShadow","imageBuffer","iimageBuffer","uimageBuffer","sampler1DArray","sampler1DArrayShadow","isampler1D","isampler1DArray","usampler1D","usampler1DArray","isampler2DRect","usampler2DRect","samplerBuffer","isamplerBuffer","usamplerBuffer","sampler2DMS","isampler2DMS","usampler2DMS","sampler2DMSArray","isampler2DMSArray","usampler2DMSArray"])},7960:function(i){i.exports=a;function 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O=M[0];M[0]=M[1],M[1]=O}E.push(M)}}return E};function p(k,E){var S=k.length;if(S===0)throw new Error("Must have at least d+1 points");var L=k[0].length;if(S<=L)throw new Error("Must input at least d+1 points");var x=k.slice(0,L+1),C=s.apply(void 0,x);if(C===0)throw new Error("Input not in general position");for(var M=new Array(L+1),g=0;g<=L;++g)M[g]=g;C<0&&(M[0]=1,M[1]=0);for(var P=new u(M,new Array(L+1),!1),T=P.adjacent,z=new Array(L+2),g=0;g<=L;++g){for(var O=M.slice(),V=0;V<=L;++V)V===g&&(O[V]=-1);var G=O[0];O[0]=O[1],O[1]=G;var Z=new u(O,new Array(L+1),!0);T[g]=Z,z[g]=Z}z[L+1]=P;for(var g=0;g<=L;++g)for(var O=T[g].vertices,j=T[g].adjacent,V=0;V<=L;++V){var N=O[V];if(N<0){j[V]=P;continue}for(var H=0;H<=L;++H)T[H].vertices.indexOf(N)<0&&(j[V]=T[H])}for(var te=new _(L,x,z),oe=!!E,g=L+1;g=1},p.isTransparent=function(){return this.opacity<1},p.pickSlots=1,p.setPickBase=function(C){this.pickId=C};function k(C){for(var M=v({colormap:C,nshades:256,format:"rgba"}),g=new 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V={model:g,view:P,projection:T,clipBounds:z,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},G=this.pickShader;G.bind(),G.uniforms=V,this.triangleCount>0&&(this.triangleVAO.bind(),M.drawArrays(M.TRIANGLES,0,this.triangleCount*3),this.triangleVAO.unbind())},p.pick=function(C){if(!C||C.id!==this.pickId)return null;var M=C.value[0]+256*C.value[1]+65536*C.value[2],g=this.cells[M],P=this.positions[g[1]].slice(0,3),T={position:P,dataCoordinate:P,index:Math.floor(g[1]/48)};return this.traceType==="cone"?T.index=Math.floor(g[1]/48):this.traceType==="streamtube"&&(T.intensity=this.intensity[g[1]],T.velocity=this.vectors[g[1]].slice(0,3),T.divergence=this.vectors[g[1]][3],T.index=M),T},p.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()};function S(C,M){var g=s(C,M.meshShader.vertex,M.meshShader.fragment,null,M.meshShader.attributes);return g.attributes.position.location=0,g.attributes.color.location=2,g.attributes.uv.location=3,g.attributes.vector.location=4,g}function L(C,M){var g=s(C,M.pickShader.vertex,M.pickShader.fragment,null,M.pickShader.attributes);return g.attributes.position.location=0,g.attributes.id.location=1,g.attributes.vector.location=4,g}function x(C,M,g){var P=g.shaders;arguments.length===1&&(M=C,C=M.gl);var 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E=0;E<3;++E)p[0][E]=Math.min(p[0][E],k[E]),p[1][E]=Math.max(p[1][E],k[E])}var v=function(){for(var p=new Array(3),k=0;k<3;++k){for(var E=[],S=1;S<=2;++S)for(var L=-1;L<=1;L+=2){var x=(S+k)%3,C=[0,0,0];C[x]=L,E.push(C)}p[k]=E}return p}();function _(p,k,E,S){for(var L=v[S],x=0;x0){var V=P.slice();V[M]+=z[1][M],L.push(P[0],P[1],P[2],O[0],O[1],O[2],O[3],0,0,0,V[0],V[1],V[2],O[0],O[1],O[2],O[3],0,0,0),d(this.bounds,V),C+=2+_(L,V,O,M)}}}this.lineCount[M]=C-this.lineOffset[M]}this.buffer.update(L)}},h.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()};function b(p){var k=p.gl,E=s(k),S=l(k,[{buffer:E,type:k.FLOAT,size:3,offset:0,stride:40},{buffer:E,type:k.FLOAT,size:4,offset:12,stride:40},{buffer:E,type:k.FLOAT,size:3,offset:28,stride:40}]),L=u(k);L.attributes.position.location=0,L.attributes.color.location=1,L.attributes.offset.location=2;var x=new f(k,E,S,L);return x.update(p),x}},9215:function(i,a,o){"use strict";i.exports=d;var s=o(4769),l=o(2478);function 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a(o,s,l){return o[0]=s[0]*l,o[1]=s[1]*l,o[2]=s[2]*l,o[3]=s[3]*l,o}},9346:function(i){"use strict";var a=new Float64Array(4),o=new Float64Array(4),s=new Float64Array(4);function l(u,c,f,h,d){a.length=_?(g=1,T=_+2*k+S):(g=-k/_,T=k*g+S)):(g=0,E>=0?(P=0,T=S):-E>=p?(P=1,T=p+2*E+S):(P=-E/p,T=E*P+S));else if(P<0)P=0,k>=0?(g=0,T=S):-k>=_?(g=1,T=_+2*k+S):(g=-k/_,T=k*g+S);else{var z=1/M;g*=z,P*=z,T=g*(_*g+b*P+2*k)+P*(b*g+p*P+2*E)+S}else{var O,V,G,Z;g<0?(O=b+k,V=p+E,V>O?(G=V-O,Z=_-2*b+p,G>=Z?(g=1,P=0,T=_+2*k+S):(g=G/Z,P=1-g,T=g*(_*g+b*P+2*k)+P*(b*g+p*P+2*E)+S)):(g=0,V<=0?(P=1,T=p+2*E+S):E>=0?(P=0,T=S):(P=-E/p,T=E*P+S))):P<0?(O=b+E,V=_+k,V>O?(G=V-O,Z=_-2*b+p,G>=Z?(P=1,g=0,T=p+2*E+S):(P=G/Z,g=1-P,T=g*(_*g+b*P+2*k)+P*(b*g+p*P+2*E)+S)):(P=0,V<=0?(g=1,T=_+2*k+S):k>=0?(g=0,T=S):(g=-k/_,T=k*g+S))):(G=p+E-b-k,G<=0?(g=0,P=1,T=p+2*E+S):(Z=_-2*b+p,G>=Z?(g=1,P=0,T=_+2*k+S):(g=G/Z,P=1-g,T=g*(_*g+b*P+2*k)+P*(b*g+p*P+2*E)+S)))}for(var j=1-g-P,v=0;vE)for(p=E;pk)for(p=k;p=0){for(var j=Z.type.charAt(Z.type.length-1)|0,N=new Array(j),H=0;H=0;)te+=1;V[G]=te}var oe=new Array(E.length);function _e(){x.program=c.program(C,x._vref,x._fref,O,V);for(var Ee=0;EePe&&Re>0){var ce=(ge[Re][0]-Pe)/(ge[Re][0]-ge[Re-1][0]);return ge[Re][1]*(1-ce)+ce*ge[Re-1][1]}}return 1}var H=[0,0,0],te={showSurface:!1,showContour:!1,projections:[T.slice(),T.slice(),T.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function oe(Pe,ge){var Re,ce,Ze,ut=ge.axes&&ge.axes.lastCubeProps.axis||H,pt=ge.showSurface,Zt=ge.showContour;for(Re=0;Re<3;++Re)for(pt=pt||ge.surfaceProject[Re],ce=0;ce<3;++ce)Zt=Zt||ge.contourProject[Re][ce];for(Re=0;Re<3;++Re){var st=te.projections[Re];for(ce=0;ce<16;++ce)st[ce]=0;for(ce=0;ce<4;++ce)st[5*ce]=1;st[5*Re]=0,st[12+Re]=ge.axesBounds[+(ut[Re]>0)][Re],p(st,Pe.model,st);var lt=te.clipBounds[Re];for(Ze=0;Ze<2;++Ze)for(ce=0;ce<3;++ce)lt[Ze][ce]=Pe.clipBounds[Ze][ce];lt[0][Re]=-1e8,lt[1][Re]=1e8}return te.showSurface=pt,te.showContour=Zt,te}var _e={model:T,view:T,projection:T,inverseModel:T.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},Ee=T.slice(),Ce=[1,0,0,0,1,0,0,0,1];function me(Pe,ge){Pe=Pe||{};var Re=this.gl;Re.disable(Re.CULL_FACE),this._colorMap.bind(0);var ce=_e;ce.model=Pe.model||T,ce.view=Pe.view||T,ce.projection=Pe.projection||T,ce.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],ce.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],ce.objectOffset=this.objectOffset,ce.contourColor=this.contourColor[0],ce.inverseModel=k(ce.inverseModel,ce.model);for(var Ze=0;Ze<2;++Ze)for(var ut=ce.clipBounds[Ze],pt=0;pt<3;++pt)ut[pt]=Math.min(Math.max(this.clipBounds[Ze][pt],-1e8),1e8);ce.kambient=this.ambientLight,ce.kdiffuse=this.diffuseLight,ce.kspecular=this.specularLight,ce.roughness=this.roughness,ce.fresnel=this.fresnel,ce.opacity=this.opacity,ce.height=0,ce.permutation=Ce,ce.vertexColor=this.vertexColor;var Zt=Ee;for(p(Zt,ce.view,ce.model),p(Zt,ce.projection,Zt),k(Zt,Zt),Ze=0;Ze<3;++Ze)ce.eyePosition[Ze]=Zt[12+Ze]/Zt[15];var st=Zt[15];for(Ze=0;Ze<3;++Ze)st+=this.lightPosition[Ze]*Zt[4*Ze+3];for(Ze=0;Ze<3;++Ze){var lt=Zt[12+Ze];for(pt=0;pt<3;++pt)lt+=Zt[4*pt+Ze]*this.lightPosition[pt];ce.lightPosition[Ze]=lt/st}var Gt=oe(ce,this);if(Gt.showSurface){for(this._shader.bind(),this._shader.uniforms=ce,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(Re.TRIANGLES,this._vertexCount),Ze=0;Ze<3;++Ze)!this.surfaceProject[Ze]||!this.vertexCount||(this._shader.uniforms.model=Gt.projections[Ze],this._shader.uniforms.clipBounds=Gt.clipBounds[Ze],this._vao.draw(Re.TRIANGLES,this._vertexCount));this._vao.unbind()}if(Gt.showContour){var Nt=this._contourShader;ce.kambient=1,ce.kdiffuse=0,ce.kspecular=0,ce.opacity=1,Nt.bind(),Nt.uniforms=ce;var Jt=this._contourVAO;for(Jt.bind(),Ze=0;Ze<3;++Ze)for(Nt.uniforms.permutation=O[Ze],Re.lineWidth(this.contourWidth[Ze]*this.pixelRatio),pt=0;pt>4)/16)/255,Ze=Math.floor(ce),ut=ce-Ze,pt=ge[1]*(Pe.value[1]+(Pe.value[2]&15)/16)/255,Zt=Math.floor(pt),st=pt-Zt;Ze+=1,Zt+=1;var lt=Re.position;lt[0]=lt[1]=lt[2]=0;for(var Gt=0;Gt<2;++Gt)for(var Nt=Gt?ut:1-ut,Jt=0;Jt<2;++Jt)for(var sr=Jt?st:1-st,wr=Ze+Gt,cr=Zt+Jt,$e=Nt*sr,St=0;St<3;++St)lt[St]+=this._field[St].get(wr,cr)*$e;for(var Qt=this._pickResult.level,Vt=0;Vt<3;++Vt)if(Qt[Vt]=E.le(this.contourLevels[Vt],lt[Vt]),Qt[Vt]<0)this.contourLevels[Vt].length>0&&(Qt[Vt]=0);else if(Qt[Vt]Math.abs(It-lt[Vt])&&(Qt[Vt]+=1)}for(Re.index[0]=ut<.5?Ze:Ze+1,Re.index[1]=st<.5?Zt:Zt+1,Re.uv[0]=ce/ge[0],Re.uv[1]=pt/ge[1],St=0;St<3;++St)Re.dataCoordinate[St]=this._field[St].get(Re.index[0],Re.index[1]);return Re},j.padField=function(Pe,ge){var Re=ge.shape.slice(),ce=Pe.shape.slice();d.assign(Pe.lo(1,1).hi(Re[0],Re[1]),ge),d.assign(Pe.lo(1).hi(Re[0],1),ge.hi(Re[0],1)),d.assign(Pe.lo(1,ce[1]-1).hi(Re[0],1),ge.lo(0,Re[1]-1).hi(Re[0],1)),d.assign(Pe.lo(0,1).hi(1,Re[1]),ge.hi(1)),d.assign(Pe.lo(ce[0]-1,1).hi(1,Re[1]),ge.lo(Re[0]-1)),Pe.set(0,0,ge.get(0,0)),Pe.set(0,ce[1]-1,ge.get(0,Re[1]-1)),Pe.set(ce[0]-1,0,ge.get(Re[0]-1,0)),Pe.set(ce[0]-1,ce[1]-1,ge.get(Re[0]-1,Re[1]-1))};function Se(Pe,ge){return Array.isArray(Pe)?[ge(Pe[0]),ge(Pe[1]),ge(Pe[2])]:[ge(Pe),ge(Pe),ge(Pe)]}function Le(Pe){return Array.isArray(Pe)?Pe.length===3?[Pe[0],Pe[1],Pe[2],1]:[Pe[0],Pe[1],Pe[2],Pe[3]]:[0,0,0,1]}function Ae(Pe){if(Array.isArray(Pe)){if(Array.isArray(Pe))return[Le(Pe[0]),Le(Pe[1]),Le(Pe[2])];var ge=Le(Pe);return[ge.slice(),ge.slice(),ge.slice()]}}j.update=function(Pe){Pe=Pe||{},this.objectOffset=Pe.objectOffset||this.objectOffset,this.dirty=!0,"contourWidth"in Pe&&(this.contourWidth=Se(Pe.contourWidth,Number)),"showContour"in Pe&&(this.showContour=Se(Pe.showContour,Boolean)),"showSurface"in Pe&&(this.showSurface=!!Pe.showSurface),"contourTint"in Pe&&(this.contourTint=Se(Pe.contourTint,Boolean)),"contourColor"in Pe&&(this.contourColor=Ae(Pe.contourColor)),"contourProject"in Pe&&(this.contourProject=Se(Pe.contourProject,function(yn){return Se(yn,Boolean)})),"surfaceProject"in Pe&&(this.surfaceProject=Pe.surfaceProject),"dynamicColor"in Pe&&(this.dynamicColor=Ae(Pe.dynamicColor)),"dynamicTint"in Pe&&(this.dynamicTint=Se(Pe.dynamicTint,Number)),"dynamicWidth"in Pe&&(this.dynamicWidth=Se(Pe.dynamicWidth,Number)),"opacity"in Pe&&(this.opacity=Pe.opacity),"opacityscale"in Pe&&(this.opacityscale=Pe.opacityscale),"colorBounds"in Pe&&(this.colorBounds=Pe.colorBounds),"vertexColor"in Pe&&(this.vertexColor=Pe.vertexColor?1:0),"colormap"in Pe&&this._colorMap.setPixels(this.genColormap(Pe.colormap,this.opacityscale));var ge=Pe.field||Pe.coords&&Pe.coords[2]||null,Re=!1;if(ge||(this._field[2].shape[0]||this._field[2].shape[2]?ge=this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):ge=this._field[2].hi(0,0)),"field"in Pe||"coords"in Pe){var ce=(ge.shape[0]+2)*(ge.shape[1]+2);ce>this._field[2].data.length&&(f.freeFloat(this._field[2].data),this._field[2].data=f.mallocFloat(s.nextPow2(ce))),this._field[2]=_(this._field[2].data,[ge.shape[0]+2,ge.shape[1]+2]),this.padField(this._field[2],ge),this.shape=ge.shape.slice();for(var Ze=this.shape,ut=0;ut<2;++ut)this._field[2].size>this._field[ut].data.length&&(f.freeFloat(this._field[ut].data),this._field[ut].data=f.mallocFloat(this._field[2].size)),this._field[ut]=_(this._field[ut].data,[Ze[0]+2,Ze[1]+2]);if(Pe.coords){var pt=Pe.coords;if(!Array.isArray(pt)||pt.length!==3)throw new Error("gl-surface: invalid coordinates for x/y");for(ut=0;ut<2;++ut){var Zt=pt[ut];for(Jt=0;Jt<2;++Jt)if(Zt.shape[Jt]!==Ze[Jt])throw new Error("gl-surface: coords have incorrect shape");this.padField(this._field[ut],Zt)}}else if(Pe.ticks){var st=Pe.ticks;if(!Array.isArray(st)||st.length!==2)throw new Error("gl-surface: invalid ticks");for(ut=0;ut<2;++ut){var lt=st[ut];if((Array.isArray(lt)||lt.length)&&(lt=_(lt)),lt.shape[0]!==Ze[ut])throw new Error("gl-surface: invalid tick length");var Gt=_(lt.data,Ze);Gt.stride[ut]=lt.stride[0],Gt.stride[ut^1]=0,this.padField(this._field[ut],Gt)}}else{for(ut=0;ut<2;++ut){var Nt=[0,0];Nt[ut]=1,this._field[ut]=_(this._field[ut].data,[Ze[0]+2,Ze[1]+2],Nt,0)}this._field[0].set(0,0,0);for(var Jt=0;Jt0){for(var tn=0;tn<5;++tn)pi.pop();je-=1}continue e}}}In.push(je)}this._contourOffsets[$r]=ji,this._contourCounts[$r]=In}var fn=f.mallocFloat(pi.length);for(ut=0;ut=0&&(M=x|0,C+=P*M,g-=M),new E(this.data,g,P,C)},S.step=function(x){var C=this.shape[0],M=this.stride[0],g=this.offset,P=0,T=Math.ceil;return typeof x=="number"&&(P=x|0,P<0?(g+=M*(C-1),C=T(-C/P)):C=T(C/P),M*=P),new E(this.data,C,M,g)},S.transpose=function(x){x=x===void 0?0:x|0;var C=this.shape,M=this.stride;return new E(this.data,C[x],M[x],this.offset)},S.pick=function(x){var C=[],M=[],g=this.offset;typeof x=="number"&&x>=0?g=g+this.stride[0]*x|0:(C.push(this.shape[0]),M.push(this.stride[0]));var P=p[C.length+1];return P(this.data,C,M,g)},function(x,C,M,g){return new E(x,C[0],M[0],g)}},2:function(b,p,k){function E(L,x,C,M,g,P){this.data=L,this.shape=[x,C],this.stride=[M,g],this.offset=P|0}var S=E.prototype;return S.dtype=b,S.dimension=2,Object.defineProperty(S,"size",{get:function(){return this.shape[0]*this.shape[1]}}),Object.defineProperty(S,"order",{get:function(){return Math.abs(this.stride[0])>Math.abs(this.stride[1])?[1,0]:[0,1]}}),S.set=function(x,C,M){return b==="generic"?this.data.set(this.offset+this.stride[0]*x+this.stride[1]*C,M):this.data[this.offset+this.stride[0]*x+this.stride[1]*C]=M},S.get=function(x,C){return b==="generic"?this.data.get(this.offset+this.stride[0]*x+this.stride[1]*C):this.data[this.offset+this.stride[0]*x+this.stride[1]*C]},S.index=function(x,C){return this.offset+this.stride[0]*x+this.stride[1]*C},S.hi=function(x,C){return new E(this.data,typeof x!="number"||x<0?this.shape[0]:x|0,typeof C!="number"||C<0?this.shape[1]:C|0,this.stride[0],this.stride[1],this.offset)},S.lo=function(x,C){var M=this.offset,g=0,P=this.shape[0],T=this.shape[1],z=this.stride[0],O=this.stride[1];return typeof x=="number"&&x>=0&&(g=x|0,M+=z*g,P-=g),typeof 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S.dtype=b,S.dimension=3,Object.defineProperty(S,"size",{get:function(){return this.shape[0]*this.shape[1]*this.shape[2]}}),Object.defineProperty(S,"order",{get:function(){var x=Math.abs(this.stride[0]),C=Math.abs(this.stride[1]),M=Math.abs(this.stride[2]);return x>C?C>M?[2,1,0]:x>M?[1,2,0]:[1,0,2]:x>M?[2,0,1]:M>C?[0,1,2]:[0,2,1]}}),S.set=function(x,C,M,g){return b==="generic"?this.data.set(this.offset+this.stride[0]*x+this.stride[1]*C+this.stride[2]*M,g):this.data[this.offset+this.stride[0]*x+this.stride[1]*C+this.stride[2]*M]=g},S.get=function(x,C,M){return b==="generic"?this.data.get(this.offset+this.stride[0]*x+this.stride[1]*C+this.stride[2]*M):this.data[this.offset+this.stride[0]*x+this.stride[1]*C+this.stride[2]*M]},S.index=function(x,C,M){return this.offset+this.stride[0]*x+this.stride[1]*C+this.stride[2]*M},S.hi=function(x,C,M){return new E(this.data,typeof x!="number"||x<0?this.shape[0]:x|0,typeof C!="number"||C<0?this.shape[1]:C|0,typeof 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QIt=fIe.prototype;QIt.merge=function(e,t){for(var r=this,n=0;n<3;++n){var i=t[$It[n]];if(!i.visible){r.tickEnable[n]=!1,r.labelEnable[n]=!1,r.lineEnable[n]=!1,r.lineTickEnable[n]=!1,r.gridEnable[n]=!1,r.zeroEnable[n]=!1,r.backgroundEnable[n]=!1;continue}r.labels[n]=e._meta?JIt.templateString(i.title.text,e._meta):i.title.text,"font"in i.title&&(i.title.font.color&&(r.labelColor[n]=G2(i.title.font.color)),i.title.font.family&&(r.labelFont[n]=i.title.font.family),i.title.font.size&&(r.labelSize[n]=i.title.font.size),i.title.font.weight&&(r.labelFontWeight[n]=i.title.font.weight),i.title.font.style&&(r.labelFontStyle[n]=i.title.font.style),i.title.font.variant&&(r.labelFontVariant[n]=i.title.font.variant)),"showline"in i&&(r.lineEnable[n]=i.showline),"linecolor"in i&&(r.lineColor[n]=G2(i.linecolor)),"linewidth"in i&&(r.lineWidth[n]=i.linewidth),"showgrid"in i&&(r.gridEnable[n]=i.showgrid),"gridcolor"in i&&(r.gridColor[n]=G2(i.gridcolor)),"gridwidth"in i&&(r.gridWidth[n]=i.gridwidth),i.type==="log"?r.zeroEnable[n]=!1:"zeroline"in i&&(r.zeroEnable[n]=i.zeroline),"zerolinecolor"in i&&(r.zeroLineColor[n]=G2(i.zerolinecolor)),"zerolinewidth"in i&&(r.zeroLineWidth[n]=i.zerolinewidth),"ticks"in i&&i.ticks?r.lineTickEnable[n]=!0:r.lineTickEnable[n]=!1,"ticklen"in i&&(r.lineTickLength[n]=r._defaultLineTickLength[n]=i.ticklen),"tickcolor"in i&&(r.lineTickColor[n]=G2(i.tickcolor)),"tickwidth"in i&&(r.lineTickWidth[n]=i.tickwidth),"tickangle"in i&&(r.tickAngle[n]=i.tickangle==="auto"?-3600:Math.PI*-i.tickangle/180),"showticklabels"in i&&(r.tickEnable[n]=i.showticklabels),"tickfont"in i&&(i.tickfont.color&&(r.tickColor[n]=G2(i.tickfont.color)),i.tickfont.family&&(r.tickFont[n]=i.tickfont.family),i.tickfont.size&&(r.tickSize[n]=i.tickfont.size),i.tickfont.weight&&(r.tickFontWeight[n]=i.tickfont.weight),i.tickfont.style&&(r.tickFontStyle[n]=i.tickfont.style),i.tickfont.variant&&(r.tickFontVariant[n]=i.tickfont.variant)),"mirror"in i?["ticks","all","allticks"].indexOf(i.mirror)!==-1?(r.lineTickMirror[n]=!0,r.lineMirror[n]=!0):i.mirror===!0?(r.lineTickMirror[n]=!1,r.lineMirror[n]=!0):(r.lineTickMirror[n]=!1,r.lineMirror[n]=!1):r.lineMirror[n]=!1,"showbackground"in i&&i.showbackground!==!1?(r.backgroundEnable[n]=!0,r.backgroundColor[n]=G2(i.backgroundcolor)):r.backgroundEnable[n]=!1}};function e8t(e,t){var r=new fIe;return r.merge(e,t),r}hIe.exports=e8t});var gIe=ye((sgr,pIe)=>{"use strict";var t8t=Jy(),r8t=["xaxis","yaxis","zaxis"];function vIe(){this.enabled=[!0,!0,!0],this.colors=[[0,0,0,1],[0,0,0,1],[0,0,0,1]],this.drawSides=[!0,!0,!0],this.lineWidth=[1,1,1]}var i8t=vIe.prototype;i8t.merge=function(e){for(var t=0;t<3;++t){var r=e[r8t[t]];if(!r.visible){this.enabled[t]=!1,this.drawSides[t]=!1;continue}this.enabled[t]=r.showspikes,this.colors[t]=t8t(r.spikecolor),this.drawSides[t]=r.spikesides,this.lineWidth[t]=r.spikethickness}};function n8t(e){var t=new vIe;return t.merge(e),t}pIe.exports=n8t});var _Ie=ye((lgr,yIe)=>{"use strict";yIe.exports=u8t;var mIe=ho(),a8t=Dr(),o8t=["xaxis","yaxis","zaxis"],s8t=[0,0,0];function l8t(e){for(var t=new Array(3),r=0;r<3;++r){for(var n=e[r],i=new Array(n.length),a=0;a/g," "));i[a]=u,o.tickmode=s}}t.ticks=i;for(var a=0;a<3;++a){s8t[a]=.5*(e.glplot.bounds[0][a]+e.glplot.bounds[1][a]);for(var c=0;c<2;++c)t.bounds[c][a]=e.glplot.bounds[c][a]}e.contourLevels=l8t(i)}});var MIe=ye((ugr,SIe)=>{"use strict";var wIe=Od().gl_plot3d,c8t=wIe.createCamera,xIe=wIe.createScene,f8t=lIe(),h8t=RL(),iF=qa(),up=Dr(),rF=up.preserveDrawingBuffer(),nF=ho(),Jg=vf(),d8t=Jy(),v8t=CX(),p8t=UU(),g8t=dIe(),m8t=gIe(),y8t=_Ie(),_8t=Ag().applyAutorangeOptions,YE,tF,TIe=!1;function AIe(e,t){var r=document.createElement("div"),n=e.container;this.graphDiv=e.graphDiv;var i=document.createElementNS("http://www.w3.org/2000/svg","svg");i.style.position="absolute",i.style.top=i.style.left="0px",i.style.width=i.style.height="100%",i.style["z-index"]=20,i.style["pointer-events"]="none",r.appendChild(i),this.svgContainer=i,r.id=e.id,r.style.position="absolute",r.style.top=r.style.left="0px",r.style.width=r.style.height="100%",n.appendChild(r),this.fullLayout=t,this.id=e.id||"scene",this.fullSceneLayout=t[this.id],this.plotArgs=[[],{},{}],this.axesOptions=g8t(t,t[this.id]),this.spikeOptions=m8t(t[this.id]),this.container=r,this.staticMode=!!e.staticPlot,this.pixelRatio=this.pixelRatio||e.plotGlPixelRatio||2,this.dataScale=[1,1,1],this.contourLevels=[[],[],[]],this.convertAnnotations=iF.getComponentMethod("annotations3d","convert"),this.drawAnnotations=iF.getComponentMethod("annotations3d","draw"),this.initializeGLPlot()}var Sv=AIe.prototype;Sv.prepareOptions=function(){var e=this,t={canvas:e.canvas,gl:e.gl,glOptions:{preserveDrawingBuffer:rF,premultipliedAlpha:!0,antialias:!0},container:e.container,axes:e.axesOptions,spikes:e.spikeOptions,pickRadius:10,snapToData:!0,autoScale:!0,autoBounds:!1,cameraObject:e.camera,pixelRatio:e.pixelRatio};if(e.staticMode){if(!tF&&(YE=document.createElement("canvas"),tF=f8t({canvas:YE,preserveDrawingBuffer:!0,premultipliedAlpha:!0,antialias:!0}),!tF))throw new Error("error creating static canvas/context for image server");t.gl=tF,t.canvas=YE}return t};var bIe=!0;Sv.tryCreatePlot=function(){var e=this,t=e.prepareOptions(),r=!0;try{e.glplot=xIe(t)}catch(n){if(e.staticMode||!bIe||rF)r=!1;else{up.warn(["webgl setup failed possibly due to","false preserveDrawingBuffer config.","The mobile/tablet device may not be detected by is-mobile module.","Enabling preserveDrawingBuffer in second attempt to create webgl scene..."].join(" "));try{rF=t.glOptions.preserveDrawingBuffer=!0,e.glplot=xIe(t)}catch(i){rF=t.glOptions.preserveDrawingBuffer=!1,r=!1}}}return bIe=!1,r};Sv.initializeGLCamera=function(){var e=this,t=e.fullSceneLayout.camera,r=t.projection.type==="orthographic";e.camera=c8t(e.container,{center:[t.center.x,t.center.y,t.center.z],eye:[t.eye.x,t.eye.y,t.eye.z],up:[t.up.x,t.up.y,t.up.z],_ortho:r,zoomMin:.01,zoomMax:100,mode:"orbit"})};Sv.initializeGLPlot=function(){var e=this;e.initializeGLCamera();var t=e.tryCreatePlot();if(!t)return v8t(e);e.traces={},e.make4thDimension();var r=e.graphDiv,n=r.layout,i=function(){var o={};return e.isCameraChanged(n)&&(o[e.id+".camera"]=e.getCamera()),e.isAspectChanged(n)&&(o[e.id+".aspectratio"]=e.glplot.getAspectratio(),n[e.id].aspectmode!=="manual"&&(e.fullSceneLayout.aspectmode=n[e.id].aspectmode=o[e.id+".aspectmode"]="manual")),o},a=function(o){if(o.fullSceneLayout.dragmode!==!1){var s=i();o.saveLayout(n),o.graphDiv.emit("plotly_relayout",s)}};return e.glplot.canvas&&(e.glplot.canvas.addEventListener("mouseup",function(){a(e)}),e.glplot.canvas.addEventListener("touchstart",function(){TIe=!0}),e.glplot.canvas.addEventListener("wheel",function(o){if(r._context._scrollZoom.gl3d){if(e.camera._ortho){var s=o.deltaX>o.deltaY?1.1:.9090909090909091,l=e.glplot.getAspectratio();e.glplot.setAspectratio({x:s*l.x,y:s*l.y,z:s*l.z})}a(e)}},h8t?{passive:!1}:!1),e.glplot.canvas.addEventListener("mousemove",function(){if(e.fullSceneLayout.dragmode!==!1&&e.camera.mouseListener.buttons!==0){var o=i();e.graphDiv.emit("plotly_relayouting",o)}}),e.staticMode||e.glplot.canvas.addEventListener("webglcontextlost",function(o){r&&r.emit&&r.emit("plotly_webglcontextlost",{event:o,layer:e.id})},!1)),e.glplot.oncontextloss=function(){e.recoverContext()},e.glplot.onrender=function(){e.render()},!0};Sv.render=function(){var e=this,t=e.graphDiv,r,n=e.svgContainer,i=e.container.getBoundingClientRect();t._fullLayout._calcInverseTransform(t);var a=t._fullLayout._invScaleX,o=t._fullLayout._invScaleY,s=i.width*a,l=i.height*o;n.setAttributeNS(null,"viewBox","0 0 "+s+" "+l),n.setAttributeNS(null,"width",s),n.setAttributeNS(null,"height",l),y8t(e),e.glplot.axes.update(e.axesOptions);for(var u=Object.keys(e.traces),c=null,f=e.glplot.selection,h=0;h")):r.type==="isosurface"||r.type==="volume"?(p.valueLabel=nF.hoverLabelText(e._mockAxis,e._mockAxis.d2l(f.traceCoordinate[3]),r.valuehoverformat),x.push("value: "+p.valueLabel),f.textLabel&&x.push(f.textLabel),L=x.join("
")):L=f.textLabel;var C={x:f.traceCoordinate[0],y:f.traceCoordinate[1],z:f.traceCoordinate[2],data:_._input,fullData:_,curveNumber:_.index,pointNumber:b};Jg.appendArrayPointValue(C,_,b),r._module.eventData&&(C=_._module.eventData(C,f,_,{},b));var M={points:[C]};if(e.fullSceneLayout.hovermode){var g=[];Jg.loneHover({trace:_,x:(.5+.5*v[0]/v[3])*s,y:(.5-.5*v[1]/v[3])*l,xLabel:p.xLabel,yLabel:p.yLabel,zLabel:p.zLabel,text:L,name:c.name,color:Jg.castHoverOption(_,b,"bgcolor")||c.color,borderColor:Jg.castHoverOption(_,b,"bordercolor"),fontFamily:Jg.castHoverOption(_,b,"font.family"),fontSize:Jg.castHoverOption(_,b,"font.size"),fontColor:Jg.castHoverOption(_,b,"font.color"),nameLength:Jg.castHoverOption(_,b,"namelength"),textAlign:Jg.castHoverOption(_,b,"align"),hovertemplate:up.castOption(_,b,"hovertemplate"),hovertemplateLabels:up.extendFlat({},C,p),eventData:[C]},{container:n,gd:t,inOut_bbox:g}),C.bbox=g[0]}f.distance<5&&(f.buttons||TIe)?t.emit("plotly_click",M):t.emit("plotly_hover",M),this.oldEventData=M}else Jg.loneUnhover(n),this.oldEventData&&t.emit("plotly_unhover",this.oldEventData),this.oldEventData=void 0;e.drawAnnotations(e)};Sv.recoverContext=function(){var e=this;e.glplot.dispose();var t=function(){if(e.glplot.gl.isContextLost()){requestAnimationFrame(t);return}if(!e.initializeGLPlot()){up.error("Catastrophic and unrecoverable WebGL error. Context lost.");return}e.plot.apply(e,e.plotArgs)};requestAnimationFrame(t)};var KE=["xaxis","yaxis","zaxis"];function x8t(e,t,r){for(var n=e.fullSceneLayout,i=0;i<3;i++){var a=KE[i],o=a.charAt(0),s=n[a],l=t[o],u=t[o+"calendar"],c=t["_"+o+"length"];if(!up.isArrayOrTypedArray(l))r[0][i]=Math.min(r[0][i],0),r[1][i]=Math.max(r[1][i],c-1);else for(var f,h=0;h<(c||l.length);h++)if(up.isArrayOrTypedArray(l[h]))for(var d=0;d_[1][o])_[0][o]=-1,_[1][o]=1;else{var T=_[1][o]-_[0][o];_[0][o]-=T/32,_[1][o]+=T/32}if(k=[_[0][o],_[1][o]],k=_8t(k,l),_[0][o]=k[0],_[1][o]=k[1],l.isReversed()){var z=_[0][o];_[0][o]=_[1][o],_[1][o]=z}}else k=l.range,_[0][o]=l.r2l(k[0]),_[1][o]=l.r2l(k[1]);_[0][o]===_[1][o]&&(_[0][o]-=1,_[1][o]+=1),b[o]=_[1][o]-_[0][o],l.range=[_[0][o],_[1][o]],l.limitRange(),n.glplot.setBounds(o,{min:l.range[0]*d[o],max:l.range[1]*d[o]})}var O,V=c.aspectmode;if(V==="cube")O=[1,1,1];else if(V==="manual"){var G=c.aspectratio;O=[G.x,G.y,G.z]}else if(V==="auto"||V==="data"){var Z=[1,1,1];for(o=0;o<3;++o){l=c[KE[o]],u=l.type;var j=p[u];Z[o]=Math.pow(j.acc,1/j.count)/d[o]}V==="data"||Math.max.apply(null,Z)/Math.min.apply(null,Z)<=4?O=Z:O=[1,1,1]}else throw new Error("scene.js aspectRatio was not one of the enumerated types");c.aspectratio.x=f.aspectratio.x=O[0],c.aspectratio.y=f.aspectratio.y=O[1],c.aspectratio.z=f.aspectratio.z=O[2],n.glplot.setAspectratio(c.aspectratio),n.viewInitial.aspectratio||(n.viewInitial.aspectratio={x:c.aspectratio.x,y:c.aspectratio.y,z:c.aspectratio.z}),n.viewInitial.aspectmode||(n.viewInitial.aspectmode=c.aspectmode);var N=c.domain||null,H=t._size||null;if(N&&H){var te=n.container.style;te.position="absolute",te.left=H.l+N.x[0]*H.w+"px",te.top=H.t+(1-N.y[1])*H.h+"px",te.width=H.w*(N.x[1]-N.x[0])+"px",te.height=H.h*(N.y[1]-N.y[0])+"px"}n.glplot.redraw()}};Sv.destroy=function(){var e=this;e.glplot&&(e.camera.mouseListener.enabled=!1,e.container.removeEventListener("wheel",e.camera.wheelListener),e.camera=null,e.glplot.dispose(),e.container.parentNode.removeChild(e.container),e.glplot=null)};function w8t(e){return[[e.eye.x,e.eye.y,e.eye.z],[e.center.x,e.center.y,e.center.z],[e.up.x,e.up.y,e.up.z]]}function T8t(e){return{up:{x:e.up[0],y:e.up[1],z:e.up[2]},center:{x:e.center[0],y:e.center[1],z:e.center[2]},eye:{x:e.eye[0],y:e.eye[1],z:e.eye[2]},projection:{type:e._ortho===!0?"orthographic":"perspective"}}}Sv.getCamera=function(){var e=this;return e.camera.view.recalcMatrix(e.camera.view.lastT()),T8t(e.camera)};Sv.setViewport=function(e){var t=this,r=e.camera;t.camera.lookAt.apply(this,w8t(r)),t.glplot.setAspectratio(e.aspectratio);var n=r.projection.type==="orthographic",i=t.camera._ortho;n!==i&&(t.glplot.redraw(),t.glplot.clearRGBA(),t.glplot.dispose(),t.initializeGLPlot())};Sv.isCameraChanged=function(e){var t=this,r=t.getCamera(),n=up.nestedProperty(e,t.id+".camera"),i=n.get();function a(u,c,f,h){var d=["up","center","eye"],v=["x","y","z"];return c[d[f]]&&u[d[f]][v[h]]===c[d[f]][v[h]]}var o=!1;if(i===void 0)o=!0;else{for(var s=0;s<3;s++)for(var l=0;l<3;l++)if(!a(r,i,s,l)){o=!0;break}(!i.projection||r.projection&&r.projection.type!==i.projection.type)&&(o=!0)}return o};Sv.isAspectChanged=function(e){var t=this,r=t.glplot.getAspectratio(),n=up.nestedProperty(e,t.id+".aspectratio"),i=n.get();return i===void 0||i.x!==r.x||i.y!==r.y||i.z!==r.z};Sv.saveLayout=function(e){var t=this,r=t.fullLayout,n,i,a,o,s,l,u=t.isCameraChanged(e),c=t.isAspectChanged(e),f=u||c;if(f){var h={};if(u&&(n=t.getCamera(),i=up.nestedProperty(e,t.id+".camera"),a=i.get(),h[t.id+".camera"]=a),c&&(o=t.glplot.getAspectratio(),s=up.nestedProperty(e,t.id+".aspectratio"),l=s.get(),h[t.id+".aspectratio"]=l),iF.call("_storeDirectGUIEdit",e,r._preGUI,h),u){i.set(n);var d=up.nestedProperty(r,t.id+".camera");d.set(n)}if(c){s.set(o);var v=up.nestedProperty(r,t.id+".aspectratio");v.set(o),t.glplot.redraw()}}return f};Sv.updateFx=function(e,t){var r=this,n=r.camera;if(n)if(e==="orbit")n.mode="orbit",n.keyBindingMode="rotate";else if(e==="turntable"){n.up=[0,0,1],n.mode="turntable",n.keyBindingMode="rotate";var i=r.graphDiv,a=i._fullLayout,o=r.fullSceneLayout.camera,s=o.up.x,l=o.up.y,u=o.up.z;if(u/Math.sqrt(s*s+l*l+u*u)<.999){var c=r.id+".camera.up",f={x:0,y:0,z:1},h={};h[c]=f;var d=i.layout;iF.call("_storeDirectGUIEdit",d,a._preGUI,h),o.up=f,up.nestedProperty(d,c).set(f)}}else n.keyBindingMode=e;r.fullSceneLayout.hovermode=t};function A8t(e,t,r){for(var n=0,i=r-1;n0)for(var s=255/o,l=0;l<3;++l)e[a+l]=Math.min(s*e[a+l],255)}}Sv.toImage=function(e){var t=this;e||(e="png"),t.staticMode&&t.container.appendChild(YE),t.glplot.redraw();var r=t.glplot.gl,n=r.drawingBufferWidth,i=r.drawingBufferHeight;r.bindFramebuffer(r.FRAMEBUFFER,null);var a=new Uint8Array(n*i*4);r.readPixels(0,0,n,i,r.RGBA,r.UNSIGNED_BYTE,a),A8t(a,n,i),S8t(a,n,i);var o=document.createElement("canvas");o.width=n,o.height=i;var s=o.getContext("2d",{willReadFrequently:!0}),l=s.createImageData(n,i);l.data.set(a),s.putImageData(l,0,0);var u;switch(e){case"jpeg":u=o.toDataURL("image/jpeg");break;case"webp":u=o.toDataURL("image/webp");break;default:u=o.toDataURL("image/png")}return t.staticMode&&t.container.removeChild(YE),u};Sv.setConvert=function(){for(var e=this,t=0;t<3;t++){var r=e.fullSceneLayout[KE[t]];nF.setConvert(r,e.fullLayout),r.setScale=up.noop}};Sv.make4thDimension=function(){var e=this,t=e.graphDiv,r=t._fullLayout;e._mockAxis={type:"linear",showexponent:"all",exponentformat:"B"},nF.setConvert(e._mockAxis,r)};SIe.exports=AIe});var kIe=ye((cgr,EIe)=>{"use strict";EIe.exports={scene:{valType:"subplotid",dflt:"scene",editType:"calc+clearAxisTypes"}}});var PX=ye((fgr,CIe)=>{"use strict";var M8t=ka(),xs=Rd(),LX=Ao().extendFlat,E8t=mc().overrideAll;CIe.exports=E8t({visible:xs.visible,showspikes:{valType:"boolean",dflt:!0},spikesides:{valType:"boolean",dflt:!0},spikethickness:{valType:"number",min:0,dflt:2},spikecolor:{valType:"color",dflt:M8t.defaultLine},showbackground:{valType:"boolean",dflt:!1},backgroundcolor:{valType:"color",dflt:"rgba(204, 204, 204, 0.5)"},showaxeslabels:{valType:"boolean",dflt:!0},color:xs.color,categoryorder:xs.categoryorder,categoryarray:xs.categoryarray,title:{text:xs.title.text,font:xs.title.font},type:LX({},xs.type,{values:["-","linear","log","date","category"]}),autotypenumbers:xs.autotypenumbers,autorange:xs.autorange,autorangeoptions:{minallowed:xs.autorangeoptions.minallowed,maxallowed:xs.autorangeoptions.maxallowed,clipmin:xs.autorangeoptions.clipmin,clipmax:xs.autorangeoptions.clipmax,include:xs.autorangeoptions.include,editType:"plot"},rangemode:xs.rangemode,minallowed:xs.minallowed,maxallowed:xs.maxallowed,range:LX({},xs.range,{items:[{valType:"any",editType:"plot",impliedEdits:{"^autorange":!1}},{valType:"any",editType:"plot",impliedEdits:{"^autorange":!1}}],anim:!1}),tickmode:xs.minor.tickmode,nticks:xs.nticks,tick0:xs.tick0,dtick:xs.dtick,tickvals:xs.tickvals,ticktext:xs.ticktext,ticks:xs.ticks,mirror:xs.mirror,ticklen:xs.ticklen,tickwidth:xs.tickwidth,tickcolor:xs.tickcolor,showticklabels:xs.showticklabels,labelalias:xs.labelalias,tickfont:xs.tickfont,tickangle:xs.tickangle,tickprefix:xs.tickprefix,showtickprefix:xs.showtickprefix,ticksuffix:xs.ticksuffix,showticksuffix:xs.showticksuffix,showexponent:xs.showexponent,exponentformat:xs.exponentformat,minexponent:xs.minexponent,separatethousands:xs.separatethousands,tickformat:xs.tickformat,tickformatstops:xs.tickformatstops,hoverformat:xs.hoverformat,showline:xs.showline,linecolor:xs.linecolor,linewidth:xs.linewidth,showgrid:xs.showgrid,gridcolor:LX({},xs.gridcolor,{dflt:"rgb(204, 204, 204)"}),gridwidth:xs.gridwidth,zeroline:xs.zeroline,zerolinecolor:xs.zerolinecolor,zerolinewidth:xs.zerolinewidth},"plot","from-root")});var FX=ye((hgr,LIe)=>{"use strict";var IX=PX(),k8t=Cc().attributes,RX=Ao().extendFlat,C8t=Dr().counterRegex;function DX(e,t,r){return{x:{valType:"number",dflt:e,editType:"camera"},y:{valType:"number",dflt:t,editType:"camera"},z:{valType:"number",dflt:r,editType:"camera"},editType:"camera"}}LIe.exports={_arrayAttrRegexps:[C8t("scene",".annotations",!0)],bgcolor:{valType:"color",dflt:"rgba(0,0,0,0)",editType:"plot"},camera:{up:RX(DX(0,0,1),{}),center:RX(DX(0,0,0),{}),eye:RX(DX(1.25,1.25,1.25),{}),projection:{type:{valType:"enumerated",values:["perspective","orthographic"],dflt:"perspective",editType:"calc"},editType:"calc"},editType:"camera"},domain:k8t({name:"scene",editType:"plot"}),aspectmode:{valType:"enumerated",values:["auto","cube","data","manual"],dflt:"auto",editType:"plot",impliedEdits:{"aspectratio.x":void 0,"aspectratio.y":void 0,"aspectratio.z":void 0}},aspectratio:{x:{valType:"number",min:0,editType:"plot",impliedEdits:{"^aspectmode":"manual"}},y:{valType:"number",min:0,editType:"plot",impliedEdits:{"^aspectmode":"manual"}},z:{valType:"number",min:0,editType:"plot",impliedEdits:{"^aspectmode":"manual"}},editType:"plot",impliedEdits:{aspectmode:"manual"}},xaxis:IX,yaxis:IX,zaxis:IX,dragmode:{valType:"enumerated",values:["orbit","turntable","zoom","pan",!1],editType:"plot"},hovermode:{valType:"enumerated",values:["closest",!1],dflt:"closest",editType:"modebar"},uirevision:{valType:"any",editType:"none"},editType:"plot"}});var DIe=ye((dgr,RIe)=>{"use strict";var L8t=cd().mix,PIe=Dr(),P8t=vl(),I8t=PX(),R8t=SU(),D8t=i4(),IIe=["xaxis","yaxis","zaxis"],F8t=100*136/187;RIe.exports=function(t,r,n){var i,a;function o(u,c){return PIe.coerce(i,a,I8t,u,c)}for(var s=0;s{"use strict";var z8t=Dr(),O8t=ka(),q8t=qa(),B8t=k_(),N8t=DIe(),FIe=FX(),U8t=Id().getSubplotData,zIe="gl3d";OIe.exports=function(t,r,n){var i=r._basePlotModules.length>1;function a(o){if(!i){var s=z8t.validate(t[o],FIe[o]);if(s)return t[o]}}B8t(t,r,n,{type:zIe,attributes:FIe,handleDefaults:V8t,fullLayout:r,font:r.font,fullData:n,getDfltFromLayout:a,autotypenumbersDflt:r.autotypenumbers,paper_bgcolor:r.paper_bgcolor,calendar:r.calendar})};function V8t(e,t,r,n){for(var i=r("bgcolor"),a=O8t.combine(i,n.paper_bgcolor),o=["up","center","eye"],s=0;s.999)&&(h="turntable")}else h="turntable";r("dragmode",h),r("hovermode",n.getDfltFromLayout("hovermode"))}});var $_=ye(cp=>{"use strict";var G8t=mc().overrideAll,H8t=B1(),j8t=MIe(),W8t=Id().getSubplotData,X8t=Dr(),Z8t=Wp(),GA="gl3d",zX="scene";cp.name=GA;cp.attr=zX;cp.idRoot=zX;cp.idRegex=cp.attrRegex=X8t.counterRegex("scene");cp.attributes=kIe();cp.layoutAttributes=FX();cp.baseLayoutAttrOverrides=G8t({hoverlabel:H8t.hoverlabel},"plot","nested");cp.supplyLayoutDefaults=qIe();cp.plot=function(t){for(var r=t._fullLayout,n=t._fullData,i=r._subplots[GA],a=0;a{"use strict";BIe.exports={plot:YPe(),attributes:EX(),markerSymbols:QD(),supplyDefaults:rIe(),colorbar:[{container:"marker",min:"cmin",max:"cmax"},{container:"line",min:"cmin",max:"cmax"}],calc:nIe(),moduleType:"trace",name:"scatter3d",basePlotModule:$_(),categories:["gl3d","symbols","showLegend","scatter-like"],meta:{}}});var VIe=ye((mgr,UIe)=>{"use strict";UIe.exports=NIe()});var JE=ye((ygr,jIe)=>{"use strict";var GIe=ka(),Y8t=Tu(),OX=df().axisHoverFormat,{hovertemplateAttrs:K8t,templatefallbackAttrs:J8t}=Ll(),HIe=Gl(),qX=Ao().extendFlat,$8t=mc().overrideAll;function BX(e){return{valType:"boolean",dflt:!1}}function NX(e){return{show:{valType:"boolean",dflt:!1},start:{valType:"number",dflt:null,editType:"plot"},end:{valType:"number",dflt:null,editType:"plot"},size:{valType:"number",dflt:null,min:0,editType:"plot"},project:{x:BX("x"),y:BX("y"),z:BX("z")},color:{valType:"color",dflt:GIe.defaultLine},usecolormap:{valType:"boolean",dflt:!1},width:{valType:"number",min:1,max:16,dflt:2},highlight:{valType:"boolean",dflt:!0},highlightcolor:{valType:"color",dflt:GIe.defaultLine},highlightwidth:{valType:"number",min:1,max:16,dflt:2}}}var UX=jIe.exports=$8t(qX({z:{valType:"data_array"},x:{valType:"data_array"},y:{valType:"data_array"},text:{valType:"string",dflt:"",arrayOk:!0},hovertext:{valType:"string",dflt:"",arrayOk:!0},hovertemplate:K8t(),hovertemplatefallback:J8t(),xhoverformat:OX("x"),yhoverformat:OX("y"),zhoverformat:OX("z"),connectgaps:{valType:"boolean",dflt:!1,editType:"calc"},surfacecolor:{valType:"data_array"}},Y8t("",{colorAttr:"z or surfacecolor",showScaleDflt:!0,autoColorDflt:!1,editTypeOverride:"calc"}),{contours:{x:NX("x"),y:NX("y"),z:NX("z")},hidesurface:{valType:"boolean",dflt:!1},lightposition:{x:{valType:"number",min:-1e5,max:1e5,dflt:10},y:{valType:"number",min:-1e5,max:1e5,dflt:1e4},z:{valType:"number",min:-1e5,max:1e5,dflt:0}},lighting:{ambient:{valType:"number",min:0,max:1,dflt:.8},diffuse:{valType:"number",min:0,max:1,dflt:.8},specular:{valType:"number",min:0,max:2,dflt:.05,description:"Represents the level that incident rays are reflected in a single direction, causing shine."},roughness:{valType:"number",min:0,max:1,dflt:.5,description:"Alters specular reflection; the rougher the surface, the wider and less contrasty the shine."},fresnel:{valType:"number",min:0,max:5,dflt:.2}},opacity:{valType:"number",min:0,max:1,dflt:1},opacityscale:{valType:"any",editType:"calc"},hoverinfo:qX({},HIe.hoverinfo),showlegend:qX({},HIe.showlegend,{dflt:!1})}),"calc","nested");UX.x.editType=UX.y.editType=UX.z.editType="calc+clearAxisTypes"});var GX=ye((_gr,ZIe)=>{"use strict";var Q8t=qa(),WIe=Dr(),eRt=Qh(),tRt=JE(),VX=.1;function rRt(e,t){for(var r=[],n=32,i=0;i{"use strict";var YIe=gv();KIe.exports=function(t,r){r.surfacecolor?YIe(t,r,{vals:r.surfacecolor,containerStr:"",cLetter:"c"}):YIe(t,r,{vals:r.z,containerStr:"",cLetter:"c"})}});var i8e=ye((bgr,r8e)=>{"use strict";var aRt=Od().gl_surface3d,HA=Od().ndarray,oRt=Od().ndarray_linear_interpolate.d2,sRt=o8(),lRt=s8(),$E=Dr().isArrayOrTypedArray,uRt=$y().parseColorScale,$Ie=Jy(),cRt=tc().extractOpts;function e8e(e,t,r){this.scene=e,this.uid=r,this.surface=t,this.data=null,this.showContour=[!1,!1,!1],this.contourStart=[null,null,null],this.contourEnd=[null,null,null],this.contourSize=[0,0,0],this.minValues=[1/0,1/0,1/0],this.maxValues=[-1/0,-1/0,-1/0],this.dataScaleX=1,this.dataScaleY=1,this.refineData=!0,this.objectOffset=[0,0,0]}var $g=e8e.prototype;$g.getXat=function(e,t,r,n){var i=$E(this.data.x)?$E(this.data.x[0])?this.data.x[t][e]:this.data.x[e]:e;return r===void 0?i:n.d2l(i,0,r)};$g.getYat=function(e,t,r,n){var i=$E(this.data.y)?$E(this.data.y[0])?this.data.y[t][e]:this.data.y[t]:t;return r===void 0?i:n.d2l(i,0,r)};$g.getZat=function(e,t,r,n){var i=this.data.z[t][e];return i===null&&this.data.connectgaps&&this.data._interpolatedZ&&(i=this.data._interpolatedZ[t][e]),r===void 0?i:n.d2l(i,0,r)};$g.handlePick=function(e){if(e.object===this.surface){var t=(e.data.index[0]-1)/this.dataScaleX-1,r=(e.data.index[1]-1)/this.dataScaleY-1,n=Math.max(Math.min(Math.round(t),this.data.z[0].length-1),0),i=Math.max(Math.min(Math.round(r),this.data._ylength-1),0);e.index=[n,i],e.traceCoordinate=[this.getXat(n,i),this.getYat(n,i),this.getZat(n,i)],e.dataCoordinate=[this.getXat(n,i,this.data.xcalendar,this.scene.fullSceneLayout.xaxis),this.getYat(n,i,this.data.ycalendar,this.scene.fullSceneLayout.yaxis),this.getZat(n,i,this.data.zcalendar,this.scene.fullSceneLayout.zaxis)];for(var a=0;a<3;a++){var o=e.dataCoordinate[a];o!=null&&(e.dataCoordinate[a]*=this.scene.dataScale[a])}var s=this.data.hovertext||this.data.text;return $E(s)&&s[i]&&s[i][n]!==void 0?e.textLabel=s[i][n]:s?e.textLabel=s:e.textLabel="",e.data.dataCoordinate=e.dataCoordinate.slice(),this.surface.highlight(e.data),this.scene.glplot.spikes.position=e.dataCoordinate,!0}};function fRt(e){var t=e[0].rgb,r=e[e.length-1].rgb;return t[0]===r[0]&&t[1]===r[1]&&t[2]===r[2]&&t[3]===r[3]}var 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hRt(e,t){if(e0){r=jA[n];break}return r}function vRt(e,t){if(!(e<1||t<1)){for(var r=HX(e),n=HX(t),i=1,a=0;aaF;)n--,n/=dRt(n),n++,n1?i:1};function gRt(e,t,r){var n=r[8]+r[2]*t[0]+r[5]*t[1];return e[0]=(r[6]+r[0]*t[0]+r[3]*t[1])/n,e[1]=(r[7]+r[1]*t[0]+r[4]*t[1])/n,e}function mRt(e,t,r){return yRt(e,t,gRt,r),e}function yRt(e,t,r,n){for(var i=[0,0],a=e.shape[0],o=e.shape[1],s=0;s0&&this.contourStart[n]!==null&&this.contourEnd[n]!==null&&this.contourEnd[n]>this.contourStart[n]))for(t[n]=!0,i=this.contourStart[n];ih&&(this.minValues[u]=h),this.maxValues[u]{"use strict";n8e.exports={attributes:JE(),supplyDefaults:GX().supplyDefaults,colorbar:{min:"cmin",max:"cmax"},calc:JIe(),plot:i8e(),moduleType:"trace",name:"surface",basePlotModule:$_(),categories:["gl3d","2dMap","showLegend"],meta:{}}});var s8e=ye((Tgr,o8e)=>{"use strict";o8e.exports=a8e()});var WA=ye((Agr,u8e)=>{"use strict";var bRt=Tu(),jX=df().axisHoverFormat,{hovertemplateAttrs:wRt,templatefallbackAttrs:TRt}=Ll(),Q_=JE(),l8e=Gl(),ex=Ao().extendFlat;u8e.exports=ex({x:{valType:"data_array",editType:"calc+clearAxisTypes"},y:{valType:"data_array",editType:"calc+clearAxisTypes"},z:{valType:"data_array",editType:"calc+clearAxisTypes"},i:{valType:"data_array",editType:"calc"},j:{valType:"data_array",editType:"calc"},k:{valType:"data_array",editType:"calc"},text:{valType:"string",dflt:"",arrayOk:!0,editType:"calc"},hovertext:{valType:"string",dflt:"",arrayOk:!0,editType:"calc"},hovertemplate:wRt({editType:"calc"}),hovertemplatefallback:TRt({editType:"calc"}),xhoverformat:jX("x"),yhoverformat:jX("y"),zhoverformat:jX("z"),delaunayaxis:{valType:"enumerated",values:["x","y","z"],dflt:"z",editType:"calc"},alphahull:{valType:"number",dflt:-1,editType:"calc"},intensity:{valType:"data_array",editType:"calc"},intensitymode:{valType:"enumerated",values:["vertex","cell"],dflt:"vertex",editType:"calc"},color:{valType:"color",editType:"calc"},vertexcolor:{valType:"data_array",editType:"calc"},facecolor:{valType:"data_array",editType:"calc"}},bRt("",{colorAttr:"`intensity`",showScaleDflt:!0,editTypeOverride:"calc"}),{opacity:Q_.opacity,flatshading:{valType:"boolean",dflt:!1,editType:"calc"},contour:{show:ex({},Q_.contours.x.show,{}),color:Q_.contours.x.color,width:Q_.contours.x.width,editType:"calc"},lightposition:{x:ex({},Q_.lightposition.x,{dflt:1e5}),y:ex({},Q_.lightposition.y,{dflt:1e5}),z:ex({},Q_.lightposition.z,{dflt:0}),editType:"calc"},lighting:ex({vertexnormalsepsilon:{valType:"number",min:0,max:1,dflt:1e-12,editType:"calc",description:"Epsilon for vertex normals calculation avoids math issues arising from degenerate geometry."},facenormalsepsilon:{valType:"number",min:0,max:1,dflt:1e-6,editType:"calc",description:"Epsilon for face normals calculation avoids math issues arising from degenerate geometry."},editType:"calc"},Q_.lighting),hoverinfo:ex({},l8e.hoverinfo,{editType:"calc"}),showlegend:ex({},l8e.showlegend,{dflt:!1})})});var sF=ye((Sgr,f8e)=>{"use strict";var ARt=Tu(),oF=df().axisHoverFormat,{hovertemplateAttrs:SRt,templatefallbackAttrs:MRt}=Ll(),QE=WA(),c8e=Gl(),WX=Ao().extendFlat,ERt=mc().overrideAll;function XX(e){return{show:{valType:"boolean",dflt:!1},locations:{valType:"data_array",dflt:[]},fill:{valType:"number",min:0,max:1,dflt:1}}}function ZX(e){return{show:{valType:"boolean",dflt:!0},fill:{valType:"number",min:0,max:1,dflt:1}}}var XA=f8e.exports=ERt(WX({x:{valType:"data_array"},y:{valType:"data_array"},z:{valType:"data_array"},value:{valType:"data_array"},isomin:{valType:"number"},isomax:{valType:"number"},surface:{show:{valType:"boolean",dflt:!0},count:{valType:"integer",dflt:2,min:1},fill:{valType:"number",min:0,max:1,dflt:1},pattern:{valType:"flaglist",flags:["A","B","C","D","E"],extras:["all","odd","even"],dflt:"all"}},spaceframe:{show:{valType:"boolean",dflt:!1},fill:{valType:"number",min:0,max:1,dflt:.15}},slices:{x:XX("x"),y:XX("y"),z:XX("z")},caps:{x:ZX("x"),y:ZX("y"),z:ZX("z")},text:{valType:"string",dflt:"",arrayOk:!0},hovertext:{valType:"string",dflt:"",arrayOk:!0},hovertemplate:SRt(),hovertemplatefallback:MRt(),xhoverformat:oF("x"),yhoverformat:oF("y"),zhoverformat:oF("z"),valuehoverformat:oF("value",1),showlegend:WX({},c8e.showlegend,{dflt:!1})},ARt("",{colorAttr:"`value`",showScaleDflt:!0,editTypeOverride:"calc"}),{opacity:QE.opacity,lightposition:QE.lightposition,lighting:QE.lighting,flatshading:QE.flatshading,contour:QE.contour,hoverinfo:WX({},c8e.hoverinfo)}),"calc","nested");XA.flatshading.dflt=!0;XA.lighting.facenormalsepsilon.dflt=0;XA.x.editType=XA.y.editType=XA.z.editType=XA.value.editType="calc+clearAxisTypes"});var YX=ye((Mgr,d8e)=>{"use strict";var kRt=Dr(),CRt=qa(),LRt=sF(),PRt=Qh();function IRt(e,t,r,n){function i(a,o){return kRt.coerce(e,t,LRt,a,o)}h8e(e,t,r,n,i)}function h8e(e,t,r,n,i){var a=i("isomin"),o=i("isomax");o!=null&&a!==void 0&&a!==null&&a>o&&(t.isomin=null,t.isomax=null);var s=i("x"),l=i("y"),u=i("z"),c=i("value");if(!s||!s.length||!l||!l.length||!u||!u.length||!c||!c.length){t.visible=!1;return}var f=CRt.getComponentMethod("calendars","handleTraceDefaults");f(e,t,["x","y","z"],n),i("valuehoverformat"),["x","y","z"].forEach(function(_){i(_+"hoverformat");var b="caps."+_,p=i(b+".show");p&&i(b+".fill");var k="slices."+_,E=i(k+".show");E&&(i(k+".fill"),i(k+".locations"))});var h=i("spaceframe.show");h&&i("spaceframe.fill");var d=i("surface.show");d&&(i("surface.count"),i("surface.fill"),i("surface.pattern"));var v=i("contour.show");v&&(i("contour.color"),i("contour.width")),["text","hovertext","hovertemplate","lighting.ambient","lighting.diffuse","lighting.specular","lighting.roughness","lighting.fresnel","lighting.vertexnormalsepsilon","lighting.facenormalsepsilon","lightposition.x","lightposition.y","lightposition.z","flatshading","opacity"].forEach(function(_){i(_)}),PRt(e,t,n,i,{prefix:"",cLetter:"c"}),t._length=null}d8e.exports={supplyDefaults:IRt,supplyIsoDefaults:h8e}});var lF=ye((Egr,p8e)=>{"use strict";var JX=Dr(),RRt=gv();function DRt(e,t){t._len=Math.min(t.u.length,t.v.length,t.w.length,t.x.length,t.y.length,t.z.length),t._u=jm(t.u,t._len),t._v=jm(t.v,t._len),t._w=jm(t.w,t._len),t._x=jm(t.x,t._len),t._y=jm(t.y,t._len),t._z=jm(t.z,t._len);var r=v8e(t);t._gridFill=r.fill,t._Xs=r.Xs,t._Ys=r.Ys,t._Zs=r.Zs,t._len=r.len;var n=0,i,a,o;t.starts&&(i=jm(t.starts.x||[]),a=jm(t.starts.y||[]),o=jm(t.starts.z||[]),n=Math.min(i.length,a.length,o.length)),t._startsX=i||[],t._startsY=a||[],t._startsZ=o||[];var s=0,l=1/0,u;for(u=0;u1&&(E=t[i-1],L=r[i-1],C=n[i-1]),a=0;aE?"-":"+")+"x"),v=v.replace("y",(S>L?"-":"+")+"y"),v=v.replace("z",(x>C?"-":"+")+"z");var T=function(){i=0,M=[],g=[],P=[]};(!i||i{"use strict";var FRt=gv(),zRt=lF().processGrid,uF=lF().filter;g8e.exports=function(t,r){r._len=Math.min(r.x.length,r.y.length,r.z.length,r.value.length),r._x=uF(r.x,r._len),r._y=uF(r.y,r._len),r._z=uF(r.z,r._len),r._value=uF(r.value,r._len);var n=zRt(r);r._gridFill=n.fill,r._Xs=n.Xs,r._Ys=n.Ys,r._Zs=n.Zs,r._len=n.len;for(var i=1/0,a=-1/0,o=0;o{"use strict";m8e.exports=function(t,r,n,i){i=i||t.length;for(var a=new Array(i),o=0;o{"use strict";var ORt=Od().gl_mesh3d,qRt=$y().parseColorScale,BRt=Dr().isArrayOrTypedArray,NRt=Jy(),URt=tc().extractOpts,y8e=ZA(),ek=function(e,t){for(var r=t.length-1;r>0;r--){var n=Math.min(t[r],t[r-1]),i=Math.max(t[r],t[r-1]);if(i>n&&n-1}function oe(Qt,Vt){return Qt===null?Vt:Qt}function _e(Qt,Vt,_t){T();var It=[Vt],mt=[_t];if(j>=1)It=[Vt],mt=[_t];else if(j>0){var er=H(Vt,_t);It=er.xyzv,mt=er.abc}for(var lr=0;lr-1?_t[Lr]:P(ti,Br,Vr);Ge>-1?Tr[Lr]=Ge:Tr[Lr]=O(ti,Br,Vr,oe(Qt,dt))}V(Tr[0],Tr[1],Tr[2])}}function Ee(Qt,Vt,_t){var It=function(mt,er,lr){_e(Qt,[Vt[mt],Vt[er],Vt[lr]],[_t[mt],_t[er],_t[lr]])};It(0,1,2),It(2,3,0)}function Ce(Qt,Vt,_t){var It=function(mt,er,lr){_e(Qt,[Vt[mt],Vt[er],Vt[lr]],[_t[mt],_t[er],_t[lr]])};It(0,1,2),It(3,0,1),It(2,3,0),It(1,2,3)}function me(Qt,Vt,_t,It){var mt=Qt[3];mt<_t&&(mt=_t),mt>It&&(mt=It);for(var er=(Qt[3]-mt)/(Qt[3]-Vt[3]+1e-9),lr=[],Tr=0;Tr<4;Tr++)lr[Tr]=(1-er)*Qt[Tr]+er*Vt[Tr];return lr}function ie(Qt,Vt,_t){return Qt>=Vt&&Qt<=_t}function Se(Qt){var Vt=.001*(L-S);return Qt>=S-Vt&&Qt<=L+Vt}function Le(Qt){for(var Vt=[],_t=0;_t<4;_t++){var It=Qt[_t];Vt.push([e._x[It],e._y[It],e._z[It],e._value[It]])}return Vt}var Ae=3;function Fe(Qt,Vt,_t,It,mt,er){er||(er=1),_t=[-1,-1,-1];var lr=!1,Tr=[ie(Vt[0][3],It,mt),ie(Vt[1][3],It,mt),ie(Vt[2][3],It,mt)];if(!Tr[0]&&!Tr[1]&&!Tr[2])return!1;var Lr=function(Br,Vr,dt){return Se(Vr[0][3])&&Se(Vr[1][3])&&Se(Vr[2][3])?(_e(Br,Vr,dt),!0):erTr?[k,er]:[er,E];Nt(Vt,Lr[0],Lr[1])}}var ti=[[Math.min(S,E),Math.max(S,E)],[Math.min(k,L),Math.max(k,L)]];["x","y","z"].forEach(function(Br){for(var Vr=[],dt=0;dt0&&(Ie.push(vt.id),Br==="x"?xe.push([vt.distRatio,0,0]):Br==="y"?xe.push([0,vt.distRatio,0]):xe.push([0,0,vt.distRatio]))}else Br==="x"?xt=cr(1,d-1):Br==="y"?xt=cr(1,v-1):xt=cr(1,_-1);Ie.length>0&&(Br==="x"?Vr[Ge]=Jt(Qt,Ie,Je,je,xe,Vr[Ge]):Br==="y"?Vr[Ge]=sr(Qt,Ie,Je,je,xe,Vr[Ge]):Vr[Ge]=wr(Qt,Ie,Je,je,xe,Vr[Ge]),Ge++),xt.length>0&&(Br==="x"?Vr[Ge]=pt(Qt,xt,Je,je,Vr[Ge]):Br==="y"?Vr[Ge]=Zt(Qt,xt,Je,je,Vr[Ge]):Vr[Ge]=st(Qt,xt,Je,je,Vr[Ge]),Ge++)}var ir=e.caps[Br];ir.show&&ir.fill&&(N(ir.fill),Br==="x"?Vr[Ge]=pt(Qt,[0,d-1],Je,je,Vr[Ge]):Br==="y"?Vr[Ge]=Zt(Qt,[0,v-1],Je,je,Vr[Ge]):Vr[Ge]=st(Qt,[0,_-1],Je,je,Vr[Ge]),Ge++)}}),s===0&&z(),e._meshX=x,e._meshY=C,e._meshZ=M,e._meshIntensity=g,e._Xs=c,e._Ys=f,e._Zs=h}return St(),e}function GRt(e,t){var r=e.glplot.gl,n=ORt({gl:r}),i=new _8e(e,n,t.uid);return n._trace=i,i.update(t),e.glplot.add(n),i}b8e.exports={findNearestOnAxis:ek,generateIsoMeshes:x8e,createIsosurfaceTrace:GRt}});var T8e=ye((Pgr,w8e)=>{"use strict";w8e.exports={attributes:sF(),supplyDefaults:YX().supplyDefaults,calc:$X(),colorbar:{min:"cmin",max:"cmax"},plot:cF().createIsosurfaceTrace,moduleType:"trace",name:"isosurface",basePlotModule:$_(),categories:["gl3d","showLegend"],meta:{}}});var S8e=ye((Igr,A8e)=>{"use strict";A8e.exports=T8e()});var tZ=ye((Rgr,E8e)=>{"use strict";var HRt=Tu(),yh=sF(),jRt=JE(),M8e=Gl(),eZ=Ao().extendFlat,WRt=mc().overrideAll,fF=E8e.exports=WRt(eZ({x:yh.x,y:yh.y,z:yh.z,value:yh.value,isomin:yh.isomin,isomax:yh.isomax,surface:yh.surface,spaceframe:{show:{valType:"boolean",dflt:!1},fill:{valType:"number",min:0,max:1,dflt:1}},slices:yh.slices,caps:yh.caps,text:yh.text,hovertext:yh.hovertext,xhoverformat:yh.xhoverformat,yhoverformat:yh.yhoverformat,zhoverformat:yh.zhoverformat,valuehoverformat:yh.valuehoverformat,hovertemplate:yh.hovertemplate,hovertemplatefallback:yh.hovertemplatefallback},HRt("",{colorAttr:"`value`",showScaleDflt:!0,editTypeOverride:"calc"}),{colorbar:yh.colorbar,opacity:yh.opacity,opacityscale:jRt.opacityscale,lightposition:yh.lightposition,lighting:yh.lighting,flatshading:yh.flatshading,contour:yh.contour,hoverinfo:eZ({},M8e.hoverinfo),showlegend:eZ({},M8e.showlegend,{dflt:!1})}),"calc","nested");fF.x.editType=fF.y.editType=fF.z.editType=fF.value.editType="calc+clearAxisTypes"});var C8e=ye((Dgr,k8e)=>{"use strict";var XRt=Dr(),ZRt=tZ(),YRt=YX().supplyIsoDefaults,KRt=GX().opacityscaleDefaults;k8e.exports=function(t,r,n,i){function a(o,s){return XRt.coerce(t,r,ZRt,o,s)}YRt(t,r,n,i,a),KRt(t,r,i,a)}});var R8e=ye((Fgr,I8e)=>{"use strict";var JRt=Od().gl_mesh3d,$Rt=$y().parseColorScale,QRt=Dr().isArrayOrTypedArray,eDt=Jy(),tDt=tc().extractOpts,L8e=ZA(),rZ=cF().findNearestOnAxis,rDt=cF().generateIsoMeshes;function P8e(e,t,r){this.scene=e,this.uid=r,this.mesh=t,this.name="",this.data=null,this.showContour=!1}var iZ=P8e.prototype;iZ.handlePick=function(e){if(e.object===this.mesh){var t=e.data.index,r=this.data._meshX[t],n=this.data._meshY[t],i=this.data._meshZ[t],a=this.data._Ys.length,o=this.data._Zs.length,s=rZ(r,this.data._Xs).id,l=rZ(n,this.data._Ys).id,u=rZ(i,this.data._Zs).id,c=e.index=u+o*l+o*a*s;e.traceCoordinate=[this.data._meshX[c],this.data._meshY[c],this.data._meshZ[c],this.data._value[c]];var f=this.data.hovertext||this.data.text;return QRt(f)&&f[c]!==void 0?e.textLabel=f[c]:f&&(e.textLabel=f),!0}};iZ.update=function(e){var t=this.scene,r=t.fullSceneLayout;this.data=rDt(e);function n(l,u,c,f){return u.map(function(h){return l.d2l(h,0,f)*c})}var i=L8e(n(r.xaxis,e._meshX,t.dataScale[0],e.xcalendar),n(r.yaxis,e._meshY,t.dataScale[1],e.ycalendar),n(r.zaxis,e._meshZ,t.dataScale[2],e.zcalendar)),a=L8e(e._meshI,e._meshJ,e._meshK),o={positions:i,cells:a,lightPosition:[e.lightposition.x,e.lightposition.y,e.lightposition.z],ambient:e.lighting.ambient,diffuse:e.lighting.diffuse,specular:e.lighting.specular,roughness:e.lighting.roughness,fresnel:e.lighting.fresnel,vertexNormalsEpsilon:e.lighting.vertexnormalsepsilon,faceNormalsEpsilon:e.lighting.facenormalsepsilon,opacity:e.opacity,opacityscale:e.opacityscale,contourEnable:e.contour.show,contourColor:eDt(e.contour.color).slice(0,3),contourWidth:e.contour.width,useFacetNormals:e.flatshading},s=tDt(e);o.vertexIntensity=e._meshIntensity,o.vertexIntensityBounds=[s.min,s.max],o.colormap=$Rt(e),this.mesh.update(o)};iZ.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()};function iDt(e,t){var r=e.glplot.gl,n=JRt({gl:r}),i=new P8e(e,n,t.uid);return n._trace=i,i.update(t),e.glplot.add(n),i}I8e.exports=iDt});var F8e=ye((zgr,D8e)=>{"use strict";D8e.exports={attributes:tZ(),supplyDefaults:C8e(),calc:$X(),colorbar:{min:"cmin",max:"cmax"},plot:R8e(),moduleType:"trace",name:"volume",basePlotModule:$_(),categories:["gl3d","showLegend"],meta:{}}});var O8e=ye((Ogr,z8e)=>{"use strict";z8e.exports=F8e()});var N8e=ye((qgr,B8e)=>{"use strict";var nDt=qa(),q8e=Dr(),aDt=Qh(),oDt=WA();B8e.exports=function(t,r,n,i){function a(c,f){return q8e.coerce(t,r,oDt,c,f)}function o(c){var f=c.map(function(h){var d=a(h);return d&&q8e.isArrayOrTypedArray(d)?d:null});return f.every(function(h){return h&&h.length===f[0].length})&&f}var s=o(["x","y","z"]);if(!s){r.visible=!1;return}if(o(["i","j","k"]),r.i&&(!r.j||!r.k)||r.j&&(!r.k||!r.i)||r.k&&(!r.i||!r.j)){r.visible=!1;return}var l=nDt.getComponentMethod("calendars","handleTraceDefaults");l(t,r,["x","y","z"],i),["lighting.ambient","lighting.diffuse","lighting.specular","lighting.roughness","lighting.fresnel","lighting.vertexnormalsepsilon","lighting.facenormalsepsilon","lightposition.x","lightposition.y","lightposition.z","flatshading","alphahull","delaunayaxis","opacity"].forEach(function(c){a(c)});var u=a("contour.show");u&&(a("contour.color"),a("contour.width")),"intensity"in t?(a("intensity"),a("intensitymode"),aDt(t,r,i,a,{prefix:"",cLetter:"c"})):(r.showscale=!1,"facecolor"in t?a("facecolor"):"vertexcolor"in t?a("vertexcolor"):a("color",n)),a("text"),a("hovertext"),a("hovertemplate"),a("hovertemplatefallback"),a("xhoverformat"),a("yhoverformat"),a("zhoverformat"),r._length=null}});var V8e=ye((Bgr,U8e)=>{"use strict";var sDt=gv();U8e.exports=function(t,r){r.intensity&&sDt(t,r,{vals:r.intensity,containerStr:"",cLetter:"c"})}});var X8e=ye((Ngr,W8e)=>{"use strict";var lDt=Od().gl_mesh3d,uDt=Od().delaunay_triangulate,cDt=Od().alpha_shape,fDt=Od().convex_hull,hDt=$y().parseColorScale,dDt=Dr().isArrayOrTypedArray,sZ=Jy(),vDt=tc().extractOpts,G8e=ZA();function j8e(e,t,r){this.scene=e,this.uid=r,this.mesh=t,this.name="",this.color="#fff",this.data=null,this.showContour=!1}var lZ=j8e.prototype;lZ.handlePick=function(e){if(e.object===this.mesh){var t=e.index=e.data.index;e.data._cellCenter?e.traceCoordinate=e.data.dataCoordinate:e.traceCoordinate=[this.data.x[t],this.data.y[t],this.data.z[t]];var r=this.data.hovertext||this.data.text;return dDt(r)&&r[t]!==void 0?e.textLabel=r[t]:r&&(e.textLabel=r),!0}};function H8e(e){for(var t=[],r=e.length,n=0;n=t-.5)return!1;return!0}lZ.update=function(e){var t=this.scene,r=t.fullSceneLayout;this.data=e;var n=e.x.length,i=G8e(nZ(r.xaxis,e.x,t.dataScale[0],e.xcalendar),nZ(r.yaxis,e.y,t.dataScale[1],e.ycalendar),nZ(r.zaxis,e.z,t.dataScale[2],e.zcalendar)),a;if(e.i&&e.j&&e.k){if(e.i.length!==e.j.length||e.j.length!==e.k.length||!oZ(e.i,n)||!oZ(e.j,n)||!oZ(e.k,n))return;a=G8e(aZ(e.i),aZ(e.j),aZ(e.k))}else e.alphahull===0?a=fDt(i):e.alphahull>0?a=cDt(e.alphahull,i):a=pDt(e.delaunayaxis,i);var o={positions:i,cells:a,lightPosition:[e.lightposition.x,e.lightposition.y,e.lightposition.z],ambient:e.lighting.ambient,diffuse:e.lighting.diffuse,specular:e.lighting.specular,roughness:e.lighting.roughness,fresnel:e.lighting.fresnel,vertexNormalsEpsilon:e.lighting.vertexnormalsepsilon,faceNormalsEpsilon:e.lighting.facenormalsepsilon,opacity:e.opacity,contourEnable:e.contour.show,contourColor:sZ(e.contour.color).slice(0,3),contourWidth:e.contour.width,useFacetNormals:e.flatshading};if(e.intensity){var s=vDt(e);this.color="#fff";var l=e.intensitymode;o[l+"Intensity"]=e.intensity,o[l+"IntensityBounds"]=[s.min,s.max],o.colormap=hDt(e)}else e.vertexcolor?(this.color=e.vertexcolor[0],o.vertexColors=H8e(e.vertexcolor)):e.facecolor?(this.color=e.facecolor[0],o.cellColors=H8e(e.facecolor)):(this.color=e.color,o.meshColor=sZ(e.color));this.mesh.update(o)};lZ.dispose=function(){this.scene.glplot.remove(this.mesh),this.mesh.dispose()};function gDt(e,t){var r=e.glplot.gl,n=lDt({gl:r}),i=new j8e(e,n,t.uid);return n._trace=i,i.update(t),e.glplot.add(n),i}W8e.exports=gDt});var Y8e=ye((Ugr,Z8e)=>{"use strict";Z8e.exports={attributes:WA(),supplyDefaults:N8e(),calc:V8e(),colorbar:{min:"cmin",max:"cmax"},plot:X8e(),moduleType:"trace",name:"mesh3d",basePlotModule:$_(),categories:["gl3d","showLegend"],meta:{}}});var J8e=ye((Vgr,K8e)=>{"use strict";K8e.exports=Y8e()});var cZ=ye((Ggr,Q8e)=>{"use strict";var mDt=Tu(),YA=df().axisHoverFormat,{hovertemplateAttrs:yDt,templatefallbackAttrs:_Dt}=Ll(),xDt=WA(),$8e=Gl(),uZ=Ao().extendFlat,hF={x:{valType:"data_array",editType:"calc+clearAxisTypes"},y:{valType:"data_array",editType:"calc+clearAxisTypes"},z:{valType:"data_array",editType:"calc+clearAxisTypes"},u:{valType:"data_array",editType:"calc"},v:{valType:"data_array",editType:"calc"},w:{valType:"data_array",editType:"calc"},sizemode:{valType:"enumerated",values:["scaled","absolute","raw"],editType:"calc",dflt:"scaled"},sizeref:{valType:"number",editType:"calc",min:0},anchor:{valType:"enumerated",editType:"calc",values:["tip","tail","cm","center"],dflt:"cm"},text:{valType:"string",dflt:"",arrayOk:!0,editType:"calc"},hovertext:{valType:"string",dflt:"",arrayOk:!0,editType:"calc"},hovertemplate:yDt({editType:"calc"},{keys:["norm"]}),hovertemplatefallback:_Dt({editType:"calc"}),uhoverformat:YA("u",1),vhoverformat:YA("v",1),whoverformat:YA("w",1),xhoverformat:YA("x"),yhoverformat:YA("y"),zhoverformat:YA("z"),showlegend:uZ({},$8e.showlegend,{dflt:!1})};uZ(hF,mDt("",{colorAttr:"u/v/w norm",showScaleDflt:!0,editTypeOverride:"calc"}));var bDt=["opacity","lightposition","lighting"];bDt.forEach(function(e){hF[e]=xDt[e]});hF.hoverinfo=uZ({},$8e.hoverinfo,{editType:"calc",flags:["x","y","z","u","v","w","norm","text","name"],dflt:"x+y+z+norm+text+name"});Q8e.exports=hF});var tRe=ye((Hgr,eRe)=>{"use strict";var wDt=Dr(),TDt=Qh(),ADt=cZ();eRe.exports=function(t,r,n,i){function a(d,v){return wDt.coerce(t,r,ADt,d,v)}var o=a("u"),s=a("v"),l=a("w"),u=a("x"),c=a("y"),f=a("z");if(!o||!o.length||!s||!s.length||!l||!l.length||!u||!u.length||!c||!c.length||!f||!f.length){r.visible=!1;return}var h=a("sizemode");a("sizeref",h==="raw"?1:.5),a("anchor"),a("lighting.ambient"),a("lighting.diffuse"),a("lighting.specular"),a("lighting.roughness"),a("lighting.fresnel"),a("lightposition.x"),a("lightposition.y"),a("lightposition.z"),TDt(t,r,i,a,{prefix:"",cLetter:"c"}),a("text"),a("hovertext"),a("hovertemplate"),a("hovertemplatefallback"),a("uhoverformat"),a("vhoverformat"),a("whoverformat"),a("xhoverformat"),a("yhoverformat"),a("zhoverformat"),r._length=null}});var iRe=ye((jgr,rRe)=>{"use strict";var SDt=gv();rRe.exports=function(t,r){for(var n=r.u,i=r.v,a=r.w,o=Math.min(r.x.length,r.y.length,r.z.length,n.length,i.length,a.length),s=-1/0,l=1/0,u=0;u{"use strict";var MDt=Od().gl_cone3d,EDt=Od().gl_cone3d.createConeMesh,kDt=Dr().simpleMap,CDt=$y().parseColorScale,LDt=tc().extractOpts,PDt=Dr().isArrayOrTypedArray,nRe=ZA();function aRe(e,t){this.scene=e,this.uid=t,this.mesh=null,this.data=null}var fZ=aRe.prototype;fZ.handlePick=function(e){if(e.object===this.mesh){var 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o=a("u"),s=a("v"),l=a("w"),u=a("x"),c=a("y"),f=a("z");if(!o||!o.length||!s||!s.length||!l||!l.length||!u||!u.length||!c||!c.length||!f||!f.length){r.visible=!1;return}a("starts.x"),a("starts.y"),a("starts.z"),a("maxdisplayed"),a("sizeref"),a("lighting.ambient"),a("lighting.diffuse"),a("lighting.specular"),a("lighting.roughness"),a("lighting.fresnel"),a("lightposition.x"),a("lightposition.y"),a("lightposition.z"),VDt(t,r,i,a,{prefix:"",cLetter:"c"}),a("text"),a("hovertext"),a("hovertemplate"),a("hovertemplatefallback"),a("uhoverformat"),a("vhoverformat"),a("whoverformat"),a("xhoverformat"),a("yhoverformat"),a("zhoverformat"),r._length=null}});var ARe=ye((Jgr,TRe)=>{"use strict";var _Re=Od().gl_streamtube3d,HDt=_Re.createTubeMesh,jDt=Dr(),WDt=$y().parseColorScale,XDt=tc().extractOpts,mRe=ZA(),xRe={xaxis:0,yaxis:1,zaxis:2};function bRe(e,t){this.scene=e,this.uid=t,this.mesh=null,this.data=null}var pZ=bRe.prototype;pZ.handlePick=function(e){var t=this.scene.fullSceneLayout,r=this.scene.dataScale;function n(o,s){var l=t[s],u=r[xRe[s]];return l.l2c(o)/u}if(e.object===this.mesh){var i=e.data.position,a=e.data.velocity;return e.traceCoordinate=[n(i[0],"xaxis"),n(i[1],"yaxis"),n(i[2],"zaxis"),n(a[0],"xaxis"),n(a[1],"yaxis"),n(a[2],"zaxis"),e.data.intensity*this.data._normMax,e.data.divergence],e.textLabel=this.data.hovertext||this.data.text,!0}};function yRe(e){var t=e.length,r;return t>2?r=e.slice(1,t-1):t===2?r=[(e[0]+e[1])/2]:r=e,r}function vZ(e){var t=e.length;return t===1?[.5,.5]:[e[1]-e[0],e[t-1]-e[t-2]]}function wRe(e,t){var r=e.fullSceneLayout,n=e.dataScale,i=t._len,a={};function o(z,O){var V=r[O],G=n[xRe[O]];return jDt.simpleMap(z,function(Z){return V.d2l(Z)*G})}if(a.vectors=mRe(o(t._u,"xaxis"),o(t._v,"yaxis"),o(t._w,"zaxis"),i),!i)return{positions:[],cells:[]};var s=o(t._Xs,"xaxis"),l=o(t._Ys,"yaxis"),u=o(t._Zs,"zaxis");a.meshgrid=[s,l,u],a.gridFill=t._gridFill;var c=t._slen;if(c)a.startingPositions=mRe(o(t._startsX,"xaxis"),o(t._startsY,"yaxis"),o(t._startsZ,"zaxis"));else{for(var f=l[0],h=yRe(s),d=yRe(u),v=new Array(h.length*d.length),_=0,b=0;b{"use strict";SRe.exports={moduleType:"trace",name:"streamtube",basePlotModule:$_(),categories:["gl3d","showLegend"],attributes:dZ(),supplyDefaults:gRe(),colorbar:{min:"cmin",max:"cmax"},calc:lF().calc,plot:ARe(),eventData:function(e,t){return e.tubex=e.x,e.tubey=e.y,e.tubez=e.z,e.tubeu=t.traceCoordinate[3],e.tubev=t.traceCoordinate[4],e.tubew=t.traceCoordinate[5],e.norm=t.traceCoordinate[6],e.divergence=t.traceCoordinate[7],delete e.x,delete e.y,delete e.z,e},meta:{}}});var kRe=ye((Qgr,ERe)=>{"use strict";ERe.exports=MRe()});var j2=ye((tmr,IRe)=>{"use strict";var{hovertemplateAttrs:YDt,texttemplateAttrs:KDt,templatefallbackAttrs:CRe}=Ll(),JDt=Cg(),Wm=pf(),$Dt=Gl(),LRe=Tu(),QDt=Pd().dash,H2=Ao().extendFlat,eFt=mc().overrideAll,eg=Wm.marker,PRe=Wm.line,tFt=eg.line,emr=["The library used by the *country 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DRe=ye((rmr,RRe)=>{"use strict";var vF=Dr(),gZ=Ru(),rFt=$p(),iFt=R0(),nFt=D0(),aFt=Rg(),oFt=j2(),sFt=["The library used by the *country names* `locationmode` option is changing in the next major version.","Some country names in existing plots may not work in the new version.","To ensure consistent behavior, consider setting `locationmode` to *ISO-3*."].join(" ");RRe.exports=function(t,r,n,i){function a(d,v){return vF.coerce(t,r,oFt,d,v)}var o=a("locations"),s;if(o&&o.length){var l=a("geojson"),u;(typeof l=="string"&&l!==""||vF.isPlainObject(l))&&(u="geojson-id");var c=a("locationmode",u);c==="country names"&&vF.warn(sFt),c==="geojson-id"&&a("featureidkey"),s=o.length}else{var 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Ta=ln==2?0:ln+1,fa=Vr(Be[ln].v[0],cn[ln][0],cn[Ta][0]);cn[ln][1]<0&&(fa=-fa),ln?ln==1?(fa=Ht-fa,Kn[0]-=cn[ln][0]*o(fa),Kn[1]-=cn[ln][0]*_(fa)):(fa=tr-fa,Kn[0]+=cn[ln][0]*o(fa),Kn[1]+=cn[ln][0]*_(fa)):(Kn[0]+=cn[ln][0]*o(fa),Kn[1]-=cn[ln][0]*_(fa))}return Kn[0]/=3,Kn[1]/=3,Kn}return Sr}function Je(ve){return ve[0]*=T,ve[1]*=T,ve}function je(){return tt([0,22],[45,22],[22.5,-22]).scale(380).center([22.5,2])}function tt(ve,be,De){var Be=t.geoCentroid({type:"MultiPoint",coordinates:[ve,be,De]}),et=[-Be[0],-Be[1]],We=t.geoRotation(et),it=Ge(Je(We(ve)),Je(We(be)),Je(We(De)));it.invert=st(it);var Ft=t.geoProjection(it).rotate(et),Ht=Ft.center;return delete Ft.rotate,Ft.center=function(tr){return arguments.length?Ht(We(tr)):We.invert(Ht())},Ft.clipAngle(90)}function xt(ve,be){var De=G(1-_(be));return[2/M*ve*De,M*(1-De)]}xt.invert=function(ve,be){var De=(De=be/M-1)*De;return[De>0?ve*G(E/De)/2:0,O(1-De)]};function Ie(){return t.geoProjection(xt).scale(95.6464).center([0,30])}function xe(ve){var be=b(ve);function De(Be,et){return[Be,(Be?Be/_(Be):1)*(_(et)*o(Be)-be*o(et))]}return De.invert=be?function(Be,et){Be&&(et*=_(Be)/Be);var We=o(Be);return[Be,2*a(G(We*We+be*be-et*et)-We,be-et)]}:function(Be,et){return[Be,O(Be?et*b(Be)/Be:et)]},De}function ke(){return Vt(xe).scale(249.828).clipAngle(90)}var vt=G(3);function ir(ve,be){return[vt*ve*(2*o(2*be/3)-1)/M,vt*M*_(be/3)]}ir.invert=function(ve,be){var De=3*O(be/(vt*M));return[M*ve/(vt*(2*o(2*De/3)-1)),De]};function ar(){return t.geoProjection(ir).scale(156.19)}function vr(ve){var be=o(ve);function De(Be,et){return[Be*be,_(et)/be]}return De.invert=function(Be,et){return[Be/be,O(et*be)]},De}function ii(){return Vt(vr).parallel(38.58).scale(195.044)}function pi(ve){var be=o(ve);function De(Be,et){return[Be*be,(1+be)*b(et/2)]}return De.invert=function(Be,et){return[Be/be,i(et/(1+be))*2]},De}function $r(){return Vt(pi).scale(124.75)}function di(ve,be){var De=G(8/(3*E));return[De*ve*(1-n(be)/E),De*be]}di.invert=function(ve,be){var De=G(8/(3*E)),Be=be/De;return[ve/(De*(1-n(Be)/E)),Be]};function ji(){return t.geoProjection(di).scale(165.664)}function In(ve,be){var De=G(4-3*_(n(be)));return[2/G(6*E)*ve*De,v(be)*G(2*E/3)*(2-De)]}In.invert=function(ve,be){var De=2-n(be)/G(2*E/3);return[ve*G(6*E)/(2*De),v(be)*O((4-De*De)/3)]};function wi(){return t.geoProjection(In).scale(165.664)}function On(ve,be){var De=G(E*(4+E));return[2/De*ve*(1+G(1-4*be*be/(E*E))),4/De*be]}On.invert=function(ve,be){var De=G(E*(4+E))/2;return[ve*De/(1+G(1-be*be*(4+E)/(4*E))),be*De/2]};function qn(){return t.geoProjection(On).scale(180.739)}function Fn(ve,be){var De=(2+S)*_(be);be/=2;for(var Be=0,et=1/0;Be<10&&n(et)>p;Be++){var We=o(be);be-=et=(be+_(be)*(We+2)-De)/(2*We*(1+We))}return[2/G(E*(4+E))*ve*(1+o(be)),2*G(E/(4+E))*_(be)]}Fn.invert=function(ve,be){var De=be*G((4+E)/E)/2,Be=O(De),et=o(Be);return[ve/(2/G(E*(4+E))*(1+et)),O((Be+De*(et+2))/(2+S))]};function ra(){return t.geoProjection(Fn).scale(180.739)}function la(ve,be){return[ve*(1+o(be))/G(2+E),2*be/G(2+E)]}la.invert=function(ve,be){var De=G(2+E),Be=be*De/2;return[De*ve/(1+o(Be)),Be]};function Ut(){return t.geoProjection(la).scale(173.044)}function wt(ve,be){for(var De=(1+S)*_(be),Be=0,et=1/0;Be<10&&n(et)>p;Be++)be-=et=(be+_(be)-De)/(1+o(be));return De=G(2+E),[ve*(1+o(be))/De,2*be/De]}wt.invert=function(ve,be){var De=1+S,Be=G(De/2);return[ve*2*Be/(1+o(be*=Be)),O((be+_(be))/De)]};function rr(){return t.geoProjection(wt).scale(173.044)}var nr=3+2*C;function Er(ve,be){var De=_(ve/=2),Be=o(ve),et=G(o(be)),We=o(be/=2),it=_(be)/(We+C*Be*et),Ft=G(2/(1+it*it)),Ht=G((C*We+(Be+De)*et)/(C*We+(Be-De)*et));return[nr*(Ft*(Ht-1/Ht)-2*u(Ht)),nr*(Ft*it*(Ht+1/Ht)-2*i(it))]}Er.invert=function(ve,be){if(!(We=Se.invert(ve/1.2,be*1.065)))return null;var De=We[0],Be=We[1],et=20,We;ve/=nr,be/=nr;do{var it=De/2,Ft=Be/2,Ht=_(it),tr=o(it),dr=_(Ft),Sr=o(Ft),Or=o(Be),Wr=G(Or),ni=dr/(Sr+C*tr*Wr),Pi=ni*ni,cn=G(2/(1+Pi)),ln=C*Sr+(tr+Ht)*Wr,Cn=C*Sr+(tr-Ht)*Wr,Kn=ln/Cn,Ta=G(Kn),fa=Ta-1/Ta,$a=Ta+1/Ta,Co=cn*fa-2*u(Ta)-ve,Qa=cn*ni*$a-2*i(ni)-be,mo=dr&&x*Wr*Ht*Pi/dr,Bo=(C*tr*Sr+Wr)/(2*(Sr+C*tr*Wr)*(Sr+C*tr*Wr)*Wr),Ps=-.5*ni*cn*cn*cn,Ts=Ps*mo,wo=Ps*Bo,To=(To=2*Sr+C*Wr*(tr-Ht))*To*Ta,hl=(C*tr*Sr*Wr+Or)/To,Ul=-(C*Ht*dr)/(Wr*To),Lu=fa*Ts-2*hl/Ta+cn*(hl+hl/Kn),au=fa*wo-2*Ul/Ta+cn*(Ul+Ul/Kn),Js=ni*$a*Ts-2*mo/(1+Pi)+cn*$a*mo+cn*ni*(hl-hl/Kn),Ql=ni*$a*wo-2*Bo/(1+Pi)+cn*$a*Bo+cn*ni*(Ul-Ul/Kn),dc=au*Js-Ql*Lu;if(!dc)break;var Tl=(Qa*au-Co*Ql)/dc,Al=(Co*Js-Qa*Lu)/dc;De-=Tl,Be=c(-S,f(S,Be-Al))}while((n(Tl)>p||n(Al)>p)&&--et>0);return n(n(Be)-S)Be){var Sr=G(dr),Or=a(tr,Ht),Wr=De*d(Or/De),ni=Or-Wr,Pi=ve*o(ni),cn=(ve*_(ni)-ni*_(Pi))/(S-Pi),ln=Wa(ni,cn),Cn=(E-ve)/Fa(ln,Pi,E);Ht=Sr;var Kn=50,Ta;do Ht-=Ta=(ve+Fa(ln,Pi,Ht)*Cn-Sr)/(ln(Ht)*Cn);while(n(Ta)>p&&--Kn>0);tr=ni*_(Ht),HtBe){var Ht=G(Ft),tr=a(it,We),dr=De*d(tr/De),Sr=tr-dr;We=Ht*o(Sr),it=Ht*_(Sr);for(var Or=We-S,Wr=_(We),ni=it/Wr,Pi=Wep||n(ni)>p)&&--Pi>0);return[Sr,Or]},Ht}var Wn=da(2.8284,-1.6988,.75432,-.18071,1.76003,-.38914,.042555);function Ha(){return t.geoProjection(Wn).scale(149.995)}var vo=da(2.583819,-.835827,.170354,-.038094,1.543313,-.411435,.082742);function jn(){return t.geoProjection(vo).scale(153.93)}var Mt=da(5/6*E,-.62636,-.0344,0,1.3493,-.05524,0,.045);function kr(){return t.geoProjection(Mt).scale(130.945)}function Jr(ve,be){var De=ve*ve,Be=be*be;return[ve*(1-.162388*Be)*(.87-952426e-9*De*De),be*(1+Be/12)]}Jr.invert=function(ve,be){var De=ve,Be=be,et=50,We;do{var it=Be*Be;Be-=We=(Be*(1+it/12)-be)/(1+it/4)}while(n(We)>p&&--et>0);et=50,ve/=1-.162388*it;do{var Ft=(Ft=De*De)*Ft;De-=We=(De*(.87-952426e-9*Ft)-ve)/(.87-.00476213*Ft)}while(n(We)>p&&--et>0);return[De,Be]};function vi(){return t.geoProjection(Jr).scale(131.747)}var hn=da(2.6516,-.76534,.19123,-.047094,1.36289,-.13965,.031762);function An(){return t.geoProjection(hn).scale(131.087)}function Mn(ve){var be=ve(S,0)[0]-ve(-S,0)[0];function De(Be,et){var We=Be>0?-.5:.5,it=ve(Be+We*E,et);return it[0]-=We*be,it}return ve.invert&&(De.invert=function(Be,et){var We=Be>0?-.5:.5,it=ve.invert(Be+We*be,et),Ft=it[0]-We*E;return Ft<-E?Ft+=2*E:Ft>E&&(Ft-=2*E),it[0]=Ft,it}),De}function Li(ve,be){var De=v(ve),Be=v(be),et=o(be),We=o(ve)*et,it=_(ve)*et,Ft=_(Be*be);ve=n(a(it,Ft)),be=O(We),n(ve-S)>p&&(ve%=S);var Ht=_n(ve>E/4?S-ve:ve,be);return ve>E/4&&(Ft=Ht[0],Ht[0]=-Ht[1],Ht[1]=-Ft),Ht[0]*=De,Ht[1]*=-Be,Ht}Li.invert=function(ve,be){n(ve)>1&&(ve=v(ve)*2-ve),n(be)>1&&(be=v(be)*2-be);var De=v(ve),Be=v(be),et=-De*ve,We=-Be*be,it=We/et<1,Ft=ya(it?We:et,it?et:We),Ht=Ft[0],tr=Ft[1],dr=o(tr);return it&&(Ht=-S-Ht),[De*(a(_(Ht)*dr,-_(tr))+E),Be*O(o(Ht)*dr)]};function _n(ve,be){if(be===S)return[0,0];var De=_(be),Be=De*De,et=Be*Be,We=1+et,it=1+3*et,Ft=1-et,Ht=O(1/G(We)),tr=Ft+Be*We*Ht,dr=(1-De)/tr,Sr=G(dr),Or=dr*We,Wr=G(Or),ni=Sr*Ft,Pi,cn;if(ve===0)return[0,-(ni+Be*Wr)];var ln=o(be),Cn=1/ln,Kn=2*De*ln,Ta=(-3*Be+Ht*it)*Kn,fa=(-tr*ln-(1-De)*Ta)/(tr*tr),$a=.5*fa/Sr,Co=Ft*$a-2*Be*Sr*Kn,Qa=Be*We*fa+dr*it*Kn,mo=-Cn*Kn,Bo=-Cn*Qa,Ps=-2*Cn*Co,Ts=4*ve/E,wo;if(ve>.222*E||be.175*E){if(Pi=(ni+Be*G(Or*(1+et)-ni*ni))/(1+et),ve>E/4)return[Pi,Pi];var To=Pi,hl=.5*Pi;Pi=.5*(hl+To),cn=50;do{var Ul=G(Or-Pi*Pi),Lu=Pi*(Ps+mo*Ul)+Bo*O(Pi/Wr)-Ts;if(!Lu)break;Lu<0?hl=Pi:To=Pi,Pi=.5*(hl+To)}while(n(To-hl)>p&&--cn>0)}else{Pi=p,cn=25;do{var au=Pi*Pi,Js=G(Or-au),Ql=Ps+mo*Js,dc=Pi*Ql+Bo*O(Pi/Wr)-Ts,Tl=Ql+(Bo-mo*au)/Js;Pi-=wo=Js?dc/Tl:0}while(n(wo)>p&&--cn>0)}return[Pi,-ni-Be*G(Or-Pi*Pi)]}function ya(ve,be){for(var De=0,Be=1,et=.5,We=50;;){var it=et*et,Ft=G(et),Ht=O(1/G(1+it)),tr=1-it+et*(1+it)*Ht,dr=(1-Ft)/tr,Sr=G(dr),Or=dr*(1+it),Wr=Sr*(1-it),ni=Or-ve*ve,Pi=G(ni),cn=be+Wr+et*Pi;if(n(Be-De)0?De=et:Be=et,et=.5*(De+Be)}if(!We)return null;var ln=O(Ft),Cn=o(ln),Kn=1/Cn,Ta=2*Ft*Cn,fa=(-3*et+Ht*(1+3*it))*Ta,$a=(-tr*Cn-(1-Ft)*fa)/(tr*tr),Co=.5*$a/Sr,Qa=(1-it)*Co-2*et*Sr*Ta,mo=-2*Kn*Qa,Bo=-Kn*Ta,Ps=-Kn*(et*(1+it)*$a+dr*(1+3*it)*Ta);return[E/4*(ve*(mo+Bo*Pi)+Ps*O(ve/G(Or))),ln]}function Jn(){return t.geoProjection(Mn(Li)).scale(239.75)}function Ma(ve,be,De){var Be,et,We;return ve?(Be=_o(ve,De),be?(et=_o(be,1-De),We=et[1]*et[1]+De*Be[0]*Be[0]*et[0]*et[0],[[Be[0]*et[2]/We,Be[1]*Be[2]*et[0]*et[1]/We],[Be[1]*et[1]/We,-Be[0]*Be[2]*et[0]*et[2]/We],[Be[2]*et[1]*et[2]/We,-De*Be[0]*Be[1]*et[0]/We]]):[[Be[0],0],[Be[1],0],[Be[2],0]]):(et=_o(be,1-De),[[0,et[0]/et[1]],[1/et[1],0],[et[2]/et[1],0]])}function _o(ve,be){var De,Be,et,We,it;if(be=1-p)return De=(1-be)/4,Be=N(ve),We=Z(ve),et=1/Be,it=Be*j(ve),[We+De*(it-ve)/(Be*Be),et-De*We*et*(it-ve),et+De*We*et*(it+ve),2*i(s(ve))-S+De*(it-ve)/Be];var Ft=[1,0,0,0,0,0,0,0,0],Ht=[G(be),0,0,0,0,0,0,0,0],tr=0;for(Be=G(1-be),it=1;n(Ht[tr]/Ft[tr])>p&&tr<8;)De=Ft[tr++],Ht[tr]=(De-Be)/2,Ft[tr]=(De+Be)/2,Be=G(De*Be),it*=2;et=it*Ft[tr]*ve;do We=Ht[tr]*_(Be=et)/Ft[tr],et=(O(We)+et)/2;while(--tr);return[_(et),We=o(et),We/o(et-Be),et]}function No(ve,be,De){var Be=n(ve),et=n(be),We=j(et);if(Be){var it=1/_(Be),Ft=1/(b(Be)*b(Be)),Ht=-(Ft+De*(We*We*it*it)-1+De),tr=(De-1)*Ft,dr=(-Ht+G(Ht*Ht-4*tr))/2;return[po(i(1/G(dr)),De)*v(ve),po(i(G((dr/Ft-1)/De)),1-De)*v(be)]}return[0,po(i(We),1-De)*v(be)]}function po(ve,be){if(!be)return ve;if(be===1)return u(b(ve/2+L));for(var De=1,Be=G(1-be),et=G(be),We=0;n(et)>p;We++){if(ve%E){var it=i(Be*b(ve)/De);it<0&&(it+=E),ve+=it+~~(ve/E)*E}else ve+=ve;et=(De+Be)/2,Be=G(De*Be),et=((De=et)-Be)/2}return ve/(h(2,We)*De)}function Lo(ve,be){var De=(C-1)/(C+1),Be=G(1-De*De),et=po(S,Be*Be),We=-1,it=u(b(E/4+n(be)/2)),Ft=s(We*it)/G(De),Ht=ko(Ft*o(We*ve),Ft*_(We*ve)),tr=No(Ht[0],Ht[1],Be*Be);return[-tr[1],(be>=0?1:-1)*(.5*et-tr[0])]}function ko(ve,be){var De=ve*ve,Be=be+1,et=1-De-be*be;return[.5*((ve>=0?S:-S)-a(et,2*ve)),-.25*u(et*et+4*De)+.5*u(Be*Be+De)]}function Ds(ve,be){var De=be[0]*be[0]+be[1]*be[1];return[(ve[0]*be[0]+ve[1]*be[1])/De,(ve[1]*be[0]-ve[0]*be[1])/De]}Lo.invert=function(ve,be){var De=(C-1)/(C+1),Be=G(1-De*De),et=po(S,Be*Be),We=-1,it=Ma(.5*et-be,-ve,Be*Be),Ft=Ds(it[0],it[1]),Ht=a(Ft[1],Ft[0])/We;return[Ht,2*i(s(.5/We*u(De*Ft[0]*Ft[0]+De*Ft[1]*Ft[1])))-S]};function Fs(){return t.geoProjection(Mn(Lo)).scale(151.496)}function ll(ve){var be=_(ve),De=o(ve),Be=ul(ve);Be.invert=ul(-ve);function et(We,it){var Ft=Be(We,it);We=Ft[0],it=Ft[1];var Ht=_(it),tr=o(it),dr=o(We),Sr=V(be*Ht+De*tr*dr),Or=_(Sr),Wr=n(Or)>p?Sr/Or:1;return[Wr*De*_(We),(n(We)>S?Wr:-Wr)*(be*tr-De*Ht*dr)]}return et.invert=function(We,it){var Ft=G(We*We+it*it),Ht=-_(Ft),tr=o(Ft),dr=Ft*tr,Sr=-it*Ht,Or=Ft*be,Wr=G(dr*dr+Sr*Sr-Or*Or),ni=a(dr*Or+Sr*Wr,Sr*Or-dr*Wr),Pi=(Ft>S?-1:1)*a(We*Ht,Ft*o(ni)*tr+it*_(ni)*Ht);return Be.invert(Pi,ni)},et}function ul(ve){var be=_(ve),De=o(ve);return function(Be,et){var We=o(et),it=o(Be)*We,Ft=_(Be)*We,Ht=_(et);return[a(Ft,it*De-Ht*be),O(Ht*De+it*be)]}}function zl(){var ve=0,be=t.geoProjectionMutator(ll),De=be(ve),Be=De.rotate,et=De.stream,We=t.geoCircle();return De.parallel=function(it){if(!arguments.length)return ve*P;var Ft=De.rotate();return be(ve=it*T).rotate(Ft)},De.rotate=function(it){return arguments.length?(Be.call(De,[it[0],it[1]-ve*P]),We.center([-it[0],-it[1]]),De):(it=Be.call(De),it[1]+=ve*P,it)},De.stream=function(it){return it=et(it),it.sphere=function(){it.polygonStart();var Ft=.01,Ht=We.radius(90-Ft)().coordinates[0],tr=Ht.length-1,dr=-1,Sr;for(it.lineStart();++dr=0;)it.point((Sr=Ht[dr])[0],Sr[1]);it.lineEnd(),it.polygonEnd()},it},De.scale(79.4187).parallel(45).clipAngle(180-.001)}var us=3,il=O(1-1/us)*P,As=vr(0);function cl(ve){var be=il*T,De=xt(E,be)[0]-xt(-E,be)[0],Be=As(0,be)[1],et=xt(0,be)[1],We=M-et,it=g/ve,Ft=4/g,Ht=Be+We*We*4/g;function tr(dr,Sr){var Or,Wr=n(Sr);if(Wr>be){var ni=f(ve-1,c(0,l((dr+E)/it)));dr+=E*(ve-1)/ve-ni*it,Or=xt(dr,Wr),Or[0]=Or[0]*g/De-g*(ve-1)/(2*ve)+ni*g/ve,Or[1]=Be+(Or[1]-et)*4*We/g,Sr<0&&(Or[1]=-Or[1])}else Or=As(dr,Sr);return Or[0]*=Ft,Or[1]/=Ht,Or}return tr.invert=function(dr,Sr){dr/=Ft,Sr*=Ht;var Or=n(Sr);if(Or>Be){var Wr=f(ve-1,c(0,l((dr+E)/it)));dr=(dr+E*(ve-1)/ve-Wr*it)*De/g;var ni=xt.invert(dr,.25*(Or-Be)*g/We+et);return ni[0]-=E*(ve-1)/ve-Wr*it,Sr<0&&(ni[1]=-ni[1]),ni}return As.invert(dr,Sr)},tr}function Ks(ve,be){return[ve,be&1?90-p:il]}function zs(ve,be){return[ve,be&1?-90+p:-il]}function Io(ve){return[ve[0]*(1-p),ve[1]]}function ls(ve){var be=[].concat(r.range(-180,180+ve/2,ve).map(Ks),r.range(180,-180-ve/2,-ve).map(zs));return{type:"Polygon",coordinates:[ve===180?be.map(Io):be]}}function Zl(){var ve=4,be=t.geoProjectionMutator(cl),De=be(ve),Be=De.stream;return De.lobes=function(et){return arguments.length?be(ve=+et):ve},De.stream=function(et){var We=De.rotate(),it=Be(et),Ft=(De.rotate([0,0]),Be(et));return De.rotate(We),it.sphere=function(){t.geoStream(ls(180/ve),Ft)},it},De.scale(239.75)}function Su(ve){var be=1+ve,De=_(1/be),Be=O(De),et=2*G(E/(We=E+4*Be*be)),We,it=.5*et*(be+G(ve*(2+ve))),Ft=ve*ve,Ht=be*be;function tr(dr,Sr){var Or=1-_(Sr),Wr,ni;if(Or&&Or<2){var Pi=S-Sr,cn=25,ln;do{var Cn=_(Pi),Kn=o(Pi),Ta=Be+a(Cn,be-Kn),fa=1+Ht-2*be*Kn;Pi-=ln=(Pi-Ft*Be-be*Cn+fa*Ta-.5*Or*We)/(2*be*Cn*Ta)}while(n(ln)>k&&--cn>0);Wr=et*G(fa),ni=dr*Ta/E}else Wr=et*(ve+Or),ni=dr*Be/E;return[Wr*_(ni),it-Wr*o(ni)]}return tr.invert=function(dr,Sr){var Or=dr*dr+(Sr-=it)*Sr,Wr=(1+Ht-Or/(et*et))/(2*be),ni=V(Wr),Pi=_(ni),cn=Be+a(Pi,be-Wr);return[O(dr/G(Or))*E/cn,O(1-2*(ni-Ft*Be-be*Pi+(1+Ht-2*be*Wr)*cn)/We)]},tr}function nc(){var ve=1,be=t.geoProjectionMutator(Su),De=be(ve);return De.ratio=function(Be){return arguments.length?be(ve=+Be):ve},De.scale(167.774).center([0,18.67])}var bs=.7109889596207567,Rn=.0528035274542;function _a(ve,be){return be>-bs?(ve=sr(ve,be),ve[1]+=Rn,ve):_t(ve,be)}_a.invert=function(ve,be){return be>-bs?sr.invert(ve,be-Rn):_t.invert(ve,be)};function Vu(){return t.geoProjection(_a).rotate([-20,-55]).scale(164.263).center([0,-5.4036])}function Ol(ve,be){return n(be)>bs?(ve=sr(ve,be),ve[1]-=be>0?Rn:-Rn,ve):_t(ve,be)}Ol.invert=function(ve,be){return n(be)>bs?sr.invert(ve,be+(be>0?Rn:-Rn)):_t.invert(ve,be)};function xo(){return t.geoProjection(Ol).scale(152.63)}function Yl(ve,be,De,Be){var et=G(4*E/(2*De+(1+ve-be/2)*_(2*De)+(ve+be)/2*_(4*De)+be/2*_(6*De))),We=G(Be*_(De)*G((1+ve*o(2*De)+be*o(4*De))/(1+ve+be))),it=De*Ht(1);function Ft(Sr){return G(1+ve*o(2*Sr)+be*o(4*Sr))}function Ht(Sr){var Or=Sr*De;return(2*Or+(1+ve-be/2)*_(2*Or)+(ve+be)/2*_(4*Or)+be/2*_(6*Or))/De}function tr(Sr){return Ft(Sr)*_(Sr)}var dr=function(Sr,Or){var Wr=De*Zt(Ht,it*_(Or)/De,Or/E);isNaN(Wr)&&(Wr=De*v(Or));var ni=et*Ft(Wr);return[ni*We*Sr/E*o(Wr),ni/We*_(Wr)]};return dr.invert=function(Sr,Or){var Wr=Zt(tr,Or*We/et);return[Sr*E/(o(Wr)*et*We*Ft(Wr)),O(De*Ht(Wr/De)/it)]},De===0&&(et=G(Be/E),dr=function(Sr,Or){return[Sr*et,_(Or)/et]},dr.invert=function(Sr,Or){return[Sr/et,O(Or*et)]}),dr}function Ns(){var ve=1,be=0,De=45*T,Be=2,et=t.geoProjectionMutator(Yl),We=et(ve,be,De,Be);return We.a=function(it){return arguments.length?et(ve=+it,be,De,Be):ve},We.b=function(it){return arguments.length?et(ve,be=+it,De,Be):be},We.psiMax=function(it){return 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rf=[[[[-180,0],[-100,90],[-40,0]],[[-40,0],[30,90],[180,0]]],[[[-180,0],[-160,-90],[-100,0]],[[-100,0],[-60,-90],[-20,0]],[[-20,0],[20,-90],[80,0]],[[80,0],[140,-90],[180,0]]]];function Uf(){return Do(St,rf).scale(160.857)}var pl=[[[[-180,0],[-100,90],[-40,0]],[[-40,0],[30,90],[180,0]]],[[[-180,0],[-160,-90],[-100,0]],[[-100,0],[-60,-90],[-20,0]],[[-20,0],[20,-90],[80,0]],[[80,0],[140,-90],[180,0]]]];function Zc(){return Do(Ol,pl).scale(152.63)}var Kl=[[[[-180,0],[-100,90],[-40,0]],[[-40,0],[30,90],[180,0]]],[[[-180,0],[-160,-90],[-100,0]],[[-100,0],[-60,-90],[-20,0]],[[-20,0],[20,-90],[80,0]],[[80,0],[140,-90],[180,0]]]];function Os(){return Do(sr,Kl).scale(169.529)}var yu=[[[[-180,0],[-90,90],[0,0]],[[0,0],[90,90],[180,0]]],[[[-180,0],[-90,-90],[0,0]],[[0,0],[90,-90],[180,0]]]];function oc(){return Do(sr,yu).scale(169.529).rotate([20,0])}var 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t=.5*e[0]*$A,r=.5*e[1]*$A,n=.5*e[2]*$A,i=Math.sin(t),a=Math.cos(t),o=Math.sin(r),s=Math.cos(r),l=Math.sin(n),u=Math.cos(n);return[a*s*u+i*o*l,i*s*u-a*o*l,a*o*u+i*s*l,a*s*l-i*o*u]}function Izt(e,t){var r=e[0],n=e[1],i=e[2],a=e[3],o=t[0],s=t[1],l=t[2],u=t[3];return[r*o-n*s-i*l-a*u,r*s+n*o+i*u-a*l,r*l-n*u+i*o+a*s,r*u+n*l-i*s+a*o]}function Rzt(e,t){if(!(!e||!t)){var r=Ozt(e,t),n=Math.sqrt(DDe(r,r)),i=.5*Math.acos(Math.max(-1,Math.min(1,DDe(e,t)))),a=Math.sin(i)/n;return n&&[Math.cos(i),r[2]*a,-r[1]*a,r[0]*a]}}function Dzt(e,t,r){var n=FZ(t,2,e[0]);n=FZ(n,1,e[1]),n=FZ(n,0,e[2]-r[2]);var i=t[0],a=t[1],o=t[2],s=n[0],l=n[1],u=n[2],c=Math.atan2(a,i)*W2,f=Math.sqrt(i*i+a*a),h,d;Math.abs(l)>f?(d=(l>0?90:-90)-c,h=0):(d=Math.asin(l/f)*W2-c,h=Math.sqrt(f*f-l*l));var v=180-d-2*c,_=(Math.atan2(u,s)-Math.atan2(o,h))*W2,b=(Math.atan2(u,s)-Math.atan2(o,-h))*W2,p=IDe(r[0],r[1],d,_),k=IDe(r[0],r[1],v,b);return p<=k?[d,_,r[2]]:[v,b,r[2]]}function IDe(e,t,r,n){var i=RDe(r-e),a=RDe(n-t);return Math.sqrt(i*i+a*a)}function RDe(e){return(e%360+540)%360-180}function FZ(e,t,r){var n=r*$A,i=e.slice(),a=t===0?1:0,o=t===2?1:2,s=Math.cos(n),l=Math.sin(n);return i[a]=e[a]*s-e[o]*l,i[o]=e[o]*s+e[a]*l,i}function Fzt(e){return[Math.atan2(2*(e[0]*e[1]+e[2]*e[3]),1-2*(e[1]*e[1]+e[2]*e[2]))*W2,Math.asin(Math.max(-1,Math.min(1,2*(e[0]*e[2]-e[3]*e[1]))))*W2,Math.atan2(2*(e[0]*e[3]+e[1]*e[2]),1-2*(e[2]*e[2]+e[3]*e[3]))*W2]}function zzt(e){var t=e[0]*$A,r=e[1]*$A,n=Math.cos(r);return[n*Math.cos(t),n*Math.sin(t),Math.sin(r)]}function DDe(e,t){for(var r=0,n=0,i=e.length;n{"use strict";var t1=Oa(),VZ=RZ(),Bzt=VZ.geoPath,Nzt=VZ.geoDistance,Uzt=PDe(),Vzt=qa(),ok=Dr(),Gzt=ok.strTranslate,RF=ka(),ak=So(),ODe=vf(),Hzt=Mc(),UZ=ho(),qDe=Ag().getAutoRange,NZ=yv(),jzt=Of().prepSelect,Wzt=Of().clearOutline,Xzt=Of().selectOnClick,Zzt=zDe(),fp=tk(),Yzt=ix(),NDe=mF(),Kzt=yZ().feature;function UDe(e){this.id=e.id,this.graphDiv=e.graphDiv,this.container=e.container,this.topojsonURL=e.topojsonURL,this.isStatic=e.staticPlot,this.topojsonName=null,this.topojson=null,this.projection=null,this.scope=null,this.viewInitial=null,this.fitScale=null,this.bounds=null,this.midPt=null,this.hasChoropleth=!1,this.traceHash={},this.layers={},this.basePaths={},this.dataPaths={},this.dataPoints={},this.clipDef=null,this.clipRect=null,this.bgRect=null,this.makeFramework()}var Qg=UDe.prototype;VDe.exports=function(t){return new UDe(t)};Qg.plot=function(e,t,r,n){var i=this;if(n)return i.update(e,t,!0);i._geoCalcData=e,i._fullLayout=t;var a=t[this.id],o=[],s=!1;for(var l in fp.layerNameToAdjective)if(l!=="frame"&&a["show"+l]){s=!0;break}for(var u=!1,c=0;c0&&o._module.calcGeoJSON(a,t)}if(!r){var s=this.updateProjection(e,t);if(s)return;(!this.viewInitial||this.scope!==n.scope)&&this.saveViewInitial(n)}this.scope=n.scope,this.updateBaseLayers(t,n),this.updateDims(t,n),this.updateFx(t,n),Hzt.generalUpdatePerTraceModule(this.graphDiv,this,e,n);var l=this.layers.frontplot.select(".scatterlayer");this.dataPoints.point=l.selectAll(".point"),this.dataPoints.text=l.selectAll("text"),this.dataPaths.line=l.selectAll(".js-line");var u=this.layers.backplot.select(".choroplethlayer");this.dataPaths.choropleth=u.selectAll("path"),this._render()};Qg.updateProjection=function(e,t){var r=this.graphDiv,n=t[this.id],i=t._size,a=n.domain,o=n.projection,s=n.lonaxis,l=n.lataxis,u=s._ax,c=l._ax,f=this.projection=Jzt(n),h=[[i.l+i.w*a.x[0],i.t+i.h*(1-a.y[1])],[i.l+i.w*a.x[1],i.t+i.h*(1-a.y[0])]],d=n.center||{},v=o.rotation||{},_=s.range||[],b=l.range||[];if(n.fitbounds){u._length=h[1][0]-h[0][0],c._length=h[1][1]-h[0][1],u.range=qDe(r,u),c.range=qDe(r,c);var p=(u.range[0]+u.range[1])/2,k=(c.range[0]+c.range[1])/2;if(n._isScoped)d={lon:p,lat:k};else if(n._isClipped){d={lon:p,lat:k},v={lon:p,lat:k,roll:v.roll};var E=o.type,S=fp.lonaxisSpan[E]/2||180,L=fp.lataxisSpan[E]/2||90;_=[p-S,p+S],b=[k-L,k+L]}else d={lon:p,lat:k},v={lon:p,lat:v.lat,roll:v.roll}}f.center([d.lon-v.lon,d.lat-v.lat]).rotate([-v.lon,-v.lat,v.roll]).parallels(o.parallels);var x=BDe(_,b);f.fitExtent(h,x);var C=this.bounds=f.getBounds(x),M=this.fitScale=f.scale(),g=f.translate();if(n.fitbounds){var P=f.getBounds(BDe(u.range,c.range)),T=Math.min((C[1][0]-C[0][0])/(P[1][0]-P[0][0]),(C[1][1]-C[0][1])/(P[1][1]-P[0][1]));isFinite(T)?f.scale(T*M):ok.warn("Something went wrong during"+this.id+"fitbounds computations.")}else f.scale(o.scale*M);var z=this.midPt=[(C[0][0]+C[1][0])/2,(C[0][1]+C[1][1])/2];if(f.translate([g[0]+(z[0]-g[0]),g[1]+(z[1]-g[1])]).clipExtent(C),n._isAlbersUsa){var O=f([d.lon,d.lat]),V=f.translate();f.translate([V[0]-(O[0]-V[0]),V[1]-(O[1]-V[1])])}};Qg.updateBaseLayers=function(e,t){var r=this,n=r.topojson,i=r.layers,a=r.basePaths;function o(h){return h==="lonaxis"||h==="lataxis"}function s(h){return!!fp.lineLayers[h]}function l(h){return!!fp.fillLayers[h]}var u=this.hasChoropleth?fp.layersForChoropleth:fp.layers,c=u.filter(function(h){return s(h)||l(h)?t["show"+h]:o(h)?t[h].showgrid:!0}),f=r.framework.selectAll(".layer").data(c,String);f.exit().each(function(h){delete i[h],delete a[h],t1.select(this).remove()}),f.enter().append("g").attr("class",function(h){return"layer "+h}).each(function(h){var d=i[h]=t1.select(this);h==="bg"?r.bgRect=d.append("rect").style("pointer-events","all"):o(h)?a[h]=d.append("path").style("fill","none"):h==="backplot"?d.append("g").classed("choroplethlayer",!0):h==="frontplot"?d.append("g").classed("scatterlayer",!0):s(h)?a[h]=d.append("path").style("fill","none").style("stroke-miterlimit",2):l(h)&&(a[h]=d.append("path").style("stroke","none"))}),f.order(),f.each(function(h){var d=a[h],v=fp.layerNameToAdjective[h];h==="frame"?d.datum(fp.sphereSVG):s(h)||l(h)?d.datum(Kzt(n,n.objects[h])):o(h)&&d.datum($zt(h,t,e)).call(RF.stroke,t[h].gridcolor).call(ak.dashLine,t[h].griddash,t[h].gridwidth),s(h)?d.call(RF.stroke,t[v+"color"]).call(ak.dashLine,"",t[v+"width"]):l(h)&&d.call(RF.fill,t[v+"color"])})};Qg.updateDims=function(e,t){var r=this.bounds,n=(t.framewidth||0)/2,i=r[0][0]-n,a=r[0][1]-n,o=r[1][0]-i+n,s=r[1][1]-a+n;ak.setRect(this.clipRect,i,a,o,s),this.bgRect.call(ak.setRect,i,a,o,s).call(RF.fill,t.bgcolor),this.xaxis._offset=i,this.xaxis._length=o,this.yaxis._offset=a,this.yaxis._length=s};Qg.updateFx=function(e,t){var r=this,n=r.graphDiv,i=r.bgRect,a=e.dragmode,o=e.clickmode;if(r.isStatic)return;function s(){var f=r.viewInitial,h={};for(var d in f)h[r.id+"."+d]=f[d];Vzt.call("_guiRelayout",n,h),n.emit("plotly_doubleclick",null)}function l(f){return r.projection.invert([f[0]+r.xaxis._offset,f[1]+r.yaxis._offset])}var u=function(f,h){if(h.isRect){var d=f.range={};d[r.id]=[l([h.xmin,h.ymin]),l([h.xmax,h.ymax])]}else{var v=f.lassoPoints={};v[r.id]=h.map(l)}},c={element:r.bgRect.node(),gd:n,plotinfo:{id:r.id,xaxis:r.xaxis,yaxis:r.yaxis,fillRangeItems:u},xaxes:[r.xaxis],yaxes:[r.yaxis],subplot:r.id,clickFn:function(f){f===2&&Wzt(n)}};a==="pan"?(i.node().onmousedown=null,i.call(Zzt(r,t)),i.on("dblclick.zoom",s),n._context._scrollZoom.geo||i.on("wheel.zoom",null)):(a==="select"||a==="lasso")&&(i.on(".zoom",null),c.prepFn=function(f,h,d){jzt(f,h,d,c,a)},NZ.init(c)),i.on("mousemove",function(){var f=r.projection.invert(ok.getPositionFromD3Event());if(!f)return NZ.unhover(n,t1.event);r.xaxis.p2c=function(){return f[0]},r.yaxis.p2c=function(){return f[1]},ODe.hover(n,t1.event,r.id)}),i.on("mouseout",function(){n._dragging||NZ.unhover(n,t1.event)}),i.on("click",function(){a!=="select"&&a!=="lasso"&&(o.indexOf("select")>-1&&Xzt(t1.event,n,[r.xaxis],[r.yaxis],r.id,c),o.indexOf("event")>-1&&ODe.click(n,t1.event))})};Qg.makeFramework=function(){var e=this,t=e.graphDiv,r=t._fullLayout,n="clip"+r._uid+e.id;e.clipDef=r._clips.append("clipPath").attr("id",n),e.clipRect=e.clipDef.append("rect"),e.framework=t1.select(e.container).append("g").attr("class","geo "+e.id).call(ak.setClipUrl,n,t),e.project=function(i){var a=e.projection(i);return a?[a[0]-e.xaxis._offset,a[1]-e.yaxis._offset]:[null,null]},e.xaxis={_id:"x",c2p:function(i){return e.project(i)[0]}},e.yaxis={_id:"y",c2p:function(i){return e.project(i)[1]}},e.mockAxis={type:"linear",showexponent:"all",exponentformat:"B"},UZ.setConvert(e.mockAxis,r)};Qg.saveViewInitial=function(e){var t=e.center||{},r=e.projection,n=r.rotation||{};this.viewInitial={fitbounds:e.fitbounds,"projection.scale":r.scale};var i;e._isScoped?i={"center.lon":t.lon,"center.lat":t.lat}:e._isClipped?i={"projection.rotation.lon":n.lon,"projection.rotation.lat":n.lat}:i={"center.lon":t.lon,"center.lat":t.lat,"projection.rotation.lon":n.lon},ok.extendFlat(this.viewInitial,i)};Qg.render=function(e){this._hasMarkerAngles&&e?this.plot(this._geoCalcData,this._fullLayout,[],!0):this._render()};Qg._render=function(){var e=this.projection,t=e.getPath(),r;function n(a){var o=e(a.lonlat);return o?Gzt(o[0],o[1]):null}function i(a){return e.isLonLatOverEdges(a.lonlat)?"none":null}for(r in this.basePaths)this.basePaths[r].attr("d",t);for(r in this.dataPaths)this.dataPaths[r].attr("d",function(a){return t(a.geojson)});for(r in this.dataPoints)this.dataPoints[r].attr("display",i).attr("transform",n)};function Jzt(e){var t=e.projection,r=t.type,n=fp.projNames[r];n="geo"+ok.titleCase(n);for(var 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s=(i-n)/4;return{type:"Polygon",coordinates:[[[n,a],[n,o],[n+s,o],[n+2*s,o],[n+3*s,o],[i,o],[i,a],[i-s,a],[i-2*s,a],[i-3*s,a],[n,a]]]}}});var GZ=ye((wmr,WDe)=>{"use strict";var e5=Lh(),Qzt=Cc().attributes,e7t=Pd().dash,QA=tk(),t7t=mc().overrideAll,HDe=Z1(),jDe={range:{valType:"info_array",items:[{valType:"number"},{valType:"number"}]},showgrid:{valType:"boolean",dflt:!1},tick0:{valType:"number",dflt:0},dtick:{valType:"number"},gridcolor:{valType:"color",dflt:e5.lightLine},gridwidth:{valType:"number",min:0,dflt:1},griddash:e7t},r7t=WDe.exports=t7t({domain:Qzt({name:"geo"},{}),fitbounds:{valType:"enumerated",values:[!1,"locations","geojson"],dflt:!1,editType:"plot"},resolution:{valType:"enumerated",values:[110,50],dflt:110,coerceNumber:!0},scope:{valType:"enumerated",values:HDe(QA.scopeDefaults),dflt:"world"},projection:{type:{valType:"enumerated",values:HDe(QA.projNames)},rotation:{lon:{valType:"number"},lat:{valType:"number"},roll:{valType:"number"}},tilt:{valType:"number",dflt:0},distance:{valType:"number",min:1.001,dflt:2},parallels:{valType:"info_array",items:[{valType:"number"},{valType:"number"}]},scale:{valType:"number",min:0,dflt:1}},center:{lon:{valType:"number"},lat:{valType:"number"}},visible:{valType:"boolean",dflt:!0},showcoastlines:{valType:"boolean"},coastlinecolor:{valType:"color",dflt:e5.defaultLine},coastlinewidth:{valType:"number",min:0,dflt:1},showland:{valType:"boolean",dflt:!1},landcolor:{valType:"color",dflt:QA.landColor},showocean:{valType:"boolean",dflt:!1},oceancolor:{valType:"color",dflt:QA.waterColor},showlakes:{valType:"boolean",dflt:!1},lakecolor:{valType:"color",dflt:QA.waterColor},showrivers:{valType:"boolean",dflt:!1},rivercolor:{valType:"color",dflt:QA.waterColor},riverwidth:{valType:"number",min:0,dflt:1},showcountries:{valType:"boolean"},countrycolor:{valType:"color",dflt:e5.defaultLine},countrywidth:{valType:"number",min:0,dflt:1},showsubunits:{valType:"boolean"},subunitcolor:{valType:"color",dflt:e5.defaultLine},subunitwidth:{valType:"number",min:0,dflt:1},showframe:{valType:"boolean"},framecolor:{valType:"color",dflt:e5.defaultLine},framewidth:{valType:"number",min:0,dflt:1},bgcolor:{valType:"color",dflt:e5.background},lonaxis:jDe,lataxis:jDe},"plot","from-root");r7t.uirevision={valType:"any",editType:"none"}});var YDe=ye((Tmr,ZDe)=>{"use strict";var DF=Dr(),i7t=k_(),n7t=Id().getSubplotData,FF=tk(),a7t=GZ(),XDe=FF.axesNames;ZDe.exports=function(t,r,n){i7t(t,r,n,{type:"geo",attributes:a7t,handleDefaults:o7t,fullData:n,partition:"y"})};function o7t(e,t,r,n){var i=n7t(n.fullData,"geo",n.id),a=i.map(function(oe){return oe.index}),o=r("resolution"),s=r("scope"),l=FF.scopeDefaults[s],u=r("projection.type",l.projType),c=t._isAlbersUsa=u==="albers usa";c&&(s=t.scope="usa");var f=t._isScoped=s!=="world",h=t._isSatellite=u==="satellite",d=t._isConic=u.indexOf("conic")!==-1||u==="albers",v=t._isClipped=!!FF.lonaxisSpan[u];if(e.visible===!1){var _=DF.extendDeep({},t._template);_.showcoastlines=!1,_.showcountries=!1,_.showframe=!1,_.showlakes=!1,_.showland=!1,_.showocean=!1,_.showrivers=!1,_.showsubunits=!1,_.lonaxis&&(_.lonaxis.showgrid=!1),_.lataxis&&(_.lataxis.showgrid=!1),t._template=_}for(var b=r("visible"),p,k=0;k0&&O<0&&(O+=360);var V=(z+O)/2,G;if(!c){var 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+uniform vec4 viewport; + +varying vec4 fragColor; +varying vec2 tangent; + +vec2 project(vec2 position, vec2 positionFract, vec2 scale, vec2 scaleFract, vec2 translate, vec2 translateFract) { + // the order is important + return position * scale + translate + + positionFract * scale + translateFract + + position * scaleFract + + positionFract * scaleFract; +} + +void main() { + float lineStart = 1. - lineEnd; + float lineOffset = lineTop * 2. - 1.; + + vec2 diff = (bCoord + bCoordFract - aCoord - aCoordFract); + tangent = normalize(diff * scale * viewport.zw); + vec2 normal = vec2(-tangent.y, tangent.x); + + vec2 position = project(aCoord, aCoordFract, scale, scaleFract, translate, translateFract) * lineStart + + project(bCoord, bCoordFract, scale, scaleFract, translate, translateFract) * lineEnd + + + thickness * normal * .5 * lineOffset / viewport.zw; + + gl_Position = vec4(position * 2.0 - 1.0, depth, 1); + + fragColor = color / 255.; +} +`,ANt=` +precision highp float; + +uniform float dashLength, pixelRatio, thickness, opacity, id; +uniform sampler2D dashTexture; + +varying vec4 fragColor; +varying vec2 tangent; + +void main() { + float alpha = 1.; + + float t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25; + float dash = texture2D(dashTexture, vec2(t, .5)).r; + + gl_FragColor = fragColor; + gl_FragColor.a *= alpha * opacity * dash; +} +`,SNt=` +precision highp float; + +attribute vec2 position, positionFract; + +uniform vec4 color; +uniform vec2 scale, scaleFract, translate, translateFract; +uniform float pixelRatio, id; +uniform vec4 viewport; +uniform float opacity; + +varying vec4 fragColor; + +const float MAX_LINES = 256.; + +void main() { + float depth = (MAX_LINES - 4. - id) / (MAX_LINES); + + vec2 position = position * scale + translate + + positionFract * scale + translateFract + + position * scaleFract + + positionFract * scaleFract; + + gl_Position = vec4(position * 2.0 - 1.0, depth, 1); + + fragColor = color / 255.; + fragColor.a *= opacity; +} +`,MNt=` +precision highp float; +varying vec4 fragColor; + +void main() { + gl_FragColor = fragColor; +} +`,ENt=` +precision highp float; + +attribute vec2 aCoord, bCoord, nextCoord, prevCoord; +attribute vec4 aColor, bColor; +attribute float lineEnd, lineTop; + +uniform vec2 scale, translate; +uniform float thickness, pixelRatio, id, depth; +uniform vec4 viewport; +uniform float miterLimit, miterMode; + +varying vec4 fragColor; +varying vec4 startCutoff, endCutoff; +varying vec2 tangent; +varying vec2 startCoord, endCoord; +varying float enableStartMiter, enableEndMiter; + +const float REVERSE_THRESHOLD = -.875; +const float MIN_DIFF = 1e-6; + +// TODO: possible optimizations: avoid overcalculating all for vertices and calc just one instead +// TODO: precalculate dot products, normalize things beforehead etc. +// TODO: refactor to rectangular algorithm + +float distToLine(vec2 p, vec2 a, vec2 b) { + vec2 diff = b - a; + vec2 perp = normalize(vec2(-diff.y, diff.x)); + return dot(p - a, perp); +} + +bool isNaN( float val ){ + return ( val < 0.0 || 0.0 < val || val == 0.0 ) ? false : true; +} + +void main() { + vec2 aCoord = aCoord, bCoord = bCoord, prevCoord = prevCoord, nextCoord = nextCoord; + + vec2 adjustedScale; + adjustedScale.x = (abs(scale.x) < MIN_DIFF) ? MIN_DIFF : scale.x; + adjustedScale.y = (abs(scale.y) < MIN_DIFF) ? MIN_DIFF : scale.y; + + vec2 scaleRatio = adjustedScale * viewport.zw; + vec2 normalWidth = thickness / scaleRatio; + + float lineStart = 1. - lineEnd; + float lineBot = 1. - lineTop; + + fragColor = (lineStart * aColor + lineEnd * bColor) / 255.; + + if (isNaN(aCoord.x) || isNaN(aCoord.y) || isNaN(bCoord.x) || isNaN(bCoord.y)) return; + + if (aCoord == prevCoord) prevCoord = aCoord + normalize(bCoord - aCoord); + if (bCoord == nextCoord) nextCoord = bCoord - normalize(bCoord - aCoord); + + + vec2 prevDiff = aCoord - prevCoord; + vec2 currDiff = bCoord - aCoord; + vec2 nextDiff = nextCoord - bCoord; + + vec2 prevTangent = normalize(prevDiff * scaleRatio); + vec2 currTangent = normalize(currDiff * scaleRatio); + vec2 nextTangent = normalize(nextDiff * scaleRatio); + + vec2 prevNormal = vec2(-prevTangent.y, prevTangent.x); + vec2 currNormal = vec2(-currTangent.y, currTangent.x); + vec2 nextNormal = vec2(-nextTangent.y, nextTangent.x); + + vec2 startJoinDirection = normalize(prevTangent - currTangent); + vec2 endJoinDirection = normalize(currTangent - nextTangent); + + // collapsed/unidirectional segment cases + // FIXME: there should be more elegant solution + vec2 prevTanDiff = abs(prevTangent - currTangent); + vec2 nextTanDiff = abs(nextTangent - currTangent); + if (max(prevTanDiff.x, prevTanDiff.y) < MIN_DIFF) { + startJoinDirection = currNormal; + } + if (max(nextTanDiff.x, nextTanDiff.y) < MIN_DIFF) { + endJoinDirection = currNormal; + } + if (aCoord == bCoord) { + endJoinDirection = startJoinDirection; + currNormal = prevNormal; + currTangent = prevTangent; + } + + tangent = currTangent; + + //calculate join shifts relative to normals + float startJoinShift = dot(currNormal, startJoinDirection); + float endJoinShift = dot(currNormal, endJoinDirection); + + float startMiterRatio = abs(1. / startJoinShift); + float endMiterRatio = abs(1. / endJoinShift); + + vec2 startJoin = startJoinDirection * startMiterRatio; + vec2 endJoin = endJoinDirection * endMiterRatio; + + vec2 startTopJoin, startBotJoin, endTopJoin, endBotJoin; + startTopJoin = sign(startJoinShift) * startJoin * .5; + startBotJoin = -startTopJoin; + + endTopJoin = sign(endJoinShift) * endJoin * .5; + endBotJoin = -endTopJoin; + + vec2 aTopCoord = aCoord + normalWidth * startTopJoin; + vec2 bTopCoord = bCoord + normalWidth * endTopJoin; + vec2 aBotCoord = aCoord + normalWidth * startBotJoin; + vec2 bBotCoord = bCoord + normalWidth * endBotJoin; + + //miter anti-clipping + float baClipping = distToLine(bCoord, aCoord, aBotCoord) / dot(normalize(normalWidth * endBotJoin), normalize(normalWidth.yx * vec2(-startBotJoin.y, startBotJoin.x))); + float abClipping = distToLine(aCoord, bCoord, bTopCoord) / dot(normalize(normalWidth * startBotJoin), normalize(normalWidth.yx * vec2(-endBotJoin.y, endBotJoin.x))); + + //prevent close to reverse direction switch + bool prevReverse = dot(currTangent, prevTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, prevNormal)) * min(length(prevDiff), length(currDiff)) < length(normalWidth * currNormal); + bool nextReverse = dot(currTangent, nextTangent) <= REVERSE_THRESHOLD && abs(dot(currTangent, nextNormal)) * min(length(nextDiff), length(currDiff)) < length(normalWidth * currNormal); + + if (prevReverse) { + //make join rectangular + vec2 miterShift = normalWidth * startJoinDirection * miterLimit * .5; + float normalAdjust = 1. - min(miterLimit / startMiterRatio, 1.); + aBotCoord = aCoord + miterShift - normalAdjust * normalWidth * currNormal * .5; + aTopCoord = aCoord + miterShift + normalAdjust * normalWidth * currNormal * .5; + } + else if (!nextReverse && baClipping > 0. && baClipping < length(normalWidth * endBotJoin)) { + //handle miter clipping + bTopCoord -= normalWidth * endTopJoin; + bTopCoord += normalize(endTopJoin * normalWidth) * baClipping; + } + + if (nextReverse) { + //make join rectangular + vec2 miterShift = normalWidth * endJoinDirection * miterLimit * .5; + float normalAdjust = 1. - min(miterLimit / endMiterRatio, 1.); + bBotCoord = bCoord + miterShift - normalAdjust * normalWidth * currNormal * .5; + bTopCoord = bCoord + miterShift + normalAdjust * normalWidth * currNormal * .5; + } + else if (!prevReverse && abClipping > 0. && abClipping < length(normalWidth * startBotJoin)) { + //handle miter clipping + aBotCoord -= normalWidth * startBotJoin; + aBotCoord += normalize(startBotJoin * normalWidth) * abClipping; + } + + vec2 aTopPosition = (aTopCoord) * adjustedScale + translate; + vec2 aBotPosition = (aBotCoord) * adjustedScale + translate; + + vec2 bTopPosition = (bTopCoord) * adjustedScale + translate; + vec2 bBotPosition = (bBotCoord) * adjustedScale + translate; + + //position is normalized 0..1 coord on the screen + vec2 position = (aTopPosition * lineTop + aBotPosition * lineBot) * lineStart + (bTopPosition * lineTop + bBotPosition * lineBot) * lineEnd; + + startCoord = aCoord * scaleRatio + translate * viewport.zw + viewport.xy; + endCoord = bCoord * scaleRatio + translate * viewport.zw + viewport.xy; + + gl_Position = vec4(position * 2.0 - 1.0, depth, 1); + + enableStartMiter = step(dot(currTangent, prevTangent), .5); + enableEndMiter = step(dot(currTangent, nextTangent), .5); + + //bevel miter cutoffs + if (miterMode == 1.) { + if (enableStartMiter == 1.) { + vec2 startMiterWidth = vec2(startJoinDirection) * thickness * miterLimit * .5; + startCutoff = vec4(aCoord, aCoord); + startCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio; + startCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw; + startCutoff += viewport.xyxy; + startCutoff += startMiterWidth.xyxy; + } + + if (enableEndMiter == 1.) { + vec2 endMiterWidth = vec2(endJoinDirection) * thickness * miterLimit * .5; + endCutoff = vec4(bCoord, bCoord); + endCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x) / scaleRatio; + endCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw; + endCutoff += viewport.xyxy; + endCutoff += endMiterWidth.xyxy; + } + } + + //round miter cutoffs + else if (miterMode == 2.) { + if (enableStartMiter == 1.) { + vec2 startMiterWidth = vec2(startJoinDirection) * thickness * abs(dot(startJoinDirection, currNormal)) * .5; + startCutoff = vec4(aCoord, aCoord); + startCutoff.zw += vec2(-startJoinDirection.y, startJoinDirection.x) / scaleRatio; + startCutoff = startCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw; + startCutoff += viewport.xyxy; + startCutoff += startMiterWidth.xyxy; + } + + if (enableEndMiter == 1.) { + vec2 endMiterWidth = vec2(endJoinDirection) * thickness * abs(dot(endJoinDirection, currNormal)) * .5; + endCutoff = vec4(bCoord, bCoord); + endCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x) / scaleRatio; + endCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw; + endCutoff += viewport.xyxy; + endCutoff += endMiterWidth.xyxy; + } + } +} +`,kNt=` +precision highp float; + +uniform float dashLength, pixelRatio, thickness, opacity, id, miterMode; +uniform sampler2D dashTexture; + +varying vec4 fragColor; +varying vec2 tangent; +varying vec4 startCutoff, endCutoff; +varying vec2 startCoord, endCoord; +varying float enableStartMiter, enableEndMiter; + +float distToLine(vec2 p, vec2 a, vec2 b) { + vec2 diff = b - a; + vec2 perp = normalize(vec2(-diff.y, diff.x)); + return dot(p - a, perp); +} + +void main() { + float alpha = 1., distToStart, distToEnd; + float cutoff = thickness * .5; + + //bevel miter + if (miterMode == 1.) { + if (enableStartMiter == 1.) { + distToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw); + if (distToStart < -1.) { + discard; + return; + } + alpha *= min(max(distToStart + 1., 0.), 1.); + } + + if (enableEndMiter == 1.) { + distToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw); + if (distToEnd < -1.) { + discard; + return; + } + alpha *= min(max(distToEnd + 1., 0.), 1.); + } + } + + // round miter + else if (miterMode == 2.) { + if (enableStartMiter == 1.) { + distToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw); + if (distToStart < 0.) { + float radius = length(gl_FragCoord.xy - startCoord); + + if(radius > cutoff + .5) { + discard; + return; + } + + alpha -= smoothstep(cutoff - .5, cutoff + .5, radius); + } + } + + if (enableEndMiter == 1.) { + distToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw); + if (distToEnd < 0.) { + float radius = length(gl_FragCoord.xy - endCoord); + + if(radius > cutoff + .5) { + discard; + return; + } + + alpha -= smoothstep(cutoff - .5, cutoff + .5, radius); + } + } + } + + float t = fract(dot(tangent, gl_FragCoord.xy) / dashLength) * .5 + .25; + float dash = texture2D(dashTexture, vec2(t, .5)).r; + + gl_FragColor = fragColor; + gl_FragColor.a *= alpha * opacity * dash; +} +`;dqe.exports=Wc;function Wc(e,t){if(!(this instanceof Wc))return new Wc(e,t);if(typeof e=="function"?(t||(t={}),t.regl=e):t=e,t.length&&(t.positions=t),e=t.regl,!e.hasExtension("ANGLE_instanced_arrays"))throw Error("regl-error2d: `ANGLE_instanced_arrays` extension should be enabled");this.gl=e._gl,this.regl=e,this.passes=[],this.shaders=Wc.shaders.has(e)?Wc.shaders.get(e):Wc.shaders.set(e,Wc.createShaders(e)).get(e),this.update(t)}Wc.dashMult=2;Wc.maxPatternLength=256;Wc.precisionThreshold=3e6;Wc.maxPoints=1e4;Wc.maxLines=2048;Wc.shaders=new bNt;Wc.createShaders=function(e){let t=e.buffer({usage:"static",type:"float",data:[0,1,0,0,1,1,1,0]}),r={primitive:"triangle 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alpha",dstAlpha:"one"}},depth:{enable:(o,s)=>!s.overlay},stencil:{enable:!1},scissor:{enable:!0,box:e.prop("viewport")},viewport:e.prop("viewport")},n=e(VY({vert:TNt,frag:ANt,attributes:{lineEnd:{buffer:t,divisor:0,stride:8,offset:0},lineTop:{buffer:t,divisor:0,stride:8,offset:4},aCoord:{buffer:e.prop("positionBuffer"),stride:8,offset:8,divisor:1},bCoord:{buffer:e.prop("positionBuffer"),stride:8,offset:16,divisor:1},aCoordFract:{buffer:e.prop("positionFractBuffer"),stride:8,offset:8,divisor:1},bCoordFract:{buffer:e.prop("positionFractBuffer"),stride:8,offset:16,divisor:1},color:{buffer:e.prop("colorBuffer"),stride:4,offset:0,divisor:1}}},r)),i;try{i=e(VY({cull:{enable:!0,face:"back"},vert:ENt,frag:kNt,attributes:{lineEnd:{buffer:t,divisor:0,stride:8,offset:0},lineTop:{buffer:t,divisor:0,stride:8,offset:4},aColor:{buffer:e.prop("colorBuffer"),stride:4,offset:0,divisor:1},bColor:{buffer:e.prop("colorBuffer"),stride:4,offset:4,divisor:1},prevCoord:{buffer:e.prop("positionBuffer"),stride:8,offset:0,divisor:1},aCoord:{buffer:e.prop("positionBuffer"),stride:8,offset:8,divisor:1},bCoord:{buffer:e.prop("positionBuffer"),stride:8,offset:16,divisor:1},nextCoord:{buffer:e.prop("positionBuffer"),stride:8,offset:24,divisor:1}}},r))}catch(o){i=n}return{fill:e({primitive:"triangle",elements:(o,s)=>s.triangles,offset:0,vert:SNt,frag:MNt,uniforms:{scale:e.prop("scale"),color:e.prop("fill"),scaleFract:e.prop("scaleFract"),translateFract:e.prop("translateFract"),translate:e.prop("translate"),opacity:e.prop("opacity"),pixelRatio:e.context("pixelRatio"),id:e.prop("id"),viewport:(o,s)=>[s.viewport.x,s.viewport.y,o.viewportWidth,o.viewportHeight]},attributes:{position:{buffer:e.prop("positionBuffer"),stride:8,offset:8},positionFract:{buffer:e.prop("positionFractBuffer"),stride:8,offset:8}},blend:r.blend,depth:{enable:!1},scissor:r.scissor,stencil:r.stencil,viewport:r.viewport}),rect:n,miter:i}};Wc.defaults={dashes:null,join:"miter",miterLimit:1,thickness:10,cap:"square",color:"black",opacity:1,overlay:!1,viewport:null,range:null,close:!1,fill:null};Wc.prototype.render=function(...e){e.length&&this.update(...e),this.draw()};Wc.prototype.draw=function(...e){return(e.length?e:this.passes).forEach((t,r)=>{if(t&&Array.isArray(t))return this.draw(...t);typeof t=="number"&&(t=this.passes[t]),t&&t.count>1&&t.opacity&&(this.regl._refresh(),t.fill&&t.triangles&&t.triangles.length>2&&this.shaders.fill(t),t.thickness&&(t.scale[0]*t.viewport.width>Wc.precisionThreshold||t.scale[1]*t.viewport.height>Wc.precisionThreshold?this.shaders.rect(t):t.join==="rect"||!t.join&&(t.thickness<=2||t.count>=Wc.maxPoints)?this.shaders.rect(t):this.shaders.miter(t)))}),this};Wc.prototype.update=function(e){if(!e)return;e.length!=null?typeof e[0]=="number"&&(e=[{positions:e}]):Array.isArray(e)||(e=[e]);let{regl:t,gl:r}=this;if(e.forEach((i,a)=>{let o=this.passes[a];if(i!==void 0){if(i===null){this.passes[a]=null;return}if(typeof i[0]=="number"&&(i={positions:i}),i=mNt(i,{positions:"positions points data coords",thickness:"thickness lineWidth lineWidths line-width linewidth width stroke-width strokewidth strokeWidth",join:"lineJoin linejoin join type mode",miterLimit:"miterlimit miterLimit",dashes:"dash dashes dasharray dash-array dashArray",color:"color colour stroke colors colours stroke-color strokeColor",fill:"fill fill-color fillColor",opacity:"alpha opacity",overlay:"overlay crease overlap intersect",close:"closed close closed-path closePath",range:"range dataBox",viewport:"viewport viewBox",hole:"holes hole hollow",splitNull:"splitNull"}),o||(this.passes[a]=o={id:a,scale:null,scaleFract:null,translate:null,translateFract:null,count:0,hole:[],depth:0,dashLength:1,dashTexture:t.texture({channels:1,data:new Uint8Array([255]),width:1,height:1,mag:"linear",min:"linear"}),colorBuffer:t.buffer({usage:"dynamic",type:"uint8",data:new Uint8Array}),positionBuffer:t.buffer({usage:"dynamic",type:"float",data:new Uint8Array}),positionFractBuffer:t.buffer({usage:"dynamic",type:"float",data:new Uint8Array})},i=VY({},Wc.defaults,i)),i.thickness!=null&&(o.thickness=parseFloat(i.thickness)),i.opacity!=null&&(o.opacity=parseFloat(i.opacity)),i.miterLimit!=null&&(o.miterLimit=parseFloat(i.miterLimit)),i.overlay!=null&&(o.overlay=!!i.overlay,aL-x),k=[],E=0,S=o.hole!=null?o.hole[0]:null;if(S!=null){let L=wNt(p,x=>x>=S);p=p.slice(0,L),p.push(S)}for(let L=0;Lg-S+(p[L]-E)),M=fqe(x,C);M=M.map(g=>g+E+(g+E{e.colorBuffer.destroy(),e.positionBuffer.destroy(),e.dashTexture.destroy()}),this.passes.length=0,this}});var yqe=ye((V1r,mqe)=>{"use strict";var CNt=X2(),LNt=J_(),PNt=cY(),INt=Zm(),vqe=Oh(),pqe=Z2(),{float32:RNt,fract32:HY}=ez();mqe.exports=DNt;var gqe=[[1,0,0,1,0,0],[1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,-1,0,0],[-1,0,0,1,0,0],[1,0,0,1,0,0],[1,0,-1,0,0,1],[1,0,-1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,-1],[1,0,1,0,0,1],[1,0,-1,0,0,1],[-1,0,-1,0,0,1],[-1,0,-1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,-1],[-1,0,1,0,0,1],[-1,0,-1,0,0,1],[0,1,1,0,0,0],[0,1,-1,0,0,0],[0,-1,-1,0,0,0],[0,-1,-1,0,0,0],[0,1,1,0,0,0],[0,-1,1,0,0,0],[0,1,0,-1,1,0],[0,1,0,-1,-1,0],[0,1,0,1,-1,0],[0,1,0,1,1,0],[0,1,0,-1,1,0],[0,1,0,1,-1,0],[0,-1,0,-1,1,0],[0,-1,0,-1,-1,0],[0,-1,0,1,-1,0],[0,-1,0,1,1,0],[0,-1,0,-1,1,0],[0,-1,0,1,-1,0]];function DNt(e,t){if(typeof e=="function"?(t||(t={}),t.regl=e):t=e,t.length&&(t.positions=t),e=t.regl,!e.hasExtension("ANGLE_instanced_arrays"))throw Error("regl-error2d: `ANGLE_instanced_arrays` extension should be enabled");let r=e._gl,n,i,a,o,s,l,u={color:"black",capSize:5,lineWidth:1,opacity:1,viewport:null,range:null,offset:0,count:0,bounds:null,positions:[],errors:[]},c=[];return o=e.buffer({usage:"dynamic",type:"uint8",data:new Uint8Array(0)}),i=e.buffer({usage:"dynamic",type:"float",data:new Uint8Array(0)}),a=e.buffer({usage:"dynamic",type:"float",data:new Uint8Array(0)}),s=e.buffer({usage:"dynamic",type:"float",data:new Uint8Array(0)}),l=e.buffer({usage:"static",type:"float",data:gqe}),v(t),n=e({vert:` + precision highp float; + + attribute vec2 position, positionFract; + attribute vec4 error; + attribute vec4 color; + + attribute vec2 direction, lineOffset, capOffset; + + uniform vec4 viewport; + uniform float lineWidth, capSize; + uniform vec2 scale, scaleFract, translate, translateFract; + + varying vec4 fragColor; + + void main() { + fragColor = color / 255.; + + vec2 pixelOffset = lineWidth * lineOffset + (capSize + lineWidth) * capOffset; + + vec2 dxy = -step(.5, direction.xy) * error.xz + step(direction.xy, vec2(-.5)) * error.yw; + + vec2 position = position + dxy; + + vec2 pos = (position + translate) * scale + + (positionFract + translateFract) * scale + + (position + translate) * scaleFract + + 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Az,xc=function(t){DUt(t)?(t={regl:t},this.gl=t.regl._gl):this.gl=wUt(t),this.shader=SBe.get(this.gl),this.shader?this.regl=this.shader.regl:this.regl=t.regl||bUt({gl:this.gl}),this.charBuffer=this.regl.buffer({type:"uint8",usage:"stream"}),this.sizeBuffer=this.regl.buffer({type:"float",usage:"stream"}),this.shader||(this.shader=this.createShader(),SBe.set(this.gl,this.shader)),this.batch=[],this.fontSize=[],this.font=[],this.fontAtlas=[],this.draw=this.shader.draw.bind(this),this.render=function(){this.regl._refresh(),this.draw(this.batch)},this.canvas=this.gl.canvas,this.update(MUt(t)?t:{})};xc.prototype.createShader=function(){var t=this.regl,r=t({blend:{enable:!0,color:[0,0,0,1],func:{srcRGB:"src alpha",dstRGB:"one minus src alpha",srcAlpha:"one minus dst alpha",dstAlpha:"one"}},stencil:{enable:!1},depth:{enable:!1},count:t.prop("count"),offset:t.prop("offset"),attributes:{charOffset:{offset:4,stride:8,buffer:t.this("sizeBuffer")},width:{offset:0,stride:8,buffer:t.this("sizeBuffer")},char:t.this("charBuffer"),position:t.this("position")},uniforms:{atlasSize:function(i,a){return[a.atlas.width,a.atlas.height]},atlasDim:function(i,a){return[a.atlas.cols,a.atlas.rows]},atlas:function(i,a){return a.atlas.texture},charStep:function(i,a){return a.atlas.step},em:function(i,a){return a.atlas.em},color:t.prop("color"),opacity:t.prop("opacity"),viewport:t.this("viewportArray"),scale:t.this("scale"),align:t.prop("align"),baseline:t.prop("baseline"),translate:t.this("translate"),positionOffset:t.prop("positionOffset")},primitive:"points",viewport:t.this("viewport"),vert:` + precision highp float; + attribute float width, charOffset, char; + attribute vec2 position; + uniform float fontSize, charStep, em, align, baseline; + uniform vec4 viewport; + uniform vec4 color; + uniform vec2 atlasSize, atlasDim, scale, translate, positionOffset; + varying vec2 charCoord, charId; + varying float charWidth; + varying vec4 fontColor; + void main () { + vec2 offset = floor(em * (vec2(align + charOffset, baseline) + + vec2(positionOffset.x, -positionOffset.y))) + / (viewport.zw * scale.xy); + + vec2 position = (position + translate) * scale; + position += offset * scale; + + charCoord = position * viewport.zw + viewport.xy; + + gl_Position = vec4(position * 2. - 1., 0, 1); + + gl_PointSize = charStep; + + charId.x = mod(char, atlasDim.x); + charId.y = floor(char / atlasDim.x); + + charWidth = width * em; + + fontColor = color / 255.; + }`,frag:` + precision highp float; + uniform float fontSize, charStep, opacity; + uniform vec2 atlasSize; + uniform vec4 viewport; + uniform sampler2D atlas; + varying vec4 fontColor; + varying vec2 charCoord, charId; + varying float charWidth; + + float lightness(vec4 color) { + return color.r * 0.299 + color.g * 0.587 + color.b * 0.114; + } + + void main () { + vec2 uv = gl_FragCoord.xy - charCoord + charStep * .5; + float halfCharStep = floor(charStep * .5 + .5); + + // invert y and shift by 1px (FF expecially needs that) + uv.y = charStep - uv.y; + + // ignore points outside of character bounding box + float halfCharWidth = ceil(charWidth * .5); + if (floor(uv.x) > halfCharStep + halfCharWidth || + floor(uv.x) < halfCharStep - halfCharWidth) return; + + uv += charId * charStep; + uv = uv / atlasSize; + + vec4 color = fontColor; + vec4 mask = texture2D(atlas, uv); + + float maskY = lightness(mask); + // float colorY = lightness(color); + color.a *= maskY; + color.a *= opacity; + + // color.a += .1; + + // antialiasing, see yiq color space y-channel formula + // color.rgb += (1. - color.rgb) * (1. - mask.rgb); + + gl_FragColor = color; + }`}),n={};return{regl:t,draw:r,atlas:n}};xc.prototype.update=function(t){var r=this;if(typeof t=="string")t={text:t};else if(!t)return;t=xUt(t,{position:"position positions coord coords coordinates",font:"font fontFace fontface typeface cssFont css-font family fontFamily",fontSize:"fontSize fontsize size font-size",text:"text texts chars characters value values symbols",align:"align alignment textAlign textbaseline",baseline:"baseline textBaseline textbaseline",direction:"dir direction textDirection",color:"color colour fill fill-color fillColor textColor textcolor",kerning:"kerning kern",range:"range dataBox",viewport:"vp viewport viewBox viewbox viewPort",opacity:"opacity alpha transparency visible visibility opaque",offset:"offset positionOffset padding shift indent indentation"},!0),t.opacity!=null&&(Array.isArray(t.opacity)?this.opacity=t.opacity.map(function(Ce){return parseFloat(Ce)}):this.opacity=parseFloat(t.opacity)),t.viewport!=null&&(this.viewport=SUt(t.viewport),this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),this.viewport==null&&(this.viewport={x:0,y:0,width:this.gl.drawingBufferWidth,height:this.gl.drawingBufferHeight},this.viewportArray=[this.viewport.x,this.viewport.y,this.viewport.width,this.viewport.height]),t.kerning!=null&&(this.kerning=t.kerning),t.offset!=null&&(typeof t.offset=="number"&&(t.offset=[t.offset,0]),this.positionOffset=IUt(t.offset)),t.direction&&(this.direction=t.direction),t.range&&(this.range=t.range,this.scale=[1/(t.range[2]-t.range[0]),1/(t.range[3]-t.range[1])],this.translate=[-t.range[0],-t.range[1]]),t.scale&&(this.scale=t.scale),t.translate&&(this.translate=t.translate),this.scale||(this.scale=[1/this.viewport.width,1/this.viewport.height]),this.translate||(this.translate=[0,0]),!this.font.length&&!t.font&&(t.font=xc.baseFontSize+"px sans-serif");var n=!1,i=!1;if(t.font&&(Array.isArray(t.font)?t.font:[t.font]).forEach(function(Ce,me){if(typeof Ce=="string")try{Ce=p5.parse(Ce)}catch(Ze){Ce=p5.parse(xc.baseFontSize+"px "+Ce)}else{var ie=Ce.style,Se=Ce.weight,Le=Ce.stretch,Ae=Ce.variant;Ce=p5.parse(p5.stringify(Ce)),ie&&(Ce.style=ie),Se&&(Ce.weight=Se),Le&&(Ce.stretch=Le),Ae&&(Ce.variant=Ae)}var Fe=p5.stringify({size:xc.baseFontSize,family:Ce.family,stretch:Sz?Ce.stretch:void 0,variant:Ce.variant,weight:Ce.weight,style:Ce.style}),Pe=EUt(Ce.size),ge=Math.round(Pe[0]*kUt(Pe[1]));if(ge!==r.fontSize[me]&&(i=!0,r.fontSize[me]=ge),(!r.font[me]||Fe!=r.font[me].baseString)&&(n=!0,r.font[me]=xc.fonts[Fe],!r.font[me])){var Re=Ce.family.join(", "),ce=[Ce.style];Ce.style!=Ce.variant&&ce.push(Ce.variant),Ce.variant!=Ce.weight&&ce.push(Ce.weight),Sz&&Ce.weight!=Ce.stretch&&ce.push(Ce.stretch),r.font[me]={baseString:Fe,family:Re,weight:Ce.weight,stretch:Ce.stretch,style:Ce.style,variant:Ce.variant,width:{},kerning:{},metrics:PUt(Re,{origin:"top",fontSize:xc.baseFontSize,fontStyle:ce.join(" ")})},xc.fonts[Fe]=r.font[me]}}),(n||i)&&this.font.forEach(function(Ce,me){var ie=p5.stringify({size:r.fontSize[me],family:Ce.family,stretch:Sz?Ce.stretch:void 0,variant:Ce.variant,weight:Ce.weight,style:Ce.style});if(r.fontAtlas[me]=r.shader.atlas[ie],!r.fontAtlas[me]){var Se=Ce.metrics;r.shader.atlas[ie]=r.fontAtlas[me]={fontString:ie,step:Math.ceil(r.fontSize[me]*Se.bottom*.5)*2,em:r.fontSize[me],cols:0,rows:0,height:0,width:0,chars:[],ids:{},texture:r.regl.texture()}}t.text==null&&(t.text=r.text)}),typeof t.text=="string"&&t.position&&t.position.length>2){for(var a=Array(t.position.length*.5),o=0;o2){for(var u=!t.position[0].length,c=dx.mallocFloat(this.count*2),f=0,h=0;f1?r.align[me]:r.align[0]:r.align;if(typeof ie=="number")return ie;switch(ie){case"right":case"end":return-Ce;case"center":case"centre":case"middle":return-Ce*.5}return 0})),this.baseline==null&&t.baseline==null&&(t.baseline=0),t.baseline!=null&&(this.baseline=t.baseline,Array.isArray(this.baseline)||(this.baseline=[this.baseline]),this.baselineOffset=this.baseline.map(function(Ce,me){var ie=(r.font[me]||r.font[0]).metrics,Se=0;return Se+=ie.bottom*.5,typeof Ce=="number"?Se+=Ce-ie.baseline:Se+=-ie[Ce],Se*=-1,Se})),t.color!=null)if(t.color||(t.color="transparent"),typeof t.color=="string"||!isNaN(t.color))this.color=lK(t.color,"uint8");else{var G;if(typeof t.color[0]=="number"&&t.color.length>this.counts.length){var Z=t.color.length;G=dx.mallocUint8(Z);for(var 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we.mipmap){case"string":ne.mipmapHint=mi[we.mipmap],ne.genMipmaps=!0,Ct=!0;break;case"boolean":Ct=ne.genMipmaps=we.mipmap;break;case"object":ne.genMipmaps=!1,Ct=!0;break;default:}Ct&&!("min"in we)&&(ne.minFilter=Kl)}}function al(ne,we){Me.texParameteri(we,Uf,ne.minFilter),Me.texParameteri(we,rf,ne.magFilter),Me.texParameteri(we,Oo,ne.wrapS),Me.texParameteri(we,qo,ne.wrapT),bt.ext_texture_filter_anisotropic&&Me.texParameteri(we,cs,ne.anisotropic),ne.genMipmaps&&(Me.hint(Cf,ne.mipmapHint),Me.generateMipmap(we))}var Vl=0,ss={},Vs=zt.maxTextureUnits,Ys=Array(Vs).map(function(){return null});function wa(ne){hi.call(this),this.mipmask=0,this.internalformat=Ma,this.id=Vl++,this.refCount=1,this.target=ne,this.texture=Me.createTexture(),this.unit=-1,this.bindCount=0,this.texInfo=new zo,Gr.profile&&(this.stats={size:0})}function ol(ne){Me.activeTexture(Fu),Me.bindTexture(ne.target,ne.texture)}function io(){var ne=Ys[0];ne?Me.bindTexture(ne.target,ne.texture):Me.bindTexture(_n,null)}function 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ft(ne,we),ft.subimage=Xt,ft.resize=hr,ft._reglType="texture2d",ft._texture=Ue,Gr.profile&&(ft.stats=Ue.stats),ft.destroy=function(){Ue.decRef()},ft}function J(ne,we,Ue,ft,Xt,hr){var qt=new wa(ya);ss[qt.id]=qt,Nr.cubeCount++;var Ve=new Array(6);function Qe(Ot,Rt,Bt,Dt,yt,Pt){var ht,ur=qt.texInfo;for(zo.call(ur),ht=0;ht<6;++ht)Ve[ht]=Va();if(typeof Ot=="number"||!Ot){var br=Ot|0||1;for(ht=0;ht<6;++ht)oa(Ve[ht],br,br)}else if(typeof Ot=="object")if(Rt)ba(Ve[0],Ot),ba(Ve[1],Rt),ba(Ve[2],Bt),ba(Ve[3],Dt),ba(Ve[4],yt),ba(Ve[5],Pt);else if(Qs(ur,Ot),mn(qt,Ot),"faces"in Ot){var Ur=Ot.faces;for(ht=0;ht<6;++ht)li(Ve[ht],qt),ba(Ve[ht],Ur[ht])}else 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Ea(Me,bt,zt,Rr,jr,Nr,Gr,mi,Ui,qi,Ei,Hn,en,Wi,si,Mr){var Yr=qi.Record,xi={add:32774,subtract:32778,"reverse subtract":32779};zt.ext_blend_minmax&&(xi.min=He,xi.max=Ye);var Ri=zt.angle_instanced_arrays,ci=zt.webgl_draw_buffers,an=zt.oes_vertex_array_object,Zi={dirty:!0,profile:Mr.profile},Bn={},hi=[],li={},mn={};function Ji(Ve){return Ve.replace(".","_")}function Vi(Ve,Qe,at){var Ct=Ji(Ve);hi.push(Ve),Bn[Ct]=Zi[Ct]=!!at,li[Ct]=Qe}function Ni(Ve,Qe,at){var Ct=Ji(Ve);hi.push(Ve),Array.isArray(at)?(Zi[Ct]=at.slice(),Bn[Ct]=at.slice()):Zi[Ct]=Bn[Ct]=at,mn[Ct]=Qe}function 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Vn={gl:Me,context:en,strings:bt,next:Bn,current:Zi,draw:Hn,elements:Nr,buffer:jr,shader:Ei,attributes:qi.state,vao:qi,uniforms:Ui,framebuffer:mi,extensions:zt,timer:Wi,isBufferArgs:Ii},na={primTypes:Sn,compareFuncs:Zr,blendFuncs:bi,blendEquations:xi,stencilOps:ai,glTypes:ji,orientationType:gi};ci&&(na.backBuffer=[se],na.drawBuffer=M(Rr.maxDrawbuffers,function(Ve){return Ve===0?[0]:M(Ve,function(Qe){return _i+Qe})}));var Ki=0;function kn(){var Ve=$n({cache:si}),Qe=Ve.link,at=Ve.global;Ve.id=Ki++,Ve.batchId="0";var Ct=Qe(Vn),Ot=Ve.shared={props:"a0"};Object.keys(Vn).forEach(function(Pt){Ot[Pt]=at.def(Ct,".",Pt)});var Rt=Ve.next={},Bt=Ve.current={};Object.keys(mn).forEach(function(Pt){Array.isArray(Zi[Pt])&&(Rt[Pt]=at.def(Ot.next,".",Pt),Bt[Pt]=at.def(Ot.current,".",Pt))});var Dt=Ve.constants={};Object.keys(na).forEach(function(Pt){Dt[Pt]=at.def(JSON.stringify(na[Pt]))}),Ve.invoke=function(Pt,ht){switch(ht.type){case Yn:var ur=["this",Ot.context,Ot.props,Ve.batchId];return Pt.def(Qe(ht.data),".call(",ur.slice(0,Math.max(ht.data.length+1,4)),")");case Dn:return Pt.def(Ot.props,ht.data);case Ka:return Pt.def(Ot.context,ht.data);case bo:return Pt.def("this",ht.data);case Xo:return ht.data.append(Ve,Pt),ht.data.ref;case Ss:return ht.data.toString();case as:return ht.data.map(function(br){return Ve.invoke(Pt,br)})}},Ve.attribCache={};var yt={};return Ve.scopeAttrib=function(Pt){var ht=bt.id(Pt);if(ht in yt)return yt[ht];var ur=qi.scope[ht];ur||(ur=qi.scope[ht]=new Yr);var br=yt[ht]=Qe(ur);return br},Ve}function ta(Ve){var Qe=Ve.static,at=Ve.dynamic,Ct;if(le in Qe){var Ot=!!Qe[le];Ct=En(function(Bt,Dt){return Ot}),Ct.enable=Ot}else if(le in at){var Rt=at[le];Ct=Un(Rt,function(Bt,Dt){return Bt.invoke(Dt,Rt)})}return Ct}function oa(Ve,Qe){var at=Ve.static,Ct=Ve.dynamic;if(qe in at){var Ot=at[qe];return Ot?(Ot=mi.getFramebuffer(Ot),En(function(Bt,Dt){var yt=Bt.link(Ot),Pt=Bt.shared;Dt.set(Pt.framebuffer,".next",yt);var ht=Pt.context;return 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Ot=Qe.static,Rt=Object.keys(Ot);if(Rt.length>0&&typeof Ot[Rt[0]]=="number"){for(var Bt=[],Dt=0;Dt"+Gi+"?"+ht+".constant["+Gi+"]:0;"}).join(""),"}}else{","if(",Ur,"(",ht,".buffer)){",gn,"=",Di,".createStream(",Sr,",",ht,".buffer);","}else{",gn,"=",Di,".getBuffer(",ht,".buffer);","}",rn,'="type" in ',ht,"?",br.glTypes,"[",ht,".type]:",gn,".dtype;",fi.normalized,"=!!",ht,".normalized;");function Ci(Bi){Pt(fi[Bi],"=",ht,".",Bi,"|0;")}return Ci("size"),Ci("offset"),Ci("stride"),Ci("divisor"),Pt("}}"),Pt.exit("if(",fi.isStream,"){",Di,".destroyStream(",gn,");","}"),fi}Ot[Rt]=Un(Bt,Dt)}),Ot}function al(Ve){var Qe=Ve.static,at=Ve.dynamic,Ct={};return Object.keys(Qe).forEach(function(Ot){var Rt=Qe[Ot];Ct[Ot]=En(function(Bt,Dt){return typeof Rt=="number"||typeof Rt=="boolean"?""+Rt:Bt.link(Rt)})}),Object.keys(at).forEach(function(Ot){var Rt=at[Ot];Ct[Ot]=Un(Rt,function(Bt,Dt){return Bt.invoke(Dt,Rt)})}),Ct}function Vl(Ve,Qe,at,Ct,Ot){var Rt=Ve.static,Bt=Ve.dynamic,Dt=is(Ve,Qe),yt=oa(Ve,Ot),Pt=ba(Ve,yt,Ot),ht=Va(Ve,Ot),ur=Ml(Ve,Ot),br=Zs(Ve,Ot,Dt);function Ur(Ci){var Bi=Pt[Ci];Bi&&(ur[Ci]=Bi)}Ur(ee),Ur(Ji(Q));var Di=Object.keys(ur).length>0,fi={framebuffer:yt,draw:ht,shader:br,state:ur,dirty:Di,scopeVAO:null,drawVAO:null,useVAO:!1,attributes:{}};if(fi.profile=ta(Ve,Ot),fi.uniforms=zo(at,Ot),fi.drawVAO=fi.scopeVAO=ht.vao,!fi.drawVAO&&br.program&&!Dt&&zt.angle_instanced_arrays&&ht.static.elements){var Ti=!0,gn=br.program.attributes.map(function(Ci){var Bi=Qe.static[Ci];return Ti=Ti&&!!Bi,Bi});if(Ti&&gn.length>0){var rn=qi.getVAO(qi.createVAO({attributes:gn,elements:ht.static.elements}));fi.drawVAO=new ei(null,null,null,function(Ci,Bi){return Ci.link(rn)}),fi.useVAO=!0}}return Dt?fi.useVAO=!0:fi.attributes=Qs(Qe,Ot),fi.context=al(Ct,Ot),fi}function ss(Ve,Qe,at){var Ct=Ve.shared,Ot=Ct.context,Rt=Ve.scope();Object.keys(at).forEach(function(Bt){Qe.save(Ot,"."+Bt);var 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ne(Ve,Qe,at,Ct){Ve.batchId="a1",ol(Ve,Qe);function Ot(){return!0}Y(Ve,Qe,at,Ct.attributes,Ot),D(Ve,Qe,at,Ct.uniforms,Ot,!1),J(Ve,Qe,Qe,at)}function we(Ve,Qe,at,Ct){ol(Ve,Qe);var Ot=at.contextDep,Rt=Qe.def(),Bt="a0",Dt="a1",yt=Qe.def();Ve.shared.props=yt,Ve.batchId=Rt;var Pt=Ve.scope(),ht=Ve.scope();Qe(Pt.entry,"for(",Rt,"=0;",Rt,"<",Dt,";++",Rt,"){",yt,"=",Bt,"[",Rt,"];",ht,"}",Pt.exit);function ur(gn){return gn.contextDep&&Ot||gn.propDep}function 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Ct=!1,Ot=!0;Object.keys(Qe.context).forEach(function(Ur){Ct=Ct||Qe.context[Ur].propDep}),Ct||(ss(Ve,at,Qe.context),Ot=!1);var Rt=Qe.framebuffer,Bt=!1;Rt?(Rt.propDep?Ct=Bt=!0:Rt.contextDep&&Ct&&(Bt=!0),Bt||Vs(Ve,at,Rt)):Vs(Ve,at,null),Qe.state.viewport&&Qe.state.viewport.propDep&&(Ct=!0);function Dt(Ur){return Ur.contextDep&&Ct||Ur.propDep}Ys(Ve,at,Qe),wa(Ve,at,Qe.state,function(Ur){return!Dt(Ur)}),(!Qe.profile||!Dt(Qe.profile))&&io(Ve,at,Qe,!1,"a1"),Qe.contextDep=Ct,Qe.needsContext=Ot,Qe.needsFramebuffer=Bt;var yt=Qe.shader.progVar;if(yt.contextDep&&Ct||yt.propDep)we(Ve,at,Qe,null);else{var Pt=yt.append(Ve,at);if(at(Ve.shared.gl,".useProgram(",Pt,".program);"),Qe.shader.program)we(Ve,at,Qe,Qe.shader.program);else{at(Ve.shared.vao,".setVAO(null);");var ht=Ve.global.def("{}"),ur=at.def(Pt,".id"),br=at.def(ht,"[",ur,"]");at(Ve.cond(br).then(br,".call(this,a0,a1);").else(br,"=",ht,"[",ur,"]=",Ve.link(function(Ur){return 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OVt=Tu(),wK=Rd(),TK=ec(),qVt=Cc().attributes,Fz=Ao().extendFlat,BVt=vl().templatedArray;NNe.exports={domain:qVt({name:"parcoords",trace:!0,editType:"plot"}),labelangle:{valType:"angle",dflt:0,editType:"plot"},labelside:{valType:"enumerated",values:["top","bottom"],dflt:"top",editType:"plot"},labelfont:TK({editType:"plot"}),tickfont:TK({autoShadowDflt:!0,editType:"plot"}),rangefont:TK({editType:"plot"}),dimensions:BVt("dimension",{label:{valType:"string",editType:"plot"},tickvals:Fz({},wK.tickvals,{editType:"plot"}),ticktext:Fz({},wK.ticktext,{editType:"plot"}),tickformat:Fz({},wK.tickformat,{editType:"plot"}),visible:{valType:"boolean",dflt:!0,editType:"plot"},range:{valType:"info_array",items:[{valType:"number",editType:"plot"},{valType:"number",editType:"plot"}],editType:"plot"},constraintrange:{valType:"info_array",freeLength:!0,dimensions:"1-2",items:[{valType:"any",editType:"plot"},{valType:"any",editType:"plot"}],editType:"plot"},multiselect:{valType:"boolean",dflt:!0,editType:"plot"},values:{valType:"data_array",editType:"calc"},editType:"calc"}),line:Fz({editType:"calc"},OVt("line",{colorscaleDflt:"Viridis",autoColorDflt:!1,editTypeOverride:"calc"})),unselected:{line:{color:{valType:"color",dflt:"#7f7f7f",editType:"plot"},opacity:{valType:"number",min:0,max:1,dflt:"auto",editType:"plot"},editType:"plot"},editType:"plot"}}});var Pk=ye((D_r,UNe)=>{"use strict";UNe.exports={maxDimensionCount:60,overdrag:45,verticalPadding:2,tickDistance:50,canvasPixelRatio:1,blockLineCount:5e3,layers:["contextLineLayer","focusLineLayer","pickLineLayer"],axisTitleOffset:28,axisExtentOffset:10,bar:{width:4,captureWidth:10,fillColor:"magenta",fillOpacity:1,snapDuration:150,snapRatio:.25,snapClose:.01,strokeOpacity:1,strokeWidth:1,handleHeight:8,handleOpacity:1,handleOverlap:0},cn:{axisExtentText:"axis-extent-text",parcoordsLineLayers:"parcoords-line-layers",parcoordsLineLayer:"parcoords-lines",parcoords:"parcoords",parcoordsControlView:"parcoords-control-view",yAxis:"y-axis",axisOverlays:"axis-overlays",axis:"axis",axisHeading:"axis-heading",axisTitle:"axis-title",axisExtent:"axis-extent",axisExtentTop:"axis-extent-top",axisExtentTopText:"axis-extent-top-text",axisExtentBottom:"axis-extent-bottom",axisExtentBottomText:"axis-extent-bottom-text",axisBrush:"axis-brush"},id:{filterBarPattern:"filter-bar-pattern"}}});var Jm=ye((F_r,GNe)=>{"use strict";var NVt=HS();function VNe(e){return[e]}GNe.exports={keyFun:function(e){return e.key},repeat:VNe,descend:NVt,wrap:VNe,unwrap:function(e){return e[0]}}});var EK=ye((z_r,eUe)=>{"use strict";var bh=Pk(),tm=Oa(),UVt=Jm().keyFun,zz=Jm().repeat,x5=Dr().sorterAsc,VVt=Dr().strTranslate,HNe=bh.bar.snapRatio;function jNe(e,t){return e*(1-HNe)+t*HNe}var WNe=bh.bar.snapClose;function GVt(e,t){return e*(1-WNe)+t*WNe}function qz(e,t,r,n){if(HVt(r,n))return r;var i=e?-1:1,a=0,o=t.length-1;if(i<0){var s=a;a=o,o=s}for(var l=t[a],u=l,c=a;i*c=t[r][0]&&e<=t[r][1])return!0;return!1}function jVt(e){e.attr("x",-bh.bar.captureWidth/2).attr("width",bh.bar.captureWidth)}function WVt(e){e.attr("visibility","visible").style("visibility","visible").attr("fill","yellow").attr("opacity",0)}function XVt(e){if(!e.brush.filterSpecified)return"0,"+e.height;for(var t=XNe(e.brush.filter.getConsolidated(),e.height),r=[0],n,i,a,o=t.length?t[0][0]:null,s=0;se[1]+r||t=.9*e[1]+.1*e[0]?"n":t<=.9*e[0]+.1*e[1]?"s":"ns"}function ZNe(){tm.select(document.body).style("cursor",null)}function MK(e){e.attr("stroke-dasharray",XVt)}function Oz(e,t){var r=tm.select(e).selectAll(".highlight, .highlight-shadow"),n=t?r.transition().duration(bh.bar.snapDuration).each("end",t):r;MK(n)}function YNe(e,t){var r=e.brush,n=r.filterSpecified,i=NaN,a={},o;if(n){var s=e.height,l=r.filter.getConsolidated(),u=XNe(l,s),c=NaN,f=NaN,h=NaN;for(o=0;o<=u.length;o++){var d=u[o];if(d&&d[0]<=t&&t<=d[1]){c=o;break}else if(f=o?o-1:NaN,d&&d[0]>t){h=o;break}}if(i=c,isNaN(i)&&(isNaN(f)||isNaN(h)?i=isNaN(f)?h:f:i=t-u[f][1]=k[0]&&p<=k[1]){a.clickableOrdinalRange=k;break}}}return a}function YVt(e,t){tm.event.sourceEvent.stopPropagation();var r=t.height-tm.mouse(e)[1]-2*bh.verticalPadding,n=t.unitToPaddedPx.invert(r),i=t.brush,a=YNe(t,r),o=a.interval,s=i.svgBrush;if(s.wasDragged=!1,s.grabbingBar=a.region==="ns",s.grabbingBar){var l=o.map(t.unitToPaddedPx);s.grabPoint=r-l[0]-bh.verticalPadding,s.barLength=l[1]-l[0]}s.clickableOrdinalRange=a.clickableOrdinalRange,s.stayingIntervals=t.multiselect&&i.filterSpecified?i.filter.getConsolidated():[],o&&(s.stayingIntervals=s.stayingIntervals.filter(function(u){return u[0]!==o[0]&&u[1]!==o[1]})),s.startExtent=a.region?o[a.region==="s"?1:0]:n,t.parent.inBrushDrag=!0,s.brushStartCallback()}function KNe(e,t){tm.event.sourceEvent.stopPropagation();var r=t.height-tm.mouse(e)[1]-2*bh.verticalPadding,n=t.brush.svgBrush;n.wasDragged=!0,n._dragging=!0,n.grabbingBar?n.newExtent=[r-n.grabPoint,r+n.barLength-n.grabPoint].map(t.unitToPaddedPx.invert):n.newExtent=[n.startExtent,t.unitToPaddedPx.invert(r)].sort(x5),t.brush.filterSpecified=!0,n.extent=n.stayingIntervals.concat([n.newExtent]),n.brushCallback(t),Oz(e.parentNode)}function KVt(e,t){var r=t.brush,n=r.filter,i=r.svgBrush;i._dragging||(JNe(e,t),KNe(e,t),t.brush.svgBrush.wasDragged=!1),i._dragging=!1;var a=tm.event;a.sourceEvent.stopPropagation();var o=i.grabbingBar;if(i.grabbingBar=!1,i.grabLocation=void 0,t.parent.inBrushDrag=!1,ZNe(),!i.wasDragged){i.wasDragged=void 0,i.clickableOrdinalRange?r.filterSpecified&&t.multiselect?i.extent.push(i.clickableOrdinalRange):(i.extent=[i.clickableOrdinalRange],r.filterSpecified=!0):o?(i.extent=i.stayingIntervals,i.extent.length===0&&SK(r)):SK(r),i.brushCallback(t),Oz(e.parentNode),i.brushEndCallback(r.filterSpecified?n.getConsolidated():[]);return}var s=function(){n.set(n.getConsolidated())};if(t.ordinal){var l=t.unitTickvals;l[l.length-1]i.newExtent[0];i.extent=i.stayingIntervals.concat(u?[i.newExtent]:[]),i.extent.length||SK(r),i.brushCallback(t),u?Oz(e.parentNode,s):(s(),Oz(e.parentNode))}else s();i.brushEndCallback(r.filterSpecified?n.getConsolidated():[])}function JNe(e,t){var r=t.height-tm.mouse(e)[1]-2*bh.verticalPadding,n=YNe(t,r),i="crosshair";n.clickableOrdinalRange?i="pointer":n.region&&(i=n.region+"-resize"),tm.select(document.body).style("cursor",i)}function JVt(e){e.on("mousemove",function(t){tm.event.preventDefault(),t.parent.inBrushDrag||JNe(this,t)}).on("mouseleave",function(t){t.parent.inBrushDrag||ZNe()}).call(tm.behavior.drag().on("dragstart",function(t){YVt(this,t)}).on("drag",function(t){KNe(this,t)}).on("dragend",function(t){KVt(this,t)}))}function $Ne(e,t){return e[0]-t[0]}function $Vt(e,t,r){var n=r._context.staticPlot,i=e.selectAll(".background").data(zz);i.enter().append("rect").classed("background",!0).call(jVt).call(WVt).style("pointer-events",n?"none":"auto").attr("transform",VVt(0,bh.verticalPadding)),i.call(JVt).attr("height",function(s){return s.height-bh.verticalPadding});var a=e.selectAll(".highlight-shadow").data(zz);a.enter().append("line").classed("highlight-shadow",!0).attr("x",-bh.bar.width/2).attr("stroke-width",bh.bar.width+bh.bar.strokeWidth).attr("stroke",t).attr("opacity",bh.bar.strokeOpacity).attr("stroke-linecap","butt"),a.attr("y1",function(s){return s.height}).call(MK);var o=e.selectAll(".highlight").data(zz);o.enter().append("line").classed("highlight",!0).attr("x",-bh.bar.width/2).attr("stroke-width",bh.bar.width-bh.bar.strokeWidth).attr("stroke",bh.bar.fillColor).attr("opacity",bh.bar.fillOpacity).attr("stroke-linecap","butt"),o.attr("y1",function(s){return s.height}).call(MK)}function QVt(e,t,r){var n=e.selectAll("."+bh.cn.axisBrush).data(zz,UVt);n.enter().append("g").classed(bh.cn.axisBrush,!0),$Vt(n,t,r)}function eGt(e){return e.svgBrush.extent.map(function(t){return t.slice()})}function SK(e){e.filterSpecified=!1,e.svgBrush.extent=[[-1/0,1/0]]}function tGt(e){return function(r){var n=r.brush,i=eGt(n),a=i.slice();n.filter.set(a),e()}}function QNe(e){for(var t=e.slice(),r=[],n,i=t.shift();i;){for(n=i.slice();(i=t.shift())&&i[0]<=n[1];)n[1]=Math.max(n[1],i[1]);r.push(n)}return r.length===1&&r[0][0]>r[0][1]&&(r=[]),r}function rGt(){var e=[],t,r;return{set:function(n){e=n.map(function(i){return i.slice().sort(x5)}).sort($Ne),e.length===1&&e[0][0]===-1/0&&e[0][1]===1/0&&(e=[[0,-1]]),t=QNe(e),r=e.reduce(function(i,a){return[Math.min(i[0],a[0]),Math.max(i[1],a[1])]},[1/0,-1/0])},get:function(){return e.slice()},getConsolidated:function(){return t},getBounds:function(){return r}}}function iGt(e,t,r,n,i,a){var o=rGt();return o.set(r),{filter:o,filterSpecified:t,svgBrush:{extent:[],brushStartCallback:n,brushCallback:tGt(i),brushEndCallback:a}}}function nGt(e,t){if(Array.isArray(e[0])?(e=e.map(function(n){return n.sort(x5)}),t.multiselect?e=QNe(e.sort($Ne)):e=[e[0]]):e=[e.sort(x5)],t.tickvals){var r=t.tickvals.slice().sort(x5);if(e=e.map(function(n){var i=[qz(0,r,n[0],[]),qz(1,r,n[1],[])];if(i[1]>i[0])return i}).filter(function(n){return n}),!e.length)return}return e.length>1?e:e[0]}eUe.exports={makeBrush:iGt,ensureAxisBrush:QVt,cleanRanges:nGt}});var iUe=ye((O_r,rUe)=>{"use strict";var mx=Dr(),aGt=pv().hasColorscale,oGt=Qh(),sGt=Cc().defaults,lGt=Yd(),uGt=ho(),tUe=AK(),cGt=EK(),kK=Pk().maxDimensionCount,fGt=kz();function hGt(e,t,r,n,i){var a=i("line.color",r);if(aGt(e,"line")&&mx.isArrayOrTypedArray(a)){if(a.length)return i("line.colorscale"),oGt(e,t,n,i,{prefix:"line.",cLetter:"c"}),a.length;t.line.color=r}return 1/0}function dGt(e,t,r,n){function i(u,c){return mx.coerce(e,t,tUe.dimensions,u,c)}var a=i("values"),o=i("visible");if(a&&a.length||(o=t.visible=!1),o){i("label"),i("tickvals"),i("ticktext"),i("tickformat");var s=i("range");t._ax={_id:"y",type:"linear",showexponent:"all",exponentformat:"B",range:s},uGt.setConvert(t._ax,n.layout),i("multiselect");var l=i("constraintrange");l&&(t.constraintrange=cGt.cleanRanges(l,t))}}rUe.exports=function(t,r,n,i){function a(c,f){return mx.coerce(t,r,tUe,c,f)}var o=t.dimensions;Array.isArray(o)&&o.length>kK&&(mx.log("parcoords traces support up to "+kK+" dimensions at the moment"),o.splice(kK));var s=lGt(t,r,{name:"dimensions",layout:i,handleItemDefaults:dGt}),l=hGt(t,r,n,i,a);sGt(r,i,a),(!Array.isArray(s)||!s.length)&&(r.visible=!1),fGt(r,s,"values",l);var u=mx.extendFlat({},i.font,{size:Math.round(i.font.size/1.2)});mx.coerceFont(a,"labelfont",u),mx.coerceFont(a,"tickfont",u,{autoShadowDflt:!0}),mx.coerceFont(a,"rangefont",u),a("labelangle"),a("labelside"),a("unselected.line.color"),a("unselected.line.opacity")}});var aUe=ye((q_r,nUe)=>{"use strict";var vGt=Dr().isArrayOrTypedArray,CK=tc(),pGt=Jm().wrap;nUe.exports=function(t,r){var n,i;return CK.hasColorscale(r,"line")&&vGt(r.line.color)?(n=r.line.color,i=CK.extractOpts(r.line).colorscale,CK.calc(t,r,{vals:n,containerStr:"line",cLetter:"c"})):(n=gGt(r._length),i=[[0,r.line.color],[1,r.line.color]]),pGt({lineColor:n,cscale:i})};function gGt(e){for(var t=new Array(e),r=0;r>>16,(e&65280)>>>8,e&255],alpha:1};if(typeof e=="number")return{space:"rgb",values:[e>>>16,(e&65280)>>>8,e&255],alpha:1};if(e=String(e).toLowerCase(),LK.default[e])r=LK.default[e].slice(),i="rgb";else if(e==="transparent")n=0,i="rgb",r=[0,0,0];else if(e[0]==="#"){var a=e.slice(1),o=a.length,s=o<=4;n=1,s?(r=[parseInt(a[0]+a[0],16),parseInt(a[1]+a[1],16),parseInt(a[2]+a[2],16)],o===4&&(n=parseInt(a[3]+a[3],16)/255)):(r=[parseInt(a[0]+a[1],16),parseInt(a[2]+a[3],16),parseInt(a[4]+a[5],16)],o===8&&(n=parseInt(a[6]+a[7],16)/255)),r[0]||(r[0]=0),r[1]||(r[1]=0),r[2]||(r[2]=0),i="rgb"}else if(t=/^((?:rgba?|hs[lvb]a?|hwba?|cmyk?|xy[zy]|gray|lab|lchu?v?|[ly]uv|lms|oklch|oklab|color))\s*\(([^\)]*)\)/.exec(e)){var l=t[1];i=l.replace(/a$/,"");var u=i==="cmyk"?4:i==="gray"?1:3;r=t[2].trim().split(/\s*[,\/]\s*|\s+/),i==="color"&&(i=r.shift()),r=r.map(function(h,d){if(h[h.length-1]==="%")return h=parseFloat(h)/100,d===3?h:i==="rgb"?h*255:i[0]==="h"||i[0]==="l"&&!d?h*100:i==="lab"?h*125:i==="lch"?d<2?h*150:h*360:i[0]==="o"&&!d?h:i==="oklab"?h*.4:i==="oklch"?d<2?h*.4:h*360:h;if(i[d]==="h"||d===2&&i[i.length-1]==="h"){if(oUe[h]!==void 0)return oUe[h];if(h.endsWith("deg"))return parseFloat(h);if(h.endsWith("turn"))return parseFloat(h)*360;if(h.endsWith("grad"))return parseFloat(h)*360/400;if(h.endsWith("rad"))return parseFloat(h)*180/Math.PI}return h==="none"?0:parseFloat(h)}),n=r.length>u?r.pop():1}else/[0-9](?:\s|\/|,)/.test(e)&&(r=e.match(/([0-9]+)/g).map(function(h){return parseFloat(h)}),i=((f=(c=e.match(/([a-z])/ig))==null?void 0:c.join(""))==null?void 0:f.toLowerCase())||"rgb");return{space:i,values:r,alpha:n}}var LK,sUe,oUe,lUe=gu(()=>{LK=gtt(gX(),1),sUe=mGt,oUe={red:0,orange:60,yellow:120,green:180,blue:240,purple:300}});var Ik,PK=gu(()=>{Ik={name:"rgb",min:[0,0,0],max:[255,255,255],channel:["red","green","blue"],alias:["RGB"]}});var Bz,uUe=gu(()=>{PK();Bz={name:"hsl",min:[0,0,0],max:[360,100,100],channel:["hue","saturation","lightness"],alias:["HSL"],rgb:function(e){var t=e[0]/360,r=e[1]/100,n=e[2]/100,i,a,o,s,l,u=0;if(r===0)return l=n*255,[l,l,l];for(a=n<.5?n*(1+r):n+r-n*r,i=2*n-a,s=[0,0,0];u<3;)o=t+1/3*-(u-1),o<0?o++:o>1&&o--,l=6*o<1?i+(a-i)*6*o:2*o<1?a:3*o<2?i+(a-i)*(2/3-o)*6:i,s[u++]=l*255;return s}};Ik.hsl=function(e){var t=e[0]/255,r=e[1]/255,n=e[2]/255,i=Math.min(t,r,n),a=Math.max(t,r,n),o=a-i,s,l,u;return a===i?s=0:t===a?s=(r-n)/o:r===a?s=2+(n-t)/o:n===a&&(s=4+(t-r)/o),s=Math.min(s*60,360),s<0&&(s+=360),u=(i+a)/2,a===i?l=0:u<=.5?l=o/(a+i):l=o/(2-a-i),[s,l*100,u*100]}});var fUe={};cee(fUe,{default:()=>cUe});function cUe(e){Array.isArray(e)&&e.raw&&(e=String.raw(...arguments)),e instanceof Number&&(e=+e);var t,r,n,i=sUe(e);if(!i.space)return[];let a=i.space[0]==="h"?Bz.min:Ik.min,o=i.space[0]==="h"?Bz.max:Ik.max;return t=Array(3),t[0]=Math.min(Math.max(i.values[0],a[0]),o[0]),t[1]=Math.min(Math.max(i.values[1],a[1]),o[1]),t[2]=Math.min(Math.max(i.values[2],a[2]),o[2]),i.space[0]==="h"&&(t=Bz.rgb(t)),t.push(Math.min(Math.max(i.alpha,0),1)),t}var hUe=gu(()=>{lUe();PK();uUe()});var IK=ye(Nz=>{"use strict";var yGt=Dr().isTypedArray;Nz.convertTypedArray=function(e){return yGt(e)?Array.prototype.slice.call(e):e};Nz.isOrdinal=function(e){return!!e.tickvals};Nz.isVisible=function(e){return e.visible||!("visible"in e)}});var wUe=ye((X_r,bUe)=>{"use strict";var _Gt=["precision highp float;","","varying vec4 fragColor;","","attribute vec4 p01_04, p05_08, p09_12, p13_16,"," p17_20, p21_24, p25_28, p29_32,"," p33_36, p37_40, p41_44, p45_48,"," p49_52, p53_56, p57_60, colors;","","uniform mat4 dim0A, dim1A, dim0B, dim1B, dim0C, dim1C, dim0D, dim1D,"," loA, hiA, loB, hiB, loC, hiC, loD, hiD;","","uniform vec2 resolution, viewBoxPos, viewBoxSize;","uniform float maskHeight;","uniform float drwLayer; // 0: context, 1: focus, 2: pick","uniform vec4 contextColor;","uniform sampler2D maskTexture, palette;","","bool isPick = (drwLayer > 1.5);","bool isContext = (drwLayer < 0.5);","","const vec4 ZEROS = vec4(0.0, 0.0, 0.0, 0.0);","const vec4 UNITS = vec4(1.0, 1.0, 1.0, 1.0);","","float val(mat4 p, mat4 v) {"," return dot(matrixCompMult(p, v) * UNITS, UNITS);","}","","float axisY(float ratio, mat4 A, mat4 B, mat4 C, mat4 D) {"," float y1 = val(A, dim0A) + val(B, dim0B) + val(C, dim0C) + val(D, dim0D);"," float y2 = val(A, dim1A) + val(B, dim1B) + val(C, dim1C) + val(D, dim1D);"," return y1 * (1.0 - ratio) + y2 * ratio;","}","","int iMod(int a, int b) {"," return a - b * (a / b);","}","","bool fOutside(float p, float lo, float hi) {"," return (lo < hi) && (lo > p || p > hi);","}","","bool vOutside(vec4 p, vec4 lo, vec4 hi) {"," return ("," fOutside(p[0], lo[0], hi[0]) ||"," fOutside(p[1], lo[1], hi[1]) ||"," fOutside(p[2], lo[2], hi[2]) ||"," fOutside(p[3], lo[3], hi[3])"," );","}","","bool mOutside(mat4 p, mat4 lo, mat4 hi) {"," return ("," vOutside(p[0], lo[0], hi[0]) ||"," vOutside(p[1], lo[1], hi[1]) ||"," vOutside(p[2], lo[2], hi[2]) ||"," vOutside(p[3], lo[3], hi[3])"," );","}","","bool outsideBoundingBox(mat4 A, mat4 B, mat4 C, mat4 D) {"," return mOutside(A, loA, hiA) ||"," mOutside(B, loB, hiB) ||"," mOutside(C, loC, hiC) ||"," mOutside(D, loD, hiD);","}","","bool outsideRasterMask(mat4 A, mat4 B, mat4 C, mat4 D) {"," mat4 pnts[4];"," pnts[0] = A;"," pnts[1] = B;"," pnts[2] = C;"," pnts[3] = D;",""," for(int i = 0; i < 4; ++i) {"," for(int j = 0; j < 4; ++j) {"," for(int k = 0; k < 4; ++k) {"," if(0 == iMod("," int(255.0 * texture2D(maskTexture,"," vec2("," (float(i * 2 + j / 2) + 0.5) / 8.0,"," (pnts[i][j][k] * (maskHeight - 1.0) + 1.0) / maskHeight"," ))[3]"," ) / int(pow(2.0, float(iMod(j * 4 + k, 8)))),"," 2"," )) return true;"," }"," }"," }"," return false;","}","","vec4 position(bool isContext, float v, mat4 A, mat4 B, mat4 C, mat4 D) {"," float x = 0.5 * sign(v) + 0.5;"," float y = axisY(x, A, B, C, D);"," float z = 1.0 - abs(v);",""," z += isContext ? 0.0 : 2.0 * float("," outsideBoundingBox(A, B, C, D) ||"," outsideRasterMask(A, B, C, D)"," );",""," return vec4("," 2.0 * (vec2(x, y) * viewBoxSize + viewBoxPos) / resolution - 1.0,"," z,"," 1.0"," );","}","","void main() {"," mat4 A = mat4(p01_04, p05_08, p09_12, p13_16);"," mat4 B = mat4(p17_20, p21_24, p25_28, p29_32);"," mat4 C = mat4(p33_36, p37_40, p41_44, p45_48);"," mat4 D = mat4(p49_52, p53_56, p57_60, ZEROS);",""," float v = colors[3];",""," gl_Position = position(isContext, v, A, B, C, D);",""," fragColor ="," isContext ? vec4(contextColor) :"," isPick ? vec4(colors.rgb, 1.0) : texture2D(palette, vec2(abs(v), 0.5));","}"].join(` +`),xGt=["precision highp float;","","varying vec4 fragColor;","","void main() {"," gl_FragColor = fragColor;","}"].join(` +`),Rk=Pk().maxDimensionCount,yUe=Dr(),dUe=1e-6,Uz=2048,bGt=new Uint8Array(4),vUe=new 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T=P.selectAll("."+Dl.cn.axisExtentBottomText).data(Qm,tg);T.enter().append("text").classed(Dl.cn.axisExtentBottomText,!0).attr("dy","0.75em").call(SUe),T.text(function(z){return EUe(z,!1)}).each(function(z){Vz.font(Bd.select(this),z.model.rangeFont)}),IUe.ensureAxisBrush(E,c,t)}});var NK=ye((BK,NUe)=>{"use strict";var HGt=zUe(),jGt=Mz(),OUe=IK().isVisible,BUe={};function qUe(e,t,r){var n=t.indexOf(r),i=e.indexOf(n);return i===-1&&(i+=t.length),i}function WGt(e,t){return function(n,i){return qUe(e,t,n)-qUe(e,t,i)}}var BK=NUe.exports=function(t,r){var n=t._fullLayout,i=jGt(t,[],BUe);if(i){var a={},o={},s={},l={},u=n._size;r.forEach(function(v,_){var b=v[0].trace;s[_]=b.index;var p=l[_]=b.index;a[_]=t.data[p].dimensions,o[_]=t.data[p].dimensions.slice()});var c=function(v,_,b){var p=o[v][_],k=b.map(function(M){return M.slice()}),E="dimensions["+_+"].constraintrange",S=n._tracePreGUI[t._fullData[s[v]]._fullInput.uid];if(S[E]===void 0){var L=p.constraintrange;S[E]=L||null}var 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l=i.font;w5.coerceFont(a,"labelfont",l,{overrideDflt:{size:Math.round(l.size)}}),w5.coerceFont(a,"tickfont",l,{autoShadowDflt:!0,overrideDflt:{size:Math.round(l.size/1.2)}})}});var aVe=ye((txr,nVe)=>{"use strict";var lHt=Jm().wrap,uHt=pv().hasColorscale,cHt=gv(),fHt=JO(),hHt=So(),Fk=Dr(),dHt=Eo();nVe.exports=function(t,r){var n=Fk.filterVisible(r.dimensions);if(n.length===0)return[];var i=n.map(function(g){var P;if(g.categoryorder==="trace")P=null;else if(g.categoryorder==="array")P=g.categoryarray;else{P=fHt(g.values);for(var T=!0,z=0;z=e.length||t[e[r]]!==void 0)return!1;t[e[r]]=!0}return!0}});var vVe=ye((rxr,dVe)=>{"use strict";var Fl=Oa(),AHt=(F2(),ob(D2)).interpolateNumber,SHt=HP(),qk=vf(),yx=Dr(),zk=yx.strTranslate,oVe=So(),VK=cd(),MHt=ru();function EHt(e,t,r,n){var i=t._context.staticPlot,a=e.map(VHt.bind(0,t,r)),o=n.selectAll("g.parcatslayer").data([null]);o.enter().append("g").attr("class","parcatslayer").style("pointer-events",i?"none":"all");var s=o.selectAll("g.trace.parcats").data(a,u1),l=s.enter().append("g").attr("class","trace parcats");s.attr("transform",function(k){return zk(k.x,k.y)}),l.append("g").attr("class","paths");var u=s.select("g.paths"),c=u.selectAll("path.path").data(function(k){return k.paths},u1);c.attr("fill",function(k){return k.model.color});var f=c.enter().append("path").attr("class","path").attr("stroke-opacity",0).attr("fill",function(k){return k.model.color}).attr("fill-opacity",0);jK(f),c.attr("d",function(k){return k.svgD}),f.empty()||c.sort(GK),c.exit().remove(),c.on("mouseover",kHt).on("mouseout",CHt).on("click",LHt),l.append("g").attr("class","dimensions");var h=s.select("g.dimensions"),d=h.selectAll("g.dimension").data(function(k){return k.dimensions},u1);d.enter().append("g").attr("class","dimension"),d.attr("transform",function(k){return zk(k.x,0)}),d.exit().remove();var v=d.selectAll("g.category").data(function(k){return 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e.model.rawColor>t.model.rawColor?1:e.model.rawColor"),x=Fl.mouse(i)[0];qk.loneHover({trace:a,x:v-s.left+l.left,y:_-s.top+l.top,text:L,color:e.model.color,borderColor:"black",fontFamily:'Monaco, "Courier New", monospace',fontSize:10,fontColor:b,idealAlign:x1&&u.displayInd===l.dimensions.length-1?(h=o.left,d="left"):(h=o.left+o.width,d="right");var v=s.model.count,_=s.model.categoryLabel,b=v/s.parcatsViewModel.model.count,p={countLabel:v,categoryLabel:_,probabilityLabel:b.toFixed(3)},k=[];s.parcatsViewModel.hoverinfoItems.indexOf("count")!==-1&&k.push(["Count:",p.countLabel].join(" ")),s.parcatsViewModel.hoverinfoItems.indexOf("probability")!==-1&&k.push(["P("+p.categoryLabel+"):",p.probabilityLabel].join(" "));var E=k.join("
");return{trace:c,x:n*(h-t.left),y:i*(f-t.top),text:E,color:"lightgray",borderColor:"black",fontFamily:'Monaco, "Courier New", monospace',fontSize:12,fontColor:"black",idealAlign:d,hovertemplate:c.hovertemplate,hovertemplateLabels:p,eventData:[{data:c._input,fullData:c,count:v,category:_,probability:b}]}}function FHt(e,t,r){var n=[];return Fl.select(r.parentNode.parentNode).selectAll("g.category").select("rect.catrect").each(function(){var i=this;n.push(uVe(e,t,i))}),n}function zHt(e,t,r){e._fullLayout._calcInverseTransform(e);var n=e._fullLayout._invScaleX,i=e._fullLayout._invScaleY,a=r.getBoundingClientRect(),o=Fl.select(r).datum(),s=o.categoryViewModel,l=s.parcatsViewModel,u=l.model.dimensions[s.model.dimensionInd],c=l.trace,f=a.y+a.height/2,h,d;l.dimensions.length>1&&u.displayInd===l.dimensions.length-1?(h=a.left,d="left"):(h=a.left+a.width,d="right");var v=s.model.categoryLabel,_=o.parcatsViewModel.model.count,b=0;o.categoryViewModel.bands.forEach(function(P){P.color===o.color&&(b+=P.count)});var p=s.model.count,k=0;l.pathSelection.each(function(P){P.model.color===o.color&&(k+=P.model.count)});var E=b/_,S=b/k,L=b/p,x={countLabel:b,categoryLabel:v,probabilityLabel:E.toFixed(3)},C=[];s.parcatsViewModel.hoverinfoItems.indexOf("count")!==-1&&C.push(["Count:",x.countLabel].join(" ")),s.parcatsViewModel.hoverinfoItems.indexOf("probability")!==-1&&(C.push("P(color \u2229 "+v+"): "+x.probabilityLabel),C.push("P("+v+" | color): "+S.toFixed(3)),C.push("P(color | "+v+"): "+L.toFixed(3)));var M=C.join("
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s;a==="category"?s=uVe(r,i,o):a==="color"?s=zHt(r,i,o):a==="dimension"&&(s=FHt(r,i,o)),s&&qk.loneHover(s,{container:n._hoverlayer.node(),outerContainer:n._paper.node(),gd:r})}}}function qHt(e){var t=e.parcatsViewModel;if(!t.dragDimension&&(jK(t.pathSelection),lVe(t.dimensionSelection.selectAll("g.category")),XK(t.dimensionSelection.selectAll("g.category").selectAll("rect.bandrect")),qk.loneUnhover(t.graphDiv._fullLayout._hoverlayer.node()),t.pathSelection.sort(GK),t.hoverinfoItems.indexOf("skip")===-1)){var r=e.parcatsViewModel.hoveron,n=this;r==="color"?YK(n,"plotly_unhover",Fl.event):ZK(n,"plotly_unhover",Fl.event)}}function BHt(e){e.parcatsViewModel.arrangement!=="fixed"&&(e.dragDimensionDisplayInd=e.model.displayInd,e.initialDragDimensionDisplayInds=e.parcatsViewModel.model.dimensions.map(function(t){return t.displayInd}),e.dragHasMoved=!1,e.dragCategoryDisplayInd=null,Fl.select(this).selectAll("g.category").select("rect.catrect").each(function(t){var r=Fl.mouse(this)[0],n=Fl.mouse(this)[1];-2<=r&&r<=t.width+2&&-2<=n&&n<=t.height+2&&(e.dragCategoryDisplayInd=t.model.displayInd,e.initialDragCategoryDisplayInds=e.model.categories.map(function(i){return i.displayInd}),t.model.dragY=t.y,yx.raiseToTop(this.parentNode),Fl.select(this.parentNode).selectAll("rect.bandrect").each(function(i){i.yc.y+c.height/2&&(a.model.displayInd=c.model.displayInd,c.model.displayInd=s),e.dragCategoryDisplayInd=a.model.displayInd}if(e.dragCategoryDisplayInd===null||e.parcatsViewModel.arrangement==="freeform"){i.model.dragX=Fl.event.x;var f=e.parcatsViewModel.dimensions[r],h=e.parcatsViewModel.dimensions[n];f!==void 0&&i.model.dragXh.x&&(i.model.displayInd=h.model.displayInd,h.model.displayInd=e.dragDimensionDisplayInd),e.dragDimensionDisplayInd=i.model.displayInd}JK(e.parcatsViewModel),KK(e.parcatsViewModel),hVe(e.parcatsViewModel),fVe(e.parcatsViewModel)}}function UHt(e){if(e.parcatsViewModel.arrangement!=="fixed"&&e.dragDimensionDisplayInd!==null){Fl.select(this).selectAll("text").attr("font-weight","normal");var t={},r=cVe(e.parcatsViewModel),n=e.parcatsViewModel.model.dimensions.map(function(h){return h.displayInd}),i=e.initialDragDimensionDisplayInds.some(function(h,d){return h!==n[d]});i&&n.forEach(function(h,d){var v=e.parcatsViewModel.model.dimensions[d].containerInd;t["dimensions["+v+"].displayindex"]=h});var a=!1;if(e.dragCategoryDisplayInd!==null){var o=e.model.categories.map(function(h){return h.displayInd});if(a=e.initialDragCategoryDisplayInds.some(function(h,d){return h!==o[d]}),a){var s=e.model.categories.slice().sort(function(h,d){return h.displayInd-d.displayInd}),l=s.map(function(h){return h.categoryValue}),u=s.map(function(h){return h.categoryLabel});t["dimensions["+e.model.containerInd+"].categoryarray"]=[l],t["dimensions["+e.model.containerInd+"].ticktext"]=[u],t["dimensions["+e.model.containerInd+"].categoryorder"]="array"}}if(e.parcatsViewModel.hoverinfoItems.indexOf("skip")===-1&&!e.dragHasMoved&&e.potentialClickBand&&(e.parcatsViewModel.hoveron==="color"?YK(e.potentialClickBand,"plotly_click",Fl.event.sourceEvent):ZK(e.potentialClickBand,"plotly_click",Fl.event.sourceEvent)),e.model.dragX=null,e.dragCategoryDisplayInd!==null){var c=e.parcatsViewModel.dimensions[e.dragDimensionDisplayInd].categories[e.dragCategoryDisplayInd];c.model.dragY=null,e.dragCategoryDisplayInd=null}e.dragDimensionDisplayInd=null,e.parcatsViewModel.dragDimension=null,e.dragHasMoved=null,e.potentialClickBand=null,JK(e.parcatsViewModel),KK(e.parcatsViewModel);var f=Fl.transition().duration(300).ease("cubic-in-out");f.each(function(){hVe(e.parcatsViewModel,!0),fVe(e.parcatsViewModel,!0)}).each("end",function(){(i||a)&&SHt.restyle(e.parcatsViewModel.graphDiv,t,[r])})}}function cVe(e){for(var t,r=e.graphDiv._fullData,n=0;n=0;l--)u+="C"+o[l]+","+(t[l+1]+n)+" "+a[l]+","+(t[l]+n)+" "+(e[l]+r[l])+","+(t[l]+n),u+="l-"+r[l]+",0 ";return u+="Z",u}function KK(e){var t=e.dimensions,r=e.model,n=t.map(function(O){return O.categories.map(function(V){return V.y})}),i=e.model.dimensions.map(function(O){return O.categories.map(function(V){return V.displayInd})}),a=e.model.dimensions.map(function(O){return O.displayInd}),o=e.dimensions.map(function(O){return O.model.dimensionInd}),s=t.map(function(O){return O.x}),l=t.map(function(O){return O.width}),u=[];for(var c in r.paths)r.paths.hasOwnProperty(c)&&u.push(r.paths[c]);function f(O){var V=O.categoryInds.map(function(Z,j){return i[j][Z]}),G=o.map(function(Z){return V[Z]});return G}u.sort(function(O,V){var G=f(O),Z=f(V);return e.sortpaths==="backward"&&(G.reverse(),Z.reverse()),G.push(O.valueInds[0]),Z.push(V.valueInds[0]),e.bundlecolors&&(G.unshift(O.rawColor),Z.unshift(V.rawColor)),GZ?1:0});for(var h=new Array(u.length),d=t[0].model.count,v=t[0].categories.map(function(O){return O.height}).reduce(function(O,V){return O+V}),_=0;_0?p=v*(b.count/d):p=0;for(var k=new Array(n.length),E=0;E1?o=(e.width-2*r-n)/(i-1):o=0,s=r,l=s+o*a;var u=[],c=e.model.maxCats,f=t.categories.length,h=8,d=t.count,v=e.height-h*(c-1),_,b,p,k,E,S=(c-f)*h/2,L=t.categories.map(function(x){return{displayInd:x.displayInd,categoryInd:x.categoryInd}});for(L.sort(function(x,C){return x.displayInd-C.displayInd}),E=0;E0?_=b.count/d*v:_=0,p={key:b.valueInds[0],model:b,width:n,height:_,y:b.dragY!==null?b.dragY:S,bands:[],parcatsViewModel:e},S=S+_+h,u.push(p);return{key:t.dimensionInd,x:t.dragX!==null?t.dragX:l,y:0,width:n,model:t,categories:u,parcatsViewModel:e,dragCategoryDisplayInd:null,dragDimensionDisplayInd:null,initialDragDimensionDisplayInds:null,initialDragCategoryDisplayInds:null,dragHasMoved:null,potentialClickBand:null}}});var $K=ye((ixr,pVe)=>{"use strict";var HHt=vVe();pVe.exports=function(t,r,n,i){var a=t._fullLayout,o=a._paper,s=a._size;HHt(t,o,r,{width:s.w,height:s.h,margin:{t:s.t,r:s.r,b:s.b,l:s.l}},n,i)}});var mVe=ye(jz=>{"use strict";var jHt=Id().getModuleCalcData,WHt=$K(),gVe="parcats";jz.name=gVe;jz.plot=function(e,t,r,n){var i=jHt(e.calcdata,gVe);if(i.length){var a=i[0];WHt(e,a,r,n)}};jz.clean=function(e,t,r,n){var i=n._has&&n._has("parcats"),a=t._has&&t._has("parcats");i&&!a&&n._paperdiv.selectAll(".parcats").remove()}});var _Ve=ye((axr,yVe)=>{"use strict";yVe.exports={attributes:UK(),supplyDefaults:iVe(),calc:aVe(),plot:$K(),colorbar:{container:"line",min:"cmin",max:"cmax"},moduleType:"trace",name:"parcats",basePlotModule:mVe(),categories:["noOpacity"],meta:{}}});var bVe=ye((oxr,xVe)=>{"use strict";xVe.exports=_Ve()});var c1=ye((sxr,kVe)=>{"use strict";var XHt=Z1(),wVe="1.13.4",MVe='\xA9 OpenStreetMap contributors',TVe=['\xA9 Carto',MVe].join(" "),AVe=['Map tiles by Stamen Design','under CC BY 3.0',"|",'Data by OpenStreetMap contributors','under ODbL'].join(" "),ZHt=['Map tiles by Stamen Design','under CC BY 3.0',"|",'Data by OpenStreetMap contributors','under CC BY SA'].join(" 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m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y,y.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},y.prototype.emplaceBack=function(U,$,ae,he){var Oe=this.length;return this.resize(Oe+1),this.emplace(Oe,U,$,ae,he)},y.prototype.emplace=function(U,$,ae,he,Oe){var rt=U*4;return this.float32[rt+0]=$,this.float32[rt+1]=ae,this.float32[rt+2]=he,this.float32[rt+3]=Oe,U},y}(en);is.prototype.bytesPerElement=16,X("StructArrayLayout4f16",is);var Zs=function(m){function y(){m.apply(this,arguments)}m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y;var I={anchorPointX:{configurable:!0},anchorPointY:{configurable:!0},x1:{configurable:!0},y1:{configurable:!0},x2:{configurable:!0},y2:{configurable:!0},featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0},anchorPoint:{configurable:!0}};return I.anchorPointX.get=function(){return this._structArray.int16[this._pos2+0]},I.anchorPointY.get=function(){return this._structArray.int16[this._pos2+1]},I.x1.get=function(){return this._structArray.int16[this._pos2+2]},I.y1.get=function(){return this._structArray.int16[this._pos2+3]},I.x2.get=function(){return this._structArray.int16[this._pos2+4]},I.y2.get=function(){return this._structArray.int16[this._pos2+5]},I.featureIndex.get=function(){return this._structArray.uint32[this._pos4+3]},I.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+8]},I.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+9]},I.anchorPoint.get=function(){return new u(this.anchorPointX,this.anchorPointY)},Object.defineProperties(y.prototype,I),y}(qi);Zs.prototype.size=20;var Va=function(m){function y(){m.apply(this,arguments)}return m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y,y.prototype.get=function(U){return new 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this._structArray.uint16[this._pos2+3]},I.vertexStartIndex.get=function(){return this._structArray.uint32[this._pos4+2]},I.lineStartIndex.get=function(){return this._structArray.uint32[this._pos4+3]},I.lineLength.get=function(){return this._structArray.uint32[this._pos4+4]},I.segment.get=function(){return this._structArray.uint16[this._pos2+10]},I.lowerSize.get=function(){return this._structArray.uint16[this._pos2+11]},I.upperSize.get=function(){return this._structArray.uint16[this._pos2+12]},I.lineOffsetX.get=function(){return this._structArray.float32[this._pos4+7]},I.lineOffsetY.get=function(){return this._structArray.float32[this._pos4+8]},I.writingMode.get=function(){return this._structArray.uint8[this._pos1+36]},I.placedOrientation.get=function(){return this._structArray.uint8[this._pos1+37]},I.placedOrientation.set=function(U){this._structArray.uint8[this._pos1+37]=U},I.hidden.get=function(){return this._structArray.uint8[this._pos1+38]},I.hidden.set=function(U){this._structArray.uint8[this._pos1+38]=U},I.crossTileID.get=function(){return this._structArray.uint32[this._pos4+10]},I.crossTileID.set=function(U){this._structArray.uint32[this._pos4+10]=U},I.associatedIconIndex.get=function(){return this._structArray.int16[this._pos2+22]},Object.defineProperties(y.prototype,I),y}(qi);Ml.prototype.size=48;var zo=function(m){function y(){m.apply(this,arguments)}return m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y,y.prototype.get=function(U){return new Ml(this,U)},y}(Vn);X("PlacedSymbolArray",zo);var Qs=function(m){function y(){m.apply(this,arguments)}m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y;var I={anchorX:{configurable:!0},anchorY:{configurable:!0},rightJustifiedTextSymbolIndex:{configurable:!0},centerJustifiedTextSymbolIndex:{configurable:!0},leftJustifiedTextSymbolIndex:{configurable:!0},verticalPlacedTextSymbolIndex:{configurable:!0},placedIconSymbolIndex:{configurable:!0},verticalPlacedIconSymbolIndex:{configurable:!0},key:{configurable:!0},textBoxStartIndex:{configurable:!0},textBoxEndIndex:{configurable:!0},verticalTextBoxStartIndex:{configurable:!0},verticalTextBoxEndIndex:{configurable:!0},iconBoxStartIndex:{configurable:!0},iconBoxEndIndex:{configurable:!0},verticalIconBoxStartIndex:{configurable:!0},verticalIconBoxEndIndex:{configurable:!0},featureIndex:{configurable:!0},numHorizontalGlyphVertices:{configurable:!0},numVerticalGlyphVertices:{configurable:!0},numIconVertices:{configurable:!0},numVerticalIconVertices:{configurable:!0},useRuntimeCollisionCircles:{configurable:!0},crossTileID:{configurable:!0},textBoxScale:{configurable:!0},textOffset0:{configurable:!0},textOffset1:{configurable:!0},collisionCircleDiameter:{configurable:!0}};return I.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},I.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},I.rightJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+2]},I.centerJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+3]},I.leftJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+4]},I.verticalPlacedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+5]},I.placedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+6]},I.verticalPlacedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+7]},I.key.get=function(){return this._structArray.uint16[this._pos2+8]},I.textBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+9]},I.textBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+10]},I.verticalTextBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+11]},I.verticalTextBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+12]},I.iconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+13]},I.iconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+14]},I.verticalIconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+15]},I.verticalIconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+16]},I.featureIndex.get=function(){return this._structArray.uint16[this._pos2+17]},I.numHorizontalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+18]},I.numVerticalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+19]},I.numIconVertices.get=function(){return this._structArray.uint16[this._pos2+20]},I.numVerticalIconVertices.get=function(){return this._structArray.uint16[this._pos2+21]},I.useRuntimeCollisionCircles.get=function(){return this._structArray.uint16[this._pos2+22]},I.crossTileID.get=function(){return this._structArray.uint32[this._pos4+12]},I.crossTileID.set=function(U){this._structArray.uint32[this._pos4+12]=U},I.textBoxScale.get=function(){return this._structArray.float32[this._pos4+13]},I.textOffset0.get=function(){return this._structArray.float32[this._pos4+14]},I.textOffset1.get=function(){return this._structArray.float32[this._pos4+15]},I.collisionCircleDiameter.get=function(){return this._structArray.float32[this._pos4+16]},Object.defineProperties(y.prototype,I),y}(qi);Qs.prototype.size=68;var al=function(m){function y(){m.apply(this,arguments)}return m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y,y.prototype.get=function(U){return new Qs(this,U)},y}(na);X("SymbolInstanceArray",al);var Vl=function(m){function y(){m.apply(this,arguments)}return m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y,y.prototype.getoffsetX=function(U){return this.float32[U*1+0]},y}(Ki);X("GlyphOffsetArray",Vl);var ss=function(m){function y(){m.apply(this,arguments)}return m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y,y.prototype.getx=function(U){return this.int16[U*3+0]},y.prototype.gety=function(U){return this.int16[U*3+1]},y.prototype.gettileUnitDistanceFromAnchor=function(U){return this.int16[U*3+2]},y}(kn);X("SymbolLineVertexArray",ss);var Vs=function(m){function y(){m.apply(this,arguments)}m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y;var I={featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0}};return I.featureIndex.get=function(){return this._structArray.uint32[this._pos4+0]},I.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+2]},I.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+3]},Object.defineProperties(y.prototype,I),y}(qi);Vs.prototype.size=8;var Ys=function(m){function y(){m.apply(this,arguments)}return m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y,y.prototype.get=function(U){return new Vs(this,U)},y}(ta);X("FeatureIndexArray",Ys);var wa=Wi([{name:"a_pos",components:2,type:"Int16"}],4),ol=wa.members,io=function(y){y===void 0&&(y=[]),this.segments=y};io.prototype.prepareSegment=function(y,I,U,$){var ae=this.segments[this.segments.length-1];return y>io.MAX_VERTEX_ARRAY_LENGTH&&te("Max vertices per segment is "+io.MAX_VERTEX_ARRAY_LENGTH+": bucket requested "+y),(!ae||ae.vertexLength+y>io.MAX_VERTEX_ARRAY_LENGTH||ae.sortKey!==$)&&(ae={vertexOffset:I.length,primitiveOffset:U.length,vertexLength:0,primitiveLength:0},$!==void 0&&(ae.sortKey=$),this.segments.push(ae)),ae},io.prototype.get=function(){return 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Me(Rn.layout_symbol["text-max-angle"]),"text-writing-mode":new Me(Rn.layout_symbol["text-writing-mode"]),"text-rotate":new bt(Rn.layout_symbol["text-rotate"]),"text-padding":new Me(Rn.layout_symbol["text-padding"]),"text-keep-upright":new Me(Rn.layout_symbol["text-keep-upright"]),"text-transform":new bt(Rn.layout_symbol["text-transform"]),"text-offset":new bt(Rn.layout_symbol["text-offset"]),"text-allow-overlap":new Me(Rn.layout_symbol["text-allow-overlap"]),"text-ignore-placement":new Me(Rn.layout_symbol["text-ignore-placement"]),"text-optional":new Me(Rn.layout_symbol["text-optional"])}),Get=new Nr({"icon-opacity":new bt(Rn.paint_symbol["icon-opacity"]),"icon-color":new bt(Rn.paint_symbol["icon-color"]),"icon-halo-color":new bt(Rn.paint_symbol["icon-halo-color"]),"icon-halo-width":new bt(Rn.paint_symbol["icon-halo-width"]),"icon-halo-blur":new bt(Rn.paint_symbol["icon-halo-blur"]),"icon-translate":new Me(Rn.paint_symbol["icon-translate"]),"icon-translate-anchor":new Me(Rn.paint_symbol["icon-translate-anchor"]),"text-opacity":new bt(Rn.paint_symbol["text-opacity"]),"text-color":new bt(Rn.paint_symbol["text-color"],{runtimeType:ql,getOverride:function(m){return m.textColor},hasOverride:function(m){return!!m.textColor}}),"text-halo-color":new bt(Rn.paint_symbol["text-halo-color"]),"text-halo-width":new bt(Rn.paint_symbol["text-halo-width"]),"text-halo-blur":new bt(Rn.paint_symbol["text-halo-blur"]),"text-translate":new Me(Rn.paint_symbol["text-translate"]),"text-translate-anchor":new Me(Rn.paint_symbol["text-translate-anchor"])}),vO={paint:Get,layout:Vet},Jw=function(y){this.type=y.property.overrides?y.property.overrides.runtimeType:ac,this.defaultValue=y};Jw.prototype.evaluate=function(y){if(y.formattedSection){var I=this.defaultValue.property.overrides;if(I&&I.hasOverride(y.formattedSection))return I.getOverride(y.formattedSection)}return y.feature&&y.featureState?this.defaultValue.evaluate(y.feature,y.featureState):this.defaultValue.property.specification.default},Jw.prototype.eachChild=function(y){if(!this.defaultValue.isConstant()){var I=this.defaultValue.value;y(I._styleExpression.expression)}},Jw.prototype.outputDefined=function(){return!1},Jw.prototype.serialize=function(){return null},X("FormatSectionOverride",Jw,{omit:["defaultValue"]});var Het=function(m){function y(I){m.call(this,I,vO)}return m&&(y.__proto__=m),y.prototype=Object.create(m&&m.prototype),y.prototype.constructor=y,y.prototype.recalculate=function(U,$){if(m.prototype.recalculate.call(this,U,$),this.layout.get("icon-rotation-alignment")==="auto"&&(this.layout.get("symbol-placement")!=="point"?this.layout._values["icon-rotation-alignment"]="map":this.layout._values["icon-rotation-alignment"]="viewport"),this.layout.get("text-rotation-alignment")==="auto"&&(this.layout.get("symbol-placement")!=="point"?this.layout._values["text-rotation-alignment"]="map":this.layout._values["text-rotation-alignment"]="viewport"),this.layout.get("text-pitch-alignment")==="auto"&&(this.layout._values["text-pitch-alignment"]=this.layout.get("text-rotation-alignment")),this.layout.get("icon-pitch-alignment")==="auto"&&(this.layout._values["icon-pitch-alignment"]=this.layout.get("icon-rotation-alignment")),this.layout.get("symbol-placement")==="point"){var ae=this.layout.get("text-writing-mode");if(ae){for(var 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lh=function(y,I){y&&(I?this.setSouthWest(y).setNorthEast(I):y.length===4?this.setSouthWest([y[0],y[1]]).setNorthEast([y[2],y[3]]):this.setSouthWest(y[0]).setNorthEast(y[1]))};lh.prototype.setNorthEast=function(y){return this._ne=y instanceof Hc?new Hc(y.lng,y.lat):Hc.convert(y),this},lh.prototype.setSouthWest=function(y){return this._sw=y instanceof Hc?new Hc(y.lng,y.lat):Hc.convert(y),this},lh.prototype.extend=function(y){var I=this._sw,U=this._ne,$,ae;if(y instanceof Hc)$=y,ae=y;else if(y instanceof lh){if($=y._sw,ae=y._ne,!$||!ae)return this}else{if(Array.isArray(y))if(y.length===4||y.every(Array.isArray)){var he=y;return this.extend(lh.convert(he))}else{var Oe=y;return this.extend(Hc.convert(Oe))}return this}return!I&&!U?(this._sw=new Hc($.lng,$.lat),this._ne=new Hc(ae.lng,ae.lat)):(I.lng=Math.min($.lng,I.lng),I.lat=Math.min($.lat,I.lat),U.lng=Math.max(ae.lng,U.lng),U.lat=Math.max(ae.lat,U.lat)),this},lh.prototype.getCenter=function(){return new 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he=y.params||{},Oe=Ci/y.tileSize/y.scale,rt=be(he.filter),gt=y.queryGeometry,Et=y.queryPadding*Oe,or=nee(gt),_r=this.grid.query(or.minX-Et,or.minY-Et,or.maxX+Et,or.maxY+Et),pr=nee(y.cameraQueryGeometry),Fr=this.grid3D.query(pr.minX-Et,pr.minY-Et,pr.maxX+Et,pr.maxY+Et,function(Zn,ga,ha,eo){return gp(y.cameraQueryGeometry,Zn-Et,ga-Et,ha+Et,eo+Et)}),oi=0,Hi=Fr;oi$)ae=!1;else if(!I)ae=!0;else if(this.expirationTime=Ha.maxzoom)&&Ha.visibility!=="none"){h(Wn,this.zoom,nr);var vo=$i[Ha.id]=Ha.createBucket({index:Oi.bucketLayerIDs.length,layers:Wn,zoom:this.zoom,pixelRatio:this.pixelRatio,overscaling:this.overscaling,collisionBoxArray:this.collisionBoxArray,sourceLayerIndex:Ba,sourceID:this.source});vo.populate(ua,tn,this.tileID.canonical),Oi.bucketLayerIDs.push(Wn.map(function(Li){return Li.id}))}}}}var jn,Mt,kr,Jr,vi=i.mapObject(tn.glyphDependencies,function(Li){return Object.keys(Li).map(Number)});Object.keys(vi).length?Er.send("getGlyphs",{uid:this.uid,stacks:vi},function(Li,_n){jn||(jn=Li,Mt=_n,Mn.call(ri))}):Mt={};var hn=Object.keys(tn.iconDependencies);hn.length?Er.send("getImages",{icons:hn,source:this.source,tileID:this.tileID,type:"icons"},function(Li,_n){jn||(jn=Li,kr=_n,Mn.call(ri))}):kr={};var An=Object.keys(tn.patternDependencies);An.length?Er.send("getImages",{icons:An,source:this.source,tileID:this.tileID,type:"patterns"},function(Li,_n){jn||(jn=Li,Jr=_n,Mn.call(ri))}):Jr={},Mn.call(this);function Mn(){if(jn)return Xr(jn);if(Mt&&kr&&Jr){var Li=new c(Mt),_n=new i.ImageAtlas(kr,Jr);for(var ya in $i){var Jn=$i[ya];Jn instanceof i.SymbolBucket?(h(Jn.layers,this.zoom,nr),i.performSymbolLayout(Jn,Mt,Li.positions,kr,_n.iconPositions,this.showCollisionBoxes,this.tileID.canonical)):Jn.hasPattern&&(Jn instanceof i.LineBucket||Jn instanceof i.FillBucket||Jn instanceof i.FillExtrusionBucket)&&(h(Jn.layers,this.zoom,nr),Jn.addFeatures(tn,this.tileID.canonical,_n.patternPositions))}this.status="done",Xr(null,{buckets:i.values($i).filter(function(Ma){return!Ma.isEmpty()}),featureIndex:Oi,collisionBoxArray:this.collisionBoxArray,glyphAtlasImage:Li.image,imageAtlas:_n,glyphMap:this.returnDependencies?Mt:null,iconMap:this.returnDependencies?kr:null,glyphPositions:this.returnDependencies?Li.positions:null})}}};function h(Ut,wt,rr){for(var nr=new i.EvaluationParameters(wt),Er=0,Xr=Ut;Er=0!=!!wt&&Ut.reverse()}var L=i.vectorTile.VectorTileFeature.prototype.toGeoJSON,x=function(wt){this._feature=wt,this.extent=i.EXTENT,this.type=wt.type,this.properties=wt.tags,"id"in wt&&!isNaN(wt.id)&&(this.id=parseInt(wt.id,10))};x.prototype.loadGeometry=function(){if(this._feature.type===1){for(var wt=[],rr=0,nr=this._feature.geometry;rr>31}function Ce(Ut,wt){for(var rr=Ut.loadGeometry(),nr=Ut.type,Er=0,Xr=0,ri=rr.length,Qr=0;Qr>1;Se(Ut,wt,ri,nr,Er,Xr%2),ie(Ut,wt,rr,nr,ri-1,Xr+1),ie(Ut,wt,rr,ri+1,Er,Xr+1)}}function Se(Ut,wt,rr,nr,Er,Xr){for(;Er>nr;){if(Er-nr>600){var ri=Er-nr+1,Qr=rr-nr+1,Oi=Math.log(ri),$i=.5*Math.exp(2*Oi/3),tn=.5*Math.sqrt(Oi*$i*(ri-$i)/ri)*(Qr-ri/2<0?-1:1),fn=Math.max(nr,Math.floor(rr-Qr*$i/ri+tn)),yn=Math.min(Er,Math.floor(rr+(ri-Qr)*$i/ri+tn));Se(Ut,wt,rr,fn,yn,Xr)}var Sn=wt[2*rr+Xr],Ba=nr,ua=Er;for(Le(Ut,wt,nr,rr),wt[2*Er+Xr]>Sn&&Le(Ut,wt,nr,Er);BaSn;)ua--}wt[2*nr+Xr]===Sn?Le(Ut,wt,nr,ua):(ua++,Le(Ut,wt,ua,Er)),ua<=rr&&(nr=ua+1),rr<=ua&&(Er=ua-1)}}function Le(Ut,wt,rr,nr){Ae(Ut,rr,nr),Ae(wt,2*rr,2*nr),Ae(wt,2*rr+1,2*nr+1)}function Ae(Ut,wt,rr){var nr=Ut[wt];Ut[wt]=Ut[rr],Ut[rr]=nr}function Fe(Ut,wt,rr,nr,Er,Xr,ri){for(var Qr=[0,Ut.length-1,0],Oi=[],$i,tn;Qr.length;){var fn=Qr.pop(),yn=Qr.pop(),Sn=Qr.pop();if(yn-Sn<=ri){for(var Ba=Sn;Ba<=yn;Ba++)$i=wt[2*Ba],tn=wt[2*Ba+1],$i>=rr&&$i<=Er&&tn>=nr&&tn<=Xr&&Oi.push(Ut[Ba]);continue}var ua=Math.floor((Sn+yn)/2);$i=wt[2*ua],tn=wt[2*ua+1],$i>=rr&&$i<=Er&&tn>=nr&&tn<=Xr&&Oi.push(Ut[ua]);var ma=(fn+1)%2;(fn===0?rr<=$i:nr<=tn)&&(Qr.push(Sn),Qr.push(ua-1),Qr.push(ma)),(fn===0?Er>=$i:Xr>=tn)&&(Qr.push(ua+1),Qr.push(yn),Qr.push(ma))}return Oi}function Pe(Ut,wt,rr,nr,Er,Xr){for(var ri=[0,Ut.length-1,0],Qr=[],Oi=Er*Er;ri.length;){var $i=ri.pop(),tn=ri.pop(),fn=ri.pop();if(tn-fn<=Xr){for(var yn=fn;yn<=tn;yn++)ge(wt[2*yn],wt[2*yn+1],rr,nr)<=Oi&&Qr.push(Ut[yn]);continue}var Sn=Math.floor((fn+tn)/2),Ba=wt[2*Sn],ua=wt[2*Sn+1];ge(Ba,ua,rr,nr)<=Oi&&Qr.push(Ut[Sn]);var ma=($i+1)%2;($i===0?rr-Er<=Ba:nr-Er<=ua)&&(ri.push(fn),ri.push(Sn-1),ri.push(ma)),($i===0?rr+Er>=Ba:nr+Er>=ua)&&(ri.push(Sn+1),ri.push(tn),ri.push(ma))}return Qr}function ge(Ut,wt,rr,nr){var Er=Ut-rr,Xr=wt-nr;return Er*Er+Xr*Xr}var Re=function(Ut){return Ut[0]},ce=function(Ut){return Ut[1]},Ze=function(wt,rr,nr,Er,Xr){rr===void 0&&(rr=Re),nr===void 0&&(nr=ce),Er===void 0&&(Er=64),Xr===void 0&&(Xr=Float64Array),this.nodeSize=Er,this.points=wt;for(var ri=wt.length<65536?Uint16Array:Uint32Array,Qr=this.ids=new ri(wt.length),Oi=this.coords=new Xr(wt.length*2),$i=0;$i=Er;tn--){var fn=+Date.now();Oi=this._cluster(Oi,tn),this.trees[tn]=new Ze(Oi,$e,St,ri,Float32Array),nr&&console.log("z%d: %d clusters in %dms",tn,Oi.length,+Date.now()-fn)}return nr&&console.timeEnd("total time"),this},pt.prototype.getClusters=function(wt,rr){var nr=((wt[0]+180)%360+360)%360-180,Er=Math.max(-90,Math.min(90,wt[1])),Xr=wt[2]===180?180:((wt[2]+180)%360+360)%360-180,ri=Math.max(-90,Math.min(90,wt[3]));if(wt[2]-wt[0]>=360)nr=-180,Xr=180;else if(nr>Xr){var Qr=this.getClusters([nr,Er,180,ri],rr),Oi=this.getClusters([-180,Er,Xr,ri],rr);return Qr.concat(Oi)}for(var $i=this.trees[this._limitZoom(rr)],tn=$i.range(Nt(nr),Jt(ri),Nt(Xr),Jt(Er)),fn=[],yn=0,Sn=tn;ynrr&&(ua+=Wo.numPoints||1)}if(ua>=Oi){for(var da=fn.x*Ba,Wn=fn.y*Ba,Ha=Qr&&Ba>1?this._map(fn,!0):null,vo=(tn<<5)+(rr+1)+this.points.length,jn=0,Mt=Sn;jn1)for(var hn=0,An=Sn;hn>5},pt.prototype._getOriginZoom=function(wt){return(wt-this.points.length)%32},pt.prototype._map=function(wt,rr){if(wt.numPoints)return rr?cr({},wt.properties):wt.properties;var nr=this.points[wt.index].properties,Er=this.options.map(nr);return rr&&Er===nr?cr({},Er):Er};function Zt(Ut,wt,rr,nr,Er){return{x:Ut,y:wt,zoom:1/0,id:rr,parentId:-1,numPoints:nr,properties:Er}}function st(Ut,wt){var rr=Ut.geometry.coordinates,nr=rr[0],Er=rr[1];return{x:Nt(nr),y:Jt(Er),zoom:1/0,index:wt,parentId:-1}}function lt(Ut){return{type:"Feature",id:Ut.id,properties:Gt(Ut),geometry:{type:"Point",coordinates:[sr(Ut.x),wr(Ut.y)]}}}function Gt(Ut){var wt=Ut.numPoints,rr=wt>=1e4?Math.round(wt/1e3)+"k":wt>=1e3?Math.round(wt/100)/10+"k":wt;return cr(cr({},Ut.properties),{cluster:!0,cluster_id:Ut.id,point_count:wt,point_count_abbreviated:rr})}function Nt(Ut){return Ut/360+.5}function Jt(Ut){var wt=Math.sin(Ut*Math.PI/180),rr=.5-.25*Math.log((1+wt)/(1-wt))/Math.PI;return rr<0?0:rr>1?1:rr}function sr(Ut){return(Ut-.5)*360}function wr(Ut){var wt=(180-Ut*360)*Math.PI/180;return 360*Math.atan(Math.exp(wt))/Math.PI-90}function cr(Ut,wt){for(var rr in wt)Ut[rr]=wt[rr];return Ut}function $e(Ut){return Ut.x}function St(Ut){return Ut.y}function Qt(Ut,wt,rr,nr){for(var Er=nr,Xr=rr-wt>>1,ri=rr-wt,Qr,Oi=Ut[wt],$i=Ut[wt+1],tn=Ut[rr],fn=Ut[rr+1],yn=wt+3;ynEr)Qr=yn,Er=Sn;else if(Sn===Er){var Ba=Math.abs(yn-Xr);Banr&&(Qr-wt>3&&Qt(Ut,wt,Qr,nr),Ut[Qr+2]=Er,rr-Qr>3&&Qt(Ut,Qr,rr,nr))}function Vt(Ut,wt,rr,nr,Er,Xr){var ri=Er-rr,Qr=Xr-nr;if(ri!==0||Qr!==0){var Oi=((Ut-rr)*ri+(wt-nr)*Qr)/(ri*ri+Qr*Qr);Oi>1?(rr=Er,nr=Xr):Oi>0&&(rr+=ri*Oi,nr+=Qr*Oi)}return ri=Ut-rr,Qr=wt-nr,ri*ri+Qr*Qr}function _t(Ut,wt,rr,nr){var Er={id:typeof Ut=="undefined"?null:Ut,type:wt,geometry:rr,tags:nr,minX:1/0,minY:1/0,maxX:-1/0,maxY:-1/0};return It(Er),Er}function It(Ut){var wt=Ut.geometry,rr=Ut.type;if(rr==="Point"||rr==="MultiPoint"||rr==="LineString")mt(Ut,wt);else if(rr==="Polygon"||rr==="MultiLineString")for(var nr=0;nr0&&(nr?ri+=(Er*$i-Oi*Xr)/2:ri+=Math.sqrt(Math.pow(Oi-Er,2)+Math.pow($i-Xr,2))),Er=Oi,Xr=$i}var tn=wt.length-3;wt[2]=1,Qt(wt,0,tn,rr),wt[tn+2]=1,wt.size=Math.abs(ri),wt.start=0,wt.end=wt.size}function ti(Ut,wt,rr,nr){for(var Er=0;Er1?1:rr}function dt(Ut,wt,rr,nr,Er,Xr,ri,Qr){if(rr/=wt,nr/=wt,Xr>=rr&&ri=nr)return null;for(var Oi=[],$i=0;$i=rr&&Ba=nr)continue;var ua=[];if(yn==="Point"||yn==="MultiPoint")Ge(fn,ua,rr,nr,Er);else if(yn==="LineString")Je(fn,ua,rr,nr,Er,!1,Qr.lineMetrics);else if(yn==="MultiLineString")tt(fn,ua,rr,nr,Er,!1);else if(yn==="Polygon")tt(fn,ua,rr,nr,Er,!0);else if(yn==="MultiPolygon")for(var ma=0;ma=rr&&ri<=nr&&(wt.push(Ut[Xr]),wt.push(Ut[Xr+1]),wt.push(Ut[Xr+2]))}}function Je(Ut,wt,rr,nr,Er,Xr,ri){for(var Qr=je(Ut),Oi=Er===0?Ie:xe,$i=Ut.start,tn,fn,yn=0;ynrr&&(fn=Oi(Qr,Sn,Ba,ma,Wa,rr),ri&&(Qr.start=$i+tn*fn)):Fa>nr?Wo=rr&&(fn=Oi(Qr,Sn,Ba,ma,Wa,rr),da=!0),Wo>nr&&Fa<=nr&&(fn=Oi(Qr,Sn,Ba,ma,Wa,nr),da=!0),!Xr&&da&&(ri&&(Qr.end=$i+tn*fn),wt.push(Qr),Qr=je(Ut)),ri&&($i+=tn)}var Wn=Ut.length-3;Sn=Ut[Wn],Ba=Ut[Wn+1],ua=Ut[Wn+2],Fa=Er===0?Sn:Ba,Fa>=rr&&Fa<=nr&&xt(Qr,Sn,Ba,ua),Wn=Qr.length-3,Xr&&Wn>=3&&(Qr[Wn]!==Qr[0]||Qr[Wn+1]!==Qr[1])&&xt(Qr,Qr[0],Qr[1],Qr[2]),Qr.length&&wt.push(Qr)}function je(Ut){var wt=[];return wt.size=Ut.size,wt.start=Ut.start,wt.end=Ut.end,wt}function tt(Ut,wt,rr,nr,Er,Xr){for(var ri=0;riri.maxX&&(ri.maxX=tn),fn>ri.maxY&&(ri.maxY=fn)}return ri}function pi(Ut,wt,rr,nr){var Er=wt.geometry,Xr=wt.type,ri=[];if(Xr==="Point"||Xr==="MultiPoint")for(var Qr=0;Qr0&&wt.size<(Er?ri:nr)){rr.numPoints+=wt.length/3;return}for(var Qr=[],Oi=0;Oiri)&&(rr.numSimplified++,Qr.push(wt[Oi]),Qr.push(wt[Oi+1])),rr.numPoints++;Er&&di(Qr,Xr),Ut.push(Qr)}function di(Ut,wt){for(var rr=0,nr=0,Er=Ut.length,Xr=Er-2;nr0===wt)for(nr=0,Er=Ut.length;nr24)throw new Error("maxZoom should be in the 0-24 range");if(wt.promoteId&&wt.generateId)throw new Error("promoteId and generateId cannot be used together.");var nr=er(Ut,wt);this.tiles={},this.tileCoords=[],rr&&(console.timeEnd("preprocess data"),console.log("index: maxZoom: %d, maxPoints: %d",wt.indexMaxZoom,wt.indexMaxPoints),console.time("generate tiles"),this.stats={},this.total=0),nr=ke(nr,wt),nr.length&&this.splitTile(nr,0,0,0),rr&&(nr.length&&console.log("features: %d, points: %d",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd("generate tiles"),console.log("tiles generated:",this.total,JSON.stringify(this.stats)))}In.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},In.prototype.splitTile=function(Ut,wt,rr,nr,Er,Xr,ri){for(var Qr=[Ut,wt,rr,nr],Oi=this.options,$i=Oi.debug;Qr.length;){nr=Qr.pop(),rr=Qr.pop(),wt=Qr.pop(),Ut=Qr.pop();var tn=1<1&&console.time("creation"),yn=this.tiles[fn]=ii(Ut,wt,rr,nr,Oi),this.tileCoords.push({z:wt,x:rr,y:nr}),$i)){$i>1&&(console.log("tile z%d-%d-%d (features: %d, points: %d, simplified: %d)",wt,rr,nr,yn.numFeatures,yn.numPoints,yn.numSimplified),console.timeEnd("creation"));var Sn="z"+wt;this.stats[Sn]=(this.stats[Sn]||0)+1,this.total++}if(yn.source=Ut,Er){if(wt===Oi.maxZoom||wt===Er)continue;var Ba=1<1&&console.time("clipping");var ua=.5*Oi.buffer/Oi.extent,ma=.5-ua,Wa=.5+ua,Fa=1+ua,Wo,da,Wn,Ha,vo,jn;Wo=da=Wn=Ha=null,vo=dt(Ut,tn,rr-ua,rr+Wa,0,yn.minX,yn.maxX,Oi),jn=dt(Ut,tn,rr+ma,rr+Fa,0,yn.minX,yn.maxX,Oi),Ut=null,vo&&(Wo=dt(vo,tn,nr-ua,nr+Wa,1,yn.minY,yn.maxY,Oi),da=dt(vo,tn,nr+ma,nr+Fa,1,yn.minY,yn.maxY,Oi),vo=null),jn&&(Wn=dt(jn,tn,nr-ua,nr+Wa,1,yn.minY,yn.maxY,Oi),Ha=dt(jn,tn,nr+ma,nr+Fa,1,yn.minY,yn.maxY,Oi),jn=null),$i>1&&console.timeEnd("clipping"),Qr.push(Wo||[],wt+1,rr*2,nr*2),Qr.push(da||[],wt+1,rr*2,nr*2+1),Qr.push(Wn||[],wt+1,rr*2+1,nr*2),Qr.push(Ha||[],wt+1,rr*2+1,nr*2+1)}}},In.prototype.getTile=function(Ut,wt,rr){var nr=this.options,Er=nr.extent,Xr=nr.debug;if(Ut<0||Ut>24)return null;var ri=1<1&&console.log("drilling down to z%d-%d-%d",Ut,wt,rr);for(var Oi=Ut,$i=wt,tn=rr,fn;!fn&&Oi>0;)Oi--,$i=Math.floor($i/2),tn=Math.floor(tn/2),fn=this.tiles[wi(Oi,$i,tn)];return!fn||!fn.source?null:(Xr>1&&console.log("found parent tile z%d-%d-%d",Oi,$i,tn),Xr>1&&console.time("drilling down"),this.splitTile(fn.source,Oi,$i,tn,Ut,wt,rr),Xr>1&&console.timeEnd("drilling down"),this.tiles[Qr]?ar(this.tiles[Qr],Er):null)};function wi(Ut,wt,rr){return((1<=0?0:Y.button},o.remove=function(Y){Y.parentNode&&Y.parentNode.removeChild(Y)};function _(Y,D,J){var q,K,de,ne=i.browser.devicePixelRatio>1?"@2x":"",we=i.getJSON(D.transformRequest(D.normalizeSpriteURL(Y,ne,".json"),i.ResourceType.SpriteJSON),function(Xt,hr){we=null,de||(de=Xt,q=hr,ft())}),Ue=i.getImage(D.transformRequest(D.normalizeSpriteURL(Y,ne,".png"),i.ResourceType.SpriteImage),function(Xt,hr){Ue=null,de||(de=Xt,K=hr,ft())});function ft(){if(de)J(de);else if(q&&K){var Xt=i.browser.getImageData(K),hr={};for(var qt in q){var Ve=q[qt],Qe=Ve.width,at=Ve.height,Ct=Ve.x,Ot=Ve.y,Rt=Ve.sdf,Bt=Ve.pixelRatio,Dt=Ve.stretchX,yt=Ve.stretchY,Pt=Ve.content,ht=new i.RGBAImage({width:Qe,height:at});i.RGBAImage.copy(Xt,ht,{x:Ct,y:Ot},{x:0,y:0},{width:Qe,height:at}),hr[qt]={data:ht,pixelRatio:Bt,sdf:Rt,stretchX:Dt,stretchY:yt,content:Pt}}J(null,hr)}}return{cancel:function(){we&&(we.cancel(),we=null),Ue&&(Ue.cancel(),Ue=null)}}}function b(Y){var D=Y.userImage;if(D&&D.render){var J=D.render();if(J)return Y.data.replace(new Uint8Array(D.data.buffer)),!0}return!1}var p=1,k=function(Y){function D(){Y.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new i.RGBAImage({width:1,height:1}),this.dirty=!0}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.isLoaded=function(){return this.loaded},D.prototype.setLoaded=function(q){if(this.loaded!==q&&(this.loaded=q,q)){for(var K=0,de=this.requestors;K=0?1.2:1))}C.prototype.draw=function(Y){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(Y,this.buffer,this.middle);for(var D=this.ctx.getImageData(0,0,this.size,this.size),J=new Uint8ClampedArray(this.size*this.size),q=0;q65535){Xt(new Error("glyphs > 65535 not supported"));return}if(Ve.ranges[at]){Xt(null,{stack:hr,id:qt,glyph:Qe});return}var Ct=Ve.requests[at];Ct||(Ct=Ve.requests[at]=[],P.loadGlyphRange(hr,at,q.url,q.requestManager,function(Ot,Rt){if(Rt){for(var Bt in Rt)q._doesCharSupportLocalGlyph(+Bt)||(Ve.glyphs[+Bt]=Rt[+Bt]);Ve.ranges[at]=!0}for(var Dt=0,yt=Ct;Dt1&&(ft=D[++Ue]);var hr=Math.abs(Xt-ft.left),qt=Math.abs(Xt-ft.right),Ve=Math.min(hr,qt),Qe=void 0,at=de/q*(K+1);if(ft.isDash){var Ct=K-Math.abs(at);Qe=Math.sqrt(Ve*Ve+Ct*Ct)}else Qe=K-Math.sqrt(Ve*Ve+at*at);this.data[we+Xt]=Math.max(0,Math.min(255,Qe+128))}},G.prototype.addRegularDash=function(D){for(var J=D.length-1;J>=0;--J){var q=D[J],K=D[J+1];q.zeroLength?D.splice(J,1):K&&K.isDash===q.isDash&&(K.left=q.left,D.splice(J,1))}var de=D[0],ne=D[D.length-1];de.isDash===ne.isDash&&(de.left=ne.left-this.width,ne.right=de.right+this.width);for(var we=this.width*this.nextRow,Ue=0,ft=D[Ue],Xt=0;Xt1&&(ft=D[++Ue]);var hr=Math.abs(Xt-ft.left),qt=Math.abs(Xt-ft.right),Ve=Math.min(hr,qt),Qe=ft.isDash?Ve:-Ve;this.data[we+Xt]=Math.max(0,Math.min(255,Qe+128))}},G.prototype.addDash=function(D,J){var q=J?7:0,K=2*q+1;if(this.nextRow+K>this.height)return i.warnOnce("LineAtlas out of space"),null;for(var de=0,ne=0;ne=q.minX&&D.x=q.minY&&D.y0&&(Xt[new i.OverscaledTileID(q.overscaledZ,we,K.z,ne,K.y-1).key]={backfilled:!1},Xt[new i.OverscaledTileID(q.overscaledZ,q.wrap,K.z,K.x,K.y-1).key]={backfilled:!1},Xt[new i.OverscaledTileID(q.overscaledZ,ft,K.z,Ue,K.y-1).key]={backfilled:!1}),K.y+10&&(de.resourceTiming=q._resourceTiming,q._resourceTiming=[]),q.fire(new i.Event("data",de))})},D.prototype.onAdd=function(q){this.map=q,this.load()},D.prototype.setData=function(q){var K=this;return this._data=q,this.fire(new i.Event("dataloading",{dataType:"source"})),this._updateWorkerData(function(de){if(de){K.fire(new i.ErrorEvent(de));return}var ne={dataType:"source",sourceDataType:"content"};K._collectResourceTiming&&K._resourceTiming&&K._resourceTiming.length>0&&(ne.resourceTiming=K._resourceTiming,K._resourceTiming=[]),K.fire(new i.Event("data",ne))}),this},D.prototype.getClusterExpansionZoom=function(q,K){return this.actor.send("geojson.getClusterExpansionZoom",{clusterId:q,source:this.id},K),this},D.prototype.getClusterChildren=function(q,K){return this.actor.send("geojson.getClusterChildren",{clusterId:q,source:this.id},K),this},D.prototype.getClusterLeaves=function(q,K,de,ne){return this.actor.send("geojson.getClusterLeaves",{source:this.id,clusterId:q,limit:K,offset:de},ne),this},D.prototype._updateWorkerData=function(q){var K=this;this._loaded=!1;var de=i.extend({},this.workerOptions),ne=this._data;typeof ne=="string"?(de.request=this.map._requestManager.transformRequest(i.browser.resolveURL(ne),i.ResourceType.Source),de.request.collectResourceTiming=this._collectResourceTiming):de.data=JSON.stringify(ne),this.actor.send(this.type+".loadData",de,function(we,Ue){K._removed||Ue&&Ue.abandoned||(K._loaded=!0,Ue&&Ue.resourceTiming&&Ue.resourceTiming[K.id]&&(K._resourceTiming=Ue.resourceTiming[K.id].slice(0)),K.actor.send(K.type+".coalesce",{source:de.source},null),q(we))})},D.prototype.loaded=function(){return this._loaded},D.prototype.loadTile=function(q,K){var de=this,ne=q.actor?"reloadTile":"loadTile";q.actor=this.actor;var we={type:this.type,uid:q.uid,tileID:q.tileID,zoom:q.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:i.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};q.request=this.actor.send(ne,we,function(Ue,ft){return delete q.request,q.unloadVectorData(),q.aborted?K(null):Ue?K(Ue):(q.loadVectorData(ft,de.map.painter,ne==="reloadTile"),K(null))})},D.prototype.abortTile=function(q){q.request&&(q.request.cancel(),delete q.request),q.aborted=!0},D.prototype.unloadTile=function(q){q.unloadVectorData(),this.actor.send("removeTile",{uid:q.uid,type:this.type,source:this.id})},D.prototype.onRemove=function(){this._removed=!0,this.actor.send("removeSource",{type:this.type,source:this.id})},D.prototype.serialize=function(){return i.extend({},this._options,{type:this.type,data:this._data})},D.prototype.hasTransition=function(){return!1},D}(i.Evented),Ee=i.createLayout([{name:"a_pos",type:"Int16",components:2},{name:"a_texture_pos",type:"Int16",components:2}]),Ce=function(Y){function D(J,q,K,de){Y.call(this),this.id=J,this.dispatcher=K,this.coordinates=q.coordinates,this.type="image",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(de),this.options=q}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.load=function(q,K){var de=this;this._loaded=!1,this.fire(new i.Event("dataloading",{dataType:"source"})),this.url=this.options.url,i.getImage(this.map._requestManager.transformRequest(this.url,i.ResourceType.Image),function(ne,we){de._loaded=!0,ne?de.fire(new i.ErrorEvent(ne)):we&&(de.image=we,q&&(de.coordinates=q),K&&K(),de._finishLoading())})},D.prototype.loaded=function(){return this._loaded},D.prototype.updateImage=function(q){var K=this;return!this.image||!q.url?this:(this.options.url=q.url,this.load(q.coordinates,function(){K.texture=null}),this)},D.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new i.Event("data",{dataType:"source",sourceDataType:"metadata"})))},D.prototype.onAdd=function(q){this.map=q,this.load()},D.prototype.setCoordinates=function(q){var K=this;this.coordinates=q;var de=q.map(i.MercatorCoordinate.fromLngLat);this.tileID=me(de),this.minzoom=this.maxzoom=this.tileID.z;var ne=de.map(function(we){return K.tileID.getTilePoint(we)._round()});return this._boundsArray=new i.StructArrayLayout4i8,this._boundsArray.emplaceBack(ne[0].x,ne[0].y,0,0),this._boundsArray.emplaceBack(ne[1].x,ne[1].y,i.EXTENT,0),this._boundsArray.emplaceBack(ne[3].x,ne[3].y,0,i.EXTENT),this._boundsArray.emplaceBack(ne[2].x,ne[2].y,i.EXTENT,i.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new i.Event("data",{dataType:"source",sourceDataType:"content"})),this},D.prototype.prepare=function(){if(!(Object.keys(this.tiles).length===0||!this.image)){var q=this.map.painter.context,K=q.gl;this.boundsBuffer||(this.boundsBuffer=q.createVertexBuffer(this._boundsArray,Ee.members)),this.boundsSegments||(this.boundsSegments=i.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new i.Texture(q,this.image,K.RGBA),this.texture.bind(K.LINEAR,K.CLAMP_TO_EDGE));for(var de in this.tiles){var ne=this.tiles[de];ne.state!=="loaded"&&(ne.state="loaded",ne.texture=this.texture)}}},D.prototype.loadTile=function(q,K){this.tileID&&this.tileID.equals(q.tileID.canonical)?(this.tiles[String(q.tileID.wrap)]=q,q.buckets={},K(null)):(q.state="errored",K(null))},D.prototype.serialize=function(){return{type:"image",url:this.options.url,coordinates:this.coordinates}},D.prototype.hasTransition=function(){return!1},D}(i.Evented);function me(Y){for(var D=1/0,J=1/0,q=-1/0,K=-1/0,de=0,ne=Y;deK.end(0)?this.fire(new i.ErrorEvent(new i.ValidationError("sources."+this.id,null,"Playback for this video can be set only between the "+K.start(0)+" and "+K.end(0)+"-second mark."))):this.video.currentTime=q}},D.prototype.getVideo=function(){return this.video},D.prototype.onAdd=function(q){this.map||(this.map=q,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},D.prototype.prepare=function(){if(!(Object.keys(this.tiles).length===0||this.video.readyState<2)){var q=this.map.painter.context,K=q.gl;this.boundsBuffer||(this.boundsBuffer=q.createVertexBuffer(this._boundsArray,Ee.members)),this.boundsSegments||(this.boundsSegments=i.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(K.LINEAR,K.CLAMP_TO_EDGE),K.texSubImage2D(K.TEXTURE_2D,0,0,0,K.RGBA,K.UNSIGNED_BYTE,this.video)):(this.texture=new i.Texture(q,this.video,K.RGBA),this.texture.bind(K.LINEAR,K.CLAMP_TO_EDGE));for(var de in this.tiles){var ne=this.tiles[de];ne.state!=="loaded"&&(ne.state="loaded",ne.texture=this.texture)}}},D.prototype.serialize=function(){return{type:"video",urls:this.urls,coordinates:this.coordinates}},D.prototype.hasTransition=function(){return this.video&&!this.video.paused},D}(Ce),Se=function(Y){function D(J,q,K,de){Y.call(this,J,q,K,de),q.coordinates?(!Array.isArray(q.coordinates)||q.coordinates.length!==4||q.coordinates.some(function(ne){return!Array.isArray(ne)||ne.length!==2||ne.some(function(we){return typeof we!="number"})}))&&this.fire(new i.ErrorEvent(new i.ValidationError("sources."+J,null,'"coordinates" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new i.ErrorEvent(new i.ValidationError("sources."+J,null,'missing required property "coordinates"'))),q.animate&&typeof q.animate!="boolean"&&this.fire(new i.ErrorEvent(new i.ValidationError("sources."+J,null,'optional "animate" property must be a boolean value'))),q.canvas?typeof q.canvas!="string"&&!(q.canvas instanceof i.window.HTMLCanvasElement)&&this.fire(new i.ErrorEvent(new i.ValidationError("sources."+J,null,'"canvas" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new i.ErrorEvent(new i.ValidationError("sources."+J,null,'missing required property "canvas"'))),this.options=q,this.animate=q.animate!==void 0?q.animate:!0}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.load=function(){if(this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof i.window.HTMLCanvasElement?this.options.canvas:i.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()){this.fire(new i.ErrorEvent(new Error("Canvas dimensions cannot be less than or equal to zero.")));return}this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading()},D.prototype.getCanvas=function(){return this.canvas},D.prototype.onAdd=function(q){this.map=q,this.load(),this.canvas&&this.animate&&this.play()},D.prototype.onRemove=function(){this.pause()},D.prototype.prepare=function(){var q=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,q=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,q=!0),!this._hasInvalidDimensions()&&Object.keys(this.tiles).length!==0){var K=this.map.painter.context,de=K.gl;this.boundsBuffer||(this.boundsBuffer=K.createVertexBuffer(this._boundsArray,Ee.members)),this.boundsSegments||(this.boundsSegments=i.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(q||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new i.Texture(K,this.canvas,de.RGBA,{premultiply:!0});for(var ne in this.tiles){var we=this.tiles[ne];we.state!=="loaded"&&(we.state="loaded",we.texture=this.texture)}}},D.prototype.serialize=function(){return{type:"canvas",coordinates:this.coordinates}},D.prototype.hasTransition=function(){return this._playing},D.prototype._hasInvalidDimensions=function(){for(var q=0,K=[this.canvas.width,this.canvas.height];qthis.max){var we=this._getAndRemoveByKey(this.order[0]);we&&this.onRemove(we)}return this},st.prototype.has=function(D){return D.wrapped().key in this.data},st.prototype.getAndRemove=function(D){return this.has(D)?this._getAndRemoveByKey(D.wrapped().key):null},st.prototype._getAndRemoveByKey=function(D){var J=this.data[D].shift();return J.timeout&&clearTimeout(J.timeout),this.data[D].length===0&&delete this.data[D],this.order.splice(this.order.indexOf(D),1),J.value},st.prototype.getByKey=function(D){var J=this.data[D];return J?J[0].value:null},st.prototype.get=function(D){if(!this.has(D))return null;var J=this.data[D.wrapped().key][0];return J.value},st.prototype.remove=function(D,J){if(!this.has(D))return this;var q=D.wrapped().key,K=J===void 0?0:this.data[q].indexOf(J),de=this.data[q][K];return this.data[q].splice(K,1),de.timeout&&clearTimeout(de.timeout),this.data[q].length===0&&delete this.data[q],this.onRemove(de.value),this.order.splice(this.order.indexOf(q),1),this},st.prototype.setMaxSize=function(D){for(this.max=D;this.order.length>this.max;){var J=this._getAndRemoveByKey(this.order[0]);J&&this.onRemove(J)}return this},st.prototype.filter=function(D){var J=[];for(var q in this.data)for(var K=0,de=this.data[q];K1||(Math.abs(hr)>1&&(Math.abs(hr+Ve)===1?hr+=Ve:Math.abs(hr-Ve)===1&&(hr-=Ve)),!(!Xt.dem||!ft.dem)&&(ft.dem.backfillBorder(Xt.dem,hr,qt),ft.neighboringTiles&&ft.neighboringTiles[Qe]&&(ft.neighboringTiles[Qe].backfilled=!0)))}},D.prototype.getTile=function(q){return this.getTileByID(q.key)},D.prototype.getTileByID=function(q){return this._tiles[q]},D.prototype._retainLoadedChildren=function(q,K,de,ne){for(var we in this._tiles){var Ue=this._tiles[we];if(!(ne[we]||!Ue.hasData()||Ue.tileID.overscaledZ<=K||Ue.tileID.overscaledZ>de)){for(var ft=Ue.tileID;Ue&&Ue.tileID.overscaledZ>K+1;){var Xt=Ue.tileID.scaledTo(Ue.tileID.overscaledZ-1);Ue=this._tiles[Xt.key],Ue&&Ue.hasData()&&(ft=Xt)}for(var hr=ft;hr.overscaledZ>K;)if(hr=hr.scaledTo(hr.overscaledZ-1),q[hr.key]){ne[ft.key]=ft;break}}}},D.prototype.findLoadedParent=function(q,K){if(q.key in this._loadedParentTiles){var de=this._loadedParentTiles[q.key];return de&&de.tileID.overscaledZ>=K?de:null}for(var ne=q.overscaledZ-1;ne>=K;ne--){var we=q.scaledTo(ne),Ue=this._getLoadedTile(we);if(Ue)return Ue}},D.prototype._getLoadedTile=function(q){var K=this._tiles[q.key];if(K&&K.hasData())return K;var de=this._cache.getByKey(q.wrapped().key);return de},D.prototype.updateCacheSize=function(q){var K=Math.ceil(q.width/this._source.tileSize)+1,de=Math.ceil(q.height/this._source.tileSize)+1,ne=K*de,we=5,Ue=Math.floor(ne*we),ft=typeof this._maxTileCacheSize=="number"?Math.min(this._maxTileCacheSize,Ue):Ue;this._cache.setMaxSize(ft)},D.prototype.handleWrapJump=function(q){var K=this._prevLng===void 0?q:this._prevLng,de=q-K,ne=de/360,we=Math.round(ne);if(this._prevLng=q,we){var Ue={};for(var ft in this._tiles){var Xt=this._tiles[ft];Xt.tileID=Xt.tileID.unwrapTo(Xt.tileID.wrap+we),Ue[Xt.tileID.key]=Xt}this._tiles=Ue;for(var hr in this._timers)clearTimeout(this._timers[hr]),delete this._timers[hr];for(var qt in this._tiles){var Ve=this._tiles[qt];this._setTileReloadTimer(qt,Ve)}}},D.prototype.update=function(q){var K=this;if(this.transform=q,!(!this._sourceLoaded||this._paused)){this.updateCacheSize(q),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={};var de;this.used?this._source.tileID?de=q.getVisibleUnwrappedCoordinates(this._source.tileID).map(function(Ur){return new i.OverscaledTileID(Ur.canonical.z,Ur.wrap,Ur.canonical.z,Ur.canonical.x,Ur.canonical.y)}):(de=q.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(de=de.filter(function(Ur){return K._source.hasTile(Ur)}))):de=[];var ne=q.coveringZoomLevel(this._source),we=Math.max(ne-D.maxOverzooming,this._source.minzoom),Ue=Math.max(ne+D.maxUnderzooming,this._source.minzoom),ft=this._updateRetainedTiles(de,ne);if(Oi(this._source.type)){for(var Xt={},hr={},qt=Object.keys(ft),Ve=0,Qe=qt;Vethis._source.maxzoom){var Rt=Ct.children(this._source.maxzoom)[0],Bt=this.getTile(Rt);if(Bt&&Bt.hasData()){de[Rt.key]=Rt;continue}}else{var Dt=Ct.children(this._source.maxzoom);if(de[Dt[0].key]&&de[Dt[1].key]&&de[Dt[2].key]&&de[Dt[3].key])continue}for(var yt=Ot.wasRequested(),Pt=Ct.overscaledZ-1;Pt>=we;--Pt){var ht=Ct.scaledTo(Pt);if(ne[ht.key]||(ne[ht.key]=!0,Ot=this.getTile(ht),!Ot&&yt&&(Ot=this._addTile(ht)),Ot&&(de[ht.key]=ht,yt=Ot.wasRequested(),Ot.hasData())))break}}}return de},D.prototype._updateLoadedParentTileCache=function(){this._loadedParentTiles={};for(var q in this._tiles){for(var K=[],de=void 0,ne=this._tiles[q].tileID;ne.overscaledZ>0;){if(ne.key in this._loadedParentTiles){de=this._loadedParentTiles[ne.key];break}K.push(ne.key);var we=ne.scaledTo(ne.overscaledZ-1);if(de=this._getLoadedTile(we),de)break;ne=we}for(var Ue=0,ft=K;Ue0)&&(K.hasData()&&K.state!=="reloading"?this._cache.add(K.tileID,K,K.getExpiryTimeout()):(K.aborted=!0,this._abortTile(K),this._unloadTile(K))))},D.prototype.clearTiles=function(){this._shouldReloadOnResume=!1,this._paused=!1;for(var q in this._tiles)this._removeTile(q);this._cache.reset()},D.prototype.tilesIn=function(q,K,de){var ne=this,we=[],Ue=this.transform;if(!Ue)return we;for(var ft=de?Ue.getCameraQueryGeometry(q):q,Xt=q.map(function(Pt){return Ue.pointCoordinate(Pt)}),hr=ft.map(function(Pt){return Ue.pointCoordinate(Pt)}),qt=this.getIds(),Ve=1/0,Qe=1/0,at=-1/0,Ct=-1/0,Ot=0,Rt=hr;Ot=0&&Di[1].y+Ur>=0){var fi=Xt.map(function(gn){return ur.getTilePoint(gn)}),Ti=hr.map(function(gn){return ur.getTilePoint(gn)});we.push({tile:ht,tileID:ur,queryGeometry:fi,cameraQueryGeometry:Ti,scale:br})}}},yt=0;yt=i.browser.now())return!0}return!1},D.prototype.setFeatureState=function(q,K,de){q=q||"_geojsonTileLayer",this._state.updateState(q,K,de)},D.prototype.removeFeatureState=function(q,K,de){q=q||"_geojsonTileLayer",this._state.removeFeatureState(q,K,de)},D.prototype.getFeatureState=function(q,K){return q=q||"_geojsonTileLayer",this._state.getState(q,K)},D.prototype.setDependencies=function(q,K,de){var ne=this._tiles[q];ne&&ne.setDependencies(K,de)},D.prototype.reloadTilesForDependencies=function(q,K){for(var de in this._tiles){var ne=this._tiles[de];ne.hasDependency(q,K)&&this._reloadTile(de,"reloading")}this._cache.filter(function(we){return!we.hasDependency(q,K)})},D}(i.Evented);ri.maxOverzooming=10,ri.maxUnderzooming=3;function Qr(Y,D){var J=Math.abs(Y.wrap*2)-+(Y.wrap<0),q=Math.abs(D.wrap*2)-+(D.wrap<0);return Y.overscaledZ-D.overscaledZ||q-J||D.canonical.y-Y.canonical.y||D.canonical.x-Y.canonical.x}function Oi(Y){return Y==="raster"||Y==="image"||Y==="video"}function $i(){return new i.window.Worker(io.workerUrl)}var tn="mapboxgl_preloaded_worker_pool",fn=function(){this.active={}};fn.prototype.acquire=function(D){if(!this.workers)for(this.workers=[];this.workers.length0?(K-ne)/we:0;return this.points[de].mult(1-Ue).add(this.points[J].mult(Ue))};var Li=function(D,J,q){var K=this.boxCells=[],de=this.circleCells=[];this.xCellCount=Math.ceil(D/q),this.yCellCount=Math.ceil(J/q);for(var ne=0;nethis.width||K<0||J>this.height)return de?!1:[];var we=[];if(D<=0&&J<=0&&this.width<=q&&this.height<=K){if(de)return!0;for(var Ue=0;Ue0:we}},Li.prototype._queryCircle=function(D,J,q,K,de){var ne=D-q,we=D+q,Ue=J-q,ft=J+q;if(we<0||ne>this.width||ft<0||Ue>this.height)return K?!1:[];var Xt=[],hr={hitTest:K,circle:{x:D,y:J,radius:q},seenUids:{box:{},circle:{}}};return this._forEachCell(ne,Ue,we,ft,this._queryCellCircle,Xt,hr,de),K?Xt.length>0:Xt},Li.prototype.query=function(D,J,q,K,de){return this._query(D,J,q,K,!1,de)},Li.prototype.hitTest=function(D,J,q,K,de){return this._query(D,J,q,K,!0,de)},Li.prototype.hitTestCircle=function(D,J,q,K){return this._queryCircle(D,J,q,!0,K)},Li.prototype._queryCell=function(D,J,q,K,de,ne,we,Ue){var ft=we.seenUids,Xt=this.boxCells[de];if(Xt!==null)for(var hr=this.bboxes,qt=0,Ve=Xt;qt=hr[at+0]&&K>=hr[at+1]&&(!Ue||Ue(this.boxKeys[Qe]))){if(we.hitTest)return ne.push(!0),!0;ne.push({key:this.boxKeys[Qe],x1:hr[at],y1:hr[at+1],x2:hr[at+2],y2:hr[at+3]})}}}var Ct=this.circleCells[de];if(Ct!==null)for(var Ot=this.circles,Rt=0,Bt=Ct;Rtwe*we+Ue*Ue},Li.prototype._circleAndRectCollide=function(D,J,q,K,de,ne,we){var Ue=(ne-K)/2,ft=Math.abs(D-(K+Ue));if(ft>Ue+q)return!1;var Xt=(we-de)/2,hr=Math.abs(J-(de+Xt));if(hr>Xt+q)return!1;if(ft<=Ue||hr<=Xt)return!0;var qt=ft-Ue,Ve=hr-Xt;return qt*qt+Ve*Ve<=q*q};function _n(Y,D,J,q,K){var de=i.create();return D?(i.scale(de,de,[1/K,1/K,1]),J||i.rotateZ(de,de,q.angle)):i.multiply(de,q.labelPlaneMatrix,Y),de}function ya(Y,D,J,q,K){if(D){var de=i.clone(Y);return i.scale(de,de,[K,K,1]),J||i.rotateZ(de,de,-q.angle),de}else return q.glCoordMatrix}function Jn(Y,D){var J=[Y.x,Y.y,0,1];zl(J,J,D);var q=J[3];return{point:new i.Point(J[0]/q,J[1]/q),signedDistanceFromCamera:q}}function Ma(Y,D){return .5+.5*(Y/D)}function _o(Y,D){var J=Y[0]/Y[3],q=Y[1]/Y[3],K=J>=-D[0]&&J<=D[0]&&q>=-D[1]&&q<=D[1];return K}function No(Y,D,J,q,K,de,ne,we){var Ue=q?Y.textSizeData:Y.iconSizeData,ft=i.evaluateSizeForZoom(Ue,J.transform.zoom),Xt=[256/J.width*2+1,256/J.height*2+1],hr=q?Y.text.dynamicLayoutVertexArray:Y.icon.dynamicLayoutVertexArray;hr.clear();for(var qt=Y.lineVertexArray,Ve=q?Y.text.placedSymbolArray:Y.icon.placedSymbolArray,Qe=J.transform.width/J.transform.height,at=!1,Ct=0;Ctde)return{useVertical:!0}}return(Y===i.WritingMode.vertical?D.yJ.x)?{needsFlipping:!0}:null}function ko(Y,D,J,q,K,de,ne,we,Ue,ft,Xt,hr,qt,Ve){var Qe=D/24,at=Y.lineOffsetX*Qe,Ct=Y.lineOffsetY*Qe,Ot;if(Y.numGlyphs>1){var Rt=Y.glyphStartIndex+Y.numGlyphs,Bt=Y.lineStartIndex,Dt=Y.lineStartIndex+Y.lineLength,yt=po(Qe,we,at,Ct,J,Xt,hr,Y,Ue,de,qt);if(!yt)return{notEnoughRoom:!0};var Pt=Jn(yt.first.point,ne).point,ht=Jn(yt.last.point,ne).point;if(q&&!J){var ur=Lo(Y.writingMode,Pt,ht,Ve);if(ur)return ur}Ot=[yt.first];for(var br=Y.glyphStartIndex+1;br0?Ti.point:Ds(hr,fi,Ur,1,K),rn=Lo(Y.writingMode,Ur,gn,Ve);if(rn)return rn}var Ci=Fs(Qe*we.getoffsetX(Y.glyphStartIndex),at,Ct,J,Xt,hr,Y.segment,Y.lineStartIndex,Y.lineStartIndex+Y.lineLength,Ue,de,qt);if(!Ci)return{notEnoughRoom:!0};Ot=[Ci]}for(var Bi=0,Gi=Ot;Bi0?1:-1,Qe=0;q&&(Ve*=-1,Qe=Math.PI),Ve<0&&(Qe+=Math.PI);for(var at=Ve>0?we+ne:we+ne+1,Ct=K,Ot=K,Rt=0,Bt=0,Dt=Math.abs(qt),yt=[];Rt+Bt<=Dt;){if(at+=Ve,at=Ue)return null;if(Ot=Ct,yt.push(Ct),Ct=hr[at],Ct===void 0){var Pt=new i.Point(ft.getx(at),ft.gety(at)),ht=Jn(Pt,Xt);if(ht.signedDistanceFromCamera>0)Ct=hr[at]=ht.point;else{var ur=at-Ve,br=Rt===0?de:new i.Point(ft.getx(ur),ft.gety(ur));Ct=Ds(br,Pt,Ot,Dt-Rt+1,Xt)}}Rt+=Bt,Bt=Ot.dist(Ct)}var Ur=(Dt-Rt)/Bt,Di=Ct.sub(Ot),fi=Di.mult(Ur)._add(Ot);fi._add(Di._unit()._perp()._mult(J*Ve));var Ti=Qe+Math.atan2(Ct.y-Ot.y,Ct.x-Ot.x);return yt.push(fi),{point:fi,angle:Ti,path:yt}}var ll=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function ul(Y,D){for(var J=0;J=1;sn--)Gi.push(Ci.path[sn]);for(var zn=1;zn0){for(var so=Gi[0].clone(),Zo=Gi[0].clone(),ms=1;ms=Ti.x&&Zo.x<=gn.x&&so.y>=Ti.y&&Zo.y<=gn.y?ts=[Gi]:Zo.xgn.x||Zo.ygn.y?ts=[]:ts=i.clipLine([Gi],Ti.x,Ti.y,gn.x,gn.y)}for(var ou=0,Cv=ts;ou=this.screenRightBoundary||Kthis.screenBottomBoundary},il.prototype.isInsideGrid=function(D,J,q,K){return q>=0&&D=0&&J0){var Dt;return this.prevPlacement&&this.prevPlacement.variableOffsets[qt.crossTileID]&&this.prevPlacement.placements[qt.crossTileID]&&this.prevPlacement.placements[qt.crossTileID].text&&(Dt=this.prevPlacement.variableOffsets[qt.crossTileID].anchor),this.variableOffsets[qt.crossTileID]={textOffset:Ct,width:q,height:K,anchor:D,textBoxScale:de,prevAnchor:Dt},this.markUsedJustification(Ve,D,qt,Qe),Ve.allowVerticalPlacement&&(this.markUsedOrientation(Ve,Qe,qt),this.placedOrientations[qt.crossTileID]=Qe),{shift:Ot,placedGlyphBoxes:Rt}}},bs.prototype.placeLayerBucketPart=function(D,J,q){var K=this,de=D.parameters,ne=de.bucket,we=de.layout,Ue=de.posMatrix,ft=de.textLabelPlaneMatrix,Xt=de.labelToScreenMatrix,hr=de.textPixelRatio,qt=de.holdingForFade,Ve=de.collisionBoxArray,Qe=de.partiallyEvaluatedTextSize,at=de.collisionGroup,Ct=we.get("text-optional"),Ot=we.get("icon-optional"),Rt=we.get("text-allow-overlap"),Bt=we.get("icon-allow-overlap"),Dt=we.get("text-rotation-alignment")==="map",yt=we.get("text-pitch-alignment")==="map",Pt=we.get("icon-text-fit")!=="none",ht=we.get("symbol-z-order")==="viewport-y",ur=Rt&&(Bt||!ne.hasIconData()||Ot),br=Bt&&(Rt||!ne.hasTextData()||Ct);!ne.collisionArrays&&Ve&&ne.deserializeCollisionBoxes(Ve);var Ur=function(Ci,Bi){if(!J[Ci.crossTileID]){if(qt){K.placements[Ci.crossTileID]=new zs(!1,!1,!1);return}var Gi=!1,sn=!1,zn=!0,Ja=null,co={box:null,offscreen:null},ts={box:null,offscreen:null},so=null,Zo=null,ms=null,ou=0,Cv=0,Lv=0;Bi.textFeatureIndex?ou=Bi.textFeatureIndex:Ci.useRuntimeCollisionCircles&&(ou=Ci.featureIndex),Bi.verticalTextFeatureIndex&&(Cv=Bi.verticalTextFeatureIndex);var wd=Bi.textBox;if(wd){var Kv=function(vc){var eu=i.WritingMode.horizontal;if(ne.allowVerticalPlacement&&!vc&&K.prevPlacement){var Sd=K.prevPlacement.placedOrientations[Ci.crossTileID];Sd&&(K.placedOrientations[Ci.crossTileID]=Sd,eu=Sd,K.markUsedOrientation(ne,eu,Ci))}return eu},cg=function(vc,eu){if(ne.allowVerticalPlacement&&Ci.numVerticalGlyphVertices>0&&Bi.verticalTextBox)for(var Sd=0,ly=ne.writingModes;Sd0&&(Vd=Vd.filter(function(vc){return vc!==Ad.anchor}),Vd.unshift(Ad.anchor))}var Pv=function(vc,eu,Sd){for(var ly=vc.x2-vc.x1,T1=vc.y2-vc.y1,wu=Ci.textBoxScale,Nx=Pt&&!Bt?eu:null,om={box:[],offscreen:!1},kw=Rt?Vd.length*2:Vd.length,Rv=0;Rv=Vd.length,Ux=K.attemptAnchorPlacement(sm,vc,ly,T1,wu,Dt,yt,hr,Ue,at,Cw,Ci,ne,Sd,Nx);if(Ux&&(om=Ux.placedGlyphBoxes,om&&om.box&&om.box.length)){Gi=!0,Ja=Ux.shift;break}}return om},Jv=function(){return Pv(wd,Bi.iconBox,i.WritingMode.horizontal)},Iv=function(){var vc=Bi.verticalTextBox,eu=co&&co.box&&co.box.length;return ne.allowVerticalPlacement&&!eu&&Ci.numVerticalGlyphVertices>0&&vc?Pv(vc,Bi.verticalIconBox,i.WritingMode.vertical):{box:null,offscreen:null}};cg(Jv,Iv),co&&(Gi=co.box,zn=co.offscreen);var ay=Kv(co&&co.box);if(!Gi&&K.prevPlacement){var fg=K.prevPlacement.variableOffsets[Ci.crossTileID];fg&&(K.variableOffsets[Ci.crossTileID]=fg,K.markUsedJustification(ne,fg.anchor,Ci,ay))}}else{var pp=function(vc,eu){var Sd=K.collisionIndex.placeCollisionBox(vc,Rt,hr,Ue,at.predicate);return Sd&&Sd.box&&Sd.box.length&&(K.markUsedOrientation(ne,eu,Ci),K.placedOrientations[Ci.crossTileID]=eu),Sd},Td=function(){return pp(wd,i.WritingMode.horizontal)},gp=function(){var vc=Bi.verticalTextBox;return ne.allowVerticalPlacement&&Ci.numVerticalGlyphVertices>0&&vc?pp(vc,i.WritingMode.vertical):{box:null,offscreen:null}};cg(Td,gp),Kv(co&&co.box&&co.box.length)}}if(so=co,Gi=so&&so.box&&so.box.length>0,zn=so&&so.offscreen,Ci.useRuntimeCollisionCircles){var oh=ne.text.placedSymbolArray.get(Ci.centerJustifiedTextSymbolIndex),hg=i.evaluateSizeForFeature(ne.textSizeData,Qe,oh),oy=we.get("text-padding"),jh=Ci.collisionCircleDiameter;Zo=K.collisionIndex.placeCollisionCircles(Rt,oh,ne.lineVertexArray,ne.glyphOffsetArray,hg,Ue,ft,Xt,q,yt,at.predicate,jh,oy),Gi=Rt||Zo.circles.length>0&&!Zo.collisionDetected,zn=zn&&Zo.offscreen}if(Bi.iconFeatureIndex&&(Lv=Bi.iconFeatureIndex),Bi.iconBox){var im=function(vc){var eu=Pt&&Ja?nc(vc,Ja.x,Ja.y,Dt,yt,K.transform.angle):vc;return K.collisionIndex.placeCollisionBox(eu,Bt,hr,Ue,at.predicate)};ts&&ts.box&&ts.box.length&&Bi.verticalIconBox?(ms=im(Bi.verticalIconBox),sn=ms.box.length>0):(ms=im(Bi.iconBox),sn=ms.box.length>0),zn=zn&&ms.offscreen}var b1=Ct||Ci.numHorizontalGlyphVertices===0&&Ci.numVerticalGlyphVertices===0,w1=Ot||Ci.numIconVertices===0;if(!b1&&!w1?sn=Gi=sn&&Gi:w1?b1||(sn=sn&&Gi):Gi=sn&&Gi,Gi&&so&&so.box&&(ts&&ts.box&&Cv?K.collisionIndex.insertCollisionBox(so.box,we.get("text-ignore-placement"),ne.bucketInstanceId,Cv,at.ID):K.collisionIndex.insertCollisionBox(so.box,we.get("text-ignore-placement"),ne.bucketInstanceId,ou,at.ID)),sn&&ms&&K.collisionIndex.insertCollisionBox(ms.box,we.get("icon-ignore-placement"),ne.bucketInstanceId,Lv,at.ID),Zo&&(Gi&&K.collisionIndex.insertCollisionCircles(Zo.circles,we.get("text-ignore-placement"),ne.bucketInstanceId,ou,at.ID),q)){var sy=ne.bucketInstanceId,nm=K.collisionCircleArrays[sy];nm===void 0&&(nm=K.collisionCircleArrays[sy]=new Io);for(var am=0;am=0;--fi){var Ti=Di[fi];Ur(ne.symbolInstances.get(Ti),ne.collisionArrays[Ti])}else for(var gn=D.symbolInstanceStart;gn=0&&(ne>=0&&Xt!==ne?D.text.placedSymbolArray.get(Xt).crossTileID=0:D.text.placedSymbolArray.get(Xt).crossTileID=q.crossTileID)}},bs.prototype.markUsedOrientation=function(D,J,q){for(var K=J===i.WritingMode.horizontal||J===i.WritingMode.horizontalOnly?J:0,de=J===i.WritingMode.vertical?J:0,ne=[q.leftJustifiedTextSymbolIndex,q.centerJustifiedTextSymbolIndex,q.rightJustifiedTextSymbolIndex],we=0,Ue=ne;we0||yt>0,Ur=Bt.numIconVertices>0,Di=K.placedOrientations[Bt.crossTileID],fi=Di===i.WritingMode.vertical,Ti=Di===i.WritingMode.horizontal||Di===i.WritingMode.horizontalOnly;if(br){var gn=ac(ur.text),rn=fi?aa:gn;Qe(D.text,Dt,rn);var Ci=Ti?aa:gn;Qe(D.text,yt,Ci);var Bi=ur.text.isHidden();[Bt.rightJustifiedTextSymbolIndex,Bt.centerJustifiedTextSymbolIndex,Bt.leftJustifiedTextSymbolIndex].forEach(function(Lv){Lv>=0&&(D.text.placedSymbolArray.get(Lv).hidden=Bi||fi?1:0)}),Bt.verticalPlacedTextSymbolIndex>=0&&(D.text.placedSymbolArray.get(Bt.verticalPlacedTextSymbolIndex).hidden=Bi||Ti?1:0);var Gi=K.variableOffsets[Bt.crossTileID];Gi&&K.markUsedJustification(D,Gi.anchor,Bt,Di);var sn=K.placedOrientations[Bt.crossTileID];sn&&(K.markUsedJustification(D,"left",Bt,sn),K.markUsedOrientation(D,sn,Bt))}if(Ur){var zn=ac(ur.icon),Ja=!(qt&&Bt.verticalPlacedIconSymbolIndex&&fi);if(Bt.placedIconSymbolIndex>=0){var co=Ja?zn:aa;Qe(D.icon,Bt.numIconVertices,co),D.icon.placedSymbolArray.get(Bt.placedIconSymbolIndex).hidden=ur.icon.isHidden()}if(Bt.verticalPlacedIconSymbolIndex>=0){var ts=Ja?aa:zn;Qe(D.icon,Bt.numVerticalIconVertices,ts),D.icon.placedSymbolArray.get(Bt.verticalPlacedIconSymbolIndex).hidden=ur.icon.isHidden()}}if(D.hasIconCollisionBoxData()||D.hasTextCollisionBoxData()){var so=D.collisionArrays[Rt];if(so){var Zo=new i.Point(0,0);if(so.textBox||so.verticalTextBox){var ms=!0;if(ft){var ou=K.variableOffsets[Pt];ou?(Zo=Su(ou.anchor,ou.width,ou.height,ou.textOffset,ou.textBoxScale),Xt&&Zo._rotate(hr?K.transform.angle:-K.transform.angle)):ms=!1}so.textBox&&Rn(D.textCollisionBox.collisionVertexArray,ur.text.placed,!ms||fi,Zo.x,Zo.y),so.verticalTextBox&&Rn(D.textCollisionBox.collisionVertexArray,ur.text.placed,!ms||Ti,Zo.x,Zo.y)}var Cv=!!(!Ti&&so.verticalIconBox);so.iconBox&&Rn(D.iconCollisionBox.collisionVertexArray,ur.icon.placed,Cv,qt?Zo.x:0,qt?Zo.y:0),so.verticalIconBox&&Rn(D.iconCollisionBox.collisionVertexArray,ur.icon.placed,!Cv,qt?Zo.x:0,qt?Zo.y:0)}}},Ct=0;CtD},bs.prototype.setStale=function(){this.stale=!0};function Rn(Y,D,J,q,K){Y.emplaceBack(D?1:0,J?1:0,q||0,K||0),Y.emplaceBack(D?1:0,J?1:0,q||0,K||0),Y.emplaceBack(D?1:0,J?1:0,q||0,K||0),Y.emplaceBack(D?1:0,J?1:0,q||0,K||0)}var _a=Math.pow(2,25),Vu=Math.pow(2,24),Ol=Math.pow(2,17),xo=Math.pow(2,16),Yl=Math.pow(2,9),Ns=Math.pow(2,8),Hl=Math.pow(2,1);function ac(Y){if(Y.opacity===0&&!Y.placed)return 0;if(Y.opacity===1&&Y.placed)return 4294967295;var D=Y.placed?1:0,J=Math.floor(Y.opacity*127);return J*_a+D*Vu+J*Ol+D*xo+J*Yl+D*Ns+J*Hl+D}var aa=0,Oo=function(D){this._sortAcrossTiles=D.layout.get("symbol-z-order")!=="viewport-y"&&D.layout.get("symbol-sort-key").constantOr(1)!==void 0,this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};Oo.prototype.continuePlacement=function(D,J,q,K,de){for(var ne=this._bucketParts;this._currentTileIndex2};this._currentPlacementIndex>=0;){var we=D[this._currentPlacementIndex],Ue=J[we],ft=this.placement.collisionIndex.transform.zoom;if(Ue.type==="symbol"&&(!Ue.minzoom||Ue.minzoom<=ft)&&(!Ue.maxzoom||Ue.maxzoom>ft)){this._inProgressLayer||(this._inProgressLayer=new Oo(Ue));var Xt=this._inProgressLayer.continuePlacement(q[Ue.source],this.placement,this._showCollisionBoxes,Ue,ne);if(Xt)return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},qo.prototype.commit=function(D){return this.placement.commit(D),this.placement};var ql=512/i.EXTENT/2,Pc=function(D,J,q){this.tileID=D,this.indexedSymbolInstances={},this.bucketInstanceId=q;for(var K=0;KD.overscaledZ)for(var ft in Ue){var Xt=Ue[ft];Xt.tileID.isChildOf(D)&&Xt.findMatches(J.symbolInstances,D,ne)}else{var hr=D.scaledTo(Number(we)),qt=Ue[hr.key];qt&&qt.findMatches(J.symbolInstances,D,ne)}}for(var Ve=0;Ve0)throw new Error("Unimplemented: "+ne.map(function(we){return we.command}).join(", ")+".");return de.forEach(function(we){we.command!=="setTransition"&&K[we.command].apply(K,we.args)}),this.stylesheet=q,!0},D.prototype.addImage=function(q,K){if(this.getImage(q))return this.fire(new i.ErrorEvent(new Error("An image with this name already exists.")));this.imageManager.addImage(q,K),this._afterImageUpdated(q)},D.prototype.updateImage=function(q,K){this.imageManager.updateImage(q,K)},D.prototype.getImage=function(q){return this.imageManager.getImage(q)},D.prototype.removeImage=function(q){if(!this.getImage(q))return this.fire(new i.ErrorEvent(new Error("No image with this name exists.")));this.imageManager.removeImage(q),this._afterImageUpdated(q)},D.prototype._afterImageUpdated=function(q){this._availableImages=this.imageManager.listImages(),this._changedImages[q]=!0,this._changed=!0,this.dispatcher.broadcast("setImages",this._availableImages),this.fire(new i.Event("data",{dataType:"style"}))},D.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},D.prototype.addSource=function(q,K,de){var ne=this;if(de===void 0&&(de={}),this._checkLoaded(),this.sourceCaches[q]!==void 0)throw new Error("There is already a source with this ID");if(!K.type)throw new Error("The type property must be defined, but only the following properties were given: "+Object.keys(K).join(", ")+".");var we=["vector","raster","geojson","video","image"],Ue=we.indexOf(K.type)>=0;if(!(Ue&&this._validate(i.validateStyle.source,"sources."+q,K,null,de))){this.map&&this.map._collectResourceTiming&&(K.collectResourceTiming=!0);var ft=this.sourceCaches[q]=new ri(q,K,this.dispatcher);ft.style=this,ft.setEventedParent(this,function(){return{isSourceLoaded:ne.loaded(),source:ft.serialize(),sourceId:q}}),ft.onAdd(this.map),this._changed=!0}},D.prototype.removeSource=function(q){if(this._checkLoaded(),this.sourceCaches[q]===void 0)throw new Error("There is no source with this ID");for(var K in this._layers)if(this._layers[K].source===q)return this.fire(new i.ErrorEvent(new Error('Source "'+q+'" cannot be removed while layer "'+K+'" is using it.')));var de=this.sourceCaches[q];delete this.sourceCaches[q],delete this._updatedSources[q],de.fire(new i.Event("data",{sourceDataType:"metadata",dataType:"source",sourceId:q})),de.setEventedParent(null),de.clearTiles(),de.onRemove&&de.onRemove(this.map),this._changed=!0},D.prototype.setGeoJSONSourceData=function(q,K){this._checkLoaded();var de=this.sourceCaches[q].getSource();de.setData(K),this._changed=!0},D.prototype.getSource=function(q){return this.sourceCaches[q]&&this.sourceCaches[q].getSource()},D.prototype.addLayer=function(q,K,de){de===void 0&&(de={}),this._checkLoaded();var ne=q.id;if(this.getLayer(ne)){this.fire(new i.ErrorEvent(new Error('Layer with id "'+ne+'" already exists on this map')));return}var we;if(q.type==="custom"){if(pl(this,i.validateCustomStyleLayer(q)))return;we=i.createStyleLayer(q)}else{if(typeof q.source=="object"&&(this.addSource(ne,q.source),q=i.clone$1(q),q=i.extend(q,{source:ne})),this._validate(i.validateStyle.layer,"layers."+ne,q,{arrayIndex:-1},de))return;we=i.createStyleLayer(q),this._validateLayer(we),we.setEventedParent(this,{layer:{id:ne}}),this._serializedLayers[we.id]=we.serialize()}var Ue=K?this._order.indexOf(K):this._order.length;if(K&&Ue===-1){this.fire(new i.ErrorEvent(new Error('Layer with id "'+K+'" does not exist on this map.')));return}if(this._order.splice(Ue,0,ne),this._layerOrderChanged=!0,this._layers[ne]=we,this._removedLayers[ne]&&we.source&&we.type!=="custom"){var ft=this._removedLayers[ne];delete this._removedLayers[ne],ft.type!==we.type?this._updatedSources[we.source]="clear":(this._updatedSources[we.source]="reload",this.sourceCaches[we.source].pause())}this._updateLayer(we),we.onAdd&&we.onAdd(this.map)},D.prototype.moveLayer=function(q,K){this._checkLoaded(),this._changed=!0;var de=this._layers[q];if(!de){this.fire(new i.ErrorEvent(new Error("The layer '"+q+"' does not exist in the map's style and cannot be moved.")));return}if(q!==K){var ne=this._order.indexOf(q);this._order.splice(ne,1);var we=K?this._order.indexOf(K):this._order.length;if(K&&we===-1){this.fire(new i.ErrorEvent(new Error('Layer with id "'+K+'" does not exist on this map.')));return}this._order.splice(we,0,q),this._layerOrderChanged=!0}},D.prototype.removeLayer=function(q){this._checkLoaded();var K=this._layers[q];if(!K){this.fire(new i.ErrorEvent(new Error("The layer '"+q+"' does not exist in the map's style and cannot be removed.")));return}K.setEventedParent(null);var de=this._order.indexOf(q);this._order.splice(de,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[q]=K,delete this._layers[q],delete this._serializedLayers[q],delete this._updatedLayers[q],delete this._updatedPaintProps[q],K.onRemove&&K.onRemove(this.map)},D.prototype.getLayer=function(q){return this._layers[q]},D.prototype.hasLayer=function(q){return q in this._layers},D.prototype.setLayerZoomRange=function(q,K,de){this._checkLoaded();var ne=this.getLayer(q);if(!ne){this.fire(new i.ErrorEvent(new Error("The layer '"+q+"' does not exist in the map's style and cannot have zoom extent.")));return}ne.minzoom===K&&ne.maxzoom===de||(K!=null&&(ne.minzoom=K),de!=null&&(ne.maxzoom=de),this._updateLayer(ne))},D.prototype.setFilter=function(q,K,de){de===void 0&&(de={}),this._checkLoaded();var ne=this.getLayer(q);if(!ne){this.fire(new i.ErrorEvent(new Error("The layer '"+q+"' does not exist in the map's style and cannot be filtered.")));return}if(!i.deepEqual(ne.filter,K)){if(K==null){ne.filter=void 0,this._updateLayer(ne);return}this._validate(i.validateStyle.filter,"layers."+ne.id+".filter",K,null,de)||(ne.filter=i.clone$1(K),this._updateLayer(ne))}},D.prototype.getFilter=function(q){return i.clone$1(this.getLayer(q).filter)},D.prototype.setLayoutProperty=function(q,K,de,ne){ne===void 0&&(ne={}),this._checkLoaded();var we=this.getLayer(q);if(!we){this.fire(new i.ErrorEvent(new Error("The layer '"+q+"' does not exist in the map's style and cannot be styled.")));return}i.deepEqual(we.getLayoutProperty(K),de)||(we.setLayoutProperty(K,de,ne),this._updateLayer(we))},D.prototype.getLayoutProperty=function(q,K){var de=this.getLayer(q);if(!de){this.fire(new i.ErrorEvent(new Error("The layer '"+q+"' does not exist in the map's style.")));return}return de.getLayoutProperty(K)},D.prototype.setPaintProperty=function(q,K,de,ne){ne===void 0&&(ne={}),this._checkLoaded();var we=this.getLayer(q);if(!we){this.fire(new i.ErrorEvent(new Error("The layer '"+q+"' does not exist in the map's style and cannot be styled.")));return}if(!i.deepEqual(we.getPaintProperty(K),de)){var Ue=we.setPaintProperty(K,de,ne);Ue&&this._updateLayer(we),this._changed=!0,this._updatedPaintProps[q]=!0}},D.prototype.getPaintProperty=function(q,K){return this.getLayer(q).getPaintProperty(K)},D.prototype.setFeatureState=function(q,K){this._checkLoaded();var de=q.source,ne=q.sourceLayer,we=this.sourceCaches[de];if(we===void 0){this.fire(new i.ErrorEvent(new Error("The source '"+de+"' does not exist in the map's style.")));return}var Ue=we.getSource().type;if(Ue==="geojson"&&ne){this.fire(new i.ErrorEvent(new Error("GeoJSON sources cannot have a sourceLayer parameter.")));return}if(Ue==="vector"&&!ne){this.fire(new i.ErrorEvent(new Error("The sourceLayer parameter must be provided for vector source types.")));return}q.id===void 0&&this.fire(new i.ErrorEvent(new Error("The feature id parameter must be provided."))),we.setFeatureState(ne,q.id,K)},D.prototype.removeFeatureState=function(q,K){this._checkLoaded();var de=q.source,ne=this.sourceCaches[de];if(ne===void 0){this.fire(new i.ErrorEvent(new Error("The source '"+de+"' does not exist in the map's style.")));return}var we=ne.getSource().type,Ue=we==="vector"?q.sourceLayer:void 0;if(we==="vector"&&!Ue){this.fire(new i.ErrorEvent(new Error("The sourceLayer parameter must be provided for vector source types.")));return}if(K&&typeof q.id!="string"&&typeof q.id!="number"){this.fire(new i.ErrorEvent(new Error("A feature id is required to remove its specific state property.")));return}ne.removeFeatureState(Ue,q.id,K)},D.prototype.getFeatureState=function(q){this._checkLoaded();var K=q.source,de=q.sourceLayer,ne=this.sourceCaches[K];if(ne===void 0){this.fire(new i.ErrorEvent(new Error("The source '"+K+"' does not exist in the map's style.")));return}var we=ne.getSource().type;if(we==="vector"&&!de){this.fire(new i.ErrorEvent(new Error("The sourceLayer parameter must be provided for vector source types.")));return}return q.id===void 0&&this.fire(new i.ErrorEvent(new Error("The feature id parameter must be provided."))),ne.getFeatureState(de,q.id)},D.prototype.getTransition=function(){return i.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},D.prototype.serialize=function(){return i.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:i.mapObject(this.sourceCaches,function(q){return q.serialize()}),layers:this._serializeLayers(this._order)},function(q){return q!==void 0})},D.prototype._updateLayer=function(q){this._updatedLayers[q.id]=!0,q.source&&!this._updatedSources[q.source]&&this.sourceCaches[q.source].getSource().type!=="raster"&&(this._updatedSources[q.source]="reload",this.sourceCaches[q.source].pause()),this._changed=!0},D.prototype._flattenAndSortRenderedFeatures=function(q){for(var K=this,de=function(Ti){return K._layers[Ti].type==="fill-extrusion"},ne={},we=[],Ue=this._order.length-1;Ue>=0;Ue--){var ft=this._order[Ue];if(de(ft)){ne[ft]=Ue;for(var Xt=0,hr=q;Xt=0;Rt--){var Bt=this._order[Rt];if(de(Bt))for(var Dt=we.length-1;Dt>=0;Dt--){var yt=we[Dt].feature;if(ne[yt.layer.id] 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}`,Bl=`uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting; +#pragma mapbox: define lowp float base +#pragma mapbox: define lowp float height +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float base +#pragma mapbox: initialize lowp float height +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,wh=`uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting; +#pragma mapbox: define lowp float base +#pragma mapbox: define lowp float height +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float base +#pragma mapbox: initialize lowp float height +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0 +? a_pos +: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}`,Qf=`#ifdef GL_ES +precision highp float; +#endif +uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggerationFactor=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;float exaggeration=u_zoom < 15.0 ? (u_zoom-15.0)*exaggerationFactor : 0.0;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/pow(2.0,exaggeration+(19.2562-u_zoom));gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,_f="uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}",Yc=`uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent; +#define PI 3.141592653589793 +void main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,eh="uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}",th=`uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,ju=` +#define scale 0.015873016 +attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float width +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float width +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}`,Hf=`uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp vec2 v_uv; +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,v_uv);gl_FragColor=color*(alpha*opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,cc=` +#define scale 0.015873016 +attribute vec2 a_pos_normal;attribute vec4 a_data;attribute float a_uv_x;attribute float a_split_index;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;uniform float u_image_height;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp vec2 v_uv; +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float width +void main() { +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float width +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;highp float texel_height=1.0/u_image_height;highp float half_texel_height=0.5*texel_height;v_uv=vec2(a_uv_x,a_split_index*texel_height-half_texel_height);vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}`,of=`uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width; +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,Nl=` +#define scale 0.015873016 +#define LINE_DISTANCE_SCALE 2.0 +attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width; +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define mediump float width +#pragma mapbox: define lowp float floorwidth +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize mediump float width +#pragma mapbox: initialize lowp float floorwidth +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}`,Kc=`uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float width +#pragma mapbox: define lowp float floorwidth +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float width +#pragma mapbox: initialize lowp float floorwidth +float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,Rc=` +#define scale 0.015873016 +#define LINE_DISTANCE_SCALE 2.0 +attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float width +#pragma mapbox: define lowp float floorwidth +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float width +#pragma mapbox: initialize lowp float floorwidth +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}`,gs=`uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,jf="uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}",Gh=`uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity; +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize lowp float opacity +lowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,rh=`const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity; +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize lowp float opacity +vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ? +camera_to_anchor_distance/u_camera_to_center_distance : +u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}`,sf=`#define SDF_PX 8.0 +uniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1; +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +float EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,Th=`const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1; +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ? +camera_to_anchor_distance/u_camera_to_center_distance : +u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}`,Mu=`#define SDF_PX 8.0 +#define SDF 1.0 +#define ICON 0.0 +uniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1; +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +float fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +return;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,ih=`const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1; +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ? +camera_to_anchor_distance/u_camera_to_center_distance : +u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}`,js=Us(Cf,sc),Eu=Us(Vh,Lf),Dc=Us(cs,nf),ks=Us(Vf,Jl),bc=Us(fl,lc),hu=Us(Fu,Es),_u=Us(Hs,Go),nl=Us(ps,uc),nh=Us(xl,Gu),Ah=Us(qs,ad),zu=Us(Po,od),Fc=Us(Yo,Pa),wc=Us(af,Hu),bd=Us(bl,Gf),xf=Us(Ic,yf),Pf=Us(Bl,wh),Ou=Us(Qf,_f),bf=Us(Yc,eh),jl=Us(th,ju),lf=Us(Hf,cc),Hh=Us(of,Nl),If=Us(Kc,Rc),Cs=Us(gs,jf),du=Us(Gh,rh),ku=Us(sf,Th),Wf=Us(Mu,ih);function Us(Y,D){var J=/#pragma mapbox: ([\w]+) ([\w]+) ([\w]+) ([\w]+)/g,q=D.match(/attribute ([\w]+) ([\w]+)/g),K=Y.match(/uniform ([\w]+) ([\w]+)([\s]*)([\w]*)/g),de=D.match(/uniform ([\w]+) ([\w]+)([\s]*)([\w]*)/g),ne=de?de.concat(K):K,we={};return Y=Y.replace(J,function(Ue,ft,Xt,hr,qt){return we[qt]=!0,ft==="define"?` +#ifndef HAS_UNIFORM_u_`+qt+` +varying `+Xt+" "+hr+" "+qt+`; +#else +uniform `+Xt+" "+hr+" u_"+qt+`; +#endif +`:` +#ifdef HAS_UNIFORM_u_`+qt+` + `+Xt+" "+hr+" "+qt+" = u_"+qt+`; +#endif +`}),D=D.replace(J,function(Ue,ft,Xt,hr,qt){var Ve=hr==="float"?"vec2":"vec4",Qe=qt.match(/color/)?"color":Ve;return we[qt]?ft==="define"?` +#ifndef HAS_UNIFORM_u_`+qt+` +uniform lowp float u_`+qt+`_t; +attribute `+Xt+" "+Ve+" a_"+qt+`; +varying `+Xt+" "+hr+" "+qt+`; +#else +uniform `+Xt+" "+hr+" u_"+qt+`; +#endif +`:Qe==="vec4"?` +#ifndef HAS_UNIFORM_u_`+qt+` + `+qt+" = a_"+qt+`; +#else + `+Xt+" "+hr+" "+qt+" = u_"+qt+`; +#endif +`:` +#ifndef HAS_UNIFORM_u_`+qt+` + `+qt+" = unpack_mix_"+Qe+"(a_"+qt+", u_"+qt+`_t); +#else + `+Xt+" "+hr+" "+qt+" = u_"+qt+`; +#endif +`:ft==="define"?` +#ifndef HAS_UNIFORM_u_`+qt+` +uniform lowp float u_`+qt+`_t; +attribute `+Xt+" "+Ve+" a_"+qt+`; +#else +uniform `+Xt+" "+hr+" u_"+qt+`; +#endif +`:Qe==="vec4"?` +#ifndef HAS_UNIFORM_u_`+qt+` + `+Xt+" "+hr+" "+qt+" = a_"+qt+`; +#else + `+Xt+" "+hr+" "+qt+" = u_"+qt+`; +#endif +`:` +#ifndef HAS_UNIFORM_u_`+qt+` + `+Xt+" "+hr+" "+qt+" = unpack_mix_"+Qe+"(a_"+qt+", u_"+qt+`_t); +#else + `+Xt+" "+hr+" "+qt+" = u_"+qt+`; +#endif +`}),{fragmentSource:Y,vertexSource:D,staticAttributes:q,staticUniforms:ne}}var wf=Object.freeze({__proto__:null,prelude:js,background:Eu,backgroundPattern:Dc,circle:ks,clippingMask:bc,heatmap:hu,heatmapTexture:_u,collisionBox:nl,collisionCircle:nh,debug:Ah,fill:zu,fillOutline:Fc,fillOutlinePattern:wc,fillPattern:bd,fillExtrusion:xf,fillExtrusionPattern:Pf,hillshadePrepare:Ou,hillshade:bf,line:jl,lineGradient:lf,linePattern:Hh,lineSDF:If,raster:Cs,symbolIcon:du,symbolSDF:ku,symbolTextAndIcon:Wf}),zc=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};zc.prototype.bind=function(D,J,q,K,de,ne,we,Ue){this.context=D;for(var ft=this.boundPaintVertexBuffers.length!==K.length,Xt=0;!ft&&Xt>16,we>>16],u_pixel_coord_lower:[ne&65535,we&65535]}}function uf(Y,D,J,q){var K=J.imageManager.getPattern(Y.from.toString()),de=J.imageManager.getPattern(Y.to.toString()),ne=J.imageManager.getPixelSize(),we=ne.width,Ue=ne.height,ft=Math.pow(2,q.tileID.overscaledZ),Xt=q.tileSize*Math.pow(2,J.transform.tileZoom)/ft,hr=Xt*(q.tileID.canonical.x+q.tileID.wrap*ft),qt=Xt*q.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:K.tl,u_pattern_br_a:K.br,u_pattern_tl_b:de.tl,u_pattern_br_b:de.br,u_texsize:[we,Ue],u_mix:D.t,u_pattern_size_a:K.displaySize,u_pattern_size_b:de.displaySize,u_scale_a:D.fromScale,u_scale_b:D.toScale,u_tile_units_to_pixels:1/As(q,1,J.transform.tileZoom),u_pixel_coord_upper:[hr>>16,qt>>16],u_pixel_coord_lower:[hr&65535,qt&65535]}}var Xf=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_lightpos:new i.Uniform3f(Y,D.u_lightpos),u_lightintensity:new i.Uniform1f(Y,D.u_lightintensity),u_lightcolor:new i.Uniform3f(Y,D.u_lightcolor),u_vertical_gradient:new i.Uniform1f(Y,D.u_vertical_gradient),u_opacity:new i.Uniform1f(Y,D.u_opacity)}},Wl=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_lightpos:new i.Uniform3f(Y,D.u_lightpos),u_lightintensity:new i.Uniform1f(Y,D.u_lightintensity),u_lightcolor:new i.Uniform3f(Y,D.u_lightcolor),u_vertical_gradient:new i.Uniform1f(Y,D.u_vertical_gradient),u_height_factor:new i.Uniform1f(Y,D.u_height_factor),u_image:new i.Uniform1i(Y,D.u_image),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_pixel_coord_upper:new i.Uniform2f(Y,D.u_pixel_coord_upper),u_pixel_coord_lower:new i.Uniform2f(Y,D.u_pixel_coord_lower),u_scale:new i.Uniform3f(Y,D.u_scale),u_fade:new i.Uniform1f(Y,D.u_fade),u_opacity:new i.Uniform1f(Y,D.u_opacity)}},ah=function(Y,D,J,q){var K=D.style.light,de=K.properties.get("position"),ne=[de.x,de.y,de.z],we=i.create$1();K.properties.get("anchor")==="viewport"&&i.fromRotation(we,-D.transform.angle),i.transformMat3(ne,ne,we);var Ue=K.properties.get("color");return{u_matrix:Y,u_lightpos:ne,u_lightintensity:K.properties.get("intensity"),u_lightcolor:[Ue.r,Ue.g,Ue.b],u_vertical_gradient:+J,u_opacity:q}},Zu=function(Y,D,J,q,K,de,ne){return i.extend(ah(Y,D,J,q),Xu(de,D,ne),{u_height_factor:-Math.pow(2,K.overscaledZ)/ne.tileSize/8})},Oc=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix)}},Tc=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_image:new i.Uniform1i(Y,D.u_image),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_pixel_coord_upper:new i.Uniform2f(Y,D.u_pixel_coord_upper),u_pixel_coord_lower:new i.Uniform2f(Y,D.u_pixel_coord_lower),u_scale:new i.Uniform3f(Y,D.u_scale),u_fade:new i.Uniform1f(Y,D.u_fade)}},wl=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_world:new i.Uniform2f(Y,D.u_world)}},vu=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_world:new i.Uniform2f(Y,D.u_world),u_image:new i.Uniform1i(Y,D.u_image),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_pixel_coord_upper:new i.Uniform2f(Y,D.u_pixel_coord_upper),u_pixel_coord_lower:new i.Uniform2f(Y,D.u_pixel_coord_lower),u_scale:new i.Uniform3f(Y,D.u_scale),u_fade:new i.Uniform1f(Y,D.u_fade)}},qc=function(Y){return{u_matrix:Y}},cf=function(Y,D,J,q){return i.extend(qc(Y),Xu(J,D,q))},fc=function(Y,D){return{u_matrix:Y,u_world:D}},Bc=function(Y,D,J,q,K){return i.extend(cf(Y,D,J,q),{u_world:K})},At=function(Y,D){return{u_camera_to_center_distance:new i.Uniform1f(Y,D.u_camera_to_center_distance),u_scale_with_map:new i.Uniform1i(Y,D.u_scale_with_map),u_pitch_with_map:new i.Uniform1i(Y,D.u_pitch_with_map),u_extrude_scale:new i.Uniform2f(Y,D.u_extrude_scale),u_device_pixel_ratio:new i.Uniform1f(Y,D.u_device_pixel_ratio),u_matrix:new i.UniformMatrix4f(Y,D.u_matrix)}},Wt=function(Y,D,J,q){var K=Y.transform,de,ne;if(q.paint.get("circle-pitch-alignment")==="map"){var we=As(J,1,K.zoom);de=!0,ne=[we,we]}else de=!1,ne=K.pixelsToGLUnits;return{u_camera_to_center_distance:K.cameraToCenterDistance,u_scale_with_map:+(q.paint.get("circle-pitch-scale")==="map"),u_matrix:Y.translatePosMatrix(D.posMatrix,J,q.paint.get("circle-translate"),q.paint.get("circle-translate-anchor")),u_pitch_with_map:+de,u_device_pixel_ratio:i.browser.devicePixelRatio,u_extrude_scale:ne}},Cr=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_camera_to_center_distance:new i.Uniform1f(Y,D.u_camera_to_center_distance),u_pixels_to_tile_units:new i.Uniform1f(Y,D.u_pixels_to_tile_units),u_extrude_scale:new i.Uniform2f(Y,D.u_extrude_scale),u_overscale_factor:new i.Uniform1f(Y,D.u_overscale_factor)}},Ar=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_inv_matrix:new i.UniformMatrix4f(Y,D.u_inv_matrix),u_camera_to_center_distance:new i.Uniform1f(Y,D.u_camera_to_center_distance),u_viewport_size:new i.Uniform2f(Y,D.u_viewport_size)}},Kr=function(Y,D,J){var q=As(J,1,D.zoom),K=Math.pow(2,D.zoom-J.tileID.overscaledZ),de=J.tileID.overscaleFactor();return{u_matrix:Y,u_camera_to_center_distance:D.cameraToCenterDistance,u_pixels_to_tile_units:q,u_extrude_scale:[D.pixelsToGLUnits[0]/(q*K),D.pixelsToGLUnits[1]/(q*K)],u_overscale_factor:de}},ki=function(Y,D,J){return{u_matrix:Y,u_inv_matrix:D,u_camera_to_center_distance:J.cameraToCenterDistance,u_viewport_size:[J.width,J.height]}},Xi=function(Y,D){return{u_color:new i.UniformColor(Y,D.u_color),u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_overlay:new i.Uniform1i(Y,D.u_overlay),u_overlay_scale:new i.Uniform1f(Y,D.u_overlay_scale)}},dn=function(Y,D,J){return J===void 0&&(J=1),{u_matrix:Y,u_color:D,u_overlay:0,u_overlay_scale:J}},wn=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix)}},Nn=function(Y){return{u_matrix:Y}},Yi=function(Y,D){return{u_extrude_scale:new i.Uniform1f(Y,D.u_extrude_scale),u_intensity:new i.Uniform1f(Y,D.u_intensity),u_matrix:new i.UniformMatrix4f(Y,D.u_matrix)}},Qi=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_world:new i.Uniform2f(Y,D.u_world),u_image:new i.Uniform1i(Y,D.u_image),u_color_ramp:new i.Uniform1i(Y,D.u_color_ramp),u_opacity:new i.Uniform1f(Y,D.u_opacity)}},on=function(Y,D,J,q){return{u_matrix:Y,u_extrude_scale:As(D,1,J),u_intensity:q}},Fi=function(Y,D,J,q){var K=i.create();i.ortho(K,0,Y.width,Y.height,0,0,1);var de=Y.context.gl;return{u_matrix:K,u_world:[de.drawingBufferWidth,de.drawingBufferHeight],u_image:J,u_color_ramp:q,u_opacity:D.paint.get("heatmap-opacity")}},$n=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_image:new i.Uniform1i(Y,D.u_image),u_latrange:new i.Uniform2f(Y,D.u_latrange),u_light:new i.Uniform2f(Y,D.u_light),u_shadow:new i.UniformColor(Y,D.u_shadow),u_highlight:new i.UniformColor(Y,D.u_highlight),u_accent:new i.UniformColor(Y,D.u_accent)}},Ca=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_image:new i.Uniform1i(Y,D.u_image),u_dimension:new i.Uniform2f(Y,D.u_dimension),u_zoom:new i.Uniform1f(Y,D.u_zoom),u_unpack:new i.Uniform4f(Y,D.u_unpack)}},Ra=function(Y,D,J){var q=J.paint.get("hillshade-shadow-color"),K=J.paint.get("hillshade-highlight-color"),de=J.paint.get("hillshade-accent-color"),ne=J.paint.get("hillshade-illumination-direction")*(Math.PI/180);J.paint.get("hillshade-illumination-anchor")==="viewport"&&(ne-=Y.transform.angle);var we=!Y.options.moving;return{u_matrix:Y.transform.calculatePosMatrix(D.tileID.toUnwrapped(),we),u_image:0,u_latrange:Na(Y,D.tileID),u_light:[J.paint.get("hillshade-exaggeration"),ne],u_shadow:q,u_highlight:K,u_accent:de}},La=function(Y,D){var J=D.stride,q=i.create();return i.ortho(q,0,i.EXTENT,-i.EXTENT,0,0,1),i.translate(q,q,[0,-i.EXTENT,0]),{u_matrix:q,u_image:1,u_dimension:[J,J],u_zoom:Y.overscaledZ,u_unpack:D.getUnpackVector()}};function Na(Y,D){var J=Math.pow(2,D.canonical.z),q=D.canonical.y;return[new i.MercatorCoordinate(0,q/J).toLngLat().lat,new i.MercatorCoordinate(0,(q+1)/J).toLngLat().lat]}var Yn=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_ratio:new i.Uniform1f(Y,D.u_ratio),u_device_pixel_ratio:new i.Uniform1f(Y,D.u_device_pixel_ratio),u_units_to_pixels:new i.Uniform2f(Y,D.u_units_to_pixels)}},Dn=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_ratio:new i.Uniform1f(Y,D.u_ratio),u_device_pixel_ratio:new i.Uniform1f(Y,D.u_device_pixel_ratio),u_units_to_pixels:new i.Uniform2f(Y,D.u_units_to_pixels),u_image:new i.Uniform1i(Y,D.u_image),u_image_height:new i.Uniform1f(Y,D.u_image_height)}},Ka=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_ratio:new i.Uniform1f(Y,D.u_ratio),u_device_pixel_ratio:new i.Uniform1f(Y,D.u_device_pixel_ratio),u_image:new i.Uniform1i(Y,D.u_image),u_units_to_pixels:new i.Uniform2f(Y,D.u_units_to_pixels),u_scale:new i.Uniform3f(Y,D.u_scale),u_fade:new i.Uniform1f(Y,D.u_fade)}},bo=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_ratio:new i.Uniform1f(Y,D.u_ratio),u_device_pixel_ratio:new i.Uniform1f(Y,D.u_device_pixel_ratio),u_units_to_pixels:new i.Uniform2f(Y,D.u_units_to_pixels),u_patternscale_a:new i.Uniform2f(Y,D.u_patternscale_a),u_patternscale_b:new i.Uniform2f(Y,D.u_patternscale_b),u_sdfgamma:new i.Uniform1f(Y,D.u_sdfgamma),u_image:new i.Uniform1i(Y,D.u_image),u_tex_y_a:new i.Uniform1f(Y,D.u_tex_y_a),u_tex_y_b:new i.Uniform1f(Y,D.u_tex_y_b),u_mix:new i.Uniform1f(Y,D.u_mix)}},Xo=function(Y,D,J){var q=Y.transform;return{u_matrix:ml(Y,D,J),u_ratio:1/As(D,1,q.zoom),u_device_pixel_ratio:i.browser.devicePixelRatio,u_units_to_pixels:[1/q.pixelsToGLUnits[0],1/q.pixelsToGLUnits[1]]}},Ss=function(Y,D,J,q){return i.extend(Xo(Y,D,J),{u_image:0,u_image_height:q})},as=function(Y,D,J,q){var K=Y.transform,de=Ho(D,K);return{u_matrix:ml(Y,D,J),u_texsize:D.imageAtlasTexture.size,u_ratio:1/As(D,1,K.zoom),u_device_pixel_ratio:i.browser.devicePixelRatio,u_image:0,u_scale:[de,q.fromScale,q.toScale],u_fade:q.t,u_units_to_pixels:[1/K.pixelsToGLUnits[0],1/K.pixelsToGLUnits[1]]}},ws=function(Y,D,J,q,K){var de=Y.transform,ne=Y.lineAtlas,we=Ho(D,de),Ue=J.layout.get("line-cap")==="round",ft=ne.getDash(q.from,Ue),Xt=ne.getDash(q.to,Ue),hr=ft.width*K.fromScale,qt=Xt.width*K.toScale;return i.extend(Xo(Y,D,J),{u_patternscale_a:[we/hr,-ft.height/2],u_patternscale_b:[we/qt,-Xt.height/2],u_sdfgamma:ne.width/(Math.min(hr,qt)*256*i.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:ft.y,u_tex_y_b:Xt.y,u_mix:K.t})};function Ho(Y,D){return 1/As(Y,1,D.tileZoom)}function ml(Y,D,J){return Y.translatePosMatrix(D.tileID.posMatrix,D,J.paint.get("line-translate"),J.paint.get("line-translate-anchor"))}var Ws=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_tl_parent:new i.Uniform2f(Y,D.u_tl_parent),u_scale_parent:new i.Uniform1f(Y,D.u_scale_parent),u_buffer_scale:new i.Uniform1f(Y,D.u_buffer_scale),u_fade_t:new i.Uniform1f(Y,D.u_fade_t),u_opacity:new i.Uniform1f(Y,D.u_opacity),u_image0:new i.Uniform1i(Y,D.u_image0),u_image1:new i.Uniform1i(Y,D.u_image1),u_brightness_low:new i.Uniform1f(Y,D.u_brightness_low),u_brightness_high:new i.Uniform1f(Y,D.u_brightness_high),u_saturation_factor:new i.Uniform1f(Y,D.u_saturation_factor),u_contrast_factor:new i.Uniform1f(Y,D.u_contrast_factor),u_spin_weights:new i.Uniform3f(Y,D.u_spin_weights)}},Ls=function(Y,D,J,q,K){return{u_matrix:Y,u_tl_parent:D,u_scale_parent:J,u_buffer_scale:1,u_fade_t:q.mix,u_opacity:q.opacity*K.paint.get("raster-opacity"),u_image0:0,u_image1:1,u_brightness_low:K.paint.get("raster-brightness-min"),u_brightness_high:K.paint.get("raster-brightness-max"),u_saturation_factor:ys(K.paint.get("raster-saturation")),u_contrast_factor:no(K.paint.get("raster-contrast")),u_spin_weights:va(K.paint.get("raster-hue-rotate"))}};function va(Y){Y*=Math.PI/180;var D=Math.sin(Y),J=Math.cos(Y);return[(2*J+1)/3,(-Math.sqrt(3)*D-J+1)/3,(Math.sqrt(3)*D-J+1)/3]}function no(Y){return Y>0?1/(1-Y):1+Y}function ys(Y){return Y>0?1-1/(1.001-Y):-Y}var rs=function(Y,D){return{u_is_size_zoom_constant:new i.Uniform1i(Y,D.u_is_size_zoom_constant),u_is_size_feature_constant:new i.Uniform1i(Y,D.u_is_size_feature_constant),u_size_t:new i.Uniform1f(Y,D.u_size_t),u_size:new i.Uniform1f(Y,D.u_size),u_camera_to_center_distance:new i.Uniform1f(Y,D.u_camera_to_center_distance),u_pitch:new i.Uniform1f(Y,D.u_pitch),u_rotate_symbol:new i.Uniform1i(Y,D.u_rotate_symbol),u_aspect_ratio:new i.Uniform1f(Y,D.u_aspect_ratio),u_fade_change:new i.Uniform1f(Y,D.u_fade_change),u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_label_plane_matrix:new i.UniformMatrix4f(Y,D.u_label_plane_matrix),u_coord_matrix:new i.UniformMatrix4f(Y,D.u_coord_matrix),u_is_text:new i.Uniform1i(Y,D.u_is_text),u_pitch_with_map:new i.Uniform1i(Y,D.u_pitch_with_map),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_texture:new i.Uniform1i(Y,D.u_texture)}},$l=function(Y,D){return{u_is_size_zoom_constant:new i.Uniform1i(Y,D.u_is_size_zoom_constant),u_is_size_feature_constant:new i.Uniform1i(Y,D.u_is_size_feature_constant),u_size_t:new i.Uniform1f(Y,D.u_size_t),u_size:new i.Uniform1f(Y,D.u_size),u_camera_to_center_distance:new i.Uniform1f(Y,D.u_camera_to_center_distance),u_pitch:new i.Uniform1f(Y,D.u_pitch),u_rotate_symbol:new i.Uniform1i(Y,D.u_rotate_symbol),u_aspect_ratio:new i.Uniform1f(Y,D.u_aspect_ratio),u_fade_change:new i.Uniform1f(Y,D.u_fade_change),u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_label_plane_matrix:new i.UniformMatrix4f(Y,D.u_label_plane_matrix),u_coord_matrix:new i.UniformMatrix4f(Y,D.u_coord_matrix),u_is_text:new i.Uniform1i(Y,D.u_is_text),u_pitch_with_map:new i.Uniform1i(Y,D.u_pitch_with_map),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_texture:new i.Uniform1i(Y,D.u_texture),u_gamma_scale:new i.Uniform1f(Y,D.u_gamma_scale),u_device_pixel_ratio:new i.Uniform1f(Y,D.u_device_pixel_ratio),u_is_halo:new i.Uniform1i(Y,D.u_is_halo)}},Cu=function(Y,D){return{u_is_size_zoom_constant:new i.Uniform1i(Y,D.u_is_size_zoom_constant),u_is_size_feature_constant:new i.Uniform1i(Y,D.u_is_size_feature_constant),u_size_t:new i.Uniform1f(Y,D.u_size_t),u_size:new i.Uniform1f(Y,D.u_size),u_camera_to_center_distance:new i.Uniform1f(Y,D.u_camera_to_center_distance),u_pitch:new i.Uniform1f(Y,D.u_pitch),u_rotate_symbol:new i.Uniform1i(Y,D.u_rotate_symbol),u_aspect_ratio:new i.Uniform1f(Y,D.u_aspect_ratio),u_fade_change:new i.Uniform1f(Y,D.u_fade_change),u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_label_plane_matrix:new i.UniformMatrix4f(Y,D.u_label_plane_matrix),u_coord_matrix:new i.UniformMatrix4f(Y,D.u_coord_matrix),u_is_text:new i.Uniform1i(Y,D.u_is_text),u_pitch_with_map:new i.Uniform1i(Y,D.u_pitch_with_map),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_texsize_icon:new i.Uniform2f(Y,D.u_texsize_icon),u_texture:new i.Uniform1i(Y,D.u_texture),u_texture_icon:new i.Uniform1i(Y,D.u_texture_icon),u_gamma_scale:new i.Uniform1f(Y,D.u_gamma_scale),u_device_pixel_ratio:new i.Uniform1f(Y,D.u_device_pixel_ratio),u_is_halo:new i.Uniform1i(Y,D.u_is_halo)}},Yu=function(Y,D,J,q,K,de,ne,we,Ue,ft){var Xt=K.transform;return{u_is_size_zoom_constant:+(Y==="constant"||Y==="source"),u_is_size_feature_constant:+(Y==="constant"||Y==="camera"),u_size_t:D?D.uSizeT:0,u_size:D?D.uSize:0,u_camera_to_center_distance:Xt.cameraToCenterDistance,u_pitch:Xt.pitch/360*2*Math.PI,u_rotate_symbol:+J,u_aspect_ratio:Xt.width/Xt.height,u_fade_change:K.options.fadeDuration?K.symbolFadeChange:1,u_matrix:de,u_label_plane_matrix:ne,u_coord_matrix:we,u_is_text:+Ue,u_pitch_with_map:+q,u_texsize:ft,u_texture:0}},Nc=function(Y,D,J,q,K,de,ne,we,Ue,ft,Xt){var hr=K.transform;return i.extend(Yu(Y,D,J,q,K,de,ne,we,Ue,ft),{u_gamma_scale:q?Math.cos(hr._pitch)*hr.cameraToCenterDistance:1,u_device_pixel_ratio:i.browser.devicePixelRatio,u_is_halo:+Xt})},pu=function(Y,D,J,q,K,de,ne,we,Ue,ft){return i.extend(Nc(Y,D,J,q,K,de,ne,we,!0,Ue,!0),{u_texsize_icon:ft,u_texture_icon:1})},Uc=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_opacity:new i.Uniform1f(Y,D.u_opacity),u_color:new i.UniformColor(Y,D.u_color)}},xu=function(Y,D){return{u_matrix:new i.UniformMatrix4f(Y,D.u_matrix),u_opacity:new i.Uniform1f(Y,D.u_opacity),u_image:new i.Uniform1i(Y,D.u_image),u_pattern_tl_a:new i.Uniform2f(Y,D.u_pattern_tl_a),u_pattern_br_a:new i.Uniform2f(Y,D.u_pattern_br_a),u_pattern_tl_b:new i.Uniform2f(Y,D.u_pattern_tl_b),u_pattern_br_b:new i.Uniform2f(Y,D.u_pattern_br_b),u_texsize:new i.Uniform2f(Y,D.u_texsize),u_mix:new i.Uniform1f(Y,D.u_mix),u_pattern_size_a:new i.Uniform2f(Y,D.u_pattern_size_a),u_pattern_size_b:new i.Uniform2f(Y,D.u_pattern_size_b),u_scale_a:new i.Uniform1f(Y,D.u_scale_a),u_scale_b:new i.Uniform1f(Y,D.u_scale_b),u_pixel_coord_upper:new i.Uniform2f(Y,D.u_pixel_coord_upper),u_pixel_coord_lower:new i.Uniform2f(Y,D.u_pixel_coord_lower),u_tile_units_to_pixels:new i.Uniform1f(Y,D.u_tile_units_to_pixels)}},Ac=function(Y,D,J){return{u_matrix:Y,u_opacity:D,u_color:J}},Ua=function(Y,D,J,q,K,de){return i.extend(uf(q,de,J,K),{u_matrix:Y,u_opacity:D})},oo={fillExtrusion:Xf,fillExtrusionPattern:Wl,fill:Oc,fillPattern:Tc,fillOutline:wl,fillOutlinePattern:vu,circle:At,collisionBox:Cr,collisionCircle:Ar,debug:Xi,clippingMask:wn,heatmap:Yi,heatmapTexture:Qi,hillshade:$n,hillshadePrepare:Ca,line:Yn,lineGradient:Dn,linePattern:Ka,lineSDF:bo,raster:Ws,symbolIcon:rs,symbolSDF:$l,symbolTextAndIcon:Cu,background:Uc,backgroundPattern:xu},Vc;function hc(Y,D,J,q,K,de,ne){for(var we=Y.context,Ue=we.gl,ft=Y.useProgram("collisionBox"),Xt=[],hr=0,qt=0,Ve=0;Ve0){var Dt=i.create(),yt=Ot;i.mul(Dt,Ct.placementInvProjMatrix,Y.transform.glCoordMatrix),i.mul(Dt,Dt,Ct.placementViewportMatrix),Xt.push({circleArray:Bt,circleOffset:qt,transform:yt,invTransform:Dt}),hr+=Bt.length/4,qt=hr}Rt&&ft.draw(we,Ue.LINES,wi.disabled,Fn.disabled,Y.colorModeForRenderPass(),Er.disabled,Kr(Ot,Y.transform,at),J.id,Rt.layoutVertexBuffer,Rt.indexBuffer,Rt.segments,null,Y.transform.zoom,null,null,Rt.collisionVertexBuffer)}}if(!(!ne||!Xt.length)){var Pt=Y.useProgram("collisionCircle"),ht=new i.StructArrayLayout2f1f2i16;ht.resize(hr*4),ht._trim();for(var ur=0,br=0,Ur=Xt;br=0&&(Qe[Ct.associatedIconIndex]={shiftedAnchor:Ti,angle:gn})}}if(Xt){Ve.clear();for(var Ci=Y.icon.placedSymbolArray,Bi=0;Bi0){var ne=i.browser.now(),we=(ne-Y.timeAdded)/de,Ue=D?(ne-D.timeAdded)/de:-1,ft=J.getSource(),Xt=K.coveringZoomLevel({tileSize:ft.tileSize,roundZoom:ft.roundZoom}),hr=!D||Math.abs(D.tileID.overscaledZ-Xt)>Math.abs(Y.tileID.overscaledZ-Xt),qt=hr&&Y.refreshedUponExpiration?1:i.clamp(hr?we:1-Ue,0,1);return Y.refreshedUponExpiration&&we>=1&&(Y.refreshedUponExpiration=!1),D?{opacity:1,mix:1-qt}:{opacity:qt,mix:0}}else return{opacity:1,mix:0}}function tr(Y,D,J){var q=J.paint.get("background-color"),K=J.paint.get("background-opacity");if(K!==0){var de=Y.context,ne=de.gl,we=Y.transform,Ue=we.tileSize,ft=J.paint.get("background-pattern");if(!Y.isPatternMissing(ft)){var Xt=!ft&&q.a===1&&K===1&&Y.opaquePassEnabledForLayer()?"opaque":"translucent";if(Y.renderPass===Xt){var hr=Fn.disabled,qt=Y.depthModeForSublayer(0,Xt==="opaque"?wi.ReadWrite:wi.ReadOnly),Ve=Y.colorModeForRenderPass(),Qe=Y.useProgram(ft?"backgroundPattern":"background"),at=we.coveringTiles({tileSize:Ue});ft&&(de.activeTexture.set(ne.TEXTURE0),Y.imageManager.bind(Y.context));for(var Ct=J.getCrossfadeParameters(),Ot=0,Rt=at;Ot "+J.overscaledZ);var Ot=Ct+" "+Ve+"kb";$a(Y,Ot),ne.draw(q,K.TRIANGLES,we,Ue,wt.alphaBlended,Er.disabled,dn(de,i.Color.transparent,at),Xt,Y.debugBuffer,Y.quadTriangleIndexBuffer,Y.debugSegments)}function $a(Y,D){Y.initDebugOverlayCanvas();var J=Y.debugOverlayCanvas,q=Y.context.gl,K=Y.debugOverlayCanvas.getContext("2d");K.clearRect(0,0,J.width,J.height),K.shadowColor="white",K.shadowBlur=2,K.lineWidth=1.5,K.strokeStyle="white",K.textBaseline="top",K.font="bold 36px Open Sans, sans-serif",K.fillText(D,5,5),K.strokeText(D,5,5),Y.debugOverlayTexture.update(J),Y.debugOverlayTexture.bind(q.LINEAR,q.CLAMP_TO_EDGE)}function Co(Y,D,J){var q=Y.context,K=J.implementation;if(Y.renderPass==="offscreen"){var de=K.prerender;de&&(Y.setCustomLayerDefaults(),q.setColorMode(Y.colorModeForRenderPass()),de.call(K,q.gl,Y.transform.customLayerMatrix()),q.setDirty(),Y.setBaseState())}else if(Y.renderPass==="translucent"){Y.setCustomLayerDefaults(),q.setColorMode(Y.colorModeForRenderPass()),q.setStencilMode(Fn.disabled);var ne=K.renderingMode==="3d"?new wi(Y.context.gl.LEQUAL,wi.ReadWrite,Y.depthRangeFor3D):Y.depthModeForSublayer(0,wi.ReadOnly);q.setDepthMode(ne),K.render(q.gl,Y.transform.customLayerMatrix()),q.setDirty(),Y.setBaseState(),q.bindFramebuffer.set(null)}}var Qa={symbol:w,circle:ot,heatmap:Tt,line:Ir,fill:ve,"fill-extrusion":De,hillshade:et,raster:Ft,background:tr,debug:Ta,custom:Co},mo=function(D,J){this.context=new Xr(D),this.transform=J,this._tileTextures={},this.setup(),this.numSublayers=ri.maxUnderzooming+ri.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Uf,this.gpuTimers={}};mo.prototype.resize=function(D,J){if(this.width=D*i.browser.devicePixelRatio,this.height=J*i.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var q=0,K=this.style._order;q256&&this.clearStencil(),q.setColorMode(wt.disabled),q.setDepthMode(wi.disabled);var de=this.useProgram("clippingMask");this._tileClippingMaskIDs={};for(var ne=0,we=J;ne256&&this.clearStencil();var D=this.nextStencilID++,J=this.context.gl;return new Fn({func:J.NOTEQUAL,mask:255},D,255,J.KEEP,J.KEEP,J.REPLACE)},mo.prototype.stencilModeForClipping=function(D){var J=this.context.gl;return new Fn({func:J.EQUAL,mask:255},this._tileClippingMaskIDs[D.key],0,J.KEEP,J.KEEP,J.REPLACE)},mo.prototype.stencilConfigForOverlap=function(D){var J,q=this.context.gl,K=D.sort(function(ft,Xt){return Xt.overscaledZ-ft.overscaledZ}),de=K[K.length-1].overscaledZ,ne=K[0].overscaledZ-de+1;if(ne>1){this.currentStencilSource=void 0,this.nextStencilID+ne>256&&this.clearStencil();for(var we={},Ue=0;Ue=0;this.currentLayer--){var Dt=this.style._layers[K[this.currentLayer]],yt=de[Dt.source],Pt=Ue[Dt.source];this._renderTileClippingMasks(Dt,Pt),this.renderLayer(this,yt,Dt,Pt)}for(this.renderPass="translucent",this.currentLayer=0;this.currentLayer0?J.pop():null},mo.prototype.isPatternMissing=function(D){if(!D)return!1;if(!D.from||!D.to)return!0;var J=this.imageManager.getPattern(D.from.toString()),q=this.imageManager.getPattern(D.to.toString());return!J||!q},mo.prototype.useProgram=function(D,J){this.cache=this.cache||{};var q=""+D+(J?J.cacheKey:"")+(this._showOverdrawInspector?"/overdraw":"");return this.cache[q]||(this.cache[q]=new Rf(this.context,D,wf[D],J,oo[D],this._showOverdrawInspector)),this.cache[q]},mo.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},mo.prototype.setBaseState=function(){var D=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(D.FUNC_ADD)},mo.prototype.initDebugOverlayCanvas=function(){if(this.debugOverlayCanvas==null){this.debugOverlayCanvas=i.window.document.createElement("canvas"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var D=this.context.gl;this.debugOverlayTexture=new i.Texture(this.context,this.debugOverlayCanvas,D.RGBA)}},mo.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var Bo=function(D,J){this.points=D,this.planes=J};Bo.fromInvProjectionMatrix=function(D,J,q){var K=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]],de=Math.pow(2,q),ne=K.map(function(ft){return i.transformMat4([],ft,D)}).map(function(ft){return i.scale$1([],ft,1/ft[3]/J*de)}),we=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]],Ue=we.map(function(ft){var Xt=i.sub([],ne[ft[0]],ne[ft[1]]),hr=i.sub([],ne[ft[2]],ne[ft[1]]),qt=i.normalize([],i.cross([],Xt,hr)),Ve=-i.dot(qt,ne[ft[1]]);return qt.concat(Ve)});return new Bo(ne,Ue)};var Ps=function(D,J){this.min=D,this.max=J,this.center=i.scale$2([],i.add([],this.min,this.max),.5)};Ps.prototype.quadrant=function(D){for(var J=[D%2===0,D<2],q=i.clone$2(this.min),K=i.clone$2(this.max),de=0;de=0;if(ne===0)return 0;ne!==J.length&&(q=!1)}if(q)return 2;for(var Ue=0;Ue<3;Ue++){for(var ft=Number.MAX_VALUE,Xt=-Number.MAX_VALUE,hr=0;hrthis.max[Ue]-this.min[Ue])return 0}return 1};var Ts=function(D,J,q,K){if(D===void 0&&(D=0),J===void 0&&(J=0),q===void 0&&(q=0),K===void 0&&(K=0),isNaN(D)||D<0||isNaN(J)||J<0||isNaN(q)||q<0||isNaN(K)||K<0)throw new Error("Invalid value for edge-insets, top, bottom, left and right must all be numbers");this.top=D,this.bottom=J,this.left=q,this.right=K};Ts.prototype.interpolate=function(D,J,q){return J.top!=null&&D.top!=null&&(this.top=i.number(D.top,J.top,q)),J.bottom!=null&&D.bottom!=null&&(this.bottom=i.number(D.bottom,J.bottom,q)),J.left!=null&&D.left!=null&&(this.left=i.number(D.left,J.left,q)),J.right!=null&&D.right!=null&&(this.right=i.number(D.right,J.right,q)),this},Ts.prototype.getCenter=function(D,J){var q=i.clamp((this.left+D-this.right)/2,0,D),K=i.clamp((this.top+J-this.bottom)/2,0,J);return new i.Point(q,K)},Ts.prototype.equals=function(D){return this.top===D.top&&this.bottom===D.bottom&&this.left===D.left&&this.right===D.right},Ts.prototype.clone=function(){return new Ts(this.top,this.bottom,this.left,this.right)},Ts.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var wo=function(D,J,q,K,de){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=de===void 0?!0:de,this._minZoom=D||0,this._maxZoom=J||22,this._minPitch=q==null?0:q,this._maxPitch=K==null?60:K,this.setMaxBounds(),this.width=0,this.height=0,this._center=new i.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new Ts,this._posMatrixCache={},this._alignedPosMatrixCache={}},To={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};wo.prototype.clone=function(){var D=new wo(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return D.tileSize=this.tileSize,D.latRange=this.latRange,D.width=this.width,D.height=this.height,D._center=this._center,D.zoom=this.zoom,D.angle=this.angle,D._fov=this._fov,D._pitch=this._pitch,D._unmodified=this._unmodified,D._edgeInsets=this._edgeInsets.clone(),D._calcMatrices(),D},To.minZoom.get=function(){return this._minZoom},To.minZoom.set=function(Y){this._minZoom!==Y&&(this._minZoom=Y,this.zoom=Math.max(this.zoom,Y))},To.maxZoom.get=function(){return this._maxZoom},To.maxZoom.set=function(Y){this._maxZoom!==Y&&(this._maxZoom=Y,this.zoom=Math.min(this.zoom,Y))},To.minPitch.get=function(){return this._minPitch},To.minPitch.set=function(Y){this._minPitch!==Y&&(this._minPitch=Y,this.pitch=Math.max(this.pitch,Y))},To.maxPitch.get=function(){return this._maxPitch},To.maxPitch.set=function(Y){this._maxPitch!==Y&&(this._maxPitch=Y,this.pitch=Math.min(this.pitch,Y))},To.renderWorldCopies.get=function(){return this._renderWorldCopies},To.renderWorldCopies.set=function(Y){Y===void 0?Y=!0:Y===null&&(Y=!1),this._renderWorldCopies=Y},To.worldSize.get=function(){return this.tileSize*this.scale},To.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},To.size.get=function(){return new i.Point(this.width,this.height)},To.bearing.get=function(){return-this.angle/Math.PI*180},To.bearing.set=function(Y){var D=-i.wrap(Y,-180,180)*Math.PI/180;this.angle!==D&&(this._unmodified=!1,this.angle=D,this._calcMatrices(),this.rotationMatrix=i.create$2(),i.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},To.pitch.get=function(){return this._pitch/Math.PI*180},To.pitch.set=function(Y){var D=i.clamp(Y,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==D&&(this._unmodified=!1,this._pitch=D,this._calcMatrices())},To.fov.get=function(){return this._fov/Math.PI*180},To.fov.set=function(Y){Y=Math.max(.01,Math.min(60,Y)),this._fov!==Y&&(this._unmodified=!1,this._fov=Y/180*Math.PI,this._calcMatrices())},To.zoom.get=function(){return this._zoom},To.zoom.set=function(Y){var D=Math.min(Math.max(Y,this.minZoom),this.maxZoom);this._zoom!==D&&(this._unmodified=!1,this._zoom=D,this.scale=this.zoomScale(D),this.tileZoom=Math.floor(D),this.zoomFraction=D-this.tileZoom,this._constrain(),this._calcMatrices())},To.center.get=function(){return this._center},To.center.set=function(Y){Y.lat===this._center.lat&&Y.lng===this._center.lng||(this._unmodified=!1,this._center=Y,this._constrain(),this._calcMatrices())},To.padding.get=function(){return this._edgeInsets.toJSON()},To.padding.set=function(Y){this._edgeInsets.equals(Y)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,Y,1),this._calcMatrices())},To.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},wo.prototype.isPaddingEqual=function(D){return this._edgeInsets.equals(D)},wo.prototype.interpolatePadding=function(D,J,q){this._unmodified=!1,this._edgeInsets.interpolate(D,J,q),this._constrain(),this._calcMatrices()},wo.prototype.coveringZoomLevel=function(D){var J=(D.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/D.tileSize));return Math.max(0,J)},wo.prototype.getVisibleUnwrappedCoordinates=function(D){var J=[new i.UnwrappedTileID(0,D)];if(this._renderWorldCopies)for(var q=this.pointCoordinate(new i.Point(0,0)),K=this.pointCoordinate(new i.Point(this.width,0)),de=this.pointCoordinate(new i.Point(this.width,this.height)),ne=this.pointCoordinate(new i.Point(0,this.height)),we=Math.floor(Math.min(q.x,K.x,de.x,ne.x)),Ue=Math.floor(Math.max(q.x,K.x,de.x,ne.x)),ft=1,Xt=we-ft;Xt<=Ue+ft;Xt++)Xt!==0&&J.push(new i.UnwrappedTileID(Xt,D));return J},wo.prototype.coveringTiles=function(D){var J=this.coveringZoomLevel(D),q=J;if(D.minzoom!==void 0&&JD.maxzoom&&(J=D.maxzoom);var K=i.MercatorCoordinate.fromLngLat(this.center),de=Math.pow(2,J),ne=[de*K.x,de*K.y,0],we=Bo.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,J),Ue=D.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(Ue=J);var ft=3,Xt=function(fi){return{aabb:new Ps([fi*de,0,0],[(fi+1)*de,de,0]),zoom:0,x:0,y:0,wrap:fi,fullyVisible:!1}},hr=[],qt=[],Ve=J,Qe=D.reparseOverscaled?q:J;if(this._renderWorldCopies)for(var at=1;at<=3;at++)hr.push(Xt(-at)),hr.push(Xt(at));for(hr.push(Xt(0));hr.length>0;){var Ct=hr.pop(),Ot=Ct.x,Rt=Ct.y,Bt=Ct.fullyVisible;if(!Bt){var Dt=Ct.aabb.intersects(we);if(Dt===0)continue;Bt=Dt===2}var yt=Ct.aabb.distanceX(ne),Pt=Ct.aabb.distanceY(ne),ht=Math.max(Math.abs(yt),Math.abs(Pt)),ur=ft+(1<ur&&Ct.zoom>=Ue){qt.push({tileID:new i.OverscaledTileID(Ct.zoom===Ve?Qe:Ct.zoom,Ct.wrap,Ct.zoom,Ot,Rt),distanceSq:i.sqrLen([ne[0]-.5-Ot,ne[1]-.5-Rt])});continue}for(var br=0;br<4;br++){var Ur=(Ot<<1)+br%2,Di=(Rt<<1)+(br>>1);hr.push({aabb:Ct.aabb.quadrant(br),zoom:Ct.zoom+1,x:Ur,y:Di,wrap:Ct.wrap,fullyVisible:Bt})}}return qt.sort(function(fi,Ti){return fi.distanceSq-Ti.distanceSq}).map(function(fi){return fi.tileID})},wo.prototype.resize=function(D,J){this.width=D,this.height=J,this.pixelsToGLUnits=[2/D,-2/J],this._constrain(),this._calcMatrices()},To.unmodified.get=function(){return this._unmodified},wo.prototype.zoomScale=function(D){return Math.pow(2,D)},wo.prototype.scaleZoom=function(D){return Math.log(D)/Math.LN2},wo.prototype.project=function(D){var J=i.clamp(D.lat,-this.maxValidLatitude,this.maxValidLatitude);return new i.Point(i.mercatorXfromLng(D.lng)*this.worldSize,i.mercatorYfromLat(J)*this.worldSize)},wo.prototype.unproject=function(D){return new i.MercatorCoordinate(D.x/this.worldSize,D.y/this.worldSize).toLngLat()},To.point.get=function(){return this.project(this.center)},wo.prototype.setLocationAtPoint=function(D,J){var q=this.pointCoordinate(J),K=this.pointCoordinate(this.centerPoint),de=this.locationCoordinate(D),ne=new i.MercatorCoordinate(de.x-(q.x-K.x),de.y-(q.y-K.y));this.center=this.coordinateLocation(ne),this._renderWorldCopies&&(this.center=this.center.wrap())},wo.prototype.locationPoint=function(D){return this.coordinatePoint(this.locationCoordinate(D))},wo.prototype.pointLocation=function(D){return this.coordinateLocation(this.pointCoordinate(D))},wo.prototype.locationCoordinate=function(D){return i.MercatorCoordinate.fromLngLat(D)},wo.prototype.coordinateLocation=function(D){return D.toLngLat()},wo.prototype.pointCoordinate=function(D){var J=0,q=[D.x,D.y,0,1],K=[D.x,D.y,1,1];i.transformMat4(q,q,this.pixelMatrixInverse),i.transformMat4(K,K,this.pixelMatrixInverse);var de=q[3],ne=K[3],we=q[0]/de,Ue=K[0]/ne,ft=q[1]/de,Xt=K[1]/ne,hr=q[2]/de,qt=K[2]/ne,Ve=hr===qt?0:(J-hr)/(qt-hr);return new i.MercatorCoordinate(i.number(we,Ue,Ve)/this.worldSize,i.number(ft,Xt,Ve)/this.worldSize)},wo.prototype.coordinatePoint=function(D){var J=[D.x*this.worldSize,D.y*this.worldSize,0,1];return i.transformMat4(J,J,this.pixelMatrix),new i.Point(J[0]/J[3],J[1]/J[3])},wo.prototype.getBounds=function(){return new i.LngLatBounds().extend(this.pointLocation(new i.Point(0,0))).extend(this.pointLocation(new i.Point(this.width,0))).extend(this.pointLocation(new i.Point(this.width,this.height))).extend(this.pointLocation(new i.Point(0,this.height)))},wo.prototype.getMaxBounds=function(){return!this.latRange||this.latRange.length!==2||!this.lngRange||this.lngRange.length!==2?null:new i.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]])},wo.prototype.setMaxBounds=function(D){D?(this.lngRange=[D.getWest(),D.getEast()],this.latRange=[D.getSouth(),D.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},wo.prototype.calculatePosMatrix=function(D,J){J===void 0&&(J=!1);var q=D.key,K=J?this._alignedPosMatrixCache:this._posMatrixCache;if(K[q])return K[q];var de=D.canonical,ne=this.worldSize/this.zoomScale(de.z),we=de.x+Math.pow(2,de.z)*D.wrap,Ue=i.identity(new Float64Array(16));return i.translate(Ue,Ue,[we*ne,de.y*ne,0]),i.scale(Ue,Ue,[ne/i.EXTENT,ne/i.EXTENT,1]),i.multiply(Ue,J?this.alignedProjMatrix:this.projMatrix,Ue),K[q]=new Float32Array(Ue),K[q]},wo.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},wo.prototype._constrain=function(){if(!(!this.center||!this.width||!this.height||this._constraining)){this._constraining=!0;var D=-90,J=90,q=-180,K=180,de,ne,we,Ue,ft=this.size,Xt=this._unmodified;if(this.latRange){var hr=this.latRange;D=i.mercatorYfromLat(hr[1])*this.worldSize,J=i.mercatorYfromLat(hr[0])*this.worldSize,de=J-DJ&&(Ue=J-Ct)}if(this.lngRange){var Ot=Ve.x,Rt=ft.x/2;Ot-RtK&&(we=K-Rt)}(we!==void 0||Ue!==void 0)&&(this.center=this.unproject(new i.Point(we!==void 0?we:Ve.x,Ue!==void 0?Ue:Ve.y))),this._unmodified=Xt,this._constraining=!1}},wo.prototype._calcMatrices=function(){if(this.height){var D=this._fov/2,J=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(D)*this.height;var q=Math.PI/2+this._pitch,K=this._fov*(.5+J.y/this.height),de=Math.sin(K)*this.cameraToCenterDistance/Math.sin(i.clamp(Math.PI-q-K,.01,Math.PI-.01)),ne=this.point,we=ne.x,Ue=ne.y,ft=Math.cos(Math.PI/2-this._pitch)*de+this.cameraToCenterDistance,Xt=ft*1.01,hr=this.height/50,qt=new Float64Array(16);i.perspective(qt,this._fov,this.width/this.height,hr,Xt),qt[8]=-J.x*2/this.width,qt[9]=J.y*2/this.height,i.scale(qt,qt,[1,-1,1]),i.translate(qt,qt,[0,0,-this.cameraToCenterDistance]),i.rotateX(qt,qt,this._pitch),i.rotateZ(qt,qt,this.angle),i.translate(qt,qt,[-we,-Ue,0]),this.mercatorMatrix=i.scale([],qt,[this.worldSize,this.worldSize,this.worldSize]),i.scale(qt,qt,[1,1,i.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=qt,this.invProjMatrix=i.invert([],this.projMatrix);var Ve=this.width%2/2,Qe=this.height%2/2,at=Math.cos(this.angle),Ct=Math.sin(this.angle),Ot=we-Math.round(we)+at*Ve+Ct*Qe,Rt=Ue-Math.round(Ue)+at*Qe+Ct*Ve,Bt=new Float64Array(qt);if(i.translate(Bt,Bt,[Ot>.5?Ot-1:Ot,Rt>.5?Rt-1:Rt,0]),this.alignedProjMatrix=Bt,qt=i.create(),i.scale(qt,qt,[this.width/2,-this.height/2,1]),i.translate(qt,qt,[1,-1,0]),this.labelPlaneMatrix=qt,qt=i.create(),i.scale(qt,qt,[1,-1,1]),i.translate(qt,qt,[-1,-1,0]),i.scale(qt,qt,[2/this.width,2/this.height,1]),this.glCoordMatrix=qt,this.pixelMatrix=i.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),qt=i.invert(new Float64Array(16),this.pixelMatrix),!qt)throw new Error("failed to invert matrix");this.pixelMatrixInverse=qt,this._posMatrixCache={},this._alignedPosMatrixCache={}}},wo.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var D=this.pointCoordinate(new i.Point(0,0)),J=[D.x*this.worldSize,D.y*this.worldSize,0,1],q=i.transformMat4(J,J,this.pixelMatrix);return q[3]/this.cameraToCenterDistance},wo.prototype.getCameraPoint=function(){var D=this._pitch,J=Math.tan(D)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new i.Point(0,J))},wo.prototype.getCameraQueryGeometry=function(D){var J=this.getCameraPoint();if(D.length===1)return[D[0],J];for(var q=J.x,K=J.y,de=J.x,ne=J.y,we=0,Ue=D;we=3&&!D.some(function(q){return isNaN(q)})){var J=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(D[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+D[2],+D[1]],zoom:+D[0],bearing:J,pitch:+(D[4]||0)}),!0}return!1},Ul.prototype._updateHashUnthrottled=function(){var D=i.window.location.href.replace(/(#.+)?$/,this.getHashString());try{i.window.history.replaceState(i.window.history.state,null,D)}catch(J){}};var Lu={linearity:.3,easing:i.bezier(0,0,.3,1)},au=i.extend({deceleration:2500,maxSpeed:1400},Lu),Js=i.extend({deceleration:20,maxSpeed:1400},Lu),Ql=i.extend({deceleration:1e3,maxSpeed:360},Lu),dc=i.extend({deceleration:1e3,maxSpeed:90},Lu),Tl=function(D){this._map=D,this.clear()};Tl.prototype.clear=function(){this._inertiaBuffer=[]},Tl.prototype.record=function(D){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:i.browser.now(),settings:D})},Tl.prototype._drainInertiaBuffer=function(){for(var D=this._inertiaBuffer,J=i.browser.now(),q=160;D.length>0&&J-D[0].time>q;)D.shift()},Tl.prototype._onMoveEnd=function(D){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var J={zoom:0,bearing:0,pitch:0,pan:new i.Point(0,0),pinchAround:void 0,around:void 0},q=0,K=this._inertiaBuffer;q=this._clickTolerance||this._map.fire(new se(D.type,this._map,D))},He.prototype.dblclick=function(D){return this._firePreventable(new se(D.type,this._map,D))},He.prototype.mouseover=function(D){this._map.fire(new se(D.type,this._map,D))},He.prototype.mouseout=function(D){this._map.fire(new se(D.type,this._map,D))},He.prototype.touchstart=function(D){return this._firePreventable(new Te(D.type,this._map,D))},He.prototype.touchmove=function(D){this._map.fire(new Te(D.type,this._map,D))},He.prototype.touchend=function(D){this._map.fire(new Te(D.type,this._map,D))},He.prototype.touchcancel=function(D){this._map.fire(new Te(D.type,this._map,D))},He.prototype._firePreventable=function(D){if(this._map.fire(D),D.defaultPrevented)return{}},He.prototype.isEnabled=function(){return!0},He.prototype.isActive=function(){return!1},He.prototype.enable=function(){},He.prototype.disable=function(){};var Ye=function(D){this._map=D};Ye.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},Ye.prototype.mousemove=function(D){this._map.fire(new se(D.type,this._map,D))},Ye.prototype.mousedown=function(){this._delayContextMenu=!0},Ye.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new se("contextmenu",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},Ye.prototype.contextmenu=function(D){this._delayContextMenu?this._contextMenuEvent=D:this._map.fire(new se(D.type,this._map,D)),this._map.listens("contextmenu")&&D.preventDefault()},Ye.prototype.isEnabled=function(){return!0},Ye.prototype.isActive=function(){return!1},Ye.prototype.enable=function(){},Ye.prototype.disable=function(){};var kt=function(D,J){this._map=D,this._el=D.getCanvasContainer(),this._container=D.getContainer(),this._clickTolerance=J.clickTolerance||1};kt.prototype.isEnabled=function(){return!!this._enabled},kt.prototype.isActive=function(){return!!this._active},kt.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},kt.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},kt.prototype.mousedown=function(D,J){this.isEnabled()&&D.shiftKey&&D.button===0&&(o.disableDrag(),this._startPos=this._lastPos=J,this._active=!0)},kt.prototype.mousemoveWindow=function(D,J){if(this._active){var q=J;if(!(this._lastPos.equals(q)||!this._box&&q.dist(this._startPos)this.numTouches)&&(this.aborted=!0),!this.aborted&&(this.startTime===void 0&&(this.startTime=D.timeStamp),q.length===this.numTouches&&(this.centroid=jt(J),this.touches=nt(q,J)))},qr.prototype.touchmove=function(D,J,q){if(!(this.aborted||!this.centroid)){var K=nt(q,J);for(var de in this.touches){var ne=this.touches[de],we=K[de];(!we||we.dist(ne)>Hr)&&(this.aborted=!0)}}},qr.prototype.touchend=function(D,J,q){if((!this.centroid||D.timeStamp-this.startTime>yr)&&(this.aborted=!0),q.length===0){var K=!this.aborted&&this.centroid;if(this.reset(),K)return K}};var _i=function(D){this.singleTap=new qr(D),this.numTaps=D.numTaps,this.reset()};_i.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},_i.prototype.touchstart=function(D,J,q){this.singleTap.touchstart(D,J,q)},_i.prototype.touchmove=function(D,J,q){this.singleTap.touchmove(D,J,q)},_i.prototype.touchend=function(D,J,q){var K=this.singleTap.touchend(D,J,q);if(K){var de=D.timeStamp-this.lastTime0&&(this._active=!0);var K=nt(q,J),de=new i.Point(0,0),ne=new i.Point(0,0),we=0;for(var Ue in K){var ft=K[Ue],Xt=this._touches[Ue];Xt&&(de._add(ft),ne._add(ft.sub(Xt)),we++,K[Ue]=ft)}if(this._touches=K,!(weMath.abs(Y.x)}var Gn=100,ja=function(Y){function D(){Y.apply(this,arguments)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.reset=function(){Y.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},D.prototype._start=function(q){this._lastPoints=q,Xs(q[0].sub(q[1]))&&(this._valid=!1)},D.prototype._move=function(q,K,de){var ne=q[0].sub(this._lastPoints[0]),we=q[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(ne,we,de.timeStamp),!!this._valid){this._lastPoints=q,this._active=!0;var Ue=(ne.y+we.y)/2,ft=-.5;return{pitchDelta:Ue*ft}}},D.prototype.gestureBeginsVertically=function(q,K,de){if(this._valid!==void 0)return this._valid;var ne=2,we=q.mag()>=ne,Ue=K.mag()>=ne;if(!(!we&&!Ue)){if(!we||!Ue)return this._firstMove===void 0&&(this._firstMove=de),de-this._firstMove0==K.y>0;return Xs(q)&&Xs(K)&&ft}},D}(ia),Fo={panStep:100,bearingStep:15,pitchStep:10},Uo=function(){var D=Fo;this._panStep=D.panStep,this._bearingStep=D.bearingStep,this._pitchStep=D.pitchStep,this._rotationDisabled=!1};Uo.prototype.reset=function(){this._active=!1},Uo.prototype.keydown=function(D){var J=this;if(!(D.altKey||D.ctrlKey||D.metaKey)){var q=0,K=0,de=0,ne=0,we=0;switch(D.keyCode){case 61:case 107:case 171:case 187:q=1;break;case 189:case 109:case 173:q=-1;break;case 37:D.shiftKey?K=-1:(D.preventDefault(),ne=-1);break;case 39:D.shiftKey?K=1:(D.preventDefault(),ne=1);break;case 38:D.shiftKey?de=1:(D.preventDefault(),we=-1);break;case 40:D.shiftKey?de=-1:(D.preventDefault(),we=1);break;default:return}return this._rotationDisabled&&(K=0,de=0),{cameraAnimation:function(Ue){var ft=Ue.getZoom();Ue.easeTo({duration:300,easeId:"keyboardHandler",easing:$s,zoom:q?Math.round(ft)+q*(D.shiftKey?2:1):ft,bearing:Ue.getBearing()+K*J._bearingStep,pitch:Ue.getPitch()+de*J._pitchStep,offset:[-ne*J._panStep,-we*J._panStep],center:Ue.getCenter()},{originalEvent:D})}}}},Uo.prototype.enable=function(){this._enabled=!0},Uo.prototype.disable=function(){this._enabled=!1,this.reset()},Uo.prototype.isEnabled=function(){return this._enabled},Uo.prototype.isActive=function(){return this._active},Uo.prototype.disableRotation=function(){this._rotationDisabled=!0},Uo.prototype.enableRotation=function(){this._rotationDisabled=!1};function $s(Y){return Y*(2-Y)}var Sl=4.000244140625,bu=1/100,dl=1/450,Sc=2,Me=function(D,J){this._map=D,this._el=D.getCanvasContainer(),this._handler=J,this._delta=0,this._defaultZoomRate=bu,this._wheelZoomRate=dl,i.bindAll(["_onTimeout"],this)};Me.prototype.setZoomRate=function(D){this._defaultZoomRate=D},Me.prototype.setWheelZoomRate=function(D){this._wheelZoomRate=D},Me.prototype.isEnabled=function(){return!!this._enabled},Me.prototype.isActive=function(){return!!this._active||this._finishTimeout!==void 0},Me.prototype.isZooming=function(){return!!this._zooming},Me.prototype.enable=function(D){this.isEnabled()||(this._enabled=!0,this._aroundCenter=D&&D.around==="center")},Me.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},Me.prototype.wheel=function(D){if(this.isEnabled()){var J=D.deltaMode===i.window.WheelEvent.DOM_DELTA_LINE?D.deltaY*40:D.deltaY,q=i.browser.now(),K=q-(this._lastWheelEventTime||0);this._lastWheelEventTime=q,J!==0&&J%Sl===0?this._type="wheel":J!==0&&Math.abs(J)<4?this._type="trackpad":K>400?(this._type=null,this._lastValue=J,this._timeout=setTimeout(this._onTimeout,40,D)):this._type||(this._type=Math.abs(K*J)<200?"trackpad":"wheel",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,J+=this._lastValue)),D.shiftKey&&J&&(J=J/4),this._type&&(this._lastWheelEvent=D,this._delta-=J,this._active||this._start(D)),D.preventDefault()}},Me.prototype._onTimeout=function(D){this._type="wheel",this._delta-=this._lastValue,this._active||this._start(D)},Me.prototype._start=function(D){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var J=o.mousePos(this._el,D);this._around=i.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(J)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},Me.prototype.renderFrame=function(){var D=this;if(this._frameId&&(this._frameId=null,!!this.isActive())){var J=this._map.transform;if(this._delta!==0){var q=this._type==="wheel"&&Math.abs(this._delta)>Sl?this._wheelZoomRate:this._defaultZoomRate,K=Sc/(1+Math.exp(-Math.abs(this._delta*q)));this._delta<0&&K!==0&&(K=1/K);var de=typeof this._targetZoom=="number"?J.zoomScale(this._targetZoom):J.scale;this._targetZoom=Math.min(J.maxZoom,Math.max(J.minZoom,J.scaleZoom(de*K))),this._type==="wheel"&&(this._startZoom=J.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var ne=typeof this._targetZoom=="number"?this._targetZoom:J.zoom,we=this._startZoom,Ue=this._easing,ft=!1,Xt;if(this._type==="wheel"&&we&&Ue){var hr=Math.min((i.browser.now()-this._lastWheelEventTime)/200,1),qt=Ue(hr);Xt=i.number(we,ne,qt),hr<1?this._frameId||(this._frameId=!0):ft=!0}else Xt=ne,ft=!0;return this._active=!0,ft&&(this._active=!1,this._finishTimeout=setTimeout(function(){D._zooming=!1,D._handler._triggerRenderFrame(),delete D._targetZoom,delete D._finishTimeout},200)),{noInertia:!0,needsRenderFrame:!ft,zoomDelta:Xt-J.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},Me.prototype._smoothOutEasing=function(D){var J=i.ease;if(this._prevEase){var q=this._prevEase,K=(i.browser.now()-q.start)/q.duration,de=q.easing(K+.01)-q.easing(K),ne=.27/Math.sqrt(de*de+1e-4)*.01,we=Math.sqrt(.27*.27-ne*ne);J=i.bezier(ne,we,.25,1)}return this._prevEase={start:i.browser.now(),duration:D,easing:J},J},Me.prototype.reset=function(){this._active=!1};var bt=function(D,J){this._clickZoom=D,this._tapZoom=J};bt.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},bt.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},bt.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},bt.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var zt=function(){this.reset()};zt.prototype.reset=function(){this._active=!1},zt.prototype.dblclick=function(D,J){return D.preventDefault(),{cameraAnimation:function(q){q.easeTo({duration:300,zoom:q.getZoom()+(D.shiftKey?-1:1),around:q.unproject(J)},{originalEvent:D})}}},zt.prototype.enable=function(){this._enabled=!0},zt.prototype.disable=function(){this._enabled=!1,this.reset()},zt.prototype.isEnabled=function(){return this._enabled},zt.prototype.isActive=function(){return this._active};var Rr=function(){this._tap=new _i({numTouches:1,numTaps:1}),this.reset()};Rr.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},Rr.prototype.touchstart=function(D,J,q){this._swipePoint||(this._tapTime&&D.timeStamp-this._tapTime>gr&&this.reset(),this._tapTime?q.length>0&&(this._swipePoint=J[0],this._swipeTouch=q[0].identifier):this._tap.touchstart(D,J,q))},Rr.prototype.touchmove=function(D,J,q){if(!this._tapTime)this._tap.touchmove(D,J,q);else if(this._swipePoint){if(q[0].identifier!==this._swipeTouch)return;var K=J[0],de=K.y-this._swipePoint.y;return this._swipePoint=K,D.preventDefault(),this._active=!0,{zoomDelta:de/128}}},Rr.prototype.touchend=function(D,J,q){if(this._tapTime)this._swipePoint&&q.length===0&&this.reset();else{var K=this._tap.touchend(D,J,q);K&&(this._tapTime=D.timeStamp)}},Rr.prototype.touchcancel=function(){this.reset()},Rr.prototype.enable=function(){this._enabled=!0},Rr.prototype.disable=function(){this._enabled=!1,this.reset()},Rr.prototype.isEnabled=function(){return this._enabled},Rr.prototype.isActive=function(){return this._active};var jr=function(D,J,q){this._el=D,this._mousePan=J,this._touchPan=q};jr.prototype.enable=function(D){this._inertiaOptions=D||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add("mapboxgl-touch-drag-pan")},jr.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove("mapboxgl-touch-drag-pan")},jr.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},jr.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var Nr=function(D,J,q){this._pitchWithRotate=D.pitchWithRotate,this._mouseRotate=J,this._mousePitch=q};Nr.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},Nr.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},Nr.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},Nr.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var Gr=function(D,J,q,K){this._el=D,this._touchZoom=J,this._touchRotate=q,this._tapDragZoom=K,this._rotationDisabled=!1,this._enabled=!0};Gr.prototype.enable=function(D){this._touchZoom.enable(D),this._rotationDisabled||this._touchRotate.enable(D),this._tapDragZoom.enable(),this._el.classList.add("mapboxgl-touch-zoom-rotate")},Gr.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove("mapboxgl-touch-zoom-rotate")},Gr.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},Gr.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},Gr.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},Gr.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var mi=function(Y){return Y.zoom||Y.drag||Y.pitch||Y.rotate},Ui=function(Y){function D(){Y.apply(this,arguments)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D}(i.Event);function qi(Y){return Y.panDelta&&Y.panDelta.mag()||Y.zoomDelta||Y.bearingDelta||Y.pitchDelta}var Ei=function(D,J){this._map=D,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Tl(D),this._bearingSnap=J.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(J),i.bindAll(["handleEvent","handleWindowEvent"],this);var q=this._el;this._listeners=[[q,"touchstart",{passive:!0}],[q,"touchmove",{passive:!1}],[q,"touchend",void 0],[q,"touchcancel",void 0],[q,"mousedown",void 0],[q,"mousemove",void 0],[q,"mouseup",void 0],[i.window.document,"mousemove",{capture:!0}],[i.window.document,"mouseup",void 0],[q,"mouseover",void 0],[q,"mouseout",void 0],[q,"dblclick",void 0],[q,"click",void 0],[q,"keydown",{capture:!1}],[q,"keyup",void 0],[q,"wheel",{passive:!1}],[q,"contextmenu",void 0],[i.window,"blur",void 0]];for(var K=0,de=this._listeners;Kwe?Math.min(2,yt):Math.max(.5,yt),fi=Math.pow(Di,1-br),Ti=ne.unproject(Bt.add(Dt.mult(br*fi)).mult(Ur));ne.setLocationAtPoint(ne.renderWorldCopies?Ti.wrap():Ti,Ct)}de._fireMoveEvents(K)},function(br){de._afterEase(K,br)},q),this},D.prototype._prepareEase=function(q,K,de){de===void 0&&(de={}),this._moving=!0,!K&&!de.moving&&this.fire(new i.Event("movestart",q)),this._zooming&&!de.zooming&&this.fire(new i.Event("zoomstart",q)),this._rotating&&!de.rotating&&this.fire(new i.Event("rotatestart",q)),this._pitching&&!de.pitching&&this.fire(new i.Event("pitchstart",q))},D.prototype._fireMoveEvents=function(q){this.fire(new i.Event("move",q)),this._zooming&&this.fire(new i.Event("zoom",q)),this._rotating&&this.fire(new i.Event("rotate",q)),this._pitching&&this.fire(new i.Event("pitch",q))},D.prototype._afterEase=function(q,K){if(!(this._easeId&&K&&this._easeId===K)){delete this._easeId;var de=this._zooming,ne=this._rotating,we=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,de&&this.fire(new i.Event("zoomend",q)),ne&&this.fire(new i.Event("rotateend",q)),we&&this.fire(new i.Event("pitchend",q)),this.fire(new i.Event("moveend",q))}},D.prototype.flyTo=function(q,K){var de=this;if(!q.essential&&i.browser.prefersReducedMotion){var ne=i.pick(q,["center","zoom","bearing","pitch","around"]);return this.jumpTo(ne,K)}this.stop(),q=i.extend({offset:[0,0],speed:1.2,curve:1.42,easing:i.ease},q);var we=this.transform,Ue=this.getZoom(),ft=this.getBearing(),Xt=this.getPitch(),hr=this.getPadding(),qt="zoom"in q?i.clamp(+q.zoom,we.minZoom,we.maxZoom):Ue,Ve="bearing"in q?this._normalizeBearing(q.bearing,ft):ft,Qe="pitch"in q?+q.pitch:Xt,at="padding"in q?q.padding:we.padding,Ct=we.zoomScale(qt-Ue),Ot=i.Point.convert(q.offset),Rt=we.centerPoint.add(Ot),Bt=we.pointLocation(Rt),Dt=i.LngLat.convert(q.center||Bt);this._normalizeCenter(Dt);var yt=we.project(Bt),Pt=we.project(Dt).sub(yt),ht=q.curve,ur=Math.max(we.width,we.height),br=ur/Ct,Ur=Pt.mag();if("minZoom"in q){var Di=i.clamp(Math.min(q.minZoom,Ue,qt),we.minZoom,we.maxZoom),fi=ur/we.zoomScale(Di-Ue);ht=Math.sqrt(fi/Ur*2)}var Ti=ht*ht;function gn(so){var Zo=(br*br-ur*ur+(so?-1:1)*Ti*Ti*Ur*Ur)/(2*(so?br:ur)*Ti*Ur);return Math.log(Math.sqrt(Zo*Zo+1)-Zo)}function rn(so){return(Math.exp(so)-Math.exp(-so))/2}function Ci(so){return(Math.exp(so)+Math.exp(-so))/2}function Bi(so){return rn(so)/Ci(so)}var Gi=gn(0),sn=function(so){return Ci(Gi)/Ci(Gi+ht*so)},zn=function(so){return ur*((Ci(Gi)*Bi(Gi+ht*so)-rn(Gi))/Ti)/Ur},Ja=(gn(1)-Gi)/ht;if(Math.abs(Ur)<1e-6||!isFinite(Ja)){if(Math.abs(ur-br)<1e-6)return this.easeTo(q,K);var co=brq.maxDuration&&(q.duration=0),this._zooming=!0,this._rotating=ft!==Ve,this._pitching=Qe!==Xt,this._padding=!we.isPaddingEqual(at),this._prepareEase(K,!1),this._ease(function(so){var Zo=so*Ja,ms=1/sn(Zo);we.zoom=so===1?qt:Ue+we.scaleZoom(ms),de._rotating&&(we.bearing=i.number(ft,Ve,so)),de._pitching&&(we.pitch=i.number(Xt,Qe,so)),de._padding&&(we.interpolatePadding(hr,at,so),Rt=we.centerPoint.add(Ot));var ou=so===1?Dt:we.unproject(yt.add(Pt.mult(zn(Zo))).mult(ms));we.setLocationAtPoint(we.renderWorldCopies?ou.wrap():ou,Rt),de._fireMoveEvents(K)},function(){return de._afterEase(K)},q),this},D.prototype.isEasing=function(){return!!this._easeFrameId},D.prototype.stop=function(){return this._stop()},D.prototype._stop=function(q,K){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var de=this._onEaseEnd;delete this._onEaseEnd,de.call(this,K)}if(!q){var ne=this.handlers;ne&&ne.stop(!1)}return this},D.prototype._ease=function(q,K,de){de.animate===!1||de.duration===0?(q(1),K()):(this._easeStart=i.browser.now(),this._easeOptions=de,this._onEaseFrame=q,this._onEaseEnd=K,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},D.prototype._renderFrameCallback=function(){var q=Math.min((i.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(q)),q<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},D.prototype._normalizeBearing=function(q,K){q=i.wrap(q,-180,180);var de=Math.abs(q-K);return Math.abs(q-360-K)180?-360:de<-180?360:0}},D}(i.Evented),en=function(D){D===void 0&&(D={}),this.options=D,i.bindAll(["_toggleAttribution","_updateEditLink","_updateData","_updateCompact"],this)};en.prototype.getDefaultPosition=function(){return"bottom-right"},en.prototype.onAdd=function(D){var J=this.options&&this.options.compact;return this._map=D,this._container=o.create("div","mapboxgl-ctrl mapboxgl-ctrl-attrib"),this._compactButton=o.create("button","mapboxgl-ctrl-attrib-button",this._container),this._compactButton.addEventListener("click",this._toggleAttribution),this._setElementTitle(this._compactButton,"ToggleAttribution"),this._innerContainer=o.create("div","mapboxgl-ctrl-attrib-inner",this._container),this._innerContainer.setAttribute("role","list"),J&&this._container.classList.add("mapboxgl-compact"),this._updateAttributions(),this._updateEditLink(),this._map.on("styledata",this._updateData),this._map.on("sourcedata",this._updateData),this._map.on("moveend",this._updateEditLink),J===void 0&&(this._map.on("resize",this._updateCompact),this._updateCompact()),this._container},en.prototype.onRemove=function(){o.remove(this._container),this._map.off("styledata",this._updateData),this._map.off("sourcedata",this._updateData),this._map.off("moveend",this._updateEditLink),this._map.off("resize",this._updateCompact),this._map=void 0,this._attribHTML=void 0},en.prototype._setElementTitle=function(D,J){var q=this._map._getUIString("AttributionControl."+J);D.title=q,D.setAttribute("aria-label",q)},en.prototype._toggleAttribution=function(){this._container.classList.contains("mapboxgl-compact-show")?(this._container.classList.remove("mapboxgl-compact-show"),this._compactButton.setAttribute("aria-pressed","false")):(this._container.classList.add("mapboxgl-compact-show"),this._compactButton.setAttribute("aria-pressed","true"))},en.prototype._updateEditLink=function(){var D=this._editLink;D||(D=this._editLink=this._container.querySelector(".mapbox-improve-map"));var J=[{key:"owner",value:this.styleOwner},{key:"id",value:this.styleId},{key:"access_token",value:this._map._requestManager._customAccessToken||i.config.ACCESS_TOKEN}];if(D){var q=J.reduce(function(K,de,ne){return de.value&&(K+=de.key+"="+de.value+(ne=0)return!1;return!0});var we=D.join(" | ");we!==this._attribHTML&&(this._attribHTML=we,D.length?(this._innerContainer.innerHTML=we,this._container.classList.remove("mapboxgl-attrib-empty")):this._container.classList.add("mapboxgl-attrib-empty"),this._editLink=null)}},en.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add("mapboxgl-compact"):this._container.classList.remove("mapboxgl-compact","mapboxgl-compact-show")};var Wi=function(){i.bindAll(["_updateLogo"],this),i.bindAll(["_updateCompact"],this)};Wi.prototype.onAdd=function(D){this._map=D,this._container=o.create("div","mapboxgl-ctrl");var J=o.create("a","mapboxgl-ctrl-logo");return J.target="_blank",J.rel="noopener nofollow",J.href="https://www.mapbox.com/",J.setAttribute("aria-label",this._map._getUIString("LogoControl.Title")),J.setAttribute("rel","noopener nofollow"),this._container.appendChild(J),this._container.style.display="none",this._map.on("sourcedata",this._updateLogo),this._updateLogo(),this._map.on("resize",this._updateCompact),this._updateCompact(),this._container},Wi.prototype.onRemove=function(){o.remove(this._container),this._map.off("sourcedata",this._updateLogo),this._map.off("resize",this._updateCompact)},Wi.prototype.getDefaultPosition=function(){return"bottom-left"},Wi.prototype._updateLogo=function(D){(!D||D.sourceDataType==="metadata")&&(this._container.style.display=this._logoRequired()?"block":"none")},Wi.prototype._logoRequired=function(){if(this._map.style){var D=this._map.style.sourceCaches;for(var J in D){var q=D[J].getSource();if(q.mapbox_logo)return!0}return!1}},Wi.prototype._updateCompact=function(){var D=this._container.children;if(D.length){var J=D[0];this._map.getCanvasContainer().offsetWidth<250?J.classList.add("mapboxgl-compact"):J.classList.remove("mapboxgl-compact")}};var si=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};si.prototype.add=function(D){var J=++this._id,q=this._queue;return q.push({callback:D,id:J,cancelled:!1}),J},si.prototype.remove=function(D){for(var J=this._currentlyRunning,q=J?this._queue.concat(J):this._queue,K=0,de=q;Kq.maxZoom)throw new Error("maxZoom must be greater than or equal to minZoom");if(q.minPitch!=null&&q.maxPitch!=null&&q.minPitch>q.maxPitch)throw new Error("maxPitch must be greater than or equal to minPitch");if(q.minPitch!=null&&q.minPitchBn)throw new Error("maxPitch must be less than or equal to "+Bn);var de=new wo(q.minZoom,q.maxZoom,q.minPitch,q.maxPitch,q.renderWorldCopies);if(Y.call(this,de,q),this._interactive=q.interactive,this._maxTileCacheSize=q.maxTileCacheSize,this._failIfMajorPerformanceCaveat=q.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=q.preserveDrawingBuffer,this._antialias=q.antialias,this._trackResize=q.trackResize,this._bearingSnap=q.bearingSnap,this._refreshExpiredTiles=q.refreshExpiredTiles,this._fadeDuration=q.fadeDuration,this._crossSourceCollisions=q.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=q.collectResourceTiming,this._renderTaskQueue=new si,this._controls=[],this._mapId=i.uniqueId(),this._locale=i.extend({},Mr,q.locale),this._clickTolerance=q.clickTolerance,this._requestManager=new i.RequestManager(q.transformRequest,q.accessToken),typeof q.container=="string"){if(this._container=i.window.document.getElementById(q.container),!this._container)throw new Error("Container '"+q.container+"' not found.")}else if(q.container instanceof xi)this._container=q.container;else throw new Error("Invalid type: 'container' must be a String or HTMLElement.");if(q.maxBounds&&this.setMaxBounds(q.maxBounds),i.bindAll(["_onWindowOnline","_onWindowResize","_onMapScroll","_contextLost","_contextRestored"],this),this._setupContainer(),this._setupPainter(),this.painter===void 0)throw new Error("Failed to initialize WebGL.");this.on("move",function(){return K._update(!1)}),this.on("moveend",function(){return K._update(!1)}),this.on("zoom",function(){return K._update(!0)}),typeof i.window!="undefined"&&(i.window.addEventListener("online",this._onWindowOnline,!1),i.window.addEventListener("resize",this._onWindowResize,!1),i.window.addEventListener("orientationchange",this._onWindowResize,!1)),this.handlers=new Ei(this,q);var ne=typeof q.hash=="string"&&q.hash||void 0;this._hash=q.hash&&new Ul(ne).addTo(this),(!this._hash||!this._hash._onHashChange())&&(this.jumpTo({center:q.center,zoom:q.zoom,bearing:q.bearing,pitch:q.pitch}),q.bounds&&(this.resize(),this.fitBounds(q.bounds,i.extend({},q.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=q.localIdeographFontFamily,q.style&&this.setStyle(q.style,{localIdeographFontFamily:q.localIdeographFontFamily}),q.attributionControl&&this.addControl(new en({customAttribution:q.customAttribution})),this.addControl(new Wi,q.logoPosition),this.on("style.load",function(){K.transform.unmodified&&K.jumpTo(K.style.stylesheet)}),this.on("data",function(we){K._update(we.dataType==="style"),K.fire(new i.Event(we.dataType+"data",we))}),this.on("dataloading",function(we){K.fire(new i.Event(we.dataType+"dataloading",we))})}Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D;var J={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return D.prototype._getMapId=function(){return this._mapId},D.prototype.addControl=function(K,de){if(de===void 0&&(K.getDefaultPosition?de=K.getDefaultPosition():de="top-right"),!K||!K.onAdd)return this.fire(new i.ErrorEvent(new Error("Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.")));var ne=K.onAdd(this);this._controls.push(K);var we=this._controlPositions[de];return de.indexOf("bottom")!==-1?we.insertBefore(ne,we.firstChild):we.appendChild(ne),this},D.prototype.removeControl=function(K){if(!K||!K.onRemove)return this.fire(new i.ErrorEvent(new Error("Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.")));var de=this._controls.indexOf(K);return de>-1&&this._controls.splice(de,1),K.onRemove(this),this},D.prototype.hasControl=function(K){return this._controls.indexOf(K)>-1},D.prototype.resize=function(K){var de=this._containerDimensions(),ne=de[0],we=de[1];this._resizeCanvas(ne,we),this.transform.resize(ne,we),this.painter.resize(ne,we);var Ue=!this._moving;return Ue&&(this.stop(),this.fire(new i.Event("movestart",K)).fire(new i.Event("move",K))),this.fire(new i.Event("resize",K)),Ue&&this.fire(new i.Event("moveend",K)),this},D.prototype.getBounds=function(){return this.transform.getBounds()},D.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},D.prototype.setMaxBounds=function(K){return this.transform.setMaxBounds(i.LngLatBounds.convert(K)),this._update()},D.prototype.setMinZoom=function(K){if(K=K==null?ci:K,K>=ci&&K<=this.transform.maxZoom)return this.transform.minZoom=K,this._update(),this.getZoom()=this.transform.minZoom)return this.transform.maxZoom=K,this._update(),this.getZoom()>K&&this.setZoom(K),this;throw new Error("maxZoom must be greater than the current minZoom")},D.prototype.getMaxZoom=function(){return this.transform.maxZoom},D.prototype.setMinPitch=function(K){if(K=K==null?Zi:K,K=Zi&&K<=this.transform.maxPitch)return this.transform.minPitch=K,this._update(),this.getPitch()Bn)throw new Error("maxPitch must be less than or equal to "+Bn);if(K>=this.transform.minPitch)return this.transform.maxPitch=K,this._update(),this.getPitch()>K&&this.setPitch(K),this;throw new Error("maxPitch must be greater than the current minPitch")},D.prototype.getMaxPitch=function(){return this.transform.maxPitch},D.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},D.prototype.setRenderWorldCopies=function(K){return this.transform.renderWorldCopies=K,this._update()},D.prototype.project=function(K){return this.transform.locationPoint(i.LngLat.convert(K))},D.prototype.unproject=function(K){return this.transform.pointLocation(i.Point.convert(K))},D.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},D.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},D.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},D.prototype._createDelegatedListener=function(K,de,ne){var we=this,Ue;if(K==="mouseenter"||K==="mouseover"){var ft=!1,Xt=function(Ct){var Ot=we.getLayer(de)?we.queryRenderedFeatures(Ct.point,{layers:[de]}):[];Ot.length?ft||(ft=!0,ne.call(we,new se(K,we,Ct.originalEvent,{features:Ot}))):ft=!1},hr=function(){ft=!1};return{layer:de,listener:ne,delegates:{mousemove:Xt,mouseout:hr}}}else if(K==="mouseleave"||K==="mouseout"){var qt=!1,Ve=function(Ct){var Ot=we.getLayer(de)?we.queryRenderedFeatures(Ct.point,{layers:[de]}):[];Ot.length?qt=!0:qt&&(qt=!1,ne.call(we,new se(K,we,Ct.originalEvent)))},Qe=function(Ct){qt&&(qt=!1,ne.call(we,new se(K,we,Ct.originalEvent)))};return{layer:de,listener:ne,delegates:{mousemove:Ve,mouseout:Qe}}}else{var at=function(Ct){var Ot=we.getLayer(de)?we.queryRenderedFeatures(Ct.point,{layers:[de]}):[];Ot.length&&(Ct.features=Ot,ne.call(we,Ct),delete Ct.features)};return{layer:de,listener:ne,delegates:(Ue={},Ue[K]=at,Ue)}}},D.prototype.on=function(K,de,ne){if(ne===void 0)return Y.prototype.on.call(this,K,de);var we=this._createDelegatedListener(K,de,ne);this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[K]=this._delegatedListeners[K]||[],this._delegatedListeners[K].push(we);for(var Ue in we.delegates)this.on(Ue,we.delegates[Ue]);return this},D.prototype.once=function(K,de,ne){if(ne===void 0)return Y.prototype.once.call(this,K,de);var we=this._createDelegatedListener(K,de,ne);for(var Ue in we.delegates)this.once(Ue,we.delegates[Ue]);return this},D.prototype.off=function(K,de,ne){var we=this;if(ne===void 0)return Y.prototype.off.call(this,K,de);var Ue=function(ft){for(var Xt=ft[K],hr=0;hr180;){var ne=J.locationPoint(Y);if(ne.x>=0&&ne.y>=0&&ne.x<=J.width&&ne.y<=J.height)break;Y.lng>J.center.lng?Y.lng-=360:Y.lng+=360}return Y}var Vn={center:"translate(-50%,-50%)",top:"translate(-50%,0)","top-left":"translate(0,0)","top-right":"translate(-100%,0)",bottom:"translate(-50%,-100%)","bottom-left":"translate(0,-100%)","bottom-right":"translate(-100%,-100%)",left:"translate(0,-50%)",right:"translate(-100%,-50%)"};function na(Y,D,J){var q=Y.classList;for(var K in Vn)q.remove("mapboxgl-"+J+"-anchor-"+K);q.add("mapboxgl-"+J+"-anchor-"+D)}var Ki=function(Y){function D(J,q){if(Y.call(this),(J instanceof i.window.HTMLElement||q)&&(J=i.extend({element:J},q)),i.bindAll(["_update","_onMove","_onUp","_addDragHandler","_onMapClick","_onKeyPress"],this),this._anchor=J&&J.anchor||"center",this._color=J&&J.color||"#3FB1CE",this._scale=J&&J.scale||1,this._draggable=J&&J.draggable||!1,this._clickTolerance=J&&J.clickTolerance||0,this._isDragging=!1,this._state="inactive",this._rotation=J&&J.rotation||0,this._rotationAlignment=J&&J.rotationAlignment||"auto",this._pitchAlignment=J&&J.pitchAlignment&&J.pitchAlignment!=="auto"?J.pitchAlignment:this._rotationAlignment,!J||!J.element){this._defaultMarker=!0,this._element=o.create("div"),this._element.setAttribute("aria-label","Map marker");var K=o.createNS("http://www.w3.org/2000/svg","svg"),de=41,ne=27;K.setAttributeNS(null,"display","block"),K.setAttributeNS(null,"height",de+"px"),K.setAttributeNS(null,"width",ne+"px"),K.setAttributeNS(null,"viewBox","0 0 "+ne+" "+de);var we=o.createNS("http://www.w3.org/2000/svg","g");we.setAttributeNS(null,"stroke","none"),we.setAttributeNS(null,"stroke-width","1"),we.setAttributeNS(null,"fill","none"),we.setAttributeNS(null,"fill-rule","evenodd");var Ue=o.createNS("http://www.w3.org/2000/svg","g");Ue.setAttributeNS(null,"fill-rule","nonzero");var ft=o.createNS("http://www.w3.org/2000/svg","g");ft.setAttributeNS(null,"transform","translate(3.0, 29.0)"),ft.setAttributeNS(null,"fill","#000000");for(var Xt=[{rx:"10.5",ry:"5.25002273"},{rx:"10.5",ry:"5.25002273"},{rx:"9.5",ry:"4.77275007"},{rx:"8.5",ry:"4.29549936"},{rx:"7.5",ry:"3.81822308"},{rx:"6.5",ry:"3.34094679"},{rx:"5.5",ry:"2.86367051"},{rx:"4.5",ry:"2.38636864"}],hr=0,qt=Xt;hr=K}this._isDragging&&(this._pos=q.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents="none",this._state==="pending"&&(this._state="active",this.fire(new i.Event("dragstart"))),this.fire(new i.Event("drag")))},D.prototype._onUp=function(){this._element.style.pointerEvents="auto",this._positionDelta=null,this._pointerdownPos=null,this._isDragging=!1,this._map.off("mousemove",this._onMove),this._map.off("touchmove",this._onMove),this._state==="active"&&this.fire(new i.Event("dragend")),this._state="inactive"},D.prototype._addDragHandler=function(q){this._element.contains(q.originalEvent.target)&&(q.preventDefault(),this._positionDelta=q.point.sub(this._pos).add(this._offset),this._pointerdownPos=q.point,this._state="pending",this._map.on("mousemove",this._onMove),this._map.on("touchmove",this._onMove),this._map.once("mouseup",this._onUp),this._map.once("touchend",this._onUp))},D.prototype.setDraggable=function(q){return this._draggable=!!q,this._map&&(q?(this._map.on("mousedown",this._addDragHandler),this._map.on("touchstart",this._addDragHandler)):(this._map.off("mousedown",this._addDragHandler),this._map.off("touchstart",this._addDragHandler))),this},D.prototype.isDraggable=function(){return this._draggable},D.prototype.setRotation=function(q){return this._rotation=q||0,this._update(),this},D.prototype.getRotation=function(){return this._rotation},D.prototype.setRotationAlignment=function(q){return this._rotationAlignment=q||"auto",this._update(),this},D.prototype.getRotationAlignment=function(){return this._rotationAlignment},D.prototype.setPitchAlignment=function(q){return this._pitchAlignment=q&&q!=="auto"?q:this._rotationAlignment,this._update(),this},D.prototype.getPitchAlignment=function(){return this._pitchAlignment},D}(i.Evented),kn={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0},ta;function oa(Y){ta!==void 0?Y(ta):i.window.navigator.permissions!==void 0?i.window.navigator.permissions.query({name:"geolocation"}).then(function(D){ta=D.state!=="denied",Y(ta)}):(ta=!!i.window.navigator.geolocation,Y(ta))}var ba=0,is=!1,Zs=function(Y){function D(J){Y.call(this),this.options=i.extend({},kn,J),i.bindAll(["_onSuccess","_onError","_onZoom","_finish","_setupUI","_updateCamera","_updateMarker"],this)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.onAdd=function(q){return this._map=q,this._container=o.create("div","mapboxgl-ctrl mapboxgl-ctrl-group"),oa(this._setupUI),this._container},D.prototype.onRemove=function(){this._geolocationWatchID!==void 0&&(i.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),o.remove(this._container),this._map.off("zoom",this._onZoom),this._map=void 0,ba=0,is=!1},D.prototype._isOutOfMapMaxBounds=function(q){var K=this._map.getMaxBounds(),de=q.coords;return K&&(de.longitudeK.getEast()||de.latitudeK.getNorth())},D.prototype._setErrorState=function(){switch(this._watchState){case"WAITING_ACTIVE":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active-error");break;case"ACTIVE_LOCK":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting");break;case"BACKGROUND":this._watchState="BACKGROUND_ERROR",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting");break}},D.prototype._onSuccess=function(q){if(this._map){if(this._isOutOfMapMaxBounds(q)){this._setErrorState(),this.fire(new i.Event("outofmaxbounds",q)),this._updateMarker(),this._finish();return}if(this.options.trackUserLocation)switch(this._lastKnownPosition=q,this._watchState){case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active");break;case"BACKGROUND":case"BACKGROUND_ERROR":this._watchState="BACKGROUND",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background");break}this.options.showUserLocation&&this._watchState!=="OFF"&&this._updateMarker(q),(!this.options.trackUserLocation||this._watchState==="ACTIVE_LOCK")&&this._updateCamera(q),this.options.showUserLocation&&this._dotElement.classList.remove("mapboxgl-user-location-dot-stale"),this.fire(new i.Event("geolocate",q)),this._finish()}},D.prototype._updateCamera=function(q){var K=new i.LngLat(q.coords.longitude,q.coords.latitude),de=q.coords.accuracy,ne=this._map.getBearing(),we=i.extend({bearing:ne},this.options.fitBoundsOptions);this._map.fitBounds(K.toBounds(de),we,{geolocateSource:!0})},D.prototype._updateMarker=function(q){if(q){var K=new i.LngLat(q.coords.longitude,q.coords.latitude);this._accuracyCircleMarker.setLngLat(K).addTo(this._map),this._userLocationDotMarker.setLngLat(K).addTo(this._map),this._accuracy=q.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},D.prototype._updateCircleRadius=function(){var q=this._map._container.clientHeight/2,K=this._map.unproject([0,q]),de=this._map.unproject([1,q]),ne=K.distanceTo(de),we=Math.ceil(2*this._accuracy/ne);this._circleElement.style.width=we+"px",this._circleElement.style.height=we+"px"},D.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},D.prototype._onError=function(q){if(this._map){if(this.options.trackUserLocation)if(q.code===1){this._watchState="OFF",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background-error"),this._geolocateButton.disabled=!0;var K=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.title=K,this._geolocateButton.setAttribute("aria-label",K),this._geolocationWatchID!==void 0&&this._clearWatch()}else{if(q.code===3&&is)return;this._setErrorState()}this._watchState!=="OFF"&&this.options.showUserLocation&&this._dotElement.classList.add("mapboxgl-user-location-dot-stale"),this.fire(new i.Event("error",q)),this._finish()}},D.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},D.prototype._setupUI=function(q){var K=this;if(this._container.addEventListener("contextmenu",function(we){return we.preventDefault()}),this._geolocateButton=o.create("button","mapboxgl-ctrl-geolocate",this._container),o.create("span","mapboxgl-ctrl-icon",this._geolocateButton).setAttribute("aria-hidden",!0),this._geolocateButton.type="button",q===!1){i.warnOnce("Geolocation support is not available so the GeolocateControl will be disabled.");var de=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.disabled=!0,this._geolocateButton.title=de,this._geolocateButton.setAttribute("aria-label",de)}else{var ne=this._map._getUIString("GeolocateControl.FindMyLocation");this._geolocateButton.title=ne,this._geolocateButton.setAttribute("aria-label",ne)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute("aria-pressed","false"),this._watchState="OFF"),this.options.showUserLocation&&(this._dotElement=o.create("div","mapboxgl-user-location-dot"),this._userLocationDotMarker=new Ki(this._dotElement),this._circleElement=o.create("div","mapboxgl-user-location-accuracy-circle"),this._accuracyCircleMarker=new Ki({element:this._circleElement,pitchAlignment:"map"}),this.options.trackUserLocation&&(this._watchState="OFF"),this._map.on("zoom",this._onZoom)),this._geolocateButton.addEventListener("click",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on("movestart",function(we){var Ue=we.originalEvent&&we.originalEvent.type==="resize";!we.geolocateSource&&K._watchState==="ACTIVE_LOCK"&&!Ue&&(K._watchState="BACKGROUND",K._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background"),K._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),K.fire(new i.Event("trackuserlocationend")))})},D.prototype.trigger=function(){if(!this._setup)return i.warnOnce("Geolocate control triggered before added to a map"),!1;if(this.options.trackUserLocation){switch(this._watchState){case"OFF":this._watchState="WAITING_ACTIVE",this.fire(new i.Event("trackuserlocationstart"));break;case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":case"BACKGROUND_ERROR":ba--,is=!1,this._watchState="OFF",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background-error"),this.fire(new i.Event("trackuserlocationend"));break;case"BACKGROUND":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new i.Event("trackuserlocationstart"));break}switch(this._watchState){case"WAITING_ACTIVE":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active");break;case"ACTIVE_LOCK":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active");break;case"ACTIVE_ERROR":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active-error");break;case"BACKGROUND":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background");break;case"BACKGROUND_ERROR":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background-error");break}if(this._watchState==="OFF"&&this._geolocationWatchID!==void 0)this._clearWatch();else if(this._geolocationWatchID===void 0){this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","true"),ba++;var q;ba>1?(q={maximumAge:6e5,timeout:0},is=!0):(q=this.options.positionOptions,is=!1),this._geolocationWatchID=i.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,q)}}else i.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},D.prototype._clearWatch=function(){i.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","false"),this.options.showUserLocation&&this._updateMarker(null)},D}(i.Evented),Va={maxWidth:100,unit:"metric"},Ml=function(D){this.options=i.extend({},Va,D),i.bindAll(["_onMove","setUnit"],this)};Ml.prototype.getDefaultPosition=function(){return"bottom-left"},Ml.prototype._onMove=function(){zo(this._map,this._container,this.options)},Ml.prototype.onAdd=function(D){return this._map=D,this._container=o.create("div","mapboxgl-ctrl mapboxgl-ctrl-scale",D.getContainer()),this._map.on("move",this._onMove),this._onMove(),this._container},Ml.prototype.onRemove=function(){o.remove(this._container),this._map.off("move",this._onMove),this._map=void 0},Ml.prototype.setUnit=function(D){this.options.unit=D,zo(this._map,this._container,this.options)};function zo(Y,D,J){var q=J&&J.maxWidth||100,K=Y._container.clientHeight/2,de=Y.unproject([0,K]),ne=Y.unproject([q,K]),we=de.distanceTo(ne);if(J&&J.unit==="imperial"){var Ue=3.2808*we;if(Ue>5280){var ft=Ue/5280;Qs(D,q,ft,Y._getUIString("ScaleControl.Miles"))}else Qs(D,q,Ue,Y._getUIString("ScaleControl.Feet"))}else if(J&&J.unit==="nautical"){var Xt=we/1852;Qs(D,q,Xt,Y._getUIString("ScaleControl.NauticalMiles"))}else we>=1e3?Qs(D,q,we/1e3,Y._getUIString("ScaleControl.Kilometers")):Qs(D,q,we,Y._getUIString("ScaleControl.Meters"))}function Qs(Y,D,J,q){var K=Vl(J),de=K/J;Y.style.width=D*de+"px",Y.innerHTML=K+" "+q}function al(Y){var D=Math.pow(10,Math.ceil(-Math.log(Y)/Math.LN10));return Math.round(Y*D)/D}function Vl(Y){var D=Math.pow(10,(""+Math.floor(Y)).length-1),J=Y/D;return J=J>=10?10:J>=5?5:J>=3?3:J>=2?2:J>=1?1:al(J),D*J}var ss=function(D){this._fullscreen=!1,D&&D.container&&(D.container instanceof i.window.HTMLElement?this._container=D.container:i.warnOnce("Full screen control 'container' must be a DOM element.")),i.bindAll(["_onClickFullscreen","_changeIcon"],this),"onfullscreenchange"in i.window.document?this._fullscreenchange="fullscreenchange":"onmozfullscreenchange"in i.window.document?this._fullscreenchange="mozfullscreenchange":"onwebkitfullscreenchange"in i.window.document?this._fullscreenchange="webkitfullscreenchange":"onmsfullscreenchange"in i.window.document&&(this._fullscreenchange="MSFullscreenChange")};ss.prototype.onAdd=function(D){return this._map=D,this._container||(this._container=this._map.getContainer()),this._controlContainer=o.create("div","mapboxgl-ctrl mapboxgl-ctrl-group"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display="none",i.warnOnce("This device does not support fullscreen mode.")),this._controlContainer},ss.prototype.onRemove=function(){o.remove(this._controlContainer),this._map=null,i.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},ss.prototype._checkFullscreenSupport=function(){return!!(i.window.document.fullscreenEnabled||i.window.document.mozFullScreenEnabled||i.window.document.msFullscreenEnabled||i.window.document.webkitFullscreenEnabled)},ss.prototype._setupUI=function(){var D=this._fullscreenButton=o.create("button","mapboxgl-ctrl-fullscreen",this._controlContainer);o.create("span","mapboxgl-ctrl-icon",D).setAttribute("aria-hidden",!0),D.type="button",this._updateTitle(),this._fullscreenButton.addEventListener("click",this._onClickFullscreen),i.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},ss.prototype._updateTitle=function(){var D=this._getTitle();this._fullscreenButton.setAttribute("aria-label",D),this._fullscreenButton.title=D},ss.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?"FullscreenControl.Exit":"FullscreenControl.Enter")},ss.prototype._isFullscreen=function(){return this._fullscreen},ss.prototype._changeIcon=function(){var D=i.window.document.fullscreenElement||i.window.document.mozFullScreenElement||i.window.document.webkitFullscreenElement||i.window.document.msFullscreenElement;D===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle("mapboxgl-ctrl-shrink"),this._fullscreenButton.classList.toggle("mapboxgl-ctrl-fullscreen"),this._updateTitle())},ss.prototype._onClickFullscreen=function(){this._isFullscreen()?i.window.document.exitFullscreen?i.window.document.exitFullscreen():i.window.document.mozCancelFullScreen?i.window.document.mozCancelFullScreen():i.window.document.msExitFullscreen?i.window.document.msExitFullscreen():i.window.document.webkitCancelFullScreen&&i.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var Vs={closeButton:!0,closeOnClick:!0,focusAfterOpen:!0,className:"",maxWidth:"240px"},Ys=["a[href]","[tabindex]:not([tabindex='-1'])","[contenteditable]:not([contenteditable='false'])","button:not([disabled])","input:not([disabled])","select:not([disabled])","textarea:not([disabled])"].join(", "),wa=function(Y){function D(J){Y.call(this),this.options=i.extend(Object.create(Vs),J),i.bindAll(["_update","_onClose","remove","_onMouseMove","_onMouseUp","_onDrag"],this)}return Y&&(D.__proto__=Y),D.prototype=Object.create(Y&&Y.prototype),D.prototype.constructor=D,D.prototype.addTo=function(q){return this._map&&this.remove(),this._map=q,this.options.closeOnClick&&this._map.on("click",this._onClose),this.options.closeOnMove&&this._map.on("move",this._onClose),this._map.on("remove",this.remove),this._update(),this._focusFirstElement(),this._trackPointer?(this._map.on("mousemove",this._onMouseMove),this._map.on("mouseup",this._onMouseUp),this._container&&this._container.classList.add("mapboxgl-popup-track-pointer"),this._map._canvasContainer.classList.add("mapboxgl-track-pointer")):this._map.on("move",this._update),this.fire(new i.Event("open")),this},D.prototype.isOpen=function(){return!!this._map},D.prototype.remove=function(){return this._content&&o.remove(this._content),this._container&&(o.remove(this._container),delete this._container),this._map&&(this._map.off("move",this._update),this._map.off("move",this._onClose),this._map.off("click",this._onClose),this._map.off("remove",this.remove),this._map.off("mousemove",this._onMouseMove),this._map.off("mouseup",this._onMouseUp),this._map.off("drag",this._onDrag),delete this._map),this.fire(new i.Event("close")),this},D.prototype.getLngLat=function(){return this._lngLat},D.prototype.setLngLat=function(q){return this._lngLat=i.LngLat.convert(q),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on("move",this._update),this._map.off("mousemove",this._onMouseMove),this._container&&this._container.classList.remove("mapboxgl-popup-track-pointer"),this._map._canvasContainer.classList.remove("mapboxgl-track-pointer")),this},D.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off("move",this._update),this._map.on("mousemove",this._onMouseMove),this._map.on("drag",this._onDrag),this._container&&this._container.classList.add("mapboxgl-popup-track-pointer"),this._map._canvasContainer.classList.add("mapboxgl-track-pointer")),this},D.prototype.getElement=function(){return this._container},D.prototype.setText=function(q){return this.setDOMContent(i.window.document.createTextNode(q))},D.prototype.setHTML=function(q){var K=i.window.document.createDocumentFragment(),de=i.window.document.createElement("body"),ne;for(de.innerHTML=q;ne=de.firstChild,!!ne;)K.appendChild(ne);return this.setDOMContent(K)},D.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},D.prototype.setMaxWidth=function(q){return this.options.maxWidth=q,this._update(),this},D.prototype.setDOMContent=function(q){if(this._content)for(;this._content.hasChildNodes();)this._content.firstChild&&this._content.removeChild(this._content.firstChild);else this._content=o.create("div","mapboxgl-popup-content",this._container);return this._content.appendChild(q),this._createCloseButton(),this._update(),this._focusFirstElement(),this},D.prototype.addClassName=function(q){this._container&&this._container.classList.add(q)},D.prototype.removeClassName=function(q){this._container&&this._container.classList.remove(q)},D.prototype.setOffset=function(q){return this.options.offset=q,this._update(),this},D.prototype.toggleClassName=function(q){if(this._container)return this._container.classList.toggle(q)},D.prototype._createCloseButton=function(){this.options.closeButton&&(this._closeButton=o.create("button","mapboxgl-popup-close-button",this._content),this._closeButton.type="button",this._closeButton.setAttribute("aria-label","Close popup"),this._closeButton.innerHTML="×",this._closeButton.addEventListener("click",this._onClose))},D.prototype._onMouseUp=function(q){this._update(q.point)},D.prototype._onMouseMove=function(q){this._update(q.point)},D.prototype._onDrag=function(q){this._update(q.point)},D.prototype._update=function(q){var K=this,de=this._lngLat||this._trackPointer;if(!(!this._map||!de||!this._content)&&(this._container||(this._container=o.create("div","mapboxgl-popup",this._map.getContainer()),this._tip=o.create("div","mapboxgl-popup-tip",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(" ").forEach(function(Ve){return K._container.classList.add(Ve)}),this._trackPointer&&this._container.classList.add("mapboxgl-popup-track-pointer")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=pn(this._lngLat,this._pos,this._map.transform)),!(this._trackPointer&&!q))){var ne=this._pos=this._trackPointer&&q?q:this._map.project(this._lngLat),we=this.options.anchor,Ue=ol(this.options.offset);if(!we){var ft=this._container.offsetWidth,Xt=this._container.offsetHeight,hr;ne.y+Ue.bottom.ythis._map.transform.height-Xt?hr=["bottom"]:hr=[],ne.xthis._map.transform.width-ft/2&&hr.push("right"),hr.length===0?we="bottom":we=hr.join("-")}var qt=ne.add(Ue[we]).round();o.setTransform(this._container,Vn[we]+" translate("+qt.x+"px,"+qt.y+"px)"),na(this._container,we,"popup")}},D.prototype._focusFirstElement=function(){if(!(!this.options.focusAfterOpen||!this._container)){var q=this._container.querySelector(Ys);q&&q.focus()}},D.prototype._onClose=function(){this.remove()},D}(i.Evented);function ol(Y){if(Y)if(typeof Y=="number"){var D=Math.round(Math.sqrt(.5*Math.pow(Y,2)));return{center:new i.Point(0,0),top:new i.Point(0,Y),"top-left":new i.Point(D,D),"top-right":new i.Point(-D,D),bottom:new i.Point(0,-Y),"bottom-left":new i.Point(D,-D),"bottom-right":new i.Point(-D,-D),left:new i.Point(Y,0),right:new i.Point(-Y,0)}}else if(Y instanceof i.Point||Array.isArray(Y)){var J=i.Point.convert(Y);return{center:J,top:J,"top-left":J,"top-right":J,bottom:J,"bottom-left":J,"bottom-right":J,left:J,right:J}}else return{center:i.Point.convert(Y.center||[0,0]),top:i.Point.convert(Y.top||[0,0]),"top-left":i.Point.convert(Y["top-left"]||[0,0]),"top-right":i.Point.convert(Y["top-right"]||[0,0]),bottom:i.Point.convert(Y.bottom||[0,0]),"bottom-left":i.Point.convert(Y["bottom-left"]||[0,0]),"bottom-right":i.Point.convert(Y["bottom-right"]||[0,0]),left:i.Point.convert(Y.left||[0,0]),right:i.Point.convert(Y.right||[0,0])};else return ol(new i.Point(0,0))}var io={version:i.version,supported:a,setRTLTextPlugin:i.setRTLTextPlugin,getRTLTextPluginStatus:i.getRTLTextPluginStatus,Map:li,NavigationControl:Vi,GeolocateControl:Zs,AttributionControl:en,ScaleControl:Ml,FullscreenControl:ss,Popup:wa,Marker:Ki,Style:yu,LngLat:i.LngLat,LngLatBounds:i.LngLatBounds,Point:i.Point,MercatorCoordinate:i.MercatorCoordinate,Evented:i.Evented,config:i.config,prewarm:ua,clearPrewarmedResources:ma,get accessToken(){return i.config.ACCESS_TOKEN},set accessToken(Y){i.config.ACCESS_TOKEN=Y},get baseApiUrl(){return i.config.API_URL},set baseApiUrl(Y){i.config.API_URL=Y},get workerCount(){return fn.workerCount},set workerCount(Y){fn.workerCount=Y},get maxParallelImageRequests(){return i.config.MAX_PARALLEL_IMAGE_REQUESTS},set maxParallelImageRequests(Y){i.config.MAX_PARALLEL_IMAGE_REQUESTS=Y},clearStorage:function(D){i.clearTileCache(D)},workerUrl:""};return io}),r})});var fGe=ye((_xr,cGe)=>{"use strict";var iw=Dr(),Fjt=ru().sanitizeHTML,zjt=iJ(),sGe=c1();function lGe(e,t){this.subplot=e,this.uid=e.uid+"-"+t,this.index=t,this.idSource="source-"+this.uid,this.idLayer=sGe.layoutLayerPrefix+this.uid,this.sourceType=null,this.source=null,this.layerType=null,this.below=null,this.visible=!1}var ig=lGe.prototype;ig.update=function(t){this.visible?this.needsNewImage(t)?this.updateImage(t):this.needsNewSource(t)?(this.removeLayer(),this.updateSource(t),this.updateLayer(t)):this.needsNewLayer(t)?this.updateLayer(t):this.updateStyle(t):(this.updateSource(t),this.updateLayer(t)),this.visible=$z(t)};ig.needsNewImage=function(e){var t=this.subplot.map;return t.getSource(this.idSource)&&this.sourceType==="image"&&e.sourcetype==="image"&&(this.source!==e.source||JSON.stringify(this.coordinates)!==JSON.stringify(e.coordinates))};ig.needsNewSource=function(e){return this.sourceType!==e.sourcetype||JSON.stringify(this.source)!==JSON.stringify(e.source)||this.layerType!==e.type};ig.needsNewLayer=function(e){return this.layerType!==e.type||this.below!==this.subplot.belowLookup["layout-"+this.index]};ig.lookupBelow=function(){return this.subplot.belowLookup["layout-"+this.index]};ig.updateImage=function(e){var t=this.subplot.map;t.getSource(this.idSource).updateImage({url:e.source,coordinates:e.coordinates});var r=this.findFollowingMapboxLayerId(this.lookupBelow());r!==null&&this.subplot.map.moveLayer(this.idLayer,r)};ig.updateSource=function(e){var t=this.subplot.map;if(t.getSource(this.idSource)&&t.removeSource(this.idSource),this.sourceType=e.sourcetype,this.source=e.source,!!$z(e)){var r=Ojt(e);t.addSource(this.idSource,r)}};ig.findFollowingMapboxLayerId=function(e){if(e==="traces")for(var t=this.subplot.getMapLayers(),r=0;r0){for(var r=0;r0}function uGe(e){var t={},r={};switch(e.type){case"circle":iw.extendFlat(r,{"circle-radius":e.circle.radius,"circle-color":e.color,"circle-opacity":e.opacity});break;case"line":iw.extendFlat(r,{"line-width":e.line.width,"line-color":e.color,"line-opacity":e.opacity,"line-dasharray":e.line.dash});break;case"fill":iw.extendFlat(r,{"fill-color":e.color,"fill-outline-color":e.fill.outlinecolor,"fill-opacity":e.opacity});break;case"symbol":var n=e.symbol,i=zjt(n.textposition,n.iconsize);iw.extendFlat(t,{"icon-image":n.icon+"-15","icon-size":n.iconsize/10,"text-field":n.text,"text-size":n.textfont.size,"text-anchor":i.anchor,"text-offset":i.offset,"symbol-placement":n.placement}),iw.extendFlat(r,{"icon-color":e.color,"text-color":n.textfont.color,"text-opacity":e.opacity});break;case"raster":iw.extendFlat(r,{"raster-fade-duration":0,"raster-opacity":e.opacity});break}return{layout:t,paint:r}}function Ojt(e){var t=e.sourcetype,r=e.source,n={type:t},i;return t==="geojson"?i="data":t==="vector"?i=typeof r=="string"?"url":"tiles":t==="raster"?(i="tiles",n.tileSize=256):t==="image"&&(i="url",n.coordinates=e.coordinates),n[i]=r,e.sourceattribution&&(n.attribution=Fjt(e.sourceattribution)),n}cGe.exports=function(t,r,n){var i=new lGe(t,r);return i.update(n),i}});var xGe=ye((xxr,_Ge)=>{"use strict";var cJ=uJ(),fJ=Dr(),pGe=ix(),hGe=qa(),qjt=ho(),Bjt=yv(),Qz=vf(),gGe=Eg(),Njt=gGe.drawMode,Ujt=gGe.selectMode,Vjt=Of().prepSelect,Gjt=Of().clearOutline,Hjt=Of().clearSelectionsCache,jjt=Of().selectOnClick,_x=c1(),Wjt=fGe();function mGe(e,t){this.id=t,this.gd=e;var r=e._fullLayout,n=e._context;this.container=r._glcontainer.node(),this.isStatic=n.staticPlot,this.uid=r._uid+"-"+this.id,this.div=null,this.xaxis=null,this.yaxis=null,this.createFramework(r),this.map=null,this.accessToken=null,this.styleObj=null,this.traceHash={},this.layerList=[],this.belowLookup={},this.dragging=!1,this.wheeling=!1}var Nh=mGe.prototype;Nh.plot=function(e,t,r){var n=this,i=t[n.id];n.map&&i.accesstoken!==n.accessToken&&(n.map.remove(),n.map=null,n.styleObj=null,n.traceHash={},n.layerList=[]);var a;n.map?a=new Promise(function(o,s){n.updateMap(e,t,o,s)}):a=new Promise(function(o,s){n.createMap(e,t,o,s)}),r.push(a)};Nh.createMap=function(e,t,r,n){var i=this,a=t[i.id],o=i.styleObj=yGe(a.style,t);i.accessToken=a.accesstoken;var s=a.bounds,l=s?[[s.west,s.south],[s.east,s.north]]:null,u=i.map=new cJ.Map({container:i.div,style:o.style,center:hJ(a.center),zoom:a.zoom,bearing:a.bearing,pitch:a.pitch,maxBounds:l,interactive:!i.isStatic,preserveDrawingBuffer:i.isStatic,doubleClickZoom:!1,boxZoom:!1,attributionControl:!1}).addControl(new cJ.AttributionControl({compact:!0}));u._canvas.style.left="0px",u._canvas.style.top="0px",i.rejectOnError(n),i.isStatic||i.initFx(e,t);var c=[];c.push(new Promise(function(f){u.once("load",f)})),c=c.concat(pGe.fetchTraceGeoData(e)),Promise.all(c).then(function(){i.fillBelowLookup(e,t),i.updateData(e),i.updateLayout(t),i.resolveOnRender(r)}).catch(n)};Nh.updateMap=function(e,t,r,n){var i=this,a=i.map,o=t[this.id];i.rejectOnError(n);var s=[],l=yGe(o.style,t);JSON.stringify(i.styleObj)!==JSON.stringify(l)&&(i.styleObj=l,a.setStyle(l.style),i.traceHash={},s.push(new Promise(function(u){a.once("styledata",u)}))),s=s.concat(pGe.fetchTraceGeoData(e)),Promise.all(s).then(function(){i.fillBelowLookup(e,t),i.updateData(e),i.updateLayout(t),i.resolveOnRender(r)}).catch(n)};Nh.fillBelowLookup=function(e,t){var r=t[this.id],n=r.layers,i,a,o=this.belowLookup={},s=!1;for(i=0;i1)for(i=0;i-1&&jjt(l.originalEvent,n,[r.xaxis],[r.yaxis],r.id,s),u.indexOf("event")>-1&&Qz.click(n,l.originalEvent)}}};Nh.updateFx=function(e){var t=this,r=t.map,n=t.gd;if(t.isStatic)return;function i(l){var u=t.map.unproject(l);return[u.lng,u.lat]}var a=e.dragmode,o;o=function(l,u){if(u.isRect){var c=l.range={};c[t.id]=[i([u.xmin,u.ymin]),i([u.xmax,u.ymax])]}else{var f=l.lassoPoints={};f[t.id]=u.map(i)}};var s=t.dragOptions;t.dragOptions=fJ.extendDeep(s||{},{dragmode:e.dragmode,element:t.div,gd:n,plotinfo:{id:t.id,domain:e[t.id].domain,xaxis:t.xaxis,yaxis:t.yaxis,fillRangeItems:o},xaxes:[t.xaxis],yaxes:[t.yaxis],subplot:t.id}),r.off("click",t.onClickInPanHandler),Ujt(a)||Njt(a)?(r.dragPan.disable(),r.on("zoomstart",t.clearOutline),t.dragOptions.prepFn=function(l,u,c){Vjt(l,u,c,t.dragOptions,a)},Bjt.init(t.dragOptions)):(r.dragPan.enable(),r.off("zoomstart",t.clearOutline),t.div.onmousedown=null,t.div.ontouchstart=null,t.div.removeEventListener("touchstart",t.div._ontouchstart),t.onClickInPanHandler=t.onClickInPanFn(t.dragOptions),r.on("click",t.onClickInPanHandler))};Nh.updateFramework=function(e){var t=e[this.id].domain,r=e._size,n=this.div.style;n.width=r.w*(t.x[1]-t.x[0])+"px",n.height=r.h*(t.y[1]-t.y[0])+"px",n.left=r.l+t.x[0]*r.w+"px",n.top=r.t+(1-t.y[1])*r.h+"px",this.xaxis._offset=r.l+t.x[0]*r.w,this.xaxis._length=r.w*(t.x[1]-t.x[0]),this.yaxis._offset=r.t+(1-t.y[1])*r.h,this.yaxis._length=r.h*(t.y[1]-t.y[0])};Nh.updateLayers=function(e){var t=e[this.id],r=t.layers,n=this.layerList,i;if(r.length!==n.length){for(i=0;i{"use strict";var dJ=Dr(),Xjt=k_(),Zjt=Yd(),bGe=Nk();wGe.exports=function(t,r,n){Xjt(t,r,n,{type:"mapbox",attributes:bGe,handleDefaults:Yjt,partition:"y",accessToken:r._mapboxAccessToken})};function Yjt(e,t,r,n){r("accesstoken",n.accessToken),r("style"),r("center.lon"),r("center.lat"),r("zoom"),r("bearing"),r("pitch");var i=r("bounds.west"),a=r("bounds.east"),o=r("bounds.south"),s=r("bounds.north");(i===void 0||a===void 0||o===void 0||s===void 0)&&delete t.bounds,Zjt(e,t,{name:"layers",handleItemDefaults:Kjt}),t._input=e}function Kjt(e,t){function r(l,u){return dJ.coerce(e,t,bGe.layers,l,u)}var n=r("visible");if(n){var i=r("sourcetype"),a=i==="raster"||i==="image";r("source"),r("sourceattribution"),i==="vector"&&r("sourcelayer"),i==="image"&&r("coordinates");var o;a&&(o="raster");var s=r("type",o);a&&s!=="raster"&&(s=t.type="raster",dJ.log("Source types *raster* and *image* must drawn *raster* layer type.")),r("below"),r("color"),r("opacity"),r("minzoom"),r("maxzoom"),s==="circle"&&r("circle.radius"),s==="line"&&(r("line.width"),r("line.dash")),s==="fill"&&r("fill.outlinecolor"),s==="symbol"&&(r("symbol.icon"),r("symbol.iconsize"),r("symbol.text"),dJ.coerceFont(r,"symbol.textfont",void 0,{noFontVariant:!0,noFontShadow:!0,noFontLineposition:!0,noFontTextcase:!0}),r("symbol.textposition"),r("symbol.placement"))}}});var e7=ye(Np=>{"use strict";var AGe=uJ(),rm=Dr(),vJ=rm.strTranslate,Jjt=rm.strScale,$jt=Id().getSubplotCalcData,Qjt=Wp(),eWt=Oa(),SGe=So(),tWt=ru(),rWt=xGe(),xx="mapbox",ey=Np.constants=c1();Np.name=xx;Np.attr="subplot";Np.idRoot=xx;Np.idRegex=Np.attrRegex=rm.counterRegex(xx);var iWt=["mapbox subplots and traces are deprecated!","Please consider switching to `map` subplots and traces.","Learn more at: https://plotly.com/python/maplibre-migration/","as well as https://plotly.com/javascript/maplibre-migration/"].join(" ");Np.attributes={subplot:{valType:"subplotid",dflt:"mapbox",editType:"calc"}};Np.layoutAttributes=Nk();Np.supplyLayoutDefaults=TGe();var MGe=!0;Np.plot=function(t){MGe&&(MGe=!1,rm.warn(iWt));var r=t._fullLayout,n=t.calcdata,i=r._subplots[xx];if(AGe.version!==ey.requiredVersion)throw new Error(ey.wrongVersionErrorMsg);var a=nWt(t,i);AGe.accessToken=a;for(var o=0;op/2){var k=d.split("|").join("
");_.text(k).attr("data-unformatted",k).call(tWt.convertToTspans,e),b=SGe.bBox(_.node())}_.attr("transform",vJ(-3,-b.height+8)),v.insert("rect",".static-attribution").attr({x:-b.width-6,y:-b.height-3,width:b.width+6,height:b.height+3,fill:"rgba(255, 255, 255, 0.75)"});var E=1;b.width+6>p&&(E=p/(b.width+6));var S=[n.l+n.w*o.x[1],n.t+n.h*(1-o.y[0])];v.attr("transform",vJ(S[0],S[1])+Jjt(E))}};function nWt(e,t){var r=e._fullLayout,n=e._context;if(n.mapboxAccessToken==="")return"";for(var i=[],a=[],o=!1,s=!1,l=0;l1&&rm.warn(ey.multipleTokensErrorMsg),i[0]):(a.length&&rm.log(["Listed mapbox access token(s)",a.join(","),"but did not use a Mapbox map style, ignoring token(s)."].join(" ")),"")}function EGe(e){return typeof e=="string"&&(ey.styleValuesMapbox.indexOf(e)!==-1||e.indexOf("mapbox://")===0||e.indexOf("stamen")===0)}Np.updateFx=function(e){for(var t=e._fullLayout,r=t._subplots[xx],n=0;n{"use strict";var Txr=["*scattermapbox* trace is deprecated!","Please consider switching to the *scattermap* trace type and `map` subplots.","Learn more at: https://plotly.com/python/maplibre-migration/","as well as https://plotly.com/javascript/maplibre-migration/"].join(" ");kGe.exports={attributes:Wz(),supplyDefaults:NVe(),colorbar:$d(),formatLabels:rJ(),calc:pF(),plot:eGe(),hoverPoints:Jz().hoverPoints,eventData:nGe(),selectPoints:oGe(),styleOnSelect:function(e,t){if(t){var r=t[0].trace;r._glTrace.update(t)}},moduleType:"trace",name:"scattermapbox",basePlotModule:e7(),categories:["mapbox","gl","symbols","showLegend","scatter-like"],meta:{}}});var PGe=ye((Sxr,LGe)=>{"use strict";LGe.exports=CGe()});var pJ=ye((Mxr,IGe)=>{"use strict";var f1=t5(),aWt=Tu(),{hovertemplateAttrs:oWt,templatefallbackAttrs:sWt}=Ll(),lWt=Gl(),bx=Ao().extendFlat;IGe.exports=bx({locations:{valType:"data_array",editType:"calc"},z:{valType:"data_array",editType:"calc"},geojson:{valType:"any",editType:"calc"},featureidkey:bx({},f1.featureidkey,{}),below:{valType:"string",editType:"plot"},text:f1.text,hovertext:f1.hovertext,marker:{line:{color:bx({},f1.marker.line.color,{editType:"plot"}),width:bx({},f1.marker.line.width,{editType:"plot"}),editType:"calc"},opacity:bx({},f1.marker.opacity,{editType:"plot"}),editType:"calc"},selected:{marker:{opacity:bx({},f1.selected.marker.opacity,{editType:"plot"}),editType:"plot"},editType:"plot"},unselected:{marker:{opacity:bx({},f1.unselected.marker.opacity,{editType:"plot"}),editType:"plot"},editType:"plot"},hoverinfo:f1.hoverinfo,hovertemplate:oWt({},{keys:["properties"]}),hovertemplatefallback:sWt(),showlegend:bx({},lWt.showlegend,{dflt:!1})},aWt("",{cLetter:"z",editTypeOverride:"calc"}))});var DGe=ye((Exr,RGe)=>{"use strict";var Hk=Dr(),uWt=Qh(),cWt=pJ();RGe.exports=function(t,r,n,i){function a(c,f){return Hk.coerce(t,r,cWt,c,f)}var o=a("locations"),s=a("z"),l=a("geojson");if(!Hk.isArrayOrTypedArray(o)||!o.length||!Hk.isArrayOrTypedArray(s)||!s.length||!(typeof l=="string"&&l!==""||Hk.isPlainObject(l))){r.visible=!1;return}a("featureidkey"),r._length=Math.min(o.length,s.length),a("below"),a("text"),a("hovertext"),a("hovertemplate"),a("hovertemplatefallback");var u=a("marker.line.width");u&&a("marker.line.color"),a("marker.opacity"),uWt(t,r,i,a,{prefix:"",cLetter:"z"}),Hk.coerceSelectionMarkerOpacity(r,a)}});var gJ=ye((kxr,OGe)=>{"use strict";var fWt=Eo(),h1=Dr(),hWt=tc(),dWt=So(),vWt=tx().makeBlank,FGe=ix();function pWt(e){var t=e[0].trace,r=t.visible===!0&&t._length!==0,n={layout:{visibility:"none"},paint:{}},i={layout:{visibility:"none"},paint:{}},a=t._opts={fill:n,line:i,geojson:vWt()};if(!r)return a;var o=FGe.extractTraceFeature(e);if(!o)return a;var s=hWt.makeColorScaleFuncFromTrace(t),l=t.marker,u=l.line||{},c;h1.isArrayOrTypedArray(l.opacity)&&(c=function(k){var E=k.mo;return fWt(E)?+h1.constrain(E,0,1):0});var f;h1.isArrayOrTypedArray(u.color)&&(f=function(k){return k.mlc});var h;h1.isArrayOrTypedArray(u.width)&&(h=function(k){return k.mlw});for(var d=0;d{"use strict";var BGe=gJ().convert,gWt=gJ().convertOnSelect,qGe=c1().traceLayerPrefix;function NGe(e,t){this.type="choroplethmapbox",this.subplot=e,this.uid=t,this.sourceId="source-"+t,this.layerList=[["fill",qGe+t+"-fill"],["line",qGe+t+"-line"]],this.below=null}var M5=NGe.prototype;M5.update=function(e){this._update(BGe(e)),e[0].trace._glTrace=this};M5.updateOnSelect=function(e){this._update(gWt(e))};M5._update=function(e){var t=this.subplot,r=this.layerList,n=t.belowLookup["trace-"+this.uid];t.map.getSource(this.sourceId).setData(e.geojson),n!==this.below&&(this._removeLayers(),this._addLayers(e,n),this.below=n);for(var i=0;i=0;r--)e.removeLayer(t[r][1])};M5.dispose=function(){var e=this.subplot.map;this._removeLayers(),e.removeSource(this.sourceId)};UGe.exports=function(t,r){var n=r[0].trace,i=new NGe(t,n.uid),a=i.sourceId,o=BGe(r),s=i.below=t.belowLookup["trace-"+n.uid];return t.map.addSource(a,{type:"geojson",data:o.geojson}),i._addLayers(o,s),r[0].trace._glTrace=i,i}});var HGe=ye((Pxr,GGe)=>{"use strict";var Lxr=["*choroplethmapbox* trace is deprecated!","Please consider switching to the *choroplethmap* trace type and `map` subplots.","Learn more at: https://plotly.com/python/maplibre-migration/","as well as https://plotly.com/javascript/maplibre-migration/"].join(" ");GGe.exports={attributes:pJ(),supplyDefaults:DGe(),colorbar:S_(),calc:zF(),plot:VGe(),hoverPoints:qF(),eventData:BF(),selectPoints:NF(),styleOnSelect:function(e,t){if(t){var r=t[0].trace;r._glTrace.updateOnSelect(t)}},getBelow:function(e,t){for(var r=t.getMapLayers(),n=r.length-2;n>=0;n--){var i=r[n].id;if(typeof i=="string"&&i.indexOf("water")===0){for(var a=n+1;a{"use strict";jGe.exports=HGe()});var yJ=ye((Rxr,ZGe)=>{"use strict";var mWt=Tu(),{hovertemplateAttrs:yWt,templatefallbackAttrs:_Wt}=Ll(),XGe=Gl(),t7=Wz(),mJ=Ao().extendFlat;ZGe.exports=mJ({lon:t7.lon,lat:t7.lat,z:{valType:"data_array",editType:"calc"},radius:{valType:"number",editType:"plot",arrayOk:!0,min:1,dflt:30},below:{valType:"string",editType:"plot"},text:t7.text,hovertext:t7.hovertext,hoverinfo:mJ({},XGe.hoverinfo,{flags:["lon","lat","z","text","name"]}),hovertemplate:yWt(),hovertemplatefallback:_Wt(),showlegend:mJ({},XGe.showlegend,{dflt:!1})},mWt("",{cLetter:"z",editTypeOverride:"calc"}))});var KGe=ye((Dxr,YGe)=>{"use strict";var xWt=Dr(),bWt=Qh(),wWt=yJ();YGe.exports=function(t,r,n,i){function a(u,c){return xWt.coerce(t,r,wWt,u,c)}var o=a("lon")||[],s=a("lat")||[],l=Math.min(o.length,s.length);if(!l){r.visible=!1;return}r._length=l,a("z"),a("radius"),a("below"),a("text"),a("hovertext"),a("hovertemplate"),a("hovertemplatefallback"),bWt(t,r,i,a,{prefix:"",cLetter:"z"})}});var QGe=ye((Fxr,$Ge)=>{"use strict";var _J=Eo(),TWt=Dr().isArrayOrTypedArray,xJ=fs().BADNUM,AWt=gv(),JGe=Dr()._;$Ge.exports=function(t,r){for(var n=r._length,i=new Array(n),a=r.z,o=TWt(a)&&a.length,s=0;s{"use strict";var SWt=Eo(),bJ=Dr(),eHe=ka(),tHe=tc(),rHe=fs().BADNUM,MWt=tx().makeBlank;iHe.exports=function(t){var r=t[0].trace,n=r.visible===!0&&r._length!==0,i={layout:{visibility:"none"},paint:{}},a=r._opts={heatmap:i,geojson:MWt()};if(!n)return a;var o=[],s,l=r.z,u=r.radius,c=bJ.isArrayOrTypedArray(l)&&l.length,f=bJ.isArrayOrTypedArray(u);for(s=0;s0?+u[s]:0),o.push({type:"Feature",geometry:{type:"Point",coordinates:d},properties:v})}}var b=tHe.extractOpts(r),p=b.reversescale?tHe.flipScale(b.colorscale):b.colorscale,k=p[0][1],E=eHe.opacity(k)<1?k:eHe.addOpacity(k,0),S=["interpolate",["linear"],["heatmap-density"],0,E];for(s=1;s{"use strict";var aHe=nHe(),EWt=c1().traceLayerPrefix;function oHe(e,t){this.type="densitymapbox",this.subplot=e,this.uid=t,this.sourceId="source-"+t,this.layerList=[["heatmap",EWt+t+"-heatmap"]],this.below=null}var r7=oHe.prototype;r7.update=function(e){var t=this.subplot,r=this.layerList,n=aHe(e),i=t.belowLookup["trace-"+this.uid];t.map.getSource(this.sourceId).setData(n.geojson),i!==this.below&&(this._removeLayers(),this._addLayers(n,i),this.below=i);for(var a=0;a=0;r--)e.removeLayer(t[r][1])};r7.dispose=function(){var e=this.subplot.map;this._removeLayers(),e.removeSource(this.sourceId)};sHe.exports=function(t,r){var n=r[0].trace,i=new oHe(t,n.uid),a=i.sourceId,o=aHe(r),s=i.below=t.belowLookup["trace-"+n.uid];return t.map.addSource(a,{type:"geojson",data:o.geojson}),i._addLayers(o,s),i}});var cHe=ye((qxr,uHe)=>{"use strict";var kWt=ho(),CWt=Jz().hoverPoints,LWt=Jz().getExtraText;uHe.exports=function(t,r,n){var i=CWt(t,r,n);if(i){var a=i[0],o=a.cd,s=o[0].trace,l=o[a.index];if(delete a.color,"z"in l){var u=a.subplot.mockAxis;a.z=l.z,a.zLabel=kWt.tickText(u,u.c2l(l.z),"hover").text}return a.extraText=LWt(s,l,o[0].t.labels),[a]}}});var hHe=ye((Bxr,fHe)=>{"use strict";fHe.exports=function(t,r){return t.lon=r.lon,t.lat=r.lat,t.z=r.z,t}});var vHe=ye((Uxr,dHe)=>{"use strict";var Nxr=["*densitymapbox* trace is deprecated!","Please consider switching to the *densitymap* trace type and `map` subplots.","Learn more at: https://plotly.com/python/maplibre-migration/","as well as https://plotly.com/javascript/maplibre-migration/"].join(" ");dHe.exports={attributes:yJ(),supplyDefaults:KGe(),colorbar:S_(),formatLabels:rJ(),calc:QGe(),plot:lHe(),hoverPoints:cHe(),eventData:hHe(),getBelow:function(e,t){for(var r=t.getMapLayers(),n=0;n{"use strict";pHe.exports=vHe()});var yHe=ye((Gxr,mHe)=>{mHe.exports={version:8,name:"orto",metadata:{"maputnik:renderer":"mlgljs"},center:[1.537786,41.837539],zoom:12,bearing:0,pitch:0,light:{anchor:"viewport",color:"white",intensity:.4,position:[1.15,45,30]},sources:{ortoEsri:{type:"raster",tiles:["https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}"],tileSize:256,maxzoom:18,attribution:"ESRI © ESRI"},ortoInstaMaps:{type:"raster",tiles:["https://tilemaps.icgc.cat/mapfactory/wmts/orto_8_12/CAT3857/{z}/{x}/{y}.png"],tileSize:256,maxzoom:13},ortoICGC:{type:"raster",tiles:["https://geoserveis.icgc.cat/icc_mapesmultibase/noutm/wmts/orto/GRID3857/{z}/{x}/{y}.jpeg"],tileSize:256,minzoom:13.1,maxzoom:20},openmaptiles:{type:"vector",url:"https://geoserveis.icgc.cat/contextmaps/basemap.json"}},sprite:"https://geoserveis.icgc.cat/contextmaps/sprites/sprite@1",glyphs:"https://geoserveis.icgc.cat/contextmaps/glyphs/{fontstack}/{range}.pbf",layers:[{id:"background",type:"background",paint:{"background-color":"#F4F9F4"}},{id:"ortoEsri",type:"raster",source:"ortoEsri",maxzoom:16,layout:{visibility:"visible"}},{id:"ortoICGC",type:"raster",source:"ortoICGC",minzoom:13.1,maxzoom:19,layout:{visibility:"visible"}},{id:"ortoInstaMaps",type:"raster",source:"ortoInstaMaps",maxzoom:13,layout:{visibility:"visible"}},{id:"waterway_tunnel",type:"line",source:"openmaptiles","source-layer":"waterway",minzoom:14,filter:["all",["in","class","river","stream","canal"],["==","brunnel","tunnel"]],layout:{"line-cap":"round"},paint:{"line-color":"#a0c8f0","line-width":{base:1.3,stops:[[13,.5],[20,6]]},"line-dasharray":[2,4]}},{id:"waterway-other",type:"line",metadata:{"mapbox:group":"1444849382550.77"},source:"openmaptiles","source-layer":"waterway",filter:["!in","class","canal","river","stream"],layout:{"line-cap":"round"},paint:{"line-color":"#a0c8f0","line-width":{base:1.3,stops:[[13,.5],[20,2]]}}},{id:"waterway-stream-canal",type:"line",metadata:{"mapbox:group":"1444849382550.77"},source:"openmaptiles","source-layer":"waterway",filter:["all",["in","class","canal","stream"],["!=","brunnel","tunnel"]],layout:{"line-cap":"round"},paint:{"line-color":"#a0c8f0","line-width":{base:1.3,stops:[[13,.5],[20,6]]}}},{id:"waterway-river",type:"line",metadata:{"mapbox:group":"1444849382550.77"},source:"openmaptiles","source-layer":"waterway",filter:["all",["==","class","river"],["!=","brunnel","tunnel"]],layout:{"line-cap":"round"},paint:{"line-color":"#a0c8f0","line-width":{base:1.2,stops:[[10,.8],[20,4]]},"line-opacity":.5}},{id:"water-offset",type:"fill",metadata:{"mapbox:group":"1444849382550.77"},source:"openmaptiles","source-layer":"water",maxzoom:8,filter:["==","$type","Polygon"],layout:{visibility:"visible"},paint:{"fill-opacity":0,"fill-color":"#a0c8f0","fill-translate":{base:1,stops:[[6,[2,0]],[8,[0,0]]]}}},{id:"water",type:"fill",metadata:{"mapbox:group":"1444849382550.77"},source:"openmaptiles","source-layer":"water",layout:{visibility:"visible"},paint:{"fill-color":"hsl(210, 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Xk=Dr(),TJ=Ru(),$Wt=$p(),QWt=R0(),eXt=D0(),tXt=Rg(),zHe=n7(),rXt=wJ().isSupportedFont;OHe.exports=function(t,r,n,i){function a(p,k){return Xk.coerce(t,r,zHe,p,k)}function o(p,k){return Xk.coerce2(t,r,zHe,p,k)}var s=iXt(t,r,a);if(!s){r.visible=!1;return}if(a("text"),a("texttemplate"),a("texttemplatefallback"),a("hovertext"),a("hovertemplate"),a("hovertemplatefallback"),a("mode"),a("below"),TJ.hasMarkers(r)){$Wt(t,r,n,i,a,{noLine:!0,noAngle:!0}),a("marker.allowoverlap"),a("marker.angle");var l=r.marker;l.symbol!=="circle"&&(Xk.isArrayOrTypedArray(l.size)&&(l.size=l.size[0]),Xk.isArrayOrTypedArray(l.color)&&(l.color=l.color[0]))}TJ.hasLines(r)&&(QWt(t,r,n,i,a,{noDash:!0}),a("connectgaps"));var u=o("cluster.maxzoom"),c=o("cluster.step"),f=o("cluster.color",r.marker&&r.marker.color||n),h=o("cluster.size"),d=o("cluster.opacity"),v=u!==!1||c!==!1||f!==!1||h!==!1||d!==!1,_=a("cluster.enabled",v);if(_||TJ.hasText(r)){var b=i.font.family;eXt(t,r,i,a,{noSelect:!0,noFontVariant:!0,noFontShadow:!0,noFontLineposition:!0,noFontTextcase:!0,font:{family:rXt(b)?b:"Open Sans Regular",weight:i.font.weight,style:i.font.style,size:i.font.size,color:i.font.color}})}a("fill"),r.fill!=="none"&&tXt(t,r,n,a),Xk.coerceSelectionMarkerOpacity(r,a)};function iXt(e,t,r){var n=r("lon")||[],i=r("lat")||[],a=Math.min(n.length,i.length);return t._length=a,a}});var AJ=ye((Kxr,NHe)=>{"use strict";var BHe=ho();NHe.exports=function(t,r,n){var i={},a=n[r.subplot]._subplot,o=a.mockAxis,s=t.lonlat;return i.lonLabel=BHe.tickText(o,o.c2l(s[0]),!0).text,i.latLabel=BHe.tickText(o,o.c2l(s[1]),!0).text,i}});var SJ=ye((Jxr,VHe)=>{"use strict";var UHe=Dr();VHe.exports=function(t,r){var n=t.split(" 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k=hXt(r);v.geojson=k.geojson,v.layout.visibility="visible",f&&(v.filter=["!",["has","point_count"]],b.cluster={type:"circle",filter:["has","point_count"],layout:{visibility:"visible"},paint:{"circle-color":EJ(n.cluster.color,n.cluster.step),"circle-radius":EJ(n.cluster.size,n.cluster.step),"circle-opacity":EJ(n.cluster.opacity,n.cluster.step)}},b.clusterCount={type:"symbol",filter:["has","point_count"],paint:{},layout:{"text-field":"{point_count_abbreviated}","text-font":HHe(n),"text-size":12}}),ov.extendFlat(v.paint,{"circle-color":k.mcc,"circle-radius":k.mrc,"circle-opacity":k.mo})}if(u&&f&&(v.filter=["!",["has","point_count"]]),(c||l)&&(_.geojson=dXt(r,t),ov.extendFlat(_.layout,{visibility:"visible","icon-image":"{symbol}-15","text-field":"{text}"}),c&&(ov.extendFlat(_.layout,{"icon-size":n.marker.size/10}),"angle"in n.marker&&n.marker.angle!=="auto"&&ov.extendFlat(_.layout,{"icon-rotate":{type:"identity",property:"angle"},"icon-rotation-alignment":"map"}),_.layout["icon-allow-overlap"]=n.marker.allowoverlap,ov.extendFlat(_.paint,{"icon-opacity":n.opacity*n.marker.opacity,"icon-color":n.marker.color})),l)){var E=(n.marker||{}).size,S=lXt(n.textposition,E);ov.extendFlat(_.layout,{"text-size":n.textfont.size,"text-anchor":S.anchor,"text-offset":S.offset,"text-font":HHe(n)}),ov.extendFlat(_.paint,{"text-color":n.textfont.color,"text-opacity":n.opacity})}return b};function a7(e){return{type:e,geojson:o7.makeBlank(),layout:{visibility:"none"},filter:null,paint:{}}}function hXt(e){var t=e[0].trace,r=t.marker,n=t.selectedpoints,i=ov.isArrayOrTypedArray(r.color),a=ov.isArrayOrTypedArray(r.size),o=ov.isArrayOrTypedArray(r.opacity),s;function l(E){return t.opacity*E}function u(E){return E/2}var c;i&&(GHe.hasColorscale(t,"marker")?c=GHe.makeColorScaleFuncFromTrace(r):c=ov.identity);var f;a&&(f=oXt(t));var h;o&&(h=function(E){var S=jHe(E)?+ov.constrain(E,0,1):0;return l(S)});var d=[];for(s=0;s850?s+=" Black":i>750?s+=" Extra Bold":i>650?s+=" Bold":i>550?s+=" Semi Bold":i>450?s+=" Medium":i>350?s+=" Regular":i>250?s+=" Light":i>150?s+=" Extra Light":s+=" Thin"):a.slice(0,2).join(" ")==="Open Sans"?(s="Open Sans",i>750?s+=" Extrabold":i>650?s+=" Bold":i>550?s+=" Semibold":i>350?s+=" Regular":s+=" Light"):a.slice(0,3).join(" ")==="Klokantech Noto Sans"&&(s="Klokantech Noto Sans",a[3]==="CJK"&&(s+=" CJK"),s+=i>500?" Bold":" Regular")),o&&(s+=" Italic"),s==="Open Sans Regular Italic"?s="Open Sans Italic":s==="Open Sans Regular Bold"?s="Open Sans Bold":s==="Open Sans Regular Bold Italic"?s="Open Sans Bold Italic":s==="Klokantech Noto Sans Regular Italic"&&(s="Klokantech Noto Sans Italic"),sXt(s)||(s=r);var l=s.split(", ");return l}});var $He=ye((Qxr,JHe)=>{"use strict";var vXt=Dr(),YHe=ZHe(),C5=wx().traceLayerPrefix,ng={cluster:["cluster","clusterCount","circle"],nonCluster:["fill","line","circle","symbol"]};function KHe(e,t,r,n){this.type="scattermap",this.subplot=e,this.uid=t,this.clusterEnabled=r,this.isHidden=n,this.sourceIds={fill:"source-"+t+"-fill",line:"source-"+t+"-line",circle:"source-"+t+"-circle",symbol:"source-"+t+"-symbol",cluster:"source-"+t+"-circle",clusterCount:"source-"+t+"-circle"},this.layerIds={fill:C5+t+"-fill",line:C5+t+"-line",circle:C5+t+"-circle",symbol:C5+t+"-symbol",cluster:C5+t+"-cluster",clusterCount:C5+t+"-cluster-count"},this.below=null}var Zk=KHe.prototype;Zk.addSource=function(e,t,r){var n={type:"geojson",data:t.geojson};r&&r.enabled&&vXt.extendFlat(n,{cluster:!0,clusterMaxZoom:r.maxzoom});var i=this.subplot.map.getSource(this.sourceIds[e]);i?i.setData(t.geojson):this.subplot.map.addSource(this.sourceIds[e],n)};Zk.setSourceData=function(e,t){this.subplot.map.getSource(this.sourceIds[e]).setData(t.geojson)};Zk.addLayer=function(e,t,r){var n={type:t.type,id:this.layerIds[e],source:this.sourceIds[e],layout:t.layout,paint:t.paint};t.filter&&(n.filter=t.filter);for(var i=this.layerIds[e],a,o=this.subplot.getMapLayers(),s=0;s=0;L--){var x=S[L];i.removeLayer(u.layerIds[x])}E||i.removeSource(u.sourceIds.circle)}function h(E){for(var S=ng.nonCluster,L=0;L=0;L--){var x=S[L];i.removeLayer(u.layerIds[x]),E||i.removeSource(u.sourceIds[x])}}function v(E){l?f(E):d(E)}function _(E){s?c(E):h(E)}function b(){for(var E=s?ng.cluster:ng.nonCluster,S=0;S=0;n--){var i=r[n];t.removeLayer(this.layerIds[i]),t.removeSource(this.sourceIds[i])}};JHe.exports=function(t,r){var n=r[0].trace,i=n.cluster&&n.cluster.enabled,a=n.visible!==!0,o=new KHe(t,n.uid,i,a),s=YHe(t.gd,r),l=o.below=t.belowLookup["trace-"+n.uid],u,c,f;if(i)for(o.addSource("circle",s.circle,n.cluster),u=0;u{"use strict";var pXt=vf(),kJ=Dr(),gXt=cT(),mXt=kJ.fillText,yXt=fs().BADNUM,_Xt=wx().traceLayerPrefix;function xXt(e,t,r){var n=e.cd,i=n[0].trace,a=e.xa,o=e.ya,s=e.subplot,l=[],u=_Xt+i.uid+"-circle",c=i.cluster&&i.cluster.enabled;if(c){var f=s.map.queryRenderedFeatures(null,{layers:[u]});l=f.map(function(M){return M.id})}var h=t>=0?Math.floor((t+180)/360):Math.ceil((t-180)/360),d=h*360,v=t-d;function _(M){var g=M.lonlat;if(g[0]===yXt||c&&l.indexOf(M.i+1)===-1)return 1/0;var P=kJ.modHalf(g[0],360),T=g[1],z=s.project([P,T]),O=z.x-a.c2p([v,T]),V=z.y-o.c2p([P,r]),G=Math.max(3,M.mrc||0);return Math.max(Math.sqrt(O*O+V*V)-G,1-3/G)}if(pXt.getClosest(n,_,e),e.index!==!1){var b=n[e.index],p=b.lonlat,k=[kJ.modHalf(p[0],360)+d,p[1]],E=a.c2p(k),S=o.c2p(k),L=b.mrc||1;e.x0=E-L,e.x1=E+L,e.y0=S-L,e.y1=S+L;var x={};x[i.subplot]={_subplot:s};var C=i._module.formatLabels(b,i,x);return e.lonLabel=C.lonLabel,e.latLabel=C.latLabel,e.color=gXt(i,b),e.extraText=QHe(i,b,n[0].t.labels),e.hovertemplate=i.hovertemplate,[e]}}function QHe(e,t,r){if(e.hovertemplate)return;var n=t.hi||e.hoverinfo,i=n.split("+"),a=i.indexOf("all")!==-1,o=i.indexOf("lon")!==-1,s=i.indexOf("lat")!==-1,l=t.lonlat,u=[];function c(f){return f+"\xB0"}return a||o&&s?u.push("("+c(l[1])+", "+c(l[0])+")"):o?u.push(r.lon+c(l[0])):s&&u.push(r.lat+c(l[1])),(a||i.indexOf("text")!==-1)&&mXt(t,e,u),u.join("
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ri.fromString(Ba(this.args[0].evaluate(A)));case"resolvedImage":return tn.fromString(Ba(this.args[0].evaluate(A)));default:return Ba(this.args[0].evaluate(A))}}eachChild(A){this.args.forEach(A)}outputDefined(){return this.args.every(A=>A.outputDefined())}}let Wn=["Unknown","Point","LineString","Polygon"];class Ha{constructor(){this.globals=null,this.feature=null,this.featureState=null,this.formattedSection=null,this._parseColorCache={},this.availableImages=null,this.canonical=null}id(){return this.feature&&"id"in this.feature?this.feature.id:null}geometryType(){return this.feature?typeof this.feature.type=="number"?Wn[this.feature.type]:this.feature.type:null}geometry(){return this.feature&&"geometry"in this.feature?this.feature.geometry:null}canonicalID(){return this.canonical}properties(){return this.feature&&this.feature.properties||{}}parseColor(A){let F=this._parseColorCache[A];return F||(F=this._parseColorCache[A]=nr.parse(A)),F}}class vo{constructor(A,F,W=[],re,fe=new 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F=A.value.expression||A.value._styleExpression.expression;if(R.expressionContext==="property"&&R.propertyKey==="text-font"&&!F.outputDefined())return[new cr(R.key,R.value,`Invalid data expression for "${R.propertyKey}". 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F!=="Object"&&(re.$name=F),re}function Na(R){if(Ra(R))return R;if(Array.isArray(R))return R.map(Na);if(typeof R!="object")throw new Error("can't deserialize object of type "+typeof R);let A=Ca(R)||"Object";if(!on[A])throw new Error(`can't deserialize unregistered class ${A}`);let{klass:F}=on[A];if(!F)throw new Error(`can't deserialize unregistered class ${A}`);if(F.deserialize)return F.deserialize(R);let W=Object.create(F.prototype);for(let re of Object.keys(R)){if(re==="$name")continue;let fe=R[re];W[re]=on[A].shallow.indexOf(re)>=0?fe:Na(fe)}return W}class Yn{constructor(){this.first=!0}update(A,F){let W=Math.floor(A);return this.first?(this.first=!1,this.lastIntegerZoom=W,this.lastIntegerZoomTime=0,this.lastZoom=A,this.lastFloorZoom=W,!0):(this.lastFloorZoom>W?(this.lastIntegerZoom=W+1,this.lastIntegerZoomTime=F):this.lastFloorZoomR>=128&&R<=255,"Hangul Jamo":R=>R>=4352&&R<=4607,Khmer:R=>R>=6016&&R<=6143,"General Punctuation":R=>R>=8192&&R<=8303,"Letterlike 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R)if(Ho(A.charCodeAt(0)))return!0;return!1}function bo(R){for(let A of R)if(!as(A.charCodeAt(0)))return!1;return!0}function Xo(R){let A=R.map(F=>{try{return new RegExp(`\\p{sc=${F}}`,"u").source}catch(W){return null}}).filter(F=>F);return new RegExp(A.join("|"),"u")}let Ss=Xo(["Arab","Dupl","Mong","Ougr","Syrc"]);function as(R){return!Ss.test(String.fromCodePoint(R))}let ws=Xo(["Bopo","Hani","Hira","Kana","Kits","Nshu","Tang","Yiii"]);function Ho(R){return!(R!==746&&R!==747&&(R<4352||!(Dn["CJK Compatibility Forms"](R)&&!(R>=65097&&R<=65103)||Dn["CJK Compatibility"](R)||Dn["CJK Strokes"](R)||!(!Dn["CJK Symbols and Punctuation"](R)||R>=12296&&R<=12305||R>=12308&&R<=12319||R===12336)||Dn["Enclosed CJK Letters and Months"](R)||Dn["Ideographic Description Characters"](R)||Dn.Kanbun(R)||Dn.Katakana(R)&&R!==12540||!(!Dn["Halfwidth and Fullwidth 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Ws=Xo(["Adlm","Arab","Armi","Avst","Chrs","Cprt","Egyp","Elym","Gara","Hatr","Hebr","Hung","Khar","Lydi","Mand","Mani","Mend","Merc","Mero","Narb","Nbat","Nkoo","Orkh","Palm","Phli","Phlp","Phnx","Prti","Rohg","Samr","Sarb","Sogo","Syrc","Thaa","Todr","Yezi"]);function Ls(R){return Ws.test(String.fromCodePoint(R))}function va(R,A){return!(!A&&Ls(R)||R>=2304&&R<=3583||R>=3840&&R<=4255||Dn.Khmer(R))}function no(R){for(let A of R)if(Ls(A.charCodeAt(0)))return!0;return!1}let ys=new class{constructor(){this.applyArabicShaping=null,this.processBidirectionalText=null,this.processStyledBidirectionalText=null,this.pluginStatus="unavailable",this.pluginURL=null}setState(R){this.pluginStatus=R.pluginStatus,this.pluginURL=R.pluginURL}getState(){return{pluginStatus:this.pluginStatus,pluginURL:this.pluginURL}}setMethods(R){this.applyArabicShaping=R.applyArabicShaping,this.processBidirectionalText=R.processBidirectionalText,this.processStyledBidirectionalText=R.processStyledBidirectionalText}isParsed(){return this.applyArabicShaping!=null&&this.processBidirectionalText!=null&&this.processStyledBidirectionalText!=null}getPluginURL(){return this.pluginURL}getRTLTextPluginStatus(){return this.pluginStatus}};class rs{constructor(A,F){this.zoom=A,F?(this.now=F.now,this.fadeDuration=F.fadeDuration,this.zoomHistory=F.zoomHistory,this.transition=F.transition):(this.now=0,this.fadeDuration=0,this.zoomHistory=new Yn,this.transition={})}isSupportedScript(A){return function(F,W){for(let re of F)if(!va(re.charCodeAt(0),W))return!1;return!0}(A,ys.getRTLTextPluginStatus()==="loaded")}crossFadingFactor(){return this.fadeDuration===0?1:Math.min((this.now-this.zoomHistory.lastIntegerZoomTime)/this.fadeDuration,1)}getCrossfadeParameters(){let A=this.zoom,F=A-Math.floor(A),W=this.crossFadingFactor();return A>this.zoomHistory.lastIntegerZoom?{fromScale:2,toScale:1,t:F+(1-F)*W}:{fromScale:.5,toScale:1,t:1-(1-W)*F}}}class $l{constructor(A,F){this.property=A,this.value=F,this.expression=function(W,re){if(jf(W))return new nl(W,re);if(Dc(W)){let fe=_u(W,re);if(fe.result==="error")throw new Error(fe.value.map(pe=>`${pe.key}: ${pe.message}`).join(", "));return fe.value}{let fe=W;return re.type==="color"&&typeof W=="string"?fe=nr.parse(W):re.type!=="padding"||typeof W!="number"&&!Array.isArray(W)?re.type==="variableAnchorOffsetCollection"&&Array.isArray(W)&&(fe=$i.parse(W)):fe=Qr.parse(W),{kind:"constant",evaluate:()=>fe}}}(F===void 0?A.specification.default:F,A.specification)}isDataDriven(){return this.expression.kind==="source"||this.expression.kind==="composite"}possiblyEvaluate(A,F,W){return this.property.possiblyEvaluate(this,A,F,W)}}class Cu{constructor(A){this.property=A,this.value=new $l(A,void 0)}transitioned(A,F){return new Nc(this.property,this.value,F,L({},A.transition,this.transition),A.now)}untransitioned(){return new Nc(this.property,this.value,null,{},0)}}class Yu{constructor(A){this._properties=A,this._values=Object.create(A.defaultTransitionablePropertyValues)}getValue(A){return g(this._values[A].value.value)}setValue(A,F){Object.prototype.hasOwnProperty.call(this._values,A)||(this._values[A]=new Cu(this._values[A].property)),this._values[A].value=new $l(this._values[A].property,F===null?void 0:g(F))}getTransition(A){return g(this._values[A].transition)}setTransition(A,F){Object.prototype.hasOwnProperty.call(this._values,A)||(this._values[A]=new Cu(this._values[A].property)),this._values[A].transition=g(F)||void 0}serialize(){let A={};for(let F of Object.keys(this._values)){let W=this.getValue(F);W!==void 0&&(A[F]=W);let re=this.getTransition(F);re!==void 0&&(A[`${F}-transition`]=re)}return A}transitioned(A,F){let W=new pu(this._properties);for(let re of Object.keys(this._values))W._values[re]=this._values[re].transitioned(A,F._values[re]);return W}untransitioned(){let A=new pu(this._properties);for(let F of Object.keys(this._values))A._values[F]=this._values[F].untransitioned();return A}}class Nc{constructor(A,F,W,re,fe){this.property=A,this.value=F,this.begin=fe+re.delay||0,this.end=this.begin+re.duration||0,A.specification.transition&&(re.delay||re.duration)&&(this.prior=W)}possiblyEvaluate(A,F,W){let re=A.now||0,fe=this.value.possiblyEvaluate(A,F,W),pe=this.prior;if(pe){if(re>this.end)return this.prior=null,fe;if(this.value.isDataDriven())return this.prior=null,fe;if(re=1)return 1;let ct=Ke*Ke,Lt=ct*Ke;return 4*(Ke<.5?Lt:3*(Ke-ct)+Lt-.75)}(ze))}}return fe}}class pu{constructor(A){this._properties=A,this._values=Object.create(A.defaultTransitioningPropertyValues)}possiblyEvaluate(A,F,W){let re=new Ac(this._properties);for(let fe of Object.keys(this._values))re._values[fe]=this._values[fe].possiblyEvaluate(A,F,W);return re}hasTransition(){for(let A of Object.keys(this._values))if(this._values[A].prior)return!0;return!1}}class Uc{constructor(A){this._properties=A,this._values=Object.create(A.defaultPropertyValues)}hasValue(A){return this._values[A].value!==void 0}getValue(A){return g(this._values[A].value)}setValue(A,F){this._values[A]=new $l(this._values[A].property,F===null?void 0:g(F))}serialize(){let A={};for(let F of Object.keys(this._values)){let W=this.getValue(F);W!==void 0&&(A[F]=W)}return A}possiblyEvaluate(A,F,W){let re=new Ac(this._properties);for(let fe of Object.keys(this._values))re._values[fe]=this._values[fe].possiblyEvaluate(A,F,W);return re}}class xu{constructor(A,F,W){this.property=A,this.value=F,this.parameters=W}isConstant(){return this.value.kind==="constant"}constantOr(A){return this.value.kind==="constant"?this.value.value:A}evaluate(A,F,W,re){return this.property.evaluate(this.value,this.parameters,A,F,W,re)}}class Ac{constructor(A){this._properties=A,this._values=Object.create(A.defaultPossiblyEvaluatedValues)}get(A){return this._values[A]}}class Ua{constructor(A){this.specification=A}possiblyEvaluate(A,F){if(A.isDataDriven())throw new Error("Value should not be data driven");return A.expression.evaluate(F)}interpolate(A,F,W){let re=Lo[this.specification.type];return re?re(A,F,W):A}}class oo{constructor(A,F){this.specification=A,this.overrides=F}possiblyEvaluate(A,F,W,re){return new xu(this,A.expression.kind==="constant"||A.expression.kind==="camera"?{kind:"constant",value:A.expression.evaluate(F,null,{},W,re)}:A.expression,F)}interpolate(A,F,W){if(A.value.kind!=="constant"||F.value.kind!=="constant")return A;if(A.value.value===void 0||F.value.value===void 0)return new xu(this,{kind:"constant",value:void 0},A.parameters);let re=Lo[this.specification.type];if(re){let fe=re(A.value.value,F.value.value,W);return new xu(this,{kind:"constant",value:fe},A.parameters)}return A}evaluate(A,F,W,re,fe,pe){return A.kind==="constant"?A.value:A.evaluate(F,W,re,fe,pe)}}class Vc extends oo{possiblyEvaluate(A,F,W,re){if(A.value===void 0)return new xu(this,{kind:"constant",value:void 0},F);if(A.expression.kind==="constant"){let fe=A.expression.evaluate(F,null,{},W,re),pe=A.property.specification.type==="resolvedImage"&&typeof fe!="string"?fe.name:fe,ze=this._calculate(pe,pe,pe,F);return new xu(this,{kind:"constant",value:ze},F)}if(A.expression.kind==="camera"){let fe=this._calculate(A.expression.evaluate({zoom:F.zoom-1}),A.expression.evaluate({zoom:F.zoom}),A.expression.evaluate({zoom:F.zoom+1}),F);return new xu(this,{kind:"constant",value:fe},F)}return new xu(this,A.expression,F)}evaluate(A,F,W,re,fe,pe){if(A.kind==="source"){let ze=A.evaluate(F,W,re,fe,pe);return this._calculate(ze,ze,ze,F)}return A.kind==="composite"?this._calculate(A.evaluate({zoom:Math.floor(F.zoom)-1},W,re),A.evaluate({zoom:Math.floor(F.zoom)},W,re),A.evaluate({zoom:Math.floor(F.zoom)+1},W,re),F):A.value}_calculate(A,F,W,re){return re.zoom>re.zoomHistory.lastIntegerZoom?{from:A,to:F}:{from:W,to:F}}interpolate(A){return A}}class hc{constructor(A){this.specification=A}possiblyEvaluate(A,F,W,re){if(A.value!==void 0){if(A.expression.kind==="constant"){let fe=A.expression.evaluate(F,null,{},W,re);return this._calculate(fe,fe,fe,F)}return this._calculate(A.expression.evaluate(new rs(Math.floor(F.zoom-1),F)),A.expression.evaluate(new rs(Math.floor(F.zoom),F)),A.expression.evaluate(new rs(Math.floor(F.zoom+1),F)),F)}}_calculate(A,F,W,re){return re.zoom>re.zoomHistory.lastIntegerZoom?{from:A,to:F}:{from:W,to:F}}interpolate(A){return A}}class Ku{constructor(A){this.specification=A}possiblyEvaluate(A,F,W,re){return!!A.expression.evaluate(F,null,{},W,re)}interpolate(){return!1}}class ue{constructor(A){this.properties=A,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[];for(let F in A){let W=A[F];W.specification.overridable&&this.overridableProperties.push(F);let re=this.defaultPropertyValues[F]=new $l(W,void 0),fe=this.defaultTransitionablePropertyValues[F]=new Cu(W);this.defaultTransitioningPropertyValues[F]=fe.untransitioned(),this.defaultPossiblyEvaluatedValues[F]=re.possiblyEvaluate({})}}}Fi("DataDrivenProperty",oo),Fi("DataConstantProperty",Ua),Fi("CrossFadedDataDrivenProperty",Vc),Fi("CrossFadedProperty",hc),Fi("ColorRampProperty",Ku);let w="-transition";class B extends Re{constructor(A,F){if(super(),this.id=A.id,this.type=A.type,this._featureFilter={filter:()=>!0,needGeometry:!1},A.type!=="custom"&&(this.metadata=A.metadata,this.minzoom=A.minzoom,this.maxzoom=A.maxzoom,A.type!=="background"&&(this.source=A.source,this.sourceLayer=A["source-layer"],this.filter=A.filter),F.layout&&(this._unevaluatedLayout=new Uc(F.layout)),F.paint)){this._transitionablePaint=new Yu(F.paint);for(let W in A.paint)this.setPaintProperty(W,A.paint[W],{validate:!1});for(let W in A.layout)this.setLayoutProperty(W,A.layout[W],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned(),this.paint=new Ac(F.paint)}}getCrossfadeParameters(){return this._crossfadeParameters}getLayoutProperty(A){return A==="visibility"?this.visibility:this._unevaluatedLayout.getValue(A)}setLayoutProperty(A,F,W={}){F!=null&&this._validate(Nn,`layers.${this.id}.layout.${A}`,A,F,W)||(A!=="visibility"?this._unevaluatedLayout.setValue(A,F):this.visibility=F)}getPaintProperty(A){return A.endsWith(w)?this._transitionablePaint.getTransition(A.slice(0,-11)):this._transitionablePaint.getValue(A)}setPaintProperty(A,F,W={}){if(F!=null&&this._validate(wn,`layers.${this.id}.paint.${A}`,A,F,W))return!1;if(A.endsWith(w))return this._transitionablePaint.setTransition(A.slice(0,-11),F||void 0),!1;{let re=this._transitionablePaint._values[A],fe=re.property.specification["property-type"]==="cross-faded-data-driven",pe=re.value.isDataDriven(),ze=re.value;this._transitionablePaint.setValue(A,F),this._handleSpecialPaintPropertyUpdate(A);let Ke=this._transitionablePaint._values[A].value;return Ke.isDataDriven()||pe||fe||this._handleOverridablePaintPropertyUpdate(A,ze,Ke)}}_handleSpecialPaintPropertyUpdate(A){}_handleOverridablePaintPropertyUpdate(A,F,W){return!1}isHidden(A){return!!(this.minzoom&&A=this.maxzoom)||this.visibility==="none"}updateTransitions(A){this._transitioningPaint=this._transitionablePaint.transitioned(A,this._transitioningPaint)}hasTransition(){return this._transitioningPaint.hasTransition()}recalculate(A,F){A.getCrossfadeParameters&&(this._crossfadeParameters=A.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(A,void 0,F)),this.paint=this._transitioningPaint.possiblyEvaluate(A,void 0,F)}serialize(){let A={id:this.id,type:this.type,source:this.source,"source-layer":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(A.layout=A.layout||{},A.layout.visibility=this.visibility),M(A,(F,W)=>!(F===void 0||W==="layout"&&!Object.keys(F).length||W==="paint"&&!Object.keys(F).length))}_validate(A,F,W,re,fe={}){return(!fe||fe.validate!==!1)&&Yi(this,A.call(ki,{key:F,layerType:this.type,objectKey:W,value:re,styleSpec:ce,style:{glyphs:!0,sprite:!0}}))}is3D(){return!1}isTileClipped(){return!1}hasOffscreenPass(){return!1}resize(){}isStateDependent(){for(let A in this.paint._values){let F=this.paint.get(A);if(F instanceof xu&&Nl(F.property.specification)&&(F.value.kind==="source"||F.value.kind==="composite")&&F.value.isStateDependent)return!0}return!1}}let Q={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array};class ee{constructor(A,F){this._structArray=A,this._pos1=F*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8}}class le{constructor(){this.isTransferred=!1,this.capacity=-1,this.resize(0)}static serialize(A,F){return A._trim(),F&&(A.isTransferred=!0,F.push(A.arrayBuffer)),{length:A.length,arrayBuffer:A.arrayBuffer}}static deserialize(A){let F=Object.create(this.prototype);return F.arrayBuffer=A.arrayBuffer,F.length=A.length,F.capacity=A.arrayBuffer.byteLength/F.bytesPerElement,F._refreshViews(),F}_trim(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())}clear(){this.length=0}resize(A){this.reserve(A),this.length=A}reserve(A){if(A>this.capacity){this.capacity=Math.max(A,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);let F=this.uint8;this._refreshViews(),F&&this.uint8.set(F)}}_refreshViews(){throw new Error("_refreshViews() must be implemented by each concrete StructArray layout")}}function qe(R,A=1){let F=0,W=0;return{members:R.map(re=>{let fe=Q[re.type].BYTES_PER_ELEMENT,pe=F=Xe(F,Math.max(A,fe)),ze=re.components||1;return W=Math.max(W,fe),F+=fe*ze,{name:re.name,type:re.type,components:ze,offset:pe}}),size:Xe(F,Math.max(W,A)),alignment:A}}function Xe(R,A){return Math.ceil(R/A)*A}class ot extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F){let W=this.length;return this.resize(W+1),this.emplace(W,A,F)}emplace(A,F,W){let re=2*A;return this.int16[re+0]=F,this.int16[re+1]=W,A}}ot.prototype.bytesPerElement=4,Fi("StructArrayLayout2i4",ot);class Tt extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F,W){let re=this.length;return this.resize(re+1),this.emplace(re,A,F,W)}emplace(A,F,W,re){let fe=3*A;return this.int16[fe+0]=F,this.int16[fe+1]=W,this.int16[fe+2]=re,A}}Tt.prototype.bytesPerElement=6,Fi("StructArrayLayout3i6",Tt);class Yt extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F,W,re){let fe=this.length;return this.resize(fe+1),this.emplace(fe,A,F,W,re)}emplace(A,F,W,re,fe){let pe=4*A;return this.int16[pe+0]=F,this.int16[pe+1]=W,this.int16[pe+2]=re,this.int16[pe+3]=fe,A}}Yt.prototype.bytesPerElement=8,Fi("StructArrayLayout4i8",Yt);class Kt extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F,W,re,fe,pe){let ze=this.length;return this.resize(ze+1),this.emplace(ze,A,F,W,re,fe,pe)}emplace(A,F,W,re,fe,pe,ze){let Ke=6*A;return this.int16[Ke+0]=F,this.int16[Ke+1]=W,this.int16[Ke+2]=re,this.int16[Ke+3]=fe,this.int16[Ke+4]=pe,this.int16[Ke+5]=ze,A}}Kt.prototype.bytesPerElement=12,Fi("StructArrayLayout2i4i12",Kt);class xr extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F,W,re,fe,pe){let ze=this.length;return this.resize(ze+1),this.emplace(ze,A,F,W,re,fe,pe)}emplace(A,F,W,re,fe,pe,ze){let Ke=4*A,ct=8*A;return this.int16[Ke+0]=F,this.int16[Ke+1]=W,this.uint8[ct+4]=re,this.uint8[ct+5]=fe,this.uint8[ct+6]=pe,this.uint8[ct+7]=ze,A}}xr.prototype.bytesPerElement=8,Fi("StructArrayLayout2i4ub8",xr);class Ir extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(A,F){let W=this.length;return this.resize(W+1),this.emplace(W,A,F)}emplace(A,F,W){let re=2*A;return this.float32[re+0]=F,this.float32[re+1]=W,A}}Ir.prototype.bytesPerElement=8,Fi("StructArrayLayout2f8",Ir);class ve extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(A,F,W,re,fe,pe,ze,Ke,ct,Lt){let $t=this.length;return this.resize($t+1),this.emplace($t,A,F,W,re,fe,pe,ze,Ke,ct,Lt)}emplace(A,F,W,re,fe,pe,ze,Ke,ct,Lt,$t){let fr=10*A;return this.uint16[fr+0]=F,this.uint16[fr+1]=W,this.uint16[fr+2]=re,this.uint16[fr+3]=fe,this.uint16[fr+4]=pe,this.uint16[fr+5]=ze,this.uint16[fr+6]=Ke,this.uint16[fr+7]=ct,this.uint16[fr+8]=Lt,this.uint16[fr+9]=$t,A}}ve.prototype.bytesPerElement=20,Fi("StructArrayLayout10ui20",ve);class be extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(A,F,W,re,fe,pe,ze,Ke,ct,Lt,$t,fr){let mr=this.length;return this.resize(mr+1),this.emplace(mr,A,F,W,re,fe,pe,ze,Ke,ct,Lt,$t,fr)}emplace(A,F,W,re,fe,pe,ze,Ke,ct,Lt,$t,fr,mr){let Pr=12*A;return this.int16[Pr+0]=F,this.int16[Pr+1]=W,this.int16[Pr+2]=re,this.int16[Pr+3]=fe,this.uint16[Pr+4]=pe,this.uint16[Pr+5]=ze,this.uint16[Pr+6]=Ke,this.uint16[Pr+7]=ct,this.int16[Pr+8]=Lt,this.int16[Pr+9]=$t,this.int16[Pr+10]=fr,this.int16[Pr+11]=mr,A}}be.prototype.bytesPerElement=24,Fi("StructArrayLayout4i4ui4i24",be);class De extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(A,F,W){let re=this.length;return this.resize(re+1),this.emplace(re,A,F,W)}emplace(A,F,W,re){let fe=3*A;return this.float32[fe+0]=F,this.float32[fe+1]=W,this.float32[fe+2]=re,A}}De.prototype.bytesPerElement=12,Fi("StructArrayLayout3f12",De);class Be extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)}emplaceBack(A){let F=this.length;return this.resize(F+1),this.emplace(F,A)}emplace(A,F){return this.uint32[1*A+0]=F,A}}Be.prototype.bytesPerElement=4,Fi("StructArrayLayout1ul4",Be);class et extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(A,F,W,re,fe,pe,ze,Ke,ct){let Lt=this.length;return this.resize(Lt+1),this.emplace(Lt,A,F,W,re,fe,pe,ze,Ke,ct)}emplace(A,F,W,re,fe,pe,ze,Ke,ct,Lt){let $t=10*A,fr=5*A;return this.int16[$t+0]=F,this.int16[$t+1]=W,this.int16[$t+2]=re,this.int16[$t+3]=fe,this.int16[$t+4]=pe,this.int16[$t+5]=ze,this.uint32[fr+3]=Ke,this.uint16[$t+8]=ct,this.uint16[$t+9]=Lt,A}}et.prototype.bytesPerElement=20,Fi("StructArrayLayout6i1ul2ui20",et);class We extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F,W,re,fe,pe){let ze=this.length;return this.resize(ze+1),this.emplace(ze,A,F,W,re,fe,pe)}emplace(A,F,W,re,fe,pe,ze){let Ke=6*A;return this.int16[Ke+0]=F,this.int16[Ke+1]=W,this.int16[Ke+2]=re,this.int16[Ke+3]=fe,this.int16[Ke+4]=pe,this.int16[Ke+5]=ze,A}}We.prototype.bytesPerElement=12,Fi("StructArrayLayout2i2i2i12",We);class it extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F,W,re,fe){let pe=this.length;return this.resize(pe+1),this.emplace(pe,A,F,W,re,fe)}emplace(A,F,W,re,fe,pe){let ze=4*A,Ke=8*A;return this.float32[ze+0]=F,this.float32[ze+1]=W,this.float32[ze+2]=re,this.int16[Ke+6]=fe,this.int16[Ke+7]=pe,A}}it.prototype.bytesPerElement=16,Fi("StructArrayLayout2f1f2i16",it);class Ft extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(A,F,W,re,fe,pe){let ze=this.length;return this.resize(ze+1),this.emplace(ze,A,F,W,re,fe,pe)}emplace(A,F,W,re,fe,pe,ze){let Ke=16*A,ct=4*A,Lt=8*A;return this.uint8[Ke+0]=F,this.uint8[Ke+1]=W,this.float32[ct+1]=re,this.float32[ct+2]=fe,this.int16[Lt+6]=pe,this.int16[Lt+7]=ze,A}}Ft.prototype.bytesPerElement=16,Fi("StructArrayLayout2ub2f2i16",Ft);class Ht extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(A,F,W){let re=this.length;return this.resize(re+1),this.emplace(re,A,F,W)}emplace(A,F,W,re){let fe=3*A;return this.uint16[fe+0]=F,this.uint16[fe+1]=W,this.uint16[fe+2]=re,A}}Ht.prototype.bytesPerElement=6,Fi("StructArrayLayout3ui6",Ht);class tr extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(A,F,W,re,fe,pe,ze,Ke,ct,Lt,$t,fr,mr,Pr,zr,ui,yi){let vn=this.length;return this.resize(vn+1),this.emplace(vn,A,F,W,re,fe,pe,ze,Ke,ct,Lt,$t,fr,mr,Pr,zr,ui,yi)}emplace(A,F,W,re,fe,pe,ze,Ke,ct,Lt,$t,fr,mr,Pr,zr,ui,yi,vn){let zi=24*A,un=12*A,Tn=48*A;return this.int16[zi+0]=F,this.int16[zi+1]=W,this.uint16[zi+2]=re,this.uint16[zi+3]=fe,this.uint32[un+2]=pe,this.uint32[un+3]=ze,this.uint32[un+4]=Ke,this.uint16[zi+10]=ct,this.uint16[zi+11]=Lt,this.uint16[zi+12]=$t,this.float32[un+7]=fr,this.float32[un+8]=mr,this.uint8[Tn+36]=Pr,this.uint8[Tn+37]=zr,this.uint8[Tn+38]=ui,this.uint32[un+10]=yi,this.int16[zi+22]=vn,A}}tr.prototype.bytesPerElement=48,Fi("StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48",tr);class dr extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(A,F,W,re,fe,pe,ze,Ke,ct,Lt,$t,fr,mr,Pr,zr,ui,yi,vn,zi,un,Tn,pa,ro,Vo,Xa,sa,Mo,fo){let lo=this.length;return this.resize(lo+1),this.emplace(lo,A,F,W,re,fe,pe,ze,Ke,ct,Lt,$t,fr,mr,Pr,zr,ui,yi,vn,zi,un,Tn,pa,ro,Vo,Xa,sa,Mo,fo)}emplace(A,F,W,re,fe,pe,ze,Ke,ct,Lt,$t,fr,mr,Pr,zr,ui,yi,vn,zi,un,Tn,pa,ro,Vo,Xa,sa,Mo,fo,lo){let Xn=32*A,Ro=16*A;return this.int16[Xn+0]=F,this.int16[Xn+1]=W,this.int16[Xn+2]=re,this.int16[Xn+3]=fe,this.int16[Xn+4]=pe,this.int16[Xn+5]=ze,this.int16[Xn+6]=Ke,this.int16[Xn+7]=ct,this.uint16[Xn+8]=Lt,this.uint16[Xn+9]=$t,this.uint16[Xn+10]=fr,this.uint16[Xn+11]=mr,this.uint16[Xn+12]=Pr,this.uint16[Xn+13]=zr,this.uint16[Xn+14]=ui,this.uint16[Xn+15]=yi,this.uint16[Xn+16]=vn,this.uint16[Xn+17]=zi,this.uint16[Xn+18]=un,this.uint16[Xn+19]=Tn,this.uint16[Xn+20]=pa,this.uint16[Xn+21]=ro,this.uint16[Xn+22]=Vo,this.uint32[Ro+12]=Xa,this.float32[Ro+13]=sa,this.float32[Ro+14]=Mo,this.uint16[Xn+30]=fo,this.uint16[Xn+31]=lo,A}}dr.prototype.bytesPerElement=64,Fi("StructArrayLayout8i15ui1ul2f2ui64",dr);class Sr extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(A){let F=this.length;return this.resize(F+1),this.emplace(F,A)}emplace(A,F){return this.float32[1*A+0]=F,A}}Sr.prototype.bytesPerElement=4,Fi("StructArrayLayout1f4",Sr);class Or extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(A,F,W){let re=this.length;return this.resize(re+1),this.emplace(re,A,F,W)}emplace(A,F,W,re){let fe=3*A;return this.uint16[6*A+0]=F,this.float32[fe+1]=W,this.float32[fe+2]=re,A}}Or.prototype.bytesPerElement=12,Fi("StructArrayLayout1ui2f12",Or);class Wr extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(A,F,W){let re=this.length;return this.resize(re+1),this.emplace(re,A,F,W)}emplace(A,F,W,re){let fe=4*A;return this.uint32[2*A+0]=F,this.uint16[fe+2]=W,this.uint16[fe+3]=re,A}}Wr.prototype.bytesPerElement=8,Fi("StructArrayLayout1ul2ui8",Wr);class ni extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(A,F){let W=this.length;return this.resize(W+1),this.emplace(W,A,F)}emplace(A,F,W){let re=2*A;return this.uint16[re+0]=F,this.uint16[re+1]=W,A}}ni.prototype.bytesPerElement=4,Fi("StructArrayLayout2ui4",ni);class Pi extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(A){let F=this.length;return this.resize(F+1),this.emplace(F,A)}emplace(A,F){return this.uint16[1*A+0]=F,A}}Pi.prototype.bytesPerElement=2,Fi("StructArrayLayout1ui2",Pi);class cn extends le{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(A,F,W,re){let fe=this.length;return this.resize(fe+1),this.emplace(fe,A,F,W,re)}emplace(A,F,W,re,fe){let pe=4*A;return this.float32[pe+0]=F,this.float32[pe+1]=W,this.float32[pe+2]=re,this.float32[pe+3]=fe,A}}cn.prototype.bytesPerElement=16,Fi("StructArrayLayout4f16",cn);class ln extends ee{get anchorPointX(){return this._structArray.int16[this._pos2+0]}get anchorPointY(){return this._structArray.int16[this._pos2+1]}get x1(){return this._structArray.int16[this._pos2+2]}get y1(){return this._structArray.int16[this._pos2+3]}get x2(){return this._structArray.int16[this._pos2+4]}get y2(){return this._structArray.int16[this._pos2+5]}get featureIndex(){return this._structArray.uint32[this._pos4+3]}get sourceLayerIndex(){return this._structArray.uint16[this._pos2+8]}get bucketIndex(){return this._structArray.uint16[this._pos2+9]}get anchorPoint(){return new u(this.anchorPointX,this.anchorPointY)}}ln.prototype.size=20;class Cn extends et{get(A){return new ln(this,A)}}Fi("CollisionBoxArray",Cn);class Kn extends ee{get anchorX(){return this._structArray.int16[this._pos2+0]}get anchorY(){return this._structArray.int16[this._pos2+1]}get glyphStartIndex(){return this._structArray.uint16[this._pos2+2]}get numGlyphs(){return this._structArray.uint16[this._pos2+3]}get vertexStartIndex(){return this._structArray.uint32[this._pos4+2]}get lineStartIndex(){return this._structArray.uint32[this._pos4+3]}get lineLength(){return this._structArray.uint32[this._pos4+4]}get segment(){return this._structArray.uint16[this._pos2+10]}get lowerSize(){return this._structArray.uint16[this._pos2+11]}get upperSize(){return this._structArray.uint16[this._pos2+12]}get lineOffsetX(){return this._structArray.float32[this._pos4+7]}get lineOffsetY(){return this._structArray.float32[this._pos4+8]}get writingMode(){return this._structArray.uint8[this._pos1+36]}get placedOrientation(){return this._structArray.uint8[this._pos1+37]}set placedOrientation(A){this._structArray.uint8[this._pos1+37]=A}get hidden(){return this._structArray.uint8[this._pos1+38]}set hidden(A){this._structArray.uint8[this._pos1+38]=A}get crossTileID(){return this._structArray.uint32[this._pos4+10]}set crossTileID(A){this._structArray.uint32[this._pos4+10]=A}get associatedIconIndex(){return this._structArray.int16[this._pos2+22]}}Kn.prototype.size=48;class Ta extends tr{get(A){return new Kn(this,A)}}Fi("PlacedSymbolArray",Ta);class fa extends ee{get anchorX(){return this._structArray.int16[this._pos2+0]}get anchorY(){return this._structArray.int16[this._pos2+1]}get rightJustifiedTextSymbolIndex(){return this._structArray.int16[this._pos2+2]}get centerJustifiedTextSymbolIndex(){return this._structArray.int16[this._pos2+3]}get leftJustifiedTextSymbolIndex(){return this._structArray.int16[this._pos2+4]}get verticalPlacedTextSymbolIndex(){return this._structArray.int16[this._pos2+5]}get placedIconSymbolIndex(){return this._structArray.int16[this._pos2+6]}get verticalPlacedIconSymbolIndex(){return this._structArray.int16[this._pos2+7]}get key(){return this._structArray.uint16[this._pos2+8]}get textBoxStartIndex(){return this._structArray.uint16[this._pos2+9]}get textBoxEndIndex(){return this._structArray.uint16[this._pos2+10]}get verticalTextBoxStartIndex(){return this._structArray.uint16[this._pos2+11]}get verticalTextBoxEndIndex(){return this._structArray.uint16[this._pos2+12]}get iconBoxStartIndex(){return this._structArray.uint16[this._pos2+13]}get iconBoxEndIndex(){return this._structArray.uint16[this._pos2+14]}get verticalIconBoxStartIndex(){return this._structArray.uint16[this._pos2+15]}get verticalIconBoxEndIndex(){return this._structArray.uint16[this._pos2+16]}get featureIndex(){return this._structArray.uint16[this._pos2+17]}get numHorizontalGlyphVertices(){return this._structArray.uint16[this._pos2+18]}get numVerticalGlyphVertices(){return this._structArray.uint16[this._pos2+19]}get numIconVertices(){return this._structArray.uint16[this._pos2+20]}get numVerticalIconVertices(){return this._structArray.uint16[this._pos2+21]}get useRuntimeCollisionCircles(){return this._structArray.uint16[this._pos2+22]}get crossTileID(){return this._structArray.uint32[this._pos4+12]}set crossTileID(A){this._structArray.uint32[this._pos4+12]=A}get textBoxScale(){return this._structArray.float32[this._pos4+13]}get collisionCircleDiameter(){return this._structArray.float32[this._pos4+14]}get textAnchorOffsetStartIndex(){return this._structArray.uint16[this._pos2+30]}get textAnchorOffsetEndIndex(){return this._structArray.uint16[this._pos2+31]}}fa.prototype.size=64;class $a extends dr{get(A){return new fa(this,A)}}Fi("SymbolInstanceArray",$a);class Co extends Sr{getoffsetX(A){return this.float32[1*A+0]}}Fi("GlyphOffsetArray",Co);class Qa extends Tt{getx(A){return this.int16[3*A+0]}gety(A){return this.int16[3*A+1]}gettileUnitDistanceFromAnchor(A){return this.int16[3*A+2]}}Fi("SymbolLineVertexArray",Qa);class mo extends ee{get textAnchor(){return this._structArray.uint16[this._pos2+0]}get textOffset0(){return this._structArray.float32[this._pos4+1]}get textOffset1(){return this._structArray.float32[this._pos4+2]}}mo.prototype.size=12;class Bo extends Or{get(A){return new mo(this,A)}}Fi("TextAnchorOffsetArray",Bo);class Ps extends ee{get featureIndex(){return this._structArray.uint32[this._pos4+0]}get sourceLayerIndex(){return this._structArray.uint16[this._pos2+2]}get bucketIndex(){return this._structArray.uint16[this._pos2+3]}}Ps.prototype.size=8;class Ts extends Wr{get(A){return new Ps(this,A)}}Fi("FeatureIndexArray",Ts);class wo extends ot{}class To extends ot{}class hl extends ot{}class Ul extends Kt{}class Lu extends xr{}class au extends Ir{}class Js extends ve{}class Ql extends be{}class dc extends De{}class Tl extends Be{}class Al extends We{}class X extends Ft{}class se extends Ht{}class Te extends ni{}let Ne=qe([{name:"a_pos",components:2,type:"Int16"}],4),{members:He}=Ne;class Ye{constructor(A=[]){this.segments=A}prepareSegment(A,F,W,re){let fe=this.segments[this.segments.length-1];return A>Ye.MAX_VERTEX_ARRAY_LENGTH&&T(`Max vertices per segment is ${Ye.MAX_VERTEX_ARRAY_LENGTH}: bucket requested ${A}`),(!fe||fe.vertexLength+A>Ye.MAX_VERTEX_ARRAY_LENGTH||fe.sortKey!==re)&&(fe={vertexOffset:F.length,primitiveOffset:W.length,vertexLength:0,primitiveLength:0},re!==void 0&&(fe.sortKey=re),this.segments.push(fe)),fe}get(){return this.segments}destroy(){for(let A of this.segments)for(let F in A.vaos)A.vaos[F].destroy()}static simpleSegment(A,F,W,re){return new Ye([{vertexOffset:A,primitiveOffset:F,vertexLength:W,primitiveLength:re,vaos:{},sortKey:0}])}}function kt(R,A){return 256*(R=E(Math.floor(R),0,255))+E(Math.floor(A),0,255)}Ye.MAX_VERTEX_ARRAY_LENGTH=Math.pow(2,16)-1,Fi("SegmentVector",Ye);let nt=qe([{name:"a_pattern_from",components:4,type:"Uint16"},{name:"a_pattern_to",components:4,type:"Uint16"},{name:"a_pixel_ratio_from",components:1,type:"Uint16"},{name:"a_pixel_ratio_to",components:1,type:"Uint16"}]);var jt={exports:{}},gr={exports:{}};gr.exports=function(R,A){var F,W,re,fe,pe,ze,Ke,ct;for(W=R.length-(F=3&R.length),re=A,pe=3432918353,ze=461845907,ct=0;ct>>16)*pe&65535)<<16)&4294967295)<<15|Ke>>>17))*ze+(((Ke>>>16)*ze&65535)<<16)&4294967295)<<13|re>>>19))+((5*(re>>>16)&65535)<<16)&4294967295))+((58964+(fe>>>16)&65535)<<16);switch(Ke=0,F){case 3:Ke^=(255&R.charCodeAt(ct+2))<<16;case 2:Ke^=(255&R.charCodeAt(ct+1))<<8;case 1:re^=Ke=(65535&(Ke=(Ke=(65535&(Ke^=255&R.charCodeAt(ct)))*pe+(((Ke>>>16)*pe&65535)<<16)&4294967295)<<15|Ke>>>17))*ze+(((Ke>>>16)*ze&65535)<<16)&4294967295}return re^=R.length,re=2246822507*(65535&(re^=re>>>16))+((2246822507*(re>>>16)&65535)<<16)&4294967295,re=3266489909*(65535&(re^=re>>>13))+((3266489909*(re>>>16)&65535)<<16)&4294967295,(re^=re>>>16)>>>0};var yr=gr.exports,Hr={exports:{}};Hr.exports=function(R,A){for(var F,W=R.length,re=A^W,fe=0;W>=4;)F=1540483477*(65535&(F=255&R.charCodeAt(fe)|(255&R.charCodeAt(++fe))<<8|(255&R.charCodeAt(++fe))<<16|(255&R.charCodeAt(++fe))<<24))+((1540483477*(F>>>16)&65535)<<16),re=1540483477*(65535&re)+((1540483477*(re>>>16)&65535)<<16)^(F=1540483477*(65535&(F^=F>>>24))+((1540483477*(F>>>16)&65535)<<16)),W-=4,++fe;switch(W){case 3:re^=(255&R.charCodeAt(fe+2))<<16;case 2:re^=(255&R.charCodeAt(fe+1))<<8;case 1:re=1540483477*(65535&(re^=255&R.charCodeAt(fe)))+((1540483477*(re>>>16)&65535)<<16)}return re=1540483477*(65535&(re^=re>>>13))+((1540483477*(re>>>16)&65535)<<16),(re^=re>>>15)>>>0};var qr=yr,_i=Hr.exports;jt.exports=qr,jt.exports.murmur3=qr,jt.exports.murmur2=_i;var bi=o(jt.exports);class Zr{constructor(){this.ids=[],this.positions=[],this.indexed=!1}add(A,F,W,re){this.ids.push(ai(A)),this.positions.push(F,W,re)}getPositions(A){if(!this.indexed)throw new Error("Trying to get index, but feature positions are not indexed");let F=ai(A),W=0,re=this.ids.length-1;for(;W>1;this.ids[pe]>=F?re=pe:W=pe+1}let fe=[];for(;this.ids[W]===F;)fe.push({index:this.positions[3*W],start:this.positions[3*W+1],end:this.positions[3*W+2]}),W++;return fe}static serialize(A,F){let W=new Float64Array(A.ids),re=new Uint32Array(A.positions);return gi(W,re,0,W.length-1),F&&F.push(W.buffer,re.buffer),{ids:W,positions:re}}static deserialize(A){let F=new Zr;return F.ids=A.ids,F.positions=A.positions,F.indexed=!0,F}}function ai(R){let A=+R;return!isNaN(A)&&A<=Number.MAX_SAFE_INTEGER?A:bi(String(R))}function gi(R,A,F,W){for(;F>1],fe=F-1,pe=W+1;for(;;){do fe++;while(R[fe]re);if(fe>=pe)break;Ii(R,fe,pe),Ii(A,3*fe,3*pe),Ii(A,3*fe+1,3*pe+1),Ii(A,3*fe+2,3*pe+2)}pe-F`u_${re}`),this.type=W}setUniform(A,F,W){A.set(W.constantOr(this.value))}getBinding(A,F,W){return this.type==="color"?new En(A,F):new ei(A,F)}}class Ia{constructor(A,F){this.uniformNames=F.map(W=>`u_${W}`),this.patternFrom=null,this.patternTo=null,this.pixelRatioFrom=1,this.pixelRatioTo=1}setConstantPatternPositions(A,F){this.pixelRatioFrom=F.pixelRatio,this.pixelRatioTo=A.pixelRatio,this.patternFrom=F.tlbr,this.patternTo=A.tlbr}setUniform(A,F,W,re){let fe=re==="u_pattern_to"?this.patternTo:re==="u_pattern_from"?this.patternFrom:re==="u_pixel_ratio_to"?this.pixelRatioTo:re==="u_pixel_ratio_from"?this.pixelRatioFrom:null;fe&&A.set(fe)}getBinding(A,F,W){return W.substr(0,9)==="u_pattern"?new Ln(A,F):new ei(A,F)}}class yo{constructor(A,F,W,re){this.expression=A,this.type=W,this.maxValue=0,this.paintVertexAttributes=F.map(fe=>({name:`a_${fe}`,type:"Float32",components:W==="color"?2:1,offset:0})),this.paintVertexArray=new re}populatePaintArray(A,F,W,re,fe){let pe=this.paintVertexArray.length,ze=this.expression.evaluate(new rs(0),F,{},re,[],fe);this.paintVertexArray.resize(A),this._setPaintValue(pe,A,ze)}updatePaintArray(A,F,W,re){let fe=this.expression.evaluate({zoom:0},W,re);this._setPaintValue(A,F,fe)}_setPaintValue(A,F,W){if(this.type==="color"){let re=ia(W);for(let fe=A;fe`u_${ze}_t`),this.type=W,this.useIntegerZoom=re,this.zoom=fe,this.maxValue=0,this.paintVertexAttributes=F.map(ze=>({name:`a_${ze}`,type:"Float32",components:W==="color"?4:2,offset:0})),this.paintVertexArray=new pe}populatePaintArray(A,F,W,re,fe){let pe=this.expression.evaluate(new rs(this.zoom),F,{},re,[],fe),ze=this.expression.evaluate(new rs(this.zoom+1),F,{},re,[],fe),Ke=this.paintVertexArray.length;this.paintVertexArray.resize(A),this._setPaintValue(Ke,A,pe,ze)}updatePaintArray(A,F,W,re){let fe=this.expression.evaluate({zoom:this.zoom},W,re),pe=this.expression.evaluate({zoom:this.zoom+1},W,re);this._setPaintValue(A,F,fe,pe)}_setPaintValue(A,F,W,re){if(this.type==="color"){let fe=ia(W),pe=ia(re);for(let ze=A;ze`#define HAS_UNIFORM_${re}`))}return A}getBinderAttributes(){let A=[];for(let F in this.binders){let W=this.binders[F];if(W instanceof yo||W instanceof Da)for(let re=0;re!0){this.programConfigurations={};for(let re of A)this.programConfigurations[re.id]=new Is(re,F,W);this.needsUpload=!1,this._featureMap=new Zr,this._bufferOffset=0}populatePaintArrays(A,F,W,re,fe,pe){for(let ze in this.programConfigurations)this.programConfigurations[ze].populatePaintArrays(A,F,re,fe,pe);F.id!==void 0&&this._featureMap.add(F.id,W,this._bufferOffset,A),this._bufferOffset=A,this.needsUpload=!0}updatePaintArrays(A,F,W,re){for(let fe of W)this.needsUpload=this.programConfigurations[fe.id].updatePaintArrays(A,this._featureMap,F,fe,re)||this.needsUpload}get(A){return this.programConfigurations[A]}upload(A){if(this.needsUpload){for(let F in this.programConfigurations)this.programConfigurations[F].upload(A);this.needsUpload=!1}}destroy(){for(let A in this.programConfigurations)this.programConfigurations[A].destroy()}}function Xs(R,A){return{"text-opacity":["opacity"],"icon-opacity":["opacity"],"text-color":["fill_color"],"icon-color":["fill_color"],"text-halo-color":["halo_color"],"icon-halo-color":["halo_color"],"text-halo-blur":["halo_blur"],"icon-halo-blur":["halo_blur"],"text-halo-width":["halo_width"],"icon-halo-width":["halo_width"],"line-gap-width":["gapwidth"],"line-pattern":["pattern_to","pattern_from","pixel_ratio_to","pixel_ratio_from"],"fill-pattern":["pattern_to","pattern_from","pixel_ratio_to","pixel_ratio_from"],"fill-extrusion-pattern":["pattern_to","pattern_from","pixel_ratio_to","pixel_ratio_from"]}[R]||[R.replace(`${A}-`,"").replace(/-/g,"_")]}function Gn(R,A,F){let W={color:{source:Ir,composite:cn},number:{source:Sr,composite:Ir}},re=function(fe){return{"line-pattern":{source:Js,composite:Js},"fill-pattern":{source:Js,composite:Js},"fill-extrusion-pattern":{source:Js,composite:Js}}[fe]}(R);return re&&re[F]||W[A][F]}Fi("ConstantBinder",Ea),Fi("CrossFadedConstantBinder",Ia),Fi("SourceExpressionBinder",yo),Fi("CrossFadedCompositeBinder",go),Fi("CompositeExpressionBinder",Da),Fi("ProgramConfiguration",Is,{omit:["_buffers"]}),Fi("ProgramConfigurationSet",Ms);let ja=8192,Fo=Math.pow(2,14)-1,Uo=-Fo-1;function $s(R){let A=ja/R.extent,F=R.loadGeometry();for(let W=0;Wpe.x+1||Kepe.y+1)&&T("Geometry exceeds allowed extent, reduce your vector tile buffer size")}}return F}function Sl(R,A){return{type:R.type,id:R.id,properties:R.properties,geometry:A?$s(R):[]}}function bu(R,A,F,W,re){R.emplaceBack(2*A+(W+1)/2,2*F+(re+1)/2)}class dl{constructor(A){this.zoom=A.zoom,this.overscaling=A.overscaling,this.layers=A.layers,this.layerIds=this.layers.map(F=>F.id),this.index=A.index,this.hasPattern=!1,this.layoutVertexArray=new To,this.indexArray=new se,this.segments=new Ye,this.programConfigurations=new Ms(A.layers,A.zoom),this.stateDependentLayerIds=this.layers.filter(F=>F.isStateDependent()).map(F=>F.id)}populate(A,F,W){let re=this.layers[0],fe=[],pe=null,ze=!1;re.type==="circle"&&(pe=re.layout.get("circle-sort-key"),ze=!pe.isConstant());for(let{feature:Ke,id:ct,index:Lt,sourceLayerIndex:$t}of A){let fr=this.layers[0]._featureFilter.needGeometry,mr=Sl(Ke,fr);if(!this.layers[0]._featureFilter.filter(new rs(this.zoom),mr,W))continue;let Pr=ze?pe.evaluate(mr,{},W):void 0,zr={id:ct,properties:Ke.properties,type:Ke.type,sourceLayerIndex:$t,index:Lt,geometry:fr?mr.geometry:$s(Ke),patterns:{},sortKey:Pr};fe.push(zr)}ze&&fe.sort((Ke,ct)=>Ke.sortKey-ct.sortKey);for(let Ke of fe){let{geometry:ct,index:Lt,sourceLayerIndex:$t}=Ke,fr=A[Lt].feature;this.addFeature(Ke,ct,Lt,W),F.featureIndex.insert(fr,ct,Lt,$t,this.index)}}update(A,F,W){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(A,F,this.stateDependentLayers,W)}isEmpty(){return this.layoutVertexArray.length===0}uploadPending(){return!this.uploaded||this.programConfigurations.needsUpload}upload(A){this.uploaded||(this.layoutVertexBuffer=A.createVertexBuffer(this.layoutVertexArray,He),this.indexBuffer=A.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(A),this.uploaded=!0}destroy(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())}addFeature(A,F,W,re){for(let fe of F)for(let pe of fe){let ze=pe.x,Ke=pe.y;if(ze<0||ze>=ja||Ke<0||Ke>=ja)continue;let ct=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray,A.sortKey),Lt=ct.vertexLength;bu(this.layoutVertexArray,ze,Ke,-1,-1),bu(this.layoutVertexArray,ze,Ke,1,-1),bu(this.layoutVertexArray,ze,Ke,1,1),bu(this.layoutVertexArray,ze,Ke,-1,1),this.indexArray.emplaceBack(Lt,Lt+1,Lt+2),this.indexArray.emplaceBack(Lt,Lt+3,Lt+2),ct.vertexLength+=4,ct.primitiveLength+=2}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,A,W,{},re)}}function Sc(R,A){for(let F=0;F1){if(Rr(R,A))return!0;for(let W=0;W1?F:F.sub(A)._mult(re)._add(A))}function mi(R,A){let F,W,re,fe=!1;for(let pe=0;peA.y!=re.y>A.y&&A.x<(re.x-W.x)*(A.y-W.y)/(re.y-W.y)+W.x&&(fe=!fe)}return fe}function Ui(R,A){let F=!1;for(let W=0,re=R.length-1;WA.y!=pe.y>A.y&&A.x<(pe.x-fe.x)*(A.y-fe.y)/(pe.y-fe.y)+fe.x&&(F=!F)}return F}function qi(R,A,F){let W=F[0],re=F[2];if(R.xre.x&&A.x>re.x||R.yre.y&&A.y>re.y)return!1;let fe=z(R,A,F[0]);return fe!==z(R,A,F[1])||fe!==z(R,A,F[2])||fe!==z(R,A,F[3])}function 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fe=re.patternDependencies;for(let pe of A){let ze=pe.paint.get(`${R}-pattern`).value;if(ze.kind!=="constant"){let Ke=ze.evaluate({zoom:W-1},F,{},re.availableImages),ct=ze.evaluate({zoom:W},F,{},re.availableImages),Lt=ze.evaluate({zoom:W+1},F,{},re.availableImages);Ke=Ke&&Ke.name?Ke.name:Ke,ct=ct&&ct.name?ct.name:ct,Lt=Lt&&Lt.name?Lt.name:Lt,fe[Ke]=!0,fe[ct]=!0,fe[Lt]=!0,F.patterns[pe.id]={min:Ke,mid:ct,max:Lt}}}return F}class Ot{constructor(A){this.zoom=A.zoom,this.overscaling=A.overscaling,this.layers=A.layers,this.layerIds=this.layers.map(F=>F.id),this.index=A.index,this.hasPattern=!1,this.patternFeatures=[],this.layoutVertexArray=new hl,this.indexArray=new se,this.indexArray2=new Te,this.programConfigurations=new Ms(A.layers,A.zoom),this.segments=new Ye,this.segments2=new Ye,this.stateDependentLayerIds=this.layers.filter(F=>F.isStateDependent()).map(F=>F.id)}populate(A,F,W){this.hasPattern=at("fill",this.layers,F);let re=this.layers[0].layout.get("fill-sort-key"),fe=!re.isConstant(),pe=[];for(let{feature:ze,id:Ke,index:ct,sourceLayerIndex:Lt}of A){let $t=this.layers[0]._featureFilter.needGeometry,fr=Sl(ze,$t);if(!this.layers[0]._featureFilter.filter(new rs(this.zoom),fr,W))continue;let mr=fe?re.evaluate(fr,{},W,F.availableImages):void 0,Pr={id:Ke,properties:ze.properties,type:ze.type,sourceLayerIndex:Lt,index:ct,geometry:$t?fr.geometry:$s(ze),patterns:{},sortKey:mr};pe.push(Pr)}fe&&pe.sort((ze,Ke)=>ze.sortKey-Ke.sortKey);for(let ze of pe){let{geometry:Ke,index:ct,sourceLayerIndex:Lt}=ze;if(this.hasPattern){let $t=Ct("fill",this.layers,ze,this.zoom,F);this.patternFeatures.push($t)}else this.addFeature(ze,Ke,ct,W,{});F.featureIndex.insert(A[ct].feature,Ke,ct,Lt,this.index)}}update(A,F,W){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(A,F,this.stateDependentLayers,W)}addFeatures(A,F,W){for(let re of this.patternFeatures)this.addFeature(re,re.geometry,re.index,F,W)}isEmpty(){return this.layoutVertexArray.length===0}uploadPending(){return!this.uploaded||this.programConfigurations.needsUpload}upload(A){this.uploaded||(this.layoutVertexBuffer=A.createVertexBuffer(this.layoutVertexArray,Ml),this.indexBuffer=A.createIndexBuffer(this.indexArray),this.indexBuffer2=A.createIndexBuffer(this.indexArray2)),this.programConfigurations.upload(A),this.uploaded=!0}destroy(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.indexBuffer2.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.segments2.destroy())}addFeature(A,F,W,re,fe){for(let pe of Cf(F,500)){let ze=0;for(let mr of pe)ze+=mr.length;let Ke=this.segments.prepareSegment(ze,this.layoutVertexArray,this.indexArray),ct=Ke.vertexLength,Lt=[],$t=[];for(let mr of pe){if(mr.length===0)continue;mr!==pe[0]&&$t.push(Lt.length/2);let Pr=this.segments2.prepareSegment(mr.length,this.layoutVertexArray,this.indexArray2),zr=Pr.vertexLength;this.layoutVertexArray.emplaceBack(mr[0].x,mr[0].y),this.indexArray2.emplaceBack(zr+mr.length-1,zr),Lt.push(mr[0].x),Lt.push(mr[0].y);for(let ui=1;ui>3}if(re--,W===1||W===2)fe+=R.readSVarint(),pe+=R.readSVarint(),W===1&&(A&&ze.push(A),A=[]),A.push(new Ur(fe,pe));else{if(W!==7)throw new Error("unknown command "+W);A&&A.push(A[0].clone())}}return A&&ze.push(A),ze},fi.prototype.bbox=function(){var R=this._pbf;R.pos=this._geometry;for(var A=R.readVarint()+R.pos,F=1,W=0,re=0,fe=0,pe=1/0,ze=-1/0,Ke=1/0,ct=-1/0;R.pos>3}if(W--,F===1||F===2)(re+=R.readSVarint())ze&&(ze=re),(fe+=R.readSVarint())ct&&(ct=fe);else if(F!==7)throw new Error("unknown command "+F)}return[pe,Ke,ze,ct]},fi.prototype.toGeoJSON=function(R,A,F){var W,re,fe=this.extent*Math.pow(2,F),pe=this.extent*R,ze=this.extent*A,Ke=this.loadGeometry(),ct=fi.types[this.type];function Lt(mr){for(var Pr=0;Pr>3;re=pe===1?W.readString():pe===2?W.readFloat():pe===3?W.readDouble():pe===4?W.readVarint64():pe===5?W.readVarint():pe===6?W.readSVarint():pe===7?W.readBoolean():null}return re}(F))}Bi.prototype.feature=function(R){if(R<0||R>=this._features.length)throw new Error("feature index out of bounds");this._pbf.pos=this._features[R];var A=this._pbf.readVarint()+this._pbf.pos;return new rn(this._pbf,A,this.extent,this._keys,this._values)};var sn=Ci;function zn(R,A,F){if(R===3){var W=new sn(F,F.readVarint()+F.pos);W.length&&(A[W.name]=W)}}br.VectorTile=function(R,A){this.layers=R.readFields(zn,{},A)},br.VectorTileFeature=Di,br.VectorTileLayer=Ci;let Ja=br.VectorTileFeature.types,co=Math.pow(2,13);function ts(R,A,F,W,re,fe,pe,ze){R.emplaceBack(A,F,2*Math.floor(W*co)+pe,re*co*2,fe*co*2,Math.round(ze))}class so{constructor(A){this.zoom=A.zoom,this.overscaling=A.overscaling,this.layers=A.layers,this.layerIds=this.layers.map(F=>F.id),this.index=A.index,this.hasPattern=!1,this.layoutVertexArray=new Ul,this.centroidVertexArray=new wo,this.indexArray=new se,this.programConfigurations=new Ms(A.layers,A.zoom),this.segments=new Ye,this.stateDependentLayerIds=this.layers.filter(F=>F.isStateDependent()).map(F=>F.id)}populate(A,F,W){this.features=[],this.hasPattern=at("fill-extrusion",this.layers,F);for(let{feature:re,id:fe,index:pe,sourceLayerIndex:ze}of A){let Ke=this.layers[0]._featureFilter.needGeometry,ct=Sl(re,Ke);if(!this.layers[0]._featureFilter.filter(new rs(this.zoom),ct,W))continue;let Lt={id:fe,sourceLayerIndex:ze,index:pe,geometry:Ke?ct.geometry:$s(re),properties:re.properties,type:re.type,patterns:{}};this.hasPattern?this.features.push(Ct("fill-extrusion",this.layers,Lt,this.zoom,F)):this.addFeature(Lt,Lt.geometry,pe,W,{}),F.featureIndex.insert(re,Lt.geometry,pe,ze,this.index,!0)}}addFeatures(A,F,W){for(let re of this.features){let{geometry:fe}=re;this.addFeature(re,fe,re.index,F,W)}}update(A,F,W){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(A,F,this.stateDependentLayers,W)}isEmpty(){return this.layoutVertexArray.length===0&&this.centroidVertexArray.length===0}uploadPending(){return!this.uploaded||this.programConfigurations.needsUpload}upload(A){this.uploaded||(this.layoutVertexBuffer=A.createVertexBuffer(this.layoutVertexArray,ur),this.centroidVertexBuffer=A.createVertexBuffer(this.centroidVertexArray,ht.members,!0),this.indexBuffer=A.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(A),this.uploaded=!0}destroy(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.centroidVertexBuffer.destroy())}addFeature(A,F,W,re,fe){for(let pe of Cf(F,500)){let ze={x:0,y:0,vertexCount:0},Ke=0;for(let Pr of pe)Ke+=Pr.length;let ct=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray);for(let Pr of pe){if(Pr.length===0||ms(Pr))continue;let zr=0;for(let ui=0;ui=1){let vn=Pr[ui-1];if(!Zo(yi,vn)){ct.vertexLength+4>Ye.MAX_VERTEX_ARRAY_LENGTH&&(ct=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));let zi=yi.sub(vn)._perp()._unit(),un=vn.dist(yi);zr+un>32768&&(zr=0),ts(this.layoutVertexArray,yi.x,yi.y,zi.x,zi.y,0,0,zr),ts(this.layoutVertexArray,yi.x,yi.y,zi.x,zi.y,0,1,zr),ze.x+=2*yi.x,ze.y+=2*yi.y,ze.vertexCount+=2,zr+=un,ts(this.layoutVertexArray,vn.x,vn.y,zi.x,zi.y,0,0,zr),ts(this.layoutVertexArray,vn.x,vn.y,zi.x,zi.y,0,1,zr),ze.x+=2*vn.x,ze.y+=2*vn.y,ze.vertexCount+=2;let Tn=ct.vertexLength;this.indexArray.emplaceBack(Tn,Tn+2,Tn+1),this.indexArray.emplaceBack(Tn+1,Tn+2,Tn+3),ct.vertexLength+=4,ct.primitiveLength+=2}}}}if(ct.vertexLength+Ke>Ye.MAX_VERTEX_ARRAY_LENGTH&&(ct=this.segments.prepareSegment(Ke,this.layoutVertexArray,this.indexArray)),Ja[A.type]!=="Polygon")continue;let Lt=[],$t=[],fr=ct.vertexLength;for(let Pr of pe)if(Pr.length!==0){Pr!==pe[0]&&$t.push(Lt.length/2);for(let zr=0;zrja)||R.y===A.y&&(R.y<0||R.y>ja)}function ms(R){return R.every(A=>A.x<0)||R.every(A=>A.x>ja)||R.every(A=>A.y<0)||R.every(A=>A.y>ja)}let ou;Fi("FillExtrusionBucket",so,{omit:["layers","features"]});var Cv={get paint(){return ou=ou||new ue({"fill-extrusion-opacity":new Ua(ce["paint_fill-extrusion"]["fill-extrusion-opacity"]),"fill-extrusion-color":new oo(ce["paint_fill-extrusion"]["fill-extrusion-color"]),"fill-extrusion-translate":new Ua(ce["paint_fill-extrusion"]["fill-extrusion-translate"]),"fill-extrusion-translate-anchor":new Ua(ce["paint_fill-extrusion"]["fill-extrusion-translate-anchor"]),"fill-extrusion-pattern":new Vc(ce["paint_fill-extrusion"]["fill-extrusion-pattern"]),"fill-extrusion-height":new oo(ce["paint_fill-extrusion"]["fill-extrusion-height"]),"fill-extrusion-base":new oo(ce["paint_fill-extrusion"]["fill-extrusion-base"]),"fill-extrusion-vertical-gradient":new Ua(ce["paint_fill-extrusion"]["fill-extrusion-vertical-gradient"])})}};class Lv extends B{constructor(A){super(A,Cv)}createBucket(A){return new so(A)}queryRadius(){return Hn(this.paint.get("fill-extrusion-translate"))}is3D(){return!0}queryIntersectsFeature(A,F,W,re,fe,pe,ze,Ke){let ct=en(A,this.paint.get("fill-extrusion-translate"),this.paint.get("fill-extrusion-translate-anchor"),pe.angle,ze),Lt=this.paint.get("fill-extrusion-height").evaluate(F,W),$t=this.paint.get("fill-extrusion-base").evaluate(F,W),fr=function(Pr,zr,ui,yi){let vn=[];for(let zi of Pr){let un=[zi.x,zi.y,0,1];Bn(un,un,zr),vn.push(new u(un[0]/un[3],un[1]/un[3]))}return vn}(ct,Ke),mr=function(Pr,zr,ui,yi){let vn=[],zi=[],un=yi[8]*zr,Tn=yi[9]*zr,pa=yi[10]*zr,ro=yi[11]*zr,Vo=yi[8]*ui,Xa=yi[9]*ui,sa=yi[10]*ui,Mo=yi[11]*ui;for(let fo of Pr){let lo=[],Xn=[];for(let Ro of fo){let uo=Ro.x,$o=Ro.y,Ju=yi[0]*uo+yi[4]*$o+yi[12],qu=yi[1]*uo+yi[5]*$o+yi[13],Mh=yi[2]*uo+yi[6]*$o+yi[14],Qv=yi[3]*uo+yi[7]*$o+yi[15],ld=Mh+pa,Eh=Qv+ro,Gd=Ju+Vo,Hd=qu+Xa,jd=Mh+sa,Af=Qv+Mo,kh=new u((Ju+un)/Eh,(qu+Tn)/Eh);kh.z=ld/Eh,lo.push(kh);let Ed=new u(Gd/Af,Hd/Af);Ed.z=jd/Af,Xn.push(Ed)}vn.push(lo),zi.push(Xn)}return[vn,zi]}(re,$t,Lt,Ke);return function(Pr,zr,ui){let yi=1/0;bt(ui,zr)&&(yi=Kv(ui,zr[0]));for(let vn=0;vnF.id),this.index=A.index,this.hasPattern=!1,this.patternFeatures=[],this.lineClipsArray=[],this.gradients={},this.layers.forEach(F=>{this.gradients[F.id]={}}),this.layoutVertexArray=new Lu,this.layoutVertexArray2=new au,this.indexArray=new se,this.programConfigurations=new Ms(A.layers,A.zoom),this.segments=new Ye,this.maxLineLength=0,this.stateDependentLayerIds=this.layers.filter(F=>F.isStateDependent()).map(F=>F.id)}populate(A,F,W){this.hasPattern=at("line",this.layers,F);let re=this.layers[0].layout.get("line-sort-key"),fe=!re.isConstant(),pe=[];for(let{feature:ze,id:Ke,index:ct,sourceLayerIndex:Lt}of A){let $t=this.layers[0]._featureFilter.needGeometry,fr=Sl(ze,$t);if(!this.layers[0]._featureFilter.filter(new rs(this.zoom),fr,W))continue;let mr=fe?re.evaluate(fr,{},W):void 0,Pr={id:Ke,properties:ze.properties,type:ze.type,sourceLayerIndex:Lt,index:ct,geometry:$t?fr.geometry:$s(ze),patterns:{},sortKey:mr};pe.push(Pr)}fe&&pe.sort((ze,Ke)=>ze.sortKey-Ke.sortKey);for(let ze of pe){let{geometry:Ke,index:ct,sourceLayerIndex:Lt}=ze;if(this.hasPattern){let $t=Ct("line",this.layers,ze,this.zoom,F);this.patternFeatures.push($t)}else this.addFeature(ze,Ke,ct,W,{});F.featureIndex.insert(A[ct].feature,Ke,ct,Lt,this.index)}}update(A,F,W){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(A,F,this.stateDependentLayers,W)}addFeatures(A,F,W){for(let re of this.patternFeatures)this.addFeature(re,re.geometry,re.index,F,W)}isEmpty(){return this.layoutVertexArray.length===0}uploadPending(){return!this.uploaded||this.programConfigurations.needsUpload}upload(A){this.uploaded||(this.layoutVertexArray2.length!==0&&(this.layoutVertexBuffer2=A.createVertexBuffer(this.layoutVertexArray2,gp)),this.layoutVertexBuffer=A.createVertexBuffer(this.layoutVertexArray,pp),this.indexBuffer=A.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(A),this.uploaded=!0}destroy(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())}lineFeatureClips(A){if(A.properties&&Object.prototype.hasOwnProperty.call(A.properties,"mapbox_clip_start")&&Object.prototype.hasOwnProperty.call(A.properties,"mapbox_clip_end"))return{start:+A.properties.mapbox_clip_start,end:+A.properties.mapbox_clip_end}}addFeature(A,F,W,re,fe){let pe=this.layers[0].layout,ze=pe.get("line-join").evaluate(A,{}),Ke=pe.get("line-cap"),ct=pe.get("line-miter-limit"),Lt=pe.get("line-round-limit");this.lineClips=this.lineFeatureClips(A);for(let $t of F)this.addLine($t,A,ze,Ke,ct,Lt);this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,A,W,fe,re)}addLine(A,F,W,re,fe,pe){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,this.lineClips){this.lineClipsArray.push(this.lineClips);for(let yi=0;yi=2&&A[Ke-1].equals(A[Ke-2]);)Ke--;let ct=0;for(;ct0;if(ro&&yi>ct){let Mo=fr.dist(mr);if(Mo>2*Lt){let fo=fr.sub(fr.sub(mr)._mult(Lt/Mo)._round());this.updateDistance(mr,fo),this.addCurrentVertex(fo,zr,0,0,$t),mr=fo}}let Xa=mr&&Pr,sa=Xa?W:ze?"butt":re;if(Xa&&sa==="round"&&(Tnfe&&(sa="bevel"),sa==="bevel"&&(Tn>2&&(sa="flipbevel"),Tn100)vn=ui.mult(-1);else{let Mo=Tn*zr.add(ui).mag()/zr.sub(ui).mag();vn._perp()._mult(Mo*(Vo?-1:1))}this.addCurrentVertex(fr,vn,0,0,$t),this.addCurrentVertex(fr,vn.mult(-1),0,0,$t)}else if(sa==="bevel"||sa==="fakeround"){let Mo=-Math.sqrt(Tn*Tn-1),fo=Vo?Mo:0,lo=Vo?0:Mo;if(mr&&this.addCurrentVertex(fr,zr,fo,lo,$t),sa==="fakeround"){let Xn=Math.round(180*pa/Math.PI/20);for(let Ro=1;Ro2*Lt){let fo=fr.add(Pr.sub(fr)._mult(Lt/Mo)._round());this.updateDistance(fr,fo),this.addCurrentVertex(fo,ui,0,0,$t),fr=fo}}}}addCurrentVertex(A,F,W,re,fe,pe=!1){let ze=F.y*re-F.x,Ke=-F.y-F.x*re;this.addHalfVertex(A,F.x+F.y*W,F.y-F.x*W,pe,!1,W,fe),this.addHalfVertex(A,ze,Ke,pe,!0,-re,fe),this.distance>Pv/2&&this.totalDistance===0&&(this.distance=0,this.updateScaledDistance(),this.addCurrentVertex(A,F,W,re,fe,pe))}addHalfVertex({x:A,y:F},W,re,fe,pe,ze,Ke){let ct=.5*(this.lineClips?this.scaledDistance*(Pv-1):this.scaledDistance);this.layoutVertexArray.emplaceBack((A<<1)+(fe?1:0),(F<<1)+(pe?1:0),Math.round(63*W)+128,Math.round(63*re)+128,1+(ze===0?0:ze<0?-1:1)|(63&ct)<<2,ct>>6),this.lineClips&&this.layoutVertexArray2.emplaceBack((this.scaledDistance-this.lineClips.start)/(this.lineClips.end-this.lineClips.start),this.lineClipsArray.length);let Lt=Ke.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,Lt),Ke.primitiveLength++),pe?this.e2=Lt:this.e1=Lt}updateScaledDistance(){this.scaledDistance=this.lineClips?this.lineClips.start+(this.lineClips.end-this.lineClips.start)*this.distance/this.totalDistance:this.distance}updateDistance(A,F){this.distance+=A.dist(F),this.updateScaledDistance()}}let Iv,ay;Fi("LineBucket",Jv,{omit:["layers","patternFeatures"]});var fg={get paint(){return ay=ay||new ue({"line-opacity":new oo(ce.paint_line["line-opacity"]),"line-color":new oo(ce.paint_line["line-color"]),"line-translate":new Ua(ce.paint_line["line-translate"]),"line-translate-anchor":new Ua(ce.paint_line["line-translate-anchor"]),"line-width":new oo(ce.paint_line["line-width"]),"line-gap-width":new oo(ce.paint_line["line-gap-width"]),"line-offset":new oo(ce.paint_line["line-offset"]),"line-blur":new oo(ce.paint_line["line-blur"]),"line-dasharray":new hc(ce.paint_line["line-dasharray"]),"line-pattern":new Vc(ce.paint_line["line-pattern"]),"line-gradient":new Ku(ce.paint_line["line-gradient"])})},get layout(){return Iv=Iv||new ue({"line-cap":new Ua(ce.layout_line["line-cap"]),"line-join":new oo(ce.layout_line["line-join"]),"line-miter-limit":new Ua(ce.layout_line["line-miter-limit"]),"line-round-limit":new Ua(ce.layout_line["line-round-limit"]),"line-sort-key":new oo(ce.layout_line["line-sort-key"])})}};class oh extends oo{possiblyEvaluate(A,F){return F=new rs(Math.floor(F.zoom),{now:F.now,fadeDuration:F.fadeDuration,zoomHistory:F.zoomHistory,transition:F.transition}),super.possiblyEvaluate(A,F)}evaluate(A,F,W,re){return F=L({},F,{zoom:Math.floor(F.zoom)}),super.evaluate(A,F,W,re)}}let hg;class oy extends B{constructor(A){super(A,fg),this.gradientVersion=0,hg||(hg=new oh(fg.paint.properties["line-width"].specification),hg.useIntegerZoom=!0)}_handleSpecialPaintPropertyUpdate(A){if(A==="line-gradient"){let F=this.gradientExpression();this.stepInterpolant=!!function(W){return W._styleExpression!==void 0}(F)&&F._styleExpression.expression instanceof _n,this.gradientVersion=(this.gradientVersion+1)%Number.MAX_SAFE_INTEGER}}gradientExpression(){return this._transitionablePaint._values["line-gradient"].value.expression}recalculate(A,F){super.recalculate(A,F),this.paint._values["line-floorwidth"]=hg.possiblyEvaluate(this._transitioningPaint._values["line-width"].value,A)}createBucket(A){return new Jv(A)}queryRadius(A){let F=A,W=jh(Ei("line-width",this,F),Ei("line-gap-width",this,F)),re=Ei("line-offset",this,F);return W/2+Math.abs(re)+Hn(this.paint.get("line-translate"))}queryIntersectsFeature(A,F,W,re,fe,pe,ze){let Ke=en(A,this.paint.get("line-translate"),this.paint.get("line-translate-anchor"),pe.angle,ze),ct=ze/2*jh(this.paint.get("line-width").evaluate(F,W),this.paint.get("line-gap-width").evaluate(F,W)),Lt=this.paint.get("line-offset").evaluate(F,W);return Lt&&(re=function($t,fr){let mr=[];for(let Pr=0;Pr<$t.length;Pr++){let zr=$t[Pr],ui=[];for(let yi=0;yi=3){for(let ui=0;ui0?A+2*R:R}let im=qe([{name:"a_pos_offset",components:4,type:"Int16"},{name:"a_data",components:4,type:"Uint16"},{name:"a_pixeloffset",components:4,type:"Int16"}],4),b1=qe([{name:"a_projected_pos",components:3,type:"Float32"}],4);qe([{name:"a_fade_opacity",components:1,type:"Uint32"}],4);let 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vc={"!":"\uFE15","#":"\uFF03",$:"\uFF04","%":"\uFF05","&":"\uFF06","(":"\uFE35",")":"\uFE36","*":"\uFF0A","+":"\uFF0B",",":"\uFE10","-":"\uFE32",".":"\u30FB","/":"\uFF0F",":":"\uFE13",";":"\uFE14","<":"\uFE3F","=":"\uFF1D",">":"\uFE40","?":"\uFE16","@":"\uFF20","[":"\uFE47","\\":"\uFF3C","]":"\uFE48","^":"\uFF3E",_:"\uFE33","`":"\uFF40","{":"\uFE37","|":"\u2015","}":"\uFE38","~":"\uFF5E","\xA2":"\uFFE0","\xA3":"\uFFE1","\xA5":"\uFFE5","\xA6":"\uFFE4","\xAC":"\uFFE2","\xAF":"\uFFE3","\u2013":"\uFE32","\u2014":"\uFE31","\u2018":"\uFE43","\u2019":"\uFE44","\u201C":"\uFE41","\u201D":"\uFE42","\u2026":"\uFE19","\u2027":"\u30FB","\u20A9":"\uFFE6","\u3001":"\uFE11","\u3002":"\uFE12","\u3008":"\uFE3F","\u3009":"\uFE40","\u300A":"\uFE3D","\u300B":"\uFE3E","\u300C":"\uFE41","\u300D":"\uFE42","\u300E":"\uFE43","\u300F":"\uFE44","\u3010":"\uFE3B","\u3011":"\uFE3C","\u3014":"\uFE39","\u3015":"\uFE3A","\u3016":"\uFE17","\u3017":"\uFE18","\uFF01":"\uFE15","\uFF08":"\uFE35","\uFF09":"\uFE36","\uFF0C":"\uFE10","\uFF0D":"\uFE32","\uFF0E":"\u30FB","\uFF1A":"\uFE13","\uFF1B":"\uFE14","\uFF1C":"\uFE3F","\uFF1E":"\uFE40","\uFF1F":"\uFE16","\uFF3B":"\uFE47","\uFF3D":"\uFE48","\uFF3F":"\uFE33","\uFF5B":"\uFE37","\uFF5C":"\u2015","\uFF5D":"\uFE38","\uFF5F":"\uFE35","\uFF60":"\uFE36","\uFF61":"\uFE12","\uFF62":"\uFE41","\uFF63":"\uFE42"};var eu=24,Sd=wu,ly=function(R,A,F,W,re){var fe,pe,ze=8*re-W-1,Ke=(1<>1,Lt=-7,$t=F?re-1:0,fr=F?-1:1,mr=R[A+$t];for($t+=fr,fe=mr&(1<<-Lt)-1,mr>>=-Lt,Lt+=ze;Lt>0;fe=256*fe+R[A+$t],$t+=fr,Lt-=8);for(pe=fe&(1<<-Lt)-1,fe>>=-Lt,Lt+=W;Lt>0;pe=256*pe+R[A+$t],$t+=fr,Lt-=8);if(fe===0)fe=1-ct;else{if(fe===Ke)return pe?NaN:1/0*(mr?-1:1);pe+=Math.pow(2,W),fe-=ct}return(mr?-1:1)*pe*Math.pow(2,fe-W)},T1=function(R,A,F,W,re,fe){var pe,ze,Ke,ct=8*fe-re-1,Lt=(1<>1,fr=re===23?Math.pow(2,-24)-Math.pow(2,-77):0,mr=W?0:fe-1,Pr=W?1:-1,zr=A<0||A===0&&1/A<0?1:0;for(A=Math.abs(A),isNaN(A)||A===1/0?(ze=isNaN(A)?1:0,pe=Lt):(pe=Math.floor(Math.log(A)/Math.LN2),A*(Ke=Math.pow(2,-pe))<1&&(pe--,Ke*=2),(A+=pe+$t>=1?fr/Ke:fr*Math.pow(2,1-$t))*Ke>=2&&(pe++,Ke/=2),pe+$t>=Lt?(ze=0,pe=Lt):pe+$t>=1?(ze=(A*Ke-1)*Math.pow(2,re),pe+=$t):(ze=A*Math.pow(2,$t-1)*Math.pow(2,re),pe=0));re>=8;R[F+mr]=255&ze,mr+=Pr,ze/=256,re-=8);for(pe=pe<0;R[F+mr]=255&pe,mr+=Pr,pe/=256,ct-=8);R[F+mr-Pr]|=128*zr};function wu(R){this.buf=ArrayBuffer.isView&&ArrayBuffer.isView(R)?R:new Uint8Array(R||0),this.pos=0,this.type=0,this.length=this.buf.length}wu.Varint=0,wu.Fixed64=1,wu.Bytes=2,wu.Fixed32=5;var Nx=4294967296,om=1/Nx,kw=typeof TextDecoder=="undefined"?null:new TextDecoder("utf-8");function Rv(R){return R.type===wu.Bytes?R.readVarint()+R.pos:R.pos+1}function sm(R,A,F){return F?4294967296*A+(R>>>0):4294967296*(A>>>0)+(R>>>0)}function Cw(R,A,F){var W=A<=16383?1:A<=2097151?2:A<=268435455?3:Math.floor(Math.log(A)/(7*Math.LN2));F.realloc(W);for(var re=F.pos-1;re>=R;re--)F.buf[re+W]=F.buf[re]}function Ux(R,A){for(var F=0;F>>8,R[F+2]=A>>>16,R[F+3]=A>>>24}function mC(R,A){return(R[A]|R[A+1]<<8|R[A+2]<<16)+(R[A+3]<<24)}wu.prototype={destroy:function(){this.buf=null},readFields:function(R,A,F){for(F=F||this.length;this.pos>3,fe=this.pos;this.type=7&W,R(re,A,this),this.pos===fe&&this.skip(W)}return A},readMessage:function(R,A){return this.readFields(R,A,this.readVarint()+this.pos)},readFixed32:function(){var R=uy(this.buf,this.pos);return this.pos+=4,R},readSFixed32:function(){var R=mC(this.buf,this.pos);return this.pos+=4,R},readFixed64:function(){var R=uy(this.buf,this.pos)+uy(this.buf,this.pos+4)*Nx;return this.pos+=8,R},readSFixed64:function(){var R=uy(this.buf,this.pos)+mC(this.buf,this.pos+4)*Nx;return this.pos+=8,R},readFloat:function(){var R=ly(this.buf,this.pos,!0,23,4);return this.pos+=4,R},readDouble:function(){var R=ly(this.buf,this.pos,!0,52,8);return this.pos+=8,R},readVarint:function(R){var A,F,W=this.buf;return A=127&(F=W[this.pos++]),F<128?A:(A|=(127&(F=W[this.pos++]))<<7,F<128?A:(A|=(127&(F=W[this.pos++]))<<14,F<128?A:(A|=(127&(F=W[this.pos++]))<<21,F<128?A:function(re,fe,pe){var ze,Ke,ct=pe.buf;if(ze=(112&(Ke=ct[pe.pos++]))>>4,Ke<128||(ze|=(127&(Ke=ct[pe.pos++]))<<3,Ke<128)||(ze|=(127&(Ke=ct[pe.pos++]))<<10,Ke<128)||(ze|=(127&(Ke=ct[pe.pos++]))<<17,Ke<128)||(ze|=(127&(Ke=ct[pe.pos++]))<<24,Ke<128)||(ze|=(1&(Ke=ct[pe.pos++]))<<31,Ke<128))return sm(re,ze,fe);throw new 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ct=W.pop();ze=0&&W>=A&&Iw[this.text.charCodeAt(W)];W--)F--;this.text=this.text.substring(A,F),this.sectionIndex=this.sectionIndex.slice(A,F)}substring(A,F){let W=new A1;return W.text=this.text.substring(A,F),W.sectionIndex=this.sectionIndex.slice(A,F),W.sections=this.sections,W}toString(){return this.text}getMaxScale(){return this.sectionIndex.reduce((A,F)=>Math.max(A,this.sections[F].scale),0)}addTextSection(A,F){this.text+=A.text,this.sections.push(Gx.forText(A.scale,A.fontStack||F));let W=this.sections.length-1;for(let re=0;re=63743?null:++this.imageSectionID:(this.imageSectionID=57344,this.imageSectionID)}}function Hx(R,A,F,W,re,fe,pe,ze,Ke,ct,Lt,$t,fr,mr,Pr){let zr=A1.fromFeature(R,re),ui;$t===i.ah.vertical&&zr.verticalizePunctuation();let{processBidirectionalText:yi,processStyledBidirectionalText:vn}=ys;if(yi&&zr.sections.length===1){ui=[];let Tn=yi(zr.toString(),S1(zr,ct,fe,A,W,mr));for(let pa of Tn){let ro=new A1;ro.text=pa,ro.sections=zr.sections;for(let 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Ke=A.left*fe,ct=A.right*fe,Lt,$t,fr,mr;F==="width"||F==="both"?(mr=re[0]+Ke-W[3],$t=re[0]+ct+W[1]):(mr=re[0]+(Ke+ct-pe.displaySize[0])/2,$t=mr+pe.displaySize[0]);let Pr=A.top*fe,zr=A.bottom*fe;return F==="height"||F==="both"?(Lt=re[1]+Pr-W[0],fr=re[1]+zr+W[2]):(Lt=re[1]+(Pr+zr-pe.displaySize[1])/2,fr=Lt+pe.displaySize[1]),{image:pe,top:Lt,right:$t,bottom:fr,left:mr,collisionPadding:ze}}let Wx=255,d0=128,um=Wx*d0;function SC(R,A){let{expression:F}=A;if(F.kind==="constant")return{kind:"constant",layoutSize:F.evaluate(new rs(R+1))};if(F.kind==="source")return{kind:"source"};{let{zoomStops:W,interpolationType:re}=F,fe=0;for(;fepe.id),this.index=A.index,this.pixelRatio=A.pixelRatio,this.sourceLayerIndex=A.sourceLayerIndex,this.hasPattern=!1,this.hasRTLText=!1,this.sortKeyRanges=[],this.collisionCircleArray=[],this.placementInvProjMatrix=Ri([]),this.placementViewportMatrix=Ri([]);let F=this.layers[0]._unevaluatedLayout._values;this.textSizeData=SC(this.zoom,F["text-size"]),this.iconSizeData=SC(this.zoom,F["icon-size"]);let W=this.layers[0].layout,re=W.get("symbol-sort-key"),fe=W.get("symbol-z-order");this.canOverlap=sS(W,"text-overlap","text-allow-overlap")!=="never"||sS(W,"icon-overlap","icon-allow-overlap")!=="never"||W.get("text-ignore-placement")||W.get("icon-ignore-placement"),this.sortFeaturesByKey=fe!=="viewport-y"&&!re.isConstant(),this.sortFeaturesByY=(fe==="viewport-y"||fe==="auto"&&!this.sortFeaturesByKey)&&this.canOverlap,W.get("symbol-placement")==="point"&&(this.writingModes=W.get("text-writing-mode").map(pe=>i.ah[pe])),this.stateDependentLayerIds=this.layers.filter(pe=>pe.isStateDependent()).map(pe=>pe.id),this.sourceID=A.sourceID}createArrays(){this.text=new cS(new Ms(this.layers,this.zoom,A=>/^text/.test(A))),this.icon=new cS(new Ms(this.layers,this.zoom,A=>/^icon/.test(A))),this.glyphOffsetArray=new Co,this.lineVertexArray=new Qa,this.symbolInstances=new $a,this.textAnchorOffsets=new Bo}calculateGlyphDependencies(A,F,W,re,fe){for(let pe=0;pe0)&&(pe.value.kind!=="constant"||pe.value.value.length>0),Lt=Ke.value.kind!=="constant"||!!Ke.value.value||Object.keys(Ke.parameters).length>0,$t=fe.get("symbol-sort-key");if(this.features=[],!ct&&!Lt)return;let fr=F.iconDependencies,mr=F.glyphDependencies,Pr=F.availableImages,zr=new rs(this.zoom);for(let{feature:ui,id:yi,index:vn,sourceLayerIndex:zi}of A){let un=re._featureFilter.needGeometry,Tn=Sl(ui,un);if(!re._featureFilter.filter(zr,Tn,W))continue;let pa,ro;if(un||(Tn.geometry=$s(ui)),ct){let Xa=re.getValueAndResolveTokens("text-field",Tn,W,Pr),sa=ri.factory(Xa),Mo=this.hasRTLText=this.hasRTLText||uS(sa);(!Mo||ys.getRTLTextPluginStatus()==="unavailable"||Mo&&ys.isParsed())&&(pa=am(sa,re,Tn))}if(Lt){let Xa=re.getValueAndResolveTokens("icon-image",Tn,W,Pr);ro=Xa instanceof tn?Xa:tn.fromString(Xa)}if(!pa&&!ro)continue;let Vo=this.sortFeaturesByKey?$t.evaluate(Tn,{},W):void 0;if(this.features.push({id:yi,text:pa,icon:ro,index:vn,sourceLayerIndex:zi,geometry:Tn.geometry,properties:ui.properties,type:Y9[ui.type],sortKey:Vo}),ro&&(fr[ro.name]=!0),pa){let Xa=pe.evaluate(Tn,{},W).join(","),sa=fe.get("text-rotation-alignment")!=="viewport"&&fe.get("symbol-placement")!=="point";this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(i.ah.vertical)>=0;for(let Mo of pa.sections)if(Mo.image)fr[Mo.image.name]=!0;else{let fo=Ka(pa.toString()),lo=Mo.fontStack||Xa,Xn=mr[lo]=mr[lo]||{};this.calculateGlyphDependencies(Mo.text,Xn,sa,this.allowVerticalPlacement,fo)}}}fe.get("symbol-placement")==="line"&&(this.features=function(ui){let yi={},vn={},zi=[],un=0;function Tn(Xa){zi.push(ui[Xa]),un++}function pa(Xa,sa,Mo){let fo=vn[Xa];return delete vn[Xa],vn[sa]=fo,zi[fo].geometry[0].pop(),zi[fo].geometry[0]=zi[fo].geometry[0].concat(Mo[0]),fo}function ro(Xa,sa,Mo){let fo=yi[sa];return delete 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this.symbolInstances.length===0&&!this.hasRTLText}uploadPending(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload}upload(A){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(A),this.iconCollisionBox.upload(A)),this.text.upload(A,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(A,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0}destroyDebugData(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()}destroy(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()}addToLineVertexArray(A,F){let W=this.lineVertexArray.length;if(A.segment!==void 0){let re=A.dist(F[A.segment+1]),fe=A.dist(F[A.segment]),pe={};for(let ze=A.segment+1;ze=0;ze--)pe[ze]={x:F[ze].x,y:F[ze].y,tileUnitDistanceFromAnchor:fe},ze>0&&(fe+=F[ze-1].dist(F[ze]));for(let ze=0;ze0}hasIconData(){return this.icon.segments.get().length>0}hasDebugData(){return this.textCollisionBox&&this.iconCollisionBox}hasTextCollisionBoxData(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0}hasIconCollisionBoxData(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0}addIndicesForPlacedSymbol(A,F){let W=A.placedSymbolArray.get(F),re=W.vertexStartIndex+4*W.numGlyphs;for(let fe=W.vertexStartIndex;fere[ze]-re[Ke]||fe[Ke]-fe[ze]),pe}addToSortKeyRanges(A,F){let W=this.sortKeyRanges[this.sortKeyRanges.length-1];W&&W.sortKey===F?W.symbolInstanceEnd=A+1:this.sortKeyRanges.push({sortKey:F,symbolInstanceStart:A,symbolInstanceEnd:A+1})}sortFeatures(A){if(this.sortFeaturesByY&&this.sortedAngle!==A&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(A),this.sortedAngle=A,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(let F of this.symbolInstanceIndexes){let W=this.symbolInstances.get(F);this.featureSortOrder.push(W.featureIndex),[W.rightJustifiedTextSymbolIndex,W.centerJustifiedTextSymbolIndex,W.leftJustifiedTextSymbolIndex].forEach((re,fe,pe)=>{re>=0&&pe.indexOf(re)===fe&&this.addIndicesForPlacedSymbol(this.text,re)}),W.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,W.verticalPlacedTextSymbolIndex),W.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,W.placedIconSymbolIndex),W.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,W.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}}}let Tf,Xx;Fi("SymbolBucket",M1,{omit:["layers","collisionBoxArray","features","compareText"]}),M1.MAX_GLYPHS=65535,M1.addDynamicAttributes=lS;var zw={get paint(){return Xx=Xx||new ue({"icon-opacity":new oo(ce.paint_symbol["icon-opacity"]),"icon-color":new oo(ce.paint_symbol["icon-color"]),"icon-halo-color":new oo(ce.paint_symbol["icon-halo-color"]),"icon-halo-width":new oo(ce.paint_symbol["icon-halo-width"]),"icon-halo-blur":new oo(ce.paint_symbol["icon-halo-blur"]),"icon-translate":new Ua(ce.paint_symbol["icon-translate"]),"icon-translate-anchor":new Ua(ce.paint_symbol["icon-translate-anchor"]),"text-opacity":new oo(ce.paint_symbol["text-opacity"]),"text-color":new oo(ce.paint_symbol["text-color"],{runtimeType:er,getOverride:R=>R.textColor,hasOverride:R=>!!R.textColor}),"text-halo-color":new oo(ce.paint_symbol["text-halo-color"]),"text-halo-width":new oo(ce.paint_symbol["text-halo-width"]),"text-halo-blur":new oo(ce.paint_symbol["text-halo-blur"]),"text-translate":new Ua(ce.paint_symbol["text-translate"]),"text-translate-anchor":new Ua(ce.paint_symbol["text-translate-anchor"])})},get layout(){return Tf=Tf||new ue({"symbol-placement":new Ua(ce.layout_symbol["symbol-placement"]),"symbol-spacing":new Ua(ce.layout_symbol["symbol-spacing"]),"symbol-avoid-edges":new Ua(ce.layout_symbol["symbol-avoid-edges"]),"symbol-sort-key":new oo(ce.layout_symbol["symbol-sort-key"]),"symbol-z-order":new Ua(ce.layout_symbol["symbol-z-order"]),"icon-allow-overlap":new Ua(ce.layout_symbol["icon-allow-overlap"]),"icon-overlap":new Ua(ce.layout_symbol["icon-overlap"]),"icon-ignore-placement":new Ua(ce.layout_symbol["icon-ignore-placement"]),"icon-optional":new Ua(ce.layout_symbol["icon-optional"]),"icon-rotation-alignment":new Ua(ce.layout_symbol["icon-rotation-alignment"]),"icon-size":new oo(ce.layout_symbol["icon-size"]),"icon-text-fit":new Ua(ce.layout_symbol["icon-text-fit"]),"icon-text-fit-padding":new Ua(ce.layout_symbol["icon-text-fit-padding"]),"icon-image":new oo(ce.layout_symbol["icon-image"]),"icon-rotate":new oo(ce.layout_symbol["icon-rotate"]),"icon-padding":new oo(ce.layout_symbol["icon-padding"]),"icon-keep-upright":new Ua(ce.layout_symbol["icon-keep-upright"]),"icon-offset":new oo(ce.layout_symbol["icon-offset"]),"icon-anchor":new oo(ce.layout_symbol["icon-anchor"]),"icon-pitch-alignment":new Ua(ce.layout_symbol["icon-pitch-alignment"]),"text-pitch-alignment":new Ua(ce.layout_symbol["text-pitch-alignment"]),"text-rotation-alignment":new Ua(ce.layout_symbol["text-rotation-alignment"]),"text-field":new oo(ce.layout_symbol["text-field"]),"text-font":new oo(ce.layout_symbol["text-font"]),"text-size":new oo(ce.layout_symbol["text-size"]),"text-max-width":new oo(ce.layout_symbol["text-max-width"]),"text-line-height":new Ua(ce.layout_symbol["text-line-height"]),"text-letter-spacing":new oo(ce.layout_symbol["text-letter-spacing"]),"text-justify":new oo(ce.layout_symbol["text-justify"]),"text-radial-offset":new oo(ce.layout_symbol["text-radial-offset"]),"text-variable-anchor":new Ua(ce.layout_symbol["text-variable-anchor"]),"text-variable-anchor-offset":new oo(ce.layout_symbol["text-variable-anchor-offset"]),"text-anchor":new oo(ce.layout_symbol["text-anchor"]),"text-max-angle":new Ua(ce.layout_symbol["text-max-angle"]),"text-writing-mode":new Ua(ce.layout_symbol["text-writing-mode"]),"text-rotate":new oo(ce.layout_symbol["text-rotate"]),"text-padding":new Ua(ce.layout_symbol["text-padding"]),"text-keep-upright":new Ua(ce.layout_symbol["text-keep-upright"]),"text-transform":new oo(ce.layout_symbol["text-transform"]),"text-offset":new oo(ce.layout_symbol["text-offset"]),"text-allow-overlap":new Ua(ce.layout_symbol["text-allow-overlap"]),"text-overlap":new Ua(ce.layout_symbol["text-overlap"]),"text-ignore-placement":new Ua(ce.layout_symbol["text-ignore-placement"]),"text-optional":new Ua(ce.layout_symbol["text-optional"])})}};class Zx{constructor(A){if(A.property.overrides===void 0)throw new Error("overrides must be provided to instantiate FormatSectionOverride class");this.type=A.property.overrides?A.property.overrides.runtimeType:Vt,this.defaultValue=A}evaluate(A){if(A.formattedSection){let F=this.defaultValue.property.overrides;if(F&&F.hasOverride(A.formattedSection))return F.getOverride(A.formattedSection)}return A.feature&&A.featureState?this.defaultValue.evaluate(A.feature,A.featureState):this.defaultValue.property.specification.default}eachChild(A){this.defaultValue.isConstant()||A(this.defaultValue.value._styleExpression.expression)}outputDefined(){return!1}serialize(){return null}}Fi("FormatSectionOverride",Zx,{omit:["defaultValue"]});class cy extends B{constructor(A){super(A,zw)}recalculate(A,F){if(super.recalculate(A,F),this.layout.get("icon-rotation-alignment")==="auto"&&(this.layout._values["icon-rotation-alignment"]=this.layout.get("symbol-placement")!=="point"?"map":"viewport"),this.layout.get("text-rotation-alignment")==="auto"&&(this.layout._values["text-rotation-alignment"]=this.layout.get("symbol-placement")!=="point"?"map":"viewport"),this.layout.get("text-pitch-alignment")==="auto"&&(this.layout._values["text-pitch-alignment"]=this.layout.get("text-rotation-alignment")==="map"?"map":"viewport"),this.layout.get("icon-pitch-alignment")==="auto"&&(this.layout._values["icon-pitch-alignment"]=this.layout.get("icon-rotation-alignment")),this.layout.get("symbol-placement")==="point"){let W=this.layout.get("text-writing-mode");if(W){let re=[];for(let fe of W)re.indexOf(fe)<0&&re.push(fe);this.layout._values["text-writing-mode"]=re}else this.layout._values["text-writing-mode"]=["horizontal"]}this._setPaintOverrides()}getValueAndResolveTokens(A,F,W,re){let fe=this.layout.get(A).evaluate(F,{},W,re),pe=this._unevaluatedLayout._values[A];return pe.isDataDriven()||Dc(pe.value)||!fe?fe:function(ze,Ke){return Ke.replace(/{([^{}]+)}/g,(ct,Lt)=>ze&&Lt in ze?String(ze[Lt]):"")}(F.properties,fe)}createBucket(A){return new M1(A)}queryRadius(){return 0}queryIntersectsFeature(){throw new Error("Should take a different path in FeatureIndex")}_setPaintOverrides(){for(let A of zw.paint.overridableProperties){if(!cy.hasPaintOverride(this.layout,A))continue;let F=this.paint.get(A),W=new Zx(F),re=new Eu(W,F.property.specification),fe=null;fe=F.value.kind==="constant"||F.value.kind==="source"?new bc("source",re):new hu("composite",re,F.value.zoomStops),this.paint._values[A]=new xu(F.property,fe,F.parameters)}}_handleOverridablePaintPropertyUpdate(A,F,W){return!(!this.layout||F.isDataDriven()||W.isDataDriven())&&cy.hasPaintOverride(this.layout,A)}static hasPaintOverride(A,F){let W=A.get("text-field"),re=zw.paint.properties[F],fe=!1,pe=ze=>{for(let Ke of ze)if(re.overrides&&re.overrides.hasOverride(Ke))return void(fe=!0)};if(W.value.kind==="constant"&&W.value.value instanceof ri)pe(W.value.value.sections);else if(W.value.kind==="source"){let ze=ct=>{fe||(ct instanceof ua&&Sn(ct.value)===ti?pe(ct.value.sections):ct instanceof Zl?pe(ct.sections):ct.eachChild(ze))},Ke=W.value;Ke._styleExpression&&ze(Ke._styleExpression.expression)}return fe}}let MC;var Yx={get paint(){return MC=MC||new ue({"background-color":new Ua(ce.paint_background["background-color"]),"background-pattern":new hc(ce.paint_background["background-pattern"]),"background-opacity":new Ua(ce.paint_background["background-opacity"])})}};class J9 extends B{constructor(A){super(A,Yx)}}let fS;var EC={get paint(){return fS=fS||new ue({"raster-opacity":new Ua(ce.paint_raster["raster-opacity"]),"raster-hue-rotate":new Ua(ce.paint_raster["raster-hue-rotate"]),"raster-brightness-min":new Ua(ce.paint_raster["raster-brightness-min"]),"raster-brightness-max":new Ua(ce.paint_raster["raster-brightness-max"]),"raster-saturation":new Ua(ce.paint_raster["raster-saturation"]),"raster-contrast":new Ua(ce.paint_raster["raster-contrast"]),"raster-resampling":new Ua(ce.paint_raster["raster-resampling"]),"raster-fade-duration":new Ua(ce.paint_raster["raster-fade-duration"])})}};class Kx extends B{constructor(A){super(A,EC)}}class hS extends B{constructor(A){super(A,{}),this.onAdd=F=>{this.implementation.onAdd&&this.implementation.onAdd(F,F.painter.context.gl)},this.onRemove=F=>{this.implementation.onRemove&&this.implementation.onRemove(F,F.painter.context.gl)},this.implementation=A}is3D(){return this.implementation.renderingMode==="3d"}hasOffscreenPass(){return this.implementation.prerender!==void 0}recalculate(){}updateTransitions(){}hasTransition(){return!1}serialize(){throw new Error("Custom layers cannot be serialized")}}class dS{constructor(A){this._methodToThrottle=A,this._triggered=!1,typeof MessageChannel!="undefined"&&(this._channel=new MessageChannel,this._channel.port2.onmessage=()=>{this._triggered=!1,this._methodToThrottle()})}trigger(){this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout(()=>{this._triggered=!1,this._methodToThrottle()},0))}remove(){delete this._channel,this._methodToThrottle=()=>{}}}let vS=63710088e-1;class dg{constructor(A,F){if(isNaN(A)||isNaN(F))throw new Error(`Invalid LngLat object: (${A}, ${F})`);if(this.lng=+A,this.lat=+F,this.lat>90||this.lat<-90)throw new Error("Invalid LngLat latitude value: must be between -90 and 90")}wrap(){return new dg(S(this.lng,-180,180),this.lat)}toArray(){return[this.lng,this.lat]}toString(){return`LngLat(${this.lng}, ${this.lat})`}distanceTo(A){let F=Math.PI/180,W=this.lat*F,re=A.lat*F,fe=Math.sin(W)*Math.sin(re)+Math.cos(W)*Math.cos(re)*Math.cos((A.lng-this.lng)*F);return vS*Math.acos(Math.min(fe,1))}static convert(A){if(A instanceof dg)return A;if(Array.isArray(A)&&(A.length===2||A.length===3))return new dg(Number(A[0]),Number(A[1]));if(!Array.isArray(A)&&typeof A=="object"&&A!==null)return new dg(Number("lng"in A?A.lng:A.lon),Number(A.lat));throw new Error("`LngLatLike` argument must be specified as a LngLat instance, an object {lng: , lat: }, an object {lon: , lat: }, or an array of [, ]")}}let E1=2*Math.PI*vS;function kC(R){return E1*Math.cos(R*Math.PI/180)}function Ow(R){return(180+R)/360}function CC(R){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+R*Math.PI/360)))/360}function qw(R,A){return R/kC(A)}function Jx(R){return 360/Math.PI*Math.atan(Math.exp((180-360*R)*Math.PI/180))-90}class $x{constructor(A,F,W=0){this.x=+A,this.y=+F,this.z=+W}static fromLngLat(A,F=0){let W=dg.convert(A);return new $x(Ow(W.lng),CC(W.lat),qw(F,W.lat))}toLngLat(){return new dg(360*this.x-180,Jx(this.y))}toAltitude(){return this.z*kC(Jx(this.y))}meterInMercatorCoordinateUnits(){return 1/E1*(A=Jx(this.y),1/Math.cos(A*Math.PI/180));var A}}function mp(R,A,F){var W=2*Math.PI*6378137/256/Math.pow(2,F);return[R*W-2*Math.PI*6378137/2,A*W-2*Math.PI*6378137/2]}class pS{constructor(A,F,W){if(!function(re,fe,pe){return!(re<0||re>25||pe<0||pe>=Math.pow(2,re)||fe<0||fe>=Math.pow(2,re))}(A,F,W))throw new Error(`x=${F}, y=${W}, z=${A} outside of bounds. 0<=x<${Math.pow(2,A)}, 0<=y<${Math.pow(2,A)} 0<=z<=25 `);this.z=A,this.x=F,this.y=W,this.key=Qx(0,A,A,F,W)}equals(A){return this.z===A.z&&this.x===A.x&&this.y===A.y}url(A,F,W){let re=(pe=this.y,ze=this.z,Ke=mp(256*(fe=this.x),256*(pe=Math.pow(2,ze)-pe-1),ze),ct=mp(256*(fe+1),256*(pe+1),ze),Ke[0]+","+Ke[1]+","+ct[0]+","+ct[1]);var fe,pe,ze,Ke,ct;let Lt=function($t,fr,mr){let Pr,zr="";for(let ui=$t;ui>0;ui--)Pr=1<1?"@2x":"").replace(/{quadkey}/g,Lt).replace(/{bbox-epsg-3857}/g,re)}isChildOf(A){let F=this.z-A.z;return F>0&&A.x===this.x>>F&&A.y===this.y>>F}getTilePoint(A){let F=Math.pow(2,this.z);return new u((A.x*F-this.x)*ja,(A.y*F-this.y)*ja)}toString(){return`${this.z}/${this.x}/${this.y}`}}class LC{constructor(A,F){this.wrap=A,this.canonical=F,this.key=Qx(A,F.z,F.z,F.x,F.y)}}class $v{constructor(A,F,W,re,fe){if(A= z; overscaledZ = ${A}; z = ${W}`);this.overscaledZ=A,this.wrap=F,this.canonical=new pS(W,+re,+fe),this.key=Qx(F,A,W,re,fe)}clone(){return new $v(this.overscaledZ,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)}equals(A){return this.overscaledZ===A.overscaledZ&&this.wrap===A.wrap&&this.canonical.equals(A.canonical)}scaledTo(A){if(A>this.overscaledZ)throw new Error(`targetZ > this.overscaledZ; targetZ = ${A}; overscaledZ = ${this.overscaledZ}`);let F=this.canonical.z-A;return A>this.canonical.z?new $v(A,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new $v(A,this.wrap,A,this.canonical.x>>F,this.canonical.y>>F)}calculateScaledKey(A,F){if(A>this.overscaledZ)throw new Error(`targetZ > this.overscaledZ; targetZ = ${A}; overscaledZ = ${this.overscaledZ}`);let W=this.canonical.z-A;return A>this.canonical.z?Qx(this.wrap*+F,A,this.canonical.z,this.canonical.x,this.canonical.y):Qx(this.wrap*+F,A,A,this.canonical.x>>W,this.canonical.y>>W)}isChildOf(A){if(A.wrap!==this.wrap)return!1;let F=this.canonical.z-A.canonical.z;return A.overscaledZ===0||A.overscaledZ>F&&A.canonical.y===this.canonical.y>>F}children(A){if(this.overscaledZ>=A)return[new $v(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];let F=this.canonical.z+1,W=2*this.canonical.x,re=2*this.canonical.y;return[new $v(F,this.wrap,F,W,re),new $v(F,this.wrap,F,W+1,re),new $v(F,this.wrap,F,W,re+1),new $v(F,this.wrap,F,W+1,re+1)]}isLessThan(A){return this.wrapA.wrap)&&(this.overscaledZA.overscaledZ)&&(this.canonical.xA.canonical.x)&&this.canonical.ythis.max&&(this.max=$t),$t=this.dim+1||F<-1||F>=this.dim+1)throw new RangeError("out of range source coordinates for DEM data");return(F+1)*this.stride+(A+1)}unpack(A,F,W){return A*this.redFactor+F*this.greenFactor+W*this.blueFactor-this.baseShift}getPixels(){return new Ki({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))}backfillBorder(A,F,W){if(this.dim!==A.dim)throw new Error("dem dimension mismatch");let re=F*this.dim,fe=F*this.dim+this.dim,pe=W*this.dim,ze=W*this.dim+this.dim;switch(F){case-1:re=fe-1;break;case 1:fe=re+1}switch(W){case-1:pe=ze-1;break;case 1:ze=pe+1}let Ke=-F*this.dim,ct=-W*this.dim;for(let Lt=pe;Lt=this._numberToString.length)throw new Error(`Out of bounds. Index requested n=${A} can't be >= this._numberToString.length ${this._numberToString.length}`);return this._numberToString[A]}}class gS{constructor(A,F,W,re,fe){this.type="Feature",this._vectorTileFeature=A,A._z=F,A._x=W,A._y=re,this.properties=A.properties,this.id=fe}get geometry(){return this._geometry===void 0&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry}set geometry(A){this._geometry=A}toJSON(){let A={geometry:this.geometry};for(let F in this)F!=="_geometry"&&F!=="_vectorTileFeature"&&(A[F]=this[F]);return A}}class fy{constructor(A,F){this.tileID=A,this.x=A.canonical.x,this.y=A.canonical.y,this.z=A.canonical.z,this.grid=new Qi(ja,16,0),this.grid3D=new Qi(ja,16,0),this.featureIndexArray=new Ts,this.promoteId=F}insert(A,F,W,re,fe,pe){let ze=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(W,re,fe);let Ke=pe?this.grid3D:this.grid;for(let ct=0;ct=0&&$t[3]>=0&&Ke.insert(ze,$t[0],$t[1],$t[2],$t[3])}}loadVTLayers(){return this.vtLayers||(this.vtLayers=new br.VectorTile(new nS(this.rawTileData)).layers,this.sourceLayerCoder=new IC(this.vtLayers?Object.keys(this.vtLayers).sort():["_geojsonTileLayer"])),this.vtLayers}query(A,F,W,re){this.loadVTLayers();let fe=A.params||{},pe=ja/A.tileSize/A.scale,ze=Fc(fe.filter),Ke=A.queryGeometry,ct=A.queryPadding*pe,Lt=DC(Ke),$t=this.grid.query(Lt.minX-ct,Lt.minY-ct,Lt.maxX+ct,Lt.maxY+ct),fr=DC(A.cameraQueryGeometry),mr=this.grid3D.query(fr.minX-ct,fr.minY-ct,fr.maxX+ct,fr.maxY+ct,(ui,yi,vn,zi)=>function(un,Tn,pa,ro,Vo){for(let sa of un)if(Tn<=sa.x&&pa<=sa.y&&ro>=sa.x&&Vo>=sa.y)return!0;let Xa=[new u(Tn,pa),new u(Tn,Vo),new u(ro,Vo),new u(ro,pa)];if(un.length>2){for(let sa of Xa)if(Ui(un,sa))return!0}for(let sa=0;sa(zi||(zi=$s(un)),Tn.queryIntersectsFeature(Ke,un,pa,zi,this.z,A.transform,pe,A.pixelPosMatrix)))}return Pr}loadMatchingFeature(A,F,W,re,fe,pe,ze,Ke,ct,Lt,$t){let fr=this.bucketLayerIDs[F];if(pe&&!function(ui,yi){for(let vn=0;vn=0)return!0;return!1}(pe,fr))return;let mr=this.sourceLayerCoder.decode(W),Pr=this.vtLayers[mr].feature(re);if(fe.needGeometry){let ui=Sl(Pr,!0);if(!fe.filter(new rs(this.tileID.overscaledZ),ui,this.tileID.canonical))return}else if(!fe.filter(new rs(this.tileID.overscaledZ),Pr))return;let zr=this.getId(Pr,mr);for(let ui=0;ui{let ze=A instanceof Ac?A.get(pe):null;return ze&&ze.evaluate?ze.evaluate(F,W,re):ze})}function DC(R){let A=1/0,F=1/0,W=-1/0,re=-1/0;for(let fe of R)A=Math.min(A,fe.x),F=Math.min(F,fe.y),W=Math.max(W,fe.x),re=Math.max(re,fe.y);return{minX:A,minY:F,maxX:W,maxY:re}}function $9(R,A){return A-R}function FC(R,A,F,W,re){let fe=[];for(let pe=0;pe=W&&$t.x>=W||(Lt.x>=W?Lt=new u(W,Lt.y+(W-Lt.x)/($t.x-Lt.x)*($t.y-Lt.y))._round():$t.x>=W&&($t=new u(W,Lt.y+(W-Lt.x)/($t.x-Lt.x)*($t.y-Lt.y))._round()),Lt.y>=re&&$t.y>=re||(Lt.y>=re?Lt=new u(Lt.x+(re-Lt.y)/($t.y-Lt.y)*($t.x-Lt.x),re)._round():$t.y>=re&&($t=new u(Lt.x+(re-Lt.y)/($t.y-Lt.y)*($t.x-Lt.x),re)._round()),Ke&&Lt.equals(Ke[Ke.length-1])||(Ke=[Lt],fe.push(Ke)),Ke.push($t)))))}}return fe}Fi("FeatureIndex",fy,{omit:["rawTileData","sourceLayerCoder"]});class vg extends u{constructor(A,F,W,re){super(A,F),this.angle=W,re!==void 0&&(this.segment=re)}clone(){return new vg(this.x,this.y,this.angle,this.segment)}}function mS(R,A,F,W,re){if(A.segment===void 0||F===0)return!0;let fe=A,pe=A.segment+1,ze=0;for(;ze>-F/2;){if(pe--,pe<0)return!1;ze-=R[pe].dist(fe),fe=R[pe]}ze+=R[pe].dist(R[pe+1]),pe++;let Ke=[],ct=0;for(;zeW;)ct-=Ke.shift().angleDelta;if(ct>re)return!1;pe++,ze+=Lt.dist($t)}return!0}function zC(R){let A=0;for(let F=0;Fct){let Pr=(ct-Ke)/mr,zr=Lo.number($t.x,fr.x,Pr),ui=Lo.number($t.y,fr.y,Pr),yi=new vg(zr,ui,fr.angleTo($t),Lt);return yi._round(),!pe||mS(R,yi,ze,pe,A)?yi:void 0}Ke+=mr}}function eO(R,A,F,W,re,fe,pe,ze,Ke){let ct=OC(W,fe,pe),Lt=qC(W,re),$t=Lt*pe,fr=R[0].x===0||R[0].x===Ke||R[0].y===0||R[0].y===Ke;return 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s{constructor(Ge){this.tileID=new i.S(Ge.tileID.overscaledZ,Ge.tileID.wrap,Ge.tileID.canonical.z,Ge.tileID.canonical.x,Ge.tileID.canonical.y),this.uid=Ge.uid,this.zoom=Ge.zoom,this.pixelRatio=Ge.pixelRatio,this.tileSize=Ge.tileSize,this.source=Ge.source,this.overscaling=this.tileID.overscaleFactor(),this.showCollisionBoxes=Ge.showCollisionBoxes,this.collectResourceTiming=!!Ge.collectResourceTiming,this.returnDependencies=!!Ge.returnDependencies,this.promoteId=Ge.promoteId,this.inFlightDependencies=[]}parse(Ge,Je,je,tt){return i._(this,void 0,void 0,function*(){this.status="parsing",this.data=Ge,this.collisionBoxArray=new i.a5;let xt=new i.bm(Object.keys(Ge.layers).sort()),Ie=new i.bn(this.tileID,this.promoteId);Ie.bucketLayerIDs=[];let xe={},ke={featureIndex:Ie,iconDependencies:{},patternDependencies:{},glyphDependencies:{},availableImages:je},vt=Je.familiesBySource[this.source];for(let qn in vt){let Fn=Ge.layers[qn];if(!Fn)continue;Fn.version===1&&i.w(`Vector tile source "${this.source}" layer "${qn}" does not use vector tile spec v2 and therefore may have some rendering errors.`);let ra=xt.encode(qn),la=[];for(let Ut=0;Ut=wt.maxzoom||wt.visibility!=="none"&&(l(Ut,this.zoom,je),(xe[wt.id]=wt.createBucket({index:Ie.bucketLayerIDs.length,layers:Ut,zoom:this.zoom,pixelRatio:this.pixelRatio,overscaling:this.overscaling,collisionBoxArray:this.collisionBoxArray,sourceLayerIndex:ra,sourceID:this.source})).populate(la,ke,this.tileID.canonical),Ie.bucketLayerIDs.push(Ut.map(rr=>rr.id)))}}let ir=i.aF(ke.glyphDependencies,qn=>Object.keys(qn).map(Number));this.inFlightDependencies.forEach(qn=>qn==null?void 0:qn.abort()),this.inFlightDependencies=[];let ar=Promise.resolve({});if(Object.keys(ir).length){let qn=new AbortController;this.inFlightDependencies.push(qn),ar=tt.sendAsync({type:"GG",data:{stacks:ir,source:this.source,tileID:this.tileID,type:"glyphs"}},qn)}let vr=Object.keys(ke.iconDependencies),ii=Promise.resolve({});if(vr.length){let qn=new AbortController;this.inFlightDependencies.push(qn),ii=tt.sendAsync({type:"GI",data:{icons:vr,source:this.source,tileID:this.tileID,type:"icons"}},qn)}let pi=Object.keys(ke.patternDependencies),$r=Promise.resolve({});if(pi.length){let qn=new AbortController;this.inFlightDependencies.push(qn),$r=tt.sendAsync({type:"GI",data:{icons:pi,source:this.source,tileID:this.tileID,type:"patterns"}},qn)}let[di,ji,In]=yield Promise.all([ar,ii,$r]),wi=new o(di),On=new i.bo(ji,In);for(let qn in xe){let Fn=xe[qn];Fn instanceof i.a6?(l(Fn.layers,this.zoom,je),i.bp({bucket:Fn,glyphMap:di,glyphPositions:wi.positions,imageMap:ji,imagePositions:On.iconPositions,showCollisionBoxes:this.showCollisionBoxes,canonical:this.tileID.canonical})):Fn.hasPattern&&(Fn instanceof i.bq||Fn instanceof i.br||Fn instanceof i.bs)&&(l(Fn.layers,this.zoom,je),Fn.addFeatures(ke,this.tileID.canonical,On.patternPositions))}return this.status="done",{buckets:Object.values(xe).filter(qn=>!qn.isEmpty()),featureIndex:Ie,collisionBoxArray:this.collisionBoxArray,glyphAtlasImage:wi.image,imageAtlas:On,glyphMap:this.returnDependencies?di:null,iconMap:this.returnDependencies?ji:null,glyphPositions:this.returnDependencies?wi.positions:null}})}}function l(dt,Ge,Je){let je=new i.z(Ge);for(let tt of dt)tt.recalculate(je,Je)}class u{constructor(Ge,Je,je){this.actor=Ge,this.layerIndex=Je,this.availableImages=je,this.fetching={},this.loading={},this.loaded={}}loadVectorTile(Ge,Je){return i._(this,void 0,void 0,function*(){let je=yield i.l(Ge.request,Je);try{return{vectorTile:new i.bt.VectorTile(new i.bu(je.data)),rawData:je.data,cacheControl:je.cacheControl,expires:je.expires}}catch(tt){let xt=new Uint8Array(je.data),Ie=`Unable to parse the tile at ${Ge.request.url}, `;throw Ie+=xt[0]===31&&xt[1]===139?"please make sure the data is not gzipped and that you have configured the relevant header in the server":`got error: ${tt.message}`,new Error(Ie)}})}loadTile(Ge){return i._(this,void 0,void 0,function*(){let Je=Ge.uid,je=!!(Ge&&Ge.request&&Ge.request.collectResourceTiming)&&new i.bv(Ge.request),tt=new s(Ge);this.loading[Je]=tt;let xt=new AbortController;tt.abort=xt;try{let Ie=yield this.loadVectorTile(Ge,xt);if(delete this.loading[Je],!Ie)return null;let xe=Ie.rawData,ke={};Ie.expires&&(ke.expires=Ie.expires),Ie.cacheControl&&(ke.cacheControl=Ie.cacheControl);let vt={};if(je){let ar=je.finish();ar&&(vt.resourceTiming=JSON.parse(JSON.stringify(ar)))}tt.vectorTile=Ie.vectorTile;let ir=tt.parse(Ie.vectorTile,this.layerIndex,this.availableImages,this.actor);this.loaded[Je]=tt,this.fetching[Je]={rawTileData:xe,cacheControl:ke,resourceTiming:vt};try{let ar=yield ir;return i.e({rawTileData:xe.slice(0)},ar,ke,vt)}finally{delete this.fetching[Je]}}catch(Ie){throw delete this.loading[Je],tt.status="done",this.loaded[Je]=tt,Ie}})}reloadTile(Ge){return i._(this,void 0,void 0,function*(){let Je=Ge.uid;if(!this.loaded||!this.loaded[Je])throw new Error("Should not be trying to reload a tile that was never loaded or has been removed");let je=this.loaded[Je];if(je.showCollisionBoxes=Ge.showCollisionBoxes,je.status==="parsing"){let tt=yield je.parse(je.vectorTile,this.layerIndex,this.availableImages,this.actor),xt;if(this.fetching[Je]){let{rawTileData:Ie,cacheControl:xe,resourceTiming:ke}=this.fetching[Je];delete this.fetching[Je],xt=i.e({rawTileData:Ie.slice(0)},tt,xe,ke)}else xt=tt;return xt}if(je.status==="done"&&je.vectorTile)return je.parse(je.vectorTile,this.layerIndex,this.availableImages,this.actor)})}abortTile(Ge){return i._(this,void 0,void 0,function*(){let Je=this.loading,je=Ge.uid;Je&&Je[je]&&Je[je].abort&&(Je[je].abort.abort(),delete Je[je])})}removeTile(Ge){return i._(this,void 0,void 0,function*(){this.loaded&&this.loaded[Ge.uid]&&delete this.loaded[Ge.uid]})}}class c{constructor(){this.loaded={}}loadTile(Ge){return i._(this,void 0,void 0,function*(){let{uid:Je,encoding:je,rawImageData:tt,redFactor:xt,greenFactor:Ie,blueFactor:xe,baseShift:ke}=Ge,vt=tt.width+2,ir=tt.height+2,ar=i.b(tt)?new i.R({width:vt,height:ir},yield i.bw(tt,-1,-1,vt,ir)):tt,vr=new i.bx(Je,ar,je,xt,Ie,xe,ke);return this.loaded=this.loaded||{},this.loaded[Je]=vr,vr})}removeTile(Ge){let Je=this.loaded,je=Ge.uid;Je&&Je[je]&&delete Je[je]}}function f(dt,Ge){if(dt.length!==0){h(dt[0],Ge);for(var Je=1;Je=Math.abs(xe)?Je-ke+xe:xe-ke+Je,Je=ke}Je+je>=0!=!!Ge&&dt.reverse()}var d=i.by(function dt(Ge,Je){var je,tt=Ge&&Ge.type;if(tt==="FeatureCollection")for(je=0;je>31}function O(dt,Ge){for(var Je=dt.loadGeometry(),je=dt.type,tt=0,xt=0,Ie=Je.length,xe=0;xedt},j=Math.fround||(N=new Float32Array(1),dt=>(N[0]=+dt,N[0]));var N;let H=3,te=5,oe=6;class _e{constructor(Ge){this.options=Object.assign(Object.create(Z),Ge),this.trees=new Array(this.options.maxZoom+1),this.stride=this.options.reduce?7:6,this.clusterProps=[]}load(Ge){let{log:Je,minZoom:je,maxZoom:tt}=this.options;Je&&console.time("total time");let xt=`prepare ${Ge.length} points`;Je&&console.time(xt),this.points=Ge;let Ie=[];for(let ke=0;ke=je;ke--){let vt=+Date.now();xe=this.trees[ke]=this._createTree(this._cluster(xe,ke)),Je&&console.log("z%d: %d clusters in %dms",ke,xe.numItems,+Date.now()-vt)}return Je&&console.timeEnd("total time"),this}getClusters(Ge,Je){let je=((Ge[0]+180)%360+360)%360-180,tt=Math.max(-90,Math.min(90,Ge[1])),xt=Ge[2]===180?180:((Ge[2]+180)%360+360)%360-180,Ie=Math.max(-90,Math.min(90,Ge[3]));if(Ge[2]-Ge[0]>=360)je=-180,xt=180;else if(je>xt){let ar=this.getClusters([je,tt,180,Ie],Je),vr=this.getClusters([-180,tt,xt,Ie],Je);return ar.concat(vr)}let xe=this.trees[this._limitZoom(Je)],ke=xe.range(me(je),ie(Ie),me(xt),ie(tt)),vt=xe.data,ir=[];for(let ar of ke){let vr=this.stride*ar;ir.push(vt[vr+te]>1?Ee(vt,vr,this.clusterProps):this.points[vt[vr+H]])}return ir}getChildren(Ge){let Je=this._getOriginId(Ge),je=this._getOriginZoom(Ge),tt="No cluster with the specified id.",xt=this.trees[je];if(!xt)throw new Error(tt);let Ie=xt.data;if(Je*this.stride>=Ie.length)throw new Error(tt);let xe=this.options.radius/(this.options.extent*Math.pow(2,je-1)),ke=xt.within(Ie[Je*this.stride],Ie[Je*this.stride+1],xe),vt=[];for(let ir of ke){let ar=ir*this.stride;Ie[ar+4]===Ge&&vt.push(Ie[ar+te]>1?Ee(Ie,ar,this.clusterProps):this.points[Ie[ar+H]])}if(vt.length===0)throw new Error(tt);return vt}getLeaves(Ge,Je,je){let tt=[];return this._appendLeaves(tt,Ge,Je=Je||10,je=je||0,0),tt}getTile(Ge,Je,je){let tt=this.trees[this._limitZoom(Ge)],xt=Math.pow(2,Ge),{extent:Ie,radius:xe}=this.options,ke=xe/Ie,vt=(je-ke)/xt,ir=(je+1+ke)/xt,ar={features:[]};return this._addTileFeatures(tt.range((Je-ke)/xt,vt,(Je+1+ke)/xt,ir),tt.data,Je,je,xt,ar),Je===0&&this._addTileFeatures(tt.range(1-ke/xt,vt,1,ir),tt.data,xt,je,xt,ar),Je===xt-1&&this._addTileFeatures(tt.range(0,vt,ke/xt,ir),tt.data,-1,je,xt,ar),ar.features.length?ar:null}getClusterExpansionZoom(Ge){let Je=this._getOriginZoom(Ge)-1;for(;Je<=this.options.maxZoom;){let je=this.getChildren(Ge);if(Je++,je.length!==1)break;Ge=je[0].properties.cluster_id}return Je}_appendLeaves(Ge,Je,je,tt,xt){let Ie=this.getChildren(Je);for(let xe of Ie){let ke=xe.properties;if(ke&&ke.cluster?xt+ke.point_count<=tt?xt+=ke.point_count:xt=this._appendLeaves(Ge,ke.cluster_id,je,tt,xt):xt1,ir,ar,vr;if(vt)ir=Ce(Je,ke,this.clusterProps),ar=Je[ke],vr=Je[ke+1];else{let $r=this.points[Je[ke+H]];ir=$r.properties;let[di,ji]=$r.geometry.coordinates;ar=me(di),vr=ie(ji)}let ii={type:1,geometry:[[Math.round(this.options.extent*(ar*xt-je)),Math.round(this.options.extent*(vr*xt-tt))]],tags:ir},pi;pi=vt||this.options.generateId?Je[ke+H]:this.points[Je[ke+H]].id,pi!==void 0&&(ii.id=pi),Ie.features.push(ii)}}_limitZoom(Ge){return Math.max(this.options.minZoom,Math.min(Math.floor(+Ge),this.options.maxZoom+1))}_cluster(Ge,Je){let{radius:je,extent:tt,reduce:xt,minPoints:Ie}=this.options,xe=je/(tt*Math.pow(2,Je)),ke=Ge.data,vt=[],ir=this.stride;for(let ar=0;arJe&&(di+=ke[In+te])}if(di>$r&&di>=Ie){let ji,In=vr*$r,wi=ii*$r,On=-1,qn=((ar/ir|0)<<5)+(Je+1)+this.points.length;for(let Fn of pi){let ra=Fn*ir;if(ke[ra+2]<=Je)continue;ke[ra+2]=Je;let la=ke[ra+te];In+=ke[ra]*la,wi+=ke[ra+1]*la,ke[ra+4]=qn,xt&&(ji||(ji=this._map(ke,ar,!0),On=this.clusterProps.length,this.clusterProps.push(ji)),xt(ji,this._map(ke,ra)))}ke[ar+4]=qn,vt.push(In/di,wi/di,1/0,qn,-1,di),xt&&vt.push(On)}else{for(let ji=0;ji1)for(let ji of pi){let In=ji*ir;if(!(ke[In+2]<=Je)){ke[In+2]=Je;for(let wi=0;wi>5}_getOriginZoom(Ge){return(Ge-this.points.length)%32}_map(Ge,Je,je){if(Ge[Je+te]>1){let Ie=this.clusterProps[Ge[Je+oe]];return je?Object.assign({},Ie):Ie}let tt=this.points[Ge[Je+H]].properties,xt=this.options.map(tt);return je&&xt===tt?Object.assign({},xt):xt}}function Ee(dt,Ge,Je){return{type:"Feature",id:dt[Ge+H],properties:Ce(dt,Ge,Je),geometry:{type:"Point",coordinates:[(je=dt[Ge],360*(je-.5)),Se(dt[Ge+1])]}};var je}function Ce(dt,Ge,Je){let je=dt[Ge+te],tt=je>=1e4?`${Math.round(je/1e3)}k`:je>=1e3?Math.round(je/100)/10+"k":je,xt=dt[Ge+oe],Ie=xt===-1?{}:Object.assign({},Je[xt]);return Object.assign(Ie,{cluster:!0,cluster_id:dt[Ge+H],point_count:je,point_count_abbreviated:tt})}function me(dt){return dt/360+.5}function ie(dt){let Ge=Math.sin(dt*Math.PI/180),Je=.5-.25*Math.log((1+Ge)/(1-Ge))/Math.PI;return Je<0?0:Je>1?1:Je}function Se(dt){let Ge=(180-360*dt)*Math.PI/180;return 360*Math.atan(Math.exp(Ge))/Math.PI-90}function Le(dt,Ge,Je,je){let tt=je,xt=Ge+(Je-Ge>>1),Ie,xe=Je-Ge,ke=dt[Ge],vt=dt[Ge+1],ir=dt[Je],ar=dt[Je+1];for(let vr=Ge+3;vrtt)Ie=vr,tt=ii;else if(ii===tt){let pi=Math.abs(vr-xt);pije&&(Ie-Ge>3&&Le(dt,Ge,Ie,je),dt[Ie+2]=tt,Je-Ie>3&&Le(dt,Ie,Je,je))}function Ae(dt,Ge,Je,je,tt,xt){let Ie=tt-Je,xe=xt-je;if(Ie!==0||xe!==0){let ke=((dt-Je)*Ie+(Ge-je)*xe)/(Ie*Ie+xe*xe);ke>1?(Je=tt,je=xt):ke>0&&(Je+=Ie*ke,je+=xe*ke)}return Ie=dt-Je,xe=Ge-je,Ie*Ie+xe*xe}function Fe(dt,Ge,Je,je){let tt={id:dt==null?null:dt,type:Ge,geometry:Je,tags:je,minX:1/0,minY:1/0,maxX:-1/0,maxY:-1/0};if(Ge==="Point"||Ge==="MultiPoint"||Ge==="LineString")Pe(tt,Je);else if(Ge==="Polygon")Pe(tt,Je[0]);else if(Ge==="MultiLineString")for(let xt of Je)Pe(tt,xt);else if(Ge==="MultiPolygon")for(let xt of Je)Pe(tt,xt[0]);return tt}function Pe(dt,Ge){for(let Je=0;Je0&&(Ie+=je?(tt*ir-vt*xt)/2:Math.sqrt(Math.pow(vt-tt,2)+Math.pow(ir-xt,2))),tt=vt,xt=ir}let xe=Ge.length-3;Ge[2]=1,Le(Ge,0,xe,Je),Ge[xe+2]=1,Ge.size=Math.abs(Ie),Ge.start=0,Ge.end=Ge.size}function Ze(dt,Ge,Je,je){for(let tt=0;tt1?1:Je}function Zt(dt,Ge,Je,je,tt,xt,Ie,xe){if(je/=Ge,xt>=(Je/=Ge)&&Ie=je)return null;let ke=[];for(let vt of dt){let ir=vt.geometry,ar=vt.type,vr=tt===0?vt.minX:vt.minY,ii=tt===0?vt.maxX:vt.maxY;if(vr>=Je&&ii=je)continue;let pi=[];if(ar==="Point"||ar==="MultiPoint")st(ir,pi,Je,je,tt);else if(ar==="LineString")lt(ir,pi,Je,je,tt,!1,xe.lineMetrics);else if(ar==="MultiLineString")Nt(ir,pi,Je,je,tt,!1);else if(ar==="Polygon")Nt(ir,pi,Je,je,tt,!0);else if(ar==="MultiPolygon")for(let $r of ir){let di=[];Nt($r,di,Je,je,tt,!0),di.length&&pi.push(di)}if(pi.length){if(xe.lineMetrics&&ar==="LineString"){for(let $r of pi)ke.push(Fe(vt.id,ar,$r,vt.tags));continue}ar!=="LineString"&&ar!=="MultiLineString"||(pi.length===1?(ar="LineString",pi=pi[0]):ar="MultiLineString"),ar!=="Point"&&ar!=="MultiPoint"||(ar=pi.length===3?"Point":"MultiPoint"),ke.push(Fe(vt.id,ar,pi,vt.tags))}}return ke.length?ke:null}function st(dt,Ge,Je,je,tt){for(let xt=0;xt=Je&&Ie<=je&&Jt(Ge,dt[xt],dt[xt+1],dt[xt+2])}}function lt(dt,Ge,Je,je,tt,xt,Ie){let xe=Gt(dt),ke=tt===0?sr:wr,vt,ir,ar=dt.start;for(let di=0;diJe&&(ir=ke(xe,ji,In,On,qn,Je),Ie&&(xe.start=ar+vt*ir)):Fn>je?ra=Je&&(ir=ke(xe,ji,In,On,qn,Je),la=!0),ra>je&&Fn<=je&&(ir=ke(xe,ji,In,On,qn,je),la=!0),!xt&&la&&(Ie&&(xe.end=ar+vt*ir),Ge.push(xe),xe=Gt(dt)),Ie&&(ar+=vt)}let vr=dt.length-3,ii=dt[vr],pi=dt[vr+1],$r=tt===0?ii:pi;$r>=Je&&$r<=je&&Jt(xe,ii,pi,dt[vr+2]),vr=xe.length-3,xt&&vr>=3&&(xe[vr]!==xe[0]||xe[vr+1]!==xe[1])&&Jt(xe,xe[0],xe[1],xe[2]),xe.length&&Ge.push(xe)}function Gt(dt){let Ge=[];return Ge.size=dt.size,Ge.start=dt.start,Ge.end=dt.end,Ge}function Nt(dt,Ge,Je,je,tt,xt){for(let Ie of dt)lt(Ie,Ge,Je,je,tt,xt,!1)}function Jt(dt,Ge,Je,je){dt.push(Ge,Je,je)}function sr(dt,Ge,Je,je,tt,xt){let Ie=(xt-Ge)/(je-Ge);return Jt(dt,xt,Je+(tt-Je)*Ie,1),Ie}function wr(dt,Ge,Je,je,tt,xt){let Ie=(xt-Je)/(tt-Je);return Jt(dt,Ge+(je-Ge)*Ie,xt,1),Ie}function cr(dt,Ge){let Je=[];for(let je=0;je0&&Ge.size<(tt?Ie:je))return void(Je.numPoints+=Ge.length/3);let xe=[];for(let ke=0;keIe)&&(Je.numSimplified++,xe.push(Ge[ke],Ge[ke+1])),Je.numPoints++;tt&&function(ke,vt){let ir=0;for(let ar=0,vr=ke.length,ii=vr-2;ar0===vt)for(let ar=0,vr=ke.length;ar24)throw new Error("maxZoom should be in the 0-24 range");if(Je.promoteId&&Je.generateId)throw new Error("promoteId and generateId cannot be used together.");let tt=function(xt,Ie){let xe=[];if(xt.type==="FeatureCollection")for(let ke=0;ke1&&console.time("creation"),ii=this.tiles[vr]=Vt(Ge,Je,je,tt,vt),this.tileCoords.push({z:Je,x:je,y:tt}),ir)){ir>1&&(console.log("tile z%d-%d-%d (features: %d, points: %d, simplified: %d)",Je,je,tt,ii.numFeatures,ii.numPoints,ii.numSimplified),console.timeEnd("creation"));let la=`z${Je}`;this.stats[la]=(this.stats[la]||0)+1,this.total++}if(ii.source=Ge,xt==null){if(Je===vt.indexMaxZoom||ii.numPoints<=vt.indexMaxPoints)continue}else{if(Je===vt.maxZoom||Je===xt)continue;if(xt!=null){let la=xt-Je;if(je!==Ie>>la||tt!==xe>>la)continue}}if(ii.source=null,Ge.length===0)continue;ir>1&&console.time("clipping");let pi=.5*vt.buffer/vt.extent,$r=.5-pi,di=.5+pi,ji=1+pi,In=null,wi=null,On=null,qn=null,Fn=Zt(Ge,ar,je-pi,je+di,0,ii.minX,ii.maxX,vt),ra=Zt(Ge,ar,je+$r,je+ji,0,ii.minX,ii.maxX,vt);Ge=null,Fn&&(In=Zt(Fn,ar,tt-pi,tt+di,1,ii.minY,ii.maxY,vt),wi=Zt(Fn,ar,tt+$r,tt+ji,1,ii.minY,ii.maxY,vt),Fn=null),ra&&(On=Zt(ra,ar,tt-pi,tt+di,1,ii.minY,ii.maxY,vt),qn=Zt(ra,ar,tt+$r,tt+ji,1,ii.minY,ii.maxY,vt),ra=null),ir>1&&console.timeEnd("clipping"),ke.push(In||[],Je+1,2*je,2*tt),ke.push(wi||[],Je+1,2*je,2*tt+1),ke.push(On||[],Je+1,2*je+1,2*tt),ke.push(qn||[],Je+1,2*je+1,2*tt+1)}}getTile(Ge,Je,je){Ge=+Ge,Je=+Je,je=+je;let tt=this.options,{extent:xt,debug:Ie}=tt;if(Ge<0||Ge>24)return null;let xe=1<1&&console.log("drilling down to z%d-%d-%d",Ge,Je,je);let vt,ir=Ge,ar=Je,vr=je;for(;!vt&&ir>0;)ir--,ar>>=1,vr>>=1,vt=this.tiles[lr(ir,ar,vr)];return vt&&vt.source?(Ie>1&&(console.log("found parent tile z%d-%d-%d",ir,ar,vr),console.time("drilling down")),this.splitTile(vt.source,ir,ar,vr,Ge,Je,je),Ie>1&&console.timeEnd("drilling down"),this.tiles[ke]?St(this.tiles[ke],xt):null):null}}function lr(dt,Ge,Je){return 32*((1<{ar.properties=ii;let pi={};for(let $r of vr)pi[$r]=ke[$r].evaluate(ir,ar);return pi},Ie.reduce=(ii,pi)=>{ar.properties=pi;for(let $r of vr)ir.accumulated=ii[$r],ii[$r]=vt[$r].evaluate(ir,ar)},Ie}(Ge)).load((yield this._pendingData).features):(tt=yield this._pendingData,new er(tt,Ge.geojsonVtOptions)),this.loaded={};let xt={};if(je){let Ie=je.finish();Ie&&(xt.resourceTiming={},xt.resourceTiming[Ge.source]=JSON.parse(JSON.stringify(Ie)))}return xt}catch(xt){if(delete this._pendingRequest,i.bB(xt))return{abandoned:!0};throw xt}var tt})}getData(){return i._(this,void 0,void 0,function*(){return this._pendingData})}reloadTile(Ge){let Je=this.loaded;return Je&&Je[Ge.uid]?super.reloadTile(Ge):this.loadTile(Ge)}loadAndProcessGeoJSON(Ge,Je){return i._(this,void 0,void 0,function*(){let je=yield this.loadGeoJSON(Ge,Je);if(delete this._pendingRequest,typeof je!="object")throw new Error(`Input data given to '${Ge.source}' is not a valid GeoJSON object.`);if(d(je,!0),Ge.filter){let tt=i.bC(Ge.filter,{type:"boolean","property-type":"data-driven",overridable:!1,transition:!1});if(tt.result==="error")throw new Error(tt.value.map(Ie=>`${Ie.key}: ${Ie.message}`).join(", "));je={type:"FeatureCollection",features:je.features.filter(Ie=>tt.value.evaluate({zoom:0},Ie))}}return je})}loadGeoJSON(Ge,Je){return i._(this,void 0,void 0,function*(){let{promoteId:je}=Ge;if(Ge.request){let tt=yield i.h(Ge.request,Je);return this._dataUpdateable=Lr(tt.data,je)?ti(tt.data,je):void 0,tt.data}if(typeof Ge.data=="string")try{let tt=JSON.parse(Ge.data);return this._dataUpdateable=Lr(tt,je)?ti(tt,je):void 0,tt}catch(tt){throw new Error(`Input data given to '${Ge.source}' is not a valid GeoJSON object.`)}if(!Ge.dataDiff)throw new Error(`Input data given to '${Ge.source}' is not a valid GeoJSON object.`);if(!this._dataUpdateable)throw new Error(`Cannot update existing geojson data in ${Ge.source}`);return function(tt,xt,Ie){var xe,ke,vt,ir;if(xt.removeAll&&tt.clear(),xt.remove)for(let ar of xt.remove)tt.delete(ar);if(xt.add)for(let ar of xt.add){let vr=Tr(ar,Ie);vr!=null&&tt.set(vr,ar)}if(xt.update)for(let ar of xt.update){let vr=tt.get(ar.id);if(vr==null)continue;let ii=!ar.removeAllProperties&&(((xe=ar.removeProperties)===null||xe===void 0?void 0:xe.length)>0||((ke=ar.addOrUpdateProperties)===null||ke===void 0?void 0:ke.length)>0);if((ar.newGeometry||ar.removeAllProperties||ii)&&(vr=Object.assign({},vr),tt.set(ar.id,vr),ii&&(vr.properties=Object.assign({},vr.properties))),ar.newGeometry&&(vr.geometry=ar.newGeometry),ar.removeAllProperties)vr.properties={};else if(((vt=ar.removeProperties)===null||vt===void 0?void 0:vt.length)>0)for(let pi of ar.removeProperties)Object.prototype.hasOwnProperty.call(vr.properties,pi)&&delete vr.properties[pi];if(((ir=ar.addOrUpdateProperties)===null||ir===void 0?void 0:ir.length)>0)for(let{key:pi,value:$r}of ar.addOrUpdateProperties)vr.properties[pi]=$r}}(this._dataUpdateable,Ge.dataDiff,je),{type:"FeatureCollection",features:Array.from(this._dataUpdateable.values())}})}removeSource(Ge){return i._(this,void 0,void 0,function*(){this._pendingRequest&&this._pendingRequest.abort()})}getClusterExpansionZoom(Ge){return this._geoJSONIndex.getClusterExpansionZoom(Ge.clusterId)}getClusterChildren(Ge){return this._geoJSONIndex.getChildren(Ge.clusterId)}getClusterLeaves(Ge){return this._geoJSONIndex.getLeaves(Ge.clusterId,Ge.limit,Ge.offset)}}class Vr{constructor(Ge){this.self=Ge,this.actor=new i.F(Ge),this.layerIndexes={},this.availableImages={},this.workerSources={},this.demWorkerSources={},this.externalWorkerSourceTypes={},this.self.registerWorkerSource=(Je,je)=>{if(this.externalWorkerSourceTypes[Je])throw new Error(`Worker source with name "${Je}" already registered.`);this.externalWorkerSourceTypes[Je]=je},this.self.addProtocol=i.bi,this.self.removeProtocol=i.bj,this.self.registerRTLTextPlugin=Je=>{if(i.bD.isParsed())throw new Error("RTL text plugin already registered.");i.bD.setMethods(Je)},this.actor.registerMessageHandler("LDT",(Je,je)=>this._getDEMWorkerSource(Je,je.source).loadTile(je)),this.actor.registerMessageHandler("RDT",(Je,je)=>i._(this,void 0,void 0,function*(){this._getDEMWorkerSource(Je,je.source).removeTile(je)})),this.actor.registerMessageHandler("GCEZ",(Je,je)=>i._(this,void 0,void 0,function*(){return this._getWorkerSource(Je,je.type,je.source).getClusterExpansionZoom(je)})),this.actor.registerMessageHandler("GCC",(Je,je)=>i._(this,void 0,void 0,function*(){return this._getWorkerSource(Je,je.type,je.source).getClusterChildren(je)})),this.actor.registerMessageHandler("GCL",(Je,je)=>i._(this,void 0,void 0,function*(){return this._getWorkerSource(Je,je.type,je.source).getClusterLeaves(je)})),this.actor.registerMessageHandler("LD",(Je,je)=>this._getWorkerSource(Je,je.type,je.source).loadData(je)),this.actor.registerMessageHandler("GD",(Je,je)=>this._getWorkerSource(Je,je.type,je.source).getData()),this.actor.registerMessageHandler("LT",(Je,je)=>this._getWorkerSource(Je,je.type,je.source).loadTile(je)),this.actor.registerMessageHandler("RT",(Je,je)=>this._getWorkerSource(Je,je.type,je.source).reloadTile(je)),this.actor.registerMessageHandler("AT",(Je,je)=>this._getWorkerSource(Je,je.type,je.source).abortTile(je)),this.actor.registerMessageHandler("RMT",(Je,je)=>this._getWorkerSource(Je,je.type,je.source).removeTile(je)),this.actor.registerMessageHandler("RS",(Je,je)=>i._(this,void 0,void 0,function*(){if(!this.workerSources[Je]||!this.workerSources[Je][je.type]||!this.workerSources[Je][je.type][je.source])return;let tt=this.workerSources[Je][je.type][je.source];delete this.workerSources[Je][je.type][je.source],tt.removeSource!==void 0&&tt.removeSource(je)})),this.actor.registerMessageHandler("RM",Je=>i._(this,void 0,void 0,function*(){delete this.layerIndexes[Je],delete this.availableImages[Je],delete this.workerSources[Je],delete this.demWorkerSources[Je]})),this.actor.registerMessageHandler("SR",(Je,je)=>i._(this,void 0,void 0,function*(){this.referrer=je})),this.actor.registerMessageHandler("SRPS",(Je,je)=>this._syncRTLPluginState(Je,je)),this.actor.registerMessageHandler("IS",(Je,je)=>i._(this,void 0,void 0,function*(){this.self.importScripts(je)})),this.actor.registerMessageHandler("SI",(Je,je)=>this._setImages(Je,je)),this.actor.registerMessageHandler("UL",(Je,je)=>i._(this,void 0,void 0,function*(){this._getLayerIndex(Je).update(je.layers,je.removedIds)})),this.actor.registerMessageHandler("SL",(Je,je)=>i._(this,void 0,void 0,function*(){this._getLayerIndex(Je).replace(je)}))}_setImages(Ge,Je){return i._(this,void 0,void 0,function*(){this.availableImages[Ge]=Je;for(let je in this.workerSources[Ge]){let tt=this.workerSources[Ge][je];for(let xt in tt)tt[xt].availableImages=Je}})}_syncRTLPluginState(Ge,Je){return i._(this,void 0,void 0,function*(){if(i.bD.isParsed())return i.bD.getState();if(Je.pluginStatus!=="loading")return i.bD.setState(Je),Je;let je=Je.pluginURL;if(this.self.importScripts(je),i.bD.isParsed()){let tt={pluginStatus:"loaded",pluginURL:je};return i.bD.setState(tt),tt}throw i.bD.setState({pluginStatus:"error",pluginURL:""}),new Error(`RTL Text Plugin failed to import scripts from ${je}`)})}_getAvailableImages(Ge){let Je=this.availableImages[Ge];return Je||(Je=[]),Je}_getLayerIndex(Ge){let Je=this.layerIndexes[Ge];return Je||(Je=this.layerIndexes[Ge]=new a),Je}_getWorkerSource(Ge,Je,je){if(this.workerSources[Ge]||(this.workerSources[Ge]={}),this.workerSources[Ge][Je]||(this.workerSources[Ge][Je]={}),!this.workerSources[Ge][Je][je]){let tt={sendAsync:(xt,Ie)=>(xt.targetMapId=Ge,this.actor.sendAsync(xt,Ie))};switch(Je){case"vector":this.workerSources[Ge][Je][je]=new u(tt,this._getLayerIndex(Ge),this._getAvailableImages(Ge));break;case"geojson":this.workerSources[Ge][Je][je]=new Br(tt,this._getLayerIndex(Ge),this._getAvailableImages(Ge));break;default:this.workerSources[Ge][Je][je]=new this.externalWorkerSourceTypes[Je](tt,this._getLayerIndex(Ge),this._getAvailableImages(Ge))}}return this.workerSources[Ge][Je][je]}_getDEMWorkerSource(Ge,Je){return this.demWorkerSources[Ge]||(this.demWorkerSources[Ge]={}),this.demWorkerSources[Ge][Je]||(this.demWorkerSources[Ge][Je]=new c),this.demWorkerSources[Ge][Je]}}return i.i(self)&&(self.worker=new Vr(self)),Vr}),r("index",["exports","./shared"],function(i,a){"use strict";var o="4.7.1";let s,l,u={now:typeof performance!="undefined"&&performance&&performance.now?performance.now.bind(performance):Date.now.bind(Date),frameAsync:ue=>new Promise((w,B)=>{let Q=requestAnimationFrame(w);ue.signal.addEventListener("abort",()=>{cancelAnimationFrame(Q),B(a.c())})}),getImageData(ue,w=0){return this.getImageCanvasContext(ue).getImageData(-w,-w,ue.width+2*w,ue.height+2*w)},getImageCanvasContext(ue){let w=window.document.createElement("canvas"),B=w.getContext("2d",{willReadFrequently:!0});if(!B)throw new Error("failed to create canvas 2d context");return w.width=ue.width,w.height=ue.height,B.drawImage(ue,0,0,ue.width,ue.height),B},resolveURL:ue=>(s||(s=document.createElement("a")),s.href=ue,s.href),hardwareConcurrency:typeof navigator!="undefined"&&navigator.hardwareConcurrency||4,get prefersReducedMotion(){return!!matchMedia&&(l==null&&(l=matchMedia("(prefers-reduced-motion: reduce)")),l.matches)}};class c{static testProp(w){if(!c.docStyle)return w[0];for(let B=0;B{window.removeEventListener("click",c.suppressClickInternal,!0)},0)}static getScale(w){let B=w.getBoundingClientRect();return{x:B.width/w.offsetWidth||1,y:B.height/w.offsetHeight||1,boundingClientRect:B}}static getPoint(w,B,Q){let ee=B.boundingClientRect;return new a.P((Q.clientX-ee.left)/B.x-w.clientLeft,(Q.clientY-ee.top)/B.y-w.clientTop)}static mousePos(w,B){let Q=c.getScale(w);return c.getPoint(w,Q,B)}static touchPos(w,B){let Q=[],ee=c.getScale(w);for(let le=0;le{h&&b(h),h=null,_=!0},d.onerror=()=>{v=!0,h=null},d.src="data:image/webp;base64,UklGRh4AAABXRUJQVlA4TBEAAAAvAQAAAAfQ//73v/+BiOh/AAA="),function(ue){let w,B,Q,ee;ue.resetRequestQueue=()=>{w=[],B=0,Q=0,ee={}},ue.addThrottleControl=ot=>{let Tt=Q++;return ee[Tt]=ot,Tt},ue.removeThrottleControl=ot=>{delete ee[ot],qe()},ue.getImage=(ot,Tt,Yt=!0)=>new Promise((Kt,xr)=>{f.supported&&(ot.headers||(ot.headers={}),ot.headers.accept="image/webp,*/*"),a.e(ot,{type:"image"}),w.push({abortController:Tt,requestParameters:ot,supportImageRefresh:Yt,state:"queued",onError:Ir=>{xr(Ir)},onSuccess:Ir=>{Kt(Ir)}}),qe()});let le=ot=>a._(this,void 0,void 0,function*(){ot.state="running";let{requestParameters:Tt,supportImageRefresh:Yt,onError:Kt,onSuccess:xr,abortController:Ir}=ot,ve=Yt===!1&&!a.i(self)&&!a.g(Tt.url)&&(!Tt.headers||Object.keys(Tt.headers).reduce((Be,et)=>Be&&et==="accept",!0));B++;let be=ve?Xe(Tt,Ir):a.m(Tt,Ir);try{let Be=yield be;delete ot.abortController,ot.state="completed",Be.data instanceof HTMLImageElement||a.b(Be.data)?xr(Be):Be.data&&xr({data:yield(De=Be.data,typeof createImageBitmap=="function"?a.d(De):a.f(De)),cacheControl:Be.cacheControl,expires:Be.expires})}catch(Be){delete ot.abortController,Kt(Be)}finally{B--,qe()}var De}),qe=()=>{let ot=(()=>{for(let Tt of Object.keys(ee))if(ee[Tt]())return!0;return!1})()?a.a.MAX_PARALLEL_IMAGE_REQUESTS_PER_FRAME:a.a.MAX_PARALLEL_IMAGE_REQUESTS;for(let Tt=B;Tt0;Tt++){let Yt=w.shift();Yt.abortController.signal.aborted?Tt--:le(Yt)}},Xe=(ot,Tt)=>new Promise((Yt,Kt)=>{let xr=new Image,Ir=ot.url,ve=ot.credentials;ve&&ve==="include"?xr.crossOrigin="use-credentials":(ve&&ve==="same-origin"||!a.s(Ir))&&(xr.crossOrigin="anonymous"),Tt.signal.addEventListener("abort",()=>{xr.src="",Kt(a.c())}),xr.fetchPriority="high",xr.onload=()=>{xr.onerror=xr.onload=null,Yt({data:xr})},xr.onerror=()=>{xr.onerror=xr.onload=null,Tt.signal.aborted||Kt(new Error("Could not load image. Please make sure to use a supported image type such as PNG or JPEG. Note that SVGs are not supported."))},xr.src=Ir})}(p||(p={})),p.resetRequestQueue();class k{constructor(w){this._transformRequestFn=w}transformRequest(w,B){return this._transformRequestFn&&this._transformRequestFn(w,B)||{url:w}}setTransformRequest(w){this._transformRequestFn=w}}function E(ue){var w=new a.A(3);return w[0]=ue[0],w[1]=ue[1],w[2]=ue[2],w}var S,L=function(ue,w,B){return ue[0]=w[0]-B[0],ue[1]=w[1]-B[1],ue[2]=w[2]-B[2],ue};S=new a.A(3),a.A!=Float32Array&&(S[0]=0,S[1]=0,S[2]=0);var x=function(ue){var w=ue[0],B=ue[1];return w*w+B*B};function C(ue){let w=[];if(typeof ue=="string")w.push({id:"default",url:ue});else if(ue&&ue.length>0){let B=[];for(let{id:Q,url:ee}of ue){let le=`${Q}${ee}`;B.indexOf(le)===-1&&(B.push(le),w.push({id:Q,url:ee}))}}return w}function M(ue,w,B){let Q=ue.split("?");return Q[0]+=`${w}${B}`,Q.join("?")}(function(){var ue=new a.A(2);a.A!=Float32Array&&(ue[0]=0,ue[1]=0)})();class g{constructor(w,B,Q,ee){this.context=w,this.format=Q,this.texture=w.gl.createTexture(),this.update(B,ee)}update(w,B,Q){let{width:ee,height:le}=w,qe=!(this.size&&this.size[0]===ee&&this.size[1]===le||Q),{context:Xe}=this,{gl:ot}=Xe;if(this.useMipmap=!!(B&&B.useMipmap),ot.bindTexture(ot.TEXTURE_2D,this.texture),Xe.pixelStoreUnpackFlipY.set(!1),Xe.pixelStoreUnpack.set(1),Xe.pixelStoreUnpackPremultiplyAlpha.set(this.format===ot.RGBA&&(!B||B.premultiply!==!1)),qe)this.size=[ee,le],w instanceof HTMLImageElement||w instanceof HTMLCanvasElement||w instanceof HTMLVideoElement||w instanceof ImageData||a.b(w)?ot.texImage2D(ot.TEXTURE_2D,0,this.format,this.format,ot.UNSIGNED_BYTE,w):ot.texImage2D(ot.TEXTURE_2D,0,this.format,ee,le,0,this.format,ot.UNSIGNED_BYTE,w.data);else{let{x:Tt,y:Yt}=Q||{x:0,y:0};w instanceof HTMLImageElement||w instanceof HTMLCanvasElement||w instanceof HTMLVideoElement||w instanceof ImageData||a.b(w)?ot.texSubImage2D(ot.TEXTURE_2D,0,Tt,Yt,ot.RGBA,ot.UNSIGNED_BYTE,w):ot.texSubImage2D(ot.TEXTURE_2D,0,Tt,Yt,ee,le,ot.RGBA,ot.UNSIGNED_BYTE,w.data)}this.useMipmap&&this.isSizePowerOfTwo()&&ot.generateMipmap(ot.TEXTURE_2D)}bind(w,B,Q){let{context:ee}=this,{gl:le}=ee;le.bindTexture(le.TEXTURE_2D,this.texture),Q!==le.LINEAR_MIPMAP_NEAREST||this.isSizePowerOfTwo()||(Q=le.LINEAR),w!==this.filter&&(le.texParameteri(le.TEXTURE_2D,le.TEXTURE_MAG_FILTER,w),le.texParameteri(le.TEXTURE_2D,le.TEXTURE_MIN_FILTER,Q||w),this.filter=w),B!==this.wrap&&(le.texParameteri(le.TEXTURE_2D,le.TEXTURE_WRAP_S,B),le.texParameteri(le.TEXTURE_2D,le.TEXTURE_WRAP_T,B),this.wrap=B)}isSizePowerOfTwo(){return this.size[0]===this.size[1]&&Math.log(this.size[0])/Math.LN2%1==0}destroy(){let{gl:w}=this.context;w.deleteTexture(this.texture),this.texture=null}}function P(ue){let{userImage:w}=ue;return!!(w&&w.render&&w.render())&&(ue.data.replace(new Uint8Array(w.data.buffer)),!0)}class T extends a.E{constructor(){super(),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new a.R({width:1,height:1}),this.dirty=!0}isLoaded(){return this.loaded}setLoaded(w){if(this.loaded!==w&&(this.loaded=w,w)){for(let{ids:B,promiseResolve:Q}of this.requestors)Q(this._getImagesForIds(B));this.requestors=[]}}getImage(w){let B=this.images[w];if(B&&!B.data&&B.spriteData){let Q=B.spriteData;B.data=new a.R({width:Q.width,height:Q.height},Q.context.getImageData(Q.x,Q.y,Q.width,Q.height).data),B.spriteData=null}return B}addImage(w,B){if(this.images[w])throw new Error(`Image id ${w} already exist, use updateImage instead`);this._validate(w,B)&&(this.images[w]=B)}_validate(w,B){let Q=!0,ee=B.data||B.spriteData;return this._validateStretch(B.stretchX,ee&&ee.width)||(this.fire(new a.j(new Error(`Image "${w}" has invalid "stretchX" value`))),Q=!1),this._validateStretch(B.stretchY,ee&&ee.height)||(this.fire(new a.j(new Error(`Image "${w}" has invalid "stretchY" value`))),Q=!1),this._validateContent(B.content,B)||(this.fire(new a.j(new Error(`Image "${w}" has invalid "content" value`))),Q=!1),Q}_validateStretch(w,B){if(!w)return!0;let Q=0;for(let ee of w){if(ee[0]{let ee=!0;if(!this.isLoaded())for(let le of w)this.images[le]||(ee=!1);this.isLoaded()||ee?B(this._getImagesForIds(w)):this.requestors.push({ids:w,promiseResolve:B})})}_getImagesForIds(w){let B={};for(let Q of w){let ee=this.getImage(Q);ee||(this.fire(new a.k("styleimagemissing",{id:Q})),ee=this.getImage(Q)),ee?B[Q]={data:ee.data.clone(),pixelRatio:ee.pixelRatio,sdf:ee.sdf,version:ee.version,stretchX:ee.stretchX,stretchY:ee.stretchY,content:ee.content,textFitWidth:ee.textFitWidth,textFitHeight:ee.textFitHeight,hasRenderCallback:!!(ee.userImage&&ee.userImage.render)}:a.w(`Image "${Q}" could not be loaded. Please make sure you have added the image with map.addImage() or a "sprite" property in your style. You can provide missing images by listening for the "styleimagemissing" map event.`)}return B}getPixelSize(){let{width:w,height:B}=this.atlasImage;return{width:w,height:B}}getPattern(w){let B=this.patterns[w],Q=this.getImage(w);if(!Q)return null;if(B&&B.position.version===Q.version)return B.position;if(B)B.position.version=Q.version;else{let ee={w:Q.data.width+2,h:Q.data.height+2,x:0,y:0},le=new a.I(ee,Q);this.patterns[w]={bin:ee,position:le}}return this._updatePatternAtlas(),this.patterns[w].position}bind(w){let B=w.gl;this.atlasTexture?this.dirty&&(this.atlasTexture.update(this.atlasImage),this.dirty=!1):this.atlasTexture=new g(w,this.atlasImage,B.RGBA),this.atlasTexture.bind(B.LINEAR,B.CLAMP_TO_EDGE)}_updatePatternAtlas(){let w=[];for(let le in this.patterns)w.push(this.patterns[le].bin);let{w:B,h:Q}=a.p(w),ee=this.atlasImage;ee.resize({width:B||1,height:Q||1});for(let le in this.patterns){let{bin:qe}=this.patterns[le],Xe=qe.x+1,ot=qe.y+1,Tt=this.getImage(le).data,Yt=Tt.width,Kt=Tt.height;a.R.copy(Tt,ee,{x:0,y:0},{x:Xe,y:ot},{width:Yt,height:Kt}),a.R.copy(Tt,ee,{x:0,y:Kt-1},{x:Xe,y:ot-1},{width:Yt,height:1}),a.R.copy(Tt,ee,{x:0,y:0},{x:Xe,y:ot+Kt},{width:Yt,height:1}),a.R.copy(Tt,ee,{x:Yt-1,y:0},{x:Xe-1,y:ot},{width:1,height:Kt}),a.R.copy(Tt,ee,{x:0,y:0},{x:Xe+Yt,y:ot},{width:1,height:Kt})}this.dirty=!0}beginFrame(){this.callbackDispatchedThisFrame={}}dispatchRenderCallbacks(w){for(let B of w){if(this.callbackDispatchedThisFrame[B])continue;this.callbackDispatchedThisFrame[B]=!0;let Q=this.getImage(B);Q||a.w(`Image with ID: "${B}" was not found`),P(Q)&&this.updateImage(B,Q)}}}let z=1e20;function O(ue,w,B,Q,ee,le,qe,Xe,ot){for(let Tt=w;Tt-1);ot++,le[ot]=Xe,qe[ot]=Tt,qe[ot+1]=z}for(let Xe=0,ot=0;Xe65535)throw new Error("glyphs > 65535 not supported");if(Q.ranges[le])return{stack:w,id:B,glyph:ee};if(!this.url)throw new Error("glyphsUrl is not set");if(!Q.requests[le]){let Xe=G.loadGlyphRange(w,le,this.url,this.requestManager);Q.requests[le]=Xe}let qe=yield Q.requests[le];for(let Xe in qe)this._doesCharSupportLocalGlyph(+Xe)||(Q.glyphs[+Xe]=qe[+Xe]);return Q.ranges[le]=!0,{stack:w,id:B,glyph:qe[B]||null}})}_doesCharSupportLocalGlyph(w){return!!this.localIdeographFontFamily&&new RegExp("\\p{Ideo}|\\p{sc=Hang}|\\p{sc=Hira}|\\p{sc=Kana}","u").test(String.fromCodePoint(w))}_tinySDF(w,B,Q){let ee=this.localIdeographFontFamily;if(!ee||!this._doesCharSupportLocalGlyph(Q))return;let le=w.tinySDF;if(!le){let Xe="400";/bold/i.test(B)?Xe="900":/medium/i.test(B)?Xe="500":/light/i.test(B)&&(Xe="200"),le=w.tinySDF=new G.TinySDF({fontSize:48,buffer:6,radius:16,cutoff:.25,fontFamily:ee,fontWeight:Xe})}let qe=le.draw(String.fromCharCode(Q));return{id:Q,bitmap:new a.o({width:qe.width||60,height:qe.height||60},qe.data),metrics:{width:qe.glyphWidth/2||24,height:qe.glyphHeight/2||24,left:qe.glyphLeft/2+.5||0,top:qe.glyphTop/2-27.5||-8,advance:qe.glyphAdvance/2||24,isDoubleResolution:!0}}}}G.loadGlyphRange=function(ue,w,B,Q){return a._(this,void 0,void 0,function*(){let ee=256*w,le=ee+255,qe=Q.transformRequest(B.replace("{fontstack}",ue).replace("{range}",`${ee}-${le}`),"Glyphs"),Xe=yield a.l(qe,new AbortController);if(!Xe||!Xe.data)throw new Error(`Could not load glyph range. range: ${w}, ${ee}-${le}`);let ot={};for(let Tt of a.n(Xe.data))ot[Tt.id]=Tt;return ot})},G.TinySDF=class{constructor({fontSize:ue=24,buffer:w=3,radius:B=8,cutoff:Q=.25,fontFamily:ee="sans-serif",fontWeight:le="normal",fontStyle:qe="normal"}={}){this.buffer=w,this.cutoff=Q,this.radius=B;let Xe=this.size=ue+4*w,ot=this._createCanvas(Xe),Tt=this.ctx=ot.getContext("2d",{willReadFrequently:!0});Tt.font=`${qe} ${le} ${ue}px ${ee}`,Tt.textBaseline="alphabetic",Tt.textAlign="left",Tt.fillStyle="black",this.gridOuter=new Float64Array(Xe*Xe),this.gridInner=new Float64Array(Xe*Xe),this.f=new Float64Array(Xe),this.z=new Float64Array(Xe+1),this.v=new Uint16Array(Xe)}_createCanvas(ue){let w=document.createElement("canvas");return w.width=w.height=ue,w}draw(ue){let{width:w,actualBoundingBoxAscent:B,actualBoundingBoxDescent:Q,actualBoundingBoxLeft:ee,actualBoundingBoxRight:le}=this.ctx.measureText(ue),qe=Math.ceil(B),Xe=Math.max(0,Math.min(this.size-this.buffer,Math.ceil(le-ee))),ot=Math.min(this.size-this.buffer,qe+Math.ceil(Q)),Tt=Xe+2*this.buffer,Yt=ot+2*this.buffer,Kt=Math.max(Tt*Yt,0),xr=new Uint8ClampedArray(Kt),Ir={data:xr,width:Tt,height:Yt,glyphWidth:Xe,glyphHeight:ot,glyphTop:qe,glyphLeft:0,glyphAdvance:w};if(Xe===0||ot===0)return Ir;let{ctx:ve,buffer:be,gridInner:De,gridOuter:Be}=this;ve.clearRect(be,be,Xe,ot),ve.fillText(ue,be,be+qe);let et=ve.getImageData(be,be,Xe,ot);Be.fill(z,0,Kt),De.fill(0,0,Kt);for(let We=0;We0?tr*tr:0,De[Ht]=tr<0?tr*tr:0}}O(Be,0,0,Tt,Yt,Tt,this.f,this.v,this.z),O(De,be,be,Xe,ot,Tt,this.f,this.v,this.z);for(let We=0;We1&&(ot=w[++Xe]);let Yt=Math.abs(Tt-ot.left),Kt=Math.abs(Tt-ot.right),xr=Math.min(Yt,Kt),Ir,ve=le/Q*(ee+1);if(ot.isDash){let be=ee-Math.abs(ve);Ir=Math.sqrt(xr*xr+be*be)}else Ir=ee-Math.sqrt(xr*xr+ve*ve);this.data[qe+Tt]=Math.max(0,Math.min(255,Ir+128))}}}addRegularDash(w){for(let Xe=w.length-1;Xe>=0;--Xe){let ot=w[Xe],Tt=w[Xe+1];ot.zeroLength?w.splice(Xe,1):Tt&&Tt.isDash===ot.isDash&&(Tt.left=ot.left,w.splice(Xe,1))}let B=w[0],Q=w[w.length-1];B.isDash===Q.isDash&&(B.left=Q.left-this.width,Q.right=B.right+this.width);let ee=this.width*this.nextRow,le=0,qe=w[le];for(let Xe=0;Xe1&&(qe=w[++le]);let ot=Math.abs(Xe-qe.left),Tt=Math.abs(Xe-qe.right),Yt=Math.min(ot,Tt);this.data[ee+Xe]=Math.max(0,Math.min(255,(qe.isDash?Yt:-Yt)+128))}}addDash(w,B){let Q=B?7:0,ee=2*Q+1;if(this.nextRow+ee>this.height)return a.w("LineAtlas out of space"),null;let le=0;for(let Xe=0;Xe{B.terminate()}),this.workers=null)}isPreloaded(){return!!this.active[_e]}numActive(){return Object.keys(this.active).length}}let Ce=Math.floor(u.hardwareConcurrency/2),me,ie;function Se(){return me||(me=new Ee),me}Ee.workerCount=a.C(globalThis)?Math.max(Math.min(Ce,3),1):1;class Le{constructor(w,B){this.workerPool=w,this.actors=[],this.currentActor=0,this.id=B;let Q=this.workerPool.acquire(B);for(let ee=0;ee{B.remove()}),this.actors=[],w&&this.workerPool.release(this.id)}registerMessageHandler(w,B){for(let Q of this.actors)Q.registerMessageHandler(w,B)}}function Ae(){return ie||(ie=new Le(Se(),a.G),ie.registerMessageHandler("GR",(ue,w,B)=>a.m(w,B))),ie}function Fe(ue,w){let B=a.H();return a.J(B,B,[1,1,0]),a.K(B,B,[.5*ue.width,.5*ue.height,1]),a.L(B,B,ue.calculatePosMatrix(w.toUnwrapped()))}function Pe(ue,w,B,Q,ee,le){let qe=function(Kt,xr,Ir){if(Kt)for(let ve of Kt){let be=xr[ve];if(be&&be.source===Ir&&be.type==="fill-extrusion")return!0}else for(let ve in xr){let be=xr[ve];if(be.source===Ir&&be.type==="fill-extrusion")return!0}return!1}(ee&&ee.layers,w,ue.id),Xe=le.maxPitchScaleFactor(),ot=ue.tilesIn(Q,Xe,qe);ot.sort(ge);let Tt=[];for(let Kt of ot)Tt.push({wrappedTileID:Kt.tileID.wrapped().key,queryResults:Kt.tile.queryRenderedFeatures(w,B,ue._state,Kt.queryGeometry,Kt.cameraQueryGeometry,Kt.scale,ee,le,Xe,Fe(ue.transform,Kt.tileID))});let Yt=function(Kt){let xr={},Ir={};for(let ve of Kt){let be=ve.queryResults,De=ve.wrappedTileID,Be=Ir[De]=Ir[De]||{};for(let et in be){let We=be[et],it=Be[et]=Be[et]||{},Ft=xr[et]=xr[et]||[];for(let Ht of We)it[Ht.featureIndex]||(it[Ht.featureIndex]=!0,Ft.push(Ht))}}return xr}(Tt);for(let Kt in Yt)Yt[Kt].forEach(xr=>{let Ir=xr.feature,ve=ue.getFeatureState(Ir.layer["source-layer"],Ir.id);Ir.source=Ir.layer.source,Ir.layer["source-layer"]&&(Ir.sourceLayer=Ir.layer["source-layer"]),Ir.state=ve});return Yt}function ge(ue,w){let B=ue.tileID,Q=w.tileID;return B.overscaledZ-Q.overscaledZ||B.canonical.y-Q.canonical.y||B.wrap-Q.wrap||B.canonical.x-Q.canonical.x}function Re(ue,w,B){return a._(this,void 0,void 0,function*(){let Q=ue;if(ue.url?Q=(yield a.h(w.transformRequest(ue.url,"Source"),B)).data:yield u.frameAsync(B),!Q)return null;let ee=a.M(a.e(Q,ue),["tiles","minzoom","maxzoom","attribution","bounds","scheme","tileSize","encoding"]);return"vector_layers"in Q&&Q.vector_layers&&(ee.vectorLayerIds=Q.vector_layers.map(le=>le.id)),ee})}class ce{constructor(w,B){w&&(B?this.setSouthWest(w).setNorthEast(B):Array.isArray(w)&&(w.length===4?this.setSouthWest([w[0],w[1]]).setNorthEast([w[2],w[3]]):this.setSouthWest(w[0]).setNorthEast(w[1])))}setNorthEast(w){return this._ne=w instanceof a.N?new a.N(w.lng,w.lat):a.N.convert(w),this}setSouthWest(w){return this._sw=w instanceof a.N?new a.N(w.lng,w.lat):a.N.convert(w),this}extend(w){let B=this._sw,Q=this._ne,ee,le;if(w instanceof a.N)ee=w,le=w;else{if(!(w instanceof ce))return Array.isArray(w)?w.length===4||w.every(Array.isArray)?this.extend(ce.convert(w)):this.extend(a.N.convert(w)):w&&("lng"in w||"lon"in w)&&"lat"in w?this.extend(a.N.convert(w)):this;if(ee=w._sw,le=w._ne,!ee||!le)return this}return B||Q?(B.lng=Math.min(ee.lng,B.lng),B.lat=Math.min(ee.lat,B.lat),Q.lng=Math.max(le.lng,Q.lng),Q.lat=Math.max(le.lat,Q.lat)):(this._sw=new a.N(ee.lng,ee.lat),this._ne=new a.N(le.lng,le.lat)),this}getCenter(){return new a.N((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)}getSouthWest(){return this._sw}getNorthEast(){return this._ne}getNorthWest(){return new a.N(this.getWest(),this.getNorth())}getSouthEast(){return new a.N(this.getEast(),this.getSouth())}getWest(){return this._sw.lng}getSouth(){return this._sw.lat}getEast(){return this._ne.lng}getNorth(){return this._ne.lat}toArray(){return[this._sw.toArray(),this._ne.toArray()]}toString(){return`LngLatBounds(${this._sw.toString()}, ${this._ne.toString()})`}isEmpty(){return!(this._sw&&this._ne)}contains(w){let{lng:B,lat:Q}=a.N.convert(w),ee=this._sw.lng<=B&&B<=this._ne.lng;return this._sw.lng>this._ne.lng&&(ee=this._sw.lng>=B&&B>=this._ne.lng),this._sw.lat<=Q&&Q<=this._ne.lat&&ee}static convert(w){return w instanceof ce?w:w&&new ce(w)}static fromLngLat(w,B=0){let Q=360*B/40075017,ee=Q/Math.cos(Math.PI/180*w.lat);return new ce(new a.N(w.lng-ee,w.lat-Q),new a.N(w.lng+ee,w.lat+Q))}adjustAntiMeridian(){let w=new a.N(this._sw.lng,this._sw.lat),B=new a.N(this._ne.lng,this._ne.lat);return new ce(w,w.lng>B.lng?new a.N(B.lng+360,B.lat):B)}}class Ze{constructor(w,B,Q){this.bounds=ce.convert(this.validateBounds(w)),this.minzoom=B||0,this.maxzoom=Q||24}validateBounds(w){return Array.isArray(w)&&w.length===4?[Math.max(-180,w[0]),Math.max(-90,w[1]),Math.min(180,w[2]),Math.min(90,w[3])]:[-180,-90,180,90]}contains(w){let B=Math.pow(2,w.z),Q=Math.floor(a.O(this.bounds.getWest())*B),ee=Math.floor(a.Q(this.bounds.getNorth())*B),le=Math.ceil(a.O(this.bounds.getEast())*B),qe=Math.ceil(a.Q(this.bounds.getSouth())*B);return w.x>=Q&&w.x=ee&&w.y{this._options.tiles=w}),this}setUrl(w){return this.setSourceProperty(()=>{this.url=w,this._options.url=w}),this}onRemove(){this._tileJSONRequest&&(this._tileJSONRequest.abort(),this._tileJSONRequest=null)}serialize(){return a.e({},this._options)}loadTile(w){return a._(this,void 0,void 0,function*(){let B=w.tileID.canonical.url(this.tiles,this.map.getPixelRatio(),this.scheme),Q={request:this.map._requestManager.transformRequest(B,"Tile"),uid:w.uid,tileID:w.tileID,zoom:w.tileID.overscaledZ,tileSize:this.tileSize*w.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:this.map.getPixelRatio(),showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};Q.request.collectResourceTiming=this._collectResourceTiming;let ee="RT";if(w.actor&&w.state!=="expired"){if(w.state==="loading")return new Promise((le,qe)=>{w.reloadPromise={resolve:le,reject:qe}})}else w.actor=this.dispatcher.getActor(),ee="LT";w.abortController=new AbortController;try{let le=yield w.actor.sendAsync({type:ee,data:Q},w.abortController);if(delete w.abortController,w.aborted)return;this._afterTileLoadWorkerResponse(w,le)}catch(le){if(delete w.abortController,w.aborted)return;if(le&&le.status!==404)throw le;this._afterTileLoadWorkerResponse(w,null)}})}_afterTileLoadWorkerResponse(w,B){if(B&&B.resourceTiming&&(w.resourceTiming=B.resourceTiming),B&&this.map._refreshExpiredTiles&&w.setExpiryData(B),w.loadVectorData(B,this.map.painter),w.reloadPromise){let Q=w.reloadPromise;w.reloadPromise=null,this.loadTile(w).then(Q.resolve).catch(Q.reject)}}abortTile(w){return a._(this,void 0,void 0,function*(){w.abortController&&(w.abortController.abort(),delete w.abortController),w.actor&&(yield w.actor.sendAsync({type:"AT",data:{uid:w.uid,type:this.type,source:this.id}}))})}unloadTile(w){return a._(this,void 0,void 0,function*(){w.unloadVectorData(),w.actor&&(yield w.actor.sendAsync({type:"RMT",data:{uid:w.uid,type:this.type,source:this.id}}))})}hasTransition(){return!1}}class pt extends a.E{constructor(w,B,Q,ee){super(),this.id=w,this.dispatcher=Q,this.setEventedParent(ee),this.type="raster",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme="xyz",this.tileSize=512,this._loaded=!1,this._options=a.e({type:"raster"},B),a.e(this,a.M(B,["url","scheme","tileSize"]))}load(){return a._(this,void 0,void 0,function*(){this._loaded=!1,this.fire(new a.k("dataloading",{dataType:"source"})),this._tileJSONRequest=new AbortController;try{let w=yield Re(this._options,this.map._requestManager,this._tileJSONRequest);this._tileJSONRequest=null,this._loaded=!0,w&&(a.e(this,w),w.bounds&&(this.tileBounds=new Ze(w.bounds,this.minzoom,this.maxzoom)),this.fire(new a.k("data",{dataType:"source",sourceDataType:"metadata"})),this.fire(new a.k("data",{dataType:"source",sourceDataType:"content"})))}catch(w){this._tileJSONRequest=null,this.fire(new a.j(w))}})}loaded(){return this._loaded}onAdd(w){this.map=w,this.load()}onRemove(){this._tileJSONRequest&&(this._tileJSONRequest.abort(),this._tileJSONRequest=null)}setSourceProperty(w){this._tileJSONRequest&&(this._tileJSONRequest.abort(),this._tileJSONRequest=null),w(),this.load()}setTiles(w){return this.setSourceProperty(()=>{this._options.tiles=w}),this}setUrl(w){return this.setSourceProperty(()=>{this.url=w,this._options.url=w}),this}serialize(){return a.e({},this._options)}hasTile(w){return!this.tileBounds||this.tileBounds.contains(w.canonical)}loadTile(w){return a._(this,void 0,void 0,function*(){let B=w.tileID.canonical.url(this.tiles,this.map.getPixelRatio(),this.scheme);w.abortController=new AbortController;try{let Q=yield p.getImage(this.map._requestManager.transformRequest(B,"Tile"),w.abortController,this.map._refreshExpiredTiles);if(delete w.abortController,w.aborted)return void(w.state="unloaded");if(Q&&Q.data){this.map._refreshExpiredTiles&&Q.cacheControl&&Q.expires&&w.setExpiryData({cacheControl:Q.cacheControl,expires:Q.expires});let ee=this.map.painter.context,le=ee.gl,qe=Q.data;w.texture=this.map.painter.getTileTexture(qe.width),w.texture?w.texture.update(qe,{useMipmap:!0}):(w.texture=new g(ee,qe,le.RGBA,{useMipmap:!0}),w.texture.bind(le.LINEAR,le.CLAMP_TO_EDGE,le.LINEAR_MIPMAP_NEAREST)),w.state="loaded"}}catch(Q){if(delete w.abortController,w.aborted)w.state="unloaded";else if(Q)throw w.state="errored",Q}})}abortTile(w){return a._(this,void 0,void 0,function*(){w.abortController&&(w.abortController.abort(),delete w.abortController)})}unloadTile(w){return a._(this,void 0,void 0,function*(){w.texture&&this.map.painter.saveTileTexture(w.texture)})}hasTransition(){return!1}}class Zt extends pt{constructor(w,B,Q,ee){super(w,B,Q,ee),this.type="raster-dem",this.maxzoom=22,this._options=a.e({type:"raster-dem"},B),this.encoding=B.encoding||"mapbox",this.redFactor=B.redFactor,this.greenFactor=B.greenFactor,this.blueFactor=B.blueFactor,this.baseShift=B.baseShift}loadTile(w){return a._(this,void 0,void 0,function*(){let B=w.tileID.canonical.url(this.tiles,this.map.getPixelRatio(),this.scheme),Q=this.map._requestManager.transformRequest(B,"Tile");w.neighboringTiles=this._getNeighboringTiles(w.tileID),w.abortController=new AbortController;try{let ee=yield p.getImage(Q,w.abortController,this.map._refreshExpiredTiles);if(delete w.abortController,w.aborted)return void(w.state="unloaded");if(ee&&ee.data){let le=ee.data;this.map._refreshExpiredTiles&&ee.cacheControl&&ee.expires&&w.setExpiryData({cacheControl:ee.cacheControl,expires:ee.expires});let qe=a.b(le)&&a.U()?le:yield this.readImageNow(le),Xe={type:this.type,uid:w.uid,source:this.id,rawImageData:qe,encoding:this.encoding,redFactor:this.redFactor,greenFactor:this.greenFactor,blueFactor:this.blueFactor,baseShift:this.baseShift};if(!w.actor||w.state==="expired"){w.actor=this.dispatcher.getActor();let ot=yield w.actor.sendAsync({type:"LDT",data:Xe});w.dem=ot,w.needsHillshadePrepare=!0,w.needsTerrainPrepare=!0,w.state="loaded"}}}catch(ee){if(delete w.abortController,w.aborted)w.state="unloaded";else if(ee)throw w.state="errored",ee}})}readImageNow(w){return a._(this,void 0,void 0,function*(){if(typeof VideoFrame!="undefined"&&a.V()){let B=w.width+2,Q=w.height+2;try{return new a.R({width:B,height:Q},yield a.W(w,-1,-1,B,Q))}catch(ee){}}return u.getImageData(w,1)})}_getNeighboringTiles(w){let B=w.canonical,Q=Math.pow(2,B.z),ee=(B.x-1+Q)%Q,le=B.x===0?w.wrap-1:w.wrap,qe=(B.x+1+Q)%Q,Xe=B.x+1===Q?w.wrap+1:w.wrap,ot={};return ot[new a.S(w.overscaledZ,le,B.z,ee,B.y).key]={backfilled:!1},ot[new a.S(w.overscaledZ,Xe,B.z,qe,B.y).key]={backfilled:!1},B.y>0&&(ot[new a.S(w.overscaledZ,le,B.z,ee,B.y-1).key]={backfilled:!1},ot[new a.S(w.overscaledZ,w.wrap,B.z,B.x,B.y-1).key]={backfilled:!1},ot[new a.S(w.overscaledZ,Xe,B.z,qe,B.y-1).key]={backfilled:!1}),B.y+10&&a.e(le,{resourceTiming:ee}),this.fire(new a.k("data",Object.assign(Object.assign({},le),{sourceDataType:"metadata"}))),this.fire(new a.k("data",Object.assign(Object.assign({},le),{sourceDataType:"content"})))}catch(Q){if(this._pendingLoads--,this._removed)return void this.fire(new a.k("dataabort",{dataType:"source"}));this.fire(new a.j(Q))}})}loaded(){return this._pendingLoads===0}loadTile(w){return a._(this,void 0,void 0,function*(){let B=w.actor?"RT":"LT";w.actor=this.actor;let Q={type:this.type,uid:w.uid,tileID:w.tileID,zoom:w.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:this.map.getPixelRatio(),showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};w.abortController=new AbortController;let ee=yield this.actor.sendAsync({type:B,data:Q},w.abortController);delete w.abortController,w.unloadVectorData(),w.aborted||w.loadVectorData(ee,this.map.painter,B==="RT")})}abortTile(w){return a._(this,void 0,void 0,function*(){w.abortController&&(w.abortController.abort(),delete w.abortController),w.aborted=!0})}unloadTile(w){return a._(this,void 0,void 0,function*(){w.unloadVectorData(),yield this.actor.sendAsync({type:"RMT",data:{uid:w.uid,type:this.type,source:this.id}})})}onRemove(){this._removed=!0,this.actor.sendAsync({type:"RS",data:{type:this.type,source:this.id}})}serialize(){return a.e({},this._options,{type:this.type,data:this._data})}hasTransition(){return!1}}var lt=a.Y([{name:"a_pos",type:"Int16",components:2},{name:"a_texture_pos",type:"Int16",components:2}]);class Gt extends a.E{constructor(w,B,Q,ee){super(),this.id=w,this.dispatcher=Q,this.coordinates=B.coordinates,this.type="image",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(ee),this.options=B}load(w){return a._(this,void 0,void 0,function*(){this._loaded=!1,this.fire(new a.k("dataloading",{dataType:"source"})),this.url=this.options.url,this._request=new AbortController;try{let B=yield p.getImage(this.map._requestManager.transformRequest(this.url,"Image"),this._request);this._request=null,this._loaded=!0,B&&B.data&&(this.image=B.data,w&&(this.coordinates=w),this._finishLoading())}catch(B){this._request=null,this._loaded=!0,this.fire(new a.j(B))}})}loaded(){return this._loaded}updateImage(w){return w.url?(this._request&&(this._request.abort(),this._request=null),this.options.url=w.url,this.load(w.coordinates).finally(()=>{this.texture=null}),this):this}_finishLoading(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new a.k("data",{dataType:"source",sourceDataType:"metadata"})))}onAdd(w){this.map=w,this.load()}onRemove(){this._request&&(this._request.abort(),this._request=null)}setCoordinates(w){this.coordinates=w;let B=w.map(a.Z.fromLngLat);this.tileID=function(ee){let le=1/0,qe=1/0,Xe=-1/0,ot=-1/0;for(let xr of ee)le=Math.min(le,xr.x),qe=Math.min(qe,xr.y),Xe=Math.max(Xe,xr.x),ot=Math.max(ot,xr.y);let Tt=Math.max(Xe-le,ot-qe),Yt=Math.max(0,Math.floor(-Math.log(Tt)/Math.LN2)),Kt=Math.pow(2,Yt);return new a.a1(Yt,Math.floor((le+Xe)/2*Kt),Math.floor((qe+ot)/2*Kt))}(B),this.minzoom=this.maxzoom=this.tileID.z;let Q=B.map(ee=>this.tileID.getTilePoint(ee)._round());return this._boundsArray=new a.$,this._boundsArray.emplaceBack(Q[0].x,Q[0].y,0,0),this._boundsArray.emplaceBack(Q[1].x,Q[1].y,a.X,0),this._boundsArray.emplaceBack(Q[3].x,Q[3].y,0,a.X),this._boundsArray.emplaceBack(Q[2].x,Q[2].y,a.X,a.X),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new a.k("data",{dataType:"source",sourceDataType:"content"})),this}prepare(){if(Object.keys(this.tiles).length===0||!this.image)return;let w=this.map.painter.context,B=w.gl;this.boundsBuffer||(this.boundsBuffer=w.createVertexBuffer(this._boundsArray,lt.members)),this.boundsSegments||(this.boundsSegments=a.a0.simpleSegment(0,0,4,2)),this.texture||(this.texture=new g(w,this.image,B.RGBA),this.texture.bind(B.LINEAR,B.CLAMP_TO_EDGE));let Q=!1;for(let ee in this.tiles){let le=this.tiles[ee];le.state!=="loaded"&&(le.state="loaded",le.texture=this.texture,Q=!0)}Q&&this.fire(new a.k("data",{dataType:"source",sourceDataType:"idle",sourceId:this.id}))}loadTile(w){return a._(this,void 0,void 0,function*(){this.tileID&&this.tileID.equals(w.tileID.canonical)?(this.tiles[String(w.tileID.wrap)]=w,w.buckets={}):w.state="errored"})}serialize(){return{type:"image",url:this.options.url,coordinates:this.coordinates}}hasTransition(){return!1}}class Nt extends Gt{constructor(w,B,Q,ee){super(w,B,Q,ee),this.roundZoom=!0,this.type="video",this.options=B}load(){return a._(this,void 0,void 0,function*(){this._loaded=!1;let w=this.options;this.urls=[];for(let B of w.urls)this.urls.push(this.map._requestManager.transformRequest(B,"Source").url);try{let B=yield a.a3(this.urls);if(this._loaded=!0,!B)return;this.video=B,this.video.loop=!0,this.video.addEventListener("playing",()=>{this.map.triggerRepaint()}),this.map&&this.video.play(),this._finishLoading()}catch(B){this.fire(new a.j(B))}})}pause(){this.video&&this.video.pause()}play(){this.video&&this.video.play()}seek(w){if(this.video){let B=this.video.seekable;wB.end(0)?this.fire(new a.j(new a.a2(`sources.${this.id}`,null,`Playback for this video can be set only between the ${B.start(0)} and ${B.end(0)}-second mark.`))):this.video.currentTime=w}}getVideo(){return this.video}onAdd(w){this.map||(this.map=w,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))}prepare(){if(Object.keys(this.tiles).length===0||this.video.readyState<2)return;let w=this.map.painter.context,B=w.gl;this.boundsBuffer||(this.boundsBuffer=w.createVertexBuffer(this._boundsArray,lt.members)),this.boundsSegments||(this.boundsSegments=a.a0.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(B.LINEAR,B.CLAMP_TO_EDGE),B.texSubImage2D(B.TEXTURE_2D,0,0,0,B.RGBA,B.UNSIGNED_BYTE,this.video)):(this.texture=new g(w,this.video,B.RGBA),this.texture.bind(B.LINEAR,B.CLAMP_TO_EDGE));let Q=!1;for(let ee in this.tiles){let le=this.tiles[ee];le.state!=="loaded"&&(le.state="loaded",le.texture=this.texture,Q=!0)}Q&&this.fire(new a.k("data",{dataType:"source",sourceDataType:"idle",sourceId:this.id}))}serialize(){return{type:"video",urls:this.urls,coordinates:this.coordinates}}hasTransition(){return this.video&&!this.video.paused}}class Jt extends Gt{constructor(w,B,Q,ee){super(w,B,Q,ee),B.coordinates?Array.isArray(B.coordinates)&&B.coordinates.length===4&&!B.coordinates.some(le=>!Array.isArray(le)||le.length!==2||le.some(qe=>typeof qe!="number"))||this.fire(new a.j(new a.a2(`sources.${w}`,null,'"coordinates" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new a.j(new a.a2(`sources.${w}`,null,'missing required property "coordinates"'))),B.animate&&typeof B.animate!="boolean"&&this.fire(new a.j(new a.a2(`sources.${w}`,null,'optional "animate" property must be a boolean value'))),B.canvas?typeof B.canvas=="string"||B.canvas instanceof HTMLCanvasElement||this.fire(new a.j(new a.a2(`sources.${w}`,null,'"canvas" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new a.j(new a.a2(`sources.${w}`,null,'missing required property "canvas"'))),this.options=B,this.animate=B.animate===void 0||B.animate}load(){return a._(this,void 0,void 0,function*(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof HTMLCanvasElement?this.options.canvas:document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new a.j(new Error("Canvas dimensions cannot be less than or equal to zero."))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())})}getCanvas(){return this.canvas}onAdd(w){this.map=w,this.load(),this.canvas&&this.animate&&this.play()}onRemove(){this.pause()}prepare(){let w=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,w=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,w=!0),this._hasInvalidDimensions()||Object.keys(this.tiles).length===0)return;let B=this.map.painter.context,Q=B.gl;this.boundsBuffer||(this.boundsBuffer=B.createVertexBuffer(this._boundsArray,lt.members)),this.boundsSegments||(this.boundsSegments=a.a0.simpleSegment(0,0,4,2)),this.texture?(w||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new g(B,this.canvas,Q.RGBA,{premultiply:!0});let ee=!1;for(let le in this.tiles){let qe=this.tiles[le];qe.state!=="loaded"&&(qe.state="loaded",qe.texture=this.texture,ee=!0)}ee&&this.fire(new a.k("data",{dataType:"source",sourceDataType:"idle",sourceId:this.id}))}serialize(){return{type:"canvas",coordinates:this.coordinates}}hasTransition(){return this._playing}_hasInvalidDimensions(){for(let w of[this.canvas.width,this.canvas.height])if(isNaN(w)||w<=0)return!0;return!1}}let sr={},wr=ue=>{switch(ue){case"geojson":return st;case"image":return Gt;case"raster":return pt;case"raster-dem":return Zt;case"vector":return ut;case"video":return Nt;case"canvas":return Jt}return sr[ue]},cr="RTLPluginLoaded";class $e extends a.E{constructor(){super(...arguments),this.status="unavailable",this.url=null,this.dispatcher=Ae()}_syncState(w){return this.status=w,this.dispatcher.broadcast("SRPS",{pluginStatus:w,pluginURL:this.url}).catch(B=>{throw this.status="error",B})}getRTLTextPluginStatus(){return this.status}clearRTLTextPlugin(){this.status="unavailable",this.url=null}setRTLTextPlugin(w){return a._(this,arguments,void 0,function*(B,Q=!1){if(this.url)throw new Error("setRTLTextPlugin cannot be called multiple times.");if(this.url=u.resolveURL(B),!this.url)throw new Error(`requested url ${B} is invalid`);if(this.status==="unavailable"){if(!Q)return this._requestImport();this.status="deferred",this._syncState(this.status)}else if(this.status==="requested")return this._requestImport()})}_requestImport(){return a._(this,void 0,void 0,function*(){yield this._syncState("loading"),this.status="loaded",this.fire(new a.k(cr))})}lazyLoad(){this.status==="unavailable"?this.status="requested":this.status==="deferred"&&this._requestImport()}}let St=null;function Qt(){return St||(St=new $e),St}class Vt{constructor(w,B){this.timeAdded=0,this.fadeEndTime=0,this.tileID=w,this.uid=a.a4(),this.uses=0,this.tileSize=B,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.rtt=[],this.rttCoords={},this.expiredRequestCount=0,this.state="loading"}registerFadeDuration(w){let B=w+this.timeAdded;Ble.getLayer(Tt)).filter(Boolean);if(ot.length!==0){Xe.layers=ot,Xe.stateDependentLayerIds&&(Xe.stateDependentLayers=Xe.stateDependentLayerIds.map(Tt=>ot.filter(Yt=>Yt.id===Tt)[0]));for(let Tt of ot)qe[Tt.id]=Xe}}return qe}(w.buckets,B.style),this.hasSymbolBuckets=!1;for(let ee in this.buckets){let le=this.buckets[ee];if(le instanceof a.a6){if(this.hasSymbolBuckets=!0,!Q)break;le.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(let ee in this.buckets){let le=this.buckets[ee];if(le instanceof a.a6&&le.hasRTLText){this.hasRTLText=!0,Qt().lazyLoad();break}}this.queryPadding=0;for(let ee in this.buckets){let le=this.buckets[ee];this.queryPadding=Math.max(this.queryPadding,B.style.getLayer(ee).queryRadius(le))}w.imageAtlas&&(this.imageAtlas=w.imageAtlas),w.glyphAtlasImage&&(this.glyphAtlasImage=w.glyphAtlasImage)}else this.collisionBoxArray=new a.a5}unloadVectorData(){for(let w in this.buckets)this.buckets[w].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state="unloaded"}getBucket(w){return this.buckets[w.id]}upload(w){for(let Q in this.buckets){let ee=this.buckets[Q];ee.uploadPending()&&ee.upload(w)}let B=w.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new g(w,this.imageAtlas.image,B.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new g(w,this.glyphAtlasImage,B.ALPHA),this.glyphAtlasImage=null)}prepare(w){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(w,this.imageAtlasTexture)}queryRenderedFeatures(w,B,Q,ee,le,qe,Xe,ot,Tt,Yt){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:ee,cameraQueryGeometry:le,scale:qe,tileSize:this.tileSize,pixelPosMatrix:Yt,transform:ot,params:Xe,queryPadding:this.queryPadding*Tt},w,B,Q):{}}querySourceFeatures(w,B){let Q=this.latestFeatureIndex;if(!Q||!Q.rawTileData)return;let ee=Q.loadVTLayers(),le=B&&B.sourceLayer?B.sourceLayer:"",qe=ee._geojsonTileLayer||ee[le];if(!qe)return;let Xe=a.a7(B&&B.filter),{z:ot,x:Tt,y:Yt}=this.tileID.canonical,Kt={z:ot,x:Tt,y:Yt};for(let xr=0;xrQ)ee=!1;else if(B)if(this.expirationTime{this.remove(w,le)},Q)),this.data[ee].push(le),this.order.push(ee),this.order.length>this.max){let qe=this._getAndRemoveByKey(this.order[0]);qe&&this.onRemove(qe)}return this}has(w){return w.wrapped().key in this.data}getAndRemove(w){return this.has(w)?this._getAndRemoveByKey(w.wrapped().key):null}_getAndRemoveByKey(w){let B=this.data[w].shift();return B.timeout&&clearTimeout(B.timeout),this.data[w].length===0&&delete this.data[w],this.order.splice(this.order.indexOf(w),1),B.value}getByKey(w){let B=this.data[w];return B?B[0].value:null}get(w){return this.has(w)?this.data[w.wrapped().key][0].value:null}remove(w,B){if(!this.has(w))return this;let Q=w.wrapped().key,ee=B===void 0?0:this.data[Q].indexOf(B),le=this.data[Q][ee];return this.data[Q].splice(ee,1),le.timeout&&clearTimeout(le.timeout),this.data[Q].length===0&&delete this.data[Q],this.onRemove(le.value),this.order.splice(this.order.indexOf(Q),1),this}setMaxSize(w){for(this.max=w;this.order.length>this.max;){let B=this._getAndRemoveByKey(this.order[0]);B&&this.onRemove(B)}return this}filter(w){let B=[];for(let Q in this.data)for(let ee of this.data[Q])w(ee.value)||B.push(ee);for(let Q of B)this.remove(Q.value.tileID,Q)}}class It{constructor(){this.state={},this.stateChanges={},this.deletedStates={}}updateState(w,B,Q){let ee=String(B);if(this.stateChanges[w]=this.stateChanges[w]||{},this.stateChanges[w][ee]=this.stateChanges[w][ee]||{},a.e(this.stateChanges[w][ee],Q),this.deletedStates[w]===null){this.deletedStates[w]={};for(let le in this.state[w])le!==ee&&(this.deletedStates[w][le]=null)}else if(this.deletedStates[w]&&this.deletedStates[w][ee]===null){this.deletedStates[w][ee]={};for(let le in this.state[w][ee])Q[le]||(this.deletedStates[w][ee][le]=null)}else for(let le in Q)this.deletedStates[w]&&this.deletedStates[w][ee]&&this.deletedStates[w][ee][le]===null&&delete this.deletedStates[w][ee][le]}removeFeatureState(w,B,Q){if(this.deletedStates[w]===null)return;let ee=String(B);if(this.deletedStates[w]=this.deletedStates[w]||{},Q&&B!==void 0)this.deletedStates[w][ee]!==null&&(this.deletedStates[w][ee]=this.deletedStates[w][ee]||{},this.deletedStates[w][ee][Q]=null);else if(B!==void 0)if(this.stateChanges[w]&&this.stateChanges[w][ee])for(Q in this.deletedStates[w][ee]={},this.stateChanges[w][ee])this.deletedStates[w][ee][Q]=null;else this.deletedStates[w][ee]=null;else this.deletedStates[w]=null}getState(w,B){let Q=String(B),ee=a.e({},(this.state[w]||{})[Q],(this.stateChanges[w]||{})[Q]);if(this.deletedStates[w]===null)return{};if(this.deletedStates[w]){let le=this.deletedStates[w][B];if(le===null)return{};for(let qe in le)delete ee[qe]}return ee}initializeTileState(w,B){w.setFeatureState(this.state,B)}coalesceChanges(w,B){let Q={};for(let ee in this.stateChanges){this.state[ee]=this.state[ee]||{};let le={};for(let qe in this.stateChanges[ee])this.state[ee][qe]||(this.state[ee][qe]={}),a.e(this.state[ee][qe],this.stateChanges[ee][qe]),le[qe]=this.state[ee][qe];Q[ee]=le}for(let ee in this.deletedStates){this.state[ee]=this.state[ee]||{};let le={};if(this.deletedStates[ee]===null)for(let qe in this.state[ee])le[qe]={},this.state[ee][qe]={};else for(let qe in this.deletedStates[ee]){if(this.deletedStates[ee][qe]===null)this.state[ee][qe]={};else for(let Xe of Object.keys(this.deletedStates[ee][qe]))delete this.state[ee][qe][Xe];le[qe]=this.state[ee][qe]}Q[ee]=Q[ee]||{},a.e(Q[ee],le)}if(this.stateChanges={},this.deletedStates={},Object.keys(Q).length!==0)for(let ee in w)w[ee].setFeatureState(Q,B)}}class mt extends a.E{constructor(w,B,Q){super(),this.id=w,this.dispatcher=Q,this.on("data",ee=>this._dataHandler(ee)),this.on("dataloading",()=>{this._sourceErrored=!1}),this.on("error",()=>{this._sourceErrored=this._source.loaded()}),this._source=((ee,le,qe,Xe)=>{let ot=new(wr(le.type))(ee,le,qe,Xe);if(ot.id!==ee)throw new Error(`Expected Source id to be ${ee} instead of ${ot.id}`);return ot})(w,B,Q,this),this._tiles={},this._cache=new _t(0,ee=>this._unloadTile(ee)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._maxTileCacheZoomLevels=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new It,this._didEmitContent=!1,this._updated=!1}onAdd(w){this.map=w,this._maxTileCacheSize=w?w._maxTileCacheSize:null,this._maxTileCacheZoomLevels=w?w._maxTileCacheZoomLevels:null,this._source&&this._source.onAdd&&this._source.onAdd(w)}onRemove(w){this.clearTiles(),this._source&&this._source.onRemove&&this._source.onRemove(w)}loaded(){if(this._sourceErrored)return!0;if(!this._sourceLoaded||!this._source.loaded())return!1;if(!(this.used===void 0&&this.usedForTerrain===void 0||this.used||this.usedForTerrain))return!0;if(!this._updated)return!1;for(let w in this._tiles){let B=this._tiles[w];if(B.state!=="loaded"&&B.state!=="errored")return!1}return!0}getSource(){return this._source}pause(){this._paused=!0}resume(){if(!this._paused)return;let w=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,w&&this.reload(),this.transform&&this.update(this.transform,this.terrain)}_loadTile(w,B,Q){return a._(this,void 0,void 0,function*(){try{yield this._source.loadTile(w),this._tileLoaded(w,B,Q)}catch(ee){w.state="errored",ee.status!==404?this._source.fire(new a.j(ee,{tile:w})):this.update(this.transform,this.terrain)}})}_unloadTile(w){this._source.unloadTile&&this._source.unloadTile(w)}_abortTile(w){this._source.abortTile&&this._source.abortTile(w),this._source.fire(new a.k("dataabort",{tile:w,coord:w.tileID,dataType:"source"}))}serialize(){return this._source.serialize()}prepare(w){this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null);for(let B in this._tiles){let Q=this._tiles[B];Q.upload(w),Q.prepare(this.map.style.imageManager)}}getIds(){return Object.values(this._tiles).map(w=>w.tileID).sort(er).map(w=>w.key)}getRenderableIds(w){let B=[];for(let Q in this._tiles)this._isIdRenderable(Q,w)&&B.push(this._tiles[Q]);return w?B.sort((Q,ee)=>{let le=Q.tileID,qe=ee.tileID,Xe=new a.P(le.canonical.x,le.canonical.y)._rotate(this.transform.angle),ot=new a.P(qe.canonical.x,qe.canonical.y)._rotate(this.transform.angle);return le.overscaledZ-qe.overscaledZ||ot.y-Xe.y||ot.x-Xe.x}).map(Q=>Q.tileID.key):B.map(Q=>Q.tileID).sort(er).map(Q=>Q.key)}hasRenderableParent(w){let B=this.findLoadedParent(w,0);return!!B&&this._isIdRenderable(B.tileID.key)}_isIdRenderable(w,B){return this._tiles[w]&&this._tiles[w].hasData()&&!this._coveredTiles[w]&&(B||!this._tiles[w].holdingForFade())}reload(){if(this._paused)this._shouldReloadOnResume=!0;else{this._cache.reset();for(let w in this._tiles)this._tiles[w].state!=="errored"&&this._reloadTile(w,"reloading")}}_reloadTile(w,B){return a._(this,void 0,void 0,function*(){let Q=this._tiles[w];Q&&(Q.state!=="loading"&&(Q.state=B),yield this._loadTile(Q,w,B))})}_tileLoaded(w,B,Q){w.timeAdded=u.now(),Q==="expired"&&(w.refreshedUponExpiration=!0),this._setTileReloadTimer(B,w),this.getSource().type==="raster-dem"&&w.dem&&this._backfillDEM(w),this._state.initializeTileState(w,this.map?this.map.painter:null),w.aborted||this._source.fire(new a.k("data",{dataType:"source",tile:w,coord:w.tileID}))}_backfillDEM(w){let B=this.getRenderableIds();for(let ee=0;ee1||(Math.abs(qe)>1&&(Math.abs(qe+ot)===1?qe+=ot:Math.abs(qe-ot)===1&&(qe-=ot)),le.dem&&ee.dem&&(ee.dem.backfillBorder(le.dem,qe,Xe),ee.neighboringTiles&&ee.neighboringTiles[Tt]&&(ee.neighboringTiles[Tt].backfilled=!0)))}}getTile(w){return this.getTileByID(w.key)}getTileByID(w){return this._tiles[w]}_retainLoadedChildren(w,B,Q,ee){for(let le in this._tiles){let qe=this._tiles[le];if(ee[le]||!qe.hasData()||qe.tileID.overscaledZ<=B||qe.tileID.overscaledZ>Q)continue;let Xe=qe.tileID;for(;qe&&qe.tileID.overscaledZ>B+1;){let Tt=qe.tileID.scaledTo(qe.tileID.overscaledZ-1);qe=this._tiles[Tt.key],qe&&qe.hasData()&&(Xe=Tt)}let ot=Xe;for(;ot.overscaledZ>B;)if(ot=ot.scaledTo(ot.overscaledZ-1),w[ot.key]){ee[Xe.key]=Xe;break}}}findLoadedParent(w,B){if(w.key in this._loadedParentTiles){let Q=this._loadedParentTiles[w.key];return Q&&Q.tileID.overscaledZ>=B?Q:null}for(let Q=w.overscaledZ-1;Q>=B;Q--){let ee=w.scaledTo(Q),le=this._getLoadedTile(ee);if(le)return le}}findLoadedSibling(w){return this._getLoadedTile(w)}_getLoadedTile(w){let B=this._tiles[w.key];return B&&B.hasData()?B:this._cache.getByKey(w.wrapped().key)}updateCacheSize(w){let B=Math.ceil(w.width/this._source.tileSize)+1,Q=Math.ceil(w.height/this._source.tileSize)+1,ee=Math.floor(B*Q*(this._maxTileCacheZoomLevels===null?a.a.MAX_TILE_CACHE_ZOOM_LEVELS:this._maxTileCacheZoomLevels)),le=typeof this._maxTileCacheSize=="number"?Math.min(this._maxTileCacheSize,ee):ee;this._cache.setMaxSize(le)}handleWrapJump(w){let B=Math.round((w-(this._prevLng===void 0?w:this._prevLng))/360);if(this._prevLng=w,B){let Q={};for(let ee in this._tiles){let le=this._tiles[ee];le.tileID=le.tileID.unwrapTo(le.tileID.wrap+B),Q[le.tileID.key]=le}this._tiles=Q;for(let ee in this._timers)clearTimeout(this._timers[ee]),delete this._timers[ee];for(let ee in this._tiles)this._setTileReloadTimer(ee,this._tiles[ee])}}_updateCoveredAndRetainedTiles(w,B,Q,ee,le,qe){let Xe={},ot={},Tt=Object.keys(w),Yt=u.now();for(let Kt of Tt){let xr=w[Kt],Ir=this._tiles[Kt];if(!Ir||Ir.fadeEndTime!==0&&Ir.fadeEndTime<=Yt)continue;let ve=this.findLoadedParent(xr,B),be=this.findLoadedSibling(xr),De=ve||be||null;De&&(this._addTile(De.tileID),Xe[De.tileID.key]=De.tileID),ot[Kt]=xr}this._retainLoadedChildren(ot,ee,Q,w);for(let Kt in Xe)w[Kt]||(this._coveredTiles[Kt]=!0,w[Kt]=Xe[Kt]);if(qe){let Kt={},xr={};for(let Ir of le)this._tiles[Ir.key].hasData()?Kt[Ir.key]=Ir:xr[Ir.key]=Ir;for(let Ir in xr){let ve=xr[Ir].children(this._source.maxzoom);this._tiles[ve[0].key]&&this._tiles[ve[1].key]&&this._tiles[ve[2].key]&&this._tiles[ve[3].key]&&(Kt[ve[0].key]=w[ve[0].key]=ve[0],Kt[ve[1].key]=w[ve[1].key]=ve[1],Kt[ve[2].key]=w[ve[2].key]=ve[2],Kt[ve[3].key]=w[ve[3].key]=ve[3],delete xr[Ir])}for(let Ir in xr){let ve=xr[Ir],be=this.findLoadedParent(ve,this._source.minzoom),De=this.findLoadedSibling(ve),Be=be||De||null;if(Be){Kt[Be.tileID.key]=w[Be.tileID.key]=Be.tileID;for(let et in Kt)Kt[et].isChildOf(Be.tileID)&&delete Kt[et]}}for(let Ir in this._tiles)Kt[Ir]||(this._coveredTiles[Ir]=!0)}}update(w,B){if(!this._sourceLoaded||this._paused)return;let Q;this.transform=w,this.terrain=B,this.updateCacheSize(w),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used||this.usedForTerrain?this._source.tileID?Q=w.getVisibleUnwrappedCoordinates(this._source.tileID).map(Yt=>new a.S(Yt.canonical.z,Yt.wrap,Yt.canonical.z,Yt.canonical.x,Yt.canonical.y)):(Q=w.coveringTiles({tileSize:this.usedForTerrain?this.tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:!this.usedForTerrain&&this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled,terrain:B}),this._source.hasTile&&(Q=Q.filter(Yt=>this._source.hasTile(Yt)))):Q=[];let ee=w.coveringZoomLevel(this._source),le=Math.max(ee-mt.maxOverzooming,this._source.minzoom),qe=Math.max(ee+mt.maxUnderzooming,this._source.minzoom);if(this.usedForTerrain){let Yt={};for(let Kt of Q)if(Kt.canonical.z>this._source.minzoom){let xr=Kt.scaledTo(Kt.canonical.z-1);Yt[xr.key]=xr;let Ir=Kt.scaledTo(Math.max(this._source.minzoom,Math.min(Kt.canonical.z,5)));Yt[Ir.key]=Ir}Q=Q.concat(Object.values(Yt))}let Xe=Q.length===0&&!this._updated&&this._didEmitContent;this._updated=!0,Xe&&this.fire(new a.k("data",{sourceDataType:"idle",dataType:"source",sourceId:this.id}));let ot=this._updateRetainedTiles(Q,ee);lr(this._source.type)&&this._updateCoveredAndRetainedTiles(ot,le,qe,ee,Q,B);for(let Yt in ot)this._tiles[Yt].clearFadeHold();let Tt=a.ab(this._tiles,ot);for(let Yt of Tt){let Kt=this._tiles[Yt];Kt.hasSymbolBuckets&&!Kt.holdingForFade()?Kt.setHoldDuration(this.map._fadeDuration):Kt.hasSymbolBuckets&&!Kt.symbolFadeFinished()||this._removeTile(Yt)}this._updateLoadedParentTileCache(),this._updateLoadedSiblingTileCache()}releaseSymbolFadeTiles(){for(let w in this._tiles)this._tiles[w].holdingForFade()&&this._removeTile(w)}_updateRetainedTiles(w,B){var Q;let ee={},le={},qe=Math.max(B-mt.maxOverzooming,this._source.minzoom),Xe=Math.max(B+mt.maxUnderzooming,this._source.minzoom),ot={};for(let Tt of w){let Yt=this._addTile(Tt);ee[Tt.key]=Tt,Yt.hasData()||Bthis._source.maxzoom){let xr=Tt.children(this._source.maxzoom)[0],Ir=this.getTile(xr);if(Ir&&Ir.hasData()){ee[xr.key]=xr;continue}}else{let xr=Tt.children(this._source.maxzoom);if(ee[xr[0].key]&&ee[xr[1].key]&&ee[xr[2].key]&&ee[xr[3].key])continue}let Kt=Yt.wasRequested();for(let xr=Tt.overscaledZ-1;xr>=qe;--xr){let Ir=Tt.scaledTo(xr);if(le[Ir.key])break;if(le[Ir.key]=!0,Yt=this.getTile(Ir),!Yt&&Kt&&(Yt=this._addTile(Ir)),Yt){let ve=Yt.hasData();if((ve||!(!((Q=this.map)===null||Q===void 0)&&Q.cancelPendingTileRequestsWhileZooming)||Kt)&&(ee[Ir.key]=Ir),Kt=Yt.wasRequested(),ve)break}}}return ee}_updateLoadedParentTileCache(){this._loadedParentTiles={};for(let w in this._tiles){let B=[],Q,ee=this._tiles[w].tileID;for(;ee.overscaledZ>0;){if(ee.key in this._loadedParentTiles){Q=this._loadedParentTiles[ee.key];break}B.push(ee.key);let le=ee.scaledTo(ee.overscaledZ-1);if(Q=this._getLoadedTile(le),Q)break;ee=le}for(let le of B)this._loadedParentTiles[le]=Q}}_updateLoadedSiblingTileCache(){this._loadedSiblingTiles={};for(let w in this._tiles){let B=this._tiles[w].tileID,Q=this._getLoadedTile(B);this._loadedSiblingTiles[B.key]=Q}}_addTile(w){let B=this._tiles[w.key];if(B)return B;B=this._cache.getAndRemove(w),B&&(this._setTileReloadTimer(w.key,B),B.tileID=w,this._state.initializeTileState(B,this.map?this.map.painter:null),this._cacheTimers[w.key]&&(clearTimeout(this._cacheTimers[w.key]),delete this._cacheTimers[w.key],this._setTileReloadTimer(w.key,B)));let Q=B;return B||(B=new Vt(w,this._source.tileSize*w.overscaleFactor()),this._loadTile(B,w.key,B.state)),B.uses++,this._tiles[w.key]=B,Q||this._source.fire(new a.k("dataloading",{tile:B,coord:B.tileID,dataType:"source"})),B}_setTileReloadTimer(w,B){w in this._timers&&(clearTimeout(this._timers[w]),delete this._timers[w]);let Q=B.getExpiryTimeout();Q&&(this._timers[w]=setTimeout(()=>{this._reloadTile(w,"expired"),delete this._timers[w]},Q))}_removeTile(w){let B=this._tiles[w];B&&(B.uses--,delete this._tiles[w],this._timers[w]&&(clearTimeout(this._timers[w]),delete this._timers[w]),B.uses>0||(B.hasData()&&B.state!=="reloading"?this._cache.add(B.tileID,B,B.getExpiryTimeout()):(B.aborted=!0,this._abortTile(B),this._unloadTile(B))))}_dataHandler(w){let B=w.sourceDataType;w.dataType==="source"&&B==="metadata"&&(this._sourceLoaded=!0),this._sourceLoaded&&!this._paused&&w.dataType==="source"&&B==="content"&&(this.reload(),this.transform&&this.update(this.transform,this.terrain),this._didEmitContent=!0)}clearTiles(){this._shouldReloadOnResume=!1,this._paused=!1;for(let w in this._tiles)this._removeTile(w);this._cache.reset()}tilesIn(w,B,Q){let ee=[],le=this.transform;if(!le)return ee;let qe=Q?le.getCameraQueryGeometry(w):w,Xe=w.map(ve=>le.pointCoordinate(ve,this.terrain)),ot=qe.map(ve=>le.pointCoordinate(ve,this.terrain)),Tt=this.getIds(),Yt=1/0,Kt=1/0,xr=-1/0,Ir=-1/0;for(let ve of ot)Yt=Math.min(Yt,ve.x),Kt=Math.min(Kt,ve.y),xr=Math.max(xr,ve.x),Ir=Math.max(Ir,ve.y);for(let ve=0;ve=0&&We[1].y+et>=0){let it=Xe.map(Ht=>De.getTilePoint(Ht)),Ft=ot.map(Ht=>De.getTilePoint(Ht));ee.push({tile:be,tileID:De,queryGeometry:it,cameraQueryGeometry:Ft,scale:Be})}}return ee}getVisibleCoordinates(w){let B=this.getRenderableIds(w).map(Q=>this._tiles[Q].tileID);for(let Q of B)Q.posMatrix=this.transform.calculatePosMatrix(Q.toUnwrapped());return B}hasTransition(){if(this._source.hasTransition())return!0;if(lr(this._source.type)){let w=u.now();for(let B in this._tiles)if(this._tiles[B].fadeEndTime>=w)return!0}return!1}setFeatureState(w,B,Q){this._state.updateState(w=w||"_geojsonTileLayer",B,Q)}removeFeatureState(w,B,Q){this._state.removeFeatureState(w=w||"_geojsonTileLayer",B,Q)}getFeatureState(w,B){return this._state.getState(w=w||"_geojsonTileLayer",B)}setDependencies(w,B,Q){let ee=this._tiles[w];ee&&ee.setDependencies(B,Q)}reloadTilesForDependencies(w,B){for(let Q in this._tiles)this._tiles[Q].hasDependency(w,B)&&this._reloadTile(Q,"reloading");this._cache.filter(Q=>!Q.hasDependency(w,B))}}function er(ue,w){let B=Math.abs(2*ue.wrap)-+(ue.wrap<0),Q=Math.abs(2*w.wrap)-+(w.wrap<0);return ue.overscaledZ-w.overscaledZ||Q-B||w.canonical.y-ue.canonical.y||w.canonical.x-ue.canonical.x}function lr(ue){return ue==="raster"||ue==="image"||ue==="video"}mt.maxOverzooming=10,mt.maxUnderzooming=3;class Tr{constructor(w,B){this.reset(w,B)}reset(w,B){this.points=w||[],this._distances=[0];for(let Q=1;Q0?(ee-qe)/Xe:0;return this.points[le].mult(1-ot).add(this.points[B].mult(ot))}}function Lr(ue,w){let B=!0;return ue==="always"||ue!=="never"&&w!=="never"||(B=!1),B}class ti{constructor(w,B,Q){let ee=this.boxCells=[],le=this.circleCells=[];this.xCellCount=Math.ceil(w/Q),this.yCellCount=Math.ceil(B/Q);for(let qe=0;qethis.width||ee<0||B>this.height)return[];let ot=[];if(w<=0&&B<=0&&this.width<=Q&&this.height<=ee){if(le)return[{key:null,x1:w,y1:B,x2:Q,y2:ee}];for(let Tt=0;Tt0}hitTestCircle(w,B,Q,ee,le){let qe=w-Q,Xe=w+Q,ot=B-Q,Tt=B+Q;if(Xe<0||qe>this.width||Tt<0||ot>this.height)return!1;let Yt=[];return this._forEachCell(qe,ot,Xe,Tt,this._queryCellCircle,Yt,{hitTest:!0,overlapMode:ee,circle:{x:w,y:B,radius:Q},seenUids:{box:{},circle:{}}},le),Yt.length>0}_queryCell(w,B,Q,ee,le,qe,Xe,ot){let{seenUids:Tt,hitTest:Yt,overlapMode:Kt}=Xe,xr=this.boxCells[le];if(xr!==null){let ve=this.bboxes;for(let be of xr)if(!Tt.box[be]){Tt.box[be]=!0;let De=4*be,Be=this.boxKeys[be];if(w<=ve[De+2]&&B<=ve[De+3]&&Q>=ve[De+0]&&ee>=ve[De+1]&&(!ot||ot(Be))&&(!Yt||!Lr(Kt,Be.overlapMode))&&(qe.push({key:Be,x1:ve[De],y1:ve[De+1],x2:ve[De+2],y2:ve[De+3]}),Yt))return!0}}let Ir=this.circleCells[le];if(Ir!==null){let ve=this.circles;for(let be of Ir)if(!Tt.circle[be]){Tt.circle[be]=!0;let De=3*be,Be=this.circleKeys[be];if(this._circleAndRectCollide(ve[De],ve[De+1],ve[De+2],w,B,Q,ee)&&(!ot||ot(Be))&&(!Yt||!Lr(Kt,Be.overlapMode))){let et=ve[De],We=ve[De+1],it=ve[De+2];if(qe.push({key:Be,x1:et-it,y1:We-it,x2:et+it,y2:We+it}),Yt)return!0}}}return!1}_queryCellCircle(w,B,Q,ee,le,qe,Xe,ot){let{circle:Tt,seenUids:Yt,overlapMode:Kt}=Xe,xr=this.boxCells[le];if(xr!==null){let ve=this.bboxes;for(let be of xr)if(!Yt.box[be]){Yt.box[be]=!0;let De=4*be,Be=this.boxKeys[be];if(this._circleAndRectCollide(Tt.x,Tt.y,Tt.radius,ve[De+0],ve[De+1],ve[De+2],ve[De+3])&&(!ot||ot(Be))&&!Lr(Kt,Be.overlapMode))return qe.push(!0),!0}}let Ir=this.circleCells[le];if(Ir!==null){let ve=this.circles;for(let be of Ir)if(!Yt.circle[be]){Yt.circle[be]=!0;let De=3*be,Be=this.circleKeys[be];if(this._circlesCollide(ve[De],ve[De+1],ve[De+2],Tt.x,Tt.y,Tt.radius)&&(!ot||ot(Be))&&!Lr(Kt,Be.overlapMode))return qe.push(!0),!0}}}_forEachCell(w,B,Q,ee,le,qe,Xe,ot){let Tt=this._convertToXCellCoord(w),Yt=this._convertToYCellCoord(B),Kt=this._convertToXCellCoord(Q),xr=this._convertToYCellCoord(ee);for(let Ir=Tt;Ir<=Kt;Ir++)for(let ve=Yt;ve<=xr;ve++)if(le.call(this,w,B,Q,ee,this.xCellCount*ve+Ir,qe,Xe,ot))return}_convertToXCellCoord(w){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(w*this.xScale)))}_convertToYCellCoord(w){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(w*this.yScale)))}_circlesCollide(w,B,Q,ee,le,qe){let Xe=ee-w,ot=le-B,Tt=Q+qe;return Tt*Tt>Xe*Xe+ot*ot}_circleAndRectCollide(w,B,Q,ee,le,qe,Xe){let ot=(qe-ee)/2,Tt=Math.abs(w-(ee+ot));if(Tt>ot+Q)return!1;let Yt=(Xe-le)/2,Kt=Math.abs(B-(le+Yt));if(Kt>Yt+Q)return!1;if(Tt<=ot||Kt<=Yt)return!0;let xr=Tt-ot,Ir=Kt-Yt;return xr*xr+Ir*Ir<=Q*Q}}function Br(ue,w,B,Q,ee){let le=a.H();return w?(a.K(le,le,[1/ee,1/ee,1]),B||a.ad(le,le,Q.angle)):a.L(le,Q.labelPlaneMatrix,ue),le}function Vr(ue,w,B,Q,ee){if(w){let le=a.ae(ue);return a.K(le,le,[ee,ee,1]),B||a.ad(le,le,-Q.angle),le}return Q.glCoordMatrix}function dt(ue,w,B,Q){let ee;Q?(ee=[ue,w,Q(ue,w),1],a.af(ee,ee,B)):(ee=[ue,w,0,1],$r(ee,ee,B));let le=ee[3];return{point:new a.P(ee[0]/le,ee[1]/le),signedDistanceFromCamera:le,isOccluded:!1}}function Ge(ue,w){return .5+ue/w*.5}function Je(ue,w){return ue.x>=-w[0]&&ue.x<=w[0]&&ue.y>=-w[1]&&ue.y<=w[1]}function je(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,Ir,ve){let be=Q?ue.textSizeData:ue.iconSizeData,De=a.ag(be,B.transform.zoom),Be=[256/B.width*2+1,256/B.height*2+1],et=Q?ue.text.dynamicLayoutVertexArray:ue.icon.dynamicLayoutVertexArray;et.clear();let We=ue.lineVertexArray,it=Q?ue.text.placedSymbolArray:ue.icon.placedSymbolArray,Ft=B.transform.width/B.transform.height,Ht=!1;for(let tr=0;trMath.abs(B.x-w.x)*Q?{useVertical:!0}:(ue===a.ah.vertical?w.yB.x)?{needsFlipping:!0}:null}function Ie(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt){let Kt=B/24,xr=w.lineOffsetX*Kt,Ir=w.lineOffsetY*Kt,ve;if(w.numGlyphs>1){let be=w.glyphStartIndex+w.numGlyphs,De=w.lineStartIndex,Be=w.lineStartIndex+w.lineLength,et=tt(Kt,Xe,xr,Ir,Q,w,Yt,ue);if(!et)return{notEnoughRoom:!0};let We=dt(et.first.point.x,et.first.point.y,qe,ue.getElevation).point,it=dt(et.last.point.x,et.last.point.y,qe,ue.getElevation).point;if(ee&&!Q){let Ft=xt(w.writingMode,We,it,Tt);if(Ft)return Ft}ve=[et.first];for(let Ft=w.glyphStartIndex+1;Ft0?We.point:function(Ht,tr,dr,Sr,Or,Wr){return xe(Ht,tr,dr,1,Or,Wr)}(ue.tileAnchorPoint,et,De,0,le,ue),Ft=xt(w.writingMode,De,it,Tt);if(Ft)return Ft}let be=vr(Kt*Xe.getoffsetX(w.glyphStartIndex),xr,Ir,Q,w.segment,w.lineStartIndex,w.lineStartIndex+w.lineLength,ue,Yt);if(!be||ue.projectionCache.anyProjectionOccluded)return{notEnoughRoom:!0};ve=[be]}for(let be of ve)a.aj(ot,be.point,be.angle);return{}}function xe(ue,w,B,Q,ee,le){let qe=ue.add(ue.sub(w)._unit()),Xe=ee!==void 0?dt(qe.x,qe.y,ee,le.getElevation).point:vt(qe.x,qe.y,le).point,ot=B.sub(Xe);return B.add(ot._mult(Q/ot.mag()))}function ke(ue,w,B){let Q=w.projectionCache;if(Q.projections[ue])return Q.projections[ue];let ee=new a.P(w.lineVertexArray.getx(ue),w.lineVertexArray.gety(ue)),le=vt(ee.x,ee.y,w);if(le.signedDistanceFromCamera>0)return Q.projections[ue]=le.point,Q.anyProjectionOccluded=Q.anyProjectionOccluded||le.isOccluded,le.point;let qe=ue-B.direction;return function(Xe,ot,Tt,Yt,Kt){return xe(Xe,ot,Tt,Yt,void 0,Kt)}(B.distanceFromAnchor===0?w.tileAnchorPoint:new a.P(w.lineVertexArray.getx(qe),w.lineVertexArray.gety(qe)),ee,B.previousVertex,B.absOffsetX-B.distanceFromAnchor+1,w)}function vt(ue,w,B){let Q=ue+B.translation[0],ee=w+B.translation[1],le;return!B.pitchWithMap&&B.projection.useSpecialProjectionForSymbols?(le=B.projection.projectTileCoordinates(Q,ee,B.unwrappedTileID,B.getElevation),le.point.x=(.5*le.point.x+.5)*B.width,le.point.y=(.5*-le.point.y+.5)*B.height):(le=dt(Q,ee,B.labelPlaneMatrix,B.getElevation),le.isOccluded=!1),le}function ir(ue,w,B){return ue._unit()._perp()._mult(w*B)}function ar(ue,w,B,Q,ee,le,qe,Xe,ot){if(Xe.projectionCache.offsets[ue])return Xe.projectionCache.offsets[ue];let Tt=B.add(w);if(ue+ot.direction=ee)return Xe.projectionCache.offsets[ue]=Tt,Tt;let Yt=ke(ue+ot.direction,Xe,ot),Kt=ir(Yt.sub(B),qe,ot.direction),xr=B.add(Kt),Ir=Yt.add(Kt);return Xe.projectionCache.offsets[ue]=a.ak(le,Tt,xr,Ir)||Tt,Xe.projectionCache.offsets[ue]}function vr(ue,w,B,Q,ee,le,qe,Xe,ot){let Tt=Q?ue-w:ue+w,Yt=Tt>0?1:-1,Kt=0;Q&&(Yt*=-1,Kt=Math.PI),Yt<0&&(Kt+=Math.PI);let xr,Ir=Yt>0?le+ee:le+ee+1;Xe.projectionCache.cachedAnchorPoint?xr=Xe.projectionCache.cachedAnchorPoint:(xr=vt(Xe.tileAnchorPoint.x,Xe.tileAnchorPoint.y,Xe).point,Xe.projectionCache.cachedAnchorPoint=xr);let ve,be,De=xr,Be=xr,et=0,We=0,it=Math.abs(Tt),Ft=[],Ht;for(;et+We<=it;){if(Ir+=Yt,Ir=qe)return null;et+=We,Be=De,be=ve;let Sr={absOffsetX:it,direction:Yt,distanceFromAnchor:et,previousVertex:Be};if(De=ke(Ir,Xe,Sr),B===0)Ft.push(Be),Ht=De.sub(Be);else{let Or,Wr=De.sub(Be);Or=Wr.mag()===0?ir(ke(Ir+Yt,Xe,Sr).sub(De),B,Yt):ir(Wr,B,Yt),be||(be=Be.add(Or)),ve=ar(Ir,Or,De,le,qe,be,B,Xe,Sr),Ft.push(be),Ht=ve.sub(be)}We=Ht.mag()}let tr=Ht._mult((it-et)/We)._add(be||Be),dr=Kt+Math.atan2(De.y-Be.y,De.x-Be.x);return Ft.push(tr),{point:tr,angle:ot?dr:0,path:Ft}}let ii=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function pi(ue,w){for(let B=0;B=1;fa--)Cn.push(cn.path[fa]);for(let fa=1;fa$a.signedDistanceFromCamera<=0)?[]:fa.map($a=>$a.point)}let Ta=[];if(Cn.length>0){let fa=Cn[0].clone(),$a=Cn[0].clone();for(let Co=1;Co=Wr.x&&$a.x<=ni.x&&fa.y>=Wr.y&&$a.y<=ni.y?[Cn]:$a.xni.x||$a.yni.y?[]:a.al([Cn],Wr.x,Wr.y,ni.x,ni.y)}for(let fa of Ta){Pi.reset(fa,.25*Or);let $a=0;$a=Pi.length<=.5*Or?1:Math.ceil(Pi.paddedLength/Kn)+1;for(let Co=0;Co<$a;Co++){let Qa=Co/Math.max($a-1,1),mo=Pi.lerp(Qa),Bo=mo.x+di,Ps=mo.y+di;Be.push(Bo,Ps,Or,0);let Ts=Bo-Or,wo=Ps-Or,To=Bo+Or,hl=Ps+Or;if(Sr=Sr&&this.isOffscreen(Ts,wo,To,hl),dr=dr||this.isInsideGrid(Ts,wo,To,hl),w!=="always"&&this.grid.hitTestCircle(Bo,Ps,Or,w,xr)&&(tr=!0,!Yt))return{circles:[],offscreen:!1,collisionDetected:tr}}}}return{circles:!Yt&&tr||!dr||Wedt(ee.x,ee.y,Q,B.getElevation))}queryRenderedSymbols(w){if(w.length===0||this.grid.keysLength()===0&&this.ignoredGrid.keysLength()===0)return{};let B=[],Q=1/0,ee=1/0,le=-1/0,qe=-1/0;for(let Yt of w){let Kt=new a.P(Yt.x+di,Yt.y+di);Q=Math.min(Q,Kt.x),ee=Math.min(ee,Kt.y),le=Math.max(le,Kt.x),qe=Math.max(qe,Kt.y),B.push(Kt)}let Xe=this.grid.query(Q,ee,le,qe).concat(this.ignoredGrid.query(Q,ee,le,qe)),ot={},Tt={};for(let Yt of Xe){let Kt=Yt.key;if(ot[Kt.bucketInstanceId]===void 0&&(ot[Kt.bucketInstanceId]={}),ot[Kt.bucketInstanceId][Kt.featureIndex])continue;let xr=[new a.P(Yt.x1,Yt.y1),new a.P(Yt.x2,Yt.y1),new a.P(Yt.x2,Yt.y2),new a.P(Yt.x1,Yt.y2)];a.am(B,xr)&&(ot[Kt.bucketInstanceId][Kt.featureIndex]=!0,Tt[Kt.bucketInstanceId]===void 0&&(Tt[Kt.bucketInstanceId]=[]),Tt[Kt.bucketInstanceId].push(Kt.featureIndex))}return Tt}insertCollisionBox(w,B,Q,ee,le,qe){(Q?this.ignoredGrid:this.grid).insert({bucketInstanceId:ee,featureIndex:le,collisionGroupID:qe,overlapMode:B},w[0],w[1],w[2],w[3])}insertCollisionCircles(w,B,Q,ee,le,qe){let Xe=Q?this.ignoredGrid:this.grid,ot={bucketInstanceId:ee,featureIndex:le,collisionGroupID:qe,overlapMode:B};for(let Tt=0;Tt=this.screenRightBoundary||eethis.screenBottomBoundary}isInsideGrid(w,B,Q,ee){return Q>=0&&w=0&&Bthis.projectAndGetPerspectiveRatio(Q,Or.x,Or.y,ee,Tt));dr=Sr.some(Or=>!Or.isOccluded),tr=Sr.map(Or=>Or.point)}else dr=!0;return{box:a.ao(tr),allPointsOccluded:!dr}}}function In(ue,w,B){return w*(a.X/(ue.tileSize*Math.pow(2,B-ue.tileID.overscaledZ)))}class wi{constructor(w,B,Q,ee){this.opacity=w?Math.max(0,Math.min(1,w.opacity+(w.placed?B:-B))):ee&&Q?1:0,this.placed=Q}isHidden(){return this.opacity===0&&!this.placed}}class On{constructor(w,B,Q,ee,le){this.text=new wi(w?w.text:null,B,Q,le),this.icon=new wi(w?w.icon:null,B,ee,le)}isHidden(){return this.text.isHidden()&&this.icon.isHidden()}}class qn{constructor(w,B,Q){this.text=w,this.icon=B,this.skipFade=Q}}class Fn{constructor(){this.invProjMatrix=a.H(),this.viewportMatrix=a.H(),this.circles=[]}}class ra{constructor(w,B,Q,ee,le){this.bucketInstanceId=w,this.featureIndex=B,this.sourceLayerIndex=Q,this.bucketIndex=ee,this.tileID=le}}class la{constructor(w){this.crossSourceCollisions=w,this.maxGroupID=0,this.collisionGroups={}}get(w){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[w]){let B=++this.maxGroupID;this.collisionGroups[w]={ID:B,predicate:Q=>Q.collisionGroupID===B}}return this.collisionGroups[w]}}function Ut(ue,w,B,Q,ee){let{horizontalAlign:le,verticalAlign:qe}=a.au(ue);return new a.P(-(le-.5)*w+Q[0]*ee,-(qe-.5)*B+Q[1]*ee)}class wt{constructor(w,B,Q,ee,le,qe){this.transform=w.clone(),this.terrain=Q,this.collisionIndex=new ji(this.transform,B),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=ee,this.retainedQueryData={},this.collisionGroups=new la(le),this.collisionCircleArrays={},this.collisionBoxArrays=new Map,this.prevPlacement=qe,qe&&(qe.prevPlacement=void 0),this.placedOrientations={}}_getTerrainElevationFunc(w){let B=this.terrain;return B?(Q,ee)=>B.getElevation(w,Q,ee):null}getBucketParts(w,B,Q,ee){let le=Q.getBucket(B),qe=Q.latestFeatureIndex;if(!le||!qe||B.id!==le.layerIds[0])return;let Xe=Q.collisionBoxArray,ot=le.layers[0].layout,Tt=le.layers[0].paint,Yt=Math.pow(2,this.transform.zoom-Q.tileID.overscaledZ),Kt=Q.tileSize/a.X,xr=Q.tileID.toUnwrapped(),Ir=this.transform.calculatePosMatrix(xr),ve=ot.get("text-pitch-alignment")==="map",be=ot.get("text-rotation-alignment")==="map",De=In(Q,1,this.transform.zoom),Be=this.collisionIndex.mapProjection.translatePosition(this.transform,Q,Tt.get("text-translate"),Tt.get("text-translate-anchor")),et=this.collisionIndex.mapProjection.translatePosition(this.transform,Q,Tt.get("icon-translate"),Tt.get("icon-translate-anchor")),We=Br(Ir,ve,be,this.transform,De),it=null;if(ve){let Ht=Vr(Ir,ve,be,this.transform,De);it=a.L([],this.transform.labelPlaneMatrix,Ht)}this.retainedQueryData[le.bucketInstanceId]=new ra(le.bucketInstanceId,qe,le.sourceLayerIndex,le.index,Q.tileID);let Ft={bucket:le,layout:ot,translationText:Be,translationIcon:et,posMatrix:Ir,unwrappedTileID:xr,textLabelPlaneMatrix:We,labelToScreenMatrix:it,scale:Yt,textPixelRatio:Kt,holdingForFade:Q.holdingForFade(),collisionBoxArray:Xe,partiallyEvaluatedTextSize:a.ag(le.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(le.sourceID)};if(ee)for(let Ht of le.sortKeyRanges){let{sortKey:tr,symbolInstanceStart:dr,symbolInstanceEnd:Sr}=Ht;w.push({sortKey:tr,symbolInstanceStart:dr,symbolInstanceEnd:Sr,parameters:Ft})}else w.push({symbolInstanceStart:0,symbolInstanceEnd:le.symbolInstances.length,parameters:Ft})}attemptAnchorPlacement(w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,Ir,ve,be,De,Be,et,We){let it=a.aq[w.textAnchor],Ft=[w.textOffset0,w.textOffset1],Ht=Ut(it,Q,ee,Ft,le),tr=this.collisionIndex.placeCollisionBox(B,xr,ot,Tt,Yt,Xe,qe,De,Kt.predicate,We,Ht);if((!et||this.collisionIndex.placeCollisionBox(et,xr,ot,Tt,Yt,Xe,qe,Be,Kt.predicate,We,Ht).placeable)&&tr.placeable){let dr;if(this.prevPlacement&&this.prevPlacement.variableOffsets[Ir.crossTileID]&&this.prevPlacement.placements[Ir.crossTileID]&&this.prevPlacement.placements[Ir.crossTileID].text&&(dr=this.prevPlacement.variableOffsets[Ir.crossTileID].anchor),Ir.crossTileID===0)throw new Error("symbolInstance.crossTileID can't be 0");return this.variableOffsets[Ir.crossTileID]={textOffset:Ft,width:Q,height:ee,anchor:it,textBoxScale:le,prevAnchor:dr},this.markUsedJustification(ve,it,Ir,be),ve.allowVerticalPlacement&&(this.markUsedOrientation(ve,be,Ir),this.placedOrientations[Ir.crossTileID]=be),{shift:Ht,placedGlyphBoxes:tr}}}placeLayerBucketPart(w,B,Q){let{bucket:ee,layout:le,translationText:qe,translationIcon:Xe,posMatrix:ot,unwrappedTileID:Tt,textLabelPlaneMatrix:Yt,labelToScreenMatrix:Kt,textPixelRatio:xr,holdingForFade:Ir,collisionBoxArray:ve,partiallyEvaluatedTextSize:be,collisionGroup:De}=w.parameters,Be=le.get("text-optional"),et=le.get("icon-optional"),We=a.ar(le,"text-overlap","text-allow-overlap"),it=We==="always",Ft=a.ar(le,"icon-overlap","icon-allow-overlap"),Ht=Ft==="always",tr=le.get("text-rotation-alignment")==="map",dr=le.get("text-pitch-alignment")==="map",Sr=le.get("icon-text-fit")!=="none",Or=le.get("symbol-z-order")==="viewport-y",Wr=it&&(Ht||!ee.hasIconData()||et),ni=Ht&&(it||!ee.hasTextData()||Be);!ee.collisionArrays&&ve&&ee.deserializeCollisionBoxes(ve);let Pi=this._getTerrainElevationFunc(this.retainedQueryData[ee.bucketInstanceId].tileID),cn=(ln,Cn,Kn)=>{var Ta,fa;if(B[ln.crossTileID])return;if(Ir)return void(this.placements[ln.crossTileID]=new qn(!1,!1,!1));let $a=!1,Co=!1,Qa=!0,mo=null,Bo={box:null,placeable:!1,offscreen:null},Ps={box:null,placeable:!1,offscreen:null},Ts=null,wo=null,To=null,hl=0,Ul=0,Lu=0;Cn.textFeatureIndex?hl=Cn.textFeatureIndex:ln.useRuntimeCollisionCircles&&(hl=ln.featureIndex),Cn.verticalTextFeatureIndex&&(Ul=Cn.verticalTextFeatureIndex);let au=Cn.textBox;if(au){let Tl=Te=>{let Ne=a.ah.horizontal;if(ee.allowVerticalPlacement&&!Te&&this.prevPlacement){let He=this.prevPlacement.placedOrientations[ln.crossTileID];He&&(this.placedOrientations[ln.crossTileID]=He,Ne=He,this.markUsedOrientation(ee,Ne,ln))}return Ne},Al=(Te,Ne)=>{if(ee.allowVerticalPlacement&&ln.numVerticalGlyphVertices>0&&Cn.verticalTextBox){for(let He of ee.writingModes)if(He===a.ah.vertical?(Bo=Ne(),Ps=Bo):Bo=Te(),Bo&&Bo.placeable)break}else Bo=Te()},X=ln.textAnchorOffsetStartIndex,se=ln.textAnchorOffsetEndIndex;if(se===X){let Te=(Ne,He)=>{let Ye=this.collisionIndex.placeCollisionBox(Ne,We,xr,ot,Tt,dr,tr,qe,De.predicate,Pi);return Ye&&Ye.placeable&&(this.markUsedOrientation(ee,He,ln),this.placedOrientations[ln.crossTileID]=He),Ye};Al(()=>Te(au,a.ah.horizontal),()=>{let Ne=Cn.verticalTextBox;return ee.allowVerticalPlacement&&ln.numVerticalGlyphVertices>0&&Ne?Te(Ne,a.ah.vertical):{box:null,offscreen:null}}),Tl(Bo&&Bo.placeable)}else{let Te=a.aq[(fa=(Ta=this.prevPlacement)===null||Ta===void 0?void 0:Ta.variableOffsets[ln.crossTileID])===null||fa===void 0?void 0:fa.anchor],Ne=(Ye,kt,nt)=>{let jt=Ye.x2-Ye.x1,gr=Ye.y2-Ye.y1,yr=ln.textBoxScale,Hr=Sr&&Ft==="never"?kt:null,qr=null,_i=We==="never"?1:2,bi="never";Te&&_i++;for(let Zr=0;Zr<_i;Zr++){for(let ai=X;aiNe(au,Cn.iconBox,a.ah.horizontal),()=>{let Ye=Cn.verticalTextBox;return ee.allowVerticalPlacement&&(!Bo||!Bo.placeable)&&ln.numVerticalGlyphVertices>0&&Ye?Ne(Ye,Cn.verticalIconBox,a.ah.vertical):{box:null,occluded:!0,offscreen:null}}),Bo&&($a=Bo.placeable,Qa=Bo.offscreen);let He=Tl(Bo&&Bo.placeable);if(!$a&&this.prevPlacement){let Ye=this.prevPlacement.variableOffsets[ln.crossTileID];Ye&&(this.variableOffsets[ln.crossTileID]=Ye,this.markUsedJustification(ee,Ye.anchor,ln,He))}}}if(Ts=Bo,$a=Ts&&Ts.placeable,Qa=Ts&&Ts.offscreen,ln.useRuntimeCollisionCircles){let Tl=ee.text.placedSymbolArray.get(ln.centerJustifiedTextSymbolIndex),Al=a.ai(ee.textSizeData,be,Tl),X=le.get("text-padding");wo=this.collisionIndex.placeCollisionCircles(We,Tl,ee.lineVertexArray,ee.glyphOffsetArray,Al,ot,Tt,Yt,Kt,Q,dr,De.predicate,ln.collisionCircleDiameter,X,qe,Pi),wo.circles.length&&wo.collisionDetected&&!Q&&a.w("Collisions detected, but collision boxes are not shown"),$a=it||wo.circles.length>0&&!wo.collisionDetected,Qa=Qa&&wo.offscreen}if(Cn.iconFeatureIndex&&(Lu=Cn.iconFeatureIndex),Cn.iconBox){let Tl=Al=>this.collisionIndex.placeCollisionBox(Al,Ft,xr,ot,Tt,dr,tr,Xe,De.predicate,Pi,Sr&&mo?mo:void 0);Ps&&Ps.placeable&&Cn.verticalIconBox?(To=Tl(Cn.verticalIconBox),Co=To.placeable):(To=Tl(Cn.iconBox),Co=To.placeable),Qa=Qa&&To.offscreen}let Js=Be||ln.numHorizontalGlyphVertices===0&&ln.numVerticalGlyphVertices===0,Ql=et||ln.numIconVertices===0;Js||Ql?Ql?Js||(Co=Co&&$a):$a=Co&&$a:Co=$a=Co&&$a;let dc=Co&&To.placeable;if($a&&Ts.placeable&&this.collisionIndex.insertCollisionBox(Ts.box,We,le.get("text-ignore-placement"),ee.bucketInstanceId,Ps&&Ps.placeable&&Ul?Ul:hl,De.ID),dc&&this.collisionIndex.insertCollisionBox(To.box,Ft,le.get("icon-ignore-placement"),ee.bucketInstanceId,Lu,De.ID),wo&&$a&&this.collisionIndex.insertCollisionCircles(wo.circles,We,le.get("text-ignore-placement"),ee.bucketInstanceId,hl,De.ID),Q&&this.storeCollisionData(ee.bucketInstanceId,Kn,Cn,Ts,To,wo),ln.crossTileID===0)throw new Error("symbolInstance.crossTileID can't be 0");if(ee.bucketInstanceId===0)throw new Error("bucket.bucketInstanceId can't be 0");this.placements[ln.crossTileID]=new qn($a||Wr,Co||ni,Qa||ee.justReloaded),B[ln.crossTileID]=!0};if(Or){if(w.symbolInstanceStart!==0)throw new Error("bucket.bucketInstanceId should be 0");let ln=ee.getSortedSymbolIndexes(this.transform.angle);for(let Cn=ln.length-1;Cn>=0;--Cn){let Kn=ln[Cn];cn(ee.symbolInstances.get(Kn),ee.collisionArrays[Kn],Kn)}}else for(let ln=w.symbolInstanceStart;ln=0&&(w.text.placedSymbolArray.get(Xe).crossTileID=le>=0&&Xe!==le?0:Q.crossTileID)}markUsedOrientation(w,B,Q){let ee=B===a.ah.horizontal||B===a.ah.horizontalOnly?B:0,le=B===a.ah.vertical?B:0,qe=[Q.leftJustifiedTextSymbolIndex,Q.centerJustifiedTextSymbolIndex,Q.rightJustifiedTextSymbolIndex];for(let Xe of qe)w.text.placedSymbolArray.get(Xe).placedOrientation=ee;Q.verticalPlacedTextSymbolIndex&&(w.text.placedSymbolArray.get(Q.verticalPlacedTextSymbolIndex).placedOrientation=le)}commit(w){this.commitTime=w,this.zoomAtLastRecencyCheck=this.transform.zoom;let B=this.prevPlacement,Q=!1;this.prevZoomAdjustment=B?B.zoomAdjustment(this.transform.zoom):0;let ee=B?B.symbolFadeChange(w):1,le=B?B.opacities:{},qe=B?B.variableOffsets:{},Xe=B?B.placedOrientations:{};for(let ot in this.placements){let Tt=this.placements[ot],Yt=le[ot];Yt?(this.opacities[ot]=new On(Yt,ee,Tt.text,Tt.icon),Q=Q||Tt.text!==Yt.text.placed||Tt.icon!==Yt.icon.placed):(this.opacities[ot]=new On(null,ee,Tt.text,Tt.icon,Tt.skipFade),Q=Q||Tt.text||Tt.icon)}for(let ot in le){let Tt=le[ot];if(!this.opacities[ot]){let Yt=new On(Tt,ee,!1,!1);Yt.isHidden()||(this.opacities[ot]=Yt,Q=Q||Tt.text.placed||Tt.icon.placed)}}for(let ot in qe)this.variableOffsets[ot]||!this.opacities[ot]||this.opacities[ot].isHidden()||(this.variableOffsets[ot]=qe[ot]);for(let ot in Xe)this.placedOrientations[ot]||!this.opacities[ot]||this.opacities[ot].isHidden()||(this.placedOrientations[ot]=Xe[ot]);if(B&&B.lastPlacementChangeTime===void 0)throw new Error("Last placement time for previous placement is not defined");Q?this.lastPlacementChangeTime=w:typeof this.lastPlacementChangeTime!="number"&&(this.lastPlacementChangeTime=B?B.lastPlacementChangeTime:w)}updateLayerOpacities(w,B){let Q={};for(let ee of B){let le=ee.getBucket(w);le&&ee.latestFeatureIndex&&w.id===le.layerIds[0]&&this.updateBucketOpacities(le,ee.tileID,Q,ee.collisionBoxArray)}}updateBucketOpacities(w,B,Q,ee){w.hasTextData()&&(w.text.opacityVertexArray.clear(),w.text.hasVisibleVertices=!1),w.hasIconData()&&(w.icon.opacityVertexArray.clear(),w.icon.hasVisibleVertices=!1),w.hasIconCollisionBoxData()&&w.iconCollisionBox.collisionVertexArray.clear(),w.hasTextCollisionBoxData()&&w.textCollisionBox.collisionVertexArray.clear();let le=w.layers[0],qe=le.layout,Xe=new On(null,0,!1,!1,!0),ot=qe.get("text-allow-overlap"),Tt=qe.get("icon-allow-overlap"),Yt=le._unevaluatedLayout.hasValue("text-variable-anchor")||le._unevaluatedLayout.hasValue("text-variable-anchor-offset"),Kt=qe.get("text-rotation-alignment")==="map",xr=qe.get("text-pitch-alignment")==="map",Ir=qe.get("icon-text-fit")!=="none",ve=new On(null,0,ot&&(Tt||!w.hasIconData()||qe.get("icon-optional")),Tt&&(ot||!w.hasTextData()||qe.get("text-optional")),!0);!w.collisionArrays&&ee&&(w.hasIconCollisionBoxData()||w.hasTextCollisionBoxData())&&w.deserializeCollisionBoxes(ee);let be=(Be,et,We)=>{for(let it=0;it0,dr=this.placedOrientations[et.crossTileID],Sr=dr===a.ah.vertical,Or=dr===a.ah.horizontal||dr===a.ah.horizontalOnly;if(We>0||it>0){let ni=tn(Ht.text);be(w.text,We,Sr?fn:ni),be(w.text,it,Or?fn:ni);let Pi=Ht.text.isHidden();[et.rightJustifiedTextSymbolIndex,et.centerJustifiedTextSymbolIndex,et.leftJustifiedTextSymbolIndex].forEach(Cn=>{Cn>=0&&(w.text.placedSymbolArray.get(Cn).hidden=Pi||Sr?1:0)}),et.verticalPlacedTextSymbolIndex>=0&&(w.text.placedSymbolArray.get(et.verticalPlacedTextSymbolIndex).hidden=Pi||Or?1:0);let cn=this.variableOffsets[et.crossTileID];cn&&this.markUsedJustification(w,cn.anchor,et,dr);let ln=this.placedOrientations[et.crossTileID];ln&&(this.markUsedJustification(w,"left",et,ln),this.markUsedOrientation(w,ln,et))}if(tr){let ni=tn(Ht.icon),Pi=!(Ir&&et.verticalPlacedIconSymbolIndex&&Sr);et.placedIconSymbolIndex>=0&&(be(w.icon,et.numIconVertices,Pi?ni:fn),w.icon.placedSymbolArray.get(et.placedIconSymbolIndex).hidden=Ht.icon.isHidden()),et.verticalPlacedIconSymbolIndex>=0&&(be(w.icon,et.numVerticalIconVertices,Pi?fn:ni),w.icon.placedSymbolArray.get(et.verticalPlacedIconSymbolIndex).hidden=Ht.icon.isHidden())}let Wr=De&&De.has(Be)?De.get(Be):{text:null,icon:null};if(w.hasIconCollisionBoxData()||w.hasTextCollisionBoxData()){let ni=w.collisionArrays[Be];if(ni){let Pi=new a.P(0,0);if(ni.textBox||ni.verticalTextBox){let cn=!0;if(Yt){let ln=this.variableOffsets[Ft];ln?(Pi=Ut(ln.anchor,ln.width,ln.height,ln.textOffset,ln.textBoxScale),Kt&&Pi._rotate(xr?this.transform.angle:-this.transform.angle)):cn=!1}if(ni.textBox||ni.verticalTextBox){let ln;ni.textBox&&(ln=Sr),ni.verticalTextBox&&(ln=Or),rr(w.textCollisionBox.collisionVertexArray,Ht.text.placed,!cn||ln,Wr.text,Pi.x,Pi.y)}}if(ni.iconBox||ni.verticalIconBox){let cn=!!(!Or&&ni.verticalIconBox),ln;ni.iconBox&&(ln=cn),ni.verticalIconBox&&(ln=!cn),rr(w.iconCollisionBox.collisionVertexArray,Ht.icon.placed,ln,Wr.icon,Ir?Pi.x:0,Ir?Pi.y:0)}}}}if(w.sortFeatures(this.transform.angle),this.retainedQueryData[w.bucketInstanceId]&&(this.retainedQueryData[w.bucketInstanceId].featureSortOrder=w.featureSortOrder),w.hasTextData()&&w.text.opacityVertexBuffer&&w.text.opacityVertexBuffer.updateData(w.text.opacityVertexArray),w.hasIconData()&&w.icon.opacityVertexBuffer&&w.icon.opacityVertexBuffer.updateData(w.icon.opacityVertexArray),w.hasIconCollisionBoxData()&&w.iconCollisionBox.collisionVertexBuffer&&w.iconCollisionBox.collisionVertexBuffer.updateData(w.iconCollisionBox.collisionVertexArray),w.hasTextCollisionBoxData()&&w.textCollisionBox.collisionVertexBuffer&&w.textCollisionBox.collisionVertexBuffer.updateData(w.textCollisionBox.collisionVertexArray),w.text.opacityVertexArray.length!==w.text.layoutVertexArray.length/4)throw new Error(`bucket.text.opacityVertexArray.length (= ${w.text.opacityVertexArray.length}) !== bucket.text.layoutVertexArray.length (= ${w.text.layoutVertexArray.length}) / 4`);if(w.icon.opacityVertexArray.length!==w.icon.layoutVertexArray.length/4)throw new Error(`bucket.icon.opacityVertexArray.length (= ${w.icon.opacityVertexArray.length}) !== bucket.icon.layoutVertexArray.length (= ${w.icon.layoutVertexArray.length}) / 4`);if(w.bucketInstanceId in this.collisionCircleArrays){let Be=this.collisionCircleArrays[w.bucketInstanceId];w.placementInvProjMatrix=Be.invProjMatrix,w.placementViewportMatrix=Be.viewportMatrix,w.collisionCircleArray=Be.circles,delete this.collisionCircleArrays[w.bucketInstanceId]}}symbolFadeChange(w){return this.fadeDuration===0?1:(w-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment}zoomAdjustment(w){return Math.max(0,(this.transform.zoom-w)/1.5)}hasTransitions(w){return this.stale||w-this.lastPlacementChangeTimew}setStale(){this.stale=!0}}function rr(ue,w,B,Q,ee,le){Q&&Q.length!==0||(Q=[0,0,0,0]);let qe=Q[0]-di,Xe=Q[1]-di,ot=Q[2]-di,Tt=Q[3]-di;ue.emplaceBack(w?1:0,B?1:0,ee||0,le||0,qe,Xe),ue.emplaceBack(w?1:0,B?1:0,ee||0,le||0,ot,Xe),ue.emplaceBack(w?1:0,B?1:0,ee||0,le||0,ot,Tt),ue.emplaceBack(w?1:0,B?1:0,ee||0,le||0,qe,Tt)}let nr=Math.pow(2,25),Er=Math.pow(2,24),Xr=Math.pow(2,17),ri=Math.pow(2,16),Qr=Math.pow(2,9),Oi=Math.pow(2,8),$i=Math.pow(2,1);function tn(ue){if(ue.opacity===0&&!ue.placed)return 0;if(ue.opacity===1&&ue.placed)return 4294967295;let w=ue.placed?1:0,B=Math.floor(127*ue.opacity);return B*nr+w*Er+B*Xr+w*ri+B*Qr+w*Oi+B*$i+w}let fn=0;function yn(){return{isOccluded:(ue,w,B)=>!1,getPitchedTextCorrection:(ue,w,B)=>1,get useSpecialProjectionForSymbols(){return!1},projectTileCoordinates(ue,w,B,Q){throw new Error("Not implemented.")},translatePosition:(ue,w,B,Q)=>function(ee,le,qe,Xe,ot=!1){if(!qe[0]&&!qe[1])return[0,0];let Tt=ot?Xe==="map"?ee.angle:0:Xe==="viewport"?-ee.angle:0;if(Tt){let Yt=Math.sin(Tt),Kt=Math.cos(Tt);qe=[qe[0]*Kt-qe[1]*Yt,qe[0]*Yt+qe[1]*Kt]}return[ot?qe[0]:In(le,qe[0],ee.zoom),ot?qe[1]:In(le,qe[1],ee.zoom)]}(ue,w,B,Q),getCircleRadiusCorrection:ue=>1}}class Sn{constructor(w){this._sortAcrossTiles=w.layout.get("symbol-z-order")!=="viewport-y"&&!w.layout.get("symbol-sort-key").isConstant(),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]}continuePlacement(w,B,Q,ee,le){let qe=this._bucketParts;for(;this._currentTileIndexXe.sortKey-ot.sortKey));this._currentPartIndex!this._forceFullPlacement&&u.now()-ee>2;for(;this._currentPlacementIndex>=0;){let qe=B[w[this._currentPlacementIndex]],Xe=this.placement.collisionIndex.transform.zoom;if(qe.type==="symbol"&&(!qe.minzoom||qe.minzoom<=Xe)&&(!qe.maxzoom||qe.maxzoom>Xe)){if(this._inProgressLayer||(this._inProgressLayer=new Sn(qe)),this._inProgressLayer.continuePlacement(Q[qe.source],this.placement,this._showCollisionBoxes,qe,le))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0}commit(w){return this.placement.commit(w),this.placement}}let ua=512/a.X/2;class ma{constructor(w,B,Q){this.tileID=w,this.bucketInstanceId=Q,this._symbolsByKey={};let ee=new Map;for(let le=0;le({x:Math.floor(ot.anchorX*ua),y:Math.floor(ot.anchorY*ua)})),crossTileIDs:qe.map(ot=>ot.crossTileID)};if(Xe.positions.length>128){let ot=new a.av(Xe.positions.length,16,Uint16Array);for(let{x:Tt,y:Yt}of Xe.positions)ot.add(Tt,Yt);ot.finish(),delete Xe.positions,Xe.index=ot}this._symbolsByKey[le]=Xe}}getScaledCoordinates(w,B){let{x:Q,y:ee,z:le}=this.tileID.canonical,{x:qe,y:Xe,z:ot}=B.canonical,Tt=ua/Math.pow(2,ot-le),Yt=(Xe*a.X+w.anchorY)*Tt,Kt=ee*a.X*ua;return{x:Math.floor((qe*a.X+w.anchorX)*Tt-Q*a.X*ua),y:Math.floor(Yt-Kt)}}findMatches(w,B,Q){let ee=this.tileID.canonical.zw)}}class Wa{constructor(){this.maxCrossTileID=0}generate(){return++this.maxCrossTileID}}class Fa{constructor(){this.indexes={},this.usedCrossTileIDs={},this.lng=0}handleWrapJump(w){let B=Math.round((w-this.lng)/360);if(B!==0)for(let Q in this.indexes){let ee=this.indexes[Q],le={};for(let qe in ee){let Xe=ee[qe];Xe.tileID=Xe.tileID.unwrapTo(Xe.tileID.wrap+B),le[Xe.tileID.key]=Xe}this.indexes[Q]=le}this.lng=w}addBucket(w,B,Q){if(this.indexes[w.overscaledZ]&&this.indexes[w.overscaledZ][w.key]){if(this.indexes[w.overscaledZ][w.key].bucketInstanceId===B.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(w.overscaledZ,this.indexes[w.overscaledZ][w.key])}for(let le=0;lew.overscaledZ)for(let Xe in qe){let ot=qe[Xe];ot.tileID.isChildOf(w)&&ot.findMatches(B.symbolInstances,w,ee)}else{let Xe=qe[w.scaledTo(Number(le)).key];Xe&&Xe.findMatches(B.symbolInstances,w,ee)}}for(let le=0;le{B[Q]=!0});for(let Q in this.layerIndexes)B[Q]||delete this.layerIndexes[Q]}}let da=(ue,w)=>a.t(ue,w&&w.filter(B=>B.identifier!=="source.canvas")),Wn=a.aw();class Ha extends a.E{constructor(w,B={}){super(),this._rtlPluginLoaded=()=>{for(let Q in this.sourceCaches){let ee=this.sourceCaches[Q].getSource().type;ee!=="vector"&&ee!=="geojson"||this.sourceCaches[Q].reload()}},this.map=w,this.dispatcher=new Le(Se(),w._getMapId()),this.dispatcher.registerMessageHandler("GG",(Q,ee)=>this.getGlyphs(Q,ee)),this.dispatcher.registerMessageHandler("GI",(Q,ee)=>this.getImages(Q,ee)),this.imageManager=new T,this.imageManager.setEventedParent(this),this.glyphManager=new G(w._requestManager,B.localIdeographFontFamily),this.lineAtlas=new oe(256,512),this.crossTileSymbolIndex=new Wo,this._spritesImagesIds={},this._layers={},this._order=[],this.sourceCaches={},this.zoomHistory=new a.ax,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast("SR",a.ay()),Qt().on(cr,this._rtlPluginLoaded),this.on("data",Q=>{if(Q.dataType!=="source"||Q.sourceDataType!=="metadata")return;let ee=this.sourceCaches[Q.sourceId];if(!ee)return;let le=ee.getSource();if(le&&le.vectorLayerIds)for(let qe in this._layers){let Xe=this._layers[qe];Xe.source===le.id&&this._validateLayer(Xe)}})}loadURL(w,B={},Q){this.fire(new a.k("dataloading",{dataType:"style"})),B.validate=typeof B.validate!="boolean"||B.validate;let ee=this.map._requestManager.transformRequest(w,"Style");this._loadStyleRequest=new AbortController;let le=this._loadStyleRequest;a.h(ee,this._loadStyleRequest).then(qe=>{this._loadStyleRequest=null,this._load(qe.data,B,Q)}).catch(qe=>{this._loadStyleRequest=null,qe&&!le.signal.aborted&&this.fire(new a.j(qe))})}loadJSON(w,B={},Q){this.fire(new a.k("dataloading",{dataType:"style"})),this._frameRequest=new AbortController,u.frameAsync(this._frameRequest).then(()=>{this._frameRequest=null,B.validate=B.validate!==!1,this._load(w,B,Q)}).catch(()=>{})}loadEmpty(){this.fire(new a.k("dataloading",{dataType:"style"})),this._load(Wn,{validate:!1})}_load(w,B,Q){var ee;let le=B.transformStyle?B.transformStyle(Q,w):w;if(!B.validate||!da(this,a.u(le))){this._loaded=!0,this.stylesheet=le;for(let qe in le.sources)this.addSource(qe,le.sources[qe],{validate:!1});le.sprite?this._loadSprite(le.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(le.glyphs),this._createLayers(),this.light=new N(this.stylesheet.light),this.sky=new te(this.stylesheet.sky),this.map.setTerrain((ee=this.stylesheet.terrain)!==null&&ee!==void 0?ee:null),this.fire(new a.k("data",{dataType:"style"})),this.fire(new a.k("style.load"))}}_createLayers(){let w=a.az(this.stylesheet.layers);this.dispatcher.broadcast("SL",w),this._order=w.map(B=>B.id),this._layers={},this._serializedLayers=null;for(let B of w){let Q=a.aA(B);Q.setEventedParent(this,{layer:{id:B.id}}),this._layers[B.id]=Q}}_loadSprite(w,B=!1,Q=void 0){let ee;this.imageManager.setLoaded(!1),this._spriteRequest=new AbortController,function(le,qe,Xe,ot){return a._(this,void 0,void 0,function*(){let Tt=C(le),Yt=Xe>1?"@2x":"",Kt={},xr={};for(let{id:Ir,url:ve}of Tt){let be=qe.transformRequest(M(ve,Yt,".json"),"SpriteJSON");Kt[Ir]=a.h(be,ot);let De=qe.transformRequest(M(ve,Yt,".png"),"SpriteImage");xr[Ir]=p.getImage(De,ot)}return yield Promise.all([...Object.values(Kt),...Object.values(xr)]),function(Ir,ve){return a._(this,void 0,void 0,function*(){let be={};for(let De in Ir){be[De]={};let Be=u.getImageCanvasContext((yield ve[De]).data),et=(yield Ir[De]).data;for(let We in et){let{width:it,height:Ft,x:Ht,y:tr,sdf:dr,pixelRatio:Sr,stretchX:Or,stretchY:Wr,content:ni,textFitWidth:Pi,textFitHeight:cn}=et[We];be[De][We]={data:null,pixelRatio:Sr,sdf:dr,stretchX:Or,stretchY:Wr,content:ni,textFitWidth:Pi,textFitHeight:cn,spriteData:{width:it,height:Ft,x:Ht,y:tr,context:Be}}}}return be})}(Kt,xr)})}(w,this.map._requestManager,this.map.getPixelRatio(),this._spriteRequest).then(le=>{if(this._spriteRequest=null,le)for(let qe in le){this._spritesImagesIds[qe]=[];let Xe=this._spritesImagesIds[qe]?this._spritesImagesIds[qe].filter(ot=>!(ot in le)):[];for(let ot of Xe)this.imageManager.removeImage(ot),this._changedImages[ot]=!0;for(let ot in le[qe]){let Tt=qe==="default"?ot:`${qe}:${ot}`;this._spritesImagesIds[qe].push(Tt),Tt in this.imageManager.images?this.imageManager.updateImage(Tt,le[qe][ot],!1):this.imageManager.addImage(Tt,le[qe][ot]),B&&(this._changedImages[Tt]=!0)}}}).catch(le=>{this._spriteRequest=null,ee=le,this.fire(new a.j(ee))}).finally(()=>{this.imageManager.setLoaded(!0),this._availableImages=this.imageManager.listImages(),B&&(this._changed=!0),this.dispatcher.broadcast("SI",this._availableImages),this.fire(new a.k("data",{dataType:"style"})),Q&&Q(ee)})}_unloadSprite(){for(let w of Object.values(this._spritesImagesIds).flat())this.imageManager.removeImage(w),this._changedImages[w]=!0;this._spritesImagesIds={},this._availableImages=this.imageManager.listImages(),this._changed=!0,this.dispatcher.broadcast("SI",this._availableImages),this.fire(new a.k("data",{dataType:"style"}))}_validateLayer(w){let B=this.sourceCaches[w.source];if(!B)return;let Q=w.sourceLayer;if(!Q)return;let ee=B.getSource();(ee.type==="geojson"||ee.vectorLayerIds&&ee.vectorLayerIds.indexOf(Q)===-1)&&this.fire(new a.j(new Error(`Source layer "${Q}" does not exist on source "${ee.id}" as specified by style layer "${w.id}".`)))}loaded(){if(!this._loaded||Object.keys(this._updatedSources).length)return!1;for(let w in this.sourceCaches)if(!this.sourceCaches[w].loaded())return!1;return!!this.imageManager.isLoaded()}_serializeByIds(w,B=!1){let Q=this._serializedAllLayers();if(!w||w.length===0)return Object.values(B?a.aB(Q):Q);let ee=[];for(let le of w)if(Q[le]){let qe=B?a.aB(Q[le]):Q[le];ee.push(qe)}return ee}_serializedAllLayers(){let w=this._serializedLayers;if(w)return w;w=this._serializedLayers={};let B=Object.keys(this._layers);for(let Q of B){let ee=this._layers[Q];ee.type!=="custom"&&(w[Q]=ee.serialize())}return w}hasTransitions(){if(this.light&&this.light.hasTransition()||this.sky&&this.sky.hasTransition())return!0;for(let w in this.sourceCaches)if(this.sourceCaches[w].hasTransition())return!0;for(let w in this._layers)if(this._layers[w].hasTransition())return!0;return!1}_checkLoaded(){if(!this._loaded)throw new Error("Style is not done loading.")}update(w){if(!this._loaded)return;let B=this._changed;if(B){let ee=Object.keys(this._updatedLayers),le=Object.keys(this._removedLayers);(ee.length||le.length)&&this._updateWorkerLayers(ee,le);for(let qe in this._updatedSources){let Xe=this._updatedSources[qe];if(Xe==="reload")this._reloadSource(qe);else{if(Xe!=="clear")throw new Error(`Invalid action ${Xe}`);this._clearSource(qe)}}this._updateTilesForChangedImages(),this._updateTilesForChangedGlyphs();for(let qe in this._updatedPaintProps)this._layers[qe].updateTransitions(w);this.light.updateTransitions(w),this.sky.updateTransitions(w),this._resetUpdates()}let Q={};for(let ee in this.sourceCaches){let le=this.sourceCaches[ee];Q[ee]=le.used,le.used=!1}for(let ee of this._order){let le=this._layers[ee];le.recalculate(w,this._availableImages),!le.isHidden(w.zoom)&&le.source&&(this.sourceCaches[le.source].used=!0)}for(let ee in Q){let le=this.sourceCaches[ee];!!Q[ee]!=!!le.used&&le.fire(new a.k("data",{sourceDataType:"visibility",dataType:"source",sourceId:ee}))}this.light.recalculate(w),this.sky.recalculate(w),this.z=w.zoom,B&&this.fire(new a.k("data",{dataType:"style"}))}_updateTilesForChangedImages(){let w=Object.keys(this._changedImages);if(w.length){for(let B in this.sourceCaches)this.sourceCaches[B].reloadTilesForDependencies(["icons","patterns"],w);this._changedImages={}}}_updateTilesForChangedGlyphs(){if(this._glyphsDidChange){for(let w in this.sourceCaches)this.sourceCaches[w].reloadTilesForDependencies(["glyphs"],[""]);this._glyphsDidChange=!1}}_updateWorkerLayers(w,B){this.dispatcher.broadcast("UL",{layers:this._serializeByIds(w,!1),removedIds:B})}_resetUpdates(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={},this._glyphsDidChange=!1}setState(w,B={}){var Q;this._checkLoaded();let ee=this.serialize();if(w=B.transformStyle?B.transformStyle(ee,w):w,((Q=B.validate)===null||Q===void 0||Q)&&da(this,a.u(w)))return!1;(w=a.aB(w)).layers=a.az(w.layers);let le=a.aC(ee,w),qe=this._getOperationsToPerform(le);if(qe.unimplemented.length>0)throw new Error(`Unimplemented: ${qe.unimplemented.join(", ")}.`);if(qe.operations.length===0)return!1;for(let Xe of qe.operations)Xe();return this.stylesheet=w,this._serializedLayers=null,!0}_getOperationsToPerform(w){let B=[],Q=[];for(let ee of w)switch(ee.command){case"setCenter":case"setZoom":case"setBearing":case"setPitch":continue;case"addLayer":B.push(()=>this.addLayer.apply(this,ee.args));break;case"removeLayer":B.push(()=>this.removeLayer.apply(this,ee.args));break;case"setPaintProperty":B.push(()=>this.setPaintProperty.apply(this,ee.args));break;case"setLayoutProperty":B.push(()=>this.setLayoutProperty.apply(this,ee.args));break;case"setFilter":B.push(()=>this.setFilter.apply(this,ee.args));break;case"addSource":B.push(()=>this.addSource.apply(this,ee.args));break;case"removeSource":B.push(()=>this.removeSource.apply(this,ee.args));break;case"setLayerZoomRange":B.push(()=>this.setLayerZoomRange.apply(this,ee.args));break;case"setLight":B.push(()=>this.setLight.apply(this,ee.args));break;case"setGeoJSONSourceData":B.push(()=>this.setGeoJSONSourceData.apply(this,ee.args));break;case"setGlyphs":B.push(()=>this.setGlyphs.apply(this,ee.args));break;case"setSprite":B.push(()=>this.setSprite.apply(this,ee.args));break;case"setSky":B.push(()=>this.setSky.apply(this,ee.args));break;case"setTerrain":B.push(()=>this.map.setTerrain.apply(this,ee.args));break;case"setTransition":B.push(()=>{});break;default:Q.push(ee.command)}return{operations:B,unimplemented:Q}}addImage(w,B){if(this.getImage(w))return this.fire(new a.j(new Error(`An image named "${w}" already exists.`)));this.imageManager.addImage(w,B),this._afterImageUpdated(w)}updateImage(w,B){this.imageManager.updateImage(w,B)}getImage(w){return this.imageManager.getImage(w)}removeImage(w){if(!this.getImage(w))return this.fire(new a.j(new Error(`An image named "${w}" does not exist.`)));this.imageManager.removeImage(w),this._afterImageUpdated(w)}_afterImageUpdated(w){this._availableImages=this.imageManager.listImages(),this._changedImages[w]=!0,this._changed=!0,this.dispatcher.broadcast("SI",this._availableImages),this.fire(new a.k("data",{dataType:"style"}))}listImages(){return this._checkLoaded(),this.imageManager.listImages()}addSource(w,B,Q={}){if(this._checkLoaded(),this.sourceCaches[w]!==void 0)throw new Error(`Source "${w}" already exists.`);if(!B.type)throw new Error(`The type property must be defined, but only the following properties were given: ${Object.keys(B).join(", ")}.`);if(["vector","raster","geojson","video","image"].indexOf(B.type)>=0&&this._validate(a.u.source,`sources.${w}`,B,null,Q))return;this.map&&this.map._collectResourceTiming&&(B.collectResourceTiming=!0);let ee=this.sourceCaches[w]=new mt(w,B,this.dispatcher);ee.style=this,ee.setEventedParent(this,()=>({isSourceLoaded:ee.loaded(),source:ee.serialize(),sourceId:w})),ee.onAdd(this.map),this._changed=!0}removeSource(w){if(this._checkLoaded(),this.sourceCaches[w]===void 0)throw new Error("There is no source with this ID");for(let Q in this._layers)if(this._layers[Q].source===w)return this.fire(new a.j(new Error(`Source "${w}" cannot be removed while layer "${Q}" is using it.`)));let B=this.sourceCaches[w];delete this.sourceCaches[w],delete this._updatedSources[w],B.fire(new a.k("data",{sourceDataType:"metadata",dataType:"source",sourceId:w})),B.setEventedParent(null),B.onRemove(this.map),this._changed=!0}setGeoJSONSourceData(w,B){if(this._checkLoaded(),this.sourceCaches[w]===void 0)throw new Error(`There is no source with this ID=${w}`);let Q=this.sourceCaches[w].getSource();if(Q.type!=="geojson")throw new Error(`geojsonSource.type is ${Q.type}, which is !== 'geojson`);Q.setData(B),this._changed=!0}getSource(w){return this.sourceCaches[w]&&this.sourceCaches[w].getSource()}addLayer(w,B,Q={}){this._checkLoaded();let ee=w.id;if(this.getLayer(ee))return void this.fire(new a.j(new Error(`Layer "${ee}" already exists on this map.`)));let le;if(w.type==="custom"){if(da(this,a.aD(w)))return;le=a.aA(w)}else{if("source"in w&&typeof w.source=="object"&&(this.addSource(ee,w.source),w=a.aB(w),w=a.e(w,{source:ee})),this._validate(a.u.layer,`layers.${ee}`,w,{arrayIndex:-1},Q))return;le=a.aA(w),this._validateLayer(le),le.setEventedParent(this,{layer:{id:ee}})}let qe=B?this._order.indexOf(B):this._order.length;if(B&&qe===-1)this.fire(new a.j(new Error(`Cannot add layer "${ee}" before non-existing layer "${B}".`)));else{if(this._order.splice(qe,0,ee),this._layerOrderChanged=!0,this._layers[ee]=le,this._removedLayers[ee]&&le.source&&le.type!=="custom"){let Xe=this._removedLayers[ee];delete this._removedLayers[ee],Xe.type!==le.type?this._updatedSources[le.source]="clear":(this._updatedSources[le.source]="reload",this.sourceCaches[le.source].pause())}this._updateLayer(le),le.onAdd&&le.onAdd(this.map)}}moveLayer(w,B){if(this._checkLoaded(),this._changed=!0,!this._layers[w])return void this.fire(new a.j(new Error(`The layer '${w}' does not exist in the map's style and cannot be moved.`)));if(w===B)return;let Q=this._order.indexOf(w);this._order.splice(Q,1);let ee=B?this._order.indexOf(B):this._order.length;B&&ee===-1?this.fire(new a.j(new Error(`Cannot move layer "${w}" before non-existing layer "${B}".`))):(this._order.splice(ee,0,w),this._layerOrderChanged=!0)}removeLayer(w){this._checkLoaded();let B=this._layers[w];if(!B)return void this.fire(new a.j(new Error(`Cannot remove non-existing layer "${w}".`)));B.setEventedParent(null);let Q=this._order.indexOf(w);this._order.splice(Q,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[w]=B,delete this._layers[w],this._serializedLayers&&delete this._serializedLayers[w],delete this._updatedLayers[w],delete this._updatedPaintProps[w],B.onRemove&&B.onRemove(this.map)}getLayer(w){return this._layers[w]}getLayersOrder(){return[...this._order]}hasLayer(w){return w in this._layers}setLayerZoomRange(w,B,Q){this._checkLoaded();let ee=this.getLayer(w);ee?ee.minzoom===B&&ee.maxzoom===Q||(B!=null&&(ee.minzoom=B),Q!=null&&(ee.maxzoom=Q),this._updateLayer(ee)):this.fire(new a.j(new Error(`Cannot set the zoom range of non-existing layer "${w}".`)))}setFilter(w,B,Q={}){this._checkLoaded();let ee=this.getLayer(w);if(ee){if(!a.aE(ee.filter,B))return B==null?(ee.filter=void 0,void this._updateLayer(ee)):void(this._validate(a.u.filter,`layers.${ee.id}.filter`,B,null,Q)||(ee.filter=a.aB(B),this._updateLayer(ee)))}else this.fire(new a.j(new Error(`Cannot filter non-existing layer "${w}".`)))}getFilter(w){return a.aB(this.getLayer(w).filter)}setLayoutProperty(w,B,Q,ee={}){this._checkLoaded();let le=this.getLayer(w);le?a.aE(le.getLayoutProperty(B),Q)||(le.setLayoutProperty(B,Q,ee),this._updateLayer(le)):this.fire(new a.j(new Error(`Cannot style non-existing layer "${w}".`)))}getLayoutProperty(w,B){let Q=this.getLayer(w);if(Q)return Q.getLayoutProperty(B);this.fire(new a.j(new Error(`Cannot get style of non-existing layer "${w}".`)))}setPaintProperty(w,B,Q,ee={}){this._checkLoaded();let le=this.getLayer(w);le?a.aE(le.getPaintProperty(B),Q)||(le.setPaintProperty(B,Q,ee)&&this._updateLayer(le),this._changed=!0,this._updatedPaintProps[w]=!0,this._serializedLayers=null):this.fire(new a.j(new Error(`Cannot style non-existing layer "${w}".`)))}getPaintProperty(w,B){return this.getLayer(w).getPaintProperty(B)}setFeatureState(w,B){this._checkLoaded();let Q=w.source,ee=w.sourceLayer,le=this.sourceCaches[Q];if(le===void 0)return void this.fire(new a.j(new Error(`The source '${Q}' does not exist in the map's style.`)));let qe=le.getSource().type;qe==="geojson"&&ee?this.fire(new a.j(new Error("GeoJSON sources cannot have a sourceLayer parameter."))):qe!=="vector"||ee?(w.id===void 0&&this.fire(new a.j(new Error("The feature id parameter must be provided."))),le.setFeatureState(ee,w.id,B)):this.fire(new a.j(new Error("The sourceLayer parameter must be provided for vector source types.")))}removeFeatureState(w,B){this._checkLoaded();let Q=w.source,ee=this.sourceCaches[Q];if(ee===void 0)return void this.fire(new a.j(new Error(`The source '${Q}' does not exist in the map's style.`)));let le=ee.getSource().type,qe=le==="vector"?w.sourceLayer:void 0;le!=="vector"||qe?B&&typeof w.id!="string"&&typeof w.id!="number"?this.fire(new a.j(new Error("A feature id is required to remove its specific state property."))):ee.removeFeatureState(qe,w.id,B):this.fire(new a.j(new Error("The sourceLayer parameter must be provided for vector source types.")))}getFeatureState(w){this._checkLoaded();let B=w.source,Q=w.sourceLayer,ee=this.sourceCaches[B];if(ee!==void 0)return ee.getSource().type!=="vector"||Q?(w.id===void 0&&this.fire(new a.j(new Error("The feature id parameter must be provided."))),ee.getFeatureState(Q,w.id)):void this.fire(new a.j(new Error("The sourceLayer parameter must be provided for vector source types.")));this.fire(new a.j(new Error(`The source '${B}' does not exist in the map's style.`)))}getTransition(){return a.e({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)}serialize(){if(!this._loaded)return;let w=a.aF(this.sourceCaches,le=>le.serialize()),B=this._serializeByIds(this._order,!0),Q=this.map.getTerrain()||void 0,ee=this.stylesheet;return a.aG({version:ee.version,name:ee.name,metadata:ee.metadata,light:ee.light,sky:ee.sky,center:ee.center,zoom:ee.zoom,bearing:ee.bearing,pitch:ee.pitch,sprite:ee.sprite,glyphs:ee.glyphs,transition:ee.transition,sources:w,layers:B,terrain:Q},le=>le!==void 0)}_updateLayer(w){this._updatedLayers[w.id]=!0,w.source&&!this._updatedSources[w.source]&&this.sourceCaches[w.source].getSource().type!=="raster"&&(this._updatedSources[w.source]="reload",this.sourceCaches[w.source].pause()),this._serializedLayers=null,this._changed=!0}_flattenAndSortRenderedFeatures(w){let B=qe=>this._layers[qe].type==="fill-extrusion",Q={},ee=[];for(let qe=this._order.length-1;qe>=0;qe--){let Xe=this._order[qe];if(B(Xe)){Q[Xe]=qe;for(let ot of w){let Tt=ot[Xe];if(Tt)for(let Yt of Tt)ee.push(Yt)}}}ee.sort((qe,Xe)=>Xe.intersectionZ-qe.intersectionZ);let le=[];for(let qe=this._order.length-1;qe>=0;qe--){let Xe=this._order[qe];if(B(Xe))for(let ot=ee.length-1;ot>=0;ot--){let Tt=ee[ot].feature;if(Q[Tt.layer.id]{let dr=Be.featureSortOrder;if(dr){let Sr=dr.indexOf(Ht.featureIndex);return dr.indexOf(tr.featureIndex)-Sr}return tr.featureIndex-Ht.featureIndex});for(let Ht of Ft)it.push(Ht)}}for(let Be in ve)ve[Be].forEach(et=>{let We=et.feature,it=Tt[Xe[Be].source].getFeatureState(We.layer["source-layer"],We.id);We.source=We.layer.source,We.layer["source-layer"]&&(We.sourceLayer=We.layer["source-layer"]),We.state=it});return ve}(this._layers,qe,this.sourceCaches,w,B,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(le)}querySourceFeatures(w,B){B&&B.filter&&this._validate(a.u.filter,"querySourceFeatures.filter",B.filter,null,B);let Q=this.sourceCaches[w];return Q?function(ee,le){let qe=ee.getRenderableIds().map(Tt=>ee.getTileByID(Tt)),Xe=[],ot={};for(let Tt=0;Ttxr.getTileByID(Ir)).sort((Ir,ve)=>ve.tileID.overscaledZ-Ir.tileID.overscaledZ||(Ir.tileID.isLessThan(ve.tileID)?-1:1))}let Kt=this.crossTileSymbolIndex.addLayer(Yt,ot[Yt.source],w.center.lng);qe=qe||Kt}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((le=le||this._layerOrderChanged||Q===0)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(u.now(),w.zoom))&&(this.pauseablePlacement=new Ba(w,this.map.terrain,this._order,le,B,Q,ee,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,ot),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(u.now()),Xe=!0),qe&&this.pauseablePlacement.placement.setStale()),Xe||qe)for(let Tt of this._order){let Yt=this._layers[Tt];Yt.type==="symbol"&&this.placement.updateLayerOpacities(Yt,ot[Yt.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(u.now())}_releaseSymbolFadeTiles(){for(let w in this.sourceCaches)this.sourceCaches[w].releaseSymbolFadeTiles()}getImages(w,B){return a._(this,void 0,void 0,function*(){let Q=yield this.imageManager.getImages(B.icons);this._updateTilesForChangedImages();let ee=this.sourceCaches[B.source];return ee&&ee.setDependencies(B.tileID.key,B.type,B.icons),Q})}getGlyphs(w,B){return a._(this,void 0,void 0,function*(){let Q=yield this.glyphManager.getGlyphs(B.stacks),ee=this.sourceCaches[B.source];return ee&&ee.setDependencies(B.tileID.key,B.type,[""]),Q})}getGlyphsUrl(){return this.stylesheet.glyphs||null}setGlyphs(w,B={}){this._checkLoaded(),w&&this._validate(a.u.glyphs,"glyphs",w,null,B)||(this._glyphsDidChange=!0,this.stylesheet.glyphs=w,this.glyphManager.entries={},this.glyphManager.setURL(w))}addSprite(w,B,Q={},ee){this._checkLoaded();let le=[{id:w,url:B}],qe=[...C(this.stylesheet.sprite),...le];this._validate(a.u.sprite,"sprite",qe,null,Q)||(this.stylesheet.sprite=qe,this._loadSprite(le,!0,ee))}removeSprite(w){this._checkLoaded();let B=C(this.stylesheet.sprite);if(B.find(Q=>Q.id===w)){if(this._spritesImagesIds[w])for(let Q of this._spritesImagesIds[w])this.imageManager.removeImage(Q),this._changedImages[Q]=!0;B.splice(B.findIndex(Q=>Q.id===w),1),this.stylesheet.sprite=B.length>0?B:void 0,delete this._spritesImagesIds[w],this._availableImages=this.imageManager.listImages(),this._changed=!0,this.dispatcher.broadcast("SI",this._availableImages),this.fire(new a.k("data",{dataType:"style"}))}else this.fire(new a.j(new Error(`Sprite "${w}" doesn't exists on this map.`)))}getSprite(){return C(this.stylesheet.sprite)}setSprite(w,B={},Q){this._checkLoaded(),w&&this._validate(a.u.sprite,"sprite",w,null,B)||(this.stylesheet.sprite=w,w?this._loadSprite(w,!0,Q):(this._unloadSprite(),Q&&Q(null)))}}var vo=a.Y([{name:"a_pos",type:"Int16",components:2}]);let jn={prelude:Mt(`#ifdef GL_ES +precision mediump float; +#else +#if !defined(lowp) +#define lowp +#endif +#if !defined(mediump) +#define mediump +#endif +#if !defined(highp) +#define highp +#endif +#endif +`,`#ifdef GL_ES +precision highp float; +#else +#if !defined(lowp) +#define lowp +#endif +#if !defined(mediump) +#define mediump +#endif +#if !defined(highp) +#define highp +#endif +#endif +vec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0 +);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;} +#ifdef TERRAIN3D +uniform sampler2D u_terrain;uniform float u_terrain_dim;uniform mat4 u_terrain_matrix;uniform vec4 u_terrain_unpack;uniform float u_terrain_exaggeration;uniform highp sampler2D u_depth; +#endif +const highp vec4 bitSh=vec4(256.*256.*256.,256.*256.,256.,1.);const highp vec4 bitShifts=vec4(1.)/bitSh;highp float unpack(highp vec4 color) {return dot(color,bitShifts);}highp float depthOpacity(vec3 frag) { +#ifdef TERRAIN3D +highp float d=unpack(texture2D(u_depth,frag.xy*0.5+0.5))+0.0001-frag.z;return 1.0-max(0.0,min(1.0,-d*500.0)); +#else +return 1.0; +#endif +}float calculate_visibility(vec4 pos) { +#ifdef TERRAIN3D +vec3 frag=pos.xyz/pos.w;highp float d=depthOpacity(frag);if (d > 0.95) return 1.0;return (d+depthOpacity(frag+vec3(0.0,0.01,0.0)))/2.0; +#else +return 1.0; +#endif +}float ele(vec2 pos) { +#ifdef TERRAIN3D +vec4 rgb=(texture2D(u_terrain,pos)*255.0)*u_terrain_unpack;return rgb.r+rgb.g+rgb.b-u_terrain_unpack.a; +#else +return 0.0; +#endif +}float get_elevation(vec2 pos) { +#ifdef TERRAIN3D +vec2 coord=(u_terrain_matrix*vec4(pos,0.0,1.0)).xy*u_terrain_dim+1.0;vec2 f=fract(coord);vec2 c=(floor(coord)+0.5)/(u_terrain_dim+2.0);float d=1.0/(u_terrain_dim+2.0);float tl=ele(c);float tr=ele(c+vec2(d,0.0));float bl=ele(c+vec2(0.0,d));float br=ele(c+vec2(d,d));float elevation=mix(mix(tl,tr,f.x),mix(bl,br,f.x),f.y);return elevation*u_terrain_exaggeration; +#else +return 0.0; +#endif +}`),background:Mt(`uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}"),backgroundPattern:Mt(`uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,"uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}"),circle:Mt(`varying vec3 v_data;varying float v_visibility; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define mediump float radius +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define highp vec4 stroke_color +#pragma mapbox: define mediump float stroke_width +#pragma mapbox: define lowp float stroke_opacity +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize mediump float radius +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize highp vec4 stroke_color +#pragma mapbox: initialize mediump float stroke_width +#pragma mapbox: initialize lowp float stroke_opacity +vec2 extrude=v_data.xy;float extrude_length=length(extrude);float antialiased_blur=v_data.z;float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=v_visibility*opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;varying float v_visibility; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define mediump float radius +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define highp vec4 stroke_color +#pragma mapbox: define mediump float stroke_width +#pragma mapbox: define lowp float stroke_opacity +void main(void) { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize mediump float radius +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize highp vec4 stroke_color +#pragma mapbox: initialize mediump float stroke_width +#pragma mapbox: initialize lowp float stroke_opacity +vec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);float ele=get_elevation(circle_center);v_visibility=calculate_visibility(u_matrix*vec4(circle_center,ele,1.0));if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,ele,1);} else {gl_Position=u_matrix*vec4(circle_center,ele,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}float antialiasblur=-max(1.0/u_device_pixel_ratio/(radius+stroke_width),blur);v_data=vec3(extrude.x,extrude.y,antialiasblur);}`),clippingMask:Mt("void main() {gl_FragColor=vec4(1.0);}","attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}"),heatmap:Mt(`uniform highp float u_intensity;varying vec2 v_extrude; +#pragma mapbox: define highp float weight +#define GAUSS_COEF 0.3989422804014327 +void main() { +#pragma mapbox: initialize highp float weight +float d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude; +#pragma mapbox: define highp float weight +#pragma mapbox: define mediump float radius +const highp float ZERO=1.0/255.0/16.0; +#define GAUSS_COEF 0.3989422804014327 +void main(void) { +#pragma mapbox: initialize highp float weight +#pragma mapbox: initialize mediump float radius +vec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,get_elevation(floor(a_pos*0.5)),1);gl_Position=u_matrix*pos;}`),heatmapTexture:Mt(`uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(0.0); +#endif +}`,"uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}"),collisionBox:Mt("varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}","attribute vec2 a_anchor_pos;attribute vec2 a_placed;attribute vec2 a_box_real;uniform mat4 u_matrix;uniform vec2 u_pixel_extrude_scale;varying float v_placed;varying float v_notUsed;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);}void main() {gl_Position=projectTileWithElevation(a_anchor_pos,get_elevation(a_anchor_pos));gl_Position.xy=((a_box_real+0.5)*u_pixel_extrude_scale*2.0-1.0)*vec2(1.0,-1.0)*gl_Position.w;if (gl_Position.z/gl_Position.w < 1.1) {gl_Position.z=0.5;}v_placed=a_placed.x;v_notUsed=a_placed.y;}"),collisionCircle:Mt("varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}","attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}"),debug:Mt("uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}","attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,get_elevation(a_pos),1);}"),fill:Mt(`#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float opacity +gl_FragColor=color*opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`attribute vec2 a_pos;uniform mat4 u_matrix; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float opacity +gl_Position=u_matrix*vec4(a_pos,0,1);}`),fillOutline:Mt(`varying vec2 v_pos; +#pragma mapbox: define highp vec4 outline_color +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize highp vec4 outline_color +#pragma mapbox: initialize lowp float opacity +float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos; +#pragma mapbox: define highp vec4 outline_color +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize highp vec4 outline_color +#pragma mapbox: initialize lowp float opacity +gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}`),fillOutlinePattern:Mt(`uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos; +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +void main() { +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos; +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}`),fillPattern:Mt(`#ifdef GL_ES +precision highp float; +#endif +uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b; +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +void main() { +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b; +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}`),fillExtrusion:Mt(`varying vec4 v_color;void main() {gl_FragColor=v_color; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed; +#ifdef TERRAIN3D +attribute vec2 a_centroid; +#endif +varying vec4 v_color; +#pragma mapbox: define highp float base +#pragma mapbox: define highp float height +#pragma mapbox: define highp vec4 color +void main() { +#pragma mapbox: initialize highp float base +#pragma mapbox: initialize highp float height +#pragma mapbox: initialize highp vec4 color +vec3 normal=a_normal_ed.xyz; +#ifdef TERRAIN3D +float height_terrain3d_offset=get_elevation(a_centroid);float base_terrain3d_offset=height_terrain3d_offset-(base > 0.0 ? 0.0 : 10.0); +#else +float height_terrain3d_offset=0.0;float base_terrain3d_offset=0.0; +#endif +base=max(0.0,base)+base_terrain3d_offset;height=max(0.0,height)+height_terrain3d_offset;float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}`),fillExtrusionPattern:Mt(`uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting; +#pragma mapbox: define lowp float base +#pragma mapbox: define lowp float height +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float base +#pragma mapbox: initialize lowp float height +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed; +#ifdef TERRAIN3D +attribute vec2 a_centroid; +#endif +varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting; +#pragma mapbox: define lowp float base +#pragma mapbox: define lowp float height +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float base +#pragma mapbox: initialize lowp float height +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to; +#ifdef TERRAIN3D +float height_terrain3d_offset=get_elevation(a_centroid);float base_terrain3d_offset=height_terrain3d_offset-(base > 0.0 ? 0.0 : 10.0); +#else +float height_terrain3d_offset=0.0;float base_terrain3d_offset=0.0; +#endif +base=max(0.0,base)+base_terrain3d_offset;height=max(0.0,height)+height_terrain3d_offset;float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0 +? a_pos +: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}`),hillshadePrepare:Mt(`#ifdef GL_ES +precision highp float; +#endif +uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggerationFactor=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;float exaggeration=u_zoom < 15.0 ? (u_zoom-15.0)*exaggerationFactor : 0.0;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/pow(2.0,exaggeration+(19.2562-u_zoom));gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}"),hillshade:Mt(`uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent; +#define PI 3.141592653589793 +void main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}"),line:Mt(`uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,` +#define scale 0.015873016 +attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float width +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float width +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude; +#ifdef TERRAIN3D +v_gamma_scale=1.0; +#else +float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective; +#endif +v_width2=vec2(outset,inset);}`),lineGradient:Mt(`uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp vec2 v_uv; +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,v_uv);gl_FragColor=color*(alpha*opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,` +#define scale 0.015873016 +attribute vec2 a_pos_normal;attribute vec4 a_data;attribute float a_uv_x;attribute float a_split_index;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;uniform float u_image_height;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp vec2 v_uv; +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float width +void main() { +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float width +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;highp float texel_height=1.0/u_image_height;highp float half_texel_height=0.5*texel_height;v_uv=vec2(a_uv_x,a_split_index*texel_height-half_texel_height);vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude; +#ifdef TERRAIN3D +v_gamma_scale=1.0; +#else +float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective; +#endif +v_width2=vec2(outset,inset);}`),linePattern:Mt(`#ifdef GL_ES +precision highp float; +#endif +uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width; +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,` +#define scale 0.015873016 +#define LINE_DISTANCE_SCALE 2.0 +attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width; +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define mediump float width +#pragma mapbox: define lowp float floorwidth +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize mediump float width +#pragma mapbox: initialize lowp float floorwidth +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude; +#ifdef TERRAIN3D +v_gamma_scale=1.0; +#else +float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective; +#endif +v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}`),lineSDF:Mt(`uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float width +#pragma mapbox: define lowp float floorwidth +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float width +#pragma mapbox: initialize lowp float floorwidth +float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,` +#define scale 0.015873016 +#define LINE_DISTANCE_SCALE 2.0 +attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float width +#pragma mapbox: define lowp float floorwidth +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float width +#pragma mapbox: initialize lowp float floorwidth +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude; +#ifdef TERRAIN3D +v_gamma_scale=1.0; +#else +float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective; +#endif +v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}`),raster:Mt(`uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}"),symbolIcon:Mt(`uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity; +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize lowp float opacity +lowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;uniform bool u_is_along_line;uniform bool u_is_variable_anchor;uniform vec2 u_translation;uniform float u_pitched_scale;varying vec2 v_tex;varying float v_fade_opacity;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);} +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize lowp float opacity +vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;float ele=get_elevation(a_pos);highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec2 translated_a_pos=a_pos+u_translation;vec4 projectedPoint=projectTileWithElevation(translated_a_pos,ele);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ? +camera_to_anchor_distance/u_camera_to_center_distance : +u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=projectTileWithElevation(translated_a_pos+vec2(1,0),ele);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos;if (u_is_along_line || u_is_variable_anchor) {projected_pos=vec4(a_projected_pos.xy,ele,1.0);} else if (u_pitch_with_map) {projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy+u_translation,ele,1.0);} else {projected_pos=u_label_plane_matrix*projectTileWithElevation(a_projected_pos.xy+u_translation,ele);}float z=float(u_pitch_with_map)*projected_pos.z/projected_pos.w;float projectionScaling=1.0;vec4 finalPos=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0)*projectionScaling,z,1.0);if(u_pitch_with_map) {finalPos=projectTileWithElevation(finalPos.xy,finalPos.z);}gl_Position=finalPos;v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float visibility=calculate_visibility(projectedPoint);v_fade_opacity=max(0.0,min(visibility,fade_opacity[0]+fade_change));}`),symbolSDF:Mt(`#define SDF_PX 8.0 +uniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1; +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +float EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float inner_edge=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);inner_edge=inner_edge+gamma*gamma_scale;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(inner_edge-gamma_scaled,inner_edge+gamma_scaled,dist);if (u_is_halo) {lowp float halo_edge=(6.0-halo_width/fontScale)/SDF_PX;alpha=min(smoothstep(halo_edge-gamma_scaled,halo_edge+gamma_scaled,dist),1.0-alpha);}gl_FragColor=color*(alpha*opacity*fade_opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform bool u_is_along_line;uniform bool u_is_variable_anchor;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_translation;uniform float u_pitched_scale;varying vec2 v_data0;varying vec3 v_data1;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);} +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;float ele=get_elevation(a_pos);highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec2 translated_a_pos=a_pos+u_translation;vec4 projectedPoint=projectTileWithElevation(translated_a_pos,ele);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ? +camera_to_anchor_distance/u_camera_to_center_distance : +u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=projectTileWithElevation(translated_a_pos+vec2(1,0),ele);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos;if (u_is_along_line || u_is_variable_anchor) {projected_pos=vec4(a_projected_pos.xy,ele,1.0);} else if (u_pitch_with_map) {projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy+u_translation,ele,1.0);} else {projected_pos=u_label_plane_matrix*projectTileWithElevation(a_projected_pos.xy+u_translation,ele);}float z=float(u_pitch_with_map)*projected_pos.z/projected_pos.w;float projectionScaling=1.0;vec4 finalPos=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset)*projectionScaling,z,1.0);if(u_pitch_with_map) {finalPos=projectTileWithElevation(finalPos.xy,finalPos.z);}float gamma_scale=finalPos.w;gl_Position=finalPos;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float visibility=calculate_visibility(projectedPoint);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(visibility,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}`),symbolTextAndIcon:Mt(`#define SDF_PX 8.0 +#define SDF 1.0 +#define ICON 0.0 +uniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1; +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +float fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +return;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;uniform bool u_is_along_line;uniform bool u_is_variable_anchor;uniform vec2 u_translation;uniform float u_pitched_scale;varying vec4 v_data0;varying vec4 v_data1;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);} +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;float ele=get_elevation(a_pos);highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec2 translated_a_pos=a_pos+u_translation;vec4 projectedPoint=projectTileWithElevation(translated_a_pos,ele);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ? +camera_to_anchor_distance/u_camera_to_center_distance : +u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=projectTileWithElevation(translated_a_pos+vec2(1,0),ele);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos;if (u_is_along_line || u_is_variable_anchor) {projected_pos=vec4(a_projected_pos.xy,ele,1.0);} else if (u_pitch_with_map) {projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy+u_translation,ele,1.0);} else {projected_pos=u_label_plane_matrix*projectTileWithElevation(a_projected_pos.xy+u_translation,ele);}float z=float(u_pitch_with_map)*projected_pos.z/projected_pos.w;float projectionScaling=1.0;vec4 finalPos=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale)*projectionScaling,z,1.0);if(u_pitch_with_map) {finalPos=projectTileWithElevation(finalPos.xy,finalPos.z);}float gamma_scale=finalPos.w;gl_Position=finalPos;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float visibility=calculate_visibility(projectedPoint);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(visibility,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}`),terrain:Mt("uniform sampler2D u_texture;uniform vec4 u_fog_color;uniform vec4 u_horizon_color;uniform float u_fog_ground_blend;uniform float u_fog_ground_blend_opacity;uniform float u_horizon_fog_blend;varying vec2 v_texture_pos;varying float v_fog_depth;const float gamma=2.2;vec4 gammaToLinear(vec4 color) {return pow(color,vec4(gamma));}vec4 linearToGamma(vec4 color) {return pow(color,vec4(1.0/gamma));}void main() {vec4 surface_color=texture2D(u_texture,v_texture_pos);if (v_fog_depth > u_fog_ground_blend) {vec4 surface_color_linear=gammaToLinear(surface_color);float blend_color=smoothstep(0.0,1.0,max((v_fog_depth-u_horizon_fog_blend)/(1.0-u_horizon_fog_blend),0.0));vec4 fog_horizon_color_linear=mix(gammaToLinear(u_fog_color),gammaToLinear(u_horizon_color),blend_color);float factor_fog=max(v_fog_depth-u_fog_ground_blend,0.0)/(1.0-u_fog_ground_blend);gl_FragColor=linearToGamma(mix(surface_color_linear,fog_horizon_color_linear,pow(factor_fog,2.0)*u_fog_ground_blend_opacity));} else {gl_FragColor=surface_color;}}","attribute vec3 a_pos3d;uniform mat4 u_matrix;uniform mat4 u_fog_matrix;uniform float u_ele_delta;varying vec2 v_texture_pos;varying float v_fog_depth;void main() {float ele=get_elevation(a_pos3d.xy);float ele_delta=a_pos3d.z==1.0 ? u_ele_delta : 0.0;v_texture_pos=a_pos3d.xy/8192.0;gl_Position=u_matrix*vec4(a_pos3d.xy,ele-ele_delta,1.0);vec4 pos=u_fog_matrix*vec4(a_pos3d.xy,ele,1.0);v_fog_depth=pos.z/pos.w*0.5+0.5;}"),terrainDepth:Mt("varying float v_depth;const highp vec4 bitSh=vec4(256.*256.*256.,256.*256.,256.,1.);const highp vec4 bitMsk=vec4(0.,vec3(1./256.0));highp vec4 pack(highp float value) {highp vec4 comp=fract(value*bitSh);comp-=comp.xxyz*bitMsk;return comp;}void main() {gl_FragColor=pack(v_depth);}","attribute vec3 a_pos3d;uniform mat4 u_matrix;uniform float u_ele_delta;varying float v_depth;void main() {float ele=get_elevation(a_pos3d.xy);float ele_delta=a_pos3d.z==1.0 ? u_ele_delta : 0.0;gl_Position=u_matrix*vec4(a_pos3d.xy,ele-ele_delta,1.0);v_depth=gl_Position.z/gl_Position.w;}"),terrainCoords:Mt("precision mediump float;uniform sampler2D u_texture;uniform float u_terrain_coords_id;varying vec2 v_texture_pos;void main() {vec4 rgba=texture2D(u_texture,v_texture_pos);gl_FragColor=vec4(rgba.r,rgba.g,rgba.b,u_terrain_coords_id);}","attribute vec3 a_pos3d;uniform mat4 u_matrix;uniform float u_ele_delta;varying vec2 v_texture_pos;void main() {float ele=get_elevation(a_pos3d.xy);float ele_delta=a_pos3d.z==1.0 ? u_ele_delta : 0.0;v_texture_pos=a_pos3d.xy/8192.0;gl_Position=u_matrix*vec4(a_pos3d.xy,ele-ele_delta,1.0);}"),sky:Mt("uniform vec4 u_sky_color;uniform vec4 u_horizon_color;uniform float u_horizon;uniform float u_sky_horizon_blend;void main() {float y=gl_FragCoord.y;if (y > u_horizon) {float blend=y-u_horizon;if (blend < u_sky_horizon_blend) {gl_FragColor=mix(u_sky_color,u_horizon_color,pow(1.0-blend/u_sky_horizon_blend,2.0));} else {gl_FragColor=u_sky_color;}}}","attribute vec2 a_pos;void main() {gl_Position=vec4(a_pos,1.0,1.0);}")};function Mt(ue,w){let B=/#pragma mapbox: ([\w]+) ([\w]+) ([\w]+) ([\w]+)/g,Q=w.match(/attribute ([\w]+) ([\w]+)/g),ee=ue.match(/uniform ([\w]+) ([\w]+)([\s]*)([\w]*)/g),le=w.match(/uniform ([\w]+) ([\w]+)([\s]*)([\w]*)/g),qe=le?le.concat(ee):ee,Xe={};return{fragmentSource:ue=ue.replace(B,(ot,Tt,Yt,Kt,xr)=>(Xe[xr]=!0,Tt==="define"?` +#ifndef HAS_UNIFORM_u_${xr} +varying ${Yt} ${Kt} ${xr}; +#else +uniform ${Yt} ${Kt} u_${xr}; +#endif +`:` +#ifdef HAS_UNIFORM_u_${xr} + ${Yt} ${Kt} ${xr} = u_${xr}; +#endif +`)),vertexSource:w=w.replace(B,(ot,Tt,Yt,Kt,xr)=>{let Ir=Kt==="float"?"vec2":"vec4",ve=xr.match(/color/)?"color":Ir;return Xe[xr]?Tt==="define"?` +#ifndef HAS_UNIFORM_u_${xr} +uniform lowp float u_${xr}_t; +attribute ${Yt} ${Ir} a_${xr}; +varying ${Yt} ${Kt} ${xr}; +#else +uniform ${Yt} ${Kt} u_${xr}; +#endif +`:ve==="vec4"?` +#ifndef HAS_UNIFORM_u_${xr} + ${xr} = a_${xr}; +#else + ${Yt} ${Kt} ${xr} = u_${xr}; +#endif +`:` +#ifndef HAS_UNIFORM_u_${xr} + ${xr} = unpack_mix_${ve}(a_${xr}, u_${xr}_t); +#else + ${Yt} ${Kt} ${xr} = u_${xr}; +#endif +`:Tt==="define"?` +#ifndef HAS_UNIFORM_u_${xr} +uniform lowp float u_${xr}_t; +attribute ${Yt} ${Ir} a_${xr}; +#else +uniform ${Yt} ${Kt} u_${xr}; +#endif +`:ve==="vec4"?` +#ifndef HAS_UNIFORM_u_${xr} + ${Yt} ${Kt} ${xr} = a_${xr}; +#else + ${Yt} ${Kt} ${xr} = u_${xr}; +#endif +`:` +#ifndef HAS_UNIFORM_u_${xr} + ${Yt} ${Kt} ${xr} = unpack_mix_${ve}(a_${xr}, u_${xr}_t); +#else + ${Yt} ${Kt} ${xr} = u_${xr}; +#endif +`}),staticAttributes:Q,staticUniforms:qe}}class kr{constructor(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null}bind(w,B,Q,ee,le,qe,Xe,ot,Tt){this.context=w;let Yt=this.boundPaintVertexBuffers.length!==ee.length;for(let Kt=0;!Yt&&Kt({u_matrix:ue,u_texture:0,u_ele_delta:w,u_fog_matrix:B,u_fog_color:Q?Q.properties.get("fog-color"):a.aM.white,u_fog_ground_blend:Q?Q.properties.get("fog-ground-blend"):1,u_fog_ground_blend_opacity:Q?Q.calculateFogBlendOpacity(ee):0,u_horizon_color:Q?Q.properties.get("horizon-color"):a.aM.white,u_horizon_fog_blend:Q?Q.properties.get("horizon-fog-blend"):1});function vi(ue){let w=[];for(let B=0;B({u_depth:new a.aH(Ht,tr.u_depth),u_terrain:new a.aH(Ht,tr.u_terrain),u_terrain_dim:new a.aI(Ht,tr.u_terrain_dim),u_terrain_matrix:new a.aJ(Ht,tr.u_terrain_matrix),u_terrain_unpack:new a.aK(Ht,tr.u_terrain_unpack),u_terrain_exaggeration:new a.aI(Ht,tr.u_terrain_exaggeration)}))(w,Ft),this.binderUniforms=Q?Q.getUniforms(w,Ft):[]}draw(w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,Ir,ve,be,De,Be,et){let We=w.gl;if(this.failedToCreate)return;if(w.program.set(this.program),w.setDepthMode(Q),w.setStencilMode(ee),w.setColorMode(le),w.setCullFace(qe),ot){w.activeTexture.set(We.TEXTURE2),We.bindTexture(We.TEXTURE_2D,ot.depthTexture),w.activeTexture.set(We.TEXTURE3),We.bindTexture(We.TEXTURE_2D,ot.texture);for(let Ft in this.terrainUniforms)this.terrainUniforms[Ft].set(ot[Ft])}for(let Ft in this.fixedUniforms)this.fixedUniforms[Ft].set(Xe[Ft]);be&&be.setUniforms(w,this.binderUniforms,Ir,{zoom:ve});let it=0;switch(B){case We.LINES:it=2;break;case We.TRIANGLES:it=3;break;case We.LINE_STRIP:it=1}for(let Ft of xr.get()){let Ht=Ft.vaos||(Ft.vaos={});(Ht[Tt]||(Ht[Tt]=new kr)).bind(w,this,Yt,be?be.getPaintVertexBuffers():[],Kt,Ft.vertexOffset,De,Be,et),We.drawElements(B,Ft.primitiveLength*it,We.UNSIGNED_SHORT,Ft.primitiveOffset*it*2)}}}function An(ue,w,B){let Q=1/In(B,1,w.transform.tileZoom),ee=Math.pow(2,B.tileID.overscaledZ),le=B.tileSize*Math.pow(2,w.transform.tileZoom)/ee,qe=le*(B.tileID.canonical.x+B.tileID.wrap*ee),Xe=le*B.tileID.canonical.y;return{u_image:0,u_texsize:B.imageAtlasTexture.size,u_scale:[Q,ue.fromScale,ue.toScale],u_fade:ue.t,u_pixel_coord_upper:[qe>>16,Xe>>16],u_pixel_coord_lower:[65535&qe,65535&Xe]}}let Mn=(ue,w,B,Q)=>{let ee=w.style.light,le=ee.properties.get("position"),qe=[le.x,le.y,le.z],Xe=function(){var Tt=new a.A(9);return a.A!=Float32Array&&(Tt[1]=0,Tt[2]=0,Tt[3]=0,Tt[5]=0,Tt[6]=0,Tt[7]=0),Tt[0]=1,Tt[4]=1,Tt[8]=1,Tt}();ee.properties.get("anchor")==="viewport"&&function(Tt,Yt){var Kt=Math.sin(Yt),xr=Math.cos(Yt);Tt[0]=xr,Tt[1]=Kt,Tt[2]=0,Tt[3]=-Kt,Tt[4]=xr,Tt[5]=0,Tt[6]=0,Tt[7]=0,Tt[8]=1}(Xe,-w.transform.angle),function(Tt,Yt,Kt){var xr=Yt[0],Ir=Yt[1],ve=Yt[2];Tt[0]=xr*Kt[0]+Ir*Kt[3]+ve*Kt[6],Tt[1]=xr*Kt[1]+Ir*Kt[4]+ve*Kt[7],Tt[2]=xr*Kt[2]+Ir*Kt[5]+ve*Kt[8]}(qe,qe,Xe);let ot=ee.properties.get("color");return{u_matrix:ue,u_lightpos:qe,u_lightintensity:ee.properties.get("intensity"),u_lightcolor:[ot.r,ot.g,ot.b],u_vertical_gradient:+B,u_opacity:Q}},Li=(ue,w,B,Q,ee,le,qe)=>a.e(Mn(ue,w,B,Q),An(le,w,qe),{u_height_factor:-Math.pow(2,ee.overscaledZ)/qe.tileSize/8}),_n=ue=>({u_matrix:ue}),ya=(ue,w,B,Q)=>a.e(_n(ue),An(B,w,Q)),Jn=(ue,w)=>({u_matrix:ue,u_world:w}),Ma=(ue,w,B,Q,ee)=>a.e(ya(ue,w,B,Q),{u_world:ee}),_o=(ue,w,B,Q)=>{let ee=ue.transform,le,qe;if(Q.paint.get("circle-pitch-alignment")==="map"){let Xe=In(B,1,ee.zoom);le=!0,qe=[Xe,Xe]}else le=!1,qe=ee.pixelsToGLUnits;return{u_camera_to_center_distance:ee.cameraToCenterDistance,u_scale_with_map:+(Q.paint.get("circle-pitch-scale")==="map"),u_matrix:ue.translatePosMatrix(w.posMatrix,B,Q.paint.get("circle-translate"),Q.paint.get("circle-translate-anchor")),u_pitch_with_map:+le,u_device_pixel_ratio:ue.pixelRatio,u_extrude_scale:qe}},No=(ue,w,B)=>({u_matrix:ue,u_inv_matrix:w,u_camera_to_center_distance:B.cameraToCenterDistance,u_viewport_size:[B.width,B.height]}),po=(ue,w,B=1)=>({u_matrix:ue,u_color:w,u_overlay:0,u_overlay_scale:B}),Lo=ue=>({u_matrix:ue}),ko=(ue,w,B,Q)=>({u_matrix:ue,u_extrude_scale:In(w,1,B),u_intensity:Q}),Ds=(ue,w,B,Q)=>{let ee=a.H();a.aP(ee,0,ue.width,ue.height,0,0,1);let le=ue.context.gl;return{u_matrix:ee,u_world:[le.drawingBufferWidth,le.drawingBufferHeight],u_image:B,u_color_ramp:Q,u_opacity:w.paint.get("heatmap-opacity")}};function Fs(ue,w){let B=Math.pow(2,w.canonical.z),Q=w.canonical.y;return[new a.Z(0,Q/B).toLngLat().lat,new a.Z(0,(Q+1)/B).toLngLat().lat]}let ll=(ue,w,B,Q)=>{let ee=ue.transform;return{u_matrix:As(ue,w,B,Q),u_ratio:1/In(w,1,ee.zoom),u_device_pixel_ratio:ue.pixelRatio,u_units_to_pixels:[1/ee.pixelsToGLUnits[0],1/ee.pixelsToGLUnits[1]]}},ul=(ue,w,B,Q,ee)=>a.e(ll(ue,w,B,ee),{u_image:0,u_image_height:Q}),zl=(ue,w,B,Q,ee)=>{let le=ue.transform,qe=il(w,le);return{u_matrix:As(ue,w,B,ee),u_texsize:w.imageAtlasTexture.size,u_ratio:1/In(w,1,le.zoom),u_device_pixel_ratio:ue.pixelRatio,u_image:0,u_scale:[qe,Q.fromScale,Q.toScale],u_fade:Q.t,u_units_to_pixels:[1/le.pixelsToGLUnits[0],1/le.pixelsToGLUnits[1]]}},us=(ue,w,B,Q,ee,le)=>{let qe=ue.lineAtlas,Xe=il(w,ue.transform),ot=B.layout.get("line-cap")==="round",Tt=qe.getDash(Q.from,ot),Yt=qe.getDash(Q.to,ot),Kt=Tt.width*ee.fromScale,xr=Yt.width*ee.toScale;return a.e(ll(ue,w,B,le),{u_patternscale_a:[Xe/Kt,-Tt.height/2],u_patternscale_b:[Xe/xr,-Yt.height/2],u_sdfgamma:qe.width/(256*Math.min(Kt,xr)*ue.pixelRatio)/2,u_image:0,u_tex_y_a:Tt.y,u_tex_y_b:Yt.y,u_mix:ee.t})};function il(ue,w){return 1/In(ue,1,w.tileZoom)}function As(ue,w,B,Q){return ue.translatePosMatrix(Q?Q.posMatrix:w.tileID.posMatrix,w,B.paint.get("line-translate"),B.paint.get("line-translate-anchor"))}let cl=(ue,w,B,Q,ee)=>{return{u_matrix:ue,u_tl_parent:w,u_scale_parent:B,u_buffer_scale:1,u_fade_t:Q.mix,u_opacity:Q.opacity*ee.paint.get("raster-opacity"),u_image0:0,u_image1:1,u_brightness_low:ee.paint.get("raster-brightness-min"),u_brightness_high:ee.paint.get("raster-brightness-max"),u_saturation_factor:(qe=ee.paint.get("raster-saturation"),qe>0?1-1/(1.001-qe):-qe),u_contrast_factor:(le=ee.paint.get("raster-contrast"),le>0?1/(1-le):1+le),u_spin_weights:Ks(ee.paint.get("raster-hue-rotate"))};var le,qe};function Ks(ue){ue*=Math.PI/180;let w=Math.sin(ue),B=Math.cos(ue);return[(2*B+1)/3,(-Math.sqrt(3)*w-B+1)/3,(Math.sqrt(3)*w-B+1)/3]}let zs=(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,Ir)=>{let ve=qe.transform;return{u_is_size_zoom_constant:+(ue==="constant"||ue==="source"),u_is_size_feature_constant:+(ue==="constant"||ue==="camera"),u_size_t:w?w.uSizeT:0,u_size:w?w.uSize:0,u_camera_to_center_distance:ve.cameraToCenterDistance,u_pitch:ve.pitch/360*2*Math.PI,u_rotate_symbol:+B,u_aspect_ratio:ve.width/ve.height,u_fade_change:qe.options.fadeDuration?qe.symbolFadeChange:1,u_matrix:Xe,u_label_plane_matrix:ot,u_coord_matrix:Tt,u_is_text:+Kt,u_pitch_with_map:+Q,u_is_along_line:ee,u_is_variable_anchor:le,u_texsize:xr,u_texture:0,u_translation:Yt,u_pitched_scale:Ir}},Io=(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,Ir,ve)=>{let be=qe.transform;return a.e(zs(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,ve),{u_gamma_scale:Q?Math.cos(be._pitch)*be.cameraToCenterDistance:1,u_device_pixel_ratio:qe.pixelRatio,u_is_halo:+Ir})},ls=(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,Kt,xr,Ir)=>a.e(Io(ue,w,B,Q,ee,le,qe,Xe,ot,Tt,Yt,!0,Kt,!0,Ir),{u_texsize_icon:xr,u_texture_icon:1}),Zl=(ue,w,B)=>({u_matrix:ue,u_opacity:w,u_color:B}),Su=(ue,w,B,Q,ee,le)=>a.e(function(qe,Xe,ot,Tt){let Yt=ot.imageManager.getPattern(qe.from.toString()),Kt=ot.imageManager.getPattern(qe.to.toString()),{width:xr,height:Ir}=ot.imageManager.getPixelSize(),ve=Math.pow(2,Tt.tileID.overscaledZ),be=Tt.tileSize*Math.pow(2,ot.transform.tileZoom)/ve,De=be*(Tt.tileID.canonical.x+Tt.tileID.wrap*ve),Be=be*Tt.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:Yt.tl,u_pattern_br_a:Yt.br,u_pattern_tl_b:Kt.tl,u_pattern_br_b:Kt.br,u_texsize:[xr,Ir],u_mix:Xe.t,u_pattern_size_a:Yt.displaySize,u_pattern_size_b:Kt.displaySize,u_scale_a:Xe.fromScale,u_scale_b:Xe.toScale,u_tile_units_to_pixels:1/In(Tt,1,ot.transform.tileZoom),u_pixel_coord_upper:[De>>16,Be>>16],u_pixel_coord_lower:[65535&De,65535&Be]}}(Q,le,B,ee),{u_matrix:ue,u_opacity:w}),nc={fillExtrusion:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_lightpos:new a.aN(ue,w.u_lightpos),u_lightintensity:new a.aI(ue,w.u_lightintensity),u_lightcolor:new a.aN(ue,w.u_lightcolor),u_vertical_gradient:new a.aI(ue,w.u_vertical_gradient),u_opacity:new a.aI(ue,w.u_opacity)}),fillExtrusionPattern:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_lightpos:new a.aN(ue,w.u_lightpos),u_lightintensity:new a.aI(ue,w.u_lightintensity),u_lightcolor:new a.aN(ue,w.u_lightcolor),u_vertical_gradient:new a.aI(ue,w.u_vertical_gradient),u_height_factor:new a.aI(ue,w.u_height_factor),u_image:new a.aH(ue,w.u_image),u_texsize:new a.aO(ue,w.u_texsize),u_pixel_coord_upper:new a.aO(ue,w.u_pixel_coord_upper),u_pixel_coord_lower:new a.aO(ue,w.u_pixel_coord_lower),u_scale:new a.aN(ue,w.u_scale),u_fade:new a.aI(ue,w.u_fade),u_opacity:new a.aI(ue,w.u_opacity)}),fill:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix)}),fillPattern:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_image:new a.aH(ue,w.u_image),u_texsize:new a.aO(ue,w.u_texsize),u_pixel_coord_upper:new a.aO(ue,w.u_pixel_coord_upper),u_pixel_coord_lower:new a.aO(ue,w.u_pixel_coord_lower),u_scale:new a.aN(ue,w.u_scale),u_fade:new a.aI(ue,w.u_fade)}),fillOutline:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_world:new a.aO(ue,w.u_world)}),fillOutlinePattern:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_world:new a.aO(ue,w.u_world),u_image:new a.aH(ue,w.u_image),u_texsize:new a.aO(ue,w.u_texsize),u_pixel_coord_upper:new a.aO(ue,w.u_pixel_coord_upper),u_pixel_coord_lower:new a.aO(ue,w.u_pixel_coord_lower),u_scale:new a.aN(ue,w.u_scale),u_fade:new a.aI(ue,w.u_fade)}),circle:(ue,w)=>({u_camera_to_center_distance:new a.aI(ue,w.u_camera_to_center_distance),u_scale_with_map:new a.aH(ue,w.u_scale_with_map),u_pitch_with_map:new a.aH(ue,w.u_pitch_with_map),u_extrude_scale:new a.aO(ue,w.u_extrude_scale),u_device_pixel_ratio:new a.aI(ue,w.u_device_pixel_ratio),u_matrix:new a.aJ(ue,w.u_matrix)}),collisionBox:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_pixel_extrude_scale:new a.aO(ue,w.u_pixel_extrude_scale)}),collisionCircle:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_inv_matrix:new a.aJ(ue,w.u_inv_matrix),u_camera_to_center_distance:new a.aI(ue,w.u_camera_to_center_distance),u_viewport_size:new a.aO(ue,w.u_viewport_size)}),debug:(ue,w)=>({u_color:new a.aL(ue,w.u_color),u_matrix:new a.aJ(ue,w.u_matrix),u_overlay:new a.aH(ue,w.u_overlay),u_overlay_scale:new a.aI(ue,w.u_overlay_scale)}),clippingMask:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix)}),heatmap:(ue,w)=>({u_extrude_scale:new a.aI(ue,w.u_extrude_scale),u_intensity:new a.aI(ue,w.u_intensity),u_matrix:new a.aJ(ue,w.u_matrix)}),heatmapTexture:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_world:new a.aO(ue,w.u_world),u_image:new a.aH(ue,w.u_image),u_color_ramp:new a.aH(ue,w.u_color_ramp),u_opacity:new a.aI(ue,w.u_opacity)}),hillshade:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_image:new a.aH(ue,w.u_image),u_latrange:new a.aO(ue,w.u_latrange),u_light:new a.aO(ue,w.u_light),u_shadow:new a.aL(ue,w.u_shadow),u_highlight:new a.aL(ue,w.u_highlight),u_accent:new a.aL(ue,w.u_accent)}),hillshadePrepare:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_image:new a.aH(ue,w.u_image),u_dimension:new a.aO(ue,w.u_dimension),u_zoom:new a.aI(ue,w.u_zoom),u_unpack:new a.aK(ue,w.u_unpack)}),line:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_ratio:new a.aI(ue,w.u_ratio),u_device_pixel_ratio:new a.aI(ue,w.u_device_pixel_ratio),u_units_to_pixels:new a.aO(ue,w.u_units_to_pixels)}),lineGradient:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_ratio:new a.aI(ue,w.u_ratio),u_device_pixel_ratio:new a.aI(ue,w.u_device_pixel_ratio),u_units_to_pixels:new a.aO(ue,w.u_units_to_pixels),u_image:new a.aH(ue,w.u_image),u_image_height:new a.aI(ue,w.u_image_height)}),linePattern:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_texsize:new a.aO(ue,w.u_texsize),u_ratio:new a.aI(ue,w.u_ratio),u_device_pixel_ratio:new a.aI(ue,w.u_device_pixel_ratio),u_image:new a.aH(ue,w.u_image),u_units_to_pixels:new a.aO(ue,w.u_units_to_pixels),u_scale:new a.aN(ue,w.u_scale),u_fade:new a.aI(ue,w.u_fade)}),lineSDF:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_ratio:new a.aI(ue,w.u_ratio),u_device_pixel_ratio:new a.aI(ue,w.u_device_pixel_ratio),u_units_to_pixels:new a.aO(ue,w.u_units_to_pixels),u_patternscale_a:new a.aO(ue,w.u_patternscale_a),u_patternscale_b:new a.aO(ue,w.u_patternscale_b),u_sdfgamma:new a.aI(ue,w.u_sdfgamma),u_image:new a.aH(ue,w.u_image),u_tex_y_a:new a.aI(ue,w.u_tex_y_a),u_tex_y_b:new a.aI(ue,w.u_tex_y_b),u_mix:new a.aI(ue,w.u_mix)}),raster:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_tl_parent:new a.aO(ue,w.u_tl_parent),u_scale_parent:new a.aI(ue,w.u_scale_parent),u_buffer_scale:new a.aI(ue,w.u_buffer_scale),u_fade_t:new a.aI(ue,w.u_fade_t),u_opacity:new a.aI(ue,w.u_opacity),u_image0:new a.aH(ue,w.u_image0),u_image1:new a.aH(ue,w.u_image1),u_brightness_low:new a.aI(ue,w.u_brightness_low),u_brightness_high:new a.aI(ue,w.u_brightness_high),u_saturation_factor:new a.aI(ue,w.u_saturation_factor),u_contrast_factor:new a.aI(ue,w.u_contrast_factor),u_spin_weights:new a.aN(ue,w.u_spin_weights)}),symbolIcon:(ue,w)=>({u_is_size_zoom_constant:new a.aH(ue,w.u_is_size_zoom_constant),u_is_size_feature_constant:new a.aH(ue,w.u_is_size_feature_constant),u_size_t:new a.aI(ue,w.u_size_t),u_size:new a.aI(ue,w.u_size),u_camera_to_center_distance:new a.aI(ue,w.u_camera_to_center_distance),u_pitch:new a.aI(ue,w.u_pitch),u_rotate_symbol:new a.aH(ue,w.u_rotate_symbol),u_aspect_ratio:new a.aI(ue,w.u_aspect_ratio),u_fade_change:new a.aI(ue,w.u_fade_change),u_matrix:new a.aJ(ue,w.u_matrix),u_label_plane_matrix:new a.aJ(ue,w.u_label_plane_matrix),u_coord_matrix:new a.aJ(ue,w.u_coord_matrix),u_is_text:new a.aH(ue,w.u_is_text),u_pitch_with_map:new a.aH(ue,w.u_pitch_with_map),u_is_along_line:new a.aH(ue,w.u_is_along_line),u_is_variable_anchor:new a.aH(ue,w.u_is_variable_anchor),u_texsize:new a.aO(ue,w.u_texsize),u_texture:new a.aH(ue,w.u_texture),u_translation:new a.aO(ue,w.u_translation),u_pitched_scale:new a.aI(ue,w.u_pitched_scale)}),symbolSDF:(ue,w)=>({u_is_size_zoom_constant:new a.aH(ue,w.u_is_size_zoom_constant),u_is_size_feature_constant:new a.aH(ue,w.u_is_size_feature_constant),u_size_t:new a.aI(ue,w.u_size_t),u_size:new a.aI(ue,w.u_size),u_camera_to_center_distance:new a.aI(ue,w.u_camera_to_center_distance),u_pitch:new a.aI(ue,w.u_pitch),u_rotate_symbol:new a.aH(ue,w.u_rotate_symbol),u_aspect_ratio:new a.aI(ue,w.u_aspect_ratio),u_fade_change:new a.aI(ue,w.u_fade_change),u_matrix:new a.aJ(ue,w.u_matrix),u_label_plane_matrix:new a.aJ(ue,w.u_label_plane_matrix),u_coord_matrix:new a.aJ(ue,w.u_coord_matrix),u_is_text:new a.aH(ue,w.u_is_text),u_pitch_with_map:new a.aH(ue,w.u_pitch_with_map),u_is_along_line:new a.aH(ue,w.u_is_along_line),u_is_variable_anchor:new a.aH(ue,w.u_is_variable_anchor),u_texsize:new a.aO(ue,w.u_texsize),u_texture:new a.aH(ue,w.u_texture),u_gamma_scale:new a.aI(ue,w.u_gamma_scale),u_device_pixel_ratio:new a.aI(ue,w.u_device_pixel_ratio),u_is_halo:new a.aH(ue,w.u_is_halo),u_translation:new a.aO(ue,w.u_translation),u_pitched_scale:new a.aI(ue,w.u_pitched_scale)}),symbolTextAndIcon:(ue,w)=>({u_is_size_zoom_constant:new a.aH(ue,w.u_is_size_zoom_constant),u_is_size_feature_constant:new a.aH(ue,w.u_is_size_feature_constant),u_size_t:new a.aI(ue,w.u_size_t),u_size:new a.aI(ue,w.u_size),u_camera_to_center_distance:new a.aI(ue,w.u_camera_to_center_distance),u_pitch:new a.aI(ue,w.u_pitch),u_rotate_symbol:new a.aH(ue,w.u_rotate_symbol),u_aspect_ratio:new a.aI(ue,w.u_aspect_ratio),u_fade_change:new a.aI(ue,w.u_fade_change),u_matrix:new a.aJ(ue,w.u_matrix),u_label_plane_matrix:new a.aJ(ue,w.u_label_plane_matrix),u_coord_matrix:new a.aJ(ue,w.u_coord_matrix),u_is_text:new a.aH(ue,w.u_is_text),u_pitch_with_map:new a.aH(ue,w.u_pitch_with_map),u_is_along_line:new a.aH(ue,w.u_is_along_line),u_is_variable_anchor:new a.aH(ue,w.u_is_variable_anchor),u_texsize:new a.aO(ue,w.u_texsize),u_texsize_icon:new a.aO(ue,w.u_texsize_icon),u_texture:new a.aH(ue,w.u_texture),u_texture_icon:new a.aH(ue,w.u_texture_icon),u_gamma_scale:new a.aI(ue,w.u_gamma_scale),u_device_pixel_ratio:new a.aI(ue,w.u_device_pixel_ratio),u_is_halo:new a.aH(ue,w.u_is_halo),u_translation:new a.aO(ue,w.u_translation),u_pitched_scale:new a.aI(ue,w.u_pitched_scale)}),background:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_opacity:new a.aI(ue,w.u_opacity),u_color:new a.aL(ue,w.u_color)}),backgroundPattern:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_opacity:new a.aI(ue,w.u_opacity),u_image:new a.aH(ue,w.u_image),u_pattern_tl_a:new a.aO(ue,w.u_pattern_tl_a),u_pattern_br_a:new a.aO(ue,w.u_pattern_br_a),u_pattern_tl_b:new a.aO(ue,w.u_pattern_tl_b),u_pattern_br_b:new a.aO(ue,w.u_pattern_br_b),u_texsize:new a.aO(ue,w.u_texsize),u_mix:new a.aI(ue,w.u_mix),u_pattern_size_a:new a.aO(ue,w.u_pattern_size_a),u_pattern_size_b:new a.aO(ue,w.u_pattern_size_b),u_scale_a:new a.aI(ue,w.u_scale_a),u_scale_b:new a.aI(ue,w.u_scale_b),u_pixel_coord_upper:new a.aO(ue,w.u_pixel_coord_upper),u_pixel_coord_lower:new a.aO(ue,w.u_pixel_coord_lower),u_tile_units_to_pixels:new a.aI(ue,w.u_tile_units_to_pixels)}),terrain:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_texture:new a.aH(ue,w.u_texture),u_ele_delta:new a.aI(ue,w.u_ele_delta),u_fog_matrix:new a.aJ(ue,w.u_fog_matrix),u_fog_color:new a.aL(ue,w.u_fog_color),u_fog_ground_blend:new a.aI(ue,w.u_fog_ground_blend),u_fog_ground_blend_opacity:new a.aI(ue,w.u_fog_ground_blend_opacity),u_horizon_color:new a.aL(ue,w.u_horizon_color),u_horizon_fog_blend:new a.aI(ue,w.u_horizon_fog_blend)}),terrainDepth:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_ele_delta:new a.aI(ue,w.u_ele_delta)}),terrainCoords:(ue,w)=>({u_matrix:new a.aJ(ue,w.u_matrix),u_texture:new a.aH(ue,w.u_texture),u_terrain_coords_id:new a.aI(ue,w.u_terrain_coords_id),u_ele_delta:new a.aI(ue,w.u_ele_delta)}),sky:(ue,w)=>({u_sky_color:new a.aL(ue,w.u_sky_color),u_horizon_color:new a.aL(ue,w.u_horizon_color),u_horizon:new a.aI(ue,w.u_horizon),u_sky_horizon_blend:new a.aI(ue,w.u_sky_horizon_blend)})};class bs{constructor(w,B,Q){this.context=w;let ee=w.gl;this.buffer=ee.createBuffer(),this.dynamicDraw=!!Q,this.context.unbindVAO(),w.bindElementBuffer.set(this.buffer),ee.bufferData(ee.ELEMENT_ARRAY_BUFFER,B.arrayBuffer,this.dynamicDraw?ee.DYNAMIC_DRAW:ee.STATIC_DRAW),this.dynamicDraw||delete B.arrayBuffer}bind(){this.context.bindElementBuffer.set(this.buffer)}updateData(w){let B=this.context.gl;if(!this.dynamicDraw)throw new Error("Attempted to update data while not in dynamic mode.");this.context.unbindVAO(),this.bind(),B.bufferSubData(B.ELEMENT_ARRAY_BUFFER,0,w.arrayBuffer)}destroy(){this.buffer&&(this.context.gl.deleteBuffer(this.buffer),delete this.buffer)}}let Rn={Int8:"BYTE",Uint8:"UNSIGNED_BYTE",Int16:"SHORT",Uint16:"UNSIGNED_SHORT",Int32:"INT",Uint32:"UNSIGNED_INT",Float32:"FLOAT"};class _a{constructor(w,B,Q,ee){this.length=B.length,this.attributes=Q,this.itemSize=B.bytesPerElement,this.dynamicDraw=ee,this.context=w;let le=w.gl;this.buffer=le.createBuffer(),w.bindVertexBuffer.set(this.buffer),le.bufferData(le.ARRAY_BUFFER,B.arrayBuffer,this.dynamicDraw?le.DYNAMIC_DRAW:le.STATIC_DRAW),this.dynamicDraw||delete B.arrayBuffer}bind(){this.context.bindVertexBuffer.set(this.buffer)}updateData(w){if(w.length!==this.length)throw new Error(`Length of new data is ${w.length}, which doesn't match current length of ${this.length}`);let B=this.context.gl;this.bind(),B.bufferSubData(B.ARRAY_BUFFER,0,w.arrayBuffer)}enableAttributes(w,B){for(let Q=0;Q0){let Ht=a.H();a.aQ(Ht,We.placementInvProjMatrix,ue.transform.glCoordMatrix),a.aQ(Ht,Ht,We.placementViewportMatrix),ot.push({circleArray:Ft,circleOffset:Yt,transform:et.posMatrix,invTransform:Ht,coord:et}),Tt+=Ft.length/4,Yt=Tt}it&&Xe.draw(le,qe.LINES,Po.disabled,Yo.disabled,ue.colorModeForRenderPass(),Pa.disabled,{u_matrix:et.posMatrix,u_pixel_extrude_scale:[1/(Kt=ue.transform).width,1/Kt.height]},ue.style.map.terrain&&ue.style.map.terrain.getTerrainData(et),B.id,it.layoutVertexBuffer,it.indexBuffer,it.segments,null,ue.transform.zoom,null,null,it.collisionVertexBuffer)}var Kt;if(!ee||!ot.length)return;let xr=ue.useProgram("collisionCircle"),Ir=new a.aR;Ir.resize(4*Tt),Ir._trim();let ve=0;for(let Be of ot)for(let et=0;et=0&&(Be[We.associatedIconIndex]={shiftedAnchor:Kn,angle:Ta})}else pi(We.numGlyphs,be)}if(Tt){De.clear();let et=ue.icon.placedSymbolArray;for(let We=0;Weue.style.map.terrain.getElevation(Wr,nt,jt):null,kt=B.layout.get("text-rotation-alignment")==="map";je(Pi,Wr.posMatrix,ue,ee,Ul,au,Be,Tt,kt,be,Wr.toUnwrapped(),ve.width,ve.height,Js,Ye)}let Tl=Wr.posMatrix,Al=ee&&dr||dc,X=et||Al?bl:Ul,se=Lu,Te=Cn&&B.paint.get(ee?"text-halo-width":"icon-halo-width").constantOr(1)!==0,Ne;Ne=Cn?Pi.iconsInText?ls(Kn.kind,$a,We,Be,et,Al,ue,Tl,X,se,Js,Qa,Ts,Or):Io(Kn.kind,$a,We,Be,et,Al,ue,Tl,X,se,Js,ee,Qa,!0,Or):zs(Kn.kind,$a,We,Be,et,Al,ue,Tl,X,se,Js,ee,Qa,Or);let He={program:fa,buffers:cn,uniformValues:Ne,atlasTexture:mo,atlasTextureIcon:wo,atlasInterpolation:Bo,atlasInterpolationIcon:Ps,isSDF:Cn,hasHalo:Te};if(Ft&&Pi.canOverlap){Ht=!0;let Ye=cn.segments.get();for(let kt of Ye)Sr.push({segments:new a.a0([kt]),sortKey:kt.sortKey,state:He,terrainData:Co})}else Sr.push({segments:cn.segments,sortKey:0,state:He,terrainData:Co})}Ht&&Sr.sort((Wr,ni)=>Wr.sortKey-ni.sortKey);for(let Wr of Sr){let ni=Wr.state;if(xr.activeTexture.set(Ir.TEXTURE0),ni.atlasTexture.bind(ni.atlasInterpolation,Ir.CLAMP_TO_EDGE),ni.atlasTextureIcon&&(xr.activeTexture.set(Ir.TEXTURE1),ni.atlasTextureIcon&&ni.atlasTextureIcon.bind(ni.atlasInterpolationIcon,Ir.CLAMP_TO_EDGE)),ni.isSDF){let Pi=ni.uniformValues;ni.hasHalo&&(Pi.u_is_halo=1,Qf(ni.buffers,Wr.segments,B,ue,ni.program,tr,Yt,Kt,Pi,Wr.terrainData)),Pi.u_is_halo=0}Qf(ni.buffers,Wr.segments,B,ue,ni.program,tr,Yt,Kt,ni.uniformValues,Wr.terrainData)}}function Qf(ue,w,B,Q,ee,le,qe,Xe,ot,Tt){let Yt=Q.context;ee.draw(Yt,Yt.gl.TRIANGLES,le,qe,Xe,Pa.disabled,ot,Tt,B.id,ue.layoutVertexBuffer,ue.indexBuffer,w,B.paint,Q.transform.zoom,ue.programConfigurations.get(B.id),ue.dynamicLayoutVertexBuffer,ue.opacityVertexBuffer)}function _f(ue,w,B,Q){let ee=ue.context,le=ee.gl,qe=Yo.disabled,Xe=new qs([le.ONE,le.ONE],a.aM.transparent,[!0,!0,!0,!0]),ot=w.getBucket(B);if(!ot)return;let Tt=Q.key,Yt=B.heatmapFbos.get(Tt);Yt||(Yt=eh(ee,w.tileSize,w.tileSize),B.heatmapFbos.set(Tt,Yt)),ee.bindFramebuffer.set(Yt.framebuffer),ee.viewport.set([0,0,w.tileSize,w.tileSize]),ee.clear({color:a.aM.transparent});let Kt=ot.programConfigurations.get(B.id),xr=ue.useProgram("heatmap",Kt),Ir=ue.style.map.terrain.getTerrainData(Q);xr.draw(ee,le.TRIANGLES,Po.disabled,qe,Xe,Pa.disabled,ko(Q.posMatrix,w,ue.transform.zoom,B.paint.get("heatmap-intensity")),Ir,B.id,ot.layoutVertexBuffer,ot.indexBuffer,ot.segments,B.paint,ue.transform.zoom,Kt)}function Yc(ue,w,B){let Q=ue.context,ee=Q.gl;Q.setColorMode(ue.colorModeForRenderPass());let le=th(Q,w),qe=B.key,Xe=w.heatmapFbos.get(qe);Xe&&(Q.activeTexture.set(ee.TEXTURE0),ee.bindTexture(ee.TEXTURE_2D,Xe.colorAttachment.get()),Q.activeTexture.set(ee.TEXTURE1),le.bind(ee.LINEAR,ee.CLAMP_TO_EDGE),ue.useProgram("heatmapTexture").draw(Q,ee.TRIANGLES,Po.disabled,Yo.disabled,ue.colorModeForRenderPass(),Pa.disabled,Ds(ue,w,0,1),null,w.id,ue.rasterBoundsBuffer,ue.quadTriangleIndexBuffer,ue.rasterBoundsSegments,w.paint,ue.transform.zoom),Xe.destroy(),w.heatmapFbos.delete(qe))}function eh(ue,w,B){var Q,ee;let le=ue.gl,qe=le.createTexture();le.bindTexture(le.TEXTURE_2D,qe),le.texParameteri(le.TEXTURE_2D,le.TEXTURE_WRAP_S,le.CLAMP_TO_EDGE),le.texParameteri(le.TEXTURE_2D,le.TEXTURE_WRAP_T,le.CLAMP_TO_EDGE),le.texParameteri(le.TEXTURE_2D,le.TEXTURE_MIN_FILTER,le.LINEAR),le.texParameteri(le.TEXTURE_2D,le.TEXTURE_MAG_FILTER,le.LINEAR);let Xe=(Q=ue.HALF_FLOAT)!==null&&Q!==void 0?Q:le.UNSIGNED_BYTE,ot=(ee=ue.RGBA16F)!==null&&ee!==void 0?ee:le.RGBA;le.texImage2D(le.TEXTURE_2D,0,ot,w,B,0,le.RGBA,Xe,null);let Tt=ue.createFramebuffer(w,B,!1,!1);return Tt.colorAttachment.set(qe),Tt}function th(ue,w){return w.colorRampTexture||(w.colorRampTexture=new g(ue,w.colorRamp,ue.gl.RGBA)),w.colorRampTexture}function ju(ue,w,B,Q,ee){if(!B||!Q||!Q.imageAtlas)return;let le=Q.imageAtlas.patternPositions,qe=le[B.to.toString()],Xe=le[B.from.toString()];if(!qe&&Xe&&(qe=Xe),!Xe&&qe&&(Xe=qe),!qe||!Xe){let ot=ee.getPaintProperty(w);qe=le[ot],Xe=le[ot]}qe&&Xe&&ue.setConstantPatternPositions(qe,Xe)}function Hf(ue,w,B,Q,ee,le,qe){let Xe=ue.context.gl,ot="fill-pattern",Tt=B.paint.get(ot),Yt=Tt&&Tt.constantOr(1),Kt=B.getCrossfadeParameters(),xr,Ir,ve,be,De;qe?(Ir=Yt&&!B.getPaintProperty("fill-outline-color")?"fillOutlinePattern":"fillOutline",xr=Xe.LINES):(Ir=Yt?"fillPattern":"fill",xr=Xe.TRIANGLES);let Be=Tt.constantOr(null);for(let et of Q){let We=w.getTile(et);if(Yt&&!We.patternsLoaded())continue;let it=We.getBucket(B);if(!it)continue;let Ft=it.programConfigurations.get(B.id),Ht=ue.useProgram(Ir,Ft),tr=ue.style.map.terrain&&ue.style.map.terrain.getTerrainData(et);Yt&&(ue.context.activeTexture.set(Xe.TEXTURE0),We.imageAtlasTexture.bind(Xe.LINEAR,Xe.CLAMP_TO_EDGE),Ft.updatePaintBuffers(Kt)),ju(Ft,ot,Be,We,B);let dr=tr?et:null,Sr=ue.translatePosMatrix(dr?dr.posMatrix:et.posMatrix,We,B.paint.get("fill-translate"),B.paint.get("fill-translate-anchor"));if(qe){be=it.indexBuffer2,De=it.segments2;let Or=[Xe.drawingBufferWidth,Xe.drawingBufferHeight];ve=Ir==="fillOutlinePattern"&&Yt?Ma(Sr,ue,Kt,We,Or):Jn(Sr,Or)}else be=it.indexBuffer,De=it.segments,ve=Yt?ya(Sr,ue,Kt,We):_n(Sr);Ht.draw(ue.context,xr,ee,ue.stencilModeForClipping(et),le,Pa.disabled,ve,tr,B.id,it.layoutVertexBuffer,be,De,B.paint,ue.transform.zoom,Ft)}}function cc(ue,w,B,Q,ee,le,qe){let Xe=ue.context,ot=Xe.gl,Tt="fill-extrusion-pattern",Yt=B.paint.get(Tt),Kt=Yt.constantOr(1),xr=B.getCrossfadeParameters(),Ir=B.paint.get("fill-extrusion-opacity"),ve=Yt.constantOr(null);for(let be of Q){let De=w.getTile(be),Be=De.getBucket(B);if(!Be)continue;let et=ue.style.map.terrain&&ue.style.map.terrain.getTerrainData(be),We=Be.programConfigurations.get(B.id),it=ue.useProgram(Kt?"fillExtrusionPattern":"fillExtrusion",We);Kt&&(ue.context.activeTexture.set(ot.TEXTURE0),De.imageAtlasTexture.bind(ot.LINEAR,ot.CLAMP_TO_EDGE),We.updatePaintBuffers(xr)),ju(We,Tt,ve,De,B);let Ft=ue.translatePosMatrix(be.posMatrix,De,B.paint.get("fill-extrusion-translate"),B.paint.get("fill-extrusion-translate-anchor")),Ht=B.paint.get("fill-extrusion-vertical-gradient"),tr=Kt?Li(Ft,ue,Ht,Ir,be,xr,De):Mn(Ft,ue,Ht,Ir);it.draw(Xe,Xe.gl.TRIANGLES,ee,le,qe,Pa.backCCW,tr,et,B.id,Be.layoutVertexBuffer,Be.indexBuffer,Be.segments,B.paint,ue.transform.zoom,We,ue.style.map.terrain&&Be.centroidVertexBuffer)}}function of(ue,w,B,Q,ee,le,qe){let Xe=ue.context,ot=Xe.gl,Tt=B.fbo;if(!Tt)return;let Yt=ue.useProgram("hillshade"),Kt=ue.style.map.terrain&&ue.style.map.terrain.getTerrainData(w);Xe.activeTexture.set(ot.TEXTURE0),ot.bindTexture(ot.TEXTURE_2D,Tt.colorAttachment.get()),Yt.draw(Xe,ot.TRIANGLES,ee,le,qe,Pa.disabled,((xr,Ir,ve,be)=>{let De=ve.paint.get("hillshade-shadow-color"),Be=ve.paint.get("hillshade-highlight-color"),et=ve.paint.get("hillshade-accent-color"),We=ve.paint.get("hillshade-illumination-direction")*(Math.PI/180);ve.paint.get("hillshade-illumination-anchor")==="viewport"&&(We-=xr.transform.angle);let it=!xr.options.moving;return{u_matrix:be?be.posMatrix:xr.transform.calculatePosMatrix(Ir.tileID.toUnwrapped(),it),u_image:0,u_latrange:Fs(0,Ir.tileID),u_light:[ve.paint.get("hillshade-exaggeration"),We],u_shadow:De,u_highlight:Be,u_accent:et}})(ue,B,Q,Kt?w:null),Kt,Q.id,ue.rasterBoundsBuffer,ue.quadTriangleIndexBuffer,ue.rasterBoundsSegments)}function Nl(ue,w,B,Q,ee,le){let qe=ue.context,Xe=qe.gl,ot=w.dem;if(ot&&ot.data){let Tt=ot.dim,Yt=ot.stride,Kt=ot.getPixels();if(qe.activeTexture.set(Xe.TEXTURE1),qe.pixelStoreUnpackPremultiplyAlpha.set(!1),w.demTexture=w.demTexture||ue.getTileTexture(Yt),w.demTexture){let Ir=w.demTexture;Ir.update(Kt,{premultiply:!1}),Ir.bind(Xe.NEAREST,Xe.CLAMP_TO_EDGE)}else w.demTexture=new g(qe,Kt,Xe.RGBA,{premultiply:!1}),w.demTexture.bind(Xe.NEAREST,Xe.CLAMP_TO_EDGE);qe.activeTexture.set(Xe.TEXTURE0);let xr=w.fbo;if(!xr){let Ir=new g(qe,{width:Tt,height:Tt,data:null},Xe.RGBA);Ir.bind(Xe.LINEAR,Xe.CLAMP_TO_EDGE),xr=w.fbo=qe.createFramebuffer(Tt,Tt,!0,!1),xr.colorAttachment.set(Ir.texture)}qe.bindFramebuffer.set(xr.framebuffer),qe.viewport.set([0,0,Tt,Tt]),ue.useProgram("hillshadePrepare").draw(qe,Xe.TRIANGLES,Q,ee,le,Pa.disabled,((Ir,ve)=>{let be=ve.stride,De=a.H();return a.aP(De,0,a.X,-a.X,0,0,1),a.J(De,De,[0,-a.X,0]),{u_matrix:De,u_image:1,u_dimension:[be,be],u_zoom:Ir.overscaledZ,u_unpack:ve.getUnpackVector()}})(w.tileID,ot),null,B.id,ue.rasterBoundsBuffer,ue.quadTriangleIndexBuffer,ue.rasterBoundsSegments),w.needsHillshadePrepare=!1}}function Kc(ue,w,B,Q,ee,le){let qe=Q.paint.get("raster-fade-duration");if(!le&&qe>0){let Xe=u.now(),ot=(Xe-ue.timeAdded)/qe,Tt=w?(Xe-w.timeAdded)/qe:-1,Yt=B.getSource(),Kt=ee.coveringZoomLevel({tileSize:Yt.tileSize,roundZoom:Yt.roundZoom}),xr=!w||Math.abs(w.tileID.overscaledZ-Kt)>Math.abs(ue.tileID.overscaledZ-Kt),Ir=xr&&ue.refreshedUponExpiration?1:a.ac(xr?ot:1-Tt,0,1);return ue.refreshedUponExpiration&&ot>=1&&(ue.refreshedUponExpiration=!1),w?{opacity:1,mix:1-Ir}:{opacity:Ir,mix:0}}return{opacity:1,mix:0}}let Rc=new a.aM(1,0,0,1),gs=new a.aM(0,1,0,1),jf=new a.aM(0,0,1,1),Gh=new a.aM(1,0,1,1),rh=new a.aM(0,1,1,1);function sf(ue,w,B,Q){Mu(ue,0,w+B/2,ue.transform.width,B,Q)}function Th(ue,w,B,Q){Mu(ue,w-B/2,0,B,ue.transform.height,Q)}function Mu(ue,w,B,Q,ee,le){let qe=ue.context,Xe=qe.gl;Xe.enable(Xe.SCISSOR_TEST),Xe.scissor(w*ue.pixelRatio,B*ue.pixelRatio,Q*ue.pixelRatio,ee*ue.pixelRatio),qe.clear({color:le}),Xe.disable(Xe.SCISSOR_TEST)}function ih(ue,w,B){let Q=ue.context,ee=Q.gl,le=B.posMatrix,qe=ue.useProgram("debug"),Xe=Po.disabled,ot=Yo.disabled,Tt=ue.colorModeForRenderPass(),Yt="$debug",Kt=ue.style.map.terrain&&ue.style.map.terrain.getTerrainData(B);Q.activeTexture.set(ee.TEXTURE0);let xr=w.getTileByID(B.key).latestRawTileData,Ir=Math.floor((xr&&xr.byteLength||0)/1024),ve=w.getTile(B).tileSize,be=512/Math.min(ve,512)*(B.overscaledZ/ue.transform.zoom)*.5,De=B.canonical.toString();B.overscaledZ!==B.canonical.z&&(De+=` => ${B.overscaledZ}`),function(Be,et){Be.initDebugOverlayCanvas();let We=Be.debugOverlayCanvas,it=Be.context.gl,Ft=Be.debugOverlayCanvas.getContext("2d");Ft.clearRect(0,0,We.width,We.height),Ft.shadowColor="white",Ft.shadowBlur=2,Ft.lineWidth=1.5,Ft.strokeStyle="white",Ft.textBaseline="top",Ft.font="bold 36px Open Sans, sans-serif",Ft.fillText(et,5,5),Ft.strokeText(et,5,5),Be.debugOverlayTexture.update(We),Be.debugOverlayTexture.bind(it.LINEAR,it.CLAMP_TO_EDGE)}(ue,`${De} ${Ir}kB`),qe.draw(Q,ee.TRIANGLES,Xe,ot,qs.alphaBlended,Pa.disabled,po(le,a.aM.transparent,be),null,Yt,ue.debugBuffer,ue.quadTriangleIndexBuffer,ue.debugSegments),qe.draw(Q,ee.LINE_STRIP,Xe,ot,Tt,Pa.disabled,po(le,a.aM.red),Kt,Yt,ue.debugBuffer,ue.tileBorderIndexBuffer,ue.debugSegments)}function js(ue,w,B){let Q=ue.context,ee=Q.gl,le=ue.colorModeForRenderPass(),qe=new Po(ee.LEQUAL,Po.ReadWrite,ue.depthRangeFor3D),Xe=ue.useProgram("terrain"),ot=w.getTerrainMesh();Q.bindFramebuffer.set(null),Q.viewport.set([0,0,ue.width,ue.height]);for(let Tt of B){let Yt=ue.renderToTexture.getTexture(Tt),Kt=w.getTerrainData(Tt.tileID);Q.activeTexture.set(ee.TEXTURE0),ee.bindTexture(ee.TEXTURE_2D,Yt.texture);let xr=ue.transform.calculatePosMatrix(Tt.tileID.toUnwrapped()),Ir=w.getMeshFrameDelta(ue.transform.zoom),ve=ue.transform.calculateFogMatrix(Tt.tileID.toUnwrapped()),be=Jr(xr,Ir,ve,ue.style.sky,ue.transform.pitch);Xe.draw(Q,ee.TRIANGLES,qe,Yo.disabled,le,Pa.backCCW,be,Kt,"terrain",ot.vertexBuffer,ot.indexBuffer,ot.segments)}}class Eu{constructor(w,B,Q){this.vertexBuffer=w,this.indexBuffer=B,this.segments=Q}destroy(){this.vertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.vertexBuffer=null,this.indexBuffer=null,this.segments=null}}class Dc{constructor(w,B){this.context=new ad(w),this.transform=B,this._tileTextures={},this.terrainFacilitator={dirty:!0,matrix:a.an(new Float64Array(16)),renderTime:0},this.setup(),this.numSublayers=mt.maxUnderzooming+mt.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Wo}resize(w,B,Q){if(this.width=Math.floor(w*Q),this.height=Math.floor(B*Q),this.pixelRatio=Q,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(let ee of this.style._order)this.style._layers[ee].resize()}setup(){let w=this.context,B=new a.aX;B.emplaceBack(0,0),B.emplaceBack(a.X,0),B.emplaceBack(0,a.X),B.emplaceBack(a.X,a.X),this.tileExtentBuffer=w.createVertexBuffer(B,vo.members),this.tileExtentSegments=a.a0.simpleSegment(0,0,4,2);let Q=new a.aX;Q.emplaceBack(0,0),Q.emplaceBack(a.X,0),Q.emplaceBack(0,a.X),Q.emplaceBack(a.X,a.X),this.debugBuffer=w.createVertexBuffer(Q,vo.members),this.debugSegments=a.a0.simpleSegment(0,0,4,5);let ee=new a.$;ee.emplaceBack(0,0,0,0),ee.emplaceBack(a.X,0,a.X,0),ee.emplaceBack(0,a.X,0,a.X),ee.emplaceBack(a.X,a.X,a.X,a.X),this.rasterBoundsBuffer=w.createVertexBuffer(ee,lt.members),this.rasterBoundsSegments=a.a0.simpleSegment(0,0,4,2);let le=new a.aX;le.emplaceBack(0,0),le.emplaceBack(1,0),le.emplaceBack(0,1),le.emplaceBack(1,1),this.viewportBuffer=w.createVertexBuffer(le,vo.members),this.viewportSegments=a.a0.simpleSegment(0,0,4,2);let qe=new a.aZ;qe.emplaceBack(0),qe.emplaceBack(1),qe.emplaceBack(3),qe.emplaceBack(2),qe.emplaceBack(0),this.tileBorderIndexBuffer=w.createIndexBuffer(qe);let Xe=new a.aY;Xe.emplaceBack(0,1,2),Xe.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=w.createIndexBuffer(Xe);let ot=this.context.gl;this.stencilClearMode=new Yo({func:ot.ALWAYS,mask:0},0,255,ot.ZERO,ot.ZERO,ot.ZERO)}clearStencil(){let w=this.context,B=w.gl;this.nextStencilID=1,this.currentStencilSource=void 0;let Q=a.H();a.aP(Q,0,this.width,this.height,0,0,1),a.K(Q,Q,[B.drawingBufferWidth,B.drawingBufferHeight,0]),this.useProgram("clippingMask").draw(w,B.TRIANGLES,Po.disabled,this.stencilClearMode,qs.disabled,Pa.disabled,Lo(Q),null,"$clipping",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)}_renderTileClippingMasks(w,B){if(this.currentStencilSource===w.source||!w.isTileClipped()||!B||!B.length)return;this.currentStencilSource=w.source;let Q=this.context,ee=Q.gl;this.nextStencilID+B.length>256&&this.clearStencil(),Q.setColorMode(qs.disabled),Q.setDepthMode(Po.disabled);let le=this.useProgram("clippingMask");this._tileClippingMaskIDs={};for(let qe of B){let Xe=this._tileClippingMaskIDs[qe.key]=this.nextStencilID++,ot=this.style.map.terrain&&this.style.map.terrain.getTerrainData(qe);le.draw(Q,ee.TRIANGLES,Po.disabled,new Yo({func:ee.ALWAYS,mask:0},Xe,255,ee.KEEP,ee.KEEP,ee.REPLACE),qs.disabled,Pa.disabled,Lo(qe.posMatrix),ot,"$clipping",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}stencilModeFor3D(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();let w=this.nextStencilID++,B=this.context.gl;return new Yo({func:B.NOTEQUAL,mask:255},w,255,B.KEEP,B.KEEP,B.REPLACE)}stencilModeForClipping(w){let B=this.context.gl;return new Yo({func:B.EQUAL,mask:255},this._tileClippingMaskIDs[w.key],0,B.KEEP,B.KEEP,B.REPLACE)}stencilConfigForOverlap(w){let B=this.context.gl,Q=w.sort((qe,Xe)=>Xe.overscaledZ-qe.overscaledZ),ee=Q[Q.length-1].overscaledZ,le=Q[0].overscaledZ-ee+1;if(le>1){this.currentStencilSource=void 0,this.nextStencilID+le>256&&this.clearStencil();let qe={};for(let Xe=0;Xe({u_sky_color:Be.properties.get("sky-color"),u_horizon_color:Be.properties.get("horizon-color"),u_horizon:(et.height/2+et.getHorizon())*We,u_sky_horizon_blend:Be.properties.get("sky-horizon-blend")*et.height/2*We}))(Tt,ot.style.map.transform,ot.pixelRatio),Ir=new Po(Kt.LEQUAL,Po.ReadWrite,[0,1]),ve=Yo.disabled,be=ot.colorModeForRenderPass(),De=ot.useProgram("sky");if(!Tt.mesh){let Be=new a.aX;Be.emplaceBack(-1,-1),Be.emplaceBack(1,-1),Be.emplaceBack(1,1),Be.emplaceBack(-1,1);let et=new a.aY;et.emplaceBack(0,1,2),et.emplaceBack(0,2,3),Tt.mesh=new Eu(Yt.createVertexBuffer(Be,vo.members),Yt.createIndexBuffer(et),a.a0.simpleSegment(0,0,Be.length,et.length))}De.draw(Yt,Kt.TRIANGLES,Ir,ve,be,Pa.disabled,xr,void 0,"sky",Tt.mesh.vertexBuffer,Tt.mesh.indexBuffer,Tt.mesh.segments)}(this,this.style.sky),this._showOverdrawInspector=B.showOverdrawInspector,this.depthRangeFor3D=[0,1-(w._order.length+2)*this.numSublayers*this.depthEpsilon],!this.renderToTexture)for(this.renderPass="opaque",this.currentLayer=Q.length-1;this.currentLayer>=0;this.currentLayer--){let ot=this.style._layers[Q[this.currentLayer]],Tt=ee[ot.source],Yt=le[ot.source];this._renderTileClippingMasks(ot,Yt),this.renderLayer(this,Tt,ot,Yt)}for(this.renderPass="translucent",this.currentLayer=0;this.currentLayerDe.source&&!De.isHidden(Yt)?[Tt.sourceCaches[De.source]]:[]),Ir=xr.filter(De=>De.getSource().type==="vector"),ve=xr.filter(De=>De.getSource().type!=="vector"),be=De=>{(!Kt||Kt.getSource().maxzoombe(De)),Kt||ve.forEach(De=>be(De)),Kt}(this.style,this.transform.zoom);ot&&function(Tt,Yt,Kt){for(let xr=0;xr0),ee&&(a.b0(B,Q),this.terrainFacilitator.renderTime=Date.now(),this.terrainFacilitator.dirty=!1,function(le,qe){let Xe=le.context,ot=Xe.gl,Tt=qs.unblended,Yt=new Po(ot.LEQUAL,Po.ReadWrite,[0,1]),Kt=qe.getTerrainMesh(),xr=qe.sourceCache.getRenderableTiles(),Ir=le.useProgram("terrainDepth");Xe.bindFramebuffer.set(qe.getFramebuffer("depth").framebuffer),Xe.viewport.set([0,0,le.width/devicePixelRatio,le.height/devicePixelRatio]),Xe.clear({color:a.aM.transparent,depth:1});for(let ve of xr){let be=qe.getTerrainData(ve.tileID),De={u_matrix:le.transform.calculatePosMatrix(ve.tileID.toUnwrapped()),u_ele_delta:qe.getMeshFrameDelta(le.transform.zoom)};Ir.draw(Xe,ot.TRIANGLES,Yt,Yo.disabled,Tt,Pa.backCCW,De,be,"terrain",Kt.vertexBuffer,Kt.indexBuffer,Kt.segments)}Xe.bindFramebuffer.set(null),Xe.viewport.set([0,0,le.width,le.height])}(this,this.style.map.terrain),function(le,qe){let Xe=le.context,ot=Xe.gl,Tt=qs.unblended,Yt=new Po(ot.LEQUAL,Po.ReadWrite,[0,1]),Kt=qe.getTerrainMesh(),xr=qe.getCoordsTexture(),Ir=qe.sourceCache.getRenderableTiles(),ve=le.useProgram("terrainCoords");Xe.bindFramebuffer.set(qe.getFramebuffer("coords").framebuffer),Xe.viewport.set([0,0,le.width/devicePixelRatio,le.height/devicePixelRatio]),Xe.clear({color:a.aM.transparent,depth:1}),qe.coordsIndex=[];for(let be of Ir){let De=qe.getTerrainData(be.tileID);Xe.activeTexture.set(ot.TEXTURE0),ot.bindTexture(ot.TEXTURE_2D,xr.texture);let Be={u_matrix:le.transform.calculatePosMatrix(be.tileID.toUnwrapped()),u_terrain_coords_id:(255-qe.coordsIndex.length)/255,u_texture:0,u_ele_delta:qe.getMeshFrameDelta(le.transform.zoom)};ve.draw(Xe,ot.TRIANGLES,Yt,Yo.disabled,Tt,Pa.backCCW,Be,De,"terrain",Kt.vertexBuffer,Kt.indexBuffer,Kt.segments),qe.coordsIndex.push(be.tileID.key)}Xe.bindFramebuffer.set(null),Xe.viewport.set([0,0,le.width,le.height])}(this,this.style.map.terrain))}renderLayer(w,B,Q,ee){if(!Q.isHidden(this.transform.zoom)&&(Q.type==="background"||Q.type==="custom"||(ee||[]).length))switch(this.id=Q.id,Q.type){case"symbol":(function(le,qe,Xe,ot,Tt){if(le.renderPass!=="translucent")return;let Yt=Yo.disabled,Kt=le.colorModeForRenderPass();(Xe._unevaluatedLayout.hasValue("text-variable-anchor")||Xe._unevaluatedLayout.hasValue("text-variable-anchor-offset"))&&function(xr,Ir,ve,be,De,Be,et,We,it){let Ft=Ir.transform,Ht=yn(),tr=De==="map",dr=Be==="map";for(let Sr of xr){let Or=be.getTile(Sr),Wr=Or.getBucket(ve);if(!Wr||!Wr.text||!Wr.text.segments.get().length)continue;let ni=a.ag(Wr.textSizeData,Ft.zoom),Pi=In(Or,1,Ir.transform.zoom),cn=Br(Sr.posMatrix,dr,tr,Ir.transform,Pi),ln=ve.layout.get("icon-text-fit")!=="none"&&Wr.hasIconData();if(ni){let Cn=Math.pow(2,Ft.zoom-Or.tileID.overscaledZ),Kn=Ir.style.map.terrain?(fa,$a)=>Ir.style.map.terrain.getElevation(Sr,fa,$a):null,Ta=Ht.translatePosition(Ft,Or,et,We);yf(Wr,tr,dr,it,Ft,cn,Sr.posMatrix,Cn,ni,ln,Ht,Ta,Sr.toUnwrapped(),Kn)}}}(ot,le,Xe,qe,Xe.layout.get("text-rotation-alignment"),Xe.layout.get("text-pitch-alignment"),Xe.paint.get("text-translate"),Xe.paint.get("text-translate-anchor"),Tt),Xe.paint.get("icon-opacity").constantOr(1)!==0&&wh(le,qe,Xe,ot,!1,Xe.paint.get("icon-translate"),Xe.paint.get("icon-translate-anchor"),Xe.layout.get("icon-rotation-alignment"),Xe.layout.get("icon-pitch-alignment"),Xe.layout.get("icon-keep-upright"),Yt,Kt),Xe.paint.get("text-opacity").constantOr(1)!==0&&wh(le,qe,Xe,ot,!0,Xe.paint.get("text-translate"),Xe.paint.get("text-translate-anchor"),Xe.layout.get("text-rotation-alignment"),Xe.layout.get("text-pitch-alignment"),Xe.layout.get("text-keep-upright"),Yt,Kt),qe.map.showCollisionBoxes&&(Hu(le,qe,Xe,ot,!0),Hu(le,qe,Xe,ot,!1))})(w,B,Q,ee,this.style.placement.variableOffsets);break;case"circle":(function(le,qe,Xe,ot){if(le.renderPass!=="translucent")return;let Tt=Xe.paint.get("circle-opacity"),Yt=Xe.paint.get("circle-stroke-width"),Kt=Xe.paint.get("circle-stroke-opacity"),xr=!Xe.layout.get("circle-sort-key").isConstant();if(Tt.constantOr(1)===0&&(Yt.constantOr(1)===0||Kt.constantOr(1)===0))return;let Ir=le.context,ve=Ir.gl,be=le.depthModeForSublayer(0,Po.ReadOnly),De=Yo.disabled,Be=le.colorModeForRenderPass(),et=[];for(let We=0;WeWe.sortKey-it.sortKey);for(let We of et){let{programConfiguration:it,program:Ft,layoutVertexBuffer:Ht,indexBuffer:tr,uniformValues:dr,terrainData:Sr}=We.state;Ft.draw(Ir,ve.TRIANGLES,be,De,Be,Pa.disabled,dr,Sr,Xe.id,Ht,tr,We.segments,Xe.paint,le.transform.zoom,it)}})(w,B,Q,ee);break;case"heatmap":(function(le,qe,Xe,ot){if(Xe.paint.get("heatmap-opacity")===0)return;let Tt=le.context;if(le.style.map.terrain){for(let Yt of ot){let Kt=qe.getTile(Yt);qe.hasRenderableParent(Yt)||(le.renderPass==="offscreen"?_f(le,Kt,Xe,Yt):le.renderPass==="translucent"&&Yc(le,Xe,Yt))}Tt.viewport.set([0,0,le.width,le.height])}else le.renderPass==="offscreen"?function(Yt,Kt,xr,Ir){let ve=Yt.context,be=ve.gl,De=Yo.disabled,Be=new qs([be.ONE,be.ONE],a.aM.transparent,[!0,!0,!0,!0]);(function(et,We,it){let Ft=et.gl;et.activeTexture.set(Ft.TEXTURE1),et.viewport.set([0,0,We.width/4,We.height/4]);let Ht=it.heatmapFbos.get(a.aU);Ht?(Ft.bindTexture(Ft.TEXTURE_2D,Ht.colorAttachment.get()),et.bindFramebuffer.set(Ht.framebuffer)):(Ht=eh(et,We.width/4,We.height/4),it.heatmapFbos.set(a.aU,Ht))})(ve,Yt,xr),ve.clear({color:a.aM.transparent});for(let et=0;et20&&Yt.texParameterf(Yt.TEXTURE_2D,Tt.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,Tt.extTextureFilterAnisotropicMax);let Wr=le.style.map.terrain&&le.style.map.terrain.getTerrainData(et),ni=Wr?et:null,Pi=ni?ni.posMatrix:le.transform.calculatePosMatrix(et.toUnwrapped(),Be),cn=cl(Pi,Sr||[0,0],dr||1,tr,Xe);Kt instanceof Gt?xr.draw(Tt,Yt.TRIANGLES,We,Yo.disabled,Ir,Pa.disabled,cn,Wr,Xe.id,Kt.boundsBuffer,le.quadTriangleIndexBuffer,Kt.boundsSegments):xr.draw(Tt,Yt.TRIANGLES,We,ve[et.overscaledZ],Ir,Pa.disabled,cn,Wr,Xe.id,le.rasterBoundsBuffer,le.quadTriangleIndexBuffer,le.rasterBoundsSegments)}})(w,B,Q,ee);break;case"background":(function(le,qe,Xe,ot){let Tt=Xe.paint.get("background-color"),Yt=Xe.paint.get("background-opacity");if(Yt===0)return;let Kt=le.context,xr=Kt.gl,Ir=le.transform,ve=Ir.tileSize,be=Xe.paint.get("background-pattern");if(le.isPatternMissing(be))return;let De=!be&&Tt.a===1&&Yt===1&&le.opaquePassEnabledForLayer()?"opaque":"translucent";if(le.renderPass!==De)return;let Be=Yo.disabled,et=le.depthModeForSublayer(0,De==="opaque"?Po.ReadWrite:Po.ReadOnly),We=le.colorModeForRenderPass(),it=le.useProgram(be?"backgroundPattern":"background"),Ft=ot||Ir.coveringTiles({tileSize:ve,terrain:le.style.map.terrain});be&&(Kt.activeTexture.set(xr.TEXTURE0),le.imageManager.bind(le.context));let Ht=Xe.getCrossfadeParameters();for(let tr of Ft){let dr=ot?tr.posMatrix:le.transform.calculatePosMatrix(tr.toUnwrapped()),Sr=be?Su(dr,Yt,le,be,{tileID:tr,tileSize:ve},Ht):Zl(dr,Yt,Tt),Or=le.style.map.terrain&&le.style.map.terrain.getTerrainData(tr);it.draw(Kt,xr.TRIANGLES,et,Be,We,Pa.disabled,Sr,Or,Xe.id,le.tileExtentBuffer,le.quadTriangleIndexBuffer,le.tileExtentSegments)}})(w,0,Q,ee);break;case"custom":(function(le,qe,Xe){let ot=le.context,Tt=Xe.implementation;if(le.renderPass==="offscreen"){let Yt=Tt.prerender;Yt&&(le.setCustomLayerDefaults(),ot.setColorMode(le.colorModeForRenderPass()),Yt.call(Tt,ot.gl,le.transform.customLayerMatrix()),ot.setDirty(),le.setBaseState())}else if(le.renderPass==="translucent"){le.setCustomLayerDefaults(),ot.setColorMode(le.colorModeForRenderPass()),ot.setStencilMode(Yo.disabled);let Yt=Tt.renderingMode==="3d"?new Po(le.context.gl.LEQUAL,Po.ReadWrite,le.depthRangeFor3D):le.depthModeForSublayer(0,Po.ReadOnly);ot.setDepthMode(Yt),Tt.render(ot.gl,le.transform.customLayerMatrix(),{farZ:le.transform.farZ,nearZ:le.transform.nearZ,fov:le.transform._fov,modelViewProjectionMatrix:le.transform.modelViewProjectionMatrix,projectionMatrix:le.transform.projectionMatrix}),ot.setDirty(),le.setBaseState(),ot.bindFramebuffer.set(null)}})(w,0,Q)}}translatePosMatrix(w,B,Q,ee,le){if(!Q[0]&&!Q[1])return w;let qe=le?ee==="map"?this.transform.angle:0:ee==="viewport"?-this.transform.angle:0;if(qe){let Tt=Math.sin(qe),Yt=Math.cos(qe);Q=[Q[0]*Yt-Q[1]*Tt,Q[0]*Tt+Q[1]*Yt]}let Xe=[le?Q[0]:In(B,Q[0],this.transform.zoom),le?Q[1]:In(B,Q[1],this.transform.zoom),0],ot=new Float32Array(16);return a.J(ot,w,Xe),ot}saveTileTexture(w){let B=this._tileTextures[w.size[0]];B?B.push(w):this._tileTextures[w.size[0]]=[w]}getTileTexture(w){let B=this._tileTextures[w];return B&&B.length>0?B.pop():null}isPatternMissing(w){if(!w)return!1;if(!w.from||!w.to)return!0;let B=this.imageManager.getPattern(w.from.toString()),Q=this.imageManager.getPattern(w.to.toString());return!B||!Q}useProgram(w,B){this.cache=this.cache||{};let Q=w+(B?B.cacheKey:"")+(this._showOverdrawInspector?"/overdraw":"")+(this.style.map.terrain?"/terrain":"");return this.cache[Q]||(this.cache[Q]=new hn(this.context,jn[w],B,nc[w],this._showOverdrawInspector,this.style.map.terrain)),this.cache[Q]}setCustomLayerDefaults(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()}setBaseState(){let w=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(w.FUNC_ADD)}initDebugOverlayCanvas(){this.debugOverlayCanvas==null&&(this.debugOverlayCanvas=document.createElement("canvas"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512,this.debugOverlayTexture=new g(this.context,this.debugOverlayCanvas,this.context.gl.RGBA))}destroy(){this.debugOverlayTexture&&this.debugOverlayTexture.destroy()}overLimit(){let{drawingBufferWidth:w,drawingBufferHeight:B}=this.context.gl;return this.width!==w||this.height!==B}}class ks{constructor(w,B){this.points=w,this.planes=B}static fromInvProjectionMatrix(w,B,Q){let ee=Math.pow(2,Q),le=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map(Xe=>{let ot=1/(Xe=a.af([],Xe,w))[3]/B*ee;return a.b1(Xe,Xe,[ot,ot,1/Xe[3],ot])}),qe=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map(Xe=>{let ot=function(xr,Ir){var ve=Ir[0],be=Ir[1],De=Ir[2],Be=ve*ve+be*be+De*De;return Be>0&&(Be=1/Math.sqrt(Be)),xr[0]=Ir[0]*Be,xr[1]=Ir[1]*Be,xr[2]=Ir[2]*Be,xr}([],function(xr,Ir,ve){var be=Ir[0],De=Ir[1],Be=Ir[2],et=ve[0],We=ve[1],it=ve[2];return xr[0]=De*it-Be*We,xr[1]=Be*et-be*it,xr[2]=be*We-De*et,xr}([],L([],le[Xe[0]],le[Xe[1]]),L([],le[Xe[2]],le[Xe[1]]))),Tt=-((Yt=ot)[0]*(Kt=le[Xe[1]])[0]+Yt[1]*Kt[1]+Yt[2]*Kt[2]);var Yt,Kt;return ot.concat(Tt)});return new ks(le,qe)}}class bc{constructor(w,B){this.min=w,this.max=B,this.center=function(Q,ee,le){return Q[0]=.5*ee[0],Q[1]=.5*ee[1],Q[2]=.5*ee[2],Q}([],function(Q,ee,le){return Q[0]=ee[0]+le[0],Q[1]=ee[1]+le[1],Q[2]=ee[2]+le[2],Q}([],this.min,this.max))}quadrant(w){let B=[w%2==0,w<2],Q=E(this.min),ee=E(this.max);for(let le=0;le=0&&qe++;if(qe===0)return 0;qe!==B.length&&(Q=!1)}if(Q)return 2;for(let ee=0;ee<3;ee++){let le=Number.MAX_VALUE,qe=-Number.MAX_VALUE;for(let Xe=0;Xethis.max[ee]-this.min[ee])return 0}return 1}}class hu{constructor(w=0,B=0,Q=0,ee=0){if(isNaN(w)||w<0||isNaN(B)||B<0||isNaN(Q)||Q<0||isNaN(ee)||ee<0)throw new Error("Invalid value for edge-insets, top, bottom, left and right must all be numbers");this.top=w,this.bottom=B,this.left=Q,this.right=ee}interpolate(w,B,Q){return B.top!=null&&w.top!=null&&(this.top=a.y.number(w.top,B.top,Q)),B.bottom!=null&&w.bottom!=null&&(this.bottom=a.y.number(w.bottom,B.bottom,Q)),B.left!=null&&w.left!=null&&(this.left=a.y.number(w.left,B.left,Q)),B.right!=null&&w.right!=null&&(this.right=a.y.number(w.right,B.right,Q)),this}getCenter(w,B){let Q=a.ac((this.left+w-this.right)/2,0,w),ee=a.ac((this.top+B-this.bottom)/2,0,B);return new a.P(Q,ee)}equals(w){return this.top===w.top&&this.bottom===w.bottom&&this.left===w.left&&this.right===w.right}clone(){return new hu(this.top,this.bottom,this.left,this.right)}toJSON(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}}}let _u=85.051129;class nl{constructor(w,B,Q,ee,le){this.tileSize=512,this._renderWorldCopies=le===void 0||!!le,this._minZoom=w||0,this._maxZoom=B||22,this._minPitch=Q==null?0:Q,this._maxPitch=ee==null?60:ee,this.setMaxBounds(),this.width=0,this.height=0,this._center=new a.N(0,0),this._elevation=0,this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new hu,this._posMatrixCache={},this._alignedPosMatrixCache={},this._fogMatrixCache={},this.minElevationForCurrentTile=0}clone(){let w=new nl(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return w.apply(this),w}apply(w){this.tileSize=w.tileSize,this.latRange=w.latRange,this.lngRange=w.lngRange,this.width=w.width,this.height=w.height,this._center=w._center,this._elevation=w._elevation,this.minElevationForCurrentTile=w.minElevationForCurrentTile,this.zoom=w.zoom,this.angle=w.angle,this._fov=w._fov,this._pitch=w._pitch,this._unmodified=w._unmodified,this._edgeInsets=w._edgeInsets.clone(),this._calcMatrices()}get minZoom(){return this._minZoom}set minZoom(w){this._minZoom!==w&&(this._minZoom=w,this.zoom=Math.max(this.zoom,w))}get maxZoom(){return this._maxZoom}set maxZoom(w){this._maxZoom!==w&&(this._maxZoom=w,this.zoom=Math.min(this.zoom,w))}get minPitch(){return this._minPitch}set minPitch(w){this._minPitch!==w&&(this._minPitch=w,this.pitch=Math.max(this.pitch,w))}get maxPitch(){return this._maxPitch}set maxPitch(w){this._maxPitch!==w&&(this._maxPitch=w,this.pitch=Math.min(this.pitch,w))}get renderWorldCopies(){return this._renderWorldCopies}set renderWorldCopies(w){w===void 0?w=!0:w===null&&(w=!1),this._renderWorldCopies=w}get worldSize(){return this.tileSize*this.scale}get centerOffset(){return this.centerPoint._sub(this.size._div(2))}get size(){return new a.P(this.width,this.height)}get bearing(){return-this.angle/Math.PI*180}set bearing(w){let B=-a.b3(w,-180,180)*Math.PI/180;this.angle!==B&&(this._unmodified=!1,this.angle=B,this._calcMatrices(),this.rotationMatrix=function(){var Q=new a.A(4);return a.A!=Float32Array&&(Q[1]=0,Q[2]=0),Q[0]=1,Q[3]=1,Q}(),function(Q,ee,le){var qe=ee[0],Xe=ee[1],ot=ee[2],Tt=ee[3],Yt=Math.sin(le),Kt=Math.cos(le);Q[0]=qe*Kt+ot*Yt,Q[1]=Xe*Kt+Tt*Yt,Q[2]=qe*-Yt+ot*Kt,Q[3]=Xe*-Yt+Tt*Kt}(this.rotationMatrix,this.rotationMatrix,this.angle))}get pitch(){return this._pitch/Math.PI*180}set pitch(w){let B=a.ac(w,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==B&&(this._unmodified=!1,this._pitch=B,this._calcMatrices())}get fov(){return this._fov/Math.PI*180}set fov(w){w=Math.max(.01,Math.min(60,w)),this._fov!==w&&(this._unmodified=!1,this._fov=w/180*Math.PI,this._calcMatrices())}get zoom(){return this._zoom}set zoom(w){let B=Math.min(Math.max(w,this.minZoom),this.maxZoom);this._zoom!==B&&(this._unmodified=!1,this._zoom=B,this.tileZoom=Math.max(0,Math.floor(B)),this.scale=this.zoomScale(B),this._constrain(),this._calcMatrices())}get center(){return this._center}set center(w){w.lat===this._center.lat&&w.lng===this._center.lng||(this._unmodified=!1,this._center=w,this._constrain(),this._calcMatrices())}get elevation(){return this._elevation}set elevation(w){w!==this._elevation&&(this._elevation=w,this._constrain(),this._calcMatrices())}get padding(){return this._edgeInsets.toJSON()}set padding(w){this._edgeInsets.equals(w)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,w,1),this._calcMatrices())}get centerPoint(){return this._edgeInsets.getCenter(this.width,this.height)}isPaddingEqual(w){return this._edgeInsets.equals(w)}interpolatePadding(w,B,Q){this._unmodified=!1,this._edgeInsets.interpolate(w,B,Q),this._constrain(),this._calcMatrices()}coveringZoomLevel(w){let B=(w.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/w.tileSize));return Math.max(0,B)}getVisibleUnwrappedCoordinates(w){let B=[new a.b4(0,w)];if(this._renderWorldCopies){let Q=this.pointCoordinate(new a.P(0,0)),ee=this.pointCoordinate(new a.P(this.width,0)),le=this.pointCoordinate(new a.P(this.width,this.height)),qe=this.pointCoordinate(new a.P(0,this.height)),Xe=Math.floor(Math.min(Q.x,ee.x,le.x,qe.x)),ot=Math.floor(Math.max(Q.x,ee.x,le.x,qe.x)),Tt=1;for(let Yt=Xe-Tt;Yt<=ot+Tt;Yt++)Yt!==0&&B.push(new a.b4(Yt,w))}return B}coveringTiles(w){var B,Q;let ee=this.coveringZoomLevel(w),le=ee;if(w.minzoom!==void 0&&eew.maxzoom&&(ee=w.maxzoom);let qe=this.pointCoordinate(this.getCameraPoint()),Xe=a.Z.fromLngLat(this.center),ot=Math.pow(2,ee),Tt=[ot*qe.x,ot*qe.y,0],Yt=[ot*Xe.x,ot*Xe.y,0],Kt=ks.fromInvProjectionMatrix(this.invModelViewProjectionMatrix,this.worldSize,ee),xr=w.minzoom||0;!w.terrain&&this.pitch<=60&&this._edgeInsets.top<.1&&(xr=ee);let Ir=w.terrain?2/Math.min(this.tileSize,w.tileSize)*this.tileSize:3,ve=We=>({aabb:new bc([We*ot,0,0],[(We+1)*ot,ot,0]),zoom:0,x:0,y:0,wrap:We,fullyVisible:!1}),be=[],De=[],Be=ee,et=w.reparseOverscaled?le:ee;if(this._renderWorldCopies)for(let We=1;We<=3;We++)be.push(ve(-We)),be.push(ve(We));for(be.push(ve(0));be.length>0;){let We=be.pop(),it=We.x,Ft=We.y,Ht=We.fullyVisible;if(!Ht){let Wr=We.aabb.intersects(Kt);if(Wr===0)continue;Ht=Wr===2}let tr=w.terrain?Tt:Yt,dr=We.aabb.distanceX(tr),Sr=We.aabb.distanceY(tr),Or=Math.max(Math.abs(dr),Math.abs(Sr));if(We.zoom===Be||Or>Ir+(1<=xr){let Wr=Be-We.zoom,ni=Tt[0]-.5-(it<>1),cn=We.zoom+1,ln=We.aabb.quadrant(Wr);if(w.terrain){let Cn=new a.S(cn,We.wrap,cn,ni,Pi),Kn=w.terrain.getMinMaxElevation(Cn),Ta=(B=Kn.minElevation)!==null&&B!==void 0?B:this.elevation,fa=(Q=Kn.maxElevation)!==null&&Q!==void 0?Q:this.elevation;ln=new bc([ln.min[0],ln.min[1],Ta],[ln.max[0],ln.max[1],fa])}be.push({aabb:ln,zoom:cn,x:ni,y:Pi,wrap:We.wrap,fullyVisible:Ht})}}return De.sort((We,it)=>We.distanceSq-it.distanceSq).map(We=>We.tileID)}resize(w,B){this.width=w,this.height=B,this.pixelsToGLUnits=[2/w,-2/B],this._constrain(),this._calcMatrices()}get unmodified(){return this._unmodified}zoomScale(w){return Math.pow(2,w)}scaleZoom(w){return Math.log(w)/Math.LN2}project(w){let B=a.ac(w.lat,-85.051129,_u);return new a.P(a.O(w.lng)*this.worldSize,a.Q(B)*this.worldSize)}unproject(w){return new a.Z(w.x/this.worldSize,w.y/this.worldSize).toLngLat()}get point(){return this.project(this.center)}getCameraPosition(){return{lngLat:this.pointLocation(this.getCameraPoint()),altitude:Math.cos(this._pitch)*this.cameraToCenterDistance/this._pixelPerMeter+this.elevation}}recalculateZoom(w){let B=this.elevation,Q=Math.cos(this._pitch)*this.cameraToCenterDistance/this._pixelPerMeter,ee=this.pointLocation(this.centerPoint,w),le=w.getElevationForLngLatZoom(ee,this.tileZoom);if(!(this.elevation-le))return;let qe=Q+B-le,Xe=Math.cos(this._pitch)*this.cameraToCenterDistance/qe/a.b5(1,ee.lat),ot=this.scaleZoom(Xe/this.tileSize);this._elevation=le,this._center=ee,this.zoom=ot}setLocationAtPoint(w,B){let Q=this.pointCoordinate(B),ee=this.pointCoordinate(this.centerPoint),le=this.locationCoordinate(w),qe=new a.Z(le.x-(Q.x-ee.x),le.y-(Q.y-ee.y));this.center=this.coordinateLocation(qe),this._renderWorldCopies&&(this.center=this.center.wrap())}locationPoint(w,B){return B?this.coordinatePoint(this.locationCoordinate(w),B.getElevationForLngLatZoom(w,this.tileZoom),this.pixelMatrix3D):this.coordinatePoint(this.locationCoordinate(w))}pointLocation(w,B){return this.coordinateLocation(this.pointCoordinate(w,B))}locationCoordinate(w){return a.Z.fromLngLat(w)}coordinateLocation(w){return w&&w.toLngLat()}pointCoordinate(w,B){if(B){let xr=B.pointCoordinate(w);if(xr!=null)return xr}let Q=[w.x,w.y,0,1],ee=[w.x,w.y,1,1];a.af(Q,Q,this.pixelMatrixInverse),a.af(ee,ee,this.pixelMatrixInverse);let le=Q[3],qe=ee[3],Xe=Q[1]/le,ot=ee[1]/qe,Tt=Q[2]/le,Yt=ee[2]/qe,Kt=Tt===Yt?0:(0-Tt)/(Yt-Tt);return new a.Z(a.y.number(Q[0]/le,ee[0]/qe,Kt)/this.worldSize,a.y.number(Xe,ot,Kt)/this.worldSize)}coordinatePoint(w,B=0,Q=this.pixelMatrix){let ee=[w.x*this.worldSize,w.y*this.worldSize,B,1];return a.af(ee,ee,Q),new a.P(ee[0]/ee[3],ee[1]/ee[3])}getBounds(){let w=Math.max(0,this.height/2-this.getHorizon());return new ce().extend(this.pointLocation(new a.P(0,w))).extend(this.pointLocation(new a.P(this.width,w))).extend(this.pointLocation(new a.P(this.width,this.height))).extend(this.pointLocation(new a.P(0,this.height)))}getMaxBounds(){return this.latRange&&this.latRange.length===2&&this.lngRange&&this.lngRange.length===2?new ce([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null}getHorizon(){return Math.tan(Math.PI/2-this._pitch)*this.cameraToCenterDistance*.85}setMaxBounds(w){w?(this.lngRange=[w.getWest(),w.getEast()],this.latRange=[w.getSouth(),w.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-85.051129,_u])}calculateTileMatrix(w){let B=w.canonical,Q=this.worldSize/this.zoomScale(B.z),ee=B.x+Math.pow(2,B.z)*w.wrap,le=a.an(new Float64Array(16));return a.J(le,le,[ee*Q,B.y*Q,0]),a.K(le,le,[Q/a.X,Q/a.X,1]),le}calculatePosMatrix(w,B=!1){let Q=w.key,ee=B?this._alignedPosMatrixCache:this._posMatrixCache;if(ee[Q])return ee[Q];let le=this.calculateTileMatrix(w);return a.L(le,B?this.alignedModelViewProjectionMatrix:this.modelViewProjectionMatrix,le),ee[Q]=new Float32Array(le),ee[Q]}calculateFogMatrix(w){let B=w.key,Q=this._fogMatrixCache;if(Q[B])return Q[B];let ee=this.calculateTileMatrix(w);return a.L(ee,this.fogMatrix,ee),Q[B]=new Float32Array(ee),Q[B]}customLayerMatrix(){return this.mercatorMatrix.slice()}getConstrained(w,B){B=a.ac(+B,this.minZoom,this.maxZoom);let Q={center:new a.N(w.lng,w.lat),zoom:B},ee=this.lngRange;if(!this._renderWorldCopies&&ee===null){let We=179.9999999999;ee=[-We,We]}let le=this.tileSize*this.zoomScale(Q.zoom),qe=0,Xe=le,ot=0,Tt=le,Yt=0,Kt=0,{x:xr,y:Ir}=this.size;if(this.latRange){let We=this.latRange;qe=a.Q(We[1])*le,Xe=a.Q(We[0])*le,Xe-qeXe&&(Be=Xe-We)}if(ee){let We=(ot+Tt)/2,it=ve;this._renderWorldCopies&&(it=a.b3(ve,We-le/2,We+le/2));let Ft=xr/2;it-FtTt&&(De=Tt-Ft)}if(De!==void 0||Be!==void 0){let We=new a.P(De!=null?De:ve,Be!=null?Be:be);Q.center=this.unproject.call({worldSize:le},We).wrap()}return Q}_constrain(){if(!this.center||!this.width||!this.height||this._constraining)return;this._constraining=!0;let w=this._unmodified,{center:B,zoom:Q}=this.getConstrained(this.center,this.zoom);this.center=B,this.zoom=Q,this._unmodified=w,this._constraining=!1}_calcMatrices(){if(!this.height)return;let w=this.centerOffset,B=this.point.x,Q=this.point.y;this.cameraToCenterDistance=.5/Math.tan(this._fov/2)*this.height,this._pixelPerMeter=a.b5(1,this.center.lat)*this.worldSize;let ee=a.an(new Float64Array(16));a.K(ee,ee,[this.width/2,-this.height/2,1]),a.J(ee,ee,[1,-1,0]),this.labelPlaneMatrix=ee,ee=a.an(new Float64Array(16)),a.K(ee,ee,[1,-1,1]),a.J(ee,ee,[-1,-1,0]),a.K(ee,ee,[2/this.width,2/this.height,1]),this.glCoordMatrix=ee;let le=this.cameraToCenterDistance+this._elevation*this._pixelPerMeter/Math.cos(this._pitch),qe=Math.min(this.elevation,this.minElevationForCurrentTile),Xe=le-qe*this._pixelPerMeter/Math.cos(this._pitch),ot=qe<0?Xe:le,Tt=Math.PI/2+this._pitch,Yt=this._fov*(.5+w.y/this.height),Kt=Math.sin(Yt)*ot/Math.sin(a.ac(Math.PI-Tt-Yt,.01,Math.PI-.01)),xr=this.getHorizon(),Ir=2*Math.atan(xr/this.cameraToCenterDistance)*(.5+w.y/(2*xr)),ve=Math.sin(Ir)*ot/Math.sin(a.ac(Math.PI-Tt-Ir,.01,Math.PI-.01)),be=Math.min(Kt,ve);this.farZ=1.01*(Math.cos(Math.PI/2-this._pitch)*be+ot),this.nearZ=this.height/50,ee=new Float64Array(16),a.b6(ee,this._fov,this.width/this.height,this.nearZ,this.farZ),ee[8]=2*-w.x/this.width,ee[9]=2*w.y/this.height,this.projectionMatrix=a.ae(ee),a.K(ee,ee,[1,-1,1]),a.J(ee,ee,[0,0,-this.cameraToCenterDistance]),a.b7(ee,ee,this._pitch),a.ad(ee,ee,this.angle),a.J(ee,ee,[-B,-Q,0]),this.mercatorMatrix=a.K([],ee,[this.worldSize,this.worldSize,this.worldSize]),a.K(ee,ee,[1,1,this._pixelPerMeter]),this.pixelMatrix=a.L(new Float64Array(16),this.labelPlaneMatrix,ee),a.J(ee,ee,[0,0,-this.elevation]),this.modelViewProjectionMatrix=ee,this.invModelViewProjectionMatrix=a.as([],ee),this.fogMatrix=new Float64Array(16),a.b6(this.fogMatrix,this._fov,this.width/this.height,le,this.farZ),this.fogMatrix[8]=2*-w.x/this.width,this.fogMatrix[9]=2*w.y/this.height,a.K(this.fogMatrix,this.fogMatrix,[1,-1,1]),a.J(this.fogMatrix,this.fogMatrix,[0,0,-this.cameraToCenterDistance]),a.b7(this.fogMatrix,this.fogMatrix,this._pitch),a.ad(this.fogMatrix,this.fogMatrix,this.angle),a.J(this.fogMatrix,this.fogMatrix,[-B,-Q,0]),a.K(this.fogMatrix,this.fogMatrix,[1,1,this._pixelPerMeter]),a.J(this.fogMatrix,this.fogMatrix,[0,0,-this.elevation]),this.pixelMatrix3D=a.L(new Float64Array(16),this.labelPlaneMatrix,ee);let De=this.width%2/2,Be=this.height%2/2,et=Math.cos(this.angle),We=Math.sin(this.angle),it=B-Math.round(B)+et*De+We*Be,Ft=Q-Math.round(Q)+et*Be+We*De,Ht=new Float64Array(ee);if(a.J(Ht,Ht,[it>.5?it-1:it,Ft>.5?Ft-1:Ft,0]),this.alignedModelViewProjectionMatrix=Ht,ee=a.as(new Float64Array(16),this.pixelMatrix),!ee)throw new Error("failed to invert matrix");this.pixelMatrixInverse=ee,this._posMatrixCache={},this._alignedPosMatrixCache={},this._fogMatrixCache={}}maxPitchScaleFactor(){if(!this.pixelMatrixInverse)return 1;let w=this.pointCoordinate(new a.P(0,0)),B=[w.x*this.worldSize,w.y*this.worldSize,0,1];return a.af(B,B,this.pixelMatrix)[3]/this.cameraToCenterDistance}getCameraPoint(){let w=Math.tan(this._pitch)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new a.P(0,w))}getCameraQueryGeometry(w){let B=this.getCameraPoint();if(w.length===1)return[w[0],B];{let Q=B.x,ee=B.y,le=B.x,qe=B.y;for(let Xe of w)Q=Math.min(Q,Xe.x),ee=Math.min(ee,Xe.y),le=Math.max(le,Xe.x),qe=Math.max(qe,Xe.y);return[new a.P(Q,ee),new a.P(le,ee),new a.P(le,qe),new a.P(Q,qe),new a.P(Q,ee)]}}lngLatToCameraDepth(w,B){let Q=this.locationCoordinate(w),ee=[Q.x*this.worldSize,Q.y*this.worldSize,B,1];return a.af(ee,ee,this.modelViewProjectionMatrix),ee[2]/ee[3]}}function nh(ue,w){let B,Q=!1,ee=null,le=null,qe=()=>{ee=null,Q&&(ue.apply(le,B),ee=setTimeout(qe,w),Q=!1)};return(...Xe)=>(Q=!0,le=this,B=Xe,ee||qe(),ee)}class Ah{constructor(w){this._getCurrentHash=()=>{let B=window.location.hash.replace("#","");if(this._hashName){let Q;return B.split("&").map(ee=>ee.split("=")).forEach(ee=>{ee[0]===this._hashName&&(Q=ee)}),(Q&&Q[1]||"").split("/")}return B.split("/")},this._onHashChange=()=>{let B=this._getCurrentHash();if(B.length>=3&&!B.some(Q=>isNaN(Q))){let Q=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(B[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+B[2],+B[1]],zoom:+B[0],bearing:Q,pitch:+(B[4]||0)}),!0}return!1},this._updateHashUnthrottled=()=>{let B=window.location.href.replace(/(#.*)?$/,this.getHashString());window.history.replaceState(window.history.state,null,B)},this._removeHash=()=>{let B=this._getCurrentHash();if(B.length===0)return;let Q=B.join("/"),ee=Q;ee.split("&").length>0&&(ee=ee.split("&")[0]),this._hashName&&(ee=`${this._hashName}=${Q}`);let le=window.location.hash.replace(ee,"");le.startsWith("#&")?le=le.slice(0,1)+le.slice(2):le==="#"&&(le="");let qe=window.location.href.replace(/(#.+)?$/,le);qe=qe.replace("&&","&"),window.history.replaceState(window.history.state,null,qe)},this._updateHash=nh(this._updateHashUnthrottled,300),this._hashName=w&&encodeURIComponent(w)}addTo(w){return this._map=w,addEventListener("hashchange",this._onHashChange,!1),this._map.on("moveend",this._updateHash),this}remove(){return removeEventListener("hashchange",this._onHashChange,!1),this._map.off("moveend",this._updateHash),clearTimeout(this._updateHash()),this._removeHash(),delete this._map,this}getHashString(w){let B=this._map.getCenter(),Q=Math.round(100*this._map.getZoom())/100,ee=Math.ceil((Q*Math.LN2+Math.log(512/360/.5))/Math.LN10),le=Math.pow(10,ee),qe=Math.round(B.lng*le)/le,Xe=Math.round(B.lat*le)/le,ot=this._map.getBearing(),Tt=this._map.getPitch(),Yt="";if(Yt+=w?`/${qe}/${Xe}/${Q}`:`${Q}/${Xe}/${qe}`,(ot||Tt)&&(Yt+="/"+Math.round(10*ot)/10),Tt&&(Yt+=`/${Math.round(Tt)}`),this._hashName){let Kt=this._hashName,xr=!1,Ir=window.location.hash.slice(1).split("&").map(ve=>{let be=ve.split("=")[0];return be===Kt?(xr=!0,`${be}=${Yt}`):ve}).filter(ve=>ve);return xr||Ir.push(`${Kt}=${Yt}`),`#${Ir.join("&")}`}return`#${Yt}`}}let zu={linearity:.3,easing:a.b8(0,0,.3,1)},Fc=a.e({deceleration:2500,maxSpeed:1400},zu),wc=a.e({deceleration:20,maxSpeed:1400},zu),bd=a.e({deceleration:1e3,maxSpeed:360},zu),xf=a.e({deceleration:1e3,maxSpeed:90},zu);class Pf{constructor(w){this._map=w,this.clear()}clear(){this._inertiaBuffer=[]}record(w){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:u.now(),settings:w})}_drainInertiaBuffer(){let w=this._inertiaBuffer,B=u.now();for(;w.length>0&&B-w[0].time>160;)w.shift()}_onMoveEnd(w){if(this._drainInertiaBuffer(),this._inertiaBuffer.length<2)return;let B={zoom:0,bearing:0,pitch:0,pan:new a.P(0,0),pinchAround:void 0,around:void 0};for(let{settings:le}of this._inertiaBuffer)B.zoom+=le.zoomDelta||0,B.bearing+=le.bearingDelta||0,B.pitch+=le.pitchDelta||0,le.panDelta&&B.pan._add(le.panDelta),le.around&&(B.around=le.around),le.pinchAround&&(B.pinchAround=le.pinchAround);let Q=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,ee={};if(B.pan.mag()){let le=bf(B.pan.mag(),Q,a.e({},Fc,w||{}));ee.offset=B.pan.mult(le.amount/B.pan.mag()),ee.center=this._map.transform.center,Ou(ee,le)}if(B.zoom){let le=bf(B.zoom,Q,wc);ee.zoom=this._map.transform.zoom+le.amount,Ou(ee,le)}if(B.bearing){let le=bf(B.bearing,Q,bd);ee.bearing=this._map.transform.bearing+a.ac(le.amount,-179,179),Ou(ee,le)}if(B.pitch){let le=bf(B.pitch,Q,xf);ee.pitch=this._map.transform.pitch+le.amount,Ou(ee,le)}if(ee.zoom||ee.bearing){let le=B.pinchAround===void 0?B.around:B.pinchAround;ee.around=le?this._map.unproject(le):this._map.getCenter()}return this.clear(),a.e(ee,{noMoveStart:!0})}}function Ou(ue,w){(!ue.duration||ue.durationB.unproject(ot)),Xe=le.reduce((ot,Tt,Yt,Kt)=>ot.add(Tt.div(Kt.length)),new a.P(0,0));super(w,{points:le,point:Xe,lngLats:qe,lngLat:B.unproject(Xe),originalEvent:Q}),this._defaultPrevented=!1}}class Hh extends a.k{preventDefault(){this._defaultPrevented=!0}get defaultPrevented(){return this._defaultPrevented}constructor(w,B,Q){super(w,{originalEvent:Q}),this._defaultPrevented=!1}}class If{constructor(w,B){this._map=w,this._clickTolerance=B.clickTolerance}reset(){delete this._mousedownPos}wheel(w){return this._firePreventable(new Hh(w.type,this._map,w))}mousedown(w,B){return this._mousedownPos=B,this._firePreventable(new jl(w.type,this._map,w))}mouseup(w){this._map.fire(new jl(w.type,this._map,w))}click(w,B){this._mousedownPos&&this._mousedownPos.dist(B)>=this._clickTolerance||this._map.fire(new jl(w.type,this._map,w))}dblclick(w){return this._firePreventable(new jl(w.type,this._map,w))}mouseover(w){this._map.fire(new jl(w.type,this._map,w))}mouseout(w){this._map.fire(new jl(w.type,this._map,w))}touchstart(w){return this._firePreventable(new lf(w.type,this._map,w))}touchmove(w){this._map.fire(new lf(w.type,this._map,w))}touchend(w){this._map.fire(new lf(w.type,this._map,w))}touchcancel(w){this._map.fire(new lf(w.type,this._map,w))}_firePreventable(w){if(this._map.fire(w),w.defaultPrevented)return{}}isEnabled(){return!0}isActive(){return!1}enable(){}disable(){}}class Cs{constructor(w){this._map=w}reset(){this._delayContextMenu=!1,this._ignoreContextMenu=!0,delete this._contextMenuEvent}mousemove(w){this._map.fire(new jl(w.type,this._map,w))}mousedown(){this._delayContextMenu=!0,this._ignoreContextMenu=!1}mouseup(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new jl("contextmenu",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)}contextmenu(w){this._delayContextMenu?this._contextMenuEvent=w:this._ignoreContextMenu||this._map.fire(new jl(w.type,this._map,w)),this._map.listens("contextmenu")&&w.preventDefault()}isEnabled(){return!0}isActive(){return!1}enable(){}disable(){}}class du{constructor(w){this._map=w}get transform(){return this._map._requestedCameraState||this._map.transform}get center(){return{lng:this.transform.center.lng,lat:this.transform.center.lat}}get zoom(){return this.transform.zoom}get pitch(){return this.transform.pitch}get bearing(){return this.transform.bearing}unproject(w){return this.transform.pointLocation(a.P.convert(w),this._map.terrain)}}class ku{constructor(w,B){this._map=w,this._tr=new du(w),this._el=w.getCanvasContainer(),this._container=w.getContainer(),this._clickTolerance=B.clickTolerance||1}isEnabled(){return!!this._enabled}isActive(){return!!this._active}enable(){this.isEnabled()||(this._enabled=!0)}disable(){this.isEnabled()&&(this._enabled=!1)}mousedown(w,B){this.isEnabled()&&w.shiftKey&&w.button===0&&(c.disableDrag(),this._startPos=this._lastPos=B,this._active=!0)}mousemoveWindow(w,B){if(!this._active)return;let Q=B;if(this._lastPos.equals(Q)||!this._box&&Q.dist(this._startPos)le.fitScreenCoordinates(Q,ee,this._tr.bearing,{linear:!0})};this._fireEvent("boxzoomcancel",w)}keydown(w){this._active&&w.keyCode===27&&(this.reset(),this._fireEvent("boxzoomcancel",w))}reset(){this._active=!1,this._container.classList.remove("maplibregl-crosshair"),this._box&&(c.remove(this._box),this._box=null),c.enableDrag(),delete this._startPos,delete this._lastPos}_fireEvent(w,B){return this._map.fire(new a.k(w,{originalEvent:B}))}}function Wf(ue,w){if(ue.length!==w.length)throw new Error(`The number of touches and points are not equal - touches ${ue.length}, points ${w.length}`);let B={};for(let Q=0;Qthis.numTouches)&&(this.aborted=!0),this.aborted||(this.startTime===void 0&&(this.startTime=w.timeStamp),Q.length===this.numTouches&&(this.centroid=function(ee){let le=new a.P(0,0);for(let qe of ee)le._add(qe);return le.div(ee.length)}(B),this.touches=Wf(Q,B)))}touchmove(w,B,Q){if(this.aborted||!this.centroid)return;let ee=Wf(Q,B);for(let le in this.touches){let qe=ee[le];(!qe||qe.dist(this.touches[le])>30)&&(this.aborted=!0)}}touchend(w,B,Q){if((!this.centroid||w.timeStamp-this.startTime>500)&&(this.aborted=!0),Q.length===0){let ee=!this.aborted&&this.centroid;if(this.reset(),ee)return ee}}}class wf{constructor(w){this.singleTap=new Us(w),this.numTaps=w.numTaps,this.reset()}reset(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()}touchstart(w,B,Q){this.singleTap.touchstart(w,B,Q)}touchmove(w,B,Q){this.singleTap.touchmove(w,B,Q)}touchend(w,B,Q){let ee=this.singleTap.touchend(w,B,Q);if(ee){let le=w.timeStamp-this.lastTime<500,qe=!this.lastTap||this.lastTap.dist(ee)<30;if(le&&qe||this.reset(),this.count++,this.lastTime=w.timeStamp,this.lastTap=ee,this.count===this.numTaps)return this.reset(),ee}}}class zc{constructor(w){this._tr=new du(w),this._zoomIn=new wf({numTouches:1,numTaps:2}),this._zoomOut=new wf({numTouches:2,numTaps:1}),this.reset()}reset(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()}touchstart(w,B,Q){this._zoomIn.touchstart(w,B,Q),this._zoomOut.touchstart(w,B,Q)}touchmove(w,B,Q){this._zoomIn.touchmove(w,B,Q),this._zoomOut.touchmove(w,B,Q)}touchend(w,B,Q){let ee=this._zoomIn.touchend(w,B,Q),le=this._zoomOut.touchend(w,B,Q),qe=this._tr;return ee?(this._active=!0,w.preventDefault(),setTimeout(()=>this.reset(),0),{cameraAnimation:Xe=>Xe.easeTo({duration:300,zoom:qe.zoom+1,around:qe.unproject(ee)},{originalEvent:w})}):le?(this._active=!0,w.preventDefault(),setTimeout(()=>this.reset(),0),{cameraAnimation:Xe=>Xe.easeTo({duration:300,zoom:qe.zoom-1,around:qe.unproject(le)},{originalEvent:w})}):void 0}touchcancel(){this.reset()}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}}class Wu{constructor(w){this._enabled=!!w.enable,this._moveStateManager=w.moveStateManager,this._clickTolerance=w.clickTolerance||1,this._moveFunction=w.move,this._activateOnStart=!!w.activateOnStart,w.assignEvents(this),this.reset()}reset(w){this._active=!1,this._moved=!1,delete this._lastPoint,this._moveStateManager.endMove(w)}_move(...w){let B=this._moveFunction(...w);if(B.bearingDelta||B.pitchDelta||B.around||B.panDelta)return this._active=!0,B}dragStart(w,B){this.isEnabled()&&!this._lastPoint&&this._moveStateManager.isValidStartEvent(w)&&(this._moveStateManager.startMove(w),this._lastPoint=B.length?B[0]:B,this._activateOnStart&&this._lastPoint&&(this._active=!0))}dragMove(w,B){if(!this.isEnabled())return;let Q=this._lastPoint;if(!Q)return;if(w.preventDefault(),!this._moveStateManager.isValidMoveEvent(w))return void this.reset(w);let ee=B.length?B[0]:B;return!this._moved&&ee.dist(Q){ue.mousedown=ue.dragStart,ue.mousemoveWindow=ue.dragMove,ue.mouseup=ue.dragEnd,ue.contextmenu=w=>{w.preventDefault()}},Wl=({enable:ue,clickTolerance:w,bearingDegreesPerPixelMoved:B=.8})=>{let Q=new Xu({checkCorrectEvent:ee=>c.mouseButton(ee)===0&&ee.ctrlKey||c.mouseButton(ee)===2});return new Wu({clickTolerance:w,move:(ee,le)=>({bearingDelta:(le.x-ee.x)*B}),moveStateManager:Q,enable:ue,assignEvents:Xf})},ah=({enable:ue,clickTolerance:w,pitchDegreesPerPixelMoved:B=-.5})=>{let Q=new Xu({checkCorrectEvent:ee=>c.mouseButton(ee)===0&&ee.ctrlKey||c.mouseButton(ee)===2});return new Wu({clickTolerance:w,move:(ee,le)=>({pitchDelta:(le.y-ee.y)*B}),moveStateManager:Q,enable:ue,assignEvents:Xf})};class Zu{constructor(w,B){this._clickTolerance=w.clickTolerance||1,this._map=B,this.reset()}reset(){this._active=!1,this._touches={},this._sum=new a.P(0,0)}_shouldBePrevented(w){return w<(this._map.cooperativeGestures.isEnabled()?2:1)}touchstart(w,B,Q){return this._calculateTransform(w,B,Q)}touchmove(w,B,Q){if(this._active){if(!this._shouldBePrevented(Q.length))return w.preventDefault(),this._calculateTransform(w,B,Q);this._map.cooperativeGestures.notifyGestureBlocked("touch_pan",w)}}touchend(w,B,Q){this._calculateTransform(w,B,Q),this._active&&this._shouldBePrevented(Q.length)&&this.reset()}touchcancel(){this.reset()}_calculateTransform(w,B,Q){Q.length>0&&(this._active=!0);let ee=Wf(Q,B),le=new a.P(0,0),qe=new a.P(0,0),Xe=0;for(let Tt in ee){let Yt=ee[Tt],Kt=this._touches[Tt];Kt&&(le._add(Yt),qe._add(Yt.sub(Kt)),Xe++,ee[Tt]=Yt)}if(this._touches=ee,this._shouldBePrevented(Xe)||!qe.mag())return;let ot=qe.div(Xe);return this._sum._add(ot),this._sum.mag()Math.abs(ue.x)}class Bc extends Oc{constructor(w){super(),this._currentTouchCount=0,this._map=w}reset(){super.reset(),this._valid=void 0,delete this._firstMove,delete this._lastPoints}touchstart(w,B,Q){super.touchstart(w,B,Q),this._currentTouchCount=Q.length}_start(w){this._lastPoints=w,fc(w[0].sub(w[1]))&&(this._valid=!1)}_move(w,B,Q){if(this._map.cooperativeGestures.isEnabled()&&this._currentTouchCount<3)return;let ee=w[0].sub(this._lastPoints[0]),le=w[1].sub(this._lastPoints[1]);return this._valid=this.gestureBeginsVertically(ee,le,Q.timeStamp),this._valid?(this._lastPoints=w,this._active=!0,{pitchDelta:(ee.y+le.y)/2*-.5}):void 0}gestureBeginsVertically(w,B,Q){if(this._valid!==void 0)return this._valid;let ee=w.mag()>=2,le=B.mag()>=2;if(!ee&&!le)return;if(!ee||!le)return this._firstMove===void 0&&(this._firstMove=Q),Q-this._firstMove<100&&void 0;let qe=w.y>0==B.y>0;return fc(w)&&fc(B)&&qe}}let At={panStep:100,bearingStep:15,pitchStep:10};class Wt{constructor(w){this._tr=new du(w);let B=At;this._panStep=B.panStep,this._bearingStep=B.bearingStep,this._pitchStep=B.pitchStep,this._rotationDisabled=!1}reset(){this._active=!1}keydown(w){if(w.altKey||w.ctrlKey||w.metaKey)return;let B=0,Q=0,ee=0,le=0,qe=0;switch(w.keyCode){case 61:case 107:case 171:case 187:B=1;break;case 189:case 109:case 173:B=-1;break;case 37:w.shiftKey?Q=-1:(w.preventDefault(),le=-1);break;case 39:w.shiftKey?Q=1:(w.preventDefault(),le=1);break;case 38:w.shiftKey?ee=1:(w.preventDefault(),qe=-1);break;case 40:w.shiftKey?ee=-1:(w.preventDefault(),qe=1);break;default:return}return this._rotationDisabled&&(Q=0,ee=0),{cameraAnimation:Xe=>{let ot=this._tr;Xe.easeTo({duration:300,easeId:"keyboardHandler",easing:Cr,zoom:B?Math.round(ot.zoom)+B*(w.shiftKey?2:1):ot.zoom,bearing:ot.bearing+Q*this._bearingStep,pitch:ot.pitch+ee*this._pitchStep,offset:[-le*this._panStep,-qe*this._panStep],center:ot.center},{originalEvent:w})}}}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}disableRotation(){this._rotationDisabled=!0}enableRotation(){this._rotationDisabled=!1}}function Cr(ue){return ue*(2-ue)}let Ar=4.000244140625;class Kr{constructor(w,B){this._onTimeout=Q=>{this._type="wheel",this._delta-=this._lastValue,this._active||this._start(Q)},this._map=w,this._tr=new du(w),this._triggerRenderFrame=B,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=.0022222222222222222}setZoomRate(w){this._defaultZoomRate=w}setWheelZoomRate(w){this._wheelZoomRate=w}isEnabled(){return!!this._enabled}isActive(){return!!this._active||this._finishTimeout!==void 0}isZooming(){return!!this._zooming}enable(w){this.isEnabled()||(this._enabled=!0,this._aroundCenter=!!w&&w.around==="center")}disable(){this.isEnabled()&&(this._enabled=!1)}_shouldBePrevented(w){return!!this._map.cooperativeGestures.isEnabled()&&!(w.ctrlKey||this._map.cooperativeGestures.isBypassed(w))}wheel(w){if(!this.isEnabled())return;if(this._shouldBePrevented(w))return void this._map.cooperativeGestures.notifyGestureBlocked("wheel_zoom",w);let B=w.deltaMode===WheelEvent.DOM_DELTA_LINE?40*w.deltaY:w.deltaY,Q=u.now(),ee=Q-(this._lastWheelEventTime||0);this._lastWheelEventTime=Q,B!==0&&B%Ar==0?this._type="wheel":B!==0&&Math.abs(B)<4?this._type="trackpad":ee>400?(this._type=null,this._lastValue=B,this._timeout=setTimeout(this._onTimeout,40,w)):this._type||(this._type=Math.abs(ee*B)<200?"trackpad":"wheel",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,B+=this._lastValue)),w.shiftKey&&B&&(B/=4),this._type&&(this._lastWheelEvent=w,this._delta-=B,this._active||this._start(w)),w.preventDefault()}_start(w){if(!this._delta)return;this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);let B=c.mousePos(this._map.getCanvas(),w),Q=this._tr;this._around=B.y>Q.transform.height/2-Q.transform.getHorizon()?a.N.convert(this._aroundCenter?Q.center:Q.unproject(B)):a.N.convert(Q.center),this._aroundPoint=Q.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._triggerRenderFrame())}renderFrame(){if(!this._frameId||(this._frameId=null,!this.isActive()))return;let w=this._tr.transform;if(this._delta!==0){let ot=this._type==="wheel"&&Math.abs(this._delta)>Ar?this._wheelZoomRate:this._defaultZoomRate,Tt=2/(1+Math.exp(-Math.abs(this._delta*ot)));this._delta<0&&Tt!==0&&(Tt=1/Tt);let Yt=typeof this._targetZoom=="number"?w.zoomScale(this._targetZoom):w.scale;this._targetZoom=Math.min(w.maxZoom,Math.max(w.minZoom,w.scaleZoom(Yt*Tt))),this._type==="wheel"&&(this._startZoom=w.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}let B=typeof this._targetZoom=="number"?this._targetZoom:w.zoom,Q=this._startZoom,ee=this._easing,le,qe=!1,Xe=u.now()-this._lastWheelEventTime;if(this._type==="wheel"&&Q&&ee&&Xe){let ot=Math.min(Xe/200,1),Tt=ee(ot);le=a.y.number(Q,B,Tt),ot<1?this._frameId||(this._frameId=!0):qe=!0}else le=B,qe=!0;return this._active=!0,qe&&(this._active=!1,this._finishTimeout=setTimeout(()=>{this._zooming=!1,this._triggerRenderFrame(),delete this._targetZoom,delete this._finishTimeout},200)),{noInertia:!0,needsRenderFrame:!qe,zoomDelta:le-w.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}_smoothOutEasing(w){let B=a.b9;if(this._prevEase){let Q=this._prevEase,ee=(u.now()-Q.start)/Q.duration,le=Q.easing(ee+.01)-Q.easing(ee),qe=.27/Math.sqrt(le*le+1e-4)*.01,Xe=Math.sqrt(.0729-qe*qe);B=a.b8(qe,Xe,.25,1)}return this._prevEase={start:u.now(),duration:w,easing:B},B}reset(){this._active=!1,this._zooming=!1,delete this._targetZoom,this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout)}}class ki{constructor(w,B){this._clickZoom=w,this._tapZoom=B}enable(){this._clickZoom.enable(),this._tapZoom.enable()}disable(){this._clickZoom.disable(),this._tapZoom.disable()}isEnabled(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()}isActive(){return this._clickZoom.isActive()||this._tapZoom.isActive()}}class Xi{constructor(w){this._tr=new du(w),this.reset()}reset(){this._active=!1}dblclick(w,B){return w.preventDefault(),{cameraAnimation:Q=>{Q.easeTo({duration:300,zoom:this._tr.zoom+(w.shiftKey?-1:1),around:this._tr.unproject(B)},{originalEvent:w})}}}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}}class dn{constructor(){this._tap=new wf({numTouches:1,numTaps:1}),this.reset()}reset(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,delete this._tapPoint,this._tap.reset()}touchstart(w,B,Q){if(!this._swipePoint)if(this._tapTime){let ee=B[0],le=w.timeStamp-this._tapTime<500,qe=this._tapPoint.dist(ee)<30;le&&qe?Q.length>0&&(this._swipePoint=ee,this._swipeTouch=Q[0].identifier):this.reset()}else this._tap.touchstart(w,B,Q)}touchmove(w,B,Q){if(this._tapTime){if(this._swipePoint){if(Q[0].identifier!==this._swipeTouch)return;let ee=B[0],le=ee.y-this._swipePoint.y;return this._swipePoint=ee,w.preventDefault(),this._active=!0,{zoomDelta:le/128}}}else this._tap.touchmove(w,B,Q)}touchend(w,B,Q){if(this._tapTime)this._swipePoint&&Q.length===0&&this.reset();else{let ee=this._tap.touchend(w,B,Q);ee&&(this._tapTime=w.timeStamp,this._tapPoint=ee)}}touchcancel(){this.reset()}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}}class wn{constructor(w,B,Q){this._el=w,this._mousePan=B,this._touchPan=Q}enable(w){this._inertiaOptions=w||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add("maplibregl-touch-drag-pan")}disable(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove("maplibregl-touch-drag-pan")}isEnabled(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()}isActive(){return this._mousePan.isActive()||this._touchPan.isActive()}}class Nn{constructor(w,B,Q){this._pitchWithRotate=w.pitchWithRotate,this._mouseRotate=B,this._mousePitch=Q}enable(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()}disable(){this._mouseRotate.disable(),this._mousePitch.disable()}isEnabled(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())}isActive(){return this._mouseRotate.isActive()||this._mousePitch.isActive()}}class Yi{constructor(w,B,Q,ee){this._el=w,this._touchZoom=B,this._touchRotate=Q,this._tapDragZoom=ee,this._rotationDisabled=!1,this._enabled=!0}enable(w){this._touchZoom.enable(w),this._rotationDisabled||this._touchRotate.enable(w),this._tapDragZoom.enable(),this._el.classList.add("maplibregl-touch-zoom-rotate")}disable(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove("maplibregl-touch-zoom-rotate")}isEnabled(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()}isActive(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()}disableRotation(){this._rotationDisabled=!0,this._touchRotate.disable()}enableRotation(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()}}class Qi{constructor(w,B){this._bypassKey=navigator.userAgent.indexOf("Mac")!==-1?"metaKey":"ctrlKey",this._map=w,this._options=B,this._enabled=!1}isActive(){return!1}reset(){}_setupUI(){if(this._container)return;let w=this._map.getCanvasContainer();w.classList.add("maplibregl-cooperative-gestures"),this._container=c.create("div","maplibregl-cooperative-gesture-screen",w);let B=this._map._getUIString("CooperativeGesturesHandler.WindowsHelpText");this._bypassKey==="metaKey"&&(B=this._map._getUIString("CooperativeGesturesHandler.MacHelpText"));let Q=this._map._getUIString("CooperativeGesturesHandler.MobileHelpText"),ee=document.createElement("div");ee.className="maplibregl-desktop-message",ee.textContent=B,this._container.appendChild(ee);let le=document.createElement("div");le.className="maplibregl-mobile-message",le.textContent=Q,this._container.appendChild(le),this._container.setAttribute("aria-hidden","true")}_destroyUI(){this._container&&(c.remove(this._container),this._map.getCanvasContainer().classList.remove("maplibregl-cooperative-gestures")),delete this._container}enable(){this._setupUI(),this._enabled=!0}disable(){this._enabled=!1,this._destroyUI()}isEnabled(){return this._enabled}isBypassed(w){return w[this._bypassKey]}notifyGestureBlocked(w,B){this._enabled&&(this._map.fire(new a.k("cooperativegestureprevented",{gestureType:w,originalEvent:B})),this._container.classList.add("maplibregl-show"),setTimeout(()=>{this._container.classList.remove("maplibregl-show")},100))}}let on=ue=>ue.zoom||ue.drag||ue.pitch||ue.rotate;class Fi extends a.k{}function $n(ue){return ue.panDelta&&ue.panDelta.mag()||ue.zoomDelta||ue.bearingDelta||ue.pitchDelta}class Ca{constructor(w,B){this.handleWindowEvent=ee=>{this.handleEvent(ee,`${ee.type}Window`)},this.handleEvent=(ee,le)=>{if(ee.type==="blur")return void this.stop(!0);this._updatingCamera=!0;let qe=ee.type==="renderFrame"?void 0:ee,Xe={needsRenderFrame:!1},ot={},Tt={},Yt=ee.touches,Kt=Yt?this._getMapTouches(Yt):void 0,xr=Kt?c.touchPos(this._map.getCanvas(),Kt):c.mousePos(this._map.getCanvas(),ee);for(let{handlerName:be,handler:De,allowed:Be}of this._handlers){if(!De.isEnabled())continue;let et;this._blockedByActive(Tt,Be,be)?De.reset():De[le||ee.type]&&(et=De[le||ee.type](ee,xr,Kt),this.mergeHandlerResult(Xe,ot,et,be,qe),et&&et.needsRenderFrame&&this._triggerRenderFrame()),(et||De.isActive())&&(Tt[be]=De)}let Ir={};for(let be in this._previousActiveHandlers)Tt[be]||(Ir[be]=qe);this._previousActiveHandlers=Tt,(Object.keys(Ir).length||$n(Xe))&&(this._changes.push([Xe,ot,Ir]),this._triggerRenderFrame()),(Object.keys(Tt).length||$n(Xe))&&this._map._stop(!0),this._updatingCamera=!1;let{cameraAnimation:ve}=Xe;ve&&(this._inertia.clear(),this._fireEvents({},{},!0),this._changes=[],ve(this._map))},this._map=w,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Pf(w),this._bearingSnap=B.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(B);let Q=this._el;this._listeners=[[Q,"touchstart",{passive:!0}],[Q,"touchmove",{passive:!1}],[Q,"touchend",void 0],[Q,"touchcancel",void 0],[Q,"mousedown",void 0],[Q,"mousemove",void 0],[Q,"mouseup",void 0],[document,"mousemove",{capture:!0}],[document,"mouseup",void 0],[Q,"mouseover",void 0],[Q,"mouseout",void 0],[Q,"dblclick",void 0],[Q,"click",void 0],[Q,"keydown",{capture:!1}],[Q,"keyup",void 0],[Q,"wheel",{passive:!1}],[Q,"contextmenu",void 0],[window,"blur",void 0]];for(let[ee,le,qe]of this._listeners)c.addEventListener(ee,le,ee===document?this.handleWindowEvent:this.handleEvent,qe)}destroy(){for(let[w,B,Q]of this._listeners)c.removeEventListener(w,B,w===document?this.handleWindowEvent:this.handleEvent,Q)}_addDefaultHandlers(w){let B=this._map,Q=B.getCanvasContainer();this._add("mapEvent",new If(B,w));let ee=B.boxZoom=new ku(B,w);this._add("boxZoom",ee),w.interactive&&w.boxZoom&&ee.enable();let le=B.cooperativeGestures=new Qi(B,w.cooperativeGestures);this._add("cooperativeGestures",le),w.cooperativeGestures&&le.enable();let qe=new zc(B),Xe=new Xi(B);B.doubleClickZoom=new ki(Xe,qe),this._add("tapZoom",qe),this._add("clickZoom",Xe),w.interactive&&w.doubleClickZoom&&B.doubleClickZoom.enable();let ot=new dn;this._add("tapDragZoom",ot);let Tt=B.touchPitch=new Bc(B);this._add("touchPitch",Tt),w.interactive&&w.touchPitch&&B.touchPitch.enable(w.touchPitch);let Yt=Wl(w),Kt=ah(w);B.dragRotate=new Nn(w,Yt,Kt),this._add("mouseRotate",Yt,["mousePitch"]),this._add("mousePitch",Kt,["mouseRotate"]),w.interactive&&w.dragRotate&&B.dragRotate.enable();let xr=(({enable:et,clickTolerance:We})=>{let it=new Xu({checkCorrectEvent:Ft=>c.mouseButton(Ft)===0&&!Ft.ctrlKey});return new Wu({clickTolerance:We,move:(Ft,Ht)=>({around:Ht,panDelta:Ht.sub(Ft)}),activateOnStart:!0,moveStateManager:it,enable:et,assignEvents:Xf})})(w),Ir=new Zu(w,B);B.dragPan=new wn(Q,xr,Ir),this._add("mousePan",xr),this._add("touchPan",Ir,["touchZoom","touchRotate"]),w.interactive&&w.dragPan&&B.dragPan.enable(w.dragPan);let ve=new cf,be=new vu;B.touchZoomRotate=new Yi(Q,be,ve,ot),this._add("touchRotate",ve,["touchPan","touchZoom"]),this._add("touchZoom",be,["touchPan","touchRotate"]),w.interactive&&w.touchZoomRotate&&B.touchZoomRotate.enable(w.touchZoomRotate);let De=B.scrollZoom=new Kr(B,()=>this._triggerRenderFrame());this._add("scrollZoom",De,["mousePan"]),w.interactive&&w.scrollZoom&&B.scrollZoom.enable(w.scrollZoom);let Be=B.keyboard=new Wt(B);this._add("keyboard",Be),w.interactive&&w.keyboard&&B.keyboard.enable(),this._add("blockableMapEvent",new Cs(B))}_add(w,B,Q){this._handlers.push({handlerName:w,handler:B,allowed:Q}),this._handlersById[w]=B}stop(w){if(!this._updatingCamera){for(let{handler:B}of this._handlers)B.reset();this._inertia.clear(),this._fireEvents({},{},w),this._changes=[]}}isActive(){for(let{handler:w}of this._handlers)if(w.isActive())return!0;return!1}isZooming(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()}isRotating(){return!!this._eventsInProgress.rotate}isMoving(){return!!on(this._eventsInProgress)||this.isZooming()}_blockedByActive(w,B,Q){for(let ee in w)if(ee!==Q&&(!B||B.indexOf(ee)<0))return!0;return!1}_getMapTouches(w){let B=[];for(let Q of w)this._el.contains(Q.target)&&B.push(Q);return B}mergeHandlerResult(w,B,Q,ee,le){if(!Q)return;a.e(w,Q);let qe={handlerName:ee,originalEvent:Q.originalEvent||le};Q.zoomDelta!==void 0&&(B.zoom=qe),Q.panDelta!==void 0&&(B.drag=qe),Q.pitchDelta!==void 0&&(B.pitch=qe),Q.bearingDelta!==void 0&&(B.rotate=qe)}_applyChanges(){let w={},B={},Q={};for(let[ee,le,qe]of this._changes)ee.panDelta&&(w.panDelta=(w.panDelta||new a.P(0,0))._add(ee.panDelta)),ee.zoomDelta&&(w.zoomDelta=(w.zoomDelta||0)+ee.zoomDelta),ee.bearingDelta&&(w.bearingDelta=(w.bearingDelta||0)+ee.bearingDelta),ee.pitchDelta&&(w.pitchDelta=(w.pitchDelta||0)+ee.pitchDelta),ee.around!==void 0&&(w.around=ee.around),ee.pinchAround!==void 0&&(w.pinchAround=ee.pinchAround),ee.noInertia&&(w.noInertia=ee.noInertia),a.e(B,le),a.e(Q,qe);this._updateMapTransform(w,B,Q),this._changes=[]}_updateMapTransform(w,B,Q){let ee=this._map,le=ee._getTransformForUpdate(),qe=ee.terrain;if(!($n(w)||qe&&this._terrainMovement))return this._fireEvents(B,Q,!0);let{panDelta:Xe,zoomDelta:ot,bearingDelta:Tt,pitchDelta:Yt,around:Kt,pinchAround:xr}=w;xr!==void 0&&(Kt=xr),ee._stop(!0),Kt=Kt||ee.transform.centerPoint;let Ir=le.pointLocation(Xe?Kt.sub(Xe):Kt);Tt&&(le.bearing+=Tt),Yt&&(le.pitch+=Yt),ot&&(le.zoom+=ot),qe?this._terrainMovement||!B.drag&&!B.zoom?B.drag&&this._terrainMovement?le.center=le.pointLocation(le.centerPoint.sub(Xe)):le.setLocationAtPoint(Ir,Kt):(this._terrainMovement=!0,this._map._elevationFreeze=!0,le.setLocationAtPoint(Ir,Kt)):le.setLocationAtPoint(Ir,Kt),ee._applyUpdatedTransform(le),this._map._update(),w.noInertia||this._inertia.record(w),this._fireEvents(B,Q,!0)}_fireEvents(w,B,Q){let ee=on(this._eventsInProgress),le=on(w),qe={};for(let Kt in w){let{originalEvent:xr}=w[Kt];this._eventsInProgress[Kt]||(qe[`${Kt}start`]=xr),this._eventsInProgress[Kt]=w[Kt]}!ee&&le&&this._fireEvent("movestart",le.originalEvent);for(let Kt in qe)this._fireEvent(Kt,qe[Kt]);le&&this._fireEvent("move",le.originalEvent);for(let Kt in w){let{originalEvent:xr}=w[Kt];this._fireEvent(Kt,xr)}let Xe={},ot;for(let Kt in this._eventsInProgress){let{handlerName:xr,originalEvent:Ir}=this._eventsInProgress[Kt];this._handlersById[xr].isActive()||(delete this._eventsInProgress[Kt],ot=B[xr]||Ir,Xe[`${Kt}end`]=ot)}for(let Kt in Xe)this._fireEvent(Kt,Xe[Kt]);let Tt=on(this._eventsInProgress),Yt=(ee||le)&&!Tt;if(Yt&&this._terrainMovement){this._map._elevationFreeze=!1,this._terrainMovement=!1;let Kt=this._map._getTransformForUpdate();Kt.recalculateZoom(this._map.terrain),this._map._applyUpdatedTransform(Kt)}if(Q&&Yt){this._updatingCamera=!0;let Kt=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),xr=Ir=>Ir!==0&&-this._bearingSnap{delete this._frameId,this.handleEvent(new Fi("renderFrame",{timeStamp:w})),this._applyChanges()})}_triggerRenderFrame(){this._frameId===void 0&&(this._frameId=this._requestFrame())}}class Ra extends a.E{constructor(w,B){super(),this._renderFrameCallback=()=>{let Q=Math.min((u.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(Q)),Q<1&&this._easeFrameId?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},this._moving=!1,this._zooming=!1,this.transform=w,this._bearingSnap=B.bearingSnap,this.on("moveend",()=>{delete this._requestedCameraState})}getCenter(){return new a.N(this.transform.center.lng,this.transform.center.lat)}setCenter(w,B){return this.jumpTo({center:w},B)}panBy(w,B,Q){return w=a.P.convert(w).mult(-1),this.panTo(this.transform.center,a.e({offset:w},B),Q)}panTo(w,B,Q){return this.easeTo(a.e({center:w},B),Q)}getZoom(){return this.transform.zoom}setZoom(w,B){return this.jumpTo({zoom:w},B),this}zoomTo(w,B,Q){return this.easeTo(a.e({zoom:w},B),Q)}zoomIn(w,B){return this.zoomTo(this.getZoom()+1,w,B),this}zoomOut(w,B){return this.zoomTo(this.getZoom()-1,w,B),this}getBearing(){return this.transform.bearing}setBearing(w,B){return this.jumpTo({bearing:w},B),this}getPadding(){return this.transform.padding}setPadding(w,B){return this.jumpTo({padding:w},B),this}rotateTo(w,B,Q){return this.easeTo(a.e({bearing:w},B),Q)}resetNorth(w,B){return this.rotateTo(0,a.e({duration:1e3},w),B),this}resetNorthPitch(w,B){return this.easeTo(a.e({bearing:0,pitch:0,duration:1e3},w),B),this}snapToNorth(w,B){return Math.abs(this.getBearing()){if(this._zooming&&(ee.zoom=a.y.number(le,De,tr)),this._rotating&&(ee.bearing=a.y.number(qe,Tt,tr)),this._pitching&&(ee.pitch=a.y.number(Xe,Yt,tr)),this._padding&&(ee.interpolatePadding(ot,Kt,tr),Ir=ee.centerPoint.add(xr)),this.terrain&&!w.freezeElevation&&this._updateElevation(tr),it)ee.setLocationAtPoint(it,Ft);else{let dr=ee.zoomScale(ee.zoom-le),Sr=De>le?Math.min(2,We):Math.max(.5,We),Or=Math.pow(Sr,1-tr),Wr=ee.unproject(Be.add(et.mult(tr*Or)).mult(dr));ee.setLocationAtPoint(ee.renderWorldCopies?Wr.wrap():Wr,Ir)}this._applyUpdatedTransform(ee),this._fireMoveEvents(B)},tr=>{this.terrain&&w.freezeElevation&&this._finalizeElevation(),this._afterEase(B,tr)},w),this}_prepareEase(w,B,Q={}){this._moving=!0,B||Q.moving||this.fire(new a.k("movestart",w)),this._zooming&&!Q.zooming&&this.fire(new a.k("zoomstart",w)),this._rotating&&!Q.rotating&&this.fire(new a.k("rotatestart",w)),this._pitching&&!Q.pitching&&this.fire(new a.k("pitchstart",w))}_prepareElevation(w){this._elevationCenter=w,this._elevationStart=this.transform.elevation,this._elevationTarget=this.terrain.getElevationForLngLatZoom(w,this.transform.tileZoom),this._elevationFreeze=!0}_updateElevation(w){this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this._elevationCenter,this.transform.tileZoom);let B=this.terrain.getElevationForLngLatZoom(this._elevationCenter,this.transform.tileZoom);if(w<1&&B!==this._elevationTarget){let Q=this._elevationTarget-this._elevationStart;this._elevationStart+=w*(Q-(B-(Q*w+this._elevationStart))/(1-w)),this._elevationTarget=B}this.transform.elevation=a.y.number(this._elevationStart,this._elevationTarget,w)}_finalizeElevation(){this._elevationFreeze=!1,this.transform.recalculateZoom(this.terrain)}_getTransformForUpdate(){return this.transformCameraUpdate||this.terrain?(this._requestedCameraState||(this._requestedCameraState=this.transform.clone()),this._requestedCameraState):this.transform}_elevateCameraIfInsideTerrain(w){let B=w.getCameraPosition(),Q=this.terrain.getElevationForLngLatZoom(B.lngLat,w.zoom);if(B.altitudethis._elevateCameraIfInsideTerrain(ee)),this.transformCameraUpdate&&B.push(ee=>this.transformCameraUpdate(ee)),!B.length)return;let Q=w.clone();for(let ee of B){let le=Q.clone(),{center:qe,zoom:Xe,pitch:ot,bearing:Tt,elevation:Yt}=ee(le);qe&&(le.center=qe),Xe!==void 0&&(le.zoom=Xe),ot!==void 0&&(le.pitch=ot),Tt!==void 0&&(le.bearing=Tt),Yt!==void 0&&(le.elevation=Yt),Q.apply(le)}this.transform.apply(Q)}_fireMoveEvents(w){this.fire(new a.k("move",w)),this._zooming&&this.fire(new a.k("zoom",w)),this._rotating&&this.fire(new a.k("rotate",w)),this._pitching&&this.fire(new a.k("pitch",w))}_afterEase(w,B){if(this._easeId&&B&&this._easeId===B)return;delete this._easeId;let Q=this._zooming,ee=this._rotating,le=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,Q&&this.fire(new a.k("zoomend",w)),ee&&this.fire(new a.k("rotateend",w)),le&&this.fire(new a.k("pitchend",w)),this.fire(new a.k("moveend",w))}flyTo(w,B){var Q;if(!w.essential&&u.prefersReducedMotion){let Cn=a.M(w,["center","zoom","bearing","pitch","around"]);return this.jumpTo(Cn,B)}this.stop(),w=a.e({offset:[0,0],speed:1.2,curve:1.42,easing:a.b9},w);let ee=this._getTransformForUpdate(),le=ee.zoom,qe=ee.bearing,Xe=ee.pitch,ot=ee.padding,Tt="bearing"in w?this._normalizeBearing(w.bearing,qe):qe,Yt="pitch"in w?+w.pitch:Xe,Kt="padding"in w?w.padding:ee.padding,xr=a.P.convert(w.offset),Ir=ee.centerPoint.add(xr),ve=ee.pointLocation(Ir),{center:be,zoom:De}=ee.getConstrained(a.N.convert(w.center||ve),(Q=w.zoom)!==null&&Q!==void 0?Q:le);this._normalizeCenter(be,ee);let Be=ee.zoomScale(De-le),et=ee.project(ve),We=ee.project(be).sub(et),it=w.curve,Ft=Math.max(ee.width,ee.height),Ht=Ft/Be,tr=We.mag();if("minZoom"in w){let Cn=a.ac(Math.min(w.minZoom,le,De),ee.minZoom,ee.maxZoom),Kn=Ft/ee.zoomScale(Cn-le);it=Math.sqrt(Kn/tr*2)}let dr=it*it;function Sr(Cn){let Kn=(Ht*Ht-Ft*Ft+(Cn?-1:1)*dr*dr*tr*tr)/(2*(Cn?Ht:Ft)*dr*tr);return Math.log(Math.sqrt(Kn*Kn+1)-Kn)}function Or(Cn){return(Math.exp(Cn)-Math.exp(-Cn))/2}function Wr(Cn){return(Math.exp(Cn)+Math.exp(-Cn))/2}let ni=Sr(!1),Pi=function(Cn){return Wr(ni)/Wr(ni+it*Cn)},cn=function(Cn){return Ft*((Wr(ni)*(Or(Kn=ni+it*Cn)/Wr(Kn))-Or(ni))/dr)/tr;var Kn},ln=(Sr(!0)-ni)/it;if(Math.abs(tr)<1e-6||!isFinite(ln)){if(Math.abs(Ft-Ht)<1e-6)return this.easeTo(w,B);let Cn=Ht0,Pi=Kn=>Math.exp(Cn*it*Kn)}return w.duration="duration"in w?+w.duration:1e3*ln/("screenSpeed"in w?+w.screenSpeed/it:+w.speed),w.maxDuration&&w.duration>w.maxDuration&&(w.duration=0),this._zooming=!0,this._rotating=qe!==Tt,this._pitching=Yt!==Xe,this._padding=!ee.isPaddingEqual(Kt),this._prepareEase(B,!1),this.terrain&&this._prepareElevation(be),this._ease(Cn=>{let Kn=Cn*ln,Ta=1/Pi(Kn);ee.zoom=Cn===1?De:le+ee.scaleZoom(Ta),this._rotating&&(ee.bearing=a.y.number(qe,Tt,Cn)),this._pitching&&(ee.pitch=a.y.number(Xe,Yt,Cn)),this._padding&&(ee.interpolatePadding(ot,Kt,Cn),Ir=ee.centerPoint.add(xr)),this.terrain&&!w.freezeElevation&&this._updateElevation(Cn);let fa=Cn===1?be:ee.unproject(et.add(We.mult(cn(Kn))).mult(Ta));ee.setLocationAtPoint(ee.renderWorldCopies?fa.wrap():fa,Ir),this._applyUpdatedTransform(ee),this._fireMoveEvents(B)},()=>{this.terrain&&w.freezeElevation&&this._finalizeElevation(),this._afterEase(B)},w),this}isEasing(){return!!this._easeFrameId}stop(){return this._stop()}_stop(w,B){var Q;if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){let ee=this._onEaseEnd;delete this._onEaseEnd,ee.call(this,B)}return w||(Q=this.handlers)===null||Q===void 0||Q.stop(!1),this}_ease(w,B,Q){Q.animate===!1||Q.duration===0?(w(1),B()):(this._easeStart=u.now(),this._easeOptions=Q,this._onEaseFrame=w,this._onEaseEnd=B,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))}_normalizeBearing(w,B){w=a.b3(w,-180,180);let Q=Math.abs(w-B);return Math.abs(w-360-B)180?-360:Q<-180?360:0}queryTerrainElevation(w){return this.terrain?this.terrain.getElevationForLngLatZoom(a.N.convert(w),this.transform.tileZoom)-this.transform.elevation:null}}let La={compact:!0,customAttribution:'MapLibre'};class Na{constructor(w=La){this._toggleAttribution=()=>{this._container.classList.contains("maplibregl-compact")&&(this._container.classList.contains("maplibregl-compact-show")?(this._container.setAttribute("open",""),this._container.classList.remove("maplibregl-compact-show")):(this._container.classList.add("maplibregl-compact-show"),this._container.removeAttribute("open")))},this._updateData=B=>{!B||B.sourceDataType!=="metadata"&&B.sourceDataType!=="visibility"&&B.dataType!=="style"&&B.type!=="terrain"||this._updateAttributions()},this._updateCompact=()=>{this._map.getCanvasContainer().offsetWidth<=640||this._compact?this._compact===!1?this._container.setAttribute("open",""):this._container.classList.contains("maplibregl-compact")||this._container.classList.contains("maplibregl-attrib-empty")||(this._container.setAttribute("open",""),this._container.classList.add("maplibregl-compact","maplibregl-compact-show")):(this._container.setAttribute("open",""),this._container.classList.contains("maplibregl-compact")&&this._container.classList.remove("maplibregl-compact","maplibregl-compact-show"))},this._updateCompactMinimize=()=>{this._container.classList.contains("maplibregl-compact")&&this._container.classList.contains("maplibregl-compact-show")&&this._container.classList.remove("maplibregl-compact-show")},this.options=w}getDefaultPosition(){return"bottom-right"}onAdd(w){return this._map=w,this._compact=this.options.compact,this._container=c.create("details","maplibregl-ctrl maplibregl-ctrl-attrib"),this._compactButton=c.create("summary","maplibregl-ctrl-attrib-button",this._container),this._compactButton.addEventListener("click",this._toggleAttribution),this._setElementTitle(this._compactButton,"ToggleAttribution"),this._innerContainer=c.create("div","maplibregl-ctrl-attrib-inner",this._container),this._updateAttributions(),this._updateCompact(),this._map.on("styledata",this._updateData),this._map.on("sourcedata",this._updateData),this._map.on("terrain",this._updateData),this._map.on("resize",this._updateCompact),this._map.on("drag",this._updateCompactMinimize),this._container}onRemove(){c.remove(this._container),this._map.off("styledata",this._updateData),this._map.off("sourcedata",this._updateData),this._map.off("terrain",this._updateData),this._map.off("resize",this._updateCompact),this._map.off("drag",this._updateCompactMinimize),this._map=void 0,this._compact=void 0,this._attribHTML=void 0}_setElementTitle(w,B){let Q=this._map._getUIString(`AttributionControl.${B}`);w.title=Q,w.setAttribute("aria-label",Q)}_updateAttributions(){if(!this._map.style)return;let w=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?w=w.concat(this.options.customAttribution.map(ee=>typeof ee!="string"?"":ee)):typeof this.options.customAttribution=="string"&&w.push(this.options.customAttribution)),this._map.style.stylesheet){let ee=this._map.style.stylesheet;this.styleOwner=ee.owner,this.styleId=ee.id}let B=this._map.style.sourceCaches;for(let ee in B){let le=B[ee];if(le.used||le.usedForTerrain){let qe=le.getSource();qe.attribution&&w.indexOf(qe.attribution)<0&&w.push(qe.attribution)}}w=w.filter(ee=>String(ee).trim()),w.sort((ee,le)=>ee.length-le.length),w=w.filter((ee,le)=>{for(let qe=le+1;qe=0)return!1;return!0});let Q=w.join(" | ");Q!==this._attribHTML&&(this._attribHTML=Q,w.length?(this._innerContainer.innerHTML=Q,this._container.classList.remove("maplibregl-attrib-empty")):this._container.classList.add("maplibregl-attrib-empty"),this._updateCompact(),this._editLink=null)}}class Yn{constructor(w={}){this._updateCompact=()=>{let B=this._container.children;if(B.length){let Q=B[0];this._map.getCanvasContainer().offsetWidth<=640||this._compact?this._compact!==!1&&Q.classList.add("maplibregl-compact"):Q.classList.remove("maplibregl-compact")}},this.options=w}getDefaultPosition(){return"bottom-left"}onAdd(w){this._map=w,this._compact=this.options&&this.options.compact,this._container=c.create("div","maplibregl-ctrl");let B=c.create("a","maplibregl-ctrl-logo");return B.target="_blank",B.rel="noopener nofollow",B.href="https://maplibre.org/",B.setAttribute("aria-label",this._map._getUIString("LogoControl.Title")),B.setAttribute("rel","noopener nofollow"),this._container.appendChild(B),this._container.style.display="block",this._map.on("resize",this._updateCompact),this._updateCompact(),this._container}onRemove(){c.remove(this._container),this._map.off("resize",this._updateCompact),this._map=void 0,this._compact=void 0}}class Dn{constructor(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1}add(w){let B=++this._id;return this._queue.push({callback:w,id:B,cancelled:!1}),B}remove(w){let B=this._currentlyRunning,Q=B?this._queue.concat(B):this._queue;for(let ee of Q)if(ee.id===w)return void(ee.cancelled=!0)}run(w=0){if(this._currentlyRunning)throw new Error("Attempting to run(), but is already running.");let B=this._currentlyRunning=this._queue;this._queue=[];for(let Q of B)if(!Q.cancelled&&(Q.callback(w),this._cleared))break;this._cleared=!1,this._currentlyRunning=!1}clear(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]}}var Ka=a.Y([{name:"a_pos3d",type:"Int16",components:3}]);class bo extends a.E{constructor(w){super(),this.sourceCache=w,this._tiles={},this._renderableTilesKeys=[],this._sourceTileCache={},this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.deltaZoom=1,w.usedForTerrain=!0,w.tileSize=this.tileSize*2**this.deltaZoom}destruct(){this.sourceCache.usedForTerrain=!1,this.sourceCache.tileSize=null}update(w,B){this.sourceCache.update(w,B),this._renderableTilesKeys=[];let Q={};for(let ee of w.coveringTiles({tileSize:this.tileSize,minzoom:this.minzoom,maxzoom:this.maxzoom,reparseOverscaled:!1,terrain:B}))Q[ee.key]=!0,this._renderableTilesKeys.push(ee.key),this._tiles[ee.key]||(ee.posMatrix=new Float64Array(16),a.aP(ee.posMatrix,0,a.X,0,a.X,0,1),this._tiles[ee.key]=new Vt(ee,this.tileSize));for(let ee in this._tiles)Q[ee]||delete this._tiles[ee]}freeRtt(w){for(let B in this._tiles){let Q=this._tiles[B];(!w||Q.tileID.equals(w)||Q.tileID.isChildOf(w)||w.isChildOf(Q.tileID))&&(Q.rtt=[])}}getRenderableTiles(){return this._renderableTilesKeys.map(w=>this.getTileByID(w))}getTileByID(w){return this._tiles[w]}getTerrainCoords(w){let B={};for(let Q of this._renderableTilesKeys){let ee=this._tiles[Q].tileID;if(ee.canonical.equals(w.canonical)){let le=w.clone();le.posMatrix=new Float64Array(16),a.aP(le.posMatrix,0,a.X,0,a.X,0,1),B[Q]=le}else if(ee.canonical.isChildOf(w.canonical)){let le=w.clone();le.posMatrix=new Float64Array(16);let qe=ee.canonical.z-w.canonical.z,Xe=ee.canonical.x-(ee.canonical.x>>qe<>qe<>qe;a.aP(le.posMatrix,0,Tt,0,Tt,0,1),a.J(le.posMatrix,le.posMatrix,[-Xe*Tt,-ot*Tt,0]),B[Q]=le}else if(w.canonical.isChildOf(ee.canonical)){let le=w.clone();le.posMatrix=new Float64Array(16);let qe=w.canonical.z-ee.canonical.z,Xe=w.canonical.x-(w.canonical.x>>qe<>qe<>qe;a.aP(le.posMatrix,0,a.X,0,a.X,0,1),a.J(le.posMatrix,le.posMatrix,[Xe*Tt,ot*Tt,0]),a.K(le.posMatrix,le.posMatrix,[1/2**qe,1/2**qe,0]),B[Q]=le}}return B}getSourceTile(w,B){let Q=this.sourceCache._source,ee=w.overscaledZ-this.deltaZoom;if(ee>Q.maxzoom&&(ee=Q.maxzoom),ee=Q.minzoom&&(!le||!le.dem);)le=this.sourceCache.getTileByID(w.scaledTo(ee--).key);return le}tilesAfterTime(w=Date.now()){return Object.values(this._tiles).filter(B=>B.timeAdded>=w)}}class Xo{constructor(w,B,Q){this.painter=w,this.sourceCache=new bo(B),this.options=Q,this.exaggeration=typeof Q.exaggeration=="number"?Q.exaggeration:1,this.qualityFactor=2,this.meshSize=128,this._demMatrixCache={},this.coordsIndex=[],this._coordsTextureSize=1024}getDEMElevation(w,B,Q,ee=a.X){var le;if(!(B>=0&&B=0&&Qw.canonical.z&&(w.canonical.z>=ee?le=w.canonical.z-ee:a.w("cannot calculate elevation if elevation maxzoom > source.maxzoom"));let qe=w.canonical.x-(w.canonical.x>>le<>le<>8<<4|le>>8,B[qe+3]=0;let Q=new a.R({width:this._coordsTextureSize,height:this._coordsTextureSize},new Uint8Array(B.buffer)),ee=new g(w,Q,w.gl.RGBA,{premultiply:!1});return ee.bind(w.gl.NEAREST,w.gl.CLAMP_TO_EDGE),this._coordsTexture=ee,ee}pointCoordinate(w){this.painter.maybeDrawDepthAndCoords(!0);let B=new Uint8Array(4),Q=this.painter.context,ee=Q.gl,le=Math.round(w.x*this.painter.pixelRatio/devicePixelRatio),qe=Math.round(w.y*this.painter.pixelRatio/devicePixelRatio),Xe=Math.round(this.painter.height/devicePixelRatio);Q.bindFramebuffer.set(this.getFramebuffer("coords").framebuffer),ee.readPixels(le,Xe-qe-1,1,1,ee.RGBA,ee.UNSIGNED_BYTE,B),Q.bindFramebuffer.set(null);let ot=B[0]+(B[2]>>4<<8),Tt=B[1]+((15&B[2])<<8),Yt=this.coordsIndex[255-B[3]],Kt=Yt&&this.sourceCache.getTileByID(Yt);if(!Kt)return null;let xr=this._coordsTextureSize,Ir=(1<w.id!==B),this._recentlyUsed.push(w.id)}stampObject(w){w.stamp=++this._stamp}getOrCreateFreeObject(){for(let B of this._recentlyUsed)if(!this._objects[B].inUse)return this._objects[B];if(this._objects.length>=this._size)throw new Error("No free RenderPool available, call freeAllObjects() required!");let w=this._createObject(this._objects.length);return this._objects.push(w),w}freeObject(w){w.inUse=!1}freeAllObjects(){for(let w of this._objects)this.freeObject(w)}isFull(){return!(this._objects.length!w.inUse)===!1}}let as={background:!0,fill:!0,line:!0,raster:!0,hillshade:!0};class ws{constructor(w,B){this.painter=w,this.terrain=B,this.pool=new Ss(w.context,30,B.sourceCache.tileSize*B.qualityFactor)}destruct(){this.pool.destruct()}getTexture(w){return this.pool.getObjectForId(w.rtt[this._stacks.length-1].id).texture}prepareForRender(w,B){this._stacks=[],this._prevType=null,this._rttTiles=[],this._renderableTiles=this.terrain.sourceCache.getRenderableTiles(),this._renderableLayerIds=w._order.filter(Q=>!w._layers[Q].isHidden(B)),this._coordsDescendingInv={};for(let Q in w.sourceCaches){this._coordsDescendingInv[Q]={};let ee=w.sourceCaches[Q].getVisibleCoordinates();for(let le of ee){let qe=this.terrain.sourceCache.getTerrainCoords(le);for(let Xe in qe)this._coordsDescendingInv[Q][Xe]||(this._coordsDescendingInv[Q][Xe]=[]),this._coordsDescendingInv[Q][Xe].push(qe[Xe])}}this._coordsDescendingInvStr={};for(let Q of w._order){let ee=w._layers[Q],le=ee.source;if(as[ee.type]&&!this._coordsDescendingInvStr[le]){this._coordsDescendingInvStr[le]={};for(let qe in this._coordsDescendingInv[le])this._coordsDescendingInvStr[le][qe]=this._coordsDescendingInv[le][qe].map(Xe=>Xe.key).sort().join()}}for(let Q of this._renderableTiles)for(let ee in this._coordsDescendingInvStr){let le=this._coordsDescendingInvStr[ee][Q.tileID.key];le&&le!==Q.rttCoords[ee]&&(Q.rtt=[])}}renderLayer(w){if(w.isHidden(this.painter.transform.zoom))return!1;let B=w.type,Q=this.painter,ee=this._renderableLayerIds[this._renderableLayerIds.length-1]===w.id;if(as[B]&&(this._prevType&&as[this._prevType]||this._stacks.push([]),this._prevType=B,this._stacks[this._stacks.length-1].push(w.id),!ee))return!0;if(as[this._prevType]||as[B]&&ee){this._prevType=B;let le=this._stacks.length-1,qe=this._stacks[le]||[];for(let Xe of this._renderableTiles){if(this.pool.isFull()&&(js(this.painter,this.terrain,this._rttTiles),this._rttTiles=[],this.pool.freeAllObjects()),this._rttTiles.push(Xe),Xe.rtt[le]){let Tt=this.pool.getObjectForId(Xe.rtt[le].id);if(Tt.stamp===Xe.rtt[le].stamp){this.pool.useObject(Tt);continue}}let ot=this.pool.getOrCreateFreeObject();this.pool.useObject(ot),this.pool.stampObject(ot),Xe.rtt[le]={id:ot.id,stamp:ot.stamp},Q.context.bindFramebuffer.set(ot.fbo.framebuffer),Q.context.clear({color:a.aM.transparent,stencil:0}),Q.currentStencilSource=void 0;for(let Tt=0;Tt{ue.touchstart=ue.dragStart,ue.touchmoveWindow=ue.dragMove,ue.touchend=ue.dragEnd},va={showCompass:!0,showZoom:!0,visualizePitch:!1};class no{constructor(w,B,Q=!1){this.mousedown=qe=>{this.startMouse(a.e({},qe,{ctrlKey:!0,preventDefault:()=>qe.preventDefault()}),c.mousePos(this.element,qe)),c.addEventListener(window,"mousemove",this.mousemove),c.addEventListener(window,"mouseup",this.mouseup)},this.mousemove=qe=>{this.moveMouse(qe,c.mousePos(this.element,qe))},this.mouseup=qe=>{this.mouseRotate.dragEnd(qe),this.mousePitch&&this.mousePitch.dragEnd(qe),this.offTemp()},this.touchstart=qe=>{qe.targetTouches.length!==1?this.reset():(this._startPos=this._lastPos=c.touchPos(this.element,qe.targetTouches)[0],this.startTouch(qe,this._startPos),c.addEventListener(window,"touchmove",this.touchmove,{passive:!1}),c.addEventListener(window,"touchend",this.touchend))},this.touchmove=qe=>{qe.targetTouches.length!==1?this.reset():(this._lastPos=c.touchPos(this.element,qe.targetTouches)[0],this.moveTouch(qe,this._lastPos))},this.touchend=qe=>{qe.targetTouches.length===0&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),this.touchRotate.reset(),this.touchPitch&&this.touchPitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()},this._clickTolerance=10;let ee=w.dragRotate._mouseRotate.getClickTolerance(),le=w.dragRotate._mousePitch.getClickTolerance();this.element=B,this.mouseRotate=Wl({clickTolerance:ee,enable:!0}),this.touchRotate=(({enable:qe,clickTolerance:Xe,bearingDegreesPerPixelMoved:ot=.8})=>{let Tt=new uf;return new Wu({clickTolerance:Xe,move:(Yt,Kt)=>({bearingDelta:(Kt.x-Yt.x)*ot}),moveStateManager:Tt,enable:qe,assignEvents:Ls})})({clickTolerance:ee,enable:!0}),this.map=w,Q&&(this.mousePitch=ah({clickTolerance:le,enable:!0}),this.touchPitch=(({enable:qe,clickTolerance:Xe,pitchDegreesPerPixelMoved:ot=-.5})=>{let Tt=new uf;return new Wu({clickTolerance:Xe,move:(Yt,Kt)=>({pitchDelta:(Kt.y-Yt.y)*ot}),moveStateManager:Tt,enable:qe,assignEvents:Ls})})({clickTolerance:le,enable:!0})),c.addEventListener(B,"mousedown",this.mousedown),c.addEventListener(B,"touchstart",this.touchstart,{passive:!1}),c.addEventListener(B,"touchcancel",this.reset)}startMouse(w,B){this.mouseRotate.dragStart(w,B),this.mousePitch&&this.mousePitch.dragStart(w,B),c.disableDrag()}startTouch(w,B){this.touchRotate.dragStart(w,B),this.touchPitch&&this.touchPitch.dragStart(w,B),c.disableDrag()}moveMouse(w,B){let Q=this.map,{bearingDelta:ee}=this.mouseRotate.dragMove(w,B)||{};if(ee&&Q.setBearing(Q.getBearing()+ee),this.mousePitch){let{pitchDelta:le}=this.mousePitch.dragMove(w,B)||{};le&&Q.setPitch(Q.getPitch()+le)}}moveTouch(w,B){let Q=this.map,{bearingDelta:ee}=this.touchRotate.dragMove(w,B)||{};if(ee&&Q.setBearing(Q.getBearing()+ee),this.touchPitch){let{pitchDelta:le}=this.touchPitch.dragMove(w,B)||{};le&&Q.setPitch(Q.getPitch()+le)}}off(){let w=this.element;c.removeEventListener(w,"mousedown",this.mousedown),c.removeEventListener(w,"touchstart",this.touchstart,{passive:!1}),c.removeEventListener(window,"touchmove",this.touchmove,{passive:!1}),c.removeEventListener(window,"touchend",this.touchend),c.removeEventListener(w,"touchcancel",this.reset),this.offTemp()}offTemp(){c.enableDrag(),c.removeEventListener(window,"mousemove",this.mousemove),c.removeEventListener(window,"mouseup",this.mouseup),c.removeEventListener(window,"touchmove",this.touchmove,{passive:!1}),c.removeEventListener(window,"touchend",this.touchend)}}let ys;function rs(ue,w,B){let Q=new a.N(ue.lng,ue.lat);if(ue=new a.N(ue.lng,ue.lat),w){let ee=new a.N(ue.lng-360,ue.lat),le=new a.N(ue.lng+360,ue.lat),qe=B.locationPoint(ue).distSqr(w);B.locationPoint(ee).distSqr(w)180;){let ee=B.locationPoint(ue);if(ee.x>=0&&ee.y>=0&&ee.x<=B.width&&ee.y<=B.height)break;ue.lng>B.center.lng?ue.lng-=360:ue.lng+=360}return ue.lng!==Q.lng&&B.locationPoint(ue).y>B.height/2-B.getHorizon()?ue:Q}let $l={center:"translate(-50%,-50%)",top:"translate(-50%,0)","top-left":"translate(0,0)","top-right":"translate(-100%,0)",bottom:"translate(-50%,-100%)","bottom-left":"translate(0,-100%)","bottom-right":"translate(-100%,-100%)",left:"translate(0,-50%)",right:"translate(-100%,-50%)"};function Cu(ue,w,B){let Q=ue.classList;for(let ee in $l)Q.remove(`maplibregl-${B}-anchor-${ee}`);Q.add(`maplibregl-${B}-anchor-${w}`)}class Yu extends a.E{constructor(w){if(super(),this._onKeyPress=B=>{let Q=B.code,ee=B.charCode||B.keyCode;Q!=="Space"&&Q!=="Enter"&&ee!==32&&ee!==13||this.togglePopup()},this._onMapClick=B=>{let Q=B.originalEvent.target,ee=this._element;this._popup&&(Q===ee||ee.contains(Q))&&this.togglePopup()},this._update=B=>{var Q;if(!this._map)return;let ee=this._map.loaded()&&!this._map.isMoving();((B==null?void 0:B.type)==="terrain"||(B==null?void 0:B.type)==="render"&&!ee)&&this._map.once("render",this._update),this._lngLat=this._map.transform.renderWorldCopies?rs(this._lngLat,this._flatPos,this._map.transform):(Q=this._lngLat)===null||Q===void 0?void 0:Q.wrap(),this._flatPos=this._pos=this._map.project(this._lngLat)._add(this._offset),this._map.terrain&&(this._flatPos=this._map.transform.locationPoint(this._lngLat)._add(this._offset));let le="";this._rotationAlignment==="viewport"||this._rotationAlignment==="auto"?le=`rotateZ(${this._rotation}deg)`:this._rotationAlignment==="map"&&(le=`rotateZ(${this._rotation-this._map.getBearing()}deg)`);let qe="";this._pitchAlignment==="viewport"||this._pitchAlignment==="auto"?qe="rotateX(0deg)":this._pitchAlignment==="map"&&(qe=`rotateX(${this._map.getPitch()}deg)`),this._subpixelPositioning||B&&B.type!=="moveend"||(this._pos=this._pos.round()),c.setTransform(this._element,`${$l[this._anchor]} translate(${this._pos.x}px, ${this._pos.y}px) ${qe} ${le}`),u.frameAsync(new AbortController).then(()=>{this._updateOpacity(B&&B.type==="moveend")}).catch(()=>{})},this._onMove=B=>{if(!this._isDragging){let Q=this._clickTolerance||this._map._clickTolerance;this._isDragging=B.point.dist(this._pointerdownPos)>=Q}this._isDragging&&(this._pos=B.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents="none",this._state==="pending"&&(this._state="active",this.fire(new a.k("dragstart"))),this.fire(new a.k("drag")))},this._onUp=()=>{this._element.style.pointerEvents="auto",this._positionDelta=null,this._pointerdownPos=null,this._isDragging=!1,this._map.off("mousemove",this._onMove),this._map.off("touchmove",this._onMove),this._state==="active"&&this.fire(new a.k("dragend")),this._state="inactive"},this._addDragHandler=B=>{this._element.contains(B.originalEvent.target)&&(B.preventDefault(),this._positionDelta=B.point.sub(this._pos).add(this._offset),this._pointerdownPos=B.point,this._state="pending",this._map.on("mousemove",this._onMove),this._map.on("touchmove",this._onMove),this._map.once("mouseup",this._onUp),this._map.once("touchend",this._onUp))},this._anchor=w&&w.anchor||"center",this._color=w&&w.color||"#3FB1CE",this._scale=w&&w.scale||1,this._draggable=w&&w.draggable||!1,this._clickTolerance=w&&w.clickTolerance||0,this._subpixelPositioning=w&&w.subpixelPositioning||!1,this._isDragging=!1,this._state="inactive",this._rotation=w&&w.rotation||0,this._rotationAlignment=w&&w.rotationAlignment||"auto",this._pitchAlignment=w&&w.pitchAlignment&&w.pitchAlignment!=="auto"?w.pitchAlignment:this._rotationAlignment,this.setOpacity(),this.setOpacity(w==null?void 0:w.opacity,w==null?void 0:w.opacityWhenCovered),w&&w.element)this._element=w.element,this._offset=a.P.convert(w&&w.offset||[0,0]);else{this._defaultMarker=!0,this._element=c.create("div");let B=c.createNS("http://www.w3.org/2000/svg","svg"),Q=41,ee=27;B.setAttributeNS(null,"display","block"),B.setAttributeNS(null,"height",`${Q}px`),B.setAttributeNS(null,"width",`${ee}px`),B.setAttributeNS(null,"viewBox",`0 0 ${ee} ${Q}`);let le=c.createNS("http://www.w3.org/2000/svg","g");le.setAttributeNS(null,"stroke","none"),le.setAttributeNS(null,"stroke-width","1"),le.setAttributeNS(null,"fill","none"),le.setAttributeNS(null,"fill-rule","evenodd");let qe=c.createNS("http://www.w3.org/2000/svg","g");qe.setAttributeNS(null,"fill-rule","nonzero");let Xe=c.createNS("http://www.w3.org/2000/svg","g");Xe.setAttributeNS(null,"transform","translate(3.0, 29.0)"),Xe.setAttributeNS(null,"fill","#000000");let ot=[{rx:"10.5",ry:"5.25002273"},{rx:"10.5",ry:"5.25002273"},{rx:"9.5",ry:"4.77275007"},{rx:"8.5",ry:"4.29549936"},{rx:"7.5",ry:"3.81822308"},{rx:"6.5",ry:"3.34094679"},{rx:"5.5",ry:"2.86367051"},{rx:"4.5",ry:"2.38636864"}];for(let Be of ot){let et=c.createNS("http://www.w3.org/2000/svg","ellipse");et.setAttributeNS(null,"opacity","0.04"),et.setAttributeNS(null,"cx","10.5"),et.setAttributeNS(null,"cy","5.80029008"),et.setAttributeNS(null,"rx",Be.rx),et.setAttributeNS(null,"ry",Be.ry),Xe.appendChild(et)}let Tt=c.createNS("http://www.w3.org/2000/svg","g");Tt.setAttributeNS(null,"fill",this._color);let Yt=c.createNS("http://www.w3.org/2000/svg","path");Yt.setAttributeNS(null,"d","M27,13.5 C27,19.074644 20.250001,27.000002 14.75,34.500002 C14.016665,35.500004 12.983335,35.500004 12.25,34.500002 C6.7499993,27.000002 0,19.222562 0,13.5 C0,6.0441559 6.0441559,0 13.5,0 C20.955844,0 27,6.0441559 27,13.5 Z"),Tt.appendChild(Yt);let Kt=c.createNS("http://www.w3.org/2000/svg","g");Kt.setAttributeNS(null,"opacity","0.25"),Kt.setAttributeNS(null,"fill","#000000");let xr=c.createNS("http://www.w3.org/2000/svg","path");xr.setAttributeNS(null,"d","M13.5,0 C6.0441559,0 0,6.0441559 0,13.5 C0,19.222562 6.7499993,27 12.25,34.5 C13,35.522727 14.016664,35.500004 14.75,34.5 C20.250001,27 27,19.074644 27,13.5 C27,6.0441559 20.955844,0 13.5,0 Z M13.5,1 C20.415404,1 26,6.584596 26,13.5 C26,15.898657 24.495584,19.181431 22.220703,22.738281 C19.945823,26.295132 16.705119,30.142167 13.943359,33.908203 C13.743445,34.180814 13.612715,34.322738 13.5,34.441406 C13.387285,34.322738 13.256555,34.180814 13.056641,33.908203 C10.284481,30.127985 7.4148684,26.314159 5.015625,22.773438 C2.6163816,19.232715 1,15.953538 1,13.5 C1,6.584596 6.584596,1 13.5,1 Z"),Kt.appendChild(xr);let Ir=c.createNS("http://www.w3.org/2000/svg","g");Ir.setAttributeNS(null,"transform","translate(6.0, 7.0)"),Ir.setAttributeNS(null,"fill","#FFFFFF");let ve=c.createNS("http://www.w3.org/2000/svg","g");ve.setAttributeNS(null,"transform","translate(8.0, 8.0)");let be=c.createNS("http://www.w3.org/2000/svg","circle");be.setAttributeNS(null,"fill","#000000"),be.setAttributeNS(null,"opacity","0.25"),be.setAttributeNS(null,"cx","5.5"),be.setAttributeNS(null,"cy","5.5"),be.setAttributeNS(null,"r","5.4999962");let De=c.createNS("http://www.w3.org/2000/svg","circle");De.setAttributeNS(null,"fill","#FFFFFF"),De.setAttributeNS(null,"cx","5.5"),De.setAttributeNS(null,"cy","5.5"),De.setAttributeNS(null,"r","5.4999962"),ve.appendChild(be),ve.appendChild(De),qe.appendChild(Xe),qe.appendChild(Tt),qe.appendChild(Kt),qe.appendChild(Ir),qe.appendChild(ve),B.appendChild(qe),B.setAttributeNS(null,"height",Q*this._scale+"px"),B.setAttributeNS(null,"width",ee*this._scale+"px"),this._element.appendChild(B),this._offset=a.P.convert(w&&w.offset||[0,-14])}if(this._element.classList.add("maplibregl-marker"),this._element.addEventListener("dragstart",B=>{B.preventDefault()}),this._element.addEventListener("mousedown",B=>{B.preventDefault()}),Cu(this._element,this._anchor,"marker"),w&&w.className)for(let B of w.className.split(" "))this._element.classList.add(B);this._popup=null}addTo(w){return this.remove(),this._map=w,this._element.setAttribute("aria-label",w._getUIString("Marker.Title")),w.getCanvasContainer().appendChild(this._element),w.on("move",this._update),w.on("moveend",this._update),w.on("terrain",this._update),this.setDraggable(this._draggable),this._update(),this._map.on("click",this._onMapClick),this}remove(){return this._opacityTimeout&&(clearTimeout(this._opacityTimeout),delete this._opacityTimeout),this._map&&(this._map.off("click",this._onMapClick),this._map.off("move",this._update),this._map.off("moveend",this._update),this._map.off("terrain",this._update),this._map.off("mousedown",this._addDragHandler),this._map.off("touchstart",this._addDragHandler),this._map.off("mouseup",this._onUp),this._map.off("touchend",this._onUp),this._map.off("mousemove",this._onMove),this._map.off("touchmove",this._onMove),delete this._map),c.remove(this._element),this._popup&&this._popup.remove(),this}getLngLat(){return this._lngLat}setLngLat(w){return this._lngLat=a.N.convert(w),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this}getElement(){return this._element}setPopup(w){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener("keypress",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute("tabindex")),w){if(!("offset"in w.options)){let ee=Math.abs(13.5)/Math.SQRT2;w.options.offset=this._defaultMarker?{top:[0,0],"top-left":[0,0],"top-right":[0,0],bottom:[0,-38.1],"bottom-left":[ee,-1*(38.1-13.5+ee)],"bottom-right":[-ee,-1*(38.1-13.5+ee)],left:[13.5,-1*(38.1-13.5)],right:[-13.5,-1*(38.1-13.5)]}:this._offset}this._popup=w,this._originalTabIndex=this._element.getAttribute("tabindex"),this._originalTabIndex||this._element.setAttribute("tabindex","0"),this._element.addEventListener("keypress",this._onKeyPress)}return this}setSubpixelPositioning(w){return this._subpixelPositioning=w,this}getPopup(){return this._popup}togglePopup(){let w=this._popup;return this._element.style.opacity===this._opacityWhenCovered?this:w?(w.isOpen()?w.remove():(w.setLngLat(this._lngLat),w.addTo(this._map)),this):this}_updateOpacity(w=!1){var B,Q;if(!(!((B=this._map)===null||B===void 0)&&B.terrain))return void(this._element.style.opacity!==this._opacity&&(this._element.style.opacity=this._opacity));if(w)this._opacityTimeout=null;else{if(this._opacityTimeout)return;this._opacityTimeout=setTimeout(()=>{this._opacityTimeout=null},100)}let ee=this._map,le=ee.terrain.depthAtPoint(this._pos),qe=ee.terrain.getElevationForLngLatZoom(this._lngLat,ee.transform.tileZoom);if(ee.transform.lngLatToCameraDepth(this._lngLat,qe)-le<.006)return void(this._element.style.opacity=this._opacity);let Xe=-this._offset.y/ee.transform._pixelPerMeter,ot=Math.sin(ee.getPitch()*Math.PI/180)*Xe,Tt=ee.terrain.depthAtPoint(new a.P(this._pos.x,this._pos.y-this._offset.y)),Yt=ee.transform.lngLatToCameraDepth(this._lngLat,qe+ot)-Tt>.006;!((Q=this._popup)===null||Q===void 0)&&Q.isOpen()&&Yt&&this._popup.remove(),this._element.style.opacity=Yt?this._opacityWhenCovered:this._opacity}getOffset(){return this._offset}setOffset(w){return this._offset=a.P.convert(w),this._update(),this}addClassName(w){this._element.classList.add(w)}removeClassName(w){this._element.classList.remove(w)}toggleClassName(w){return this._element.classList.toggle(w)}setDraggable(w){return this._draggable=!!w,this._map&&(w?(this._map.on("mousedown",this._addDragHandler),this._map.on("touchstart",this._addDragHandler)):(this._map.off("mousedown",this._addDragHandler),this._map.off("touchstart",this._addDragHandler))),this}isDraggable(){return this._draggable}setRotation(w){return this._rotation=w||0,this._update(),this}getRotation(){return this._rotation}setRotationAlignment(w){return this._rotationAlignment=w||"auto",this._update(),this}getRotationAlignment(){return this._rotationAlignment}setPitchAlignment(w){return this._pitchAlignment=w&&w!=="auto"?w:this._rotationAlignment,this._update(),this}getPitchAlignment(){return this._pitchAlignment}setOpacity(w,B){return w===void 0&&B===void 0&&(this._opacity="1",this._opacityWhenCovered="0.2"),w!==void 0&&(this._opacity=w),B!==void 0&&(this._opacityWhenCovered=B),this._map&&this._updateOpacity(!0),this}}let Nc={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0},pu=0,Uc=!1,xu={maxWidth:100,unit:"metric"};function Ac(ue,w,B){let Q=B&&B.maxWidth||100,ee=ue._container.clientHeight/2,le=ue.unproject([0,ee]),qe=ue.unproject([Q,ee]),Xe=le.distanceTo(qe);if(B&&B.unit==="imperial"){let ot=3.2808*Xe;ot>5280?Ua(w,Q,ot/5280,ue._getUIString("ScaleControl.Miles")):Ua(w,Q,ot,ue._getUIString("ScaleControl.Feet"))}else B&&B.unit==="nautical"?Ua(w,Q,Xe/1852,ue._getUIString("ScaleControl.NauticalMiles")):Xe>=1e3?Ua(w,Q,Xe/1e3,ue._getUIString("ScaleControl.Kilometers")):Ua(w,Q,Xe,ue._getUIString("ScaleControl.Meters"))}function Ua(ue,w,B,Q){let ee=function(le){let qe=Math.pow(10,`${Math.floor(le)}`.length-1),Xe=le/qe;return Xe=Xe>=10?10:Xe>=5?5:Xe>=3?3:Xe>=2?2:Xe>=1?1:function(ot){let Tt=Math.pow(10,Math.ceil(-Math.log(ot)/Math.LN10));return Math.round(ot*Tt)/Tt}(Xe),qe*Xe}(B);ue.style.width=w*(ee/B)+"px",ue.innerHTML=`${ee} ${Q}`}let oo={closeButton:!0,closeOnClick:!0,focusAfterOpen:!0,className:"",maxWidth:"240px",subpixelPositioning:!1},Vc=["a[href]","[tabindex]:not([tabindex='-1'])","[contenteditable]:not([contenteditable='false'])","button:not([disabled])","input:not([disabled])","select:not([disabled])","textarea:not([disabled])"].join(", ");function hc(ue){if(ue){if(typeof ue=="number"){let w=Math.round(Math.abs(ue)/Math.SQRT2);return{center:new a.P(0,0),top:new a.P(0,ue),"top-left":new a.P(w,w),"top-right":new a.P(-w,w),bottom:new a.P(0,-ue),"bottom-left":new a.P(w,-w),"bottom-right":new a.P(-w,-w),left:new a.P(ue,0),right:new a.P(-ue,0)}}if(ue instanceof a.P||Array.isArray(ue)){let w=a.P.convert(ue);return{center:w,top:w,"top-left":w,"top-right":w,bottom:w,"bottom-left":w,"bottom-right":w,left:w,right:w}}return{center:a.P.convert(ue.center||[0,0]),top:a.P.convert(ue.top||[0,0]),"top-left":a.P.convert(ue["top-left"]||[0,0]),"top-right":a.P.convert(ue["top-right"]||[0,0]),bottom:a.P.convert(ue.bottom||[0,0]),"bottom-left":a.P.convert(ue["bottom-left"]||[0,0]),"bottom-right":a.P.convert(ue["bottom-right"]||[0,0]),left:a.P.convert(ue.left||[0,0]),right:a.P.convert(ue.right||[0,0])}}return hc(new a.P(0,0))}let Ku=o;i.AJAXError=a.bh,i.Evented=a.E,i.LngLat=a.N,i.MercatorCoordinate=a.Z,i.Point=a.P,i.addProtocol=a.bi,i.config=a.a,i.removeProtocol=a.bj,i.AttributionControl=Na,i.BoxZoomHandler=ku,i.CanvasSource=Jt,i.CooperativeGesturesHandler=Qi,i.DoubleClickZoomHandler=ki,i.DragPanHandler=wn,i.DragRotateHandler=Nn,i.EdgeInsets=hu,i.FullscreenControl=class extends a.E{constructor(ue={}){super(),this._onFullscreenChange=()=>{var w;let B=window.document.fullscreenElement||window.document.mozFullScreenElement||window.document.webkitFullscreenElement||window.document.msFullscreenElement;for(;!((w=B==null?void 0:B.shadowRoot)===null||w===void 0)&&w.fullscreenElement;)B=B.shadowRoot.fullscreenElement;B===this._container!==this._fullscreen&&this._handleFullscreenChange()},this._onClickFullscreen=()=>{this._isFullscreen()?this._exitFullscreen():this._requestFullscreen()},this._fullscreen=!1,ue&&ue.container&&(ue.container instanceof HTMLElement?this._container=ue.container:a.w("Full screen control 'container' must be a DOM element.")),"onfullscreenchange"in document?this._fullscreenchange="fullscreenchange":"onmozfullscreenchange"in document?this._fullscreenchange="mozfullscreenchange":"onwebkitfullscreenchange"in document?this._fullscreenchange="webkitfullscreenchange":"onmsfullscreenchange"in document&&(this._fullscreenchange="MSFullscreenChange")}onAdd(ue){return this._map=ue,this._container||(this._container=this._map.getContainer()),this._controlContainer=c.create("div","maplibregl-ctrl maplibregl-ctrl-group"),this._setupUI(),this._controlContainer}onRemove(){c.remove(this._controlContainer),this._map=null,window.document.removeEventListener(this._fullscreenchange,this._onFullscreenChange)}_setupUI(){let ue=this._fullscreenButton=c.create("button","maplibregl-ctrl-fullscreen",this._controlContainer);c.create("span","maplibregl-ctrl-icon",ue).setAttribute("aria-hidden","true"),ue.type="button",this._updateTitle(),this._fullscreenButton.addEventListener("click",this._onClickFullscreen),window.document.addEventListener(this._fullscreenchange,this._onFullscreenChange)}_updateTitle(){let ue=this._getTitle();this._fullscreenButton.setAttribute("aria-label",ue),this._fullscreenButton.title=ue}_getTitle(){return this._map._getUIString(this._isFullscreen()?"FullscreenControl.Exit":"FullscreenControl.Enter")}_isFullscreen(){return this._fullscreen}_handleFullscreenChange(){this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle("maplibregl-ctrl-shrink"),this._fullscreenButton.classList.toggle("maplibregl-ctrl-fullscreen"),this._updateTitle(),this._fullscreen?(this.fire(new a.k("fullscreenstart")),this._prevCooperativeGesturesEnabled=this._map.cooperativeGestures.isEnabled(),this._map.cooperativeGestures.disable()):(this.fire(new a.k("fullscreenend")),this._prevCooperativeGesturesEnabled&&this._map.cooperativeGestures.enable())}_exitFullscreen(){window.document.exitFullscreen?window.document.exitFullscreen():window.document.mozCancelFullScreen?window.document.mozCancelFullScreen():window.document.msExitFullscreen?window.document.msExitFullscreen():window.document.webkitCancelFullScreen?window.document.webkitCancelFullScreen():this._togglePseudoFullScreen()}_requestFullscreen(){this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen?this._container.webkitRequestFullscreen():this._togglePseudoFullScreen()}_togglePseudoFullScreen(){this._container.classList.toggle("maplibregl-pseudo-fullscreen"),this._handleFullscreenChange(),this._map.resize()}},i.GeoJSONSource=st,i.GeolocateControl=class extends a.E{constructor(ue){super(),this._onSuccess=w=>{if(this._map){if(this._isOutOfMapMaxBounds(w))return this._setErrorState(),this.fire(new a.k("outofmaxbounds",w)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=w,this._watchState){case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-active");break;case"BACKGROUND":case"BACKGROUND_ERROR":this._watchState="BACKGROUND",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-background");break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}this.options.showUserLocation&&this._watchState!=="OFF"&&this._updateMarker(w),this.options.trackUserLocation&&this._watchState!=="ACTIVE_LOCK"||this._updateCamera(w),this.options.showUserLocation&&this._dotElement.classList.remove("maplibregl-user-location-dot-stale"),this.fire(new a.k("geolocate",w)),this._finish()}},this._updateCamera=w=>{let B=new a.N(w.coords.longitude,w.coords.latitude),Q=w.coords.accuracy,ee=this._map.getBearing(),le=a.e({bearing:ee},this.options.fitBoundsOptions),qe=ce.fromLngLat(B,Q);this._map.fitBounds(qe,le,{geolocateSource:!0})},this._updateMarker=w=>{if(w){let B=new a.N(w.coords.longitude,w.coords.latitude);this._accuracyCircleMarker.setLngLat(B).addTo(this._map),this._userLocationDotMarker.setLngLat(B).addTo(this._map),this._accuracy=w.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},this._onZoom=()=>{this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},this._onError=w=>{if(this._map){if(this.options.trackUserLocation)if(w.code===1){this._watchState="OFF",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background-error"),this._geolocateButton.disabled=!0;let B=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.title=B,this._geolocateButton.setAttribute("aria-label",B),this._geolocationWatchID!==void 0&&this._clearWatch()}else{if(w.code===3&&Uc)return;this._setErrorState()}this._watchState!=="OFF"&&this.options.showUserLocation&&this._dotElement.classList.add("maplibregl-user-location-dot-stale"),this.fire(new a.k("error",w)),this._finish()}},this._finish=()=>{this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},this._setupUI=()=>{this._map&&(this._container.addEventListener("contextmenu",w=>w.preventDefault()),this._geolocateButton=c.create("button","maplibregl-ctrl-geolocate",this._container),c.create("span","maplibregl-ctrl-icon",this._geolocateButton).setAttribute("aria-hidden","true"),this._geolocateButton.type="button",this._geolocateButton.disabled=!0)},this._finishSetupUI=w=>{if(this._map){if(w===!1){a.w("Geolocation support is not available so the GeolocateControl will be disabled.");let B=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.disabled=!0,this._geolocateButton.title=B,this._geolocateButton.setAttribute("aria-label",B)}else{let B=this._map._getUIString("GeolocateControl.FindMyLocation");this._geolocateButton.disabled=!1,this._geolocateButton.title=B,this._geolocateButton.setAttribute("aria-label",B)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute("aria-pressed","false"),this._watchState="OFF"),this.options.showUserLocation&&(this._dotElement=c.create("div","maplibregl-user-location-dot"),this._userLocationDotMarker=new Yu({element:this._dotElement}),this._circleElement=c.create("div","maplibregl-user-location-accuracy-circle"),this._accuracyCircleMarker=new Yu({element:this._circleElement,pitchAlignment:"map"}),this.options.trackUserLocation&&(this._watchState="OFF"),this._map.on("zoom",this._onZoom)),this._geolocateButton.addEventListener("click",()=>this.trigger()),this._setup=!0,this.options.trackUserLocation&&this._map.on("movestart",B=>{B.geolocateSource||this._watchState!=="ACTIVE_LOCK"||B.originalEvent&&B.originalEvent.type==="resize"||(this._watchState="BACKGROUND",this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active"),this.fire(new a.k("trackuserlocationend")),this.fire(new a.k("userlocationlostfocus")))})}},this.options=a.e({},Nc,ue)}onAdd(ue){return this._map=ue,this._container=c.create("div","maplibregl-ctrl maplibregl-ctrl-group"),this._setupUI(),function(){return a._(this,arguments,void 0,function*(w=!1){if(ys!==void 0&&!w)return ys;if(window.navigator.permissions===void 0)return ys=!!window.navigator.geolocation,ys;try{ys=(yield window.navigator.permissions.query({name:"geolocation"})).state!=="denied"}catch(B){ys=!!window.navigator.geolocation}return ys})}().then(w=>this._finishSetupUI(w)),this._container}onRemove(){this._geolocationWatchID!==void 0&&(window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),c.remove(this._container),this._map.off("zoom",this._onZoom),this._map=void 0,pu=0,Uc=!1}_isOutOfMapMaxBounds(ue){let w=this._map.getMaxBounds(),B=ue.coords;return w&&(B.longitudew.getEast()||B.latitudew.getNorth())}_setErrorState(){switch(this._watchState){case"WAITING_ACTIVE":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-active-error");break;case"ACTIVE_LOCK":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-waiting");break;case"BACKGROUND":this._watchState="BACKGROUND_ERROR",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-waiting");break;case"ACTIVE_ERROR":break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}}_updateCircleRadius(){let ue=this._map.getBounds(),w=ue.getSouthEast(),B=ue.getNorthEast(),Q=w.distanceTo(B),ee=Math.ceil(this._accuracy/(Q/this._map._container.clientHeight)*2);this._circleElement.style.width=`${ee}px`,this._circleElement.style.height=`${ee}px`}trigger(){if(!this._setup)return a.w("Geolocate control triggered before added to a map"),!1;if(this.options.trackUserLocation){switch(this._watchState){case"OFF":this._watchState="WAITING_ACTIVE",this.fire(new a.k("trackuserlocationstart"));break;case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":case"BACKGROUND_ERROR":pu--,Uc=!1,this._watchState="OFF",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background-error"),this.fire(new a.k("trackuserlocationend"));break;case"BACKGROUND":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new a.k("trackuserlocationstart")),this.fire(new a.k("userlocationfocus"));break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}switch(this._watchState){case"WAITING_ACTIVE":this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-active");break;case"ACTIVE_LOCK":this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-active");break;case"OFF":break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}if(this._watchState==="OFF"&&this._geolocationWatchID!==void 0)this._clearWatch();else if(this._geolocationWatchID===void 0){let ue;this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","true"),pu++,pu>1?(ue={maximumAge:6e5,timeout:0},Uc=!0):(ue=this.options.positionOptions,Uc=!1),this._geolocationWatchID=window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,ue)}}else window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0}_clearWatch(){window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","false"),this.options.showUserLocation&&this._updateMarker(null)}},i.Hash=Ah,i.ImageSource=Gt,i.KeyboardHandler=Wt,i.LngLatBounds=ce,i.LogoControl=Yn,i.Map=class extends Ra{constructor(ue){a.bf.mark(a.bg.create);let w=Object.assign(Object.assign({},Ws),ue);if(w.minZoom!=null&&w.maxZoom!=null&&w.minZoom>w.maxZoom)throw new Error("maxZoom must be greater than or equal to minZoom");if(w.minPitch!=null&&w.maxPitch!=null&&w.minPitch>w.maxPitch)throw new Error("maxPitch must be greater than or equal to minPitch");if(w.minPitch!=null&&w.minPitch<0)throw new Error("minPitch must be greater than or equal to 0");if(w.maxPitch!=null&&w.maxPitch>85)throw new Error("maxPitch must be less than or equal to 85");if(super(new nl(w.minZoom,w.maxZoom,w.minPitch,w.maxPitch,w.renderWorldCopies),{bearingSnap:w.bearingSnap}),this._idleTriggered=!1,this._crossFadingFactor=1,this._renderTaskQueue=new Dn,this._controls=[],this._mapId=a.a4(),this._contextLost=B=>{B.preventDefault(),this._frameRequest&&(this._frameRequest.abort(),this._frameRequest=null),this.fire(new a.k("webglcontextlost",{originalEvent:B}))},this._contextRestored=B=>{this._setupPainter(),this.resize(),this._update(),this.fire(new a.k("webglcontextrestored",{originalEvent:B}))},this._onMapScroll=B=>{if(B.target===this._container)return this._container.scrollTop=0,this._container.scrollLeft=0,!1},this._onWindowOnline=()=>{this._update()},this._interactive=w.interactive,this._maxTileCacheSize=w.maxTileCacheSize,this._maxTileCacheZoomLevels=w.maxTileCacheZoomLevels,this._failIfMajorPerformanceCaveat=w.failIfMajorPerformanceCaveat===!0,this._preserveDrawingBuffer=w.preserveDrawingBuffer===!0,this._antialias=w.antialias===!0,this._trackResize=w.trackResize===!0,this._bearingSnap=w.bearingSnap,this._refreshExpiredTiles=w.refreshExpiredTiles===!0,this._fadeDuration=w.fadeDuration,this._crossSourceCollisions=w.crossSourceCollisions===!0,this._collectResourceTiming=w.collectResourceTiming===!0,this._locale=Object.assign(Object.assign({},Ho),w.locale),this._clickTolerance=w.clickTolerance,this._overridePixelRatio=w.pixelRatio,this._maxCanvasSize=w.maxCanvasSize,this.transformCameraUpdate=w.transformCameraUpdate,this.cancelPendingTileRequestsWhileZooming=w.cancelPendingTileRequestsWhileZooming===!0,this._imageQueueHandle=p.addThrottleControl(()=>this.isMoving()),this._requestManager=new k(w.transformRequest),typeof w.container=="string"){if(this._container=document.getElementById(w.container),!this._container)throw new Error(`Container '${w.container}' not found.`)}else{if(!(w.container instanceof HTMLElement))throw new Error("Invalid type: 'container' must be a String or HTMLElement.");this._container=w.container}if(w.maxBounds&&this.setMaxBounds(w.maxBounds),this._setupContainer(),this._setupPainter(),this.on("move",()=>this._update(!1)).on("moveend",()=>this._update(!1)).on("zoom",()=>this._update(!0)).on("terrain",()=>{this.painter.terrainFacilitator.dirty=!0,this._update(!0)}).once("idle",()=>{this._idleTriggered=!0}),typeof window!="undefined"){addEventListener("online",this._onWindowOnline,!1);let B=!1,Q=nh(ee=>{this._trackResize&&!this._removed&&(this.resize(ee),this.redraw())},50);this._resizeObserver=new ResizeObserver(ee=>{B?Q(ee):B=!0}),this._resizeObserver.observe(this._container)}this.handlers=new Ca(this,w),this._hash=w.hash&&new Ah(typeof w.hash=="string"&&w.hash||void 0).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:w.center,zoom:w.zoom,bearing:w.bearing,pitch:w.pitch}),w.bounds&&(this.resize(),this.fitBounds(w.bounds,a.e({},w.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=w.localIdeographFontFamily,this._validateStyle=w.validateStyle,w.style&&this.setStyle(w.style,{localIdeographFontFamily:w.localIdeographFontFamily}),w.attributionControl&&this.addControl(new Na(typeof w.attributionControl=="boolean"?void 0:w.attributionControl)),w.maplibreLogo&&this.addControl(new Yn,w.logoPosition),this.on("style.load",()=>{this.transform.unmodified&&this.jumpTo(this.style.stylesheet)}),this.on("data",B=>{this._update(B.dataType==="style"),this.fire(new a.k(`${B.dataType}data`,B))}),this.on("dataloading",B=>{this.fire(new a.k(`${B.dataType}dataloading`,B))}),this.on("dataabort",B=>{this.fire(new a.k("sourcedataabort",B))})}_getMapId(){return this._mapId}addControl(ue,w){if(w===void 0&&(w=ue.getDefaultPosition?ue.getDefaultPosition():"top-right"),!ue||!ue.onAdd)return this.fire(new a.j(new Error("Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.")));let B=ue.onAdd(this);this._controls.push(ue);let Q=this._controlPositions[w];return w.indexOf("bottom")!==-1?Q.insertBefore(B,Q.firstChild):Q.appendChild(B),this}removeControl(ue){if(!ue||!ue.onRemove)return this.fire(new a.j(new Error("Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.")));let w=this._controls.indexOf(ue);return w>-1&&this._controls.splice(w,1),ue.onRemove(this),this}hasControl(ue){return this._controls.indexOf(ue)>-1}calculateCameraOptionsFromTo(ue,w,B,Q){return Q==null&&this.terrain&&(Q=this.terrain.getElevationForLngLatZoom(B,this.transform.tileZoom)),super.calculateCameraOptionsFromTo(ue,w,B,Q)}resize(ue){var w;let B=this._containerDimensions(),Q=B[0],ee=B[1],le=this._getClampedPixelRatio(Q,ee);if(this._resizeCanvas(Q,ee,le),this.painter.resize(Q,ee,le),this.painter.overLimit()){let Xe=this.painter.context.gl;this._maxCanvasSize=[Xe.drawingBufferWidth,Xe.drawingBufferHeight];let ot=this._getClampedPixelRatio(Q,ee);this._resizeCanvas(Q,ee,ot),this.painter.resize(Q,ee,ot)}this.transform.resize(Q,ee),(w=this._requestedCameraState)===null||w===void 0||w.resize(Q,ee);let qe=!this._moving;return qe&&(this.stop(),this.fire(new a.k("movestart",ue)).fire(new a.k("move",ue))),this.fire(new a.k("resize",ue)),qe&&this.fire(new a.k("moveend",ue)),this}_getClampedPixelRatio(ue,w){let{0:B,1:Q}=this._maxCanvasSize,ee=this.getPixelRatio(),le=ue*ee,qe=w*ee;return Math.min(le>B?B/le:1,qe>Q?Q/qe:1)*ee}getPixelRatio(){var ue;return(ue=this._overridePixelRatio)!==null&&ue!==void 0?ue:devicePixelRatio}setPixelRatio(ue){this._overridePixelRatio=ue,this.resize()}getBounds(){return this.transform.getBounds()}getMaxBounds(){return this.transform.getMaxBounds()}setMaxBounds(ue){return this.transform.setMaxBounds(ce.convert(ue)),this._update()}setMinZoom(ue){if((ue=ue==null?-2:ue)>=-2&&ue<=this.transform.maxZoom)return this.transform.minZoom=ue,this._update(),this.getZoom()=this.transform.minZoom)return this.transform.maxZoom=ue,this._update(),this.getZoom()>ue&&this.setZoom(ue),this;throw new Error("maxZoom must be greater than the current minZoom")}getMaxZoom(){return this.transform.maxZoom}setMinPitch(ue){if((ue=ue==null?0:ue)<0)throw new Error("minPitch must be greater than or equal to 0");if(ue>=0&&ue<=this.transform.maxPitch)return this.transform.minPitch=ue,this._update(),this.getPitch()85)throw new Error("maxPitch must be less than or equal to 85");if(ue>=this.transform.minPitch)return this.transform.maxPitch=ue,this._update(),this.getPitch()>ue&&this.setPitch(ue),this;throw new Error("maxPitch must be greater than the current minPitch")}getMaxPitch(){return this.transform.maxPitch}getRenderWorldCopies(){return this.transform.renderWorldCopies}setRenderWorldCopies(ue){return this.transform.renderWorldCopies=ue,this._update()}project(ue){return this.transform.locationPoint(a.N.convert(ue),this.style&&this.terrain)}unproject(ue){return this.transform.pointLocation(a.P.convert(ue),this.terrain)}isMoving(){var ue;return this._moving||((ue=this.handlers)===null||ue===void 0?void 0:ue.isMoving())}isZooming(){var ue;return this._zooming||((ue=this.handlers)===null||ue===void 0?void 0:ue.isZooming())}isRotating(){var ue;return this._rotating||((ue=this.handlers)===null||ue===void 0?void 0:ue.isRotating())}_createDelegatedListener(ue,w,B){if(ue==="mouseenter"||ue==="mouseover"){let Q=!1;return{layers:w,listener:B,delegates:{mousemove:le=>{let qe=w.filter(ot=>this.getLayer(ot)),Xe=qe.length!==0?this.queryRenderedFeatures(le.point,{layers:qe}):[];Xe.length?Q||(Q=!0,B.call(this,new jl(ue,this,le.originalEvent,{features:Xe}))):Q=!1},mouseout:()=>{Q=!1}}}}if(ue==="mouseleave"||ue==="mouseout"){let Q=!1;return{layers:w,listener:B,delegates:{mousemove:qe=>{let Xe=w.filter(ot=>this.getLayer(ot));(Xe.length!==0?this.queryRenderedFeatures(qe.point,{layers:Xe}):[]).length?Q=!0:Q&&(Q=!1,B.call(this,new jl(ue,this,qe.originalEvent)))},mouseout:qe=>{Q&&(Q=!1,B.call(this,new jl(ue,this,qe.originalEvent)))}}}}{let Q=ee=>{let le=w.filter(Xe=>this.getLayer(Xe)),qe=le.length!==0?this.queryRenderedFeatures(ee.point,{layers:le}):[];qe.length&&(ee.features=qe,B.call(this,ee),delete ee.features)};return{layers:w,listener:B,delegates:{[ue]:Q}}}}_saveDelegatedListener(ue,w){this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[ue]=this._delegatedListeners[ue]||[],this._delegatedListeners[ue].push(w)}_removeDelegatedListener(ue,w,B){if(!this._delegatedListeners||!this._delegatedListeners[ue])return;let Q=this._delegatedListeners[ue];for(let ee=0;eew.includes(qe))){for(let qe in le.delegates)this.off(qe,le.delegates[qe]);return void Q.splice(ee,1)}}}on(ue,w,B){if(B===void 0)return super.on(ue,w);let Q=this._createDelegatedListener(ue,typeof w=="string"?[w]:w,B);this._saveDelegatedListener(ue,Q);for(let ee in Q.delegates)this.on(ee,Q.delegates[ee]);return this}once(ue,w,B){if(B===void 0)return super.once(ue,w);let Q=typeof w=="string"?[w]:w,ee=this._createDelegatedListener(ue,Q,B);for(let le in ee.delegates){let qe=ee.delegates[le];ee.delegates[le]=(...Xe)=>{this._removeDelegatedListener(ue,Q,B),qe(...Xe)}}this._saveDelegatedListener(ue,ee);for(let le in ee.delegates)this.once(le,ee.delegates[le]);return this}off(ue,w,B){return B===void 0?super.off(ue,w):(this._removeDelegatedListener(ue,typeof w=="string"?[w]:w,B),this)}queryRenderedFeatures(ue,w){if(!this.style)return[];let B,Q=ue instanceof a.P||Array.isArray(ue),ee=Q?ue:[[0,0],[this.transform.width,this.transform.height]];if(w=w||(Q?{}:ue)||{},ee instanceof a.P||typeof ee[0]=="number")B=[a.P.convert(ee)];else{let le=a.P.convert(ee[0]),qe=a.P.convert(ee[1]);B=[le,new a.P(qe.x,le.y),qe,new a.P(le.x,qe.y),le]}return this.style.queryRenderedFeatures(B,w,this.transform)}querySourceFeatures(ue,w){return this.style.querySourceFeatures(ue,w)}setStyle(ue,w){return(w=a.e({},{localIdeographFontFamily:this._localIdeographFontFamily,validate:this._validateStyle},w)).diff!==!1&&w.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&ue?(this._diffStyle(ue,w),this):(this._localIdeographFontFamily=w.localIdeographFontFamily,this._updateStyle(ue,w))}setTransformRequest(ue){return this._requestManager.setTransformRequest(ue),this}_getUIString(ue){let w=this._locale[ue];if(w==null)throw new Error(`Missing UI string '${ue}'`);return w}_updateStyle(ue,w){if(w.transformStyle&&this.style&&!this.style._loaded)return void this.style.once("style.load",()=>this._updateStyle(ue,w));let B=this.style&&w.transformStyle?this.style.serialize():void 0;return this.style&&(this.style.setEventedParent(null),this.style._remove(!ue)),ue?(this.style=new Ha(this,w||{}),this.style.setEventedParent(this,{style:this.style}),typeof ue=="string"?this.style.loadURL(ue,w,B):this.style.loadJSON(ue,w,B),this):(delete this.style,this)}_lazyInitEmptyStyle(){this.style||(this.style=new Ha(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())}_diffStyle(ue,w){if(typeof ue=="string"){let B=this._requestManager.transformRequest(ue,"Style");a.h(B,new AbortController).then(Q=>{this._updateDiff(Q.data,w)}).catch(Q=>{Q&&this.fire(new a.j(Q))})}else typeof ue=="object"&&this._updateDiff(ue,w)}_updateDiff(ue,w){try{this.style.setState(ue,w)&&this._update(!0)}catch(B){a.w(`Unable to perform style diff: ${B.message||B.error||B}. Rebuilding the style from scratch.`),this._updateStyle(ue,w)}}getStyle(){if(this.style)return this.style.serialize()}isStyleLoaded(){return this.style?this.style.loaded():a.w("There is no style added to the map.")}addSource(ue,w){return this._lazyInitEmptyStyle(),this.style.addSource(ue,w),this._update(!0)}isSourceLoaded(ue){let w=this.style&&this.style.sourceCaches[ue];if(w!==void 0)return w.loaded();this.fire(new a.j(new Error(`There is no source with ID '${ue}'`)))}setTerrain(ue){if(this.style._checkLoaded(),this._terrainDataCallback&&this.style.off("data",this._terrainDataCallback),ue){let w=this.style.sourceCaches[ue.source];if(!w)throw new Error(`cannot load terrain, because there exists no source with ID: ${ue.source}`);this.terrain===null&&w.reload();for(let B in this.style._layers){let Q=this.style._layers[B];Q.type==="hillshade"&&Q.source===ue.source&&a.w("You are using the same source for a hillshade layer and for 3D terrain. Please consider using two separate sources to improve rendering quality.")}this.terrain=new Xo(this.painter,w,ue),this.painter.renderToTexture=new ws(this.painter,this.terrain),this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this.transform.elevation=this.terrain.getElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this._terrainDataCallback=B=>{B.dataType==="style"?this.terrain.sourceCache.freeRtt():B.dataType==="source"&&B.tile&&(B.sourceId!==ue.source||this._elevationFreeze||(this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this.transform.elevation=this.terrain.getElevationForLngLatZoom(this.transform.center,this.transform.tileZoom)),this.terrain.sourceCache.freeRtt(B.tile.tileID))},this.style.on("data",this._terrainDataCallback)}else this.terrain&&this.terrain.sourceCache.destruct(),this.terrain=null,this.painter.renderToTexture&&this.painter.renderToTexture.destruct(),this.painter.renderToTexture=null,this.transform.minElevationForCurrentTile=0,this.transform.elevation=0;return this.fire(new a.k("terrain",{terrain:ue})),this}getTerrain(){var ue,w;return(w=(ue=this.terrain)===null||ue===void 0?void 0:ue.options)!==null&&w!==void 0?w:null}areTilesLoaded(){let ue=this.style&&this.style.sourceCaches;for(let w in ue){let B=ue[w]._tiles;for(let Q in B){let ee=B[Q];if(ee.state!=="loaded"&&ee.state!=="errored")return!1}}return!0}removeSource(ue){return this.style.removeSource(ue),this._update(!0)}getSource(ue){return this.style.getSource(ue)}addImage(ue,w,B={}){let{pixelRatio:Q=1,sdf:ee=!1,stretchX:le,stretchY:qe,content:Xe,textFitWidth:ot,textFitHeight:Tt}=B;if(this._lazyInitEmptyStyle(),!(w instanceof HTMLImageElement||a.b(w))){if(w.width===void 0||w.height===void 0)return this.fire(new a.j(new Error("Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`")));{let{width:Yt,height:Kt,data:xr}=w,Ir=w;return this.style.addImage(ue,{data:new a.R({width:Yt,height:Kt},new Uint8Array(xr)),pixelRatio:Q,stretchX:le,stretchY:qe,content:Xe,textFitWidth:ot,textFitHeight:Tt,sdf:ee,version:0,userImage:Ir}),Ir.onAdd&&Ir.onAdd(this,ue),this}}{let{width:Yt,height:Kt,data:xr}=u.getImageData(w);this.style.addImage(ue,{data:new a.R({width:Yt,height:Kt},xr),pixelRatio:Q,stretchX:le,stretchY:qe,content:Xe,textFitWidth:ot,textFitHeight:Tt,sdf:ee,version:0})}}updateImage(ue,w){let B=this.style.getImage(ue);if(!B)return this.fire(new a.j(new Error("The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.")));let Q=w instanceof HTMLImageElement||a.b(w)?u.getImageData(w):w,{width:ee,height:le,data:qe}=Q;if(ee===void 0||le===void 0)return this.fire(new a.j(new Error("Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`")));if(ee!==B.data.width||le!==B.data.height)return this.fire(new a.j(new Error("The width and height of the updated image must be that same as the previous version of the image")));let Xe=!(w instanceof HTMLImageElement||a.b(w));return B.data.replace(qe,Xe),this.style.updateImage(ue,B),this}getImage(ue){return this.style.getImage(ue)}hasImage(ue){return ue?!!this.style.getImage(ue):(this.fire(new a.j(new Error("Missing required image id"))),!1)}removeImage(ue){this.style.removeImage(ue)}loadImage(ue){return p.getImage(this._requestManager.transformRequest(ue,"Image"),new AbortController)}listImages(){return this.style.listImages()}addLayer(ue,w){return this._lazyInitEmptyStyle(),this.style.addLayer(ue,w),this._update(!0)}moveLayer(ue,w){return this.style.moveLayer(ue,w),this._update(!0)}removeLayer(ue){return this.style.removeLayer(ue),this._update(!0)}getLayer(ue){return this.style.getLayer(ue)}getLayersOrder(){return this.style.getLayersOrder()}setLayerZoomRange(ue,w,B){return this.style.setLayerZoomRange(ue,w,B),this._update(!0)}setFilter(ue,w,B={}){return this.style.setFilter(ue,w,B),this._update(!0)}getFilter(ue){return this.style.getFilter(ue)}setPaintProperty(ue,w,B,Q={}){return this.style.setPaintProperty(ue,w,B,Q),this._update(!0)}getPaintProperty(ue,w){return this.style.getPaintProperty(ue,w)}setLayoutProperty(ue,w,B,Q={}){return this.style.setLayoutProperty(ue,w,B,Q),this._update(!0)}getLayoutProperty(ue,w){return this.style.getLayoutProperty(ue,w)}setGlyphs(ue,w={}){return this._lazyInitEmptyStyle(),this.style.setGlyphs(ue,w),this._update(!0)}getGlyphs(){return this.style.getGlyphsUrl()}addSprite(ue,w,B={}){return this._lazyInitEmptyStyle(),this.style.addSprite(ue,w,B,Q=>{Q||this._update(!0)}),this}removeSprite(ue){return this._lazyInitEmptyStyle(),this.style.removeSprite(ue),this._update(!0)}getSprite(){return this.style.getSprite()}setSprite(ue,w={}){return this._lazyInitEmptyStyle(),this.style.setSprite(ue,w,B=>{B||this._update(!0)}),this}setLight(ue,w={}){return this._lazyInitEmptyStyle(),this.style.setLight(ue,w),this._update(!0)}getLight(){return this.style.getLight()}setSky(ue){return this._lazyInitEmptyStyle(),this.style.setSky(ue),this._update(!0)}getSky(){return this.style.getSky()}setFeatureState(ue,w){return this.style.setFeatureState(ue,w),this._update()}removeFeatureState(ue,w){return this.style.removeFeatureState(ue,w),this._update()}getFeatureState(ue){return this.style.getFeatureState(ue)}getContainer(){return this._container}getCanvasContainer(){return this._canvasContainer}getCanvas(){return this._canvas}_containerDimensions(){let ue=0,w=0;return this._container&&(ue=this._container.clientWidth||400,w=this._container.clientHeight||300),[ue,w]}_setupContainer(){let ue=this._container;ue.classList.add("maplibregl-map");let w=this._canvasContainer=c.create("div","maplibregl-canvas-container",ue);this._interactive&&w.classList.add("maplibregl-interactive"),this._canvas=c.create("canvas","maplibregl-canvas",w),this._canvas.addEventListener("webglcontextlost",this._contextLost,!1),this._canvas.addEventListener("webglcontextrestored",this._contextRestored,!1),this._canvas.setAttribute("tabindex",this._interactive?"0":"-1"),this._canvas.setAttribute("aria-label",this._getUIString("Map.Title")),this._canvas.setAttribute("role","region");let B=this._containerDimensions(),Q=this._getClampedPixelRatio(B[0],B[1]);this._resizeCanvas(B[0],B[1],Q);let ee=this._controlContainer=c.create("div","maplibregl-control-container",ue),le=this._controlPositions={};["top-left","top-right","bottom-left","bottom-right"].forEach(qe=>{le[qe]=c.create("div",`maplibregl-ctrl-${qe} `,ee)}),this._container.addEventListener("scroll",this._onMapScroll,!1)}_resizeCanvas(ue,w,B){this._canvas.width=Math.floor(B*ue),this._canvas.height=Math.floor(B*w),this._canvas.style.width=`${ue}px`,this._canvas.style.height=`${w}px`}_setupPainter(){let ue={alpha:!0,stencil:!0,depth:!0,failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1},w=null;this._canvas.addEventListener("webglcontextcreationerror",Q=>{w={requestedAttributes:ue},Q&&(w.statusMessage=Q.statusMessage,w.type=Q.type)},{once:!0});let B=this._canvas.getContext("webgl2",ue)||this._canvas.getContext("webgl",ue);if(!B){let Q="Failed to initialize WebGL";throw w?(w.message=Q,new Error(JSON.stringify(w))):new Error(Q)}this.painter=new Dc(B,this.transform),f.testSupport(B)}loaded(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()}_update(ue){return this.style&&this.style._loaded?(this._styleDirty=this._styleDirty||ue,this._sourcesDirty=!0,this.triggerRepaint(),this):this}_requestRenderFrame(ue){return this._update(),this._renderTaskQueue.add(ue)}_cancelRenderFrame(ue){this._renderTaskQueue.remove(ue)}_render(ue){let w=this._idleTriggered?this._fadeDuration:0;if(this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(ue),this._removed)return;let B=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;let ee=this.transform.zoom,le=u.now();this.style.zoomHistory.update(ee,le);let qe=new a.z(ee,{now:le,fadeDuration:w,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),Xe=qe.crossFadingFactor();Xe===1&&Xe===this._crossFadingFactor||(B=!0,this._crossFadingFactor=Xe),this.style.update(qe)}this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this.terrain?(this.terrain.sourceCache.update(this.transform,this.terrain),this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this._elevationFreeze||(this.transform.elevation=this.terrain.getElevationForLngLatZoom(this.transform.center,this.transform.tileZoom))):(this.transform.minElevationForCurrentTile=0,this.transform.elevation=0),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,w,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:w,showPadding:this.showPadding}),this.fire(new a.k("render")),this.loaded()&&!this._loaded&&(this._loaded=!0,a.bf.mark(a.bg.load),this.fire(new a.k("load"))),this.style&&(this.style.hasTransitions()||B)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles();let Q=this._sourcesDirty||this._styleDirty||this._placementDirty;return Q||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&this.fire(new a.k("idle")),!this._loaded||this._fullyLoaded||Q||(this._fullyLoaded=!0,a.bf.mark(a.bg.fullLoad)),this}redraw(){return this.style&&(this._frameRequest&&(this._frameRequest.abort(),this._frameRequest=null),this._render(0)),this}remove(){var ue;this._hash&&this._hash.remove();for(let B of this._controls)B.onRemove(this);this._controls=[],this._frameRequest&&(this._frameRequest.abort(),this._frameRequest=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),typeof window!="undefined"&&removeEventListener("online",this._onWindowOnline,!1),p.removeThrottleControl(this._imageQueueHandle),(ue=this._resizeObserver)===null||ue===void 0||ue.disconnect();let w=this.painter.context.gl.getExtension("WEBGL_lose_context");w!=null&&w.loseContext&&w.loseContext(),this._canvas.removeEventListener("webglcontextrestored",this._contextRestored,!1),this._canvas.removeEventListener("webglcontextlost",this._contextLost,!1),c.remove(this._canvasContainer),c.remove(this._controlContainer),this._container.classList.remove("maplibregl-map"),a.bf.clearMetrics(),this._removed=!0,this.fire(new a.k("remove"))}triggerRepaint(){this.style&&!this._frameRequest&&(this._frameRequest=new AbortController,u.frameAsync(this._frameRequest).then(ue=>{a.bf.frame(ue),this._frameRequest=null,this._render(ue)}).catch(()=>{}))}get showTileBoundaries(){return!!this._showTileBoundaries}set showTileBoundaries(ue){this._showTileBoundaries!==ue&&(this._showTileBoundaries=ue,this._update())}get showPadding(){return!!this._showPadding}set showPadding(ue){this._showPadding!==ue&&(this._showPadding=ue,this._update())}get showCollisionBoxes(){return!!this._showCollisionBoxes}set showCollisionBoxes(ue){this._showCollisionBoxes!==ue&&(this._showCollisionBoxes=ue,ue?this.style._generateCollisionBoxes():this._update())}get showOverdrawInspector(){return!!this._showOverdrawInspector}set showOverdrawInspector(ue){this._showOverdrawInspector!==ue&&(this._showOverdrawInspector=ue,this._update())}get repaint(){return!!this._repaint}set repaint(ue){this._repaint!==ue&&(this._repaint=ue,this.triggerRepaint())}get vertices(){return!!this._vertices}set vertices(ue){this._vertices=ue,this._update()}get version(){return ml}getCameraTargetElevation(){return this.transform.elevation}},i.MapMouseEvent=jl,i.MapTouchEvent=lf,i.MapWheelEvent=Hh,i.Marker=Yu,i.NavigationControl=class{constructor(ue){this._updateZoomButtons=()=>{let w=this._map.getZoom(),B=w===this._map.getMaxZoom(),Q=w===this._map.getMinZoom();this._zoomInButton.disabled=B,this._zoomOutButton.disabled=Q,this._zoomInButton.setAttribute("aria-disabled",B.toString()),this._zoomOutButton.setAttribute("aria-disabled",Q.toString())},this._rotateCompassArrow=()=>{let w=this.options.visualizePitch?`scale(${1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)}) rotateX(${this._map.transform.pitch}deg) rotateZ(${this._map.transform.angle*(180/Math.PI)}deg)`:`rotate(${this._map.transform.angle*(180/Math.PI)}deg)`;this._compassIcon.style.transform=w},this._setButtonTitle=(w,B)=>{let Q=this._map._getUIString(`NavigationControl.${B}`);w.title=Q,w.setAttribute("aria-label",Q)},this.options=a.e({},va,ue),this._container=c.create("div","maplibregl-ctrl maplibregl-ctrl-group"),this._container.addEventListener("contextmenu",w=>w.preventDefault()),this.options.showZoom&&(this._zoomInButton=this._createButton("maplibregl-ctrl-zoom-in",w=>this._map.zoomIn({},{originalEvent:w})),c.create("span","maplibregl-ctrl-icon",this._zoomInButton).setAttribute("aria-hidden","true"),this._zoomOutButton=this._createButton("maplibregl-ctrl-zoom-out",w=>this._map.zoomOut({},{originalEvent:w})),c.create("span","maplibregl-ctrl-icon",this._zoomOutButton).setAttribute("aria-hidden","true")),this.options.showCompass&&(this._compass=this._createButton("maplibregl-ctrl-compass",w=>{this.options.visualizePitch?this._map.resetNorthPitch({},{originalEvent:w}):this._map.resetNorth({},{originalEvent:w})}),this._compassIcon=c.create("span","maplibregl-ctrl-icon",this._compass),this._compassIcon.setAttribute("aria-hidden","true"))}onAdd(ue){return this._map=ue,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,"ZoomIn"),this._setButtonTitle(this._zoomOutButton,"ZoomOut"),this._map.on("zoom",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,"ResetBearing"),this.options.visualizePitch&&this._map.on("pitch",this._rotateCompassArrow),this._map.on("rotate",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new no(this._map,this._compass,this.options.visualizePitch)),this._container}onRemove(){c.remove(this._container),this.options.showZoom&&this._map.off("zoom",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off("pitch",this._rotateCompassArrow),this._map.off("rotate",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map}_createButton(ue,w){let B=c.create("button",ue,this._container);return B.type="button",B.addEventListener("click",w),B}},i.Popup=class extends a.E{constructor(ue){super(),this.remove=()=>(this._content&&c.remove(this._content),this._container&&(c.remove(this._container),delete this._container),this._map&&(this._map.off("move",this._update),this._map.off("move",this._onClose),this._map.off("click",this._onClose),this._map.off("remove",this.remove),this._map.off("mousemove",this._onMouseMove),this._map.off("mouseup",this._onMouseUp),this._map.off("drag",this._onDrag),this._map._canvasContainer.classList.remove("maplibregl-track-pointer"),delete this._map,this.fire(new a.k("close"))),this),this._onMouseUp=w=>{this._update(w.point)},this._onMouseMove=w=>{this._update(w.point)},this._onDrag=w=>{this._update(w.point)},this._update=w=>{var B;if(!this._map||!this._lngLat&&!this._trackPointer||!this._content)return;if(!this._container){if(this._container=c.create("div","maplibregl-popup",this._map.getContainer()),this._tip=c.create("div","maplibregl-popup-tip",this._container),this._container.appendChild(this._content),this.options.className)for(let Xe of this.options.className.split(" "))this._container.classList.add(Xe);this._closeButton&&this._closeButton.setAttribute("aria-label",this._map._getUIString("Popup.Close")),this._trackPointer&&this._container.classList.add("maplibregl-popup-track-pointer")}if(this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._lngLat=this._map.transform.renderWorldCopies&&!this._trackPointer?rs(this._lngLat,this._flatPos,this._map.transform):(B=this._lngLat)===null||B===void 0?void 0:B.wrap(),this._trackPointer&&!w)return;let Q=this._flatPos=this._pos=this._trackPointer&&w?w:this._map.project(this._lngLat);this._map.terrain&&(this._flatPos=this._trackPointer&&w?w:this._map.transform.locationPoint(this._lngLat));let ee=this.options.anchor,le=hc(this.options.offset);if(!ee){let Xe=this._container.offsetWidth,ot=this._container.offsetHeight,Tt;Tt=Q.y+le.bottom.ythis._map.transform.height-ot?["bottom"]:[],Q.xthis._map.transform.width-Xe/2&&Tt.push("right"),ee=Tt.length===0?"bottom":Tt.join("-")}let qe=Q.add(le[ee]);this.options.subpixelPositioning||(qe=qe.round()),c.setTransform(this._container,`${$l[ee]} translate(${qe.x}px,${qe.y}px)`),Cu(this._container,ee,"popup")},this._onClose=()=>{this.remove()},this.options=a.e(Object.create(oo),ue)}addTo(ue){return this._map&&this.remove(),this._map=ue,this.options.closeOnClick&&this._map.on("click",this._onClose),this.options.closeOnMove&&this._map.on("move",this._onClose),this._map.on("remove",this.remove),this._update(),this._focusFirstElement(),this._trackPointer?(this._map.on("mousemove",this._onMouseMove),this._map.on("mouseup",this._onMouseUp),this._container&&this._container.classList.add("maplibregl-popup-track-pointer"),this._map._canvasContainer.classList.add("maplibregl-track-pointer")):this._map.on("move",this._update),this.fire(new a.k("open")),this}isOpen(){return!!this._map}getLngLat(){return this._lngLat}setLngLat(ue){return this._lngLat=a.N.convert(ue),this._pos=null,this._flatPos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on("move",this._update),this._map.off("mousemove",this._onMouseMove),this._container&&this._container.classList.remove("maplibregl-popup-track-pointer"),this._map._canvasContainer.classList.remove("maplibregl-track-pointer")),this}trackPointer(){return this._trackPointer=!0,this._pos=null,this._flatPos=null,this._update(),this._map&&(this._map.off("move",this._update),this._map.on("mousemove",this._onMouseMove),this._map.on("drag",this._onDrag),this._container&&this._container.classList.add("maplibregl-popup-track-pointer"),this._map._canvasContainer.classList.add("maplibregl-track-pointer")),this}getElement(){return this._container}setText(ue){return this.setDOMContent(document.createTextNode(ue))}setHTML(ue){let w=document.createDocumentFragment(),B=document.createElement("body"),Q;for(B.innerHTML=ue;Q=B.firstChild,Q;)w.appendChild(Q);return this.setDOMContent(w)}getMaxWidth(){var ue;return(ue=this._container)===null||ue===void 0?void 0:ue.style.maxWidth}setMaxWidth(ue){return this.options.maxWidth=ue,this._update(),this}setDOMContent(ue){if(this._content)for(;this._content.hasChildNodes();)this._content.firstChild&&this._content.removeChild(this._content.firstChild);else this._content=c.create("div","maplibregl-popup-content",this._container);return this._content.appendChild(ue),this._createCloseButton(),this._update(),this._focusFirstElement(),this}addClassName(ue){return this._container&&this._container.classList.add(ue),this}removeClassName(ue){return this._container&&this._container.classList.remove(ue),this}setOffset(ue){return this.options.offset=ue,this._update(),this}toggleClassName(ue){if(this._container)return this._container.classList.toggle(ue)}setSubpixelPositioning(ue){this.options.subpixelPositioning=ue}_createCloseButton(){this.options.closeButton&&(this._closeButton=c.create("button","maplibregl-popup-close-button",this._content),this._closeButton.type="button",this._closeButton.innerHTML="×",this._closeButton.addEventListener("click",this._onClose))}_focusFirstElement(){if(!this.options.focusAfterOpen||!this._container)return;let ue=this._container.querySelector(Vc);ue&&ue.focus()}},i.RasterDEMTileSource=Zt,i.RasterTileSource=pt,i.ScaleControl=class{constructor(ue){this._onMove=()=>{Ac(this._map,this._container,this.options)},this.setUnit=w=>{this.options.unit=w,Ac(this._map,this._container,this.options)},this.options=Object.assign(Object.assign({},xu),ue)}getDefaultPosition(){return"bottom-left"}onAdd(ue){return this._map=ue,this._container=c.create("div","maplibregl-ctrl maplibregl-ctrl-scale",ue.getContainer()),this._map.on("move",this._onMove),this._onMove(),this._container}onRemove(){c.remove(this._container),this._map.off("move",this._onMove),this._map=void 0}},i.ScrollZoomHandler=Kr,i.Style=Ha,i.TerrainControl=class{constructor(ue){this._toggleTerrain=()=>{this._map.getTerrain()?this._map.setTerrain(null):this._map.setTerrain(this.options),this._updateTerrainIcon()},this._updateTerrainIcon=()=>{this._terrainButton.classList.remove("maplibregl-ctrl-terrain"),this._terrainButton.classList.remove("maplibregl-ctrl-terrain-enabled"),this._map.terrain?(this._terrainButton.classList.add("maplibregl-ctrl-terrain-enabled"),this._terrainButton.title=this._map._getUIString("TerrainControl.Disable")):(this._terrainButton.classList.add("maplibregl-ctrl-terrain"),this._terrainButton.title=this._map._getUIString("TerrainControl.Enable"))},this.options=ue}onAdd(ue){return this._map=ue,this._container=c.create("div","maplibregl-ctrl maplibregl-ctrl-group"),this._terrainButton=c.create("button","maplibregl-ctrl-terrain",this._container),c.create("span","maplibregl-ctrl-icon",this._terrainButton).setAttribute("aria-hidden","true"),this._terrainButton.type="button",this._terrainButton.addEventListener("click",this._toggleTerrain),this._updateTerrainIcon(),this._map.on("terrain",this._updateTerrainIcon),this._container}onRemove(){c.remove(this._container),this._map.off("terrain",this._updateTerrainIcon),this._map=void 0}},i.TwoFingersTouchPitchHandler=Bc,i.TwoFingersTouchRotateHandler=cf,i.TwoFingersTouchZoomHandler=vu,i.TwoFingersTouchZoomRotateHandler=Yi,i.VectorTileSource=ut,i.VideoSource=Nt,i.addSourceType=(ue,w)=>a._(void 0,void 0,void 0,function*(){if(wr(ue))throw new Error(`A source type called "${ue}" already exists.`);((B,Q)=>{sr[B]=Q})(ue,w)}),i.clearPrewarmedResources=function(){let ue=me;ue&&(ue.isPreloaded()&&ue.numActive()===1?(ue.release(_e),me=null):console.warn("Could not clear WebWorkers since there are active Map instances that still reference it. The pre-warmed WebWorker pool can only be cleared when all map instances have been removed with map.remove()"))},i.getMaxParallelImageRequests=function(){return a.a.MAX_PARALLEL_IMAGE_REQUESTS},i.getRTLTextPluginStatus=function(){return Qt().getRTLTextPluginStatus()},i.getVersion=function(){return Ku},i.getWorkerCount=function(){return Ee.workerCount},i.getWorkerUrl=function(){return a.a.WORKER_URL},i.importScriptInWorkers=function(ue){return Ae().broadcast("IS",ue)},i.prewarm=function(){Se().acquire(_e)},i.setMaxParallelImageRequests=function(ue){a.a.MAX_PARALLEL_IMAGE_REQUESTS=ue},i.setRTLTextPlugin=function(ue,w){return Qt().setRTLTextPlugin(ue,w)},i.setWorkerCount=function(ue){Ee.workerCount=ue},i.setWorkerUrl=function(ue){a.a.WORKER_URL=ue}});var n=e;return n})});var fje=ye((Ebr,cje)=>{"use strict";var aw=Dr(),AXt=ru().sanitizeHTML,SXt=SJ(),sje=wx();function lje(e,t){this.subplot=e,this.uid=e.uid+"-"+t,this.index=t,this.idSource="source-"+this.uid,this.idLayer=sje.layoutLayerPrefix+this.uid,this.sourceType=null,this.source=null,this.layerType=null,this.below=null,this.visible=!1}var ag=lje.prototype;ag.update=function(t){this.visible?this.needsNewImage(t)?this.updateImage(t):this.needsNewSource(t)?(this.removeLayer(),this.updateSource(t),this.updateLayer(t)):this.needsNewLayer(t)?this.updateLayer(t):this.updateStyle(t):(this.updateSource(t),this.updateLayer(t)),this.visible=c7(t)};ag.needsNewImage=function(e){var t=this.subplot.map;return t.getSource(this.idSource)&&this.sourceType==="image"&&e.sourcetype==="image"&&(this.source!==e.source||JSON.stringify(this.coordinates)!==JSON.stringify(e.coordinates))};ag.needsNewSource=function(e){return this.sourceType!==e.sourcetype||JSON.stringify(this.source)!==JSON.stringify(e.source)||this.layerType!==e.type};ag.needsNewLayer=function(e){return this.layerType!==e.type||this.below!==this.subplot.belowLookup["layout-"+this.index]};ag.lookupBelow=function(){return this.subplot.belowLookup["layout-"+this.index]};ag.updateImage=function(e){var t=this.subplot.map;t.getSource(this.idSource).updateImage({url:e.source,coordinates:e.coordinates});var r=this.findFollowingMapLayerId(this.lookupBelow());r!==null&&this.subplot.map.moveLayer(this.idLayer,r)};ag.updateSource=function(e){var t=this.subplot.map;if(t.getSource(this.idSource)&&t.removeSource(this.idSource),this.sourceType=e.sourcetype,this.source=e.source,!!c7(e)){var r=MXt(e);t.addSource(this.idSource,r)}};ag.findFollowingMapLayerId=function(e){if(e==="traces")for(var t=this.subplot.getMapLayers(),r=0;r0){for(var r=0;r0}function uje(e){var t={},r={};switch(e.type){case"circle":aw.extendFlat(r,{"circle-radius":e.circle.radius,"circle-color":e.color,"circle-opacity":e.opacity});break;case"line":aw.extendFlat(r,{"line-width":e.line.width,"line-color":e.color,"line-opacity":e.opacity,"line-dasharray":e.line.dash});break;case"fill":aw.extendFlat(r,{"fill-color":e.color,"fill-outline-color":e.fill.outlinecolor,"fill-opacity":e.opacity});break;case"symbol":var n=e.symbol,i=SXt(n.textposition,n.iconsize);aw.extendFlat(t,{"icon-image":n.icon+"-15","icon-size":n.iconsize/10,"text-field":n.text,"text-size":n.textfont.size,"text-anchor":i.anchor,"text-offset":i.offset,"symbol-placement":n.placement}),aw.extendFlat(r,{"icon-color":e.color,"text-color":n.textfont.color,"text-opacity":e.opacity});break;case"raster":aw.extendFlat(r,{"raster-fade-duration":0,"raster-opacity":e.opacity});break}return{layout:t,paint:r}}function MXt(e){var t=e.sourcetype,r=e.source,n={type:t},i;return t==="geojson"?i="data":t==="vector"?i=typeof r=="string"?"url":"tiles":t==="raster"?(i="tiles",n.tileSize=256):t==="image"&&(i="url",n.coordinates=e.coordinates),n[i]=r,e.sourceattribution&&(n.attribution=AXt(e.sourceattribution)),n}cje.exports=function(t,r,n){var i=new lje(t,r);return i.update(n),i}});var _je=ye((kbr,yje)=>{"use strict";var PJ=oje(),IJ=Dr(),vje=ix(),hje=qa(),EXt=ho(),kXt=yv(),f7=vf(),pje=Eg(),CXt=pje.drawMode,LXt=pje.selectMode,PXt=Of().prepSelect,IXt=Of().clearOutline,RXt=Of().clearSelectionsCache,DXt=Of().selectOnClick,ow=wx(),FXt=fje();function gje(e,t){this.id=t,this.gd=e;var r=e._fullLayout,n=e._context;this.container=r._glcontainer.node(),this.isStatic=n.staticPlot,this.uid=r._uid+"-"+this.id,this.div=null,this.xaxis=null,this.yaxis=null,this.createFramework(r),this.map=null,this.styleObj=null,this.traceHash={},this.layerList=[],this.belowLookup={},this.dragging=!1,this.wheeling=!1}var Uh=gje.prototype;Uh.plot=function(e,t,r){var n=this,i;n.map?i=new Promise(function(a,o){n.updateMap(e,t,a,o)}):i=new Promise(function(a,o){n.createMap(e,t,a,o)}),r.push(i)};Uh.createMap=function(e,t,r,n){var i=this,a=t[i.id],o=i.styleObj=mje(a.style),s=a.bounds,l=s?[[s.west,s.south],[s.east,s.north]]:null,u=i.map=new PJ.Map({container:i.div,style:o.style,center:RJ(a.center),zoom:a.zoom,bearing:a.bearing,pitch:a.pitch,maxBounds:l,interactive:!i.isStatic,preserveDrawingBuffer:i.isStatic,doubleClickZoom:!1,boxZoom:!1,attributionControl:!1}).addControl(new PJ.AttributionControl({compact:!0})),c={};u.on("styleimagemissing",function(h){var d=h.id;if(!c[d]&&d.includes("-15")){c[d]=!0;var v=new Image(15,15);v.onload=function(){u.addImage(d,v)},v.crossOrigin="Anonymous",v.src="https://unpkg.com/maki@2.1.0/icons/"+d+".svg"}}),u.setTransformRequest(function(h){return h=h.replace("https://fonts.openmaptiles.org/Open Sans Extrabold","https://fonts.openmaptiles.org/Open Sans Extra Bold"),h=h.replace("https://tiles.basemaps.cartocdn.com/fonts/Open Sans Extrabold","https://fonts.openmaptiles.org/Open Sans Extra Bold"),h=h.replace("https://fonts.openmaptiles.org/Open Sans Regular,Arial Unicode MS Regular","https://fonts.openmaptiles.org/Klokantech Noto Sans Regular"),{url:h}}),u._canvas.style.left="0px",u._canvas.style.top="0px",i.rejectOnError(n),i.isStatic||i.initFx(e,t);var f=[];f.push(new Promise(function(h){u.once("load",h)})),f=f.concat(vje.fetchTraceGeoData(e)),Promise.all(f).then(function(){i.fillBelowLookup(e,t),i.updateData(e),i.updateLayout(t),i.resolveOnRender(r)}).catch(n)};Uh.updateMap=function(e,t,r,n){var i=this,a=i.map,o=t[this.id];i.rejectOnError(n);var s=[],l=mje(o.style);JSON.stringify(i.styleObj)!==JSON.stringify(l)&&(i.styleObj=l,a.setStyle(l.style),i.traceHash={},s.push(new Promise(function(u){a.once("styledata",u)}))),s=s.concat(vje.fetchTraceGeoData(e)),Promise.all(s).then(function(){i.fillBelowLookup(e,t),i.updateData(e),i.updateLayout(t),i.resolveOnRender(r)}).catch(n)};Uh.fillBelowLookup=function(e,t){var r=t[this.id],n=r.layers,i,a,o=this.belowLookup={},s=!1;for(i=0;i1)for(i=0;i-1&&DXt(l.originalEvent,n,[r.xaxis],[r.yaxis],r.id,s),u.indexOf("event")>-1&&f7.click(n,l.originalEvent)}}};Uh.updateFx=function(e){var t=this,r=t.map,n=t.gd;if(t.isStatic)return;function i(l){var u=t.map.unproject(l);return[u.lng,u.lat]}var a=e.dragmode,o;o=function(l,u){if(u.isRect){var c=l.range={};c[t.id]=[i([u.xmin,u.ymin]),i([u.xmax,u.ymax])]}else{var f=l.lassoPoints={};f[t.id]=u.map(i)}};var s=t.dragOptions;t.dragOptions=IJ.extendDeep(s||{},{dragmode:e.dragmode,element:t.div,gd:n,plotinfo:{id:t.id,domain:e[t.id].domain,xaxis:t.xaxis,yaxis:t.yaxis,fillRangeItems:o},xaxes:[t.xaxis],yaxes:[t.yaxis],subplot:t.id}),r.off("click",t.onClickInPanHandler),LXt(a)||CXt(a)?(r.dragPan.disable(),r.on("zoomstart",t.clearOutline),t.dragOptions.prepFn=function(l,u,c){PXt(l,u,c,t.dragOptions,a)},kXt.init(t.dragOptions)):(r.dragPan.enable(),r.off("zoomstart",t.clearOutline),t.div.onmousedown=null,t.div.ontouchstart=null,t.div.removeEventListener("touchstart",t.div._ontouchstart),t.onClickInPanHandler=t.onClickInPanFn(t.dragOptions),r.on("click",t.onClickInPanHandler))};Uh.updateFramework=function(e){var t=e[this.id].domain,r=e._size,n=this.div.style;n.width=r.w*(t.x[1]-t.x[0])+"px",n.height=r.h*(t.y[1]-t.y[0])+"px",n.left=r.l+t.x[0]*r.w+"px",n.top=r.t+(1-t.y[1])*r.h+"px",this.xaxis._offset=r.l+t.x[0]*r.w,this.xaxis._length=r.w*(t.x[1]-t.x[0]),this.yaxis._offset=r.t+(1-t.y[1])*r.h,this.yaxis._length=r.h*(t.y[1]-t.y[0])};Uh.updateLayers=function(e){var t=e[this.id],r=t.layers,n=this.layerList,i;if(r.length!==n.length){for(i=0;i{"use strict";var DJ=Dr(),OXt=k_(),qXt=Yd(),xje=jk();bje.exports=function(t,r,n){OXt(t,r,n,{type:"map",attributes:xje,handleDefaults:BXt,partition:"y"})};function BXt(e,t,r){r("style"),r("center.lon"),r("center.lat"),r("zoom"),r("bearing"),r("pitch");var n=r("bounds.west"),i=r("bounds.east"),a=r("bounds.south"),o=r("bounds.north");(n===void 0||i===void 0||a===void 0||o===void 0)&&delete t.bounds,qXt(e,t,{name:"layers",handleItemDefaults:NXt}),t._input=e}function NXt(e,t){function r(l,u){return DJ.coerce(e,t,xje.layers,l,u)}var n=r("visible");if(n){var i=r("sourcetype"),a=i==="raster"||i==="image";r("source"),r("sourceattribution"),i==="vector"&&r("sourcelayer"),i==="image"&&r("coordinates");var o;a&&(o="raster");var s=r("type",o);a&&s!=="raster"&&(s=t.type="raster",DJ.log("Source types *raster* and *image* must drawn *raster* layer type.")),r("below"),r("color"),r("opacity"),r("minzoom"),r("maxzoom"),s==="circle"&&r("circle.radius"),s==="line"&&(r("line.width"),r("line.dash")),s==="fill"&&r("fill.outlinecolor"),s==="symbol"&&(r("symbol.icon"),r("symbol.iconsize"),r("symbol.text"),DJ.coerceFont(r,"symbol.textfont",void 0,{noFontVariant:!0,noFontShadow:!0,noFontLineposition:!0,noFontTextcase:!0}),r("symbol.textposition"),r("symbol.placement"))}}});var d7=ye(l0=>{"use strict";var h7=Dr(),Tje=h7.strTranslate,UXt=h7.strScale,VXt=Id().getSubplotCalcData,GXt=Wp(),HXt=Oa(),Aje=So(),jXt=ru(),WXt=_je(),Tx="map";l0.name=Tx;l0.attr="subplot";l0.idRoot=Tx;l0.idRegex=l0.attrRegex=h7.counterRegex(Tx);l0.attributes={subplot:{valType:"subplotid",dflt:"map",editType:"calc"}};l0.layoutAttributes=jk();l0.supplyLayoutDefaults=wje();l0.plot=function(t){for(var r=t._fullLayout,n=t.calcdata,i=r._subplots[Tx],a=0;a_/2){var b=f.split("|").join("
");d.text(b).attr("data-unformatted",b).call(jXt.convertToTspans,e),v=Aje.bBox(d.node())}d.attr("transform",Tje(-3,-v.height+8)),h.insert("rect",".static-attribution").attr({x:-v.width-6,y:-v.height-3,width:v.width+6,height:v.height+3,fill:"rgba(255, 255, 255, 0.75)"});var p=1;v.width+6>_&&(p=_/(v.width+6));var k=[n.l+n.w*o.x[1],n.t+n.h*(1-o.y[0])];h.attr("transform",Tje(k[0],k[1])+UXt(p))}};l0.updateFx=function(e){for(var t=e._fullLayout,r=t._subplots[Tx],n=0;n{"use strict";Sje.exports={attributes:n7(),supplyDefaults:qHe(),colorbar:$d(),formatLabels:AJ(),calc:pF(),plot:$He(),hoverPoints:u7().hoverPoints,eventData:rje(),selectPoints:nje(),styleOnSelect:function(e,t){if(t){var r=t[0].trace;r._glTrace.update(t)}},moduleType:"trace",name:"scattermap",basePlotModule:d7(),categories:["map","gl","symbols","showLegend","scatter-like"],meta:{}}});var kje=ye((Ibr,Eje)=>{"use strict";Eje.exports=Mje()});var FJ=ye((Rbr,Cje)=>{"use strict";var d1=t5(),XXt=Tu(),{hovertemplateAttrs:ZXt,templatefallbackAttrs:YXt}=Ll(),KXt=Gl(),Ax=Ao().extendFlat;Cje.exports=Ax({locations:{valType:"data_array",editType:"calc"},z:{valType:"data_array",editType:"calc"},geojson:{valType:"any",editType:"calc"},featureidkey:Ax({},d1.featureidkey,{}),below:{valType:"string",editType:"plot"},text:d1.text,hovertext:d1.hovertext,marker:{line:{color:Ax({},d1.marker.line.color,{editType:"plot"}),width:Ax({},d1.marker.line.width,{editType:"plot"}),editType:"calc"},opacity:Ax({},d1.marker.opacity,{editType:"plot"}),editType:"calc"},selected:{marker:{opacity:Ax({},d1.selected.marker.opacity,{editType:"plot"}),editType:"plot"},editType:"plot"},unselected:{marker:{opacity:Ax({},d1.unselected.marker.opacity,{editType:"plot"}),editType:"plot"},editType:"plot"},hoverinfo:d1.hoverinfo,hovertemplate:ZXt({},{keys:["properties"]}),hovertemplatefallback:YXt(),showlegend:Ax({},KXt.showlegend,{dflt:!1})},XXt("",{cLetter:"z",editTypeOverride:"calc"}))});var Pje=ye((Dbr,Lje)=>{"use strict";var Yk=Dr(),JXt=Qh(),$Xt=FJ();Lje.exports=function(t,r,n,i){function a(c,f){return Yk.coerce(t,r,$Xt,c,f)}var o=a("locations"),s=a("z"),l=a("geojson");if(!Yk.isArrayOrTypedArray(o)||!o.length||!Yk.isArrayOrTypedArray(s)||!s.length||!(typeof l=="string"&&l!==""||Yk.isPlainObject(l))){r.visible=!1;return}a("featureidkey"),r._length=Math.min(o.length,s.length),a("below"),a("text"),a("hovertext"),a("hovertemplate"),a("hovertemplatefallback");var u=a("marker.line.width");u&&a("marker.line.color"),a("marker.opacity"),JXt(t,r,i,a,{prefix:"",cLetter:"z"}),Yk.coerceSelectionMarkerOpacity(r,a)}});var zJ=ye((Fbr,Dje)=>{"use strict";var QXt=Eo(),v1=Dr(),eZt=tc(),tZt=So(),rZt=tx().makeBlank,Ije=ix();function iZt(e){var t=e[0].trace,r=t.visible===!0&&t._length!==0,n={layout:{visibility:"none"},paint:{}},i={layout:{visibility:"none"},paint:{}},a=t._opts={fill:n,line:i,geojson:rZt()};if(!r)return a;var o=Ije.extractTraceFeature(e);if(!o)return a;var s=eZt.makeColorScaleFuncFromTrace(t),l=t.marker,u=l.line||{},c;v1.isArrayOrTypedArray(l.opacity)&&(c=function(k){var E=k.mo;return QXt(E)?+v1.constrain(E,0,1):0});var f;v1.isArrayOrTypedArray(u.color)&&(f=function(k){return k.mlc});var h;v1.isArrayOrTypedArray(u.width)&&(h=function(k){return k.mlw});for(var d=0;d{"use strict";var zje=zJ().convert,nZt=zJ().convertOnSelect,Fje=wx().traceLayerPrefix;function Oje(e,t){this.type="choroplethmap",this.subplot=e,this.uid=t,this.sourceId="source-"+t,this.layerList=[["fill",Fje+t+"-fill"],["line",Fje+t+"-line"]],this.below=null}var L5=Oje.prototype;L5.update=function(e){this._update(zje(e)),e[0].trace._glTrace=this};L5.updateOnSelect=function(e){this._update(nZt(e))};L5._update=function(e){var t=this.subplot,r=this.layerList,n=t.belowLookup["trace-"+this.uid];t.map.getSource(this.sourceId).setData(e.geojson),n!==this.below&&(this._removeLayers(),this._addLayers(e,n),this.below=n);for(var i=0;i=0;r--)e.removeLayer(t[r][1])};L5.dispose=function(){var e=this.subplot.map;this._removeLayers(),e.removeSource(this.sourceId)};qje.exports=function(t,r){var n=r[0].trace,i=new Oje(t,n.uid),a=i.sourceId,o=zje(r),s=i.below=t.belowLookup["trace-"+n.uid];return t.map.addSource(a,{type:"geojson",data:o.geojson}),i._addLayers(o,s),r[0].trace._glTrace=i,i}});var Uje=ye((Obr,Nje)=>{"use strict";Nje.exports={attributes:FJ(),supplyDefaults:Pje(),colorbar:S_(),calc:zF(),plot:Bje(),hoverPoints:qF(),eventData:BF(),selectPoints:NF(),styleOnSelect:function(e,t){if(t){var r=t[0].trace;r._glTrace.updateOnSelect(t)}},getBelow:function(e,t){for(var r=t.getMapLayers(),n=r.length-2;n>=0;n--){var i=r[n].id;if(typeof i=="string"&&i.indexOf("water")===0){for(var a=n+1;a{"use strict";Vje.exports=Uje()});var qJ=ye((Bbr,jje)=>{"use strict";var aZt=Tu(),{hovertemplateAttrs:oZt,templatefallbackAttrs:sZt}=Ll(),Hje=Gl(),v7=n7(),OJ=Ao().extendFlat;jje.exports=OJ({lon:v7.lon,lat:v7.lat,z:{valType:"data_array",editType:"calc"},radius:{valType:"number",editType:"plot",arrayOk:!0,min:1,dflt:30},below:{valType:"string",editType:"plot"},text:v7.text,hovertext:v7.hovertext,hoverinfo:OJ({},Hje.hoverinfo,{flags:["lon","lat","z","text","name"]}),hovertemplate:oZt(),hovertemplatefallback:sZt(),showlegend:OJ({},Hje.showlegend,{dflt:!1})},aZt("",{cLetter:"z",editTypeOverride:"calc"}))});var Xje=ye((Nbr,Wje)=>{"use strict";var lZt=Dr(),uZt=Qh(),cZt=qJ();Wje.exports=function(t,r,n,i){function a(u,c){return lZt.coerce(t,r,cZt,u,c)}var o=a("lon")||[],s=a("lat")||[],l=Math.min(o.length,s.length);if(!l){r.visible=!1;return}r._length=l,a("z"),a("radius"),a("below"),a("text"),a("hovertext"),a("hovertemplate"),a("hovertemplatefallback"),uZt(t,r,i,a,{prefix:"",cLetter:"z"})}});var Kje=ye((Ubr,Yje)=>{"use strict";var BJ=Eo(),fZt=Dr().isArrayOrTypedArray,NJ=fs().BADNUM,hZt=gv(),Zje=Dr()._;Yje.exports=function(t,r){for(var n=r._length,i=new Array(n),a=r.z,o=fZt(a)&&a.length,s=0;s{"use strict";var dZt=Eo(),UJ=Dr(),Jje=ka(),$je=tc(),Qje=fs().BADNUM,vZt=tx().makeBlank;eWe.exports=function(t){var r=t[0].trace,n=r.visible===!0&&r._length!==0,i={layout:{visibility:"none"},paint:{}},a=r._opts={heatmap:i,geojson:vZt()};if(!n)return a;var o=[],s,l=r.z,u=r.radius,c=UJ.isArrayOrTypedArray(l)&&l.length,f=UJ.isArrayOrTypedArray(u);for(s=0;s0?+u[s]:0),o.push({type:"Feature",geometry:{type:"Point",coordinates:d},properties:v})}}var b=$je.extractOpts(r),p=b.reversescale?$je.flipScale(b.colorscale):b.colorscale,k=p[0][1],E=Jje.opacity(k)<1?k:Jje.addOpacity(k,0),S=["interpolate",["linear"],["heatmap-density"],0,E];for(s=1;s{"use strict";var rWe=tWe(),pZt=wx().traceLayerPrefix;function 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n$=ye((u2r,PXe)=>{"use strict";PXe.exports={defaultNumberFontSize:80,bulletNumberDomainSize:.25,bulletPadding:.025,innerRadius:.75,valueThickness:.5,titlePadding:5,horizontalPadding:10}});var DXe=ye((c2r,RXe)=>{"use strict";var ty=Dr(),I7=i$(),mYt=Cc().defaults,IXe=vl(),yYt=Yd(),P7=n$(),_Yt=bb(),xYt=M3(),bYt=e_(),wYt=t_();function TYt(e,t,r,n){function i(x,C){return ty.coerce(e,t,I7,x,C)}mYt(t,n,i),i("mode"),t._hasNumber=t.mode.indexOf("number")!==-1,t._hasDelta=t.mode.indexOf("delta")!==-1,t._hasGauge=t.mode.indexOf("gauge")!==-1;var a=i("value");t._range=[0,typeof a=="number"?1.5*a:1];var o=new Array(2),s;if(t._hasNumber){i("number.valueformat");var l=ty.extendFlat({},n.font);l.size=void 0,ty.coerceFont(i,"number.font",l),t.number.font.size===void 0&&(t.number.font.size=P7.defaultNumberFontSize,o[0]=!0),i("number.prefix"),i("number.suffix"),s=t.number.font.size}var u;if(t._hasDelta){var c=ty.extendFlat({},n.font);c.size=void 0,ty.coerceFont(i,"delta.font",c),t.delta.font.size===void 0&&(t.delta.font.size=(t._hasNumber?.5:1)*(s||P7.defaultNumberFontSize),o[1]=!0),i("delta.reference",t.value),i("delta.relative"),i("delta.valueformat",t.delta.relative?"2%":""),i("delta.increasing.symbol"),i("delta.increasing.color"),i("delta.decreasing.symbol"),i("delta.decreasing.color"),i("delta.position"),i("delta.prefix"),i("delta.suffix"),u=t.delta.font.size}t._scaleNumbers=(!t._hasNumber||o[0])&&(!t._hasDelta||o[1])||!1;var f=ty.extendFlat({},n.font);f.size=.25*(s||u||P7.defaultNumberFontSize),ty.coerceFont(i,"title.font",f),i("title.text");var h,d,v,_;function b(x,C){return ty.coerce(h,d,I7.gauge,x,C)}function p(x,C){return ty.coerce(v,_,I7.gauge.axis,x,C)}if(t._hasGauge){h=e.gauge,h||(h={}),d=IXe.newContainer(t,"gauge"),b("shape");var k=t._isBullet=t.gauge.shape==="bullet";k||i("title.align","center");var E=t._isAngular=t.gauge.shape==="angular";E||i("align","center"),b("bgcolor",n.paper_bgcolor),b("borderwidth"),b("bordercolor"),b("bar.color"),b("bar.line.color"),b("bar.line.width");var S=P7.valueThickness*(t.gauge.shape==="bullet"?.5:1);b("bar.thickness",S),yYt(h,d,{name:"steps",handleItemDefaults:AYt}),b("threshold.value"),b("threshold.thickness"),b("threshold.line.width"),b("threshold.line.color"),v={},h&&(v=h.axis||{}),_=IXe.newContainer(d,"axis"),p("visible"),t._range=p("range",t._range);var L={font:n.font,noAutotickangles:!0,outerTicks:!0,noTicklabelshift:!0,noTicklabelstandoff:!0};_Yt(v,_,p,"linear"),wYt(v,_,p,"linear",L),bYt(v,_,p,"linear",L),xYt(v,_,p,L)}else i("title.align","center"),i("align","center"),t._isAngular=t._isBullet=!1;t._length=null}function AYt(e,t){function r(n,i){return ty.coerce(e,t,I7.gauge.steps,n,i)}r("color"),r("line.color"),r("line.width"),r("range"),r("thickness")}RXe.exports={supplyDefaults:TYt}});var zXe=ye((f2r,FXe)=>{"use strict";function SYt(e,t){var r=[],n=t.value;typeof t._lastValue!="number"&&(t._lastValue=t.value);var i=t._lastValue,a=i;return t._hasDelta&&typeof t.delta.reference=="number"&&(a=t.delta.reference),r[0]={y:n,lastY:i,delta:n-a,relativeDelta:(n-a)/a},r}FXe.exports={calc:SYt}});var VXe=ye((h2r,UXe)=>{"use strict";var dw=Oa(),MYt=(F2(),ob(D2)).interpolate,OXe=(F2(),ob(D2)).interpolateNumber,Ex=Dr(),EYt=Ex.strScale,rC=Ex.strTranslate,kYt=Ex.rad2deg,CYt=$h().MID_SHIFT,hw=So(),uw=n$(),D7=ru(),sv=ho(),LYt=i4(),PYt=uI(),IYt=Rd(),q5=ka(),a$={left:"start",center:"middle",right:"end"},cw={left:0,center:.5,right:1},qXe=/[yzafpnµmkMGTPEZY]/;function iC(e){return e&&e.duration>0}UXe.exports=function(t,r,n,i){var a=t._fullLayout,o;iC(n)&&i&&(o=i()),Ex.makeTraceGroups(a._indicatorlayer,r,"trace").each(function(s){var l=s[0],u=l.trace,c=dw.select(this),f=u._hasGauge,h=u._isAngular,d=u._isBullet,v=u.domain,_={w:a._size.w*(v.x[1]-v.x[0]),h:a._size.h*(v.y[1]-v.y[0]),l:a._size.l+a._size.w*v.x[0],r:a._size.r+a._size.w*(1-v.x[1]),t:a._size.t+a._size.h*(1-v.y[1]),b:a._size.b+a._size.h*v.y[0]},b=_.l+_.w/2,p=_.t+_.h/2,k=Math.min(_.w/2,_.h),E=uw.innerRadius*k,S,L,x,C=u.align||"center";if(L=p,!f)S=_.l+cw[C]*_.w,x=function(j){return BXe(j,_.w,_.h)};else if(h&&(S=b,L=p+k/2,x=function(j){return OYt(j,.9*E)}),d){var M=uw.bulletPadding,g=1-uw.bulletNumberDomainSize+M;S=_.l+(g+(1-g)*cw[C])*_.w,x=function(j){return BXe(j,(uw.bulletNumberDomainSize-M)*_.w,_.h)}}FYt(t,c,s,{numbersX:S,numbersY:L,numbersScaler:x,transitionOpts:n,onComplete:o});var P,T;f&&(P={range:u.gauge.axis.range,color:u.gauge.bgcolor,line:{color:u.gauge.bordercolor,width:0},thickness:1},T={range:u.gauge.axis.range,color:"rgba(0, 0, 0, 0)",line:{color:u.gauge.bordercolor,width:u.gauge.borderwidth},thickness:1});var z=c.selectAll("g.angular").data(h?s:[]);z.exit().remove();var O=c.selectAll("g.angularaxis").data(h?s:[]);O.exit().remove(),h&&DYt(t,c,s,{radius:k,innerRadius:E,gauge:z,layer:O,size:_,gaugeBg:P,gaugeOutline:T,transitionOpts:n,onComplete:o});var V=c.selectAll("g.bullet").data(d?s:[]);V.exit().remove();var G=c.selectAll("g.bulletaxis").data(d?s:[]);G.exit().remove(),d&&RYt(t,c,s,{gauge:V,layer:G,size:_,gaugeBg:P,gaugeOutline:T,transitionOpts:n,onComplete:o});var Z=c.selectAll("text.title").data(s);Z.exit().remove(),Z.enter().append("text").classed("title",!0),Z.attr("text-anchor",function(){return d?a$.right:a$[u.title.align]}).text(u.title.text).call(hw.font,u.title.font).call(D7.convertToTspans,t),Z.attr("transform",function(){var j=_.l+_.w*cw[u.title.align],N,H=uw.titlePadding,te=hw.bBox(Z.node());if(f){if(h)if(u.gauge.axis.visible){var oe=hw.bBox(O.node());N=oe.top-H-te.bottom}else N=_.t+_.h/2-k/2-te.bottom-H;d&&(N=L-(te.top+te.bottom)/2,j=_.l-uw.bulletPadding*_.w)}else N=u._numbersTop-H-te.bottom;return rC(j,N)})})};function RYt(e,t,r,n){var i=r[0].trace,a=n.gauge,o=n.layer,s=n.gaugeBg,l=n.gaugeOutline,u=n.size,c=i.domain,f=n.transitionOpts,h=n.onComplete,d,v,_,b,p;a.enter().append("g").classed("bullet",!0),a.attr("transform",rC(u.l,u.t)),o.enter().append("g").classed("bulletaxis",!0).classed("crisp",!0),o.selectAll("g.xbulletaxistick,path,text").remove();var k=u.h,E=i.gauge.bar.thickness*k,S=c.x[0],L=c.x[0]+(c.x[1]-c.x[0])*(i._hasNumber||i._hasDelta?1-uw.bulletNumberDomainSize:1);d=tC(e,i.gauge.axis),d._id="xbulletaxis",d.domain=[S,L],d.setScale(),v=sv.calcTicks(d),_=sv.makeTransTickFn(d),b=sv.getTickSigns(d)[2],p=u.t+u.h,d.visible&&(sv.drawTicks(e,d,{vals:d.ticks==="inside"?sv.clipEnds(d,v):v,layer:o,path:sv.makeTickPath(d,p,b),transFn:_}),sv.drawLabels(e,d,{vals:v,layer:o,transFn:_,labelFns:sv.makeLabelFns(d,p)}));function x(O){O.attr("width",function(V){return Math.max(0,d.c2p(V.range[1])-d.c2p(V.range[0]))}).attr("x",function(V){return d.c2p(V.range[0])}).attr("y",function(V){return .5*(1-V.thickness)*k}).attr("height",function(V){return V.thickness*k})}var C=[s].concat(i.gauge.steps),M=a.selectAll("g.bg-bullet").data(C);M.enter().append("g").classed("bg-bullet",!0).append("rect"),M.select("rect").call(x).call(fw),M.exit().remove();var g=a.selectAll("g.value-bullet").data([i.gauge.bar]);g.enter().append("g").classed("value-bullet",!0).append("rect"),g.select("rect").attr("height",E).attr("y",(k-E)/2).call(fw),iC(f)?g.select("rect").transition().duration(f.duration).ease(f.easing).each("end",function(){h&&h()}).each("interrupt",function(){h&&h()}).attr("width",Math.max(0,d.c2p(Math.min(i.gauge.axis.range[1],r[0].y)))):g.select("rect").attr("width",typeof r[0].y=="number"?Math.max(0,d.c2p(Math.min(i.gauge.axis.range[1],r[0].y))):0),g.exit().remove();var P=r.filter(function(){return i.gauge.threshold.value||i.gauge.threshold.value===0}),T=a.selectAll("g.threshold-bullet").data(P);T.enter().append("g").classed("threshold-bullet",!0).append("line"),T.select("line").attr("x1",d.c2p(i.gauge.threshold.value)).attr("x2",d.c2p(i.gauge.threshold.value)).attr("y1",(1-i.gauge.threshold.thickness)/2*k).attr("y2",(1-(1-i.gauge.threshold.thickness)/2)*k).call(q5.stroke,i.gauge.threshold.line.color).style("stroke-width",i.gauge.threshold.line.width),T.exit().remove();var z=a.selectAll("g.gauge-outline").data([l]);z.enter().append("g").classed("gauge-outline",!0).append("rect"),z.select("rect").call(x).call(fw),z.exit().remove()}function DYt(e,t,r,n){var i=r[0].trace,a=n.size,o=n.radius,s=n.innerRadius,l=n.gaugeBg,u=n.gaugeOutline,c=[a.l+a.w/2,a.t+a.h/2+o/2],f=n.gauge,h=n.layer,d=n.transitionOpts,v=n.onComplete,_=Math.PI/2;function b(_e){var Ee=i.gauge.axis.range[0],Ce=i.gauge.axis.range[1],me=(_e-Ee)/(Ce-Ee)*Math.PI-_;return me<-_?-_:me>_?_:me}function p(_e){return dw.svg.arc().innerRadius((s+o)/2-_e/2*(o-s)).outerRadius((s+o)/2+_e/2*(o-s)).startAngle(-_)}function k(_e){_e.attr("d",function(Ee){return p(Ee.thickness).startAngle(b(Ee.range[0])).endAngle(b(Ee.range[1]))()})}var E,S,L,x;f.enter().append("g").classed("angular",!0),f.attr("transform",rC(c[0],c[1])),h.enter().append("g").classed("angularaxis",!0).classed("crisp",!0),h.selectAll("g.xangularaxistick,path,text").remove(),E=tC(e,i.gauge.axis),E.type="linear",E.range=i.gauge.axis.range,E._id="xangularaxis",E.ticklabeloverflow="allow",E.setScale();var C=function(_e){return(E.range[0]-_e.x)/(E.range[1]-E.range[0])*Math.PI+Math.PI},M={},g=sv.makeLabelFns(E,0),P=g.labelStandoff;M.xFn=function(_e){var Ee=C(_e);return Math.cos(Ee)*P},M.yFn=function(_e){var Ee=C(_e),Ce=Math.sin(Ee)>0?.2:1;return-Math.sin(Ee)*(P+_e.fontSize*Ce)+Math.abs(Math.cos(Ee))*(_e.fontSize*CYt)},M.anchorFn=function(_e){var Ee=C(_e),Ce=Math.cos(Ee);return 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N=j.select("path");iC(d)?(N.transition().duration(d.duration).ease(d.easing).each("end",function(){v&&v()}).each("interrupt",function(){v&&v()}).attrTween("d",zYt(Z,b(r[0].lastY),b(r[0].y))),i._lastValue=r[0].y):N.attr("d",typeof r[0].y=="number"?Z.endAngle(b(r[0].y)):"M0,0Z"),N.call(fw),j.exit().remove(),V=[];var H=i.gauge.threshold.value;(H||H===0)&&V.push({range:[H,H],color:i.gauge.threshold.color,line:{color:i.gauge.threshold.line.color,width:i.gauge.threshold.line.width},thickness:i.gauge.threshold.thickness});var te=f.selectAll("g.threshold-arc").data(V);te.enter().append("g").classed("threshold-arc",!0).append("path"),te.select("path").call(k).call(fw),te.exit().remove();var oe=f.selectAll("g.gauge-outline").data([u]);oe.enter().append("g").classed("gauge-outline",!0).append("path"),oe.select("path").call(k).call(fw),oe.exit().remove()}function FYt(e,t,r,n){var i=r[0].trace,a=n.numbersX,o=n.numbersY,s=i.align||"center",l=a$[s],u=n.transitionOpts,c=n.onComplete,f=Ex.ensureSingle(t,"g","numbers"),h,d,v,_=[];i._hasNumber&&_.push("number"),i._hasDelta&&(_.push("delta"),i.delta.position==="left"&&_.reverse());var b=f.selectAll("text").data(_);b.enter().append("text"),b.attr("text-anchor",function(){return l}).attr("class",function(T){return T}).attr("x",null).attr("y",null).attr("dx",null).attr("dy",null),b.exit().remove();function p(T,z,O,V){if(T.match("s")&&O>=0!=V>=0&&!z(O).slice(-1).match(qXe)&&!z(V).slice(-1).match(qXe)){var G=T.slice().replace("s","f").replace(/\d+/,function(j){return parseInt(j)-1}),Z=tC(e,{tickformat:G});return function(j){return Math.abs(j)<1?sv.tickText(Z,j).text:z(j)}}else return z}function k(){var T=tC(e,{tickformat:i.number.valueformat},i._range);T.setScale(),sv.prepTicks(T);var z=function(j){return sv.tickText(T,j).text},O=i.number.suffix,V=i.number.prefix,G=f.select("text.number");function Z(){var j=typeof r[0].y=="number"?V+z(r[0].y)+O:"-";G.text(j).call(hw.font,i.number.font).call(D7.convertToTspans,e)}return iC(u)?G.transition().duration(u.duration).ease(u.easing).each("end",function(){Z(),c&&c()}).each("interrupt",function(){Z(),c&&c()}).attrTween("text",function(){var j=dw.select(this),N=OXe(r[0].lastY,r[0].y);i._lastValue=r[0].y;var H=p(i.number.valueformat,z,r[0].lastY,r[0].y);return function(te){j.text(V+H(N(te))+O)}}):Z(),h=NXe(V+z(r[0].y)+O,i.number.font,l,e),G}function E(){var T=tC(e,{tickformat:i.delta.valueformat},i._range);T.setScale(),sv.prepTicks(T);var z=function(te){return sv.tickText(T,te).text},O=i.delta.suffix,V=i.delta.prefix,G=function(te){var oe=i.delta.relative?te.relativeDelta:te.delta;return oe},Z=function(te,oe){return te===0||typeof te!="number"||isNaN(te)?"-":(te>0?i.delta.increasing.symbol:i.delta.decreasing.symbol)+V+oe(te)+O},j=function(te){return te.delta>=0?i.delta.increasing.color:i.delta.decreasing.color};i._deltaLastValue===void 0&&(i._deltaLastValue=G(r[0]));var N=f.select("text.delta");N.call(hw.font,i.delta.font).call(q5.fill,j({delta:i._deltaLastValue}));function H(){N.text(Z(G(r[0]),z)).call(q5.fill,j(r[0])).call(D7.convertToTspans,e)}return iC(u)?N.transition().duration(u.duration).ease(u.easing).tween("text",function(){var te=dw.select(this),oe=G(r[0]),_e=i._deltaLastValue,Ee=p(i.delta.valueformat,z,_e,oe),Ce=OXe(_e,oe);return i._deltaLastValue=oe,function(me){te.text(Z(Ce(me),Ee)),te.call(q5.fill,j({delta:Ce(me)}))}}).each("end",function(){H(),c&&c()}).each("interrupt",function(){H(),c&&c()}):H(),d=NXe(Z(G(r[0]),z),i.delta.font,l,e),N}var S=i.mode+i.align,L;if(i._hasDelta&&(L=E(),S+=i.delta.position+i.delta.font.size+i.delta.font.family+i.delta.valueformat,S+=i.delta.increasing.symbol+i.delta.decreasing.symbol,v=d),i._hasNumber&&(k(),S+=i.number.font.size+i.number.font.family+i.number.valueformat+i.number.suffix+i.number.prefix,v=h),i._hasDelta&&i._hasNumber){var x=[(h.left+h.right)/2,(h.top+h.bottom)/2],C=[(d.left+d.right)/2,(d.top+d.bottom)/2],M,g,P=.75*i.delta.font.size;i.delta.position==="left"&&(M=R7(i,"deltaPos",0,-1*(h.width*cw[i.align]+d.width*(1-cw[i.align])+P),S,Math.min),g=x[1]-C[1],v={width:h.width+d.width+P,height:Math.max(h.height,d.height),left:d.left+M,right:h.right,top:Math.min(h.top,d.top+g),bottom:Math.max(h.bottom,d.bottom+g)}),i.delta.position==="right"&&(M=R7(i,"deltaPos",0,h.width*(1-cw[i.align])+d.width*cw[i.align]+P,S,Math.max),g=x[1]-C[1],v={width:h.width+d.width+P,height:Math.max(h.height,d.height),left:h.left,right:d.right+M,top:Math.min(h.top,d.top+g),bottom:Math.max(h.bottom,d.bottom+g)}),i.delta.position==="bottom"&&(M=null,g=d.height,v={width:Math.max(h.width,d.width),height:h.height+d.height,left:Math.min(h.left,d.left),right:Math.max(h.right,d.right),top:h.bottom-h.height,bottom:h.bottom+d.height}),i.delta.position==="top"&&(M=null,g=h.top,v={width:Math.max(h.width,d.width),height:h.height+d.height,left:Math.min(h.left,d.left),right:Math.max(h.right,d.right),top:h.bottom-h.height-d.height,bottom:h.bottom}),L.attr({dx:M,dy:g})}(i._hasNumber||i._hasDelta)&&f.attr("transform",function(){var T=n.numbersScaler(v);S+=T[2];var z=R7(i,"numbersScale",1,T[0],S,Math.min),O;i._scaleNumbers||(z=1),i._isAngular?O=o-z*v.bottom:O=o-z*(v.top+v.bottom)/2,i._numbersTop=z*v.top+O;var V=v[s];s==="center"&&(V=(v.left+v.right)/2);var G=a-z*V;return G=R7(i,"numbersTranslate",0,G,S,Math.max),rC(G,O)+EYt(z)})}function fw(e){e.each(function(t){q5.stroke(dw.select(this),t.line.color)}).each(function(t){q5.fill(dw.select(this),t.color)}).style("stroke-width",function(t){return t.line.width})}function zYt(e,t,r){return function(){var n=MYt(t,r);return function(i){return e.endAngle(n(i))()}}}function tC(e,t,r){var n=e._fullLayout,i=Ex.extendFlat({type:"linear",ticks:"outside",range:r,showline:!0},t),a={type:"linear",_id:"x"+t._id},o={letter:"x",font:n.font,noAutotickangles:!0,noHover:!0,noTickson:!0};function s(l,u){return Ex.coerce(i,a,IYt,l,u)}return LYt(i,a,s,o,n),PYt(i,a,s,o),a}function BXe(e,t,r){var n=Math.min(t/e.width,r/e.height);return[n,e,t+"x"+r]}function OYt(e,t){var 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Oer(p,a,t),qer(k,a,o,t),t.hovertemplate=a.hovertemplate,t.color=zer(a,p),t.xLabelVal=t.yLabelVal=void 0,p.s<0&&(t.idealAlign="left"),[t]}}});var sQe=ye((f3r,oQe)=>{"use strict";oQe.exports={moduleType:"trace",name:"barpolar",basePlotModule:y9(),categories:["polar","bar","showLegend"],attributes:Q$(),layoutAttributes:eQ(),supplyDefaults:Y$e(),supplyLayoutDefaults:J$e(),calc:tQ().calc,crossTraceCalc:tQ().crossTraceCalc,plot:iQe(),colorbar:$d(),formatLabels:w9(),style:N0().style,styleOnSelect:N0().styleOnSelect,hoverPoints:aQe(),selectPoints:kT(),meta:{}}});var uQe=ye((h3r,lQe)=>{"use strict";lQe.exports=sQe()});var nQ=ye((d3r,cQe)=>{"use strict";cQe.exports={attr:"subplot",name:"smith",axisNames:["realaxis","imaginaryaxis"],axisName2dataArray:{imaginaryaxis:"imag",realaxis:"real"}}});var aQ=ye((v3r,vQe)=>{"use strict";var 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mQe=ye((p3r,gQe)=>{"use strict";var $5=Dr(),Her=ka(),jer=vl(),Wer=k_(),Xer=Id().getSubplotData,Zer=t_(),Yer=e_(),Ker=t4(),Jer=ym(),Q5=aQ(),oQ=nQ(),pQe=oQ.axisNames,$er=etr(function(e){return $5.isTypedArray(e)&&(e=Array.from(e)),e.slice().reverse().map(function(t){return-t}).concat([0]).concat(e)},String);function Qer(e,t,r,n){var i=r("bgcolor");n.bgColor=Her.combine(i,n.paper_bgcolor);var a=Xer(n.fullData,oQ.name,n.id),o=n.layoutOut,s;function l(L,x){return r(s+"."+L,x)}for(var u=0;u{"use strict";var ttr=Id().getSubplotCalcData,rtr=Dr().counterRegex,itr=Z$(),_Qe=nQ(),xQe=_Qe.attr,xw=_Qe.name,yQe=rtr(xw),bQe={};bQe[xQe]={valType:"subplotid",dflt:xw,editType:"calc"};function ntr(e){for(var t=e._fullLayout,r=e.calcdata,n=t._subplots[xw],i=0;i{"use 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kQe=ye((y3r,EQe)=>{"use strict";var k9=Dr(),tS=Ru(),ctr=$p(),ftr=R0(),MQe=tT(),htr=D0(),dtr=Rg(),vtr=Sm().PTS_LINESONLY,ptr=sQ();EQe.exports=function(t,r,n,i){function a(l,u){return k9.coerce(t,r,ptr,l,u)}var o=gtr(t,r,i,a);if(!o){r.visible=!1;return}a("mode",o{"use strict";var CQe=ho();LQe.exports=function(t,r,n){var i={},a=n[r.subplot]._subplot;return i.realLabel=CQe.tickText(a.radialAxis,t.real,!0).text,i.imagLabel=CQe.tickText(a.angularAxis,t.imag,!0).text,i}});var DQe=ye((x3r,RQe)=>{"use strict";var IQe=Eo(),mtr=fs().BADNUM,ytr=F0(),_tr=km(),xtr=z0(),btr=O0().calcMarkerSize;RQe.exports=function(t,r){for(var n=t._fullLayout,i=r.subplot,a=n[i].realaxis,o=n[i].imaginaryaxis,s=a.makeCalcdata(r,"real"),l=o.makeCalcdata(r,"imag"),u=r._length,c=new Array(u),f=0;f{"use strict";var wtr=sT(),FQe=fs().BADNUM,Ttr=j$(),Atr=Ttr.smith;zQe.exports=function(t,r,n){for(var i=r.layers.frontplot.select("g.scatterlayer"),a=r.xaxis,o=r.yaxis,s={xaxis:a,yaxis:o,plot:r.framework,layerClipId:r._hasClipOnAxisFalse?r.clipIds.forTraces:null},l=0;l{"use strict";var Str=fT();function Mtr(e,t,r,n){var i=Str(e,t,r,n);if(!(!i||i[0].index===!1)){var a=i[0];if(a.index===void 0)return i;var o=e.subplot,s=a.cd[a.index],l=a.trace;if(o.isPtInside(s))return a.xLabelVal=void 0,a.yLabelVal=void 0,qQe(s,l,o,a),a.hovertemplate=l.hovertemplate,i}}function qQe(e,t,r,n){var i=r.radialAxis,a=r.angularAxis;i._hovertitle="real",a._hovertitle="imag";var o={};o[t.subplot]={_subplot:r};var s=t._module.formatLabels(e,t,o);n.realLabel=s.realLabel,n.imagLabel=s.imagLabel;var l=e.hi||t.hoverinfo,u=[];function c(h,d){u.push(h._hovertitle+": "+d)}if(!t.hovertemplate){var f=l.split("+");f.indexOf("all")!==-1&&(f=["real","imag","text"]),f.indexOf("real")!==-1&&c(i,n.realLabel),f.indexOf("imag")!==-1&&c(a,n.imagLabel),f.indexOf("text")!==-1&&n.text&&(u.push(n.text),delete 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n=this._validate(e,t,r,Gs.local.invalidDate||Gs.regionalOptions[""].invalidDate);return(Math.floor(this.toJD(n))+2)%this.daysInWeek()},extraInfo:function(e,t,r){return this._validate(e,t,r,Gs.local.invalidDate||Gs.regionalOptions[""].invalidDate),{}},add:function(e,t,r){return this._validate(e,this.minMonth,this.minDay,Gs.local.invalidDate||Gs.regionalOptions[""].invalidDate),this._correctAdd(e,this._add(e,t,r),t,r)},_add:function(e,t,r){if(this._validateLevel++,r==="d"||r==="w"){var n=e.toJD()+t*(r==="w"?this.daysInWeek():1),i=e.calendar().fromJD(n);return this._validateLevel--,[i.year(),i.month(),i.day()]}try{var a=e.year()+(r==="y"?t:0),o=e.monthOfYear()+(r==="m"?t:0),i=e.day(),s=function(c){for(;of-1+c.minMonth;)a++,o-=f,f=c.monthsInYear(a)};r==="y"?(e.month()!==this.fromMonthOfYear(a,o)&&(o=this.newDate(a,e.month(),this.minDay).monthOfYear()),o=Math.min(o,this.monthsInYear(a)),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o)))):r==="m"&&(s(this),i=Math.min(i,this.daysInMonth(a,this.fromMonthOfYear(a,o))));var l=[a,this.fromMonthOfYear(a,o),i];return this._validateLevel--,l}catch(u){throw this._validateLevel--,u}},_correctAdd:function(e,t,r,n){if(!this.hasYearZero&&(n==="y"||n==="m")&&(t[0]===0||e.year()>0!=t[0]>0)){var i={y:[1,1,"y"],m:[1,this.monthsInYear(-1),"m"],w:[this.daysInWeek(),this.daysInYear(-1),"d"],d:[1,this.daysInYear(-1),"d"]}[n],a=r<0?-1:1;t=this._add(e,r*i[0]+a*i[1],i[2])}return e.date(t[0],t[1],t[2])},set:function(e,t,r){this._validate(e,this.minMonth,this.minDay,Gs.local.invalidDate||Gs.regionalOptions[""].invalidDate);var n=r==="y"?t:e.year(),i=r==="m"?t:e.month(),a=r==="d"?t:e.day();return(r==="y"||r==="m")&&(a=Math.min(a,this.daysInMonth(n,i))),e.date(n,i,a)},isValid:function(e,t,r){this._validateLevel++;var n=this.hasYearZero||e!==0;if(n){var i=this.newDate(e,t,this.minDay);n=t>=this.minMonth&&t-this.minMonth=this.minDay&&r-this.minDay13.5?13:1),u=i-(l>2.5?4716:4715);return u<=0&&u--,this.newDate(u,l,s)},toJSDate:function(e,t,r){var n=this._validate(e,t,r,Gs.local.invalidDate||Gs.regionalOptions[""].invalidDate),i=new Date(n.year(),n.month()-1,n.day());return i.setHours(0),i.setMinutes(0),i.setSeconds(0),i.setMilliseconds(0),i.setHours(i.getHours()>12?i.getHours()+2:0),i},fromJSDate:function(e){return this.newDate(e.getFullYear(),e.getMonth()+1,e.getDate())}});var Gs=WQe.exports=new jQe;Gs.cdate=lQ;Gs.baseCalendar=uQ;Gs.calendars.gregorian=cQ});var XQe=ye(()=>{var fQ=Oh(),Ud=kv();fQ(Ud.regionalOptions[""],{invalidArguments:"Invalid arguments",invalidFormat:"Cannot format a date from another 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Ud.local.invalidFormat||Ud.regionalOptions[""].invalidFormat;e=e||this.local.dateFormat,r=r||{};for(var n=r.dayNamesShort||this.local.dayNamesShort,i=r.dayNames||this.local.dayNames,a=r.monthNumbers||this.local.monthNumbers,o=r.monthNamesShort||this.local.monthNamesShort,s=r.monthNames||this.local.monthNames,l=r.calculateWeek||this.local.calculateWeek,u=function(S,L){for(var x=1;E+x1},c=function(S,L,x,C){var M=""+L;if(u(S,C))for(;M.length1},k=function(z,O){var V=p(z,O),G=[2,3,V?4:2,V?4:2,10,11,20]["oyYJ@!".indexOf(z)+1],Z=new RegExp("^-?\\d{1,"+G+"}"),j=t.substring(M).match(Z);if(!j)throw(Ud.local.missingNumberAt||Ud.regionalOptions[""].missingNumberAt).replace(/\{0\}/,M);return M+=j[0].length,parseInt(j[0],10)},E=this,S=function(){if(typeof s=="function"){p("m");var z=s.call(E,t.substring(M));return M+=z.length,z}return k("m")},L=function(z,O,V,G){for(var Z=p(z,G)?V:O,j=0;j-1){h=1,d=v;for(var T=this.daysInMonth(f,h);d>T;T=this.daysInMonth(f,h))h++,d-=T}return c>-1?this.fromJD(c):this.newDate(f,h,d)},determineDate:function(e,t,r,n,i){r&&typeof r!="object"&&(i=n,n=r,r=null),typeof n!="string"&&(i=n,n="");var a=this,o=function(s){try{return a.parseDate(n,s,i)}catch(f){}s=s.toLowerCase();for(var l=(s.match(/^c/)&&r?r.newDate():null)||a.today(),u=/([+-]?[0-9]+)\s*(d|w|m|y)?/g,c=u.exec(s);c;)l.add(parseInt(c[1],10),c[2]||"d"),c=u.exec(s);return l};return t=t?t.newDate():null,e=e==null?t:typeof e=="string"?o(e):typeof e=="number"?isNaN(e)||e===1/0||e===-1/0?t:a.today().add(e,"d"):a.newDate(e),e}})});var ZQe=ye(()=>{var Fx=kv(),Etr=Oh(),hQ=Fx.instance();function P9(e){this.local=this.regionalOptions[e||""]||this.regionalOptions[""]}P9.prototype=new Fx.baseCalendar;Etr(P9.prototype,{name:"Chinese",jdEpoch:17214255e-1,hasYearZero:!1,minMonth:0,firstMonth:0,minDay:1,regionalOptions:{"":{name:"Chinese",epochs:["BEC","EC"],monthNumbers:function(e,t){if(typeof e=="string"){var r=e.match(Ctr);return r?r[0]:""}var n=this._validateYear(e),i=e.month(),a=""+this.toChineseMonth(n,i);return t&&a.length<2&&(a="0"+a),this.isIntercalaryMonth(n,i)&&(a+="i"),a},monthNames:function(e){if(typeof e=="string"){var t=e.match(Ltr);return t?t[0]:""}var r=this._validateYear(e),n=e.month(),i=this.toChineseMonth(r,n),a=["\u4E00\u6708","\u4E8C\u6708","\u4E09\u6708","\u56DB\u6708","\u4E94\u6708","\u516D\u6708","\u4E03\u6708","\u516B\u6708","\u4E5D\u6708","\u5341\u6708","\u5341\u4E00\u6708","\u5341\u4E8C\u6708"][i-1];return this.isIntercalaryMonth(r,n)&&(a="\u95F0"+a),a},monthNamesShort:function(e){if(typeof e=="string"){var t=e.match(Ptr);return t?t[0]:""}var r=this._validateYear(e),n=e.month(),i=this.toChineseMonth(r,n),a=["\u4E00","\u4E8C","\u4E09","\u56DB","\u4E94","\u516D","\u4E03","\u516B","\u4E5D","\u5341","\u5341\u4E00","\u5341\u4E8C"][i-1];return this.isIntercalaryMonth(r,n)&&(a="\u95F0"+a),a},parseMonth:function(e,t){e=this._validateYear(e);var r=parseInt(t),n;if(isNaN(r))t[0]==="\u95F0"&&(n=!0,t=t.substring(1)),t[t.length-1]==="\u6708"&&(t=t.substring(0,t.length-1)),r=1+["\u4E00","\u4E8C","\u4E09","\u56DB","\u4E94","\u516D","\u4E03","\u516B","\u4E5D","\u5341","\u5341\u4E00","\u5341\u4E8C"].indexOf(t);else{var i=t[t.length-1];n=i==="i"||i==="I"}var a=this.toMonthIndex(e,r,n);return a},dayNames:["Sunday","Monday","Tuesday","Wednesday","Thursday","Friday","Saturday"],dayNamesShort:["Sun","Mon","Tue","Wed","Thu","Fri","Sat"],dayNamesMin:["Su","Mo","Tu","We","Th","Fr","Sa"],digits:null,dateFormat:"yyyy/mm/dd",firstDay:1,isRTL:!1}},_validateYear:function(e,t){if(e.year&&(e=e.year()),typeof e!="number"||e<1888||e>2111)throw t.replace(/\{0\}/,this.local.name);return e},toMonthIndex:function(e,t,r){var n=this.intercalaryMonth(e),i=r&&t!==n;if(i||t<1||t>12)throw Fx.local.invalidMonth.replace(/\{0\}/,this.local.name);var a;return n?!r&&t<=n?a=t-1:a=t:a=t-1,a},toChineseMonth:function(e,t){e.year&&(e=e.year(),t=e.month());var r=this.intercalaryMonth(e),n=r?12:11;if(t<0||t>n)throw Fx.local.invalidMonth.replace(/\{0\}/,this.local.name);var i;return r?t>13;return r},isIntercalaryMonth:function(e,t){e.year&&(e=e.year(),t=e.month());var r=this.intercalaryMonth(e);return!!r&&r===t},leapYear:function(e){return this.intercalaryMonth(e)!==0},weekOfYear:function(e,t,r){var n=this._validateYear(e,Fx.local.invalidyear),i=Ox[n-Ox[0]],a=i>>9&4095,o=i>>5&15,s=i&31,l;l=hQ.newDate(a,o,s),l.add(4-(l.dayOfWeek()||7),"d");var u=this.toJD(e,t,r)-l.toJD();return 1+Math.floor(u/7)},monthsInYear:function(e){return this.leapYear(e)?13:12},daysInMonth:function(e,t){e.year&&(t=e.month(),e=e.year()),e=this._validateYear(e);var r=zx[e-zx[0]],n=r>>13,i=n?12:11;if(t>i)throw Fx.local.invalidMonth.replace(/\{0\}/,this.local.name);var a=r&1<<12-t?30:29;return a},weekDay:function(e,t,r){return(this.dayOfWeek(e,t,r)||7)<6},toJD:function(e,t,r){var n=this._validate(e,a,r,Fx.local.invalidDate);e=this._validateYear(n.year()),t=n.month(),r=n.day();var i=this.isIntercalaryMonth(e,t),a=this.toChineseMonth(e,t),o=Rtr(e,a,r,i);return hQ.toJD(o.year,o.month,o.day)},fromJD:function(e){var t=hQ.fromJD(e),r=Itr(t.year(),t.month(),t.day()),n=this.toMonthIndex(r.year,r.month,r.isIntercalary);return this.newDate(r.year,n,r.day)},fromString:function(e){var t=e.match(ktr),r=this._validateYear(+t[1]),n=+t[2],i=!!t[3],a=this.toMonthIndex(r,n,i),o=+t[4];return this.newDate(r,a,o)},add:function(e,t,r){var n=e.year(),i=e.month(),a=this.isIntercalaryMonth(n,i),o=this.toChineseMonth(n,i),s=Object.getPrototypeOf(P9.prototype).add.call(this,e,t,r);if(r==="y"){var l=s.year(),u=s.month(),c=this.isIntercalaryMonth(l,o),f=a&&c?this.toMonthIndex(l,o,!0):this.toMonthIndex(l,o,!1);f!==u&&s.month(f)}return s}});var ktr=/^\s*(-?\d\d\d\d|\d\d)[-/](\d?\d)([iI]?)[-/](\d?\d)/m,Ctr=/^\d?\d[iI]?/m,Ltr=/^闰?十?[一二三四五六七八九]?月/m,Ptr=/^闰?十?[一二三四五六七八九]?/m;Fx.calendars.chinese=P9;var 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Itr(e,t,r,n){var i,a;if(typeof e=="object")i=e,a=t||{};else{var o=typeof e=="number"&&e>=1888&&e<=2111;if(!o)throw new Error("Solar year outside range 1888-2111");var s=typeof t=="number"&&t>=1&&t<=12;if(!s)throw new Error("Solar month outside range 1 - 12");var l=typeof r=="number"&&r>=1&&r<=31;if(!l)throw new Error("Solar day outside range 1 - 31");i={year:e,month:t,day:r},a=n||{}}var u=Ox[i.year-Ox[0]],c=i.year<<9|i.month<<5|i.day;a.year=c>=u?i.year:i.year-1,u=Ox[a.year-Ox[0]];var f=u>>9&4095,h=u>>5&15,d=u&31,v,_=new Date(f,h-1,d),b=new Date(i.year,i.month-1,i.day);v=Math.round((b-_)/(24*3600*1e3));var p=zx[a.year-zx[0]],k;for(k=0;k<13;k++){var E=p&1<<12-k?30:29;if(v>13;return!S||k=1888&&e<=2111;if(!s)throw new Error("Lunar year outside range 1888-2111");var l=typeof t=="number"&&t>=1&&t<=12;if(!l)throw new Error("Lunar month outside range 1 - 12");var u=typeof r=="number"&&r>=1&&r<=30;if(!u)throw new Error("Lunar day outside range 1 - 30");var c;typeof n=="object"?(c=!1,a=n):(c=!!n,a=i||{}),o={year:e,month:t,day:r,isIntercalary:c}}var f;f=o.day-1;var h=zx[o.year-zx[0]],d=h>>13,v;d&&(o.month>d||o.isIntercalary)?v=o.month:v=o.month-1;for(var _=0;_>9&4095,E=p>>5&15,S=p&31,L=new Date(k,E-1,S+f);return a.year=L.getFullYear(),a.month=1+L.getMonth(),a.day=L.getDate(),a}});var YQe=ye(()=>{var bw=kv(),Dtr=Oh();function dQ(e){this.local=this.regionalOptions[e||""]||this.regionalOptions[""]}dQ.prototype=new bw.baseCalendar;Dtr(dQ.prototype,{name:"Coptic",jdEpoch:18250295e-1,daysPerMonth:[30,30,30,30,30,30,30,30,30,30,30,30,5],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{"":{name:"Coptic",epochs:["BAM","AM"],monthNames:["Thout","Paopi","Hathor","Koiak","Tobi","Meshir","Paremhat","Paremoude","Pashons","Paoni","Epip","Mesori","Pi Kogi 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this.daysPerMonth[r.month()-1]+(r.month()===13&&this.leapYear(r.year())?1:0)},weekDay:function(e,t,r){return(this.dayOfWeek(e,t,r)||7)<6},toJD:function(e,t,r){var n=this._validate(e,t,r,bw.local.invalidDate);return e=n.year(),e<0&&e++,n.day()+(n.month()-1)*30+(e-1)*365+Math.floor(e/4)+this.jdEpoch-1},fromJD:function(e){var t=Math.floor(e)+.5-this.jdEpoch,r=Math.floor((t-Math.floor((t+366)/1461))/365)+1;r<=0&&r--,t=Math.floor(e)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(t/30)+1,i=t-(n-1)*30+1;return this.newDate(r,n,i)}});bw.calendars.coptic=dQ});var KQe=ye(()=>{var x1=kv(),Ftr=Oh();function vQ(e){this.local=this.regionalOptions[e||""]||this.regionalOptions[""]}vQ.prototype=new x1.baseCalendar;Ftr(vQ.prototype,{name:"Discworld",jdEpoch:17214255e-1,daysPerMonth:[16,32,32,32,32,32,32,32,32,32,32,32,32],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{"":{name:"Discworld",epochs:["BUC","UC"],monthNames:["Ick","Offle","February","March","April","May","June","Grune","August","Spune","Sektober","Ember","December"],monthNamesShort:["Ick","Off","Feb","Mar","Apr","May","Jun","Gru","Aug","Spu","Sek","Emb","Dec"],dayNames:["Sunday","Octeday","Monday","Tuesday","Wednesday","Thursday","Friday","Saturday"],dayNamesShort:["Sun","Oct","Mon","Tue","Wed","Thu","Fri","Sat"],dayNamesMin:["Su","Oc","Mo","Tu","We","Th","Fr","Sa"],digits:null,dateFormat:"yyyy/mm/dd",firstDay:2,isRTL:!1}},leapYear:function(e){return this._validate(e,this.minMonth,this.minDay,x1.local.invalidYear),!1},monthsInYear:function(e){return this._validate(e,this.minMonth,this.minDay,x1.local.invalidYear),13},daysInYear:function(e){return this._validate(e,this.minMonth,this.minDay,x1.local.invalidYear),400},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(-n.dayOfWeek(),"d"),Math.floor((n.dayOfYear()-1)/8)+1},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,x1.local.invalidMonth);return this.daysPerMonth[r.month()-1]},daysInWeek:function(){return 8},dayOfWeek:function(e,t,r){var n=this._validate(e,t,r,x1.local.invalidDate);return(n.day()+1)%8},weekDay:function(e,t,r){var n=this.dayOfWeek(e,t,r);return n>=2&&n<=6},extraInfo:function(e,t,r){var n=this._validate(e,t,r,x1.local.invalidDate);return{century:ztr[Math.floor((n.year()-1)/100)+1]||""}},toJD:function(e,t,r){var n=this._validate(e,t,r,x1.local.invalidDate);return e=n.year()+(n.year()<0?1:0),t=n.month(),r=n.day(),r+(t>1?16:0)+(t>2?(t-2)*32:0)+(e-1)*400+this.jdEpoch-1},fromJD:function(e){e=Math.floor(e+.5)-Math.floor(this.jdEpoch)-1;var t=Math.floor(e/400)+1;e-=(t-1)*400,e+=e>15?16:0;var r=Math.floor(e/32)+1,n=e-(r-1)*32+1;return this.newDate(t<=0?t-1:t,r,n)}});var ztr={20:"Fruitbat",21:"Anchovy"};x1.calendars.discworld=vQ});var JQe=ye(()=>{var ww=kv(),Otr=Oh();function pQ(e){this.local=this.regionalOptions[e||""]||this.regionalOptions[""]}pQ.prototype=new ww.baseCalendar;Otr(pQ.prototype,{name:"Ethiopian",jdEpoch:17242205e-1,daysPerMonth:[30,30,30,30,30,30,30,30,30,30,30,30,5],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{"":{name:"Ethiopian",epochs:["BEE","EE"],monthNames:["Meskerem","Tikemet","Hidar","Tahesas","Tir","Yekatit","Megabit","Miazia","Genbot","Sene","Hamle","Nehase","Pagume"],monthNamesShort:["Mes","Tik","Hid","Tah","Tir","Yek","Meg","Mia","Gen","Sen","Ham","Neh","Pag"],dayNames:["Ehud","Segno","Maksegno","Irob","Hamus","Arb","Kidame"],dayNamesShort:["Ehu","Seg","Mak","Iro","Ham","Arb","Kid"],dayNamesMin:["Eh","Se","Ma","Ir","Ha","Ar","Ki"],digits:null,dateFormat:"dd/mm/yyyy",firstDay:0,isRTL:!1}},leapYear:function(r){var t=this._validate(r,this.minMonth,this.minDay,ww.local.invalidYear),r=t.year()+(t.year()<0?1:0);return r%4===3||r%4===-1},monthsInYear:function(e){return this._validate(e,this.minMonth,this.minDay,ww.local.invalidYear||ww.regionalOptions[""].invalidYear),13},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(-n.dayOfWeek(),"d"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,ww.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(r.month()===13&&this.leapYear(r.year())?1:0)},weekDay:function(e,t,r){return(this.dayOfWeek(e,t,r)||7)<6},toJD:function(e,t,r){var n=this._validate(e,t,r,ww.local.invalidDate);return e=n.year(),e<0&&e++,n.day()+(n.month()-1)*30+(e-1)*365+Math.floor(e/4)+this.jdEpoch-1},fromJD:function(e){var t=Math.floor(e)+.5-this.jdEpoch,r=Math.floor((t-Math.floor((t+366)/1461))/365)+1;r<=0&&r--,t=Math.floor(e)+.5-this.newDate(r,1,1).toJD();var n=Math.floor(t/30)+1,i=t-(n-1)*30+1;return this.newDate(r,n,i)}});ww.calendars.ethiopian=pQ});var $Qe=ye(()=>{var qx=kv(),qtr=Oh();function gQ(e){this.local=this.regionalOptions[e||""]||this.regionalOptions[""]}gQ.prototype=new qx.baseCalendar;qtr(gQ.prototype,{name:"Hebrew",jdEpoch:347995.5,daysPerMonth:[30,29,30,29,30,29,30,29,30,29,30,29,29],hasYearZero:!1,minMonth:1,firstMonth:7,minDay:1,regionalOptions:{"":{name:"Hebrew",epochs:["BAM","AM"],monthNames:["Nisan","Iyar","Sivan","Tammuz","Av","Elul","Tishrei","Cheshvan","Kislev","Tevet","Shevat","Adar","Adar II"],monthNamesShort:["Nis","Iya","Siv","Tam","Av","Elu","Tis","Che","Kis","Tev","She","Ada","Ad2"],dayNames:["Yom Rishon","Yom Sheni","Yom Shlishi","Yom Revi'i","Yom Chamishi","Yom Shishi","Yom Shabbat"],dayNamesShort:["Ris","She","Shl","Rev","Cha","Shi","Sha"],dayNamesMin:["Ri","She","Shl","Re","Ch","Shi","Sha"],digits:null,dateFormat:"dd/mm/yyyy",firstDay:0,isRTL:!1}},leapYear:function(e){var t=this._validate(e,this.minMonth,this.minDay,qx.local.invalidYear);return this._leapYear(t.year())},_leapYear:function(e){return e=e<0?e+1:e,I9(e*7+1,19)<7},monthsInYear:function(e){return this._validate(e,this.minMonth,this.minDay,qx.local.invalidYear),this._leapYear(e.year?e.year():e)?13:12},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(-n.dayOfWeek(),"d"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(e){var t=this._validate(e,this.minMonth,this.minDay,qx.local.invalidYear);return e=t.year(),this.toJD(e===-1?1:e+1,7,1)-this.toJD(e,7,1)},daysInMonth:function(e,t){return e.year&&(t=e.month(),e=e.year()),this._validate(e,t,this.minDay,qx.local.invalidMonth),t===12&&this.leapYear(e)||t===8&&I9(this.daysInYear(e),10)===5?30:t===9&&I9(this.daysInYear(e),10)===3?29:this.daysPerMonth[t-1]},weekDay:function(e,t,r){return this.dayOfWeek(e,t,r)!==6},extraInfo:function(e,t,r){var n=this._validate(e,t,r,qx.local.invalidDate);return{yearType:(this.leapYear(n)?"embolismic":"common")+" 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this.dayOfWeek(e,t,r)!==5},toJD:function(e,t,r){var n=this._validate(e,t,r,dC.local.invalidDate);return e=n.year(),t=n.month(),r=n.day(),e=e<=0?e+1:e,r+Math.ceil(29.5*(t-1))+(e-1)*354+Math.floor((3+11*e)/30)+this.jdEpoch-1},fromJD:function(e){e=Math.floor(e)+.5;var t=Math.floor((30*(e-this.jdEpoch)+10646)/10631);t=t<=0?t-1:t;var r=Math.min(12,Math.ceil((e-29-this.toJD(t,1,1))/29.5)+1),n=e-this.toJD(t,r,1)+1;return this.newDate(t,r,n)}});dC.calendars.islamic=mQ});var eet=ye(()=>{var vC=kv(),Ntr=Oh();function yQ(e){this.local=this.regionalOptions[e||""]||this.regionalOptions[""]}yQ.prototype=new vC.baseCalendar;Ntr(yQ.prototype,{name:"Julian",jdEpoch:17214235e-1,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{"":{name:"Julian",epochs:["BC","AD"],monthNames:["January","February","March","April","May","June","July","August","September","October","November","December"],monthNamesShort:["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"],dayNames:["Sunday","Monday","Tuesday","Wednesday","Thursday","Friday","Saturday"],dayNamesShort:["Sun","Mon","Tue","Wed","Thu","Fri","Sat"],dayNamesMin:["Su","Mo","Tu","We","Th","Fr","Sa"],digits:null,dateFormat:"mm/dd/yyyy",firstDay:0,isRTL:!1}},leapYear:function(r){var t=this._validate(r,this.minMonth,this.minDay,vC.local.invalidYear),r=t.year()<0?t.year()+1:t.year();return r%4===0},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(4-(n.dayOfWeek()||7),"d"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,vC.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(r.month()===2&&this.leapYear(r.year())?1:0)},weekDay:function(e,t,r){return(this.dayOfWeek(e,t,r)||7)<6},toJD:function(e,t,r){var n=this._validate(e,t,r,vC.local.invalidDate);return e=n.year(),t=n.month(),r=n.day(),e<0&&e++,t<=2&&(e--,t+=12),Math.floor(365.25*(e+4716))+Math.floor(30.6001*(t+1))+r-1524.5},fromJD:function(e){var t=Math.floor(e+.5),r=t+1524,n=Math.floor((r-122.1)/365.25),i=Math.floor(365.25*n),a=Math.floor((r-i)/30.6001),o=a-Math.floor(a<14?1:13),s=n-Math.floor(o>2?4716:4715),l=r-i-Math.floor(30.6001*a);return s<=0&&s--,this.newDate(s,o,l)}});vC.calendars.julian=yQ});var ret=ye(()=>{var ug=kv(),Utr=Oh();function xQ(e){this.local=this.regionalOptions[e||""]||this.regionalOptions[""]}xQ.prototype=new ug.baseCalendar;Utr(xQ.prototype,{name:"Mayan",jdEpoch:584282.5,hasYearZero:!0,minMonth:0,firstMonth:0,minDay:0,regionalOptions:{"":{name:"Mayan",epochs:["",""],monthNames:["0","1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17"],monthNamesShort:["0","1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17"],dayNames:["0","1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19"],dayNamesShort:["0","1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19"],dayNamesMin:["0","1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19"],digits:null,dateFormat:"YYYY.m.d",firstDay:0,isRTL:!1,haabMonths:["Pop","Uo","Zip","Zotz","Tzec","Xul","Yaxkin","Mol","Chen","Yax","Zac","Ceh","Mac","Kankin","Muan","Pax","Kayab","Cumku","Uayeb"],tzolkinMonths:["Imix","Ik","Akbal","Kan","Chicchan","Cimi","Manik","Lamat","Muluc","Oc","Chuen","Eb","Ben","Ix","Men","Cib","Caban","Etznab","Cauac","Ahau"]}},leapYear:function(e){return this._validate(e,this.minMonth,this.minDay,ug.local.invalidYear),!1},formatYear:function(e){var t=this._validate(e,this.minMonth,this.minDay,ug.local.invalidYear);e=t.year();var r=Math.floor(e/400);e=e%400,e+=e<0?400:0;var n=Math.floor(e/20);return r+"."+n+"."+e%20},forYear:function(e){if(e=e.split("."),e.length<3)throw"Invalid Mayan year";for(var t=0,r=0;r19||r>0&&n<0)throw"Invalid Mayan year";t=t*20+n}return t},monthsInYear:function(e){return this._validate(e,this.minMonth,this.minDay,ug.local.invalidYear),18},weekOfYear:function(e,t,r){return this._validate(e,t,r,ug.local.invalidDate),0},daysInYear:function(e){return this._validate(e,this.minMonth,this.minDay,ug.local.invalidYear),360},daysInMonth:function(e,t){return this._validate(e,t,this.minDay,ug.local.invalidMonth),20},daysInWeek:function(){return 5},dayOfWeek:function(e,t,r){var n=this._validate(e,t,r,ug.local.invalidDate);return n.day()},weekDay:function(e,t,r){return this._validate(e,t,r,ug.local.invalidDate),!0},extraInfo:function(e,t,r){var n=this._validate(e,t,r,ug.local.invalidDate),i=n.toJD(),a=this._toHaab(i),o=this._toTzolkin(i);return{haabMonthName:this.local.haabMonths[a[0]-1],haabMonth:a[0],haabDay:a[1],tzolkinDayName:this.local.tzolkinMonths[o[0]-1],tzolkinDay:o[0],tzolkinTrecena:o[1]}},_toHaab:function(e){e-=this.jdEpoch;var t=_Q(e+8+17*20,365);return[Math.floor(t/20)+1,_Q(t,20)]},_toTzolkin:function(e){return e-=this.jdEpoch,[tet(e+20,20),tet(e+4,13)]},toJD:function(e,t,r){var n=this._validate(e,t,r,ug.local.invalidDate);return n.day()+n.month()*20+n.year()*360+this.jdEpoch},fromJD:function(e){e=Math.floor(e)+.5-this.jdEpoch;var t=Math.floor(e/360);e=e%360,e+=e<0?360:0;var r=Math.floor(e/20),n=e%20;return this.newDate(t,r,n)}});function _Q(e,t){return e-t*Math.floor(e/t)}function tet(e,t){return _Q(e-1,t)+1}ug.calendars.mayan=xQ});var net=ye(()=>{var Tw=kv(),Vtr=Oh();function 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iet.leapYear(t.year()+(t.year()<1?1:0)+1469)},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(1-(n.dayOfWeek()||7),"d"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,Tw.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(r.month()===12&&this.leapYear(r.year())?1:0)},weekDay:function(e,t,r){return(this.dayOfWeek(e,t,r)||7)<6},toJD:function(i,t,r){var n=this._validate(i,t,r,Tw.local.invalidMonth),i=n.year();i<0&&i++;for(var a=n.day(),o=1;o=this.toJD(t+1,1,1);)t++;for(var r=e-Math.floor(this.toJD(t,1,1)+.5)+1,n=1;r>this.daysInMonth(t,n);)r-=this.daysInMonth(t,n),n++;return this.newDate(t,n,r)}});Tw.calendars.nanakshahi=bQ});var aet=ye(()=>{var Aw=kv(),Gtr=Oh();function wQ(e){this.local=this.regionalOptions[e||""]||this.regionalOptions[""]}wQ.prototype=new Aw.baseCalendar;Gtr(wQ.prototype,{name:"Nepali",jdEpoch:17007095e-1,daysPerMonth:[31,31,32,32,31,30,30,29,30,29,30,30],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,daysPerYear:365,regionalOptions:{"":{name:"Nepali",epochs:["BBS","ABS"],monthNames:["Baisakh","Jestha","Ashadh","Shrawan","Bhadra","Ashwin","Kartik","Mangsir","Paush","Mangh","Falgun","Chaitra"],monthNamesShort:["Bai","Je","As","Shra","Bha","Ash","Kar","Mang","Pau","Ma","Fal","Chai"],dayNames:["Aaitabaar","Sombaar","Manglbaar","Budhabaar","Bihibaar","Shukrabaar","Shanibaar"],dayNamesShort:["Aaita","Som","Mangl","Budha","Bihi","Shukra","Shani"],dayNamesMin:["Aai","So","Man","Bu","Bi","Shu","Sha"],digits:null,dateFormat:"dd/mm/yyyy",firstDay:1,isRTL:!1}},leapYear:function(e){return this.daysInYear(e)!==this.daysPerYear},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(-n.dayOfWeek(),"d"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(e){var t=this._validate(e,this.minMonth,this.minDay,Aw.local.invalidYear);if(e=t.year(),typeof this.NEPALI_CALENDAR_DATA[e]=="undefined")return this.daysPerYear;for(var r=0,n=this.minMonth;n<=12;n++)r+=this.NEPALI_CALENDAR_DATA[e][n];return r},daysInMonth:function(e,t){return e.year&&(t=e.month(),e=e.year()),this._validate(e,t,this.minDay,Aw.local.invalidMonth),typeof this.NEPALI_CALENDAR_DATA[e]=="undefined"?this.daysPerMonth[t-1]:this.NEPALI_CALENDAR_DATA[e][t]},weekDay:function(e,t,r){return this.dayOfWeek(e,t,r)!==6},toJD:function(e,t,r){var n=this._validate(e,t,r,Aw.local.invalidDate);e=n.year(),t=n.month(),r=n.day();var i=Aw.instance(),a=0,o=t,s=e;this._createMissingCalendarData(e);var l=e-(o>9||o===9&&r>=this.NEPALI_CALENDAR_DATA[s][0]?56:57);for(t!==9&&(a=r,o--);o!==9;)o<=0&&(o=12,s--),a+=this.NEPALI_CALENDAR_DATA[s][o],o--;return t===9?(a+=r-this.NEPALI_CALENDAR_DATA[s][0],a<0&&(a+=i.daysInYear(l))):a+=this.NEPALI_CALENDAR_DATA[s][9]-this.NEPALI_CALENDAR_DATA[s][0],i.newDate(l,1,1).add(a,"d").toJD()},fromJD:function(e){var t=Aw.instance(),r=t.fromJD(e),n=r.year(),i=r.dayOfYear(),a=n+56;this._createMissingCalendarData(a);for(var o=9,s=this.NEPALI_CALENDAR_DATA[a][0],l=this.NEPALI_CALENDAR_DATA[a][o]-s+1;i>l;)o++,o>12&&(o=1,a++),l+=this.NEPALI_CALENDAR_DATA[a][o];var u=this.NEPALI_CALENDAR_DATA[a][o]-(l-i);return this.newDate(a,o,u)},_createMissingCalendarData:function(e){var t=this.daysPerMonth.slice(0);t.unshift(17);for(var r=e-1;r{var rS=kv(),Htr=Oh();function D9(e){this.local=this.regionalOptions[e||""]||this.regionalOptions[""]}function R9(e){var t=e-475;e<0&&t++;var r=.242197,n=r*t,i=r*(t+1),a=n-Math.floor(n),o=i-Math.floor(i);return a>o}D9.prototype=new rS.baseCalendar;Htr(D9.prototype,{name:"Persian",jdEpoch:19483205e-1,daysPerMonth:[31,31,31,31,31,31,30,30,30,30,30,29],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{"":{name:"Persian",epochs:["BP","AP"],monthNames:["Farvardin","Ordibehesht","Khordad","Tir","Mordad","Shahrivar","Mehr","Aban","Azar","Dey","Bahman","Esfand"],monthNamesShort:["Far","Ord","Kho","Tir","Mor","Sha","Meh","Aba","Aza","Dey","Bah","Esf"],dayNames:["Yekshanbeh","Doshanbeh","Seshanbeh","Chah\u0101rshanbeh","Panjshanbeh","Jom'eh","Shanbeh"],dayNamesShort:["Yek","Do","Se","Cha","Panj","Jom","Sha"],dayNamesMin:["Ye","Do","Se","Ch","Pa","Jo","Sh"],digits:null,dateFormat:"yyyy/mm/dd",firstDay:6,isRTL:!1}},leapYear:function(e){var t=this._validate(e,this.minMonth,this.minDay,rS.local.invalidYear);return R9(t.year())},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(-((n.dayOfWeek()+1)%7),"d"),Math.floor((n.dayOfYear()-1)/7)+1},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,rS.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(r.month()===12&&this.leapYear(r.year())?1:0)},weekDay:function(e,t,r){return this.dayOfWeek(e,t,r)!==5},toJD:function(e,t,r){var n=this._validate(e,t,r,rS.local.invalidDate);e=n.year(),t=n.month(),r=n.day();var i=0;if(e>0)for(var a=1;a0?e-1:e)*365+i+this.jdEpoch-1},fromJD:function(e){e=Math.floor(e)+.5;var t=475+(e-this.toJD(475,1,1))/365.242197,r=Math.floor(t);r<=0&&r--,e>this.toJD(r,12,R9(r)?30:29)&&(r++,r===0&&r++);var n=e-this.toJD(r,1,1)+1,i=n<=186?Math.ceil(n/31):Math.ceil((n-6)/30),a=e-this.toJD(r,i,1)+1;return this.newDate(r,i,a)}});rS.calendars.persian=D9;rS.calendars.jalali=D9});var set=ye(()=>{var Sw=kv(),jtr=Oh(),F9=Sw.instance();function TQ(e){this.local=this.regionalOptions[e||""]||this.regionalOptions[""]}TQ.prototype=new Sw.baseCalendar;jtr(TQ.prototype,{name:"Taiwan",jdEpoch:24194025e-1,yearsOffset:1911,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{"":{name:"Taiwan",epochs:["BROC","ROC"],monthNames:["January","February","March","April","May","June","July","August","September","October","November","December"],monthNamesShort:["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"],dayNames:["Sunday","Monday","Tuesday","Wednesday","Thursday","Friday","Saturday"],dayNamesShort:["Sun","Mon","Tue","Wed","Thu","Fri","Sat"],dayNamesMin:["Su","Mo","Tu","We","Th","Fr","Sa"],digits:null,dateFormat:"yyyy/mm/dd",firstDay:1,isRTL:!1}},leapYear:function(r){var t=this._validate(r,this.minMonth,this.minDay,Sw.local.invalidYear),r=this._t2gYear(t.year());return F9.leapYear(r)},weekOfYear:function(i,t,r){var n=this._validate(i,this.minMonth,this.minDay,Sw.local.invalidYear),i=this._t2gYear(n.year());return F9.weekOfYear(i,n.month(),n.day())},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,Sw.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(r.month()===2&&this.leapYear(r.year())?1:0)},weekDay:function(e,t,r){return(this.dayOfWeek(e,t,r)||7)<6},toJD:function(i,t,r){var n=this._validate(i,t,r,Sw.local.invalidDate),i=this._t2gYear(n.year());return F9.toJD(i,n.month(),n.day())},fromJD:function(e){var t=F9.fromJD(e),r=this._g2tYear(t.year());return this.newDate(r,t.month(),t.day())},_t2gYear:function(e){return e+this.yearsOffset+(e>=-this.yearsOffset&&e<=-1?1:0)},_g2tYear:function(e){return e-this.yearsOffset-(e>=1&&e<=this.yearsOffset?1:0)}});Sw.calendars.taiwan=TQ});var uet=ye(()=>{var Mw=kv(),Wtr=Oh(),z9=Mw.instance();function AQ(e){this.local=this.regionalOptions[e||""]||this.regionalOptions[""]}AQ.prototype=new Mw.baseCalendar;Wtr(AQ.prototype,{name:"Thai",jdEpoch:15230985e-1,yearsOffset:543,daysPerMonth:[31,28,31,30,31,30,31,31,30,31,30,31],hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{"":{name:"Thai",epochs:["BBE","BE"],monthNames:["January","February","March","April","May","June","July","August","September","October","November","December"],monthNamesShort:["Jan","Feb","Mar","Apr","May","Jun","Jul","Aug","Sep","Oct","Nov","Dec"],dayNames:["Sunday","Monday","Tuesday","Wednesday","Thursday","Friday","Saturday"],dayNamesShort:["Sun","Mon","Tue","Wed","Thu","Fri","Sat"],dayNamesMin:["Su","Mo","Tu","We","Th","Fr","Sa"],digits:null,dateFormat:"dd/mm/yyyy",firstDay:0,isRTL:!1}},leapYear:function(r){var t=this._validate(r,this.minMonth,this.minDay,Mw.local.invalidYear),r=this._t2gYear(t.year());return z9.leapYear(r)},weekOfYear:function(i,t,r){var n=this._validate(i,this.minMonth,this.minDay,Mw.local.invalidYear),i=this._t2gYear(n.year());return z9.weekOfYear(i,n.month(),n.day())},daysInMonth:function(e,t){var r=this._validate(e,t,this.minDay,Mw.local.invalidMonth);return this.daysPerMonth[r.month()-1]+(r.month()===2&&this.leapYear(r.year())?1:0)},weekDay:function(e,t,r){return(this.dayOfWeek(e,t,r)||7)<6},toJD:function(i,t,r){var n=this._validate(i,t,r,Mw.local.invalidDate),i=this._t2gYear(n.year());return z9.toJD(i,n.month(),n.day())},fromJD:function(e){var t=z9.fromJD(e),r=this._g2tYear(t.year());return this.newDate(r,t.month(),t.day())},_t2gYear:function(e){return e-this.yearsOffset-(e>=1&&e<=this.yearsOffset?1:0)},_g2tYear:function(e){return e+this.yearsOffset+(e>=-this.yearsOffset&&e<=-1?1:0)}});Mw.calendars.thai=AQ});var cet=ye(()=>{var Ew=kv(),Xtr=Oh();function SQ(e){this.local=this.regionalOptions[e||""]||this.regionalOptions[""]}SQ.prototype=new Ew.baseCalendar;Xtr(SQ.prototype,{name:"UmmAlQura",hasYearZero:!1,minMonth:1,firstMonth:1,minDay:1,regionalOptions:{"":{name:"Umm al-Qura",epochs:["BH","AH"],monthNames:["Al-Muharram","Safar","Rabi' al-awwal","Rabi' Al-Thani","Jumada Al-Awwal","Jumada Al-Thani","Rajab","Sha'aban","Ramadan","Shawwal","Dhu al-Qi'dah","Dhu al-Hijjah"],monthNamesShort:["Muh","Saf","Rab1","Rab2","Jum1","Jum2","Raj","Sha'","Ram","Shaw","DhuQ","DhuH"],dayNames:["Yawm al-Ahad","Yawm al-Ithnain","Yawm al-Thal\u0101th\u0101\u2019","Yawm al-Arba\u2018\u0101\u2019","Yawm al-Kham\u012Bs","Yawm al-Jum\u2018a","Yawm al-Sabt"],dayNamesMin:["Ah","Ith","Th","Ar","Kh","Ju","Sa"],digits:null,dateFormat:"yyyy/mm/dd",firstDay:6,isRTL:!0}},leapYear:function(e){var t=this._validate(e,this.minMonth,this.minDay,Ew.local.invalidYear);return this.daysInYear(t.year())===355},weekOfYear:function(e,t,r){var n=this.newDate(e,t,r);return n.add(-n.dayOfWeek(),"d"),Math.floor((n.dayOfYear()-1)/7)+1},daysInYear:function(e){for(var t=0,r=1;r<=12;r++)t+=this.daysInMonth(e,r);return t},daysInMonth:function(e,t){for(var r=this._validate(e,t,this.minDay,Ew.local.invalidMonth),n=r.toJD()-24e5+.5,i=0,a=0;an)return Bx[i]-Bx[i-1];i++}return 30},weekDay:function(e,t,r){return this.dayOfWeek(e,t,r)!==5},toJD:function(e,t,r){var n=this._validate(e,t,r,Ew.local.invalidDate),i=12*(n.year()-1)+n.month()-15292,a=n.day()+Bx[i-1]-1;return a+24e5-.5},fromJD:function(e){for(var t=e-24e5+.5,r=0,n=0;nt);n++)r++;var i=r+15292,a=Math.floor((i-1)/12),o=a+1,s=i-12*a,l=t-Bx[r-1]+1;return this.newDate(o,s,l)},isValid:function(e,t,r){var n=Ew.baseCalendar.prototype.isValid.apply(this,arguments);return n&&(e=e.year!=null?e.year:e,n=e>=1276&&e<=1500),n},_validate:function(e,t,r,n){var i=Ew.baseCalendar.prototype._validate.apply(this,arguments);if(i.year<1276||i.year>1500)throw n.replace(/\{0\}/,this.local.name);return i}});Ew.calendars.ummalqura=SQ;var 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het=ye((rTr,fet)=>{"use strict";fet.exports=kv();XQe();ZQe();YQe();KQe();JQe();$Qe();QQe();eet();ret();net();aet();oet();set();uet();cet()});var _et=ye((iTr,yet)=>{"use strict";var vet=het(),pC=Dr(),pet=fs(),Ztr=pet.EPOCHJD,Ytr=pet.ONEDAY,kQ={valType:"enumerated",values:pC.sortObjectKeys(vet.calendars),editType:"calc",dflt:"gregorian"},get=function(e,t,r,n){var i={};return i[r]=kQ,pC.coerce(e,t,i,r,n)},Ktr=function(e,t,r,n){for(var i=0;i{"use strict";xet.exports=_et()});var rrr=ye((aTr,Tet)=>{var wet=iye();wet.register([o1e(),X1e(),sxe(),kxe(),Vxe(),qbe(),Jbe(),q2e(),dwe(),Ywe(),z3e(),ZEe(),Oke(),k6e(),gLe(),XLe(),mPe(),VIe(),s8e(),S8e(),O8e(),J8e(),hRe(),kRe(),rFe(),wFe(),BBe(),BNe(),YUe(),bVe(),PGe(),WGe(),gHe(),kje(),Gje(),dWe(),wXe(),WXe(),EZe(),YYe(),_Ke(),NKe(),hJe(),MJe(),S$e(),H$e(),uQe(),HQe(),bet()]);Tet.exports=wet});return rrr();})(); +/*! + * pad-left + * + * Copyright (c) 2014-2015, Jon Schlinkert. + * Licensed under the MIT license. + */ +/*! + * repeat-string + * + * Copyright (c) 2014-2015, Jon Schlinkert. + * Licensed under the MIT License. + */ +/*! ieee754. BSD-3-Clause License. Feross Aboukhadijeh */ +/*! + * The buffer module from node.js, for the browser. + * + * @author Feross Aboukhadijeh + * @license MIT + */ +/*! + * Determine if an object is a Buffer + * + * @author Feross Aboukhadijeh + * @license MIT + */ +/*! Bundled license information: + +native-promise-only/lib/npo.src.js: + (*! Native Promise Only + v0.8.1 (c) Kyle Simpson + MIT License: http://getify.mit-license.org + *) + +polybooljs/index.js: + (* + * @copyright 2016 Sean Connelly (@voidqk), http://syntheti.cc + * @license MIT + * @preserve Project Home: https://github.com/voidqk/polybooljs + *) + +ieee754/index.js: + (*! ieee754. BSD-3-Clause License. Feross Aboukhadijeh *) + +buffer/index.js: + (*! + * The buffer module from node.js, for the browser. + * + * @author Feross Aboukhadijeh + * @license MIT + *) + +safe-buffer/index.js: + (*! safe-buffer. MIT License. Feross Aboukhadijeh *) + +assert/build/internal/util/comparisons.js: + (*! + * The buffer module from node.js, for the browser. + * + * @author Feross Aboukhadijeh + * @license MIT + *) + +object-assign/index.js: + (* + object-assign + (c) Sindre Sorhus + @license MIT + *) + +maplibre-gl/dist/maplibre-gl.js: + (** + * MapLibre GL JS + * @license 3-Clause BSD. Full text of license: https://github.com/maplibre/maplibre-gl-js/blob/v4.7.1/LICENSE.txt + *) +*/ + +window.Plotly = Plotly; +return Plotly; +})); \ No newline at end of file diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/package_data/templates/ggplot2.json b/.venv_haddock/lib/python3.12/site-packages/plotly/package_data/templates/ggplot2.json new file mode 100644 index 0000000000000000000000000000000000000000..4f11cdb72b2c0bfd336eea7e68f2448dec85d113 --- /dev/null +++ b/.venv_haddock/lib/python3.12/site-packages/plotly/package_data/templates/ggplot2.json @@ -0,0 +1 @@ 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ra=ft.x<0;Dr[1]===1?Dr[0]===1?ft.text="\u03C0":ft.text=Dr[0]+"\u03C0":ft.text=["",Dr[0],"","\u2044","",Dr[1],"","\u03C0"].join(""),ra&&(ft.text=z+ft.text)}}}else ft.text=xt(ft.x,kt,zr,Rr)}function Pe(kt){function ft(ra,Gr){return Math.abs(ra-Gr)<=1e-6}function Mr(ra,Gr){return ft(Gr,0)?ra:Mr(Gr,ra%Gr)}function Rr(ra){for(var Gr=1;!ft(Math.round(ra*Gr)/Gr,ra);)Gr*=10;return Gr}var zr=Rr(kt),kr=kt*zr,Dr=Math.abs(Mr(kr,zr));return[Math.round(kr/Dr),Math.round(zr/Dr)]}var je=["f","p","n","\u03BC","m","","k","M","G","T"],Ce=["q","r","y","z","a",...je,"P","E","Z","Y","R","Q"],Ee=kt=>["SI","SI extended","B"].includes(kt);function Ie(kt){return kt>14||kt<-15}function ot(kt){return kt>32||kt<-30}function gt(kt,ft){return Ee(ft)?!!(ft==="SI extended"&&ot(kt)||ft!=="SI extended"&&Ie(kt)):!1}function xt(kt,ft,Mr,Rr){var zr=kt<0,kr=ft._tickround,Dr=Mr||ft.exponentformat||"B",ra=ft._tickexponent,Gr=J.getTickFormat(ft),wt=ft.separatethousands;if(Rr){var Kt={exponentformat:Dr,minexponent:ft.minexponent,dtick:ft.showexponent==="none"?ft.dtick:x(kt)&&Math.abs(kt)||1,range:ft.showexponent==="none"?ft.range.map(ft.r2d):[0,kt||1]};xr(Kt),kr=(Number(Kt._tickround)||0)+4,ra=Kt._tickexponent,ft.hoverformat&&(Gr=ft.hoverformat)}if(Gr)return ft._numFormat(Gr)(kt).replace(/-/g,z);var Cr=Math.pow(10,-kr)/2;if(Dr==="none"&&(ra=0),kt=Math.abs(kt),kt"+Ca+"":Dr==="B"&&ra===9?kt+="B":Ee(Dr)&&(kt+=Dr==="SI extended"?Ce[ra/3+10]:je[ra/3+5])}return zr?z+kt:kt}J.getTickFormat=function(kt){var ft;function Mr(Gr){return typeof Gr!="string"?Gr:Number(Gr.replace("M",""))*S}function Rr(Gr,wt){var Kt=["L","D"];if(typeof Gr==typeof wt){if(typeof Gr=="number")return Gr-wt;var Cr=Kt.indexOf(Gr.charAt(0)),Xr=Kt.indexOf(wt.charAt(0));return Cr===Xr?Number(Gr.replace(/(L|D)/g,""))-Number(wt.replace(/(L|D)/g,"")):Cr-Xr}else return typeof Gr=="number"?1:-1}function zr(Gr,wt,Kt){var Cr=Kt||function(Ca){return Ca},Xr=wt[0],Ta=wt[1];return(!Xr&&typeof 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Af=os.right-(ft._offset+ft._length);Af>0&&(Rs.xr=1,Rs.r=Af);var Uc=ft._offset-os.left;Uc>0&&(Rs.xl=0,Rs.l=Uc)}}else if(Js==="l"?(ft._depth=Math.max(os.height>0?ul-os.left:0,wl),Rs[Js]=ft._depth-ku):(ft._depth=Math.max(os.height>0?os.right-ul:0,wl),Rs[Js]=ft._depth+ku,ic.reverse()),os.height>0){var Ds=os.bottom-(ft._offset+ft._length);Ds>0&&(Rs.yb=0,Rs.b=Ds);var vc=ft._offset-os.top;vc>0&&(Rs.yt=1,Rs.t=vc)}Rs[Cr]=ft.anchor==="free"?ft.position:ft._anchorAxis.domain[ic[0]],ft.title.text!==Gr._dfltTitle[Kt]&&(Rs[Js]+=Xa(ft)+(ft.title.standoff||0)),ft.mirror&&ft.anchor!=="free"&&($s={x:0,y:0,r:0,l:0,t:0,b:0},$s[Qn]=ft.linewidth,ft.mirror&&ft.mirror!==!0&&($s[Qn]+=wl),ft.mirror===!0||ft.mirror==="ticks"?$s[Cr]=ft._anchorAxis.domain[ic[1]]:(ft.mirror==="all"||ft.mirror==="allticks")&&($s[Cr]=[ft._counterDomainMin,ft._counterDomainMax][ic[1]]))}fl&&(qs=E.getComponentMethod("rangeslider","autoMarginOpts")(kt,ft)),typeof ft.automargin=="string"&&(It(Rs,ft.automargin),It($s,ft.automargin)),A.autoMargin(kt,Zt(ft),Rs),A.autoMargin(kt,Jt(ft),$s),A.autoMargin(kt,Br(ft),qs)}),e.syncOrAsync(bo)}};function It(kt,ft){if(kt){var Mr=Object.keys(W).reduce(function(Rr,zr){return ft.indexOf(zr)!==-1&&W[zr].forEach(function(kr){Rr[kr]=1}),Rr},{});Object.keys(kt).forEach(function(Rr){Mr[Rr]||(Rr.length===1?kt[Rr]=0:delete kt[Rr])})}}function cr(kt,ft){var Mr=[],Rr,zr=function(kr,Dr){var ra=kr.xbnd[Dr];ra!==null&&Mr.push(e.extendFlat({},kr,{x:ra}))};if(ft.length){for(Rr=0;Rrkt.range[1],ra=kt.ticklabelposition&&kt.ticklabelposition.indexOf("inside")!==-1,Gr=!ra;if(Mr){var wt=Dr?-1:1;Mr=Mr*wt}if(Rr){var Kt=kt.side,Cr=ra&&(Kt==="top"||Kt==="left")||Gr&&(Kt==="bottom"||Kt==="right")?1:-1;Rr=Rr*Cr}return kt._id.charAt(0)==="x"?function(Xr){return t(zr+kt._offset+kt.l2p(ha(Xr))+Mr,kr+Rr)}:function(Xr){return t(kr+Rr,zr+kt._offset+kt.l2p(ha(Xr))+Mr)}};function ha(kt){return kt.periodX!==void 0?kt.periodX:kt.x}function za(kt){var ft=kt.ticklabelposition||"",Mr=kt.tickson||"",Rr=function(Ca){return ft.indexOf(Ca)!==-1},zr=Rr("top"),kr=Rr("left"),Dr=Rr("right"),ra=Rr("bottom"),Gr=Rr("inside"),wt=Mr!=="boundaries"&&(ra||kr||zr||Dr);if(!wt&&!Gr)return[0,0];var Kt=kt.side,Cr=wt?(kt.tickwidth||0)/2:0,Xr=$,Ta=kt.tickfont?kt.tickfont.size:12;return(ra||zr)&&(Cr+=Ta*se,Xr+=(kt.linewidth||0)/2),(kr||Dr)&&(Cr+=(kt.linewidth||0)/2,Xr+=$),Gr&&Kt==="top"&&(Xr-=Ta*(1-se)),(kr||zr)&&(Cr=-Cr),(Kt==="bottom"||Kt==="right")&&(Xr=-Xr),[wt?Cr:0,Gr?Xr:0]}J.makeTickPath=function(kt,ft,Mr,Rr){Rr||(Rr={});var zr=Rr.minor;if(zr&&!kt.minor)return"";var kr=Rr.len!==void 0?Rr.len:zr?kt.minor.ticklen:kt.ticklen,Dr=kt._id.charAt(0),ra=(kt.linewidth||1)/2;return Dr==="x"?"M0,"+(ft+ra*Mr)+"v"+kr*Mr:"M"+(ft+ra*Mr)+",0h"+kr*Mr},J.makeLabelFns=function(kt,ft,Mr){var Rr=kt.ticklabelposition||"",zr=kt.tickson||"",kr=function(So){return Rr.indexOf(So)!==-1},Dr=kr("top"),ra=kr("left"),Gr=kr("right"),wt=kr("bottom"),Kt=zr!=="boundaries"&&(wt||ra||Dr||Gr),Cr=kr("inside"),Xr=Rr==="inside"&&kt.ticks==="inside"||!Cr&&kt.ticks==="outside"&&zr!=="boundaries",Ta=0,Ca=0,La=Xr?kt.ticklen:0;if(Cr?La*=-1:Kt&&(La=0),Xr&&(Ta+=La,Mr)){var ia=e.deg2rad(Mr);Ta=La*Math.cos(ia)+1,Ca=La*Math.sin(ia)}kt.showticklabels&&(Xr||kt.showline)&&(Ta+=.2*kt.tickfont.size),Ta+=(kt.linewidth||1)/2*(Cr?-1:1);var Aa={labelStandoff:Ta,labelShift:Ca},Ki,pi,cn,yn,Pn=0,In=kt.side,Hn=kt._id.charAt(0),Vn=kt.tickangle,hn;if(Hn==="x")hn=!Cr&&In==="bottom"||Cr&&In==="top",yn=hn?1:-1,Cr&&(yn*=-1),Ki=Ca*yn,pi=ft+Ta*yn,cn=hn?1:-.2,Math.abs(Vn)===90&&(Cr?cn+=ue:Vn===-90&&In==="bottom"?cn=se:Vn===90&&In==="top"?cn=ue:cn=.5,Pn=ue/2*(Vn/90)),Aa.xFn=function(So){return So.dx+Ki+Pn*So.fontSize},Aa.yFn=function(So){return So.dy+pi+So.fontSize*cn},Aa.anchorFn=function(So,go){if(Kt){if(ra)return"end";if(Gr)return"start"}return!x(go)||go===0||go===180?"middle":go*yn<0!==Cr?"end":"start"},Aa.heightFn=function(So,go,Po){return go<-60||go>60?-.5*Po:kt.side==="top"!==Cr?-Po:0};else if(Hn==="y"){if(hn=!Cr&&In==="left"||Cr&&In==="right",yn=hn?1:-1,Cr&&(yn*=-1),Ki=Ta,pi=Ca*yn,cn=0,!Cr&&Math.abs(Vn)===90&&(Vn===-90&&In==="left"||Vn===90&&In==="right"?cn=se:cn=.5),Cr){var Co=x(Vn)?+Vn:0;if(Co!==0){var Wo=e.deg2rad(Co);Pn=Math.abs(Math.sin(Wo))*se*yn,cn=0}}Aa.xFn=function(So){return So.dx+ft-(Ki+So.fontSize*cn)*yn+Pn*So.fontSize},Aa.yFn=function(So){return So.dy+pi+So.fontSize*ue},Aa.anchorFn=function(So,go){return x(go)&&Math.abs(go)===90?"middle":hn?"end":"start"},Aa.heightFn=function(So,go,Po){return kt.side==="right"&&(go*=-1),go<-30?-Po:go<30?-.5*Po:0}}return Aa};function Ra(kt){return[kt.text,kt.x,kt.axInfo,kt.font,kt.fontSize,kt.fontColor].join("_")}J.drawTicks=function(kt,ft,Mr){Mr=Mr||{};var Rr=ft._id+"tick",zr=[].concat(ft.minor&&ft.minor.ticks?Mr.vals.filter(function(Dr){return Dr.minor&&!Dr.noTick}):[]).concat(ft.ticks?Mr.vals.filter(function(Dr){return!Dr.minor&&!Dr.noTick}):[]),kr=Mr.layer.selectAll("path."+Rr).data(zr,Ra);kr.exit().remove(),kr.enter().append("path").classed(Rr,1).classed("ticks",1).classed("crisp",Mr.crisp!==!1).each(function(Dr){return a.stroke(d.select(this),Dr.minor?ft.minor.tickcolor:ft.tickcolor)}).style("stroke-width",function(Dr){return n.crispRound(kt,Dr.minor?ft.minor.tickwidth:ft.tickwidth,1)+"px"}).attr("d",Mr.path).style("display",null),mi(ft,[N]),kr.attr("transform",Mr.transFn)},J.drawGrid=function(kt,ft,Mr){if(Mr=Mr||{},ft.tickmode!=="sync"){var Rr=ft._id+"grid",zr=ft.minor&&ft.minor.showgrid,kr=zr?Mr.vals.filter(function(Aa){return Aa.minor}):[],Dr=ft.showgrid?Mr.vals.filter(function(Aa){return!Aa.minor}):[],ra=Mr.counterAxis;if(ra&&J.shouldShowZeroLine(kt,ft,ra))for(var Gr=ft.tickmode==="array",wt=0;wt=0;Ca--){var La=Ca?Xr:Ta;if(La){var ia=La.selectAll("path."+Rr).data(Ca?Dr:kr,Ra);ia.exit().remove(),ia.enter().append("path").classed(Rr,1).classed("crisp",Mr.crisp!==!1),ia.attr("transform",Mr.transFn).attr("d",Mr.path).each(function(Aa){return a.stroke(d.select(this),Aa.minor?ft.minor.gridcolor:ft.gridcolor||"#ddd")}).style("stroke-dasharray",function(Aa){return n.dashStyle(Aa.minor?ft.minor.griddash:ft.griddash,Aa.minor?ft.minor.gridwidth:ft.gridwidth)}).style("stroke-width",function(Aa){return(Aa.minor?Cr:ft._gw)+"px"}).style("display",null),typeof Mr.path=="function"&&ia.attr("d",Mr.path)}}mi(ft,[O,I])}},J.drawZeroLine=function(kt,ft,Mr){Mr=Mr||Mr;var Rr=ft._id+"zl",zr=J.shouldShowZeroLine(kt,ft,Mr.counterAxis),kr=Mr.layer.selectAll("path."+Rr).data(zr?[{x:0,id:ft._id}]:[]);kr.exit().remove(),kr.enter().append("path").classed(Rr,1).classed("zl",1).classed("crisp",Mr.crisp!==!1).each(function(){Mr.layer.selectAll("path").sort(function(Dr,ra){return ie(Dr.id,ra.id)})}),kr.attr("transform",Mr.transFn).attr("d",Mr.path).call(a.stroke,ft.zerolinecolor||a.defaultLine).style("stroke-width",n.crispRound(kt,ft.zerolinewidth,ft._gw||1)+"px").style("display",null),mi(ft,[B])},J.drawLabels=function(kt,ft,Mr){Mr=Mr||{};var Rr=kt._fullLayout,zr=ft._id,kr=ft.zerolinelayer==="above traces",Dr=Mr.cls||zr+"tick",ra=Mr.vals.filter(function(ho){return ho.text}),Gr=Mr.labelFns,wt=Mr.secondary?0:ft.tickangle,Kt=(ft._prevTickAngles||{})[Dr],Cr=Mr.layer.selectAll("g."+Dr).data(ft.showticklabels?ra:[],Ra),Xr=[];Cr.enter().append("g").classed(Dr,1).append("text").attr("text-anchor","middle").each(function(ho){var po=d.select(this),Un=kt._promises.length;po.call(r.positionText,Gr.xFn(ho),Gr.yFn(ho)).call(n.font,{family:ho.font,size:ho.fontSize,color:ho.fontColor,weight:ho.fontWeight,style:ho.fontStyle,variant:ho.fontVariant,textcase:ho.fontTextcase,lineposition:ho.fontLineposition,shadow:ho.fontShadow}).text(ho.text).call(r.convertToTspans,kt),kt._promises[Un]?Xr.push(kt._promises.pop().then(function(){Ta(po,wt)})):Ta(po,wt)}),mi(ft,[U]),Cr.exit().remove(),Mr.repositionOnUpdate&&Cr.each(function(ho){d.select(this).select("text").call(r.positionText,Gr.xFn(ho),Gr.yFn(ho))});function Ta(ho,po){ho.each(function(Un){var oo=d.select(this),ys=oo.select(".text-math-group"),Bs=Gr.anchorFn(Un,po),js=Mr.transFn.call(oo.node(),Un)+(x(po)&&+po!=0?" rotate("+po+","+Gr.xFn(Un)+","+(Gr.yFn(Un)-Un.fontSize/2)+")":""),Xo=r.lineCount(oo),Zi=pe*Un.fontSize,Mn=Gr.heightFn(Un,x(po)?+po:0,(Xo-1)*Zi);if(Mn&&(js+=t(0,Mn)),ys.empty()){var 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gt=N(Te,ee),xt=Te.anchor,It=xt==="end"?-1:1,cr,ar;if(xt==="middle")cr=Te.crossPos+(Ce?Oe(gt.y-Te.by/2):fe(Te.bx/2+Te.tx2width/2)),ar=cr+(Ce?Oe(Te.by):fe(Te.bx));else if(Ce)cr=Te.crossPos+Oe(p+gt.y)-Oe(Te.by/2-p),ar=cr+Oe(Te.by);else{var tr=fe(It*p+gt.x),Lr=tr+fe(It*Te.bx);cr=Te.crossPos+Math.min(tr,Lr),ar=Te.crossPos+Math.max(tr,Lr)}Ce?Me!==void 0&&_e!==void 0&&Math.min(ar,_e)-Math.max(cr,Me)>1&&(je.side==="left"?(Ie=je._mainLinePosition,ot=re.width):ot=je._mainLinePosition):tt!==void 0&&ut!==void 0&&Math.min(ar,ut)-Math.max(cr,tt)>1&&(je.side==="top"?(Ie=je._mainLinePosition,ot=re.height):ot=je._mainLinePosition)}at[nt++]=[{datum:Te,traceIndex:Te.trace.index,dp:0,pos:Te.pos,posref:Te.posref,size:Te.by*(Ce?M:1)/2,pmin:Ie,pmax:ot}]}),at.sort(function(Te,Pe){return Te[0].posref-Pe[0].posref||Fe*(Pe[0].traceIndex-Te[0].traceIndex)});var rt,st,Qe,Pt,Lt,qt,Ht;function Ar(Te){var 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a=this.position.w-this._box.w,n=this.position.h-this._box.h;if(r=E.constrain(r||0,0,a),o=E.constrain(o||0,0,n),this.translateX=r,this.translateY=o,this.container.call(A.setTranslate,this._box.l-this.position.l-r,this._box.t-this.position.t-o),this._clipRect&&this._clipRect.attr({x:Math.floor(this.position.l+r-.5),y:Math.floor(this.position.t+o-.5)}),this.hbar){var i=r/a;this.hbar.call(A.setTranslate,r+i*this._hbarTranslateMax,o)}if(this.vbar){var s=o/n;this.vbar.call(A.setTranslate,r,o+s*this._vbarTranslateMax)}}}}),_9=Xe({"src/components/updatemenus/draw.js"(Z,q){"use strict";var d=Gn(),x=wc(),A=Kn(),E=rs(),e=ua(),t=hu(),r=Fl().arrayEditor,o=gh().LINE_SPACING,a=F2(),n=y9();q.exports=function(L){var z=L._fullLayout,F=e.filterVisible(z[a.name]);function B(se){x.autoMargin(L,u(se))}var 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e=A.cd,t=A.xaxis,r=A.yaxis,o=e[0].trace,a=o.type==="funnel",n=o.orientation==="h",i=[],s;if(E===!1)for(s=0;s0?(L="v",p>0?z=Math.min(g,u):z=Math.min(u)):p>0?(L="h",z=Math.min(g)):z=0;if(!z){h.visible=!1;return}h._length=z;var N=c("orientation",L);h._hasPreCompStats?N==="v"&&p===0?(c("x0",0),c("dx",1)):N==="h"&&b===0&&(c("y0",0),c("dy",1)):N==="v"&&p===0?c("x0"):N==="h"&&b===0&&c("y0");var U=x.getComponentMethod("calendars","handleTraceDefaults");U(s,h,["x","y"],m)}function n(s,h,c,m){var v=m.prefix,T=d.coerce2(s,h,r,"marker.outliercolor"),l=c("marker.line.outliercolor"),_="outliers";h._hasPreCompStats?_="all":(T||l)&&(_="suspectedoutliers");var 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rt=1/0,st=-1/0,Qe=M.quartilemethod,Pt=Qe==="exclusive",Lt=Qe==="inclusive";for(f=0;f<_e;f++)if(fe[f].length>0){if(se={},se.pos=se[B]=Q[f],pe=se.pts=fe[f].sort(h),V=se[z]=pe.map(c),$=V.length,se.min=V[0],se.max=V[$-1],se.mean=E.mean(V,$),se.sd=E.stdev(V,$,se.mean)*M.sdmultiple,se.med=E.interp(V,.5),$%2&&(Pt||Lt)){var qt,Ht;Pt?(qt=V.slice(0,$/2),Ht=V.slice($/2+1)):Lt&&(qt=V.slice(0,$/2+1),Ht=V.slice($/2)),se.q1=E.interp(qt,.5),se.q3=E.interp(Ht,.5)}else se.q1=E.interp(V,.25),se.q3=E.interp(V,.75);se.lf=m(se,V,$),se.uf=v(se,V,$),se.lo=T(se),se.uo=l(se);var Ar=_(se,$);se.ln=se.med-Ar,se.un=se.med+Ar,rt=Math.min(rt,se.ln),st=Math.max(st,se.un),se.pts2=pe.filter(oe),u.push(se)}M.notched&&E.isTypedArray(ut)&&(ut=Array.from(ut)),M._extremes[L._id]=x.findExtremes(L,M.notched?ut.concat([rt,st]):ut,{padded:!0})}return s(u,M),u.length>0?(u[0].t={num:y[g],dPos:ue,posLetter:B,valLetter:z,labels:{med:t(S,"median:"),min:t(S,"min:"),q1:t(S,"q1:"),q3:t(S,"q3:"),max:t(S,"max:"),mean:M.boxmean==="sd"||M.sizemode==="sd"?t(S,"mean \xB1 \u03C3:").replace("\u03C3",M.sdmultiple===1?"\u03C3":M.sdmultiple+"\u03C3"):t(S,"mean:"),lf:t(S,"lower fence:"),uf:t(S,"upper fence:")}},y[g]++,u):[{t:{empty:!0}}]};function r(w,S,M,y){var b=S in w,p=S+"0"in w,u="d"+S in w;if(b||p&&u){var g=M.makeCalcdata(w,S),f=A(w,M,S,g).vals;return[f,g]}var P;p?P=w[S+"0"]:"name"in w&&(M.type==="category"||d(w.name)&&["linear","log"].indexOf(M.type)!==-1||E.isDateTime(w.name)&&M.type==="date")?P=w.name:P=y;for(var L=M.type==="multicategory"?M.r2c_just_indices(P):M.d2c(P,0,w[S+"calendar"]),z=w._length,F=new Array(z),B=0;B1,p=1-s[r+"gap"],u=1-s[r+"groupgap"];for(m=0;m0;if(L==="positive"?(se=z*(P?1:.5),$=V,pe=$=B):L==="negative"?(se=$=B,pe=z*(P?1:.5),J=V):(se=pe=z,$=J=V),re){var ce=g.pointpos,be=g.jitter,Se=g.marker.size/2,De=0;ce+be>=0&&(De=V*(ce+be),De>se?(ee=!0,ie=Se,X=De):De>$&&(ie=Se,X=se)),De<=se&&(X=se);var Fe=0;ce-be<=0&&(Fe=-V*(ce-be),Fe>pe?(ee=!0,j=Se,oe=Fe):Fe>J&&(j=Se,oe=pe)),Fe<=pe&&(oe=pe)}else X=se,oe=pe;var Ze=new Array(T.length);for(v=0;vM.lo&&(N.so=!0)}return b});S.enter().append("path").classed("point",!0),S.exit().remove(),S.call(A.translatePoints,c,m)}function a(n,i,s,h){var c=i.val,m=i.pos,v=!!m.rangebreaks,T=h.bPos,l=h.bPosPxOffset||0,_=s.boxmean||(s.meanline||{}).visible,w,S;Array.isArray(h.bdPos)?(w=h.bdPos[0],S=h.bdPos[1]):(w=h.bdPos,S=h.bdPos);var M=n.selectAll("path.mean").data(s.type==="box"&&s.boxmean||s.type==="violin"&&s.box.visible&&s.meanline.visible?x.identity:[]);M.enter().append("path").attr("class","mean").style({fill:"none","vector-effect":"non-scaling-stroke"}),M.exit().remove(),M.each(function(y){var b=m.c2l(y.pos+T,!0),p=m.l2p(b-w)+l,u=m.l2p(b+S)+l,g=v?(p+u)/2:m.l2p(b)+l,f=c.c2p(y.mean,!0),P=c.c2p(y.mean-y.sd,!0),L=c.c2p(y.mean+y.sd,!0);s.orientation==="h"?d.select(this).attr("d","M"+f+","+p+"V"+u+(_==="sd"?"m0,0L"+P+","+g+"L"+f+","+p+"L"+L+","+g+"Z":"")):d.select(this).attr("d","M"+p+","+f+"H"+u+(_==="sd"?"m0,0L"+g+","+P+"L"+p+","+f+"L"+g+","+L+"Z":""))})}q.exports={plot:t,plotBoxAndWhiskers:r,plotPoints:o,plotBoxMean:a}}}),W2=Xe({"src/traces/box/style.js"(Z,q){"use strict";var d=Gn(),x=Kn(),A=rs();function E(t,r,o){var a=o||d.select(t).selectAll("g.trace.boxes");a.style("opacity",function(n){return n[0].trace.opacity}),a.each(function(n){var i=d.select(this),s=n[0].trace,h=s.line.width;function c(T,l,_,w){T.style("stroke-width",l+"px").call(x.stroke,_).call(x.fill,w)}var m=i.selectAll("path.box");if(s.type==="candlestick")m.each(function(T){if(!T.empty){var l=d.select(this),_=s[T.dir];c(l,_.line.width,_.line.color,_.fillcolor),l.style("opacity",s.selectedpoints&&!T.selected?.3:1)}});else{c(m,h,s.line.color,s.fillcolor),i.selectAll("path.mean").style({"stroke-width":h,"stroke-dasharray":2*h+"px,"+h+"px"}).call(x.stroke,s.line.color);var v=i.selectAll("path.point");A.pointStyle(v,s,t)}})}function e(t,r,o){var a=r[0].trace,n=o.selectAll("path.point");a.selectedpoints?A.selectedPointStyle(n,a):A.pointStyle(n,a,t)}q.exports={style:E,styleOnSelect:e}}}),$5=Xe({"src/traces/box/hover.js"(Z,q){"use strict";var d=Ho(),x=ua(),A=tf(),E=Kn(),e=x.fillText;function t(a,n,i,s){var h=a.cd,c=h[0].trace,m=c.hoveron,v=[],T;return m.indexOf("boxes")!==-1&&(v=v.concat(r(a,n,i,s))),m.indexOf("points")!==-1&&(T=o(a,n,i)),s==="closest"?T?[T]:v:(T&&v.push(T),v)}function r(a,n,i,s){var h=a.cd,c=a.xa,m=a.ya,v=h[0].trace,T=h[0].t,l=v.type==="violin",_,w,S,M,y,b,p,u,g,f,P,L=T.bdPos,z,F,B=T.wHover,O=function(Fe){return 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q=XO().Transform,d=oB();function x(){q.call(this,{readableObjectMode:!0})}x.prototype=Object.create(q.prototype),x.prototype.constructor=x,d(x.prototype),Z.ParserStream=x,Z.sliceEq=function(E,e,t){for(var r=e,o=0;o>4&15,c=i[4]&15,m=i[5]>>4&15,v=d(i,6),T=8,l=0;lv.width||m.width===v.width&&m.height>v.height?m:v}),h=i.reduce(function(m,v){return m.height>v.height||m.height===v.height&&m.width>v.width?m:v}),c;return s.width>h.height||s.width===h.height&&s.height>h.width?c=s:c=h,c}q.exports.readSizeFromMeta=function(i){var s={sizes:[],transforms:[],item_inf:{},item_loc:{}};if(a(i,s),!!s.sizes.length){var h=n(s.sizes),c=1;s.transforms.forEach(function(v){var T={1:6,2:5,3:8,4:7,5:4,6:3,7:2,8:1},l={1:4,2:3,3:2,4:1,5:6,6:5,7:8,8:7};if(v.type==="imir"&&(v.value===0?c=l[c]:(c=l[c],c=T[c],c=T[c])),v.type==="irot")for(var _=0;_0&&!this.aborted;){var t=this.ifds_to_read.shift();t.offset&&this.scan_ifd(t.id,t.offset,E)}},A.prototype.read_uint16=function(E){var e=this.input;if(E+2>e.length)throw 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d=ac().str2arr,x=ac().sliceEq,A=ac().readUInt16LE,E=d("GIF87a"),e=d("GIF89a");q.exports=function(t){if(!(t.length<10)&&!(!x(t,0,E)&&!x(t,0,e)))return{width:A(t,6),height:A(t,8),type:"gif",mime:"image/gif",wUnits:"px",hUnits:"px"}}}}),fB=Xe({"node_modules/probe-image-size/lib/parse_sync/ico.js"(Z,q){"use strict";var d=ac().readUInt16LE,x=0,A=1,E=16;q.exports=function(e){var t=d(e,0),r=d(e,2),o=d(e,4);if(!(t!==x||r!==A||!o)){for(var a=[],n={width:0,height:0},i=0;in.width||h>n.height)&&(n=c)}return{width:n.width,height:n.height,variants:a,type:"ico",mime:"image/x-icon",wUnits:"px",hUnits:"px"}}}}}),hB=Xe({"node_modules/probe-image-size/lib/parse_sync/jpeg.js"(Z,q){"use strict";var d=ac().readUInt16BE,x=ac().str2arr,A=ac().sliceEq,E=y3(),e=x("Exif\0\0");q.exports=function(t){if(!(t.length<2)&&!(t[0]!==255||t[1]!==216||t[2]!==255))for(var r=2;;){for(;;){if(t.length-r<2)return;if(t[r++]===255)break}for(var o=t[r++],a;o===255;)o=t[r++];if(208<=o&&o<=217||o===1)a=0;else 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GL_OES_standard_derivatives : enable + +precision highp float; +#define GLSLIFY 1 + +float beckmannDistribution(float x, float roughness) { + float NdotH = max(x, 0.0001); + float cos2Alpha = NdotH * NdotH; + float tan2Alpha = (cos2Alpha - 1.0) / cos2Alpha; + float roughness2 = roughness * roughness; + float denom = 3.141592653589793 * roughness2 * cos2Alpha * cos2Alpha; + return exp(tan2Alpha / roughness2) / denom; +} + +float cookTorranceSpecular( + vec3 lightDirection, + vec3 viewDirection, + vec3 surfaceNormal, + float roughness, + float fresnel) { + + float VdotN = max(dot(viewDirection, surfaceNormal), 0.0); + float LdotN = max(dot(lightDirection, surfaceNormal), 0.0); + + //Half angle vector + vec3 H = normalize(lightDirection + viewDirection); + + //Geometric term + float NdotH = max(dot(surfaceNormal, H), 0.0); + float VdotH = max(dot(viewDirection, H), 0.000001); + float LdotH = max(dot(lightDirection, H), 0.000001); + float G1 = (2.0 * NdotH * VdotN) / VdotH; + float G2 = (2.0 * NdotH * LdotN) / LdotH; + float G = min(1.0, min(G1, G2)); + + //Distribution term + float D = beckmannDistribution(NdotH, roughness); + + //Fresnel term + float F = pow(1.0 - VdotN, fresnel); + + //Multiply terms and done + return G * F * D / max(3.14159265 * VdotN, 0.000001); +} + +//#pragma glslify: beckmann = require(glsl-specular-beckmann) // used in gl-surface3d + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec3 clipBounds[2]; +uniform float roughness + , fresnel + , kambient + , kdiffuse + , kspecular; +uniform sampler2D texture; + +varying vec3 f_normal + , f_lightDirection + , f_eyeDirection + , f_data; +varying vec4 f_color; +varying vec2 f_uv; + +void main() { + if (f_color.a == 0.0 || + outOfRange(clipBounds[0], clipBounds[1], f_data) + ) discard; + + vec3 N = normalize(f_normal); + vec3 L = normalize(f_lightDirection); + vec3 V = normalize(f_eyeDirection); + + if(gl_FrontFacing) { + N = -N; + } + + float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel))); + //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d + + float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0); + + vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv); + vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0); + + gl_FragColor = litColor * f_color.a; +} +`]),i=o([`precision highp float; +#define GLSLIFY 1 + +attribute vec3 position; +attribute vec4 color; +attribute vec2 uv; + +uniform mat4 model, view, projection; + +varying vec4 f_color; +varying vec3 f_data; +varying vec2 f_uv; + +void main() { + gl_Position = projection * (view * (model * vec4(position, 1.0))); + f_color = color; + f_data = position; + f_uv = uv; +}`]),s=o([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec3 clipBounds[2]; +uniform sampler2D texture; +uniform float opacity; + +varying vec4 f_color; +varying vec3 f_data; +varying vec2 f_uv; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], f_data)) discard; + + gl_FragColor = f_color * texture2D(texture, f_uv) * opacity; +}`]),h=o([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +attribute vec3 position; +attribute vec4 color; +attribute vec2 uv; +attribute float pointSize; + +uniform mat4 model, view, projection; +uniform vec3 clipBounds[2]; + +varying vec4 f_color; +varying vec2 f_uv; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], position)) { + + gl_Position = vec4(0.0, 0.0 ,0.0 ,0.0); + } else { + gl_Position = projection * (view * (model * vec4(position, 1.0))); + } + gl_PointSize = pointSize; + f_color = color; + f_uv = uv; +}`]),c=o([`precision highp float; +#define GLSLIFY 1 + +uniform sampler2D texture; +uniform float opacity; + +varying vec4 f_color; +varying vec2 f_uv; + +void main() { + vec2 pointR = gl_PointCoord.xy - vec2(0.5, 0.5); + if(dot(pointR, pointR) > 0.25) { + discard; + } + gl_FragColor = f_color * texture2D(texture, f_uv) * opacity; +}`]),m=o([`precision highp float; +#define GLSLIFY 1 + +attribute vec3 position; +attribute vec4 id; + +uniform mat4 model, view, projection; + +varying vec3 f_position; +varying vec4 f_id; + +void main() { + gl_Position = projection * (view * (model * vec4(position, 1.0))); + f_id = id; + f_position = position; +}`]),v=o([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec3 clipBounds[2]; +uniform float pickId; + +varying vec3 f_position; +varying vec4 f_id; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard; + + gl_FragColor = vec4(pickId, f_id.xyz); +}`]),T=o([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +attribute vec3 position; +attribute float pointSize; +attribute vec4 id; + +uniform mat4 model, view, projection; +uniform vec3 clipBounds[2]; + +varying vec3 f_position; +varying vec4 f_id; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], position)) { + + gl_Position = vec4(0.0, 0.0, 0.0, 0.0); + } else { + gl_Position = projection * (view * (model * vec4(position, 1.0))); + gl_PointSize = pointSize; + } + f_id = id; + f_position = position; +}`]),l=o([`precision highp float; +#define GLSLIFY 1 + +attribute vec3 position; + +uniform mat4 model, view, projection; + +void main() { + gl_Position = projection * (view * (model * vec4(position, 1.0))); +}`]),_=o([`precision highp float; +#define GLSLIFY 1 + +uniform vec3 contourColor; + +void main() { + gl_FragColor = vec4(contourColor, 1.0); +} 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vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec3 lowerBound, upperBound; +uniform float contourTint; +uniform vec4 contourColor; +uniform sampler2D colormap; +uniform vec3 clipBounds[2]; +uniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity; +uniform float vertexColor; + +varying float value, kill; +varying vec3 worldCoordinate; +varying vec3 lightDirection, eyeDirection, surfaceNormal; +varying vec4 vColor; + +void main() { + if ( + kill > 0.0 || + vColor.a == 0.0 || + outOfRange(clipBounds[0], clipBounds[1], worldCoordinate) + ) discard; + + vec3 N = normalize(surfaceNormal); + vec3 V = normalize(eyeDirection); + vec3 L = normalize(lightDirection); + + if(gl_FrontFacing) { + N = -N; + } + + float specular = max(beckmannSpecular(L, V, N, roughness), 0.); + float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0); + + //decide how to interpolate color \u2014 in vertex or in fragment + vec4 surfaceColor = + step(vertexColor, .5) * texture2D(colormap, vec2(value, value)) + + step(.5, vertexColor) * vColor; + + vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0); + + gl_FragColor = mix(litColor, contourColor, contourTint) * opacity; +} +`]),s=a([`precision highp float; +#define GLSLIFY 1 + +attribute vec4 uv; +attribute float f; + +uniform vec3 objectOffset; +uniform mat3 permutation; +uniform mat4 model, view, projection; +uniform float height, zOffset; +uniform sampler2D colormap; + +varying float value, kill; +varying vec3 worldCoordinate; +varying vec2 planeCoordinate; +varying vec3 lightDirection, eyeDirection, surfaceNormal; +varying vec4 vColor; + +void main() { + vec3 dataCoordinate = permutation * vec3(uv.xy, height); + worldCoordinate = objectOffset + dataCoordinate; + mat4 objectOffsetTranslation = mat4(1.0) + mat4(vec4(0), vec4(0), vec4(0), vec4(objectOffset, 0)); + vec4 worldPosition = (model * objectOffsetTranslation) * vec4(dataCoordinate, 1.0); + + vec4 clipPosition = projection * (view * worldPosition); + clipPosition.z += zOffset; + + gl_Position = clipPosition; + value = f + objectOffset.z; + kill = -1.0; + planeCoordinate = uv.zw; + + vColor = texture2D(colormap, vec2(value, value)); + + //Don't do lighting for contours + surfaceNormal = vec3(1,0,0); + eyeDirection = vec3(0,1,0); + lightDirection = vec3(0,0,1); +} +`]),h=a([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec2 shape; +uniform vec3 clipBounds[2]; +uniform float pickId; + +varying float value, kill; +varying vec3 worldCoordinate; +varying vec2 planeCoordinate; +varying vec3 surfaceNormal; + +vec2 splitFloat(float v) { + float vh = 255.0 * v; + float upper = floor(vh); + float lower = fract(vh); + return vec2(upper / 255.0, floor(lower * 16.0) / 16.0); +} + +void main() { + if ((kill > 0.0) || + (outOfRange(clipBounds[0], clipBounds[1], worldCoordinate))) discard; + + vec2 ux = splitFloat(planeCoordinate.x / shape.x); + vec2 uy = splitFloat(planeCoordinate.y / shape.y); + gl_FragColor = vec4(pickId, ux.x, uy.x, ux.y + (uy.y/16.0)); +} +`]);t.createShader=function(c){var m=o(c,n,i,null,[{name:"uv",type:"vec4"},{name:"f",type:"vec3"},{name:"normal",type:"vec3"}]);return 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(outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +attribute vec3 position; +attribute vec4 color; +attribute vec2 glyph; +attribute vec4 id; + +uniform vec4 highlightId; +uniform float highlightScale; +uniform mat4 model, view, projection; +uniform vec3 clipBounds[2]; + +varying vec4 interpColor; +varying vec4 pickId; +varying vec3 dataCoordinate; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], position)) { + + gl_Position = vec4(0,0,0,0); + } else { + float scale = 1.0; + if(distance(highlightId, id) < 0.0001) { + scale = highlightScale; + } + + vec4 worldPosition = model * vec4(position, 1); + vec4 viewPosition = view * worldPosition; + viewPosition = viewPosition / viewPosition.w; + vec4 clipPosition = projection * (viewPosition + scale * vec4(glyph.x, -glyph.y, 0, 0)); + + gl_Position = clipPosition; + interpColor = color; + pickId = id; + dataCoordinate = position; + } +}`]),i=a([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +attribute vec3 position; +attribute vec4 color; +attribute vec2 glyph; +attribute vec4 id; + +uniform mat4 model, view, projection; +uniform vec2 screenSize; +uniform vec3 clipBounds[2]; +uniform float highlightScale, pixelRatio; +uniform vec4 highlightId; + +varying vec4 interpColor; +varying vec4 pickId; +varying vec3 dataCoordinate; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], position)) { + + gl_Position = vec4(0,0,0,0); + } else { + float scale = pixelRatio; + if(distance(highlightId.bgr, id.bgr) < 0.001) { + scale *= highlightScale; + } + + vec4 worldPosition = model * vec4(position, 1.0); + vec4 viewPosition = view * worldPosition; + vec4 clipPosition = projection * viewPosition; + clipPosition /= clipPosition.w; + + gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0); + interpColor = color; + pickId = id; + dataCoordinate = position; + } +}`]),s=a([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +attribute vec3 position; +attribute vec4 color; +attribute vec2 glyph; +attribute vec4 id; + +uniform float highlightScale; +uniform vec4 highlightId; +uniform vec3 axes[2]; +uniform mat4 model, view, projection; +uniform vec2 screenSize; +uniform vec3 clipBounds[2]; +uniform float scale, pixelRatio; + +varying vec4 interpColor; +varying vec4 pickId; +varying vec3 dataCoordinate; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], position)) { + + gl_Position = vec4(0,0,0,0); + } else { + float lscale = pixelRatio * scale; + if(distance(highlightId, id) < 0.0001) { + lscale *= highlightScale; + } + + vec4 clipCenter = projection * (view * (model * vec4(position, 1))); + vec3 dataPosition = position + 0.5*lscale*(axes[0] * glyph.x + axes[1] * glyph.y) * clipCenter.w * screenSize.y; + vec4 clipPosition = projection * (view * (model * vec4(dataPosition, 1))); + + gl_Position = clipPosition; + interpColor = color; + pickId = id; + dataCoordinate = dataPosition; + } +} +`]),h=a([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec3 fragClipBounds[2]; +uniform float opacity; + +varying vec4 interpColor; +varying vec3 dataCoordinate; + +void main() { + if ( + outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate) || + interpColor.a * opacity == 0. + ) discard; + gl_FragColor = interpColor * opacity; +} +`]),c=a([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec3 fragClipBounds[2]; +uniform float pickGroup; + +varying vec4 pickId; +varying vec3 dataCoordinate; + +void main() { + if (outOfRange(fragClipBounds[0], fragClipBounds[1], dataCoordinate)) discard; + + gl_FragColor = vec4(pickGroup, pickId.bgr); +}`]),m=[{name:"position",type:"vec3"},{name:"color",type:"vec4"},{name:"glyph",type:"vec2"},{name:"id",type:"vec4"}],v={vertex:n,fragment:h,attributes:m},T={vertex:i,fragment:h,attributes:m},l={vertex:s,fragment:h,attributes:m},_={vertex:n,fragment:c,attributes:m},w={vertex:i,fragment:c,attributes:m},S={vertex:s,fragment:c,attributes:m};function M(y,b){var p=o(y,b),u=p.attributes;return 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0.75 the result would + // likely be more horizontal than vertical. + + float b = positive_angle(a); + + return + (b < ( ratio) * HALF_PI) ? 0.0 : + (b < (2.0 - ratio) * HALF_PI) ? -HALF_PI : + (b < (2.0 + ratio) * HALF_PI) ? 0.0 : + (b < (4.0 - ratio) * HALF_PI) ? HALF_PI : + 0.0; +} + +float roundTo(float a, float b) { + return float(b * floor((a + 0.5 * b) / b)); +} + +float look_round_n_directions(float a, int n) { + float b = positive_angle(a); + float div = TWO_PI / float(n); + float c = roundTo(b, div); + return look_upwards(c); +} + +float applyAlignOption(float rawAngle, float delta) { + return + (option > 2) ? look_round_n_directions(rawAngle + delta, option) : // option 3-n: round to n directions + (option == 2) ? look_horizontal_or_vertical(rawAngle + delta, hv_ratio) : // horizontal or vertical + (option == 1) ? rawAngle + delta : // use free angle, and flip to align with one direction of the axis + (option == 0) ? look_upwards(rawAngle) : // use free angle, and stay upwards + (option ==-1) ? 0.0 : // useful for backward compatibility, all texts remains horizontal + rawAngle; // otherwise return back raw input angle +} + +bool isAxisTitle = (axis.x == 0.0) && + (axis.y == 0.0) && + (axis.z == 0.0); + +void main() { + //Compute world offset + float axisDistance = position.z; + vec3 dataPosition = axisDistance * axis + offset; + + float beta = angle; // i.e. user defined attributes for each tick + + float axisAngle; + float clipAngle; + float flip; + + if (enableAlign) { + axisAngle = (isAxisTitle) ? HALF_PI : + computeViewAngle(dataPosition, dataPosition + axis); + clipAngle = computeViewAngle(dataPosition, dataPosition + alignDir); + + axisAngle += (sin(axisAngle) < 0.0) ? PI : 0.0; + clipAngle += (sin(clipAngle) < 0.0) ? 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f_normal, f_lightDirection, f_eyeDirection, f_data, f_position; +varying vec4 f_color; +varying vec2 f_uv; + +void main() { + // Scale the vector magnitude to stay constant with + // model & view changes. + vec3 normal; + vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal); + vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0); + + //Lighting geometry parameters + vec4 cameraCoordinate = view * tubePosition; + cameraCoordinate.xyz /= cameraCoordinate.w; + f_lightDirection = lightPosition - cameraCoordinate.xyz; + f_eyeDirection = eyePosition - cameraCoordinate.xyz; + f_normal = normalize((vec4(normal, 0.0) * inverseModel).xyz); + + // vec4 m_position = model * vec4(tubePosition, 1.0); + vec4 t_position = view * tubePosition; + gl_Position = projection * t_position; + + f_color = color; + f_data = tubePosition.xyz; + f_position = position.xyz; + f_uv = uv; +} +`]),n=o([`#extension GL_OES_standard_derivatives : 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float G = min(1.0, min(G1, G2)); + + //Distribution term + float D = beckmannDistribution(NdotH, roughness); + + //Fresnel term + float F = pow(1.0 - VdotN, fresnel); + + //Multiply terms and done + return G * F * D / max(3.14159265 * VdotN, 0.000001); +} + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec3 clipBounds[2]; +uniform float roughness, fresnel, kambient, kdiffuse, kspecular, opacity; +uniform sampler2D texture; + +varying vec3 f_normal, f_lightDirection, f_eyeDirection, f_data, f_position; +varying vec4 f_color; +varying vec2 f_uv; + +void main() { + if 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(v.x*v.x > v.z*v.z || v.y*v.y > v.z*v.z) { + return normalize(vec3(-v.y, v.x, 0.0)); + } else { + return normalize(vec3(0.0, v.z, -v.y)); + } +} + +// Calculate the tube vertex and normal at the given index. +// +// The returned vertex is for a tube ring with its center at origin, radius of length(d), pointing in the direction of d. +// +// Each tube segment is made up of a ring of vertices. +// These vertices are used to make up the triangles of the tube by connecting them together in the vertex array. +// The indexes of tube segments run from 0 to 8. +// +vec3 getTubePosition(vec3 d, float index, out vec3 normal) { + float segmentCount = 8.0; + + float angle = 2.0 * 3.14159 * (index / segmentCount); + + vec3 u = getOrthogonalVector(d); + vec3 v = normalize(cross(u, d)); + + vec3 x = u * cos(angle) * length(d); + vec3 y = v * sin(angle) * length(d); + vec3 v3 = x + y; + + normal = normalize(v3); + + return v3; +} + +attribute vec4 vector; +attribute vec4 position; +attribute vec4 id; + +uniform mat4 model, view, projection; +uniform float tubeScale; + +varying vec3 f_position; +varying vec4 f_id; + +void main() { + vec3 normal; + vec3 XYZ = getTubePosition(mat3(model) * (tubeScale * vector.w * normalize(vector.xyz)), position.w, normal); + vec4 tubePosition = model * vec4(position.xyz, 1.0) + vec4(XYZ, 0.0); + + gl_Position = projection * (view * tubePosition); + f_id = id; + f_position = position.xyz; +} +`]),s=o([`precision highp float; +#define GLSLIFY 1 + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec3 clipBounds[2]; +uniform float pickId; + +varying vec3 f_position; +varying vec4 f_id; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], f_position)) discard; + + gl_FragColor = vec4(pickId, f_id.xyz); +}`]);t.meshShader={vertex:a,fragment:n,attributes:[{name:"position",type:"vec4"},{name:"color",type:"vec4"},{name:"uv",type:"vec2"},{name:"vector",type:"vec4"}]},t.pickShader={vertex:i,fragment:s,attributes:[{name:"position",type:"vec4"},{name:"id",type:"vec4"},{name:"vector",type:"vec4"}]}},6743:function(e){e.exports=t;function t(r,o,a){var n=o[0],i=o[1],s=o[2],h=o[3],c=n+n,m=i+i,v=s+s,T=n*c,l=n*m,_=n*v,w=i*m,S=i*v,M=s*v,y=h*c,b=h*m,p=h*v;return r[0]=1-(w+M),r[1]=l+p,r[2]=_-b,r[3]=0,r[4]=l-p,r[5]=1-(T+M),r[6]=S+y,r[7]=0,r[8]=_+b,r[9]=S-y,r[10]=1-(T+w),r[11]=0,r[12]=a[0],r[13]=a[1],r[14]=a[2],r[15]=1,r}},6760:function(e){e.exports=t;function t(r,o,a){var n=o[0],i=o[1],s=o[2],h=o[3],c=o[4],m=o[5],v=o[6],T=o[7],l=o[8],_=o[9],w=o[10],S=o[11],M=o[12],y=o[13],b=o[14],p=o[15],u=a[0],g=a[1],f=a[2],P=a[3];return 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T=["","0","00","000","0000","00000","000000","0000000","00000000","000000000","0000000000","00000000000","000000000000","0000000000000","00000000000000","000000000000000","0000000000000000","00000000000000000","000000000000000000","0000000000000000000","00000000000000000000","000000000000000000000","0000000000000000000000","00000000000000000000000","000000000000000000000000","0000000000000000000000000"],l=[0,0,25,16,12,11,10,9,8,8,7,7,7,7,6,6,6,6,6,6,6,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5],_=[0,0,33554432,43046721,16777216,48828125,60466176,40353607,16777216,43046721,1e7,19487171,35831808,62748517,7529536,11390625,16777216,24137569,34012224,47045881,64e6,4084101,5153632,6436343,7962624,9765625,11881376,14348907,17210368,20511149,243e5,28629151,33554432,39135393,45435424,52521875,60466176];s.prototype.toString=function(I,N){I=I||10,N=N|0||1;var U;if(I===16||I==="hex"){U="";for(var 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$a=(se+pe|0)+((V&8191)<<13)|0;se=($+(V>>>13)|0)+($a>>>26)|0,$a&=67108863,pe=Math.imul(Lt,br),V=Math.imul(Lt,Ir),V=V+Math.imul(qt,br)|0,$=Math.imul(qt,Ir),pe=pe+Math.imul(st,Ne)|0,V=V+Math.imul(st,Ke)|0,V=V+Math.imul(Qe,Ne)|0,$=$+Math.imul(Qe,Ke)|0,pe=pe+Math.imul(fe,Pe)|0,V=V+Math.imul(fe,je)|0,V=V+Math.imul(Oe,Pe)|0,$=$+Math.imul(Oe,je)|0,pe=pe+Math.imul(ut,Ee)|0,V=V+Math.imul(ut,Ie)|0,V=V+Math.imul(Me,Ee)|0,$=$+Math.imul(Me,Ie)|0,pe=pe+Math.imul(at,gt)|0,V=V+Math.imul(at,xt)|0,V=V+Math.imul(nt,gt)|0,$=$+Math.imul(nt,xt)|0,pe=pe+Math.imul(De,cr)|0,V=V+Math.imul(De,ar)|0,V=V+Math.imul(Fe,cr)|0,$=$+Math.imul(Fe,ar)|0,pe=pe+Math.imul(ce,Lr)|0,V=V+Math.imul(ce,ha)|0,V=V+Math.imul(be,Lr)|0,$=$+Math.imul(be,ha)|0,pe=pe+Math.imul(j,Ra)|0,V=V+Math.imul(j,Va)|0,V=V+Math.imul(ee,Ra)|0,$=$+Math.imul(ee,Va)|0,pe=pe+Math.imul(X,Pa)|0,V=V+Math.imul(X,di)|0,V=V+Math.imul(oe,Pa)|0,$=$+Math.imul(oe,di)|0;var Ya=(se+pe|0)+((V&8191)<<13)|0;se=($+(V>>>13)|0)+(Ya>>>26)|0,Ya&=67108863,pe=Math.imul(Ar,br),V=Math.imul(Ar,Ir),V=V+Math.imul(xr,br)|0,$=Math.imul(xr,Ir),pe=pe+Math.imul(Lt,Ne)|0,V=V+Math.imul(Lt,Ke)|0,V=V+Math.imul(qt,Ne)|0,$=$+Math.imul(qt,Ke)|0,pe=pe+Math.imul(st,Pe)|0,V=V+Math.imul(st,je)|0,V=V+Math.imul(Qe,Pe)|0,$=$+Math.imul(Qe,je)|0,pe=pe+Math.imul(fe,Ee)|0,V=V+Math.imul(fe,Ie)|0,V=V+Math.imul(Oe,Ee)|0,$=$+Math.imul(Oe,Ie)|0,pe=pe+Math.imul(ut,gt)|0,V=V+Math.imul(ut,xt)|0,V=V+Math.imul(Me,gt)|0,$=$+Math.imul(Me,xt)|0,pe=pe+Math.imul(at,cr)|0,V=V+Math.imul(at,ar)|0,V=V+Math.imul(nt,cr)|0,$=$+Math.imul(nt,ar)|0,pe=pe+Math.imul(De,Lr)|0,V=V+Math.imul(De,ha)|0,V=V+Math.imul(Fe,Lr)|0,$=$+Math.imul(Fe,ha)|0,pe=pe+Math.imul(ce,Ra)|0,V=V+Math.imul(ce,Va)|0,V=V+Math.imul(be,Ra)|0,$=$+Math.imul(be,Va)|0,pe=pe+Math.imul(j,Pa)|0,V=V+Math.imul(j,di)|0,V=V+Math.imul(ee,Pa)|0,$=$+Math.imul(ee,di)|0,pe=pe+Math.imul(X,Yt)|0,V=V+Math.imul(X,Ft)|0,V=V+Math.imul(oe,Yt)|0,$=$+Math.imul(oe,Ft)|0;var ri=(se+pe|0)+((V&8191)<<13)|0;se=($+(V>>>13)|0)+(ri>>>26)|0,ri&=67108863,pe=Math.imul(Ar,Ne),V=Math.imul(Ar,Ke),V=V+Math.imul(xr,Ne)|0,$=Math.imul(xr,Ke),pe=pe+Math.imul(Lt,Pe)|0,V=V+Math.imul(Lt,je)|0,V=V+Math.imul(qt,Pe)|0,$=$+Math.imul(qt,je)|0,pe=pe+Math.imul(st,Ee)|0,V=V+Math.imul(st,Ie)|0,V=V+Math.imul(Qe,Ee)|0,$=$+Math.imul(Qe,Ie)|0,pe=pe+Math.imul(fe,gt)|0,V=V+Math.imul(fe,xt)|0,V=V+Math.imul(Oe,gt)|0,$=$+Math.imul(Oe,xt)|0,pe=pe+Math.imul(ut,cr)|0,V=V+Math.imul(ut,ar)|0,V=V+Math.imul(Me,cr)|0,$=$+Math.imul(Me,ar)|0,pe=pe+Math.imul(at,Lr)|0,V=V+Math.imul(at,ha)|0,V=V+Math.imul(nt,Lr)|0,$=$+Math.imul(nt,ha)|0,pe=pe+Math.imul(De,Ra)|0,V=V+Math.imul(De,Va)|0,V=V+Math.imul(Fe,Ra)|0,$=$+Math.imul(Fe,Va)|0,pe=pe+Math.imul(ce,Pa)|0,V=V+Math.imul(ce,di)|0,V=V+Math.imul(be,Pa)|0,$=$+Math.imul(be,di)|0,pe=pe+Math.imul(j,Yt)|0,V=V+Math.imul(j,Ft)|0,V=V+Math.imul(ee,Yt)|0,$=$+Math.imul(ee,Ft)|0;var mi=(se+pe|0)+((V&8191)<<13)|0;se=($+(V>>>13)|0)+(mi>>>26)|0,mi&=67108863,pe=Math.imul(Ar,Pe),V=Math.imul(Ar,je),V=V+Math.imul(xr,Pe)|0,$=Math.imul(xr,je),pe=pe+Math.imul(Lt,Ee)|0,V=V+Math.imul(Lt,Ie)|0,V=V+Math.imul(qt,Ee)|0,$=$+Math.imul(qt,Ie)|0,pe=pe+Math.imul(st,gt)|0,V=V+Math.imul(st,xt)|0,V=V+Math.imul(Qe,gt)|0,$=$+Math.imul(Qe,xt)|0,pe=pe+Math.imul(fe,cr)|0,V=V+Math.imul(fe,ar)|0,V=V+Math.imul(Oe,cr)|0,$=$+Math.imul(Oe,ar)|0,pe=pe+Math.imul(ut,Lr)|0,V=V+Math.imul(ut,ha)|0,V=V+Math.imul(Me,Lr)|0,$=$+Math.imul(Me,ha)|0,pe=pe+Math.imul(at,Ra)|0,V=V+Math.imul(at,Va)|0,V=V+Math.imul(nt,Ra)|0,$=$+Math.imul(nt,Va)|0,pe=pe+Math.imul(De,Pa)|0,V=V+Math.imul(De,di)|0,V=V+Math.imul(Fe,Pa)|0,$=$+Math.imul(Fe,di)|0,pe=pe+Math.imul(ce,Yt)|0,V=V+Math.imul(ce,Ft)|0,V=V+Math.imul(be,Yt)|0,$=$+Math.imul(be,Ft)|0;var Da=(se+pe|0)+((V&8191)<<13)|0;se=($+(V>>>13)|0)+(Da>>>26)|0,Da&=67108863,pe=Math.imul(Ar,Ee),V=Math.imul(Ar,Ie),V=V+Math.imul(xr,Ee)|0,$=Math.imul(xr,Ie),pe=pe+Math.imul(Lt,gt)|0,V=V+Math.imul(Lt,xt)|0,V=V+Math.imul(qt,gt)|0,$=$+Math.imul(qt,xt)|0,pe=pe+Math.imul(st,cr)|0,V=V+Math.imul(st,ar)|0,V=V+Math.imul(Qe,cr)|0,$=$+Math.imul(Qe,ar)|0,pe=pe+Math.imul(fe,Lr)|0,V=V+Math.imul(fe,ha)|0,V=V+Math.imul(Oe,Lr)|0,$=$+Math.imul(Oe,ha)|0,pe=pe+Math.imul(ut,Ra)|0,V=V+Math.imul(ut,Va)|0,V=V+Math.imul(Me,Ra)|0,$=$+Math.imul(Me,Va)|0,pe=pe+Math.imul(at,Pa)|0,V=V+Math.imul(at,di)|0,V=V+Math.imul(nt,Pa)|0,$=$+Math.imul(nt,di)|0,pe=pe+Math.imul(De,Yt)|0,V=V+Math.imul(De,Ft)|0,V=V+Math.imul(Fe,Yt)|0,$=$+Math.imul(Fe,Ft)|0;var rn=(se+pe|0)+((V&8191)<<13)|0;se=($+(V>>>13)|0)+(rn>>>26)|0,rn&=67108863,pe=Math.imul(Ar,gt),V=Math.imul(Ar,xt),V=V+Math.imul(xr,gt)|0,$=Math.imul(xr,xt),pe=pe+Math.imul(Lt,cr)|0,V=V+Math.imul(Lt,ar)|0,V=V+Math.imul(qt,cr)|0,$=$+Math.imul(qt,ar)|0,pe=pe+Math.imul(st,Lr)|0,V=V+Math.imul(st,ha)|0,V=V+Math.imul(Qe,Lr)|0,$=$+Math.imul(Qe,ha)|0,pe=pe+Math.imul(fe,Ra)|0,V=V+Math.imul(fe,Va)|0,V=V+Math.imul(Oe,Ra)|0,$=$+Math.imul(Oe,Va)|0,pe=pe+Math.imul(ut,Pa)|0,V=V+Math.imul(ut,di)|0,V=V+Math.imul(Me,Pa)|0,$=$+Math.imul(Me,di)|0,pe=pe+Math.imul(at,Yt)|0,V=V+Math.imul(at,Ft)|0,V=V+Math.imul(nt,Yt)|0,$=$+Math.imul(nt,Ft)|0;var on=(se+pe|0)+((V&8191)<<13)|0;se=($+(V>>>13)|0)+(on>>>26)|0,on&=67108863,pe=Math.imul(Ar,cr),V=Math.imul(Ar,ar),V=V+Math.imul(xr,cr)|0,$=Math.imul(xr,ar),pe=pe+Math.imul(Lt,Lr)|0,V=V+Math.imul(Lt,ha)|0,V=V+Math.imul(qt,Lr)|0,$=$+Math.imul(qt,ha)|0,pe=pe+Math.imul(st,Ra)|0,V=V+Math.imul(st,Va)|0,V=V+Math.imul(Qe,Ra)|0,$=$+Math.imul(Qe,Va)|0,pe=pe+Math.imul(fe,Pa)|0,V=V+Math.imul(fe,di)|0,V=V+Math.imul(Oe,Pa)|0,$=$+Math.imul(Oe,di)|0,pe=pe+Math.imul(ut,Yt)|0,V=V+Math.imul(ut,Ft)|0,V=V+Math.imul(Me,Yt)|0,$=$+Math.imul(Me,Ft)|0;var kt=(se+pe|0)+((V&8191)<<13)|0;se=($+(V>>>13)|0)+(kt>>>26)|0,kt&=67108863,pe=Math.imul(Ar,Lr),V=Math.imul(Ar,ha),V=V+Math.imul(xr,Lr)|0,$=Math.imul(xr,ha),pe=pe+Math.imul(Lt,Ra)|0,V=V+Math.imul(Lt,Va)|0,V=V+Math.imul(qt,Ra)|0,$=$+Math.imul(qt,Va)|0,pe=pe+Math.imul(st,Pa)|0,V=V+Math.imul(st,di)|0,V=V+Math.imul(Qe,Pa)|0,$=$+Math.imul(Qe,di)|0,pe=pe+Math.imul(fe,Yt)|0,V=V+Math.imul(fe,Ft)|0,V=V+Math.imul(Oe,Yt)|0,$=$+Math.imul(Oe,Ft)|0;var ft=(se+pe|0)+((V&8191)<<13)|0;se=($+(V>>>13)|0)+(ft>>>26)|0,ft&=67108863,pe=Math.imul(Ar,Ra),V=Math.imul(Ar,Va),V=V+Math.imul(xr,Ra)|0,$=Math.imul(xr,Va),pe=pe+Math.imul(Lt,Pa)|0,V=V+Math.imul(Lt,di)|0,V=V+Math.imul(qt,Pa)|0,$=$+Math.imul(qt,di)|0,pe=pe+Math.imul(st,Yt)|0,V=V+Math.imul(st,Ft)|0,V=V+Math.imul(Qe,Yt)|0,$=$+Math.imul(Qe,Ft)|0;var Mr=(se+pe|0)+((V&8191)<<13)|0;se=($+(V>>>13)|0)+(Mr>>>26)|0,Mr&=67108863,pe=Math.imul(Ar,Pa),V=Math.imul(Ar,di),V=V+Math.imul(xr,Pa)|0,$=Math.imul(xr,di),pe=pe+Math.imul(Lt,Yt)|0,V=V+Math.imul(Lt,Ft)|0,V=V+Math.imul(qt,Yt)|0,$=$+Math.imul(qt,Ft)|0;var Rr=(se+pe|0)+((V&8191)<<13)|0;se=($+(V>>>13)|0)+(Rr>>>26)|0,Rr&=67108863,pe=Math.imul(Ar,Yt),V=Math.imul(Ar,Ft),V=V+Math.imul(xr,Yt)|0,$=Math.imul(xr,Ft);var zr=(se+pe|0)+((V&8191)<<13)|0;return se=($+(V>>>13)|0)+(zr>>>26)|0,zr&=67108863,ue[0]=Zt,ue[1]=Jt,ue[2]=Br,ue[3]=ta,ue[4]=aa,ue[5]=fa,ue[6]=Na,ue[7]=$a,ue[8]=Ya,ue[9]=ri,ue[10]=mi,ue[11]=Da,ue[12]=rn,ue[13]=on,ue[14]=kt,ue[15]=ft,ue[16]=Mr,ue[17]=Rr,ue[18]=zr,se!==0&&(ue[19]=se,U.length++),U};Math.imul||(M=S);function y(O,I,N){N.negative=I.negative^O.negative,N.length=O.length+I.length;for(var U=0,W=0,Q=0;Q>>26)|0,W+=ue>>>26,ue&=67108863}N.words[Q]=se,U=ue,ue=W}return U!==0?N.words[Q]=U:N.length--,N.strip()}function b(O,I,N){var U=new p;return U.mulp(O,I,N)}s.prototype.mulTo=function(I,N){var U,W=this.length+I.length;return this.length===10&&I.length===10?U=M(this,I,N):W<63?U=S(this,I,N):W<1024?U=y(this,I,N):U=b(this,I,N),U};function p(O,I){this.x=O,this.y=I}p.prototype.makeRBT=function(I){for(var N=new Array(I),U=s.prototype._countBits(I)-1,W=0;W>=1;return W},p.prototype.permute=function(I,N,U,W,Q,ue){for(var se=0;se>>1)Q++;return 1<>>13,U[2*ue+1]=Q&8191,Q=Q>>>13;for(ue=2*N;ue>=26,N+=W/67108864|0,N+=Q>>>26,this.words[U]=Q&67108863}return N!==0&&(this.words[U]=N,this.length++),this},s.prototype.muln=function(I){return this.clone().imuln(I)},s.prototype.sqr=function(){return this.mul(this)},s.prototype.isqr=function(){return this.imul(this.clone())},s.prototype.pow=function(I){var N=w(I);if(N.length===0)return new s(1);for(var U=this,W=0;W=0);var N=I%26,U=(I-N)/26,W=67108863>>>26-N<<26-N,Q;if(N!==0){var ue=0;for(Q=0;Q>>26-N}ue&&(this.words[Q]=ue,this.length++)}if(U!==0){for(Q=this.length-1;Q>=0;Q--)this.words[Q+U]=this.words[Q];for(Q=0;Q=0);var W;N?W=(N-N%26)/26:W=0;var Q=I%26,ue=Math.min((I-Q)/26,this.length),se=67108863^67108863>>>Q<ue)for(this.length-=ue,V=0;V=0&&($!==0||V>=W);V--){var J=this.words[V]|0;this.words[V]=$<<26-Q|J>>>Q,$=J&se}return pe&&$!==0&&(pe.words[pe.length++]=$),this.length===0&&(this.words[0]=0,this.length=1),this.strip()},s.prototype.ishrn=function(I,N,U){return n(this.negative===0),this.iushrn(I,N,U)},s.prototype.shln=function(I){return this.clone().ishln(I)},s.prototype.ushln=function(I){return this.clone().iushln(I)},s.prototype.shrn=function(I){return this.clone().ishrn(I)},s.prototype.ushrn=function(I){return this.clone().iushrn(I)},s.prototype.testn=function(I){n(typeof I=="number"&&I>=0);var N=I%26,U=(I-N)/26,W=1<=0);var N=I%26,U=(I-N)/26;if(n(this.negative===0,"imaskn works only with positive numbers"),this.length<=U)return this;if(N!==0&&U++,this.length=Math.min(U,this.length),N!==0){var W=67108863^67108863>>>N<=67108864;N++)this.words[N]-=67108864,N===this.length-1?this.words[N+1]=1:this.words[N+1]++;return this.length=Math.max(this.length,N+1),this},s.prototype.isubn=function(I){if(n(typeof I=="number"),n(I<67108864),I<0)return this.iaddn(-I);if(this.negative!==0)return this.negative=0,this.iaddn(I),this.negative=1,this;if(this.words[0]-=I,this.length===1&&this.words[0]<0)this.words[0]=-this.words[0],this.negative=1;else for(var N=0;N>26)-(pe/67108864|0),this.words[Q+U]=ue&67108863}for(;Q>26,this.words[Q+U]=ue&67108863;if(se===0)return this.strip();for(n(se===-1),se=0,Q=0;Q>26,this.words[Q]=ue&67108863;return this.negative=1,this.strip()},s.prototype._wordDiv=function(I,N){var U=this.length-I.length,W=this.clone(),Q=I,ue=Q.words[Q.length-1]|0,se=this._countBits(ue);U=26-se,U!==0&&(Q=Q.ushln(U),W.iushln(U),ue=Q.words[Q.length-1]|0);var pe=W.length-Q.length,V;if(N!=="mod"){V=new s(null),V.length=pe+1,V.words=new Array(V.length);for(var $=0;$=0;X--){var oe=(W.words[Q.length+X]|0)*67108864+(W.words[Q.length+X-1]|0);for(oe=Math.min(oe/ue|0,67108863),W._ishlnsubmul(Q,oe,X);W.negative!==0;)oe--,W.negative=0,W._ishlnsubmul(Q,1,X),W.isZero()||(W.negative^=1);V&&(V.words[X]=oe)}return V&&V.strip(),W.strip(),N!=="div"&&U!==0&&W.iushrn(U),{div:V||null,mod:W}},s.prototype.divmod=function(I,N,U){if(n(!I.isZero()),this.isZero())return{div:new s(0),mod:new s(0)};var W,Q,ue;return this.negative!==0&&I.negative===0?(ue=this.neg().divmod(I,N),N!=="mod"&&(W=ue.div.neg()),N!=="div"&&(Q=ue.mod.neg(),U&&Q.negative!==0&&Q.iadd(I)),{div:W,mod:Q}):this.negative===0&&I.negative!==0?(ue=this.divmod(I.neg(),N),N!=="mod"&&(W=ue.div.neg()),{div:W,mod:ue.mod}):this.negative&I.negative?(ue=this.neg().divmod(I.neg(),N),N!=="div"&&(Q=ue.mod.neg(),U&&Q.negative!==0&&Q.isub(I)),{div:ue.div,mod:Q}):I.length>this.length||this.cmp(I)<0?{div:new s(0),mod:this}:I.length===1?N==="div"?{div:this.divn(I.words[0]),mod:null}:N==="mod"?{div:null,mod:new s(this.modn(I.words[0]))}:{div:this.divn(I.words[0]),mod:new s(this.modn(I.words[0]))}:this._wordDiv(I,N)},s.prototype.div=function(I){return this.divmod(I,"div",!1).div},s.prototype.mod=function(I){return this.divmod(I,"mod",!1).mod},s.prototype.umod=function(I){return this.divmod(I,"mod",!0).mod},s.prototype.divRound=function(I){var N=this.divmod(I);if(N.mod.isZero())return N.div;var U=N.div.negative!==0?N.mod.isub(I):N.mod,W=I.ushrn(1),Q=I.andln(1),ue=U.cmp(W);return ue<0||Q===1&&ue===0?N.div:N.div.negative!==0?N.div.isubn(1):N.div.iaddn(1)},s.prototype.modn=function(I){n(I<=67108863);for(var N=(1<<26)%I,U=0,W=this.length-1;W>=0;W--)U=(N*U+(this.words[W]|0))%I;return U},s.prototype.idivn=function(I){n(I<=67108863);for(var N=0,U=this.length-1;U>=0;U--){var W=(this.words[U]|0)+N*67108864;this.words[U]=W/I|0,N=W%I}return this.strip()},s.prototype.divn=function(I){return this.clone().idivn(I)},s.prototype.egcd=function(I){n(I.negative===0),n(!I.isZero());var N=this,U=I.clone();N.negative!==0?N=N.umod(I):N=N.clone();for(var W=new s(1),Q=new s(0),ue=new s(0),se=new s(1),pe=0;N.isEven()&&U.isEven();)N.iushrn(1),U.iushrn(1),++pe;for(var V=U.clone(),$=N.clone();!N.isZero();){for(var J=0,X=1;!(N.words[0]&X)&&J<26;++J,X<<=1);if(J>0)for(N.iushrn(J);J-- >0;)(W.isOdd()||Q.isOdd())&&(W.iadd(V),Q.isub($)),W.iushrn(1),Q.iushrn(1);for(var oe=0,ie=1;!(U.words[0]&ie)&&oe<26;++oe,ie<<=1);if(oe>0)for(U.iushrn(oe);oe-- >0;)(ue.isOdd()||se.isOdd())&&(ue.iadd(V),se.isub($)),ue.iushrn(1),se.iushrn(1);N.cmp(U)>=0?(N.isub(U),W.isub(ue),Q.isub(se)):(U.isub(N),ue.isub(W),se.isub(Q))}return{a:ue,b:se,gcd:U.iushln(pe)}},s.prototype._invmp=function(I){n(I.negative===0),n(!I.isZero());var N=this,U=I.clone();N.negative!==0?N=N.umod(I):N=N.clone();for(var W=new s(1),Q=new s(0),ue=U.clone();N.cmpn(1)>0&&U.cmpn(1)>0;){for(var se=0,pe=1;!(N.words[0]&pe)&&se<26;++se,pe<<=1);if(se>0)for(N.iushrn(se);se-- >0;)W.isOdd()&&W.iadd(ue),W.iushrn(1);for(var V=0,$=1;!(U.words[0]&$)&&V<26;++V,$<<=1);if(V>0)for(U.iushrn(V);V-- >0;)Q.isOdd()&&Q.iadd(ue),Q.iushrn(1);N.cmp(U)>=0?(N.isub(U),W.isub(Q)):(U.isub(N),Q.isub(W))}var J;return N.cmpn(1)===0?J=W:J=Q,J.cmpn(0)<0&&J.iadd(I),J},s.prototype.gcd=function(I){if(this.isZero())return I.abs();if(I.isZero())return this.abs();var N=this.clone(),U=I.clone();N.negative=0,U.negative=0;for(var W=0;N.isEven()&&U.isEven();W++)N.iushrn(1),U.iushrn(1);do{for(;N.isEven();)N.iushrn(1);for(;U.isEven();)U.iushrn(1);var Q=N.cmp(U);if(Q<0){var ue=N;N=U,U=ue}else if(Q===0||U.cmpn(1)===0)break;N.isub(U)}while(!0);return U.iushln(W)},s.prototype.invm=function(I){return this.egcd(I).a.umod(I)},s.prototype.isEven=function(){return(this.words[0]&1)===0},s.prototype.isOdd=function(){return(this.words[0]&1)===1},s.prototype.andln=function(I){return this.words[0]&I},s.prototype.bincn=function(I){n(typeof I=="number");var N=I%26,U=(I-N)/26,W=1<>>26,se&=67108863,this.words[ue]=se}return Q!==0&&(this.words[ue]=Q,this.length++),this},s.prototype.isZero=function(){return this.length===1&&this.words[0]===0},s.prototype.cmpn=function(I){var N=I<0;if(this.negative!==0&&!N)return-1;if(this.negative===0&&N)return 1;this.strip();var U;if(this.length>1)U=1;else{N&&(I=-I),n(I<=67108863,"Number is too big");var W=this.words[0]|0;U=W===I?0:WI.length)return 1;if(this.length=0;U--){var W=this.words[U]|0,Q=I.words[U]|0;if(W!==Q){WQ&&(N=1);break}}return N},s.prototype.gtn=function(I){return this.cmpn(I)===1},s.prototype.gt=function(I){return this.cmp(I)===1},s.prototype.gten=function(I){return this.cmpn(I)>=0},s.prototype.gte=function(I){return this.cmp(I)>=0},s.prototype.ltn=function(I){return this.cmpn(I)===-1},s.prototype.lt=function(I){return this.cmp(I)===-1},s.prototype.lten=function(I){return this.cmpn(I)<=0},s.prototype.lte=function(I){return this.cmp(I)<=0},s.prototype.eqn=function(I){return this.cmpn(I)===0},s.prototype.eq=function(I){return this.cmp(I)===0},s.red=function(I){return new F(I)},s.prototype.toRed=function(I){return n(!this.red,"Already a number in reduction context"),n(this.negative===0,"red works only with positives"),I.convertTo(this)._forceRed(I)},s.prototype.fromRed=function(){return n(this.red,"fromRed works only with numbers in reduction context"),this.red.convertFrom(this)},s.prototype._forceRed=function(I){return this.red=I,this},s.prototype.forceRed=function(I){return n(!this.red,"Already a number in reduction context"),this._forceRed(I)},s.prototype.redAdd=function(I){return n(this.red,"redAdd works only with red numbers"),this.red.add(this,I)},s.prototype.redIAdd=function(I){return n(this.red,"redIAdd works only with red numbers"),this.red.iadd(this,I)},s.prototype.redSub=function(I){return n(this.red,"redSub works only with red numbers"),this.red.sub(this,I)},s.prototype.redISub=function(I){return n(this.red,"redISub works only with red numbers"),this.red.isub(this,I)},s.prototype.redShl=function(I){return n(this.red,"redShl works only with red numbers"),this.red.shl(this,I)},s.prototype.redMul=function(I){return n(this.red,"redMul works only with red numbers"),this.red._verify2(this,I),this.red.mul(this,I)},s.prototype.redIMul=function(I){return n(this.red,"redMul works only with red numbers"),this.red._verify2(this,I),this.red.imul(this,I)},s.prototype.redSqr=function(){return n(this.red,"redSqr works only with red numbers"),this.red._verify1(this),this.red.sqr(this)},s.prototype.redISqr=function(){return n(this.red,"redISqr works only with red numbers"),this.red._verify1(this),this.red.isqr(this)},s.prototype.redSqrt=function(){return n(this.red,"redSqrt works only with red numbers"),this.red._verify1(this),this.red.sqrt(this)},s.prototype.redInvm=function(){return n(this.red,"redInvm works only with red numbers"),this.red._verify1(this),this.red.invm(this)},s.prototype.redNeg=function(){return n(this.red,"redNeg works only with red numbers"),this.red._verify1(this),this.red.neg(this)},s.prototype.redPow=function(I){return n(this.red&&!I.red,"redPow(normalNum)"),this.red._verify1(this),this.red.pow(this,I)};var u={k256:null,p224:null,p192:null,p25519:null};function g(O,I){this.name=O,this.p=new s(I,16),this.n=this.p.bitLength(),this.k=new s(1).iushln(this.n).isub(this.p),this.tmp=this._tmp()}g.prototype._tmp=function(){var I=new s(null);return I.words=new Array(Math.ceil(this.n/13)),I},g.prototype.ireduce=function(I){var N=I,U;do this.split(N,this.tmp),N=this.imulK(N),N=N.iadd(this.tmp),U=N.bitLength();while(U>this.n);var W=U0?N.isub(this.p):N.strip!==void 0?N.strip():N._strip(),N},g.prototype.split=function(I,N){I.iushrn(this.n,0,N)},g.prototype.imulK=function(I){return I.imul(this.k)};function f(){g.call(this,"k256","ffffffff ffffffff ffffffff ffffffff ffffffff ffffffff fffffffe fffffc2f")}i(f,g),f.prototype.split=function(I,N){for(var U=4194303,W=Math.min(I.length,9),Q=0;Q>>22,ue=se}ue>>>=22,I.words[Q-10]=ue,ue===0&&I.length>10?I.length-=10:I.length-=9},f.prototype.imulK=function(I){I.words[I.length]=0,I.words[I.length+1]=0,I.length+=2;for(var N=0,U=0;U>>=26,I.words[U]=Q,N=W}return N!==0&&(I.words[I.length++]=N),I},s._prime=function(I){if(u[I])return u[I];var N;if(I==="k256")N=new f;else if(I==="p224")N=new P;else if(I==="p192")N=new L;else if(I==="p25519")N=new z;else throw new Error("Unknown prime "+I);return u[I]=N,N};function F(O){if(typeof O=="string"){var I=s._prime(O);this.m=I.p,this.prime=I}else n(O.gtn(1),"modulus must be greater than 1"),this.m=O,this.prime=null}F.prototype._verify1=function(I){n(I.negative===0,"red works only with positives"),n(I.red,"red works only with red numbers")},F.prototype._verify2=function(I,N){n((I.negative|N.negative)===0,"red works only with positives"),n(I.red&&I.red===N.red,"red works only with red numbers")},F.prototype.imod=function(I){return this.prime?this.prime.ireduce(I)._forceRed(this):I.umod(this.m)._forceRed(this)},F.prototype.neg=function(I){return I.isZero()?I.clone():this.m.sub(I)._forceRed(this)},F.prototype.add=function(I,N){this._verify2(I,N);var U=I.add(N);return U.cmp(this.m)>=0&&U.isub(this.m),U._forceRed(this)},F.prototype.iadd=function(I,N){this._verify2(I,N);var U=I.iadd(N);return U.cmp(this.m)>=0&&U.isub(this.m),U},F.prototype.sub=function(I,N){this._verify2(I,N);var U=I.sub(N);return U.cmpn(0)<0&&U.iadd(this.m),U._forceRed(this)},F.prototype.isub=function(I,N){this._verify2(I,N);var U=I.isub(N);return U.cmpn(0)<0&&U.iadd(this.m),U},F.prototype.shl=function(I,N){return this._verify1(I),this.imod(I.ushln(N))},F.prototype.imul=function(I,N){return this._verify2(I,N),this.imod(I.imul(N))},F.prototype.mul=function(I,N){return this._verify2(I,N),this.imod(I.mul(N))},F.prototype.isqr=function(I){return this.imul(I,I.clone())},F.prototype.sqr=function(I){return this.mul(I,I)},F.prototype.sqrt=function(I){if(I.isZero())return I.clone();var N=this.m.andln(3);if(n(N%2===1),N===3){var U=this.m.add(new s(1)).iushrn(2);return this.pow(I,U)}for(var W=this.m.subn(1),Q=0;!W.isZero()&&W.andln(1)===0;)Q++,W.iushrn(1);n(!W.isZero());var ue=new s(1).toRed(this),se=ue.redNeg(),pe=this.m.subn(1).iushrn(1),V=this.m.bitLength();for(V=new s(2*V*V).toRed(this);this.pow(V,pe).cmp(se)!==0;)V.redIAdd(se);for(var $=this.pow(V,W),J=this.pow(I,W.addn(1).iushrn(1)),X=this.pow(I,W),oe=Q;X.cmp(ue)!==0;){for(var ie=X,j=0;ie.cmp(ue)!==0;j++)ie=ie.redSqr();n(j=0;Q--){for(var $=N.words[Q],J=V-1;J>=0;J--){var X=$>>J&1;if(ue!==W[0]&&(ue=this.sqr(ue)),X===0&&se===0){pe=0;continue}se<<=1,se|=X,pe++,!(pe!==U&&(Q!==0||J!==0))&&(ue=this.mul(ue,W[se]),pe=0,se=0)}V=26}return ue},F.prototype.convertTo=function(I){var N=I.umod(this.m);return N===I?N.clone():N},F.prototype.convertFrom=function(I){var N=I.clone();return N.red=null,N},s.mont=function(I){return new B(I)};function B(O){F.call(this,O),this.shift=this.m.bitLength(),this.shift%26!==0&&(this.shift+=26-this.shift%26),this.r=new s(1).iushln(this.shift),this.r2=this.imod(this.r.sqr()),this.rinv=this.r._invmp(this.m),this.minv=this.rinv.mul(this.r).isubn(1).div(this.m),this.minv=this.minv.umod(this.r),this.minv=this.r.sub(this.minv)}i(B,F),B.prototype.convertTo=function(I){return this.imod(I.ushln(this.shift))},B.prototype.convertFrom=function(I){var N=this.imod(I.mul(this.rinv));return N.red=null,N},B.prototype.imul=function(I,N){if(I.isZero()||N.isZero())return I.words[0]=0,I.length=1,I;var U=I.imul(N),W=U.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),Q=U.isub(W).iushrn(this.shift),ue=Q;return Q.cmp(this.m)>=0?ue=Q.isub(this.m):Q.cmpn(0)<0&&(ue=Q.iadd(this.m)),ue._forceRed(this)},B.prototype.mul=function(I,N){if(I.isZero()||N.isZero())return new s(0)._forceRed(this);var U=I.mul(N),W=U.maskn(this.shift).mul(this.minv).imaskn(this.shift).mul(this.m),Q=U.isub(W).iushrn(this.shift),ue=Q;return Q.cmp(this.m)>=0?ue=Q.isub(this.m):Q.cmpn(0)<0&&(ue=Q.iadd(this.m)),ue._forceRed(this)},B.prototype.invm=function(I){var N=this.imod(I._invmp(this.m).mul(this.r2));return N._forceRed(this)}}(e,this)},6860:function(e){e.exports=t;function t(r,o,a){return r[0]=o[0]-a[0],r[1]=o[1]-a[1],r[2]=o[2]-a[2],r[3]=o[3]-a[3],r}},6864:function(e){e.exports=t;function t(){var r=new Float32Array(16);return 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L(pe,V,$,J,X,oe,ie,j,ee,re,ce,be,Se,De,Fe,Ze,at,nt,tt,ut,Me,_e,fe,Oe,rt,st,Qe){this.gl=pe,this.pixelRatio=1,this.cells=[],this.positions=[],this.intensity=[],this.texture=V,this.dirty=!0,this.triShader=$,this.lineShader=J,this.pointShader=X,this.pickShader=oe,this.pointPickShader=ie,this.contourShader=j,this.trianglePositions=ee,this.triangleColors=ce,this.triangleNormals=Se,this.triangleUVs=be,this.triangleIds=re,this.triangleVAO=De,this.triangleCount=0,this.lineWidth=1,this.edgePositions=Fe,this.edgeColors=at,this.edgeUVs=nt,this.edgeIds=Ze,this.edgeVAO=tt,this.edgeCount=0,this.pointPositions=ut,this.pointColors=_e,this.pointUVs=fe,this.pointSizes=Oe,this.pointIds=Me,this.pointVAO=rt,this.pointCount=0,this.contourLineWidth=1,this.contourPositions=st,this.contourVAO=Qe,this.contourCount=0,this.contourColor=[0,0,0],this.contourEnable=!0,this.pickVertex=!0,this.pickId=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lightPosition=[1e5,1e5,0],this.ambientLight=.8,this.diffuseLight=.8,this.specularLight=2,this.roughness=.5,this.fresnel=1.5,this.opacity=1,this.hasAlpha=!1,this.opacityscale=!1,this._model=P,this._view=P,this._projection=P,this._resolution=[1,1]}var z=L.prototype;z.isOpaque=function(){return!this.hasAlpha},z.isTransparent=function(){return this.hasAlpha},z.pickSlots=1,z.setPickBase=function(pe){this.pickId=pe};function F(pe,V){if(!V||!V.length)return 1;for(var $=0;$pe&&$>0){var J=(V[$][0]-pe)/(V[$][0]-V[$-1][0]);return V[$][1]*(1-J)+J*V[$-1][1]}}return 1}function B(pe,V){for(var $=l({colormap:pe,nshades:256,format:"rgba"}),J=new Uint8Array(256*4),X=0;X<256;++X){for(var oe=$[X],ie=0;ie<3;++ie)J[4*X+ie]=oe[ie];V?J[4*X+3]=255*F(X/255,V):J[4*X+3]=255*oe[3]}return T(J,[256,256,4],[4,0,1])}function O(pe){for(var V=pe.length,$=new Array(V),J=0;J0){var Se=this.triShader;Se.bind(),Se.uniforms=j,this.triangleVAO.bind(),V.drawArrays(V.TRIANGLES,0,this.triangleCount*3),this.triangleVAO.unbind()}if(this.edgeCount>0&&this.lineWidth>0){var Se=this.lineShader;Se.bind(),Se.uniforms=j,this.edgeVAO.bind(),V.lineWidth(this.lineWidth*this.pixelRatio),V.drawArrays(V.LINES,0,this.edgeCount*2),this.edgeVAO.unbind()}if(this.pointCount>0){var Se=this.pointShader;Se.bind(),Se.uniforms=j,this.pointVAO.bind(),V.drawArrays(V.POINTS,0,this.pointCount),this.pointVAO.unbind()}if(this.contourEnable&&this.contourCount>0&&this.contourLineWidth>0){var Se=this.contourShader;Se.bind(),Se.uniforms=j,this.contourVAO.bind(),V.drawArrays(V.LINES,0,this.contourCount),this.contourVAO.unbind()}},z.drawPick=function(pe){pe=pe||{};for(var V=this.gl,$=pe.model||P,J=pe.view||P,X=pe.projection||P,oe=[[-1e6,-1e6,-1e6],[1e6,1e6,1e6]],ie=0;ie<3;++ie)oe[0][ie]=Math.max(oe[0][ie],this.clipBounds[0][ie]),oe[1][ie]=Math.min(oe[1][ie],this.clipBounds[1][ie]);this._model=[].slice.call($),this._view=[].slice.call(J),this._projection=[].slice.call(X),this._resolution=[V.drawingBufferWidth,V.drawingBufferHeight];var j={model:$,view:J,projection:X,clipBounds:oe,pickId:this.pickId/255},ee=this.pickShader;if(ee.bind(),ee.uniforms=j,this.triangleCount>0&&(this.triangleVAO.bind(),V.drawArrays(V.TRIANGLES,0,this.triangleCount*3),this.triangleVAO.unbind()),this.edgeCount>0&&(this.edgeVAO.bind(),V.lineWidth(this.lineWidth*this.pixelRatio),V.drawArrays(V.LINES,0,this.edgeCount*2),this.edgeVAO.unbind()),this.pointCount>0){var ee=this.pointPickShader;ee.bind(),ee.uniforms=j,this.pointVAO.bind(),V.drawArrays(V.POINTS,0,this.pointCount),this.pointVAO.unbind()}},z.pick=function(pe){if(!pe||pe.id!==this.pickId)return null;for(var V=pe.value[0]+256*pe.value[1]+65536*pe.value[2],$=this.cells[V],J=this.positions,X=new Array($.length),oe=0;oe<$.length;++oe)X[oe]=J[$[oe]];var ie=pe.coord[0],j=pe.coord[1];if(!this.pickVertex){var ee=this.positions[$[0]],re=this.positions[$[1]],ce=this.positions[$[2]],be=[(ee[0]+re[0]+ce[0])/3,(ee[1]+re[1]+ce[1])/3,(ee[2]+re[2]+ce[2])/3];return{_cellCenter:!0,position:[ie,j],index:V,cell:$,cellId:V,intensity:this.intensity[V],dataCoordinate:be}}var Se=M(X,[ie*this.pixelRatio,this._resolution[1]-j*this.pixelRatio],this._model,this._view,this._projection,this._resolution);if(!Se)return null;for(var De=Se[2],Fe=0,oe=0;oe<$.length;++oe)Fe+=De[oe]*this.intensity[$[oe]];return{position:Se[1],index:$[Se[0]],cell:$,cellId:V,intensity:Fe,dataCoordinate:this.positions[$[Se[0]]]}},z.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.lineShader.dispose(),this.pointShader.dispose(),this.pickShader.dispose(),this.pointPickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleNormals.dispose(),this.triangleIds.dispose(),this.edgeVAO.dispose(),this.edgePositions.dispose(),this.edgeColors.dispose(),this.edgeUVs.dispose(),this.edgeIds.dispose(),this.pointVAO.dispose(),this.pointPositions.dispose(),this.pointColors.dispose(),this.pointUVs.dispose(),this.pointSizes.dispose(),this.pointIds.dispose(),this.contourVAO.dispose(),this.contourPositions.dispose(),this.contourShader.dispose()};function I(pe){var V=n(pe,y.vertex,y.fragment);return V.attributes.position.location=0,V.attributes.color.location=2,V.attributes.uv.location=3,V.attributes.normal.location=4,V}function N(pe){var V=n(pe,b.vertex,b.fragment);return V.attributes.position.location=0,V.attributes.color.location=2,V.attributes.uv.location=3,V}function U(pe){var V=n(pe,p.vertex,p.fragment);return V.attributes.position.location=0,V.attributes.color.location=2,V.attributes.uv.location=3,V.attributes.pointSize.location=4,V}function W(pe){var V=n(pe,u.vertex,u.fragment);return V.attributes.position.location=0,V.attributes.id.location=1,V}function Q(pe){var V=n(pe,g.vertex,g.fragment);return V.attributes.position.location=0,V.attributes.id.location=1,V.attributes.pointSize.location=4,V}function ue(pe){var V=n(pe,f.vertex,f.fragment);return V.attributes.position.location=0,V}function se(pe,V){arguments.length===1&&(V=pe,pe=V.gl);var $=pe.getExtension("OES_standard_derivatives")||pe.getExtension("MOZ_OES_standard_derivatives")||pe.getExtension("WEBKIT_OES_standard_derivatives");if(!$)throw new Error("derivatives not supported");var J=I(pe),X=N(pe),oe=U(pe),ie=W(pe),j=Q(pe),ee=ue(pe),re=h(pe,T(new Uint8Array([255,255,255,255]),[1,1,4]));re.generateMipmap(),re.minFilter=pe.LINEAR_MIPMAP_LINEAR,re.magFilter=pe.LINEAR;var ce=i(pe),be=i(pe),Se=i(pe),De=i(pe),Fe=i(pe),Ze=s(pe,[{buffer:ce,type:pe.FLOAT,size:3},{buffer:Fe,type:pe.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:be,type:pe.FLOAT,size:4},{buffer:Se,type:pe.FLOAT,size:2},{buffer:De,type:pe.FLOAT,size:3}]),at=i(pe),nt=i(pe),tt=i(pe),ut=i(pe),Me=s(pe,[{buffer:at,type:pe.FLOAT,size:3},{buffer:ut,type:pe.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:nt,type:pe.FLOAT,size:4},{buffer:tt,type:pe.FLOAT,size:2}]),_e=i(pe),fe=i(pe),Oe=i(pe),rt=i(pe),st=i(pe),Qe=s(pe,[{buffer:_e,type:pe.FLOAT,size:3},{buffer:st,type:pe.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:fe,type:pe.FLOAT,size:4},{buffer:Oe,type:pe.FLOAT,size:2},{buffer:rt,type:pe.FLOAT,size:1}]),Pt=i(pe),Lt=s(pe,[{buffer:Pt,type:pe.FLOAT,size:3}]),qt=new L(pe,re,J,X,oe,ie,j,ee,ce,Fe,be,Se,De,Ze,at,ut,nt,tt,Me,_e,st,fe,Oe,rt,Qe,Pt,Lt);return qt.update(V),qt}e.exports=se},7261:function(e,t,r){"use strict";e.exports=w;var o=r(9215),a=r(7608),n=r(6079),i=r(5911),s=r(3536),h=r(244);function c(S,M,y){return Math.sqrt(Math.pow(S,2)+Math.pow(M,2)+Math.pow(y,2))}function m(S){return Math.min(1,Math.max(-1,S))}function v(S){var M=Math.abs(S[0]),y=Math.abs(S[1]),b=Math.abs(S[2]),p=[0,0,0];M>Math.max(y,b)?p[2]=1:y>Math.max(M,b)?p[0]=1:p[1]=1;for(var u=0,g=0,f=0;f<3;++f)u+=S[f]*S[f],g+=p[f]*S[f];for(var f=0;f<3;++f)p[f]-=g/u*S[f];return s(p,p),p}function T(S,M,y,b,p,u,g,f){this.center=o(y),this.up=o(b),this.right=o(p),this.radius=o([u]),this.angle=o([g,f]),this.angle.bounds=[[-1/0,-Math.PI/2],[1/0,Math.PI/2]],this.setDistanceLimits(S,M),this.computedCenter=this.center.curve(0),this.computedUp=this.up.curve(0),this.computedRight=this.right.curve(0),this.computedRadius=this.radius.curve(0),this.computedAngle=this.angle.curve(0),this.computedToward=[0,0,0],this.computedEye=[0,0,0],this.computedMatrix=new Array(16);for(var P=0;P<16;++P)this.computedMatrix[P]=.5;this.recalcMatrix(0)}var l=T.prototype;l.setDistanceLimits=function(S,M){S>0?S=Math.log(S):S=-1/0,M>0?M=Math.log(M):M=1/0,M=Math.max(M,S),this.radius.bounds[0][0]=S,this.radius.bounds[1][0]=M},l.getDistanceLimits=function(S){var M=this.radius.bounds[0];return S?(S[0]=Math.exp(M[0][0]),S[1]=Math.exp(M[1][0]),S):[Math.exp(M[0][0]),Math.exp(M[1][0])]},l.recalcMatrix=function(S){this.center.curve(S),this.up.curve(S),this.right.curve(S),this.radius.curve(S),this.angle.curve(S);for(var M=this.computedUp,y=this.computedRight,b=0,p=0,u=0;u<3;++u)p+=M[u]*y[u],b+=M[u]*M[u];for(var g=Math.sqrt(b),f=0,u=0;u<3;++u)y[u]-=M[u]*p/b,f+=y[u]*y[u],M[u]/=g;for(var P=Math.sqrt(f),u=0;u<3;++u)y[u]/=P;var L=this.computedToward;i(L,M,y),s(L,L);for(var z=Math.exp(this.computedRadius[0]),F=this.computedAngle[0],B=this.computedAngle[1],O=Math.cos(F),I=Math.sin(F),N=Math.cos(B),U=Math.sin(B),W=this.computedCenter,Q=O*N,ue=I*N,se=U,pe=-O*U,V=-I*U,$=N,J=this.computedEye,X=this.computedMatrix,u=0;u<3;++u){var oe=Q*y[u]+ue*L[u]+se*M[u];X[4*u+1]=pe*y[u]+V*L[u]+$*M[u],X[4*u+2]=oe,X[4*u+3]=0}var ie=X[1],j=X[5],ee=X[9],re=X[2],ce=X[6],be=X[10],Se=j*be-ee*ce,De=ee*re-ie*be,Fe=ie*ce-j*re,Ze=c(Se,De,Fe);Se/=Ze,De/=Ze,Fe/=Ze,X[0]=Se,X[4]=De,X[8]=Fe;for(var u=0;u<3;++u)J[u]=W[u]+X[2+4*u]*z;for(var u=0;u<3;++u){for(var f=0,at=0;at<3;++at)f+=X[u+4*at]*J[at];X[12+u]=-f}X[15]=1},l.getMatrix=function(S,M){this.recalcMatrix(S);var y=this.computedMatrix;if(M){for(var b=0;b<16;++b)M[b]=y[b];return M}return y};var _=[0,0,0];l.rotate=function(S,M,y,b){if(this.angle.move(S,M,y),b){this.recalcMatrix(S);var p=this.computedMatrix;_[0]=p[2],_[1]=p[6],_[2]=p[10];for(var u=this.computedUp,g=this.computedRight,f=this.computedToward,P=0;P<3;++P)p[4*P]=u[P],p[4*P+1]=g[P],p[4*P+2]=f[P];n(p,p,b,_);for(var P=0;P<3;++P)u[P]=p[4*P],g[P]=p[4*P+1];this.up.set(S,u[0],u[1],u[2]),this.right.set(S,g[0],g[1],g[2])}},l.pan=function(S,M,y,b){M=M||0,y=y||0,b=b||0,this.recalcMatrix(S);var p=this.computedMatrix,u=Math.exp(this.computedRadius[0]),g=p[1],f=p[5],P=p[9],L=c(g,f,P);g/=L,f/=L,P/=L;var z=p[0],F=p[4],B=p[8],O=z*g+F*f+B*P;z-=g*O,F-=f*O,B-=P*O;var I=c(z,F,B);z/=I,F/=I,B/=I;var N=z*M+g*y,U=F*M+f*y,W=B*M+P*y;this.center.move(S,N,U,W);var Q=Math.exp(this.computedRadius[0]);Q=Math.max(1e-4,Q+b),this.radius.set(S,Math.log(Q))},l.translate=function(S,M,y,b){this.center.move(S,M||0,y||0,b||0)},l.setMatrix=function(S,M,y,b){var p=1;typeof y=="number"&&(p=y|0),(p<0||p>3)&&(p=1);var u=(p+2)%3,g=(p+1)%3;M||(this.recalcMatrix(S),M=this.computedMatrix);var f=M[p],P=M[p+4],L=M[p+8];if(b){var F=Math.abs(f),B=Math.abs(P),O=Math.abs(L),I=Math.max(F,B,O);F===I?(f=f<0?-1:1,P=L=0):O===I?(L=L<0?-1:1,f=P=0):(P=P<0?-1:1,f=L=0)}else{var z=c(f,P,L);f/=z,P/=z,L/=z}var N=M[u],U=M[u+4],W=M[u+8],Q=N*f+U*P+W*L;N-=f*Q,U-=P*Q,W-=L*Q;var ue=c(N,U,W);N/=ue,U/=ue,W/=ue;var se=P*W-L*U,pe=L*N-f*W,V=f*U-P*N,$=c(se,pe,V);se/=$,pe/=$,V/=$,this.center.jump(S,_e,fe,Oe),this.radius.idle(S),this.up.jump(S,f,P,L),this.right.jump(S,N,U,W);var J,X;if(p===2){var oe=M[1],ie=M[5],j=M[9],ee=oe*N+ie*U+j*W,re=oe*se+ie*pe+j*V;De<0?J=-Math.PI/2:J=Math.PI/2,X=Math.atan2(re,ee)}else{var ce=M[2],be=M[6],Se=M[10],De=ce*f+be*P+Se*L,Fe=ce*N+be*U+Se*W,Ze=ce*se+be*pe+Se*V;J=Math.asin(m(De)),X=Math.atan2(Ze,Fe)}this.angle.jump(S,X,J),this.recalcMatrix(S);var at=M[2],nt=M[6],tt=M[10],ut=this.computedMatrix;a(ut,M);var Me=ut[15],_e=ut[12]/Me,fe=ut[13]/Me,Oe=ut[14]/Me,rt=Math.exp(this.computedRadius[0]);this.center.jump(S,_e-at*rt,fe-nt*rt,Oe-tt*rt)},l.lastT=function(){return Math.max(this.center.lastT(),this.up.lastT(),this.right.lastT(),this.radius.lastT(),this.angle.lastT())},l.idle=function(S){this.center.idle(S),this.up.idle(S),this.right.idle(S),this.radius.idle(S),this.angle.idle(S)},l.flush=function(S){this.center.flush(S),this.up.flush(S),this.right.flush(S),this.radius.flush(S),this.angle.flush(S)},l.setDistance=function(S,M){M>0&&this.radius.set(S,Math.log(M))},l.lookAt=function(S,M,y,b){this.recalcMatrix(S),M=M||this.computedEye,y=y||this.computedCenter,b=b||this.computedUp;var p=b[0],u=b[1],g=b[2],f=c(p,u,g);if(!(f<1e-6)){p/=f,u/=f,g/=f;var P=M[0]-y[0],L=M[1]-y[1],z=M[2]-y[2],F=c(P,L,z);if(!(F<1e-6)){P/=F,L/=F,z/=F;var B=this.computedRight,O=B[0],I=B[1],N=B[2],U=p*O+u*I+g*N;O-=U*p,I-=U*u,N-=U*g;var W=c(O,I,N);if(!(W<.01&&(O=u*z-g*L,I=g*P-p*z,N=p*L-u*P,W=c(O,I,N),W<1e-6))){O/=W,I/=W,N/=W,this.up.set(S,p,u,g),this.right.set(S,O,I,N),this.center.set(S,y[0],y[1],y[2]),this.radius.set(S,Math.log(F));var Q=u*N-g*I,ue=g*O-p*N,se=p*I-u*O,pe=c(Q,ue,se);Q/=pe,ue/=pe,se/=pe;var V=p*P+u*L+g*z,$=O*P+I*L+N*z,J=Q*P+ue*L+se*z,X=Math.asin(m(V)),oe=Math.atan2(J,$),ie=this.angle._state,j=ie[ie.length-1],ee=ie[ie.length-2];j=j%(2*Math.PI);var re=Math.abs(j+2*Math.PI-oe),ce=Math.abs(j-oe),be=Math.abs(j-2*Math.PI-oe);re max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform vec3 clipBounds[2]; +uniform sampler2D dashTexture; +uniform float dashScale; +uniform float opacity; + +varying vec3 worldPosition; +varying float pixelArcLength; +varying vec4 fragColor; + +void main() { + if ( + outOfRange(clipBounds[0], clipBounds[1], worldPosition) || + fragColor.a * opacity == 0. + ) discard; + + float dashWeight = texture2D(dashTexture, vec2(dashScale * pixelArcLength, 0)).r; + if(dashWeight < 0.5) { + discard; + } + gl_FragColor = fragColor * opacity; +} +`]),s=o([`precision highp float; +#define GLSLIFY 1 + +#define FLOAT_MAX 1.70141184e38 +#define FLOAT_MIN 1.17549435e-38 + +// https://github.com/mikolalysenko/glsl-read-float/blob/master/index.glsl +vec4 packFloat(float v) { + float av = abs(v); + + //Handle special cases + if(av < FLOAT_MIN) { + return vec4(0.0, 0.0, 0.0, 0.0); + } else if(v > FLOAT_MAX) { + return vec4(127.0, 128.0, 0.0, 0.0) / 255.0; + } else if(v < -FLOAT_MAX) { + return vec4(255.0, 128.0, 0.0, 0.0) / 255.0; + } + + vec4 c = vec4(0,0,0,0); + + //Compute exponent and mantissa + float e = floor(log2(av)); + float m = av * pow(2.0, -e) - 1.0; + + //Unpack mantissa + c[1] = floor(128.0 * m); + m -= c[1] / 128.0; + c[2] = floor(32768.0 * m); + m -= c[2] / 32768.0; + c[3] = floor(8388608.0 * m); + + //Unpack exponent + float ebias = e + 127.0; + c[0] = floor(ebias / 2.0); + ebias -= c[0] * 2.0; + c[1] += floor(ebias) * 128.0; + + //Unpack sign bit + c[0] += 128.0 * step(0.0, -v); + + //Scale back to range + return c / 255.0; +} + +bool outOfRange(float a, float b, float p) { + return ((p > max(a, b)) || + (p < min(a, b))); +} + +bool outOfRange(vec2 a, vec2 b, vec2 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y)); +} + +bool outOfRange(vec3 a, vec3 b, vec3 p) { + return (outOfRange(a.x, b.x, p.x) || + outOfRange(a.y, b.y, p.y) || + outOfRange(a.z, b.z, p.z)); +} + +bool outOfRange(vec4 a, vec4 b, vec4 p) { + return outOfRange(a.xyz, b.xyz, p.xyz); +} + +uniform float pickId; +uniform vec3 clipBounds[2]; + +varying vec3 worldPosition; +varying float pixelArcLength; +varying vec4 fragColor; + +void main() { + if (outOfRange(clipBounds[0], clipBounds[1], worldPosition)) discard; + + gl_FragColor = vec4(pickId/255.0, packFloat(pixelArcLength).xyz); 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z={model:u,view:g,projection:f,clipBounds:P,tubeScale:this.tubeScale,vectorScale:this.vectorScale,coneScale:this.coneScale,coneOffset:this.coneOffset,pickId:this.pickId/255},F=this.pickShader;F.bind(),F.uniforms=z,this.triangleCount>0&&(this.triangleVAO.bind(),p.drawArrays(p.TRIANGLES,0,this.triangleCount*3),this.triangleVAO.unbind())},l.pick=function(b){if(!b||b.id!==this.pickId)return null;var p=b.value[0]+256*b.value[1]+65536*b.value[2],u=this.cells[p],g=this.positions[u[1]].slice(0,3),f={position:g,dataCoordinate:g,index:Math.floor(u[1]/48)};return this.traceType==="cone"?f.index=Math.floor(u[1]/48):this.traceType==="streamtube"&&(f.intensity=this.intensity[u[1]],f.velocity=this.vectors[u[1]].slice(0,3),f.divergence=this.vectors[u[1]][3],f.index=p),f},l.dispose=function(){this.texture.dispose(),this.triShader.dispose(),this.pickShader.dispose(),this.triangleVAO.dispose(),this.trianglePositions.dispose(),this.triangleVectors.dispose(),this.triangleColors.dispose(),this.triangleUVs.dispose(),this.triangleIds.dispose()};function S(b,p){var u=o(b,p.meshShader.vertex,p.meshShader.fragment,null,p.meshShader.attributes);return u.attributes.position.location=0,u.attributes.color.location=2,u.attributes.uv.location=3,u.attributes.vector.location=4,u}function M(b,p){var u=o(b,p.pickShader.vertex,p.pickShader.fragment,null,p.pickShader.attributes);return u.attributes.position.location=0,u.attributes.id.location=1,u.attributes.vector.location=4,u}function y(b,p,u){var g=u.shaders;arguments.length===1&&(p=b,b=p.gl);var f=S(b,g),P=M(b,g),L=i(b,c(new Uint8Array([255,255,255,255]),[1,1,4]));L.generateMipmap(),L.minFilter=b.LINEAR_MIPMAP_LINEAR,L.magFilter=b.LINEAR;var z=a(b),F=a(b),B=a(b),O=a(b),I=a(b),N=n(b,[{buffer:z,type:b.FLOAT,size:4},{buffer:I,type:b.UNSIGNED_BYTE,size:4,normalized:!0},{buffer:B,type:b.FLOAT,size:4},{buffer:O,type:b.FLOAT,size:2},{buffer:F,type:b.FLOAT,size:4}]),U=new T(b,L,f,P,z,F,I,B,O,N,u.traceType||"cone");return U.update(p),U}e.exports=y},9127:function(e,t,r){"use strict";e.exports=n;var o=r(6204),a=r(5771);function n(i){return a(o(i))}},9131:function(e,t,r){var o=r(5177),a=r(9288);e.exports=n;function n(i,s){return s=s||1,i[0]=Math.random(),i[1]=Math.random(),i[2]=Math.random(),i[3]=Math.random(),o(i,i),a(i,i,s),i}},9165:function(e,t,r){"use strict";e.exports=T;var o=r(2762),a=r(8116),n=r(3436),i=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1];function s(l,_,w,S){this.gl=l,this.shader=S,this.buffer=_,this.vao=w,this.pixelRatio=1,this.bounds=[[1/0,1/0,1/0],[-1/0,-1/0,-1/0]],this.clipBounds=[[-1/0,-1/0,-1/0],[1/0,1/0,1/0]],this.lineWidth=[1,1,1],this.capSize=[10,10,10],this.lineCount=[0,0,0],this.lineOffset=[0,0,0],this.opacity=1,this.hasAlpha=!1}var h=s.prototype;h.isOpaque=function(){return!this.hasAlpha},h.isTransparent=function(){return this.hasAlpha},h.drawTransparent=h.draw=function(l){var _=this.gl,w=this.shader.uniforms;this.shader.bind();var S=w.view=l.view||i,M=w.projection=l.projection||i;w.model=l.model||i,w.clipBounds=this.clipBounds,w.opacity=this.opacity;var y=S[12],b=S[13],p=S[14],u=S[15],g=l._ortho||!1,f=g?2:1,P=f*this.pixelRatio*(M[3]*y+M[7]*b+M[11]*p+M[15]*u)/_.drawingBufferHeight;this.vao.bind();for(var L=0;L<3;++L)_.lineWidth(this.lineWidth[L]*this.pixelRatio),w.capSize=this.capSize[L]*P,this.lineCount[L]&&_.drawArrays(_.LINES,this.lineOffset[L],this.lineCount[L]);this.vao.unbind()};function c(l,_){for(var w=0;w<3;++w)l[0][w]=Math.min(l[0][w],_[w]),l[1][w]=Math.max(l[1][w],_[w])}var m=function(){for(var l=new Array(3),_=0;_<3;++_){for(var w=[],S=1;S<=2;++S)for(var M=-1;M<=1;M+=2){var y=(S+_)%3,b=[0,0,0];b[y]=M,w.push(b)}l[_]=w}return l}();function v(l,_,w,S){for(var M=m[S],y=0;y0){var z=g.slice();z[p]+=P[1][p],M.push(g[0],g[1],g[2],L[0],L[1],L[2],L[3],0,0,0,z[0],z[1],z[2],L[0],L[1],L[2],L[3],0,0,0),c(this.bounds,z),b+=2+v(M,z,L,p)}}}this.lineCount[p]=b-this.lineOffset[p]}this.buffer.update(M)}},h.dispose=function(){this.shader.dispose(),this.buffer.dispose(),this.vao.dispose()};function T(l){var _=l.gl,w=o(_),S=a(_,[{buffer:w,type:_.FLOAT,size:3,offset:0,stride:40},{buffer:w,type:_.FLOAT,size:4,offset:12,stride:40},{buffer:w,type:_.FLOAT,size:3,offset:28,stride:40}]),M=n(_);M.attributes.position.location=0,M.attributes.color.location=1,M.attributes.offset.location=2;var y=new s(_,w,S,M);return y.update(l),y}},9215:function(e,t,r){"use strict";e.exports=c;var o=r(4769),a=r(2478);function n(m,v,T){return Math.min(v,Math.max(m,T))}function i(m,v,T){this.dimension=m.length,this.bounds=[new Array(this.dimension),new Array(this.dimension)];for(var l=0;l=T-1)for(var b=w.length-1,u=m-v[T-1],p=0;p=T-1)for(var y=w.length-1,b=m-v[T-1],p=0;p=0;--T)if(m[--v])return!1;return!0},s.jump=function(m){var v=this.lastT(),T=this.dimension;if(!(m0;--p)l.push(n(M[p-1],y[p-1],arguments[p])),_.push(0)}},s.push=function(m){var v=this.lastT(),T=this.dimension;if(!(m1e-6?1/S:0;this._time.push(m);for(var u=T;u>0;--u){var g=n(y[u-1],b[u-1],arguments[u]);l.push(g),_.push((g-l[w++])*p)}}},s.set=function(m){var v=this.dimension;if(!(m0;--M)T.push(n(w[M-1],S[M-1],arguments[M])),l.push(0)}},s.move=function(m){var v=this.lastT(),T=this.dimension;if(!(m<=v||arguments.length!==T+1)){var l=this._state,_=this._velocity,w=l.length-this.dimension,S=this.bounds,M=S[0],y=S[1],b=m-v,p=b>1e-6?1/b:0;this._time.push(m);for(var u=T;u>0;--u){var g=arguments[u];l.push(n(M[u-1],y[u-1],l[w++]+g)),_.push(g*p)}}},s.idle=function(m){var v=this.lastT();if(!(m=0;--p)l.push(n(M[p],y[p],l[w]+b*_[w])),_.push(0),w+=1}};function h(m){for(var v=new Array(m),T=0;T1&&i.indexOf("Macintosh")!==-1&&i.indexOf("Safari")!==-1&&(s=!0),s}},9226:function(e){e.exports=t;function t(r,o){return r[0]=Math.ceil(o[0]),r[1]=Math.ceil(o[1]),r[2]=Math.ceil(o[2]),r}},9265:function(e){e.exports=t;function t(r,o){return r[0]===o[0]&&r[1]===o[1]&&r[2]===o[2]}},9288:function(e){e.exports=t;function t(r,o,a){return r[0]=o[0]*a,r[1]=o[1]*a,r[2]=o[2]*a,r[3]=o[3]*a,r}},9346:function(e){"use strict";var t=new Float64Array(4),r=new Float64Array(4),o=new Float64Array(4);function a(n,i,s,h,c){t.length=v?(u=1,f=v+2*_+S):(u=-_/v,f=_*u+S)):(u=0,w>=0?(g=0,f=S):-w>=l?(g=1,f=l+2*w+S):(g=-w/l,f=w*g+S));else if(g<0)g=0,_>=0?(u=0,f=S):-_>=v?(u=1,f=v+2*_+S):(u=-_/v,f=_*u+S);else{var P=1/p;u*=P,g*=P,f=u*(v*u+T*g+2*_)+g*(T*u+l*g+2*w)+S}else{var L,z,F,B;u<0?(L=T+_,z=l+w,z>L?(F=z-L,B=v-2*T+l,F>=B?(u=1,g=0,f=v+2*_+S):(u=F/B,g=1-u,f=u*(v*u+T*g+2*_)+g*(T*u+l*g+2*w)+S)):(u=0,z<=0?(g=1,f=l+2*w+S):w>=0?(g=0,f=S):(g=-w/l,f=w*g+S))):g<0?(L=T+w,z=v+_,z>L?(F=z-L,B=v-2*T+l,F>=B?(g=1,u=0,f=l+2*w+S):(g=F/B,u=1-g,f=u*(v*u+T*g+2*_)+g*(T*u+l*g+2*w)+S)):(g=0,z<=0?(u=1,f=v+2*_+S):_>=0?(u=0,f=S):(u=-_/v,f=_*u+S))):(F=l+w-T-_,F<=0?(u=0,g=1,f=l+2*w+S):(B=v-2*T+l,F>=B?(u=1,g=0,f=v+2*_+S):(u=F/B,g=1-u,f=u*(v*u+T*g+2*_)+g*(T*u+l*g+2*w)+S)))}for(var O=1-u-g,m=0;mw)for(l=w;l<_;l++)this.gl.enableVertexAttribArray(l);else if(w>_)for(l=_;l=0){for(var O=B.type.charAt(B.type.length-1)|0,I=new Array(O),N=0;N=0;)U+=1;z[F]=U}var W=new Array(w.length);function Q(){y.program=i.program(b,y._vref,y._fref,L,z);for(var ue=0;ueie&&ee>0){var re=(j[ee][0]-ie)/(j[ee][0]-j[ee-1][0]);return j[ee][1]*(1-re)+re*j[ee-1][1]}}return 1}var N=[0,0,0],U={showSurface:!1,showContour:!1,projections:[f.slice(),f.slice(),f.slice()],clipBounds:[[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]],[[0,0,0],[0,0,0]]]};function W(ie,j){var ee,re,ce,be=j.axes&&j.axes.lastCubeProps.axis||N,Se=j.showSurface,De=j.showContour;for(ee=0;ee<3;++ee)for(Se=Se||j.surfaceProject[ee],re=0;re<3;++re)De=De||j.contourProject[ee][re];for(ee=0;ee<3;++ee){var Fe=U.projections[ee];for(re=0;re<16;++re)Fe[re]=0;for(re=0;re<4;++re)Fe[5*re]=1;Fe[5*ee]=0,Fe[12+ee]=j.axesBounds[+(be[ee]>0)][ee],l(Fe,ie.model,Fe);var Ze=U.clipBounds[ee];for(ce=0;ce<2;++ce)for(re=0;re<3;++re)Ze[ce][re]=ie.clipBounds[ce][re];Ze[0][ee]=-1e8,Ze[1][ee]=1e8}return U.showSurface=Se,U.showContour=De,U}var Q={model:f,view:f,projection:f,inverseModel:f.slice(),lowerBound:[0,0,0],upperBound:[0,0,0],colorMap:0,clipBounds:[[0,0,0],[0,0,0]],height:0,contourTint:0,contourColor:[0,0,0,1],permutation:[1,0,0,0,1,0,0,0,1],zOffset:-1e-4,objectOffset:[0,0,0],kambient:1,kdiffuse:1,kspecular:1,lightPosition:[1e3,1e3,1e3],eyePosition:[0,0,0],roughness:1,fresnel:1,opacity:1,vertexColor:0},ue=f.slice(),se=[1,0,0,0,1,0,0,0,1];function pe(ie,j){ie=ie||{};var ee=this.gl;ee.disable(ee.CULL_FACE),this._colorMap.bind(0);var re=Q;re.model=ie.model||f,re.view=ie.view||f,re.projection=ie.projection||f,re.lowerBound=[this.bounds[0][0],this.bounds[0][1],this.colorBounds[0]||this.bounds[0][2]],re.upperBound=[this.bounds[1][0],this.bounds[1][1],this.colorBounds[1]||this.bounds[1][2]],re.objectOffset=this.objectOffset,re.contourColor=this.contourColor[0],re.inverseModel=_(re.inverseModel,re.model);for(var ce=0;ce<2;++ce)for(var be=re.clipBounds[ce],Se=0;Se<3;++Se)be[Se]=Math.min(Math.max(this.clipBounds[ce][Se],-1e8),1e8);re.kambient=this.ambientLight,re.kdiffuse=this.diffuseLight,re.kspecular=this.specularLight,re.roughness=this.roughness,re.fresnel=this.fresnel,re.opacity=this.opacity,re.height=0,re.permutation=se,re.vertexColor=this.vertexColor;var De=ue;for(l(De,re.view,re.model),l(De,re.projection,De),_(De,De),ce=0;ce<3;++ce)re.eyePosition[ce]=De[12+ce]/De[15];var Fe=De[15];for(ce=0;ce<3;++ce)Fe+=this.lightPosition[ce]*De[4*ce+3];for(ce=0;ce<3;++ce){var Ze=De[12+ce];for(Se=0;Se<3;++Se)Ze+=De[4*Se+ce]*this.lightPosition[Se];re.lightPosition[ce]=Ze/Fe}var at=W(re,this);if(at.showSurface){for(this._shader.bind(),this._shader.uniforms=re,this._vao.bind(),this.showSurface&&this._vertexCount&&this._vao.draw(ee.TRIANGLES,this._vertexCount),ce=0;ce<3;++ce)!this.surfaceProject[ce]||!this.vertexCount||(this._shader.uniforms.model=at.projections[ce],this._shader.uniforms.clipBounds=at.clipBounds[ce],this._vao.draw(ee.TRIANGLES,this._vertexCount));this._vao.unbind()}if(at.showContour){var nt=this._contourShader;re.kambient=1,re.kdiffuse=0,re.kspecular=0,re.opacity=1,nt.bind(),nt.uniforms=re;var tt=this._contourVAO;for(tt.bind(),ce=0;ce<3;++ce)for(nt.uniforms.permutation=L[ce],ee.lineWidth(this.contourWidth[ce]*this.pixelRatio),Se=0;Se>4)/16)/255,ce=Math.floor(re),be=re-ce,Se=j[1]*(ie.value[1]+(ie.value[2]&15)/16)/255,De=Math.floor(Se),Fe=Se-De;ce+=1,De+=1;var Ze=ee.position;Ze[0]=Ze[1]=Ze[2]=0;for(var at=0;at<2;++at)for(var nt=at?be:1-be,tt=0;tt<2;++tt)for(var ut=tt?Fe:1-Fe,Me=ce+at,_e=De+tt,fe=nt*ut,Oe=0;Oe<3;++Oe)Ze[Oe]+=this._field[Oe].get(Me,_e)*fe;for(var rt=this._pickResult.level,st=0;st<3;++st)if(rt[st]=w.le(this.contourLevels[st],Ze[st]),rt[st]<0)this.contourLevels[st].length>0&&(rt[st]=0);else if(rt[st]Math.abs(Pt-Ze[st])&&(rt[st]+=1)}for(ee.index[0]=be<.5?ce:ce+1,ee.index[1]=Fe<.5?De:De+1,ee.uv[0]=re/j[0],ee.uv[1]=Se/j[1],Oe=0;Oe<3;++Oe)ee.dataCoordinate[Oe]=this._field[Oe].get(ee.index[0],ee.index[1]);return ee},O.padField=function(ie,j){var ee=j.shape.slice(),re=ie.shape.slice();c.assign(ie.lo(1,1).hi(ee[0],ee[1]),j),c.assign(ie.lo(1).hi(ee[0],1),j.hi(ee[0],1)),c.assign(ie.lo(1,re[1]-1).hi(ee[0],1),j.lo(0,ee[1]-1).hi(ee[0],1)),c.assign(ie.lo(0,1).hi(1,ee[1]),j.hi(1)),c.assign(ie.lo(re[0]-1,1).hi(1,ee[1]),j.lo(ee[0]-1)),ie.set(0,0,j.get(0,0)),ie.set(0,re[1]-1,j.get(0,ee[1]-1)),ie.set(re[0]-1,0,j.get(ee[0]-1,0)),ie.set(re[0]-1,re[1]-1,j.get(ee[0]-1,ee[1]-1))};function $(ie,j){return Array.isArray(ie)?[j(ie[0]),j(ie[1]),j(ie[2])]:[j(ie),j(ie),j(ie)]}function J(ie){return Array.isArray(ie)?ie.length===3?[ie[0],ie[1],ie[2],1]:[ie[0],ie[1],ie[2],ie[3]]:[0,0,0,1]}function X(ie){if(Array.isArray(ie)){if(Array.isArray(ie))return[J(ie[0]),J(ie[1]),J(ie[2])];var j=J(ie);return[j.slice(),j.slice(),j.slice()]}}O.update=function(ie){ie=ie||{},this.objectOffset=ie.objectOffset||this.objectOffset,this.dirty=!0,"contourWidth"in ie&&(this.contourWidth=$(ie.contourWidth,Number)),"showContour"in ie&&(this.showContour=$(ie.showContour,Boolean)),"showSurface"in ie&&(this.showSurface=!!ie.showSurface),"contourTint"in ie&&(this.contourTint=$(ie.contourTint,Boolean)),"contourColor"in ie&&(this.contourColor=X(ie.contourColor)),"contourProject"in ie&&(this.contourProject=$(ie.contourProject,function(mi){return $(mi,Boolean)})),"surfaceProject"in ie&&(this.surfaceProject=ie.surfaceProject),"dynamicColor"in ie&&(this.dynamicColor=X(ie.dynamicColor)),"dynamicTint"in ie&&(this.dynamicTint=$(ie.dynamicTint,Number)),"dynamicWidth"in ie&&(this.dynamicWidth=$(ie.dynamicWidth,Number)),"opacity"in ie&&(this.opacity=ie.opacity),"opacityscale"in ie&&(this.opacityscale=ie.opacityscale),"colorBounds"in ie&&(this.colorBounds=ie.colorBounds),"vertexColor"in ie&&(this.vertexColor=ie.vertexColor?1:0),"colormap"in ie&&this._colorMap.setPixels(this.genColormap(ie.colormap,this.opacityscale));var j=ie.field||ie.coords&&ie.coords[2]||null,ee=!1;if(j||(this._field[2].shape[0]||this._field[2].shape[2]?j=this._field[2].lo(1,1).hi(this._field[2].shape[0]-2,this._field[2].shape[1]-2):j=this._field[2].hi(0,0)),"field"in ie||"coords"in ie){var re=(j.shape[0]+2)*(j.shape[1]+2);re>this._field[2].data.length&&(s.freeFloat(this._field[2].data),this._field[2].data=s.mallocFloat(o.nextPow2(re))),this._field[2]=v(this._field[2].data,[j.shape[0]+2,j.shape[1]+2]),this.padField(this._field[2],j),this.shape=j.shape.slice();for(var ce=this.shape,be=0;be<2;++be)this._field[2].size>this._field[be].data.length&&(s.freeFloat(this._field[be].data),this._field[be].data=s.mallocFloat(this._field[2].size)),this._field[be]=v(this._field[be].data,[ce[0]+2,ce[1]+2]);if(ie.coords){var Se=ie.coords;if(!Array.isArray(Se)||Se.length!==3)throw new Error("gl-surface: invalid coordinates for x/y");for(be=0;be<2;++be){var De=Se[be];for(tt=0;tt<2;++tt)if(De.shape[tt]!==ce[tt])throw new Error("gl-surface: coords have incorrect shape");this.padField(this._field[be],De)}}else if(ie.ticks){var Fe=ie.ticks;if(!Array.isArray(Fe)||Fe.length!==2)throw new Error("gl-surface: invalid ticks");for(be=0;be<2;++be){var Ze=Fe[be];if((Array.isArray(Ze)||Ze.length)&&(Ze=v(Ze)),Ze.shape[0]!==ce[be])throw new Error("gl-surface: invalid tick length");var at=v(Ze.data,ce);at.stride[be]=Ze.stride[0],at.stride[be^1]=0,this.padField(this._field[be],at)}}else{for(be=0;be<2;++be){var nt=[0,0];nt[be]=1,this._field[be]=v(this._field[be].data,[ce[0]+2,ce[1]+2],nt,0)}this._field[0].set(0,0,0);for(var tt=0;tt0){for(var Ya=0;Ya<5;++Ya)ar.pop();Te-=1}continue e}}}za.push(Te)}this._contourOffsets[tr]=ha,this._contourCounts[tr]=za}var ri=s.mallocFloat(ar.length);for(be=0;be=0&&(p=y|0,b+=g*p,u-=p),new w(this.data,u,g,b)},S.step=function(y){var b=this.shape[0],p=this.stride[0],u=this.offset,g=0,f=Math.ceil;return typeof y=="number"&&(g=y|0,g<0?(u+=p*(b-1),b=f(-b/g)):b=f(b/g),p*=g),new w(this.data,b,p,u)},S.transpose=function(y){y=y===void 0?0:y|0;var b=this.shape,p=this.stride;return new w(this.data,b[y],p[y],this.offset)},S.pick=function(y){var b=[],p=[],u=this.offset;typeof y=="number"&&y>=0?u=u+this.stride[0]*y|0:(b.push(this.shape[0]),p.push(this.stride[0]));var g=l[b.length+1];return g(this.data,b,p,u)},function(y,b,p,u){return new w(y,b[0],p[0],u)}},2:function(T,l,_){function w(M,y,b,p,u,g){this.data=M,this.shape=[y,b],this.stride=[p,u],this.offset=g|0}var 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w(this.data,u[y],u[b],u[p],g[y],g[b],g[p],this.offset)},S.pick=function(y,b,p){var u=[],g=[],f=this.offset;typeof y=="number"&&y>=0?f=f+this.stride[0]*y|0:(u.push(this.shape[0]),g.push(this.stride[0])),typeof b=="number"&&b>=0?f=f+this.stride[1]*b|0:(u.push(this.shape[1]),g.push(this.stride[1])),typeof p=="number"&&p>=0?f=f+this.stride[2]*p|0:(u.push(this.shape[2]),g.push(this.stride[2]));var P=l[u.length+1];return P(this.data,u,g,f)},function(y,b,p,u){return new w(y,b[0],b[1],b[2],p[0],p[1],p[2],u)}},4:function(T,l,_){function w(M,y,b,p,u,g,f,P,L,z){this.data=M,this.shape=[y,b,p,u],this.stride=[g,f,P,L],this.offset=z|0}var S=w.prototype;return S.dtype=T,S.dimension=4,Object.defineProperty(S,"size",{get:function(){return this.shape[0]*this.shape[1]*this.shape[2]*this.shape[3]}}),Object.defineProperty(S,"order",{get:_}),S.set=function(y,b,p,u,g){return T==="generic"?this.data.set(this.offset+this.stride[0]*y+this.stride[1]*b+this.stride[2]*p+this.stride[3]*u,g):this.data[this.offset+this.stride[0]*y+this.stride[1]*b+this.stride[2]*p+this.stride[3]*u]=g},S.get=function(y,b,p,u){return T==="generic"?this.data.get(this.offset+this.stride[0]*y+this.stride[1]*b+this.stride[2]*p+this.stride[3]*u):this.data[this.offset+this.stride[0]*y+this.stride[1]*b+this.stride[2]*p+this.stride[3]*u]},S.index=function(y,b,p,u){return this.offset+this.stride[0]*y+this.stride[1]*b+this.stride[2]*p+this.stride[3]*u},S.hi=function(y,b,p,u){return new w(this.data,typeof y!="number"||y<0?this.shape[0]:y|0,typeof b!="number"||b<0?this.shape[1]:b|0,typeof p!="number"||p<0?this.shape[2]:p|0,typeof u!="number"||u<0?this.shape[3]:u|0,this.stride[0],this.stride[1],this.stride[2],this.stride[3],this.offset)},S.lo=function(y,b,p,u){var g=this.offset,f=0,P=this.shape[0],L=this.shape[1],z=this.shape[2],F=this.shape[3],B=this.stride[0],O=this.stride[1],I=this.stride[2],N=this.stride[3];return typeof y=="number"&&y>=0&&(f=y|0,g+=B*f,P-=f),typeof b=="number"&&b>=0&&(f=b|0,g+=O*f,L-=f),typeof p=="number"&&p>=0&&(f=p|0,g+=I*f,z-=f),typeof u=="number"&&u>=0&&(f=u|0,g+=N*f,F-=f),new w(this.data,P,L,z,F,B,O,I,N,g)},S.step=function(y,b,p,u){var g=this.shape[0],f=this.shape[1],P=this.shape[2],L=this.shape[3],z=this.stride[0],F=this.stride[1],B=this.stride[2],O=this.stride[3],I=this.offset,N=0,U=Math.ceil;return typeof y=="number"&&(N=y|0,N<0?(I+=z*(g-1),g=U(-g/N)):g=U(g/N),z*=N),typeof b=="number"&&(N=b|0,N<0?(I+=F*(f-1),f=U(-f/N)):f=U(f/N),F*=N),typeof p=="number"&&(N=p|0,N<0?(I+=B*(P-1),P=U(-P/N)):P=U(P/N),B*=N),typeof u=="number"&&(N=u|0,N<0?(I+=O*(L-1),L=U(-L/N)):L=U(L/N),O*=N),new w(this.data,g,f,P,L,z,F,B,O,I)},S.transpose=function(y,b,p,u){y=y===void 0?0:y|0,b=b===void 0?1:b|0,p=p===void 0?2:p|0,u=u===void 0?3:u|0;var g=this.shape,f=this.stride;return new w(this.data,g[y],g[b],g[p],g[u],f[y],f[b],f[p],f[u],this.offset)},S.pick=function(y,b,p,u){var g=[],f=[],P=this.offset;typeof y=="number"&&y>=0?P=P+this.stride[0]*y|0:(g.push(this.shape[0]),f.push(this.stride[0])),typeof b=="number"&&b>=0?P=P+this.stride[1]*b|0:(g.push(this.shape[1]),f.push(this.stride[1])),typeof p=="number"&&p>=0?P=P+this.stride[2]*p|0:(g.push(this.shape[2]),f.push(this.stride[2])),typeof u=="number"&&u>=0?P=P+this.stride[3]*u|0:(g.push(this.shape[3]),f.push(this.stride[3]));var L=l[g.length+1];return L(this.data,g,f,P)},function(y,b,p,u){return new w(y,b[0],b[1],b[2],b[3],p[0],p[1],p[2],p[3],u)}},5:function(l,_,w){function S(y,b,p,u,g,f,P,L,z,F,B,O){this.data=y,this.shape=[b,p,u,g,f],this.stride=[P,L,z,F,B],this.offset=O|0}var M=S.prototype;return M.dtype=l,M.dimension=5,Object.defineProperty(M,"size",{get:function(){return this.shape[0]*this.shape[1]*this.shape[2]*this.shape[3]*this.shape[4]}}),Object.defineProperty(M,"order",{get:w}),M.set=function(b,p,u,g,f,P){return l==="generic"?this.data.set(this.offset+this.stride[0]*b+this.stride[1]*p+this.stride[2]*u+this.stride[3]*g+this.stride[4]*f,P):this.data[this.offset+this.stride[0]*b+this.stride[1]*p+this.stride[2]*u+this.stride[3]*g+this.stride[4]*f]=P},M.get=function(b,p,u,g,f){return l==="generic"?this.data.get(this.offset+this.stride[0]*b+this.stride[1]*p+this.stride[2]*u+this.stride[3]*g+this.stride[4]*f):this.data[this.offset+this.stride[0]*b+this.stride[1]*p+this.stride[2]*u+this.stride[3]*g+this.stride[4]*f]},M.index=function(b,p,u,g,f){return this.offset+this.stride[0]*b+this.stride[1]*p+this.stride[2]*u+this.stride[3]*g+this.stride[4]*f},M.hi=function(b,p,u,g,f){return new S(this.data,typeof b!="number"||b<0?this.shape[0]:b|0,typeof p!="number"||p<0?this.shape[1]:p|0,typeof u!="number"||u<0?this.shape[2]:u|0,typeof g!="number"||g<0?this.shape[3]:g|0,typeof f!="number"||f<0?this.shape[4]:f|0,this.stride[0],this.stride[1],this.stride[2],this.stride[3],this.stride[4],this.offset)},M.lo=function(b,p,u,g,f){var P=this.offset,L=0,z=this.shape[0],F=this.shape[1],B=this.shape[2],O=this.shape[3],I=this.shape[4],N=this.stride[0],U=this.stride[1],W=this.stride[2],Q=this.stride[3],ue=this.stride[4];return typeof b=="number"&&b>=0&&(L=b|0,P+=N*L,z-=L),typeof p=="number"&&p>=0&&(L=p|0,P+=U*L,F-=L),typeof u=="number"&&u>=0&&(L=u|0,P+=W*L,B-=L),typeof g=="number"&&g>=0&&(L=g|0,P+=Q*L,O-=L),typeof f=="number"&&f>=0&&(L=f|0,P+=ue*L,I-=L),new S(this.data,z,F,B,O,I,N,U,W,Q,ue,P)},M.step=function(b,p,u,g,f){var P=this.shape[0],L=this.shape[1],z=this.shape[2],F=this.shape[3],B=this.shape[4],O=this.stride[0],I=this.stride[1],N=this.stride[2],U=this.stride[3],W=this.stride[4],Q=this.offset,ue=0,se=Math.ceil;return typeof b=="number"&&(ue=b|0,ue<0?(Q+=O*(P-1),P=se(-P/ue)):P=se(P/ue),O*=ue),typeof p=="number"&&(ue=p|0,ue<0?(Q+=I*(L-1),L=se(-L/ue)):L=se(L/ue),I*=ue),typeof u=="number"&&(ue=u|0,ue<0?(Q+=N*(z-1),z=se(-z/ue)):z=se(z/ue),N*=ue),typeof g=="number"&&(ue=g|0,ue<0?(Q+=U*(F-1),F=se(-F/ue)):F=se(F/ue),U*=ue),typeof f=="number"&&(ue=f|0,ue<0?(Q+=W*(B-1),B=se(-B/ue)):B=se(B/ue),W*=ue),new S(this.data,P,L,z,F,B,O,I,N,U,W,Q)},M.transpose=function(b,p,u,g,f){b=b===void 0?0:b|0,p=p===void 0?1:p|0,u=u===void 0?2:u|0,g=g===void 0?3:g|0,f=f===void 0?4:f|0;var P=this.shape,L=this.stride;return new S(this.data,P[b],P[p],P[u],P[g],P[f],L[b],L[p],L[u],L[g],L[f],this.offset)},M.pick=function(b,p,u,g,f){var P=[],L=[],z=this.offset;typeof b=="number"&&b>=0?z=z+this.stride[0]*b|0:(P.push(this.shape[0]),L.push(this.stride[0])),typeof p=="number"&&p>=0?z=z+this.stride[1]*p|0:(P.push(this.shape[1]),L.push(this.stride[1])),typeof u=="number"&&u>=0?z=z+this.stride[2]*u|0:(P.push(this.shape[2]),L.push(this.stride[2])),typeof 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z.glplot.canvas&&(z.glplot.canvas.addEventListener("mouseup",function(){N(z)}),z.glplot.canvas.addEventListener("touchstart",function(){w=!0}),z.glplot.canvas.addEventListener("wheel",function(U){if(B._context._scrollZoom.gl3d){if(z.camera._ortho){var W=U.deltaX>U.deltaY?1.1:.9090909090909091,Q=z.glplot.getAspectratio();z.glplot.setAspectratio({x:W*Q.x,y:W*Q.y,z:W*Q.z})}N(z)}},e?{passive:!1}:!1),z.glplot.canvas.addEventListener("mousemove",function(){if(z.fullSceneLayout.dragmode!==!1&&z.camera.mouseListener.buttons!==0){var U=I();z.graphDiv.emit("plotly_relayouting",U)}}),z.staticMode||z.glplot.canvas.addEventListener("webglcontextlost",function(U){B&&B.emit&&B.emit("plotly_webglcontextlost",{event:U,layer:z.id})},!1)),z.glplot.oncontextloss=function(){z.recoverContext()},z.glplot.onrender=function(){z.render()},!0},M.render=function(){var z=this,F=z.graphDiv,B,O=z.svgContainer,I=z.container.getBoundingClientRect();F._fullLayout._calcInverseTransform(F);var N=F._fullLayout._invScaleX,U=F._fullLayout._invScaleY,W=I.width*N,Q=I.height*U;O.setAttributeNS(null,"viewBox","0 0 "+W+" "+Q),O.setAttributeNS(null,"width",W),O.setAttributeNS(null,"height",Q),v(z),z.glplot.axes.update(z.axesOptions);for(var ue=Object.keys(z.traces),se=null,pe=z.glplot.selection,V=0;V")):B.type==="isosurface"||B.type==="volume"?(ie.valueLabel=a.hoverLabelText(z._mockAxis,z._mockAxis.d2l(pe.traceCoordinate[3]),B.valuehoverformat),be.push("value: "+ie.valueLabel),pe.textLabel&&be.push(pe.textLabel),ce=be.join("
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if(ut==="auto"||ut==="data"){var _e=[1,1,1];for(U=0;U<3;++U){Q=se[b[U]],ue=Q.type;var fe=ie[ue];_e[U]=Math.pow(fe.acc,1/fe.count)/$[U]}ut==="data"||Math.max.apply(null,_e)/Math.min.apply(null,_e)<=4?tt=_e:tt=[1,1,1]}else throw new Error("scene.js aspectRatio was not one of the enumerated types");se.aspectratio.x=pe.aspectratio.x=tt[0],se.aspectratio.y=pe.aspectratio.y=tt[1],se.aspectratio.z=pe.aspectratio.z=tt[2],O.glplot.setAspectratio(se.aspectratio),O.viewInitial.aspectratio||(O.viewInitial.aspectratio={x:se.aspectratio.x,y:se.aspectratio.y,z:se.aspectratio.z}),O.viewInitial.aspectmode||(O.viewInitial.aspectmode=se.aspectmode);var Oe=se.domain||null,rt=F._size||null;if(Oe&&rt){var st=O.container.style;st.position="absolute",st.left=rt.l+Oe.x[0]*rt.w+"px",st.top=rt.t+(1-Oe.y[1])*rt.h+"px",st.width=rt.w*(Oe.x[1]-Oe.x[0])+"px",st.height=rt.h*(Oe.y[1]-Oe.y[0])+"px"}O.glplot.redraw()}},M.destroy=function(){var z=this;z.glplot&&(z.camera.mouseListener.enabled=!1,z.container.removeEventListener("wheel",z.camera.wheelListener),z.camera=null,z.glplot.dispose(),z.container.parentNode.removeChild(z.container),z.glplot=null)};function g(z){return[[z.eye.x,z.eye.y,z.eye.z],[z.center.x,z.center.y,z.center.z],[z.up.x,z.up.y,z.up.z]]}function f(z){return{up:{x:z.up[0],y:z.up[1],z:z.up[2]},center:{x:z.center[0],y:z.center[1],z:z.center[2]},eye:{x:z.eye[0],y:z.eye[1],z:z.eye[2]},projection:{type:z._ortho===!0?"orthographic":"perspective"}}}M.getCamera=function(){var z=this;return z.camera.view.recalcMatrix(z.camera.view.lastT()),f(z.camera)},M.setViewport=function(z){var F=this,B=z.camera;F.camera.lookAt.apply(this,g(B)),F.glplot.setAspectratio(z.aspectratio);var O=B.projection.type==="orthographic",I=F.camera._ortho;O!==I&&(F.glplot.redraw(),F.glplot.clearRGBA(),F.glplot.dispose(),F.initializeGLPlot())},M.isCameraChanged=function(z){var F=this,B=F.getCamera(),O=r.nestedProperty(z,F.id+".camera"),I=O.get();function N(ue,se,pe,V){var $=["up","center","eye"],J=["x","y","z"];return se[$[pe]]&&ue[$[pe]][J[V]]===se[$[pe]][J[V]]}var U=!1;if(I===void 0)U=!0;else{for(var W=0;W<3;W++)for(var Q=0;Q<3;Q++)if(!N(B,I,W,Q)){U=!0;break}(!I.projection||B.projection&&B.projection.type!==I.projection.type)&&(U=!0)}return U},M.isAspectChanged=function(z){var F=this,B=F.glplot.getAspectratio(),O=r.nestedProperty(z,F.id+".aspectratio"),I=O.get();return I===void 0||I.x!==B.x||I.y!==B.y||I.z!==B.z},M.saveLayout=function(z){var F=this,B=F.fullLayout,O,I,N,U,W,Q,ue=F.isCameraChanged(z),se=F.isAspectChanged(z),pe=ue||se;if(pe){var V={};if(ue&&(O=F.getCamera(),I=r.nestedProperty(z,F.id+".camera"),N=I.get(),V[F.id+".camera"]=N),se&&(U=F.glplot.getAspectratio(),W=r.nestedProperty(z,F.id+".aspectratio"),Q=W.get(),V[F.id+".aspectratio"]=Q),t.call("_storeDirectGUIEdit",z,B._preGUI,V),ue){I.set(O);var 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d=Kn(),x=Wh(),A=ts().extendFlat,E=dc().overrideAll;q.exports=E({visible:x.visible,showspikes:{valType:"boolean",dflt:!0},spikesides:{valType:"boolean",dflt:!0},spikethickness:{valType:"number",min:0,dflt:2},spikecolor:{valType:"color",dflt:d.defaultLine},showbackground:{valType:"boolean",dflt:!1},backgroundcolor:{valType:"color",dflt:"rgba(204, 204, 204, 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* thickness * abs(dot(endJoinDirection, currNormal)) * .5; + endCutoff = vec4(bCoord, bCoord); + endCutoff.zw += vec2(-endJoinDirection.y, endJoinDirection.x) / scaleRatio; + endCutoff = endCutoff * scaleRatio.xyxy + translate.xyxy * viewport.zwzw; + endCutoff += viewport.xyxy; + endCutoff += endMiterWidth.xyxy; + } + } +} +`,l=` +precision highp float; + +uniform float dashLength, pixelRatio, thickness, opacity, id, miterMode; +uniform sampler2D dashTexture; + +varying vec4 fragColor; +varying vec2 tangent; +varying vec4 startCutoff, endCutoff; +varying vec2 startCoord, endCoord; +varying float enableStartMiter, enableEndMiter; + +float distToLine(vec2 p, vec2 a, vec2 b) { + vec2 diff = b - a; + vec2 perp = normalize(vec2(-diff.y, diff.x)); + return dot(p - a, perp); +} + +void main() { + float alpha = 1., distToStart, distToEnd; + float cutoff = thickness * .5; + + //bevel miter + if (miterMode == 1.) { + if (enableStartMiter == 1.) { + distToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw); + if (distToStart < -1.) { + discard; + return; + } + alpha *= min(max(distToStart + 1., 0.), 1.); + } + + if (enableEndMiter == 1.) { + distToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw); + if (distToEnd < -1.) { + discard; + return; + } + alpha *= min(max(distToEnd + 1., 0.), 1.); + } + } + + // round miter + else if (miterMode == 2.) { + if (enableStartMiter == 1.) { + distToStart = distToLine(gl_FragCoord.xy, startCutoff.xy, startCutoff.zw); + if (distToStart < 0.) { + float radius = length(gl_FragCoord.xy - startCoord); + + if(radius > cutoff + .5) { + discard; + return; + } + + alpha -= smoothstep(cutoff - .5, cutoff + .5, radius); + } + } + + if (enableEndMiter == 1.) { + distToEnd = distToLine(gl_FragCoord.xy, endCutoff.xy, endCutoff.zw); + if (distToEnd < 0.) { + float radius = length(gl_FragCoord.xy - endCoord); + + if(radius > cutoff + .5) { + discard; + return; + } + + alpha -= smoothstep(cutoff - .5, cutoff + .5, radius); + 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Me=tt.selectAll("rect.bandrect").data(function(fe){return fe.bands},i);Me.each(function(){e.raiseToTop(this)}),Me.attr("fill",function(fe){return fe.color});var _e=Me.enter().append("rect").attr("class","bandrect").attr("stroke-opacity",0).attr("fill",function(fe){return fe.color}).attr("fill-opacity",0);Me.attr("fill",function(fe){return fe.color}).attr("width",function(fe){return fe.width}).attr("height",function(fe){return fe.height}).attr("y",function(fe){return fe.y}).attr("cursor",function(fe){return fe.parcatsViewModel.arrangement==="fixed"?"default":fe.parcatsViewModel.arrangement==="perpendicular"?"ns-resize":"move"}),b(_e),Me.exit().remove(),ut.append("text").attr("class","catlabel").attr("pointer-events","none"),tt.select("text.catlabel").attr("text-anchor",function(fe){return s(fe)?"start":"end"}).attr("alignment-baseline","middle").style("fill","rgb(0, 0, 0)").attr("x",function(fe){return s(fe)?fe.width+5:-5}).attr("y",function(fe){return fe.height/2}).text(function(fe){return fe.model.categoryLabel}).each(function(fe){r.font(d.select(this),fe.parcatsViewModel.categorylabelfont),a.convertToTspans(d.select(this),oe)}),ut.append("text").attr("class","dimlabel"),tt.select("text.dimlabel").attr("text-anchor","middle").attr("alignment-baseline","baseline").attr("cursor",function(fe){return fe.parcatsViewModel.arrangement==="fixed"?"default":"ew-resize"}).attr("x",function(fe){return fe.width/2}).attr("y",-5).text(function(fe,Oe){return 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"),qt=o.mostReadable(ce.color,["black","white"]);return{trace:Fe,x:j*(at-oe.left),y:ee*(Ze-oe.top),text:Lt,color:ce.color,borderColor:"black",fontFamily:'Monaco, "Courier New", monospace',fontColor:qt,fontSize:10,idealAlign:nt,hovertemplate:Fe.hovertemplate,hovertemplateLabels:Qe,eventData:[{data:Fe._input,fullData:Fe,category:tt,count:ut,probability:Oe,categorycount:_e,colorcount:fe,bandcolorcount:Me}]}}function B(X){if(!X.parcatsViewModel.dragDimension&&X.parcatsViewModel.hoverinfoItems.indexOf("skip")===-1){var oe=d.mouse(this)[1];if(oe<-1)return;var ie=X.parcatsViewModel.graphDiv,j=ie._fullLayout,ee=j._paperdiv.node().getBoundingClientRect(),re=X.parcatsViewModel.hoveron,ce=this;if(re==="color"?(g(ce),P(ce,"plotly_hover",d.event)):(u(ce),f(ce,"plotly_hover",d.event)),X.parcatsViewModel.hoverinfoItems.indexOf("none")===-1){var be;re==="category"?be=L(ie,ee,ce):re==="color"?be=F(ie,ee,ce):re==="dimension"&&(be=z(ie,ee,ce)),be&&E.loneHover(be,{container:j._hoverlayer.node(),outerContainer:j._paper.node(),gd:ie})}}}function O(X){var oe=X.parcatsViewModel;if(!oe.dragDimension&&(_(oe.pathSelection),M(oe.dimensionSelection.selectAll("g.category")),b(oe.dimensionSelection.selectAll("g.category").selectAll("rect.bandrect")),E.loneUnhover(oe.graphDiv._fullLayout._hoverlayer.node()),oe.pathSelection.sort(h),oe.hoverinfoItems.indexOf("skip")===-1)){var ie=X.parcatsViewModel.hoveron,j=this;ie==="color"?P(j,"plotly_unhover",d.event):f(j,"plotly_unhover",d.event)}}function I(X){X.parcatsViewModel.arrangement!=="fixed"&&(X.dragDimensionDisplayInd=X.model.displayInd,X.initialDragDimensionDisplayInds=X.parcatsViewModel.model.dimensions.map(function(oe){return oe.displayInd}),X.dragHasMoved=!1,X.dragCategoryDisplayInd=null,d.select(this).selectAll("g.category").select("rect.catrect").each(function(oe){var ie=d.mouse(this)[0],j=d.mouse(this)[1];-2<=ie&&ie<=oe.width+2&&-2<=j&&j<=oe.height+2&&(X.dragCategoryDisplayInd=oe.model.displayInd,X.initialDragCategoryDisplayInds=X.model.categories.map(function(ee){return ee.displayInd}),oe.model.dragY=oe.y,e.raiseToTop(this.parentNode),d.select(this.parentNode).selectAll("rect.bandrect").each(function(ee){ee.yFe.y+Fe.height/2&&(re.model.displayInd=Fe.model.displayInd,Fe.model.displayInd=be),X.dragCategoryDisplayInd=re.model.displayInd}if(X.dragCategoryDisplayInd===null||X.parcatsViewModel.arrangement==="freeform"){ee.model.dragX=d.event.x;var Ze=X.parcatsViewModel.dimensions[ie],at=X.parcatsViewModel.dimensions[j];Ze!==void 0&&ee.model.dragXat.x&&(ee.model.displayInd=at.model.displayInd,at.model.displayInd=X.dragDimensionDisplayInd),X.dragDimensionDisplayInd=ee.model.displayInd}$(X.parcatsViewModel),V(X.parcatsViewModel),ue(X.parcatsViewModel),Q(X.parcatsViewModel)}}function U(X){if(X.parcatsViewModel.arrangement!=="fixed"&&X.dragDimensionDisplayInd!==null){d.select(this).selectAll("text").attr("font-weight","normal");var oe={},ie=W(X.parcatsViewModel),j=X.parcatsViewModel.model.dimensions.map(function(at){return at.displayInd}),ee=X.initialDragDimensionDisplayInds.some(function(at,nt){return at!==j[nt]});ee&&j.forEach(function(at,nt){var tt=X.parcatsViewModel.model.dimensions[nt].containerInd;oe["dimensions["+tt+"].displayindex"]=at});var re=!1;if(X.dragCategoryDisplayInd!==null){var ce=X.model.categories.map(function(at){return at.displayInd});if(re=X.initialDragCategoryDisplayInds.some(function(at,nt){return at!==ce[nt]}),re){var be=X.model.categories.slice().sort(function(at,nt){return at.displayInd-nt.displayInd}),Se=be.map(function(at){return at.categoryValue}),De=be.map(function(at){return at.categoryLabel});oe["dimensions["+X.model.containerInd+"].categoryarray"]=[Se],oe["dimensions["+X.model.containerInd+"].ticktext"]=[De],oe["dimensions["+X.model.containerInd+"].categoryorder"]="array"}}if(X.parcatsViewModel.hoverinfoItems.indexOf("skip")===-1&&!X.dragHasMoved&&X.potentialClickBand&&(X.parcatsViewModel.hoveron==="color"?P(X.potentialClickBand,"plotly_click",d.event.sourceEvent):f(X.potentialClickBand,"plotly_click",d.event.sourceEvent)),X.model.dragX=null,X.dragCategoryDisplayInd!==null){var Fe=X.parcatsViewModel.dimensions[X.dragDimensionDisplayInd].categories[X.dragCategoryDisplayInd];Fe.model.dragY=null,X.dragCategoryDisplayInd=null}X.dragDimensionDisplayInd=null,X.parcatsViewModel.dragDimension=null,X.dragHasMoved=null,X.potentialClickBand=null,$(X.parcatsViewModel),V(X.parcatsViewModel);var 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k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)},C.prototype.emplaceBack=function(ne){var xe=this.length;return this.resize(xe+1),this.emplace(xe,ne)},C.prototype.emplace=function(ne,xe){var Re=ne*1;return this.uint32[Re+0]=xe,ne},C}(zi);ja.prototype.bytesPerElement=4,de("StructArrayLayout1ul4",ja);var Yi=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},C.prototype.emplaceBack=function(ne,xe,Re,Ve,ht,Dt,Gt,er,Pr){var Zr=this.length;return this.resize(Zr+1),this.emplace(Zr,ne,xe,Re,Ve,ht,Dt,Gt,er,Pr)},C.prototype.emplace=function(ne,xe,Re,Ve,ht,Dt,Gt,er,Pr,Zr){var jr=ne*10,ca=ne*5;return this.int16[jr+0]=xe,this.int16[jr+1]=Re,this.int16[jr+2]=Ve,this.int16[jr+3]=ht,this.int16[jr+4]=Dt,this.int16[jr+5]=Gt,this.uint32[ca+3]=er,this.uint16[jr+8]=Pr,this.uint16[jr+9]=Zr,ne},C}(zi);Yi.prototype.bytesPerElement=20,de("StructArrayLayout6i1ul2ui20",Yi);var Ri=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},C.prototype.emplaceBack=function(ne,xe,Re,Ve,ht,Dt){var Gt=this.length;return this.resize(Gt+1),this.emplace(Gt,ne,xe,Re,Ve,ht,Dt)},C.prototype.emplace=function(ne,xe,Re,Ve,ht,Dt,Gt){var er=ne*6;return this.int16[er+0]=xe,this.int16[er+1]=Re,this.int16[er+2]=Ve,this.int16[er+3]=ht,this.int16[er+4]=Dt,this.int16[er+5]=Gt,ne},C}(zi);Ri.prototype.bytesPerElement=12,de("StructArrayLayout2i2i2i12",Ri);var Ai=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},C.prototype.emplaceBack=function(ne,xe,Re,Ve,ht){var Dt=this.length;return this.resize(Dt+1),this.emplace(Dt,ne,xe,Re,Ve,ht)},C.prototype.emplace=function(ne,xe,Re,Ve,ht,Dt){var Gt=ne*4,er=ne*8;return this.float32[Gt+0]=xe,this.float32[Gt+1]=Re,this.float32[Gt+2]=Ve,this.int16[er+6]=ht,this.int16[er+7]=Dt,ne},C}(zi);Ai.prototype.bytesPerElement=16,de("StructArrayLayout2f1f2i16",Ai);var wi=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},C.prototype.emplaceBack=function(ne,xe,Re,Ve){var ht=this.length;return this.resize(ht+1),this.emplace(ht,ne,xe,Re,Ve)},C.prototype.emplace=function(ne,xe,Re,Ve,ht){var Dt=ne*12,Gt=ne*3;return this.uint8[Dt+0]=xe,this.uint8[Dt+1]=Re,this.float32[Gt+1]=Ve,this.float32[Gt+2]=ht,ne},C}(zi);wi.prototype.bytesPerElement=12,de("StructArrayLayout2ub2f12",wi);var Wi=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},C.prototype.emplaceBack=function(ne,xe,Re){var Ve=this.length;return this.resize(Ve+1),this.emplace(Ve,ne,xe,Re)},C.prototype.emplace=function(ne,xe,Re,Ve){var ht=ne*3;return this.uint16[ht+0]=xe,this.uint16[ht+1]=Re,this.uint16[ht+2]=Ve,ne},C}(zi);Wi.prototype.bytesPerElement=6,de("StructArrayLayout3ui6",Wi);var mn=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},C.prototype.emplaceBack=function(ne,xe,Re,Ve,ht,Dt,Gt,er,Pr,Zr,jr,ca,Ba,Ei,ni,$i,Oi){var Ji=this.length;return this.resize(Ji+1),this.emplace(Ji,ne,xe,Re,Ve,ht,Dt,Gt,er,Pr,Zr,jr,ca,Ba,Ei,ni,$i,Oi)},C.prototype.emplace=function(ne,xe,Re,Ve,ht,Dt,Gt,er,Pr,Zr,jr,ca,Ba,Ei,ni,$i,Oi,Ji){var ln=ne*24,Tn=ne*12,qn=ne*48;return this.int16[ln+0]=xe,this.int16[ln+1]=Re,this.uint16[ln+2]=Ve,this.uint16[ln+3]=ht,this.uint32[Tn+2]=Dt,this.uint32[Tn+3]=Gt,this.uint32[Tn+4]=er,this.uint16[ln+10]=Pr,this.uint16[ln+11]=Zr,this.uint16[ln+12]=jr,this.float32[Tn+7]=ca,this.float32[Tn+8]=Ba,this.uint8[qn+36]=Ei,this.uint8[qn+37]=ni,this.uint8[qn+38]=$i,this.uint32[Tn+10]=Oi,this.int16[ln+22]=Ji,ne},C}(zi);mn.prototype.bytesPerElement=48,de("StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48",mn);var Rn=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},C.prototype.emplaceBack=function(ne,xe,Re,Ve,ht,Dt,Gt,er,Pr,Zr,jr,ca,Ba,Ei,ni,$i,Oi,Ji,ln,Tn,qn,Bn,Eo,io,mo,Es,ko,Do){var Ys=this.length;return this.resize(Ys+1),this.emplace(Ys,ne,xe,Re,Ve,ht,Dt,Gt,er,Pr,Zr,jr,ca,Ba,Ei,ni,$i,Oi,Ji,ln,Tn,qn,Bn,Eo,io,mo,Es,ko,Do)},C.prototype.emplace=function(ne,xe,Re,Ve,ht,Dt,Gt,er,Pr,Zr,jr,ca,Ba,Ei,ni,$i,Oi,Ji,ln,Tn,qn,Bn,Eo,io,mo,Es,ko,Do,Ys){var ws=ne*34,Zl=ne*17;return this.int16[ws+0]=xe,this.int16[ws+1]=Re,this.int16[ws+2]=Ve,this.int16[ws+3]=ht,this.int16[ws+4]=Dt,this.int16[ws+5]=Gt,this.int16[ws+6]=er,this.int16[ws+7]=Pr,this.uint16[ws+8]=Zr,this.uint16[ws+9]=jr,this.uint16[ws+10]=ca,this.uint16[ws+11]=Ba,this.uint16[ws+12]=Ei,this.uint16[ws+13]=ni,this.uint16[ws+14]=$i,this.uint16[ws+15]=Oi,this.uint16[ws+16]=Ji,this.uint16[ws+17]=ln,this.uint16[ws+18]=Tn,this.uint16[ws+19]=qn,this.uint16[ws+20]=Bn,this.uint16[ws+21]=Eo,this.uint16[ws+22]=io,this.uint32[Zl+12]=mo,this.float32[Zl+13]=Es,this.float32[Zl+14]=ko,this.float32[Zl+15]=Do,this.float32[Zl+16]=Ys,ne},C}(zi);Rn.prototype.bytesPerElement=68,de("StructArrayLayout8i15ui1ul4f68",Rn);var Ii=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},C.prototype.emplaceBack=function(ne){var xe=this.length;return this.resize(xe+1),this.emplace(xe,ne)},C.prototype.emplace=function(ne,xe){var Re=ne*1;return this.float32[Re+0]=xe,ne},C}(zi);Ii.prototype.bytesPerElement=4,de("StructArrayLayout1f4",Ii);var an=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)},C.prototype.emplaceBack=function(ne,xe,Re){var Ve=this.length;return this.resize(Ve+1),this.emplace(Ve,ne,xe,Re)},C.prototype.emplace=function(ne,xe,Re,Ve){var ht=ne*3;return this.int16[ht+0]=xe,this.int16[ht+1]=Re,this.int16[ht+2]=Ve,ne},C}(zi);an.prototype.bytesPerElement=6,de("StructArrayLayout3i6",an);var kn=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},C.prototype.emplaceBack=function(ne,xe,Re){var Ve=this.length;return this.resize(Ve+1),this.emplace(Ve,ne,xe,Re)},C.prototype.emplace=function(ne,xe,Re,Ve){var ht=ne*2,Dt=ne*4;return this.uint32[ht+0]=xe,this.uint16[Dt+2]=Re,this.uint16[Dt+3]=Ve,ne},C}(zi);kn.prototype.bytesPerElement=8,de("StructArrayLayout1ul2ui8",kn);var Dn=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},C.prototype.emplaceBack=function(ne,xe){var Re=this.length;return this.resize(Re+1),this.emplace(Re,ne,xe)},C.prototype.emplace=function(ne,xe,Re){var Ve=ne*2;return this.uint16[Ve+0]=xe,this.uint16[Ve+1]=Re,ne},C}(zi);Dn.prototype.bytesPerElement=4,de("StructArrayLayout2ui4",Dn);var Wn=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)},C.prototype.emplaceBack=function(ne){var xe=this.length;return this.resize(xe+1),this.emplace(xe,ne)},C.prototype.emplace=function(ne,xe){var Re=ne*1;return this.uint16[Re+0]=xe,ne},C}(zi);Wn.prototype.bytesPerElement=2,de("StructArrayLayout1ui2",Wn);var Ps=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype._refreshViews=function(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)},C.prototype.emplaceBack=function(ne,xe,Re,Ve){var ht=this.length;return this.resize(ht+1),this.emplace(ht,ne,xe,Re,Ve)},C.prototype.emplace=function(ne,xe,Re,Ve,ht){var Dt=ne*4;return this.float32[Dt+0]=xe,this.float32[Dt+1]=Re,this.float32[Dt+2]=Ve,this.float32[Dt+3]=ht,ne},C}(zi);Ps.prototype.bytesPerElement=16,de("StructArrayLayout4f16",Ps);var xl=function(k){function C(){k.apply(this,arguments)}k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C;var G={anchorPointX:{configurable:!0},anchorPointY:{configurable:!0},x1:{configurable:!0},y1:{configurable:!0},x2:{configurable:!0},y2:{configurable:!0},featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0},anchorPoint:{configurable:!0}};return G.anchorPointX.get=function(){return this._structArray.int16[this._pos2+0]},G.anchorPointY.get=function(){return this._structArray.int16[this._pos2+1]},G.x1.get=function(){return this._structArray.int16[this._pos2+2]},G.y1.get=function(){return this._structArray.int16[this._pos2+3]},G.x2.get=function(){return this._structArray.int16[this._pos2+4]},G.y2.get=function(){return this._structArray.int16[this._pos2+5]},G.featureIndex.get=function(){return this._structArray.uint32[this._pos4+3]},G.sourceLayerIndex.get=function(){return this._structArray.uint16[this._pos2+8]},G.bucketIndex.get=function(){return this._structArray.uint16[this._pos2+9]},G.anchorPoint.get=function(){return new n(this.anchorPointX,this.anchorPointY)},Object.defineProperties(C.prototype,G),C}(xi);xl.prototype.size=20;var co=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype.get=function(ne){return new xl(this,ne)},C}(Yi);de("CollisionBoxArray",co);var Xl=function(k){function C(){k.apply(this,arguments)}k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C;var G={anchorX:{configurable:!0},anchorY:{configurable:!0},glyphStartIndex:{configurable:!0},numGlyphs:{configurable:!0},vertexStartIndex:{configurable:!0},lineStartIndex:{configurable:!0},lineLength:{configurable:!0},segment:{configurable:!0},lowerSize:{configurable:!0},upperSize:{configurable:!0},lineOffsetX:{configurable:!0},lineOffsetY:{configurable:!0},writingMode:{configurable:!0},placedOrientation:{configurable:!0},hidden:{configurable:!0},crossTileID:{configurable:!0},associatedIconIndex:{configurable:!0}};return G.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},G.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},G.glyphStartIndex.get=function(){return this._structArray.uint16[this._pos2+2]},G.numGlyphs.get=function(){return this._structArray.uint16[this._pos2+3]},G.vertexStartIndex.get=function(){return this._structArray.uint32[this._pos4+2]},G.lineStartIndex.get=function(){return this._structArray.uint32[this._pos4+3]},G.lineLength.get=function(){return this._structArray.uint32[this._pos4+4]},G.segment.get=function(){return this._structArray.uint16[this._pos2+10]},G.lowerSize.get=function(){return this._structArray.uint16[this._pos2+11]},G.upperSize.get=function(){return this._structArray.uint16[this._pos2+12]},G.lineOffsetX.get=function(){return this._structArray.float32[this._pos4+7]},G.lineOffsetY.get=function(){return this._structArray.float32[this._pos4+8]},G.writingMode.get=function(){return this._structArray.uint8[this._pos1+36]},G.placedOrientation.get=function(){return this._structArray.uint8[this._pos1+37]},G.placedOrientation.set=function(ne){this._structArray.uint8[this._pos1+37]=ne},G.hidden.get=function(){return this._structArray.uint8[this._pos1+38]},G.hidden.set=function(ne){this._structArray.uint8[this._pos1+38]=ne},G.crossTileID.get=function(){return this._structArray.uint32[this._pos4+10]},G.crossTileID.set=function(ne){this._structArray.uint32[this._pos4+10]=ne},G.associatedIconIndex.get=function(){return this._structArray.int16[this._pos2+22]},Object.defineProperties(C.prototype,G),C}(xi);Xl.prototype.size=48;var hs=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype.get=function(ne){return new Xl(this,ne)},C}(mn);de("PlacedSymbolArray",hs);var Sl=function(k){function C(){k.apply(this,arguments)}k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C;var G={anchorX:{configurable:!0},anchorY:{configurable:!0},rightJustifiedTextSymbolIndex:{configurable:!0},centerJustifiedTextSymbolIndex:{configurable:!0},leftJustifiedTextSymbolIndex:{configurable:!0},verticalPlacedTextSymbolIndex:{configurable:!0},placedIconSymbolIndex:{configurable:!0},verticalPlacedIconSymbolIndex:{configurable:!0},key:{configurable:!0},textBoxStartIndex:{configurable:!0},textBoxEndIndex:{configurable:!0},verticalTextBoxStartIndex:{configurable:!0},verticalTextBoxEndIndex:{configurable:!0},iconBoxStartIndex:{configurable:!0},iconBoxEndIndex:{configurable:!0},verticalIconBoxStartIndex:{configurable:!0},verticalIconBoxEndIndex:{configurable:!0},featureIndex:{configurable:!0},numHorizontalGlyphVertices:{configurable:!0},numVerticalGlyphVertices:{configurable:!0},numIconVertices:{configurable:!0},numVerticalIconVertices:{configurable:!0},useRuntimeCollisionCircles:{configurable:!0},crossTileID:{configurable:!0},textBoxScale:{configurable:!0},textOffset0:{configurable:!0},textOffset1:{configurable:!0},collisionCircleDiameter:{configurable:!0}};return G.anchorX.get=function(){return this._structArray.int16[this._pos2+0]},G.anchorY.get=function(){return this._structArray.int16[this._pos2+1]},G.rightJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+2]},G.centerJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+3]},G.leftJustifiedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+4]},G.verticalPlacedTextSymbolIndex.get=function(){return this._structArray.int16[this._pos2+5]},G.placedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+6]},G.verticalPlacedIconSymbolIndex.get=function(){return this._structArray.int16[this._pos2+7]},G.key.get=function(){return this._structArray.uint16[this._pos2+8]},G.textBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+9]},G.textBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+10]},G.verticalTextBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+11]},G.verticalTextBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+12]},G.iconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+13]},G.iconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+14]},G.verticalIconBoxStartIndex.get=function(){return this._structArray.uint16[this._pos2+15]},G.verticalIconBoxEndIndex.get=function(){return this._structArray.uint16[this._pos2+16]},G.featureIndex.get=function(){return this._structArray.uint16[this._pos2+17]},G.numHorizontalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+18]},G.numVerticalGlyphVertices.get=function(){return this._structArray.uint16[this._pos2+19]},G.numIconVertices.get=function(){return this._structArray.uint16[this._pos2+20]},G.numVerticalIconVertices.get=function(){return this._structArray.uint16[this._pos2+21]},G.useRuntimeCollisionCircles.get=function(){return this._structArray.uint16[this._pos2+22]},G.crossTileID.get=function(){return this._structArray.uint32[this._pos4+12]},G.crossTileID.set=function(ne){this._structArray.uint32[this._pos4+12]=ne},G.textBoxScale.get=function(){return this._structArray.float32[this._pos4+13]},G.textOffset0.get=function(){return this._structArray.float32[this._pos4+14]},G.textOffset1.get=function(){return this._structArray.float32[this._pos4+15]},G.collisionCircleDiameter.get=function(){return this._structArray.float32[this._pos4+16]},Object.defineProperties(C.prototype,G),C}(xi);Sl.prototype.size=68;var Cl=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype.get=function(ne){return new Sl(this,ne)},C}(Rn);de("SymbolInstanceArray",Cl);var ru=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype.getoffsetX=function(ne){return this.float32[ne*1+0]},C}(Ii);de("GlyphOffsetArray",ru);var Os=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype.getx=function(ne){return this.int16[ne*3+0]},C.prototype.gety=function(ne){return this.int16[ne*3+1]},C.prototype.gettileUnitDistanceFromAnchor=function(ne){return this.int16[ne*3+2]},C}(an);de("SymbolLineVertexArray",Os);var pl=function(k){function C(){k.apply(this,arguments)}k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C;var G={featureIndex:{configurable:!0},sourceLayerIndex:{configurable:!0},bucketIndex:{configurable:!0}};return G.featureIndex.get=function(){return this._structArray.uint32[this._pos4+0]},G.sourceLayerIndex.get=function(){return 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ne=this.extent*Math.pow(2,G),xe=this.extent*k,Re=this.extent*C,Ve=this.loadGeometry(),ht=zv.types[this.type],Dt,Gt;function er(jr){for(var ca=0;ca>3;C=ne===1?k.readString():ne===2?k.readFloat():ne===3?k.readDouble():ne===4?k.readVarint64():ne===5?k.readVarint():ne===6?k.readSVarint():ne===7?k.readBoolean():null}return C}G1.prototype.feature=function(k){if(k<0||k>=this._features.length)throw new Error("feature index out of bounds");this._pbf.pos=this._features[k];var C=this._pbf.readVarint()+this._pbf.pos;return new V1(this._pbf,C,this.extent,this._keys,this._values)};var Kx=tA;function tA(k,C){this.layers=k.readFields(rA,{},C)}function rA(k,C,G){if(k===3){var ne=new Wd(G,G.readVarint()+G.pos);ne.length&&(C[ne.name]=ne)}}var Jx=Kx,hm=V1,$x=Wd,Xd={VectorTile:Jx,VectorTileFeature:hm,VectorTileLayer:$x},Qx=Xd.VectorTileFeature.types,Pg=500,pm=Math.pow(2,13);function hv(k,C,G,ne,xe,Re,Ve,ht){k.emplaceBack(C,G,Math.floor(ne*pm)*2+Ve,xe*pm*2,Re*pm*2,Math.round(ht))}var cd=function(C){this.zoom=C.zoom,this.overscaling=C.overscaling,this.layers=C.layers,this.layerIds=this.layers.map(function(G){return G.id}),this.index=C.index,this.hasPattern=!1,this.layoutVertexArray=new vi,this.indexArray=new Wi,this.programConfigurations=new Ha(C.layers,C.zoom),this.segments=new Io,this.stateDependentLayerIds=this.layers.filter(function(G){return G.isStateDependent()}).map(function(G){return G.id})};cd.prototype.populate=function(C,G,ne){this.features=[],this.hasPattern=Lg("fill-extrusion",this.layers,G);for(var xe=0,Re=C;xe=1){var Ji=Ei[$i-1];if(!aA(Oi,Ji)){jr.vertexLength+4>Io.MAX_VERTEX_ARRAY_LENGTH&&(jr=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));var ln=Oi.sub(Ji)._perp()._unit(),Tn=Ji.dist(Oi);ni+Tn>32768&&(ni=0),hv(this.layoutVertexArray,Oi.x,Oi.y,ln.x,ln.y,0,0,ni),hv(this.layoutVertexArray,Oi.x,Oi.y,ln.x,ln.y,0,1,ni),ni+=Tn,hv(this.layoutVertexArray,Ji.x,Ji.y,ln.x,ln.y,0,0,ni),hv(this.layoutVertexArray,Ji.x,Ji.y,ln.x,ln.y,0,1,ni);var qn=jr.vertexLength;this.indexArray.emplaceBack(qn,qn+2,qn+1),this.indexArray.emplaceBack(qn+1,qn+2,qn+3),jr.vertexLength+=4,jr.primitiveLength+=2}}}}if(jr.vertexLength+Gt>Io.MAX_VERTEX_ARRAY_LENGTH&&(jr=this.segments.prepareSegment(Gt,this.layoutVertexArray,this.indexArray)),Qx[C.type]==="Polygon"){for(var Bn=[],Eo=[],io=jr.vertexLength,mo=0,Es=Dt;moci)||k.y===C.y&&(k.y<0||k.y>ci)}function iA(k){return k.every(function(C){return C.x<0})||k.every(function(C){return C.x>ci})||k.every(function(C){return C.y<0})||k.every(function(C){return C.y>ci})}var dm=new ga({"fill-extrusion-opacity":new it(Zi["paint_fill-extrusion"]["fill-extrusion-opacity"]),"fill-extrusion-color":new 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Cp(this.paint.get("fill-extrusion-translate"))},C.prototype.is3D=function(){return!0},C.prototype.queryIntersectsFeature=function(ne,xe,Re,Ve,ht,Dt,Gt,er){var Pr=Vp(ne,this.paint.get("fill-extrusion-translate"),this.paint.get("fill-extrusion-translate-anchor"),Dt.angle,Gt),Zr=this.paint.get("fill-extrusion-height").evaluate(xe,Re),jr=this.paint.get("fill-extrusion-base").evaluate(xe,Re),ca=nA(Pr,er,Dt,0),Ba=W1(Ve,jr,Zr,er),Ei=Ba[0],ni=Ba[1];return eb(Ei,ni,ca)},C}(Ka);function Fv(k,C){return k.x*C.x+k.y*C.y}function H1(k,C){if(k.length===1){for(var G=0,ne=C[G++],xe;!xe||ne.equals(xe);)if(xe=C[G++],!xe)return 1/0;for(;G=2&&C[Gt-1].equals(C[Gt-2]);)Gt--;for(var er=0;er0;if(Bn&&$i>er){var io=jr.dist(ca);if(io>2*Pr){var mo=jr.sub(jr.sub(ca)._mult(Pr/io)._round());this.updateDistance(ca,mo),this.addCurrentVertex(mo,Ei,0,0,Zr),ca=mo}}var Es=ca&&Ba,ko=Es?ne:Dt?"butt":xe;if(Es&&ko==="round"&&(TnRe&&(ko="bevel"),ko==="bevel"&&(Tn>2&&(ko="flipbevel"),Tn100)Oi=ni.mult(-1);else{var Do=Tn*Ei.add(ni).mag()/Ei.sub(ni).mag();Oi._perp()._mult(Do*(Eo?-1:1))}this.addCurrentVertex(jr,Oi,0,0,Zr),this.addCurrentVertex(jr,Oi.mult(-1),0,0,Zr)}else if(ko==="bevel"||ko==="fakeround"){var Ys=-Math.sqrt(Tn*Tn-1),ws=Eo?Ys:0,Zl=Eo?0:Ys;if(ca&&this.addCurrentVertex(jr,Ei,ws,Zl,Zr),ko==="fakeround")for(var zu=Math.round(qn*180/Math.PI/Z1),Yl=1;Yl2*Pr){var Zf=jr.add(Ba.sub(jr)._mult(Pr/vh)._round());this.updateDistance(jr,Zf),this.addCurrentVertex(Zf,ni,0,0,Zr),jr=Zf}}}}},Hf.prototype.addCurrentVertex=function(C,G,ne,xe,Re,Ve){Ve===void 0&&(Ve=!1);var ht=G.x+G.y*ne,Dt=G.y-G.x*ne,Gt=-G.x+G.y*xe,er=-G.y-G.x*xe;this.addHalfVertex(C,ht,Dt,Ve,!1,ne,Re),this.addHalfVertex(C,Gt,er,Ve,!0,-xe,Re),this.distance>F0/2&&this.totalDistance===0&&(this.distance=0,this.addCurrentVertex(C,G,ne,xe,Re,Ve))},Hf.prototype.addHalfVertex=function(C,G,ne,xe,Re,Ve,ht){var Dt=C.x,Gt=C.y,er=this.lineClips?this.scaledDistance*(F0-1):this.scaledDistance,Pr=er*Rg;if(this.layoutVertexArray.emplaceBack((Dt<<1)+(xe?1:0),(Gt<<1)+(Re?1:0),Math.round(Ig*G)+128,Math.round(Ig*ne)+128,(Ve===0?0:Ve<0?-1:1)+1|(Pr&63)<<2,Pr>>6),this.lineClips){var Zr=this.scaledDistance-this.lineClips.start,jr=this.lineClips.end-this.lineClips.start,ca=Zr/jr;this.layoutVertexArray2.emplaceBack(ca,this.lineClipsArray.length)}var Ba=ht.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,Ba),ht.primitiveLength++),Re?this.e2=Ba:this.e1=Ba},Hf.prototype.updateScaledDistance=function(){this.scaledDistance=this.lineClips?this.lineClips.start+(this.lineClips.end-this.lineClips.start)*this.distance/this.totalDistance:this.distance},Hf.prototype.updateDistance=function(C,G){this.distance+=C.dist(G),this.updateScaledDistance()},de("LineBucket",Hf,{omit:["layers","patternFeatures"]});var Y1=new ga({"line-cap":new it(Zi.layout_line["line-cap"]),"line-join":new Xt(Zi.layout_line["line-join"]),"line-miter-limit":new it(Zi.layout_line["line-miter-limit"]),"line-round-limit":new it(Zi.layout_line["line-round-limit"]),"line-sort-key":new Xt(Zi.layout_line["line-sort-key"])}),K1=new ga({"line-opacity":new Xt(Zi.paint_line["line-opacity"]),"line-color":new Xt(Zi.paint_line["line-color"]),"line-translate":new it(Zi.paint_line["line-translate"]),"line-translate-anchor":new it(Zi.paint_line["line-translate-anchor"]),"line-width":new Xt(Zi.paint_line["line-width"]),"line-gap-width":new Xt(Zi.paint_line["line-gap-width"]),"line-offset":new Xt(Zi.paint_line["line-offset"]),"line-blur":new Xt(Zi.paint_line["line-blur"]),"line-dasharray":new la(Zi.paint_line["line-dasharray"]),"line-pattern":new fr(Zi.paint_line["line-pattern"]),"line-gradient":new ba(Zi.paint_line["line-gradient"])}),Dg={paint:K1,layout:Y1},sA=function(k){function C(){k.apply(this,arguments)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype.possiblyEvaluate=function(ne,xe){return xe=new gn(Math.floor(xe.zoom),{now:xe.now,fadeDuration:xe.fadeDuration,zoomHistory:xe.zoomHistory,transition:xe.transition}),k.prototype.possiblyEvaluate.call(this,ne,xe)},C.prototype.evaluate=function(ne,xe,Re,Ve){return xe=y({},xe,{zoom:Math.floor(xe.zoom)}),k.prototype.evaluate.call(this,ne,xe,Re,Ve)},C}(Xt),H=new sA(Dg.paint.properties["line-width"].specification);H.useIntegerZoom=!0;var D=function(k){function C(G){k.call(this,G,Dg),this.gradientVersion=0}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype._handleSpecialPaintPropertyUpdate=function(ne){if(ne==="line-gradient"){var xe=this._transitionablePaint._values["line-gradient"].value.expression;this.stepInterpolant=xe._styleExpression.expression instanceof 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G=0;G=128&&Hp(G,ne,this),this.pos=G-1,this.writeVarint(ne),this.pos+=ne},writeMessage:function(k,C,G){this.writeTag(k,zn.Bytes),this.writeRawMessage(C,G)},writePackedVarint:function(k,C){C.length&&this.writeMessage(k,wh,C)},writePackedSVarint:function(k,C){C.length&&this.writeMessage(k,rh,C)},writePackedBoolean:function(k,C){C.length&&this.writeMessage(k,Qh,C)},writePackedFloat:function(k,C){C.length&&this.writeMessage(k,Jh,C)},writePackedDouble:function(k,C){C.length&&this.writeMessage(k,$h,C)},writePackedFixed32:function(k,C){C.length&&this.writeMessage(k,cf,C)},writePackedSFixed32:function(k,C){C.length&&this.writeMessage(k,ah,C)},writePackedFixed64:function(k,C){C.length&&this.writeMessage(k,Fh,C)},writePackedSFixed64:function(k,C){C.length&&this.writeMessage(k,Th,C)},writeBytesField:function(k,C){this.writeTag(k,zn.Bytes),this.writeBytes(C)},writeFixed32Field:function(k,C){this.writeTag(k,zn.Fixed32),this.writeFixed32(C)},writeSFixed32Field:function(k,C){this.writeTag(k,zn.Fixed32),this.writeSFixed32(C)},writeFixed64Field:function(k,C){this.writeTag(k,zn.Fixed64),this.writeFixed64(C)},writeSFixed64Field:function(k,C){this.writeTag(k,zn.Fixed64),this.writeSFixed64(C)},writeVarintField:function(k,C){this.writeTag(k,zn.Varint),this.writeVarint(C)},writeSVarintField:function(k,C){this.writeTag(k,zn.Varint),this.writeSVarint(C)},writeStringField:function(k,C){this.writeTag(k,zn.Bytes),this.writeString(C)},writeFloatField:function(k,C){this.writeTag(k,zn.Fixed32),this.writeFloat(C)},writeDoubleField:function(k,C){this.writeTag(k,zn.Fixed64),this.writeDouble(C)},writeBooleanField:function(k,C){this.writeVarintField(k,!!C)}};function cs(k,C,G){var ne=G.buf,xe,Re;if(Re=ne[G.pos++],xe=(Re&112)>>4,Re<128||(Re=ne[G.pos++],xe|=(Re&127)<<3,Re<128)||(Re=ne[G.pos++],xe|=(Re&127)<<10,Re<128)||(Re=ne[G.pos++],xe|=(Re&127)<<17,Re<128)||(Re=ne[G.pos++],xe|=(Re&127)<<24,Re<128)||(Re=ne[G.pos++],xe|=(Re&1)<<31,Re<128))return ks(k,xe,C);throw new Error("Expected varint not more than 10 bytes")}function No(k){return k.type===zn.Bytes?k.readVarint()+k.pos:k.pos+1}function ks(k,C,G){return G?C*4294967296+(k>>>0):(C>>>0)*4294967296+(k>>>0)}function Ku(k,C){var G,ne;if(k>=0?(G=k%4294967296|0,ne=k/4294967296|0):(G=~(-k%4294967296),ne=~(-k/4294967296),G^4294967295?G=G+1|0:(G=0,ne=ne+1|0)),k>=18446744073709552e3||k<-18446744073709552e3)throw new Error("Given varint doesn't fit into 10 bytes");C.realloc(10),Uu(G,ne,C),th(ne,C)}function Uu(k,C,G){G.buf[G.pos++]=k&127|128,k>>>=7,G.buf[G.pos++]=k&127|128,k>>>=7,G.buf[G.pos++]=k&127|128,k>>>=7,G.buf[G.pos++]=k&127|128,k>>>=7,G.buf[G.pos]=k&127}function th(k,C){var G=(k&7)<<4;C.buf[C.pos++]|=G|((k>>>=3)?128:0),k&&(C.buf[C.pos++]=k&127|((k>>>=7)?128:0),k&&(C.buf[C.pos++]=k&127|((k>>>=7)?128:0),k&&(C.buf[C.pos++]=k&127|((k>>>=7)?128:0),k&&(C.buf[C.pos++]=k&127|((k>>>=7)?128:0),k&&(C.buf[C.pos++]=k&127)))))}function Hp(k,C,G){var ne=C<=16383?1:C<=2097151?2:C<=268435455?3:Math.floor(Math.log(C)/(Math.LN2*7));G.realloc(ne);for(var xe=G.pos-1;xe>=k;xe--)G.buf[xe+ne]=G.buf[xe]}function wh(k,C){for(var G=0;G>>8,k[G+2]=C>>>16,k[G+3]=C>>>24}function Rp(k,C){return(k[C]|k[C+1]<<8|k[C+2]<<16)+(k[C+3]<<24)}function dp(k,C,G){for(var ne="",xe=C;xe239?4:Re>223?3:Re>191?2:1;if(xe+ht>G)break;var 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ff=ub(Kl.stretch-$i,Oi,Gt,k.left),yf=cb(Kl.fixed-Tn,qn,Kl.stretch,ca),vh=ub(Nl.stretch-Ji,ln,er,k.top),Zf=cb(Nl.fixed-Bn,Eo,Nl.stretch,Ba),tp=ub($u.stretch-$i,Oi,Gt,k.left),rp=cb($u.fixed-Tn,qn,$u.stretch,ca),mh=ub(pc.stretch-Ji,ln,er,k.top),gp=cb(pc.fixed-Bn,Eo,pc.stretch,Ba),yp=new n(ff,vh),ih=new n(tp,vh),_p=new n(tp,mh),nd=new n(ff,mh),Uv=new n(yf/Ve,Zf/Ve),_m=new n(rp/Ve,gp/Ve),xm=C*Math.PI/180;if(xm){var bm=Math.sin(xm),Wg=Math.cos(xm),wd=[Wg,-bm,bm,Wg];yp._matMult(wd),ih._matMult(wd),nd._matMult(wd),_p._matMult(wd)}var mb=Kl.stretch+Kl.fixed,xA=$u.stretch+$u.fixed,gb=Nl.stretch+Nl.fixed,bA=pc.stretch+pc.fixed,hd={x:Re.paddedRect.x+Bg+mb,y:Re.paddedRect.y+Bg+gb,w:xA-mb,h:bA-gb},Xg=qn/Ve/Gt,yb=Eo/Ve/er;return{tl:yp,tr:ih,bl:nd,br:_p,tex:hd,writingMode:void 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ne=(this.length>>1)-1;ne>=0;ne--)this._down(ne)};Ng.prototype.push=function(C){this.data.push(C),this.length++,this._up(this.length-1)},Ng.prototype.pop=function(){if(this.length!==0){var C=this.data[0],G=this.data.pop();return this.length--,this.length>0&&(this.data[0]=G,this._down(0)),C}},Ng.prototype.peek=function(){return this.data[0]},Ng.prototype._up=function(C){for(var G=this,ne=G.data,xe=G.compare,Re=ne[C];C>0;){var Ve=C-1>>1,ht=ne[Ve];if(xe(Re,ht)>=0)break;ne[C]=ht,C=Ve}ne[C]=Re},Ng.prototype._down=function(C){for(var G=this,ne=G.data,xe=G.compare,Re=this.length>>1,Ve=ne[C];C=0)break;ne[C]=Dt,C=ht}ne[C]=Ve};function bW(k,C){return kC?1:0}function wW(k,C,G){C===void 0&&(C=1),G===void 0&&(G=!1);for(var ne=1/0,xe=1/0,Re=-1/0,Ve=-1/0,ht=k[0],Dt=0;DtRe)&&(Re=Gt.x),(!Dt||Gt.y>Ve)&&(Ve=Gt.y)}var er=Re-ne,Pr=Ve-xe,Zr=Math.min(er,Pr),jr=Zr/2,ca=new Ng([],TW);if(Zr===0)return new n(ne,xe);for(var Ba=ne;Bani.d||!ni.d)&&(ni=Oi,G&&console.log("found best %d after %d 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if(C.type==="Polygon")for(var Zf=0,tp=Cg(C.geometry,0);Zfgm&&U(k.layerIds[0]+': Value for "text-size" is >= '+Q1+'. Reduce your "text-size".')):Ei.kind==="composite"&&(ni=[Bh*jr.compositeTextSizes[0].evaluate(Ve,{},ca),Bh*jr.compositeTextSizes[1].evaluate(Ve,{},ca)],(ni[0]>gm||ni[1]>gm)&&U(k.layerIds[0]+': Value for "text-size" is >= '+Q1+'. Reduce your "text-size".')),k.addSymbols(k.text,Ba,ni,ht,Re,Ve,Gt,C,Dt.lineStartIndex,Dt.lineLength,Zr,ca);for(var $i=0,Oi=er;$igm&&U(k.layerIds[0]+': Value for "icon-size" is >= '+Q1+'. Reduce your "icon-size".')):yp.kind==="composite"&&(ih=[Bh*ln.compositeIconSizes[0].evaluate(Ji,{},qn),Bh*ln.compositeIconSizes[1].evaluate(Ji,{},qn)],(ih[0]>gm||ih[1]>gm)&&U(k.layerIds[0]+': Value for "icon-size" is >= '+Q1+'. Reduce your "icon-size".')),k.addSymbols(k.icon,mh,ih,Oi,$i,Ji,!1,C,io.lineStartIndex,io.lineLength,-1,qn),Yl=k.icon.placedSymbolArray.length-1,gp&&(ws=gp.length*4,k.addSymbols(k.icon,gp,ih,Oi,$i,Ji,vp.vertical,C,io.lineStartIndex,io.lineLength,-1,qn),Kl=k.icon.placedSymbolArray.length-1)}for(var _p in ne.horizontal){var nd=ne.horizontal[_p];if(!mo){$u=me(nd.text);var Uv=ht.layout.get("text-rotate").evaluate(Ji,{},qn);mo=new fb(Dt,C,Gt,er,Pr,nd,Zr,jr,ca,Uv)}var _m=nd.positionedLines.length===1;if(Zl+=Ek(k,C,nd,Re,ht,ca,Ji,Ba,io,ne.vertical?vp.horizontal:vp.horizontalOnly,_m?Object.keys(ne.horizontal):[_p],Nl,Yl,ln,qn),_m)break}ne.vertical&&(zu+=Ek(k,C,ne.vertical,Re,ht,ca,Ji,Ba,io,vp.vertical,["vertical"],Nl,Kl,ln,qn));var xm=mo?mo.boxStartIndex:k.collisionBoxArray.length,bm=mo?mo.boxEndIndex:k.collisionBoxArray.length,Wg=ko?ko.boxStartIndex:k.collisionBoxArray.length,wd=ko?ko.boxEndIndex:k.collisionBoxArray.length,mb=Es?Es.boxStartIndex:k.collisionBoxArray.length,xA=Es?Es.boxEndIndex:k.collisionBoxArray.length,gb=Do?Do.boxStartIndex:k.collisionBoxArray.length,bA=Do?Do.boxEndIndex:k.collisionBoxArray.length,hd=-1,Xg=function(r_,Gk){return r_&&r_.circleDiameter?Math.max(r_.circleDiameter,Gk):Gk};hd=Xg(mo,hd),hd=Xg(ko,hd),hd=Xg(Es,hd),hd=Xg(Do,hd);var yb=hd>-1?1:0;yb&&(hd*=Bn/en),k.glyphOffsetArray.length>=Du.MAX_GLYPHS&&U("Too many glyphs being rendered in a tile. See https://github.com/mapbox/mapbox-gl-js/issues/2907"),Ji.sortKey!==void 0&&k.addToSortKeyRanges(k.symbolInstances.length,Ji.sortKey),k.symbolInstances.emplaceBack(C.x,C.y,Nl.right>=0?Nl.right:-1,Nl.center>=0?Nl.center:-1,Nl.left>=0?Nl.left:-1,Nl.vertical||-1,Yl,Kl,$u,xm,bm,Wg,wd,mb,xA,gb,bA,Gt,Zl,zu,Ys,ws,yb,0,Zr,pc,ff,hd)}function CW(k,C,G,ne){var xe=k.compareText;if(!(C in xe))xe[C]=[];else for(var Re=xe[C],Ve=Re.length-1;Ve>=0;Ve--)if(ne.dist(Re[Ve])0)&&(Ve.value.kind!=="constant"||Ve.value.value.length>0),er=Dt.value.kind!=="constant"||!!Dt.value.value||Object.keys(Dt.parameters).length>0,Pr=Re.get("symbol-sort-key");if(this.features=[],!(!Gt&&!er)){for(var Zr=G.iconDependencies,jr=G.glyphDependencies,ca=G.availableImages,Ba=new gn(this.zoom),Ei=0,ni=C;Ei=0;for(var zu=0,Yl=Eo.sections;zu=0;Dt--)Ve[Dt]={x:G[Dt].x,y:G[Dt].y,tileUnitDistanceFromAnchor:Re},Dt>0&&(Re+=G[Dt-1].dist(G[Dt]));for(var Gt=0;Gt0},Du.prototype.hasIconData=function(){return this.icon.segments.get().length>0},Du.prototype.hasDebugData=function(){return this.textCollisionBox&&this.iconCollisionBox},Du.prototype.hasTextCollisionBoxData=function(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0},Du.prototype.hasIconCollisionBoxData=function(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0},Du.prototype.addIndicesForPlacedSymbol=function(C,G){for(var ne=C.placedSymbolArray.get(G),xe=ne.vertexStartIndex+ne.numGlyphs*4,Re=ne.vertexStartIndex;Re1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(C),this.sortedAngle=C,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(var ne=0,xe=this.symbolInstanceIndexes;ne=0&&Gt.indexOf(ht)===Dt&&G.addIndicesForPlacedSymbol(G.text,ht)}),Ve.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,Ve.verticalPlacedTextSymbolIndex),Ve.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,Ve.placedIconSymbolIndex),Ve.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,Ve.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}},de("SymbolBucket",Du,{omit:["layers","collisionBoxArray","features","compareText"]}),Du.MAX_GLYPHS=65535,Du.addDynamicAttributes=vA;function RW(k,C){return C.replace(/{([^{}]+)}/g,function(G,ne){return ne in k?String(k[ne]):""})}var DW=new ga({"symbol-placement":new it(Zi.layout_symbol["symbol-placement"]),"symbol-spacing":new it(Zi.layout_symbol["symbol-spacing"]),"symbol-avoid-edges":new it(Zi.layout_symbol["symbol-avoid-edges"]),"symbol-sort-key":new Xt(Zi.layout_symbol["symbol-sort-key"]),"symbol-z-order":new it(Zi.layout_symbol["symbol-z-order"]),"icon-allow-overlap":new it(Zi.layout_symbol["icon-allow-overlap"]),"icon-ignore-placement":new it(Zi.layout_symbol["icon-ignore-placement"]),"icon-optional":new it(Zi.layout_symbol["icon-optional"]),"icon-rotation-alignment":new it(Zi.layout_symbol["icon-rotation-alignment"]),"icon-size":new Xt(Zi.layout_symbol["icon-size"]),"icon-text-fit":new it(Zi.layout_symbol["icon-text-fit"]),"icon-text-fit-padding":new it(Zi.layout_symbol["icon-text-fit-padding"]),"icon-image":new Xt(Zi.layout_symbol["icon-image"]),"icon-rotate":new Xt(Zi.layout_symbol["icon-rotate"]),"icon-padding":new it(Zi.layout_symbol["icon-padding"]),"icon-keep-upright":new it(Zi.layout_symbol["icon-keep-upright"]),"icon-offset":new Xt(Zi.layout_symbol["icon-offset"]),"icon-anchor":new Xt(Zi.layout_symbol["icon-anchor"]),"icon-pitch-alignment":new it(Zi.layout_symbol["icon-pitch-alignment"]),"text-pitch-alignment":new it(Zi.layout_symbol["text-pitch-alignment"]),"text-rotation-alignment":new it(Zi.layout_symbol["text-rotation-alignment"]),"text-field":new Xt(Zi.layout_symbol["text-field"]),"text-font":new Xt(Zi.layout_symbol["text-font"]),"text-size":new Xt(Zi.layout_symbol["text-size"]),"text-max-width":new Xt(Zi.layout_symbol["text-max-width"]),"text-line-height":new it(Zi.layout_symbol["text-line-height"]),"text-letter-spacing":new Xt(Zi.layout_symbol["text-letter-spacing"]),"text-justify":new Xt(Zi.layout_symbol["text-justify"]),"text-radial-offset":new Xt(Zi.layout_symbol["text-radial-offset"]),"text-variable-anchor":new it(Zi.layout_symbol["text-variable-anchor"]),"text-anchor":new Xt(Zi.layout_symbol["text-anchor"]),"text-max-angle":new it(Zi.layout_symbol["text-max-angle"]),"text-writing-mode":new it(Zi.layout_symbol["text-writing-mode"]),"text-rotate":new Xt(Zi.layout_symbol["text-rotate"]),"text-padding":new it(Zi.layout_symbol["text-padding"]),"text-keep-upright":new it(Zi.layout_symbol["text-keep-upright"]),"text-transform":new Xt(Zi.layout_symbol["text-transform"]),"text-offset":new Xt(Zi.layout_symbol["text-offset"]),"text-allow-overlap":new it(Zi.layout_symbol["text-allow-overlap"]),"text-ignore-placement":new it(Zi.layout_symbol["text-ignore-placement"]),"text-optional":new it(Zi.layout_symbol["text-optional"])}),zW=new ga({"icon-opacity":new Xt(Zi.paint_symbol["icon-opacity"]),"icon-color":new Xt(Zi.paint_symbol["icon-color"]),"icon-halo-color":new Xt(Zi.paint_symbol["icon-halo-color"]),"icon-halo-width":new Xt(Zi.paint_symbol["icon-halo-width"]),"icon-halo-blur":new Xt(Zi.paint_symbol["icon-halo-blur"]),"icon-translate":new it(Zi.paint_symbol["icon-translate"]),"icon-translate-anchor":new it(Zi.paint_symbol["icon-translate-anchor"]),"text-opacity":new Xt(Zi.paint_symbol["text-opacity"]),"text-color":new Xt(Zi.paint_symbol["text-color"],{runtimeType:fl,getOverride:function(k){return k.textColor},hasOverride:function(k){return!!k.textColor}}),"text-halo-color":new Xt(Zi.paint_symbol["text-halo-color"]),"text-halo-width":new Xt(Zi.paint_symbol["text-halo-width"]),"text-halo-blur":new Xt(Zi.paint_symbol["text-halo-blur"]),"text-translate":new it(Zi.paint_symbol["text-translate"]),"text-translate-anchor":new it(Zi.paint_symbol["text-translate-anchor"])}),mA={paint:zW,layout:DW},Vg=function(C){this.type=C.property.overrides?C.property.overrides.runtimeType:El,this.defaultValue=C};Vg.prototype.evaluate=function(C){if(C.formattedSection){var G=this.defaultValue.property.overrides;if(G&&G.hasOverride(C.formattedSection))return G.getOverride(C.formattedSection)}return C.feature&&C.featureState?this.defaultValue.evaluate(C.feature,C.featureState):this.defaultValue.property.specification.default},Vg.prototype.eachChild=function(C){if(!this.defaultValue.isConstant()){var G=this.defaultValue.value;C(G._styleExpression.expression)}},Vg.prototype.outputDefined=function(){return!1},Vg.prototype.serialize=function(){return null},de("FormatSectionOverride",Vg,{omit:["defaultValue"]});var FW=function(k){function C(G){k.call(this,G,mA)}return k&&(C.__proto__=k),C.prototype=Object.create(k&&k.prototype),C.prototype.constructor=C,C.prototype.recalculate=function(ne,xe){if(k.prototype.recalculate.call(this,ne,xe),this.layout.get("icon-rotation-alignment")==="auto"&&(this.layout.get("symbol-placement")!=="point"?this.layout._values["icon-rotation-alignment"]="map":this.layout._values["icon-rotation-alignment"]="viewport"),this.layout.get("text-rotation-alignment")==="auto"&&(this.layout.get("symbol-placement")!=="point"?this.layout._values["text-rotation-alignment"]="map":this.layout._values["text-rotation-alignment"]="viewport"),this.layout.get("text-pitch-alignment")==="auto"&&(this.layout._values["text-pitch-alignment"]=this.layout.get("text-rotation-alignment")),this.layout.get("icon-pitch-alignment")==="auto"&&(this.layout._values["icon-pitch-alignment"]=this.layout.get("icon-rotation-alignment")),this.layout.get("symbol-placement")==="point"){var Re=this.layout.get("text-writing-mode");if(Re){for(var Ve=[],ht=0,Dt=Re;ht",targetMapId:xe,sourceMapId:Ve.mapId})}}},Gg.prototype.receive=function(C){var G=C.data,ne=G.id;if(ne&&!(G.targetMapId&&this.mapId!==G.targetMapId))if(G.type===""){delete this.tasks[ne];var xe=this.cancelCallbacks[ne];delete this.cancelCallbacks[ne],xe&&xe()}else se()||G.mustQueue?(this.tasks[ne]=G,this.taskQueue.push(ne),this.invoker.trigger()):this.processTask(ne,G)},Gg.prototype.process=function(){if(this.taskQueue.length){var C=this.taskQueue.shift(),G=this.tasks[C];delete this.tasks[C],this.taskQueue.length&&this.invoker.trigger(),G&&this.processTask(C,G)}},Gg.prototype.processTask=function(C,G){var ne=this;if(G.type===""){var xe=this.callbacks[C];delete this.callbacks[C],xe&&(G.error?xe(St(G.error)):xe(null,St(G.data)))}else{var Re=!1,Ve=$(this.globalScope)?void 0:[],ht=G.hasCallback?function(Zr,jr){Re=!0,delete ne.cancelCallbacks[C],ne.target.postMessage({id:C,type:"",sourceMapId:ne.mapId,error:Zr?_t(Zr):null,data:_t(jr,Ve)},Ve)}:function(Zr){Re=!0},Dt=null,Gt=St(G.data);if(this.parent[G.type])Dt=this.parent[G.type](G.sourceMapId,Gt,ht);else if(this.parent.getWorkerSource){var er=G.type.split("."),Pr=this.parent.getWorkerSource(G.sourceMapId,er[0],Gt.source);Dt=Pr[er[1]](Gt,ht)}else ht(new Error("Could not find function "+G.type));!Re&&Dt&&Dt.cancel&&(this.cancelCallbacks[C]=Dt.cancel)}},Gg.prototype.remove=function(){this.invoker.remove(),this.target.removeEventListener("message",this.receive,!1)};function XW(k,C,G){C=Math.pow(2,G)-C-1;var ne=Rk(k*256,C*256,G),xe=Rk((k+1)*256,(C+1)*256,G);return ne[0]+","+ne[1]+","+xe[0]+","+xe[1]}function Rk(k,C,G){var ne=2*Math.PI*6378137/256/Math.pow(2,G),xe=k*ne-2*Math.PI*6378137/2,Re=C*ne-2*Math.PI*6378137/2;return[xe,Re]}var Wf=function(C,G){C&&(G?this.setSouthWest(C).setNorthEast(G):C.length===4?this.setSouthWest([C[0],C[1]]).setNorthEast([C[2],C[3]]):this.setSouthWest(C[0]).setNorthEast(C[1]))};Wf.prototype.setNorthEast=function(C){return this._ne=C instanceof Fc?new Fc(C.lng,C.lat):Fc.convert(C),this},Wf.prototype.setSouthWest=function(C){return this._sw=C instanceof Fc?new Fc(C.lng,C.lat):Fc.convert(C),this},Wf.prototype.extend=function(C){var G=this._sw,ne=this._ne,xe,Re;if(C instanceof Fc)xe=C,Re=C;else if(C instanceof Wf){if(xe=C._sw,Re=C._ne,!xe||!Re)return this}else{if(Array.isArray(C))if(C.length===4||C.every(Array.isArray)){var Ve=C;return this.extend(Wf.convert(Ve))}else{var ht=C;return this.extend(Fc.convert(ht))}return this}return!G&&!ne?(this._sw=new Fc(xe.lng,xe.lat),this._ne=new Fc(Re.lng,Re.lat)):(G.lng=Math.min(xe.lng,G.lng),G.lat=Math.min(xe.lat,G.lat),ne.lng=Math.max(Re.lng,ne.lng),ne.lat=Math.max(Re.lat,ne.lat)),this},Wf.prototype.getCenter=function(){return new Fc((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)},Wf.prototype.getSouthWest=function(){return this._sw},Wf.prototype.getNorthEast=function(){return this._ne},Wf.prototype.getNorthWest=function(){return new Fc(this.getWest(),this.getNorth())},Wf.prototype.getSouthEast=function(){return new Fc(this.getEast(),this.getSouth())},Wf.prototype.getWest=function(){return this._sw.lng},Wf.prototype.getSouth=function(){return this._sw.lat},Wf.prototype.getEast=function(){return this._ne.lng},Wf.prototype.getNorth=function(){return this._ne.lat},Wf.prototype.toArray=function(){return[this._sw.toArray(),this._ne.toArray()]},Wf.prototype.toString=function(){return"LngLatBounds("+this._sw.toString()+", "+this._ne.toString()+")"},Wf.prototype.isEmpty=function(){return!(this._sw&&this._ne)},Wf.prototype.contains=function(C){var G=Fc.convert(C),ne=G.lng,xe=G.lat,Re=this._sw.lat<=xe&&xe<=this._ne.lat,Ve=this._sw.lng<=ne&&ne<=this._ne.lng;return this._sw.lng>this._ne.lng&&(Ve=this._sw.lng>=ne&&ne>=this._ne.lng),Re&&Ve},Wf.convert=function(C){return!C||C instanceof Wf?C:new Wf(C)};var Dk=63710088e-1,Fc=function(C,G){if(isNaN(C)||isNaN(G))throw new Error("Invalid LngLat object: ("+C+", "+G+")");if(this.lng=+C,this.lat=+G,this.lat>90||this.lat<-90)throw new Error("Invalid LngLat latitude value: must be between -90 and 90")};Fc.prototype.wrap=function(){return new Fc(_(this.lng,-180,180),this.lat)},Fc.prototype.toArray=function(){return[this.lng,this.lat]},Fc.prototype.toString=function(){return"LngLat("+this.lng+", "+this.lat+")"},Fc.prototype.distanceTo=function(C){var G=Math.PI/180,ne=this.lat*G,xe=C.lat*G,Re=Math.sin(ne)*Math.sin(xe)+Math.cos(ne)*Math.cos(xe)*Math.cos((C.lng-this.lng)*G),Ve=Dk*Math.acos(Math.min(Re,1));return Ve},Fc.prototype.toBounds=function(C){C===void 0&&(C=0);var G=40075017,ne=360*C/G,xe=ne/Math.cos(Math.PI/180*this.lat);return new Wf(new Fc(this.lng-xe,this.lat-ne),new Fc(this.lng+xe,this.lat+ne))},Fc.convert=function(C){if(C instanceof Fc)return C;if(Array.isArray(C)&&(C.length===2||C.length===3))return new Fc(Number(C[0]),Number(C[1]));if(!Array.isArray(C)&&typeof C=="object"&&C!==null)return new Fc(Number("lng"in C?C.lng:C.lon),Number(C.lat));throw new Error("`LngLatLike` argument must be specified as a LngLat instance, an object {lng: , lat: }, an object {lon: , lat: }, or an array of [, ]")};var zk=2*Math.PI*Dk;function Fk(k){return zk*Math.cos(k*Math.PI/180)}function Ok(k){return(180+k)/360}function Bk(k){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+k*Math.PI/360)))/360}function Nk(k,C){return k/Fk(C)}function ZW(k){return k*360-180}function yA(k){var C=180-k*360;return 360/Math.PI*Math.atan(Math.exp(C*Math.PI/180))-90}function YW(k,C){return k*Fk(yA(C))}function KW(k){return 1/Math.cos(k*Math.PI/180)}var N0=function(C,G,ne){ne===void 0&&(ne=0),this.x=+C,this.y=+G,this.z=+ne};N0.fromLngLat=function(C,G){G===void 0&&(G=0);var ne=Fc.convert(C);return new N0(Ok(ne.lng),Bk(ne.lat),Nk(G,ne.lat))},N0.prototype.toLngLat=function(){return new Fc(ZW(this.x),yA(this.y))},N0.prototype.toAltitude=function(){return YW(this.z,this.y)},N0.prototype.meterInMercatorCoordinateUnits=function(){return 1/zk*KW(yA(this.y))};var U0=function(C,G,ne){this.z=C,this.x=G,this.y=ne,this.key=t_(0,C,C,G,ne)};U0.prototype.equals=function(C){return this.z===C.z&&this.x===C.x&&this.y===C.y},U0.prototype.url=function(C,G){var ne=XW(this.x,this.y,this.z),xe=JW(this.z,this.x,this.y);return C[(this.x+this.y)%C.length].replace("{prefix}",(this.x%16).toString(16)+(this.y%16).toString(16)).replace("{z}",String(this.z)).replace("{x}",String(this.x)).replace("{y}",String(G==="tms"?Math.pow(2,this.z)-this.y-1:this.y)).replace("{quadkey}",xe).replace("{bbox-epsg-3857}",ne)},U0.prototype.getTilePoint=function(C){var G=Math.pow(2,this.z);return new n((C.x*G-this.x)*ci,(C.y*G-this.y)*ci)},U0.prototype.toString=function(){return this.z+"/"+this.x+"/"+this.y};var Uk=function(C,G){this.wrap=C,this.canonical=G,this.key=t_(C,G.z,G.z,G.x,G.y)},Xf=function(C,G,ne,xe,Re){this.overscaledZ=C,this.wrap=G,this.canonical=new U0(ne,+xe,+Re),this.key=t_(G,C,ne,xe,Re)};Xf.prototype.equals=function(C){return this.overscaledZ===C.overscaledZ&&this.wrap===C.wrap&&this.canonical.equals(C.canonical)},Xf.prototype.scaledTo=function(C){var G=this.canonical.z-C;return C>this.canonical.z?new Xf(C,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new Xf(C,this.wrap,C,this.canonical.x>>G,this.canonical.y>>G)},Xf.prototype.calculateScaledKey=function(C,G){var ne=this.canonical.z-C;return C>this.canonical.z?t_(this.wrap*+G,C,this.canonical.z,this.canonical.x,this.canonical.y):t_(this.wrap*+G,C,C,this.canonical.x>>ne,this.canonical.y>>ne)},Xf.prototype.isChildOf=function(C){if(C.wrap!==this.wrap)return!1;var G=this.canonical.z-C.canonical.z;return C.overscaledZ===0||C.overscaledZ>G&&C.canonical.y===this.canonical.y>>G},Xf.prototype.children=function(C){if(this.overscaledZ>=C)return[new Xf(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];var G=this.canonical.z+1,ne=this.canonical.x*2,xe=this.canonical.y*2;return[new Xf(G,this.wrap,G,ne,xe),new Xf(G,this.wrap,G,ne+1,xe),new Xf(G,this.wrap,G,ne,xe+1),new Xf(G,this.wrap,G,ne+1,xe+1)]},Xf.prototype.isLessThan=function(C){return this.wrapC.wrap?!1:this.overscaledZC.overscaledZ?!1:this.canonical.xC.canonical.x?!1:this.canonical.y0;Re--)xe=1<=this.dim+1||G<-1||G>=this.dim+1)throw new RangeError("out of range source coordinates for DEM data");return(G+1)*this.stride+(C+1)},Bv.prototype._unpackMapbox=function(C,G,ne){return(C*256*256+G*256+ne)/10-1e4},Bv.prototype._unpackTerrarium=function(C,G,ne){return C*256+G+ne/256-32768},Bv.prototype.getPixels=function(){return new eh({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))},Bv.prototype.backfillBorder=function(C,G,ne){if(this.dim!==C.dim)throw new Error("dem dimension mismatch");var xe=G*this.dim,Re=G*this.dim+this.dim,Ve=ne*this.dim,ht=ne*this.dim+this.dim;switch(G){case-1:xe=Re-1;break;case 1:Re=xe+1;break}switch(ne){case-1:Ve=ht-1;break;case 1:ht=Ve+1;break}for(var Dt=-G*this.dim,Gt=-ne*this.dim,er=Ve;er=0&&Pr[3]>=0&&Dt.insert(ht,Pr[0],Pr[1],Pr[2],Pr[3])}},Nv.prototype.loadVTLayers=function(){return this.vtLayers||(this.vtLayers=new Xd.VectorTile(new vo(this.rawTileData)).layers,this.sourceLayerCoder=new db(this.vtLayers?Object.keys(this.vtLayers).sort():["_geojsonTileLayer"])),this.vtLayers},Nv.prototype.query=function(C,G,ne,xe){var Re=this;this.loadVTLayers();for(var Ve=C.params||{},ht=ci/C.tileSize/C.scale,Dt=Je(Ve.filter),Gt=C.queryGeometry,er=C.queryPadding*ht,Pr=qk(Gt),Zr=this.grid.query(Pr.minX-er,Pr.minY-er,Pr.maxX+er,Pr.maxY+er),jr=qk(C.cameraQueryGeometry),ca=this.grid3D.query(jr.minX-er,jr.minY-er,jr.maxX+er,jr.maxY+er,function(Tn,qn,Bn,Eo){return td(C.cameraQueryGeometry,Tn-er,qn-er,Bn+er,Eo+er)}),Ba=0,Ei=ca;Baxe)Re=!1;else if(!G)Re=!0;else if(this.expirationTime=Dr.maxzoom)&&Dr.visibility!=="none"){h(kr,this.zoom,Jt);var ra=$a[Dr.id]=Dr.createBucket({index:Na.bucketLayerIDs.length,layers:kr,zoom:this.zoom,pixelRatio:this.pixelRatio,overscaling:this.overscaling,collisionBoxArray:this.collisionBoxArray,sourceLayerIndex:rn,sourceID:this.source});ra.populate(on,Ya,this.tileID.canonical),Na.bucketLayerIDs.push(kr.map(function(ia){return ia.id}))}}}}var Gr,wt,Kt,Cr,Xr=e.mapObject(Ya.glyphDependencies,function(ia){return Object.keys(ia).map(Number)});Object.keys(Xr).length?Br.send("getGlyphs",{uid:this.uid,stacks:Xr},function(ia,Aa){Gr||(Gr=ia,wt=Aa,La.call(aa))}):wt={};var Ta=Object.keys(Ya.iconDependencies);Ta.length?Br.send("getImages",{icons:Ta,source:this.source,tileID:this.tileID,type:"icons"},function(ia,Aa){Gr||(Gr=ia,Kt=Aa,La.call(aa))}):Kt={};var Ca=Object.keys(Ya.patternDependencies);Ca.length?Br.send("getImages",{icons:Ca,source:this.source,tileID:this.tileID,type:"patterns"},function(ia,Aa){Gr||(Gr=ia,Cr=Aa,La.call(aa))}):Cr={},La.call(this);function La(){if(Gr)return ta(Gr);if(wt&&Kt&&Cr){var ia=new i(wt),Aa=new e.ImageAtlas(Kt,Cr);for(var Ki in $a){var pi=$a[Ki];pi instanceof e.SymbolBucket?(h(pi.layers,this.zoom,Jt),e.performSymbolLayout(pi,wt,ia.positions,Kt,Aa.iconPositions,this.showCollisionBoxes,this.tileID.canonical)):pi.hasPattern&&(pi instanceof e.LineBucket||pi instanceof e.FillBucket||pi instanceof e.FillExtrusionBucket)&&(h(pi.layers,this.zoom,Jt),pi.addFeatures(Ya,this.tileID.canonical,Aa.patternPositions))}this.status="done",ta(null,{buckets:e.values($a).filter(function(cn){return!cn.isEmpty()}),featureIndex:Na,collisionBoxArray:this.collisionBoxArray,glyphAtlasImage:ia.image,imageAtlas:Aa,glyphMap:this.returnDependencies?wt:null,iconMap:this.returnDependencies?Kt:null,glyphPositions:this.returnDependencies?ia.positions:null})}}};function h(Yt,Ft,Zt){for(var Jt=new e.EvaluationParameters(Ft),Br=0,ta=Yt;Br=0!=!!Ft&&Yt.reverse()}var M=e.vectorTile.VectorTileFeature.prototype.toGeoJSON,y=function(Ft){this._feature=Ft,this.extent=e.EXTENT,this.type=Ft.type,this.properties=Ft.tags,"id"in Ft&&!isNaN(Ft.id)&&(this.id=parseInt(Ft.id,10))};y.prototype.loadGeometry=function(){if(this._feature.type===1){for(var Ft=[],Zt=0,Jt=this._feature.geometry;Zt"u"&&(Jt.push(fa),Na=Jt.length-1,ta[fa]=Na),Ft.writeVarint(Na);var $a=Zt.properties[fa],Ya=typeof $a;Ya!=="string"&&Ya!=="boolean"&&Ya!=="number"&&($a=JSON.stringify($a));var ri=Ya+":"+$a,mi=aa[ri];typeof mi>"u"&&(Br.push($a),mi=Br.length-1,aa[ri]=mi),Ft.writeVarint(mi)}}function Q(Yt,Ft){return(Ft<<3)+(Yt&7)}function ue(Yt){return Yt<<1^Yt>>31}function se(Yt,Ft){for(var Zt=Yt.loadGeometry(),Jt=Yt.type,Br=0,ta=0,aa=Zt.length,fa=0;fa>1;$(Yt,Ft,aa,Jt,Br,ta%2),V(Yt,Ft,Zt,Jt,aa-1,ta+1),V(Yt,Ft,Zt,aa+1,Br,ta+1)}}function $(Yt,Ft,Zt,Jt,Br,ta){for(;Br>Jt;){if(Br-Jt>600){var aa=Br-Jt+1,fa=Zt-Jt+1,Na=Math.log(aa),$a=.5*Math.exp(2*Na/3),Ya=.5*Math.sqrt(Na*$a*(aa-$a)/aa)*(fa-aa/2<0?-1:1),ri=Math.max(Jt,Math.floor(Zt-fa*$a/aa+Ya)),mi=Math.min(Br,Math.floor(Zt+(aa-fa)*$a/aa+Ya));$(Yt,Ft,Zt,ri,mi,ta)}var Da=Ft[2*Zt+ta],rn=Jt,on=Br;for(J(Yt,Ft,Jt,Zt),Ft[2*Br+ta]>Da&&J(Yt,Ft,Jt,Br);rnDa;)on--}Ft[2*Jt+ta]===Da?J(Yt,Ft,Jt,on):(on++,J(Yt,Ft,on,Br)),on<=Zt&&(Jt=on+1),Zt<=on&&(Br=on-1)}}function J(Yt,Ft,Zt,Jt){X(Yt,Zt,Jt),X(Ft,2*Zt,2*Jt),X(Ft,2*Zt+1,2*Jt+1)}function X(Yt,Ft,Zt){var Jt=Yt[Ft];Yt[Ft]=Yt[Zt],Yt[Zt]=Jt}function oe(Yt,Ft,Zt,Jt,Br,ta,aa){for(var fa=[0,Yt.length-1,0],Na=[],$a,Ya;fa.length;){var ri=fa.pop(),mi=fa.pop(),Da=fa.pop();if(mi-Da<=aa){for(var rn=Da;rn<=mi;rn++)$a=Ft[2*rn],Ya=Ft[2*rn+1],$a>=Zt&&$a<=Br&&Ya>=Jt&&Ya<=ta&&Na.push(Yt[rn]);continue}var on=Math.floor((Da+mi)/2);$a=Ft[2*on],Ya=Ft[2*on+1],$a>=Zt&&$a<=Br&&Ya>=Jt&&Ya<=ta&&Na.push(Yt[on]);var kt=(ri+1)%2;(ri===0?Zt<=$a:Jt<=Ya)&&(fa.push(Da),fa.push(on-1),fa.push(kt)),(ri===0?Br>=$a:ta>=Ya)&&(fa.push(on+1),fa.push(mi),fa.push(kt))}return Na}function ie(Yt,Ft,Zt,Jt,Br,ta){for(var aa=[0,Yt.length-1,0],fa=[],Na=Br*Br;aa.length;){var $a=aa.pop(),Ya=aa.pop(),ri=aa.pop();if(Ya-ri<=ta){for(var mi=ri;mi<=Ya;mi++)j(Ft[2*mi],Ft[2*mi+1],Zt,Jt)<=Na&&fa.push(Yt[mi]);continue}var Da=Math.floor((ri+Ya)/2),rn=Ft[2*Da],on=Ft[2*Da+1];j(rn,on,Zt,Jt)<=Na&&fa.push(Yt[Da]);var kt=($a+1)%2;($a===0?Zt-Br<=rn:Jt-Br<=on)&&(aa.push(ri),aa.push(Da-1),aa.push(kt)),($a===0?Zt+Br>=rn:Jt+Br>=on)&&(aa.push(Da+1),aa.push(Ya),aa.push(kt))}return fa}function j(Yt,Ft,Zt,Jt){var Br=Yt-Zt,ta=Ft-Jt;return Br*Br+ta*ta}var ee=function(Yt){return Yt[0]},re=function(Yt){return Yt[1]},ce=function(Ft,Zt,Jt,Br,ta){Zt===void 0&&(Zt=ee),Jt===void 0&&(Jt=re),Br===void 0&&(Br=64),ta===void 0&&(ta=Float64Array),this.nodeSize=Br,this.points=Ft;for(var aa=Ft.length<65536?Uint16Array:Uint32Array,fa=this.ids=new aa(Ft.length),Na=this.coords=new ta(Ft.length*2),$a=0;$a=Br;Ya--){var ri=+Date.now();Na=this._cluster(Na,Ya),this.trees[Ya]=new ce(Na,fe,Oe,aa,Float32Array),Jt&&console.log("z%d: %d clusters in %dms",Ya,Na.length,+Date.now()-ri)}return Jt&&console.timeEnd("total time"),this},Se.prototype.getClusters=function(Ft,Zt){var Jt=((Ft[0]+180)%360+360)%360-180,Br=Math.max(-90,Math.min(90,Ft[1])),ta=Ft[2]===180?180:((Ft[2]+180)%360+360)%360-180,aa=Math.max(-90,Math.min(90,Ft[3]));if(Ft[2]-Ft[0]>=360)Jt=-180,ta=180;else if(Jt>ta){var fa=this.getClusters([Jt,Br,180,aa],Zt),Na=this.getClusters([-180,Br,ta,aa],Zt);return fa.concat(Na)}for(var $a=this.trees[this._limitZoom(Zt)],Ya=$a.range(nt(Jt),tt(aa),nt(ta),tt(Br)),ri=[],mi=0,Da=Ya;miZt&&(on+=Rr.numPoints||1)}if(on>=Na){for(var zr=ri.x*rn,kr=ri.y*rn,Dr=fa&&rn>1?this._map(ri,!0):null,ra=(Ya<<5)+(Zt+1)+this.points.length,Gr=0,wt=Da;Gr1)for(var Ta=0,Ca=Da;Ta>5},Se.prototype._getOriginZoom=function(Ft){return(Ft-this.points.length)%32},Se.prototype._map=function(Ft,Zt){if(Ft.numPoints)return Zt?_e({},Ft.properties):Ft.properties;var Jt=this.points[Ft.index].properties,Br=this.options.map(Jt);return Zt&&Br===Jt?_e({},Br):Br};function De(Yt,Ft,Zt,Jt,Br){return{x:Yt,y:Ft,zoom:1/0,id:Zt,parentId:-1,numPoints:Jt,properties:Br}}function Fe(Yt,Ft){var Zt=Yt.geometry.coordinates,Jt=Zt[0],Br=Zt[1];return{x:nt(Jt),y:tt(Br),zoom:1/0,index:Ft,parentId:-1}}function Ze(Yt){return{type:"Feature",id:Yt.id,properties:at(Yt),geometry:{type:"Point",coordinates:[ut(Yt.x),Me(Yt.y)]}}}function at(Yt){var Ft=Yt.numPoints,Zt=Ft>=1e4?Math.round(Ft/1e3)+"k":Ft>=1e3?Math.round(Ft/100)/10+"k":Ft;return _e(_e({},Yt.properties),{cluster:!0,cluster_id:Yt.id,point_count:Ft,point_count_abbreviated:Zt})}function nt(Yt){return Yt/360+.5}function tt(Yt){var Ft=Math.sin(Yt*Math.PI/180),Zt=.5-.25*Math.log((1+Ft)/(1-Ft))/Math.PI;return Zt<0?0:Zt>1?1:Zt}function ut(Yt){return(Yt-.5)*360}function Me(Yt){var Ft=(180-Yt*360)*Math.PI/180;return 360*Math.atan(Math.exp(Ft))/Math.PI-90}function _e(Yt,Ft){for(var Zt in Ft)Yt[Zt]=Ft[Zt];return Yt}function fe(Yt){return Yt.x}function Oe(Yt){return Yt.y}function rt(Yt,Ft,Zt,Jt){for(var Br=Jt,ta=Zt-Ft>>1,aa=Zt-Ft,fa,Na=Yt[Ft],$a=Yt[Ft+1],Ya=Yt[Zt],ri=Yt[Zt+1],mi=Ft+3;miBr)fa=mi,Br=Da;else if(Da===Br){var rn=Math.abs(mi-ta);rnJt&&(fa-Ft>3&&rt(Yt,Ft,fa,Jt),Yt[fa+2]=Br,Zt-fa>3&&rt(Yt,fa,Zt,Jt))}function st(Yt,Ft,Zt,Jt,Br,ta){var aa=Br-Zt,fa=ta-Jt;if(aa!==0||fa!==0){var Na=((Yt-Zt)*aa+(Ft-Jt)*fa)/(aa*aa+fa*fa);Na>1?(Zt=Br,Jt=ta):Na>0&&(Zt+=aa*Na,Jt+=fa*Na)}return aa=Yt-Zt,fa=Ft-Jt,aa*aa+fa*fa}function Qe(Yt,Ft,Zt,Jt){var Br={id:typeof Yt>"u"?null:Yt,type:Ft,geometry:Zt,tags:Jt,minX:1/0,minY:1/0,maxX:-1/0,maxY:-1/0};return Pt(Br),Br}function Pt(Yt){var Ft=Yt.geometry,Zt=Yt.type;if(Zt==="Point"||Zt==="MultiPoint"||Zt==="LineString")Lt(Yt,Ft);else if(Zt==="Polygon"||Zt==="MultiLineString")for(var Jt=0;Jt0&&(Jt?aa+=(Br*$a-Na*ta)/2:aa+=Math.sqrt(Math.pow(Na-Br,2)+Math.pow($a-ta,2))),Br=Na,ta=$a}var Ya=Ft.length-3;Ft[2]=1,rt(Ft,0,Ya,Zt),Ft[Ya+2]=1,Ft.size=Math.abs(aa),Ft.start=0,Ft.end=Ft.size}function qr(Yt,Ft,Zt,Jt){for(var Br=0;Br1?1:Zt}function bt(Yt,Ft,Zt,Jt,Br,ta,aa,fa){if(Zt/=Ft,Jt/=Ft,ta>=Zt&&aa=Jt)return null;for(var Na=[],$a=0;$a=Zt&&rn=Jt)continue;var on=[];if(mi==="Point"||mi==="MultiPoint")Ne(ri,on,Zt,Jt,Br);else if(mi==="LineString")Ke(ri,on,Zt,Jt,Br,!1,fa.lineMetrics);else if(mi==="MultiLineString")Pe(ri,on,Zt,Jt,Br,!1);else if(mi==="Polygon")Pe(ri,on,Zt,Jt,Br,!0);else if(mi==="MultiPolygon")for(var kt=0;kt=Zt&&aa<=Jt&&(Ft.push(Yt[ta]),Ft.push(Yt[ta+1]),Ft.push(Yt[ta+2]))}}function Ke(Yt,Ft,Zt,Jt,Br,ta,aa){for(var fa=Te(Yt),Na=Br===0?Ce:Ee,$a=Yt.start,Ya,ri,mi=0;miZt&&(ri=Na(fa,Da,rn,kt,ft,Zt),aa&&(fa.start=$a+Ya*ri)):Mr>Jt?Rr=Zt&&(ri=Na(fa,Da,rn,kt,ft,Zt),zr=!0),Rr>Jt&&Mr<=Jt&&(ri=Na(fa,Da,rn,kt,ft,Jt),zr=!0),!ta&&zr&&(aa&&(fa.end=$a+Ya*ri),Ft.push(fa),fa=Te(Yt)),aa&&($a+=Ya)}var kr=Yt.length-3;Da=Yt[kr],rn=Yt[kr+1],on=Yt[kr+2],Mr=Br===0?Da:rn,Mr>=Zt&&Mr<=Jt&&je(fa,Da,rn,on),kr=fa.length-3,ta&&kr>=3&&(fa[kr]!==fa[0]||fa[kr+1]!==fa[1])&&je(fa,fa[0],fa[1],fa[2]),fa.length&&Ft.push(fa)}function Te(Yt){var Ft=[];return Ft.size=Yt.size,Ft.start=Yt.start,Ft.end=Yt.end,Ft}function Pe(Yt,Ft,Zt,Jt,Br,ta){for(var aa=0;aaaa.maxX&&(aa.maxX=Ya),ri>aa.maxY&&(aa.maxY=ri)}return aa}function ar(Yt,Ft,Zt,Jt){var Br=Ft.geometry,ta=Ft.type,aa=[];if(ta==="Point"||ta==="MultiPoint")for(var fa=0;fa0&&Ft.size<(Br?aa:Jt)){Zt.numPoints+=Ft.length/3;return}for(var fa=[],Na=0;Naaa)&&(Zt.numSimplified++,fa.push(Ft[Na]),fa.push(Ft[Na+1])),Zt.numPoints++;Br&&Lr(fa,ta),Yt.push(fa)}function Lr(Yt,Ft){for(var Zt=0,Jt=0,Br=Yt.length,ta=Br-2;Jt0===Ft)for(Jt=0,Br=Yt.length;Jt
24)throw new Error("maxZoom should be in the 0-24 range");if(Ft.promoteId&&Ft.generateId)throw new Error("promoteId and generateId cannot be used together.");var Jt=qt(Yt,Ft);this.tiles={},this.tileCoords=[],Zt&&(console.timeEnd("preprocess data"),console.log("index: maxZoom: %d, maxPoints: %d",Ft.indexMaxZoom,Ft.indexMaxPoints),console.time("generate tiles"),this.stats={},this.total=0),Jt=Ie(Jt,Ft),Jt.length&&this.splitTile(Jt,0,0,0),Zt&&(Jt.length&&console.log("features: %d, points: %d",this.tiles[0].numFeatures,this.tiles[0].numPoints),console.timeEnd("generate tiles"),console.log("tiles generated:",this.total,JSON.stringify(this.stats)))}za.prototype.options={maxZoom:14,indexMaxZoom:5,indexMaxPoints:1e5,tolerance:3,extent:4096,buffer:64,lineMetrics:!1,promoteId:null,generateId:!1,debug:0},za.prototype.splitTile=function(Yt,Ft,Zt,Jt,Br,ta,aa){for(var fa=[Yt,Ft,Zt,Jt],Na=this.options,$a=Na.debug;fa.length;){Jt=fa.pop(),Zt=fa.pop(),Ft=fa.pop(),Yt=fa.pop();var Ya=1<1&&console.time("creation"),mi=this.tiles[ri]=cr(Yt,Ft,Zt,Jt,Na),this.tileCoords.push({z:Ft,x:Zt,y:Jt}),$a)){$a>1&&(console.log("tile z%d-%d-%d (features: %d, points: %d, simplified: %d)",Ft,Zt,Jt,mi.numFeatures,mi.numPoints,mi.numSimplified),console.timeEnd("creation"));var Da="z"+Ft;this.stats[Da]=(this.stats[Da]||0)+1,this.total++}if(mi.source=Yt,Br){if(Ft===Na.maxZoom||Ft===Br)continue;var rn=1<1&&console.time("clipping");var on=.5*Na.buffer/Na.extent,kt=.5-on,ft=.5+on,Mr=1+on,Rr,zr,kr,Dr,ra,Gr;Rr=zr=kr=Dr=null,ra=bt(Yt,Ya,Zt-on,Zt+ft,0,mi.minX,mi.maxX,Na),Gr=bt(Yt,Ya,Zt+kt,Zt+Mr,0,mi.minX,mi.maxX,Na),Yt=null,ra&&(Rr=bt(ra,Ya,Jt-on,Jt+ft,1,mi.minY,mi.maxY,Na),zr=bt(ra,Ya,Jt+kt,Jt+Mr,1,mi.minY,mi.maxY,Na),ra=null),Gr&&(kr=bt(Gr,Ya,Jt-on,Jt+ft,1,mi.minY,mi.maxY,Na),Dr=bt(Gr,Ya,Jt+kt,Jt+Mr,1,mi.minY,mi.maxY,Na),Gr=null),$a>1&&console.timeEnd("clipping"),fa.push(Rr||[],Ft+1,Zt*2,Jt*2),fa.push(zr||[],Ft+1,Zt*2,Jt*2+1),fa.push(kr||[],Ft+1,Zt*2+1,Jt*2),fa.push(Dr||[],Ft+1,Zt*2+1,Jt*2+1)}}},za.prototype.getTile=function(Yt,Ft,Zt){var Jt=this.options,Br=Jt.extent,ta=Jt.debug;if(Yt<0||Yt>24)return null;var aa=1<1&&console.log("drilling down to z%d-%d-%d",Yt,Ft,Zt);for(var Na=Yt,$a=Ft,Ya=Zt,ri;!ri&&Na>0;)Na--,$a=Math.floor($a/2),Ya=Math.floor(Ya/2),ri=this.tiles[Ra(Na,$a,Ya)];return!ri||!ri.source?null:(ta>1&&console.log("found parent tile z%d-%d-%d",Na,$a,Ya),ta>1&&console.time("drilling down"),this.splitTile(ri.source,Na,$a,Ya,Yt,Ft,Zt),ta>1&&console.timeEnd("drilling down"),this.tiles[fa]?xt(this.tiles[fa],Br):null)};function Ra(Yt,Ft,Zt){return((1<=0?0:ve.button},r.remove=function(ve){ve.parentNode&&ve.parentNode.removeChild(ve)};function v(ve,Y,ye){var te,me,Ge,Le=e.browser.devicePixelRatio>1?"@2x":"",$e=e.getJSON(Y.transformRequest(Y.normalizeSpriteURL(ve,Le,".json"),e.ResourceType.SpriteJSON),function(_r,Nr){$e=null,Ge||(Ge=_r,te=Nr,jt())}),mt=e.getImage(Y.transformRequest(Y.normalizeSpriteURL(ve,Le,".png"),e.ResourceType.SpriteImage),function(_r,Nr){mt=null,Ge||(Ge=_r,me=Nr,jt())});function jt(){if(Ge)ye(Ge);else if(te&&me){var _r=e.browser.getImageData(me),Nr={};for(var pr in te){var yt=te[pr],Et=yt.width,Bt=yt.height,ir=yt.x,hr=yt.y,sr=yt.sdf,dr=yt.pixelRatio,lr=yt.stretchX,Wt=yt.stretchY,or=yt.content,Vt=new e.RGBAImage({width:Et,height:Bt});e.RGBAImage.copy(_r,Vt,{x:ir,y:hr},{x:0,y:0},{width:Et,height:Bt}),Nr[pr]={data:Vt,pixelRatio:dr,sdf:sr,stretchX:lr,stretchY:Wt,content:or}}ye(null,Nr)}}return{cancel:function(){$e&&($e.cancel(),$e=null),mt&&(mt.cancel(),mt=null)}}}function T(ve){var Y=ve.userImage;if(Y&&Y.render){var ye=Y.render();if(ye)return ve.data.replace(new Uint8Array(Y.data.buffer)),!0}return!1}var l=1,_=function(ve){function Y(){ve.call(this),this.images={},this.updatedImages={},this.callbackDispatchedThisFrame={},this.loaded=!1,this.requestors=[],this.patterns={},this.atlasImage=new e.RGBAImage({width:1,height:1}),this.dirty=!0}return ve&&(Y.__proto__=ve),Y.prototype=Object.create(ve&&ve.prototype),Y.prototype.constructor=Y,Y.prototype.isLoaded=function(){return this.loaded},Y.prototype.setLoaded=function(te){if(this.loaded!==te&&(this.loaded=te,te)){for(var me=0,Ge=this.requestors;me=0?1.2:1))}b.prototype.draw=function(ve){this.ctx.clearRect(0,0,this.size,this.size),this.ctx.fillText(ve,this.buffer,this.middle);for(var Y=this.ctx.getImageData(0,0,this.size,this.size),ye=new Uint8ClampedArray(this.size*this.size),te=0;te65535){_r(new Error("glyphs > 65535 not supported"));return}if(yt.ranges[Bt]){_r(null,{stack:Nr,id:pr,glyph:Et});return}var ir=yt.requests[Bt];ir||(ir=yt.requests[Bt]=[],g.loadGlyphRange(Nr,Bt,te.url,te.requestManager,function(hr,sr){if(sr){for(var dr in sr)te._doesCharSupportLocalGlyph(+dr)||(yt.glyphs[+dr]=sr[+dr]);yt.ranges[Bt]=!0}for(var lr=0,Wt=ir;lr1&&(jt=Y[++mt]);var Nr=Math.abs(_r-jt.left),pr=Math.abs(_r-jt.right),yt=Math.min(Nr,pr),Et=void 0,Bt=Ge/te*(me+1);if(jt.isDash){var ir=me-Math.abs(Bt);Et=Math.sqrt(yt*yt+ir*ir)}else Et=me-Math.sqrt(yt*yt+Bt*Bt);this.data[$e+_r]=Math.max(0,Math.min(255,Et+128))}},F.prototype.addRegularDash=function(Y){for(var ye=Y.length-1;ye>=0;--ye){var te=Y[ye],me=Y[ye+1];te.zeroLength?Y.splice(ye,1):me&&me.isDash===te.isDash&&(me.left=te.left,Y.splice(ye,1))}var Ge=Y[0],Le=Y[Y.length-1];Ge.isDash===Le.isDash&&(Ge.left=Le.left-this.width,Le.right=Ge.right+this.width);for(var $e=this.width*this.nextRow,mt=0,jt=Y[mt],_r=0;_r1&&(jt=Y[++mt]);var Nr=Math.abs(_r-jt.left),pr=Math.abs(_r-jt.right),yt=Math.min(Nr,pr),Et=jt.isDash?yt:-yt;this.data[$e+_r]=Math.max(0,Math.min(255,Et+128))}},F.prototype.addDash=function(Y,ye){var te=ye?7:0,me=2*te+1;if(this.nextRow+me>this.height)return e.warnOnce("LineAtlas out of space"),null;for(var Ge=0,Le=0;Le=te.minX&&Y.x=te.minY&&Y.y0&&(_r[new e.OverscaledTileID(te.overscaledZ,$e,me.z,Le,me.y-1).key]={backfilled:!1},_r[new e.OverscaledTileID(te.overscaledZ,te.wrap,me.z,me.x,me.y-1).key]={backfilled:!1},_r[new e.OverscaledTileID(te.overscaledZ,jt,me.z,mt,me.y-1).key]={backfilled:!1}),me.y+10&&(Ge.resourceTiming=te._resourceTiming,te._resourceTiming=[]),te.fire(new e.Event("data",Ge))})},Y.prototype.onAdd=function(te){this.map=te,this.load()},Y.prototype.setData=function(te){var me=this;return this._data=te,this.fire(new e.Event("dataloading",{dataType:"source"})),this._updateWorkerData(function(Ge){if(Ge){me.fire(new e.ErrorEvent(Ge));return}var Le={dataType:"source",sourceDataType:"content"};me._collectResourceTiming&&me._resourceTiming&&me._resourceTiming.length>0&&(Le.resourceTiming=me._resourceTiming,me._resourceTiming=[]),me.fire(new e.Event("data",Le))}),this},Y.prototype.getClusterExpansionZoom=function(te,me){return this.actor.send("geojson.getClusterExpansionZoom",{clusterId:te,source:this.id},me),this},Y.prototype.getClusterChildren=function(te,me){return this.actor.send("geojson.getClusterChildren",{clusterId:te,source:this.id},me),this},Y.prototype.getClusterLeaves=function(te,me,Ge,Le){return this.actor.send("geojson.getClusterLeaves",{source:this.id,clusterId:te,limit:me,offset:Ge},Le),this},Y.prototype._updateWorkerData=function(te){var me=this;this._loaded=!1;var Ge=e.extend({},this.workerOptions),Le=this._data;typeof Le=="string"?(Ge.request=this.map._requestManager.transformRequest(e.browser.resolveURL(Le),e.ResourceType.Source),Ge.request.collectResourceTiming=this._collectResourceTiming):Ge.data=JSON.stringify(Le),this.actor.send(this.type+".loadData",Ge,function($e,mt){me._removed||mt&&mt.abandoned||(me._loaded=!0,mt&&mt.resourceTiming&&mt.resourceTiming[me.id]&&(me._resourceTiming=mt.resourceTiming[me.id].slice(0)),me.actor.send(me.type+".coalesce",{source:Ge.source},null),te($e))})},Y.prototype.loaded=function(){return this._loaded},Y.prototype.loadTile=function(te,me){var Ge=this,Le=te.actor?"reloadTile":"loadTile";te.actor=this.actor;var $e={type:this.type,uid:te.uid,tileID:te.tileID,zoom:te.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:e.browser.devicePixelRatio,showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};te.request=this.actor.send(Le,$e,function(mt,jt){return delete te.request,te.unloadVectorData(),te.aborted?me(null):mt?me(mt):(te.loadVectorData(jt,Ge.map.painter,Le==="reloadTile"),me(null))})},Y.prototype.abortTile=function(te){te.request&&(te.request.cancel(),delete te.request),te.aborted=!0},Y.prototype.unloadTile=function(te){te.unloadVectorData(),this.actor.send("removeTile",{uid:te.uid,type:this.type,source:this.id})},Y.prototype.onRemove=function(){this._removed=!0,this.actor.send("removeSource",{type:this.type,source:this.id})},Y.prototype.serialize=function(){return e.extend({},this._options,{type:this.type,data:this._data})},Y.prototype.hasTransition=function(){return!1},Y}(e.Evented),ue=e.createLayout([{name:"a_pos",type:"Int16",components:2},{name:"a_texture_pos",type:"Int16",components:2}]),se=function(ve){function Y(ye,te,me,Ge){ve.call(this),this.id=ye,this.dispatcher=me,this.coordinates=te.coordinates,this.type="image",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(Ge),this.options=te}return ve&&(Y.__proto__=ve),Y.prototype=Object.create(ve&&ve.prototype),Y.prototype.constructor=Y,Y.prototype.load=function(te,me){var Ge=this;this._loaded=!1,this.fire(new e.Event("dataloading",{dataType:"source"})),this.url=this.options.url,e.getImage(this.map._requestManager.transformRequest(this.url,e.ResourceType.Image),function(Le,$e){Ge._loaded=!0,Le?Ge.fire(new e.ErrorEvent(Le)):$e&&(Ge.image=$e,te&&(Ge.coordinates=te),me&&me(),Ge._finishLoading())})},Y.prototype.loaded=function(){return this._loaded},Y.prototype.updateImage=function(te){var me=this;return!this.image||!te.url?this:(this.options.url=te.url,this.load(te.coordinates,function(){me.texture=null}),this)},Y.prototype._finishLoading=function(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new e.Event("data",{dataType:"source",sourceDataType:"metadata"})))},Y.prototype.onAdd=function(te){this.map=te,this.load()},Y.prototype.setCoordinates=function(te){var me=this;this.coordinates=te;var Ge=te.map(e.MercatorCoordinate.fromLngLat);this.tileID=pe(Ge),this.minzoom=this.maxzoom=this.tileID.z;var Le=Ge.map(function($e){return me.tileID.getTilePoint($e)._round()});return this._boundsArray=new e.StructArrayLayout4i8,this._boundsArray.emplaceBack(Le[0].x,Le[0].y,0,0),this._boundsArray.emplaceBack(Le[1].x,Le[1].y,e.EXTENT,0),this._boundsArray.emplaceBack(Le[3].x,Le[3].y,0,e.EXTENT),this._boundsArray.emplaceBack(Le[2].x,Le[2].y,e.EXTENT,e.EXTENT),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new e.Event("data",{dataType:"source",sourceDataType:"content"})),this},Y.prototype.prepare=function(){if(!(Object.keys(this.tiles).length===0||!this.image)){var te=this.map.painter.context,me=te.gl;this.boundsBuffer||(this.boundsBuffer=te.createVertexBuffer(this._boundsArray,ue.members)),this.boundsSegments||(this.boundsSegments=e.SegmentVector.simpleSegment(0,0,4,2)),this.texture||(this.texture=new e.Texture(te,this.image,me.RGBA),this.texture.bind(me.LINEAR,me.CLAMP_TO_EDGE));for(var Ge in this.tiles){var Le=this.tiles[Ge];Le.state!=="loaded"&&(Le.state="loaded",Le.texture=this.texture)}}},Y.prototype.loadTile=function(te,me){this.tileID&&this.tileID.equals(te.tileID.canonical)?(this.tiles[String(te.tileID.wrap)]=te,te.buckets={},me(null)):(te.state="errored",me(null))},Y.prototype.serialize=function(){return{type:"image",url:this.options.url,coordinates:this.coordinates}},Y.prototype.hasTransition=function(){return!1},Y}(e.Evented);function pe(ve){for(var Y=1/0,ye=1/0,te=-1/0,me=-1/0,Ge=0,Le=ve;Geme.end(0)?this.fire(new e.ErrorEvent(new e.ValidationError("sources."+this.id,null,"Playback for this video can be set only between the "+me.start(0)+" and "+me.end(0)+"-second mark."))):this.video.currentTime=te}},Y.prototype.getVideo=function(){return this.video},Y.prototype.onAdd=function(te){this.map||(this.map=te,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))},Y.prototype.prepare=function(){if(!(Object.keys(this.tiles).length===0||this.video.readyState<2)){var te=this.map.painter.context,me=te.gl;this.boundsBuffer||(this.boundsBuffer=te.createVertexBuffer(this._boundsArray,ue.members)),this.boundsSegments||(this.boundsSegments=e.SegmentVector.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(me.LINEAR,me.CLAMP_TO_EDGE),me.texSubImage2D(me.TEXTURE_2D,0,0,0,me.RGBA,me.UNSIGNED_BYTE,this.video)):(this.texture=new e.Texture(te,this.video,me.RGBA),this.texture.bind(me.LINEAR,me.CLAMP_TO_EDGE));for(var Ge in this.tiles){var Le=this.tiles[Ge];Le.state!=="loaded"&&(Le.state="loaded",Le.texture=this.texture)}}},Y.prototype.serialize=function(){return{type:"video",urls:this.urls,coordinates:this.coordinates}},Y.prototype.hasTransition=function(){return this.video&&!this.video.paused},Y}(se),$=function(ve){function Y(ye,te,me,Ge){ve.call(this,ye,te,me,Ge),te.coordinates?(!Array.isArray(te.coordinates)||te.coordinates.length!==4||te.coordinates.some(function(Le){return!Array.isArray(Le)||Le.length!==2||Le.some(function($e){return typeof $e!="number"})}))&&this.fire(new e.ErrorEvent(new e.ValidationError("sources."+ye,null,'"coordinates" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new e.ErrorEvent(new e.ValidationError("sources."+ye,null,'missing required property "coordinates"'))),te.animate&&typeof te.animate!="boolean"&&this.fire(new e.ErrorEvent(new e.ValidationError("sources."+ye,null,'optional "animate" property must be a boolean value'))),te.canvas?typeof te.canvas!="string"&&!(te.canvas instanceof e.window.HTMLCanvasElement)&&this.fire(new e.ErrorEvent(new e.ValidationError("sources."+ye,null,'"canvas" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new e.ErrorEvent(new e.ValidationError("sources."+ye,null,'missing required property "canvas"'))),this.options=te,this.animate=te.animate!==void 0?te.animate:!0}return ve&&(Y.__proto__=ve),Y.prototype=Object.create(ve&&ve.prototype),Y.prototype.constructor=Y,Y.prototype.load=function(){if(this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof e.window.HTMLCanvasElement?this.options.canvas:e.window.document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()){this.fire(new e.ErrorEvent(new Error("Canvas dimensions cannot be less than or equal to zero.")));return}this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading()},Y.prototype.getCanvas=function(){return this.canvas},Y.prototype.onAdd=function(te){this.map=te,this.load(),this.canvas&&this.animate&&this.play()},Y.prototype.onRemove=function(){this.pause()},Y.prototype.prepare=function(){var te=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,te=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,te=!0),!this._hasInvalidDimensions()&&Object.keys(this.tiles).length!==0){var me=this.map.painter.context,Ge=me.gl;this.boundsBuffer||(this.boundsBuffer=me.createVertexBuffer(this._boundsArray,ue.members)),this.boundsSegments||(this.boundsSegments=e.SegmentVector.simpleSegment(0,0,4,2)),this.texture?(te||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new e.Texture(me,this.canvas,Ge.RGBA,{premultiply:!0});for(var Le in this.tiles){var $e=this.tiles[Le];$e.state!=="loaded"&&($e.state="loaded",$e.texture=this.texture)}}},Y.prototype.serialize=function(){return{type:"canvas",coordinates:this.coordinates}},Y.prototype.hasTransition=function(){return this._playing},Y.prototype._hasInvalidDimensions=function(){for(var te=0,me=[this.canvas.width,this.canvas.height];tethis.max){var $e=this._getAndRemoveByKey(this.order[0]);$e&&this.onRemove($e)}return this},Fe.prototype.has=function(Y){return Y.wrapped().key in this.data},Fe.prototype.getAndRemove=function(Y){return this.has(Y)?this._getAndRemoveByKey(Y.wrapped().key):null},Fe.prototype._getAndRemoveByKey=function(Y){var ye=this.data[Y].shift();return ye.timeout&&clearTimeout(ye.timeout),this.data[Y].length===0&&delete this.data[Y],this.order.splice(this.order.indexOf(Y),1),ye.value},Fe.prototype.getByKey=function(Y){var ye=this.data[Y];return ye?ye[0].value:null},Fe.prototype.get=function(Y){if(!this.has(Y))return null;var ye=this.data[Y.wrapped().key][0];return ye.value},Fe.prototype.remove=function(Y,ye){if(!this.has(Y))return this;var te=Y.wrapped().key,me=ye===void 0?0:this.data[te].indexOf(ye),Ge=this.data[te][me];return this.data[te].splice(me,1),Ge.timeout&&clearTimeout(Ge.timeout),this.data[te].length===0&&delete this.data[te],this.onRemove(Ge.value),this.order.splice(this.order.indexOf(te),1),this},Fe.prototype.setMaxSize=function(Y){for(this.max=Y;this.order.length>this.max;){var ye=this._getAndRemoveByKey(this.order[0]);ye&&this.onRemove(ye)}return this},Fe.prototype.filter=function(Y){var ye=[];for(var te in this.data)for(var me=0,Ge=this.data[te];me1||(Math.abs(Nr)>1&&(Math.abs(Nr+yt)===1?Nr+=yt:Math.abs(Nr-yt)===1&&(Nr-=yt)),!(!_r.dem||!jt.dem)&&(jt.dem.backfillBorder(_r.dem,Nr,pr),jt.neighboringTiles&&jt.neighboringTiles[Et]&&(jt.neighboringTiles[Et].backfilled=!0)))}},Y.prototype.getTile=function(te){return this.getTileByID(te.key)},Y.prototype.getTileByID=function(te){return this._tiles[te]},Y.prototype._retainLoadedChildren=function(te,me,Ge,Le){for(var $e in this._tiles){var mt=this._tiles[$e];if(!(Le[$e]||!mt.hasData()||mt.tileID.overscaledZ<=me||mt.tileID.overscaledZ>Ge)){for(var jt=mt.tileID;mt&&mt.tileID.overscaledZ>me+1;){var _r=mt.tileID.scaledTo(mt.tileID.overscaledZ-1);mt=this._tiles[_r.key],mt&&mt.hasData()&&(jt=_r)}for(var Nr=jt;Nr.overscaledZ>me;)if(Nr=Nr.scaledTo(Nr.overscaledZ-1),te[Nr.key]){Le[jt.key]=jt;break}}}},Y.prototype.findLoadedParent=function(te,me){if(te.key in this._loadedParentTiles){var Ge=this._loadedParentTiles[te.key];return Ge&&Ge.tileID.overscaledZ>=me?Ge:null}for(var Le=te.overscaledZ-1;Le>=me;Le--){var $e=te.scaledTo(Le),mt=this._getLoadedTile($e);if(mt)return mt}},Y.prototype._getLoadedTile=function(te){var me=this._tiles[te.key];if(me&&me.hasData())return me;var Ge=this._cache.getByKey(te.wrapped().key);return Ge},Y.prototype.updateCacheSize=function(te){var me=Math.ceil(te.width/this._source.tileSize)+1,Ge=Math.ceil(te.height/this._source.tileSize)+1,Le=me*Ge,$e=5,mt=Math.floor(Le*$e),jt=typeof this._maxTileCacheSize=="number"?Math.min(this._maxTileCacheSize,mt):mt;this._cache.setMaxSize(jt)},Y.prototype.handleWrapJump=function(te){var me=this._prevLng===void 0?te:this._prevLng,Ge=te-me,Le=Ge/360,$e=Math.round(Le);if(this._prevLng=te,$e){var mt={};for(var jt in this._tiles){var _r=this._tiles[jt];_r.tileID=_r.tileID.unwrapTo(_r.tileID.wrap+$e),mt[_r.tileID.key]=_r}this._tiles=mt;for(var Nr in this._timers)clearTimeout(this._timers[Nr]),delete this._timers[Nr];for(var pr in this._tiles){var yt=this._tiles[pr];this._setTileReloadTimer(pr,yt)}}},Y.prototype.update=function(te){var me=this;if(this.transform=te,!(!this._sourceLoaded||this._paused)){this.updateCacheSize(te),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={};var Ge;this.used?this._source.tileID?Ge=te.getVisibleUnwrappedCoordinates(this._source.tileID).map(function(ya){return new e.OverscaledTileID(ya.canonical.z,ya.wrap,ya.canonical.z,ya.canonical.x,ya.canonical.y)}):(Ge=te.coveringTiles({tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled}),this._source.hasTile&&(Ge=Ge.filter(function(ya){return me._source.hasTile(ya)}))):Ge=[];var Le=te.coveringZoomLevel(this._source),$e=Math.max(Le-Y.maxOverzooming,this._source.minzoom),mt=Math.max(Le+Y.maxUnderzooming,this._source.minzoom),jt=this._updateRetainedTiles(Ge,Le);if(Na(this._source.type)){for(var _r={},Nr={},pr=Object.keys(jt),yt=0,Et=pr;ytthis._source.maxzoom){var sr=ir.children(this._source.maxzoom)[0],dr=this.getTile(sr);if(dr&&dr.hasData()){Ge[sr.key]=sr;continue}}else{var lr=ir.children(this._source.maxzoom);if(Ge[lr[0].key]&&Ge[lr[1].key]&&Ge[lr[2].key]&&Ge[lr[3].key])continue}for(var Wt=hr.wasRequested(),or=ir.overscaledZ-1;or>=$e;--or){var Vt=ir.scaledTo(or);if(Le[Vt.key]||(Le[Vt.key]=!0,hr=this.getTile(Vt),!hr&&Wt&&(hr=this._addTile(Vt)),hr&&(Ge[Vt.key]=Vt,Wt=hr.wasRequested(),hr.hasData())))break}}}return Ge},Y.prototype._updateLoadedParentTileCache=function(){this._loadedParentTiles={};for(var te in this._tiles){for(var me=[],Ge=void 0,Le=this._tiles[te].tileID;Le.overscaledZ>0;){if(Le.key in this._loadedParentTiles){Ge=this._loadedParentTiles[Le.key];break}me.push(Le.key);var $e=Le.scaledTo(Le.overscaledZ-1);if(Ge=this._getLoadedTile($e),Ge)break;Le=$e}for(var mt=0,jt=me;mt0)&&(me.hasData()&&me.state!=="reloading"?this._cache.add(me.tileID,me,me.getExpiryTimeout()):(me.aborted=!0,this._abortTile(me),this._unloadTile(me))))},Y.prototype.clearTiles=function(){this._shouldReloadOnResume=!1,this._paused=!1;for(var te in this._tiles)this._removeTile(te);this._cache.reset()},Y.prototype.tilesIn=function(te,me,Ge){var Le=this,$e=[],mt=this.transform;if(!mt)return $e;for(var jt=Ge?mt.getCameraQueryGeometry(te):te,_r=te.map(function(or){return mt.pointCoordinate(or)}),Nr=jt.map(function(or){return mt.pointCoordinate(or)}),pr=this.getIds(),yt=1/0,Et=1/0,Bt=-1/0,ir=-1/0,hr=0,sr=Nr;hr=0&&gi[1].y+ya>=0){var Ha=_r.map(function(Xi){return Fr.getTilePoint(Xi)}),ii=Nr.map(function(Xi){return Fr.getTilePoint(Xi)});$e.push({tile:Vt,tileID:Fr,queryGeometry:Ha,cameraQueryGeometry:ii,scale:Jr})}}},Wt=0;Wt=e.browser.now())return!0}return!1},Y.prototype.setFeatureState=function(te,me,Ge){te=te||"_geojsonTileLayer",this._state.updateState(te,me,Ge)},Y.prototype.removeFeatureState=function(te,me,Ge){te=te||"_geojsonTileLayer",this._state.removeFeatureState(te,me,Ge)},Y.prototype.getFeatureState=function(te,me){return te=te||"_geojsonTileLayer",this._state.getState(te,me)},Y.prototype.setDependencies=function(te,me,Ge){var Le=this._tiles[te];Le&&Le.setDependencies(me,Ge)},Y.prototype.reloadTilesForDependencies=function(te,me){for(var Ge in this._tiles){var Le=this._tiles[Ge];Le.hasDependency(te,me)&&this._reloadTile(Ge,"reloading")}this._cache.filter(function($e){return!$e.hasDependency(te,me)})},Y}(e.Evented);aa.maxOverzooming=10,aa.maxUnderzooming=3;function fa(ve,Y){var ye=Math.abs(ve.wrap*2)-+(ve.wrap<0),te=Math.abs(Y.wrap*2)-+(Y.wrap<0);return ve.overscaledZ-Y.overscaledZ||te-ye||Y.canonical.y-ve.canonical.y||Y.canonical.x-ve.canonical.x}function Na(ve){return ve==="raster"||ve==="image"||ve==="video"}function $a(){return new e.window.Worker(Io.workerUrl)}var Ya="mapboxgl_preloaded_worker_pool",ri=function(){this.active={}};ri.prototype.acquire=function(Y){if(!this.workers)for(this.workers=[];this.workers.length0?(me-Le)/$e:0;return this.points[Ge].mult(1-mt).add(this.points[ye].mult(mt))};var ia=function(Y,ye,te){var me=this.boxCells=[],Ge=this.circleCells=[];this.xCellCount=Math.ceil(Y/te),this.yCellCount=Math.ceil(ye/te);for(var Le=0;Lethis.width||me<0||ye>this.height)return Ge?!1:[];var $e=[];if(Y<=0&&ye<=0&&this.width<=te&&this.height<=me){if(Ge)return!0;for(var mt=0;mt0:$e}},ia.prototype._queryCircle=function(Y,ye,te,me,Ge){var Le=Y-te,$e=Y+te,mt=ye-te,jt=ye+te;if($e<0||Le>this.width||jt<0||mt>this.height)return me?!1:[];var _r=[],Nr={hitTest:me,circle:{x:Y,y:ye,radius:te},seenUids:{box:{},circle:{}}};return this._forEachCell(Le,mt,$e,jt,this._queryCellCircle,_r,Nr,Ge),me?_r.length>0:_r},ia.prototype.query=function(Y,ye,te,me,Ge){return this._query(Y,ye,te,me,!1,Ge)},ia.prototype.hitTest=function(Y,ye,te,me,Ge){return this._query(Y,ye,te,me,!0,Ge)},ia.prototype.hitTestCircle=function(Y,ye,te,me){return this._queryCircle(Y,ye,te,!0,me)},ia.prototype._queryCell=function(Y,ye,te,me,Ge,Le,$e,mt){var jt=$e.seenUids,_r=this.boxCells[Ge];if(_r!==null)for(var Nr=this.bboxes,pr=0,yt=_r;pr=Nr[Bt+0]&&me>=Nr[Bt+1]&&(!mt||mt(this.boxKeys[Et]))){if($e.hitTest)return Le.push(!0),!0;Le.push({key:this.boxKeys[Et],x1:Nr[Bt],y1:Nr[Bt+1],x2:Nr[Bt+2],y2:Nr[Bt+3]})}}}var ir=this.circleCells[Ge];if(ir!==null)for(var hr=this.circles,sr=0,dr=ir;sr$e*$e+mt*mt},ia.prototype._circleAndRectCollide=function(Y,ye,te,me,Ge,Le,$e){var mt=(Le-me)/2,jt=Math.abs(Y-(me+mt));if(jt>mt+te)return!1;var _r=($e-Ge)/2,Nr=Math.abs(ye-(Ge+_r));if(Nr>_r+te)return!1;if(jt<=mt||Nr<=_r)return!0;var pr=jt-mt,yt=Nr-_r;return pr*pr+yt*yt<=te*te};function Aa(ve,Y,ye,te,me){var Ge=e.create();return Y?(e.scale(Ge,Ge,[1/me,1/me,1]),ye||e.rotateZ(Ge,Ge,te.angle)):e.multiply(Ge,te.labelPlaneMatrix,ve),Ge}function Ki(ve,Y,ye,te,me){if(Y){var Ge=e.clone(ve);return e.scale(Ge,Ge,[me,me,1]),ye||e.rotateZ(Ge,Ge,-te.angle),Ge}else return te.glCoordMatrix}function pi(ve,Y){var ye=[ve.x,ve.y,0,1];go(ye,ye,Y);var te=ye[3];return{point:new e.Point(ye[0]/te,ye[1]/te),signedDistanceFromCamera:te}}function cn(ve,Y){return .5+.5*(ve/Y)}function yn(ve,Y){var ye=ve[0]/ve[3],te=ve[1]/ve[3],me=ye>=-Y[0]&&ye<=Y[0]&&te>=-Y[1]&&te<=Y[1];return me}function Pn(ve,Y,ye,te,me,Ge,Le,$e){var mt=te?ve.textSizeData:ve.iconSizeData,jt=e.evaluateSizeForZoom(mt,ye.transform.zoom),_r=[256/ye.width*2+1,256/ye.height*2+1],Nr=te?ve.text.dynamicLayoutVertexArray:ve.icon.dynamicLayoutVertexArray;Nr.clear();for(var pr=ve.lineVertexArray,yt=te?ve.text.placedSymbolArray:ve.icon.placedSymbolArray,Et=ye.transform.width/ye.transform.height,Bt=!1,ir=0;irGe)return{useVertical:!0}}return(ve===e.WritingMode.vertical?Y.yye.x)?{needsFlipping:!0}:null}function Vn(ve,Y,ye,te,me,Ge,Le,$e,mt,jt,_r,Nr,pr,yt){var Et=Y/24,Bt=ve.lineOffsetX*Et,ir=ve.lineOffsetY*Et,hr;if(ve.numGlyphs>1){var sr=ve.glyphStartIndex+ve.numGlyphs,dr=ve.lineStartIndex,lr=ve.lineStartIndex+ve.lineLength,Wt=In(Et,$e,Bt,ir,ye,_r,Nr,ve,mt,Ge,pr);if(!Wt)return{notEnoughRoom:!0};var or=pi(Wt.first.point,Le).point,Vt=pi(Wt.last.point,Le).point;if(te&&!ye){var Fr=Hn(ve.writingMode,or,Vt,yt);if(Fr)return Fr}hr=[Wt.first];for(var Jr=ve.glyphStartIndex+1;Jr0?ii.point:hn(Nr,Ha,ya,1,me),Fi=Hn(ve.writingMode,ya,Xi,yt);if(Fi)return Fi}var ci=Co(Et*$e.getoffsetX(ve.glyphStartIndex),Bt,ir,ye,_r,Nr,ve.segment,ve.lineStartIndex,ve.lineStartIndex+ve.lineLength,mt,Ge,pr);if(!ci)return{notEnoughRoom:!0};hr=[ci]}for(var bi=0,Si=hr;bi0?1:-1,Et=0;te&&(yt*=-1,Et=Math.PI),yt<0&&(Et+=Math.PI);for(var Bt=yt>0?$e+Le:$e+Le+1,ir=me,hr=me,sr=0,dr=0,lr=Math.abs(pr),Wt=[];sr+dr<=lr;){if(Bt+=yt,Bt<$e||Bt>=mt)return null;if(hr=ir,Wt.push(ir),ir=Nr[Bt],ir===void 0){var or=new e.Point(jt.getx(Bt),jt.gety(Bt)),Vt=pi(or,_r);if(Vt.signedDistanceFromCamera>0)ir=Nr[Bt]=Vt.point;else{var Fr=Bt-yt,Jr=sr===0?Ge:new e.Point(jt.getx(Fr),jt.gety(Fr));ir=hn(Jr,or,hr,lr-sr+1,_r)}}sr+=dr,dr=hr.dist(ir)}var ya=(lr-sr)/dr,gi=ir.sub(hr),Ha=gi.mult(ya)._add(hr);Ha._add(gi._unit()._perp()._mult(ye*yt));var ii=Et+Math.atan2(ir.y-hr.y,ir.x-hr.x);return Wt.push(Ha),{point:Ha,angle:ii,path:Wt}}var Wo=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function So(ve,Y){for(var ye=0;ye=1;Ui--)Si.push(ci.path[Ui]);for(var fn=1;fn0){for(var Oo=Si[0].clone(),Ss=Si[0].clone(),Xs=1;Xs=ii.x&&Ss.x<=Xi.x&&Oo.y>=ii.y&&Ss.y<=Xi.y?Cs=[Si]:Ss.xXi.x||Ss.yXi.y?Cs=[]:Cs=e.clipLine([Si],ii.x,ii.y,Xi.x,Xi.y)}for(var du=0,Ep=Cs;du=this.screenRightBoundary||methis.screenBottomBoundary},as.prototype.isInsideGrid=function(Y,ye,te,me){return te>=0&&Y=0&&ye0){var lr;return this.prevPlacement&&this.prevPlacement.variableOffsets[pr.crossTileID]&&this.prevPlacement.placements[pr.crossTileID]&&this.prevPlacement.placements[pr.crossTileID].text&&(lr=this.prevPlacement.variableOffsets[pr.crossTileID].anchor),this.variableOffsets[pr.crossTileID]={textOffset:ir,width:te,height:me,anchor:Y,textBoxScale:Ge,prevAnchor:lr},this.markUsedJustification(yt,Y,pr,Et),yt.allowVerticalPlacement&&(this.markUsedOrientation(yt,Et,pr),this.placedOrientations[pr.crossTileID]=Et),{shift:hr,placedGlyphBoxes:sr}}},Xo.prototype.placeLayerBucketPart=function(Y,ye,te){var me=this,Ge=Y.parameters,Le=Ge.bucket,$e=Ge.layout,mt=Ge.posMatrix,jt=Ge.textLabelPlaneMatrix,_r=Ge.labelToScreenMatrix,Nr=Ge.textPixelRatio,pr=Ge.holdingForFade,yt=Ge.collisionBoxArray,Et=Ge.partiallyEvaluatedTextSize,Bt=Ge.collisionGroup,ir=$e.get("text-optional"),hr=$e.get("icon-optional"),sr=$e.get("text-allow-overlap"),dr=$e.get("icon-allow-overlap"),lr=$e.get("text-rotation-alignment")==="map",Wt=$e.get("text-pitch-alignment")==="map",or=$e.get("icon-text-fit")!=="none",Vt=$e.get("symbol-z-order")==="viewport-y",Fr=sr&&(dr||!Le.hasIconData()||hr),Jr=dr&&(sr||!Le.hasTextData()||ir);!Le.collisionArrays&&yt&&Le.deserializeCollisionBoxes(yt);var ya=function(ci,bi){if(!ye[ci.crossTileID]){if(pr){me.placements[ci.crossTileID]=new po(!1,!1,!1);return}var Si=!1,Ui=!1,fn=!0,_o=null,Uo={box:null,offscreen:null},Cs={box:null,offscreen:null},Oo=null,Ss=null,Xs=null,du=0,Ep=0,kp=0;bi.textFeatureIndex?du=bi.textFeatureIndex:ci.useRuntimeCollisionCircles&&(du=ci.featureIndex),bi.verticalTextFeatureIndex&&(Ep=bi.verticalTextFeatureIndex);var Ph=bi.textBox;if(Ph){var qp=function(fc){var cu=e.WritingMode.horizontal;if(Le.allowVerticalPlacement&&!fc&&me.prevPlacement){var Dh=me.prevPlacement.placedOrientations[ci.crossTileID];Dh&&(me.placedOrientations[ci.crossTileID]=Dh,cu=Dh,me.markUsedOrientation(Le,cu,ci))}return cu},qd=function(fc,cu){if(Le.allowVerticalPlacement&&ci.numVerticalGlyphVertices>0&&bi.verticalTextBox)for(var Dh=0,Iv=Le.writingModes;Dh0&&(Kh=Kh.filter(function(fc){return fc!==Rh.anchor}),Kh.unshift(Rh.anchor))}var Cp=function(fc,cu,Dh){for(var Iv=fc.x2-fc.x1,sm=fc.y2-fc.y1,Su=ci.textBoxScale,b0=or&&!dr?cu:null,sv={box:[],offscreen:!1},xg=sr?Kh.length*2:Kh.length,Pp=0;Pp=Kh.length,w0=me.attemptAnchorPlacement(lv,fc,Iv,sm,Su,lr,Wt,Nr,mt,Bt,bg,ci,Le,Dh,b0);if(w0&&(sv=w0.placedGlyphBoxes,sv&&sv.box&&sv.box.length)){Si=!0,_o=w0.shift;break}}return sv},Vp=function(){return Cp(Ph,bi.iconBox,e.WritingMode.horizontal)},Lp=function(){var fc=bi.verticalTextBox,cu=Uo&&Uo.box&&Uo.box.length;return Le.allowVerticalPlacement&&!cu&&ci.numVerticalGlyphVertices>0&&fc?Cp(fc,bi.verticalIconBox,e.WritingMode.vertical):{box:null,offscreen:null}};qd(Vp,Lp),Uo&&(Si=Uo.box,fn=Uo.offscreen);var Cv=qp(Uo&&Uo.box);if(!Si&&me.prevPlacement){var Vd=me.prevPlacement.variableOffsets[ci.crossTileID];Vd&&(me.variableOffsets[ci.crossTileID]=Vd,me.markUsedJustification(Le,Vd.anchor,ci,Cv))}}else{var ed=function(fc,cu){var Dh=me.collisionIndex.placeCollisionBox(fc,sr,Nr,mt,Bt.predicate);return Dh&&Dh.box&&Dh.box.length&&(me.markUsedOrientation(Le,cu,ci),me.placedOrientations[ci.crossTileID]=cu),Dh},Ih=function(){return ed(Ph,e.WritingMode.horizontal)},td=function(){var fc=bi.verticalTextBox;return Le.allowVerticalPlacement&&ci.numVerticalGlyphVertices>0&&fc?ed(fc,e.WritingMode.vertical):{box:null,offscreen:null}};qd(Ih,td),qp(Uo&&Uo.box&&Uo.box.length)}}if(Oo=Uo,Si=Oo&&Oo.box&&Oo.box.length>0,fn=Oo&&Oo.offscreen,ci.useRuntimeCollisionCircles){var Gf=Le.text.placedSymbolArray.get(ci.centerJustifiedTextSymbolIndex),Gd=e.evaluateSizeForFeature(Le.textSizeData,Et,Gf),Lv=$e.get("text-padding"),fh=ci.collisionCircleDiameter;Ss=me.collisionIndex.placeCollisionCircles(sr,Gf,Le.lineVertexArray,Le.glyphOffsetArray,Gd,mt,jt,_r,te,Wt,Bt.predicate,fh,Lv),Si=sr||Ss.circles.length>0&&!Ss.collisionDetected,fn=fn&&Ss.offscreen}if(bi.iconFeatureIndex&&(kp=bi.iconFeatureIndex),bi.iconBox){var iv=function(fc){var cu=or&&_o?js(fc,_o.x,_o.y,lr,Wt,me.transform.angle):fc;return me.collisionIndex.placeCollisionBox(cu,dr,Nr,mt,Bt.predicate)};Cs&&Cs.box&&Cs.box.length&&bi.verticalIconBox?(Xs=iv(bi.verticalIconBox),Ui=Xs.box.length>0):(Xs=iv(bi.iconBox),Ui=Xs.box.length>0),fn=fn&&Xs.offscreen}var nm=ir||ci.numHorizontalGlyphVertices===0&&ci.numVerticalGlyphVertices===0,om=hr||ci.numIconVertices===0;if(!nm&&!om?Ui=Si=Ui&&Si:om?nm||(Ui=Ui&&Si):Si=Ui&&Si,Si&&Oo&&Oo.box&&(Cs&&Cs.box&&Ep?me.collisionIndex.insertCollisionBox(Oo.box,$e.get("text-ignore-placement"),Le.bucketInstanceId,Ep,Bt.ID):me.collisionIndex.insertCollisionBox(Oo.box,$e.get("text-ignore-placement"),Le.bucketInstanceId,du,Bt.ID)),Ui&&Xs&&me.collisionIndex.insertCollisionBox(Xs.box,$e.get("icon-ignore-placement"),Le.bucketInstanceId,kp,Bt.ID),Ss&&(Si&&me.collisionIndex.insertCollisionCircles(Ss.circles,$e.get("text-ignore-placement"),Le.bucketInstanceId,du,Bt.ID),te)){var Pv=Le.bucketInstanceId,nv=me.collisionCircleArrays[Pv];nv===void 0&&(nv=me.collisionCircleArrays[Pv]=new Un);for(var ov=0;ov=0;--Ha){var ii=gi[Ha];ya(Le.symbolInstances.get(ii),Le.collisionArrays[ii])}else for(var Xi=Y.symbolInstanceStart;Xi=0&&(Le>=0&&_r!==Le?Y.text.placedSymbolArray.get(_r).crossTileID=0:Y.text.placedSymbolArray.get(_r).crossTileID=te.crossTileID)}},Xo.prototype.markUsedOrientation=function(Y,ye,te){for(var me=ye===e.WritingMode.horizontal||ye===e.WritingMode.horizontalOnly?ye:0,Ge=ye===e.WritingMode.vertical?ye:0,Le=[te.leftJustifiedTextSymbolIndex,te.centerJustifiedTextSymbolIndex,te.rightJustifiedTextSymbolIndex],$e=0,mt=Le;$e0||Wt>0,ya=dr.numIconVertices>0,gi=me.placedOrientations[dr.crossTileID],Ha=gi===e.WritingMode.vertical,ii=gi===e.WritingMode.horizontal||gi===e.WritingMode.horizontalOnly;if(Jr){var Xi=El(Fr.text),Fi=Ha?xn:Xi;Et(Y.text,lr,Fi);var ci=ii?xn:Xi;Et(Y.text,Wt,ci);var bi=Fr.text.isHidden();[dr.rightJustifiedTextSymbolIndex,dr.centerJustifiedTextSymbolIndex,dr.leftJustifiedTextSymbolIndex].forEach(function(kp){kp>=0&&(Y.text.placedSymbolArray.get(kp).hidden=bi||Ha?1:0)}),dr.verticalPlacedTextSymbolIndex>=0&&(Y.text.placedSymbolArray.get(dr.verticalPlacedTextSymbolIndex).hidden=bi||ii?1:0);var Si=me.variableOffsets[dr.crossTileID];Si&&me.markUsedJustification(Y,Si.anchor,dr,gi);var Ui=me.placedOrientations[dr.crossTileID];Ui&&(me.markUsedJustification(Y,"left",dr,Ui),me.markUsedOrientation(Y,Ui,dr))}if(ya){var fn=El(Fr.icon),_o=!(pr&&dr.verticalPlacedIconSymbolIndex&&Ha);if(dr.placedIconSymbolIndex>=0){var Uo=_o?fn:xn;Et(Y.icon,dr.numIconVertices,Uo),Y.icon.placedSymbolArray.get(dr.placedIconSymbolIndex).hidden=Fr.icon.isHidden()}if(dr.verticalPlacedIconSymbolIndex>=0){var Cs=_o?xn:fn;Et(Y.icon,dr.numVerticalIconVertices,Cs),Y.icon.placedSymbolArray.get(dr.verticalPlacedIconSymbolIndex).hidden=Fr.icon.isHidden()}}if(Y.hasIconCollisionBoxData()||Y.hasTextCollisionBoxData()){var Oo=Y.collisionArrays[sr];if(Oo){var Ss=new e.Point(0,0);if(Oo.textBox||Oo.verticalTextBox){var Xs=!0;if(jt){var du=me.variableOffsets[or];du?(Ss=Bs(du.anchor,du.width,du.height,du.textOffset,du.textBoxScale),_r&&Ss._rotate(Nr?me.transform.angle:-me.transform.angle)):Xs=!1}Oo.textBox&&Zi(Y.textCollisionBox.collisionVertexArray,Fr.text.placed,!Xs||Ha,Ss.x,Ss.y),Oo.verticalTextBox&&Zi(Y.textCollisionBox.collisionVertexArray,Fr.text.placed,!Xs||ii,Ss.x,Ss.y)}var Ep=!!(!ii&&Oo.verticalIconBox);Oo.iconBox&&Zi(Y.iconCollisionBox.collisionVertexArray,Fr.icon.placed,Ep,pr?Ss.x:0,pr?Ss.y:0),Oo.verticalIconBox&&Zi(Y.iconCollisionBox.collisionVertexArray,Fr.icon.placed,!Ep,pr?Ss.x:0,pr?Ss.y:0)}}},ir=0;irY},Xo.prototype.setStale=function(){this.stale=!0};function Zi(ve,Y,ye,te,me){ve.emplaceBack(Y?1:0,ye?1:0,te||0,me||0),ve.emplaceBack(Y?1:0,ye?1:0,te||0,me||0),ve.emplaceBack(Y?1:0,ye?1:0,te||0,me||0),ve.emplaceBack(Y?1:0,ye?1:0,te||0,me||0)}var Mn=Math.pow(2,25),Ns=Math.pow(2,24),Jo=Math.pow(2,17),so=Math.pow(2,16),Us=Math.pow(2,9),Ts=Math.pow(2,8),Is=Math.pow(2,1);function El(ve){if(ve.opacity===0&&!ve.placed)return 0;if(ve.opacity===1&&ve.placed)return 4294967295;var Y=ve.placed?1:0,ye=Math.floor(ve.opacity*127);return ye*Mn+Y*Ns+ye*Jo+Y*so+ye*Us+Y*Ts+ye*Is+Y}var xn=0,bo=function(Y){this._sortAcrossTiles=Y.layout.get("symbol-z-order")!=="viewport-y"&&Y.layout.get("symbol-sort-key").constantOr(1)!==void 0,this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]};bo.prototype.continuePlacement=function(Y,ye,te,me,Ge){for(var Le=this._bucketParts;this._currentTileIndex2};this._currentPlacementIndex>=0;){var $e=Y[this._currentPlacementIndex],mt=ye[$e],jt=this.placement.collisionIndex.transform.zoom;if(mt.type==="symbol"&&(!mt.minzoom||mt.minzoom<=jt)&&(!mt.maxzoom||mt.maxzoom>jt)){this._inProgressLayer||(this._inProgressLayer=new bo(mt));var _r=this._inProgressLayer.continuePlacement(te[mt.source],this.placement,this._showCollisionBoxes,mt,Le);if(_r)return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0},wo.prototype.commit=function(Y){return this.placement.commit(Y),this.placement};var fl=512/e.EXTENT/2,Js=function(Y,ye,te){this.tileID=Y,this.indexedSymbolInstances={},this.bucketInstanceId=te;for(var me=0;meY.overscaledZ)for(var jt in mt){var _r=mt[jt];_r.tileID.isChildOf(Y)&&_r.findMatches(ye.symbolInstances,Y,Le)}else{var Nr=Y.scaledTo(Number($e)),pr=mt[Nr.key];pr&&pr.findMatches(ye.symbolInstances,Y,Le)}}for(var yt=0;yt0)throw new Error("Unimplemented: "+Le.map(function($e){return $e.command}).join(", ")+".");return Ge.forEach(function($e){$e.command!=="setTransition"&&me[$e.command].apply(me,$e.args)}),this.stylesheet=te,!0},Y.prototype.addImage=function(te,me){if(this.getImage(te))return this.fire(new e.ErrorEvent(new Error("An image with this name already exists.")));this.imageManager.addImage(te,me),this._afterImageUpdated(te)},Y.prototype.updateImage=function(te,me){this.imageManager.updateImage(te,me)},Y.prototype.getImage=function(te){return this.imageManager.getImage(te)},Y.prototype.removeImage=function(te){if(!this.getImage(te))return this.fire(new e.ErrorEvent(new Error("No image with this name exists.")));this.imageManager.removeImage(te),this._afterImageUpdated(te)},Y.prototype._afterImageUpdated=function(te){this._availableImages=this.imageManager.listImages(),this._changedImages[te]=!0,this._changed=!0,this.dispatcher.broadcast("setImages",this._availableImages),this.fire(new e.Event("data",{dataType:"style"}))},Y.prototype.listImages=function(){return this._checkLoaded(),this.imageManager.listImages()},Y.prototype.addSource=function(te,me,Ge){var Le=this;if(Ge===void 0&&(Ge={}),this._checkLoaded(),this.sourceCaches[te]!==void 0)throw new Error("There is already a source with this ID");if(!me.type)throw new Error("The type property must be defined, but only the following properties were given: "+Object.keys(me).join(", ")+".");var $e=["vector","raster","geojson","video","image"],mt=$e.indexOf(me.type)>=0;if(!(mt&&this._validate(e.validateStyle.source,"sources."+te,me,null,Ge))){this.map&&this.map._collectResourceTiming&&(me.collectResourceTiming=!0);var jt=this.sourceCaches[te]=new aa(te,me,this.dispatcher);jt.style=this,jt.setEventedParent(this,function(){return{isSourceLoaded:Le.loaded(),source:jt.serialize(),sourceId:te}}),jt.onAdd(this.map),this._changed=!0}},Y.prototype.removeSource=function(te){if(this._checkLoaded(),this.sourceCaches[te]===void 0)throw new Error("There is no source with this ID");for(var me in this._layers)if(this._layers[me].source===te)return this.fire(new e.ErrorEvent(new Error('Source "'+te+'" cannot be removed while layer "'+me+'" is using it.')));var Ge=this.sourceCaches[te];delete this.sourceCaches[te],delete this._updatedSources[te],Ge.fire(new e.Event("data",{sourceDataType:"metadata",dataType:"source",sourceId:te})),Ge.setEventedParent(null),Ge.clearTiles(),Ge.onRemove&&Ge.onRemove(this.map),this._changed=!0},Y.prototype.setGeoJSONSourceData=function(te,me){this._checkLoaded();var Ge=this.sourceCaches[te].getSource();Ge.setData(me),this._changed=!0},Y.prototype.getSource=function(te){return this.sourceCaches[te]&&this.sourceCaches[te].getSource()},Y.prototype.addLayer=function(te,me,Ge){Ge===void 0&&(Ge={}),this._checkLoaded();var Le=te.id;if(this.getLayer(Le)){this.fire(new e.ErrorEvent(new Error('Layer with id "'+Le+'" already exists on this map')));return}var $e;if(te.type==="custom"){if(os(this,e.validateCustomStyleLayer(te)))return;$e=e.createStyleLayer(te)}else{if(typeof te.source=="object"&&(this.addSource(Le,te.source),te=e.clone$1(te),te=e.extend(te,{source:Le})),this._validate(e.validateStyle.layer,"layers."+Le,te,{arrayIndex:-1},Ge))return;$e=e.createStyleLayer(te),this._validateLayer($e),$e.setEventedParent(this,{layer:{id:Le}}),this._serializedLayers[$e.id]=$e.serialize()}var mt=me?this._order.indexOf(me):this._order.length;if(me&&mt===-1){this.fire(new e.ErrorEvent(new Error('Layer with id "'+me+'" does not exist on this map.')));return}if(this._order.splice(mt,0,Le),this._layerOrderChanged=!0,this._layers[Le]=$e,this._removedLayers[Le]&&$e.source&&$e.type!=="custom"){var jt=this._removedLayers[Le];delete this._removedLayers[Le],jt.type!==$e.type?this._updatedSources[$e.source]="clear":(this._updatedSources[$e.source]="reload",this.sourceCaches[$e.source].pause())}this._updateLayer($e),$e.onAdd&&$e.onAdd(this.map)},Y.prototype.moveLayer=function(te,me){this._checkLoaded(),this._changed=!0;var Ge=this._layers[te];if(!Ge){this.fire(new e.ErrorEvent(new Error("The layer '"+te+"' does not exist in the map's style and cannot be moved.")));return}if(te!==me){var Le=this._order.indexOf(te);this._order.splice(Le,1);var $e=me?this._order.indexOf(me):this._order.length;if(me&&$e===-1){this.fire(new e.ErrorEvent(new Error('Layer with id "'+me+'" does not exist on this map.')));return}this._order.splice($e,0,te),this._layerOrderChanged=!0}},Y.prototype.removeLayer=function(te){this._checkLoaded();var me=this._layers[te];if(!me){this.fire(new e.ErrorEvent(new Error("The layer '"+te+"' does not exist in the map's style and cannot be removed.")));return}me.setEventedParent(null);var Ge=this._order.indexOf(te);this._order.splice(Ge,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[te]=me,delete this._layers[te],delete this._serializedLayers[te],delete this._updatedLayers[te],delete this._updatedPaintProps[te],me.onRemove&&me.onRemove(this.map)},Y.prototype.getLayer=function(te){return this._layers[te]},Y.prototype.hasLayer=function(te){return te in this._layers},Y.prototype.setLayerZoomRange=function(te,me,Ge){this._checkLoaded();var Le=this.getLayer(te);if(!Le){this.fire(new e.ErrorEvent(new Error("The layer '"+te+"' does not exist in the map's style and cannot have zoom extent.")));return}Le.minzoom===me&&Le.maxzoom===Ge||(me!=null&&(Le.minzoom=me),Ge!=null&&(Le.maxzoom=Ge),this._updateLayer(Le))},Y.prototype.setFilter=function(te,me,Ge){Ge===void 0&&(Ge={}),this._checkLoaded();var Le=this.getLayer(te);if(!Le){this.fire(new e.ErrorEvent(new Error("The layer '"+te+"' does not exist in the map's style and cannot be filtered.")));return}if(!e.deepEqual(Le.filter,me)){if(me==null){Le.filter=void 0,this._updateLayer(Le);return}this._validate(e.validateStyle.filter,"layers."+Le.id+".filter",me,null,Ge)||(Le.filter=e.clone$1(me),this._updateLayer(Le))}},Y.prototype.getFilter=function(te){return e.clone$1(this.getLayer(te).filter)},Y.prototype.setLayoutProperty=function(te,me,Ge,Le){Le===void 0&&(Le={}),this._checkLoaded();var $e=this.getLayer(te);if(!$e){this.fire(new e.ErrorEvent(new Error("The layer '"+te+"' does not exist in the map's style and cannot be styled.")));return}e.deepEqual($e.getLayoutProperty(me),Ge)||($e.setLayoutProperty(me,Ge,Le),this._updateLayer($e))},Y.prototype.getLayoutProperty=function(te,me){var Ge=this.getLayer(te);if(!Ge){this.fire(new e.ErrorEvent(new Error("The layer '"+te+"' does not exist in the map's style.")));return}return Ge.getLayoutProperty(me)},Y.prototype.setPaintProperty=function(te,me,Ge,Le){Le===void 0&&(Le={}),this._checkLoaded();var $e=this.getLayer(te);if(!$e){this.fire(new e.ErrorEvent(new Error("The layer '"+te+"' does not exist in the map's style and cannot be styled.")));return}if(!e.deepEqual($e.getPaintProperty(me),Ge)){var mt=$e.setPaintProperty(me,Ge,Le);mt&&this._updateLayer($e),this._changed=!0,this._updatedPaintProps[te]=!0}},Y.prototype.getPaintProperty=function(te,me){return this.getLayer(te).getPaintProperty(me)},Y.prototype.setFeatureState=function(te,me){this._checkLoaded();var Ge=te.source,Le=te.sourceLayer,$e=this.sourceCaches[Ge];if($e===void 0){this.fire(new e.ErrorEvent(new Error("The source '"+Ge+"' does not exist in the map's style.")));return}var mt=$e.getSource().type;if(mt==="geojson"&&Le){this.fire(new e.ErrorEvent(new Error("GeoJSON sources cannot have a sourceLayer parameter.")));return}if(mt==="vector"&&!Le){this.fire(new e.ErrorEvent(new Error("The sourceLayer parameter must be provided for vector source types.")));return}te.id===void 0&&this.fire(new e.ErrorEvent(new Error("The feature id parameter must be provided."))),$e.setFeatureState(Le,te.id,me)},Y.prototype.removeFeatureState=function(te,me){this._checkLoaded();var Ge=te.source,Le=this.sourceCaches[Ge];if(Le===void 0){this.fire(new e.ErrorEvent(new Error("The source '"+Ge+"' does not exist in the map's style.")));return}var $e=Le.getSource().type,mt=$e==="vector"?te.sourceLayer:void 0;if($e==="vector"&&!mt){this.fire(new e.ErrorEvent(new Error("The sourceLayer parameter must be provided for vector source types.")));return}if(me&&typeof te.id!="string"&&typeof te.id!="number"){this.fire(new e.ErrorEvent(new Error("A feature id is required to remove its specific state property.")));return}Le.removeFeatureState(mt,te.id,me)},Y.prototype.getFeatureState=function(te){this._checkLoaded();var me=te.source,Ge=te.sourceLayer,Le=this.sourceCaches[me];if(Le===void 0){this.fire(new e.ErrorEvent(new Error("The source '"+me+"' does not exist in the map's style.")));return}var $e=Le.getSource().type;if($e==="vector"&&!Ge){this.fire(new e.ErrorEvent(new Error("The sourceLayer parameter must be provided for vector source types.")));return}return te.id===void 0&&this.fire(new e.ErrorEvent(new Error("The feature id parameter must be provided."))),Le.getFeatureState(Ge,te.id)},Y.prototype.getTransition=function(){return e.extend({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)},Y.prototype.serialize=function(){return e.filterObject({version:this.stylesheet.version,name:this.stylesheet.name,metadata:this.stylesheet.metadata,light:this.stylesheet.light,center:this.stylesheet.center,zoom:this.stylesheet.zoom,bearing:this.stylesheet.bearing,pitch:this.stylesheet.pitch,sprite:this.stylesheet.sprite,glyphs:this.stylesheet.glyphs,transition:this.stylesheet.transition,sources:e.mapObject(this.sourceCaches,function(te){return te.serialize()}),layers:this._serializeLayers(this._order)},function(te){return te!==void 0})},Y.prototype._updateLayer=function(te){this._updatedLayers[te.id]=!0,te.source&&!this._updatedSources[te.source]&&this.sourceCaches[te.source].getSource().type!=="raster"&&(this._updatedSources[te.source]="reload",this.sourceCaches[te.source].pause()),this._changed=!0},Y.prototype._flattenAndSortRenderedFeatures=function(te){for(var me=this,Ge=function(ii){return me._layers[ii].type==="fill-extrusion"},Le={},$e=[],mt=this._order.length-1;mt>=0;mt--){var jt=this._order[mt];if(Ge(jt)){Le[jt]=mt;for(var _r=0,Nr=te;_r=0;sr--){var dr=this._order[sr];if(Ge(dr))for(var lr=$e.length-1;lr>=0;lr--){var Wt=$e[lr].feature;if(Le[Wt.layer.id] 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}`,Ql=`uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting; +#pragma mapbox: define lowp float base +#pragma mapbox: define lowp float height +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float base +#pragma mapbox: initialize lowp float height +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,Jf=`uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting; +#pragma mapbox: define lowp float base +#pragma mapbox: define lowp float height +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float base +#pragma mapbox: initialize lowp float height +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;base=max(0.0,base);height=max(0.0,height);float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0 +? a_pos +: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}`,Of=`#ifdef GL_ES +precision highp float; +#endif +uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggerationFactor=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;float exaggeration=u_zoom < 15.0 ? (u_zoom-15.0)*exaggerationFactor : 0.0;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/pow(2.0,exaggeration+(19.2562-u_zoom));gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,nf="uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}",jc=`uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent; +#define PI 3.141592653589793 +void main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,Bf="uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}",Nf=`uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,Gu=` +#define scale 0.015873016 +attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float width +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float width +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}`,Ef=`uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp vec2 v_uv; +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,v_uv);gl_FragColor=color*(alpha*opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,sc=` +#define scale 0.015873016 +attribute vec2 a_pos_normal;attribute vec4 a_data;attribute float a_uv_x;attribute float a_split_index;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;uniform float u_image_height;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp vec2 v_uv; +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float width +void main() { +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float width +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;highp float texel_height=1.0/u_image_height;highp float half_texel_height=0.5*texel_height;v_uv=vec2(a_uv_x,a_split_index*texel_height-half_texel_height);vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_width2=vec2(outset,inset);}`,Wc=`uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width; +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,eu=` +#define scale 0.015873016 +#define LINE_DISTANCE_SCALE 2.0 +attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width; +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define mediump float width +#pragma mapbox: define lowp float floorwidth +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize mediump float width +#pragma mapbox: initialize lowp float floorwidth +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}`,qc=`uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float width +#pragma mapbox: define lowp float floorwidth +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float width +#pragma mapbox: initialize lowp float floorwidth +float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,Sc=` +#define scale 0.015873016 +#define LINE_DISTANCE_SCALE 2.0 +attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float width +#pragma mapbox: define lowp float floorwidth +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float width +#pragma mapbox: initialize lowp float floorwidth +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude;float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective;v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}`,Ws=`uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,kf="uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}",uh=`uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity; +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize lowp float opacity +lowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,Uf=`const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;varying vec2 v_tex;varying float v_fade_opacity; +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize lowp float opacity +vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ? +camera_to_anchor_distance/u_camera_to_center_distance : +u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0),0.0,1.0);v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;v_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));}`,Xc=`#define SDF_PX 8.0 +uniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1; +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +float EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,$f=`const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;varying vec2 v_data0;varying vec3 v_data1; +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ? +camera_to_anchor_distance/u_camera_to_center_distance : +u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}`,Cu=`#define SDF_PX 8.0 +#define SDF 1.0 +#define ICON 0.0 +uniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1; +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +float fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +return;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,jf=`const float PI=3.141592653589793;attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;varying vec4 v_data0;varying vec4 v_data1; +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec4 projectedPoint=u_matrix*vec4(a_pos,0,1);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ? +camera_to_anchor_distance/u_camera_to_center_distance : +u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=u_matrix*vec4(a_pos+vec2(1,0),0,1);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy,0.0,1.0);gl_Position=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale),0.0,1.0);float gamma_scale=gl_Position.w;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(1.0,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}`,ml=hl(ic,ku),Lu=hl(Af,Uc),Mc=hl(Ds,vc),il=hl(Sf,su),mc=hl(Il,nc),mu=hl(Ou,al),wu=hl(vl,xs),kl=hl(Hs,oc),qf=hl(jl,qu),Qf=hl(cl,_h),Bu=hl(ls,xh),Ec=hl(Ms,eo),gc=hl(Hc,Vu),Lh=hl(ql,Mf),of=hl(Ac,af),df=hl(Ql,Jf),Nu=hl(Of,nf),sf=hl(jc,Bf),iu=hl(Nf,Gu),Zc=hl(Ef,sc),ch=hl(Wc,eu),vf=hl(qc,Sc),nl=hl(Ws,kf),gu=hl(uh,Uf),Pu=hl(Xc,$f),Cf=hl(Cu,jf);function hl(ve,Y){var ye=/#pragma mapbox: ([\w]+) ([\w]+) ([\w]+) ([\w]+)/g,te=Y.match(/attribute ([\w]+) ([\w]+)/g),me=ve.match(/uniform ([\w]+) ([\w]+)([\s]*)([\w]*)/g),Ge=Y.match(/uniform ([\w]+) ([\w]+)([\s]*)([\w]*)/g),Le=Ge?Ge.concat(me):me,$e={};return ve=ve.replace(ye,function(mt,jt,_r,Nr,pr){return $e[pr]=!0,jt==="define"?` +#ifndef HAS_UNIFORM_u_`+pr+` +varying `+_r+" "+Nr+" "+pr+`; +#else +uniform `+_r+" "+Nr+" u_"+pr+`; +#endif +`:` +#ifdef HAS_UNIFORM_u_`+pr+` + `+_r+" "+Nr+" "+pr+" = u_"+pr+`; +#endif +`}),Y=Y.replace(ye,function(mt,jt,_r,Nr,pr){var yt=Nr==="float"?"vec2":"vec4",Et=pr.match(/color/)?"color":yt;return $e[pr]?jt==="define"?` +#ifndef HAS_UNIFORM_u_`+pr+` +uniform lowp float u_`+pr+`_t; +attribute `+_r+" "+yt+" a_"+pr+`; +varying `+_r+" "+Nr+" "+pr+`; +#else +uniform `+_r+" "+Nr+" u_"+pr+`; +#endif +`:Et==="vec4"?` +#ifndef HAS_UNIFORM_u_`+pr+` + `+pr+" = a_"+pr+`; +#else + `+_r+" "+Nr+" "+pr+" = u_"+pr+`; +#endif +`:` +#ifndef HAS_UNIFORM_u_`+pr+` + `+pr+" = unpack_mix_"+Et+"(a_"+pr+", u_"+pr+`_t); +#else + `+_r+" "+Nr+" "+pr+" = u_"+pr+`; +#endif +`:jt==="define"?` +#ifndef HAS_UNIFORM_u_`+pr+` +uniform lowp float u_`+pr+`_t; +attribute `+_r+" "+yt+" a_"+pr+`; +#else +uniform `+_r+" "+Nr+" u_"+pr+`; +#endif +`:Et==="vec4"?` +#ifndef HAS_UNIFORM_u_`+pr+` + `+_r+" "+Nr+" "+pr+" = a_"+pr+`; +#else + `+_r+" "+Nr+" "+pr+" = u_"+pr+`; +#endif +`:` +#ifndef HAS_UNIFORM_u_`+pr+` + `+_r+" "+Nr+" "+pr+" = unpack_mix_"+Et+"(a_"+pr+", u_"+pr+`_t); +#else + `+_r+" "+Nr+" "+pr+" = u_"+pr+`; +#endif +`}),{fragmentSource:ve,vertexSource:Y,staticAttributes:te,staticUniforms:Le}}var lf=Object.freeze({__proto__:null,prelude:ml,background:Lu,backgroundPattern:Mc,circle:il,clippingMask:mc,heatmap:mu,heatmapTexture:wu,collisionBox:kl,collisionCircle:qf,debug:Qf,fill:Bu,fillOutline:Ec,fillOutlinePattern:gc,fillPattern:Lh,fillExtrusion:of,fillExtrusionPattern:df,hillshadePrepare:Nu,hillshade:sf,line:iu,lineGradient:Zc,linePattern:ch,lineSDF:vf,raster:nl,symbolIcon:gu,symbolSDF:Pu,symbolTextAndIcon:Cf}),kc=function(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null};kc.prototype.bind=function(Y,ye,te,me,Ge,Le,$e,mt){this.context=Y;for(var jt=this.boundPaintVertexBuffers.length!==me.length,_r=0;!jt&&_r>16,$e>>16],u_pixel_coord_lower:[Le&65535,$e&65535]}}function Yc(ve,Y,ye,te){var me=ye.imageManager.getPattern(ve.from.toString()),Ge=ye.imageManager.getPattern(ve.to.toString()),Le=ye.imageManager.getPixelSize(),$e=Le.width,mt=Le.height,jt=Math.pow(2,te.tileID.overscaledZ),_r=te.tileSize*Math.pow(2,ye.transform.tileZoom)/jt,Nr=_r*(te.tileID.canonical.x+te.tileID.wrap*jt),pr=_r*te.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:me.tl,u_pattern_br_a:me.br,u_pattern_tl_b:Ge.tl,u_pattern_br_b:Ge.br,u_texsize:[$e,mt],u_mix:Y.t,u_pattern_size_a:me.displaySize,u_pattern_size_b:Ge.displaySize,u_scale_a:Y.fromScale,u_scale_b:Y.toScale,u_tile_units_to_pixels:1/us(te,1,ye.transform.tileZoom),u_pixel_coord_upper:[Nr>>16,pr>>16],u_pixel_coord_lower:[Nr&65535,pr&65535]}}var Lf=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_lightpos:new e.Uniform3f(ve,Y.u_lightpos),u_lightintensity:new e.Uniform1f(ve,Y.u_lightintensity),u_lightcolor:new e.Uniform3f(ve,Y.u_lightcolor),u_vertical_gradient:new e.Uniform1f(ve,Y.u_vertical_gradient),u_opacity:new e.Uniform1f(ve,Y.u_opacity)}},nu=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_lightpos:new e.Uniform3f(ve,Y.u_lightpos),u_lightintensity:new e.Uniform1f(ve,Y.u_lightintensity),u_lightcolor:new e.Uniform3f(ve,Y.u_lightcolor),u_vertical_gradient:new e.Uniform1f(ve,Y.u_vertical_gradient),u_height_factor:new e.Uniform1f(ve,Y.u_height_factor),u_image:new e.Uniform1i(ve,Y.u_image),u_texsize:new e.Uniform2f(ve,Y.u_texsize),u_pixel_coord_upper:new e.Uniform2f(ve,Y.u_pixel_coord_upper),u_pixel_coord_lower:new e.Uniform2f(ve,Y.u_pixel_coord_lower),u_scale:new e.Uniform3f(ve,Y.u_scale),u_fade:new e.Uniform1f(ve,Y.u_fade),u_opacity:new e.Uniform1f(ve,Y.u_opacity)}},Vf=function(ve,Y,ye,te){var me=Y.style.light,Ge=me.properties.get("position"),Le=[Ge.x,Ge.y,Ge.z],$e=e.create$1();me.properties.get("anchor")==="viewport"&&e.fromRotation($e,-Y.transform.angle),e.transformMat3(Le,Le,$e);var mt=me.properties.get("color");return{u_matrix:ve,u_lightpos:Le,u_lightintensity:me.properties.get("intensity"),u_lightcolor:[mt.r,mt.g,mt.b],u_vertical_gradient:+ye,u_opacity:te}},Xu=function(ve,Y,ye,te,me,Ge,Le){return e.extend(Vf(ve,Y,ye,te),Wu(Ge,Y,Le),{u_height_factor:-Math.pow(2,me.overscaledZ)/Le.tileSize/8})},Cc=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix)}},yc=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_image:new e.Uniform1i(ve,Y.u_image),u_texsize:new e.Uniform2f(ve,Y.u_texsize),u_pixel_coord_upper:new e.Uniform2f(ve,Y.u_pixel_coord_upper),u_pixel_coord_lower:new e.Uniform2f(ve,Y.u_pixel_coord_lower),u_scale:new e.Uniform3f(ve,Y.u_scale),u_fade:new e.Uniform1f(ve,Y.u_fade)}},Vl=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_world:new e.Uniform2f(ve,Y.u_world)}},yu=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_world:new e.Uniform2f(ve,Y.u_world),u_image:new e.Uniform1i(ve,Y.u_image),u_texsize:new e.Uniform2f(ve,Y.u_texsize),u_pixel_coord_upper:new e.Uniform2f(ve,Y.u_pixel_coord_upper),u_pixel_coord_lower:new e.Uniform2f(ve,Y.u_pixel_coord_lower),u_scale:new e.Uniform3f(ve,Y.u_scale),u_fade:new e.Uniform1f(ve,Y.u_fade)}},Lc=function(ve){return{u_matrix:ve}},Kc=function(ve,Y,ye,te){return e.extend(Lc(ve),Wu(ye,Y,te))},lc=function(ve,Y){return{u_matrix:ve,u_world:Y}},Pc=function(ve,Y,ye,te,me){return e.extend(Kc(ve,Y,ye,te),{u_world:me})},Qt=function(ve,Y){return{u_camera_to_center_distance:new e.Uniform1f(ve,Y.u_camera_to_center_distance),u_scale_with_map:new e.Uniform1i(ve,Y.u_scale_with_map),u_pitch_with_map:new e.Uniform1i(ve,Y.u_pitch_with_map),u_extrude_scale:new e.Uniform2f(ve,Y.u_extrude_scale),u_device_pixel_ratio:new e.Uniform1f(ve,Y.u_device_pixel_ratio),u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix)}},yr=function(ve,Y,ye,te){var me=ve.transform,Ge,Le;if(te.paint.get("circle-pitch-alignment")==="map"){var $e=us(ye,1,me.zoom);Ge=!0,Le=[$e,$e]}else Ge=!1,Le=me.pixelsToGLUnits;return{u_camera_to_center_distance:me.cameraToCenterDistance,u_scale_with_map:+(te.paint.get("circle-pitch-scale")==="map"),u_matrix:ve.translatePosMatrix(Y.posMatrix,ye,te.paint.get("circle-translate"),te.paint.get("circle-translate-anchor")),u_pitch_with_map:+Ge,u_device_pixel_ratio:e.browser.devicePixelRatio,u_extrude_scale:Le}},na=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_camera_to_center_distance:new e.Uniform1f(ve,Y.u_camera_to_center_distance),u_pixels_to_tile_units:new e.Uniform1f(ve,Y.u_pixels_to_tile_units),u_extrude_scale:new e.Uniform2f(ve,Y.u_extrude_scale),u_overscale_factor:new e.Uniform1f(ve,Y.u_overscale_factor)}},$r=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_inv_matrix:new e.UniformMatrix4f(ve,Y.u_inv_matrix),u_camera_to_center_distance:new e.Uniform1f(ve,Y.u_camera_to_center_distance),u_viewport_size:new e.Uniform2f(ve,Y.u_viewport_size)}},ka=function(ve,Y,ye){var te=us(ye,1,Y.zoom),me=Math.pow(2,Y.zoom-ye.tileID.overscaledZ),Ge=ye.tileID.overscaleFactor();return{u_matrix:ve,u_camera_to_center_distance:Y.cameraToCenterDistance,u_pixels_to_tile_units:te,u_extrude_scale:[Y.pixelsToGLUnits[0]/(te*me),Y.pixelsToGLUnits[1]/(te*me)],u_overscale_factor:Ge}},ui=function(ve,Y,ye){return{u_matrix:ve,u_inv_matrix:Y,u_camera_to_center_distance:ye.cameraToCenterDistance,u_viewport_size:[ye.width,ye.height]}},Ci=function(ve,Y){return{u_color:new e.UniformColor(ve,Y.u_color),u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_overlay:new e.Uniform1i(ve,Y.u_overlay),u_overlay_scale:new e.Uniform1f(ve,Y.u_overlay_scale)}},Gi=function(ve,Y,ye){return ye===void 0&&(ye=1),{u_matrix:ve,u_color:Y,u_overlay:0,u_overlay_scale:ye}},Qi=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix)}},dn=function(ve){return{u_matrix:ve}},Pi=function(ve,Y){return{u_extrude_scale:new e.Uniform1f(ve,Y.u_extrude_scale),u_intensity:new e.Uniform1f(ve,Y.u_intensity),u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix)}},Di=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_world:new e.Uniform2f(ve,Y.u_world),u_image:new e.Uniform1i(ve,Y.u_image),u_color_ramp:new e.Uniform1i(ve,Y.u_color_ramp),u_opacity:new e.Uniform1f(ve,Y.u_opacity)}},Ni=function(ve,Y,ye,te){return{u_matrix:ve,u_extrude_scale:us(Y,1,ye),u_intensity:te}},yi=function(ve,Y,ye,te){var me=e.create();e.ortho(me,0,ve.width,ve.height,0,0,1);var Ge=ve.context.gl;return{u_matrix:me,u_world:[Ge.drawingBufferWidth,Ge.drawingBufferHeight],u_image:ye,u_color_ramp:te,u_opacity:Y.paint.get("heatmap-opacity")}},En=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_image:new e.Uniform1i(ve,Y.u_image),u_latrange:new e.Uniform2f(ve,Y.u_latrange),u_light:new e.Uniform2f(ve,Y.u_light),u_shadow:new e.UniformColor(ve,Y.u_shadow),u_highlight:new e.UniformColor(ve,Y.u_highlight),u_accent:new e.UniformColor(ve,Y.u_accent)}},Jn=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_image:new e.Uniform1i(ve,Y.u_image),u_dimension:new e.Uniform2f(ve,Y.u_dimension),u_zoom:new e.Uniform1f(ve,Y.u_zoom),u_unpack:new e.Uniform4f(ve,Y.u_unpack)}},ro=function(ve,Y,ye){var te=ye.paint.get("hillshade-shadow-color"),me=ye.paint.get("hillshade-highlight-color"),Ge=ye.paint.get("hillshade-accent-color"),Le=ye.paint.get("hillshade-illumination-direction")*(Math.PI/180);ye.paint.get("hillshade-illumination-anchor")==="viewport"&&(Le-=ve.transform.angle);var $e=!ve.options.moving;return{u_matrix:ve.transform.calculatePosMatrix(Y.tileID.toUnwrapped(),$e),u_image:0,u_latrange:lo(ve,Y.tileID),u_light:[ye.paint.get("hillshade-exaggeration"),Le],u_shadow:te,u_highlight:me,u_accent:Ge}},$n=function(ve,Y){var ye=Y.stride,te=e.create();return e.ortho(te,0,e.EXTENT,-e.EXTENT,0,0,1),e.translate(te,te,[0,-e.EXTENT,0]),{u_matrix:te,u_image:1,u_dimension:[ye,ye],u_zoom:ve.overscaledZ,u_unpack:Y.getUnpackVector()}};function lo(ve,Y){var ye=Math.pow(2,Y.canonical.z),te=Y.canonical.y;return[new e.MercatorCoordinate(0,te/ye).toLngLat().lat,new e.MercatorCoordinate(0,(te+1)/ye).toLngLat().lat]}var An=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_ratio:new e.Uniform1f(ve,Y.u_ratio),u_device_pixel_ratio:new e.Uniform1f(ve,Y.u_device_pixel_ratio),u_units_to_pixels:new e.Uniform2f(ve,Y.u_units_to_pixels)}},un=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_ratio:new e.Uniform1f(ve,Y.u_ratio),u_device_pixel_ratio:new e.Uniform1f(ve,Y.u_device_pixel_ratio),u_units_to_pixels:new e.Uniform2f(ve,Y.u_units_to_pixels),u_image:new e.Uniform1i(ve,Y.u_image),u_image_height:new e.Uniform1f(ve,Y.u_image_height)}},yo=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_texsize:new e.Uniform2f(ve,Y.u_texsize),u_ratio:new e.Uniform1f(ve,Y.u_ratio),u_device_pixel_ratio:new e.Uniform1f(ve,Y.u_device_pixel_ratio),u_image:new e.Uniform1i(ve,Y.u_image),u_units_to_pixels:new e.Uniform2f(ve,Y.u_units_to_pixels),u_scale:new e.Uniform3f(ve,Y.u_scale),u_fade:new e.Uniform1f(ve,Y.u_fade)}},$o=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_ratio:new e.Uniform1f(ve,Y.u_ratio),u_device_pixel_ratio:new e.Uniform1f(ve,Y.u_device_pixel_ratio),u_units_to_pixels:new e.Uniform2f(ve,Y.u_units_to_pixels),u_patternscale_a:new e.Uniform2f(ve,Y.u_patternscale_a),u_patternscale_b:new e.Uniform2f(ve,Y.u_patternscale_b),u_sdfgamma:new e.Uniform1f(ve,Y.u_sdfgamma),u_image:new e.Uniform1i(ve,Y.u_image),u_tex_y_a:new e.Uniform1f(ve,Y.u_tex_y_a),u_tex_y_b:new e.Uniform1f(ve,Y.u_tex_y_b),u_mix:new e.Uniform1f(ve,Y.u_mix)}},As=function(ve,Y,ye){var te=ve.transform;return{u_matrix:Bl(ve,Y,ye),u_ratio:1/us(Y,1,te.zoom),u_device_pixel_ratio:e.browser.devicePixelRatio,u_units_to_pixels:[1/te.pixelsToGLUnits[0],1/te.pixelsToGLUnits[1]]}},tl=function(ve,Y,ye,te){return e.extend(As(ve,Y,ye),{u_image:0,u_image_height:te})},zs=function(ve,Y,ye,te){var me=ve.transform,Ge=bs(Y,me);return{u_matrix:Bl(ve,Y,ye),u_texsize:Y.imageAtlasTexture.size,u_ratio:1/us(Y,1,me.zoom),u_device_pixel_ratio:e.browser.devicePixelRatio,u_image:0,u_scale:[Ge,te.fromScale,te.toScale],u_fade:te.t,u_units_to_pixels:[1/me.pixelsToGLUnits[0],1/me.pixelsToGLUnits[1]]}},Qs=function(ve,Y,ye,te,me){var Ge=ve.transform,Le=ve.lineAtlas,$e=bs(Y,Ge),mt=ye.layout.get("line-cap")==="round",jt=Le.getDash(te.from,mt),_r=Le.getDash(te.to,mt),Nr=jt.width*me.fromScale,pr=_r.width*me.toScale;return e.extend(As(ve,Y,ye),{u_patternscale_a:[$e/Nr,-jt.height/2],u_patternscale_b:[$e/pr,-_r.height/2],u_sdfgamma:Le.width/(Math.min(Nr,pr)*256*e.browser.devicePixelRatio)/2,u_image:0,u_tex_y_a:jt.y,u_tex_y_b:_r.y,u_mix:me.t})};function bs(ve,Y){return 1/us(ve,1,Y.tileZoom)}function Bl(ve,Y,ye){return ve.translatePosMatrix(Y.tileID.posMatrix,Y,ye.paint.get("line-translate"),ye.paint.get("line-translate-anchor"))}var yl=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_tl_parent:new e.Uniform2f(ve,Y.u_tl_parent),u_scale_parent:new e.Uniform1f(ve,Y.u_scale_parent),u_buffer_scale:new e.Uniform1f(ve,Y.u_buffer_scale),u_fade_t:new e.Uniform1f(ve,Y.u_fade_t),u_opacity:new e.Uniform1f(ve,Y.u_opacity),u_image0:new e.Uniform1i(ve,Y.u_image0),u_image1:new e.Uniform1i(ve,Y.u_image1),u_brightness_low:new e.Uniform1f(ve,Y.u_brightness_low),u_brightness_high:new e.Uniform1f(ve,Y.u_brightness_high),u_saturation_factor:new e.Uniform1f(ve,Y.u_saturation_factor),u_contrast_factor:new e.Uniform1f(ve,Y.u_contrast_factor),u_spin_weights:new e.Uniform3f(ve,Y.u_spin_weights)}},ol=function(ve,Y,ye,te,me){return{u_matrix:ve,u_tl_parent:Y,u_scale_parent:ye,u_buffer_scale:1,u_fade_t:te.mix,u_opacity:te.opacity*me.paint.get("raster-opacity"),u_image0:0,u_image1:1,u_brightness_low:me.paint.get("raster-brightness-min"),u_brightness_high:me.paint.get("raster-brightness-max"),u_saturation_factor:Zs(me.paint.get("raster-saturation")),u_contrast_factor:Ro(me.paint.get("raster-contrast")),u_spin_weights:Nn(me.paint.get("raster-hue-rotate"))}};function Nn(ve){ve*=Math.PI/180;var Y=Math.sin(ve),ye=Math.cos(ve);return[(2*ye+1)/3,(-Math.sqrt(3)*Y-ye+1)/3,(Math.sqrt(3)*Y-ye+1)/3]}function Ro(ve){return ve>0?1/(1-ve):1+ve}function Zs(ve){return ve>0?1-1/(1.001-ve):-ve}var Ls=function(ve,Y){return{u_is_size_zoom_constant:new e.Uniform1i(ve,Y.u_is_size_zoom_constant),u_is_size_feature_constant:new e.Uniform1i(ve,Y.u_is_size_feature_constant),u_size_t:new e.Uniform1f(ve,Y.u_size_t),u_size:new e.Uniform1f(ve,Y.u_size),u_camera_to_center_distance:new e.Uniform1f(ve,Y.u_camera_to_center_distance),u_pitch:new e.Uniform1f(ve,Y.u_pitch),u_rotate_symbol:new e.Uniform1i(ve,Y.u_rotate_symbol),u_aspect_ratio:new e.Uniform1f(ve,Y.u_aspect_ratio),u_fade_change:new e.Uniform1f(ve,Y.u_fade_change),u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_label_plane_matrix:new e.UniformMatrix4f(ve,Y.u_label_plane_matrix),u_coord_matrix:new e.UniformMatrix4f(ve,Y.u_coord_matrix),u_is_text:new e.Uniform1i(ve,Y.u_is_text),u_pitch_with_map:new e.Uniform1i(ve,Y.u_pitch_with_map),u_texsize:new e.Uniform2f(ve,Y.u_texsize),u_texture:new e.Uniform1i(ve,Y.u_texture)}},lu=function(ve,Y){return{u_is_size_zoom_constant:new e.Uniform1i(ve,Y.u_is_size_zoom_constant),u_is_size_feature_constant:new e.Uniform1i(ve,Y.u_is_size_feature_constant),u_size_t:new e.Uniform1f(ve,Y.u_size_t),u_size:new e.Uniform1f(ve,Y.u_size),u_camera_to_center_distance:new e.Uniform1f(ve,Y.u_camera_to_center_distance),u_pitch:new e.Uniform1f(ve,Y.u_pitch),u_rotate_symbol:new e.Uniform1i(ve,Y.u_rotate_symbol),u_aspect_ratio:new e.Uniform1f(ve,Y.u_aspect_ratio),u_fade_change:new e.Uniform1f(ve,Y.u_fade_change),u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_label_plane_matrix:new e.UniformMatrix4f(ve,Y.u_label_plane_matrix),u_coord_matrix:new e.UniformMatrix4f(ve,Y.u_coord_matrix),u_is_text:new e.Uniform1i(ve,Y.u_is_text),u_pitch_with_map:new e.Uniform1i(ve,Y.u_pitch_with_map),u_texsize:new e.Uniform2f(ve,Y.u_texsize),u_texture:new e.Uniform1i(ve,Y.u_texture),u_gamma_scale:new e.Uniform1f(ve,Y.u_gamma_scale),u_device_pixel_ratio:new e.Uniform1f(ve,Y.u_device_pixel_ratio),u_is_halo:new e.Uniform1i(ve,Y.u_is_halo)}},Iu=function(ve,Y){return{u_is_size_zoom_constant:new e.Uniform1i(ve,Y.u_is_size_zoom_constant),u_is_size_feature_constant:new e.Uniform1i(ve,Y.u_is_size_feature_constant),u_size_t:new e.Uniform1f(ve,Y.u_size_t),u_size:new e.Uniform1f(ve,Y.u_size),u_camera_to_center_distance:new e.Uniform1f(ve,Y.u_camera_to_center_distance),u_pitch:new e.Uniform1f(ve,Y.u_pitch),u_rotate_symbol:new e.Uniform1i(ve,Y.u_rotate_symbol),u_aspect_ratio:new e.Uniform1f(ve,Y.u_aspect_ratio),u_fade_change:new e.Uniform1f(ve,Y.u_fade_change),u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_label_plane_matrix:new e.UniformMatrix4f(ve,Y.u_label_plane_matrix),u_coord_matrix:new e.UniformMatrix4f(ve,Y.u_coord_matrix),u_is_text:new e.Uniform1i(ve,Y.u_is_text),u_pitch_with_map:new e.Uniform1i(ve,Y.u_pitch_with_map),u_texsize:new e.Uniform2f(ve,Y.u_texsize),u_texsize_icon:new e.Uniform2f(ve,Y.u_texsize_icon),u_texture:new e.Uniform1i(ve,Y.u_texture),u_texture_icon:new e.Uniform1i(ve,Y.u_texture_icon),u_gamma_scale:new e.Uniform1f(ve,Y.u_gamma_scale),u_device_pixel_ratio:new e.Uniform1f(ve,Y.u_device_pixel_ratio),u_is_halo:new e.Uniform1i(ve,Y.u_is_halo)}},Zu=function(ve,Y,ye,te,me,Ge,Le,$e,mt,jt){var _r=me.transform;return{u_is_size_zoom_constant:+(ve==="constant"||ve==="source"),u_is_size_feature_constant:+(ve==="constant"||ve==="camera"),u_size_t:Y?Y.uSizeT:0,u_size:Y?Y.uSize:0,u_camera_to_center_distance:_r.cameraToCenterDistance,u_pitch:_r.pitch/360*2*Math.PI,u_rotate_symbol:+ye,u_aspect_ratio:_r.width/_r.height,u_fade_change:me.options.fadeDuration?me.symbolFadeChange:1,u_matrix:Ge,u_label_plane_matrix:Le,u_coord_matrix:$e,u_is_text:+mt,u_pitch_with_map:+te,u_texsize:jt,u_texture:0}},Ic=function(ve,Y,ye,te,me,Ge,Le,$e,mt,jt,_r){var Nr=me.transform;return e.extend(Zu(ve,Y,ye,te,me,Ge,Le,$e,mt,jt),{u_gamma_scale:te?Math.cos(Nr._pitch)*Nr.cameraToCenterDistance:1,u_device_pixel_ratio:e.browser.devicePixelRatio,u_is_halo:+_r})},_u=function(ve,Y,ye,te,me,Ge,Le,$e,mt,jt){return e.extend(Ic(ve,Y,ye,te,me,Ge,Le,$e,!0,mt,!0),{u_texsize_icon:jt,u_texture_icon:1})},Rc=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_opacity:new e.Uniform1f(ve,Y.u_opacity),u_color:new e.UniformColor(ve,Y.u_color)}},Tu=function(ve,Y){return{u_matrix:new e.UniformMatrix4f(ve,Y.u_matrix),u_opacity:new e.Uniform1f(ve,Y.u_opacity),u_image:new e.Uniform1i(ve,Y.u_image),u_pattern_tl_a:new e.Uniform2f(ve,Y.u_pattern_tl_a),u_pattern_br_a:new e.Uniform2f(ve,Y.u_pattern_br_a),u_pattern_tl_b:new e.Uniform2f(ve,Y.u_pattern_tl_b),u_pattern_br_b:new e.Uniform2f(ve,Y.u_pattern_br_b),u_texsize:new e.Uniform2f(ve,Y.u_texsize),u_mix:new e.Uniform1f(ve,Y.u_mix),u_pattern_size_a:new e.Uniform2f(ve,Y.u_pattern_size_a),u_pattern_size_b:new e.Uniform2f(ve,Y.u_pattern_size_b),u_scale_a:new e.Uniform1f(ve,Y.u_scale_a),u_scale_b:new e.Uniform1f(ve,Y.u_scale_b),u_pixel_coord_upper:new e.Uniform2f(ve,Y.u_pixel_coord_upper),u_pixel_coord_lower:new e.Uniform2f(ve,Y.u_pixel_coord_lower),u_tile_units_to_pixels:new e.Uniform1f(ve,Y.u_tile_units_to_pixels)}},_c=function(ve,Y,ye){return{u_matrix:ve,u_opacity:Y,u_color:ye}},uo=function(ve,Y,ye,te,me,Ge){return e.extend(Yc(te,Ge,ye,me),{u_matrix:ve,u_opacity:Y})},Fo={fillExtrusion:Lf,fillExtrusionPattern:nu,fill:Cc,fillPattern:yc,fillOutline:Vl,fillOutlinePattern:yu,circle:Qt,collisionBox:na,collisionCircle:$r,debug:Ci,clippingMask:Qi,heatmap:Pi,heatmapTexture:Di,hillshade:En,hillshadePrepare:Jn,line:An,lineGradient:un,linePattern:yo,lineSDF:$o,raster:yl,symbolIcon:Ls,symbolSDF:lu,symbolTextAndIcon:Iu,background:Rc,backgroundPattern:Tu},Dc;function uc(ve,Y,ye,te,me,Ge,Le){for(var $e=ve.context,mt=$e.gl,jt=ve.useProgram("collisionBox"),_r=[],Nr=0,pr=0,yt=0;yt0){var lr=e.create(),Wt=hr;e.mul(lr,ir.placementInvProjMatrix,ve.transform.glCoordMatrix),e.mul(lr,lr,ir.placementViewportMatrix),_r.push({circleArray:dr,circleOffset:pr,transform:Wt,invTransform:lr}),Nr+=dr.length/4,pr=Nr}sr&&jt.draw($e,mt.LINES,Ra.disabled,Pa.disabled,ve.colorModeForRenderPass(),Br.disabled,ka(hr,ve.transform,Bt),ye.id,sr.layoutVertexBuffer,sr.indexBuffer,sr.segments,null,ve.transform.zoom,null,null,sr.collisionVertexBuffer)}}if(!(!Le||!_r.length)){var or=ve.useProgram("collisionCircle"),Vt=new e.StructArrayLayout2f1f2i16;Vt.resize(Nr*4),Vt._trim();for(var Fr=0,Jr=0,ya=_r;Jr=0&&(Et[ir.associatedIconIndex]={shiftedAnchor:ii,angle:Xi})}}if(_r){yt.clear();for(var ci=ve.icon.placedSymbolArray,bi=0;bi0){var Le=e.browser.now(),$e=(Le-ve.timeAdded)/Ge,mt=Y?(Le-Y.timeAdded)/Ge:-1,jt=ye.getSource(),_r=me.coveringZoomLevel({tileSize:jt.tileSize,roundZoom:jt.roundZoom}),Nr=!Y||Math.abs(Y.tileID.overscaledZ-_r)>Math.abs(ve.tileID.overscaledZ-_r),pr=Nr&&ve.refreshedUponExpiration?1:e.clamp(Nr?$e:1-mt,0,1);return ve.refreshedUponExpiration&&$e>=1&&(ve.refreshedUponExpiration=!1),Y?{opacity:1,mix:1-pr}:{opacity:pr,mix:0}}else return{opacity:1,mix:0}}function Er(ve,Y,ye){var te=ye.paint.get("background-color"),me=ye.paint.get("background-opacity");if(me!==0){var Ge=ve.context,Le=Ge.gl,$e=ve.transform,mt=$e.tileSize,jt=ye.paint.get("background-pattern");if(!ve.isPatternMissing(jt)){var _r=!jt&&te.a===1&&me===1&&ve.opaquePassEnabledForLayer()?"opaque":"translucent";if(ve.renderPass===_r){var Nr=Pa.disabled,pr=ve.depthModeForSublayer(0,_r==="opaque"?Ra.ReadWrite:Ra.ReadOnly),yt=ve.colorModeForRenderPass(),Et=ve.useProgram(jt?"backgroundPattern":"background"),Bt=$e.coveringTiles({tileSize:mt});jt&&(Ge.activeTexture.set(Le.TEXTURE0),ve.imageManager.bind(ve.context));for(var ir=ye.getCrossfadeParameters(),hr=0,sr=Bt;hr "+ye.overscaledZ);var hr=ir+" "+yt+"kb";To(ve,hr),Le.draw(te,me.TRIANGLES,$e,mt,Ft.alphaBlended,Br.disabled,Gi(Ge,e.Color.transparent,Bt),_r,ve.debugBuffer,ve.quadTriangleIndexBuffer,ve.debugSegments)}function To(ve,Y){ve.initDebugOverlayCanvas();var ye=ve.debugOverlayCanvas,te=ve.context.gl,me=ve.debugOverlayCanvas.getContext("2d");me.clearRect(0,0,ye.width,ye.height),me.shadowColor="white",me.shadowBlur=2,me.lineWidth=1.5,me.strokeStyle="white",me.textBaseline="top",me.font="bold 36px Open Sans, sans-serif",me.fillText(Y,5,5),me.strokeText(Y,5,5),ve.debugOverlayTexture.update(ye),ve.debugOverlayTexture.bind(te.LINEAR,te.CLAMP_TO_EDGE)}function ss(ve,Y,ye){var te=ve.context,me=ye.implementation;if(ve.renderPass==="offscreen"){var Ge=me.prerender;Ge&&(ve.setCustomLayerDefaults(),te.setColorMode(ve.colorModeForRenderPass()),Ge.call(me,te.gl,ve.transform.customLayerMatrix()),te.setDirty(),ve.setBaseState())}else if(ve.renderPass==="translucent"){ve.setCustomLayerDefaults(),te.setColorMode(ve.colorModeForRenderPass()),te.setStencilMode(Pa.disabled);var Le=me.renderingMode==="3d"?new Ra(ve.context.gl.LEQUAL,Ra.ReadWrite,ve.depthRangeFor3D):ve.depthModeForSublayer(0,Ra.ReadOnly);te.setDepthMode(Le),me.render(te.gl,ve.transform.customLayerMatrix()),te.setDirty(),ve.setBaseState(),te.bindFramebuffer.set(null)}}var Mo={symbol:R,circle:Nt,heatmap:$t,line:sa,fill:He,"fill-extrusion":lt,hillshade:Ct,raster:ur,background:Er,debug:Zn,custom:ss},Yo=function(Y,ye){this.context=new ta(Y),this.transform=ye,this._tileTextures={},this.setup(),this.numSublayers=aa.maxUnderzooming+aa.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new wl,this.gpuTimers={}};Yo.prototype.resize=function(Y,ye){if(this.width=Y*e.browser.devicePixelRatio,this.height=ye*e.browser.devicePixelRatio,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(var te=0,me=this.style._order;te256&&this.clearStencil(),te.setColorMode(Ft.disabled),te.setDepthMode(Ra.disabled);var Ge=this.useProgram("clippingMask");this._tileClippingMaskIDs={};for(var Le=0,$e=ye;Le<$e.length;Le+=1){var mt=$e[Le],jt=this._tileClippingMaskIDs[mt.key]=this.nextStencilID++;Ge.draw(te,me.TRIANGLES,Ra.disabled,new Pa({func:me.ALWAYS,mask:0},jt,255,me.KEEP,me.KEEP,me.REPLACE),Ft.disabled,Br.disabled,dn(mt.posMatrix),"$clipping",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}},Yo.prototype.stencilModeFor3D=function(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();var Y=this.nextStencilID++,ye=this.context.gl;return new Pa({func:ye.NOTEQUAL,mask:255},Y,255,ye.KEEP,ye.KEEP,ye.REPLACE)},Yo.prototype.stencilModeForClipping=function(Y){var ye=this.context.gl;return new Pa({func:ye.EQUAL,mask:255},this._tileClippingMaskIDs[Y.key],0,ye.KEEP,ye.KEEP,ye.REPLACE)},Yo.prototype.stencilConfigForOverlap=function(Y){var ye,te=this.context.gl,me=Y.sort(function(jt,_r){return _r.overscaledZ-jt.overscaledZ}),Ge=me[me.length-1].overscaledZ,Le=me[0].overscaledZ-Ge+1;if(Le>1){this.currentStencilSource=void 0,this.nextStencilID+Le>256&&this.clearStencil();for(var $e={},mt=0;mt=0;this.currentLayer--){var lr=this.style._layers[me[this.currentLayer]],Wt=Ge[lr.source],or=mt[lr.source];this._renderTileClippingMasks(lr,or),this.renderLayer(this,Wt,lr,or)}for(this.renderPass="translucent",this.currentLayer=0;this.currentLayer0?ye.pop():null},Yo.prototype.isPatternMissing=function(Y){if(!Y)return!1;if(!Y.from||!Y.to)return!0;var ye=this.imageManager.getPattern(Y.from.toString()),te=this.imageManager.getPattern(Y.to.toString());return!ye||!te},Yo.prototype.useProgram=function(Y,ye){this.cache=this.cache||{};var te=""+Y+(ye?ye.cacheKey:"")+(this._showOverdrawInspector?"/overdraw":"");return this.cache[te]||(this.cache[te]=new mf(this.context,Y,lf[Y],ye,Fo[Y],this._showOverdrawInspector)),this.cache[te]},Yo.prototype.setCustomLayerDefaults=function(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()},Yo.prototype.setBaseState=function(){var Y=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(Y.FUNC_ADD)},Yo.prototype.initDebugOverlayCanvas=function(){if(this.debugOverlayCanvas==null){this.debugOverlayCanvas=e.window.document.createElement("canvas"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512;var Y=this.context.gl;this.debugOverlayTexture=new e.Texture(this.context,this.debugOverlayCanvas,Y.RGBA)}},Yo.prototype.destroy=function(){this.emptyTexture.destroy(),this.debugOverlayTexture&&this.debugOverlayTexture.destroy()};var ps=function(Y,ye){this.points=Y,this.planes=ye};ps.fromInvProjectionMatrix=function(Y,ye,te){var me=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]],Ge=Math.pow(2,te),Le=me.map(function(jt){return e.transformMat4([],jt,Y)}).map(function(jt){return e.scale$1([],jt,1/jt[3]/ye*Ge)}),$e=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]],mt=$e.map(function(jt){var _r=e.sub([],Le[jt[0]],Le[jt[1]]),Nr=e.sub([],Le[jt[2]],Le[jt[1]]),pr=e.normalize([],e.cross([],_r,Nr)),yt=-e.dot(pr,Le[jt[1]]);return pr.concat(yt)});return new ps(Le,mt)};var sl=function(Y,ye){this.min=Y,this.max=ye,this.center=e.scale$2([],e.add([],this.min,this.max),.5)};sl.prototype.quadrant=function(Y){for(var ye=[Y%2===0,Y<2],te=e.clone$2(this.min),me=e.clone$2(this.max),Ge=0;Ge=0;if(Le===0)return 0;Le!==ye.length&&(te=!1)}if(te)return 2;for(var mt=0;mt<3;mt++){for(var jt=Number.MAX_VALUE,_r=-Number.MAX_VALUE,Nr=0;Nrthis.max[mt]-this.min[mt])return 0}return 1};var el=function(Y,ye,te,me){if(Y===void 0&&(Y=0),ye===void 0&&(ye=0),te===void 0&&(te=0),me===void 0&&(me=0),isNaN(Y)||Y<0||isNaN(ye)||ye<0||isNaN(te)||te<0||isNaN(me)||me<0)throw new Error("Invalid value for edge-insets, top, bottom, left and right must all be numbers");this.top=Y,this.bottom=ye,this.left=te,this.right=me};el.prototype.interpolate=function(Y,ye,te){return ye.top!=null&&Y.top!=null&&(this.top=e.number(Y.top,ye.top,te)),ye.bottom!=null&&Y.bottom!=null&&(this.bottom=e.number(Y.bottom,ye.bottom,te)),ye.left!=null&&Y.left!=null&&(this.left=e.number(Y.left,ye.left,te)),ye.right!=null&&Y.right!=null&&(this.right=e.number(Y.right,ye.right,te)),this},el.prototype.getCenter=function(Y,ye){var te=e.clamp((this.left+Y-this.right)/2,0,Y),me=e.clamp((this.top+ye-this.bottom)/2,0,ye);return new e.Point(te,me)},el.prototype.equals=function(Y){return this.top===Y.top&&this.bottom===Y.bottom&&this.left===Y.left&&this.right===Y.right},el.prototype.clone=function(){return new el(this.top,this.bottom,this.left,this.right)},el.prototype.toJSON=function(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}};var Qo=function(Y,ye,te,me,Ge){this.tileSize=512,this.maxValidLatitude=85.051129,this._renderWorldCopies=Ge===void 0?!0:Ge,this._minZoom=Y||0,this._maxZoom=ye||22,this._minPitch=te??0,this._maxPitch=me??60,this.setMaxBounds(),this.width=0,this.height=0,this._center=new e.LngLat(0,0),this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new el,this._posMatrixCache={},this._alignedPosMatrixCache={}},es={minZoom:{configurable:!0},maxZoom:{configurable:!0},minPitch:{configurable:!0},maxPitch:{configurable:!0},renderWorldCopies:{configurable:!0},worldSize:{configurable:!0},centerOffset:{configurable:!0},size:{configurable:!0},bearing:{configurable:!0},pitch:{configurable:!0},fov:{configurable:!0},zoom:{configurable:!0},center:{configurable:!0},padding:{configurable:!0},centerPoint:{configurable:!0},unmodified:{configurable:!0},point:{configurable:!0}};Qo.prototype.clone=function(){var Y=new Qo(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return Y.tileSize=this.tileSize,Y.latRange=this.latRange,Y.width=this.width,Y.height=this.height,Y._center=this._center,Y.zoom=this.zoom,Y.angle=this.angle,Y._fov=this._fov,Y._pitch=this._pitch,Y._unmodified=this._unmodified,Y._edgeInsets=this._edgeInsets.clone(),Y._calcMatrices(),Y},es.minZoom.get=function(){return this._minZoom},es.minZoom.set=function(ve){this._minZoom!==ve&&(this._minZoom=ve,this.zoom=Math.max(this.zoom,ve))},es.maxZoom.get=function(){return this._maxZoom},es.maxZoom.set=function(ve){this._maxZoom!==ve&&(this._maxZoom=ve,this.zoom=Math.min(this.zoom,ve))},es.minPitch.get=function(){return this._minPitch},es.minPitch.set=function(ve){this._minPitch!==ve&&(this._minPitch=ve,this.pitch=Math.max(this.pitch,ve))},es.maxPitch.get=function(){return this._maxPitch},es.maxPitch.set=function(ve){this._maxPitch!==ve&&(this._maxPitch=ve,this.pitch=Math.min(this.pitch,ve))},es.renderWorldCopies.get=function(){return this._renderWorldCopies},es.renderWorldCopies.set=function(ve){ve===void 0?ve=!0:ve===null&&(ve=!1),this._renderWorldCopies=ve},es.worldSize.get=function(){return this.tileSize*this.scale},es.centerOffset.get=function(){return this.centerPoint._sub(this.size._div(2))},es.size.get=function(){return new e.Point(this.width,this.height)},es.bearing.get=function(){return-this.angle/Math.PI*180},es.bearing.set=function(ve){var Y=-e.wrap(ve,-180,180)*Math.PI/180;this.angle!==Y&&(this._unmodified=!1,this.angle=Y,this._calcMatrices(),this.rotationMatrix=e.create$2(),e.rotate(this.rotationMatrix,this.rotationMatrix,this.angle))},es.pitch.get=function(){return this._pitch/Math.PI*180},es.pitch.set=function(ve){var Y=e.clamp(ve,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==Y&&(this._unmodified=!1,this._pitch=Y,this._calcMatrices())},es.fov.get=function(){return this._fov/Math.PI*180},es.fov.set=function(ve){ve=Math.max(.01,Math.min(60,ve)),this._fov!==ve&&(this._unmodified=!1,this._fov=ve/180*Math.PI,this._calcMatrices())},es.zoom.get=function(){return this._zoom},es.zoom.set=function(ve){var Y=Math.min(Math.max(ve,this.minZoom),this.maxZoom);this._zoom!==Y&&(this._unmodified=!1,this._zoom=Y,this.scale=this.zoomScale(Y),this.tileZoom=Math.floor(Y),this.zoomFraction=Y-this.tileZoom,this._constrain(),this._calcMatrices())},es.center.get=function(){return this._center},es.center.set=function(ve){ve.lat===this._center.lat&&ve.lng===this._center.lng||(this._unmodified=!1,this._center=ve,this._constrain(),this._calcMatrices())},es.padding.get=function(){return this._edgeInsets.toJSON()},es.padding.set=function(ve){this._edgeInsets.equals(ve)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,ve,1),this._calcMatrices())},es.centerPoint.get=function(){return this._edgeInsets.getCenter(this.width,this.height)},Qo.prototype.isPaddingEqual=function(Y){return this._edgeInsets.equals(Y)},Qo.prototype.interpolatePadding=function(Y,ye,te){this._unmodified=!1,this._edgeInsets.interpolate(Y,ye,te),this._constrain(),this._calcMatrices()},Qo.prototype.coveringZoomLevel=function(Y){var ye=(Y.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/Y.tileSize));return Math.max(0,ye)},Qo.prototype.getVisibleUnwrappedCoordinates=function(Y){var ye=[new e.UnwrappedTileID(0,Y)];if(this._renderWorldCopies)for(var te=this.pointCoordinate(new e.Point(0,0)),me=this.pointCoordinate(new e.Point(this.width,0)),Ge=this.pointCoordinate(new e.Point(this.width,this.height)),Le=this.pointCoordinate(new e.Point(0,this.height)),$e=Math.floor(Math.min(te.x,me.x,Ge.x,Le.x)),mt=Math.floor(Math.max(te.x,me.x,Ge.x,Le.x)),jt=1,_r=$e-jt;_r<=mt+jt;_r++)_r!==0&&ye.push(new e.UnwrappedTileID(_r,Y));return ye},Qo.prototype.coveringTiles=function(Y){var ye=this.coveringZoomLevel(Y),te=ye;if(Y.minzoom!==void 0&&yeY.maxzoom&&(ye=Y.maxzoom);var me=e.MercatorCoordinate.fromLngLat(this.center),Ge=Math.pow(2,ye),Le=[Ge*me.x,Ge*me.y,0],$e=ps.fromInvProjectionMatrix(this.invProjMatrix,this.worldSize,ye),mt=Y.minzoom||0;this.pitch<=60&&this._edgeInsets.top<.1&&(mt=ye);var jt=3,_r=function(Ha){return{aabb:new sl([Ha*Ge,0,0],[(Ha+1)*Ge,Ge,0]),zoom:0,x:0,y:0,wrap:Ha,fullyVisible:!1}},Nr=[],pr=[],yt=ye,Et=Y.reparseOverscaled?te:ye;if(this._renderWorldCopies)for(var Bt=1;Bt<=3;Bt++)Nr.push(_r(-Bt)),Nr.push(_r(Bt));for(Nr.push(_r(0));Nr.length>0;){var ir=Nr.pop(),hr=ir.x,sr=ir.y,dr=ir.fullyVisible;if(!dr){var lr=ir.aabb.intersects($e);if(lr===0)continue;dr=lr===2}var Wt=ir.aabb.distanceX(Le),or=ir.aabb.distanceY(Le),Vt=Math.max(Math.abs(Wt),Math.abs(or)),Fr=jt+(1<Fr&&ir.zoom>=mt){pr.push({tileID:new e.OverscaledTileID(ir.zoom===yt?Et:ir.zoom,ir.wrap,ir.zoom,hr,sr),distanceSq:e.sqrLen([Le[0]-.5-hr,Le[1]-.5-sr])});continue}for(var Jr=0;Jr<4;Jr++){var ya=(hr<<1)+Jr%2,gi=(sr<<1)+(Jr>>1);Nr.push({aabb:ir.aabb.quadrant(Jr),zoom:ir.zoom+1,x:ya,y:gi,wrap:ir.wrap,fullyVisible:dr})}}return pr.sort(function(Ha,ii){return Ha.distanceSq-ii.distanceSq}).map(function(Ha){return Ha.tileID})},Qo.prototype.resize=function(Y,ye){this.width=Y,this.height=ye,this.pixelsToGLUnits=[2/Y,-2/ye],this._constrain(),this._calcMatrices()},es.unmodified.get=function(){return this._unmodified},Qo.prototype.zoomScale=function(Y){return Math.pow(2,Y)},Qo.prototype.scaleZoom=function(Y){return Math.log(Y)/Math.LN2},Qo.prototype.project=function(Y){var ye=e.clamp(Y.lat,-this.maxValidLatitude,this.maxValidLatitude);return new e.Point(e.mercatorXfromLng(Y.lng)*this.worldSize,e.mercatorYfromLat(ye)*this.worldSize)},Qo.prototype.unproject=function(Y){return new e.MercatorCoordinate(Y.x/this.worldSize,Y.y/this.worldSize).toLngLat()},es.point.get=function(){return this.project(this.center)},Qo.prototype.setLocationAtPoint=function(Y,ye){var te=this.pointCoordinate(ye),me=this.pointCoordinate(this.centerPoint),Ge=this.locationCoordinate(Y),Le=new e.MercatorCoordinate(Ge.x-(te.x-me.x),Ge.y-(te.y-me.y));this.center=this.coordinateLocation(Le),this._renderWorldCopies&&(this.center=this.center.wrap())},Qo.prototype.locationPoint=function(Y){return this.coordinatePoint(this.locationCoordinate(Y))},Qo.prototype.pointLocation=function(Y){return this.coordinateLocation(this.pointCoordinate(Y))},Qo.prototype.locationCoordinate=function(Y){return e.MercatorCoordinate.fromLngLat(Y)},Qo.prototype.coordinateLocation=function(Y){return Y.toLngLat()},Qo.prototype.pointCoordinate=function(Y){var ye=0,te=[Y.x,Y.y,0,1],me=[Y.x,Y.y,1,1];e.transformMat4(te,te,this.pixelMatrixInverse),e.transformMat4(me,me,this.pixelMatrixInverse);var Ge=te[3],Le=me[3],$e=te[0]/Ge,mt=me[0]/Le,jt=te[1]/Ge,_r=me[1]/Le,Nr=te[2]/Ge,pr=me[2]/Le,yt=Nr===pr?0:(ye-Nr)/(pr-Nr);return new e.MercatorCoordinate(e.number($e,mt,yt)/this.worldSize,e.number(jt,_r,yt)/this.worldSize)},Qo.prototype.coordinatePoint=function(Y){var ye=[Y.x*this.worldSize,Y.y*this.worldSize,0,1];return e.transformMat4(ye,ye,this.pixelMatrix),new e.Point(ye[0]/ye[3],ye[1]/ye[3])},Qo.prototype.getBounds=function(){return new e.LngLatBounds().extend(this.pointLocation(new e.Point(0,0))).extend(this.pointLocation(new e.Point(this.width,0))).extend(this.pointLocation(new e.Point(this.width,this.height))).extend(this.pointLocation(new e.Point(0,this.height)))},Qo.prototype.getMaxBounds=function(){return!this.latRange||this.latRange.length!==2||!this.lngRange||this.lngRange.length!==2?null:new e.LngLatBounds([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]])},Qo.prototype.setMaxBounds=function(Y){Y?(this.lngRange=[Y.getWest(),Y.getEast()],this.latRange=[Y.getSouth(),Y.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-this.maxValidLatitude,this.maxValidLatitude])},Qo.prototype.calculatePosMatrix=function(Y,ye){ye===void 0&&(ye=!1);var te=Y.key,me=ye?this._alignedPosMatrixCache:this._posMatrixCache;if(me[te])return me[te];var Ge=Y.canonical,Le=this.worldSize/this.zoomScale(Ge.z),$e=Ge.x+Math.pow(2,Ge.z)*Y.wrap,mt=e.identity(new Float64Array(16));return e.translate(mt,mt,[$e*Le,Ge.y*Le,0]),e.scale(mt,mt,[Le/e.EXTENT,Le/e.EXTENT,1]),e.multiply(mt,ye?this.alignedProjMatrix:this.projMatrix,mt),me[te]=new Float32Array(mt),me[te]},Qo.prototype.customLayerMatrix=function(){return this.mercatorMatrix.slice()},Qo.prototype._constrain=function(){if(!(!this.center||!this.width||!this.height||this._constraining)){this._constraining=!0;var Y=-90,ye=90,te=-180,me=180,Ge,Le,$e,mt,jt=this.size,_r=this._unmodified;if(this.latRange){var Nr=this.latRange;Y=e.mercatorYfromLat(Nr[1])*this.worldSize,ye=e.mercatorYfromLat(Nr[0])*this.worldSize,Ge=ye-Yye&&(mt=ye-ir)}if(this.lngRange){var hr=yt.x,sr=jt.x/2;hr-srme&&($e=me-sr)}($e!==void 0||mt!==void 0)&&(this.center=this.unproject(new e.Point($e!==void 0?$e:yt.x,mt!==void 0?mt:yt.y))),this._unmodified=_r,this._constraining=!1}},Qo.prototype._calcMatrices=function(){if(this.height){var Y=this._fov/2,ye=this.centerOffset;this.cameraToCenterDistance=.5/Math.tan(Y)*this.height;var te=Math.PI/2+this._pitch,me=this._fov*(.5+ye.y/this.height),Ge=Math.sin(me)*this.cameraToCenterDistance/Math.sin(e.clamp(Math.PI-te-me,.01,Math.PI-.01)),Le=this.point,$e=Le.x,mt=Le.y,jt=Math.cos(Math.PI/2-this._pitch)*Ge+this.cameraToCenterDistance,_r=jt*1.01,Nr=this.height/50,pr=new Float64Array(16);e.perspective(pr,this._fov,this.width/this.height,Nr,_r),pr[8]=-ye.x*2/this.width,pr[9]=ye.y*2/this.height,e.scale(pr,pr,[1,-1,1]),e.translate(pr,pr,[0,0,-this.cameraToCenterDistance]),e.rotateX(pr,pr,this._pitch),e.rotateZ(pr,pr,this.angle),e.translate(pr,pr,[-$e,-mt,0]),this.mercatorMatrix=e.scale([],pr,[this.worldSize,this.worldSize,this.worldSize]),e.scale(pr,pr,[1,1,e.mercatorZfromAltitude(1,this.center.lat)*this.worldSize,1]),this.projMatrix=pr,this.invProjMatrix=e.invert([],this.projMatrix);var yt=this.width%2/2,Et=this.height%2/2,Bt=Math.cos(this.angle),ir=Math.sin(this.angle),hr=$e-Math.round($e)+Bt*yt+ir*Et,sr=mt-Math.round(mt)+Bt*Et+ir*yt,dr=new Float64Array(pr);if(e.translate(dr,dr,[hr>.5?hr-1:hr,sr>.5?sr-1:sr,0]),this.alignedProjMatrix=dr,pr=e.create(),e.scale(pr,pr,[this.width/2,-this.height/2,1]),e.translate(pr,pr,[1,-1,0]),this.labelPlaneMatrix=pr,pr=e.create(),e.scale(pr,pr,[1,-1,1]),e.translate(pr,pr,[-1,-1,0]),e.scale(pr,pr,[2/this.width,2/this.height,1]),this.glCoordMatrix=pr,this.pixelMatrix=e.multiply(new Float64Array(16),this.labelPlaneMatrix,this.projMatrix),pr=e.invert(new Float64Array(16),this.pixelMatrix),!pr)throw new Error("failed to invert matrix");this.pixelMatrixInverse=pr,this._posMatrixCache={},this._alignedPosMatrixCache={}}},Qo.prototype.maxPitchScaleFactor=function(){if(!this.pixelMatrixInverse)return 1;var Y=this.pointCoordinate(new e.Point(0,0)),ye=[Y.x*this.worldSize,Y.y*this.worldSize,0,1],te=e.transformMat4(ye,ye,this.pixelMatrix);return te[3]/this.cameraToCenterDistance},Qo.prototype.getCameraPoint=function(){var Y=this._pitch,ye=Math.tan(Y)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new e.Point(0,ye))},Qo.prototype.getCameraQueryGeometry=function(Y){var ye=this.getCameraPoint();if(Y.length===1)return[Y[0],ye];for(var te=ye.x,me=ye.y,Ge=ye.x,Le=ye.y,$e=0,mt=Y;$e=3&&!Y.some(function(te){return isNaN(te)})){var ye=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(Y[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+Y[2],+Y[1]],zoom:+Y[0],bearing:ye,pitch:+(Y[4]||0)}),!0}return!1},tu.prototype._updateHashUnthrottled=function(){var Y=e.window.location.href.replace(/(#.+)?$/,this.getHashString());try{e.window.history.replaceState(e.window.history.state,null,Y)}catch{}};var Ru={linearity:.3,easing:e.bezier(0,0,.3,1)},pu=e.extend({deceleration:2500,maxSpeed:1400},Ru),Tl=e.extend({deceleration:20,maxSpeed:1400},Ru),uu=e.extend({deceleration:1e3,maxSpeed:360},Ru),cc=e.extend({deceleration:1e3,maxSpeed:90},Ru),Gl=function(Y){this._map=Y,this.clear()};Gl.prototype.clear=function(){this._inertiaBuffer=[]},Gl.prototype.record=function(Y){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:e.browser.now(),settings:Y})},Gl.prototype._drainInertiaBuffer=function(){for(var Y=this._inertiaBuffer,ye=e.browser.now(),te=160;Y.length>0&&ye-Y[0].time>te;)Y.shift()},Gl.prototype._onMoveEnd=function(Y){if(this._drainInertiaBuffer(),!(this._inertiaBuffer.length<2)){for(var ye={zoom:0,bearing:0,pitch:0,pan:new e.Point(0,0),pinchAround:void 0,around:void 0},te=0,me=this._inertiaBuffer;te=this._clickTolerance||this._map.fire(new ze(Y.type,this._map,Y))},_t.prototype.dblclick=function(Y){return this._firePreventable(new ze(Y.type,this._map,Y))},_t.prototype.mouseover=function(Y){this._map.fire(new ze(Y.type,this._map,Y))},_t.prototype.mouseout=function(Y){this._map.fire(new ze(Y.type,this._map,Y))},_t.prototype.touchstart=function(Y){return this._firePreventable(new et(Y.type,this._map,Y))},_t.prototype.touchmove=function(Y){this._map.fire(new et(Y.type,this._map,Y))},_t.prototype.touchend=function(Y){this._map.fire(new et(Y.type,this._map,Y))},_t.prototype.touchcancel=function(Y){this._map.fire(new et(Y.type,this._map,Y))},_t.prototype._firePreventable=function(Y){if(this._map.fire(Y),Y.defaultPrevented)return{}},_t.prototype.isEnabled=function(){return!0},_t.prototype.isActive=function(){return!1},_t.prototype.enable=function(){},_t.prototype.disable=function(){};var St=function(Y){this._map=Y};St.prototype.reset=function(){this._delayContextMenu=!1,delete this._contextMenuEvent},St.prototype.mousemove=function(Y){this._map.fire(new ze(Y.type,this._map,Y))},St.prototype.mousedown=function(){this._delayContextMenu=!0},St.prototype.mouseup=function(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new ze("contextmenu",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)},St.prototype.contextmenu=function(Y){this._delayContextMenu?this._contextMenuEvent=Y:this._map.fire(new ze(Y.type,this._map,Y)),this._map.listens("contextmenu")&&Y.preventDefault()},St.prototype.isEnabled=function(){return!0},St.prototype.isActive=function(){return!1},St.prototype.enable=function(){},St.prototype.disable=function(){};var rr=function(Y,ye){this._map=Y,this._el=Y.getCanvasContainer(),this._container=Y.getContainer(),this._clickTolerance=ye.clickTolerance||1};rr.prototype.isEnabled=function(){return!!this._enabled},rr.prototype.isActive=function(){return!!this._active},rr.prototype.enable=function(){this.isEnabled()||(this._enabled=!0)},rr.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},rr.prototype.mousedown=function(Y,ye){this.isEnabled()&&Y.shiftKey&&Y.button===0&&(r.disableDrag(),this._startPos=this._lastPos=ye,this._active=!0)},rr.prototype.mousemoveWindow=function(Y,ye){if(this._active){var te=ye;if(!(this._lastPos.equals(te)||!this._box&&te.dist(this._startPos)this.numTouches)&&(this.aborted=!0),!this.aborted&&(this.startTime===void 0&&(this.startTime=Y.timeStamp),te.length===this.numTouches&&(this.centroid=gr(ye),this.touches=Ot(te,ye)))},va.prototype.touchmove=function(Y,ye,te){if(!(this.aborted||!this.centroid)){var me=Ot(te,ye);for(var Ge in this.touches){var Le=this.touches[Ge],$e=me[Ge];(!$e||$e.dist(Le)>xa)&&(this.aborted=!0)}}},va.prototype.touchend=function(Y,ye,te){if((!this.centroid||Y.timeStamp-this.startTime>Wr)&&(this.aborted=!0),te.length===0){var me=!this.aborted&&this.centroid;if(this.reset(),me)return me}};var Qa=function(Y){this.singleTap=new va(Y),this.numTaps=Y.numTaps,this.reset()};Qa.prototype.reset=function(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()},Qa.prototype.touchstart=function(Y,ye,te){this.singleTap.touchstart(Y,ye,te)},Qa.prototype.touchmove=function(Y,ye,te){this.singleTap.touchmove(Y,ye,te)},Qa.prototype.touchend=function(Y,ye,te){var me=this.singleTap.touchend(Y,ye,te);if(me){var Ge=Y.timeStamp-this.lastTime0&&(this._active=!0);var me=Ot(te,ye),Ge=new e.Point(0,0),Le=new e.Point(0,0),$e=0;for(var mt in me){var jt=me[mt],_r=this._touches[mt];_r&&(Ge._add(jt),Le._add(jt.sub(_r)),$e++,me[mt]=jt)}if(this._touches=me,!($eMath.abs(ve.x)}var gn=100,fo=function(ve){function Y(){ve.apply(this,arguments)}return ve&&(Y.__proto__=ve),Y.prototype=Object.create(ve&&ve.prototype),Y.prototype.constructor=Y,Y.prototype.reset=function(){ve.prototype.reset.call(this),this._valid=void 0,delete this._firstMove,delete this._lastPoints},Y.prototype._start=function(te){this._lastPoints=te,_l(te[0].sub(te[1]))&&(this._valid=!1)},Y.prototype._move=function(te,me,Ge){var Le=te[0].sub(this._lastPoints[0]),$e=te[1].sub(this._lastPoints[1]);if(this._valid=this.gestureBeginsVertically(Le,$e,Ge.timeStamp),!!this._valid){this._lastPoints=te,this._active=!0;var mt=(Le.y+$e.y)/2,jt=-.5;return{pitchDelta:mt*jt}}},Y.prototype.gestureBeginsVertically=function(te,me,Ge){if(this._valid!==void 0)return this._valid;var Le=2,$e=te.mag()>=Le,mt=me.mag()>=Le;if(!(!$e&&!mt)){if(!$e||!mt)return this._firstMove===void 0&&(this._firstMove=Ge),Ge-this._firstMove0==me.y>0;return _l(te)&&_l(me)&&jt}},Y}(Ln),fs={panStep:100,bearingStep:15,pitchStep:10},vs=function(){var Y=fs;this._panStep=Y.panStep,this._bearingStep=Y.bearingStep,this._pitchStep=Y.pitchStep,this._rotationDisabled=!1};vs.prototype.reset=function(){this._active=!1},vs.prototype.keydown=function(Y){var ye=this;if(!(Y.altKey||Y.ctrlKey||Y.metaKey)){var te=0,me=0,Ge=0,Le=0,$e=0;switch(Y.keyCode){case 61:case 107:case 171:case 187:te=1;break;case 189:case 109:case 173:te=-1;break;case 37:Y.shiftKey?me=-1:(Y.preventDefault(),Le=-1);break;case 39:Y.shiftKey?me=1:(Y.preventDefault(),Le=1);break;case 38:Y.shiftKey?Ge=1:(Y.preventDefault(),$e=-1);break;case 40:Y.shiftKey?Ge=-1:(Y.preventDefault(),$e=1);break;default:return}return this._rotationDisabled&&(me=0,Ge=0),{cameraAnimation:function(mt){var jt=mt.getZoom();mt.easeTo({duration:300,easeId:"keyboardHandler",easing:Al,zoom:te?Math.round(jt)+te*(Y.shiftKey?2:1):jt,bearing:mt.getBearing()+me*ye._bearingStep,pitch:mt.getPitch()+Ge*ye._pitchStep,offset:[-Le*ye._panStep,-$e*ye._panStep],center:mt.getCenter()},{originalEvent:Y})}}}},vs.prototype.enable=function(){this._enabled=!0},vs.prototype.disable=function(){this._enabled=!1,this.reset()},vs.prototype.isEnabled=function(){return this._enabled},vs.prototype.isActive=function(){return this._active},vs.prototype.disableRotation=function(){this._rotationDisabled=!0},vs.prototype.enableRotation=function(){this._rotationDisabled=!1};function Al(ve){return ve*(2-ve)}var Wl=4.000244140625,Au=1/100,Dl=1/450,xc=2,it=function(Y,ye){this._map=Y,this._el=Y.getCanvasContainer(),this._handler=ye,this._delta=0,this._defaultZoomRate=Au,this._wheelZoomRate=Dl,e.bindAll(["_onTimeout"],this)};it.prototype.setZoomRate=function(Y){this._defaultZoomRate=Y},it.prototype.setWheelZoomRate=function(Y){this._wheelZoomRate=Y},it.prototype.isEnabled=function(){return!!this._enabled},it.prototype.isActive=function(){return!!this._active||this._finishTimeout!==void 0},it.prototype.isZooming=function(){return!!this._zooming},it.prototype.enable=function(Y){this.isEnabled()||(this._enabled=!0,this._aroundCenter=Y&&Y.around==="center")},it.prototype.disable=function(){this.isEnabled()&&(this._enabled=!1)},it.prototype.wheel=function(Y){if(this.isEnabled()){var ye=Y.deltaMode===e.window.WheelEvent.DOM_DELTA_LINE?Y.deltaY*40:Y.deltaY,te=e.browser.now(),me=te-(this._lastWheelEventTime||0);this._lastWheelEventTime=te,ye!==0&&ye%Wl===0?this._type="wheel":ye!==0&&Math.abs(ye)<4?this._type="trackpad":me>400?(this._type=null,this._lastValue=ye,this._timeout=setTimeout(this._onTimeout,40,Y)):this._type||(this._type=Math.abs(me*ye)<200?"trackpad":"wheel",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,ye+=this._lastValue)),Y.shiftKey&&ye&&(ye=ye/4),this._type&&(this._lastWheelEvent=Y,this._delta-=ye,this._active||this._start(Y)),Y.preventDefault()}},it.prototype._onTimeout=function(Y){this._type="wheel",this._delta-=this._lastValue,this._active||this._start(Y)},it.prototype._start=function(Y){if(this._delta){this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);var ye=r.mousePos(this._el,Y);this._around=e.LngLat.convert(this._aroundCenter?this._map.getCenter():this._map.unproject(ye)),this._aroundPoint=this._map.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._handler._triggerRenderFrame())}},it.prototype.renderFrame=function(){var Y=this;if(this._frameId&&(this._frameId=null,!!this.isActive())){var ye=this._map.transform;if(this._delta!==0){var te=this._type==="wheel"&&Math.abs(this._delta)>Wl?this._wheelZoomRate:this._defaultZoomRate,me=xc/(1+Math.exp(-Math.abs(this._delta*te)));this._delta<0&&me!==0&&(me=1/me);var Ge=typeof this._targetZoom=="number"?ye.zoomScale(this._targetZoom):ye.scale;this._targetZoom=Math.min(ye.maxZoom,Math.max(ye.minZoom,ye.scaleZoom(Ge*me))),this._type==="wheel"&&(this._startZoom=ye.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}var Le=typeof this._targetZoom=="number"?this._targetZoom:ye.zoom,$e=this._startZoom,mt=this._easing,jt=!1,_r;if(this._type==="wheel"&&$e&&mt){var Nr=Math.min((e.browser.now()-this._lastWheelEventTime)/200,1),pr=mt(Nr);_r=e.number($e,Le,pr),Nr<1?this._frameId||(this._frameId=!0):jt=!0}else _r=Le,jt=!0;return this._active=!0,jt&&(this._active=!1,this._finishTimeout=setTimeout(function(){Y._zooming=!1,Y._handler._triggerRenderFrame(),delete Y._targetZoom,delete Y._finishTimeout},200)),{noInertia:!0,needsRenderFrame:!jt,zoomDelta:_r-ye.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}},it.prototype._smoothOutEasing=function(Y){var ye=e.ease;if(this._prevEase){var te=this._prevEase,me=(e.browser.now()-te.start)/te.duration,Ge=te.easing(me+.01)-te.easing(me),Le=.27/Math.sqrt(Ge*Ge+1e-4)*.01,$e=Math.sqrt(.27*.27-Le*Le);ye=e.bezier(Le,$e,.25,1)}return this._prevEase={start:e.browser.now(),duration:Y,easing:ye},ye},it.prototype.reset=function(){this._active=!1};var Xt=function(Y,ye){this._clickZoom=Y,this._tapZoom=ye};Xt.prototype.enable=function(){this._clickZoom.enable(),this._tapZoom.enable()},Xt.prototype.disable=function(){this._clickZoom.disable(),this._tapZoom.disable()},Xt.prototype.isEnabled=function(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()},Xt.prototype.isActive=function(){return this._clickZoom.isActive()||this._tapZoom.isActive()};var fr=function(){this.reset()};fr.prototype.reset=function(){this._active=!1},fr.prototype.dblclick=function(Y,ye){return Y.preventDefault(),{cameraAnimation:function(te){te.easeTo({duration:300,zoom:te.getZoom()+(Y.shiftKey?-1:1),around:te.unproject(ye)},{originalEvent:Y})}}},fr.prototype.enable=function(){this._enabled=!0},fr.prototype.disable=function(){this._enabled=!1,this.reset()},fr.prototype.isEnabled=function(){return this._enabled},fr.prototype.isActive=function(){return this._active};var la=function(){this._tap=new Qa({numTouches:1,numTaps:1}),this.reset()};la.prototype.reset=function(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,this._tap.reset()},la.prototype.touchstart=function(Y,ye,te){this._swipePoint||(this._tapTime&&Y.timeStamp-this._tapTime>Vr&&this.reset(),this._tapTime?te.length>0&&(this._swipePoint=ye[0],this._swipeTouch=te[0].identifier):this._tap.touchstart(Y,ye,te))},la.prototype.touchmove=function(Y,ye,te){if(!this._tapTime)this._tap.touchmove(Y,ye,te);else if(this._swipePoint){if(te[0].identifier!==this._swipeTouch)return;var me=ye[0],Ge=me.y-this._swipePoint.y;return this._swipePoint=me,Y.preventDefault(),this._active=!0,{zoomDelta:Ge/128}}},la.prototype.touchend=function(Y,ye,te){if(this._tapTime)this._swipePoint&&te.length===0&&this.reset();else{var me=this._tap.touchend(Y,ye,te);me&&(this._tapTime=Y.timeStamp)}},la.prototype.touchcancel=function(){this.reset()},la.prototype.enable=function(){this._enabled=!0},la.prototype.disable=function(){this._enabled=!1,this.reset()},la.prototype.isEnabled=function(){return this._enabled},la.prototype.isActive=function(){return this._active};var ba=function(Y,ye,te){this._el=Y,this._mousePan=ye,this._touchPan=te};ba.prototype.enable=function(Y){this._inertiaOptions=Y||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add("mapboxgl-touch-drag-pan")},ba.prototype.disable=function(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove("mapboxgl-touch-drag-pan")},ba.prototype.isEnabled=function(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()},ba.prototype.isActive=function(){return this._mousePan.isActive()||this._touchPan.isActive()};var ga=function(Y,ye,te){this._pitchWithRotate=Y.pitchWithRotate,this._mouseRotate=ye,this._mousePitch=te};ga.prototype.enable=function(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()},ga.prototype.disable=function(){this._mouseRotate.disable(),this._mousePitch.disable()},ga.prototype.isEnabled=function(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())},ga.prototype.isActive=function(){return this._mouseRotate.isActive()||this._mousePitch.isActive()};var _a=function(Y,ye,te,me){this._el=Y,this._touchZoom=ye,this._touchRotate=te,this._tapDragZoom=me,this._rotationDisabled=!1,this._enabled=!0};_a.prototype.enable=function(Y){this._touchZoom.enable(Y),this._rotationDisabled||this._touchRotate.enable(Y),this._tapDragZoom.enable(),this._el.classList.add("mapboxgl-touch-zoom-rotate")},_a.prototype.disable=function(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove("mapboxgl-touch-zoom-rotate")},_a.prototype.isEnabled=function(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()},_a.prototype.isActive=function(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()},_a.prototype.disableRotation=function(){this._rotationDisabled=!0,this._touchRotate.disable()},_a.prototype.enableRotation=function(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()};var Ka=function(ve){return ve.zoom||ve.drag||ve.pitch||ve.rotate},Ti=function(ve){function Y(){ve.apply(this,arguments)}return ve&&(Y.__proto__=ve),Y.prototype=Object.create(ve&&ve.prototype),Y.prototype.constructor=Y,Y}(e.Event);function xi(ve){return ve.panDelta&&ve.panDelta.mag()||ve.zoomDelta||ve.bearingDelta||ve.pitchDelta}var li=function(Y,ye){this._map=Y,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new Gl(Y),this._bearingSnap=ye.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(ye),e.bindAll(["handleEvent","handleWindowEvent"],this);var te=this._el;this._listeners=[[te,"touchstart",{passive:!0}],[te,"touchmove",{passive:!1}],[te,"touchend",void 0],[te,"touchcancel",void 0],[te,"mousedown",void 0],[te,"mousemove",void 0],[te,"mouseup",void 0],[e.window.document,"mousemove",{capture:!0}],[e.window.document,"mouseup",void 0],[te,"mouseover",void 0],[te,"mouseout",void 0],[te,"dblclick",void 0],[te,"click",void 0],[te,"keydown",{capture:!1}],[te,"keyup",void 0],[te,"wheel",{passive:!1}],[te,"contextmenu",void 0],[e.window,"blur",void 0]];for(var me=0,Ge=this._listeners;me$e?Math.min(2,Wt):Math.max(.5,Wt),Ha=Math.pow(gi,1-Jr),ii=Le.unproject(dr.add(lr.mult(Jr*Ha)).mult(ya));Le.setLocationAtPoint(Le.renderWorldCopies?ii.wrap():ii,ir)}Ge._fireMoveEvents(me)},function(Jr){Ge._afterEase(me,Jr)},te),this},Y.prototype._prepareEase=function(te,me,Ge){Ge===void 0&&(Ge={}),this._moving=!0,!me&&!Ge.moving&&this.fire(new e.Event("movestart",te)),this._zooming&&!Ge.zooming&&this.fire(new e.Event("zoomstart",te)),this._rotating&&!Ge.rotating&&this.fire(new e.Event("rotatestart",te)),this._pitching&&!Ge.pitching&&this.fire(new e.Event("pitchstart",te))},Y.prototype._fireMoveEvents=function(te){this.fire(new e.Event("move",te)),this._zooming&&this.fire(new e.Event("zoom",te)),this._rotating&&this.fire(new e.Event("rotate",te)),this._pitching&&this.fire(new e.Event("pitch",te))},Y.prototype._afterEase=function(te,me){if(!(this._easeId&&me&&this._easeId===me)){delete this._easeId;var Ge=this._zooming,Le=this._rotating,$e=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,Ge&&this.fire(new e.Event("zoomend",te)),Le&&this.fire(new e.Event("rotateend",te)),$e&&this.fire(new e.Event("pitchend",te)),this.fire(new e.Event("moveend",te))}},Y.prototype.flyTo=function(te,me){var Ge=this;if(!te.essential&&e.browser.prefersReducedMotion){var Le=e.pick(te,["center","zoom","bearing","pitch","around"]);return this.jumpTo(Le,me)}this.stop(),te=e.extend({offset:[0,0],speed:1.2,curve:1.42,easing:e.ease},te);var $e=this.transform,mt=this.getZoom(),jt=this.getBearing(),_r=this.getPitch(),Nr=this.getPadding(),pr="zoom"in te?e.clamp(+te.zoom,$e.minZoom,$e.maxZoom):mt,yt="bearing"in te?this._normalizeBearing(te.bearing,jt):jt,Et="pitch"in te?+te.pitch:_r,Bt="padding"in te?te.padding:$e.padding,ir=$e.zoomScale(pr-mt),hr=e.Point.convert(te.offset),sr=$e.centerPoint.add(hr),dr=$e.pointLocation(sr),lr=e.LngLat.convert(te.center||dr);this._normalizeCenter(lr);var Wt=$e.project(dr),or=$e.project(lr).sub(Wt),Vt=te.curve,Fr=Math.max($e.width,$e.height),Jr=Fr/ir,ya=or.mag();if("minZoom"in te){var gi=e.clamp(Math.min(te.minZoom,mt,pr),$e.minZoom,$e.maxZoom),Ha=Fr/$e.zoomScale(gi-mt);Vt=Math.sqrt(Ha/ya*2)}var ii=Vt*Vt;function Xi(Oo){var Ss=(Jr*Jr-Fr*Fr+(Oo?-1:1)*ii*ii*ya*ya)/(2*(Oo?Jr:Fr)*ii*ya);return Math.log(Math.sqrt(Ss*Ss+1)-Ss)}function Fi(Oo){return(Math.exp(Oo)-Math.exp(-Oo))/2}function ci(Oo){return(Math.exp(Oo)+Math.exp(-Oo))/2}function bi(Oo){return Fi(Oo)/ci(Oo)}var Si=Xi(0),Ui=function(Oo){return ci(Si)/ci(Si+Vt*Oo)},fn=function(Oo){return Fr*((ci(Si)*bi(Si+Vt*Oo)-Fi(Si))/ii)/ya},_o=(Xi(1)-Si)/Vt;if(Math.abs(ya)<1e-6||!isFinite(_o)){if(Math.abs(Fr-Jr)<1e-6)return this.easeTo(te,me);var Uo=Jrte.maxDuration&&(te.duration=0),this._zooming=!0,this._rotating=jt!==yt,this._pitching=Et!==_r,this._padding=!$e.isPaddingEqual(Bt),this._prepareEase(me,!1),this._ease(function(Oo){var Ss=Oo*_o,Xs=1/Ui(Ss);$e.zoom=Oo===1?pr:mt+$e.scaleZoom(Xs),Ge._rotating&&($e.bearing=e.number(jt,yt,Oo)),Ge._pitching&&($e.pitch=e.number(_r,Et,Oo)),Ge._padding&&($e.interpolatePadding(Nr,Bt,Oo),sr=$e.centerPoint.add(hr));var du=Oo===1?lr:$e.unproject(Wt.add(or.mult(fn(Ss))).mult(Xs));$e.setLocationAtPoint($e.renderWorldCopies?du.wrap():du,sr),Ge._fireMoveEvents(me)},function(){return Ge._afterEase(me)},te),this},Y.prototype.isEasing=function(){return!!this._easeFrameId},Y.prototype.stop=function(){return this._stop()},Y.prototype._stop=function(te,me){if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){var Ge=this._onEaseEnd;delete this._onEaseEnd,Ge.call(this,me)}if(!te){var Le=this.handlers;Le&&Le.stop(!1)}return this},Y.prototype._ease=function(te,me,Ge){Ge.animate===!1||Ge.duration===0?(te(1),me()):(this._easeStart=e.browser.now(),this._easeOptions=Ge,this._onEaseFrame=te,this._onEaseEnd=me,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))},Y.prototype._renderFrameCallback=function(){var te=Math.min((e.browser.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(te)),te<1?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},Y.prototype._normalizeBearing=function(te,me){te=e.wrap(te,-180,180);var Ge=Math.abs(te-me);return Math.abs(te-360-me)180?-360:Ge<-180?360:0}},Y}(e.Evented),zi=function(Y){Y===void 0&&(Y={}),this.options=Y,e.bindAll(["_toggleAttribution","_updateEditLink","_updateData","_updateCompact"],this)};zi.prototype.getDefaultPosition=function(){return"bottom-right"},zi.prototype.onAdd=function(Y){var ye=this.options&&this.options.compact;return this._map=Y,this._container=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-attrib"),this._compactButton=r.create("button","mapboxgl-ctrl-attrib-button",this._container),this._compactButton.addEventListener("click",this._toggleAttribution),this._setElementTitle(this._compactButton,"ToggleAttribution"),this._innerContainer=r.create("div","mapboxgl-ctrl-attrib-inner",this._container),this._innerContainer.setAttribute("role","list"),ye&&this._container.classList.add("mapboxgl-compact"),this._updateAttributions(),this._updateEditLink(),this._map.on("styledata",this._updateData),this._map.on("sourcedata",this._updateData),this._map.on("moveend",this._updateEditLink),ye===void 0&&(this._map.on("resize",this._updateCompact),this._updateCompact()),this._container},zi.prototype.onRemove=function(){r.remove(this._container),this._map.off("styledata",this._updateData),this._map.off("sourcedata",this._updateData),this._map.off("moveend",this._updateEditLink),this._map.off("resize",this._updateCompact),this._map=void 0,this._attribHTML=void 0},zi.prototype._setElementTitle=function(Y,ye){var te=this._map._getUIString("AttributionControl."+ye);Y.title=te,Y.setAttribute("aria-label",te)},zi.prototype._toggleAttribution=function(){this._container.classList.contains("mapboxgl-compact-show")?(this._container.classList.remove("mapboxgl-compact-show"),this._compactButton.setAttribute("aria-pressed","false")):(this._container.classList.add("mapboxgl-compact-show"),this._compactButton.setAttribute("aria-pressed","true"))},zi.prototype._updateEditLink=function(){var Y=this._editLink;Y||(Y=this._editLink=this._container.querySelector(".mapbox-improve-map"));var ye=[{key:"owner",value:this.styleOwner},{key:"id",value:this.styleId},{key:"access_token",value:this._map._requestManager._customAccessToken||e.config.ACCESS_TOKEN}];if(Y){var te=ye.reduce(function(me,Ge,Le){return Ge.value&&(me+=Ge.key+"="+Ge.value+(Le=0)return!1;return!0});var $e=Y.join(" | ");$e!==this._attribHTML&&(this._attribHTML=$e,Y.length?(this._innerContainer.innerHTML=$e,this._container.classList.remove("mapboxgl-attrib-empty")):this._container.classList.add("mapboxgl-attrib-empty"),this._editLink=null)}},zi.prototype._updateCompact=function(){this._map.getCanvasContainer().offsetWidth<=640?this._container.classList.add("mapboxgl-compact"):this._container.classList.remove("mapboxgl-compact","mapboxgl-compact-show")};var ki=function(){e.bindAll(["_updateLogo"],this),e.bindAll(["_updateCompact"],this)};ki.prototype.onAdd=function(Y){this._map=Y,this._container=r.create("div","mapboxgl-ctrl");var ye=r.create("a","mapboxgl-ctrl-logo");return ye.target="_blank",ye.rel="noopener nofollow",ye.href="https://www.mapbox.com/",ye.setAttribute("aria-label",this._map._getUIString("LogoControl.Title")),ye.setAttribute("rel","noopener nofollow"),this._container.appendChild(ye),this._container.style.display="none",this._map.on("sourcedata",this._updateLogo),this._updateLogo(),this._map.on("resize",this._updateCompact),this._updateCompact(),this._container},ki.prototype.onRemove=function(){r.remove(this._container),this._map.off("sourcedata",this._updateLogo),this._map.off("resize",this._updateCompact)},ki.prototype.getDefaultPosition=function(){return"bottom-left"},ki.prototype._updateLogo=function(Y){(!Y||Y.sourceDataType==="metadata")&&(this._container.style.display=this._logoRequired()?"block":"none")},ki.prototype._logoRequired=function(){if(this._map.style){var Y=this._map.style.sourceCaches;for(var ye in Y){var te=Y[ye].getSource();if(te.mapbox_logo)return!0}return!1}},ki.prototype._updateCompact=function(){var Y=this._container.children;if(Y.length){var ye=Y[0];this._map.getCanvasContainer().offsetWidth<250?ye.classList.add("mapboxgl-compact"):ye.classList.remove("mapboxgl-compact")}};var Ua=function(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1};Ua.prototype.add=function(Y){var ye=++this._id,te=this._queue;return te.push({callback:Y,id:ye,cancelled:!1}),ye},Ua.prototype.remove=function(Y){for(var ye=this._currentlyRunning,te=ye?this._queue.concat(ye):this._queue,me=0,Ge=te;mete.maxZoom)throw new Error("maxZoom must be greater than or equal to minZoom");if(te.minPitch!=null&&te.maxPitch!=null&&te.minPitch>te.maxPitch)throw new Error("maxPitch must be greater than or equal to minPitch");if(te.minPitch!=null&&te.minPitchpn)throw new Error("maxPitch must be less than or equal to "+pn);var Ge=new Qo(te.minZoom,te.maxZoom,te.minPitch,te.maxPitch,te.renderWorldCopies);if(ve.call(this,Ge,te),this._interactive=te.interactive,this._maxTileCacheSize=te.maxTileCacheSize,this._failIfMajorPerformanceCaveat=te.failIfMajorPerformanceCaveat,this._preserveDrawingBuffer=te.preserveDrawingBuffer,this._antialias=te.antialias,this._trackResize=te.trackResize,this._bearingSnap=te.bearingSnap,this._refreshExpiredTiles=te.refreshExpiredTiles,this._fadeDuration=te.fadeDuration,this._crossSourceCollisions=te.crossSourceCollisions,this._crossFadingFactor=1,this._collectResourceTiming=te.collectResourceTiming,this._renderTaskQueue=new Ua,this._controls=[],this._mapId=e.uniqueId(),this._locale=e.extend({},ea,te.locale),this._clickTolerance=te.clickTolerance,this._requestManager=new e.RequestManager(te.transformRequest,te.accessToken),typeof te.container=="string"){if(this._container=e.window.document.getElementById(te.container),!this._container)throw new Error("Container '"+te.container+"' not found.")}else if(te.container instanceof ei)this._container=te.container;else throw new Error("Invalid type: 'container' must be a String or HTMLElement.");if(te.maxBounds&&this.setMaxBounds(te.maxBounds),e.bindAll(["_onWindowOnline","_onWindowResize","_onMapScroll","_contextLost","_contextRestored"],this),this._setupContainer(),this._setupPainter(),this.painter===void 0)throw new Error("Failed to initialize WebGL.");this.on("move",function(){return me._update(!1)}),this.on("moveend",function(){return me._update(!1)}),this.on("zoom",function(){return me._update(!0)}),typeof e.window<"u"&&(e.window.addEventListener("online",this._onWindowOnline,!1),e.window.addEventListener("resize",this._onWindowResize,!1),e.window.addEventListener("orientationchange",this._onWindowResize,!1)),this.handlers=new li(this,te);var Le=typeof te.hash=="string"&&te.hash||void 0;this._hash=te.hash&&new tu(Le).addTo(this),(!this._hash||!this._hash._onHashChange())&&(this.jumpTo({center:te.center,zoom:te.zoom,bearing:te.bearing,pitch:te.pitch}),te.bounds&&(this.resize(),this.fitBounds(te.bounds,e.extend({},te.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=te.localIdeographFontFamily,te.style&&this.setStyle(te.style,{localIdeographFontFamily:te.localIdeographFontFamily}),te.attributionControl&&this.addControl(new zi({customAttribution:te.customAttribution})),this.addControl(new ki,te.logoPosition),this.on("style.load",function(){me.transform.unmodified&&me.jumpTo(me.style.stylesheet)}),this.on("data",function($e){me._update($e.dataType==="style"),me.fire(new e.Event($e.dataType+"data",$e))}),this.on("dataloading",function($e){me.fire(new e.Event($e.dataType+"dataloading",$e))})}ve&&(Y.__proto__=ve),Y.prototype=Object.create(ve&&ve.prototype),Y.prototype.constructor=Y;var ye={showTileBoundaries:{configurable:!0},showPadding:{configurable:!0},showCollisionBoxes:{configurable:!0},showOverdrawInspector:{configurable:!0},repaint:{configurable:!0},vertices:{configurable:!0},version:{configurable:!0}};return Y.prototype._getMapId=function(){return this._mapId},Y.prototype.addControl=function(me,Ge){if(Ge===void 0&&(me.getDefaultPosition?Ge=me.getDefaultPosition():Ge="top-right"),!me||!me.onAdd)return this.fire(new e.ErrorEvent(new Error("Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.")));var Le=me.onAdd(this);this._controls.push(me);var $e=this._controlPositions[Ge];return Ge.indexOf("bottom")!==-1?$e.insertBefore(Le,$e.firstChild):$e.appendChild(Le),this},Y.prototype.removeControl=function(me){if(!me||!me.onRemove)return this.fire(new e.ErrorEvent(new Error("Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.")));var Ge=this._controls.indexOf(me);return Ge>-1&&this._controls.splice(Ge,1),me.onRemove(this),this},Y.prototype.hasControl=function(me){return this._controls.indexOf(me)>-1},Y.prototype.resize=function(me){var Ge=this._containerDimensions(),Le=Ge[0],$e=Ge[1];this._resizeCanvas(Le,$e),this.transform.resize(Le,$e),this.painter.resize(Le,$e);var mt=!this._moving;return mt&&(this.stop(),this.fire(new e.Event("movestart",me)).fire(new e.Event("move",me))),this.fire(new e.Event("resize",me)),mt&&this.fire(new e.Event("moveend",me)),this},Y.prototype.getBounds=function(){return this.transform.getBounds()},Y.prototype.getMaxBounds=function(){return this.transform.getMaxBounds()},Y.prototype.setMaxBounds=function(me){return this.transform.setMaxBounds(e.LngLatBounds.convert(me)),this._update()},Y.prototype.setMinZoom=function(me){if(me=me??Ga,me>=Ga&&me<=this.transform.maxZoom)return this.transform.minZoom=me,this._update(),this.getZoom()=this.transform.minZoom)return this.transform.maxZoom=me,this._update(),this.getZoom()>me&&this.setZoom(me),this;throw new Error("maxZoom must be greater than the current minZoom")},Y.prototype.getMaxZoom=function(){return this.transform.maxZoom},Y.prototype.setMinPitch=function(me){if(me=me??Li,me=Li&&me<=this.transform.maxPitch)return this.transform.minPitch=me,this._update(),this.getPitch()pn)throw new Error("maxPitch must be less than or equal to "+pn);if(me>=this.transform.minPitch)return this.transform.maxPitch=me,this._update(),this.getPitch()>me&&this.setPitch(me),this;throw new Error("maxPitch must be greater than the current minPitch")},Y.prototype.getMaxPitch=function(){return this.transform.maxPitch},Y.prototype.getRenderWorldCopies=function(){return this.transform.renderWorldCopies},Y.prototype.setRenderWorldCopies=function(me){return this.transform.renderWorldCopies=me,this._update()},Y.prototype.project=function(me){return this.transform.locationPoint(e.LngLat.convert(me))},Y.prototype.unproject=function(me){return this.transform.pointLocation(e.Point.convert(me))},Y.prototype.isMoving=function(){return this._moving||this.handlers.isMoving()},Y.prototype.isZooming=function(){return this._zooming||this.handlers.isZooming()},Y.prototype.isRotating=function(){return this._rotating||this.handlers.isRotating()},Y.prototype._createDelegatedListener=function(me,Ge,Le){var $e=this,mt;if(me==="mouseenter"||me==="mouseover"){var jt=!1,_r=function(ir){var hr=$e.getLayer(Ge)?$e.queryRenderedFeatures(ir.point,{layers:[Ge]}):[];hr.length?jt||(jt=!0,Le.call($e,new ze(me,$e,ir.originalEvent,{features:hr}))):jt=!1},Nr=function(){jt=!1};return{layer:Ge,listener:Le,delegates:{mousemove:_r,mouseout:Nr}}}else if(me==="mouseleave"||me==="mouseout"){var pr=!1,yt=function(ir){var hr=$e.getLayer(Ge)?$e.queryRenderedFeatures(ir.point,{layers:[Ge]}):[];hr.length?pr=!0:pr&&(pr=!1,Le.call($e,new ze(me,$e,ir.originalEvent)))},Et=function(ir){pr&&(pr=!1,Le.call($e,new ze(me,$e,ir.originalEvent)))};return{layer:Ge,listener:Le,delegates:{mousemove:yt,mouseout:Et}}}else{var Bt=function(ir){var hr=$e.getLayer(Ge)?$e.queryRenderedFeatures(ir.point,{layers:[Ge]}):[];hr.length&&(ir.features=hr,Le.call($e,ir),delete ir.features)};return{layer:Ge,listener:Le,delegates:(mt={},mt[me]=Bt,mt)}}},Y.prototype.on=function(me,Ge,Le){if(Le===void 0)return ve.prototype.on.call(this,me,Ge);var $e=this._createDelegatedListener(me,Ge,Le);this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[me]=this._delegatedListeners[me]||[],this._delegatedListeners[me].push($e);for(var mt in $e.delegates)this.on(mt,$e.delegates[mt]);return this},Y.prototype.once=function(me,Ge,Le){if(Le===void 0)return ve.prototype.once.call(this,me,Ge);var $e=this._createDelegatedListener(me,Ge,Le);for(var mt in $e.delegates)this.once(mt,$e.delegates[mt]);return this},Y.prototype.off=function(me,Ge,Le){var $e=this;if(Le===void 0)return ve.prototype.off.call(this,me,Ge);var mt=function(jt){for(var _r=jt[me],Nr=0;Nr<_r.length;Nr++){var pr=_r[Nr];if(pr.layer===Ge&&pr.listener===Le){for(var yt in pr.delegates)$e.off(yt,pr.delegates[yt]);return _r.splice(Nr,1),$e}}};return this._delegatedListeners&&this._delegatedListeners[me]&&mt(this._delegatedListeners),this},Y.prototype.queryRenderedFeatures=function(me,Ge){if(!this.style)return[];Ge===void 0&&me!==void 0&&!(me instanceof e.Point)&&!Array.isArray(me)&&(Ge=me,me=void 0),Ge=Ge||{},me=me||[[0,0],[this.transform.width,this.transform.height]];var Le;if(me instanceof e.Point||typeof me[0]=="number")Le=[e.Point.convert(me)];else{var $e=e.Point.convert(me[0]),mt=e.Point.convert(me[1]);Le=[$e,new e.Point(mt.x,$e.y),mt,new e.Point($e.x,mt.y),$e]}return this.style.queryRenderedFeatures(Le,Ge,this.transform)},Y.prototype.querySourceFeatures=function(me,Ge){return this.style.querySourceFeatures(me,Ge)},Y.prototype.setStyle=function(me,Ge){return Ge=e.extend({},{localIdeographFontFamily:this._localIdeographFontFamily},Ge),Ge.diff!==!1&&Ge.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&me?(this._diffStyle(me,Ge),this):(this._localIdeographFontFamily=Ge.localIdeographFontFamily,this._updateStyle(me,Ge))},Y.prototype._getUIString=function(me){var Ge=this._locale[me];if(Ge==null)throw new Error("Missing UI string '"+me+"'");return Ge},Y.prototype._updateStyle=function(me,Ge){if(this.style&&(this.style.setEventedParent(null),this.style._remove()),me)this.style=new Ol(this,Ge||{});else return delete this.style,this;return this.style.setEventedParent(this,{style:this.style}),typeof me=="string"?this.style.loadURL(me):this.style.loadJSON(me),this},Y.prototype._lazyInitEmptyStyle=function(){this.style||(this.style=new Ol(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())},Y.prototype._diffStyle=function(me,Ge){var Le=this;if(typeof me=="string"){var $e=this._requestManager.normalizeStyleURL(me),mt=this._requestManager.transformRequest($e,e.ResourceType.Style);e.getJSON(mt,function(jt,_r){jt?Le.fire(new e.ErrorEvent(jt)):_r&&Le._updateDiff(_r,Ge)})}else typeof me=="object"&&this._updateDiff(me,Ge)},Y.prototype._updateDiff=function(me,Ge){try{this.style.setState(me)&&this._update(!0)}catch(Le){e.warnOnce("Unable to perform style diff: "+(Le.message||Le.error||Le)+". Rebuilding the style from scratch."),this._updateStyle(me,Ge)}},Y.prototype.getStyle=function(){if(this.style)return this.style.serialize()},Y.prototype.isStyleLoaded=function(){return this.style?this.style.loaded():e.warnOnce("There is no style added to the map.")},Y.prototype.addSource=function(me,Ge){return this._lazyInitEmptyStyle(),this.style.addSource(me,Ge),this._update(!0)},Y.prototype.isSourceLoaded=function(me){var Ge=this.style&&this.style.sourceCaches[me];if(Ge===void 0){this.fire(new e.ErrorEvent(new Error("There is no source with ID '"+me+"'")));return}return Ge.loaded()},Y.prototype.areTilesLoaded=function(){var me=this.style&&this.style.sourceCaches;for(var Ge in me){var Le=me[Ge],$e=Le._tiles;for(var mt in $e){var jt=$e[mt];if(!(jt.state==="loaded"||jt.state==="errored"))return!1}}return!0},Y.prototype.addSourceType=function(me,Ge,Le){return this._lazyInitEmptyStyle(),this.style.addSourceType(me,Ge,Le)},Y.prototype.removeSource=function(me){return this.style.removeSource(me),this._update(!0)},Y.prototype.getSource=function(me){return this.style.getSource(me)},Y.prototype.addImage=function(me,Ge,Le){Le===void 0&&(Le={});var $e=Le.pixelRatio;$e===void 0&&($e=1);var mt=Le.sdf;mt===void 0&&(mt=!1);var jt=Le.stretchX,_r=Le.stretchY,Nr=Le.content;this._lazyInitEmptyStyle();var pr=0;if(Ge instanceof Ma||vi&&Ge instanceof vi){var yt=e.browser.getImageData(Ge),Et=yt.width,Bt=yt.height,ir=yt.data;this.style.addImage(me,{data:new e.RGBAImage({width:Et,height:Bt},ir),pixelRatio:$e,stretchX:jt,stretchY:_r,content:Nr,sdf:mt,version:pr})}else{if(Ge.width===void 0||Ge.height===void 0)return this.fire(new e.ErrorEvent(new Error("Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`")));var hr=Ge.width,sr=Ge.height,dr=Ge.data,lr=Ge;this.style.addImage(me,{data:new e.RGBAImage({width:hr,height:sr},new Uint8Array(dr)),pixelRatio:$e,stretchX:jt,stretchY:_r,content:Nr,sdf:mt,version:pr,userImage:lr}),lr.onAdd&&lr.onAdd(this,me)}},Y.prototype.updateImage=function(me,Ge){var Le=this.style.getImage(me);if(!Le)return this.fire(new e.ErrorEvent(new Error("The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.")));var $e=Ge instanceof Ma||vi&&Ge instanceof vi?e.browser.getImageData(Ge):Ge,mt=$e.width,jt=$e.height,_r=$e.data;if(mt===void 0||jt===void 0)return this.fire(new e.ErrorEvent(new Error("Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`")));if(mt!==Le.data.width||jt!==Le.data.height)return this.fire(new e.ErrorEvent(new Error("The width and height of the updated image must be that same as the previous version of the image")));var Nr=!(Ge instanceof Ma||vi&&Ge instanceof vi);Le.data.replace(_r,Nr),this.style.updateImage(me,Le)},Y.prototype.hasImage=function(me){return me?!!this.style.getImage(me):(this.fire(new e.ErrorEvent(new Error("Missing required image id"))),!1)},Y.prototype.removeImage=function(me){this.style.removeImage(me)},Y.prototype.loadImage=function(me,Ge){e.getImage(this._requestManager.transformRequest(me,e.ResourceType.Image),Ge)},Y.prototype.listImages=function(){return this.style.listImages()},Y.prototype.addLayer=function(me,Ge){return this._lazyInitEmptyStyle(),this.style.addLayer(me,Ge),this._update(!0)},Y.prototype.moveLayer=function(me,Ge){return this.style.moveLayer(me,Ge),this._update(!0)},Y.prototype.removeLayer=function(me){return this.style.removeLayer(me),this._update(!0)},Y.prototype.getLayer=function(me){return this.style.getLayer(me)},Y.prototype.setLayerZoomRange=function(me,Ge,Le){return this.style.setLayerZoomRange(me,Ge,Le),this._update(!0)},Y.prototype.setFilter=function(me,Ge,Le){return Le===void 0&&(Le={}),this.style.setFilter(me,Ge,Le),this._update(!0)},Y.prototype.getFilter=function(me){return this.style.getFilter(me)},Y.prototype.setPaintProperty=function(me,Ge,Le,$e){return $e===void 0&&($e={}),this.style.setPaintProperty(me,Ge,Le,$e),this._update(!0)},Y.prototype.getPaintProperty=function(me,Ge){return this.style.getPaintProperty(me,Ge)},Y.prototype.setLayoutProperty=function(me,Ge,Le,$e){return $e===void 0&&($e={}),this.style.setLayoutProperty(me,Ge,Le,$e),this._update(!0)},Y.prototype.getLayoutProperty=function(me,Ge){return this.style.getLayoutProperty(me,Ge)},Y.prototype.setLight=function(me,Ge){return Ge===void 0&&(Ge={}),this._lazyInitEmptyStyle(),this.style.setLight(me,Ge),this._update(!0)},Y.prototype.getLight=function(){return this.style.getLight()},Y.prototype.setFeatureState=function(me,Ge){return this.style.setFeatureState(me,Ge),this._update()},Y.prototype.removeFeatureState=function(me,Ge){return this.style.removeFeatureState(me,Ge),this._update()},Y.prototype.getFeatureState=function(me){return this.style.getFeatureState(me)},Y.prototype.getContainer=function(){return this._container},Y.prototype.getCanvasContainer=function(){return this._canvasContainer},Y.prototype.getCanvas=function(){return this._canvas},Y.prototype._containerDimensions=function(){var me=0,Ge=0;return this._container&&(me=this._container.clientWidth||400,Ge=this._container.clientHeight||300),[me,Ge]},Y.prototype._detectMissingCSS=function(){var me=e.window.getComputedStyle(this._missingCSSCanary).getPropertyValue("background-color");me!=="rgb(250, 128, 114)"&&e.warnOnce("This page appears to be missing CSS declarations for Mapbox GL JS, which may cause the map to display incorrectly. Please ensure your page includes mapbox-gl.css, as described in https://www.mapbox.com/mapbox-gl-js/api/.")},Y.prototype._setupContainer=function(){var me=this._container;me.classList.add("mapboxgl-map");var Ge=this._missingCSSCanary=r.create("div","mapboxgl-canary",me);Ge.style.visibility="hidden",this._detectMissingCSS();var Le=this._canvasContainer=r.create("div","mapboxgl-canvas-container",me);this._interactive&&Le.classList.add("mapboxgl-interactive"),this._canvas=r.create("canvas","mapboxgl-canvas",Le),this._canvas.addEventListener("webglcontextlost",this._contextLost,!1),this._canvas.addEventListener("webglcontextrestored",this._contextRestored,!1),this._canvas.setAttribute("tabindex","0"),this._canvas.setAttribute("aria-label","Map"),this._canvas.setAttribute("role","region");var $e=this._containerDimensions();this._resizeCanvas($e[0],$e[1]);var mt=this._controlContainer=r.create("div","mapboxgl-control-container",me),jt=this._controlPositions={};["top-left","top-right","bottom-left","bottom-right"].forEach(function(_r){jt[_r]=r.create("div","mapboxgl-ctrl-"+_r,mt)}),this._container.addEventListener("scroll",this._onMapScroll,!1)},Y.prototype._resizeCanvas=function(me,Ge){var Le=e.browser.devicePixelRatio||1;this._canvas.width=Le*me,this._canvas.height=Le*Ge,this._canvas.style.width=me+"px",this._canvas.style.height=Ge+"px"},Y.prototype._setupPainter=function(){var me=e.extend({},t.webGLContextAttributes,{failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1}),Ge=this._canvas.getContext("webgl",me)||this._canvas.getContext("experimental-webgl",me);if(!Ge){this.fire(new e.ErrorEvent(new Error("Failed to initialize WebGL")));return}this.painter=new Yo(Ge,this.transform),e.webpSupported.testSupport(Ge)},Y.prototype._contextLost=function(me){me.preventDefault(),this._frame&&(this._frame.cancel(),this._frame=null),this.fire(new e.Event("webglcontextlost",{originalEvent:me}))},Y.prototype._contextRestored=function(me){this._setupPainter(),this.resize(),this._update(),this.fire(new e.Event("webglcontextrestored",{originalEvent:me}))},Y.prototype._onMapScroll=function(me){if(me.target===this._container)return this._container.scrollTop=0,this._container.scrollLeft=0,!1},Y.prototype.loaded=function(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()},Y.prototype._update=function(me){return this.style?(this._styleDirty=this._styleDirty||me,this._sourcesDirty=!0,this.triggerRepaint(),this):this},Y.prototype._requestRenderFrame=function(me){return this._update(),this._renderTaskQueue.add(me)},Y.prototype._cancelRenderFrame=function(me){this._renderTaskQueue.remove(me)},Y.prototype._render=function(me){var Ge=this,Le,$e=0,mt=this.painter.context.extTimerQuery;if(this.listens("gpu-timing-frame")&&(Le=mt.createQueryEXT(),mt.beginQueryEXT(mt.TIME_ELAPSED_EXT,Le),$e=e.browser.now()),this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(me),!this._removed){var jt=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;var _r=this.transform.zoom,Nr=e.browser.now();this.style.zoomHistory.update(_r,Nr);var pr=new e.EvaluationParameters(_r,{now:Nr,fadeDuration:this._fadeDuration,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),yt=pr.crossFadingFactor();(yt!==1||yt!==this._crossFadingFactor)&&(jt=!0,this._crossFadingFactor=yt),this.style.update(pr)}if(this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,this._fadeDuration,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:this._fadeDuration,showPadding:this.showPadding,gpuTiming:!!this.listens("gpu-timing-layer")}),this.fire(new e.Event("render")),this.loaded()&&!this._loaded&&(this._loaded=!0,this.fire(new e.Event("load"))),this.style&&(this.style.hasTransitions()||jt)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles(),this.listens("gpu-timing-frame")){var Et=e.browser.now()-$e;mt.endQueryEXT(mt.TIME_ELAPSED_EXT,Le),setTimeout(function(){var hr=mt.getQueryObjectEXT(Le,mt.QUERY_RESULT_EXT)/1e6;mt.deleteQueryEXT(Le),Ge.fire(new e.Event("gpu-timing-frame",{cpuTime:Et,gpuTime:hr}))},50)}if(this.listens("gpu-timing-layer")){var Bt=this.painter.collectGpuTimers();setTimeout(function(){var hr=Ge.painter.queryGpuTimers(Bt);Ge.fire(new e.Event("gpu-timing-layer",{layerTimes:hr}))},50)}var ir=this._sourcesDirty||this._styleDirty||this._placementDirty;return ir||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&this.fire(new e.Event("idle")),this._loaded&&!this._fullyLoaded&&!ir&&(this._fullyLoaded=!0),this}},Y.prototype.remove=function(){this._hash&&this._hash.remove();for(var me=0,Ge=this._controls;me180;){var Le=ye.locationPoint(ve);if(Le.x>=0&&Le.y>=0&&Le.x<=ye.width&&Le.y<=ye.height)break;ve.lng>ye.center.lng?ve.lng-=360:ve.lng+=360}return ve}var mn={center:"translate(-50%,-50%)",top:"translate(-50%,0)","top-left":"translate(0,0)","top-right":"translate(-100%,0)",bottom:"translate(-50%,-100%)","bottom-left":"translate(0,-100%)","bottom-right":"translate(-100%,-100%)",left:"translate(0,-50%)",right:"translate(-100%,-50%)"};function Rn(ve,Y,ye){var te=ve.classList;for(var me in mn)te.remove("mapboxgl-"+ye+"-anchor-"+me);te.add("mapboxgl-"+ye+"-anchor-"+Y)}var Ii=function(ve){function Y(ye,te){if(ve.call(this),(ye instanceof e.window.HTMLElement||te)&&(ye=e.extend({element:ye},te)),e.bindAll(["_update","_onMove","_onUp","_addDragHandler","_onMapClick","_onKeyPress"],this),this._anchor=ye&&ye.anchor||"center",this._color=ye&&ye.color||"#3FB1CE",this._scale=ye&&ye.scale||1,this._draggable=ye&&ye.draggable||!1,this._clickTolerance=ye&&ye.clickTolerance||0,this._isDragging=!1,this._state="inactive",this._rotation=ye&&ye.rotation||0,this._rotationAlignment=ye&&ye.rotationAlignment||"auto",this._pitchAlignment=ye&&ye.pitchAlignment&&ye.pitchAlignment!=="auto"?ye.pitchAlignment:this._rotationAlignment,!ye||!ye.element){this._defaultMarker=!0,this._element=r.create("div"),this._element.setAttribute("aria-label","Map marker");var me=r.createNS("http://www.w3.org/2000/svg","svg"),Ge=41,Le=27;me.setAttributeNS(null,"display","block"),me.setAttributeNS(null,"height",Ge+"px"),me.setAttributeNS(null,"width",Le+"px"),me.setAttributeNS(null,"viewBox","0 0 "+Le+" "+Ge);var $e=r.createNS("http://www.w3.org/2000/svg","g");$e.setAttributeNS(null,"stroke","none"),$e.setAttributeNS(null,"stroke-width","1"),$e.setAttributeNS(null,"fill","none"),$e.setAttributeNS(null,"fill-rule","evenodd");var mt=r.createNS("http://www.w3.org/2000/svg","g");mt.setAttributeNS(null,"fill-rule","nonzero");var jt=r.createNS("http://www.w3.org/2000/svg","g");jt.setAttributeNS(null,"transform","translate(3.0, 29.0)"),jt.setAttributeNS(null,"fill","#000000");for(var _r=[{rx:"10.5",ry:"5.25002273"},{rx:"10.5",ry:"5.25002273"},{rx:"9.5",ry:"4.77275007"},{rx:"8.5",ry:"4.29549936"},{rx:"7.5",ry:"3.81822308"},{rx:"6.5",ry:"3.34094679"},{rx:"5.5",ry:"2.86367051"},{rx:"4.5",ry:"2.38636864"}],Nr=0,pr=_r;Nr=me}this._isDragging&&(this._pos=te.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents="none",this._state==="pending"&&(this._state="active",this.fire(new e.Event("dragstart"))),this.fire(new e.Event("drag")))},Y.prototype._onUp=function(){this._element.style.pointerEvents="auto",this._positionDelta=null,this._pointerdownPos=null,this._isDragging=!1,this._map.off("mousemove",this._onMove),this._map.off("touchmove",this._onMove),this._state==="active"&&this.fire(new e.Event("dragend")),this._state="inactive"},Y.prototype._addDragHandler=function(te){this._element.contains(te.originalEvent.target)&&(te.preventDefault(),this._positionDelta=te.point.sub(this._pos).add(this._offset),this._pointerdownPos=te.point,this._state="pending",this._map.on("mousemove",this._onMove),this._map.on("touchmove",this._onMove),this._map.once("mouseup",this._onUp),this._map.once("touchend",this._onUp))},Y.prototype.setDraggable=function(te){return this._draggable=!!te,this._map&&(te?(this._map.on("mousedown",this._addDragHandler),this._map.on("touchstart",this._addDragHandler)):(this._map.off("mousedown",this._addDragHandler),this._map.off("touchstart",this._addDragHandler))),this},Y.prototype.isDraggable=function(){return this._draggable},Y.prototype.setRotation=function(te){return this._rotation=te||0,this._update(),this},Y.prototype.getRotation=function(){return this._rotation},Y.prototype.setRotationAlignment=function(te){return this._rotationAlignment=te||"auto",this._update(),this},Y.prototype.getRotationAlignment=function(){return this._rotationAlignment},Y.prototype.setPitchAlignment=function(te){return this._pitchAlignment=te&&te!=="auto"?te:this._rotationAlignment,this._update(),this},Y.prototype.getPitchAlignment=function(){return this._pitchAlignment},Y}(e.Evented),an={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0},kn;function Dn(ve){kn!==void 0?ve(kn):e.window.navigator.permissions!==void 0?e.window.navigator.permissions.query({name:"geolocation"}).then(function(Y){kn=Y.state!=="denied",ve(kn)}):(kn=!!e.window.navigator.geolocation,ve(kn))}var Wn=0,Ps=!1,xl=function(ve){function Y(ye){ve.call(this),this.options=e.extend({},an,ye),e.bindAll(["_onSuccess","_onError","_onZoom","_finish","_setupUI","_updateCamera","_updateMarker"],this)}return ve&&(Y.__proto__=ve),Y.prototype=Object.create(ve&&ve.prototype),Y.prototype.constructor=Y,Y.prototype.onAdd=function(te){return this._map=te,this._container=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-group"),Dn(this._setupUI),this._container},Y.prototype.onRemove=function(){this._geolocationWatchID!==void 0&&(e.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),r.remove(this._container),this._map.off("zoom",this._onZoom),this._map=void 0,Wn=0,Ps=!1},Y.prototype._isOutOfMapMaxBounds=function(te){var me=this._map.getMaxBounds(),Ge=te.coords;return me&&(Ge.longitudeme.getEast()||Ge.latitudeme.getNorth())},Y.prototype._setErrorState=function(){switch(this._watchState){case"WAITING_ACTIVE":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active-error");break;case"ACTIVE_LOCK":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting");break;case"BACKGROUND":this._watchState="BACKGROUND_ERROR",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting");break}},Y.prototype._onSuccess=function(te){if(this._map){if(this._isOutOfMapMaxBounds(te)){this._setErrorState(),this.fire(new e.Event("outofmaxbounds",te)),this._updateMarker(),this._finish();return}if(this.options.trackUserLocation)switch(this._lastKnownPosition=te,this._watchState){case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active");break;case"BACKGROUND":case"BACKGROUND_ERROR":this._watchState="BACKGROUND",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background");break}this.options.showUserLocation&&this._watchState!=="OFF"&&this._updateMarker(te),(!this.options.trackUserLocation||this._watchState==="ACTIVE_LOCK")&&this._updateCamera(te),this.options.showUserLocation&&this._dotElement.classList.remove("mapboxgl-user-location-dot-stale"),this.fire(new e.Event("geolocate",te)),this._finish()}},Y.prototype._updateCamera=function(te){var me=new e.LngLat(te.coords.longitude,te.coords.latitude),Ge=te.coords.accuracy,Le=this._map.getBearing(),$e=e.extend({bearing:Le},this.options.fitBoundsOptions);this._map.fitBounds(me.toBounds(Ge),$e,{geolocateSource:!0})},Y.prototype._updateMarker=function(te){if(te){var me=new e.LngLat(te.coords.longitude,te.coords.latitude);this._accuracyCircleMarker.setLngLat(me).addTo(this._map),this._userLocationDotMarker.setLngLat(me).addTo(this._map),this._accuracy=te.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},Y.prototype._updateCircleRadius=function(){var te=this._map._container.clientHeight/2,me=this._map.unproject([0,te]),Ge=this._map.unproject([1,te]),Le=me.distanceTo(Ge),$e=Math.ceil(2*this._accuracy/Le);this._circleElement.style.width=$e+"px",this._circleElement.style.height=$e+"px"},Y.prototype._onZoom=function(){this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},Y.prototype._onError=function(te){if(this._map){if(this.options.trackUserLocation)if(te.code===1){this._watchState="OFF",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background-error"),this._geolocateButton.disabled=!0;var me=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.title=me,this._geolocateButton.setAttribute("aria-label",me),this._geolocationWatchID!==void 0&&this._clearWatch()}else{if(te.code===3&&Ps)return;this._setErrorState()}this._watchState!=="OFF"&&this.options.showUserLocation&&this._dotElement.classList.add("mapboxgl-user-location-dot-stale"),this.fire(new e.Event("error",te)),this._finish()}},Y.prototype._finish=function(){this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},Y.prototype._setupUI=function(te){var me=this;if(this._container.addEventListener("contextmenu",function($e){return $e.preventDefault()}),this._geolocateButton=r.create("button","mapboxgl-ctrl-geolocate",this._container),r.create("span","mapboxgl-ctrl-icon",this._geolocateButton).setAttribute("aria-hidden",!0),this._geolocateButton.type="button",te===!1){e.warnOnce("Geolocation support is not available so the GeolocateControl will be disabled.");var Ge=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.disabled=!0,this._geolocateButton.title=Ge,this._geolocateButton.setAttribute("aria-label",Ge)}else{var Le=this._map._getUIString("GeolocateControl.FindMyLocation");this._geolocateButton.title=Le,this._geolocateButton.setAttribute("aria-label",Le)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute("aria-pressed","false"),this._watchState="OFF"),this.options.showUserLocation&&(this._dotElement=r.create("div","mapboxgl-user-location-dot"),this._userLocationDotMarker=new Ii(this._dotElement),this._circleElement=r.create("div","mapboxgl-user-location-accuracy-circle"),this._accuracyCircleMarker=new Ii({element:this._circleElement,pitchAlignment:"map"}),this.options.trackUserLocation&&(this._watchState="OFF"),this._map.on("zoom",this._onZoom)),this._geolocateButton.addEventListener("click",this.trigger.bind(this)),this._setup=!0,this.options.trackUserLocation&&this._map.on("movestart",function($e){var mt=$e.originalEvent&&$e.originalEvent.type==="resize";!$e.geolocateSource&&me._watchState==="ACTIVE_LOCK"&&!mt&&(me._watchState="BACKGROUND",me._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background"),me._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),me.fire(new e.Event("trackuserlocationend")))})},Y.prototype.trigger=function(){if(!this._setup)return e.warnOnce("Geolocate control triggered before added to a map"),!1;if(this.options.trackUserLocation){switch(this._watchState){case"OFF":this._watchState="WAITING_ACTIVE",this.fire(new e.Event("trackuserlocationstart"));break;case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":case"BACKGROUND_ERROR":Wn--,Ps=!1,this._watchState="OFF",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background-error"),this.fire(new e.Event("trackuserlocationend"));break;case"BACKGROUND":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-background"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new e.Event("trackuserlocationstart"));break}switch(this._watchState){case"WAITING_ACTIVE":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active");break;case"ACTIVE_LOCK":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active");break;case"ACTIVE_ERROR":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-active-error");break;case"BACKGROUND":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background");break;case"BACKGROUND_ERROR":this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-background-error");break}if(this._watchState==="OFF"&&this._geolocationWatchID!==void 0)this._clearWatch();else if(this._geolocationWatchID===void 0){this._geolocateButton.classList.add("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","true"),Wn++;var te;Wn>1?(te={maximumAge:6e5,timeout:0},Ps=!0):(te=this.options.positionOptions,Ps=!1),this._geolocationWatchID=e.window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,te)}}else e.window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0},Y.prototype._clearWatch=function(){e.window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove("mapboxgl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","false"),this.options.showUserLocation&&this._updateMarker(null)},Y}(e.Evented),co={maxWidth:100,unit:"metric"},Xl=function(Y){this.options=e.extend({},co,Y),e.bindAll(["_onMove","setUnit"],this)};Xl.prototype.getDefaultPosition=function(){return"bottom-left"},Xl.prototype._onMove=function(){hs(this._map,this._container,this.options)},Xl.prototype.onAdd=function(Y){return this._map=Y,this._container=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-scale",Y.getContainer()),this._map.on("move",this._onMove),this._onMove(),this._container},Xl.prototype.onRemove=function(){r.remove(this._container),this._map.off("move",this._onMove),this._map=void 0},Xl.prototype.setUnit=function(Y){this.options.unit=Y,hs(this._map,this._container,this.options)};function hs(ve,Y,ye){var te=ye&&ye.maxWidth||100,me=ve._container.clientHeight/2,Ge=ve.unproject([0,me]),Le=ve.unproject([te,me]),$e=Ge.distanceTo(Le);if(ye&&ye.unit==="imperial"){var mt=3.2808*$e;if(mt>5280){var jt=mt/5280;Sl(Y,te,jt,ve._getUIString("ScaleControl.Miles"))}else Sl(Y,te,mt,ve._getUIString("ScaleControl.Feet"))}else if(ye&&ye.unit==="nautical"){var _r=$e/1852;Sl(Y,te,_r,ve._getUIString("ScaleControl.NauticalMiles"))}else $e>=1e3?Sl(Y,te,$e/1e3,ve._getUIString("ScaleControl.Kilometers")):Sl(Y,te,$e,ve._getUIString("ScaleControl.Meters"))}function Sl(ve,Y,ye,te){var me=ru(ye),Ge=me/ye;ve.style.width=Y*Ge+"px",ve.innerHTML=me+" "+te}function Cl(ve){var Y=Math.pow(10,Math.ceil(-Math.log(ve)/Math.LN10));return Math.round(ve*Y)/Y}function ru(ve){var Y=Math.pow(10,(""+Math.floor(ve)).length-1),ye=ve/Y;return ye=ye>=10?10:ye>=5?5:ye>=3?3:ye>=2?2:ye>=1?1:Cl(ye),Y*ye}var Os=function(Y){this._fullscreen=!1,Y&&Y.container&&(Y.container instanceof e.window.HTMLElement?this._container=Y.container:e.warnOnce("Full screen control 'container' must be a DOM element.")),e.bindAll(["_onClickFullscreen","_changeIcon"],this),"onfullscreenchange"in e.window.document?this._fullscreenchange="fullscreenchange":"onmozfullscreenchange"in e.window.document?this._fullscreenchange="mozfullscreenchange":"onwebkitfullscreenchange"in e.window.document?this._fullscreenchange="webkitfullscreenchange":"onmsfullscreenchange"in e.window.document&&(this._fullscreenchange="MSFullscreenChange")};Os.prototype.onAdd=function(Y){return this._map=Y,this._container||(this._container=this._map.getContainer()),this._controlContainer=r.create("div","mapboxgl-ctrl mapboxgl-ctrl-group"),this._checkFullscreenSupport()?this._setupUI():(this._controlContainer.style.display="none",e.warnOnce("This device does not support fullscreen mode.")),this._controlContainer},Os.prototype.onRemove=function(){r.remove(this._controlContainer),this._map=null,e.window.document.removeEventListener(this._fullscreenchange,this._changeIcon)},Os.prototype._checkFullscreenSupport=function(){return!!(e.window.document.fullscreenEnabled||e.window.document.mozFullScreenEnabled||e.window.document.msFullscreenEnabled||e.window.document.webkitFullscreenEnabled)},Os.prototype._setupUI=function(){var Y=this._fullscreenButton=r.create("button","mapboxgl-ctrl-fullscreen",this._controlContainer);r.create("span","mapboxgl-ctrl-icon",Y).setAttribute("aria-hidden",!0),Y.type="button",this._updateTitle(),this._fullscreenButton.addEventListener("click",this._onClickFullscreen),e.window.document.addEventListener(this._fullscreenchange,this._changeIcon)},Os.prototype._updateTitle=function(){var Y=this._getTitle();this._fullscreenButton.setAttribute("aria-label",Y),this._fullscreenButton.title=Y},Os.prototype._getTitle=function(){return this._map._getUIString(this._isFullscreen()?"FullscreenControl.Exit":"FullscreenControl.Enter")},Os.prototype._isFullscreen=function(){return this._fullscreen},Os.prototype._changeIcon=function(){var Y=e.window.document.fullscreenElement||e.window.document.mozFullScreenElement||e.window.document.webkitFullscreenElement||e.window.document.msFullscreenElement;Y===this._container!==this._fullscreen&&(this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle("mapboxgl-ctrl-shrink"),this._fullscreenButton.classList.toggle("mapboxgl-ctrl-fullscreen"),this._updateTitle())},Os.prototype._onClickFullscreen=function(){this._isFullscreen()?e.window.document.exitFullscreen?e.window.document.exitFullscreen():e.window.document.mozCancelFullScreen?e.window.document.mozCancelFullScreen():e.window.document.msExitFullscreen?e.window.document.msExitFullscreen():e.window.document.webkitCancelFullScreen&&e.window.document.webkitCancelFullScreen():this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen&&this._container.webkitRequestFullscreen()};var pl={closeButton:!0,closeOnClick:!0,focusAfterOpen:!0,className:"",maxWidth:"240px"},bl=["a[href]","[tabindex]:not([tabindex='-1'])","[contenteditable]:not([contenteditable='false'])","button:not([disabled])","input:not([disabled])","select:not([disabled])","textarea:not([disabled])"].join(", "),Xn=function(ve){function Y(ye){ve.call(this),this.options=e.extend(Object.create(pl),ye),e.bindAll(["_update","_onClose","remove","_onMouseMove","_onMouseUp","_onDrag"],this)}return ve&&(Y.__proto__=ve),Y.prototype=Object.create(ve&&ve.prototype),Y.prototype.constructor=Y,Y.prototype.addTo=function(te){return this._map&&this.remove(),this._map=te,this.options.closeOnClick&&this._map.on("click",this._onClose),this.options.closeOnMove&&this._map.on("move",this._onClose),this._map.on("remove",this.remove),this._update(),this._focusFirstElement(),this._trackPointer?(this._map.on("mousemove",this._onMouseMove),this._map.on("mouseup",this._onMouseUp),this._container&&this._container.classList.add("mapboxgl-popup-track-pointer"),this._map._canvasContainer.classList.add("mapboxgl-track-pointer")):this._map.on("move",this._update),this.fire(new e.Event("open")),this},Y.prototype.isOpen=function(){return!!this._map},Y.prototype.remove=function(){return this._content&&r.remove(this._content),this._container&&(r.remove(this._container),delete this._container),this._map&&(this._map.off("move",this._update),this._map.off("move",this._onClose),this._map.off("click",this._onClose),this._map.off("remove",this.remove),this._map.off("mousemove",this._onMouseMove),this._map.off("mouseup",this._onMouseUp),this._map.off("drag",this._onDrag),delete this._map),this.fire(new e.Event("close")),this},Y.prototype.getLngLat=function(){return this._lngLat},Y.prototype.setLngLat=function(te){return this._lngLat=e.LngLat.convert(te),this._pos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on("move",this._update),this._map.off("mousemove",this._onMouseMove),this._container&&this._container.classList.remove("mapboxgl-popup-track-pointer"),this._map._canvasContainer.classList.remove("mapboxgl-track-pointer")),this},Y.prototype.trackPointer=function(){return this._trackPointer=!0,this._pos=null,this._update(),this._map&&(this._map.off("move",this._update),this._map.on("mousemove",this._onMouseMove),this._map.on("drag",this._onDrag),this._container&&this._container.classList.add("mapboxgl-popup-track-pointer"),this._map._canvasContainer.classList.add("mapboxgl-track-pointer")),this},Y.prototype.getElement=function(){return this._container},Y.prototype.setText=function(te){return this.setDOMContent(e.window.document.createTextNode(te))},Y.prototype.setHTML=function(te){var me=e.window.document.createDocumentFragment(),Ge=e.window.document.createElement("body"),Le;for(Ge.innerHTML=te;Le=Ge.firstChild,!!Le;)me.appendChild(Le);return this.setDOMContent(me)},Y.prototype.getMaxWidth=function(){return this._container&&this._container.style.maxWidth},Y.prototype.setMaxWidth=function(te){return this.options.maxWidth=te,this._update(),this},Y.prototype.setDOMContent=function(te){if(this._content)for(;this._content.hasChildNodes();)this._content.firstChild&&this._content.removeChild(this._content.firstChild);else this._content=r.create("div","mapboxgl-popup-content",this._container);return this._content.appendChild(te),this._createCloseButton(),this._update(),this._focusFirstElement(),this},Y.prototype.addClassName=function(te){this._container&&this._container.classList.add(te)},Y.prototype.removeClassName=function(te){this._container&&this._container.classList.remove(te)},Y.prototype.setOffset=function(te){return this.options.offset=te,this._update(),this},Y.prototype.toggleClassName=function(te){if(this._container)return this._container.classList.toggle(te)},Y.prototype._createCloseButton=function(){this.options.closeButton&&(this._closeButton=r.create("button","mapboxgl-popup-close-button",this._content),this._closeButton.type="button",this._closeButton.setAttribute("aria-label","Close popup"),this._closeButton.innerHTML="×",this._closeButton.addEventListener("click",this._onClose))},Y.prototype._onMouseUp=function(te){this._update(te.point)},Y.prototype._onMouseMove=function(te){this._update(te.point)},Y.prototype._onDrag=function(te){this._update(te.point)},Y.prototype._update=function(te){var me=this,Ge=this._lngLat||this._trackPointer;if(!(!this._map||!Ge||!this._content)&&(this._container||(this._container=r.create("div","mapboxgl-popup",this._map.getContainer()),this._tip=r.create("div","mapboxgl-popup-tip",this._container),this._container.appendChild(this._content),this.options.className&&this.options.className.split(" ").forEach(function(yt){return me._container.classList.add(yt)}),this._trackPointer&&this._container.classList.add("mapboxgl-popup-track-pointer")),this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._map.transform.renderWorldCopies&&!this._trackPointer&&(this._lngLat=Wi(this._lngLat,this._pos,this._map.transform)),!(this._trackPointer&&!te))){var Le=this._pos=this._trackPointer&&te?te:this._map.project(this._lngLat),$e=this.options.anchor,mt=Ll(this.options.offset);if(!$e){var jt=this._container.offsetWidth,_r=this._container.offsetHeight,Nr;Le.y+mt.bottom.y<_r?Nr=["top"]:Le.y>this._map.transform.height-_r?Nr=["bottom"]:Nr=[],Le.xthis._map.transform.width-jt/2&&Nr.push("right"),Nr.length===0?$e="bottom":$e=Nr.join("-")}var pr=Le.add(mt[$e]).round();r.setTransform(this._container,mn[$e]+" translate("+pr.x+"px,"+pr.y+"px)"),Rn(this._container,$e,"popup")}},Y.prototype._focusFirstElement=function(){if(!(!this.options.focusAfterOpen||!this._container)){var te=this._container.querySelector(bl);te&&te.focus()}},Y.prototype._onClose=function(){this.remove()},Y}(e.Evented);function Ll(ve){if(ve)if(typeof ve=="number"){var Y=Math.round(Math.sqrt(.5*Math.pow(ve,2)));return{center:new e.Point(0,0),top:new e.Point(0,ve),"top-left":new e.Point(Y,Y),"top-right":new e.Point(-Y,Y),bottom:new e.Point(0,-ve),"bottom-left":new e.Point(Y,-Y),"bottom-right":new e.Point(-Y,-Y),left:new e.Point(ve,0),right:new e.Point(-ve,0)}}else if(ve instanceof e.Point||Array.isArray(ve)){var ye=e.Point.convert(ve);return{center:ye,top:ye,"top-left":ye,"top-right":ye,bottom:ye,"bottom-left":ye,"bottom-right":ye,left:ye,right:ye}}else return{center:e.Point.convert(ve.center||[0,0]),top:e.Point.convert(ve.top||[0,0]),"top-left":e.Point.convert(ve["top-left"]||[0,0]),"top-right":e.Point.convert(ve["top-right"]||[0,0]),bottom:e.Point.convert(ve.bottom||[0,0]),"bottom-left":e.Point.convert(ve["bottom-left"]||[0,0]),"bottom-right":e.Point.convert(ve["bottom-right"]||[0,0]),left:e.Point.convert(ve.left||[0,0]),right:e.Point.convert(ve.right||[0,0])};else return Ll(new e.Point(0,0))}var Io={version:e.version,supported:t,setRTLTextPlugin:e.setRTLTextPlugin,getRTLTextPluginStatus:e.getRTLTextPluginStatus,Map:ja,NavigationControl:Ai,GeolocateControl:xl,AttributionControl:zi,ScaleControl:Xl,FullscreenControl:Os,Popup:Xn,Marker:Ii,Style:Ol,LngLat:e.LngLat,LngLatBounds:e.LngLatBounds,Point:e.Point,MercatorCoordinate:e.MercatorCoordinate,Evented:e.Evented,config:e.config,prewarm:on,clearPrewarmedResources:kt,get accessToken(){return e.config.ACCESS_TOKEN},set accessToken(ve){e.config.ACCESS_TOKEN=ve},get baseApiUrl(){return e.config.API_URL},set baseApiUrl(ve){e.config.API_URL=ve},get workerCount(){return ri.workerCount},set workerCount(ve){ri.workerCount=ve},get maxParallelImageRequests(){return e.config.MAX_PARALLEL_IMAGE_REQUESTS},set maxParallelImageRequests(ve){e.config.MAX_PARALLEL_IMAGE_REQUESTS=ve},clearStorage:function(Y){e.clearTileCache(Y)},workerUrl:""};return Io}),A})}}),gV=Xe({"src/plots/mapbox/layers.js"(Z,q){"use strict";var d=ua(),x=hu().sanitizeHTML,A=M6(),E=im();function e(n,i){this.subplot=n,this.uid=n.uid+"-"+i,this.index=i,this.idSource="source-"+this.uid,this.idLayer=E.layoutLayerPrefix+this.uid,this.sourceType=null,this.source=null,this.layerType=null,this.below=null,this.visible=!1}var t=e.prototype;t.update=function(i){this.visible?this.needsNewImage(i)?this.updateImage(i):this.needsNewSource(i)?(this.removeLayer(),this.updateSource(i),this.updateLayer(i)):this.needsNewLayer(i)?this.updateLayer(i):this.updateStyle(i):(this.updateSource(i),this.updateLayer(i)),this.visible=r(i)},t.needsNewImage=function(n){var i=this.subplot.map;return i.getSource(this.idSource)&&this.sourceType==="image"&&n.sourcetype==="image"&&(this.source!==n.source||JSON.stringify(this.coordinates)!==JSON.stringify(n.coordinates))},t.needsNewSource=function(n){return this.sourceType!==n.sourcetype||JSON.stringify(this.source)!==JSON.stringify(n.source)||this.layerType!==n.type},t.needsNewLayer=function(n){return this.layerType!==n.type||this.below!==this.subplot.belowLookup["layout-"+this.index]},t.lookupBelow=function(){return this.subplot.belowLookup["layout-"+this.index]},t.updateImage=function(n){var i=this.subplot.map;i.getSource(this.idSource).updateImage({url:n.source,coordinates:n.coordinates});var s=this.findFollowingMapboxLayerId(this.lookupBelow());s!==null&&this.subplot.map.moveLayer(this.idLayer,s)},t.updateSource=function(n){var i=this.subplot.map;if(i.getSource(this.idSource)&&i.removeSource(this.idSource),this.sourceType=n.sourcetype,this.source=n.source,!!r(n)){var s=a(n);i.addSource(this.idSource,s)}},t.findFollowingMapboxLayerId=function(n){if(n==="traces")for(var i=this.subplot.getMapLayers(),s=0;s0){for(var s=0;s0}function o(n){var i={},s={};switch(n.type){case"circle":d.extendFlat(s,{"circle-radius":n.circle.radius,"circle-color":n.color,"circle-opacity":n.opacity});break;case"line":d.extendFlat(s,{"line-width":n.line.width,"line-color":n.color,"line-opacity":n.opacity,"line-dasharray":n.line.dash});break;case"fill":d.extendFlat(s,{"fill-color":n.color,"fill-outline-color":n.fill.outlinecolor,"fill-opacity":n.opacity});break;case"symbol":var h=n.symbol,c=A(h.textposition,h.iconsize);d.extendFlat(i,{"icon-image":h.icon+"-15","icon-size":h.iconsize/10,"text-field":h.text,"text-size":h.textfont.size,"text-anchor":c.anchor,"text-offset":c.offset,"symbol-placement":h.placement}),d.extendFlat(s,{"icon-color":n.color,"text-color":h.textfont.color,"text-opacity":n.opacity});break;case"raster":d.extendFlat(s,{"raster-fade-duration":0,"raster-opacity":n.opacity});break}return{layout:i,paint:s}}function a(n){var i=n.sourcetype,s=n.source,h={type:i},c;return i==="geojson"?c="data":i==="vector"?c=typeof s=="string"?"url":"tiles":i==="raster"?(c="tiles",h.tileSize=256):i==="image"&&(c="url",h.coordinates=n.coordinates),h[c]=s,n.sourceattribution&&(h.attribution=x(n.sourceattribution)),h}q.exports=function(i,s,h){var c=new e(i,s);return c.update(h),c}}}),yV=Xe({"src/plots/mapbox/mapbox.js"(Z,q){"use strict";var d=E6(),x=ua(),A=m0(),E=no(),e=Ho(),t=Ap(),r=tf(),o=Jd(),a=o.drawMode,n=o.selectMode,i=Tf().prepSelect,s=Tf().clearOutline,h=Tf().clearSelectionsCache,c=Tf().selectOnClick,m=im(),v=gV();function T(y,b){this.id=b,this.gd=y;var p=y._fullLayout,u=y._context;this.container=p._glcontainer.node(),this.isStatic=u.staticPlot,this.uid=p._uid+"-"+this.id,this.div=null,this.xaxis=null,this.yaxis=null,this.createFramework(p),this.map=null,this.accessToken=null,this.styleObj=null,this.traceHash={},this.layerList=[],this.belowLookup={},this.dragging=!1,this.wheeling=!1}var l=T.prototype;l.plot=function(y,b,p){var u=this,g=b[u.id];u.map&&g.accesstoken!==u.accessToken&&(u.map.remove(),u.map=null,u.styleObj=null,u.traceHash={},u.layerList=[]);var f;u.map?f=new Promise(function(P,L){u.updateMap(y,b,P,L)}):f=new Promise(function(P,L){u.createMap(y,b,P,L)}),p.push(f)},l.createMap=function(y,b,p,u){var g=this,f=b[g.id],P=g.styleObj=w(f.style,b);g.accessToken=f.accesstoken;var L=f.bounds,z=L?[[L.west,L.south],[L.east,L.north]]:null,F=g.map=new d.Map({container:g.div,style:P.style,center:M(f.center),zoom:f.zoom,bearing:f.bearing,pitch:f.pitch,maxBounds:z,interactive:!g.isStatic,preserveDrawingBuffer:g.isStatic,doubleClickZoom:!1,boxZoom:!1,attributionControl:!1}).addControl(new d.AttributionControl({compact:!0}));F._canvas.style.left="0px",F._canvas.style.top="0px",g.rejectOnError(u),g.isStatic||g.initFx(y,b);var B=[];B.push(new Promise(function(O){F.once("load",O)})),B=B.concat(A.fetchTraceGeoData(y)),Promise.all(B).then(function(){g.fillBelowLookup(y,b),g.updateData(y),g.updateLayout(b),g.resolveOnRender(p)}).catch(u)},l.updateMap=function(y,b,p,u){var g=this,f=g.map,P=b[this.id];g.rejectOnError(u);var L=[],z=w(P.style,b);JSON.stringify(g.styleObj)!==JSON.stringify(z)&&(g.styleObj=z,f.setStyle(z.style),g.traceHash={},L.push(new Promise(function(F){f.once("styledata",F)}))),L=L.concat(A.fetchTraceGeoData(y)),Promise.all(L).then(function(){g.fillBelowLookup(y,b),g.updateData(y),g.updateLayout(b),g.resolveOnRender(p)}).catch(u)},l.fillBelowLookup=function(y,b){var p=b[this.id],u=p.layers,g,f,P=this.belowLookup={},L=!1;for(g=0;g1)for(g=0;g-1&&c(z.originalEvent,u,[p.xaxis],[p.yaxis],p.id,L),F.indexOf("event")>-1&&r.click(u,z.originalEvent)}}},l.updateFx=function(y){var b=this,p=b.map,u=b.gd;if(b.isStatic)return;function g(z){var F=b.map.unproject(z);return[F.lng,F.lat]}var f=y.dragmode,P;P=function(z,F){if(F.isRect){var B=z.range={};B[b.id]=[g([F.xmin,F.ymin]),g([F.xmax,F.ymax])]}else{var O=z.lassoPoints={};O[b.id]=F.map(g)}};var L=b.dragOptions;b.dragOptions=x.extendDeep(L||{},{dragmode:y.dragmode,element:b.div,gd:u,plotinfo:{id:b.id,domain:y[b.id].domain,xaxis:b.xaxis,yaxis:b.yaxis,fillRangeItems:P},xaxes:[b.xaxis],yaxes:[b.yaxis],subplot:b.id}),p.off("click",b.onClickInPanHandler),n(f)||a(f)?(p.dragPan.disable(),p.on("zoomstart",b.clearOutline),b.dragOptions.prepFn=function(z,F,B){i(z,F,B,b.dragOptions,f)},t.init(b.dragOptions)):(p.dragPan.enable(),p.off("zoomstart",b.clearOutline),b.div.onmousedown=null,b.div.ontouchstart=null,b.div.removeEventListener("touchstart",b.div._ontouchstart),b.onClickInPanHandler=b.onClickInPanFn(b.dragOptions),p.on("click",b.onClickInPanHandler))},l.updateFramework=function(y){var b=y[this.id].domain,p=y._size,u=this.div.style;u.width=p.w*(b.x[1]-b.x[0])+"px",u.height=p.h*(b.y[1]-b.y[0])+"px",u.left=p.l+b.x[0]*p.w+"px",u.top=p.t+(1-b.y[1])*p.h+"px",this.xaxis._offset=p.l+b.x[0]*p.w,this.xaxis._length=p.w*(b.x[1]-b.x[0]),this.yaxis._offset=p.t+(1-b.y[1])*p.h,this.yaxis._length=p.h*(b.y[1]-b.y[0])},l.updateLayers=function(y){var b=y[this.id],p=b.layers,u=this.layerList,g;if(p.length!==u.length){for(g=0;gB/2){var O=P.split("|").join("
");z.text(O).attr("data-unformatted",O).call(o.convertToTspans,v),F=r.bBox(z.node())}z.attr("transform",x(-3,-F.height+8)),L.insert("rect",".static-attribution").attr({x:-F.width-6,y:-F.height-3,width:F.width+6,height:F.height+3,fill:"rgba(255, 255, 255, 0.75)"});var I=1;F.width+6>B&&(I=B/(F.width+6));var N=[_.l+_.w*M.x[1],_.t+_.h*(1-M.y[0])];L.attr("transform",x(N[0],N[1])+A(I))}};function c(v,T){var l=v._fullLayout,_=v._context;if(_.mapboxAccessToken==="")return"";for(var w=[],S=[],M=!1,y=!1,b=0;b1&&d.warn(i.multipleTokensErrorMsg),w[0]):(S.length&&d.log(["Listed mapbox access token(s)",S.join(","),"but did not use a Mapbox map style, ignoring token(s)."].join(" ")),"")}function m(v){return typeof v=="string"&&(i.styleValuesMapbox.indexOf(v)!==-1||v.indexOf("mapbox://")===0||v.indexOf("stamen")===0)}Z.updateFx=function(v){for(var T=v._fullLayout,l=T._subplots[n],_=0;_=0;o--)t.removeLayer(r[o][1])},e.dispose=function(){var t=this.subplot.map;this._removeLayers(),t.removeSource(this.sourceId)},q.exports=function(r,o){var a=o[0].trace,n=new E(r,a.uid),i=n.sourceId,s=d(o),h=n.below=r.belowLookup["trace-"+a.uid];return r.map.addSource(i,{type:"geojson",data:s.geojson}),n._addLayers(s,h),o[0].trace._glTrace=n,n}}}),AV=Xe({"src/traces/choroplethmapbox/index.js"(Z,q){"use strict";var d=["*choroplethmapbox* trace is deprecated!","Please consider switching to the *choroplethmap* trace type and `map` subplots.","Learn more at: https://plotly.com/python/maplibre-migration/","as well as https://plotly.com/javascript/maplibre-migration/"].join(" ");q.exports={attributes:k6(),supplyDefaults:wV(),colorbar:i0(),calc:lT(),plot:TV(),hoverPoints:cT(),eventData:fT(),selectPoints:hT(),styleOnSelect:function(x,A){if(A){var E=A[0].trace;E._glTrace.updateOnSelect(A)}},getBelow:function(x,A){for(var E=A.getMapLayers(),e=E.length-2;e>=0;e--){var t=E[e].id;if(typeof t=="string"&&t.indexOf("water")===0){for(var r=e+1;r0?+v[c]:0),h.push({type:"Feature",geometry:{type:"Point",coordinates:w},properties:S})}}var y=E.extractOpts(a),b=y.reversescale?E.flipScale(y.colorscale):y.colorscale,p=b[0][1],u=A.opacity(p)<1?p:A.addOpacity(p,0),g=["interpolate",["linear"],["heatmap-density"],0,u];for(c=1;c=0;r--)e.removeLayer(t[r][1])},E.dispose=function(){var e=this.subplot.map;this._removeLayers(),e.removeSource(this.sourceId)},q.exports=function(t,r){var o=r[0].trace,a=new A(t,o.uid),n=a.sourceId,i=d(r),s=a.below=t.belowLookup["trace-"+o.uid];return t.map.addSource(n,{type:"geojson",data:i.geojson}),a._addLayers(i,s),a}}}),LV=Xe({"src/traces/densitymapbox/hover.js"(Z,q){"use strict";var d=Ho(),x=ST().hoverPoints,A=ST().getExtraText;q.exports=function(e,t,r){var o=x(e,t,r);if(o){var a=o[0],n=a.cd,i=n[0].trace,s=n[a.index];if(delete a.color,"z"in s){var h=a.subplot.mockAxis;a.z=s.z,a.zLabel=d.tickText(h,h.c2l(s.z),"hover").text}return a.extraText=A(i,s,n[0].t.labels),[a]}}}}),PV=Xe({"src/traces/densitymapbox/event_data.js"(Z,q){"use strict";q.exports=function(x,A){return x.lon=A.lon,x.lat=A.lat,x.z=A.z,x}}}),IV=Xe({"src/traces/densitymapbox/index.js"(Z,q){"use strict";var d=["*densitymapbox* trace is deprecated!","Please consider switching to the *densitymap* trace type and `map` subplots.","Learn more at: https://plotly.com/python/maplibre-migration/","as well as https://plotly.com/javascript/maplibre-migration/"].join(" ");q.exports={attributes:L6(),supplyDefaults:MV(),colorbar:i0(),formatLabels:S6(),calc:EV(),plot:CV(),hoverPoints:LV(),eventData:PV(),getBelow:function(x,A){for(var 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Jt{constructor(D,K,he,ke=1,qe=!0){this.r=D,this.g=K,this.b=he,this.a=ke,qe||(this.r*=ke,this.g*=ke,this.b*=ke,ke||this.overwriteGetter("rgb",[D,K,he,ke]))}static parse(D){if(D instanceof Jt)return D;if(typeof D!="string")return;let K=function(he){if((he=he.toLowerCase().trim())==="transparent")return[0,0,0,0];let ke=Zt[he];if(ke){let[We,ct,Mt]=ke;return[We/255,ct/255,Mt/255,1]}if(he.startsWith("#")&&/^#(?:[0-9a-f]{3,4}|[0-9a-f]{6}|[0-9a-f]{8})$/.test(he)){let We=he.length<6?1:2,ct=1;return[di(he.slice(ct,ct+=We)),di(he.slice(ct,ct+=We)),di(he.slice(ct,ct+=We)),di(he.slice(ct,ct+We)||"ff")]}if(he.startsWith("rgb")){let We=he.match(/^rgba?\(\s*([\de.+-]+)(%)?(?:\s+|\s*(,)\s*)([\de.+-]+)(%)?(?:\s+|\s*(,)\s*)([\de.+-]+)(%)?(?:\s*([,\/])\s*([\de.+-]+)(%)?)?\s*\)$/);if(We){let[ct,Mt,Ut,nr,Sr,Or,Hr,oa,pa,qa,Ja,Hi]=We,_i=[nr||" ",Hr||" ",qa].join("");if(_i===" "||_i===" /"||_i===",,"||_i===",,,"){let qi=[Ut,Or,pa].join(""),en=qi==="%%%"?100:qi===""?255:0;if(en){let 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this.overwriteGetter("lab",ha(this.rgb))}overwriteGetter(D,K){return Object.defineProperty(this,D,{value:K}),K}toString(){let[D,K,he,ke]=this.rgb;return`rgba(${[D,K,he].map(qe=>Math.round(255*qe)).join(",")},${ke})`}}Jt.black=new Jt(0,0,0,1),Jt.white=new Jt(1,1,1,1),Jt.transparent=new Jt(0,0,0,0),Jt.red=new Jt(1,0,0,1);class Br{constructor(D,K,he){this.sensitivity=D?K?"variant":"case":K?"accent":"base",this.locale=he,this.collator=new Intl.Collator(this.locale?this.locale:[],{sensitivity:this.sensitivity,usage:"search"})}compare(D,K){return this.collator.compare(D,K)}resolvedLocale(){return new Intl.Collator(this.locale?this.locale:[]).resolvedOptions().locale}}class ta{constructor(D,K,he,ke,qe){this.text=D,this.image=K,this.scale=he,this.fontStack=ke,this.textColor=qe}}class aa{constructor(D){this.sections=D}static fromString(D){return new aa([new ta(D,null,null,null,null)])}isEmpty(){return 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aa.fromString(rn(this.args[0].evaluate(D)));case"resolvedImage":return Ya.fromString(rn(this.args[0].evaluate(D)));default:return rn(this.args[0].evaluate(D))}}eachChild(D){this.args.forEach(D)}outputDefined(){return this.args.every(D=>D.outputDefined())}}let kr=["Unknown","Point","LineString","Polygon"];class Dr{constructor(){this.globals=null,this.feature=null,this.featureState=null,this.formattedSection=null,this._parseColorCache={},this.availableImages=null,this.canonical=null}id(){return this.feature&&"id"in this.feature?this.feature.id:null}geometryType(){return this.feature?typeof this.feature.type=="number"?kr[this.feature.type]:this.feature.type:null}geometry(){return this.feature&&"geometry"in this.feature?this.feature.geometry:null}canonicalID(){return this.canonical}properties(){return this.feature&&this.feature.properties||{}}parseColor(D){let K=this._parseColorCache[D];return K||(K=this._parseColorCache[D]=Jt.parse(D)),K}}class ra{constructor(D,K,he=[],ke,qe=new 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he[K]}eachChild(D){D(this.index),D(this.input)}outputDefined(){return!1}}class Cr{constructor(D,K){this.type=Lt,this.needle=D,this.haystack=K}static parse(D,K){if(D.length!==3)return K.error(`Expected 2 arguments, but found ${D.length-1} instead.`);let he=K.parse(D[1],1,Ar),ke=K.parse(D[2],2,Ar);return he&&ke?je(he.type,[Lt,Pt,Qe,st,Ar])?new Cr(he,ke):K.error(`Expected first argument to be of type boolean, string, number or null, but found ${Ke(he.type)} instead`):null}evaluate(D){let K=this.needle.evaluate(D),he=this.haystack.evaluate(D);if(!he)return!1;if(!Ce(K,["boolean","string","number","null"]))throw new kt(`Expected first argument to be of type boolean, string, number or null, but found ${Ke(Da(K))} instead.`);if(!Ce(he,["string","array"]))throw new kt(`Expected second argument to be of type array or string, but found ${Ke(Da(he))} instead.`);return he.indexOf(K)>=0}eachChild(D){D(this.needle),D(this.haystack)}outputDefined(){return!0}}class Xr{constructor(D,K,he){this.type=Qe,this.needle=D,this.haystack=K,this.fromIndex=he}static parse(D,K){if(D.length<=2||D.length>=5)return K.error(`Expected 3 or 4 arguments, but found ${D.length-1} instead.`);let he=K.parse(D[1],1,Ar),ke=K.parse(D[2],2,Ar);if(!he||!ke)return null;if(!je(he.type,[Lt,Pt,Qe,st,Ar]))return K.error(`Expected first argument to be of type boolean, string, number or null, but found ${Ke(he.type)} instead`);if(D.length===4){let qe=K.parse(D[3],3,Qe);return qe?new Xr(he,ke,qe):null}return new Xr(he,ke)}evaluate(D){let K=this.needle.evaluate(D),he=this.haystack.evaluate(D);if(!Ce(K,["boolean","string","number","null"]))throw new kt(`Expected first argument to be of type boolean, string, number or null, but found ${Ke(Da(K))} instead.`);let ke;if(this.fromIndex&&(ke=this.fromIndex.evaluate(D)),Ce(he,["string"])){let qe=he.indexOf(K,ke);return qe===-1?-1:[...he.slice(0,qe)].length}if(Ce(he,["array"]))return he.indexOf(K,ke);throw new kt(`Expected second argument to 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this._styleExpression.evaluateWithoutErrorHandling(D,K,he,ke,qe,We)}evaluate(D,K,he,ke,qe,We){return this._styleExpression.evaluate(D,K,he,ke,qe,We)}interpolationFactor(D,K,he){return this.interpolationType?Vn.interpolationFactor(this.interpolationType,D,K,he):0}}function wu(H,D){let K=il(H,D);if(K.result==="error")return K;let he=K.value.expression,ke=Nf(he);if(!ke&&!eu(D))return Wc([new Oe("","data expressions not supported")]);let qe=Ef(he,["zoom"]);if(!qe&&!qc(D))return Wc([new Oe("","zoom expressions not supported")]);let We=qf(he);return We||qe?We instanceof Oe?Wc([We]):We instanceof Vn&&!Sc(D)?Wc([new Oe("",'"interpolate" expressions cannot be used with this property')]):sc(We?new mu(ke?"camera":"composite",K.value,We.labels,We instanceof Vn?We.interpolation:void 0):new mc(ke?"constant":"source",K.value)):Wc([new Oe("",'"zoom" expression may only be used as input to a top-level "step" or "interpolate" expression.')])}class 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K=D.value.expression||D.value._styleExpression.expression;if(H.expressionContext==="property"&&H.propertyKey==="text-font"&&!K.outputDefined())return[new _e(H.key,H.value,`Invalid data expression for "${H.propertyKey}". 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found`)):Object.keys(he.values).indexOf(nl(K))===-1&&ke.push(new _e(D,K,`expected one of [${Object.keys(he.values).join(", ")}], ${JSON.stringify(K)} found`)),ke}function mf(H){return Qf(gu(H.value))?kc(fe({},H,{expressionContext:"filter",valueSpec:{value:"boolean"}})):Wu(H)}function Wu(H){let D=H.value,K=H.key;if(Ws(D)!=="array")return[new _e(K,D,`array expected, ${Ws(D)} found`)];let he=H.styleSpec,ke,qe=[];if(D.length<1)return[new _e(K,D,"filter array must have at least 1 element")];switch(qe=qe.concat(Hu({key:`${K}[0]`,value:D[0],valueSpec:he.filter_operator,style:H.style,styleSpec:H.styleSpec})),nl(D[0])){case"<":case"<=":case">":case">=":D.length>=2&&nl(D[1])==="$type"&&qe.push(new _e(K,D,`"$type" cannot be use with operator "${D[0]}"`));case"==":case"!=":D.length!==3&&qe.push(new _e(K,D,`filter array for operator "${D[0]}" must have 3 elements`));case"in":case"!in":D.length>=2&&(ke=Ws(D[1]),ke!=="string"&&qe.push(new _e(`${K}[1]`,D[1],`string expected, ${ke} found`)));for(let 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class{constructor(){this.applyArabicShaping=null,this.processBidirectionalText=null,this.processStyledBidirectionalText=null,this.pluginStatus="unavailable",this.pluginURL=null}setState(H){this.pluginStatus=H.pluginStatus,this.pluginURL=H.pluginURL}getState(){return{pluginStatus:this.pluginStatus,pluginURL:this.pluginURL}}setMethods(H){this.applyArabicShaping=H.applyArabicShaping,this.processBidirectionalText=H.processBidirectionalText,this.processStyledBidirectionalText=H.processStyledBidirectionalText}isParsed(){return this.applyArabicShaping!=null&&this.processBidirectionalText!=null&&this.processStyledBidirectionalText!=null}getPluginURL(){return this.pluginURL}getRTLTextPluginStatus(){return this.pluginStatus}};class Ls{constructor(D,K){this.zoom=D,K?(this.now=K.now,this.fadeDuration=K.fadeDuration,this.zoomHistory=K.zoomHistory,this.transition=K.transition):(this.now=0,this.fadeDuration=0,this.zoomHistory=new An,this.transition={})}isSupportedScript(D){return 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4*(Mt<.5?nr:3*(Mt-Ut)+nr-.75)}(ct))}}return qe}}class _u{constructor(D){this._properties=D,this._values=Object.create(D.defaultTransitioningPropertyValues)}possiblyEvaluate(D,K,he){let ke=new _c(this._properties);for(let qe of Object.keys(this._values))ke._values[qe]=this._values[qe].possiblyEvaluate(D,K,he);return ke}hasTransition(){for(let D of Object.keys(this._values))if(this._values[D].prior)return!0;return!1}}class Rc{constructor(D){this._properties=D,this._values=Object.create(D.defaultPropertyValues)}hasValue(D){return this._values[D].value!==void 0}getValue(D){return u(this._values[D].value)}setValue(D,K){this._values[D]=new lu(this._values[D].property,K===null?void 0:u(K))}serialize(){let D={};for(let K of Object.keys(this._values)){let he=this.getValue(K);he!==void 0&&(D[K]=he)}return D}possiblyEvaluate(D,K,he){let ke=new _c(this._properties);for(let qe of Object.keys(this._values))ke._values[qe]=this._values[qe].possiblyEvaluate(D,K,he);return ke}}class Tu{constructor(D,K,he){this.property=D,this.value=K,this.parameters=he}isConstant(){return this.value.kind==="constant"}constantOr(D){return this.value.kind==="constant"?this.value.value:D}evaluate(D,K,he,ke){return this.property.evaluate(this.value,this.parameters,D,K,he,ke)}}class _c{constructor(D){this._properties=D,this._values=Object.create(D.defaultPossiblyEvaluatedValues)}get(D){return this._values[D]}}class uo{constructor(D){this.specification=D}possiblyEvaluate(D,K){if(D.isDataDriven())throw new Error("Value should not be data driven");return D.expression.evaluate(K)}interpolate(D,K,he){let ke=Hn[this.specification.type];return ke?ke(D,K,he):D}}class Fo{constructor(D,K){this.specification=D,this.overrides=K}possiblyEvaluate(D,K,he,ke){return new Tu(this,D.expression.kind==="constant"||D.expression.kind==="camera"?{kind:"constant",value:D.expression.evaluate(K,null,{},he,ke)}:D.expression,K)}interpolate(D,K,he){if(D.value.kind!=="constant"||K.value.kind!=="constant")return D;if(D.value.value===void 0||K.value.value===void 0)return new Tu(this,{kind:"constant",value:void 0},D.parameters);let ke=Hn[this.specification.type];if(ke){let qe=ke(D.value.value,K.value.value,he);return new Tu(this,{kind:"constant",value:qe},D.parameters)}return D}evaluate(D,K,he,ke,qe,We){return D.kind==="constant"?D.value:D.evaluate(K,he,ke,qe,We)}}class Dc extends Fo{possiblyEvaluate(D,K,he,ke){if(D.value===void 0)return new Tu(this,{kind:"constant",value:void 0},K);if(D.expression.kind==="constant"){let qe=D.expression.evaluate(K,null,{},he,ke),We=D.property.specification.type==="resolvedImage"&&typeof qe!="string"?qe.name:qe,ct=this._calculate(We,We,We,K);return new Tu(this,{kind:"constant",value:ct},K)}if(D.expression.kind==="camera"){let qe=this._calculate(D.expression.evaluate({zoom:K.zoom-1}),D.expression.evaluate({zoom:K.zoom}),D.expression.evaluate({zoom:K.zoom+1}),K);return new Tu(this,{kind:"constant",value:qe},K)}return new Tu(this,D.expression,K)}evaluate(D,K,he,ke,qe,We){if(D.kind==="source"){let ct=D.evaluate(K,he,ke,qe,We);return this._calculate(ct,ct,ct,K)}return D.kind==="composite"?this._calculate(D.evaluate({zoom:Math.floor(K.zoom)-1},he,ke),D.evaluate({zoom:Math.floor(K.zoom)},he,ke),D.evaluate({zoom:Math.floor(K.zoom)+1},he,ke),K):D.value}_calculate(D,K,he,ke){return ke.zoom>ke.zoomHistory.lastIntegerZoom?{from:D,to:K}:{from:he,to:K}}interpolate(D){return D}}class uc{constructor(D){this.specification=D}possiblyEvaluate(D,K,he,ke){if(D.value!==void 0){if(D.expression.kind==="constant"){let qe=D.expression.evaluate(K,null,{},he,ke);return this._calculate(qe,qe,qe,K)}return this._calculate(D.expression.evaluate(new Ls(Math.floor(K.zoom-1),K)),D.expression.evaluate(new Ls(Math.floor(K.zoom),K)),D.expression.evaluate(new Ls(Math.floor(K.zoom+1),K)),K)}}_calculate(D,K,he,ke){return ke.zoom>ke.zoomHistory.lastIntegerZoom?{from:D,to:K}:{from:he,to:K}}interpolate(D){return D}}class Yu{constructor(D){this.specification=D}possiblyEvaluate(D,K,he,ke){return!!D.expression.evaluate(K,null,{},he,ke)}interpolate(){return!1}}class Ue{constructor(D){this.properties=D,this.defaultPropertyValues={},this.defaultTransitionablePropertyValues={},this.defaultTransitioningPropertyValues={},this.defaultPossiblyEvaluatedValues={},this.overridableProperties=[];for(let K in D){let he=D[K];he.specification.overridable&&this.overridableProperties.push(K);let ke=this.defaultPropertyValues[K]=new lu(he,void 0),qe=this.defaultTransitionablePropertyValues[K]=new Iu(he);this.defaultTransitioningPropertyValues[K]=qe.untransitioned(),this.defaultPossiblyEvaluatedValues[K]=ke.possiblyEvaluate({})}}}yi("DataDrivenProperty",Fo),yi("DataConstantProperty",uo),yi("CrossFadedDataDrivenProperty",Dc),yi("CrossFadedProperty",uc),yi("ColorRampProperty",Yu);let R="-transition";class ae extends ee{constructor(D,K){if(super(),this.id=D.id,this.type=D.type,this._featureFilter={filter:()=>!0,needGeometry:!1},D.type!=="custom"&&(this.metadata=D.metadata,this.minzoom=D.minzoom,this.maxzoom=D.maxzoom,D.type!=="background"&&(this.source=D.source,this.sourceLayer=D["source-layer"],this.filter=D.filter),K.layout&&(this._unevaluatedLayout=new Rc(K.layout)),K.paint)){this._transitionablePaint=new Zu(K.paint);for(let he in D.paint)this.setPaintProperty(he,D.paint[he],{validate:!1});for(let he in D.layout)this.setLayoutProperty(he,D.layout[he],{validate:!1});this._transitioningPaint=this._transitionablePaint.untransitioned(),this.paint=new _c(K.paint)}}getCrossfadeParameters(){return this._crossfadeParameters}getLayoutProperty(D){return D==="visibility"?this.visibility:this._unevaluatedLayout.getValue(D)}setLayoutProperty(D,K,he={}){K!=null&&this._validate(dn,`layers.${this.id}.layout.${D}`,D,K,he)||(D!=="visibility"?this._unevaluatedLayout.setValue(D,K):this.visibility=K)}getPaintProperty(D){return D.endsWith(R)?this._transitionablePaint.getTransition(D.slice(0,-11)):this._transitionablePaint.getValue(D)}setPaintProperty(D,K,he={}){if(K!=null&&this._validate(Qi,`layers.${this.id}.paint.${D}`,D,K,he))return!1;if(D.endsWith(R))return this._transitionablePaint.setTransition(D.slice(0,-11),K||void 0),!1;{let ke=this._transitionablePaint._values[D],qe=ke.property.specification["property-type"]==="cross-faded-data-driven",We=ke.value.isDataDriven(),ct=ke.value;this._transitionablePaint.setValue(D,K),this._handleSpecialPaintPropertyUpdate(D);let Mt=this._transitionablePaint._values[D].value;return Mt.isDataDriven()||We||qe||this._handleOverridablePaintPropertyUpdate(D,ct,Mt)}}_handleSpecialPaintPropertyUpdate(D){}_handleOverridablePaintPropertyUpdate(D,K,he){return!1}isHidden(D){return!!(this.minzoom&&D=this.maxzoom)||this.visibility==="none"}updateTransitions(D){this._transitioningPaint=this._transitionablePaint.transitioned(D,this._transitioningPaint)}hasTransition(){return this._transitioningPaint.hasTransition()}recalculate(D,K){D.getCrossfadeParameters&&(this._crossfadeParameters=D.getCrossfadeParameters()),this._unevaluatedLayout&&(this.layout=this._unevaluatedLayout.possiblyEvaluate(D,void 0,K)),this.paint=this._transitioningPaint.possiblyEvaluate(D,void 0,K)}serialize(){let D={id:this.id,type:this.type,source:this.source,"source-layer":this.sourceLayer,metadata:this.metadata,minzoom:this.minzoom,maxzoom:this.maxzoom,filter:this.filter,layout:this._unevaluatedLayout&&this._unevaluatedLayout.serialize(),paint:this._transitionablePaint&&this._transitionablePaint.serialize()};return this.visibility&&(D.layout=D.layout||{},D.layout.visibility=this.visibility),p(D,(K,he)=>!(K===void 0||he==="layout"&&!Object.keys(K).length||he==="paint"&&!Object.keys(K).length))}_validate(D,K,he,ke,qe={}){return(!qe||qe.validate!==!1)&&Pi(this,D.call(ui,{key:K,layerType:this.type,objectKey:he,value:ke,styleSpec:re,style:{glyphs:!0,sprite:!0}}))}is3D(){return!1}isTileClipped(){return!1}hasOffscreenPass(){return!1}resize(){}isStateDependent(){for(let D in this.paint._values){let K=this.paint.get(D);if(K instanceof Tu&&eu(K.property.specification)&&(K.value.kind==="source"||K.value.kind==="composite")&&K.value.isStateDependent)return!0}return!1}}let we={Int8:Int8Array,Uint8:Uint8Array,Int16:Int16Array,Uint16:Uint16Array,Int32:Int32Array,Uint32:Uint32Array,Float32:Float32Array};class Ae{constructor(D,K){this._structArray=D,this._pos1=K*this.size,this._pos2=this._pos1/2,this._pos4=this._pos1/4,this._pos8=this._pos1/8}}class Be{constructor(){this.isTransferred=!1,this.capacity=-1,this.resize(0)}static serialize(D,K){return D._trim(),K&&(D.isTransferred=!0,K.push(D.arrayBuffer)),{length:D.length,arrayBuffer:D.arrayBuffer}}static deserialize(D){let K=Object.create(this.prototype);return K.arrayBuffer=D.arrayBuffer,K.length=D.length,K.capacity=D.arrayBuffer.byteLength/K.bytesPerElement,K._refreshViews(),K}_trim(){this.length!==this.capacity&&(this.capacity=this.length,this.arrayBuffer=this.arrayBuffer.slice(0,this.length*this.bytesPerElement),this._refreshViews())}clear(){this.length=0}resize(D){this.reserve(D),this.length=D}reserve(D){if(D>this.capacity){this.capacity=Math.max(D,Math.floor(5*this.capacity),128),this.arrayBuffer=new ArrayBuffer(this.capacity*this.bytesPerElement);let K=this.uint8;this._refreshViews(),K&&this.uint8.set(K)}}_refreshViews(){throw new Error("_refreshViews() must be implemented by each concrete StructArray layout")}}function pt(H,D=1){let K=0,he=0;return{members:H.map(ke=>{let qe=we[ke.type].BYTES_PER_ELEMENT,We=K=At(K,Math.max(D,qe)),ct=ke.components||1;return he=Math.max(he,qe),K+=qe*ct,{name:ke.name,type:ke.type,components:ct,offset:We}}),size:At(K,Math.max(he,D)),alignment:D}}function At(H,D){return Math.ceil(H/D)*D}class Nt extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(D,K){let he=this.length;return this.resize(he+1),this.emplace(he,D,K)}emplace(D,K,he){let ke=2*D;return this.int16[ke+0]=K,this.int16[ke+1]=he,D}}Nt.prototype.bytesPerElement=4,yi("StructArrayLayout2i4",Nt);class $t extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(D,K,he){let ke=this.length;return this.resize(ke+1),this.emplace(ke,D,K,he)}emplace(D,K,he,ke){let qe=3*D;return this.int16[qe+0]=K,this.int16[qe+1]=he,this.int16[qe+2]=ke,D}}$t.prototype.bytesPerElement=6,yi("StructArrayLayout3i6",$t);class wr extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(D,K,he,ke){let qe=this.length;return this.resize(qe+1),this.emplace(qe,D,K,he,ke)}emplace(D,K,he,ke,qe){let We=4*D;return this.int16[We+0]=K,this.int16[We+1]=he,this.int16[We+2]=ke,this.int16[We+3]=qe,D}}wr.prototype.bytesPerElement=8,yi("StructArrayLayout4i8",wr);class Tr extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(D,K,he,ke,qe,We){let ct=this.length;return this.resize(ct+1),this.emplace(ct,D,K,he,ke,qe,We)}emplace(D,K,he,ke,qe,We,ct){let Mt=6*D;return this.int16[Mt+0]=K,this.int16[Mt+1]=he,this.int16[Mt+2]=ke,this.int16[Mt+3]=qe,this.int16[Mt+4]=We,this.int16[Mt+5]=ct,D}}Tr.prototype.bytesPerElement=12,yi("StructArrayLayout2i4i12",Tr);class Kr extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(D,K,he,ke,qe,We){let ct=this.length;return this.resize(ct+1),this.emplace(ct,D,K,he,ke,qe,We)}emplace(D,K,he,ke,qe,We,ct){let Mt=4*D,Ut=8*D;return this.int16[Mt+0]=K,this.int16[Mt+1]=he,this.uint8[Ut+4]=ke,this.uint8[Ut+5]=qe,this.uint8[Ut+6]=We,this.uint8[Ut+7]=ct,D}}Kr.prototype.bytesPerElement=8,yi("StructArrayLayout2i4ub8",Kr);class sa extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(D,K){let he=this.length;return this.resize(he+1),this.emplace(he,D,K)}emplace(D,K,he){let ke=2*D;return this.float32[ke+0]=K,this.float32[ke+1]=he,D}}sa.prototype.bytesPerElement=8,yi("StructArrayLayout2f8",sa);class He extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(D,K,he,ke,qe,We,ct,Mt,Ut,nr){let Sr=this.length;return this.resize(Sr+1),this.emplace(Sr,D,K,he,ke,qe,We,ct,Mt,Ut,nr)}emplace(D,K,he,ke,qe,We,ct,Mt,Ut,nr,Sr){let Or=10*D;return this.uint16[Or+0]=K,this.uint16[Or+1]=he,this.uint16[Or+2]=ke,this.uint16[Or+3]=qe,this.uint16[Or+4]=We,this.uint16[Or+5]=ct,this.uint16[Or+6]=Mt,this.uint16[Or+7]=Ut,this.uint16[Or+8]=nr,this.uint16[Or+9]=Sr,D}}He.prototype.bytesPerElement=20,yi("StructArrayLayout10ui20",He);class Je extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(D,K,he,ke,qe,We,ct,Mt,Ut,nr,Sr,Or){let Hr=this.length;return this.resize(Hr+1),this.emplace(Hr,D,K,he,ke,qe,We,ct,Mt,Ut,nr,Sr,Or)}emplace(D,K,he,ke,qe,We,ct,Mt,Ut,nr,Sr,Or,Hr){let oa=12*D;return this.int16[oa+0]=K,this.int16[oa+1]=he,this.int16[oa+2]=ke,this.int16[oa+3]=qe,this.uint16[oa+4]=We,this.uint16[oa+5]=ct,this.uint16[oa+6]=Mt,this.uint16[oa+7]=Ut,this.int16[oa+8]=nr,this.int16[oa+9]=Sr,this.int16[oa+10]=Or,this.int16[oa+11]=Hr,D}}Je.prototype.bytesPerElement=24,yi("StructArrayLayout4i4ui4i24",Je);class lt extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(D,K,he){let ke=this.length;return this.resize(ke+1),this.emplace(ke,D,K,he)}emplace(D,K,he,ke){let qe=3*D;return this.float32[qe+0]=K,this.float32[qe+1]=he,this.float32[qe+2]=ke,D}}lt.prototype.bytesPerElement=12,yi("StructArrayLayout3f12",lt);class dt extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer)}emplaceBack(D){let K=this.length;return this.resize(K+1),this.emplace(K,D)}emplace(D,K){return this.uint32[1*D+0]=K,D}}dt.prototype.bytesPerElement=4,yi("StructArrayLayout1ul4",dt);class Ct extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(D,K,he,ke,qe,We,ct,Mt,Ut){let nr=this.length;return this.resize(nr+1),this.emplace(nr,D,K,he,ke,qe,We,ct,Mt,Ut)}emplace(D,K,he,ke,qe,We,ct,Mt,Ut,nr){let Sr=10*D,Or=5*D;return this.int16[Sr+0]=K,this.int16[Sr+1]=he,this.int16[Sr+2]=ke,this.int16[Sr+3]=qe,this.int16[Sr+4]=We,this.int16[Sr+5]=ct,this.uint32[Or+3]=Mt,this.uint16[Sr+8]=Ut,this.uint16[Sr+9]=nr,D}}Ct.prototype.bytesPerElement=20,yi("StructArrayLayout6i1ul2ui20",Ct);class Tt extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(D,K,he,ke,qe,We){let ct=this.length;return this.resize(ct+1),this.emplace(ct,D,K,he,ke,qe,We)}emplace(D,K,he,ke,qe,We,ct){let Mt=6*D;return this.int16[Mt+0]=K,this.int16[Mt+1]=he,this.int16[Mt+2]=ke,this.int16[Mt+3]=qe,this.int16[Mt+4]=We,this.int16[Mt+5]=ct,D}}Tt.prototype.bytesPerElement=12,yi("StructArrayLayout2i2i2i12",Tt);class zt extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(D,K,he,ke,qe){let We=this.length;return this.resize(We+1),this.emplace(We,D,K,he,ke,qe)}emplace(D,K,he,ke,qe,We){let ct=4*D,Mt=8*D;return this.float32[ct+0]=K,this.float32[ct+1]=he,this.float32[ct+2]=ke,this.int16[Mt+6]=qe,this.int16[Mt+7]=We,D}}zt.prototype.bytesPerElement=16,yi("StructArrayLayout2f1f2i16",zt);class ur extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer)}emplaceBack(D,K,he,ke,qe,We){let ct=this.length;return this.resize(ct+1),this.emplace(ct,D,K,he,ke,qe,We)}emplace(D,K,he,ke,qe,We,ct){let Mt=16*D,Ut=4*D,nr=8*D;return this.uint8[Mt+0]=K,this.uint8[Mt+1]=he,this.float32[Ut+1]=ke,this.float32[Ut+2]=qe,this.int16[nr+6]=We,this.int16[nr+7]=ct,D}}ur.prototype.bytesPerElement=16,yi("StructArrayLayout2ub2f2i16",ur);class mr extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(D,K,he){let ke=this.length;return this.resize(ke+1),this.emplace(ke,D,K,he)}emplace(D,K,he,ke){let qe=3*D;return this.uint16[qe+0]=K,this.uint16[qe+1]=he,this.uint16[qe+2]=ke,D}}mr.prototype.bytesPerElement=6,yi("StructArrayLayout3ui6",mr);class Er extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(D,K,he,ke,qe,We,ct,Mt,Ut,nr,Sr,Or,Hr,oa,pa,qa,Ja){let Hi=this.length;return this.resize(Hi+1),this.emplace(Hi,D,K,he,ke,qe,We,ct,Mt,Ut,nr,Sr,Or,Hr,oa,pa,qa,Ja)}emplace(D,K,he,ke,qe,We,ct,Mt,Ut,nr,Sr,Or,Hr,oa,pa,qa,Ja,Hi){let _i=24*D,qi=12*D,en=48*D;return this.int16[_i+0]=K,this.int16[_i+1]=he,this.uint16[_i+2]=ke,this.uint16[_i+3]=qe,this.uint32[qi+2]=We,this.uint32[qi+3]=ct,this.uint32[qi+4]=Mt,this.uint16[_i+10]=Ut,this.uint16[_i+11]=nr,this.uint16[_i+12]=Sr,this.float32[qi+7]=Or,this.float32[qi+8]=Hr,this.uint8[en+36]=oa,this.uint8[en+37]=pa,this.uint8[en+38]=qa,this.uint32[qi+10]=Ja,this.int16[_i+22]=Hi,D}}Er.prototype.bytesPerElement=48,yi("StructArrayLayout2i2ui3ul3ui2f3ub1ul1i48",Er);class Ur extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.int16=new Int16Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(D,K,he,ke,qe,We,ct,Mt,Ut,nr,Sr,Or,Hr,oa,pa,qa,Ja,Hi,_i,qi,en,jn,Lo,_s,vo,zn,is,jo){let Bo=this.length;return this.resize(Bo+1),this.emplace(Bo,D,K,he,ke,qe,We,ct,Mt,Ut,nr,Sr,Or,Hr,oa,pa,qa,Ja,Hi,_i,qi,en,jn,Lo,_s,vo,zn,is,jo)}emplace(D,K,he,ke,qe,We,ct,Mt,Ut,nr,Sr,Or,Hr,oa,pa,qa,Ja,Hi,_i,qi,en,jn,Lo,_s,vo,zn,is,jo,Bo){let wn=32*D,cs=16*D;return this.int16[wn+0]=K,this.int16[wn+1]=he,this.int16[wn+2]=ke,this.int16[wn+3]=qe,this.int16[wn+4]=We,this.int16[wn+5]=ct,this.int16[wn+6]=Mt,this.int16[wn+7]=Ut,this.uint16[wn+8]=nr,this.uint16[wn+9]=Sr,this.uint16[wn+10]=Or,this.uint16[wn+11]=Hr,this.uint16[wn+12]=oa,this.uint16[wn+13]=pa,this.uint16[wn+14]=qa,this.uint16[wn+15]=Ja,this.uint16[wn+16]=Hi,this.uint16[wn+17]=_i,this.uint16[wn+18]=qi,this.uint16[wn+19]=en,this.uint16[wn+20]=jn,this.uint16[wn+21]=Lo,this.uint16[wn+22]=_s,this.uint32[cs+12]=vo,this.float32[cs+13]=zn,this.float32[cs+14]=is,this.uint16[wn+30]=jo,this.uint16[wn+31]=Bo,D}}Ur.prototype.bytesPerElement=64,yi("StructArrayLayout8i15ui1ul2f2ui64",Ur);class Qr extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(D){let K=this.length;return this.resize(K+1),this.emplace(K,D)}emplace(D,K){return this.float32[1*D+0]=K,D}}Qr.prototype.bytesPerElement=4,yi("StructArrayLayout1f4",Qr);class da extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(D,K,he){let ke=this.length;return this.resize(ke+1),this.emplace(ke,D,K,he)}emplace(D,K,he,ke){let qe=3*D;return this.uint16[6*D+0]=K,this.float32[qe+1]=he,this.float32[qe+2]=ke,D}}da.prototype.bytesPerElement=12,yi("StructArrayLayout1ui2f12",da);class wa extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint32=new Uint32Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(D,K,he){let ke=this.length;return this.resize(ke+1),this.emplace(ke,D,K,he)}emplace(D,K,he,ke){let qe=4*D;return this.uint32[2*D+0]=K,this.uint16[qe+2]=he,this.uint16[qe+3]=ke,D}}wa.prototype.bytesPerElement=8,yi("StructArrayLayout1ul2ui8",wa);class Fa extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(D,K){let he=this.length;return this.resize(he+1),this.emplace(he,D,K)}emplace(D,K,he){let ke=2*D;return this.uint16[ke+0]=K,this.uint16[ke+1]=he,D}}Fa.prototype.bytesPerElement=4,yi("StructArrayLayout2ui4",Fa);class fi extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.uint16=new Uint16Array(this.arrayBuffer)}emplaceBack(D){let K=this.length;return this.resize(K+1),this.emplace(K,D)}emplace(D,K){return this.uint16[1*D+0]=K,D}}fi.prototype.bytesPerElement=2,yi("StructArrayLayout1ui2",fi);class Vi extends Be{_refreshViews(){this.uint8=new Uint8Array(this.arrayBuffer),this.float32=new Float32Array(this.arrayBuffer)}emplaceBack(D,K,he,ke){let qe=this.length;return this.resize(qe+1),this.emplace(qe,D,K,he,ke)}emplace(D,K,he,ke,qe){let We=4*D;return this.float32[We+0]=K,this.float32[We+1]=he,this.float32[We+2]=ke,this.float32[We+3]=qe,D}}Vi.prototype.bytesPerElement=16,yi("StructArrayLayout4f16",Vi);class ji extends Ae{get anchorPointX(){return this._structArray.int16[this._pos2+0]}get anchorPointY(){return this._structArray.int16[this._pos2+1]}get x1(){return this._structArray.int16[this._pos2+2]}get y1(){return this._structArray.int16[this._pos2+3]}get x2(){return this._structArray.int16[this._pos2+4]}get y2(){return this._structArray.int16[this._pos2+5]}get featureIndex(){return this._structArray.uint32[this._pos4+3]}get sourceLayerIndex(){return this._structArray.uint16[this._pos2+8]}get bucketIndex(){return this._structArray.uint16[this._pos2+9]}get anchorPoint(){return new n(this.anchorPointX,this.anchorPointY)}}ji.prototype.size=20;class nn extends Ct{get(D){return new ji(this,D)}}yi("CollisionBoxArray",nn);class Sn extends Ae{get anchorX(){return this._structArray.int16[this._pos2+0]}get anchorY(){return this._structArray.int16[this._pos2+1]}get glyphStartIndex(){return this._structArray.uint16[this._pos2+2]}get numGlyphs(){return this._structArray.uint16[this._pos2+3]}get vertexStartIndex(){return this._structArray.uint32[this._pos4+2]}get lineStartIndex(){return this._structArray.uint32[this._pos4+3]}get lineLength(){return this._structArray.uint32[this._pos4+4]}get segment(){return this._structArray.uint16[this._pos2+10]}get lowerSize(){return this._structArray.uint16[this._pos2+11]}get upperSize(){return this._structArray.uint16[this._pos2+12]}get lineOffsetX(){return this._structArray.float32[this._pos4+7]}get lineOffsetY(){return this._structArray.float32[this._pos4+8]}get writingMode(){return this._structArray.uint8[this._pos1+36]}get placedOrientation(){return this._structArray.uint8[this._pos1+37]}set placedOrientation(D){this._structArray.uint8[this._pos1+37]=D}get hidden(){return this._structArray.uint8[this._pos1+38]}set hidden(D){this._structArray.uint8[this._pos1+38]=D}get crossTileID(){return this._structArray.uint32[this._pos4+10]}set crossTileID(D){this._structArray.uint32[this._pos4+10]=D}get associatedIconIndex(){return this._structArray.int16[this._pos2+22]}}Sn.prototype.size=48;class Zn extends Er{get(D){return new Sn(this,D)}}yi("PlacedSymbolArray",Zn);class On extends Ae{get anchorX(){return this._structArray.int16[this._pos2+0]}get anchorY(){return this._structArray.int16[this._pos2+1]}get rightJustifiedTextSymbolIndex(){return this._structArray.int16[this._pos2+2]}get centerJustifiedTextSymbolIndex(){return this._structArray.int16[this._pos2+3]}get leftJustifiedTextSymbolIndex(){return this._structArray.int16[this._pos2+4]}get verticalPlacedTextSymbolIndex(){return this._structArray.int16[this._pos2+5]}get placedIconSymbolIndex(){return this._structArray.int16[this._pos2+6]}get verticalPlacedIconSymbolIndex(){return this._structArray.int16[this._pos2+7]}get key(){return this._structArray.uint16[this._pos2+8]}get textBoxStartIndex(){return this._structArray.uint16[this._pos2+9]}get textBoxEndIndex(){return this._structArray.uint16[this._pos2+10]}get verticalTextBoxStartIndex(){return this._structArray.uint16[this._pos2+11]}get verticalTextBoxEndIndex(){return this._structArray.uint16[this._pos2+12]}get iconBoxStartIndex(){return this._structArray.uint16[this._pos2+13]}get iconBoxEndIndex(){return this._structArray.uint16[this._pos2+14]}get verticalIconBoxStartIndex(){return this._structArray.uint16[this._pos2+15]}get verticalIconBoxEndIndex(){return this._structArray.uint16[this._pos2+16]}get featureIndex(){return this._structArray.uint16[this._pos2+17]}get numHorizontalGlyphVertices(){return this._structArray.uint16[this._pos2+18]}get numVerticalGlyphVertices(){return this._structArray.uint16[this._pos2+19]}get numIconVertices(){return this._structArray.uint16[this._pos2+20]}get numVerticalIconVertices(){return this._structArray.uint16[this._pos2+21]}get useRuntimeCollisionCircles(){return this._structArray.uint16[this._pos2+22]}get crossTileID(){return this._structArray.uint32[this._pos4+12]}set crossTileID(D){this._structArray.uint32[this._pos4+12]=D}get textBoxScale(){return this._structArray.float32[this._pos4+13]}get collisionCircleDiameter(){return this._structArray.float32[this._pos4+14]}get textAnchorOffsetStartIndex(){return this._structArray.uint16[this._pos2+30]}get textAnchorOffsetEndIndex(){return this._structArray.uint16[this._pos2+31]}}On.prototype.size=64;class To extends Ur{get(D){return new On(this,D)}}yi("SymbolInstanceArray",To);class ss extends Qr{getoffsetX(D){return this.float32[1*D+0]}}yi("GlyphOffsetArray",ss);class Mo extends $t{getx(D){return this.int16[3*D+0]}gety(D){return this.int16[3*D+1]}gettileUnitDistanceFromAnchor(D){return this.int16[3*D+2]}}yi("SymbolLineVertexArray",Mo);class Yo extends Ae{get textAnchor(){return this._structArray.uint16[this._pos2+0]}get textOffset0(){return this._structArray.float32[this._pos4+1]}get textOffset1(){return this._structArray.float32[this._pos4+2]}}Yo.prototype.size=12;class ps extends da{get(D){return new Yo(this,D)}}yi("TextAnchorOffsetArray",ps);class sl extends Ae{get featureIndex(){return this._structArray.uint32[this._pos4+0]}get sourceLayerIndex(){return this._structArray.uint16[this._pos2+2]}get bucketIndex(){return this._structArray.uint16[this._pos2+3]}}sl.prototype.size=8;class el extends wa{get(D){return new sl(this,D)}}yi("FeatureIndexArray",el);class Qo extends Nt{}class es extends Nt{}class Rl extends Nt{}class tu extends Tr{}class Ru extends Kr{}class pu extends sa{}class Tl extends He{}class uu extends Je{}class cc extends lt{}class Gl extends dt{}class Hl extends Tt{}class de extends ur{}class ze extends mr{}class et extends Fa{}let vt=pt([{name:"a_pos",components:2,type:"Int16"}],4),{members:_t}=vt;class St{constructor(D=[]){this.segments=D}prepareSegment(D,K,he,ke){let qe=this.segments[this.segments.length-1];return D>St.MAX_VERTEX_ARRAY_LENGTH&&f(`Max vertices per segment is ${St.MAX_VERTEX_ARRAY_LENGTH}: bucket requested ${D}`),(!qe||qe.vertexLength+D>St.MAX_VERTEX_ARRAY_LENGTH||qe.sortKey!==ke)&&(qe={vertexOffset:K.length,primitiveOffset:he.length,vertexLength:0,primitiveLength:0},ke!==void 0&&(qe.sortKey=ke),this.segments.push(qe)),qe}get(){return this.segments}destroy(){for(let D of this.segments)for(let K in D.vaos)D.vaos[K].destroy()}static simpleSegment(D,K,he,ke){return new St([{vertexOffset:D,primitiveOffset:K,vertexLength:he,primitiveLength:ke,vaos:{},sortKey:0}])}}function rr(H,D){return 256*(H=w(Math.floor(H),0,255))+w(Math.floor(D),0,255)}St.MAX_VERTEX_ARRAY_LENGTH=Math.pow(2,16)-1,yi("SegmentVector",St);let Ot=pt([{name:"a_pattern_from",components:4,type:"Uint16"},{name:"a_pattern_to",components:4,type:"Uint16"},{name:"a_pixel_ratio_from",components:1,type:"Uint16"},{name:"a_pixel_ratio_to",components:1,type:"Uint16"}]);var gr={exports:{}},Vr={exports:{}};Vr.exports=function(H,D){var K,he,ke,qe,We,ct,Mt,Ut;for(he=H.length-(K=3&H.length),ke=D,We=3432918353,ct=461845907,Ut=0;Ut>>16)*We&65535)<<16)&4294967295)<<15|Mt>>>17))*ct+(((Mt>>>16)*ct&65535)<<16)&4294967295)<<13|ke>>>19))+((5*(ke>>>16)&65535)<<16)&4294967295))+((58964+(qe>>>16)&65535)<<16);switch(Mt=0,K){case 3:Mt^=(255&H.charCodeAt(Ut+2))<<16;case 2:Mt^=(255&H.charCodeAt(Ut+1))<<8;case 1:ke^=Mt=(65535&(Mt=(Mt=(65535&(Mt^=255&H.charCodeAt(Ut)))*We+(((Mt>>>16)*We&65535)<<16)&4294967295)<<15|Mt>>>17))*ct+(((Mt>>>16)*ct&65535)<<16)&4294967295}return ke^=H.length,ke=2246822507*(65535&(ke^=ke>>>16))+((2246822507*(ke>>>16)&65535)<<16)&4294967295,ke=3266489909*(65535&(ke^=ke>>>13))+((3266489909*(ke>>>16)&65535)<<16)&4294967295,(ke^=ke>>>16)>>>0};var Wr=Vr.exports,xa={exports:{}};xa.exports=function(H,D){for(var K,he=H.length,ke=D^he,qe=0;he>=4;)K=1540483477*(65535&(K=255&H.charCodeAt(qe)|(255&H.charCodeAt(++qe))<<8|(255&H.charCodeAt(++qe))<<16|(255&H.charCodeAt(++qe))<<24))+((1540483477*(K>>>16)&65535)<<16),ke=1540483477*(65535&ke)+((1540483477*(ke>>>16)&65535)<<16)^(K=1540483477*(65535&(K^=K>>>24))+((1540483477*(K>>>16)&65535)<<16)),he-=4,++qe;switch(he){case 3:ke^=(255&H.charCodeAt(qe+2))<<16;case 2:ke^=(255&H.charCodeAt(qe+1))<<8;case 1:ke=1540483477*(65535&(ke^=255&H.charCodeAt(qe)))+((1540483477*(ke>>>16)&65535)<<16)}return ke=1540483477*(65535&(ke^=ke>>>13))+((1540483477*(ke>>>16)&65535)<<16),(ke^=ke>>>15)>>>0};var va=Wr,Qa=xa.exports;gr.exports=va,gr.exports.murmur3=va,gr.exports.murmur2=Qa;var ai=r(gr.exports);class Sa{constructor(){this.ids=[],this.positions=[],this.indexed=!1}add(D,K,he,ke){this.ids.push(Oa(D)),this.positions.push(K,he,ke)}getPositions(D){if(!this.indexed)throw new Error("Trying to get index, but feature positions are not indexed");let K=Oa(D),he=0,ke=this.ids.length-1;for(;he>1;this.ids[We]>=K?ke=We:he=We+1}let qe=[];for(;this.ids[he]===K;)qe.push({index:this.positions[3*he],start:this.positions[3*he+1],end:this.positions[3*he+2]}),he++;return qe}static serialize(D,K){let he=new Float64Array(D.ids),ke=new Uint32Array(D.positions);return Za(he,ke,0,he.length-1),K&&K.push(he.buffer,ke.buffer),{ids:he,positions:ke}}static deserialize(D){let K=new Sa;return K.ids=D.ids,K.positions=D.positions,K.indexed=!0,K}}function Oa(H){let D=+H;return!isNaN(D)&&D<=Number.MAX_SAFE_INTEGER?D:ai(String(H))}function Za(H,D,K,he){for(;K>1],qe=K-1,We=he+1;for(;;){do qe++;while(H[qe]ke);if(qe>=We)break;hi(H,qe,We),hi(D,3*qe,3*We),hi(D,3*qe+1,3*We+1),hi(D,3*qe+2,3*We+2)}We-K`u_${ke}`),this.type=he}setUniform(D,K,he){D.set(he.constantOr(this.value))}getBinding(D,K,he){return this.type==="color"?new tn(D,K):new Ia(D,K)}}class to{constructor(D,K){this.uniformNames=K.map(he=>`u_${he}`),this.patternFrom=null,this.patternTo=null,this.pixelRatioFrom=1,this.pixelRatioTo=1}setConstantPatternPositions(D,K){this.pixelRatioFrom=K.pixelRatio,this.pixelRatioTo=D.pixelRatio,this.patternFrom=K.tlbr,this.patternTo=D.tlbr}setUniform(D,K,he,ke){let qe=ke==="u_pattern_to"?this.patternTo:ke==="u_pattern_from"?this.patternFrom:ke==="u_pixel_ratio_to"?this.pixelRatioTo:ke==="u_pixel_ratio_from"?this.pixelRatioFrom:null;qe&&D.set(qe)}getBinding(D,K,he){return he.substr(0,9)==="u_pattern"?new sn(D,K):new Ia(D,K)}}class Ko{constructor(D,K,he,ke){this.expression=D,this.type=he,this.maxValue=0,this.paintVertexAttributes=K.map(qe=>({name:`a_${qe}`,type:"Float32",components:he==="color"?2:1,offset:0})),this.paintVertexArray=new ke}populatePaintArray(D,K,he,ke,qe){let We=this.paintVertexArray.length,ct=this.expression.evaluate(new Ls(0),K,{},ke,[],qe);this.paintVertexArray.resize(D),this._setPaintValue(We,D,ct)}updatePaintArray(D,K,he,ke){let qe=this.expression.evaluate({zoom:0},he,ke);this._setPaintValue(D,K,qe)}_setPaintValue(D,K,he){if(this.type==="color"){let ke=Ln(he);for(let qe=D;qe`u_${ct}_t`),this.type=he,this.useIntegerZoom=ke,this.zoom=qe,this.maxValue=0,this.paintVertexAttributes=K.map(ct=>({name:`a_${ct}`,type:"Float32",components:he==="color"?4:2,offset:0})),this.paintVertexArray=new We}populatePaintArray(D,K,he,ke,qe){let We=this.expression.evaluate(new Ls(this.zoom),K,{},ke,[],qe),ct=this.expression.evaluate(new Ls(this.zoom+1),K,{},ke,[],qe),Mt=this.paintVertexArray.length;this.paintVertexArray.resize(D),this._setPaintValue(Mt,D,We,ct)}updatePaintArray(D,K,he,ke){let qe=this.expression.evaluate({zoom:this.zoom},he,ke),We=this.expression.evaluate({zoom:this.zoom+1},he,ke);this._setPaintValue(D,K,qe,We)}_setPaintValue(D,K,he,ke){if(this.type==="color"){let qe=Ln(he),We=Ln(ke);for(let ct=D;ct`#define HAS_UNIFORM_${ke}`))}return D}getBinderAttributes(){let D=[];for(let K in this.binders){let he=this.binders[K];if(he instanceof Ko||he instanceof ao)for(let ke=0;ke!0){this.programConfigurations={};for(let ke of D)this.programConfigurations[ke.id]=new ll(ke,K,he);this.needsUpload=!1,this._featureMap=new Sa,this._bufferOffset=0}populatePaintArrays(D,K,he,ke,qe,We){for(let ct in this.programConfigurations)this.programConfigurations[ct].populatePaintArrays(D,K,ke,qe,We);K.id!==void 0&&this._featureMap.add(K.id,he,this._bufferOffset,D),this._bufferOffset=D,this.needsUpload=!0}updatePaintArrays(D,K,he,ke){for(let qe of he)this.needsUpload=this.programConfigurations[qe.id].updatePaintArrays(D,this._featureMap,K,qe,ke)||this.needsUpload}get(D){return this.programConfigurations[D]}upload(D){if(this.needsUpload){for(let K in this.programConfigurations)this.programConfigurations[K].upload(D);this.needsUpload=!1}}destroy(){for(let D in this.programConfigurations)this.programConfigurations[D].destroy()}}function _l(H,D){return{"text-opacity":["opacity"],"icon-opacity":["opacity"],"text-color":["fill_color"],"icon-color":["fill_color"],"text-halo-color":["halo_color"],"icon-halo-color":["halo_color"],"text-halo-blur":["halo_blur"],"icon-halo-blur":["halo_blur"],"text-halo-width":["halo_width"],"icon-halo-width":["halo_width"],"line-gap-width":["gapwidth"],"line-pattern":["pattern_to","pattern_from","pixel_ratio_to","pixel_ratio_from"],"fill-pattern":["pattern_to","pattern_from","pixel_ratio_to","pixel_ratio_from"],"fill-extrusion-pattern":["pattern_to","pattern_from","pixel_ratio_to","pixel_ratio_from"]}[H]||[H.replace(`${D}-`,"").replace(/-/g,"_")]}function gn(H,D,K){let he={color:{source:sa,composite:Vi},number:{source:Qr,composite:sa}},ke=function(qe){return{"line-pattern":{source:Tl,composite:Tl},"fill-pattern":{source:Tl,composite:Tl},"fill-extrusion-pattern":{source:Tl,composite:Tl}}[qe]}(H);return ke&&ke[K]||he[D][K]}yi("ConstantBinder",Yn),yi("CrossFadedConstantBinder",to),yi("SourceExpressionBinder",Ko),yi("CrossFadedCompositeBinder",Zo),yi("CompositeExpressionBinder",ao),yi("ProgramConfiguration",ll,{omit:["_buffers"]}),yi("ProgramConfigurationSet",rl);let fo=8192,fs=Math.pow(2,14)-1,vs=-fs-1;function Al(H){let D=fo/H.extent,K=H.loadGeometry();for(let he=0;heWe.x+1||MtWe.y+1)&&f("Geometry exceeds allowed extent, reduce your vector tile buffer size")}}return K}function Wl(H,D){return{type:H.type,id:H.id,properties:H.properties,geometry:D?Al(H):[]}}function Au(H,D,K,he,ke){H.emplaceBack(2*D+(he+1)/2,2*K+(ke+1)/2)}class Dl{constructor(D){this.zoom=D.zoom,this.overscaling=D.overscaling,this.layers=D.layers,this.layerIds=this.layers.map(K=>K.id),this.index=D.index,this.hasPattern=!1,this.layoutVertexArray=new es,this.indexArray=new ze,this.segments=new St,this.programConfigurations=new rl(D.layers,D.zoom),this.stateDependentLayerIds=this.layers.filter(K=>K.isStateDependent()).map(K=>K.id)}populate(D,K,he){let ke=this.layers[0],qe=[],We=null,ct=!1;ke.type==="circle"&&(We=ke.layout.get("circle-sort-key"),ct=!We.isConstant());for(let{feature:Mt,id:Ut,index:nr,sourceLayerIndex:Sr}of D){let Or=this.layers[0]._featureFilter.needGeometry,Hr=Wl(Mt,Or);if(!this.layers[0]._featureFilter.filter(new Ls(this.zoom),Hr,he))continue;let oa=ct?We.evaluate(Hr,{},he):void 0,pa={id:Ut,properties:Mt.properties,type:Mt.type,sourceLayerIndex:Sr,index:nr,geometry:Or?Hr.geometry:Al(Mt),patterns:{},sortKey:oa};qe.push(pa)}ct&&qe.sort((Mt,Ut)=>Mt.sortKey-Ut.sortKey);for(let Mt of qe){let{geometry:Ut,index:nr,sourceLayerIndex:Sr}=Mt,Or=D[nr].feature;this.addFeature(Mt,Ut,nr,he),K.featureIndex.insert(Or,Ut,nr,Sr,this.index)}}update(D,K,he){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(D,K,this.stateDependentLayers,he)}isEmpty(){return this.layoutVertexArray.length===0}uploadPending(){return!this.uploaded||this.programConfigurations.needsUpload}upload(D){this.uploaded||(this.layoutVertexBuffer=D.createVertexBuffer(this.layoutVertexArray,_t),this.indexBuffer=D.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(D),this.uploaded=!0}destroy(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())}addFeature(D,K,he,ke){for(let qe of K)for(let We of qe){let ct=We.x,Mt=We.y;if(ct<0||ct>=fo||Mt<0||Mt>=fo)continue;let Ut=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray,D.sortKey),nr=Ut.vertexLength;Au(this.layoutVertexArray,ct,Mt,-1,-1),Au(this.layoutVertexArray,ct,Mt,1,-1),Au(this.layoutVertexArray,ct,Mt,1,1),Au(this.layoutVertexArray,ct,Mt,-1,1),this.indexArray.emplaceBack(nr,nr+1,nr+2),this.indexArray.emplaceBack(nr,nr+3,nr+2),Ut.vertexLength+=4,Ut.primitiveLength+=2}this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,D,he,{},ke)}}function xc(H,D){for(let K=0;K1){if(la(H,D))return!0;for(let he=0;he1?K:K.sub(D)._mult(ke)._add(D))}function Ka(H,D){let K,he,ke,qe=!1;for(let We=0;WeD.y!=ke.y>D.y&&D.x<(ke.x-he.x)*(D.y-he.y)/(ke.y-he.y)+he.x&&(qe=!qe)}return qe}function Ti(H,D){let K=!1;for(let he=0,ke=H.length-1;heD.y!=We.y>D.y&&D.x<(We.x-qe.x)*(D.y-qe.y)/(We.y-qe.y)+qe.x&&(K=!K)}return K}function xi(H,D,K){let he=K[0],ke=K[2];if(H.xke.x&&D.x>ke.x||H.yke.y&&D.y>ke.y)return!1;let qe=P(H,D,K[0]);return qe!==P(H,D,K[1])||qe!==P(H,D,K[2])||qe!==P(H,D,K[3])}function li(H,D,K){let he=D.paint.get(H).value;return he.kind==="constant"?he.value:K.programConfigurations.get(D.id).getMaxValue(H)}function _n(H){return Math.sqrt(H[0]*H[0]+H[1]*H[1])}function zi(H,D,K,he,ke){if(!D[0]&&!D[1])return H;let qe=n.convert(D)._mult(ke);K==="viewport"&&qe._rotate(-he);let We=[];for(let ct=0;ctja(qa,pa))}(Ut,Mt),Hr=Sr?nr*ct:nr;for(let oa of ke)for(let pa of oa){let qa=Sr?pa:ja(pa,Mt),Ja=Hr,Hi=pn([],[pa.x,pa.y,0,1],Mt);if(this.paint.get("circle-pitch-scale")==="viewport"&&this.paint.get("circle-pitch-alignment")==="map"?Ja*=Hi[3]/We.cameraToCenterDistance:this.paint.get("circle-pitch-scale")==="map"&&this.paint.get("circle-pitch-alignment")==="viewport"&&(Ja*=We.cameraToCenterDistance/Hi[3]),it(Or,qa,Ja))return!0}return!1}}function ja(H,D){let K=pn([],[H.x,H.y,0,1],D);return new n(K[0]/K[3],K[1]/K[3])}class Yi extends Dl{}let Ri;yi("HeatmapBucket",Yi,{omit:["layers"]});var Ai={get paint(){return Ri=Ri||new Ue({"heatmap-radius":new Fo(re.paint_heatmap["heatmap-radius"]),"heatmap-weight":new Fo(re.paint_heatmap["heatmap-weight"]),"heatmap-intensity":new uo(re.paint_heatmap["heatmap-intensity"]),"heatmap-color":new Yu(re.paint_heatmap["heatmap-color"]),"heatmap-opacity":new uo(re.paint_heatmap["heatmap-opacity"])})}};function wi(H,{width:D,height:K},he,ke){if(ke){if(ke instanceof Uint8ClampedArray)ke=new Uint8Array(ke.buffer);else if(ke.length!==D*K*he)throw new RangeError(`mismatched image size. expected: ${ke.length} but got: ${D*K*he}`)}else ke=new Uint8Array(D*K*he);return H.width=D,H.height=K,H.data=ke,H}function Wi(H,{width:D,height:K},he){if(D===H.width&&K===H.height)return;let ke=wi({},{width:D,height:K},he);mn(H,ke,{x:0,y:0},{x:0,y:0},{width:Math.min(H.width,D),height:Math.min(H.height,K)},he),H.width=D,H.height=K,H.data=ke.data}function mn(H,D,K,he,ke,qe){if(ke.width===0||ke.height===0)return D;if(ke.width>H.width||ke.height>H.height||K.x>H.width-ke.width||K.y>H.height-ke.height)throw new RangeError("out of range source coordinates for image copy");if(ke.width>D.width||ke.height>D.height||he.x>D.width-ke.width||he.y>D.height-ke.height)throw new RangeError("out of range destination coordinates for image copy");let We=H.data,ct=D.data;if(We===ct)throw new Error("srcData equals dstData, so image is already copied");for(let Mt=0;Mt{D[H.evaluationKey]=Mt;let Ut=H.expression.evaluate(D);ke.data[We+ct+0]=Math.floor(255*Ut.r/Ut.a),ke.data[We+ct+1]=Math.floor(255*Ut.g/Ut.a),ke.data[We+ct+2]=Math.floor(255*Ut.b/Ut.a),ke.data[We+ct+3]=Math.floor(255*Ut.a)};if(H.clips)for(let We=0,ct=0;We80*K){ct=1/0,Mt=1/0;let nr=-1/0,Sr=-1/0;for(let Or=K;Ornr&&(nr=Hr),oa>Sr&&(Sr=oa)}Ut=Math.max(nr-ct,Sr-Mt),Ut=Ut!==0?32767/Ut:0}return ru(qe,We,K,ct,Mt,Ut,0),We}function Sl(H,D,K,he,ke){let qe;if(ke===function(We,ct,Mt,Ut){let nr=0;for(let Sr=ct,Or=Mt-Ut;Sr0)for(let We=D;We=D;We-=he)qe=pr(We/he|0,H[We],H[We+1],qe);return qe&&Le(qe,qe.next)&&(yt(qe),qe=qe.next),qe}function Cl(H,D){if(!H)return H;D||(D=H);let K,he=H;do if(K=!1,he.steiner||!Le(he,he.next)&&Ge(he.prev,he,he.next)!==0)he=he.next;else{if(yt(he),he=D=he.prev,he===he.next)break;K=!0}while(K||he!==D);return D}function ru(H,D,K,he,ke,qe,We){if(!H)return;!We&&qe&&function(Mt,Ut,nr,Sr){let Or=Mt;do Or.z===0&&(Or.z=Y(Or.x,Or.y,Ut,nr,Sr)),Or.prevZ=Or.prev,Or.nextZ=Or.next,Or=Or.next;while(Or!==Mt);Or.prevZ.nextZ=null,Or.prevZ=null,function(Hr){let oa,pa=1;do{let qa,Ja=Hr;Hr=null;let Hi=null;for(oa=0;Ja;){oa++;let _i=Ja,qi=0;for(let jn=0;jn0||en>0&&_i;)qi!==0&&(en===0||!_i||Ja.z<=_i.z)?(qa=Ja,Ja=Ja.nextZ,qi--):(qa=_i,_i=_i.nextZ,en--),Hi?Hi.nextZ=qa:Hr=qa,qa.prevZ=Hi,Hi=qa;Ja=_i}Hi.nextZ=null,pa*=2}while(oa>1)}(Or)}(H,he,ke,qe);let ct=H;for(;H.prev!==H.next;){let Mt=H.prev,Ut=H.next;if(qe?pl(H,he,ke,qe):Os(H))D.push(Mt.i,H.i,Ut.i),yt(H),H=Ut.next,ct=Ut.next;else if((H=Ut)===ct){We?We===1?ru(H=bl(Cl(H),D),D,K,he,ke,qe,2):We===2&&Xn(H,D,K,he,ke,qe):ru(Cl(H),D,K,he,ke,qe,1);break}}}function Os(H){let D=H.prev,K=H,he=H.next;if(Ge(D,K,he)>=0)return!1;let ke=D.x,qe=K.x,We=he.x,ct=D.y,Mt=K.y,Ut=he.y,nr=keqe?ke>We?ke:We:qe>We?qe:We,Hr=ct>Mt?ct>Ut?ct:Ut:Mt>Ut?Mt:Ut,oa=he.next;for(;oa!==D;){if(oa.x>=nr&&oa.x<=Or&&oa.y>=Sr&&oa.y<=Hr&&te(ke,ct,qe,Mt,We,Ut,oa.x,oa.y)&&Ge(oa.prev,oa,oa.next)>=0)return!1;oa=oa.next}return!0}function pl(H,D,K,he){let ke=H.prev,qe=H,We=H.next;if(Ge(ke,qe,We)>=0)return!1;let ct=ke.x,Mt=qe.x,Ut=We.x,nr=ke.y,Sr=qe.y,Or=We.y,Hr=ctMt?ct>Ut?ct:Ut:Mt>Ut?Mt:Ut,qa=nr>Sr?nr>Or?nr:Or:Sr>Or?Sr:Or,Ja=Y(Hr,oa,D,K,he),Hi=Y(pa,qa,D,K,he),_i=H.prevZ,qi=H.nextZ;for(;_i&&_i.z>=Ja&&qi&&qi.z<=Hi;){if(_i.x>=Hr&&_i.x<=pa&&_i.y>=oa&&_i.y<=qa&&_i!==ke&&_i!==We&&te(ct,nr,Mt,Sr,Ut,Or,_i.x,_i.y)&&Ge(_i.prev,_i,_i.next)>=0||(_i=_i.prevZ,qi.x>=Hr&&qi.x<=pa&&qi.y>=oa&&qi.y<=qa&&qi!==ke&&qi!==We&&te(ct,nr,Mt,Sr,Ut,Or,qi.x,qi.y)&&Ge(qi.prev,qi,qi.next)>=0))return!1;qi=qi.nextZ}for(;_i&&_i.z>=Ja;){if(_i.x>=Hr&&_i.x<=pa&&_i.y>=oa&&_i.y<=qa&&_i!==ke&&_i!==We&&te(ct,nr,Mt,Sr,Ut,Or,_i.x,_i.y)&&Ge(_i.prev,_i,_i.next)>=0)return!1;_i=_i.prevZ}for(;qi&&qi.z<=Hi;){if(qi.x>=Hr&&qi.x<=pa&&qi.y>=oa&&qi.y<=qa&&qi!==ke&&qi!==We&&te(ct,nr,Mt,Sr,Ut,Or,qi.x,qi.y)&&Ge(qi.prev,qi,qi.next)>=0)return!1;qi=qi.nextZ}return!0}function bl(H,D){let K=H;do{let he=K.prev,ke=K.next.next;!Le(he,ke)&&$e(he,K,K.next,ke)&&_r(he,ke)&&_r(ke,he)&&(D.push(he.i,K.i,ke.i),yt(K),yt(K.next),K=H=ke),K=K.next}while(K!==H);return Cl(K)}function Xn(H,D,K,he,ke,qe){let We=H;do{let ct=We.next.next;for(;ct!==We.prev;){if(We.i!==ct.i&&me(We,ct)){let Mt=Nr(We,ct);return We=Cl(We,We.next),Mt=Cl(Mt,Mt.next),ru(We,D,K,he,ke,qe,0),void ru(Mt,D,K,he,ke,qe,0)}ct=ct.next}We=We.next}while(We!==H)}function Ll(H,D){return H.x-D.x}function Io(H,D){let K=function(ke,qe){let We=qe,ct=ke.x,Mt=ke.y,Ut,nr=-1/0;do{if(Mt<=We.y&&Mt>=We.next.y&&We.next.y!==We.y){let pa=We.x+(Mt-We.y)*(We.next.x-We.x)/(We.next.y-We.y);if(pa<=ct&&pa>nr&&(nr=pa,Ut=We.x=We.x&&We.x>=Or&&ct!==We.x&&te(MtUt.x||We.x===Ut.x&&ve(Ut,We)))&&(Ut=We,oa=pa)}We=We.next}while(We!==Sr);return Ut}(H,D);if(!K)return D;let he=Nr(K,H);return Cl(he,he.next),Cl(K,K.next)}function ve(H,D){return Ge(H.prev,H,D.prev)<0&&Ge(D.next,H,H.next)<0}function Y(H,D,K,he,ke){return(H=1431655765&((H=858993459&((H=252645135&((H=16711935&((H=(H-K)*ke|0)|H<<8))|H<<4))|H<<2))|H<<1))|(D=1431655765&((D=858993459&((D=252645135&((D=16711935&((D=(D-he)*ke|0)|D<<8))|D<<4))|D<<2))|D<<1))<<1}function ye(H){let D=H,K=H;do(D.x=(H-We)*(qe-ct)&&(H-We)*(he-ct)>=(K-We)*(D-ct)&&(K-We)*(qe-ct)>=(ke-We)*(he-ct)}function me(H,D){return H.next.i!==D.i&&H.prev.i!==D.i&&!function(K,he){let ke=K;do{if(ke.i!==K.i&&ke.next.i!==K.i&&ke.i!==he.i&&ke.next.i!==he.i&&$e(ke,ke.next,K,he))return!0;ke=ke.next}while(ke!==K);return!1}(H,D)&&(_r(H,D)&&_r(D,H)&&function(K,he){let ke=K,qe=!1,We=(K.x+he.x)/2,ct=(K.y+he.y)/2;do ke.y>ct!=ke.next.y>ct&&ke.next.y!==ke.y&&We<(ke.next.x-ke.x)*(ct-ke.y)/(ke.next.y-ke.y)+ke.x&&(qe=!qe),ke=ke.next;while(ke!==K);return qe}(H,D)&&(Ge(H.prev,H,D.prev)||Ge(H,D.prev,D))||Le(H,D)&&Ge(H.prev,H,H.next)>0&&Ge(D.prev,D,D.next)>0)}function Ge(H,D,K){return(D.y-H.y)*(K.x-D.x)-(D.x-H.x)*(K.y-D.y)}function Le(H,D){return H.x===D.x&&H.y===D.y}function $e(H,D,K,he){let ke=jt(Ge(H,D,K)),qe=jt(Ge(H,D,he)),We=jt(Ge(K,he,H)),ct=jt(Ge(K,he,D));return ke!==qe&&We!==ct||!(ke!==0||!mt(H,K,D))||!(qe!==0||!mt(H,he,D))||!(We!==0||!mt(K,H,he))||!(ct!==0||!mt(K,D,he))}function mt(H,D,K){return D.x<=Math.max(H.x,K.x)&&D.x>=Math.min(H.x,K.x)&&D.y<=Math.max(H.y,K.y)&&D.y>=Math.min(H.y,K.y)}function jt(H){return H>0?1:H<0?-1:0}function _r(H,D){return Ge(H.prev,H,H.next)<0?Ge(H,D,H.next)>=0&&Ge(H,H.prev,D)>=0:Ge(H,D,H.prev)<0||Ge(H,H.next,D)<0}function Nr(H,D){let K=Et(H.i,H.x,H.y),he=Et(D.i,D.x,D.y),ke=H.next,qe=D.prev;return H.next=D,D.prev=H,K.next=ke,ke.prev=K,he.next=K,K.prev=he,qe.next=he,he.prev=qe,he}function pr(H,D,K,he){let ke=Et(H,D,K);return he?(ke.next=he.next,ke.prev=he,he.next.prev=ke,he.next=ke):(ke.prev=ke,ke.next=ke),ke}function yt(H){H.next.prev=H.prev,H.prev.next=H.next,H.prevZ&&(H.prevZ.nextZ=H.nextZ),H.nextZ&&(H.nextZ.prevZ=H.prevZ)}function Et(H,D,K){return{i:H,x:D,y:K,prev:null,next:null,z:0,prevZ:null,nextZ:null,steiner:!1}}function Bt(H,D,K){let he=K.patternDependencies,ke=!1;for(let qe of D){let We=qe.paint.get(`${H}-pattern`);We.isConstant()||(ke=!0);let ct=We.constantOr(null);ct&&(ke=!0,he[ct.to]=!0,he[ct.from]=!0)}return ke}function ir(H,D,K,he,ke){let qe=ke.patternDependencies;for(let We of D){let ct=We.paint.get(`${H}-pattern`).value;if(ct.kind!=="constant"){let Mt=ct.evaluate({zoom:he-1},K,{},ke.availableImages),Ut=ct.evaluate({zoom:he},K,{},ke.availableImages),nr=ct.evaluate({zoom:he+1},K,{},ke.availableImages);Mt=Mt&&Mt.name?Mt.name:Mt,Ut=Ut&&Ut.name?Ut.name:Ut,nr=nr&&nr.name?nr.name:nr,qe[Mt]=!0,qe[Ut]=!0,qe[nr]=!0,K.patterns[We.id]={min:Mt,mid:Ut,max:nr}}}return K}class hr{constructor(D){this.zoom=D.zoom,this.overscaling=D.overscaling,this.layers=D.layers,this.layerIds=this.layers.map(K=>K.id),this.index=D.index,this.hasPattern=!1,this.patternFeatures=[],this.layoutVertexArray=new Rl,this.indexArray=new ze,this.indexArray2=new et,this.programConfigurations=new rl(D.layers,D.zoom),this.segments=new St,this.segments2=new St,this.stateDependentLayerIds=this.layers.filter(K=>K.isStateDependent()).map(K=>K.id)}populate(D,K,he){this.hasPattern=Bt("fill",this.layers,K);let ke=this.layers[0].layout.get("fill-sort-key"),qe=!ke.isConstant(),We=[];for(let{feature:ct,id:Mt,index:Ut,sourceLayerIndex:nr}of D){let Sr=this.layers[0]._featureFilter.needGeometry,Or=Wl(ct,Sr);if(!this.layers[0]._featureFilter.filter(new Ls(this.zoom),Or,he))continue;let Hr=qe?ke.evaluate(Or,{},he,K.availableImages):void 0,oa={id:Mt,properties:ct.properties,type:ct.type,sourceLayerIndex:nr,index:Ut,geometry:Sr?Or.geometry:Al(ct),patterns:{},sortKey:Hr};We.push(oa)}qe&&We.sort((ct,Mt)=>ct.sortKey-Mt.sortKey);for(let ct of We){let{geometry:Mt,index:Ut,sourceLayerIndex:nr}=ct;if(this.hasPattern){let Sr=ir("fill",this.layers,ct,this.zoom,K);this.patternFeatures.push(Sr)}else this.addFeature(ct,Mt,Ut,he,{});K.featureIndex.insert(D[Ut].feature,Mt,Ut,nr,this.index)}}update(D,K,he){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(D,K,this.stateDependentLayers,he)}addFeatures(D,K,he){for(let ke of this.patternFeatures)this.addFeature(ke,ke.geometry,ke.index,K,he)}isEmpty(){return this.layoutVertexArray.length===0}uploadPending(){return!this.uploaded||this.programConfigurations.needsUpload}upload(D){this.uploaded||(this.layoutVertexBuffer=D.createVertexBuffer(this.layoutVertexArray,Xl),this.indexBuffer=D.createIndexBuffer(this.indexArray),this.indexBuffer2=D.createIndexBuffer(this.indexArray2)),this.programConfigurations.upload(D),this.uploaded=!0}destroy(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.indexBuffer2.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.segments2.destroy())}addFeature(D,K,he,ke,qe){for(let We of ic(K,500)){let ct=0;for(let Hr of We)ct+=Hr.length;let Mt=this.segments.prepareSegment(ct,this.layoutVertexArray,this.indexArray),Ut=Mt.vertexLength,nr=[],Sr=[];for(let Hr of We){if(Hr.length===0)continue;Hr!==We[0]&&Sr.push(nr.length/2);let oa=this.segments2.prepareSegment(Hr.length,this.layoutVertexArray,this.indexArray2),pa=oa.vertexLength;this.layoutVertexArray.emplaceBack(Hr[0].x,Hr[0].y),this.indexArray2.emplaceBack(pa+Hr.length-1,pa),nr.push(Hr[0].x),nr.push(Hr[0].y);for(let qa=1;qa>3}if(ke--,he===1||he===2)qe+=H.readSVarint(),We+=H.readSVarint(),he===1&&(D&&ct.push(D),D=[]),D.push(new ya(qe,We));else{if(he!==7)throw new Error("unknown command "+he);D&&D.push(D[0].clone())}}return D&&ct.push(D),ct},Ha.prototype.bbox=function(){var H=this._pbf;H.pos=this._geometry;for(var D=H.readVarint()+H.pos,K=1,he=0,ke=0,qe=0,We=1/0,ct=-1/0,Mt=1/0,Ut=-1/0;H.pos>3}if(he--,K===1||K===2)(ke+=H.readSVarint())ct&&(ct=ke),(qe+=H.readSVarint())Ut&&(Ut=qe);else if(K!==7)throw new Error("unknown command "+K)}return[We,Mt,ct,Ut]},Ha.prototype.toGeoJSON=function(H,D,K){var he,ke,qe=this.extent*Math.pow(2,K),We=this.extent*H,ct=this.extent*D,Mt=this.loadGeometry(),Ut=Ha.types[this.type];function nr(Hr){for(var oa=0;oa>3;ke=We===1?he.readString():We===2?he.readFloat():We===3?he.readDouble():We===4?he.readVarint64():We===5?he.readVarint():We===6?he.readSVarint():We===7?he.readBoolean():null}return ke}(K))}bi.prototype.feature=function(H){if(H<0||H>=this._features.length)throw new Error("feature index out of bounds");this._pbf.pos=this._features[H];var D=this._pbf.readVarint()+this._pbf.pos;return new Fi(this._pbf,D,this.extent,this._keys,this._values)};var Ui=ci;function fn(H,D,K){if(H===3){var he=new Ui(K,K.readVarint()+K.pos);he.length&&(D[he.name]=he)}}Jr.VectorTile=function(H,D){this.layers=H.readFields(fn,{},D)},Jr.VectorTileFeature=gi,Jr.VectorTileLayer=ci;let _o=Jr.VectorTileFeature.types,Uo=Math.pow(2,13);function Cs(H,D,K,he,ke,qe,We,ct){H.emplaceBack(D,K,2*Math.floor(he*Uo)+We,ke*Uo*2,qe*Uo*2,Math.round(ct))}class Oo{constructor(D){this.zoom=D.zoom,this.overscaling=D.overscaling,this.layers=D.layers,this.layerIds=this.layers.map(K=>K.id),this.index=D.index,this.hasPattern=!1,this.layoutVertexArray=new tu,this.centroidVertexArray=new Qo,this.indexArray=new ze,this.programConfigurations=new rl(D.layers,D.zoom),this.segments=new St,this.stateDependentLayerIds=this.layers.filter(K=>K.isStateDependent()).map(K=>K.id)}populate(D,K,he){this.features=[],this.hasPattern=Bt("fill-extrusion",this.layers,K);for(let{feature:ke,id:qe,index:We,sourceLayerIndex:ct}of D){let Mt=this.layers[0]._featureFilter.needGeometry,Ut=Wl(ke,Mt);if(!this.layers[0]._featureFilter.filter(new Ls(this.zoom),Ut,he))continue;let nr={id:qe,sourceLayerIndex:ct,index:We,geometry:Mt?Ut.geometry:Al(ke),properties:ke.properties,type:ke.type,patterns:{}};this.hasPattern?this.features.push(ir("fill-extrusion",this.layers,nr,this.zoom,K)):this.addFeature(nr,nr.geometry,We,he,{}),K.featureIndex.insert(ke,nr.geometry,We,ct,this.index,!0)}}addFeatures(D,K,he){for(let ke of this.features){let{geometry:qe}=ke;this.addFeature(ke,qe,ke.index,K,he)}}update(D,K,he){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(D,K,this.stateDependentLayers,he)}isEmpty(){return this.layoutVertexArray.length===0&&this.centroidVertexArray.length===0}uploadPending(){return!this.uploaded||this.programConfigurations.needsUpload}upload(D){this.uploaded||(this.layoutVertexBuffer=D.createVertexBuffer(this.layoutVertexArray,Fr),this.centroidVertexBuffer=D.createVertexBuffer(this.centroidVertexArray,Vt.members,!0),this.indexBuffer=D.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(D),this.uploaded=!0}destroy(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy(),this.centroidVertexBuffer.destroy())}addFeature(D,K,he,ke,qe){for(let We of ic(K,500)){let ct={x:0,y:0,vertexCount:0},Mt=0;for(let oa of We)Mt+=oa.length;let Ut=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray);for(let oa of We){if(oa.length===0||Xs(oa))continue;let pa=0;for(let qa=0;qa=1){let Hi=oa[qa-1];if(!Ss(Ja,Hi)){Ut.vertexLength+4>St.MAX_VERTEX_ARRAY_LENGTH&&(Ut=this.segments.prepareSegment(4,this.layoutVertexArray,this.indexArray));let _i=Ja.sub(Hi)._perp()._unit(),qi=Hi.dist(Ja);pa+qi>32768&&(pa=0),Cs(this.layoutVertexArray,Ja.x,Ja.y,_i.x,_i.y,0,0,pa),Cs(this.layoutVertexArray,Ja.x,Ja.y,_i.x,_i.y,0,1,pa),ct.x+=2*Ja.x,ct.y+=2*Ja.y,ct.vertexCount+=2,pa+=qi,Cs(this.layoutVertexArray,Hi.x,Hi.y,_i.x,_i.y,0,0,pa),Cs(this.layoutVertexArray,Hi.x,Hi.y,_i.x,_i.y,0,1,pa),ct.x+=2*Hi.x,ct.y+=2*Hi.y,ct.vertexCount+=2;let en=Ut.vertexLength;this.indexArray.emplaceBack(en,en+2,en+1),this.indexArray.emplaceBack(en+1,en+2,en+3),Ut.vertexLength+=4,Ut.primitiveLength+=2}}}}if(Ut.vertexLength+Mt>St.MAX_VERTEX_ARRAY_LENGTH&&(Ut=this.segments.prepareSegment(Mt,this.layoutVertexArray,this.indexArray)),_o[D.type]!=="Polygon")continue;let nr=[],Sr=[],Or=Ut.vertexLength;for(let oa of We)if(oa.length!==0){oa!==We[0]&&Sr.push(nr.length/2);for(let pa=0;pafo)||H.y===D.y&&(H.y<0||H.y>fo)}function Xs(H){return H.every(D=>D.x<0)||H.every(D=>D.x>fo)||H.every(D=>D.y<0)||H.every(D=>D.y>fo)}let du;yi("FillExtrusionBucket",Oo,{omit:["layers","features"]});var Ep={get paint(){return du=du||new Ue({"fill-extrusion-opacity":new uo(re["paint_fill-extrusion"]["fill-extrusion-opacity"]),"fill-extrusion-color":new Fo(re["paint_fill-extrusion"]["fill-extrusion-color"]),"fill-extrusion-translate":new uo(re["paint_fill-extrusion"]["fill-extrusion-translate"]),"fill-extrusion-translate-anchor":new uo(re["paint_fill-extrusion"]["fill-extrusion-translate-anchor"]),"fill-extrusion-pattern":new Dc(re["paint_fill-extrusion"]["fill-extrusion-pattern"]),"fill-extrusion-height":new Fo(re["paint_fill-extrusion"]["fill-extrusion-height"]),"fill-extrusion-base":new Fo(re["paint_fill-extrusion"]["fill-extrusion-base"]),"fill-extrusion-vertical-gradient":new uo(re["paint_fill-extrusion"]["fill-extrusion-vertical-gradient"])})}};class kp extends ae{constructor(D){super(D,Ep)}createBucket(D){return new Oo(D)}queryRadius(){return _n(this.paint.get("fill-extrusion-translate"))}is3D(){return!0}queryIntersectsFeature(D,K,he,ke,qe,We,ct,Mt){let Ut=zi(D,this.paint.get("fill-extrusion-translate"),this.paint.get("fill-extrusion-translate-anchor"),We.angle,ct),nr=this.paint.get("fill-extrusion-height").evaluate(K,he),Sr=this.paint.get("fill-extrusion-base").evaluate(K,he),Or=function(oa,pa,qa,Ja){let Hi=[];for(let _i of oa){let qi=[_i.x,_i.y,0,1];pn(qi,qi,pa),Hi.push(new n(qi[0]/qi[3],qi[1]/qi[3]))}return Hi}(Ut,Mt),Hr=function(oa,pa,qa,Ja){let Hi=[],_i=[],qi=Ja[8]*pa,en=Ja[9]*pa,jn=Ja[10]*pa,Lo=Ja[11]*pa,_s=Ja[8]*qa,vo=Ja[9]*qa,zn=Ja[10]*qa,is=Ja[11]*qa;for(let jo of oa){let Bo=[],wn=[];for(let cs of jo){let No=cs.x,ks=cs.y,Ku=Ja[0]*No+Ja[4]*ks+Ja[12],Uu=Ja[1]*No+Ja[5]*ks+Ja[13],th=Ja[2]*No+Ja[6]*ks+Ja[14],Hp=Ja[3]*No+Ja[7]*ks+Ja[15],wh=th+jn,rh=Hp+Lo,Jh=Ku+_s,$h=Uu+vo,Qh=th+zn,cf=Hp+is,ah=new n((Ku+qi)/rh,(Uu+en)/rh);ah.z=wh/rh,Bo.push(ah);let Fh=new n(Jh/cf,$h/cf);Fh.z=Qh/cf,wn.push(Fh)}Hi.push(Bo),_i.push(wn)}return[Hi,_i]}(ke,Sr,nr,Mt);return function(oa,pa,qa){let Ja=1/0;Xt(qa,pa)&&(Ja=qp(qa,pa[0]));for(let Hi=0;HiK.id),this.index=D.index,this.hasPattern=!1,this.patternFeatures=[],this.lineClipsArray=[],this.gradients={},this.layers.forEach(K=>{this.gradients[K.id]={}}),this.layoutVertexArray=new Ru,this.layoutVertexArray2=new pu,this.indexArray=new ze,this.programConfigurations=new rl(D.layers,D.zoom),this.segments=new St,this.maxLineLength=0,this.stateDependentLayerIds=this.layers.filter(K=>K.isStateDependent()).map(K=>K.id)}populate(D,K,he){this.hasPattern=Bt("line",this.layers,K);let ke=this.layers[0].layout.get("line-sort-key"),qe=!ke.isConstant(),We=[];for(let{feature:ct,id:Mt,index:Ut,sourceLayerIndex:nr}of D){let Sr=this.layers[0]._featureFilter.needGeometry,Or=Wl(ct,Sr);if(!this.layers[0]._featureFilter.filter(new Ls(this.zoom),Or,he))continue;let Hr=qe?ke.evaluate(Or,{},he):void 0,oa={id:Mt,properties:ct.properties,type:ct.type,sourceLayerIndex:nr,index:Ut,geometry:Sr?Or.geometry:Al(ct),patterns:{},sortKey:Hr};We.push(oa)}qe&&We.sort((ct,Mt)=>ct.sortKey-Mt.sortKey);for(let ct of We){let{geometry:Mt,index:Ut,sourceLayerIndex:nr}=ct;if(this.hasPattern){let Sr=ir("line",this.layers,ct,this.zoom,K);this.patternFeatures.push(Sr)}else this.addFeature(ct,Mt,Ut,he,{});K.featureIndex.insert(D[Ut].feature,Mt,Ut,nr,this.index)}}update(D,K,he){this.stateDependentLayers.length&&this.programConfigurations.updatePaintArrays(D,K,this.stateDependentLayers,he)}addFeatures(D,K,he){for(let ke of this.patternFeatures)this.addFeature(ke,ke.geometry,ke.index,K,he)}isEmpty(){return this.layoutVertexArray.length===0}uploadPending(){return!this.uploaded||this.programConfigurations.needsUpload}upload(D){this.uploaded||(this.layoutVertexArray2.length!==0&&(this.layoutVertexBuffer2=D.createVertexBuffer(this.layoutVertexArray2,td)),this.layoutVertexBuffer=D.createVertexBuffer(this.layoutVertexArray,ed),this.indexBuffer=D.createIndexBuffer(this.indexArray)),this.programConfigurations.upload(D),this.uploaded=!0}destroy(){this.layoutVertexBuffer&&(this.layoutVertexBuffer.destroy(),this.indexBuffer.destroy(),this.programConfigurations.destroy(),this.segments.destroy())}lineFeatureClips(D){if(D.properties&&Object.prototype.hasOwnProperty.call(D.properties,"mapbox_clip_start")&&Object.prototype.hasOwnProperty.call(D.properties,"mapbox_clip_end"))return{start:+D.properties.mapbox_clip_start,end:+D.properties.mapbox_clip_end}}addFeature(D,K,he,ke,qe){let We=this.layers[0].layout,ct=We.get("line-join").evaluate(D,{}),Mt=We.get("line-cap"),Ut=We.get("line-miter-limit"),nr=We.get("line-round-limit");this.lineClips=this.lineFeatureClips(D);for(let Sr of K)this.addLine(Sr,D,ct,Mt,Ut,nr);this.programConfigurations.populatePaintArrays(this.layoutVertexArray.length,D,he,qe,ke)}addLine(D,K,he,ke,qe,We){if(this.distance=0,this.scaledDistance=0,this.totalDistance=0,this.lineClips){this.lineClipsArray.push(this.lineClips);for(let Ja=0;Ja=2&&D[Mt-1].equals(D[Mt-2]);)Mt--;let Ut=0;for(;Ut0;if(Lo&&Ja>Ut){let is=Or.dist(Hr);if(is>2*nr){let jo=Or.sub(Or.sub(Hr)._mult(nr/is)._round());this.updateDistance(Hr,jo),this.addCurrentVertex(jo,pa,0,0,Sr),Hr=jo}}let vo=Hr&&oa,zn=vo?he:ct?"butt":ke;if(vo&&zn==="round"&&(enqe&&(zn="bevel"),zn==="bevel"&&(en>2&&(zn="flipbevel"),en100)Hi=qa.mult(-1);else{let is=en*pa.add(qa).mag()/pa.sub(qa).mag();Hi._perp()._mult(is*(_s?-1:1))}this.addCurrentVertex(Or,Hi,0,0,Sr),this.addCurrentVertex(Or,Hi.mult(-1),0,0,Sr)}else if(zn==="bevel"||zn==="fakeround"){let is=-Math.sqrt(en*en-1),jo=_s?is:0,Bo=_s?0:is;if(Hr&&this.addCurrentVertex(Or,pa,jo,Bo,Sr),zn==="fakeround"){let wn=Math.round(180*jn/Math.PI/20);for(let cs=1;cs2*nr){let jo=Or.add(oa.sub(Or)._mult(nr/is)._round());this.updateDistance(Or,jo),this.addCurrentVertex(jo,qa,0,0,Sr),Or=jo}}}}addCurrentVertex(D,K,he,ke,qe,We=!1){let ct=K.y*ke-K.x,Mt=-K.y-K.x*ke;this.addHalfVertex(D,K.x+K.y*he,K.y-K.x*he,We,!1,he,qe),this.addHalfVertex(D,ct,Mt,We,!0,-ke,qe),this.distance>Cp/2&&this.totalDistance===0&&(this.distance=0,this.updateScaledDistance(),this.addCurrentVertex(D,K,he,ke,qe,We))}addHalfVertex({x:D,y:K},he,ke,qe,We,ct,Mt){let Ut=.5*(this.lineClips?this.scaledDistance*(Cp-1):this.scaledDistance);this.layoutVertexArray.emplaceBack((D<<1)+(qe?1:0),(K<<1)+(We?1:0),Math.round(63*he)+128,Math.round(63*ke)+128,1+(ct===0?0:ct<0?-1:1)|(63&Ut)<<2,Ut>>6),this.lineClips&&this.layoutVertexArray2.emplaceBack((this.scaledDistance-this.lineClips.start)/(this.lineClips.end-this.lineClips.start),this.lineClipsArray.length);let nr=Mt.vertexLength++;this.e1>=0&&this.e2>=0&&(this.indexArray.emplaceBack(this.e1,this.e2,nr),Mt.primitiveLength++),We?this.e2=nr:this.e1=nr}updateScaledDistance(){this.scaledDistance=this.lineClips?this.lineClips.start+(this.lineClips.end-this.lineClips.start)*this.distance/this.totalDistance:this.distance}updateDistance(D,K){this.distance+=D.dist(K),this.updateScaledDistance()}}let Lp,Cv;yi("LineBucket",Vp,{omit:["layers","patternFeatures"]});var Vd={get paint(){return Cv=Cv||new Ue({"line-opacity":new Fo(re.paint_line["line-opacity"]),"line-color":new Fo(re.paint_line["line-color"]),"line-translate":new uo(re.paint_line["line-translate"]),"line-translate-anchor":new uo(re.paint_line["line-translate-anchor"]),"line-width":new Fo(re.paint_line["line-width"]),"line-gap-width":new Fo(re.paint_line["line-gap-width"]),"line-offset":new Fo(re.paint_line["line-offset"]),"line-blur":new Fo(re.paint_line["line-blur"]),"line-dasharray":new uc(re.paint_line["line-dasharray"]),"line-pattern":new Dc(re.paint_line["line-pattern"]),"line-gradient":new Yu(re.paint_line["line-gradient"])})},get layout(){return Lp=Lp||new Ue({"line-cap":new uo(re.layout_line["line-cap"]),"line-join":new Fo(re.layout_line["line-join"]),"line-miter-limit":new uo(re.layout_line["line-miter-limit"]),"line-round-limit":new uo(re.layout_line["line-round-limit"]),"line-sort-key":new Fo(re.layout_line["line-sort-key"])})}};class Gf extends Fo{possiblyEvaluate(D,K){return K=new Ls(Math.floor(K.zoom),{now:K.now,fadeDuration:K.fadeDuration,zoomHistory:K.zoomHistory,transition:K.transition}),super.possiblyEvaluate(D,K)}evaluate(D,K,he,ke){return K=M({},K,{zoom:Math.floor(K.zoom)}),super.evaluate(D,K,he,ke)}}let Gd;class Lv extends ae{constructor(D){super(D,Vd),this.gradientVersion=0,Gd||(Gd=new Gf(Vd.paint.properties["line-width"].specification),Gd.useIntegerZoom=!0)}_handleSpecialPaintPropertyUpdate(D){if(D==="line-gradient"){let K=this.gradientExpression();this.stepInterpolant=!!function(he){return he._styleExpression!==void 0}(K)&&K._styleExpression.expression instanceof Aa,this.gradientVersion=(this.gradientVersion+1)%Number.MAX_SAFE_INTEGER}}gradientExpression(){return this._transitionablePaint._values["line-gradient"].value.expression}recalculate(D,K){super.recalculate(D,K),this.paint._values["line-floorwidth"]=Gd.possiblyEvaluate(this._transitioningPaint._values["line-width"].value,D)}createBucket(D){return new Vp(D)}queryRadius(D){let K=D,he=fh(li("line-width",this,K),li("line-gap-width",this,K)),ke=li("line-offset",this,K);return he/2+Math.abs(ke)+_n(this.paint.get("line-translate"))}queryIntersectsFeature(D,K,he,ke,qe,We,ct){let Mt=zi(D,this.paint.get("line-translate"),this.paint.get("line-translate-anchor"),We.angle,ct),Ut=ct/2*fh(this.paint.get("line-width").evaluate(K,he),this.paint.get("line-gap-width").evaluate(K,he)),nr=this.paint.get("line-offset").evaluate(K,he);return nr&&(ke=function(Sr,Or){let Hr=[];for(let oa=0;oa=3){for(let qa=0;qa0?D+2*H:H}let iv=pt([{name:"a_pos_offset",components:4,type:"Int16"},{name:"a_data",components:4,type:"Uint16"},{name:"a_pixeloffset",components:4,type:"Int16"}],4),nm=pt([{name:"a_projected_pos",components:3,type:"Float32"}],4);pt([{name:"a_fade_opacity",components:1,type:"Uint32"}],4);let 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fc={"!":"\uFE15","#":"\uFF03",$:"\uFF04","%":"\uFF05","&":"\uFF06","(":"\uFE35",")":"\uFE36","*":"\uFF0A","+":"\uFF0B",",":"\uFE10","-":"\uFE32",".":"\u30FB","/":"\uFF0F",":":"\uFE13",";":"\uFE14","<":"\uFE3F","=":"\uFF1D",">":"\uFE40","?":"\uFE16","@":"\uFF20","[":"\uFE47","\\":"\uFF3C","]":"\uFE48","^":"\uFF3E",_:"\uFE33","`":"\uFF40","{":"\uFE37","|":"\u2015","}":"\uFE38","~":"\uFF5E","\xA2":"\uFFE0","\xA3":"\uFFE1","\xA5":"\uFFE5","\xA6":"\uFFE4","\xAC":"\uFFE2","\xAF":"\uFFE3","\u2013":"\uFE32","\u2014":"\uFE31","\u2018":"\uFE43","\u2019":"\uFE44","\u201C":"\uFE41","\u201D":"\uFE42","\u2026":"\uFE19","\u2027":"\u30FB","\u20A9":"\uFFE6","\u3001":"\uFE11","\u3002":"\uFE12","\u3008":"\uFE3F","\u3009":"\uFE40","\u300A":"\uFE3D","\u300B":"\uFE3E","\u300C":"\uFE41","\u300D":"\uFE42","\u300E":"\uFE43","\u300F":"\uFE44","\u3010":"\uFE3B","\u3011":"\uFE3C","\u3014":"\uFE39","\u3015":"\uFE3A","\u3016":"\uFE17","\u3017":"\uFE18","\uFF01":"\uFE15","\uFF08":"\uFE35","\uFF09":"\uFE36","\uFF0C":"\uFE10","\uFF0D":"\uFE32","\uFF0E":"\u30FB","\uFF1A":"\uFE13","\uFF1B":"\uFE14","\uFF1C":"\uFE3F","\uFF1E":"\uFE40","\uFF1F":"\uFE16","\uFF3B":"\uFE47","\uFF3D":"\uFE48","\uFF3F":"\uFE33","\uFF5B":"\uFE37","\uFF5C":"\u2015","\uFF5D":"\uFE38","\uFF5F":"\uFE35","\uFF60":"\uFE36","\uFF61":"\uFE12","\uFF62":"\uFE41","\uFF63":"\uFE42"};var cu=24,Dh=Su,Iv=function(H,D,K,he,ke){var qe,We,ct=8*ke-he-1,Mt=(1<>1,nr=-7,Sr=K?ke-1:0,Or=K?-1:1,Hr=H[D+Sr];for(Sr+=Or,qe=Hr&(1<<-nr)-1,Hr>>=-nr,nr+=ct;nr>0;qe=256*qe+H[D+Sr],Sr+=Or,nr-=8);for(We=qe&(1<<-nr)-1,qe>>=-nr,nr+=he;nr>0;We=256*We+H[D+Sr],Sr+=Or,nr-=8);if(qe===0)qe=1-Ut;else{if(qe===Mt)return We?NaN:1/0*(Hr?-1:1);We+=Math.pow(2,he),qe-=Ut}return(Hr?-1:1)*We*Math.pow(2,qe-he)},sm=function(H,D,K,he,ke,qe){var We,ct,Mt,Ut=8*qe-ke-1,nr=(1<>1,Or=ke===23?Math.pow(2,-24)-Math.pow(2,-77):0,Hr=he?0:qe-1,oa=he?1:-1,pa=D<0||D===0&&1/D<0?1:0;for(D=Math.abs(D),isNaN(D)||D===1/0?(ct=isNaN(D)?1:0,We=nr):(We=Math.floor(Math.log(D)/Math.LN2),D*(Mt=Math.pow(2,-We))<1&&(We--,Mt*=2),(D+=We+Sr>=1?Or/Mt:Or*Math.pow(2,1-Sr))*Mt>=2&&(We++,Mt/=2),We+Sr>=nr?(ct=0,We=nr):We+Sr>=1?(ct=(D*Mt-1)*Math.pow(2,ke),We+=Sr):(ct=D*Math.pow(2,Sr-1)*Math.pow(2,ke),We=0));ke>=8;H[K+Hr]=255&ct,Hr+=oa,ct/=256,ke-=8);for(We=We<0;H[K+Hr]=255&We,Hr+=oa,We/=256,Ut-=8);H[K+Hr-oa]|=128*pa};function 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_s=this.sortFeaturesByKey?Sr.evaluate(en,{},he):void 0;if(this.features.push({id:Ja,text:jn,icon:Lo,index:Hi,sourceLayerIndex:_i,geometry:en.geometry,properties:qa.properties,type:JT[qa.type],sortKey:_s}),Lo&&(Or[Lo.name]=!0),jn){let vo=We.evaluate(en,{},he).join(","),zn=qe.get("text-rotation-alignment")!=="viewport"&&qe.get("symbol-placement")!=="point";this.allowVerticalPlacement=this.writingModes&&this.writingModes.indexOf(e.ah.vertical)>=0;for(let is of jn.sections)if(is.image)Or[is.image.name]=!0;else{let jo=yo(jn.toString()),Bo=is.fontStack||vo,wn=Hr[Bo]=Hr[Bo]||{};this.calculateGlyphDependencies(is.text,wn,zn,this.allowVerticalPlacement,jo)}}}qe.get("symbol-placement")==="line"&&(this.features=function(qa){let Ja={},Hi={},_i=[],qi=0;function en(vo){_i.push(qa[vo]),qi++}function jn(vo,zn,is){let jo=Hi[vo];return delete Hi[vo],Hi[zn]=jo,_i[jo].geometry[0].pop(),_i[jo].geometry[0]=_i[jo].geometry[0].concat(is[0]),jo}function Lo(vo,zn,is){let jo=Ja[zn];return delete Ja[zn],Ja[vo]=jo,_i[jo].geometry[0].shift(),_i[jo].geometry[0]=is[0].concat(_i[jo].geometry[0]),jo}function _s(vo,zn,is){let jo=is?zn[0][zn[0].length-1]:zn[0][0];return`${vo}:${jo.x}:${jo.y}`}for(let vo=0;vovo.geometry)}(this.features)),this.sortFeaturesByKey&&this.features.sort((qa,Ja)=>qa.sortKey-Ja.sortKey)}update(D,K,he){this.stateDependentLayers.length&&(this.text.programConfigurations.updatePaintArrays(D,K,this.layers,he),this.icon.programConfigurations.updatePaintArrays(D,K,this.layers,he))}isEmpty(){return this.symbolInstances.length===0&&!this.hasRTLText}uploadPending(){return!this.uploaded||this.text.programConfigurations.needsUpload||this.icon.programConfigurations.needsUpload}upload(D){!this.uploaded&&this.hasDebugData()&&(this.textCollisionBox.upload(D),this.iconCollisionBox.upload(D)),this.text.upload(D,this.sortFeaturesByY,!this.uploaded,this.text.programConfigurations.needsUpload),this.icon.upload(D,this.sortFeaturesByY,!this.uploaded,this.icon.programConfigurations.needsUpload),this.uploaded=!0}destroyDebugData(){this.textCollisionBox.destroy(),this.iconCollisionBox.destroy()}destroy(){this.text.destroy(),this.icon.destroy(),this.hasDebugData()&&this.destroyDebugData()}addToLineVertexArray(D,K){let he=this.lineVertexArray.length;if(D.segment!==void 0){let ke=D.dist(K[D.segment+1]),qe=D.dist(K[D.segment]),We={};for(let ct=D.segment+1;ct=0;ct--)We[ct]={x:K[ct].x,y:K[ct].y,tileUnitDistanceFromAnchor:qe},ct>0&&(qe+=K[ct-1].dist(K[ct]));for(let ct=0;ct0}hasIconData(){return this.icon.segments.get().length>0}hasDebugData(){return this.textCollisionBox&&this.iconCollisionBox}hasTextCollisionBoxData(){return this.hasDebugData()&&this.textCollisionBox.segments.get().length>0}hasIconCollisionBoxData(){return this.hasDebugData()&&this.iconCollisionBox.segments.get().length>0}addIndicesForPlacedSymbol(D,K){let he=D.placedSymbolArray.get(K),ke=he.vertexStartIndex+4*he.numGlyphs;for(let qe=he.vertexStartIndex;qeke[ct]-ke[Mt]||qe[Mt]-qe[ct]),We}addToSortKeyRanges(D,K){let he=this.sortKeyRanges[this.sortKeyRanges.length-1];he&&he.sortKey===K?he.symbolInstanceEnd=D+1:this.sortKeyRanges.push({sortKey:K,symbolInstanceStart:D,symbolInstanceEnd:D+1})}sortFeatures(D){if(this.sortFeaturesByY&&this.sortedAngle!==D&&!(this.text.segments.get().length>1||this.icon.segments.get().length>1)){this.symbolInstanceIndexes=this.getSortedSymbolIndexes(D),this.sortedAngle=D,this.text.indexArray.clear(),this.icon.indexArray.clear(),this.featureSortOrder=[];for(let K of this.symbolInstanceIndexes){let he=this.symbolInstances.get(K);this.featureSortOrder.push(he.featureIndex),[he.rightJustifiedTextSymbolIndex,he.centerJustifiedTextSymbolIndex,he.leftJustifiedTextSymbolIndex].forEach((ke,qe,We)=>{ke>=0&&We.indexOf(ke)===qe&&this.addIndicesForPlacedSymbol(this.text,ke)}),he.verticalPlacedTextSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.text,he.verticalPlacedTextSymbolIndex),he.placedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,he.placedIconSymbolIndex),he.verticalPlacedIconSymbolIndex>=0&&this.addIndicesForPlacedSymbol(this.icon,he.verticalPlacedIconSymbolIndex)}this.text.indexBuffer&&this.text.indexBuffer.updateData(this.text.indexArray),this.icon.indexBuffer&&this.icon.indexBuffer.updateData(this.icon.indexArray)}}}let uf,k0;yi("SymbolBucket",cm,{omit:["layers","collisionBoxArray","features","compareText"]}),cm.MAX_GLYPHS=65535,cm.addDynamicAttributes=z1;var kg={get paint(){return k0=k0||new Ue({"icon-opacity":new Fo(re.paint_symbol["icon-opacity"]),"icon-color":new Fo(re.paint_symbol["icon-color"]),"icon-halo-color":new Fo(re.paint_symbol["icon-halo-color"]),"icon-halo-width":new Fo(re.paint_symbol["icon-halo-width"]),"icon-halo-blur":new Fo(re.paint_symbol["icon-halo-blur"]),"icon-translate":new uo(re.paint_symbol["icon-translate"]),"icon-translate-anchor":new uo(re.paint_symbol["icon-translate-anchor"]),"text-opacity":new Fo(re.paint_symbol["text-opacity"]),"text-color":new Fo(re.paint_symbol["text-color"],{runtimeType:qt,getOverride:H=>H.textColor,hasOverride:H=>!!H.textColor}),"text-halo-color":new Fo(re.paint_symbol["text-halo-color"]),"text-halo-width":new Fo(re.paint_symbol["text-halo-width"]),"text-halo-blur":new Fo(re.paint_symbol["text-halo-blur"]),"text-translate":new uo(re.paint_symbol["text-translate"]),"text-translate-anchor":new uo(re.paint_symbol["text-translate-anchor"])})},get layout(){return uf=uf||new Ue({"symbol-placement":new uo(re.layout_symbol["symbol-placement"]),"symbol-spacing":new uo(re.layout_symbol["symbol-spacing"]),"symbol-avoid-edges":new uo(re.layout_symbol["symbol-avoid-edges"]),"symbol-sort-key":new Fo(re.layout_symbol["symbol-sort-key"]),"symbol-z-order":new uo(re.layout_symbol["symbol-z-order"]),"icon-allow-overlap":new uo(re.layout_symbol["icon-allow-overlap"]),"icon-overlap":new uo(re.layout_symbol["icon-overlap"]),"icon-ignore-placement":new uo(re.layout_symbol["icon-ignore-placement"]),"icon-optional":new uo(re.layout_symbol["icon-optional"]),"icon-rotation-alignment":new uo(re.layout_symbol["icon-rotation-alignment"]),"icon-size":new Fo(re.layout_symbol["icon-size"]),"icon-text-fit":new uo(re.layout_symbol["icon-text-fit"]),"icon-text-fit-padding":new uo(re.layout_symbol["icon-text-fit-padding"]),"icon-image":new Fo(re.layout_symbol["icon-image"]),"icon-rotate":new Fo(re.layout_symbol["icon-rotate"]),"icon-padding":new Fo(re.layout_symbol["icon-padding"]),"icon-keep-upright":new uo(re.layout_symbol["icon-keep-upright"]),"icon-offset":new Fo(re.layout_symbol["icon-offset"]),"icon-anchor":new Fo(re.layout_symbol["icon-anchor"]),"icon-pitch-alignment":new uo(re.layout_symbol["icon-pitch-alignment"]),"text-pitch-alignment":new uo(re.layout_symbol["text-pitch-alignment"]),"text-rotation-alignment":new uo(re.layout_symbol["text-rotation-alignment"]),"text-field":new Fo(re.layout_symbol["text-field"]),"text-font":new Fo(re.layout_symbol["text-font"]),"text-size":new Fo(re.layout_symbol["text-size"]),"text-max-width":new Fo(re.layout_symbol["text-max-width"]),"text-line-height":new uo(re.layout_symbol["text-line-height"]),"text-letter-spacing":new Fo(re.layout_symbol["text-letter-spacing"]),"text-justify":new Fo(re.layout_symbol["text-justify"]),"text-radial-offset":new Fo(re.layout_symbol["text-radial-offset"]),"text-variable-anchor":new uo(re.layout_symbol["text-variable-anchor"]),"text-variable-anchor-offset":new Fo(re.layout_symbol["text-variable-anchor-offset"]),"text-anchor":new Fo(re.layout_symbol["text-anchor"]),"text-max-angle":new uo(re.layout_symbol["text-max-angle"]),"text-writing-mode":new uo(re.layout_symbol["text-writing-mode"]),"text-rotate":new Fo(re.layout_symbol["text-rotate"]),"text-padding":new uo(re.layout_symbol["text-padding"]),"text-keep-upright":new uo(re.layout_symbol["text-keep-upright"]),"text-transform":new Fo(re.layout_symbol["text-transform"]),"text-offset":new Fo(re.layout_symbol["text-offset"]),"text-allow-overlap":new uo(re.layout_symbol["text-allow-overlap"]),"text-overlap":new uo(re.layout_symbol["text-overlap"]),"text-ignore-placement":new uo(re.layout_symbol["text-ignore-placement"]),"text-optional":new uo(re.layout_symbol["text-optional"])})}};class C0{constructor(D){if(D.property.overrides===void 0)throw new Error("overrides must be provided to instantiate FormatSectionOverride class");this.type=D.property.overrides?D.property.overrides.runtimeType:st,this.defaultValue=D}evaluate(D){if(D.formattedSection){let K=this.defaultValue.property.overrides;if(K&&K.hasOverride(D.formattedSection))return K.getOverride(D.formattedSection)}return D.feature&&D.featureState?this.defaultValue.evaluate(D.feature,D.featureState):this.defaultValue.property.specification.default}eachChild(D){this.defaultValue.isConstant()||D(this.defaultValue.value._styleExpression.expression)}outputDefined(){return!1}serialize(){return null}}yi("FormatSectionOverride",C0,{omit:["defaultValue"]});class Dv extends ae{constructor(D){super(D,kg)}recalculate(D,K){if(super.recalculate(D,K),this.layout.get("icon-rotation-alignment")==="auto"&&(this.layout._values["icon-rotation-alignment"]=this.layout.get("symbol-placement")!=="point"?"map":"viewport"),this.layout.get("text-rotation-alignment")==="auto"&&(this.layout._values["text-rotation-alignment"]=this.layout.get("symbol-placement")!=="point"?"map":"viewport"),this.layout.get("text-pitch-alignment")==="auto"&&(this.layout._values["text-pitch-alignment"]=this.layout.get("text-rotation-alignment")==="map"?"map":"viewport"),this.layout.get("icon-pitch-alignment")==="auto"&&(this.layout._values["icon-pitch-alignment"]=this.layout.get("icon-rotation-alignment")),this.layout.get("symbol-placement")==="point"){let he=this.layout.get("text-writing-mode");if(he){let ke=[];for(let qe of he)ke.indexOf(qe)<0&&ke.push(qe);this.layout._values["text-writing-mode"]=ke}else this.layout._values["text-writing-mode"]=["horizontal"]}this._setPaintOverrides()}getValueAndResolveTokens(D,K,he,ke){let qe=this.layout.get(D).evaluate(K,{},he,ke),We=this._unevaluatedLayout._values[D];return We.isDataDriven()||Mc(We.value)||!qe?qe:function(ct,Mt){return Mt.replace(/{([^{}]+)}/g,(Ut,nr)=>ct&&nr in ct?String(ct[nr]):"")}(K.properties,qe)}createBucket(D){return new cm(D)}queryRadius(){return 0}queryIntersectsFeature(){throw new Error("Should take a different path in FeatureIndex")}_setPaintOverrides(){for(let D of kg.paint.overridableProperties){if(!Dv.hasPaintOverride(this.layout,D))continue;let K=this.paint.get(D),he=new C0(K),ke=new Lu(he,K.property.specification),qe=null;qe=K.value.kind==="constant"||K.value.kind==="source"?new mc("source",ke):new mu("composite",ke,K.value.zoomStops),this.paint._values[D]=new Tu(K.property,qe,K.parameters)}}_handleOverridablePaintPropertyUpdate(D,K,he){return!(!this.layout||K.isDataDriven()||he.isDataDriven())&&Dv.hasPaintOverride(this.layout,D)}static hasPaintOverride(D,K){let he=D.get("text-field"),ke=kg.paint.properties[K],qe=!1,We=ct=>{for(let Mt of ct)if(ke.overrides&&ke.overrides.hasOverride(Mt))return void(qe=!0)};if(he.value.kind==="constant"&&he.value.value instanceof aa)We(he.value.value.sections);else if(he.value.kind==="source"){let ct=Ut=>{qe||(Ut instanceof on&&Da(Ut.value)===qr?We(Ut.value.sections):Ut instanceof ys?We(Ut.sections):Ut.eachChild(ct))},Mt=he.value;Mt._styleExpression&&ct(Mt._styleExpression.expression)}return qe}}let Bx;var L0={get paint(){return Bx=Bx||new Ue({"background-color":new uo(re.paint_background["background-color"]),"background-pattern":new uc(re.paint_background["background-pattern"]),"background-opacity":new uo(re.paint_background["background-opacity"])})}};class QT extends ae{constructor(D){super(D,L0)}}let B1;var Nx={get paint(){return B1=B1||new Ue({"raster-opacity":new uo(re.paint_raster["raster-opacity"]),"raster-hue-rotate":new uo(re.paint_raster["raster-hue-rotate"]),"raster-brightness-min":new uo(re.paint_raster["raster-brightness-min"]),"raster-brightness-max":new uo(re.paint_raster["raster-brightness-max"]),"raster-saturation":new uo(re.paint_raster["raster-saturation"]),"raster-contrast":new uo(re.paint_raster["raster-contrast"]),"raster-resampling":new uo(re.paint_raster["raster-resampling"]),"raster-fade-duration":new uo(re.paint_raster["raster-fade-duration"])})}};class P0 extends ae{constructor(D){super(D,Nx)}}class N1 extends ae{constructor(D){super(D,{}),this.onAdd=K=>{this.implementation.onAdd&&this.implementation.onAdd(K,K.painter.context.gl)},this.onRemove=K=>{this.implementation.onRemove&&this.implementation.onRemove(K,K.painter.context.gl)},this.implementation=D}is3D(){return this.implementation.renderingMode==="3d"}hasOffscreenPass(){return this.implementation.prerender!==void 0}recalculate(){}updateTransitions(){}hasTransition(){return!1}serialize(){throw new Error("Custom layers cannot be serialized")}}class U1{constructor(D){this._methodToThrottle=D,this._triggered=!1,typeof MessageChannel<"u"&&(this._channel=new MessageChannel,this._channel.port2.onmessage=()=>{this._triggered=!1,this._methodToThrottle()})}trigger(){this._triggered||(this._triggered=!0,this._channel?this._channel.port1.postMessage(!0):setTimeout(()=>{this._triggered=!1,this._methodToThrottle()},0))}remove(){delete this._channel,this._methodToThrottle=()=>{}}}let j1=63710088e-1;class Hd{constructor(D,K){if(isNaN(D)||isNaN(K))throw new Error(`Invalid LngLat object: (${D}, ${K})`);if(this.lng=+D,this.lat=+K,this.lat>90||this.lat<-90)throw new Error("Invalid LngLat latitude value: must be between -90 and 90")}wrap(){return new Hd(S(this.lng,-180,180),this.lat)}toArray(){return[this.lng,this.lat]}toString(){return`LngLat(${this.lng}, ${this.lat})`}distanceTo(D){let K=Math.PI/180,he=this.lat*K,ke=D.lat*K,qe=Math.sin(he)*Math.sin(ke)+Math.cos(he)*Math.cos(ke)*Math.cos((D.lng-this.lng)*K);return j1*Math.acos(Math.min(qe,1))}static convert(D){if(D instanceof Hd)return D;if(Array.isArray(D)&&(D.length===2||D.length===3))return new Hd(Number(D[0]),Number(D[1]));if(!Array.isArray(D)&&typeof D=="object"&&D!==null)return new Hd(Number("lng"in D?D.lng:D.lon),Number(D.lat));throw new Error("`LngLatLike` argument must be specified as a LngLat instance, an object {lng: , lat: }, an object {lon: , lat: }, or an array of [, ]")}}let fm=2*Math.PI*j1;function Ux(H){return fm*Math.cos(H*Math.PI/180)}function Cg(H){return(180+H)/360}function jx(H){return(180-180/Math.PI*Math.log(Math.tan(Math.PI/4+H*Math.PI/360)))/360}function Lg(H,D){return H/Ux(D)}function I0(H){return 360/Math.PI*Math.atan(Math.exp((180-360*H)*Math.PI/180))-90}class R0{constructor(D,K,he=0){this.x=+D,this.y=+K,this.z=+he}static fromLngLat(D,K=0){let he=Hd.convert(D);return new R0(Cg(he.lng),jx(he.lat),Lg(K,he.lat))}toLngLat(){return new Hd(360*this.x-180,I0(this.y))}toAltitude(){return this.z*Ux(I0(this.y))}meterInMercatorCoordinateUnits(){return 1/fm*(D=I0(this.y),1/Math.cos(D*Math.PI/180));var D}}function rd(H,D,K){var he=2*Math.PI*6378137/256/Math.pow(2,K);return[H*he-2*Math.PI*6378137/2,D*he-2*Math.PI*6378137/2]}class q1{constructor(D,K,he){if(!function(ke,qe,We){return!(ke<0||ke>25||We<0||We>=Math.pow(2,ke)||qe<0||qe>=Math.pow(2,ke))}(D,K,he))throw new Error(`x=${K}, y=${he}, z=${D} outside of bounds. 0<=x<${Math.pow(2,D)}, 0<=y<${Math.pow(2,D)} 0<=z<=25 `);this.z=D,this.x=K,this.y=he,this.key=D0(0,D,D,K,he)}equals(D){return this.z===D.z&&this.x===D.x&&this.y===D.y}url(D,K,he){let ke=(We=this.y,ct=this.z,Mt=rd(256*(qe=this.x),256*(We=Math.pow(2,ct)-We-1),ct),Ut=rd(256*(qe+1),256*(We+1),ct),Mt[0]+","+Mt[1]+","+Ut[0]+","+Ut[1]);var qe,We,ct,Mt,Ut;let nr=function(Sr,Or,Hr){let oa,pa="";for(let qa=Sr;qa>0;qa--)oa=1<1?"@2x":"").replace(/{quadkey}/g,nr).replace(/{bbox-epsg-3857}/g,ke)}isChildOf(D){let K=this.z-D.z;return K>0&&D.x===this.x>>K&&D.y===this.y>>K}getTilePoint(D){let K=Math.pow(2,this.z);return new n((D.x*K-this.x)*fo,(D.y*K-this.y)*fo)}toString(){return`${this.z}/${this.x}/${this.y}`}}class qx{constructor(D,K){this.wrap=D,this.canonical=K,this.key=D0(D,K.z,K.z,K.x,K.y)}}class Gp{constructor(D,K,he,ke,qe){if(D= z; overscaledZ = ${D}; z = ${he}`);this.overscaledZ=D,this.wrap=K,this.canonical=new q1(he,+ke,+qe),this.key=D0(K,D,he,ke,qe)}clone(){return new Gp(this.overscaledZ,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)}equals(D){return this.overscaledZ===D.overscaledZ&&this.wrap===D.wrap&&this.canonical.equals(D.canonical)}scaledTo(D){if(D>this.overscaledZ)throw new Error(`targetZ > this.overscaledZ; targetZ = ${D}; overscaledZ = ${this.overscaledZ}`);let K=this.canonical.z-D;return D>this.canonical.z?new Gp(D,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y):new Gp(D,this.wrap,D,this.canonical.x>>K,this.canonical.y>>K)}calculateScaledKey(D,K){if(D>this.overscaledZ)throw new Error(`targetZ > this.overscaledZ; targetZ = ${D}; overscaledZ = ${this.overscaledZ}`);let he=this.canonical.z-D;return D>this.canonical.z?D0(this.wrap*+K,D,this.canonical.z,this.canonical.x,this.canonical.y):D0(this.wrap*+K,D,D,this.canonical.x>>he,this.canonical.y>>he)}isChildOf(D){if(D.wrap!==this.wrap)return!1;let K=this.canonical.z-D.canonical.z;return D.overscaledZ===0||D.overscaledZ>K&&D.canonical.y===this.canonical.y>>K}children(D){if(this.overscaledZ>=D)return[new Gp(this.overscaledZ+1,this.wrap,this.canonical.z,this.canonical.x,this.canonical.y)];let K=this.canonical.z+1,he=2*this.canonical.x,ke=2*this.canonical.y;return[new Gp(K,this.wrap,K,he,ke),new Gp(K,this.wrap,K,he+1,ke),new Gp(K,this.wrap,K,he,ke+1),new Gp(K,this.wrap,K,he+1,ke+1)]}isLessThan(D){return this.wrapD.wrap)&&(this.overscaledZD.overscaledZ)&&(this.canonical.xD.canonical.x)&&this.canonical.ythis.max&&(this.max=Sr),Sr=this.dim+1||K<-1||K>=this.dim+1)throw new RangeError("out of range source coordinates for DEM data");return(K+1)*this.stride+(D+1)}unpack(D,K,he){return D*this.redFactor+K*this.greenFactor+he*this.blueFactor-this.baseShift}getPixels(){return new Ii({width:this.stride,height:this.stride},new Uint8Array(this.data.buffer))}backfillBorder(D,K,he){if(this.dim!==D.dim)throw new Error("dem dimension mismatch");let ke=K*this.dim,qe=K*this.dim+this.dim,We=he*this.dim,ct=he*this.dim+this.dim;switch(K){case-1:ke=qe-1;break;case 1:qe=ke+1}switch(he){case-1:We=ct-1;break;case 1:ct=We+1}let Mt=-K*this.dim,Ut=-he*this.dim;for(let nr=We;nr=this._numberToString.length)throw new Error(`Out of bounds. Index requested n=${D} can't be >= this._numberToString.length ${this._numberToString.length}`);return this._numberToString[D]}}class V1{constructor(D,K,he,ke,qe){this.type="Feature",this._vectorTileFeature=D,D._z=K,D._x=he,D._y=ke,this.properties=D.properties,this.id=qe}get geometry(){return this._geometry===void 0&&(this._geometry=this._vectorTileFeature.toGeoJSON(this._vectorTileFeature._x,this._vectorTileFeature._y,this._vectorTileFeature._z).geometry),this._geometry}set geometry(D){this._geometry=D}toJSON(){let D={geometry:this.geometry};for(let K in this)K!=="_geometry"&&K!=="_vectorTileFeature"&&(D[K]=this[K]);return D}}class zv{constructor(D,K){this.tileID=D,this.x=D.canonical.x,this.y=D.canonical.y,this.z=D.canonical.z,this.grid=new Di(fo,16,0),this.grid3D=new Di(fo,16,0),this.featureIndexArray=new el,this.promoteId=K}insert(D,K,he,ke,qe,We){let ct=this.featureIndexArray.length;this.featureIndexArray.emplaceBack(he,ke,qe);let Mt=We?this.grid3D:this.grid;for(let Ut=0;Ut=0&&Sr[3]>=0&&Mt.insert(ct,Sr[0],Sr[1],Sr[2],Sr[3])}}loadVTLayers(){return this.vtLayers||(this.vtLayers=new Jr.VectorTile(new P1(this.rawTileData)).layers,this.sourceLayerCoder=new Gx(this.vtLayers?Object.keys(this.vtLayers).sort():["_geojsonTileLayer"])),this.vtLayers}query(D,K,he,ke){this.loadVTLayers();let qe=D.params||{},We=fo/D.tileSize/D.scale,ct=Ec(qe.filter),Mt=D.queryGeometry,Ut=D.queryPadding*We,nr=Wx(Mt),Sr=this.grid.query(nr.minX-Ut,nr.minY-Ut,nr.maxX+Ut,nr.maxY+Ut),Or=Wx(D.cameraQueryGeometry),Hr=this.grid3D.query(Or.minX-Ut,Or.minY-Ut,Or.maxX+Ut,Or.maxY+Ut,(qa,Ja,Hi,_i)=>function(qi,en,jn,Lo,_s){for(let zn of qi)if(en<=zn.x&&jn<=zn.y&&Lo>=zn.x&&_s>=zn.y)return!0;let vo=[new n(en,jn),new n(en,_s),new n(Lo,_s),new n(Lo,jn)];if(qi.length>2){for(let zn of vo)if(Ti(qi,zn))return!0}for(let zn=0;zn(_i||(_i=Al(qi)),en.queryIntersectsFeature(Mt,qi,jn,_i,this.z,D.transform,We,D.pixelPosMatrix)))}return oa}loadMatchingFeature(D,K,he,ke,qe,We,ct,Mt,Ut,nr,Sr){let Or=this.bucketLayerIDs[K];if(We&&!function(qa,Ja){for(let Hi=0;Hi=0)return!0;return!1}(We,Or))return;let Hr=this.sourceLayerCoder.decode(he),oa=this.vtLayers[Hr].feature(ke);if(qe.needGeometry){let qa=Wl(oa,!0);if(!qe.filter(new Ls(this.tileID.overscaledZ),qa,this.tileID.canonical))return}else if(!qe.filter(new Ls(this.tileID.overscaledZ),oa))return;let pa=this.getId(oa,Hr);for(let qa=0;qa{let ct=D instanceof _c?D.get(We):null;return ct&&ct.evaluate?ct.evaluate(K,he,ke):ct})}function Wx(H){let D=1/0,K=1/0,he=-1/0,ke=-1/0;for(let qe of H)D=Math.min(D,qe.x),K=Math.min(K,qe.y),he=Math.max(he,qe.x),ke=Math.max(ke,qe.y);return{minX:D,minY:K,maxX:he,maxY:ke}}function eA(H,D){return D-H}function Xx(H,D,K,he,ke){let qe=[];for(let We=0;We=he&&Sr.x>=he||(nr.x>=he?nr=new n(he,nr.y+(he-nr.x)/(Sr.x-nr.x)*(Sr.y-nr.y))._round():Sr.x>=he&&(Sr=new n(he,nr.y+(he-nr.x)/(Sr.x-nr.x)*(Sr.y-nr.y))._round()),nr.y>=ke&&Sr.y>=ke||(nr.y>=ke?nr=new n(nr.x+(ke-nr.y)/(Sr.y-nr.y)*(Sr.x-nr.x),ke)._round():Sr.y>=ke&&(Sr=new n(nr.x+(ke-nr.y)/(Sr.y-nr.y)*(Sr.x-nr.x),ke)._round()),Mt&&nr.equals(Mt[Mt.length-1])||(Mt=[nr],qe.push(Mt)),Mt.push(Sr)))))}}return qe}yi("FeatureIndex",zv,{omit:["rawTileData","sourceLayerCoder"]});class Wd extends n{constructor(D,K,he,ke){super(D,K),this.angle=he,ke!==void 0&&(this.segment=ke)}clone(){return new Wd(this.x,this.y,this.angle,this.segment)}}function G1(H,D,K,he,ke){if(D.segment===void 0||K===0)return!0;let qe=D,We=D.segment+1,ct=0;for(;ct>-K/2;){if(We--,We<0)return!1;ct-=H[We].dist(qe),qe=H[We]}ct+=H[We].dist(H[We+1]),We++;let Mt=[],Ut=0;for(;cthe;)Ut-=Mt.shift().angleDelta;if(Ut>ke)return!1;We++,ct+=nr.dist(Sr)}return!0}function Zx(H){let D=0;for(let K=0;KUt){let oa=(Ut-Mt)/Hr,pa=Hn.number(Sr.x,Or.x,oa),qa=Hn.number(Sr.y,Or.y,oa),Ja=new Wd(pa,qa,Or.angleTo(Sr),nr);return Ja._round(),!We||G1(H,Ja,ct,We,D)?Ja:void 0}Mt+=Hr}}function rA(H,D,K,he,ke,qe,We,ct,Mt){let Ut=Yx(he,qe,We),nr=Kx(he,ke),Sr=nr*We,Or=H[0].x===0||H[0].x===Mt||H[0].y===0||H[0].y===Mt;return D-Sr=0&&qi=0&&en=0&&Or+Ut<=nr){let jn=new Wd(qi,en,Hi,oa);jn._round(),he&&!G1(H,jn,qe,he,ke)||Hr.push(jn)}}Sr+=Ja}return ct||Hr.length||We||(Hr=Jx(H,Sr/2,K,he,ke,qe,We,!0,Mt)),Hr}yi("Anchor",Wd);let hm=zh;function $x(H,D,K,he){let ke=[],qe=H.image,We=qe.pixelRatio,ct=qe.paddedRect.w-2*hm,Mt=qe.paddedRect.h-2*hm,Ut={x1:H.left,y1:H.top,x2:H.right,y2:H.bottom},nr=qe.stretchX||[[0,ct]],Sr=qe.stretchY||[[0,Mt]],Or=(wn,cs)=>wn+cs[1]-cs[0],Hr=nr.reduce(Or,0),oa=Sr.reduce(Or,0),pa=ct-Hr,qa=Mt-oa,Ja=0,Hi=Hr,_i=0,qi=oa,en=0,jn=pa,Lo=0,_s=qa;if(qe.content&&he){let wn=qe.content,cs=wn[2]-wn[0],No=wn[3]-wn[1];(qe.textFitWidth||qe.textFitHeight)&&(Ut=zx(H)),Ja=Xd(nr,0,wn[0]),_i=Xd(Sr,0,wn[1]),Hi=Xd(nr,wn[0],wn[2]),qi=Xd(Sr,wn[1],wn[3]),en=wn[0]-Ja,Lo=wn[1]-_i,jn=cs-Hi,_s=No-qi}let vo=Ut.x1,zn=Ut.y1,is=Ut.x2-vo,jo=Ut.y2-zn,Bo=(wn,cs,No,ks)=>{let Ku=Pg(wn.stretch-Ja,Hi,is,vo),Uu=pm(wn.fixed-en,jn,wn.stretch,Hr),th=Pg(cs.stretch-_i,qi,jo,zn),Hp=pm(cs.fixed-Lo,_s,cs.stretch,oa),wh=Pg(No.stretch-Ja,Hi,is,vo),rh=pm(No.fixed-en,jn,No.stretch,Hr),Jh=Pg(ks.stretch-_i,qi,jo,zn),$h=pm(ks.fixed-Lo,_s,ks.stretch,oa),Qh=new n(Ku,th),cf=new n(wh,th),ah=new n(wh,Jh),Fh=new n(Ku,Jh),Th=new n(Uu/We,Hp/We),hh=new n(rh/We,$h/We),gf=D*Math.PI/180;if(gf){let fu=Math.sin(gf),hc=Math.cos(gf),Ju=[hc,-fu,fu,hc];Qh._matMult(Ju),cf._matMult(Ju),Fh._matMult(Ju),ah._matMult(Ju)}let Rp=wn.stretch+wn.fixed,dp=cs.stretch+cs.fixed;return{tl:Qh,tr:cf,bl:Fh,br:ah,tex:{x:qe.paddedRect.x+hm+Rp,y:qe.paddedRect.y+hm+dp,w:No.stretch+No.fixed-Rp,h:ks.stretch+ks.fixed-dp},writingMode:void 0,glyphOffset:[0,0],sectionIndex:0,pixelOffsetTL:Th,pixelOffsetBR:hh,minFontScaleX:jn/We/is,minFontScaleY:_s/We/jo,isSDF:K}};if(he&&(qe.stretchX||qe.stretchY)){let wn=Qx(nr,pa,Hr),cs=Qx(Sr,qa,oa);for(let No=0;No0&&(pa=Math.max(10,pa),this.circleDiameter=pa)}else{let Or=!((Sr=We.image)===null||Sr===void 0)&&Sr.content&&(We.image.textFitWidth||We.image.textFitHeight)?zx(We):{x1:We.left,y1:We.top,x2:We.right,y2:We.bottom};Or.y1=Or.y1*ct-Mt[0],Or.y2=Or.y2*ct+Mt[2],Or.x1=Or.x1*ct-Mt[3],Or.x2=Or.x2*ct+Mt[1];let Hr=We.collisionPadding;if(Hr&&(Or.x1-=Hr[0]*ct,Or.y1-=Hr[1]*ct,Or.x2+=Hr[2]*ct,Or.y2+=Hr[3]*ct),nr){let oa=new n(Or.x1,Or.y1),pa=new n(Or.x2,Or.y1),qa=new n(Or.x1,Or.y2),Ja=new n(Or.x2,Or.y2),Hi=nr*Math.PI/180;oa._rotate(Hi),pa._rotate(Hi),qa._rotate(Hi),Ja._rotate(Hi),Or.x1=Math.min(oa.x,pa.x,qa.x,Ja.x),Or.x2=Math.max(oa.x,pa.x,qa.x,Ja.x),Or.y1=Math.min(oa.y,pa.y,qa.y,Ja.y),Or.y2=Math.max(oa.y,pa.y,qa.y,Ja.y)}D.emplaceBack(K.x,K.y,Or.x1,Or.y1,Or.x2,Or.y2,he,ke,qe)}this.boxEndIndex=D.length}}class cd{constructor(D=[],K=(he,ke)=>heke?1:0){if(this.data=D,this.length=this.data.length,this.compare=K,this.length>0)for(let he=(this.length>>1)-1;he>=0;he--)this._down(he)}push(D){this.data.push(D),this._up(this.length++)}pop(){if(this.length===0)return;let D=this.data[0],K=this.data.pop();return--this.length>0&&(this.data[0]=K,this._down(0)),D}peek(){return this.data[0]}_up(D){let{data:K,compare:he}=this,ke=K[D];for(;D>0;){let qe=D-1>>1,We=K[qe];if(he(ke,We)>=0)break;K[D]=We,D=qe}K[D]=ke}_down(D){let{data:K,compare:he}=this,ke=this.length>>1,qe=K[D];for(;D=0)break;K[D]=K[We],D=We}K[D]=qe}}function aA(H,D=1,K=!1){let he=1/0,ke=1/0,qe=-1/0,We=-1/0,ct=H[0];for(let Hr=0;Hrqe)&&(qe=oa.x),(!Hr||oa.y>We)&&(We=oa.y)}let Mt=Math.min(qe-he,We-ke),Ut=Mt/2,nr=new cd([],iA);if(Mt===0)return new n(he,ke);for(let Hr=he;HrSr.d||!Sr.d)&&(Sr=Hr,K&&console.log("found best %d after %d probes",Math.round(1e4*Hr.d)/1e4,Or)),Hr.max-Sr.d<=D||(Ut=Hr.h/2,nr.push(new dm(Hr.p.x-Ut,Hr.p.y-Ut,Ut,H)),nr.push(new dm(Hr.p.x+Ut,Hr.p.y-Ut,Ut,H)),nr.push(new dm(Hr.p.x-Ut,Hr.p.y+Ut,Ut,H)),nr.push(new dm(Hr.p.x+Ut,Hr.p.y+Ut,Ut,H)),Or+=4)}return K&&(console.log(`num probes: ${Or}`),console.log(`best distance: ${Sr.d}`)),Sr.p}function iA(H,D){return D.max-H.max}function dm(H,D,K,he){this.p=new n(H,D),this.h=K,this.d=function(ke,qe){let We=!1,ct=1/0;for(let Mt=0;Mtke.y!=oa.y>ke.y&&ke.x<(oa.x-Hr.x)*(ke.y-Hr.y)/(oa.y-Hr.y)+Hr.x&&(We=!We),ct=Math.min(ct,_a(ke,Hr,oa))}}return(We?1:-1)*Math.sqrt(ct)}(this.p,he),this.max=this.d+this.h*Math.SQRT2}var bh;e.aq=void 0,(bh=e.aq||(e.aq={}))[bh.center=1]="center",bh[bh.left=2]="left",bh[bh.right=3]="right",bh[bh.top=4]="top",bh[bh.bottom=5]="bottom",bh[bh["top-left"]=6]="top-left",bh[bh["top-right"]=7]="top-right",bh[bh["bottom-left"]=8]="bottom-left",bh[bh["bottom-right"]=9]="bottom-right";let pv=7,Fv=Number.POSITIVE_INFINITY;function H1(H,D){return D[1]!==Fv?function(K,he,ke){let qe=0,We=0;switch(he=Math.abs(he),ke=Math.abs(ke),K){case"top-right":case"top-left":case"top":We=ke-pv;break;case"bottom-right":case"bottom-left":case"bottom":We=-ke+pv}switch(K){case"top-right":case"bottom-right":case"right":qe=-he;break;case"top-left":case"bottom-left":case"left":qe=he}return[qe,We]}(H,D[0],D[1]):function(K,he){let ke=0,qe=0;he<0&&(he=0);let We=he/Math.SQRT2;switch(K){case"top-right":case"top-left":qe=We-pv;break;case"bottom-right":case"bottom-left":qe=-We+pv;break;case"bottom":qe=-he+pv;break;case"top":qe=he-pv}switch(K){case"top-right":case"bottom-right":ke=-We;break;case"top-left":case"bottom-left":ke=We;break;case"left":ke=he;break;case"right":ke=-he}return[ke,qe]}(H,D[0])}function eb(H,D,K){var he;let ke=H.layout,qe=(he=ke.get("text-variable-anchor-offset"))===null||he===void 0?void 0:he.evaluate(D,{},K);if(qe){let ct=qe.values,Mt=[];for(let Ut=0;UtOr*cu);nr.startsWith("top")?Sr[1]-=pv:nr.startsWith("bottom")&&(Sr[1]+=pv),Mt[Ut+1]=Sr}return new $a(Mt)}let We=ke.get("text-variable-anchor");if(We){let ct;ct=H._unevaluatedLayout.getValue("text-radial-offset")!==void 0?[ke.get("text-radial-offset").evaluate(D,{},K)*cu,Fv]:ke.get("text-offset").evaluate(D,{},K).map(Ut=>Ut*cu);let Mt=[];for(let Ut of We)Mt.push(Ut,H1(Ut,ct));return new $a(Mt)}return null}function W1(H){switch(H){case"right":case"top-right":case"bottom-right":return"right";case"left":case"top-left":case"bottom-left":return"left"}return"center"}function nA(H,D,K,he,ke,qe,We,ct,Mt,Ut,nr){let Sr=qe.textMaxSize.evaluate(D,{});Sr===void 0&&(Sr=We);let Or=H.layers[0].layout,Hr=Or.get("icon-offset").evaluate(D,{},nr),oa=rb(K.horizontal),pa=We/24,qa=H.tilePixelRatio*pa,Ja=H.tilePixelRatio*Sr/24,Hi=H.tilePixelRatio*ct,_i=H.tilePixelRatio*Or.get("symbol-spacing"),qi=Or.get("text-padding")*H.tilePixelRatio,en=function(wn,cs,No,ks=1){let Ku=wn.get("icon-padding").evaluate(cs,{},No),Uu=Ku&&Ku.values;return[Uu[0]*ks,Uu[1]*ks,Uu[2]*ks,Uu[3]*ks]}(Or,D,nr,H.tilePixelRatio),jn=Or.get("text-max-angle")/180*Math.PI,Lo=Or.get("text-rotation-alignment")!=="viewport"&&Or.get("symbol-placement")!=="point",_s=Or.get("icon-rotation-alignment")==="map"&&Or.get("symbol-placement")!=="point",vo=Or.get("symbol-placement"),zn=_i/2,is=Or.get("icon-text-fit"),jo;he&&is!=="none"&&(H.allowVerticalPlacement&&K.vertical&&(jo=Fx(he,K.vertical,is,Or.get("icon-text-fit-padding"),Hr,pa)),oa&&(he=Fx(he,oa,is,Or.get("icon-text-fit-padding"),Hr,pa)));let Bo=(wn,cs)=>{cs.x<0||cs.x>=fo||cs.y<0||cs.y>=fo||function(No,ks,Ku,Uu,th,Hp,wh,rh,Jh,$h,Qh,cf,ah,Fh,Th,hh,gf,Rp,dp,fu,hc,Ju,Dp,Jc,vm){let _d=No.addToLineVertexArray(ks,Ku),fd,Wp,zc,Pf,Xp=0,Zd=0,vp=0,mm=0,J1=-1,zg=-1,xd={},Ov=ai("");if(No.allowVerticalPlacement&&Uu.vertical){let Oh=rh.layout.get("text-rotate").evaluate(hc,{},Jc)+90;zc=new hv(Jh,ks,$h,Qh,cf,Uu.vertical,ah,Fh,Th,Oh),wh&&(Pf=new hv(Jh,ks,$h,Qh,cf,wh,gf,Rp,Th,Oh))}if(th){let Oh=rh.layout.get("icon-rotate").evaluate(hc,{}),Zp=rh.layout.get("icon-text-fit")!=="none",dv=$x(th,Oh,Dp,Zp),ep=wh?$x(wh,Oh,Dp,Zp):void 0;Wp=new hv(Jh,ks,$h,Qh,cf,th,gf,Rp,!1,Oh),Xp=4*dv.length;let Bh=No.iconSizeData,id=null;Bh.kind==="source"?(id=[yd*rh.layout.get("icon-size").evaluate(hc,{})],id[0]>cv&&f(`${No.layerIds[0]}: Value for "icon-size" is >= ${E0}. 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Array(this.options.maxZoom+1),this.stride=this.options.reduce?7:6,this.clusterProps=[]}load(Ne){let{log:Ke,minZoom:Te,maxZoom:Pe}=this.options;Ke&&console.time("total time");let je=`prepare ${Ne.length} points`;Ke&&console.time(je),this.points=Ne;let Ce=[];for(let Ie=0;Ie=Te;Ie--){let ot=+Date.now();Ee=this.trees[Ie]=this._createTree(this._cluster(Ee,Ie)),Ke&&console.log("z%d: %d clusters in %dms",Ie,Ee.numItems,+Date.now()-ot)}return Ke&&console.timeEnd("total time"),this}getClusters(Ne,Ke){let Te=((Ne[0]+180)%360+360)%360-180,Pe=Math.max(-90,Math.min(90,Ne[1])),je=Ne[2]===180?180:((Ne[2]+180)%360+360)%360-180,Ce=Math.max(-90,Math.min(90,Ne[3]));if(Ne[2]-Ne[0]>=360)Te=-180,je=180;else if(Te>je){let xt=this.getClusters([Te,Pe,180,Ce],Ke),It=this.getClusters([-180,Pe,je,Ce],Ke);return xt.concat(It)}let Ee=this.trees[this._limitZoom(Ke)],Ie=Ee.range(pe(Te),V(Ce),pe(je),V(Pe)),ot=Ee.data,gt=[];for(let xt of Ie){let It=this.stride*xt;gt.push(ot[It+U]>1?ue(ot,It,this.clusterProps):this.points[ot[It+N]])}return gt}getChildren(Ne){let Ke=this._getOriginId(Ne),Te=this._getOriginZoom(Ne),Pe="No cluster with the specified id.",je=this.trees[Te];if(!je)throw new Error(Pe);let Ce=je.data;if(Ke*this.stride>=Ce.length)throw new Error(Pe);let Ee=this.options.radius/(this.options.extent*Math.pow(2,Te-1)),Ie=je.within(Ce[Ke*this.stride],Ce[Ke*this.stride+1],Ee),ot=[];for(let gt of Ie){let xt=gt*this.stride;Ce[xt+4]===Ne&&ot.push(Ce[xt+U]>1?ue(Ce,xt,this.clusterProps):this.points[Ce[xt+N]])}if(ot.length===0)throw new Error(Pe);return ot}getLeaves(Ne,Ke,Te){let Pe=[];return this._appendLeaves(Pe,Ne,Ke=Ke||10,Te=Te||0,0),Pe}getTile(Ne,Ke,Te){let Pe=this.trees[this._limitZoom(Ne)],je=Math.pow(2,Ne),{extent:Ce,radius:Ee}=this.options,Ie=Ee/Ce,ot=(Te-Ie)/je,gt=(Te+1+Ie)/je,xt={features:[]};return this._addTileFeatures(Pe.range((Ke-Ie)/je,ot,(Ke+1+Ie)/je,gt),Pe.data,Ke,Te,je,xt),Ke===0&&this._addTileFeatures(Pe.range(1-Ie/je,ot,1,gt),Pe.data,je,Te,je,xt),Ke===je-1&&this._addTileFeatures(Pe.range(0,ot,Ie/je,gt),Pe.data,-1,Te,je,xt),xt.features.length?xt:null}getClusterExpansionZoom(Ne){let Ke=this._getOriginZoom(Ne)-1;for(;Ke<=this.options.maxZoom;){let Te=this.getChildren(Ne);if(Ke++,Te.length!==1)break;Ne=Te[0].properties.cluster_id}return Ke}_appendLeaves(Ne,Ke,Te,Pe,je){let Ce=this.getChildren(Ke);for(let Ee of Ce){let Ie=Ee.properties;if(Ie&&Ie.cluster?je+Ie.point_count<=Pe?je+=Ie.point_count:je=this._appendLeaves(Ne,Ie.cluster_id,Te,Pe,je):je1,gt,xt,It;if(ot)gt=se(Ke,Ie,this.clusterProps),xt=Ke[Ie],It=Ke[Ie+1];else{let tr=this.points[Ke[Ie+N]];gt=tr.properties;let[Lr,ha]=tr.geometry.coordinates;xt=pe(Lr),It=V(ha)}let cr={type:1,geometry:[[Math.round(this.options.extent*(xt*je-Te)),Math.round(this.options.extent*(It*je-Pe))]],tags:gt},ar;ar=ot||this.options.generateId?Ke[Ie+N]:this.points[Ke[Ie+N]].id,ar!==void 0&&(cr.id=ar),Ce.features.push(cr)}}_limitZoom(Ne){return Math.max(this.options.minZoom,Math.min(Math.floor(+Ne),this.options.maxZoom+1))}_cluster(Ne,Ke){let{radius:Te,extent:Pe,reduce:je,minPoints:Ce}=this.options,Ee=Te/(Pe*Math.pow(2,Ke)),Ie=Ne.data,ot=[],gt=this.stride;for(let xt=0;xtKe&&(Lr+=Ie[za+U])}if(Lr>tr&&Lr>=Ce){let ha,za=It*tr,Ra=cr*tr,Va=-1,Xa=((xt/gt|0)<<5)+(Ke+1)+this.points.length;for(let Pa of ar){let di=Pa*gt;if(Ie[di+2]<=Ke)continue;Ie[di+2]=Ke;let Mi=Ie[di+U];za+=Ie[di]*Mi,Ra+=Ie[di+1]*Mi,Ie[di+4]=Xa,je&&(ha||(ha=this._map(Ie,xt,!0),Va=this.clusterProps.length,this.clusterProps.push(ha)),je(ha,this._map(Ie,di)))}Ie[xt+4]=Xa,ot.push(za/Lr,Ra/Lr,1/0,Xa,-1,Lr),je&&ot.push(Va)}else{for(let ha=0;ha1)for(let ha of ar){let za=ha*gt;if(!(Ie[za+2]<=Ke)){Ie[za+2]=Ke;for(let Ra=0;Ra>5}_getOriginZoom(Ne){return(Ne-this.points.length)%32}_map(Ne,Ke,Te){if(Ne[Ke+U]>1){let Ce=this.clusterProps[Ne[Ke+W]];return Te?Object.assign({},Ce):Ce}let Pe=this.points[Ne[Ke+N]].properties,je=this.options.map(Pe);return Te&&je===Pe?Object.assign({},je):je}}function ue(bt,Ne,Ke){return{type:"Feature",id:bt[Ne+N],properties:se(bt,Ne,Ke),geometry:{type:"Point",coordinates:[(Te=bt[Ne],360*(Te-.5)),$(bt[Ne+1])]}};var Te}function se(bt,Ne,Ke){let Te=bt[Ne+U],Pe=Te>=1e4?`${Math.round(Te/1e3)}k`:Te>=1e3?Math.round(Te/100)/10+"k":Te,je=bt[Ne+W],Ce=je===-1?{}:Object.assign({},Ke[je]);return Object.assign(Ce,{cluster:!0,cluster_id:bt[Ne+N],point_count:Te,point_count_abbreviated:Pe})}function pe(bt){return bt/360+.5}function V(bt){let Ne=Math.sin(bt*Math.PI/180),Ke=.5-.25*Math.log((1+Ne)/(1-Ne))/Math.PI;return Ke<0?0:Ke>1?1:Ke}function $(bt){let Ne=(180-360*bt)*Math.PI/180;return 360*Math.atan(Math.exp(Ne))/Math.PI-90}function J(bt,Ne,Ke,Te){let Pe=Te,je=Ne+(Ke-Ne>>1),Ce,Ee=Ke-Ne,Ie=bt[Ne],ot=bt[Ne+1],gt=bt[Ke],xt=bt[Ke+1];for(let It=Ne+3;ItPe)Ce=It,Pe=cr;else if(cr===Pe){let ar=Math.abs(It-je);arTe&&(Ce-Ne>3&&J(bt,Ne,Ce,Te),bt[Ce+2]=Pe,Ke-Ce>3&&J(bt,Ce,Ke,Te))}function X(bt,Ne,Ke,Te,Pe,je){let Ce=Pe-Ke,Ee=je-Te;if(Ce!==0||Ee!==0){let Ie=((bt-Ke)*Ce+(Ne-Te)*Ee)/(Ce*Ce+Ee*Ee);Ie>1?(Ke=Pe,Te=je):Ie>0&&(Ke+=Ce*Ie,Te+=Ee*Ie)}return Ce=bt-Ke,Ee=Ne-Te,Ce*Ce+Ee*Ee}function oe(bt,Ne,Ke,Te){let Pe={id:bt??null,type:Ne,geometry:Ke,tags:Te,minX:1/0,minY:1/0,maxX:-1/0,maxY:-1/0};if(Ne==="Point"||Ne==="MultiPoint"||Ne==="LineString")ie(Pe,Ke);else if(Ne==="Polygon")ie(Pe,Ke[0]);else if(Ne==="MultiLineString")for(let je of Ke)ie(Pe,je);else if(Ne==="MultiPolygon")for(let je of Ke)ie(Pe,je[0]);return Pe}function ie(bt,Ne){for(let Ke=0;Ke0&&(Ce+=Te?(Pe*gt-ot*je)/2:Math.sqrt(Math.pow(ot-Pe,2)+Math.pow(gt-je,2))),Pe=ot,je=gt}let Ee=Ne.length-3;Ne[2]=1,J(Ne,0,Ee,Ke),Ne[Ee+2]=1,Ne.size=Math.abs(Ce),Ne.start=0,Ne.end=Ne.size}function ce(bt,Ne,Ke,Te){for(let Pe=0;Pe1?1:Ke}function De(bt,Ne,Ke,Te,Pe,je,Ce,Ee){if(Te/=Ne,je>=(Ke/=Ne)&&Ce=Te)return null;let Ie=[];for(let ot of bt){let gt=ot.geometry,xt=ot.type,It=Pe===0?ot.minX:ot.minY,cr=Pe===0?ot.maxX:ot.maxY;if(It>=Ke&&cr=Te)continue;let ar=[];if(xt==="Point"||xt==="MultiPoint")Fe(gt,ar,Ke,Te,Pe);else if(xt==="LineString")Ze(gt,ar,Ke,Te,Pe,!1,Ee.lineMetrics);else if(xt==="MultiLineString")nt(gt,ar,Ke,Te,Pe,!1);else if(xt==="Polygon")nt(gt,ar,Ke,Te,Pe,!0);else if(xt==="MultiPolygon")for(let tr of gt){let Lr=[];nt(tr,Lr,Ke,Te,Pe,!0),Lr.length&&ar.push(Lr)}if(ar.length){if(Ee.lineMetrics&&xt==="LineString"){for(let tr of ar)Ie.push(oe(ot.id,xt,tr,ot.tags));continue}xt!=="LineString"&&xt!=="MultiLineString"||(ar.length===1?(xt="LineString",ar=ar[0]):xt="MultiLineString"),xt!=="Point"&&xt!=="MultiPoint"||(xt=ar.length===3?"Point":"MultiPoint"),Ie.push(oe(ot.id,xt,ar,ot.tags))}}return Ie.length?Ie:null}function Fe(bt,Ne,Ke,Te,Pe){for(let je=0;je=Ke&&Ce<=Te&&tt(Ne,bt[je],bt[je+1],bt[je+2])}}function Ze(bt,Ne,Ke,Te,Pe,je,Ce){let Ee=at(bt),Ie=Pe===0?ut:Me,ot,gt,xt=bt.start;for(let Lr=0;LrKe&&(gt=Ie(Ee,ha,za,Va,Xa,Ke),Ce&&(Ee.start=xt+ot*gt)):Pa>Te?di=Ke&&(gt=Ie(Ee,ha,za,Va,Xa,Ke),Mi=!0),di>Te&&Pa<=Te&&(gt=Ie(Ee,ha,za,Va,Xa,Te),Mi=!0),!je&&Mi&&(Ce&&(Ee.end=xt+ot*gt),Ne.push(Ee),Ee=at(bt)),Ce&&(xt+=ot)}let It=bt.length-3,cr=bt[It],ar=bt[It+1],tr=Pe===0?cr:ar;tr>=Ke&&tr<=Te&&tt(Ee,cr,ar,bt[It+2]),It=Ee.length-3,je&&It>=3&&(Ee[It]!==Ee[0]||Ee[It+1]!==Ee[1])&&tt(Ee,Ee[0],Ee[1],Ee[2]),Ee.length&&Ne.push(Ee)}function at(bt){let Ne=[];return Ne.size=bt.size,Ne.start=bt.start,Ne.end=bt.end,Ne}function nt(bt,Ne,Ke,Te,Pe,je){for(let Ce of bt)Ze(Ce,Ne,Ke,Te,Pe,je,!1)}function tt(bt,Ne,Ke,Te){bt.push(Ne,Ke,Te)}function ut(bt,Ne,Ke,Te,Pe,je){let Ce=(je-Ne)/(Te-Ne);return tt(bt,je,Ke+(Pe-Ke)*Ce,1),Ce}function Me(bt,Ne,Ke,Te,Pe,je){let Ce=(je-Ke)/(Pe-Ke);return tt(bt,Ne+(Te-Ne)*Ce,je,1),Ce}function _e(bt,Ne){let Ke=[];for(let Te=0;Te0&&Ne.size<(Pe?Ce:Te))return void(Ke.numPoints+=Ne.length/3);let Ee=[];for(let Ie=0;IeCe)&&(Ke.numSimplified++,Ee.push(Ne[Ie],Ne[Ie+1])),Ke.numPoints++;Pe&&function(Ie,ot){let gt=0;for(let xt=0,It=Ie.length,cr=It-2;xt0===ot)for(let xt=0,It=Ie.length;xt24)throw new Error("maxZoom should be in the 0-24 range");if(Ke.promoteId&&Ke.generateId)throw new Error("promoteId and generateId cannot be used together.");let Pe=function(je,Ce){let Ee=[];if(je.type==="FeatureCollection")for(let Ie=0;Ie1&&console.time("creation"),cr=this.tiles[It]=st(Ne,Ke,Te,Pe,ot),this.tileCoords.push({z:Ke,x:Te,y:Pe}),gt)){gt>1&&(console.log("tile z%d-%d-%d (features: %d, points: %d, simplified: %d)",Ke,Te,Pe,cr.numFeatures,cr.numPoints,cr.numSimplified),console.timeEnd("creation"));let Mi=`z${Ke}`;this.stats[Mi]=(this.stats[Mi]||0)+1,this.total++}if(cr.source=Ne,je==null){if(Ke===ot.indexMaxZoom||cr.numPoints<=ot.indexMaxPoints)continue}else{if(Ke===ot.maxZoom||Ke===je)continue;if(je!=null){let Mi=je-Ke;if(Te!==Ce>>Mi||Pe!==Ee>>Mi)continue}}if(cr.source=null,Ne.length===0)continue;gt>1&&console.time("clipping");let ar=.5*ot.buffer/ot.extent,tr=.5-ar,Lr=.5+ar,ha=1+ar,za=null,Ra=null,Va=null,Xa=null,Pa=De(Ne,xt,Te-ar,Te+Lr,0,cr.minX,cr.maxX,ot),di=De(Ne,xt,Te+tr,Te+ha,0,cr.minX,cr.maxX,ot);Ne=null,Pa&&(za=De(Pa,xt,Pe-ar,Pe+Lr,1,cr.minY,cr.maxY,ot),Ra=De(Pa,xt,Pe+tr,Pe+ha,1,cr.minY,cr.maxY,ot),Pa=null),di&&(Va=De(di,xt,Pe-ar,Pe+Lr,1,cr.minY,cr.maxY,ot),Xa=De(di,xt,Pe+tr,Pe+ha,1,cr.minY,cr.maxY,ot),di=null),gt>1&&console.timeEnd("clipping"),Ie.push(za||[],Ke+1,2*Te,2*Pe),Ie.push(Ra||[],Ke+1,2*Te,2*Pe+1),Ie.push(Va||[],Ke+1,2*Te+1,2*Pe),Ie.push(Xa||[],Ke+1,2*Te+1,2*Pe+1)}}getTile(Ne,Ke,Te){Ne=+Ne,Ke=+Ke,Te=+Te;let Pe=this.options,{extent:je,debug:Ce}=Pe;if(Ne<0||Ne>24)return null;let Ee=1<1&&console.log("drilling down to z%d-%d-%d",Ne,Ke,Te);let ot,gt=Ne,xt=Ke,It=Te;for(;!ot&>>0;)gt--,xt>>=1,It>>=1,ot=this.tiles[Ht(gt,xt,It)];return ot&&ot.source?(Ce>1&&(console.log("found parent tile z%d-%d-%d",gt,xt,It),console.time("drilling down")),this.splitTile(ot.source,gt,xt,It,Ne,Ke,Te),Ce>1&&console.timeEnd("drilling down"),this.tiles[Ie]?Oe(this.tiles[Ie],je):null):null}}function Ht(bt,Ne,Ke){return 32*((1<{xt.properties=cr;let ar={};for(let tr of It)ar[tr]=Ie[tr].evaluate(gt,xt);return ar},Ce.reduce=(cr,ar)=>{xt.properties=ar;for(let tr of It)gt.accumulated=cr[tr],cr[tr]=ot[tr].evaluate(gt,xt)},Ce}(Ne)).load((yield this._pendingData).features):(Pe=yield this._pendingData,new qt(Pe,Ne.geojsonVtOptions)),this.loaded={};let je={};if(Te){let Ce=Te.finish();Ce&&(je.resourceTiming={},je.resourceTiming[Ne.source]=JSON.parse(JSON.stringify(Ce)))}return je}catch(je){if(delete this._pendingRequest,e.bB(je))return{abandoned:!0};throw je}var Pe})}getData(){return e._(this,void 0,void 0,function*(){return this._pendingData})}reloadTile(Ne){let Ke=this.loaded;return Ke&&Ke[Ne.uid]?super.reloadTile(Ne):this.loadTile(Ne)}loadAndProcessGeoJSON(Ne,Ke){return e._(this,void 0,void 0,function*(){let Te=yield this.loadGeoJSON(Ne,Ke);if(delete this._pendingRequest,typeof Te!="object")throw new Error(`Input data given to '${Ne.source}' is not a valid GeoJSON object.`);if(c(Te,!0),Ne.filter){let Pe=e.bC(Ne.filter,{type:"boolean","property-type":"data-driven",overridable:!1,transition:!1});if(Pe.result==="error")throw new Error(Pe.value.map(Ce=>`${Ce.key}: ${Ce.message}`).join(", "));Te={type:"FeatureCollection",features:Te.features.filter(Ce=>Pe.value.evaluate({zoom:0},Ce))}}return Te})}loadGeoJSON(Ne,Ke){return e._(this,void 0,void 0,function*(){let{promoteId:Te}=Ne;if(Ne.request){let Pe=yield e.h(Ne.request,Ke);return this._dataUpdateable=xr(Pe.data,Te)?qr(Pe.data,Te):void 0,Pe.data}if(typeof Ne.data=="string")try{let Pe=JSON.parse(Ne.data);return this._dataUpdateable=xr(Pe,Te)?qr(Pe,Te):void 0,Pe}catch{throw new Error(`Input data given to '${Ne.source}' is not a valid GeoJSON object.`)}if(!Ne.dataDiff)throw new Error(`Input data given to '${Ne.source}' is not a valid GeoJSON object.`);if(!this._dataUpdateable)throw new Error(`Cannot update existing geojson data in ${Ne.source}`);return function(Pe,je,Ce){var Ee,Ie,ot,gt;if(je.removeAll&&Pe.clear(),je.remove)for(let xt of je.remove)Pe.delete(xt);if(je.add)for(let xt of je.add){let It=Ar(xt,Ce);It!=null&&Pe.set(It,xt)}if(je.update)for(let xt of je.update){let It=Pe.get(xt.id);if(It==null)continue;let cr=!xt.removeAllProperties&&(((Ee=xt.removeProperties)===null||Ee===void 0?void 0:Ee.length)>0||((Ie=xt.addOrUpdateProperties)===null||Ie===void 0?void 0:Ie.length)>0);if((xt.newGeometry||xt.removeAllProperties||cr)&&(It=Object.assign({},It),Pe.set(xt.id,It),cr&&(It.properties=Object.assign({},It.properties))),xt.newGeometry&&(It.geometry=xt.newGeometry),xt.removeAllProperties)It.properties={};else if(((ot=xt.removeProperties)===null||ot===void 0?void 0:ot.length)>0)for(let ar of xt.removeProperties)Object.prototype.hasOwnProperty.call(It.properties,ar)&&delete It.properties[ar];if(((gt=xt.addOrUpdateProperties)===null||gt===void 0?void 0:gt.length)>0)for(let{key:ar,value:tr}of xt.addOrUpdateProperties)It.properties[ar]=tr}}(this._dataUpdateable,Ne.dataDiff,Te),{type:"FeatureCollection",features:Array.from(this._dataUpdateable.values())}})}removeSource(Ne){return e._(this,void 0,void 0,function*(){this._pendingRequest&&this._pendingRequest.abort()})}getClusterExpansionZoom(Ne){return this._geoJSONIndex.getClusterExpansionZoom(Ne.clusterId)}getClusterChildren(Ne){return this._geoJSONIndex.getChildren(Ne.clusterId)}getClusterLeaves(Ne){return this._geoJSONIndex.getLeaves(Ne.clusterId,Ne.limit,Ne.offset)}}class Ir{constructor(Ne){this.self=Ne,this.actor=new e.F(Ne),this.layerIndexes={},this.availableImages={},this.workerSources={},this.demWorkerSources={},this.externalWorkerSourceTypes={},this.self.registerWorkerSource=(Ke,Te)=>{if(this.externalWorkerSourceTypes[Ke])throw new Error(`Worker source with name "${Ke}" already registered.`);this.externalWorkerSourceTypes[Ke]=Te},this.self.addProtocol=e.bi,this.self.removeProtocol=e.bj,this.self.registerRTLTextPlugin=Ke=>{if(e.bD.isParsed())throw new Error("RTL text plugin already registered.");e.bD.setMethods(Ke)},this.actor.registerMessageHandler("LDT",(Ke,Te)=>this._getDEMWorkerSource(Ke,Te.source).loadTile(Te)),this.actor.registerMessageHandler("RDT",(Ke,Te)=>e._(this,void 0,void 0,function*(){this._getDEMWorkerSource(Ke,Te.source).removeTile(Te)})),this.actor.registerMessageHandler("GCEZ",(Ke,Te)=>e._(this,void 0,void 0,function*(){return this._getWorkerSource(Ke,Te.type,Te.source).getClusterExpansionZoom(Te)})),this.actor.registerMessageHandler("GCC",(Ke,Te)=>e._(this,void 0,void 0,function*(){return this._getWorkerSource(Ke,Te.type,Te.source).getClusterChildren(Te)})),this.actor.registerMessageHandler("GCL",(Ke,Te)=>e._(this,void 0,void 0,function*(){return this._getWorkerSource(Ke,Te.type,Te.source).getClusterLeaves(Te)})),this.actor.registerMessageHandler("LD",(Ke,Te)=>this._getWorkerSource(Ke,Te.type,Te.source).loadData(Te)),this.actor.registerMessageHandler("GD",(Ke,Te)=>this._getWorkerSource(Ke,Te.type,Te.source).getData()),this.actor.registerMessageHandler("LT",(Ke,Te)=>this._getWorkerSource(Ke,Te.type,Te.source).loadTile(Te)),this.actor.registerMessageHandler("RT",(Ke,Te)=>this._getWorkerSource(Ke,Te.type,Te.source).reloadTile(Te)),this.actor.registerMessageHandler("AT",(Ke,Te)=>this._getWorkerSource(Ke,Te.type,Te.source).abortTile(Te)),this.actor.registerMessageHandler("RMT",(Ke,Te)=>this._getWorkerSource(Ke,Te.type,Te.source).removeTile(Te)),this.actor.registerMessageHandler("RS",(Ke,Te)=>e._(this,void 0,void 0,function*(){if(!this.workerSources[Ke]||!this.workerSources[Ke][Te.type]||!this.workerSources[Ke][Te.type][Te.source])return;let Pe=this.workerSources[Ke][Te.type][Te.source];delete this.workerSources[Ke][Te.type][Te.source],Pe.removeSource!==void 0&&Pe.removeSource(Te)})),this.actor.registerMessageHandler("RM",Ke=>e._(this,void 0,void 0,function*(){delete this.layerIndexes[Ke],delete this.availableImages[Ke],delete this.workerSources[Ke],delete this.demWorkerSources[Ke]})),this.actor.registerMessageHandler("SR",(Ke,Te)=>e._(this,void 0,void 0,function*(){this.referrer=Te})),this.actor.registerMessageHandler("SRPS",(Ke,Te)=>this._syncRTLPluginState(Ke,Te)),this.actor.registerMessageHandler("IS",(Ke,Te)=>e._(this,void 0,void 0,function*(){this.self.importScripts(Te)})),this.actor.registerMessageHandler("SI",(Ke,Te)=>this._setImages(Ke,Te)),this.actor.registerMessageHandler("UL",(Ke,Te)=>e._(this,void 0,void 0,function*(){this._getLayerIndex(Ke).update(Te.layers,Te.removedIds)})),this.actor.registerMessageHandler("SL",(Ke,Te)=>e._(this,void 0,void 0,function*(){this._getLayerIndex(Ke).replace(Te)}))}_setImages(Ne,Ke){return e._(this,void 0,void 0,function*(){this.availableImages[Ne]=Ke;for(let Te in this.workerSources[Ne]){let Pe=this.workerSources[Ne][Te];for(let je in Pe)Pe[je].availableImages=Ke}})}_syncRTLPluginState(Ne,Ke){return e._(this,void 0,void 0,function*(){if(e.bD.isParsed())return e.bD.getState();if(Ke.pluginStatus!=="loading")return e.bD.setState(Ke),Ke;let Te=Ke.pluginURL;if(this.self.importScripts(Te),e.bD.isParsed()){let Pe={pluginStatus:"loaded",pluginURL:Te};return e.bD.setState(Pe),Pe}throw e.bD.setState({pluginStatus:"error",pluginURL:""}),new Error(`RTL Text Plugin failed to import scripts from ${Te}`)})}_getAvailableImages(Ne){let Ke=this.availableImages[Ne];return Ke||(Ke=[]),Ke}_getLayerIndex(Ne){let Ke=this.layerIndexes[Ne];return Ke||(Ke=this.layerIndexes[Ne]=new t),Ke}_getWorkerSource(Ne,Ke,Te){if(this.workerSources[Ne]||(this.workerSources[Ne]={}),this.workerSources[Ne][Ke]||(this.workerSources[Ne][Ke]={}),!this.workerSources[Ne][Ke][Te]){let Pe={sendAsync:(je,Ce)=>(je.targetMapId=Ne,this.actor.sendAsync(je,Ce))};switch(Ke){case"vector":this.workerSources[Ne][Ke][Te]=new n(Pe,this._getLayerIndex(Ne),this._getAvailableImages(Ne));break;case"geojson":this.workerSources[Ne][Ke][Te]=new br(Pe,this._getLayerIndex(Ne),this._getAvailableImages(Ne));break;default:this.workerSources[Ne][Ke][Te]=new this.externalWorkerSourceTypes[Ke](Pe,this._getLayerIndex(Ne),this._getAvailableImages(Ne))}}return this.workerSources[Ne][Ke][Te]}_getDEMWorkerSource(Ne,Ke){return this.demWorkerSources[Ne]||(this.demWorkerSources[Ne]={}),this.demWorkerSources[Ne][Ke]||(this.demWorkerSources[Ne][Ke]=new i),this.demWorkerSources[Ne][Ke]}}return e.i(self)&&(self.worker=new Ir(self)),Ir}),A("index",["exports","./shared"],function(e,t){"use strict";var r="4.7.1";let o,a,n={now:typeof performance<"u"&&performance&&performance.now?performance.now.bind(performance):Date.now.bind(Date),frameAsync:Ue=>new Promise((R,ae)=>{let we=requestAnimationFrame(R);Ue.signal.addEventListener("abort",()=>{cancelAnimationFrame(we),ae(t.c())})}),getImageData(Ue,R=0){return this.getImageCanvasContext(Ue).getImageData(-R,-R,Ue.width+2*R,Ue.height+2*R)},getImageCanvasContext(Ue){let R=window.document.createElement("canvas"),ae=R.getContext("2d",{willReadFrequently:!0});if(!ae)throw new Error("failed to create canvas 2d context");return R.width=Ue.width,R.height=Ue.height,ae.drawImage(Ue,0,0,Ue.width,Ue.height),ae},resolveURL:Ue=>(o||(o=document.createElement("a")),o.href=Ue,o.href),hardwareConcurrency:typeof navigator<"u"&&navigator.hardwareConcurrency||4,get prefersReducedMotion(){return!!matchMedia&&(a==null&&(a=matchMedia("(prefers-reduced-motion: reduce)")),a.matches)}};class i{static testProp(R){if(!i.docStyle)return R[0];for(let ae=0;ae{window.removeEventListener("click",i.suppressClickInternal,!0)},0)}static getScale(R){let 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wr}function j(Ue,R){let ae=Ue.tileID,we=R.tileID;return ae.overscaledZ-we.overscaledZ||ae.canonical.y-we.canonical.y||ae.wrap-we.wrap||ae.canonical.x-we.canonical.x}function ee(Ue,R,ae){return t._(this,void 0,void 0,function*(){let we=Ue;if(Ue.url?we=(yield t.h(R.transformRequest(Ue.url,"Source"),ae)).data:yield n.frameAsync(ae),!we)return null;let Ae=t.M(t.e(we,Ue),["tiles","minzoom","maxzoom","attribution","bounds","scheme","tileSize","encoding"]);return"vector_layers"in we&&we.vector_layers&&(Ae.vectorLayerIds=we.vector_layers.map(Be=>Be.id)),Ae})}class re{constructor(R,ae){R&&(ae?this.setSouthWest(R).setNorthEast(ae):Array.isArray(R)&&(R.length===4?this.setSouthWest([R[0],R[1]]).setNorthEast([R[2],R[3]]):this.setSouthWest(R[0]).setNorthEast(R[1])))}setNorthEast(R){return this._ne=R instanceof t.N?new t.N(R.lng,R.lat):t.N.convert(R),this}setSouthWest(R){return this._sw=R instanceof t.N?new t.N(R.lng,R.lat):t.N.convert(R),this}extend(R){let ae=this._sw,we=this._ne,Ae,Be;if(R instanceof t.N)Ae=R,Be=R;else{if(!(R instanceof re))return Array.isArray(R)?R.length===4||R.every(Array.isArray)?this.extend(re.convert(R)):this.extend(t.N.convert(R)):R&&("lng"in R||"lon"in R)&&"lat"in R?this.extend(t.N.convert(R)):this;if(Ae=R._sw,Be=R._ne,!Ae||!Be)return this}return ae||we?(ae.lng=Math.min(Ae.lng,ae.lng),ae.lat=Math.min(Ae.lat,ae.lat),we.lng=Math.max(Be.lng,we.lng),we.lat=Math.max(Be.lat,we.lat)):(this._sw=new t.N(Ae.lng,Ae.lat),this._ne=new t.N(Be.lng,Be.lat)),this}getCenter(){return new t.N((this._sw.lng+this._ne.lng)/2,(this._sw.lat+this._ne.lat)/2)}getSouthWest(){return this._sw}getNorthEast(){return this._ne}getNorthWest(){return new t.N(this.getWest(),this.getNorth())}getSouthEast(){return new t.N(this.getEast(),this.getSouth())}getWest(){return this._sw.lng}getSouth(){return this._sw.lat}getEast(){return this._ne.lng}getNorth(){return this._ne.lat}toArray(){return[this._sw.toArray(),this._ne.toArray()]}toString(){return`LngLatBounds(${this._sw.toString()}, ${this._ne.toString()})`}isEmpty(){return!(this._sw&&this._ne)}contains(R){let{lng:ae,lat:we}=t.N.convert(R),Ae=this._sw.lng<=ae&&ae<=this._ne.lng;return this._sw.lng>this._ne.lng&&(Ae=this._sw.lng>=ae&&ae>=this._ne.lng),this._sw.lat<=we&&we<=this._ne.lat&&Ae}static convert(R){return R instanceof re?R:R&&new re(R)}static fromLngLat(R,ae=0){let we=360*ae/40075017,Ae=we/Math.cos(Math.PI/180*R.lat);return new re(new t.N(R.lng-Ae,R.lat-we),new t.N(R.lng+Ae,R.lat+we))}adjustAntiMeridian(){let R=new t.N(this._sw.lng,this._sw.lat),ae=new t.N(this._ne.lng,this._ne.lat);return new re(R,R.lng>ae.lng?new t.N(ae.lng+360,ae.lat):ae)}}class ce{constructor(R,ae,we){this.bounds=re.convert(this.validateBounds(R)),this.minzoom=ae||0,this.maxzoom=we||24}validateBounds(R){return Array.isArray(R)&&R.length===4?[Math.max(-180,R[0]),Math.max(-90,R[1]),Math.min(180,R[2]),Math.min(90,R[3])]:[-180,-90,180,90]}contains(R){let ae=Math.pow(2,R.z),we=Math.floor(t.O(this.bounds.getWest())*ae),Ae=Math.floor(t.Q(this.bounds.getNorth())*ae),Be=Math.ceil(t.O(this.bounds.getEast())*ae),pt=Math.ceil(t.Q(this.bounds.getSouth())*ae);return R.x>=we&&R.x=Ae&&R.y{this._options.tiles=R}),this}setUrl(R){return this.setSourceProperty(()=>{this.url=R,this._options.url=R}),this}onRemove(){this._tileJSONRequest&&(this._tileJSONRequest.abort(),this._tileJSONRequest=null)}serialize(){return t.e({},this._options)}loadTile(R){return t._(this,void 0,void 0,function*(){let ae=R.tileID.canonical.url(this.tiles,this.map.getPixelRatio(),this.scheme),we={request:this.map._requestManager.transformRequest(ae,"Tile"),uid:R.uid,tileID:R.tileID,zoom:R.tileID.overscaledZ,tileSize:this.tileSize*R.tileID.overscaleFactor(),type:this.type,source:this.id,pixelRatio:this.map.getPixelRatio(),showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};we.request.collectResourceTiming=this._collectResourceTiming;let Ae="RT";if(R.actor&&R.state!=="expired"){if(R.state==="loading")return new Promise((Be,pt)=>{R.reloadPromise={resolve:Be,reject:pt}})}else R.actor=this.dispatcher.getActor(),Ae="LT";R.abortController=new AbortController;try{let Be=yield R.actor.sendAsync({type:Ae,data:we},R.abortController);if(delete R.abortController,R.aborted)return;this._afterTileLoadWorkerResponse(R,Be)}catch(Be){if(delete R.abortController,R.aborted)return;if(Be&&Be.status!==404)throw Be;this._afterTileLoadWorkerResponse(R,null)}})}_afterTileLoadWorkerResponse(R,ae){if(ae&&ae.resourceTiming&&(R.resourceTiming=ae.resourceTiming),ae&&this.map._refreshExpiredTiles&&R.setExpiryData(ae),R.loadVectorData(ae,this.map.painter),R.reloadPromise){let we=R.reloadPromise;R.reloadPromise=null,this.loadTile(R).then(we.resolve).catch(we.reject)}}abortTile(R){return t._(this,void 0,void 0,function*(){R.abortController&&(R.abortController.abort(),delete R.abortController),R.actor&&(yield R.actor.sendAsync({type:"AT",data:{uid:R.uid,type:this.type,source:this.id}}))})}unloadTile(R){return t._(this,void 0,void 0,function*(){R.unloadVectorData(),R.actor&&(yield R.actor.sendAsync({type:"RMT",data:{uid:R.uid,type:this.type,source:this.id}}))})}hasTransition(){return!1}}class Se extends t.E{constructor(R,ae,we,Ae){super(),this.id=R,this.dispatcher=we,this.setEventedParent(Ae),this.type="raster",this.minzoom=0,this.maxzoom=22,this.roundZoom=!0,this.scheme="xyz",this.tileSize=512,this._loaded=!1,this._options=t.e({type:"raster"},ae),t.e(this,t.M(ae,["url","scheme","tileSize"]))}load(){return t._(this,void 0,void 0,function*(){this._loaded=!1,this.fire(new t.k("dataloading",{dataType:"source"})),this._tileJSONRequest=new AbortController;try{let R=yield ee(this._options,this.map._requestManager,this._tileJSONRequest);this._tileJSONRequest=null,this._loaded=!0,R&&(t.e(this,R),R.bounds&&(this.tileBounds=new ce(R.bounds,this.minzoom,this.maxzoom)),this.fire(new t.k("data",{dataType:"source",sourceDataType:"metadata"})),this.fire(new t.k("data",{dataType:"source",sourceDataType:"content"})))}catch(R){this._tileJSONRequest=null,this.fire(new t.j(R))}})}loaded(){return this._loaded}onAdd(R){this.map=R,this.load()}onRemove(){this._tileJSONRequest&&(this._tileJSONRequest.abort(),this._tileJSONRequest=null)}setSourceProperty(R){this._tileJSONRequest&&(this._tileJSONRequest.abort(),this._tileJSONRequest=null),R(),this.load()}setTiles(R){return this.setSourceProperty(()=>{this._options.tiles=R}),this}setUrl(R){return this.setSourceProperty(()=>{this.url=R,this._options.url=R}),this}serialize(){return t.e({},this._options)}hasTile(R){return!this.tileBounds||this.tileBounds.contains(R.canonical)}loadTile(R){return t._(this,void 0,void 0,function*(){let ae=R.tileID.canonical.url(this.tiles,this.map.getPixelRatio(),this.scheme);R.abortController=new AbortController;try{let we=yield l.getImage(this.map._requestManager.transformRequest(ae,"Tile"),R.abortController,this.map._refreshExpiredTiles);if(delete R.abortController,R.aborted)return void(R.state="unloaded");if(we&&we.data){this.map._refreshExpiredTiles&&we.cacheControl&&we.expires&&R.setExpiryData({cacheControl:we.cacheControl,expires:we.expires});let Ae=this.map.painter.context,Be=Ae.gl,pt=we.data;R.texture=this.map.painter.getTileTexture(pt.width),R.texture?R.texture.update(pt,{useMipmap:!0}):(R.texture=new u(Ae,pt,Be.RGBA,{useMipmap:!0}),R.texture.bind(Be.LINEAR,Be.CLAMP_TO_EDGE,Be.LINEAR_MIPMAP_NEAREST)),R.state="loaded"}}catch(we){if(delete R.abortController,R.aborted)R.state="unloaded";else if(we)throw R.state="errored",we}})}abortTile(R){return t._(this,void 0,void 0,function*(){R.abortController&&(R.abortController.abort(),delete R.abortController)})}unloadTile(R){return t._(this,void 0,void 0,function*(){R.texture&&this.map.painter.saveTileTexture(R.texture)})}hasTransition(){return!1}}class De extends Se{constructor(R,ae,we,Ae){super(R,ae,we,Ae),this.type="raster-dem",this.maxzoom=22,this._options=t.e({type:"raster-dem"},ae),this.encoding=ae.encoding||"mapbox",this.redFactor=ae.redFactor,this.greenFactor=ae.greenFactor,this.blueFactor=ae.blueFactor,this.baseShift=ae.baseShift}loadTile(R){return t._(this,void 0,void 0,function*(){let ae=R.tileID.canonical.url(this.tiles,this.map.getPixelRatio(),this.scheme),we=this.map._requestManager.transformRequest(ae,"Tile");R.neighboringTiles=this._getNeighboringTiles(R.tileID),R.abortController=new AbortController;try{let Ae=yield l.getImage(we,R.abortController,this.map._refreshExpiredTiles);if(delete R.abortController,R.aborted)return void(R.state="unloaded");if(Ae&&Ae.data){let Be=Ae.data;this.map._refreshExpiredTiles&&Ae.cacheControl&&Ae.expires&&R.setExpiryData({cacheControl:Ae.cacheControl,expires:Ae.expires});let pt=t.b(Be)&&t.U()?Be:yield this.readImageNow(Be),At={type:this.type,uid:R.uid,source:this.id,rawImageData:pt,encoding:this.encoding,redFactor:this.redFactor,greenFactor:this.greenFactor,blueFactor:this.blueFactor,baseShift:this.baseShift};if(!R.actor||R.state==="expired"){R.actor=this.dispatcher.getActor();let Nt=yield R.actor.sendAsync({type:"LDT",data:At});R.dem=Nt,R.needsHillshadePrepare=!0,R.needsTerrainPrepare=!0,R.state="loaded"}}}catch(Ae){if(delete R.abortController,R.aborted)R.state="unloaded";else if(Ae)throw R.state="errored",Ae}})}readImageNow(R){return t._(this,void 0,void 0,function*(){if(typeof VideoFrame<"u"&&t.V()){let ae=R.width+2,we=R.height+2;try{return new t.R({width:ae,height:we},yield t.W(R,-1,-1,ae,we))}catch{}}return n.getImageData(R,1)})}_getNeighboringTiles(R){let ae=R.canonical,we=Math.pow(2,ae.z),Ae=(ae.x-1+we)%we,Be=ae.x===0?R.wrap-1:R.wrap,pt=(ae.x+1+we)%we,At=ae.x+1===we?R.wrap+1:R.wrap,Nt={};return Nt[new t.S(R.overscaledZ,Be,ae.z,Ae,ae.y).key]={backfilled:!1},Nt[new t.S(R.overscaledZ,At,ae.z,pt,ae.y).key]={backfilled:!1},ae.y>0&&(Nt[new t.S(R.overscaledZ,Be,ae.z,Ae,ae.y-1).key]={backfilled:!1},Nt[new t.S(R.overscaledZ,R.wrap,ae.z,ae.x,ae.y-1).key]={backfilled:!1},Nt[new t.S(R.overscaledZ,At,ae.z,pt,ae.y-1).key]={backfilled:!1}),ae.y+10&&t.e(Be,{resourceTiming:Ae}),this.fire(new t.k("data",Object.assign(Object.assign({},Be),{sourceDataType:"metadata"}))),this.fire(new t.k("data",Object.assign(Object.assign({},Be),{sourceDataType:"content"})))}catch(we){if(this._pendingLoads--,this._removed)return void this.fire(new t.k("dataabort",{dataType:"source"}));this.fire(new t.j(we))}})}loaded(){return this._pendingLoads===0}loadTile(R){return t._(this,void 0,void 0,function*(){let ae=R.actor?"RT":"LT";R.actor=this.actor;let we={type:this.type,uid:R.uid,tileID:R.tileID,zoom:R.tileID.overscaledZ,maxZoom:this.maxzoom,tileSize:this.tileSize,source:this.id,pixelRatio:this.map.getPixelRatio(),showCollisionBoxes:this.map.showCollisionBoxes,promoteId:this.promoteId};R.abortController=new AbortController;let Ae=yield this.actor.sendAsync({type:ae,data:we},R.abortController);delete R.abortController,R.unloadVectorData(),R.aborted||R.loadVectorData(Ae,this.map.painter,ae==="RT")})}abortTile(R){return t._(this,void 0,void 0,function*(){R.abortController&&(R.abortController.abort(),delete R.abortController),R.aborted=!0})}unloadTile(R){return t._(this,void 0,void 0,function*(){R.unloadVectorData(),yield this.actor.sendAsync({type:"RMT",data:{uid:R.uid,type:this.type,source:this.id}})})}onRemove(){this._removed=!0,this.actor.sendAsync({type:"RS",data:{type:this.type,source:this.id}})}serialize(){return t.e({},this._options,{type:this.type,data:this._data})}hasTransition(){return!1}}var Ze=t.Y([{name:"a_pos",type:"Int16",components:2},{name:"a_texture_pos",type:"Int16",components:2}]);class at extends t.E{constructor(R,ae,we,Ae){super(),this.id=R,this.dispatcher=we,this.coordinates=ae.coordinates,this.type="image",this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.tiles={},this._loaded=!1,this.setEventedParent(Ae),this.options=ae}load(R){return t._(this,void 0,void 0,function*(){this._loaded=!1,this.fire(new t.k("dataloading",{dataType:"source"})),this.url=this.options.url,this._request=new AbortController;try{let ae=yield l.getImage(this.map._requestManager.transformRequest(this.url,"Image"),this._request);this._request=null,this._loaded=!0,ae&&ae.data&&(this.image=ae.data,R&&(this.coordinates=R),this._finishLoading())}catch(ae){this._request=null,this._loaded=!0,this.fire(new t.j(ae))}})}loaded(){return this._loaded}updateImage(R){return R.url?(this._request&&(this._request.abort(),this._request=null),this.options.url=R.url,this.load(R.coordinates).finally(()=>{this.texture=null}),this):this}_finishLoading(){this.map&&(this.setCoordinates(this.coordinates),this.fire(new t.k("data",{dataType:"source",sourceDataType:"metadata"})))}onAdd(R){this.map=R,this.load()}onRemove(){this._request&&(this._request.abort(),this._request=null)}setCoordinates(R){this.coordinates=R;let ae=R.map(t.Z.fromLngLat);this.tileID=function(Ae){let Be=1/0,pt=1/0,At=-1/0,Nt=-1/0;for(let Kr of Ae)Be=Math.min(Be,Kr.x),pt=Math.min(pt,Kr.y),At=Math.max(At,Kr.x),Nt=Math.max(Nt,Kr.y);let $t=Math.max(At-Be,Nt-pt),wr=Math.max(0,Math.floor(-Math.log($t)/Math.LN2)),Tr=Math.pow(2,wr);return new t.a1(wr,Math.floor((Be+At)/2*Tr),Math.floor((pt+Nt)/2*Tr))}(ae),this.minzoom=this.maxzoom=this.tileID.z;let we=ae.map(Ae=>this.tileID.getTilePoint(Ae)._round());return this._boundsArray=new t.$,this._boundsArray.emplaceBack(we[0].x,we[0].y,0,0),this._boundsArray.emplaceBack(we[1].x,we[1].y,t.X,0),this._boundsArray.emplaceBack(we[3].x,we[3].y,0,t.X),this._boundsArray.emplaceBack(we[2].x,we[2].y,t.X,t.X),this.boundsBuffer&&(this.boundsBuffer.destroy(),delete this.boundsBuffer),this.fire(new t.k("data",{dataType:"source",sourceDataType:"content"})),this}prepare(){if(Object.keys(this.tiles).length===0||!this.image)return;let R=this.map.painter.context,ae=R.gl;this.boundsBuffer||(this.boundsBuffer=R.createVertexBuffer(this._boundsArray,Ze.members)),this.boundsSegments||(this.boundsSegments=t.a0.simpleSegment(0,0,4,2)),this.texture||(this.texture=new u(R,this.image,ae.RGBA),this.texture.bind(ae.LINEAR,ae.CLAMP_TO_EDGE));let we=!1;for(let Ae in this.tiles){let Be=this.tiles[Ae];Be.state!=="loaded"&&(Be.state="loaded",Be.texture=this.texture,we=!0)}we&&this.fire(new t.k("data",{dataType:"source",sourceDataType:"idle",sourceId:this.id}))}loadTile(R){return t._(this,void 0,void 0,function*(){this.tileID&&this.tileID.equals(R.tileID.canonical)?(this.tiles[String(R.tileID.wrap)]=R,R.buckets={}):R.state="errored"})}serialize(){return{type:"image",url:this.options.url,coordinates:this.coordinates}}hasTransition(){return!1}}class nt extends at{constructor(R,ae,we,Ae){super(R,ae,we,Ae),this.roundZoom=!0,this.type="video",this.options=ae}load(){return t._(this,void 0,void 0,function*(){this._loaded=!1;let R=this.options;this.urls=[];for(let ae of R.urls)this.urls.push(this.map._requestManager.transformRequest(ae,"Source").url);try{let ae=yield t.a3(this.urls);if(this._loaded=!0,!ae)return;this.video=ae,this.video.loop=!0,this.video.addEventListener("playing",()=>{this.map.triggerRepaint()}),this.map&&this.video.play(),this._finishLoading()}catch(ae){this.fire(new t.j(ae))}})}pause(){this.video&&this.video.pause()}play(){this.video&&this.video.play()}seek(R){if(this.video){let ae=this.video.seekable;Rae.end(0)?this.fire(new t.j(new t.a2(`sources.${this.id}`,null,`Playback for this video can be set only between the ${ae.start(0)} and ${ae.end(0)}-second mark.`))):this.video.currentTime=R}}getVideo(){return this.video}onAdd(R){this.map||(this.map=R,this.load(),this.video&&(this.video.play(),this.setCoordinates(this.coordinates)))}prepare(){if(Object.keys(this.tiles).length===0||this.video.readyState<2)return;let R=this.map.painter.context,ae=R.gl;this.boundsBuffer||(this.boundsBuffer=R.createVertexBuffer(this._boundsArray,Ze.members)),this.boundsSegments||(this.boundsSegments=t.a0.simpleSegment(0,0,4,2)),this.texture?this.video.paused||(this.texture.bind(ae.LINEAR,ae.CLAMP_TO_EDGE),ae.texSubImage2D(ae.TEXTURE_2D,0,0,0,ae.RGBA,ae.UNSIGNED_BYTE,this.video)):(this.texture=new u(R,this.video,ae.RGBA),this.texture.bind(ae.LINEAR,ae.CLAMP_TO_EDGE));let we=!1;for(let Ae in this.tiles){let Be=this.tiles[Ae];Be.state!=="loaded"&&(Be.state="loaded",Be.texture=this.texture,we=!0)}we&&this.fire(new t.k("data",{dataType:"source",sourceDataType:"idle",sourceId:this.id}))}serialize(){return{type:"video",urls:this.urls,coordinates:this.coordinates}}hasTransition(){return this.video&&!this.video.paused}}class tt extends at{constructor(R,ae,we,Ae){super(R,ae,we,Ae),ae.coordinates?Array.isArray(ae.coordinates)&&ae.coordinates.length===4&&!ae.coordinates.some(Be=>!Array.isArray(Be)||Be.length!==2||Be.some(pt=>typeof pt!="number"))||this.fire(new t.j(new t.a2(`sources.${R}`,null,'"coordinates" property must be an array of 4 longitude/latitude array pairs'))):this.fire(new t.j(new t.a2(`sources.${R}`,null,'missing required property "coordinates"'))),ae.animate&&typeof ae.animate!="boolean"&&this.fire(new t.j(new t.a2(`sources.${R}`,null,'optional "animate" property must be a boolean value'))),ae.canvas?typeof ae.canvas=="string"||ae.canvas instanceof HTMLCanvasElement||this.fire(new t.j(new t.a2(`sources.${R}`,null,'"canvas" must be either a string representing the ID of the canvas element from which to read, or an HTMLCanvasElement instance'))):this.fire(new t.j(new t.a2(`sources.${R}`,null,'missing required property "canvas"'))),this.options=ae,this.animate=ae.animate===void 0||ae.animate}load(){return t._(this,void 0,void 0,function*(){this._loaded=!0,this.canvas||(this.canvas=this.options.canvas instanceof HTMLCanvasElement?this.options.canvas:document.getElementById(this.options.canvas)),this.width=this.canvas.width,this.height=this.canvas.height,this._hasInvalidDimensions()?this.fire(new t.j(new Error("Canvas dimensions cannot be less than or equal to zero."))):(this.play=function(){this._playing=!0,this.map.triggerRepaint()},this.pause=function(){this._playing&&(this.prepare(),this._playing=!1)},this._finishLoading())})}getCanvas(){return this.canvas}onAdd(R){this.map=R,this.load(),this.canvas&&this.animate&&this.play()}onRemove(){this.pause()}prepare(){let R=!1;if(this.canvas.width!==this.width&&(this.width=this.canvas.width,R=!0),this.canvas.height!==this.height&&(this.height=this.canvas.height,R=!0),this._hasInvalidDimensions()||Object.keys(this.tiles).length===0)return;let ae=this.map.painter.context,we=ae.gl;this.boundsBuffer||(this.boundsBuffer=ae.createVertexBuffer(this._boundsArray,Ze.members)),this.boundsSegments||(this.boundsSegments=t.a0.simpleSegment(0,0,4,2)),this.texture?(R||this._playing)&&this.texture.update(this.canvas,{premultiply:!0}):this.texture=new u(ae,this.canvas,we.RGBA,{premultiply:!0});let Ae=!1;for(let Be in this.tiles){let pt=this.tiles[Be];pt.state!=="loaded"&&(pt.state="loaded",pt.texture=this.texture,Ae=!0)}Ae&&this.fire(new t.k("data",{dataType:"source",sourceDataType:"idle",sourceId:this.id}))}serialize(){return{type:"canvas",coordinates:this.coordinates}}hasTransition(){return this._playing}_hasInvalidDimensions(){for(let R of[this.canvas.width,this.canvas.height])if(isNaN(R)||R<=0)return!0;return!1}}let ut={},Me=Ue=>{switch(Ue){case"geojson":return Fe;case"image":return at;case"raster":return Se;case"raster-dem":return De;case"vector":return be;case"video":return nt;case"canvas":return tt}return ut[Ue]},_e="RTLPluginLoaded";class fe extends t.E{constructor(){super(...arguments),this.status="unavailable",this.url=null,this.dispatcher=X()}_syncState(R){return this.status=R,this.dispatcher.broadcast("SRPS",{pluginStatus:R,pluginURL:this.url}).catch(ae=>{throw this.status="error",ae})}getRTLTextPluginStatus(){return this.status}clearRTLTextPlugin(){this.status="unavailable",this.url=null}setRTLTextPlugin(R){return t._(this,arguments,void 0,function*(ae,we=!1){if(this.url)throw new Error("setRTLTextPlugin cannot be called multiple times.");if(this.url=n.resolveURL(ae),!this.url)throw new Error(`requested url ${ae} is invalid`);if(this.status==="unavailable"){if(!we)return this._requestImport();this.status="deferred",this._syncState(this.status)}else if(this.status==="requested")return this._requestImport()})}_requestImport(){return t._(this,void 0,void 0,function*(){yield this._syncState("loading"),this.status="loaded",this.fire(new t.k(_e))})}lazyLoad(){this.status==="unavailable"?this.status="requested":this.status==="deferred"&&this._requestImport()}}let Oe=null;function rt(){return Oe||(Oe=new fe),Oe}class st{constructor(R,ae){this.timeAdded=0,this.fadeEndTime=0,this.tileID=R,this.uid=t.a4(),this.uses=0,this.tileSize=ae,this.buckets={},this.expirationTime=null,this.queryPadding=0,this.hasSymbolBuckets=!1,this.hasRTLText=!1,this.dependencies={},this.rtt=[],this.rttCoords={},this.expiredRequestCount=0,this.state="loading"}registerFadeDuration(R){let ae=R+this.timeAdded;aeBe.getLayer($t)).filter(Boolean);if(Nt.length!==0){At.layers=Nt,At.stateDependentLayerIds&&(At.stateDependentLayers=At.stateDependentLayerIds.map($t=>Nt.filter(wr=>wr.id===$t)[0]));for(let $t of Nt)pt[$t.id]=At}}return pt}(R.buckets,ae.style),this.hasSymbolBuckets=!1;for(let Ae in this.buckets){let Be=this.buckets[Ae];if(Be instanceof t.a6){if(this.hasSymbolBuckets=!0,!we)break;Be.justReloaded=!0}}if(this.hasRTLText=!1,this.hasSymbolBuckets)for(let Ae in this.buckets){let Be=this.buckets[Ae];if(Be instanceof t.a6&&Be.hasRTLText){this.hasRTLText=!0,rt().lazyLoad();break}}this.queryPadding=0;for(let Ae in this.buckets){let Be=this.buckets[Ae];this.queryPadding=Math.max(this.queryPadding,ae.style.getLayer(Ae).queryRadius(Be))}R.imageAtlas&&(this.imageAtlas=R.imageAtlas),R.glyphAtlasImage&&(this.glyphAtlasImage=R.glyphAtlasImage)}else this.collisionBoxArray=new t.a5}unloadVectorData(){for(let R in this.buckets)this.buckets[R].destroy();this.buckets={},this.imageAtlasTexture&&this.imageAtlasTexture.destroy(),this.imageAtlas&&(this.imageAtlas=null),this.glyphAtlasTexture&&this.glyphAtlasTexture.destroy(),this.latestFeatureIndex=null,this.state="unloaded"}getBucket(R){return this.buckets[R.id]}upload(R){for(let we in this.buckets){let Ae=this.buckets[we];Ae.uploadPending()&&Ae.upload(R)}let ae=R.gl;this.imageAtlas&&!this.imageAtlas.uploaded&&(this.imageAtlasTexture=new u(R,this.imageAtlas.image,ae.RGBA),this.imageAtlas.uploaded=!0),this.glyphAtlasImage&&(this.glyphAtlasTexture=new u(R,this.glyphAtlasImage,ae.ALPHA),this.glyphAtlasImage=null)}prepare(R){this.imageAtlas&&this.imageAtlas.patchUpdatedImages(R,this.imageAtlasTexture)}queryRenderedFeatures(R,ae,we,Ae,Be,pt,At,Nt,$t,wr){return this.latestFeatureIndex&&this.latestFeatureIndex.rawTileData?this.latestFeatureIndex.query({queryGeometry:Ae,cameraQueryGeometry:Be,scale:pt,tileSize:this.tileSize,pixelPosMatrix:wr,transform:Nt,params:At,queryPadding:this.queryPadding*$t},R,ae,we):{}}querySourceFeatures(R,ae){let we=this.latestFeatureIndex;if(!we||!we.rawTileData)return;let Ae=we.loadVTLayers(),Be=ae&&ae.sourceLayer?ae.sourceLayer:"",pt=Ae._geojsonTileLayer||Ae[Be];if(!pt)return;let At=t.a7(ae&&ae.filter),{z:Nt,x:$t,y:wr}=this.tileID.canonical,Tr={z:Nt,x:$t,y:wr};for(let Kr=0;Krwe)Ae=!1;else if(ae)if(this.expirationTime{this.remove(R,Be)},we)),this.data[Ae].push(Be),this.order.push(Ae),this.order.length>this.max){let pt=this._getAndRemoveByKey(this.order[0]);pt&&this.onRemove(pt)}return this}has(R){return R.wrapped().key in this.data}getAndRemove(R){return this.has(R)?this._getAndRemoveByKey(R.wrapped().key):null}_getAndRemoveByKey(R){let ae=this.data[R].shift();return ae.timeout&&clearTimeout(ae.timeout),this.data[R].length===0&&delete this.data[R],this.order.splice(this.order.indexOf(R),1),ae.value}getByKey(R){let ae=this.data[R];return ae?ae[0].value:null}get(R){return this.has(R)?this.data[R.wrapped().key][0].value:null}remove(R,ae){if(!this.has(R))return this;let we=R.wrapped().key,Ae=ae===void 0?0:this.data[we].indexOf(ae),Be=this.data[we][Ae];return this.data[we].splice(Ae,1),Be.timeout&&clearTimeout(Be.timeout),this.data[we].length===0&&delete this.data[we],this.onRemove(Be.value),this.order.splice(this.order.indexOf(we),1),this}setMaxSize(R){for(this.max=R;this.order.length>this.max;){let ae=this._getAndRemoveByKey(this.order[0]);ae&&this.onRemove(ae)}return this}filter(R){let ae=[];for(let we in this.data)for(let Ae of this.data[we])R(Ae.value)||ae.push(Ae);for(let we of ae)this.remove(we.value.tileID,we)}}class Pt{constructor(){this.state={},this.stateChanges={},this.deletedStates={}}updateState(R,ae,we){let Ae=String(ae);if(this.stateChanges[R]=this.stateChanges[R]||{},this.stateChanges[R][Ae]=this.stateChanges[R][Ae]||{},t.e(this.stateChanges[R][Ae],we),this.deletedStates[R]===null){this.deletedStates[R]={};for(let Be in this.state[R])Be!==Ae&&(this.deletedStates[R][Be]=null)}else if(this.deletedStates[R]&&this.deletedStates[R][Ae]===null){this.deletedStates[R][Ae]={};for(let Be in this.state[R][Ae])we[Be]||(this.deletedStates[R][Ae][Be]=null)}else for(let Be in we)this.deletedStates[R]&&this.deletedStates[R][Ae]&&this.deletedStates[R][Ae][Be]===null&&delete this.deletedStates[R][Ae][Be]}removeFeatureState(R,ae,we){if(this.deletedStates[R]===null)return;let Ae=String(ae);if(this.deletedStates[R]=this.deletedStates[R]||{},we&&ae!==void 0)this.deletedStates[R][Ae]!==null&&(this.deletedStates[R][Ae]=this.deletedStates[R][Ae]||{},this.deletedStates[R][Ae][we]=null);else if(ae!==void 0)if(this.stateChanges[R]&&this.stateChanges[R][Ae])for(we in this.deletedStates[R][Ae]={},this.stateChanges[R][Ae])this.deletedStates[R][Ae][we]=null;else this.deletedStates[R][Ae]=null;else this.deletedStates[R]=null}getState(R,ae){let we=String(ae),Ae=t.e({},(this.state[R]||{})[we],(this.stateChanges[R]||{})[we]);if(this.deletedStates[R]===null)return{};if(this.deletedStates[R]){let Be=this.deletedStates[R][ae];if(Be===null)return{};for(let pt in Be)delete Ae[pt]}return Ae}initializeTileState(R,ae){R.setFeatureState(this.state,ae)}coalesceChanges(R,ae){let we={};for(let Ae in this.stateChanges){this.state[Ae]=this.state[Ae]||{};let Be={};for(let pt in this.stateChanges[Ae])this.state[Ae][pt]||(this.state[Ae][pt]={}),t.e(this.state[Ae][pt],this.stateChanges[Ae][pt]),Be[pt]=this.state[Ae][pt];we[Ae]=Be}for(let Ae in this.deletedStates){this.state[Ae]=this.state[Ae]||{};let Be={};if(this.deletedStates[Ae]===null)for(let pt in this.state[Ae])Be[pt]={},this.state[Ae][pt]={};else for(let pt in this.deletedStates[Ae]){if(this.deletedStates[Ae][pt]===null)this.state[Ae][pt]={};else for(let At of Object.keys(this.deletedStates[Ae][pt]))delete this.state[Ae][pt][At];Be[pt]=this.state[Ae][pt]}we[Ae]=we[Ae]||{},t.e(we[Ae],Be)}if(this.stateChanges={},this.deletedStates={},Object.keys(we).length!==0)for(let Ae in R)R[Ae].setFeatureState(we,ae)}}class Lt extends t.E{constructor(R,ae,we){super(),this.id=R,this.dispatcher=we,this.on("data",Ae=>this._dataHandler(Ae)),this.on("dataloading",()=>{this._sourceErrored=!1}),this.on("error",()=>{this._sourceErrored=this._source.loaded()}),this._source=((Ae,Be,pt,At)=>{let Nt=new(Me(Be.type))(Ae,Be,pt,At);if(Nt.id!==Ae)throw new Error(`Expected Source id to be ${Ae} instead of ${Nt.id}`);return Nt})(R,ae,we,this),this._tiles={},this._cache=new Qe(0,Ae=>this._unloadTile(Ae)),this._timers={},this._cacheTimers={},this._maxTileCacheSize=null,this._maxTileCacheZoomLevels=null,this._loadedParentTiles={},this._coveredTiles={},this._state=new Pt,this._didEmitContent=!1,this._updated=!1}onAdd(R){this.map=R,this._maxTileCacheSize=R?R._maxTileCacheSize:null,this._maxTileCacheZoomLevels=R?R._maxTileCacheZoomLevels:null,this._source&&this._source.onAdd&&this._source.onAdd(R)}onRemove(R){this.clearTiles(),this._source&&this._source.onRemove&&this._source.onRemove(R)}loaded(){if(this._sourceErrored)return!0;if(!this._sourceLoaded||!this._source.loaded())return!1;if(!(this.used===void 0&&this.usedForTerrain===void 0||this.used||this.usedForTerrain))return!0;if(!this._updated)return!1;for(let R in this._tiles){let ae=this._tiles[R];if(ae.state!=="loaded"&&ae.state!=="errored")return!1}return!0}getSource(){return this._source}pause(){this._paused=!0}resume(){if(!this._paused)return;let R=this._shouldReloadOnResume;this._paused=!1,this._shouldReloadOnResume=!1,R&&this.reload(),this.transform&&this.update(this.transform,this.terrain)}_loadTile(R,ae,we){return t._(this,void 0,void 0,function*(){try{yield this._source.loadTile(R),this._tileLoaded(R,ae,we)}catch(Ae){R.state="errored",Ae.status!==404?this._source.fire(new t.j(Ae,{tile:R})):this.update(this.transform,this.terrain)}})}_unloadTile(R){this._source.unloadTile&&this._source.unloadTile(R)}_abortTile(R){this._source.abortTile&&this._source.abortTile(R),this._source.fire(new t.k("dataabort",{tile:R,coord:R.tileID,dataType:"source"}))}serialize(){return this._source.serialize()}prepare(R){this._source.prepare&&this._source.prepare(),this._state.coalesceChanges(this._tiles,this.map?this.map.painter:null);for(let ae in this._tiles){let we=this._tiles[ae];we.upload(R),we.prepare(this.map.style.imageManager)}}getIds(){return Object.values(this._tiles).map(R=>R.tileID).sort(qt).map(R=>R.key)}getRenderableIds(R){let ae=[];for(let we in this._tiles)this._isIdRenderable(we,R)&&ae.push(this._tiles[we]);return R?ae.sort((we,Ae)=>{let Be=we.tileID,pt=Ae.tileID,At=new t.P(Be.canonical.x,Be.canonical.y)._rotate(this.transform.angle),Nt=new t.P(pt.canonical.x,pt.canonical.y)._rotate(this.transform.angle);return Be.overscaledZ-pt.overscaledZ||Nt.y-At.y||Nt.x-At.x}).map(we=>we.tileID.key):ae.map(we=>we.tileID).sort(qt).map(we=>we.key)}hasRenderableParent(R){let ae=this.findLoadedParent(R,0);return!!ae&&this._isIdRenderable(ae.tileID.key)}_isIdRenderable(R,ae){return this._tiles[R]&&this._tiles[R].hasData()&&!this._coveredTiles[R]&&(ae||!this._tiles[R].holdingForFade())}reload(){if(this._paused)this._shouldReloadOnResume=!0;else{this._cache.reset();for(let R in this._tiles)this._tiles[R].state!=="errored"&&this._reloadTile(R,"reloading")}}_reloadTile(R,ae){return t._(this,void 0,void 0,function*(){let we=this._tiles[R];we&&(we.state!=="loading"&&(we.state=ae),yield this._loadTile(we,R,ae))})}_tileLoaded(R,ae,we){R.timeAdded=n.now(),we==="expired"&&(R.refreshedUponExpiration=!0),this._setTileReloadTimer(ae,R),this.getSource().type==="raster-dem"&&R.dem&&this._backfillDEM(R),this._state.initializeTileState(R,this.map?this.map.painter:null),R.aborted||this._source.fire(new t.k("data",{dataType:"source",tile:R,coord:R.tileID}))}_backfillDEM(R){let ae=this.getRenderableIds();for(let Ae=0;Ae1||(Math.abs(pt)>1&&(Math.abs(pt+Nt)===1?pt+=Nt:Math.abs(pt-Nt)===1&&(pt-=Nt)),Be.dem&&Ae.dem&&(Ae.dem.backfillBorder(Be.dem,pt,At),Ae.neighboringTiles&&Ae.neighboringTiles[$t]&&(Ae.neighboringTiles[$t].backfilled=!0)))}}getTile(R){return this.getTileByID(R.key)}getTileByID(R){return this._tiles[R]}_retainLoadedChildren(R,ae,we,Ae){for(let Be in this._tiles){let pt=this._tiles[Be];if(Ae[Be]||!pt.hasData()||pt.tileID.overscaledZ<=ae||pt.tileID.overscaledZ>we)continue;let At=pt.tileID;for(;pt&&pt.tileID.overscaledZ>ae+1;){let $t=pt.tileID.scaledTo(pt.tileID.overscaledZ-1);pt=this._tiles[$t.key],pt&&pt.hasData()&&(At=$t)}let Nt=At;for(;Nt.overscaledZ>ae;)if(Nt=Nt.scaledTo(Nt.overscaledZ-1),R[Nt.key]){Ae[At.key]=At;break}}}findLoadedParent(R,ae){if(R.key in this._loadedParentTiles){let we=this._loadedParentTiles[R.key];return we&&we.tileID.overscaledZ>=ae?we:null}for(let we=R.overscaledZ-1;we>=ae;we--){let Ae=R.scaledTo(we),Be=this._getLoadedTile(Ae);if(Be)return Be}}findLoadedSibling(R){return this._getLoadedTile(R)}_getLoadedTile(R){let ae=this._tiles[R.key];return ae&&ae.hasData()?ae:this._cache.getByKey(R.wrapped().key)}updateCacheSize(R){let ae=Math.ceil(R.width/this._source.tileSize)+1,we=Math.ceil(R.height/this._source.tileSize)+1,Ae=Math.floor(ae*we*(this._maxTileCacheZoomLevels===null?t.a.MAX_TILE_CACHE_ZOOM_LEVELS:this._maxTileCacheZoomLevels)),Be=typeof this._maxTileCacheSize=="number"?Math.min(this._maxTileCacheSize,Ae):Ae;this._cache.setMaxSize(Be)}handleWrapJump(R){let ae=Math.round((R-(this._prevLng===void 0?R:this._prevLng))/360);if(this._prevLng=R,ae){let we={};for(let Ae in this._tiles){let Be=this._tiles[Ae];Be.tileID=Be.tileID.unwrapTo(Be.tileID.wrap+ae),we[Be.tileID.key]=Be}this._tiles=we;for(let Ae in this._timers)clearTimeout(this._timers[Ae]),delete this._timers[Ae];for(let Ae in this._tiles)this._setTileReloadTimer(Ae,this._tiles[Ae])}}_updateCoveredAndRetainedTiles(R,ae,we,Ae,Be,pt){let At={},Nt={},$t=Object.keys(R),wr=n.now();for(let Tr of $t){let Kr=R[Tr],sa=this._tiles[Tr];if(!sa||sa.fadeEndTime!==0&&sa.fadeEndTime<=wr)continue;let He=this.findLoadedParent(Kr,ae),Je=this.findLoadedSibling(Kr),lt=He||Je||null;lt&&(this._addTile(lt.tileID),At[lt.tileID.key]=lt.tileID),Nt[Tr]=Kr}this._retainLoadedChildren(Nt,Ae,we,R);for(let Tr in At)R[Tr]||(this._coveredTiles[Tr]=!0,R[Tr]=At[Tr]);if(pt){let Tr={},Kr={};for(let sa of Be)this._tiles[sa.key].hasData()?Tr[sa.key]=sa:Kr[sa.key]=sa;for(let sa in Kr){let He=Kr[sa].children(this._source.maxzoom);this._tiles[He[0].key]&&this._tiles[He[1].key]&&this._tiles[He[2].key]&&this._tiles[He[3].key]&&(Tr[He[0].key]=R[He[0].key]=He[0],Tr[He[1].key]=R[He[1].key]=He[1],Tr[He[2].key]=R[He[2].key]=He[2],Tr[He[3].key]=R[He[3].key]=He[3],delete Kr[sa])}for(let sa in Kr){let He=Kr[sa],Je=this.findLoadedParent(He,this._source.minzoom),lt=this.findLoadedSibling(He),dt=Je||lt||null;if(dt){Tr[dt.tileID.key]=R[dt.tileID.key]=dt.tileID;for(let Ct in Tr)Tr[Ct].isChildOf(dt.tileID)&&delete Tr[Ct]}}for(let sa in this._tiles)Tr[sa]||(this._coveredTiles[sa]=!0)}}update(R,ae){if(!this._sourceLoaded||this._paused)return;let we;this.transform=R,this.terrain=ae,this.updateCacheSize(R),this.handleWrapJump(this.transform.center.lng),this._coveredTiles={},this.used||this.usedForTerrain?this._source.tileID?we=R.getVisibleUnwrappedCoordinates(this._source.tileID).map(wr=>new t.S(wr.canonical.z,wr.wrap,wr.canonical.z,wr.canonical.x,wr.canonical.y)):(we=R.coveringTiles({tileSize:this.usedForTerrain?this.tileSize:this._source.tileSize,minzoom:this._source.minzoom,maxzoom:this._source.maxzoom,roundZoom:!this.usedForTerrain&&this._source.roundZoom,reparseOverscaled:this._source.reparseOverscaled,terrain:ae}),this._source.hasTile&&(we=we.filter(wr=>this._source.hasTile(wr)))):we=[];let Ae=R.coveringZoomLevel(this._source),Be=Math.max(Ae-Lt.maxOverzooming,this._source.minzoom),pt=Math.max(Ae+Lt.maxUnderzooming,this._source.minzoom);if(this.usedForTerrain){let wr={};for(let Tr of we)if(Tr.canonical.z>this._source.minzoom){let Kr=Tr.scaledTo(Tr.canonical.z-1);wr[Kr.key]=Kr;let sa=Tr.scaledTo(Math.max(this._source.minzoom,Math.min(Tr.canonical.z,5)));wr[sa.key]=sa}we=we.concat(Object.values(wr))}let At=we.length===0&&!this._updated&&this._didEmitContent;this._updated=!0,At&&this.fire(new t.k("data",{sourceDataType:"idle",dataType:"source",sourceId:this.id}));let Nt=this._updateRetainedTiles(we,Ae);Ht(this._source.type)&&this._updateCoveredAndRetainedTiles(Nt,Be,pt,Ae,we,ae);for(let wr in Nt)this._tiles[wr].clearFadeHold();let $t=t.ab(this._tiles,Nt);for(let wr of $t){let Tr=this._tiles[wr];Tr.hasSymbolBuckets&&!Tr.holdingForFade()?Tr.setHoldDuration(this.map._fadeDuration):Tr.hasSymbolBuckets&&!Tr.symbolFadeFinished()||this._removeTile(wr)}this._updateLoadedParentTileCache(),this._updateLoadedSiblingTileCache()}releaseSymbolFadeTiles(){for(let R in this._tiles)this._tiles[R].holdingForFade()&&this._removeTile(R)}_updateRetainedTiles(R,ae){var we;let Ae={},Be={},pt=Math.max(ae-Lt.maxOverzooming,this._source.minzoom),At=Math.max(ae+Lt.maxUnderzooming,this._source.minzoom),Nt={};for(let $t of R){let wr=this._addTile($t);Ae[$t.key]=$t,wr.hasData()||aethis._source.maxzoom){let Kr=$t.children(this._source.maxzoom)[0],sa=this.getTile(Kr);if(sa&&sa.hasData()){Ae[Kr.key]=Kr;continue}}else{let Kr=$t.children(this._source.maxzoom);if(Ae[Kr[0].key]&&Ae[Kr[1].key]&&Ae[Kr[2].key]&&Ae[Kr[3].key])continue}let Tr=wr.wasRequested();for(let Kr=$t.overscaledZ-1;Kr>=pt;--Kr){let sa=$t.scaledTo(Kr);if(Be[sa.key])break;if(Be[sa.key]=!0,wr=this.getTile(sa),!wr&&Tr&&(wr=this._addTile(sa)),wr){let He=wr.hasData();if((He||!(!((we=this.map)===null||we===void 0)&&we.cancelPendingTileRequestsWhileZooming)||Tr)&&(Ae[sa.key]=sa),Tr=wr.wasRequested(),He)break}}}return Ae}_updateLoadedParentTileCache(){this._loadedParentTiles={};for(let R in this._tiles){let ae=[],we,Ae=this._tiles[R].tileID;for(;Ae.overscaledZ>0;){if(Ae.key in this._loadedParentTiles){we=this._loadedParentTiles[Ae.key];break}ae.push(Ae.key);let Be=Ae.scaledTo(Ae.overscaledZ-1);if(we=this._getLoadedTile(Be),we)break;Ae=Be}for(let Be of ae)this._loadedParentTiles[Be]=we}}_updateLoadedSiblingTileCache(){this._loadedSiblingTiles={};for(let R in this._tiles){let ae=this._tiles[R].tileID,we=this._getLoadedTile(ae);this._loadedSiblingTiles[ae.key]=we}}_addTile(R){let ae=this._tiles[R.key];if(ae)return ae;ae=this._cache.getAndRemove(R),ae&&(this._setTileReloadTimer(R.key,ae),ae.tileID=R,this._state.initializeTileState(ae,this.map?this.map.painter:null),this._cacheTimers[R.key]&&(clearTimeout(this._cacheTimers[R.key]),delete this._cacheTimers[R.key],this._setTileReloadTimer(R.key,ae)));let we=ae;return ae||(ae=new st(R,this._source.tileSize*R.overscaleFactor()),this._loadTile(ae,R.key,ae.state)),ae.uses++,this._tiles[R.key]=ae,we||this._source.fire(new t.k("dataloading",{tile:ae,coord:ae.tileID,dataType:"source"})),ae}_setTileReloadTimer(R,ae){R in this._timers&&(clearTimeout(this._timers[R]),delete this._timers[R]);let we=ae.getExpiryTimeout();we&&(this._timers[R]=setTimeout(()=>{this._reloadTile(R,"expired"),delete this._timers[R]},we))}_removeTile(R){let ae=this._tiles[R];ae&&(ae.uses--,delete this._tiles[R],this._timers[R]&&(clearTimeout(this._timers[R]),delete this._timers[R]),ae.uses>0||(ae.hasData()&&ae.state!=="reloading"?this._cache.add(ae.tileID,ae,ae.getExpiryTimeout()):(ae.aborted=!0,this._abortTile(ae),this._unloadTile(ae))))}_dataHandler(R){let ae=R.sourceDataType;R.dataType==="source"&&ae==="metadata"&&(this._sourceLoaded=!0),this._sourceLoaded&&!this._paused&&R.dataType==="source"&&ae==="content"&&(this.reload(),this.transform&&this.update(this.transform,this.terrain),this._didEmitContent=!0)}clearTiles(){this._shouldReloadOnResume=!1,this._paused=!1;for(let R in this._tiles)this._removeTile(R);this._cache.reset()}tilesIn(R,ae,we){let Ae=[],Be=this.transform;if(!Be)return Ae;let pt=we?Be.getCameraQueryGeometry(R):R,At=R.map(He=>Be.pointCoordinate(He,this.terrain)),Nt=pt.map(He=>Be.pointCoordinate(He,this.terrain)),$t=this.getIds(),wr=1/0,Tr=1/0,Kr=-1/0,sa=-1/0;for(let He of Nt)wr=Math.min(wr,He.x),Tr=Math.min(Tr,He.y),Kr=Math.max(Kr,He.x),sa=Math.max(sa,He.y);for(let He=0;He<$t.length;He++){let Je=this._tiles[$t[He]];if(Je.holdingForFade())continue;let lt=Je.tileID,dt=Math.pow(2,Be.zoom-Je.tileID.overscaledZ),Ct=ae*Je.queryPadding*t.X/Je.tileSize/dt,Tt=[lt.getTilePoint(new t.Z(wr,Tr)),lt.getTilePoint(new t.Z(Kr,sa))];if(Tt[0].x-Ct=0&&Tt[1].y+Ct>=0){let zt=At.map(mr=>lt.getTilePoint(mr)),ur=Nt.map(mr=>lt.getTilePoint(mr));Ae.push({tile:Je,tileID:lt,queryGeometry:zt,cameraQueryGeometry:ur,scale:dt})}}return Ae}getVisibleCoordinates(R){let ae=this.getRenderableIds(R).map(we=>this._tiles[we].tileID);for(let we of ae)we.posMatrix=this.transform.calculatePosMatrix(we.toUnwrapped());return ae}hasTransition(){if(this._source.hasTransition())return!0;if(Ht(this._source.type)){let R=n.now();for(let ae in this._tiles)if(this._tiles[ae].fadeEndTime>=R)return!0}return!1}setFeatureState(R,ae,we){this._state.updateState(R=R||"_geojsonTileLayer",ae,we)}removeFeatureState(R,ae,we){this._state.removeFeatureState(R=R||"_geojsonTileLayer",ae,we)}getFeatureState(R,ae){return this._state.getState(R=R||"_geojsonTileLayer",ae)}setDependencies(R,ae,we){let Ae=this._tiles[R];Ae&&Ae.setDependencies(ae,we)}reloadTilesForDependencies(R,ae){for(let we in this._tiles)this._tiles[we].hasDependency(R,ae)&&this._reloadTile(we,"reloading");this._cache.filter(we=>!we.hasDependency(R,ae))}}function qt(Ue,R){let ae=Math.abs(2*Ue.wrap)-+(Ue.wrap<0),we=Math.abs(2*R.wrap)-+(R.wrap<0);return Ue.overscaledZ-R.overscaledZ||we-ae||R.canonical.y-Ue.canonical.y||R.canonical.x-Ue.canonical.x}function Ht(Ue){return Ue==="raster"||Ue==="image"||Ue==="video"}Lt.maxOverzooming=10,Lt.maxUnderzooming=3;class Ar{constructor(R,ae){this.reset(R,ae)}reset(R,ae){this.points=R||[],this._distances=[0];for(let we=1;we0?(Ae-pt)/At:0;return this.points[Be].mult(1-Nt).add(this.points[ae].mult(Nt))}}function xr(Ue,R){let ae=!0;return Ue==="always"||Ue!=="never"&&R!=="never"||(ae=!1),ae}class qr{constructor(R,ae,we){let Ae=this.boxCells=[],Be=this.circleCells=[];this.xCellCount=Math.ceil(R/we),this.yCellCount=Math.ceil(ae/we);for(let pt=0;ptthis.width||Ae<0||ae>this.height)return[];let Nt=[];if(R<=0&&ae<=0&&this.width<=we&&this.height<=Ae){if(Be)return[{key:null,x1:R,y1:ae,x2:we,y2:Ae}];for(let $t=0;$t0}hitTestCircle(R,ae,we,Ae,Be){let pt=R-we,At=R+we,Nt=ae-we,$t=ae+we;if(At<0||pt>this.width||$t<0||Nt>this.height)return!1;let wr=[];return this._forEachCell(pt,Nt,At,$t,this._queryCellCircle,wr,{hitTest:!0,overlapMode:Ae,circle:{x:R,y:ae,radius:we},seenUids:{box:{},circle:{}}},Be),wr.length>0}_queryCell(R,ae,we,Ae,Be,pt,At,Nt){let{seenUids:$t,hitTest:wr,overlapMode:Tr}=At,Kr=this.boxCells[Be];if(Kr!==null){let He=this.bboxes;for(let Je of Kr)if(!$t.box[Je]){$t.box[Je]=!0;let lt=4*Je,dt=this.boxKeys[Je];if(R<=He[lt+2]&&ae<=He[lt+3]&&we>=He[lt+0]&&Ae>=He[lt+1]&&(!Nt||Nt(dt))&&(!wr||!xr(Tr,dt.overlapMode))&&(pt.push({key:dt,x1:He[lt],y1:He[lt+1],x2:He[lt+2],y2:He[lt+3]}),wr))return!0}}let sa=this.circleCells[Be];if(sa!==null){let He=this.circles;for(let Je of sa)if(!$t.circle[Je]){$t.circle[Je]=!0;let lt=3*Je,dt=this.circleKeys[Je];if(this._circleAndRectCollide(He[lt],He[lt+1],He[lt+2],R,ae,we,Ae)&&(!Nt||Nt(dt))&&(!wr||!xr(Tr,dt.overlapMode))){let Ct=He[lt],Tt=He[lt+1],zt=He[lt+2];if(pt.push({key:dt,x1:Ct-zt,y1:Tt-zt,x2:Ct+zt,y2:Tt+zt}),wr)return!0}}}return!1}_queryCellCircle(R,ae,we,Ae,Be,pt,At,Nt){let{circle:$t,seenUids:wr,overlapMode:Tr}=At,Kr=this.boxCells[Be];if(Kr!==null){let He=this.bboxes;for(let Je of Kr)if(!wr.box[Je]){wr.box[Je]=!0;let lt=4*Je,dt=this.boxKeys[Je];if(this._circleAndRectCollide($t.x,$t.y,$t.radius,He[lt+0],He[lt+1],He[lt+2],He[lt+3])&&(!Nt||Nt(dt))&&!xr(Tr,dt.overlapMode))return pt.push(!0),!0}}let sa=this.circleCells[Be];if(sa!==null){let He=this.circles;for(let Je of sa)if(!wr.circle[Je]){wr.circle[Je]=!0;let lt=3*Je,dt=this.circleKeys[Je];if(this._circlesCollide(He[lt],He[lt+1],He[lt+2],$t.x,$t.y,$t.radius)&&(!Nt||Nt(dt))&&!xr(Tr,dt.overlapMode))return pt.push(!0),!0}}}_forEachCell(R,ae,we,Ae,Be,pt,At,Nt){let $t=this._convertToXCellCoord(R),wr=this._convertToYCellCoord(ae),Tr=this._convertToXCellCoord(we),Kr=this._convertToYCellCoord(Ae);for(let sa=$t;sa<=Tr;sa++)for(let He=wr;He<=Kr;He++)if(Be.call(this,R,ae,we,Ae,this.xCellCount*He+sa,pt,At,Nt))return}_convertToXCellCoord(R){return Math.max(0,Math.min(this.xCellCount-1,Math.floor(R*this.xScale)))}_convertToYCellCoord(R){return Math.max(0,Math.min(this.yCellCount-1,Math.floor(R*this.yScale)))}_circlesCollide(R,ae,we,Ae,Be,pt){let At=Ae-R,Nt=Be-ae,$t=we+pt;return $t*$t>At*At+Nt*Nt}_circleAndRectCollide(R,ae,we,Ae,Be,pt,At){let Nt=(pt-Ae)/2,$t=Math.abs(R-(Ae+Nt));if($t>Nt+we)return!1;let wr=(At-Be)/2,Tr=Math.abs(ae-(Be+wr));if(Tr>wr+we)return!1;if($t<=Nt||Tr<=wr)return!0;let Kr=$t-Nt,sa=Tr-wr;return Kr*Kr+sa*sa<=we*we}}function br(Ue,R,ae,we,Ae){let Be=t.H();return R?(t.K(Be,Be,[1/Ae,1/Ae,1]),ae||t.ad(Be,Be,we.angle)):t.L(Be,we.labelPlaneMatrix,Ue),Be}function Ir(Ue,R,ae,we,Ae){if(R){let Be=t.ae(Ue);return t.K(Be,Be,[Ae,Ae,1]),ae||t.ad(Be,Be,-we.angle),Be}return we.glCoordMatrix}function bt(Ue,R,ae,we){let Ae;we?(Ae=[Ue,R,we(Ue,R),1],t.af(Ae,Ae,ae)):(Ae=[Ue,R,0,1],tr(Ae,Ae,ae));let Be=Ae[3];return{point:new t.P(Ae[0]/Be,Ae[1]/Be),signedDistanceFromCamera:Be,isOccluded:!1}}function Ne(Ue,R){return .5+Ue/R*.5}function Ke(Ue,R){return Ue.x>=-R[0]&&Ue.x<=R[0]&&Ue.y>=-R[1]&&Ue.y<=R[1]}function Te(Ue,R,ae,we,Ae,Be,pt,At,Nt,$t,wr,Tr,Kr,sa,He){let Je=we?Ue.textSizeData:Ue.iconSizeData,lt=t.ag(Je,ae.transform.zoom),dt=[256/ae.width*2+1,256/ae.height*2+1],Ct=we?Ue.text.dynamicLayoutVertexArray:Ue.icon.dynamicLayoutVertexArray;Ct.clear();let Tt=Ue.lineVertexArray,zt=we?Ue.text.placedSymbolArray:Ue.icon.placedSymbolArray,ur=ae.transform.width/ae.transform.height,mr=!1;for(let Er=0;ErMath.abs(ae.x-R.x)*we?{useVertical:!0}:(Ue===t.ah.vertical?R.yae.x)?{needsFlipping:!0}:null}function Ce(Ue,R,ae,we,Ae,Be,pt,At,Nt,$t,wr){let Tr=ae/24,Kr=R.lineOffsetX*Tr,sa=R.lineOffsetY*Tr,He;if(R.numGlyphs>1){let Je=R.glyphStartIndex+R.numGlyphs,lt=R.lineStartIndex,dt=R.lineStartIndex+R.lineLength,Ct=Pe(Tr,At,Kr,sa,we,R,wr,Ue);if(!Ct)return{notEnoughRoom:!0};let Tt=bt(Ct.first.point.x,Ct.first.point.y,pt,Ue.getElevation).point,zt=bt(Ct.last.point.x,Ct.last.point.y,pt,Ue.getElevation).point;if(Ae&&!we){let ur=je(R.writingMode,Tt,zt,$t);if(ur)return ur}He=[Ct.first];for(let ur=R.glyphStartIndex+1;ur0?Tt.point:function(mr,Er,Ur,Qr,da,wa){return Ee(mr,Er,Ur,1,da,wa)}(Ue.tileAnchorPoint,Ct,lt,0,Be,Ue),ur=je(R.writingMode,lt,zt,$t);if(ur)return ur}let Je=It(Tr*At.getoffsetX(R.glyphStartIndex),Kr,sa,we,R.segment,R.lineStartIndex,R.lineStartIndex+R.lineLength,Ue,wr);if(!Je||Ue.projectionCache.anyProjectionOccluded)return{notEnoughRoom:!0};He=[Je]}for(let Je of He)t.aj(Nt,Je.point,Je.angle);return{}}function Ee(Ue,R,ae,we,Ae,Be){let pt=Ue.add(Ue.sub(R)._unit()),At=Ae!==void 0?bt(pt.x,pt.y,Ae,Be.getElevation).point:ot(pt.x,pt.y,Be).point,Nt=ae.sub(At);return ae.add(Nt._mult(we/Nt.mag()))}function Ie(Ue,R,ae){let we=R.projectionCache;if(we.projections[Ue])return we.projections[Ue];let Ae=new t.P(R.lineVertexArray.getx(Ue),R.lineVertexArray.gety(Ue)),Be=ot(Ae.x,Ae.y,R);if(Be.signedDistanceFromCamera>0)return we.projections[Ue]=Be.point,we.anyProjectionOccluded=we.anyProjectionOccluded||Be.isOccluded,Be.point;let pt=Ue-ae.direction;return function(At,Nt,$t,wr,Tr){return Ee(At,Nt,$t,wr,void 0,Tr)}(ae.distanceFromAnchor===0?R.tileAnchorPoint:new t.P(R.lineVertexArray.getx(pt),R.lineVertexArray.gety(pt)),Ae,ae.previousVertex,ae.absOffsetX-ae.distanceFromAnchor+1,R)}function ot(Ue,R,ae){let we=Ue+ae.translation[0],Ae=R+ae.translation[1],Be;return!ae.pitchWithMap&&ae.projection.useSpecialProjectionForSymbols?(Be=ae.projection.projectTileCoordinates(we,Ae,ae.unwrappedTileID,ae.getElevation),Be.point.x=(.5*Be.point.x+.5)*ae.width,Be.point.y=(.5*-Be.point.y+.5)*ae.height):(Be=bt(we,Ae,ae.labelPlaneMatrix,ae.getElevation),Be.isOccluded=!1),Be}function gt(Ue,R,ae){return Ue._unit()._perp()._mult(R*ae)}function xt(Ue,R,ae,we,Ae,Be,pt,At,Nt){if(At.projectionCache.offsets[Ue])return At.projectionCache.offsets[Ue];let $t=ae.add(R);if(Ue+Nt.direction=Ae)return At.projectionCache.offsets[Ue]=$t,$t;let wr=Ie(Ue+Nt.direction,At,Nt),Tr=gt(wr.sub(ae),pt,Nt.direction),Kr=ae.add(Tr),sa=wr.add(Tr);return At.projectionCache.offsets[Ue]=t.ak(Be,$t,Kr,sa)||$t,At.projectionCache.offsets[Ue]}function It(Ue,R,ae,we,Ae,Be,pt,At,Nt){let $t=we?Ue-R:Ue+R,wr=$t>0?1:-1,Tr=0;we&&(wr*=-1,Tr=Math.PI),wr<0&&(Tr+=Math.PI);let Kr,sa=wr>0?Be+Ae:Be+Ae+1;At.projectionCache.cachedAnchorPoint?Kr=At.projectionCache.cachedAnchorPoint:(Kr=ot(At.tileAnchorPoint.x,At.tileAnchorPoint.y,At).point,At.projectionCache.cachedAnchorPoint=Kr);let He,Je,lt=Kr,dt=Kr,Ct=0,Tt=0,zt=Math.abs($t),ur=[],mr;for(;Ct+Tt<=zt;){if(sa+=wr,sa=pt)return null;Ct+=Tt,dt=lt,Je=He;let Qr={absOffsetX:zt,direction:wr,distanceFromAnchor:Ct,previousVertex:dt};if(lt=Ie(sa,At,Qr),ae===0)ur.push(dt),mr=lt.sub(dt);else{let da,wa=lt.sub(dt);da=wa.mag()===0?gt(Ie(sa+wr,At,Qr).sub(lt),ae,wr):gt(wa,ae,wr),Je||(Je=dt.add(da)),He=xt(sa,da,lt,Be,pt,Je,ae,At,Qr),ur.push(Je),mr=He.sub(Je)}Tt=mr.mag()}let Er=mr._mult((zt-Ct)/Tt)._add(Je||dt),Ur=Tr+Math.atan2(lt.y-dt.y,lt.x-dt.x);return ur.push(Er),{point:Er,angle:Nt?Ur:0,path:ur}}let cr=new Float32Array([-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0,-1/0,-1/0,0]);function ar(Ue,R){for(let ae=0;ae=1;On--)nn.push(Vi.path[On]);for(let On=1;OnTo.signedDistanceFromCamera<=0)?[]:On.map(To=>To.point)}let Zn=[];if(nn.length>0){let On=nn[0].clone(),To=nn[0].clone();for(let ss=1;ss=wa.x&&To.x<=Fa.x&&On.y>=wa.y&&To.y<=Fa.y?[nn]:To.xFa.x||To.yFa.y?[]:t.al([nn],wa.x,wa.y,Fa.x,Fa.y)}for(let On of Zn){fi.reset(On,.25*da);let To=0;To=fi.length<=.5*da?1:Math.ceil(fi.paddedLength/Sn)+1;for(let ss=0;ssbt(Ae.x,Ae.y,we,ae.getElevation))}queryRenderedSymbols(R){if(R.length===0||this.grid.keysLength()===0&&this.ignoredGrid.keysLength()===0)return{};let ae=[],we=1/0,Ae=1/0,Be=-1/0,pt=-1/0;for(let wr of R){let Tr=new t.P(wr.x+Lr,wr.y+Lr);we=Math.min(we,Tr.x),Ae=Math.min(Ae,Tr.y),Be=Math.max(Be,Tr.x),pt=Math.max(pt,Tr.y),ae.push(Tr)}let At=this.grid.query(we,Ae,Be,pt).concat(this.ignoredGrid.query(we,Ae,Be,pt)),Nt={},$t={};for(let wr of At){let Tr=wr.key;if(Nt[Tr.bucketInstanceId]===void 0&&(Nt[Tr.bucketInstanceId]={}),Nt[Tr.bucketInstanceId][Tr.featureIndex])continue;let Kr=[new t.P(wr.x1,wr.y1),new t.P(wr.x2,wr.y1),new t.P(wr.x2,wr.y2),new t.P(wr.x1,wr.y2)];t.am(ae,Kr)&&(Nt[Tr.bucketInstanceId][Tr.featureIndex]=!0,$t[Tr.bucketInstanceId]===void 0&&($t[Tr.bucketInstanceId]=[]),$t[Tr.bucketInstanceId].push(Tr.featureIndex))}return $t}insertCollisionBox(R,ae,we,Ae,Be,pt){(we?this.ignoredGrid:this.grid).insert({bucketInstanceId:Ae,featureIndex:Be,collisionGroupID:pt,overlapMode:ae},R[0],R[1],R[2],R[3])}insertCollisionCircles(R,ae,we,Ae,Be,pt){let At=we?this.ignoredGrid:this.grid,Nt={bucketInstanceId:Ae,featureIndex:Be,collisionGroupID:pt,overlapMode:ae};for(let $t=0;$t=this.screenRightBoundary||Aethis.screenBottomBoundary}isInsideGrid(R,ae,we,Ae){return we>=0&&R=0&&aethis.projectAndGetPerspectiveRatio(we,da.x,da.y,Ae,$t));Ur=Qr.some(da=>!da.isOccluded),Er=Qr.map(da=>da.point)}else Ur=!0;return{box:t.ao(Er),allPointsOccluded:!Ur}}}function za(Ue,R,ae){return R*(t.X/(Ue.tileSize*Math.pow(2,ae-Ue.tileID.overscaledZ)))}class Ra{constructor(R,ae,we,Ae){this.opacity=R?Math.max(0,Math.min(1,R.opacity+(R.placed?ae:-ae))):Ae&&we?1:0,this.placed=we}isHidden(){return this.opacity===0&&!this.placed}}class Va{constructor(R,ae,we,Ae,Be){this.text=new Ra(R?R.text:null,ae,we,Be),this.icon=new Ra(R?R.icon:null,ae,Ae,Be)}isHidden(){return this.text.isHidden()&&this.icon.isHidden()}}class Xa{constructor(R,ae,we){this.text=R,this.icon=ae,this.skipFade=we}}class Pa{constructor(){this.invProjMatrix=t.H(),this.viewportMatrix=t.H(),this.circles=[]}}class di{constructor(R,ae,we,Ae,Be){this.bucketInstanceId=R,this.featureIndex=ae,this.sourceLayerIndex=we,this.bucketIndex=Ae,this.tileID=Be}}class Mi{constructor(R){this.crossSourceCollisions=R,this.maxGroupID=0,this.collisionGroups={}}get(R){if(this.crossSourceCollisions)return{ID:0,predicate:null};if(!this.collisionGroups[R]){let ae=++this.maxGroupID;this.collisionGroups[R]={ID:ae,predicate:we=>we.collisionGroupID===ae}}return this.collisionGroups[R]}}function Yt(Ue,R,ae,we,Ae){let{horizontalAlign:Be,verticalAlign:pt}=t.au(Ue);return new t.P(-(Be-.5)*R+we[0]*Ae,-(pt-.5)*ae+we[1]*Ae)}class Ft{constructor(R,ae,we,Ae,Be,pt){this.transform=R.clone(),this.terrain=we,this.collisionIndex=new ha(this.transform,ae),this.placements={},this.opacities={},this.variableOffsets={},this.stale=!1,this.commitTime=0,this.fadeDuration=Ae,this.retainedQueryData={},this.collisionGroups=new Mi(Be),this.collisionCircleArrays={},this.collisionBoxArrays=new Map,this.prevPlacement=pt,pt&&(pt.prevPlacement=void 0),this.placedOrientations={}}_getTerrainElevationFunc(R){let ae=this.terrain;return ae?(we,Ae)=>ae.getElevation(R,we,Ae):null}getBucketParts(R,ae,we,Ae){let Be=we.getBucket(ae),pt=we.latestFeatureIndex;if(!Be||!pt||ae.id!==Be.layerIds[0])return;let At=we.collisionBoxArray,Nt=Be.layers[0].layout,$t=Be.layers[0].paint,wr=Math.pow(2,this.transform.zoom-we.tileID.overscaledZ),Tr=we.tileSize/t.X,Kr=we.tileID.toUnwrapped(),sa=this.transform.calculatePosMatrix(Kr),He=Nt.get("text-pitch-alignment")==="map",Je=Nt.get("text-rotation-alignment")==="map",lt=za(we,1,this.transform.zoom),dt=this.collisionIndex.mapProjection.translatePosition(this.transform,we,$t.get("text-translate"),$t.get("text-translate-anchor")),Ct=this.collisionIndex.mapProjection.translatePosition(this.transform,we,$t.get("icon-translate"),$t.get("icon-translate-anchor")),Tt=br(sa,He,Je,this.transform,lt),zt=null;if(He){let mr=Ir(sa,He,Je,this.transform,lt);zt=t.L([],this.transform.labelPlaneMatrix,mr)}this.retainedQueryData[Be.bucketInstanceId]=new di(Be.bucketInstanceId,pt,Be.sourceLayerIndex,Be.index,we.tileID);let ur={bucket:Be,layout:Nt,translationText:dt,translationIcon:Ct,posMatrix:sa,unwrappedTileID:Kr,textLabelPlaneMatrix:Tt,labelToScreenMatrix:zt,scale:wr,textPixelRatio:Tr,holdingForFade:we.holdingForFade(),collisionBoxArray:At,partiallyEvaluatedTextSize:t.ag(Be.textSizeData,this.transform.zoom),collisionGroup:this.collisionGroups.get(Be.sourceID)};if(Ae)for(let mr of Be.sortKeyRanges){let{sortKey:Er,symbolInstanceStart:Ur,symbolInstanceEnd:Qr}=mr;R.push({sortKey:Er,symbolInstanceStart:Ur,symbolInstanceEnd:Qr,parameters:ur})}else R.push({symbolInstanceStart:0,symbolInstanceEnd:Be.symbolInstances.length,parameters:ur})}attemptAnchorPlacement(R,ae,we,Ae,Be,pt,At,Nt,$t,wr,Tr,Kr,sa,He,Je,lt,dt,Ct,Tt){let zt=t.aq[R.textAnchor],ur=[R.textOffset0,R.textOffset1],mr=Yt(zt,we,Ae,ur,Be),Er=this.collisionIndex.placeCollisionBox(ae,Kr,Nt,$t,wr,At,pt,lt,Tr.predicate,Tt,mr);if((!Ct||this.collisionIndex.placeCollisionBox(Ct,Kr,Nt,$t,wr,At,pt,dt,Tr.predicate,Tt,mr).placeable)&&Er.placeable){let Ur;if(this.prevPlacement&&this.prevPlacement.variableOffsets[sa.crossTileID]&&this.prevPlacement.placements[sa.crossTileID]&&this.prevPlacement.placements[sa.crossTileID].text&&(Ur=this.prevPlacement.variableOffsets[sa.crossTileID].anchor),sa.crossTileID===0)throw new Error("symbolInstance.crossTileID can't be 0");return this.variableOffsets[sa.crossTileID]={textOffset:ur,width:we,height:Ae,anchor:zt,textBoxScale:Be,prevAnchor:Ur},this.markUsedJustification(He,zt,sa,Je),He.allowVerticalPlacement&&(this.markUsedOrientation(He,Je,sa),this.placedOrientations[sa.crossTileID]=Je),{shift:mr,placedGlyphBoxes:Er}}}placeLayerBucketPart(R,ae,we){let{bucket:Ae,layout:Be,translationText:pt,translationIcon:At,posMatrix:Nt,unwrappedTileID:$t,textLabelPlaneMatrix:wr,labelToScreenMatrix:Tr,textPixelRatio:Kr,holdingForFade:sa,collisionBoxArray:He,partiallyEvaluatedTextSize:Je,collisionGroup:lt}=R.parameters,dt=Be.get("text-optional"),Ct=Be.get("icon-optional"),Tt=t.ar(Be,"text-overlap","text-allow-overlap"),zt=Tt==="always",ur=t.ar(Be,"icon-overlap","icon-allow-overlap"),mr=ur==="always",Er=Be.get("text-rotation-alignment")==="map",Ur=Be.get("text-pitch-alignment")==="map",Qr=Be.get("icon-text-fit")!=="none",da=Be.get("symbol-z-order")==="viewport-y",wa=zt&&(mr||!Ae.hasIconData()||Ct),Fa=mr&&(zt||!Ae.hasTextData()||dt);!Ae.collisionArrays&&He&&Ae.deserializeCollisionBoxes(He);let fi=this._getTerrainElevationFunc(this.retainedQueryData[Ae.bucketInstanceId].tileID),Vi=(ji,nn,Sn)=>{var Zn,On;if(ae[ji.crossTileID])return;if(sa)return void(this.placements[ji.crossTileID]=new Xa(!1,!1,!1));let To=!1,ss=!1,Mo=!0,Yo=null,ps={box:null,placeable:!1,offscreen:null},sl={box:null,placeable:!1,offscreen:null},el=null,Qo=null,es=null,Rl=0,tu=0,Ru=0;nn.textFeatureIndex?Rl=nn.textFeatureIndex:ji.useRuntimeCollisionCircles&&(Rl=ji.featureIndex),nn.verticalTextFeatureIndex&&(tu=nn.verticalTextFeatureIndex);let pu=nn.textBox;if(pu){let Gl=et=>{let vt=t.ah.horizontal;if(Ae.allowVerticalPlacement&&!et&&this.prevPlacement){let _t=this.prevPlacement.placedOrientations[ji.crossTileID];_t&&(this.placedOrientations[ji.crossTileID]=_t,vt=_t,this.markUsedOrientation(Ae,vt,ji))}return vt},Hl=(et,vt)=>{if(Ae.allowVerticalPlacement&&ji.numVerticalGlyphVertices>0&&nn.verticalTextBox){for(let _t of Ae.writingModes)if(_t===t.ah.vertical?(ps=vt(),sl=ps):ps=et(),ps&&ps.placeable)break}else ps=et()},de=ji.textAnchorOffsetStartIndex,ze=ji.textAnchorOffsetEndIndex;if(ze===de){let et=(vt,_t)=>{let St=this.collisionIndex.placeCollisionBox(vt,Tt,Kr,Nt,$t,Ur,Er,pt,lt.predicate,fi);return St&&St.placeable&&(this.markUsedOrientation(Ae,_t,ji),this.placedOrientations[ji.crossTileID]=_t),St};Hl(()=>et(pu,t.ah.horizontal),()=>{let vt=nn.verticalTextBox;return Ae.allowVerticalPlacement&&ji.numVerticalGlyphVertices>0&&vt?et(vt,t.ah.vertical):{box:null,offscreen:null}}),Gl(ps&&ps.placeable)}else{let et=t.aq[(On=(Zn=this.prevPlacement)===null||Zn===void 0?void 0:Zn.variableOffsets[ji.crossTileID])===null||On===void 0?void 0:On.anchor],vt=(St,rr,Ot)=>{let gr=St.x2-St.x1,Vr=St.y2-St.y1,Wr=ji.textBoxScale,xa=Qr&&ur==="never"?rr:null,va=null,Qa=Tt==="never"?1:2,ai="never";et&&Qa++;for(let Sa=0;Savt(pu,nn.iconBox,t.ah.horizontal),()=>{let St=nn.verticalTextBox;return Ae.allowVerticalPlacement&&(!ps||!ps.placeable)&&ji.numVerticalGlyphVertices>0&&St?vt(St,nn.verticalIconBox,t.ah.vertical):{box:null,occluded:!0,offscreen:null}}),ps&&(To=ps.placeable,Mo=ps.offscreen);let _t=Gl(ps&&ps.placeable);if(!To&&this.prevPlacement){let St=this.prevPlacement.variableOffsets[ji.crossTileID];St&&(this.variableOffsets[ji.crossTileID]=St,this.markUsedJustification(Ae,St.anchor,ji,_t))}}}if(el=ps,To=el&&el.placeable,Mo=el&&el.offscreen,ji.useRuntimeCollisionCircles){let Gl=Ae.text.placedSymbolArray.get(ji.centerJustifiedTextSymbolIndex),Hl=t.ai(Ae.textSizeData,Je,Gl),de=Be.get("text-padding");Qo=this.collisionIndex.placeCollisionCircles(Tt,Gl,Ae.lineVertexArray,Ae.glyphOffsetArray,Hl,Nt,$t,wr,Tr,we,Ur,lt.predicate,ji.collisionCircleDiameter,de,pt,fi),Qo.circles.length&&Qo.collisionDetected&&!we&&t.w("Collisions detected, but collision boxes are not shown"),To=zt||Qo.circles.length>0&&!Qo.collisionDetected,Mo=Mo&&Qo.offscreen}if(nn.iconFeatureIndex&&(Ru=nn.iconFeatureIndex),nn.iconBox){let Gl=Hl=>this.collisionIndex.placeCollisionBox(Hl,ur,Kr,Nt,$t,Ur,Er,At,lt.predicate,fi,Qr&&Yo?Yo:void 0);sl&&sl.placeable&&nn.verticalIconBox?(es=Gl(nn.verticalIconBox),ss=es.placeable):(es=Gl(nn.iconBox),ss=es.placeable),Mo=Mo&&es.offscreen}let Tl=dt||ji.numHorizontalGlyphVertices===0&&ji.numVerticalGlyphVertices===0,uu=Ct||ji.numIconVertices===0;Tl||uu?uu?Tl||(ss=ss&&To):To=ss&&To:ss=To=ss&&To;let cc=ss&&es.placeable;if(To&&el.placeable&&this.collisionIndex.insertCollisionBox(el.box,Tt,Be.get("text-ignore-placement"),Ae.bucketInstanceId,sl&&sl.placeable&&tu?tu:Rl,lt.ID),cc&&this.collisionIndex.insertCollisionBox(es.box,ur,Be.get("icon-ignore-placement"),Ae.bucketInstanceId,Ru,lt.ID),Qo&&To&&this.collisionIndex.insertCollisionCircles(Qo.circles,Tt,Be.get("text-ignore-placement"),Ae.bucketInstanceId,Rl,lt.ID),we&&this.storeCollisionData(Ae.bucketInstanceId,Sn,nn,el,es,Qo),ji.crossTileID===0)throw new Error("symbolInstance.crossTileID can't be 0");if(Ae.bucketInstanceId===0)throw new Error("bucket.bucketInstanceId can't be 0");this.placements[ji.crossTileID]=new Xa(To||wa,ss||Fa,Mo||Ae.justReloaded),ae[ji.crossTileID]=!0};if(da){if(R.symbolInstanceStart!==0)throw new Error("bucket.bucketInstanceId should be 0");let ji=Ae.getSortedSymbolIndexes(this.transform.angle);for(let nn=ji.length-1;nn>=0;--nn){let Sn=ji[nn];Vi(Ae.symbolInstances.get(Sn),Ae.collisionArrays[Sn],Sn)}}else for(let ji=R.symbolInstanceStart;ji=0&&(R.text.placedSymbolArray.get(At).crossTileID=Be>=0&&At!==Be?0:we.crossTileID)}markUsedOrientation(R,ae,we){let Ae=ae===t.ah.horizontal||ae===t.ah.horizontalOnly?ae:0,Be=ae===t.ah.vertical?ae:0,pt=[we.leftJustifiedTextSymbolIndex,we.centerJustifiedTextSymbolIndex,we.rightJustifiedTextSymbolIndex];for(let At of pt)R.text.placedSymbolArray.get(At).placedOrientation=Ae;we.verticalPlacedTextSymbolIndex&&(R.text.placedSymbolArray.get(we.verticalPlacedTextSymbolIndex).placedOrientation=Be)}commit(R){this.commitTime=R,this.zoomAtLastRecencyCheck=this.transform.zoom;let ae=this.prevPlacement,we=!1;this.prevZoomAdjustment=ae?ae.zoomAdjustment(this.transform.zoom):0;let Ae=ae?ae.symbolFadeChange(R):1,Be=ae?ae.opacities:{},pt=ae?ae.variableOffsets:{},At=ae?ae.placedOrientations:{};for(let Nt in this.placements){let $t=this.placements[Nt],wr=Be[Nt];wr?(this.opacities[Nt]=new Va(wr,Ae,$t.text,$t.icon),we=we||$t.text!==wr.text.placed||$t.icon!==wr.icon.placed):(this.opacities[Nt]=new Va(null,Ae,$t.text,$t.icon,$t.skipFade),we=we||$t.text||$t.icon)}for(let Nt in Be){let $t=Be[Nt];if(!this.opacities[Nt]){let wr=new Va($t,Ae,!1,!1);wr.isHidden()||(this.opacities[Nt]=wr,we=we||$t.text.placed||$t.icon.placed)}}for(let Nt in pt)this.variableOffsets[Nt]||!this.opacities[Nt]||this.opacities[Nt].isHidden()||(this.variableOffsets[Nt]=pt[Nt]);for(let Nt in At)this.placedOrientations[Nt]||!this.opacities[Nt]||this.opacities[Nt].isHidden()||(this.placedOrientations[Nt]=At[Nt]);if(ae&&ae.lastPlacementChangeTime===void 0)throw new Error("Last placement time for previous placement is not defined");we?this.lastPlacementChangeTime=R:typeof this.lastPlacementChangeTime!="number"&&(this.lastPlacementChangeTime=ae?ae.lastPlacementChangeTime:R)}updateLayerOpacities(R,ae){let we={};for(let Ae of ae){let Be=Ae.getBucket(R);Be&&Ae.latestFeatureIndex&&R.id===Be.layerIds[0]&&this.updateBucketOpacities(Be,Ae.tileID,we,Ae.collisionBoxArray)}}updateBucketOpacities(R,ae,we,Ae){R.hasTextData()&&(R.text.opacityVertexArray.clear(),R.text.hasVisibleVertices=!1),R.hasIconData()&&(R.icon.opacityVertexArray.clear(),R.icon.hasVisibleVertices=!1),R.hasIconCollisionBoxData()&&R.iconCollisionBox.collisionVertexArray.clear(),R.hasTextCollisionBoxData()&&R.textCollisionBox.collisionVertexArray.clear();let Be=R.layers[0],pt=Be.layout,At=new Va(null,0,!1,!1,!0),Nt=pt.get("text-allow-overlap"),$t=pt.get("icon-allow-overlap"),wr=Be._unevaluatedLayout.hasValue("text-variable-anchor")||Be._unevaluatedLayout.hasValue("text-variable-anchor-offset"),Tr=pt.get("text-rotation-alignment")==="map",Kr=pt.get("text-pitch-alignment")==="map",sa=pt.get("icon-text-fit")!=="none",He=new Va(null,0,Nt&&($t||!R.hasIconData()||pt.get("icon-optional")),$t&&(Nt||!R.hasTextData()||pt.get("text-optional")),!0);!R.collisionArrays&&Ae&&(R.hasIconCollisionBoxData()||R.hasTextCollisionBoxData())&&R.deserializeCollisionBoxes(Ae);let Je=(dt,Ct,Tt)=>{for(let zt=0;zt0,Ur=this.placedOrientations[Ct.crossTileID],Qr=Ur===t.ah.vertical,da=Ur===t.ah.horizontal||Ur===t.ah.horizontalOnly;if(Tt>0||zt>0){let Fa=Ya(mr.text);Je(R.text,Tt,Qr?ri:Fa),Je(R.text,zt,da?ri:Fa);let fi=mr.text.isHidden();[Ct.rightJustifiedTextSymbolIndex,Ct.centerJustifiedTextSymbolIndex,Ct.leftJustifiedTextSymbolIndex].forEach(nn=>{nn>=0&&(R.text.placedSymbolArray.get(nn).hidden=fi||Qr?1:0)}),Ct.verticalPlacedTextSymbolIndex>=0&&(R.text.placedSymbolArray.get(Ct.verticalPlacedTextSymbolIndex).hidden=fi||da?1:0);let Vi=this.variableOffsets[Ct.crossTileID];Vi&&this.markUsedJustification(R,Vi.anchor,Ct,Ur);let ji=this.placedOrientations[Ct.crossTileID];ji&&(this.markUsedJustification(R,"left",Ct,ji),this.markUsedOrientation(R,ji,Ct))}if(Er){let Fa=Ya(mr.icon),fi=!(sa&&Ct.verticalPlacedIconSymbolIndex&&Qr);Ct.placedIconSymbolIndex>=0&&(Je(R.icon,Ct.numIconVertices,fi?Fa:ri),R.icon.placedSymbolArray.get(Ct.placedIconSymbolIndex).hidden=mr.icon.isHidden()),Ct.verticalPlacedIconSymbolIndex>=0&&(Je(R.icon,Ct.numVerticalIconVertices,fi?ri:Fa),R.icon.placedSymbolArray.get(Ct.verticalPlacedIconSymbolIndex).hidden=mr.icon.isHidden())}let wa=lt&<.has(dt)?lt.get(dt):{text:null,icon:null};if(R.hasIconCollisionBoxData()||R.hasTextCollisionBoxData()){let Fa=R.collisionArrays[dt];if(Fa){let fi=new t.P(0,0);if(Fa.textBox||Fa.verticalTextBox){let Vi=!0;if(wr){let ji=this.variableOffsets[ur];ji?(fi=Yt(ji.anchor,ji.width,ji.height,ji.textOffset,ji.textBoxScale),Tr&&fi._rotate(Kr?this.transform.angle:-this.transform.angle)):Vi=!1}if(Fa.textBox||Fa.verticalTextBox){let ji;Fa.textBox&&(ji=Qr),Fa.verticalTextBox&&(ji=da),Zt(R.textCollisionBox.collisionVertexArray,mr.text.placed,!Vi||ji,wa.text,fi.x,fi.y)}}if(Fa.iconBox||Fa.verticalIconBox){let Vi=!!(!da&&Fa.verticalIconBox),ji;Fa.iconBox&&(ji=Vi),Fa.verticalIconBox&&(ji=!Vi),Zt(R.iconCollisionBox.collisionVertexArray,mr.icon.placed,ji,wa.icon,sa?fi.x:0,sa?fi.y:0)}}}}if(R.sortFeatures(this.transform.angle),this.retainedQueryData[R.bucketInstanceId]&&(this.retainedQueryData[R.bucketInstanceId].featureSortOrder=R.featureSortOrder),R.hasTextData()&&R.text.opacityVertexBuffer&&R.text.opacityVertexBuffer.updateData(R.text.opacityVertexArray),R.hasIconData()&&R.icon.opacityVertexBuffer&&R.icon.opacityVertexBuffer.updateData(R.icon.opacityVertexArray),R.hasIconCollisionBoxData()&&R.iconCollisionBox.collisionVertexBuffer&&R.iconCollisionBox.collisionVertexBuffer.updateData(R.iconCollisionBox.collisionVertexArray),R.hasTextCollisionBoxData()&&R.textCollisionBox.collisionVertexBuffer&&R.textCollisionBox.collisionVertexBuffer.updateData(R.textCollisionBox.collisionVertexArray),R.text.opacityVertexArray.length!==R.text.layoutVertexArray.length/4)throw new Error(`bucket.text.opacityVertexArray.length (= ${R.text.opacityVertexArray.length}) !== bucket.text.layoutVertexArray.length (= ${R.text.layoutVertexArray.length}) / 4`);if(R.icon.opacityVertexArray.length!==R.icon.layoutVertexArray.length/4)throw new Error(`bucket.icon.opacityVertexArray.length (= ${R.icon.opacityVertexArray.length}) !== bucket.icon.layoutVertexArray.length (= ${R.icon.layoutVertexArray.length}) / 4`);if(R.bucketInstanceId in this.collisionCircleArrays){let dt=this.collisionCircleArrays[R.bucketInstanceId];R.placementInvProjMatrix=dt.invProjMatrix,R.placementViewportMatrix=dt.viewportMatrix,R.collisionCircleArray=dt.circles,delete this.collisionCircleArrays[R.bucketInstanceId]}}symbolFadeChange(R){return this.fadeDuration===0?1:(R-this.commitTime)/this.fadeDuration+this.prevZoomAdjustment}zoomAdjustment(R){return Math.max(0,(this.transform.zoom-R)/1.5)}hasTransitions(R){return this.stale||R-this.lastPlacementChangeTimeR}setStale(){this.stale=!0}}function Zt(Ue,R,ae,we,Ae,Be){we&&we.length!==0||(we=[0,0,0,0]);let pt=we[0]-Lr,At=we[1]-Lr,Nt=we[2]-Lr,$t=we[3]-Lr;Ue.emplaceBack(R?1:0,ae?1:0,Ae||0,Be||0,pt,At),Ue.emplaceBack(R?1:0,ae?1:0,Ae||0,Be||0,Nt,At),Ue.emplaceBack(R?1:0,ae?1:0,Ae||0,Be||0,Nt,$t),Ue.emplaceBack(R?1:0,ae?1:0,Ae||0,Be||0,pt,$t)}let Jt=Math.pow(2,25),Br=Math.pow(2,24),ta=Math.pow(2,17),aa=Math.pow(2,16),fa=Math.pow(2,9),Na=Math.pow(2,8),$a=Math.pow(2,1);function Ya(Ue){if(Ue.opacity===0&&!Ue.placed)return 0;if(Ue.opacity===1&&Ue.placed)return 4294967295;let R=Ue.placed?1:0,ae=Math.floor(127*Ue.opacity);return ae*Jt+R*Br+ae*ta+R*aa+ae*fa+R*Na+ae*$a+R}let ri=0;function mi(){return{isOccluded:(Ue,R,ae)=>!1,getPitchedTextCorrection:(Ue,R,ae)=>1,get useSpecialProjectionForSymbols(){return!1},projectTileCoordinates(Ue,R,ae,we){throw new Error("Not implemented.")},translatePosition:(Ue,R,ae,we)=>function(Ae,Be,pt,At,Nt=!1){if(!pt[0]&&!pt[1])return[0,0];let $t=Nt?At==="map"?Ae.angle:0:At==="viewport"?-Ae.angle:0;if($t){let wr=Math.sin($t),Tr=Math.cos($t);pt=[pt[0]*Tr-pt[1]*wr,pt[0]*wr+pt[1]*Tr]}return[Nt?pt[0]:za(Be,pt[0],Ae.zoom),Nt?pt[1]:za(Be,pt[1],Ae.zoom)]}(Ue,R,ae,we),getCircleRadiusCorrection:Ue=>1}}class Da{constructor(R){this._sortAcrossTiles=R.layout.get("symbol-z-order")!=="viewport-y"&&!R.layout.get("symbol-sort-key").isConstant(),this._currentTileIndex=0,this._currentPartIndex=0,this._seenCrossTileIDs={},this._bucketParts=[]}continuePlacement(R,ae,we,Ae,Be){let pt=this._bucketParts;for(;this._currentTileIndexAt.sortKey-Nt.sortKey));this._currentPartIndex!this._forceFullPlacement&&n.now()-Ae>2;for(;this._currentPlacementIndex>=0;){let pt=ae[R[this._currentPlacementIndex]],At=this.placement.collisionIndex.transform.zoom;if(pt.type==="symbol"&&(!pt.minzoom||pt.minzoom<=At)&&(!pt.maxzoom||pt.maxzoom>At)){if(this._inProgressLayer||(this._inProgressLayer=new Da(pt)),this._inProgressLayer.continuePlacement(we[pt.source],this.placement,this._showCollisionBoxes,pt,Be))return;delete this._inProgressLayer}this._currentPlacementIndex--}this._done=!0}commit(R){return this.placement.commit(R),this.placement}}let on=512/t.X/2;class kt{constructor(R,ae,we){this.tileID=R,this.bucketInstanceId=we,this._symbolsByKey={};let Ae=new Map;for(let Be=0;Be({x:Math.floor(Nt.anchorX*on),y:Math.floor(Nt.anchorY*on)})),crossTileIDs:pt.map(Nt=>Nt.crossTileID)};if(At.positions.length>128){let Nt=new t.av(At.positions.length,16,Uint16Array);for(let{x:$t,y:wr}of At.positions)Nt.add($t,wr);Nt.finish(),delete At.positions,At.index=Nt}this._symbolsByKey[Be]=At}}getScaledCoordinates(R,ae){let{x:we,y:Ae,z:Be}=this.tileID.canonical,{x:pt,y:At,z:Nt}=ae.canonical,$t=on/Math.pow(2,Nt-Be),wr=(At*t.X+R.anchorY)*$t,Tr=Ae*t.X*on;return{x:Math.floor((pt*t.X+R.anchorX)*$t-we*t.X*on),y:Math.floor(wr-Tr)}}findMatches(R,ae,we){let Ae=this.tileID.canonical.zR)}}class ft{constructor(){this.maxCrossTileID=0}generate(){return++this.maxCrossTileID}}class Mr{constructor(){this.indexes={},this.usedCrossTileIDs={},this.lng=0}handleWrapJump(R){let ae=Math.round((R-this.lng)/360);if(ae!==0)for(let we in this.indexes){let Ae=this.indexes[we],Be={};for(let pt in Ae){let At=Ae[pt];At.tileID=At.tileID.unwrapTo(At.tileID.wrap+ae),Be[At.tileID.key]=At}this.indexes[we]=Be}this.lng=R}addBucket(R,ae,we){if(this.indexes[R.overscaledZ]&&this.indexes[R.overscaledZ][R.key]){if(this.indexes[R.overscaledZ][R.key].bucketInstanceId===ae.bucketInstanceId)return!1;this.removeBucketCrossTileIDs(R.overscaledZ,this.indexes[R.overscaledZ][R.key])}for(let Be=0;BeR.overscaledZ)for(let At in pt){let Nt=pt[At];Nt.tileID.isChildOf(R)&&Nt.findMatches(ae.symbolInstances,R,Ae)}else{let At=pt[R.scaledTo(Number(Be)).key];At&&At.findMatches(ae.symbolInstances,R,Ae)}}for(let Be=0;Be{ae[we]=!0});for(let we in this.layerIndexes)ae[we]||delete this.layerIndexes[we]}}let zr=(Ue,R)=>t.t(Ue,R&&R.filter(ae=>ae.identifier!=="source.canvas")),kr=t.aw();class Dr extends t.E{constructor(R,ae={}){super(),this._rtlPluginLoaded=()=>{for(let we in this.sourceCaches){let Ae=this.sourceCaches[we].getSource().type;Ae!=="vector"&&Ae!=="geojson"||this.sourceCaches[we].reload()}},this.map=R,this.dispatcher=new J($(),R._getMapId()),this.dispatcher.registerMessageHandler("GG",(we,Ae)=>this.getGlyphs(we,Ae)),this.dispatcher.registerMessageHandler("GI",(we,Ae)=>this.getImages(we,Ae)),this.imageManager=new f,this.imageManager.setEventedParent(this),this.glyphManager=new F(R._requestManager,ae.localIdeographFontFamily),this.lineAtlas=new W(256,512),this.crossTileSymbolIndex=new Rr,this._spritesImagesIds={},this._layers={},this._order=[],this.sourceCaches={},this.zoomHistory=new t.ax,this._loaded=!1,this._availableImages=[],this._resetUpdates(),this.dispatcher.broadcast("SR",t.ay()),rt().on(_e,this._rtlPluginLoaded),this.on("data",we=>{if(we.dataType!=="source"||we.sourceDataType!=="metadata")return;let Ae=this.sourceCaches[we.sourceId];if(!Ae)return;let Be=Ae.getSource();if(Be&&Be.vectorLayerIds)for(let pt in this._layers){let At=this._layers[pt];At.source===Be.id&&this._validateLayer(At)}})}loadURL(R,ae={},we){this.fire(new t.k("dataloading",{dataType:"style"})),ae.validate=typeof ae.validate!="boolean"||ae.validate;let Ae=this.map._requestManager.transformRequest(R,"Style");this._loadStyleRequest=new AbortController;let Be=this._loadStyleRequest;t.h(Ae,this._loadStyleRequest).then(pt=>{this._loadStyleRequest=null,this._load(pt.data,ae,we)}).catch(pt=>{this._loadStyleRequest=null,pt&&!Be.signal.aborted&&this.fire(new t.j(pt))})}loadJSON(R,ae={},we){this.fire(new t.k("dataloading",{dataType:"style"})),this._frameRequest=new AbortController,n.frameAsync(this._frameRequest).then(()=>{this._frameRequest=null,ae.validate=ae.validate!==!1,this._load(R,ae,we)}).catch(()=>{})}loadEmpty(){this.fire(new t.k("dataloading",{dataType:"style"})),this._load(kr,{validate:!1})}_load(R,ae,we){var Ae;let Be=ae.transformStyle?ae.transformStyle(we,R):R;if(!ae.validate||!zr(this,t.u(Be))){this._loaded=!0,this.stylesheet=Be;for(let pt in Be.sources)this.addSource(pt,Be.sources[pt],{validate:!1});Be.sprite?this._loadSprite(Be.sprite):this.imageManager.setLoaded(!0),this.glyphManager.setURL(Be.glyphs),this._createLayers(),this.light=new I(this.stylesheet.light),this.sky=new U(this.stylesheet.sky),this.map.setTerrain((Ae=this.stylesheet.terrain)!==null&&Ae!==void 0?Ae:null),this.fire(new t.k("data",{dataType:"style"})),this.fire(new t.k("style.load"))}}_createLayers(){let R=t.az(this.stylesheet.layers);this.dispatcher.broadcast("SL",R),this._order=R.map(ae=>ae.id),this._layers={},this._serializedLayers=null;for(let ae of R){let we=t.aA(ae);we.setEventedParent(this,{layer:{id:ae.id}}),this._layers[ae.id]=we}}_loadSprite(R,ae=!1,we=void 0){let Ae;this.imageManager.setLoaded(!1),this._spriteRequest=new AbortController,function(Be,pt,At,Nt){return t._(this,void 0,void 0,function*(){let $t=b(Be),wr=At>1?"@2x":"",Tr={},Kr={};for(let{id:sa,url:He}of $t){let Je=pt.transformRequest(p(He,wr,".json"),"SpriteJSON");Tr[sa]=t.h(Je,Nt);let lt=pt.transformRequest(p(He,wr,".png"),"SpriteImage");Kr[sa]=l.getImage(lt,Nt)}return yield Promise.all([...Object.values(Tr),...Object.values(Kr)]),function(sa,He){return t._(this,void 0,void 0,function*(){let Je={};for(let lt in sa){Je[lt]={};let dt=n.getImageCanvasContext((yield He[lt]).data),Ct=(yield sa[lt]).data;for(let Tt in Ct){let{width:zt,height:ur,x:mr,y:Er,sdf:Ur,pixelRatio:Qr,stretchX:da,stretchY:wa,content:Fa,textFitWidth:fi,textFitHeight:Vi}=Ct[Tt];Je[lt][Tt]={data:null,pixelRatio:Qr,sdf:Ur,stretchX:da,stretchY:wa,content:Fa,textFitWidth:fi,textFitHeight:Vi,spriteData:{width:zt,height:ur,x:mr,y:Er,context:dt}}}}return Je})}(Tr,Kr)})}(R,this.map._requestManager,this.map.getPixelRatio(),this._spriteRequest).then(Be=>{if(this._spriteRequest=null,Be)for(let pt in Be){this._spritesImagesIds[pt]=[];let At=this._spritesImagesIds[pt]?this._spritesImagesIds[pt].filter(Nt=>!(Nt in Be)):[];for(let Nt of At)this.imageManager.removeImage(Nt),this._changedImages[Nt]=!0;for(let Nt in Be[pt]){let $t=pt==="default"?Nt:`${pt}:${Nt}`;this._spritesImagesIds[pt].push($t),$t in this.imageManager.images?this.imageManager.updateImage($t,Be[pt][Nt],!1):this.imageManager.addImage($t,Be[pt][Nt]),ae&&(this._changedImages[$t]=!0)}}}).catch(Be=>{this._spriteRequest=null,Ae=Be,this.fire(new t.j(Ae))}).finally(()=>{this.imageManager.setLoaded(!0),this._availableImages=this.imageManager.listImages(),ae&&(this._changed=!0),this.dispatcher.broadcast("SI",this._availableImages),this.fire(new t.k("data",{dataType:"style"})),we&&we(Ae)})}_unloadSprite(){for(let R of Object.values(this._spritesImagesIds).flat())this.imageManager.removeImage(R),this._changedImages[R]=!0;this._spritesImagesIds={},this._availableImages=this.imageManager.listImages(),this._changed=!0,this.dispatcher.broadcast("SI",this._availableImages),this.fire(new t.k("data",{dataType:"style"}))}_validateLayer(R){let ae=this.sourceCaches[R.source];if(!ae)return;let we=R.sourceLayer;if(!we)return;let Ae=ae.getSource();(Ae.type==="geojson"||Ae.vectorLayerIds&&Ae.vectorLayerIds.indexOf(we)===-1)&&this.fire(new t.j(new Error(`Source layer "${we}" does not exist on source "${Ae.id}" as specified by style layer "${R.id}".`)))}loaded(){if(!this._loaded||Object.keys(this._updatedSources).length)return!1;for(let R in this.sourceCaches)if(!this.sourceCaches[R].loaded())return!1;return!!this.imageManager.isLoaded()}_serializeByIds(R,ae=!1){let we=this._serializedAllLayers();if(!R||R.length===0)return Object.values(ae?t.aB(we):we);let Ae=[];for(let Be of R)if(we[Be]){let pt=ae?t.aB(we[Be]):we[Be];Ae.push(pt)}return Ae}_serializedAllLayers(){let R=this._serializedLayers;if(R)return R;R=this._serializedLayers={};let ae=Object.keys(this._layers);for(let we of ae){let Ae=this._layers[we];Ae.type!=="custom"&&(R[we]=Ae.serialize())}return R}hasTransitions(){if(this.light&&this.light.hasTransition()||this.sky&&this.sky.hasTransition())return!0;for(let R in this.sourceCaches)if(this.sourceCaches[R].hasTransition())return!0;for(let R in this._layers)if(this._layers[R].hasTransition())return!0;return!1}_checkLoaded(){if(!this._loaded)throw new Error("Style is not done loading.")}update(R){if(!this._loaded)return;let ae=this._changed;if(ae){let Ae=Object.keys(this._updatedLayers),Be=Object.keys(this._removedLayers);(Ae.length||Be.length)&&this._updateWorkerLayers(Ae,Be);for(let pt in this._updatedSources){let At=this._updatedSources[pt];if(At==="reload")this._reloadSource(pt);else{if(At!=="clear")throw new Error(`Invalid action ${At}`);this._clearSource(pt)}}this._updateTilesForChangedImages(),this._updateTilesForChangedGlyphs();for(let pt in this._updatedPaintProps)this._layers[pt].updateTransitions(R);this.light.updateTransitions(R),this.sky.updateTransitions(R),this._resetUpdates()}let we={};for(let Ae in this.sourceCaches){let Be=this.sourceCaches[Ae];we[Ae]=Be.used,Be.used=!1}for(let Ae of this._order){let Be=this._layers[Ae];Be.recalculate(R,this._availableImages),!Be.isHidden(R.zoom)&&Be.source&&(this.sourceCaches[Be.source].used=!0)}for(let Ae in we){let Be=this.sourceCaches[Ae];!!we[Ae]!=!!Be.used&&Be.fire(new t.k("data",{sourceDataType:"visibility",dataType:"source",sourceId:Ae}))}this.light.recalculate(R),this.sky.recalculate(R),this.z=R.zoom,ae&&this.fire(new t.k("data",{dataType:"style"}))}_updateTilesForChangedImages(){let R=Object.keys(this._changedImages);if(R.length){for(let ae in this.sourceCaches)this.sourceCaches[ae].reloadTilesForDependencies(["icons","patterns"],R);this._changedImages={}}}_updateTilesForChangedGlyphs(){if(this._glyphsDidChange){for(let R in this.sourceCaches)this.sourceCaches[R].reloadTilesForDependencies(["glyphs"],[""]);this._glyphsDidChange=!1}}_updateWorkerLayers(R,ae){this.dispatcher.broadcast("UL",{layers:this._serializeByIds(R,!1),removedIds:ae})}_resetUpdates(){this._changed=!1,this._updatedLayers={},this._removedLayers={},this._updatedSources={},this._updatedPaintProps={},this._changedImages={},this._glyphsDidChange=!1}setState(R,ae={}){var we;this._checkLoaded();let Ae=this.serialize();if(R=ae.transformStyle?ae.transformStyle(Ae,R):R,((we=ae.validate)===null||we===void 0||we)&&zr(this,t.u(R)))return!1;(R=t.aB(R)).layers=t.az(R.layers);let Be=t.aC(Ae,R),pt=this._getOperationsToPerform(Be);if(pt.unimplemented.length>0)throw new Error(`Unimplemented: ${pt.unimplemented.join(", ")}.`);if(pt.operations.length===0)return!1;for(let At of pt.operations)At();return this.stylesheet=R,this._serializedLayers=null,!0}_getOperationsToPerform(R){let ae=[],we=[];for(let Ae of R)switch(Ae.command){case"setCenter":case"setZoom":case"setBearing":case"setPitch":continue;case"addLayer":ae.push(()=>this.addLayer.apply(this,Ae.args));break;case"removeLayer":ae.push(()=>this.removeLayer.apply(this,Ae.args));break;case"setPaintProperty":ae.push(()=>this.setPaintProperty.apply(this,Ae.args));break;case"setLayoutProperty":ae.push(()=>this.setLayoutProperty.apply(this,Ae.args));break;case"setFilter":ae.push(()=>this.setFilter.apply(this,Ae.args));break;case"addSource":ae.push(()=>this.addSource.apply(this,Ae.args));break;case"removeSource":ae.push(()=>this.removeSource.apply(this,Ae.args));break;case"setLayerZoomRange":ae.push(()=>this.setLayerZoomRange.apply(this,Ae.args));break;case"setLight":ae.push(()=>this.setLight.apply(this,Ae.args));break;case"setGeoJSONSourceData":ae.push(()=>this.setGeoJSONSourceData.apply(this,Ae.args));break;case"setGlyphs":ae.push(()=>this.setGlyphs.apply(this,Ae.args));break;case"setSprite":ae.push(()=>this.setSprite.apply(this,Ae.args));break;case"setSky":ae.push(()=>this.setSky.apply(this,Ae.args));break;case"setTerrain":ae.push(()=>this.map.setTerrain.apply(this,Ae.args));break;case"setTransition":ae.push(()=>{});break;default:we.push(Ae.command)}return{operations:ae,unimplemented:we}}addImage(R,ae){if(this.getImage(R))return this.fire(new t.j(new Error(`An image named "${R}" already exists.`)));this.imageManager.addImage(R,ae),this._afterImageUpdated(R)}updateImage(R,ae){this.imageManager.updateImage(R,ae)}getImage(R){return this.imageManager.getImage(R)}removeImage(R){if(!this.getImage(R))return this.fire(new t.j(new Error(`An image named "${R}" does not exist.`)));this.imageManager.removeImage(R),this._afterImageUpdated(R)}_afterImageUpdated(R){this._availableImages=this.imageManager.listImages(),this._changedImages[R]=!0,this._changed=!0,this.dispatcher.broadcast("SI",this._availableImages),this.fire(new t.k("data",{dataType:"style"}))}listImages(){return this._checkLoaded(),this.imageManager.listImages()}addSource(R,ae,we={}){if(this._checkLoaded(),this.sourceCaches[R]!==void 0)throw new Error(`Source "${R}" already exists.`);if(!ae.type)throw new Error(`The type property must be defined, but only the following properties were given: ${Object.keys(ae).join(", ")}.`);if(["vector","raster","geojson","video","image"].indexOf(ae.type)>=0&&this._validate(t.u.source,`sources.${R}`,ae,null,we))return;this.map&&this.map._collectResourceTiming&&(ae.collectResourceTiming=!0);let Ae=this.sourceCaches[R]=new Lt(R,ae,this.dispatcher);Ae.style=this,Ae.setEventedParent(this,()=>({isSourceLoaded:Ae.loaded(),source:Ae.serialize(),sourceId:R})),Ae.onAdd(this.map),this._changed=!0}removeSource(R){if(this._checkLoaded(),this.sourceCaches[R]===void 0)throw new Error("There is no source with this ID");for(let we in this._layers)if(this._layers[we].source===R)return this.fire(new t.j(new Error(`Source "${R}" cannot be removed while layer "${we}" is using it.`)));let ae=this.sourceCaches[R];delete this.sourceCaches[R],delete this._updatedSources[R],ae.fire(new t.k("data",{sourceDataType:"metadata",dataType:"source",sourceId:R})),ae.setEventedParent(null),ae.onRemove(this.map),this._changed=!0}setGeoJSONSourceData(R,ae){if(this._checkLoaded(),this.sourceCaches[R]===void 0)throw new Error(`There is no source with this ID=${R}`);let we=this.sourceCaches[R].getSource();if(we.type!=="geojson")throw new Error(`geojsonSource.type is ${we.type}, which is !== 'geojson`);we.setData(ae),this._changed=!0}getSource(R){return this.sourceCaches[R]&&this.sourceCaches[R].getSource()}addLayer(R,ae,we={}){this._checkLoaded();let Ae=R.id;if(this.getLayer(Ae))return void this.fire(new t.j(new Error(`Layer "${Ae}" already exists on this map.`)));let Be;if(R.type==="custom"){if(zr(this,t.aD(R)))return;Be=t.aA(R)}else{if("source"in R&&typeof R.source=="object"&&(this.addSource(Ae,R.source),R=t.aB(R),R=t.e(R,{source:Ae})),this._validate(t.u.layer,`layers.${Ae}`,R,{arrayIndex:-1},we))return;Be=t.aA(R),this._validateLayer(Be),Be.setEventedParent(this,{layer:{id:Ae}})}let pt=ae?this._order.indexOf(ae):this._order.length;if(ae&&pt===-1)this.fire(new t.j(new Error(`Cannot add layer "${Ae}" before non-existing layer "${ae}".`)));else{if(this._order.splice(pt,0,Ae),this._layerOrderChanged=!0,this._layers[Ae]=Be,this._removedLayers[Ae]&&Be.source&&Be.type!=="custom"){let At=this._removedLayers[Ae];delete this._removedLayers[Ae],At.type!==Be.type?this._updatedSources[Be.source]="clear":(this._updatedSources[Be.source]="reload",this.sourceCaches[Be.source].pause())}this._updateLayer(Be),Be.onAdd&&Be.onAdd(this.map)}}moveLayer(R,ae){if(this._checkLoaded(),this._changed=!0,!this._layers[R])return void this.fire(new t.j(new Error(`The layer '${R}' does not exist in the map's style and cannot be moved.`)));if(R===ae)return;let we=this._order.indexOf(R);this._order.splice(we,1);let Ae=ae?this._order.indexOf(ae):this._order.length;ae&&Ae===-1?this.fire(new t.j(new Error(`Cannot move layer "${R}" before non-existing layer "${ae}".`))):(this._order.splice(Ae,0,R),this._layerOrderChanged=!0)}removeLayer(R){this._checkLoaded();let ae=this._layers[R];if(!ae)return void this.fire(new t.j(new Error(`Cannot remove non-existing layer "${R}".`)));ae.setEventedParent(null);let we=this._order.indexOf(R);this._order.splice(we,1),this._layerOrderChanged=!0,this._changed=!0,this._removedLayers[R]=ae,delete this._layers[R],this._serializedLayers&&delete this._serializedLayers[R],delete this._updatedLayers[R],delete this._updatedPaintProps[R],ae.onRemove&&ae.onRemove(this.map)}getLayer(R){return this._layers[R]}getLayersOrder(){return[...this._order]}hasLayer(R){return R in this._layers}setLayerZoomRange(R,ae,we){this._checkLoaded();let Ae=this.getLayer(R);Ae?Ae.minzoom===ae&&Ae.maxzoom===we||(ae!=null&&(Ae.minzoom=ae),we!=null&&(Ae.maxzoom=we),this._updateLayer(Ae)):this.fire(new t.j(new Error(`Cannot set the zoom range of non-existing layer "${R}".`)))}setFilter(R,ae,we={}){this._checkLoaded();let Ae=this.getLayer(R);if(Ae){if(!t.aE(Ae.filter,ae))return ae==null?(Ae.filter=void 0,void this._updateLayer(Ae)):void(this._validate(t.u.filter,`layers.${Ae.id}.filter`,ae,null,we)||(Ae.filter=t.aB(ae),this._updateLayer(Ae)))}else this.fire(new t.j(new Error(`Cannot filter non-existing layer "${R}".`)))}getFilter(R){return t.aB(this.getLayer(R).filter)}setLayoutProperty(R,ae,we,Ae={}){this._checkLoaded();let Be=this.getLayer(R);Be?t.aE(Be.getLayoutProperty(ae),we)||(Be.setLayoutProperty(ae,we,Ae),this._updateLayer(Be)):this.fire(new t.j(new Error(`Cannot style non-existing layer "${R}".`)))}getLayoutProperty(R,ae){let we=this.getLayer(R);if(we)return we.getLayoutProperty(ae);this.fire(new t.j(new Error(`Cannot get style of non-existing layer "${R}".`)))}setPaintProperty(R,ae,we,Ae={}){this._checkLoaded();let Be=this.getLayer(R);Be?t.aE(Be.getPaintProperty(ae),we)||(Be.setPaintProperty(ae,we,Ae)&&this._updateLayer(Be),this._changed=!0,this._updatedPaintProps[R]=!0,this._serializedLayers=null):this.fire(new t.j(new Error(`Cannot style non-existing layer "${R}".`)))}getPaintProperty(R,ae){return this.getLayer(R).getPaintProperty(ae)}setFeatureState(R,ae){this._checkLoaded();let we=R.source,Ae=R.sourceLayer,Be=this.sourceCaches[we];if(Be===void 0)return void this.fire(new t.j(new Error(`The source '${we}' does not exist in the map's style.`)));let pt=Be.getSource().type;pt==="geojson"&&Ae?this.fire(new t.j(new Error("GeoJSON sources cannot have a sourceLayer parameter."))):pt!=="vector"||Ae?(R.id===void 0&&this.fire(new t.j(new Error("The feature id parameter must be provided."))),Be.setFeatureState(Ae,R.id,ae)):this.fire(new t.j(new Error("The sourceLayer parameter must be provided for vector source types.")))}removeFeatureState(R,ae){this._checkLoaded();let we=R.source,Ae=this.sourceCaches[we];if(Ae===void 0)return void this.fire(new t.j(new Error(`The source '${we}' does not exist in the map's style.`)));let Be=Ae.getSource().type,pt=Be==="vector"?R.sourceLayer:void 0;Be!=="vector"||pt?ae&&typeof R.id!="string"&&typeof R.id!="number"?this.fire(new t.j(new Error("A feature id is required to remove its specific state property."))):Ae.removeFeatureState(pt,R.id,ae):this.fire(new t.j(new Error("The sourceLayer parameter must be provided for vector source types.")))}getFeatureState(R){this._checkLoaded();let ae=R.source,we=R.sourceLayer,Ae=this.sourceCaches[ae];if(Ae!==void 0)return Ae.getSource().type!=="vector"||we?(R.id===void 0&&this.fire(new t.j(new Error("The feature id parameter must be provided."))),Ae.getFeatureState(we,R.id)):void this.fire(new t.j(new Error("The sourceLayer parameter must be provided for vector source types.")));this.fire(new t.j(new Error(`The source '${ae}' does not exist in the map's style.`)))}getTransition(){return t.e({duration:300,delay:0},this.stylesheet&&this.stylesheet.transition)}serialize(){if(!this._loaded)return;let R=t.aF(this.sourceCaches,Be=>Be.serialize()),ae=this._serializeByIds(this._order,!0),we=this.map.getTerrain()||void 0,Ae=this.stylesheet;return t.aG({version:Ae.version,name:Ae.name,metadata:Ae.metadata,light:Ae.light,sky:Ae.sky,center:Ae.center,zoom:Ae.zoom,bearing:Ae.bearing,pitch:Ae.pitch,sprite:Ae.sprite,glyphs:Ae.glyphs,transition:Ae.transition,sources:R,layers:ae,terrain:we},Be=>Be!==void 0)}_updateLayer(R){this._updatedLayers[R.id]=!0,R.source&&!this._updatedSources[R.source]&&this.sourceCaches[R.source].getSource().type!=="raster"&&(this._updatedSources[R.source]="reload",this.sourceCaches[R.source].pause()),this._serializedLayers=null,this._changed=!0}_flattenAndSortRenderedFeatures(R){let ae=pt=>this._layers[pt].type==="fill-extrusion",we={},Ae=[];for(let pt=this._order.length-1;pt>=0;pt--){let At=this._order[pt];if(ae(At)){we[At]=pt;for(let Nt of R){let $t=Nt[At];if($t)for(let wr of $t)Ae.push(wr)}}}Ae.sort((pt,At)=>At.intersectionZ-pt.intersectionZ);let Be=[];for(let pt=this._order.length-1;pt>=0;pt--){let At=this._order[pt];if(ae(At))for(let Nt=Ae.length-1;Nt>=0;Nt--){let $t=Ae[Nt].feature;if(we[$t.layer.id]{let Ur=dt.featureSortOrder;if(Ur){let Qr=Ur.indexOf(mr.featureIndex);return Ur.indexOf(Er.featureIndex)-Qr}return Er.featureIndex-mr.featureIndex});for(let mr of ur)zt.push(mr)}}for(let dt in He)He[dt].forEach(Ct=>{let Tt=Ct.feature,zt=$t[At[dt].source].getFeatureState(Tt.layer["source-layer"],Tt.id);Tt.source=Tt.layer.source,Tt.layer["source-layer"]&&(Tt.sourceLayer=Tt.layer["source-layer"]),Tt.state=zt});return He}(this._layers,pt,this.sourceCaches,R,ae,this.placement.collisionIndex,this.placement.retainedQueryData)),this._flattenAndSortRenderedFeatures(Be)}querySourceFeatures(R,ae){ae&&ae.filter&&this._validate(t.u.filter,"querySourceFeatures.filter",ae.filter,null,ae);let we=this.sourceCaches[R];return we?function(Ae,Be){let pt=Ae.getRenderableIds().map($t=>Ae.getTileByID($t)),At=[],Nt={};for(let $t=0;$tKr.getTileByID(sa)).sort((sa,He)=>He.tileID.overscaledZ-sa.tileID.overscaledZ||(sa.tileID.isLessThan(He.tileID)?-1:1))}let Tr=this.crossTileSymbolIndex.addLayer(wr,Nt[wr.source],R.center.lng);pt=pt||Tr}if(this.crossTileSymbolIndex.pruneUnusedLayers(this._order),((Be=Be||this._layerOrderChanged||we===0)||!this.pauseablePlacement||this.pauseablePlacement.isDone()&&!this.placement.stillRecent(n.now(),R.zoom))&&(this.pauseablePlacement=new rn(R,this.map.terrain,this._order,Be,ae,we,Ae,this.placement),this._layerOrderChanged=!1),this.pauseablePlacement.isDone()?this.placement.setStale():(this.pauseablePlacement.continuePlacement(this._order,this._layers,Nt),this.pauseablePlacement.isDone()&&(this.placement=this.pauseablePlacement.commit(n.now()),At=!0),pt&&this.pauseablePlacement.placement.setStale()),At||pt)for(let $t of this._order){let wr=this._layers[$t];wr.type==="symbol"&&this.placement.updateLayerOpacities(wr,Nt[wr.source])}return!this.pauseablePlacement.isDone()||this.placement.hasTransitions(n.now())}_releaseSymbolFadeTiles(){for(let R in this.sourceCaches)this.sourceCaches[R].releaseSymbolFadeTiles()}getImages(R,ae){return t._(this,void 0,void 0,function*(){let we=yield this.imageManager.getImages(ae.icons);this._updateTilesForChangedImages();let Ae=this.sourceCaches[ae.source];return Ae&&Ae.setDependencies(ae.tileID.key,ae.type,ae.icons),we})}getGlyphs(R,ae){return t._(this,void 0,void 0,function*(){let we=yield this.glyphManager.getGlyphs(ae.stacks),Ae=this.sourceCaches[ae.source];return Ae&&Ae.setDependencies(ae.tileID.key,ae.type,[""]),we})}getGlyphsUrl(){return this.stylesheet.glyphs||null}setGlyphs(R,ae={}){this._checkLoaded(),R&&this._validate(t.u.glyphs,"glyphs",R,null,ae)||(this._glyphsDidChange=!0,this.stylesheet.glyphs=R,this.glyphManager.entries={},this.glyphManager.setURL(R))}addSprite(R,ae,we={},Ae){this._checkLoaded();let Be=[{id:R,url:ae}],pt=[...b(this.stylesheet.sprite),...Be];this._validate(t.u.sprite,"sprite",pt,null,we)||(this.stylesheet.sprite=pt,this._loadSprite(Be,!0,Ae))}removeSprite(R){this._checkLoaded();let ae=b(this.stylesheet.sprite);if(ae.find(we=>we.id===R)){if(this._spritesImagesIds[R])for(let we of this._spritesImagesIds[R])this.imageManager.removeImage(we),this._changedImages[we]=!0;ae.splice(ae.findIndex(we=>we.id===R),1),this.stylesheet.sprite=ae.length>0?ae:void 0,delete this._spritesImagesIds[R],this._availableImages=this.imageManager.listImages(),this._changed=!0,this.dispatcher.broadcast("SI",this._availableImages),this.fire(new t.k("data",{dataType:"style"}))}else this.fire(new t.j(new Error(`Sprite "${R}" doesn't exists on this map.`)))}getSprite(){return b(this.stylesheet.sprite)}setSprite(R,ae={},we){this._checkLoaded(),R&&this._validate(t.u.sprite,"sprite",R,null,ae)||(this.stylesheet.sprite=R,R?this._loadSprite(R,!0,we):(this._unloadSprite(),we&&we(null)))}}var ra=t.Y([{name:"a_pos",type:"Int16",components:2}]);let Gr={prelude:wt(`#ifdef GL_ES +precision mediump float; +#else +#if !defined(lowp) +#define lowp +#endif +#if !defined(mediump) +#define mediump +#endif +#if !defined(highp) +#define highp +#endif +#endif +`,`#ifdef GL_ES +precision highp float; +#else +#if !defined(lowp) +#define lowp +#endif +#if !defined(mediump) +#define mediump +#endif +#if !defined(highp) +#define highp +#endif +#endif +vec2 unpack_float(const float packedValue) {int packedIntValue=int(packedValue);int v0=packedIntValue/256;return vec2(v0,packedIntValue-v0*256);}vec2 unpack_opacity(const float packedOpacity) {int intOpacity=int(packedOpacity)/2;return vec2(float(intOpacity)/127.0,mod(packedOpacity,2.0));}vec4 decode_color(const vec2 encodedColor) {return vec4(unpack_float(encodedColor[0])/255.0,unpack_float(encodedColor[1])/255.0 +);}float unpack_mix_vec2(const vec2 packedValue,const float t) {return mix(packedValue[0],packedValue[1],t);}vec4 unpack_mix_color(const vec4 packedColors,const float t) {vec4 minColor=decode_color(vec2(packedColors[0],packedColors[1]));vec4 maxColor=decode_color(vec2(packedColors[2],packedColors[3]));return mix(minColor,maxColor,t);}vec2 get_pattern_pos(const vec2 pixel_coord_upper,const vec2 pixel_coord_lower,const vec2 pattern_size,const float tile_units_to_pixels,const vec2 pos) {vec2 offset=mod(mod(mod(pixel_coord_upper,pattern_size)*256.0,pattern_size)*256.0+pixel_coord_lower,pattern_size);return (tile_units_to_pixels*pos+offset)/pattern_size;} +#ifdef TERRAIN3D +uniform sampler2D u_terrain;uniform float u_terrain_dim;uniform mat4 u_terrain_matrix;uniform vec4 u_terrain_unpack;uniform float u_terrain_exaggeration;uniform highp sampler2D u_depth; +#endif +const highp vec4 bitSh=vec4(256.*256.*256.,256.*256.,256.,1.);const highp vec4 bitShifts=vec4(1.)/bitSh;highp float unpack(highp vec4 color) {return dot(color,bitShifts);}highp float depthOpacity(vec3 frag) { +#ifdef TERRAIN3D +highp float d=unpack(texture2D(u_depth,frag.xy*0.5+0.5))+0.0001-frag.z;return 1.0-max(0.0,min(1.0,-d*500.0)); +#else +return 1.0; +#endif +}float calculate_visibility(vec4 pos) { +#ifdef TERRAIN3D +vec3 frag=pos.xyz/pos.w;highp float d=depthOpacity(frag);if (d > 0.95) return 1.0;return (d+depthOpacity(frag+vec3(0.0,0.01,0.0)))/2.0; +#else +return 1.0; +#endif +}float ele(vec2 pos) { +#ifdef TERRAIN3D +vec4 rgb=(texture2D(u_terrain,pos)*255.0)*u_terrain_unpack;return rgb.r+rgb.g+rgb.b-u_terrain_unpack.a; +#else +return 0.0; +#endif +}float get_elevation(vec2 pos) { +#ifdef TERRAIN3D +vec2 coord=(u_terrain_matrix*vec4(pos,0.0,1.0)).xy*u_terrain_dim+1.0;vec2 f=fract(coord);vec2 c=(floor(coord)+0.5)/(u_terrain_dim+2.0);float d=1.0/(u_terrain_dim+2.0);float tl=ele(c);float tr=ele(c+vec2(d,0.0));float bl=ele(c+vec2(0.0,d));float br=ele(c+vec2(d,d));float elevation=mix(mix(tl,tr,f.x),mix(bl,br,f.x),f.y);return elevation*u_terrain_exaggeration; +#else +return 0.0; +#endif +}`),background:wt(`uniform vec4 u_color;uniform float u_opacity;void main() {gl_FragColor=u_color*u_opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,"attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}"),backgroundPattern:wt(`uniform vec2 u_pattern_tl_a;uniform vec2 u_pattern_br_a;uniform vec2 u_pattern_tl_b;uniform vec2 u_pattern_br_b;uniform vec2 u_texsize;uniform float u_mix;uniform float u_opacity;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(u_pattern_tl_a/u_texsize,u_pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(u_pattern_tl_b/u_texsize,u_pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_mix)*u_opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,"uniform mat4 u_matrix;uniform vec2 u_pattern_size_a;uniform vec2 u_pattern_size_b;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_scale_a;uniform float u_scale_b;uniform float u_tile_units_to_pixels;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_a*u_pattern_size_a,u_tile_units_to_pixels,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,u_scale_b*u_pattern_size_b,u_tile_units_to_pixels,a_pos);}"),circle:wt(`varying vec3 v_data;varying float v_visibility; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define mediump float radius +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define highp vec4 stroke_color +#pragma mapbox: define mediump float stroke_width +#pragma mapbox: define lowp float stroke_opacity +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize mediump float radius +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize highp vec4 stroke_color +#pragma mapbox: initialize mediump float stroke_width +#pragma mapbox: initialize lowp float stroke_opacity +vec2 extrude=v_data.xy;float extrude_length=length(extrude);float antialiased_blur=v_data.z;float opacity_t=smoothstep(0.0,antialiased_blur,extrude_length-1.0);float color_t=stroke_width < 0.01 ? 0.0 : smoothstep(antialiased_blur,0.0,extrude_length-radius/(radius+stroke_width));gl_FragColor=v_visibility*opacity_t*mix(color*opacity,stroke_color*stroke_opacity,color_t); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`uniform mat4 u_matrix;uniform bool u_scale_with_map;uniform bool u_pitch_with_map;uniform vec2 u_extrude_scale;uniform lowp float u_device_pixel_ratio;uniform highp float u_camera_to_center_distance;attribute vec2 a_pos;varying vec3 v_data;varying float v_visibility; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define mediump float radius +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define highp vec4 stroke_color +#pragma mapbox: define mediump float stroke_width +#pragma mapbox: define lowp float stroke_opacity +void main(void) { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize mediump float radius +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize highp vec4 stroke_color +#pragma mapbox: initialize mediump float stroke_width +#pragma mapbox: initialize lowp float stroke_opacity +vec2 extrude=vec2(mod(a_pos,2.0)*2.0-1.0);vec2 circle_center=floor(a_pos*0.5);float ele=get_elevation(circle_center);v_visibility=calculate_visibility(u_matrix*vec4(circle_center,ele,1.0));if (u_pitch_with_map) {vec2 corner_position=circle_center;if (u_scale_with_map) {corner_position+=extrude*(radius+stroke_width)*u_extrude_scale;} else {vec4 projected_center=u_matrix*vec4(circle_center,0,1);corner_position+=extrude*(radius+stroke_width)*u_extrude_scale*(projected_center.w/u_camera_to_center_distance);}gl_Position=u_matrix*vec4(corner_position,ele,1);} else {gl_Position=u_matrix*vec4(circle_center,ele,1);if (u_scale_with_map) {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*u_camera_to_center_distance;} else {gl_Position.xy+=extrude*(radius+stroke_width)*u_extrude_scale*gl_Position.w;}}float antialiasblur=-max(1.0/u_device_pixel_ratio/(radius+stroke_width),blur);v_data=vec3(extrude.x,extrude.y,antialiasblur);}`),clippingMask:wt("void main() {gl_FragColor=vec4(1.0);}","attribute vec2 a_pos;uniform mat4 u_matrix;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);}"),heatmap:wt(`uniform highp float u_intensity;varying vec2 v_extrude; +#pragma mapbox: define highp float weight +#define GAUSS_COEF 0.3989422804014327 +void main() { +#pragma mapbox: initialize highp float weight +float d=-0.5*3.0*3.0*dot(v_extrude,v_extrude);float val=weight*u_intensity*GAUSS_COEF*exp(d);gl_FragColor=vec4(val,1.0,1.0,1.0); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`uniform mat4 u_matrix;uniform float u_extrude_scale;uniform float u_opacity;uniform float u_intensity;attribute vec2 a_pos;varying vec2 v_extrude; +#pragma mapbox: define highp float weight +#pragma mapbox: define mediump float radius +const highp float ZERO=1.0/255.0/16.0; +#define GAUSS_COEF 0.3989422804014327 +void main(void) { +#pragma mapbox: initialize highp float weight +#pragma mapbox: initialize mediump float radius +vec2 unscaled_extrude=vec2(mod(a_pos,2.0)*2.0-1.0);float S=sqrt(-2.0*log(ZERO/weight/u_intensity/GAUSS_COEF))/3.0;v_extrude=S*unscaled_extrude;vec2 extrude=v_extrude*radius*u_extrude_scale;vec4 pos=vec4(floor(a_pos*0.5)+extrude,get_elevation(floor(a_pos*0.5)),1);gl_Position=u_matrix*pos;}`),heatmapTexture:wt(`uniform sampler2D u_image;uniform sampler2D u_color_ramp;uniform float u_opacity;varying vec2 v_pos;void main() {float t=texture2D(u_image,v_pos).r;vec4 color=texture2D(u_color_ramp,vec2(t,0.5));gl_FragColor=color*u_opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(0.0); +#endif +}`,"uniform mat4 u_matrix;uniform vec2 u_world;attribute vec2 a_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos*u_world,0,1);v_pos.x=a_pos.x;v_pos.y=1.0-a_pos.y;}"),collisionBox:wt("varying float v_placed;varying float v_notUsed;void main() {float alpha=0.5;gl_FragColor=vec4(1.0,0.0,0.0,1.0)*alpha;if (v_placed > 0.5) {gl_FragColor=vec4(0.0,0.0,1.0,0.5)*alpha;}if (v_notUsed > 0.5) {gl_FragColor*=.1;}}","attribute vec2 a_anchor_pos;attribute vec2 a_placed;attribute vec2 a_box_real;uniform mat4 u_matrix;uniform vec2 u_pixel_extrude_scale;varying float v_placed;varying float v_notUsed;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);}void main() {gl_Position=projectTileWithElevation(a_anchor_pos,get_elevation(a_anchor_pos));gl_Position.xy=((a_box_real+0.5)*u_pixel_extrude_scale*2.0-1.0)*vec2(1.0,-1.0)*gl_Position.w;if (gl_Position.z/gl_Position.w < 1.1) {gl_Position.z=0.5;}v_placed=a_placed.x;v_notUsed=a_placed.y;}"),collisionCircle:wt("varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;void main() {float alpha=0.5*min(v_perspective_ratio,1.0);float stroke_radius=0.9*max(v_perspective_ratio,1.0);float distance_to_center=length(v_extrude);float distance_to_edge=abs(distance_to_center-v_radius);float opacity_t=smoothstep(-stroke_radius,0.0,-distance_to_edge);vec4 color=mix(vec4(0.0,0.0,1.0,0.5),vec4(1.0,0.0,0.0,1.0),v_collision);gl_FragColor=color*alpha*opacity_t;}","attribute vec2 a_pos;attribute float a_radius;attribute vec2 a_flags;uniform mat4 u_matrix;uniform mat4 u_inv_matrix;uniform vec2 u_viewport_size;uniform float u_camera_to_center_distance;varying float v_radius;varying vec2 v_extrude;varying float v_perspective_ratio;varying float v_collision;vec3 toTilePosition(vec2 screenPos) {vec4 rayStart=u_inv_matrix*vec4(screenPos,-1.0,1.0);vec4 rayEnd =u_inv_matrix*vec4(screenPos, 1.0,1.0);rayStart.xyz/=rayStart.w;rayEnd.xyz /=rayEnd.w;highp float t=(0.0-rayStart.z)/(rayEnd.z-rayStart.z);return mix(rayStart.xyz,rayEnd.xyz,t);}void main() {vec2 quadCenterPos=a_pos;float radius=a_radius;float collision=a_flags.x;float vertexIdx=a_flags.y;vec2 quadVertexOffset=vec2(mix(-1.0,1.0,float(vertexIdx >=2.0)),mix(-1.0,1.0,float(vertexIdx >=1.0 && vertexIdx <=2.0)));vec2 quadVertexExtent=quadVertexOffset*radius;vec3 tilePos=toTilePosition(quadCenterPos);vec4 clipPos=u_matrix*vec4(tilePos,1.0);highp float camera_to_anchor_distance=clipPos.w;highp float collision_perspective_ratio=clamp(0.5+0.5*(u_camera_to_center_distance/camera_to_anchor_distance),0.0,4.0);float padding_factor=1.2;v_radius=radius;v_extrude=quadVertexExtent*padding_factor;v_perspective_ratio=collision_perspective_ratio;v_collision=collision;gl_Position=vec4(clipPos.xyz/clipPos.w,1.0)+vec4(quadVertexExtent*padding_factor/u_viewport_size*2.0,0.0,0.0);}"),debug:wt("uniform highp vec4 u_color;uniform sampler2D u_overlay;varying vec2 v_uv;void main() {vec4 overlay_color=texture2D(u_overlay,v_uv);gl_FragColor=mix(u_color,overlay_color,overlay_color.a);}","attribute vec2 a_pos;varying vec2 v_uv;uniform mat4 u_matrix;uniform float u_overlay_scale;void main() {v_uv=a_pos/8192.0;gl_Position=u_matrix*vec4(a_pos*u_overlay_scale,get_elevation(a_pos),1);}"),fill:wt(`#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float opacity +gl_FragColor=color*opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`attribute vec2 a_pos;uniform mat4 u_matrix; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float opacity +gl_Position=u_matrix*vec4(a_pos,0,1);}`),fillOutline:wt(`varying vec2 v_pos; +#pragma mapbox: define highp vec4 outline_color +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize highp vec4 outline_color +#pragma mapbox: initialize lowp float opacity +float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=outline_color*(alpha*opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`attribute vec2 a_pos;uniform mat4 u_matrix;uniform vec2 u_world;varying vec2 v_pos; +#pragma mapbox: define highp vec4 outline_color +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize highp vec4 outline_color +#pragma mapbox: initialize lowp float opacity +gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}`),fillOutlinePattern:wt(`uniform vec2 u_texsize;uniform sampler2D u_image;uniform float u_fade;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos; +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +void main() { +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);float dist=length(v_pos-gl_FragCoord.xy);float alpha=1.0-smoothstep(0.0,1.0,dist);gl_FragColor=mix(color1,color2,u_fade)*alpha*opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`uniform mat4 u_matrix;uniform vec2 u_world;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec2 v_pos; +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;gl_Position=u_matrix*vec4(a_pos,0,1);vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,a_pos);v_pos=(gl_Position.xy/gl_Position.w+1.0)/2.0*u_world;}`),fillPattern:wt(`#ifdef GL_ES +precision highp float; +#endif +uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b; +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +void main() { +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);gl_FragColor=mix(color1,color2,u_fade)*opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform vec3 u_scale;attribute vec2 a_pos;varying vec2 v_pos_a;varying vec2 v_pos_b; +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;gl_Position=u_matrix*vec4(a_pos,0,1);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileZoomRatio,a_pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileZoomRatio,a_pos);}`),fillExtrusion:wt(`varying vec4 v_color;void main() {gl_FragColor=v_color; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`uniform mat4 u_matrix;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;uniform float u_vertical_gradient;uniform lowp float u_opacity;attribute vec2 a_pos;attribute vec4 a_normal_ed; +#ifdef TERRAIN3D +attribute vec2 a_centroid; +#endif +varying vec4 v_color; +#pragma mapbox: define highp float base +#pragma mapbox: define highp float height +#pragma mapbox: define highp vec4 color +void main() { +#pragma mapbox: initialize highp float base +#pragma mapbox: initialize highp float height +#pragma mapbox: initialize highp vec4 color +vec3 normal=a_normal_ed.xyz; +#ifdef TERRAIN3D +float height_terrain3d_offset=get_elevation(a_centroid);float base_terrain3d_offset=height_terrain3d_offset-(base > 0.0 ? 0.0 : 10.0); +#else +float height_terrain3d_offset=0.0;float base_terrain3d_offset=0.0; +#endif +base=max(0.0,base)+base_terrain3d_offset;height=max(0.0,height)+height_terrain3d_offset;float t=mod(normal.x,2.0);gl_Position=u_matrix*vec4(a_pos,t > 0.0 ? height : base,1);float colorvalue=color.r*0.2126+color.g*0.7152+color.b*0.0722;v_color=vec4(0.0,0.0,0.0,1.0);vec4 ambientlight=vec4(0.03,0.03,0.03,1.0);color+=ambientlight;float directional=clamp(dot(normal/16384.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((1.0-colorvalue+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_color.r+=clamp(color.r*directional*u_lightcolor.r,mix(0.0,0.3,1.0-u_lightcolor.r),1.0);v_color.g+=clamp(color.g*directional*u_lightcolor.g,mix(0.0,0.3,1.0-u_lightcolor.g),1.0);v_color.b+=clamp(color.b*directional*u_lightcolor.b,mix(0.0,0.3,1.0-u_lightcolor.b),1.0);v_color*=u_opacity;}`),fillExtrusionPattern:wt(`uniform vec2 u_texsize;uniform float u_fade;uniform sampler2D u_image;varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting; +#pragma mapbox: define lowp float base +#pragma mapbox: define lowp float height +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float base +#pragma mapbox: initialize lowp float height +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;vec2 imagecoord=mod(v_pos_a,1.0);vec2 pos=mix(pattern_tl_a/u_texsize,pattern_br_a/u_texsize,imagecoord);vec4 color1=texture2D(u_image,pos);vec2 imagecoord_b=mod(v_pos_b,1.0);vec2 pos2=mix(pattern_tl_b/u_texsize,pattern_br_b/u_texsize,imagecoord_b);vec4 color2=texture2D(u_image,pos2);vec4 mixedColor=mix(color1,color2,u_fade);gl_FragColor=mixedColor*v_lighting; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`uniform mat4 u_matrix;uniform vec2 u_pixel_coord_upper;uniform vec2 u_pixel_coord_lower;uniform float u_height_factor;uniform vec3 u_scale;uniform float u_vertical_gradient;uniform lowp float u_opacity;uniform vec3 u_lightcolor;uniform lowp vec3 u_lightpos;uniform lowp float u_lightintensity;attribute vec2 a_pos;attribute vec4 a_normal_ed; +#ifdef TERRAIN3D +attribute vec2 a_centroid; +#endif +varying vec2 v_pos_a;varying vec2 v_pos_b;varying vec4 v_lighting; +#pragma mapbox: define lowp float base +#pragma mapbox: define lowp float height +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float base +#pragma mapbox: initialize lowp float height +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec3 normal=a_normal_ed.xyz;float edgedistance=a_normal_ed.w;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to; +#ifdef TERRAIN3D +float height_terrain3d_offset=get_elevation(a_centroid);float base_terrain3d_offset=height_terrain3d_offset-(base > 0.0 ? 0.0 : 10.0); +#else +float height_terrain3d_offset=0.0;float base_terrain3d_offset=0.0; +#endif +base=max(0.0,base)+base_terrain3d_offset;height=max(0.0,height)+height_terrain3d_offset;float t=mod(normal.x,2.0);float z=t > 0.0 ? height : base;gl_Position=u_matrix*vec4(a_pos,z,1);vec2 pos=normal.x==1.0 && normal.y==0.0 && normal.z==16384.0 +? a_pos +: vec2(edgedistance,z*u_height_factor);v_pos_a=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,fromScale*display_size_a,tileRatio,pos);v_pos_b=get_pattern_pos(u_pixel_coord_upper,u_pixel_coord_lower,toScale*display_size_b,tileRatio,pos);v_lighting=vec4(0.0,0.0,0.0,1.0);float directional=clamp(dot(normal/16383.0,u_lightpos),0.0,1.0);directional=mix((1.0-u_lightintensity),max((0.5+u_lightintensity),1.0),directional);if (normal.y !=0.0) {directional*=((1.0-u_vertical_gradient)+(u_vertical_gradient*clamp((t+base)*pow(height/150.0,0.5),mix(0.7,0.98,1.0-u_lightintensity),1.0)));}v_lighting.rgb+=clamp(directional*u_lightcolor,mix(vec3(0.0),vec3(0.3),1.0-u_lightcolor),vec3(1.0));v_lighting*=u_opacity;}`),hillshadePrepare:wt(`#ifdef GL_ES +precision highp float; +#endif +uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_dimension;uniform float u_zoom;uniform vec4 u_unpack;float getElevation(vec2 coord,float bias) {vec4 data=texture2D(u_image,coord)*255.0;data.a=-1.0;return dot(data,u_unpack)/4.0;}void main() {vec2 epsilon=1.0/u_dimension;float a=getElevation(v_pos+vec2(-epsilon.x,-epsilon.y),0.0);float b=getElevation(v_pos+vec2(0,-epsilon.y),0.0);float c=getElevation(v_pos+vec2(epsilon.x,-epsilon.y),0.0);float d=getElevation(v_pos+vec2(-epsilon.x,0),0.0);float e=getElevation(v_pos,0.0);float f=getElevation(v_pos+vec2(epsilon.x,0),0.0);float g=getElevation(v_pos+vec2(-epsilon.x,epsilon.y),0.0);float h=getElevation(v_pos+vec2(0,epsilon.y),0.0);float i=getElevation(v_pos+vec2(epsilon.x,epsilon.y),0.0);float exaggerationFactor=u_zoom < 2.0 ? 0.4 : u_zoom < 4.5 ? 0.35 : 0.3;float exaggeration=u_zoom < 15.0 ? (u_zoom-15.0)*exaggerationFactor : 0.0;vec2 deriv=vec2((c+f+f+i)-(a+d+d+g),(g+h+h+i)-(a+b+b+c))/pow(2.0,exaggeration+(19.2562-u_zoom));gl_FragColor=clamp(vec4(deriv.x/2.0+0.5,deriv.y/2.0+0.5,1.0,1.0),0.0,1.0); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,"uniform mat4 u_matrix;uniform vec2 u_dimension;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);highp vec2 epsilon=1.0/u_dimension;float scale=(u_dimension.x-2.0)/u_dimension.x;v_pos=(a_texture_pos/8192.0)*scale+epsilon;}"),hillshade:wt(`uniform sampler2D u_image;varying vec2 v_pos;uniform vec2 u_latrange;uniform vec2 u_light;uniform vec4 u_shadow;uniform vec4 u_highlight;uniform vec4 u_accent; +#define PI 3.141592653589793 +void main() {vec4 pixel=texture2D(u_image,v_pos);vec2 deriv=((pixel.rg*2.0)-1.0);float scaleFactor=cos(radians((u_latrange[0]-u_latrange[1])*(1.0-v_pos.y)+u_latrange[1]));float slope=atan(1.25*length(deriv)/scaleFactor);float aspect=deriv.x !=0.0 ? atan(deriv.y,-deriv.x) : PI/2.0*(deriv.y > 0.0 ? 1.0 :-1.0);float intensity=u_light.x;float azimuth=u_light.y+PI;float base=1.875-intensity*1.75;float maxValue=0.5*PI;float scaledSlope=intensity !=0.5 ? ((pow(base,slope)-1.0)/(pow(base,maxValue)-1.0))*maxValue : slope;float accent=cos(scaledSlope);vec4 accent_color=(1.0-accent)*u_accent*clamp(intensity*2.0,0.0,1.0);float shade=abs(mod((aspect+azimuth)/PI+0.5,2.0)-1.0);vec4 shade_color=mix(u_shadow,u_highlight,shade)*sin(scaledSlope)*clamp(intensity*2.0,0.0,1.0);gl_FragColor=accent_color*(1.0-shade_color.a)+shade_color; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,"uniform mat4 u_matrix;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos=a_texture_pos/8192.0;}"),line:wt(`uniform lowp float u_device_pixel_ratio;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);gl_FragColor=color*(alpha*opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,` +#define scale 0.015873016 +attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform vec2 u_units_to_pixels;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp float v_linesofar; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float width +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float width +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;v_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*2.0;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude; +#ifdef TERRAIN3D +v_gamma_scale=1.0; +#else +float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective; +#endif +v_width2=vec2(outset,inset);}`),lineGradient:wt(`uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;varying vec2 v_width2;varying vec2 v_normal;varying float v_gamma_scale;varying highp vec2 v_uv; +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);vec4 color=texture2D(u_image,v_uv);gl_FragColor=color*(alpha*opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,` +#define scale 0.015873016 +attribute vec2 a_pos_normal;attribute vec4 a_data;attribute float a_uv_x;attribute float a_split_index;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_units_to_pixels;uniform float u_image_height;varying vec2 v_normal;varying vec2 v_width2;varying float v_gamma_scale;varying highp vec2 v_uv; +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float width +void main() { +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float width +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;highp float texel_height=1.0/u_image_height;highp float half_texel_height=0.5*texel_height;v_uv=vec2(a_uv_x,a_split_index*texel_height-half_texel_height);vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude; +#ifdef TERRAIN3D +v_gamma_scale=1.0; +#else +float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective; +#endif +v_width2=vec2(outset,inset);}`),linePattern:wt(`#ifdef GL_ES +precision highp float; +#endif +uniform lowp float u_device_pixel_ratio;uniform vec2 u_texsize;uniform float u_fade;uniform mediump vec3 u_scale;uniform sampler2D u_image;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width; +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +vec2 pattern_tl_a=pattern_from.xy;vec2 pattern_br_a=pattern_from.zw;vec2 pattern_tl_b=pattern_to.xy;vec2 pattern_br_b=pattern_to.zw;float tileZoomRatio=u_scale.x;float fromScale=u_scale.y;float toScale=u_scale.z;vec2 display_size_a=(pattern_br_a-pattern_tl_a)/pixel_ratio_from;vec2 display_size_b=(pattern_br_b-pattern_tl_b)/pixel_ratio_to;vec2 pattern_size_a=vec2(display_size_a.x*fromScale/tileZoomRatio,display_size_a.y);vec2 pattern_size_b=vec2(display_size_b.x*toScale/tileZoomRatio,display_size_b.y);float aspect_a=display_size_a.y/v_width;float aspect_b=display_size_b.y/v_width;float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float x_a=mod(v_linesofar/pattern_size_a.x*aspect_a,1.0);float x_b=mod(v_linesofar/pattern_size_b.x*aspect_b,1.0);float y=0.5*v_normal.y+0.5;vec2 texel_size=1.0/u_texsize;vec2 pos_a=mix(pattern_tl_a*texel_size-texel_size,pattern_br_a*texel_size+texel_size,vec2(x_a,y));vec2 pos_b=mix(pattern_tl_b*texel_size-texel_size,pattern_br_b*texel_size+texel_size,vec2(x_b,y));vec4 color=mix(texture2D(u_image,pos_a),texture2D(u_image,pos_b),u_fade);gl_FragColor=color*alpha*opacity; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,` +#define scale 0.015873016 +#define LINE_DISTANCE_SCALE 2.0 +attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform vec2 u_units_to_pixels;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;varying vec2 v_normal;varying vec2 v_width2;varying float v_linesofar;varying float v_gamma_scale;varying float v_width; +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define mediump float width +#pragma mapbox: define lowp float floorwidth +#pragma mapbox: define lowp vec4 pattern_from +#pragma mapbox: define lowp vec4 pattern_to +#pragma mapbox: define lowp float pixel_ratio_from +#pragma mapbox: define lowp float pixel_ratio_to +void main() { +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize mediump float width +#pragma mapbox: initialize lowp float floorwidth +#pragma mapbox: initialize mediump vec4 pattern_from +#pragma mapbox: initialize mediump vec4 pattern_to +#pragma mapbox: initialize lowp float pixel_ratio_from +#pragma mapbox: initialize lowp float pixel_ratio_to +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude; +#ifdef TERRAIN3D +v_gamma_scale=1.0; +#else +float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective; +#endif +v_linesofar=a_linesofar;v_width2=vec2(outset,inset);v_width=floorwidth;}`),lineSDF:wt(`uniform lowp float u_device_pixel_ratio;uniform sampler2D u_image;uniform float u_sdfgamma;uniform float u_mix;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float width +#pragma mapbox: define lowp float floorwidth +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float width +#pragma mapbox: initialize lowp float floorwidth +float dist=length(v_normal)*v_width2.s;float blur2=(blur+1.0/u_device_pixel_ratio)*v_gamma_scale;float alpha=clamp(min(dist-(v_width2.t-blur2),v_width2.s-dist)/blur2,0.0,1.0);float sdfdist_a=texture2D(u_image,v_tex_a).a;float sdfdist_b=texture2D(u_image,v_tex_b).a;float sdfdist=mix(sdfdist_a,sdfdist_b,u_mix);alpha*=smoothstep(0.5-u_sdfgamma/floorwidth,0.5+u_sdfgamma/floorwidth,sdfdist);gl_FragColor=color*(alpha*opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,` +#define scale 0.015873016 +#define LINE_DISTANCE_SCALE 2.0 +attribute vec2 a_pos_normal;attribute vec4 a_data;uniform mat4 u_matrix;uniform mediump float u_ratio;uniform lowp float u_device_pixel_ratio;uniform vec2 u_patternscale_a;uniform float u_tex_y_a;uniform vec2 u_patternscale_b;uniform float u_tex_y_b;uniform vec2 u_units_to_pixels;varying vec2 v_normal;varying vec2 v_width2;varying vec2 v_tex_a;varying vec2 v_tex_b;varying float v_gamma_scale; +#pragma mapbox: define highp vec4 color +#pragma mapbox: define lowp float blur +#pragma mapbox: define lowp float opacity +#pragma mapbox: define mediump float gapwidth +#pragma mapbox: define lowp float offset +#pragma mapbox: define mediump float width +#pragma mapbox: define lowp float floorwidth +void main() { +#pragma mapbox: initialize highp vec4 color +#pragma mapbox: initialize lowp float blur +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize mediump float gapwidth +#pragma mapbox: initialize lowp float offset +#pragma mapbox: initialize mediump float width +#pragma mapbox: initialize lowp float floorwidth +float ANTIALIASING=1.0/u_device_pixel_ratio/2.0;vec2 a_extrude=a_data.xy-128.0;float a_direction=mod(a_data.z,4.0)-1.0;float a_linesofar=(floor(a_data.z/4.0)+a_data.w*64.0)*LINE_DISTANCE_SCALE;vec2 pos=floor(a_pos_normal*0.5);mediump vec2 normal=a_pos_normal-2.0*pos;normal.y=normal.y*2.0-1.0;v_normal=normal;gapwidth=gapwidth/2.0;float halfwidth=width/2.0;offset=-1.0*offset;float inset=gapwidth+(gapwidth > 0.0 ? ANTIALIASING : 0.0);float outset=gapwidth+halfwidth*(gapwidth > 0.0 ? 2.0 : 1.0)+(halfwidth==0.0 ? 0.0 : ANTIALIASING);mediump vec2 dist=outset*a_extrude*scale;mediump float u=0.5*a_direction;mediump float t=1.0-abs(u);mediump vec2 offset2=offset*a_extrude*scale*normal.y*mat2(t,-u,u,t);vec4 projected_extrude=u_matrix*vec4(dist/u_ratio,0.0,0.0);gl_Position=u_matrix*vec4(pos+offset2/u_ratio,0.0,1.0)+projected_extrude; +#ifdef TERRAIN3D +v_gamma_scale=1.0; +#else +float extrude_length_without_perspective=length(dist);float extrude_length_with_perspective=length(projected_extrude.xy/gl_Position.w*u_units_to_pixels);v_gamma_scale=extrude_length_without_perspective/extrude_length_with_perspective; +#endif +v_tex_a=vec2(a_linesofar*u_patternscale_a.x/floorwidth,normal.y*u_patternscale_a.y+u_tex_y_a);v_tex_b=vec2(a_linesofar*u_patternscale_b.x/floorwidth,normal.y*u_patternscale_b.y+u_tex_y_b);v_width2=vec2(outset,inset);}`),raster:wt(`uniform float u_fade_t;uniform float u_opacity;uniform sampler2D u_image0;uniform sampler2D u_image1;varying vec2 v_pos0;varying vec2 v_pos1;uniform float u_brightness_low;uniform float u_brightness_high;uniform float u_saturation_factor;uniform float u_contrast_factor;uniform vec3 u_spin_weights;void main() {vec4 color0=texture2D(u_image0,v_pos0);vec4 color1=texture2D(u_image1,v_pos1);if (color0.a > 0.0) {color0.rgb=color0.rgb/color0.a;}if (color1.a > 0.0) {color1.rgb=color1.rgb/color1.a;}vec4 color=mix(color0,color1,u_fade_t);color.a*=u_opacity;vec3 rgb=color.rgb;rgb=vec3(dot(rgb,u_spin_weights.xyz),dot(rgb,u_spin_weights.zxy),dot(rgb,u_spin_weights.yzx));float average=(color.r+color.g+color.b)/3.0;rgb+=(average-rgb)*u_saturation_factor;rgb=(rgb-0.5)*u_contrast_factor+0.5;vec3 u_high_vec=vec3(u_brightness_low,u_brightness_low,u_brightness_low);vec3 u_low_vec=vec3(u_brightness_high,u_brightness_high,u_brightness_high);gl_FragColor=vec4(mix(u_high_vec,u_low_vec,rgb)*color.a,color.a); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,"uniform mat4 u_matrix;uniform vec2 u_tl_parent;uniform float u_scale_parent;uniform float u_buffer_scale;attribute vec2 a_pos;attribute vec2 a_texture_pos;varying vec2 v_pos0;varying vec2 v_pos1;void main() {gl_Position=u_matrix*vec4(a_pos,0,1);v_pos0=(((a_texture_pos/8192.0)-0.5)/u_buffer_scale )+0.5;v_pos1=(v_pos0*u_scale_parent)+u_tl_parent;}"),symbolIcon:wt(`uniform sampler2D u_texture;varying vec2 v_tex;varying float v_fade_opacity; +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize lowp float opacity +lowp float alpha=opacity*v_fade_opacity;gl_FragColor=texture2D(u_texture,v_tex)*alpha; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform highp float u_camera_to_center_distance;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform float u_fade_change;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform vec2 u_texsize;uniform bool u_is_along_line;uniform bool u_is_variable_anchor;uniform vec2 u_translation;uniform float u_pitched_scale;varying vec2 v_tex;varying float v_fade_opacity;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);} +#pragma mapbox: define lowp float opacity +void main() { +#pragma mapbox: initialize lowp float opacity +vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;vec2 a_minFontScale=a_pixeloffset.zw/256.0;float ele=get_elevation(a_pos);highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec2 translated_a_pos=a_pos+u_translation;vec4 projectedPoint=projectTileWithElevation(translated_a_pos,ele);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ? +camera_to_anchor_distance/u_camera_to_center_distance : +u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=projectTileWithElevation(translated_a_pos+vec2(1,0),ele);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos;if (u_is_along_line || u_is_variable_anchor) {projected_pos=vec4(a_projected_pos.xy,ele,1.0);} else if (u_pitch_with_map) {projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy+u_translation,ele,1.0);} else {projected_pos=u_label_plane_matrix*projectTileWithElevation(a_projected_pos.xy+u_translation,ele);}float z=float(u_pitch_with_map)*projected_pos.z/projected_pos.w;float projectionScaling=1.0;vec4 finalPos=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*max(a_minFontScale,fontScale)+a_pxoffset/16.0)*projectionScaling,z,1.0);if(u_pitch_with_map) {finalPos=projectTileWithElevation(finalPos.xy,finalPos.z);}gl_Position=finalPos;v_tex=a_tex/u_texsize;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float visibility=calculate_visibility(projectedPoint);v_fade_opacity=max(0.0,min(visibility,fade_opacity[0]+fade_change));}`),symbolSDF:wt(`#define SDF_PX 8.0 +uniform bool u_is_halo;uniform sampler2D u_texture;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;uniform bool u_is_text;varying vec2 v_data0;varying vec3 v_data1; +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +float EDGE_GAMMA=0.105/u_device_pixel_ratio;vec2 tex=v_data0.xy;float gamma_scale=v_data1.x;float size=v_data1.y;float fade_opacity=v_data1[2];float fontScale=u_is_text ? size/24.0 : size;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float inner_edge=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);inner_edge=inner_edge+gamma*gamma_scale;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(inner_edge-gamma_scaled,inner_edge+gamma_scaled,dist);if (u_is_halo) {lowp float halo_edge=(6.0-halo_width/fontScale)/SDF_PX;alpha=min(smoothstep(halo_edge-gamma_scaled,halo_edge+gamma_scaled,dist),1.0-alpha);}gl_FragColor=color*(alpha*opacity*fade_opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec4 a_pixeloffset;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform bool u_is_along_line;uniform bool u_is_variable_anchor;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_translation;uniform float u_pitched_scale;varying vec2 v_data0;varying vec3 v_data1;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);} +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);vec2 a_pxoffset=a_pixeloffset.xy;float ele=get_elevation(a_pos);highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec2 translated_a_pos=a_pos+u_translation;vec4 projectedPoint=projectTileWithElevation(translated_a_pos,ele);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ? +camera_to_anchor_distance/u_camera_to_center_distance : +u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=u_is_text ? size/24.0 : size;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=projectTileWithElevation(translated_a_pos+vec2(1,0),ele);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos;if (u_is_along_line || u_is_variable_anchor) {projected_pos=vec4(a_projected_pos.xy,ele,1.0);} else if (u_pitch_with_map) {projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy+u_translation,ele,1.0);} else {projected_pos=u_label_plane_matrix*projectTileWithElevation(a_projected_pos.xy+u_translation,ele);}float z=float(u_pitch_with_map)*projected_pos.z/projected_pos.w;float projectionScaling=1.0;vec4 finalPos=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale+a_pxoffset)*projectionScaling,z,1.0);if(u_pitch_with_map) {finalPos=projectTileWithElevation(finalPos.xy,finalPos.z);}float gamma_scale=finalPos.w;gl_Position=finalPos;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float visibility=calculate_visibility(projectedPoint);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(visibility,fade_opacity[0]+fade_change));v_data0=a_tex/u_texsize;v_data1=vec3(gamma_scale,size,interpolated_fade_opacity);}`),symbolTextAndIcon:wt(`#define SDF_PX 8.0 +#define SDF 1.0 +#define ICON 0.0 +uniform bool u_is_halo;uniform sampler2D u_texture;uniform sampler2D u_texture_icon;uniform highp float u_gamma_scale;uniform lowp float u_device_pixel_ratio;varying vec4 v_data0;varying vec4 v_data1; +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +float fade_opacity=v_data1[2];if (v_data1.w==ICON) {vec2 tex_icon=v_data0.zw;lowp float alpha=opacity*fade_opacity;gl_FragColor=texture2D(u_texture_icon,tex_icon)*alpha; +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +return;}vec2 tex=v_data0.xy;float EDGE_GAMMA=0.105/u_device_pixel_ratio;float gamma_scale=v_data1.x;float size=v_data1.y;float fontScale=size/24.0;lowp vec4 color=fill_color;highp float gamma=EDGE_GAMMA/(fontScale*u_gamma_scale);lowp float buff=(256.0-64.0)/256.0;if (u_is_halo) {color=halo_color;gamma=(halo_blur*1.19/SDF_PX+EDGE_GAMMA)/(fontScale*u_gamma_scale);buff=(6.0-halo_width/fontScale)/SDF_PX;}lowp float dist=texture2D(u_texture,tex).a;highp float gamma_scaled=gamma*gamma_scale;highp float alpha=smoothstep(buff-gamma_scaled,buff+gamma_scaled,dist);gl_FragColor=color*(alpha*opacity*fade_opacity); +#ifdef OVERDRAW_INSPECTOR +gl_FragColor=vec4(1.0); +#endif +}`,`attribute vec4 a_pos_offset;attribute vec4 a_data;attribute vec3 a_projected_pos;attribute float a_fade_opacity;uniform bool u_is_size_zoom_constant;uniform bool u_is_size_feature_constant;uniform highp float u_size_t;uniform highp float u_size;uniform mat4 u_matrix;uniform mat4 u_label_plane_matrix;uniform mat4 u_coord_matrix;uniform bool u_is_text;uniform bool u_pitch_with_map;uniform highp float u_pitch;uniform bool u_rotate_symbol;uniform highp float u_aspect_ratio;uniform highp float u_camera_to_center_distance;uniform float u_fade_change;uniform vec2 u_texsize;uniform vec2 u_texsize_icon;uniform bool u_is_along_line;uniform bool u_is_variable_anchor;uniform vec2 u_translation;uniform float u_pitched_scale;varying vec4 v_data0;varying vec4 v_data1;vec4 projectTileWithElevation(vec2 posInTile,float elevation) {return u_matrix*vec4(posInTile,elevation,1.0);} +#pragma mapbox: define highp vec4 fill_color +#pragma mapbox: define highp vec4 halo_color +#pragma mapbox: define lowp float opacity +#pragma mapbox: define lowp float halo_width +#pragma mapbox: define lowp float halo_blur +void main() { +#pragma mapbox: initialize highp vec4 fill_color +#pragma mapbox: initialize highp vec4 halo_color +#pragma mapbox: initialize lowp float opacity +#pragma mapbox: initialize lowp float halo_width +#pragma mapbox: initialize lowp float halo_blur +vec2 a_pos=a_pos_offset.xy;vec2 a_offset=a_pos_offset.zw;vec2 a_tex=a_data.xy;vec2 a_size=a_data.zw;float a_size_min=floor(a_size[0]*0.5);float is_sdf=a_size[0]-2.0*a_size_min;float ele=get_elevation(a_pos);highp float segment_angle=-a_projected_pos[2];float size;if (!u_is_size_zoom_constant && !u_is_size_feature_constant) {size=mix(a_size_min,a_size[1],u_size_t)/128.0;} else if (u_is_size_zoom_constant && !u_is_size_feature_constant) {size=a_size_min/128.0;} else {size=u_size;}vec2 translated_a_pos=a_pos+u_translation;vec4 projectedPoint=projectTileWithElevation(translated_a_pos,ele);highp float camera_to_anchor_distance=projectedPoint.w;highp float distance_ratio=u_pitch_with_map ? +camera_to_anchor_distance/u_camera_to_center_distance : +u_camera_to_center_distance/camera_to_anchor_distance;highp float perspective_ratio=clamp(0.5+0.5*distance_ratio,0.0,4.0);size*=perspective_ratio;float fontScale=size/24.0;highp float symbol_rotation=0.0;if (u_rotate_symbol) {vec4 offsetProjectedPoint=projectTileWithElevation(translated_a_pos+vec2(1,0),ele);vec2 a=projectedPoint.xy/projectedPoint.w;vec2 b=offsetProjectedPoint.xy/offsetProjectedPoint.w;symbol_rotation=atan((b.y-a.y)/u_aspect_ratio,b.x-a.x);}highp float angle_sin=sin(segment_angle+symbol_rotation);highp float angle_cos=cos(segment_angle+symbol_rotation);mat2 rotation_matrix=mat2(angle_cos,-1.0*angle_sin,angle_sin,angle_cos);vec4 projected_pos;if (u_is_along_line || u_is_variable_anchor) {projected_pos=vec4(a_projected_pos.xy,ele,1.0);} else if (u_pitch_with_map) {projected_pos=u_label_plane_matrix*vec4(a_projected_pos.xy+u_translation,ele,1.0);} else {projected_pos=u_label_plane_matrix*projectTileWithElevation(a_projected_pos.xy+u_translation,ele);}float z=float(u_pitch_with_map)*projected_pos.z/projected_pos.w;float projectionScaling=1.0;vec4 finalPos=u_coord_matrix*vec4(projected_pos.xy/projected_pos.w+rotation_matrix*(a_offset/32.0*fontScale)*projectionScaling,z,1.0);if(u_pitch_with_map) {finalPos=projectTileWithElevation(finalPos.xy,finalPos.z);}float gamma_scale=finalPos.w;gl_Position=finalPos;vec2 fade_opacity=unpack_opacity(a_fade_opacity);float visibility=calculate_visibility(projectedPoint);float fade_change=fade_opacity[1] > 0.5 ? u_fade_change :-u_fade_change;float interpolated_fade_opacity=max(0.0,min(visibility,fade_opacity[0]+fade_change));v_data0.xy=a_tex/u_texsize;v_data0.zw=a_tex/u_texsize_icon;v_data1=vec4(gamma_scale,size,interpolated_fade_opacity,is_sdf);}`),terrain:wt("uniform sampler2D u_texture;uniform vec4 u_fog_color;uniform vec4 u_horizon_color;uniform float u_fog_ground_blend;uniform float u_fog_ground_blend_opacity;uniform float u_horizon_fog_blend;varying vec2 v_texture_pos;varying float v_fog_depth;const float gamma=2.2;vec4 gammaToLinear(vec4 color) {return pow(color,vec4(gamma));}vec4 linearToGamma(vec4 color) {return pow(color,vec4(1.0/gamma));}void main() {vec4 surface_color=texture2D(u_texture,v_texture_pos);if (v_fog_depth > u_fog_ground_blend) {vec4 surface_color_linear=gammaToLinear(surface_color);float blend_color=smoothstep(0.0,1.0,max((v_fog_depth-u_horizon_fog_blend)/(1.0-u_horizon_fog_blend),0.0));vec4 fog_horizon_color_linear=mix(gammaToLinear(u_fog_color),gammaToLinear(u_horizon_color),blend_color);float factor_fog=max(v_fog_depth-u_fog_ground_blend,0.0)/(1.0-u_fog_ground_blend);gl_FragColor=linearToGamma(mix(surface_color_linear,fog_horizon_color_linear,pow(factor_fog,2.0)*u_fog_ground_blend_opacity));} else {gl_FragColor=surface_color;}}","attribute vec3 a_pos3d;uniform mat4 u_matrix;uniform mat4 u_fog_matrix;uniform float u_ele_delta;varying vec2 v_texture_pos;varying float v_fog_depth;void main() {float ele=get_elevation(a_pos3d.xy);float ele_delta=a_pos3d.z==1.0 ? u_ele_delta : 0.0;v_texture_pos=a_pos3d.xy/8192.0;gl_Position=u_matrix*vec4(a_pos3d.xy,ele-ele_delta,1.0);vec4 pos=u_fog_matrix*vec4(a_pos3d.xy,ele,1.0);v_fog_depth=pos.z/pos.w*0.5+0.5;}"),terrainDepth:wt("varying float v_depth;const highp vec4 bitSh=vec4(256.*256.*256.,256.*256.,256.,1.);const highp vec4 bitMsk=vec4(0.,vec3(1./256.0));highp vec4 pack(highp float value) {highp vec4 comp=fract(value*bitSh);comp-=comp.xxyz*bitMsk;return comp;}void main() {gl_FragColor=pack(v_depth);}","attribute vec3 a_pos3d;uniform mat4 u_matrix;uniform float u_ele_delta;varying float v_depth;void main() {float ele=get_elevation(a_pos3d.xy);float ele_delta=a_pos3d.z==1.0 ? u_ele_delta : 0.0;gl_Position=u_matrix*vec4(a_pos3d.xy,ele-ele_delta,1.0);v_depth=gl_Position.z/gl_Position.w;}"),terrainCoords:wt("precision mediump float;uniform sampler2D u_texture;uniform float u_terrain_coords_id;varying vec2 v_texture_pos;void main() {vec4 rgba=texture2D(u_texture,v_texture_pos);gl_FragColor=vec4(rgba.r,rgba.g,rgba.b,u_terrain_coords_id);}","attribute vec3 a_pos3d;uniform mat4 u_matrix;uniform float u_ele_delta;varying vec2 v_texture_pos;void main() {float ele=get_elevation(a_pos3d.xy);float ele_delta=a_pos3d.z==1.0 ? u_ele_delta : 0.0;v_texture_pos=a_pos3d.xy/8192.0;gl_Position=u_matrix*vec4(a_pos3d.xy,ele-ele_delta,1.0);}"),sky:wt("uniform vec4 u_sky_color;uniform vec4 u_horizon_color;uniform float u_horizon;uniform float u_sky_horizon_blend;void main() {float y=gl_FragCoord.y;if (y > u_horizon) {float blend=y-u_horizon;if (blend < u_sky_horizon_blend) {gl_FragColor=mix(u_sky_color,u_horizon_color,pow(1.0-blend/u_sky_horizon_blend,2.0));} else {gl_FragColor=u_sky_color;}}}","attribute vec2 a_pos;void main() {gl_Position=vec4(a_pos,1.0,1.0);}")};function wt(Ue,R){let ae=/#pragma mapbox: ([\w]+) ([\w]+) ([\w]+) ([\w]+)/g,we=R.match(/attribute ([\w]+) ([\w]+)/g),Ae=Ue.match(/uniform ([\w]+) ([\w]+)([\s]*)([\w]*)/g),Be=R.match(/uniform ([\w]+) ([\w]+)([\s]*)([\w]*)/g),pt=Be?Be.concat(Ae):Ae,At={};return{fragmentSource:Ue=Ue.replace(ae,(Nt,$t,wr,Tr,Kr)=>(At[Kr]=!0,$t==="define"?` +#ifndef HAS_UNIFORM_u_${Kr} +varying ${wr} ${Tr} ${Kr}; +#else +uniform ${wr} ${Tr} u_${Kr}; +#endif +`:` +#ifdef HAS_UNIFORM_u_${Kr} + ${wr} ${Tr} ${Kr} = u_${Kr}; +#endif +`)),vertexSource:R=R.replace(ae,(Nt,$t,wr,Tr,Kr)=>{let sa=Tr==="float"?"vec2":"vec4",He=Kr.match(/color/)?"color":sa;return At[Kr]?$t==="define"?` +#ifndef HAS_UNIFORM_u_${Kr} +uniform lowp float u_${Kr}_t; +attribute ${wr} ${sa} a_${Kr}; +varying ${wr} ${Tr} ${Kr}; +#else +uniform ${wr} ${Tr} u_${Kr}; +#endif +`:He==="vec4"?` +#ifndef HAS_UNIFORM_u_${Kr} + ${Kr} = a_${Kr}; +#else + ${wr} ${Tr} ${Kr} = u_${Kr}; +#endif +`:` +#ifndef HAS_UNIFORM_u_${Kr} + ${Kr} = unpack_mix_${He}(a_${Kr}, u_${Kr}_t); +#else + ${wr} ${Tr} ${Kr} = u_${Kr}; +#endif +`:$t==="define"?` +#ifndef HAS_UNIFORM_u_${Kr} +uniform lowp float u_${Kr}_t; +attribute ${wr} ${sa} a_${Kr}; +#else +uniform ${wr} ${Tr} u_${Kr}; +#endif +`:He==="vec4"?` +#ifndef HAS_UNIFORM_u_${Kr} + ${wr} ${Tr} ${Kr} = a_${Kr}; +#else + ${wr} ${Tr} ${Kr} = u_${Kr}; +#endif +`:` +#ifndef HAS_UNIFORM_u_${Kr} + ${wr} ${Tr} ${Kr} = unpack_mix_${He}(a_${Kr}, u_${Kr}_t); +#else + ${wr} ${Tr} ${Kr} = u_${Kr}; +#endif +`}),staticAttributes:we,staticUniforms:pt}}class Kt{constructor(){this.boundProgram=null,this.boundLayoutVertexBuffer=null,this.boundPaintVertexBuffers=[],this.boundIndexBuffer=null,this.boundVertexOffset=null,this.boundDynamicVertexBuffer=null,this.vao=null}bind(R,ae,we,Ae,Be,pt,At,Nt,$t){this.context=R;let wr=this.boundPaintVertexBuffers.length!==Ae.length;for(let Tr=0;!wr&&Tr({u_matrix:Ue,u_texture:0,u_ele_delta:R,u_fog_matrix:ae,u_fog_color:we?we.properties.get("fog-color"):t.aM.white,u_fog_ground_blend:we?we.properties.get("fog-ground-blend"):1,u_fog_ground_blend_opacity:we?we.calculateFogBlendOpacity(Ae):0,u_horizon_color:we?we.properties.get("horizon-color"):t.aM.white,u_horizon_fog_blend:we?we.properties.get("horizon-fog-blend"):1});function Xr(Ue){let R=[];for(let ae=0;ae({u_depth:new t.aH(mr,Er.u_depth),u_terrain:new t.aH(mr,Er.u_terrain),u_terrain_dim:new t.aI(mr,Er.u_terrain_dim),u_terrain_matrix:new t.aJ(mr,Er.u_terrain_matrix),u_terrain_unpack:new t.aK(mr,Er.u_terrain_unpack),u_terrain_exaggeration:new t.aI(mr,Er.u_terrain_exaggeration)}))(R,ur),this.binderUniforms=we?we.getUniforms(R,ur):[]}draw(R,ae,we,Ae,Be,pt,At,Nt,$t,wr,Tr,Kr,sa,He,Je,lt,dt,Ct){let Tt=R.gl;if(this.failedToCreate)return;if(R.program.set(this.program),R.setDepthMode(we),R.setStencilMode(Ae),R.setColorMode(Be),R.setCullFace(pt),Nt){R.activeTexture.set(Tt.TEXTURE2),Tt.bindTexture(Tt.TEXTURE_2D,Nt.depthTexture),R.activeTexture.set(Tt.TEXTURE3),Tt.bindTexture(Tt.TEXTURE_2D,Nt.texture);for(let ur in this.terrainUniforms)this.terrainUniforms[ur].set(Nt[ur])}for(let ur in this.fixedUniforms)this.fixedUniforms[ur].set(At[ur]);Je&&Je.setUniforms(R,this.binderUniforms,sa,{zoom:He});let zt=0;switch(ae){case Tt.LINES:zt=2;break;case Tt.TRIANGLES:zt=3;break;case Tt.LINE_STRIP:zt=1}for(let ur of Kr.get()){let mr=ur.vaos||(ur.vaos={});(mr[$t]||(mr[$t]=new Kt)).bind(R,this,wr,Je?Je.getPaintVertexBuffers():[],Tr,ur.vertexOffset,lt,dt,Ct),Tt.drawElements(ae,ur.primitiveLength*zt,Tt.UNSIGNED_SHORT,ur.primitiveOffset*zt*2)}}}function Ca(Ue,R,ae){let we=1/za(ae,1,R.transform.tileZoom),Ae=Math.pow(2,ae.tileID.overscaledZ),Be=ae.tileSize*Math.pow(2,R.transform.tileZoom)/Ae,pt=Be*(ae.tileID.canonical.x+ae.tileID.wrap*Ae),At=Be*ae.tileID.canonical.y;return{u_image:0,u_texsize:ae.imageAtlasTexture.size,u_scale:[we,Ue.fromScale,Ue.toScale],u_fade:Ue.t,u_pixel_coord_upper:[pt>>16,At>>16],u_pixel_coord_lower:[65535&pt,65535&At]}}let La=(Ue,R,ae,we)=>{let Ae=R.style.light,Be=Ae.properties.get("position"),pt=[Be.x,Be.y,Be.z],At=function(){var $t=new t.A(9);return t.A!=Float32Array&&($t[1]=0,$t[2]=0,$t[3]=0,$t[5]=0,$t[6]=0,$t[7]=0),$t[0]=1,$t[4]=1,$t[8]=1,$t}();Ae.properties.get("anchor")==="viewport"&&function($t,wr){var Tr=Math.sin(wr),Kr=Math.cos(wr);$t[0]=Kr,$t[1]=Tr,$t[2]=0,$t[3]=-Tr,$t[4]=Kr,$t[5]=0,$t[6]=0,$t[7]=0,$t[8]=1}(At,-R.transform.angle),function($t,wr,Tr){var Kr=wr[0],sa=wr[1],He=wr[2];$t[0]=Kr*Tr[0]+sa*Tr[3]+He*Tr[6],$t[1]=Kr*Tr[1]+sa*Tr[4]+He*Tr[7],$t[2]=Kr*Tr[2]+sa*Tr[5]+He*Tr[8]}(pt,pt,At);let Nt=Ae.properties.get("color");return{u_matrix:Ue,u_lightpos:pt,u_lightintensity:Ae.properties.get("intensity"),u_lightcolor:[Nt.r,Nt.g,Nt.b],u_vertical_gradient:+ae,u_opacity:we}},ia=(Ue,R,ae,we,Ae,Be,pt)=>t.e(La(Ue,R,ae,we),Ca(Be,R,pt),{u_height_factor:-Math.pow(2,Ae.overscaledZ)/pt.tileSize/8}),Aa=Ue=>({u_matrix:Ue}),Ki=(Ue,R,ae,we)=>t.e(Aa(Ue),Ca(ae,R,we)),pi=(Ue,R)=>({u_matrix:Ue,u_world:R}),cn=(Ue,R,ae,we,Ae)=>t.e(Ki(Ue,R,ae,we),{u_world:Ae}),yn=(Ue,R,ae,we)=>{let Ae=Ue.transform,Be,pt;if(we.paint.get("circle-pitch-alignment")==="map"){let At=za(ae,1,Ae.zoom);Be=!0,pt=[At,At]}else Be=!1,pt=Ae.pixelsToGLUnits;return{u_camera_to_center_distance:Ae.cameraToCenterDistance,u_scale_with_map:+(we.paint.get("circle-pitch-scale")==="map"),u_matrix:Ue.translatePosMatrix(R.posMatrix,ae,we.paint.get("circle-translate"),we.paint.get("circle-translate-anchor")),u_pitch_with_map:+Be,u_device_pixel_ratio:Ue.pixelRatio,u_extrude_scale:pt}},Pn=(Ue,R,ae)=>({u_matrix:Ue,u_inv_matrix:R,u_camera_to_center_distance:ae.cameraToCenterDistance,u_viewport_size:[ae.width,ae.height]}),In=(Ue,R,ae=1)=>({u_matrix:Ue,u_color:R,u_overlay:0,u_overlay_scale:ae}),Hn=Ue=>({u_matrix:Ue}),Vn=(Ue,R,ae,we)=>({u_matrix:Ue,u_extrude_scale:za(R,1,ae),u_intensity:we}),hn=(Ue,R,ae,we)=>{let Ae=t.H();t.aP(Ae,0,Ue.width,Ue.height,0,0,1);let Be=Ue.context.gl;return{u_matrix:Ae,u_world:[Be.drawingBufferWidth,Be.drawingBufferHeight],u_image:ae,u_color_ramp:we,u_opacity:R.paint.get("heatmap-opacity")}};function Co(Ue,R){let ae=Math.pow(2,R.canonical.z),we=R.canonical.y;return[new t.Z(0,we/ae).toLngLat().lat,new t.Z(0,(we+1)/ae).toLngLat().lat]}let Wo=(Ue,R,ae,we)=>{let Ae=Ue.transform;return{u_matrix:us(Ue,R,ae,we),u_ratio:1/za(R,1,Ae.zoom),u_device_pixel_ratio:Ue.pixelRatio,u_units_to_pixels:[1/Ae.pixelsToGLUnits[0],1/Ae.pixelsToGLUnits[1]]}},So=(Ue,R,ae,we,Ae)=>t.e(Wo(Ue,R,ae,Ae),{u_image:0,u_image_height:we}),go=(Ue,R,ae,we,Ae)=>{let Be=Ue.transform,pt=as(R,Be);return{u_matrix:us(Ue,R,ae,Ae),u_texsize:R.imageAtlasTexture.size,u_ratio:1/za(R,1,Be.zoom),u_device_pixel_ratio:Ue.pixelRatio,u_image:0,u_scale:[pt,we.fromScale,we.toScale],u_fade:we.t,u_units_to_pixels:[1/Be.pixelsToGLUnits[0],1/Be.pixelsToGLUnits[1]]}},Po=(Ue,R,ae,we,Ae,Be)=>{let pt=Ue.lineAtlas,At=as(R,Ue.transform),Nt=ae.layout.get("line-cap")==="round",$t=pt.getDash(we.from,Nt),wr=pt.getDash(we.to,Nt),Tr=$t.width*Ae.fromScale,Kr=wr.width*Ae.toScale;return t.e(Wo(Ue,R,ae,Be),{u_patternscale_a:[At/Tr,-$t.height/2],u_patternscale_b:[At/Kr,-wr.height/2],u_sdfgamma:pt.width/(256*Math.min(Tr,Kr)*Ue.pixelRatio)/2,u_image:0,u_tex_y_a:$t.y,u_tex_y_b:wr.y,u_mix:Ae.t})};function as(Ue,R){return 1/za(Ue,1,R.tileZoom)}function us(Ue,R,ae,we){return Ue.translatePosMatrix(we?we.posMatrix:R.tileID.posMatrix,R,ae.paint.get("line-translate"),ae.paint.get("line-translate-anchor"))}let gs=(Ue,R,ae,we,Ae)=>{return{u_matrix:Ue,u_tl_parent:R,u_scale_parent:ae,u_buffer_scale:1,u_fade_t:we.mix,u_opacity:we.opacity*Ae.paint.get("raster-opacity"),u_image0:0,u_image1:1,u_brightness_low:Ae.paint.get("raster-brightness-min"),u_brightness_high:Ae.paint.get("raster-brightness-max"),u_saturation_factor:(pt=Ae.paint.get("raster-saturation"),pt>0?1-1/(1.001-pt):-pt),u_contrast_factor:(Be=Ae.paint.get("raster-contrast"),Be>0?1/(1-Be):1+Be),u_spin_weights:ho(Ae.paint.get("raster-hue-rotate"))};var Be,pt};function ho(Ue){Ue*=Math.PI/180;let R=Math.sin(Ue),ae=Math.cos(Ue);return[(2*ae+1)/3,(-Math.sqrt(3)*R-ae+1)/3,(Math.sqrt(3)*R-ae+1)/3]}let po=(Ue,R,ae,we,Ae,Be,pt,At,Nt,$t,wr,Tr,Kr,sa)=>{let He=pt.transform;return{u_is_size_zoom_constant:+(Ue==="constant"||Ue==="source"),u_is_size_feature_constant:+(Ue==="constant"||Ue==="camera"),u_size_t:R?R.uSizeT:0,u_size:R?R.uSize:0,u_camera_to_center_distance:He.cameraToCenterDistance,u_pitch:He.pitch/360*2*Math.PI,u_rotate_symbol:+ae,u_aspect_ratio:He.width/He.height,u_fade_change:pt.options.fadeDuration?pt.symbolFadeChange:1,u_matrix:At,u_label_plane_matrix:Nt,u_coord_matrix:$t,u_is_text:+Tr,u_pitch_with_map:+we,u_is_along_line:Ae,u_is_variable_anchor:Be,u_texsize:Kr,u_texture:0,u_translation:wr,u_pitched_scale:sa}},Un=(Ue,R,ae,we,Ae,Be,pt,At,Nt,$t,wr,Tr,Kr,sa,He)=>{let Je=pt.transform;return t.e(po(Ue,R,ae,we,Ae,Be,pt,At,Nt,$t,wr,Tr,Kr,He),{u_gamma_scale:we?Math.cos(Je._pitch)*Je.cameraToCenterDistance:1,u_device_pixel_ratio:pt.pixelRatio,u_is_halo:+sa})},oo=(Ue,R,ae,we,Ae,Be,pt,At,Nt,$t,wr,Tr,Kr,sa)=>t.e(Un(Ue,R,ae,we,Ae,Be,pt,At,Nt,$t,wr,!0,Tr,!0,sa),{u_texsize_icon:Kr,u_texture_icon:1}),ys=(Ue,R,ae)=>({u_matrix:Ue,u_opacity:R,u_color:ae}),Bs=(Ue,R,ae,we,Ae,Be)=>t.e(function(pt,At,Nt,$t){let wr=Nt.imageManager.getPattern(pt.from.toString()),Tr=Nt.imageManager.getPattern(pt.to.toString()),{width:Kr,height:sa}=Nt.imageManager.getPixelSize(),He=Math.pow(2,$t.tileID.overscaledZ),Je=$t.tileSize*Math.pow(2,Nt.transform.tileZoom)/He,lt=Je*($t.tileID.canonical.x+$t.tileID.wrap*He),dt=Je*$t.tileID.canonical.y;return{u_image:0,u_pattern_tl_a:wr.tl,u_pattern_br_a:wr.br,u_pattern_tl_b:Tr.tl,u_pattern_br_b:Tr.br,u_texsize:[Kr,sa],u_mix:At.t,u_pattern_size_a:wr.displaySize,u_pattern_size_b:Tr.displaySize,u_scale_a:At.fromScale,u_scale_b:At.toScale,u_tile_units_to_pixels:1/za($t,1,Nt.transform.tileZoom),u_pixel_coord_upper:[lt>>16,dt>>16],u_pixel_coord_lower:[65535<,65535&dt]}}(we,Be,ae,Ae),{u_matrix:Ue,u_opacity:R}),js={fillExtrusion:(Ue,R)=>({u_matrix:new t.aJ(Ue,R.u_matrix),u_lightpos:new t.aN(Ue,R.u_lightpos),u_lightintensity:new t.aI(Ue,R.u_lightintensity),u_lightcolor:new t.aN(Ue,R.u_lightcolor),u_vertical_gradient:new t.aI(Ue,R.u_vertical_gradient),u_opacity:new t.aI(Ue,R.u_opacity)}),fillExtrusionPattern:(Ue,R)=>({u_matrix:new t.aJ(Ue,R.u_matrix),u_lightpos:new t.aN(Ue,R.u_lightpos),u_lightintensity:new t.aI(Ue,R.u_lightintensity),u_lightcolor:new t.aN(Ue,R.u_lightcolor),u_vertical_gradient:new t.aI(Ue,R.u_vertical_gradient),u_height_factor:new t.aI(Ue,R.u_height_factor),u_image:new t.aH(Ue,R.u_image),u_texsize:new t.aO(Ue,R.u_texsize),u_pixel_coord_upper:new t.aO(Ue,R.u_pixel_coord_upper),u_pixel_coord_lower:new t.aO(Ue,R.u_pixel_coord_lower),u_scale:new t.aN(Ue,R.u_scale),u_fade:new t.aI(Ue,R.u_fade),u_opacity:new t.aI(Ue,R.u_opacity)}),fill:(Ue,R)=>({u_matrix:new t.aJ(Ue,R.u_matrix)}),fillPattern:(Ue,R)=>({u_matrix:new t.aJ(Ue,R.u_matrix),u_image:new t.aH(Ue,R.u_image),u_texsize:new t.aO(Ue,R.u_texsize),u_pixel_coord_upper:new t.aO(Ue,R.u_pixel_coord_upper),u_pixel_coord_lower:new t.aO(Ue,R.u_pixel_coord_lower),u_scale:new t.aN(Ue,R.u_scale),u_fade:new t.aI(Ue,R.u_fade)}),fillOutline:(Ue,R)=>({u_matrix:new t.aJ(Ue,R.u_matrix),u_world:new 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t.aO(Ue,R.u_viewport_size)}),debug:(Ue,R)=>({u_color:new t.aL(Ue,R.u_color),u_matrix:new t.aJ(Ue,R.u_matrix),u_overlay:new t.aH(Ue,R.u_overlay),u_overlay_scale:new t.aI(Ue,R.u_overlay_scale)}),clippingMask:(Ue,R)=>({u_matrix:new t.aJ(Ue,R.u_matrix)}),heatmap:(Ue,R)=>({u_extrude_scale:new t.aI(Ue,R.u_extrude_scale),u_intensity:new t.aI(Ue,R.u_intensity),u_matrix:new t.aJ(Ue,R.u_matrix)}),heatmapTexture:(Ue,R)=>({u_matrix:new t.aJ(Ue,R.u_matrix),u_world:new t.aO(Ue,R.u_world),u_image:new t.aH(Ue,R.u_image),u_color_ramp:new t.aH(Ue,R.u_color_ramp),u_opacity:new t.aI(Ue,R.u_opacity)}),hillshade:(Ue,R)=>({u_matrix:new t.aJ(Ue,R.u_matrix),u_image:new t.aH(Ue,R.u_image),u_latrange:new t.aO(Ue,R.u_latrange),u_light:new t.aO(Ue,R.u_light),u_shadow:new t.aL(Ue,R.u_shadow),u_highlight:new t.aL(Ue,R.u_highlight),u_accent:new t.aL(Ue,R.u_accent)}),hillshadePrepare:(Ue,R)=>({u_matrix:new t.aJ(Ue,R.u_matrix),u_image:new t.aH(Ue,R.u_image),u_dimension:new t.aO(Ue,R.u_dimension),u_zoom:new 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t.aO(Ue,R.u_units_to_pixels),u_patternscale_a:new t.aO(Ue,R.u_patternscale_a),u_patternscale_b:new t.aO(Ue,R.u_patternscale_b),u_sdfgamma:new t.aI(Ue,R.u_sdfgamma),u_image:new t.aH(Ue,R.u_image),u_tex_y_a:new t.aI(Ue,R.u_tex_y_a),u_tex_y_b:new t.aI(Ue,R.u_tex_y_b),u_mix:new t.aI(Ue,R.u_mix)}),raster:(Ue,R)=>({u_matrix:new t.aJ(Ue,R.u_matrix),u_tl_parent:new t.aO(Ue,R.u_tl_parent),u_scale_parent:new t.aI(Ue,R.u_scale_parent),u_buffer_scale:new t.aI(Ue,R.u_buffer_scale),u_fade_t:new t.aI(Ue,R.u_fade_t),u_opacity:new t.aI(Ue,R.u_opacity),u_image0:new t.aH(Ue,R.u_image0),u_image1:new t.aH(Ue,R.u_image1),u_brightness_low:new t.aI(Ue,R.u_brightness_low),u_brightness_high:new t.aI(Ue,R.u_brightness_high),u_saturation_factor:new t.aI(Ue,R.u_saturation_factor),u_contrast_factor:new t.aI(Ue,R.u_contrast_factor),u_spin_weights:new t.aN(Ue,R.u_spin_weights)}),symbolIcon:(Ue,R)=>({u_is_size_zoom_constant:new t.aH(Ue,R.u_is_size_zoom_constant),u_is_size_feature_constant:new 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t.aI(Ue,R.u_size_t),u_size:new t.aI(Ue,R.u_size),u_camera_to_center_distance:new t.aI(Ue,R.u_camera_to_center_distance),u_pitch:new t.aI(Ue,R.u_pitch),u_rotate_symbol:new t.aH(Ue,R.u_rotate_symbol),u_aspect_ratio:new t.aI(Ue,R.u_aspect_ratio),u_fade_change:new t.aI(Ue,R.u_fade_change),u_matrix:new t.aJ(Ue,R.u_matrix),u_label_plane_matrix:new t.aJ(Ue,R.u_label_plane_matrix),u_coord_matrix:new t.aJ(Ue,R.u_coord_matrix),u_is_text:new t.aH(Ue,R.u_is_text),u_pitch_with_map:new t.aH(Ue,R.u_pitch_with_map),u_is_along_line:new t.aH(Ue,R.u_is_along_line),u_is_variable_anchor:new t.aH(Ue,R.u_is_variable_anchor),u_texsize:new t.aO(Ue,R.u_texsize),u_texture:new t.aH(Ue,R.u_texture),u_gamma_scale:new t.aI(Ue,R.u_gamma_scale),u_device_pixel_ratio:new t.aI(Ue,R.u_device_pixel_ratio),u_is_halo:new t.aH(Ue,R.u_is_halo),u_translation:new t.aO(Ue,R.u_translation),u_pitched_scale:new t.aI(Ue,R.u_pitched_scale)}),symbolTextAndIcon:(Ue,R)=>({u_is_size_zoom_constant:new 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t.aH(Ue,R.u_is_halo),u_translation:new t.aO(Ue,R.u_translation),u_pitched_scale:new t.aI(Ue,R.u_pitched_scale)}),background:(Ue,R)=>({u_matrix:new t.aJ(Ue,R.u_matrix),u_opacity:new t.aI(Ue,R.u_opacity),u_color:new t.aL(Ue,R.u_color)}),backgroundPattern:(Ue,R)=>({u_matrix:new t.aJ(Ue,R.u_matrix),u_opacity:new t.aI(Ue,R.u_opacity),u_image:new t.aH(Ue,R.u_image),u_pattern_tl_a:new t.aO(Ue,R.u_pattern_tl_a),u_pattern_br_a:new t.aO(Ue,R.u_pattern_br_a),u_pattern_tl_b:new t.aO(Ue,R.u_pattern_tl_b),u_pattern_br_b:new t.aO(Ue,R.u_pattern_br_b),u_texsize:new t.aO(Ue,R.u_texsize),u_mix:new t.aI(Ue,R.u_mix),u_pattern_size_a:new t.aO(Ue,R.u_pattern_size_a),u_pattern_size_b:new t.aO(Ue,R.u_pattern_size_b),u_scale_a:new t.aI(Ue,R.u_scale_a),u_scale_b:new t.aI(Ue,R.u_scale_b),u_pixel_coord_upper:new t.aO(Ue,R.u_pixel_coord_upper),u_pixel_coord_lower:new t.aO(Ue,R.u_pixel_coord_lower),u_tile_units_to_pixels:new t.aI(Ue,R.u_tile_units_to_pixels)}),terrain:(Ue,R)=>({u_matrix:new t.aJ(Ue,R.u_matrix),u_texture:new t.aH(Ue,R.u_texture),u_ele_delta:new t.aI(Ue,R.u_ele_delta),u_fog_matrix:new t.aJ(Ue,R.u_fog_matrix),u_fog_color:new t.aL(Ue,R.u_fog_color),u_fog_ground_blend:new t.aI(Ue,R.u_fog_ground_blend),u_fog_ground_blend_opacity:new t.aI(Ue,R.u_fog_ground_blend_opacity),u_horizon_color:new t.aL(Ue,R.u_horizon_color),u_horizon_fog_blend:new t.aI(Ue,R.u_horizon_fog_blend)}),terrainDepth:(Ue,R)=>({u_matrix:new t.aJ(Ue,R.u_matrix),u_ele_delta:new t.aI(Ue,R.u_ele_delta)}),terrainCoords:(Ue,R)=>({u_matrix:new t.aJ(Ue,R.u_matrix),u_texture:new t.aH(Ue,R.u_texture),u_terrain_coords_id:new t.aI(Ue,R.u_terrain_coords_id),u_ele_delta:new t.aI(Ue,R.u_ele_delta)}),sky:(Ue,R)=>({u_sky_color:new t.aL(Ue,R.u_sky_color),u_horizon_color:new t.aL(Ue,R.u_horizon_color),u_horizon:new t.aI(Ue,R.u_horizon),u_sky_horizon_blend:new t.aI(Ue,R.u_sky_horizon_blend)})};class Xo{constructor(R,ae,we){this.context=R;let Ae=R.gl;this.buffer=Ae.createBuffer(),this.dynamicDraw=!!we,this.context.unbindVAO(),R.bindElementBuffer.set(this.buffer),Ae.bufferData(Ae.ELEMENT_ARRAY_BUFFER,ae.arrayBuffer,this.dynamicDraw?Ae.DYNAMIC_DRAW:Ae.STATIC_DRAW),this.dynamicDraw||delete ae.arrayBuffer}bind(){this.context.bindElementBuffer.set(this.buffer)}updateData(R){let ae=this.context.gl;if(!this.dynamicDraw)throw new Error("Attempted to update data while not in dynamic mode.");this.context.unbindVAO(),this.bind(),ae.bufferSubData(ae.ELEMENT_ARRAY_BUFFER,0,R.arrayBuffer)}destroy(){this.buffer&&(this.context.gl.deleteBuffer(this.buffer),delete this.buffer)}}let Zi={Int8:"BYTE",Uint8:"UNSIGNED_BYTE",Int16:"SHORT",Uint16:"UNSIGNED_SHORT",Int32:"INT",Uint32:"UNSIGNED_INT",Float32:"FLOAT"};class Mn{constructor(R,ae,we,Ae){this.length=ae.length,this.attributes=we,this.itemSize=ae.bytesPerElement,this.dynamicDraw=Ae,this.context=R;let Be=R.gl;this.buffer=Be.createBuffer(),R.bindVertexBuffer.set(this.buffer),Be.bufferData(Be.ARRAY_BUFFER,ae.arrayBuffer,this.dynamicDraw?Be.DYNAMIC_DRAW:Be.STATIC_DRAW),this.dynamicDraw||delete ae.arrayBuffer}bind(){this.context.bindVertexBuffer.set(this.buffer)}updateData(R){if(R.length!==this.length)throw new Error(`Length of new data is ${R.length}, which doesn't match current length of ${this.length}`);let ae=this.context.gl;this.bind(),ae.bufferSubData(ae.ARRAY_BUFFER,0,R.arrayBuffer)}enableAttributes(R,ae){for(let we=0;we0){let mr=t.H();t.aQ(mr,Tt.placementInvProjMatrix,Ue.transform.glCoordMatrix),t.aQ(mr,mr,Tt.placementViewportMatrix),Nt.push({circleArray:ur,circleOffset:wr,transform:Ct.posMatrix,invTransform:mr,coord:Ct}),$t+=ur.length/4,wr=$t}zt&&At.draw(Be,pt.LINES,ls.disabled,Ms.disabled,Ue.colorModeForRenderPass(),eo.disabled,{u_matrix:Ct.posMatrix,u_pixel_extrude_scale:[1/(Tr=Ue.transform).width,1/Tr.height]},Ue.style.map.terrain&&Ue.style.map.terrain.getTerrainData(Ct),ae.id,zt.layoutVertexBuffer,zt.indexBuffer,zt.segments,null,Ue.transform.zoom,null,null,zt.collisionVertexBuffer)}var Tr;if(!Ae||!Nt.length)return;let Kr=Ue.useProgram("collisionCircle"),sa=new t.aR;sa.resize(4*$t),sa._trim();let He=0;for(let dt of Nt)for(let Ct=0;Ct=0&&(dt[Tt.associatedIconIndex]={shiftedAnchor:Sn,angle:Zn})}else ar(Tt.numGlyphs,Je)}if($t){lt.clear();let Ct=Ue.icon.placedSymbolArray;for(let Tt=0;TtUe.style.map.terrain.getElevation(wa,Ot,gr):null,rr=ae.layout.get("text-rotation-alignment")==="map";Te(fi,wa.posMatrix,Ue,Ae,tu,pu,dt,$t,rr,Je,wa.toUnwrapped(),He.width,He.height,Tl,St)}let Gl=wa.posMatrix,Hl=Ae&&Ur||cc,de=Ct||Hl?ql:tu,ze=Ru,et=nn&&ae.paint.get(Ae?"text-halo-width":"icon-halo-width").constantOr(1)!==0,vt;vt=nn?fi.iconsInText?oo(Sn.kind,To,Tt,dt,Ct,Hl,Ue,Gl,de,ze,Tl,Mo,el,da):Un(Sn.kind,To,Tt,dt,Ct,Hl,Ue,Gl,de,ze,Tl,Ae,Mo,!0,da):po(Sn.kind,To,Tt,dt,Ct,Hl,Ue,Gl,de,ze,Tl,Ae,Mo,da);let _t={program:On,buffers:Vi,uniformValues:vt,atlasTexture:Yo,atlasTextureIcon:Qo,atlasInterpolation:ps,atlasInterpolationIcon:sl,isSDF:nn,hasHalo:et};if(ur&&fi.canOverlap){mr=!0;let St=Vi.segments.get();for(let rr of St)Qr.push({segments:new t.a0([rr]),sortKey:rr.sortKey,state:_t,terrainData:ss})}else Qr.push({segments:Vi.segments,sortKey:0,state:_t,terrainData:ss})}mr&&Qr.sort((wa,Fa)=>wa.sortKey-Fa.sortKey);for(let wa of Qr){let Fa=wa.state;if(Kr.activeTexture.set(sa.TEXTURE0),Fa.atlasTexture.bind(Fa.atlasInterpolation,sa.CLAMP_TO_EDGE),Fa.atlasTextureIcon&&(Kr.activeTexture.set(sa.TEXTURE1),Fa.atlasTextureIcon&&Fa.atlasTextureIcon.bind(Fa.atlasInterpolationIcon,sa.CLAMP_TO_EDGE)),Fa.isSDF){let fi=Fa.uniformValues;Fa.hasHalo&&(fi.u_is_halo=1,Of(Fa.buffers,wa.segments,ae,Ue,Fa.program,Er,wr,Tr,fi,wa.terrainData)),fi.u_is_halo=0}Of(Fa.buffers,wa.segments,ae,Ue,Fa.program,Er,wr,Tr,Fa.uniformValues,wa.terrainData)}}function Of(Ue,R,ae,we,Ae,Be,pt,At,Nt,$t){let wr=we.context;Ae.draw(wr,wr.gl.TRIANGLES,Be,pt,At,eo.disabled,Nt,$t,ae.id,Ue.layoutVertexBuffer,Ue.indexBuffer,R,ae.paint,we.transform.zoom,Ue.programConfigurations.get(ae.id),Ue.dynamicLayoutVertexBuffer,Ue.opacityVertexBuffer)}function nf(Ue,R,ae,we){let Ae=Ue.context,Be=Ae.gl,pt=Ms.disabled,At=new cl([Be.ONE,Be.ONE],t.aM.transparent,[!0,!0,!0,!0]),Nt=R.getBucket(ae);if(!Nt)return;let $t=we.key,wr=ae.heatmapFbos.get($t);wr||(wr=Bf(Ae,R.tileSize,R.tileSize),ae.heatmapFbos.set($t,wr)),Ae.bindFramebuffer.set(wr.framebuffer),Ae.viewport.set([0,0,R.tileSize,R.tileSize]),Ae.clear({color:t.aM.transparent});let Tr=Nt.programConfigurations.get(ae.id),Kr=Ue.useProgram("heatmap",Tr),sa=Ue.style.map.terrain.getTerrainData(we);Kr.draw(Ae,Be.TRIANGLES,ls.disabled,pt,At,eo.disabled,Vn(we.posMatrix,R,Ue.transform.zoom,ae.paint.get("heatmap-intensity")),sa,ae.id,Nt.layoutVertexBuffer,Nt.indexBuffer,Nt.segments,ae.paint,Ue.transform.zoom,Tr)}function jc(Ue,R,ae){let we=Ue.context,Ae=we.gl;we.setColorMode(Ue.colorModeForRenderPass());let Be=Nf(we,R),pt=ae.key,At=R.heatmapFbos.get(pt);At&&(we.activeTexture.set(Ae.TEXTURE0),Ae.bindTexture(Ae.TEXTURE_2D,At.colorAttachment.get()),we.activeTexture.set(Ae.TEXTURE1),Be.bind(Ae.LINEAR,Ae.CLAMP_TO_EDGE),Ue.useProgram("heatmapTexture").draw(we,Ae.TRIANGLES,ls.disabled,Ms.disabled,Ue.colorModeForRenderPass(),eo.disabled,hn(Ue,R,0,1),null,R.id,Ue.rasterBoundsBuffer,Ue.quadTriangleIndexBuffer,Ue.rasterBoundsSegments,R.paint,Ue.transform.zoom),At.destroy(),R.heatmapFbos.delete(pt))}function Bf(Ue,R,ae){var we,Ae;let Be=Ue.gl,pt=Be.createTexture();Be.bindTexture(Be.TEXTURE_2D,pt),Be.texParameteri(Be.TEXTURE_2D,Be.TEXTURE_WRAP_S,Be.CLAMP_TO_EDGE),Be.texParameteri(Be.TEXTURE_2D,Be.TEXTURE_WRAP_T,Be.CLAMP_TO_EDGE),Be.texParameteri(Be.TEXTURE_2D,Be.TEXTURE_MIN_FILTER,Be.LINEAR),Be.texParameteri(Be.TEXTURE_2D,Be.TEXTURE_MAG_FILTER,Be.LINEAR);let At=(we=Ue.HALF_FLOAT)!==null&&we!==void 0?we:Be.UNSIGNED_BYTE,Nt=(Ae=Ue.RGBA16F)!==null&&Ae!==void 0?Ae:Be.RGBA;Be.texImage2D(Be.TEXTURE_2D,0,Nt,R,ae,0,Be.RGBA,At,null);let $t=Ue.createFramebuffer(R,ae,!1,!1);return $t.colorAttachment.set(pt),$t}function Nf(Ue,R){return R.colorRampTexture||(R.colorRampTexture=new u(Ue,R.colorRamp,Ue.gl.RGBA)),R.colorRampTexture}function Gu(Ue,R,ae,we,Ae){if(!ae||!we||!we.imageAtlas)return;let Be=we.imageAtlas.patternPositions,pt=Be[ae.to.toString()],At=Be[ae.from.toString()];if(!pt&&At&&(pt=At),!At&&pt&&(At=pt),!pt||!At){let Nt=Ae.getPaintProperty(R);pt=Be[Nt],At=Be[Nt]}pt&&At&&Ue.setConstantPatternPositions(pt,At)}function Ef(Ue,R,ae,we,Ae,Be,pt){let At=Ue.context.gl,Nt="fill-pattern",$t=ae.paint.get(Nt),wr=$t&&$t.constantOr(1),Tr=ae.getCrossfadeParameters(),Kr,sa,He,Je,lt;pt?(sa=wr&&!ae.getPaintProperty("fill-outline-color")?"fillOutlinePattern":"fillOutline",Kr=At.LINES):(sa=wr?"fillPattern":"fill",Kr=At.TRIANGLES);let dt=$t.constantOr(null);for(let Ct of we){let Tt=R.getTile(Ct);if(wr&&!Tt.patternsLoaded())continue;let zt=Tt.getBucket(ae);if(!zt)continue;let ur=zt.programConfigurations.get(ae.id),mr=Ue.useProgram(sa,ur),Er=Ue.style.map.terrain&&Ue.style.map.terrain.getTerrainData(Ct);wr&&(Ue.context.activeTexture.set(At.TEXTURE0),Tt.imageAtlasTexture.bind(At.LINEAR,At.CLAMP_TO_EDGE),ur.updatePaintBuffers(Tr)),Gu(ur,Nt,dt,Tt,ae);let Ur=Er?Ct:null,Qr=Ue.translatePosMatrix(Ur?Ur.posMatrix:Ct.posMatrix,Tt,ae.paint.get("fill-translate"),ae.paint.get("fill-translate-anchor"));if(pt){Je=zt.indexBuffer2,lt=zt.segments2;let da=[At.drawingBufferWidth,At.drawingBufferHeight];He=sa==="fillOutlinePattern"&&wr?cn(Qr,Ue,Tr,Tt,da):pi(Qr,da)}else Je=zt.indexBuffer,lt=zt.segments,He=wr?Ki(Qr,Ue,Tr,Tt):Aa(Qr);mr.draw(Ue.context,Kr,Ae,Ue.stencilModeForClipping(Ct),Be,eo.disabled,He,Er,ae.id,zt.layoutVertexBuffer,Je,lt,ae.paint,Ue.transform.zoom,ur)}}function sc(Ue,R,ae,we,Ae,Be,pt){let At=Ue.context,Nt=At.gl,$t="fill-extrusion-pattern",wr=ae.paint.get($t),Tr=wr.constantOr(1),Kr=ae.getCrossfadeParameters(),sa=ae.paint.get("fill-extrusion-opacity"),He=wr.constantOr(null);for(let Je of we){let lt=R.getTile(Je),dt=lt.getBucket(ae);if(!dt)continue;let Ct=Ue.style.map.terrain&&Ue.style.map.terrain.getTerrainData(Je),Tt=dt.programConfigurations.get(ae.id),zt=Ue.useProgram(Tr?"fillExtrusionPattern":"fillExtrusion",Tt);Tr&&(Ue.context.activeTexture.set(Nt.TEXTURE0),lt.imageAtlasTexture.bind(Nt.LINEAR,Nt.CLAMP_TO_EDGE),Tt.updatePaintBuffers(Kr)),Gu(Tt,$t,He,lt,ae);let ur=Ue.translatePosMatrix(Je.posMatrix,lt,ae.paint.get("fill-extrusion-translate"),ae.paint.get("fill-extrusion-translate-anchor")),mr=ae.paint.get("fill-extrusion-vertical-gradient"),Er=Tr?ia(ur,Ue,mr,sa,Je,Kr,lt):La(ur,Ue,mr,sa);zt.draw(At,At.gl.TRIANGLES,Ae,Be,pt,eo.backCCW,Er,Ct,ae.id,dt.layoutVertexBuffer,dt.indexBuffer,dt.segments,ae.paint,Ue.transform.zoom,Tt,Ue.style.map.terrain&&dt.centroidVertexBuffer)}}function Wc(Ue,R,ae,we,Ae,Be,pt){let At=Ue.context,Nt=At.gl,$t=ae.fbo;if(!$t)return;let wr=Ue.useProgram("hillshade"),Tr=Ue.style.map.terrain&&Ue.style.map.terrain.getTerrainData(R);At.activeTexture.set(Nt.TEXTURE0),Nt.bindTexture(Nt.TEXTURE_2D,$t.colorAttachment.get()),wr.draw(At,Nt.TRIANGLES,Ae,Be,pt,eo.disabled,((Kr,sa,He,Je)=>{let lt=He.paint.get("hillshade-shadow-color"),dt=He.paint.get("hillshade-highlight-color"),Ct=He.paint.get("hillshade-accent-color"),Tt=He.paint.get("hillshade-illumination-direction")*(Math.PI/180);He.paint.get("hillshade-illumination-anchor")==="viewport"&&(Tt-=Kr.transform.angle);let zt=!Kr.options.moving;return{u_matrix:Je?Je.posMatrix:Kr.transform.calculatePosMatrix(sa.tileID.toUnwrapped(),zt),u_image:0,u_latrange:Co(0,sa.tileID),u_light:[He.paint.get("hillshade-exaggeration"),Tt],u_shadow:lt,u_highlight:dt,u_accent:Ct}})(Ue,ae,we,Tr?R:null),Tr,we.id,Ue.rasterBoundsBuffer,Ue.quadTriangleIndexBuffer,Ue.rasterBoundsSegments)}function eu(Ue,R,ae,we,Ae,Be){let pt=Ue.context,At=pt.gl,Nt=R.dem;if(Nt&&Nt.data){let $t=Nt.dim,wr=Nt.stride,Tr=Nt.getPixels();if(pt.activeTexture.set(At.TEXTURE1),pt.pixelStoreUnpackPremultiplyAlpha.set(!1),R.demTexture=R.demTexture||Ue.getTileTexture(wr),R.demTexture){let sa=R.demTexture;sa.update(Tr,{premultiply:!1}),sa.bind(At.NEAREST,At.CLAMP_TO_EDGE)}else R.demTexture=new u(pt,Tr,At.RGBA,{premultiply:!1}),R.demTexture.bind(At.NEAREST,At.CLAMP_TO_EDGE);pt.activeTexture.set(At.TEXTURE0);let Kr=R.fbo;if(!Kr){let sa=new u(pt,{width:$t,height:$t,data:null},At.RGBA);sa.bind(At.LINEAR,At.CLAMP_TO_EDGE),Kr=R.fbo=pt.createFramebuffer($t,$t,!0,!1),Kr.colorAttachment.set(sa.texture)}pt.bindFramebuffer.set(Kr.framebuffer),pt.viewport.set([0,0,$t,$t]),Ue.useProgram("hillshadePrepare").draw(pt,At.TRIANGLES,we,Ae,Be,eo.disabled,((sa,He)=>{let Je=He.stride,lt=t.H();return t.aP(lt,0,t.X,-t.X,0,0,1),t.J(lt,lt,[0,-t.X,0]),{u_matrix:lt,u_image:1,u_dimension:[Je,Je],u_zoom:sa.overscaledZ,u_unpack:He.getUnpackVector()}})(R.tileID,Nt),null,ae.id,Ue.rasterBoundsBuffer,Ue.quadTriangleIndexBuffer,Ue.rasterBoundsSegments),R.needsHillshadePrepare=!1}}function qc(Ue,R,ae,we,Ae,Be){let pt=we.paint.get("raster-fade-duration");if(!Be&&pt>0){let At=n.now(),Nt=(At-Ue.timeAdded)/pt,$t=R?(At-R.timeAdded)/pt:-1,wr=ae.getSource(),Tr=Ae.coveringZoomLevel({tileSize:wr.tileSize,roundZoom:wr.roundZoom}),Kr=!R||Math.abs(R.tileID.overscaledZ-Tr)>Math.abs(Ue.tileID.overscaledZ-Tr),sa=Kr&&Ue.refreshedUponExpiration?1:t.ac(Kr?Nt:1-$t,0,1);return Ue.refreshedUponExpiration&&Nt>=1&&(Ue.refreshedUponExpiration=!1),R?{opacity:1,mix:1-sa}:{opacity:sa,mix:0}}return{opacity:1,mix:0}}let Sc=new t.aM(1,0,0,1),Ws=new t.aM(0,1,0,1),kf=new t.aM(0,0,1,1),uh=new t.aM(1,0,1,1),Uf=new t.aM(0,1,1,1);function Xc(Ue,R,ae,we){Cu(Ue,0,R+ae/2,Ue.transform.width,ae,we)}function $f(Ue,R,ae,we){Cu(Ue,R-ae/2,0,ae,Ue.transform.height,we)}function Cu(Ue,R,ae,we,Ae,Be){let pt=Ue.context,At=pt.gl;At.enable(At.SCISSOR_TEST),At.scissor(R*Ue.pixelRatio,ae*Ue.pixelRatio,we*Ue.pixelRatio,Ae*Ue.pixelRatio),pt.clear({color:Be}),At.disable(At.SCISSOR_TEST)}function jf(Ue,R,ae){let we=Ue.context,Ae=we.gl,Be=ae.posMatrix,pt=Ue.useProgram("debug"),At=ls.disabled,Nt=Ms.disabled,$t=Ue.colorModeForRenderPass(),wr="$debug",Tr=Ue.style.map.terrain&&Ue.style.map.terrain.getTerrainData(ae);we.activeTexture.set(Ae.TEXTURE0);let Kr=R.getTileByID(ae.key).latestRawTileData,sa=Math.floor((Kr&&Kr.byteLength||0)/1024),He=R.getTile(ae).tileSize,Je=512/Math.min(He,512)*(ae.overscaledZ/Ue.transform.zoom)*.5,lt=ae.canonical.toString();ae.overscaledZ!==ae.canonical.z&&(lt+=` => ${ae.overscaledZ}`),function(dt,Ct){dt.initDebugOverlayCanvas();let Tt=dt.debugOverlayCanvas,zt=dt.context.gl,ur=dt.debugOverlayCanvas.getContext("2d");ur.clearRect(0,0,Tt.width,Tt.height),ur.shadowColor="white",ur.shadowBlur=2,ur.lineWidth=1.5,ur.strokeStyle="white",ur.textBaseline="top",ur.font="bold 36px Open Sans, sans-serif",ur.fillText(Ct,5,5),ur.strokeText(Ct,5,5),dt.debugOverlayTexture.update(Tt),dt.debugOverlayTexture.bind(zt.LINEAR,zt.CLAMP_TO_EDGE)}(Ue,`${lt} ${sa}kB`),pt.draw(we,Ae.TRIANGLES,At,Nt,cl.alphaBlended,eo.disabled,In(Be,t.aM.transparent,Je),null,wr,Ue.debugBuffer,Ue.quadTriangleIndexBuffer,Ue.debugSegments),pt.draw(we,Ae.LINE_STRIP,At,Nt,$t,eo.disabled,In(Be,t.aM.red),Tr,wr,Ue.debugBuffer,Ue.tileBorderIndexBuffer,Ue.debugSegments)}function ml(Ue,R,ae){let we=Ue.context,Ae=we.gl,Be=Ue.colorModeForRenderPass(),pt=new ls(Ae.LEQUAL,ls.ReadWrite,Ue.depthRangeFor3D),At=Ue.useProgram("terrain"),Nt=R.getTerrainMesh();we.bindFramebuffer.set(null),we.viewport.set([0,0,Ue.width,Ue.height]);for(let $t of ae){let wr=Ue.renderToTexture.getTexture($t),Tr=R.getTerrainData($t.tileID);we.activeTexture.set(Ae.TEXTURE0),Ae.bindTexture(Ae.TEXTURE_2D,wr.texture);let Kr=Ue.transform.calculatePosMatrix($t.tileID.toUnwrapped()),sa=R.getMeshFrameDelta(Ue.transform.zoom),He=Ue.transform.calculateFogMatrix($t.tileID.toUnwrapped()),Je=Cr(Kr,sa,He,Ue.style.sky,Ue.transform.pitch);At.draw(we,Ae.TRIANGLES,pt,Ms.disabled,Be,eo.backCCW,Je,Tr,"terrain",Nt.vertexBuffer,Nt.indexBuffer,Nt.segments)}}class Lu{constructor(R,ae,we){this.vertexBuffer=R,this.indexBuffer=ae,this.segments=we}destroy(){this.vertexBuffer.destroy(),this.indexBuffer.destroy(),this.segments.destroy(),this.vertexBuffer=null,this.indexBuffer=null,this.segments=null}}class Mc{constructor(R,ae){this.context=new _h(R),this.transform=ae,this._tileTextures={},this.terrainFacilitator={dirty:!0,matrix:t.an(new Float64Array(16)),renderTime:0},this.setup(),this.numSublayers=Lt.maxUnderzooming+Lt.maxOverzooming+1,this.depthEpsilon=1/Math.pow(2,16),this.crossTileSymbolIndex=new Rr}resize(R,ae,we){if(this.width=Math.floor(R*we),this.height=Math.floor(ae*we),this.pixelRatio=we,this.context.viewport.set([0,0,this.width,this.height]),this.style)for(let Ae of this.style._order)this.style._layers[Ae].resize()}setup(){let R=this.context,ae=new t.aX;ae.emplaceBack(0,0),ae.emplaceBack(t.X,0),ae.emplaceBack(0,t.X),ae.emplaceBack(t.X,t.X),this.tileExtentBuffer=R.createVertexBuffer(ae,ra.members),this.tileExtentSegments=t.a0.simpleSegment(0,0,4,2);let we=new t.aX;we.emplaceBack(0,0),we.emplaceBack(t.X,0),we.emplaceBack(0,t.X),we.emplaceBack(t.X,t.X),this.debugBuffer=R.createVertexBuffer(we,ra.members),this.debugSegments=t.a0.simpleSegment(0,0,4,5);let Ae=new t.$;Ae.emplaceBack(0,0,0,0),Ae.emplaceBack(t.X,0,t.X,0),Ae.emplaceBack(0,t.X,0,t.X),Ae.emplaceBack(t.X,t.X,t.X,t.X),this.rasterBoundsBuffer=R.createVertexBuffer(Ae,Ze.members),this.rasterBoundsSegments=t.a0.simpleSegment(0,0,4,2);let Be=new t.aX;Be.emplaceBack(0,0),Be.emplaceBack(1,0),Be.emplaceBack(0,1),Be.emplaceBack(1,1),this.viewportBuffer=R.createVertexBuffer(Be,ra.members),this.viewportSegments=t.a0.simpleSegment(0,0,4,2);let pt=new t.aZ;pt.emplaceBack(0),pt.emplaceBack(1),pt.emplaceBack(3),pt.emplaceBack(2),pt.emplaceBack(0),this.tileBorderIndexBuffer=R.createIndexBuffer(pt);let At=new t.aY;At.emplaceBack(0,1,2),At.emplaceBack(2,1,3),this.quadTriangleIndexBuffer=R.createIndexBuffer(At);let Nt=this.context.gl;this.stencilClearMode=new Ms({func:Nt.ALWAYS,mask:0},0,255,Nt.ZERO,Nt.ZERO,Nt.ZERO)}clearStencil(){let R=this.context,ae=R.gl;this.nextStencilID=1,this.currentStencilSource=void 0;let we=t.H();t.aP(we,0,this.width,this.height,0,0,1),t.K(we,we,[ae.drawingBufferWidth,ae.drawingBufferHeight,0]),this.useProgram("clippingMask").draw(R,ae.TRIANGLES,ls.disabled,this.stencilClearMode,cl.disabled,eo.disabled,Hn(we),null,"$clipping",this.viewportBuffer,this.quadTriangleIndexBuffer,this.viewportSegments)}_renderTileClippingMasks(R,ae){if(this.currentStencilSource===R.source||!R.isTileClipped()||!ae||!ae.length)return;this.currentStencilSource=R.source;let we=this.context,Ae=we.gl;this.nextStencilID+ae.length>256&&this.clearStencil(),we.setColorMode(cl.disabled),we.setDepthMode(ls.disabled);let Be=this.useProgram("clippingMask");this._tileClippingMaskIDs={};for(let pt of ae){let At=this._tileClippingMaskIDs[pt.key]=this.nextStencilID++,Nt=this.style.map.terrain&&this.style.map.terrain.getTerrainData(pt);Be.draw(we,Ae.TRIANGLES,ls.disabled,new Ms({func:Ae.ALWAYS,mask:0},At,255,Ae.KEEP,Ae.KEEP,Ae.REPLACE),cl.disabled,eo.disabled,Hn(pt.posMatrix),Nt,"$clipping",this.tileExtentBuffer,this.quadTriangleIndexBuffer,this.tileExtentSegments)}}stencilModeFor3D(){this.currentStencilSource=void 0,this.nextStencilID+1>256&&this.clearStencil();let R=this.nextStencilID++,ae=this.context.gl;return new Ms({func:ae.NOTEQUAL,mask:255},R,255,ae.KEEP,ae.KEEP,ae.REPLACE)}stencilModeForClipping(R){let ae=this.context.gl;return new Ms({func:ae.EQUAL,mask:255},this._tileClippingMaskIDs[R.key],0,ae.KEEP,ae.KEEP,ae.REPLACE)}stencilConfigForOverlap(R){let ae=this.context.gl,we=R.sort((pt,At)=>At.overscaledZ-pt.overscaledZ),Ae=we[we.length-1].overscaledZ,Be=we[0].overscaledZ-Ae+1;if(Be>1){this.currentStencilSource=void 0,this.nextStencilID+Be>256&&this.clearStencil();let pt={};for(let At=0;At({u_sky_color:dt.properties.get("sky-color"),u_horizon_color:dt.properties.get("horizon-color"),u_horizon:(Ct.height/2+Ct.getHorizon())*Tt,u_sky_horizon_blend:dt.properties.get("sky-horizon-blend")*Ct.height/2*Tt}))($t,Nt.style.map.transform,Nt.pixelRatio),sa=new ls(Tr.LEQUAL,ls.ReadWrite,[0,1]),He=Ms.disabled,Je=Nt.colorModeForRenderPass(),lt=Nt.useProgram("sky");if(!$t.mesh){let dt=new t.aX;dt.emplaceBack(-1,-1),dt.emplaceBack(1,-1),dt.emplaceBack(1,1),dt.emplaceBack(-1,1);let Ct=new t.aY;Ct.emplaceBack(0,1,2),Ct.emplaceBack(0,2,3),$t.mesh=new Lu(wr.createVertexBuffer(dt,ra.members),wr.createIndexBuffer(Ct),t.a0.simpleSegment(0,0,dt.length,Ct.length))}lt.draw(wr,Tr.TRIANGLES,sa,He,Je,eo.disabled,Kr,void 0,"sky",$t.mesh.vertexBuffer,$t.mesh.indexBuffer,$t.mesh.segments)}(this,this.style.sky),this._showOverdrawInspector=ae.showOverdrawInspector,this.depthRangeFor3D=[0,1-(R._order.length+2)*this.numSublayers*this.depthEpsilon],!this.renderToTexture)for(this.renderPass="opaque",this.currentLayer=we.length-1;this.currentLayer>=0;this.currentLayer--){let Nt=this.style._layers[we[this.currentLayer]],$t=Ae[Nt.source],wr=Be[Nt.source];this._renderTileClippingMasks(Nt,wr),this.renderLayer(this,$t,Nt,wr)}for(this.renderPass="translucent",this.currentLayer=0;this.currentLayerlt.source&&!lt.isHidden(wr)?[$t.sourceCaches[lt.source]]:[]),sa=Kr.filter(lt=>lt.getSource().type==="vector"),He=Kr.filter(lt=>lt.getSource().type!=="vector"),Je=lt=>{(!Tr||Tr.getSource().maxzoomJe(lt)),Tr||He.forEach(lt=>Je(lt)),Tr}(this.style,this.transform.zoom);Nt&&function($t,wr,Tr){for(let Kr=0;Kr0),Ae&&(t.b0(ae,we),this.terrainFacilitator.renderTime=Date.now(),this.terrainFacilitator.dirty=!1,function(Be,pt){let At=Be.context,Nt=At.gl,$t=cl.unblended,wr=new ls(Nt.LEQUAL,ls.ReadWrite,[0,1]),Tr=pt.getTerrainMesh(),Kr=pt.sourceCache.getRenderableTiles(),sa=Be.useProgram("terrainDepth");At.bindFramebuffer.set(pt.getFramebuffer("depth").framebuffer),At.viewport.set([0,0,Be.width/devicePixelRatio,Be.height/devicePixelRatio]),At.clear({color:t.aM.transparent,depth:1});for(let He of Kr){let Je=pt.getTerrainData(He.tileID),lt={u_matrix:Be.transform.calculatePosMatrix(He.tileID.toUnwrapped()),u_ele_delta:pt.getMeshFrameDelta(Be.transform.zoom)};sa.draw(At,Nt.TRIANGLES,wr,Ms.disabled,$t,eo.backCCW,lt,Je,"terrain",Tr.vertexBuffer,Tr.indexBuffer,Tr.segments)}At.bindFramebuffer.set(null),At.viewport.set([0,0,Be.width,Be.height])}(this,this.style.map.terrain),function(Be,pt){let At=Be.context,Nt=At.gl,$t=cl.unblended,wr=new ls(Nt.LEQUAL,ls.ReadWrite,[0,1]),Tr=pt.getTerrainMesh(),Kr=pt.getCoordsTexture(),sa=pt.sourceCache.getRenderableTiles(),He=Be.useProgram("terrainCoords");At.bindFramebuffer.set(pt.getFramebuffer("coords").framebuffer),At.viewport.set([0,0,Be.width/devicePixelRatio,Be.height/devicePixelRatio]),At.clear({color:t.aM.transparent,depth:1}),pt.coordsIndex=[];for(let Je of sa){let lt=pt.getTerrainData(Je.tileID);At.activeTexture.set(Nt.TEXTURE0),Nt.bindTexture(Nt.TEXTURE_2D,Kr.texture);let dt={u_matrix:Be.transform.calculatePosMatrix(Je.tileID.toUnwrapped()),u_terrain_coords_id:(255-pt.coordsIndex.length)/255,u_texture:0,u_ele_delta:pt.getMeshFrameDelta(Be.transform.zoom)};He.draw(At,Nt.TRIANGLES,wr,Ms.disabled,$t,eo.backCCW,dt,lt,"terrain",Tr.vertexBuffer,Tr.indexBuffer,Tr.segments),pt.coordsIndex.push(Je.tileID.key)}At.bindFramebuffer.set(null),At.viewport.set([0,0,Be.width,Be.height])}(this,this.style.map.terrain))}renderLayer(R,ae,we,Ae){if(!we.isHidden(this.transform.zoom)&&(we.type==="background"||we.type==="custom"||(Ae||[]).length))switch(this.id=we.id,we.type){case"symbol":(function(Be,pt,At,Nt,$t){if(Be.renderPass!=="translucent")return;let wr=Ms.disabled,Tr=Be.colorModeForRenderPass();(At._unevaluatedLayout.hasValue("text-variable-anchor")||At._unevaluatedLayout.hasValue("text-variable-anchor-offset"))&&function(Kr,sa,He,Je,lt,dt,Ct,Tt,zt){let ur=sa.transform,mr=mi(),Er=lt==="map",Ur=dt==="map";for(let Qr of Kr){let da=Je.getTile(Qr),wa=da.getBucket(He);if(!wa||!wa.text||!wa.text.segments.get().length)continue;let Fa=t.ag(wa.textSizeData,ur.zoom),fi=za(da,1,sa.transform.zoom),Vi=br(Qr.posMatrix,Ur,Er,sa.transform,fi),ji=He.layout.get("icon-text-fit")!=="none"&&wa.hasIconData();if(Fa){let nn=Math.pow(2,ur.zoom-da.tileID.overscaledZ),Sn=sa.style.map.terrain?(On,To)=>sa.style.map.terrain.getElevation(Qr,On,To):null,Zn=mr.translatePosition(ur,da,Ct,Tt);af(wa,Er,Ur,zt,ur,Vi,Qr.posMatrix,nn,Fa,ji,mr,Zn,Qr.toUnwrapped(),Sn)}}}(Nt,Be,At,pt,At.layout.get("text-rotation-alignment"),At.layout.get("text-pitch-alignment"),At.paint.get("text-translate"),At.paint.get("text-translate-anchor"),$t),At.paint.get("icon-opacity").constantOr(1)!==0&&Jf(Be,pt,At,Nt,!1,At.paint.get("icon-translate"),At.paint.get("icon-translate-anchor"),At.layout.get("icon-rotation-alignment"),At.layout.get("icon-pitch-alignment"),At.layout.get("icon-keep-upright"),wr,Tr),At.paint.get("text-opacity").constantOr(1)!==0&&Jf(Be,pt,At,Nt,!0,At.paint.get("text-translate"),At.paint.get("text-translate-anchor"),At.layout.get("text-rotation-alignment"),At.layout.get("text-pitch-alignment"),At.layout.get("text-keep-upright"),wr,Tr),pt.map.showCollisionBoxes&&(Vu(Be,pt,At,Nt,!0),Vu(Be,pt,At,Nt,!1))})(R,ae,we,Ae,this.style.placement.variableOffsets);break;case"circle":(function(Be,pt,At,Nt){if(Be.renderPass!=="translucent")return;let $t=At.paint.get("circle-opacity"),wr=At.paint.get("circle-stroke-width"),Tr=At.paint.get("circle-stroke-opacity"),Kr=!At.layout.get("circle-sort-key").isConstant();if($t.constantOr(1)===0&&(wr.constantOr(1)===0||Tr.constantOr(1)===0))return;let sa=Be.context,He=sa.gl,Je=Be.depthModeForSublayer(0,ls.ReadOnly),lt=Ms.disabled,dt=Be.colorModeForRenderPass(),Ct=[];for(let Tt=0;TtTt.sortKey-zt.sortKey);for(let Tt of Ct){let{programConfiguration:zt,program:ur,layoutVertexBuffer:mr,indexBuffer:Er,uniformValues:Ur,terrainData:Qr}=Tt.state;ur.draw(sa,He.TRIANGLES,Je,lt,dt,eo.disabled,Ur,Qr,At.id,mr,Er,Tt.segments,At.paint,Be.transform.zoom,zt)}})(R,ae,we,Ae);break;case"heatmap":(function(Be,pt,At,Nt){if(At.paint.get("heatmap-opacity")===0)return;let $t=Be.context;if(Be.style.map.terrain){for(let wr of Nt){let Tr=pt.getTile(wr);pt.hasRenderableParent(wr)||(Be.renderPass==="offscreen"?nf(Be,Tr,At,wr):Be.renderPass==="translucent"&&jc(Be,At,wr))}$t.viewport.set([0,0,Be.width,Be.height])}else Be.renderPass==="offscreen"?function(wr,Tr,Kr,sa){let He=wr.context,Je=He.gl,lt=Ms.disabled,dt=new cl([Je.ONE,Je.ONE],t.aM.transparent,[!0,!0,!0,!0]);(function(Ct,Tt,zt){let ur=Ct.gl;Ct.activeTexture.set(ur.TEXTURE1),Ct.viewport.set([0,0,Tt.width/4,Tt.height/4]);let mr=zt.heatmapFbos.get(t.aU);mr?(ur.bindTexture(ur.TEXTURE_2D,mr.colorAttachment.get()),Ct.bindFramebuffer.set(mr.framebuffer)):(mr=Bf(Ct,Tt.width/4,Tt.height/4),zt.heatmapFbos.set(t.aU,mr))})(He,wr,Kr),He.clear({color:t.aM.transparent});for(let Ct=0;Ct20&&wr.texParameterf(wr.TEXTURE_2D,$t.extTextureFilterAnisotropic.TEXTURE_MAX_ANISOTROPY_EXT,$t.extTextureFilterAnisotropicMax);let wa=Be.style.map.terrain&&Be.style.map.terrain.getTerrainData(Ct),Fa=wa?Ct:null,fi=Fa?Fa.posMatrix:Be.transform.calculatePosMatrix(Ct.toUnwrapped(),dt),Vi=gs(fi,Qr||[0,0],Ur||1,Er,At);Tr instanceof at?Kr.draw($t,wr.TRIANGLES,Tt,Ms.disabled,sa,eo.disabled,Vi,wa,At.id,Tr.boundsBuffer,Be.quadTriangleIndexBuffer,Tr.boundsSegments):Kr.draw($t,wr.TRIANGLES,Tt,He[Ct.overscaledZ],sa,eo.disabled,Vi,wa,At.id,Be.rasterBoundsBuffer,Be.quadTriangleIndexBuffer,Be.rasterBoundsSegments)}})(R,ae,we,Ae);break;case"background":(function(Be,pt,At,Nt){let $t=At.paint.get("background-color"),wr=At.paint.get("background-opacity");if(wr===0)return;let Tr=Be.context,Kr=Tr.gl,sa=Be.transform,He=sa.tileSize,Je=At.paint.get("background-pattern");if(Be.isPatternMissing(Je))return;let lt=!Je&&$t.a===1&&wr===1&&Be.opaquePassEnabledForLayer()?"opaque":"translucent";if(Be.renderPass!==lt)return;let dt=Ms.disabled,Ct=Be.depthModeForSublayer(0,lt==="opaque"?ls.ReadWrite:ls.ReadOnly),Tt=Be.colorModeForRenderPass(),zt=Be.useProgram(Je?"backgroundPattern":"background"),ur=Nt||sa.coveringTiles({tileSize:He,terrain:Be.style.map.terrain});Je&&(Tr.activeTexture.set(Kr.TEXTURE0),Be.imageManager.bind(Be.context));let mr=At.getCrossfadeParameters();for(let Er of ur){let Ur=Nt?Er.posMatrix:Be.transform.calculatePosMatrix(Er.toUnwrapped()),Qr=Je?Bs(Ur,wr,Be,Je,{tileID:Er,tileSize:He},mr):ys(Ur,wr,$t),da=Be.style.map.terrain&&Be.style.map.terrain.getTerrainData(Er);zt.draw(Tr,Kr.TRIANGLES,Ct,dt,Tt,eo.disabled,Qr,da,At.id,Be.tileExtentBuffer,Be.quadTriangleIndexBuffer,Be.tileExtentSegments)}})(R,0,we,Ae);break;case"custom":(function(Be,pt,At){let Nt=Be.context,$t=At.implementation;if(Be.renderPass==="offscreen"){let wr=$t.prerender;wr&&(Be.setCustomLayerDefaults(),Nt.setColorMode(Be.colorModeForRenderPass()),wr.call($t,Nt.gl,Be.transform.customLayerMatrix()),Nt.setDirty(),Be.setBaseState())}else if(Be.renderPass==="translucent"){Be.setCustomLayerDefaults(),Nt.setColorMode(Be.colorModeForRenderPass()),Nt.setStencilMode(Ms.disabled);let wr=$t.renderingMode==="3d"?new ls(Be.context.gl.LEQUAL,ls.ReadWrite,Be.depthRangeFor3D):Be.depthModeForSublayer(0,ls.ReadOnly);Nt.setDepthMode(wr),$t.render(Nt.gl,Be.transform.customLayerMatrix(),{farZ:Be.transform.farZ,nearZ:Be.transform.nearZ,fov:Be.transform._fov,modelViewProjectionMatrix:Be.transform.modelViewProjectionMatrix,projectionMatrix:Be.transform.projectionMatrix}),Nt.setDirty(),Be.setBaseState(),Nt.bindFramebuffer.set(null)}})(R,0,we)}}translatePosMatrix(R,ae,we,Ae,Be){if(!we[0]&&!we[1])return R;let pt=Be?Ae==="map"?this.transform.angle:0:Ae==="viewport"?-this.transform.angle:0;if(pt){let $t=Math.sin(pt),wr=Math.cos(pt);we=[we[0]*wr-we[1]*$t,we[0]*$t+we[1]*wr]}let At=[Be?we[0]:za(ae,we[0],this.transform.zoom),Be?we[1]:za(ae,we[1],this.transform.zoom),0],Nt=new Float32Array(16);return t.J(Nt,R,At),Nt}saveTileTexture(R){let ae=this._tileTextures[R.size[0]];ae?ae.push(R):this._tileTextures[R.size[0]]=[R]}getTileTexture(R){let ae=this._tileTextures[R];return ae&&ae.length>0?ae.pop():null}isPatternMissing(R){if(!R)return!1;if(!R.from||!R.to)return!0;let ae=this.imageManager.getPattern(R.from.toString()),we=this.imageManager.getPattern(R.to.toString());return!ae||!we}useProgram(R,ae){this.cache=this.cache||{};let we=R+(ae?ae.cacheKey:"")+(this._showOverdrawInspector?"/overdraw":"")+(this.style.map.terrain?"/terrain":"");return this.cache[we]||(this.cache[we]=new Ta(this.context,Gr[R],ae,js[R],this._showOverdrawInspector,this.style.map.terrain)),this.cache[we]}setCustomLayerDefaults(){this.context.unbindVAO(),this.context.cullFace.setDefault(),this.context.activeTexture.setDefault(),this.context.pixelStoreUnpack.setDefault(),this.context.pixelStoreUnpackPremultiplyAlpha.setDefault(),this.context.pixelStoreUnpackFlipY.setDefault()}setBaseState(){let R=this.context.gl;this.context.cullFace.set(!1),this.context.viewport.set([0,0,this.width,this.height]),this.context.blendEquation.set(R.FUNC_ADD)}initDebugOverlayCanvas(){this.debugOverlayCanvas==null&&(this.debugOverlayCanvas=document.createElement("canvas"),this.debugOverlayCanvas.width=512,this.debugOverlayCanvas.height=512,this.debugOverlayTexture=new u(this.context,this.debugOverlayCanvas,this.context.gl.RGBA))}destroy(){this.debugOverlayTexture&&this.debugOverlayTexture.destroy()}overLimit(){let{drawingBufferWidth:R,drawingBufferHeight:ae}=this.context.gl;return this.width!==R||this.height!==ae}}class il{constructor(R,ae){this.points=R,this.planes=ae}static fromInvProjectionMatrix(R,ae,we){let Ae=Math.pow(2,we),Be=[[-1,1,-1,1],[1,1,-1,1],[1,-1,-1,1],[-1,-1,-1,1],[-1,1,1,1],[1,1,1,1],[1,-1,1,1],[-1,-1,1,1]].map(At=>{let Nt=1/(At=t.af([],At,R))[3]/ae*Ae;return t.b1(At,At,[Nt,Nt,1/At[3],Nt])}),pt=[[0,1,2],[6,5,4],[0,3,7],[2,1,5],[3,2,6],[0,4,5]].map(At=>{let Nt=function(Kr,sa){var He=sa[0],Je=sa[1],lt=sa[2],dt=He*He+Je*Je+lt*lt;return dt>0&&(dt=1/Math.sqrt(dt)),Kr[0]=sa[0]*dt,Kr[1]=sa[1]*dt,Kr[2]=sa[2]*dt,Kr}([],function(Kr,sa,He){var Je=sa[0],lt=sa[1],dt=sa[2],Ct=He[0],Tt=He[1],zt=He[2];return Kr[0]=lt*zt-dt*Tt,Kr[1]=dt*Ct-Je*zt,Kr[2]=Je*Tt-lt*Ct,Kr}([],M([],Be[At[0]],Be[At[1]]),M([],Be[At[2]],Be[At[1]]))),$t=-((wr=Nt)[0]*(Tr=Be[At[1]])[0]+wr[1]*Tr[1]+wr[2]*Tr[2]);var wr,Tr;return Nt.concat($t)});return new il(Be,pt)}}class mc{constructor(R,ae){this.min=R,this.max=ae,this.center=function(we,Ae,Be){return we[0]=.5*Ae[0],we[1]=.5*Ae[1],we[2]=.5*Ae[2],we}([],function(we,Ae,Be){return we[0]=Ae[0]+Be[0],we[1]=Ae[1]+Be[1],we[2]=Ae[2]+Be[2],we}([],this.min,this.max))}quadrant(R){let ae=[R%2==0,R<2],we=w(this.min),Ae=w(this.max);for(let Be=0;Be=0&&pt++;if(pt===0)return 0;pt!==ae.length&&(we=!1)}if(we)return 2;for(let Ae=0;Ae<3;Ae++){let Be=Number.MAX_VALUE,pt=-Number.MAX_VALUE;for(let At=0;Atthis.max[Ae]-this.min[Ae])return 0}return 1}}class mu{constructor(R=0,ae=0,we=0,Ae=0){if(isNaN(R)||R<0||isNaN(ae)||ae<0||isNaN(we)||we<0||isNaN(Ae)||Ae<0)throw new Error("Invalid value for edge-insets, top, bottom, left and right must all be numbers");this.top=R,this.bottom=ae,this.left=we,this.right=Ae}interpolate(R,ae,we){return ae.top!=null&&R.top!=null&&(this.top=t.y.number(R.top,ae.top,we)),ae.bottom!=null&&R.bottom!=null&&(this.bottom=t.y.number(R.bottom,ae.bottom,we)),ae.left!=null&&R.left!=null&&(this.left=t.y.number(R.left,ae.left,we)),ae.right!=null&&R.right!=null&&(this.right=t.y.number(R.right,ae.right,we)),this}getCenter(R,ae){let we=t.ac((this.left+R-this.right)/2,0,R),Ae=t.ac((this.top+ae-this.bottom)/2,0,ae);return new t.P(we,Ae)}equals(R){return this.top===R.top&&this.bottom===R.bottom&&this.left===R.left&&this.right===R.right}clone(){return new mu(this.top,this.bottom,this.left,this.right)}toJSON(){return{top:this.top,bottom:this.bottom,left:this.left,right:this.right}}}let wu=85.051129;class kl{constructor(R,ae,we,Ae,Be){this.tileSize=512,this._renderWorldCopies=Be===void 0||!!Be,this._minZoom=R||0,this._maxZoom=ae||22,this._minPitch=we??0,this._maxPitch=Ae??60,this.setMaxBounds(),this.width=0,this.height=0,this._center=new t.N(0,0),this._elevation=0,this.zoom=0,this.angle=0,this._fov=.6435011087932844,this._pitch=0,this._unmodified=!0,this._edgeInsets=new mu,this._posMatrixCache={},this._alignedPosMatrixCache={},this._fogMatrixCache={},this.minElevationForCurrentTile=0}clone(){let R=new kl(this._minZoom,this._maxZoom,this._minPitch,this.maxPitch,this._renderWorldCopies);return R.apply(this),R}apply(R){this.tileSize=R.tileSize,this.latRange=R.latRange,this.lngRange=R.lngRange,this.width=R.width,this.height=R.height,this._center=R._center,this._elevation=R._elevation,this.minElevationForCurrentTile=R.minElevationForCurrentTile,this.zoom=R.zoom,this.angle=R.angle,this._fov=R._fov,this._pitch=R._pitch,this._unmodified=R._unmodified,this._edgeInsets=R._edgeInsets.clone(),this._calcMatrices()}get minZoom(){return this._minZoom}set minZoom(R){this._minZoom!==R&&(this._minZoom=R,this.zoom=Math.max(this.zoom,R))}get maxZoom(){return this._maxZoom}set maxZoom(R){this._maxZoom!==R&&(this._maxZoom=R,this.zoom=Math.min(this.zoom,R))}get minPitch(){return this._minPitch}set minPitch(R){this._minPitch!==R&&(this._minPitch=R,this.pitch=Math.max(this.pitch,R))}get maxPitch(){return this._maxPitch}set maxPitch(R){this._maxPitch!==R&&(this._maxPitch=R,this.pitch=Math.min(this.pitch,R))}get renderWorldCopies(){return this._renderWorldCopies}set renderWorldCopies(R){R===void 0?R=!0:R===null&&(R=!1),this._renderWorldCopies=R}get worldSize(){return this.tileSize*this.scale}get centerOffset(){return this.centerPoint._sub(this.size._div(2))}get size(){return new t.P(this.width,this.height)}get bearing(){return-this.angle/Math.PI*180}set bearing(R){let ae=-t.b3(R,-180,180)*Math.PI/180;this.angle!==ae&&(this._unmodified=!1,this.angle=ae,this._calcMatrices(),this.rotationMatrix=function(){var we=new t.A(4);return t.A!=Float32Array&&(we[1]=0,we[2]=0),we[0]=1,we[3]=1,we}(),function(we,Ae,Be){var pt=Ae[0],At=Ae[1],Nt=Ae[2],$t=Ae[3],wr=Math.sin(Be),Tr=Math.cos(Be);we[0]=pt*Tr+Nt*wr,we[1]=At*Tr+$t*wr,we[2]=pt*-wr+Nt*Tr,we[3]=At*-wr+$t*Tr}(this.rotationMatrix,this.rotationMatrix,this.angle))}get pitch(){return this._pitch/Math.PI*180}set pitch(R){let ae=t.ac(R,this.minPitch,this.maxPitch)/180*Math.PI;this._pitch!==ae&&(this._unmodified=!1,this._pitch=ae,this._calcMatrices())}get fov(){return this._fov/Math.PI*180}set fov(R){R=Math.max(.01,Math.min(60,R)),this._fov!==R&&(this._unmodified=!1,this._fov=R/180*Math.PI,this._calcMatrices())}get zoom(){return this._zoom}set zoom(R){let ae=Math.min(Math.max(R,this.minZoom),this.maxZoom);this._zoom!==ae&&(this._unmodified=!1,this._zoom=ae,this.tileZoom=Math.max(0,Math.floor(ae)),this.scale=this.zoomScale(ae),this._constrain(),this._calcMatrices())}get center(){return this._center}set center(R){R.lat===this._center.lat&&R.lng===this._center.lng||(this._unmodified=!1,this._center=R,this._constrain(),this._calcMatrices())}get elevation(){return this._elevation}set elevation(R){R!==this._elevation&&(this._elevation=R,this._constrain(),this._calcMatrices())}get padding(){return this._edgeInsets.toJSON()}set padding(R){this._edgeInsets.equals(R)||(this._unmodified=!1,this._edgeInsets.interpolate(this._edgeInsets,R,1),this._calcMatrices())}get centerPoint(){return this._edgeInsets.getCenter(this.width,this.height)}isPaddingEqual(R){return this._edgeInsets.equals(R)}interpolatePadding(R,ae,we){this._unmodified=!1,this._edgeInsets.interpolate(R,ae,we),this._constrain(),this._calcMatrices()}coveringZoomLevel(R){let ae=(R.roundZoom?Math.round:Math.floor)(this.zoom+this.scaleZoom(this.tileSize/R.tileSize));return Math.max(0,ae)}getVisibleUnwrappedCoordinates(R){let ae=[new t.b4(0,R)];if(this._renderWorldCopies){let we=this.pointCoordinate(new t.P(0,0)),Ae=this.pointCoordinate(new t.P(this.width,0)),Be=this.pointCoordinate(new t.P(this.width,this.height)),pt=this.pointCoordinate(new t.P(0,this.height)),At=Math.floor(Math.min(we.x,Ae.x,Be.x,pt.x)),Nt=Math.floor(Math.max(we.x,Ae.x,Be.x,pt.x)),$t=1;for(let wr=At-$t;wr<=Nt+$t;wr++)wr!==0&&ae.push(new t.b4(wr,R))}return ae}coveringTiles(R){var ae,we;let Ae=this.coveringZoomLevel(R),Be=Ae;if(R.minzoom!==void 0&&AeR.maxzoom&&(Ae=R.maxzoom);let pt=this.pointCoordinate(this.getCameraPoint()),At=t.Z.fromLngLat(this.center),Nt=Math.pow(2,Ae),$t=[Nt*pt.x,Nt*pt.y,0],wr=[Nt*At.x,Nt*At.y,0],Tr=il.fromInvProjectionMatrix(this.invModelViewProjectionMatrix,this.worldSize,Ae),Kr=R.minzoom||0;!R.terrain&&this.pitch<=60&&this._edgeInsets.top<.1&&(Kr=Ae);let sa=R.terrain?2/Math.min(this.tileSize,R.tileSize)*this.tileSize:3,He=Tt=>({aabb:new mc([Tt*Nt,0,0],[(Tt+1)*Nt,Nt,0]),zoom:0,x:0,y:0,wrap:Tt,fullyVisible:!1}),Je=[],lt=[],dt=Ae,Ct=R.reparseOverscaled?Be:Ae;if(this._renderWorldCopies)for(let Tt=1;Tt<=3;Tt++)Je.push(He(-Tt)),Je.push(He(Tt));for(Je.push(He(0));Je.length>0;){let Tt=Je.pop(),zt=Tt.x,ur=Tt.y,mr=Tt.fullyVisible;if(!mr){let wa=Tt.aabb.intersects(Tr);if(wa===0)continue;mr=wa===2}let Er=R.terrain?$t:wr,Ur=Tt.aabb.distanceX(Er),Qr=Tt.aabb.distanceY(Er),da=Math.max(Math.abs(Ur),Math.abs(Qr));if(Tt.zoom===dt||da>sa+(1<=Kr){let wa=dt-Tt.zoom,Fa=$t[0]-.5-(zt<>1),Vi=Tt.zoom+1,ji=Tt.aabb.quadrant(wa);if(R.terrain){let nn=new t.S(Vi,Tt.wrap,Vi,Fa,fi),Sn=R.terrain.getMinMaxElevation(nn),Zn=(ae=Sn.minElevation)!==null&&ae!==void 0?ae:this.elevation,On=(we=Sn.maxElevation)!==null&&we!==void 0?we:this.elevation;ji=new mc([ji.min[0],ji.min[1],Zn],[ji.max[0],ji.max[1],On])}Je.push({aabb:ji,zoom:Vi,x:Fa,y:fi,wrap:Tt.wrap,fullyVisible:mr})}}return lt.sort((Tt,zt)=>Tt.distanceSq-zt.distanceSq).map(Tt=>Tt.tileID)}resize(R,ae){this.width=R,this.height=ae,this.pixelsToGLUnits=[2/R,-2/ae],this._constrain(),this._calcMatrices()}get unmodified(){return this._unmodified}zoomScale(R){return Math.pow(2,R)}scaleZoom(R){return Math.log(R)/Math.LN2}project(R){let ae=t.ac(R.lat,-85.051129,wu);return new t.P(t.O(R.lng)*this.worldSize,t.Q(ae)*this.worldSize)}unproject(R){return new t.Z(R.x/this.worldSize,R.y/this.worldSize).toLngLat()}get point(){return this.project(this.center)}getCameraPosition(){return{lngLat:this.pointLocation(this.getCameraPoint()),altitude:Math.cos(this._pitch)*this.cameraToCenterDistance/this._pixelPerMeter+this.elevation}}recalculateZoom(R){let ae=this.elevation,we=Math.cos(this._pitch)*this.cameraToCenterDistance/this._pixelPerMeter,Ae=this.pointLocation(this.centerPoint,R),Be=R.getElevationForLngLatZoom(Ae,this.tileZoom);if(!(this.elevation-Be))return;let pt=we+ae-Be,At=Math.cos(this._pitch)*this.cameraToCenterDistance/pt/t.b5(1,Ae.lat),Nt=this.scaleZoom(At/this.tileSize);this._elevation=Be,this._center=Ae,this.zoom=Nt}setLocationAtPoint(R,ae){let we=this.pointCoordinate(ae),Ae=this.pointCoordinate(this.centerPoint),Be=this.locationCoordinate(R),pt=new t.Z(Be.x-(we.x-Ae.x),Be.y-(we.y-Ae.y));this.center=this.coordinateLocation(pt),this._renderWorldCopies&&(this.center=this.center.wrap())}locationPoint(R,ae){return ae?this.coordinatePoint(this.locationCoordinate(R),ae.getElevationForLngLatZoom(R,this.tileZoom),this.pixelMatrix3D):this.coordinatePoint(this.locationCoordinate(R))}pointLocation(R,ae){return this.coordinateLocation(this.pointCoordinate(R,ae))}locationCoordinate(R){return t.Z.fromLngLat(R)}coordinateLocation(R){return R&&R.toLngLat()}pointCoordinate(R,ae){if(ae){let Kr=ae.pointCoordinate(R);if(Kr!=null)return Kr}let we=[R.x,R.y,0,1],Ae=[R.x,R.y,1,1];t.af(we,we,this.pixelMatrixInverse),t.af(Ae,Ae,this.pixelMatrixInverse);let Be=we[3],pt=Ae[3],At=we[1]/Be,Nt=Ae[1]/pt,$t=we[2]/Be,wr=Ae[2]/pt,Tr=$t===wr?0:(0-$t)/(wr-$t);return new t.Z(t.y.number(we[0]/Be,Ae[0]/pt,Tr)/this.worldSize,t.y.number(At,Nt,Tr)/this.worldSize)}coordinatePoint(R,ae=0,we=this.pixelMatrix){let Ae=[R.x*this.worldSize,R.y*this.worldSize,ae,1];return t.af(Ae,Ae,we),new t.P(Ae[0]/Ae[3],Ae[1]/Ae[3])}getBounds(){let R=Math.max(0,this.height/2-this.getHorizon());return new re().extend(this.pointLocation(new t.P(0,R))).extend(this.pointLocation(new t.P(this.width,R))).extend(this.pointLocation(new t.P(this.width,this.height))).extend(this.pointLocation(new t.P(0,this.height)))}getMaxBounds(){return this.latRange&&this.latRange.length===2&&this.lngRange&&this.lngRange.length===2?new re([this.lngRange[0],this.latRange[0]],[this.lngRange[1],this.latRange[1]]):null}getHorizon(){return Math.tan(Math.PI/2-this._pitch)*this.cameraToCenterDistance*.85}setMaxBounds(R){R?(this.lngRange=[R.getWest(),R.getEast()],this.latRange=[R.getSouth(),R.getNorth()],this._constrain()):(this.lngRange=null,this.latRange=[-85.051129,wu])}calculateTileMatrix(R){let ae=R.canonical,we=this.worldSize/this.zoomScale(ae.z),Ae=ae.x+Math.pow(2,ae.z)*R.wrap,Be=t.an(new Float64Array(16));return t.J(Be,Be,[Ae*we,ae.y*we,0]),t.K(Be,Be,[we/t.X,we/t.X,1]),Be}calculatePosMatrix(R,ae=!1){let we=R.key,Ae=ae?this._alignedPosMatrixCache:this._posMatrixCache;if(Ae[we])return Ae[we];let Be=this.calculateTileMatrix(R);return t.L(Be,ae?this.alignedModelViewProjectionMatrix:this.modelViewProjectionMatrix,Be),Ae[we]=new Float32Array(Be),Ae[we]}calculateFogMatrix(R){let ae=R.key,we=this._fogMatrixCache;if(we[ae])return we[ae];let Ae=this.calculateTileMatrix(R);return t.L(Ae,this.fogMatrix,Ae),we[ae]=new Float32Array(Ae),we[ae]}customLayerMatrix(){return this.mercatorMatrix.slice()}getConstrained(R,ae){ae=t.ac(+ae,this.minZoom,this.maxZoom);let we={center:new t.N(R.lng,R.lat),zoom:ae},Ae=this.lngRange;if(!this._renderWorldCopies&&Ae===null){let Tt=179.9999999999;Ae=[-Tt,Tt]}let Be=this.tileSize*this.zoomScale(we.zoom),pt=0,At=Be,Nt=0,$t=Be,wr=0,Tr=0,{x:Kr,y:sa}=this.size;if(this.latRange){let Tt=this.latRange;pt=t.Q(Tt[1])*Be,At=t.Q(Tt[0])*Be,At-ptAt&&(dt=At-Tt)}if(Ae){let Tt=(Nt+$t)/2,zt=He;this._renderWorldCopies&&(zt=t.b3(He,Tt-Be/2,Tt+Be/2));let ur=Kr/2;zt-ur$t&&(lt=$t-ur)}if(lt!==void 0||dt!==void 0){let Tt=new t.P(lt??He,dt??Je);we.center=this.unproject.call({worldSize:Be},Tt).wrap()}return we}_constrain(){if(!this.center||!this.width||!this.height||this._constraining)return;this._constraining=!0;let R=this._unmodified,{center:ae,zoom:we}=this.getConstrained(this.center,this.zoom);this.center=ae,this.zoom=we,this._unmodified=R,this._constraining=!1}_calcMatrices(){if(!this.height)return;let R=this.centerOffset,ae=this.point.x,we=this.point.y;this.cameraToCenterDistance=.5/Math.tan(this._fov/2)*this.height,this._pixelPerMeter=t.b5(1,this.center.lat)*this.worldSize;let Ae=t.an(new Float64Array(16));t.K(Ae,Ae,[this.width/2,-this.height/2,1]),t.J(Ae,Ae,[1,-1,0]),this.labelPlaneMatrix=Ae,Ae=t.an(new Float64Array(16)),t.K(Ae,Ae,[1,-1,1]),t.J(Ae,Ae,[-1,-1,0]),t.K(Ae,Ae,[2/this.width,2/this.height,1]),this.glCoordMatrix=Ae;let Be=this.cameraToCenterDistance+this._elevation*this._pixelPerMeter/Math.cos(this._pitch),pt=Math.min(this.elevation,this.minElevationForCurrentTile),At=Be-pt*this._pixelPerMeter/Math.cos(this._pitch),Nt=pt<0?At:Be,$t=Math.PI/2+this._pitch,wr=this._fov*(.5+R.y/this.height),Tr=Math.sin(wr)*Nt/Math.sin(t.ac(Math.PI-$t-wr,.01,Math.PI-.01)),Kr=this.getHorizon(),sa=2*Math.atan(Kr/this.cameraToCenterDistance)*(.5+R.y/(2*Kr)),He=Math.sin(sa)*Nt/Math.sin(t.ac(Math.PI-$t-sa,.01,Math.PI-.01)),Je=Math.min(Tr,He);this.farZ=1.01*(Math.cos(Math.PI/2-this._pitch)*Je+Nt),this.nearZ=this.height/50,Ae=new Float64Array(16),t.b6(Ae,this._fov,this.width/this.height,this.nearZ,this.farZ),Ae[8]=2*-R.x/this.width,Ae[9]=2*R.y/this.height,this.projectionMatrix=t.ae(Ae),t.K(Ae,Ae,[1,-1,1]),t.J(Ae,Ae,[0,0,-this.cameraToCenterDistance]),t.b7(Ae,Ae,this._pitch),t.ad(Ae,Ae,this.angle),t.J(Ae,Ae,[-ae,-we,0]),this.mercatorMatrix=t.K([],Ae,[this.worldSize,this.worldSize,this.worldSize]),t.K(Ae,Ae,[1,1,this._pixelPerMeter]),this.pixelMatrix=t.L(new Float64Array(16),this.labelPlaneMatrix,Ae),t.J(Ae,Ae,[0,0,-this.elevation]),this.modelViewProjectionMatrix=Ae,this.invModelViewProjectionMatrix=t.as([],Ae),this.fogMatrix=new Float64Array(16),t.b6(this.fogMatrix,this._fov,this.width/this.height,Be,this.farZ),this.fogMatrix[8]=2*-R.x/this.width,this.fogMatrix[9]=2*R.y/this.height,t.K(this.fogMatrix,this.fogMatrix,[1,-1,1]),t.J(this.fogMatrix,this.fogMatrix,[0,0,-this.cameraToCenterDistance]),t.b7(this.fogMatrix,this.fogMatrix,this._pitch),t.ad(this.fogMatrix,this.fogMatrix,this.angle),t.J(this.fogMatrix,this.fogMatrix,[-ae,-we,0]),t.K(this.fogMatrix,this.fogMatrix,[1,1,this._pixelPerMeter]),t.J(this.fogMatrix,this.fogMatrix,[0,0,-this.elevation]),this.pixelMatrix3D=t.L(new Float64Array(16),this.labelPlaneMatrix,Ae);let lt=this.width%2/2,dt=this.height%2/2,Ct=Math.cos(this.angle),Tt=Math.sin(this.angle),zt=ae-Math.round(ae)+Ct*lt+Tt*dt,ur=we-Math.round(we)+Ct*dt+Tt*lt,mr=new Float64Array(Ae);if(t.J(mr,mr,[zt>.5?zt-1:zt,ur>.5?ur-1:ur,0]),this.alignedModelViewProjectionMatrix=mr,Ae=t.as(new Float64Array(16),this.pixelMatrix),!Ae)throw new Error("failed to invert matrix");this.pixelMatrixInverse=Ae,this._posMatrixCache={},this._alignedPosMatrixCache={},this._fogMatrixCache={}}maxPitchScaleFactor(){if(!this.pixelMatrixInverse)return 1;let R=this.pointCoordinate(new t.P(0,0)),ae=[R.x*this.worldSize,R.y*this.worldSize,0,1];return t.af(ae,ae,this.pixelMatrix)[3]/this.cameraToCenterDistance}getCameraPoint(){let R=Math.tan(this._pitch)*(this.cameraToCenterDistance||1);return this.centerPoint.add(new t.P(0,R))}getCameraQueryGeometry(R){let ae=this.getCameraPoint();if(R.length===1)return[R[0],ae];{let we=ae.x,Ae=ae.y,Be=ae.x,pt=ae.y;for(let At of R)we=Math.min(we,At.x),Ae=Math.min(Ae,At.y),Be=Math.max(Be,At.x),pt=Math.max(pt,At.y);return[new t.P(we,Ae),new t.P(Be,Ae),new t.P(Be,pt),new t.P(we,pt),new t.P(we,Ae)]}}lngLatToCameraDepth(R,ae){let we=this.locationCoordinate(R),Ae=[we.x*this.worldSize,we.y*this.worldSize,ae,1];return t.af(Ae,Ae,this.modelViewProjectionMatrix),Ae[2]/Ae[3]}}function qf(Ue,R){let ae,we=!1,Ae=null,Be=null,pt=()=>{Ae=null,we&&(Ue.apply(Be,ae),Ae=setTimeout(pt,R),we=!1)};return(...At)=>(we=!0,Be=this,ae=At,Ae||pt(),Ae)}class Qf{constructor(R){this._getCurrentHash=()=>{let ae=window.location.hash.replace("#","");if(this._hashName){let we;return ae.split("&").map(Ae=>Ae.split("=")).forEach(Ae=>{Ae[0]===this._hashName&&(we=Ae)}),(we&&we[1]||"").split("/")}return ae.split("/")},this._onHashChange=()=>{let ae=this._getCurrentHash();if(ae.length>=3&&!ae.some(we=>isNaN(we))){let we=this._map.dragRotate.isEnabled()&&this._map.touchZoomRotate.isEnabled()?+(ae[3]||0):this._map.getBearing();return this._map.jumpTo({center:[+ae[2],+ae[1]],zoom:+ae[0],bearing:we,pitch:+(ae[4]||0)}),!0}return!1},this._updateHashUnthrottled=()=>{let ae=window.location.href.replace(/(#.*)?$/,this.getHashString());window.history.replaceState(window.history.state,null,ae)},this._removeHash=()=>{let ae=this._getCurrentHash();if(ae.length===0)return;let we=ae.join("/"),Ae=we;Ae.split("&").length>0&&(Ae=Ae.split("&")[0]),this._hashName&&(Ae=`${this._hashName}=${we}`);let Be=window.location.hash.replace(Ae,"");Be.startsWith("#&")?Be=Be.slice(0,1)+Be.slice(2):Be==="#"&&(Be="");let pt=window.location.href.replace(/(#.+)?$/,Be);pt=pt.replace("&&","&"),window.history.replaceState(window.history.state,null,pt)},this._updateHash=qf(this._updateHashUnthrottled,300),this._hashName=R&&encodeURIComponent(R)}addTo(R){return this._map=R,addEventListener("hashchange",this._onHashChange,!1),this._map.on("moveend",this._updateHash),this}remove(){return removeEventListener("hashchange",this._onHashChange,!1),this._map.off("moveend",this._updateHash),clearTimeout(this._updateHash()),this._removeHash(),delete this._map,this}getHashString(R){let ae=this._map.getCenter(),we=Math.round(100*this._map.getZoom())/100,Ae=Math.ceil((we*Math.LN2+Math.log(512/360/.5))/Math.LN10),Be=Math.pow(10,Ae),pt=Math.round(ae.lng*Be)/Be,At=Math.round(ae.lat*Be)/Be,Nt=this._map.getBearing(),$t=this._map.getPitch(),wr="";if(wr+=R?`/${pt}/${At}/${we}`:`${we}/${At}/${pt}`,(Nt||$t)&&(wr+="/"+Math.round(10*Nt)/10),$t&&(wr+=`/${Math.round($t)}`),this._hashName){let Tr=this._hashName,Kr=!1,sa=window.location.hash.slice(1).split("&").map(He=>{let Je=He.split("=")[0];return Je===Tr?(Kr=!0,`${Je}=${wr}`):He}).filter(He=>He);return Kr||sa.push(`${Tr}=${wr}`),`#${sa.join("&")}`}return`#${wr}`}}let Bu={linearity:.3,easing:t.b8(0,0,.3,1)},Ec=t.e({deceleration:2500,maxSpeed:1400},Bu),gc=t.e({deceleration:20,maxSpeed:1400},Bu),Lh=t.e({deceleration:1e3,maxSpeed:360},Bu),of=t.e({deceleration:1e3,maxSpeed:90},Bu);class df{constructor(R){this._map=R,this.clear()}clear(){this._inertiaBuffer=[]}record(R){this._drainInertiaBuffer(),this._inertiaBuffer.push({time:n.now(),settings:R})}_drainInertiaBuffer(){let R=this._inertiaBuffer,ae=n.now();for(;R.length>0&&ae-R[0].time>160;)R.shift()}_onMoveEnd(R){if(this._drainInertiaBuffer(),this._inertiaBuffer.length<2)return;let ae={zoom:0,bearing:0,pitch:0,pan:new t.P(0,0),pinchAround:void 0,around:void 0};for(let{settings:Be}of this._inertiaBuffer)ae.zoom+=Be.zoomDelta||0,ae.bearing+=Be.bearingDelta||0,ae.pitch+=Be.pitchDelta||0,Be.panDelta&&ae.pan._add(Be.panDelta),Be.around&&(ae.around=Be.around),Be.pinchAround&&(ae.pinchAround=Be.pinchAround);let we=this._inertiaBuffer[this._inertiaBuffer.length-1].time-this._inertiaBuffer[0].time,Ae={};if(ae.pan.mag()){let Be=sf(ae.pan.mag(),we,t.e({},Ec,R||{}));Ae.offset=ae.pan.mult(Be.amount/ae.pan.mag()),Ae.center=this._map.transform.center,Nu(Ae,Be)}if(ae.zoom){let Be=sf(ae.zoom,we,gc);Ae.zoom=this._map.transform.zoom+Be.amount,Nu(Ae,Be)}if(ae.bearing){let Be=sf(ae.bearing,we,Lh);Ae.bearing=this._map.transform.bearing+t.ac(Be.amount,-179,179),Nu(Ae,Be)}if(ae.pitch){let Be=sf(ae.pitch,we,of);Ae.pitch=this._map.transform.pitch+Be.amount,Nu(Ae,Be)}if(Ae.zoom||Ae.bearing){let Be=ae.pinchAround===void 0?ae.around:ae.pinchAround;Ae.around=Be?this._map.unproject(Be):this._map.getCenter()}return this.clear(),t.e(Ae,{noMoveStart:!0})}}function Nu(Ue,R){(!Ue.duration||Ue.durationae.unproject(Nt)),At=Be.reduce((Nt,$t,wr,Tr)=>Nt.add($t.div(Tr.length)),new t.P(0,0));super(R,{points:Be,point:At,lngLats:pt,lngLat:ae.unproject(At),originalEvent:we}),this._defaultPrevented=!1}}class ch extends t.k{preventDefault(){this._defaultPrevented=!0}get defaultPrevented(){return this._defaultPrevented}constructor(R,ae,we){super(R,{originalEvent:we}),this._defaultPrevented=!1}}class vf{constructor(R,ae){this._map=R,this._clickTolerance=ae.clickTolerance}reset(){delete this._mousedownPos}wheel(R){return this._firePreventable(new ch(R.type,this._map,R))}mousedown(R,ae){return this._mousedownPos=ae,this._firePreventable(new iu(R.type,this._map,R))}mouseup(R){this._map.fire(new iu(R.type,this._map,R))}click(R,ae){this._mousedownPos&&this._mousedownPos.dist(ae)>=this._clickTolerance||this._map.fire(new iu(R.type,this._map,R))}dblclick(R){return this._firePreventable(new iu(R.type,this._map,R))}mouseover(R){this._map.fire(new iu(R.type,this._map,R))}mouseout(R){this._map.fire(new iu(R.type,this._map,R))}touchstart(R){return this._firePreventable(new Zc(R.type,this._map,R))}touchmove(R){this._map.fire(new Zc(R.type,this._map,R))}touchend(R){this._map.fire(new Zc(R.type,this._map,R))}touchcancel(R){this._map.fire(new Zc(R.type,this._map,R))}_firePreventable(R){if(this._map.fire(R),R.defaultPrevented)return{}}isEnabled(){return!0}isActive(){return!1}enable(){}disable(){}}class nl{constructor(R){this._map=R}reset(){this._delayContextMenu=!1,this._ignoreContextMenu=!0,delete this._contextMenuEvent}mousemove(R){this._map.fire(new iu(R.type,this._map,R))}mousedown(){this._delayContextMenu=!0,this._ignoreContextMenu=!1}mouseup(){this._delayContextMenu=!1,this._contextMenuEvent&&(this._map.fire(new iu("contextmenu",this._map,this._contextMenuEvent)),delete this._contextMenuEvent)}contextmenu(R){this._delayContextMenu?this._contextMenuEvent=R:this._ignoreContextMenu||this._map.fire(new iu(R.type,this._map,R)),this._map.listens("contextmenu")&&R.preventDefault()}isEnabled(){return!0}isActive(){return!1}enable(){}disable(){}}class gu{constructor(R){this._map=R}get transform(){return this._map._requestedCameraState||this._map.transform}get center(){return{lng:this.transform.center.lng,lat:this.transform.center.lat}}get zoom(){return this.transform.zoom}get pitch(){return this.transform.pitch}get bearing(){return this.transform.bearing}unproject(R){return this.transform.pointLocation(t.P.convert(R),this._map.terrain)}}class Pu{constructor(R,ae){this._map=R,this._tr=new gu(R),this._el=R.getCanvasContainer(),this._container=R.getContainer(),this._clickTolerance=ae.clickTolerance||1}isEnabled(){return!!this._enabled}isActive(){return!!this._active}enable(){this.isEnabled()||(this._enabled=!0)}disable(){this.isEnabled()&&(this._enabled=!1)}mousedown(R,ae){this.isEnabled()&&R.shiftKey&&R.button===0&&(i.disableDrag(),this._startPos=this._lastPos=ae,this._active=!0)}mousemoveWindow(R,ae){if(!this._active)return;let we=ae;if(this._lastPos.equals(we)||!this._box&&we.dist(this._startPos)Be.fitScreenCoordinates(we,Ae,this._tr.bearing,{linear:!0})};this._fireEvent("boxzoomcancel",R)}keydown(R){this._active&&R.keyCode===27&&(this.reset(),this._fireEvent("boxzoomcancel",R))}reset(){this._active=!1,this._container.classList.remove("maplibregl-crosshair"),this._box&&(i.remove(this._box),this._box=null),i.enableDrag(),delete this._startPos,delete this._lastPos}_fireEvent(R,ae){return this._map.fire(new t.k(R,{originalEvent:ae}))}}function Cf(Ue,R){if(Ue.length!==R.length)throw new Error(`The number of touches and points are not equal - touches ${Ue.length}, points ${R.length}`);let ae={};for(let we=0;wethis.numTouches)&&(this.aborted=!0),this.aborted||(this.startTime===void 0&&(this.startTime=R.timeStamp),we.length===this.numTouches&&(this.centroid=function(Ae){let Be=new t.P(0,0);for(let pt of Ae)Be._add(pt);return Be.div(Ae.length)}(ae),this.touches=Cf(we,ae)))}touchmove(R,ae,we){if(this.aborted||!this.centroid)return;let Ae=Cf(we,ae);for(let Be in this.touches){let pt=Ae[Be];(!pt||pt.dist(this.touches[Be])>30)&&(this.aborted=!0)}}touchend(R,ae,we){if((!this.centroid||R.timeStamp-this.startTime>500)&&(this.aborted=!0),we.length===0){let Ae=!this.aborted&&this.centroid;if(this.reset(),Ae)return Ae}}}class lf{constructor(R){this.singleTap=new hl(R),this.numTaps=R.numTaps,this.reset()}reset(){this.lastTime=1/0,delete this.lastTap,this.count=0,this.singleTap.reset()}touchstart(R,ae,we){this.singleTap.touchstart(R,ae,we)}touchmove(R,ae,we){this.singleTap.touchmove(R,ae,we)}touchend(R,ae,we){let Ae=this.singleTap.touchend(R,ae,we);if(Ae){let Be=R.timeStamp-this.lastTime<500,pt=!this.lastTap||this.lastTap.dist(Ae)<30;if(Be&&pt||this.reset(),this.count++,this.lastTime=R.timeStamp,this.lastTap=Ae,this.count===this.numTaps)return this.reset(),Ae}}}class kc{constructor(R){this._tr=new gu(R),this._zoomIn=new lf({numTouches:1,numTaps:2}),this._zoomOut=new lf({numTouches:2,numTaps:1}),this.reset()}reset(){this._active=!1,this._zoomIn.reset(),this._zoomOut.reset()}touchstart(R,ae,we){this._zoomIn.touchstart(R,ae,we),this._zoomOut.touchstart(R,ae,we)}touchmove(R,ae,we){this._zoomIn.touchmove(R,ae,we),this._zoomOut.touchmove(R,ae,we)}touchend(R,ae,we){let Ae=this._zoomIn.touchend(R,ae,we),Be=this._zoomOut.touchend(R,ae,we),pt=this._tr;return Ae?(this._active=!0,R.preventDefault(),setTimeout(()=>this.reset(),0),{cameraAnimation:At=>At.easeTo({duration:300,zoom:pt.zoom+1,around:pt.unproject(Ae)},{originalEvent:R})}):Be?(this._active=!0,R.preventDefault(),setTimeout(()=>this.reset(),0),{cameraAnimation:At=>At.easeTo({duration:300,zoom:pt.zoom-1,around:pt.unproject(Be)},{originalEvent:R})}):void 0}touchcancel(){this.reset()}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}}class Hu{constructor(R){this._enabled=!!R.enable,this._moveStateManager=R.moveStateManager,this._clickTolerance=R.clickTolerance||1,this._moveFunction=R.move,this._activateOnStart=!!R.activateOnStart,R.assignEvents(this),this.reset()}reset(R){this._active=!1,this._moved=!1,delete this._lastPoint,this._moveStateManager.endMove(R)}_move(...R){let ae=this._moveFunction(...R);if(ae.bearingDelta||ae.pitchDelta||ae.around||ae.panDelta)return this._active=!0,ae}dragStart(R,ae){this.isEnabled()&&!this._lastPoint&&this._moveStateManager.isValidStartEvent(R)&&(this._moveStateManager.startMove(R),this._lastPoint=ae.length?ae[0]:ae,this._activateOnStart&&this._lastPoint&&(this._active=!0))}dragMove(R,ae){if(!this.isEnabled())return;let we=this._lastPoint;if(!we)return;if(R.preventDefault(),!this._moveStateManager.isValidMoveEvent(R))return void this.reset(R);let Ae=ae.length?ae[0]:ae;return!this._moved&&Ae.dist(we){Ue.mousedown=Ue.dragStart,Ue.mousemoveWindow=Ue.dragMove,Ue.mouseup=Ue.dragEnd,Ue.contextmenu=R=>{R.preventDefault()}},nu=({enable:Ue,clickTolerance:R,bearingDegreesPerPixelMoved:ae=.8})=>{let we=new Wu({checkCorrectEvent:Ae=>i.mouseButton(Ae)===0&&Ae.ctrlKey||i.mouseButton(Ae)===2});return new Hu({clickTolerance:R,move:(Ae,Be)=>({bearingDelta:(Be.x-Ae.x)*ae}),moveStateManager:we,enable:Ue,assignEvents:Lf})},Vf=({enable:Ue,clickTolerance:R,pitchDegreesPerPixelMoved:ae=-.5})=>{let we=new Wu({checkCorrectEvent:Ae=>i.mouseButton(Ae)===0&&Ae.ctrlKey||i.mouseButton(Ae)===2});return new Hu({clickTolerance:R,move:(Ae,Be)=>({pitchDelta:(Be.y-Ae.y)*ae}),moveStateManager:we,enable:Ue,assignEvents:Lf})};class Xu{constructor(R,ae){this._clickTolerance=R.clickTolerance||1,this._map=ae,this.reset()}reset(){this._active=!1,this._touches={},this._sum=new t.P(0,0)}_shouldBePrevented(R){return R<(this._map.cooperativeGestures.isEnabled()?2:1)}touchstart(R,ae,we){return this._calculateTransform(R,ae,we)}touchmove(R,ae,we){if(this._active){if(!this._shouldBePrevented(we.length))return R.preventDefault(),this._calculateTransform(R,ae,we);this._map.cooperativeGestures.notifyGestureBlocked("touch_pan",R)}}touchend(R,ae,we){this._calculateTransform(R,ae,we),this._active&&this._shouldBePrevented(we.length)&&this.reset()}touchcancel(){this.reset()}_calculateTransform(R,ae,we){we.length>0&&(this._active=!0);let Ae=Cf(we,ae),Be=new t.P(0,0),pt=new t.P(0,0),At=0;for(let $t in Ae){let wr=Ae[$t],Tr=this._touches[$t];Tr&&(Be._add(wr),pt._add(wr.sub(Tr)),At++,Ae[$t]=wr)}if(this._touches=Ae,this._shouldBePrevented(At)||!pt.mag())return;let Nt=pt.div(At);return this._sum._add(Nt),this._sum.mag()Math.abs(Ue.x)}class Pc extends Cc{constructor(R){super(),this._currentTouchCount=0,this._map=R}reset(){super.reset(),this._valid=void 0,delete this._firstMove,delete this._lastPoints}touchstart(R,ae,we){super.touchstart(R,ae,we),this._currentTouchCount=we.length}_start(R){this._lastPoints=R,lc(R[0].sub(R[1]))&&(this._valid=!1)}_move(R,ae,we){if(this._map.cooperativeGestures.isEnabled()&&this._currentTouchCount<3)return;let Ae=R[0].sub(this._lastPoints[0]),Be=R[1].sub(this._lastPoints[1]);return this._valid=this.gestureBeginsVertically(Ae,Be,we.timeStamp),this._valid?(this._lastPoints=R,this._active=!0,{pitchDelta:(Ae.y+Be.y)/2*-.5}):void 0}gestureBeginsVertically(R,ae,we){if(this._valid!==void 0)return this._valid;let Ae=R.mag()>=2,Be=ae.mag()>=2;if(!Ae&&!Be)return;if(!Ae||!Be)return this._firstMove===void 0&&(this._firstMove=we),we-this._firstMove<100&&void 0;let pt=R.y>0==ae.y>0;return lc(R)&&lc(ae)&&pt}}let Qt={panStep:100,bearingStep:15,pitchStep:10};class yr{constructor(R){this._tr=new gu(R);let ae=Qt;this._panStep=ae.panStep,this._bearingStep=ae.bearingStep,this._pitchStep=ae.pitchStep,this._rotationDisabled=!1}reset(){this._active=!1}keydown(R){if(R.altKey||R.ctrlKey||R.metaKey)return;let ae=0,we=0,Ae=0,Be=0,pt=0;switch(R.keyCode){case 61:case 107:case 171:case 187:ae=1;break;case 189:case 109:case 173:ae=-1;break;case 37:R.shiftKey?we=-1:(R.preventDefault(),Be=-1);break;case 39:R.shiftKey?we=1:(R.preventDefault(),Be=1);break;case 38:R.shiftKey?Ae=1:(R.preventDefault(),pt=-1);break;case 40:R.shiftKey?Ae=-1:(R.preventDefault(),pt=1);break;default:return}return this._rotationDisabled&&(we=0,Ae=0),{cameraAnimation:At=>{let Nt=this._tr;At.easeTo({duration:300,easeId:"keyboardHandler",easing:na,zoom:ae?Math.round(Nt.zoom)+ae*(R.shiftKey?2:1):Nt.zoom,bearing:Nt.bearing+we*this._bearingStep,pitch:Nt.pitch+Ae*this._pitchStep,offset:[-Be*this._panStep,-pt*this._panStep],center:Nt.center},{originalEvent:R})}}}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}disableRotation(){this._rotationDisabled=!0}enableRotation(){this._rotationDisabled=!1}}function na(Ue){return Ue*(2-Ue)}let $r=4.000244140625;class ka{constructor(R,ae){this._onTimeout=we=>{this._type="wheel",this._delta-=this._lastValue,this._active||this._start(we)},this._map=R,this._tr=new gu(R),this._triggerRenderFrame=ae,this._delta=0,this._defaultZoomRate=.01,this._wheelZoomRate=.0022222222222222222}setZoomRate(R){this._defaultZoomRate=R}setWheelZoomRate(R){this._wheelZoomRate=R}isEnabled(){return!!this._enabled}isActive(){return!!this._active||this._finishTimeout!==void 0}isZooming(){return!!this._zooming}enable(R){this.isEnabled()||(this._enabled=!0,this._aroundCenter=!!R&&R.around==="center")}disable(){this.isEnabled()&&(this._enabled=!1)}_shouldBePrevented(R){return!!this._map.cooperativeGestures.isEnabled()&&!(R.ctrlKey||this._map.cooperativeGestures.isBypassed(R))}wheel(R){if(!this.isEnabled())return;if(this._shouldBePrevented(R))return void this._map.cooperativeGestures.notifyGestureBlocked("wheel_zoom",R);let ae=R.deltaMode===WheelEvent.DOM_DELTA_LINE?40*R.deltaY:R.deltaY,we=n.now(),Ae=we-(this._lastWheelEventTime||0);this._lastWheelEventTime=we,ae!==0&&ae%$r==0?this._type="wheel":ae!==0&&Math.abs(ae)<4?this._type="trackpad":Ae>400?(this._type=null,this._lastValue=ae,this._timeout=setTimeout(this._onTimeout,40,R)):this._type||(this._type=Math.abs(Ae*ae)<200?"trackpad":"wheel",this._timeout&&(clearTimeout(this._timeout),this._timeout=null,ae+=this._lastValue)),R.shiftKey&&ae&&(ae/=4),this._type&&(this._lastWheelEvent=R,this._delta-=ae,this._active||this._start(R)),R.preventDefault()}_start(R){if(!this._delta)return;this._frameId&&(this._frameId=null),this._active=!0,this.isZooming()||(this._zooming=!0),this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout);let ae=i.mousePos(this._map.getCanvas(),R),we=this._tr;this._around=ae.y>we.transform.height/2-we.transform.getHorizon()?t.N.convert(this._aroundCenter?we.center:we.unproject(ae)):t.N.convert(we.center),this._aroundPoint=we.transform.locationPoint(this._around),this._frameId||(this._frameId=!0,this._triggerRenderFrame())}renderFrame(){if(!this._frameId||(this._frameId=null,!this.isActive()))return;let R=this._tr.transform;if(this._delta!==0){let Nt=this._type==="wheel"&&Math.abs(this._delta)>$r?this._wheelZoomRate:this._defaultZoomRate,$t=2/(1+Math.exp(-Math.abs(this._delta*Nt)));this._delta<0&&$t!==0&&($t=1/$t);let wr=typeof this._targetZoom=="number"?R.zoomScale(this._targetZoom):R.scale;this._targetZoom=Math.min(R.maxZoom,Math.max(R.minZoom,R.scaleZoom(wr*$t))),this._type==="wheel"&&(this._startZoom=R.zoom,this._easing=this._smoothOutEasing(200)),this._delta=0}let ae=typeof this._targetZoom=="number"?this._targetZoom:R.zoom,we=this._startZoom,Ae=this._easing,Be,pt=!1,At=n.now()-this._lastWheelEventTime;if(this._type==="wheel"&&we&&Ae&&At){let Nt=Math.min(At/200,1),$t=Ae(Nt);Be=t.y.number(we,ae,$t),Nt<1?this._frameId||(this._frameId=!0):pt=!0}else Be=ae,pt=!0;return this._active=!0,pt&&(this._active=!1,this._finishTimeout=setTimeout(()=>{this._zooming=!1,this._triggerRenderFrame(),delete this._targetZoom,delete this._finishTimeout},200)),{noInertia:!0,needsRenderFrame:!pt,zoomDelta:Be-R.zoom,around:this._aroundPoint,originalEvent:this._lastWheelEvent}}_smoothOutEasing(R){let ae=t.b9;if(this._prevEase){let we=this._prevEase,Ae=(n.now()-we.start)/we.duration,Be=we.easing(Ae+.01)-we.easing(Ae),pt=.27/Math.sqrt(Be*Be+1e-4)*.01,At=Math.sqrt(.0729-pt*pt);ae=t.b8(pt,At,.25,1)}return this._prevEase={start:n.now(),duration:R,easing:ae},ae}reset(){this._active=!1,this._zooming=!1,delete this._targetZoom,this._finishTimeout&&(clearTimeout(this._finishTimeout),delete this._finishTimeout)}}class ui{constructor(R,ae){this._clickZoom=R,this._tapZoom=ae}enable(){this._clickZoom.enable(),this._tapZoom.enable()}disable(){this._clickZoom.disable(),this._tapZoom.disable()}isEnabled(){return this._clickZoom.isEnabled()&&this._tapZoom.isEnabled()}isActive(){return this._clickZoom.isActive()||this._tapZoom.isActive()}}class Ci{constructor(R){this._tr=new gu(R),this.reset()}reset(){this._active=!1}dblclick(R,ae){return R.preventDefault(),{cameraAnimation:we=>{we.easeTo({duration:300,zoom:this._tr.zoom+(R.shiftKey?-1:1),around:this._tr.unproject(ae)},{originalEvent:R})}}}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}}class Gi{constructor(){this._tap=new lf({numTouches:1,numTaps:1}),this.reset()}reset(){this._active=!1,delete this._swipePoint,delete this._swipeTouch,delete this._tapTime,delete this._tapPoint,this._tap.reset()}touchstart(R,ae,we){if(!this._swipePoint)if(this._tapTime){let Ae=ae[0],Be=R.timeStamp-this._tapTime<500,pt=this._tapPoint.dist(Ae)<30;Be&&pt?we.length>0&&(this._swipePoint=Ae,this._swipeTouch=we[0].identifier):this.reset()}else this._tap.touchstart(R,ae,we)}touchmove(R,ae,we){if(this._tapTime){if(this._swipePoint){if(we[0].identifier!==this._swipeTouch)return;let Ae=ae[0],Be=Ae.y-this._swipePoint.y;return this._swipePoint=Ae,R.preventDefault(),this._active=!0,{zoomDelta:Be/128}}}else this._tap.touchmove(R,ae,we)}touchend(R,ae,we){if(this._tapTime)this._swipePoint&&we.length===0&&this.reset();else{let Ae=this._tap.touchend(R,ae,we);Ae&&(this._tapTime=R.timeStamp,this._tapPoint=Ae)}}touchcancel(){this.reset()}enable(){this._enabled=!0}disable(){this._enabled=!1,this.reset()}isEnabled(){return this._enabled}isActive(){return this._active}}class Qi{constructor(R,ae,we){this._el=R,this._mousePan=ae,this._touchPan=we}enable(R){this._inertiaOptions=R||{},this._mousePan.enable(),this._touchPan.enable(),this._el.classList.add("maplibregl-touch-drag-pan")}disable(){this._mousePan.disable(),this._touchPan.disable(),this._el.classList.remove("maplibregl-touch-drag-pan")}isEnabled(){return this._mousePan.isEnabled()&&this._touchPan.isEnabled()}isActive(){return this._mousePan.isActive()||this._touchPan.isActive()}}class dn{constructor(R,ae,we){this._pitchWithRotate=R.pitchWithRotate,this._mouseRotate=ae,this._mousePitch=we}enable(){this._mouseRotate.enable(),this._pitchWithRotate&&this._mousePitch.enable()}disable(){this._mouseRotate.disable(),this._mousePitch.disable()}isEnabled(){return this._mouseRotate.isEnabled()&&(!this._pitchWithRotate||this._mousePitch.isEnabled())}isActive(){return this._mouseRotate.isActive()||this._mousePitch.isActive()}}class Pi{constructor(R,ae,we,Ae){this._el=R,this._touchZoom=ae,this._touchRotate=we,this._tapDragZoom=Ae,this._rotationDisabled=!1,this._enabled=!0}enable(R){this._touchZoom.enable(R),this._rotationDisabled||this._touchRotate.enable(R),this._tapDragZoom.enable(),this._el.classList.add("maplibregl-touch-zoom-rotate")}disable(){this._touchZoom.disable(),this._touchRotate.disable(),this._tapDragZoom.disable(),this._el.classList.remove("maplibregl-touch-zoom-rotate")}isEnabled(){return this._touchZoom.isEnabled()&&(this._rotationDisabled||this._touchRotate.isEnabled())&&this._tapDragZoom.isEnabled()}isActive(){return this._touchZoom.isActive()||this._touchRotate.isActive()||this._tapDragZoom.isActive()}disableRotation(){this._rotationDisabled=!0,this._touchRotate.disable()}enableRotation(){this._rotationDisabled=!1,this._touchZoom.isEnabled()&&this._touchRotate.enable()}}class Di{constructor(R,ae){this._bypassKey=navigator.userAgent.indexOf("Mac")!==-1?"metaKey":"ctrlKey",this._map=R,this._options=ae,this._enabled=!1}isActive(){return!1}reset(){}_setupUI(){if(this._container)return;let R=this._map.getCanvasContainer();R.classList.add("maplibregl-cooperative-gestures"),this._container=i.create("div","maplibregl-cooperative-gesture-screen",R);let ae=this._map._getUIString("CooperativeGesturesHandler.WindowsHelpText");this._bypassKey==="metaKey"&&(ae=this._map._getUIString("CooperativeGesturesHandler.MacHelpText"));let we=this._map._getUIString("CooperativeGesturesHandler.MobileHelpText"),Ae=document.createElement("div");Ae.className="maplibregl-desktop-message",Ae.textContent=ae,this._container.appendChild(Ae);let Be=document.createElement("div");Be.className="maplibregl-mobile-message",Be.textContent=we,this._container.appendChild(Be),this._container.setAttribute("aria-hidden","true")}_destroyUI(){this._container&&(i.remove(this._container),this._map.getCanvasContainer().classList.remove("maplibregl-cooperative-gestures")),delete this._container}enable(){this._setupUI(),this._enabled=!0}disable(){this._enabled=!1,this._destroyUI()}isEnabled(){return this._enabled}isBypassed(R){return R[this._bypassKey]}notifyGestureBlocked(R,ae){this._enabled&&(this._map.fire(new t.k("cooperativegestureprevented",{gestureType:R,originalEvent:ae})),this._container.classList.add("maplibregl-show"),setTimeout(()=>{this._container.classList.remove("maplibregl-show")},100))}}let Ni=Ue=>Ue.zoom||Ue.drag||Ue.pitch||Ue.rotate;class yi extends t.k{}function En(Ue){return Ue.panDelta&&Ue.panDelta.mag()||Ue.zoomDelta||Ue.bearingDelta||Ue.pitchDelta}class Jn{constructor(R,ae){this.handleWindowEvent=Ae=>{this.handleEvent(Ae,`${Ae.type}Window`)},this.handleEvent=(Ae,Be)=>{if(Ae.type==="blur")return void this.stop(!0);this._updatingCamera=!0;let pt=Ae.type==="renderFrame"?void 0:Ae,At={needsRenderFrame:!1},Nt={},$t={},wr=Ae.touches,Tr=wr?this._getMapTouches(wr):void 0,Kr=Tr?i.touchPos(this._map.getCanvas(),Tr):i.mousePos(this._map.getCanvas(),Ae);for(let{handlerName:Je,handler:lt,allowed:dt}of this._handlers){if(!lt.isEnabled())continue;let Ct;this._blockedByActive($t,dt,Je)?lt.reset():lt[Be||Ae.type]&&(Ct=lt[Be||Ae.type](Ae,Kr,Tr),this.mergeHandlerResult(At,Nt,Ct,Je,pt),Ct&&Ct.needsRenderFrame&&this._triggerRenderFrame()),(Ct||lt.isActive())&&($t[Je]=lt)}let sa={};for(let Je in this._previousActiveHandlers)$t[Je]||(sa[Je]=pt);this._previousActiveHandlers=$t,(Object.keys(sa).length||En(At))&&(this._changes.push([At,Nt,sa]),this._triggerRenderFrame()),(Object.keys($t).length||En(At))&&this._map._stop(!0),this._updatingCamera=!1;let{cameraAnimation:He}=At;He&&(this._inertia.clear(),this._fireEvents({},{},!0),this._changes=[],He(this._map))},this._map=R,this._el=this._map.getCanvasContainer(),this._handlers=[],this._handlersById={},this._changes=[],this._inertia=new df(R),this._bearingSnap=ae.bearingSnap,this._previousActiveHandlers={},this._eventsInProgress={},this._addDefaultHandlers(ae);let we=this._el;this._listeners=[[we,"touchstart",{passive:!0}],[we,"touchmove",{passive:!1}],[we,"touchend",void 0],[we,"touchcancel",void 0],[we,"mousedown",void 0],[we,"mousemove",void 0],[we,"mouseup",void 0],[document,"mousemove",{capture:!0}],[document,"mouseup",void 0],[we,"mouseover",void 0],[we,"mouseout",void 0],[we,"dblclick",void 0],[we,"click",void 0],[we,"keydown",{capture:!1}],[we,"keyup",void 0],[we,"wheel",{passive:!1}],[we,"contextmenu",void 0],[window,"blur",void 0]];for(let[Ae,Be,pt]of this._listeners)i.addEventListener(Ae,Be,Ae===document?this.handleWindowEvent:this.handleEvent,pt)}destroy(){for(let[R,ae,we]of this._listeners)i.removeEventListener(R,ae,R===document?this.handleWindowEvent:this.handleEvent,we)}_addDefaultHandlers(R){let ae=this._map,we=ae.getCanvasContainer();this._add("mapEvent",new vf(ae,R));let Ae=ae.boxZoom=new Pu(ae,R);this._add("boxZoom",Ae),R.interactive&&R.boxZoom&&Ae.enable();let Be=ae.cooperativeGestures=new Di(ae,R.cooperativeGestures);this._add("cooperativeGestures",Be),R.cooperativeGestures&&Be.enable();let pt=new kc(ae),At=new Ci(ae);ae.doubleClickZoom=new ui(At,pt),this._add("tapZoom",pt),this._add("clickZoom",At),R.interactive&&R.doubleClickZoom&&ae.doubleClickZoom.enable();let Nt=new Gi;this._add("tapDragZoom",Nt);let $t=ae.touchPitch=new Pc(ae);this._add("touchPitch",$t),R.interactive&&R.touchPitch&&ae.touchPitch.enable(R.touchPitch);let wr=nu(R),Tr=Vf(R);ae.dragRotate=new dn(R,wr,Tr),this._add("mouseRotate",wr,["mousePitch"]),this._add("mousePitch",Tr,["mouseRotate"]),R.interactive&&R.dragRotate&&ae.dragRotate.enable();let Kr=(({enable:Ct,clickTolerance:Tt})=>{let zt=new Wu({checkCorrectEvent:ur=>i.mouseButton(ur)===0&&!ur.ctrlKey});return new Hu({clickTolerance:Tt,move:(ur,mr)=>({around:mr,panDelta:mr.sub(ur)}),activateOnStart:!0,moveStateManager:zt,enable:Ct,assignEvents:Lf})})(R),sa=new Xu(R,ae);ae.dragPan=new Qi(we,Kr,sa),this._add("mousePan",Kr),this._add("touchPan",sa,["touchZoom","touchRotate"]),R.interactive&&R.dragPan&&ae.dragPan.enable(R.dragPan);let He=new Kc,Je=new yu;ae.touchZoomRotate=new Pi(we,Je,He,Nt),this._add("touchRotate",He,["touchPan","touchZoom"]),this._add("touchZoom",Je,["touchPan","touchRotate"]),R.interactive&&R.touchZoomRotate&&ae.touchZoomRotate.enable(R.touchZoomRotate);let lt=ae.scrollZoom=new ka(ae,()=>this._triggerRenderFrame());this._add("scrollZoom",lt,["mousePan"]),R.interactive&&R.scrollZoom&&ae.scrollZoom.enable(R.scrollZoom);let dt=ae.keyboard=new yr(ae);this._add("keyboard",dt),R.interactive&&R.keyboard&&ae.keyboard.enable(),this._add("blockableMapEvent",new nl(ae))}_add(R,ae,we){this._handlers.push({handlerName:R,handler:ae,allowed:we}),this._handlersById[R]=ae}stop(R){if(!this._updatingCamera){for(let{handler:ae}of this._handlers)ae.reset();this._inertia.clear(),this._fireEvents({},{},R),this._changes=[]}}isActive(){for(let{handler:R}of this._handlers)if(R.isActive())return!0;return!1}isZooming(){return!!this._eventsInProgress.zoom||this._map.scrollZoom.isZooming()}isRotating(){return!!this._eventsInProgress.rotate}isMoving(){return!!Ni(this._eventsInProgress)||this.isZooming()}_blockedByActive(R,ae,we){for(let Ae in R)if(Ae!==we&&(!ae||ae.indexOf(Ae)<0))return!0;return!1}_getMapTouches(R){let ae=[];for(let we of R)this._el.contains(we.target)&&ae.push(we);return ae}mergeHandlerResult(R,ae,we,Ae,Be){if(!we)return;t.e(R,we);let pt={handlerName:Ae,originalEvent:we.originalEvent||Be};we.zoomDelta!==void 0&&(ae.zoom=pt),we.panDelta!==void 0&&(ae.drag=pt),we.pitchDelta!==void 0&&(ae.pitch=pt),we.bearingDelta!==void 0&&(ae.rotate=pt)}_applyChanges(){let R={},ae={},we={};for(let[Ae,Be,pt]of this._changes)Ae.panDelta&&(R.panDelta=(R.panDelta||new t.P(0,0))._add(Ae.panDelta)),Ae.zoomDelta&&(R.zoomDelta=(R.zoomDelta||0)+Ae.zoomDelta),Ae.bearingDelta&&(R.bearingDelta=(R.bearingDelta||0)+Ae.bearingDelta),Ae.pitchDelta&&(R.pitchDelta=(R.pitchDelta||0)+Ae.pitchDelta),Ae.around!==void 0&&(R.around=Ae.around),Ae.pinchAround!==void 0&&(R.pinchAround=Ae.pinchAround),Ae.noInertia&&(R.noInertia=Ae.noInertia),t.e(ae,Be),t.e(we,pt);this._updateMapTransform(R,ae,we),this._changes=[]}_updateMapTransform(R,ae,we){let Ae=this._map,Be=Ae._getTransformForUpdate(),pt=Ae.terrain;if(!(En(R)||pt&&this._terrainMovement))return this._fireEvents(ae,we,!0);let{panDelta:At,zoomDelta:Nt,bearingDelta:$t,pitchDelta:wr,around:Tr,pinchAround:Kr}=R;Kr!==void 0&&(Tr=Kr),Ae._stop(!0),Tr=Tr||Ae.transform.centerPoint;let sa=Be.pointLocation(At?Tr.sub(At):Tr);$t&&(Be.bearing+=$t),wr&&(Be.pitch+=wr),Nt&&(Be.zoom+=Nt),pt?this._terrainMovement||!ae.drag&&!ae.zoom?ae.drag&&this._terrainMovement?Be.center=Be.pointLocation(Be.centerPoint.sub(At)):Be.setLocationAtPoint(sa,Tr):(this._terrainMovement=!0,this._map._elevationFreeze=!0,Be.setLocationAtPoint(sa,Tr)):Be.setLocationAtPoint(sa,Tr),Ae._applyUpdatedTransform(Be),this._map._update(),R.noInertia||this._inertia.record(R),this._fireEvents(ae,we,!0)}_fireEvents(R,ae,we){let Ae=Ni(this._eventsInProgress),Be=Ni(R),pt={};for(let Tr in R){let{originalEvent:Kr}=R[Tr];this._eventsInProgress[Tr]||(pt[`${Tr}start`]=Kr),this._eventsInProgress[Tr]=R[Tr]}!Ae&&Be&&this._fireEvent("movestart",Be.originalEvent);for(let Tr in pt)this._fireEvent(Tr,pt[Tr]);Be&&this._fireEvent("move",Be.originalEvent);for(let Tr in R){let{originalEvent:Kr}=R[Tr];this._fireEvent(Tr,Kr)}let At={},Nt;for(let Tr in this._eventsInProgress){let{handlerName:Kr,originalEvent:sa}=this._eventsInProgress[Tr];this._handlersById[Kr].isActive()||(delete this._eventsInProgress[Tr],Nt=ae[Kr]||sa,At[`${Tr}end`]=Nt)}for(let Tr in At)this._fireEvent(Tr,At[Tr]);let $t=Ni(this._eventsInProgress),wr=(Ae||Be)&&!$t;if(wr&&this._terrainMovement){this._map._elevationFreeze=!1,this._terrainMovement=!1;let Tr=this._map._getTransformForUpdate();Tr.recalculateZoom(this._map.terrain),this._map._applyUpdatedTransform(Tr)}if(we&&wr){this._updatingCamera=!0;let Tr=this._inertia._onMoveEnd(this._map.dragPan._inertiaOptions),Kr=sa=>sa!==0&&-this._bearingSnap{delete this._frameId,this.handleEvent(new yi("renderFrame",{timeStamp:R})),this._applyChanges()})}_triggerRenderFrame(){this._frameId===void 0&&(this._frameId=this._requestFrame())}}class ro extends t.E{constructor(R,ae){super(),this._renderFrameCallback=()=>{let we=Math.min((n.now()-this._easeStart)/this._easeOptions.duration,1);this._onEaseFrame(this._easeOptions.easing(we)),we<1&&this._easeFrameId?this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback):this.stop()},this._moving=!1,this._zooming=!1,this.transform=R,this._bearingSnap=ae.bearingSnap,this.on("moveend",()=>{delete this._requestedCameraState})}getCenter(){return new t.N(this.transform.center.lng,this.transform.center.lat)}setCenter(R,ae){return this.jumpTo({center:R},ae)}panBy(R,ae,we){return R=t.P.convert(R).mult(-1),this.panTo(this.transform.center,t.e({offset:R},ae),we)}panTo(R,ae,we){return this.easeTo(t.e({center:R},ae),we)}getZoom(){return this.transform.zoom}setZoom(R,ae){return this.jumpTo({zoom:R},ae),this}zoomTo(R,ae,we){return this.easeTo(t.e({zoom:R},ae),we)}zoomIn(R,ae){return this.zoomTo(this.getZoom()+1,R,ae),this}zoomOut(R,ae){return this.zoomTo(this.getZoom()-1,R,ae),this}getBearing(){return this.transform.bearing}setBearing(R,ae){return this.jumpTo({bearing:R},ae),this}getPadding(){return this.transform.padding}setPadding(R,ae){return this.jumpTo({padding:R},ae),this}rotateTo(R,ae,we){return this.easeTo(t.e({bearing:R},ae),we)}resetNorth(R,ae){return this.rotateTo(0,t.e({duration:1e3},R),ae),this}resetNorthPitch(R,ae){return this.easeTo(t.e({bearing:0,pitch:0,duration:1e3},R),ae),this}snapToNorth(R,ae){return Math.abs(this.getBearing()){if(this._zooming&&(Ae.zoom=t.y.number(Be,lt,Er)),this._rotating&&(Ae.bearing=t.y.number(pt,$t,Er)),this._pitching&&(Ae.pitch=t.y.number(At,wr,Er)),this._padding&&(Ae.interpolatePadding(Nt,Tr,Er),sa=Ae.centerPoint.add(Kr)),this.terrain&&!R.freezeElevation&&this._updateElevation(Er),zt)Ae.setLocationAtPoint(zt,ur);else{let Ur=Ae.zoomScale(Ae.zoom-Be),Qr=lt>Be?Math.min(2,Tt):Math.max(.5,Tt),da=Math.pow(Qr,1-Er),wa=Ae.unproject(dt.add(Ct.mult(Er*da)).mult(Ur));Ae.setLocationAtPoint(Ae.renderWorldCopies?wa.wrap():wa,sa)}this._applyUpdatedTransform(Ae),this._fireMoveEvents(ae)},Er=>{this.terrain&&R.freezeElevation&&this._finalizeElevation(),this._afterEase(ae,Er)},R),this}_prepareEase(R,ae,we={}){this._moving=!0,ae||we.moving||this.fire(new t.k("movestart",R)),this._zooming&&!we.zooming&&this.fire(new t.k("zoomstart",R)),this._rotating&&!we.rotating&&this.fire(new t.k("rotatestart",R)),this._pitching&&!we.pitching&&this.fire(new t.k("pitchstart",R))}_prepareElevation(R){this._elevationCenter=R,this._elevationStart=this.transform.elevation,this._elevationTarget=this.terrain.getElevationForLngLatZoom(R,this.transform.tileZoom),this._elevationFreeze=!0}_updateElevation(R){this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this._elevationCenter,this.transform.tileZoom);let ae=this.terrain.getElevationForLngLatZoom(this._elevationCenter,this.transform.tileZoom);if(R<1&&ae!==this._elevationTarget){let we=this._elevationTarget-this._elevationStart;this._elevationStart+=R*(we-(ae-(we*R+this._elevationStart))/(1-R)),this._elevationTarget=ae}this.transform.elevation=t.y.number(this._elevationStart,this._elevationTarget,R)}_finalizeElevation(){this._elevationFreeze=!1,this.transform.recalculateZoom(this.terrain)}_getTransformForUpdate(){return this.transformCameraUpdate||this.terrain?(this._requestedCameraState||(this._requestedCameraState=this.transform.clone()),this._requestedCameraState):this.transform}_elevateCameraIfInsideTerrain(R){let ae=R.getCameraPosition(),we=this.terrain.getElevationForLngLatZoom(ae.lngLat,R.zoom);if(ae.altitudethis._elevateCameraIfInsideTerrain(Ae)),this.transformCameraUpdate&&ae.push(Ae=>this.transformCameraUpdate(Ae)),!ae.length)return;let we=R.clone();for(let Ae of ae){let Be=we.clone(),{center:pt,zoom:At,pitch:Nt,bearing:$t,elevation:wr}=Ae(Be);pt&&(Be.center=pt),At!==void 0&&(Be.zoom=At),Nt!==void 0&&(Be.pitch=Nt),$t!==void 0&&(Be.bearing=$t),wr!==void 0&&(Be.elevation=wr),we.apply(Be)}this.transform.apply(we)}_fireMoveEvents(R){this.fire(new t.k("move",R)),this._zooming&&this.fire(new t.k("zoom",R)),this._rotating&&this.fire(new t.k("rotate",R)),this._pitching&&this.fire(new t.k("pitch",R))}_afterEase(R,ae){if(this._easeId&&ae&&this._easeId===ae)return;delete this._easeId;let we=this._zooming,Ae=this._rotating,Be=this._pitching;this._moving=!1,this._zooming=!1,this._rotating=!1,this._pitching=!1,this._padding=!1,we&&this.fire(new t.k("zoomend",R)),Ae&&this.fire(new t.k("rotateend",R)),Be&&this.fire(new t.k("pitchend",R)),this.fire(new t.k("moveend",R))}flyTo(R,ae){var we;if(!R.essential&&n.prefersReducedMotion){let nn=t.M(R,["center","zoom","bearing","pitch","around"]);return this.jumpTo(nn,ae)}this.stop(),R=t.e({offset:[0,0],speed:1.2,curve:1.42,easing:t.b9},R);let Ae=this._getTransformForUpdate(),Be=Ae.zoom,pt=Ae.bearing,At=Ae.pitch,Nt=Ae.padding,$t="bearing"in R?this._normalizeBearing(R.bearing,pt):pt,wr="pitch"in R?+R.pitch:At,Tr="padding"in R?R.padding:Ae.padding,Kr=t.P.convert(R.offset),sa=Ae.centerPoint.add(Kr),He=Ae.pointLocation(sa),{center:Je,zoom:lt}=Ae.getConstrained(t.N.convert(R.center||He),(we=R.zoom)!==null&&we!==void 0?we:Be);this._normalizeCenter(Je,Ae);let dt=Ae.zoomScale(lt-Be),Ct=Ae.project(He),Tt=Ae.project(Je).sub(Ct),zt=R.curve,ur=Math.max(Ae.width,Ae.height),mr=ur/dt,Er=Tt.mag();if("minZoom"in R){let nn=t.ac(Math.min(R.minZoom,Be,lt),Ae.minZoom,Ae.maxZoom),Sn=ur/Ae.zoomScale(nn-Be);zt=Math.sqrt(Sn/Er*2)}let Ur=zt*zt;function Qr(nn){let Sn=(mr*mr-ur*ur+(nn?-1:1)*Ur*Ur*Er*Er)/(2*(nn?mr:ur)*Ur*Er);return Math.log(Math.sqrt(Sn*Sn+1)-Sn)}function da(nn){return(Math.exp(nn)-Math.exp(-nn))/2}function wa(nn){return(Math.exp(nn)+Math.exp(-nn))/2}let Fa=Qr(!1),fi=function(nn){return wa(Fa)/wa(Fa+zt*nn)},Vi=function(nn){return ur*((wa(Fa)*(da(Sn=Fa+zt*nn)/wa(Sn))-da(Fa))/Ur)/Er;var Sn},ji=(Qr(!0)-Fa)/zt;if(Math.abs(Er)<1e-6||!isFinite(ji)){if(Math.abs(ur-mr)<1e-6)return this.easeTo(R,ae);let nn=mr0,fi=Sn=>Math.exp(nn*zt*Sn)}return R.duration="duration"in R?+R.duration:1e3*ji/("screenSpeed"in R?+R.screenSpeed/zt:+R.speed),R.maxDuration&&R.duration>R.maxDuration&&(R.duration=0),this._zooming=!0,this._rotating=pt!==$t,this._pitching=wr!==At,this._padding=!Ae.isPaddingEqual(Tr),this._prepareEase(ae,!1),this.terrain&&this._prepareElevation(Je),this._ease(nn=>{let Sn=nn*ji,Zn=1/fi(Sn);Ae.zoom=nn===1?lt:Be+Ae.scaleZoom(Zn),this._rotating&&(Ae.bearing=t.y.number(pt,$t,nn)),this._pitching&&(Ae.pitch=t.y.number(At,wr,nn)),this._padding&&(Ae.interpolatePadding(Nt,Tr,nn),sa=Ae.centerPoint.add(Kr)),this.terrain&&!R.freezeElevation&&this._updateElevation(nn);let On=nn===1?Je:Ae.unproject(Ct.add(Tt.mult(Vi(Sn))).mult(Zn));Ae.setLocationAtPoint(Ae.renderWorldCopies?On.wrap():On,sa),this._applyUpdatedTransform(Ae),this._fireMoveEvents(ae)},()=>{this.terrain&&R.freezeElevation&&this._finalizeElevation(),this._afterEase(ae)},R),this}isEasing(){return!!this._easeFrameId}stop(){return this._stop()}_stop(R,ae){var we;if(this._easeFrameId&&(this._cancelRenderFrame(this._easeFrameId),delete this._easeFrameId,delete this._onEaseFrame),this._onEaseEnd){let Ae=this._onEaseEnd;delete this._onEaseEnd,Ae.call(this,ae)}return R||(we=this.handlers)===null||we===void 0||we.stop(!1),this}_ease(R,ae,we){we.animate===!1||we.duration===0?(R(1),ae()):(this._easeStart=n.now(),this._easeOptions=we,this._onEaseFrame=R,this._onEaseEnd=ae,this._easeFrameId=this._requestRenderFrame(this._renderFrameCallback))}_normalizeBearing(R,ae){R=t.b3(R,-180,180);let we=Math.abs(R-ae);return Math.abs(R-360-ae)180?-360:we<-180?360:0}queryTerrainElevation(R){return this.terrain?this.terrain.getElevationForLngLatZoom(t.N.convert(R),this.transform.tileZoom)-this.transform.elevation:null}}let $n={compact:!0,customAttribution:'MapLibre'};class lo{constructor(R=$n){this._toggleAttribution=()=>{this._container.classList.contains("maplibregl-compact")&&(this._container.classList.contains("maplibregl-compact-show")?(this._container.setAttribute("open",""),this._container.classList.remove("maplibregl-compact-show")):(this._container.classList.add("maplibregl-compact-show"),this._container.removeAttribute("open")))},this._updateData=ae=>{!ae||ae.sourceDataType!=="metadata"&&ae.sourceDataType!=="visibility"&&ae.dataType!=="style"&&ae.type!=="terrain"||this._updateAttributions()},this._updateCompact=()=>{this._map.getCanvasContainer().offsetWidth<=640||this._compact?this._compact===!1?this._container.setAttribute("open",""):this._container.classList.contains("maplibregl-compact")||this._container.classList.contains("maplibregl-attrib-empty")||(this._container.setAttribute("open",""),this._container.classList.add("maplibregl-compact","maplibregl-compact-show")):(this._container.setAttribute("open",""),this._container.classList.contains("maplibregl-compact")&&this._container.classList.remove("maplibregl-compact","maplibregl-compact-show"))},this._updateCompactMinimize=()=>{this._container.classList.contains("maplibregl-compact")&&this._container.classList.contains("maplibregl-compact-show")&&this._container.classList.remove("maplibregl-compact-show")},this.options=R}getDefaultPosition(){return"bottom-right"}onAdd(R){return this._map=R,this._compact=this.options.compact,this._container=i.create("details","maplibregl-ctrl maplibregl-ctrl-attrib"),this._compactButton=i.create("summary","maplibregl-ctrl-attrib-button",this._container),this._compactButton.addEventListener("click",this._toggleAttribution),this._setElementTitle(this._compactButton,"ToggleAttribution"),this._innerContainer=i.create("div","maplibregl-ctrl-attrib-inner",this._container),this._updateAttributions(),this._updateCompact(),this._map.on("styledata",this._updateData),this._map.on("sourcedata",this._updateData),this._map.on("terrain",this._updateData),this._map.on("resize",this._updateCompact),this._map.on("drag",this._updateCompactMinimize),this._container}onRemove(){i.remove(this._container),this._map.off("styledata",this._updateData),this._map.off("sourcedata",this._updateData),this._map.off("terrain",this._updateData),this._map.off("resize",this._updateCompact),this._map.off("drag",this._updateCompactMinimize),this._map=void 0,this._compact=void 0,this._attribHTML=void 0}_setElementTitle(R,ae){let we=this._map._getUIString(`AttributionControl.${ae}`);R.title=we,R.setAttribute("aria-label",we)}_updateAttributions(){if(!this._map.style)return;let R=[];if(this.options.customAttribution&&(Array.isArray(this.options.customAttribution)?R=R.concat(this.options.customAttribution.map(Ae=>typeof Ae!="string"?"":Ae)):typeof this.options.customAttribution=="string"&&R.push(this.options.customAttribution)),this._map.style.stylesheet){let Ae=this._map.style.stylesheet;this.styleOwner=Ae.owner,this.styleId=Ae.id}let ae=this._map.style.sourceCaches;for(let Ae in ae){let Be=ae[Ae];if(Be.used||Be.usedForTerrain){let pt=Be.getSource();pt.attribution&&R.indexOf(pt.attribution)<0&&R.push(pt.attribution)}}R=R.filter(Ae=>String(Ae).trim()),R.sort((Ae,Be)=>Ae.length-Be.length),R=R.filter((Ae,Be)=>{for(let pt=Be+1;pt=0)return!1;return!0});let we=R.join(" | ");we!==this._attribHTML&&(this._attribHTML=we,R.length?(this._innerContainer.innerHTML=we,this._container.classList.remove("maplibregl-attrib-empty")):this._container.classList.add("maplibregl-attrib-empty"),this._updateCompact(),this._editLink=null)}}class An{constructor(R={}){this._updateCompact=()=>{let ae=this._container.children;if(ae.length){let we=ae[0];this._map.getCanvasContainer().offsetWidth<=640||this._compact?this._compact!==!1&&we.classList.add("maplibregl-compact"):we.classList.remove("maplibregl-compact")}},this.options=R}getDefaultPosition(){return"bottom-left"}onAdd(R){this._map=R,this._compact=this.options&&this.options.compact,this._container=i.create("div","maplibregl-ctrl");let ae=i.create("a","maplibregl-ctrl-logo");return ae.target="_blank",ae.rel="noopener nofollow",ae.href="https://maplibre.org/",ae.setAttribute("aria-label",this._map._getUIString("LogoControl.Title")),ae.setAttribute("rel","noopener nofollow"),this._container.appendChild(ae),this._container.style.display="block",this._map.on("resize",this._updateCompact),this._updateCompact(),this._container}onRemove(){i.remove(this._container),this._map.off("resize",this._updateCompact),this._map=void 0,this._compact=void 0}}class un{constructor(){this._queue=[],this._id=0,this._cleared=!1,this._currentlyRunning=!1}add(R){let ae=++this._id;return this._queue.push({callback:R,id:ae,cancelled:!1}),ae}remove(R){let ae=this._currentlyRunning,we=ae?this._queue.concat(ae):this._queue;for(let Ae of we)if(Ae.id===R)return void(Ae.cancelled=!0)}run(R=0){if(this._currentlyRunning)throw new Error("Attempting to run(), but is already running.");let ae=this._currentlyRunning=this._queue;this._queue=[];for(let we of ae)if(!we.cancelled&&(we.callback(R),this._cleared))break;this._cleared=!1,this._currentlyRunning=!1}clear(){this._currentlyRunning&&(this._cleared=!0),this._queue=[]}}var yo=t.Y([{name:"a_pos3d",type:"Int16",components:3}]);class $o extends t.E{constructor(R){super(),this.sourceCache=R,this._tiles={},this._renderableTilesKeys=[],this._sourceTileCache={},this.minzoom=0,this.maxzoom=22,this.tileSize=512,this.deltaZoom=1,R.usedForTerrain=!0,R.tileSize=this.tileSize*2**this.deltaZoom}destruct(){this.sourceCache.usedForTerrain=!1,this.sourceCache.tileSize=null}update(R,ae){this.sourceCache.update(R,ae),this._renderableTilesKeys=[];let we={};for(let Ae of R.coveringTiles({tileSize:this.tileSize,minzoom:this.minzoom,maxzoom:this.maxzoom,reparseOverscaled:!1,terrain:ae}))we[Ae.key]=!0,this._renderableTilesKeys.push(Ae.key),this._tiles[Ae.key]||(Ae.posMatrix=new Float64Array(16),t.aP(Ae.posMatrix,0,t.X,0,t.X,0,1),this._tiles[Ae.key]=new st(Ae,this.tileSize));for(let Ae in this._tiles)we[Ae]||delete this._tiles[Ae]}freeRtt(R){for(let ae in this._tiles){let we=this._tiles[ae];(!R||we.tileID.equals(R)||we.tileID.isChildOf(R)||R.isChildOf(we.tileID))&&(we.rtt=[])}}getRenderableTiles(){return this._renderableTilesKeys.map(R=>this.getTileByID(R))}getTileByID(R){return this._tiles[R]}getTerrainCoords(R){let ae={};for(let we of this._renderableTilesKeys){let Ae=this._tiles[we].tileID;if(Ae.canonical.equals(R.canonical)){let Be=R.clone();Be.posMatrix=new Float64Array(16),t.aP(Be.posMatrix,0,t.X,0,t.X,0,1),ae[we]=Be}else if(Ae.canonical.isChildOf(R.canonical)){let Be=R.clone();Be.posMatrix=new Float64Array(16);let pt=Ae.canonical.z-R.canonical.z,At=Ae.canonical.x-(Ae.canonical.x>>pt<>pt<>pt;t.aP(Be.posMatrix,0,$t,0,$t,0,1),t.J(Be.posMatrix,Be.posMatrix,[-At*$t,-Nt*$t,0]),ae[we]=Be}else if(R.canonical.isChildOf(Ae.canonical)){let Be=R.clone();Be.posMatrix=new Float64Array(16);let pt=R.canonical.z-Ae.canonical.z,At=R.canonical.x-(R.canonical.x>>pt<>pt<>pt;t.aP(Be.posMatrix,0,t.X,0,t.X,0,1),t.J(Be.posMatrix,Be.posMatrix,[At*$t,Nt*$t,0]),t.K(Be.posMatrix,Be.posMatrix,[1/2**pt,1/2**pt,0]),ae[we]=Be}}return ae}getSourceTile(R,ae){let we=this.sourceCache._source,Ae=R.overscaledZ-this.deltaZoom;if(Ae>we.maxzoom&&(Ae=we.maxzoom),Ae=we.minzoom&&(!Be||!Be.dem);)Be=this.sourceCache.getTileByID(R.scaledTo(Ae--).key);return Be}tilesAfterTime(R=Date.now()){return Object.values(this._tiles).filter(ae=>ae.timeAdded>=R)}}class As{constructor(R,ae,we){this.painter=R,this.sourceCache=new $o(ae),this.options=we,this.exaggeration=typeof we.exaggeration=="number"?we.exaggeration:1,this.qualityFactor=2,this.meshSize=128,this._demMatrixCache={},this.coordsIndex=[],this._coordsTextureSize=1024}getDEMElevation(R,ae,we,Ae=t.X){var Be;if(!(ae>=0&&ae=0&&weR.canonical.z&&(R.canonical.z>=Ae?Be=R.canonical.z-Ae:t.w("cannot calculate elevation if elevation maxzoom > source.maxzoom"));let pt=R.canonical.x-(R.canonical.x>>Be<>Be<>8<<4|Be>>8,ae[pt+3]=0;let we=new t.R({width:this._coordsTextureSize,height:this._coordsTextureSize},new Uint8Array(ae.buffer)),Ae=new u(R,we,R.gl.RGBA,{premultiply:!1});return Ae.bind(R.gl.NEAREST,R.gl.CLAMP_TO_EDGE),this._coordsTexture=Ae,Ae}pointCoordinate(R){this.painter.maybeDrawDepthAndCoords(!0);let ae=new Uint8Array(4),we=this.painter.context,Ae=we.gl,Be=Math.round(R.x*this.painter.pixelRatio/devicePixelRatio),pt=Math.round(R.y*this.painter.pixelRatio/devicePixelRatio),At=Math.round(this.painter.height/devicePixelRatio);we.bindFramebuffer.set(this.getFramebuffer("coords").framebuffer),Ae.readPixels(Be,At-pt-1,1,1,Ae.RGBA,Ae.UNSIGNED_BYTE,ae),we.bindFramebuffer.set(null);let Nt=ae[0]+(ae[2]>>4<<8),$t=ae[1]+((15&ae[2])<<8),wr=this.coordsIndex[255-ae[3]],Tr=wr&&this.sourceCache.getTileByID(wr);if(!Tr)return null;let Kr=this._coordsTextureSize,sa=(1<R.id!==ae),this._recentlyUsed.push(R.id)}stampObject(R){R.stamp=++this._stamp}getOrCreateFreeObject(){for(let ae of this._recentlyUsed)if(!this._objects[ae].inUse)return this._objects[ae];if(this._objects.length>=this._size)throw new Error("No free RenderPool available, call freeAllObjects() required!");let R=this._createObject(this._objects.length);return this._objects.push(R),R}freeObject(R){R.inUse=!1}freeAllObjects(){for(let R of this._objects)this.freeObject(R)}isFull(){return!(this._objects.length!R.inUse)===!1}}let zs={background:!0,fill:!0,line:!0,raster:!0,hillshade:!0};class Qs{constructor(R,ae){this.painter=R,this.terrain=ae,this.pool=new tl(R.context,30,ae.sourceCache.tileSize*ae.qualityFactor)}destruct(){this.pool.destruct()}getTexture(R){return this.pool.getObjectForId(R.rtt[this._stacks.length-1].id).texture}prepareForRender(R,ae){this._stacks=[],this._prevType=null,this._rttTiles=[],this._renderableTiles=this.terrain.sourceCache.getRenderableTiles(),this._renderableLayerIds=R._order.filter(we=>!R._layers[we].isHidden(ae)),this._coordsDescendingInv={};for(let we in R.sourceCaches){this._coordsDescendingInv[we]={};let Ae=R.sourceCaches[we].getVisibleCoordinates();for(let Be of Ae){let pt=this.terrain.sourceCache.getTerrainCoords(Be);for(let At in pt)this._coordsDescendingInv[we][At]||(this._coordsDescendingInv[we][At]=[]),this._coordsDescendingInv[we][At].push(pt[At])}}this._coordsDescendingInvStr={};for(let we of R._order){let Ae=R._layers[we],Be=Ae.source;if(zs[Ae.type]&&!this._coordsDescendingInvStr[Be]){this._coordsDescendingInvStr[Be]={};for(let pt in this._coordsDescendingInv[Be])this._coordsDescendingInvStr[Be][pt]=this._coordsDescendingInv[Be][pt].map(At=>At.key).sort().join()}}for(let we of this._renderableTiles)for(let Ae in this._coordsDescendingInvStr){let Be=this._coordsDescendingInvStr[Ae][we.tileID.key];Be&&Be!==we.rttCoords[Ae]&&(we.rtt=[])}}renderLayer(R){if(R.isHidden(this.painter.transform.zoom))return!1;let ae=R.type,we=this.painter,Ae=this._renderableLayerIds[this._renderableLayerIds.length-1]===R.id;if(zs[ae]&&(this._prevType&&zs[this._prevType]||this._stacks.push([]),this._prevType=ae,this._stacks[this._stacks.length-1].push(R.id),!Ae))return!0;if(zs[this._prevType]||zs[ae]&&Ae){this._prevType=ae;let Be=this._stacks.length-1,pt=this._stacks[Be]||[];for(let At of this._renderableTiles){if(this.pool.isFull()&&(ml(this.painter,this.terrain,this._rttTiles),this._rttTiles=[],this.pool.freeAllObjects()),this._rttTiles.push(At),At.rtt[Be]){let $t=this.pool.getObjectForId(At.rtt[Be].id);if($t.stamp===At.rtt[Be].stamp){this.pool.useObject($t);continue}}let Nt=this.pool.getOrCreateFreeObject();this.pool.useObject(Nt),this.pool.stampObject(Nt),At.rtt[Be]={id:Nt.id,stamp:Nt.stamp},we.context.bindFramebuffer.set(Nt.fbo.framebuffer),we.context.clear({color:t.aM.transparent,stencil:0}),we.currentStencilSource=void 0;for(let $t=0;$t{Ue.touchstart=Ue.dragStart,Ue.touchmoveWindow=Ue.dragMove,Ue.touchend=Ue.dragEnd},Nn={showCompass:!0,showZoom:!0,visualizePitch:!1};class Ro{constructor(R,ae,we=!1){this.mousedown=pt=>{this.startMouse(t.e({},pt,{ctrlKey:!0,preventDefault:()=>pt.preventDefault()}),i.mousePos(this.element,pt)),i.addEventListener(window,"mousemove",this.mousemove),i.addEventListener(window,"mouseup",this.mouseup)},this.mousemove=pt=>{this.moveMouse(pt,i.mousePos(this.element,pt))},this.mouseup=pt=>{this.mouseRotate.dragEnd(pt),this.mousePitch&&this.mousePitch.dragEnd(pt),this.offTemp()},this.touchstart=pt=>{pt.targetTouches.length!==1?this.reset():(this._startPos=this._lastPos=i.touchPos(this.element,pt.targetTouches)[0],this.startTouch(pt,this._startPos),i.addEventListener(window,"touchmove",this.touchmove,{passive:!1}),i.addEventListener(window,"touchend",this.touchend))},this.touchmove=pt=>{pt.targetTouches.length!==1?this.reset():(this._lastPos=i.touchPos(this.element,pt.targetTouches)[0],this.moveTouch(pt,this._lastPos))},this.touchend=pt=>{pt.targetTouches.length===0&&this._startPos&&this._lastPos&&this._startPos.dist(this._lastPos){this.mouseRotate.reset(),this.mousePitch&&this.mousePitch.reset(),this.touchRotate.reset(),this.touchPitch&&this.touchPitch.reset(),delete this._startPos,delete this._lastPos,this.offTemp()},this._clickTolerance=10;let Ae=R.dragRotate._mouseRotate.getClickTolerance(),Be=R.dragRotate._mousePitch.getClickTolerance();this.element=ae,this.mouseRotate=nu({clickTolerance:Ae,enable:!0}),this.touchRotate=(({enable:pt,clickTolerance:At,bearingDegreesPerPixelMoved:Nt=.8})=>{let $t=new Yc;return new Hu({clickTolerance:At,move:(wr,Tr)=>({bearingDelta:(Tr.x-wr.x)*Nt}),moveStateManager:$t,enable:pt,assignEvents:ol})})({clickTolerance:Ae,enable:!0}),this.map=R,we&&(this.mousePitch=Vf({clickTolerance:Be,enable:!0}),this.touchPitch=(({enable:pt,clickTolerance:At,pitchDegreesPerPixelMoved:Nt=-.5})=>{let $t=new Yc;return new Hu({clickTolerance:At,move:(wr,Tr)=>({pitchDelta:(Tr.y-wr.y)*Nt}),moveStateManager:$t,enable:pt,assignEvents:ol})})({clickTolerance:Be,enable:!0})),i.addEventListener(ae,"mousedown",this.mousedown),i.addEventListener(ae,"touchstart",this.touchstart,{passive:!1}),i.addEventListener(ae,"touchcancel",this.reset)}startMouse(R,ae){this.mouseRotate.dragStart(R,ae),this.mousePitch&&this.mousePitch.dragStart(R,ae),i.disableDrag()}startTouch(R,ae){this.touchRotate.dragStart(R,ae),this.touchPitch&&this.touchPitch.dragStart(R,ae),i.disableDrag()}moveMouse(R,ae){let we=this.map,{bearingDelta:Ae}=this.mouseRotate.dragMove(R,ae)||{};if(Ae&&we.setBearing(we.getBearing()+Ae),this.mousePitch){let{pitchDelta:Be}=this.mousePitch.dragMove(R,ae)||{};Be&&we.setPitch(we.getPitch()+Be)}}moveTouch(R,ae){let we=this.map,{bearingDelta:Ae}=this.touchRotate.dragMove(R,ae)||{};if(Ae&&we.setBearing(we.getBearing()+Ae),this.touchPitch){let{pitchDelta:Be}=this.touchPitch.dragMove(R,ae)||{};Be&&we.setPitch(we.getPitch()+Be)}}off(){let R=this.element;i.removeEventListener(R,"mousedown",this.mousedown),i.removeEventListener(R,"touchstart",this.touchstart,{passive:!1}),i.removeEventListener(window,"touchmove",this.touchmove,{passive:!1}),i.removeEventListener(window,"touchend",this.touchend),i.removeEventListener(R,"touchcancel",this.reset),this.offTemp()}offTemp(){i.enableDrag(),i.removeEventListener(window,"mousemove",this.mousemove),i.removeEventListener(window,"mouseup",this.mouseup),i.removeEventListener(window,"touchmove",this.touchmove,{passive:!1}),i.removeEventListener(window,"touchend",this.touchend)}}let Zs;function Ls(Ue,R,ae){let we=new t.N(Ue.lng,Ue.lat);if(Ue=new t.N(Ue.lng,Ue.lat),R){let Ae=new t.N(Ue.lng-360,Ue.lat),Be=new 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pt="";this._pitchAlignment==="viewport"||this._pitchAlignment==="auto"?pt="rotateX(0deg)":this._pitchAlignment==="map"&&(pt=`rotateX(${this._map.getPitch()}deg)`),this._subpixelPositioning||ae&&ae.type!=="moveend"||(this._pos=this._pos.round()),i.setTransform(this._element,`${lu[this._anchor]} translate(${this._pos.x}px, ${this._pos.y}px) ${pt} ${Be}`),n.frameAsync(new AbortController).then(()=>{this._updateOpacity(ae&&ae.type==="moveend")}).catch(()=>{})},this._onMove=ae=>{if(!this._isDragging){let we=this._clickTolerance||this._map._clickTolerance;this._isDragging=ae.point.dist(this._pointerdownPos)>=we}this._isDragging&&(this._pos=ae.point.sub(this._positionDelta),this._lngLat=this._map.unproject(this._pos),this.setLngLat(this._lngLat),this._element.style.pointerEvents="none",this._state==="pending"&&(this._state="active",this.fire(new t.k("dragstart"))),this.fire(new t.k("drag")))},this._onUp=()=>{this._element.style.pointerEvents="auto",this._positionDelta=null,this._pointerdownPos=null,this._isDragging=!1,this._map.off("mousemove",this._onMove),this._map.off("touchmove",this._onMove),this._state==="active"&&this.fire(new t.k("dragend")),this._state="inactive"},this._addDragHandler=ae=>{this._element.contains(ae.originalEvent.target)&&(ae.preventDefault(),this._positionDelta=ae.point.sub(this._pos).add(this._offset),this._pointerdownPos=ae.point,this._state="pending",this._map.on("mousemove",this._onMove),this._map.on("touchmove",this._onMove),this._map.once("mouseup",this._onUp),this._map.once("touchend",this._onUp))},this._anchor=R&&R.anchor||"center",this._color=R&&R.color||"#3FB1CE",this._scale=R&&R.scale||1,this._draggable=R&&R.draggable||!1,this._clickTolerance=R&&R.clickTolerance||0,this._subpixelPositioning=R&&R.subpixelPositioning||!1,this._isDragging=!1,this._state="inactive",this._rotation=R&&R.rotation||0,this._rotationAlignment=R&&R.rotationAlignment||"auto",this._pitchAlignment=R&&R.pitchAlignment&&R.pitchAlignment!=="auto"?R.pitchAlignment:this._rotationAlignment,this.setOpacity(),this.setOpacity(R?.opacity,R?.opacityWhenCovered),R&&R.element)this._element=R.element,this._offset=t.P.convert(R&&R.offset||[0,0]);else{this._defaultMarker=!0,this._element=i.create("div");let 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lt=i.createNS("http://www.w3.org/2000/svg","circle");lt.setAttributeNS(null,"fill","#FFFFFF"),lt.setAttributeNS(null,"cx","5.5"),lt.setAttributeNS(null,"cy","5.5"),lt.setAttributeNS(null,"r","5.4999962"),He.appendChild(Je),He.appendChild(lt),pt.appendChild(At),pt.appendChild($t),pt.appendChild(Tr),pt.appendChild(sa),pt.appendChild(He),ae.appendChild(pt),ae.setAttributeNS(null,"height",we*this._scale+"px"),ae.setAttributeNS(null,"width",Ae*this._scale+"px"),this._element.appendChild(ae),this._offset=t.P.convert(R&&R.offset||[0,-14])}if(this._element.classList.add("maplibregl-marker"),this._element.addEventListener("dragstart",ae=>{ae.preventDefault()}),this._element.addEventListener("mousedown",ae=>{ae.preventDefault()}),Iu(this._element,this._anchor,"marker"),R&&R.className)for(let ae of R.className.split(" "))this._element.classList.add(ae);this._popup=null}addTo(R){return this.remove(),this._map=R,this._element.setAttribute("aria-label",R._getUIString("Marker.Title")),R.getCanvasContainer().appendChild(this._element),R.on("move",this._update),R.on("moveend",this._update),R.on("terrain",this._update),this.setDraggable(this._draggable),this._update(),this._map.on("click",this._onMapClick),this}remove(){return this._opacityTimeout&&(clearTimeout(this._opacityTimeout),delete this._opacityTimeout),this._map&&(this._map.off("click",this._onMapClick),this._map.off("move",this._update),this._map.off("moveend",this._update),this._map.off("terrain",this._update),this._map.off("mousedown",this._addDragHandler),this._map.off("touchstart",this._addDragHandler),this._map.off("mouseup",this._onUp),this._map.off("touchend",this._onUp),this._map.off("mousemove",this._onMove),this._map.off("touchmove",this._onMove),delete this._map),i.remove(this._element),this._popup&&this._popup.remove(),this}getLngLat(){return this._lngLat}setLngLat(R){return this._lngLat=t.N.convert(R),this._pos=null,this._popup&&this._popup.setLngLat(this._lngLat),this._update(),this}getElement(){return this._element}setPopup(R){if(this._popup&&(this._popup.remove(),this._popup=null,this._element.removeEventListener("keypress",this._onKeyPress),this._originalTabIndex||this._element.removeAttribute("tabindex")),R){if(!("offset"in R.options)){let Ae=Math.abs(13.5)/Math.SQRT2;R.options.offset=this._defaultMarker?{top:[0,0],"top-left":[0,0],"top-right":[0,0],bottom:[0,-38.1],"bottom-left":[Ae,-1*(38.1-13.5+Ae)],"bottom-right":[-Ae,-1*(38.1-13.5+Ae)],left:[13.5,-1*(38.1-13.5)],right:[-13.5,-1*(38.1-13.5)]}:this._offset}this._popup=R,this._originalTabIndex=this._element.getAttribute("tabindex"),this._originalTabIndex||this._element.setAttribute("tabindex","0"),this._element.addEventListener("keypress",this._onKeyPress)}return this}setSubpixelPositioning(R){return this._subpixelPositioning=R,this}getPopup(){return this._popup}togglePopup(){let 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this._rotationAlignment=R||"auto",this._update(),this}getRotationAlignment(){return this._rotationAlignment}setPitchAlignment(R){return this._pitchAlignment=R&&R!=="auto"?R:this._rotationAlignment,this._update(),this}getPitchAlignment(){return this._pitchAlignment}setOpacity(R,ae){return R===void 0&&ae===void 0&&(this._opacity="1",this._opacityWhenCovered="0.2"),R!==void 0&&(this._opacity=R),ae!==void 0&&(this._opacityWhenCovered=ae),this._map&&this._updateOpacity(!0),this}}let Ic={positionOptions:{enableHighAccuracy:!1,maximumAge:0,timeout:6e3},fitBoundsOptions:{maxZoom:15},trackUserLocation:!1,showAccuracyCircle:!0,showUserLocation:!0},_u=0,Rc=!1,Tu={maxWidth:100,unit:"metric"};function _c(Ue,R,ae){let we=ae&&ae.maxWidth||100,Ae=Ue._container.clientHeight/2,Be=Ue.unproject([0,Ae]),pt=Ue.unproject([we,Ae]),At=Be.distanceTo(pt);if(ae&&ae.unit==="imperial"){let Nt=3.2808*At;Nt>5280?uo(R,we,Nt/5280,Ue._getUIString("ScaleControl.Miles")):uo(R,we,Nt,Ue._getUIString("ScaleControl.Feet"))}else ae&&ae.unit==="nautical"?uo(R,we,At/1852,Ue._getUIString("ScaleControl.NauticalMiles")):At>=1e3?uo(R,we,At/1e3,Ue._getUIString("ScaleControl.Kilometers")):uo(R,we,At,Ue._getUIString("ScaleControl.Meters"))}function uo(Ue,R,ae,we){let Ae=function(Be){let pt=Math.pow(10,`${Math.floor(Be)}`.length-1),At=Be/pt;return At=At>=10?10:At>=5?5:At>=3?3:At>=2?2:At>=1?1:function(Nt){let $t=Math.pow(10,Math.ceil(-Math.log(Nt)/Math.LN10));return Math.round(Nt*$t)/$t}(At),pt*At}(ae);Ue.style.width=R*(Ae/ae)+"px",Ue.innerHTML=`${Ae} ${we}`}let Fo={closeButton:!0,closeOnClick:!0,focusAfterOpen:!0,className:"",maxWidth:"240px",subpixelPositioning:!1},Dc=["a[href]","[tabindex]:not([tabindex='-1'])","[contenteditable]:not([contenteditable='false'])","button:not([disabled])","input:not([disabled])","select:not([disabled])","textarea:not([disabled])"].join(", ");function uc(Ue){if(Ue){if(typeof Ue=="number"){let R=Math.round(Math.abs(Ue)/Math.SQRT2);return{center:new t.P(0,0),top:new t.P(0,Ue),"top-left":new t.P(R,R),"top-right":new t.P(-R,R),bottom:new t.P(0,-Ue),"bottom-left":new t.P(R,-R),"bottom-right":new t.P(-R,-R),left:new t.P(Ue,0),right:new t.P(-Ue,0)}}if(Ue instanceof t.P||Array.isArray(Ue)){let R=t.P.convert(Ue);return{center:R,top:R,"top-left":R,"top-right":R,bottom:R,"bottom-left":R,"bottom-right":R,left:R,right:R}}return{center:t.P.convert(Ue.center||[0,0]),top:t.P.convert(Ue.top||[0,0]),"top-left":t.P.convert(Ue["top-left"]||[0,0]),"top-right":t.P.convert(Ue["top-right"]||[0,0]),bottom:t.P.convert(Ue.bottom||[0,0]),"bottom-left":t.P.convert(Ue["bottom-left"]||[0,0]),"bottom-right":t.P.convert(Ue["bottom-right"]||[0,0]),left:t.P.convert(Ue.left||[0,0]),right:t.P.convert(Ue.right||[0,0])}}return uc(new t.P(0,0))}let Yu=r;e.AJAXError=t.bh,e.Evented=t.E,e.LngLat=t.N,e.MercatorCoordinate=t.Z,e.Point=t.P,e.addProtocol=t.bi,e.config=t.a,e.removeProtocol=t.bj,e.AttributionControl=lo,e.BoxZoomHandler=Pu,e.CanvasSource=tt,e.CooperativeGesturesHandler=Di,e.DoubleClickZoomHandler=ui,e.DragPanHandler=Qi,e.DragRotateHandler=dn,e.EdgeInsets=mu,e.FullscreenControl=class extends t.E{constructor(Ue={}){super(),this._onFullscreenChange=()=>{var R;let ae=window.document.fullscreenElement||window.document.mozFullScreenElement||window.document.webkitFullscreenElement||window.document.msFullscreenElement;for(;!((R=ae?.shadowRoot)===null||R===void 0)&&R.fullscreenElement;)ae=ae.shadowRoot.fullscreenElement;ae===this._container!==this._fullscreen&&this._handleFullscreenChange()},this._onClickFullscreen=()=>{this._isFullscreen()?this._exitFullscreen():this._requestFullscreen()},this._fullscreen=!1,Ue&&Ue.container&&(Ue.container instanceof HTMLElement?this._container=Ue.container:t.w("Full screen control 'container' must be a DOM element.")),"onfullscreenchange"in document?this._fullscreenchange="fullscreenchange":"onmozfullscreenchange"in document?this._fullscreenchange="mozfullscreenchange":"onwebkitfullscreenchange"in document?this._fullscreenchange="webkitfullscreenchange":"onmsfullscreenchange"in document&&(this._fullscreenchange="MSFullscreenChange")}onAdd(Ue){return this._map=Ue,this._container||(this._container=this._map.getContainer()),this._controlContainer=i.create("div","maplibregl-ctrl maplibregl-ctrl-group"),this._setupUI(),this._controlContainer}onRemove(){i.remove(this._controlContainer),this._map=null,window.document.removeEventListener(this._fullscreenchange,this._onFullscreenChange)}_setupUI(){let Ue=this._fullscreenButton=i.create("button","maplibregl-ctrl-fullscreen",this._controlContainer);i.create("span","maplibregl-ctrl-icon",Ue).setAttribute("aria-hidden","true"),Ue.type="button",this._updateTitle(),this._fullscreenButton.addEventListener("click",this._onClickFullscreen),window.document.addEventListener(this._fullscreenchange,this._onFullscreenChange)}_updateTitle(){let Ue=this._getTitle();this._fullscreenButton.setAttribute("aria-label",Ue),this._fullscreenButton.title=Ue}_getTitle(){return this._map._getUIString(this._isFullscreen()?"FullscreenControl.Exit":"FullscreenControl.Enter")}_isFullscreen(){return this._fullscreen}_handleFullscreenChange(){this._fullscreen=!this._fullscreen,this._fullscreenButton.classList.toggle("maplibregl-ctrl-shrink"),this._fullscreenButton.classList.toggle("maplibregl-ctrl-fullscreen"),this._updateTitle(),this._fullscreen?(this.fire(new t.k("fullscreenstart")),this._prevCooperativeGesturesEnabled=this._map.cooperativeGestures.isEnabled(),this._map.cooperativeGestures.disable()):(this.fire(new t.k("fullscreenend")),this._prevCooperativeGesturesEnabled&&this._map.cooperativeGestures.enable())}_exitFullscreen(){window.document.exitFullscreen?window.document.exitFullscreen():window.document.mozCancelFullScreen?window.document.mozCancelFullScreen():window.document.msExitFullscreen?window.document.msExitFullscreen():window.document.webkitCancelFullScreen?window.document.webkitCancelFullScreen():this._togglePseudoFullScreen()}_requestFullscreen(){this._container.requestFullscreen?this._container.requestFullscreen():this._container.mozRequestFullScreen?this._container.mozRequestFullScreen():this._container.msRequestFullscreen?this._container.msRequestFullscreen():this._container.webkitRequestFullscreen?this._container.webkitRequestFullscreen():this._togglePseudoFullScreen()}_togglePseudoFullScreen(){this._container.classList.toggle("maplibregl-pseudo-fullscreen"),this._handleFullscreenChange(),this._map.resize()}},e.GeoJSONSource=Fe,e.GeolocateControl=class extends t.E{constructor(Ue){super(),this._onSuccess=R=>{if(this._map){if(this._isOutOfMapMaxBounds(R))return this._setErrorState(),this.fire(new t.k("outofmaxbounds",R)),this._updateMarker(),void this._finish();if(this.options.trackUserLocation)switch(this._lastKnownPosition=R,this._watchState){case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-active");break;case"BACKGROUND":case"BACKGROUND_ERROR":this._watchState="BACKGROUND",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-background");break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}this.options.showUserLocation&&this._watchState!=="OFF"&&this._updateMarker(R),this.options.trackUserLocation&&this._watchState!=="ACTIVE_LOCK"||this._updateCamera(R),this.options.showUserLocation&&this._dotElement.classList.remove("maplibregl-user-location-dot-stale"),this.fire(new t.k("geolocate",R)),this._finish()}},this._updateCamera=R=>{let ae=new t.N(R.coords.longitude,R.coords.latitude),we=R.coords.accuracy,Ae=this._map.getBearing(),Be=t.e({bearing:Ae},this.options.fitBoundsOptions),pt=re.fromLngLat(ae,we);this._map.fitBounds(pt,Be,{geolocateSource:!0})},this._updateMarker=R=>{if(R){let ae=new t.N(R.coords.longitude,R.coords.latitude);this._accuracyCircleMarker.setLngLat(ae).addTo(this._map),this._userLocationDotMarker.setLngLat(ae).addTo(this._map),this._accuracy=R.coords.accuracy,this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()}else this._userLocationDotMarker.remove(),this._accuracyCircleMarker.remove()},this._onZoom=()=>{this.options.showUserLocation&&this.options.showAccuracyCircle&&this._updateCircleRadius()},this._onError=R=>{if(this._map){if(this.options.trackUserLocation)if(R.code===1){this._watchState="OFF",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background-error"),this._geolocateButton.disabled=!0;let ae=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.title=ae,this._geolocateButton.setAttribute("aria-label",ae),this._geolocationWatchID!==void 0&&this._clearWatch()}else{if(R.code===3&&Rc)return;this._setErrorState()}this._watchState!=="OFF"&&this.options.showUserLocation&&this._dotElement.classList.add("maplibregl-user-location-dot-stale"),this.fire(new t.k("error",R)),this._finish()}},this._finish=()=>{this._timeoutId&&clearTimeout(this._timeoutId),this._timeoutId=void 0},this._setupUI=()=>{this._map&&(this._container.addEventListener("contextmenu",R=>R.preventDefault()),this._geolocateButton=i.create("button","maplibregl-ctrl-geolocate",this._container),i.create("span","maplibregl-ctrl-icon",this._geolocateButton).setAttribute("aria-hidden","true"),this._geolocateButton.type="button",this._geolocateButton.disabled=!0)},this._finishSetupUI=R=>{if(this._map){if(R===!1){t.w("Geolocation support is not available so the GeolocateControl will be disabled.");let ae=this._map._getUIString("GeolocateControl.LocationNotAvailable");this._geolocateButton.disabled=!0,this._geolocateButton.title=ae,this._geolocateButton.setAttribute("aria-label",ae)}else{let ae=this._map._getUIString("GeolocateControl.FindMyLocation");this._geolocateButton.disabled=!1,this._geolocateButton.title=ae,this._geolocateButton.setAttribute("aria-label",ae)}this.options.trackUserLocation&&(this._geolocateButton.setAttribute("aria-pressed","false"),this._watchState="OFF"),this.options.showUserLocation&&(this._dotElement=i.create("div","maplibregl-user-location-dot"),this._userLocationDotMarker=new Zu({element:this._dotElement}),this._circleElement=i.create("div","maplibregl-user-location-accuracy-circle"),this._accuracyCircleMarker=new Zu({element:this._circleElement,pitchAlignment:"map"}),this.options.trackUserLocation&&(this._watchState="OFF"),this._map.on("zoom",this._onZoom)),this._geolocateButton.addEventListener("click",()=>this.trigger()),this._setup=!0,this.options.trackUserLocation&&this._map.on("movestart",ae=>{ae.geolocateSource||this._watchState!=="ACTIVE_LOCK"||ae.originalEvent&&ae.originalEvent.type==="resize"||(this._watchState="BACKGROUND",this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active"),this.fire(new t.k("trackuserlocationend")),this.fire(new t.k("userlocationlostfocus")))})}},this.options=t.e({},Ic,Ue)}onAdd(Ue){return this._map=Ue,this._container=i.create("div","maplibregl-ctrl maplibregl-ctrl-group"),this._setupUI(),function(){return t._(this,arguments,void 0,function*(R=!1){if(Zs!==void 0&&!R)return Zs;if(window.navigator.permissions===void 0)return Zs=!!window.navigator.geolocation,Zs;try{Zs=(yield window.navigator.permissions.query({name:"geolocation"})).state!=="denied"}catch{Zs=!!window.navigator.geolocation}return Zs})}().then(R=>this._finishSetupUI(R)),this._container}onRemove(){this._geolocationWatchID!==void 0&&(window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0),this.options.showUserLocation&&this._userLocationDotMarker&&this._userLocationDotMarker.remove(),this.options.showAccuracyCircle&&this._accuracyCircleMarker&&this._accuracyCircleMarker.remove(),i.remove(this._container),this._map.off("zoom",this._onZoom),this._map=void 0,_u=0,Rc=!1}_isOutOfMapMaxBounds(Ue){let R=this._map.getMaxBounds(),ae=Ue.coords;return R&&(ae.longitudeR.getEast()||ae.latitudeR.getNorth())}_setErrorState(){switch(this._watchState){case"WAITING_ACTIVE":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-active-error");break;case"ACTIVE_LOCK":this._watchState="ACTIVE_ERROR",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-active-error"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-waiting");break;case"BACKGROUND":this._watchState="BACKGROUND_ERROR",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-background-error"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-waiting");break;case"ACTIVE_ERROR":break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}}_updateCircleRadius(){let Ue=this._map.getBounds(),R=Ue.getSouthEast(),ae=Ue.getNorthEast(),we=R.distanceTo(ae),Ae=Math.ceil(this._accuracy/(we/this._map._container.clientHeight)*2);this._circleElement.style.width=`${Ae}px`,this._circleElement.style.height=`${Ae}px`}trigger(){if(!this._setup)return t.w("Geolocate control triggered before added to a map"),!1;if(this.options.trackUserLocation){switch(this._watchState){case"OFF":this._watchState="WAITING_ACTIVE",this.fire(new t.k("trackuserlocationstart"));break;case"WAITING_ACTIVE":case"ACTIVE_LOCK":case"ACTIVE_ERROR":case"BACKGROUND_ERROR":_u--,Rc=!1,this._watchState="OFF",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-active-error"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background"),this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background-error"),this.fire(new t.k("trackuserlocationend"));break;case"BACKGROUND":this._watchState="ACTIVE_LOCK",this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-background"),this._lastKnownPosition&&this._updateCamera(this._lastKnownPosition),this.fire(new t.k("trackuserlocationstart")),this.fire(new t.k("userlocationfocus"));break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}switch(this._watchState){case"WAITING_ACTIVE":this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-active");break;case"ACTIVE_LOCK":this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-active");break;case"OFF":break;default:throw new Error(`Unexpected watchState ${this._watchState}`)}if(this._watchState==="OFF"&&this._geolocationWatchID!==void 0)this._clearWatch();else if(this._geolocationWatchID===void 0){let Ue;this._geolocateButton.classList.add("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","true"),_u++,_u>1?(Ue={maximumAge:6e5,timeout:0},Rc=!0):(Ue=this.options.positionOptions,Rc=!1),this._geolocationWatchID=window.navigator.geolocation.watchPosition(this._onSuccess,this._onError,Ue)}}else window.navigator.geolocation.getCurrentPosition(this._onSuccess,this._onError,this.options.positionOptions),this._timeoutId=setTimeout(this._finish,1e4);return!0}_clearWatch(){window.navigator.geolocation.clearWatch(this._geolocationWatchID),this._geolocationWatchID=void 0,this._geolocateButton.classList.remove("maplibregl-ctrl-geolocate-waiting"),this._geolocateButton.setAttribute("aria-pressed","false"),this.options.showUserLocation&&this._updateMarker(null)}},e.Hash=Qf,e.ImageSource=at,e.KeyboardHandler=yr,e.LngLatBounds=re,e.LogoControl=An,e.Map=class extends ro{constructor(Ue){t.bf.mark(t.bg.create);let R=Object.assign(Object.assign({},yl),Ue);if(R.minZoom!=null&&R.maxZoom!=null&&R.minZoom>R.maxZoom)throw new Error("maxZoom must be greater than or equal to minZoom");if(R.minPitch!=null&&R.maxPitch!=null&&R.minPitch>R.maxPitch)throw new Error("maxPitch must be greater than or equal to minPitch");if(R.minPitch!=null&&R.minPitch<0)throw new Error("minPitch must be greater than or equal to 0");if(R.maxPitch!=null&&R.maxPitch>85)throw new Error("maxPitch must be less than or equal to 85");if(super(new kl(R.minZoom,R.maxZoom,R.minPitch,R.maxPitch,R.renderWorldCopies),{bearingSnap:R.bearingSnap}),this._idleTriggered=!1,this._crossFadingFactor=1,this._renderTaskQueue=new un,this._controls=[],this._mapId=t.a4(),this._contextLost=ae=>{ae.preventDefault(),this._frameRequest&&(this._frameRequest.abort(),this._frameRequest=null),this.fire(new t.k("webglcontextlost",{originalEvent:ae}))},this._contextRestored=ae=>{this._setupPainter(),this.resize(),this._update(),this.fire(new t.k("webglcontextrestored",{originalEvent:ae}))},this._onMapScroll=ae=>{if(ae.target===this._container)return this._container.scrollTop=0,this._container.scrollLeft=0,!1},this._onWindowOnline=()=>{this._update()},this._interactive=R.interactive,this._maxTileCacheSize=R.maxTileCacheSize,this._maxTileCacheZoomLevels=R.maxTileCacheZoomLevels,this._failIfMajorPerformanceCaveat=R.failIfMajorPerformanceCaveat===!0,this._preserveDrawingBuffer=R.preserveDrawingBuffer===!0,this._antialias=R.antialias===!0,this._trackResize=R.trackResize===!0,this._bearingSnap=R.bearingSnap,this._refreshExpiredTiles=R.refreshExpiredTiles===!0,this._fadeDuration=R.fadeDuration,this._crossSourceCollisions=R.crossSourceCollisions===!0,this._collectResourceTiming=R.collectResourceTiming===!0,this._locale=Object.assign(Object.assign({},bs),R.locale),this._clickTolerance=R.clickTolerance,this._overridePixelRatio=R.pixelRatio,this._maxCanvasSize=R.maxCanvasSize,this.transformCameraUpdate=R.transformCameraUpdate,this.cancelPendingTileRequestsWhileZooming=R.cancelPendingTileRequestsWhileZooming===!0,this._imageQueueHandle=l.addThrottleControl(()=>this.isMoving()),this._requestManager=new _(R.transformRequest),typeof R.container=="string"){if(this._container=document.getElementById(R.container),!this._container)throw new Error(`Container '${R.container}' not found.`)}else{if(!(R.container instanceof HTMLElement))throw new Error("Invalid type: 'container' must be a String or HTMLElement.");this._container=R.container}if(R.maxBounds&&this.setMaxBounds(R.maxBounds),this._setupContainer(),this._setupPainter(),this.on("move",()=>this._update(!1)).on("moveend",()=>this._update(!1)).on("zoom",()=>this._update(!0)).on("terrain",()=>{this.painter.terrainFacilitator.dirty=!0,this._update(!0)}).once("idle",()=>{this._idleTriggered=!0}),typeof window<"u"){addEventListener("online",this._onWindowOnline,!1);let ae=!1,we=qf(Ae=>{this._trackResize&&!this._removed&&(this.resize(Ae),this.redraw())},50);this._resizeObserver=new ResizeObserver(Ae=>{ae?we(Ae):ae=!0}),this._resizeObserver.observe(this._container)}this.handlers=new Jn(this,R),this._hash=R.hash&&new Qf(typeof R.hash=="string"&&R.hash||void 0).addTo(this),this._hash&&this._hash._onHashChange()||(this.jumpTo({center:R.center,zoom:R.zoom,bearing:R.bearing,pitch:R.pitch}),R.bounds&&(this.resize(),this.fitBounds(R.bounds,t.e({},R.fitBoundsOptions,{duration:0})))),this.resize(),this._localIdeographFontFamily=R.localIdeographFontFamily,this._validateStyle=R.validateStyle,R.style&&this.setStyle(R.style,{localIdeographFontFamily:R.localIdeographFontFamily}),R.attributionControl&&this.addControl(new lo(typeof R.attributionControl=="boolean"?void 0:R.attributionControl)),R.maplibreLogo&&this.addControl(new An,R.logoPosition),this.on("style.load",()=>{this.transform.unmodified&&this.jumpTo(this.style.stylesheet)}),this.on("data",ae=>{this._update(ae.dataType==="style"),this.fire(new t.k(`${ae.dataType}data`,ae))}),this.on("dataloading",ae=>{this.fire(new t.k(`${ae.dataType}dataloading`,ae))}),this.on("dataabort",ae=>{this.fire(new t.k("sourcedataabort",ae))})}_getMapId(){return this._mapId}addControl(Ue,R){if(R===void 0&&(R=Ue.getDefaultPosition?Ue.getDefaultPosition():"top-right"),!Ue||!Ue.onAdd)return this.fire(new t.j(new Error("Invalid argument to map.addControl(). Argument must be a control with onAdd and onRemove methods.")));let ae=Ue.onAdd(this);this._controls.push(Ue);let we=this._controlPositions[R];return R.indexOf("bottom")!==-1?we.insertBefore(ae,we.firstChild):we.appendChild(ae),this}removeControl(Ue){if(!Ue||!Ue.onRemove)return this.fire(new t.j(new Error("Invalid argument to map.removeControl(). Argument must be a control with onAdd and onRemove methods.")));let R=this._controls.indexOf(Ue);return R>-1&&this._controls.splice(R,1),Ue.onRemove(this),this}hasControl(Ue){return this._controls.indexOf(Ue)>-1}calculateCameraOptionsFromTo(Ue,R,ae,we){return we==null&&this.terrain&&(we=this.terrain.getElevationForLngLatZoom(ae,this.transform.tileZoom)),super.calculateCameraOptionsFromTo(Ue,R,ae,we)}resize(Ue){var R;let ae=this._containerDimensions(),we=ae[0],Ae=ae[1],Be=this._getClampedPixelRatio(we,Ae);if(this._resizeCanvas(we,Ae,Be),this.painter.resize(we,Ae,Be),this.painter.overLimit()){let At=this.painter.context.gl;this._maxCanvasSize=[At.drawingBufferWidth,At.drawingBufferHeight];let Nt=this._getClampedPixelRatio(we,Ae);this._resizeCanvas(we,Ae,Nt),this.painter.resize(we,Ae,Nt)}this.transform.resize(we,Ae),(R=this._requestedCameraState)===null||R===void 0||R.resize(we,Ae);let pt=!this._moving;return pt&&(this.stop(),this.fire(new t.k("movestart",Ue)).fire(new t.k("move",Ue))),this.fire(new t.k("resize",Ue)),pt&&this.fire(new t.k("moveend",Ue)),this}_getClampedPixelRatio(Ue,R){let{0:ae,1:we}=this._maxCanvasSize,Ae=this.getPixelRatio(),Be=Ue*Ae,pt=R*Ae;return Math.min(Be>ae?ae/Be:1,pt>we?we/pt:1)*Ae}getPixelRatio(){var Ue;return(Ue=this._overridePixelRatio)!==null&&Ue!==void 0?Ue:devicePixelRatio}setPixelRatio(Ue){this._overridePixelRatio=Ue,this.resize()}getBounds(){return this.transform.getBounds()}getMaxBounds(){return this.transform.getMaxBounds()}setMaxBounds(Ue){return this.transform.setMaxBounds(re.convert(Ue)),this._update()}setMinZoom(Ue){if((Ue=Ue??-2)>=-2&&Ue<=this.transform.maxZoom)return this.transform.minZoom=Ue,this._update(),this.getZoom()=this.transform.minZoom)return this.transform.maxZoom=Ue,this._update(),this.getZoom()>Ue&&this.setZoom(Ue),this;throw new Error("maxZoom must be greater than the current minZoom")}getMaxZoom(){return this.transform.maxZoom}setMinPitch(Ue){if((Ue=Ue??0)<0)throw new Error("minPitch must be greater than or equal to 0");if(Ue>=0&&Ue<=this.transform.maxPitch)return this.transform.minPitch=Ue,this._update(),this.getPitch()85)throw new Error("maxPitch must be less than or equal to 85");if(Ue>=this.transform.minPitch)return this.transform.maxPitch=Ue,this._update(),this.getPitch()>Ue&&this.setPitch(Ue),this;throw new Error("maxPitch must be greater than the current minPitch")}getMaxPitch(){return this.transform.maxPitch}getRenderWorldCopies(){return this.transform.renderWorldCopies}setRenderWorldCopies(Ue){return this.transform.renderWorldCopies=Ue,this._update()}project(Ue){return this.transform.locationPoint(t.N.convert(Ue),this.style&&this.terrain)}unproject(Ue){return this.transform.pointLocation(t.P.convert(Ue),this.terrain)}isMoving(){var Ue;return this._moving||((Ue=this.handlers)===null||Ue===void 0?void 0:Ue.isMoving())}isZooming(){var Ue;return this._zooming||((Ue=this.handlers)===null||Ue===void 0?void 0:Ue.isZooming())}isRotating(){var Ue;return this._rotating||((Ue=this.handlers)===null||Ue===void 0?void 0:Ue.isRotating())}_createDelegatedListener(Ue,R,ae){if(Ue==="mouseenter"||Ue==="mouseover"){let we=!1;return{layers:R,listener:ae,delegates:{mousemove:Be=>{let pt=R.filter(Nt=>this.getLayer(Nt)),At=pt.length!==0?this.queryRenderedFeatures(Be.point,{layers:pt}):[];At.length?we||(we=!0,ae.call(this,new iu(Ue,this,Be.originalEvent,{features:At}))):we=!1},mouseout:()=>{we=!1}}}}if(Ue==="mouseleave"||Ue==="mouseout"){let we=!1;return{layers:R,listener:ae,delegates:{mousemove:pt=>{let At=R.filter(Nt=>this.getLayer(Nt));(At.length!==0?this.queryRenderedFeatures(pt.point,{layers:At}):[]).length?we=!0:we&&(we=!1,ae.call(this,new iu(Ue,this,pt.originalEvent)))},mouseout:pt=>{we&&(we=!1,ae.call(this,new iu(Ue,this,pt.originalEvent)))}}}}{let we=Ae=>{let Be=R.filter(At=>this.getLayer(At)),pt=Be.length!==0?this.queryRenderedFeatures(Ae.point,{layers:Be}):[];pt.length&&(Ae.features=pt,ae.call(this,Ae),delete Ae.features)};return{layers:R,listener:ae,delegates:{[Ue]:we}}}}_saveDelegatedListener(Ue,R){this._delegatedListeners=this._delegatedListeners||{},this._delegatedListeners[Ue]=this._delegatedListeners[Ue]||[],this._delegatedListeners[Ue].push(R)}_removeDelegatedListener(Ue,R,ae){if(!this._delegatedListeners||!this._delegatedListeners[Ue])return;let we=this._delegatedListeners[Ue];for(let Ae=0;AeR.includes(pt))){for(let pt in Be.delegates)this.off(pt,Be.delegates[pt]);return void we.splice(Ae,1)}}}on(Ue,R,ae){if(ae===void 0)return super.on(Ue,R);let we=this._createDelegatedListener(Ue,typeof R=="string"?[R]:R,ae);this._saveDelegatedListener(Ue,we);for(let Ae in we.delegates)this.on(Ae,we.delegates[Ae]);return this}once(Ue,R,ae){if(ae===void 0)return super.once(Ue,R);let we=typeof R=="string"?[R]:R,Ae=this._createDelegatedListener(Ue,we,ae);for(let Be in Ae.delegates){let pt=Ae.delegates[Be];Ae.delegates[Be]=(...At)=>{this._removeDelegatedListener(Ue,we,ae),pt(...At)}}this._saveDelegatedListener(Ue,Ae);for(let Be in Ae.delegates)this.once(Be,Ae.delegates[Be]);return this}off(Ue,R,ae){return ae===void 0?super.off(Ue,R):(this._removeDelegatedListener(Ue,typeof R=="string"?[R]:R,ae),this)}queryRenderedFeatures(Ue,R){if(!this.style)return[];let ae,we=Ue instanceof t.P||Array.isArray(Ue),Ae=we?Ue:[[0,0],[this.transform.width,this.transform.height]];if(R=R||(we?{}:Ue)||{},Ae instanceof t.P||typeof Ae[0]=="number")ae=[t.P.convert(Ae)];else{let Be=t.P.convert(Ae[0]),pt=t.P.convert(Ae[1]);ae=[Be,new t.P(pt.x,Be.y),pt,new t.P(Be.x,pt.y),Be]}return this.style.queryRenderedFeatures(ae,R,this.transform)}querySourceFeatures(Ue,R){return this.style.querySourceFeatures(Ue,R)}setStyle(Ue,R){return(R=t.e({},{localIdeographFontFamily:this._localIdeographFontFamily,validate:this._validateStyle},R)).diff!==!1&&R.localIdeographFontFamily===this._localIdeographFontFamily&&this.style&&Ue?(this._diffStyle(Ue,R),this):(this._localIdeographFontFamily=R.localIdeographFontFamily,this._updateStyle(Ue,R))}setTransformRequest(Ue){return this._requestManager.setTransformRequest(Ue),this}_getUIString(Ue){let R=this._locale[Ue];if(R==null)throw new Error(`Missing UI string '${Ue}'`);return R}_updateStyle(Ue,R){if(R.transformStyle&&this.style&&!this.style._loaded)return void this.style.once("style.load",()=>this._updateStyle(Ue,R));let ae=this.style&&R.transformStyle?this.style.serialize():void 0;return this.style&&(this.style.setEventedParent(null),this.style._remove(!Ue)),Ue?(this.style=new Dr(this,R||{}),this.style.setEventedParent(this,{style:this.style}),typeof Ue=="string"?this.style.loadURL(Ue,R,ae):this.style.loadJSON(Ue,R,ae),this):(delete this.style,this)}_lazyInitEmptyStyle(){this.style||(this.style=new Dr(this,{}),this.style.setEventedParent(this,{style:this.style}),this.style.loadEmpty())}_diffStyle(Ue,R){if(typeof Ue=="string"){let ae=this._requestManager.transformRequest(Ue,"Style");t.h(ae,new AbortController).then(we=>{this._updateDiff(we.data,R)}).catch(we=>{we&&this.fire(new t.j(we))})}else typeof Ue=="object"&&this._updateDiff(Ue,R)}_updateDiff(Ue,R){try{this.style.setState(Ue,R)&&this._update(!0)}catch(ae){t.w(`Unable to perform style diff: ${ae.message||ae.error||ae}. Rebuilding the style from scratch.`),this._updateStyle(Ue,R)}}getStyle(){if(this.style)return this.style.serialize()}isStyleLoaded(){return this.style?this.style.loaded():t.w("There is no style added to the map.")}addSource(Ue,R){return this._lazyInitEmptyStyle(),this.style.addSource(Ue,R),this._update(!0)}isSourceLoaded(Ue){let R=this.style&&this.style.sourceCaches[Ue];if(R!==void 0)return R.loaded();this.fire(new t.j(new Error(`There is no source with ID '${Ue}'`)))}setTerrain(Ue){if(this.style._checkLoaded(),this._terrainDataCallback&&this.style.off("data",this._terrainDataCallback),Ue){let R=this.style.sourceCaches[Ue.source];if(!R)throw new Error(`cannot load terrain, because there exists no source with ID: ${Ue.source}`);this.terrain===null&&R.reload();for(let ae in this.style._layers){let we=this.style._layers[ae];we.type==="hillshade"&&we.source===Ue.source&&t.w("You are using the same source for a hillshade layer and for 3D terrain. Please consider using two separate sources to improve rendering quality.")}this.terrain=new As(this.painter,R,Ue),this.painter.renderToTexture=new Qs(this.painter,this.terrain),this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this.transform.elevation=this.terrain.getElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this._terrainDataCallback=ae=>{ae.dataType==="style"?this.terrain.sourceCache.freeRtt():ae.dataType==="source"&&ae.tile&&(ae.sourceId!==Ue.source||this._elevationFreeze||(this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this.transform.elevation=this.terrain.getElevationForLngLatZoom(this.transform.center,this.transform.tileZoom)),this.terrain.sourceCache.freeRtt(ae.tile.tileID))},this.style.on("data",this._terrainDataCallback)}else this.terrain&&this.terrain.sourceCache.destruct(),this.terrain=null,this.painter.renderToTexture&&this.painter.renderToTexture.destruct(),this.painter.renderToTexture=null,this.transform.minElevationForCurrentTile=0,this.transform.elevation=0;return this.fire(new t.k("terrain",{terrain:Ue})),this}getTerrain(){var Ue,R;return(R=(Ue=this.terrain)===null||Ue===void 0?void 0:Ue.options)!==null&&R!==void 0?R:null}areTilesLoaded(){let Ue=this.style&&this.style.sourceCaches;for(let R in Ue){let ae=Ue[R]._tiles;for(let we in ae){let Ae=ae[we];if(Ae.state!=="loaded"&&Ae.state!=="errored")return!1}}return!0}removeSource(Ue){return this.style.removeSource(Ue),this._update(!0)}getSource(Ue){return this.style.getSource(Ue)}addImage(Ue,R,ae={}){let{pixelRatio:we=1,sdf:Ae=!1,stretchX:Be,stretchY:pt,content:At,textFitWidth:Nt,textFitHeight:$t}=ae;if(this._lazyInitEmptyStyle(),!(R instanceof HTMLImageElement||t.b(R))){if(R.width===void 0||R.height===void 0)return this.fire(new t.j(new Error("Invalid arguments to map.addImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`")));{let{width:wr,height:Tr,data:Kr}=R,sa=R;return this.style.addImage(Ue,{data:new t.R({width:wr,height:Tr},new Uint8Array(Kr)),pixelRatio:we,stretchX:Be,stretchY:pt,content:At,textFitWidth:Nt,textFitHeight:$t,sdf:Ae,version:0,userImage:sa}),sa.onAdd&&sa.onAdd(this,Ue),this}}{let{width:wr,height:Tr,data:Kr}=n.getImageData(R);this.style.addImage(Ue,{data:new t.R({width:wr,height:Tr},Kr),pixelRatio:we,stretchX:Be,stretchY:pt,content:At,textFitWidth:Nt,textFitHeight:$t,sdf:Ae,version:0})}}updateImage(Ue,R){let ae=this.style.getImage(Ue);if(!ae)return this.fire(new t.j(new Error("The map has no image with that id. If you are adding a new image use `map.addImage(...)` instead.")));let we=R instanceof HTMLImageElement||t.b(R)?n.getImageData(R):R,{width:Ae,height:Be,data:pt}=we;if(Ae===void 0||Be===void 0)return this.fire(new t.j(new Error("Invalid arguments to map.updateImage(). The second argument must be an `HTMLImageElement`, `ImageData`, `ImageBitmap`, or object with `width`, `height`, and `data` properties with the same format as `ImageData`")));if(Ae!==ae.data.width||Be!==ae.data.height)return this.fire(new t.j(new Error("The width and height of the updated image must be that same as the previous version of the image")));let At=!(R instanceof HTMLImageElement||t.b(R));return ae.data.replace(pt,At),this.style.updateImage(Ue,ae),this}getImage(Ue){return this.style.getImage(Ue)}hasImage(Ue){return Ue?!!this.style.getImage(Ue):(this.fire(new t.j(new Error("Missing required image id"))),!1)}removeImage(Ue){this.style.removeImage(Ue)}loadImage(Ue){return l.getImage(this._requestManager.transformRequest(Ue,"Image"),new AbortController)}listImages(){return this.style.listImages()}addLayer(Ue,R){return this._lazyInitEmptyStyle(),this.style.addLayer(Ue,R),this._update(!0)}moveLayer(Ue,R){return this.style.moveLayer(Ue,R),this._update(!0)}removeLayer(Ue){return this.style.removeLayer(Ue),this._update(!0)}getLayer(Ue){return this.style.getLayer(Ue)}getLayersOrder(){return this.style.getLayersOrder()}setLayerZoomRange(Ue,R,ae){return this.style.setLayerZoomRange(Ue,R,ae),this._update(!0)}setFilter(Ue,R,ae={}){return this.style.setFilter(Ue,R,ae),this._update(!0)}getFilter(Ue){return this.style.getFilter(Ue)}setPaintProperty(Ue,R,ae,we={}){return this.style.setPaintProperty(Ue,R,ae,we),this._update(!0)}getPaintProperty(Ue,R){return this.style.getPaintProperty(Ue,R)}setLayoutProperty(Ue,R,ae,we={}){return this.style.setLayoutProperty(Ue,R,ae,we),this._update(!0)}getLayoutProperty(Ue,R){return this.style.getLayoutProperty(Ue,R)}setGlyphs(Ue,R={}){return this._lazyInitEmptyStyle(),this.style.setGlyphs(Ue,R),this._update(!0)}getGlyphs(){return this.style.getGlyphsUrl()}addSprite(Ue,R,ae={}){return this._lazyInitEmptyStyle(),this.style.addSprite(Ue,R,ae,we=>{we||this._update(!0)}),this}removeSprite(Ue){return this._lazyInitEmptyStyle(),this.style.removeSprite(Ue),this._update(!0)}getSprite(){return this.style.getSprite()}setSprite(Ue,R={}){return this._lazyInitEmptyStyle(),this.style.setSprite(Ue,R,ae=>{ae||this._update(!0)}),this}setLight(Ue,R={}){return this._lazyInitEmptyStyle(),this.style.setLight(Ue,R),this._update(!0)}getLight(){return this.style.getLight()}setSky(Ue){return this._lazyInitEmptyStyle(),this.style.setSky(Ue),this._update(!0)}getSky(){return this.style.getSky()}setFeatureState(Ue,R){return this.style.setFeatureState(Ue,R),this._update()}removeFeatureState(Ue,R){return this.style.removeFeatureState(Ue,R),this._update()}getFeatureState(Ue){return this.style.getFeatureState(Ue)}getContainer(){return this._container}getCanvasContainer(){return this._canvasContainer}getCanvas(){return this._canvas}_containerDimensions(){let Ue=0,R=0;return this._container&&(Ue=this._container.clientWidth||400,R=this._container.clientHeight||300),[Ue,R]}_setupContainer(){let Ue=this._container;Ue.classList.add("maplibregl-map");let R=this._canvasContainer=i.create("div","maplibregl-canvas-container",Ue);this._interactive&&R.classList.add("maplibregl-interactive"),this._canvas=i.create("canvas","maplibregl-canvas",R),this._canvas.addEventListener("webglcontextlost",this._contextLost,!1),this._canvas.addEventListener("webglcontextrestored",this._contextRestored,!1),this._canvas.setAttribute("tabindex",this._interactive?"0":"-1"),this._canvas.setAttribute("aria-label",this._getUIString("Map.Title")),this._canvas.setAttribute("role","region");let ae=this._containerDimensions(),we=this._getClampedPixelRatio(ae[0],ae[1]);this._resizeCanvas(ae[0],ae[1],we);let Ae=this._controlContainer=i.create("div","maplibregl-control-container",Ue),Be=this._controlPositions={};["top-left","top-right","bottom-left","bottom-right"].forEach(pt=>{Be[pt]=i.create("div",`maplibregl-ctrl-${pt} `,Ae)}),this._container.addEventListener("scroll",this._onMapScroll,!1)}_resizeCanvas(Ue,R,ae){this._canvas.width=Math.floor(ae*Ue),this._canvas.height=Math.floor(ae*R),this._canvas.style.width=`${Ue}px`,this._canvas.style.height=`${R}px`}_setupPainter(){let Ue={alpha:!0,stencil:!0,depth:!0,failIfMajorPerformanceCaveat:this._failIfMajorPerformanceCaveat,preserveDrawingBuffer:this._preserveDrawingBuffer,antialias:this._antialias||!1},R=null;this._canvas.addEventListener("webglcontextcreationerror",we=>{R={requestedAttributes:Ue},we&&(R.statusMessage=we.statusMessage,R.type=we.type)},{once:!0});let ae=this._canvas.getContext("webgl2",Ue)||this._canvas.getContext("webgl",Ue);if(!ae){let we="Failed to initialize WebGL";throw R?(R.message=we,new Error(JSON.stringify(R))):new Error(we)}this.painter=new Mc(ae,this.transform),s.testSupport(ae)}loaded(){return!this._styleDirty&&!this._sourcesDirty&&!!this.style&&this.style.loaded()}_update(Ue){return this.style&&this.style._loaded?(this._styleDirty=this._styleDirty||Ue,this._sourcesDirty=!0,this.triggerRepaint(),this):this}_requestRenderFrame(Ue){return this._update(),this._renderTaskQueue.add(Ue)}_cancelRenderFrame(Ue){this._renderTaskQueue.remove(Ue)}_render(Ue){let R=this._idleTriggered?this._fadeDuration:0;if(this.painter.context.setDirty(),this.painter.setBaseState(),this._renderTaskQueue.run(Ue),this._removed)return;let ae=!1;if(this.style&&this._styleDirty){this._styleDirty=!1;let Ae=this.transform.zoom,Be=n.now();this.style.zoomHistory.update(Ae,Be);let pt=new t.z(Ae,{now:Be,fadeDuration:R,zoomHistory:this.style.zoomHistory,transition:this.style.getTransition()}),At=pt.crossFadingFactor();At===1&&At===this._crossFadingFactor||(ae=!0,this._crossFadingFactor=At),this.style.update(pt)}this.style&&this._sourcesDirty&&(this._sourcesDirty=!1,this.style._updateSources(this.transform)),this.terrain?(this.terrain.sourceCache.update(this.transform,this.terrain),this.transform.minElevationForCurrentTile=this.terrain.getMinTileElevationForLngLatZoom(this.transform.center,this.transform.tileZoom),this._elevationFreeze||(this.transform.elevation=this.terrain.getElevationForLngLatZoom(this.transform.center,this.transform.tileZoom))):(this.transform.minElevationForCurrentTile=0,this.transform.elevation=0),this._placementDirty=this.style&&this.style._updatePlacement(this.painter.transform,this.showCollisionBoxes,R,this._crossSourceCollisions),this.painter.render(this.style,{showTileBoundaries:this.showTileBoundaries,showOverdrawInspector:this._showOverdrawInspector,rotating:this.isRotating(),zooming:this.isZooming(),moving:this.isMoving(),fadeDuration:R,showPadding:this.showPadding}),this.fire(new t.k("render")),this.loaded()&&!this._loaded&&(this._loaded=!0,t.bf.mark(t.bg.load),this.fire(new t.k("load"))),this.style&&(this.style.hasTransitions()||ae)&&(this._styleDirty=!0),this.style&&!this._placementDirty&&this.style._releaseSymbolFadeTiles();let we=this._sourcesDirty||this._styleDirty||this._placementDirty;return we||this._repaint?this.triggerRepaint():!this.isMoving()&&this.loaded()&&this.fire(new t.k("idle")),!this._loaded||this._fullyLoaded||we||(this._fullyLoaded=!0,t.bf.mark(t.bg.fullLoad)),this}redraw(){return this.style&&(this._frameRequest&&(this._frameRequest.abort(),this._frameRequest=null),this._render(0)),this}remove(){var Ue;this._hash&&this._hash.remove();for(let ae of this._controls)ae.onRemove(this);this._controls=[],this._frameRequest&&(this._frameRequest.abort(),this._frameRequest=null),this._renderTaskQueue.clear(),this.painter.destroy(),this.handlers.destroy(),delete this.handlers,this.setStyle(null),typeof window<"u"&&removeEventListener("online",this._onWindowOnline,!1),l.removeThrottleControl(this._imageQueueHandle),(Ue=this._resizeObserver)===null||Ue===void 0||Ue.disconnect();let R=this.painter.context.gl.getExtension("WEBGL_lose_context");R?.loseContext&&R.loseContext(),this._canvas.removeEventListener("webglcontextrestored",this._contextRestored,!1),this._canvas.removeEventListener("webglcontextlost",this._contextLost,!1),i.remove(this._canvasContainer),i.remove(this._controlContainer),this._container.classList.remove("maplibregl-map"),t.bf.clearMetrics(),this._removed=!0,this.fire(new t.k("remove"))}triggerRepaint(){this.style&&!this._frameRequest&&(this._frameRequest=new AbortController,n.frameAsync(this._frameRequest).then(Ue=>{t.bf.frame(Ue),this._frameRequest=null,this._render(Ue)}).catch(()=>{}))}get showTileBoundaries(){return!!this._showTileBoundaries}set showTileBoundaries(Ue){this._showTileBoundaries!==Ue&&(this._showTileBoundaries=Ue,this._update())}get showPadding(){return!!this._showPadding}set showPadding(Ue){this._showPadding!==Ue&&(this._showPadding=Ue,this._update())}get showCollisionBoxes(){return!!this._showCollisionBoxes}set showCollisionBoxes(Ue){this._showCollisionBoxes!==Ue&&(this._showCollisionBoxes=Ue,Ue?this.style._generateCollisionBoxes():this._update())}get showOverdrawInspector(){return!!this._showOverdrawInspector}set showOverdrawInspector(Ue){this._showOverdrawInspector!==Ue&&(this._showOverdrawInspector=Ue,this._update())}get repaint(){return!!this._repaint}set repaint(Ue){this._repaint!==Ue&&(this._repaint=Ue,this.triggerRepaint())}get vertices(){return!!this._vertices}set vertices(Ue){this._vertices=Ue,this._update()}get version(){return Bl}getCameraTargetElevation(){return this.transform.elevation}},e.MapMouseEvent=iu,e.MapTouchEvent=Zc,e.MapWheelEvent=ch,e.Marker=Zu,e.NavigationControl=class{constructor(Ue){this._updateZoomButtons=()=>{let R=this._map.getZoom(),ae=R===this._map.getMaxZoom(),we=R===this._map.getMinZoom();this._zoomInButton.disabled=ae,this._zoomOutButton.disabled=we,this._zoomInButton.setAttribute("aria-disabled",ae.toString()),this._zoomOutButton.setAttribute("aria-disabled",we.toString())},this._rotateCompassArrow=()=>{let R=this.options.visualizePitch?`scale(${1/Math.pow(Math.cos(this._map.transform.pitch*(Math.PI/180)),.5)}) rotateX(${this._map.transform.pitch}deg) rotateZ(${this._map.transform.angle*(180/Math.PI)}deg)`:`rotate(${this._map.transform.angle*(180/Math.PI)}deg)`;this._compassIcon.style.transform=R},this._setButtonTitle=(R,ae)=>{let we=this._map._getUIString(`NavigationControl.${ae}`);R.title=we,R.setAttribute("aria-label",we)},this.options=t.e({},Nn,Ue),this._container=i.create("div","maplibregl-ctrl maplibregl-ctrl-group"),this._container.addEventListener("contextmenu",R=>R.preventDefault()),this.options.showZoom&&(this._zoomInButton=this._createButton("maplibregl-ctrl-zoom-in",R=>this._map.zoomIn({},{originalEvent:R})),i.create("span","maplibregl-ctrl-icon",this._zoomInButton).setAttribute("aria-hidden","true"),this._zoomOutButton=this._createButton("maplibregl-ctrl-zoom-out",R=>this._map.zoomOut({},{originalEvent:R})),i.create("span","maplibregl-ctrl-icon",this._zoomOutButton).setAttribute("aria-hidden","true")),this.options.showCompass&&(this._compass=this._createButton("maplibregl-ctrl-compass",R=>{this.options.visualizePitch?this._map.resetNorthPitch({},{originalEvent:R}):this._map.resetNorth({},{originalEvent:R})}),this._compassIcon=i.create("span","maplibregl-ctrl-icon",this._compass),this._compassIcon.setAttribute("aria-hidden","true"))}onAdd(Ue){return this._map=Ue,this.options.showZoom&&(this._setButtonTitle(this._zoomInButton,"ZoomIn"),this._setButtonTitle(this._zoomOutButton,"ZoomOut"),this._map.on("zoom",this._updateZoomButtons),this._updateZoomButtons()),this.options.showCompass&&(this._setButtonTitle(this._compass,"ResetBearing"),this.options.visualizePitch&&this._map.on("pitch",this._rotateCompassArrow),this._map.on("rotate",this._rotateCompassArrow),this._rotateCompassArrow(),this._handler=new Ro(this._map,this._compass,this.options.visualizePitch)),this._container}onRemove(){i.remove(this._container),this.options.showZoom&&this._map.off("zoom",this._updateZoomButtons),this.options.showCompass&&(this.options.visualizePitch&&this._map.off("pitch",this._rotateCompassArrow),this._map.off("rotate",this._rotateCompassArrow),this._handler.off(),delete this._handler),delete this._map}_createButton(Ue,R){let ae=i.create("button",Ue,this._container);return ae.type="button",ae.addEventListener("click",R),ae}},e.Popup=class extends t.E{constructor(Ue){super(),this.remove=()=>(this._content&&i.remove(this._content),this._container&&(i.remove(this._container),delete this._container),this._map&&(this._map.off("move",this._update),this._map.off("move",this._onClose),this._map.off("click",this._onClose),this._map.off("remove",this.remove),this._map.off("mousemove",this._onMouseMove),this._map.off("mouseup",this._onMouseUp),this._map.off("drag",this._onDrag),this._map._canvasContainer.classList.remove("maplibregl-track-pointer"),delete this._map,this.fire(new t.k("close"))),this),this._onMouseUp=R=>{this._update(R.point)},this._onMouseMove=R=>{this._update(R.point)},this._onDrag=R=>{this._update(R.point)},this._update=R=>{var ae;if(!this._map||!this._lngLat&&!this._trackPointer||!this._content)return;if(!this._container){if(this._container=i.create("div","maplibregl-popup",this._map.getContainer()),this._tip=i.create("div","maplibregl-popup-tip",this._container),this._container.appendChild(this._content),this.options.className)for(let At of this.options.className.split(" "))this._container.classList.add(At);this._closeButton&&this._closeButton.setAttribute("aria-label",this._map._getUIString("Popup.Close")),this._trackPointer&&this._container.classList.add("maplibregl-popup-track-pointer")}if(this.options.maxWidth&&this._container.style.maxWidth!==this.options.maxWidth&&(this._container.style.maxWidth=this.options.maxWidth),this._lngLat=this._map.transform.renderWorldCopies&&!this._trackPointer?Ls(this._lngLat,this._flatPos,this._map.transform):(ae=this._lngLat)===null||ae===void 0?void 0:ae.wrap(),this._trackPointer&&!R)return;let we=this._flatPos=this._pos=this._trackPointer&&R?R:this._map.project(this._lngLat);this._map.terrain&&(this._flatPos=this._trackPointer&&R?R:this._map.transform.locationPoint(this._lngLat));let Ae=this.options.anchor,Be=uc(this.options.offset);if(!Ae){let At=this._container.offsetWidth,Nt=this._container.offsetHeight,$t;$t=we.y+Be.bottom.ythis._map.transform.height-Nt?["bottom"]:[],we.xthis._map.transform.width-At/2&&$t.push("right"),Ae=$t.length===0?"bottom":$t.join("-")}let pt=we.add(Be[Ae]);this.options.subpixelPositioning||(pt=pt.round()),i.setTransform(this._container,`${lu[Ae]} translate(${pt.x}px,${pt.y}px)`),Iu(this._container,Ae,"popup")},this._onClose=()=>{this.remove()},this.options=t.e(Object.create(Fo),Ue)}addTo(Ue){return this._map&&this.remove(),this._map=Ue,this.options.closeOnClick&&this._map.on("click",this._onClose),this.options.closeOnMove&&this._map.on("move",this._onClose),this._map.on("remove",this.remove),this._update(),this._focusFirstElement(),this._trackPointer?(this._map.on("mousemove",this._onMouseMove),this._map.on("mouseup",this._onMouseUp),this._container&&this._container.classList.add("maplibregl-popup-track-pointer"),this._map._canvasContainer.classList.add("maplibregl-track-pointer")):this._map.on("move",this._update),this.fire(new t.k("open")),this}isOpen(){return!!this._map}getLngLat(){return this._lngLat}setLngLat(Ue){return this._lngLat=t.N.convert(Ue),this._pos=null,this._flatPos=null,this._trackPointer=!1,this._update(),this._map&&(this._map.on("move",this._update),this._map.off("mousemove",this._onMouseMove),this._container&&this._container.classList.remove("maplibregl-popup-track-pointer"),this._map._canvasContainer.classList.remove("maplibregl-track-pointer")),this}trackPointer(){return this._trackPointer=!0,this._pos=null,this._flatPos=null,this._update(),this._map&&(this._map.off("move",this._update),this._map.on("mousemove",this._onMouseMove),this._map.on("drag",this._onDrag),this._container&&this._container.classList.add("maplibregl-popup-track-pointer"),this._map._canvasContainer.classList.add("maplibregl-track-pointer")),this}getElement(){return this._container}setText(Ue){return this.setDOMContent(document.createTextNode(Ue))}setHTML(Ue){let R=document.createDocumentFragment(),ae=document.createElement("body"),we;for(ae.innerHTML=Ue;we=ae.firstChild,we;)R.appendChild(we);return this.setDOMContent(R)}getMaxWidth(){var Ue;return(Ue=this._container)===null||Ue===void 0?void 0:Ue.style.maxWidth}setMaxWidth(Ue){return this.options.maxWidth=Ue,this._update(),this}setDOMContent(Ue){if(this._content)for(;this._content.hasChildNodes();)this._content.firstChild&&this._content.removeChild(this._content.firstChild);else this._content=i.create("div","maplibregl-popup-content",this._container);return this._content.appendChild(Ue),this._createCloseButton(),this._update(),this._focusFirstElement(),this}addClassName(Ue){return this._container&&this._container.classList.add(Ue),this}removeClassName(Ue){return this._container&&this._container.classList.remove(Ue),this}setOffset(Ue){return this.options.offset=Ue,this._update(),this}toggleClassName(Ue){if(this._container)return this._container.classList.toggle(Ue)}setSubpixelPositioning(Ue){this.options.subpixelPositioning=Ue}_createCloseButton(){this.options.closeButton&&(this._closeButton=i.create("button","maplibregl-popup-close-button",this._content),this._closeButton.type="button",this._closeButton.innerHTML="×",this._closeButton.addEventListener("click",this._onClose))}_focusFirstElement(){if(!this.options.focusAfterOpen||!this._container)return;let Ue=this._container.querySelector(Dc);Ue&&Ue.focus()}},e.RasterDEMTileSource=De,e.RasterTileSource=Se,e.ScaleControl=class{constructor(Ue){this._onMove=()=>{_c(this._map,this._container,this.options)},this.setUnit=R=>{this.options.unit=R,_c(this._map,this._container,this.options)},this.options=Object.assign(Object.assign({},Tu),Ue)}getDefaultPosition(){return"bottom-left"}onAdd(Ue){return this._map=Ue,this._container=i.create("div","maplibregl-ctrl maplibregl-ctrl-scale",Ue.getContainer()),this._map.on("move",this._onMove),this._onMove(),this._container}onRemove(){i.remove(this._container),this._map.off("move",this._onMove),this._map=void 0}},e.ScrollZoomHandler=ka,e.Style=Dr,e.TerrainControl=class{constructor(Ue){this._toggleTerrain=()=>{this._map.getTerrain()?this._map.setTerrain(null):this._map.setTerrain(this.options),this._updateTerrainIcon()},this._updateTerrainIcon=()=>{this._terrainButton.classList.remove("maplibregl-ctrl-terrain"),this._terrainButton.classList.remove("maplibregl-ctrl-terrain-enabled"),this._map.terrain?(this._terrainButton.classList.add("maplibregl-ctrl-terrain-enabled"),this._terrainButton.title=this._map._getUIString("TerrainControl.Disable")):(this._terrainButton.classList.add("maplibregl-ctrl-terrain"),this._terrainButton.title=this._map._getUIString("TerrainControl.Enable"))},this.options=Ue}onAdd(Ue){return this._map=Ue,this._container=i.create("div","maplibregl-ctrl maplibregl-ctrl-group"),this._terrainButton=i.create("button","maplibregl-ctrl-terrain",this._container),i.create("span","maplibregl-ctrl-icon",this._terrainButton).setAttribute("aria-hidden","true"),this._terrainButton.type="button",this._terrainButton.addEventListener("click",this._toggleTerrain),this._updateTerrainIcon(),this._map.on("terrain",this._updateTerrainIcon),this._container}onRemove(){i.remove(this._container),this._map.off("terrain",this._updateTerrainIcon),this._map=void 0}},e.TwoFingersTouchPitchHandler=Pc,e.TwoFingersTouchRotateHandler=Kc,e.TwoFingersTouchZoomHandler=yu,e.TwoFingersTouchZoomRotateHandler=Pi,e.VectorTileSource=be,e.VideoSource=nt,e.addSourceType=(Ue,R)=>t._(void 0,void 0,void 0,function*(){if(Me(Ue))throw new Error(`A source type called "${Ue}" already exists.`);((ae,we)=>{ut[ae]=we})(Ue,R)}),e.clearPrewarmedResources=function(){let Ue=pe;Ue&&(Ue.isPreloaded()&&Ue.numActive()===1?(Ue.release(Q),pe=null):console.warn("Could not clear WebWorkers since there are active Map instances that still reference it. The pre-warmed WebWorker pool can only be cleared when all map instances have been removed with map.remove()"))},e.getMaxParallelImageRequests=function(){return t.a.MAX_PARALLEL_IMAGE_REQUESTS},e.getRTLTextPluginStatus=function(){return rt().getRTLTextPluginStatus()},e.getVersion=function(){return Yu},e.getWorkerCount=function(){return ue.workerCount},e.getWorkerUrl=function(){return t.a.WORKER_URL},e.importScriptInWorkers=function(Ue){return X().broadcast("IS",Ue)},e.prewarm=function(){$().acquire(Q)},e.setMaxParallelImageRequests=function(Ue){t.a.MAX_PARALLEL_IMAGE_REQUESTS=Ue},e.setRTLTextPlugin=function(Ue,R){return rt().setRTLTextPlugin(Ue,R)},e.setWorkerCount=function(Ue){ue.workerCount=Ue},e.setWorkerUrl=function(Ue){t.a.WORKER_URL=Ue}});var E=d;return E})}}),qV=Xe({"src/plots/map/layers.js"(Z,q){"use strict";var d=ua(),x=hu().sanitizeHTML,A=R6(),E=x0();function e(n,i){this.subplot=n,this.uid=n.uid+"-"+i,this.index=i,this.idSource="source-"+this.uid,this.idLayer=E.layoutLayerPrefix+this.uid,this.sourceType=null,this.source=null,this.layerType=null,this.below=null,this.visible=!1}var t=e.prototype;t.update=function(i){this.visible?this.needsNewImage(i)?this.updateImage(i):this.needsNewSource(i)?(this.removeLayer(),this.updateSource(i),this.updateLayer(i)):this.needsNewLayer(i)?this.updateLayer(i):this.updateStyle(i):(this.updateSource(i),this.updateLayer(i)),this.visible=r(i)},t.needsNewImage=function(n){var i=this.subplot.map;return i.getSource(this.idSource)&&this.sourceType==="image"&&n.sourcetype==="image"&&(this.source!==n.source||JSON.stringify(this.coordinates)!==JSON.stringify(n.coordinates))},t.needsNewSource=function(n){return this.sourceType!==n.sourcetype||JSON.stringify(this.source)!==JSON.stringify(n.source)||this.layerType!==n.type},t.needsNewLayer=function(n){return this.layerType!==n.type||this.below!==this.subplot.belowLookup["layout-"+this.index]},t.lookupBelow=function(){return this.subplot.belowLookup["layout-"+this.index]},t.updateImage=function(n){var i=this.subplot.map;i.getSource(this.idSource).updateImage({url:n.source,coordinates:n.coordinates});var s=this.findFollowingMapLayerId(this.lookupBelow());s!==null&&this.subplot.map.moveLayer(this.idLayer,s)},t.updateSource=function(n){var i=this.subplot.map;if(i.getSource(this.idSource)&&i.removeSource(this.idSource),this.sourceType=n.sourcetype,this.source=n.source,!!r(n)){var s=a(n);i.addSource(this.idSource,s)}},t.findFollowingMapLayerId=function(n){if(n==="traces")for(var i=this.subplot.getMapLayers(),s=0;s0){for(var s=0;s0}function o(n){var i={},s={};switch(n.type){case"circle":d.extendFlat(s,{"circle-radius":n.circle.radius,"circle-color":n.color,"circle-opacity":n.opacity});break;case"line":d.extendFlat(s,{"line-width":n.line.width,"line-color":n.color,"line-opacity":n.opacity,"line-dasharray":n.line.dash});break;case"fill":d.extendFlat(s,{"fill-color":n.color,"fill-outline-color":n.fill.outlinecolor,"fill-opacity":n.opacity});break;case"symbol":var h=n.symbol,c=A(h.textposition,h.iconsize);d.extendFlat(i,{"icon-image":h.icon+"-15","icon-size":h.iconsize/10,"text-field":h.text,"text-size":h.textfont.size,"text-anchor":c.anchor,"text-offset":c.offset,"symbol-placement":h.placement}),d.extendFlat(s,{"icon-color":n.color,"text-color":h.textfont.color,"text-opacity":n.opacity});break;case"raster":d.extendFlat(s,{"raster-fade-duration":0,"raster-opacity":n.opacity});break}return{layout:i,paint:s}}function a(n){var i=n.sourcetype,s=n.source,h={type:i},c;return i==="geojson"?c="data":i==="vector"?c=typeof 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nt=Fe.nodes,tt=Fe.links,ut=!1,Me=!1;if(tt.forEach(function(Qe){Qe.circularLinkType=="top"?ut=!0:Qe.circularLinkType=="bottom"&&(Me=!0)}),ut==!1||Me==!1){var _e=x.min(nt,function(Qe){return Qe.y0}),fe=x.max(nt,function(Qe){return Qe.y1}),Oe=fe-_e,rt=at-Ze,st=rt/Oe;nt.forEach(function(Qe){var Pt=(Qe.y1-Qe.y0)*st;Qe.y0=(Qe.y0-_e)*st,Qe.y1=Qe.y0+Pt}),tt.forEach(function(Qe){Qe.y0=(Qe.y0-_e)*st,Qe.y1=(Qe.y1-_e)*st,Qe.width=Qe.width*st})}}d.sankeyCircular=f,d.sankeyCenter=n,d.sankeyLeft=r,d.sankeyRight=o,d.sankeyJustify=a,Object.defineProperty(d,"__esModule",{value:!0})})}}),U6=Xe({"src/traces/sankey/constants.js"(Z,q){"use 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0}];Ul.prototype.clone=WD;Ul.prototype.reverse=XD;Ul.prototype.value=YD;ma.prototype.at=Id.at;ma.prototype.chain=Id.wrapperChain;ma.prototype.commit=Id.commit;ma.prototype.next=Id.next;ma.prototype.plant=Id.plant;ma.prototype.reverse=Id.reverse;ma.prototype.toJSON=ma.prototype.valueOf=ma.prototype.value=Id.value;ma.prototype.first=ma.prototype.head;KD&&(ma.prototype[KD]=Id.toIterator);var $c=ma;var Rd=uX(r7());window.PlotlyConfig={MathJaxConfig:"local"};var XA=class{constructor(ge,Ye){this.model=ge,this.serializers=Ye}get(ge){let Ye=this.serializers[ge],Rt=this.model.get(ge);return Ye?.deserialize?Ye.deserialize(Rt):Rt}set(ge,Ye){let 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ge=this.model.get("_py2js_update");if(ge!==null){var Ye=ge.style_data,Rt=ge.layout_data,vr=this._normalize_trace_indexes(ge.style_traces);i7(this.model.get("_widget_data"),Ye,vr),c2(this.model.get("_widget_layout"),Rt)}}do_animate(){var ge=this.model.get("_py2js_animate");if(ge!==null){for(var Ye=ge.style_data,Rt=ge.layout_data,vr=this._normalize_trace_indexes(ge.style_traces),Yr=0;Yrthis.do_addTraces()),this.model.on("change:_py2js_deleteTraces",()=>this.do_deleteTraces()),this.model.on("change:_py2js_moveTraces",()=>this.do_moveTraces()),this.model.on("change:_py2js_restyle",()=>this.do_restyle()),this.model.on("change:_py2js_relayout",()=>this.do_relayout()),this.model.on("change:_py2js_update",()=>this.do_update()),this.model.on("change:_py2js_animate",()=>this.do_animate()),window?.MathJax?.Hub?.Config?.({SVG:{font:"STIX-Web"}});var Ye=this.model.get("_last_layout_edit_id"),Rt=this.model.get("_last_trace_edit_id");this.viewID=o7();var 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Ye.perform_render(),()=>Ye.remove()}}};export{XA as FigureModel,ZA as FigureView,MHe as default}; +/*! Bundled license information: + +plotly.js/dist/plotly.js: + (*! + * pad-left + * + * Copyright (c) 2014-2015, Jon Schlinkert. + * Licensed under the MIT license. + *) + (*! + * repeat-string + * + * Copyright (c) 2014-2015, Jon Schlinkert. + * Licensed under the MIT License. + *) + (*! ieee754. BSD-3-Clause License. Feross Aboukhadijeh *) + (*! + * The buffer module from node.js, for the browser. + * + * @author Feross Aboukhadijeh + * @license MIT + *) + (*! + * Determine if an object is a Buffer + * + * @author Feross Aboukhadijeh + * @license MIT + *) + (*! Bundled license information: + + native-promise-only/lib/npo.src.js: + (*! Native Promise Only + v0.8.1 (c) Kyle Simpson + MIT License: http://getify.mit-license.org + *) + + polybooljs/index.js: + (* + * @copyright 2016 Sean Connelly (@voidqk), http://syntheti.cc + * @license MIT + * @preserve Project Home: https://github.com/voidqk/polybooljs + *) + + ieee754/index.js: + (*! ieee754. BSD-3-Clause License. Feross Aboukhadijeh *) + + buffer/index.js: + (*! + * The buffer module from node.js, for the browser. + * + * @author Feross Aboukhadijeh + * @license MIT + *) + + safe-buffer/index.js: + (*! safe-buffer. MIT License. Feross Aboukhadijeh *) + + assert/build/internal/util/comparisons.js: + (*! + * The buffer module from node.js, for the browser. + * + * @author Feross Aboukhadijeh + * @license MIT + *) + + object-assign/index.js: + (* + object-assign + (c) Sindre Sorhus + @license MIT + *) + + maplibre-gl/dist/maplibre-gl.js: + (** + * MapLibre GL JS + * @license 3-Clause BSD. Full text of license: https://github.com/maplibre/maplibre-gl-js/blob/v4.7.1/LICENSE.txt + *) + *) + +lodash-es/lodash.default.js: + (** + * @license + * Lodash (Custom Build) + * Build: `lodash modularize exports="es" -o ./` + * Copyright OpenJS Foundation and other contributors + * Released under MIT license + * Based on Underscore.js 1.8.3 + * Copyright Jeremy Ashkenas, DocumentCloud and Investigative Reporters & Editors + *) + +lodash-es/lodash.js: + (** + * @license + * Lodash (Custom Build) + * Build: `lodash modularize exports="es" -o ./` + * Copyright OpenJS Foundation and other contributors + * Released under MIT license + * Based on Underscore.js 1.8.3 + * Copyright Jeremy Ashkenas, DocumentCloud and Investigative Reporters & Editors + *) +*/ diff --git a/.venv_haddock/lib/python3.12/site-packages/plotly/validators/_validators.json b/.venv_haddock/lib/python3.12/site-packages/plotly/validators/_validators.json new file mode 100644 index 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"layout.yaxis.zerolinecolor": { + "params": { + "plotly_name": "zerolinecolor", + "parent_name": "layout.yaxis", + "edit_type": "ticks" + }, + "superclass": "ColorValidator" + }, + "layout.yaxis.zeroline": { + "params": { + "plotly_name": "zeroline", + "parent_name": "layout.yaxis", + "edit_type": "ticks" + }, + "superclass": "BooleanValidator" + }, + "layout.yaxis.visible": { + "params": { + "plotly_name": "visible", + "parent_name": "layout.yaxis", + "edit_type": "plot" + }, + "superclass": "BooleanValidator" + }, + "layout.yaxis.unifiedhovertitle": { + "params": { + "plotly_name": "unifiedhovertitle", + "parent_name": "layout.yaxis", + "data_class_str": "Unifiedhovertitle", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "layout.yaxis.unifiedhovertitle.text": { + "params": { + "plotly_name": "text", + "parent_name": "layout.yaxis.unifiedhovertitle", + "edit_type": "none" + }, + "superclass": "StringValidator" + }, + "layout.yaxis.uirevision": { + "params": { + "plotly_name": "uirevision", + "parent_name": "layout.yaxis", + "edit_type": "none" + }, + "superclass": "AnyValidator" + }, + "layout.yaxis.type": { + "params": { + "plotly_name": "type", + "parent_name": "layout.yaxis", + "edit_type": "calc", + "values": [ + "-", + "linear", + "log", + "date", + "category", + "multicategory" + ] + }, + "superclass": "EnumeratedValidator" + }, + "layout.yaxis.title": { + "params": { + "plotly_name": "title", + "parent_name": "layout.yaxis", + "data_class_str": "Title", + "data_docs": "\n" + }, + "superclass": "TitleValidator" + }, + "layout.yaxis.title.text": { + "params": { + "plotly_name": "text", + "parent_name": "layout.yaxis.title", + "edit_type": "ticks" + }, + "superclass": "StringValidator" + }, + "layout.yaxis.title.standoff": { + "params": { + "plotly_name": "standoff", + "parent_name": "layout.yaxis.title", + "edit_type": "ticks", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "layout.yaxis.title.font": { + "params": { + "plotly_name": "font", + "parent_name": "layout.yaxis.title", + "data_class_str": "Font", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "layout.yaxis.title.font.weight": { + "params": { + "plotly_name": "weight", + "parent_name": "layout.yaxis.title.font", + "edit_type": "ticks", + "extras": [ + "normal", + "bold" + ], + "max": 1000, + "min": 1 + }, + "superclass": "IntegerValidator" + }, + "layout.yaxis.title.font.variant": { + "params": { + "plotly_name": "variant", + "parent_name": "layout.yaxis.title.font", + "edit_type": "ticks", + "values": [ + "normal", + "small-caps", + "all-small-caps", + "all-petite-caps", + "petite-caps", + "unicase" + ] + }, + "superclass": "EnumeratedValidator" + }, + "layout.yaxis.title.font.textcase": { + "params": { + "plotly_name": "textcase", + "parent_name": "layout.yaxis.title.font", + "edit_type": "ticks", + "values": [ + "normal", + "word caps", + "upper", + "lower" + ] + }, + "superclass": "EnumeratedValidator" + }, + 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"edit_type": "calc" + }, + "superclass": "StringValidator" + }, + "violin.name": { + "params": { + "plotly_name": "name", + "parent_name": "violin", + "edit_type": "calc+clearAxisTypes" + }, + "superclass": "StringValidator" + }, + "violin.metasrc": { + "params": { + "plotly_name": "metasrc", + "parent_name": "violin", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "violin.meta": { + "params": { + "plotly_name": "meta", + "parent_name": "violin", + "array_ok": true, + "edit_type": "plot" + }, + "superclass": "AnyValidator" + }, + "violin.meanline": { + "params": { + "plotly_name": "meanline", + "parent_name": "violin", + "data_class_str": "Meanline", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "violin.meanline.width": { + "params": { + "plotly_name": "width", + "parent_name": "violin.meanline", + "edit_type": "style", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "violin.meanline.visible": { + "params": { + "plotly_name": "visible", 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"SrcValidator" + }, + "scattersmith.meta": { + "params": { + "plotly_name": "meta", + "parent_name": "scattersmith", + "array_ok": true, + "edit_type": "plot" + }, + "superclass": "AnyValidator" + }, + "scattersmith.marker": { + "params": { + "plotly_name": "marker", + "parent_name": "scattersmith", + "data_class_str": "Marker", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scattersmith.marker.symbolsrc": { + "params": { + "plotly_name": "symbolsrc", + "parent_name": "scattersmith.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattersmith.marker.symbol": { + "params": { + "plotly_name": "symbol", + "parent_name": "scattersmith.marker", + "array_ok": true, + "edit_type": "style", + "values": [ + 0, + "0", + "circle", + 100, + "100", + "circle-open", + 200, + "200", + "circle-dot", + 300, + "300", + "circle-open-dot", + 1, + "1", + "square", + 101, + "101", + "square-open", + 201, + "201", + "square-dot", + 301, + "301", + 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+ "triangle-ne", + 109, + "109", + "triangle-ne-open", + 209, + "209", + "triangle-ne-dot", + 309, + "309", + "triangle-ne-open-dot", + 10, + "10", + "triangle-se", + 110, + "110", + "triangle-se-open", + 210, + "210", + "triangle-se-dot", + 310, + "310", + "triangle-se-open-dot", + 11, + "11", + "triangle-sw", + 111, + "111", + "triangle-sw-open", + 211, + "211", + "triangle-sw-dot", + 311, + "311", + "triangle-sw-open-dot", + 12, + "12", + "triangle-nw", + 112, + "112", + "triangle-nw-open", + 212, + "212", + "triangle-nw-dot", + 312, + "312", + "triangle-nw-open-dot", + 13, + "13", + "pentagon", + 113, + "113", + "pentagon-open", + 213, + "213", + "pentagon-dot", + 313, + "313", + "pentagon-open-dot", + 14, + "14", + "hexagon", + 114, + "114", + "hexagon-open", + 214, + "214", + "hexagon-dot", + 314, + "314", + "hexagon-open-dot", + 15, + "15", + "hexagon2", + 115, + "115", + "hexagon2-open", + 215, + "215", + "hexagon2-dot", + 315, + "315", + "hexagon2-open-dot", + 16, + "16", + 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"star-diamond-open-dot", + 23, + "23", + "diamond-tall", + 123, + "123", + "diamond-tall-open", + 223, + "223", + "diamond-tall-dot", + 323, + "323", + "diamond-tall-open-dot", + 24, + "24", + "diamond-wide", + 124, + "124", + "diamond-wide-open", + 224, + "224", + "diamond-wide-dot", + 324, + "324", + "diamond-wide-open-dot", + 25, + "25", + "hourglass", + 125, + "125", + "hourglass-open", + 26, + "26", + "bowtie", + 126, + "126", + "bowtie-open", + 27, + "27", + "circle-cross", + 127, + "127", + "circle-cross-open", + 28, + "28", + "circle-x", + 128, + "128", + "circle-x-open", + 29, + "29", + "square-cross", + 129, + "129", + "square-cross-open", + 30, + "30", + "square-x", + 130, + "130", + "square-x-open", + 31, + "31", + "diamond-cross", + 131, + "131", + "diamond-cross-open", + 32, + "32", + "diamond-x", + 132, + "132", + "diamond-x-open", + 33, + "33", + "cross-thin", + 133, + "133", + "cross-thin-open", + 34, + "34", + "x-thin", + 134, + "134", + "x-thin-open", + 35, + "35", + "asterisk", + 135, + "135", + "asterisk-open", + 36, + "36", + "hash", + 136, + "136", + "hash-open", + 236, + "236", + "hash-dot", + 336, + "336", + "hash-open-dot", + 37, + "37", + "y-up", + 137, + "137", + "y-up-open", + 38, + "38", + "y-down", + 138, + "138", + "y-down-open", + 39, + "39", + "y-left", + 139, + "139", + "y-left-open", + 40, + "40", + "y-right", + 140, + "140", + "y-right-open", + 41, + "41", + "line-ew", + 141, + "141", + "line-ew-open", + 42, + "42", + "line-ns", + 142, + "142", + "line-ns-open", + 43, + "43", + "line-ne", + 143, + "143", + "line-ne-open", + 44, + "44", + "line-nw", + 144, + "144", + "line-nw-open", + 45, + "45", + "arrow-up", + 145, + "145", + "arrow-up-open", + 46, + "46", + "arrow-down", + 146, + "146", + "arrow-down-open", + 47, + "47", + "arrow-left", + 147, + "147", + "arrow-left-open", + 48, + "48", + "arrow-right", + 148, + "148", + "arrow-right-open", + 49, + "49", + "arrow-bar-up", + 149, + "149", + "arrow-bar-up-open", + 50, + "50", + 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}, + "scattersmith.marker.reversescale": { + "params": { + "plotly_name": "reversescale", + "parent_name": "scattersmith.marker", + "edit_type": "plot" + }, + "superclass": "BooleanValidator" + }, + "scattersmith.marker.opacitysrc": { + "params": { + "plotly_name": "opacitysrc", + "parent_name": "scattersmith.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattersmith.marker.opacity": { + "params": { + "plotly_name": "opacity", + "parent_name": "scattersmith.marker", + "array_ok": true, + "edit_type": "style", + "max": 1, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattersmith.marker.maxdisplayed": { + "params": { + "plotly_name": "maxdisplayed", + "parent_name": "scattersmith.marker", + "edit_type": "plot", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattersmith.marker.line": { + "params": { + "plotly_name": "line", + "parent_name": "scattersmith.marker", + "data_class_str": "Line", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scattersmith.marker.line.widthsrc": { + "params": { + "plotly_name": "widthsrc", + "parent_name": "scattersmith.marker.line", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattersmith.marker.line.width": { + "params": { + "plotly_name": "width", + "parent_name": "scattersmith.marker.line", + "array_ok": true, + "edit_type": "style", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattersmith.marker.line.reversescale": { + "params": { + "plotly_name": "reversescale", + "parent_name": "scattersmith.marker.line", + "edit_type": "plot" + }, + "superclass": "BooleanValidator" + }, + "scattersmith.marker.line.colorsrc": { + "params": { + "plotly_name": "colorsrc", + "parent_name": "scattersmith.marker.line", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattersmith.marker.line.colorscale": { + "params": { + "plotly_name": "colorscale", + "parent_name": "scattersmith.marker.line", + "edit_type": "calc", + 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"calc+clearAxisTypes" + }, + "superclass": "AnyValidator" + }, + "scatterpolargl.theta": { + "params": { + "plotly_name": "theta", + "parent_name": "scatterpolargl", + "edit_type": "calc+clearAxisTypes" + }, + "superclass": "DataArrayValidator" + }, + "scatterpolargl.texttemplatesrc": { + "params": { + "plotly_name": "texttemplatesrc", + "parent_name": "scatterpolargl", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolargl.texttemplatefallback": { + "params": { + "plotly_name": "texttemplatefallback", + "parent_name": "scatterpolargl", + "edit_type": "plot" + }, + "superclass": "AnyValidator" + }, + "scatterpolargl.texttemplate": { + "params": { + "plotly_name": "texttemplate", + "parent_name": "scatterpolargl", + "array_ok": true, + "edit_type": "plot" + }, + "superclass": "StringValidator" + }, + "scatterpolargl.textsrc": { + "params": { + "plotly_name": "textsrc", + "parent_name": "scatterpolargl", + "edit_type": "none" + }, + "superclass": "SrcValidator" 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"scatterpolargl.textfont", + "array_ok": true, + "edit_type": "calc", + "values": [ + "normal", + "italic" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scatterpolargl.textfont.sizesrc": { + "params": { + "plotly_name": "sizesrc", + "parent_name": "scatterpolargl.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolargl.textfont.size": { + "params": { + "plotly_name": "size", + "parent_name": "scatterpolargl.textfont", + "array_ok": true, + "edit_type": "calc", + "min": 1 + }, + "superclass": "NumberValidator" + }, + "scatterpolargl.textfont.familysrc": { + "params": { + "plotly_name": "familysrc", + "parent_name": "scatterpolargl.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolargl.textfont.family": { + "params": { + "plotly_name": "family", + "parent_name": "scatterpolargl.textfont", + "array_ok": true, + "edit_type": "calc", + "no_blank": true, + "strict": true + }, + "superclass": "StringValidator" + }, + "scatterpolargl.textfont.colorsrc": { + "params": { + "plotly_name": "colorsrc", + "parent_name": "scatterpolargl.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolargl.textfont.color": { + "params": { + "plotly_name": "color", + "parent_name": "scatterpolargl.textfont", + "array_ok": true, + "edit_type": "calc" + }, + "superclass": "ColorValidator" + }, + "scatterpolargl.text": { + "params": { + "plotly_name": "text", + "parent_name": "scatterpolargl", + "array_ok": true, + "edit_type": "calc" + }, + "superclass": "StringValidator" + }, + "scatterpolargl.subplot": { + "params": { + "plotly_name": "subplot", + "parent_name": "scatterpolargl", + "dflt": "polar", + "edit_type": "calc" + }, + "superclass": "SubplotidValidator" + }, + "scatterpolargl.stream": { + "params": { + "plotly_name": "stream", + "parent_name": "scatterpolargl", + "data_class_str": "Stream", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatterpolargl.stream.token": { + "params": { + "plotly_name": "token", + "parent_name": "scatterpolargl.stream", + "edit_type": "calc", + "no_blank": true, + "strict": true + }, + "superclass": "StringValidator" + }, + "scatterpolargl.stream.maxpoints": { + "params": { + "plotly_name": "maxpoints", + "parent_name": "scatterpolargl.stream", + "edit_type": "calc", + "max": 10000, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatterpolargl.showlegend": { + "params": { + "plotly_name": "showlegend", + "parent_name": "scatterpolargl", + "edit_type": "style" + }, + "superclass": "BooleanValidator" + }, + "scatterpolargl.selectedpoints": { + "params": { + "plotly_name": "selectedpoints", + "parent_name": "scatterpolargl", + "edit_type": "calc" + }, + "superclass": "AnyValidator" + }, + "scatterpolargl.selected": { + "params": { + "plotly_name": "selected", + "parent_name": "scatterpolargl", + "data_class_str": "Selected", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatterpolargl.selected.textfont": { + "params": { + "plotly_name": "textfont", + "parent_name": "scatterpolargl.selected", + "data_class_str": "Textfont", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatterpolargl.selected.textfont.color": { + "params": { + "plotly_name": "color", + "parent_name": "scatterpolargl.selected.textfont", + "edit_type": "style" + }, + "superclass": "ColorValidator" + }, + "scatterpolargl.selected.marker": { + "params": { + "plotly_name": "marker", + "parent_name": "scatterpolargl.selected", + "data_class_str": "Marker", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatterpolargl.selected.marker.size": { + "params": { + "plotly_name": "size", + "parent_name": "scatterpolargl.selected.marker", + "edit_type": "style", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatterpolargl.selected.marker.opacity": { + "params": { + "plotly_name": "opacity", + "parent_name": "scatterpolargl.selected.marker", + "edit_type": "style", + "max": 1, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatterpolargl.selected.marker.color": { + "params": { + "plotly_name": "color", + "parent_name": "scatterpolargl.selected.marker", + "edit_type": "style" + }, + "superclass": "ColorValidator" + }, + "scatterpolargl.rsrc": { + "params": { + "plotly_name": "rsrc", + "parent_name": "scatterpolargl", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolargl.r0": { + "params": { + "plotly_name": "r0", + "parent_name": "scatterpolargl", + "edit_type": "calc+clearAxisTypes" + }, + "superclass": "AnyValidator" + }, + "scatterpolargl.r": { + "params": { + "plotly_name": "r", + "parent_name": "scatterpolargl", + "edit_type": "calc+clearAxisTypes" + }, + "superclass": "DataArrayValidator" + }, + "scatterpolargl.opacity": { + "params": { + "plotly_name": "opacity", + "parent_name": "scatterpolargl", + "edit_type": "style", + "max": 1, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatterpolargl.name": { + "params": { + "plotly_name": "name", + "parent_name": "scatterpolargl", + "edit_type": "style" + }, + "superclass": "StringValidator" + }, + "scatterpolargl.mode": { + "params": { + "plotly_name": "mode", + "parent_name": "scatterpolargl", + "edit_type": "calc", + "extras": [ + "none" + ], + "flags": [ + "lines", + "markers", + "text" + ] + }, + "superclass": "FlaglistValidator" + }, + "scatterpolargl.metasrc": { + "params": { + "plotly_name": "metasrc", + "parent_name": "scatterpolargl", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolargl.meta": { + "params": { + "plotly_name": "meta", + "parent_name": "scatterpolargl", + "array_ok": true, + "edit_type": "plot" + }, + "superclass": "AnyValidator" + }, + "scatterpolargl.marker": { + "params": { + "plotly_name": "marker", + "parent_name": "scatterpolargl", + "data_class_str": "Marker", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatterpolargl.marker.symbolsrc": { + "params": { + "plotly_name": "symbolsrc", + "parent_name": "scatterpolargl.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolargl.marker.symbol": { + "params": { + "plotly_name": "symbol", + "parent_name": "scatterpolargl.marker", + "array_ok": true, + "edit_type": "calc", + "values": [ + 0, + "0", + "circle", + 100, + "100", + "circle-open", + 200, + "200", + "circle-dot", + 300, + "300", + "circle-open-dot", + 1, + "1", + "square", + 101, + "101", + "square-open", + 201, + "201", + "square-dot", + 301, + "301", + "square-open-dot", + 2, + "2", + "diamond", + 102, + "102", + "diamond-open", + 202, + "202", + "diamond-dot", + 302, + "302", + "diamond-open-dot", + 3, + "3", + "cross", + 103, + "103", + "cross-open", + 203, + "203", + "cross-dot", + 303, + "303", + "cross-open-dot", + 4, + "4", + "x", + 104, + "104", + "x-open", + 204, + "204", + "x-dot", + 304, + "304", + "x-open-dot", + 5, + "5", + "triangle-up", + 105, + "105", + "triangle-up-open", + 205, + "205", + "triangle-up-dot", + 305, + "305", + "triangle-up-open-dot", + 6, + "6", + "triangle-down", + 106, + "106", + "triangle-down-open", + 206, + "206", + "triangle-down-dot", + 306, + "306", + "triangle-down-open-dot", + 7, + "7", + "triangle-left", + 107, + "107", + "triangle-left-open", + 207, + "207", + "triangle-left-dot", + 307, + "307", + "triangle-left-open-dot", + 8, + "8", + "triangle-right", + 108, + "108", + "triangle-right-open", + 208, + "208", + "triangle-right-dot", + 308, + "308", + "triangle-right-open-dot", + 9, + "9", + "triangle-ne", + 109, + "109", + "triangle-ne-open", + 209, + "209", + "triangle-ne-dot", + 309, + "309", + "triangle-ne-open-dot", + 10, + "10", + "triangle-se", + 110, + "110", + "triangle-se-open", + 210, + "210", + "triangle-se-dot", + 310, + "310", + "triangle-se-open-dot", + 11, + "11", + "triangle-sw", + 111, + "111", + "triangle-sw-open", + 211, + "211", + "triangle-sw-dot", + 311, + "311", + "triangle-sw-open-dot", + 12, + "12", + "triangle-nw", + 112, + "112", + "triangle-nw-open", + 212, + "212", + "triangle-nw-dot", + 312, + "312", + "triangle-nw-open-dot", + 13, + "13", + "pentagon", + 113, + "113", + "pentagon-open", + 213, + "213", + "pentagon-dot", + 313, + "313", + "pentagon-open-dot", + 14, + "14", + "hexagon", + 114, + "114", + "hexagon-open", + 214, + "214", + "hexagon-dot", + 314, + "314", + "hexagon-open-dot", + 15, + "15", + "hexagon2", + 115, + "115", + "hexagon2-open", + 215, + "215", + "hexagon2-dot", + 315, + "315", + "hexagon2-open-dot", + 16, + "16", + "octagon", + 116, + "116", + "octagon-open", + 216, + "216", + "octagon-dot", + 316, + "316", + "octagon-open-dot", + 17, + "17", + "star", + 117, + "117", + "star-open", + 217, + "217", + "star-dot", + 317, + "317", + "star-open-dot", + 18, + "18", + "hexagram", + 118, + "118", + "hexagram-open", + 218, + "218", + "hexagram-dot", + 318, + "318", + "hexagram-open-dot", + 19, + "19", + "star-triangle-up", + 119, + "119", + "star-triangle-up-open", + 219, + "219", + "star-triangle-up-dot", + 319, + "319", + "star-triangle-up-open-dot", + 20, + "20", + "star-triangle-down", + 120, + "120", + "star-triangle-down-open", + 220, + "220", + "star-triangle-down-dot", + 320, + "320", + "star-triangle-down-open-dot", + 21, + "21", + "star-square", + 121, + "121", + "star-square-open", + 221, + "221", + "star-square-dot", + 321, + "321", + "star-square-open-dot", + 22, + "22", + "star-diamond", + 122, + "122", + "star-diamond-open", + 222, + "222", + "star-diamond-dot", + 322, + "322", + "star-diamond-open-dot", + 23, + "23", + "diamond-tall", + 123, + "123", + "diamond-tall-open", + 223, + "223", + "diamond-tall-dot", + 323, + "323", + "diamond-tall-open-dot", + 24, + "24", + "diamond-wide", + 124, + "124", + "diamond-wide-open", + 224, + "224", + "diamond-wide-dot", + 324, + "324", + "diamond-wide-open-dot", + 25, + "25", + "hourglass", + 125, + "125", + "hourglass-open", + 26, + "26", + "bowtie", + 126, + "126", + "bowtie-open", + 27, + "27", + "circle-cross", + 127, + "127", + "circle-cross-open", + 28, + "28", + "circle-x", + 128, + "128", + "circle-x-open", + 29, + "29", + "square-cross", + 129, + "129", + "square-cross-open", + 30, + "30", + "square-x", + 130, + "130", + "square-x-open", + 31, + "31", + "diamond-cross", + 131, + "131", + "diamond-cross-open", + 32, + "32", + "diamond-x", + 132, + "132", + "diamond-x-open", + 33, + "33", + "cross-thin", + 133, + "133", + "cross-thin-open", + 34, + "34", + "x-thin", + 134, + "134", + "x-thin-open", + 35, + "35", + "asterisk", + 135, + "135", + "asterisk-open", + 36, + "36", + "hash", + 136, + "136", + "hash-open", + 236, + "236", + "hash-dot", + 336, + "336", + "hash-open-dot", + 37, + "37", + "y-up", + 137, + "137", + "y-up-open", + 38, + "38", + "y-down", + 138, + "138", + "y-down-open", + 39, + "39", + "y-left", + 139, + "139", + "y-left-open", + 40, + "40", + "y-right", + 140, + "140", + "y-right-open", + 41, + "41", + "line-ew", + 141, + "141", + "line-ew-open", + 42, + "42", + "line-ns", + 142, + "142", + "line-ns-open", + 43, + "43", + "line-ne", + 143, + "143", + "line-ne-open", + 44, + "44", + "line-nw", + 144, + "144", + "line-nw-open", + 45, + "45", + "arrow-up", + 145, + "145", + "arrow-up-open", + 46, + "46", + "arrow-down", + 146, + "146", + "arrow-down-open", + 47, + "47", + "arrow-left", + 147, + "147", + "arrow-left-open", + 48, + "48", + "arrow-right", + 148, + "148", + "arrow-right-open", + 49, + "49", + "arrow-bar-up", + 149, + "149", + "arrow-bar-up-open", + 50, + "50", + "arrow-bar-down", + 150, + "150", + "arrow-bar-down-open", + 51, + "51", + "arrow-bar-left", + 151, + "151", + "arrow-bar-left-open", + 52, + "52", + "arrow-bar-right", + 152, + "152", + "arrow-bar-right-open", + 53, + "53", + "arrow", + 153, + "153", + "arrow-open", + 54, + "54", + "arrow-wide", + 154, + "154", + "arrow-wide-open" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scatterpolargl.marker.sizesrc": { + "params": { + "plotly_name": "sizesrc", + "parent_name": "scatterpolargl.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolargl.marker.sizeref": { + "params": { + "plotly_name": "sizeref", + "parent_name": "scatterpolargl.marker", + "edit_type": "calc" + }, + "superclass": "NumberValidator" + }, + "scatterpolargl.marker.sizemode": { + "params": { + "plotly_name": "sizemode", + "parent_name": "scatterpolargl.marker", + "edit_type": "calc", + "values": [ + "diameter", + "area" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scatterpolargl.marker.sizemin": { + "params": { + "plotly_name": "sizemin", + "parent_name": "scatterpolargl.marker", + "edit_type": "calc", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatterpolargl.marker.size": { + "params": { + "plotly_name": "size", + "parent_name": "scatterpolargl.marker", + "array_ok": true, + "edit_type": "calc", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatterpolargl.marker.showscale": { + "params": { + "plotly_name": "showscale", + "parent_name": "scatterpolargl.marker", + "edit_type": "calc" + }, + "superclass": "BooleanValidator" + }, + "scatterpolargl.marker.reversescale": { + "params": { + "plotly_name": "reversescale", + "parent_name": "scatterpolargl.marker", + "edit_type": "calc" + }, + "superclass": "BooleanValidator" + }, + "scatterpolargl.marker.opacitysrc": { + "params": { + "plotly_name": "opacitysrc", + "parent_name": "scatterpolargl.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolargl.marker.opacity": { + "params": { + "plotly_name": "opacity", + "parent_name": "scatterpolargl.marker", + "array_ok": true, + "edit_type": "calc", + "max": 1, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatterpolargl.marker.line": { + "params": { + "plotly_name": "line", + "parent_name": "scatterpolargl.marker", + "data_class_str": "Line", + 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true, + "edit_type": "calc", + "values": [ + "top left", + "top center", + "top right", + "middle left", + "middle center", + "middle right", + "bottom left", + "bottom center", + "bottom right" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scatterpolar.textfont": { + "params": { + "plotly_name": "textfont", + "parent_name": "scatterpolar", + "data_class_str": "Textfont", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatterpolar.textfont.weightsrc": { + "params": { + "plotly_name": "weightsrc", + "parent_name": "scatterpolar.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolar.textfont.weight": { + "params": { + "plotly_name": "weight", + "parent_name": "scatterpolar.textfont", + "array_ok": true, + "edit_type": "calc", + "extras": [ + "normal", + "bold" + ], + "max": 1000, + "min": 1 + }, + "superclass": "IntegerValidator" + }, + "scatterpolar.textfont.variantsrc": { + "params": { + "plotly_name": "variantsrc", + "parent_name": "scatterpolar.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolar.textfont.variant": { + "params": { + "plotly_name": "variant", + "parent_name": "scatterpolar.textfont", + "array_ok": true, + "edit_type": "calc", + "values": [ + "normal", + "small-caps", + "all-small-caps", + "all-petite-caps", + "petite-caps", + "unicase" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scatterpolar.textfont.textcasesrc": { + "params": { + "plotly_name": "textcasesrc", + "parent_name": "scatterpolar.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolar.textfont.textcase": { + "params": { + "plotly_name": "textcase", + "parent_name": "scatterpolar.textfont", + "array_ok": true, + "edit_type": "calc", + "values": [ + "normal", + "word caps", + "upper", + "lower" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scatterpolar.textfont.stylesrc": { + "params": { + "plotly_name": "stylesrc", + "parent_name": "scatterpolar.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolar.textfont.style": { + "params": { + "plotly_name": "style", + "parent_name": "scatterpolar.textfont", + "array_ok": true, + "edit_type": "calc", + "values": [ + "normal", + "italic" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scatterpolar.textfont.sizesrc": { + "params": { + "plotly_name": "sizesrc", + "parent_name": "scatterpolar.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolar.textfont.size": { + "params": { + "plotly_name": "size", + "parent_name": "scatterpolar.textfont", + "array_ok": true, + "edit_type": "calc", + "min": 1 + }, + "superclass": "NumberValidator" + }, + "scatterpolar.textfont.shadowsrc": { + "params": { + "plotly_name": "shadowsrc", + "parent_name": "scatterpolar.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolar.textfont.shadow": { + "params": { + "plotly_name": "shadow", + "parent_name": "scatterpolar.textfont", + "array_ok": true, + "edit_type": "calc" + }, + "superclass": "StringValidator" + }, + "scatterpolar.textfont.linepositionsrc": { + "params": { + "plotly_name": "linepositionsrc", + "parent_name": "scatterpolar.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolar.textfont.lineposition": { + "params": { + "plotly_name": "lineposition", + "parent_name": "scatterpolar.textfont", + "array_ok": true, + "edit_type": "calc", + "extras": [ + "none" + ], + "flags": [ + "under", + "over", + "through" + ] + }, + "superclass": "FlaglistValidator" + }, + "scatterpolar.textfont.familysrc": { + "params": { + "plotly_name": "familysrc", + "parent_name": "scatterpolar.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolar.textfont.family": { + "params": { + "plotly_name": "family", + "parent_name": "scatterpolar.textfont", + "array_ok": true, + "edit_type": "calc", + "no_blank": true, + "strict": true + }, + "superclass": "StringValidator" + }, + "scatterpolar.textfont.colorsrc": { + "params": { + "plotly_name": "colorsrc", + "parent_name": "scatterpolar.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolar.textfont.color": { + "params": { + "plotly_name": "color", + "parent_name": "scatterpolar.textfont", + "array_ok": true, + "edit_type": "style" + }, + "superclass": "ColorValidator" + }, + "scatterpolar.text": { + "params": { + "plotly_name": "text", + "parent_name": "scatterpolar", + "array_ok": true, + "edit_type": "calc" + }, + "superclass": "StringValidator" + }, + "scatterpolar.subplot": { + "params": { + "plotly_name": "subplot", + "parent_name": "scatterpolar", + "dflt": "polar", + "edit_type": "calc" + }, + "superclass": "SubplotidValidator" + }, + "scatterpolar.stream": { + "params": { + "plotly_name": "stream", + "parent_name": "scatterpolar", + "data_class_str": "Stream", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatterpolar.stream.token": { + "params": { + "plotly_name": "token", + "parent_name": "scatterpolar.stream", + "edit_type": "calc", + "no_blank": true, + "strict": true + }, + "superclass": "StringValidator" + }, + "scatterpolar.stream.maxpoints": { + "params": { + "plotly_name": "maxpoints", + "parent_name": "scatterpolar.stream", + "edit_type": "calc", + "max": 10000, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatterpolar.showlegend": { + "params": { + "plotly_name": "showlegend", + "parent_name": "scatterpolar", + "edit_type": "style" + }, + "superclass": "BooleanValidator" + }, + "scatterpolar.selectedpoints": { + "params": { + "plotly_name": "selectedpoints", + "parent_name": "scatterpolar", + "edit_type": "calc" + }, + "superclass": "AnyValidator" + }, + "scatterpolar.selected": { + "params": { + "plotly_name": "selected", + "parent_name": "scatterpolar", + "data_class_str": "Selected", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatterpolar.selected.textfont": { + "params": { + "plotly_name": "textfont", + "parent_name": "scatterpolar.selected", + "data_class_str": "Textfont", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatterpolar.selected.textfont.color": { + "params": { + "plotly_name": "color", + "parent_name": "scatterpolar.selected.textfont", + "edit_type": "style" + }, + "superclass": "ColorValidator" + }, + "scatterpolar.selected.marker": { + "params": { + "plotly_name": "marker", + "parent_name": "scatterpolar.selected", + "data_class_str": "Marker", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatterpolar.selected.marker.size": { + "params": { + "plotly_name": "size", + "parent_name": "scatterpolar.selected.marker", + "edit_type": "style", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatterpolar.selected.marker.opacity": { + "params": { + "plotly_name": "opacity", + "parent_name": "scatterpolar.selected.marker", + "edit_type": "style", + "max": 1, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatterpolar.selected.marker.color": { + "params": { + "plotly_name": "color", + "parent_name": "scatterpolar.selected.marker", + "edit_type": "style" + }, + "superclass": "ColorValidator" + }, + "scatterpolar.rsrc": { + "params": { + "plotly_name": "rsrc", + "parent_name": "scatterpolar", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolar.r0": { + "params": { + "plotly_name": "r0", + "parent_name": "scatterpolar", + "edit_type": "calc+clearAxisTypes" + }, + "superclass": "AnyValidator" + }, + "scatterpolar.r": { + "params": { + "plotly_name": "r", + "parent_name": "scatterpolar", + "edit_type": "calc+clearAxisTypes" + }, + "superclass": "DataArrayValidator" + }, + "scatterpolar.opacity": { + "params": { + "plotly_name": "opacity", + "parent_name": "scatterpolar", + "edit_type": "style", + "max": 1, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatterpolar.name": { + "params": { + "plotly_name": "name", + "parent_name": "scatterpolar", + "edit_type": "style" + }, + "superclass": "StringValidator" + }, + "scatterpolar.mode": { + "params": { + "plotly_name": "mode", + "parent_name": "scatterpolar", + "edit_type": "calc", + "extras": [ + "none" + ], + "flags": [ + "lines", + "markers", + "text" + ] + }, + "superclass": "FlaglistValidator" + }, + "scatterpolar.metasrc": { + "params": { + "plotly_name": "metasrc", + "parent_name": "scatterpolar", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolar.meta": { + "params": { + "plotly_name": "meta", + "parent_name": "scatterpolar", + "array_ok": true, + "edit_type": "plot" + }, + "superclass": "AnyValidator" + }, + "scatterpolar.marker": { + "params": { + "plotly_name": "marker", + "parent_name": "scatterpolar", + "data_class_str": "Marker", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatterpolar.marker.symbolsrc": { + "params": { + "plotly_name": "symbolsrc", + "parent_name": "scatterpolar.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolar.marker.symbol": { + "params": { + "plotly_name": "symbol", + "parent_name": "scatterpolar.marker", + "array_ok": true, + "edit_type": "style", + "values": [ + 0, + "0", + "circle", + 100, + "100", + "circle-open", + 200, + "200", + "circle-dot", + 300, + "300", + "circle-open-dot", + 1, + "1", + "square", + 101, + "101", + "square-open", + 201, + "201", + "square-dot", + 301, + "301", + "square-open-dot", + 2, + "2", + "diamond", + 102, + "102", + "diamond-open", + 202, + "202", + "diamond-dot", + 302, + "302", + "diamond-open-dot", + 3, + "3", + "cross", + 103, + "103", + "cross-open", + 203, + "203", + "cross-dot", + 303, + "303", + "cross-open-dot", + 4, + "4", + "x", + 104, + "104", + "x-open", + 204, + "204", + "x-dot", + 304, + "304", + "x-open-dot", + 5, + "5", + "triangle-up", + 105, + "105", + "triangle-up-open", + 205, + "205", + "triangle-up-dot", + 305, + "305", + "triangle-up-open-dot", + 6, + "6", + "triangle-down", + 106, + "106", + "triangle-down-open", + 206, + "206", + "triangle-down-dot", + 306, + "306", + "triangle-down-open-dot", + 7, + "7", + "triangle-left", + 107, + "107", + "triangle-left-open", + 207, + "207", + "triangle-left-dot", + 307, + "307", + "triangle-left-open-dot", + 8, + "8", + "triangle-right", + 108, + "108", + "triangle-right-open", + 208, + "208", + "triangle-right-dot", + 308, + "308", + "triangle-right-open-dot", + 9, + "9", + "triangle-ne", + 109, + "109", + "triangle-ne-open", + 209, + "209", + "triangle-ne-dot", + 309, + "309", + "triangle-ne-open-dot", + 10, + "10", + "triangle-se", + 110, + "110", + "triangle-se-open", + 210, + "210", + "triangle-se-dot", + 310, + "310", + "triangle-se-open-dot", + 11, + "11", + "triangle-sw", + 111, + "111", + "triangle-sw-open", + 211, + "211", + "triangle-sw-dot", + 311, + "311", + "triangle-sw-open-dot", + 12, + "12", + "triangle-nw", + 112, + "112", + "triangle-nw-open", + 212, + "212", + "triangle-nw-dot", + 312, + "312", + "triangle-nw-open-dot", + 13, + "13", + "pentagon", + 113, + "113", + "pentagon-open", + 213, + "213", + "pentagon-dot", + 313, + "313", + "pentagon-open-dot", + 14, + "14", + "hexagon", + 114, + "114", + "hexagon-open", + 214, + "214", + "hexagon-dot", + 314, + "314", + "hexagon-open-dot", + 15, + "15", + "hexagon2", + 115, + "115", + "hexagon2-open", + 215, + "215", + "hexagon2-dot", + 315, + "315", + "hexagon2-open-dot", + 16, + "16", + "octagon", + 116, + "116", + "octagon-open", + 216, + "216", + "octagon-dot", + 316, + "316", + "octagon-open-dot", + 17, + "17", + "star", + 117, + "117", + "star-open", + 217, + "217", + "star-dot", + 317, + "317", + "star-open-dot", + 18, + "18", + "hexagram", + 118, + "118", + "hexagram-open", + 218, + "218", + "hexagram-dot", + 318, + "318", + "hexagram-open-dot", + 19, + "19", + "star-triangle-up", + 119, + "119", + "star-triangle-up-open", + 219, + "219", + "star-triangle-up-dot", + 319, + "319", + "star-triangle-up-open-dot", + 20, + "20", + "star-triangle-down", + 120, + "120", + "star-triangle-down-open", + 220, + "220", + "star-triangle-down-dot", + 320, + "320", + "star-triangle-down-open-dot", + 21, + "21", + "star-square", + 121, + "121", + "star-square-open", + 221, + "221", + "star-square-dot", + 321, + "321", + "star-square-open-dot", + 22, + "22", + "star-diamond", + 122, + "122", + "star-diamond-open", + 222, + "222", + "star-diamond-dot", + 322, + "322", + "star-diamond-open-dot", + 23, + "23", + "diamond-tall", + 123, + "123", + "diamond-tall-open", + 223, + "223", + "diamond-tall-dot", + 323, + "323", + "diamond-tall-open-dot", + 24, + "24", + "diamond-wide", + 124, + "124", + "diamond-wide-open", + 224, + "224", + "diamond-wide-dot", + 324, + "324", + "diamond-wide-open-dot", + 25, + "25", + "hourglass", + 125, + "125", + "hourglass-open", + 26, + "26", + "bowtie", + 126, + "126", + "bowtie-open", + 27, + "27", + "circle-cross", + 127, + "127", + "circle-cross-open", + 28, + "28", + "circle-x", + 128, + "128", + "circle-x-open", + 29, + "29", + "square-cross", + 129, + "129", + "square-cross-open", + 30, + "30", + "square-x", + 130, + "130", + "square-x-open", + 31, + "31", + "diamond-cross", + 131, + "131", + "diamond-cross-open", + 32, + "32", + "diamond-x", + 132, + "132", + "diamond-x-open", + 33, + "33", + "cross-thin", + 133, + "133", + "cross-thin-open", + 34, + "34", + "x-thin", + 134, + "134", + "x-thin-open", + 35, + "35", + "asterisk", + 135, + "135", + "asterisk-open", + 36, + "36", + "hash", + 136, + "136", + "hash-open", + 236, + "236", + "hash-dot", + 336, + "336", + "hash-open-dot", + 37, + "37", + "y-up", + 137, + "137", + "y-up-open", + 38, + "38", + "y-down", + 138, + "138", + "y-down-open", + 39, + "39", + "y-left", + 139, + "139", + "y-left-open", + 40, + "40", + "y-right", + 140, + "140", + "y-right-open", + 41, + "41", + "line-ew", + 141, + "141", + "line-ew-open", + 42, + "42", + "line-ns", + 142, + "142", + "line-ns-open", + 43, + "43", + "line-ne", + 143, + "143", + "line-ne-open", + 44, + "44", + "line-nw", + 144, + "144", + "line-nw-open", + 45, + "45", + "arrow-up", + 145, + "145", + "arrow-up-open", + 46, + "46", + "arrow-down", + 146, + "146", + "arrow-down-open", + 47, + "47", + "arrow-left", + 147, + "147", + "arrow-left-open", + 48, + "48", + "arrow-right", + 148, + "148", + "arrow-right-open", + 49, + "49", + "arrow-bar-up", + 149, + "149", + "arrow-bar-up-open", + 50, + "50", + "arrow-bar-down", + 150, + "150", + "arrow-bar-down-open", + 51, + "51", + "arrow-bar-left", + 151, + "151", + "arrow-bar-left-open", + 52, + "52", + "arrow-bar-right", + 152, + "152", + "arrow-bar-right-open", + 53, + "53", + "arrow", + 153, + "153", + "arrow-open", + 54, + "54", + "arrow-wide", + 154, + "154", + "arrow-wide-open" + ] + }, + "superclass": "EnumeratedValidator" + }, + 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"scatterpolar.marker.sizemin": { + "params": { + "plotly_name": "sizemin", + "parent_name": "scatterpolar.marker", + "edit_type": "calc", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatterpolar.marker.size": { + "params": { + "plotly_name": "size", + "parent_name": "scatterpolar.marker", + "array_ok": true, + "edit_type": "calc", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatterpolar.marker.showscale": { + "params": { + "plotly_name": "showscale", + "parent_name": "scatterpolar.marker", + "edit_type": "calc" + }, + "superclass": "BooleanValidator" + }, + "scatterpolar.marker.reversescale": { + "params": { + "plotly_name": "reversescale", + "parent_name": "scatterpolar.marker", + "edit_type": "plot" + }, + "superclass": "BooleanValidator" + }, + "scatterpolar.marker.opacitysrc": { + "params": { + "plotly_name": "opacitysrc", + "parent_name": "scatterpolar.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolar.marker.opacity": { + "params": { + "plotly_name": "opacity", + "parent_name": "scatterpolar.marker", + "array_ok": true, + "edit_type": "style", + "max": 1, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatterpolar.marker.maxdisplayed": { + "params": { + "plotly_name": "maxdisplayed", + "parent_name": "scatterpolar.marker", + "edit_type": "plot", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatterpolar.marker.line": { + "params": { + "plotly_name": "line", + "parent_name": "scatterpolar.marker", + "data_class_str": "Line", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatterpolar.marker.line.widthsrc": { + "params": { + "plotly_name": "widthsrc", + "parent_name": "scatterpolar.marker.line", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatterpolar.marker.line.width": { + "params": { + "plotly_name": "width", + "parent_name": "scatterpolar.marker.line", + "array_ok": true, + "edit_type": "style", + 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"edit_type": "calc", + "max": 1, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattergl.selected.marker.color": { + "params": { + "plotly_name": "color", + "parent_name": "scattergl.selected.marker", + "edit_type": "calc" + }, + "superclass": "ColorValidator" + }, + "scattergl.opacity": { + "params": { + "plotly_name": "opacity", + "parent_name": "scattergl", + "edit_type": "calc", + "max": 1, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattergl.name": { + "params": { + "plotly_name": "name", + "parent_name": "scattergl", + "edit_type": "style" + }, + "superclass": "StringValidator" + }, + "scattergl.mode": { + "params": { + "plotly_name": "mode", + "parent_name": "scattergl", + "edit_type": "calc", + "extras": [ + "none" + ], + "flags": [ + "lines", + "markers", + "text" + ] + }, + "superclass": "FlaglistValidator" + }, + "scattergl.metasrc": { + "params": { + "plotly_name": "metasrc", + "parent_name": "scattergl", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattergl.meta": { + "params": { + "plotly_name": "meta", + "parent_name": "scattergl", + "array_ok": true, + "edit_type": "plot" + }, + "superclass": "AnyValidator" + }, + "scattergl.marker": { + "params": { + "plotly_name": "marker", + "parent_name": "scattergl", + "data_class_str": "Marker", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scattergl.marker.symbolsrc": { + "params": { + "plotly_name": "symbolsrc", + "parent_name": "scattergl.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattergl.marker.symbol": { + "params": { + "plotly_name": "symbol", + "parent_name": "scattergl.marker", + "array_ok": true, + "edit_type": "calc", + "values": [ + 0, + "0", + "circle", + 100, + "100", + "circle-open", + 200, + "200", + "circle-dot", + 300, + "300", + "circle-open-dot", + 1, + "1", + "square", + 101, + "101", + "square-open", + 201, + "201", + "square-dot", + 301, + "301", + "square-open-dot", + 2, + "2", + "diamond", + 102, + "102", + "diamond-open", + 202, + "202", + "diamond-dot", + 302, + "302", + "diamond-open-dot", + 3, + "3", + "cross", + 103, + "103", + "cross-open", + 203, + "203", + "cross-dot", + 303, + "303", + "cross-open-dot", + 4, + "4", + "x", + 104, + "104", + "x-open", + 204, + "204", + "x-dot", + 304, + "304", + "x-open-dot", + 5, + "5", + "triangle-up", + 105, + "105", + "triangle-up-open", + 205, + "205", + "triangle-up-dot", + 305, + "305", + "triangle-up-open-dot", + 6, + "6", + "triangle-down", + 106, + "106", + "triangle-down-open", + 206, + "206", + "triangle-down-dot", + 306, + "306", + "triangle-down-open-dot", + 7, + "7", + "triangle-left", + 107, + "107", + "triangle-left-open", + 207, + "207", + "triangle-left-dot", + 307, + "307", + "triangle-left-open-dot", + 8, + "8", + "triangle-right", + 108, + "108", + "triangle-right-open", + 208, + "208", + "triangle-right-dot", + 308, + "308", + "triangle-right-open-dot", + 9, + "9", + "triangle-ne", + 109, + "109", 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{ + "plotly_name": "symbolsrc", + "parent_name": "scattergeo.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattergeo.marker.symbol": { + "params": { + "plotly_name": "symbol", + "parent_name": "scattergeo.marker", + "array_ok": true, + "edit_type": "calc", + "values": [ + 0, + "0", + "circle", + 100, + "100", + "circle-open", + 200, + "200", + "circle-dot", + 300, + "300", + "circle-open-dot", + 1, + "1", + "square", + 101, + "101", + "square-open", + 201, + "201", + "square-dot", + 301, + "301", + "square-open-dot", + 2, + "2", + "diamond", + 102, + "102", + "diamond-open", + 202, + "202", + "diamond-dot", + 302, + "302", + "diamond-open-dot", + 3, + "3", + "cross", + 103, + "103", + "cross-open", + 203, + "203", + "cross-dot", + 303, + "303", + "cross-open-dot", + 4, + "4", + "x", + 104, + "104", + "x-open", + 204, + "204", + "x-dot", + 304, + "304", + "x-open-dot", + 5, + "5", + "triangle-up", + 105, + "105", + "triangle-up-open", + 205, + "205", + 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"circle-cross", + 127, + "127", + "circle-cross-open", + 28, + "28", + "circle-x", + 128, + "128", + "circle-x-open", + 29, + "29", + "square-cross", + 129, + "129", + "square-cross-open", + 30, + "30", + "square-x", + 130, + "130", + "square-x-open", + 31, + "31", + "diamond-cross", + 131, + "131", + "diamond-cross-open", + 32, + "32", + "diamond-x", + 132, + "132", + "diamond-x-open", + 33, + "33", + "cross-thin", + 133, + "133", + "cross-thin-open", + 34, + "34", + "x-thin", + 134, + "134", + "x-thin-open", + 35, + "35", + "asterisk", + 135, + "135", + "asterisk-open", + 36, + "36", + "hash", + 136, + "136", + "hash-open", + 236, + "236", + "hash-dot", + 336, + "336", + "hash-open-dot", + 37, + "37", + "y-up", + 137, + "137", + "y-up-open", + 38, + "38", + "y-down", + 138, + "138", + "y-down-open", + 39, + "39", + "y-left", + 139, + "139", + "y-left-open", + 40, + "40", + "y-right", + 140, + "140", + "y-right-open", + 41, + "41", + "line-ew", + 141, + "141", + "line-ew-open", + 42, 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"edit_type": "calc", + "max": 1, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattergeo.marker.line": { + "params": { + "plotly_name": "line", + "parent_name": "scattergeo.marker", + "data_class_str": "Line", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scattergeo.marker.line.widthsrc": { + "params": { + "plotly_name": "widthsrc", + "parent_name": "scattergeo.marker.line", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattergeo.marker.line.width": { + "params": { + "plotly_name": "width", + "parent_name": "scattergeo.marker.line", + "array_ok": true, + "edit_type": "calc", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattergeo.marker.line.reversescale": { + "params": { + "plotly_name": "reversescale", + "parent_name": "scattergeo.marker.line", + "edit_type": "calc" + }, + "superclass": "BooleanValidator" + }, + "scattergeo.marker.line.colorsrc": { + "params": { + "plotly_name": "colorsrc", + "parent_name": 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"params": { + "plotly_name": "gradient", + "parent_name": "scattergeo.marker", + "data_class_str": "Gradient", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scattergeo.marker.gradient.typesrc": { + "params": { + "plotly_name": "typesrc", + "parent_name": "scattergeo.marker.gradient", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattergeo.marker.gradient.type": { + "params": { + "plotly_name": "type", + "parent_name": "scattergeo.marker.gradient", + "array_ok": true, + "edit_type": "calc", + "values": [ + "radial", + "horizontal", + "vertical", + "none" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scattergeo.marker.gradient.colorsrc": { + "params": { + "plotly_name": "colorsrc", + "parent_name": "scattergeo.marker.gradient", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattergeo.marker.gradient.color": { + "params": { + "plotly_name": "color", + "parent_name": "scattergeo.marker.gradient", + "array_ok": true, + "edit_type": "calc" + }, + "superclass": "ColorValidator" + }, + "scattergeo.marker.colorsrc": { + "params": { + "plotly_name": "colorsrc", + "parent_name": "scattergeo.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattergeo.marker.colorscale": { + "params": { + "plotly_name": "colorscale", + "parent_name": "scattergeo.marker", + "edit_type": "calc", + "implied_edits": { + "autocolorscale": false + } + }, + "superclass": "ColorscaleValidator" + }, + "scattergeo.marker.colorbar": { + "params": { + "plotly_name": "colorbar", + "parent_name": "scattergeo.marker", + "data_class_str": "ColorBar", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scattergeo.marker.colorbar.yref": { + "params": { + "plotly_name": "yref", + "parent_name": "scattergeo.marker.colorbar", + "edit_type": "calc", + "values": [ + "container", + "paper" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scattergeo.marker.colorbar.ypad": { + "params": { + 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"familysrc", + "parent_name": "scattercarpet.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattercarpet.textfont.family": { + "params": { + "plotly_name": "family", + "parent_name": "scattercarpet.textfont", + "array_ok": true, + "edit_type": "calc", + "no_blank": true, + "strict": true + }, + "superclass": "StringValidator" + }, + "scattercarpet.textfont.colorsrc": { + "params": { + "plotly_name": "colorsrc", + "parent_name": "scattercarpet.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattercarpet.textfont.color": { + "params": { + "plotly_name": "color", + "parent_name": "scattercarpet.textfont", + "array_ok": true, + "edit_type": "style" + }, + "superclass": "ColorValidator" + }, + "scattercarpet.text": { + "params": { + "plotly_name": "text", + "parent_name": "scattercarpet", + "array_ok": true, + "edit_type": "calc" + }, + "superclass": "StringValidator" + }, + "scattercarpet.stream": { + "params": { + "plotly_name": "stream", + "parent_name": "scattercarpet", + "data_class_str": "Stream", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scattercarpet.stream.token": { + "params": { + "plotly_name": "token", + "parent_name": "scattercarpet.stream", + "edit_type": "calc", + "no_blank": true, + "strict": true + }, + "superclass": "StringValidator" + }, + "scattercarpet.stream.maxpoints": { + "params": { + "plotly_name": "maxpoints", + "parent_name": "scattercarpet.stream", + "edit_type": "calc", + "max": 10000, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattercarpet.showlegend": { + "params": { + "plotly_name": "showlegend", + "parent_name": "scattercarpet", + "edit_type": "style" + }, + "superclass": "BooleanValidator" + }, + "scattercarpet.selectedpoints": { + "params": { + "plotly_name": "selectedpoints", + "parent_name": "scattercarpet", + "edit_type": "calc" + }, + "superclass": "AnyValidator" + }, + "scattercarpet.selected": { + "params": { + "plotly_name": "selected", + "parent_name": "scattercarpet", + "data_class_str": "Selected", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scattercarpet.selected.textfont": { + "params": { + "plotly_name": "textfont", + "parent_name": "scattercarpet.selected", + "data_class_str": "Textfont", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scattercarpet.selected.textfont.color": { + "params": { + "plotly_name": "color", + "parent_name": "scattercarpet.selected.textfont", + "edit_type": "style" + }, + "superclass": "ColorValidator" + }, + "scattercarpet.selected.marker": { + "params": { + "plotly_name": "marker", + "parent_name": "scattercarpet.selected", + "data_class_str": "Marker", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scattercarpet.selected.marker.size": { + "params": { + "plotly_name": "size", + "parent_name": "scattercarpet.selected.marker", + "edit_type": "style", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattercarpet.selected.marker.opacity": { + "params": { + "plotly_name": "opacity", + "parent_name": "scattercarpet.selected.marker", + "edit_type": "style", + "max": 1, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattercarpet.selected.marker.color": { + "params": { + "plotly_name": "color", + "parent_name": "scattercarpet.selected.marker", + "edit_type": "style" + }, + "superclass": "ColorValidator" + }, + "scattercarpet.opacity": { + "params": { + "plotly_name": "opacity", + "parent_name": "scattercarpet", + "edit_type": "style", + "max": 1, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattercarpet.name": { + "params": { + "plotly_name": "name", + "parent_name": "scattercarpet", + "edit_type": "style" + }, + "superclass": "StringValidator" + }, + "scattercarpet.mode": { + "params": { + "plotly_name": "mode", + "parent_name": "scattercarpet", + "edit_type": "calc", + "extras": [ + "none" + ], + "flags": [ + "lines", + "markers", + "text" + ] + }, + "superclass": "FlaglistValidator" + }, + "scattercarpet.metasrc": { + "params": { + "plotly_name": "metasrc", + "parent_name": "scattercarpet", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattercarpet.meta": { + "params": { + "plotly_name": "meta", + "parent_name": "scattercarpet", + "array_ok": true, + "edit_type": "plot" + }, + "superclass": "AnyValidator" + }, + "scattercarpet.marker": { + "params": { + "plotly_name": "marker", + "parent_name": "scattercarpet", + "data_class_str": "Marker", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scattercarpet.marker.symbolsrc": { + "params": { + "plotly_name": "symbolsrc", + "parent_name": "scattercarpet.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattercarpet.marker.symbol": { + "params": { + "plotly_name": "symbol", + "parent_name": "scattercarpet.marker", + "array_ok": true, + "edit_type": "style", + "values": [ + 0, + "0", + "circle", + 100, + "100", + "circle-open", + 200, + "200", + "circle-dot", + 300, + "300", + "circle-open-dot", + 1, + "1", + "square", + 101, + "101", + "square-open", + 201, + "201", + "square-dot", + 301, + "301", + "square-open-dot", + 2, + "2", + "diamond", + 102, + "102", + "diamond-open", + 202, + "202", + "diamond-dot", + 302, + "302", + "diamond-open-dot", + 3, + "3", + "cross", + 103, + "103", + "cross-open", + 203, + "203", + "cross-dot", + 303, + "303", + "cross-open-dot", + 4, + "4", + "x", + 104, + "104", + "x-open", + 204, + "204", + "x-dot", + 304, + "304", + "x-open-dot", + 5, + "5", + "triangle-up", + 105, + "105", + "triangle-up-open", + 205, + "205", + "triangle-up-dot", + 305, + "305", + "triangle-up-open-dot", + 6, + "6", + "triangle-down", + 106, + "106", + "triangle-down-open", + 206, + "206", + "triangle-down-dot", + 306, + "306", + "triangle-down-open-dot", + 7, + "7", + "triangle-left", + 107, + "107", + "triangle-left-open", + 207, + "207", + "triangle-left-dot", + 307, + "307", + "triangle-left-open-dot", + 8, + "8", + "triangle-right", + 108, + "108", + "triangle-right-open", + 208, + "208", + "triangle-right-dot", + 308, + "308", + "triangle-right-open-dot", + 9, + "9", + "triangle-ne", + 109, + "109", + "triangle-ne-open", + 209, + "209", + "triangle-ne-dot", + 309, + "309", + "triangle-ne-open-dot", + 10, + "10", + "triangle-se", + 110, + "110", + "triangle-se-open", + 210, + "210", + "triangle-se-dot", + 310, + "310", + "triangle-se-open-dot", + 11, + "11", + "triangle-sw", + 111, + "111", + "triangle-sw-open", + 211, + "211", + "triangle-sw-dot", + 311, + "311", + "triangle-sw-open-dot", + 12, + "12", + "triangle-nw", + 112, + "112", + "triangle-nw-open", + 212, + "212", + "triangle-nw-dot", + 312, + "312", + "triangle-nw-open-dot", + 13, + "13", + "pentagon", + 113, + "113", + "pentagon-open", + 213, + "213", + "pentagon-dot", + 313, + "313", + "pentagon-open-dot", + 14, + "14", + "hexagon", + 114, + "114", + "hexagon-open", + 214, + "214", + "hexagon-dot", + 314, + "314", + "hexagon-open-dot", + 15, + "15", + "hexagon2", + 115, + "115", + "hexagon2-open", + 215, + "215", + "hexagon2-dot", + 315, + "315", + "hexagon2-open-dot", + 16, + "16", + "octagon", + 116, + "116", + "octagon-open", + 216, + "216", + "octagon-dot", + 316, + "316", + "octagon-open-dot", + 17, + "17", + "star", + 117, + "117", + "star-open", + 217, + "217", + "star-dot", + 317, + "317", + "star-open-dot", + 18, + "18", + "hexagram", + 118, + "118", + "hexagram-open", + 218, + "218", + "hexagram-dot", + 318, + "318", + "hexagram-open-dot", + 19, + "19", + "star-triangle-up", + 119, + "119", + "star-triangle-up-open", + 219, + "219", + "star-triangle-up-dot", + 319, + "319", + "star-triangle-up-open-dot", + 20, + "20", + "star-triangle-down", + 120, + "120", + "star-triangle-down-open", + 220, + "220", + "star-triangle-down-dot", + 320, + "320", + "star-triangle-down-open-dot", + 21, + "21", + "star-square", + 121, + "121", + "star-square-open", + 221, + "221", + "star-square-dot", + 321, + "321", + "star-square-open-dot", + 22, + "22", + "star-diamond", + 122, + "122", + "star-diamond-open", + 222, + "222", + "star-diamond-dot", + 322, + "322", + "star-diamond-open-dot", + 23, + "23", + "diamond-tall", + 123, + "123", + "diamond-tall-open", + 223, + "223", + "diamond-tall-dot", + 323, + "323", + "diamond-tall-open-dot", + 24, + "24", + "diamond-wide", + 124, + "124", + "diamond-wide-open", + 224, + "224", + "diamond-wide-dot", + 324, + "324", + "diamond-wide-open-dot", + 25, + "25", + "hourglass", + 125, + "125", + "hourglass-open", + 26, + "26", + "bowtie", + 126, + "126", + "bowtie-open", + 27, + "27", + "circle-cross", + 127, + "127", + "circle-cross-open", + 28, + "28", + "circle-x", + 128, + "128", + "circle-x-open", + 29, + "29", + "square-cross", + 129, + "129", + "square-cross-open", + 30, + "30", + "square-x", + 130, + "130", + "square-x-open", + 31, + "31", + "diamond-cross", + 131, + "131", + "diamond-cross-open", + 32, + "32", + "diamond-x", + 132, + "132", + "diamond-x-open", + 33, + "33", + "cross-thin", + 133, + "133", + "cross-thin-open", + 34, + "34", + "x-thin", + 134, + "134", + "x-thin-open", + 35, + "35", + "asterisk", + 135, + "135", + "asterisk-open", + 36, + "36", + "hash", + 136, + "136", + "hash-open", + 236, + "236", + "hash-dot", + 336, + "336", + "hash-open-dot", + 37, + "37", + "y-up", + 137, + "137", + "y-up-open", + 38, + "38", + "y-down", + 138, + "138", + "y-down-open", + 39, + "39", + "y-left", + 139, + "139", + "y-left-open", + 40, + "40", + "y-right", + 140, + "140", + "y-right-open", + 41, + "41", + "line-ew", + 141, + "141", + "line-ew-open", + 42, + "42", + "line-ns", + 142, + "142", + "line-ns-open", + 43, + "43", + "line-ne", + 143, + "143", + "line-ne-open", + 44, + "44", + "line-nw", + 144, + "144", + "line-nw-open", + 45, + "45", + "arrow-up", + 145, + "145", + "arrow-up-open", + 46, + "46", + "arrow-down", + 146, + "146", + "arrow-down-open", + 47, + "47", + "arrow-left", + 147, + "147", + "arrow-left-open", + 48, + "48", + "arrow-right", + 148, + "148", + "arrow-right-open", + 49, + "49", + "arrow-bar-up", + 149, + "149", + "arrow-bar-up-open", + 50, + "50", + "arrow-bar-down", + 150, + "150", + "arrow-bar-down-open", + 51, + "51", + "arrow-bar-left", + 151, + "151", + "arrow-bar-left-open", + 52, + "52", + "arrow-bar-right", + 152, + "152", + "arrow-bar-right-open", + 53, + "53", + "arrow", + 153, + "153", + "arrow-open", + 54, + "54", + "arrow-wide", + 154, + "154", + "arrow-wide-open" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scattercarpet.marker.standoffsrc": { + "params": { + "plotly_name": "standoffsrc", + "parent_name": "scattercarpet.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattercarpet.marker.standoff": { + "params": { + "plotly_name": "standoff", + "parent_name": "scattercarpet.marker", + "array_ok": true, + "edit_type": "plot", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattercarpet.marker.sizesrc": { + "params": { + "plotly_name": "sizesrc", + "parent_name": "scattercarpet.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattercarpet.marker.sizeref": { + "params": { + "plotly_name": "sizeref", + "parent_name": "scattercarpet.marker", + "edit_type": "calc" + }, + "superclass": "NumberValidator" + }, + "scattercarpet.marker.sizemode": { + "params": { + "plotly_name": "sizemode", + "parent_name": "scattercarpet.marker", + "edit_type": "calc", + "values": [ + "diameter", + "area" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scattercarpet.marker.sizemin": { + "params": { + "plotly_name": "sizemin", + "parent_name": "scattercarpet.marker", + "edit_type": "calc", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattercarpet.marker.size": { + "params": { + "plotly_name": "size", + "parent_name": "scattercarpet.marker", + "array_ok": true, + "edit_type": "calc", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattercarpet.marker.showscale": { + "params": { + "plotly_name": "showscale", + "parent_name": "scattercarpet.marker", + "edit_type": "calc" + }, + "superclass": "BooleanValidator" + }, + "scattercarpet.marker.reversescale": { + "params": { + "plotly_name": "reversescale", + "parent_name": "scattercarpet.marker", + "edit_type": "plot" + }, + "superclass": "BooleanValidator" + }, + "scattercarpet.marker.opacitysrc": { + "params": { + "plotly_name": "opacitysrc", + "parent_name": "scattercarpet.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattercarpet.marker.opacity": { + "params": { + "plotly_name": "opacity", + "parent_name": "scattercarpet.marker", + "array_ok": true, + "edit_type": "style", + "max": 1, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattercarpet.marker.maxdisplayed": { + "params": { + "plotly_name": "maxdisplayed", + "parent_name": "scattercarpet.marker", + "edit_type": "plot", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattercarpet.marker.line": { + "params": { + "plotly_name": "line", + "parent_name": "scattercarpet.marker", + "data_class_str": "Line", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scattercarpet.marker.line.widthsrc": { + "params": { + "plotly_name": "widthsrc", + "parent_name": "scattercarpet.marker.line", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattercarpet.marker.line.width": { + "params": { + "plotly_name": "width", + "parent_name": "scattercarpet.marker.line", + "array_ok": true, + "edit_type": "style", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scattercarpet.marker.line.reversescale": { + "params": { + "plotly_name": "reversescale", + "parent_name": "scattercarpet.marker.line", + "edit_type": "plot" + }, + "superclass": "BooleanValidator" + }, + "scattercarpet.marker.line.colorsrc": { + "params": { + "plotly_name": "colorsrc", + "parent_name": "scattercarpet.marker.line", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattercarpet.marker.line.colorscale": { + "params": { + "plotly_name": "colorscale", + "parent_name": "scattercarpet.marker.line", + "edit_type": "calc", + "implied_edits": { + "autocolorscale": false + } + }, + "superclass": "ColorscaleValidator" + }, + "scattercarpet.marker.line.coloraxis": { + "params": { + "plotly_name": "coloraxis", + "parent_name": "scattercarpet.marker.line", + "dflt": null, + "edit_type": "calc", + "regex": "/^coloraxis([2-9]|[1-9][0-9]+)?$/" + }, + "superclass": "SubplotidValidator" + }, + "scattercarpet.marker.line.color": { + "params": { + "plotly_name": "color", + "parent_name": "scattercarpet.marker.line", + "array_ok": true, + "edit_type": "style", + "colorscale_path": "scattercarpet.marker.line.colorscale" + }, + "superclass": "ColorValidator" + }, + "scattercarpet.marker.line.cmin": { + "params": { + "plotly_name": "cmin", + "parent_name": "scattercarpet.marker.line", + "edit_type": "plot", + "implied_edits": { + "cauto": false + } + }, + "superclass": "NumberValidator" + }, + "scattercarpet.marker.line.cmid": { + "params": { + "plotly_name": "cmid", + "parent_name": "scattercarpet.marker.line", + "edit_type": "calc", + "implied_edits": {} + }, + "superclass": "NumberValidator" + }, + "scattercarpet.marker.line.cmax": { + "params": { + "plotly_name": "cmax", + "parent_name": "scattercarpet.marker.line", + "edit_type": "plot", + "implied_edits": { + "cauto": false + } + }, + "superclass": "NumberValidator" + }, + "scattercarpet.marker.line.cauto": { + "params": { + "plotly_name": "cauto", + "parent_name": "scattercarpet.marker.line", + "edit_type": "calc", + "implied_edits": {} + }, + "superclass": "BooleanValidator" + }, + "scattercarpet.marker.line.autocolorscale": { + "params": { + "plotly_name": "autocolorscale", + "parent_name": "scattercarpet.marker.line", + "edit_type": "calc", + "implied_edits": {} + }, + "superclass": "BooleanValidator" + }, + "scattercarpet.marker.gradient": { + "params": { + "plotly_name": "gradient", + "parent_name": "scattercarpet.marker", + "data_class_str": "Gradient", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scattercarpet.marker.gradient.typesrc": { + "params": { + "plotly_name": "typesrc", + "parent_name": "scattercarpet.marker.gradient", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattercarpet.marker.gradient.type": { + "params": { + "plotly_name": "type", + "parent_name": "scattercarpet.marker.gradient", + "array_ok": true, + "edit_type": "calc", + "values": [ + "radial", + "horizontal", + "vertical", + "none" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scattercarpet.marker.gradient.colorsrc": { + "params": { + "plotly_name": "colorsrc", + "parent_name": "scattercarpet.marker.gradient", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattercarpet.marker.gradient.color": { + "params": { + "plotly_name": "color", + "parent_name": "scattercarpet.marker.gradient", + "array_ok": true, + "edit_type": "calc" + }, + "superclass": "ColorValidator" + }, + "scattercarpet.marker.colorsrc": { + "params": { + "plotly_name": "colorsrc", + "parent_name": "scattercarpet.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scattercarpet.marker.colorscale": { + "params": { + "plotly_name": "colorscale", + "parent_name": "scattercarpet.marker", + "edit_type": "calc", + "implied_edits": { + "autocolorscale": false + } + }, + "superclass": "ColorscaleValidator" + }, + "scattercarpet.marker.colorbar": { + "params": { + "plotly_name": "colorbar", + "parent_name": "scattercarpet.marker", + "data_class_str": "ColorBar", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scattercarpet.marker.colorbar.yref": { + "params": { + "plotly_name": "yref", + "parent_name": "scattercarpet.marker.colorbar", + "edit_type": "colorbars", + "values": [ + "container", + "paper" + ] + }, + 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+ }, + "superclass": "NumberValidator" + }, + "scatter.unselected.marker.color": { + "params": { + "plotly_name": "color", + "parent_name": "scatter.unselected.marker", + "edit_type": "style" + }, + "superclass": "ColorValidator" + }, + "scatter.uirevision": { + "params": { + "plotly_name": "uirevision", + "parent_name": "scatter", + "edit_type": "none" + }, + "superclass": "AnyValidator" + }, + "scatter.uid": { + "params": { + "plotly_name": "uid", + "parent_name": "scatter", + "anim": true, + "edit_type": "plot" + }, + "superclass": "StringValidator" + }, + "scatter.texttemplatesrc": { + "params": { + "plotly_name": "texttemplatesrc", + "parent_name": "scatter", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.texttemplatefallback": { + "params": { + "plotly_name": "texttemplatefallback", + "parent_name": "scatter", + "edit_type": "calc" + }, + "superclass": "AnyValidator" + }, + "scatter.texttemplate": { + "params": { + "plotly_name": "texttemplate", + "parent_name": "scatter", + "array_ok": true, + "edit_type": "calc" + }, + "superclass": "StringValidator" + }, + "scatter.textsrc": { + "params": { + "plotly_name": "textsrc", + "parent_name": "scatter", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.textpositionsrc": { + "params": { + "plotly_name": "textpositionsrc", + "parent_name": "scatter", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.textposition": { + "params": { + "plotly_name": "textposition", + "parent_name": "scatter", + "array_ok": true, + "edit_type": "calc", + "values": [ + "top left", + "top center", + "top right", + "middle left", + "middle center", + "middle right", + "bottom left", + "bottom center", + "bottom right" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scatter.textfont": { + "params": { + "plotly_name": "textfont", + "parent_name": "scatter", + "data_class_str": "Textfont", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatter.textfont.weightsrc": { + "params": { + "plotly_name": "weightsrc", + "parent_name": "scatter.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.textfont.weight": { + "params": { + "plotly_name": "weight", + "parent_name": "scatter.textfont", + "array_ok": true, + "edit_type": "calc", + "extras": [ + "normal", + "bold" + ], + "max": 1000, + "min": 1 + }, + "superclass": "IntegerValidator" + }, + "scatter.textfont.variantsrc": { + "params": { + "plotly_name": "variantsrc", + "parent_name": "scatter.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.textfont.variant": { + "params": { + "plotly_name": "variant", + "parent_name": "scatter.textfont", + "array_ok": true, + "edit_type": "calc", + "values": [ + "normal", + "small-caps", + "all-small-caps", + "all-petite-caps", + "petite-caps", + "unicase" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scatter.textfont.textcasesrc": { + "params": { + "plotly_name": "textcasesrc", + "parent_name": "scatter.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.textfont.textcase": { + "params": { + "plotly_name": "textcase", + "parent_name": "scatter.textfont", + "array_ok": true, + "edit_type": "calc", + "values": [ + "normal", + "word caps", + "upper", + "lower" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scatter.textfont.stylesrc": { + "params": { + "plotly_name": "stylesrc", + "parent_name": "scatter.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.textfont.style": { + "params": { + "plotly_name": "style", + "parent_name": "scatter.textfont", + "array_ok": true, + "edit_type": "calc", + "values": [ + "normal", + "italic" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scatter.textfont.sizesrc": { + "params": { + "plotly_name": "sizesrc", + "parent_name": "scatter.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.textfont.size": { + "params": { + "plotly_name": "size", + "parent_name": "scatter.textfont", + "array_ok": true, + "edit_type": "calc", + "min": 1 + }, + "superclass": "NumberValidator" + }, + "scatter.textfont.shadowsrc": { + "params": { + "plotly_name": "shadowsrc", + "parent_name": "scatter.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.textfont.shadow": { + "params": { + "plotly_name": "shadow", + "parent_name": "scatter.textfont", + "array_ok": true, + "edit_type": "calc" + }, + "superclass": "StringValidator" + }, + "scatter.textfont.linepositionsrc": { + "params": { + "plotly_name": "linepositionsrc", + "parent_name": "scatter.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.textfont.lineposition": { + "params": { + "plotly_name": "lineposition", + "parent_name": "scatter.textfont", + "array_ok": true, + "edit_type": "calc", + "extras": [ + "none" + ], + "flags": [ + "under", + "over", + "through" + ] + }, + "superclass": "FlaglistValidator" + }, + "scatter.textfont.familysrc": { + "params": { + "plotly_name": "familysrc", + "parent_name": "scatter.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.textfont.family": { + "params": { + "plotly_name": "family", + "parent_name": "scatter.textfont", + "array_ok": true, + "edit_type": "calc", + "no_blank": true, + "strict": true + }, + "superclass": "StringValidator" + }, + "scatter.textfont.colorsrc": { + "params": { + "plotly_name": "colorsrc", + "parent_name": "scatter.textfont", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.textfont.color": { + "params": { + "plotly_name": "color", + "parent_name": "scatter.textfont", + "array_ok": true, + "edit_type": "style" + }, + "superclass": "ColorValidator" + }, + "scatter.text": { + "params": { + "plotly_name": "text", + "parent_name": "scatter", + "array_ok": true, + "edit_type": "calc" + }, + "superclass": "StringValidator" + }, + "scatter.stream": { + "params": { + "plotly_name": "stream", + "parent_name": "scatter", + "data_class_str": "Stream", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatter.stream.token": { + "params": { + "plotly_name": "token", + "parent_name": "scatter.stream", + "edit_type": "calc", + "no_blank": true, + "strict": true + }, + "superclass": "StringValidator" + }, + "scatter.stream.maxpoints": { + "params": { + "plotly_name": "maxpoints", + "parent_name": "scatter.stream", + "edit_type": "calc", + "max": 10000, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatter.stackgroup": { + "params": { + "plotly_name": "stackgroup", + "parent_name": "scatter", + "edit_type": "calc" + }, + "superclass": "StringValidator" + }, + "scatter.stackgaps": { + "params": { + "plotly_name": "stackgaps", + "parent_name": "scatter", + "edit_type": "calc", + "values": [ + "infer zero", + "interpolate" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scatter.showlegend": { + "params": { + "plotly_name": "showlegend", + "parent_name": "scatter", + "edit_type": "style" + }, + "superclass": "BooleanValidator" + }, + "scatter.selectedpoints": { + "params": { + "plotly_name": "selectedpoints", + "parent_name": "scatter", + "edit_type": "calc" + }, + "superclass": "AnyValidator" + }, + "scatter.selected": { + "params": { + "plotly_name": "selected", + "parent_name": "scatter", + "data_class_str": "Selected", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatter.selected.textfont": { + "params": { + "plotly_name": "textfont", + "parent_name": "scatter.selected", + "data_class_str": "Textfont", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatter.selected.textfont.color": { + "params": { + "plotly_name": "color", + "parent_name": "scatter.selected.textfont", + "edit_type": "style" + }, + "superclass": "ColorValidator" + }, + "scatter.selected.marker": { + "params": { + "plotly_name": "marker", + "parent_name": "scatter.selected", + "data_class_str": "Marker", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatter.selected.marker.size": { + "params": { + "plotly_name": "size", + "parent_name": "scatter.selected.marker", + "edit_type": "style", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatter.selected.marker.opacity": { + "params": { + "plotly_name": "opacity", + "parent_name": "scatter.selected.marker", + "edit_type": "style", + "max": 1, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatter.selected.marker.color": { + "params": { + "plotly_name": "color", + "parent_name": "scatter.selected.marker", + "edit_type": "style" + }, + "superclass": "ColorValidator" + }, + "scatter.orientation": { + "params": { + "plotly_name": "orientation", + "parent_name": "scatter", + "edit_type": "calc", + "values": [ + "v", + "h" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scatter.opacity": { + "params": { + "plotly_name": "opacity", + "parent_name": "scatter", + "edit_type": "style", + "max": 1, + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatter.offsetgroup": { + "params": { + "plotly_name": "offsetgroup", + "parent_name": "scatter", + "edit_type": "calc" + }, + "superclass": "StringValidator" + }, + "scatter.name": { + "params": { + "plotly_name": "name", + "parent_name": "scatter", + "edit_type": "style" + }, + "superclass": "StringValidator" + }, + "scatter.mode": { + "params": { + "plotly_name": "mode", + "parent_name": "scatter", + "edit_type": "calc", + "extras": [ + "none" + ], + "flags": [ + "lines", + "markers", + "text" + ] + }, + "superclass": "FlaglistValidator" + }, + "scatter.metasrc": { + "params": { + "plotly_name": "metasrc", + "parent_name": "scatter", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.meta": { + "params": { + "plotly_name": "meta", + "parent_name": "scatter", + "array_ok": true, + "edit_type": "plot" + }, + "superclass": "AnyValidator" + }, + "scatter.marker": { + "params": { + "plotly_name": "marker", + "parent_name": "scatter", + "data_class_str": "Marker", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "scatter.marker.symbolsrc": { + "params": { + "plotly_name": "symbolsrc", + "parent_name": "scatter.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.marker.symbol": { + "params": { + "plotly_name": "symbol", + "parent_name": "scatter.marker", + "array_ok": true, + "edit_type": "style", + "values": [ + 0, + "0", + "circle", + 100, + "100", + "circle-open", + 200, + "200", + "circle-dot", + 300, + "300", + "circle-open-dot", + 1, + "1", + "square", + 101, + "101", + "square-open", + 201, + "201", + "square-dot", + 301, + "301", + "square-open-dot", + 2, + "2", + "diamond", + 102, + "102", + "diamond-open", + 202, + "202", + "diamond-dot", + 302, + "302", + "diamond-open-dot", + 3, + "3", + "cross", + 103, + "103", + "cross-open", + 203, + "203", + "cross-dot", + 303, + "303", + "cross-open-dot", + 4, + "4", + "x", + 104, + "104", + "x-open", + 204, + "204", + "x-dot", + 304, + "304", + "x-open-dot", + 5, + "5", + "triangle-up", + 105, + "105", + "triangle-up-open", + 205, + "205", + "triangle-up-dot", + 305, + "305", + "triangle-up-open-dot", + 6, + "6", + "triangle-down", + 106, + "106", + "triangle-down-open", + 206, + "206", + "triangle-down-dot", + 306, + "306", + "triangle-down-open-dot", + 7, + "7", + "triangle-left", + 107, + "107", + "triangle-left-open", + 207, + "207", + "triangle-left-dot", + 307, + "307", + "triangle-left-open-dot", + 8, + "8", + "triangle-right", + 108, + "108", + "triangle-right-open", + 208, + "208", + "triangle-right-dot", + 308, + "308", + "triangle-right-open-dot", + 9, + "9", + "triangle-ne", + 109, + "109", + "triangle-ne-open", + 209, + "209", + "triangle-ne-dot", + 309, + "309", + "triangle-ne-open-dot", + 10, + "10", + "triangle-se", + 110, + "110", + "triangle-se-open", + 210, + "210", + "triangle-se-dot", + 310, + "310", + "triangle-se-open-dot", + 11, + "11", + "triangle-sw", + 111, + "111", + "triangle-sw-open", + 211, + "211", + "triangle-sw-dot", + 311, + "311", + "triangle-sw-open-dot", + 12, + "12", + "triangle-nw", + 112, + "112", + "triangle-nw-open", + 212, + "212", + "triangle-nw-dot", + 312, + "312", + "triangle-nw-open-dot", + 13, + "13", + "pentagon", + 113, + "113", + "pentagon-open", + 213, + "213", + "pentagon-dot", + 313, + "313", + "pentagon-open-dot", + 14, + "14", + "hexagon", + 114, + "114", + "hexagon-open", + 214, + "214", + "hexagon-dot", + 314, + "314", + "hexagon-open-dot", + 15, + "15", + "hexagon2", + 115, + "115", + "hexagon2-open", + 215, + "215", + "hexagon2-dot", + 315, + "315", + "hexagon2-open-dot", + 16, + "16", + "octagon", + 116, + "116", + "octagon-open", + 216, + "216", + "octagon-dot", + 316, + "316", + "octagon-open-dot", + 17, + "17", + "star", + 117, + "117", + "star-open", + 217, + "217", + "star-dot", + 317, + "317", + "star-open-dot", + 18, + "18", + "hexagram", + 118, + "118", + "hexagram-open", + 218, + "218", + "hexagram-dot", + 318, + "318", + "hexagram-open-dot", + 19, + "19", + "star-triangle-up", + 119, + "119", + "star-triangle-up-open", + 219, + "219", + "star-triangle-up-dot", + 319, + "319", + "star-triangle-up-open-dot", + 20, + "20", + "star-triangle-down", + 120, + "120", + "star-triangle-down-open", + 220, + "220", + "star-triangle-down-dot", + 320, + "320", + "star-triangle-down-open-dot", + 21, + "21", + "star-square", + 121, + "121", + "star-square-open", + 221, + "221", + "star-square-dot", + 321, + "321", + "star-square-open-dot", + 22, + "22", + "star-diamond", + 122, + "122", + "star-diamond-open", + 222, + "222", + "star-diamond-dot", + 322, + "322", + "star-diamond-open-dot", + 23, + "23", + "diamond-tall", + 123, + "123", + "diamond-tall-open", + 223, + "223", + "diamond-tall-dot", + 323, + "323", + "diamond-tall-open-dot", + 24, + "24", + "diamond-wide", + 124, + "124", + "diamond-wide-open", + 224, + "224", + "diamond-wide-dot", + 324, + "324", + "diamond-wide-open-dot", + 25, + "25", + "hourglass", + 125, + "125", + "hourglass-open", + 26, + "26", + "bowtie", + 126, + "126", + "bowtie-open", + 27, + "27", + "circle-cross", + 127, + "127", + "circle-cross-open", + 28, + "28", + "circle-x", + 128, + "128", + "circle-x-open", + 29, + "29", + "square-cross", + 129, + "129", + "square-cross-open", + 30, + "30", + "square-x", + 130, + "130", + "square-x-open", + 31, + "31", + "diamond-cross", + 131, + "131", + "diamond-cross-open", + 32, + "32", + "diamond-x", + 132, + "132", + "diamond-x-open", + 33, + "33", + "cross-thin", + 133, + "133", + "cross-thin-open", + 34, + "34", + "x-thin", + 134, + "134", + "x-thin-open", + 35, + "35", + "asterisk", + 135, + "135", + "asterisk-open", + 36, + "36", + "hash", + 136, + "136", + "hash-open", + 236, + "236", + "hash-dot", + 336, + "336", + "hash-open-dot", + 37, + "37", + "y-up", + 137, + "137", + "y-up-open", + 38, + "38", + "y-down", + 138, + "138", + "y-down-open", + 39, + "39", + "y-left", + 139, + "139", + "y-left-open", + 40, + "40", + "y-right", + 140, + "140", + "y-right-open", + 41, + "41", + "line-ew", + 141, + "141", + "line-ew-open", + 42, + "42", + "line-ns", + 142, + "142", + "line-ns-open", + 43, + "43", + "line-ne", + 143, + "143", + "line-ne-open", + 44, + "44", + "line-nw", + 144, + "144", + "line-nw-open", + 45, + "45", + "arrow-up", + 145, + "145", + "arrow-up-open", + 46, + "46", + "arrow-down", + 146, + "146", + "arrow-down-open", + 47, + "47", + "arrow-left", + 147, + "147", + "arrow-left-open", + 48, + "48", + "arrow-right", + 148, + "148", + "arrow-right-open", + 49, + "49", + "arrow-bar-up", + 149, + "149", + "arrow-bar-up-open", + 50, + "50", + "arrow-bar-down", + 150, + "150", + "arrow-bar-down-open", + 51, + "51", + "arrow-bar-left", + 151, + "151", + "arrow-bar-left-open", + 52, + "52", + "arrow-bar-right", + 152, + "152", + "arrow-bar-right-open", + 53, + "53", + "arrow", + 153, + "153", + "arrow-open", + 54, + "54", + "arrow-wide", + 154, + "154", + "arrow-wide-open" + ] + }, + "superclass": "EnumeratedValidator" + }, + "scatter.marker.standoffsrc": { + "params": { + "plotly_name": "standoffsrc", + "parent_name": "scatter.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.marker.standoff": { + "params": { + "plotly_name": "standoff", + "parent_name": "scatter.marker", + "anim": true, + "array_ok": true, + "edit_type": "plot", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "scatter.marker.sizesrc": { + "params": { + "plotly_name": "sizesrc", + "parent_name": "scatter.marker", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "scatter.marker.sizeref": { + "params": { + "plotly_name": "sizeref", + "parent_name": "scatter.marker", + "edit_type": "calc" + }, + "superclass": "NumberValidator" + }, + "scatter.marker.sizemode": { + "params": { + "plotly_name": "sizemode", + "parent_name": 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"diamond-tall-open-dot", + 24, + "24", + "diamond-wide", + 124, + "124", + "diamond-wide-open", + 224, + "224", + "diamond-wide-dot", + 324, + "324", + "diamond-wide-open-dot", + 25, + "25", + "hourglass", + 125, + "125", + "hourglass-open", + 26, + "26", + "bowtie", + 126, + "126", + "bowtie-open", + 27, + "27", + "circle-cross", + 127, + "127", + "circle-cross-open", + 28, + "28", + "circle-x", + 128, + "128", + "circle-x-open", + 29, + "29", + "square-cross", + 129, + "129", + "square-cross-open", + 30, + "30", + "square-x", + 130, + "130", + "square-x-open", + 31, + "31", + "diamond-cross", + 131, + "131", + "diamond-cross-open", + 32, + "32", + "diamond-x", + 132, + "132", + "diamond-x-open", + 33, + "33", + "cross-thin", + 133, + "133", + "cross-thin-open", + 34, + "34", + "x-thin", + 134, + "134", + "x-thin-open", + 35, + "35", + "asterisk", + 135, + "135", + "asterisk-open", + 36, + "36", + "hash", + 136, + "136", + "hash-open", + 236, + "236", + "hash-dot", + 336, + "336", + "hash-open-dot", + 37, + "37", + "y-up", + 137, + "137", + "y-up-open", + 38, + "38", + "y-down", + 138, + "138", + "y-down-open", + 39, + "39", + "y-left", + 139, + "139", + "y-left-open", + 40, + "40", + "y-right", + 140, + "140", + "y-right-open", + 41, + "41", + "line-ew", + 141, + "141", + "line-ew-open", + 42, + "42", + "line-ns", + 142, + "142", + "line-ns-open", + 43, + "43", + "line-ne", + 143, + "143", + "line-ne-open", + 44, + "44", + "line-nw", + 144, + "144", + "line-nw-open", + 45, + "45", + "arrow-up", + 145, + "145", + "arrow-up-open", + 46, + "46", + "arrow-down", + 146, + "146", + "arrow-down-open", + 47, + "47", + "arrow-left", + 147, + "147", + "arrow-left-open", + 48, + "48", + "arrow-right", + 148, + "148", + "arrow-right-open", + 49, + "49", + "arrow-bar-up", + 149, + "149", + "arrow-bar-up-open", + 50, + "50", + "arrow-bar-down", + 150, + "150", + "arrow-bar-down-open", + 51, + "51", + "arrow-bar-left", + 151, + "151", + "arrow-bar-left-open", + 52, + "52", + 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"bar.hoverlabel.font.lineposition": { + "params": { + "plotly_name": "lineposition", + "parent_name": "bar.hoverlabel.font", + "array_ok": true, + "edit_type": "none", + "extras": [ + "none" + ], + "flags": [ + "under", + "over", + "through" + ] + }, + "superclass": "FlaglistValidator" + }, + "bar.hoverlabel.font.familysrc": { + "params": { + "plotly_name": "familysrc", + "parent_name": "bar.hoverlabel.font", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "bar.hoverlabel.font.family": { + "params": { + "plotly_name": "family", + "parent_name": "bar.hoverlabel.font", + "array_ok": true, + "edit_type": "none", + "no_blank": true, + "strict": true + }, + "superclass": "StringValidator" + }, + "bar.hoverlabel.font.colorsrc": { + "params": { + "plotly_name": "colorsrc", + "parent_name": "bar.hoverlabel.font", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "bar.hoverlabel.font.color": { + "params": { + "plotly_name": "color", + "parent_name": "bar.hoverlabel.font", + "array_ok": true, + "edit_type": "none" + }, + "superclass": "ColorValidator" + }, + "bar.hoverlabel.bordercolorsrc": { + "params": { + "plotly_name": "bordercolorsrc", + "parent_name": "bar.hoverlabel", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "bar.hoverlabel.bordercolor": { + "params": { + "plotly_name": "bordercolor", + "parent_name": "bar.hoverlabel", + "array_ok": true, + "edit_type": "none" + }, + "superclass": "ColorValidator" + }, + "bar.hoverlabel.bgcolorsrc": { + "params": { + "plotly_name": "bgcolorsrc", + "parent_name": "bar.hoverlabel", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "bar.hoverlabel.bgcolor": { + "params": { + "plotly_name": "bgcolor", + "parent_name": "bar.hoverlabel", + "array_ok": true, + "edit_type": "none" + }, + "superclass": "ColorValidator" + }, + "bar.hoverlabel.alignsrc": { + "params": { + "plotly_name": "alignsrc", + "parent_name": "bar.hoverlabel", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "bar.hoverlabel.align": { + "params": { + "plotly_name": "align", + "parent_name": "bar.hoverlabel", + "array_ok": true, + "edit_type": "none", + "values": [ + "left", + "right", + "auto" + ] + }, + "superclass": "EnumeratedValidator" + }, + "bar.hoverinfosrc": { + "params": { + "plotly_name": "hoverinfosrc", + "parent_name": "bar", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "bar.hoverinfo": { + "params": { + "plotly_name": "hoverinfo", + "parent_name": "bar", + "array_ok": true, + "edit_type": "none", + "extras": [ + "all", + "none", + "skip" + ], + "flags": [ + "x", + "y", + "z", + "text", + "name" + ] + }, + "superclass": "FlaglistValidator" + }, + "bar.error_y": { + "params": { + "plotly_name": "error_y", + "parent_name": "bar", + "data_class_str": "ErrorY", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "bar.error_y.width": { + "params": { + "plotly_name": "width", + "parent_name": "bar.error_y", + "edit_type": "plot", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "bar.error_y.visible": { + "params": { + "plotly_name": "visible", + "parent_name": "bar.error_y", + "edit_type": "calc" + }, + "superclass": "BooleanValidator" + }, + "bar.error_y.valueminus": { + "params": { + "plotly_name": "valueminus", + "parent_name": "bar.error_y", + "edit_type": "calc", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "bar.error_y.value": { + "params": { + "plotly_name": "value", + "parent_name": "bar.error_y", + "edit_type": "calc", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "bar.error_y.type": { + "params": { + "plotly_name": "type", + "parent_name": "bar.error_y", + "edit_type": "calc", + "values": [ + "percent", + "constant", + "sqrt", + "data" + ] + }, + "superclass": "EnumeratedValidator" + }, + "bar.error_y.tracerefminus": { + "params": { + "plotly_name": "tracerefminus", + "parent_name": "bar.error_y", + "edit_type": "style", + "min": 0 + }, + "superclass": "IntegerValidator" + }, + "bar.error_y.traceref": { + "params": { + "plotly_name": "traceref", + "parent_name": "bar.error_y", + "edit_type": "style", + "min": 0 + }, + "superclass": "IntegerValidator" + }, + "bar.error_y.thickness": { + "params": { + "plotly_name": "thickness", + "parent_name": "bar.error_y", + "edit_type": "style", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "bar.error_y.symmetric": { + "params": { + "plotly_name": "symmetric", + "parent_name": "bar.error_y", + "edit_type": "calc" + }, + "superclass": "BooleanValidator" + }, + "bar.error_y.color": { + "params": { + "plotly_name": "color", + "parent_name": "bar.error_y", + "edit_type": "style" + }, + "superclass": "ColorValidator" + }, + "bar.error_y.arraysrc": { + "params": { + "plotly_name": "arraysrc", + "parent_name": "bar.error_y", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "bar.error_y.arrayminussrc": { + "params": { + "plotly_name": "arrayminussrc", + "parent_name": "bar.error_y", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "bar.error_y.arrayminus": { + "params": { + "plotly_name": "arrayminus", + "parent_name": "bar.error_y", + "edit_type": "calc" + }, + "superclass": "DataArrayValidator" + }, + "bar.error_y.array": { + "params": { + "plotly_name": "array", + "parent_name": "bar.error_y", + "edit_type": "calc" + }, + "superclass": "DataArrayValidator" + }, + "bar.error_x": { + "params": { + "plotly_name": "error_x", + "parent_name": "bar", + "data_class_str": "ErrorX", + "data_docs": "\n" + }, + "superclass": "CompoundValidator" + }, + "bar.error_x.width": { + "params": { + "plotly_name": "width", + "parent_name": "bar.error_x", + "edit_type": "plot", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "bar.error_x.visible": { + "params": { + "plotly_name": "visible", + "parent_name": "bar.error_x", + "edit_type": "calc" + }, + "superclass": "BooleanValidator" + }, + "bar.error_x.valueminus": { + "params": { + "plotly_name": "valueminus", + "parent_name": "bar.error_x", + "edit_type": "calc", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "bar.error_x.value": { + "params": { + "plotly_name": "value", + "parent_name": "bar.error_x", + "edit_type": "calc", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "bar.error_x.type": { + "params": { + "plotly_name": "type", + "parent_name": "bar.error_x", + "edit_type": "calc", + "values": [ + "percent", + "constant", + "sqrt", + "data" + ] + }, + "superclass": "EnumeratedValidator" + }, + "bar.error_x.tracerefminus": { + "params": { + "plotly_name": "tracerefminus", + "parent_name": "bar.error_x", + "edit_type": "style", + "min": 0 + }, + "superclass": "IntegerValidator" + }, + "bar.error_x.traceref": { + "params": { + "plotly_name": "traceref", + "parent_name": "bar.error_x", + "edit_type": "style", + "min": 0 + }, + "superclass": "IntegerValidator" + }, + "bar.error_x.thickness": { + "params": { + "plotly_name": "thickness", + "parent_name": "bar.error_x", + "edit_type": "style", + "min": 0 + }, + "superclass": "NumberValidator" + }, + "bar.error_x.symmetric": { + "params": { + "plotly_name": "symmetric", + "parent_name": "bar.error_x", + "edit_type": "calc" + }, + "superclass": "BooleanValidator" + }, + "bar.error_x.copy_ystyle": { + "params": { + "plotly_name": "copy_ystyle", + "parent_name": "bar.error_x", + "edit_type": "plot" + }, + "superclass": "BooleanValidator" + }, + "bar.error_x.color": { + "params": { + "plotly_name": "color", + "parent_name": "bar.error_x", + "edit_type": "style" + }, + "superclass": "ColorValidator" + }, + "bar.error_x.arraysrc": { + "params": { + "plotly_name": "arraysrc", + "parent_name": "bar.error_x", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "bar.error_x.arrayminussrc": { + "params": { + "plotly_name": "arrayminussrc", + "parent_name": "bar.error_x", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "bar.error_x.arrayminus": { + "params": { + "plotly_name": "arrayminus", + "parent_name": "bar.error_x", + "edit_type": "calc" + }, + "superclass": "DataArrayValidator" + }, + "bar.error_x.array": { + "params": { + "plotly_name": "array", + "parent_name": "bar.error_x", + "edit_type": "calc" + }, + "superclass": "DataArrayValidator" + }, + "bar.dy": { + "params": { + "plotly_name": "dy", + "parent_name": "bar", + "anim": true, + "edit_type": "calc" + }, + "superclass": "NumberValidator" + }, + "bar.dx": { + "params": { + "plotly_name": "dx", + "parent_name": "bar", + "anim": true, + "edit_type": "calc" + }, + "superclass": "NumberValidator" + }, + "bar.customdatasrc": { + "params": { + "plotly_name": "customdatasrc", + "parent_name": "bar", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "bar.customdata": { + "params": { + "plotly_name": "customdata", + "parent_name": "bar", + "edit_type": "calc" + }, + "superclass": "DataArrayValidator" + }, + "bar.constraintext": { + "params": { + "plotly_name": "constraintext", + "parent_name": "bar", + "edit_type": "calc", + "values": [ + "inside", + "outside", + "both", + "none" + ] + }, + "superclass": "EnumeratedValidator" + }, + "bar.cliponaxis": { + "params": { + "plotly_name": "cliponaxis", + "parent_name": "bar", + "edit_type": "plot" + }, + "superclass": "BooleanValidator" + }, + "bar.basesrc": { + "params": { + "plotly_name": "basesrc", + "parent_name": "bar", + "edit_type": "none" + }, + "superclass": "SrcValidator" + }, + "bar.base": { + "params": { + "plotly_name": "base", + "parent_name": "bar", + "array_ok": true, + "edit_type": "calc" + }, + "superclass": "AnyValidator" + }, + "bar.alignmentgroup": { + "params": { + "plotly_name": "alignmentgroup", + "parent_name": "bar", + "edit_type": "calc" + }, + "superclass": "StringValidator" + }, + "frames": { + "params": { + "plotly_name": "frames", + "parent_name": "", + "data_class_str": "Frame", + "data_docs": "\n" + }, + "superclass": "CompoundArrayValidator" + }, + "frame.traces": { + "params": { + "plotly_name": "traces", + "parent_name": "frame" + }, + "superclass": "AnyValidator" + }, + "frame.name": { + "params": { + "plotly_name": "name", + "parent_name": "frame" + }, + "superclass": "StringValidator" + }, + "frame.layout": { + "params": { + "plotly_name": "layout", + "parent_name": "frame" + }, + "superclass": "LayoutValidator" + }, + "frame.group": { + "params": { + "plotly_name": "group", + "parent_name": "frame" + }, + "superclass": "StringValidator" + }, + "frame.data": { + "params": { + "plotly_name": "data", + "parent_name": "frame" + }, + "superclass": "DataValidator" + }, + "frame.baseframe": { + "params": { + "plotly_name": "baseframe", + "parent_name": "frame" + }, + "superclass": "StringValidator" + }, + "data": { + "params": { + "class_strs_map": { + "bar": "Bar", + "barpolar": "Barpolar", + "box": "Box", + "candlestick": "Candlestick", + "carpet": "Carpet", + "choropleth": "Choropleth", + "choroplethmap": "Choroplethmap", + "choroplethmapbox": "Choroplethmapbox", + "cone": "Cone", + "contour": "Contour", + "contourcarpet": "Contourcarpet", + "densitymap": "Densitymap", + "densitymapbox": "Densitymapbox", + "funnel": "Funnel", + "funnelarea": "Funnelarea", + "heatmap": "Heatmap", + "histogram": "Histogram", + "histogram2d": "Histogram2d", + "histogram2dcontour": "Histogram2dContour", + "icicle": "Icicle", + "image": "Image", + "indicator": "Indicator", + "isosurface": "Isosurface", + "mesh3d": "Mesh3d", + "ohlc": "Ohlc", + "parcats": "Parcats", + "parcoords": "Parcoords", + "pie": "Pie", + "sankey": "Sankey", + "scatter": "Scatter", + "scatter3d": "Scatter3d", + "scattercarpet": "Scattercarpet", + "scattergeo": "Scattergeo", + "scattergl": "Scattergl", + "scattermap": "Scattermap", + "scattermapbox": "Scattermapbox", + "scatterpolar": "Scatterpolar", + "scatterpolargl": "Scatterpolargl", + "scattersmith": "Scattersmith", + "scatterternary": "Scatterternary", + "splom": "Splom", + "streamtube": "Streamtube", + "sunburst": "Sunburst", + "surface": "Surface", + "table": "Table", + "treemap": "Treemap", + "violin": "Violin", + "volume": "Volume", + "waterfall": "Waterfall" + }, + "plotly_name": "data", + "parent_name": "" + }, + "superclass": "BaseDataValidator" + } +} \ No newline at end of file